2022/09/07 15:44:32 - 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: 1332582900 GPU 0,1,2,3: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/cache/share/cuda-11.1 NVCC: Cuda compilation tools, release 11.1, V11.1.74 GCC: gcc (GCC) 5.4.0 PyTorch: 1.11.0 PyTorch compiling details: PyTorch built with: - GCC 7.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.2 Product Build 20200624 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.3 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-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;-gencode;arch=compute_37,code=compute_37 - CuDNN 8.2 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-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=1.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, TorchVision: 0.12.0 OpenCV: 4.5.5 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 ------------------------------------------------------------ 2022/09/07 15:44:32 - mmengine - INFO - Config: model = dict( type='Recognizer2D', data_preprocessor=dict( type='ActionDataPreprocessor', mean=[123.675, 116.28, 103.5], std=[58.395, 57.12, 57.375], format_shape='NCHW'), backbone=dict( type='TANet', pretrained='torchvision://resnet50', depth=50, num_segments=16, tam_cfg=None), cls_head=dict( type='TSMHead', num_classes=174, in_channels=2048, spatial_type='avg', consensus=dict(type='AvgConsensus', dim=1), dropout_ratio=0.6, init_std=0.001, average_clips='prob', num_segments=16)) 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', max_keep_ckpts=3), sampler_seed=dict(type='DistSamplerSeedHook')) env_cfg = dict( cudnn_benchmark=False, mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), dist_cfg=dict(backend='nccl')) log_processor = dict(type='LogProcessor', window_size=20, by_epoch=True) vis_backends = [dict(type='LocalVisBackend')] visualizer = dict( type='ActionVisualizer', vis_backends=[dict(type='LocalVisBackend')]) log_level = 'INFO' load_from = None resume = False train_cfg = dict( type='EpochBasedTrainLoop', max_epochs=50, val_begin=1, val_interval=1) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') param_scheduler = [ dict( type='MultiStepLR', begin=0, end=50, by_epoch=True, milestones=[30, 40, 45], gamma=0.1) ] optim_wrapper = dict( constructor='TSMOptimWrapperConstructor', paramwise_cfg=dict(fc_lr5=True), optimizer=dict(type='SGD', lr=0.0075, momentum=0.9, weight_decay=0.001), clip_grad=dict(max_norm=20, norm_type=2)) file_client_args = dict( io_backend='petrel', path_mapping=dict( {'data/sthv1': 's204:s3://openmmlab/datasets/action/sthv1'})) dataset_type = 'RawframeDataset' data_root = 'data/sthv1/rawframes' data_root_val = 'data/sthv1/rawframes' ann_file_train = 'data/sthv1/sthv1_train_list_rawframes.txt' ann_file_val = 'data/sthv1/sthv1_val_list_rawframes.txt' ann_file_test = 'data/sthv1/sthv1_val_list_rawframes.txt' sthv1_flip_label_map = dict({2: 4, 4: 2, 30: 41, 41: 30, 52: 66, 66: 52}) train_pipeline = [ dict(type='SampleFrames', clip_len=1, frame_interval=1, num_clips=16), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict( {'data/sthv1': 's204:s3://openmmlab/datasets/action/sthv1'})), 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, num_fixed_crops=13), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict( type='Flip', flip_ratio=0.5, flip_label_map=dict({ 2: 4, 4: 2, 30: 41, 41: 30, 52: 66, 66: 52 })), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ] val_pipeline = [ dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=16, test_mode=True), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict( {'data/sthv1': 's204:s3://openmmlab/datasets/action/sthv1'})), 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='SampleFrames', clip_len=1, frame_interval=1, num_clips=16, twice_sample=True, test_mode=True), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict( {'data/sthv1': 's204:s3://openmmlab/datasets/action/sthv1'})), 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=6, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='RawframeDataset', ann_file='data/sthv1/sthv1_train_list_rawframes.txt', data_prefix=dict(img='data/sthv1/rawframes'), filename_tmpl='{:05}.jpg', pipeline=[ dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=16), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict({ 'data/sthv1': 's204:s3://openmmlab/datasets/action/sthv1' })), 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, num_fixed_crops=13), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict( type='Flip', flip_ratio=0.5, flip_label_map=dict({ 2: 4, 4: 2, 30: 41, 41: 30, 52: 66, 66: 52 })), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ])) val_dataloader = dict( batch_size=6, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='RawframeDataset', ann_file='data/sthv1/sthv1_val_list_rawframes.txt', data_prefix=dict(img='data/sthv1/rawframes'), filename_tmpl='{:05}.jpg', pipeline=[ dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=16, test_mode=True), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict({ 'data/sthv1': 's204:s3://openmmlab/datasets/action/sthv1' })), 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='RawframeDataset', ann_file='data/sthv1/sthv1_val_list_rawframes.txt', data_prefix=dict(img='data/sthv1/rawframes'), filename_tmpl='{:05}.jpg', pipeline=[ dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=16, twice_sample=True, test_mode=True), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict({ 'data/sthv1': 's204:s3://openmmlab/datasets/action/sthv1' })), 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') launcher = 'slurm' work_dir = './work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb' 2022/09/07 15:44:35 - mmengine - INFO - These parameters in pretrained checkpoint are not loaded: {'fc.bias', 'fc.weight'} 2022/09/07 15:44:36 - mmengine - INFO - Checkpoints will be saved to /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb by HardDiskBackend. 2022/09/07 15:46:14 - mmengine - INFO - Epoch(train) [1][20/1793] lr: 7.5000e-03 eta: 5 days, 2:13:58 time: 4.9095 data_time: 4.1926 memory: 10464 grad_norm: 4.4850 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.6319 loss: 5.6319 2022/09/07 15:46:33 - mmengine - INFO - Epoch(train) [1][40/1793] lr: 7.5000e-03 eta: 3 days, 0:49:12 time: 0.9415 data_time: 0.1517 memory: 10464 grad_norm: 4.5432 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.7104 loss: 5.7104 2022/09/07 15:46:49 - mmengine - INFO - Epoch(train) [1][60/1793] lr: 7.5000e-03 eta: 2 days, 6:50:03 time: 0.7593 data_time: 0.4697 memory: 10464 grad_norm: 3.0813 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.4188 loss: 5.4188 2022/09/07 15:47:08 - mmengine - INFO - Epoch(train) [1][80/1793] lr: 7.5000e-03 eta: 1 day, 23:10:11 time: 0.9731 data_time: 0.1747 memory: 10464 grad_norm: 1.8721 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.0883 loss: 5.0883 2022/09/07 15:47:28 - mmengine - INFO - Epoch(train) [1][100/1793] lr: 7.5000e-03 eta: 1 day, 18:35:46 time: 0.9786 data_time: 0.0100 memory: 10464 grad_norm: 1.9192 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.0719 loss: 5.0719 2022/09/07 15:47:38 - mmengine - INFO - Epoch(train) [1][120/1793] lr: 7.5000e-03 eta: 1 day, 13:43:58 time: 0.5414 data_time: 0.0327 memory: 10464 grad_norm: 1.7471 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 5.0635 loss: 5.0635 2022/09/07 15:48:02 - mmengine - INFO - Epoch(train) [1][140/1793] lr: 7.5000e-03 eta: 1 day, 12:32:00 time: 1.1820 data_time: 0.4078 memory: 10464 grad_norm: 1.5272 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.0541 loss: 5.0541 2022/09/07 15:48:23 - mmengine - INFO - Epoch(train) [1][160/1793] lr: 7.5000e-03 eta: 1 day, 11:11:01 time: 1.0376 data_time: 0.0644 memory: 10464 grad_norm: 1.9082 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.1113 loss: 5.1113 2022/09/07 15:48:52 - mmengine - INFO - Epoch(train) [1][180/1793] lr: 7.5000e-03 eta: 1 day, 11:20:00 time: 1.4724 data_time: 0.0105 memory: 10464 grad_norm: 1.6654 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.0570 loss: 5.0570 2022/09/07 15:49:09 - mmengine - INFO - Epoch(train) [1][200/1793] lr: 7.5000e-03 eta: 1 day, 9:52:10 time: 0.8358 data_time: 0.0094 memory: 10464 grad_norm: 1.6298 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.9357 loss: 4.9357 2022/09/07 15:49:35 - mmengine - INFO - Epoch(train) [1][220/1793] lr: 7.5000e-03 eta: 1 day, 9:46:45 time: 1.3264 data_time: 0.0100 memory: 10464 grad_norm: 2.0394 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.9695 loss: 4.9695 2022/09/07 15:49:51 - mmengine - INFO - Epoch(train) [1][240/1793] lr: 7.5000e-03 eta: 1 day, 8:32:19 time: 0.7641 data_time: 0.0090 memory: 10464 grad_norm: 1.7388 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.0863 loss: 5.0863 2022/09/07 15:50:17 - mmengine - INFO - Epoch(train) [1][260/1793] lr: 7.5000e-03 eta: 1 day, 8:34:20 time: 1.3316 data_time: 0.0102 memory: 10464 grad_norm: 1.8323 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.9683 loss: 4.9683 2022/09/07 15:50:36 - mmengine - INFO - Epoch(train) [1][280/1793] lr: 7.5000e-03 eta: 1 day, 7:53:48 time: 0.9349 data_time: 0.0098 memory: 10464 grad_norm: 1.7120 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.0435 loss: 5.0435 2022/09/07 15:50:49 - mmengine - INFO - Epoch(train) [1][300/1793] lr: 7.5000e-03 eta: 1 day, 6:51:24 time: 0.6605 data_time: 0.0125 memory: 10464 grad_norm: 1.7939 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.9643 loss: 4.9643 2022/09/07 15:51:04 - mmengine - INFO - Epoch(train) [1][320/1793] lr: 7.5000e-03 eta: 1 day, 6:04:55 time: 0.7483 data_time: 0.0236 memory: 10464 grad_norm: 1.8632 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.0312 loss: 5.0312 2022/09/07 15:51:12 - mmengine - INFO - Epoch(train) [1][340/1793] lr: 7.5000e-03 eta: 1 day, 4:51:05 time: 0.3736 data_time: 0.1487 memory: 10464 grad_norm: 2.2877 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.9559 loss: 4.9559 2022/09/07 15:51:19 - mmengine - INFO - Epoch(train) [1][360/1793] lr: 7.5000e-03 eta: 1 day, 3:43:44 time: 0.3531 data_time: 0.0065 memory: 10464 grad_norm: 2.2661 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.9123 loss: 4.9123 2022/09/07 15:51:26 - mmengine - INFO - Epoch(train) [1][380/1793] lr: 7.5000e-03 eta: 1 day, 2:45:19 time: 0.3768 data_time: 0.0441 memory: 10464 grad_norm: 2.4409 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.9450 loss: 4.9450 2022/09/07 15:51:49 - mmengine - INFO - Epoch(train) [1][400/1793] lr: 7.5000e-03 eta: 1 day, 2:47:30 time: 1.1130 data_time: 0.2083 memory: 10464 grad_norm: 2.2851 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 4.8733 loss: 4.8733 2022/09/07 15:52:07 - mmengine - INFO - Epoch(train) [1][420/1793] lr: 7.5000e-03 eta: 1 day, 2:36:17 time: 0.9275 data_time: 0.2678 memory: 10464 grad_norm: 2.1391 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.0049 loss: 5.0049 2022/09/07 15:52:28 - mmengine - INFO - Epoch(train) [1][440/1793] lr: 7.5000e-03 eta: 1 day, 2:32:21 time: 1.0205 data_time: 0.0089 memory: 10464 grad_norm: 2.5613 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.9215 loss: 4.9215 2022/09/07 15:52:42 - mmengine - INFO - Epoch(train) [1][460/1793] lr: 7.5000e-03 eta: 1 day, 2:10:28 time: 0.7379 data_time: 0.0101 memory: 10464 grad_norm: 2.2373 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.9518 loss: 4.9518 2022/09/07 15:52:59 - mmengine - INFO - Epoch(train) [1][480/1793] lr: 7.5000e-03 eta: 1 day, 1:56:45 time: 0.8406 data_time: 0.0088 memory: 10464 grad_norm: 2.3838 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.8500 loss: 4.8500 2022/09/07 15:53:16 - mmengine - INFO - Epoch(train) [1][500/1793] lr: 7.5000e-03 eta: 1 day, 1:45:12 time: 0.8591 data_time: 0.0094 memory: 10464 grad_norm: 2.4863 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.8650 loss: 4.8650 2022/09/07 15:53:38 - mmengine - INFO - Epoch(train) [1][520/1793] lr: 7.5000e-03 eta: 1 day, 1:46:31 time: 1.0690 data_time: 0.0096 memory: 10464 grad_norm: 2.7412 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.7660 loss: 4.7660 2022/09/07 15:53:54 - mmengine - INFO - Epoch(train) [1][540/1793] lr: 7.5000e-03 eta: 1 day, 1:34:22 time: 0.8265 data_time: 0.0674 memory: 10464 grad_norm: 2.2102 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 4.8672 loss: 4.8672 2022/09/07 15:54:16 - mmengine - INFO - Epoch(train) [1][560/1793] lr: 7.5000e-03 eta: 1 day, 1:37:00 time: 1.0893 data_time: 0.0095 memory: 10464 grad_norm: 2.6135 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 4.8463 loss: 4.8463 2022/09/07 15:54:31 - mmengine - INFO - Epoch(train) [1][580/1793] lr: 7.5000e-03 eta: 1 day, 1:22:07 time: 0.7513 data_time: 0.0093 memory: 10464 grad_norm: 2.4230 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.9530 loss: 4.9530 2022/09/07 15:54:53 - mmengine - INFO - Epoch(train) [1][600/1793] lr: 7.5000e-03 eta: 1 day, 1:25:51 time: 1.1076 data_time: 0.0096 memory: 10464 grad_norm: 2.8634 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.9428 loss: 4.9428 2022/09/07 15:55:18 - mmengine - INFO - Epoch(train) [1][620/1793] lr: 7.5000e-03 eta: 1 day, 1:35:19 time: 1.2329 data_time: 0.0104 memory: 10464 grad_norm: 3.1484 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.7561 loss: 4.7561 2022/09/07 15:55:39 - mmengine - INFO - Epoch(train) [1][640/1793] lr: 7.5000e-03 eta: 1 day, 1:35:11 time: 1.0394 data_time: 0.0115 memory: 10464 grad_norm: 3.1434 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.8308 loss: 4.8308 2022/09/07 15:55:59 - mmengine - INFO - Epoch(train) [1][660/1793] lr: 7.5000e-03 eta: 1 day, 1:34:17 time: 1.0225 data_time: 0.5001 memory: 10464 grad_norm: 2.8089 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.8307 loss: 4.8307 2022/09/07 15:56:09 - mmengine - INFO - Epoch(train) [1][680/1793] lr: 7.5000e-03 eta: 1 day, 1:09:50 time: 0.4818 data_time: 0.0857 memory: 10464 grad_norm: 3.1527 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.8704 loss: 4.8704 2022/09/07 15:56:27 - mmengine - INFO - Epoch(train) [1][700/1793] lr: 7.5000e-03 eta: 1 day, 1:05:00 time: 0.9122 data_time: 0.0076 memory: 10464 grad_norm: 3.0374 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 4.7724 loss: 4.7724 2022/09/07 15:56:45 - mmengine - INFO - Epoch(train) [1][720/1793] lr: 7.5000e-03 eta: 1 day, 1:00:39 time: 0.9175 data_time: 0.1425 memory: 10464 grad_norm: 3.4210 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.8050 loss: 4.8050 2022/09/07 15:56:54 - mmengine - INFO - Epoch(train) [1][740/1793] lr: 7.5000e-03 eta: 1 day, 0:37:22 time: 0.4395 data_time: 0.0092 memory: 10464 grad_norm: 3.3017 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.9067 loss: 4.9067 2022/09/07 15:57:03 - mmengine - INFO - Epoch(train) [1][760/1793] lr: 7.5000e-03 eta: 1 day, 0:15:08 time: 0.4355 data_time: 0.0050 memory: 10464 grad_norm: 3.1718 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.7410 loss: 4.7410 2022/09/07 15:57:13 - mmengine - INFO - Epoch(train) [1][780/1793] lr: 7.5000e-03 eta: 23:56:59 time: 0.5128 data_time: 0.0988 memory: 10464 grad_norm: 3.2789 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 4.6345 loss: 4.6345 2022/09/07 15:57:19 - mmengine - INFO - Epoch(train) [1][800/1793] lr: 7.5000e-03 eta: 23:31:09 time: 0.2812 data_time: 0.0186 memory: 10464 grad_norm: 3.0958 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.8513 loss: 4.8513 2022/09/07 15:57:25 - mmengine - INFO - Epoch(train) [1][820/1793] lr: 7.5000e-03 eta: 23:08:21 time: 0.3301 data_time: 0.0485 memory: 10464 grad_norm: 3.2510 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.7905 loss: 4.7905 2022/09/07 15:57:36 - mmengine - INFO - Epoch(train) [1][840/1793] lr: 7.5000e-03 eta: 22:54:36 time: 0.5565 data_time: 0.0084 memory: 10464 grad_norm: 2.8299 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.7052 loss: 4.7052 2022/09/07 15:57:56 - mmengine - INFO - Epoch(train) [1][860/1793] lr: 7.5000e-03 eta: 22:55:44 time: 0.9708 data_time: 0.0105 memory: 10464 grad_norm: 3.7174 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.7303 loss: 4.7303 2022/09/07 15:58:21 - mmengine - INFO - Epoch(train) [1][880/1793] lr: 7.5000e-03 eta: 23:07:19 time: 1.2833 data_time: 0.0105 memory: 10464 grad_norm: 3.2888 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.5716 loss: 4.5716 2022/09/07 15:58:38 - mmengine - INFO - Epoch(train) [1][900/1793] lr: 7.5000e-03 eta: 23:04:04 time: 0.8486 data_time: 0.0089 memory: 10464 grad_norm: 4.1365 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 4.6798 loss: 4.6798 2022/09/07 15:58:58 - mmengine - INFO - Epoch(train) [1][920/1793] lr: 7.5000e-03 eta: 23:05:35 time: 0.9925 data_time: 0.0093 memory: 10464 grad_norm: 3.4251 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 4.7470 loss: 4.7470 2022/09/07 15:59:22 - mmengine - INFO - Epoch(train) [1][940/1793] lr: 7.5000e-03 eta: 23:12:48 time: 1.1760 data_time: 0.0654 memory: 10464 grad_norm: 3.4387 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.7565 loss: 4.7565 2022/09/07 15:59:46 - mmengine - INFO - Epoch(train) [1][960/1793] lr: 7.5000e-03 eta: 23:21:14 time: 1.2260 data_time: 0.0097 memory: 10464 grad_norm: 3.3794 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 4.5149 loss: 4.5149 2022/09/07 16:00:05 - mmengine - INFO - Epoch(train) [1][980/1793] lr: 7.5000e-03 eta: 23:20:30 time: 0.9342 data_time: 0.0102 memory: 10464 grad_norm: 3.7383 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 4.4694 loss: 4.4694 2022/09/07 16:00:20 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 16:00:20 - mmengine - INFO - Epoch(train) [1][1000/1793] lr: 7.5000e-03 eta: 23:14:05 time: 0.7413 data_time: 0.0090 memory: 10464 grad_norm: 3.9489 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.6471 loss: 4.6471 2022/09/07 16:00:41 - mmengine - INFO - Epoch(train) [1][1020/1793] lr: 7.5000e-03 eta: 23:16:21 time: 1.0326 data_time: 0.0095 memory: 10464 grad_norm: 3.8412 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.6574 loss: 4.6574 2022/09/07 16:00:56 - mmengine - INFO - Epoch(train) [1][1040/1793] lr: 7.5000e-03 eta: 23:11:32 time: 0.7871 data_time: 0.0122 memory: 10464 grad_norm: 3.9082 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 4.6280 loss: 4.6280 2022/09/07 16:01:22 - mmengine - INFO - Epoch(train) [1][1060/1793] lr: 7.5000e-03 eta: 23:21:28 time: 1.3100 data_time: 0.0088 memory: 10464 grad_norm: 4.0980 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.6089 loss: 4.6089 2022/09/07 16:01:40 - mmengine - INFO - Epoch(train) [1][1080/1793] lr: 7.5000e-03 eta: 23:19:16 time: 0.8802 data_time: 0.0087 memory: 10464 grad_norm: 3.9022 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.4786 loss: 4.4786 2022/09/07 16:01:53 - mmengine - INFO - Epoch(train) [1][1100/1793] lr: 7.5000e-03 eta: 23:11:14 time: 0.6602 data_time: 0.0091 memory: 10464 grad_norm: 5.4814 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.5698 loss: 4.5698 2022/09/07 16:02:13 - mmengine - INFO - Epoch(train) [1][1120/1793] lr: 7.5000e-03 eta: 23:11:59 time: 0.9830 data_time: 0.1235 memory: 10464 grad_norm: 3.9856 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.7978 loss: 4.7978 2022/09/07 16:02:29 - mmengine - INFO - Epoch(train) [1][1140/1793] lr: 7.5000e-03 eta: 23:07:56 time: 0.7992 data_time: 0.0089 memory: 10464 grad_norm: 3.8211 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 4.3395 loss: 4.3395 2022/09/07 16:02:46 - mmengine - INFO - Epoch(train) [1][1160/1793] lr: 7.5000e-03 eta: 23:05:51 time: 0.8709 data_time: 0.0091 memory: 10464 grad_norm: 3.8141 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 4.6224 loss: 4.6224 2022/09/07 16:02:59 - mmengine - INFO - Epoch(train) [1][1180/1793] lr: 7.5000e-03 eta: 22:57:40 time: 0.6252 data_time: 0.0091 memory: 10464 grad_norm: 4.5252 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.3652 loss: 4.3652 2022/09/07 16:03:19 - mmengine - INFO - Epoch(train) [1][1200/1793] lr: 7.5000e-03 eta: 22:58:57 time: 0.9990 data_time: 0.0091 memory: 10464 grad_norm: 3.9368 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 4.5145 loss: 4.5145 2022/09/07 16:03:29 - mmengine - INFO - Epoch(train) [1][1220/1793] lr: 7.5000e-03 eta: 22:48:15 time: 0.5052 data_time: 0.0106 memory: 10464 grad_norm: 4.0420 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.6160 loss: 4.6160 2022/09/07 16:03:38 - mmengine - INFO - Epoch(train) [1][1240/1793] lr: 7.5000e-03 eta: 22:36:57 time: 0.4665 data_time: 0.2391 memory: 10464 grad_norm: 4.1085 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 4.4326 loss: 4.4326 2022/09/07 16:03:44 - mmengine - INFO - Epoch(train) [1][1260/1793] lr: 7.5000e-03 eta: 22:21:55 time: 0.2908 data_time: 0.0210 memory: 10464 grad_norm: 4.6160 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 4.4947 loss: 4.4947 2022/09/07 16:03:52 - mmengine - INFO - Epoch(train) [1][1280/1793] lr: 7.5000e-03 eta: 22:10:15 time: 0.4176 data_time: 0.0082 memory: 10464 grad_norm: 4.4175 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 4.4199 loss: 4.4199 2022/09/07 16:03:59 - mmengine - INFO - Epoch(train) [1][1300/1793] lr: 7.5000e-03 eta: 21:56:29 time: 0.3086 data_time: 0.0066 memory: 10464 grad_norm: 4.0886 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.5967 loss: 4.5967 2022/09/07 16:04:22 - mmengine - INFO - Epoch(train) [1][1320/1793] lr: 7.5000e-03 eta: 22:01:57 time: 1.1527 data_time: 0.0086 memory: 10464 grad_norm: 4.0579 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.3431 loss: 4.3431 2022/09/07 16:04:39 - mmengine - INFO - Epoch(train) [1][1340/1793] lr: 7.5000e-03 eta: 22:01:15 time: 0.8792 data_time: 0.0101 memory: 10464 grad_norm: 4.2461 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.4920 loss: 4.4920 2022/09/07 16:05:10 - mmengine - INFO - Epoch(train) [1][1360/1793] lr: 7.5000e-03 eta: 22:15:03 time: 1.5493 data_time: 0.0100 memory: 10464 grad_norm: 4.0689 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 4.5968 loss: 4.5968 2022/09/07 16:05:32 - mmengine - INFO - Epoch(train) [1][1380/1793] lr: 7.5000e-03 eta: 22:18:16 time: 1.0724 data_time: 0.0100 memory: 10464 grad_norm: 4.2417 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 4.3706 loss: 4.3706 2022/09/07 16:05:43 - mmengine - INFO - Epoch(train) [1][1400/1793] lr: 7.5000e-03 eta: 22:10:57 time: 0.5758 data_time: 0.0097 memory: 10464 grad_norm: 4.3458 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 4.1927 loss: 4.1927 2022/09/07 16:06:03 - mmengine - INFO - Epoch(train) [1][1420/1793] lr: 7.5000e-03 eta: 22:12:34 time: 0.9976 data_time: 0.0380 memory: 10464 grad_norm: 4.9790 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.4813 loss: 4.4813 2022/09/07 16:06:18 - mmengine - INFO - Epoch(train) [1][1440/1793] lr: 7.5000e-03 eta: 22:09:16 time: 0.7598 data_time: 0.0096 memory: 10464 grad_norm: 4.0506 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 4.6938 loss: 4.6938 2022/09/07 16:06:37 - mmengine - INFO - Epoch(train) [1][1460/1793] lr: 7.5000e-03 eta: 22:09:07 time: 0.9113 data_time: 0.1441 memory: 10464 grad_norm: 4.1615 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.5182 loss: 4.5182 2022/09/07 16:06:52 - mmengine - INFO - Epoch(train) [1][1480/1793] lr: 7.5000e-03 eta: 22:06:09 time: 0.7697 data_time: 0.0098 memory: 10464 grad_norm: 4.1932 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 4.5060 loss: 4.5060 2022/09/07 16:07:10 - mmengine - INFO - Epoch(train) [1][1500/1793] lr: 7.5000e-03 eta: 22:05:25 time: 0.8807 data_time: 0.0111 memory: 10464 grad_norm: 4.3500 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.3233 loss: 4.3233 2022/09/07 16:07:28 - mmengine - INFO - Epoch(train) [1][1520/1793] lr: 7.5000e-03 eta: 22:05:19 time: 0.9123 data_time: 0.0116 memory: 10464 grad_norm: 4.1811 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 4.2999 loss: 4.2999 2022/09/07 16:07:50 - mmengine - INFO - Epoch(train) [1][1540/1793] lr: 7.5000e-03 eta: 22:08:54 time: 1.1060 data_time: 0.0097 memory: 10464 grad_norm: 4.2290 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 4.3798 loss: 4.3798 2022/09/07 16:08:08 - mmengine - INFO - Epoch(train) [1][1560/1793] lr: 7.5000e-03 eta: 22:08:39 time: 0.9080 data_time: 0.0117 memory: 10464 grad_norm: 4.7028 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.5172 loss: 4.5172 2022/09/07 16:08:34 - mmengine - INFO - Epoch(train) [1][1580/1793] lr: 7.5000e-03 eta: 22:15:22 time: 1.2826 data_time: 0.0103 memory: 10464 grad_norm: 4.4804 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.4150 loss: 4.4150 2022/09/07 16:08:53 - mmengine - INFO - Epoch(train) [1][1600/1793] lr: 7.5000e-03 eta: 22:15:43 time: 0.9454 data_time: 0.0094 memory: 10464 grad_norm: 4.4334 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 4.0386 loss: 4.0386 2022/09/07 16:09:14 - mmengine - INFO - Epoch(train) [1][1620/1793] lr: 7.5000e-03 eta: 22:18:18 time: 1.0703 data_time: 0.3158 memory: 10464 grad_norm: 4.6198 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 4.3960 loss: 4.3960 2022/09/07 16:09:32 - mmengine - INFO - Epoch(train) [1][1640/1793] lr: 7.5000e-03 eta: 22:17:43 time: 0.8958 data_time: 0.0106 memory: 10464 grad_norm: 4.7084 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 4.3359 loss: 4.3359 2022/09/07 16:09:48 - mmengine - INFO - Epoch(train) [1][1660/1793] lr: 7.5000e-03 eta: 22:15:09 time: 0.7847 data_time: 0.1584 memory: 10464 grad_norm: 4.4168 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 4.2345 loss: 4.2345 2022/09/07 16:10:06 - mmengine - INFO - Epoch(train) [1][1680/1793] lr: 7.5000e-03 eta: 22:15:07 time: 0.9260 data_time: 0.0094 memory: 10464 grad_norm: 4.4426 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 4.4657 loss: 4.4657 2022/09/07 16:10:13 - mmengine - INFO - Epoch(train) [1][1700/1793] lr: 7.5000e-03 eta: 22:04:45 time: 0.3263 data_time: 0.0840 memory: 10464 grad_norm: 4.6127 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.1705 loss: 4.1705 2022/09/07 16:10:21 - mmengine - INFO - Epoch(train) [1][1720/1793] lr: 7.5000e-03 eta: 21:56:31 time: 0.4384 data_time: 0.0053 memory: 10464 grad_norm: 4.8894 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 4.2437 loss: 4.2437 2022/09/07 16:10:38 - mmengine - INFO - Epoch(train) [1][1740/1793] lr: 7.5000e-03 eta: 21:55:07 time: 0.8335 data_time: 0.0099 memory: 10464 grad_norm: 4.6203 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.3112 loss: 4.3112 2022/09/07 16:10:52 - mmengine - INFO - Epoch(train) [1][1760/1793] lr: 7.5000e-03 eta: 21:51:19 time: 0.6871 data_time: 0.0184 memory: 10464 grad_norm: 4.6062 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.3119 loss: 4.3119 2022/09/07 16:11:17 - mmengine - INFO - Epoch(train) [1][1780/1793] lr: 7.5000e-03 eta: 21:56:48 time: 1.2466 data_time: 0.2846 memory: 10464 grad_norm: 4.8348 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 4.3898 loss: 4.3898 2022/09/07 16:11:34 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 16:11:34 - mmengine - INFO - Epoch(train) [1][1793/1793] lr: 7.5000e-03 eta: 21:56:48 time: 1.3644 data_time: 0.6457 memory: 10464 grad_norm: 4.9861 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.3077 loss: 4.3077 2022/09/07 16:11:35 - mmengine - INFO - Saving checkpoint at 1 epochs 2022/09/07 16:12:33 - mmengine - INFO - Epoch(val) [1][20/241] eta: 0:10:16 time: 2.7914 data_time: 2.7086 memory: 1482 2022/09/07 16:12:46 - mmengine - INFO - Epoch(val) [1][40/241] eta: 0:02:10 time: 0.6495 data_time: 0.5729 memory: 1482 2022/09/07 16:12:58 - mmengine - INFO - Epoch(val) [1][60/241] eta: 0:01:49 time: 0.6038 data_time: 0.5275 memory: 1482 2022/09/07 16:13:12 - mmengine - INFO - Epoch(val) [1][80/241] eta: 0:01:53 time: 0.7024 data_time: 0.6287 memory: 1482 2022/09/07 16:13:18 - mmengine - INFO - Epoch(val) [1][100/241] eta: 0:00:42 time: 0.3021 data_time: 0.2266 memory: 1482 2022/09/07 16:13:44 - mmengine - INFO - Epoch(val) [1][120/241] eta: 0:02:33 time: 1.2711 data_time: 1.2070 memory: 1482 2022/09/07 16:13:56 - mmengine - INFO - Epoch(val) [1][140/241] eta: 0:00:59 time: 0.5885 data_time: 0.5189 memory: 1482 2022/09/07 16:14:12 - mmengine - INFO - Epoch(val) [1][160/241] eta: 0:01:05 time: 0.8092 data_time: 0.7544 memory: 1482 2022/09/07 16:14:21 - mmengine - INFO - Epoch(val) [1][180/241] eta: 0:00:29 time: 0.4755 data_time: 0.4195 memory: 1482 2022/09/07 16:14:30 - mmengine - INFO - Epoch(val) [1][200/241] eta: 0:00:17 time: 0.4173 data_time: 0.3455 memory: 1482 2022/09/07 16:14:54 - mmengine - INFO - Epoch(val) [1][220/241] eta: 0:00:25 time: 1.2292 data_time: 1.1576 memory: 1482 2022/09/07 16:15:03 - mmengine - INFO - Epoch(val) [1][240/241] eta: 0:00:00 time: 0.4180 data_time: 0.3527 memory: 1482 2022/09/07 16:15:34 - mmengine - INFO - Epoch(val) [1][241/241] acc/top1: 0.0725 acc/top5: 0.2392 acc/mean1: 0.0634 2022/09/07 16:15:35 - mmengine - INFO - The best checkpoint with 0.0725 acc/top1 at 1 epoch is saved to best_acc/top1_epoch_1.pth. 2022/09/07 16:16:01 - mmengine - INFO - Epoch(train) [2][20/1793] lr: 7.5000e-03 eta: 21:52:49 time: 1.2678 data_time: 0.1063 memory: 10464 grad_norm: 5.3080 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.3509 loss: 4.3509 2022/09/07 16:16:10 - mmengine - INFO - Epoch(train) [2][40/1793] lr: 7.5000e-03 eta: 21:45:53 time: 0.4807 data_time: 0.0093 memory: 10464 grad_norm: 5.2858 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.5134 loss: 4.5134 2022/09/07 16:16:21 - mmengine - INFO - Epoch(train) [2][60/1793] lr: 7.5000e-03 eta: 21:39:37 time: 0.5148 data_time: 0.0072 memory: 10464 grad_norm: 5.6487 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 4.1742 loss: 4.1742 2022/09/07 16:16:33 - mmengine - INFO - Epoch(train) [2][80/1793] lr: 7.5000e-03 eta: 21:34:53 time: 0.6041 data_time: 0.0091 memory: 10464 grad_norm: 5.1916 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 4.2339 loss: 4.2339 2022/09/07 16:16:44 - mmengine - INFO - Epoch(train) [2][100/1793] lr: 7.5000e-03 eta: 21:29:21 time: 0.5462 data_time: 0.0100 memory: 10464 grad_norm: 4.9961 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.0268 loss: 4.0268 2022/09/07 16:16:56 - mmengine - INFO - Epoch(train) [2][120/1793] lr: 7.5000e-03 eta: 21:24:42 time: 0.5957 data_time: 0.0092 memory: 10464 grad_norm: 5.3963 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.1882 loss: 4.1882 2022/09/07 16:17:15 - mmengine - INFO - Epoch(train) [2][140/1793] lr: 7.5000e-03 eta: 21:26:03 time: 0.9874 data_time: 0.0103 memory: 10464 grad_norm: 6.0831 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.1982 loss: 4.1982 2022/09/07 16:17:34 - mmengine - INFO - Epoch(train) [2][160/1793] lr: 7.5000e-03 eta: 21:26:20 time: 0.9184 data_time: 0.0103 memory: 10464 grad_norm: 4.8901 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.1755 loss: 4.1755 2022/09/07 16:17:58 - mmengine - INFO - Epoch(train) [2][180/1793] lr: 7.5000e-03 eta: 21:30:40 time: 1.1920 data_time: 0.0102 memory: 10464 grad_norm: 5.3013 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.2305 loss: 4.2305 2022/09/07 16:18:10 - mmengine - INFO - Epoch(train) [2][200/1793] lr: 7.5000e-03 eta: 21:26:10 time: 0.5968 data_time: 0.0100 memory: 10464 grad_norm: 4.9680 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.0693 loss: 4.0693 2022/09/07 16:18:16 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 16:18:24 - mmengine - INFO - Epoch(train) [2][220/1793] lr: 7.5000e-03 eta: 21:23:45 time: 0.7345 data_time: 0.0110 memory: 10464 grad_norm: 4.9139 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.4734 loss: 4.4734 2022/09/07 16:18:41 - mmengine - INFO - Epoch(train) [2][240/1793] lr: 7.5000e-03 eta: 21:22:58 time: 0.8450 data_time: 0.0106 memory: 10464 grad_norm: 5.1266 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 4.1716 loss: 4.1716 2022/09/07 16:18:51 - mmengine - INFO - Epoch(train) [2][260/1793] lr: 7.5000e-03 eta: 21:17:02 time: 0.4816 data_time: 0.0087 memory: 10464 grad_norm: 5.1204 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 4.1632 loss: 4.1632 2022/09/07 16:19:07 - mmengine - INFO - Epoch(train) [2][280/1793] lr: 7.5000e-03 eta: 21:16:10 time: 0.8338 data_time: 0.0077 memory: 10464 grad_norm: 5.5853 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.9518 loss: 3.9518 2022/09/07 16:19:26 - mmengine - INFO - Epoch(train) [2][300/1793] lr: 7.5000e-03 eta: 21:16:50 time: 0.9436 data_time: 0.0088 memory: 10464 grad_norm: 5.4349 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 4.3713 loss: 4.3713 2022/09/07 16:19:50 - mmengine - INFO - Epoch(train) [2][320/1793] lr: 7.5000e-03 eta: 21:21:09 time: 1.2082 data_time: 0.7193 memory: 10464 grad_norm: 5.0407 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 4.2509 loss: 4.2509 2022/09/07 16:20:07 - mmengine - INFO - Epoch(train) [2][340/1793] lr: 7.5000e-03 eta: 21:19:58 time: 0.8132 data_time: 0.5532 memory: 10464 grad_norm: 4.7155 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.1968 loss: 4.1968 2022/09/07 16:20:27 - mmengine - INFO - Epoch(train) [2][360/1793] lr: 7.5000e-03 eta: 21:21:34 time: 1.0169 data_time: 0.7485 memory: 10464 grad_norm: 5.1960 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 4.0149 loss: 4.0149 2022/09/07 16:20:42 - mmengine - INFO - Epoch(train) [2][380/1793] lr: 7.5000e-03 eta: 21:19:13 time: 0.7250 data_time: 0.2519 memory: 10464 grad_norm: 4.9695 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.9559 loss: 3.9559 2022/09/07 16:21:00 - mmengine - INFO - Epoch(train) [2][400/1793] lr: 7.5000e-03 eta: 21:19:50 time: 0.9465 data_time: 0.6415 memory: 10464 grad_norm: 5.4189 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.8985 loss: 3.8985 2022/09/07 16:21:07 - mmengine - INFO - Epoch(train) [2][420/1793] lr: 7.5000e-03 eta: 21:12:07 time: 0.3141 data_time: 0.0151 memory: 10464 grad_norm: 5.0732 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.9061 loss: 3.9061 2022/09/07 16:21:25 - mmengine - INFO - Epoch(train) [2][440/1793] lr: 7.5000e-03 eta: 21:12:34 time: 0.9299 data_time: 0.0068 memory: 10464 grad_norm: 5.1572 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 4.1208 loss: 4.1208 2022/09/07 16:21:37 - mmengine - INFO - Epoch(train) [2][460/1793] lr: 7.5000e-03 eta: 21:08:15 time: 0.5616 data_time: 0.1227 memory: 10464 grad_norm: 4.9749 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 4.0644 loss: 4.0644 2022/09/07 16:21:54 - mmengine - INFO - Epoch(train) [2][480/1793] lr: 7.5000e-03 eta: 21:08:13 time: 0.8909 data_time: 0.1077 memory: 10464 grad_norm: 5.1229 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 4.0217 loss: 4.0217 2022/09/07 16:22:06 - mmengine - INFO - Epoch(train) [2][500/1793] lr: 7.5000e-03 eta: 21:04:14 time: 0.5797 data_time: 0.0098 memory: 10464 grad_norm: 4.7321 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.2249 loss: 4.2249 2022/09/07 16:22:28 - mmengine - INFO - Epoch(train) [2][520/1793] lr: 7.5000e-03 eta: 21:06:33 time: 1.0764 data_time: 0.7022 memory: 10464 grad_norm: 5.0126 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.3042 loss: 4.3042 2022/09/07 16:22:42 - mmengine - INFO - Epoch(train) [2][540/1793] lr: 7.5000e-03 eta: 21:04:22 time: 0.7178 data_time: 0.0685 memory: 10464 grad_norm: 4.8315 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.0729 loss: 4.0729 2022/09/07 16:22:53 - mmengine - INFO - Epoch(train) [2][560/1793] lr: 7.5000e-03 eta: 21:00:07 time: 0.5480 data_time: 0.0577 memory: 10464 grad_norm: 5.6708 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 4.1888 loss: 4.1888 2022/09/07 16:23:05 - mmengine - INFO - Epoch(train) [2][580/1793] lr: 7.5000e-03 eta: 20:56:44 time: 0.6146 data_time: 0.0393 memory: 10464 grad_norm: 5.0075 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 4.1200 loss: 4.1200 2022/09/07 16:23:12 - mmengine - INFO - Epoch(train) [2][600/1793] lr: 7.5000e-03 eta: 20:50:02 time: 0.3354 data_time: 0.0096 memory: 10464 grad_norm: 4.9704 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 4.1258 loss: 4.1258 2022/09/07 16:23:17 - mmengine - INFO - Epoch(train) [2][620/1793] lr: 7.5000e-03 eta: 20:42:17 time: 0.2410 data_time: 0.0064 memory: 10464 grad_norm: 4.7769 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 4.1811 loss: 4.1811 2022/09/07 16:23:23 - mmengine - INFO - Epoch(train) [2][640/1793] lr: 7.5000e-03 eta: 20:35:21 time: 0.2977 data_time: 0.0086 memory: 10464 grad_norm: 5.4927 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 4.0996 loss: 4.0996 2022/09/07 16:23:28 - mmengine - INFO - Epoch(train) [2][660/1793] lr: 7.5000e-03 eta: 20:27:53 time: 0.2436 data_time: 0.0071 memory: 10464 grad_norm: 5.6552 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.8745 loss: 3.8745 2022/09/07 16:23:46 - mmengine - INFO - Epoch(train) [2][680/1793] lr: 7.5000e-03 eta: 20:28:32 time: 0.9248 data_time: 0.0431 memory: 10464 grad_norm: 5.1047 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.0267 loss: 4.0267 2022/09/07 16:24:08 - mmengine - INFO - Epoch(train) [2][700/1793] lr: 7.5000e-03 eta: 20:30:58 time: 1.0776 data_time: 0.0091 memory: 10464 grad_norm: 5.3149 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 4.0464 loss: 4.0464 2022/09/07 16:24:24 - mmengine - INFO - Epoch(train) [2][720/1793] lr: 7.5000e-03 eta: 20:30:14 time: 0.8087 data_time: 0.0463 memory: 10464 grad_norm: 5.4061 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 3.9494 loss: 3.9494 2022/09/07 16:24:43 - mmengine - INFO - Epoch(train) [2][740/1793] lr: 7.5000e-03 eta: 20:31:24 time: 0.9740 data_time: 0.4766 memory: 10464 grad_norm: 5.8318 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.0910 loss: 4.0910 2022/09/07 16:25:05 - mmengine - INFO - Epoch(train) [2][760/1793] lr: 7.5000e-03 eta: 20:33:45 time: 1.0790 data_time: 0.0108 memory: 10464 grad_norm: 5.9500 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.9731 loss: 3.9731 2022/09/07 16:25:21 - mmengine - INFO - Epoch(train) [2][780/1793] lr: 7.5000e-03 eta: 20:33:17 time: 0.8344 data_time: 0.0094 memory: 10464 grad_norm: 5.1854 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.9532 loss: 3.9532 2022/09/07 16:25:33 - mmengine - INFO - Epoch(train) [2][800/1793] lr: 7.5000e-03 eta: 20:30:12 time: 0.5996 data_time: 0.0091 memory: 10464 grad_norm: 5.0539 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.0711 loss: 4.0711 2022/09/07 16:25:49 - mmengine - INFO - Epoch(train) [2][820/1793] lr: 7.5000e-03 eta: 20:28:59 time: 0.7638 data_time: 0.0100 memory: 10464 grad_norm: 5.0965 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 4.2139 loss: 4.2139 2022/09/07 16:26:07 - mmengine - INFO - Epoch(train) [2][840/1793] lr: 7.5000e-03 eta: 20:29:24 time: 0.9100 data_time: 0.0099 memory: 10464 grad_norm: 5.2492 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.9206 loss: 3.9206 2022/09/07 16:26:29 - mmengine - INFO - Epoch(train) [2][860/1793] lr: 7.5000e-03 eta: 20:31:53 time: 1.1011 data_time: 0.5413 memory: 10464 grad_norm: 5.5598 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 4.0827 loss: 4.0827 2022/09/07 16:26:44 - mmengine - INFO - Epoch(train) [2][880/1793] lr: 7.5000e-03 eta: 20:30:16 time: 0.7264 data_time: 0.1006 memory: 10464 grad_norm: 5.4216 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 4.2431 loss: 4.2431 2022/09/07 16:26:58 - mmengine - INFO - Epoch(train) [2][900/1793] lr: 7.5000e-03 eta: 20:28:51 time: 0.7441 data_time: 0.0089 memory: 10464 grad_norm: 5.3017 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.9217 loss: 3.9217 2022/09/07 16:27:11 - mmengine - INFO - Epoch(train) [2][920/1793] lr: 7.5000e-03 eta: 20:26:20 time: 0.6391 data_time: 0.0100 memory: 10464 grad_norm: 4.8863 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 4.0830 loss: 4.0830 2022/09/07 16:27:27 - mmengine - INFO - Epoch(train) [2][940/1793] lr: 7.5000e-03 eta: 20:25:38 time: 0.8063 data_time: 0.0108 memory: 10464 grad_norm: 5.2221 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.9136 loss: 3.9136 2022/09/07 16:27:42 - mmengine - INFO - Epoch(train) [2][960/1793] lr: 7.5000e-03 eta: 20:24:19 time: 0.7484 data_time: 0.0109 memory: 10464 grad_norm: 5.0789 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.9235 loss: 3.9235 2022/09/07 16:27:51 - mmengine - INFO - Epoch(train) [2][980/1793] lr: 7.5000e-03 eta: 20:19:52 time: 0.4463 data_time: 0.0101 memory: 10464 grad_norm: 5.4111 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.2623 loss: 4.2623 2022/09/07 16:28:03 - mmengine - INFO - Epoch(train) [2][1000/1793] lr: 7.5000e-03 eta: 20:17:14 time: 0.6146 data_time: 0.0067 memory: 10464 grad_norm: 5.0749 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 4.0179 loss: 4.0179 2022/09/07 16:28:15 - mmengine - INFO - Epoch(train) [2][1020/1793] lr: 7.5000e-03 eta: 20:14:20 time: 0.5861 data_time: 0.0093 memory: 10464 grad_norm: 5.2782 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.7431 loss: 3.7431 2022/09/07 16:28:26 - mmengine - INFO - Epoch(train) [2][1040/1793] lr: 7.5000e-03 eta: 20:11:00 time: 0.5411 data_time: 0.0098 memory: 10464 grad_norm: 5.0948 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 3.8791 loss: 3.8791 2022/09/07 16:28:57 - mmengine - INFO - Epoch(train) [2][1060/1793] lr: 7.5000e-03 eta: 20:17:54 time: 1.5447 data_time: 0.8572 memory: 10464 grad_norm: 5.9440 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.8167 loss: 3.8167 2022/09/07 16:29:06 - mmengine - INFO - Epoch(train) [2][1080/1793] lr: 7.5000e-03 eta: 20:13:54 time: 0.4718 data_time: 0.0092 memory: 10464 grad_norm: 4.9409 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.8887 loss: 3.8887 2022/09/07 16:29:15 - mmengine - INFO - Epoch(train) [2][1100/1793] lr: 7.5000e-03 eta: 20:09:30 time: 0.4278 data_time: 0.0056 memory: 10464 grad_norm: 5.3329 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.3290 loss: 4.3290 2022/09/07 16:29:25 - mmengine - INFO - Epoch(train) [2][1120/1793] lr: 7.5000e-03 eta: 20:05:50 time: 0.4953 data_time: 0.0083 memory: 10464 grad_norm: 5.3552 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 3.6063 loss: 3.6063 2022/09/07 16:29:33 - mmengine - INFO - Epoch(train) [2][1140/1793] lr: 7.5000e-03 eta: 20:01:28 time: 0.4189 data_time: 0.0529 memory: 10464 grad_norm: 5.4467 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.9254 loss: 3.9254 2022/09/07 16:29:41 - mmengine - INFO - Epoch(train) [2][1160/1793] lr: 7.5000e-03 eta: 19:56:52 time: 0.3897 data_time: 0.0085 memory: 10464 grad_norm: 5.0746 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.8546 loss: 3.8546 2022/09/07 16:29:49 - mmengine - INFO - Epoch(train) [2][1180/1793] lr: 7.5000e-03 eta: 19:52:40 time: 0.4242 data_time: 0.0059 memory: 10464 grad_norm: 5.6670 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.9238 loss: 3.9238 2022/09/07 16:29:56 - mmengine - INFO - Epoch(train) [2][1200/1793] lr: 7.5000e-03 eta: 19:47:44 time: 0.3438 data_time: 0.1080 memory: 10464 grad_norm: 4.9214 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.7814 loss: 3.7814 2022/09/07 16:30:00 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 16:30:03 - mmengine - INFO - Epoch(train) [2][1220/1793] lr: 7.5000e-03 eta: 19:42:51 time: 0.3409 data_time: 0.0802 memory: 10464 grad_norm: 5.2743 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 3.6968 loss: 3.6968 2022/09/07 16:30:14 - mmengine - INFO - Epoch(train) [2][1240/1793] lr: 7.5000e-03 eta: 19:39:45 time: 0.5213 data_time: 0.0089 memory: 10464 grad_norm: 5.5646 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.9701 loss: 3.9701 2022/09/07 16:30:29 - mmengine - INFO - Epoch(train) [2][1260/1793] lr: 7.5000e-03 eta: 19:38:54 time: 0.7562 data_time: 0.0096 memory: 10464 grad_norm: 5.3978 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 3.9654 loss: 3.9654 2022/09/07 16:30:47 - mmengine - INFO - Epoch(train) [2][1280/1793] lr: 7.5000e-03 eta: 19:39:24 time: 0.8997 data_time: 0.0093 memory: 10464 grad_norm: 5.4211 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 4.0307 loss: 4.0307 2022/09/07 16:31:08 - mmengine - INFO - Epoch(train) [2][1300/1793] lr: 7.5000e-03 eta: 19:41:36 time: 1.0819 data_time: 0.0094 memory: 10464 grad_norm: 5.3017 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.6672 loss: 3.6672 2022/09/07 16:31:17 - mmengine - INFO - Epoch(train) [2][1320/1793] lr: 7.5000e-03 eta: 19:37:55 time: 0.4515 data_time: 0.0100 memory: 10464 grad_norm: 5.4695 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.7127 loss: 3.7127 2022/09/07 16:31:33 - mmengine - INFO - Epoch(train) [2][1340/1793] lr: 7.5000e-03 eta: 19:37:20 time: 0.7829 data_time: 0.0069 memory: 10464 grad_norm: 5.3832 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.9319 loss: 3.9319 2022/09/07 16:31:46 - mmengine - INFO - Epoch(train) [2][1360/1793] lr: 7.5000e-03 eta: 19:35:35 time: 0.6544 data_time: 0.0920 memory: 10464 grad_norm: 5.4259 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 4.0505 loss: 4.0505 2022/09/07 16:32:07 - mmengine - INFO - Epoch(train) [2][1380/1793] lr: 7.5000e-03 eta: 19:37:17 time: 1.0332 data_time: 0.0096 memory: 10464 grad_norm: 5.4166 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.9013 loss: 3.9013 2022/09/07 16:32:21 - mmengine - INFO - Epoch(train) [2][1400/1793] lr: 7.5000e-03 eta: 19:36:10 time: 0.7227 data_time: 0.0099 memory: 10464 grad_norm: 5.2141 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 3.8362 loss: 3.8362 2022/09/07 16:32:39 - mmengine - INFO - Epoch(train) [2][1420/1793] lr: 7.5000e-03 eta: 19:36:43 time: 0.9086 data_time: 0.6124 memory: 10464 grad_norm: 5.3987 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 4.1124 loss: 4.1124 2022/09/07 16:32:51 - mmengine - INFO - Epoch(train) [2][1440/1793] lr: 7.5000e-03 eta: 19:34:30 time: 0.5982 data_time: 0.1359 memory: 10464 grad_norm: 5.6805 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 4.0300 loss: 4.0300 2022/09/07 16:33:07 - mmengine - INFO - Epoch(train) [2][1460/1793] lr: 7.5000e-03 eta: 19:33:58 time: 0.7863 data_time: 0.1842 memory: 10464 grad_norm: 5.3458 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.7160 loss: 3.7160 2022/09/07 16:33:21 - mmengine - INFO - Epoch(train) [2][1480/1793] lr: 7.5000e-03 eta: 19:32:27 time: 0.6731 data_time: 0.0088 memory: 10464 grad_norm: 5.2961 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.6388 loss: 3.6388 2022/09/07 16:33:40 - mmengine - INFO - Epoch(train) [2][1500/1793] lr: 7.5000e-03 eta: 19:33:27 time: 0.9603 data_time: 0.0099 memory: 10464 grad_norm: 5.0654 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.7702 loss: 3.7702 2022/09/07 16:33:56 - mmengine - INFO - Epoch(train) [2][1520/1793] lr: 7.5000e-03 eta: 19:33:12 time: 0.8180 data_time: 0.1998 memory: 10464 grad_norm: 5.6646 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.4224 loss: 3.4224 2022/09/07 16:34:10 - mmengine - INFO - Epoch(train) [2][1540/1793] lr: 7.5000e-03 eta: 19:31:44 time: 0.6766 data_time: 0.3383 memory: 10464 grad_norm: 5.5435 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 4.0139 loss: 4.0139 2022/09/07 16:34:22 - mmengine - INFO - Epoch(train) [2][1560/1793] lr: 7.5000e-03 eta: 19:29:40 time: 0.6055 data_time: 0.2606 memory: 10464 grad_norm: 5.0945 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.5544 loss: 3.5544 2022/09/07 16:34:39 - mmengine - INFO - Epoch(train) [2][1580/1793] lr: 7.5000e-03 eta: 19:29:49 time: 0.8627 data_time: 0.5376 memory: 10464 grad_norm: 6.2554 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 3.8219 loss: 3.8219 2022/09/07 16:35:01 - mmengine - INFO - Epoch(train) [2][1600/1793] lr: 7.5000e-03 eta: 19:31:58 time: 1.0984 data_time: 0.1298 memory: 10464 grad_norm: 5.2938 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 3.9830 loss: 3.9830 2022/09/07 16:35:14 - mmengine - INFO - Epoch(train) [2][1620/1793] lr: 7.5000e-03 eta: 19:30:11 time: 0.6370 data_time: 0.0094 memory: 10464 grad_norm: 6.0655 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.9939 loss: 3.9939 2022/09/07 16:35:32 - mmengine - INFO - Epoch(train) [2][1640/1793] lr: 7.5000e-03 eta: 19:30:51 time: 0.9265 data_time: 0.0089 memory: 10464 grad_norm: 5.3476 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.8450 loss: 3.8450 2022/09/07 16:35:44 - mmengine - INFO - Epoch(train) [2][1660/1793] lr: 7.5000e-03 eta: 19:28:52 time: 0.6083 data_time: 0.0106 memory: 10464 grad_norm: 5.7660 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.8653 loss: 3.8653 2022/09/07 16:35:56 - mmengine - INFO - Epoch(train) [2][1680/1793] lr: 7.5000e-03 eta: 19:26:42 time: 0.5837 data_time: 0.0086 memory: 10464 grad_norm: 5.3829 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.6350 loss: 3.6350 2022/09/07 16:36:03 - mmengine - INFO - Epoch(train) [2][1700/1793] lr: 7.5000e-03 eta: 19:22:27 time: 0.3289 data_time: 0.0913 memory: 10464 grad_norm: 5.7679 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.9605 loss: 3.9605 2022/09/07 16:36:10 - mmengine - INFO - Epoch(train) [2][1720/1793] lr: 7.5000e-03 eta: 19:18:29 time: 0.3584 data_time: 0.0053 memory: 10464 grad_norm: 5.9282 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.8099 loss: 3.8099 2022/09/07 16:36:20 - mmengine - INFO - Epoch(train) [2][1740/1793] lr: 7.5000e-03 eta: 19:15:56 time: 0.5250 data_time: 0.0084 memory: 10464 grad_norm: 6.4410 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.7951 loss: 3.7951 2022/09/07 16:36:27 - mmengine - INFO - Epoch(train) [2][1760/1793] lr: 7.5000e-03 eta: 19:12:02 time: 0.3560 data_time: 0.0094 memory: 10464 grad_norm: 5.0863 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.7298 loss: 3.7298 2022/09/07 16:36:43 - mmengine - INFO - Epoch(train) [2][1780/1793] lr: 7.5000e-03 eta: 19:11:37 time: 0.7850 data_time: 0.0075 memory: 10464 grad_norm: 5.9828 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.8569 loss: 3.8569 2022/09/07 16:36:57 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 16:36:57 - mmengine - INFO - Epoch(train) [2][1793/1793] lr: 7.5000e-03 eta: 19:11:37 time: 0.8693 data_time: 0.0770 memory: 10464 grad_norm: 6.1768 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 3.8160 loss: 3.8160 2022/09/07 16:36:57 - mmengine - INFO - Saving checkpoint at 2 epochs 2022/09/07 16:37:00 - mmengine - INFO - Epoch(val) [2][20/241] eta: 0:00:17 time: 0.0784 data_time: 0.0093 memory: 1482 2022/09/07 16:37:02 - mmengine - INFO - Epoch(val) [2][40/241] eta: 0:00:15 time: 0.0756 data_time: 0.0055 memory: 1482 2022/09/07 16:37:03 - mmengine - INFO - Epoch(val) [2][60/241] eta: 0:00:12 time: 0.0714 data_time: 0.0050 memory: 1482 2022/09/07 16:37:04 - mmengine - INFO - Epoch(val) [2][80/241] eta: 0:00:10 time: 0.0638 data_time: 0.0052 memory: 1482 2022/09/07 16:37:06 - mmengine - INFO - Epoch(val) [2][100/241] eta: 0:00:13 time: 0.0939 data_time: 0.0057 memory: 1482 2022/09/07 16:37:08 - mmengine - INFO - Epoch(val) [2][120/241] eta: 0:00:07 time: 0.0614 data_time: 0.0055 memory: 1482 2022/09/07 16:37:09 - mmengine - INFO - Epoch(val) [2][140/241] eta: 0:00:07 time: 0.0708 data_time: 0.0058 memory: 1482 2022/09/07 16:37:11 - mmengine - INFO - Epoch(val) [2][160/241] eta: 0:00:06 time: 0.0823 data_time: 0.0052 memory: 1482 2022/09/07 16:37:12 - mmengine - INFO - Epoch(val) [2][180/241] eta: 0:00:04 time: 0.0690 data_time: 0.0057 memory: 1482 2022/09/07 16:37:14 - mmengine - INFO - Epoch(val) [2][200/241] eta: 0:00:03 time: 0.0796 data_time: 0.0046 memory: 1482 2022/09/07 16:37:15 - mmengine - INFO - Epoch(val) [2][220/241] eta: 0:00:01 time: 0.0745 data_time: 0.0052 memory: 1482 2022/09/07 16:37:16 - mmengine - INFO - Epoch(val) [2][240/241] eta: 0:00:00 time: 0.0692 data_time: 0.0076 memory: 1482 2022/09/07 16:37:17 - mmengine - INFO - Epoch(val) [2][241/241] acc/top1: 0.1017 acc/top5: 0.3075 acc/mean1: 0.1010 2022/09/07 16:37:17 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_1.pth is removed 2022/09/07 16:37:19 - mmengine - INFO - The best checkpoint with 0.1017 acc/top1 at 2 epoch is saved to best_acc/top1_epoch_2.pth. 2022/09/07 16:37:42 - mmengine - INFO - Epoch(train) [3][20/1793] lr: 7.5000e-03 eta: 19:10:00 time: 1.1767 data_time: 0.2003 memory: 10464 grad_norm: 5.4799 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 3.7494 loss: 3.7494 2022/09/07 16:37:54 - mmengine - INFO - Epoch(train) [3][40/1793] lr: 7.5000e-03 eta: 19:08:08 time: 0.5995 data_time: 0.0099 memory: 10464 grad_norm: 5.3730 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.8336 loss: 3.8336 2022/09/07 16:38:11 - mmengine - INFO - Epoch(train) [3][60/1793] lr: 7.5000e-03 eta: 19:08:13 time: 0.8447 data_time: 0.0093 memory: 10464 grad_norm: 5.8729 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.7520 loss: 3.7520 2022/09/07 16:38:27 - mmengine - INFO - Epoch(train) [3][80/1793] lr: 7.5000e-03 eta: 19:08:02 time: 0.8126 data_time: 0.3775 memory: 10464 grad_norm: 5.7188 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.8141 loss: 3.8141 2022/09/07 16:38:40 - mmengine - INFO - Epoch(train) [3][100/1793] lr: 7.5000e-03 eta: 19:06:33 time: 0.6438 data_time: 0.0091 memory: 10464 grad_norm: 5.5299 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.6638 loss: 3.6638 2022/09/07 16:38:50 - mmengine - INFO - Epoch(train) [3][120/1793] lr: 7.5000e-03 eta: 19:03:46 time: 0.4746 data_time: 0.0102 memory: 10464 grad_norm: 5.5227 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.9518 loss: 3.9518 2022/09/07 16:39:03 - mmengine - INFO - Epoch(train) [3][140/1793] lr: 7.5000e-03 eta: 19:02:29 time: 0.6675 data_time: 0.0066 memory: 10464 grad_norm: 5.2909 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 3.4169 loss: 3.4169 2022/09/07 16:39:16 - mmengine - INFO - Epoch(train) [3][160/1793] lr: 7.5000e-03 eta: 19:01:15 time: 0.6713 data_time: 0.0097 memory: 10464 grad_norm: 5.7144 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.6420 loss: 3.6420 2022/09/07 16:39:35 - mmengine - INFO - Epoch(train) [3][180/1793] lr: 7.5000e-03 eta: 19:01:54 time: 0.9156 data_time: 0.0096 memory: 10464 grad_norm: 5.9131 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.6687 loss: 3.6687 2022/09/07 16:39:47 - mmengine - INFO - Epoch(train) [3][200/1793] lr: 7.5000e-03 eta: 19:00:24 time: 0.6355 data_time: 0.0089 memory: 10464 grad_norm: 5.4887 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.7818 loss: 3.7818 2022/09/07 16:40:01 - mmengine - INFO - Epoch(train) [3][220/1793] lr: 7.5000e-03 eta: 18:59:18 time: 0.6857 data_time: 0.0095 memory: 10464 grad_norm: 5.7391 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.7656 loss: 3.7656 2022/09/07 16:40:16 - mmengine - INFO - Epoch(train) [3][240/1793] lr: 7.5000e-03 eta: 18:58:39 time: 0.7450 data_time: 0.0137 memory: 10464 grad_norm: 5.6405 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.7915 loss: 3.7915 2022/09/07 16:40:31 - mmengine - INFO - Epoch(train) [3][260/1793] lr: 7.5000e-03 eta: 18:58:06 time: 0.7586 data_time: 0.0107 memory: 10464 grad_norm: 5.4156 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 3.7612 loss: 3.7612 2022/09/07 16:40:51 - mmengine - INFO - Epoch(train) [3][280/1793] lr: 7.5000e-03 eta: 18:59:12 time: 0.9795 data_time: 0.0090 memory: 10464 grad_norm: 5.5502 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.6740 loss: 3.6740 2022/09/07 16:41:01 - mmengine - INFO - Epoch(train) [3][300/1793] lr: 7.5000e-03 eta: 18:56:48 time: 0.5066 data_time: 0.0092 memory: 10464 grad_norm: 5.7055 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.7916 loss: 3.7916 2022/09/07 16:41:18 - mmengine - INFO - Epoch(train) [3][320/1793] lr: 7.5000e-03 eta: 18:56:55 time: 0.8470 data_time: 0.0099 memory: 10464 grad_norm: 5.9041 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.6940 loss: 3.6940 2022/09/07 16:41:29 - mmengine - INFO - Epoch(train) [3][340/1793] lr: 7.5000e-03 eta: 18:54:45 time: 0.5355 data_time: 0.1430 memory: 10464 grad_norm: 5.9625 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.8324 loss: 3.8324 2022/09/07 16:41:45 - mmengine - INFO - Epoch(train) [3][360/1793] lr: 7.5000e-03 eta: 18:54:35 time: 0.8071 data_time: 0.1376 memory: 10464 grad_norm: 5.4743 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.6826 loss: 3.6826 2022/09/07 16:41:58 - mmengine - INFO - Epoch(train) [3][380/1793] lr: 7.5000e-03 eta: 18:53:13 time: 0.6426 data_time: 0.0099 memory: 10464 grad_norm: 5.3269 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 3.8405 loss: 3.8405 2022/09/07 16:42:09 - mmengine - INFO - Epoch(train) [3][400/1793] lr: 7.5000e-03 eta: 18:51:19 time: 0.5643 data_time: 0.0101 memory: 10464 grad_norm: 5.4886 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.5992 loss: 3.5992 2022/09/07 16:42:16 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 16:42:18 - mmengine - INFO - Epoch(train) [3][420/1793] lr: 7.5000e-03 eta: 18:48:32 time: 0.4391 data_time: 0.0096 memory: 10464 grad_norm: 5.8234 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.8751 loss: 3.8751 2022/09/07 16:42:28 - mmengine - INFO - Epoch(train) [3][440/1793] lr: 7.5000e-03 eta: 18:46:19 time: 0.5153 data_time: 0.0316 memory: 10464 grad_norm: 5.6776 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 3.4792 loss: 3.4792 2022/09/07 16:42:39 - mmengine - INFO - Epoch(train) [3][460/1793] lr: 7.5000e-03 eta: 18:44:12 time: 0.5265 data_time: 0.0090 memory: 10464 grad_norm: 5.6050 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.6853 loss: 3.6853 2022/09/07 16:42:45 - mmengine - INFO - Epoch(train) [3][480/1793] lr: 7.5000e-03 eta: 18:40:47 time: 0.3369 data_time: 0.0103 memory: 10464 grad_norm: 5.7418 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.8385 loss: 3.8385 2022/09/07 16:42:55 - mmengine - INFO - Epoch(train) [3][500/1793] lr: 7.5000e-03 eta: 18:38:30 time: 0.4985 data_time: 0.0058 memory: 10464 grad_norm: 5.7902 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.5543 loss: 3.5543 2022/09/07 16:43:23 - mmengine - INFO - Epoch(train) [3][520/1793] lr: 7.5000e-03 eta: 18:42:20 time: 1.3726 data_time: 0.0091 memory: 10464 grad_norm: 5.5628 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.4165 loss: 3.4165 2022/09/07 16:43:35 - mmengine - INFO - Epoch(train) [3][540/1793] lr: 7.5000e-03 eta: 18:40:51 time: 0.6111 data_time: 0.0103 memory: 10464 grad_norm: 6.0239 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.7828 loss: 3.7828 2022/09/07 16:43:49 - mmengine - INFO - Epoch(train) [3][560/1793] lr: 7.5000e-03 eta: 18:40:02 time: 0.7047 data_time: 0.0091 memory: 10464 grad_norm: 5.8342 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 3.8881 loss: 3.8881 2022/09/07 16:44:07 - mmengine - INFO - Epoch(train) [3][580/1793] lr: 7.5000e-03 eta: 18:40:27 time: 0.8857 data_time: 0.0096 memory: 10464 grad_norm: 5.7667 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.7420 loss: 3.7420 2022/09/07 16:44:17 - mmengine - INFO - Epoch(train) [3][600/1793] lr: 7.5000e-03 eta: 18:38:23 time: 0.5224 data_time: 0.0366 memory: 10464 grad_norm: 5.4354 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 3.7250 loss: 3.7250 2022/09/07 16:44:32 - mmengine - INFO - Epoch(train) [3][620/1793] lr: 7.5000e-03 eta: 18:37:40 time: 0.7181 data_time: 0.0107 memory: 10464 grad_norm: 5.6524 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.8403 loss: 3.8403 2022/09/07 16:44:52 - mmengine - INFO - Epoch(train) [3][640/1793] lr: 7.5000e-03 eta: 18:38:53 time: 1.0027 data_time: 0.0099 memory: 10464 grad_norm: 5.5489 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.6326 loss: 3.6326 2022/09/07 16:44:59 - mmengine - INFO - Epoch(train) [3][660/1793] lr: 7.5000e-03 eta: 18:36:00 time: 0.3955 data_time: 0.0407 memory: 10464 grad_norm: 5.9290 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.6427 loss: 3.6427 2022/09/07 16:45:19 - mmengine - INFO - Epoch(train) [3][680/1793] lr: 7.5000e-03 eta: 18:36:52 time: 0.9528 data_time: 0.0060 memory: 10464 grad_norm: 6.0102 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.6190 loss: 3.6190 2022/09/07 16:45:33 - mmengine - INFO - Epoch(train) [3][700/1793] lr: 7.5000e-03 eta: 18:36:05 time: 0.7068 data_time: 0.0093 memory: 10464 grad_norm: 5.9295 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.7323 loss: 3.7323 2022/09/07 16:45:58 - mmengine - INFO - Epoch(train) [3][720/1793] lr: 7.5000e-03 eta: 18:39:09 time: 1.2876 data_time: 0.0127 memory: 10464 grad_norm: 5.8350 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.5323 loss: 3.5323 2022/09/07 16:46:10 - mmengine - INFO - Epoch(train) [3][740/1793] lr: 7.5000e-03 eta: 18:37:30 time: 0.5759 data_time: 0.0107 memory: 10464 grad_norm: 5.8517 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 3.6481 loss: 3.6481 2022/09/07 16:46:24 - mmengine - INFO - Epoch(train) [3][760/1793] lr: 7.5000e-03 eta: 18:36:43 time: 0.7066 data_time: 0.0080 memory: 10464 grad_norm: 5.6523 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 3.3727 loss: 3.3727 2022/09/07 16:46:43 - mmengine - INFO - Epoch(train) [3][780/1793] lr: 7.5000e-03 eta: 18:37:26 time: 0.9356 data_time: 0.0119 memory: 10464 grad_norm: 5.5569 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.7470 loss: 3.7470 2022/09/07 16:47:00 - mmengine - INFO - Epoch(train) [3][800/1793] lr: 7.5000e-03 eta: 18:37:31 time: 0.8399 data_time: 0.0090 memory: 10464 grad_norm: 5.9155 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.5980 loss: 3.5980 2022/09/07 16:47:17 - mmengine - INFO - Epoch(train) [3][820/1793] lr: 7.5000e-03 eta: 18:37:45 time: 0.8633 data_time: 0.0091 memory: 10464 grad_norm: 5.8510 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.5072 loss: 3.5072 2022/09/07 16:47:29 - mmengine - INFO - Epoch(train) [3][840/1793] lr: 7.5000e-03 eta: 18:36:13 time: 0.5880 data_time: 0.0097 memory: 10464 grad_norm: 5.9149 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.6254 loss: 3.6254 2022/09/07 16:47:40 - mmengine - INFO - Epoch(train) [3][860/1793] lr: 7.5000e-03 eta: 18:34:42 time: 0.5904 data_time: 0.0103 memory: 10464 grad_norm: 5.5727 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.5752 loss: 3.5752 2022/09/07 16:47:57 - mmengine - INFO - Epoch(train) [3][880/1793] lr: 7.5000e-03 eta: 18:34:51 time: 0.8478 data_time: 0.3118 memory: 10464 grad_norm: 6.1692 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.9150 loss: 3.9150 2022/09/07 16:48:15 - mmengine - INFO - Epoch(train) [3][900/1793] lr: 7.5000e-03 eta: 18:35:19 time: 0.9013 data_time: 0.0094 memory: 10464 grad_norm: 5.6428 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.9031 loss: 3.9031 2022/09/07 16:48:29 - mmengine - INFO - Epoch(train) [3][920/1793] lr: 7.5000e-03 eta: 18:34:20 time: 0.6708 data_time: 0.0093 memory: 10464 grad_norm: 5.8033 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.6905 loss: 3.6905 2022/09/07 16:48:41 - mmengine - INFO - Epoch(train) [3][940/1793] lr: 7.5000e-03 eta: 18:32:55 time: 0.6002 data_time: 0.2047 memory: 10464 grad_norm: 6.6156 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.6531 loss: 3.6531 2022/09/07 16:48:48 - mmengine - INFO - Epoch(train) [3][960/1793] lr: 7.5000e-03 eta: 18:30:05 time: 0.3748 data_time: 0.0456 memory: 10464 grad_norm: 5.8679 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.7057 loss: 3.7057 2022/09/07 16:48:58 - mmengine - INFO - Epoch(train) [3][980/1793] lr: 7.5000e-03 eta: 18:28:05 time: 0.5013 data_time: 0.0061 memory: 10464 grad_norm: 6.5765 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 3.6264 loss: 3.6264 2022/09/07 16:49:06 - mmengine - INFO - Epoch(train) [3][1000/1793] lr: 7.5000e-03 eta: 18:25:20 time: 0.3780 data_time: 0.0609 memory: 10464 grad_norm: 5.6903 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.4303 loss: 3.4303 2022/09/07 16:49:12 - mmengine - INFO - Epoch(train) [3][1020/1793] lr: 7.5000e-03 eta: 18:22:13 time: 0.3167 data_time: 0.1191 memory: 10464 grad_norm: 5.8959 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.6510 loss: 3.6510 2022/09/07 16:49:20 - mmengine - INFO - Epoch(train) [3][1040/1793] lr: 7.5000e-03 eta: 18:19:32 time: 0.3805 data_time: 0.0643 memory: 10464 grad_norm: 5.8019 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.4607 loss: 3.4607 2022/09/07 16:49:27 - mmengine - INFO - Epoch(train) [3][1060/1793] lr: 7.5000e-03 eta: 18:16:42 time: 0.3536 data_time: 0.0059 memory: 10464 grad_norm: 6.9711 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.4073 loss: 3.4073 2022/09/07 16:49:38 - mmengine - INFO - Epoch(train) [3][1080/1793] lr: 7.5000e-03 eta: 18:15:07 time: 0.5578 data_time: 0.0092 memory: 10464 grad_norm: 6.3025 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.6144 loss: 3.6144 2022/09/07 16:49:49 - mmengine - INFO - Epoch(train) [3][1100/1793] lr: 7.5000e-03 eta: 18:13:36 time: 0.5635 data_time: 0.2202 memory: 10464 grad_norm: 6.7072 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.6018 loss: 3.6018 2022/09/07 16:50:05 - mmengine - INFO - Epoch(train) [3][1120/1793] lr: 7.5000e-03 eta: 18:13:22 time: 0.7768 data_time: 0.0089 memory: 10464 grad_norm: 5.5539 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.5700 loss: 3.5700 2022/09/07 16:50:24 - mmengine - INFO - Epoch(train) [3][1140/1793] lr: 7.5000e-03 eta: 18:14:07 time: 0.9397 data_time: 0.0099 memory: 10464 grad_norm: 5.6966 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.6363 loss: 3.6363 2022/09/07 16:50:35 - mmengine - INFO - Epoch(train) [3][1160/1793] lr: 7.5000e-03 eta: 18:12:35 time: 0.5594 data_time: 0.0100 memory: 10464 grad_norm: 5.8640 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.2802 loss: 3.2802 2022/09/07 16:50:50 - mmengine - INFO - Epoch(train) [3][1180/1793] lr: 7.5000e-03 eta: 18:12:10 time: 0.7449 data_time: 0.0092 memory: 10464 grad_norm: 6.0807 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.5118 loss: 3.5118 2022/09/07 16:51:09 - mmengine - INFO - Epoch(train) [3][1200/1793] lr: 7.5000e-03 eta: 18:12:59 time: 0.9556 data_time: 0.0113 memory: 10464 grad_norm: 5.6043 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.8483 loss: 3.8483 2022/09/07 16:51:21 - mmengine - INFO - Epoch(train) [3][1220/1793] lr: 7.5000e-03 eta: 18:11:50 time: 0.6196 data_time: 0.0088 memory: 10464 grad_norm: 6.1994 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.5608 loss: 3.5608 2022/09/07 16:51:38 - mmengine - INFO - Epoch(train) [3][1240/1793] lr: 7.5000e-03 eta: 18:11:54 time: 0.8282 data_time: 0.0099 memory: 10464 grad_norm: 5.6523 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.3930 loss: 3.3930 2022/09/07 16:51:47 - mmengine - INFO - Epoch(train) [3][1260/1793] lr: 7.5000e-03 eta: 18:09:52 time: 0.4683 data_time: 0.0907 memory: 10464 grad_norm: 6.2888 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.4736 loss: 3.4736 2022/09/07 16:52:12 - mmengine - INFO - Epoch(train) [3][1280/1793] lr: 7.5000e-03 eta: 18:12:16 time: 1.2266 data_time: 0.1190 memory: 10464 grad_norm: 5.8428 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 3.4566 loss: 3.4566 2022/09/07 16:52:24 - mmengine - INFO - Epoch(train) [3][1300/1793] lr: 7.5000e-03 eta: 18:11:08 time: 0.6215 data_time: 0.1844 memory: 10464 grad_norm: 5.8364 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.6814 loss: 3.6814 2022/09/07 16:52:35 - mmengine - INFO - Epoch(train) [3][1320/1793] lr: 7.5000e-03 eta: 18:09:38 time: 0.5585 data_time: 0.2232 memory: 10464 grad_norm: 6.0351 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.4861 loss: 3.4861 2022/09/07 16:52:50 - mmengine - INFO - Epoch(train) [3][1340/1793] lr: 7.5000e-03 eta: 18:09:04 time: 0.7171 data_time: 0.0102 memory: 10464 grad_norm: 5.7126 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.5646 loss: 3.5646 2022/09/07 16:53:08 - mmengine - INFO - Epoch(train) [3][1360/1793] lr: 7.5000e-03 eta: 18:09:33 time: 0.9009 data_time: 0.4179 memory: 10464 grad_norm: 5.6868 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.5320 loss: 3.5320 2022/09/07 16:53:22 - mmengine - INFO - Epoch(train) [3][1380/1793] lr: 7.5000e-03 eta: 18:08:54 time: 0.7017 data_time: 0.4008 memory: 10464 grad_norm: 6.0280 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.3975 loss: 3.3975 2022/09/07 16:53:42 - mmengine - INFO - Epoch(train) [3][1400/1793] lr: 7.5000e-03 eta: 18:10:03 time: 1.0196 data_time: 0.0092 memory: 10464 grad_norm: 5.6593 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.4176 loss: 3.4176 2022/09/07 16:53:52 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 16:53:57 - mmengine - INFO - Epoch(train) [3][1420/1793] lr: 7.5000e-03 eta: 18:09:30 time: 0.7212 data_time: 0.0093 memory: 10464 grad_norm: 5.7809 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.4644 loss: 3.4644 2022/09/07 16:54:07 - mmengine - INFO - Epoch(train) [3][1440/1793] lr: 7.5000e-03 eta: 18:07:58 time: 0.5466 data_time: 0.0086 memory: 10464 grad_norm: 6.2758 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.2643 loss: 3.2643 2022/09/07 16:54:19 - mmengine - INFO - Epoch(train) [3][1460/1793] lr: 7.5000e-03 eta: 18:06:39 time: 0.5815 data_time: 0.0102 memory: 10464 grad_norm: 6.2759 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.5232 loss: 3.5232 2022/09/07 16:54:38 - mmengine - INFO - Epoch(train) [3][1480/1793] lr: 7.5000e-03 eta: 18:07:23 time: 0.9477 data_time: 0.0093 memory: 10464 grad_norm: 6.0045 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.5630 loss: 3.5630 2022/09/07 16:54:51 - mmengine - INFO - Epoch(train) [3][1500/1793] lr: 7.5000e-03 eta: 18:06:27 time: 0.6502 data_time: 0.1736 memory: 10464 grad_norm: 6.0577 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.7562 loss: 3.7562 2022/09/07 16:55:09 - mmengine - INFO - Epoch(train) [3][1520/1793] lr: 7.5000e-03 eta: 18:06:50 time: 0.8871 data_time: 0.0087 memory: 10464 grad_norm: 5.9361 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.6869 loss: 3.6869 2022/09/07 16:55:22 - mmengine - INFO - Epoch(train) [3][1540/1793] lr: 7.5000e-03 eta: 18:06:02 time: 0.6718 data_time: 0.0094 memory: 10464 grad_norm: 5.9589 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.7197 loss: 3.7197 2022/09/07 16:55:31 - mmengine - INFO - Epoch(train) [3][1560/1793] lr: 7.5000e-03 eta: 18:03:56 time: 0.4330 data_time: 0.0087 memory: 10464 grad_norm: 6.0017 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.4933 loss: 3.4933 2022/09/07 16:55:39 - mmengine - INFO - Epoch(train) [3][1580/1793] lr: 7.5000e-03 eta: 18:01:43 time: 0.4100 data_time: 0.0067 memory: 10464 grad_norm: 5.9759 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.3000 loss: 3.3000 2022/09/07 16:55:47 - mmengine - INFO - Epoch(train) [3][1600/1793] lr: 7.5000e-03 eta: 17:59:22 time: 0.3842 data_time: 0.1480 memory: 10464 grad_norm: 6.0594 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 3.5304 loss: 3.5304 2022/09/07 16:55:55 - mmengine - INFO - Epoch(train) [3][1620/1793] lr: 7.5000e-03 eta: 17:57:18 time: 0.4326 data_time: 0.1783 memory: 10464 grad_norm: 5.8228 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 3.1742 loss: 3.1742 2022/09/07 16:56:01 - mmengine - INFO - Epoch(train) [3][1640/1793] lr: 7.5000e-03 eta: 17:54:23 time: 0.2685 data_time: 0.0553 memory: 10464 grad_norm: 5.8168 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.6066 loss: 3.6066 2022/09/07 16:56:10 - mmengine - INFO - Epoch(train) [3][1660/1793] lr: 7.5000e-03 eta: 17:52:34 time: 0.4752 data_time: 0.0060 memory: 10464 grad_norm: 6.2062 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 3.2232 loss: 3.2232 2022/09/07 16:56:30 - mmengine - INFO - Epoch(train) [3][1680/1793] lr: 7.5000e-03 eta: 17:53:23 time: 0.9626 data_time: 0.0094 memory: 10464 grad_norm: 6.1092 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.3538 loss: 3.3538 2022/09/07 16:56:42 - mmengine - INFO - Epoch(train) [3][1700/1793] lr: 7.5000e-03 eta: 17:52:26 time: 0.6302 data_time: 0.0095 memory: 10464 grad_norm: 5.8604 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.4415 loss: 3.4415 2022/09/07 16:56:56 - mmengine - INFO - Epoch(train) [3][1720/1793] lr: 7.5000e-03 eta: 17:51:49 time: 0.6953 data_time: 0.0099 memory: 10464 grad_norm: 5.7863 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 3.2576 loss: 3.2576 2022/09/07 16:57:18 - mmengine - INFO - Epoch(train) [3][1740/1793] lr: 7.5000e-03 eta: 17:53:22 time: 1.1031 data_time: 0.0108 memory: 10464 grad_norm: 5.8770 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.3503 loss: 3.3503 2022/09/07 16:57:26 - mmengine - INFO - Epoch(train) [3][1760/1793] lr: 7.5000e-03 eta: 17:51:14 time: 0.4069 data_time: 0.1213 memory: 10464 grad_norm: 6.0861 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.6066 loss: 3.6066 2022/09/07 16:57:33 - mmengine - INFO - Epoch(train) [3][1780/1793] lr: 7.5000e-03 eta: 17:48:47 time: 0.3450 data_time: 0.0053 memory: 10464 grad_norm: 5.9813 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.3620 loss: 3.3620 2022/09/07 16:57:42 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 16:57:42 - mmengine - INFO - Epoch(train) [3][1793/1793] lr: 7.5000e-03 eta: 17:48:47 time: 0.5512 data_time: 0.0088 memory: 10464 grad_norm: 6.3195 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.6341 loss: 3.6341 2022/09/07 16:57:42 - mmengine - INFO - Saving checkpoint at 3 epochs 2022/09/07 16:57:46 - mmengine - INFO - Epoch(val) [3][20/241] eta: 0:00:19 time: 0.0873 data_time: 0.0245 memory: 1482 2022/09/07 16:57:47 - mmengine - INFO - Epoch(val) [3][40/241] eta: 0:00:13 time: 0.0692 data_time: 0.0053 memory: 1482 2022/09/07 16:57:49 - mmengine - INFO - Epoch(val) [3][60/241] eta: 0:00:14 time: 0.0809 data_time: 0.0053 memory: 1482 2022/09/07 16:57:50 - mmengine - INFO - Epoch(val) [3][80/241] eta: 0:00:11 time: 0.0695 data_time: 0.0053 memory: 1482 2022/09/07 16:57:52 - mmengine - INFO - Epoch(val) [3][100/241] eta: 0:00:10 time: 0.0753 data_time: 0.0049 memory: 1482 2022/09/07 16:57:53 - mmengine - INFO - Epoch(val) [3][120/241] eta: 0:00:09 time: 0.0744 data_time: 0.0053 memory: 1482 2022/09/07 16:57:55 - mmengine - INFO - Epoch(val) [3][140/241] eta: 0:00:06 time: 0.0636 data_time: 0.0059 memory: 1482 2022/09/07 16:57:57 - mmengine - INFO - Epoch(val) [3][160/241] eta: 0:00:07 time: 0.0879 data_time: 0.0048 memory: 1482 2022/09/07 16:57:58 - mmengine - INFO - Epoch(val) [3][180/241] eta: 0:00:04 time: 0.0663 data_time: 0.0070 memory: 1482 2022/09/07 16:57:59 - mmengine - INFO - Epoch(val) [3][200/241] eta: 0:00:03 time: 0.0763 data_time: 0.0047 memory: 1482 2022/09/07 16:58:01 - mmengine - INFO - Epoch(val) [3][220/241] eta: 0:00:01 time: 0.0648 data_time: 0.0048 memory: 1482 2022/09/07 16:58:02 - mmengine - INFO - Epoch(val) [3][240/241] eta: 0:00:00 time: 0.0709 data_time: 0.0047 memory: 1482 2022/09/07 16:58:03 - mmengine - INFO - Epoch(val) [3][241/241] acc/top1: 0.1422 acc/top5: 0.3890 acc/mean1: 0.1330 2022/09/07 16:58:03 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_2.pth is removed 2022/09/07 16:58:04 - mmengine - INFO - The best checkpoint with 0.1422 acc/top1 at 3 epoch is saved to best_acc/top1_epoch_3.pth. 2022/09/07 16:58:20 - mmengine - INFO - Epoch(train) [4][20/1793] lr: 7.5000e-03 eta: 17:45:54 time: 0.7819 data_time: 0.2566 memory: 10464 grad_norm: 5.4980 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.4955 loss: 3.4955 2022/09/07 16:58:35 - mmengine - INFO - Epoch(train) [4][40/1793] lr: 7.5000e-03 eta: 17:45:40 time: 0.7603 data_time: 0.0087 memory: 10464 grad_norm: 6.0743 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.3844 loss: 3.3844 2022/09/07 16:58:45 - mmengine - INFO - Epoch(train) [4][60/1793] lr: 7.5000e-03 eta: 17:44:07 time: 0.5102 data_time: 0.0136 memory: 10464 grad_norm: 6.1148 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.1744 loss: 3.1744 2022/09/07 16:58:54 - mmengine - INFO - Epoch(train) [4][80/1793] lr: 7.5000e-03 eta: 17:42:17 time: 0.4506 data_time: 0.0089 memory: 10464 grad_norm: 5.7679 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.4516 loss: 3.4516 2022/09/07 16:59:08 - mmengine - INFO - Epoch(train) [4][100/1793] lr: 7.5000e-03 eta: 17:41:43 time: 0.6939 data_time: 0.0604 memory: 10464 grad_norm: 5.9508 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.5268 loss: 3.5268 2022/09/07 16:59:20 - mmengine - INFO - Epoch(train) [4][120/1793] lr: 7.5000e-03 eta: 17:40:43 time: 0.6098 data_time: 0.1353 memory: 10464 grad_norm: 5.8461 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.1655 loss: 3.1655 2022/09/07 16:59:33 - mmengine - INFO - Epoch(train) [4][140/1793] lr: 7.5000e-03 eta: 17:39:56 time: 0.6515 data_time: 0.0112 memory: 10464 grad_norm: 6.0947 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.3102 loss: 3.3102 2022/09/07 16:59:54 - mmengine - INFO - Epoch(train) [4][160/1793] lr: 7.5000e-03 eta: 17:41:03 time: 1.0261 data_time: 0.0096 memory: 10464 grad_norm: 5.7909 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.4601 loss: 3.4601 2022/09/07 17:00:04 - mmengine - INFO - Epoch(train) [4][180/1793] lr: 7.5000e-03 eta: 17:39:34 time: 0.5155 data_time: 0.0093 memory: 10464 grad_norm: 6.2884 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 3.3453 loss: 3.3453 2022/09/07 17:00:13 - mmengine - INFO - Epoch(train) [4][200/1793] lr: 7.5000e-03 eta: 17:37:43 time: 0.4363 data_time: 0.0083 memory: 10464 grad_norm: 5.8611 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 3.5657 loss: 3.5657 2022/09/07 17:00:27 - mmengine - INFO - Epoch(train) [4][220/1793] lr: 7.5000e-03 eta: 17:37:14 time: 0.7101 data_time: 0.0988 memory: 10464 grad_norm: 6.6802 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.2043 loss: 3.2043 2022/09/07 17:00:44 - mmengine - INFO - Epoch(train) [4][240/1793] lr: 7.5000e-03 eta: 17:37:21 time: 0.8290 data_time: 0.0090 memory: 10464 grad_norm: 6.5492 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.3640 loss: 3.3640 2022/09/07 17:00:54 - mmengine - INFO - Epoch(train) [4][260/1793] lr: 7.5000e-03 eta: 17:35:59 time: 0.5274 data_time: 0.0969 memory: 10464 grad_norm: 6.2898 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.5089 loss: 3.5089 2022/09/07 17:01:11 - mmengine - INFO - Epoch(train) [4][280/1793] lr: 7.5000e-03 eta: 17:36:07 time: 0.8329 data_time: 0.0085 memory: 10464 grad_norm: 6.5785 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.2902 loss: 3.2902 2022/09/07 17:01:20 - mmengine - INFO - Epoch(train) [4][300/1793] lr: 7.5000e-03 eta: 17:34:27 time: 0.4673 data_time: 0.0092 memory: 10464 grad_norm: 6.2893 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.6172 loss: 3.6172 2022/09/07 17:01:37 - mmengine - INFO - Epoch(train) [4][320/1793] lr: 7.5000e-03 eta: 17:34:38 time: 0.8435 data_time: 0.0057 memory: 10464 grad_norm: 6.6128 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 3.1935 loss: 3.1935 2022/09/07 17:01:52 - mmengine - INFO - Epoch(train) [4][340/1793] lr: 7.5000e-03 eta: 17:34:29 time: 0.7741 data_time: 0.0110 memory: 10464 grad_norm: 6.3550 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 3.1254 loss: 3.1254 2022/09/07 17:02:02 - mmengine - INFO - Epoch(train) [4][360/1793] lr: 7.5000e-03 eta: 17:32:55 time: 0.4824 data_time: 0.0876 memory: 10464 grad_norm: 5.9887 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.7360 loss: 3.7360 2022/09/07 17:02:13 - mmengine - INFO - Epoch(train) [4][380/1793] lr: 7.5000e-03 eta: 17:31:45 time: 0.5662 data_time: 0.0068 memory: 10464 grad_norm: 6.2801 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.4125 loss: 3.4125 2022/09/07 17:02:22 - mmengine - INFO - Epoch(train) [4][400/1793] lr: 7.5000e-03 eta: 17:29:55 time: 0.4237 data_time: 0.0178 memory: 10464 grad_norm: 6.8972 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.4103 loss: 3.4103 2022/09/07 17:02:31 - mmengine - INFO - Epoch(train) [4][420/1793] lr: 7.5000e-03 eta: 17:28:11 time: 0.4431 data_time: 0.1437 memory: 10464 grad_norm: 6.7132 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.2585 loss: 3.2585 2022/09/07 17:02:38 - mmengine - INFO - Epoch(train) [4][440/1793] lr: 7.5000e-03 eta: 17:26:03 time: 0.3568 data_time: 0.0091 memory: 10464 grad_norm: 9.0867 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.5181 loss: 3.5181 2022/09/07 17:02:50 - mmengine - INFO - Epoch(train) [4][460/1793] lr: 7.5000e-03 eta: 17:25:05 time: 0.5990 data_time: 0.0079 memory: 10464 grad_norm: 7.0319 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.4737 loss: 3.4737 2022/09/07 17:03:02 - mmengine - INFO - Epoch(train) [4][480/1793] lr: 7.5000e-03 eta: 17:24:05 time: 0.5910 data_time: 0.0101 memory: 10464 grad_norm: 6.0965 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.1392 loss: 3.1392 2022/09/07 17:03:17 - mmengine - INFO - Epoch(train) [4][500/1793] lr: 7.5000e-03 eta: 17:23:59 time: 0.7796 data_time: 0.0090 memory: 10464 grad_norm: 6.1596 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.5557 loss: 3.5557 2022/09/07 17:03:32 - mmengine - INFO - Epoch(train) [4][520/1793] lr: 7.5000e-03 eta: 17:23:47 time: 0.7597 data_time: 0.0095 memory: 10464 grad_norm: 6.5901 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.4739 loss: 3.4739 2022/09/07 17:03:53 - mmengine - INFO - Epoch(train) [4][540/1793] lr: 7.5000e-03 eta: 17:24:46 time: 1.0098 data_time: 0.0104 memory: 10464 grad_norm: 6.1193 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.5946 loss: 3.5946 2022/09/07 17:04:03 - mmengine - INFO - Epoch(train) [4][560/1793] lr: 7.5000e-03 eta: 17:23:20 time: 0.4966 data_time: 0.0104 memory: 10464 grad_norm: 6.1907 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.3617 loss: 3.3617 2022/09/07 17:04:15 - mmengine - INFO - Epoch(train) [4][580/1793] lr: 7.5000e-03 eta: 17:22:29 time: 0.6188 data_time: 0.0068 memory: 10464 grad_norm: 6.1871 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.7557 loss: 3.7557 2022/09/07 17:04:24 - mmengine - INFO - Epoch(train) [4][600/1793] lr: 7.5000e-03 eta: 17:20:56 time: 0.4690 data_time: 0.0963 memory: 10464 grad_norm: 6.4186 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.3880 loss: 3.3880 2022/09/07 17:04:49 - mmengine - INFO - Epoch(train) [4][620/1793] lr: 7.5000e-03 eta: 17:22:56 time: 1.2281 data_time: 0.7504 memory: 10464 grad_norm: 6.6650 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.2820 loss: 3.2820 2022/09/07 17:04:49 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 17:04:59 - mmengine - INFO - Epoch(train) [4][640/1793] lr: 7.5000e-03 eta: 17:21:35 time: 0.5095 data_time: 0.1815 memory: 10464 grad_norm: 6.4257 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.8626 loss: 3.8626 2022/09/07 17:05:12 - mmengine - INFO - Epoch(train) [4][660/1793] lr: 7.5000e-03 eta: 17:20:56 time: 0.6617 data_time: 0.0095 memory: 10464 grad_norm: 5.7738 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 3.5873 loss: 3.5873 2022/09/07 17:05:22 - mmengine - INFO - Epoch(train) [4][680/1793] lr: 7.5000e-03 eta: 17:19:29 time: 0.4879 data_time: 0.0092 memory: 10464 grad_norm: 6.6123 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 3.3813 loss: 3.3813 2022/09/07 17:05:39 - mmengine - INFO - Epoch(train) [4][700/1793] lr: 7.5000e-03 eta: 17:19:38 time: 0.8316 data_time: 0.0091 memory: 10464 grad_norm: 5.7434 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 3.4569 loss: 3.4569 2022/09/07 17:05:50 - mmengine - INFO - Epoch(train) [4][720/1793] lr: 7.5000e-03 eta: 17:18:37 time: 0.5780 data_time: 0.0094 memory: 10464 grad_norm: 6.1573 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.4530 loss: 3.4530 2022/09/07 17:06:01 - mmengine - INFO - Epoch(train) [4][740/1793] lr: 7.5000e-03 eta: 17:17:26 time: 0.5410 data_time: 0.0086 memory: 10464 grad_norm: 6.1501 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.2876 loss: 3.2876 2022/09/07 17:06:12 - mmengine - INFO - Epoch(train) [4][760/1793] lr: 7.5000e-03 eta: 17:16:11 time: 0.5250 data_time: 0.0102 memory: 10464 grad_norm: 6.9634 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.4167 loss: 3.4167 2022/09/07 17:06:31 - mmengine - INFO - Epoch(train) [4][780/1793] lr: 7.5000e-03 eta: 17:16:55 time: 0.9590 data_time: 0.0098 memory: 10464 grad_norm: 6.6021 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 3.5496 loss: 3.5496 2022/09/07 17:06:40 - mmengine - INFO - Epoch(train) [4][800/1793] lr: 7.5000e-03 eta: 17:15:26 time: 0.4715 data_time: 0.2430 memory: 10464 grad_norm: 6.2095 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 3.2038 loss: 3.2038 2022/09/07 17:06:55 - mmengine - INFO - Epoch(train) [4][820/1793] lr: 7.5000e-03 eta: 17:15:10 time: 0.7428 data_time: 0.1230 memory: 10464 grad_norm: 5.9211 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.3427 loss: 3.3427 2022/09/07 17:07:12 - mmengine - INFO - Epoch(train) [4][840/1793] lr: 7.5000e-03 eta: 17:15:21 time: 0.8404 data_time: 0.0094 memory: 10464 grad_norm: 6.9605 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.6078 loss: 3.6078 2022/09/07 17:07:20 - mmengine - INFO - Epoch(train) [4][860/1793] lr: 7.5000e-03 eta: 17:13:39 time: 0.4158 data_time: 0.0574 memory: 10464 grad_norm: 6.8351 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.0206 loss: 3.0206 2022/09/07 17:07:30 - mmengine - INFO - Epoch(train) [4][880/1793] lr: 7.5000e-03 eta: 17:12:11 time: 0.4717 data_time: 0.1410 memory: 10464 grad_norm: 6.8099 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.3737 loss: 3.3737 2022/09/07 17:07:42 - mmengine - INFO - Epoch(train) [4][900/1793] lr: 7.5000e-03 eta: 17:11:20 time: 0.6040 data_time: 0.0077 memory: 10464 grad_norm: 6.8899 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.3242 loss: 3.3242 2022/09/07 17:07:58 - mmengine - INFO - Epoch(train) [4][920/1793] lr: 7.5000e-03 eta: 17:11:22 time: 0.8088 data_time: 0.0096 memory: 10464 grad_norm: 5.9171 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.6463 loss: 3.6463 2022/09/07 17:08:11 - mmengine - INFO - Epoch(train) [4][940/1793] lr: 7.5000e-03 eta: 17:10:46 time: 0.6621 data_time: 0.0108 memory: 10464 grad_norm: 7.0655 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 3.1295 loss: 3.1295 2022/09/07 17:08:23 - mmengine - INFO - Epoch(train) [4][960/1793] lr: 7.5000e-03 eta: 17:09:50 time: 0.5854 data_time: 0.0187 memory: 10464 grad_norm: 6.2856 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.0649 loss: 3.0649 2022/09/07 17:08:36 - mmengine - INFO - Epoch(train) [4][980/1793] lr: 7.5000e-03 eta: 17:09:19 time: 0.6785 data_time: 0.0088 memory: 10464 grad_norm: 6.2389 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.4421 loss: 3.4421 2022/09/07 17:08:50 - mmengine - INFO - Epoch(train) [4][1000/1793] lr: 7.5000e-03 eta: 17:08:47 time: 0.6779 data_time: 0.0096 memory: 10464 grad_norm: 6.0402 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.2255 loss: 3.2255 2022/09/07 17:09:03 - mmengine - INFO - Epoch(train) [4][1020/1793] lr: 7.5000e-03 eta: 17:08:09 time: 0.6519 data_time: 0.0095 memory: 10464 grad_norm: 6.6826 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.3425 loss: 3.3425 2022/09/07 17:09:11 - mmengine - INFO - Epoch(train) [4][1040/1793] lr: 7.5000e-03 eta: 17:06:30 time: 0.4132 data_time: 0.0085 memory: 10464 grad_norm: 5.9302 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 3.3618 loss: 3.3618 2022/09/07 17:09:19 - mmengine - INFO - Epoch(train) [4][1060/1793] lr: 7.5000e-03 eta: 17:04:46 time: 0.3974 data_time: 0.0065 memory: 10464 grad_norm: 6.3965 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.6975 loss: 3.6975 2022/09/07 17:09:31 - mmengine - INFO - Epoch(train) [4][1080/1793] lr: 7.5000e-03 eta: 17:03:46 time: 0.5639 data_time: 0.0084 memory: 10464 grad_norm: 6.6101 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.3132 loss: 3.3132 2022/09/07 17:09:37 - mmengine - INFO - Epoch(train) [4][1100/1793] lr: 7.5000e-03 eta: 17:01:45 time: 0.3218 data_time: 0.0088 memory: 10464 grad_norm: 7.8946 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.7119 loss: 3.7119 2022/09/07 17:09:50 - mmengine - INFO - Epoch(train) [4][1120/1793] lr: 7.5000e-03 eta: 17:01:05 time: 0.6410 data_time: 0.0072 memory: 10464 grad_norm: 6.4987 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 3.3537 loss: 3.3537 2022/09/07 17:10:01 - mmengine - INFO - Epoch(train) [4][1140/1793] lr: 7.5000e-03 eta: 17:00:05 time: 0.5575 data_time: 0.0478 memory: 10464 grad_norm: 6.3273 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.4198 loss: 3.4198 2022/09/07 17:10:13 - mmengine - INFO - Epoch(train) [4][1160/1793] lr: 7.5000e-03 eta: 16:59:21 time: 0.6226 data_time: 0.0108 memory: 10464 grad_norm: 6.2368 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.4093 loss: 3.4093 2022/09/07 17:10:27 - mmengine - INFO - Epoch(train) [4][1180/1793] lr: 7.5000e-03 eta: 16:58:52 time: 0.6781 data_time: 0.0095 memory: 10464 grad_norm: 6.2793 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.1400 loss: 3.1400 2022/09/07 17:10:40 - mmengine - INFO - Epoch(train) [4][1200/1793] lr: 7.5000e-03 eta: 16:58:18 time: 0.6607 data_time: 0.0102 memory: 10464 grad_norm: 6.0635 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 3.2773 loss: 3.2773 2022/09/07 17:10:54 - mmengine - INFO - Epoch(train) [4][1220/1793] lr: 7.5000e-03 eta: 16:57:50 time: 0.6804 data_time: 0.4020 memory: 10464 grad_norm: 6.1562 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.3346 loss: 3.3346 2022/09/07 17:11:02 - mmengine - INFO - Epoch(train) [4][1240/1793] lr: 7.5000e-03 eta: 16:56:07 time: 0.3868 data_time: 0.1174 memory: 10464 grad_norm: 5.8688 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.2781 loss: 3.2781 2022/09/07 17:11:22 - mmengine - INFO - Epoch(train) [4][1260/1793] lr: 7.5000e-03 eta: 16:57:02 time: 1.0116 data_time: 0.0063 memory: 10464 grad_norm: 6.1133 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 3.3986 loss: 3.3986 2022/09/07 17:11:32 - mmengine - INFO - Epoch(train) [4][1280/1793] lr: 7.5000e-03 eta: 16:55:54 time: 0.5205 data_time: 0.0103 memory: 10464 grad_norm: 6.3267 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.3817 loss: 3.3817 2022/09/07 17:11:44 - mmengine - INFO - Epoch(train) [4][1300/1793] lr: 7.5000e-03 eta: 16:55:07 time: 0.6050 data_time: 0.0084 memory: 10464 grad_norm: 6.5360 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.2813 loss: 3.2813 2022/09/07 17:11:56 - mmengine - INFO - Epoch(train) [4][1320/1793] lr: 7.5000e-03 eta: 16:54:14 time: 0.5806 data_time: 0.0094 memory: 10464 grad_norm: 6.7759 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9799 loss: 2.9799 2022/09/07 17:12:12 - mmengine - INFO - Epoch(train) [4][1340/1793] lr: 7.5000e-03 eta: 16:54:12 time: 0.7830 data_time: 0.0094 memory: 10464 grad_norm: 6.6538 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.2780 loss: 3.2780 2022/09/07 17:12:21 - mmengine - INFO - Epoch(train) [4][1360/1793] lr: 7.5000e-03 eta: 16:52:47 time: 0.4502 data_time: 0.0280 memory: 10464 grad_norm: 6.6210 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.2466 loss: 3.2466 2022/09/07 17:12:35 - mmengine - INFO - Epoch(train) [4][1380/1793] lr: 7.5000e-03 eta: 16:52:36 time: 0.7466 data_time: 0.0066 memory: 10464 grad_norm: 6.3173 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.1261 loss: 3.1261 2022/09/07 17:12:50 - mmengine - INFO - Epoch(train) [4][1400/1793] lr: 7.5000e-03 eta: 16:52:21 time: 0.7303 data_time: 0.0195 memory: 10464 grad_norm: 6.2983 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.5532 loss: 3.5532 2022/09/07 17:13:10 - mmengine - INFO - Epoch(train) [4][1420/1793] lr: 7.5000e-03 eta: 16:53:07 time: 0.9830 data_time: 0.0097 memory: 10464 grad_norm: 6.1111 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.4571 loss: 3.4571 2022/09/07 17:13:19 - mmengine - INFO - Epoch(train) [4][1440/1793] lr: 7.5000e-03 eta: 16:51:51 time: 0.4815 data_time: 0.0090 memory: 10464 grad_norm: 6.5058 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.2724 loss: 3.2724 2022/09/07 17:13:31 - mmengine - INFO - Epoch(train) [4][1460/1793] lr: 7.5000e-03 eta: 16:51:05 time: 0.6021 data_time: 0.0074 memory: 10464 grad_norm: 6.7304 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.2050 loss: 3.2050 2022/09/07 17:13:47 - mmengine - INFO - Epoch(train) [4][1480/1793] lr: 7.5000e-03 eta: 16:50:58 time: 0.7662 data_time: 0.0104 memory: 10464 grad_norm: 6.3940 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.8220 loss: 2.8220 2022/09/07 17:14:00 - mmengine - INFO - Epoch(train) [4][1500/1793] lr: 7.5000e-03 eta: 16:50:22 time: 0.6410 data_time: 0.0092 memory: 10464 grad_norm: 6.6600 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.1046 loss: 3.1046 2022/09/07 17:14:09 - mmengine - INFO - Epoch(train) [4][1520/1793] lr: 7.5000e-03 eta: 16:49:03 time: 0.4650 data_time: 0.1021 memory: 10464 grad_norm: 6.5930 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.3229 loss: 3.3229 2022/09/07 17:14:16 - mmengine - INFO - Epoch(train) [4][1540/1793] lr: 7.5000e-03 eta: 16:47:17 time: 0.3505 data_time: 0.0067 memory: 10464 grad_norm: 5.9717 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 3.3382 loss: 3.3382 2022/09/07 17:14:22 - mmengine - INFO - Epoch(train) [4][1560/1793] lr: 7.5000e-03 eta: 16:45:25 time: 0.3239 data_time: 0.0081 memory: 10464 grad_norm: 6.4164 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 3.2464 loss: 3.2464 2022/09/07 17:14:38 - mmengine - INFO - Epoch(train) [4][1580/1793] lr: 7.5000e-03 eta: 16:45:20 time: 0.7662 data_time: 0.0075 memory: 10464 grad_norm: 6.3460 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.4567 loss: 3.4567 2022/09/07 17:14:51 - mmengine - INFO - Epoch(train) [4][1600/1793] lr: 7.5000e-03 eta: 16:44:49 time: 0.6618 data_time: 0.0101 memory: 10464 grad_norm: 6.3175 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.2587 loss: 3.2587 2022/09/07 17:15:06 - mmengine - INFO - Epoch(train) [4][1620/1793] lr: 7.5000e-03 eta: 16:44:35 time: 0.7337 data_time: 0.0113 memory: 10464 grad_norm: 6.1977 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.3169 loss: 3.3169 2022/09/07 17:15:06 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 17:15:16 - mmengine - INFO - Epoch(train) [4][1640/1793] lr: 7.5000e-03 eta: 16:43:34 time: 0.5286 data_time: 0.0085 memory: 10464 grad_norm: 6.4704 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 3.2764 loss: 3.2764 2022/09/07 17:15:38 - mmengine - INFO - Epoch(train) [4][1660/1793] lr: 7.5000e-03 eta: 16:44:41 time: 1.0783 data_time: 0.0099 memory: 10464 grad_norm: 6.0605 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.4716 loss: 3.4716 2022/09/07 17:15:48 - mmengine - INFO - Epoch(train) [4][1680/1793] lr: 7.5000e-03 eta: 16:43:33 time: 0.5010 data_time: 0.0093 memory: 10464 grad_norm: 6.2606 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.2443 loss: 3.2443 2022/09/07 17:15:59 - mmengine - INFO - Epoch(train) [4][1700/1793] lr: 7.5000e-03 eta: 16:42:40 time: 0.5648 data_time: 0.0752 memory: 10464 grad_norm: 6.1822 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.3624 loss: 3.3624 2022/09/07 17:16:10 - mmengine - INFO - Epoch(train) [4][1720/1793] lr: 7.5000e-03 eta: 16:41:46 time: 0.5594 data_time: 0.0100 memory: 10464 grad_norm: 6.2153 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.0835 loss: 3.0835 2022/09/07 17:16:19 - mmengine - INFO - Epoch(train) [4][1740/1793] lr: 7.5000e-03 eta: 16:40:26 time: 0.4447 data_time: 0.0091 memory: 10464 grad_norm: 6.1656 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.4629 loss: 3.4629 2022/09/07 17:16:31 - mmengine - INFO - Epoch(train) [4][1760/1793] lr: 7.5000e-03 eta: 16:39:42 time: 0.6019 data_time: 0.0581 memory: 10464 grad_norm: 6.5669 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.1915 loss: 3.1915 2022/09/07 17:16:44 - mmengine - INFO - Epoch(train) [4][1780/1793] lr: 7.5000e-03 eta: 16:39:12 time: 0.6585 data_time: 0.0771 memory: 10464 grad_norm: 6.0342 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.0618 loss: 3.0618 2022/09/07 17:16:54 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 17:16:54 - mmengine - INFO - Epoch(train) [4][1793/1793] lr: 7.5000e-03 eta: 16:39:12 time: 0.6890 data_time: 0.3638 memory: 10464 grad_norm: 6.1619 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.1088 loss: 3.1088 2022/09/07 17:16:54 - mmengine - INFO - Saving checkpoint at 4 epochs 2022/09/07 17:16:57 - mmengine - INFO - Epoch(val) [4][20/241] eta: 0:00:16 time: 0.0738 data_time: 0.0094 memory: 1482 2022/09/07 17:16:59 - mmengine - INFO - Epoch(val) [4][40/241] eta: 0:00:16 time: 0.0812 data_time: 0.0050 memory: 1482 2022/09/07 17:17:00 - mmengine - INFO - Epoch(val) [4][60/241] eta: 0:00:12 time: 0.0684 data_time: 0.0051 memory: 1482 2022/09/07 17:17:02 - mmengine - INFO - Epoch(val) [4][80/241] eta: 0:00:12 time: 0.0762 data_time: 0.0053 memory: 1482 2022/09/07 17:17:03 - mmengine - INFO - Epoch(val) [4][100/241] eta: 0:00:09 time: 0.0656 data_time: 0.0052 memory: 1482 2022/09/07 17:17:05 - mmengine - INFO - Epoch(val) [4][120/241] eta: 0:00:08 time: 0.0716 data_time: 0.0049 memory: 1482 2022/09/07 17:17:06 - mmengine - INFO - Epoch(val) [4][140/241] eta: 0:00:08 time: 0.0794 data_time: 0.0052 memory: 1482 2022/09/07 17:17:08 - mmengine - INFO - Epoch(val) [4][160/241] eta: 0:00:05 time: 0.0702 data_time: 0.0047 memory: 1482 2022/09/07 17:17:09 - mmengine - INFO - Epoch(val) [4][180/241] eta: 0:00:04 time: 0.0814 data_time: 0.0055 memory: 1482 2022/09/07 17:17:11 - mmengine - INFO - Epoch(val) [4][200/241] eta: 0:00:03 time: 0.0777 data_time: 0.0062 memory: 1482 2022/09/07 17:17:12 - mmengine - INFO - Epoch(val) [4][220/241] eta: 0:00:01 time: 0.0603 data_time: 0.0049 memory: 1482 2022/09/07 17:17:14 - mmengine - INFO - Epoch(val) [4][240/241] eta: 0:00:00 time: 0.0879 data_time: 0.0046 memory: 1482 2022/09/07 17:17:14 - mmengine - INFO - Epoch(val) [4][241/241] acc/top1: 0.1988 acc/top5: 0.4610 acc/mean1: 0.1788 2022/09/07 17:17:14 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_3.pth is removed 2022/09/07 17:17:16 - mmengine - INFO - The best checkpoint with 0.1988 acc/top1 at 4 epoch is saved to best_acc/top1_epoch_4.pth. 2022/09/07 17:17:31 - mmengine - INFO - Epoch(train) [5][20/1793] lr: 7.5000e-03 eta: 16:37:03 time: 0.7404 data_time: 0.1372 memory: 10464 grad_norm: 5.9538 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 3.5465 loss: 3.5465 2022/09/07 17:17:45 - mmengine - INFO - Epoch(train) [5][40/1793] lr: 7.5000e-03 eta: 16:36:43 time: 0.7037 data_time: 0.0213 memory: 10464 grad_norm: 6.9577 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.0279 loss: 3.0279 2022/09/07 17:17:57 - mmengine - INFO - Epoch(train) [5][60/1793] lr: 7.5000e-03 eta: 16:36:04 time: 0.6176 data_time: 0.0090 memory: 10464 grad_norm: 6.1568 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.1600 loss: 3.1600 2022/09/07 17:18:13 - mmengine - INFO - Epoch(train) [5][80/1793] lr: 7.5000e-03 eta: 16:36:01 time: 0.7759 data_time: 0.0878 memory: 10464 grad_norm: 6.4802 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.0443 loss: 3.0443 2022/09/07 17:18:23 - mmengine - INFO - Epoch(train) [5][100/1793] lr: 7.5000e-03 eta: 16:35:01 time: 0.5242 data_time: 0.0100 memory: 10464 grad_norm: 6.4785 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 3.4511 loss: 3.4511 2022/09/07 17:18:33 - mmengine - INFO - Epoch(train) [5][120/1793] lr: 7.5000e-03 eta: 16:33:50 time: 0.4724 data_time: 0.0190 memory: 10464 grad_norm: 6.4288 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.0901 loss: 3.0901 2022/09/07 17:18:50 - mmengine - INFO - Epoch(train) [5][140/1793] lr: 7.5000e-03 eta: 16:34:14 time: 0.8942 data_time: 0.5724 memory: 10464 grad_norm: 6.3140 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.9284 loss: 2.9284 2022/09/07 17:19:06 - mmengine - INFO - Epoch(train) [5][160/1793] lr: 7.5000e-03 eta: 16:34:17 time: 0.8021 data_time: 0.0087 memory: 10464 grad_norm: 6.6548 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.2742 loss: 3.2742 2022/09/07 17:19:14 - mmengine - INFO - Epoch(train) [5][180/1793] lr: 7.5000e-03 eta: 16:32:50 time: 0.4008 data_time: 0.0137 memory: 10464 grad_norm: 6.5541 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.5579 loss: 3.5579 2022/09/07 17:19:27 - mmengine - INFO - Epoch(train) [5][200/1793] lr: 7.5000e-03 eta: 16:32:09 time: 0.6068 data_time: 0.0995 memory: 10464 grad_norm: 6.3524 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.2190 loss: 3.2190 2022/09/07 17:19:37 - mmengine - INFO - Epoch(train) [5][220/1793] lr: 7.5000e-03 eta: 16:31:07 time: 0.5106 data_time: 0.2062 memory: 10464 grad_norm: 6.4941 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.2955 loss: 3.2955 2022/09/07 17:19:50 - mmengine - INFO - Epoch(train) [5][240/1793] lr: 7.5000e-03 eta: 16:30:39 time: 0.6601 data_time: 0.0089 memory: 10464 grad_norm: 7.4421 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.1376 loss: 3.1376 2022/09/07 17:19:59 - mmengine - INFO - Epoch(train) [5][260/1793] lr: 7.5000e-03 eta: 16:29:28 time: 0.4699 data_time: 0.0318 memory: 10464 grad_norm: 6.5944 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 3.3369 loss: 3.3369 2022/09/07 17:20:09 - mmengine - INFO - Epoch(train) [5][280/1793] lr: 7.5000e-03 eta: 16:28:16 time: 0.4592 data_time: 0.0062 memory: 10464 grad_norm: 6.2548 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 3.3010 loss: 3.3010 2022/09/07 17:20:24 - mmengine - INFO - Epoch(train) [5][300/1793] lr: 7.5000e-03 eta: 16:28:10 time: 0.7622 data_time: 0.0091 memory: 10464 grad_norm: 6.0854 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 3.1185 loss: 3.1185 2022/09/07 17:20:32 - mmengine - INFO - Epoch(train) [5][320/1793] lr: 7.5000e-03 eta: 16:26:52 time: 0.4281 data_time: 0.0934 memory: 10464 grad_norm: 6.2028 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.9477 loss: 2.9477 2022/09/07 17:20:45 - mmengine - INFO - Epoch(train) [5][340/1793] lr: 7.5000e-03 eta: 16:26:21 time: 0.6469 data_time: 0.0068 memory: 10464 grad_norm: 6.0242 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.2631 loss: 3.2631 2022/09/07 17:20:59 - mmengine - INFO - Epoch(train) [5][360/1793] lr: 7.5000e-03 eta: 16:26:01 time: 0.6947 data_time: 0.0094 memory: 10464 grad_norm: 6.1377 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.9888 loss: 2.9888 2022/09/07 17:21:08 - mmengine - INFO - Epoch(train) [5][380/1793] lr: 7.5000e-03 eta: 16:24:44 time: 0.4330 data_time: 0.0097 memory: 10464 grad_norm: 6.3044 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.9598 loss: 2.9598 2022/09/07 17:21:16 - mmengine - INFO - Epoch(train) [5][400/1793] lr: 7.5000e-03 eta: 16:23:22 time: 0.4093 data_time: 0.0060 memory: 10464 grad_norm: 6.5263 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.2207 loss: 3.2207 2022/09/07 17:21:30 - mmengine - INFO - Epoch(train) [5][420/1793] lr: 7.5000e-03 eta: 16:23:07 time: 0.7153 data_time: 0.0095 memory: 10464 grad_norm: 5.9210 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 3.2154 loss: 3.2154 2022/09/07 17:21:39 - mmengine - INFO - Epoch(train) [5][440/1793] lr: 7.5000e-03 eta: 16:21:47 time: 0.4151 data_time: 0.0096 memory: 10464 grad_norm: 6.2831 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.1629 loss: 3.1629 2022/09/07 17:21:52 - mmengine - INFO - Epoch(train) [5][460/1793] lr: 7.5000e-03 eta: 16:21:18 time: 0.6481 data_time: 0.0065 memory: 10464 grad_norm: 6.4745 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.3004 loss: 3.3004 2022/09/07 17:21:59 - mmengine - INFO - Epoch(train) [5][480/1793] lr: 7.5000e-03 eta: 16:19:52 time: 0.3854 data_time: 0.0105 memory: 10464 grad_norm: 6.2763 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.1391 loss: 3.1391 2022/09/07 17:22:11 - mmengine - INFO - Epoch(train) [5][500/1793] lr: 7.5000e-03 eta: 16:19:12 time: 0.5936 data_time: 0.0058 memory: 10464 grad_norm: 6.2294 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.2265 loss: 3.2265 2022/09/07 17:22:19 - mmengine - INFO - Epoch(train) [5][520/1793] lr: 7.5000e-03 eta: 16:17:53 time: 0.4124 data_time: 0.0388 memory: 10464 grad_norm: 6.5816 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.2048 loss: 3.2048 2022/09/07 17:22:28 - mmengine - INFO - Epoch(train) [5][540/1793] lr: 7.5000e-03 eta: 16:16:38 time: 0.4347 data_time: 0.0056 memory: 10464 grad_norm: 6.8911 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.1531 loss: 3.1531 2022/09/07 17:22:37 - mmengine - INFO - Epoch(train) [5][560/1793] lr: 7.5000e-03 eta: 16:15:22 time: 0.4201 data_time: 0.0099 memory: 10464 grad_norm: 6.4517 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.0916 loss: 3.0916 2022/09/07 17:22:46 - mmengine - INFO - Epoch(train) [5][580/1793] lr: 7.5000e-03 eta: 16:14:19 time: 0.4868 data_time: 0.0058 memory: 10464 grad_norm: 7.1303 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 3.4409 loss: 3.4409 2022/09/07 17:22:53 - mmengine - INFO - Epoch(train) [5][600/1793] lr: 7.5000e-03 eta: 16:12:46 time: 0.3374 data_time: 0.0094 memory: 10464 grad_norm: 7.1138 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.2456 loss: 3.2456 2022/09/07 17:23:01 - mmengine - INFO - Epoch(train) [5][620/1793] lr: 7.5000e-03 eta: 16:11:28 time: 0.4124 data_time: 0.0848 memory: 10464 grad_norm: 7.0830 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 3.2930 loss: 3.2930 2022/09/07 17:23:14 - mmengine - INFO - Epoch(train) [5][640/1793] lr: 7.5000e-03 eta: 16:10:57 time: 0.6305 data_time: 0.0081 memory: 10464 grad_norm: 6.7543 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.1637 loss: 3.1637 2022/09/07 17:23:24 - mmengine - INFO - Epoch(train) [5][660/1793] lr: 7.5000e-03 eta: 16:09:57 time: 0.4932 data_time: 0.0095 memory: 10464 grad_norm: 6.4631 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.0948 loss: 3.0948 2022/09/07 17:23:41 - mmengine - INFO - Epoch(train) [5][680/1793] lr: 7.5000e-03 eta: 16:10:10 time: 0.8437 data_time: 0.2656 memory: 10464 grad_norm: 6.8611 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 3.1741 loss: 3.1741 2022/09/07 17:23:59 - mmengine - INFO - Epoch(train) [5][700/1793] lr: 7.5000e-03 eta: 16:10:34 time: 0.8945 data_time: 0.6079 memory: 10464 grad_norm: 6.5147 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.2012 loss: 3.2012 2022/09/07 17:24:08 - mmengine - INFO - Epoch(train) [5][720/1793] lr: 7.5000e-03 eta: 16:09:25 time: 0.4492 data_time: 0.1416 memory: 10464 grad_norm: 6.2368 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.2244 loss: 3.2244 2022/09/07 17:24:22 - mmengine - INFO - Epoch(train) [5][740/1793] lr: 7.5000e-03 eta: 16:09:14 time: 0.7236 data_time: 0.0076 memory: 10464 grad_norm: 6.4082 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.2272 loss: 3.2272 2022/09/07 17:24:32 - mmengine - INFO - Epoch(train) [5][760/1793] lr: 7.5000e-03 eta: 16:08:16 time: 0.5005 data_time: 0.0103 memory: 10464 grad_norm: 6.8676 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 3.4595 loss: 3.4595 2022/09/07 17:24:43 - mmengine - INFO - Epoch(train) [5][780/1793] lr: 7.5000e-03 eta: 16:07:31 time: 0.5623 data_time: 0.0064 memory: 10464 grad_norm: 6.4167 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.1159 loss: 3.1159 2022/09/07 17:24:51 - mmengine - INFO - Epoch(train) [5][800/1793] lr: 7.5000e-03 eta: 16:06:14 time: 0.4025 data_time: 0.0312 memory: 10464 grad_norm: 6.3284 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.0966 loss: 3.0966 2022/09/07 17:24:58 - mmengine - INFO - Epoch(train) [5][820/1793] lr: 7.5000e-03 eta: 16:04:43 time: 0.3340 data_time: 0.0305 memory: 10464 grad_norm: 5.9515 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.9417 loss: 2.9417 2022/09/07 17:25:01 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 17:25:06 - mmengine - INFO - Epoch(train) [5][840/1793] lr: 7.5000e-03 eta: 16:03:26 time: 0.4027 data_time: 0.0094 memory: 10464 grad_norm: 6.3418 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.3737 loss: 3.3737 2022/09/07 17:25:15 - mmengine - INFO - Epoch(train) [5][860/1793] lr: 7.5000e-03 eta: 16:02:16 time: 0.4314 data_time: 0.0063 memory: 10464 grad_norm: 5.9123 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.0154 loss: 3.0154 2022/09/07 17:25:28 - mmengine - INFO - Epoch(train) [5][880/1793] lr: 7.5000e-03 eta: 16:01:54 time: 0.6698 data_time: 0.0095 memory: 10464 grad_norm: 6.5922 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 3.0429 loss: 3.0429 2022/09/07 17:25:36 - mmengine - INFO - Epoch(train) [5][900/1793] lr: 7.5000e-03 eta: 16:00:34 time: 0.3797 data_time: 0.0096 memory: 10464 grad_norm: 6.3764 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.0919 loss: 3.0919 2022/09/07 17:25:46 - mmengine - INFO - Epoch(train) [5][920/1793] lr: 7.5000e-03 eta: 15:59:43 time: 0.5249 data_time: 0.0056 memory: 10464 grad_norm: 6.2370 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.2903 loss: 3.2903 2022/09/07 17:26:03 - mmengine - INFO - Epoch(train) [5][940/1793] lr: 7.5000e-03 eta: 15:59:52 time: 0.8197 data_time: 0.2186 memory: 10464 grad_norm: 6.4717 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.2302 loss: 3.2302 2022/09/07 17:26:14 - mmengine - INFO - Epoch(train) [5][960/1793] lr: 7.5000e-03 eta: 15:59:07 time: 0.5539 data_time: 0.0749 memory: 10464 grad_norm: 6.4329 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.1736 loss: 3.1736 2022/09/07 17:26:26 - mmengine - INFO - Epoch(train) [5][980/1793] lr: 7.5000e-03 eta: 15:58:32 time: 0.5998 data_time: 0.0095 memory: 10464 grad_norm: 6.3972 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.9975 loss: 2.9975 2022/09/07 17:26:39 - mmengine - INFO - Epoch(train) [5][1000/1793] lr: 7.5000e-03 eta: 15:58:06 time: 0.6467 data_time: 0.0087 memory: 10464 grad_norm: 6.3295 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.0986 loss: 3.0986 2022/09/07 17:26:52 - mmengine - INFO - Epoch(train) [5][1020/1793] lr: 7.5000e-03 eta: 15:57:46 time: 0.6782 data_time: 0.0104 memory: 10464 grad_norm: 6.3613 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.0967 loss: 3.0967 2022/09/07 17:27:04 - mmengine - INFO - Epoch(train) [5][1040/1793] lr: 7.5000e-03 eta: 15:57:13 time: 0.6069 data_time: 0.0091 memory: 10464 grad_norm: 6.5542 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.0994 loss: 3.0994 2022/09/07 17:27:13 - mmengine - INFO - Epoch(train) [5][1060/1793] lr: 7.5000e-03 eta: 15:56:04 time: 0.4301 data_time: 0.0098 memory: 10464 grad_norm: 6.4440 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 3.0752 loss: 3.0752 2022/09/07 17:27:22 - mmengine - INFO - Epoch(train) [5][1080/1793] lr: 7.5000e-03 eta: 15:54:57 time: 0.4362 data_time: 0.0060 memory: 10464 grad_norm: 6.0676 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.8583 loss: 2.8583 2022/09/07 17:27:33 - mmengine - INFO - Epoch(train) [5][1100/1793] lr: 7.5000e-03 eta: 15:54:16 time: 0.5686 data_time: 0.0095 memory: 10464 grad_norm: 6.3872 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.8806 loss: 2.8806 2022/09/07 17:27:43 - mmengine - INFO - Epoch(train) [5][1120/1793] lr: 7.5000e-03 eta: 15:53:26 time: 0.5203 data_time: 0.0089 memory: 10464 grad_norm: 6.5087 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.3366 loss: 3.3366 2022/09/07 17:27:58 - mmengine - INFO - Epoch(train) [5][1140/1793] lr: 7.5000e-03 eta: 15:53:17 time: 0.7284 data_time: 0.0091 memory: 10464 grad_norm: 6.8344 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.2495 loss: 3.2495 2022/09/07 17:28:15 - mmengine - INFO - Epoch(train) [5][1160/1793] lr: 7.5000e-03 eta: 15:53:29 time: 0.8328 data_time: 0.0103 memory: 10464 grad_norm: 6.8671 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.8460 loss: 2.8460 2022/09/07 17:28:24 - mmengine - INFO - Epoch(train) [5][1180/1793] lr: 7.5000e-03 eta: 15:52:26 time: 0.4547 data_time: 0.0095 memory: 10464 grad_norm: 6.4998 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.9171 loss: 2.9171 2022/09/07 17:28:37 - mmengine - INFO - Epoch(train) [5][1200/1793] lr: 7.5000e-03 eta: 15:52:06 time: 0.6714 data_time: 0.0061 memory: 10464 grad_norm: 6.3723 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 3.1926 loss: 3.1926 2022/09/07 17:28:46 - mmengine - INFO - Epoch(train) [5][1220/1793] lr: 7.5000e-03 eta: 15:51:00 time: 0.4354 data_time: 0.0088 memory: 10464 grad_norm: 7.0100 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.0481 loss: 3.0481 2022/09/07 17:28:55 - mmengine - INFO - Epoch(train) [5][1240/1793] lr: 7.5000e-03 eta: 15:49:58 time: 0.4526 data_time: 0.0066 memory: 10464 grad_norm: 6.3925 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.1775 loss: 3.1775 2022/09/07 17:29:01 - mmengine - INFO - Epoch(train) [5][1260/1793] lr: 7.5000e-03 eta: 15:48:28 time: 0.3097 data_time: 0.0090 memory: 10464 grad_norm: 6.2742 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.4687 loss: 3.4687 2022/09/07 17:29:06 - mmengine - INFO - Epoch(train) [5][1280/1793] lr: 7.5000e-03 eta: 15:46:49 time: 0.2561 data_time: 0.0060 memory: 10464 grad_norm: 6.7091 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.1502 loss: 3.1502 2022/09/07 17:29:15 - mmengine - INFO - Epoch(train) [5][1300/1793] lr: 7.5000e-03 eta: 15:45:44 time: 0.4350 data_time: 0.0089 memory: 10464 grad_norm: 6.5257 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.2710 loss: 3.2710 2022/09/07 17:29:20 - mmengine - INFO - Epoch(train) [5][1320/1793] lr: 7.5000e-03 eta: 15:44:02 time: 0.2401 data_time: 0.0067 memory: 10464 grad_norm: 6.1283 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.9077 loss: 2.9077 2022/09/07 17:29:24 - mmengine - INFO - Epoch(train) [5][1340/1793] lr: 7.5000e-03 eta: 15:42:20 time: 0.2338 data_time: 0.0082 memory: 10464 grad_norm: 6.4755 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.0481 loss: 3.0481 2022/09/07 17:29:35 - mmengine - INFO - Epoch(train) [5][1360/1793] lr: 7.5000e-03 eta: 15:41:35 time: 0.5322 data_time: 0.0056 memory: 10464 grad_norm: 6.2427 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 3.1345 loss: 3.1345 2022/09/07 17:29:44 - mmengine - INFO - Epoch(train) [5][1380/1793] lr: 7.5000e-03 eta: 15:40:31 time: 0.4352 data_time: 0.0099 memory: 10464 grad_norm: 6.3342 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.9295 loss: 2.9295 2022/09/07 17:30:02 - mmengine - INFO - Epoch(train) [5][1400/1793] lr: 7.5000e-03 eta: 15:40:55 time: 0.8950 data_time: 0.0967 memory: 10464 grad_norm: 6.5629 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.2014 loss: 3.2014 2022/09/07 17:30:15 - mmengine - INFO - Epoch(train) [5][1420/1793] lr: 7.5000e-03 eta: 15:40:34 time: 0.6611 data_time: 0.0120 memory: 10464 grad_norm: 6.8372 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.8447 loss: 2.8447 2022/09/07 17:30:30 - mmengine - INFO - Epoch(train) [5][1440/1793] lr: 7.5000e-03 eta: 15:40:30 time: 0.7483 data_time: 0.0097 memory: 10464 grad_norm: 6.2549 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.3585 loss: 3.3585 2022/09/07 17:30:36 - mmengine - INFO - Epoch(train) [5][1460/1793] lr: 7.5000e-03 eta: 15:39:08 time: 0.3309 data_time: 0.0092 memory: 10464 grad_norm: 6.6783 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 3.1599 loss: 3.1599 2022/09/07 17:30:47 - mmengine - INFO - Epoch(train) [5][1480/1793] lr: 7.5000e-03 eta: 15:38:21 time: 0.5217 data_time: 0.0068 memory: 10464 grad_norm: 7.9414 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.1303 loss: 3.1303 2022/09/07 17:30:57 - mmengine - INFO - Epoch(train) [5][1500/1793] lr: 7.5000e-03 eta: 15:37:36 time: 0.5254 data_time: 0.0087 memory: 10464 grad_norm: 7.2144 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.9427 loss: 2.9427 2022/09/07 17:31:08 - mmengine - INFO - Epoch(train) [5][1520/1793] lr: 7.5000e-03 eta: 15:36:47 time: 0.5101 data_time: 0.0108 memory: 10464 grad_norm: 6.8763 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.1493 loss: 3.1493 2022/09/07 17:31:20 - mmengine - INFO - Epoch(train) [5][1540/1793] lr: 7.5000e-03 eta: 15:36:19 time: 0.6177 data_time: 0.0135 memory: 10464 grad_norm: 6.4930 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.0169 loss: 3.0169 2022/09/07 17:31:31 - mmengine - INFO - Epoch(train) [5][1560/1793] lr: 7.5000e-03 eta: 15:35:36 time: 0.5358 data_time: 0.2704 memory: 10464 grad_norm: 6.4295 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.9592 loss: 2.9592 2022/09/07 17:31:42 - mmengine - INFO - Epoch(train) [5][1580/1793] lr: 7.5000e-03 eta: 15:34:56 time: 0.5504 data_time: 0.0255 memory: 10464 grad_norm: 6.6719 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.8892 loss: 2.8892 2022/09/07 17:31:50 - mmengine - INFO - Epoch(train) [5][1600/1793] lr: 7.5000e-03 eta: 15:33:55 time: 0.4410 data_time: 0.0092 memory: 10464 grad_norm: 6.4653 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7744 loss: 2.7744 2022/09/07 17:32:03 - mmengine - INFO - Epoch(train) [5][1620/1793] lr: 7.5000e-03 eta: 15:33:28 time: 0.6181 data_time: 0.0059 memory: 10464 grad_norm: 6.8255 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.1952 loss: 3.1952 2022/09/07 17:32:15 - mmengine - INFO - Epoch(train) [5][1640/1793] lr: 7.5000e-03 eta: 15:32:55 time: 0.5924 data_time: 0.1164 memory: 10464 grad_norm: 5.9631 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.9976 loss: 2.9976 2022/09/07 17:32:27 - mmengine - INFO - Epoch(train) [5][1660/1793] lr: 7.5000e-03 eta: 15:32:24 time: 0.5946 data_time: 0.0764 memory: 10464 grad_norm: 6.2540 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 3.1146 loss: 3.1146 2022/09/07 17:32:37 - mmengine - INFO - Epoch(train) [5][1680/1793] lr: 7.5000e-03 eta: 15:31:39 time: 0.5219 data_time: 0.2934 memory: 10464 grad_norm: 6.3285 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.9826 loss: 2.9826 2022/09/07 17:32:51 - mmengine - INFO - Epoch(train) [5][1700/1793] lr: 7.5000e-03 eta: 15:31:23 time: 0.6831 data_time: 0.2098 memory: 10464 grad_norm: 6.4451 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 3.0949 loss: 3.0949 2022/09/07 17:33:06 - mmengine - INFO - Epoch(train) [5][1720/1793] lr: 7.5000e-03 eta: 15:31:20 time: 0.7512 data_time: 0.0226 memory: 10464 grad_norm: 6.5887 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.2476 loss: 3.2476 2022/09/07 17:33:21 - mmengine - INFO - Epoch(train) [5][1740/1793] lr: 7.5000e-03 eta: 15:31:18 time: 0.7562 data_time: 0.0085 memory: 10464 grad_norm: 6.2530 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 3.0433 loss: 3.0433 2022/09/07 17:33:28 - mmengine - INFO - Epoch(train) [5][1760/1793] lr: 7.5000e-03 eta: 15:30:04 time: 0.3585 data_time: 0.0119 memory: 10464 grad_norm: 6.5876 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.3399 loss: 3.3399 2022/09/07 17:33:48 - mmengine - INFO - Epoch(train) [5][1780/1793] lr: 7.5000e-03 eta: 15:30:42 time: 0.9805 data_time: 0.0073 memory: 10464 grad_norm: 6.4315 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.9616 loss: 2.9616 2022/09/07 17:33:54 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 17:33:54 - mmengine - INFO - Epoch(train) [5][1793/1793] lr: 7.5000e-03 eta: 15:30:42 time: 1.0650 data_time: 0.0089 memory: 10464 grad_norm: 6.5621 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.1956 loss: 3.1956 2022/09/07 17:33:54 - mmengine - INFO - Saving checkpoint at 5 epochs 2022/09/07 17:33:58 - mmengine - INFO - Epoch(val) [5][20/241] eta: 0:00:17 time: 0.0792 data_time: 0.0101 memory: 1482 2022/09/07 17:34:00 - mmengine - INFO - Epoch(val) [5][40/241] eta: 0:00:16 time: 0.0828 data_time: 0.0049 memory: 1482 2022/09/07 17:34:01 - mmengine - INFO - Epoch(val) [5][60/241] eta: 0:00:11 time: 0.0613 data_time: 0.0053 memory: 1482 2022/09/07 17:34:03 - mmengine - INFO - Epoch(val) [5][80/241] eta: 0:00:14 time: 0.0879 data_time: 0.0049 memory: 1482 2022/09/07 17:34:04 - mmengine - INFO - Epoch(val) [5][100/241] eta: 0:00:09 time: 0.0678 data_time: 0.0056 memory: 1482 2022/09/07 17:34:05 - mmengine - INFO - Epoch(val) [5][120/241] eta: 0:00:07 time: 0.0636 data_time: 0.0051 memory: 1482 2022/09/07 17:34:07 - mmengine - INFO - Epoch(val) [5][140/241] eta: 0:00:08 time: 0.0818 data_time: 0.0049 memory: 1482 2022/09/07 17:34:08 - mmengine - INFO - Epoch(val) [5][160/241] eta: 0:00:05 time: 0.0684 data_time: 0.0055 memory: 1482 2022/09/07 17:34:10 - mmengine - INFO - Epoch(val) [5][180/241] eta: 0:00:04 time: 0.0807 data_time: 0.0047 memory: 1482 2022/09/07 17:34:11 - mmengine - INFO - Epoch(val) [5][200/241] eta: 0:00:02 time: 0.0695 data_time: 0.0078 memory: 1482 2022/09/07 17:34:13 - mmengine - INFO - Epoch(val) [5][220/241] eta: 0:00:01 time: 0.0740 data_time: 0.0048 memory: 1482 2022/09/07 17:34:15 - mmengine - INFO - Epoch(val) [5][240/241] eta: 0:00:00 time: 0.0814 data_time: 0.0050 memory: 1482 2022/09/07 17:34:15 - mmengine - INFO - Epoch(val) [5][241/241] acc/top1: 0.2236 acc/top5: 0.5023 acc/mean1: 0.2013 2022/09/07 17:34:15 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_4.pth is removed 2022/09/07 17:34:16 - mmengine - INFO - The best checkpoint with 0.2236 acc/top1 at 5 epoch is saved to best_acc/top1_epoch_5.pth. 2022/09/07 17:34:32 - mmengine - INFO - Epoch(train) [6][20/1793] lr: 7.5000e-03 eta: 15:29:14 time: 0.7761 data_time: 0.3519 memory: 10464 grad_norm: 6.2444 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.9876 loss: 2.9876 2022/09/07 17:34:40 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 17:34:44 - mmengine - INFO - Epoch(train) [6][40/1793] lr: 7.5000e-03 eta: 15:28:40 time: 0.5802 data_time: 0.0097 memory: 10464 grad_norm: 6.1341 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.8659 loss: 2.8659 2022/09/07 17:34:53 - mmengine - INFO - Epoch(train) [6][60/1793] lr: 7.5000e-03 eta: 15:27:46 time: 0.4690 data_time: 0.0097 memory: 10464 grad_norm: 6.8575 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 3.3882 loss: 3.3882 2022/09/07 17:35:01 - mmengine - INFO - Epoch(train) [6][80/1793] lr: 7.5000e-03 eta: 15:26:41 time: 0.4004 data_time: 0.0057 memory: 10464 grad_norm: 6.4116 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.0606 loss: 3.0606 2022/09/07 17:35:11 - mmengine - INFO - Epoch(train) [6][100/1793] lr: 7.5000e-03 eta: 15:25:56 time: 0.5170 data_time: 0.0906 memory: 10464 grad_norm: 6.3545 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.9148 loss: 2.9148 2022/09/07 17:35:20 - mmengine - INFO - Epoch(train) [6][120/1793] lr: 7.5000e-03 eta: 15:24:58 time: 0.4358 data_time: 0.0096 memory: 10464 grad_norm: 6.7406 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.2897 loss: 3.2897 2022/09/07 17:35:26 - mmengine - INFO - Epoch(train) [6][140/1793] lr: 7.5000e-03 eta: 15:23:33 time: 0.2855 data_time: 0.0052 memory: 10464 grad_norm: 6.3554 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.1106 loss: 3.1106 2022/09/07 17:35:33 - mmengine - INFO - Epoch(train) [6][160/1793] lr: 7.5000e-03 eta: 15:22:24 time: 0.3760 data_time: 0.0088 memory: 10464 grad_norm: 6.5787 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.8715 loss: 2.8715 2022/09/07 17:35:38 - mmengine - INFO - Epoch(train) [6][180/1793] lr: 7.5000e-03 eta: 15:20:51 time: 0.2414 data_time: 0.0060 memory: 10464 grad_norm: 6.4546 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.0741 loss: 3.0741 2022/09/07 17:35:43 - mmengine - INFO - Epoch(train) [6][200/1793] lr: 7.5000e-03 eta: 15:19:19 time: 0.2399 data_time: 0.0105 memory: 10464 grad_norm: 6.3328 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.9922 loss: 2.9922 2022/09/07 17:35:50 - mmengine - INFO - Epoch(train) [6][220/1793] lr: 7.5000e-03 eta: 15:18:07 time: 0.3490 data_time: 0.0065 memory: 10464 grad_norm: 6.2873 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 3.0515 loss: 3.0515 2022/09/07 17:35:55 - mmengine - INFO - Epoch(train) [6][240/1793] lr: 7.5000e-03 eta: 15:16:36 time: 0.2448 data_time: 0.0096 memory: 10464 grad_norm: 6.3600 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.2071 loss: 3.2071 2022/09/07 17:36:00 - mmengine - INFO - Epoch(train) [6][260/1793] lr: 7.5000e-03 eta: 15:15:08 time: 0.2558 data_time: 0.0063 memory: 10464 grad_norm: 7.7306 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.6615 loss: 2.6615 2022/09/07 17:36:05 - mmengine - INFO - Epoch(train) [6][280/1793] lr: 7.5000e-03 eta: 15:13:38 time: 0.2451 data_time: 0.0080 memory: 10464 grad_norm: 6.4292 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.8696 loss: 2.8696 2022/09/07 17:36:10 - mmengine - INFO - Epoch(train) [6][300/1793] lr: 7.5000e-03 eta: 15:12:09 time: 0.2464 data_time: 0.0067 memory: 10464 grad_norm: 6.6004 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 2.8088 loss: 2.8088 2022/09/07 17:36:19 - mmengine - INFO - Epoch(train) [6][320/1793] lr: 7.5000e-03 eta: 15:11:14 time: 0.4432 data_time: 0.0075 memory: 10464 grad_norm: 6.6437 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.8303 loss: 2.8303 2022/09/07 17:36:33 - mmengine - INFO - Epoch(train) [6][340/1793] lr: 7.5000e-03 eta: 15:11:11 time: 0.7395 data_time: 0.0077 memory: 10464 grad_norm: 6.7768 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.3175 loss: 3.3175 2022/09/07 17:36:43 - mmengine - INFO - Epoch(train) [6][360/1793] lr: 7.5000e-03 eta: 15:10:21 time: 0.4706 data_time: 0.0094 memory: 10464 grad_norm: 6.8959 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.9349 loss: 2.9349 2022/09/07 17:36:54 - mmengine - INFO - Epoch(train) [6][380/1793] lr: 7.5000e-03 eta: 15:09:48 time: 0.5687 data_time: 0.0073 memory: 10464 grad_norm: 6.4310 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.0413 loss: 3.0413 2022/09/07 17:37:05 - mmengine - INFO - Epoch(train) [6][400/1793] lr: 7.5000e-03 eta: 15:09:14 time: 0.5602 data_time: 0.0099 memory: 10464 grad_norm: 6.4746 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.8311 loss: 2.8311 2022/09/07 17:37:12 - mmengine - INFO - Epoch(train) [6][420/1793] lr: 7.5000e-03 eta: 15:08:03 time: 0.3427 data_time: 0.0080 memory: 10464 grad_norm: 6.6107 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.8676 loss: 2.8676 2022/09/07 17:37:27 - mmengine - INFO - Epoch(train) [6][440/1793] lr: 7.5000e-03 eta: 15:08:02 time: 0.7553 data_time: 0.0069 memory: 10464 grad_norm: 6.7575 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.0722 loss: 3.0722 2022/09/07 17:37:34 - mmengine - INFO - Epoch(train) [6][460/1793] lr: 7.5000e-03 eta: 15:06:50 time: 0.3353 data_time: 0.0102 memory: 10464 grad_norm: 6.4689 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.9206 loss: 2.9206 2022/09/07 17:37:42 - mmengine - INFO - Epoch(train) [6][480/1793] lr: 7.5000e-03 eta: 15:05:51 time: 0.4077 data_time: 0.0061 memory: 10464 grad_norm: 6.5934 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7481 loss: 2.7481 2022/09/07 17:37:50 - mmengine - INFO - Epoch(train) [6][500/1793] lr: 7.5000e-03 eta: 15:04:48 time: 0.3867 data_time: 0.0093 memory: 10464 grad_norm: 6.3947 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 3.0895 loss: 3.0895 2022/09/07 17:37:57 - mmengine - INFO - Epoch(train) [6][520/1793] lr: 7.5000e-03 eta: 15:03:40 time: 0.3548 data_time: 0.0347 memory: 10464 grad_norm: 6.7585 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7543 loss: 2.7543 2022/09/07 17:38:11 - mmengine - INFO - Epoch(train) [6][540/1793] lr: 7.5000e-03 eta: 15:03:28 time: 0.6838 data_time: 0.0314 memory: 10464 grad_norm: 6.7950 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.1265 loss: 3.1265 2022/09/07 17:38:26 - mmengine - INFO - Epoch(train) [6][560/1793] lr: 7.5000e-03 eta: 15:03:33 time: 0.7854 data_time: 0.0097 memory: 10464 grad_norm: 6.5200 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.3520 loss: 3.3520 2022/09/07 17:38:37 - mmengine - INFO - Epoch(train) [6][580/1793] lr: 7.5000e-03 eta: 15:02:56 time: 0.5415 data_time: 0.0099 memory: 10464 grad_norm: 6.2488 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.0186 loss: 3.0186 2022/09/07 17:38:44 - mmengine - INFO - Epoch(train) [6][600/1793] lr: 7.5000e-03 eta: 15:01:49 time: 0.3578 data_time: 0.1145 memory: 10464 grad_norm: 6.6227 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 3.0315 loss: 3.0315 2022/09/07 17:38:56 - mmengine - INFO - Epoch(train) [6][620/1793] lr: 7.5000e-03 eta: 15:01:20 time: 0.5795 data_time: 0.0063 memory: 10464 grad_norm: 6.2975 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.1787 loss: 3.1787 2022/09/07 17:39:04 - mmengine - INFO - Epoch(train) [6][640/1793] lr: 7.5000e-03 eta: 15:00:16 time: 0.3749 data_time: 0.0097 memory: 10464 grad_norm: 6.9210 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.0912 loss: 3.0912 2022/09/07 17:39:18 - mmengine - INFO - Epoch(train) [6][660/1793] lr: 7.5000e-03 eta: 15:00:13 time: 0.7340 data_time: 0.0359 memory: 10464 grad_norm: 6.7806 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.0406 loss: 3.0406 2022/09/07 17:39:39 - mmengine - INFO - Epoch(train) [6][680/1793] lr: 7.5000e-03 eta: 15:00:56 time: 1.0188 data_time: 0.0108 memory: 10464 grad_norm: 6.8927 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 3.0806 loss: 3.0806 2022/09/07 17:39:44 - mmengine - INFO - Epoch(train) [6][700/1793] lr: 7.5000e-03 eta: 14:59:33 time: 0.2574 data_time: 0.0099 memory: 10464 grad_norm: 6.5843 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 3.1455 loss: 3.1455 2022/09/07 17:39:57 - mmengine - INFO - Epoch(train) [6][720/1793] lr: 7.5000e-03 eta: 14:59:21 time: 0.6822 data_time: 0.0064 memory: 10464 grad_norm: 6.8941 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.9136 loss: 2.9136 2022/09/07 17:40:11 - mmengine - INFO - Epoch(train) [6][740/1793] lr: 7.5000e-03 eta: 14:59:06 time: 0.6673 data_time: 0.0095 memory: 10464 grad_norm: 6.3508 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9509 loss: 2.9509 2022/09/07 17:40:20 - mmengine - INFO - Epoch(train) [6][760/1793] lr: 7.5000e-03 eta: 14:58:15 time: 0.4441 data_time: 0.1036 memory: 10464 grad_norm: 7.0016 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.7106 loss: 2.7106 2022/09/07 17:40:26 - mmengine - INFO - Epoch(train) [6][780/1793] lr: 7.5000e-03 eta: 14:57:05 time: 0.3299 data_time: 0.0048 memory: 10464 grad_norm: 6.9641 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9341 loss: 2.9341 2022/09/07 17:40:42 - mmengine - INFO - Epoch(train) [6][800/1793] lr: 7.5000e-03 eta: 14:57:10 time: 0.7837 data_time: 0.0098 memory: 10464 grad_norm: 6.5887 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.2324 loss: 3.2324 2022/09/07 17:40:49 - mmengine - INFO - Epoch(train) [6][820/1793] lr: 7.5000e-03 eta: 14:56:03 time: 0.3487 data_time: 0.0094 memory: 10464 grad_norm: 7.2428 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6480 loss: 2.6480 2022/09/07 17:40:59 - mmengine - INFO - Epoch(train) [6][840/1793] lr: 7.5000e-03 eta: 14:55:26 time: 0.5270 data_time: 0.1218 memory: 10464 grad_norm: 6.6017 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.7703 loss: 2.7703 2022/09/07 17:41:13 - mmengine - INFO - Epoch(train) [6][860/1793] lr: 7.5000e-03 eta: 14:55:11 time: 0.6633 data_time: 0.2362 memory: 10464 grad_norm: 7.0124 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 3.2296 loss: 3.2296 2022/09/07 17:41:20 - mmengine - INFO - Epoch(train) [6][880/1793] lr: 7.5000e-03 eta: 14:54:04 time: 0.3446 data_time: 0.0092 memory: 10464 grad_norm: 6.7805 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.0727 loss: 3.0727 2022/09/07 17:41:31 - mmengine - INFO - Epoch(train) [6][900/1793] lr: 7.5000e-03 eta: 14:53:31 time: 0.5496 data_time: 0.0055 memory: 10464 grad_norm: 6.4273 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.0534 loss: 3.0534 2022/09/07 17:41:47 - mmengine - INFO - Epoch(train) [6][920/1793] lr: 7.5000e-03 eta: 14:53:43 time: 0.8315 data_time: 0.0106 memory: 10464 grad_norm: 6.4243 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.9713 loss: 2.9713 2022/09/07 17:42:00 - mmengine - INFO - Epoch(train) [6][940/1793] lr: 7.5000e-03 eta: 14:53:24 time: 0.6378 data_time: 0.0082 memory: 10464 grad_norm: 6.6943 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.0604 loss: 3.0604 2022/09/07 17:42:06 - mmengine - INFO - Epoch(train) [6][960/1793] lr: 7.5000e-03 eta: 14:52:08 time: 0.2815 data_time: 0.0095 memory: 10464 grad_norm: 6.3800 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.0827 loss: 3.0827 2022/09/07 17:42:13 - mmengine - INFO - Epoch(train) [6][980/1793] lr: 7.5000e-03 eta: 14:51:06 time: 0.3712 data_time: 0.0083 memory: 10464 grad_norm: 6.4205 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.6672 loss: 2.6672 2022/09/07 17:42:18 - mmengine - INFO - Epoch(train) [6][1000/1793] lr: 7.5000e-03 eta: 14:49:47 time: 0.2584 data_time: 0.0075 memory: 10464 grad_norm: 6.4971 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 3.1287 loss: 3.1287 2022/09/07 17:42:29 - mmengine - INFO - Epoch(train) [6][1020/1793] lr: 7.5000e-03 eta: 14:49:14 time: 0.5467 data_time: 0.0067 memory: 10464 grad_norm: 6.9701 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.7760 loss: 2.7760 2022/09/07 17:42:33 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 17:42:36 - mmengine - INFO - Epoch(train) [6][1040/1793] lr: 7.5000e-03 eta: 14:48:05 time: 0.3222 data_time: 0.0092 memory: 10464 grad_norm: 6.2527 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.8377 loss: 2.8377 2022/09/07 17:42:50 - mmengine - INFO - Epoch(train) [6][1060/1793] lr: 7.5000e-03 eta: 14:48:03 time: 0.7388 data_time: 0.0063 memory: 10464 grad_norm: 6.5497 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.9190 loss: 2.9190 2022/09/07 17:42:59 - mmengine - INFO - Epoch(train) [6][1080/1793] lr: 7.5000e-03 eta: 14:47:15 time: 0.4499 data_time: 0.0106 memory: 10464 grad_norm: 6.7175 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.0635 loss: 3.0635 2022/09/07 17:43:11 - mmengine - INFO - Epoch(train) [6][1100/1793] lr: 7.5000e-03 eta: 14:46:51 time: 0.6032 data_time: 0.0059 memory: 10464 grad_norm: 6.8738 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.0585 loss: 3.0585 2022/09/07 17:43:25 - mmengine - INFO - Epoch(train) [6][1120/1793] lr: 7.5000e-03 eta: 14:46:40 time: 0.6850 data_time: 0.0110 memory: 10464 grad_norm: 6.5487 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 3.0633 loss: 3.0633 2022/09/07 17:43:32 - mmengine - INFO - Epoch(train) [6][1140/1793] lr: 7.5000e-03 eta: 14:45:38 time: 0.3615 data_time: 0.0093 memory: 10464 grad_norm: 6.5467 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.7962 loss: 2.7962 2022/09/07 17:43:39 - mmengine - INFO - Epoch(train) [6][1160/1793] lr: 7.5000e-03 eta: 14:44:33 time: 0.3346 data_time: 0.0064 memory: 10464 grad_norm: 6.6812 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 3.0019 loss: 3.0019 2022/09/07 17:43:47 - mmengine - INFO - Epoch(train) [6][1180/1793] lr: 7.5000e-03 eta: 14:43:37 time: 0.3951 data_time: 0.1448 memory: 10464 grad_norm: 6.5234 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.9804 loss: 2.9804 2022/09/07 17:43:57 - mmengine - INFO - Epoch(train) [6][1200/1793] lr: 7.5000e-03 eta: 14:43:00 time: 0.5179 data_time: 0.0059 memory: 10464 grad_norm: 6.7420 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.8879 loss: 2.8879 2022/09/07 17:44:07 - mmengine - INFO - Epoch(train) [6][1220/1793] lr: 7.5000e-03 eta: 14:42:15 time: 0.4651 data_time: 0.0099 memory: 10464 grad_norm: 6.2634 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6170 loss: 2.6170 2022/09/07 17:44:17 - mmengine - INFO - Epoch(train) [6][1240/1793] lr: 7.5000e-03 eta: 14:41:36 time: 0.4967 data_time: 0.0716 memory: 10464 grad_norm: 6.6850 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.6900 loss: 2.6900 2022/09/07 17:44:26 - mmengine - INFO - Epoch(train) [6][1260/1793] lr: 7.5000e-03 eta: 14:40:55 time: 0.4890 data_time: 0.0169 memory: 10464 grad_norm: 6.3693 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.0213 loss: 3.0213 2022/09/07 17:44:37 - mmengine - INFO - Epoch(train) [6][1280/1793] lr: 7.5000e-03 eta: 14:40:18 time: 0.5140 data_time: 0.2425 memory: 10464 grad_norm: 6.7387 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.7303 loss: 2.7303 2022/09/07 17:44:46 - mmengine - INFO - Epoch(train) [6][1300/1793] lr: 7.5000e-03 eta: 14:39:38 time: 0.4950 data_time: 0.2870 memory: 10464 grad_norm: 6.4437 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.1202 loss: 3.1202 2022/09/07 17:44:56 - mmengine - INFO - Epoch(train) [6][1320/1793] lr: 7.5000e-03 eta: 14:38:59 time: 0.4974 data_time: 0.2420 memory: 10464 grad_norm: 6.6688 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.7318 loss: 2.7318 2022/09/07 17:45:05 - mmengine - INFO - Epoch(train) [6][1340/1793] lr: 7.5000e-03 eta: 14:38:13 time: 0.4515 data_time: 0.2392 memory: 10464 grad_norm: 6.4176 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.9829 loss: 2.9829 2022/09/07 17:45:13 - mmengine - INFO - Epoch(train) [6][1360/1793] lr: 7.5000e-03 eta: 14:37:13 time: 0.3576 data_time: 0.0995 memory: 10464 grad_norm: 6.4823 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7336 loss: 2.7336 2022/09/07 17:45:26 - mmengine - INFO - Epoch(train) [6][1380/1793] lr: 7.5000e-03 eta: 14:37:01 time: 0.6729 data_time: 0.3471 memory: 10464 grad_norm: 6.9246 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 3.1234 loss: 3.1234 2022/09/07 17:45:37 - mmengine - INFO - Epoch(train) [6][1400/1793] lr: 7.5000e-03 eta: 14:36:32 time: 0.5593 data_time: 0.0089 memory: 10464 grad_norm: 6.5968 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.3256 loss: 3.3256 2022/09/07 17:45:49 - mmengine - INFO - Epoch(train) [6][1420/1793] lr: 7.5000e-03 eta: 14:36:06 time: 0.5823 data_time: 0.0835 memory: 10464 grad_norm: 6.5862 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.8095 loss: 2.8095 2022/09/07 17:46:06 - mmengine - INFO - Epoch(train) [6][1440/1793] lr: 7.5000e-03 eta: 14:36:19 time: 0.8340 data_time: 0.4371 memory: 10464 grad_norm: 6.7631 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 3.4805 loss: 3.4805 2022/09/07 17:46:19 - mmengine - INFO - Epoch(train) [6][1460/1793] lr: 7.5000e-03 eta: 14:36:04 time: 0.6542 data_time: 0.0090 memory: 10464 grad_norm: 6.5603 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5897 loss: 2.5897 2022/09/07 17:46:28 - mmengine - INFO - Epoch(train) [6][1480/1793] lr: 7.5000e-03 eta: 14:35:25 time: 0.4919 data_time: 0.0093 memory: 10464 grad_norm: 6.2671 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.8115 loss: 2.8115 2022/09/07 17:46:38 - mmengine - INFO - Epoch(train) [6][1500/1793] lr: 7.5000e-03 eta: 14:34:42 time: 0.4699 data_time: 0.1418 memory: 10464 grad_norm: 6.5338 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.8172 loss: 2.8172 2022/09/07 17:46:47 - mmengine - INFO - Epoch(train) [6][1520/1793] lr: 7.5000e-03 eta: 14:33:55 time: 0.4400 data_time: 0.0084 memory: 10464 grad_norm: 6.6352 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.0151 loss: 3.0151 2022/09/07 17:46:59 - mmengine - INFO - Epoch(train) [6][1540/1793] lr: 7.5000e-03 eta: 14:33:32 time: 0.5915 data_time: 0.0064 memory: 10464 grad_norm: 6.3467 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.8902 loss: 2.8902 2022/09/07 17:47:08 - mmengine - INFO - Epoch(train) [6][1560/1793] lr: 7.5000e-03 eta: 14:32:49 time: 0.4684 data_time: 0.0101 memory: 10464 grad_norm: 6.4481 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.0384 loss: 3.0384 2022/09/07 17:47:16 - mmengine - INFO - Epoch(train) [6][1580/1793] lr: 7.5000e-03 eta: 14:31:57 time: 0.4057 data_time: 0.0126 memory: 10464 grad_norm: 6.6715 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6487 loss: 2.6487 2022/09/07 17:47:26 - mmengine - INFO - Epoch(train) [6][1600/1793] lr: 7.5000e-03 eta: 14:31:23 time: 0.5166 data_time: 0.0089 memory: 10464 grad_norm: 6.7611 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.0658 loss: 3.0658 2022/09/07 17:47:35 - mmengine - INFO - Epoch(train) [6][1620/1793] lr: 7.5000e-03 eta: 14:30:36 time: 0.4369 data_time: 0.0102 memory: 10464 grad_norm: 6.5363 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.9827 loss: 2.9827 2022/09/07 17:47:47 - mmengine - INFO - Epoch(train) [6][1640/1793] lr: 7.5000e-03 eta: 14:30:16 time: 0.6144 data_time: 0.0069 memory: 10464 grad_norm: 6.4108 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.7101 loss: 2.7101 2022/09/07 17:47:59 - mmengine - INFO - Epoch(train) [6][1660/1793] lr: 7.5000e-03 eta: 14:29:48 time: 0.5660 data_time: 0.0091 memory: 10464 grad_norm: 6.5041 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.8939 loss: 2.8939 2022/09/07 17:48:07 - mmengine - INFO - Epoch(train) [6][1680/1793] lr: 7.5000e-03 eta: 14:28:58 time: 0.4119 data_time: 0.0095 memory: 10464 grad_norm: 6.6768 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.9743 loss: 2.9743 2022/09/07 17:48:15 - mmengine - INFO - Epoch(train) [6][1700/1793] lr: 7.5000e-03 eta: 14:28:09 time: 0.4126 data_time: 0.0255 memory: 10464 grad_norm: 6.8138 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.8314 loss: 2.8314 2022/09/07 17:48:28 - mmengine - INFO - Epoch(train) [6][1720/1793] lr: 7.5000e-03 eta: 14:27:50 time: 0.6221 data_time: 0.0872 memory: 10464 grad_norm: 6.7150 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 3.1749 loss: 3.1749 2022/09/07 17:48:41 - mmengine - INFO - Epoch(train) [6][1740/1793] lr: 7.5000e-03 eta: 14:27:40 time: 0.6856 data_time: 0.4274 memory: 10464 grad_norm: 6.4819 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8770 loss: 2.8770 2022/09/07 17:48:51 - mmengine - INFO - Epoch(train) [6][1760/1793] lr: 7.5000e-03 eta: 14:26:58 time: 0.4603 data_time: 0.0083 memory: 10464 grad_norm: 6.7178 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.2136 loss: 3.2136 2022/09/07 17:49:01 - mmengine - INFO - Epoch(train) [6][1780/1793] lr: 7.5000e-03 eta: 14:26:28 time: 0.5432 data_time: 0.0060 memory: 10464 grad_norm: 6.7422 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.3088 loss: 3.3088 2022/09/07 17:49:05 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 17:49:05 - mmengine - INFO - Epoch(train) [6][1793/1793] lr: 7.5000e-03 eta: 14:26:28 time: 0.3686 data_time: 0.0093 memory: 10464 grad_norm: 7.2250 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.2259 loss: 3.2259 2022/09/07 17:49:05 - mmengine - INFO - Saving checkpoint at 6 epochs 2022/09/07 17:49:08 - mmengine - INFO - Epoch(val) [6][20/241] eta: 0:00:19 time: 0.0878 data_time: 0.0097 memory: 1482 2022/09/07 17:49:10 - mmengine - INFO - Epoch(val) [6][40/241] eta: 0:00:12 time: 0.0606 data_time: 0.0055 memory: 1482 2022/09/07 17:49:11 - mmengine - INFO - Epoch(val) [6][60/241] eta: 0:00:16 time: 0.0902 data_time: 0.0051 memory: 1482 2022/09/07 17:49:13 - mmengine - INFO - Epoch(val) [6][80/241] eta: 0:00:08 time: 0.0545 data_time: 0.0055 memory: 1482 2022/09/07 17:49:14 - mmengine - INFO - Epoch(val) [6][100/241] eta: 0:00:10 time: 0.0772 data_time: 0.0053 memory: 1482 2022/09/07 17:49:16 - mmengine - INFO - Epoch(val) [6][120/241] eta: 0:00:08 time: 0.0732 data_time: 0.0052 memory: 1482 2022/09/07 17:49:17 - mmengine - INFO - Epoch(val) [6][140/241] eta: 0:00:06 time: 0.0643 data_time: 0.0044 memory: 1482 2022/09/07 17:49:19 - mmengine - INFO - Epoch(val) [6][160/241] eta: 0:00:06 time: 0.0823 data_time: 0.0047 memory: 1482 2022/09/07 17:49:20 - mmengine - INFO - Epoch(val) [6][180/241] eta: 0:00:04 time: 0.0663 data_time: 0.0050 memory: 1482 2022/09/07 17:49:21 - mmengine - INFO - Epoch(val) [6][200/241] eta: 0:00:03 time: 0.0760 data_time: 0.0051 memory: 1482 2022/09/07 17:49:23 - mmengine - INFO - Epoch(val) [6][220/241] eta: 0:00:01 time: 0.0813 data_time: 0.0061 memory: 1482 2022/09/07 17:49:24 - mmengine - INFO - Epoch(val) [6][240/241] eta: 0:00:00 time: 0.0588 data_time: 0.0049 memory: 1482 2022/09/07 17:49:25 - mmengine - INFO - Epoch(val) [6][241/241] acc/top1: 0.2206 acc/top5: 0.4952 acc/mean1: 0.1953 2022/09/07 17:49:40 - mmengine - INFO - Epoch(train) [7][20/1793] lr: 7.5000e-03 eta: 14:25:17 time: 0.7492 data_time: 0.0527 memory: 10464 grad_norm: 6.6614 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 3.0898 loss: 3.0898 2022/09/07 17:49:47 - mmengine - INFO - Epoch(train) [7][40/1793] lr: 7.5000e-03 eta: 14:24:24 time: 0.3864 data_time: 0.0081 memory: 10464 grad_norm: 7.0734 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.9736 loss: 2.9736 2022/09/07 17:49:57 - mmengine - INFO - Epoch(train) [7][60/1793] lr: 7.5000e-03 eta: 14:23:44 time: 0.4780 data_time: 0.0092 memory: 10464 grad_norm: 6.6864 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4547 loss: 2.4547 2022/09/07 17:50:04 - mmengine - INFO - Epoch(train) [7][80/1793] lr: 7.5000e-03 eta: 14:22:46 time: 0.3494 data_time: 0.0089 memory: 10464 grad_norm: 6.8911 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.8731 loss: 2.8731 2022/09/07 17:50:14 - mmengine - INFO - Epoch(train) [7][100/1793] lr: 7.5000e-03 eta: 14:22:13 time: 0.5145 data_time: 0.1302 memory: 10464 grad_norm: 6.5271 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7744 loss: 2.7744 2022/09/07 17:50:23 - mmengine - INFO - Epoch(train) [7][120/1793] lr: 7.5000e-03 eta: 14:21:28 time: 0.4386 data_time: 0.0103 memory: 10464 grad_norm: 6.5498 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.1171 loss: 3.1171 2022/09/07 17:50:29 - mmengine - INFO - Epoch(train) [7][140/1793] lr: 7.5000e-03 eta: 14:20:23 time: 0.2944 data_time: 0.0285 memory: 10464 grad_norm: 6.6615 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.2396 loss: 3.2396 2022/09/07 17:50:40 - mmengine - INFO - Epoch(train) [7][160/1793] lr: 7.5000e-03 eta: 14:19:57 time: 0.5701 data_time: 0.0085 memory: 10464 grad_norm: 6.7433 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.8846 loss: 2.8846 2022/09/07 17:50:55 - mmengine - INFO - Epoch(train) [7][180/1793] lr: 7.5000e-03 eta: 14:19:56 time: 0.7420 data_time: 0.0085 memory: 10464 grad_norm: 6.5319 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.8656 loss: 2.8656 2022/09/07 17:51:00 - mmengine - INFO - Epoch(train) [7][200/1793] lr: 7.5000e-03 eta: 14:18:45 time: 0.2488 data_time: 0.0099 memory: 10464 grad_norm: 6.5662 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 2.7445 loss: 2.7445 2022/09/07 17:51:09 - mmengine - INFO - Epoch(train) [7][220/1793] lr: 7.5000e-03 eta: 14:18:03 time: 0.4506 data_time: 0.2122 memory: 10464 grad_norm: 6.7514 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.9498 loss: 2.9498 2022/09/07 17:51:19 - mmengine - INFO - Epoch(train) [7][240/1793] lr: 7.5000e-03 eta: 14:17:26 time: 0.4878 data_time: 0.0091 memory: 10464 grad_norm: 6.8998 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.8518 loss: 2.8518 2022/09/07 17:51:20 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 17:51:27 - mmengine - INFO - Epoch(train) [7][260/1793] lr: 7.5000e-03 eta: 14:16:40 time: 0.4251 data_time: 0.0971 memory: 10464 grad_norm: 6.7179 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.8594 loss: 2.8594 2022/09/07 17:51:37 - mmengine - INFO - Epoch(train) [7][280/1793] lr: 7.5000e-03 eta: 14:15:59 time: 0.4576 data_time: 0.0086 memory: 10464 grad_norm: 6.5813 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.8815 loss: 2.8815 2022/09/07 17:51:47 - mmengine - INFO - Epoch(train) [7][300/1793] lr: 7.5000e-03 eta: 14:15:28 time: 0.5245 data_time: 0.0058 memory: 10464 grad_norm: 6.7979 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.9966 loss: 2.9966 2022/09/07 17:51:57 - mmengine - INFO - Epoch(train) [7][320/1793] lr: 7.5000e-03 eta: 14:14:53 time: 0.4991 data_time: 0.2158 memory: 10464 grad_norm: 6.8886 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.9768 loss: 2.9768 2022/09/07 17:52:05 - mmengine - INFO - Epoch(train) [7][340/1793] lr: 7.5000e-03 eta: 14:14:04 time: 0.4024 data_time: 0.0052 memory: 10464 grad_norm: 6.8632 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.6019 loss: 2.6019 2022/09/07 17:52:15 - mmengine - INFO - Epoch(train) [7][360/1793] lr: 7.5000e-03 eta: 14:13:26 time: 0.4756 data_time: 0.0092 memory: 10464 grad_norm: 7.0378 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.9563 loss: 2.9563 2022/09/07 17:52:24 - mmengine - INFO - Epoch(train) [7][380/1793] lr: 7.5000e-03 eta: 14:12:50 time: 0.4907 data_time: 0.0061 memory: 10464 grad_norm: 6.3780 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.8923 loss: 2.8923 2022/09/07 17:52:30 - mmengine - INFO - Epoch(train) [7][400/1793] lr: 7.5000e-03 eta: 14:11:48 time: 0.3023 data_time: 0.0088 memory: 10464 grad_norm: 6.5491 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.8640 loss: 2.8640 2022/09/07 17:52:41 - mmengine - INFO - Epoch(train) [7][420/1793] lr: 7.5000e-03 eta: 14:11:21 time: 0.5483 data_time: 0.0071 memory: 10464 grad_norm: 6.8797 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 3.1640 loss: 3.1640 2022/09/07 17:52:47 - mmengine - INFO - Epoch(train) [7][440/1793] lr: 7.5000e-03 eta: 14:10:18 time: 0.2965 data_time: 0.0096 memory: 10464 grad_norm: 7.1413 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.6172 loss: 2.6172 2022/09/07 17:53:02 - mmengine - INFO - Epoch(train) [7][460/1793] lr: 7.5000e-03 eta: 14:10:14 time: 0.7130 data_time: 0.4566 memory: 10464 grad_norm: 6.7936 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7978 loss: 2.7978 2022/09/07 17:53:15 - mmengine - INFO - Epoch(train) [7][480/1793] lr: 7.5000e-03 eta: 14:10:05 time: 0.6846 data_time: 0.1389 memory: 10464 grad_norm: 6.4451 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.1134 loss: 3.1134 2022/09/07 17:53:26 - mmengine - INFO - Epoch(train) [7][500/1793] lr: 7.5000e-03 eta: 14:09:39 time: 0.5517 data_time: 0.0095 memory: 10464 grad_norm: 6.4621 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.6301 loss: 2.6301 2022/09/07 17:53:53 - mmengine - INFO - Epoch(train) [7][520/1793] lr: 7.5000e-03 eta: 14:10:57 time: 1.3090 data_time: 0.0084 memory: 10464 grad_norm: 6.3113 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.7405 loss: 2.7405 2022/09/07 17:53:59 - mmengine - INFO - Epoch(train) [7][540/1793] lr: 7.5000e-03 eta: 14:09:57 time: 0.3079 data_time: 0.0111 memory: 10464 grad_norm: 6.6768 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.0830 loss: 3.0830 2022/09/07 17:54:07 - mmengine - INFO - Epoch(train) [7][560/1793] lr: 7.5000e-03 eta: 14:09:11 time: 0.4135 data_time: 0.0061 memory: 10464 grad_norm: 6.6821 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.8471 loss: 2.8471 2022/09/07 17:54:18 - mmengine - INFO - Epoch(train) [7][580/1793] lr: 7.5000e-03 eta: 14:08:46 time: 0.5690 data_time: 0.1051 memory: 10464 grad_norm: 6.5580 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.6444 loss: 2.6444 2022/09/07 17:54:24 - mmengine - INFO - Epoch(train) [7][600/1793] lr: 7.5000e-03 eta: 14:07:45 time: 0.3021 data_time: 0.0245 memory: 10464 grad_norm: 6.6679 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.7053 loss: 2.7053 2022/09/07 17:54:34 - mmengine - INFO - Epoch(train) [7][620/1793] lr: 7.5000e-03 eta: 14:07:11 time: 0.4918 data_time: 0.0070 memory: 10464 grad_norm: 6.5634 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.1408 loss: 3.1408 2022/09/07 17:54:51 - mmengine - INFO - Epoch(train) [7][640/1793] lr: 7.5000e-03 eta: 14:07:23 time: 0.8360 data_time: 0.0084 memory: 10464 grad_norm: 6.9844 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7418 loss: 2.7418 2022/09/07 17:54:56 - mmengine - INFO - Epoch(train) [7][660/1793] lr: 7.5000e-03 eta: 14:06:18 time: 0.2702 data_time: 0.0108 memory: 10464 grad_norm: 6.8994 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6180 loss: 2.6180 2022/09/07 17:55:02 - mmengine - INFO - Epoch(train) [7][680/1793] lr: 7.5000e-03 eta: 14:05:17 time: 0.2980 data_time: 0.0058 memory: 10464 grad_norm: 6.6920 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.0544 loss: 3.0544 2022/09/07 17:55:11 - mmengine - INFO - Epoch(train) [7][700/1793] lr: 7.5000e-03 eta: 14:04:36 time: 0.4424 data_time: 0.0085 memory: 10464 grad_norm: 6.8680 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.1036 loss: 3.1036 2022/09/07 17:55:17 - mmengine - INFO - Epoch(train) [7][720/1793] lr: 7.5000e-03 eta: 14:03:37 time: 0.3086 data_time: 0.0672 memory: 10464 grad_norm: 6.5099 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.8045 loss: 2.8045 2022/09/07 17:55:29 - mmengine - INFO - Epoch(train) [7][740/1793] lr: 7.5000e-03 eta: 14:03:14 time: 0.5742 data_time: 0.0358 memory: 10464 grad_norm: 6.7589 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5086 loss: 2.5086 2022/09/07 17:55:37 - mmengine - INFO - Epoch(train) [7][760/1793] lr: 7.5000e-03 eta: 14:02:27 time: 0.3964 data_time: 0.0535 memory: 10464 grad_norm: 6.3639 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4175 loss: 2.4175 2022/09/07 17:55:45 - mmengine - INFO - Epoch(train) [7][780/1793] lr: 7.5000e-03 eta: 14:01:40 time: 0.3978 data_time: 0.0061 memory: 10464 grad_norm: 6.5207 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.8533 loss: 2.8533 2022/09/07 17:55:56 - mmengine - INFO - Epoch(train) [7][800/1793] lr: 7.5000e-03 eta: 14:01:18 time: 0.5759 data_time: 0.2065 memory: 10464 grad_norm: 6.7205 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 2.6030 loss: 2.6030 2022/09/07 17:56:05 - mmengine - INFO - Epoch(train) [7][820/1793] lr: 7.5000e-03 eta: 14:00:39 time: 0.4519 data_time: 0.0095 memory: 10464 grad_norm: 6.6376 top1_acc: 0.1667 top5_acc: 1.0000 loss_cls: 3.1060 loss: 3.1060 2022/09/07 17:56:17 - mmengine - INFO - Epoch(train) [7][840/1793] lr: 7.5000e-03 eta: 14:00:19 time: 0.5974 data_time: 0.0064 memory: 10464 grad_norm: 6.9333 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.8535 loss: 2.8535 2022/09/07 17:56:25 - mmengine - INFO - Epoch(train) [7][860/1793] lr: 7.5000e-03 eta: 13:59:32 time: 0.3911 data_time: 0.0100 memory: 10464 grad_norm: 6.9934 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.9033 loss: 2.9033 2022/09/07 17:56:33 - mmengine - INFO - Epoch(train) [7][880/1793] lr: 7.5000e-03 eta: 13:58:44 time: 0.3798 data_time: 0.0100 memory: 10464 grad_norm: 6.8418 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.1793 loss: 3.1793 2022/09/07 17:56:39 - mmengine - INFO - Epoch(train) [7][900/1793] lr: 7.5000e-03 eta: 13:57:45 time: 0.2996 data_time: 0.0086 memory: 10464 grad_norm: 7.0076 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.0471 loss: 3.0471 2022/09/07 17:56:43 - mmengine - INFO - Epoch(train) [7][920/1793] lr: 7.5000e-03 eta: 13:56:37 time: 0.2358 data_time: 0.0063 memory: 10464 grad_norm: 7.0331 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.7525 loss: 2.7525 2022/09/07 17:56:50 - mmengine - INFO - Epoch(train) [7][940/1793] lr: 7.5000e-03 eta: 13:55:41 time: 0.3188 data_time: 0.0096 memory: 10464 grad_norm: 6.6771 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.6832 loss: 2.6832 2022/09/07 17:56:57 - mmengine - INFO - Epoch(train) [7][960/1793] lr: 7.5000e-03 eta: 13:54:51 time: 0.3638 data_time: 0.0053 memory: 10464 grad_norm: 6.5439 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.8320 loss: 2.8320 2022/09/07 17:57:05 - mmengine - INFO - Epoch(train) [7][980/1793] lr: 7.5000e-03 eta: 13:54:04 time: 0.3889 data_time: 0.0114 memory: 10464 grad_norm: 6.6799 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 2.8658 loss: 2.8658 2022/09/07 17:57:24 - mmengine - INFO - Epoch(train) [7][1000/1793] lr: 7.5000e-03 eta: 13:54:32 time: 0.9504 data_time: 0.0052 memory: 10464 grad_norm: 6.6223 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4983 loss: 2.4983 2022/09/07 17:57:35 - mmengine - INFO - Epoch(train) [7][1020/1793] lr: 7.5000e-03 eta: 13:54:06 time: 0.5408 data_time: 0.0094 memory: 10464 grad_norm: 6.4439 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.8471 loss: 2.8471 2022/09/07 17:57:46 - mmengine - INFO - Epoch(train) [7][1040/1793] lr: 7.5000e-03 eta: 13:53:46 time: 0.5918 data_time: 0.0088 memory: 10464 grad_norm: 6.7904 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.8873 loss: 2.8873 2022/09/07 17:57:59 - mmengine - INFO - Epoch(train) [7][1060/1793] lr: 7.5000e-03 eta: 13:53:33 time: 0.6387 data_time: 0.3129 memory: 10464 grad_norm: 6.5518 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.8324 loss: 2.8324 2022/09/07 17:58:07 - mmengine - INFO - Epoch(train) [7][1080/1793] lr: 7.5000e-03 eta: 13:52:48 time: 0.3967 data_time: 0.0088 memory: 10464 grad_norm: 6.7696 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.6546 loss: 2.6546 2022/09/07 17:58:16 - mmengine - INFO - Epoch(train) [7][1100/1793] lr: 7.5000e-03 eta: 13:52:07 time: 0.4271 data_time: 0.1094 memory: 10464 grad_norm: 6.9734 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.7567 loss: 2.7567 2022/09/07 17:58:25 - mmengine - INFO - Epoch(train) [7][1120/1793] lr: 7.5000e-03 eta: 13:51:28 time: 0.4466 data_time: 0.0075 memory: 10464 grad_norm: 6.5794 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.8191 loss: 2.8191 2022/09/07 17:58:33 - mmengine - INFO - Epoch(train) [7][1140/1793] lr: 7.5000e-03 eta: 13:50:45 time: 0.4061 data_time: 0.0068 memory: 10464 grad_norm: 6.5921 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.8294 loss: 2.8294 2022/09/07 17:58:40 - mmengine - INFO - Epoch(train) [7][1160/1793] lr: 7.5000e-03 eta: 13:49:56 time: 0.3623 data_time: 0.0086 memory: 10464 grad_norm: 6.5039 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 3.0725 loss: 3.0725 2022/09/07 17:58:48 - mmengine - INFO - Epoch(train) [7][1180/1793] lr: 7.5000e-03 eta: 13:49:13 time: 0.4158 data_time: 0.0210 memory: 10464 grad_norm: 6.8832 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.8429 loss: 2.8429 2022/09/07 17:58:57 - mmengine - INFO - Epoch(train) [7][1200/1793] lr: 7.5000e-03 eta: 13:48:36 time: 0.4539 data_time: 0.0091 memory: 10464 grad_norm: 6.5416 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4406 loss: 2.4406 2022/09/07 17:59:15 - mmengine - INFO - Epoch(train) [7][1220/1793] lr: 7.5000e-03 eta: 13:48:54 time: 0.8778 data_time: 0.0065 memory: 10464 grad_norm: 6.4949 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.6352 loss: 2.6352 2022/09/07 17:59:25 - mmengine - INFO - Epoch(train) [7][1240/1793] lr: 7.5000e-03 eta: 13:48:26 time: 0.5159 data_time: 0.2661 memory: 10464 grad_norm: 6.8482 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.7040 loss: 2.7040 2022/09/07 17:59:26 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 17:59:33 - mmengine - INFO - Epoch(train) [7][1260/1793] lr: 7.5000e-03 eta: 13:47:42 time: 0.4029 data_time: 0.1599 memory: 10464 grad_norm: 6.5836 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.8555 loss: 2.8555 2022/09/07 17:59:44 - mmengine - INFO - Epoch(train) [7][1280/1793] lr: 7.5000e-03 eta: 13:47:18 time: 0.5517 data_time: 0.0056 memory: 10464 grad_norm: 6.7304 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.8384 loss: 2.8384 2022/09/07 17:59:54 - mmengine - INFO - Epoch(train) [7][1300/1793] lr: 7.5000e-03 eta: 13:46:44 time: 0.4719 data_time: 0.0087 memory: 10464 grad_norm: 7.0037 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.7475 loss: 2.7475 2022/09/07 18:00:10 - mmengine - INFO - Epoch(train) [7][1320/1793] lr: 7.5000e-03 eta: 13:46:50 time: 0.7897 data_time: 0.1010 memory: 10464 grad_norm: 6.6160 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6543 loss: 2.6543 2022/09/07 18:00:20 - mmengine - INFO - Epoch(train) [7][1340/1793] lr: 7.5000e-03 eta: 13:46:24 time: 0.5371 data_time: 0.0089 memory: 10464 grad_norm: 6.4832 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.0985 loss: 3.0985 2022/09/07 18:00:27 - mmengine - INFO - Epoch(train) [7][1360/1793] lr: 7.5000e-03 eta: 13:45:30 time: 0.3126 data_time: 0.0095 memory: 10464 grad_norm: 6.5840 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.9314 loss: 2.9314 2022/09/07 18:00:34 - mmengine - INFO - Epoch(train) [7][1380/1793] lr: 7.5000e-03 eta: 13:44:43 time: 0.3748 data_time: 0.0055 memory: 10464 grad_norm: 6.5323 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.0268 loss: 3.0268 2022/09/07 18:00:41 - mmengine - INFO - Epoch(train) [7][1400/1793] lr: 7.5000e-03 eta: 13:43:53 time: 0.3417 data_time: 0.0085 memory: 10464 grad_norm: 6.2817 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.0291 loss: 3.0291 2022/09/07 18:00:53 - mmengine - INFO - Epoch(train) [7][1420/1793] lr: 7.5000e-03 eta: 13:43:37 time: 0.6135 data_time: 0.0056 memory: 10464 grad_norm: 6.6150 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.9904 loss: 2.9904 2022/09/07 18:00:59 - mmengine - INFO - Epoch(train) [7][1440/1793] lr: 7.5000e-03 eta: 13:42:37 time: 0.2652 data_time: 0.0095 memory: 10464 grad_norm: 6.7050 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.8499 loss: 2.8499 2022/09/07 18:01:08 - mmengine - INFO - Epoch(train) [7][1460/1793] lr: 7.5000e-03 eta: 13:42:03 time: 0.4723 data_time: 0.0063 memory: 10464 grad_norm: 7.4121 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5849 loss: 2.5849 2022/09/07 18:01:16 - mmengine - INFO - Epoch(train) [7][1480/1793] lr: 7.5000e-03 eta: 13:41:19 time: 0.3925 data_time: 0.0091 memory: 10464 grad_norm: 7.0552 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.8231 loss: 2.8231 2022/09/07 18:01:25 - mmengine - INFO - Epoch(train) [7][1500/1793] lr: 7.5000e-03 eta: 13:40:43 time: 0.4502 data_time: 0.0092 memory: 10464 grad_norm: 6.4480 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.7969 loss: 2.7969 2022/09/07 18:01:37 - mmengine - INFO - Epoch(train) [7][1520/1793] lr: 7.5000e-03 eta: 13:40:28 time: 0.6169 data_time: 0.0094 memory: 10464 grad_norm: 6.6725 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.7657 loss: 2.7657 2022/09/07 18:01:46 - mmengine - INFO - Epoch(train) [7][1540/1793] lr: 7.5000e-03 eta: 13:39:51 time: 0.4430 data_time: 0.0092 memory: 10464 grad_norm: 7.0305 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.0132 loss: 3.0132 2022/09/07 18:01:52 - mmengine - INFO - Epoch(train) [7][1560/1793] lr: 7.5000e-03 eta: 13:38:55 time: 0.2894 data_time: 0.0071 memory: 10464 grad_norm: 6.6726 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 2.9805 loss: 2.9805 2022/09/07 18:02:05 - mmengine - INFO - Epoch(train) [7][1580/1793] lr: 7.5000e-03 eta: 13:38:44 time: 0.6512 data_time: 0.0093 memory: 10464 grad_norm: 6.1223 top1_acc: 0.1667 top5_acc: 1.0000 loss_cls: 2.8716 loss: 2.8716 2022/09/07 18:02:13 - mmengine - INFO - Epoch(train) [7][1600/1793] lr: 7.5000e-03 eta: 13:38:01 time: 0.3928 data_time: 0.0095 memory: 10464 grad_norm: 6.7913 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 2.9342 loss: 2.9342 2022/09/07 18:02:21 - mmengine - INFO - Epoch(train) [7][1620/1793] lr: 7.5000e-03 eta: 13:37:23 time: 0.4325 data_time: 0.0061 memory: 10464 grad_norm: 6.5375 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.8289 loss: 2.8289 2022/09/07 18:02:31 - mmengine - INFO - Epoch(train) [7][1640/1793] lr: 7.5000e-03 eta: 13:36:51 time: 0.4799 data_time: 0.0096 memory: 10464 grad_norm: 6.9688 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.8032 loss: 2.8032 2022/09/07 18:02:37 - mmengine - INFO - Epoch(train) [7][1660/1793] lr: 7.5000e-03 eta: 13:35:58 time: 0.3118 data_time: 0.0059 memory: 10464 grad_norm: 6.4256 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.9112 loss: 2.9112 2022/09/07 18:02:45 - mmengine - INFO - Epoch(train) [7][1680/1793] lr: 7.5000e-03 eta: 13:35:13 time: 0.3752 data_time: 0.0087 memory: 10464 grad_norm: 6.9502 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.7100 loss: 2.7100 2022/09/07 18:02:50 - mmengine - INFO - Epoch(train) [7][1700/1793] lr: 7.5000e-03 eta: 13:34:18 time: 0.2883 data_time: 0.0082 memory: 10464 grad_norm: 6.6148 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7258 loss: 2.7258 2022/09/07 18:02:54 - mmengine - INFO - Epoch(train) [7][1720/1793] lr: 7.5000e-03 eta: 13:33:10 time: 0.1914 data_time: 0.0096 memory: 10464 grad_norm: 6.5463 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.7043 loss: 2.7043 2022/09/07 18:02:58 - mmengine - INFO - Epoch(train) [7][1740/1793] lr: 7.5000e-03 eta: 13:32:02 time: 0.1835 data_time: 0.0073 memory: 10464 grad_norm: 6.3590 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.7409 loss: 2.7409 2022/09/07 18:03:02 - mmengine - INFO - Epoch(train) [7][1760/1793] lr: 7.5000e-03 eta: 13:30:56 time: 0.1940 data_time: 0.0068 memory: 10464 grad_norm: 6.3095 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.0956 loss: 3.0956 2022/09/07 18:03:05 - mmengine - INFO - Epoch(train) [7][1780/1793] lr: 7.5000e-03 eta: 13:29:48 time: 0.1827 data_time: 0.0083 memory: 10464 grad_norm: 6.6489 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.6133 loss: 2.6133 2022/09/07 18:03:11 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 18:03:11 - mmengine - INFO - Epoch(train) [7][1793/1793] lr: 7.5000e-03 eta: 13:29:48 time: 0.3127 data_time: 0.0064 memory: 10464 grad_norm: 7.0026 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 2.5545 loss: 2.5545 2022/09/07 18:03:11 - mmengine - INFO - Saving checkpoint at 7 epochs 2022/09/07 18:03:14 - mmengine - INFO - Epoch(val) [7][20/241] eta: 0:00:13 time: 0.0616 data_time: 0.0103 memory: 1482 2022/09/07 18:03:15 - mmengine - INFO - Epoch(val) [7][40/241] eta: 0:00:13 time: 0.0672 data_time: 0.0163 memory: 1482 2022/09/07 18:03:17 - mmengine - INFO - Epoch(val) [7][60/241] eta: 0:00:10 time: 0.0564 data_time: 0.0054 memory: 1482 2022/09/07 18:03:18 - mmengine - INFO - Epoch(val) [7][80/241] eta: 0:00:09 time: 0.0563 data_time: 0.0055 memory: 1482 2022/09/07 18:03:19 - mmengine - INFO - Epoch(val) [7][100/241] eta: 0:00:07 time: 0.0560 data_time: 0.0054 memory: 1482 2022/09/07 18:03:20 - mmengine - INFO - Epoch(val) [7][120/241] eta: 0:00:07 time: 0.0582 data_time: 0.0061 memory: 1482 2022/09/07 18:03:21 - mmengine - INFO - Epoch(val) [7][140/241] eta: 0:00:05 time: 0.0560 data_time: 0.0055 memory: 1482 2022/09/07 18:03:22 - mmengine - INFO - Epoch(val) [7][160/241] eta: 0:00:04 time: 0.0561 data_time: 0.0054 memory: 1482 2022/09/07 18:03:23 - mmengine - INFO - Epoch(val) [7][180/241] eta: 0:00:03 time: 0.0555 data_time: 0.0056 memory: 1482 2022/09/07 18:03:25 - mmengine - INFO - Epoch(val) [7][200/241] eta: 0:00:02 time: 0.0706 data_time: 0.0092 memory: 1482 2022/09/07 18:03:26 - mmengine - INFO - Epoch(val) [7][220/241] eta: 0:00:01 time: 0.0551 data_time: 0.0048 memory: 1482 2022/09/07 18:03:27 - mmengine - INFO - Epoch(val) [7][240/241] eta: 0:00:00 time: 0.0549 data_time: 0.0047 memory: 1482 2022/09/07 18:03:28 - mmengine - INFO - Epoch(val) [7][241/241] acc/top1: 0.2454 acc/top5: 0.5342 acc/mean1: 0.2190 2022/09/07 18:03:28 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_5.pth is removed 2022/09/07 18:03:30 - mmengine - INFO - The best checkpoint with 0.2454 acc/top1 at 7 epoch is saved to best_acc/top1_epoch_7.pth. 2022/09/07 18:03:45 - mmengine - INFO - Epoch(train) [8][20/1793] lr: 7.5000e-03 eta: 13:28:50 time: 0.7356 data_time: 0.1462 memory: 10464 grad_norm: 6.2553 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.6831 loss: 2.6831 2022/09/07 18:03:50 - mmengine - INFO - Epoch(train) [8][40/1793] lr: 7.5000e-03 eta: 13:27:55 time: 0.2861 data_time: 0.0339 memory: 10464 grad_norm: 6.6933 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.6402 loss: 2.6402 2022/09/07 18:03:59 - mmengine - INFO - Epoch(train) [8][60/1793] lr: 7.5000e-03 eta: 13:27:21 time: 0.4537 data_time: 0.0055 memory: 10464 grad_norm: 6.6331 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7611 loss: 2.7611 2022/09/07 18:04:06 - mmengine - INFO - Epoch(train) [8][80/1793] lr: 7.5000e-03 eta: 13:26:35 time: 0.3533 data_time: 0.0090 memory: 10464 grad_norm: 6.7283 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.5914 loss: 2.5914 2022/09/07 18:04:15 - mmengine - INFO - Epoch(train) [8][100/1793] lr: 7.5000e-03 eta: 13:26:01 time: 0.4537 data_time: 0.0069 memory: 10464 grad_norm: 6.8722 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.0231 loss: 3.0231 2022/09/07 18:04:22 - mmengine - INFO - Epoch(train) [8][120/1793] lr: 7.5000e-03 eta: 13:25:10 time: 0.3056 data_time: 0.0089 memory: 10464 grad_norm: 6.6366 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.0621 loss: 3.0621 2022/09/07 18:04:30 - mmengine - INFO - Epoch(train) [8][140/1793] lr: 7.5000e-03 eta: 13:24:31 time: 0.4135 data_time: 0.0077 memory: 10464 grad_norm: 6.7668 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.7740 loss: 2.7740 2022/09/07 18:04:37 - mmengine - INFO - Epoch(train) [8][160/1793] lr: 7.5000e-03 eta: 13:23:48 time: 0.3762 data_time: 0.0312 memory: 10464 grad_norm: 6.4978 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.8793 loss: 2.8793 2022/09/07 18:04:51 - mmengine - INFO - Epoch(train) [8][180/1793] lr: 7.5000e-03 eta: 13:23:39 time: 0.6580 data_time: 0.0051 memory: 10464 grad_norm: 6.9203 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.5304 loss: 2.5304 2022/09/07 18:04:55 - mmengine - INFO - Epoch(train) [8][200/1793] lr: 7.5000e-03 eta: 13:22:41 time: 0.2451 data_time: 0.0101 memory: 10464 grad_norm: 6.5320 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.6642 loss: 2.6642 2022/09/07 18:05:10 - mmengine - INFO - Epoch(train) [8][220/1793] lr: 7.5000e-03 eta: 13:22:42 time: 0.7399 data_time: 0.0059 memory: 10464 grad_norm: 6.5516 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.2515 loss: 2.2515 2022/09/07 18:05:20 - mmengine - INFO - Epoch(train) [8][240/1793] lr: 7.5000e-03 eta: 13:22:12 time: 0.4812 data_time: 0.0095 memory: 10464 grad_norm: 6.7217 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.5394 loss: 2.5394 2022/09/07 18:05:26 - mmengine - INFO - Epoch(train) [8][260/1793] lr: 7.5000e-03 eta: 13:21:23 time: 0.3256 data_time: 0.0065 memory: 10464 grad_norm: 6.8475 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.9833 loss: 2.9833 2022/09/07 18:05:32 - mmengine - INFO - Epoch(train) [8][280/1793] lr: 7.5000e-03 eta: 13:20:30 time: 0.2863 data_time: 0.0089 memory: 10464 grad_norm: 6.5013 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.8037 loss: 2.8037 2022/09/07 18:05:46 - mmengine - INFO - Epoch(train) [8][300/1793] lr: 7.5000e-03 eta: 13:20:25 time: 0.6827 data_time: 0.0068 memory: 10464 grad_norm: 6.5498 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.6202 loss: 2.6202 2022/09/07 18:05:53 - mmengine - INFO - Epoch(train) [8][320/1793] lr: 7.5000e-03 eta: 13:19:40 time: 0.3526 data_time: 0.0101 memory: 10464 grad_norm: 6.6251 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.4477 loss: 2.4477 2022/09/07 18:06:00 - mmengine - INFO - Epoch(train) [8][340/1793] lr: 7.5000e-03 eta: 13:18:57 time: 0.3703 data_time: 0.0051 memory: 10464 grad_norm: 6.6907 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6687 loss: 2.6687 2022/09/07 18:06:09 - mmengine - INFO - Epoch(train) [8][360/1793] lr: 7.5000e-03 eta: 13:18:24 time: 0.4525 data_time: 0.0091 memory: 10464 grad_norm: 6.8702 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3628 loss: 2.3628 2022/09/07 18:06:15 - mmengine - INFO - Epoch(train) [8][380/1793] lr: 7.5000e-03 eta: 13:17:30 time: 0.2745 data_time: 0.0066 memory: 10464 grad_norm: 6.8963 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.7882 loss: 2.7882 2022/09/07 18:06:28 - mmengine - INFO - Epoch(train) [8][400/1793] lr: 7.5000e-03 eta: 13:17:19 time: 0.6406 data_time: 0.0103 memory: 10464 grad_norm: 6.8270 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.6558 loss: 2.6558 2022/09/07 18:06:35 - mmengine - INFO - Epoch(train) [8][420/1793] lr: 7.5000e-03 eta: 13:16:38 time: 0.3829 data_time: 0.0085 memory: 10464 grad_norm: 6.7742 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.7389 loss: 2.7389 2022/09/07 18:06:43 - mmengine - INFO - Epoch(train) [8][440/1793] lr: 7.5000e-03 eta: 13:15:56 time: 0.3672 data_time: 0.0074 memory: 10464 grad_norm: 6.6565 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5290 loss: 2.5290 2022/09/07 18:06:49 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 18:06:55 - mmengine - INFO - Epoch(train) [8][460/1793] lr: 7.5000e-03 eta: 13:15:42 time: 0.6118 data_time: 0.0081 memory: 10464 grad_norm: 6.7985 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7416 loss: 2.7416 2022/09/07 18:07:02 - mmengine - INFO - Epoch(train) [8][480/1793] lr: 7.5000e-03 eta: 13:14:57 time: 0.3431 data_time: 0.0100 memory: 10464 grad_norm: 6.6586 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6510 loss: 2.6510 2022/09/07 18:07:09 - mmengine - INFO - Epoch(train) [8][500/1793] lr: 7.5000e-03 eta: 13:14:12 time: 0.3457 data_time: 0.0063 memory: 10464 grad_norm: 6.9549 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.5245 loss: 2.5245 2022/09/07 18:07:13 - mmengine - INFO - Epoch(train) [8][520/1793] lr: 7.5000e-03 eta: 13:13:14 time: 0.2400 data_time: 0.0085 memory: 10464 grad_norm: 6.7294 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.6125 loss: 2.6125 2022/09/07 18:07:18 - mmengine - INFO - Epoch(train) [8][540/1793] lr: 7.5000e-03 eta: 13:12:18 time: 0.2469 data_time: 0.0073 memory: 10464 grad_norm: 6.8809 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.4892 loss: 2.4892 2022/09/07 18:07:25 - mmengine - INFO - Epoch(train) [8][560/1793] lr: 7.5000e-03 eta: 13:11:34 time: 0.3494 data_time: 0.0061 memory: 10464 grad_norm: 6.8194 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.7312 loss: 2.7312 2022/09/07 18:07:32 - mmengine - INFO - Epoch(train) [8][580/1793] lr: 7.5000e-03 eta: 13:10:49 time: 0.3390 data_time: 0.0086 memory: 10464 grad_norm: 6.6055 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.8934 loss: 2.8934 2022/09/07 18:07:37 - mmengine - INFO - Epoch(train) [8][600/1793] lr: 7.5000e-03 eta: 13:09:54 time: 0.2519 data_time: 0.0380 memory: 10464 grad_norm: 7.0013 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.8853 loss: 2.8853 2022/09/07 18:07:45 - mmengine - INFO - Epoch(train) [8][620/1793] lr: 7.5000e-03 eta: 13:09:14 time: 0.3886 data_time: 0.0082 memory: 10464 grad_norm: 7.0193 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.7202 loss: 2.7202 2022/09/07 18:07:51 - mmengine - INFO - Epoch(train) [8][640/1793] lr: 7.5000e-03 eta: 13:08:23 time: 0.2822 data_time: 0.0072 memory: 10464 grad_norm: 7.4728 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.9829 loss: 2.9829 2022/09/07 18:07:58 - mmengine - INFO - Epoch(train) [8][660/1793] lr: 7.5000e-03 eta: 13:07:39 time: 0.3492 data_time: 0.0075 memory: 10464 grad_norm: 6.9576 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.4872 loss: 2.4872 2022/09/07 18:08:06 - mmengine - INFO - Epoch(train) [8][680/1793] lr: 7.5000e-03 eta: 13:07:05 time: 0.4273 data_time: 0.0077 memory: 10464 grad_norm: 6.8503 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.7937 loss: 2.7937 2022/09/07 18:08:11 - mmengine - INFO - Epoch(train) [8][700/1793] lr: 7.5000e-03 eta: 13:06:08 time: 0.2331 data_time: 0.0085 memory: 10464 grad_norm: 6.7495 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.0288 loss: 3.0288 2022/09/07 18:08:16 - mmengine - INFO - Epoch(train) [8][720/1793] lr: 7.5000e-03 eta: 13:05:16 time: 0.2692 data_time: 0.0070 memory: 10464 grad_norm: 6.7507 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5476 loss: 2.5476 2022/09/07 18:08:21 - mmengine - INFO - Epoch(train) [8][740/1793] lr: 7.5000e-03 eta: 13:04:20 time: 0.2415 data_time: 0.0088 memory: 10464 grad_norm: 6.3908 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.6365 loss: 2.6365 2022/09/07 18:08:26 - mmengine - INFO - Epoch(train) [8][760/1793] lr: 7.5000e-03 eta: 13:03:24 time: 0.2330 data_time: 0.0072 memory: 10464 grad_norm: 6.8297 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.8769 loss: 2.8769 2022/09/07 18:08:31 - mmengine - INFO - Epoch(train) [8][780/1793] lr: 7.5000e-03 eta: 13:02:29 time: 0.2469 data_time: 0.0079 memory: 10464 grad_norm: 6.5468 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4403 loss: 2.4403 2022/09/07 18:08:36 - mmengine - INFO - Epoch(train) [8][800/1793] lr: 7.5000e-03 eta: 13:01:37 time: 0.2613 data_time: 0.0119 memory: 10464 grad_norm: 6.6221 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5268 loss: 2.5268 2022/09/07 18:08:41 - mmengine - INFO - Epoch(train) [8][820/1793] lr: 7.5000e-03 eta: 13:00:45 time: 0.2717 data_time: 0.0286 memory: 10464 grad_norm: 6.4158 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.8683 loss: 2.8683 2022/09/07 18:08:58 - mmengine - INFO - Epoch(train) [8][840/1793] lr: 7.5000e-03 eta: 13:00:57 time: 0.8281 data_time: 0.0084 memory: 10464 grad_norm: 6.6251 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.7826 loss: 2.7826 2022/09/07 18:09:06 - mmengine - INFO - Epoch(train) [8][860/1793] lr: 7.5000e-03 eta: 13:00:20 time: 0.3962 data_time: 0.0092 memory: 10464 grad_norm: 6.6605 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.6576 loss: 2.6576 2022/09/07 18:09:14 - mmengine - INFO - Epoch(train) [8][880/1793] lr: 7.5000e-03 eta: 12:59:46 time: 0.4239 data_time: 0.0066 memory: 10464 grad_norm: 7.2811 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.7152 loss: 2.7152 2022/09/07 18:09:24 - mmengine - INFO - Epoch(train) [8][900/1793] lr: 7.5000e-03 eta: 12:59:19 time: 0.4804 data_time: 0.0717 memory: 10464 grad_norm: 6.7855 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 3.0302 loss: 3.0302 2022/09/07 18:09:32 - mmengine - INFO - Epoch(train) [8][920/1793] lr: 7.5000e-03 eta: 12:58:46 time: 0.4338 data_time: 0.0923 memory: 10464 grad_norm: 6.8463 top1_acc: 0.0000 top5_acc: 0.8333 loss_cls: 2.5729 loss: 2.5729 2022/09/07 18:09:42 - mmengine - INFO - Epoch(train) [8][940/1793] lr: 7.5000e-03 eta: 12:58:19 time: 0.4782 data_time: 0.0081 memory: 10464 grad_norm: 6.6263 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.9411 loss: 2.9411 2022/09/07 18:09:50 - mmengine - INFO - Epoch(train) [8][960/1793] lr: 7.5000e-03 eta: 12:57:40 time: 0.3743 data_time: 0.0459 memory: 10464 grad_norm: 7.1331 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3820 loss: 2.3820 2022/09/07 18:09:59 - mmengine - INFO - Epoch(train) [8][980/1793] lr: 7.5000e-03 eta: 12:57:14 time: 0.4901 data_time: 0.0722 memory: 10464 grad_norm: 6.5679 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.5583 loss: 2.5583 2022/09/07 18:10:06 - mmengine - INFO - Epoch(train) [8][1000/1793] lr: 7.5000e-03 eta: 12:56:30 time: 0.3362 data_time: 0.0064 memory: 10464 grad_norm: 6.9621 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.6806 loss: 2.6806 2022/09/07 18:10:13 - mmengine - INFO - Epoch(train) [8][1020/1793] lr: 7.5000e-03 eta: 12:55:49 time: 0.3563 data_time: 0.0093 memory: 10464 grad_norm: 6.6356 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.8246 loss: 2.8246 2022/09/07 18:10:23 - mmengine - INFO - Epoch(train) [8][1040/1793] lr: 7.5000e-03 eta: 12:55:22 time: 0.4798 data_time: 0.0441 memory: 10464 grad_norm: 6.7728 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.9348 loss: 2.9348 2022/09/07 18:10:28 - mmengine - INFO - Epoch(train) [8][1060/1793] lr: 7.5000e-03 eta: 12:54:33 time: 0.2775 data_time: 0.0357 memory: 10464 grad_norm: 6.8995 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.6001 loss: 2.6001 2022/09/07 18:10:34 - mmengine - INFO - Epoch(train) [8][1080/1793] lr: 7.5000e-03 eta: 12:53:46 time: 0.3011 data_time: 0.0780 memory: 10464 grad_norm: 6.6541 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 3.1673 loss: 3.1673 2022/09/07 18:10:43 - mmengine - INFO - Epoch(train) [8][1100/1793] lr: 7.5000e-03 eta: 12:53:15 time: 0.4390 data_time: 0.0666 memory: 10464 grad_norm: 6.6457 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.8955 loss: 2.8955 2022/09/07 18:10:51 - mmengine - INFO - Epoch(train) [8][1120/1793] lr: 7.5000e-03 eta: 12:52:37 time: 0.3822 data_time: 0.0056 memory: 10464 grad_norm: 6.4394 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.5687 loss: 2.5687 2022/09/07 18:11:00 - mmengine - INFO - Epoch(train) [8][1140/1793] lr: 7.5000e-03 eta: 12:52:08 time: 0.4592 data_time: 0.1961 memory: 10464 grad_norm: 6.6953 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.5786 loss: 2.5786 2022/09/07 18:11:08 - mmengine - INFO - Epoch(train) [8][1160/1793] lr: 7.5000e-03 eta: 12:51:31 time: 0.3837 data_time: 0.0053 memory: 10464 grad_norm: 6.7776 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.7787 loss: 2.7787 2022/09/07 18:11:13 - mmengine - INFO - Epoch(train) [8][1180/1793] lr: 7.5000e-03 eta: 12:50:39 time: 0.2502 data_time: 0.0079 memory: 10464 grad_norm: 6.9978 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4414 loss: 2.4414 2022/09/07 18:11:18 - mmengine - INFO - Epoch(train) [8][1200/1793] lr: 7.5000e-03 eta: 12:49:48 time: 0.2630 data_time: 0.0075 memory: 10464 grad_norm: 6.9483 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7723 loss: 2.7723 2022/09/07 18:11:28 - mmengine - INFO - Epoch(train) [8][1220/1793] lr: 7.5000e-03 eta: 12:49:26 time: 0.5194 data_time: 0.0083 memory: 10464 grad_norm: 6.5828 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.2747 loss: 2.2747 2022/09/07 18:11:43 - mmengine - INFO - Epoch(train) [8][1240/1793] lr: 7.5000e-03 eta: 12:49:27 time: 0.7236 data_time: 0.0092 memory: 10464 grad_norm: 6.6099 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.6695 loss: 2.6695 2022/09/07 18:11:58 - mmengine - INFO - Epoch(train) [8][1260/1793] lr: 7.5000e-03 eta: 12:49:32 time: 0.7671 data_time: 0.0093 memory: 10464 grad_norm: 7.1949 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.7127 loss: 2.7127 2022/09/07 18:12:06 - mmengine - INFO - Epoch(train) [8][1280/1793] lr: 7.5000e-03 eta: 12:48:58 time: 0.4046 data_time: 0.0111 memory: 10464 grad_norm: 6.9206 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.6287 loss: 2.6287 2022/09/07 18:12:16 - mmengine - INFO - Epoch(train) [8][1300/1793] lr: 7.5000e-03 eta: 12:48:30 time: 0.4678 data_time: 0.0382 memory: 10464 grad_norm: 6.8688 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5519 loss: 2.5519 2022/09/07 18:12:23 - mmengine - INFO - Epoch(train) [8][1320/1793] lr: 7.5000e-03 eta: 12:47:50 time: 0.3527 data_time: 0.0083 memory: 10464 grad_norm: 6.5875 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.8867 loss: 2.8867 2022/09/07 18:12:30 - mmengine - INFO - Epoch(train) [8][1340/1793] lr: 7.5000e-03 eta: 12:47:09 time: 0.3474 data_time: 0.0071 memory: 10464 grad_norm: 6.6052 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8429 loss: 2.8429 2022/09/07 18:12:41 - mmengine - INFO - Epoch(train) [8][1360/1793] lr: 7.5000e-03 eta: 12:46:53 time: 0.5668 data_time: 0.1467 memory: 10464 grad_norm: 6.6238 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7418 loss: 2.7418 2022/09/07 18:12:46 - mmengine - INFO - Epoch(train) [8][1380/1793] lr: 7.5000e-03 eta: 12:46:03 time: 0.2603 data_time: 0.0080 memory: 10464 grad_norm: 6.9054 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.6755 loss: 2.6755 2022/09/07 18:12:55 - mmengine - INFO - Epoch(train) [8][1400/1793] lr: 7.5000e-03 eta: 12:45:34 time: 0.4554 data_time: 0.0074 memory: 10464 grad_norm: 7.0168 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3369 loss: 2.3369 2022/09/07 18:13:03 - mmengine - INFO - Epoch(train) [8][1420/1793] lr: 7.5000e-03 eta: 12:44:59 time: 0.3972 data_time: 0.0077 memory: 10464 grad_norm: 6.3774 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7580 loss: 2.7580 2022/09/07 18:13:11 - mmengine - INFO - Epoch(train) [8][1440/1793] lr: 7.5000e-03 eta: 12:44:25 time: 0.3960 data_time: 0.0057 memory: 10464 grad_norm: 6.8267 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.7963 loss: 2.7963 2022/09/07 18:13:19 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 18:13:22 - mmengine - INFO - Epoch(train) [8][1460/1793] lr: 7.5000e-03 eta: 12:44:03 time: 0.5225 data_time: 0.0099 memory: 10464 grad_norm: 6.8600 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.8435 loss: 2.8435 2022/09/07 18:13:33 - mmengine - INFO - Epoch(train) [8][1480/1793] lr: 7.5000e-03 eta: 12:43:48 time: 0.5784 data_time: 0.0439 memory: 10464 grad_norm: 6.9046 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.5459 loss: 2.5459 2022/09/07 18:13:39 - mmengine - INFO - Epoch(train) [8][1500/1793] lr: 7.5000e-03 eta: 12:43:00 time: 0.2706 data_time: 0.0252 memory: 10464 grad_norm: 7.2733 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.7497 loss: 2.7497 2022/09/07 18:13:44 - mmengine - INFO - Epoch(train) [8][1520/1793] lr: 7.5000e-03 eta: 12:42:12 time: 0.2724 data_time: 0.0117 memory: 10464 grad_norm: 7.1478 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7121 loss: 2.7121 2022/09/07 18:13:51 - mmengine - INFO - Epoch(train) [8][1540/1793] lr: 7.5000e-03 eta: 12:41:32 time: 0.3477 data_time: 0.0083 memory: 10464 grad_norm: 6.4749 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.8448 loss: 2.8448 2022/09/07 18:13:56 - mmengine - INFO - Epoch(train) [8][1560/1793] lr: 7.5000e-03 eta: 12:40:43 time: 0.2515 data_time: 0.0061 memory: 10464 grad_norm: 7.0093 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.5550 loss: 2.5550 2022/09/07 18:14:01 - mmengine - INFO - Epoch(train) [8][1580/1793] lr: 7.5000e-03 eta: 12:39:52 time: 0.2475 data_time: 0.0080 memory: 10464 grad_norm: 6.6977 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.8698 loss: 2.8698 2022/09/07 18:14:06 - mmengine - INFO - Epoch(train) [8][1600/1793] lr: 7.5000e-03 eta: 12:39:04 time: 0.2610 data_time: 0.0056 memory: 10464 grad_norm: 6.6004 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6892 loss: 2.6892 2022/09/07 18:14:12 - mmengine - INFO - Epoch(train) [8][1620/1793] lr: 7.5000e-03 eta: 12:38:17 time: 0.2763 data_time: 0.0086 memory: 10464 grad_norm: 6.4657 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.8736 loss: 2.8736 2022/09/07 18:14:17 - mmengine - INFO - Epoch(train) [8][1640/1793] lr: 7.5000e-03 eta: 12:37:29 time: 0.2659 data_time: 0.0078 memory: 10464 grad_norm: 6.4457 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4578 loss: 2.4578 2022/09/07 18:14:23 - mmengine - INFO - Epoch(train) [8][1660/1793] lr: 7.5000e-03 eta: 12:36:46 time: 0.3081 data_time: 0.0075 memory: 10464 grad_norm: 6.7750 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.6759 loss: 2.6759 2022/09/07 18:14:30 - mmengine - INFO - Epoch(train) [8][1680/1793] lr: 7.5000e-03 eta: 12:36:05 time: 0.3305 data_time: 0.0062 memory: 10464 grad_norm: 6.6805 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.8626 loss: 2.8626 2022/09/07 18:14:38 - mmengine - INFO - Epoch(train) [8][1700/1793] lr: 7.5000e-03 eta: 12:35:35 time: 0.4358 data_time: 0.0092 memory: 10464 grad_norm: 6.8090 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6667 loss: 2.6667 2022/09/07 18:14:52 - mmengine - INFO - Epoch(train) [8][1720/1793] lr: 7.5000e-03 eta: 12:35:32 time: 0.6863 data_time: 0.0075 memory: 10464 grad_norm: 6.6656 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5950 loss: 2.5950 2022/09/07 18:15:00 - mmengine - INFO - Epoch(train) [8][1740/1793] lr: 7.5000e-03 eta: 12:34:56 time: 0.3715 data_time: 0.0097 memory: 10464 grad_norm: 6.5566 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9270 loss: 2.9270 2022/09/07 18:15:10 - mmengine - INFO - Epoch(train) [8][1760/1793] lr: 7.5000e-03 eta: 12:34:34 time: 0.5077 data_time: 0.0056 memory: 10464 grad_norm: 6.4966 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8540 loss: 2.8540 2022/09/07 18:15:17 - mmengine - INFO - Epoch(train) [8][1780/1793] lr: 7.5000e-03 eta: 12:33:55 time: 0.3384 data_time: 0.0091 memory: 10464 grad_norm: 6.6712 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 3.0730 loss: 3.0730 2022/09/07 18:15:29 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 18:15:29 - mmengine - INFO - Epoch(train) [8][1793/1793] lr: 7.5000e-03 eta: 12:33:55 time: 0.7167 data_time: 0.0060 memory: 10464 grad_norm: 7.2279 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.8121 loss: 2.8121 2022/09/07 18:15:29 - mmengine - INFO - Saving checkpoint at 8 epochs 2022/09/07 18:15:34 - mmengine - INFO - Epoch(val) [8][20/241] eta: 0:00:24 time: 0.1117 data_time: 0.0305 memory: 1482 2022/09/07 18:15:35 - mmengine - INFO - Epoch(val) [8][40/241] eta: 0:00:13 time: 0.0658 data_time: 0.0050 memory: 1482 2022/09/07 18:15:36 - mmengine - INFO - Epoch(val) [8][60/241] eta: 0:00:13 time: 0.0767 data_time: 0.0051 memory: 1482 2022/09/07 18:15:38 - mmengine - INFO - Epoch(val) [8][80/241] eta: 0:00:11 time: 0.0744 data_time: 0.0048 memory: 1482 2022/09/07 18:15:39 - mmengine - INFO - Epoch(val) [8][100/241] eta: 0:00:08 time: 0.0638 data_time: 0.0056 memory: 1482 2022/09/07 18:15:41 - mmengine - INFO - Epoch(val) [8][120/241] eta: 0:00:10 time: 0.0847 data_time: 0.0049 memory: 1482 2022/09/07 18:15:42 - mmengine - INFO - Epoch(val) [8][140/241] eta: 0:00:06 time: 0.0656 data_time: 0.0049 memory: 1482 2022/09/07 18:15:44 - mmengine - INFO - Epoch(val) [8][160/241] eta: 0:00:06 time: 0.0758 data_time: 0.0048 memory: 1482 2022/09/07 18:15:45 - mmengine - INFO - Epoch(val) [8][180/241] eta: 0:00:04 time: 0.0797 data_time: 0.0071 memory: 1482 2022/09/07 18:15:47 - mmengine - INFO - Epoch(val) [8][200/241] eta: 0:00:02 time: 0.0673 data_time: 0.0053 memory: 1482 2022/09/07 18:15:48 - mmengine - INFO - Epoch(val) [8][220/241] eta: 0:00:01 time: 0.0805 data_time: 0.0050 memory: 1482 2022/09/07 18:15:50 - mmengine - INFO - Epoch(val) [8][240/241] eta: 0:00:00 time: 0.0707 data_time: 0.0044 memory: 1482 2022/09/07 18:15:50 - mmengine - INFO - Epoch(val) [8][241/241] acc/top1: 0.2536 acc/top5: 0.5392 acc/mean1: 0.2399 2022/09/07 18:15:50 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_7.pth is removed 2022/09/07 18:15:52 - mmengine - INFO - The best checkpoint with 0.2536 acc/top1 at 8 epoch is saved to best_acc/top1_epoch_8.pth. 2022/09/07 18:16:02 - mmengine - INFO - Epoch(train) [9][20/1793] lr: 7.5000e-03 eta: 12:32:43 time: 0.4955 data_time: 0.0972 memory: 10464 grad_norm: 6.5566 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7424 loss: 2.7424 2022/09/07 18:16:09 - mmengine - INFO - Epoch(train) [9][40/1793] lr: 7.5000e-03 eta: 12:32:08 time: 0.3831 data_time: 0.0082 memory: 10464 grad_norm: 6.7509 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.9437 loss: 2.9437 2022/09/07 18:16:16 - mmengine - INFO - Epoch(train) [9][60/1793] lr: 7.5000e-03 eta: 12:31:30 time: 0.3467 data_time: 0.0289 memory: 10464 grad_norm: 6.7324 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.6902 loss: 2.6902 2022/09/07 18:16:24 - mmengine - INFO - Epoch(train) [9][80/1793] lr: 7.5000e-03 eta: 12:30:56 time: 0.3962 data_time: 0.1202 memory: 10464 grad_norm: 6.7752 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4829 loss: 2.4829 2022/09/07 18:16:29 - mmengine - INFO - Epoch(train) [9][100/1793] lr: 7.5000e-03 eta: 12:30:10 time: 0.2630 data_time: 0.0063 memory: 10464 grad_norm: 6.6230 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.9499 loss: 2.9499 2022/09/07 18:16:37 - mmengine - INFO - Epoch(train) [9][120/1793] lr: 7.5000e-03 eta: 12:29:33 time: 0.3582 data_time: 0.0073 memory: 10464 grad_norm: 6.6302 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.6888 loss: 2.6888 2022/09/07 18:16:44 - mmengine - INFO - Epoch(train) [9][140/1793] lr: 7.5000e-03 eta: 12:28:57 time: 0.3748 data_time: 0.0064 memory: 10464 grad_norm: 6.7989 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3196 loss: 2.3196 2022/09/07 18:16:49 - mmengine - INFO - Epoch(train) [9][160/1793] lr: 7.5000e-03 eta: 12:28:07 time: 0.2269 data_time: 0.0085 memory: 10464 grad_norm: 6.5965 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4596 loss: 2.4596 2022/09/07 18:16:55 - mmengine - INFO - Epoch(train) [9][180/1793] lr: 7.5000e-03 eta: 12:27:26 time: 0.3118 data_time: 0.0062 memory: 10464 grad_norm: 6.7567 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.0622 loss: 3.0622 2022/09/07 18:17:00 - mmengine - INFO - Epoch(train) [9][200/1793] lr: 7.5000e-03 eta: 12:26:36 time: 0.2375 data_time: 0.0114 memory: 10464 grad_norm: 6.8752 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.7178 loss: 2.7178 2022/09/07 18:17:05 - mmengine - INFO - Epoch(train) [9][220/1793] lr: 7.5000e-03 eta: 12:25:50 time: 0.2621 data_time: 0.0059 memory: 10464 grad_norm: 6.4348 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6089 loss: 2.6089 2022/09/07 18:17:12 - mmengine - INFO - Epoch(train) [9][240/1793] lr: 7.5000e-03 eta: 12:25:13 time: 0.3475 data_time: 0.0358 memory: 10464 grad_norm: 6.7256 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.5996 loss: 2.5996 2022/09/07 18:17:18 - mmengine - INFO - Epoch(train) [9][260/1793] lr: 7.5000e-03 eta: 12:24:33 time: 0.3309 data_time: 0.0326 memory: 10464 grad_norm: 6.8762 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.5954 loss: 2.5954 2022/09/07 18:17:24 - mmengine - INFO - Epoch(train) [9][280/1793] lr: 7.5000e-03 eta: 12:23:47 time: 0.2593 data_time: 0.0064 memory: 10464 grad_norm: 6.6791 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 2.5608 loss: 2.5608 2022/09/07 18:17:33 - mmengine - INFO - Epoch(train) [9][300/1793] lr: 7.5000e-03 eta: 12:23:22 time: 0.4683 data_time: 0.0960 memory: 10464 grad_norm: 6.5673 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.5021 loss: 2.5021 2022/09/07 18:17:43 - mmengine - INFO - Epoch(train) [9][320/1793] lr: 7.5000e-03 eta: 12:23:01 time: 0.5062 data_time: 0.0063 memory: 10464 grad_norm: 6.5150 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3682 loss: 2.3682 2022/09/07 18:17:50 - mmengine - INFO - Epoch(train) [9][340/1793] lr: 7.5000e-03 eta: 12:22:26 time: 0.3667 data_time: 0.0088 memory: 10464 grad_norm: 6.7102 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.6057 loss: 2.6057 2022/09/07 18:18:09 - mmengine - INFO - Epoch(train) [9][360/1793] lr: 7.5000e-03 eta: 12:22:46 time: 0.9052 data_time: 0.0067 memory: 10464 grad_norm: 6.8450 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.5188 loss: 2.5188 2022/09/07 18:18:16 - mmengine - INFO - Epoch(train) [9][380/1793] lr: 7.5000e-03 eta: 12:22:12 time: 0.3787 data_time: 0.0117 memory: 10464 grad_norm: 7.2704 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5099 loss: 2.5099 2022/09/07 18:18:25 - mmengine - INFO - Epoch(train) [9][400/1793] lr: 7.5000e-03 eta: 12:21:46 time: 0.4522 data_time: 0.0063 memory: 10464 grad_norm: 6.5943 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3921 loss: 2.3921 2022/09/07 18:18:32 - mmengine - INFO - Epoch(train) [9][420/1793] lr: 7.5000e-03 eta: 12:21:09 time: 0.3505 data_time: 0.0103 memory: 10464 grad_norm: 6.8963 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.8767 loss: 2.8767 2022/09/07 18:18:39 - mmengine - INFO - Epoch(train) [9][440/1793] lr: 7.5000e-03 eta: 12:20:32 time: 0.3476 data_time: 0.0056 memory: 10464 grad_norm: 6.8198 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5370 loss: 2.5370 2022/09/07 18:18:44 - mmengine - INFO - Epoch(train) [9][460/1793] lr: 7.5000e-03 eta: 12:19:47 time: 0.2623 data_time: 0.0076 memory: 10464 grad_norm: 6.8253 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.6800 loss: 2.6800 2022/09/07 18:18:52 - mmengine - INFO - Epoch(train) [9][480/1793] lr: 7.5000e-03 eta: 12:19:13 time: 0.3777 data_time: 0.0270 memory: 10464 grad_norm: 6.7262 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4992 loss: 2.4992 2022/09/07 18:19:04 - mmengine - INFO - Epoch(train) [9][500/1793] lr: 7.5000e-03 eta: 12:19:02 time: 0.6009 data_time: 0.0081 memory: 10464 grad_norm: 6.5853 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4405 loss: 2.4405 2022/09/07 18:19:10 - mmengine - INFO - Epoch(train) [9][520/1793] lr: 7.5000e-03 eta: 12:18:22 time: 0.3088 data_time: 0.0596 memory: 10464 grad_norm: 6.4648 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.5125 loss: 2.5125 2022/09/07 18:19:18 - mmengine - INFO - Epoch(train) [9][540/1793] lr: 7.5000e-03 eta: 12:17:51 time: 0.4054 data_time: 0.0075 memory: 10464 grad_norm: 6.8773 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5890 loss: 2.5890 2022/09/07 18:19:27 - mmengine - INFO - Epoch(train) [9][560/1793] lr: 7.5000e-03 eta: 12:17:23 time: 0.4319 data_time: 0.2002 memory: 10464 grad_norm: 6.6072 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5842 loss: 2.5842 2022/09/07 18:19:34 - mmengine - INFO - Epoch(train) [9][580/1793] lr: 7.5000e-03 eta: 12:16:48 time: 0.3546 data_time: 0.0311 memory: 10464 grad_norm: 7.0125 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.7663 loss: 2.7663 2022/09/07 18:19:40 - mmengine - INFO - Epoch(train) [9][600/1793] lr: 7.5000e-03 eta: 12:16:06 time: 0.2951 data_time: 0.0079 memory: 10464 grad_norm: 6.7169 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.7116 loss: 2.7116 2022/09/07 18:19:45 - mmengine - INFO - Epoch(train) [9][620/1793] lr: 7.5000e-03 eta: 12:15:19 time: 0.2336 data_time: 0.0065 memory: 10464 grad_norm: 6.7570 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.7026 loss: 2.7026 2022/09/07 18:19:52 - mmengine - INFO - Epoch(train) [9][640/1793] lr: 7.5000e-03 eta: 12:14:45 time: 0.3691 data_time: 0.0088 memory: 10464 grad_norm: 6.6839 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5707 loss: 2.5707 2022/09/07 18:19:56 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 18:19:57 - mmengine - INFO - Epoch(train) [9][660/1793] lr: 7.5000e-03 eta: 12:14:00 time: 0.2560 data_time: 0.0061 memory: 10464 grad_norm: 6.7027 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.7488 loss: 2.7488 2022/09/07 18:20:02 - mmengine - INFO - Epoch(train) [9][680/1793] lr: 7.5000e-03 eta: 12:13:14 time: 0.2499 data_time: 0.0088 memory: 10464 grad_norm: 6.9923 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5949 loss: 2.5949 2022/09/07 18:20:07 - mmengine - INFO - Epoch(train) [9][700/1793] lr: 7.5000e-03 eta: 12:12:29 time: 0.2509 data_time: 0.0058 memory: 10464 grad_norm: 6.9142 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5177 loss: 2.5177 2022/09/07 18:20:16 - mmengine - INFO - Epoch(train) [9][720/1793] lr: 7.5000e-03 eta: 12:12:01 time: 0.4282 data_time: 0.1899 memory: 10464 grad_norm: 6.7615 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 2.5917 loss: 2.5917 2022/09/07 18:20:24 - mmengine - INFO - Epoch(train) [9][740/1793] lr: 7.5000e-03 eta: 12:11:35 time: 0.4433 data_time: 0.0060 memory: 10464 grad_norm: 6.7615 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7161 loss: 2.7161 2022/09/07 18:20:32 - mmengine - INFO - Epoch(train) [9][760/1793] lr: 7.5000e-03 eta: 12:11:02 time: 0.3722 data_time: 0.0078 memory: 10464 grad_norm: 6.6049 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3758 loss: 2.3758 2022/09/07 18:20:41 - mmengine - INFO - Epoch(train) [9][780/1793] lr: 7.5000e-03 eta: 12:10:36 time: 0.4431 data_time: 0.0071 memory: 10464 grad_norm: 6.7296 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6978 loss: 2.6978 2022/09/07 18:20:48 - mmengine - INFO - Epoch(train) [9][800/1793] lr: 7.5000e-03 eta: 12:10:03 time: 0.3727 data_time: 0.0089 memory: 10464 grad_norm: 6.4765 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.6055 loss: 2.6055 2022/09/07 18:20:57 - mmengine - INFO - Epoch(train) [9][820/1793] lr: 7.5000e-03 eta: 12:09:37 time: 0.4480 data_time: 0.0069 memory: 10464 grad_norm: 6.6752 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.6370 loss: 2.6370 2022/09/07 18:21:04 - mmengine - INFO - Epoch(train) [9][840/1793] lr: 7.5000e-03 eta: 12:09:00 time: 0.3250 data_time: 0.0079 memory: 10464 grad_norm: 6.8112 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.7540 loss: 2.7540 2022/09/07 18:21:11 - mmengine - INFO - Epoch(train) [9][860/1793] lr: 7.5000e-03 eta: 12:08:25 time: 0.3535 data_time: 0.0070 memory: 10464 grad_norm: 6.6174 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.6026 loss: 2.6026 2022/09/07 18:21:17 - mmengine - INFO - Epoch(train) [9][880/1793] lr: 7.5000e-03 eta: 12:07:44 time: 0.2863 data_time: 0.0090 memory: 10464 grad_norm: 6.8116 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.6916 loss: 2.6916 2022/09/07 18:21:30 - mmengine - INFO - Epoch(train) [9][900/1793] lr: 7.5000e-03 eta: 12:07:39 time: 0.6597 data_time: 0.0086 memory: 10464 grad_norm: 6.5106 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5485 loss: 2.5485 2022/09/07 18:21:38 - mmengine - INFO - Epoch(train) [9][920/1793] lr: 7.5000e-03 eta: 12:07:09 time: 0.3966 data_time: 0.0093 memory: 10464 grad_norm: 6.5386 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.7581 loss: 2.7581 2022/09/07 18:21:47 - mmengine - INFO - Epoch(train) [9][940/1793] lr: 7.5000e-03 eta: 12:06:48 time: 0.4920 data_time: 0.0062 memory: 10464 grad_norm: 6.8077 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.8557 loss: 2.8557 2022/09/07 18:21:54 - mmengine - INFO - Epoch(train) [9][960/1793] lr: 7.5000e-03 eta: 12:06:09 time: 0.3076 data_time: 0.0086 memory: 10464 grad_norm: 6.5012 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7143 loss: 2.7143 2022/09/07 18:22:04 - mmengine - INFO - Epoch(train) [9][980/1793] lr: 7.5000e-03 eta: 12:05:49 time: 0.4947 data_time: 0.0058 memory: 10464 grad_norm: 6.7111 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.7342 loss: 2.7342 2022/09/07 18:22:17 - mmengine - INFO - Epoch(train) [9][1000/1793] lr: 7.5000e-03 eta: 12:05:47 time: 0.6871 data_time: 0.0091 memory: 10464 grad_norm: 6.7727 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.6795 loss: 2.6795 2022/09/07 18:22:29 - mmengine - INFO - Epoch(train) [9][1020/1793] lr: 7.5000e-03 eta: 12:05:33 time: 0.5668 data_time: 0.0096 memory: 10464 grad_norm: 6.8285 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.8076 loss: 2.8076 2022/09/07 18:22:36 - mmengine - INFO - Epoch(train) [9][1040/1793] lr: 7.5000e-03 eta: 12:05:00 time: 0.3678 data_time: 0.1259 memory: 10464 grad_norm: 6.4942 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7938 loss: 2.7938 2022/09/07 18:22:46 - mmengine - INFO - Epoch(train) [9][1060/1793] lr: 7.5000e-03 eta: 12:04:38 time: 0.4780 data_time: 0.0797 memory: 10464 grad_norm: 6.6302 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2600 loss: 2.2600 2022/09/07 18:22:54 - mmengine - INFO - Epoch(train) [9][1080/1793] lr: 7.5000e-03 eta: 12:04:11 time: 0.4206 data_time: 0.0093 memory: 10464 grad_norm: 6.6366 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4000 loss: 2.4000 2022/09/07 18:23:03 - mmengine - INFO - Epoch(train) [9][1100/1793] lr: 7.5000e-03 eta: 12:03:47 time: 0.4656 data_time: 0.0988 memory: 10464 grad_norm: 6.8257 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.3445 loss: 2.3445 2022/09/07 18:23:13 - mmengine - INFO - Epoch(train) [9][1120/1793] lr: 7.5000e-03 eta: 12:03:25 time: 0.4761 data_time: 0.1672 memory: 10464 grad_norm: 6.6692 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.7877 loss: 2.7877 2022/09/07 18:23:20 - mmengine - INFO - Epoch(train) [9][1140/1793] lr: 7.5000e-03 eta: 12:02:52 time: 0.3649 data_time: 0.0069 memory: 10464 grad_norm: 6.4402 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.8505 loss: 2.8505 2022/09/07 18:23:29 - mmengine - INFO - Epoch(train) [9][1160/1793] lr: 7.5000e-03 eta: 12:02:26 time: 0.4322 data_time: 0.1934 memory: 10464 grad_norm: 6.6032 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5595 loss: 2.5595 2022/09/07 18:23:33 - mmengine - INFO - Epoch(train) [9][1180/1793] lr: 7.5000e-03 eta: 12:01:41 time: 0.2364 data_time: 0.0042 memory: 10464 grad_norm: 6.7044 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.6426 loss: 2.6426 2022/09/07 18:23:38 - mmengine - INFO - Epoch(train) [9][1200/1793] lr: 7.5000e-03 eta: 12:00:56 time: 0.2272 data_time: 0.0096 memory: 10464 grad_norm: 6.5906 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.6770 loss: 2.6770 2022/09/07 18:23:50 - mmengine - INFO - Epoch(train) [9][1220/1793] lr: 7.5000e-03 eta: 12:00:43 time: 0.5798 data_time: 0.0060 memory: 10464 grad_norm: 6.6886 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7779 loss: 2.7779 2022/09/07 18:23:59 - mmengine - INFO - Epoch(train) [9][1240/1793] lr: 7.5000e-03 eta: 12:00:22 time: 0.4800 data_time: 0.0096 memory: 10464 grad_norm: 6.6141 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5989 loss: 2.5989 2022/09/07 18:24:08 - mmengine - INFO - Epoch(train) [9][1260/1793] lr: 7.5000e-03 eta: 11:59:56 time: 0.4333 data_time: 0.0068 memory: 10464 grad_norm: 6.7770 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6572 loss: 2.6572 2022/09/07 18:24:15 - mmengine - INFO - Epoch(train) [9][1280/1793] lr: 7.5000e-03 eta: 11:59:24 time: 0.3660 data_time: 0.0079 memory: 10464 grad_norm: 7.0430 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.4566 loss: 2.4566 2022/09/07 18:24:21 - mmengine - INFO - Epoch(train) [9][1300/1793] lr: 7.5000e-03 eta: 11:58:43 time: 0.2770 data_time: 0.0073 memory: 10464 grad_norm: 6.6652 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 3.0829 loss: 3.0829 2022/09/07 18:24:26 - mmengine - INFO - Epoch(train) [9][1320/1793] lr: 7.5000e-03 eta: 11:58:03 time: 0.2856 data_time: 0.0088 memory: 10464 grad_norm: 6.6880 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.8284 loss: 2.8284 2022/09/07 18:24:34 - mmengine - INFO - Epoch(train) [9][1340/1793] lr: 7.5000e-03 eta: 11:57:33 time: 0.3790 data_time: 0.0066 memory: 10464 grad_norm: 6.9489 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.7664 loss: 2.7664 2022/09/07 18:24:39 - mmengine - INFO - Epoch(train) [9][1360/1793] lr: 7.5000e-03 eta: 11:56:51 time: 0.2682 data_time: 0.0083 memory: 10464 grad_norm: 6.5074 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.7098 loss: 2.7098 2022/09/07 18:24:47 - mmengine - INFO - Epoch(train) [9][1380/1793] lr: 7.5000e-03 eta: 11:56:23 time: 0.4052 data_time: 0.0065 memory: 10464 grad_norm: 6.9360 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.9866 loss: 2.9866 2022/09/07 18:24:54 - mmengine - INFO - Epoch(train) [9][1400/1793] lr: 7.5000e-03 eta: 11:55:48 time: 0.3293 data_time: 0.0086 memory: 10464 grad_norm: 6.6806 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4725 loss: 2.4725 2022/09/07 18:25:02 - mmengine - INFO - Epoch(train) [9][1420/1793] lr: 7.5000e-03 eta: 11:55:20 time: 0.4096 data_time: 0.0056 memory: 10464 grad_norm: 6.6184 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.7955 loss: 2.7955 2022/09/07 18:25:08 - mmengine - INFO - Epoch(train) [9][1440/1793] lr: 7.5000e-03 eta: 11:54:39 time: 0.2694 data_time: 0.0089 memory: 10464 grad_norm: 6.7108 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.3262 loss: 2.3262 2022/09/07 18:25:14 - mmengine - INFO - Epoch(train) [9][1460/1793] lr: 7.5000e-03 eta: 11:54:05 time: 0.3395 data_time: 0.0061 memory: 10464 grad_norm: 6.7397 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.9682 loss: 2.9682 2022/09/07 18:25:20 - mmengine - INFO - Epoch(train) [9][1480/1793] lr: 7.5000e-03 eta: 11:53:25 time: 0.2706 data_time: 0.0087 memory: 10464 grad_norm: 6.6319 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5728 loss: 2.5728 2022/09/07 18:25:25 - mmengine - INFO - Epoch(train) [9][1500/1793] lr: 7.5000e-03 eta: 11:52:43 time: 0.2576 data_time: 0.0064 memory: 10464 grad_norm: 6.5537 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.7470 loss: 2.7470 2022/09/07 18:25:32 - mmengine - INFO - Epoch(train) [9][1520/1793] lr: 7.5000e-03 eta: 11:52:12 time: 0.3639 data_time: 0.0085 memory: 10464 grad_norm: 6.8912 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6552 loss: 2.6552 2022/09/07 18:25:37 - mmengine - INFO - Epoch(train) [9][1540/1793] lr: 7.5000e-03 eta: 11:51:29 time: 0.2507 data_time: 0.0094 memory: 10464 grad_norm: 6.7148 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7435 loss: 2.7435 2022/09/07 18:25:42 - mmengine - INFO - Epoch(train) [9][1560/1793] lr: 7.5000e-03 eta: 11:50:46 time: 0.2364 data_time: 0.0073 memory: 10464 grad_norm: 6.6737 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.5539 loss: 2.5539 2022/09/07 18:25:47 - mmengine - INFO - Epoch(train) [9][1580/1793] lr: 7.5000e-03 eta: 11:50:03 time: 0.2413 data_time: 0.0062 memory: 10464 grad_norm: 6.8859 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.9251 loss: 2.9251 2022/09/07 18:25:52 - mmengine - INFO - Epoch(train) [9][1600/1793] lr: 7.5000e-03 eta: 11:49:20 time: 0.2323 data_time: 0.0065 memory: 10464 grad_norm: 6.8555 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.7125 loss: 2.7125 2022/09/07 18:25:57 - mmengine - INFO - Epoch(train) [9][1620/1793] lr: 7.5000e-03 eta: 11:48:40 time: 0.2688 data_time: 0.0088 memory: 10464 grad_norm: 6.8882 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.6544 loss: 2.6544 2022/09/07 18:26:02 - mmengine - INFO - Epoch(train) [9][1640/1793] lr: 7.5000e-03 eta: 11:48:01 time: 0.2780 data_time: 0.0067 memory: 10464 grad_norm: 6.9877 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.7936 loss: 2.7936 2022/09/07 18:26:08 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 18:26:09 - mmengine - INFO - Epoch(train) [9][1660/1793] lr: 7.5000e-03 eta: 11:47:26 time: 0.3210 data_time: 0.0086 memory: 10464 grad_norm: 6.6323 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6748 loss: 2.6748 2022/09/07 18:26:15 - mmengine - INFO - Epoch(train) [9][1680/1793] lr: 7.5000e-03 eta: 11:46:48 time: 0.2975 data_time: 0.0067 memory: 10464 grad_norm: 6.7168 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7671 loss: 2.7671 2022/09/07 18:26:20 - mmengine - INFO - Epoch(train) [9][1700/1793] lr: 7.5000e-03 eta: 11:46:09 time: 0.2725 data_time: 0.0091 memory: 10464 grad_norm: 6.4074 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.5527 loss: 2.5527 2022/09/07 18:26:30 - mmengine - INFO - Epoch(train) [9][1720/1793] lr: 7.5000e-03 eta: 11:45:51 time: 0.5011 data_time: 0.0069 memory: 10464 grad_norm: 6.3286 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.5896 loss: 2.5896 2022/09/07 18:26:46 - mmengine - INFO - Epoch(train) [9][1740/1793] lr: 7.5000e-03 eta: 11:45:58 time: 0.7812 data_time: 0.0098 memory: 10464 grad_norm: 6.6013 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.6482 loss: 2.6482 2022/09/07 18:26:51 - mmengine - INFO - Epoch(train) [9][1760/1793] lr: 7.5000e-03 eta: 11:45:18 time: 0.2597 data_time: 0.0122 memory: 10464 grad_norm: 6.8216 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.6454 loss: 2.6454 2022/09/07 18:26:57 - mmengine - INFO - Epoch(train) [9][1780/1793] lr: 7.5000e-03 eta: 11:44:42 time: 0.3093 data_time: 0.0057 memory: 10464 grad_norm: 6.5928 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.8663 loss: 2.8663 2022/09/07 18:27:00 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 18:27:00 - mmengine - INFO - Epoch(train) [9][1793/1793] lr: 7.5000e-03 eta: 11:44:42 time: 0.2756 data_time: 0.0090 memory: 10464 grad_norm: 6.6554 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.8201 loss: 2.8201 2022/09/07 18:27:00 - mmengine - INFO - Saving checkpoint at 9 epochs 2022/09/07 18:27:04 - mmengine - INFO - Epoch(val) [9][20/241] eta: 0:00:13 time: 0.0611 data_time: 0.0097 memory: 1482 2022/09/07 18:27:05 - mmengine - INFO - Epoch(val) [9][40/241] eta: 0:00:11 time: 0.0558 data_time: 0.0057 memory: 1482 2022/09/07 18:27:06 - mmengine - INFO - Epoch(val) [9][60/241] eta: 0:00:10 time: 0.0558 data_time: 0.0053 memory: 1482 2022/09/07 18:27:07 - mmengine - INFO - Epoch(val) [9][80/241] eta: 0:00:09 time: 0.0562 data_time: 0.0054 memory: 1482 2022/09/07 18:27:08 - mmengine - INFO - Epoch(val) [9][100/241] eta: 0:00:07 time: 0.0558 data_time: 0.0054 memory: 1482 2022/09/07 18:27:09 - mmengine - INFO - Epoch(val) [9][120/241] eta: 0:00:06 time: 0.0556 data_time: 0.0057 memory: 1482 2022/09/07 18:27:10 - mmengine - INFO - Epoch(val) [9][140/241] eta: 0:00:05 time: 0.0551 data_time: 0.0053 memory: 1482 2022/09/07 18:27:11 - mmengine - INFO - Epoch(val) [9][160/241] eta: 0:00:04 time: 0.0548 data_time: 0.0049 memory: 1482 2022/09/07 18:27:12 - mmengine - INFO - Epoch(val) [9][180/241] eta: 0:00:03 time: 0.0555 data_time: 0.0053 memory: 1482 2022/09/07 18:27:14 - mmengine - INFO - Epoch(val) [9][200/241] eta: 0:00:02 time: 0.0547 data_time: 0.0051 memory: 1482 2022/09/07 18:27:15 - mmengine - INFO - Epoch(val) [9][220/241] eta: 0:00:01 time: 0.0546 data_time: 0.0050 memory: 1482 2022/09/07 18:27:16 - mmengine - INFO - Epoch(val) [9][240/241] eta: 0:00:00 time: 0.0542 data_time: 0.0046 memory: 1482 2022/09/07 18:27:16 - mmengine - INFO - Epoch(val) [9][241/241] acc/top1: 0.2909 acc/top5: 0.5802 acc/mean1: 0.2691 2022/09/07 18:27:17 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_8.pth is removed 2022/09/07 18:27:18 - mmengine - INFO - The best checkpoint with 0.2909 acc/top1 at 9 epoch is saved to best_acc/top1_epoch_9.pth. 2022/09/07 18:27:26 - mmengine - INFO - Epoch(train) [10][20/1793] lr: 7.5000e-03 eta: 11:43:31 time: 0.3792 data_time: 0.0284 memory: 10464 grad_norm: 6.5835 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.9149 loss: 2.9149 2022/09/07 18:27:33 - mmengine - INFO - Epoch(train) [10][40/1793] lr: 7.5000e-03 eta: 11:42:59 time: 0.3517 data_time: 0.0074 memory: 10464 grad_norm: 6.7558 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6573 loss: 2.6573 2022/09/07 18:27:40 - mmengine - INFO - Epoch(train) [10][60/1793] lr: 7.5000e-03 eta: 11:42:29 time: 0.3686 data_time: 0.0105 memory: 10464 grad_norm: 6.8966 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3602 loss: 2.3602 2022/09/07 18:27:48 - mmengine - INFO - Epoch(train) [10][80/1793] lr: 7.5000e-03 eta: 11:42:01 time: 0.3847 data_time: 0.0061 memory: 10464 grad_norm: 7.0284 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3262 loss: 2.3262 2022/09/07 18:27:55 - mmengine - INFO - Epoch(train) [10][100/1793] lr: 7.5000e-03 eta: 11:41:29 time: 0.3468 data_time: 0.0108 memory: 10464 grad_norm: 6.8429 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.4366 loss: 2.4366 2022/09/07 18:28:04 - mmengine - INFO - Epoch(train) [10][120/1793] lr: 7.5000e-03 eta: 11:41:06 time: 0.4472 data_time: 0.1787 memory: 10464 grad_norm: 6.8456 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3696 loss: 2.3696 2022/09/07 18:28:09 - mmengine - INFO - Epoch(train) [10][140/1793] lr: 7.5000e-03 eta: 11:40:28 time: 0.2789 data_time: 0.0089 memory: 10464 grad_norm: 6.5534 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.5529 loss: 2.5529 2022/09/07 18:28:14 - mmengine - INFO - Epoch(train) [10][160/1793] lr: 7.5000e-03 eta: 11:39:47 time: 0.2447 data_time: 0.0072 memory: 10464 grad_norm: 6.9209 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4503 loss: 2.4503 2022/09/07 18:28:20 - mmengine - INFO - Epoch(train) [10][180/1793] lr: 7.5000e-03 eta: 11:39:08 time: 0.2678 data_time: 0.0086 memory: 10464 grad_norm: 6.9492 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 2.7772 loss: 2.7772 2022/09/07 18:28:26 - mmengine - INFO - Epoch(train) [10][200/1793] lr: 7.5000e-03 eta: 11:38:34 time: 0.3240 data_time: 0.0059 memory: 10464 grad_norm: 6.6130 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.8436 loss: 2.8436 2022/09/07 18:28:33 - mmengine - INFO - Epoch(train) [10][220/1793] lr: 7.5000e-03 eta: 11:38:04 time: 0.3577 data_time: 0.0092 memory: 10464 grad_norm: 6.6825 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5758 loss: 2.5758 2022/09/07 18:28:38 - mmengine - INFO - Epoch(train) [10][240/1793] lr: 7.5000e-03 eta: 11:37:20 time: 0.2147 data_time: 0.0065 memory: 10464 grad_norm: 6.7963 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4503 loss: 2.4503 2022/09/07 18:28:42 - mmengine - INFO - Epoch(train) [10][260/1793] lr: 7.5000e-03 eta: 11:36:40 time: 0.2449 data_time: 0.0098 memory: 10464 grad_norm: 7.0680 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6932 loss: 2.6932 2022/09/07 18:28:51 - mmengine - INFO - Epoch(train) [10][280/1793] lr: 7.5000e-03 eta: 11:36:17 time: 0.4473 data_time: 0.0060 memory: 10464 grad_norm: 6.7194 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6217 loss: 2.6217 2022/09/07 18:28:57 - mmengine - INFO - Epoch(train) [10][300/1793] lr: 7.5000e-03 eta: 11:35:42 time: 0.3001 data_time: 0.0099 memory: 10464 grad_norm: 6.7958 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.8884 loss: 2.8884 2022/09/07 18:29:06 - mmengine - INFO - Epoch(train) [10][320/1793] lr: 7.5000e-03 eta: 11:35:17 time: 0.4201 data_time: 0.0080 memory: 10464 grad_norm: 7.0747 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4159 loss: 2.4159 2022/09/07 18:29:11 - mmengine - INFO - Epoch(train) [10][340/1793] lr: 7.5000e-03 eta: 11:34:39 time: 0.2693 data_time: 0.0102 memory: 10464 grad_norm: 6.8928 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.4760 loss: 2.4760 2022/09/07 18:29:19 - mmengine - INFO - Epoch(train) [10][360/1793] lr: 7.5000e-03 eta: 11:34:09 time: 0.3649 data_time: 0.0066 memory: 10464 grad_norm: 7.1829 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.4851 loss: 2.4851 2022/09/07 18:29:26 - mmengine - INFO - Epoch(train) [10][380/1793] lr: 7.5000e-03 eta: 11:33:42 time: 0.3881 data_time: 0.0085 memory: 10464 grad_norm: 7.2443 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3792 loss: 2.3792 2022/09/07 18:29:34 - mmengine - INFO - Epoch(train) [10][400/1793] lr: 7.5000e-03 eta: 11:33:13 time: 0.3718 data_time: 0.0078 memory: 10464 grad_norm: 6.7192 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.8896 loss: 2.8896 2022/09/07 18:29:41 - mmengine - INFO - Epoch(train) [10][420/1793] lr: 7.5000e-03 eta: 11:32:43 time: 0.3551 data_time: 0.0827 memory: 10464 grad_norm: 6.7296 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.7047 loss: 2.7047 2022/09/07 18:29:48 - mmengine - INFO - Epoch(train) [10][440/1793] lr: 7.5000e-03 eta: 11:32:11 time: 0.3356 data_time: 0.1467 memory: 10464 grad_norm: 6.9187 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.6258 loss: 2.6258 2022/09/07 18:29:52 - mmengine - INFO - Epoch(train) [10][460/1793] lr: 7.5000e-03 eta: 11:31:31 time: 0.2440 data_time: 0.0098 memory: 10464 grad_norm: 6.5772 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5486 loss: 2.5486 2022/09/07 18:29:58 - mmengine - INFO - Epoch(train) [10][480/1793] lr: 7.5000e-03 eta: 11:30:53 time: 0.2614 data_time: 0.0847 memory: 10464 grad_norm: 6.8016 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4820 loss: 2.4820 2022/09/07 18:30:04 - mmengine - INFO - Epoch(train) [10][500/1793] lr: 7.5000e-03 eta: 11:30:20 time: 0.3210 data_time: 0.0096 memory: 10464 grad_norm: 6.9789 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.8490 loss: 2.8490 2022/09/07 18:30:13 - mmengine - INFO - Epoch(train) [10][520/1793] lr: 7.5000e-03 eta: 11:29:58 time: 0.4499 data_time: 0.1328 memory: 10464 grad_norm: 7.1385 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1306 loss: 2.1306 2022/09/07 18:30:19 - mmengine - INFO - Epoch(train) [10][540/1793] lr: 7.5000e-03 eta: 11:29:24 time: 0.3117 data_time: 0.0650 memory: 10464 grad_norm: 6.8381 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.8703 loss: 2.8703 2022/09/07 18:30:25 - mmengine - INFO - Epoch(train) [10][560/1793] lr: 7.5000e-03 eta: 11:28:47 time: 0.2624 data_time: 0.0054 memory: 10464 grad_norm: 6.8216 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.7173 loss: 2.7173 2022/09/07 18:30:34 - mmengine - INFO - Epoch(train) [10][580/1793] lr: 7.5000e-03 eta: 11:28:25 time: 0.4511 data_time: 0.0347 memory: 10464 grad_norm: 7.1740 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3440 loss: 2.3440 2022/09/07 18:30:38 - mmengine - INFO - Epoch(train) [10][600/1793] lr: 7.5000e-03 eta: 11:27:42 time: 0.1970 data_time: 0.0061 memory: 10464 grad_norm: 7.0370 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.7802 loss: 2.7802 2022/09/07 18:30:45 - mmengine - INFO - Epoch(train) [10][620/1793] lr: 7.5000e-03 eta: 11:27:15 time: 0.3892 data_time: 0.0088 memory: 10464 grad_norm: 6.8585 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6024 loss: 2.6024 2022/09/07 18:30:49 - mmengine - INFO - Epoch(train) [10][640/1793] lr: 7.5000e-03 eta: 11:26:30 time: 0.1758 data_time: 0.0055 memory: 10464 grad_norm: 6.8557 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3812 loss: 2.3812 2022/09/07 18:30:56 - mmengine - INFO - Epoch(train) [10][660/1793] lr: 7.5000e-03 eta: 11:26:03 time: 0.3832 data_time: 0.1500 memory: 10464 grad_norm: 6.8271 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4651 loss: 2.4651 2022/09/07 18:31:05 - mmengine - INFO - Epoch(train) [10][680/1793] lr: 7.5000e-03 eta: 11:25:39 time: 0.4206 data_time: 0.2466 memory: 10464 grad_norm: 6.8317 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.6455 loss: 2.6455 2022/09/07 18:31:13 - mmengine - INFO - Epoch(train) [10][700/1793] lr: 7.5000e-03 eta: 11:25:12 time: 0.3802 data_time: 0.0110 memory: 10464 grad_norm: 6.7730 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.5900 loss: 2.5900 2022/09/07 18:31:17 - mmengine - INFO - Epoch(train) [10][720/1793] lr: 7.5000e-03 eta: 11:24:29 time: 0.2002 data_time: 0.0063 memory: 10464 grad_norm: 6.4499 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3476 loss: 2.3476 2022/09/07 18:31:22 - mmengine - INFO - Epoch(train) [10][740/1793] lr: 7.5000e-03 eta: 11:23:51 time: 0.2579 data_time: 0.0090 memory: 10464 grad_norm: 7.3915 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.7857 loss: 2.7857 2022/09/07 18:31:25 - mmengine - INFO - Epoch(train) [10][760/1793] lr: 7.5000e-03 eta: 11:23:07 time: 0.1805 data_time: 0.0069 memory: 10464 grad_norm: 6.6090 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.8162 loss: 2.8162 2022/09/07 18:31:29 - mmengine - INFO - Epoch(train) [10][780/1793] lr: 7.5000e-03 eta: 11:22:22 time: 0.1759 data_time: 0.0060 memory: 10464 grad_norm: 6.8004 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.5852 loss: 2.5852 2022/09/07 18:31:32 - mmengine - INFO - Epoch(train) [10][800/1793] lr: 7.5000e-03 eta: 11:21:38 time: 0.1782 data_time: 0.0103 memory: 10464 grad_norm: 6.8507 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.3976 loss: 2.3976 2022/09/07 18:31:36 - mmengine - INFO - Epoch(train) [10][820/1793] lr: 7.5000e-03 eta: 11:20:55 time: 0.1918 data_time: 0.0057 memory: 10464 grad_norm: 6.8769 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4199 loss: 2.4199 2022/09/07 18:31:40 - mmengine - INFO - Epoch(train) [10][840/1793] lr: 7.5000e-03 eta: 11:20:11 time: 0.1829 data_time: 0.0081 memory: 10464 grad_norm: 7.0534 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7763 loss: 2.7763 2022/09/07 18:31:43 - mmengine - INFO - Epoch(train) [10][860/1793] lr: 7.5000e-03 eta: 11:19:27 time: 0.1777 data_time: 0.0074 memory: 10464 grad_norm: 6.9789 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5182 loss: 2.5182 2022/09/07 18:31:44 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 18:31:47 - mmengine - INFO - Epoch(train) [10][880/1793] lr: 7.5000e-03 eta: 11:18:43 time: 0.1730 data_time: 0.0071 memory: 10464 grad_norm: 6.8650 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6913 loss: 2.6913 2022/09/07 18:31:51 - mmengine - INFO - Epoch(train) [10][900/1793] lr: 7.5000e-03 eta: 11:18:03 time: 0.2210 data_time: 0.0066 memory: 10464 grad_norm: 6.7906 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.5172 loss: 2.5172 2022/09/07 18:32:00 - mmengine - INFO - Epoch(train) [10][920/1793] lr: 7.5000e-03 eta: 11:17:42 time: 0.4530 data_time: 0.0103 memory: 10464 grad_norm: 7.0663 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.9577 loss: 2.9577 2022/09/07 18:32:08 - mmengine - INFO - Epoch(train) [10][940/1793] lr: 7.5000e-03 eta: 11:17:15 time: 0.3677 data_time: 0.1790 memory: 10464 grad_norm: 6.6882 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5811 loss: 2.5811 2022/09/07 18:32:18 - mmengine - INFO - Epoch(train) [10][960/1793] lr: 7.5000e-03 eta: 11:16:58 time: 0.4961 data_time: 0.0106 memory: 10464 grad_norm: 6.7269 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.6809 loss: 2.6809 2022/09/07 18:32:23 - mmengine - INFO - Epoch(train) [10][980/1793] lr: 7.5000e-03 eta: 11:16:20 time: 0.2424 data_time: 0.0063 memory: 10464 grad_norm: 6.7456 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6540 loss: 2.6540 2022/09/07 18:32:30 - mmengine - INFO - Epoch(train) [10][1000/1793] lr: 7.5000e-03 eta: 11:15:54 time: 0.3870 data_time: 0.0083 memory: 10464 grad_norm: 6.7546 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5708 loss: 2.5708 2022/09/07 18:32:37 - mmengine - INFO - Epoch(train) [10][1020/1793] lr: 7.5000e-03 eta: 11:15:26 time: 0.3581 data_time: 0.0071 memory: 10464 grad_norm: 7.1408 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.6148 loss: 2.6148 2022/09/07 18:32:42 - mmengine - INFO - Epoch(train) [10][1040/1793] lr: 7.5000e-03 eta: 11:14:49 time: 0.2473 data_time: 0.0087 memory: 10464 grad_norm: 7.1717 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.6587 loss: 2.6587 2022/09/07 18:32:47 - mmengine - INFO - Epoch(train) [10][1060/1793] lr: 7.5000e-03 eta: 11:14:12 time: 0.2567 data_time: 0.0064 memory: 10464 grad_norm: 6.9697 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5916 loss: 2.5916 2022/09/07 18:32:59 - mmengine - INFO - Epoch(train) [10][1080/1793] lr: 7.5000e-03 eta: 11:14:02 time: 0.5733 data_time: 0.0084 memory: 10464 grad_norm: 6.8414 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.4609 loss: 2.4609 2022/09/07 18:33:05 - mmengine - INFO - Epoch(train) [10][1100/1793] lr: 7.5000e-03 eta: 11:13:30 time: 0.3146 data_time: 0.0167 memory: 10464 grad_norm: 7.1140 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.8726 loss: 2.8726 2022/09/07 18:33:11 - mmengine - INFO - Epoch(train) [10][1120/1793] lr: 7.5000e-03 eta: 11:12:55 time: 0.2650 data_time: 0.0055 memory: 10464 grad_norm: 6.8970 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.6721 loss: 2.6721 2022/09/07 18:33:17 - mmengine - INFO - Epoch(train) [10][1140/1793] lr: 7.5000e-03 eta: 11:12:24 time: 0.3224 data_time: 0.0083 memory: 10464 grad_norm: 6.8631 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.4698 loss: 2.4698 2022/09/07 18:33:26 - mmengine - INFO - Epoch(train) [10][1160/1793] lr: 7.5000e-03 eta: 11:12:04 time: 0.4511 data_time: 0.0436 memory: 10464 grad_norm: 7.0744 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 2.7368 loss: 2.7368 2022/09/07 18:33:33 - mmengine - INFO - Epoch(train) [10][1180/1793] lr: 7.5000e-03 eta: 11:11:35 time: 0.3434 data_time: 0.0086 memory: 10464 grad_norm: 6.7162 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.5290 loss: 2.5290 2022/09/07 18:33:38 - mmengine - INFO - Epoch(train) [10][1200/1793] lr: 7.5000e-03 eta: 11:10:58 time: 0.2520 data_time: 0.0059 memory: 10464 grad_norm: 6.9242 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3360 loss: 2.3360 2022/09/07 18:33:48 - mmengine - INFO - Epoch(train) [10][1220/1793] lr: 7.5000e-03 eta: 11:10:43 time: 0.5034 data_time: 0.3261 memory: 10464 grad_norm: 6.7826 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.8100 loss: 2.8100 2022/09/07 18:33:53 - mmengine - INFO - Epoch(train) [10][1240/1793] lr: 7.5000e-03 eta: 11:10:07 time: 0.2671 data_time: 0.0744 memory: 10464 grad_norm: 6.9160 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2900 loss: 2.2900 2022/09/07 18:34:02 - mmengine - INFO - Epoch(train) [10][1260/1793] lr: 7.5000e-03 eta: 11:09:46 time: 0.4299 data_time: 0.0056 memory: 10464 grad_norm: 6.6062 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.8918 loss: 2.8918 2022/09/07 18:34:09 - mmengine - INFO - Epoch(train) [10][1280/1793] lr: 7.5000e-03 eta: 11:09:16 time: 0.3276 data_time: 0.0108 memory: 10464 grad_norm: 6.6024 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 3.0289 loss: 3.0289 2022/09/07 18:34:23 - mmengine - INFO - Epoch(train) [10][1300/1793] lr: 7.5000e-03 eta: 11:09:19 time: 0.7273 data_time: 0.0060 memory: 10464 grad_norm: 7.0325 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.7317 loss: 2.7317 2022/09/07 18:34:28 - mmengine - INFO - Epoch(train) [10][1320/1793] lr: 7.5000e-03 eta: 11:08:44 time: 0.2665 data_time: 0.0101 memory: 10464 grad_norm: 6.8236 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6672 loss: 2.6672 2022/09/07 18:34:37 - mmengine - INFO - Epoch(train) [10][1340/1793] lr: 7.5000e-03 eta: 11:08:22 time: 0.4236 data_time: 0.0057 memory: 10464 grad_norm: 6.7902 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5544 loss: 2.5544 2022/09/07 18:34:43 - mmengine - INFO - Epoch(train) [10][1360/1793] lr: 7.5000e-03 eta: 11:07:50 time: 0.3036 data_time: 0.1172 memory: 10464 grad_norm: 6.6610 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5284 loss: 2.5284 2022/09/07 18:34:51 - mmengine - INFO - Epoch(train) [10][1380/1793] lr: 7.5000e-03 eta: 11:07:26 time: 0.4008 data_time: 0.0054 memory: 10464 grad_norm: 7.1457 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3478 loss: 2.3478 2022/09/07 18:34:56 - mmengine - INFO - Epoch(train) [10][1400/1793] lr: 7.5000e-03 eta: 11:06:50 time: 0.2536 data_time: 0.0476 memory: 10464 grad_norm: 6.8746 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7160 loss: 2.7160 2022/09/07 18:35:02 - mmengine - INFO - Epoch(train) [10][1420/1793] lr: 7.5000e-03 eta: 11:06:19 time: 0.3130 data_time: 0.0055 memory: 10464 grad_norm: 6.5693 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 3.0242 loss: 3.0242 2022/09/07 18:35:08 - mmengine - INFO - Epoch(train) [10][1440/1793] lr: 7.5000e-03 eta: 11:05:45 time: 0.2720 data_time: 0.0969 memory: 10464 grad_norm: 6.5858 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4809 loss: 2.4809 2022/09/07 18:35:13 - mmengine - INFO - Epoch(train) [10][1460/1793] lr: 7.5000e-03 eta: 11:05:08 time: 0.2402 data_time: 0.0699 memory: 10464 grad_norm: 7.0231 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.0022 loss: 3.0022 2022/09/07 18:35:18 - mmengine - INFO - Epoch(train) [10][1480/1793] lr: 7.5000e-03 eta: 11:04:33 time: 0.2657 data_time: 0.0722 memory: 10464 grad_norm: 6.6978 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5061 loss: 2.5061 2022/09/07 18:35:26 - mmengine - INFO - Epoch(train) [10][1500/1793] lr: 7.5000e-03 eta: 11:04:11 time: 0.4135 data_time: 0.0064 memory: 10464 grad_norm: 7.0286 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.8274 loss: 2.8274 2022/09/07 18:35:33 - mmengine - INFO - Epoch(train) [10][1520/1793] lr: 7.5000e-03 eta: 11:03:43 time: 0.3538 data_time: 0.0086 memory: 10464 grad_norm: 7.2019 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1847 loss: 2.1847 2022/09/07 18:35:39 - mmengine - INFO - Epoch(train) [10][1540/1793] lr: 7.5000e-03 eta: 11:03:13 time: 0.3108 data_time: 0.0064 memory: 10464 grad_norm: 6.8394 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6124 loss: 2.6124 2022/09/07 18:35:50 - mmengine - INFO - Epoch(train) [10][1560/1793] lr: 7.5000e-03 eta: 11:03:00 time: 0.5289 data_time: 0.3018 memory: 10464 grad_norm: 6.7062 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7666 loss: 2.7666 2022/09/07 18:35:59 - mmengine - INFO - Epoch(train) [10][1580/1793] lr: 7.5000e-03 eta: 11:02:42 time: 0.4737 data_time: 0.0106 memory: 10464 grad_norm: 6.8706 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.5792 loss: 2.5792 2022/09/07 18:36:04 - mmengine - INFO - Epoch(train) [10][1600/1793] lr: 7.5000e-03 eta: 11:02:06 time: 0.2452 data_time: 0.0054 memory: 10464 grad_norm: 6.7058 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5081 loss: 2.5081 2022/09/07 18:36:11 - mmengine - INFO - Epoch(train) [10][1620/1793] lr: 7.5000e-03 eta: 11:01:36 time: 0.3147 data_time: 0.0678 memory: 10464 grad_norm: 6.9494 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4277 loss: 2.4277 2022/09/07 18:36:19 - mmengine - INFO - Epoch(train) [10][1640/1793] lr: 7.5000e-03 eta: 11:01:13 time: 0.4009 data_time: 0.0065 memory: 10464 grad_norm: 6.7722 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6782 loss: 2.6782 2022/09/07 18:36:25 - mmengine - INFO - Epoch(train) [10][1660/1793] lr: 7.5000e-03 eta: 11:00:41 time: 0.2934 data_time: 0.0080 memory: 10464 grad_norm: 6.9863 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8601 loss: 2.8601 2022/09/07 18:36:32 - mmengine - INFO - Epoch(train) [10][1680/1793] lr: 7.5000e-03 eta: 11:00:13 time: 0.3480 data_time: 0.1720 memory: 10464 grad_norm: 7.0563 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3863 loss: 2.3863 2022/09/07 18:36:37 - mmengine - INFO - Epoch(train) [10][1700/1793] lr: 7.5000e-03 eta: 10:59:40 time: 0.2814 data_time: 0.1071 memory: 10464 grad_norm: 6.8407 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3095 loss: 2.3095 2022/09/07 18:36:43 - mmengine - INFO - Epoch(train) [10][1720/1793] lr: 7.5000e-03 eta: 10:59:07 time: 0.2737 data_time: 0.0058 memory: 10464 grad_norm: 6.4827 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 2.6039 loss: 2.6039 2022/09/07 18:36:49 - mmengine - INFO - Epoch(train) [10][1740/1793] lr: 7.5000e-03 eta: 10:58:36 time: 0.2993 data_time: 0.0074 memory: 10464 grad_norm: 6.7362 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.7446 loss: 2.7446 2022/09/07 18:36:54 - mmengine - INFO - Epoch(train) [10][1760/1793] lr: 7.5000e-03 eta: 10:58:02 time: 0.2712 data_time: 0.0067 memory: 10464 grad_norm: 6.9881 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2717 loss: 2.2717 2022/09/07 18:37:00 - mmengine - INFO - Epoch(train) [10][1780/1793] lr: 7.5000e-03 eta: 10:57:29 time: 0.2746 data_time: 0.0087 memory: 10464 grad_norm: 6.8015 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.7488 loss: 2.7488 2022/09/07 18:37:03 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 18:37:03 - mmengine - INFO - Epoch(train) [10][1793/1793] lr: 7.5000e-03 eta: 10:57:29 time: 0.2531 data_time: 0.0913 memory: 10464 grad_norm: 7.0103 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.7829 loss: 2.7829 2022/09/07 18:37:03 - mmengine - INFO - Saving checkpoint at 10 epochs 2022/09/07 18:37:07 - mmengine - INFO - Epoch(val) [10][20/241] eta: 0:00:12 time: 0.0585 data_time: 0.0091 memory: 1482 2022/09/07 18:37:08 - mmengine - INFO - Epoch(val) [10][40/241] eta: 0:00:10 time: 0.0538 data_time: 0.0053 memory: 1482 2022/09/07 18:37:09 - mmengine - INFO - Epoch(val) [10][60/241] eta: 0:00:09 time: 0.0535 data_time: 0.0053 memory: 1482 2022/09/07 18:37:10 - mmengine - INFO - Epoch(val) [10][80/241] eta: 0:00:08 time: 0.0533 data_time: 0.0050 memory: 1482 2022/09/07 18:37:11 - mmengine - INFO - Epoch(val) [10][100/241] eta: 0:00:07 time: 0.0524 data_time: 0.0042 memory: 1482 2022/09/07 18:37:12 - mmengine - INFO - Epoch(val) [10][120/241] eta: 0:00:06 time: 0.0536 data_time: 0.0052 memory: 1482 2022/09/07 18:37:13 - mmengine - INFO - Epoch(val) [10][140/241] eta: 0:00:05 time: 0.0530 data_time: 0.0046 memory: 1482 2022/09/07 18:37:14 - mmengine - INFO - Epoch(val) [10][160/241] eta: 0:00:04 time: 0.0537 data_time: 0.0054 memory: 1482 2022/09/07 18:37:15 - mmengine - INFO - Epoch(val) [10][180/241] eta: 0:00:03 time: 0.0523 data_time: 0.0041 memory: 1482 2022/09/07 18:37:16 - mmengine - INFO - Epoch(val) [10][200/241] eta: 0:00:02 time: 0.0525 data_time: 0.0046 memory: 1482 2022/09/07 18:37:17 - mmengine - INFO - Epoch(val) [10][220/241] eta: 0:00:01 time: 0.0573 data_time: 0.0066 memory: 1482 2022/09/07 18:37:18 - mmengine - INFO - Epoch(val) [10][240/241] eta: 0:00:00 time: 0.0515 data_time: 0.0039 memory: 1482 2022/09/07 18:37:19 - mmengine - INFO - Epoch(val) [10][241/241] acc/top1: 0.2958 acc/top5: 0.5847 acc/mean1: 0.2576 2022/09/07 18:37:19 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_9.pth is removed 2022/09/07 18:37:21 - mmengine - INFO - The best checkpoint with 0.2958 acc/top1 at 10 epoch is saved to best_acc/top1_epoch_10.pth. 2022/09/07 18:37:25 - mmengine - INFO - Epoch(train) [11][20/1793] lr: 7.5000e-03 eta: 10:56:15 time: 0.1995 data_time: 0.0099 memory: 10464 grad_norm: 6.6773 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4402 loss: 2.4402 2022/09/07 18:37:30 - mmengine - INFO - Epoch(train) [11][40/1793] lr: 7.5000e-03 eta: 10:55:41 time: 0.2612 data_time: 0.0065 memory: 10464 grad_norm: 6.8672 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7031 loss: 2.7031 2022/09/07 18:37:34 - mmengine - INFO - Epoch(train) [11][60/1793] lr: 7.5000e-03 eta: 10:55:00 time: 0.1763 data_time: 0.0082 memory: 10464 grad_norm: 6.7076 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4982 loss: 2.4982 2022/09/07 18:37:36 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 18:37:38 - mmengine - INFO - Epoch(train) [11][80/1793] lr: 7.5000e-03 eta: 10:54:21 time: 0.1971 data_time: 0.0075 memory: 10464 grad_norm: 6.7996 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.8650 loss: 2.8650 2022/09/07 18:37:41 - mmengine - INFO - Epoch(train) [11][100/1793] lr: 7.5000e-03 eta: 10:53:40 time: 0.1737 data_time: 0.0063 memory: 10464 grad_norm: 6.9083 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2990 loss: 2.2990 2022/09/07 18:37:46 - mmengine - INFO - Epoch(train) [11][120/1793] lr: 7.5000e-03 eta: 10:53:06 time: 0.2472 data_time: 0.0092 memory: 10464 grad_norm: 6.8225 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.6947 loss: 2.6947 2022/09/07 18:37:54 - mmengine - INFO - Epoch(train) [11][140/1793] lr: 7.5000e-03 eta: 10:52:42 time: 0.3888 data_time: 0.0058 memory: 10464 grad_norm: 6.6934 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3673 loss: 2.3673 2022/09/07 18:38:01 - mmengine - INFO - Epoch(train) [11][160/1793] lr: 7.5000e-03 eta: 10:52:18 time: 0.3766 data_time: 0.0533 memory: 10464 grad_norm: 6.8750 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5659 loss: 2.5659 2022/09/07 18:38:06 - mmengine - INFO - Epoch(train) [11][180/1793] lr: 7.5000e-03 eta: 10:51:43 time: 0.2457 data_time: 0.0386 memory: 10464 grad_norm: 6.9947 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.5454 loss: 2.5454 2022/09/07 18:38:13 - mmengine - INFO - Epoch(train) [11][200/1793] lr: 7.5000e-03 eta: 10:51:14 time: 0.3203 data_time: 0.0088 memory: 10464 grad_norm: 6.4578 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3424 loss: 2.3424 2022/09/07 18:38:24 - mmengine - INFO - Epoch(train) [11][220/1793] lr: 7.5000e-03 eta: 10:51:04 time: 0.5571 data_time: 0.0055 memory: 10464 grad_norm: 6.9090 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5251 loss: 2.5251 2022/09/07 18:38:29 - mmengine - INFO - Epoch(train) [11][240/1793] lr: 7.5000e-03 eta: 10:50:32 time: 0.2802 data_time: 0.0665 memory: 10464 grad_norm: 6.8781 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.7207 loss: 2.7207 2022/09/07 18:38:34 - mmengine - INFO - Epoch(train) [11][260/1793] lr: 7.5000e-03 eta: 10:49:57 time: 0.2411 data_time: 0.0596 memory: 10464 grad_norm: 6.5368 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.8136 loss: 2.8136 2022/09/07 18:38:41 - mmengine - INFO - Epoch(train) [11][280/1793] lr: 7.5000e-03 eta: 10:49:31 time: 0.3458 data_time: 0.0086 memory: 10464 grad_norm: 7.2867 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.6134 loss: 2.6134 2022/09/07 18:38:48 - mmengine - INFO - Epoch(train) [11][300/1793] lr: 7.5000e-03 eta: 10:49:04 time: 0.3385 data_time: 0.0053 memory: 10464 grad_norm: 6.8717 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6252 loss: 2.6252 2022/09/07 18:38:53 - mmengine - INFO - Epoch(train) [11][320/1793] lr: 7.5000e-03 eta: 10:48:32 time: 0.2738 data_time: 0.0892 memory: 10464 grad_norm: 6.5024 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4847 loss: 2.4847 2022/09/07 18:39:01 - mmengine - INFO - Epoch(train) [11][340/1793] lr: 7.5000e-03 eta: 10:48:07 time: 0.3690 data_time: 0.0675 memory: 10464 grad_norm: 6.7282 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.4950 loss: 2.4950 2022/09/07 18:39:11 - mmengine - INFO - Epoch(train) [11][360/1793] lr: 7.5000e-03 eta: 10:47:54 time: 0.5248 data_time: 0.0078 memory: 10464 grad_norm: 6.9558 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3822 loss: 2.3822 2022/09/07 18:39:15 - mmengine - INFO - Epoch(train) [11][380/1793] lr: 7.5000e-03 eta: 10:47:17 time: 0.2068 data_time: 0.0091 memory: 10464 grad_norm: 6.7057 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2753 loss: 2.2753 2022/09/07 18:39:20 - mmengine - INFO - Epoch(train) [11][400/1793] lr: 7.5000e-03 eta: 10:46:44 time: 0.2521 data_time: 0.0057 memory: 10464 grad_norm: 6.9119 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5752 loss: 2.5752 2022/09/07 18:39:27 - mmengine - INFO - Epoch(train) [11][420/1793] lr: 7.5000e-03 eta: 10:46:17 time: 0.3435 data_time: 0.0058 memory: 10464 grad_norm: 6.9626 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7811 loss: 2.7811 2022/09/07 18:39:31 - mmengine - INFO - Epoch(train) [11][440/1793] lr: 7.5000e-03 eta: 10:45:38 time: 0.1788 data_time: 0.0083 memory: 10464 grad_norm: 7.0259 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6813 loss: 2.6813 2022/09/07 18:39:36 - mmengine - INFO - Epoch(train) [11][460/1793] lr: 7.5000e-03 eta: 10:45:04 time: 0.2503 data_time: 0.0063 memory: 10464 grad_norm: 7.0097 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.4292 loss: 2.4292 2022/09/07 18:39:41 - mmengine - INFO - Epoch(train) [11][480/1793] lr: 7.5000e-03 eta: 10:44:31 time: 0.2574 data_time: 0.0061 memory: 10464 grad_norm: 6.9823 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4606 loss: 2.4606 2022/09/07 18:39:48 - mmengine - INFO - Epoch(train) [11][500/1793] lr: 7.5000e-03 eta: 10:44:05 time: 0.3449 data_time: 0.0210 memory: 10464 grad_norm: 6.8046 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.5430 loss: 2.5430 2022/09/07 18:39:55 - mmengine - INFO - Epoch(train) [11][520/1793] lr: 7.5000e-03 eta: 10:43:39 time: 0.3386 data_time: 0.1643 memory: 10464 grad_norm: 6.9416 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5726 loss: 2.5726 2022/09/07 18:39:58 - mmengine - INFO - Epoch(train) [11][540/1793] lr: 7.5000e-03 eta: 10:43:00 time: 0.1834 data_time: 0.0142 memory: 10464 grad_norm: 6.5180 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.5237 loss: 2.5237 2022/09/07 18:40:05 - mmengine - INFO - Epoch(train) [11][560/1793] lr: 7.5000e-03 eta: 10:42:33 time: 0.3311 data_time: 0.0055 memory: 10464 grad_norm: 6.8723 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3502 loss: 2.3502 2022/09/07 18:40:10 - mmengine - INFO - Epoch(train) [11][580/1793] lr: 7.5000e-03 eta: 10:42:01 time: 0.2717 data_time: 0.0086 memory: 10464 grad_norm: 6.9846 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.3334 loss: 2.3334 2022/09/07 18:40:17 - mmengine - INFO - Epoch(train) [11][600/1793] lr: 7.5000e-03 eta: 10:41:34 time: 0.3321 data_time: 0.0062 memory: 10464 grad_norm: 6.6657 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3439 loss: 2.3439 2022/09/07 18:40:23 - mmengine - INFO - Epoch(train) [11][620/1793] lr: 7.5000e-03 eta: 10:41:06 time: 0.3064 data_time: 0.0098 memory: 10464 grad_norm: 7.0711 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5310 loss: 2.5310 2022/09/07 18:40:32 - mmengine - INFO - Epoch(train) [11][640/1793] lr: 7.5000e-03 eta: 10:40:47 time: 0.4401 data_time: 0.0069 memory: 10464 grad_norm: 6.9338 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4847 loss: 2.4847 2022/09/07 18:40:37 - mmengine - INFO - Epoch(train) [11][660/1793] lr: 7.5000e-03 eta: 10:40:14 time: 0.2442 data_time: 0.0080 memory: 10464 grad_norm: 7.2251 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 2.5805 loss: 2.5805 2022/09/07 18:40:40 - mmengine - INFO - Epoch(train) [11][680/1793] lr: 7.5000e-03 eta: 10:39:35 time: 0.1740 data_time: 0.0061 memory: 10464 grad_norm: 6.9211 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.6716 loss: 2.6716 2022/09/07 18:40:47 - mmengine - INFO - Epoch(train) [11][700/1793] lr: 7.5000e-03 eta: 10:39:10 time: 0.3548 data_time: 0.0364 memory: 10464 grad_norm: 6.7912 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4434 loss: 2.4434 2022/09/07 18:40:51 - mmengine - INFO - Epoch(train) [11][720/1793] lr: 7.5000e-03 eta: 10:38:31 time: 0.1769 data_time: 0.0090 memory: 10464 grad_norm: 7.2035 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.6136 loss: 2.6136 2022/09/07 18:40:56 - mmengine - INFO - Epoch(train) [11][740/1793] lr: 7.5000e-03 eta: 10:37:58 time: 0.2461 data_time: 0.0058 memory: 10464 grad_norm: 6.7642 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3637 loss: 2.3637 2022/09/07 18:41:01 - mmengine - INFO - Epoch(train) [11][760/1793] lr: 7.5000e-03 eta: 10:37:26 time: 0.2560 data_time: 0.0066 memory: 10464 grad_norm: 6.9303 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3860 loss: 2.3860 2022/09/07 18:41:08 - mmengine - INFO - Epoch(train) [11][780/1793] lr: 7.5000e-03 eta: 10:37:00 time: 0.3447 data_time: 0.0090 memory: 10464 grad_norm: 6.8916 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.3027 loss: 2.3027 2022/09/07 18:41:16 - mmengine - INFO - Epoch(train) [11][800/1793] lr: 7.5000e-03 eta: 10:36:38 time: 0.3850 data_time: 0.0054 memory: 10464 grad_norm: 6.8324 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.8763 loss: 2.8763 2022/09/07 18:41:21 - mmengine - INFO - Epoch(train) [11][820/1793] lr: 7.5000e-03 eta: 10:36:05 time: 0.2454 data_time: 0.0094 memory: 10464 grad_norm: 6.9791 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.7764 loss: 2.7764 2022/09/07 18:41:25 - mmengine - INFO - Epoch(train) [11][840/1793] lr: 7.5000e-03 eta: 10:35:32 time: 0.2481 data_time: 0.0053 memory: 10464 grad_norm: 7.0340 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.8882 loss: 2.8882 2022/09/07 18:41:31 - mmengine - INFO - Epoch(train) [11][860/1793] lr: 7.5000e-03 eta: 10:35:00 time: 0.2559 data_time: 0.0064 memory: 10464 grad_norm: 6.4772 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.6290 loss: 2.6290 2022/09/07 18:41:35 - mmengine - INFO - Epoch(train) [11][880/1793] lr: 7.5000e-03 eta: 10:34:25 time: 0.2046 data_time: 0.0085 memory: 10464 grad_norm: 6.8331 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7485 loss: 2.7485 2022/09/07 18:41:40 - mmengine - INFO - Epoch(train) [11][900/1793] lr: 7.5000e-03 eta: 10:33:55 time: 0.2851 data_time: 0.0062 memory: 10464 grad_norm: 7.1954 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2834 loss: 2.2834 2022/09/07 18:41:45 - mmengine - INFO - Epoch(train) [11][920/1793] lr: 7.5000e-03 eta: 10:33:22 time: 0.2399 data_time: 0.0639 memory: 10464 grad_norm: 6.8594 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.5567 loss: 2.5567 2022/09/07 18:41:53 - mmengine - INFO - Epoch(train) [11][940/1793] lr: 7.5000e-03 eta: 10:33:00 time: 0.3834 data_time: 0.1649 memory: 10464 grad_norm: 6.7412 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.5118 loss: 2.5118 2022/09/07 18:41:57 - mmengine - INFO - Epoch(train) [11][960/1793] lr: 7.5000e-03 eta: 10:32:25 time: 0.2177 data_time: 0.0410 memory: 10464 grad_norm: 7.0862 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.5141 loss: 2.5141 2022/09/07 18:42:06 - mmengine - INFO - Epoch(train) [11][980/1793] lr: 7.5000e-03 eta: 10:32:08 time: 0.4478 data_time: 0.0099 memory: 10464 grad_norm: 6.7620 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.3560 loss: 2.3560 2022/09/07 18:42:12 - mmengine - INFO - Epoch(train) [11][1000/1793] lr: 7.5000e-03 eta: 10:31:38 time: 0.2784 data_time: 0.0199 memory: 10464 grad_norm: 6.7798 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2400 loss: 2.2400 2022/09/07 18:42:17 - mmengine - INFO - Epoch(train) [11][1020/1793] lr: 7.5000e-03 eta: 10:31:07 time: 0.2734 data_time: 0.1049 memory: 10464 grad_norm: 7.0742 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.3791 loss: 2.3791 2022/09/07 18:42:23 - mmengine - INFO - Epoch(train) [11][1040/1793] lr: 7.5000e-03 eta: 10:30:38 time: 0.2818 data_time: 0.0709 memory: 10464 grad_norm: 6.9268 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2694 loss: 2.2694 2022/09/07 18:42:28 - mmengine - INFO - Epoch(train) [11][1060/1793] lr: 7.5000e-03 eta: 10:30:06 time: 0.2570 data_time: 0.0091 memory: 10464 grad_norm: 6.8192 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.8010 loss: 2.8010 2022/09/07 18:42:33 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 18:42:37 - mmengine - INFO - Epoch(train) [11][1080/1793] lr: 7.5000e-03 eta: 10:29:48 time: 0.4309 data_time: 0.0060 memory: 10464 grad_norm: 7.2796 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.6150 loss: 2.6150 2022/09/07 18:42:42 - mmengine - INFO - Epoch(train) [11][1100/1793] lr: 7.5000e-03 eta: 10:29:18 time: 0.2771 data_time: 0.0099 memory: 10464 grad_norm: 6.9026 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2474 loss: 2.2474 2022/09/07 18:42:53 - mmengine - INFO - Epoch(train) [11][1120/1793] lr: 7.5000e-03 eta: 10:29:09 time: 0.5555 data_time: 0.3773 memory: 10464 grad_norm: 6.9732 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4714 loss: 2.4714 2022/09/07 18:42:59 - mmengine - INFO - Epoch(train) [11][1140/1793] lr: 7.5000e-03 eta: 10:28:41 time: 0.2996 data_time: 0.0227 memory: 10464 grad_norm: 7.0425 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.3454 loss: 2.3454 2022/09/07 18:43:03 - mmengine - INFO - Epoch(train) [11][1160/1793] lr: 7.5000e-03 eta: 10:28:03 time: 0.1735 data_time: 0.0063 memory: 10464 grad_norm: 6.8635 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.4012 loss: 2.4012 2022/09/07 18:43:08 - mmengine - INFO - Epoch(train) [11][1180/1793] lr: 7.5000e-03 eta: 10:27:31 time: 0.2459 data_time: 0.0425 memory: 10464 grad_norm: 6.7301 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4232 loss: 2.4232 2022/09/07 18:43:11 - mmengine - INFO - Epoch(train) [11][1200/1793] lr: 7.5000e-03 eta: 10:26:54 time: 0.1744 data_time: 0.0073 memory: 10464 grad_norm: 6.9112 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.7852 loss: 2.7852 2022/09/07 18:43:15 - mmengine - INFO - Epoch(train) [11][1220/1793] lr: 7.5000e-03 eta: 10:26:17 time: 0.1746 data_time: 0.0060 memory: 10464 grad_norm: 7.0254 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4162 loss: 2.4162 2022/09/07 18:43:18 - mmengine - INFO - Epoch(train) [11][1240/1793] lr: 7.5000e-03 eta: 10:25:40 time: 0.1762 data_time: 0.0061 memory: 10464 grad_norm: 7.2421 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5233 loss: 2.5233 2022/09/07 18:43:22 - mmengine - INFO - Epoch(train) [11][1260/1793] lr: 7.5000e-03 eta: 10:25:03 time: 0.1755 data_time: 0.0085 memory: 10464 grad_norm: 6.8545 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3697 loss: 2.3697 2022/09/07 18:43:25 - mmengine - INFO - Epoch(train) [11][1280/1793] lr: 7.5000e-03 eta: 10:24:27 time: 0.1799 data_time: 0.0060 memory: 10464 grad_norm: 6.9436 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4225 loss: 2.4225 2022/09/07 18:43:29 - mmengine - INFO - Epoch(train) [11][1300/1793] lr: 7.5000e-03 eta: 10:23:50 time: 0.1742 data_time: 0.0063 memory: 10464 grad_norm: 6.7934 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4835 loss: 2.4835 2022/09/07 18:43:32 - mmengine - INFO - Epoch(train) [11][1320/1793] lr: 7.5000e-03 eta: 10:23:13 time: 0.1741 data_time: 0.0086 memory: 10464 grad_norm: 6.6475 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.7409 loss: 2.7409 2022/09/07 18:43:36 - mmengine - INFO - Epoch(train) [11][1340/1793] lr: 7.5000e-03 eta: 10:22:37 time: 0.1817 data_time: 0.0062 memory: 10464 grad_norm: 7.0087 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5740 loss: 2.5740 2022/09/07 18:43:39 - mmengine - INFO - Epoch(train) [11][1360/1793] lr: 7.5000e-03 eta: 10:22:01 time: 0.1797 data_time: 0.0059 memory: 10464 grad_norm: 6.8483 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.8519 loss: 2.8519 2022/09/07 18:43:45 - mmengine - INFO - Epoch(train) [11][1380/1793] lr: 7.5000e-03 eta: 10:21:33 time: 0.2877 data_time: 0.0089 memory: 10464 grad_norm: 6.5161 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5917 loss: 2.5917 2022/09/07 18:43:51 - mmengine - INFO - Epoch(train) [11][1400/1793] lr: 7.5000e-03 eta: 10:21:04 time: 0.2858 data_time: 0.0894 memory: 10464 grad_norm: 6.7536 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5964 loss: 2.5964 2022/09/07 18:43:58 - mmengine - INFO - Epoch(train) [11][1420/1793] lr: 7.5000e-03 eta: 10:20:42 time: 0.3645 data_time: 0.0502 memory: 10464 grad_norm: 6.9902 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4099 loss: 2.4099 2022/09/07 18:44:03 - mmengine - INFO - Epoch(train) [11][1440/1793] lr: 7.5000e-03 eta: 10:20:10 time: 0.2374 data_time: 0.0053 memory: 10464 grad_norm: 7.0507 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5424 loss: 2.5424 2022/09/07 18:44:09 - mmengine - INFO - Epoch(train) [11][1460/1793] lr: 7.5000e-03 eta: 10:19:42 time: 0.2979 data_time: 0.0081 memory: 10464 grad_norm: 7.1021 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5641 loss: 2.5641 2022/09/07 18:44:15 - mmengine - INFO - Epoch(train) [11][1480/1793] lr: 7.5000e-03 eta: 10:19:14 time: 0.2880 data_time: 0.0559 memory: 10464 grad_norm: 6.5680 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.3954 loss: 2.3954 2022/09/07 18:44:21 - mmengine - INFO - Epoch(train) [11][1500/1793] lr: 7.5000e-03 eta: 10:18:50 time: 0.3362 data_time: 0.0077 memory: 10464 grad_norm: 6.9419 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4703 loss: 2.4703 2022/09/07 18:44:27 - mmengine - INFO - Epoch(train) [11][1520/1793] lr: 7.5000e-03 eta: 10:18:19 time: 0.2546 data_time: 0.0063 memory: 10464 grad_norm: 6.8712 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5967 loss: 2.5967 2022/09/07 18:44:33 - mmengine - INFO - Epoch(train) [11][1540/1793] lr: 7.5000e-03 eta: 10:17:55 time: 0.3422 data_time: 0.0082 memory: 10464 grad_norm: 6.8645 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5057 loss: 2.5057 2022/09/07 18:44:39 - mmengine - INFO - Epoch(train) [11][1560/1793] lr: 7.5000e-03 eta: 10:17:26 time: 0.2662 data_time: 0.0334 memory: 10464 grad_norm: 7.0057 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4951 loss: 2.4951 2022/09/07 18:44:43 - mmengine - INFO - Epoch(train) [11][1580/1793] lr: 7.5000e-03 eta: 10:16:53 time: 0.2103 data_time: 0.0068 memory: 10464 grad_norm: 6.5423 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4739 loss: 2.4739 2022/09/07 18:44:48 - mmengine - INFO - Epoch(train) [11][1600/1793] lr: 7.5000e-03 eta: 10:16:23 time: 0.2688 data_time: 0.0618 memory: 10464 grad_norm: 6.8124 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3583 loss: 2.3583 2022/09/07 18:44:55 - mmengine - INFO - Epoch(train) [11][1620/1793] lr: 7.5000e-03 eta: 10:16:00 time: 0.3471 data_time: 0.0708 memory: 10464 grad_norm: 6.8309 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.6157 loss: 2.6157 2022/09/07 18:45:00 - mmengine - INFO - Epoch(train) [11][1640/1793] lr: 7.5000e-03 eta: 10:15:29 time: 0.2466 data_time: 0.0081 memory: 10464 grad_norm: 7.0192 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.6213 loss: 2.6213 2022/09/07 18:45:06 - mmengine - INFO - Epoch(train) [11][1660/1793] lr: 7.5000e-03 eta: 10:15:02 time: 0.2914 data_time: 0.0058 memory: 10464 grad_norm: 7.4088 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.1846 loss: 2.1846 2022/09/07 18:45:12 - mmengine - INFO - Epoch(train) [11][1680/1793] lr: 7.5000e-03 eta: 10:14:36 time: 0.3167 data_time: 0.0087 memory: 10464 grad_norm: 7.2843 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.5816 loss: 2.5816 2022/09/07 18:45:17 - mmengine - INFO - Epoch(train) [11][1700/1793] lr: 7.5000e-03 eta: 10:14:06 time: 0.2511 data_time: 0.0353 memory: 10464 grad_norm: 7.1943 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.5303 loss: 2.5303 2022/09/07 18:45:22 - mmengine - INFO - Epoch(train) [11][1720/1793] lr: 7.5000e-03 eta: 10:13:36 time: 0.2553 data_time: 0.0082 memory: 10464 grad_norm: 6.9248 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.3639 loss: 2.3639 2022/09/07 18:45:28 - mmengine - INFO - Epoch(train) [11][1740/1793] lr: 7.5000e-03 eta: 10:13:09 time: 0.2952 data_time: 0.0074 memory: 10464 grad_norm: 7.1076 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6637 loss: 2.6637 2022/09/07 18:45:36 - mmengine - INFO - Epoch(train) [11][1760/1793] lr: 7.5000e-03 eta: 10:12:49 time: 0.3838 data_time: 0.0080 memory: 10464 grad_norm: 6.8953 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5186 loss: 2.5186 2022/09/07 18:45:41 - mmengine - INFO - Epoch(train) [11][1780/1793] lr: 7.5000e-03 eta: 10:12:19 time: 0.2526 data_time: 0.0427 memory: 10464 grad_norm: 6.8490 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5100 loss: 2.5100 2022/09/07 18:45:44 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 18:45:44 - mmengine - INFO - Epoch(train) [11][1793/1793] lr: 7.5000e-03 eta: 10:12:19 time: 0.2565 data_time: 0.0072 memory: 10464 grad_norm: 7.3922 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.3733 loss: 2.3733 2022/09/07 18:45:44 - mmengine - INFO - Saving checkpoint at 11 epochs 2022/09/07 18:45:49 - mmengine - INFO - Epoch(val) [11][20/241] eta: 0:00:12 time: 0.0581 data_time: 0.0092 memory: 1482 2022/09/07 18:45:50 - mmengine - INFO - Epoch(val) [11][40/241] eta: 0:00:10 time: 0.0534 data_time: 0.0049 memory: 1482 2022/09/07 18:45:51 - mmengine - INFO - Epoch(val) [11][60/241] eta: 0:00:09 time: 0.0540 data_time: 0.0053 memory: 1482 2022/09/07 18:45:52 - mmengine - INFO - Epoch(val) [11][80/241] eta: 0:00:08 time: 0.0535 data_time: 0.0050 memory: 1482 2022/09/07 18:45:53 - mmengine - INFO - Epoch(val) [11][100/241] eta: 0:00:07 time: 0.0530 data_time: 0.0044 memory: 1482 2022/09/07 18:45:54 - mmengine - INFO - Epoch(val) [11][120/241] eta: 0:00:06 time: 0.0532 data_time: 0.0047 memory: 1482 2022/09/07 18:45:55 - mmengine - INFO - Epoch(val) [11][140/241] eta: 0:00:05 time: 0.0534 data_time: 0.0051 memory: 1482 2022/09/07 18:45:56 - mmengine - INFO - Epoch(val) [11][160/241] eta: 0:00:04 time: 0.0544 data_time: 0.0051 memory: 1482 2022/09/07 18:45:57 - mmengine - INFO - Epoch(val) [11][180/241] eta: 0:00:03 time: 0.0600 data_time: 0.0117 memory: 1482 2022/09/07 18:45:58 - mmengine - INFO - Epoch(val) [11][200/241] eta: 0:00:02 time: 0.0553 data_time: 0.0049 memory: 1482 2022/09/07 18:45:59 - mmengine - INFO - Epoch(val) [11][220/241] eta: 0:00:01 time: 0.0526 data_time: 0.0046 memory: 1482 2022/09/07 18:46:01 - mmengine - INFO - Epoch(val) [11][240/241] eta: 0:00:00 time: 0.0522 data_time: 0.0043 memory: 1482 2022/09/07 18:46:01 - mmengine - INFO - Epoch(val) [11][241/241] acc/top1: 0.2684 acc/top5: 0.5682 acc/mean1: 0.2407 2022/09/07 18:46:10 - mmengine - INFO - Epoch(train) [12][20/1793] lr: 7.5000e-03 eta: 10:11:31 time: 0.4355 data_time: 0.0214 memory: 10464 grad_norm: 7.1848 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3246 loss: 2.3246 2022/09/07 18:46:18 - mmengine - INFO - Epoch(train) [12][40/1793] lr: 7.5000e-03 eta: 10:11:13 time: 0.4216 data_time: 0.0749 memory: 10464 grad_norm: 6.9542 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1657 loss: 2.1657 2022/09/07 18:46:23 - mmengine - INFO - Epoch(train) [12][60/1793] lr: 7.5000e-03 eta: 10:10:44 time: 0.2566 data_time: 0.0072 memory: 10464 grad_norm: 7.0643 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.4566 loss: 2.4566 2022/09/07 18:46:27 - mmengine - INFO - Epoch(train) [12][80/1793] lr: 7.5000e-03 eta: 10:10:11 time: 0.2059 data_time: 0.0059 memory: 10464 grad_norm: 6.8415 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.5497 loss: 2.5497 2022/09/07 18:46:34 - mmengine - INFO - Epoch(train) [12][100/1793] lr: 7.5000e-03 eta: 10:09:45 time: 0.3090 data_time: 0.0061 memory: 10464 grad_norm: 6.8095 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6345 loss: 2.6345 2022/09/07 18:46:39 - mmengine - INFO - Epoch(train) [12][120/1793] lr: 7.5000e-03 eta: 10:09:17 time: 0.2750 data_time: 0.0108 memory: 10464 grad_norm: 7.0420 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4129 loss: 2.4129 2022/09/07 18:46:44 - mmengine - INFO - Epoch(train) [12][140/1793] lr: 7.5000e-03 eta: 10:08:47 time: 0.2401 data_time: 0.0687 memory: 10464 grad_norm: 6.8775 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3529 loss: 2.3529 2022/09/07 18:46:50 - mmengine - INFO - Epoch(train) [12][160/1793] lr: 7.5000e-03 eta: 10:08:20 time: 0.2843 data_time: 0.0408 memory: 10464 grad_norm: 6.9024 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.6387 loss: 2.6387 2022/09/07 18:46:57 - mmengine - INFO - Epoch(train) [12][180/1793] lr: 7.5000e-03 eta: 10:08:00 time: 0.3881 data_time: 0.1467 memory: 10464 grad_norm: 7.0065 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3700 loss: 2.3700 2022/09/07 18:47:04 - mmengine - INFO - Epoch(train) [12][200/1793] lr: 7.5000e-03 eta: 10:07:34 time: 0.3057 data_time: 0.1296 memory: 10464 grad_norm: 6.8794 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7664 loss: 2.7664 2022/09/07 18:47:10 - mmengine - INFO - Epoch(train) [12][220/1793] lr: 7.5000e-03 eta: 10:07:10 time: 0.3296 data_time: 0.0059 memory: 10464 grad_norm: 6.8254 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3603 loss: 2.3603 2022/09/07 18:47:16 - mmengine - INFO - Epoch(train) [12][240/1793] lr: 7.5000e-03 eta: 10:06:44 time: 0.3045 data_time: 0.0086 memory: 10464 grad_norm: 6.9181 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.8089 loss: 2.8089 2022/09/07 18:47:23 - mmengine - INFO - Epoch(train) [12][260/1793] lr: 7.5000e-03 eta: 10:06:23 time: 0.3591 data_time: 0.0063 memory: 10464 grad_norm: 6.9238 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3982 loss: 2.3982 2022/09/07 18:47:29 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 18:47:29 - mmengine - INFO - Epoch(train) [12][280/1793] lr: 7.5000e-03 eta: 10:05:57 time: 0.3015 data_time: 0.0101 memory: 10464 grad_norm: 7.0150 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3724 loss: 2.3724 2022/09/07 18:47:35 - mmengine - INFO - Epoch(train) [12][300/1793] lr: 7.5000e-03 eta: 10:05:28 time: 0.2600 data_time: 0.0055 memory: 10464 grad_norm: 6.8825 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2548 loss: 2.2548 2022/09/07 18:47:39 - mmengine - INFO - Epoch(train) [12][320/1793] lr: 7.5000e-03 eta: 10:04:58 time: 0.2403 data_time: 0.0663 memory: 10464 grad_norm: 7.2143 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3668 loss: 2.3668 2022/09/07 18:47:46 - mmengine - INFO - Epoch(train) [12][340/1793] lr: 7.5000e-03 eta: 10:04:33 time: 0.3133 data_time: 0.1221 memory: 10464 grad_norm: 6.9002 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4187 loss: 2.4187 2022/09/07 18:47:52 - mmengine - INFO - Epoch(train) [12][360/1793] lr: 7.5000e-03 eta: 10:04:09 time: 0.3272 data_time: 0.0140 memory: 10464 grad_norm: 6.8601 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5995 loss: 2.5995 2022/09/07 18:47:57 - mmengine - INFO - Epoch(train) [12][380/1793] lr: 7.5000e-03 eta: 10:03:40 time: 0.2452 data_time: 0.0072 memory: 10464 grad_norm: 6.8934 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4625 loss: 2.4625 2022/09/07 18:48:03 - mmengine - INFO - Epoch(train) [12][400/1793] lr: 7.5000e-03 eta: 10:03:12 time: 0.2758 data_time: 0.0090 memory: 10464 grad_norm: 7.0239 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.3339 loss: 2.3339 2022/09/07 18:48:08 - mmengine - INFO - Epoch(train) [12][420/1793] lr: 7.5000e-03 eta: 10:02:43 time: 0.2494 data_time: 0.0064 memory: 10464 grad_norm: 7.2697 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6071 loss: 2.6071 2022/09/07 18:48:14 - mmengine - INFO - Epoch(train) [12][440/1793] lr: 7.5000e-03 eta: 10:02:20 time: 0.3325 data_time: 0.1637 memory: 10464 grad_norm: 6.9955 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3750 loss: 2.3750 2022/09/07 18:48:19 - mmengine - INFO - Epoch(train) [12][460/1793] lr: 7.5000e-03 eta: 10:01:50 time: 0.2345 data_time: 0.0050 memory: 10464 grad_norm: 6.7195 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5879 loss: 2.5879 2022/09/07 18:48:25 - mmengine - INFO - Epoch(train) [12][480/1793] lr: 7.5000e-03 eta: 10:01:25 time: 0.3076 data_time: 0.0084 memory: 10464 grad_norm: 7.0107 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.3186 loss: 2.3186 2022/09/07 18:48:31 - mmengine - INFO - Epoch(train) [12][500/1793] lr: 7.5000e-03 eta: 10:00:58 time: 0.2729 data_time: 0.0066 memory: 10464 grad_norm: 7.1047 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.6275 loss: 2.6275 2022/09/07 18:48:35 - mmengine - INFO - Epoch(train) [12][520/1793] lr: 7.5000e-03 eta: 10:00:26 time: 0.2169 data_time: 0.0083 memory: 10464 grad_norm: 7.0911 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6522 loss: 2.6522 2022/09/07 18:48:41 - mmengine - INFO - Epoch(train) [12][540/1793] lr: 7.5000e-03 eta: 10:00:00 time: 0.2855 data_time: 0.0333 memory: 10464 grad_norm: 7.1017 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4882 loss: 2.4882 2022/09/07 18:48:45 - mmengine - INFO - Epoch(train) [12][560/1793] lr: 7.5000e-03 eta: 9:59:30 time: 0.2245 data_time: 0.0096 memory: 10464 grad_norm: 6.9287 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.7476 loss: 2.7476 2022/09/07 18:48:50 - mmengine - INFO - Epoch(train) [12][580/1793] lr: 7.5000e-03 eta: 9:59:02 time: 0.2614 data_time: 0.0068 memory: 10464 grad_norm: 6.7914 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.3771 loss: 2.3771 2022/09/07 18:48:54 - mmengine - INFO - Epoch(train) [12][600/1793] lr: 7.5000e-03 eta: 9:58:28 time: 0.1734 data_time: 0.0057 memory: 10464 grad_norm: 6.8271 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 2.5189 loss: 2.5189 2022/09/07 18:48:58 - mmengine - INFO - Epoch(train) [12][620/1793] lr: 7.5000e-03 eta: 9:57:55 time: 0.1907 data_time: 0.0083 memory: 10464 grad_norm: 6.4942 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.5413 loss: 2.5413 2022/09/07 18:49:01 - mmengine - INFO - Epoch(train) [12][640/1793] lr: 7.5000e-03 eta: 9:57:22 time: 0.1781 data_time: 0.0068 memory: 10464 grad_norm: 6.9429 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.4902 loss: 2.4902 2022/09/07 18:49:05 - mmengine - INFO - Epoch(train) [12][660/1793] lr: 7.5000e-03 eta: 9:56:48 time: 0.1744 data_time: 0.0062 memory: 10464 grad_norm: 6.7950 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5382 loss: 2.5382 2022/09/07 18:49:08 - mmengine - INFO - Epoch(train) [12][680/1793] lr: 7.5000e-03 eta: 9:56:15 time: 0.1764 data_time: 0.0079 memory: 10464 grad_norm: 7.0209 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2251 loss: 2.2251 2022/09/07 18:49:12 - mmengine - INFO - Epoch(train) [12][700/1793] lr: 7.5000e-03 eta: 9:55:41 time: 0.1741 data_time: 0.0068 memory: 10464 grad_norm: 7.3372 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.5690 loss: 2.5690 2022/09/07 18:49:15 - mmengine - INFO - Epoch(train) [12][720/1793] lr: 7.5000e-03 eta: 9:55:07 time: 0.1727 data_time: 0.0065 memory: 10464 grad_norm: 6.7455 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5281 loss: 2.5281 2022/09/07 18:49:19 - mmengine - INFO - Epoch(train) [12][740/1793] lr: 7.5000e-03 eta: 9:54:35 time: 0.1861 data_time: 0.0097 memory: 10464 grad_norm: 6.8833 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.2512 loss: 2.2512 2022/09/07 18:49:25 - mmengine - INFO - Epoch(train) [12][760/1793] lr: 7.5000e-03 eta: 9:54:09 time: 0.2862 data_time: 0.0069 memory: 10464 grad_norm: 7.0526 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4782 loss: 2.4782 2022/09/07 18:49:30 - mmengine - INFO - Epoch(train) [12][780/1793] lr: 7.5000e-03 eta: 9:53:42 time: 0.2636 data_time: 0.0082 memory: 10464 grad_norm: 7.0032 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.5579 loss: 2.5579 2022/09/07 18:49:39 - mmengine - INFO - Epoch(train) [12][800/1793] lr: 7.5000e-03 eta: 9:53:26 time: 0.4335 data_time: 0.0522 memory: 10464 grad_norm: 6.6972 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.3247 loss: 2.3247 2022/09/07 18:49:44 - mmengine - INFO - Epoch(train) [12][820/1793] lr: 7.5000e-03 eta: 9:53:00 time: 0.2808 data_time: 0.0260 memory: 10464 grad_norm: 6.9429 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3937 loss: 2.3937 2022/09/07 18:49:49 - mmengine - INFO - Epoch(train) [12][840/1793] lr: 7.5000e-03 eta: 9:52:30 time: 0.2215 data_time: 0.0082 memory: 10464 grad_norm: 6.6516 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4473 loss: 2.4473 2022/09/07 18:49:53 - mmengine - INFO - Epoch(train) [12][860/1793] lr: 7.5000e-03 eta: 9:51:59 time: 0.2033 data_time: 0.0062 memory: 10464 grad_norm: 7.0305 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.6960 loss: 2.6960 2022/09/07 18:49:59 - mmengine - INFO - Epoch(train) [12][880/1793] lr: 7.5000e-03 eta: 9:51:36 time: 0.3300 data_time: 0.0066 memory: 10464 grad_norm: 6.6348 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4380 loss: 2.4380 2022/09/07 18:50:05 - mmengine - INFO - Epoch(train) [12][900/1793] lr: 7.5000e-03 eta: 9:51:10 time: 0.2789 data_time: 0.0476 memory: 10464 grad_norm: 6.7288 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3507 loss: 2.3507 2022/09/07 18:50:11 - mmengine - INFO - Epoch(train) [12][920/1793] lr: 7.5000e-03 eta: 9:50:45 time: 0.2903 data_time: 0.0056 memory: 10464 grad_norm: 7.1361 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5981 loss: 2.5981 2022/09/07 18:50:17 - mmengine - INFO - Epoch(train) [12][940/1793] lr: 7.5000e-03 eta: 9:50:20 time: 0.2934 data_time: 0.0096 memory: 10464 grad_norm: 6.7709 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.4120 loss: 2.4120 2022/09/07 18:50:22 - mmengine - INFO - Epoch(train) [12][960/1793] lr: 7.5000e-03 eta: 9:49:53 time: 0.2663 data_time: 0.0062 memory: 10464 grad_norm: 6.8744 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3334 loss: 2.3334 2022/09/07 18:50:26 - mmengine - INFO - Epoch(train) [12][980/1793] lr: 7.5000e-03 eta: 9:49:21 time: 0.1844 data_time: 0.0114 memory: 10464 grad_norm: 6.9188 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5092 loss: 2.5092 2022/09/07 18:50:30 - mmengine - INFO - Epoch(train) [12][1000/1793] lr: 7.5000e-03 eta: 9:48:50 time: 0.1984 data_time: 0.0057 memory: 10464 grad_norm: 6.6348 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6138 loss: 2.6138 2022/09/07 18:50:34 - mmengine - INFO - Epoch(train) [12][1020/1793] lr: 7.5000e-03 eta: 9:48:21 time: 0.2280 data_time: 0.0063 memory: 10464 grad_norm: 6.6886 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2591 loss: 2.2591 2022/09/07 18:50:40 - mmengine - INFO - Epoch(train) [12][1040/1793] lr: 7.5000e-03 eta: 9:47:55 time: 0.2783 data_time: 0.0496 memory: 10464 grad_norm: 7.0215 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4088 loss: 2.4088 2022/09/07 18:50:43 - mmengine - INFO - Epoch(train) [12][1060/1793] lr: 7.5000e-03 eta: 9:47:22 time: 0.1771 data_time: 0.0066 memory: 10464 grad_norm: 6.9516 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.6650 loss: 2.6650 2022/09/07 18:50:49 - mmengine - INFO - Epoch(train) [12][1080/1793] lr: 7.5000e-03 eta: 9:46:56 time: 0.2756 data_time: 0.0066 memory: 10464 grad_norm: 7.0989 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5466 loss: 2.5466 2022/09/07 18:50:54 - mmengine - INFO - Epoch(train) [12][1100/1793] lr: 7.5000e-03 eta: 9:46:30 time: 0.2704 data_time: 0.1001 memory: 10464 grad_norm: 7.3015 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4545 loss: 2.4545 2022/09/07 18:51:01 - mmengine - INFO - Epoch(train) [12][1120/1793] lr: 7.5000e-03 eta: 9:46:08 time: 0.3258 data_time: 0.0074 memory: 10464 grad_norm: 6.9719 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5664 loss: 2.5664 2022/09/07 18:51:06 - mmengine - INFO - Epoch(train) [12][1140/1793] lr: 7.5000e-03 eta: 9:45:40 time: 0.2432 data_time: 0.0100 memory: 10464 grad_norm: 6.8769 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.4243 loss: 2.4243 2022/09/07 18:51:09 - mmengine - INFO - Epoch(train) [12][1160/1793] lr: 7.5000e-03 eta: 9:45:08 time: 0.1749 data_time: 0.0059 memory: 10464 grad_norm: 6.8464 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.6792 loss: 2.6792 2022/09/07 18:51:13 - mmengine - INFO - Epoch(train) [12][1180/1793] lr: 7.5000e-03 eta: 9:44:35 time: 0.1744 data_time: 0.0064 memory: 10464 grad_norm: 6.7966 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5818 loss: 2.5818 2022/09/07 18:51:18 - mmengine - INFO - Epoch(train) [12][1200/1793] lr: 7.5000e-03 eta: 9:44:09 time: 0.2618 data_time: 0.0891 memory: 10464 grad_norm: 6.8808 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4245 loss: 2.4245 2022/09/07 18:51:22 - mmengine - INFO - Epoch(train) [12][1220/1793] lr: 7.5000e-03 eta: 9:43:40 time: 0.2314 data_time: 0.0053 memory: 10464 grad_norm: 6.7592 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1950 loss: 2.1950 2022/09/07 18:51:28 - mmengine - INFO - Epoch(train) [12][1240/1793] lr: 7.5000e-03 eta: 9:43:15 time: 0.2755 data_time: 0.0073 memory: 10464 grad_norm: 6.6797 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4826 loss: 2.4826 2022/09/07 18:51:33 - mmengine - INFO - Epoch(train) [12][1260/1793] lr: 7.5000e-03 eta: 9:42:49 time: 0.2801 data_time: 0.0091 memory: 10464 grad_norm: 7.1110 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3958 loss: 2.3958 2022/09/07 18:51:37 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 18:51:38 - mmengine - INFO - Epoch(train) [12][1280/1793] lr: 7.5000e-03 eta: 9:42:21 time: 0.2288 data_time: 0.0067 memory: 10464 grad_norm: 7.3011 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4166 loss: 2.4166 2022/09/07 18:51:45 - mmengine - INFO - Epoch(train) [12][1300/1793] lr: 7.5000e-03 eta: 9:42:01 time: 0.3628 data_time: 0.0090 memory: 10464 grad_norm: 6.7205 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5752 loss: 2.5752 2022/09/07 18:51:50 - mmengine - INFO - Epoch(train) [12][1320/1793] lr: 7.5000e-03 eta: 9:41:32 time: 0.2160 data_time: 0.0423 memory: 10464 grad_norm: 6.5560 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.2571 loss: 2.2571 2022/09/07 18:51:54 - mmengine - INFO - Epoch(train) [12][1340/1793] lr: 7.5000e-03 eta: 9:41:04 time: 0.2312 data_time: 0.0645 memory: 10464 grad_norm: 7.1769 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.5344 loss: 2.5344 2022/09/07 18:51:58 - mmengine - INFO - Epoch(train) [12][1360/1793] lr: 7.5000e-03 eta: 9:40:32 time: 0.1832 data_time: 0.0056 memory: 10464 grad_norm: 6.6816 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3523 loss: 2.3523 2022/09/07 18:52:03 - mmengine - INFO - Epoch(train) [12][1380/1793] lr: 7.5000e-03 eta: 9:40:07 time: 0.2689 data_time: 0.0275 memory: 10464 grad_norm: 7.1977 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.3945 loss: 2.3945 2022/09/07 18:52:07 - mmengine - INFO - Epoch(train) [12][1400/1793] lr: 7.5000e-03 eta: 9:39:36 time: 0.1956 data_time: 0.0089 memory: 10464 grad_norm: 6.7452 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1838 loss: 2.1838 2022/09/07 18:52:18 - mmengine - INFO - Epoch(train) [12][1420/1793] lr: 7.5000e-03 eta: 9:39:27 time: 0.5225 data_time: 0.0060 memory: 10464 grad_norm: 6.8730 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.5157 loss: 2.5157 2022/09/07 18:52:23 - mmengine - INFO - Epoch(train) [12][1440/1793] lr: 7.5000e-03 eta: 9:39:00 time: 0.2425 data_time: 0.0089 memory: 10464 grad_norm: 6.8198 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3344 loss: 2.3344 2022/09/07 18:52:30 - mmengine - INFO - Epoch(train) [12][1460/1793] lr: 7.5000e-03 eta: 9:38:41 time: 0.3801 data_time: 0.0064 memory: 10464 grad_norm: 7.0604 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5444 loss: 2.5444 2022/09/07 18:52:40 - mmengine - INFO - Epoch(train) [12][1480/1793] lr: 7.5000e-03 eta: 9:38:29 time: 0.4768 data_time: 0.0089 memory: 10464 grad_norm: 6.9310 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4074 loss: 2.4074 2022/09/07 18:52:46 - mmengine - INFO - Epoch(train) [12][1500/1793] lr: 7.5000e-03 eta: 9:38:08 time: 0.3328 data_time: 0.0063 memory: 10464 grad_norm: 7.2129 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.1449 loss: 2.1449 2022/09/07 18:52:52 - mmengine - INFO - Epoch(train) [12][1520/1793] lr: 7.5000e-03 eta: 9:37:44 time: 0.2905 data_time: 0.0469 memory: 10464 grad_norm: 6.7098 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.1658 loss: 2.1658 2022/09/07 18:53:00 - mmengine - INFO - Epoch(train) [12][1540/1793] lr: 7.5000e-03 eta: 9:37:25 time: 0.3722 data_time: 0.0067 memory: 10464 grad_norm: 7.1791 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1296 loss: 2.1296 2022/09/07 18:53:04 - mmengine - INFO - Epoch(train) [12][1560/1793] lr: 7.5000e-03 eta: 9:36:56 time: 0.2077 data_time: 0.0090 memory: 10464 grad_norm: 6.9933 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5963 loss: 2.5963 2022/09/07 18:53:12 - mmengine - INFO - Epoch(train) [12][1580/1793] lr: 7.5000e-03 eta: 9:36:38 time: 0.3928 data_time: 0.0077 memory: 10464 grad_norm: 7.1971 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.7417 loss: 2.7417 2022/09/07 18:53:19 - mmengine - INFO - Epoch(train) [12][1600/1793] lr: 7.5000e-03 eta: 9:36:21 time: 0.3931 data_time: 0.0087 memory: 10464 grad_norm: 7.0265 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.4641 loss: 2.4641 2022/09/07 18:53:25 - mmengine - INFO - Epoch(train) [12][1620/1793] lr: 7.5000e-03 eta: 9:35:56 time: 0.2712 data_time: 0.0065 memory: 10464 grad_norm: 6.9543 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2471 loss: 2.2471 2022/09/07 18:53:31 - mmengine - INFO - Epoch(train) [12][1640/1793] lr: 7.5000e-03 eta: 9:35:34 time: 0.3212 data_time: 0.0081 memory: 10464 grad_norm: 7.0871 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.5391 loss: 2.5391 2022/09/07 18:53:35 - mmengine - INFO - Epoch(train) [12][1660/1793] lr: 7.5000e-03 eta: 9:35:03 time: 0.1773 data_time: 0.0064 memory: 10464 grad_norm: 6.7124 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3210 loss: 2.3210 2022/09/07 18:53:41 - mmengine - INFO - Epoch(train) [12][1680/1793] lr: 7.5000e-03 eta: 9:34:39 time: 0.2954 data_time: 0.0461 memory: 10464 grad_norm: 7.2851 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.8348 loss: 2.8348 2022/09/07 18:53:46 - mmengine - INFO - Epoch(train) [12][1700/1793] lr: 7.5000e-03 eta: 9:34:13 time: 0.2427 data_time: 0.0727 memory: 10464 grad_norm: 7.2544 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5804 loss: 2.5804 2022/09/07 18:53:53 - mmengine - INFO - Epoch(train) [12][1720/1793] lr: 7.5000e-03 eta: 9:33:54 time: 0.3659 data_time: 0.0063 memory: 10464 grad_norm: 6.8927 top1_acc: 0.0000 top5_acc: 0.8333 loss_cls: 2.7376 loss: 2.7376 2022/09/07 18:53:57 - mmengine - INFO - Epoch(train) [12][1740/1793] lr: 7.5000e-03 eta: 9:33:23 time: 0.1791 data_time: 0.0079 memory: 10464 grad_norm: 6.8236 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.7658 loss: 2.7658 2022/09/07 18:54:02 - mmengine - INFO - Epoch(train) [12][1760/1793] lr: 7.5000e-03 eta: 9:32:58 time: 0.2802 data_time: 0.0062 memory: 10464 grad_norm: 6.7723 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4286 loss: 2.4286 2022/09/07 18:54:10 - mmengine - INFO - Epoch(train) [12][1780/1793] lr: 7.5000e-03 eta: 9:32:40 time: 0.3703 data_time: 0.1297 memory: 10464 grad_norm: 6.8278 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5731 loss: 2.5731 2022/09/07 18:54:14 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 18:54:14 - mmengine - INFO - Epoch(train) [12][1793/1793] lr: 7.5000e-03 eta: 9:32:40 time: 0.4122 data_time: 0.2417 memory: 10464 grad_norm: 6.8073 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.6462 loss: 2.6462 2022/09/07 18:54:14 - mmengine - INFO - Saving checkpoint at 12 epochs 2022/09/07 18:54:18 - mmengine - INFO - Epoch(val) [12][20/241] eta: 0:00:17 time: 0.0782 data_time: 0.0290 memory: 1482 2022/09/07 18:54:19 - mmengine - INFO - Epoch(val) [12][40/241] eta: 0:00:10 time: 0.0535 data_time: 0.0051 memory: 1482 2022/09/07 18:54:20 - mmengine - INFO - Epoch(val) [12][60/241] eta: 0:00:09 time: 0.0541 data_time: 0.0054 memory: 1482 2022/09/07 18:54:21 - mmengine - INFO - Epoch(val) [12][80/241] eta: 0:00:08 time: 0.0535 data_time: 0.0050 memory: 1482 2022/09/07 18:54:22 - mmengine - INFO - Epoch(val) [12][100/241] eta: 0:00:07 time: 0.0535 data_time: 0.0049 memory: 1482 2022/09/07 18:54:23 - mmengine - INFO - Epoch(val) [12][120/241] eta: 0:00:06 time: 0.0537 data_time: 0.0052 memory: 1482 2022/09/07 18:54:25 - mmengine - INFO - Epoch(val) [12][140/241] eta: 0:00:05 time: 0.0535 data_time: 0.0051 memory: 1482 2022/09/07 18:54:26 - mmengine - INFO - Epoch(val) [12][160/241] eta: 0:00:04 time: 0.0536 data_time: 0.0053 memory: 1482 2022/09/07 18:54:27 - mmengine - INFO - Epoch(val) [12][180/241] eta: 0:00:03 time: 0.0536 data_time: 0.0052 memory: 1482 2022/09/07 18:54:28 - mmengine - INFO - Epoch(val) [12][200/241] eta: 0:00:02 time: 0.0607 data_time: 0.0127 memory: 1482 2022/09/07 18:54:29 - mmengine - INFO - Epoch(val) [12][220/241] eta: 0:00:01 time: 0.0557 data_time: 0.0045 memory: 1482 2022/09/07 18:54:30 - mmengine - INFO - Epoch(val) [12][240/241] eta: 0:00:00 time: 0.0521 data_time: 0.0039 memory: 1482 2022/09/07 18:54:31 - mmengine - INFO - Epoch(val) [12][241/241] acc/top1: 0.2874 acc/top5: 0.5868 acc/mean1: 0.2663 2022/09/07 18:54:38 - mmengine - INFO - Epoch(train) [13][20/1793] lr: 7.5000e-03 eta: 9:31:53 time: 0.3465 data_time: 0.0602 memory: 10464 grad_norm: 6.8302 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6863 loss: 2.6863 2022/09/07 18:54:44 - mmengine - INFO - Epoch(train) [13][40/1793] lr: 7.5000e-03 eta: 9:31:32 time: 0.3313 data_time: 0.0052 memory: 10464 grad_norm: 7.0171 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4433 loss: 2.4433 2022/09/07 18:54:48 - mmengine - INFO - Epoch(train) [13][60/1793] lr: 7.5000e-03 eta: 9:31:01 time: 0.1865 data_time: 0.0095 memory: 10464 grad_norm: 6.9254 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3554 loss: 2.3554 2022/09/07 18:54:52 - mmengine - INFO - Epoch(train) [13][80/1793] lr: 7.5000e-03 eta: 9:30:31 time: 0.1770 data_time: 0.0056 memory: 10464 grad_norm: 7.2148 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.5441 loss: 2.5441 2022/09/07 18:54:55 - mmengine - INFO - Epoch(train) [13][100/1793] lr: 7.5000e-03 eta: 9:30:00 time: 0.1750 data_time: 0.0063 memory: 10464 grad_norm: 6.8569 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.1228 loss: 2.1228 2022/09/07 18:54:59 - mmengine - INFO - Epoch(train) [13][120/1793] lr: 7.5000e-03 eta: 9:29:29 time: 0.1749 data_time: 0.0085 memory: 10464 grad_norm: 6.9910 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3830 loss: 2.3830 2022/09/07 18:55:02 - mmengine - INFO - Epoch(train) [13][140/1793] lr: 7.5000e-03 eta: 9:28:59 time: 0.1743 data_time: 0.0068 memory: 10464 grad_norm: 6.8596 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4460 loss: 2.4460 2022/09/07 18:55:05 - mmengine - INFO - Epoch(train) [13][160/1793] lr: 7.5000e-03 eta: 9:28:28 time: 0.1713 data_time: 0.0064 memory: 10464 grad_norm: 6.9944 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.3556 loss: 2.3556 2022/09/07 18:55:09 - mmengine - INFO - Epoch(train) [13][180/1793] lr: 7.5000e-03 eta: 9:27:58 time: 0.1825 data_time: 0.0082 memory: 10464 grad_norm: 7.3236 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3370 loss: 2.3370 2022/09/07 18:55:15 - mmengine - INFO - Epoch(train) [13][200/1793] lr: 7.5000e-03 eta: 9:27:34 time: 0.2841 data_time: 0.0070 memory: 10464 grad_norm: 7.0850 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4454 loss: 2.4454 2022/09/07 18:55:20 - mmengine - INFO - Epoch(train) [13][220/1793] lr: 7.5000e-03 eta: 9:27:11 time: 0.2826 data_time: 0.0086 memory: 10464 grad_norm: 6.9793 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3625 loss: 2.3625 2022/09/07 18:55:24 - mmengine - INFO - Epoch(train) [13][240/1793] lr: 7.5000e-03 eta: 9:26:40 time: 0.1766 data_time: 0.0076 memory: 10464 grad_norm: 6.8765 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.4533 loss: 2.4533 2022/09/07 18:55:29 - mmengine - INFO - Epoch(train) [13][260/1793] lr: 7.5000e-03 eta: 9:26:15 time: 0.2508 data_time: 0.0066 memory: 10464 grad_norm: 7.3137 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 2.3126 loss: 2.3126 2022/09/07 18:55:38 - mmengine - INFO - Epoch(train) [13][280/1793] lr: 7.5000e-03 eta: 9:26:02 time: 0.4589 data_time: 0.0065 memory: 10464 grad_norm: 6.9110 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.5309 loss: 2.5309 2022/09/07 18:55:43 - mmengine - INFO - Epoch(train) [13][300/1793] lr: 7.5000e-03 eta: 9:25:36 time: 0.2463 data_time: 0.0713 memory: 10464 grad_norm: 7.0901 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.6917 loss: 2.6917 2022/09/07 18:55:49 - mmengine - INFO - Epoch(train) [13][320/1793] lr: 7.5000e-03 eta: 9:25:13 time: 0.2833 data_time: 0.0119 memory: 10464 grad_norm: 6.8890 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.6970 loss: 2.6970 2022/09/07 18:55:58 - mmengine - INFO - Epoch(train) [13][340/1793] lr: 7.5000e-03 eta: 9:25:01 time: 0.4726 data_time: 0.2492 memory: 10464 grad_norm: 7.3914 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.8371 loss: 2.8371 2022/09/07 18:56:03 - mmengine - INFO - Epoch(train) [13][360/1793] lr: 7.5000e-03 eta: 9:24:33 time: 0.2136 data_time: 0.0387 memory: 10464 grad_norm: 7.0141 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4237 loss: 2.4237 2022/09/07 18:56:07 - mmengine - INFO - Epoch(train) [13][380/1793] lr: 7.5000e-03 eta: 9:24:08 time: 0.2447 data_time: 0.0197 memory: 10464 grad_norm: 6.8169 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3793 loss: 2.3793 2022/09/07 18:56:15 - mmengine - INFO - Epoch(train) [13][400/1793] lr: 7.5000e-03 eta: 9:23:50 time: 0.3757 data_time: 0.0066 memory: 10464 grad_norm: 6.9676 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.6025 loss: 2.6025 2022/09/07 18:56:21 - mmengine - INFO - Epoch(train) [13][420/1793] lr: 7.5000e-03 eta: 9:23:27 time: 0.2906 data_time: 0.0097 memory: 10464 grad_norm: 6.9943 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.1580 loss: 2.1580 2022/09/07 18:56:25 - mmengine - INFO - Epoch(train) [13][440/1793] lr: 7.5000e-03 eta: 9:23:00 time: 0.2207 data_time: 0.0057 memory: 10464 grad_norm: 6.9728 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.5700 loss: 2.5700 2022/09/07 18:56:30 - mmengine - INFO - Epoch(train) [13][460/1793] lr: 7.5000e-03 eta: 9:22:35 time: 0.2534 data_time: 0.0128 memory: 10464 grad_norm: 7.2533 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3475 loss: 2.3475 2022/09/07 18:56:34 - mmengine - INFO - Epoch(train) [13][480/1793] lr: 7.5000e-03 eta: 9:22:05 time: 0.1738 data_time: 0.0055 memory: 10464 grad_norm: 7.0639 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.8360 loss: 2.8360 2022/09/07 18:56:35 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 18:56:39 - mmengine - INFO - Epoch(train) [13][500/1793] lr: 7.5000e-03 eta: 9:21:39 time: 0.2401 data_time: 0.0168 memory: 10464 grad_norm: 7.1112 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3391 loss: 2.3391 2022/09/07 18:56:44 - mmengine - INFO - Epoch(train) [13][520/1793] lr: 7.5000e-03 eta: 9:21:14 time: 0.2498 data_time: 0.0081 memory: 10464 grad_norm: 7.2598 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0101 loss: 2.0101 2022/09/07 18:56:49 - mmengine - INFO - Epoch(train) [13][540/1793] lr: 7.5000e-03 eta: 9:20:49 time: 0.2543 data_time: 0.0059 memory: 10464 grad_norm: 7.1889 top1_acc: 0.0000 top5_acc: 0.8333 loss_cls: 2.5466 loss: 2.5466 2022/09/07 18:56:54 - mmengine - INFO - Epoch(train) [13][560/1793] lr: 7.5000e-03 eta: 9:20:24 time: 0.2472 data_time: 0.0772 memory: 10464 grad_norm: 6.7840 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.6120 loss: 2.6120 2022/09/07 18:56:59 - mmengine - INFO - Epoch(train) [13][580/1793] lr: 7.5000e-03 eta: 9:20:00 time: 0.2806 data_time: 0.0070 memory: 10464 grad_norm: 7.0921 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5162 loss: 2.5162 2022/09/07 18:57:03 - mmengine - INFO - Epoch(train) [13][600/1793] lr: 7.5000e-03 eta: 9:19:32 time: 0.1997 data_time: 0.0099 memory: 10464 grad_norm: 6.9265 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.1442 loss: 2.1442 2022/09/07 18:57:07 - mmengine - INFO - Epoch(train) [13][620/1793] lr: 7.5000e-03 eta: 9:19:05 time: 0.2112 data_time: 0.0060 memory: 10464 grad_norm: 6.9011 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5753 loss: 2.5753 2022/09/07 18:57:13 - mmengine - INFO - Epoch(train) [13][640/1793] lr: 7.5000e-03 eta: 9:18:41 time: 0.2608 data_time: 0.0632 memory: 10464 grad_norm: 7.1123 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.8167 loss: 2.8167 2022/09/07 18:57:16 - mmengine - INFO - Epoch(train) [13][660/1793] lr: 7.5000e-03 eta: 9:18:12 time: 0.1848 data_time: 0.0067 memory: 10464 grad_norm: 6.9801 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.7166 loss: 2.7166 2022/09/07 18:57:21 - mmengine - INFO - Epoch(train) [13][680/1793] lr: 7.5000e-03 eta: 9:17:47 time: 0.2502 data_time: 0.0073 memory: 10464 grad_norm: 6.9158 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3069 loss: 2.3069 2022/09/07 18:57:26 - mmengine - INFO - Epoch(train) [13][700/1793] lr: 7.5000e-03 eta: 9:17:21 time: 0.2398 data_time: 0.0053 memory: 10464 grad_norm: 7.1173 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4357 loss: 2.4357 2022/09/07 18:57:31 - mmengine - INFO - Epoch(train) [13][720/1793] lr: 7.5000e-03 eta: 9:16:56 time: 0.2486 data_time: 0.0099 memory: 10464 grad_norm: 7.2725 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5215 loss: 2.5215 2022/09/07 18:57:36 - mmengine - INFO - Epoch(train) [13][740/1793] lr: 7.5000e-03 eta: 9:16:31 time: 0.2415 data_time: 0.0062 memory: 10464 grad_norm: 6.7760 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5264 loss: 2.5264 2022/09/07 18:57:41 - mmengine - INFO - Epoch(train) [13][760/1793] lr: 7.5000e-03 eta: 9:16:06 time: 0.2479 data_time: 0.0072 memory: 10464 grad_norm: 6.9412 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.4448 loss: 2.4448 2022/09/07 18:57:44 - mmengine - INFO - Epoch(train) [13][780/1793] lr: 7.5000e-03 eta: 9:15:37 time: 0.1793 data_time: 0.0094 memory: 10464 grad_norm: 6.7090 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.5025 loss: 2.5025 2022/09/07 18:57:48 - mmengine - INFO - Epoch(train) [13][800/1793] lr: 7.5000e-03 eta: 9:15:08 time: 0.1799 data_time: 0.0069 memory: 10464 grad_norm: 7.1794 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3616 loss: 2.3616 2022/09/07 18:57:56 - mmengine - INFO - Epoch(train) [13][820/1793] lr: 7.5000e-03 eta: 9:14:51 time: 0.3794 data_time: 0.0060 memory: 10464 grad_norm: 7.1267 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.8331 loss: 2.8331 2022/09/07 18:58:02 - mmengine - INFO - Epoch(train) [13][840/1793] lr: 7.5000e-03 eta: 9:14:30 time: 0.2970 data_time: 0.0093 memory: 10464 grad_norm: 7.1030 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1834 loss: 2.1834 2022/09/07 18:58:08 - mmengine - INFO - Epoch(train) [13][860/1793] lr: 7.5000e-03 eta: 9:14:10 time: 0.3313 data_time: 0.0060 memory: 10464 grad_norm: 6.7410 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2256 loss: 2.2256 2022/09/07 18:58:15 - mmengine - INFO - Epoch(train) [13][880/1793] lr: 7.5000e-03 eta: 9:13:50 time: 0.3199 data_time: 0.0088 memory: 10464 grad_norm: 7.2119 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.2627 loss: 2.2627 2022/09/07 18:58:21 - mmengine - INFO - Epoch(train) [13][900/1793] lr: 7.5000e-03 eta: 9:13:29 time: 0.3226 data_time: 0.0058 memory: 10464 grad_norm: 7.1709 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.4324 loss: 2.4324 2022/09/07 18:58:27 - mmengine - INFO - Epoch(train) [13][920/1793] lr: 7.5000e-03 eta: 9:13:08 time: 0.2958 data_time: 0.0109 memory: 10464 grad_norm: 7.5792 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5052 loss: 2.5052 2022/09/07 18:58:30 - mmengine - INFO - Epoch(train) [13][940/1793] lr: 7.5000e-03 eta: 9:12:39 time: 0.1757 data_time: 0.0056 memory: 10464 grad_norm: 7.5082 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5956 loss: 2.5956 2022/09/07 18:58:36 - mmengine - INFO - Epoch(train) [13][960/1793] lr: 7.5000e-03 eta: 9:12:16 time: 0.2761 data_time: 0.0059 memory: 10464 grad_norm: 7.1463 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4322 loss: 2.4322 2022/09/07 18:58:43 - mmengine - INFO - Epoch(train) [13][980/1793] lr: 7.5000e-03 eta: 9:11:56 time: 0.3244 data_time: 0.0104 memory: 10464 grad_norm: 7.0259 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4878 loss: 2.4878 2022/09/07 18:58:50 - mmengine - INFO - Epoch(train) [13][1000/1793] lr: 7.5000e-03 eta: 9:11:40 time: 0.3993 data_time: 0.0059 memory: 10464 grad_norm: 7.1985 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3815 loss: 2.3815 2022/09/07 18:58:54 - mmengine - INFO - Epoch(train) [13][1020/1793] lr: 7.5000e-03 eta: 9:11:12 time: 0.1787 data_time: 0.0090 memory: 10464 grad_norm: 6.9559 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.7048 loss: 2.7048 2022/09/07 18:59:01 - mmengine - INFO - Epoch(train) [13][1040/1793] lr: 7.5000e-03 eta: 9:10:52 time: 0.3244 data_time: 0.0061 memory: 10464 grad_norm: 7.2179 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4478 loss: 2.4478 2022/09/07 18:59:08 - mmengine - INFO - Epoch(train) [13][1060/1793] lr: 7.5000e-03 eta: 9:10:34 time: 0.3471 data_time: 0.0095 memory: 10464 grad_norm: 7.0177 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3686 loss: 2.3686 2022/09/07 18:59:12 - mmengine - INFO - Epoch(train) [13][1080/1793] lr: 7.5000e-03 eta: 9:10:09 time: 0.2426 data_time: 0.0062 memory: 10464 grad_norm: 7.0316 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.1772 loss: 2.1772 2022/09/07 18:59:17 - mmengine - INFO - Epoch(train) [13][1100/1793] lr: 7.5000e-03 eta: 9:09:45 time: 0.2495 data_time: 0.0087 memory: 10464 grad_norm: 7.2522 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4076 loss: 2.4076 2022/09/07 18:59:24 - mmengine - INFO - Epoch(train) [13][1120/1793] lr: 7.5000e-03 eta: 9:09:26 time: 0.3453 data_time: 0.0061 memory: 10464 grad_norm: 7.0193 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2277 loss: 2.2277 2022/09/07 18:59:29 - mmengine - INFO - Epoch(train) [13][1140/1793] lr: 7.5000e-03 eta: 9:09:03 time: 0.2617 data_time: 0.0395 memory: 10464 grad_norm: 6.9379 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.5247 loss: 2.5247 2022/09/07 18:59:34 - mmengine - INFO - Epoch(train) [13][1160/1793] lr: 7.5000e-03 eta: 9:08:36 time: 0.2004 data_time: 0.0280 memory: 10464 grad_norm: 7.0522 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3368 loss: 2.3368 2022/09/07 18:59:39 - mmengine - INFO - Epoch(train) [13][1180/1793] lr: 7.5000e-03 eta: 9:08:13 time: 0.2687 data_time: 0.0064 memory: 10464 grad_norm: 6.6811 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3246 loss: 2.3246 2022/09/07 18:59:44 - mmengine - INFO - Epoch(train) [13][1200/1793] lr: 7.5000e-03 eta: 9:07:49 time: 0.2507 data_time: 0.0105 memory: 10464 grad_norm: 7.1074 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3763 loss: 2.3763 2022/09/07 18:59:49 - mmengine - INFO - Epoch(train) [13][1220/1793] lr: 7.5000e-03 eta: 9:07:24 time: 0.2483 data_time: 0.0058 memory: 10464 grad_norm: 6.9228 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.6266 loss: 2.6266 2022/09/07 18:59:58 - mmengine - INFO - Epoch(train) [13][1240/1793] lr: 7.5000e-03 eta: 9:07:12 time: 0.4399 data_time: 0.0965 memory: 10464 grad_norm: 7.4280 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.2093 loss: 2.2093 2022/09/07 19:00:03 - mmengine - INFO - Epoch(train) [13][1260/1793] lr: 7.5000e-03 eta: 9:06:49 time: 0.2652 data_time: 0.0086 memory: 10464 grad_norm: 7.4996 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.3849 loss: 2.3849 2022/09/07 19:00:08 - mmengine - INFO - Epoch(train) [13][1280/1793] lr: 7.5000e-03 eta: 9:06:25 time: 0.2608 data_time: 0.0053 memory: 10464 grad_norm: 7.2160 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6445 loss: 2.6445 2022/09/07 19:00:13 - mmengine - INFO - Epoch(train) [13][1300/1793] lr: 7.5000e-03 eta: 9:06:01 time: 0.2510 data_time: 0.0611 memory: 10464 grad_norm: 7.1474 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6871 loss: 2.6871 2022/09/07 19:00:19 - mmengine - INFO - Epoch(train) [13][1320/1793] lr: 7.5000e-03 eta: 9:05:39 time: 0.2675 data_time: 0.0049 memory: 10464 grad_norm: 6.7582 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.7124 loss: 2.7124 2022/09/07 19:00:22 - mmengine - INFO - Epoch(train) [13][1340/1793] lr: 7.5000e-03 eta: 9:05:11 time: 0.1787 data_time: 0.0106 memory: 10464 grad_norm: 6.8687 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4140 loss: 2.4140 2022/09/07 19:00:27 - mmengine - INFO - Epoch(train) [13][1360/1793] lr: 7.5000e-03 eta: 9:04:47 time: 0.2572 data_time: 0.0050 memory: 10464 grad_norm: 6.9036 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6160 loss: 2.6160 2022/09/07 19:00:31 - mmengine - INFO - Epoch(train) [13][1380/1793] lr: 7.5000e-03 eta: 9:04:20 time: 0.1970 data_time: 0.0063 memory: 10464 grad_norm: 7.1911 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.2765 loss: 2.2765 2022/09/07 19:00:36 - mmengine - INFO - Epoch(train) [13][1400/1793] lr: 7.5000e-03 eta: 9:03:57 time: 0.2473 data_time: 0.0175 memory: 10464 grad_norm: 6.6729 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6961 loss: 2.6961 2022/09/07 19:00:42 - mmengine - INFO - Epoch(train) [13][1420/1793] lr: 7.5000e-03 eta: 9:03:35 time: 0.2868 data_time: 0.0057 memory: 10464 grad_norm: 6.9020 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.2877 loss: 2.2877 2022/09/07 19:00:45 - mmengine - INFO - Epoch(train) [13][1440/1793] lr: 7.5000e-03 eta: 9:03:07 time: 0.1755 data_time: 0.0095 memory: 10464 grad_norm: 6.8048 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2894 loss: 2.2894 2022/09/07 19:00:49 - mmengine - INFO - Epoch(train) [13][1460/1793] lr: 7.5000e-03 eta: 9:02:39 time: 0.1799 data_time: 0.0063 memory: 10464 grad_norm: 6.9821 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.8810 loss: 2.8810 2022/09/07 19:00:53 - mmengine - INFO - Epoch(train) [13][1480/1793] lr: 7.5000e-03 eta: 9:02:11 time: 0.1739 data_time: 0.0064 memory: 10464 grad_norm: 7.0932 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6623 loss: 2.6623 2022/09/07 19:00:53 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:00:56 - mmengine - INFO - Epoch(train) [13][1500/1793] lr: 7.5000e-03 eta: 9:01:43 time: 0.1757 data_time: 0.0090 memory: 10464 grad_norm: 7.3033 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.4684 loss: 2.4684 2022/09/07 19:01:00 - mmengine - INFO - Epoch(train) [13][1520/1793] lr: 7.5000e-03 eta: 9:01:16 time: 0.1782 data_time: 0.0074 memory: 10464 grad_norm: 6.8180 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5909 loss: 2.5909 2022/09/07 19:01:03 - mmengine - INFO - Epoch(train) [13][1540/1793] lr: 7.5000e-03 eta: 9:00:48 time: 0.1744 data_time: 0.0063 memory: 10464 grad_norm: 7.1320 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.6715 loss: 2.6715 2022/09/07 19:01:11 - mmengine - INFO - Epoch(train) [13][1560/1793] lr: 7.5000e-03 eta: 9:00:32 time: 0.3737 data_time: 0.0085 memory: 10464 grad_norm: 6.6469 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.5772 loss: 2.5772 2022/09/07 19:01:17 - mmengine - INFO - Epoch(train) [13][1580/1793] lr: 7.5000e-03 eta: 9:00:12 time: 0.3110 data_time: 0.0074 memory: 10464 grad_norm: 6.9859 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.4183 loss: 2.4183 2022/09/07 19:01:21 - mmengine - INFO - Epoch(train) [13][1600/1793] lr: 7.5000e-03 eta: 8:59:47 time: 0.2204 data_time: 0.0081 memory: 10464 grad_norm: 6.9938 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.7277 loss: 2.7277 2022/09/07 19:01:26 - mmengine - INFO - Epoch(train) [13][1620/1793] lr: 7.5000e-03 eta: 8:59:23 time: 0.2501 data_time: 0.0064 memory: 10464 grad_norm: 7.2628 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3531 loss: 2.3531 2022/09/07 19:01:36 - mmengine - INFO - Epoch(train) [13][1640/1793] lr: 7.5000e-03 eta: 8:59:14 time: 0.4949 data_time: 0.0057 memory: 10464 grad_norm: 7.0708 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.4340 loss: 2.4340 2022/09/07 19:01:42 - mmengine - INFO - Epoch(train) [13][1660/1793] lr: 7.5000e-03 eta: 8:58:53 time: 0.2925 data_time: 0.0099 memory: 10464 grad_norm: 7.2430 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2361 loss: 2.2361 2022/09/07 19:01:47 - mmengine - INFO - Epoch(train) [13][1680/1793] lr: 7.5000e-03 eta: 8:58:30 time: 0.2554 data_time: 0.0060 memory: 10464 grad_norm: 7.1270 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6189 loss: 2.6189 2022/09/07 19:01:54 - mmengine - INFO - Epoch(train) [13][1700/1793] lr: 7.5000e-03 eta: 8:58:11 time: 0.3277 data_time: 0.0087 memory: 10464 grad_norm: 6.8414 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.7748 loss: 2.7748 2022/09/07 19:02:00 - mmengine - INFO - Epoch(train) [13][1720/1793] lr: 7.5000e-03 eta: 8:57:51 time: 0.3019 data_time: 0.0055 memory: 10464 grad_norm: 7.0863 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3581 loss: 2.3581 2022/09/07 19:02:03 - mmengine - INFO - Epoch(train) [13][1740/1793] lr: 7.5000e-03 eta: 8:57:24 time: 0.1837 data_time: 0.0088 memory: 10464 grad_norm: 7.0669 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3626 loss: 2.3626 2022/09/07 19:02:09 - mmengine - INFO - Epoch(train) [13][1760/1793] lr: 7.5000e-03 eta: 8:57:02 time: 0.2700 data_time: 0.0055 memory: 10464 grad_norm: 6.9604 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.1165 loss: 2.1165 2022/09/07 19:02:14 - mmengine - INFO - Epoch(train) [13][1780/1793] lr: 7.5000e-03 eta: 8:56:39 time: 0.2546 data_time: 0.0066 memory: 10464 grad_norm: 6.8619 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.6889 loss: 2.6889 2022/09/07 19:02:16 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:02:16 - mmengine - INFO - Epoch(train) [13][1793/1793] lr: 7.5000e-03 eta: 8:56:39 time: 0.1697 data_time: 0.0082 memory: 10464 grad_norm: 7.0386 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 2.2913 loss: 2.2913 2022/09/07 19:02:16 - mmengine - INFO - Saving checkpoint at 13 epochs 2022/09/07 19:02:19 - mmengine - INFO - Epoch(val) [13][20/241] eta: 0:00:12 time: 0.0584 data_time: 0.0091 memory: 1482 2022/09/07 19:02:20 - mmengine - INFO - Epoch(val) [13][40/241] eta: 0:00:10 time: 0.0538 data_time: 0.0055 memory: 1482 2022/09/07 19:02:22 - mmengine - INFO - Epoch(val) [13][60/241] eta: 0:00:11 time: 0.0608 data_time: 0.0122 memory: 1482 2022/09/07 19:02:23 - mmengine - INFO - Epoch(val) [13][80/241] eta: 0:00:08 time: 0.0535 data_time: 0.0049 memory: 1482 2022/09/07 19:02:24 - mmengine - INFO - Epoch(val) [13][100/241] eta: 0:00:07 time: 0.0531 data_time: 0.0047 memory: 1482 2022/09/07 19:02:25 - mmengine - INFO - Epoch(val) [13][120/241] eta: 0:00:06 time: 0.0530 data_time: 0.0047 memory: 1482 2022/09/07 19:02:26 - mmengine - INFO - Epoch(val) [13][140/241] eta: 0:00:05 time: 0.0531 data_time: 0.0048 memory: 1482 2022/09/07 19:02:27 - mmengine - INFO - Epoch(val) [13][160/241] eta: 0:00:04 time: 0.0540 data_time: 0.0054 memory: 1482 2022/09/07 19:02:28 - mmengine - INFO - Epoch(val) [13][180/241] eta: 0:00:03 time: 0.0530 data_time: 0.0045 memory: 1482 2022/09/07 19:02:29 - mmengine - INFO - Epoch(val) [13][200/241] eta: 0:00:02 time: 0.0527 data_time: 0.0046 memory: 1482 2022/09/07 19:02:30 - mmengine - INFO - Epoch(val) [13][220/241] eta: 0:00:01 time: 0.0590 data_time: 0.0060 memory: 1482 2022/09/07 19:02:31 - mmengine - INFO - Epoch(val) [13][240/241] eta: 0:00:00 time: 0.0525 data_time: 0.0047 memory: 1482 2022/09/07 19:02:32 - mmengine - INFO - Epoch(val) [13][241/241] acc/top1: 0.3003 acc/top5: 0.5992 acc/mean1: 0.2754 2022/09/07 19:02:32 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_10.pth is removed 2022/09/07 19:02:34 - mmengine - INFO - The best checkpoint with 0.3003 acc/top1 at 13 epoch is saved to best_acc/top1_epoch_13.pth. 2022/09/07 19:02:40 - mmengine - INFO - Epoch(train) [14][20/1793] lr: 7.5000e-03 eta: 8:55:57 time: 0.3389 data_time: 0.0851 memory: 10464 grad_norm: 6.8168 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.4001 loss: 2.4001 2022/09/07 19:02:45 - mmengine - INFO - Epoch(train) [14][40/1793] lr: 7.5000e-03 eta: 8:55:34 time: 0.2505 data_time: 0.0061 memory: 10464 grad_norm: 7.1000 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.3433 loss: 2.3433 2022/09/07 19:02:50 - mmengine - INFO - Epoch(train) [14][60/1793] lr: 7.5000e-03 eta: 8:55:11 time: 0.2460 data_time: 0.0094 memory: 10464 grad_norm: 7.4250 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.5300 loss: 2.5300 2022/09/07 19:02:55 - mmengine - INFO - Epoch(train) [14][80/1793] lr: 7.5000e-03 eta: 8:54:47 time: 0.2360 data_time: 0.0685 memory: 10464 grad_norm: 6.9716 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4987 loss: 2.4987 2022/09/07 19:03:00 - mmengine - INFO - Epoch(train) [14][100/1793] lr: 7.5000e-03 eta: 8:54:24 time: 0.2459 data_time: 0.0727 memory: 10464 grad_norm: 6.9940 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3788 loss: 2.3788 2022/09/07 19:03:05 - mmengine - INFO - Epoch(train) [14][120/1793] lr: 7.5000e-03 eta: 8:54:01 time: 0.2576 data_time: 0.0889 memory: 10464 grad_norm: 6.8748 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.2360 loss: 2.2360 2022/09/07 19:03:11 - mmengine - INFO - Epoch(train) [14][140/1793] lr: 7.5000e-03 eta: 8:53:40 time: 0.2734 data_time: 0.1022 memory: 10464 grad_norm: 7.3493 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4174 loss: 2.4174 2022/09/07 19:03:14 - mmengine - INFO - Epoch(train) [14][160/1793] lr: 7.5000e-03 eta: 8:53:14 time: 0.1918 data_time: 0.0078 memory: 10464 grad_norm: 7.1163 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.4274 loss: 2.4274 2022/09/07 19:03:21 - mmengine - INFO - Epoch(train) [14][180/1793] lr: 7.5000e-03 eta: 8:52:54 time: 0.3091 data_time: 0.0711 memory: 10464 grad_norm: 7.1666 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.5089 loss: 2.5089 2022/09/07 19:03:26 - mmengine - INFO - Epoch(train) [14][200/1793] lr: 7.5000e-03 eta: 8:52:31 time: 0.2451 data_time: 0.0096 memory: 10464 grad_norm: 6.6740 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0417 loss: 2.0417 2022/09/07 19:03:30 - mmengine - INFO - Epoch(train) [14][220/1793] lr: 7.5000e-03 eta: 8:52:08 time: 0.2463 data_time: 0.0061 memory: 10464 grad_norm: 6.9103 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4084 loss: 2.4084 2022/09/07 19:03:35 - mmengine - INFO - Epoch(train) [14][240/1793] lr: 7.5000e-03 eta: 8:51:45 time: 0.2432 data_time: 0.0066 memory: 10464 grad_norm: 7.2754 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4131 loss: 2.4131 2022/09/07 19:03:48 - mmengine - INFO - Epoch(train) [14][260/1793] lr: 7.5000e-03 eta: 8:51:43 time: 0.6225 data_time: 0.4391 memory: 10464 grad_norm: 7.0026 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3470 loss: 2.3470 2022/09/07 19:03:51 - mmengine - INFO - Epoch(train) [14][280/1793] lr: 7.5000e-03 eta: 8:51:16 time: 0.1767 data_time: 0.0099 memory: 10464 grad_norm: 7.2530 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3447 loss: 2.3447 2022/09/07 19:03:56 - mmengine - INFO - Epoch(train) [14][300/1793] lr: 7.5000e-03 eta: 8:50:52 time: 0.2213 data_time: 0.0047 memory: 10464 grad_norm: 6.8819 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.2064 loss: 2.2064 2022/09/07 19:04:00 - mmengine - INFO - Epoch(train) [14][320/1793] lr: 7.5000e-03 eta: 8:50:28 time: 0.2131 data_time: 0.0081 memory: 10464 grad_norm: 6.8848 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3285 loss: 2.3285 2022/09/07 19:04:07 - mmengine - INFO - Epoch(train) [14][340/1793] lr: 7.5000e-03 eta: 8:50:11 time: 0.3632 data_time: 0.0098 memory: 10464 grad_norm: 6.7810 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2700 loss: 2.2700 2022/09/07 19:04:12 - mmengine - INFO - Epoch(train) [14][360/1793] lr: 7.5000e-03 eta: 8:49:47 time: 0.2170 data_time: 0.0065 memory: 10464 grad_norm: 7.1552 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.2864 loss: 2.2864 2022/09/07 19:04:15 - mmengine - INFO - Epoch(train) [14][380/1793] lr: 7.5000e-03 eta: 8:49:21 time: 0.1886 data_time: 0.0077 memory: 10464 grad_norm: 6.8914 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4255 loss: 2.4255 2022/09/07 19:04:20 - mmengine - INFO - Epoch(train) [14][400/1793] lr: 7.5000e-03 eta: 8:48:56 time: 0.2159 data_time: 0.0073 memory: 10464 grad_norm: 6.9615 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5500 loss: 2.5500 2022/09/07 19:04:23 - mmengine - INFO - Epoch(train) [14][420/1793] lr: 7.5000e-03 eta: 8:48:30 time: 0.1745 data_time: 0.0064 memory: 10464 grad_norm: 7.1987 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3199 loss: 2.3199 2022/09/07 19:04:28 - mmengine - INFO - Epoch(train) [14][440/1793] lr: 7.5000e-03 eta: 8:48:07 time: 0.2424 data_time: 0.0716 memory: 10464 grad_norm: 6.8993 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3036 loss: 2.3036 2022/09/07 19:04:32 - mmengine - INFO - Epoch(train) [14][460/1793] lr: 7.5000e-03 eta: 8:47:43 time: 0.2212 data_time: 0.0066 memory: 10464 grad_norm: 7.2545 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5643 loss: 2.5643 2022/09/07 19:04:36 - mmengine - INFO - Epoch(train) [14][480/1793] lr: 7.5000e-03 eta: 8:47:17 time: 0.1892 data_time: 0.0059 memory: 10464 grad_norm: 6.6754 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.0769 loss: 2.0769 2022/09/07 19:04:41 - mmengine - INFO - Epoch(train) [14][500/1793] lr: 7.5000e-03 eta: 8:46:55 time: 0.2582 data_time: 0.0109 memory: 10464 grad_norm: 7.2556 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2933 loss: 2.2933 2022/09/07 19:04:46 - mmengine - INFO - Epoch(train) [14][520/1793] lr: 7.5000e-03 eta: 8:46:33 time: 0.2471 data_time: 0.0765 memory: 10464 grad_norm: 7.2229 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3635 loss: 2.3635 2022/09/07 19:04:51 - mmengine - INFO - Epoch(train) [14][540/1793] lr: 7.5000e-03 eta: 8:46:09 time: 0.2266 data_time: 0.0081 memory: 10464 grad_norm: 7.2766 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.6830 loss: 2.6830 2022/09/07 19:04:55 - mmengine - INFO - Epoch(train) [14][560/1793] lr: 7.5000e-03 eta: 8:45:45 time: 0.2146 data_time: 0.0454 memory: 10464 grad_norm: 6.9124 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4277 loss: 2.4277 2022/09/07 19:05:00 - mmengine - INFO - Epoch(train) [14][580/1793] lr: 7.5000e-03 eta: 8:45:23 time: 0.2466 data_time: 0.0049 memory: 10464 grad_norm: 6.9301 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5284 loss: 2.5284 2022/09/07 19:05:04 - mmengine - INFO - Epoch(train) [14][600/1793] lr: 7.5000e-03 eta: 8:44:56 time: 0.1774 data_time: 0.0106 memory: 10464 grad_norm: 7.2769 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.3819 loss: 2.3819 2022/09/07 19:05:08 - mmengine - INFO - Epoch(train) [14][620/1793] lr: 7.5000e-03 eta: 8:44:31 time: 0.1944 data_time: 0.0054 memory: 10464 grad_norm: 6.9432 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3374 loss: 2.3374 2022/09/07 19:05:11 - mmengine - INFO - Epoch(train) [14][640/1793] lr: 7.5000e-03 eta: 8:44:05 time: 0.1847 data_time: 0.0066 memory: 10464 grad_norm: 7.3205 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2651 loss: 2.2651 2022/09/07 19:05:16 - mmengine - INFO - Epoch(train) [14][660/1793] lr: 7.5000e-03 eta: 8:43:42 time: 0.2247 data_time: 0.0085 memory: 10464 grad_norm: 6.8159 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.4448 loss: 2.4448 2022/09/07 19:05:21 - mmengine - INFO - Epoch(train) [14][680/1793] lr: 7.5000e-03 eta: 8:43:20 time: 0.2506 data_time: 0.0704 memory: 10464 grad_norm: 6.8546 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2654 loss: 2.2654 2022/09/07 19:05:24 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:05:25 - mmengine - INFO - Epoch(train) [14][700/1793] lr: 7.5000e-03 eta: 8:42:57 time: 0.2345 data_time: 0.0058 memory: 10464 grad_norm: 6.9380 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.4873 loss: 2.4873 2022/09/07 19:05:35 - mmengine - INFO - Epoch(train) [14][720/1793] lr: 7.5000e-03 eta: 8:42:48 time: 0.4803 data_time: 0.0095 memory: 10464 grad_norm: 6.8815 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3551 loss: 2.3551 2022/09/07 19:05:39 - mmengine - INFO - Epoch(train) [14][740/1793] lr: 7.5000e-03 eta: 8:42:22 time: 0.1753 data_time: 0.0065 memory: 10464 grad_norm: 6.9680 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2444 loss: 2.2444 2022/09/07 19:05:42 - mmengine - INFO - Epoch(train) [14][760/1793] lr: 7.5000e-03 eta: 8:41:56 time: 0.1934 data_time: 0.0109 memory: 10464 grad_norm: 6.8314 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4661 loss: 2.4661 2022/09/07 19:05:50 - mmengine - INFO - Epoch(train) [14][780/1793] lr: 7.5000e-03 eta: 8:41:42 time: 0.3862 data_time: 0.0057 memory: 10464 grad_norm: 7.0675 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2988 loss: 2.2988 2022/09/07 19:05:57 - mmengine - INFO - Epoch(train) [14][800/1793] lr: 7.5000e-03 eta: 8:41:24 time: 0.3293 data_time: 0.1589 memory: 10464 grad_norm: 6.6493 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.5859 loss: 2.5859 2022/09/07 19:06:02 - mmengine - INFO - Epoch(train) [14][820/1793] lr: 7.5000e-03 eta: 8:41:03 time: 0.2532 data_time: 0.0058 memory: 10464 grad_norm: 6.8274 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.7247 loss: 2.7247 2022/09/07 19:06:07 - mmengine - INFO - Epoch(train) [14][840/1793] lr: 7.5000e-03 eta: 8:40:40 time: 0.2397 data_time: 0.0082 memory: 10464 grad_norm: 7.0031 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4401 loss: 2.4401 2022/09/07 19:06:10 - mmengine - INFO - Epoch(train) [14][860/1793] lr: 7.5000e-03 eta: 8:40:15 time: 0.1881 data_time: 0.0067 memory: 10464 grad_norm: 7.3475 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.3040 loss: 2.3040 2022/09/07 19:06:14 - mmengine - INFO - Epoch(train) [14][880/1793] lr: 7.5000e-03 eta: 8:39:49 time: 0.1722 data_time: 0.0057 memory: 10464 grad_norm: 7.1152 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3778 loss: 2.3778 2022/09/07 19:06:17 - mmengine - INFO - Epoch(train) [14][900/1793] lr: 7.5000e-03 eta: 8:39:23 time: 0.1800 data_time: 0.0090 memory: 10464 grad_norm: 7.2966 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2212 loss: 2.2212 2022/09/07 19:06:21 - mmengine - INFO - Epoch(train) [14][920/1793] lr: 7.5000e-03 eta: 8:38:59 time: 0.2029 data_time: 0.0342 memory: 10464 grad_norm: 7.1287 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3165 loss: 2.3165 2022/09/07 19:06:25 - mmengine - INFO - Epoch(train) [14][940/1793] lr: 7.5000e-03 eta: 8:38:33 time: 0.1741 data_time: 0.0066 memory: 10464 grad_norm: 6.9574 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5713 loss: 2.5713 2022/09/07 19:06:28 - mmengine - INFO - Epoch(train) [14][960/1793] lr: 7.5000e-03 eta: 8:38:08 time: 0.1759 data_time: 0.0093 memory: 10464 grad_norm: 6.8268 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.6724 loss: 2.6724 2022/09/07 19:06:33 - mmengine - INFO - Epoch(train) [14][980/1793] lr: 7.5000e-03 eta: 8:37:45 time: 0.2278 data_time: 0.0066 memory: 10464 grad_norm: 6.7451 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.6464 loss: 2.6464 2022/09/07 19:06:37 - mmengine - INFO - Epoch(train) [14][1000/1793] lr: 7.5000e-03 eta: 8:37:19 time: 0.1730 data_time: 0.0065 memory: 10464 grad_norm: 6.8534 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1097 loss: 2.1097 2022/09/07 19:06:41 - mmengine - INFO - Epoch(train) [14][1020/1793] lr: 7.5000e-03 eta: 8:36:55 time: 0.1994 data_time: 0.0097 memory: 10464 grad_norm: 6.7400 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4068 loss: 2.4068 2022/09/07 19:06:44 - mmengine - INFO - Epoch(train) [14][1040/1793] lr: 7.5000e-03 eta: 8:36:29 time: 0.1719 data_time: 0.0064 memory: 10464 grad_norm: 7.3785 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3311 loss: 2.3311 2022/09/07 19:06:47 - mmengine - INFO - Epoch(train) [14][1060/1793] lr: 7.5000e-03 eta: 8:36:03 time: 0.1722 data_time: 0.0060 memory: 10464 grad_norm: 6.9349 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.5074 loss: 2.5074 2022/09/07 19:06:52 - mmengine - INFO - Epoch(train) [14][1080/1793] lr: 7.5000e-03 eta: 8:35:42 time: 0.2450 data_time: 0.0086 memory: 10464 grad_norm: 7.3029 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.5032 loss: 2.5032 2022/09/07 19:06:56 - mmengine - INFO - Epoch(train) [14][1100/1793] lr: 7.5000e-03 eta: 8:35:17 time: 0.1917 data_time: 0.0063 memory: 10464 grad_norm: 6.9050 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5260 loss: 2.5260 2022/09/07 19:07:00 - mmengine - INFO - Epoch(train) [14][1120/1793] lr: 7.5000e-03 eta: 8:34:54 time: 0.2166 data_time: 0.0067 memory: 10464 grad_norm: 7.0880 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2814 loss: 2.2814 2022/09/07 19:07:05 - mmengine - INFO - Epoch(train) [14][1140/1793] lr: 7.5000e-03 eta: 8:34:32 time: 0.2416 data_time: 0.0084 memory: 10464 grad_norm: 6.8592 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.3596 loss: 2.3596 2022/09/07 19:07:09 - mmengine - INFO - Epoch(train) [14][1160/1793] lr: 7.5000e-03 eta: 8:34:07 time: 0.1770 data_time: 0.0064 memory: 10464 grad_norm: 7.3715 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.6026 loss: 2.6026 2022/09/07 19:07:16 - mmengine - INFO - Epoch(train) [14][1180/1793] lr: 7.5000e-03 eta: 8:33:50 time: 0.3336 data_time: 0.0061 memory: 10464 grad_norm: 6.6969 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.4630 loss: 2.4630 2022/09/07 19:07:22 - mmengine - INFO - Epoch(train) [14][1200/1793] lr: 7.5000e-03 eta: 8:33:33 time: 0.3325 data_time: 0.0080 memory: 10464 grad_norm: 7.2445 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.6740 loss: 2.6740 2022/09/07 19:07:29 - mmengine - INFO - Epoch(train) [14][1220/1793] lr: 7.5000e-03 eta: 8:33:17 time: 0.3553 data_time: 0.0062 memory: 10464 grad_norm: 7.0152 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5685 loss: 2.5685 2022/09/07 19:07:34 - mmengine - INFO - Epoch(train) [14][1240/1793] lr: 7.5000e-03 eta: 8:32:56 time: 0.2583 data_time: 0.0846 memory: 10464 grad_norm: 6.8416 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3345 loss: 2.3345 2022/09/07 19:07:41 - mmengine - INFO - Epoch(train) [14][1260/1793] lr: 7.5000e-03 eta: 8:32:40 time: 0.3449 data_time: 0.0472 memory: 10464 grad_norm: 7.2916 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4290 loss: 2.4290 2022/09/07 19:07:45 - mmengine - INFO - Epoch(train) [14][1280/1793] lr: 7.5000e-03 eta: 8:32:15 time: 0.1763 data_time: 0.0085 memory: 10464 grad_norm: 6.9206 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.5216 loss: 2.5216 2022/09/07 19:07:50 - mmengine - INFO - Epoch(train) [14][1300/1793] lr: 7.5000e-03 eta: 8:31:54 time: 0.2551 data_time: 0.0059 memory: 10464 grad_norm: 6.9496 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5903 loss: 2.5903 2022/09/07 19:07:55 - mmengine - INFO - Epoch(train) [14][1320/1793] lr: 7.5000e-03 eta: 8:31:32 time: 0.2416 data_time: 0.0075 memory: 10464 grad_norm: 6.8913 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3192 loss: 2.3192 2022/09/07 19:08:00 - mmengine - INFO - Epoch(train) [14][1340/1793] lr: 7.5000e-03 eta: 8:31:12 time: 0.2619 data_time: 0.0096 memory: 10464 grad_norm: 6.8937 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4161 loss: 2.4161 2022/09/07 19:08:06 - mmengine - INFO - Epoch(train) [14][1360/1793] lr: 7.5000e-03 eta: 8:30:53 time: 0.2896 data_time: 0.0088 memory: 10464 grad_norm: 7.0928 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.2445 loss: 2.2445 2022/09/07 19:08:09 - mmengine - INFO - Epoch(train) [14][1380/1793] lr: 7.5000e-03 eta: 8:30:28 time: 0.1819 data_time: 0.0090 memory: 10464 grad_norm: 6.9987 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.4635 loss: 2.4635 2022/09/07 19:08:15 - mmengine - INFO - Epoch(train) [14][1400/1793] lr: 7.5000e-03 eta: 8:30:08 time: 0.2718 data_time: 0.0071 memory: 10464 grad_norm: 6.9737 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 2.4474 loss: 2.4474 2022/09/07 19:08:23 - mmengine - INFO - Epoch(train) [14][1420/1793] lr: 7.5000e-03 eta: 8:29:55 time: 0.3971 data_time: 0.1680 memory: 10464 grad_norm: 6.7281 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.1912 loss: 2.1912 2022/09/07 19:08:29 - mmengine - INFO - Epoch(train) [14][1440/1793] lr: 7.5000e-03 eta: 8:29:36 time: 0.2886 data_time: 0.0086 memory: 10464 grad_norm: 7.2992 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.5130 loss: 2.5130 2022/09/07 19:08:34 - mmengine - INFO - Epoch(train) [14][1460/1793] lr: 7.5000e-03 eta: 8:29:15 time: 0.2533 data_time: 0.0738 memory: 10464 grad_norm: 6.8685 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.4088 loss: 2.4088 2022/09/07 19:08:39 - mmengine - INFO - Epoch(train) [14][1480/1793] lr: 7.5000e-03 eta: 8:28:54 time: 0.2513 data_time: 0.0071 memory: 10464 grad_norm: 6.7763 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 2.4006 loss: 2.4006 2022/09/07 19:08:43 - mmengine - INFO - Epoch(train) [14][1500/1793] lr: 7.5000e-03 eta: 8:28:32 time: 0.2244 data_time: 0.0067 memory: 10464 grad_norm: 6.9245 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2462 loss: 2.2462 2022/09/07 19:08:48 - mmengine - INFO - Epoch(train) [14][1520/1793] lr: 7.5000e-03 eta: 8:28:11 time: 0.2567 data_time: 0.0064 memory: 10464 grad_norm: 6.9214 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5882 loss: 2.5882 2022/09/07 19:08:55 - mmengine - INFO - Epoch(train) [14][1540/1793] lr: 7.5000e-03 eta: 8:27:54 time: 0.3238 data_time: 0.0098 memory: 10464 grad_norm: 7.0916 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6708 loss: 2.6708 2022/09/07 19:08:59 - mmengine - INFO - Epoch(train) [14][1560/1793] lr: 7.5000e-03 eta: 8:27:31 time: 0.2042 data_time: 0.0065 memory: 10464 grad_norm: 7.0564 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.5685 loss: 2.5685 2022/09/07 19:09:04 - mmengine - INFO - Epoch(train) [14][1580/1793] lr: 7.5000e-03 eta: 8:27:10 time: 0.2411 data_time: 0.0082 memory: 10464 grad_norm: 6.8629 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3469 loss: 2.3469 2022/09/07 19:09:07 - mmengine - INFO - Epoch(train) [14][1600/1793] lr: 7.5000e-03 eta: 8:26:45 time: 0.1777 data_time: 0.0078 memory: 10464 grad_norm: 6.7185 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2570 loss: 2.2570 2022/09/07 19:09:12 - mmengine - INFO - Epoch(train) [14][1620/1793] lr: 7.5000e-03 eta: 8:26:24 time: 0.2412 data_time: 0.0069 memory: 10464 grad_norm: 6.9843 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4739 loss: 2.4739 2022/09/07 19:09:19 - mmengine - INFO - Epoch(train) [14][1640/1793] lr: 7.5000e-03 eta: 8:26:09 time: 0.3649 data_time: 0.1922 memory: 10464 grad_norm: 7.1460 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7469 loss: 2.7469 2022/09/07 19:09:26 - mmengine - INFO - Epoch(train) [14][1660/1793] lr: 7.5000e-03 eta: 8:25:53 time: 0.3434 data_time: 0.0059 memory: 10464 grad_norm: 6.8484 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5053 loss: 2.5053 2022/09/07 19:09:30 - mmengine - INFO - Epoch(train) [14][1680/1793] lr: 7.5000e-03 eta: 8:25:29 time: 0.1926 data_time: 0.0090 memory: 10464 grad_norm: 6.8270 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.4482 loss: 2.4482 2022/09/07 19:09:32 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:09:34 - mmengine - INFO - Epoch(train) [14][1700/1793] lr: 7.5000e-03 eta: 8:25:06 time: 0.1919 data_time: 0.0064 memory: 10464 grad_norm: 7.1082 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3960 loss: 2.3960 2022/09/07 19:09:40 - mmengine - INFO - Epoch(train) [14][1720/1793] lr: 7.5000e-03 eta: 8:24:47 time: 0.2822 data_time: 0.0064 memory: 10464 grad_norm: 6.9666 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.7615 loss: 2.7615 2022/09/07 19:09:44 - mmengine - INFO - Epoch(train) [14][1740/1793] lr: 7.5000e-03 eta: 8:24:26 time: 0.2438 data_time: 0.0087 memory: 10464 grad_norm: 7.1201 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2230 loss: 2.2230 2022/09/07 19:09:48 - mmengine - INFO - Epoch(train) [14][1760/1793] lr: 7.5000e-03 eta: 8:24:01 time: 0.1816 data_time: 0.0099 memory: 10464 grad_norm: 7.0296 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6211 loss: 2.6211 2022/09/07 19:09:54 - mmengine - INFO - Epoch(train) [14][1780/1793] lr: 7.5000e-03 eta: 8:23:42 time: 0.2683 data_time: 0.0616 memory: 10464 grad_norm: 6.9811 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3878 loss: 2.3878 2022/09/07 19:09:56 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:09:56 - mmengine - INFO - Epoch(train) [14][1793/1793] lr: 7.5000e-03 eta: 8:23:42 time: 0.2127 data_time: 0.0173 memory: 10464 grad_norm: 7.5535 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.2445 loss: 2.2445 2022/09/07 19:09:56 - mmengine - INFO - Saving checkpoint at 14 epochs 2022/09/07 19:10:00 - mmengine - INFO - Epoch(val) [14][20/241] eta: 0:00:12 time: 0.0588 data_time: 0.0091 memory: 1482 2022/09/07 19:10:01 - mmengine - INFO - Epoch(val) [14][40/241] eta: 0:00:10 time: 0.0535 data_time: 0.0050 memory: 1482 2022/09/07 19:10:02 - mmengine - INFO - Epoch(val) [14][60/241] eta: 0:00:09 time: 0.0540 data_time: 0.0054 memory: 1482 2022/09/07 19:10:03 - mmengine - INFO - Epoch(val) [14][80/241] eta: 0:00:08 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 19:10:04 - mmengine - INFO - Epoch(val) [14][100/241] eta: 0:00:07 time: 0.0530 data_time: 0.0047 memory: 1482 2022/09/07 19:10:05 - mmengine - INFO - Epoch(val) [14][120/241] eta: 0:00:06 time: 0.0530 data_time: 0.0047 memory: 1482 2022/09/07 19:10:06 - mmengine - INFO - Epoch(val) [14][140/241] eta: 0:00:05 time: 0.0569 data_time: 0.0086 memory: 1482 2022/09/07 19:10:07 - mmengine - INFO - Epoch(val) [14][160/241] eta: 0:00:04 time: 0.0527 data_time: 0.0044 memory: 1482 2022/09/07 19:10:08 - mmengine - INFO - Epoch(val) [14][180/241] eta: 0:00:03 time: 0.0536 data_time: 0.0050 memory: 1482 2022/09/07 19:10:09 - mmengine - INFO - Epoch(val) [14][200/241] eta: 0:00:02 time: 0.0527 data_time: 0.0046 memory: 1482 2022/09/07 19:10:11 - mmengine - INFO - Epoch(val) [14][220/241] eta: 0:00:01 time: 0.0613 data_time: 0.0054 memory: 1482 2022/09/07 19:10:12 - mmengine - INFO - Epoch(val) [14][240/241] eta: 0:00:00 time: 0.0528 data_time: 0.0047 memory: 1482 2022/09/07 19:10:12 - mmengine - INFO - Epoch(val) [14][241/241] acc/top1: 0.2751 acc/top5: 0.5763 acc/mean1: 0.2536 2022/09/07 19:10:20 - mmengine - INFO - Epoch(train) [15][20/1793] lr: 7.5000e-03 eta: 8:23:06 time: 0.3740 data_time: 0.0316 memory: 10464 grad_norm: 7.6439 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2628 loss: 2.2628 2022/09/07 19:10:25 - mmengine - INFO - Epoch(train) [15][40/1793] lr: 7.5000e-03 eta: 8:22:46 time: 0.2536 data_time: 0.0063 memory: 10464 grad_norm: 7.0666 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.4694 loss: 2.4694 2022/09/07 19:10:29 - mmengine - INFO - Epoch(train) [15][60/1793] lr: 7.5000e-03 eta: 8:22:22 time: 0.1946 data_time: 0.0078 memory: 10464 grad_norm: 7.2780 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3985 loss: 2.3985 2022/09/07 19:10:33 - mmengine - INFO - Epoch(train) [15][80/1793] lr: 7.5000e-03 eta: 8:22:01 time: 0.2413 data_time: 0.0667 memory: 10464 grad_norm: 6.7263 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.3842 loss: 2.3842 2022/09/07 19:10:37 - mmengine - INFO - Epoch(train) [15][100/1793] lr: 7.5000e-03 eta: 8:21:38 time: 0.1937 data_time: 0.0062 memory: 10464 grad_norm: 7.0369 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2785 loss: 2.2785 2022/09/07 19:10:41 - mmengine - INFO - Epoch(train) [15][120/1793] lr: 7.5000e-03 eta: 8:21:14 time: 0.1819 data_time: 0.0088 memory: 10464 grad_norm: 7.2359 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5767 loss: 2.5767 2022/09/07 19:10:46 - mmengine - INFO - Epoch(train) [15][140/1793] lr: 7.5000e-03 eta: 8:20:54 time: 0.2575 data_time: 0.0068 memory: 10464 grad_norm: 6.8013 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.5950 loss: 2.5950 2022/09/07 19:10:51 - mmengine - INFO - Epoch(train) [15][160/1793] lr: 7.5000e-03 eta: 8:20:34 time: 0.2611 data_time: 0.0067 memory: 10464 grad_norm: 6.9192 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4146 loss: 2.4146 2022/09/07 19:10:56 - mmengine - INFO - Epoch(train) [15][180/1793] lr: 7.5000e-03 eta: 8:20:12 time: 0.2105 data_time: 0.0141 memory: 10464 grad_norm: 6.9806 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3160 loss: 2.3160 2022/09/07 19:11:03 - mmengine - INFO - Epoch(train) [15][200/1793] lr: 7.5000e-03 eta: 8:19:57 time: 0.3637 data_time: 0.0051 memory: 10464 grad_norm: 7.0737 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.9709 loss: 1.9709 2022/09/07 19:11:13 - mmengine - INFO - Epoch(train) [15][220/1793] lr: 7.5000e-03 eta: 8:19:50 time: 0.5039 data_time: 0.0093 memory: 10464 grad_norm: 7.2325 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3227 loss: 2.3227 2022/09/07 19:11:17 - mmengine - INFO - Epoch(train) [15][240/1793] lr: 7.5000e-03 eta: 8:19:26 time: 0.1852 data_time: 0.0106 memory: 10464 grad_norm: 7.0927 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3129 loss: 2.3129 2022/09/07 19:11:22 - mmengine - INFO - Epoch(train) [15][260/1793] lr: 7.5000e-03 eta: 8:19:07 time: 0.2775 data_time: 0.0050 memory: 10464 grad_norm: 6.9977 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.7429 loss: 2.7429 2022/09/07 19:11:27 - mmengine - INFO - Epoch(train) [15][280/1793] lr: 7.5000e-03 eta: 8:18:48 time: 0.2586 data_time: 0.0895 memory: 10464 grad_norm: 6.8586 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.5550 loss: 2.5550 2022/09/07 19:11:32 - mmengine - INFO - Epoch(train) [15][300/1793] lr: 7.5000e-03 eta: 8:18:26 time: 0.2188 data_time: 0.0091 memory: 10464 grad_norm: 6.9115 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3970 loss: 2.3970 2022/09/07 19:11:36 - mmengine - INFO - Epoch(train) [15][320/1793] lr: 7.5000e-03 eta: 8:18:03 time: 0.2021 data_time: 0.0336 memory: 10464 grad_norm: 7.4179 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.3043 loss: 2.3043 2022/09/07 19:11:40 - mmengine - INFO - Epoch(train) [15][340/1793] lr: 7.5000e-03 eta: 8:17:41 time: 0.2117 data_time: 0.0051 memory: 10464 grad_norm: 7.0095 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0737 loss: 2.0737 2022/09/07 19:11:44 - mmengine - INFO - Epoch(train) [15][360/1793] lr: 7.5000e-03 eta: 8:17:17 time: 0.1801 data_time: 0.0091 memory: 10464 grad_norm: 7.2777 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4883 loss: 2.4883 2022/09/07 19:11:47 - mmengine - INFO - Epoch(train) [15][380/1793] lr: 7.5000e-03 eta: 8:16:54 time: 0.1754 data_time: 0.0064 memory: 10464 grad_norm: 6.9187 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3750 loss: 2.3750 2022/09/07 19:11:51 - mmengine - INFO - Epoch(train) [15][400/1793] lr: 7.5000e-03 eta: 8:16:32 time: 0.2124 data_time: 0.0054 memory: 10464 grad_norm: 7.2002 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.5077 loss: 2.5077 2022/09/07 19:11:55 - mmengine - INFO - Epoch(train) [15][420/1793] lr: 7.5000e-03 eta: 8:16:09 time: 0.1919 data_time: 0.0099 memory: 10464 grad_norm: 7.0061 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3626 loss: 2.3626 2022/09/07 19:11:59 - mmengine - INFO - Epoch(train) [15][440/1793] lr: 7.5000e-03 eta: 8:15:45 time: 0.1748 data_time: 0.0064 memory: 10464 grad_norm: 6.9835 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.0617 loss: 2.0617 2022/09/07 19:12:02 - mmengine - INFO - Epoch(train) [15][460/1793] lr: 7.5000e-03 eta: 8:15:21 time: 0.1729 data_time: 0.0055 memory: 10464 grad_norm: 7.2012 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.5534 loss: 2.5534 2022/09/07 19:12:06 - mmengine - INFO - Epoch(train) [15][480/1793] lr: 7.5000e-03 eta: 8:14:57 time: 0.1748 data_time: 0.0094 memory: 10464 grad_norm: 6.5908 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.6280 loss: 2.6280 2022/09/07 19:12:10 - mmengine - INFO - Epoch(train) [15][500/1793] lr: 7.5000e-03 eta: 8:14:34 time: 0.1912 data_time: 0.0054 memory: 10464 grad_norm: 6.7861 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.1184 loss: 2.1184 2022/09/07 19:12:13 - mmengine - INFO - Epoch(train) [15][520/1793] lr: 7.5000e-03 eta: 8:14:12 time: 0.1946 data_time: 0.0072 memory: 10464 grad_norm: 6.8985 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3392 loss: 2.3392 2022/09/07 19:12:18 - mmengine - INFO - Epoch(train) [15][540/1793] lr: 7.5000e-03 eta: 8:13:50 time: 0.2212 data_time: 0.0097 memory: 10464 grad_norm: 6.9962 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.3296 loss: 2.3296 2022/09/07 19:12:22 - mmengine - INFO - Epoch(train) [15][560/1793] lr: 7.5000e-03 eta: 8:13:27 time: 0.1908 data_time: 0.0073 memory: 10464 grad_norm: 7.0158 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5405 loss: 2.5405 2022/09/07 19:12:25 - mmengine - INFO - Epoch(train) [15][580/1793] lr: 7.5000e-03 eta: 8:13:04 time: 0.1876 data_time: 0.0175 memory: 10464 grad_norm: 7.0685 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1006 loss: 2.1006 2022/09/07 19:12:32 - mmengine - INFO - Epoch(train) [15][600/1793] lr: 7.5000e-03 eta: 8:12:47 time: 0.3040 data_time: 0.0108 memory: 10464 grad_norm: 7.0246 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4893 loss: 2.4893 2022/09/07 19:12:37 - mmengine - INFO - Epoch(train) [15][620/1793] lr: 7.5000e-03 eta: 8:12:28 time: 0.2674 data_time: 0.0068 memory: 10464 grad_norm: 6.9212 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2407 loss: 2.2407 2022/09/07 19:12:42 - mmengine - INFO - Epoch(train) [15][640/1793] lr: 7.5000e-03 eta: 8:12:08 time: 0.2446 data_time: 0.0096 memory: 10464 grad_norm: 6.7406 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4819 loss: 2.4819 2022/09/07 19:12:46 - mmengine - INFO - Epoch(train) [15][660/1793] lr: 7.5000e-03 eta: 8:11:46 time: 0.1971 data_time: 0.0062 memory: 10464 grad_norm: 7.0583 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.3293 loss: 2.3293 2022/09/07 19:12:50 - mmengine - INFO - Epoch(train) [15][680/1793] lr: 7.5000e-03 eta: 8:11:23 time: 0.1917 data_time: 0.0061 memory: 10464 grad_norm: 6.8698 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.0087 loss: 2.0087 2022/09/07 19:12:53 - mmengine - INFO - Epoch(train) [15][700/1793] lr: 7.5000e-03 eta: 8:11:00 time: 0.1864 data_time: 0.0094 memory: 10464 grad_norm: 7.0908 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3818 loss: 2.3818 2022/09/07 19:12:58 - mmengine - INFO - Epoch(train) [15][720/1793] lr: 7.5000e-03 eta: 8:10:41 time: 0.2455 data_time: 0.0065 memory: 10464 grad_norm: 7.1393 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1374 loss: 2.1374 2022/09/07 19:13:04 - mmengine - INFO - Epoch(train) [15][740/1793] lr: 7.5000e-03 eta: 8:10:23 time: 0.2863 data_time: 0.0108 memory: 10464 grad_norm: 7.2914 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2565 loss: 2.2565 2022/09/07 19:13:08 - mmengine - INFO - Epoch(train) [15][760/1793] lr: 7.5000e-03 eta: 8:10:01 time: 0.2175 data_time: 0.0089 memory: 10464 grad_norm: 6.9618 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3762 loss: 2.3762 2022/09/07 19:13:12 - mmengine - INFO - Epoch(train) [15][780/1793] lr: 7.5000e-03 eta: 8:09:38 time: 0.1826 data_time: 0.0058 memory: 10464 grad_norm: 7.1788 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0088 loss: 2.0088 2022/09/07 19:13:17 - mmengine - INFO - Epoch(train) [15][800/1793] lr: 7.5000e-03 eta: 8:09:19 time: 0.2443 data_time: 0.0063 memory: 10464 grad_norm: 6.9488 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.4748 loss: 2.4748 2022/09/07 19:13:20 - mmengine - INFO - Epoch(train) [15][820/1793] lr: 7.5000e-03 eta: 8:08:56 time: 0.1798 data_time: 0.0088 memory: 10464 grad_norm: 6.8759 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3569 loss: 2.3569 2022/09/07 19:13:24 - mmengine - INFO - Epoch(train) [15][840/1793] lr: 7.5000e-03 eta: 8:08:33 time: 0.1788 data_time: 0.0062 memory: 10464 grad_norm: 7.3272 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3044 loss: 2.3044 2022/09/07 19:13:27 - mmengine - INFO - Epoch(train) [15][860/1793] lr: 7.5000e-03 eta: 8:08:09 time: 0.1765 data_time: 0.0065 memory: 10464 grad_norm: 7.0169 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4361 loss: 2.4361 2022/09/07 19:13:32 - mmengine - INFO - Epoch(train) [15][880/1793] lr: 7.5000e-03 eta: 8:07:49 time: 0.2369 data_time: 0.0089 memory: 10464 grad_norm: 7.1696 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4596 loss: 2.4596 2022/09/07 19:13:37 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:13:38 - mmengine - INFO - Epoch(train) [15][900/1793] lr: 7.5000e-03 eta: 8:07:31 time: 0.2714 data_time: 0.0069 memory: 10464 grad_norm: 7.1122 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.2706 loss: 2.2706 2022/09/07 19:13:42 - mmengine - INFO - Epoch(train) [15][920/1793] lr: 7.5000e-03 eta: 8:07:09 time: 0.2029 data_time: 0.0096 memory: 10464 grad_norm: 7.0408 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3656 loss: 2.3656 2022/09/07 19:13:45 - mmengine - INFO - Epoch(train) [15][940/1793] lr: 7.5000e-03 eta: 8:06:46 time: 0.1774 data_time: 0.0074 memory: 10464 grad_norm: 7.1572 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3713 loss: 2.3713 2022/09/07 19:13:49 - mmengine - INFO - Epoch(train) [15][960/1793] lr: 7.5000e-03 eta: 8:06:24 time: 0.1867 data_time: 0.0047 memory: 10464 grad_norm: 6.9256 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4326 loss: 2.4326 2022/09/07 19:13:54 - mmengine - INFO - Epoch(train) [15][980/1793] lr: 7.5000e-03 eta: 8:06:04 time: 0.2412 data_time: 0.0169 memory: 10464 grad_norm: 6.5356 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5383 loss: 2.5383 2022/09/07 19:14:00 - mmengine - INFO - Epoch(train) [15][1000/1793] lr: 7.5000e-03 eta: 8:05:47 time: 0.3053 data_time: 0.0756 memory: 10464 grad_norm: 6.9984 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1900 loss: 2.1900 2022/09/07 19:14:05 - mmengine - INFO - Epoch(train) [15][1020/1793] lr: 7.5000e-03 eta: 8:05:28 time: 0.2426 data_time: 0.0090 memory: 10464 grad_norm: 6.9041 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3584 loss: 2.3584 2022/09/07 19:14:09 - mmengine - INFO - Epoch(train) [15][1040/1793] lr: 7.5000e-03 eta: 8:05:06 time: 0.2092 data_time: 0.0055 memory: 10464 grad_norm: 7.0623 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.6477 loss: 2.6477 2022/09/07 19:14:13 - mmengine - INFO - Epoch(train) [15][1060/1793] lr: 7.5000e-03 eta: 8:04:44 time: 0.1975 data_time: 0.0083 memory: 10464 grad_norm: 6.8228 top1_acc: 0.1667 top5_acc: 1.0000 loss_cls: 2.5078 loss: 2.5078 2022/09/07 19:14:17 - mmengine - INFO - Epoch(train) [15][1080/1793] lr: 7.5000e-03 eta: 8:04:23 time: 0.2037 data_time: 0.0089 memory: 10464 grad_norm: 6.7637 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3865 loss: 2.3865 2022/09/07 19:14:21 - mmengine - INFO - Epoch(train) [15][1100/1793] lr: 7.5000e-03 eta: 8:04:02 time: 0.2193 data_time: 0.0485 memory: 10464 grad_norm: 6.7183 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3659 loss: 2.3659 2022/09/07 19:14:26 - mmengine - INFO - Epoch(train) [15][1120/1793] lr: 7.5000e-03 eta: 8:03:43 time: 0.2471 data_time: 0.0059 memory: 10464 grad_norm: 7.1146 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4456 loss: 2.4456 2022/09/07 19:14:32 - mmengine - INFO - Epoch(train) [15][1140/1793] lr: 7.5000e-03 eta: 8:03:24 time: 0.2587 data_time: 0.0720 memory: 10464 grad_norm: 6.9163 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3966 loss: 2.3966 2022/09/07 19:14:36 - mmengine - INFO - Epoch(train) [15][1160/1793] lr: 7.5000e-03 eta: 8:03:03 time: 0.2020 data_time: 0.0051 memory: 10464 grad_norm: 6.9600 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4377 loss: 2.4377 2022/09/07 19:14:41 - mmengine - INFO - Epoch(train) [15][1180/1793] lr: 7.5000e-03 eta: 8:02:45 time: 0.2793 data_time: 0.0072 memory: 10464 grad_norm: 7.0382 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.6083 loss: 2.6083 2022/09/07 19:14:47 - mmengine - INFO - Epoch(train) [15][1200/1793] lr: 7.5000e-03 eta: 8:02:28 time: 0.2925 data_time: 0.0340 memory: 10464 grad_norm: 7.4159 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6255 loss: 2.6255 2022/09/07 19:14:51 - mmengine - INFO - Epoch(train) [15][1220/1793] lr: 7.5000e-03 eta: 8:02:08 time: 0.2243 data_time: 0.0055 memory: 10464 grad_norm: 7.0882 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.5749 loss: 2.5749 2022/09/07 19:14:56 - mmengine - INFO - Epoch(train) [15][1240/1793] lr: 7.5000e-03 eta: 8:01:46 time: 0.2015 data_time: 0.0094 memory: 10464 grad_norm: 7.0128 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.5443 loss: 2.5443 2022/09/07 19:15:02 - mmengine - INFO - Epoch(train) [15][1260/1793] lr: 7.5000e-03 eta: 8:01:30 time: 0.3062 data_time: 0.0066 memory: 10464 grad_norm: 7.1464 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2363 loss: 2.2363 2022/09/07 19:15:08 - mmengine - INFO - Epoch(train) [15][1280/1793] lr: 7.5000e-03 eta: 8:01:13 time: 0.2982 data_time: 0.0097 memory: 10464 grad_norm: 6.8986 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.4293 loss: 2.4293 2022/09/07 19:15:15 - mmengine - INFO - Epoch(train) [15][1300/1793] lr: 7.5000e-03 eta: 8:01:00 time: 0.3650 data_time: 0.0075 memory: 10464 grad_norm: 7.0666 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.9992 loss: 1.9992 2022/09/07 19:15:18 - mmengine - INFO - Epoch(train) [15][1320/1793] lr: 7.5000e-03 eta: 8:00:37 time: 0.1762 data_time: 0.0087 memory: 10464 grad_norm: 7.1489 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3778 loss: 2.3778 2022/09/07 19:15:24 - mmengine - INFO - Epoch(train) [15][1340/1793] lr: 7.5000e-03 eta: 8:00:20 time: 0.2932 data_time: 0.0065 memory: 10464 grad_norm: 7.1667 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.3290 loss: 2.3290 2022/09/07 19:15:28 - mmengine - INFO - Epoch(train) [15][1360/1793] lr: 7.5000e-03 eta: 7:59:58 time: 0.1743 data_time: 0.0062 memory: 10464 grad_norm: 7.1461 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.5265 loss: 2.5265 2022/09/07 19:15:34 - mmengine - INFO - Epoch(train) [15][1380/1793] lr: 7.5000e-03 eta: 7:59:41 time: 0.2935 data_time: 0.0742 memory: 10464 grad_norm: 7.2739 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4083 loss: 2.4083 2022/09/07 19:15:38 - mmengine - INFO - Epoch(train) [15][1400/1793] lr: 7.5000e-03 eta: 7:59:20 time: 0.2052 data_time: 0.0052 memory: 10464 grad_norm: 7.3665 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5861 loss: 2.5861 2022/09/07 19:15:43 - mmengine - INFO - Epoch(train) [15][1420/1793] lr: 7.5000e-03 eta: 7:59:01 time: 0.2588 data_time: 0.0191 memory: 10464 grad_norm: 7.0745 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7158 loss: 2.7158 2022/09/07 19:15:48 - mmengine - INFO - Epoch(train) [15][1440/1793] lr: 7.5000e-03 eta: 7:58:42 time: 0.2446 data_time: 0.0086 memory: 10464 grad_norm: 6.9926 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2405 loss: 2.2405 2022/09/07 19:15:52 - mmengine - INFO - Epoch(train) [15][1460/1793] lr: 7.5000e-03 eta: 7:58:21 time: 0.1987 data_time: 0.0056 memory: 10464 grad_norm: 6.9156 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4942 loss: 2.4942 2022/09/07 19:15:57 - mmengine - INFO - Epoch(train) [15][1480/1793] lr: 7.5000e-03 eta: 7:58:02 time: 0.2511 data_time: 0.0068 memory: 10464 grad_norm: 7.0868 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3742 loss: 2.3742 2022/09/07 19:16:01 - mmengine - INFO - Epoch(train) [15][1500/1793] lr: 7.5000e-03 eta: 7:57:42 time: 0.2211 data_time: 0.0099 memory: 10464 grad_norm: 6.8055 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4017 loss: 2.4017 2022/09/07 19:16:05 - mmengine - INFO - Epoch(train) [15][1520/1793] lr: 7.5000e-03 eta: 7:57:20 time: 0.1771 data_time: 0.0065 memory: 10464 grad_norm: 6.9419 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.5417 loss: 2.5417 2022/09/07 19:16:10 - mmengine - INFO - Epoch(train) [15][1540/1793] lr: 7.5000e-03 eta: 7:57:01 time: 0.2549 data_time: 0.0061 memory: 10464 grad_norm: 6.8459 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5129 loss: 2.5129 2022/09/07 19:16:14 - mmengine - INFO - Epoch(train) [15][1560/1793] lr: 7.5000e-03 eta: 7:56:39 time: 0.1802 data_time: 0.0098 memory: 10464 grad_norm: 6.9673 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2921 loss: 2.2921 2022/09/07 19:16:21 - mmengine - INFO - Epoch(train) [15][1580/1793] lr: 7.5000e-03 eta: 7:56:25 time: 0.3501 data_time: 0.0060 memory: 10464 grad_norm: 6.8862 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3444 loss: 2.3444 2022/09/07 19:16:25 - mmengine - INFO - Epoch(train) [15][1600/1793] lr: 7.5000e-03 eta: 7:56:04 time: 0.2071 data_time: 0.0099 memory: 10464 grad_norm: 7.1042 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4864 loss: 2.4864 2022/09/07 19:16:29 - mmengine - INFO - Epoch(train) [15][1620/1793] lr: 7.5000e-03 eta: 7:55:45 time: 0.2262 data_time: 0.0060 memory: 10464 grad_norm: 7.2029 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2085 loss: 2.2085 2022/09/07 19:16:33 - mmengine - INFO - Epoch(train) [15][1640/1793] lr: 7.5000e-03 eta: 7:55:23 time: 0.1800 data_time: 0.0075 memory: 10464 grad_norm: 7.0511 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6063 loss: 2.6063 2022/09/07 19:16:37 - mmengine - INFO - Epoch(train) [15][1660/1793] lr: 7.5000e-03 eta: 7:55:01 time: 0.1859 data_time: 0.0080 memory: 10464 grad_norm: 7.4250 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.7199 loss: 2.7199 2022/09/07 19:16:41 - mmengine - INFO - Epoch(train) [15][1680/1793] lr: 7.5000e-03 eta: 7:54:41 time: 0.2247 data_time: 0.0063 memory: 10464 grad_norm: 6.9455 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4347 loss: 2.4347 2022/09/07 19:16:46 - mmengine - INFO - Epoch(train) [15][1700/1793] lr: 7.5000e-03 eta: 7:54:22 time: 0.2422 data_time: 0.0065 memory: 10464 grad_norm: 7.0281 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.5142 loss: 2.5142 2022/09/07 19:16:49 - mmengine - INFO - Epoch(train) [15][1720/1793] lr: 7.5000e-03 eta: 7:54:00 time: 0.1809 data_time: 0.0082 memory: 10464 grad_norm: 7.2301 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4372 loss: 2.4372 2022/09/07 19:16:54 - mmengine - INFO - Epoch(train) [15][1740/1793] lr: 7.5000e-03 eta: 7:53:41 time: 0.2402 data_time: 0.0711 memory: 10464 grad_norm: 6.9471 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2758 loss: 2.2758 2022/09/07 19:16:59 - mmengine - INFO - Epoch(train) [15][1760/1793] lr: 7.5000e-03 eta: 7:53:23 time: 0.2564 data_time: 0.0063 memory: 10464 grad_norm: 7.1800 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4431 loss: 2.4431 2022/09/07 19:17:04 - mmengine - INFO - Epoch(train) [15][1780/1793] lr: 7.5000e-03 eta: 7:53:03 time: 0.2190 data_time: 0.0408 memory: 10464 grad_norm: 6.8713 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3627 loss: 2.3627 2022/09/07 19:17:07 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:17:07 - mmengine - INFO - Epoch(train) [15][1793/1793] lr: 7.5000e-03 eta: 7:53:03 time: 0.2374 data_time: 0.0734 memory: 10464 grad_norm: 7.0191 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.5240 loss: 2.5240 2022/09/07 19:17:07 - mmengine - INFO - Saving checkpoint at 15 epochs 2022/09/07 19:17:11 - mmengine - INFO - Epoch(val) [15][20/241] eta: 0:00:13 time: 0.0590 data_time: 0.0097 memory: 1482 2022/09/07 19:17:12 - mmengine - INFO - Epoch(val) [15][40/241] eta: 0:00:10 time: 0.0529 data_time: 0.0046 memory: 1482 2022/09/07 19:17:13 - mmengine - INFO - Epoch(val) [15][60/241] eta: 0:00:09 time: 0.0531 data_time: 0.0047 memory: 1482 2022/09/07 19:17:14 - mmengine - INFO - Epoch(val) [15][80/241] eta: 0:00:08 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 19:17:15 - mmengine - INFO - Epoch(val) [15][100/241] eta: 0:00:07 time: 0.0535 data_time: 0.0051 memory: 1482 2022/09/07 19:17:16 - mmengine - INFO - Epoch(val) [15][120/241] eta: 0:00:06 time: 0.0530 data_time: 0.0047 memory: 1482 2022/09/07 19:17:17 - mmengine - INFO - Epoch(val) [15][140/241] eta: 0:00:05 time: 0.0533 data_time: 0.0048 memory: 1482 2022/09/07 19:17:18 - mmengine - INFO - Epoch(val) [15][160/241] eta: 0:00:04 time: 0.0534 data_time: 0.0051 memory: 1482 2022/09/07 19:17:19 - mmengine - INFO - Epoch(val) [15][180/241] eta: 0:00:03 time: 0.0536 data_time: 0.0050 memory: 1482 2022/09/07 19:17:20 - mmengine - INFO - Epoch(val) [15][200/241] eta: 0:00:02 time: 0.0530 data_time: 0.0048 memory: 1482 2022/09/07 19:17:21 - mmengine - INFO - Epoch(val) [15][220/241] eta: 0:00:01 time: 0.0592 data_time: 0.0063 memory: 1482 2022/09/07 19:17:22 - mmengine - INFO - Epoch(val) [15][240/241] eta: 0:00:00 time: 0.0526 data_time: 0.0047 memory: 1482 2022/09/07 19:17:23 - mmengine - INFO - Epoch(val) [15][241/241] acc/top1: 0.3073 acc/top5: 0.6218 acc/mean1: 0.2838 2022/09/07 19:17:23 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_13.pth is removed 2022/09/07 19:17:25 - mmengine - INFO - The best checkpoint with 0.3073 acc/top1 at 15 epoch is saved to best_acc/top1_epoch_15.pth. 2022/09/07 19:17:29 - mmengine - INFO - Epoch(train) [16][20/1793] lr: 7.5000e-03 eta: 7:52:24 time: 0.2324 data_time: 0.0109 memory: 10464 grad_norm: 6.8773 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1539 loss: 2.1539 2022/09/07 19:17:33 - mmengine - INFO - Epoch(train) [16][40/1793] lr: 7.5000e-03 eta: 7:52:04 time: 0.2046 data_time: 0.0058 memory: 10464 grad_norm: 6.9972 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.9678 loss: 1.9678 2022/09/07 19:17:37 - mmengine - INFO - Epoch(train) [16][60/1793] lr: 7.5000e-03 eta: 7:51:42 time: 0.1755 data_time: 0.0084 memory: 10464 grad_norm: 7.4040 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2521 loss: 2.2521 2022/09/07 19:17:41 - mmengine - INFO - Epoch(train) [16][80/1793] lr: 7.5000e-03 eta: 7:51:21 time: 0.1843 data_time: 0.0063 memory: 10464 grad_norm: 6.7376 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1866 loss: 2.1866 2022/09/07 19:17:44 - mmengine - INFO - Epoch(train) [16][100/1793] lr: 7.5000e-03 eta: 7:50:59 time: 0.1778 data_time: 0.0066 memory: 10464 grad_norm: 7.1232 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.1375 loss: 2.1375 2022/09/07 19:17:45 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:17:48 - mmengine - INFO - Epoch(train) [16][120/1793] lr: 7.5000e-03 eta: 7:50:37 time: 0.1767 data_time: 0.0084 memory: 10464 grad_norm: 7.1248 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2289 loss: 2.2289 2022/09/07 19:17:51 - mmengine - INFO - Epoch(train) [16][140/1793] lr: 7.5000e-03 eta: 7:50:15 time: 0.1751 data_time: 0.0070 memory: 10464 grad_norm: 6.5854 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5314 loss: 2.5314 2022/09/07 19:17:55 - mmengine - INFO - Epoch(train) [16][160/1793] lr: 7.5000e-03 eta: 7:49:53 time: 0.1735 data_time: 0.0070 memory: 10464 grad_norm: 6.9712 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.2116 loss: 2.2116 2022/09/07 19:17:58 - mmengine - INFO - Epoch(train) [16][180/1793] lr: 7.5000e-03 eta: 7:49:32 time: 0.1883 data_time: 0.0089 memory: 10464 grad_norm: 7.1568 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5781 loss: 2.5781 2022/09/07 19:18:02 - mmengine - INFO - Epoch(train) [16][200/1793] lr: 7.5000e-03 eta: 7:49:11 time: 0.1784 data_time: 0.0072 memory: 10464 grad_norm: 7.2008 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5542 loss: 2.5542 2022/09/07 19:18:05 - mmengine - INFO - Epoch(train) [16][220/1793] lr: 7.5000e-03 eta: 7:48:49 time: 0.1716 data_time: 0.0061 memory: 10464 grad_norm: 7.1490 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4069 loss: 2.4069 2022/09/07 19:18:09 - mmengine - INFO - Epoch(train) [16][240/1793] lr: 7.5000e-03 eta: 7:48:27 time: 0.1751 data_time: 0.0084 memory: 10464 grad_norm: 6.9847 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1961 loss: 2.1961 2022/09/07 19:18:12 - mmengine - INFO - Epoch(train) [16][260/1793] lr: 7.5000e-03 eta: 7:48:06 time: 0.1728 data_time: 0.0065 memory: 10464 grad_norm: 6.9486 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.9633 loss: 2.9633 2022/09/07 19:18:16 - mmengine - INFO - Epoch(train) [16][280/1793] lr: 7.5000e-03 eta: 7:47:44 time: 0.1725 data_time: 0.0068 memory: 10464 grad_norm: 7.0003 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3271 loss: 2.3271 2022/09/07 19:18:20 - mmengine - INFO - Epoch(train) [16][300/1793] lr: 7.5000e-03 eta: 7:47:23 time: 0.2001 data_time: 0.0085 memory: 10464 grad_norm: 7.1680 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.3503 loss: 2.3503 2022/09/07 19:18:24 - mmengine - INFO - Epoch(train) [16][320/1793] lr: 7.5000e-03 eta: 7:47:02 time: 0.1821 data_time: 0.0064 memory: 10464 grad_norm: 7.0273 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4222 loss: 2.4222 2022/09/07 19:18:27 - mmengine - INFO - Epoch(train) [16][340/1793] lr: 7.5000e-03 eta: 7:46:41 time: 0.1729 data_time: 0.0069 memory: 10464 grad_norm: 6.9273 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.3978 loss: 2.3978 2022/09/07 19:18:32 - mmengine - INFO - Epoch(train) [16][360/1793] lr: 7.5000e-03 eta: 7:46:23 time: 0.2645 data_time: 0.0083 memory: 10464 grad_norm: 7.2464 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1682 loss: 2.1682 2022/09/07 19:18:40 - mmengine - INFO - Epoch(train) [16][380/1793] lr: 7.5000e-03 eta: 7:46:11 time: 0.3762 data_time: 0.0065 memory: 10464 grad_norm: 7.2555 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.5498 loss: 2.5498 2022/09/07 19:18:44 - mmengine - INFO - Epoch(train) [16][400/1793] lr: 7.5000e-03 eta: 7:45:51 time: 0.2182 data_time: 0.0092 memory: 10464 grad_norm: 6.7678 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5585 loss: 2.5585 2022/09/07 19:18:49 - mmengine - INFO - Epoch(train) [16][420/1793] lr: 7.5000e-03 eta: 7:45:33 time: 0.2490 data_time: 0.0062 memory: 10464 grad_norm: 6.8886 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.3677 loss: 2.3677 2022/09/07 19:18:53 - mmengine - INFO - Epoch(train) [16][440/1793] lr: 7.5000e-03 eta: 7:45:14 time: 0.2109 data_time: 0.0069 memory: 10464 grad_norm: 7.0122 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3884 loss: 2.3884 2022/09/07 19:18:57 - mmengine - INFO - Epoch(train) [16][460/1793] lr: 7.5000e-03 eta: 7:44:53 time: 0.1938 data_time: 0.0086 memory: 10464 grad_norm: 6.8152 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.4675 loss: 2.4675 2022/09/07 19:19:01 - mmengine - INFO - Epoch(train) [16][480/1793] lr: 7.5000e-03 eta: 7:44:33 time: 0.2040 data_time: 0.0088 memory: 10464 grad_norm: 7.1419 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4678 loss: 2.4678 2022/09/07 19:19:06 - mmengine - INFO - Epoch(train) [16][500/1793] lr: 7.5000e-03 eta: 7:44:14 time: 0.2317 data_time: 0.0063 memory: 10464 grad_norm: 7.3981 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3112 loss: 2.3112 2022/09/07 19:19:12 - mmengine - INFO - Epoch(train) [16][520/1793] lr: 7.5000e-03 eta: 7:43:58 time: 0.2965 data_time: 0.0080 memory: 10464 grad_norm: 6.9428 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2435 loss: 2.2435 2022/09/07 19:19:16 - mmengine - INFO - Epoch(train) [16][540/1793] lr: 7.5000e-03 eta: 7:43:38 time: 0.1866 data_time: 0.0069 memory: 10464 grad_norm: 6.9943 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.4297 loss: 2.4297 2022/09/07 19:19:23 - mmengine - INFO - Epoch(train) [16][560/1793] lr: 7.5000e-03 eta: 7:43:24 time: 0.3524 data_time: 0.0724 memory: 10464 grad_norm: 7.2901 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.0318 loss: 2.0318 2022/09/07 19:19:26 - mmengine - INFO - Epoch(train) [16][580/1793] lr: 7.5000e-03 eta: 7:43:03 time: 0.1776 data_time: 0.0082 memory: 10464 grad_norm: 6.7982 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5459 loss: 2.5459 2022/09/07 19:19:30 - mmengine - INFO - Epoch(train) [16][600/1793] lr: 7.5000e-03 eta: 7:42:43 time: 0.1936 data_time: 0.0214 memory: 10464 grad_norm: 7.3236 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3421 loss: 2.3421 2022/09/07 19:19:35 - mmengine - INFO - Epoch(train) [16][620/1793] lr: 7.5000e-03 eta: 7:42:25 time: 0.2422 data_time: 0.0058 memory: 10464 grad_norm: 6.9622 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4817 loss: 2.4817 2022/09/07 19:19:39 - mmengine - INFO - Epoch(train) [16][640/1793] lr: 7.5000e-03 eta: 7:42:04 time: 0.1966 data_time: 0.0074 memory: 10464 grad_norm: 6.9690 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.1970 loss: 2.1970 2022/09/07 19:19:44 - mmengine - INFO - Epoch(train) [16][660/1793] lr: 7.5000e-03 eta: 7:41:46 time: 0.2313 data_time: 0.0063 memory: 10464 grad_norm: 7.2142 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7045 loss: 2.7045 2022/09/07 19:19:51 - mmengine - INFO - Epoch(train) [16][680/1793] lr: 7.5000e-03 eta: 7:41:33 time: 0.3506 data_time: 0.0060 memory: 10464 grad_norm: 7.1517 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1838 loss: 2.1838 2022/09/07 19:19:55 - mmengine - INFO - Epoch(train) [16][700/1793] lr: 7.5000e-03 eta: 7:41:15 time: 0.2429 data_time: 0.0087 memory: 10464 grad_norm: 7.3200 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.4529 loss: 2.4529 2022/09/07 19:19:59 - mmengine - INFO - Epoch(train) [16][720/1793] lr: 7.5000e-03 eta: 7:40:54 time: 0.1971 data_time: 0.0057 memory: 10464 grad_norm: 6.8432 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2713 loss: 2.2713 2022/09/07 19:20:04 - mmengine - INFO - Epoch(train) [16][740/1793] lr: 7.5000e-03 eta: 7:40:37 time: 0.2559 data_time: 0.0066 memory: 10464 grad_norm: 7.0592 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3959 loss: 2.3959 2022/09/07 19:20:09 - mmengine - INFO - Epoch(train) [16][760/1793] lr: 7.5000e-03 eta: 7:40:18 time: 0.2143 data_time: 0.0091 memory: 10464 grad_norm: 7.0465 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.2849 loss: 2.2849 2022/09/07 19:20:14 - mmengine - INFO - Epoch(train) [16][780/1793] lr: 7.5000e-03 eta: 7:40:01 time: 0.2729 data_time: 0.0070 memory: 10464 grad_norm: 6.8095 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 2.4212 loss: 2.4212 2022/09/07 19:20:18 - mmengine - INFO - Epoch(train) [16][800/1793] lr: 7.5000e-03 eta: 7:39:40 time: 0.1782 data_time: 0.0070 memory: 10464 grad_norm: 7.3191 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3402 loss: 2.3402 2022/09/07 19:20:22 - mmengine - INFO - Epoch(train) [16][820/1793] lr: 7.5000e-03 eta: 7:39:21 time: 0.2067 data_time: 0.0103 memory: 10464 grad_norm: 7.2361 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1101 loss: 2.1101 2022/09/07 19:20:27 - mmengine - INFO - Epoch(train) [16][840/1793] lr: 7.5000e-03 eta: 7:39:03 time: 0.2402 data_time: 0.0615 memory: 10464 grad_norm: 7.4339 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.3303 loss: 2.3303 2022/09/07 19:20:32 - mmengine - INFO - Epoch(train) [16][860/1793] lr: 7.5000e-03 eta: 7:38:45 time: 0.2510 data_time: 0.0563 memory: 10464 grad_norm: 7.5230 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4050 loss: 2.4050 2022/09/07 19:20:35 - mmengine - INFO - Epoch(train) [16][880/1793] lr: 7.5000e-03 eta: 7:38:24 time: 0.1793 data_time: 0.0104 memory: 10464 grad_norm: 7.0049 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5415 loss: 2.5415 2022/09/07 19:20:41 - mmengine - INFO - Epoch(train) [16][900/1793] lr: 7.5000e-03 eta: 7:38:09 time: 0.3061 data_time: 0.0067 memory: 10464 grad_norm: 7.0717 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3698 loss: 2.3698 2022/09/07 19:20:46 - mmengine - INFO - Epoch(train) [16][920/1793] lr: 7.5000e-03 eta: 7:37:51 time: 0.2245 data_time: 0.0556 memory: 10464 grad_norm: 7.0299 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2007 loss: 2.2007 2022/09/07 19:20:50 - mmengine - INFO - Epoch(train) [16][940/1793] lr: 7.5000e-03 eta: 7:37:32 time: 0.2175 data_time: 0.0404 memory: 10464 grad_norm: 6.9922 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3668 loss: 2.3668 2022/09/07 19:20:55 - mmengine - INFO - Epoch(train) [16][960/1793] lr: 7.5000e-03 eta: 7:37:13 time: 0.2161 data_time: 0.0063 memory: 10464 grad_norm: 7.1651 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2738 loss: 2.2738 2022/09/07 19:20:58 - mmengine - INFO - Epoch(train) [16][980/1793] lr: 7.5000e-03 eta: 7:36:52 time: 0.1785 data_time: 0.0077 memory: 10464 grad_norm: 7.1971 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3731 loss: 2.3731 2022/09/07 19:21:05 - mmengine - INFO - Epoch(train) [16][1000/1793] lr: 7.5000e-03 eta: 7:36:38 time: 0.3236 data_time: 0.0094 memory: 10464 grad_norm: 6.9987 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5441 loss: 2.5441 2022/09/07 19:21:10 - mmengine - INFO - Epoch(train) [16][1020/1793] lr: 7.5000e-03 eta: 7:36:22 time: 0.2794 data_time: 0.1095 memory: 10464 grad_norm: 6.9881 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3158 loss: 2.3158 2022/09/07 19:21:16 - mmengine - INFO - Epoch(train) [16][1040/1793] lr: 7.5000e-03 eta: 7:36:05 time: 0.2722 data_time: 0.0076 memory: 10464 grad_norm: 7.1787 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5341 loss: 2.5341 2022/09/07 19:21:19 - mmengine - INFO - Epoch(train) [16][1060/1793] lr: 7.5000e-03 eta: 7:35:45 time: 0.1838 data_time: 0.0082 memory: 10464 grad_norm: 7.2711 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3622 loss: 2.3622 2022/09/07 19:21:23 - mmengine - INFO - Epoch(train) [16][1080/1793] lr: 7.5000e-03 eta: 7:35:25 time: 0.1914 data_time: 0.0056 memory: 10464 grad_norm: 6.9287 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3319 loss: 2.3319 2022/09/07 19:21:27 - mmengine - INFO - Epoch(train) [16][1100/1793] lr: 7.5000e-03 eta: 7:35:05 time: 0.1916 data_time: 0.0079 memory: 10464 grad_norm: 7.1799 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.5316 loss: 2.5316 2022/09/07 19:21:28 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:21:32 - mmengine - INFO - Epoch(train) [16][1120/1793] lr: 7.5000e-03 eta: 7:34:47 time: 0.2332 data_time: 0.0067 memory: 10464 grad_norm: 6.9954 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4782 loss: 2.4782 2022/09/07 19:21:37 - mmengine - INFO - Epoch(train) [16][1140/1793] lr: 7.5000e-03 eta: 7:34:29 time: 0.2416 data_time: 0.0058 memory: 10464 grad_norm: 7.4143 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4372 loss: 2.4372 2022/09/07 19:21:42 - mmengine - INFO - Epoch(train) [16][1160/1793] lr: 7.5000e-03 eta: 7:34:13 time: 0.2647 data_time: 0.0086 memory: 10464 grad_norm: 7.1122 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.4572 loss: 2.4572 2022/09/07 19:21:45 - mmengine - INFO - Epoch(train) [16][1180/1793] lr: 7.5000e-03 eta: 7:33:52 time: 0.1767 data_time: 0.0102 memory: 10464 grad_norm: 7.2861 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5012 loss: 2.5012 2022/09/07 19:21:51 - mmengine - INFO - Epoch(train) [16][1200/1793] lr: 7.5000e-03 eta: 7:33:35 time: 0.2651 data_time: 0.0046 memory: 10464 grad_norm: 6.8982 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4355 loss: 2.4355 2022/09/07 19:21:56 - mmengine - INFO - Epoch(train) [16][1220/1793] lr: 7.5000e-03 eta: 7:33:18 time: 0.2413 data_time: 0.0090 memory: 10464 grad_norm: 7.0265 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.1146 loss: 2.1146 2022/09/07 19:22:00 - mmengine - INFO - Epoch(train) [16][1240/1793] lr: 7.5000e-03 eta: 7:32:59 time: 0.2101 data_time: 0.0108 memory: 10464 grad_norm: 6.8087 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.3170 loss: 2.3170 2022/09/07 19:22:05 - mmengine - INFO - Epoch(train) [16][1260/1793] lr: 7.5000e-03 eta: 7:32:41 time: 0.2429 data_time: 0.0065 memory: 10464 grad_norm: 7.3659 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2576 loss: 2.2576 2022/09/07 19:22:10 - mmengine - INFO - Epoch(train) [16][1280/1793] lr: 7.5000e-03 eta: 7:32:25 time: 0.2791 data_time: 0.0078 memory: 10464 grad_norm: 7.2275 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4885 loss: 2.4885 2022/09/07 19:22:16 - mmengine - INFO - Epoch(train) [16][1300/1793] lr: 7.5000e-03 eta: 7:32:09 time: 0.2771 data_time: 0.0061 memory: 10464 grad_norm: 6.8852 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.1169 loss: 2.1169 2022/09/07 19:22:21 - mmengine - INFO - Epoch(train) [16][1320/1793] lr: 7.5000e-03 eta: 7:31:53 time: 0.2582 data_time: 0.0095 memory: 10464 grad_norm: 6.8981 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3286 loss: 2.3286 2022/09/07 19:22:24 - mmengine - INFO - Epoch(train) [16][1340/1793] lr: 7.5000e-03 eta: 7:31:32 time: 0.1797 data_time: 0.0077 memory: 10464 grad_norm: 6.7332 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2220 loss: 2.2220 2022/09/07 19:22:28 - mmengine - INFO - Epoch(train) [16][1360/1793] lr: 7.5000e-03 eta: 7:31:13 time: 0.1919 data_time: 0.0058 memory: 10464 grad_norm: 7.2798 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.5139 loss: 2.5139 2022/09/07 19:22:33 - mmengine - INFO - Epoch(train) [16][1380/1793] lr: 7.5000e-03 eta: 7:30:56 time: 0.2523 data_time: 0.0810 memory: 10464 grad_norm: 7.0455 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2026 loss: 2.2026 2022/09/07 19:22:37 - mmengine - INFO - Epoch(train) [16][1400/1793] lr: 7.5000e-03 eta: 7:30:35 time: 0.1773 data_time: 0.0059 memory: 10464 grad_norm: 6.8957 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.4432 loss: 2.4432 2022/09/07 19:22:40 - mmengine - INFO - Epoch(train) [16][1420/1793] lr: 7.5000e-03 eta: 7:30:15 time: 0.1775 data_time: 0.0056 memory: 10464 grad_norm: 6.8738 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3271 loss: 2.3271 2022/09/07 19:22:44 - mmengine - INFO - Epoch(train) [16][1440/1793] lr: 7.5000e-03 eta: 7:29:55 time: 0.1835 data_time: 0.0102 memory: 10464 grad_norm: 6.9650 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.6660 loss: 2.6660 2022/09/07 19:22:48 - mmengine - INFO - Epoch(train) [16][1460/1793] lr: 7.5000e-03 eta: 7:29:35 time: 0.1745 data_time: 0.0063 memory: 10464 grad_norm: 6.9982 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.2662 loss: 2.2662 2022/09/07 19:22:53 - mmengine - INFO - Epoch(train) [16][1480/1793] lr: 7.5000e-03 eta: 7:29:18 time: 0.2537 data_time: 0.0058 memory: 10464 grad_norm: 7.2219 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9372 loss: 1.9372 2022/09/07 19:22:57 - mmengine - INFO - Epoch(train) [16][1500/1793] lr: 7.5000e-03 eta: 7:29:01 time: 0.2356 data_time: 0.0100 memory: 10464 grad_norm: 6.9746 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4963 loss: 2.4963 2022/09/07 19:23:02 - mmengine - INFO - Epoch(train) [16][1520/1793] lr: 7.5000e-03 eta: 7:28:43 time: 0.2469 data_time: 0.0606 memory: 10464 grad_norm: 7.0985 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4918 loss: 2.4918 2022/09/07 19:23:07 - mmengine - INFO - Epoch(train) [16][1540/1793] lr: 7.5000e-03 eta: 7:28:27 time: 0.2537 data_time: 0.0525 memory: 10464 grad_norm: 7.1826 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.5210 loss: 2.5210 2022/09/07 19:23:11 - mmengine - INFO - Epoch(train) [16][1560/1793] lr: 7.5000e-03 eta: 7:28:07 time: 0.1766 data_time: 0.0094 memory: 10464 grad_norm: 6.8712 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3770 loss: 2.3770 2022/09/07 19:23:14 - mmengine - INFO - Epoch(train) [16][1580/1793] lr: 7.5000e-03 eta: 7:27:46 time: 0.1748 data_time: 0.0054 memory: 10464 grad_norm: 6.9221 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3736 loss: 2.3736 2022/09/07 19:23:19 - mmengine - INFO - Epoch(train) [16][1600/1793] lr: 7.5000e-03 eta: 7:27:29 time: 0.2482 data_time: 0.0060 memory: 10464 grad_norm: 6.8047 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4708 loss: 2.4708 2022/09/07 19:23:24 - mmengine - INFO - Epoch(train) [16][1620/1793] lr: 7.5000e-03 eta: 7:27:12 time: 0.2369 data_time: 0.0106 memory: 10464 grad_norm: 6.9848 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3134 loss: 2.3134 2022/09/07 19:23:28 - mmengine - INFO - Epoch(train) [16][1640/1793] lr: 7.5000e-03 eta: 7:26:53 time: 0.2118 data_time: 0.0057 memory: 10464 grad_norm: 6.9902 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4285 loss: 2.4285 2022/09/07 19:23:38 - mmengine - INFO - Epoch(train) [16][1660/1793] lr: 7.5000e-03 eta: 7:26:46 time: 0.4705 data_time: 0.2334 memory: 10464 grad_norm: 7.2994 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6440 loss: 2.6440 2022/09/07 19:23:43 - mmengine - INFO - Epoch(train) [16][1680/1793] lr: 7.5000e-03 eta: 7:26:29 time: 0.2442 data_time: 0.0081 memory: 10464 grad_norm: 6.9709 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5855 loss: 2.5855 2022/09/07 19:23:46 - mmengine - INFO - Epoch(train) [16][1700/1793] lr: 7.5000e-03 eta: 7:26:09 time: 0.1739 data_time: 0.0068 memory: 10464 grad_norm: 7.0524 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3438 loss: 2.3438 2022/09/07 19:23:51 - mmengine - INFO - Epoch(train) [16][1720/1793] lr: 7.5000e-03 eta: 7:25:52 time: 0.2445 data_time: 0.0065 memory: 10464 grad_norm: 6.9661 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2672 loss: 2.2672 2022/09/07 19:23:57 - mmengine - INFO - Epoch(train) [16][1740/1793] lr: 7.5000e-03 eta: 7:25:37 time: 0.2915 data_time: 0.0097 memory: 10464 grad_norm: 7.5442 top1_acc: 0.0000 top5_acc: 0.8333 loss_cls: 2.4583 loss: 2.4583 2022/09/07 19:24:00 - mmengine - INFO - Epoch(train) [16][1760/1793] lr: 7.5000e-03 eta: 7:25:17 time: 0.1749 data_time: 0.0055 memory: 10464 grad_norm: 7.3250 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.2209 loss: 2.2209 2022/09/07 19:24:04 - mmengine - INFO - Epoch(train) [16][1780/1793] lr: 7.5000e-03 eta: 7:24:58 time: 0.1919 data_time: 0.0059 memory: 10464 grad_norm: 7.1135 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.4624 loss: 2.4624 2022/09/07 19:24:06 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:24:06 - mmengine - INFO - Epoch(train) [16][1793/1793] lr: 7.5000e-03 eta: 7:24:58 time: 0.1844 data_time: 0.0094 memory: 10464 grad_norm: 7.2444 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.5246 loss: 2.5246 2022/09/07 19:24:06 - mmengine - INFO - Saving checkpoint at 16 epochs 2022/09/07 19:24:10 - mmengine - INFO - Epoch(val) [16][20/241] eta: 0:00:12 time: 0.0587 data_time: 0.0097 memory: 1482 2022/09/07 19:24:11 - mmengine - INFO - Epoch(val) [16][40/241] eta: 0:00:10 time: 0.0537 data_time: 0.0051 memory: 1482 2022/09/07 19:24:12 - mmengine - INFO - Epoch(val) [16][60/241] eta: 0:00:09 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 19:24:13 - mmengine - INFO - Epoch(val) [16][80/241] eta: 0:00:08 time: 0.0530 data_time: 0.0048 memory: 1482 2022/09/07 19:24:14 - mmengine - INFO - Epoch(val) [16][100/241] eta: 0:00:07 time: 0.0533 data_time: 0.0050 memory: 1482 2022/09/07 19:24:15 - mmengine - INFO - Epoch(val) [16][120/241] eta: 0:00:06 time: 0.0533 data_time: 0.0048 memory: 1482 2022/09/07 19:24:16 - mmengine - INFO - Epoch(val) [16][140/241] eta: 0:00:05 time: 0.0532 data_time: 0.0049 memory: 1482 2022/09/07 19:24:18 - mmengine - INFO - Epoch(val) [16][160/241] eta: 0:00:04 time: 0.0532 data_time: 0.0050 memory: 1482 2022/09/07 19:24:19 - mmengine - INFO - Epoch(val) [16][180/241] eta: 0:00:03 time: 0.0534 data_time: 0.0052 memory: 1482 2022/09/07 19:24:20 - mmengine - INFO - Epoch(val) [16][200/241] eta: 0:00:02 time: 0.0524 data_time: 0.0045 memory: 1482 2022/09/07 19:24:21 - mmengine - INFO - Epoch(val) [16][220/241] eta: 0:00:01 time: 0.0529 data_time: 0.0047 memory: 1482 2022/09/07 19:24:22 - mmengine - INFO - Epoch(val) [16][240/241] eta: 0:00:00 time: 0.0612 data_time: 0.0068 memory: 1482 2022/09/07 19:24:23 - mmengine - INFO - Epoch(val) [16][241/241] acc/top1: 0.3118 acc/top5: 0.6237 acc/mean1: 0.2870 2022/09/07 19:24:23 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_15.pth is removed 2022/09/07 19:24:24 - mmengine - INFO - The best checkpoint with 0.3118 acc/top1 at 16 epoch is saved to best_acc/top1_epoch_16.pth. 2022/09/07 19:24:30 - mmengine - INFO - Epoch(train) [17][20/1793] lr: 7.5000e-03 eta: 7:24:24 time: 0.2634 data_time: 0.0927 memory: 10464 grad_norm: 6.8901 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1556 loss: 2.1556 2022/09/07 19:24:34 - mmengine - INFO - Epoch(train) [17][40/1793] lr: 7.5000e-03 eta: 7:24:05 time: 0.2132 data_time: 0.0062 memory: 10464 grad_norm: 7.2332 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3186 loss: 2.3186 2022/09/07 19:24:37 - mmengine - INFO - Epoch(train) [17][60/1793] lr: 7.5000e-03 eta: 7:23:46 time: 0.1819 data_time: 0.0121 memory: 10464 grad_norm: 7.1718 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.1697 loss: 2.1697 2022/09/07 19:24:43 - mmengine - INFO - Epoch(train) [17][80/1793] lr: 7.5000e-03 eta: 7:23:30 time: 0.2643 data_time: 0.0068 memory: 10464 grad_norm: 7.0292 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.5635 loss: 2.5635 2022/09/07 19:24:48 - mmengine - INFO - Epoch(train) [17][100/1793] lr: 7.5000e-03 eta: 7:23:15 time: 0.2876 data_time: 0.0060 memory: 10464 grad_norm: 7.0312 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3232 loss: 2.3232 2022/09/07 19:24:53 - mmengine - INFO - Epoch(train) [17][120/1793] lr: 7.5000e-03 eta: 7:22:57 time: 0.2251 data_time: 0.0092 memory: 10464 grad_norm: 7.2316 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2082 loss: 2.2082 2022/09/07 19:24:57 - mmengine - INFO - Epoch(train) [17][140/1793] lr: 7.5000e-03 eta: 7:22:38 time: 0.2001 data_time: 0.0326 memory: 10464 grad_norm: 7.0827 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4303 loss: 2.4303 2022/09/07 19:25:02 - mmengine - INFO - Epoch(train) [17][160/1793] lr: 7.5000e-03 eta: 7:22:23 time: 0.2753 data_time: 0.0070 memory: 10464 grad_norm: 6.9500 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3484 loss: 2.3484 2022/09/07 19:25:06 - mmengine - INFO - Epoch(train) [17][180/1793] lr: 7.5000e-03 eta: 7:22:03 time: 0.1771 data_time: 0.0080 memory: 10464 grad_norm: 7.5130 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5013 loss: 2.5013 2022/09/07 19:25:10 - mmengine - INFO - Epoch(train) [17][200/1793] lr: 7.5000e-03 eta: 7:21:44 time: 0.1909 data_time: 0.0067 memory: 10464 grad_norm: 6.9660 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1495 loss: 2.1495 2022/09/07 19:25:13 - mmengine - INFO - Epoch(train) [17][220/1793] lr: 7.5000e-03 eta: 7:21:24 time: 0.1754 data_time: 0.0056 memory: 10464 grad_norm: 7.3345 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1786 loss: 2.1786 2022/09/07 19:25:17 - mmengine - INFO - Epoch(train) [17][240/1793] lr: 7.5000e-03 eta: 7:21:06 time: 0.2058 data_time: 0.0085 memory: 10464 grad_norm: 7.5520 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2018 loss: 2.2018 2022/09/07 19:25:23 - mmengine - INFO - Epoch(train) [17][260/1793] lr: 7.5000e-03 eta: 7:20:50 time: 0.2535 data_time: 0.0106 memory: 10464 grad_norm: 6.9291 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5345 loss: 2.5345 2022/09/07 19:25:26 - mmengine - INFO - Epoch(train) [17][280/1793] lr: 7.5000e-03 eta: 7:20:30 time: 0.1771 data_time: 0.0092 memory: 10464 grad_norm: 7.3368 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0161 loss: 2.0161 2022/09/07 19:25:33 - mmengine - INFO - Epoch(train) [17][300/1793] lr: 7.5000e-03 eta: 7:20:17 time: 0.3214 data_time: 0.0099 memory: 10464 grad_norm: 6.9989 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0675 loss: 2.0675 2022/09/07 19:25:35 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:25:36 - mmengine - INFO - Epoch(train) [17][320/1793] lr: 7.5000e-03 eta: 7:19:57 time: 0.1733 data_time: 0.0070 memory: 10464 grad_norm: 7.1093 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1884 loss: 2.1884 2022/09/07 19:25:40 - mmengine - INFO - Epoch(train) [17][340/1793] lr: 7.5000e-03 eta: 7:19:37 time: 0.1783 data_time: 0.0057 memory: 10464 grad_norm: 6.8922 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2998 loss: 2.2998 2022/09/07 19:25:45 - mmengine - INFO - Epoch(train) [17][360/1793] lr: 7.5000e-03 eta: 7:19:21 time: 0.2578 data_time: 0.0093 memory: 10464 grad_norm: 6.9888 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1205 loss: 2.1205 2022/09/07 19:25:48 - mmengine - INFO - Epoch(train) [17][380/1793] lr: 7.5000e-03 eta: 7:19:02 time: 0.1857 data_time: 0.0065 memory: 10464 grad_norm: 7.1838 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.0537 loss: 2.0537 2022/09/07 19:25:53 - mmengine - INFO - Epoch(train) [17][400/1793] lr: 7.5000e-03 eta: 7:18:44 time: 0.2100 data_time: 0.0066 memory: 10464 grad_norm: 7.5150 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.5434 loss: 2.5434 2022/09/07 19:25:57 - mmengine - INFO - Epoch(train) [17][420/1793] lr: 7.5000e-03 eta: 7:18:27 time: 0.2390 data_time: 0.0079 memory: 10464 grad_norm: 6.9690 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2705 loss: 2.2705 2022/09/07 19:26:01 - mmengine - INFO - Epoch(train) [17][440/1793] lr: 7.5000e-03 eta: 7:18:08 time: 0.1867 data_time: 0.0072 memory: 10464 grad_norm: 7.0355 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7933 loss: 2.7933 2022/09/07 19:26:05 - mmengine - INFO - Epoch(train) [17][460/1793] lr: 7.5000e-03 eta: 7:17:50 time: 0.1973 data_time: 0.0066 memory: 10464 grad_norm: 6.7139 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3864 loss: 2.3864 2022/09/07 19:26:09 - mmengine - INFO - Epoch(train) [17][480/1793] lr: 7.5000e-03 eta: 7:17:31 time: 0.1831 data_time: 0.0097 memory: 10464 grad_norm: 7.0802 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.1510 loss: 2.1510 2022/09/07 19:26:12 - mmengine - INFO - Epoch(train) [17][500/1793] lr: 7.5000e-03 eta: 7:17:11 time: 0.1781 data_time: 0.0053 memory: 10464 grad_norm: 7.2837 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3741 loss: 2.3741 2022/09/07 19:26:18 - mmengine - INFO - Epoch(train) [17][520/1793] lr: 7.5000e-03 eta: 7:16:56 time: 0.2609 data_time: 0.0063 memory: 10464 grad_norm: 6.7643 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3102 loss: 2.3102 2022/09/07 19:26:21 - mmengine - INFO - Epoch(train) [17][540/1793] lr: 7.5000e-03 eta: 7:16:36 time: 0.1795 data_time: 0.0086 memory: 10464 grad_norm: 7.2533 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1792 loss: 2.1792 2022/09/07 19:26:25 - mmengine - INFO - Epoch(train) [17][560/1793] lr: 7.5000e-03 eta: 7:16:18 time: 0.1982 data_time: 0.0068 memory: 10464 grad_norm: 6.7862 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3916 loss: 2.3916 2022/09/07 19:26:29 - mmengine - INFO - Epoch(train) [17][580/1793] lr: 7.5000e-03 eta: 7:16:00 time: 0.2134 data_time: 0.0066 memory: 10464 grad_norm: 7.0880 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2773 loss: 2.2773 2022/09/07 19:26:34 - mmengine - INFO - Epoch(train) [17][600/1793] lr: 7.5000e-03 eta: 7:15:44 time: 0.2460 data_time: 0.0095 memory: 10464 grad_norm: 7.3714 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1519 loss: 2.1519 2022/09/07 19:26:38 - mmengine - INFO - Epoch(train) [17][620/1793] lr: 7.5000e-03 eta: 7:15:25 time: 0.1764 data_time: 0.0069 memory: 10464 grad_norm: 6.9796 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.9277 loss: 2.9277 2022/09/07 19:26:42 - mmengine - INFO - Epoch(train) [17][640/1793] lr: 7.5000e-03 eta: 7:15:07 time: 0.2015 data_time: 0.0070 memory: 10464 grad_norm: 7.1535 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3672 loss: 2.3672 2022/09/07 19:26:45 - mmengine - INFO - Epoch(train) [17][660/1793] lr: 7.5000e-03 eta: 7:14:47 time: 0.1796 data_time: 0.0092 memory: 10464 grad_norm: 7.0781 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4068 loss: 2.4068 2022/09/07 19:26:49 - mmengine - INFO - Epoch(train) [17][680/1793] lr: 7.5000e-03 eta: 7:14:28 time: 0.1737 data_time: 0.0058 memory: 10464 grad_norm: 6.9302 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 2.5237 loss: 2.5237 2022/09/07 19:26:54 - mmengine - INFO - Epoch(train) [17][700/1793] lr: 7.5000e-03 eta: 7:14:12 time: 0.2570 data_time: 0.0075 memory: 10464 grad_norm: 7.3338 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2843 loss: 2.2843 2022/09/07 19:26:58 - mmengine - INFO - Epoch(train) [17][720/1793] lr: 7.5000e-03 eta: 7:13:53 time: 0.1763 data_time: 0.0076 memory: 10464 grad_norm: 7.0880 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4678 loss: 2.4678 2022/09/07 19:27:01 - mmengine - INFO - Epoch(train) [17][740/1793] lr: 7.5000e-03 eta: 7:13:34 time: 0.1819 data_time: 0.0060 memory: 10464 grad_norm: 6.9629 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.9366 loss: 1.9366 2022/09/07 19:27:08 - mmengine - INFO - Epoch(train) [17][760/1793] lr: 7.5000e-03 eta: 7:13:22 time: 0.3492 data_time: 0.0076 memory: 10464 grad_norm: 7.1117 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.6109 loss: 2.6109 2022/09/07 19:27:13 - mmengine - INFO - Epoch(train) [17][780/1793] lr: 7.5000e-03 eta: 7:13:06 time: 0.2450 data_time: 0.0090 memory: 10464 grad_norm: 6.9988 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3248 loss: 2.3248 2022/09/07 19:27:17 - mmengine - INFO - Epoch(train) [17][800/1793] lr: 7.5000e-03 eta: 7:12:47 time: 0.1744 data_time: 0.0068 memory: 10464 grad_norm: 6.8695 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2679 loss: 2.2679 2022/09/07 19:27:20 - mmengine - INFO - Epoch(train) [17][820/1793] lr: 7.5000e-03 eta: 7:12:28 time: 0.1839 data_time: 0.0061 memory: 10464 grad_norm: 6.8933 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3991 loss: 2.3991 2022/09/07 19:27:25 - mmengine - INFO - Epoch(train) [17][840/1793] lr: 7.5000e-03 eta: 7:12:12 time: 0.2418 data_time: 0.0717 memory: 10464 grad_norm: 7.3702 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5881 loss: 2.5881 2022/09/07 19:27:29 - mmengine - INFO - Epoch(train) [17][860/1793] lr: 7.5000e-03 eta: 7:11:53 time: 0.1814 data_time: 0.0118 memory: 10464 grad_norm: 7.0314 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.1875 loss: 2.1875 2022/09/07 19:27:34 - mmengine - INFO - Epoch(train) [17][880/1793] lr: 7.5000e-03 eta: 7:11:38 time: 0.2715 data_time: 0.0054 memory: 10464 grad_norm: 6.9023 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9840 loss: 1.9840 2022/09/07 19:27:38 - mmengine - INFO - Epoch(train) [17][900/1793] lr: 7.5000e-03 eta: 7:11:20 time: 0.2089 data_time: 0.0091 memory: 10464 grad_norm: 6.9109 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.4907 loss: 2.4907 2022/09/07 19:27:42 - mmengine - INFO - Epoch(train) [17][920/1793] lr: 7.5000e-03 eta: 7:11:02 time: 0.2018 data_time: 0.0071 memory: 10464 grad_norm: 7.1885 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1663 loss: 2.1663 2022/09/07 19:27:46 - mmengine - INFO - Epoch(train) [17][940/1793] lr: 7.5000e-03 eta: 7:10:43 time: 0.1712 data_time: 0.0057 memory: 10464 grad_norm: 6.7833 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4658 loss: 2.4658 2022/09/07 19:27:51 - mmengine - INFO - Epoch(train) [17][960/1793] lr: 7.5000e-03 eta: 7:10:27 time: 0.2469 data_time: 0.0090 memory: 10464 grad_norm: 7.3465 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.3762 loss: 2.3762 2022/09/07 19:27:54 - mmengine - INFO - Epoch(train) [17][980/1793] lr: 7.5000e-03 eta: 7:10:08 time: 0.1773 data_time: 0.0069 memory: 10464 grad_norm: 6.9015 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.3132 loss: 2.3132 2022/09/07 19:27:58 - mmengine - INFO - Epoch(train) [17][1000/1793] lr: 7.5000e-03 eta: 7:09:49 time: 0.1751 data_time: 0.0062 memory: 10464 grad_norm: 7.0659 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 2.3701 loss: 2.3701 2022/09/07 19:28:03 - mmengine - INFO - Epoch(train) [17][1020/1793] lr: 7.5000e-03 eta: 7:09:33 time: 0.2455 data_time: 0.0084 memory: 10464 grad_norm: 7.0650 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3648 loss: 2.3648 2022/09/07 19:28:06 - mmengine - INFO - Epoch(train) [17][1040/1793] lr: 7.5000e-03 eta: 7:09:14 time: 0.1751 data_time: 0.0059 memory: 10464 grad_norm: 7.4701 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3652 loss: 2.3652 2022/09/07 19:28:10 - mmengine - INFO - Epoch(train) [17][1060/1793] lr: 7.5000e-03 eta: 7:08:56 time: 0.1720 data_time: 0.0065 memory: 10464 grad_norm: 6.8705 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3587 loss: 2.3587 2022/09/07 19:28:13 - mmengine - INFO - Epoch(train) [17][1080/1793] lr: 7.5000e-03 eta: 7:08:37 time: 0.1825 data_time: 0.0086 memory: 10464 grad_norm: 7.3788 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3988 loss: 2.3988 2022/09/07 19:28:18 - mmengine - INFO - Epoch(train) [17][1100/1793] lr: 7.5000e-03 eta: 7:08:21 time: 0.2430 data_time: 0.0064 memory: 10464 grad_norm: 7.2177 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1016 loss: 2.1016 2022/09/07 19:28:23 - mmengine - INFO - Epoch(train) [17][1120/1793] lr: 7.5000e-03 eta: 7:08:05 time: 0.2578 data_time: 0.0070 memory: 10464 grad_norm: 7.2402 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3104 loss: 2.3104 2022/09/07 19:28:27 - mmengine - INFO - Epoch(train) [17][1140/1793] lr: 7.5000e-03 eta: 7:07:47 time: 0.1778 data_time: 0.0089 memory: 10464 grad_norm: 7.1396 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.4155 loss: 2.4155 2022/09/07 19:28:34 - mmengine - INFO - Epoch(train) [17][1160/1793] lr: 7.5000e-03 eta: 7:07:35 time: 0.3535 data_time: 0.1823 memory: 10464 grad_norm: 7.0393 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.3134 loss: 2.3134 2022/09/07 19:28:38 - mmengine - INFO - Epoch(train) [17][1180/1793] lr: 7.5000e-03 eta: 7:07:18 time: 0.2062 data_time: 0.0370 memory: 10464 grad_norm: 7.1335 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1296 loss: 2.1296 2022/09/07 19:28:42 - mmengine - INFO - Epoch(train) [17][1200/1793] lr: 7.5000e-03 eta: 7:07:00 time: 0.1960 data_time: 0.0067 memory: 10464 grad_norm: 7.2031 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.3033 loss: 2.3033 2022/09/07 19:28:46 - mmengine - INFO - Epoch(train) [17][1220/1793] lr: 7.5000e-03 eta: 7:06:41 time: 0.1733 data_time: 0.0060 memory: 10464 grad_norm: 7.2160 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4361 loss: 2.4361 2022/09/07 19:28:49 - mmengine - INFO - Epoch(train) [17][1240/1793] lr: 7.5000e-03 eta: 7:06:22 time: 0.1752 data_time: 0.0095 memory: 10464 grad_norm: 7.0061 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1111 loss: 2.1111 2022/09/07 19:28:53 - mmengine - INFO - Epoch(train) [17][1260/1793] lr: 7.5000e-03 eta: 7:06:04 time: 0.1748 data_time: 0.0057 memory: 10464 grad_norm: 7.1233 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6382 loss: 2.6382 2022/09/07 19:28:57 - mmengine - INFO - Epoch(train) [17][1280/1793] lr: 7.5000e-03 eta: 7:05:46 time: 0.2107 data_time: 0.0079 memory: 10464 grad_norm: 6.8934 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3920 loss: 2.3920 2022/09/07 19:29:01 - mmengine - INFO - Epoch(train) [17][1300/1793] lr: 7.5000e-03 eta: 7:05:30 time: 0.2195 data_time: 0.0080 memory: 10464 grad_norm: 6.8021 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2888 loss: 2.2888 2022/09/07 19:29:05 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:29:06 - mmengine - INFO - Epoch(train) [17][1320/1793] lr: 7.5000e-03 eta: 7:05:13 time: 0.2370 data_time: 0.0066 memory: 10464 grad_norm: 6.8904 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1949 loss: 2.1949 2022/09/07 19:29:11 - mmengine - INFO - Epoch(train) [17][1340/1793] lr: 7.5000e-03 eta: 7:04:58 time: 0.2562 data_time: 0.0063 memory: 10464 grad_norm: 7.2737 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1608 loss: 2.1608 2022/09/07 19:29:15 - mmengine - INFO - Epoch(train) [17][1360/1793] lr: 7.5000e-03 eta: 7:04:40 time: 0.1785 data_time: 0.0093 memory: 10464 grad_norm: 7.0513 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.9440 loss: 1.9440 2022/09/07 19:29:20 - mmengine - INFO - Epoch(train) [17][1380/1793] lr: 7.5000e-03 eta: 7:04:24 time: 0.2489 data_time: 0.0054 memory: 10464 grad_norm: 7.0529 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2103 loss: 2.2103 2022/09/07 19:29:23 - mmengine - INFO - Epoch(train) [17][1400/1793] lr: 7.5000e-03 eta: 7:04:06 time: 0.1854 data_time: 0.0071 memory: 10464 grad_norm: 7.4251 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4427 loss: 2.4427 2022/09/07 19:29:29 - mmengine - INFO - Epoch(train) [17][1420/1793] lr: 7.5000e-03 eta: 7:03:52 time: 0.2846 data_time: 0.0087 memory: 10464 grad_norm: 7.2919 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3060 loss: 2.3060 2022/09/07 19:29:35 - mmengine - INFO - Epoch(train) [17][1440/1793] lr: 7.5000e-03 eta: 7:03:38 time: 0.3087 data_time: 0.0062 memory: 10464 grad_norm: 6.9920 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.4843 loss: 2.4843 2022/09/07 19:29:39 - mmengine - INFO - Epoch(train) [17][1460/1793] lr: 7.5000e-03 eta: 7:03:20 time: 0.1843 data_time: 0.0097 memory: 10464 grad_norm: 7.1800 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.1436 loss: 2.1436 2022/09/07 19:29:42 - mmengine - INFO - Epoch(train) [17][1480/1793] lr: 7.5000e-03 eta: 7:03:02 time: 0.1728 data_time: 0.0057 memory: 10464 grad_norm: 7.1849 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2710 loss: 2.2710 2022/09/07 19:29:46 - mmengine - INFO - Epoch(train) [17][1500/1793] lr: 7.5000e-03 eta: 7:02:43 time: 0.1737 data_time: 0.0065 memory: 10464 grad_norm: 7.1437 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2953 loss: 2.2953 2022/09/07 19:29:50 - mmengine - INFO - Epoch(train) [17][1520/1793] lr: 7.5000e-03 eta: 7:02:25 time: 0.1884 data_time: 0.0095 memory: 10464 grad_norm: 7.1173 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4735 loss: 2.4735 2022/09/07 19:29:53 - mmengine - INFO - Epoch(train) [17][1540/1793] lr: 7.5000e-03 eta: 7:02:07 time: 0.1728 data_time: 0.0073 memory: 10464 grad_norm: 6.8405 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 2.3342 loss: 2.3342 2022/09/07 19:29:56 - mmengine - INFO - Epoch(train) [17][1560/1793] lr: 7.5000e-03 eta: 7:01:48 time: 0.1723 data_time: 0.0067 memory: 10464 grad_norm: 6.7428 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.4514 loss: 2.4514 2022/09/07 19:30:00 - mmengine - INFO - Epoch(train) [17][1580/1793] lr: 7.5000e-03 eta: 7:01:30 time: 0.1738 data_time: 0.0091 memory: 10464 grad_norm: 6.9529 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2402 loss: 2.2402 2022/09/07 19:30:03 - mmengine - INFO - Epoch(train) [17][1600/1793] lr: 7.5000e-03 eta: 7:01:11 time: 0.1729 data_time: 0.0061 memory: 10464 grad_norm: 6.9079 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0853 loss: 2.0853 2022/09/07 19:30:07 - mmengine - INFO - Epoch(train) [17][1620/1793] lr: 7.5000e-03 eta: 7:00:53 time: 0.1750 data_time: 0.0066 memory: 10464 grad_norm: 6.9256 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.2086 loss: 2.2086 2022/09/07 19:30:11 - mmengine - INFO - Epoch(train) [17][1640/1793] lr: 7.5000e-03 eta: 7:00:36 time: 0.1932 data_time: 0.0091 memory: 10464 grad_norm: 7.2453 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.3903 loss: 2.3903 2022/09/07 19:30:14 - mmengine - INFO - Epoch(train) [17][1660/1793] lr: 7.5000e-03 eta: 7:00:17 time: 0.1728 data_time: 0.0064 memory: 10464 grad_norm: 7.4510 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.5782 loss: 2.5782 2022/09/07 19:30:18 - mmengine - INFO - Epoch(train) [17][1680/1793] lr: 7.5000e-03 eta: 6:59:59 time: 0.1719 data_time: 0.0066 memory: 10464 grad_norm: 6.8693 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2999 loss: 2.2999 2022/09/07 19:30:21 - mmengine - INFO - Epoch(train) [17][1700/1793] lr: 7.5000e-03 eta: 6:59:41 time: 0.1827 data_time: 0.0084 memory: 10464 grad_norm: 6.7883 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0816 loss: 2.0816 2022/09/07 19:30:25 - mmengine - INFO - Epoch(train) [17][1720/1793] lr: 7.5000e-03 eta: 6:59:22 time: 0.1726 data_time: 0.0063 memory: 10464 grad_norm: 6.9405 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2760 loss: 2.2760 2022/09/07 19:30:28 - mmengine - INFO - Epoch(train) [17][1740/1793] lr: 7.5000e-03 eta: 6:59:04 time: 0.1706 data_time: 0.0071 memory: 10464 grad_norm: 7.0607 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1431 loss: 2.1431 2022/09/07 19:30:32 - mmengine - INFO - Epoch(train) [17][1760/1793] lr: 7.5000e-03 eta: 6:58:46 time: 0.1768 data_time: 0.0088 memory: 10464 grad_norm: 7.2085 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1828 loss: 2.1828 2022/09/07 19:30:36 - mmengine - INFO - Epoch(train) [17][1780/1793] lr: 7.5000e-03 eta: 6:58:30 time: 0.2228 data_time: 0.0527 memory: 10464 grad_norm: 7.0286 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.7084 loss: 2.7084 2022/09/07 19:30:39 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:30:39 - mmengine - INFO - Epoch(train) [17][1793/1793] lr: 7.5000e-03 eta: 6:58:30 time: 0.1802 data_time: 0.0055 memory: 10464 grad_norm: 8.1756 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.6469 loss: 2.6469 2022/09/07 19:30:39 - mmengine - INFO - Saving checkpoint at 17 epochs 2022/09/07 19:30:43 - mmengine - INFO - Epoch(val) [17][20/241] eta: 0:00:13 time: 0.0591 data_time: 0.0095 memory: 1482 2022/09/07 19:30:44 - mmengine - INFO - Epoch(val) [17][40/241] eta: 0:00:10 time: 0.0536 data_time: 0.0050 memory: 1482 2022/09/07 19:30:45 - mmengine - INFO - Epoch(val) [17][60/241] eta: 0:00:09 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 19:30:46 - mmengine - INFO - Epoch(val) [17][80/241] eta: 0:00:08 time: 0.0531 data_time: 0.0048 memory: 1482 2022/09/07 19:30:47 - mmengine - INFO - Epoch(val) [17][100/241] eta: 0:00:07 time: 0.0534 data_time: 0.0051 memory: 1482 2022/09/07 19:30:48 - mmengine - INFO - Epoch(val) [17][120/241] eta: 0:00:06 time: 0.0535 data_time: 0.0049 memory: 1482 2022/09/07 19:30:49 - mmengine - INFO - Epoch(val) [17][140/241] eta: 0:00:05 time: 0.0537 data_time: 0.0051 memory: 1482 2022/09/07 19:30:50 - mmengine - INFO - Epoch(val) [17][160/241] eta: 0:00:04 time: 0.0533 data_time: 0.0050 memory: 1482 2022/09/07 19:30:51 - mmengine - INFO - Epoch(val) [17][180/241] eta: 0:00:03 time: 0.0530 data_time: 0.0048 memory: 1482 2022/09/07 19:30:52 - mmengine - INFO - Epoch(val) [17][200/241] eta: 0:00:02 time: 0.0598 data_time: 0.0064 memory: 1482 2022/09/07 19:30:53 - mmengine - INFO - Epoch(val) [17][220/241] eta: 0:00:01 time: 0.0530 data_time: 0.0049 memory: 1482 2022/09/07 19:30:54 - mmengine - INFO - Epoch(val) [17][240/241] eta: 0:00:00 time: 0.0523 data_time: 0.0045 memory: 1482 2022/09/07 19:30:55 - mmengine - INFO - Epoch(val) [17][241/241] acc/top1: 0.3270 acc/top5: 0.6246 acc/mean1: 0.2948 2022/09/07 19:30:55 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_16.pth is removed 2022/09/07 19:30:56 - mmengine - INFO - The best checkpoint with 0.3270 acc/top1 at 17 epoch is saved to best_acc/top1_epoch_17.pth. 2022/09/07 19:31:01 - mmengine - INFO - Epoch(train) [18][20/1793] lr: 7.5000e-03 eta: 6:57:58 time: 0.2447 data_time: 0.0101 memory: 10464 grad_norm: 6.9601 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0848 loss: 2.0848 2022/09/07 19:31:05 - mmengine - INFO - Epoch(train) [18][40/1793] lr: 7.5000e-03 eta: 6:57:40 time: 0.1907 data_time: 0.0075 memory: 10464 grad_norm: 7.1891 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.1219 loss: 2.1219 2022/09/07 19:31:11 - mmengine - INFO - Epoch(train) [18][60/1793] lr: 7.5000e-03 eta: 6:57:27 time: 0.2868 data_time: 0.0074 memory: 10464 grad_norm: 7.0281 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1019 loss: 2.1019 2022/09/07 19:31:16 - mmengine - INFO - Epoch(train) [18][80/1793] lr: 7.5000e-03 eta: 6:57:13 time: 0.2774 data_time: 0.0065 memory: 10464 grad_norm: 6.8286 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1590 loss: 2.1590 2022/09/07 19:31:20 - mmengine - INFO - Epoch(train) [18][100/1793] lr: 7.5000e-03 eta: 6:56:54 time: 0.1741 data_time: 0.0078 memory: 10464 grad_norm: 7.2271 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.2168 loss: 2.2168 2022/09/07 19:31:25 - mmengine - INFO - Epoch(train) [18][120/1793] lr: 7.5000e-03 eta: 6:56:39 time: 0.2464 data_time: 0.0073 memory: 10464 grad_norm: 6.8029 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3176 loss: 2.3176 2022/09/07 19:31:28 - mmengine - INFO - Epoch(train) [18][140/1793] lr: 7.5000e-03 eta: 6:56:21 time: 0.1754 data_time: 0.0070 memory: 10464 grad_norm: 6.9008 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2623 loss: 2.2623 2022/09/07 19:31:32 - mmengine - INFO - Epoch(train) [18][160/1793] lr: 7.5000e-03 eta: 6:56:03 time: 0.1803 data_time: 0.0079 memory: 10464 grad_norm: 7.3015 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.2920 loss: 2.2920 2022/09/07 19:31:36 - mmengine - INFO - Epoch(train) [18][180/1793] lr: 7.5000e-03 eta: 6:55:45 time: 0.1761 data_time: 0.0055 memory: 10464 grad_norm: 6.8854 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.0303 loss: 2.0303 2022/09/07 19:31:39 - mmengine - INFO - Epoch(train) [18][200/1793] lr: 7.5000e-03 eta: 6:55:27 time: 0.1744 data_time: 0.0070 memory: 10464 grad_norm: 6.9445 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.9309 loss: 1.9309 2022/09/07 19:31:44 - mmengine - INFO - Epoch(train) [18][220/1793] lr: 7.5000e-03 eta: 6:55:12 time: 0.2409 data_time: 0.0084 memory: 10464 grad_norm: 6.9820 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4858 loss: 2.4858 2022/09/07 19:31:47 - mmengine - INFO - Epoch(train) [18][240/1793] lr: 7.5000e-03 eta: 6:54:54 time: 0.1736 data_time: 0.0062 memory: 10464 grad_norm: 6.6679 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3094 loss: 2.3094 2022/09/07 19:31:51 - mmengine - INFO - Epoch(train) [18][260/1793] lr: 7.5000e-03 eta: 6:54:36 time: 0.1774 data_time: 0.0069 memory: 10464 grad_norm: 7.2483 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.0906 loss: 2.0906 2022/09/07 19:31:56 - mmengine - INFO - Epoch(train) [18][280/1793] lr: 7.5000e-03 eta: 6:54:21 time: 0.2625 data_time: 0.0084 memory: 10464 grad_norm: 7.4220 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 2.3581 loss: 2.3581 2022/09/07 19:32:00 - mmengine - INFO - Epoch(train) [18][300/1793] lr: 7.5000e-03 eta: 6:54:04 time: 0.1764 data_time: 0.0060 memory: 10464 grad_norm: 6.7839 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.1089 loss: 2.1089 2022/09/07 19:32:03 - mmengine - INFO - Epoch(train) [18][320/1793] lr: 7.5000e-03 eta: 6:53:46 time: 0.1841 data_time: 0.0076 memory: 10464 grad_norm: 6.9500 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2344 loss: 2.2344 2022/09/07 19:32:07 - mmengine - INFO - Epoch(train) [18][340/1793] lr: 7.5000e-03 eta: 6:53:28 time: 0.1810 data_time: 0.0098 memory: 10464 grad_norm: 7.3039 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0907 loss: 2.0907 2022/09/07 19:32:10 - mmengine - INFO - Epoch(train) [18][360/1793] lr: 7.5000e-03 eta: 6:53:11 time: 0.1739 data_time: 0.0053 memory: 10464 grad_norm: 6.9965 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4156 loss: 2.4156 2022/09/07 19:32:14 - mmengine - INFO - Epoch(train) [18][380/1793] lr: 7.5000e-03 eta: 6:52:53 time: 0.1760 data_time: 0.0064 memory: 10464 grad_norm: 6.9087 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6628 loss: 2.6628 2022/09/07 19:32:17 - mmengine - INFO - Epoch(train) [18][400/1793] lr: 7.5000e-03 eta: 6:52:35 time: 0.1770 data_time: 0.0084 memory: 10464 grad_norm: 7.1134 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1123 loss: 2.1123 2022/09/07 19:32:25 - mmengine - INFO - Epoch(train) [18][420/1793] lr: 7.5000e-03 eta: 6:52:26 time: 0.3930 data_time: 0.0065 memory: 10464 grad_norm: 7.1016 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.0612 loss: 2.0612 2022/09/07 19:32:29 - mmengine - INFO - Epoch(train) [18][440/1793] lr: 7.5000e-03 eta: 6:52:08 time: 0.1780 data_time: 0.0095 memory: 10464 grad_norm: 7.2039 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8897 loss: 1.8897 2022/09/07 19:32:32 - mmengine - INFO - Epoch(train) [18][460/1793] lr: 7.5000e-03 eta: 6:51:50 time: 0.1755 data_time: 0.0065 memory: 10464 grad_norm: 7.1286 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.5782 loss: 2.5782 2022/09/07 19:32:37 - mmengine - INFO - Epoch(train) [18][480/1793] lr: 7.5000e-03 eta: 6:51:35 time: 0.2435 data_time: 0.0497 memory: 10464 grad_norm: 6.9984 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3305 loss: 2.3305 2022/09/07 19:32:41 - mmengine - INFO - Epoch(train) [18][500/1793] lr: 7.5000e-03 eta: 6:51:18 time: 0.2006 data_time: 0.0075 memory: 10464 grad_norm: 7.3471 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2195 loss: 2.2195 2022/09/07 19:32:45 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:32:45 - mmengine - INFO - Epoch(train) [18][520/1793] lr: 7.5000e-03 eta: 6:51:01 time: 0.1816 data_time: 0.0071 memory: 10464 grad_norm: 7.2261 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.7015 loss: 2.7015 2022/09/07 19:32:49 - mmengine - INFO - Epoch(train) [18][540/1793] lr: 7.5000e-03 eta: 6:50:44 time: 0.2037 data_time: 0.0349 memory: 10464 grad_norm: 7.1047 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2888 loss: 2.2888 2022/09/07 19:32:53 - mmengine - INFO - Epoch(train) [18][560/1793] lr: 7.5000e-03 eta: 6:50:27 time: 0.1799 data_time: 0.0076 memory: 10464 grad_norm: 7.3591 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4917 loss: 2.4917 2022/09/07 19:32:57 - mmengine - INFO - Epoch(train) [18][580/1793] lr: 7.5000e-03 eta: 6:50:11 time: 0.2385 data_time: 0.0056 memory: 10464 grad_norm: 7.3210 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2449 loss: 2.2449 2022/09/07 19:33:01 - mmengine - INFO - Epoch(train) [18][600/1793] lr: 7.5000e-03 eta: 6:49:55 time: 0.1987 data_time: 0.0063 memory: 10464 grad_norm: 7.0234 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7263 loss: 2.7263 2022/09/07 19:33:05 - mmengine - INFO - Epoch(train) [18][620/1793] lr: 7.5000e-03 eta: 6:49:37 time: 0.1784 data_time: 0.0094 memory: 10464 grad_norm: 7.0286 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.1375 loss: 2.1375 2022/09/07 19:33:08 - mmengine - INFO - Epoch(train) [18][640/1793] lr: 7.5000e-03 eta: 6:49:20 time: 0.1733 data_time: 0.0064 memory: 10464 grad_norm: 7.2612 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2472 loss: 2.2472 2022/09/07 19:33:12 - mmengine - INFO - Epoch(train) [18][660/1793] lr: 7.5000e-03 eta: 6:49:02 time: 0.1785 data_time: 0.0070 memory: 10464 grad_norm: 7.1870 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5281 loss: 2.5281 2022/09/07 19:33:16 - mmengine - INFO - Epoch(train) [18][680/1793] lr: 7.5000e-03 eta: 6:48:45 time: 0.1794 data_time: 0.0093 memory: 10464 grad_norm: 7.1059 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4619 loss: 2.4619 2022/09/07 19:33:20 - mmengine - INFO - Epoch(train) [18][700/1793] lr: 7.5000e-03 eta: 6:48:28 time: 0.2012 data_time: 0.0049 memory: 10464 grad_norm: 7.2076 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.1202 loss: 2.1202 2022/09/07 19:33:23 - mmengine - INFO - Epoch(train) [18][720/1793] lr: 7.5000e-03 eta: 6:48:11 time: 0.1786 data_time: 0.0068 memory: 10464 grad_norm: 7.1242 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4894 loss: 2.4894 2022/09/07 19:33:27 - mmengine - INFO - Epoch(train) [18][740/1793] lr: 7.5000e-03 eta: 6:47:53 time: 0.1764 data_time: 0.0093 memory: 10464 grad_norm: 6.8416 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3340 loss: 2.3340 2022/09/07 19:33:30 - mmengine - INFO - Epoch(train) [18][760/1793] lr: 7.5000e-03 eta: 6:47:36 time: 0.1819 data_time: 0.0057 memory: 10464 grad_norm: 7.0230 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.0919 loss: 2.0919 2022/09/07 19:33:35 - mmengine - INFO - Epoch(train) [18][780/1793] lr: 7.5000e-03 eta: 6:47:20 time: 0.2142 data_time: 0.0069 memory: 10464 grad_norm: 6.7950 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3068 loss: 2.3068 2022/09/07 19:33:38 - mmengine - INFO - Epoch(train) [18][800/1793] lr: 7.5000e-03 eta: 6:47:03 time: 0.1774 data_time: 0.0093 memory: 10464 grad_norm: 7.3546 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0962 loss: 2.0962 2022/09/07 19:33:42 - mmengine - INFO - Epoch(train) [18][820/1793] lr: 7.5000e-03 eta: 6:46:45 time: 0.1787 data_time: 0.0071 memory: 10464 grad_norm: 7.0439 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.2008 loss: 2.2008 2022/09/07 19:33:48 - mmengine - INFO - Epoch(train) [18][840/1793] lr: 7.5000e-03 eta: 6:46:32 time: 0.2940 data_time: 0.0056 memory: 10464 grad_norm: 7.0024 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.1895 loss: 2.1895 2022/09/07 19:33:53 - mmengine - INFO - Epoch(train) [18][860/1793] lr: 7.5000e-03 eta: 6:46:19 time: 0.2802 data_time: 0.1003 memory: 10464 grad_norm: 7.0455 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4909 loss: 2.4909 2022/09/07 19:33:57 - mmengine - INFO - Epoch(train) [18][880/1793] lr: 7.5000e-03 eta: 6:46:01 time: 0.1725 data_time: 0.0051 memory: 10464 grad_norm: 7.2449 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4205 loss: 2.4205 2022/09/07 19:34:02 - mmengine - INFO - Epoch(train) [18][900/1793] lr: 7.5000e-03 eta: 6:45:47 time: 0.2638 data_time: 0.0727 memory: 10464 grad_norm: 6.9890 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2664 loss: 2.2664 2022/09/07 19:34:06 - mmengine - INFO - Epoch(train) [18][920/1793] lr: 7.5000e-03 eta: 6:45:31 time: 0.1976 data_time: 0.0094 memory: 10464 grad_norm: 7.3293 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4766 loss: 2.4766 2022/09/07 19:34:09 - mmengine - INFO - Epoch(train) [18][940/1793] lr: 7.5000e-03 eta: 6:45:13 time: 0.1727 data_time: 0.0068 memory: 10464 grad_norm: 7.4450 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.1067 loss: 2.1067 2022/09/07 19:34:13 - mmengine - INFO - Epoch(train) [18][960/1793] lr: 7.5000e-03 eta: 6:44:56 time: 0.1779 data_time: 0.0056 memory: 10464 grad_norm: 7.1226 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3307 loss: 2.3307 2022/09/07 19:34:17 - mmengine - INFO - Epoch(train) [18][980/1793] lr: 7.5000e-03 eta: 6:44:39 time: 0.1773 data_time: 0.0089 memory: 10464 grad_norm: 7.1812 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1966 loss: 2.1966 2022/09/07 19:34:20 - mmengine - INFO - Epoch(train) [18][1000/1793] lr: 7.5000e-03 eta: 6:44:22 time: 0.1769 data_time: 0.0059 memory: 10464 grad_norm: 7.0627 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1690 loss: 2.1690 2022/09/07 19:34:25 - mmengine - INFO - Epoch(train) [18][1020/1793] lr: 7.5000e-03 eta: 6:44:07 time: 0.2467 data_time: 0.0065 memory: 10464 grad_norm: 7.0218 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.5860 loss: 2.5860 2022/09/07 19:34:29 - mmengine - INFO - Epoch(train) [18][1040/1793] lr: 7.5000e-03 eta: 6:43:51 time: 0.1971 data_time: 0.0266 memory: 10464 grad_norm: 6.9218 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.5782 loss: 2.5782 2022/09/07 19:34:33 - mmengine - INFO - Epoch(train) [18][1060/1793] lr: 7.5000e-03 eta: 6:43:34 time: 0.1935 data_time: 0.0214 memory: 10464 grad_norm: 7.2644 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.5198 loss: 2.5198 2022/09/07 19:34:40 - mmengine - INFO - Epoch(train) [18][1080/1793] lr: 7.5000e-03 eta: 6:43:24 time: 0.3599 data_time: 0.0052 memory: 10464 grad_norm: 7.9525 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.1579 loss: 2.1579 2022/09/07 19:34:44 - mmengine - INFO - Epoch(train) [18][1100/1793] lr: 7.5000e-03 eta: 6:43:06 time: 0.1753 data_time: 0.0084 memory: 10464 grad_norm: 7.5006 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1269 loss: 2.1269 2022/09/07 19:34:49 - mmengine - INFO - Epoch(train) [18][1120/1793] lr: 7.5000e-03 eta: 6:42:53 time: 0.2709 data_time: 0.0354 memory: 10464 grad_norm: 6.9990 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4165 loss: 2.4165 2022/09/07 19:34:52 - mmengine - INFO - Epoch(train) [18][1140/1793] lr: 7.5000e-03 eta: 6:42:35 time: 0.1755 data_time: 0.0062 memory: 10464 grad_norm: 7.0154 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3066 loss: 2.3066 2022/09/07 19:34:56 - mmengine - INFO - Epoch(train) [18][1160/1793] lr: 7.5000e-03 eta: 6:42:18 time: 0.1784 data_time: 0.0088 memory: 10464 grad_norm: 7.0215 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.0978 loss: 2.0978 2022/09/07 19:35:00 - mmengine - INFO - Epoch(train) [18][1180/1793] lr: 7.5000e-03 eta: 6:42:01 time: 0.1761 data_time: 0.0058 memory: 10464 grad_norm: 7.4925 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3981 loss: 2.3981 2022/09/07 19:35:03 - mmengine - INFO - Epoch(train) [18][1200/1793] lr: 7.5000e-03 eta: 6:41:44 time: 0.1811 data_time: 0.0059 memory: 10464 grad_norm: 6.9880 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3964 loss: 2.3964 2022/09/07 19:35:08 - mmengine - INFO - Epoch(train) [18][1220/1793] lr: 7.5000e-03 eta: 6:41:30 time: 0.2372 data_time: 0.0088 memory: 10464 grad_norm: 6.9518 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 2.1835 loss: 2.1835 2022/09/07 19:35:11 - mmengine - INFO - Epoch(train) [18][1240/1793] lr: 7.5000e-03 eta: 6:41:13 time: 0.1792 data_time: 0.0067 memory: 10464 grad_norm: 7.1942 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6876 loss: 2.6876 2022/09/07 19:35:16 - mmengine - INFO - Epoch(train) [18][1260/1793] lr: 7.5000e-03 eta: 6:40:58 time: 0.2459 data_time: 0.0738 memory: 10464 grad_norm: 6.9099 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2847 loss: 2.2847 2022/09/07 19:35:20 - mmengine - INFO - Epoch(train) [18][1280/1793] lr: 7.5000e-03 eta: 6:40:41 time: 0.1750 data_time: 0.0085 memory: 10464 grad_norm: 7.3717 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3066 loss: 2.3066 2022/09/07 19:35:24 - mmengine - INFO - Epoch(train) [18][1300/1793] lr: 7.5000e-03 eta: 6:40:26 time: 0.2260 data_time: 0.0073 memory: 10464 grad_norm: 6.8799 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4376 loss: 2.4376 2022/09/07 19:35:28 - mmengine - INFO - Epoch(train) [18][1320/1793] lr: 7.5000e-03 eta: 6:40:09 time: 0.1738 data_time: 0.0068 memory: 10464 grad_norm: 7.0528 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.6455 loss: 2.6455 2022/09/07 19:35:32 - mmengine - INFO - Epoch(train) [18][1340/1793] lr: 7.5000e-03 eta: 6:39:53 time: 0.1969 data_time: 0.0083 memory: 10464 grad_norm: 7.0690 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.1692 loss: 2.1692 2022/09/07 19:35:36 - mmengine - INFO - Epoch(train) [18][1360/1793] lr: 7.5000e-03 eta: 6:39:37 time: 0.2233 data_time: 0.0544 memory: 10464 grad_norm: 7.4016 top1_acc: 0.1667 top5_acc: 1.0000 loss_cls: 2.4758 loss: 2.4758 2022/09/07 19:35:43 - mmengine - INFO - Epoch(train) [18][1380/1793] lr: 7.5000e-03 eta: 6:39:25 time: 0.3142 data_time: 0.0061 memory: 10464 grad_norm: 7.2555 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2526 loss: 2.2526 2022/09/07 19:35:47 - mmengine - INFO - Epoch(train) [18][1400/1793] lr: 7.5000e-03 eta: 6:39:11 time: 0.2383 data_time: 0.0096 memory: 10464 grad_norm: 7.2666 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1105 loss: 2.1105 2022/09/07 19:35:53 - mmengine - INFO - Epoch(train) [18][1420/1793] lr: 7.5000e-03 eta: 6:38:57 time: 0.2597 data_time: 0.0065 memory: 10464 grad_norm: 6.8962 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.8880 loss: 1.8880 2022/09/07 19:35:56 - mmengine - INFO - Epoch(train) [18][1440/1793] lr: 7.5000e-03 eta: 6:38:40 time: 0.1736 data_time: 0.0068 memory: 10464 grad_norm: 7.0689 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2681 loss: 2.2681 2022/09/07 19:36:00 - mmengine - INFO - Epoch(train) [18][1460/1793] lr: 7.5000e-03 eta: 6:38:23 time: 0.1762 data_time: 0.0084 memory: 10464 grad_norm: 6.7433 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.2690 loss: 2.2690 2022/09/07 19:36:04 - mmengine - INFO - Epoch(train) [18][1480/1793] lr: 7.5000e-03 eta: 6:38:07 time: 0.1970 data_time: 0.0068 memory: 10464 grad_norm: 6.9152 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.6645 loss: 2.6645 2022/09/07 19:36:07 - mmengine - INFO - Epoch(train) [18][1500/1793] lr: 7.5000e-03 eta: 6:37:50 time: 0.1747 data_time: 0.0065 memory: 10464 grad_norm: 7.2121 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3717 loss: 2.3717 2022/09/07 19:36:12 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:36:12 - mmengine - INFO - Epoch(train) [18][1520/1793] lr: 7.5000e-03 eta: 6:37:36 time: 0.2587 data_time: 0.0087 memory: 10464 grad_norm: 7.0547 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4633 loss: 2.4633 2022/09/07 19:36:16 - mmengine - INFO - Epoch(train) [18][1540/1793] lr: 7.5000e-03 eta: 6:37:19 time: 0.1840 data_time: 0.0062 memory: 10464 grad_norm: 7.1250 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2594 loss: 2.2594 2022/09/07 19:36:19 - mmengine - INFO - Epoch(train) [18][1560/1793] lr: 7.5000e-03 eta: 6:37:02 time: 0.1738 data_time: 0.0058 memory: 10464 grad_norm: 7.2019 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.0322 loss: 2.0322 2022/09/07 19:36:24 - mmengine - INFO - Epoch(train) [18][1580/1793] lr: 7.5000e-03 eta: 6:36:48 time: 0.2530 data_time: 0.0088 memory: 10464 grad_norm: 7.4100 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1233 loss: 2.1233 2022/09/07 19:36:28 - mmengine - INFO - Epoch(train) [18][1600/1793] lr: 7.5000e-03 eta: 6:36:32 time: 0.1958 data_time: 0.0067 memory: 10464 grad_norm: 7.1173 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.0407 loss: 2.0407 2022/09/07 19:36:32 - mmengine - INFO - Epoch(train) [18][1620/1793] lr: 7.5000e-03 eta: 6:36:16 time: 0.1767 data_time: 0.0056 memory: 10464 grad_norm: 7.0440 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1659 loss: 2.1659 2022/09/07 19:36:35 - mmengine - INFO - Epoch(train) [18][1640/1793] lr: 7.5000e-03 eta: 6:35:59 time: 0.1798 data_time: 0.0100 memory: 10464 grad_norm: 7.0309 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.5025 loss: 2.5025 2022/09/07 19:36:39 - mmengine - INFO - Epoch(train) [18][1660/1793] lr: 7.5000e-03 eta: 6:35:42 time: 0.1760 data_time: 0.0066 memory: 10464 grad_norm: 6.7175 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3872 loss: 2.3872 2022/09/07 19:36:43 - mmengine - INFO - Epoch(train) [18][1680/1793] lr: 7.5000e-03 eta: 6:35:27 time: 0.2077 data_time: 0.0063 memory: 10464 grad_norm: 7.4809 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1726 loss: 2.1726 2022/09/07 19:36:47 - mmengine - INFO - Epoch(train) [18][1700/1793] lr: 7.5000e-03 eta: 6:35:10 time: 0.1791 data_time: 0.0104 memory: 10464 grad_norm: 7.2511 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6311 loss: 2.6311 2022/09/07 19:36:52 - mmengine - INFO - Epoch(train) [18][1720/1793] lr: 7.5000e-03 eta: 6:34:56 time: 0.2434 data_time: 0.0062 memory: 10464 grad_norm: 7.1448 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3520 loss: 2.3520 2022/09/07 19:36:55 - mmengine - INFO - Epoch(train) [18][1740/1793] lr: 7.5000e-03 eta: 6:34:39 time: 0.1827 data_time: 0.0057 memory: 10464 grad_norm: 7.4570 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2454 loss: 2.2454 2022/09/07 19:36:59 - mmengine - INFO - Epoch(train) [18][1760/1793] lr: 7.5000e-03 eta: 6:34:23 time: 0.1771 data_time: 0.0089 memory: 10464 grad_norm: 7.0764 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.9861 loss: 1.9861 2022/09/07 19:37:04 - mmengine - INFO - Epoch(train) [18][1780/1793] lr: 7.5000e-03 eta: 6:34:09 time: 0.2531 data_time: 0.0797 memory: 10464 grad_norm: 6.9683 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.1729 loss: 2.1729 2022/09/07 19:37:06 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:37:06 - mmengine - INFO - Epoch(train) [18][1793/1793] lr: 7.5000e-03 eta: 6:34:09 time: 0.1717 data_time: 0.0053 memory: 10464 grad_norm: 8.2202 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 2.3180 loss: 2.3180 2022/09/07 19:37:06 - mmengine - INFO - Saving checkpoint at 18 epochs 2022/09/07 19:37:10 - mmengine - INFO - Epoch(val) [18][20/241] eta: 0:00:17 time: 0.0786 data_time: 0.0281 memory: 1482 2022/09/07 19:37:11 - mmengine - INFO - Epoch(val) [18][40/241] eta: 0:00:10 time: 0.0536 data_time: 0.0051 memory: 1482 2022/09/07 19:37:12 - mmengine - INFO - Epoch(val) [18][60/241] eta: 0:00:09 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 19:37:13 - mmengine - INFO - Epoch(val) [18][80/241] eta: 0:00:08 time: 0.0535 data_time: 0.0050 memory: 1482 2022/09/07 19:37:15 - mmengine - INFO - Epoch(val) [18][100/241] eta: 0:00:07 time: 0.0534 data_time: 0.0050 memory: 1482 2022/09/07 19:37:16 - mmengine - INFO - Epoch(val) [18][120/241] eta: 0:00:06 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 19:37:17 - mmengine - INFO - Epoch(val) [18][140/241] eta: 0:00:05 time: 0.0528 data_time: 0.0047 memory: 1482 2022/09/07 19:37:18 - mmengine - INFO - Epoch(val) [18][160/241] eta: 0:00:04 time: 0.0529 data_time: 0.0047 memory: 1482 2022/09/07 19:37:19 - mmengine - INFO - Epoch(val) [18][180/241] eta: 0:00:03 time: 0.0526 data_time: 0.0046 memory: 1482 2022/09/07 19:37:20 - mmengine - INFO - Epoch(val) [18][200/241] eta: 0:00:02 time: 0.0528 data_time: 0.0048 memory: 1482 2022/09/07 19:37:21 - mmengine - INFO - Epoch(val) [18][220/241] eta: 0:00:01 time: 0.0523 data_time: 0.0045 memory: 1482 2022/09/07 19:37:22 - mmengine - INFO - Epoch(val) [18][240/241] eta: 0:00:00 time: 0.0529 data_time: 0.0048 memory: 1482 2022/09/07 19:37:22 - mmengine - INFO - Epoch(val) [18][241/241] acc/top1: 0.3258 acc/top5: 0.6271 acc/mean1: 0.2982 2022/09/07 19:37:28 - mmengine - INFO - Epoch(train) [19][20/1793] lr: 7.5000e-03 eta: 6:33:41 time: 0.2910 data_time: 0.0119 memory: 10464 grad_norm: 7.0240 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.0068 loss: 2.0068 2022/09/07 19:37:32 - mmengine - INFO - Epoch(train) [19][40/1793] lr: 7.5000e-03 eta: 6:33:25 time: 0.1726 data_time: 0.0059 memory: 10464 grad_norm: 7.3138 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.3392 loss: 2.3392 2022/09/07 19:37:37 - mmengine - INFO - Epoch(train) [19][60/1793] lr: 7.5000e-03 eta: 6:33:11 time: 0.2510 data_time: 0.0075 memory: 10464 grad_norm: 7.3271 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1713 loss: 2.1713 2022/09/07 19:37:44 - mmengine - INFO - Epoch(train) [19][80/1793] lr: 7.5000e-03 eta: 6:33:00 time: 0.3450 data_time: 0.0097 memory: 10464 grad_norm: 6.9360 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1084 loss: 2.1084 2022/09/07 19:37:47 - mmengine - INFO - Epoch(train) [19][100/1793] lr: 7.5000e-03 eta: 6:32:43 time: 0.1736 data_time: 0.0063 memory: 10464 grad_norm: 7.2786 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4250 loss: 2.4250 2022/09/07 19:37:51 - mmengine - INFO - Epoch(train) [19][120/1793] lr: 7.5000e-03 eta: 6:32:27 time: 0.1787 data_time: 0.0087 memory: 10464 grad_norm: 7.1641 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.4124 loss: 2.4124 2022/09/07 19:37:55 - mmengine - INFO - Epoch(train) [19][140/1793] lr: 7.5000e-03 eta: 6:32:12 time: 0.2323 data_time: 0.0062 memory: 10464 grad_norm: 7.2445 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.1860 loss: 2.1860 2022/09/07 19:37:59 - mmengine - INFO - Epoch(train) [19][160/1793] lr: 7.5000e-03 eta: 6:31:56 time: 0.1760 data_time: 0.0067 memory: 10464 grad_norm: 7.0309 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3096 loss: 2.3096 2022/09/07 19:38:03 - mmengine - INFO - Epoch(train) [19][180/1793] lr: 7.5000e-03 eta: 6:31:40 time: 0.2012 data_time: 0.0093 memory: 10464 grad_norm: 7.2679 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.5533 loss: 2.5533 2022/09/07 19:38:07 - mmengine - INFO - Epoch(train) [19][200/1793] lr: 7.5000e-03 eta: 6:31:24 time: 0.1820 data_time: 0.0054 memory: 10464 grad_norm: 7.1578 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2695 loss: 2.2695 2022/09/07 19:38:10 - mmengine - INFO - Epoch(train) [19][220/1793] lr: 7.5000e-03 eta: 6:31:08 time: 0.1744 data_time: 0.0063 memory: 10464 grad_norm: 7.0671 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.3620 loss: 2.3620 2022/09/07 19:38:14 - mmengine - INFO - Epoch(train) [19][240/1793] lr: 7.5000e-03 eta: 6:30:51 time: 0.1778 data_time: 0.0092 memory: 10464 grad_norm: 7.3524 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3563 loss: 2.3563 2022/09/07 19:38:19 - mmengine - INFO - Epoch(train) [19][260/1793] lr: 7.5000e-03 eta: 6:30:38 time: 0.2762 data_time: 0.0057 memory: 10464 grad_norm: 7.0485 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5227 loss: 2.5227 2022/09/07 19:38:24 - mmengine - INFO - Epoch(train) [19][280/1793] lr: 7.5000e-03 eta: 6:30:24 time: 0.2526 data_time: 0.0062 memory: 10464 grad_norm: 6.6676 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9655 loss: 1.9655 2022/09/07 19:38:29 - mmengine - INFO - Epoch(train) [19][300/1793] lr: 7.5000e-03 eta: 6:30:10 time: 0.2407 data_time: 0.0090 memory: 10464 grad_norm: 7.1413 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0258 loss: 2.0258 2022/09/07 19:38:33 - mmengine - INFO - Epoch(train) [19][320/1793] lr: 7.5000e-03 eta: 6:29:55 time: 0.2176 data_time: 0.0062 memory: 10464 grad_norm: 7.0951 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.1872 loss: 2.1872 2022/09/07 19:38:38 - mmengine - INFO - Epoch(train) [19][340/1793] lr: 7.5000e-03 eta: 6:29:41 time: 0.2255 data_time: 0.0058 memory: 10464 grad_norm: 6.8873 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0814 loss: 2.0814 2022/09/07 19:38:43 - mmengine - INFO - Epoch(train) [19][360/1793] lr: 7.5000e-03 eta: 6:29:27 time: 0.2411 data_time: 0.0083 memory: 10464 grad_norm: 6.9751 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.2030 loss: 2.2030 2022/09/07 19:38:47 - mmengine - INFO - Epoch(train) [19][380/1793] lr: 7.5000e-03 eta: 6:29:11 time: 0.1992 data_time: 0.0064 memory: 10464 grad_norm: 7.3193 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3828 loss: 2.3828 2022/09/07 19:38:51 - mmengine - INFO - Epoch(train) [19][400/1793] lr: 7.5000e-03 eta: 6:28:56 time: 0.2091 data_time: 0.0061 memory: 10464 grad_norm: 6.9724 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0531 loss: 2.0531 2022/09/07 19:38:55 - mmengine - INFO - Epoch(train) [19][420/1793] lr: 7.5000e-03 eta: 6:28:40 time: 0.1794 data_time: 0.0088 memory: 10464 grad_norm: 7.2356 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3098 loss: 2.3098 2022/09/07 19:38:58 - mmengine - INFO - Epoch(train) [19][440/1793] lr: 7.5000e-03 eta: 6:28:24 time: 0.1814 data_time: 0.0063 memory: 10464 grad_norm: 6.9443 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9277 loss: 1.9277 2022/09/07 19:39:02 - mmengine - INFO - Epoch(train) [19][460/1793] lr: 7.5000e-03 eta: 6:28:07 time: 0.1752 data_time: 0.0065 memory: 10464 grad_norm: 7.2313 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.1004 loss: 2.1004 2022/09/07 19:39:06 - mmengine - INFO - Epoch(train) [19][480/1793] lr: 7.5000e-03 eta: 6:27:51 time: 0.1914 data_time: 0.0101 memory: 10464 grad_norm: 7.0657 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2025 loss: 2.2025 2022/09/07 19:39:09 - mmengine - INFO - Epoch(train) [19][500/1793] lr: 7.5000e-03 eta: 6:27:35 time: 0.1748 data_time: 0.0061 memory: 10464 grad_norm: 7.2563 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4704 loss: 2.4704 2022/09/07 19:39:14 - mmengine - INFO - Epoch(train) [19][520/1793] lr: 7.5000e-03 eta: 6:27:21 time: 0.2452 data_time: 0.0070 memory: 10464 grad_norm: 7.1754 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2573 loss: 2.2573 2022/09/07 19:39:18 - mmengine - INFO - Epoch(train) [19][540/1793] lr: 7.5000e-03 eta: 6:27:06 time: 0.1913 data_time: 0.0087 memory: 10464 grad_norm: 7.0074 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.3633 loss: 2.3633 2022/09/07 19:39:23 - mmengine - INFO - Epoch(train) [19][560/1793] lr: 7.5000e-03 eta: 6:26:52 time: 0.2493 data_time: 0.0061 memory: 10464 grad_norm: 7.0067 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1238 loss: 2.1238 2022/09/07 19:39:27 - mmengine - INFO - Epoch(train) [19][580/1793] lr: 7.5000e-03 eta: 6:26:36 time: 0.1949 data_time: 0.0084 memory: 10464 grad_norm: 7.1309 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3821 loss: 2.3821 2022/09/07 19:39:31 - mmengine - INFO - Epoch(train) [19][600/1793] lr: 7.5000e-03 eta: 6:26:22 time: 0.2388 data_time: 0.0648 memory: 10464 grad_norm: 6.9132 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.0623 loss: 2.0623 2022/09/07 19:39:35 - mmengine - INFO - Epoch(train) [19][620/1793] lr: 7.5000e-03 eta: 6:26:06 time: 0.1760 data_time: 0.0064 memory: 10464 grad_norm: 7.0459 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2875 loss: 2.2875 2022/09/07 19:39:40 - mmengine - INFO - Epoch(train) [19][640/1793] lr: 7.5000e-03 eta: 6:25:53 time: 0.2567 data_time: 0.0054 memory: 10464 grad_norm: 7.1689 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.5247 loss: 2.5247 2022/09/07 19:39:44 - mmengine - INFO - Epoch(train) [19][660/1793] lr: 7.5000e-03 eta: 6:25:37 time: 0.1828 data_time: 0.0157 memory: 10464 grad_norm: 7.5226 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2875 loss: 2.2875 2022/09/07 19:39:47 - mmengine - INFO - Epoch(train) [19][680/1793] lr: 7.5000e-03 eta: 6:25:21 time: 0.1766 data_time: 0.0058 memory: 10464 grad_norm: 7.4179 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2187 loss: 2.2187 2022/09/07 19:39:52 - mmengine - INFO - Epoch(train) [19][700/1793] lr: 7.5000e-03 eta: 6:25:07 time: 0.2452 data_time: 0.0068 memory: 10464 grad_norm: 7.0230 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4344 loss: 2.4344 2022/09/07 19:39:56 - mmengine - INFO - Epoch(train) [19][720/1793] lr: 7.5000e-03 eta: 6:24:51 time: 0.1749 data_time: 0.0085 memory: 10464 grad_norm: 7.1623 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.4061 loss: 2.4061 2022/09/07 19:39:57 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:39:59 - mmengine - INFO - Epoch(train) [19][740/1793] lr: 7.5000e-03 eta: 6:24:35 time: 0.1754 data_time: 0.0059 memory: 10464 grad_norm: 7.2809 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5066 loss: 2.5066 2022/09/07 19:40:03 - mmengine - INFO - Epoch(train) [19][760/1793] lr: 7.5000e-03 eta: 6:24:19 time: 0.1744 data_time: 0.0065 memory: 10464 grad_norm: 6.9703 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.2754 loss: 2.2754 2022/09/07 19:40:06 - mmengine - INFO - Epoch(train) [19][780/1793] lr: 7.5000e-03 eta: 6:24:03 time: 0.1821 data_time: 0.0089 memory: 10464 grad_norm: 7.3615 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1646 loss: 2.1646 2022/09/07 19:40:12 - mmengine - INFO - Epoch(train) [19][800/1793] lr: 7.5000e-03 eta: 6:23:50 time: 0.2634 data_time: 0.0797 memory: 10464 grad_norm: 7.0703 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4984 loss: 2.4984 2022/09/07 19:40:17 - mmengine - INFO - Epoch(train) [19][820/1793] lr: 7.5000e-03 eta: 6:23:36 time: 0.2444 data_time: 0.0056 memory: 10464 grad_norm: 7.4418 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4033 loss: 2.4033 2022/09/07 19:40:22 - mmengine - INFO - Epoch(train) [19][840/1793] lr: 7.5000e-03 eta: 6:23:24 time: 0.2969 data_time: 0.0093 memory: 10464 grad_norm: 7.0514 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.5889 loss: 2.5889 2022/09/07 19:40:26 - mmengine - INFO - Epoch(train) [19][860/1793] lr: 7.5000e-03 eta: 6:23:09 time: 0.1897 data_time: 0.0055 memory: 10464 grad_norm: 7.0221 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.1979 loss: 2.1979 2022/09/07 19:40:31 - mmengine - INFO - Epoch(train) [19][880/1793] lr: 7.5000e-03 eta: 6:22:54 time: 0.2206 data_time: 0.0062 memory: 10464 grad_norm: 7.1672 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.9840 loss: 1.9840 2022/09/07 19:40:34 - mmengine - INFO - Epoch(train) [19][900/1793] lr: 7.5000e-03 eta: 6:22:38 time: 0.1763 data_time: 0.0086 memory: 10464 grad_norm: 7.1013 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.6375 loss: 2.6375 2022/09/07 19:40:38 - mmengine - INFO - Epoch(train) [19][920/1793] lr: 7.5000e-03 eta: 6:22:22 time: 0.1834 data_time: 0.0179 memory: 10464 grad_norm: 6.9484 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.4199 loss: 2.4199 2022/09/07 19:40:41 - mmengine - INFO - Epoch(train) [19][940/1793] lr: 7.5000e-03 eta: 6:22:06 time: 0.1755 data_time: 0.0045 memory: 10464 grad_norm: 7.3393 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4619 loss: 2.4619 2022/09/07 19:40:45 - mmengine - INFO - Epoch(train) [19][960/1793] lr: 7.5000e-03 eta: 6:21:51 time: 0.1795 data_time: 0.0099 memory: 10464 grad_norm: 6.8767 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3365 loss: 2.3365 2022/09/07 19:40:48 - mmengine - INFO - Epoch(train) [19][980/1793] lr: 7.5000e-03 eta: 6:21:34 time: 0.1714 data_time: 0.0054 memory: 10464 grad_norm: 6.8538 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1768 loss: 2.1768 2022/09/07 19:40:52 - mmengine - INFO - Epoch(train) [19][1000/1793] lr: 7.5000e-03 eta: 6:21:18 time: 0.1710 data_time: 0.0061 memory: 10464 grad_norm: 7.2530 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3727 loss: 2.3727 2022/09/07 19:40:56 - mmengine - INFO - Epoch(train) [19][1020/1793] lr: 7.5000e-03 eta: 6:21:03 time: 0.1972 data_time: 0.0256 memory: 10464 grad_norm: 7.1318 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0111 loss: 2.0111 2022/09/07 19:41:01 - mmengine - INFO - Epoch(train) [19][1040/1793] lr: 7.5000e-03 eta: 6:20:50 time: 0.2463 data_time: 0.0334 memory: 10464 grad_norm: 6.8583 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5508 loss: 2.5508 2022/09/07 19:41:05 - mmengine - INFO - Epoch(train) [19][1060/1793] lr: 7.5000e-03 eta: 6:20:34 time: 0.1947 data_time: 0.0062 memory: 10464 grad_norm: 7.1849 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2448 loss: 2.2448 2022/09/07 19:41:08 - mmengine - INFO - Epoch(train) [19][1080/1793] lr: 7.5000e-03 eta: 6:20:19 time: 0.1779 data_time: 0.0077 memory: 10464 grad_norm: 7.1838 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.3562 loss: 2.3562 2022/09/07 19:41:12 - mmengine - INFO - Epoch(train) [19][1100/1793] lr: 7.5000e-03 eta: 6:20:03 time: 0.1751 data_time: 0.0063 memory: 10464 grad_norm: 7.2357 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1977 loss: 2.1977 2022/09/07 19:41:17 - mmengine - INFO - Epoch(train) [19][1120/1793] lr: 7.5000e-03 eta: 6:19:49 time: 0.2496 data_time: 0.0071 memory: 10464 grad_norm: 7.3817 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3343 loss: 2.3343 2022/09/07 19:41:20 - mmengine - INFO - Epoch(train) [19][1140/1793] lr: 7.5000e-03 eta: 6:19:34 time: 0.1777 data_time: 0.0088 memory: 10464 grad_norm: 7.0969 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.3149 loss: 2.3149 2022/09/07 19:41:26 - mmengine - INFO - Epoch(train) [19][1160/1793] lr: 7.5000e-03 eta: 6:19:21 time: 0.2741 data_time: 0.0057 memory: 10464 grad_norm: 7.1574 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.3709 loss: 2.3709 2022/09/07 19:41:29 - mmengine - INFO - Epoch(train) [19][1180/1793] lr: 7.5000e-03 eta: 6:19:05 time: 0.1731 data_time: 0.0066 memory: 10464 grad_norm: 6.9267 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.4761 loss: 2.4761 2022/09/07 19:41:33 - mmengine - INFO - Epoch(train) [19][1200/1793] lr: 7.5000e-03 eta: 6:18:51 time: 0.2060 data_time: 0.0317 memory: 10464 grad_norm: 7.3040 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.2306 loss: 2.2306 2022/09/07 19:41:37 - mmengine - INFO - Epoch(train) [19][1220/1793] lr: 7.5000e-03 eta: 6:18:35 time: 0.1764 data_time: 0.0069 memory: 10464 grad_norm: 6.9618 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.4402 loss: 2.4402 2022/09/07 19:41:42 - mmengine - INFO - Epoch(train) [19][1240/1793] lr: 7.5000e-03 eta: 6:18:22 time: 0.2502 data_time: 0.0716 memory: 10464 grad_norm: 7.2863 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.0638 loss: 2.0638 2022/09/07 19:41:46 - mmengine - INFO - Epoch(train) [19][1260/1793] lr: 7.5000e-03 eta: 6:18:06 time: 0.1911 data_time: 0.0102 memory: 10464 grad_norm: 7.1303 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3159 loss: 2.3159 2022/09/07 19:41:50 - mmengine - INFO - Epoch(train) [19][1280/1793] lr: 7.5000e-03 eta: 6:17:53 time: 0.2411 data_time: 0.0069 memory: 10464 grad_norm: 6.9237 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 2.3299 loss: 2.3299 2022/09/07 19:41:54 - mmengine - INFO - Epoch(train) [19][1300/1793] lr: 7.5000e-03 eta: 6:17:37 time: 0.1718 data_time: 0.0059 memory: 10464 grad_norm: 7.0021 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.0706 loss: 2.0706 2022/09/07 19:41:58 - mmengine - INFO - Epoch(train) [19][1320/1793] lr: 7.5000e-03 eta: 6:17:21 time: 0.1813 data_time: 0.0098 memory: 10464 grad_norm: 7.1107 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4106 loss: 2.4106 2022/09/07 19:42:02 - mmengine - INFO - Epoch(train) [19][1340/1793] lr: 7.5000e-03 eta: 6:17:08 time: 0.2427 data_time: 0.0050 memory: 10464 grad_norm: 7.2910 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1171 loss: 2.1171 2022/09/07 19:42:06 - mmengine - INFO - Epoch(train) [19][1360/1793] lr: 7.5000e-03 eta: 6:16:53 time: 0.1955 data_time: 0.0081 memory: 10464 grad_norm: 7.0012 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.2714 loss: 2.2714 2022/09/07 19:42:10 - mmengine - INFO - Epoch(train) [19][1380/1793] lr: 7.5000e-03 eta: 6:16:37 time: 0.1793 data_time: 0.0095 memory: 10464 grad_norm: 7.2330 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4217 loss: 2.4217 2022/09/07 19:42:13 - mmengine - INFO - Epoch(train) [19][1400/1793] lr: 7.5000e-03 eta: 6:16:22 time: 0.1726 data_time: 0.0065 memory: 10464 grad_norm: 6.9136 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3113 loss: 2.3113 2022/09/07 19:42:17 - mmengine - INFO - Epoch(train) [19][1420/1793] lr: 7.5000e-03 eta: 6:16:06 time: 0.1733 data_time: 0.0063 memory: 10464 grad_norm: 7.3316 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1780 loss: 2.1780 2022/09/07 19:42:22 - mmengine - INFO - Epoch(train) [19][1440/1793] lr: 7.5000e-03 eta: 6:15:53 time: 0.2559 data_time: 0.0087 memory: 10464 grad_norm: 6.9054 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0716 loss: 2.0716 2022/09/07 19:42:25 - mmengine - INFO - Epoch(train) [19][1460/1793] lr: 7.5000e-03 eta: 6:15:37 time: 0.1776 data_time: 0.0081 memory: 10464 grad_norm: 7.3683 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4504 loss: 2.4504 2022/09/07 19:42:29 - mmengine - INFO - Epoch(train) [19][1480/1793] lr: 7.5000e-03 eta: 6:15:22 time: 0.1925 data_time: 0.0049 memory: 10464 grad_norm: 7.0928 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.4259 loss: 2.4259 2022/09/07 19:42:33 - mmengine - INFO - Epoch(train) [19][1500/1793] lr: 7.5000e-03 eta: 6:15:07 time: 0.1881 data_time: 0.0085 memory: 10464 grad_norm: 7.0622 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.0411 loss: 2.0411 2022/09/07 19:42:38 - mmengine - INFO - Epoch(train) [19][1520/1793] lr: 7.5000e-03 eta: 6:14:54 time: 0.2386 data_time: 0.0102 memory: 10464 grad_norm: 7.3726 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2101 loss: 2.2101 2022/09/07 19:42:41 - mmengine - INFO - Epoch(train) [19][1540/1793] lr: 7.5000e-03 eta: 6:14:38 time: 0.1775 data_time: 0.0057 memory: 10464 grad_norm: 7.0109 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3486 loss: 2.3486 2022/09/07 19:42:46 - mmengine - INFO - Epoch(train) [19][1560/1793] lr: 7.5000e-03 eta: 6:14:25 time: 0.2476 data_time: 0.0090 memory: 10464 grad_norm: 7.0434 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2320 loss: 2.2320 2022/09/07 19:42:50 - mmengine - INFO - Epoch(train) [19][1580/1793] lr: 7.5000e-03 eta: 6:14:10 time: 0.1787 data_time: 0.0070 memory: 10464 grad_norm: 7.2161 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4597 loss: 2.4597 2022/09/07 19:42:54 - mmengine - INFO - Epoch(train) [19][1600/1793] lr: 7.5000e-03 eta: 6:13:54 time: 0.1773 data_time: 0.0071 memory: 10464 grad_norm: 6.8346 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.4783 loss: 2.4783 2022/09/07 19:42:57 - mmengine - INFO - Epoch(train) [19][1620/1793] lr: 7.5000e-03 eta: 6:13:39 time: 0.1829 data_time: 0.0084 memory: 10464 grad_norm: 6.7913 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1426 loss: 2.1426 2022/09/07 19:43:01 - mmengine - INFO - Epoch(train) [19][1640/1793] lr: 7.5000e-03 eta: 6:13:24 time: 0.1787 data_time: 0.0061 memory: 10464 grad_norm: 7.3643 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9293 loss: 1.9293 2022/09/07 19:43:04 - mmengine - INFO - Epoch(train) [19][1660/1793] lr: 7.5000e-03 eta: 6:13:08 time: 0.1783 data_time: 0.0066 memory: 10464 grad_norm: 7.2721 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1338 loss: 2.1338 2022/09/07 19:43:09 - mmengine - INFO - Epoch(train) [19][1680/1793] lr: 7.5000e-03 eta: 6:12:55 time: 0.2367 data_time: 0.0087 memory: 10464 grad_norm: 7.1021 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0850 loss: 2.0850 2022/09/07 19:43:13 - mmengine - INFO - Epoch(train) [19][1700/1793] lr: 7.5000e-03 eta: 6:12:39 time: 0.1812 data_time: 0.0071 memory: 10464 grad_norm: 7.0972 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4289 loss: 2.4289 2022/09/07 19:43:16 - mmengine - INFO - Epoch(train) [19][1720/1793] lr: 7.5000e-03 eta: 6:12:24 time: 0.1805 data_time: 0.0057 memory: 10464 grad_norm: 6.9323 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.1141 loss: 2.1141 2022/09/07 19:43:17 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:43:20 - mmengine - INFO - Epoch(train) [19][1740/1793] lr: 7.5000e-03 eta: 6:12:09 time: 0.1768 data_time: 0.0082 memory: 10464 grad_norm: 6.9043 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3391 loss: 2.3391 2022/09/07 19:43:24 - mmengine - INFO - Epoch(train) [19][1760/1793] lr: 7.5000e-03 eta: 6:11:54 time: 0.1922 data_time: 0.0068 memory: 10464 grad_norm: 6.9404 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.2779 loss: 2.2779 2022/09/07 19:43:27 - mmengine - INFO - Epoch(train) [19][1780/1793] lr: 7.5000e-03 eta: 6:11:39 time: 0.1802 data_time: 0.0060 memory: 10464 grad_norm: 7.0732 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3214 loss: 2.3214 2022/09/07 19:43:29 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:43:29 - mmengine - INFO - Epoch(train) [19][1793/1793] lr: 7.5000e-03 eta: 6:11:39 time: 0.1743 data_time: 0.0075 memory: 10464 grad_norm: 7.9068 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 2.4410 loss: 2.4410 2022/09/07 19:43:29 - mmengine - INFO - Saving checkpoint at 19 epochs 2022/09/07 19:43:33 - mmengine - INFO - Epoch(val) [19][20/241] eta: 0:00:12 time: 0.0584 data_time: 0.0091 memory: 1482 2022/09/07 19:43:34 - mmengine - INFO - Epoch(val) [19][40/241] eta: 0:00:10 time: 0.0532 data_time: 0.0049 memory: 1482 2022/09/07 19:43:35 - mmengine - INFO - Epoch(val) [19][60/241] eta: 0:00:09 time: 0.0535 data_time: 0.0050 memory: 1482 2022/09/07 19:43:36 - mmengine - INFO - Epoch(val) [19][80/241] eta: 0:00:08 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 19:43:37 - mmengine - INFO - Epoch(val) [19][100/241] eta: 0:00:07 time: 0.0531 data_time: 0.0047 memory: 1482 2022/09/07 19:43:38 - mmengine - INFO - Epoch(val) [19][120/241] eta: 0:00:06 time: 0.0533 data_time: 0.0048 memory: 1482 2022/09/07 19:43:39 - mmengine - INFO - Epoch(val) [19][140/241] eta: 0:00:05 time: 0.0537 data_time: 0.0054 memory: 1482 2022/09/07 19:43:40 - mmengine - INFO - Epoch(val) [19][160/241] eta: 0:00:04 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 19:43:41 - mmengine - INFO - Epoch(val) [19][180/241] eta: 0:00:03 time: 0.0536 data_time: 0.0051 memory: 1482 2022/09/07 19:43:42 - mmengine - INFO - Epoch(val) [19][200/241] eta: 0:00:02 time: 0.0533 data_time: 0.0050 memory: 1482 2022/09/07 19:43:43 - mmengine - INFO - Epoch(val) [19][220/241] eta: 0:00:01 time: 0.0574 data_time: 0.0045 memory: 1482 2022/09/07 19:43:44 - mmengine - INFO - Epoch(val) [19][240/241] eta: 0:00:00 time: 0.0535 data_time: 0.0052 memory: 1482 2022/09/07 19:43:45 - mmengine - INFO - Epoch(val) [19][241/241] acc/top1: 0.3238 acc/top5: 0.6177 acc/mean1: 0.2977 2022/09/07 19:43:50 - mmengine - INFO - Epoch(train) [20][20/1793] lr: 7.5000e-03 eta: 6:11:12 time: 0.2630 data_time: 0.0107 memory: 10464 grad_norm: 7.1492 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.1873 loss: 2.1873 2022/09/07 19:43:56 - mmengine - INFO - Epoch(train) [20][40/1793] lr: 7.5000e-03 eta: 6:11:00 time: 0.2513 data_time: 0.0060 memory: 10464 grad_norm: 7.2310 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3124 loss: 2.3124 2022/09/07 19:43:59 - mmengine - INFO - Epoch(train) [20][60/1793] lr: 7.5000e-03 eta: 6:10:44 time: 0.1775 data_time: 0.0092 memory: 10464 grad_norm: 7.4651 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2051 loss: 2.2051 2022/09/07 19:44:04 - mmengine - INFO - Epoch(train) [20][80/1793] lr: 7.5000e-03 eta: 6:10:31 time: 0.2450 data_time: 0.0059 memory: 10464 grad_norm: 7.1483 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5017 loss: 2.5017 2022/09/07 19:44:08 - mmengine - INFO - Epoch(train) [20][100/1793] lr: 7.5000e-03 eta: 6:10:16 time: 0.1837 data_time: 0.0077 memory: 10464 grad_norm: 7.1964 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3920 loss: 2.3920 2022/09/07 19:44:13 - mmengine - INFO - Epoch(train) [20][120/1793] lr: 7.5000e-03 eta: 6:10:03 time: 0.2451 data_time: 0.0099 memory: 10464 grad_norm: 7.3065 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3278 loss: 2.3278 2022/09/07 19:44:17 - mmengine - INFO - Epoch(train) [20][140/1793] lr: 7.5000e-03 eta: 6:09:50 time: 0.2411 data_time: 0.0064 memory: 10464 grad_norm: 7.0873 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3157 loss: 2.3157 2022/09/07 19:44:21 - mmengine - INFO - Epoch(train) [20][160/1793] lr: 7.5000e-03 eta: 6:09:35 time: 0.1804 data_time: 0.0061 memory: 10464 grad_norm: 7.2509 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7596 loss: 1.7596 2022/09/07 19:44:25 - mmengine - INFO - Epoch(train) [20][180/1793] lr: 7.5000e-03 eta: 6:09:20 time: 0.1881 data_time: 0.0098 memory: 10464 grad_norm: 7.3269 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2481 loss: 2.2481 2022/09/07 19:44:28 - mmengine - INFO - Epoch(train) [20][200/1793] lr: 7.5000e-03 eta: 6:09:05 time: 0.1746 data_time: 0.0072 memory: 10464 grad_norm: 7.5794 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2576 loss: 2.2576 2022/09/07 19:44:32 - mmengine - INFO - Epoch(train) [20][220/1793] lr: 7.5000e-03 eta: 6:08:49 time: 0.1767 data_time: 0.0072 memory: 10464 grad_norm: 6.9583 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3308 loss: 2.3308 2022/09/07 19:44:36 - mmengine - INFO - Epoch(train) [20][240/1793] lr: 7.5000e-03 eta: 6:08:35 time: 0.1931 data_time: 0.0086 memory: 10464 grad_norm: 7.3176 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3760 loss: 2.3760 2022/09/07 19:44:39 - mmengine - INFO - Epoch(train) [20][260/1793] lr: 7.5000e-03 eta: 6:08:20 time: 0.1744 data_time: 0.0051 memory: 10464 grad_norm: 6.9854 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.0100 loss: 2.0100 2022/09/07 19:44:43 - mmengine - INFO - Epoch(train) [20][280/1793] lr: 7.5000e-03 eta: 6:08:05 time: 0.1951 data_time: 0.0059 memory: 10464 grad_norm: 7.1798 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1865 loss: 2.1865 2022/09/07 19:44:48 - mmengine - INFO - Epoch(train) [20][300/1793] lr: 7.5000e-03 eta: 6:07:53 time: 0.2612 data_time: 0.0817 memory: 10464 grad_norm: 7.1461 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2183 loss: 2.2183 2022/09/07 19:44:52 - mmengine - INFO - Epoch(train) [20][320/1793] lr: 7.5000e-03 eta: 6:07:37 time: 0.1790 data_time: 0.0063 memory: 10464 grad_norm: 7.3861 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1881 loss: 2.1881 2022/09/07 19:44:55 - mmengine - INFO - Epoch(train) [20][340/1793] lr: 7.5000e-03 eta: 6:07:22 time: 0.1755 data_time: 0.0060 memory: 10464 grad_norm: 6.9983 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.9079 loss: 1.9079 2022/09/07 19:44:59 - mmengine - INFO - Epoch(train) [20][360/1793] lr: 7.5000e-03 eta: 6:07:07 time: 0.1749 data_time: 0.0087 memory: 10464 grad_norm: 7.1042 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3639 loss: 2.3639 2022/09/07 19:45:02 - mmengine - INFO - Epoch(train) [20][380/1793] lr: 7.5000e-03 eta: 6:06:52 time: 0.1778 data_time: 0.0072 memory: 10464 grad_norm: 7.2081 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0752 loss: 2.0752 2022/09/07 19:45:06 - mmengine - INFO - Epoch(train) [20][400/1793] lr: 7.5000e-03 eta: 6:06:38 time: 0.1966 data_time: 0.0070 memory: 10464 grad_norm: 7.4482 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3006 loss: 2.3006 2022/09/07 19:45:10 - mmengine - INFO - Epoch(train) [20][420/1793] lr: 7.5000e-03 eta: 6:06:23 time: 0.1774 data_time: 0.0095 memory: 10464 grad_norm: 7.0678 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1657 loss: 2.1657 2022/09/07 19:45:14 - mmengine - INFO - Epoch(train) [20][440/1793] lr: 7.5000e-03 eta: 6:06:08 time: 0.1820 data_time: 0.0061 memory: 10464 grad_norm: 7.0269 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2497 loss: 2.2497 2022/09/07 19:45:17 - mmengine - INFO - Epoch(train) [20][460/1793] lr: 7.5000e-03 eta: 6:05:53 time: 0.1820 data_time: 0.0138 memory: 10464 grad_norm: 7.5999 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4313 loss: 2.4313 2022/09/07 19:45:23 - mmengine - INFO - Epoch(train) [20][480/1793] lr: 7.5000e-03 eta: 6:05:42 time: 0.2936 data_time: 0.1142 memory: 10464 grad_norm: 6.7195 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4993 loss: 2.4993 2022/09/07 19:45:27 - mmengine - INFO - Epoch(train) [20][500/1793] lr: 7.5000e-03 eta: 6:05:27 time: 0.1956 data_time: 0.0063 memory: 10464 grad_norm: 7.1320 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.1018 loss: 2.1018 2022/09/07 19:45:31 - mmengine - INFO - Epoch(train) [20][520/1793] lr: 7.5000e-03 eta: 6:05:12 time: 0.1813 data_time: 0.0067 memory: 10464 grad_norm: 7.0304 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1395 loss: 2.1395 2022/09/07 19:45:34 - mmengine - INFO - Epoch(train) [20][540/1793] lr: 7.5000e-03 eta: 6:04:57 time: 0.1797 data_time: 0.0091 memory: 10464 grad_norm: 7.2373 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.5358 loss: 2.5358 2022/09/07 19:45:39 - mmengine - INFO - Epoch(train) [20][560/1793] lr: 7.5000e-03 eta: 6:04:45 time: 0.2610 data_time: 0.0068 memory: 10464 grad_norm: 7.4807 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1774 loss: 2.1774 2022/09/07 19:45:43 - mmengine - INFO - Epoch(train) [20][580/1793] lr: 7.5000e-03 eta: 6:04:30 time: 0.1761 data_time: 0.0057 memory: 10464 grad_norm: 7.2477 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5129 loss: 2.5129 2022/09/07 19:45:48 - mmengine - INFO - Epoch(train) [20][600/1793] lr: 7.5000e-03 eta: 6:04:18 time: 0.2613 data_time: 0.0091 memory: 10464 grad_norm: 6.9735 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2236 loss: 2.2236 2022/09/07 19:45:53 - mmengine - INFO - Epoch(train) [20][620/1793] lr: 7.5000e-03 eta: 6:04:05 time: 0.2401 data_time: 0.0060 memory: 10464 grad_norm: 7.1908 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3251 loss: 2.3251 2022/09/07 19:45:58 - mmengine - INFO - Epoch(train) [20][640/1793] lr: 7.5000e-03 eta: 6:03:52 time: 0.2465 data_time: 0.0080 memory: 10464 grad_norm: 6.7605 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3108 loss: 2.3108 2022/09/07 19:46:01 - mmengine - INFO - Epoch(train) [20][660/1793] lr: 7.5000e-03 eta: 6:03:37 time: 0.1749 data_time: 0.0062 memory: 10464 grad_norm: 7.0085 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1474 loss: 2.1474 2022/09/07 19:46:05 - mmengine - INFO - Epoch(train) [20][680/1793] lr: 7.5000e-03 eta: 6:03:22 time: 0.1777 data_time: 0.0071 memory: 10464 grad_norm: 6.9599 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1597 loss: 2.1597 2022/09/07 19:46:09 - mmengine - INFO - Epoch(train) [20][700/1793] lr: 7.5000e-03 eta: 6:03:07 time: 0.1779 data_time: 0.0084 memory: 10464 grad_norm: 7.1722 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3962 loss: 2.3962 2022/09/07 19:46:16 - mmengine - INFO - Epoch(train) [20][720/1793] lr: 7.5000e-03 eta: 6:02:58 time: 0.3495 data_time: 0.0067 memory: 10464 grad_norm: 7.0909 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4529 loss: 2.4529 2022/09/07 19:46:21 - mmengine - INFO - Epoch(train) [20][740/1793] lr: 7.5000e-03 eta: 6:02:45 time: 0.2507 data_time: 0.0660 memory: 10464 grad_norm: 7.1019 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1861 loss: 2.1861 2022/09/07 19:46:24 - mmengine - INFO - Epoch(train) [20][760/1793] lr: 7.5000e-03 eta: 6:02:31 time: 0.1824 data_time: 0.0056 memory: 10464 grad_norm: 7.0248 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5003 loss: 2.5003 2022/09/07 19:46:28 - mmengine - INFO - Epoch(train) [20][780/1793] lr: 7.5000e-03 eta: 6:02:16 time: 0.1725 data_time: 0.0068 memory: 10464 grad_norm: 7.3879 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7257 loss: 2.7257 2022/09/07 19:46:34 - mmengine - INFO - Epoch(train) [20][800/1793] lr: 7.5000e-03 eta: 6:02:05 time: 0.3084 data_time: 0.0079 memory: 10464 grad_norm: 7.1004 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3068 loss: 2.3068 2022/09/07 19:46:37 - mmengine - INFO - Epoch(train) [20][820/1793] lr: 7.5000e-03 eta: 6:01:50 time: 0.1755 data_time: 0.0067 memory: 10464 grad_norm: 7.0201 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2960 loss: 2.2960 2022/09/07 19:46:42 - mmengine - INFO - Epoch(train) [20][840/1793] lr: 7.5000e-03 eta: 6:01:37 time: 0.2435 data_time: 0.0772 memory: 10464 grad_norm: 7.4466 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3230 loss: 2.3230 2022/09/07 19:46:46 - mmengine - INFO - Epoch(train) [20][860/1793] lr: 7.5000e-03 eta: 6:01:23 time: 0.1804 data_time: 0.0077 memory: 10464 grad_norm: 7.2963 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2275 loss: 2.2275 2022/09/07 19:46:49 - mmengine - INFO - Epoch(train) [20][880/1793] lr: 7.5000e-03 eta: 6:01:08 time: 0.1735 data_time: 0.0053 memory: 10464 grad_norm: 7.3030 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2429 loss: 2.2429 2022/09/07 19:46:53 - mmengine - INFO - Epoch(train) [20][900/1793] lr: 7.5000e-03 eta: 6:00:53 time: 0.1749 data_time: 0.0061 memory: 10464 grad_norm: 7.2971 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1715 loss: 2.1715 2022/09/07 19:46:58 - mmengine - INFO - Epoch(train) [20][920/1793] lr: 7.5000e-03 eta: 6:00:40 time: 0.2426 data_time: 0.0083 memory: 10464 grad_norm: 7.3254 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.1976 loss: 2.1976 2022/09/07 19:47:00 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:47:01 - mmengine - INFO - Epoch(train) [20][940/1793] lr: 7.5000e-03 eta: 6:00:25 time: 0.1756 data_time: 0.0065 memory: 10464 grad_norm: 7.2685 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.0953 loss: 2.0953 2022/09/07 19:47:05 - mmengine - INFO - Epoch(train) [20][960/1793] lr: 7.5000e-03 eta: 6:00:11 time: 0.1835 data_time: 0.0072 memory: 10464 grad_norm: 7.2533 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.1861 loss: 2.1861 2022/09/07 19:47:08 - mmengine - INFO - Epoch(train) [20][980/1793] lr: 7.5000e-03 eta: 5:59:56 time: 0.1760 data_time: 0.0087 memory: 10464 grad_norm: 7.3656 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3738 loss: 2.3738 2022/09/07 19:47:13 - mmengine - INFO - Epoch(train) [20][1000/1793] lr: 7.5000e-03 eta: 5:59:43 time: 0.2163 data_time: 0.0056 memory: 10464 grad_norm: 7.2310 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3301 loss: 2.3301 2022/09/07 19:47:16 - mmengine - INFO - Epoch(train) [20][1020/1793] lr: 7.5000e-03 eta: 5:59:28 time: 0.1782 data_time: 0.0066 memory: 10464 grad_norm: 7.0032 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2869 loss: 2.2869 2022/09/07 19:47:21 - mmengine - INFO - Epoch(train) [20][1040/1793] lr: 7.5000e-03 eta: 5:59:15 time: 0.2430 data_time: 0.0085 memory: 10464 grad_norm: 6.9014 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.2487 loss: 2.2487 2022/09/07 19:47:26 - mmengine - INFO - Epoch(train) [20][1060/1793] lr: 7.5000e-03 eta: 5:59:04 time: 0.2688 data_time: 0.0069 memory: 10464 grad_norm: 7.2039 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1775 loss: 2.1775 2022/09/07 19:47:30 - mmengine - INFO - Epoch(train) [20][1080/1793] lr: 7.5000e-03 eta: 5:58:49 time: 0.1739 data_time: 0.0076 memory: 10464 grad_norm: 7.0418 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.1243 loss: 2.1243 2022/09/07 19:47:34 - mmengine - INFO - Epoch(train) [20][1100/1793] lr: 7.5000e-03 eta: 5:58:35 time: 0.2050 data_time: 0.0097 memory: 10464 grad_norm: 7.1165 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0947 loss: 2.0947 2022/09/07 19:47:38 - mmengine - INFO - Epoch(train) [20][1120/1793] lr: 7.5000e-03 eta: 5:58:20 time: 0.1753 data_time: 0.0060 memory: 10464 grad_norm: 7.2388 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4049 loss: 2.4049 2022/09/07 19:47:41 - mmengine - INFO - Epoch(train) [20][1140/1793] lr: 7.5000e-03 eta: 5:58:06 time: 0.1798 data_time: 0.0087 memory: 10464 grad_norm: 6.9963 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2203 loss: 2.2203 2022/09/07 19:47:45 - mmengine - INFO - Epoch(train) [20][1160/1793] lr: 7.5000e-03 eta: 5:57:51 time: 0.1752 data_time: 0.0058 memory: 10464 grad_norm: 7.1853 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0967 loss: 2.0967 2022/09/07 19:47:48 - mmengine - INFO - Epoch(train) [20][1180/1793] lr: 7.5000e-03 eta: 5:57:36 time: 0.1755 data_time: 0.0083 memory: 10464 grad_norm: 7.2196 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3207 loss: 2.3207 2022/09/07 19:47:52 - mmengine - INFO - Epoch(train) [20][1200/1793] lr: 7.5000e-03 eta: 5:57:22 time: 0.1844 data_time: 0.0079 memory: 10464 grad_norm: 7.1195 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3702 loss: 2.3702 2022/09/07 19:47:56 - mmengine - INFO - Epoch(train) [20][1220/1793] lr: 7.5000e-03 eta: 5:57:08 time: 0.1831 data_time: 0.0054 memory: 10464 grad_norm: 6.8967 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.1607 loss: 2.1607 2022/09/07 19:47:59 - mmengine - INFO - Epoch(train) [20][1240/1793] lr: 7.5000e-03 eta: 5:56:53 time: 0.1751 data_time: 0.0081 memory: 10464 grad_norm: 7.3030 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.0356 loss: 2.0356 2022/09/07 19:48:03 - mmengine - INFO - Epoch(train) [20][1260/1793] lr: 7.5000e-03 eta: 5:56:38 time: 0.1739 data_time: 0.0082 memory: 10464 grad_norm: 7.0654 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3263 loss: 2.3263 2022/09/07 19:48:06 - mmengine - INFO - Epoch(train) [20][1280/1793] lr: 7.5000e-03 eta: 5:56:24 time: 0.1703 data_time: 0.0065 memory: 10464 grad_norm: 7.0820 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.0941 loss: 2.0941 2022/09/07 19:48:09 - mmengine - INFO - Epoch(train) [20][1300/1793] lr: 7.5000e-03 eta: 5:56:09 time: 0.1714 data_time: 0.0066 memory: 10464 grad_norm: 7.1837 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.4771 loss: 2.4771 2022/09/07 19:48:13 - mmengine - INFO - Epoch(train) [20][1320/1793] lr: 7.5000e-03 eta: 5:55:55 time: 0.1917 data_time: 0.0224 memory: 10464 grad_norm: 7.0363 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2888 loss: 2.2888 2022/09/07 19:48:17 - mmengine - INFO - Epoch(train) [20][1340/1793] lr: 7.5000e-03 eta: 5:55:40 time: 0.1741 data_time: 0.0058 memory: 10464 grad_norm: 7.1434 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0965 loss: 2.0965 2022/09/07 19:48:20 - mmengine - INFO - Epoch(train) [20][1360/1793] lr: 7.5000e-03 eta: 5:55:26 time: 0.1743 data_time: 0.0072 memory: 10464 grad_norm: 6.8524 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.1852 loss: 2.1852 2022/09/07 19:48:24 - mmengine - INFO - Epoch(train) [20][1380/1793] lr: 7.5000e-03 eta: 5:55:11 time: 0.1765 data_time: 0.0079 memory: 10464 grad_norm: 7.3785 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0446 loss: 2.0446 2022/09/07 19:48:28 - mmengine - INFO - Epoch(train) [20][1400/1793] lr: 7.5000e-03 eta: 5:54:58 time: 0.2263 data_time: 0.0059 memory: 10464 grad_norm: 7.0471 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.5352 loss: 2.5352 2022/09/07 19:48:32 - mmengine - INFO - Epoch(train) [20][1420/1793] lr: 7.5000e-03 eta: 5:54:44 time: 0.1791 data_time: 0.0079 memory: 10464 grad_norm: 7.2284 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.1213 loss: 2.1213 2022/09/07 19:48:38 - mmengine - INFO - Epoch(train) [20][1440/1793] lr: 7.5000e-03 eta: 5:54:34 time: 0.3184 data_time: 0.0085 memory: 10464 grad_norm: 7.1618 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.9620 loss: 1.9620 2022/09/07 19:48:42 - mmengine - INFO - Epoch(train) [20][1460/1793] lr: 7.5000e-03 eta: 5:54:20 time: 0.1843 data_time: 0.0079 memory: 10464 grad_norm: 6.9320 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.3678 loss: 2.3678 2022/09/07 19:48:45 - mmengine - INFO - Epoch(train) [20][1480/1793] lr: 7.5000e-03 eta: 5:54:05 time: 0.1778 data_time: 0.0090 memory: 10464 grad_norm: 7.1127 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4034 loss: 2.4034 2022/09/07 19:48:49 - mmengine - INFO - Epoch(train) [20][1500/1793] lr: 7.5000e-03 eta: 5:53:51 time: 0.1752 data_time: 0.0070 memory: 10464 grad_norm: 7.0333 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.2700 loss: 2.2700 2022/09/07 19:48:55 - mmengine - INFO - Epoch(train) [20][1520/1793] lr: 7.5000e-03 eta: 5:53:40 time: 0.3104 data_time: 0.0077 memory: 10464 grad_norm: 6.7832 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4229 loss: 2.4229 2022/09/07 19:49:01 - mmengine - INFO - Epoch(train) [20][1540/1793] lr: 7.5000e-03 eta: 5:53:29 time: 0.2701 data_time: 0.0091 memory: 10464 grad_norm: 7.0374 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5153 loss: 2.5153 2022/09/07 19:49:04 - mmengine - INFO - Epoch(train) [20][1560/1793] lr: 7.5000e-03 eta: 5:53:14 time: 0.1783 data_time: 0.0067 memory: 10464 grad_norm: 7.4707 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1930 loss: 2.1930 2022/09/07 19:49:08 - mmengine - INFO - Epoch(train) [20][1580/1793] lr: 7.5000e-03 eta: 5:53:00 time: 0.1749 data_time: 0.0061 memory: 10464 grad_norm: 7.0731 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.1675 loss: 2.1675 2022/09/07 19:49:11 - mmengine - INFO - Epoch(train) [20][1600/1793] lr: 7.5000e-03 eta: 5:52:46 time: 0.1859 data_time: 0.0083 memory: 10464 grad_norm: 7.3201 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.0334 loss: 2.0334 2022/09/07 19:49:16 - mmengine - INFO - Epoch(train) [20][1620/1793] lr: 7.5000e-03 eta: 5:52:34 time: 0.2432 data_time: 0.0062 memory: 10464 grad_norm: 6.7550 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0738 loss: 2.0738 2022/09/07 19:49:20 - mmengine - INFO - Epoch(train) [20][1640/1793] lr: 7.5000e-03 eta: 5:52:19 time: 0.1752 data_time: 0.0071 memory: 10464 grad_norm: 7.1786 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.4216 loss: 2.4216 2022/09/07 19:49:25 - mmengine - INFO - Epoch(train) [20][1660/1793] lr: 7.5000e-03 eta: 5:52:07 time: 0.2468 data_time: 0.0084 memory: 10464 grad_norm: 7.1978 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5100 loss: 2.5100 2022/09/07 19:49:28 - mmengine - INFO - Epoch(train) [20][1680/1793] lr: 7.5000e-03 eta: 5:51:52 time: 0.1729 data_time: 0.0074 memory: 10464 grad_norm: 7.3058 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.2016 loss: 2.2016 2022/09/07 19:49:32 - mmengine - INFO - Epoch(train) [20][1700/1793] lr: 7.5000e-03 eta: 5:51:38 time: 0.1772 data_time: 0.0050 memory: 10464 grad_norm: 7.2985 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4076 loss: 2.4076 2022/09/07 19:49:35 - mmengine - INFO - Epoch(train) [20][1720/1793] lr: 7.5000e-03 eta: 5:51:24 time: 0.1811 data_time: 0.0093 memory: 10464 grad_norm: 7.6588 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1634 loss: 2.1634 2022/09/07 19:49:39 - mmengine - INFO - Epoch(train) [20][1740/1793] lr: 7.5000e-03 eta: 5:51:10 time: 0.1763 data_time: 0.0076 memory: 10464 grad_norm: 7.0347 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2393 loss: 2.2393 2022/09/07 19:49:44 - mmengine - INFO - Epoch(train) [20][1760/1793] lr: 7.5000e-03 eta: 5:50:58 time: 0.2458 data_time: 0.0780 memory: 10464 grad_norm: 7.3783 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2754 loss: 2.2754 2022/09/07 19:49:47 - mmengine - INFO - Epoch(train) [20][1780/1793] lr: 7.5000e-03 eta: 5:50:43 time: 0.1746 data_time: 0.0079 memory: 10464 grad_norm: 7.0307 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3336 loss: 2.3336 2022/09/07 19:49:49 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:49:49 - mmengine - INFO - Epoch(train) [20][1793/1793] lr: 7.5000e-03 eta: 5:50:43 time: 0.1692 data_time: 0.0075 memory: 10464 grad_norm: 7.6860 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.6773 loss: 2.6773 2022/09/07 19:49:49 - mmengine - INFO - Saving checkpoint at 20 epochs 2022/09/07 19:49:53 - mmengine - INFO - Epoch(val) [20][20/241] eta: 0:00:12 time: 0.0582 data_time: 0.0091 memory: 1482 2022/09/07 19:49:54 - mmengine - INFO - Epoch(val) [20][40/241] eta: 0:00:10 time: 0.0535 data_time: 0.0052 memory: 1482 2022/09/07 19:49:55 - mmengine - INFO - Epoch(val) [20][60/241] eta: 0:00:09 time: 0.0538 data_time: 0.0053 memory: 1482 2022/09/07 19:49:56 - mmengine - INFO - Epoch(val) [20][80/241] eta: 0:00:08 time: 0.0543 data_time: 0.0056 memory: 1482 2022/09/07 19:49:57 - mmengine - INFO - Epoch(val) [20][100/241] eta: 0:00:07 time: 0.0536 data_time: 0.0052 memory: 1482 2022/09/07 19:49:58 - mmengine - INFO - Epoch(val) [20][120/241] eta: 0:00:06 time: 0.0535 data_time: 0.0051 memory: 1482 2022/09/07 19:49:59 - mmengine - INFO - Epoch(val) [20][140/241] eta: 0:00:05 time: 0.0536 data_time: 0.0051 memory: 1482 2022/09/07 19:50:00 - mmengine - INFO - Epoch(val) [20][160/241] eta: 0:00:04 time: 0.0534 data_time: 0.0048 memory: 1482 2022/09/07 19:50:01 - mmengine - INFO - Epoch(val) [20][180/241] eta: 0:00:03 time: 0.0534 data_time: 0.0049 memory: 1482 2022/09/07 19:50:02 - mmengine - INFO - Epoch(val) [20][200/241] eta: 0:00:02 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 19:50:03 - mmengine - INFO - Epoch(val) [20][220/241] eta: 0:00:01 time: 0.0528 data_time: 0.0046 memory: 1482 2022/09/07 19:50:04 - mmengine - INFO - Epoch(val) [20][240/241] eta: 0:00:00 time: 0.0557 data_time: 0.0052 memory: 1482 2022/09/07 19:50:05 - mmengine - INFO - Epoch(val) [20][241/241] acc/top1: 0.3259 acc/top5: 0.6201 acc/mean1: 0.2971 2022/09/07 19:50:10 - mmengine - INFO - Epoch(train) [21][20/1793] lr: 7.5000e-03 eta: 5:50:18 time: 0.2361 data_time: 0.0669 memory: 10464 grad_norm: 7.0975 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3686 loss: 2.3686 2022/09/07 19:50:13 - mmengine - INFO - Epoch(train) [21][40/1793] lr: 7.5000e-03 eta: 5:50:04 time: 0.1735 data_time: 0.0055 memory: 10464 grad_norm: 7.1468 top1_acc: 0.0000 top5_acc: 0.8333 loss_cls: 2.1965 loss: 2.1965 2022/09/07 19:50:17 - mmengine - INFO - Epoch(train) [21][60/1793] lr: 7.5000e-03 eta: 5:49:50 time: 0.1792 data_time: 0.0064 memory: 10464 grad_norm: 7.2247 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4239 loss: 2.4239 2022/09/07 19:50:20 - mmengine - INFO - Epoch(train) [21][80/1793] lr: 7.5000e-03 eta: 5:49:35 time: 0.1781 data_time: 0.0085 memory: 10464 grad_norm: 6.9562 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.0731 loss: 2.0731 2022/09/07 19:50:25 - mmengine - INFO - Epoch(train) [21][100/1793] lr: 7.5000e-03 eta: 5:49:23 time: 0.2409 data_time: 0.0069 memory: 10464 grad_norm: 7.4436 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.4115 loss: 2.4115 2022/09/07 19:50:29 - mmengine - INFO - Epoch(train) [21][120/1793] lr: 7.5000e-03 eta: 5:49:09 time: 0.1755 data_time: 0.0070 memory: 10464 grad_norm: 7.1666 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2755 loss: 2.2755 2022/09/07 19:50:34 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:50:34 - mmengine - INFO - Epoch(train) [21][140/1793] lr: 7.5000e-03 eta: 5:48:57 time: 0.2474 data_time: 0.0750 memory: 10464 grad_norm: 7.2380 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3023 loss: 2.3023 2022/09/07 19:50:39 - mmengine - INFO - Epoch(train) [21][160/1793] lr: 7.5000e-03 eta: 5:48:45 time: 0.2418 data_time: 0.0061 memory: 10464 grad_norm: 7.0925 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1746 loss: 2.1746 2022/09/07 19:50:42 - mmengine - INFO - Epoch(train) [21][180/1793] lr: 7.5000e-03 eta: 5:48:30 time: 0.1708 data_time: 0.0063 memory: 10464 grad_norm: 7.2391 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.0557 loss: 2.0557 2022/09/07 19:50:46 - mmengine - INFO - Epoch(train) [21][200/1793] lr: 7.5000e-03 eta: 5:48:16 time: 0.1780 data_time: 0.0097 memory: 10464 grad_norm: 7.2067 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0002 loss: 2.0002 2022/09/07 19:50:49 - mmengine - INFO - Epoch(train) [21][220/1793] lr: 7.5000e-03 eta: 5:48:02 time: 0.1751 data_time: 0.0060 memory: 10464 grad_norm: 7.2759 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0996 loss: 2.0996 2022/09/07 19:50:55 - mmengine - INFO - Epoch(train) [21][240/1793] lr: 7.5000e-03 eta: 5:47:51 time: 0.2919 data_time: 0.0070 memory: 10464 grad_norm: 6.7812 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2653 loss: 2.2653 2022/09/07 19:50:58 - mmengine - INFO - Epoch(train) [21][260/1793] lr: 7.5000e-03 eta: 5:47:37 time: 0.1749 data_time: 0.0090 memory: 10464 grad_norm: 6.9155 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1563 loss: 2.1563 2022/09/07 19:51:02 - mmengine - INFO - Epoch(train) [21][280/1793] lr: 7.5000e-03 eta: 5:47:23 time: 0.1747 data_time: 0.0062 memory: 10464 grad_norm: 7.4045 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0433 loss: 2.0433 2022/09/07 19:51:06 - mmengine - INFO - Epoch(train) [21][300/1793] lr: 7.5000e-03 eta: 5:47:09 time: 0.1864 data_time: 0.0062 memory: 10464 grad_norm: 7.2389 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.3830 loss: 2.3830 2022/09/07 19:51:10 - mmengine - INFO - Epoch(train) [21][320/1793] lr: 7.5000e-03 eta: 5:46:57 time: 0.2290 data_time: 0.0084 memory: 10464 grad_norm: 6.9321 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1102 loss: 2.1102 2022/09/07 19:51:14 - mmengine - INFO - Epoch(train) [21][340/1793] lr: 7.5000e-03 eta: 5:46:43 time: 0.1754 data_time: 0.0063 memory: 10464 grad_norm: 7.1840 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1230 loss: 2.1230 2022/09/07 19:51:17 - mmengine - INFO - Epoch(train) [21][360/1793] lr: 7.5000e-03 eta: 5:46:28 time: 0.1778 data_time: 0.0070 memory: 10464 grad_norm: 7.1102 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.2338 loss: 2.2338 2022/09/07 19:51:21 - mmengine - INFO - Epoch(train) [21][380/1793] lr: 7.5000e-03 eta: 5:46:14 time: 0.1765 data_time: 0.0082 memory: 10464 grad_norm: 7.3832 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5508 loss: 2.5508 2022/09/07 19:51:24 - mmengine - INFO - Epoch(train) [21][400/1793] lr: 7.5000e-03 eta: 5:46:00 time: 0.1722 data_time: 0.0067 memory: 10464 grad_norm: 6.9748 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.9900 loss: 1.9900 2022/09/07 19:51:28 - mmengine - INFO - Epoch(train) [21][420/1793] lr: 7.5000e-03 eta: 5:45:46 time: 0.1731 data_time: 0.0068 memory: 10464 grad_norm: 7.2176 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.3274 loss: 2.3274 2022/09/07 19:51:31 - mmengine - INFO - Epoch(train) [21][440/1793] lr: 7.5000e-03 eta: 5:45:32 time: 0.1741 data_time: 0.0084 memory: 10464 grad_norm: 7.0388 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.9911 loss: 1.9911 2022/09/07 19:51:36 - mmengine - INFO - Epoch(train) [21][460/1793] lr: 7.5000e-03 eta: 5:45:20 time: 0.2471 data_time: 0.0073 memory: 10464 grad_norm: 7.2863 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1744 loss: 2.1744 2022/09/07 19:51:40 - mmengine - INFO - Epoch(train) [21][480/1793] lr: 7.5000e-03 eta: 5:45:06 time: 0.1782 data_time: 0.0061 memory: 10464 grad_norm: 6.8135 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2183 loss: 2.2183 2022/09/07 19:51:44 - mmengine - INFO - Epoch(train) [21][500/1793] lr: 7.5000e-03 eta: 5:44:54 time: 0.2376 data_time: 0.0089 memory: 10464 grad_norm: 7.1609 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3051 loss: 2.3051 2022/09/07 19:51:48 - mmengine - INFO - Epoch(train) [21][520/1793] lr: 7.5000e-03 eta: 5:44:40 time: 0.1769 data_time: 0.0069 memory: 10464 grad_norm: 7.2056 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.2462 loss: 2.2462 2022/09/07 19:51:53 - mmengine - INFO - Epoch(train) [21][540/1793] lr: 7.5000e-03 eta: 5:44:28 time: 0.2555 data_time: 0.0066 memory: 10464 grad_norm: 7.2274 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4467 loss: 2.4467 2022/09/07 19:51:57 - mmengine - INFO - Epoch(train) [21][560/1793] lr: 7.5000e-03 eta: 5:44:15 time: 0.1801 data_time: 0.0092 memory: 10464 grad_norm: 7.1656 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0955 loss: 2.0955 2022/09/07 19:52:00 - mmengine - INFO - Epoch(train) [21][580/1793] lr: 7.5000e-03 eta: 5:44:01 time: 0.1732 data_time: 0.0061 memory: 10464 grad_norm: 7.2168 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2922 loss: 2.2922 2022/09/07 19:52:04 - mmengine - INFO - Epoch(train) [21][600/1793] lr: 7.5000e-03 eta: 5:43:47 time: 0.1778 data_time: 0.0062 memory: 10464 grad_norm: 7.1300 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 2.2149 loss: 2.2149 2022/09/07 19:52:09 - mmengine - INFO - Epoch(train) [21][620/1793] lr: 7.5000e-03 eta: 5:43:35 time: 0.2410 data_time: 0.0094 memory: 10464 grad_norm: 7.4912 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.2264 loss: 2.2264 2022/09/07 19:52:12 - mmengine - INFO - Epoch(train) [21][640/1793] lr: 7.5000e-03 eta: 5:43:21 time: 0.1824 data_time: 0.0060 memory: 10464 grad_norm: 7.6301 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2388 loss: 2.2388 2022/09/07 19:52:16 - mmengine - INFO - Epoch(train) [21][660/1793] lr: 7.5000e-03 eta: 5:43:07 time: 0.1869 data_time: 0.0069 memory: 10464 grad_norm: 6.9833 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0525 loss: 2.0525 2022/09/07 19:52:20 - mmengine - INFO - Epoch(train) [21][680/1793] lr: 7.5000e-03 eta: 5:42:53 time: 0.1779 data_time: 0.0099 memory: 10464 grad_norm: 7.4525 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2751 loss: 2.2751 2022/09/07 19:52:25 - mmengine - INFO - Epoch(train) [21][700/1793] lr: 7.5000e-03 eta: 5:42:42 time: 0.2592 data_time: 0.0060 memory: 10464 grad_norm: 7.0117 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.2338 loss: 2.2338 2022/09/07 19:52:28 - mmengine - INFO - Epoch(train) [21][720/1793] lr: 7.5000e-03 eta: 5:42:28 time: 0.1767 data_time: 0.0072 memory: 10464 grad_norm: 7.2478 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6713 loss: 2.6713 2022/09/07 19:52:32 - mmengine - INFO - Epoch(train) [21][740/1793] lr: 7.5000e-03 eta: 5:42:14 time: 0.1784 data_time: 0.0072 memory: 10464 grad_norm: 7.2533 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.3101 loss: 2.3101 2022/09/07 19:52:35 - mmengine - INFO - Epoch(train) [21][760/1793] lr: 7.5000e-03 eta: 5:42:00 time: 0.1761 data_time: 0.0066 memory: 10464 grad_norm: 7.1138 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1967 loss: 2.1967 2022/09/07 19:52:39 - mmengine - INFO - Epoch(train) [21][780/1793] lr: 7.5000e-03 eta: 5:41:47 time: 0.1772 data_time: 0.0063 memory: 10464 grad_norm: 7.0949 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3083 loss: 2.3083 2022/09/07 19:52:42 - mmengine - INFO - Epoch(train) [21][800/1793] lr: 7.5000e-03 eta: 5:41:33 time: 0.1765 data_time: 0.0084 memory: 10464 grad_norm: 7.1769 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3958 loss: 2.3958 2022/09/07 19:52:47 - mmengine - INFO - Epoch(train) [21][820/1793] lr: 7.5000e-03 eta: 5:41:20 time: 0.2082 data_time: 0.0070 memory: 10464 grad_norm: 7.0789 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1098 loss: 2.1098 2022/09/07 19:52:50 - mmengine - INFO - Epoch(train) [21][840/1793] lr: 7.5000e-03 eta: 5:41:06 time: 0.1748 data_time: 0.0060 memory: 10464 grad_norm: 7.3587 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2359 loss: 2.2359 2022/09/07 19:52:54 - mmengine - INFO - Epoch(train) [21][860/1793] lr: 7.5000e-03 eta: 5:40:52 time: 0.1831 data_time: 0.0083 memory: 10464 grad_norm: 7.1108 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3005 loss: 2.3005 2022/09/07 19:52:57 - mmengine - INFO - Epoch(train) [21][880/1793] lr: 7.5000e-03 eta: 5:40:39 time: 0.1801 data_time: 0.0068 memory: 10464 grad_norm: 7.3309 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4645 loss: 2.4645 2022/09/07 19:53:01 - mmengine - INFO - Epoch(train) [21][900/1793] lr: 7.5000e-03 eta: 5:40:25 time: 0.1714 data_time: 0.0062 memory: 10464 grad_norm: 7.2963 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.5129 loss: 2.5129 2022/09/07 19:53:06 - mmengine - INFO - Epoch(train) [21][920/1793] lr: 7.5000e-03 eta: 5:40:13 time: 0.2579 data_time: 0.0088 memory: 10464 grad_norm: 7.0545 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.4409 loss: 2.4409 2022/09/07 19:53:09 - mmengine - INFO - Epoch(train) [21][940/1793] lr: 7.5000e-03 eta: 5:40:00 time: 0.1718 data_time: 0.0061 memory: 10464 grad_norm: 7.4196 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.0394 loss: 2.0394 2022/09/07 19:53:13 - mmengine - INFO - Epoch(train) [21][960/1793] lr: 7.5000e-03 eta: 5:39:46 time: 0.1775 data_time: 0.0065 memory: 10464 grad_norm: 7.2462 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0866 loss: 2.0866 2022/09/07 19:53:16 - mmengine - INFO - Epoch(train) [21][980/1793] lr: 7.5000e-03 eta: 5:39:32 time: 0.1775 data_time: 0.0092 memory: 10464 grad_norm: 7.6060 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1173 loss: 2.1173 2022/09/07 19:53:20 - mmengine - INFO - Epoch(train) [21][1000/1793] lr: 7.5000e-03 eta: 5:39:18 time: 0.1734 data_time: 0.0070 memory: 10464 grad_norm: 7.2984 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.3382 loss: 2.3382 2022/09/07 19:53:25 - mmengine - INFO - Epoch(train) [21][1020/1793] lr: 7.5000e-03 eta: 5:39:07 time: 0.2436 data_time: 0.0054 memory: 10464 grad_norm: 7.0615 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.1865 loss: 2.1865 2022/09/07 19:53:28 - mmengine - INFO - Epoch(train) [21][1040/1793] lr: 7.5000e-03 eta: 5:38:53 time: 0.1767 data_time: 0.0096 memory: 10464 grad_norm: 7.0560 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1163 loss: 2.1163 2022/09/07 19:53:32 - mmengine - INFO - Epoch(train) [21][1060/1793] lr: 7.5000e-03 eta: 5:38:40 time: 0.1943 data_time: 0.0060 memory: 10464 grad_norm: 7.1527 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1778 loss: 2.1778 2022/09/07 19:53:38 - mmengine - INFO - Epoch(train) [21][1080/1793] lr: 7.5000e-03 eta: 5:38:29 time: 0.2691 data_time: 0.0070 memory: 10464 grad_norm: 7.2487 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3062 loss: 2.3062 2022/09/07 19:53:41 - mmengine - INFO - Epoch(train) [21][1100/1793] lr: 7.5000e-03 eta: 5:38:15 time: 0.1757 data_time: 0.0086 memory: 10464 grad_norm: 7.3015 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3314 loss: 2.3314 2022/09/07 19:53:45 - mmengine - INFO - Epoch(train) [21][1120/1793] lr: 7.5000e-03 eta: 5:38:01 time: 0.1733 data_time: 0.0058 memory: 10464 grad_norm: 7.0786 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0663 loss: 2.0663 2022/09/07 19:53:48 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:53:48 - mmengine - INFO - Epoch(train) [21][1140/1793] lr: 7.5000e-03 eta: 5:37:48 time: 0.1717 data_time: 0.0065 memory: 10464 grad_norm: 7.2226 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2885 loss: 2.2885 2022/09/07 19:53:52 - mmengine - INFO - Epoch(train) [21][1160/1793] lr: 7.5000e-03 eta: 5:37:34 time: 0.1797 data_time: 0.0096 memory: 10464 grad_norm: 6.9218 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3277 loss: 2.3277 2022/09/07 19:53:55 - mmengine - INFO - Epoch(train) [21][1180/1793] lr: 7.5000e-03 eta: 5:37:20 time: 0.1741 data_time: 0.0060 memory: 10464 grad_norm: 7.6494 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5212 loss: 2.5212 2022/09/07 19:53:59 - mmengine - INFO - Epoch(train) [21][1200/1793] lr: 7.5000e-03 eta: 5:37:07 time: 0.1710 data_time: 0.0063 memory: 10464 grad_norm: 7.0719 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.1348 loss: 2.1348 2022/09/07 19:54:02 - mmengine - INFO - Epoch(train) [21][1220/1793] lr: 7.5000e-03 eta: 5:36:53 time: 0.1816 data_time: 0.0090 memory: 10464 grad_norm: 7.0517 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1723 loss: 2.1723 2022/09/07 19:54:06 - mmengine - INFO - Epoch(train) [21][1240/1793] lr: 7.5000e-03 eta: 5:36:39 time: 0.1733 data_time: 0.0066 memory: 10464 grad_norm: 7.0739 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.1983 loss: 2.1983 2022/09/07 19:54:09 - mmengine - INFO - Epoch(train) [21][1260/1793] lr: 7.5000e-03 eta: 5:36:26 time: 0.1752 data_time: 0.0065 memory: 10464 grad_norm: 7.2438 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4790 loss: 2.4790 2022/09/07 19:54:13 - mmengine - INFO - Epoch(train) [21][1280/1793] lr: 7.5000e-03 eta: 5:36:12 time: 0.1805 data_time: 0.0110 memory: 10464 grad_norm: 7.3773 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1864 loss: 2.1864 2022/09/07 19:54:16 - mmengine - INFO - Epoch(train) [21][1300/1793] lr: 7.5000e-03 eta: 5:35:59 time: 0.1762 data_time: 0.0049 memory: 10464 grad_norm: 6.9427 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4185 loss: 2.4185 2022/09/07 19:54:21 - mmengine - INFO - Epoch(train) [21][1320/1793] lr: 7.5000e-03 eta: 5:35:47 time: 0.2429 data_time: 0.0061 memory: 10464 grad_norm: 7.0645 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.9816 loss: 1.9816 2022/09/07 19:54:25 - mmengine - INFO - Epoch(train) [21][1340/1793] lr: 7.5000e-03 eta: 5:35:34 time: 0.1762 data_time: 0.0087 memory: 10464 grad_norm: 7.1866 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2375 loss: 2.2375 2022/09/07 19:54:30 - mmengine - INFO - Epoch(train) [21][1360/1793] lr: 7.5000e-03 eta: 5:35:22 time: 0.2408 data_time: 0.0063 memory: 10464 grad_norm: 7.5235 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3893 loss: 2.3893 2022/09/07 19:54:33 - mmengine - INFO - Epoch(train) [21][1380/1793] lr: 7.5000e-03 eta: 5:35:09 time: 0.1812 data_time: 0.0067 memory: 10464 grad_norm: 7.0696 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1241 loss: 2.1241 2022/09/07 19:54:38 - mmengine - INFO - Epoch(train) [21][1400/1793] lr: 7.5000e-03 eta: 5:34:57 time: 0.2448 data_time: 0.0088 memory: 10464 grad_norm: 7.4276 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.1851 loss: 2.1851 2022/09/07 19:54:41 - mmengine - INFO - Epoch(train) [21][1420/1793] lr: 7.5000e-03 eta: 5:34:43 time: 0.1708 data_time: 0.0066 memory: 10464 grad_norm: 7.3940 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2626 loss: 2.2626 2022/09/07 19:54:47 - mmengine - INFO - Epoch(train) [21][1440/1793] lr: 7.5000e-03 eta: 5:34:32 time: 0.2585 data_time: 0.0076 memory: 10464 grad_norm: 7.2927 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0330 loss: 2.0330 2022/09/07 19:54:50 - mmengine - INFO - Epoch(train) [21][1460/1793] lr: 7.5000e-03 eta: 5:34:19 time: 0.1775 data_time: 0.0073 memory: 10464 grad_norm: 7.2955 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.1651 loss: 2.1651 2022/09/07 19:54:55 - mmengine - INFO - Epoch(train) [21][1480/1793] lr: 7.5000e-03 eta: 5:34:07 time: 0.2438 data_time: 0.0624 memory: 10464 grad_norm: 7.5173 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.1612 loss: 2.1612 2022/09/07 19:54:59 - mmengine - INFO - Epoch(train) [21][1500/1793] lr: 7.5000e-03 eta: 5:33:54 time: 0.1772 data_time: 0.0058 memory: 10464 grad_norm: 7.2079 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.9539 loss: 1.9539 2022/09/07 19:55:02 - mmengine - INFO - Epoch(train) [21][1520/1793] lr: 7.5000e-03 eta: 5:33:40 time: 0.1775 data_time: 0.0093 memory: 10464 grad_norm: 7.2608 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.9786 loss: 1.9786 2022/09/07 19:55:06 - mmengine - INFO - Epoch(train) [21][1540/1793] lr: 7.5000e-03 eta: 5:33:27 time: 0.1711 data_time: 0.0057 memory: 10464 grad_norm: 7.4499 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1280 loss: 2.1280 2022/09/07 19:55:09 - mmengine - INFO - Epoch(train) [21][1560/1793] lr: 7.5000e-03 eta: 5:33:13 time: 0.1729 data_time: 0.0061 memory: 10464 grad_norm: 7.1277 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.9526 loss: 1.9526 2022/09/07 19:55:13 - mmengine - INFO - Epoch(train) [21][1580/1793] lr: 7.5000e-03 eta: 5:33:00 time: 0.1835 data_time: 0.0096 memory: 10464 grad_norm: 7.1274 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.3803 loss: 2.3803 2022/09/07 19:55:16 - mmengine - INFO - Epoch(train) [21][1600/1793] lr: 7.5000e-03 eta: 5:32:47 time: 0.1867 data_time: 0.0057 memory: 10464 grad_norm: 7.2764 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.4035 loss: 2.4035 2022/09/07 19:55:22 - mmengine - INFO - Epoch(train) [21][1620/1793] lr: 7.5000e-03 eta: 5:32:36 time: 0.2598 data_time: 0.0066 memory: 10464 grad_norm: 7.4585 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3685 loss: 2.3685 2022/09/07 19:55:25 - mmengine - INFO - Epoch(train) [21][1640/1793] lr: 7.5000e-03 eta: 5:32:22 time: 0.1786 data_time: 0.0109 memory: 10464 grad_norm: 7.1589 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3891 loss: 2.3891 2022/09/07 19:55:29 - mmengine - INFO - Epoch(train) [21][1660/1793] lr: 7.5000e-03 eta: 5:32:09 time: 0.1775 data_time: 0.0050 memory: 10464 grad_norm: 6.9869 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3010 loss: 2.3010 2022/09/07 19:55:34 - mmengine - INFO - Epoch(train) [21][1680/1793] lr: 7.5000e-03 eta: 5:31:58 time: 0.2554 data_time: 0.0826 memory: 10464 grad_norm: 7.2725 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.2266 loss: 2.2266 2022/09/07 19:55:38 - mmengine - INFO - Epoch(train) [21][1700/1793] lr: 7.5000e-03 eta: 5:31:45 time: 0.1813 data_time: 0.0082 memory: 10464 grad_norm: 7.0265 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1492 loss: 2.1492 2022/09/07 19:55:42 - mmengine - INFO - Epoch(train) [21][1720/1793] lr: 7.5000e-03 eta: 5:31:33 time: 0.2427 data_time: 0.0054 memory: 10464 grad_norm: 7.0696 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2602 loss: 2.2602 2022/09/07 19:55:48 - mmengine - INFO - Epoch(train) [21][1740/1793] lr: 7.5000e-03 eta: 5:31:23 time: 0.2851 data_time: 0.1054 memory: 10464 grad_norm: 7.1746 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1274 loss: 2.1274 2022/09/07 19:55:53 - mmengine - INFO - Epoch(train) [21][1760/1793] lr: 7.5000e-03 eta: 5:31:11 time: 0.2441 data_time: 0.0086 memory: 10464 grad_norm: 7.4834 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3367 loss: 2.3367 2022/09/07 19:55:57 - mmengine - INFO - Epoch(train) [21][1780/1793] lr: 7.5000e-03 eta: 5:30:59 time: 0.1921 data_time: 0.0071 memory: 10464 grad_norm: 7.5488 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1918 loss: 2.1918 2022/09/07 19:55:59 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:55:59 - mmengine - INFO - Epoch(train) [21][1793/1793] lr: 7.5000e-03 eta: 5:30:59 time: 0.1672 data_time: 0.0064 memory: 10464 grad_norm: 7.2963 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.3554 loss: 2.3554 2022/09/07 19:55:59 - mmengine - INFO - Saving checkpoint at 21 epochs 2022/09/07 19:56:02 - mmengine - INFO - Epoch(val) [21][20/241] eta: 0:00:13 time: 0.0601 data_time: 0.0106 memory: 1482 2022/09/07 19:56:03 - mmengine - INFO - Epoch(val) [21][40/241] eta: 0:00:10 time: 0.0546 data_time: 0.0056 memory: 1482 2022/09/07 19:56:05 - mmengine - INFO - Epoch(val) [21][60/241] eta: 0:00:09 time: 0.0535 data_time: 0.0051 memory: 1482 2022/09/07 19:56:06 - mmengine - INFO - Epoch(val) [21][80/241] eta: 0:00:08 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 19:56:07 - mmengine - INFO - Epoch(val) [21][100/241] eta: 0:00:07 time: 0.0541 data_time: 0.0051 memory: 1482 2022/09/07 19:56:08 - mmengine - INFO - Epoch(val) [21][120/241] eta: 0:00:06 time: 0.0534 data_time: 0.0050 memory: 1482 2022/09/07 19:56:09 - mmengine - INFO - Epoch(val) [21][140/241] eta: 0:00:05 time: 0.0544 data_time: 0.0058 memory: 1482 2022/09/07 19:56:10 - mmengine - INFO - Epoch(val) [21][160/241] eta: 0:00:04 time: 0.0531 data_time: 0.0045 memory: 1482 2022/09/07 19:56:11 - mmengine - INFO - Epoch(val) [21][180/241] eta: 0:00:03 time: 0.0547 data_time: 0.0062 memory: 1482 2022/09/07 19:56:12 - mmengine - INFO - Epoch(val) [21][200/241] eta: 0:00:02 time: 0.0541 data_time: 0.0053 memory: 1482 2022/09/07 19:56:13 - mmengine - INFO - Epoch(val) [21][220/241] eta: 0:00:01 time: 0.0530 data_time: 0.0048 memory: 1482 2022/09/07 19:56:14 - mmengine - INFO - Epoch(val) [21][240/241] eta: 0:00:00 time: 0.0529 data_time: 0.0048 memory: 1482 2022/09/07 19:56:15 - mmengine - INFO - Epoch(val) [21][241/241] acc/top1: 0.3216 acc/top5: 0.6110 acc/mean1: 0.2899 2022/09/07 19:56:20 - mmengine - INFO - Epoch(train) [22][20/1793] lr: 7.5000e-03 eta: 5:30:36 time: 0.2797 data_time: 0.0113 memory: 10464 grad_norm: 7.2280 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8757 loss: 1.8757 2022/09/07 19:56:25 - mmengine - INFO - Epoch(train) [22][40/1793] lr: 7.5000e-03 eta: 5:30:25 time: 0.2432 data_time: 0.0065 memory: 10464 grad_norm: 7.3331 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1396 loss: 2.1396 2022/09/07 19:56:29 - mmengine - INFO - Epoch(train) [22][60/1793] lr: 7.5000e-03 eta: 5:30:12 time: 0.1776 data_time: 0.0094 memory: 10464 grad_norm: 7.2519 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1461 loss: 2.1461 2022/09/07 19:56:33 - mmengine - INFO - Epoch(train) [22][80/1793] lr: 7.5000e-03 eta: 5:29:59 time: 0.1891 data_time: 0.0063 memory: 10464 grad_norm: 7.1347 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0730 loss: 2.0730 2022/09/07 19:56:36 - mmengine - INFO - Epoch(train) [22][100/1793] lr: 7.5000e-03 eta: 5:29:45 time: 0.1759 data_time: 0.0073 memory: 10464 grad_norm: 7.1005 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3084 loss: 2.3084 2022/09/07 19:56:40 - mmengine - INFO - Epoch(train) [22][120/1793] lr: 7.5000e-03 eta: 5:29:32 time: 0.1775 data_time: 0.0096 memory: 10464 grad_norm: 7.2145 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3987 loss: 2.3987 2022/09/07 19:56:43 - mmengine - INFO - Epoch(train) [22][140/1793] lr: 7.5000e-03 eta: 5:29:19 time: 0.1772 data_time: 0.0070 memory: 10464 grad_norm: 7.4398 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2470 loss: 2.2470 2022/09/07 19:56:47 - mmengine - INFO - Epoch(train) [22][160/1793] lr: 7.5000e-03 eta: 5:29:06 time: 0.1746 data_time: 0.0069 memory: 10464 grad_norm: 7.1102 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0201 loss: 2.0201 2022/09/07 19:56:50 - mmengine - INFO - Epoch(train) [22][180/1793] lr: 7.5000e-03 eta: 5:28:52 time: 0.1751 data_time: 0.0099 memory: 10464 grad_norm: 7.0724 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2655 loss: 2.2655 2022/09/07 19:56:54 - mmengine - INFO - Epoch(train) [22][200/1793] lr: 7.5000e-03 eta: 5:28:39 time: 0.1793 data_time: 0.0071 memory: 10464 grad_norm: 7.3025 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2828 loss: 2.2828 2022/09/07 19:56:59 - mmengine - INFO - Epoch(train) [22][220/1793] lr: 7.5000e-03 eta: 5:28:28 time: 0.2646 data_time: 0.0071 memory: 10464 grad_norm: 7.1656 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2954 loss: 2.2954 2022/09/07 19:57:03 - mmengine - INFO - Epoch(train) [22][240/1793] lr: 7.5000e-03 eta: 5:28:15 time: 0.1744 data_time: 0.0087 memory: 10464 grad_norm: 7.2377 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5186 loss: 2.5186 2022/09/07 19:57:06 - mmengine - INFO - Epoch(train) [22][260/1793] lr: 7.5000e-03 eta: 5:28:02 time: 0.1753 data_time: 0.0079 memory: 10464 grad_norm: 7.2279 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.0364 loss: 2.0364 2022/09/07 19:57:10 - mmengine - INFO - Epoch(train) [22][280/1793] lr: 7.5000e-03 eta: 5:27:49 time: 0.1748 data_time: 0.0062 memory: 10464 grad_norm: 7.2342 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8329 loss: 1.8329 2022/09/07 19:57:13 - mmengine - INFO - Epoch(train) [22][300/1793] lr: 7.5000e-03 eta: 5:27:36 time: 0.1810 data_time: 0.0085 memory: 10464 grad_norm: 7.1654 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.4102 loss: 2.4102 2022/09/07 19:57:18 - mmengine - INFO - Epoch(train) [22][320/1793] lr: 7.5000e-03 eta: 5:27:24 time: 0.2147 data_time: 0.0082 memory: 10464 grad_norm: 7.6493 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2793 loss: 2.2793 2022/09/07 19:57:21 - mmengine - INFO - Epoch(train) [22][340/1793] lr: 7.5000e-03 eta: 5:27:10 time: 0.1706 data_time: 0.0054 memory: 10464 grad_norm: 7.6629 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2576 loss: 2.2576 2022/09/07 19:57:22 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 19:57:24 - mmengine - INFO - Epoch(train) [22][360/1793] lr: 7.5000e-03 eta: 5:26:57 time: 0.1737 data_time: 0.0082 memory: 10464 grad_norm: 7.1550 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.6000 loss: 2.6000 2022/09/07 19:57:28 - mmengine - INFO - Epoch(train) [22][380/1793] lr: 7.5000e-03 eta: 5:26:44 time: 0.1741 data_time: 0.0072 memory: 10464 grad_norm: 7.3594 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.0372 loss: 2.0372 2022/09/07 19:57:31 - mmengine - INFO - Epoch(train) [22][400/1793] lr: 7.5000e-03 eta: 5:26:31 time: 0.1752 data_time: 0.0057 memory: 10464 grad_norm: 7.2920 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3364 loss: 2.3364 2022/09/07 19:57:36 - mmengine - INFO - Epoch(train) [22][420/1793] lr: 7.5000e-03 eta: 5:26:19 time: 0.2265 data_time: 0.0099 memory: 10464 grad_norm: 6.9567 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3727 loss: 2.3727 2022/09/07 19:57:40 - mmengine - INFO - Epoch(train) [22][440/1793] lr: 7.5000e-03 eta: 5:26:06 time: 0.1821 data_time: 0.0063 memory: 10464 grad_norm: 7.1504 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.1788 loss: 2.1788 2022/09/07 19:57:43 - mmengine - INFO - Epoch(train) [22][460/1793] lr: 7.5000e-03 eta: 5:25:53 time: 0.1760 data_time: 0.0062 memory: 10464 grad_norm: 7.3675 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6953 loss: 2.6953 2022/09/07 19:57:47 - mmengine - INFO - Epoch(train) [22][480/1793] lr: 7.5000e-03 eta: 5:25:41 time: 0.2119 data_time: 0.0089 memory: 10464 grad_norm: 6.9288 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0432 loss: 2.0432 2022/09/07 19:57:51 - mmengine - INFO - Epoch(train) [22][500/1793] lr: 7.5000e-03 eta: 5:25:28 time: 0.1725 data_time: 0.0067 memory: 10464 grad_norm: 7.4203 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0751 loss: 2.0751 2022/09/07 19:57:54 - mmengine - INFO - Epoch(train) [22][520/1793] lr: 7.5000e-03 eta: 5:25:15 time: 0.1763 data_time: 0.0067 memory: 10464 grad_norm: 7.1191 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.3209 loss: 2.3209 2022/09/07 19:57:58 - mmengine - INFO - Epoch(train) [22][540/1793] lr: 7.5000e-03 eta: 5:25:02 time: 0.1838 data_time: 0.0106 memory: 10464 grad_norm: 7.0459 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3508 loss: 2.3508 2022/09/07 19:58:02 - mmengine - INFO - Epoch(train) [22][560/1793] lr: 7.5000e-03 eta: 5:24:49 time: 0.1745 data_time: 0.0054 memory: 10464 grad_norm: 6.9640 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1282 loss: 2.1282 2022/09/07 19:58:05 - mmengine - INFO - Epoch(train) [22][580/1793] lr: 7.5000e-03 eta: 5:24:36 time: 0.1757 data_time: 0.0067 memory: 10464 grad_norm: 7.0380 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5720 loss: 2.5720 2022/09/07 19:58:09 - mmengine - INFO - Epoch(train) [22][600/1793] lr: 7.5000e-03 eta: 5:24:23 time: 0.1755 data_time: 0.0089 memory: 10464 grad_norm: 7.0706 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0464 loss: 2.0464 2022/09/07 19:58:12 - mmengine - INFO - Epoch(train) [22][620/1793] lr: 7.5000e-03 eta: 5:24:10 time: 0.1925 data_time: 0.0062 memory: 10464 grad_norm: 7.3414 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1950 loss: 2.1950 2022/09/07 19:58:16 - mmengine - INFO - Epoch(train) [22][640/1793] lr: 7.5000e-03 eta: 5:23:57 time: 0.1770 data_time: 0.0078 memory: 10464 grad_norm: 7.0443 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 1.6851 loss: 1.6851 2022/09/07 19:58:20 - mmengine - INFO - Epoch(train) [22][660/1793] lr: 7.5000e-03 eta: 5:23:45 time: 0.1998 data_time: 0.0090 memory: 10464 grad_norm: 7.0274 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2073 loss: 2.2073 2022/09/07 19:58:23 - mmengine - INFO - Epoch(train) [22][680/1793] lr: 7.5000e-03 eta: 5:23:32 time: 0.1749 data_time: 0.0065 memory: 10464 grad_norm: 7.1204 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4146 loss: 2.4146 2022/09/07 19:58:27 - mmengine - INFO - Epoch(train) [22][700/1793] lr: 7.5000e-03 eta: 5:23:19 time: 0.1741 data_time: 0.0066 memory: 10464 grad_norm: 7.0568 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2028 loss: 2.2028 2022/09/07 19:58:30 - mmengine - INFO - Epoch(train) [22][720/1793] lr: 7.5000e-03 eta: 5:23:06 time: 0.1742 data_time: 0.0083 memory: 10464 grad_norm: 7.3245 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1442 loss: 2.1442 2022/09/07 19:58:34 - mmengine - INFO - Epoch(train) [22][740/1793] lr: 7.5000e-03 eta: 5:22:53 time: 0.1778 data_time: 0.0066 memory: 10464 grad_norm: 7.4311 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2770 loss: 2.2770 2022/09/07 19:58:38 - mmengine - INFO - Epoch(train) [22][760/1793] lr: 7.5000e-03 eta: 5:22:40 time: 0.1786 data_time: 0.0080 memory: 10464 grad_norm: 7.2898 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3495 loss: 2.3495 2022/09/07 19:58:41 - mmengine - INFO - Epoch(train) [22][780/1793] lr: 7.5000e-03 eta: 5:22:27 time: 0.1753 data_time: 0.0084 memory: 10464 grad_norm: 7.9241 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.4094 loss: 2.4094 2022/09/07 19:58:45 - mmengine - INFO - Epoch(train) [22][800/1793] lr: 7.5000e-03 eta: 5:22:14 time: 0.1740 data_time: 0.0066 memory: 10464 grad_norm: 7.1381 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1579 loss: 2.1579 2022/09/07 19:58:48 - mmengine - INFO - Epoch(train) [22][820/1793] lr: 7.5000e-03 eta: 5:22:01 time: 0.1722 data_time: 0.0075 memory: 10464 grad_norm: 7.5856 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.3567 loss: 2.3567 2022/09/07 19:58:52 - mmengine - INFO - Epoch(train) [22][840/1793] lr: 7.5000e-03 eta: 5:21:48 time: 0.1738 data_time: 0.0080 memory: 10464 grad_norm: 7.3627 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.9442 loss: 1.9442 2022/09/07 19:58:55 - mmengine - INFO - Epoch(train) [22][860/1793] lr: 7.5000e-03 eta: 5:21:36 time: 0.1910 data_time: 0.0073 memory: 10464 grad_norm: 7.4519 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1969 loss: 2.1969 2022/09/07 19:58:59 - mmengine - INFO - Epoch(train) [22][880/1793] lr: 7.5000e-03 eta: 5:21:23 time: 0.1729 data_time: 0.0070 memory: 10464 grad_norm: 7.2985 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2567 loss: 2.2567 2022/09/07 19:59:03 - mmengine - INFO - Epoch(train) [22][900/1793] lr: 7.5000e-03 eta: 5:21:10 time: 0.1954 data_time: 0.0101 memory: 10464 grad_norm: 7.4408 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3192 loss: 2.3192 2022/09/07 19:59:06 - mmengine - INFO - Epoch(train) [22][920/1793] lr: 7.5000e-03 eta: 5:20:57 time: 0.1744 data_time: 0.0067 memory: 10464 grad_norm: 7.0862 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3164 loss: 2.3164 2022/09/07 19:59:10 - mmengine - INFO - Epoch(train) [22][940/1793] lr: 7.5000e-03 eta: 5:20:45 time: 0.2125 data_time: 0.0066 memory: 10464 grad_norm: 7.0435 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.5606 loss: 2.5606 2022/09/07 19:59:14 - mmengine - INFO - Epoch(train) [22][960/1793] lr: 7.5000e-03 eta: 5:20:33 time: 0.1879 data_time: 0.0092 memory: 10464 grad_norm: 7.1464 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1363 loss: 2.1363 2022/09/07 19:59:18 - mmengine - INFO - Epoch(train) [22][980/1793] lr: 7.5000e-03 eta: 5:20:20 time: 0.1780 data_time: 0.0081 memory: 10464 grad_norm: 7.3141 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2342 loss: 2.2342 2022/09/07 19:59:21 - mmengine - INFO - Epoch(train) [22][1000/1793] lr: 7.5000e-03 eta: 5:20:07 time: 0.1731 data_time: 0.0061 memory: 10464 grad_norm: 7.3016 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0400 loss: 2.0400 2022/09/07 19:59:25 - mmengine - INFO - Epoch(train) [22][1020/1793] lr: 7.5000e-03 eta: 5:19:55 time: 0.1903 data_time: 0.0099 memory: 10464 grad_norm: 7.2333 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3171 loss: 2.3171 2022/09/07 19:59:29 - mmengine - INFO - Epoch(train) [22][1040/1793] lr: 7.5000e-03 eta: 5:19:42 time: 0.1727 data_time: 0.0062 memory: 10464 grad_norm: 7.5310 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2795 loss: 2.2795 2022/09/07 19:59:32 - mmengine - INFO - Epoch(train) [22][1060/1793] lr: 7.5000e-03 eta: 5:19:29 time: 0.1724 data_time: 0.0066 memory: 10464 grad_norm: 7.1409 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.2267 loss: 2.2267 2022/09/07 19:59:36 - mmengine - INFO - Epoch(train) [22][1080/1793] lr: 7.5000e-03 eta: 5:19:16 time: 0.1873 data_time: 0.0091 memory: 10464 grad_norm: 7.3363 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0440 loss: 2.0440 2022/09/07 19:59:40 - mmengine - INFO - Epoch(train) [22][1100/1793] lr: 7.5000e-03 eta: 5:19:04 time: 0.1921 data_time: 0.0063 memory: 10464 grad_norm: 7.4688 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4732 loss: 2.4732 2022/09/07 19:59:43 - mmengine - INFO - Epoch(train) [22][1120/1793] lr: 7.5000e-03 eta: 5:18:51 time: 0.1751 data_time: 0.0061 memory: 10464 grad_norm: 7.1101 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2313 loss: 2.2313 2022/09/07 19:59:47 - mmengine - INFO - Epoch(train) [22][1140/1793] lr: 7.5000e-03 eta: 5:18:38 time: 0.1758 data_time: 0.0102 memory: 10464 grad_norm: 7.1377 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5522 loss: 2.5522 2022/09/07 19:59:50 - mmengine - INFO - Epoch(train) [22][1160/1793] lr: 7.5000e-03 eta: 5:18:26 time: 0.1703 data_time: 0.0060 memory: 10464 grad_norm: 7.1011 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.2649 loss: 2.2649 2022/09/07 19:59:53 - mmengine - INFO - Epoch(train) [22][1180/1793] lr: 7.5000e-03 eta: 5:18:13 time: 0.1720 data_time: 0.0065 memory: 10464 grad_norm: 6.9818 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.0099 loss: 2.0099 2022/09/07 19:59:57 - mmengine - INFO - Epoch(train) [22][1200/1793] lr: 7.5000e-03 eta: 5:18:00 time: 0.1788 data_time: 0.0113 memory: 10464 grad_norm: 7.2058 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.3346 loss: 2.3346 2022/09/07 20:00:00 - mmengine - INFO - Epoch(train) [22][1220/1793] lr: 7.5000e-03 eta: 5:17:47 time: 0.1731 data_time: 0.0066 memory: 10464 grad_norm: 7.4031 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6299 loss: 2.6299 2022/09/07 20:00:04 - mmengine - INFO - Epoch(train) [22][1240/1793] lr: 7.5000e-03 eta: 5:17:35 time: 0.1780 data_time: 0.0063 memory: 10464 grad_norm: 7.1780 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2879 loss: 2.2879 2022/09/07 20:00:08 - mmengine - INFO - Epoch(train) [22][1260/1793] lr: 7.5000e-03 eta: 5:17:22 time: 0.1741 data_time: 0.0090 memory: 10464 grad_norm: 7.4632 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.8328 loss: 1.8328 2022/09/07 20:00:11 - mmengine - INFO - Epoch(train) [22][1280/1793] lr: 7.5000e-03 eta: 5:17:09 time: 0.1722 data_time: 0.0062 memory: 10464 grad_norm: 7.1267 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1640 loss: 2.1640 2022/09/07 20:00:14 - mmengine - INFO - Epoch(train) [22][1300/1793] lr: 7.5000e-03 eta: 5:16:56 time: 0.1730 data_time: 0.0079 memory: 10464 grad_norm: 7.2407 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.2940 loss: 2.2940 2022/09/07 20:00:18 - mmengine - INFO - Epoch(train) [22][1320/1793] lr: 7.5000e-03 eta: 5:16:44 time: 0.1820 data_time: 0.0074 memory: 10464 grad_norm: 7.1984 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1666 loss: 2.1666 2022/09/07 20:00:22 - mmengine - INFO - Epoch(train) [22][1340/1793] lr: 7.5000e-03 eta: 5:16:31 time: 0.1746 data_time: 0.0065 memory: 10464 grad_norm: 7.4253 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3682 loss: 2.3682 2022/09/07 20:00:23 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:00:25 - mmengine - INFO - Epoch(train) [22][1360/1793] lr: 7.5000e-03 eta: 5:16:19 time: 0.1828 data_time: 0.0069 memory: 10464 grad_norm: 7.2535 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.1705 loss: 2.1705 2022/09/07 20:00:29 - mmengine - INFO - Epoch(train) [22][1380/1793] lr: 7.5000e-03 eta: 5:16:06 time: 0.1761 data_time: 0.0080 memory: 10464 grad_norm: 7.3147 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1854 loss: 2.1854 2022/09/07 20:00:34 - mmengine - INFO - Epoch(train) [22][1400/1793] lr: 7.5000e-03 eta: 5:15:55 time: 0.2468 data_time: 0.0063 memory: 10464 grad_norm: 7.5461 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.1957 loss: 2.1957 2022/09/07 20:00:37 - mmengine - INFO - Epoch(train) [22][1420/1793] lr: 7.5000e-03 eta: 5:15:43 time: 0.1790 data_time: 0.0066 memory: 10464 grad_norm: 7.3571 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1151 loss: 2.1151 2022/09/07 20:00:42 - mmengine - INFO - Epoch(train) [22][1440/1793] lr: 7.5000e-03 eta: 5:15:32 time: 0.2436 data_time: 0.0085 memory: 10464 grad_norm: 7.3874 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3775 loss: 2.3775 2022/09/07 20:00:46 - mmengine - INFO - Epoch(train) [22][1460/1793] lr: 7.5000e-03 eta: 5:15:20 time: 0.2105 data_time: 0.0065 memory: 10464 grad_norm: 7.1514 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0944 loss: 2.0944 2022/09/07 20:00:50 - mmengine - INFO - Epoch(train) [22][1480/1793] lr: 7.5000e-03 eta: 5:15:07 time: 0.1744 data_time: 0.0071 memory: 10464 grad_norm: 7.8028 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.1541 loss: 2.1541 2022/09/07 20:00:53 - mmengine - INFO - Epoch(train) [22][1500/1793] lr: 7.5000e-03 eta: 5:14:55 time: 0.1766 data_time: 0.0079 memory: 10464 grad_norm: 7.3031 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1632 loss: 2.1632 2022/09/07 20:00:57 - mmengine - INFO - Epoch(train) [22][1520/1793] lr: 7.5000e-03 eta: 5:14:42 time: 0.1762 data_time: 0.0062 memory: 10464 grad_norm: 7.0901 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3042 loss: 2.3042 2022/09/07 20:01:00 - mmengine - INFO - Epoch(train) [22][1540/1793] lr: 7.5000e-03 eta: 5:14:30 time: 0.1776 data_time: 0.0068 memory: 10464 grad_norm: 7.4722 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3919 loss: 2.3919 2022/09/07 20:01:04 - mmengine - INFO - Epoch(train) [22][1560/1793] lr: 7.5000e-03 eta: 5:14:17 time: 0.1863 data_time: 0.0091 memory: 10464 grad_norm: 7.0069 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4197 loss: 2.4197 2022/09/07 20:01:08 - mmengine - INFO - Epoch(train) [22][1580/1793] lr: 7.5000e-03 eta: 5:14:05 time: 0.1723 data_time: 0.0064 memory: 10464 grad_norm: 7.1597 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0415 loss: 2.0415 2022/09/07 20:01:11 - mmengine - INFO - Epoch(train) [22][1600/1793] lr: 7.5000e-03 eta: 5:13:52 time: 0.1762 data_time: 0.0067 memory: 10464 grad_norm: 7.5711 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6154 loss: 2.6154 2022/09/07 20:01:15 - mmengine - INFO - Epoch(train) [22][1620/1793] lr: 7.5000e-03 eta: 5:13:39 time: 0.1747 data_time: 0.0075 memory: 10464 grad_norm: 7.2674 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2976 loss: 2.2976 2022/09/07 20:01:19 - mmengine - INFO - Epoch(train) [22][1640/1793] lr: 7.5000e-03 eta: 5:13:27 time: 0.1952 data_time: 0.0061 memory: 10464 grad_norm: 7.2469 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.0534 loss: 2.0534 2022/09/07 20:01:22 - mmengine - INFO - Epoch(train) [22][1660/1793] lr: 7.5000e-03 eta: 5:13:15 time: 0.1758 data_time: 0.0076 memory: 10464 grad_norm: 7.2006 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4956 loss: 2.4956 2022/09/07 20:01:26 - mmengine - INFO - Epoch(train) [22][1680/1793] lr: 7.5000e-03 eta: 5:13:02 time: 0.1779 data_time: 0.0092 memory: 10464 grad_norm: 6.9089 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2282 loss: 2.2282 2022/09/07 20:01:29 - mmengine - INFO - Epoch(train) [22][1700/1793] lr: 7.5000e-03 eta: 5:12:50 time: 0.1718 data_time: 0.0052 memory: 10464 grad_norm: 6.9551 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3434 loss: 2.3434 2022/09/07 20:01:33 - mmengine - INFO - Epoch(train) [22][1720/1793] lr: 7.5000e-03 eta: 5:12:38 time: 0.1945 data_time: 0.0070 memory: 10464 grad_norm: 7.0630 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.3324 loss: 2.3324 2022/09/07 20:01:37 - mmengine - INFO - Epoch(train) [22][1740/1793] lr: 7.5000e-03 eta: 5:12:26 time: 0.2015 data_time: 0.0095 memory: 10464 grad_norm: 7.4333 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4100 loss: 2.4100 2022/09/07 20:01:40 - mmengine - INFO - Epoch(train) [22][1760/1793] lr: 7.5000e-03 eta: 5:12:13 time: 0.1739 data_time: 0.0073 memory: 10464 grad_norm: 7.2399 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1543 loss: 2.1543 2022/09/07 20:01:44 - mmengine - INFO - Epoch(train) [22][1780/1793] lr: 7.5000e-03 eta: 5:12:01 time: 0.1841 data_time: 0.0058 memory: 10464 grad_norm: 7.0371 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4315 loss: 2.4315 2022/09/07 20:01:46 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:01:46 - mmengine - INFO - Epoch(train) [22][1793/1793] lr: 7.5000e-03 eta: 5:12:01 time: 0.1696 data_time: 0.0076 memory: 10464 grad_norm: 7.4884 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 2.2643 loss: 2.2643 2022/09/07 20:01:46 - mmengine - INFO - Saving checkpoint at 22 epochs 2022/09/07 20:01:50 - mmengine - INFO - Epoch(val) [22][20/241] eta: 0:00:13 time: 0.0589 data_time: 0.0095 memory: 1482 2022/09/07 20:01:51 - mmengine - INFO - Epoch(val) [22][40/241] eta: 0:00:10 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 20:01:52 - mmengine - INFO - Epoch(val) [22][60/241] eta: 0:00:09 time: 0.0532 data_time: 0.0047 memory: 1482 2022/09/07 20:01:53 - mmengine - INFO - Epoch(val) [22][80/241] eta: 0:00:08 time: 0.0534 data_time: 0.0049 memory: 1482 2022/09/07 20:01:55 - mmengine - INFO - Epoch(val) [22][100/241] eta: 0:00:07 time: 0.0535 data_time: 0.0049 memory: 1482 2022/09/07 20:01:56 - mmengine - INFO - Epoch(val) [22][120/241] eta: 0:00:06 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 20:01:57 - mmengine - INFO - Epoch(val) [22][140/241] eta: 0:00:05 time: 0.0548 data_time: 0.0060 memory: 1482 2022/09/07 20:01:58 - mmengine - INFO - Epoch(val) [22][160/241] eta: 0:00:04 time: 0.0526 data_time: 0.0043 memory: 1482 2022/09/07 20:01:59 - mmengine - INFO - Epoch(val) [22][180/241] eta: 0:00:03 time: 0.0534 data_time: 0.0051 memory: 1482 2022/09/07 20:02:00 - mmengine - INFO - Epoch(val) [22][200/241] eta: 0:00:02 time: 0.0581 data_time: 0.0100 memory: 1482 2022/09/07 20:02:01 - mmengine - INFO - Epoch(val) [22][220/241] eta: 0:00:01 time: 0.0528 data_time: 0.0048 memory: 1482 2022/09/07 20:02:02 - mmengine - INFO - Epoch(val) [22][240/241] eta: 0:00:00 time: 0.0528 data_time: 0.0047 memory: 1482 2022/09/07 20:02:03 - mmengine - INFO - Epoch(val) [22][241/241] acc/top1: 0.3284 acc/top5: 0.6202 acc/mean1: 0.2982 2022/09/07 20:02:03 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_17.pth is removed 2022/09/07 20:02:04 - mmengine - INFO - The best checkpoint with 0.3284 acc/top1 at 22 epoch is saved to best_acc/top1_epoch_22.pth. 2022/09/07 20:02:09 - mmengine - INFO - Epoch(train) [23][20/1793] lr: 7.5000e-03 eta: 5:11:38 time: 0.2076 data_time: 0.0097 memory: 10464 grad_norm: 7.1978 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.0312 loss: 2.0312 2022/09/07 20:02:12 - mmengine - INFO - Epoch(train) [23][40/1793] lr: 7.5000e-03 eta: 5:11:26 time: 0.1756 data_time: 0.0060 memory: 10464 grad_norm: 7.0720 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0632 loss: 2.0632 2022/09/07 20:02:16 - mmengine - INFO - Epoch(train) [23][60/1793] lr: 7.5000e-03 eta: 5:11:14 time: 0.1775 data_time: 0.0067 memory: 10464 grad_norm: 6.9679 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0011 loss: 2.0011 2022/09/07 20:02:19 - mmengine - INFO - Epoch(train) [23][80/1793] lr: 7.5000e-03 eta: 5:11:01 time: 0.1765 data_time: 0.0087 memory: 10464 grad_norm: 7.1994 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1009 loss: 2.1009 2022/09/07 20:02:23 - mmengine - INFO - Epoch(train) [23][100/1793] lr: 7.5000e-03 eta: 5:10:49 time: 0.1785 data_time: 0.0069 memory: 10464 grad_norm: 7.1844 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3109 loss: 2.3109 2022/09/07 20:02:27 - mmengine - INFO - Epoch(train) [23][120/1793] lr: 7.5000e-03 eta: 5:10:38 time: 0.2393 data_time: 0.0056 memory: 10464 grad_norm: 7.3251 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0223 loss: 2.0223 2022/09/07 20:02:31 - mmengine - INFO - Epoch(train) [23][140/1793] lr: 7.5000e-03 eta: 5:10:26 time: 0.1782 data_time: 0.0083 memory: 10464 grad_norm: 7.2200 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.2596 loss: 2.2596 2022/09/07 20:02:36 - mmengine - INFO - Epoch(train) [23][160/1793] lr: 7.5000e-03 eta: 5:10:15 time: 0.2587 data_time: 0.0072 memory: 10464 grad_norm: 7.3159 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1017 loss: 2.1017 2022/09/07 20:02:40 - mmengine - INFO - Epoch(train) [23][180/1793] lr: 7.5000e-03 eta: 5:10:03 time: 0.1755 data_time: 0.0068 memory: 10464 grad_norm: 6.9825 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1464 loss: 2.1464 2022/09/07 20:02:43 - mmengine - INFO - Epoch(train) [23][200/1793] lr: 7.5000e-03 eta: 5:09:51 time: 0.1880 data_time: 0.0091 memory: 10464 grad_norm: 7.0195 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.9249 loss: 1.9249 2022/09/07 20:02:47 - mmengine - INFO - Epoch(train) [23][220/1793] lr: 7.5000e-03 eta: 5:09:39 time: 0.1756 data_time: 0.0056 memory: 10464 grad_norm: 7.2329 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4478 loss: 2.4478 2022/09/07 20:02:51 - mmengine - INFO - Epoch(train) [23][240/1793] lr: 7.5000e-03 eta: 5:09:26 time: 0.1746 data_time: 0.0065 memory: 10464 grad_norm: 7.4382 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.6291 loss: 2.6291 2022/09/07 20:02:54 - mmengine - INFO - Epoch(train) [23][260/1793] lr: 7.5000e-03 eta: 5:09:14 time: 0.1790 data_time: 0.0087 memory: 10464 grad_norm: 7.3777 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1172 loss: 2.1172 2022/09/07 20:02:58 - mmengine - INFO - Epoch(train) [23][280/1793] lr: 7.5000e-03 eta: 5:09:02 time: 0.1764 data_time: 0.0066 memory: 10464 grad_norm: 7.2304 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.7342 loss: 2.7342 2022/09/07 20:03:01 - mmengine - INFO - Epoch(train) [23][300/1793] lr: 7.5000e-03 eta: 5:08:49 time: 0.1761 data_time: 0.0061 memory: 10464 grad_norm: 7.3370 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.2412 loss: 2.2412 2022/09/07 20:03:05 - mmengine - INFO - Epoch(train) [23][320/1793] lr: 7.5000e-03 eta: 5:08:37 time: 0.1944 data_time: 0.0087 memory: 10464 grad_norm: 7.4844 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.2291 loss: 2.2291 2022/09/07 20:03:09 - mmengine - INFO - Epoch(train) [23][340/1793] lr: 7.5000e-03 eta: 5:08:25 time: 0.1818 data_time: 0.0062 memory: 10464 grad_norm: 7.1132 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.2411 loss: 2.2411 2022/09/07 20:03:13 - mmengine - INFO - Epoch(train) [23][360/1793] lr: 7.5000e-03 eta: 5:08:14 time: 0.2353 data_time: 0.0668 memory: 10464 grad_norm: 7.3167 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.9995 loss: 1.9995 2022/09/07 20:03:17 - mmengine - INFO - Epoch(train) [23][380/1793] lr: 7.5000e-03 eta: 5:08:02 time: 0.1816 data_time: 0.0097 memory: 10464 grad_norm: 7.1011 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.2590 loss: 2.2590 2022/09/07 20:03:20 - mmengine - INFO - Epoch(train) [23][400/1793] lr: 7.5000e-03 eta: 5:07:50 time: 0.1717 data_time: 0.0065 memory: 10464 grad_norm: 7.1834 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0369 loss: 2.0369 2022/09/07 20:03:24 - mmengine - INFO - Epoch(train) [23][420/1793] lr: 7.5000e-03 eta: 5:07:37 time: 0.1719 data_time: 0.0066 memory: 10464 grad_norm: 7.4765 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1298 loss: 2.1298 2022/09/07 20:03:27 - mmengine - INFO - Epoch(train) [23][440/1793] lr: 7.5000e-03 eta: 5:07:25 time: 0.1728 data_time: 0.0084 memory: 10464 grad_norm: 7.1824 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.3092 loss: 2.3092 2022/09/07 20:03:31 - mmengine - INFO - Epoch(train) [23][460/1793] lr: 7.5000e-03 eta: 5:07:13 time: 0.1761 data_time: 0.0062 memory: 10464 grad_norm: 7.4231 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3422 loss: 2.3422 2022/09/07 20:03:34 - mmengine - INFO - Epoch(train) [23][480/1793] lr: 7.5000e-03 eta: 5:07:00 time: 0.1731 data_time: 0.0062 memory: 10464 grad_norm: 7.3440 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.2358 loss: 2.2358 2022/09/07 20:03:38 - mmengine - INFO - Epoch(train) [23][500/1793] lr: 7.5000e-03 eta: 5:06:48 time: 0.1825 data_time: 0.0085 memory: 10464 grad_norm: 7.4350 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.0377 loss: 2.0377 2022/09/07 20:03:41 - mmengine - INFO - Epoch(train) [23][520/1793] lr: 7.5000e-03 eta: 5:06:36 time: 0.1700 data_time: 0.0063 memory: 10464 grad_norm: 7.4040 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.2107 loss: 2.2107 2022/09/07 20:03:45 - mmengine - INFO - Epoch(train) [23][540/1793] lr: 7.5000e-03 eta: 5:06:24 time: 0.1769 data_time: 0.0069 memory: 10464 grad_norm: 6.9196 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.2174 loss: 2.2174 2022/09/07 20:03:47 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:03:48 - mmengine - INFO - Epoch(train) [23][560/1793] lr: 7.5000e-03 eta: 5:06:12 time: 0.1756 data_time: 0.0086 memory: 10464 grad_norm: 6.8185 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1404 loss: 2.1404 2022/09/07 20:03:52 - mmengine - INFO - Epoch(train) [23][580/1793] lr: 7.5000e-03 eta: 5:05:59 time: 0.1721 data_time: 0.0060 memory: 10464 grad_norm: 7.2239 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1994 loss: 2.1994 2022/09/07 20:03:56 - mmengine - INFO - Epoch(train) [23][600/1793] lr: 7.5000e-03 eta: 5:05:47 time: 0.1901 data_time: 0.0060 memory: 10464 grad_norm: 7.1408 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1544 loss: 2.1544 2022/09/07 20:03:59 - mmengine - INFO - Epoch(train) [23][620/1793] lr: 7.5000e-03 eta: 5:05:35 time: 0.1727 data_time: 0.0087 memory: 10464 grad_norm: 7.2132 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3903 loss: 2.3903 2022/09/07 20:04:03 - mmengine - INFO - Epoch(train) [23][640/1793] lr: 7.5000e-03 eta: 5:05:23 time: 0.1711 data_time: 0.0068 memory: 10464 grad_norm: 7.3598 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.2812 loss: 2.2812 2022/09/07 20:04:07 - mmengine - INFO - Epoch(train) [23][660/1793] lr: 7.5000e-03 eta: 5:05:11 time: 0.2048 data_time: 0.0064 memory: 10464 grad_norm: 7.3989 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3153 loss: 2.3153 2022/09/07 20:04:10 - mmengine - INFO - Epoch(train) [23][680/1793] lr: 7.5000e-03 eta: 5:04:59 time: 0.1722 data_time: 0.0083 memory: 10464 grad_norm: 7.0946 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2618 loss: 2.2618 2022/09/07 20:04:14 - mmengine - INFO - Epoch(train) [23][700/1793] lr: 7.5000e-03 eta: 5:04:47 time: 0.1765 data_time: 0.0070 memory: 10464 grad_norm: 7.2056 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.0102 loss: 2.0102 2022/09/07 20:04:18 - mmengine - INFO - Epoch(train) [23][720/1793] lr: 7.5000e-03 eta: 5:04:35 time: 0.1925 data_time: 0.0069 memory: 10464 grad_norm: 7.3078 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2665 loss: 2.2665 2022/09/07 20:04:21 - mmengine - INFO - Epoch(train) [23][740/1793] lr: 7.5000e-03 eta: 5:04:23 time: 0.1737 data_time: 0.0093 memory: 10464 grad_norm: 7.2065 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3078 loss: 2.3078 2022/09/07 20:04:24 - mmengine - INFO - Epoch(train) [23][760/1793] lr: 7.5000e-03 eta: 5:04:11 time: 0.1700 data_time: 0.0059 memory: 10464 grad_norm: 7.1418 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5085 loss: 2.5085 2022/09/07 20:04:28 - mmengine - INFO - Epoch(train) [23][780/1793] lr: 7.5000e-03 eta: 5:03:58 time: 0.1722 data_time: 0.0067 memory: 10464 grad_norm: 7.1994 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3129 loss: 2.3129 2022/09/07 20:04:31 - mmengine - INFO - Epoch(train) [23][800/1793] lr: 7.5000e-03 eta: 5:03:46 time: 0.1738 data_time: 0.0093 memory: 10464 grad_norm: 7.2447 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.2348 loss: 2.2348 2022/09/07 20:04:35 - mmengine - INFO - Epoch(train) [23][820/1793] lr: 7.5000e-03 eta: 5:03:34 time: 0.1743 data_time: 0.0062 memory: 10464 grad_norm: 7.3078 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3049 loss: 2.3049 2022/09/07 20:04:39 - mmengine - INFO - Epoch(train) [23][840/1793] lr: 7.5000e-03 eta: 5:03:22 time: 0.1925 data_time: 0.0058 memory: 10464 grad_norm: 7.2771 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0867 loss: 2.0867 2022/09/07 20:04:42 - mmengine - INFO - Epoch(train) [23][860/1793] lr: 7.5000e-03 eta: 5:03:10 time: 0.1738 data_time: 0.0091 memory: 10464 grad_norm: 6.9424 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2662 loss: 2.2662 2022/09/07 20:04:46 - mmengine - INFO - Epoch(train) [23][880/1793] lr: 7.5000e-03 eta: 5:02:58 time: 0.1713 data_time: 0.0062 memory: 10464 grad_norm: 7.0623 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 1.9419 loss: 1.9419 2022/09/07 20:04:49 - mmengine - INFO - Epoch(train) [23][900/1793] lr: 7.5000e-03 eta: 5:02:46 time: 0.1703 data_time: 0.0062 memory: 10464 grad_norm: 7.2329 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2708 loss: 2.2708 2022/09/07 20:04:52 - mmengine - INFO - Epoch(train) [23][920/1793] lr: 7.5000e-03 eta: 5:02:34 time: 0.1724 data_time: 0.0093 memory: 10464 grad_norm: 7.3055 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.0450 loss: 2.0450 2022/09/07 20:04:56 - mmengine - INFO - Epoch(train) [23][940/1793] lr: 7.5000e-03 eta: 5:02:22 time: 0.1947 data_time: 0.0073 memory: 10464 grad_norm: 7.3566 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9005 loss: 1.9005 2022/09/07 20:05:00 - mmengine - INFO - Epoch(train) [23][960/1793] lr: 7.5000e-03 eta: 5:02:10 time: 0.1703 data_time: 0.0060 memory: 10464 grad_norm: 7.3563 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.4891 loss: 2.4891 2022/09/07 20:05:03 - mmengine - INFO - Epoch(train) [23][980/1793] lr: 7.5000e-03 eta: 5:01:58 time: 0.1729 data_time: 0.0088 memory: 10464 grad_norm: 6.9916 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0374 loss: 2.0374 2022/09/07 20:05:07 - mmengine - INFO - Epoch(train) [23][1000/1793] lr: 7.5000e-03 eta: 5:01:46 time: 0.1698 data_time: 0.0061 memory: 10464 grad_norm: 7.8394 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3308 loss: 2.3308 2022/09/07 20:05:10 - mmengine - INFO - Epoch(train) [23][1020/1793] lr: 7.5000e-03 eta: 5:01:33 time: 0.1729 data_time: 0.0088 memory: 10464 grad_norm: 7.4953 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3065 loss: 2.3065 2022/09/07 20:05:14 - mmengine - INFO - Epoch(train) [23][1040/1793] lr: 7.5000e-03 eta: 5:01:22 time: 0.1807 data_time: 0.0090 memory: 10464 grad_norm: 7.2800 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.1735 loss: 2.1735 2022/09/07 20:05:17 - mmengine - INFO - Epoch(train) [23][1060/1793] lr: 7.5000e-03 eta: 5:01:10 time: 0.1773 data_time: 0.0067 memory: 10464 grad_norm: 7.1654 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.2825 loss: 2.2825 2022/09/07 20:05:21 - mmengine - INFO - Epoch(train) [23][1080/1793] lr: 7.5000e-03 eta: 5:00:57 time: 0.1697 data_time: 0.0066 memory: 10464 grad_norm: 6.8136 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1573 loss: 2.1573 2022/09/07 20:05:24 - mmengine - INFO - Epoch(train) [23][1100/1793] lr: 7.5000e-03 eta: 5:00:45 time: 0.1729 data_time: 0.0087 memory: 10464 grad_norm: 7.4810 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2512 loss: 2.2512 2022/09/07 20:05:28 - mmengine - INFO - Epoch(train) [23][1120/1793] lr: 7.5000e-03 eta: 5:00:33 time: 0.1707 data_time: 0.0065 memory: 10464 grad_norm: 7.2226 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.0825 loss: 2.0825 2022/09/07 20:05:32 - mmengine - INFO - Epoch(train) [23][1140/1793] lr: 7.5000e-03 eta: 5:00:23 time: 0.2424 data_time: 0.0064 memory: 10464 grad_norm: 7.3779 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1400 loss: 2.1400 2022/09/07 20:05:37 - mmengine - INFO - Epoch(train) [23][1160/1793] lr: 7.5000e-03 eta: 5:00:12 time: 0.2397 data_time: 0.0125 memory: 10464 grad_norm: 7.2915 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1842 loss: 2.1842 2022/09/07 20:05:41 - mmengine - INFO - Epoch(train) [23][1180/1793] lr: 7.5000e-03 eta: 5:00:00 time: 0.1745 data_time: 0.0080 memory: 10464 grad_norm: 7.1377 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1053 loss: 2.1053 2022/09/07 20:05:44 - mmengine - INFO - Epoch(train) [23][1200/1793] lr: 7.5000e-03 eta: 4:59:48 time: 0.1723 data_time: 0.0062 memory: 10464 grad_norm: 7.4155 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3285 loss: 2.3285 2022/09/07 20:05:48 - mmengine - INFO - Epoch(train) [23][1220/1793] lr: 7.5000e-03 eta: 4:59:36 time: 0.1751 data_time: 0.0093 memory: 10464 grad_norm: 6.9356 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.9571 loss: 1.9571 2022/09/07 20:05:51 - mmengine - INFO - Epoch(train) [23][1240/1793] lr: 7.5000e-03 eta: 4:59:25 time: 0.1791 data_time: 0.0070 memory: 10464 grad_norm: 7.3369 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.1662 loss: 2.1662 2022/09/07 20:05:55 - mmengine - INFO - Epoch(train) [23][1260/1793] lr: 7.5000e-03 eta: 4:59:13 time: 0.1760 data_time: 0.0059 memory: 10464 grad_norm: 7.5934 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 1.9648 loss: 1.9648 2022/09/07 20:06:00 - mmengine - INFO - Epoch(train) [23][1280/1793] lr: 7.5000e-03 eta: 4:59:03 time: 0.2538 data_time: 0.0106 memory: 10464 grad_norm: 7.3335 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1959 loss: 2.1959 2022/09/07 20:06:03 - mmengine - INFO - Epoch(train) [23][1300/1793] lr: 7.5000e-03 eta: 4:58:51 time: 0.1844 data_time: 0.0061 memory: 10464 grad_norm: 7.2554 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5112 loss: 2.5112 2022/09/07 20:06:08 - mmengine - INFO - Epoch(train) [23][1320/1793] lr: 7.5000e-03 eta: 4:58:40 time: 0.2379 data_time: 0.0068 memory: 10464 grad_norm: 7.4224 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.5969 loss: 2.5969 2022/09/07 20:06:12 - mmengine - INFO - Epoch(train) [23][1340/1793] lr: 7.5000e-03 eta: 4:58:29 time: 0.1764 data_time: 0.0087 memory: 10464 grad_norm: 7.2806 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5573 loss: 2.5573 2022/09/07 20:06:17 - mmengine - INFO - Epoch(train) [23][1360/1793] lr: 7.5000e-03 eta: 4:58:19 time: 0.2589 data_time: 0.0083 memory: 10464 grad_norm: 7.0898 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2538 loss: 2.2538 2022/09/07 20:06:20 - mmengine - INFO - Epoch(train) [23][1380/1793] lr: 7.5000e-03 eta: 4:58:07 time: 0.1749 data_time: 0.0060 memory: 10464 grad_norm: 7.1234 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0339 loss: 2.0339 2022/09/07 20:06:24 - mmengine - INFO - Epoch(train) [23][1400/1793] lr: 7.5000e-03 eta: 4:57:55 time: 0.1915 data_time: 0.0086 memory: 10464 grad_norm: 7.3643 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2393 loss: 2.2393 2022/09/07 20:06:28 - mmengine - INFO - Epoch(train) [23][1420/1793] lr: 7.5000e-03 eta: 4:57:43 time: 0.1715 data_time: 0.0063 memory: 10464 grad_norm: 7.5669 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.1601 loss: 2.1601 2022/09/07 20:06:31 - mmengine - INFO - Epoch(train) [23][1440/1793] lr: 7.5000e-03 eta: 4:57:31 time: 0.1730 data_time: 0.0066 memory: 10464 grad_norm: 7.0292 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.2161 loss: 2.2161 2022/09/07 20:06:35 - mmengine - INFO - Epoch(train) [23][1460/1793] lr: 7.5000e-03 eta: 4:57:19 time: 0.1734 data_time: 0.0080 memory: 10464 grad_norm: 7.0353 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3334 loss: 2.3334 2022/09/07 20:06:38 - mmengine - INFO - Epoch(train) [23][1480/1793] lr: 7.5000e-03 eta: 4:57:08 time: 0.1766 data_time: 0.0071 memory: 10464 grad_norm: 7.2882 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2792 loss: 2.2792 2022/09/07 20:06:42 - mmengine - INFO - Epoch(train) [23][1500/1793] lr: 7.5000e-03 eta: 4:56:56 time: 0.1708 data_time: 0.0068 memory: 10464 grad_norm: 7.1676 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2378 loss: 2.2378 2022/09/07 20:06:45 - mmengine - INFO - Epoch(train) [23][1520/1793] lr: 7.5000e-03 eta: 4:56:44 time: 0.1865 data_time: 0.0089 memory: 10464 grad_norm: 7.1290 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.0950 loss: 2.0950 2022/09/07 20:06:49 - mmengine - INFO - Epoch(train) [23][1540/1793] lr: 7.5000e-03 eta: 4:56:32 time: 0.1711 data_time: 0.0064 memory: 10464 grad_norm: 7.0752 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1181 loss: 2.1181 2022/09/07 20:06:51 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:06:52 - mmengine - INFO - Epoch(train) [23][1560/1793] lr: 7.5000e-03 eta: 4:56:20 time: 0.1720 data_time: 0.0065 memory: 10464 grad_norm: 7.5614 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0957 loss: 2.0957 2022/09/07 20:06:56 - mmengine - INFO - Epoch(train) [23][1580/1793] lr: 7.5000e-03 eta: 4:56:09 time: 0.1930 data_time: 0.0106 memory: 10464 grad_norm: 6.9108 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2943 loss: 2.2943 2022/09/07 20:06:59 - mmengine - INFO - Epoch(train) [23][1600/1793] lr: 7.5000e-03 eta: 4:55:57 time: 0.1703 data_time: 0.0068 memory: 10464 grad_norm: 7.0764 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.0458 loss: 2.0458 2022/09/07 20:07:03 - mmengine - INFO - Epoch(train) [23][1620/1793] lr: 7.5000e-03 eta: 4:55:45 time: 0.1764 data_time: 0.0073 memory: 10464 grad_norm: 6.8002 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3061 loss: 2.3061 2022/09/07 20:07:07 - mmengine - INFO - Epoch(train) [23][1640/1793] lr: 7.5000e-03 eta: 4:55:33 time: 0.1771 data_time: 0.0083 memory: 10464 grad_norm: 7.1508 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.1744 loss: 2.1744 2022/09/07 20:07:10 - mmengine - INFO - Epoch(train) [23][1660/1793] lr: 7.5000e-03 eta: 4:55:21 time: 0.1712 data_time: 0.0072 memory: 10464 grad_norm: 7.0545 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3365 loss: 2.3365 2022/09/07 20:07:13 - mmengine - INFO - Epoch(train) [23][1680/1793] lr: 7.5000e-03 eta: 4:55:10 time: 0.1742 data_time: 0.0058 memory: 10464 grad_norm: 7.1319 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0208 loss: 2.0208 2022/09/07 20:07:17 - mmengine - INFO - Epoch(train) [23][1700/1793] lr: 7.5000e-03 eta: 4:54:58 time: 0.1817 data_time: 0.0115 memory: 10464 grad_norm: 7.1202 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3308 loss: 2.3308 2022/09/07 20:07:21 - mmengine - INFO - Epoch(train) [23][1720/1793] lr: 7.5000e-03 eta: 4:54:46 time: 0.1712 data_time: 0.0063 memory: 10464 grad_norm: 7.0377 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3216 loss: 2.3216 2022/09/07 20:07:24 - mmengine - INFO - Epoch(train) [23][1740/1793] lr: 7.5000e-03 eta: 4:54:34 time: 0.1738 data_time: 0.0062 memory: 10464 grad_norm: 6.9729 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.0663 loss: 2.0663 2022/09/07 20:07:28 - mmengine - INFO - Epoch(train) [23][1760/1793] lr: 7.5000e-03 eta: 4:54:23 time: 0.1770 data_time: 0.0089 memory: 10464 grad_norm: 7.4284 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2238 loss: 2.2238 2022/09/07 20:07:31 - mmengine - INFO - Epoch(train) [23][1780/1793] lr: 7.5000e-03 eta: 4:54:11 time: 0.1699 data_time: 0.0062 memory: 10464 grad_norm: 7.4565 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1611 loss: 2.1611 2022/09/07 20:07:33 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:07:33 - mmengine - INFO - Epoch(train) [23][1793/1793] lr: 7.5000e-03 eta: 4:54:11 time: 0.1698 data_time: 0.0066 memory: 10464 grad_norm: 7.5622 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.3922 loss: 2.3922 2022/09/07 20:07:33 - mmengine - INFO - Saving checkpoint at 23 epochs 2022/09/07 20:07:36 - mmengine - INFO - Epoch(val) [23][20/241] eta: 0:00:12 time: 0.0581 data_time: 0.0089 memory: 1482 2022/09/07 20:07:38 - mmengine - INFO - Epoch(val) [23][40/241] eta: 0:00:10 time: 0.0537 data_time: 0.0050 memory: 1482 2022/09/07 20:07:39 - mmengine - INFO - Epoch(val) [23][60/241] eta: 0:00:09 time: 0.0534 data_time: 0.0051 memory: 1482 2022/09/07 20:07:40 - mmengine - INFO - Epoch(val) [23][80/241] eta: 0:00:08 time: 0.0536 data_time: 0.0050 memory: 1482 2022/09/07 20:07:41 - mmengine - INFO - Epoch(val) [23][100/241] eta: 0:00:07 time: 0.0528 data_time: 0.0047 memory: 1482 2022/09/07 20:07:42 - mmengine - INFO - Epoch(val) [23][120/241] eta: 0:00:06 time: 0.0531 data_time: 0.0047 memory: 1482 2022/09/07 20:07:43 - mmengine - INFO - Epoch(val) [23][140/241] eta: 0:00:05 time: 0.0536 data_time: 0.0051 memory: 1482 2022/09/07 20:07:44 - mmengine - INFO - Epoch(val) [23][160/241] eta: 0:00:04 time: 0.0533 data_time: 0.0050 memory: 1482 2022/09/07 20:07:45 - mmengine - INFO - Epoch(val) [23][180/241] eta: 0:00:03 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 20:07:46 - mmengine - INFO - Epoch(val) [23][200/241] eta: 0:00:02 time: 0.0593 data_time: 0.0069 memory: 1482 2022/09/07 20:07:47 - mmengine - INFO - Epoch(val) [23][220/241] eta: 0:00:01 time: 0.0524 data_time: 0.0044 memory: 1482 2022/09/07 20:07:48 - mmengine - INFO - Epoch(val) [23][240/241] eta: 0:00:00 time: 0.0525 data_time: 0.0045 memory: 1482 2022/09/07 20:07:49 - mmengine - INFO - Epoch(val) [23][241/241] acc/top1: 0.3205 acc/top5: 0.6279 acc/mean1: 0.2930 2022/09/07 20:07:53 - mmengine - INFO - Epoch(train) [24][20/1793] lr: 7.5000e-03 eta: 4:53:50 time: 0.2057 data_time: 0.0118 memory: 10464 grad_norm: 6.8910 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2829 loss: 2.2829 2022/09/07 20:07:56 - mmengine - INFO - Epoch(train) [24][40/1793] lr: 7.5000e-03 eta: 4:53:38 time: 0.1702 data_time: 0.0068 memory: 10464 grad_norm: 7.0528 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2170 loss: 2.2170 2022/09/07 20:08:00 - mmengine - INFO - Epoch(train) [24][60/1793] lr: 7.5000e-03 eta: 4:53:26 time: 0.1730 data_time: 0.0057 memory: 10464 grad_norm: 6.9842 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.7748 loss: 1.7748 2022/09/07 20:08:03 - mmengine - INFO - Epoch(train) [24][80/1793] lr: 7.5000e-03 eta: 4:53:14 time: 0.1769 data_time: 0.0089 memory: 10464 grad_norm: 7.0420 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0531 loss: 2.0531 2022/09/07 20:08:07 - mmengine - INFO - Epoch(train) [24][100/1793] lr: 7.5000e-03 eta: 4:53:03 time: 0.1775 data_time: 0.0067 memory: 10464 grad_norm: 7.0364 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.2227 loss: 2.2227 2022/09/07 20:08:10 - mmengine - INFO - Epoch(train) [24][120/1793] lr: 7.5000e-03 eta: 4:52:51 time: 0.1704 data_time: 0.0070 memory: 10464 grad_norm: 7.3287 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1908 loss: 2.1908 2022/09/07 20:08:14 - mmengine - INFO - Epoch(train) [24][140/1793] lr: 7.5000e-03 eta: 4:52:39 time: 0.1757 data_time: 0.0095 memory: 10464 grad_norm: 7.0428 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4268 loss: 2.4268 2022/09/07 20:08:17 - mmengine - INFO - Epoch(train) [24][160/1793] lr: 7.5000e-03 eta: 4:52:27 time: 0.1701 data_time: 0.0065 memory: 10464 grad_norm: 7.1259 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.9017 loss: 1.9017 2022/09/07 20:08:21 - mmengine - INFO - Epoch(train) [24][180/1793] lr: 7.5000e-03 eta: 4:52:16 time: 0.1699 data_time: 0.0065 memory: 10464 grad_norm: 6.9267 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4031 loss: 2.4031 2022/09/07 20:08:25 - mmengine - INFO - Epoch(train) [24][200/1793] lr: 7.5000e-03 eta: 4:52:04 time: 0.1953 data_time: 0.0085 memory: 10464 grad_norm: 7.2481 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.1865 loss: 2.1865 2022/09/07 20:08:28 - mmengine - INFO - Epoch(train) [24][220/1793] lr: 7.5000e-03 eta: 4:51:53 time: 0.1757 data_time: 0.0072 memory: 10464 grad_norm: 7.4886 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.1713 loss: 2.1713 2022/09/07 20:08:32 - mmengine - INFO - Epoch(train) [24][240/1793] lr: 7.5000e-03 eta: 4:51:41 time: 0.1727 data_time: 0.0081 memory: 10464 grad_norm: 7.2961 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.0271 loss: 2.0271 2022/09/07 20:08:35 - mmengine - INFO - Epoch(train) [24][260/1793] lr: 7.5000e-03 eta: 4:51:29 time: 0.1738 data_time: 0.0085 memory: 10464 grad_norm: 7.3038 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.7367 loss: 1.7367 2022/09/07 20:08:39 - mmengine - INFO - Epoch(train) [24][280/1793] lr: 7.5000e-03 eta: 4:51:18 time: 0.1713 data_time: 0.0068 memory: 10464 grad_norm: 7.1490 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9156 loss: 1.9156 2022/09/07 20:08:42 - mmengine - INFO - Epoch(train) [24][300/1793] lr: 7.5000e-03 eta: 4:51:06 time: 0.1700 data_time: 0.0060 memory: 10464 grad_norm: 7.1732 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.0546 loss: 2.0546 2022/09/07 20:08:45 - mmengine - INFO - Epoch(train) [24][320/1793] lr: 7.5000e-03 eta: 4:50:54 time: 0.1738 data_time: 0.0082 memory: 10464 grad_norm: 7.2487 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.1092 loss: 2.1092 2022/09/07 20:08:49 - mmengine - INFO - Epoch(train) [24][340/1793] lr: 7.5000e-03 eta: 4:50:43 time: 0.1889 data_time: 0.0069 memory: 10464 grad_norm: 6.9568 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3894 loss: 2.3894 2022/09/07 20:08:53 - mmengine - INFO - Epoch(train) [24][360/1793] lr: 7.5000e-03 eta: 4:50:31 time: 0.1704 data_time: 0.0067 memory: 10464 grad_norm: 7.1702 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3390 loss: 2.3390 2022/09/07 20:08:56 - mmengine - INFO - Epoch(train) [24][380/1793] lr: 7.5000e-03 eta: 4:50:20 time: 0.1758 data_time: 0.0096 memory: 10464 grad_norm: 7.0614 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.9791 loss: 1.9791 2022/09/07 20:09:00 - mmengine - INFO - Epoch(train) [24][400/1793] lr: 7.5000e-03 eta: 4:50:08 time: 0.1701 data_time: 0.0067 memory: 10464 grad_norm: 7.3062 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8942 loss: 1.8942 2022/09/07 20:09:03 - mmengine - INFO - Epoch(train) [24][420/1793] lr: 7.5000e-03 eta: 4:49:56 time: 0.1690 data_time: 0.0061 memory: 10464 grad_norm: 7.0217 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0004 loss: 2.0004 2022/09/07 20:09:07 - mmengine - INFO - Epoch(train) [24][440/1793] lr: 7.5000e-03 eta: 4:49:45 time: 0.1829 data_time: 0.0113 memory: 10464 grad_norm: 7.3114 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.2098 loss: 2.2098 2022/09/07 20:09:10 - mmengine - INFO - Epoch(train) [24][460/1793] lr: 7.5000e-03 eta: 4:49:33 time: 0.1704 data_time: 0.0064 memory: 10464 grad_norm: 7.3324 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5211 loss: 2.5211 2022/09/07 20:09:13 - mmengine - INFO - Epoch(train) [24][480/1793] lr: 7.5000e-03 eta: 4:49:22 time: 0.1746 data_time: 0.0066 memory: 10464 grad_norm: 7.0671 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3754 loss: 2.3754 2022/09/07 20:09:17 - mmengine - INFO - Epoch(train) [24][500/1793] lr: 7.5000e-03 eta: 4:49:10 time: 0.1745 data_time: 0.0107 memory: 10464 grad_norm: 7.2244 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4438 loss: 2.4438 2022/09/07 20:09:20 - mmengine - INFO - Epoch(train) [24][520/1793] lr: 7.5000e-03 eta: 4:48:59 time: 0.1695 data_time: 0.0062 memory: 10464 grad_norm: 7.3642 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1263 loss: 2.1263 2022/09/07 20:09:24 - mmengine - INFO - Epoch(train) [24][540/1793] lr: 7.5000e-03 eta: 4:48:47 time: 0.1822 data_time: 0.0064 memory: 10464 grad_norm: 7.1552 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2559 loss: 2.2559 2022/09/07 20:09:28 - mmengine - INFO - Epoch(train) [24][560/1793] lr: 7.5000e-03 eta: 4:48:36 time: 0.1802 data_time: 0.0093 memory: 10464 grad_norm: 7.3893 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.0298 loss: 2.0298 2022/09/07 20:09:31 - mmengine - INFO - Epoch(train) [24][580/1793] lr: 7.5000e-03 eta: 4:48:24 time: 0.1699 data_time: 0.0067 memory: 10464 grad_norm: 7.2737 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.0343 loss: 2.0343 2022/09/07 20:09:34 - mmengine - INFO - Epoch(train) [24][600/1793] lr: 7.5000e-03 eta: 4:48:13 time: 0.1722 data_time: 0.0063 memory: 10464 grad_norm: 7.4499 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.0758 loss: 2.0758 2022/09/07 20:09:38 - mmengine - INFO - Epoch(train) [24][620/1793] lr: 7.5000e-03 eta: 4:48:01 time: 0.1732 data_time: 0.0087 memory: 10464 grad_norm: 7.2762 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3813 loss: 2.3813 2022/09/07 20:09:41 - mmengine - INFO - Epoch(train) [24][640/1793] lr: 7.5000e-03 eta: 4:47:49 time: 0.1692 data_time: 0.0061 memory: 10464 grad_norm: 7.3270 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.9817 loss: 1.9817 2022/09/07 20:09:45 - mmengine - INFO - Epoch(train) [24][660/1793] lr: 7.5000e-03 eta: 4:47:38 time: 0.1733 data_time: 0.0068 memory: 10464 grad_norm: 7.0984 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2311 loss: 2.2311 2022/09/07 20:09:49 - mmengine - INFO - Epoch(train) [24][680/1793] lr: 7.5000e-03 eta: 4:47:27 time: 0.1977 data_time: 0.0092 memory: 10464 grad_norm: 7.0940 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0598 loss: 2.0598 2022/09/07 20:09:52 - mmengine - INFO - Epoch(train) [24][700/1793] lr: 7.5000e-03 eta: 4:47:15 time: 0.1699 data_time: 0.0063 memory: 10464 grad_norm: 7.4625 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.2815 loss: 2.2815 2022/09/07 20:09:56 - mmengine - INFO - Epoch(train) [24][720/1793] lr: 7.5000e-03 eta: 4:47:04 time: 0.1740 data_time: 0.0061 memory: 10464 grad_norm: 7.3625 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0362 loss: 2.0362 2022/09/07 20:09:59 - mmengine - INFO - Epoch(train) [24][740/1793] lr: 7.5000e-03 eta: 4:46:52 time: 0.1752 data_time: 0.0106 memory: 10464 grad_norm: 7.1845 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3084 loss: 2.3084 2022/09/07 20:10:03 - mmengine - INFO - Epoch(train) [24][760/1793] lr: 7.5000e-03 eta: 4:46:41 time: 0.1708 data_time: 0.0065 memory: 10464 grad_norm: 7.4083 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2200 loss: 2.2200 2022/09/07 20:10:03 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:10:06 - mmengine - INFO - Epoch(train) [24][780/1793] lr: 7.5000e-03 eta: 4:46:30 time: 0.1788 data_time: 0.0074 memory: 10464 grad_norm: 7.3753 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.4574 loss: 2.4574 2022/09/07 20:10:10 - mmengine - INFO - Epoch(train) [24][800/1793] lr: 7.5000e-03 eta: 4:46:18 time: 0.1737 data_time: 0.0091 memory: 10464 grad_norm: 7.3743 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0199 loss: 2.0199 2022/09/07 20:10:13 - mmengine - INFO - Epoch(train) [24][820/1793] lr: 7.5000e-03 eta: 4:46:07 time: 0.1716 data_time: 0.0063 memory: 10464 grad_norm: 7.3107 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.9833 loss: 1.9833 2022/09/07 20:10:17 - mmengine - INFO - Epoch(train) [24][840/1793] lr: 7.5000e-03 eta: 4:45:55 time: 0.1819 data_time: 0.0064 memory: 10464 grad_norm: 7.4611 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5988 loss: 2.5988 2022/09/07 20:10:20 - mmengine - INFO - Epoch(train) [24][860/1793] lr: 7.5000e-03 eta: 4:45:44 time: 0.1751 data_time: 0.0114 memory: 10464 grad_norm: 7.1929 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9549 loss: 1.9549 2022/09/07 20:10:24 - mmengine - INFO - Epoch(train) [24][880/1793] lr: 7.5000e-03 eta: 4:45:32 time: 0.1711 data_time: 0.0060 memory: 10464 grad_norm: 7.0654 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1406 loss: 2.1406 2022/09/07 20:10:27 - mmengine - INFO - Epoch(train) [24][900/1793] lr: 7.5000e-03 eta: 4:45:21 time: 0.1768 data_time: 0.0066 memory: 10464 grad_norm: 7.3435 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2218 loss: 2.2218 2022/09/07 20:10:31 - mmengine - INFO - Epoch(train) [24][920/1793] lr: 7.5000e-03 eta: 4:45:10 time: 0.1749 data_time: 0.0095 memory: 10464 grad_norm: 7.1288 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.1894 loss: 2.1894 2022/09/07 20:10:34 - mmengine - INFO - Epoch(train) [24][940/1793] lr: 7.5000e-03 eta: 4:44:58 time: 0.1741 data_time: 0.0063 memory: 10464 grad_norm: 7.5024 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.2860 loss: 2.2860 2022/09/07 20:10:38 - mmengine - INFO - Epoch(train) [24][960/1793] lr: 7.5000e-03 eta: 4:44:47 time: 0.1719 data_time: 0.0075 memory: 10464 grad_norm: 6.9091 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9840 loss: 1.9840 2022/09/07 20:10:41 - mmengine - INFO - Epoch(train) [24][980/1793] lr: 7.5000e-03 eta: 4:44:35 time: 0.1741 data_time: 0.0093 memory: 10464 grad_norm: 7.4894 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.2193 loss: 2.2193 2022/09/07 20:10:44 - mmengine - INFO - Epoch(train) [24][1000/1793] lr: 7.5000e-03 eta: 4:44:24 time: 0.1716 data_time: 0.0063 memory: 10464 grad_norm: 7.0084 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9574 loss: 1.9574 2022/09/07 20:10:48 - mmengine - INFO - Epoch(train) [24][1020/1793] lr: 7.5000e-03 eta: 4:44:13 time: 0.1737 data_time: 0.0076 memory: 10464 grad_norm: 7.0281 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5409 loss: 2.5409 2022/09/07 20:10:51 - mmengine - INFO - Epoch(train) [24][1040/1793] lr: 7.5000e-03 eta: 4:44:01 time: 0.1722 data_time: 0.0094 memory: 10464 grad_norm: 7.1559 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3285 loss: 2.3285 2022/09/07 20:10:55 - mmengine - INFO - Epoch(train) [24][1060/1793] lr: 7.5000e-03 eta: 4:43:50 time: 0.1764 data_time: 0.0065 memory: 10464 grad_norm: 7.3821 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0657 loss: 2.0657 2022/09/07 20:10:58 - mmengine - INFO - Epoch(train) [24][1080/1793] lr: 7.5000e-03 eta: 4:43:39 time: 0.1732 data_time: 0.0071 memory: 10464 grad_norm: 7.1740 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3590 loss: 2.3590 2022/09/07 20:11:02 - mmengine - INFO - Epoch(train) [24][1100/1793] lr: 7.5000e-03 eta: 4:43:27 time: 0.1725 data_time: 0.0083 memory: 10464 grad_norm: 7.4161 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4246 loss: 2.4246 2022/09/07 20:11:05 - mmengine - INFO - Epoch(train) [24][1120/1793] lr: 7.5000e-03 eta: 4:43:16 time: 0.1732 data_time: 0.0070 memory: 10464 grad_norm: 7.1669 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0737 loss: 2.0737 2022/09/07 20:11:09 - mmengine - INFO - Epoch(train) [24][1140/1793] lr: 7.5000e-03 eta: 4:43:05 time: 0.1794 data_time: 0.0069 memory: 10464 grad_norm: 7.3123 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1254 loss: 2.1254 2022/09/07 20:11:12 - mmengine - INFO - Epoch(train) [24][1160/1793] lr: 7.5000e-03 eta: 4:42:53 time: 0.1725 data_time: 0.0090 memory: 10464 grad_norm: 7.4982 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 2.5636 loss: 2.5636 2022/09/07 20:11:16 - mmengine - INFO - Epoch(train) [24][1180/1793] lr: 7.5000e-03 eta: 4:42:42 time: 0.1940 data_time: 0.0076 memory: 10464 grad_norm: 7.0525 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.0706 loss: 2.0706 2022/09/07 20:11:20 - mmengine - INFO - Epoch(train) [24][1200/1793] lr: 7.5000e-03 eta: 4:42:31 time: 0.1703 data_time: 0.0062 memory: 10464 grad_norm: 7.3782 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.2232 loss: 2.2232 2022/09/07 20:11:24 - mmengine - INFO - Epoch(train) [24][1220/1793] lr: 7.5000e-03 eta: 4:42:20 time: 0.1971 data_time: 0.0096 memory: 10464 grad_norm: 7.6943 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.3524 loss: 2.3524 2022/09/07 20:11:28 - mmengine - INFO - Epoch(train) [24][1240/1793] lr: 7.5000e-03 eta: 4:42:09 time: 0.1952 data_time: 0.0063 memory: 10464 grad_norm: 7.6418 top1_acc: 0.1667 top5_acc: 0.1667 loss_cls: 2.2522 loss: 2.2522 2022/09/07 20:11:31 - mmengine - INFO - Epoch(train) [24][1260/1793] lr: 7.5000e-03 eta: 4:41:58 time: 0.1695 data_time: 0.0065 memory: 10464 grad_norm: 7.4416 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.4796 loss: 2.4796 2022/09/07 20:11:34 - mmengine - INFO - Epoch(train) [24][1280/1793] lr: 7.5000e-03 eta: 4:41:47 time: 0.1754 data_time: 0.0090 memory: 10464 grad_norm: 7.4394 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.1148 loss: 2.1148 2022/09/07 20:11:38 - mmengine - INFO - Epoch(train) [24][1300/1793] lr: 7.5000e-03 eta: 4:41:36 time: 0.1725 data_time: 0.0065 memory: 10464 grad_norm: 7.2550 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.2831 loss: 2.2831 2022/09/07 20:11:41 - mmengine - INFO - Epoch(train) [24][1320/1793] lr: 7.5000e-03 eta: 4:41:24 time: 0.1699 data_time: 0.0064 memory: 10464 grad_norm: 7.3973 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1370 loss: 2.1370 2022/09/07 20:11:45 - mmengine - INFO - Epoch(train) [24][1340/1793] lr: 7.5000e-03 eta: 4:41:13 time: 0.1753 data_time: 0.0095 memory: 10464 grad_norm: 7.2569 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.0734 loss: 2.0734 2022/09/07 20:11:48 - mmengine - INFO - Epoch(train) [24][1360/1793] lr: 7.5000e-03 eta: 4:41:02 time: 0.1735 data_time: 0.0064 memory: 10464 grad_norm: 6.9007 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.1873 loss: 2.1873 2022/09/07 20:11:52 - mmengine - INFO - Epoch(train) [24][1380/1793] lr: 7.5000e-03 eta: 4:40:50 time: 0.1709 data_time: 0.0063 memory: 10464 grad_norm: 7.1797 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.9729 loss: 1.9729 2022/09/07 20:11:55 - mmengine - INFO - Epoch(train) [24][1400/1793] lr: 7.5000e-03 eta: 4:40:39 time: 0.1719 data_time: 0.0085 memory: 10464 grad_norm: 7.4499 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3982 loss: 2.3982 2022/09/07 20:11:59 - mmengine - INFO - Epoch(train) [24][1420/1793] lr: 7.5000e-03 eta: 4:40:28 time: 0.1719 data_time: 0.0069 memory: 10464 grad_norm: 6.9578 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0794 loss: 2.0794 2022/09/07 20:12:02 - mmengine - INFO - Epoch(train) [24][1440/1793] lr: 7.5000e-03 eta: 4:40:17 time: 0.1701 data_time: 0.0071 memory: 10464 grad_norm: 7.2544 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1851 loss: 2.1851 2022/09/07 20:12:06 - mmengine - INFO - Epoch(train) [24][1460/1793] lr: 7.5000e-03 eta: 4:40:05 time: 0.1762 data_time: 0.0087 memory: 10464 grad_norm: 7.4182 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.9387 loss: 1.9387 2022/09/07 20:12:09 - mmengine - INFO - Epoch(train) [24][1480/1793] lr: 7.5000e-03 eta: 4:39:54 time: 0.1760 data_time: 0.0076 memory: 10464 grad_norm: 7.1321 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2757 loss: 2.2757 2022/09/07 20:12:12 - mmengine - INFO - Epoch(train) [24][1500/1793] lr: 7.5000e-03 eta: 4:39:43 time: 0.1705 data_time: 0.0065 memory: 10464 grad_norm: 7.4526 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3590 loss: 2.3590 2022/09/07 20:12:16 - mmengine - INFO - Epoch(train) [24][1520/1793] lr: 7.5000e-03 eta: 4:39:32 time: 0.1777 data_time: 0.0083 memory: 10464 grad_norm: 7.3094 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.1954 loss: 2.1954 2022/09/07 20:12:19 - mmengine - INFO - Epoch(train) [24][1540/1793] lr: 7.5000e-03 eta: 4:39:21 time: 0.1709 data_time: 0.0065 memory: 10464 grad_norm: 7.2248 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1689 loss: 2.1689 2022/09/07 20:12:23 - mmengine - INFO - Epoch(train) [24][1560/1793] lr: 7.5000e-03 eta: 4:39:09 time: 0.1724 data_time: 0.0071 memory: 10464 grad_norm: 7.3102 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.8961 loss: 1.8961 2022/09/07 20:12:27 - mmengine - INFO - Epoch(train) [24][1580/1793] lr: 7.5000e-03 eta: 4:38:58 time: 0.1850 data_time: 0.0106 memory: 10464 grad_norm: 7.2469 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1361 loss: 2.1361 2022/09/07 20:12:30 - mmengine - INFO - Epoch(train) [24][1600/1793] lr: 7.5000e-03 eta: 4:38:47 time: 0.1702 data_time: 0.0065 memory: 10464 grad_norm: 7.1360 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0062 loss: 2.0062 2022/09/07 20:12:33 - mmengine - INFO - Epoch(train) [24][1620/1793] lr: 7.5000e-03 eta: 4:38:36 time: 0.1747 data_time: 0.0060 memory: 10464 grad_norm: 7.2196 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 1.9650 loss: 1.9650 2022/09/07 20:12:37 - mmengine - INFO - Epoch(train) [24][1640/1793] lr: 7.5000e-03 eta: 4:38:25 time: 0.1752 data_time: 0.0099 memory: 10464 grad_norm: 7.2720 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3115 loss: 2.3115 2022/09/07 20:12:40 - mmengine - INFO - Epoch(train) [24][1660/1793] lr: 7.5000e-03 eta: 4:38:14 time: 0.1707 data_time: 0.0064 memory: 10464 grad_norm: 7.1812 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4682 loss: 2.4682 2022/09/07 20:12:44 - mmengine - INFO - Epoch(train) [24][1680/1793] lr: 7.5000e-03 eta: 4:38:03 time: 0.1750 data_time: 0.0063 memory: 10464 grad_norm: 7.4879 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1816 loss: 2.1816 2022/09/07 20:12:48 - mmengine - INFO - Epoch(train) [24][1700/1793] lr: 7.5000e-03 eta: 4:37:52 time: 0.1914 data_time: 0.0108 memory: 10464 grad_norm: 7.3637 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1985 loss: 2.1985 2022/09/07 20:12:51 - mmengine - INFO - Epoch(train) [24][1720/1793] lr: 7.5000e-03 eta: 4:37:41 time: 0.1700 data_time: 0.0064 memory: 10464 grad_norm: 7.4356 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.1613 loss: 2.1613 2022/09/07 20:12:55 - mmengine - INFO - Epoch(train) [24][1740/1793] lr: 7.5000e-03 eta: 4:37:30 time: 0.1724 data_time: 0.0062 memory: 10464 grad_norm: 7.4667 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.5461 loss: 2.5461 2022/09/07 20:12:58 - mmengine - INFO - Epoch(train) [24][1760/1793] lr: 7.5000e-03 eta: 4:37:18 time: 0.1723 data_time: 0.0084 memory: 10464 grad_norm: 7.4086 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1225 loss: 2.1225 2022/09/07 20:12:58 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:13:01 - mmengine - INFO - Epoch(train) [24][1780/1793] lr: 7.5000e-03 eta: 4:37:07 time: 0.1699 data_time: 0.0064 memory: 10464 grad_norm: 7.5518 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.1296 loss: 2.1296 2022/09/07 20:13:04 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:13:04 - mmengine - INFO - Epoch(train) [24][1793/1793] lr: 7.5000e-03 eta: 4:37:07 time: 0.1728 data_time: 0.0071 memory: 10464 grad_norm: 7.5798 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 2.5163 loss: 2.5163 2022/09/07 20:13:04 - mmengine - INFO - Saving checkpoint at 24 epochs 2022/09/07 20:13:08 - mmengine - INFO - Epoch(val) [24][20/241] eta: 0:00:16 time: 0.0731 data_time: 0.0243 memory: 1482 2022/09/07 20:13:09 - mmengine - INFO - Epoch(val) [24][40/241] eta: 0:00:12 time: 0.0629 data_time: 0.0142 memory: 1482 2022/09/07 20:13:10 - mmengine - INFO - Epoch(val) [24][60/241] eta: 0:00:09 time: 0.0534 data_time: 0.0048 memory: 1482 2022/09/07 20:13:11 - mmengine - INFO - Epoch(val) [24][80/241] eta: 0:00:08 time: 0.0531 data_time: 0.0047 memory: 1482 2022/09/07 20:13:12 - mmengine - INFO - Epoch(val) [24][100/241] eta: 0:00:07 time: 0.0538 data_time: 0.0051 memory: 1482 2022/09/07 20:13:13 - mmengine - INFO - Epoch(val) [24][120/241] eta: 0:00:06 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 20:13:14 - mmengine - INFO - Epoch(val) [24][140/241] eta: 0:00:05 time: 0.0534 data_time: 0.0048 memory: 1482 2022/09/07 20:13:15 - mmengine - INFO - Epoch(val) [24][160/241] eta: 0:00:04 time: 0.0539 data_time: 0.0050 memory: 1482 2022/09/07 20:13:16 - mmengine - INFO - Epoch(val) [24][180/241] eta: 0:00:03 time: 0.0565 data_time: 0.0048 memory: 1482 2022/09/07 20:13:17 - mmengine - INFO - Epoch(val) [24][200/241] eta: 0:00:02 time: 0.0530 data_time: 0.0048 memory: 1482 2022/09/07 20:13:18 - mmengine - INFO - Epoch(val) [24][220/241] eta: 0:00:01 time: 0.0531 data_time: 0.0049 memory: 1482 2022/09/07 20:13:20 - mmengine - INFO - Epoch(val) [24][240/241] eta: 0:00:00 time: 0.0530 data_time: 0.0048 memory: 1482 2022/09/07 20:13:20 - mmengine - INFO - Epoch(val) [24][241/241] acc/top1: 0.3414 acc/top5: 0.6465 acc/mean1: 0.3205 2022/09/07 20:13:20 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_22.pth is removed 2022/09/07 20:13:22 - mmengine - INFO - The best checkpoint with 0.3414 acc/top1 at 24 epoch is saved to best_acc/top1_epoch_24.pth. 2022/09/07 20:13:26 - mmengine - INFO - Epoch(train) [25][20/1793] lr: 7.5000e-03 eta: 4:36:47 time: 0.1786 data_time: 0.0099 memory: 10464 grad_norm: 6.8975 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1520 loss: 2.1520 2022/09/07 20:13:29 - mmengine - INFO - Epoch(train) [25][40/1793] lr: 7.5000e-03 eta: 4:36:35 time: 0.1708 data_time: 0.0063 memory: 10464 grad_norm: 7.3169 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2020 loss: 2.2020 2022/09/07 20:13:32 - mmengine - INFO - Epoch(train) [25][60/1793] lr: 7.5000e-03 eta: 4:36:24 time: 0.1701 data_time: 0.0062 memory: 10464 grad_norm: 7.4779 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.8357 loss: 1.8357 2022/09/07 20:13:36 - mmengine - INFO - Epoch(train) [25][80/1793] lr: 7.5000e-03 eta: 4:36:13 time: 0.1770 data_time: 0.0085 memory: 10464 grad_norm: 7.2617 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 1.7543 loss: 1.7543 2022/09/07 20:13:40 - mmengine - INFO - Epoch(train) [25][100/1793] lr: 7.5000e-03 eta: 4:36:03 time: 0.1986 data_time: 0.0075 memory: 10464 grad_norm: 7.3016 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.0912 loss: 2.0912 2022/09/07 20:13:43 - mmengine - INFO - Epoch(train) [25][120/1793] lr: 7.5000e-03 eta: 4:35:52 time: 0.1699 data_time: 0.0065 memory: 10464 grad_norm: 7.0886 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.1273 loss: 2.1273 2022/09/07 20:13:47 - mmengine - INFO - Epoch(train) [25][140/1793] lr: 7.5000e-03 eta: 4:35:41 time: 0.1771 data_time: 0.0108 memory: 10464 grad_norm: 7.4742 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.0085 loss: 2.0085 2022/09/07 20:13:50 - mmengine - INFO - Epoch(train) [25][160/1793] lr: 7.5000e-03 eta: 4:35:30 time: 0.1718 data_time: 0.0072 memory: 10464 grad_norm: 7.3253 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.2362 loss: 2.2362 2022/09/07 20:13:54 - mmengine - INFO - Epoch(train) [25][180/1793] lr: 7.5000e-03 eta: 4:35:19 time: 0.1740 data_time: 0.0064 memory: 10464 grad_norm: 7.3572 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2846 loss: 2.2846 2022/09/07 20:13:57 - mmengine - INFO - Epoch(train) [25][200/1793] lr: 7.5000e-03 eta: 4:35:08 time: 0.1751 data_time: 0.0088 memory: 10464 grad_norm: 7.4187 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0229 loss: 2.0229 2022/09/07 20:14:01 - mmengine - INFO - Epoch(train) [25][220/1793] lr: 7.5000e-03 eta: 4:34:57 time: 0.1778 data_time: 0.0062 memory: 10464 grad_norm: 7.6160 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.0411 loss: 2.0411 2022/09/07 20:14:04 - mmengine - INFO - Epoch(train) [25][240/1793] lr: 7.5000e-03 eta: 4:34:46 time: 0.1795 data_time: 0.0065 memory: 10464 grad_norm: 7.3537 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1824 loss: 2.1824 2022/09/07 20:14:08 - mmengine - INFO - Epoch(train) [25][260/1793] lr: 7.5000e-03 eta: 4:34:35 time: 0.1739 data_time: 0.0089 memory: 10464 grad_norm: 7.2844 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1305 loss: 2.1305 2022/09/07 20:14:11 - mmengine - INFO - Epoch(train) [25][280/1793] lr: 7.5000e-03 eta: 4:34:24 time: 0.1704 data_time: 0.0062 memory: 10464 grad_norm: 7.2993 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.2151 loss: 2.2151 2022/09/07 20:14:15 - mmengine - INFO - Epoch(train) [25][300/1793] lr: 7.5000e-03 eta: 4:34:13 time: 0.1912 data_time: 0.0067 memory: 10464 grad_norm: 7.5878 top1_acc: 0.0000 top5_acc: 0.8333 loss_cls: 2.2339 loss: 2.2339 2022/09/07 20:14:19 - mmengine - INFO - Epoch(train) [25][320/1793] lr: 7.5000e-03 eta: 4:34:02 time: 0.1809 data_time: 0.0096 memory: 10464 grad_norm: 7.2154 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.9016 loss: 1.9016 2022/09/07 20:14:22 - mmengine - INFO - Epoch(train) [25][340/1793] lr: 7.5000e-03 eta: 4:33:51 time: 0.1705 data_time: 0.0063 memory: 10464 grad_norm: 7.3735 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1867 loss: 2.1867 2022/09/07 20:14:26 - mmengine - INFO - Epoch(train) [25][360/1793] lr: 7.5000e-03 eta: 4:33:40 time: 0.1715 data_time: 0.0062 memory: 10464 grad_norm: 7.5256 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2994 loss: 2.2994 2022/09/07 20:14:29 - mmengine - INFO - Epoch(train) [25][380/1793] lr: 7.5000e-03 eta: 4:33:29 time: 0.1761 data_time: 0.0106 memory: 10464 grad_norm: 7.2955 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.2501 loss: 2.2501 2022/09/07 20:14:33 - mmengine - INFO - Epoch(train) [25][400/1793] lr: 7.5000e-03 eta: 4:33:18 time: 0.1719 data_time: 0.0056 memory: 10464 grad_norm: 7.5128 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.1768 loss: 2.1768 2022/09/07 20:14:36 - mmengine - INFO - Epoch(train) [25][420/1793] lr: 7.5000e-03 eta: 4:33:08 time: 0.1866 data_time: 0.0069 memory: 10464 grad_norm: 7.5880 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3621 loss: 2.3621 2022/09/07 20:14:40 - mmengine - INFO - Epoch(train) [25][440/1793] lr: 7.5000e-03 eta: 4:32:57 time: 0.1751 data_time: 0.0091 memory: 10464 grad_norm: 7.3758 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0234 loss: 2.0234 2022/09/07 20:14:43 - mmengine - INFO - Epoch(train) [25][460/1793] lr: 7.5000e-03 eta: 4:32:46 time: 0.1707 data_time: 0.0066 memory: 10464 grad_norm: 7.3586 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4247 loss: 2.4247 2022/09/07 20:14:48 - mmengine - INFO - Epoch(train) [25][480/1793] lr: 7.5000e-03 eta: 4:32:36 time: 0.2452 data_time: 0.0052 memory: 10464 grad_norm: 7.0521 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.1431 loss: 2.1431 2022/09/07 20:14:52 - mmengine - INFO - Epoch(train) [25][500/1793] lr: 7.5000e-03 eta: 4:32:26 time: 0.1773 data_time: 0.0106 memory: 10464 grad_norm: 7.2141 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1826 loss: 2.1826 2022/09/07 20:14:55 - mmengine - INFO - Epoch(train) [25][520/1793] lr: 7.5000e-03 eta: 4:32:15 time: 0.1779 data_time: 0.0064 memory: 10464 grad_norm: 7.2264 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4076 loss: 2.4076 2022/09/07 20:14:59 - mmengine - INFO - Epoch(train) [25][540/1793] lr: 7.5000e-03 eta: 4:32:04 time: 0.1751 data_time: 0.0069 memory: 10464 grad_norm: 7.3665 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.3135 loss: 2.3135 2022/09/07 20:15:02 - mmengine - INFO - Epoch(train) [25][560/1793] lr: 7.5000e-03 eta: 4:31:53 time: 0.1761 data_time: 0.0091 memory: 10464 grad_norm: 7.3133 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.1716 loss: 2.1716 2022/09/07 20:15:06 - mmengine - INFO - Epoch(train) [25][580/1793] lr: 7.5000e-03 eta: 4:31:42 time: 0.1763 data_time: 0.0060 memory: 10464 grad_norm: 7.0861 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.3298 loss: 2.3298 2022/09/07 20:15:09 - mmengine - INFO - Epoch(train) [25][600/1793] lr: 7.5000e-03 eta: 4:31:31 time: 0.1800 data_time: 0.0087 memory: 10464 grad_norm: 7.2648 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3066 loss: 2.3066 2022/09/07 20:15:13 - mmengine - INFO - Epoch(train) [25][620/1793] lr: 7.5000e-03 eta: 4:31:21 time: 0.1753 data_time: 0.0083 memory: 10464 grad_norm: 7.2818 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.0926 loss: 2.0926 2022/09/07 20:15:17 - mmengine - INFO - Epoch(train) [25][640/1793] lr: 7.5000e-03 eta: 4:31:10 time: 0.1860 data_time: 0.0072 memory: 10464 grad_norm: 7.3174 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1065 loss: 2.1065 2022/09/07 20:15:20 - mmengine - INFO - Epoch(train) [25][660/1793] lr: 7.5000e-03 eta: 4:30:59 time: 0.1820 data_time: 0.0063 memory: 10464 grad_norm: 7.6261 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1026 loss: 2.1026 2022/09/07 20:15:24 - mmengine - INFO - Epoch(train) [25][680/1793] lr: 7.5000e-03 eta: 4:30:48 time: 0.1744 data_time: 0.0083 memory: 10464 grad_norm: 7.3710 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4258 loss: 2.4258 2022/09/07 20:15:27 - mmengine - INFO - Epoch(train) [25][700/1793] lr: 7.5000e-03 eta: 4:30:38 time: 0.1745 data_time: 0.0082 memory: 10464 grad_norm: 7.0975 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.9555 loss: 1.9555 2022/09/07 20:15:31 - mmengine - INFO - Epoch(train) [25][720/1793] lr: 7.5000e-03 eta: 4:30:27 time: 0.1723 data_time: 0.0061 memory: 10464 grad_norm: 7.1603 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0348 loss: 2.0348 2022/09/07 20:15:34 - mmengine - INFO - Epoch(train) [25][740/1793] lr: 7.5000e-03 eta: 4:30:16 time: 0.1825 data_time: 0.0098 memory: 10464 grad_norm: 7.0571 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.9905 loss: 1.9905 2022/09/07 20:15:38 - mmengine - INFO - Epoch(train) [25][760/1793] lr: 7.5000e-03 eta: 4:30:05 time: 0.1736 data_time: 0.0067 memory: 10464 grad_norm: 7.2167 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3637 loss: 2.3637 2022/09/07 20:15:41 - mmengine - INFO - Epoch(train) [25][780/1793] lr: 7.5000e-03 eta: 4:29:54 time: 0.1710 data_time: 0.0057 memory: 10464 grad_norm: 7.3188 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4604 loss: 2.4604 2022/09/07 20:15:45 - mmengine - INFO - Epoch(train) [25][800/1793] lr: 7.5000e-03 eta: 4:29:43 time: 0.1749 data_time: 0.0091 memory: 10464 grad_norm: 7.1889 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.0127 loss: 2.0127 2022/09/07 20:15:48 - mmengine - INFO - Epoch(train) [25][820/1793] lr: 7.5000e-03 eta: 4:29:33 time: 0.1767 data_time: 0.0074 memory: 10464 grad_norm: 7.5643 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0189 loss: 2.0189 2022/09/07 20:15:52 - mmengine - INFO - Epoch(train) [25][840/1793] lr: 7.5000e-03 eta: 4:29:22 time: 0.1700 data_time: 0.0064 memory: 10464 grad_norm: 7.3841 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.2844 loss: 2.2844 2022/09/07 20:15:55 - mmengine - INFO - Epoch(train) [25][860/1793] lr: 7.5000e-03 eta: 4:29:11 time: 0.1753 data_time: 0.0089 memory: 10464 grad_norm: 7.3768 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.0428 loss: 2.0428 2022/09/07 20:15:59 - mmengine - INFO - Epoch(train) [25][880/1793] lr: 7.5000e-03 eta: 4:29:00 time: 0.1753 data_time: 0.0066 memory: 10464 grad_norm: 7.2192 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.1076 loss: 2.1076 2022/09/07 20:16:02 - mmengine - INFO - Epoch(train) [25][900/1793] lr: 7.5000e-03 eta: 4:28:49 time: 0.1724 data_time: 0.0069 memory: 10464 grad_norm: 7.1360 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0949 loss: 2.0949 2022/09/07 20:16:06 - mmengine - INFO - Epoch(train) [25][920/1793] lr: 7.5000e-03 eta: 4:28:39 time: 0.1737 data_time: 0.0094 memory: 10464 grad_norm: 7.1063 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 2.3381 loss: 2.3381 2022/09/07 20:16:09 - mmengine - INFO - Epoch(train) [25][940/1793] lr: 7.5000e-03 eta: 4:28:28 time: 0.1785 data_time: 0.0070 memory: 10464 grad_norm: 6.9893 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.9477 loss: 1.9477 2022/09/07 20:16:13 - mmengine - INFO - Epoch(train) [25][960/1793] lr: 7.5000e-03 eta: 4:28:17 time: 0.1708 data_time: 0.0069 memory: 10464 grad_norm: 7.5308 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1440 loss: 2.1440 2022/09/07 20:16:14 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:16:17 - mmengine - INFO - Epoch(train) [25][980/1793] lr: 7.5000e-03 eta: 4:28:07 time: 0.1938 data_time: 0.0090 memory: 10464 grad_norm: 7.2691 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1759 loss: 2.1759 2022/09/07 20:16:20 - mmengine - INFO - Epoch(train) [25][1000/1793] lr: 7.5000e-03 eta: 4:27:56 time: 0.1728 data_time: 0.0059 memory: 10464 grad_norm: 7.4295 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3652 loss: 2.3652 2022/09/07 20:16:23 - mmengine - INFO - Epoch(train) [25][1020/1793] lr: 7.5000e-03 eta: 4:27:45 time: 0.1703 data_time: 0.0063 memory: 10464 grad_norm: 6.9752 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.8852 loss: 1.8852 2022/09/07 20:16:27 - mmengine - INFO - Epoch(train) [25][1040/1793] lr: 7.5000e-03 eta: 4:27:35 time: 0.1805 data_time: 0.0090 memory: 10464 grad_norm: 7.3983 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3096 loss: 2.3096 2022/09/07 20:16:30 - mmengine - INFO - Epoch(train) [25][1060/1793] lr: 7.5000e-03 eta: 4:27:24 time: 0.1740 data_time: 0.0069 memory: 10464 grad_norm: 7.1041 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2340 loss: 2.2340 2022/09/07 20:16:34 - mmengine - INFO - Epoch(train) [25][1080/1793] lr: 7.5000e-03 eta: 4:27:14 time: 0.1906 data_time: 0.0061 memory: 10464 grad_norm: 7.3324 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.2127 loss: 2.2127 2022/09/07 20:16:38 - mmengine - INFO - Epoch(train) [25][1100/1793] lr: 7.5000e-03 eta: 4:27:03 time: 0.1791 data_time: 0.0088 memory: 10464 grad_norm: 7.5844 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.0915 loss: 2.0915 2022/09/07 20:16:41 - mmengine - INFO - Epoch(train) [25][1120/1793] lr: 7.5000e-03 eta: 4:26:52 time: 0.1746 data_time: 0.0066 memory: 10464 grad_norm: 7.0948 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3720 loss: 2.3720 2022/09/07 20:16:45 - mmengine - INFO - Epoch(train) [25][1140/1793] lr: 7.5000e-03 eta: 4:26:42 time: 0.1736 data_time: 0.0067 memory: 10464 grad_norm: 7.3080 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0368 loss: 2.0368 2022/09/07 20:16:48 - mmengine - INFO - Epoch(train) [25][1160/1793] lr: 7.5000e-03 eta: 4:26:31 time: 0.1810 data_time: 0.0083 memory: 10464 grad_norm: 7.1389 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.9825 loss: 1.9825 2022/09/07 20:16:52 - mmengine - INFO - Epoch(train) [25][1180/1793] lr: 7.5000e-03 eta: 4:26:20 time: 0.1732 data_time: 0.0069 memory: 10464 grad_norm: 6.9669 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.1133 loss: 2.1133 2022/09/07 20:16:56 - mmengine - INFO - Epoch(train) [25][1200/1793] lr: 7.5000e-03 eta: 4:26:10 time: 0.1797 data_time: 0.0065 memory: 10464 grad_norm: 7.3669 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5113 loss: 2.5113 2022/09/07 20:16:59 - mmengine - INFO - Epoch(train) [25][1220/1793] lr: 7.5000e-03 eta: 4:25:59 time: 0.1754 data_time: 0.0088 memory: 10464 grad_norm: 7.1530 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0215 loss: 2.0215 2022/09/07 20:17:02 - mmengine - INFO - Epoch(train) [25][1240/1793] lr: 7.5000e-03 eta: 4:25:48 time: 0.1713 data_time: 0.0071 memory: 10464 grad_norm: 7.0605 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.1754 loss: 2.1754 2022/09/07 20:17:06 - mmengine - INFO - Epoch(train) [25][1260/1793] lr: 7.5000e-03 eta: 4:25:38 time: 0.1832 data_time: 0.0052 memory: 10464 grad_norm: 7.2636 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.1498 loss: 2.1498 2022/09/07 20:17:10 - mmengine - INFO - Epoch(train) [25][1280/1793] lr: 7.5000e-03 eta: 4:25:27 time: 0.1770 data_time: 0.0107 memory: 10464 grad_norm: 7.2881 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0944 loss: 2.0944 2022/09/07 20:17:13 - mmengine - INFO - Epoch(train) [25][1300/1793] lr: 7.5000e-03 eta: 4:25:17 time: 0.1726 data_time: 0.0062 memory: 10464 grad_norm: 7.5928 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 2.7301 loss: 2.7301 2022/09/07 20:17:18 - mmengine - INFO - Epoch(train) [25][1320/1793] lr: 7.5000e-03 eta: 4:25:07 time: 0.2466 data_time: 0.0067 memory: 10464 grad_norm: 7.0879 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.3326 loss: 2.3326 2022/09/07 20:17:22 - mmengine - INFO - Epoch(train) [25][1340/1793] lr: 7.5000e-03 eta: 4:24:57 time: 0.1725 data_time: 0.0086 memory: 10464 grad_norm: 7.3771 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3213 loss: 2.3213 2022/09/07 20:17:25 - mmengine - INFO - Epoch(train) [25][1360/1793] lr: 7.5000e-03 eta: 4:24:46 time: 0.1728 data_time: 0.0064 memory: 10464 grad_norm: 7.4033 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3548 loss: 2.3548 2022/09/07 20:17:29 - mmengine - INFO - Epoch(train) [25][1380/1793] lr: 7.5000e-03 eta: 4:24:35 time: 0.1745 data_time: 0.0067 memory: 10464 grad_norm: 7.2721 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.1716 loss: 2.1716 2022/09/07 20:17:32 - mmengine - INFO - Epoch(train) [25][1400/1793] lr: 7.5000e-03 eta: 4:24:25 time: 0.1763 data_time: 0.0094 memory: 10464 grad_norm: 7.3551 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.9657 loss: 1.9657 2022/09/07 20:17:36 - mmengine - INFO - Epoch(train) [25][1420/1793] lr: 7.5000e-03 eta: 4:24:15 time: 0.1978 data_time: 0.0069 memory: 10464 grad_norm: 7.1412 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.1054 loss: 2.1054 2022/09/07 20:17:39 - mmengine - INFO - Epoch(train) [25][1440/1793] lr: 7.5000e-03 eta: 4:24:04 time: 0.1729 data_time: 0.0059 memory: 10464 grad_norm: 7.0590 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.9931 loss: 1.9931 2022/09/07 20:17:43 - mmengine - INFO - Epoch(train) [25][1460/1793] lr: 7.5000e-03 eta: 4:23:54 time: 0.1740 data_time: 0.0094 memory: 10464 grad_norm: 7.2242 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.2566 loss: 2.2566 2022/09/07 20:17:46 - mmengine - INFO - Epoch(train) [25][1480/1793] lr: 7.5000e-03 eta: 4:23:43 time: 0.1732 data_time: 0.0066 memory: 10464 grad_norm: 7.3039 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.1170 loss: 2.1170 2022/09/07 20:17:50 - mmengine - INFO - Epoch(train) [25][1500/1793] lr: 7.5000e-03 eta: 4:23:32 time: 0.1780 data_time: 0.0076 memory: 10464 grad_norm: 7.2053 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.8427 loss: 1.8427 2022/09/07 20:17:53 - mmengine - INFO - Epoch(train) [25][1520/1793] lr: 7.5000e-03 eta: 4:23:22 time: 0.1745 data_time: 0.0090 memory: 10464 grad_norm: 7.4467 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3085 loss: 2.3085 2022/09/07 20:17:57 - mmengine - INFO - Epoch(train) [25][1540/1793] lr: 7.5000e-03 eta: 4:23:12 time: 0.1855 data_time: 0.0075 memory: 10464 grad_norm: 7.2883 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8967 loss: 1.8967 2022/09/07 20:18:01 - mmengine - INFO - Epoch(train) [25][1560/1793] lr: 7.5000e-03 eta: 4:23:01 time: 0.1740 data_time: 0.0065 memory: 10464 grad_norm: 7.0665 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1369 loss: 2.1369 2022/09/07 20:18:04 - mmengine - INFO - Epoch(train) [25][1580/1793] lr: 7.5000e-03 eta: 4:22:50 time: 0.1791 data_time: 0.0084 memory: 10464 grad_norm: 7.5670 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1660 loss: 2.1660 2022/09/07 20:18:08 - mmengine - INFO - Epoch(train) [25][1600/1793] lr: 7.5000e-03 eta: 4:22:40 time: 0.1791 data_time: 0.0061 memory: 10464 grad_norm: 7.4262 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.2340 loss: 2.2340 2022/09/07 20:18:11 - mmengine - INFO - Epoch(train) [25][1620/1793] lr: 7.5000e-03 eta: 4:22:29 time: 0.1739 data_time: 0.0063 memory: 10464 grad_norm: 7.2137 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0183 loss: 2.0183 2022/09/07 20:18:15 - mmengine - INFO - Epoch(train) [25][1640/1793] lr: 7.5000e-03 eta: 4:22:19 time: 0.1821 data_time: 0.0086 memory: 10464 grad_norm: 7.1105 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3718 loss: 2.3718 2022/09/07 20:18:18 - mmengine - INFO - Epoch(train) [25][1660/1793] lr: 7.5000e-03 eta: 4:22:09 time: 0.1722 data_time: 0.0060 memory: 10464 grad_norm: 7.1053 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1097 loss: 2.1097 2022/09/07 20:18:22 - mmengine - INFO - Epoch(train) [25][1680/1793] lr: 7.5000e-03 eta: 4:21:58 time: 0.1714 data_time: 0.0061 memory: 10464 grad_norm: 7.5470 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2276 loss: 2.2276 2022/09/07 20:18:25 - mmengine - INFO - Epoch(train) [25][1700/1793] lr: 7.5000e-03 eta: 4:21:47 time: 0.1745 data_time: 0.0085 memory: 10464 grad_norm: 7.5212 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1837 loss: 2.1837 2022/09/07 20:18:29 - mmengine - INFO - Epoch(train) [25][1720/1793] lr: 7.5000e-03 eta: 4:21:37 time: 0.1766 data_time: 0.0072 memory: 10464 grad_norm: 7.2029 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.9795 loss: 1.9795 2022/09/07 20:18:32 - mmengine - INFO - Epoch(train) [25][1740/1793] lr: 7.5000e-03 eta: 4:21:26 time: 0.1735 data_time: 0.0067 memory: 10464 grad_norm: 7.1671 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4060 loss: 2.4060 2022/09/07 20:18:36 - mmengine - INFO - Epoch(train) [25][1760/1793] lr: 7.5000e-03 eta: 4:21:16 time: 0.1814 data_time: 0.0090 memory: 10464 grad_norm: 7.6046 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.1391 loss: 2.1391 2022/09/07 20:18:39 - mmengine - INFO - Epoch(train) [25][1780/1793] lr: 7.5000e-03 eta: 4:21:06 time: 0.1729 data_time: 0.0068 memory: 10464 grad_norm: 7.6834 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.0198 loss: 2.0198 2022/09/07 20:18:42 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:18:42 - mmengine - INFO - Epoch(train) [25][1793/1793] lr: 7.5000e-03 eta: 4:21:06 time: 0.1875 data_time: 0.0065 memory: 10464 grad_norm: 8.3812 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.3055 loss: 2.3055 2022/09/07 20:18:42 - mmengine - INFO - Saving checkpoint at 25 epochs 2022/09/07 20:18:46 - mmengine - INFO - Epoch(val) [25][20/241] eta: 0:00:12 time: 0.0586 data_time: 0.0092 memory: 1482 2022/09/07 20:18:47 - mmengine - INFO - Epoch(val) [25][40/241] eta: 0:00:10 time: 0.0534 data_time: 0.0048 memory: 1482 2022/09/07 20:18:48 - mmengine - INFO - Epoch(val) [25][60/241] eta: 0:00:09 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 20:18:49 - mmengine - INFO - Epoch(val) [25][80/241] eta: 0:00:08 time: 0.0535 data_time: 0.0051 memory: 1482 2022/09/07 20:18:50 - mmengine - INFO - Epoch(val) [25][100/241] eta: 0:00:07 time: 0.0536 data_time: 0.0049 memory: 1482 2022/09/07 20:18:51 - mmengine - INFO - Epoch(val) [25][120/241] eta: 0:00:06 time: 0.0538 data_time: 0.0051 memory: 1482 2022/09/07 20:18:52 - mmengine - INFO - Epoch(val) [25][140/241] eta: 0:00:05 time: 0.0535 data_time: 0.0051 memory: 1482 2022/09/07 20:18:53 - mmengine - INFO - Epoch(val) [25][160/241] eta: 0:00:04 time: 0.0538 data_time: 0.0052 memory: 1482 2022/09/07 20:18:54 - mmengine - INFO - Epoch(val) [25][180/241] eta: 0:00:03 time: 0.0535 data_time: 0.0049 memory: 1482 2022/09/07 20:18:55 - mmengine - INFO - Epoch(val) [25][200/241] eta: 0:00:02 time: 0.0531 data_time: 0.0047 memory: 1482 2022/09/07 20:18:56 - mmengine - INFO - Epoch(val) [25][220/241] eta: 0:00:01 time: 0.0530 data_time: 0.0048 memory: 1482 2022/09/07 20:18:58 - mmengine - INFO - Epoch(val) [25][240/241] eta: 0:00:00 time: 0.0588 data_time: 0.0056 memory: 1482 2022/09/07 20:18:58 - mmengine - INFO - Epoch(val) [25][241/241] acc/top1: 0.3529 acc/top5: 0.6561 acc/mean1: 0.3212 2022/09/07 20:18:58 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_24.pth is removed 2022/09/07 20:19:00 - mmengine - INFO - The best checkpoint with 0.3529 acc/top1 at 25 epoch is saved to best_acc/top1_epoch_25.pth. 2022/09/07 20:19:04 - mmengine - INFO - Epoch(train) [26][20/1793] lr: 7.5000e-03 eta: 4:20:47 time: 0.2401 data_time: 0.0489 memory: 10464 grad_norm: 7.3483 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.2264 loss: 2.2264 2022/09/07 20:19:08 - mmengine - INFO - Epoch(train) [26][40/1793] lr: 7.5000e-03 eta: 4:20:37 time: 0.1733 data_time: 0.0070 memory: 10464 grad_norm: 7.4491 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.0738 loss: 2.0738 2022/09/07 20:19:11 - mmengine - INFO - Epoch(train) [26][60/1793] lr: 7.5000e-03 eta: 4:20:26 time: 0.1726 data_time: 0.0062 memory: 10464 grad_norm: 7.2647 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3195 loss: 2.3195 2022/09/07 20:19:15 - mmengine - INFO - Epoch(train) [26][80/1793] lr: 7.5000e-03 eta: 4:20:16 time: 0.1865 data_time: 0.0107 memory: 10464 grad_norm: 7.6288 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1818 loss: 2.1818 2022/09/07 20:19:19 - mmengine - INFO - Epoch(train) [26][100/1793] lr: 7.5000e-03 eta: 4:20:06 time: 0.1759 data_time: 0.0056 memory: 10464 grad_norm: 7.2547 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.2373 loss: 2.2373 2022/09/07 20:19:22 - mmengine - INFO - Epoch(train) [26][120/1793] lr: 7.5000e-03 eta: 4:19:55 time: 0.1718 data_time: 0.0062 memory: 10464 grad_norm: 7.4074 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.1855 loss: 2.1855 2022/09/07 20:19:26 - mmengine - INFO - Epoch(train) [26][140/1793] lr: 7.5000e-03 eta: 4:19:45 time: 0.1778 data_time: 0.0090 memory: 10464 grad_norm: 7.1411 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.8337 loss: 1.8337 2022/09/07 20:19:29 - mmengine - INFO - Epoch(train) [26][160/1793] lr: 7.5000e-03 eta: 4:19:34 time: 0.1745 data_time: 0.0069 memory: 10464 grad_norm: 7.3996 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5087 loss: 2.5087 2022/09/07 20:19:32 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:19:33 - mmengine - INFO - Epoch(train) [26][180/1793] lr: 7.5000e-03 eta: 4:19:24 time: 0.1741 data_time: 0.0066 memory: 10464 grad_norm: 7.3288 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.8621 loss: 1.8621 2022/09/07 20:19:36 - mmengine - INFO - Epoch(train) [26][200/1793] lr: 7.5000e-03 eta: 4:19:14 time: 0.1870 data_time: 0.0079 memory: 10464 grad_norm: 7.2663 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1722 loss: 2.1722 2022/09/07 20:19:40 - mmengine - INFO - Epoch(train) [26][220/1793] lr: 7.5000e-03 eta: 4:19:03 time: 0.1758 data_time: 0.0060 memory: 10464 grad_norm: 7.2377 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4212 loss: 2.4212 2022/09/07 20:19:43 - mmengine - INFO - Epoch(train) [26][240/1793] lr: 7.5000e-03 eta: 4:18:53 time: 0.1739 data_time: 0.0059 memory: 10464 grad_norm: 7.3019 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.9410 loss: 1.9410 2022/09/07 20:19:47 - mmengine - INFO - Epoch(train) [26][260/1793] lr: 7.5000e-03 eta: 4:18:43 time: 0.1856 data_time: 0.0102 memory: 10464 grad_norm: 7.5627 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2958 loss: 2.2958 2022/09/07 20:19:51 - mmengine - INFO - Epoch(train) [26][280/1793] lr: 7.5000e-03 eta: 4:18:32 time: 0.1724 data_time: 0.0062 memory: 10464 grad_norm: 7.2042 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.1787 loss: 2.1787 2022/09/07 20:19:54 - mmengine - INFO - Epoch(train) [26][300/1793] lr: 7.5000e-03 eta: 4:18:22 time: 0.1746 data_time: 0.0074 memory: 10464 grad_norm: 7.3074 top1_acc: 0.1667 top5_acc: 1.0000 loss_cls: 2.5650 loss: 2.5650 2022/09/07 20:19:58 - mmengine - INFO - Epoch(train) [26][320/1793] lr: 7.5000e-03 eta: 4:18:12 time: 0.1775 data_time: 0.0076 memory: 10464 grad_norm: 7.2081 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8145 loss: 1.8145 2022/09/07 20:20:01 - mmengine - INFO - Epoch(train) [26][340/1793] lr: 7.5000e-03 eta: 4:18:01 time: 0.1739 data_time: 0.0062 memory: 10464 grad_norm: 7.4115 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2650 loss: 2.2650 2022/09/07 20:20:05 - mmengine - INFO - Epoch(train) [26][360/1793] lr: 7.5000e-03 eta: 4:17:51 time: 0.1783 data_time: 0.0065 memory: 10464 grad_norm: 7.3168 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3783 loss: 2.3783 2022/09/07 20:20:08 - mmengine - INFO - Epoch(train) [26][380/1793] lr: 7.5000e-03 eta: 4:17:41 time: 0.1777 data_time: 0.0085 memory: 10464 grad_norm: 7.0175 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.9325 loss: 1.9325 2022/09/07 20:20:12 - mmengine - INFO - Epoch(train) [26][400/1793] lr: 7.5000e-03 eta: 4:17:30 time: 0.1707 data_time: 0.0067 memory: 10464 grad_norm: 7.6887 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0705 loss: 2.0705 2022/09/07 20:20:15 - mmengine - INFO - Epoch(train) [26][420/1793] lr: 7.5000e-03 eta: 4:17:20 time: 0.1757 data_time: 0.0062 memory: 10464 grad_norm: 7.3371 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2859 loss: 2.2859 2022/09/07 20:20:19 - mmengine - INFO - Epoch(train) [26][440/1793] lr: 7.5000e-03 eta: 4:17:09 time: 0.1764 data_time: 0.0085 memory: 10464 grad_norm: 7.2565 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0647 loss: 2.0647 2022/09/07 20:20:22 - mmengine - INFO - Epoch(train) [26][460/1793] lr: 7.5000e-03 eta: 4:16:59 time: 0.1726 data_time: 0.0059 memory: 10464 grad_norm: 6.9269 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3571 loss: 2.3571 2022/09/07 20:20:26 - mmengine - INFO - Epoch(train) [26][480/1793] lr: 7.5000e-03 eta: 4:16:49 time: 0.1735 data_time: 0.0061 memory: 10464 grad_norm: 7.1385 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2047 loss: 2.2047 2022/09/07 20:20:29 - mmengine - INFO - Epoch(train) [26][500/1793] lr: 7.5000e-03 eta: 4:16:39 time: 0.1811 data_time: 0.0114 memory: 10464 grad_norm: 7.2972 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.3121 loss: 2.3121 2022/09/07 20:20:33 - mmengine - INFO - Epoch(train) [26][520/1793] lr: 7.5000e-03 eta: 4:16:28 time: 0.1715 data_time: 0.0056 memory: 10464 grad_norm: 7.1962 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0380 loss: 2.0380 2022/09/07 20:20:38 - mmengine - INFO - Epoch(train) [26][540/1793] lr: 7.5000e-03 eta: 4:16:19 time: 0.2574 data_time: 0.0062 memory: 10464 grad_norm: 7.6539 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.9582 loss: 1.9582 2022/09/07 20:20:41 - mmengine - INFO - Epoch(train) [26][560/1793] lr: 7.5000e-03 eta: 4:16:09 time: 0.1756 data_time: 0.0088 memory: 10464 grad_norm: 7.2144 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3273 loss: 2.3273 2022/09/07 20:20:45 - mmengine - INFO - Epoch(train) [26][580/1793] lr: 7.5000e-03 eta: 4:15:59 time: 0.1724 data_time: 0.0064 memory: 10464 grad_norm: 7.3517 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.4030 loss: 2.4030 2022/09/07 20:20:49 - mmengine - INFO - Epoch(train) [26][600/1793] lr: 7.5000e-03 eta: 4:15:49 time: 0.2021 data_time: 0.0329 memory: 10464 grad_norm: 7.1680 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0930 loss: 2.0930 2022/09/07 20:20:55 - mmengine - INFO - Epoch(train) [26][620/1793] lr: 7.5000e-03 eta: 4:15:42 time: 0.3258 data_time: 0.0067 memory: 10464 grad_norm: 7.4061 top1_acc: 0.1667 top5_acc: 1.0000 loss_cls: 1.9505 loss: 1.9505 2022/09/07 20:20:59 - mmengine - INFO - Epoch(train) [26][640/1793] lr: 7.5000e-03 eta: 4:15:31 time: 0.1762 data_time: 0.0073 memory: 10464 grad_norm: 7.1001 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0627 loss: 2.0627 2022/09/07 20:21:02 - mmengine - INFO - Epoch(train) [26][660/1793] lr: 7.5000e-03 eta: 4:15:21 time: 0.1756 data_time: 0.0090 memory: 10464 grad_norm: 7.3160 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2291 loss: 2.2291 2022/09/07 20:21:06 - mmengine - INFO - Epoch(train) [26][680/1793] lr: 7.5000e-03 eta: 4:15:11 time: 0.1731 data_time: 0.0068 memory: 10464 grad_norm: 7.3985 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2830 loss: 2.2830 2022/09/07 20:21:11 - mmengine - INFO - Epoch(train) [26][700/1793] lr: 7.5000e-03 eta: 4:15:02 time: 0.2542 data_time: 0.0853 memory: 10464 grad_norm: 7.5053 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.1864 loss: 2.1864 2022/09/07 20:21:15 - mmengine - INFO - Epoch(train) [26][720/1793] lr: 7.5000e-03 eta: 4:14:52 time: 0.1870 data_time: 0.0069 memory: 10464 grad_norm: 7.0221 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9755 loss: 1.9755 2022/09/07 20:21:18 - mmengine - INFO - Epoch(train) [26][740/1793] lr: 7.5000e-03 eta: 4:14:42 time: 0.1818 data_time: 0.0096 memory: 10464 grad_norm: 6.8973 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.0231 loss: 2.0231 2022/09/07 20:21:22 - mmengine - INFO - Epoch(train) [26][760/1793] lr: 7.5000e-03 eta: 4:14:32 time: 0.1717 data_time: 0.0054 memory: 10464 grad_norm: 7.1463 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.0666 loss: 2.0666 2022/09/07 20:21:25 - mmengine - INFO - Epoch(train) [26][780/1793] lr: 7.5000e-03 eta: 4:14:21 time: 0.1772 data_time: 0.0090 memory: 10464 grad_norm: 7.2046 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.2979 loss: 2.2979 2022/09/07 20:21:29 - mmengine - INFO - Epoch(train) [26][800/1793] lr: 7.5000e-03 eta: 4:14:12 time: 0.2046 data_time: 0.0085 memory: 10464 grad_norm: 7.1602 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.9812 loss: 1.9812 2022/09/07 20:21:33 - mmengine - INFO - Epoch(train) [26][820/1793] lr: 7.5000e-03 eta: 4:14:01 time: 0.1715 data_time: 0.0058 memory: 10464 grad_norm: 7.2705 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 2.4822 loss: 2.4822 2022/09/07 20:21:36 - mmengine - INFO - Epoch(train) [26][840/1793] lr: 7.5000e-03 eta: 4:13:51 time: 0.1780 data_time: 0.0093 memory: 10464 grad_norm: 7.2992 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0375 loss: 2.0375 2022/09/07 20:21:40 - mmengine - INFO - Epoch(train) [26][860/1793] lr: 7.5000e-03 eta: 4:13:41 time: 0.1766 data_time: 0.0069 memory: 10464 grad_norm: 7.1310 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.1106 loss: 2.1106 2022/09/07 20:21:43 - mmengine - INFO - Epoch(train) [26][880/1793] lr: 7.5000e-03 eta: 4:13:31 time: 0.1696 data_time: 0.0067 memory: 10464 grad_norm: 7.2057 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2578 loss: 2.2578 2022/09/07 20:21:49 - mmengine - INFO - Epoch(train) [26][900/1793] lr: 7.5000e-03 eta: 4:13:23 time: 0.2821 data_time: 0.0084 memory: 10464 grad_norm: 7.3985 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2204 loss: 2.2204 2022/09/07 20:21:52 - mmengine - INFO - Epoch(train) [26][920/1793] lr: 7.5000e-03 eta: 4:13:12 time: 0.1706 data_time: 0.0063 memory: 10464 grad_norm: 7.3507 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4093 loss: 2.4093 2022/09/07 20:21:56 - mmengine - INFO - Epoch(train) [26][940/1793] lr: 7.5000e-03 eta: 4:13:02 time: 0.1821 data_time: 0.0067 memory: 10464 grad_norm: 7.1463 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4123 loss: 2.4123 2022/09/07 20:22:00 - mmengine - INFO - Epoch(train) [26][960/1793] lr: 7.5000e-03 eta: 4:12:52 time: 0.1764 data_time: 0.0085 memory: 10464 grad_norm: 7.3156 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0840 loss: 2.0840 2022/09/07 20:22:03 - mmengine - INFO - Epoch(train) [26][980/1793] lr: 7.5000e-03 eta: 4:12:42 time: 0.1713 data_time: 0.0060 memory: 10464 grad_norm: 7.5455 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2163 loss: 2.2163 2022/09/07 20:22:07 - mmengine - INFO - Epoch(train) [26][1000/1793] lr: 7.5000e-03 eta: 4:12:32 time: 0.1889 data_time: 0.0078 memory: 10464 grad_norm: 6.8102 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.9368 loss: 1.9368 2022/09/07 20:22:10 - mmengine - INFO - Epoch(train) [26][1020/1793] lr: 7.5000e-03 eta: 4:12:22 time: 0.1752 data_time: 0.0087 memory: 10464 grad_norm: 7.3842 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.9813 loss: 1.9813 2022/09/07 20:22:14 - mmengine - INFO - Epoch(train) [26][1040/1793] lr: 7.5000e-03 eta: 4:12:11 time: 0.1715 data_time: 0.0063 memory: 10464 grad_norm: 7.1638 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9277 loss: 1.9277 2022/09/07 20:22:17 - mmengine - INFO - Epoch(train) [26][1060/1793] lr: 7.5000e-03 eta: 4:12:01 time: 0.1767 data_time: 0.0096 memory: 10464 grad_norm: 7.1934 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.8524 loss: 1.8524 2022/09/07 20:22:22 - mmengine - INFO - Epoch(train) [26][1080/1793] lr: 7.5000e-03 eta: 4:11:52 time: 0.2354 data_time: 0.0084 memory: 10464 grad_norm: 7.3089 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2899 loss: 2.2899 2022/09/07 20:22:26 - mmengine - INFO - Epoch(train) [26][1100/1793] lr: 7.5000e-03 eta: 4:11:42 time: 0.1848 data_time: 0.0067 memory: 10464 grad_norm: 7.3659 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.4071 loss: 2.4071 2022/09/07 20:22:30 - mmengine - INFO - Epoch(train) [26][1120/1793] lr: 7.5000e-03 eta: 4:11:33 time: 0.2404 data_time: 0.0061 memory: 10464 grad_norm: 7.3828 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3833 loss: 2.3833 2022/09/07 20:22:34 - mmengine - INFO - Epoch(train) [26][1140/1793] lr: 7.5000e-03 eta: 4:11:23 time: 0.1757 data_time: 0.0094 memory: 10464 grad_norm: 7.1962 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.2307 loss: 2.2307 2022/09/07 20:22:38 - mmengine - INFO - Epoch(train) [26][1160/1793] lr: 7.5000e-03 eta: 4:11:13 time: 0.1779 data_time: 0.0064 memory: 10464 grad_norm: 7.0974 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 1.8690 loss: 1.8690 2022/09/07 20:22:40 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:22:41 - mmengine - INFO - Epoch(train) [26][1180/1793] lr: 7.5000e-03 eta: 4:11:03 time: 0.1711 data_time: 0.0066 memory: 10464 grad_norm: 7.5600 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.0971 loss: 2.0971 2022/09/07 20:22:45 - mmengine - INFO - Epoch(train) [26][1200/1793] lr: 7.5000e-03 eta: 4:10:54 time: 0.2068 data_time: 0.0085 memory: 10464 grad_norm: 7.2495 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3107 loss: 2.3107 2022/09/07 20:22:49 - mmengine - INFO - Epoch(train) [26][1220/1793] lr: 7.5000e-03 eta: 4:10:44 time: 0.1946 data_time: 0.0086 memory: 10464 grad_norm: 7.3616 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3488 loss: 2.3488 2022/09/07 20:22:55 - mmengine - INFO - Epoch(train) [26][1240/1793] lr: 7.5000e-03 eta: 4:10:36 time: 0.2952 data_time: 0.0052 memory: 10464 grad_norm: 7.2544 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.3614 loss: 2.3614 2022/09/07 20:22:59 - mmengine - INFO - Epoch(train) [26][1260/1793] lr: 7.5000e-03 eta: 4:10:26 time: 0.1873 data_time: 0.0095 memory: 10464 grad_norm: 7.4132 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1066 loss: 2.1066 2022/09/07 20:23:02 - mmengine - INFO - Epoch(train) [26][1280/1793] lr: 7.5000e-03 eta: 4:10:16 time: 0.1735 data_time: 0.0070 memory: 10464 grad_norm: 7.4777 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1711 loss: 2.1711 2022/09/07 20:23:06 - mmengine - INFO - Epoch(train) [26][1300/1793] lr: 7.5000e-03 eta: 4:10:06 time: 0.1801 data_time: 0.0052 memory: 10464 grad_norm: 6.8827 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.2625 loss: 2.2625 2022/09/07 20:23:09 - mmengine - INFO - Epoch(train) [26][1320/1793] lr: 7.5000e-03 eta: 4:09:56 time: 0.1805 data_time: 0.0089 memory: 10464 grad_norm: 7.4935 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 2.3323 loss: 2.3323 2022/09/07 20:23:13 - mmengine - INFO - Epoch(train) [26][1340/1793] lr: 7.5000e-03 eta: 4:09:46 time: 0.1715 data_time: 0.0061 memory: 10464 grad_norm: 7.4921 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3983 loss: 2.3983 2022/09/07 20:23:16 - mmengine - INFO - Epoch(train) [26][1360/1793] lr: 7.5000e-03 eta: 4:09:36 time: 0.1742 data_time: 0.0066 memory: 10464 grad_norm: 7.4829 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.0897 loss: 2.0897 2022/09/07 20:23:20 - mmengine - INFO - Epoch(train) [26][1380/1793] lr: 7.5000e-03 eta: 4:09:26 time: 0.1796 data_time: 0.0090 memory: 10464 grad_norm: 7.6177 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.1375 loss: 2.1375 2022/09/07 20:23:23 - mmengine - INFO - Epoch(train) [26][1400/1793] lr: 7.5000e-03 eta: 4:09:16 time: 0.1730 data_time: 0.0064 memory: 10464 grad_norm: 7.4804 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3894 loss: 2.3894 2022/09/07 20:23:27 - mmengine - INFO - Epoch(train) [26][1420/1793] lr: 7.5000e-03 eta: 4:09:06 time: 0.1775 data_time: 0.0063 memory: 10464 grad_norm: 7.0230 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2759 loss: 2.2759 2022/09/07 20:23:30 - mmengine - INFO - Epoch(train) [26][1440/1793] lr: 7.5000e-03 eta: 4:08:55 time: 0.1752 data_time: 0.0102 memory: 10464 grad_norm: 7.3430 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4579 loss: 2.4579 2022/09/07 20:23:34 - mmengine - INFO - Epoch(train) [26][1460/1793] lr: 7.5000e-03 eta: 4:08:45 time: 0.1727 data_time: 0.0060 memory: 10464 grad_norm: 7.4902 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5549 loss: 2.5549 2022/09/07 20:23:37 - mmengine - INFO - Epoch(train) [26][1480/1793] lr: 7.5000e-03 eta: 4:08:35 time: 0.1773 data_time: 0.0069 memory: 10464 grad_norm: 7.2038 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1258 loss: 2.1258 2022/09/07 20:23:41 - mmengine - INFO - Epoch(train) [26][1500/1793] lr: 7.5000e-03 eta: 4:08:25 time: 0.1746 data_time: 0.0099 memory: 10464 grad_norm: 7.3966 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1756 loss: 2.1756 2022/09/07 20:23:45 - mmengine - INFO - Epoch(train) [26][1520/1793] lr: 7.5000e-03 eta: 4:08:16 time: 0.2308 data_time: 0.0063 memory: 10464 grad_norm: 7.4490 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.0802 loss: 2.0802 2022/09/07 20:23:49 - mmengine - INFO - Epoch(train) [26][1540/1793] lr: 7.5000e-03 eta: 4:08:06 time: 0.1755 data_time: 0.0069 memory: 10464 grad_norm: 7.1019 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.0885 loss: 2.0885 2022/09/07 20:23:52 - mmengine - INFO - Epoch(train) [26][1560/1793] lr: 7.5000e-03 eta: 4:07:56 time: 0.1738 data_time: 0.0095 memory: 10464 grad_norm: 7.1518 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1968 loss: 2.1968 2022/09/07 20:23:56 - mmengine - INFO - Epoch(train) [26][1580/1793] lr: 7.5000e-03 eta: 4:07:46 time: 0.1773 data_time: 0.0060 memory: 10464 grad_norm: 6.9617 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1290 loss: 2.1290 2022/09/07 20:24:00 - mmengine - INFO - Epoch(train) [26][1600/1793] lr: 7.5000e-03 eta: 4:07:36 time: 0.1774 data_time: 0.0065 memory: 10464 grad_norm: 7.4021 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.3316 loss: 2.3316 2022/09/07 20:24:03 - mmengine - INFO - Epoch(train) [26][1620/1793] lr: 7.5000e-03 eta: 4:07:26 time: 0.1760 data_time: 0.0090 memory: 10464 grad_norm: 7.1611 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.8211 loss: 1.8211 2022/09/07 20:24:07 - mmengine - INFO - Epoch(train) [26][1640/1793] lr: 7.5000e-03 eta: 4:07:17 time: 0.1917 data_time: 0.0060 memory: 10464 grad_norm: 7.4126 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1846 loss: 2.1846 2022/09/07 20:24:11 - mmengine - INFO - Epoch(train) [26][1660/1793] lr: 7.5000e-03 eta: 4:07:07 time: 0.1790 data_time: 0.0064 memory: 10464 grad_norm: 7.2373 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3198 loss: 2.3198 2022/09/07 20:24:14 - mmengine - INFO - Epoch(train) [26][1680/1793] lr: 7.5000e-03 eta: 4:06:57 time: 0.1757 data_time: 0.0091 memory: 10464 grad_norm: 6.9047 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0030 loss: 2.0030 2022/09/07 20:24:18 - mmengine - INFO - Epoch(train) [26][1700/1793] lr: 7.5000e-03 eta: 4:06:47 time: 0.1827 data_time: 0.0076 memory: 10464 grad_norm: 7.3722 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3430 loss: 2.3430 2022/09/07 20:24:21 - mmengine - INFO - Epoch(train) [26][1720/1793] lr: 7.5000e-03 eta: 4:06:37 time: 0.1740 data_time: 0.0066 memory: 10464 grad_norm: 7.3880 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1674 loss: 2.1674 2022/09/07 20:24:25 - mmengine - INFO - Epoch(train) [26][1740/1793] lr: 7.5000e-03 eta: 4:06:27 time: 0.1795 data_time: 0.0089 memory: 10464 grad_norm: 7.0326 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3241 loss: 2.3241 2022/09/07 20:24:28 - mmengine - INFO - Epoch(train) [26][1760/1793] lr: 7.5000e-03 eta: 4:06:17 time: 0.1717 data_time: 0.0067 memory: 10464 grad_norm: 7.3209 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.9711 loss: 1.9711 2022/09/07 20:24:32 - mmengine - INFO - Epoch(train) [26][1780/1793] lr: 7.5000e-03 eta: 4:06:07 time: 0.1721 data_time: 0.0060 memory: 10464 grad_norm: 7.2022 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2532 loss: 2.2532 2022/09/07 20:24:34 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:24:34 - mmengine - INFO - Epoch(train) [26][1793/1793] lr: 7.5000e-03 eta: 4:06:07 time: 0.1703 data_time: 0.0086 memory: 10464 grad_norm: 7.4602 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.3813 loss: 2.3813 2022/09/07 20:24:34 - mmengine - INFO - Saving checkpoint at 26 epochs 2022/09/07 20:24:37 - mmengine - INFO - Epoch(val) [26][20/241] eta: 0:00:13 time: 0.0593 data_time: 0.0094 memory: 1482 2022/09/07 20:24:39 - mmengine - INFO - Epoch(val) [26][40/241] eta: 0:00:10 time: 0.0535 data_time: 0.0050 memory: 1482 2022/09/07 20:24:40 - mmengine - INFO - Epoch(val) [26][60/241] eta: 0:00:09 time: 0.0531 data_time: 0.0047 memory: 1482 2022/09/07 20:24:41 - mmengine - INFO - Epoch(val) [26][80/241] eta: 0:00:08 time: 0.0531 data_time: 0.0047 memory: 1482 2022/09/07 20:24:42 - mmengine - INFO - Epoch(val) [26][100/241] eta: 0:00:07 time: 0.0533 data_time: 0.0050 memory: 1482 2022/09/07 20:24:43 - mmengine - INFO - Epoch(val) [26][120/241] eta: 0:00:06 time: 0.0535 data_time: 0.0052 memory: 1482 2022/09/07 20:24:44 - mmengine - INFO - Epoch(val) [26][140/241] eta: 0:00:05 time: 0.0534 data_time: 0.0048 memory: 1482 2022/09/07 20:24:45 - mmengine - INFO - Epoch(val) [26][160/241] eta: 0:00:04 time: 0.0533 data_time: 0.0051 memory: 1482 2022/09/07 20:24:46 - mmengine - INFO - Epoch(val) [26][180/241] eta: 0:00:03 time: 0.0530 data_time: 0.0048 memory: 1482 2022/09/07 20:24:47 - mmengine - INFO - Epoch(val) [26][200/241] eta: 0:00:02 time: 0.0527 data_time: 0.0047 memory: 1482 2022/09/07 20:24:48 - mmengine - INFO - Epoch(val) [26][220/241] eta: 0:00:01 time: 0.0602 data_time: 0.0055 memory: 1482 2022/09/07 20:24:49 - mmengine - INFO - Epoch(val) [26][240/241] eta: 0:00:00 time: 0.0526 data_time: 0.0047 memory: 1482 2022/09/07 20:24:50 - mmengine - INFO - Epoch(val) [26][241/241] acc/top1: 0.3404 acc/top5: 0.6408 acc/mean1: 0.2997 2022/09/07 20:24:53 - mmengine - INFO - Epoch(train) [27][20/1793] lr: 7.5000e-03 eta: 4:05:48 time: 0.1787 data_time: 0.0126 memory: 10464 grad_norm: 6.9179 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3170 loss: 2.3170 2022/09/07 20:24:57 - mmengine - INFO - Epoch(train) [27][40/1793] lr: 7.5000e-03 eta: 4:05:38 time: 0.1731 data_time: 0.0048 memory: 10464 grad_norm: 7.2498 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7792 loss: 1.7792 2022/09/07 20:25:00 - mmengine - INFO - Epoch(train) [27][60/1793] lr: 7.5000e-03 eta: 4:05:28 time: 0.1738 data_time: 0.0064 memory: 10464 grad_norm: 7.3851 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 2.2004 loss: 2.2004 2022/09/07 20:25:04 - mmengine - INFO - Epoch(train) [27][80/1793] lr: 7.5000e-03 eta: 4:05:18 time: 0.1739 data_time: 0.0090 memory: 10464 grad_norm: 7.2661 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1638 loss: 2.1638 2022/09/07 20:25:08 - mmengine - INFO - Epoch(train) [27][100/1793] lr: 7.5000e-03 eta: 4:05:09 time: 0.2134 data_time: 0.0076 memory: 10464 grad_norm: 7.4636 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.9065 loss: 1.9065 2022/09/07 20:25:12 - mmengine - INFO - Epoch(train) [27][120/1793] lr: 7.5000e-03 eta: 4:04:59 time: 0.1721 data_time: 0.0069 memory: 10464 grad_norm: 7.4845 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0471 loss: 2.0471 2022/09/07 20:25:15 - mmengine - INFO - Epoch(train) [27][140/1793] lr: 7.5000e-03 eta: 4:04:49 time: 0.1778 data_time: 0.0101 memory: 10464 grad_norm: 7.7503 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2454 loss: 2.2454 2022/09/07 20:25:19 - mmengine - INFO - Epoch(train) [27][160/1793] lr: 7.5000e-03 eta: 4:04:39 time: 0.1742 data_time: 0.0060 memory: 10464 grad_norm: 7.1344 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3482 loss: 2.3482 2022/09/07 20:25:22 - mmengine - INFO - Epoch(train) [27][180/1793] lr: 7.5000e-03 eta: 4:04:30 time: 0.1734 data_time: 0.0062 memory: 10464 grad_norm: 7.3454 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4055 loss: 2.4055 2022/09/07 20:25:26 - mmengine - INFO - Epoch(train) [27][200/1793] lr: 7.5000e-03 eta: 4:04:20 time: 0.1811 data_time: 0.0089 memory: 10464 grad_norm: 7.3663 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0960 loss: 2.0960 2022/09/07 20:25:29 - mmengine - INFO - Epoch(train) [27][220/1793] lr: 7.5000e-03 eta: 4:04:10 time: 0.1726 data_time: 0.0067 memory: 10464 grad_norm: 7.1081 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1867 loss: 2.1867 2022/09/07 20:25:33 - mmengine - INFO - Epoch(train) [27][240/1793] lr: 7.5000e-03 eta: 4:04:00 time: 0.1731 data_time: 0.0066 memory: 10464 grad_norm: 7.5879 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3406 loss: 2.3406 2022/09/07 20:25:36 - mmengine - INFO - Epoch(train) [27][260/1793] lr: 7.5000e-03 eta: 4:03:50 time: 0.1734 data_time: 0.0083 memory: 10464 grad_norm: 7.5419 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1424 loss: 2.1424 2022/09/07 20:25:40 - mmengine - INFO - Epoch(train) [27][280/1793] lr: 7.5000e-03 eta: 4:03:40 time: 0.1737 data_time: 0.0066 memory: 10464 grad_norm: 7.3302 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3655 loss: 2.3655 2022/09/07 20:25:43 - mmengine - INFO - Epoch(train) [27][300/1793] lr: 7.5000e-03 eta: 4:03:30 time: 0.1723 data_time: 0.0064 memory: 10464 grad_norm: 7.4578 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5646 loss: 2.5646 2022/09/07 20:25:47 - mmengine - INFO - Epoch(train) [27][320/1793] lr: 7.5000e-03 eta: 4:03:20 time: 0.1865 data_time: 0.0084 memory: 10464 grad_norm: 7.5240 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2187 loss: 2.2187 2022/09/07 20:25:50 - mmengine - INFO - Epoch(train) [27][340/1793] lr: 7.5000e-03 eta: 4:03:11 time: 0.1768 data_time: 0.0078 memory: 10464 grad_norm: 7.1193 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1979 loss: 2.1979 2022/09/07 20:25:54 - mmengine - INFO - Epoch(train) [27][360/1793] lr: 7.5000e-03 eta: 4:03:01 time: 0.1717 data_time: 0.0062 memory: 10464 grad_norm: 7.2329 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6795 loss: 2.6795 2022/09/07 20:25:57 - mmengine - INFO - Epoch(train) [27][380/1793] lr: 7.5000e-03 eta: 4:02:51 time: 0.1744 data_time: 0.0096 memory: 10464 grad_norm: 7.1885 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2032 loss: 2.2032 2022/09/07 20:25:58 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:26:01 - mmengine - INFO - Epoch(train) [27][400/1793] lr: 7.5000e-03 eta: 4:02:41 time: 0.1738 data_time: 0.0064 memory: 10464 grad_norm: 7.2531 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.0896 loss: 2.0896 2022/09/07 20:26:04 - mmengine - INFO - Epoch(train) [27][420/1793] lr: 7.5000e-03 eta: 4:02:31 time: 0.1767 data_time: 0.0061 memory: 10464 grad_norm: 7.4521 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.2018 loss: 2.2018 2022/09/07 20:26:08 - mmengine - INFO - Epoch(train) [27][440/1793] lr: 7.5000e-03 eta: 4:02:21 time: 0.1815 data_time: 0.0093 memory: 10464 grad_norm: 7.2036 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2863 loss: 2.2863 2022/09/07 20:26:11 - mmengine - INFO - Epoch(train) [27][460/1793] lr: 7.5000e-03 eta: 4:02:11 time: 0.1709 data_time: 0.0066 memory: 10464 grad_norm: 7.5629 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.9946 loss: 1.9946 2022/09/07 20:26:15 - mmengine - INFO - Epoch(train) [27][480/1793] lr: 7.5000e-03 eta: 4:02:02 time: 0.1730 data_time: 0.0065 memory: 10464 grad_norm: 7.3332 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1127 loss: 2.1127 2022/09/07 20:26:18 - mmengine - INFO - Epoch(train) [27][500/1793] lr: 7.5000e-03 eta: 4:01:52 time: 0.1800 data_time: 0.0106 memory: 10464 grad_norm: 7.1417 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2981 loss: 2.2981 2022/09/07 20:26:22 - mmengine - INFO - Epoch(train) [27][520/1793] lr: 7.5000e-03 eta: 4:01:42 time: 0.1723 data_time: 0.0060 memory: 10464 grad_norm: 7.3178 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1554 loss: 2.1554 2022/09/07 20:26:26 - mmengine - INFO - Epoch(train) [27][540/1793] lr: 7.5000e-03 eta: 4:01:32 time: 0.1860 data_time: 0.0071 memory: 10464 grad_norm: 7.2722 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.9630 loss: 1.9630 2022/09/07 20:26:29 - mmengine - INFO - Epoch(train) [27][560/1793] lr: 7.5000e-03 eta: 4:01:23 time: 0.1808 data_time: 0.0107 memory: 10464 grad_norm: 7.7066 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1867 loss: 2.1867 2022/09/07 20:26:33 - mmengine - INFO - Epoch(train) [27][580/1793] lr: 7.5000e-03 eta: 4:01:13 time: 0.1734 data_time: 0.0064 memory: 10464 grad_norm: 7.2629 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.1812 loss: 2.1812 2022/09/07 20:26:36 - mmengine - INFO - Epoch(train) [27][600/1793] lr: 7.5000e-03 eta: 4:01:03 time: 0.1738 data_time: 0.0069 memory: 10464 grad_norm: 7.4536 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3010 loss: 2.3010 2022/09/07 20:26:40 - mmengine - INFO - Epoch(train) [27][620/1793] lr: 7.5000e-03 eta: 4:00:53 time: 0.1744 data_time: 0.0078 memory: 10464 grad_norm: 7.1294 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.1416 loss: 2.1416 2022/09/07 20:26:43 - mmengine - INFO - Epoch(train) [27][640/1793] lr: 7.5000e-03 eta: 4:00:43 time: 0.1719 data_time: 0.0070 memory: 10464 grad_norm: 7.5451 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.6149 loss: 1.6149 2022/09/07 20:26:47 - mmengine - INFO - Epoch(train) [27][660/1793] lr: 7.5000e-03 eta: 4:00:34 time: 0.1757 data_time: 0.0065 memory: 10464 grad_norm: 7.2433 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0361 loss: 2.0361 2022/09/07 20:26:51 - mmengine - INFO - Epoch(train) [27][680/1793] lr: 7.5000e-03 eta: 4:00:24 time: 0.1974 data_time: 0.0099 memory: 10464 grad_norm: 7.2787 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0349 loss: 2.0349 2022/09/07 20:26:54 - mmengine - INFO - Epoch(train) [27][700/1793] lr: 7.5000e-03 eta: 4:00:14 time: 0.1717 data_time: 0.0067 memory: 10464 grad_norm: 7.4596 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.9452 loss: 1.9452 2022/09/07 20:26:57 - mmengine - INFO - Epoch(train) [27][720/1793] lr: 7.5000e-03 eta: 4:00:05 time: 0.1718 data_time: 0.0063 memory: 10464 grad_norm: 7.4198 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.8671 loss: 1.8671 2022/09/07 20:27:01 - mmengine - INFO - Epoch(train) [27][740/1793] lr: 7.5000e-03 eta: 3:59:55 time: 0.1751 data_time: 0.0097 memory: 10464 grad_norm: 7.1740 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1105 loss: 2.1105 2022/09/07 20:27:04 - mmengine - INFO - Epoch(train) [27][760/1793] lr: 7.5000e-03 eta: 3:59:45 time: 0.1711 data_time: 0.0065 memory: 10464 grad_norm: 7.5436 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4158 loss: 2.4158 2022/09/07 20:27:08 - mmengine - INFO - Epoch(train) [27][780/1793] lr: 7.5000e-03 eta: 3:59:36 time: 0.1941 data_time: 0.0063 memory: 10464 grad_norm: 7.2913 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2459 loss: 2.2459 2022/09/07 20:27:12 - mmengine - INFO - Epoch(train) [27][800/1793] lr: 7.5000e-03 eta: 3:59:26 time: 0.1747 data_time: 0.0094 memory: 10464 grad_norm: 7.6824 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.2150 loss: 2.2150 2022/09/07 20:27:15 - mmengine - INFO - Epoch(train) [27][820/1793] lr: 7.5000e-03 eta: 3:59:16 time: 0.1711 data_time: 0.0062 memory: 10464 grad_norm: 7.1501 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2054 loss: 2.2054 2022/09/07 20:27:19 - mmengine - INFO - Epoch(train) [27][840/1793] lr: 7.5000e-03 eta: 3:59:06 time: 0.1733 data_time: 0.0058 memory: 10464 grad_norm: 7.2419 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.2723 loss: 2.2723 2022/09/07 20:27:22 - mmengine - INFO - Epoch(train) [27][860/1793] lr: 7.5000e-03 eta: 3:58:56 time: 0.1757 data_time: 0.0091 memory: 10464 grad_norm: 7.2267 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4402 loss: 2.4402 2022/09/07 20:27:26 - mmengine - INFO - Epoch(train) [27][880/1793] lr: 7.5000e-03 eta: 3:58:47 time: 0.1772 data_time: 0.0062 memory: 10464 grad_norm: 7.0541 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2028 loss: 2.2028 2022/09/07 20:27:29 - mmengine - INFO - Epoch(train) [27][900/1793] lr: 7.5000e-03 eta: 3:58:37 time: 0.1791 data_time: 0.0088 memory: 10464 grad_norm: 7.0210 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.0495 loss: 2.0495 2022/09/07 20:27:33 - mmengine - INFO - Epoch(train) [27][920/1793] lr: 7.5000e-03 eta: 3:58:27 time: 0.1746 data_time: 0.0084 memory: 10464 grad_norm: 7.6693 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.2494 loss: 2.2494 2022/09/07 20:27:36 - mmengine - INFO - Epoch(train) [27][940/1793] lr: 7.5000e-03 eta: 3:58:18 time: 0.1742 data_time: 0.0064 memory: 10464 grad_norm: 7.0304 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2141 loss: 2.2141 2022/09/07 20:27:40 - mmengine - INFO - Epoch(train) [27][960/1793] lr: 7.5000e-03 eta: 3:58:08 time: 0.1732 data_time: 0.0062 memory: 10464 grad_norm: 7.5565 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 2.1360 loss: 2.1360 2022/09/07 20:27:45 - mmengine - INFO - Epoch(train) [27][980/1793] lr: 7.5000e-03 eta: 3:57:59 time: 0.2417 data_time: 0.0086 memory: 10464 grad_norm: 7.4872 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2722 loss: 2.2722 2022/09/07 20:27:48 - mmengine - INFO - Epoch(train) [27][1000/1793] lr: 7.5000e-03 eta: 3:57:50 time: 0.1882 data_time: 0.0061 memory: 10464 grad_norm: 7.2503 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6614 loss: 1.6614 2022/09/07 20:27:53 - mmengine - INFO - Epoch(train) [27][1020/1793] lr: 7.5000e-03 eta: 3:57:41 time: 0.2415 data_time: 0.0066 memory: 10464 grad_norm: 7.2484 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.9502 loss: 1.9502 2022/09/07 20:27:57 - mmengine - INFO - Epoch(train) [27][1040/1793] lr: 7.5000e-03 eta: 3:57:32 time: 0.1762 data_time: 0.0099 memory: 10464 grad_norm: 7.0761 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.8289 loss: 1.8289 2022/09/07 20:28:02 - mmengine - INFO - Epoch(train) [27][1060/1793] lr: 7.5000e-03 eta: 3:57:23 time: 0.2404 data_time: 0.0063 memory: 10464 grad_norm: 7.4714 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.1899 loss: 2.1899 2022/09/07 20:28:05 - mmengine - INFO - Epoch(train) [27][1080/1793] lr: 7.5000e-03 eta: 3:57:14 time: 0.1822 data_time: 0.0063 memory: 10464 grad_norm: 7.4833 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1714 loss: 2.1714 2022/09/07 20:28:09 - mmengine - INFO - Epoch(train) [27][1100/1793] lr: 7.5000e-03 eta: 3:57:04 time: 0.1874 data_time: 0.0110 memory: 10464 grad_norm: 7.5878 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.9013 loss: 1.9013 2022/09/07 20:28:12 - mmengine - INFO - Epoch(train) [27][1120/1793] lr: 7.5000e-03 eta: 3:56:54 time: 0.1715 data_time: 0.0060 memory: 10464 grad_norm: 7.7680 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.4442 loss: 2.4442 2022/09/07 20:28:16 - mmengine - INFO - Epoch(train) [27][1140/1793] lr: 7.5000e-03 eta: 3:56:45 time: 0.1722 data_time: 0.0059 memory: 10464 grad_norm: 7.4636 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3727 loss: 2.3727 2022/09/07 20:28:19 - mmengine - INFO - Epoch(train) [27][1160/1793] lr: 7.5000e-03 eta: 3:56:35 time: 0.1789 data_time: 0.0084 memory: 10464 grad_norm: 7.2381 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1962 loss: 2.1962 2022/09/07 20:28:23 - mmengine - INFO - Epoch(train) [27][1180/1793] lr: 7.5000e-03 eta: 3:56:25 time: 0.1712 data_time: 0.0062 memory: 10464 grad_norm: 7.3746 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.0477 loss: 2.0477 2022/09/07 20:28:26 - mmengine - INFO - Epoch(train) [27][1200/1793] lr: 7.5000e-03 eta: 3:56:16 time: 0.1780 data_time: 0.0067 memory: 10464 grad_norm: 7.2138 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6492 loss: 2.6492 2022/09/07 20:28:30 - mmengine - INFO - Epoch(train) [27][1220/1793] lr: 7.5000e-03 eta: 3:56:06 time: 0.1836 data_time: 0.0097 memory: 10464 grad_norm: 7.2292 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4814 loss: 2.4814 2022/09/07 20:28:33 - mmengine - INFO - Epoch(train) [27][1240/1793] lr: 7.5000e-03 eta: 3:55:57 time: 0.1710 data_time: 0.0059 memory: 10464 grad_norm: 6.9737 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2596 loss: 2.2596 2022/09/07 20:28:37 - mmengine - INFO - Epoch(train) [27][1260/1793] lr: 7.5000e-03 eta: 3:55:47 time: 0.1700 data_time: 0.0064 memory: 10464 grad_norm: 7.3997 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.9819 loss: 1.9819 2022/09/07 20:28:40 - mmengine - INFO - Epoch(train) [27][1280/1793] lr: 7.5000e-03 eta: 3:55:37 time: 0.1748 data_time: 0.0087 memory: 10464 grad_norm: 7.3724 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1193 loss: 2.1193 2022/09/07 20:28:44 - mmengine - INFO - Epoch(train) [27][1300/1793] lr: 7.5000e-03 eta: 3:55:28 time: 0.1728 data_time: 0.0067 memory: 10464 grad_norm: 7.4404 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3464 loss: 2.3464 2022/09/07 20:28:47 - mmengine - INFO - Epoch(train) [27][1320/1793] lr: 7.5000e-03 eta: 3:55:18 time: 0.1753 data_time: 0.0061 memory: 10464 grad_norm: 7.2659 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1364 loss: 2.1364 2022/09/07 20:28:51 - mmengine - INFO - Epoch(train) [27][1340/1793] lr: 7.5000e-03 eta: 3:55:09 time: 0.1825 data_time: 0.0099 memory: 10464 grad_norm: 7.4434 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0681 loss: 2.0681 2022/09/07 20:28:54 - mmengine - INFO - Epoch(train) [27][1360/1793] lr: 7.5000e-03 eta: 3:54:59 time: 0.1699 data_time: 0.0063 memory: 10464 grad_norm: 7.3368 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2590 loss: 2.2590 2022/09/07 20:28:58 - mmengine - INFO - Epoch(train) [27][1380/1793] lr: 7.5000e-03 eta: 3:54:49 time: 0.1722 data_time: 0.0065 memory: 10464 grad_norm: 7.0001 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.2144 loss: 2.2144 2022/09/07 20:28:58 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:29:01 - mmengine - INFO - Epoch(train) [27][1400/1793] lr: 7.5000e-03 eta: 3:54:40 time: 0.1764 data_time: 0.0088 memory: 10464 grad_norm: 7.3259 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2260 loss: 2.2260 2022/09/07 20:29:05 - mmengine - INFO - Epoch(train) [27][1420/1793] lr: 7.5000e-03 eta: 3:54:30 time: 0.1715 data_time: 0.0061 memory: 10464 grad_norm: 7.3185 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4499 loss: 2.4499 2022/09/07 20:29:09 - mmengine - INFO - Epoch(train) [27][1440/1793] lr: 7.5000e-03 eta: 3:54:21 time: 0.2096 data_time: 0.0072 memory: 10464 grad_norm: 7.1849 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2994 loss: 2.2994 2022/09/07 20:29:13 - mmengine - INFO - Epoch(train) [27][1460/1793] lr: 7.5000e-03 eta: 3:54:11 time: 0.1744 data_time: 0.0093 memory: 10464 grad_norm: 7.3937 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1312 loss: 2.1312 2022/09/07 20:29:16 - mmengine - INFO - Epoch(train) [27][1480/1793] lr: 7.5000e-03 eta: 3:54:02 time: 0.1721 data_time: 0.0065 memory: 10464 grad_norm: 7.5829 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.4913 loss: 2.4913 2022/09/07 20:29:19 - mmengine - INFO - Epoch(train) [27][1500/1793] lr: 7.5000e-03 eta: 3:53:52 time: 0.1743 data_time: 0.0066 memory: 10464 grad_norm: 7.0244 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0905 loss: 2.0905 2022/09/07 20:29:23 - mmengine - INFO - Epoch(train) [27][1520/1793] lr: 7.5000e-03 eta: 3:53:43 time: 0.1753 data_time: 0.0088 memory: 10464 grad_norm: 7.7285 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1792 loss: 2.1792 2022/09/07 20:29:27 - mmengine - INFO - Epoch(train) [27][1540/1793] lr: 7.5000e-03 eta: 3:53:33 time: 0.1795 data_time: 0.0063 memory: 10464 grad_norm: 7.3310 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.0875 loss: 2.0875 2022/09/07 20:29:30 - mmengine - INFO - Epoch(train) [27][1560/1793] lr: 7.5000e-03 eta: 3:53:24 time: 0.1812 data_time: 0.0087 memory: 10464 grad_norm: 7.2001 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1775 loss: 2.1775 2022/09/07 20:29:34 - mmengine - INFO - Epoch(train) [27][1580/1793] lr: 7.5000e-03 eta: 3:53:14 time: 0.1733 data_time: 0.0099 memory: 10464 grad_norm: 7.2145 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2027 loss: 2.2027 2022/09/07 20:29:37 - mmengine - INFO - Epoch(train) [27][1600/1793] lr: 7.5000e-03 eta: 3:53:05 time: 0.1715 data_time: 0.0062 memory: 10464 grad_norm: 7.3285 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1678 loss: 2.1678 2022/09/07 20:29:41 - mmengine - INFO - Epoch(train) [27][1620/1793] lr: 7.5000e-03 eta: 3:52:55 time: 0.1734 data_time: 0.0070 memory: 10464 grad_norm: 7.1299 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.6186 loss: 1.6186 2022/09/07 20:29:44 - mmengine - INFO - Epoch(train) [27][1640/1793] lr: 7.5000e-03 eta: 3:52:45 time: 0.1753 data_time: 0.0094 memory: 10464 grad_norm: 7.1898 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3355 loss: 2.3355 2022/09/07 20:29:48 - mmengine - INFO - Epoch(train) [27][1660/1793] lr: 7.5000e-03 eta: 3:52:36 time: 0.1862 data_time: 0.0069 memory: 10464 grad_norm: 7.1968 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1361 loss: 2.1361 2022/09/07 20:29:51 - mmengine - INFO - Epoch(train) [27][1680/1793] lr: 7.5000e-03 eta: 3:52:27 time: 0.1788 data_time: 0.0088 memory: 10464 grad_norm: 7.3503 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.8831 loss: 1.8831 2022/09/07 20:29:55 - mmengine - INFO - Epoch(train) [27][1700/1793] lr: 7.5000e-03 eta: 3:52:17 time: 0.1743 data_time: 0.0081 memory: 10464 grad_norm: 7.1806 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3508 loss: 2.3508 2022/09/07 20:29:58 - mmengine - INFO - Epoch(train) [27][1720/1793] lr: 7.5000e-03 eta: 3:52:08 time: 0.1752 data_time: 0.0063 memory: 10464 grad_norm: 7.4877 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1263 loss: 2.1263 2022/09/07 20:30:02 - mmengine - INFO - Epoch(train) [27][1740/1793] lr: 7.5000e-03 eta: 3:51:58 time: 0.1720 data_time: 0.0065 memory: 10464 grad_norm: 7.2840 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2341 loss: 2.2341 2022/09/07 20:30:05 - mmengine - INFO - Epoch(train) [27][1760/1793] lr: 7.5000e-03 eta: 3:51:49 time: 0.1796 data_time: 0.0085 memory: 10464 grad_norm: 6.9947 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.4135 loss: 2.4135 2022/09/07 20:30:09 - mmengine - INFO - Epoch(train) [27][1780/1793] lr: 7.5000e-03 eta: 3:51:39 time: 0.1751 data_time: 0.0072 memory: 10464 grad_norm: 7.0458 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2255 loss: 2.2255 2022/09/07 20:30:11 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:30:11 - mmengine - INFO - Epoch(train) [27][1793/1793] lr: 7.5000e-03 eta: 3:51:39 time: 0.1711 data_time: 0.0069 memory: 10464 grad_norm: 7.4958 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.9157 loss: 1.9157 2022/09/07 20:30:11 - mmengine - INFO - Saving checkpoint at 27 epochs 2022/09/07 20:30:15 - mmengine - INFO - Epoch(val) [27][20/241] eta: 0:00:12 time: 0.0584 data_time: 0.0089 memory: 1482 2022/09/07 20:30:16 - mmengine - INFO - Epoch(val) [27][40/241] eta: 0:00:10 time: 0.0534 data_time: 0.0048 memory: 1482 2022/09/07 20:30:17 - mmengine - INFO - Epoch(val) [27][60/241] eta: 0:00:09 time: 0.0538 data_time: 0.0053 memory: 1482 2022/09/07 20:30:18 - mmengine - INFO - Epoch(val) [27][80/241] eta: 0:00:08 time: 0.0535 data_time: 0.0051 memory: 1482 2022/09/07 20:30:19 - mmengine - INFO - Epoch(val) [27][100/241] eta: 0:00:07 time: 0.0531 data_time: 0.0048 memory: 1482 2022/09/07 20:30:20 - mmengine - INFO - Epoch(val) [27][120/241] eta: 0:00:06 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 20:30:21 - mmengine - INFO - Epoch(val) [27][140/241] eta: 0:00:05 time: 0.0533 data_time: 0.0050 memory: 1482 2022/09/07 20:30:22 - mmengine - INFO - Epoch(val) [27][160/241] eta: 0:00:04 time: 0.0536 data_time: 0.0052 memory: 1482 2022/09/07 20:30:23 - mmengine - INFO - Epoch(val) [27][180/241] eta: 0:00:03 time: 0.0533 data_time: 0.0050 memory: 1482 2022/09/07 20:30:24 - mmengine - INFO - Epoch(val) [27][200/241] eta: 0:00:02 time: 0.0528 data_time: 0.0047 memory: 1482 2022/09/07 20:30:25 - mmengine - INFO - Epoch(val) [27][220/241] eta: 0:00:01 time: 0.0524 data_time: 0.0045 memory: 1482 2022/09/07 20:30:26 - mmengine - INFO - Epoch(val) [27][240/241] eta: 0:00:00 time: 0.0522 data_time: 0.0044 memory: 1482 2022/09/07 20:30:27 - mmengine - INFO - Epoch(val) [27][241/241] acc/top1: 0.3389 acc/top5: 0.6367 acc/mean1: 0.3069 2022/09/07 20:30:31 - mmengine - INFO - Epoch(train) [28][20/1793] lr: 7.5000e-03 eta: 3:51:22 time: 0.1835 data_time: 0.0163 memory: 10464 grad_norm: 7.2624 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.8186 loss: 1.8186 2022/09/07 20:30:34 - mmengine - INFO - Epoch(train) [28][40/1793] lr: 7.5000e-03 eta: 3:51:12 time: 0.1724 data_time: 0.0061 memory: 10464 grad_norm: 7.1258 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7729 loss: 1.7729 2022/09/07 20:30:38 - mmengine - INFO - Epoch(train) [28][60/1793] lr: 7.5000e-03 eta: 3:51:03 time: 0.1711 data_time: 0.0066 memory: 10464 grad_norm: 7.4307 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.8166 loss: 1.8166 2022/09/07 20:30:41 - mmengine - INFO - Epoch(train) [28][80/1793] lr: 7.5000e-03 eta: 3:50:53 time: 0.1787 data_time: 0.0096 memory: 10464 grad_norm: 7.1341 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.8653 loss: 1.8653 2022/09/07 20:30:47 - mmengine - INFO - Epoch(train) [28][100/1793] lr: 7.5000e-03 eta: 3:50:46 time: 0.3065 data_time: 0.0070 memory: 10464 grad_norm: 7.1810 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.7602 loss: 1.7602 2022/09/07 20:30:52 - mmengine - INFO - Epoch(train) [28][120/1793] lr: 7.5000e-03 eta: 3:50:37 time: 0.2352 data_time: 0.0064 memory: 10464 grad_norm: 7.1145 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1990 loss: 2.1990 2022/09/07 20:30:56 - mmengine - INFO - Epoch(train) [28][140/1793] lr: 7.5000e-03 eta: 3:50:28 time: 0.1823 data_time: 0.0091 memory: 10464 grad_norm: 7.5375 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.0278 loss: 2.0278 2022/09/07 20:30:59 - mmengine - INFO - Epoch(train) [28][160/1793] lr: 7.5000e-03 eta: 3:50:19 time: 0.1836 data_time: 0.0059 memory: 10464 grad_norm: 7.4442 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0104 loss: 2.0104 2022/09/07 20:31:03 - mmengine - INFO - Epoch(train) [28][180/1793] lr: 7.5000e-03 eta: 3:50:09 time: 0.1744 data_time: 0.0073 memory: 10464 grad_norm: 7.1842 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2166 loss: 2.2166 2022/09/07 20:31:06 - mmengine - INFO - Epoch(train) [28][200/1793] lr: 7.5000e-03 eta: 3:50:00 time: 0.1822 data_time: 0.0085 memory: 10464 grad_norm: 6.9066 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.6222 loss: 2.6222 2022/09/07 20:31:10 - mmengine - INFO - Epoch(train) [28][220/1793] lr: 7.5000e-03 eta: 3:49:50 time: 0.1722 data_time: 0.0063 memory: 10464 grad_norm: 7.1735 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0153 loss: 2.0153 2022/09/07 20:31:13 - mmengine - INFO - Epoch(train) [28][240/1793] lr: 7.5000e-03 eta: 3:49:41 time: 0.1723 data_time: 0.0067 memory: 10464 grad_norm: 7.3831 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.9666 loss: 1.9666 2022/09/07 20:31:17 - mmengine - INFO - Epoch(train) [28][260/1793] lr: 7.5000e-03 eta: 3:49:32 time: 0.1967 data_time: 0.0088 memory: 10464 grad_norm: 7.5053 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.0799 loss: 2.0799 2022/09/07 20:31:21 - mmengine - INFO - Epoch(train) [28][280/1793] lr: 7.5000e-03 eta: 3:49:23 time: 0.1984 data_time: 0.0085 memory: 10464 grad_norm: 7.5257 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2308 loss: 2.2308 2022/09/07 20:31:25 - mmengine - INFO - Epoch(train) [28][300/1793] lr: 7.5000e-03 eta: 3:49:13 time: 0.1715 data_time: 0.0070 memory: 10464 grad_norm: 7.7183 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2222 loss: 2.2222 2022/09/07 20:31:28 - mmengine - INFO - Epoch(train) [28][320/1793] lr: 7.5000e-03 eta: 3:49:04 time: 0.1762 data_time: 0.0087 memory: 10464 grad_norm: 7.3650 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3492 loss: 2.3492 2022/09/07 20:31:32 - mmengine - INFO - Epoch(train) [28][340/1793] lr: 7.5000e-03 eta: 3:48:55 time: 0.1722 data_time: 0.0064 memory: 10464 grad_norm: 7.2147 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.2522 loss: 2.2522 2022/09/07 20:31:35 - mmengine - INFO - Epoch(train) [28][360/1793] lr: 7.5000e-03 eta: 3:48:45 time: 0.1716 data_time: 0.0063 memory: 10464 grad_norm: 7.5960 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6876 loss: 1.6876 2022/09/07 20:31:39 - mmengine - INFO - Epoch(train) [28][380/1793] lr: 7.5000e-03 eta: 3:48:36 time: 0.1837 data_time: 0.0098 memory: 10464 grad_norm: 7.4051 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.9988 loss: 1.9988 2022/09/07 20:31:42 - mmengine - INFO - Epoch(train) [28][400/1793] lr: 7.5000e-03 eta: 3:48:26 time: 0.1705 data_time: 0.0066 memory: 10464 grad_norm: 7.1913 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0464 loss: 2.0464 2022/09/07 20:31:46 - mmengine - INFO - Epoch(train) [28][420/1793] lr: 7.5000e-03 eta: 3:48:17 time: 0.1941 data_time: 0.0061 memory: 10464 grad_norm: 7.1601 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.9860 loss: 1.9860 2022/09/07 20:31:50 - mmengine - INFO - Epoch(train) [28][440/1793] lr: 7.5000e-03 eta: 3:48:08 time: 0.1738 data_time: 0.0097 memory: 10464 grad_norm: 7.1761 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.9987 loss: 1.9987 2022/09/07 20:31:53 - mmengine - INFO - Epoch(train) [28][460/1793] lr: 7.5000e-03 eta: 3:47:58 time: 0.1739 data_time: 0.0064 memory: 10464 grad_norm: 7.7241 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3723 loss: 2.3723 2022/09/07 20:31:56 - mmengine - INFO - Epoch(train) [28][480/1793] lr: 7.5000e-03 eta: 3:47:49 time: 0.1702 data_time: 0.0060 memory: 10464 grad_norm: 7.0044 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.4158 loss: 2.4158 2022/09/07 20:32:01 - mmengine - INFO - Epoch(train) [28][500/1793] lr: 7.5000e-03 eta: 3:47:41 time: 0.2411 data_time: 0.0623 memory: 10464 grad_norm: 7.4958 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2090 loss: 2.2090 2022/09/07 20:32:05 - mmengine - INFO - Epoch(train) [28][520/1793] lr: 7.5000e-03 eta: 3:47:31 time: 0.1708 data_time: 0.0062 memory: 10464 grad_norm: 7.6953 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.0432 loss: 2.0432 2022/09/07 20:32:08 - mmengine - INFO - Epoch(train) [28][540/1793] lr: 7.5000e-03 eta: 3:47:22 time: 0.1781 data_time: 0.0064 memory: 10464 grad_norm: 7.4038 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0443 loss: 2.0443 2022/09/07 20:32:12 - mmengine - INFO - Epoch(train) [28][560/1793] lr: 7.5000e-03 eta: 3:47:13 time: 0.1736 data_time: 0.0093 memory: 10464 grad_norm: 7.2240 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0687 loss: 2.0687 2022/09/07 20:32:15 - mmengine - INFO - Epoch(train) [28][580/1793] lr: 7.5000e-03 eta: 3:47:03 time: 0.1711 data_time: 0.0064 memory: 10464 grad_norm: 7.5527 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1056 loss: 2.1056 2022/09/07 20:32:17 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:32:19 - mmengine - INFO - Epoch(train) [28][600/1793] lr: 7.5000e-03 eta: 3:46:54 time: 0.1906 data_time: 0.0072 memory: 10464 grad_norm: 7.6262 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.2923 loss: 2.2923 2022/09/07 20:32:22 - mmengine - INFO - Epoch(train) [28][620/1793] lr: 7.5000e-03 eta: 3:46:45 time: 0.1750 data_time: 0.0088 memory: 10464 grad_norm: 7.6787 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2337 loss: 2.2337 2022/09/07 20:32:26 - mmengine - INFO - Epoch(train) [28][640/1793] lr: 7.5000e-03 eta: 3:46:35 time: 0.1782 data_time: 0.0066 memory: 10464 grad_norm: 7.4680 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1569 loss: 2.1569 2022/09/07 20:32:30 - mmengine - INFO - Epoch(train) [28][660/1793] lr: 7.5000e-03 eta: 3:46:26 time: 0.1745 data_time: 0.0059 memory: 10464 grad_norm: 7.3773 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0618 loss: 2.0618 2022/09/07 20:32:33 - mmengine - INFO - Epoch(train) [28][680/1793] lr: 7.5000e-03 eta: 3:46:17 time: 0.1740 data_time: 0.0094 memory: 10464 grad_norm: 7.1348 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1188 loss: 2.1188 2022/09/07 20:32:36 - mmengine - INFO - Epoch(train) [28][700/1793] lr: 7.5000e-03 eta: 3:46:07 time: 0.1720 data_time: 0.0055 memory: 10464 grad_norm: 7.4532 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2917 loss: 2.2917 2022/09/07 20:32:40 - mmengine - INFO - Epoch(train) [28][720/1793] lr: 7.5000e-03 eta: 3:45:58 time: 0.1780 data_time: 0.0078 memory: 10464 grad_norm: 7.4756 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1838 loss: 2.1838 2022/09/07 20:32:44 - mmengine - INFO - Epoch(train) [28][740/1793] lr: 7.5000e-03 eta: 3:45:49 time: 0.1744 data_time: 0.0090 memory: 10464 grad_norm: 7.2907 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9602 loss: 1.9602 2022/09/07 20:32:47 - mmengine - INFO - Epoch(train) [28][760/1793] lr: 7.5000e-03 eta: 3:45:39 time: 0.1735 data_time: 0.0059 memory: 10464 grad_norm: 7.5210 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2759 loss: 2.2759 2022/09/07 20:32:50 - mmengine - INFO - Epoch(train) [28][780/1793] lr: 7.5000e-03 eta: 3:45:30 time: 0.1737 data_time: 0.0063 memory: 10464 grad_norm: 7.4618 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1505 loss: 2.1505 2022/09/07 20:32:54 - mmengine - INFO - Epoch(train) [28][800/1793] lr: 7.5000e-03 eta: 3:45:21 time: 0.1743 data_time: 0.0090 memory: 10464 grad_norm: 7.5961 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9376 loss: 1.9376 2022/09/07 20:32:57 - mmengine - INFO - Epoch(train) [28][820/1793] lr: 7.5000e-03 eta: 3:45:11 time: 0.1722 data_time: 0.0070 memory: 10464 grad_norm: 7.3552 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.2877 loss: 2.2877 2022/09/07 20:33:01 - mmengine - INFO - Epoch(train) [28][840/1793] lr: 7.5000e-03 eta: 3:45:02 time: 0.1800 data_time: 0.0078 memory: 10464 grad_norm: 7.2325 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1609 loss: 2.1609 2022/09/07 20:33:05 - mmengine - INFO - Epoch(train) [28][860/1793] lr: 7.5000e-03 eta: 3:44:53 time: 0.1743 data_time: 0.0096 memory: 10464 grad_norm: 7.2414 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1766 loss: 2.1766 2022/09/07 20:33:08 - mmengine - INFO - Epoch(train) [28][880/1793] lr: 7.5000e-03 eta: 3:44:44 time: 0.1753 data_time: 0.0055 memory: 10464 grad_norm: 7.3677 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2001 loss: 2.2001 2022/09/07 20:33:11 - mmengine - INFO - Epoch(train) [28][900/1793] lr: 7.5000e-03 eta: 3:44:34 time: 0.1715 data_time: 0.0058 memory: 10464 grad_norm: 7.5763 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.0935 loss: 2.0935 2022/09/07 20:33:15 - mmengine - INFO - Epoch(train) [28][920/1793] lr: 7.5000e-03 eta: 3:44:25 time: 0.1901 data_time: 0.0242 memory: 10464 grad_norm: 7.1841 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0997 loss: 2.0997 2022/09/07 20:33:19 - mmengine - INFO - Epoch(train) [28][940/1793] lr: 7.5000e-03 eta: 3:44:16 time: 0.1777 data_time: 0.0057 memory: 10464 grad_norm: 7.3017 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.4487 loss: 2.4487 2022/09/07 20:33:22 - mmengine - INFO - Epoch(train) [28][960/1793] lr: 7.5000e-03 eta: 3:44:07 time: 0.1700 data_time: 0.0062 memory: 10464 grad_norm: 7.3874 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.2830 loss: 2.2830 2022/09/07 20:33:26 - mmengine - INFO - Epoch(train) [28][980/1793] lr: 7.5000e-03 eta: 3:43:57 time: 0.1807 data_time: 0.0101 memory: 10464 grad_norm: 7.1282 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.2538 loss: 2.2538 2022/09/07 20:33:29 - mmengine - INFO - Epoch(train) [28][1000/1793] lr: 7.5000e-03 eta: 3:43:48 time: 0.1782 data_time: 0.0071 memory: 10464 grad_norm: 7.6592 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1297 loss: 2.1297 2022/09/07 20:33:33 - mmengine - INFO - Epoch(train) [28][1020/1793] lr: 7.5000e-03 eta: 3:43:39 time: 0.1726 data_time: 0.0058 memory: 10464 grad_norm: 6.9343 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1079 loss: 2.1079 2022/09/07 20:33:36 - mmengine - INFO - Epoch(train) [28][1040/1793] lr: 7.5000e-03 eta: 3:43:30 time: 0.1822 data_time: 0.0086 memory: 10464 grad_norm: 7.3137 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.4233 loss: 2.4233 2022/09/07 20:33:40 - mmengine - INFO - Epoch(train) [28][1060/1793] lr: 7.5000e-03 eta: 3:43:21 time: 0.1790 data_time: 0.0068 memory: 10464 grad_norm: 7.2762 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.0308 loss: 2.0308 2022/09/07 20:33:44 - mmengine - INFO - Epoch(train) [28][1080/1793] lr: 7.5000e-03 eta: 3:43:11 time: 0.1756 data_time: 0.0067 memory: 10464 grad_norm: 7.5169 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0204 loss: 2.0204 2022/09/07 20:33:47 - mmengine - INFO - Epoch(train) [28][1100/1793] lr: 7.5000e-03 eta: 3:43:02 time: 0.1795 data_time: 0.0090 memory: 10464 grad_norm: 7.2675 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.0017 loss: 2.0017 2022/09/07 20:33:51 - mmengine - INFO - Epoch(train) [28][1120/1793] lr: 7.5000e-03 eta: 3:42:53 time: 0.1781 data_time: 0.0072 memory: 10464 grad_norm: 7.5888 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.1635 loss: 2.1635 2022/09/07 20:33:54 - mmengine - INFO - Epoch(train) [28][1140/1793] lr: 7.5000e-03 eta: 3:42:44 time: 0.1722 data_time: 0.0068 memory: 10464 grad_norm: 7.7915 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2488 loss: 2.2488 2022/09/07 20:33:58 - mmengine - INFO - Epoch(train) [28][1160/1793] lr: 7.5000e-03 eta: 3:42:35 time: 0.1815 data_time: 0.0087 memory: 10464 grad_norm: 7.1077 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.9139 loss: 1.9139 2022/09/07 20:34:01 - mmengine - INFO - Epoch(train) [28][1180/1793] lr: 7.5000e-03 eta: 3:42:25 time: 0.1826 data_time: 0.0068 memory: 10464 grad_norm: 7.7677 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.3091 loss: 2.3091 2022/09/07 20:34:05 - mmengine - INFO - Epoch(train) [28][1200/1793] lr: 7.5000e-03 eta: 3:42:16 time: 0.1779 data_time: 0.0073 memory: 10464 grad_norm: 7.2388 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.9186 loss: 1.9186 2022/09/07 20:34:09 - mmengine - INFO - Epoch(train) [28][1220/1793] lr: 7.5000e-03 eta: 3:42:07 time: 0.1783 data_time: 0.0084 memory: 10464 grad_norm: 7.5310 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2330 loss: 2.2330 2022/09/07 20:34:12 - mmengine - INFO - Epoch(train) [28][1240/1793] lr: 7.5000e-03 eta: 3:41:58 time: 0.1726 data_time: 0.0069 memory: 10464 grad_norm: 7.4067 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.9634 loss: 1.9634 2022/09/07 20:34:16 - mmengine - INFO - Epoch(train) [28][1260/1793] lr: 7.5000e-03 eta: 3:41:49 time: 0.1711 data_time: 0.0062 memory: 10464 grad_norm: 7.5758 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.1880 loss: 2.1880 2022/09/07 20:34:20 - mmengine - INFO - Epoch(train) [28][1280/1793] lr: 7.5000e-03 eta: 3:41:40 time: 0.2001 data_time: 0.0101 memory: 10464 grad_norm: 7.5427 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3381 loss: 2.3381 2022/09/07 20:34:23 - mmengine - INFO - Epoch(train) [28][1300/1793] lr: 7.5000e-03 eta: 3:41:31 time: 0.1780 data_time: 0.0073 memory: 10464 grad_norm: 7.3836 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3897 loss: 2.3897 2022/09/07 20:34:27 - mmengine - INFO - Epoch(train) [28][1320/1793] lr: 7.5000e-03 eta: 3:41:21 time: 0.1724 data_time: 0.0064 memory: 10464 grad_norm: 7.3090 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0174 loss: 2.0174 2022/09/07 20:34:30 - mmengine - INFO - Epoch(train) [28][1340/1793] lr: 7.5000e-03 eta: 3:41:12 time: 0.1788 data_time: 0.0092 memory: 10464 grad_norm: 7.4343 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1645 loss: 2.1645 2022/09/07 20:34:34 - mmengine - INFO - Epoch(train) [28][1360/1793] lr: 7.5000e-03 eta: 3:41:03 time: 0.1731 data_time: 0.0074 memory: 10464 grad_norm: 7.2408 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.9859 loss: 1.9859 2022/09/07 20:34:37 - mmengine - INFO - Epoch(train) [28][1380/1793] lr: 7.5000e-03 eta: 3:40:54 time: 0.1730 data_time: 0.0049 memory: 10464 grad_norm: 7.4458 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2250 loss: 2.2250 2022/09/07 20:34:41 - mmengine - INFO - Epoch(train) [28][1400/1793] lr: 7.5000e-03 eta: 3:40:45 time: 0.1798 data_time: 0.0096 memory: 10464 grad_norm: 7.3681 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2335 loss: 2.2335 2022/09/07 20:34:44 - mmengine - INFO - Epoch(train) [28][1420/1793] lr: 7.5000e-03 eta: 3:40:36 time: 0.1794 data_time: 0.0062 memory: 10464 grad_norm: 7.0877 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2363 loss: 2.2363 2022/09/07 20:34:49 - mmengine - INFO - Epoch(train) [28][1440/1793] lr: 7.5000e-03 eta: 3:40:27 time: 0.2169 data_time: 0.0081 memory: 10464 grad_norm: 7.3708 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2914 loss: 2.2914 2022/09/07 20:34:52 - mmengine - INFO - Epoch(train) [28][1460/1793] lr: 7.5000e-03 eta: 3:40:18 time: 0.1763 data_time: 0.0095 memory: 10464 grad_norm: 7.3538 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0633 loss: 2.0633 2022/09/07 20:34:57 - mmengine - INFO - Epoch(train) [28][1480/1793] lr: 7.5000e-03 eta: 3:40:10 time: 0.2429 data_time: 0.0064 memory: 10464 grad_norm: 7.1011 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2116 loss: 2.2116 2022/09/07 20:35:01 - mmengine - INFO - Epoch(train) [28][1500/1793] lr: 7.5000e-03 eta: 3:40:01 time: 0.1776 data_time: 0.0072 memory: 10464 grad_norm: 7.4086 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1968 loss: 2.1968 2022/09/07 20:35:04 - mmengine - INFO - Epoch(train) [28][1520/1793] lr: 7.5000e-03 eta: 3:39:52 time: 0.1782 data_time: 0.0097 memory: 10464 grad_norm: 6.9716 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.0792 loss: 2.0792 2022/09/07 20:35:08 - mmengine - INFO - Epoch(train) [28][1540/1793] lr: 7.5000e-03 eta: 3:39:43 time: 0.2065 data_time: 0.0064 memory: 10464 grad_norm: 7.2014 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.2698 loss: 2.2698 2022/09/07 20:35:12 - mmengine - INFO - Epoch(train) [28][1560/1793] lr: 7.5000e-03 eta: 3:39:34 time: 0.1858 data_time: 0.0074 memory: 10464 grad_norm: 7.5546 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9680 loss: 1.9680 2022/09/07 20:35:15 - mmengine - INFO - Epoch(train) [28][1580/1793] lr: 7.5000e-03 eta: 3:39:25 time: 0.1738 data_time: 0.0086 memory: 10464 grad_norm: 7.1711 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0397 loss: 2.0397 2022/09/07 20:35:17 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:35:19 - mmengine - INFO - Epoch(train) [28][1600/1793] lr: 7.5000e-03 eta: 3:39:16 time: 0.1785 data_time: 0.0072 memory: 10464 grad_norm: 7.5766 top1_acc: 0.0000 top5_acc: 0.3333 loss_cls: 2.0482 loss: 2.0482 2022/09/07 20:35:23 - mmengine - INFO - Epoch(train) [28][1620/1793] lr: 7.5000e-03 eta: 3:39:07 time: 0.1807 data_time: 0.0065 memory: 10464 grad_norm: 7.3572 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.9138 loss: 1.9138 2022/09/07 20:35:26 - mmengine - INFO - Epoch(train) [28][1640/1793] lr: 7.5000e-03 eta: 3:38:58 time: 0.1771 data_time: 0.0085 memory: 10464 grad_norm: 7.5753 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.1573 loss: 2.1573 2022/09/07 20:35:30 - mmengine - INFO - Epoch(train) [28][1660/1793] lr: 7.5000e-03 eta: 3:38:49 time: 0.1765 data_time: 0.0073 memory: 10464 grad_norm: 7.1540 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2150 loss: 2.2150 2022/09/07 20:35:33 - mmengine - INFO - Epoch(train) [28][1680/1793] lr: 7.5000e-03 eta: 3:38:40 time: 0.1732 data_time: 0.0063 memory: 10464 grad_norm: 7.2661 top1_acc: 0.1667 top5_acc: 1.0000 loss_cls: 2.1077 loss: 2.1077 2022/09/07 20:35:37 - mmengine - INFO - Epoch(train) [28][1700/1793] lr: 7.5000e-03 eta: 3:38:31 time: 0.1833 data_time: 0.0101 memory: 10464 grad_norm: 7.1645 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.2229 loss: 2.2229 2022/09/07 20:35:40 - mmengine - INFO - Epoch(train) [28][1720/1793] lr: 7.5000e-03 eta: 3:38:22 time: 0.1780 data_time: 0.0062 memory: 10464 grad_norm: 7.1493 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7910 loss: 1.7910 2022/09/07 20:35:44 - mmengine - INFO - Epoch(train) [28][1740/1793] lr: 7.5000e-03 eta: 3:38:13 time: 0.1736 data_time: 0.0065 memory: 10464 grad_norm: 7.5224 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2929 loss: 2.2929 2022/09/07 20:35:47 - mmengine - INFO - Epoch(train) [28][1760/1793] lr: 7.5000e-03 eta: 3:38:03 time: 0.1762 data_time: 0.0091 memory: 10464 grad_norm: 7.5990 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4368 loss: 2.4368 2022/09/07 20:35:51 - mmengine - INFO - Epoch(train) [28][1780/1793] lr: 7.5000e-03 eta: 3:37:54 time: 0.1769 data_time: 0.0081 memory: 10464 grad_norm: 6.9943 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2404 loss: 2.2404 2022/09/07 20:35:53 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:35:53 - mmengine - INFO - Epoch(train) [28][1793/1793] lr: 7.5000e-03 eta: 3:37:54 time: 0.1707 data_time: 0.0063 memory: 10464 grad_norm: 7.2861 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.4310 loss: 2.4310 2022/09/07 20:35:53 - mmengine - INFO - Saving checkpoint at 28 epochs 2022/09/07 20:35:57 - mmengine - INFO - Epoch(val) [28][20/241] eta: 0:00:12 time: 0.0586 data_time: 0.0091 memory: 1482 2022/09/07 20:35:58 - mmengine - INFO - Epoch(val) [28][40/241] eta: 0:00:10 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 20:35:59 - mmengine - INFO - Epoch(val) [28][60/241] eta: 0:00:09 time: 0.0529 data_time: 0.0048 memory: 1482 2022/09/07 20:36:00 - mmengine - INFO - Epoch(val) [28][80/241] eta: 0:00:08 time: 0.0535 data_time: 0.0052 memory: 1482 2022/09/07 20:36:01 - mmengine - INFO - Epoch(val) [28][100/241] eta: 0:00:07 time: 0.0534 data_time: 0.0050 memory: 1482 2022/09/07 20:36:02 - mmengine - INFO - Epoch(val) [28][120/241] eta: 0:00:06 time: 0.0534 data_time: 0.0050 memory: 1482 2022/09/07 20:36:03 - mmengine - INFO - Epoch(val) [28][140/241] eta: 0:00:05 time: 0.0533 data_time: 0.0048 memory: 1482 2022/09/07 20:36:04 - mmengine - INFO - Epoch(val) [28][160/241] eta: 0:00:04 time: 0.0534 data_time: 0.0050 memory: 1482 2022/09/07 20:36:05 - mmengine - INFO - Epoch(val) [28][180/241] eta: 0:00:03 time: 0.0527 data_time: 0.0045 memory: 1482 2022/09/07 20:36:06 - mmengine - INFO - Epoch(val) [28][200/241] eta: 0:00:02 time: 0.0529 data_time: 0.0048 memory: 1482 2022/09/07 20:36:07 - mmengine - INFO - Epoch(val) [28][220/241] eta: 0:00:01 time: 0.0526 data_time: 0.0046 memory: 1482 2022/09/07 20:36:08 - mmengine - INFO - Epoch(val) [28][240/241] eta: 0:00:00 time: 0.0573 data_time: 0.0052 memory: 1482 2022/09/07 20:36:09 - mmengine - INFO - Epoch(val) [28][241/241] acc/top1: 0.3464 acc/top5: 0.6448 acc/mean1: 0.3173 2022/09/07 20:36:13 - mmengine - INFO - Epoch(train) [29][20/1793] lr: 7.5000e-03 eta: 3:37:38 time: 0.2068 data_time: 0.0112 memory: 10464 grad_norm: 7.1179 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3672 loss: 2.3672 2022/09/07 20:36:17 - mmengine - INFO - Epoch(train) [29][40/1793] lr: 7.5000e-03 eta: 3:37:29 time: 0.1718 data_time: 0.0062 memory: 10464 grad_norm: 7.0186 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.9401 loss: 1.9401 2022/09/07 20:36:20 - mmengine - INFO - Epoch(train) [29][60/1793] lr: 7.5000e-03 eta: 3:37:20 time: 0.1738 data_time: 0.0062 memory: 10464 grad_norm: 7.4956 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.9255 loss: 1.9255 2022/09/07 20:36:24 - mmengine - INFO - Epoch(train) [29][80/1793] lr: 7.5000e-03 eta: 3:37:11 time: 0.1778 data_time: 0.0085 memory: 10464 grad_norm: 7.2297 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9104 loss: 1.9104 2022/09/07 20:36:27 - mmengine - INFO - Epoch(train) [29][100/1793] lr: 7.5000e-03 eta: 3:37:02 time: 0.1850 data_time: 0.0070 memory: 10464 grad_norm: 7.5803 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0207 loss: 2.0207 2022/09/07 20:36:31 - mmengine - INFO - Epoch(train) [29][120/1793] lr: 7.5000e-03 eta: 3:36:53 time: 0.1970 data_time: 0.0070 memory: 10464 grad_norm: 7.1663 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9639 loss: 1.9639 2022/09/07 20:36:35 - mmengine - INFO - Epoch(train) [29][140/1793] lr: 7.5000e-03 eta: 3:36:44 time: 0.1736 data_time: 0.0088 memory: 10464 grad_norm: 7.1888 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1241 loss: 2.1241 2022/09/07 20:36:38 - mmengine - INFO - Epoch(train) [29][160/1793] lr: 7.5000e-03 eta: 3:36:35 time: 0.1706 data_time: 0.0066 memory: 10464 grad_norm: 7.2313 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0994 loss: 2.0994 2022/09/07 20:36:42 - mmengine - INFO - Epoch(train) [29][180/1793] lr: 7.5000e-03 eta: 3:36:26 time: 0.1739 data_time: 0.0065 memory: 10464 grad_norm: 7.2862 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.1339 loss: 2.1339 2022/09/07 20:36:45 - mmengine - INFO - Epoch(train) [29][200/1793] lr: 7.5000e-03 eta: 3:36:17 time: 0.1761 data_time: 0.0091 memory: 10464 grad_norm: 7.6359 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1379 loss: 2.1379 2022/09/07 20:36:49 - mmengine - INFO - Epoch(train) [29][220/1793] lr: 7.5000e-03 eta: 3:36:08 time: 0.1895 data_time: 0.0071 memory: 10464 grad_norm: 7.5287 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.1846 loss: 2.1846 2022/09/07 20:36:52 - mmengine - INFO - Epoch(train) [29][240/1793] lr: 7.5000e-03 eta: 3:35:59 time: 0.1723 data_time: 0.0066 memory: 10464 grad_norm: 7.7646 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.3684 loss: 2.3684 2022/09/07 20:36:56 - mmengine - INFO - Epoch(train) [29][260/1793] lr: 7.5000e-03 eta: 3:35:50 time: 0.1769 data_time: 0.0098 memory: 10464 grad_norm: 7.7062 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2851 loss: 2.2851 2022/09/07 20:37:00 - mmengine - INFO - Epoch(train) [29][280/1793] lr: 7.5000e-03 eta: 3:35:41 time: 0.1764 data_time: 0.0063 memory: 10464 grad_norm: 7.2554 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.0940 loss: 2.0940 2022/09/07 20:37:03 - mmengine - INFO - Epoch(train) [29][300/1793] lr: 7.5000e-03 eta: 3:35:32 time: 0.1793 data_time: 0.0064 memory: 10464 grad_norm: 7.2561 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.0384 loss: 2.0384 2022/09/07 20:37:07 - mmengine - INFO - Epoch(train) [29][320/1793] lr: 7.5000e-03 eta: 3:35:23 time: 0.1780 data_time: 0.0099 memory: 10464 grad_norm: 7.1835 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1387 loss: 2.1387 2022/09/07 20:37:10 - mmengine - INFO - Epoch(train) [29][340/1793] lr: 7.5000e-03 eta: 3:35:14 time: 0.1815 data_time: 0.0082 memory: 10464 grad_norm: 7.3960 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4261 loss: 2.4261 2022/09/07 20:37:14 - mmengine - INFO - Epoch(train) [29][360/1793] lr: 7.5000e-03 eta: 3:35:05 time: 0.1747 data_time: 0.0066 memory: 10464 grad_norm: 7.3065 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.4064 loss: 2.4064 2022/09/07 20:37:17 - mmengine - INFO - Epoch(train) [29][380/1793] lr: 7.5000e-03 eta: 3:34:56 time: 0.1751 data_time: 0.0086 memory: 10464 grad_norm: 7.1247 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.0540 loss: 2.0540 2022/09/07 20:37:21 - mmengine - INFO - Epoch(train) [29][400/1793] lr: 7.5000e-03 eta: 3:34:47 time: 0.1740 data_time: 0.0068 memory: 10464 grad_norm: 7.0359 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8837 loss: 1.8837 2022/09/07 20:37:24 - mmengine - INFO - Epoch(train) [29][420/1793] lr: 7.5000e-03 eta: 3:34:38 time: 0.1727 data_time: 0.0060 memory: 10464 grad_norm: 7.4104 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.5354 loss: 2.5354 2022/09/07 20:37:28 - mmengine - INFO - Epoch(train) [29][440/1793] lr: 7.5000e-03 eta: 3:34:29 time: 0.1771 data_time: 0.0087 memory: 10464 grad_norm: 8.0092 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1738 loss: 2.1738 2022/09/07 20:37:31 - mmengine - INFO - Epoch(train) [29][460/1793] lr: 7.5000e-03 eta: 3:34:20 time: 0.1770 data_time: 0.0074 memory: 10464 grad_norm: 7.8525 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.4568 loss: 2.4568 2022/09/07 20:37:35 - mmengine - INFO - Epoch(train) [29][480/1793] lr: 7.5000e-03 eta: 3:34:11 time: 0.1823 data_time: 0.0067 memory: 10464 grad_norm: 7.3501 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4339 loss: 2.4339 2022/09/07 20:37:38 - mmengine - INFO - Epoch(train) [29][500/1793] lr: 7.5000e-03 eta: 3:34:02 time: 0.1730 data_time: 0.0086 memory: 10464 grad_norm: 7.3319 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.2495 loss: 2.2495 2022/09/07 20:37:42 - mmengine - INFO - Epoch(train) [29][520/1793] lr: 7.5000e-03 eta: 3:33:53 time: 0.1732 data_time: 0.0064 memory: 10464 grad_norm: 7.1842 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3999 loss: 2.3999 2022/09/07 20:37:46 - mmengine - INFO - Epoch(train) [29][540/1793] lr: 7.5000e-03 eta: 3:33:45 time: 0.1800 data_time: 0.0069 memory: 10464 grad_norm: 7.2459 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3052 loss: 2.3052 2022/09/07 20:37:49 - mmengine - INFO - Epoch(train) [29][560/1793] lr: 7.5000e-03 eta: 3:33:36 time: 0.1894 data_time: 0.0095 memory: 10464 grad_norm: 7.4310 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1360 loss: 2.1360 2022/09/07 20:37:53 - mmengine - INFO - Epoch(train) [29][580/1793] lr: 7.5000e-03 eta: 3:33:27 time: 0.1720 data_time: 0.0063 memory: 10464 grad_norm: 7.3529 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.1784 loss: 2.1784 2022/09/07 20:37:56 - mmengine - INFO - Epoch(train) [29][600/1793] lr: 7.5000e-03 eta: 3:33:18 time: 0.1736 data_time: 0.0071 memory: 10464 grad_norm: 7.3190 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2339 loss: 2.2339 2022/09/07 20:38:00 - mmengine - INFO - Epoch(train) [29][620/1793] lr: 7.5000e-03 eta: 3:33:09 time: 0.1761 data_time: 0.0084 memory: 10464 grad_norm: 7.0730 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.1254 loss: 2.1254 2022/09/07 20:38:03 - mmengine - INFO - Epoch(train) [29][640/1793] lr: 7.5000e-03 eta: 3:33:00 time: 0.1821 data_time: 0.0063 memory: 10464 grad_norm: 7.2506 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4233 loss: 2.4233 2022/09/07 20:38:07 - mmengine - INFO - Epoch(train) [29][660/1793] lr: 7.5000e-03 eta: 3:32:51 time: 0.1806 data_time: 0.0063 memory: 10464 grad_norm: 7.3993 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.1728 loss: 2.1728 2022/09/07 20:38:11 - mmengine - INFO - Epoch(train) [29][680/1793] lr: 7.5000e-03 eta: 3:32:42 time: 0.1836 data_time: 0.0096 memory: 10464 grad_norm: 7.3004 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2438 loss: 2.2438 2022/09/07 20:38:14 - mmengine - INFO - Epoch(train) [29][700/1793] lr: 7.5000e-03 eta: 3:32:33 time: 0.1705 data_time: 0.0065 memory: 10464 grad_norm: 7.1854 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2485 loss: 2.2485 2022/09/07 20:38:18 - mmengine - INFO - Epoch(train) [29][720/1793] lr: 7.5000e-03 eta: 3:32:25 time: 0.1766 data_time: 0.0062 memory: 10464 grad_norm: 7.4416 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0472 loss: 2.0472 2022/09/07 20:38:21 - mmengine - INFO - Epoch(train) [29][740/1793] lr: 7.5000e-03 eta: 3:32:16 time: 0.1751 data_time: 0.0086 memory: 10464 grad_norm: 7.5833 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.9349 loss: 1.9349 2022/09/07 20:38:25 - mmengine - INFO - Epoch(train) [29][760/1793] lr: 7.5000e-03 eta: 3:32:07 time: 0.1719 data_time: 0.0064 memory: 10464 grad_norm: 7.4901 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1223 loss: 2.1223 2022/09/07 20:38:28 - mmengine - INFO - Epoch(train) [29][780/1793] lr: 7.5000e-03 eta: 3:31:58 time: 0.1883 data_time: 0.0061 memory: 10464 grad_norm: 7.3624 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2520 loss: 2.2520 2022/09/07 20:38:31 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:38:32 - mmengine - INFO - Epoch(train) [29][800/1793] lr: 7.5000e-03 eta: 3:31:49 time: 0.1820 data_time: 0.0091 memory: 10464 grad_norm: 7.3899 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 1.9727 loss: 1.9727 2022/09/07 20:38:36 - mmengine - INFO - Epoch(train) [29][820/1793] lr: 7.5000e-03 eta: 3:31:40 time: 0.1746 data_time: 0.0061 memory: 10464 grad_norm: 7.1106 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0852 loss: 2.0852 2022/09/07 20:38:39 - mmengine - INFO - Epoch(train) [29][840/1793] lr: 7.5000e-03 eta: 3:31:31 time: 0.1779 data_time: 0.0062 memory: 10464 grad_norm: 7.7147 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3561 loss: 2.3561 2022/09/07 20:38:43 - mmengine - INFO - Epoch(train) [29][860/1793] lr: 7.5000e-03 eta: 3:31:22 time: 0.1758 data_time: 0.0094 memory: 10464 grad_norm: 7.3041 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2379 loss: 2.2379 2022/09/07 20:38:46 - mmengine - INFO - Epoch(train) [29][880/1793] lr: 7.5000e-03 eta: 3:31:14 time: 0.1909 data_time: 0.0062 memory: 10464 grad_norm: 7.1109 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.9077 loss: 1.9077 2022/09/07 20:38:50 - mmengine - INFO - Epoch(train) [29][900/1793] lr: 7.5000e-03 eta: 3:31:05 time: 0.1925 data_time: 0.0078 memory: 10464 grad_norm: 7.3287 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.0902 loss: 2.0902 2022/09/07 20:38:54 - mmengine - INFO - Epoch(train) [29][920/1793] lr: 7.5000e-03 eta: 3:30:56 time: 0.1766 data_time: 0.0091 memory: 10464 grad_norm: 7.1513 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.0960 loss: 2.0960 2022/09/07 20:38:57 - mmengine - INFO - Epoch(train) [29][940/1793] lr: 7.5000e-03 eta: 3:30:47 time: 0.1710 data_time: 0.0062 memory: 10464 grad_norm: 7.3167 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0428 loss: 2.0428 2022/09/07 20:39:01 - mmengine - INFO - Epoch(train) [29][960/1793] lr: 7.5000e-03 eta: 3:30:38 time: 0.1713 data_time: 0.0063 memory: 10464 grad_norm: 7.3444 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2660 loss: 2.2660 2022/09/07 20:39:04 - mmengine - INFO - Epoch(train) [29][980/1793] lr: 7.5000e-03 eta: 3:30:30 time: 0.1778 data_time: 0.0087 memory: 10464 grad_norm: 7.5739 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2148 loss: 2.2148 2022/09/07 20:39:09 - mmengine - INFO - Epoch(train) [29][1000/1793] lr: 7.5000e-03 eta: 3:30:22 time: 0.2551 data_time: 0.0065 memory: 10464 grad_norm: 7.0726 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3368 loss: 2.3368 2022/09/07 20:39:13 - mmengine - INFO - Epoch(train) [29][1020/1793] lr: 7.5000e-03 eta: 3:30:13 time: 0.1735 data_time: 0.0063 memory: 10464 grad_norm: 7.2651 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3469 loss: 2.3469 2022/09/07 20:39:16 - mmengine - INFO - Epoch(train) [29][1040/1793] lr: 7.5000e-03 eta: 3:30:04 time: 0.1758 data_time: 0.0086 memory: 10464 grad_norm: 7.1431 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.9337 loss: 1.9337 2022/09/07 20:39:20 - mmengine - INFO - Epoch(train) [29][1060/1793] lr: 7.5000e-03 eta: 3:29:55 time: 0.1803 data_time: 0.0070 memory: 10464 grad_norm: 7.2784 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2195 loss: 2.2195 2022/09/07 20:39:23 - mmengine - INFO - Epoch(train) [29][1080/1793] lr: 7.5000e-03 eta: 3:29:47 time: 0.1744 data_time: 0.0067 memory: 10464 grad_norm: 7.5941 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.0895 loss: 2.0895 2022/09/07 20:39:27 - mmengine - INFO - Epoch(train) [29][1100/1793] lr: 7.5000e-03 eta: 3:29:38 time: 0.1827 data_time: 0.0083 memory: 10464 grad_norm: 7.1747 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 1.8786 loss: 1.8786 2022/09/07 20:39:31 - mmengine - INFO - Epoch(train) [29][1120/1793] lr: 7.5000e-03 eta: 3:29:29 time: 0.1718 data_time: 0.0069 memory: 10464 grad_norm: 7.3263 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.8600 loss: 1.8600 2022/09/07 20:39:34 - mmengine - INFO - Epoch(train) [29][1140/1793] lr: 7.5000e-03 eta: 3:29:20 time: 0.1713 data_time: 0.0071 memory: 10464 grad_norm: 7.4068 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3010 loss: 2.3010 2022/09/07 20:39:37 - mmengine - INFO - Epoch(train) [29][1160/1793] lr: 7.5000e-03 eta: 3:29:11 time: 0.1730 data_time: 0.0083 memory: 10464 grad_norm: 7.2222 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1402 loss: 2.1402 2022/09/07 20:39:41 - mmengine - INFO - Epoch(train) [29][1180/1793] lr: 7.5000e-03 eta: 3:29:02 time: 0.1769 data_time: 0.0070 memory: 10464 grad_norm: 7.1452 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.1682 loss: 2.1682 2022/09/07 20:39:44 - mmengine - INFO - Epoch(train) [29][1200/1793] lr: 7.5000e-03 eta: 3:28:54 time: 0.1745 data_time: 0.0067 memory: 10464 grad_norm: 7.3693 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1262 loss: 2.1262 2022/09/07 20:39:48 - mmengine - INFO - Epoch(train) [29][1220/1793] lr: 7.5000e-03 eta: 3:28:45 time: 0.1793 data_time: 0.0084 memory: 10464 grad_norm: 7.5367 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4053 loss: 2.4053 2022/09/07 20:39:52 - mmengine - INFO - Epoch(train) [29][1240/1793] lr: 7.5000e-03 eta: 3:28:36 time: 0.1756 data_time: 0.0072 memory: 10464 grad_norm: 7.1921 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.0992 loss: 2.0992 2022/09/07 20:39:55 - mmengine - INFO - Epoch(train) [29][1260/1793] lr: 7.5000e-03 eta: 3:28:27 time: 0.1757 data_time: 0.0068 memory: 10464 grad_norm: 7.0970 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0331 loss: 2.0331 2022/09/07 20:39:59 - mmengine - INFO - Epoch(train) [29][1280/1793] lr: 7.5000e-03 eta: 3:28:18 time: 0.1746 data_time: 0.0081 memory: 10464 grad_norm: 7.4514 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.4448 loss: 2.4448 2022/09/07 20:40:02 - mmengine - INFO - Epoch(train) [29][1300/1793] lr: 7.5000e-03 eta: 3:28:10 time: 0.1912 data_time: 0.0075 memory: 10464 grad_norm: 7.3307 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1479 loss: 2.1479 2022/09/07 20:40:06 - mmengine - INFO - Epoch(train) [29][1320/1793] lr: 7.5000e-03 eta: 3:28:01 time: 0.1723 data_time: 0.0067 memory: 10464 grad_norm: 7.3712 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 1.9733 loss: 1.9733 2022/09/07 20:40:10 - mmengine - INFO - Epoch(train) [29][1340/1793] lr: 7.5000e-03 eta: 3:27:52 time: 0.1860 data_time: 0.0094 memory: 10464 grad_norm: 7.5392 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.2644 loss: 2.2644 2022/09/07 20:40:14 - mmengine - INFO - Epoch(train) [29][1360/1793] lr: 7.5000e-03 eta: 3:27:44 time: 0.2419 data_time: 0.0063 memory: 10464 grad_norm: 7.4585 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1259 loss: 2.1259 2022/09/07 20:40:18 - mmengine - INFO - Epoch(train) [29][1380/1793] lr: 7.5000e-03 eta: 3:27:36 time: 0.1727 data_time: 0.0063 memory: 10464 grad_norm: 7.1293 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.9969 loss: 1.9969 2022/09/07 20:40:22 - mmengine - INFO - Epoch(train) [29][1400/1793] lr: 7.5000e-03 eta: 3:27:27 time: 0.1823 data_time: 0.0091 memory: 10464 grad_norm: 7.2884 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.1915 loss: 2.1915 2022/09/07 20:40:25 - mmengine - INFO - Epoch(train) [29][1420/1793] lr: 7.5000e-03 eta: 3:27:18 time: 0.1726 data_time: 0.0063 memory: 10464 grad_norm: 7.2858 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.9350 loss: 1.9350 2022/09/07 20:40:29 - mmengine - INFO - Epoch(train) [29][1440/1793] lr: 7.5000e-03 eta: 3:27:09 time: 0.1786 data_time: 0.0063 memory: 10464 grad_norm: 7.2838 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.8811 loss: 1.8811 2022/09/07 20:40:32 - mmengine - INFO - Epoch(train) [29][1460/1793] lr: 7.5000e-03 eta: 3:27:01 time: 0.1759 data_time: 0.0098 memory: 10464 grad_norm: 7.5728 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.3581 loss: 2.3581 2022/09/07 20:40:36 - mmengine - INFO - Epoch(train) [29][1480/1793] lr: 7.5000e-03 eta: 3:26:52 time: 0.1745 data_time: 0.0064 memory: 10464 grad_norm: 7.2655 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1507 loss: 2.1507 2022/09/07 20:40:39 - mmengine - INFO - Epoch(train) [29][1500/1793] lr: 7.5000e-03 eta: 3:26:43 time: 0.1810 data_time: 0.0069 memory: 10464 grad_norm: 7.5437 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1136 loss: 2.1136 2022/09/07 20:40:43 - mmengine - INFO - Epoch(train) [29][1520/1793] lr: 7.5000e-03 eta: 3:26:34 time: 0.1748 data_time: 0.0093 memory: 10464 grad_norm: 7.9157 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1998 loss: 2.1998 2022/09/07 20:40:46 - mmengine - INFO - Epoch(train) [29][1540/1793] lr: 7.5000e-03 eta: 3:26:26 time: 0.1738 data_time: 0.0063 memory: 10464 grad_norm: 7.5256 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.8782 loss: 1.8782 2022/09/07 20:40:50 - mmengine - INFO - Epoch(train) [29][1560/1793] lr: 7.5000e-03 eta: 3:26:17 time: 0.1729 data_time: 0.0070 memory: 10464 grad_norm: 7.0334 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.1408 loss: 2.1408 2022/09/07 20:40:53 - mmengine - INFO - Epoch(train) [29][1580/1793] lr: 7.5000e-03 eta: 3:26:08 time: 0.1730 data_time: 0.0080 memory: 10464 grad_norm: 7.5751 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.4157 loss: 2.4157 2022/09/07 20:40:57 - mmengine - INFO - Epoch(train) [29][1600/1793] lr: 7.5000e-03 eta: 3:25:59 time: 0.1739 data_time: 0.0064 memory: 10464 grad_norm: 7.6173 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.0910 loss: 2.0910 2022/09/07 20:41:00 - mmengine - INFO - Epoch(train) [29][1620/1793] lr: 7.5000e-03 eta: 3:25:51 time: 0.1762 data_time: 0.0067 memory: 10464 grad_norm: 7.4562 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.9925 loss: 1.9925 2022/09/07 20:41:04 - mmengine - INFO - Epoch(train) [29][1640/1793] lr: 7.5000e-03 eta: 3:25:42 time: 0.1740 data_time: 0.0084 memory: 10464 grad_norm: 7.2682 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2536 loss: 2.2536 2022/09/07 20:41:07 - mmengine - INFO - Epoch(train) [29][1660/1793] lr: 7.5000e-03 eta: 3:25:33 time: 0.1821 data_time: 0.0063 memory: 10464 grad_norm: 7.2120 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.1729 loss: 2.1729 2022/09/07 20:41:11 - mmengine - INFO - Epoch(train) [29][1680/1793] lr: 7.5000e-03 eta: 3:25:24 time: 0.1725 data_time: 0.0076 memory: 10464 grad_norm: 7.2838 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0758 loss: 2.0758 2022/09/07 20:41:14 - mmengine - INFO - Epoch(train) [29][1700/1793] lr: 7.5000e-03 eta: 3:25:16 time: 0.1735 data_time: 0.0085 memory: 10464 grad_norm: 7.3595 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1390 loss: 2.1390 2022/09/07 20:41:18 - mmengine - INFO - Epoch(train) [29][1720/1793] lr: 7.5000e-03 eta: 3:25:07 time: 0.1728 data_time: 0.0063 memory: 10464 grad_norm: 7.5910 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3429 loss: 2.3429 2022/09/07 20:41:21 - mmengine - INFO - Epoch(train) [29][1740/1793] lr: 7.5000e-03 eta: 3:24:58 time: 0.1768 data_time: 0.0072 memory: 10464 grad_norm: 7.4968 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2058 loss: 2.2058 2022/09/07 20:41:25 - mmengine - INFO - Epoch(train) [29][1760/1793] lr: 7.5000e-03 eta: 3:24:49 time: 0.1745 data_time: 0.0092 memory: 10464 grad_norm: 7.2923 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.8741 loss: 1.8741 2022/09/07 20:41:28 - mmengine - INFO - Epoch(train) [29][1780/1793] lr: 7.5000e-03 eta: 3:24:41 time: 0.1780 data_time: 0.0067 memory: 10464 grad_norm: 7.6071 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.9671 loss: 1.9671 2022/09/07 20:41:30 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:41:30 - mmengine - INFO - Epoch(train) [29][1793/1793] lr: 7.5000e-03 eta: 3:24:41 time: 0.1684 data_time: 0.0065 memory: 10464 grad_norm: 7.7986 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.2323 loss: 2.2323 2022/09/07 20:41:30 - mmengine - INFO - Saving checkpoint at 29 epochs 2022/09/07 20:41:35 - mmengine - INFO - Epoch(val) [29][20/241] eta: 0:00:13 time: 0.0602 data_time: 0.0111 memory: 1482 2022/09/07 20:41:36 - mmengine - INFO - Epoch(val) [29][40/241] eta: 0:00:10 time: 0.0533 data_time: 0.0050 memory: 1482 2022/09/07 20:41:37 - mmengine - INFO - Epoch(val) [29][60/241] eta: 0:00:09 time: 0.0527 data_time: 0.0046 memory: 1482 2022/09/07 20:41:38 - mmengine - INFO - Epoch(val) [29][80/241] eta: 0:00:08 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 20:41:39 - mmengine - INFO - Epoch(val) [29][100/241] eta: 0:00:07 time: 0.0535 data_time: 0.0050 memory: 1482 2022/09/07 20:41:40 - mmengine - INFO - Epoch(val) [29][120/241] eta: 0:00:06 time: 0.0534 data_time: 0.0050 memory: 1482 2022/09/07 20:41:41 - mmengine - INFO - Epoch(val) [29][140/241] eta: 0:00:05 time: 0.0531 data_time: 0.0048 memory: 1482 2022/09/07 20:41:42 - mmengine - INFO - Epoch(val) [29][160/241] eta: 0:00:04 time: 0.0539 data_time: 0.0054 memory: 1482 2022/09/07 20:41:43 - mmengine - INFO - Epoch(val) [29][180/241] eta: 0:00:03 time: 0.0524 data_time: 0.0042 memory: 1482 2022/09/07 20:41:44 - mmengine - INFO - Epoch(val) [29][200/241] eta: 0:00:02 time: 0.0522 data_time: 0.0044 memory: 1482 2022/09/07 20:41:45 - mmengine - INFO - Epoch(val) [29][220/241] eta: 0:00:01 time: 0.0521 data_time: 0.0043 memory: 1482 2022/09/07 20:41:46 - mmengine - INFO - Epoch(val) [29][240/241] eta: 0:00:00 time: 0.0519 data_time: 0.0043 memory: 1482 2022/09/07 20:41:47 - mmengine - INFO - Epoch(val) [29][241/241] acc/top1: 0.3422 acc/top5: 0.6473 acc/mean1: 0.3143 2022/09/07 20:41:48 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:41:51 - mmengine - INFO - Epoch(train) [30][20/1793] lr: 7.5000e-03 eta: 3:24:25 time: 0.2128 data_time: 0.0113 memory: 10464 grad_norm: 7.2742 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0149 loss: 2.0149 2022/09/07 20:41:55 - mmengine - INFO - Epoch(train) [30][40/1793] lr: 7.5000e-03 eta: 3:24:17 time: 0.1747 data_time: 0.0065 memory: 10464 grad_norm: 7.2721 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1231 loss: 2.1231 2022/09/07 20:41:58 - mmengine - INFO - Epoch(train) [30][60/1793] lr: 7.5000e-03 eta: 3:24:08 time: 0.1723 data_time: 0.0058 memory: 10464 grad_norm: 7.8164 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1758 loss: 2.1758 2022/09/07 20:42:02 - mmengine - INFO - Epoch(train) [30][80/1793] lr: 7.5000e-03 eta: 3:23:59 time: 0.1806 data_time: 0.0084 memory: 10464 grad_norm: 7.2800 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0315 loss: 2.0315 2022/09/07 20:42:05 - mmengine - INFO - Epoch(train) [30][100/1793] lr: 7.5000e-03 eta: 3:23:51 time: 0.1718 data_time: 0.0066 memory: 10464 grad_norm: 7.2379 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.0092 loss: 2.0092 2022/09/07 20:42:09 - mmengine - INFO - Epoch(train) [30][120/1793] lr: 7.5000e-03 eta: 3:23:42 time: 0.1803 data_time: 0.0065 memory: 10464 grad_norm: 7.2232 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3174 loss: 2.3174 2022/09/07 20:42:12 - mmengine - INFO - Epoch(train) [30][140/1793] lr: 7.5000e-03 eta: 3:23:33 time: 0.1767 data_time: 0.0092 memory: 10464 grad_norm: 7.2346 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.9803 loss: 1.9803 2022/09/07 20:42:16 - mmengine - INFO - Epoch(train) [30][160/1793] lr: 7.5000e-03 eta: 3:23:25 time: 0.1728 data_time: 0.0065 memory: 10464 grad_norm: 7.4287 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.0134 loss: 2.0134 2022/09/07 20:42:20 - mmengine - INFO - Epoch(train) [30][180/1793] lr: 7.5000e-03 eta: 3:23:16 time: 0.1908 data_time: 0.0086 memory: 10464 grad_norm: 7.4798 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.0633 loss: 2.0633 2022/09/07 20:42:23 - mmengine - INFO - Epoch(train) [30][200/1793] lr: 7.5000e-03 eta: 3:23:07 time: 0.1743 data_time: 0.0095 memory: 10464 grad_norm: 7.0923 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.1552 loss: 2.1552 2022/09/07 20:42:27 - mmengine - INFO - Epoch(train) [30][220/1793] lr: 7.5000e-03 eta: 3:22:59 time: 0.1805 data_time: 0.0061 memory: 10464 grad_norm: 7.1521 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2269 loss: 2.2269 2022/09/07 20:42:30 - mmengine - INFO - Epoch(train) [30][240/1793] lr: 7.5000e-03 eta: 3:22:50 time: 0.1718 data_time: 0.0065 memory: 10464 grad_norm: 7.2678 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 1.8159 loss: 1.8159 2022/09/07 20:42:34 - mmengine - INFO - Epoch(train) [30][260/1793] lr: 7.5000e-03 eta: 3:22:42 time: 0.1761 data_time: 0.0093 memory: 10464 grad_norm: 7.5983 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0833 loss: 2.0833 2022/09/07 20:42:37 - mmengine - INFO - Epoch(train) [30][280/1793] lr: 7.5000e-03 eta: 3:22:33 time: 0.1749 data_time: 0.0062 memory: 10464 grad_norm: 7.6680 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2257 loss: 2.2257 2022/09/07 20:42:41 - mmengine - INFO - Epoch(train) [30][300/1793] lr: 7.5000e-03 eta: 3:22:24 time: 0.1831 data_time: 0.0071 memory: 10464 grad_norm: 7.1396 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9933 loss: 1.9933 2022/09/07 20:42:44 - mmengine - INFO - Epoch(train) [30][320/1793] lr: 7.5000e-03 eta: 3:22:16 time: 0.1750 data_time: 0.0085 memory: 10464 grad_norm: 7.3456 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0317 loss: 2.0317 2022/09/07 20:42:48 - mmengine - INFO - Epoch(train) [30][340/1793] lr: 7.5000e-03 eta: 3:22:07 time: 0.1793 data_time: 0.0075 memory: 10464 grad_norm: 7.4269 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.0271 loss: 2.0271 2022/09/07 20:42:51 - mmengine - INFO - Epoch(train) [30][360/1793] lr: 7.5000e-03 eta: 3:21:58 time: 0.1710 data_time: 0.0048 memory: 10464 grad_norm: 7.1923 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.6706 loss: 1.6706 2022/09/07 20:42:55 - mmengine - INFO - Epoch(train) [30][380/1793] lr: 7.5000e-03 eta: 3:21:50 time: 0.1798 data_time: 0.0095 memory: 10464 grad_norm: 7.5128 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2121 loss: 2.2121 2022/09/07 20:42:58 - mmengine - INFO - Epoch(train) [30][400/1793] lr: 7.5000e-03 eta: 3:21:41 time: 0.1720 data_time: 0.0060 memory: 10464 grad_norm: 7.1014 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0705 loss: 2.0705 2022/09/07 20:43:02 - mmengine - INFO - Epoch(train) [30][420/1793] lr: 7.5000e-03 eta: 3:21:33 time: 0.1743 data_time: 0.0071 memory: 10464 grad_norm: 7.3893 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9999 loss: 1.9999 2022/09/07 20:43:05 - mmengine - INFO - Epoch(train) [30][440/1793] lr: 7.5000e-03 eta: 3:21:24 time: 0.1749 data_time: 0.0085 memory: 10464 grad_norm: 7.4925 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.9672 loss: 1.9672 2022/09/07 20:43:09 - mmengine - INFO - Epoch(train) [30][460/1793] lr: 7.5000e-03 eta: 3:21:15 time: 0.1731 data_time: 0.0071 memory: 10464 grad_norm: 7.0381 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0588 loss: 2.0588 2022/09/07 20:43:12 - mmengine - INFO - Epoch(train) [30][480/1793] lr: 7.5000e-03 eta: 3:21:07 time: 0.1789 data_time: 0.0070 memory: 10464 grad_norm: 7.3883 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.8776 loss: 1.8776 2022/09/07 20:43:16 - mmengine - INFO - Epoch(train) [30][500/1793] lr: 7.5000e-03 eta: 3:20:58 time: 0.1765 data_time: 0.0089 memory: 10464 grad_norm: 7.3823 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.1344 loss: 2.1344 2022/09/07 20:43:19 - mmengine - INFO - Epoch(train) [30][520/1793] lr: 7.5000e-03 eta: 3:20:50 time: 0.1785 data_time: 0.0070 memory: 10464 grad_norm: 7.3466 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3784 loss: 2.3784 2022/09/07 20:43:23 - mmengine - INFO - Epoch(train) [30][540/1793] lr: 7.5000e-03 eta: 3:20:41 time: 0.1746 data_time: 0.0067 memory: 10464 grad_norm: 7.3394 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.0875 loss: 2.0875 2022/09/07 20:43:27 - mmengine - INFO - Epoch(train) [30][560/1793] lr: 7.5000e-03 eta: 3:20:32 time: 0.1779 data_time: 0.0098 memory: 10464 grad_norm: 7.3545 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0784 loss: 2.0784 2022/09/07 20:43:30 - mmengine - INFO - Epoch(train) [30][580/1793] lr: 7.5000e-03 eta: 3:20:24 time: 0.1794 data_time: 0.0068 memory: 10464 grad_norm: 7.3132 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1223 loss: 2.1223 2022/09/07 20:43:34 - mmengine - INFO - Epoch(train) [30][600/1793] lr: 7.5000e-03 eta: 3:20:15 time: 0.1723 data_time: 0.0066 memory: 10464 grad_norm: 7.3972 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1700 loss: 2.1700 2022/09/07 20:43:37 - mmengine - INFO - Epoch(train) [30][620/1793] lr: 7.5000e-03 eta: 3:20:07 time: 0.1785 data_time: 0.0087 memory: 10464 grad_norm: 7.3378 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0902 loss: 2.0902 2022/09/07 20:43:41 - mmengine - INFO - Epoch(train) [30][640/1793] lr: 7.5000e-03 eta: 3:19:58 time: 0.1774 data_time: 0.0064 memory: 10464 grad_norm: 8.0439 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.2750 loss: 2.2750 2022/09/07 20:43:44 - mmengine - INFO - Epoch(train) [30][660/1793] lr: 7.5000e-03 eta: 3:19:50 time: 0.1754 data_time: 0.0061 memory: 10464 grad_norm: 7.4242 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3836 loss: 2.3836 2022/09/07 20:43:48 - mmengine - INFO - Epoch(train) [30][680/1793] lr: 7.5000e-03 eta: 3:19:41 time: 0.1768 data_time: 0.0092 memory: 10464 grad_norm: 7.0543 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.9323 loss: 1.9323 2022/09/07 20:43:51 - mmengine - INFO - Epoch(train) [30][700/1793] lr: 7.5000e-03 eta: 3:19:33 time: 0.1869 data_time: 0.0066 memory: 10464 grad_norm: 7.4633 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.1839 loss: 2.1839 2022/09/07 20:43:55 - mmengine - INFO - Epoch(train) [30][720/1793] lr: 7.5000e-03 eta: 3:19:24 time: 0.1780 data_time: 0.0102 memory: 10464 grad_norm: 7.2919 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.2506 loss: 2.2506 2022/09/07 20:43:59 - mmengine - INFO - Epoch(train) [30][740/1793] lr: 7.5000e-03 eta: 3:19:16 time: 0.1810 data_time: 0.0075 memory: 10464 grad_norm: 7.2586 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.0709 loss: 2.0709 2022/09/07 20:44:02 - mmengine - INFO - Epoch(train) [30][760/1793] lr: 7.5000e-03 eta: 3:19:07 time: 0.1808 data_time: 0.0081 memory: 10464 grad_norm: 7.4221 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.8212 loss: 1.8212 2022/09/07 20:44:06 - mmengine - INFO - Epoch(train) [30][780/1793] lr: 7.5000e-03 eta: 3:18:59 time: 0.1701 data_time: 0.0065 memory: 10464 grad_norm: 7.1074 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.0213 loss: 2.0213 2022/09/07 20:44:09 - mmengine - INFO - Epoch(train) [30][800/1793] lr: 7.5000e-03 eta: 3:18:50 time: 0.1834 data_time: 0.0112 memory: 10464 grad_norm: 7.0824 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2643 loss: 2.2643 2022/09/07 20:44:13 - mmengine - INFO - Epoch(train) [30][820/1793] lr: 7.5000e-03 eta: 3:18:42 time: 0.1736 data_time: 0.0062 memory: 10464 grad_norm: 7.2751 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.0813 loss: 2.0813 2022/09/07 20:44:16 - mmengine - INFO - Epoch(train) [30][840/1793] lr: 7.5000e-03 eta: 3:18:33 time: 0.1748 data_time: 0.0064 memory: 10464 grad_norm: 7.6173 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.9122 loss: 1.9122 2022/09/07 20:44:20 - mmengine - INFO - Epoch(train) [30][860/1793] lr: 7.5000e-03 eta: 3:18:24 time: 0.1794 data_time: 0.0097 memory: 10464 grad_norm: 7.4701 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.8976 loss: 1.8976 2022/09/07 20:44:23 - mmengine - INFO - Epoch(train) [30][880/1793] lr: 7.5000e-03 eta: 3:18:16 time: 0.1712 data_time: 0.0062 memory: 10464 grad_norm: 7.5041 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 2.3224 loss: 2.3224 2022/09/07 20:44:27 - mmengine - INFO - Epoch(train) [30][900/1793] lr: 7.5000e-03 eta: 3:18:07 time: 0.1769 data_time: 0.0063 memory: 10464 grad_norm: 7.3033 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.1645 loss: 2.1645 2022/09/07 20:44:30 - mmengine - INFO - Epoch(train) [30][920/1793] lr: 7.5000e-03 eta: 3:17:59 time: 0.1751 data_time: 0.0090 memory: 10464 grad_norm: 7.6221 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3423 loss: 2.3423 2022/09/07 20:44:34 - mmengine - INFO - Epoch(train) [30][940/1793] lr: 7.5000e-03 eta: 3:17:50 time: 0.1738 data_time: 0.0080 memory: 10464 grad_norm: 7.2030 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9212 loss: 1.9212 2022/09/07 20:44:37 - mmengine - INFO - Epoch(train) [30][960/1793] lr: 7.5000e-03 eta: 3:17:42 time: 0.1737 data_time: 0.0051 memory: 10464 grad_norm: 7.3063 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.4050 loss: 2.4050 2022/09/07 20:44:41 - mmengine - INFO - Epoch(train) [30][980/1793] lr: 7.5000e-03 eta: 3:17:33 time: 0.1828 data_time: 0.0107 memory: 10464 grad_norm: 7.4315 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3761 loss: 2.3761 2022/09/07 20:44:45 - mmengine - INFO - Epoch(train) [30][1000/1793] lr: 7.5000e-03 eta: 3:17:25 time: 0.1793 data_time: 0.0062 memory: 10464 grad_norm: 7.5510 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2384 loss: 2.2384 2022/09/07 20:44:45 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:44:48 - mmengine - INFO - Epoch(train) [30][1020/1793] lr: 7.5000e-03 eta: 3:17:16 time: 0.1770 data_time: 0.0064 memory: 10464 grad_norm: 7.4137 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3895 loss: 2.3895 2022/09/07 20:44:52 - mmengine - INFO - Epoch(train) [30][1040/1793] lr: 7.5000e-03 eta: 3:17:08 time: 0.1749 data_time: 0.0098 memory: 10464 grad_norm: 7.2347 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3397 loss: 2.3397 2022/09/07 20:44:55 - mmengine - INFO - Epoch(train) [30][1060/1793] lr: 7.5000e-03 eta: 3:16:59 time: 0.1723 data_time: 0.0062 memory: 10464 grad_norm: 7.4328 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.0033 loss: 2.0033 2022/09/07 20:44:59 - mmengine - INFO - Epoch(train) [30][1080/1793] lr: 7.5000e-03 eta: 3:16:51 time: 0.1809 data_time: 0.0072 memory: 10464 grad_norm: 7.1063 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.2198 loss: 2.2198 2022/09/07 20:45:03 - mmengine - INFO - Epoch(train) [30][1100/1793] lr: 7.5000e-03 eta: 3:16:43 time: 0.1945 data_time: 0.0099 memory: 10464 grad_norm: 7.5771 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.8399 loss: 1.8399 2022/09/07 20:45:06 - mmengine - INFO - Epoch(train) [30][1120/1793] lr: 7.5000e-03 eta: 3:16:34 time: 0.1703 data_time: 0.0066 memory: 10464 grad_norm: 7.4922 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0564 loss: 2.0564 2022/09/07 20:45:10 - mmengine - INFO - Epoch(train) [30][1140/1793] lr: 7.5000e-03 eta: 3:16:26 time: 0.1831 data_time: 0.0064 memory: 10464 grad_norm: 7.2710 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.1859 loss: 2.1859 2022/09/07 20:45:13 - mmengine - INFO - Epoch(train) [30][1160/1793] lr: 7.5000e-03 eta: 3:16:17 time: 0.1739 data_time: 0.0092 memory: 10464 grad_norm: 7.3873 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.0953 loss: 2.0953 2022/09/07 20:45:17 - mmengine - INFO - Epoch(train) [30][1180/1793] lr: 7.5000e-03 eta: 3:16:09 time: 0.1735 data_time: 0.0064 memory: 10464 grad_norm: 7.0892 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2348 loss: 2.2348 2022/09/07 20:45:21 - mmengine - INFO - Epoch(train) [30][1200/1793] lr: 7.5000e-03 eta: 3:16:01 time: 0.2110 data_time: 0.0077 memory: 10464 grad_norm: 7.1249 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7927 loss: 1.7927 2022/09/07 20:45:24 - mmengine - INFO - Epoch(train) [30][1220/1793] lr: 7.5000e-03 eta: 3:15:52 time: 0.1780 data_time: 0.0105 memory: 10464 grad_norm: 7.4355 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0054 loss: 2.0054 2022/09/07 20:45:28 - mmengine - INFO - Epoch(train) [30][1240/1793] lr: 7.5000e-03 eta: 3:15:44 time: 0.1745 data_time: 0.0067 memory: 10464 grad_norm: 7.5520 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.0289 loss: 2.0289 2022/09/07 20:45:31 - mmengine - INFO - Epoch(train) [30][1260/1793] lr: 7.5000e-03 eta: 3:15:35 time: 0.1738 data_time: 0.0068 memory: 10464 grad_norm: 7.4372 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.9380 loss: 1.9380 2022/09/07 20:45:35 - mmengine - INFO - Epoch(train) [30][1280/1793] lr: 7.5000e-03 eta: 3:15:27 time: 0.1733 data_time: 0.0085 memory: 10464 grad_norm: 7.5379 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.8934 loss: 1.8934 2022/09/07 20:45:38 - mmengine - INFO - Epoch(train) [30][1300/1793] lr: 7.5000e-03 eta: 3:15:19 time: 0.1796 data_time: 0.0067 memory: 10464 grad_norm: 7.4799 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0508 loss: 2.0508 2022/09/07 20:45:42 - mmengine - INFO - Epoch(train) [30][1320/1793] lr: 7.5000e-03 eta: 3:15:10 time: 0.1880 data_time: 0.0088 memory: 10464 grad_norm: 7.1793 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.1719 loss: 2.1719 2022/09/07 20:45:46 - mmengine - INFO - Epoch(train) [30][1340/1793] lr: 7.5000e-03 eta: 3:15:02 time: 0.1760 data_time: 0.0091 memory: 10464 grad_norm: 7.6360 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.1446 loss: 2.1446 2022/09/07 20:45:49 - mmengine - INFO - Epoch(train) [30][1360/1793] lr: 7.5000e-03 eta: 3:14:53 time: 0.1770 data_time: 0.0058 memory: 10464 grad_norm: 7.3249 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7876 loss: 1.7876 2022/09/07 20:45:53 - mmengine - INFO - Epoch(train) [30][1380/1793] lr: 7.5000e-03 eta: 3:14:45 time: 0.1704 data_time: 0.0064 memory: 10464 grad_norm: 7.2967 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.9620 loss: 1.9620 2022/09/07 20:45:56 - mmengine - INFO - Epoch(train) [30][1400/1793] lr: 7.5000e-03 eta: 3:14:36 time: 0.1755 data_time: 0.0101 memory: 10464 grad_norm: 7.1217 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2764 loss: 2.2764 2022/09/07 20:46:00 - mmengine - INFO - Epoch(train) [30][1420/1793] lr: 7.5000e-03 eta: 3:14:29 time: 0.2132 data_time: 0.0082 memory: 10464 grad_norm: 8.2341 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.0203 loss: 2.0203 2022/09/07 20:46:04 - mmengine - INFO - Epoch(train) [30][1440/1793] lr: 7.5000e-03 eta: 3:14:20 time: 0.1754 data_time: 0.0060 memory: 10464 grad_norm: 7.2045 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1833 loss: 2.1833 2022/09/07 20:46:08 - mmengine - INFO - Epoch(train) [30][1460/1793] lr: 7.5000e-03 eta: 3:14:12 time: 0.1781 data_time: 0.0103 memory: 10464 grad_norm: 7.3766 top1_acc: 0.0000 top5_acc: 0.8333 loss_cls: 2.1660 loss: 2.1660 2022/09/07 20:46:11 - mmengine - INFO - Epoch(train) [30][1480/1793] lr: 7.5000e-03 eta: 3:14:03 time: 0.1721 data_time: 0.0061 memory: 10464 grad_norm: 7.3611 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9949 loss: 1.9949 2022/09/07 20:46:14 - mmengine - INFO - Epoch(train) [30][1500/1793] lr: 7.5000e-03 eta: 3:13:55 time: 0.1724 data_time: 0.0071 memory: 10464 grad_norm: 7.3038 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1218 loss: 2.1218 2022/09/07 20:46:18 - mmengine - INFO - Epoch(train) [30][1520/1793] lr: 7.5000e-03 eta: 3:13:46 time: 0.1739 data_time: 0.0086 memory: 10464 grad_norm: 7.5301 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4870 loss: 2.4870 2022/09/07 20:46:22 - mmengine - INFO - Epoch(train) [30][1540/1793] lr: 7.5000e-03 eta: 3:13:38 time: 0.1778 data_time: 0.0070 memory: 10464 grad_norm: 7.4740 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.9909 loss: 1.9909 2022/09/07 20:46:25 - mmengine - INFO - Epoch(train) [30][1560/1793] lr: 7.5000e-03 eta: 3:13:30 time: 0.1721 data_time: 0.0066 memory: 10464 grad_norm: 7.5239 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.1100 loss: 2.1100 2022/09/07 20:46:28 - mmengine - INFO - Epoch(train) [30][1580/1793] lr: 7.5000e-03 eta: 3:13:21 time: 0.1751 data_time: 0.0093 memory: 10464 grad_norm: 7.3701 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2418 loss: 2.2418 2022/09/07 20:46:32 - mmengine - INFO - Epoch(train) [30][1600/1793] lr: 7.5000e-03 eta: 3:13:13 time: 0.1716 data_time: 0.0063 memory: 10464 grad_norm: 7.3330 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2075 loss: 2.2075 2022/09/07 20:46:35 - mmengine - INFO - Epoch(train) [30][1620/1793] lr: 7.5000e-03 eta: 3:13:04 time: 0.1729 data_time: 0.0063 memory: 10464 grad_norm: 7.6555 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2422 loss: 2.2422 2022/09/07 20:46:39 - mmengine - INFO - Epoch(train) [30][1640/1793] lr: 7.5000e-03 eta: 3:12:56 time: 0.1743 data_time: 0.0091 memory: 10464 grad_norm: 7.2744 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.0463 loss: 2.0463 2022/09/07 20:46:42 - mmengine - INFO - Epoch(train) [30][1660/1793] lr: 7.5000e-03 eta: 3:12:47 time: 0.1779 data_time: 0.0070 memory: 10464 grad_norm: 7.3124 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9560 loss: 1.9560 2022/09/07 20:46:46 - mmengine - INFO - Epoch(train) [30][1680/1793] lr: 7.5000e-03 eta: 3:12:39 time: 0.1722 data_time: 0.0065 memory: 10464 grad_norm: 7.4050 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.9419 loss: 1.9419 2022/09/07 20:46:50 - mmengine - INFO - Epoch(train) [30][1700/1793] lr: 7.5000e-03 eta: 3:12:31 time: 0.1832 data_time: 0.0084 memory: 10464 grad_norm: 7.0769 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.1888 loss: 2.1888 2022/09/07 20:46:53 - mmengine - INFO - Epoch(train) [30][1720/1793] lr: 7.5000e-03 eta: 3:12:22 time: 0.1754 data_time: 0.0066 memory: 10464 grad_norm: 7.3393 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.8078 loss: 1.8078 2022/09/07 20:46:56 - mmengine - INFO - Epoch(train) [30][1740/1793] lr: 7.5000e-03 eta: 3:12:14 time: 0.1715 data_time: 0.0063 memory: 10464 grad_norm: 7.5415 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.0336 loss: 2.0336 2022/09/07 20:47:00 - mmengine - INFO - Epoch(train) [30][1760/1793] lr: 7.5000e-03 eta: 3:12:06 time: 0.1967 data_time: 0.0119 memory: 10464 grad_norm: 7.2388 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.9408 loss: 1.9408 2022/09/07 20:47:04 - mmengine - INFO - Epoch(train) [30][1780/1793] lr: 7.5000e-03 eta: 3:11:57 time: 0.1721 data_time: 0.0067 memory: 10464 grad_norm: 7.4988 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2290 loss: 2.2290 2022/09/07 20:47:06 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:47:06 - mmengine - INFO - Epoch(train) [30][1793/1793] lr: 7.5000e-03 eta: 3:11:57 time: 0.1690 data_time: 0.0059 memory: 10464 grad_norm: 9.1660 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.3302 loss: 2.3302 2022/09/07 20:47:06 - mmengine - INFO - Saving checkpoint at 30 epochs 2022/09/07 20:47:10 - mmengine - INFO - Epoch(val) [30][20/241] eta: 0:00:12 time: 0.0586 data_time: 0.0091 memory: 1482 2022/09/07 20:47:11 - mmengine - INFO - Epoch(val) [30][40/241] eta: 0:00:10 time: 0.0534 data_time: 0.0049 memory: 1482 2022/09/07 20:47:12 - mmengine - INFO - Epoch(val) [30][60/241] eta: 0:00:09 time: 0.0538 data_time: 0.0052 memory: 1482 2022/09/07 20:47:13 - mmengine - INFO - Epoch(val) [30][80/241] eta: 0:00:08 time: 0.0538 data_time: 0.0051 memory: 1482 2022/09/07 20:47:14 - mmengine - INFO - Epoch(val) [30][100/241] eta: 0:00:07 time: 0.0531 data_time: 0.0048 memory: 1482 2022/09/07 20:47:15 - mmengine - INFO - Epoch(val) [30][120/241] eta: 0:00:06 time: 0.0534 data_time: 0.0049 memory: 1482 2022/09/07 20:47:17 - mmengine - INFO - Epoch(val) [30][140/241] eta: 0:00:05 time: 0.0535 data_time: 0.0049 memory: 1482 2022/09/07 20:47:18 - mmengine - INFO - Epoch(val) [30][160/241] eta: 0:00:04 time: 0.0533 data_time: 0.0048 memory: 1482 2022/09/07 20:47:19 - mmengine - INFO - Epoch(val) [30][180/241] eta: 0:00:03 time: 0.0527 data_time: 0.0046 memory: 1482 2022/09/07 20:47:20 - mmengine - INFO - Epoch(val) [30][200/241] eta: 0:00:02 time: 0.0610 data_time: 0.0059 memory: 1482 2022/09/07 20:47:21 - mmengine - INFO - Epoch(val) [30][220/241] eta: 0:00:01 time: 0.0530 data_time: 0.0050 memory: 1482 2022/09/07 20:47:22 - mmengine - INFO - Epoch(val) [30][240/241] eta: 0:00:00 time: 0.0518 data_time: 0.0040 memory: 1482 2022/09/07 20:47:23 - mmengine - INFO - Epoch(val) [30][241/241] acc/top1: 0.3495 acc/top5: 0.6541 acc/mean1: 0.3168 2022/09/07 20:47:27 - mmengine - INFO - Epoch(train) [31][20/1793] lr: 7.5000e-04 eta: 3:11:42 time: 0.1935 data_time: 0.0121 memory: 10464 grad_norm: 7.5274 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.0179 loss: 2.0179 2022/09/07 20:47:30 - mmengine - INFO - Epoch(train) [31][40/1793] lr: 7.5000e-04 eta: 3:11:34 time: 0.1710 data_time: 0.0064 memory: 10464 grad_norm: 6.9868 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.7184 loss: 1.7184 2022/09/07 20:47:34 - mmengine - INFO - Epoch(train) [31][60/1793] lr: 7.5000e-04 eta: 3:11:26 time: 0.1780 data_time: 0.0072 memory: 10464 grad_norm: 6.7101 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.1197 loss: 2.1197 2022/09/07 20:47:37 - mmengine - INFO - Epoch(train) [31][80/1793] lr: 7.5000e-04 eta: 3:11:17 time: 0.1766 data_time: 0.0093 memory: 10464 grad_norm: 6.8326 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0477 loss: 2.0477 2022/09/07 20:47:41 - mmengine - INFO - Epoch(train) [31][100/1793] lr: 7.5000e-04 eta: 3:11:09 time: 0.1924 data_time: 0.0070 memory: 10464 grad_norm: 7.0324 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.8804 loss: 1.8804 2022/09/07 20:47:44 - mmengine - INFO - Epoch(train) [31][120/1793] lr: 7.5000e-04 eta: 3:11:01 time: 0.1721 data_time: 0.0067 memory: 10464 grad_norm: 6.9366 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.6202 loss: 1.6202 2022/09/07 20:47:48 - mmengine - INFO - Epoch(train) [31][140/1793] lr: 7.5000e-04 eta: 3:10:53 time: 0.1794 data_time: 0.0086 memory: 10464 grad_norm: 6.7666 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.5233 loss: 1.5233 2022/09/07 20:47:51 - mmengine - INFO - Epoch(train) [31][160/1793] lr: 7.5000e-04 eta: 3:10:44 time: 0.1726 data_time: 0.0063 memory: 10464 grad_norm: 6.7465 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.0127 loss: 2.0127 2022/09/07 20:47:55 - mmengine - INFO - Epoch(train) [31][180/1793] lr: 7.5000e-04 eta: 3:10:36 time: 0.1772 data_time: 0.0065 memory: 10464 grad_norm: 6.6692 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.9240 loss: 1.9240 2022/09/07 20:47:58 - mmengine - INFO - Epoch(train) [31][200/1793] lr: 7.5000e-04 eta: 3:10:28 time: 0.1760 data_time: 0.0083 memory: 10464 grad_norm: 6.6765 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.6486 loss: 1.6486 2022/09/07 20:48:00 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:48:02 - mmengine - INFO - Epoch(train) [31][220/1793] lr: 7.5000e-04 eta: 3:10:19 time: 0.1752 data_time: 0.0082 memory: 10464 grad_norm: 6.5407 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4973 loss: 1.4973 2022/09/07 20:48:05 - mmengine - INFO - Epoch(train) [31][240/1793] lr: 7.5000e-04 eta: 3:10:11 time: 0.1716 data_time: 0.0062 memory: 10464 grad_norm: 6.9919 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6614 loss: 1.6614 2022/09/07 20:48:09 - mmengine - INFO - Epoch(train) [31][260/1793] lr: 7.5000e-04 eta: 3:10:03 time: 0.1757 data_time: 0.0084 memory: 10464 grad_norm: 6.6828 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.8318 loss: 1.8318 2022/09/07 20:48:12 - mmengine - INFO - Epoch(train) [31][280/1793] lr: 7.5000e-04 eta: 3:09:54 time: 0.1713 data_time: 0.0061 memory: 10464 grad_norm: 6.8458 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.5154 loss: 1.5154 2022/09/07 20:48:16 - mmengine - INFO - Epoch(train) [31][300/1793] lr: 7.5000e-04 eta: 3:09:46 time: 0.1784 data_time: 0.0063 memory: 10464 grad_norm: 6.8523 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.6666 loss: 1.6666 2022/09/07 20:48:20 - mmengine - INFO - Epoch(train) [31][320/1793] lr: 7.5000e-04 eta: 3:09:38 time: 0.1993 data_time: 0.0091 memory: 10464 grad_norm: 6.8213 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7579 loss: 1.7579 2022/09/07 20:48:23 - mmengine - INFO - Epoch(train) [31][340/1793] lr: 7.5000e-04 eta: 3:09:30 time: 0.1755 data_time: 0.0066 memory: 10464 grad_norm: 6.6991 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.8015 loss: 1.8015 2022/09/07 20:48:27 - mmengine - INFO - Epoch(train) [31][360/1793] lr: 7.5000e-04 eta: 3:09:21 time: 0.1766 data_time: 0.0064 memory: 10464 grad_norm: 7.1157 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7081 loss: 1.7081 2022/09/07 20:48:30 - mmengine - INFO - Epoch(train) [31][380/1793] lr: 7.5000e-04 eta: 3:09:13 time: 0.1739 data_time: 0.0085 memory: 10464 grad_norm: 6.8341 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.5456 loss: 1.5456 2022/09/07 20:48:34 - mmengine - INFO - Epoch(train) [31][400/1793] lr: 7.5000e-04 eta: 3:09:05 time: 0.1705 data_time: 0.0061 memory: 10464 grad_norm: 6.8421 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5771 loss: 1.5771 2022/09/07 20:48:38 - mmengine - INFO - Epoch(train) [31][420/1793] lr: 7.5000e-04 eta: 3:08:56 time: 0.1850 data_time: 0.0070 memory: 10464 grad_norm: 7.0007 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.8056 loss: 1.8056 2022/09/07 20:48:41 - mmengine - INFO - Epoch(train) [31][440/1793] lr: 7.5000e-04 eta: 3:08:48 time: 0.1779 data_time: 0.0083 memory: 10464 grad_norm: 6.8857 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5514 loss: 1.5514 2022/09/07 20:48:45 - mmengine - INFO - Epoch(train) [31][460/1793] lr: 7.5000e-04 eta: 3:08:40 time: 0.1863 data_time: 0.0067 memory: 10464 grad_norm: 6.8831 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7623 loss: 1.7623 2022/09/07 20:48:48 - mmengine - INFO - Epoch(train) [31][480/1793] lr: 7.5000e-04 eta: 3:08:32 time: 0.1709 data_time: 0.0058 memory: 10464 grad_norm: 7.0960 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.4437 loss: 1.4437 2022/09/07 20:48:52 - mmengine - INFO - Epoch(train) [31][500/1793] lr: 7.5000e-04 eta: 3:08:24 time: 0.1816 data_time: 0.0085 memory: 10464 grad_norm: 7.1873 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.5140 loss: 1.5140 2022/09/07 20:48:55 - mmengine - INFO - Epoch(train) [31][520/1793] lr: 7.5000e-04 eta: 3:08:15 time: 0.1723 data_time: 0.0070 memory: 10464 grad_norm: 6.9805 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.5848 loss: 1.5848 2022/09/07 20:48:59 - mmengine - INFO - Epoch(train) [31][540/1793] lr: 7.5000e-04 eta: 3:08:07 time: 0.1763 data_time: 0.0062 memory: 10464 grad_norm: 6.9069 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.9411 loss: 1.9411 2022/09/07 20:49:02 - mmengine - INFO - Epoch(train) [31][560/1793] lr: 7.5000e-04 eta: 3:07:59 time: 0.1781 data_time: 0.0096 memory: 10464 grad_norm: 7.0887 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.6781 loss: 1.6781 2022/09/07 20:49:06 - mmengine - INFO - Epoch(train) [31][580/1793] lr: 7.5000e-04 eta: 3:07:50 time: 0.1716 data_time: 0.0066 memory: 10464 grad_norm: 6.8061 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.7897 loss: 1.7897 2022/09/07 20:49:09 - mmengine - INFO - Epoch(train) [31][600/1793] lr: 7.5000e-04 eta: 3:07:42 time: 0.1744 data_time: 0.0064 memory: 10464 grad_norm: 6.9857 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.7292 loss: 1.7292 2022/09/07 20:49:13 - mmengine - INFO - Epoch(train) [31][620/1793] lr: 7.5000e-04 eta: 3:07:34 time: 0.1745 data_time: 0.0092 memory: 10464 grad_norm: 7.1143 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6838 loss: 1.6838 2022/09/07 20:49:16 - mmengine - INFO - Epoch(train) [31][640/1793] lr: 7.5000e-04 eta: 3:07:26 time: 0.1727 data_time: 0.0061 memory: 10464 grad_norm: 6.9538 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.4942 loss: 1.4942 2022/09/07 20:49:20 - mmengine - INFO - Epoch(train) [31][660/1793] lr: 7.5000e-04 eta: 3:07:18 time: 0.1888 data_time: 0.0073 memory: 10464 grad_norm: 6.9585 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6864 loss: 1.6864 2022/09/07 20:49:24 - mmengine - INFO - Epoch(train) [31][680/1793] lr: 7.5000e-04 eta: 3:07:09 time: 0.1790 data_time: 0.0105 memory: 10464 grad_norm: 7.0054 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6311 loss: 1.6311 2022/09/07 20:49:27 - mmengine - INFO - Epoch(train) [31][700/1793] lr: 7.5000e-04 eta: 3:07:01 time: 0.1708 data_time: 0.0062 memory: 10464 grad_norm: 7.0815 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3217 loss: 1.3217 2022/09/07 20:49:31 - mmengine - INFO - Epoch(train) [31][720/1793] lr: 7.5000e-04 eta: 3:06:53 time: 0.1703 data_time: 0.0048 memory: 10464 grad_norm: 6.9069 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3605 loss: 1.3605 2022/09/07 20:49:34 - mmengine - INFO - Epoch(train) [31][740/1793] lr: 7.5000e-04 eta: 3:06:45 time: 0.1769 data_time: 0.0090 memory: 10464 grad_norm: 7.0202 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.9549 loss: 1.9549 2022/09/07 20:49:38 - mmengine - INFO - Epoch(train) [31][760/1793] lr: 7.5000e-04 eta: 3:06:36 time: 0.1827 data_time: 0.0068 memory: 10464 grad_norm: 6.8344 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.5212 loss: 1.5212 2022/09/07 20:49:41 - mmengine - INFO - Epoch(train) [31][780/1793] lr: 7.5000e-04 eta: 3:06:28 time: 0.1820 data_time: 0.0084 memory: 10464 grad_norm: 7.0636 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6775 loss: 1.6775 2022/09/07 20:49:45 - mmengine - INFO - Epoch(train) [31][800/1793] lr: 7.5000e-04 eta: 3:06:20 time: 0.1739 data_time: 0.0094 memory: 10464 grad_norm: 7.0545 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5824 loss: 1.5824 2022/09/07 20:49:48 - mmengine - INFO - Epoch(train) [31][820/1793] lr: 7.5000e-04 eta: 3:06:12 time: 0.1716 data_time: 0.0062 memory: 10464 grad_norm: 7.1396 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.8803 loss: 1.8803 2022/09/07 20:49:52 - mmengine - INFO - Epoch(train) [31][840/1793] lr: 7.5000e-04 eta: 3:06:03 time: 0.1727 data_time: 0.0064 memory: 10464 grad_norm: 6.9155 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.4332 loss: 1.4332 2022/09/07 20:49:55 - mmengine - INFO - Epoch(train) [31][860/1793] lr: 7.5000e-04 eta: 3:05:55 time: 0.1742 data_time: 0.0083 memory: 10464 grad_norm: 6.9519 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.5420 loss: 1.5420 2022/09/07 20:49:59 - mmengine - INFO - Epoch(train) [31][880/1793] lr: 7.5000e-04 eta: 3:05:47 time: 0.1880 data_time: 0.0065 memory: 10464 grad_norm: 7.0438 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5185 loss: 1.5185 2022/09/07 20:50:03 - mmengine - INFO - Epoch(train) [31][900/1793] lr: 7.5000e-04 eta: 3:05:39 time: 0.2113 data_time: 0.0077 memory: 10464 grad_norm: 7.1395 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.6012 loss: 1.6012 2022/09/07 20:50:07 - mmengine - INFO - Epoch(train) [31][920/1793] lr: 7.5000e-04 eta: 3:05:31 time: 0.1765 data_time: 0.0088 memory: 10464 grad_norm: 7.0941 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6901 loss: 1.6901 2022/09/07 20:50:10 - mmengine - INFO - Epoch(train) [31][940/1793] lr: 7.5000e-04 eta: 3:05:23 time: 0.1701 data_time: 0.0063 memory: 10464 grad_norm: 7.3350 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.6276 loss: 1.6276 2022/09/07 20:50:14 - mmengine - INFO - Epoch(train) [31][960/1793] lr: 7.5000e-04 eta: 3:05:15 time: 0.1720 data_time: 0.0064 memory: 10464 grad_norm: 7.1869 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7367 loss: 1.7367 2022/09/07 20:50:17 - mmengine - INFO - Epoch(train) [31][980/1793] lr: 7.5000e-04 eta: 3:05:07 time: 0.1861 data_time: 0.0084 memory: 10464 grad_norm: 7.1460 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6232 loss: 1.6232 2022/09/07 20:50:21 - mmengine - INFO - Epoch(train) [31][1000/1793] lr: 7.5000e-04 eta: 3:04:59 time: 0.1846 data_time: 0.0072 memory: 10464 grad_norm: 7.0544 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6696 loss: 1.6696 2022/09/07 20:50:25 - mmengine - INFO - Epoch(train) [31][1020/1793] lr: 7.5000e-04 eta: 3:04:50 time: 0.1746 data_time: 0.0076 memory: 10464 grad_norm: 7.0581 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6995 loss: 1.6995 2022/09/07 20:50:28 - mmengine - INFO - Epoch(train) [31][1040/1793] lr: 7.5000e-04 eta: 3:04:42 time: 0.1720 data_time: 0.0069 memory: 10464 grad_norm: 6.8552 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.4832 loss: 1.4832 2022/09/07 20:50:31 - mmengine - INFO - Epoch(train) [31][1060/1793] lr: 7.5000e-04 eta: 3:04:34 time: 0.1729 data_time: 0.0062 memory: 10464 grad_norm: 6.9266 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6250 loss: 1.6250 2022/09/07 20:50:35 - mmengine - INFO - Epoch(train) [31][1080/1793] lr: 7.5000e-04 eta: 3:04:26 time: 0.1715 data_time: 0.0060 memory: 10464 grad_norm: 7.4012 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.7297 loss: 1.7297 2022/09/07 20:50:39 - mmengine - INFO - Epoch(train) [31][1100/1793] lr: 7.5000e-04 eta: 3:04:18 time: 0.1905 data_time: 0.0086 memory: 10464 grad_norm: 7.3966 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.8210 loss: 1.8210 2022/09/07 20:50:42 - mmengine - INFO - Epoch(train) [31][1120/1793] lr: 7.5000e-04 eta: 3:04:10 time: 0.1818 data_time: 0.0085 memory: 10464 grad_norm: 7.1891 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4092 loss: 1.4092 2022/09/07 20:50:46 - mmengine - INFO - Epoch(train) [31][1140/1793] lr: 7.5000e-04 eta: 3:04:02 time: 0.1723 data_time: 0.0051 memory: 10464 grad_norm: 7.2605 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5930 loss: 1.5930 2022/09/07 20:50:49 - mmengine - INFO - Epoch(train) [31][1160/1793] lr: 7.5000e-04 eta: 3:03:53 time: 0.1756 data_time: 0.0088 memory: 10464 grad_norm: 7.2608 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4529 loss: 1.4529 2022/09/07 20:50:53 - mmengine - INFO - Epoch(train) [31][1180/1793] lr: 7.5000e-04 eta: 3:03:45 time: 0.1701 data_time: 0.0063 memory: 10464 grad_norm: 7.2493 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8452 loss: 1.8452 2022/09/07 20:50:56 - mmengine - INFO - Epoch(train) [31][1200/1793] lr: 7.5000e-04 eta: 3:03:37 time: 0.1721 data_time: 0.0061 memory: 10464 grad_norm: 7.0432 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2248 loss: 1.2248 2022/09/07 20:50:58 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:51:01 - mmengine - INFO - Epoch(train) [31][1220/1793] lr: 7.5000e-04 eta: 3:03:29 time: 0.2218 data_time: 0.0094 memory: 10464 grad_norm: 7.2096 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.3660 loss: 1.3660 2022/09/07 20:51:04 - mmengine - INFO - Epoch(train) [31][1240/1793] lr: 7.5000e-04 eta: 3:03:21 time: 0.1772 data_time: 0.0076 memory: 10464 grad_norm: 7.2495 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.6142 loss: 1.6142 2022/09/07 20:51:08 - mmengine - INFO - Epoch(train) [31][1260/1793] lr: 7.5000e-04 eta: 3:03:13 time: 0.1799 data_time: 0.0060 memory: 10464 grad_norm: 6.9013 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6075 loss: 1.6075 2022/09/07 20:51:11 - mmengine - INFO - Epoch(train) [31][1280/1793] lr: 7.5000e-04 eta: 3:03:05 time: 0.1788 data_time: 0.0096 memory: 10464 grad_norm: 7.2775 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.5069 loss: 1.5069 2022/09/07 20:51:15 - mmengine - INFO - Epoch(train) [31][1300/1793] lr: 7.5000e-04 eta: 3:02:57 time: 0.1724 data_time: 0.0061 memory: 10464 grad_norm: 7.4055 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5289 loss: 1.5289 2022/09/07 20:51:18 - mmengine - INFO - Epoch(train) [31][1320/1793] lr: 7.5000e-04 eta: 3:02:49 time: 0.1752 data_time: 0.0064 memory: 10464 grad_norm: 7.4424 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6026 loss: 1.6026 2022/09/07 20:51:22 - mmengine - INFO - Epoch(train) [31][1340/1793] lr: 7.5000e-04 eta: 3:02:41 time: 0.1840 data_time: 0.0115 memory: 10464 grad_norm: 7.0582 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7715 loss: 1.7715 2022/09/07 20:51:25 - mmengine - INFO - Epoch(train) [31][1360/1793] lr: 7.5000e-04 eta: 3:02:33 time: 0.1713 data_time: 0.0061 memory: 10464 grad_norm: 7.3109 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.6737 loss: 1.6737 2022/09/07 20:51:29 - mmengine - INFO - Epoch(train) [31][1380/1793] lr: 7.5000e-04 eta: 3:02:24 time: 0.1708 data_time: 0.0061 memory: 10464 grad_norm: 6.8457 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5084 loss: 1.5084 2022/09/07 20:51:32 - mmengine - INFO - Epoch(train) [31][1400/1793] lr: 7.5000e-04 eta: 3:02:16 time: 0.1838 data_time: 0.0124 memory: 10464 grad_norm: 7.1733 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4684 loss: 1.4684 2022/09/07 20:51:36 - mmengine - INFO - Epoch(train) [31][1420/1793] lr: 7.5000e-04 eta: 3:02:08 time: 0.1733 data_time: 0.0064 memory: 10464 grad_norm: 7.0345 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.8618 loss: 1.8618 2022/09/07 20:51:40 - mmengine - INFO - Epoch(train) [31][1440/1793] lr: 7.5000e-04 eta: 3:02:00 time: 0.1782 data_time: 0.0060 memory: 10464 grad_norm: 7.0793 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.7649 loss: 1.7649 2022/09/07 20:51:43 - mmengine - INFO - Epoch(train) [31][1460/1793] lr: 7.5000e-04 eta: 3:01:52 time: 0.1845 data_time: 0.0103 memory: 10464 grad_norm: 7.0246 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.8337 loss: 1.8337 2022/09/07 20:51:47 - mmengine - INFO - Epoch(train) [31][1480/1793] lr: 7.5000e-04 eta: 3:01:44 time: 0.1725 data_time: 0.0061 memory: 10464 grad_norm: 7.2531 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.8139 loss: 1.8139 2022/09/07 20:51:50 - mmengine - INFO - Epoch(train) [31][1500/1793] lr: 7.5000e-04 eta: 3:01:36 time: 0.1749 data_time: 0.0070 memory: 10464 grad_norm: 6.9256 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4259 loss: 1.4259 2022/09/07 20:51:54 - mmengine - INFO - Epoch(train) [31][1520/1793] lr: 7.5000e-04 eta: 3:01:28 time: 0.1746 data_time: 0.0089 memory: 10464 grad_norm: 7.1380 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.5142 loss: 1.5142 2022/09/07 20:51:57 - mmengine - INFO - Epoch(train) [31][1540/1793] lr: 7.5000e-04 eta: 3:01:20 time: 0.1768 data_time: 0.0062 memory: 10464 grad_norm: 7.0750 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4602 loss: 1.4602 2022/09/07 20:52:01 - mmengine - INFO - Epoch(train) [31][1560/1793] lr: 7.5000e-04 eta: 3:01:12 time: 0.1817 data_time: 0.0072 memory: 10464 grad_norm: 7.0093 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.6415 loss: 1.6415 2022/09/07 20:52:04 - mmengine - INFO - Epoch(train) [31][1580/1793] lr: 7.5000e-04 eta: 3:01:04 time: 0.1772 data_time: 0.0095 memory: 10464 grad_norm: 7.2578 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.5554 loss: 1.5554 2022/09/07 20:52:08 - mmengine - INFO - Epoch(train) [31][1600/1793] lr: 7.5000e-04 eta: 3:00:55 time: 0.1716 data_time: 0.0061 memory: 10464 grad_norm: 7.2636 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.6052 loss: 1.6052 2022/09/07 20:52:11 - mmengine - INFO - Epoch(train) [31][1620/1793] lr: 7.5000e-04 eta: 3:00:47 time: 0.1722 data_time: 0.0068 memory: 10464 grad_norm: 7.1614 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4158 loss: 1.4158 2022/09/07 20:52:15 - mmengine - INFO - Epoch(train) [31][1640/1793] lr: 7.5000e-04 eta: 3:00:39 time: 0.1767 data_time: 0.0100 memory: 10464 grad_norm: 7.1642 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.6172 loss: 1.6172 2022/09/07 20:52:19 - mmengine - INFO - Epoch(train) [31][1660/1793] lr: 7.5000e-04 eta: 3:00:31 time: 0.1984 data_time: 0.0064 memory: 10464 grad_norm: 7.5004 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6308 loss: 1.6308 2022/09/07 20:52:22 - mmengine - INFO - Epoch(train) [31][1680/1793] lr: 7.5000e-04 eta: 3:00:23 time: 0.1844 data_time: 0.0072 memory: 10464 grad_norm: 7.3146 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5587 loss: 1.5587 2022/09/07 20:52:26 - mmengine - INFO - Epoch(train) [31][1700/1793] lr: 7.5000e-04 eta: 3:00:15 time: 0.1761 data_time: 0.0084 memory: 10464 grad_norm: 7.0367 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.3680 loss: 1.3680 2022/09/07 20:52:29 - mmengine - INFO - Epoch(train) [31][1720/1793] lr: 7.5000e-04 eta: 3:00:07 time: 0.1711 data_time: 0.0062 memory: 10464 grad_norm: 7.4020 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7177 loss: 1.7177 2022/09/07 20:52:33 - mmengine - INFO - Epoch(train) [31][1740/1793] lr: 7.5000e-04 eta: 2:59:59 time: 0.1715 data_time: 0.0068 memory: 10464 grad_norm: 7.1545 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5874 loss: 1.5874 2022/09/07 20:52:36 - mmengine - INFO - Epoch(train) [31][1760/1793] lr: 7.5000e-04 eta: 2:59:51 time: 0.1753 data_time: 0.0089 memory: 10464 grad_norm: 7.2692 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.7421 loss: 1.7421 2022/09/07 20:52:40 - mmengine - INFO - Epoch(train) [31][1780/1793] lr: 7.5000e-04 eta: 2:59:43 time: 0.1775 data_time: 0.0059 memory: 10464 grad_norm: 6.8193 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4150 loss: 1.4150 2022/09/07 20:52:42 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:52:42 - mmengine - INFO - Epoch(train) [31][1793/1793] lr: 7.5000e-04 eta: 2:59:43 time: 0.1731 data_time: 0.0064 memory: 10464 grad_norm: 7.0381 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5626 loss: 1.5626 2022/09/07 20:52:42 - mmengine - INFO - Saving checkpoint at 31 epochs 2022/09/07 20:52:46 - mmengine - INFO - Epoch(val) [31][20/241] eta: 0:00:13 time: 0.0607 data_time: 0.0113 memory: 1482 2022/09/07 20:52:47 - mmengine - INFO - Epoch(val) [31][40/241] eta: 0:00:10 time: 0.0532 data_time: 0.0047 memory: 1482 2022/09/07 20:52:48 - mmengine - INFO - Epoch(val) [31][60/241] eta: 0:00:09 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 20:52:49 - mmengine - INFO - Epoch(val) [31][80/241] eta: 0:00:08 time: 0.0532 data_time: 0.0047 memory: 1482 2022/09/07 20:52:50 - mmengine - INFO - Epoch(val) [31][100/241] eta: 0:00:07 time: 0.0530 data_time: 0.0047 memory: 1482 2022/09/07 20:52:51 - mmengine - INFO - Epoch(val) [31][120/241] eta: 0:00:06 time: 0.0530 data_time: 0.0047 memory: 1482 2022/09/07 20:52:52 - mmengine - INFO - Epoch(val) [31][140/241] eta: 0:00:05 time: 0.0531 data_time: 0.0047 memory: 1482 2022/09/07 20:52:53 - mmengine - INFO - Epoch(val) [31][160/241] eta: 0:00:04 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 20:52:54 - mmengine - INFO - Epoch(val) [31][180/241] eta: 0:00:03 time: 0.0530 data_time: 0.0047 memory: 1482 2022/09/07 20:52:55 - mmengine - INFO - Epoch(val) [31][200/241] eta: 0:00:02 time: 0.0525 data_time: 0.0045 memory: 1482 2022/09/07 20:52:56 - mmengine - INFO - Epoch(val) [31][220/241] eta: 0:00:01 time: 0.0531 data_time: 0.0049 memory: 1482 2022/09/07 20:52:57 - mmengine - INFO - Epoch(val) [31][240/241] eta: 0:00:00 time: 0.0527 data_time: 0.0048 memory: 1482 2022/09/07 20:52:58 - mmengine - INFO - Epoch(val) [31][241/241] acc/top1: 0.4357 acc/top5: 0.7424 acc/mean1: 0.4016 2022/09/07 20:52:58 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_25.pth is removed 2022/09/07 20:53:00 - mmengine - INFO - The best checkpoint with 0.4357 acc/top1 at 31 epoch is saved to best_acc/top1_epoch_31.pth. 2022/09/07 20:53:03 - mmengine - INFO - Epoch(train) [32][20/1793] lr: 7.5000e-04 eta: 2:59:28 time: 0.1788 data_time: 0.0101 memory: 10464 grad_norm: 7.1586 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.7367 loss: 1.7367 2022/09/07 20:53:07 - mmengine - INFO - Epoch(train) [32][40/1793] lr: 7.5000e-04 eta: 2:59:20 time: 0.1719 data_time: 0.0062 memory: 10464 grad_norm: 7.5290 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.6922 loss: 1.6922 2022/09/07 20:53:10 - mmengine - INFO - Epoch(train) [32][60/1793] lr: 7.5000e-04 eta: 2:59:12 time: 0.1757 data_time: 0.0072 memory: 10464 grad_norm: 7.1921 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.6968 loss: 1.6968 2022/09/07 20:53:14 - mmengine - INFO - Epoch(train) [32][80/1793] lr: 7.5000e-04 eta: 2:59:04 time: 0.1746 data_time: 0.0092 memory: 10464 grad_norm: 6.9968 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3732 loss: 1.3732 2022/09/07 20:53:17 - mmengine - INFO - Epoch(train) [32][100/1793] lr: 7.5000e-04 eta: 2:58:56 time: 0.1713 data_time: 0.0062 memory: 10464 grad_norm: 7.2881 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4003 loss: 1.4003 2022/09/07 20:53:21 - mmengine - INFO - Epoch(train) [32][120/1793] lr: 7.5000e-04 eta: 2:58:48 time: 0.1929 data_time: 0.0067 memory: 10464 grad_norm: 7.4041 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4325 loss: 1.4325 2022/09/07 20:53:24 - mmengine - INFO - Epoch(train) [32][140/1793] lr: 7.5000e-04 eta: 2:58:40 time: 0.1734 data_time: 0.0091 memory: 10464 grad_norm: 7.3257 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 1.4453 loss: 1.4453 2022/09/07 20:53:28 - mmengine - INFO - Epoch(train) [32][160/1793] lr: 7.5000e-04 eta: 2:58:32 time: 0.1736 data_time: 0.0067 memory: 10464 grad_norm: 7.2203 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2632 loss: 1.2632 2022/09/07 20:53:31 - mmengine - INFO - Epoch(train) [32][180/1793] lr: 7.5000e-04 eta: 2:58:24 time: 0.1777 data_time: 0.0065 memory: 10464 grad_norm: 7.1701 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1560 loss: 1.1560 2022/09/07 20:53:35 - mmengine - INFO - Epoch(train) [32][200/1793] lr: 7.5000e-04 eta: 2:58:16 time: 0.1736 data_time: 0.0081 memory: 10464 grad_norm: 7.3300 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4740 loss: 1.4740 2022/09/07 20:53:38 - mmengine - INFO - Epoch(train) [32][220/1793] lr: 7.5000e-04 eta: 2:58:08 time: 0.1747 data_time: 0.0063 memory: 10464 grad_norm: 7.3634 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.3945 loss: 1.3945 2022/09/07 20:53:42 - mmengine - INFO - Epoch(train) [32][240/1793] lr: 7.5000e-04 eta: 2:58:00 time: 0.1754 data_time: 0.0064 memory: 10464 grad_norm: 7.1800 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4247 loss: 1.4247 2022/09/07 20:53:45 - mmengine - INFO - Epoch(train) [32][260/1793] lr: 7.5000e-04 eta: 2:57:52 time: 0.1755 data_time: 0.0092 memory: 10464 grad_norm: 7.2567 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5425 loss: 1.5425 2022/09/07 20:53:49 - mmengine - INFO - Epoch(train) [32][280/1793] lr: 7.5000e-04 eta: 2:57:44 time: 0.1735 data_time: 0.0061 memory: 10464 grad_norm: 7.2394 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3956 loss: 1.3956 2022/09/07 20:53:52 - mmengine - INFO - Epoch(train) [32][300/1793] lr: 7.5000e-04 eta: 2:57:36 time: 0.1764 data_time: 0.0058 memory: 10464 grad_norm: 7.2200 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.5850 loss: 1.5850 2022/09/07 20:53:56 - mmengine - INFO - Epoch(train) [32][320/1793] lr: 7.5000e-04 eta: 2:57:28 time: 0.1775 data_time: 0.0091 memory: 10464 grad_norm: 7.2607 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6650 loss: 1.6650 2022/09/07 20:54:00 - mmengine - INFO - Epoch(train) [32][340/1793] lr: 7.5000e-04 eta: 2:57:20 time: 0.1828 data_time: 0.0062 memory: 10464 grad_norm: 7.7040 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4733 loss: 1.4733 2022/09/07 20:54:03 - mmengine - INFO - Epoch(train) [32][360/1793] lr: 7.5000e-04 eta: 2:57:12 time: 0.1731 data_time: 0.0066 memory: 10464 grad_norm: 7.4089 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.2903 loss: 1.2903 2022/09/07 20:54:07 - mmengine - INFO - Epoch(train) [32][380/1793] lr: 7.5000e-04 eta: 2:57:04 time: 0.1762 data_time: 0.0088 memory: 10464 grad_norm: 7.6560 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.6919 loss: 1.6919 2022/09/07 20:54:10 - mmengine - INFO - Epoch(train) [32][400/1793] lr: 7.5000e-04 eta: 2:56:56 time: 0.1770 data_time: 0.0069 memory: 10464 grad_norm: 7.0643 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2454 loss: 1.2454 2022/09/07 20:54:13 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:54:14 - mmengine - INFO - Epoch(train) [32][420/1793] lr: 7.5000e-04 eta: 2:56:48 time: 0.1730 data_time: 0.0080 memory: 10464 grad_norm: 7.1666 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 1.6002 loss: 1.6002 2022/09/07 20:54:17 - mmengine - INFO - Epoch(train) [32][440/1793] lr: 7.5000e-04 eta: 2:56:40 time: 0.1750 data_time: 0.0076 memory: 10464 grad_norm: 7.2476 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.4728 loss: 1.4728 2022/09/07 20:54:21 - mmengine - INFO - Epoch(train) [32][460/1793] lr: 7.5000e-04 eta: 2:56:32 time: 0.1883 data_time: 0.0085 memory: 10464 grad_norm: 7.1951 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5719 loss: 1.5719 2022/09/07 20:54:24 - mmengine - INFO - Epoch(train) [32][480/1793] lr: 7.5000e-04 eta: 2:56:24 time: 0.1724 data_time: 0.0060 memory: 10464 grad_norm: 7.2919 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4511 loss: 1.4511 2022/09/07 20:54:28 - mmengine - INFO - Epoch(train) [32][500/1793] lr: 7.5000e-04 eta: 2:56:16 time: 0.1770 data_time: 0.0097 memory: 10464 grad_norm: 7.0316 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.5451 loss: 1.5451 2022/09/07 20:54:32 - mmengine - INFO - Epoch(train) [32][520/1793] lr: 7.5000e-04 eta: 2:56:09 time: 0.1884 data_time: 0.0076 memory: 10464 grad_norm: 7.0621 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4326 loss: 1.4326 2022/09/07 20:54:35 - mmengine - INFO - Epoch(train) [32][540/1793] lr: 7.5000e-04 eta: 2:56:01 time: 0.1718 data_time: 0.0063 memory: 10464 grad_norm: 7.1827 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3512 loss: 1.3512 2022/09/07 20:54:39 - mmengine - INFO - Epoch(train) [32][560/1793] lr: 7.5000e-04 eta: 2:55:53 time: 0.1795 data_time: 0.0087 memory: 10464 grad_norm: 7.5223 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3935 loss: 1.3935 2022/09/07 20:54:42 - mmengine - INFO - Epoch(train) [32][580/1793] lr: 7.5000e-04 eta: 2:55:45 time: 0.1735 data_time: 0.0067 memory: 10464 grad_norm: 7.2677 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4324 loss: 1.4324 2022/09/07 20:54:46 - mmengine - INFO - Epoch(train) [32][600/1793] lr: 7.5000e-04 eta: 2:55:37 time: 0.1715 data_time: 0.0063 memory: 10464 grad_norm: 7.1343 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6759 loss: 1.6759 2022/09/07 20:54:49 - mmengine - INFO - Epoch(train) [32][620/1793] lr: 7.5000e-04 eta: 2:55:29 time: 0.1759 data_time: 0.0092 memory: 10464 grad_norm: 7.3451 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.7436 loss: 1.7436 2022/09/07 20:54:53 - mmengine - INFO - Epoch(train) [32][640/1793] lr: 7.5000e-04 eta: 2:55:21 time: 0.1945 data_time: 0.0068 memory: 10464 grad_norm: 7.2296 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3887 loss: 1.3887 2022/09/07 20:54:57 - mmengine - INFO - Epoch(train) [32][660/1793] lr: 7.5000e-04 eta: 2:55:13 time: 0.1728 data_time: 0.0066 memory: 10464 grad_norm: 7.2675 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.6351 loss: 1.6351 2022/09/07 20:55:00 - mmengine - INFO - Epoch(train) [32][680/1793] lr: 7.5000e-04 eta: 2:55:05 time: 0.1787 data_time: 0.0096 memory: 10464 grad_norm: 7.3671 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.3783 loss: 1.3783 2022/09/07 20:55:04 - mmengine - INFO - Epoch(train) [32][700/1793] lr: 7.5000e-04 eta: 2:54:57 time: 0.1736 data_time: 0.0068 memory: 10464 grad_norm: 7.4332 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.6714 loss: 1.6714 2022/09/07 20:55:07 - mmengine - INFO - Epoch(train) [32][720/1793] lr: 7.5000e-04 eta: 2:54:49 time: 0.1703 data_time: 0.0063 memory: 10464 grad_norm: 7.2673 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4517 loss: 1.4517 2022/09/07 20:55:12 - mmengine - INFO - Epoch(train) [32][740/1793] lr: 7.5000e-04 eta: 2:54:42 time: 0.2518 data_time: 0.0094 memory: 10464 grad_norm: 7.6373 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.6937 loss: 1.6937 2022/09/07 20:55:16 - mmengine - INFO - Epoch(train) [32][760/1793] lr: 7.5000e-04 eta: 2:54:34 time: 0.1718 data_time: 0.0064 memory: 10464 grad_norm: 7.3218 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6047 loss: 1.6047 2022/09/07 20:55:19 - mmengine - INFO - Epoch(train) [32][780/1793] lr: 7.5000e-04 eta: 2:54:26 time: 0.1747 data_time: 0.0060 memory: 10464 grad_norm: 7.4952 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.6478 loss: 1.6478 2022/09/07 20:55:23 - mmengine - INFO - Epoch(train) [32][800/1793] lr: 7.5000e-04 eta: 2:54:18 time: 0.1924 data_time: 0.0100 memory: 10464 grad_norm: 7.2348 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.6997 loss: 1.6997 2022/09/07 20:55:26 - mmengine - INFO - Epoch(train) [32][820/1793] lr: 7.5000e-04 eta: 2:54:10 time: 0.1714 data_time: 0.0061 memory: 10464 grad_norm: 7.3509 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.7949 loss: 1.7949 2022/09/07 20:55:30 - mmengine - INFO - Epoch(train) [32][840/1793] lr: 7.5000e-04 eta: 2:54:03 time: 0.1762 data_time: 0.0061 memory: 10464 grad_norm: 7.3819 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3376 loss: 1.3376 2022/09/07 20:55:33 - mmengine - INFO - Epoch(train) [32][860/1793] lr: 7.5000e-04 eta: 2:53:55 time: 0.1800 data_time: 0.0099 memory: 10464 grad_norm: 7.4174 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.5514 loss: 1.5514 2022/09/07 20:55:37 - mmengine - INFO - Epoch(train) [32][880/1793] lr: 7.5000e-04 eta: 2:53:47 time: 0.1714 data_time: 0.0063 memory: 10464 grad_norm: 7.4291 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.5216 loss: 1.5216 2022/09/07 20:55:41 - mmengine - INFO - Epoch(train) [32][900/1793] lr: 7.5000e-04 eta: 2:53:39 time: 0.1850 data_time: 0.0061 memory: 10464 grad_norm: 7.1976 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4379 loss: 1.4379 2022/09/07 20:55:44 - mmengine - INFO - Epoch(train) [32][920/1793] lr: 7.5000e-04 eta: 2:53:31 time: 0.1759 data_time: 0.0096 memory: 10464 grad_norm: 7.3867 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3104 loss: 1.3104 2022/09/07 20:55:48 - mmengine - INFO - Epoch(train) [32][940/1793] lr: 7.5000e-04 eta: 2:53:23 time: 0.1805 data_time: 0.0058 memory: 10464 grad_norm: 7.4398 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.0763 loss: 1.0763 2022/09/07 20:55:51 - mmengine - INFO - Epoch(train) [32][960/1793] lr: 7.5000e-04 eta: 2:53:15 time: 0.1870 data_time: 0.0069 memory: 10464 grad_norm: 7.3882 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.3907 loss: 1.3907 2022/09/07 20:55:55 - mmengine - INFO - Epoch(train) [32][980/1793] lr: 7.5000e-04 eta: 2:53:08 time: 0.1750 data_time: 0.0093 memory: 10464 grad_norm: 7.4289 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4007 loss: 1.4007 2022/09/07 20:55:58 - mmengine - INFO - Epoch(train) [32][1000/1793] lr: 7.5000e-04 eta: 2:53:00 time: 0.1716 data_time: 0.0064 memory: 10464 grad_norm: 7.4421 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.5511 loss: 1.5511 2022/09/07 20:56:02 - mmengine - INFO - Epoch(train) [32][1020/1793] lr: 7.5000e-04 eta: 2:52:52 time: 0.1769 data_time: 0.0067 memory: 10464 grad_norm: 7.4446 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.8161 loss: 1.8161 2022/09/07 20:56:05 - mmengine - INFO - Epoch(train) [32][1040/1793] lr: 7.5000e-04 eta: 2:52:44 time: 0.1740 data_time: 0.0094 memory: 10464 grad_norm: 7.5809 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4582 loss: 1.4582 2022/09/07 20:56:09 - mmengine - INFO - Epoch(train) [32][1060/1793] lr: 7.5000e-04 eta: 2:52:36 time: 0.1734 data_time: 0.0062 memory: 10464 grad_norm: 7.2802 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3400 loss: 1.3400 2022/09/07 20:56:12 - mmengine - INFO - Epoch(train) [32][1080/1793] lr: 7.5000e-04 eta: 2:52:28 time: 0.1735 data_time: 0.0069 memory: 10464 grad_norm: 7.2615 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.6805 loss: 1.6805 2022/09/07 20:56:16 - mmengine - INFO - Epoch(train) [32][1100/1793] lr: 7.5000e-04 eta: 2:52:20 time: 0.1748 data_time: 0.0094 memory: 10464 grad_norm: 7.4564 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4520 loss: 1.4520 2022/09/07 20:56:19 - mmengine - INFO - Epoch(train) [32][1120/1793] lr: 7.5000e-04 eta: 2:52:12 time: 0.1802 data_time: 0.0064 memory: 10464 grad_norm: 7.1372 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2610 loss: 1.2610 2022/09/07 20:56:23 - mmengine - INFO - Epoch(train) [32][1140/1793] lr: 7.5000e-04 eta: 2:52:04 time: 0.1807 data_time: 0.0066 memory: 10464 grad_norm: 7.3836 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3384 loss: 1.3384 2022/09/07 20:56:27 - mmengine - INFO - Epoch(train) [32][1160/1793] lr: 7.5000e-04 eta: 2:51:57 time: 0.1829 data_time: 0.0099 memory: 10464 grad_norm: 7.5189 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.3312 loss: 1.3312 2022/09/07 20:56:30 - mmengine - INFO - Epoch(train) [32][1180/1793] lr: 7.5000e-04 eta: 2:51:49 time: 0.1711 data_time: 0.0054 memory: 10464 grad_norm: 7.3483 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3694 loss: 1.3694 2022/09/07 20:56:34 - mmengine - INFO - Epoch(train) [32][1200/1793] lr: 7.5000e-04 eta: 2:51:41 time: 0.1816 data_time: 0.0068 memory: 10464 grad_norm: 7.1091 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5970 loss: 1.5970 2022/09/07 20:56:37 - mmengine - INFO - Epoch(train) [32][1220/1793] lr: 7.5000e-04 eta: 2:51:33 time: 0.1754 data_time: 0.0102 memory: 10464 grad_norm: 7.4817 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4948 loss: 1.4948 2022/09/07 20:56:41 - mmengine - INFO - Epoch(train) [32][1240/1793] lr: 7.5000e-04 eta: 2:51:25 time: 0.1823 data_time: 0.0063 memory: 10464 grad_norm: 7.5147 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.6157 loss: 1.6157 2022/09/07 20:56:44 - mmengine - INFO - Epoch(train) [32][1260/1793] lr: 7.5000e-04 eta: 2:51:17 time: 0.1715 data_time: 0.0061 memory: 10464 grad_norm: 7.3148 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5760 loss: 1.5760 2022/09/07 20:56:48 - mmengine - INFO - Epoch(train) [32][1280/1793] lr: 7.5000e-04 eta: 2:51:10 time: 0.1741 data_time: 0.0083 memory: 10464 grad_norm: 7.8131 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.5105 loss: 1.5105 2022/09/07 20:56:51 - mmengine - INFO - Epoch(train) [32][1300/1793] lr: 7.5000e-04 eta: 2:51:02 time: 0.1787 data_time: 0.0069 memory: 10464 grad_norm: 7.3156 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.4411 loss: 1.4411 2022/09/07 20:56:55 - mmengine - INFO - Epoch(train) [32][1320/1793] lr: 7.5000e-04 eta: 2:50:54 time: 0.1722 data_time: 0.0063 memory: 10464 grad_norm: 7.6218 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5174 loss: 1.5174 2022/09/07 20:56:58 - mmengine - INFO - Epoch(train) [32][1340/1793] lr: 7.5000e-04 eta: 2:50:46 time: 0.1776 data_time: 0.0084 memory: 10464 grad_norm: 7.6706 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4783 loss: 1.4783 2022/09/07 20:57:02 - mmengine - INFO - Epoch(train) [32][1360/1793] lr: 7.5000e-04 eta: 2:50:38 time: 0.1732 data_time: 0.0065 memory: 10464 grad_norm: 7.3440 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3809 loss: 1.3809 2022/09/07 20:57:05 - mmengine - INFO - Epoch(train) [32][1380/1793] lr: 7.5000e-04 eta: 2:50:30 time: 0.1710 data_time: 0.0061 memory: 10464 grad_norm: 7.5743 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5230 loss: 1.5230 2022/09/07 20:57:09 - mmengine - INFO - Epoch(train) [32][1400/1793] lr: 7.5000e-04 eta: 2:50:22 time: 0.1756 data_time: 0.0086 memory: 10464 grad_norm: 7.6597 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7853 loss: 1.7853 2022/09/07 20:57:12 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:57:12 - mmengine - INFO - Epoch(train) [32][1420/1793] lr: 7.5000e-04 eta: 2:50:15 time: 0.1734 data_time: 0.0070 memory: 10464 grad_norm: 7.3038 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8159 loss: 1.8159 2022/09/07 20:57:16 - mmengine - INFO - Epoch(train) [32][1440/1793] lr: 7.5000e-04 eta: 2:50:07 time: 0.1744 data_time: 0.0063 memory: 10464 grad_norm: 7.4835 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3352 loss: 1.3352 2022/09/07 20:57:19 - mmengine - INFO - Epoch(train) [32][1460/1793] lr: 7.5000e-04 eta: 2:49:59 time: 0.1744 data_time: 0.0085 memory: 10464 grad_norm: 7.7389 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4081 loss: 1.4081 2022/09/07 20:57:23 - mmengine - INFO - Epoch(train) [32][1480/1793] lr: 7.5000e-04 eta: 2:49:51 time: 0.1730 data_time: 0.0067 memory: 10464 grad_norm: 7.5733 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.6923 loss: 1.6923 2022/09/07 20:57:26 - mmengine - INFO - Epoch(train) [32][1500/1793] lr: 7.5000e-04 eta: 2:49:43 time: 0.1722 data_time: 0.0063 memory: 10464 grad_norm: 7.5352 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3916 loss: 1.3916 2022/09/07 20:57:30 - mmengine - INFO - Epoch(train) [32][1520/1793] lr: 7.5000e-04 eta: 2:49:35 time: 0.1913 data_time: 0.0081 memory: 10464 grad_norm: 7.4508 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5096 loss: 1.5096 2022/09/07 20:57:34 - mmengine - INFO - Epoch(train) [32][1540/1793] lr: 7.5000e-04 eta: 2:49:28 time: 0.1880 data_time: 0.0066 memory: 10464 grad_norm: 7.3371 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3508 loss: 1.3508 2022/09/07 20:57:37 - mmengine - INFO - Epoch(train) [32][1560/1793] lr: 7.5000e-04 eta: 2:49:20 time: 0.1717 data_time: 0.0067 memory: 10464 grad_norm: 7.6782 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.5403 loss: 1.5403 2022/09/07 20:57:41 - mmengine - INFO - Epoch(train) [32][1580/1793] lr: 7.5000e-04 eta: 2:49:12 time: 0.1794 data_time: 0.0088 memory: 10464 grad_norm: 7.5453 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3784 loss: 1.3784 2022/09/07 20:57:44 - mmengine - INFO - Epoch(train) [32][1600/1793] lr: 7.5000e-04 eta: 2:49:04 time: 0.1759 data_time: 0.0061 memory: 10464 grad_norm: 7.6444 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.5451 loss: 1.5451 2022/09/07 20:57:48 - mmengine - INFO - Epoch(train) [32][1620/1793] lr: 7.5000e-04 eta: 2:48:57 time: 0.1723 data_time: 0.0062 memory: 10464 grad_norm: 7.4455 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4099 loss: 1.4099 2022/09/07 20:57:51 - mmengine - INFO - Epoch(train) [32][1640/1793] lr: 7.5000e-04 eta: 2:48:49 time: 0.1763 data_time: 0.0089 memory: 10464 grad_norm: 7.4714 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9177 loss: 1.9177 2022/09/07 20:57:55 - mmengine - INFO - Epoch(train) [32][1660/1793] lr: 7.5000e-04 eta: 2:48:41 time: 0.1717 data_time: 0.0072 memory: 10464 grad_norm: 7.1756 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4941 loss: 1.4941 2022/09/07 20:57:58 - mmengine - INFO - Epoch(train) [32][1680/1793] lr: 7.5000e-04 eta: 2:48:33 time: 0.1753 data_time: 0.0057 memory: 10464 grad_norm: 7.5638 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7156 loss: 1.7156 2022/09/07 20:58:03 - mmengine - INFO - Epoch(train) [32][1700/1793] lr: 7.5000e-04 eta: 2:48:26 time: 0.2416 data_time: 0.0094 memory: 10464 grad_norm: 7.2351 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.3521 loss: 1.3521 2022/09/07 20:58:07 - mmengine - INFO - Epoch(train) [32][1720/1793] lr: 7.5000e-04 eta: 2:48:18 time: 0.1725 data_time: 0.0068 memory: 10464 grad_norm: 7.3777 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.5386 loss: 1.5386 2022/09/07 20:58:10 - mmengine - INFO - Epoch(train) [32][1740/1793] lr: 7.5000e-04 eta: 2:48:10 time: 0.1735 data_time: 0.0061 memory: 10464 grad_norm: 7.2560 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4323 loss: 1.4323 2022/09/07 20:58:14 - mmengine - INFO - Epoch(train) [32][1760/1793] lr: 7.5000e-04 eta: 2:48:03 time: 0.1791 data_time: 0.0102 memory: 10464 grad_norm: 7.3862 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4146 loss: 1.4146 2022/09/07 20:58:17 - mmengine - INFO - Epoch(train) [32][1780/1793] lr: 7.5000e-04 eta: 2:47:55 time: 0.1717 data_time: 0.0059 memory: 10464 grad_norm: 7.4214 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3085 loss: 1.3085 2022/09/07 20:58:20 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 20:58:20 - mmengine - INFO - Epoch(train) [32][1793/1793] lr: 7.5000e-04 eta: 2:47:55 time: 0.1839 data_time: 0.0060 memory: 10464 grad_norm: 8.1043 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 1.3865 loss: 1.3865 2022/09/07 20:58:20 - mmengine - INFO - Saving checkpoint at 32 epochs 2022/09/07 20:58:23 - mmengine - INFO - Epoch(val) [32][20/241] eta: 0:00:12 time: 0.0581 data_time: 0.0088 memory: 1482 2022/09/07 20:58:25 - mmengine - INFO - Epoch(val) [32][40/241] eta: 0:00:10 time: 0.0536 data_time: 0.0050 memory: 1482 2022/09/07 20:58:26 - mmengine - INFO - Epoch(val) [32][60/241] eta: 0:00:09 time: 0.0530 data_time: 0.0048 memory: 1482 2022/09/07 20:58:27 - mmengine - INFO - Epoch(val) [32][80/241] eta: 0:00:08 time: 0.0536 data_time: 0.0051 memory: 1482 2022/09/07 20:58:28 - mmengine - INFO - Epoch(val) [32][100/241] eta: 0:00:07 time: 0.0534 data_time: 0.0050 memory: 1482 2022/09/07 20:58:29 - mmengine - INFO - Epoch(val) [32][120/241] eta: 0:00:06 time: 0.0539 data_time: 0.0053 memory: 1482 2022/09/07 20:58:30 - mmengine - INFO - Epoch(val) [32][140/241] eta: 0:00:05 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 20:58:31 - mmengine - INFO - Epoch(val) [32][160/241] eta: 0:00:04 time: 0.0592 data_time: 0.0051 memory: 1482 2022/09/07 20:58:32 - mmengine - INFO - Epoch(val) [32][180/241] eta: 0:00:03 time: 0.0590 data_time: 0.0107 memory: 1482 2022/09/07 20:58:33 - mmengine - INFO - Epoch(val) [32][200/241] eta: 0:00:02 time: 0.0519 data_time: 0.0039 memory: 1482 2022/09/07 20:58:34 - mmengine - INFO - Epoch(val) [32][220/241] eta: 0:00:01 time: 0.0523 data_time: 0.0044 memory: 1482 2022/09/07 20:58:35 - mmengine - INFO - Epoch(val) [32][240/241] eta: 0:00:00 time: 0.0522 data_time: 0.0043 memory: 1482 2022/09/07 20:58:36 - mmengine - INFO - Epoch(val) [32][241/241] acc/top1: 0.4432 acc/top5: 0.7530 acc/mean1: 0.4062 2022/09/07 20:58:36 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_31.pth is removed 2022/09/07 20:58:38 - mmengine - INFO - The best checkpoint with 0.4432 acc/top1 at 32 epoch is saved to best_acc/top1_epoch_32.pth. 2022/09/07 20:58:41 - mmengine - INFO - Epoch(train) [33][20/1793] lr: 7.5000e-04 eta: 2:47:41 time: 0.1796 data_time: 0.0102 memory: 10464 grad_norm: 7.5485 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3247 loss: 1.3247 2022/09/07 20:58:45 - mmengine - INFO - Epoch(train) [33][40/1793] lr: 7.5000e-04 eta: 2:47:33 time: 0.1706 data_time: 0.0063 memory: 10464 grad_norm: 7.3682 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6035 loss: 1.6035 2022/09/07 20:58:48 - mmengine - INFO - Epoch(train) [33][60/1793] lr: 7.5000e-04 eta: 2:47:25 time: 0.1740 data_time: 0.0061 memory: 10464 grad_norm: 7.2994 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4576 loss: 1.4576 2022/09/07 20:58:52 - mmengine - INFO - Epoch(train) [33][80/1793] lr: 7.5000e-04 eta: 2:47:18 time: 0.1886 data_time: 0.0084 memory: 10464 grad_norm: 7.5742 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.5234 loss: 1.5234 2022/09/07 20:58:56 - mmengine - INFO - Epoch(train) [33][100/1793] lr: 7.5000e-04 eta: 2:47:10 time: 0.1727 data_time: 0.0067 memory: 10464 grad_norm: 7.4000 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.6653 loss: 1.6653 2022/09/07 20:58:59 - mmengine - INFO - Epoch(train) [33][120/1793] lr: 7.5000e-04 eta: 2:47:02 time: 0.1721 data_time: 0.0062 memory: 10464 grad_norm: 7.8057 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.5065 loss: 1.5065 2022/09/07 20:59:02 - mmengine - INFO - Epoch(train) [33][140/1793] lr: 7.5000e-04 eta: 2:46:54 time: 0.1747 data_time: 0.0080 memory: 10464 grad_norm: 7.1683 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3515 loss: 1.3515 2022/09/07 20:59:06 - mmengine - INFO - Epoch(train) [33][160/1793] lr: 7.5000e-04 eta: 2:46:46 time: 0.1743 data_time: 0.0060 memory: 10464 grad_norm: 7.5977 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4732 loss: 1.4732 2022/09/07 20:59:10 - mmengine - INFO - Epoch(train) [33][180/1793] lr: 7.5000e-04 eta: 2:46:39 time: 0.1768 data_time: 0.0065 memory: 10464 grad_norm: 7.3679 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4420 loss: 1.4420 2022/09/07 20:59:14 - mmengine - INFO - Epoch(train) [33][200/1793] lr: 7.5000e-04 eta: 2:46:31 time: 0.1997 data_time: 0.0090 memory: 10464 grad_norm: 7.5855 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.3048 loss: 1.3048 2022/09/07 20:59:17 - mmengine - INFO - Epoch(train) [33][220/1793] lr: 7.5000e-04 eta: 2:46:23 time: 0.1723 data_time: 0.0062 memory: 10464 grad_norm: 7.4881 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3556 loss: 1.3556 2022/09/07 20:59:20 - mmengine - INFO - Epoch(train) [33][240/1793] lr: 7.5000e-04 eta: 2:46:16 time: 0.1727 data_time: 0.0059 memory: 10464 grad_norm: 7.5555 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5851 loss: 1.5851 2022/09/07 20:59:24 - mmengine - INFO - Epoch(train) [33][260/1793] lr: 7.5000e-04 eta: 2:46:08 time: 0.1749 data_time: 0.0086 memory: 10464 grad_norm: 7.6497 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.5935 loss: 1.5935 2022/09/07 20:59:27 - mmengine - INFO - Epoch(train) [33][280/1793] lr: 7.5000e-04 eta: 2:46:00 time: 0.1733 data_time: 0.0065 memory: 10464 grad_norm: 7.2269 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.5530 loss: 1.5530 2022/09/07 20:59:31 - mmengine - INFO - Epoch(train) [33][300/1793] lr: 7.5000e-04 eta: 2:45:53 time: 0.1818 data_time: 0.0074 memory: 10464 grad_norm: 7.5907 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.3438 loss: 1.3438 2022/09/07 20:59:34 - mmengine - INFO - Epoch(train) [33][320/1793] lr: 7.5000e-04 eta: 2:45:45 time: 0.1730 data_time: 0.0084 memory: 10464 grad_norm: 7.5311 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.4304 loss: 1.4304 2022/09/07 20:59:38 - mmengine - INFO - Epoch(train) [33][340/1793] lr: 7.5000e-04 eta: 2:45:37 time: 0.1738 data_time: 0.0063 memory: 10464 grad_norm: 7.8240 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.7029 loss: 1.7029 2022/09/07 20:59:41 - mmengine - INFO - Epoch(train) [33][360/1793] lr: 7.5000e-04 eta: 2:45:29 time: 0.1735 data_time: 0.0072 memory: 10464 grad_norm: 7.7441 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.3966 loss: 1.3966 2022/09/07 20:59:45 - mmengine - INFO - Epoch(train) [33][380/1793] lr: 7.5000e-04 eta: 2:45:22 time: 0.1715 data_time: 0.0074 memory: 10464 grad_norm: 7.6779 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1706 loss: 1.1706 2022/09/07 20:59:48 - mmengine - INFO - Epoch(train) [33][400/1793] lr: 7.5000e-04 eta: 2:45:14 time: 0.1731 data_time: 0.0064 memory: 10464 grad_norm: 7.5711 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2996 loss: 1.2996 2022/09/07 20:59:52 - mmengine - INFO - Epoch(train) [33][420/1793] lr: 7.5000e-04 eta: 2:45:06 time: 0.1801 data_time: 0.0071 memory: 10464 grad_norm: 7.4544 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.5934 loss: 1.5934 2022/09/07 20:59:55 - mmengine - INFO - Epoch(train) [33][440/1793] lr: 7.5000e-04 eta: 2:44:58 time: 0.1746 data_time: 0.0099 memory: 10464 grad_norm: 7.3383 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5982 loss: 1.5982 2022/09/07 20:59:59 - mmengine - INFO - Epoch(train) [33][460/1793] lr: 7.5000e-04 eta: 2:44:51 time: 0.1741 data_time: 0.0070 memory: 10464 grad_norm: 7.6806 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5967 loss: 1.5967 2022/09/07 21:00:02 - mmengine - INFO - Epoch(train) [33][480/1793] lr: 7.5000e-04 eta: 2:44:43 time: 0.1715 data_time: 0.0061 memory: 10464 grad_norm: 7.5439 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4545 loss: 1.4545 2022/09/07 21:00:06 - mmengine - INFO - Epoch(train) [33][500/1793] lr: 7.5000e-04 eta: 2:44:35 time: 0.1733 data_time: 0.0092 memory: 10464 grad_norm: 7.7020 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.3354 loss: 1.3354 2022/09/07 21:00:09 - mmengine - INFO - Epoch(train) [33][520/1793] lr: 7.5000e-04 eta: 2:44:27 time: 0.1722 data_time: 0.0059 memory: 10464 grad_norm: 7.4308 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.6056 loss: 1.6056 2022/09/07 21:00:13 - mmengine - INFO - Epoch(train) [33][540/1793] lr: 7.5000e-04 eta: 2:44:20 time: 0.1761 data_time: 0.0074 memory: 10464 grad_norm: 7.4985 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3190 loss: 1.3190 2022/09/07 21:00:16 - mmengine - INFO - Epoch(train) [33][560/1793] lr: 7.5000e-04 eta: 2:44:12 time: 0.1748 data_time: 0.0097 memory: 10464 grad_norm: 7.7538 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3682 loss: 1.3682 2022/09/07 21:00:20 - mmengine - INFO - Epoch(train) [33][580/1793] lr: 7.5000e-04 eta: 2:44:04 time: 0.1755 data_time: 0.0061 memory: 10464 grad_norm: 7.9265 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4047 loss: 1.4047 2022/09/07 21:00:23 - mmengine - INFO - Epoch(train) [33][600/1793] lr: 7.5000e-04 eta: 2:43:57 time: 0.1809 data_time: 0.0067 memory: 10464 grad_norm: 7.9980 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.5959 loss: 1.5959 2022/09/07 21:00:27 - mmengine - INFO - Epoch(train) [33][620/1793] lr: 7.5000e-04 eta: 2:43:49 time: 0.1737 data_time: 0.0083 memory: 10464 grad_norm: 7.5125 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3643 loss: 1.3643 2022/09/07 21:00:28 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:00:30 - mmengine - INFO - Epoch(train) [33][640/1793] lr: 7.5000e-04 eta: 2:43:41 time: 0.1762 data_time: 0.0063 memory: 10464 grad_norm: 7.3520 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5156 loss: 1.5156 2022/09/07 21:00:34 - mmengine - INFO - Epoch(train) [33][660/1793] lr: 7.5000e-04 eta: 2:43:34 time: 0.1779 data_time: 0.0074 memory: 10464 grad_norm: 7.4004 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4551 loss: 1.4551 2022/09/07 21:00:37 - mmengine - INFO - Epoch(train) [33][680/1793] lr: 7.5000e-04 eta: 2:43:26 time: 0.1733 data_time: 0.0085 memory: 10464 grad_norm: 7.7249 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1742 loss: 1.1742 2022/09/07 21:00:41 - mmengine - INFO - Epoch(train) [33][700/1793] lr: 7.5000e-04 eta: 2:43:18 time: 0.1745 data_time: 0.0067 memory: 10464 grad_norm: 7.7539 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7055 loss: 1.7055 2022/09/07 21:00:44 - mmengine - INFO - Epoch(train) [33][720/1793] lr: 7.5000e-04 eta: 2:43:11 time: 0.1734 data_time: 0.0065 memory: 10464 grad_norm: 7.8628 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4029 loss: 1.4029 2022/09/07 21:00:48 - mmengine - INFO - Epoch(train) [33][740/1793] lr: 7.5000e-04 eta: 2:43:03 time: 0.1753 data_time: 0.0089 memory: 10464 grad_norm: 7.6338 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4517 loss: 1.4517 2022/09/07 21:00:52 - mmengine - INFO - Epoch(train) [33][760/1793] lr: 7.5000e-04 eta: 2:42:55 time: 0.1931 data_time: 0.0072 memory: 10464 grad_norm: 7.1091 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3026 loss: 1.3026 2022/09/07 21:00:55 - mmengine - INFO - Epoch(train) [33][780/1793] lr: 7.5000e-04 eta: 2:42:48 time: 0.1744 data_time: 0.0064 memory: 10464 grad_norm: 8.0810 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4181 loss: 1.4181 2022/09/07 21:00:59 - mmengine - INFO - Epoch(train) [33][800/1793] lr: 7.5000e-04 eta: 2:42:40 time: 0.1727 data_time: 0.0085 memory: 10464 grad_norm: 7.8509 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.3640 loss: 1.3640 2022/09/07 21:01:02 - mmengine - INFO - Epoch(train) [33][820/1793] lr: 7.5000e-04 eta: 2:42:32 time: 0.1724 data_time: 0.0066 memory: 10464 grad_norm: 7.6011 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3375 loss: 1.3375 2022/09/07 21:01:06 - mmengine - INFO - Epoch(train) [33][840/1793] lr: 7.5000e-04 eta: 2:42:25 time: 0.1722 data_time: 0.0061 memory: 10464 grad_norm: 7.8929 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4403 loss: 1.4403 2022/09/07 21:01:09 - mmengine - INFO - Epoch(train) [33][860/1793] lr: 7.5000e-04 eta: 2:42:17 time: 0.1752 data_time: 0.0093 memory: 10464 grad_norm: 7.6658 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3732 loss: 1.3732 2022/09/07 21:01:13 - mmengine - INFO - Epoch(train) [33][880/1793] lr: 7.5000e-04 eta: 2:42:09 time: 0.1734 data_time: 0.0074 memory: 10464 grad_norm: 7.7769 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4736 loss: 1.4736 2022/09/07 21:01:16 - mmengine - INFO - Epoch(train) [33][900/1793] lr: 7.5000e-04 eta: 2:42:02 time: 0.1753 data_time: 0.0061 memory: 10464 grad_norm: 7.6208 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2984 loss: 1.2984 2022/09/07 21:01:20 - mmengine - INFO - Epoch(train) [33][920/1793] lr: 7.5000e-04 eta: 2:41:54 time: 0.1802 data_time: 0.0087 memory: 10464 grad_norm: 7.9304 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5111 loss: 1.5111 2022/09/07 21:01:23 - mmengine - INFO - Epoch(train) [33][940/1793] lr: 7.5000e-04 eta: 2:41:46 time: 0.1698 data_time: 0.0065 memory: 10464 grad_norm: 8.1463 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.6034 loss: 1.6034 2022/09/07 21:01:27 - mmengine - INFO - Epoch(train) [33][960/1793] lr: 7.5000e-04 eta: 2:41:39 time: 0.1731 data_time: 0.0060 memory: 10464 grad_norm: 7.6795 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4709 loss: 1.4709 2022/09/07 21:01:30 - mmengine - INFO - Epoch(train) [33][980/1793] lr: 7.5000e-04 eta: 2:41:31 time: 0.1791 data_time: 0.0107 memory: 10464 grad_norm: 7.5528 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4613 loss: 1.4613 2022/09/07 21:01:34 - mmengine - INFO - Epoch(train) [33][1000/1793] lr: 7.5000e-04 eta: 2:41:24 time: 0.1747 data_time: 0.0064 memory: 10464 grad_norm: 7.8944 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.6406 loss: 1.6406 2022/09/07 21:01:37 - mmengine - INFO - Epoch(train) [33][1020/1793] lr: 7.5000e-04 eta: 2:41:16 time: 0.1729 data_time: 0.0067 memory: 10464 grad_norm: 7.8101 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.5279 loss: 1.5279 2022/09/07 21:01:41 - mmengine - INFO - Epoch(train) [33][1040/1793] lr: 7.5000e-04 eta: 2:41:08 time: 0.1730 data_time: 0.0085 memory: 10464 grad_norm: 7.3090 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 1.2466 loss: 1.2466 2022/09/07 21:01:44 - mmengine - INFO - Epoch(train) [33][1060/1793] lr: 7.5000e-04 eta: 2:41:01 time: 0.1731 data_time: 0.0066 memory: 10464 grad_norm: 7.5709 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1516 loss: 1.1516 2022/09/07 21:01:48 - mmengine - INFO - Epoch(train) [33][1080/1793] lr: 7.5000e-04 eta: 2:40:53 time: 0.1715 data_time: 0.0060 memory: 10464 grad_norm: 7.8144 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5080 loss: 1.5080 2022/09/07 21:01:51 - mmengine - INFO - Epoch(train) [33][1100/1793] lr: 7.5000e-04 eta: 2:40:45 time: 0.1856 data_time: 0.0093 memory: 10464 grad_norm: 7.7343 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.6281 loss: 1.6281 2022/09/07 21:01:55 - mmengine - INFO - Epoch(train) [33][1120/1793] lr: 7.5000e-04 eta: 2:40:38 time: 0.1739 data_time: 0.0066 memory: 10464 grad_norm: 7.7351 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6275 loss: 1.6275 2022/09/07 21:01:58 - mmengine - INFO - Epoch(train) [33][1140/1793] lr: 7.5000e-04 eta: 2:40:30 time: 0.1720 data_time: 0.0061 memory: 10464 grad_norm: 7.7396 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.3575 loss: 1.3575 2022/09/07 21:02:02 - mmengine - INFO - Epoch(train) [33][1160/1793] lr: 7.5000e-04 eta: 2:40:23 time: 0.1745 data_time: 0.0098 memory: 10464 grad_norm: 7.7190 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6098 loss: 1.6098 2022/09/07 21:02:05 - mmengine - INFO - Epoch(train) [33][1180/1793] lr: 7.5000e-04 eta: 2:40:15 time: 0.1714 data_time: 0.0073 memory: 10464 grad_norm: 8.3736 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.8625 loss: 1.8625 2022/09/07 21:02:09 - mmengine - INFO - Epoch(train) [33][1200/1793] lr: 7.5000e-04 eta: 2:40:07 time: 0.1825 data_time: 0.0062 memory: 10464 grad_norm: 7.9286 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5781 loss: 1.5781 2022/09/07 21:02:13 - mmengine - INFO - Epoch(train) [33][1220/1793] lr: 7.5000e-04 eta: 2:40:00 time: 0.2025 data_time: 0.0095 memory: 10464 grad_norm: 7.6303 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.4570 loss: 1.4570 2022/09/07 21:02:16 - mmengine - INFO - Epoch(train) [33][1240/1793] lr: 7.5000e-04 eta: 2:39:52 time: 0.1717 data_time: 0.0065 memory: 10464 grad_norm: 7.7628 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4673 loss: 1.4673 2022/09/07 21:02:20 - mmengine - INFO - Epoch(train) [33][1260/1793] lr: 7.5000e-04 eta: 2:39:45 time: 0.1720 data_time: 0.0061 memory: 10464 grad_norm: 7.5442 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.2769 loss: 1.2769 2022/09/07 21:02:23 - mmengine - INFO - Epoch(train) [33][1280/1793] lr: 7.5000e-04 eta: 2:39:37 time: 0.1749 data_time: 0.0102 memory: 10464 grad_norm: 7.2841 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3060 loss: 1.3060 2022/09/07 21:02:27 - mmengine - INFO - Epoch(train) [33][1300/1793] lr: 7.5000e-04 eta: 2:39:30 time: 0.1710 data_time: 0.0067 memory: 10464 grad_norm: 7.7287 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3980 loss: 1.3980 2022/09/07 21:02:31 - mmengine - INFO - Epoch(train) [33][1320/1793] lr: 7.5000e-04 eta: 2:39:22 time: 0.1935 data_time: 0.0069 memory: 10464 grad_norm: 7.4958 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.4137 loss: 1.4137 2022/09/07 21:02:35 - mmengine - INFO - Epoch(train) [33][1340/1793] lr: 7.5000e-04 eta: 2:39:15 time: 0.1993 data_time: 0.0093 memory: 10464 grad_norm: 8.0368 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5223 loss: 1.5223 2022/09/07 21:02:38 - mmengine - INFO - Epoch(train) [33][1360/1793] lr: 7.5000e-04 eta: 2:39:07 time: 0.1720 data_time: 0.0066 memory: 10464 grad_norm: 7.9228 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4782 loss: 1.4782 2022/09/07 21:02:41 - mmengine - INFO - Epoch(train) [33][1380/1793] lr: 7.5000e-04 eta: 2:39:00 time: 0.1717 data_time: 0.0070 memory: 10464 grad_norm: 7.8125 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3827 loss: 1.3827 2022/09/07 21:02:45 - mmengine - INFO - Epoch(train) [33][1400/1793] lr: 7.5000e-04 eta: 2:38:52 time: 0.1720 data_time: 0.0083 memory: 10464 grad_norm: 8.0321 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.2264 loss: 1.2264 2022/09/07 21:02:48 - mmengine - INFO - Epoch(train) [33][1420/1793] lr: 7.5000e-04 eta: 2:38:44 time: 0.1806 data_time: 0.0063 memory: 10464 grad_norm: 7.9041 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.7347 loss: 1.7347 2022/09/07 21:02:52 - mmengine - INFO - Epoch(train) [33][1440/1793] lr: 7.5000e-04 eta: 2:38:37 time: 0.1961 data_time: 0.0086 memory: 10464 grad_norm: 7.4637 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0784 loss: 1.0784 2022/09/07 21:02:56 - mmengine - INFO - Epoch(train) [33][1460/1793] lr: 7.5000e-04 eta: 2:38:29 time: 0.1729 data_time: 0.0088 memory: 10464 grad_norm: 8.0387 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4857 loss: 1.4857 2022/09/07 21:02:59 - mmengine - INFO - Epoch(train) [33][1480/1793] lr: 7.5000e-04 eta: 2:38:22 time: 0.1711 data_time: 0.0064 memory: 10464 grad_norm: 8.3074 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4411 loss: 1.4411 2022/09/07 21:03:03 - mmengine - INFO - Epoch(train) [33][1500/1793] lr: 7.5000e-04 eta: 2:38:14 time: 0.1757 data_time: 0.0090 memory: 10464 grad_norm: 7.7762 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.5628 loss: 1.5628 2022/09/07 21:03:06 - mmengine - INFO - Epoch(train) [33][1520/1793] lr: 7.5000e-04 eta: 2:38:07 time: 0.1731 data_time: 0.0069 memory: 10464 grad_norm: 7.8589 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2376 loss: 1.2376 2022/09/07 21:03:10 - mmengine - INFO - Epoch(train) [33][1540/1793] lr: 7.5000e-04 eta: 2:37:59 time: 0.1752 data_time: 0.0067 memory: 10464 grad_norm: 7.6181 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.5168 loss: 1.5168 2022/09/07 21:03:13 - mmengine - INFO - Epoch(train) [33][1560/1793] lr: 7.5000e-04 eta: 2:37:52 time: 0.1857 data_time: 0.0072 memory: 10464 grad_norm: 7.7336 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4704 loss: 1.4704 2022/09/07 21:03:17 - mmengine - INFO - Epoch(train) [33][1580/1793] lr: 7.5000e-04 eta: 2:37:44 time: 0.1737 data_time: 0.0086 memory: 10464 grad_norm: 7.7666 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3016 loss: 1.3016 2022/09/07 21:03:20 - mmengine - INFO - Epoch(train) [33][1600/1793] lr: 7.5000e-04 eta: 2:37:37 time: 0.1739 data_time: 0.0066 memory: 10464 grad_norm: 7.6059 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5098 loss: 1.5098 2022/09/07 21:03:24 - mmengine - INFO - Epoch(train) [33][1620/1793] lr: 7.5000e-04 eta: 2:37:29 time: 0.1704 data_time: 0.0063 memory: 10464 grad_norm: 7.9289 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3033 loss: 1.3033 2022/09/07 21:03:25 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:03:27 - mmengine - INFO - Epoch(train) [33][1640/1793] lr: 7.5000e-04 eta: 2:37:21 time: 0.1728 data_time: 0.0092 memory: 10464 grad_norm: 7.5925 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1063 loss: 1.1063 2022/09/07 21:03:31 - mmengine - INFO - Epoch(train) [33][1660/1793] lr: 7.5000e-04 eta: 2:37:14 time: 0.1839 data_time: 0.0064 memory: 10464 grad_norm: 7.6330 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3557 loss: 1.3557 2022/09/07 21:03:34 - mmengine - INFO - Epoch(train) [33][1680/1793] lr: 7.5000e-04 eta: 2:37:06 time: 0.1758 data_time: 0.0062 memory: 10464 grad_norm: 7.8344 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.5796 loss: 1.5796 2022/09/07 21:03:38 - mmengine - INFO - Epoch(train) [33][1700/1793] lr: 7.5000e-04 eta: 2:36:59 time: 0.1738 data_time: 0.0093 memory: 10464 grad_norm: 7.7057 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7514 loss: 1.7514 2022/09/07 21:03:42 - mmengine - INFO - Epoch(train) [33][1720/1793] lr: 7.5000e-04 eta: 2:36:51 time: 0.1781 data_time: 0.0065 memory: 10464 grad_norm: 7.6429 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2297 loss: 1.2297 2022/09/07 21:03:45 - mmengine - INFO - Epoch(train) [33][1740/1793] lr: 7.5000e-04 eta: 2:36:44 time: 0.1704 data_time: 0.0064 memory: 10464 grad_norm: 7.5070 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2653 loss: 1.2653 2022/09/07 21:03:49 - mmengine - INFO - Epoch(train) [33][1760/1793] lr: 7.5000e-04 eta: 2:36:36 time: 0.1847 data_time: 0.0097 memory: 10464 grad_norm: 8.1351 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4497 loss: 1.4497 2022/09/07 21:03:52 - mmengine - INFO - Epoch(train) [33][1780/1793] lr: 7.5000e-04 eta: 2:36:29 time: 0.1828 data_time: 0.0065 memory: 10464 grad_norm: 7.7505 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3749 loss: 1.3749 2022/09/07 21:03:54 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:03:54 - mmengine - INFO - Epoch(train) [33][1793/1793] lr: 7.5000e-04 eta: 2:36:29 time: 0.1797 data_time: 0.0063 memory: 10464 grad_norm: 7.6862 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 1.5624 loss: 1.5624 2022/09/07 21:03:54 - mmengine - INFO - Saving checkpoint at 33 epochs 2022/09/07 21:03:59 - mmengine - INFO - Epoch(val) [33][20/241] eta: 0:00:18 time: 0.0820 data_time: 0.0328 memory: 1482 2022/09/07 21:04:00 - mmengine - INFO - Epoch(val) [33][40/241] eta: 0:00:10 time: 0.0540 data_time: 0.0053 memory: 1482 2022/09/07 21:04:01 - mmengine - INFO - Epoch(val) [33][60/241] eta: 0:00:09 time: 0.0535 data_time: 0.0050 memory: 1482 2022/09/07 21:04:02 - mmengine - INFO - Epoch(val) [33][80/241] eta: 0:00:08 time: 0.0533 data_time: 0.0048 memory: 1482 2022/09/07 21:04:03 - mmengine - INFO - Epoch(val) [33][100/241] eta: 0:00:07 time: 0.0534 data_time: 0.0049 memory: 1482 2022/09/07 21:04:04 - mmengine - INFO - Epoch(val) [33][120/241] eta: 0:00:06 time: 0.0541 data_time: 0.0055 memory: 1482 2022/09/07 21:04:05 - mmengine - INFO - Epoch(val) [33][140/241] eta: 0:00:05 time: 0.0532 data_time: 0.0045 memory: 1482 2022/09/07 21:04:06 - mmengine - INFO - Epoch(val) [33][160/241] eta: 0:00:04 time: 0.0533 data_time: 0.0048 memory: 1482 2022/09/07 21:04:07 - mmengine - INFO - Epoch(val) [33][180/241] eta: 0:00:03 time: 0.0528 data_time: 0.0046 memory: 1482 2022/09/07 21:04:08 - mmengine - INFO - Epoch(val) [33][200/241] eta: 0:00:02 time: 0.0526 data_time: 0.0046 memory: 1482 2022/09/07 21:04:09 - mmengine - INFO - Epoch(val) [33][220/241] eta: 0:00:01 time: 0.0525 data_time: 0.0046 memory: 1482 2022/09/07 21:04:10 - mmengine - INFO - Epoch(val) [33][240/241] eta: 0:00:00 time: 0.0520 data_time: 0.0044 memory: 1482 2022/09/07 21:04:11 - mmengine - INFO - Epoch(val) [33][241/241] acc/top1: 0.4610 acc/top5: 0.7601 acc/mean1: 0.4220 2022/09/07 21:04:11 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_32.pth is removed 2022/09/07 21:04:13 - mmengine - INFO - The best checkpoint with 0.4610 acc/top1 at 33 epoch is saved to best_acc/top1_epoch_33.pth. 2022/09/07 21:04:16 - mmengine - INFO - Epoch(train) [34][20/1793] lr: 7.5000e-04 eta: 2:36:15 time: 0.1782 data_time: 0.0099 memory: 10464 grad_norm: 7.6741 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.7314 loss: 1.7314 2022/09/07 21:04:20 - mmengine - INFO - Epoch(train) [34][40/1793] lr: 7.5000e-04 eta: 2:36:08 time: 0.1705 data_time: 0.0063 memory: 10464 grad_norm: 7.4442 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5045 loss: 1.5045 2022/09/07 21:04:23 - mmengine - INFO - Epoch(train) [34][60/1793] lr: 7.5000e-04 eta: 2:36:00 time: 0.1763 data_time: 0.0071 memory: 10464 grad_norm: 8.0262 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 1.5596 loss: 1.5596 2022/09/07 21:04:27 - mmengine - INFO - Epoch(train) [34][80/1793] lr: 7.5000e-04 eta: 2:35:53 time: 0.1720 data_time: 0.0087 memory: 10464 grad_norm: 7.7407 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4365 loss: 1.4365 2022/09/07 21:04:30 - mmengine - INFO - Epoch(train) [34][100/1793] lr: 7.5000e-04 eta: 2:35:45 time: 0.1713 data_time: 0.0063 memory: 10464 grad_norm: 7.8342 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4712 loss: 1.4712 2022/09/07 21:04:34 - mmengine - INFO - Epoch(train) [34][120/1793] lr: 7.5000e-04 eta: 2:35:38 time: 0.1848 data_time: 0.0078 memory: 10464 grad_norm: 7.5475 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.5180 loss: 1.5180 2022/09/07 21:04:37 - mmengine - INFO - Epoch(train) [34][140/1793] lr: 7.5000e-04 eta: 2:35:30 time: 0.1724 data_time: 0.0083 memory: 10464 grad_norm: 7.7127 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2676 loss: 1.2676 2022/09/07 21:04:41 - mmengine - INFO - Epoch(train) [34][160/1793] lr: 7.5000e-04 eta: 2:35:23 time: 0.1712 data_time: 0.0069 memory: 10464 grad_norm: 7.7510 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2589 loss: 1.2589 2022/09/07 21:04:44 - mmengine - INFO - Epoch(train) [34][180/1793] lr: 7.5000e-04 eta: 2:35:15 time: 0.1723 data_time: 0.0064 memory: 10464 grad_norm: 7.9378 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2165 loss: 1.2165 2022/09/07 21:04:48 - mmengine - INFO - Epoch(train) [34][200/1793] lr: 7.5000e-04 eta: 2:35:08 time: 0.1729 data_time: 0.0084 memory: 10464 grad_norm: 7.5984 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1733 loss: 1.1733 2022/09/07 21:04:52 - mmengine - INFO - Epoch(train) [34][220/1793] lr: 7.5000e-04 eta: 2:35:00 time: 0.1988 data_time: 0.0084 memory: 10464 grad_norm: 7.4075 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3692 loss: 1.3692 2022/09/07 21:04:55 - mmengine - INFO - Epoch(train) [34][240/1793] lr: 7.5000e-04 eta: 2:34:53 time: 0.1709 data_time: 0.0063 memory: 10464 grad_norm: 7.7047 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3556 loss: 1.3556 2022/09/07 21:04:59 - mmengine - INFO - Epoch(train) [34][260/1793] lr: 7.5000e-04 eta: 2:34:45 time: 0.1742 data_time: 0.0094 memory: 10464 grad_norm: 8.0240 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.4485 loss: 1.4485 2022/09/07 21:05:02 - mmengine - INFO - Epoch(train) [34][280/1793] lr: 7.5000e-04 eta: 2:34:38 time: 0.1721 data_time: 0.0061 memory: 10464 grad_norm: 7.8728 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3179 loss: 1.3179 2022/09/07 21:05:05 - mmengine - INFO - Epoch(train) [34][300/1793] lr: 7.5000e-04 eta: 2:34:30 time: 0.1718 data_time: 0.0074 memory: 10464 grad_norm: 7.6533 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4268 loss: 1.4268 2022/09/07 21:05:09 - mmengine - INFO - Epoch(train) [34][320/1793] lr: 7.5000e-04 eta: 2:34:23 time: 0.1917 data_time: 0.0088 memory: 10464 grad_norm: 7.6941 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3868 loss: 1.3868 2022/09/07 21:05:13 - mmengine - INFO - Epoch(train) [34][340/1793] lr: 7.5000e-04 eta: 2:34:16 time: 0.1873 data_time: 0.0071 memory: 10464 grad_norm: 8.0600 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5404 loss: 1.5404 2022/09/07 21:05:16 - mmengine - INFO - Epoch(train) [34][360/1793] lr: 7.5000e-04 eta: 2:34:08 time: 0.1718 data_time: 0.0065 memory: 10464 grad_norm: 7.6162 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4517 loss: 1.4517 2022/09/07 21:05:20 - mmengine - INFO - Epoch(train) [34][380/1793] lr: 7.5000e-04 eta: 2:34:01 time: 0.1732 data_time: 0.0088 memory: 10464 grad_norm: 8.1247 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.8948 loss: 1.8948 2022/09/07 21:05:23 - mmengine - INFO - Epoch(train) [34][400/1793] lr: 7.5000e-04 eta: 2:33:53 time: 0.1703 data_time: 0.0062 memory: 10464 grad_norm: 7.7021 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3808 loss: 1.3808 2022/09/07 21:05:27 - mmengine - INFO - Epoch(train) [34][420/1793] lr: 7.5000e-04 eta: 2:33:46 time: 0.1756 data_time: 0.0070 memory: 10464 grad_norm: 8.0454 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4103 loss: 1.4103 2022/09/07 21:05:30 - mmengine - INFO - Epoch(train) [34][440/1793] lr: 7.5000e-04 eta: 2:33:38 time: 0.1762 data_time: 0.0084 memory: 10464 grad_norm: 7.5028 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4584 loss: 1.4584 2022/09/07 21:05:34 - mmengine - INFO - Epoch(train) [34][460/1793] lr: 7.5000e-04 eta: 2:33:31 time: 0.1703 data_time: 0.0061 memory: 10464 grad_norm: 7.7098 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2971 loss: 1.2971 2022/09/07 21:05:37 - mmengine - INFO - Epoch(train) [34][480/1793] lr: 7.5000e-04 eta: 2:33:23 time: 0.1704 data_time: 0.0066 memory: 10464 grad_norm: 7.9570 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.4803 loss: 1.4803 2022/09/07 21:05:41 - mmengine - INFO - Epoch(train) [34][500/1793] lr: 7.5000e-04 eta: 2:33:16 time: 0.1721 data_time: 0.0087 memory: 10464 grad_norm: 7.8728 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.3636 loss: 1.3636 2022/09/07 21:05:44 - mmengine - INFO - Epoch(train) [34][520/1793] lr: 7.5000e-04 eta: 2:33:08 time: 0.1890 data_time: 0.0068 memory: 10464 grad_norm: 7.9593 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 1.3032 loss: 1.3032 2022/09/07 21:05:48 - mmengine - INFO - Epoch(train) [34][540/1793] lr: 7.5000e-04 eta: 2:33:01 time: 0.1709 data_time: 0.0064 memory: 10464 grad_norm: 7.9479 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5017 loss: 1.5017 2022/09/07 21:05:51 - mmengine - INFO - Epoch(train) [34][560/1793] lr: 7.5000e-04 eta: 2:32:53 time: 0.1794 data_time: 0.0091 memory: 10464 grad_norm: 7.9129 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3234 loss: 1.3234 2022/09/07 21:05:55 - mmengine - INFO - Epoch(train) [34][580/1793] lr: 7.5000e-04 eta: 2:32:46 time: 0.1709 data_time: 0.0069 memory: 10464 grad_norm: 7.9305 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3879 loss: 1.3879 2022/09/07 21:05:58 - mmengine - INFO - Epoch(train) [34][600/1793] lr: 7.5000e-04 eta: 2:32:38 time: 0.1702 data_time: 0.0061 memory: 10464 grad_norm: 7.8572 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.3921 loss: 1.3921 2022/09/07 21:06:02 - mmengine - INFO - Epoch(train) [34][620/1793] lr: 7.5000e-04 eta: 2:32:31 time: 0.1781 data_time: 0.0094 memory: 10464 grad_norm: 8.0058 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2182 loss: 1.2182 2022/09/07 21:06:05 - mmengine - INFO - Epoch(train) [34][640/1793] lr: 7.5000e-04 eta: 2:32:24 time: 0.1709 data_time: 0.0075 memory: 10464 grad_norm: 7.8219 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4098 loss: 1.4098 2022/09/07 21:06:09 - mmengine - INFO - Epoch(train) [34][660/1793] lr: 7.5000e-04 eta: 2:32:16 time: 0.1759 data_time: 0.0061 memory: 10464 grad_norm: 7.7104 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3279 loss: 1.3279 2022/09/07 21:06:12 - mmengine - INFO - Epoch(train) [34][680/1793] lr: 7.5000e-04 eta: 2:32:09 time: 0.1771 data_time: 0.0101 memory: 10464 grad_norm: 8.3235 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3362 loss: 1.3362 2022/09/07 21:06:16 - mmengine - INFO - Epoch(train) [34][700/1793] lr: 7.5000e-04 eta: 2:32:01 time: 0.1698 data_time: 0.0062 memory: 10464 grad_norm: 7.9037 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4444 loss: 1.4444 2022/09/07 21:06:19 - mmengine - INFO - Epoch(train) [34][720/1793] lr: 7.5000e-04 eta: 2:31:54 time: 0.1711 data_time: 0.0064 memory: 10464 grad_norm: 7.8294 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.1387 loss: 1.1387 2022/09/07 21:06:23 - mmengine - INFO - Epoch(train) [34][740/1793] lr: 7.5000e-04 eta: 2:31:46 time: 0.1753 data_time: 0.0105 memory: 10464 grad_norm: 7.9631 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5123 loss: 1.5123 2022/09/07 21:06:26 - mmengine - INFO - Epoch(train) [34][760/1793] lr: 7.5000e-04 eta: 2:31:39 time: 0.1701 data_time: 0.0062 memory: 10464 grad_norm: 7.8686 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5061 loss: 1.5061 2022/09/07 21:06:30 - mmengine - INFO - Epoch(train) [34][780/1793] lr: 7.5000e-04 eta: 2:31:31 time: 0.1759 data_time: 0.0065 memory: 10464 grad_norm: 7.8646 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6753 loss: 1.6753 2022/09/07 21:06:33 - mmengine - INFO - Epoch(train) [34][800/1793] lr: 7.5000e-04 eta: 2:31:24 time: 0.1745 data_time: 0.0091 memory: 10464 grad_norm: 7.9808 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3083 loss: 1.3083 2022/09/07 21:06:37 - mmengine - INFO - Epoch(train) [34][820/1793] lr: 7.5000e-04 eta: 2:31:17 time: 0.1707 data_time: 0.0062 memory: 10464 grad_norm: 7.8394 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.4743 loss: 1.4743 2022/09/07 21:06:38 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:06:40 - mmengine - INFO - Epoch(train) [34][840/1793] lr: 7.5000e-04 eta: 2:31:09 time: 0.1731 data_time: 0.0069 memory: 10464 grad_norm: 7.8070 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.2987 loss: 1.2987 2022/09/07 21:06:43 - mmengine - INFO - Epoch(train) [34][860/1793] lr: 7.5000e-04 eta: 2:31:02 time: 0.1731 data_time: 0.0096 memory: 10464 grad_norm: 8.1715 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4289 loss: 1.4289 2022/09/07 21:06:47 - mmengine - INFO - Epoch(train) [34][880/1793] lr: 7.5000e-04 eta: 2:30:54 time: 0.1717 data_time: 0.0078 memory: 10464 grad_norm: 7.6467 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.0295 loss: 1.0295 2022/09/07 21:06:50 - mmengine - INFO - Epoch(train) [34][900/1793] lr: 7.5000e-04 eta: 2:30:47 time: 0.1708 data_time: 0.0059 memory: 10464 grad_norm: 7.7105 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.4935 loss: 1.4935 2022/09/07 21:06:54 - mmengine - INFO - Epoch(train) [34][920/1793] lr: 7.5000e-04 eta: 2:30:40 time: 0.1919 data_time: 0.0089 memory: 10464 grad_norm: 7.8780 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3001 loss: 1.3001 2022/09/07 21:06:58 - mmengine - INFO - Epoch(train) [34][940/1793] lr: 7.5000e-04 eta: 2:30:32 time: 0.1705 data_time: 0.0062 memory: 10464 grad_norm: 8.0239 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.5467 loss: 1.5467 2022/09/07 21:07:01 - mmengine - INFO - Epoch(train) [34][960/1793] lr: 7.5000e-04 eta: 2:30:25 time: 0.1732 data_time: 0.0061 memory: 10464 grad_norm: 8.0486 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3928 loss: 1.3928 2022/09/07 21:07:05 - mmengine - INFO - Epoch(train) [34][980/1793] lr: 7.5000e-04 eta: 2:30:17 time: 0.1742 data_time: 0.0090 memory: 10464 grad_norm: 8.1555 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5155 loss: 1.5155 2022/09/07 21:07:08 - mmengine - INFO - Epoch(train) [34][1000/1793] lr: 7.5000e-04 eta: 2:30:10 time: 0.1701 data_time: 0.0068 memory: 10464 grad_norm: 7.8291 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5105 loss: 1.5105 2022/09/07 21:07:12 - mmengine - INFO - Epoch(train) [34][1020/1793] lr: 7.5000e-04 eta: 2:30:03 time: 0.1871 data_time: 0.0063 memory: 10464 grad_norm: 7.9905 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 1.4099 loss: 1.4099 2022/09/07 21:07:15 - mmengine - INFO - Epoch(train) [34][1040/1793] lr: 7.5000e-04 eta: 2:29:55 time: 0.1734 data_time: 0.0087 memory: 10464 grad_norm: 7.8883 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.6581 loss: 1.6581 2022/09/07 21:07:19 - mmengine - INFO - Epoch(train) [34][1060/1793] lr: 7.5000e-04 eta: 2:29:48 time: 0.1706 data_time: 0.0063 memory: 10464 grad_norm: 7.9275 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0543 loss: 1.0543 2022/09/07 21:07:22 - mmengine - INFO - Epoch(train) [34][1080/1793] lr: 7.5000e-04 eta: 2:29:40 time: 0.1736 data_time: 0.0068 memory: 10464 grad_norm: 7.9018 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1760 loss: 1.1760 2022/09/07 21:07:26 - mmengine - INFO - Epoch(train) [34][1100/1793] lr: 7.5000e-04 eta: 2:29:33 time: 0.1730 data_time: 0.0088 memory: 10464 grad_norm: 7.9965 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3926 loss: 1.3926 2022/09/07 21:07:29 - mmengine - INFO - Epoch(train) [34][1120/1793] lr: 7.5000e-04 eta: 2:29:26 time: 0.1723 data_time: 0.0061 memory: 10464 grad_norm: 7.9874 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.6831 loss: 1.6831 2022/09/07 21:07:32 - mmengine - INFO - Epoch(train) [34][1140/1793] lr: 7.5000e-04 eta: 2:29:18 time: 0.1734 data_time: 0.0062 memory: 10464 grad_norm: 8.0981 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3485 loss: 1.3485 2022/09/07 21:07:36 - mmengine - INFO - Epoch(train) [34][1160/1793] lr: 7.5000e-04 eta: 2:29:11 time: 0.1745 data_time: 0.0094 memory: 10464 grad_norm: 7.8923 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.2969 loss: 1.2969 2022/09/07 21:07:39 - mmengine - INFO - Epoch(train) [34][1180/1793] lr: 7.5000e-04 eta: 2:29:03 time: 0.1713 data_time: 0.0060 memory: 10464 grad_norm: 7.7383 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3482 loss: 1.3482 2022/09/07 21:07:43 - mmengine - INFO - Epoch(train) [34][1200/1793] lr: 7.5000e-04 eta: 2:28:56 time: 0.1776 data_time: 0.0071 memory: 10464 grad_norm: 8.1229 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5926 loss: 1.5926 2022/09/07 21:07:46 - mmengine - INFO - Epoch(train) [34][1220/1793] lr: 7.5000e-04 eta: 2:28:49 time: 0.1739 data_time: 0.0094 memory: 10464 grad_norm: 8.1260 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.4481 loss: 1.4481 2022/09/07 21:07:50 - mmengine - INFO - Epoch(train) [34][1240/1793] lr: 7.5000e-04 eta: 2:28:41 time: 0.1743 data_time: 0.0062 memory: 10464 grad_norm: 7.8684 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4411 loss: 1.4411 2022/09/07 21:07:53 - mmengine - INFO - Epoch(train) [34][1260/1793] lr: 7.5000e-04 eta: 2:28:34 time: 0.1717 data_time: 0.0065 memory: 10464 grad_norm: 7.8069 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.4021 loss: 1.4021 2022/09/07 21:07:57 - mmengine - INFO - Epoch(train) [34][1280/1793] lr: 7.5000e-04 eta: 2:28:27 time: 0.1743 data_time: 0.0086 memory: 10464 grad_norm: 7.9666 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2380 loss: 1.2380 2022/09/07 21:08:00 - mmengine - INFO - Epoch(train) [34][1300/1793] lr: 7.5000e-04 eta: 2:28:19 time: 0.1710 data_time: 0.0062 memory: 10464 grad_norm: 7.9705 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.5166 loss: 1.5166 2022/09/07 21:08:04 - mmengine - INFO - Epoch(train) [34][1320/1793] lr: 7.5000e-04 eta: 2:28:12 time: 0.1759 data_time: 0.0066 memory: 10464 grad_norm: 7.9991 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.4362 loss: 1.4362 2022/09/07 21:08:07 - mmengine - INFO - Epoch(train) [34][1340/1793] lr: 7.5000e-04 eta: 2:28:04 time: 0.1727 data_time: 0.0084 memory: 10464 grad_norm: 7.9502 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1771 loss: 1.1771 2022/09/07 21:08:11 - mmengine - INFO - Epoch(train) [34][1360/1793] lr: 7.5000e-04 eta: 2:27:57 time: 0.1877 data_time: 0.0060 memory: 10464 grad_norm: 8.0372 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5349 loss: 1.5349 2022/09/07 21:08:15 - mmengine - INFO - Epoch(train) [34][1380/1793] lr: 7.5000e-04 eta: 2:27:50 time: 0.1757 data_time: 0.0072 memory: 10464 grad_norm: 7.9202 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3905 loss: 1.3905 2022/09/07 21:08:18 - mmengine - INFO - Epoch(train) [34][1400/1793] lr: 7.5000e-04 eta: 2:27:43 time: 0.1735 data_time: 0.0084 memory: 10464 grad_norm: 7.7823 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4247 loss: 1.4247 2022/09/07 21:08:21 - mmengine - INFO - Epoch(train) [34][1420/1793] lr: 7.5000e-04 eta: 2:27:35 time: 0.1732 data_time: 0.0067 memory: 10464 grad_norm: 8.2216 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.3196 loss: 1.3196 2022/09/07 21:08:25 - mmengine - INFO - Epoch(train) [34][1440/1793] lr: 7.5000e-04 eta: 2:27:28 time: 0.1718 data_time: 0.0079 memory: 10464 grad_norm: 7.8450 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.5231 loss: 1.5231 2022/09/07 21:08:28 - mmengine - INFO - Epoch(train) [34][1460/1793] lr: 7.5000e-04 eta: 2:27:20 time: 0.1733 data_time: 0.0084 memory: 10464 grad_norm: 7.8245 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4118 loss: 1.4118 2022/09/07 21:08:32 - mmengine - INFO - Epoch(train) [34][1480/1793] lr: 7.5000e-04 eta: 2:27:13 time: 0.1778 data_time: 0.0065 memory: 10464 grad_norm: 8.2407 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3177 loss: 1.3177 2022/09/07 21:08:35 - mmengine - INFO - Epoch(train) [34][1500/1793] lr: 7.5000e-04 eta: 2:27:06 time: 0.1704 data_time: 0.0062 memory: 10464 grad_norm: 8.1827 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4457 loss: 1.4457 2022/09/07 21:08:39 - mmengine - INFO - Epoch(train) [34][1520/1793] lr: 7.5000e-04 eta: 2:26:58 time: 0.1756 data_time: 0.0091 memory: 10464 grad_norm: 7.9255 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6127 loss: 1.6127 2022/09/07 21:08:43 - mmengine - INFO - Epoch(train) [34][1540/1793] lr: 7.5000e-04 eta: 2:26:51 time: 0.1820 data_time: 0.0071 memory: 10464 grad_norm: 8.1276 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3529 loss: 1.3529 2022/09/07 21:08:46 - mmengine - INFO - Epoch(train) [34][1560/1793] lr: 7.5000e-04 eta: 2:26:44 time: 0.1700 data_time: 0.0062 memory: 10464 grad_norm: 7.9605 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.3208 loss: 1.3208 2022/09/07 21:08:50 - mmengine - INFO - Epoch(train) [34][1580/1793] lr: 7.5000e-04 eta: 2:26:37 time: 0.1810 data_time: 0.0092 memory: 10464 grad_norm: 8.2935 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.5643 loss: 1.5643 2022/09/07 21:08:53 - mmengine - INFO - Epoch(train) [34][1600/1793] lr: 7.5000e-04 eta: 2:26:29 time: 0.1715 data_time: 0.0065 memory: 10464 grad_norm: 7.8938 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3018 loss: 1.3018 2022/09/07 21:08:56 - mmengine - INFO - Epoch(train) [34][1620/1793] lr: 7.5000e-04 eta: 2:26:22 time: 0.1712 data_time: 0.0077 memory: 10464 grad_norm: 8.0921 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4196 loss: 1.4196 2022/09/07 21:09:00 - mmengine - INFO - Epoch(train) [34][1640/1793] lr: 7.5000e-04 eta: 2:26:15 time: 0.1737 data_time: 0.0086 memory: 10464 grad_norm: 8.0298 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2703 loss: 1.2703 2022/09/07 21:09:03 - mmengine - INFO - Epoch(train) [34][1660/1793] lr: 7.5000e-04 eta: 2:26:07 time: 0.1739 data_time: 0.0069 memory: 10464 grad_norm: 8.1960 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.4235 loss: 1.4235 2022/09/07 21:09:07 - mmengine - INFO - Epoch(train) [34][1680/1793] lr: 7.5000e-04 eta: 2:26:00 time: 0.1703 data_time: 0.0067 memory: 10464 grad_norm: 8.2290 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.5031 loss: 1.5031 2022/09/07 21:09:10 - mmengine - INFO - Epoch(train) [34][1700/1793] lr: 7.5000e-04 eta: 2:25:53 time: 0.1812 data_time: 0.0086 memory: 10464 grad_norm: 8.2285 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.5434 loss: 1.5434 2022/09/07 21:09:14 - mmengine - INFO - Epoch(train) [34][1720/1793] lr: 7.5000e-04 eta: 2:25:45 time: 0.1844 data_time: 0.0069 memory: 10464 grad_norm: 8.0634 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3491 loss: 1.3491 2022/09/07 21:09:18 - mmengine - INFO - Epoch(train) [34][1740/1793] lr: 7.5000e-04 eta: 2:25:38 time: 0.1725 data_time: 0.0062 memory: 10464 grad_norm: 7.8955 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2228 loss: 1.2228 2022/09/07 21:09:21 - mmengine - INFO - Epoch(train) [34][1760/1793] lr: 7.5000e-04 eta: 2:25:31 time: 0.1722 data_time: 0.0085 memory: 10464 grad_norm: 8.4566 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1515 loss: 1.1515 2022/09/07 21:09:24 - mmengine - INFO - Epoch(train) [34][1780/1793] lr: 7.5000e-04 eta: 2:25:23 time: 0.1731 data_time: 0.0068 memory: 10464 grad_norm: 8.2617 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5630 loss: 1.5630 2022/09/07 21:09:27 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:09:27 - mmengine - INFO - Epoch(train) [34][1793/1793] lr: 7.5000e-04 eta: 2:25:23 time: 0.1666 data_time: 0.0069 memory: 10464 grad_norm: 8.8237 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 1.3678 loss: 1.3678 2022/09/07 21:09:27 - mmengine - INFO - Saving checkpoint at 34 epochs 2022/09/07 21:09:30 - mmengine - INFO - Epoch(val) [34][20/241] eta: 0:00:13 time: 0.0628 data_time: 0.0134 memory: 1482 2022/09/07 21:09:31 - mmengine - INFO - Epoch(val) [34][40/241] eta: 0:00:10 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 21:09:32 - mmengine - INFO - Epoch(val) [34][60/241] eta: 0:00:09 time: 0.0535 data_time: 0.0051 memory: 1482 2022/09/07 21:09:33 - mmengine - INFO - Epoch(val) [34][80/241] eta: 0:00:08 time: 0.0532 data_time: 0.0049 memory: 1482 2022/09/07 21:09:34 - mmengine - INFO - Epoch(val) [34][100/241] eta: 0:00:07 time: 0.0530 data_time: 0.0048 memory: 1482 2022/09/07 21:09:35 - mmengine - INFO - Epoch(val) [34][120/241] eta: 0:00:06 time: 0.0528 data_time: 0.0047 memory: 1482 2022/09/07 21:09:36 - mmengine - INFO - Epoch(val) [34][140/241] eta: 0:00:05 time: 0.0550 data_time: 0.0065 memory: 1482 2022/09/07 21:09:38 - mmengine - INFO - Epoch(val) [34][160/241] eta: 0:00:04 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 21:09:39 - mmengine - INFO - Epoch(val) [34][180/241] eta: 0:00:03 time: 0.0530 data_time: 0.0047 memory: 1482 2022/09/07 21:09:40 - mmengine - INFO - Epoch(val) [34][200/241] eta: 0:00:02 time: 0.0539 data_time: 0.0054 memory: 1482 2022/09/07 21:09:41 - mmengine - INFO - Epoch(val) [34][220/241] eta: 0:00:01 time: 0.0538 data_time: 0.0054 memory: 1482 2022/09/07 21:09:42 - mmengine - INFO - Epoch(val) [34][240/241] eta: 0:00:00 time: 0.0595 data_time: 0.0063 memory: 1482 2022/09/07 21:09:42 - mmengine - INFO - Epoch(val) [34][241/241] acc/top1: 0.4631 acc/top5: 0.7554 acc/mean1: 0.4256 2022/09/07 21:09:43 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_33.pth is removed 2022/09/07 21:09:44 - mmengine - INFO - The best checkpoint with 0.4631 acc/top1 at 34 epoch is saved to best_acc/top1_epoch_34.pth. 2022/09/07 21:09:48 - mmengine - INFO - Epoch(train) [35][20/1793] lr: 7.5000e-04 eta: 2:25:10 time: 0.1769 data_time: 0.0099 memory: 10464 grad_norm: 8.1258 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2950 loss: 1.2950 2022/09/07 21:09:51 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:09:51 - mmengine - INFO - Epoch(train) [35][40/1793] lr: 7.5000e-04 eta: 2:25:03 time: 0.1712 data_time: 0.0061 memory: 10464 grad_norm: 8.1590 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4249 loss: 1.4249 2022/09/07 21:09:55 - mmengine - INFO - Epoch(train) [35][60/1793] lr: 7.5000e-04 eta: 2:24:56 time: 0.1707 data_time: 0.0064 memory: 10464 grad_norm: 7.7037 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2389 loss: 1.2389 2022/09/07 21:09:58 - mmengine - INFO - Epoch(train) [35][80/1793] lr: 7.5000e-04 eta: 2:24:48 time: 0.1737 data_time: 0.0098 memory: 10464 grad_norm: 8.3474 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3915 loss: 1.3915 2022/09/07 21:10:02 - mmengine - INFO - Epoch(train) [35][100/1793] lr: 7.5000e-04 eta: 2:24:41 time: 0.1747 data_time: 0.0065 memory: 10464 grad_norm: 8.3233 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2186 loss: 1.2186 2022/09/07 21:10:05 - mmengine - INFO - Epoch(train) [35][120/1793] lr: 7.5000e-04 eta: 2:24:34 time: 0.1724 data_time: 0.0083 memory: 10464 grad_norm: 8.1088 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4661 loss: 1.4661 2022/09/07 21:10:09 - mmengine - INFO - Epoch(train) [35][140/1793] lr: 7.5000e-04 eta: 2:24:27 time: 0.1740 data_time: 0.0097 memory: 10464 grad_norm: 8.0019 top1_acc: 0.1667 top5_acc: 1.0000 loss_cls: 1.4018 loss: 1.4018 2022/09/07 21:10:12 - mmengine - INFO - Epoch(train) [35][160/1793] lr: 7.5000e-04 eta: 2:24:19 time: 0.1866 data_time: 0.0066 memory: 10464 grad_norm: 8.4733 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.4619 loss: 1.4619 2022/09/07 21:10:16 - mmengine - INFO - Epoch(train) [35][180/1793] lr: 7.5000e-04 eta: 2:24:12 time: 0.1719 data_time: 0.0063 memory: 10464 grad_norm: 7.9980 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3018 loss: 1.3018 2022/09/07 21:10:19 - mmengine - INFO - Epoch(train) [35][200/1793] lr: 7.5000e-04 eta: 2:24:05 time: 0.1756 data_time: 0.0089 memory: 10464 grad_norm: 8.2792 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1615 loss: 1.1615 2022/09/07 21:10:23 - mmengine - INFO - Epoch(train) [35][220/1793] lr: 7.5000e-04 eta: 2:23:58 time: 0.1777 data_time: 0.0069 memory: 10464 grad_norm: 8.2705 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4776 loss: 1.4776 2022/09/07 21:10:26 - mmengine - INFO - Epoch(train) [35][240/1793] lr: 7.5000e-04 eta: 2:23:50 time: 0.1725 data_time: 0.0072 memory: 10464 grad_norm: 7.7202 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.3996 loss: 1.3996 2022/09/07 21:10:30 - mmengine - INFO - Epoch(train) [35][260/1793] lr: 7.5000e-04 eta: 2:23:43 time: 0.1764 data_time: 0.0092 memory: 10464 grad_norm: 7.8690 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2776 loss: 1.2776 2022/09/07 21:10:33 - mmengine - INFO - Epoch(train) [35][280/1793] lr: 7.5000e-04 eta: 2:23:36 time: 0.1716 data_time: 0.0067 memory: 10464 grad_norm: 7.7593 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.5071 loss: 1.5071 2022/09/07 21:10:37 - mmengine - INFO - Epoch(train) [35][300/1793] lr: 7.5000e-04 eta: 2:23:28 time: 0.1707 data_time: 0.0060 memory: 10464 grad_norm: 7.9990 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.4055 loss: 1.4055 2022/09/07 21:10:40 - mmengine - INFO - Epoch(train) [35][320/1793] lr: 7.5000e-04 eta: 2:23:21 time: 0.1730 data_time: 0.0088 memory: 10464 grad_norm: 8.1111 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.4667 loss: 1.4667 2022/09/07 21:10:44 - mmengine - INFO - Epoch(train) [35][340/1793] lr: 7.5000e-04 eta: 2:23:14 time: 0.1788 data_time: 0.0068 memory: 10464 grad_norm: 8.4108 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4213 loss: 1.4213 2022/09/07 21:10:47 - mmengine - INFO - Epoch(train) [35][360/1793] lr: 7.5000e-04 eta: 2:23:07 time: 0.1712 data_time: 0.0063 memory: 10464 grad_norm: 8.2468 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2946 loss: 1.2946 2022/09/07 21:10:51 - mmengine - INFO - Epoch(train) [35][380/1793] lr: 7.5000e-04 eta: 2:22:59 time: 0.1779 data_time: 0.0084 memory: 10464 grad_norm: 7.9862 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.6240 loss: 1.6240 2022/09/07 21:10:54 - mmengine - INFO - Epoch(train) [35][400/1793] lr: 7.5000e-04 eta: 2:22:52 time: 0.1715 data_time: 0.0072 memory: 10464 grad_norm: 7.9519 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.3869 loss: 1.3869 2022/09/07 21:10:58 - mmengine - INFO - Epoch(train) [35][420/1793] lr: 7.5000e-04 eta: 2:22:45 time: 0.1727 data_time: 0.0070 memory: 10464 grad_norm: 8.0506 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1282 loss: 1.1282 2022/09/07 21:11:01 - mmengine - INFO - Epoch(train) [35][440/1793] lr: 7.5000e-04 eta: 2:22:38 time: 0.1817 data_time: 0.0083 memory: 10464 grad_norm: 8.7613 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2908 loss: 1.2908 2022/09/07 21:11:05 - mmengine - INFO - Epoch(train) [35][460/1793] lr: 7.5000e-04 eta: 2:22:31 time: 0.1845 data_time: 0.0070 memory: 10464 grad_norm: 8.3896 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4064 loss: 1.4064 2022/09/07 21:11:08 - mmengine - INFO - Epoch(train) [35][480/1793] lr: 7.5000e-04 eta: 2:22:23 time: 0.1697 data_time: 0.0063 memory: 10464 grad_norm: 8.2874 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.2597 loss: 1.2597 2022/09/07 21:11:12 - mmengine - INFO - Epoch(train) [35][500/1793] lr: 7.5000e-04 eta: 2:22:16 time: 0.1780 data_time: 0.0110 memory: 10464 grad_norm: 8.1288 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3945 loss: 1.3945 2022/09/07 21:11:15 - mmengine - INFO - Epoch(train) [35][520/1793] lr: 7.5000e-04 eta: 2:22:09 time: 0.1698 data_time: 0.0066 memory: 10464 grad_norm: 8.2207 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4150 loss: 1.4150 2022/09/07 21:11:19 - mmengine - INFO - Epoch(train) [35][540/1793] lr: 7.5000e-04 eta: 2:22:02 time: 0.1717 data_time: 0.0060 memory: 10464 grad_norm: 8.4429 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.2950 loss: 1.2950 2022/09/07 21:11:22 - mmengine - INFO - Epoch(train) [35][560/1793] lr: 7.5000e-04 eta: 2:21:54 time: 0.1843 data_time: 0.0086 memory: 10464 grad_norm: 8.1742 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1208 loss: 1.1208 2022/09/07 21:11:26 - mmengine - INFO - Epoch(train) [35][580/1793] lr: 7.5000e-04 eta: 2:21:47 time: 0.1701 data_time: 0.0064 memory: 10464 grad_norm: 8.4746 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2898 loss: 1.2898 2022/09/07 21:11:29 - mmengine - INFO - Epoch(train) [35][600/1793] lr: 7.5000e-04 eta: 2:21:40 time: 0.1721 data_time: 0.0064 memory: 10464 grad_norm: 8.2216 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3988 loss: 1.3988 2022/09/07 21:11:33 - mmengine - INFO - Epoch(train) [35][620/1793] lr: 7.5000e-04 eta: 2:21:33 time: 0.1756 data_time: 0.0101 memory: 10464 grad_norm: 8.1171 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4036 loss: 1.4036 2022/09/07 21:11:36 - mmengine - INFO - Epoch(train) [35][640/1793] lr: 7.5000e-04 eta: 2:21:25 time: 0.1701 data_time: 0.0064 memory: 10464 grad_norm: 8.2327 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.4162 loss: 1.4162 2022/09/07 21:11:40 - mmengine - INFO - Epoch(train) [35][660/1793] lr: 7.5000e-04 eta: 2:21:18 time: 0.1833 data_time: 0.0063 memory: 10464 grad_norm: 8.1260 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4865 loss: 1.4865 2022/09/07 21:11:43 - mmengine - INFO - Epoch(train) [35][680/1793] lr: 7.5000e-04 eta: 2:21:11 time: 0.1798 data_time: 0.0095 memory: 10464 grad_norm: 8.3893 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.3994 loss: 1.3994 2022/09/07 21:11:47 - mmengine - INFO - Epoch(train) [35][700/1793] lr: 7.5000e-04 eta: 2:21:04 time: 0.1712 data_time: 0.0062 memory: 10464 grad_norm: 7.9727 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2634 loss: 1.2634 2022/09/07 21:11:50 - mmengine - INFO - Epoch(train) [35][720/1793] lr: 7.5000e-04 eta: 2:20:57 time: 0.1730 data_time: 0.0061 memory: 10464 grad_norm: 8.3610 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.2797 loss: 1.2797 2022/09/07 21:11:54 - mmengine - INFO - Epoch(train) [35][740/1793] lr: 7.5000e-04 eta: 2:20:49 time: 0.1745 data_time: 0.0099 memory: 10464 grad_norm: 8.5712 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4310 loss: 1.4310 2022/09/07 21:11:57 - mmengine - INFO - Epoch(train) [35][760/1793] lr: 7.5000e-04 eta: 2:20:42 time: 0.1730 data_time: 0.0072 memory: 10464 grad_norm: 8.1843 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5017 loss: 1.5017 2022/09/07 21:12:01 - mmengine - INFO - Epoch(train) [35][780/1793] lr: 7.5000e-04 eta: 2:20:35 time: 0.1762 data_time: 0.0063 memory: 10464 grad_norm: 8.2600 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.3693 loss: 1.3693 2022/09/07 21:12:04 - mmengine - INFO - Epoch(train) [35][800/1793] lr: 7.5000e-04 eta: 2:20:28 time: 0.1767 data_time: 0.0094 memory: 10464 grad_norm: 8.2246 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4700 loss: 1.4700 2022/09/07 21:12:08 - mmengine - INFO - Epoch(train) [35][820/1793] lr: 7.5000e-04 eta: 2:20:21 time: 0.1697 data_time: 0.0061 memory: 10464 grad_norm: 8.1469 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4164 loss: 1.4164 2022/09/07 21:12:11 - mmengine - INFO - Epoch(train) [35][840/1793] lr: 7.5000e-04 eta: 2:20:13 time: 0.1730 data_time: 0.0061 memory: 10464 grad_norm: 8.4669 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5042 loss: 1.5042 2022/09/07 21:12:15 - mmengine - INFO - Epoch(train) [35][860/1793] lr: 7.5000e-04 eta: 2:20:06 time: 0.1759 data_time: 0.0101 memory: 10464 grad_norm: 8.2354 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0522 loss: 1.0522 2022/09/07 21:12:18 - mmengine - INFO - Epoch(train) [35][880/1793] lr: 7.5000e-04 eta: 2:19:59 time: 0.1706 data_time: 0.0063 memory: 10464 grad_norm: 8.2932 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3835 loss: 1.3835 2022/09/07 21:12:22 - mmengine - INFO - Epoch(train) [35][900/1793] lr: 7.5000e-04 eta: 2:19:52 time: 0.1745 data_time: 0.0062 memory: 10464 grad_norm: 8.0620 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4111 loss: 1.4111 2022/09/07 21:12:25 - mmengine - INFO - Epoch(train) [35][920/1793] lr: 7.5000e-04 eta: 2:19:45 time: 0.1748 data_time: 0.0090 memory: 10464 grad_norm: 8.2805 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3210 loss: 1.3210 2022/09/07 21:12:29 - mmengine - INFO - Epoch(train) [35][940/1793] lr: 7.5000e-04 eta: 2:19:37 time: 0.1711 data_time: 0.0064 memory: 10464 grad_norm: 8.0722 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4711 loss: 1.4711 2022/09/07 21:12:32 - mmengine - INFO - Epoch(train) [35][960/1793] lr: 7.5000e-04 eta: 2:19:30 time: 0.1757 data_time: 0.0075 memory: 10464 grad_norm: 8.4628 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4144 loss: 1.4144 2022/09/07 21:12:36 - mmengine - INFO - Epoch(train) [35][980/1793] lr: 7.5000e-04 eta: 2:19:23 time: 0.1741 data_time: 0.0099 memory: 10464 grad_norm: 8.1584 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4196 loss: 1.4196 2022/09/07 21:12:39 - mmengine - INFO - Epoch(train) [35][1000/1793] lr: 7.5000e-04 eta: 2:19:16 time: 0.1705 data_time: 0.0062 memory: 10464 grad_norm: 8.2279 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.4049 loss: 1.4049 2022/09/07 21:12:43 - mmengine - INFO - Epoch(train) [35][1020/1793] lr: 7.5000e-04 eta: 2:19:09 time: 0.1772 data_time: 0.0073 memory: 10464 grad_norm: 8.2295 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2613 loss: 1.2613 2022/09/07 21:12:46 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:12:46 - mmengine - INFO - Epoch(train) [35][1040/1793] lr: 7.5000e-04 eta: 2:19:02 time: 0.1719 data_time: 0.0087 memory: 10464 grad_norm: 8.3640 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.5052 loss: 1.5052 2022/09/07 21:12:49 - mmengine - INFO - Epoch(train) [35][1060/1793] lr: 7.5000e-04 eta: 2:18:54 time: 0.1737 data_time: 0.0062 memory: 10464 grad_norm: 8.5066 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2064 loss: 1.2064 2022/09/07 21:12:53 - mmengine - INFO - Epoch(train) [35][1080/1793] lr: 7.5000e-04 eta: 2:18:47 time: 0.1715 data_time: 0.0065 memory: 10464 grad_norm: 8.3125 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4590 loss: 1.4590 2022/09/07 21:12:56 - mmengine - INFO - Epoch(train) [35][1100/1793] lr: 7.5000e-04 eta: 2:18:40 time: 0.1731 data_time: 0.0088 memory: 10464 grad_norm: 8.2568 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3755 loss: 1.3755 2022/09/07 21:13:00 - mmengine - INFO - Epoch(train) [35][1120/1793] lr: 7.5000e-04 eta: 2:18:33 time: 0.1723 data_time: 0.0063 memory: 10464 grad_norm: 8.0701 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7153 loss: 1.7153 2022/09/07 21:13:03 - mmengine - INFO - Epoch(train) [35][1140/1793] lr: 7.5000e-04 eta: 2:18:26 time: 0.1730 data_time: 0.0067 memory: 10464 grad_norm: 8.7787 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5875 loss: 1.5875 2022/09/07 21:13:07 - mmengine - INFO - Epoch(train) [35][1160/1793] lr: 7.5000e-04 eta: 2:18:19 time: 0.1733 data_time: 0.0084 memory: 10464 grad_norm: 8.7928 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4702 loss: 1.4702 2022/09/07 21:13:10 - mmengine - INFO - Epoch(train) [35][1180/1793] lr: 7.5000e-04 eta: 2:18:11 time: 0.1751 data_time: 0.0063 memory: 10464 grad_norm: 8.2176 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4578 loss: 1.4578 2022/09/07 21:13:14 - mmengine - INFO - Epoch(train) [35][1200/1793] lr: 7.5000e-04 eta: 2:18:04 time: 0.1867 data_time: 0.0079 memory: 10464 grad_norm: 8.5433 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3287 loss: 1.3287 2022/09/07 21:13:17 - mmengine - INFO - Epoch(train) [35][1220/1793] lr: 7.5000e-04 eta: 2:17:57 time: 0.1725 data_time: 0.0084 memory: 10464 grad_norm: 8.1794 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.3949 loss: 1.3949 2022/09/07 21:13:21 - mmengine - INFO - Epoch(train) [35][1240/1793] lr: 7.5000e-04 eta: 2:17:50 time: 0.1717 data_time: 0.0061 memory: 10464 grad_norm: 8.4521 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2274 loss: 1.2274 2022/09/07 21:13:24 - mmengine - INFO - Epoch(train) [35][1260/1793] lr: 7.5000e-04 eta: 2:17:43 time: 0.1725 data_time: 0.0070 memory: 10464 grad_norm: 8.2737 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4038 loss: 1.4038 2022/09/07 21:13:28 - mmengine - INFO - Epoch(train) [35][1280/1793] lr: 7.5000e-04 eta: 2:17:36 time: 0.1723 data_time: 0.0086 memory: 10464 grad_norm: 8.2985 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2216 loss: 1.2216 2022/09/07 21:13:31 - mmengine - INFO - Epoch(train) [35][1300/1793] lr: 7.5000e-04 eta: 2:17:29 time: 0.1735 data_time: 0.0063 memory: 10464 grad_norm: 8.2764 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2420 loss: 1.2420 2022/09/07 21:13:35 - mmengine - INFO - Epoch(train) [35][1320/1793] lr: 7.5000e-04 eta: 2:17:21 time: 0.1757 data_time: 0.0068 memory: 10464 grad_norm: 8.1044 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.5874 loss: 1.5874 2022/09/07 21:13:38 - mmengine - INFO - Epoch(train) [35][1340/1793] lr: 7.5000e-04 eta: 2:17:14 time: 0.1733 data_time: 0.0093 memory: 10464 grad_norm: 8.5419 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5325 loss: 1.5325 2022/09/07 21:13:42 - mmengine - INFO - Epoch(train) [35][1360/1793] lr: 7.5000e-04 eta: 2:17:07 time: 0.1708 data_time: 0.0057 memory: 10464 grad_norm: 8.4107 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.4118 loss: 1.4118 2022/09/07 21:13:45 - mmengine - INFO - Epoch(train) [35][1380/1793] lr: 7.5000e-04 eta: 2:17:00 time: 0.1730 data_time: 0.0063 memory: 10464 grad_norm: 8.2311 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3829 loss: 1.3829 2022/09/07 21:13:49 - mmengine - INFO - Epoch(train) [35][1400/1793] lr: 7.5000e-04 eta: 2:16:53 time: 0.1732 data_time: 0.0084 memory: 10464 grad_norm: 8.4995 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2788 loss: 1.2788 2022/09/07 21:13:52 - mmengine - INFO - Epoch(train) [35][1420/1793] lr: 7.5000e-04 eta: 2:16:46 time: 0.1803 data_time: 0.0073 memory: 10464 grad_norm: 8.1622 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6393 loss: 1.6393 2022/09/07 21:13:56 - mmengine - INFO - Epoch(train) [35][1440/1793] lr: 7.5000e-04 eta: 2:16:39 time: 0.1698 data_time: 0.0064 memory: 10464 grad_norm: 8.2810 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4760 loss: 1.4760 2022/09/07 21:13:59 - mmengine - INFO - Epoch(train) [35][1460/1793] lr: 7.5000e-04 eta: 2:16:31 time: 0.1729 data_time: 0.0095 memory: 10464 grad_norm: 8.0791 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2922 loss: 1.2922 2022/09/07 21:14:03 - mmengine - INFO - Epoch(train) [35][1480/1793] lr: 7.5000e-04 eta: 2:16:24 time: 0.1725 data_time: 0.0066 memory: 10464 grad_norm: 8.6906 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2107 loss: 1.2107 2022/09/07 21:14:06 - mmengine - INFO - Epoch(train) [35][1500/1793] lr: 7.5000e-04 eta: 2:16:17 time: 0.1706 data_time: 0.0068 memory: 10464 grad_norm: 8.4212 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2713 loss: 1.2713 2022/09/07 21:14:09 - mmengine - INFO - Epoch(train) [35][1520/1793] lr: 7.5000e-04 eta: 2:16:10 time: 0.1742 data_time: 0.0092 memory: 10464 grad_norm: 8.3489 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3809 loss: 1.3809 2022/09/07 21:14:13 - mmengine - INFO - Epoch(train) [35][1540/1793] lr: 7.5000e-04 eta: 2:16:03 time: 0.1783 data_time: 0.0073 memory: 10464 grad_norm: 8.2276 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.2882 loss: 1.2882 2022/09/07 21:14:16 - mmengine - INFO - Epoch(train) [35][1560/1793] lr: 7.5000e-04 eta: 2:15:56 time: 0.1701 data_time: 0.0065 memory: 10464 grad_norm: 8.5758 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3402 loss: 1.3402 2022/09/07 21:14:20 - mmengine - INFO - Epoch(train) [35][1580/1793] lr: 7.5000e-04 eta: 2:15:49 time: 0.1766 data_time: 0.0091 memory: 10464 grad_norm: 8.2106 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.6537 loss: 1.6537 2022/09/07 21:14:23 - mmengine - INFO - Epoch(train) [35][1600/1793] lr: 7.5000e-04 eta: 2:15:42 time: 0.1715 data_time: 0.0062 memory: 10464 grad_norm: 8.1194 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2419 loss: 1.2419 2022/09/07 21:14:27 - mmengine - INFO - Epoch(train) [35][1620/1793] lr: 7.5000e-04 eta: 2:15:34 time: 0.1712 data_time: 0.0066 memory: 10464 grad_norm: 8.3648 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2557 loss: 1.2557 2022/09/07 21:14:30 - mmengine - INFO - Epoch(train) [35][1640/1793] lr: 7.5000e-04 eta: 2:15:27 time: 0.1761 data_time: 0.0101 memory: 10464 grad_norm: 8.4599 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5430 loss: 1.5430 2022/09/07 21:14:34 - mmengine - INFO - Epoch(train) [35][1660/1793] lr: 7.5000e-04 eta: 2:15:20 time: 0.1756 data_time: 0.0074 memory: 10464 grad_norm: 8.4305 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2789 loss: 1.2789 2022/09/07 21:14:37 - mmengine - INFO - Epoch(train) [35][1680/1793] lr: 7.5000e-04 eta: 2:15:13 time: 0.1712 data_time: 0.0066 memory: 10464 grad_norm: 8.6192 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3466 loss: 1.3466 2022/09/07 21:14:41 - mmengine - INFO - Epoch(train) [35][1700/1793] lr: 7.5000e-04 eta: 2:15:06 time: 0.1749 data_time: 0.0086 memory: 10464 grad_norm: 8.3220 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3502 loss: 1.3502 2022/09/07 21:14:44 - mmengine - INFO - Epoch(train) [35][1720/1793] lr: 7.5000e-04 eta: 2:14:59 time: 0.1768 data_time: 0.0072 memory: 10464 grad_norm: 8.2428 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.2909 loss: 1.2909 2022/09/07 21:14:48 - mmengine - INFO - Epoch(train) [35][1740/1793] lr: 7.5000e-04 eta: 2:14:52 time: 0.1715 data_time: 0.0063 memory: 10464 grad_norm: 8.8794 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5219 loss: 1.5219 2022/09/07 21:14:51 - mmengine - INFO - Epoch(train) [35][1760/1793] lr: 7.5000e-04 eta: 2:14:45 time: 0.1733 data_time: 0.0086 memory: 10464 grad_norm: 8.1783 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.3970 loss: 1.3970 2022/09/07 21:14:55 - mmengine - INFO - Epoch(train) [35][1780/1793] lr: 7.5000e-04 eta: 2:14:38 time: 0.1770 data_time: 0.0073 memory: 10464 grad_norm: 8.3321 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2625 loss: 1.2625 2022/09/07 21:14:57 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:14:57 - mmengine - INFO - Epoch(train) [35][1793/1793] lr: 7.5000e-04 eta: 2:14:38 time: 0.1667 data_time: 0.0064 memory: 10464 grad_norm: 8.9625 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 1.3986 loss: 1.3986 2022/09/07 21:14:57 - mmengine - INFO - Saving checkpoint at 35 epochs 2022/09/07 21:15:01 - mmengine - INFO - Epoch(val) [35][20/241] eta: 0:00:14 time: 0.0650 data_time: 0.0154 memory: 1482 2022/09/07 21:15:02 - mmengine - INFO - Epoch(val) [35][40/241] eta: 0:00:10 time: 0.0529 data_time: 0.0046 memory: 1482 2022/09/07 21:15:03 - mmengine - INFO - Epoch(val) [35][60/241] eta: 0:00:09 time: 0.0538 data_time: 0.0054 memory: 1482 2022/09/07 21:15:04 - mmengine - INFO - Epoch(val) [35][80/241] eta: 0:00:08 time: 0.0525 data_time: 0.0043 memory: 1482 2022/09/07 21:15:05 - mmengine - INFO - Epoch(val) [35][100/241] eta: 0:00:07 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 21:15:06 - mmengine - INFO - Epoch(val) [35][120/241] eta: 0:00:06 time: 0.0537 data_time: 0.0054 memory: 1482 2022/09/07 21:15:07 - mmengine - INFO - Epoch(val) [35][140/241] eta: 0:00:05 time: 0.0534 data_time: 0.0050 memory: 1482 2022/09/07 21:15:08 - mmengine - INFO - Epoch(val) [35][160/241] eta: 0:00:04 time: 0.0530 data_time: 0.0048 memory: 1482 2022/09/07 21:15:09 - mmengine - INFO - Epoch(val) [35][180/241] eta: 0:00:03 time: 0.0529 data_time: 0.0047 memory: 1482 2022/09/07 21:15:10 - mmengine - INFO - Epoch(val) [35][200/241] eta: 0:00:02 time: 0.0524 data_time: 0.0045 memory: 1482 2022/09/07 21:15:11 - mmengine - INFO - Epoch(val) [35][220/241] eta: 0:00:01 time: 0.0585 data_time: 0.0107 memory: 1482 2022/09/07 21:15:13 - mmengine - INFO - Epoch(val) [35][240/241] eta: 0:00:00 time: 0.0625 data_time: 0.0061 memory: 1482 2022/09/07 21:15:13 - mmengine - INFO - Epoch(val) [35][241/241] acc/top1: 0.4715 acc/top5: 0.7677 acc/mean1: 0.4301 2022/09/07 21:15:13 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_34.pth is removed 2022/09/07 21:15:15 - mmengine - INFO - The best checkpoint with 0.4715 acc/top1 at 35 epoch is saved to best_acc/top1_epoch_35.pth. 2022/09/07 21:15:18 - mmengine - INFO - Epoch(train) [36][20/1793] lr: 7.5000e-04 eta: 2:14:25 time: 0.1779 data_time: 0.0102 memory: 10464 grad_norm: 7.7556 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4158 loss: 1.4158 2022/09/07 21:15:22 - mmengine - INFO - Epoch(train) [36][40/1793] lr: 7.5000e-04 eta: 2:14:18 time: 0.1705 data_time: 0.0063 memory: 10464 grad_norm: 8.3522 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.5531 loss: 1.5531 2022/09/07 21:15:25 - mmengine - INFO - Epoch(train) [36][60/1793] lr: 7.5000e-04 eta: 2:14:11 time: 0.1706 data_time: 0.0062 memory: 10464 grad_norm: 8.4282 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9712 loss: 0.9712 2022/09/07 21:15:29 - mmengine - INFO - Epoch(train) [36][80/1793] lr: 7.5000e-04 eta: 2:14:04 time: 0.1722 data_time: 0.0084 memory: 10464 grad_norm: 8.4800 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.4325 loss: 1.4325 2022/09/07 21:15:32 - mmengine - INFO - Epoch(train) [36][100/1793] lr: 7.5000e-04 eta: 2:13:57 time: 0.1915 data_time: 0.0063 memory: 10464 grad_norm: 8.0935 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.3631 loss: 1.3631 2022/09/07 21:15:36 - mmengine - INFO - Epoch(train) [36][120/1793] lr: 7.5000e-04 eta: 2:13:50 time: 0.1723 data_time: 0.0067 memory: 10464 grad_norm: 8.2973 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3964 loss: 1.3964 2022/09/07 21:15:39 - mmengine - INFO - Epoch(train) [36][140/1793] lr: 7.5000e-04 eta: 2:13:43 time: 0.1757 data_time: 0.0091 memory: 10464 grad_norm: 8.2992 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3781 loss: 1.3781 2022/09/07 21:15:43 - mmengine - INFO - Epoch(train) [36][160/1793] lr: 7.5000e-04 eta: 2:13:36 time: 0.1736 data_time: 0.0064 memory: 10464 grad_norm: 8.2553 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2759 loss: 1.2759 2022/09/07 21:15:46 - mmengine - INFO - Epoch(train) [36][180/1793] lr: 7.5000e-04 eta: 2:13:29 time: 0.1716 data_time: 0.0060 memory: 10464 grad_norm: 8.2557 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5332 loss: 1.5332 2022/09/07 21:15:50 - mmengine - INFO - Epoch(train) [36][200/1793] lr: 7.5000e-04 eta: 2:13:21 time: 0.1746 data_time: 0.0096 memory: 10464 grad_norm: 8.2361 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2664 loss: 1.2664 2022/09/07 21:15:53 - mmengine - INFO - Epoch(train) [36][220/1793] lr: 7.5000e-04 eta: 2:13:14 time: 0.1765 data_time: 0.0071 memory: 10464 grad_norm: 8.4536 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6144 loss: 1.6144 2022/09/07 21:15:57 - mmengine - INFO - Epoch(train) [36][240/1793] lr: 7.5000e-04 eta: 2:13:07 time: 0.1745 data_time: 0.0063 memory: 10464 grad_norm: 8.3832 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.4766 loss: 1.4766 2022/09/07 21:15:58 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:16:00 - mmengine - INFO - Epoch(train) [36][260/1793] lr: 7.5000e-04 eta: 2:13:00 time: 0.1746 data_time: 0.0091 memory: 10464 grad_norm: 8.4893 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.4053 loss: 1.4053 2022/09/07 21:16:04 - mmengine - INFO - Epoch(train) [36][280/1793] lr: 7.5000e-04 eta: 2:12:53 time: 0.1716 data_time: 0.0062 memory: 10464 grad_norm: 8.7402 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2291 loss: 1.2291 2022/09/07 21:16:07 - mmengine - INFO - Epoch(train) [36][300/1793] lr: 7.5000e-04 eta: 2:12:46 time: 0.1716 data_time: 0.0063 memory: 10464 grad_norm: 8.4855 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1066 loss: 1.1066 2022/09/07 21:16:11 - mmengine - INFO - Epoch(train) [36][320/1793] lr: 7.5000e-04 eta: 2:12:39 time: 0.1731 data_time: 0.0090 memory: 10464 grad_norm: 8.4894 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2559 loss: 1.2559 2022/09/07 21:16:14 - mmengine - INFO - Epoch(train) [36][340/1793] lr: 7.5000e-04 eta: 2:12:32 time: 0.1751 data_time: 0.0071 memory: 10464 grad_norm: 8.5158 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4357 loss: 1.4357 2022/09/07 21:16:18 - mmengine - INFO - Epoch(train) [36][360/1793] lr: 7.5000e-04 eta: 2:12:25 time: 0.1701 data_time: 0.0060 memory: 10464 grad_norm: 8.4478 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3175 loss: 1.3175 2022/09/07 21:16:21 - mmengine - INFO - Epoch(train) [36][380/1793] lr: 7.5000e-04 eta: 2:12:18 time: 0.1773 data_time: 0.0088 memory: 10464 grad_norm: 8.4012 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4090 loss: 1.4090 2022/09/07 21:16:25 - mmengine - INFO - Epoch(train) [36][400/1793] lr: 7.5000e-04 eta: 2:12:11 time: 0.1707 data_time: 0.0061 memory: 10464 grad_norm: 8.4897 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.3323 loss: 1.3323 2022/09/07 21:16:28 - mmengine - INFO - Epoch(train) [36][420/1793] lr: 7.5000e-04 eta: 2:12:04 time: 0.1705 data_time: 0.0065 memory: 10464 grad_norm: 8.4074 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.6141 loss: 1.6141 2022/09/07 21:16:32 - mmengine - INFO - Epoch(train) [36][440/1793] lr: 7.5000e-04 eta: 2:11:57 time: 0.1817 data_time: 0.0086 memory: 10464 grad_norm: 8.5394 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3811 loss: 1.3811 2022/09/07 21:16:36 - mmengine - INFO - Epoch(train) [36][460/1793] lr: 7.5000e-04 eta: 2:11:50 time: 0.2088 data_time: 0.0073 memory: 10464 grad_norm: 8.2239 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0687 loss: 1.0687 2022/09/07 21:16:39 - mmengine - INFO - Epoch(train) [36][480/1793] lr: 7.5000e-04 eta: 2:11:43 time: 0.1709 data_time: 0.0064 memory: 10464 grad_norm: 8.5044 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.3431 loss: 1.3431 2022/09/07 21:16:43 - mmengine - INFO - Epoch(train) [36][500/1793] lr: 7.5000e-04 eta: 2:11:36 time: 0.1746 data_time: 0.0084 memory: 10464 grad_norm: 8.2093 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.4142 loss: 1.4142 2022/09/07 21:16:46 - mmengine - INFO - Epoch(train) [36][520/1793] lr: 7.5000e-04 eta: 2:11:29 time: 0.1713 data_time: 0.0066 memory: 10464 grad_norm: 8.4640 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4346 loss: 1.4346 2022/09/07 21:16:50 - mmengine - INFO - Epoch(train) [36][540/1793] lr: 7.5000e-04 eta: 2:11:22 time: 0.1713 data_time: 0.0060 memory: 10464 grad_norm: 8.2669 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.3836 loss: 1.3836 2022/09/07 21:16:53 - mmengine - INFO - Epoch(train) [36][560/1793] lr: 7.5000e-04 eta: 2:11:15 time: 0.1774 data_time: 0.0088 memory: 10464 grad_norm: 8.7789 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2557 loss: 1.2557 2022/09/07 21:16:57 - mmengine - INFO - Epoch(train) [36][580/1793] lr: 7.5000e-04 eta: 2:11:08 time: 0.1718 data_time: 0.0062 memory: 10464 grad_norm: 8.5848 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3740 loss: 1.3740 2022/09/07 21:17:00 - mmengine - INFO - Epoch(train) [36][600/1793] lr: 7.5000e-04 eta: 2:11:01 time: 0.1762 data_time: 0.0069 memory: 10464 grad_norm: 9.0400 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.3435 loss: 1.3435 2022/09/07 21:17:04 - mmengine - INFO - Epoch(train) [36][620/1793] lr: 7.5000e-04 eta: 2:10:54 time: 0.1764 data_time: 0.0101 memory: 10464 grad_norm: 8.5070 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.5190 loss: 1.5190 2022/09/07 21:17:07 - mmengine - INFO - Epoch(train) [36][640/1793] lr: 7.5000e-04 eta: 2:10:47 time: 0.1707 data_time: 0.0062 memory: 10464 grad_norm: 8.3890 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.4163 loss: 1.4163 2022/09/07 21:17:11 - mmengine - INFO - Epoch(train) [36][660/1793] lr: 7.5000e-04 eta: 2:10:40 time: 0.1844 data_time: 0.0064 memory: 10464 grad_norm: 8.6808 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4813 loss: 1.4813 2022/09/07 21:17:14 - mmengine - INFO - Epoch(train) [36][680/1793] lr: 7.5000e-04 eta: 2:10:33 time: 0.1815 data_time: 0.0103 memory: 10464 grad_norm: 8.3984 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2969 loss: 1.2969 2022/09/07 21:17:18 - mmengine - INFO - Epoch(train) [36][700/1793] lr: 7.5000e-04 eta: 2:10:26 time: 0.1709 data_time: 0.0066 memory: 10464 grad_norm: 8.2688 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3398 loss: 1.3398 2022/09/07 21:17:21 - mmengine - INFO - Epoch(train) [36][720/1793] lr: 7.5000e-04 eta: 2:10:19 time: 0.1753 data_time: 0.0062 memory: 10464 grad_norm: 8.3938 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3033 loss: 1.3033 2022/09/07 21:17:25 - mmengine - INFO - Epoch(train) [36][740/1793] lr: 7.5000e-04 eta: 2:10:12 time: 0.1758 data_time: 0.0086 memory: 10464 grad_norm: 8.1965 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.2589 loss: 1.2589 2022/09/07 21:17:28 - mmengine - INFO - Epoch(train) [36][760/1793] lr: 7.5000e-04 eta: 2:10:05 time: 0.1697 data_time: 0.0062 memory: 10464 grad_norm: 8.4476 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.1826 loss: 1.1826 2022/09/07 21:17:32 - mmengine - INFO - Epoch(train) [36][780/1793] lr: 7.5000e-04 eta: 2:09:58 time: 0.1784 data_time: 0.0062 memory: 10464 grad_norm: 8.4252 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.5007 loss: 1.5007 2022/09/07 21:17:36 - mmengine - INFO - Epoch(train) [36][800/1793] lr: 7.5000e-04 eta: 2:09:51 time: 0.1959 data_time: 0.0100 memory: 10464 grad_norm: 8.5470 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4169 loss: 1.4169 2022/09/07 21:17:39 - mmengine - INFO - Epoch(train) [36][820/1793] lr: 7.5000e-04 eta: 2:09:44 time: 0.1714 data_time: 0.0061 memory: 10464 grad_norm: 8.4552 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1342 loss: 1.1342 2022/09/07 21:17:43 - mmengine - INFO - Epoch(train) [36][840/1793] lr: 7.5000e-04 eta: 2:09:37 time: 0.1741 data_time: 0.0065 memory: 10464 grad_norm: 8.8772 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3972 loss: 1.3972 2022/09/07 21:17:46 - mmengine - INFO - Epoch(train) [36][860/1793] lr: 7.5000e-04 eta: 2:09:30 time: 0.1812 data_time: 0.0101 memory: 10464 grad_norm: 8.5153 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.4298 loss: 1.4298 2022/09/07 21:17:50 - mmengine - INFO - Epoch(train) [36][880/1793] lr: 7.5000e-04 eta: 2:09:23 time: 0.1701 data_time: 0.0060 memory: 10464 grad_norm: 8.4225 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7206 loss: 1.7206 2022/09/07 21:17:53 - mmengine - INFO - Epoch(train) [36][900/1793] lr: 7.5000e-04 eta: 2:09:16 time: 0.1788 data_time: 0.0064 memory: 10464 grad_norm: 8.5540 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3231 loss: 1.3231 2022/09/07 21:17:57 - mmengine - INFO - Epoch(train) [36][920/1793] lr: 7.5000e-04 eta: 2:09:09 time: 0.1732 data_time: 0.0080 memory: 10464 grad_norm: 8.2004 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4003 loss: 1.4003 2022/09/07 21:18:00 - mmengine - INFO - Epoch(train) [36][940/1793] lr: 7.5000e-04 eta: 2:09:02 time: 0.1717 data_time: 0.0061 memory: 10464 grad_norm: 8.3781 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1495 loss: 1.1495 2022/09/07 21:18:04 - mmengine - INFO - Epoch(train) [36][960/1793] lr: 7.5000e-04 eta: 2:08:55 time: 0.1724 data_time: 0.0072 memory: 10464 grad_norm: 8.5978 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2558 loss: 1.2558 2022/09/07 21:18:07 - mmengine - INFO - Epoch(train) [36][980/1793] lr: 7.5000e-04 eta: 2:08:48 time: 0.1730 data_time: 0.0083 memory: 10464 grad_norm: 8.5566 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4114 loss: 1.4114 2022/09/07 21:18:10 - mmengine - INFO - Epoch(train) [36][1000/1793] lr: 7.5000e-04 eta: 2:08:41 time: 0.1737 data_time: 0.0067 memory: 10464 grad_norm: 8.6262 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3162 loss: 1.3162 2022/09/07 21:18:14 - mmengine - INFO - Epoch(train) [36][1020/1793] lr: 7.5000e-04 eta: 2:08:34 time: 0.1756 data_time: 0.0070 memory: 10464 grad_norm: 8.5306 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2771 loss: 1.2771 2022/09/07 21:18:18 - mmengine - INFO - Epoch(train) [36][1040/1793] lr: 7.5000e-04 eta: 2:08:27 time: 0.1744 data_time: 0.0084 memory: 10464 grad_norm: 8.1564 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2874 loss: 1.2874 2022/09/07 21:18:21 - mmengine - INFO - Epoch(train) [36][1060/1793] lr: 7.5000e-04 eta: 2:08:20 time: 0.1732 data_time: 0.0067 memory: 10464 grad_norm: 8.6997 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3271 loss: 1.3271 2022/09/07 21:18:24 - mmengine - INFO - Epoch(train) [36][1080/1793] lr: 7.5000e-04 eta: 2:08:13 time: 0.1709 data_time: 0.0062 memory: 10464 grad_norm: 8.2882 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3324 loss: 1.3324 2022/09/07 21:18:28 - mmengine - INFO - Epoch(train) [36][1100/1793] lr: 7.5000e-04 eta: 2:08:07 time: 0.1730 data_time: 0.0089 memory: 10464 grad_norm: 8.5924 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5034 loss: 1.5034 2022/09/07 21:18:31 - mmengine - INFO - Epoch(train) [36][1120/1793] lr: 7.5000e-04 eta: 2:08:00 time: 0.1747 data_time: 0.0065 memory: 10464 grad_norm: 8.2824 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4429 loss: 1.4429 2022/09/07 21:18:35 - mmengine - INFO - Epoch(train) [36][1140/1793] lr: 7.5000e-04 eta: 2:07:53 time: 0.1819 data_time: 0.0073 memory: 10464 grad_norm: 8.6612 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.5103 loss: 1.5103 2022/09/07 21:18:38 - mmengine - INFO - Epoch(train) [36][1160/1793] lr: 7.5000e-04 eta: 2:07:46 time: 0.1729 data_time: 0.0088 memory: 10464 grad_norm: 8.2971 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2456 loss: 1.2456 2022/09/07 21:18:42 - mmengine - INFO - Epoch(train) [36][1180/1793] lr: 7.5000e-04 eta: 2:07:39 time: 0.1739 data_time: 0.0067 memory: 10464 grad_norm: 8.3333 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3271 loss: 1.3271 2022/09/07 21:18:45 - mmengine - INFO - Epoch(train) [36][1200/1793] lr: 7.5000e-04 eta: 2:07:32 time: 0.1740 data_time: 0.0063 memory: 10464 grad_norm: 8.4258 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2814 loss: 1.2814 2022/09/07 21:18:49 - mmengine - INFO - Epoch(train) [36][1220/1793] lr: 7.5000e-04 eta: 2:07:25 time: 0.1746 data_time: 0.0094 memory: 10464 grad_norm: 8.7637 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3017 loss: 1.3017 2022/09/07 21:18:53 - mmengine - INFO - Epoch(train) [36][1240/1793] lr: 7.5000e-04 eta: 2:07:18 time: 0.1770 data_time: 0.0060 memory: 10464 grad_norm: 8.7146 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1883 loss: 1.1883 2022/09/07 21:18:54 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:18:56 - mmengine - INFO - Epoch(train) [36][1260/1793] lr: 7.5000e-04 eta: 2:07:11 time: 0.1820 data_time: 0.0084 memory: 10464 grad_norm: 8.8193 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.5880 loss: 1.5880 2022/09/07 21:19:00 - mmengine - INFO - Epoch(train) [36][1280/1793] lr: 7.5000e-04 eta: 2:07:04 time: 0.1732 data_time: 0.0091 memory: 10464 grad_norm: 8.4600 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2958 loss: 1.2958 2022/09/07 21:19:03 - mmengine - INFO - Epoch(train) [36][1300/1793] lr: 7.5000e-04 eta: 2:06:57 time: 0.1815 data_time: 0.0066 memory: 10464 grad_norm: 8.1168 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2695 loss: 1.2695 2022/09/07 21:19:07 - mmengine - INFO - Epoch(train) [36][1320/1793] lr: 7.5000e-04 eta: 2:06:50 time: 0.1708 data_time: 0.0061 memory: 10464 grad_norm: 8.5157 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.5722 loss: 1.5722 2022/09/07 21:19:10 - mmengine - INFO - Epoch(train) [36][1340/1793] lr: 7.5000e-04 eta: 2:06:43 time: 0.1807 data_time: 0.0084 memory: 10464 grad_norm: 8.2449 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.4481 loss: 1.4481 2022/09/07 21:19:14 - mmengine - INFO - Epoch(train) [36][1360/1793] lr: 7.5000e-04 eta: 2:06:36 time: 0.1836 data_time: 0.0066 memory: 10464 grad_norm: 8.5609 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4760 loss: 1.4760 2022/09/07 21:19:17 - mmengine - INFO - Epoch(train) [36][1380/1793] lr: 7.5000e-04 eta: 2:06:30 time: 0.1721 data_time: 0.0069 memory: 10464 grad_norm: 8.6745 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3535 loss: 1.3535 2022/09/07 21:19:21 - mmengine - INFO - Epoch(train) [36][1400/1793] lr: 7.5000e-04 eta: 2:06:23 time: 0.1736 data_time: 0.0094 memory: 10464 grad_norm: 8.6006 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3080 loss: 1.3080 2022/09/07 21:19:24 - mmengine - INFO - Epoch(train) [36][1420/1793] lr: 7.5000e-04 eta: 2:06:16 time: 0.1697 data_time: 0.0062 memory: 10464 grad_norm: 8.5663 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4728 loss: 1.4728 2022/09/07 21:19:28 - mmengine - INFO - Epoch(train) [36][1440/1793] lr: 7.5000e-04 eta: 2:06:09 time: 0.1699 data_time: 0.0062 memory: 10464 grad_norm: 8.5652 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3107 loss: 1.3107 2022/09/07 21:19:31 - mmengine - INFO - Epoch(train) [36][1460/1793] lr: 7.5000e-04 eta: 2:06:02 time: 0.1893 data_time: 0.0086 memory: 10464 grad_norm: 8.4477 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2415 loss: 1.2415 2022/09/07 21:19:35 - mmengine - INFO - Epoch(train) [36][1480/1793] lr: 7.5000e-04 eta: 2:05:55 time: 0.1805 data_time: 0.0071 memory: 10464 grad_norm: 8.9279 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2424 loss: 1.2424 2022/09/07 21:19:39 - mmengine - INFO - Epoch(train) [36][1500/1793] lr: 7.5000e-04 eta: 2:05:48 time: 0.1737 data_time: 0.0086 memory: 10464 grad_norm: 8.5506 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2350 loss: 1.2350 2022/09/07 21:19:42 - mmengine - INFO - Epoch(train) [36][1520/1793] lr: 7.5000e-04 eta: 2:05:41 time: 0.1732 data_time: 0.0071 memory: 10464 grad_norm: 8.7734 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.5173 loss: 1.5173 2022/09/07 21:19:45 - mmengine - INFO - Epoch(train) [36][1540/1793] lr: 7.5000e-04 eta: 2:05:34 time: 0.1709 data_time: 0.0068 memory: 10464 grad_norm: 8.9536 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3286 loss: 1.3286 2022/09/07 21:19:49 - mmengine - INFO - Epoch(train) [36][1560/1793] lr: 7.5000e-04 eta: 2:05:27 time: 0.1709 data_time: 0.0063 memory: 10464 grad_norm: 8.6311 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2805 loss: 1.2805 2022/09/07 21:19:52 - mmengine - INFO - Epoch(train) [36][1580/1793] lr: 7.5000e-04 eta: 2:05:20 time: 0.1737 data_time: 0.0090 memory: 10464 grad_norm: 8.7958 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5592 loss: 1.5592 2022/09/07 21:19:56 - mmengine - INFO - Epoch(train) [36][1600/1793] lr: 7.5000e-04 eta: 2:05:14 time: 0.1798 data_time: 0.0088 memory: 10464 grad_norm: 9.0361 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4140 loss: 1.4140 2022/09/07 21:19:59 - mmengine - INFO - Epoch(train) [36][1620/1793] lr: 7.5000e-04 eta: 2:05:07 time: 0.1708 data_time: 0.0063 memory: 10464 grad_norm: 8.5764 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1456 loss: 1.1456 2022/09/07 21:20:03 - mmengine - INFO - Epoch(train) [36][1640/1793] lr: 7.5000e-04 eta: 2:05:00 time: 0.1744 data_time: 0.0091 memory: 10464 grad_norm: 8.6205 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5188 loss: 1.5188 2022/09/07 21:20:06 - mmengine - INFO - Epoch(train) [36][1660/1793] lr: 7.5000e-04 eta: 2:04:53 time: 0.1716 data_time: 0.0061 memory: 10464 grad_norm: 8.8571 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3451 loss: 1.3451 2022/09/07 21:20:10 - mmengine - INFO - Epoch(train) [36][1680/1793] lr: 7.5000e-04 eta: 2:04:46 time: 0.1715 data_time: 0.0062 memory: 10464 grad_norm: 8.5471 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2386 loss: 1.2386 2022/09/07 21:20:13 - mmengine - INFO - Epoch(train) [36][1700/1793] lr: 7.5000e-04 eta: 2:04:39 time: 0.1774 data_time: 0.0098 memory: 10464 grad_norm: 8.7114 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4807 loss: 1.4807 2022/09/07 21:20:17 - mmengine - INFO - Epoch(train) [36][1720/1793] lr: 7.5000e-04 eta: 2:04:32 time: 0.1718 data_time: 0.0066 memory: 10464 grad_norm: 8.3933 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3493 loss: 1.3493 2022/09/07 21:20:20 - mmengine - INFO - Epoch(train) [36][1740/1793] lr: 7.5000e-04 eta: 2:04:25 time: 0.1735 data_time: 0.0062 memory: 10464 grad_norm: 8.9836 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.2692 loss: 1.2692 2022/09/07 21:20:24 - mmengine - INFO - Epoch(train) [36][1760/1793] lr: 7.5000e-04 eta: 2:04:18 time: 0.1749 data_time: 0.0097 memory: 10464 grad_norm: 8.4953 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1417 loss: 1.1417 2022/09/07 21:20:27 - mmengine - INFO - Epoch(train) [36][1780/1793] lr: 7.5000e-04 eta: 2:04:11 time: 0.1697 data_time: 0.0061 memory: 10464 grad_norm: 8.3385 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3835 loss: 1.3835 2022/09/07 21:20:29 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:20:29 - mmengine - INFO - Epoch(train) [36][1793/1793] lr: 7.5000e-04 eta: 2:04:11 time: 0.1666 data_time: 0.0062 memory: 10464 grad_norm: 8.9498 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 1.3773 loss: 1.3773 2022/09/07 21:20:29 - mmengine - INFO - Saving checkpoint at 36 epochs 2022/09/07 21:20:33 - mmengine - INFO - Epoch(val) [36][20/241] eta: 0:00:17 time: 0.0805 data_time: 0.0314 memory: 1482 2022/09/07 21:20:34 - mmengine - INFO - Epoch(val) [36][40/241] eta: 0:00:10 time: 0.0528 data_time: 0.0046 memory: 1482 2022/09/07 21:20:35 - mmengine - INFO - Epoch(val) [36][60/241] eta: 0:00:10 time: 0.0574 data_time: 0.0087 memory: 1482 2022/09/07 21:20:36 - mmengine - INFO - Epoch(val) [36][80/241] eta: 0:00:08 time: 0.0532 data_time: 0.0049 memory: 1482 2022/09/07 21:20:37 - mmengine - INFO - Epoch(val) [36][100/241] eta: 0:00:07 time: 0.0530 data_time: 0.0048 memory: 1482 2022/09/07 21:20:38 - mmengine - INFO - Epoch(val) [36][120/241] eta: 0:00:06 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 21:20:40 - mmengine - INFO - Epoch(val) [36][140/241] eta: 0:00:05 time: 0.0533 data_time: 0.0050 memory: 1482 2022/09/07 21:20:41 - mmengine - INFO - Epoch(val) [36][160/241] eta: 0:00:04 time: 0.0533 data_time: 0.0048 memory: 1482 2022/09/07 21:20:42 - mmengine - INFO - Epoch(val) [36][180/241] eta: 0:00:03 time: 0.0549 data_time: 0.0060 memory: 1482 2022/09/07 21:20:43 - mmengine - INFO - Epoch(val) [36][200/241] eta: 0:00:02 time: 0.0564 data_time: 0.0049 memory: 1482 2022/09/07 21:20:44 - mmengine - INFO - Epoch(val) [36][220/241] eta: 0:00:01 time: 0.0529 data_time: 0.0050 memory: 1482 2022/09/07 21:20:45 - mmengine - INFO - Epoch(val) [36][240/241] eta: 0:00:00 time: 0.0520 data_time: 0.0043 memory: 1482 2022/09/07 21:20:45 - mmengine - INFO - Epoch(val) [36][241/241] acc/top1: 0.4703 acc/top5: 0.7720 acc/mean1: 0.4315 2022/09/07 21:20:49 - mmengine - INFO - Epoch(train) [37][20/1793] lr: 7.5000e-04 eta: 2:03:59 time: 0.1793 data_time: 0.0114 memory: 10464 grad_norm: 8.6467 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2921 loss: 1.2921 2022/09/07 21:20:53 - mmengine - INFO - Epoch(train) [37][40/1793] lr: 7.5000e-04 eta: 2:03:52 time: 0.1743 data_time: 0.0071 memory: 10464 grad_norm: 8.4491 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.2050 loss: 1.2050 2022/09/07 21:20:56 - mmengine - INFO - Epoch(train) [37][60/1793] lr: 7.5000e-04 eta: 2:03:45 time: 0.1709 data_time: 0.0066 memory: 10464 grad_norm: 8.7350 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3043 loss: 1.3043 2022/09/07 21:21:00 - mmengine - INFO - Epoch(train) [37][80/1793] lr: 7.5000e-04 eta: 2:03:38 time: 0.1754 data_time: 0.0100 memory: 10464 grad_norm: 8.4320 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1772 loss: 1.1772 2022/09/07 21:21:04 - mmengine - INFO - Epoch(train) [37][100/1793] lr: 7.5000e-04 eta: 2:03:32 time: 0.2150 data_time: 0.0090 memory: 10464 grad_norm: 8.4724 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.1940 loss: 1.1940 2022/09/07 21:21:07 - mmengine - INFO - Epoch(train) [37][120/1793] lr: 7.5000e-04 eta: 2:03:25 time: 0.1703 data_time: 0.0068 memory: 10464 grad_norm: 8.6614 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3151 loss: 1.3151 2022/09/07 21:21:11 - mmengine - INFO - Epoch(train) [37][140/1793] lr: 7.5000e-04 eta: 2:03:18 time: 0.1735 data_time: 0.0092 memory: 10464 grad_norm: 8.2910 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0283 loss: 1.0283 2022/09/07 21:21:14 - mmengine - INFO - Epoch(train) [37][160/1793] lr: 7.5000e-04 eta: 2:03:11 time: 0.1722 data_time: 0.0064 memory: 10464 grad_norm: 8.6914 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2475 loss: 1.2475 2022/09/07 21:21:18 - mmengine - INFO - Epoch(train) [37][180/1793] lr: 7.5000e-04 eta: 2:03:04 time: 0.1714 data_time: 0.0069 memory: 10464 grad_norm: 8.2968 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0849 loss: 1.0849 2022/09/07 21:21:21 - mmengine - INFO - Epoch(train) [37][200/1793] lr: 7.5000e-04 eta: 2:02:58 time: 0.1771 data_time: 0.0093 memory: 10464 grad_norm: 8.7287 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9562 loss: 0.9562 2022/09/07 21:21:25 - mmengine - INFO - Epoch(train) [37][220/1793] lr: 7.5000e-04 eta: 2:02:51 time: 0.1722 data_time: 0.0064 memory: 10464 grad_norm: 8.8841 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1961 loss: 1.1961 2022/09/07 21:21:28 - mmengine - INFO - Epoch(train) [37][240/1793] lr: 7.5000e-04 eta: 2:02:44 time: 0.1702 data_time: 0.0065 memory: 10464 grad_norm: 8.5392 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4406 loss: 1.4406 2022/09/07 21:21:31 - mmengine - INFO - Epoch(train) [37][260/1793] lr: 7.5000e-04 eta: 2:02:37 time: 0.1726 data_time: 0.0086 memory: 10464 grad_norm: 8.5087 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2079 loss: 1.2079 2022/09/07 21:21:35 - mmengine - INFO - Epoch(train) [37][280/1793] lr: 7.5000e-04 eta: 2:02:30 time: 0.1750 data_time: 0.0068 memory: 10464 grad_norm: 8.4293 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2017 loss: 1.2017 2022/09/07 21:21:38 - mmengine - INFO - Epoch(train) [37][300/1793] lr: 7.5000e-04 eta: 2:02:23 time: 0.1716 data_time: 0.0066 memory: 10464 grad_norm: 8.5653 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1602 loss: 1.1602 2022/09/07 21:21:42 - mmengine - INFO - Epoch(train) [37][320/1793] lr: 7.5000e-04 eta: 2:02:16 time: 0.1762 data_time: 0.0085 memory: 10464 grad_norm: 8.9174 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3375 loss: 1.3375 2022/09/07 21:21:45 - mmengine - INFO - Epoch(train) [37][340/1793] lr: 7.5000e-04 eta: 2:02:09 time: 0.1712 data_time: 0.0069 memory: 10464 grad_norm: 8.8072 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4194 loss: 1.4194 2022/09/07 21:21:49 - mmengine - INFO - Epoch(train) [37][360/1793] lr: 7.5000e-04 eta: 2:02:03 time: 0.1711 data_time: 0.0067 memory: 10464 grad_norm: 8.6080 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.3654 loss: 1.3654 2022/09/07 21:21:53 - mmengine - INFO - Epoch(train) [37][380/1793] lr: 7.5000e-04 eta: 2:01:56 time: 0.1855 data_time: 0.0085 memory: 10464 grad_norm: 8.4468 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2242 loss: 1.2242 2022/09/07 21:21:56 - mmengine - INFO - Epoch(train) [37][400/1793] lr: 7.5000e-04 eta: 2:01:49 time: 0.1726 data_time: 0.0070 memory: 10464 grad_norm: 8.4647 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3636 loss: 1.3636 2022/09/07 21:21:59 - mmengine - INFO - Epoch(train) [37][420/1793] lr: 7.5000e-04 eta: 2:01:42 time: 0.1715 data_time: 0.0066 memory: 10464 grad_norm: 8.4258 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1515 loss: 1.1515 2022/09/07 21:22:03 - mmengine - INFO - Epoch(train) [37][440/1793] lr: 7.5000e-04 eta: 2:01:35 time: 0.1830 data_time: 0.0102 memory: 10464 grad_norm: 8.7164 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.6224 loss: 1.6224 2022/09/07 21:22:05 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:22:07 - mmengine - INFO - Epoch(train) [37][460/1793] lr: 7.5000e-04 eta: 2:01:28 time: 0.1701 data_time: 0.0064 memory: 10464 grad_norm: 8.8561 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9009 loss: 0.9009 2022/09/07 21:22:10 - mmengine - INFO - Epoch(train) [37][480/1793] lr: 7.5000e-04 eta: 2:01:22 time: 0.1716 data_time: 0.0062 memory: 10464 grad_norm: 8.8415 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4921 loss: 1.4921 2022/09/07 21:22:14 - mmengine - INFO - Epoch(train) [37][500/1793] lr: 7.5000e-04 eta: 2:01:15 time: 0.1869 data_time: 0.0104 memory: 10464 grad_norm: 8.9340 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3679 loss: 1.3679 2022/09/07 21:22:17 - mmengine - INFO - Epoch(train) [37][520/1793] lr: 7.5000e-04 eta: 2:01:08 time: 0.1717 data_time: 0.0072 memory: 10464 grad_norm: 9.3254 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4155 loss: 1.4155 2022/09/07 21:22:21 - mmengine - INFO - Epoch(train) [37][540/1793] lr: 7.5000e-04 eta: 2:01:01 time: 0.1728 data_time: 0.0062 memory: 10464 grad_norm: 8.8987 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2009 loss: 1.2009 2022/09/07 21:22:24 - mmengine - INFO - Epoch(train) [37][560/1793] lr: 7.5000e-04 eta: 2:00:54 time: 0.1827 data_time: 0.0099 memory: 10464 grad_norm: 8.9154 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.1536 loss: 1.1536 2022/09/07 21:22:28 - mmengine - INFO - Epoch(train) [37][580/1793] lr: 7.5000e-04 eta: 2:00:48 time: 0.1700 data_time: 0.0065 memory: 10464 grad_norm: 8.7582 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2377 loss: 1.2377 2022/09/07 21:22:31 - mmengine - INFO - Epoch(train) [37][600/1793] lr: 7.5000e-04 eta: 2:00:41 time: 0.1707 data_time: 0.0065 memory: 10464 grad_norm: 8.9655 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4324 loss: 1.4324 2022/09/07 21:22:35 - mmengine - INFO - Epoch(train) [37][620/1793] lr: 7.5000e-04 eta: 2:00:34 time: 0.1786 data_time: 0.0090 memory: 10464 grad_norm: 8.3453 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0316 loss: 1.0316 2022/09/07 21:22:38 - mmengine - INFO - Epoch(train) [37][640/1793] lr: 7.5000e-04 eta: 2:00:27 time: 0.1696 data_time: 0.0064 memory: 10464 grad_norm: 8.8080 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2741 loss: 1.2741 2022/09/07 21:22:42 - mmengine - INFO - Epoch(train) [37][660/1793] lr: 7.5000e-04 eta: 2:00:20 time: 0.1838 data_time: 0.0065 memory: 10464 grad_norm: 8.7724 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3927 loss: 1.3927 2022/09/07 21:22:45 - mmengine - INFO - Epoch(train) [37][680/1793] lr: 7.5000e-04 eta: 2:00:13 time: 0.1749 data_time: 0.0089 memory: 10464 grad_norm: 8.5483 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2542 loss: 1.2542 2022/09/07 21:22:49 - mmengine - INFO - Epoch(train) [37][700/1793] lr: 7.5000e-04 eta: 2:00:07 time: 0.1730 data_time: 0.0073 memory: 10464 grad_norm: 8.8763 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2153 loss: 1.2153 2022/09/07 21:22:52 - mmengine - INFO - Epoch(train) [37][720/1793] lr: 7.5000e-04 eta: 2:00:00 time: 0.1708 data_time: 0.0067 memory: 10464 grad_norm: 8.8488 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3429 loss: 1.3429 2022/09/07 21:22:56 - mmengine - INFO - Epoch(train) [37][740/1793] lr: 7.5000e-04 eta: 1:59:53 time: 0.1752 data_time: 0.0092 memory: 10464 grad_norm: 9.0818 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3056 loss: 1.3056 2022/09/07 21:22:59 - mmengine - INFO - Epoch(train) [37][760/1793] lr: 7.5000e-04 eta: 1:59:46 time: 0.1711 data_time: 0.0067 memory: 10464 grad_norm: 8.9194 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.6135 loss: 1.6135 2022/09/07 21:23:03 - mmengine - INFO - Epoch(train) [37][780/1793] lr: 7.5000e-04 eta: 1:59:39 time: 0.1749 data_time: 0.0062 memory: 10464 grad_norm: 8.9081 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1505 loss: 1.1505 2022/09/07 21:23:06 - mmengine - INFO - Epoch(train) [37][800/1793] lr: 7.5000e-04 eta: 1:59:33 time: 0.1766 data_time: 0.0098 memory: 10464 grad_norm: 9.0454 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4795 loss: 1.4795 2022/09/07 21:23:09 - mmengine - INFO - Epoch(train) [37][820/1793] lr: 7.5000e-04 eta: 1:59:26 time: 0.1703 data_time: 0.0063 memory: 10464 grad_norm: 8.7180 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1996 loss: 1.1996 2022/09/07 21:23:13 - mmengine - INFO - Epoch(train) [37][840/1793] lr: 7.5000e-04 eta: 1:59:19 time: 0.1725 data_time: 0.0061 memory: 10464 grad_norm: 8.8150 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3833 loss: 1.3833 2022/09/07 21:23:16 - mmengine - INFO - Epoch(train) [37][860/1793] lr: 7.5000e-04 eta: 1:59:12 time: 0.1727 data_time: 0.0091 memory: 10464 grad_norm: 8.8496 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4642 loss: 1.4642 2022/09/07 21:23:20 - mmengine - INFO - Epoch(train) [37][880/1793] lr: 7.5000e-04 eta: 1:59:05 time: 0.1706 data_time: 0.0063 memory: 10464 grad_norm: 8.6560 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.5370 loss: 1.5370 2022/09/07 21:23:24 - mmengine - INFO - Epoch(train) [37][900/1793] lr: 7.5000e-04 eta: 1:58:59 time: 0.1974 data_time: 0.0075 memory: 10464 grad_norm: 8.7364 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3178 loss: 1.3178 2022/09/07 21:23:27 - mmengine - INFO - Epoch(train) [37][920/1793] lr: 7.5000e-04 eta: 1:58:52 time: 0.1734 data_time: 0.0096 memory: 10464 grad_norm: 8.9072 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2727 loss: 1.2727 2022/09/07 21:23:31 - mmengine - INFO - Epoch(train) [37][940/1793] lr: 7.5000e-04 eta: 1:58:45 time: 0.1729 data_time: 0.0065 memory: 10464 grad_norm: 9.2086 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4625 loss: 1.4625 2022/09/07 21:23:34 - mmengine - INFO - Epoch(train) [37][960/1793] lr: 7.5000e-04 eta: 1:58:38 time: 0.1712 data_time: 0.0062 memory: 10464 grad_norm: 9.1523 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.3709 loss: 1.3709 2022/09/07 21:23:38 - mmengine - INFO - Epoch(train) [37][980/1793] lr: 7.5000e-04 eta: 1:58:32 time: 0.1727 data_time: 0.0087 memory: 10464 grad_norm: 8.6223 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2870 loss: 1.2870 2022/09/07 21:23:41 - mmengine - INFO - Epoch(train) [37][1000/1793] lr: 7.5000e-04 eta: 1:58:25 time: 0.1756 data_time: 0.0064 memory: 10464 grad_norm: 9.1656 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.6445 loss: 1.6445 2022/09/07 21:23:45 - mmengine - INFO - Epoch(train) [37][1020/1793] lr: 7.5000e-04 eta: 1:58:18 time: 0.2026 data_time: 0.0074 memory: 10464 grad_norm: 8.9160 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1745 loss: 1.1745 2022/09/07 21:23:49 - mmengine - INFO - Epoch(train) [37][1040/1793] lr: 7.5000e-04 eta: 1:58:11 time: 0.1725 data_time: 0.0087 memory: 10464 grad_norm: 8.8153 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.3731 loss: 1.3731 2022/09/07 21:23:52 - mmengine - INFO - Epoch(train) [37][1060/1793] lr: 7.5000e-04 eta: 1:58:05 time: 0.1702 data_time: 0.0064 memory: 10464 grad_norm: 8.8215 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1025 loss: 1.1025 2022/09/07 21:23:55 - mmengine - INFO - Epoch(train) [37][1080/1793] lr: 7.5000e-04 eta: 1:57:58 time: 0.1730 data_time: 0.0067 memory: 10464 grad_norm: 9.2150 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3611 loss: 1.3611 2022/09/07 21:23:59 - mmengine - INFO - Epoch(train) [37][1100/1793] lr: 7.5000e-04 eta: 1:57:51 time: 0.1741 data_time: 0.0084 memory: 10464 grad_norm: 9.0629 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.5024 loss: 1.5024 2022/09/07 21:24:02 - mmengine - INFO - Epoch(train) [37][1120/1793] lr: 7.5000e-04 eta: 1:57:44 time: 0.1723 data_time: 0.0061 memory: 10464 grad_norm: 8.8270 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4660 loss: 1.4660 2022/09/07 21:24:06 - mmengine - INFO - Epoch(train) [37][1140/1793] lr: 7.5000e-04 eta: 1:57:37 time: 0.1761 data_time: 0.0067 memory: 10464 grad_norm: 8.8116 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.2275 loss: 1.2275 2022/09/07 21:24:09 - mmengine - INFO - Epoch(train) [37][1160/1793] lr: 7.5000e-04 eta: 1:57:31 time: 0.1735 data_time: 0.0095 memory: 10464 grad_norm: 9.0140 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.3964 loss: 1.3964 2022/09/07 21:24:13 - mmengine - INFO - Epoch(train) [37][1180/1793] lr: 7.5000e-04 eta: 1:57:24 time: 0.1754 data_time: 0.0064 memory: 10464 grad_norm: 8.7945 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.4174 loss: 1.4174 2022/09/07 21:24:16 - mmengine - INFO - Epoch(train) [37][1200/1793] lr: 7.5000e-04 eta: 1:57:17 time: 0.1714 data_time: 0.0066 memory: 10464 grad_norm: 9.0660 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 1.5691 loss: 1.5691 2022/09/07 21:24:20 - mmengine - INFO - Epoch(train) [37][1220/1793] lr: 7.5000e-04 eta: 1:57:10 time: 0.1734 data_time: 0.0093 memory: 10464 grad_norm: 9.2705 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.5707 loss: 1.5707 2022/09/07 21:24:24 - mmengine - INFO - Epoch(train) [37][1240/1793] lr: 7.5000e-04 eta: 1:57:04 time: 0.2024 data_time: 0.0071 memory: 10464 grad_norm: 8.8275 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3655 loss: 1.3655 2022/09/07 21:24:27 - mmengine - INFO - Epoch(train) [37][1260/1793] lr: 7.5000e-04 eta: 1:56:57 time: 0.1700 data_time: 0.0064 memory: 10464 grad_norm: 8.7316 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2234 loss: 1.2234 2022/09/07 21:24:31 - mmengine - INFO - Epoch(train) [37][1280/1793] lr: 7.5000e-04 eta: 1:56:50 time: 0.1757 data_time: 0.0091 memory: 10464 grad_norm: 8.9163 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.2698 loss: 1.2698 2022/09/07 21:24:34 - mmengine - INFO - Epoch(train) [37][1300/1793] lr: 7.5000e-04 eta: 1:56:44 time: 0.1720 data_time: 0.0065 memory: 10464 grad_norm: 8.7103 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0511 loss: 1.0511 2022/09/07 21:24:38 - mmengine - INFO - Epoch(train) [37][1320/1793] lr: 7.5000e-04 eta: 1:56:37 time: 0.1734 data_time: 0.0067 memory: 10464 grad_norm: 8.5924 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1609 loss: 1.1609 2022/09/07 21:24:41 - mmengine - INFO - Epoch(train) [37][1340/1793] lr: 7.5000e-04 eta: 1:56:30 time: 0.1743 data_time: 0.0084 memory: 10464 grad_norm: 8.7999 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4360 loss: 1.4360 2022/09/07 21:24:45 - mmengine - INFO - Epoch(train) [37][1360/1793] lr: 7.5000e-04 eta: 1:56:23 time: 0.1780 data_time: 0.0074 memory: 10464 grad_norm: 9.2321 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1511 loss: 1.1511 2022/09/07 21:24:48 - mmengine - INFO - Epoch(train) [37][1380/1793] lr: 7.5000e-04 eta: 1:56:17 time: 0.1715 data_time: 0.0069 memory: 10464 grad_norm: 8.6568 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1865 loss: 1.1865 2022/09/07 21:24:52 - mmengine - INFO - Epoch(train) [37][1400/1793] lr: 7.5000e-04 eta: 1:56:10 time: 0.1739 data_time: 0.0087 memory: 10464 grad_norm: 8.8885 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3465 loss: 1.3465 2022/09/07 21:24:55 - mmengine - INFO - Epoch(train) [37][1420/1793] lr: 7.5000e-04 eta: 1:56:03 time: 0.1712 data_time: 0.0068 memory: 10464 grad_norm: 9.3750 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2668 loss: 1.2668 2022/09/07 21:24:59 - mmengine - INFO - Epoch(train) [37][1440/1793] lr: 7.5000e-04 eta: 1:55:56 time: 0.1714 data_time: 0.0067 memory: 10464 grad_norm: 8.7807 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.2042 loss: 1.2042 2022/09/07 21:25:01 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:25:02 - mmengine - INFO - Epoch(train) [37][1460/1793] lr: 7.5000e-04 eta: 1:55:50 time: 0.1737 data_time: 0.0088 memory: 10464 grad_norm: 9.2926 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3440 loss: 1.3440 2022/09/07 21:25:06 - mmengine - INFO - Epoch(train) [37][1480/1793] lr: 7.5000e-04 eta: 1:55:43 time: 0.1773 data_time: 0.0081 memory: 10464 grad_norm: 9.1544 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3429 loss: 1.3429 2022/09/07 21:25:09 - mmengine - INFO - Epoch(train) [37][1500/1793] lr: 7.5000e-04 eta: 1:55:36 time: 0.1715 data_time: 0.0067 memory: 10464 grad_norm: 8.9077 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2991 loss: 1.2991 2022/09/07 21:25:12 - mmengine - INFO - Epoch(train) [37][1520/1793] lr: 7.5000e-04 eta: 1:55:29 time: 0.1730 data_time: 0.0095 memory: 10464 grad_norm: 8.6970 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1233 loss: 1.1233 2022/09/07 21:25:16 - mmengine - INFO - Epoch(train) [37][1540/1793] lr: 7.5000e-04 eta: 1:55:23 time: 0.1743 data_time: 0.0071 memory: 10464 grad_norm: 9.1181 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3918 loss: 1.3918 2022/09/07 21:25:19 - mmengine - INFO - Epoch(train) [37][1560/1793] lr: 7.5000e-04 eta: 1:55:16 time: 0.1705 data_time: 0.0062 memory: 10464 grad_norm: 8.9872 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.2146 loss: 1.2146 2022/09/07 21:25:23 - mmengine - INFO - Epoch(train) [37][1580/1793] lr: 7.5000e-04 eta: 1:55:09 time: 0.1808 data_time: 0.0092 memory: 10464 grad_norm: 8.6379 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4048 loss: 1.4048 2022/09/07 21:25:27 - mmengine - INFO - Epoch(train) [37][1600/1793] lr: 7.5000e-04 eta: 1:55:02 time: 0.1815 data_time: 0.0066 memory: 10464 grad_norm: 8.9568 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4067 loss: 1.4067 2022/09/07 21:25:30 - mmengine - INFO - Epoch(train) [37][1620/1793] lr: 7.5000e-04 eta: 1:54:56 time: 0.1713 data_time: 0.0067 memory: 10464 grad_norm: 9.1920 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2870 loss: 1.2870 2022/09/07 21:25:34 - mmengine - INFO - Epoch(train) [37][1640/1793] lr: 7.5000e-04 eta: 1:54:49 time: 0.1763 data_time: 0.0097 memory: 10464 grad_norm: 9.4262 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.3814 loss: 1.3814 2022/09/07 21:25:37 - mmengine - INFO - Epoch(train) [37][1660/1793] lr: 7.5000e-04 eta: 1:54:42 time: 0.1706 data_time: 0.0061 memory: 10464 grad_norm: 8.8352 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1688 loss: 1.1688 2022/09/07 21:25:41 - mmengine - INFO - Epoch(train) [37][1680/1793] lr: 7.5000e-04 eta: 1:54:36 time: 0.1796 data_time: 0.0062 memory: 10464 grad_norm: 9.1179 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2545 loss: 1.2545 2022/09/07 21:25:44 - mmengine - INFO - Epoch(train) [37][1700/1793] lr: 7.5000e-04 eta: 1:54:29 time: 0.1765 data_time: 0.0106 memory: 10464 grad_norm: 8.9133 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.3595 loss: 1.3595 2022/09/07 21:25:48 - mmengine - INFO - Epoch(train) [37][1720/1793] lr: 7.5000e-04 eta: 1:54:22 time: 0.1704 data_time: 0.0060 memory: 10464 grad_norm: 9.1117 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5882 loss: 1.5882 2022/09/07 21:25:51 - mmengine - INFO - Epoch(train) [37][1740/1793] lr: 7.5000e-04 eta: 1:54:15 time: 0.1817 data_time: 0.0064 memory: 10464 grad_norm: 8.7461 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1276 loss: 1.1276 2022/09/07 21:25:55 - mmengine - INFO - Epoch(train) [37][1760/1793] lr: 7.5000e-04 eta: 1:54:09 time: 0.1743 data_time: 0.0087 memory: 10464 grad_norm: 9.0961 top1_acc: 0.1667 top5_acc: 1.0000 loss_cls: 1.2814 loss: 1.2814 2022/09/07 21:25:58 - mmengine - INFO - Epoch(train) [37][1780/1793] lr: 7.5000e-04 eta: 1:54:02 time: 0.1706 data_time: 0.0072 memory: 10464 grad_norm: 8.7287 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2829 loss: 1.2829 2022/09/07 21:26:00 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:26:00 - mmengine - INFO - Epoch(train) [37][1793/1793] lr: 7.5000e-04 eta: 1:54:02 time: 0.1675 data_time: 0.0062 memory: 10464 grad_norm: 9.2763 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 1.2298 loss: 1.2298 2022/09/07 21:26:00 - mmengine - INFO - Saving checkpoint at 37 epochs 2022/09/07 21:26:04 - mmengine - INFO - Epoch(val) [37][20/241] eta: 0:00:12 time: 0.0582 data_time: 0.0090 memory: 1482 2022/09/07 21:26:05 - mmengine - INFO - Epoch(val) [37][40/241] eta: 0:00:10 time: 0.0532 data_time: 0.0049 memory: 1482 2022/09/07 21:26:06 - mmengine - INFO - Epoch(val) [37][60/241] eta: 0:00:09 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 21:26:07 - mmengine - INFO - Epoch(val) [37][80/241] eta: 0:00:08 time: 0.0535 data_time: 0.0050 memory: 1482 2022/09/07 21:26:08 - mmengine - INFO - Epoch(val) [37][100/241] eta: 0:00:07 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 21:26:09 - mmengine - INFO - Epoch(val) [37][120/241] eta: 0:00:06 time: 0.0538 data_time: 0.0052 memory: 1482 2022/09/07 21:26:10 - mmengine - INFO - Epoch(val) [37][140/241] eta: 0:00:05 time: 0.0534 data_time: 0.0049 memory: 1482 2022/09/07 21:26:11 - mmengine - INFO - Epoch(val) [37][160/241] eta: 0:00:04 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 21:26:12 - mmengine - INFO - Epoch(val) [37][180/241] eta: 0:00:03 time: 0.0537 data_time: 0.0052 memory: 1482 2022/09/07 21:26:14 - mmengine - INFO - Epoch(val) [37][200/241] eta: 0:00:02 time: 0.0604 data_time: 0.0049 memory: 1482 2022/09/07 21:26:15 - mmengine - INFO - Epoch(val) [37][220/241] eta: 0:00:01 time: 0.0528 data_time: 0.0047 memory: 1482 2022/09/07 21:26:16 - mmengine - INFO - Epoch(val) [37][240/241] eta: 0:00:00 time: 0.0520 data_time: 0.0043 memory: 1482 2022/09/07 21:26:16 - mmengine - INFO - Epoch(val) [37][241/241] acc/top1: 0.4635 acc/top5: 0.7656 acc/mean1: 0.4265 2022/09/07 21:26:20 - mmengine - INFO - Epoch(train) [38][20/1793] lr: 7.5000e-04 eta: 1:53:50 time: 0.1807 data_time: 0.0111 memory: 10464 grad_norm: 8.5574 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.3711 loss: 1.3711 2022/09/07 21:26:23 - mmengine - INFO - Epoch(train) [38][40/1793] lr: 7.5000e-04 eta: 1:53:44 time: 0.1726 data_time: 0.0069 memory: 10464 grad_norm: 8.5047 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1555 loss: 1.1555 2022/09/07 21:26:27 - mmengine - INFO - Epoch(train) [38][60/1793] lr: 7.5000e-04 eta: 1:53:37 time: 0.1729 data_time: 0.0087 memory: 10464 grad_norm: 8.4218 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1252 loss: 1.1252 2022/09/07 21:26:30 - mmengine - INFO - Epoch(train) [38][80/1793] lr: 7.5000e-04 eta: 1:53:30 time: 0.1730 data_time: 0.0082 memory: 10464 grad_norm: 8.7389 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.2913 loss: 1.2913 2022/09/07 21:26:34 - mmengine - INFO - Epoch(train) [38][100/1793] lr: 7.5000e-04 eta: 1:53:24 time: 0.1879 data_time: 0.0068 memory: 10464 grad_norm: 9.4420 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3534 loss: 1.3534 2022/09/07 21:26:37 - mmengine - INFO - Epoch(train) [38][120/1793] lr: 7.5000e-04 eta: 1:53:17 time: 0.1724 data_time: 0.0064 memory: 10464 grad_norm: 8.5588 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2998 loss: 1.2998 2022/09/07 21:26:41 - mmengine - INFO - Epoch(train) [38][140/1793] lr: 7.5000e-04 eta: 1:53:10 time: 0.1742 data_time: 0.0086 memory: 10464 grad_norm: 8.7537 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.2249 loss: 1.2249 2022/09/07 21:26:44 - mmengine - INFO - Epoch(train) [38][160/1793] lr: 7.5000e-04 eta: 1:53:03 time: 0.1734 data_time: 0.0071 memory: 10464 grad_norm: 8.8984 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3173 loss: 1.3173 2022/09/07 21:26:48 - mmengine - INFO - Epoch(train) [38][180/1793] lr: 7.5000e-04 eta: 1:52:57 time: 0.1703 data_time: 0.0065 memory: 10464 grad_norm: 8.8119 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.3483 loss: 1.3483 2022/09/07 21:26:51 - mmengine - INFO - Epoch(train) [38][200/1793] lr: 7.5000e-04 eta: 1:52:50 time: 0.1760 data_time: 0.0093 memory: 10464 grad_norm: 9.2171 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4086 loss: 1.4086 2022/09/07 21:26:55 - mmengine - INFO - Epoch(train) [38][220/1793] lr: 7.5000e-04 eta: 1:52:43 time: 0.1749 data_time: 0.0066 memory: 10464 grad_norm: 8.7755 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1979 loss: 1.1979 2022/09/07 21:26:58 - mmengine - INFO - Epoch(train) [38][240/1793] lr: 7.5000e-04 eta: 1:52:37 time: 0.1708 data_time: 0.0064 memory: 10464 grad_norm: 8.7281 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0498 loss: 1.0498 2022/09/07 21:27:02 - mmengine - INFO - Epoch(train) [38][260/1793] lr: 7.5000e-04 eta: 1:52:30 time: 0.1769 data_time: 0.0097 memory: 10464 grad_norm: 9.0928 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2544 loss: 1.2544 2022/09/07 21:27:05 - mmengine - INFO - Epoch(train) [38][280/1793] lr: 7.5000e-04 eta: 1:52:23 time: 0.1764 data_time: 0.0085 memory: 10464 grad_norm: 9.3226 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.1921 loss: 1.1921 2022/09/07 21:27:09 - mmengine - INFO - Epoch(train) [38][300/1793] lr: 7.5000e-04 eta: 1:52:17 time: 0.1707 data_time: 0.0064 memory: 10464 grad_norm: 9.4547 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4012 loss: 1.4012 2022/09/07 21:27:12 - mmengine - INFO - Epoch(train) [38][320/1793] lr: 7.5000e-04 eta: 1:52:10 time: 0.1813 data_time: 0.0092 memory: 10464 grad_norm: 8.8704 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1493 loss: 1.1493 2022/09/07 21:27:16 - mmengine - INFO - Epoch(train) [38][340/1793] lr: 7.5000e-04 eta: 1:52:03 time: 0.1759 data_time: 0.0073 memory: 10464 grad_norm: 9.0217 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.4716 loss: 1.4716 2022/09/07 21:27:19 - mmengine - INFO - Epoch(train) [38][360/1793] lr: 7.5000e-04 eta: 1:51:57 time: 0.1714 data_time: 0.0066 memory: 10464 grad_norm: 8.7865 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3950 loss: 1.3950 2022/09/07 21:27:23 - mmengine - INFO - Epoch(train) [38][380/1793] lr: 7.5000e-04 eta: 1:51:50 time: 0.1784 data_time: 0.0089 memory: 10464 grad_norm: 9.2573 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4414 loss: 1.4414 2022/09/07 21:27:26 - mmengine - INFO - Epoch(train) [38][400/1793] lr: 7.5000e-04 eta: 1:51:43 time: 0.1713 data_time: 0.0065 memory: 10464 grad_norm: 8.5928 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.5171 loss: 1.5171 2022/09/07 21:27:30 - mmengine - INFO - Epoch(train) [38][420/1793] lr: 7.5000e-04 eta: 1:51:37 time: 0.1727 data_time: 0.0069 memory: 10464 grad_norm: 8.8626 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4286 loss: 1.4286 2022/09/07 21:27:33 - mmengine - INFO - Epoch(train) [38][440/1793] lr: 7.5000e-04 eta: 1:51:30 time: 0.1796 data_time: 0.0099 memory: 10464 grad_norm: 9.0334 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1944 loss: 1.1944 2022/09/07 21:27:37 - mmengine - INFO - Epoch(train) [38][460/1793] lr: 7.5000e-04 eta: 1:51:23 time: 0.1710 data_time: 0.0065 memory: 10464 grad_norm: 8.4863 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3860 loss: 1.3860 2022/09/07 21:27:40 - mmengine - INFO - Epoch(train) [38][480/1793] lr: 7.5000e-04 eta: 1:51:17 time: 0.1721 data_time: 0.0073 memory: 10464 grad_norm: 9.2573 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2106 loss: 1.2106 2022/09/07 21:27:44 - mmengine - INFO - Epoch(train) [38][500/1793] lr: 7.5000e-04 eta: 1:51:10 time: 0.1863 data_time: 0.0094 memory: 10464 grad_norm: 9.0127 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.3968 loss: 1.3968 2022/09/07 21:27:47 - mmengine - INFO - Epoch(train) [38][520/1793] lr: 7.5000e-04 eta: 1:51:03 time: 0.1715 data_time: 0.0065 memory: 10464 grad_norm: 8.8850 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.4683 loss: 1.4683 2022/09/07 21:27:51 - mmengine - INFO - Epoch(train) [38][540/1793] lr: 7.5000e-04 eta: 1:50:57 time: 0.1726 data_time: 0.0067 memory: 10464 grad_norm: 8.8562 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1788 loss: 1.1788 2022/09/07 21:27:55 - mmengine - INFO - Epoch(train) [38][560/1793] lr: 7.5000e-04 eta: 1:50:50 time: 0.1970 data_time: 0.0101 memory: 10464 grad_norm: 9.0730 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1825 loss: 1.1825 2022/09/07 21:27:58 - mmengine - INFO - Epoch(train) [38][580/1793] lr: 7.5000e-04 eta: 1:50:44 time: 0.1705 data_time: 0.0062 memory: 10464 grad_norm: 8.8286 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2283 loss: 1.2283 2022/09/07 21:28:02 - mmengine - INFO - Epoch(train) [38][600/1793] lr: 7.5000e-04 eta: 1:50:37 time: 0.1811 data_time: 0.0062 memory: 10464 grad_norm: 9.1055 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2697 loss: 1.2697 2022/09/07 21:28:05 - mmengine - INFO - Epoch(train) [38][620/1793] lr: 7.5000e-04 eta: 1:50:30 time: 0.1754 data_time: 0.0092 memory: 10464 grad_norm: 8.6804 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.0166 loss: 1.0166 2022/09/07 21:28:09 - mmengine - INFO - Epoch(train) [38][640/1793] lr: 7.5000e-04 eta: 1:50:24 time: 0.1708 data_time: 0.0066 memory: 10464 grad_norm: 9.1896 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2914 loss: 1.2914 2022/09/07 21:28:12 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:28:12 - mmengine - INFO - Epoch(train) [38][660/1793] lr: 7.5000e-04 eta: 1:50:17 time: 0.1728 data_time: 0.0063 memory: 10464 grad_norm: 9.6418 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.6207 loss: 1.6207 2022/09/07 21:28:16 - mmengine - INFO - Epoch(train) [38][680/1793] lr: 7.5000e-04 eta: 1:50:10 time: 0.1767 data_time: 0.0089 memory: 10464 grad_norm: 9.3432 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4359 loss: 1.4359 2022/09/07 21:28:19 - mmengine - INFO - Epoch(train) [38][700/1793] lr: 7.5000e-04 eta: 1:50:04 time: 0.1710 data_time: 0.0065 memory: 10464 grad_norm: 8.7760 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.1152 loss: 1.1152 2022/09/07 21:28:23 - mmengine - INFO - Epoch(train) [38][720/1793] lr: 7.5000e-04 eta: 1:49:57 time: 0.1722 data_time: 0.0063 memory: 10464 grad_norm: 9.0437 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0519 loss: 1.0519 2022/09/07 21:28:26 - mmengine - INFO - Epoch(train) [38][740/1793] lr: 7.5000e-04 eta: 1:49:51 time: 0.1818 data_time: 0.0106 memory: 10464 grad_norm: 9.1705 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0625 loss: 1.0625 2022/09/07 21:28:30 - mmengine - INFO - Epoch(train) [38][760/1793] lr: 7.5000e-04 eta: 1:49:44 time: 0.1707 data_time: 0.0065 memory: 10464 grad_norm: 9.0818 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.2649 loss: 1.2649 2022/09/07 21:28:33 - mmengine - INFO - Epoch(train) [38][780/1793] lr: 7.5000e-04 eta: 1:49:37 time: 0.1727 data_time: 0.0068 memory: 10464 grad_norm: 8.9505 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2886 loss: 1.2886 2022/09/07 21:28:37 - mmengine - INFO - Epoch(train) [38][800/1793] lr: 7.5000e-04 eta: 1:49:31 time: 0.1782 data_time: 0.0105 memory: 10464 grad_norm: 9.2306 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4164 loss: 1.4164 2022/09/07 21:28:40 - mmengine - INFO - Epoch(train) [38][820/1793] lr: 7.5000e-04 eta: 1:49:24 time: 0.1713 data_time: 0.0067 memory: 10464 grad_norm: 9.0044 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2065 loss: 1.2065 2022/09/07 21:28:44 - mmengine - INFO - Epoch(train) [38][840/1793] lr: 7.5000e-04 eta: 1:49:17 time: 0.1823 data_time: 0.0067 memory: 10464 grad_norm: 8.8944 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4879 loss: 1.4879 2022/09/07 21:28:47 - mmengine - INFO - Epoch(train) [38][860/1793] lr: 7.5000e-04 eta: 1:49:11 time: 0.1725 data_time: 0.0088 memory: 10464 grad_norm: 9.1093 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 1.4694 loss: 1.4694 2022/09/07 21:28:51 - mmengine - INFO - Epoch(train) [38][880/1793] lr: 7.5000e-04 eta: 1:49:04 time: 0.1739 data_time: 0.0064 memory: 10464 grad_norm: 8.9327 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3843 loss: 1.3843 2022/09/07 21:28:54 - mmengine - INFO - Epoch(train) [38][900/1793] lr: 7.5000e-04 eta: 1:48:58 time: 0.1746 data_time: 0.0068 memory: 10464 grad_norm: 9.0954 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1669 loss: 1.1669 2022/09/07 21:28:58 - mmengine - INFO - Epoch(train) [38][920/1793] lr: 7.5000e-04 eta: 1:48:51 time: 0.1723 data_time: 0.0084 memory: 10464 grad_norm: 9.1391 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2624 loss: 1.2624 2022/09/07 21:29:01 - mmengine - INFO - Epoch(train) [38][940/1793] lr: 7.5000e-04 eta: 1:48:44 time: 0.1724 data_time: 0.0064 memory: 10464 grad_norm: 9.0197 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2091 loss: 1.2091 2022/09/07 21:29:05 - mmengine - INFO - Epoch(train) [38][960/1793] lr: 7.5000e-04 eta: 1:48:38 time: 0.1720 data_time: 0.0077 memory: 10464 grad_norm: 9.2973 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3596 loss: 1.3596 2022/09/07 21:29:08 - mmengine - INFO - Epoch(train) [38][980/1793] lr: 7.5000e-04 eta: 1:48:31 time: 0.1744 data_time: 0.0097 memory: 10464 grad_norm: 9.1408 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3209 loss: 1.3209 2022/09/07 21:29:12 - mmengine - INFO - Epoch(train) [38][1000/1793] lr: 7.5000e-04 eta: 1:48:24 time: 0.1707 data_time: 0.0064 memory: 10464 grad_norm: 9.1995 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.1842 loss: 1.1842 2022/09/07 21:29:15 - mmengine - INFO - Epoch(train) [38][1020/1793] lr: 7.5000e-04 eta: 1:48:18 time: 0.1712 data_time: 0.0075 memory: 10464 grad_norm: 8.8384 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3825 loss: 1.3825 2022/09/07 21:29:18 - mmengine - INFO - Epoch(train) [38][1040/1793] lr: 7.5000e-04 eta: 1:48:11 time: 0.1742 data_time: 0.0076 memory: 10464 grad_norm: 9.4836 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.2391 loss: 1.2391 2022/09/07 21:29:22 - mmengine - INFO - Epoch(train) [38][1060/1793] lr: 7.5000e-04 eta: 1:48:05 time: 0.1729 data_time: 0.0062 memory: 10464 grad_norm: 9.2371 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.5019 loss: 1.5019 2022/09/07 21:29:25 - mmengine - INFO - Epoch(train) [38][1080/1793] lr: 7.5000e-04 eta: 1:47:58 time: 0.1735 data_time: 0.0071 memory: 10464 grad_norm: 9.3733 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4109 loss: 1.4109 2022/09/07 21:29:29 - mmengine - INFO - Epoch(train) [38][1100/1793] lr: 7.5000e-04 eta: 1:47:51 time: 0.1727 data_time: 0.0085 memory: 10464 grad_norm: 9.3902 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3234 loss: 1.3234 2022/09/07 21:29:32 - mmengine - INFO - Epoch(train) [38][1120/1793] lr: 7.5000e-04 eta: 1:47:45 time: 0.1746 data_time: 0.0070 memory: 10464 grad_norm: 9.3535 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3358 loss: 1.3358 2022/09/07 21:29:36 - mmengine - INFO - Epoch(train) [38][1140/1793] lr: 7.5000e-04 eta: 1:47:38 time: 0.1731 data_time: 0.0068 memory: 10464 grad_norm: 9.0963 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2514 loss: 1.2514 2022/09/07 21:29:39 - mmengine - INFO - Epoch(train) [38][1160/1793] lr: 7.5000e-04 eta: 1:47:32 time: 0.1731 data_time: 0.0086 memory: 10464 grad_norm: 9.1998 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2801 loss: 1.2801 2022/09/07 21:29:43 - mmengine - INFO - Epoch(train) [38][1180/1793] lr: 7.5000e-04 eta: 1:47:25 time: 0.1811 data_time: 0.0062 memory: 10464 grad_norm: 9.1262 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.5101 loss: 1.5101 2022/09/07 21:29:46 - mmengine - INFO - Epoch(train) [38][1200/1793] lr: 7.5000e-04 eta: 1:47:18 time: 0.1727 data_time: 0.0072 memory: 10464 grad_norm: 9.5390 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2538 loss: 1.2538 2022/09/07 21:29:50 - mmengine - INFO - Epoch(train) [38][1220/1793] lr: 7.5000e-04 eta: 1:47:12 time: 0.1727 data_time: 0.0083 memory: 10464 grad_norm: 9.0181 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1638 loss: 1.1638 2022/09/07 21:29:53 - mmengine - INFO - Epoch(train) [38][1240/1793] lr: 7.5000e-04 eta: 1:47:05 time: 0.1709 data_time: 0.0063 memory: 10464 grad_norm: 9.0766 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0254 loss: 1.0254 2022/09/07 21:29:57 - mmengine - INFO - Epoch(train) [38][1260/1793] lr: 7.5000e-04 eta: 1:46:59 time: 0.1742 data_time: 0.0065 memory: 10464 grad_norm: 8.9076 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4457 loss: 1.4457 2022/09/07 21:30:00 - mmengine - INFO - Epoch(train) [38][1280/1793] lr: 7.5000e-04 eta: 1:46:52 time: 0.1734 data_time: 0.0096 memory: 10464 grad_norm: 9.3695 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1593 loss: 1.1593 2022/09/07 21:30:04 - mmengine - INFO - Epoch(train) [38][1300/1793] lr: 7.5000e-04 eta: 1:46:45 time: 0.1775 data_time: 0.0073 memory: 10464 grad_norm: 9.2771 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2079 loss: 1.2079 2022/09/07 21:30:07 - mmengine - INFO - Epoch(train) [38][1320/1793] lr: 7.5000e-04 eta: 1:46:39 time: 0.1700 data_time: 0.0066 memory: 10464 grad_norm: 9.2806 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4043 loss: 1.4043 2022/09/07 21:30:11 - mmengine - INFO - Epoch(train) [38][1340/1793] lr: 7.5000e-04 eta: 1:46:32 time: 0.1735 data_time: 0.0095 memory: 10464 grad_norm: 9.5719 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.3950 loss: 1.3950 2022/09/07 21:30:14 - mmengine - INFO - Epoch(train) [38][1360/1793] lr: 7.5000e-04 eta: 1:46:26 time: 0.1734 data_time: 0.0070 memory: 10464 grad_norm: 9.6002 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2052 loss: 1.2052 2022/09/07 21:30:18 - mmengine - INFO - Epoch(train) [38][1380/1793] lr: 7.5000e-04 eta: 1:46:19 time: 0.1711 data_time: 0.0065 memory: 10464 grad_norm: 9.0342 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3530 loss: 1.3530 2022/09/07 21:30:21 - mmengine - INFO - Epoch(train) [38][1400/1793] lr: 7.5000e-04 eta: 1:46:12 time: 0.1746 data_time: 0.0085 memory: 10464 grad_norm: 9.0397 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.3013 loss: 1.3013 2022/09/07 21:30:25 - mmengine - INFO - Epoch(train) [38][1420/1793] lr: 7.5000e-04 eta: 1:46:06 time: 0.1764 data_time: 0.0070 memory: 10464 grad_norm: 9.3007 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2732 loss: 1.2732 2022/09/07 21:30:28 - mmengine - INFO - Epoch(train) [38][1440/1793] lr: 7.5000e-04 eta: 1:45:59 time: 0.1724 data_time: 0.0068 memory: 10464 grad_norm: 9.3678 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1298 loss: 1.1298 2022/09/07 21:30:31 - mmengine - INFO - Epoch(train) [38][1460/1793] lr: 7.5000e-04 eta: 1:45:53 time: 0.1732 data_time: 0.0086 memory: 10464 grad_norm: 9.3587 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5145 loss: 1.5145 2022/09/07 21:30:35 - mmengine - INFO - Epoch(train) [38][1480/1793] lr: 7.5000e-04 eta: 1:45:46 time: 0.1739 data_time: 0.0065 memory: 10464 grad_norm: 9.2939 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1032 loss: 1.1032 2022/09/07 21:30:38 - mmengine - INFO - Epoch(train) [38][1500/1793] lr: 7.5000e-04 eta: 1:45:40 time: 0.1710 data_time: 0.0067 memory: 10464 grad_norm: 9.3573 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.5245 loss: 1.5245 2022/09/07 21:30:42 - mmengine - INFO - Epoch(train) [38][1520/1793] lr: 7.5000e-04 eta: 1:45:33 time: 0.1752 data_time: 0.0099 memory: 10464 grad_norm: 9.7790 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3193 loss: 1.3193 2022/09/07 21:30:45 - mmengine - INFO - Epoch(train) [38][1540/1793] lr: 7.5000e-04 eta: 1:45:27 time: 0.1784 data_time: 0.0077 memory: 10464 grad_norm: 9.4026 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3596 loss: 1.3596 2022/09/07 21:30:49 - mmengine - INFO - Epoch(train) [38][1560/1793] lr: 7.5000e-04 eta: 1:45:20 time: 0.1709 data_time: 0.0062 memory: 10464 grad_norm: 8.9906 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2507 loss: 1.2507 2022/09/07 21:30:53 - mmengine - INFO - Epoch(train) [38][1580/1793] lr: 7.5000e-04 eta: 1:45:14 time: 0.1999 data_time: 0.0094 memory: 10464 grad_norm: 9.5334 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4660 loss: 1.4660 2022/09/07 21:30:56 - mmengine - INFO - Epoch(train) [38][1600/1793] lr: 7.5000e-04 eta: 1:45:07 time: 0.1706 data_time: 0.0065 memory: 10464 grad_norm: 9.4172 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3055 loss: 1.3055 2022/09/07 21:31:00 - mmengine - INFO - Epoch(train) [38][1620/1793] lr: 7.5000e-04 eta: 1:45:00 time: 0.1704 data_time: 0.0066 memory: 10464 grad_norm: 9.3490 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.5471 loss: 1.5471 2022/09/07 21:31:03 - mmengine - INFO - Epoch(train) [38][1640/1793] lr: 7.5000e-04 eta: 1:44:54 time: 0.1765 data_time: 0.0098 memory: 10464 grad_norm: 9.1755 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3279 loss: 1.3279 2022/09/07 21:31:07 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:31:07 - mmengine - INFO - Epoch(train) [38][1660/1793] lr: 7.5000e-04 eta: 1:44:47 time: 0.1748 data_time: 0.0071 memory: 10464 grad_norm: 9.4854 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1263 loss: 1.1263 2022/09/07 21:31:10 - mmengine - INFO - Epoch(train) [38][1680/1793] lr: 7.5000e-04 eta: 1:44:41 time: 0.1711 data_time: 0.0065 memory: 10464 grad_norm: 9.3863 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1090 loss: 1.1090 2022/09/07 21:31:14 - mmengine - INFO - Epoch(train) [38][1700/1793] lr: 7.5000e-04 eta: 1:44:34 time: 0.1791 data_time: 0.0087 memory: 10464 grad_norm: 9.9066 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4024 loss: 1.4024 2022/09/07 21:31:17 - mmengine - INFO - Epoch(train) [38][1720/1793] lr: 7.5000e-04 eta: 1:44:28 time: 0.1707 data_time: 0.0065 memory: 10464 grad_norm: 9.5151 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.2932 loss: 1.2932 2022/09/07 21:31:21 - mmengine - INFO - Epoch(train) [38][1740/1793] lr: 7.5000e-04 eta: 1:44:21 time: 0.1714 data_time: 0.0069 memory: 10464 grad_norm: 9.2048 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.5670 loss: 1.5670 2022/09/07 21:31:24 - mmengine - INFO - Epoch(train) [38][1760/1793] lr: 7.5000e-04 eta: 1:44:15 time: 0.1858 data_time: 0.0093 memory: 10464 grad_norm: 9.4252 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7528 loss: 1.7528 2022/09/07 21:31:28 - mmengine - INFO - Epoch(train) [38][1780/1793] lr: 7.5000e-04 eta: 1:44:08 time: 0.1733 data_time: 0.0073 memory: 10464 grad_norm: 9.4252 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4820 loss: 1.4820 2022/09/07 21:31:30 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:31:30 - mmengine - INFO - Epoch(train) [38][1793/1793] lr: 7.5000e-04 eta: 1:44:08 time: 0.1670 data_time: 0.0062 memory: 10464 grad_norm: 9.5887 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 1.5564 loss: 1.5564 2022/09/07 21:31:30 - mmengine - INFO - Saving checkpoint at 38 epochs 2022/09/07 21:31:34 - mmengine - INFO - Epoch(val) [38][20/241] eta: 0:00:12 time: 0.0587 data_time: 0.0089 memory: 1482 2022/09/07 21:31:35 - mmengine - INFO - Epoch(val) [38][40/241] eta: 0:00:10 time: 0.0535 data_time: 0.0050 memory: 1482 2022/09/07 21:31:36 - mmengine - INFO - Epoch(val) [38][60/241] eta: 0:00:09 time: 0.0535 data_time: 0.0049 memory: 1482 2022/09/07 21:31:37 - mmengine - INFO - Epoch(val) [38][80/241] eta: 0:00:08 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 21:31:38 - mmengine - INFO - Epoch(val) [38][100/241] eta: 0:00:07 time: 0.0536 data_time: 0.0050 memory: 1482 2022/09/07 21:31:39 - mmengine - INFO - Epoch(val) [38][120/241] eta: 0:00:06 time: 0.0537 data_time: 0.0052 memory: 1482 2022/09/07 21:31:40 - mmengine - INFO - Epoch(val) [38][140/241] eta: 0:00:05 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 21:31:41 - mmengine - INFO - Epoch(val) [38][160/241] eta: 0:00:04 time: 0.0534 data_time: 0.0050 memory: 1482 2022/09/07 21:31:42 - mmengine - INFO - Epoch(val) [38][180/241] eta: 0:00:03 time: 0.0535 data_time: 0.0050 memory: 1482 2022/09/07 21:31:43 - mmengine - INFO - Epoch(val) [38][200/241] eta: 0:00:02 time: 0.0528 data_time: 0.0047 memory: 1482 2022/09/07 21:31:45 - mmengine - INFO - Epoch(val) [38][220/241] eta: 0:00:01 time: 0.0618 data_time: 0.0061 memory: 1482 2022/09/07 21:31:46 - mmengine - INFO - Epoch(val) [38][240/241] eta: 0:00:00 time: 0.0524 data_time: 0.0045 memory: 1482 2022/09/07 21:31:46 - mmengine - INFO - Epoch(val) [38][241/241] acc/top1: 0.4654 acc/top5: 0.7706 acc/mean1: 0.4291 2022/09/07 21:31:50 - mmengine - INFO - Epoch(train) [39][20/1793] lr: 7.5000e-04 eta: 1:43:57 time: 0.1797 data_time: 0.0117 memory: 10464 grad_norm: 8.5908 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0398 loss: 1.0398 2022/09/07 21:31:53 - mmengine - INFO - Epoch(train) [39][40/1793] lr: 7.5000e-04 eta: 1:43:50 time: 0.1707 data_time: 0.0060 memory: 10464 grad_norm: 8.9467 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.5159 loss: 1.5159 2022/09/07 21:31:57 - mmengine - INFO - Epoch(train) [39][60/1793] lr: 7.5000e-04 eta: 1:43:44 time: 0.1712 data_time: 0.0068 memory: 10464 grad_norm: 9.2806 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.3404 loss: 1.3404 2022/09/07 21:32:00 - mmengine - INFO - Epoch(train) [39][80/1793] lr: 7.5000e-04 eta: 1:43:37 time: 0.1728 data_time: 0.0087 memory: 10464 grad_norm: 9.3703 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2844 loss: 1.2844 2022/09/07 21:32:04 - mmengine - INFO - Epoch(train) [39][100/1793] lr: 7.5000e-04 eta: 1:43:30 time: 0.1748 data_time: 0.0068 memory: 10464 grad_norm: 9.3630 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.2676 loss: 1.2676 2022/09/07 21:32:08 - mmengine - INFO - Epoch(train) [39][120/1793] lr: 7.5000e-04 eta: 1:43:24 time: 0.2031 data_time: 0.0072 memory: 10464 grad_norm: 8.9127 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2692 loss: 1.2692 2022/09/07 21:32:11 - mmengine - INFO - Epoch(train) [39][140/1793] lr: 7.5000e-04 eta: 1:43:18 time: 0.1751 data_time: 0.0089 memory: 10464 grad_norm: 9.0268 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1857 loss: 1.1857 2022/09/07 21:32:15 - mmengine - INFO - Epoch(train) [39][160/1793] lr: 7.5000e-04 eta: 1:43:11 time: 0.1706 data_time: 0.0064 memory: 10464 grad_norm: 9.2616 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.2276 loss: 1.2276 2022/09/07 21:32:18 - mmengine - INFO - Epoch(train) [39][180/1793] lr: 7.5000e-04 eta: 1:43:05 time: 0.1721 data_time: 0.0068 memory: 10464 grad_norm: 9.1098 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3065 loss: 1.3065 2022/09/07 21:32:22 - mmengine - INFO - Epoch(train) [39][200/1793] lr: 7.5000e-04 eta: 1:42:58 time: 0.1764 data_time: 0.0090 memory: 10464 grad_norm: 9.7736 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2475 loss: 1.2475 2022/09/07 21:32:25 - mmengine - INFO - Epoch(train) [39][220/1793] lr: 7.5000e-04 eta: 1:42:52 time: 0.1806 data_time: 0.0070 memory: 10464 grad_norm: 9.2335 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.0422 loss: 1.0422 2022/09/07 21:32:29 - mmengine - INFO - Epoch(train) [39][240/1793] lr: 7.5000e-04 eta: 1:42:45 time: 0.1705 data_time: 0.0063 memory: 10464 grad_norm: 8.8400 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1354 loss: 1.1354 2022/09/07 21:32:32 - mmengine - INFO - Epoch(train) [39][260/1793] lr: 7.5000e-04 eta: 1:42:38 time: 0.1759 data_time: 0.0094 memory: 10464 grad_norm: 9.4185 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4315 loss: 1.4315 2022/09/07 21:32:36 - mmengine - INFO - Epoch(train) [39][280/1793] lr: 7.5000e-04 eta: 1:42:32 time: 0.1761 data_time: 0.0062 memory: 10464 grad_norm: 9.2116 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2241 loss: 1.2241 2022/09/07 21:32:39 - mmengine - INFO - Epoch(train) [39][300/1793] lr: 7.5000e-04 eta: 1:42:25 time: 0.1710 data_time: 0.0065 memory: 10464 grad_norm: 9.6872 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1845 loss: 1.1845 2022/09/07 21:32:43 - mmengine - INFO - Epoch(train) [39][320/1793] lr: 7.5000e-04 eta: 1:42:19 time: 0.1785 data_time: 0.0093 memory: 10464 grad_norm: 9.3639 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3392 loss: 1.3392 2022/09/07 21:32:46 - mmengine - INFO - Epoch(train) [39][340/1793] lr: 7.5000e-04 eta: 1:42:13 time: 0.1941 data_time: 0.0072 memory: 10464 grad_norm: 9.3949 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2204 loss: 1.2204 2022/09/07 21:32:50 - mmengine - INFO - Epoch(train) [39][360/1793] lr: 7.5000e-04 eta: 1:42:06 time: 0.1716 data_time: 0.0072 memory: 10464 grad_norm: 8.9990 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.1989 loss: 1.1989 2022/09/07 21:32:53 - mmengine - INFO - Epoch(train) [39][380/1793] lr: 7.5000e-04 eta: 1:42:00 time: 0.1737 data_time: 0.0087 memory: 10464 grad_norm: 9.7070 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.3674 loss: 1.3674 2022/09/07 21:32:57 - mmengine - INFO - Epoch(train) [39][400/1793] lr: 7.5000e-04 eta: 1:41:53 time: 0.1727 data_time: 0.0071 memory: 10464 grad_norm: 9.6044 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2856 loss: 1.2856 2022/09/07 21:33:00 - mmengine - INFO - Epoch(train) [39][420/1793] lr: 7.5000e-04 eta: 1:41:47 time: 0.1709 data_time: 0.0068 memory: 10464 grad_norm: 9.2860 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2804 loss: 1.2804 2022/09/07 21:33:04 - mmengine - INFO - Epoch(train) [39][440/1793] lr: 7.5000e-04 eta: 1:41:40 time: 0.1855 data_time: 0.0091 memory: 10464 grad_norm: 9.3785 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.1309 loss: 1.1309 2022/09/07 21:33:07 - mmengine - INFO - Epoch(train) [39][460/1793] lr: 7.5000e-04 eta: 1:41:34 time: 0.1715 data_time: 0.0065 memory: 10464 grad_norm: 9.4662 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2342 loss: 1.2342 2022/09/07 21:33:11 - mmengine - INFO - Epoch(train) [39][480/1793] lr: 7.5000e-04 eta: 1:41:27 time: 0.1707 data_time: 0.0063 memory: 10464 grad_norm: 9.7109 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1704 loss: 1.1704 2022/09/07 21:33:14 - mmengine - INFO - Epoch(train) [39][500/1793] lr: 7.5000e-04 eta: 1:41:21 time: 0.1733 data_time: 0.0092 memory: 10464 grad_norm: 9.5055 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2727 loss: 1.2727 2022/09/07 21:33:18 - mmengine - INFO - Epoch(train) [39][520/1793] lr: 7.5000e-04 eta: 1:41:14 time: 0.1714 data_time: 0.0067 memory: 10464 grad_norm: 9.4451 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.5050 loss: 1.5050 2022/09/07 21:33:21 - mmengine - INFO - Epoch(train) [39][540/1793] lr: 7.5000e-04 eta: 1:41:08 time: 0.1730 data_time: 0.0062 memory: 10464 grad_norm: 9.0915 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4862 loss: 1.4862 2022/09/07 21:33:25 - mmengine - INFO - Epoch(train) [39][560/1793] lr: 7.5000e-04 eta: 1:41:01 time: 0.1819 data_time: 0.0105 memory: 10464 grad_norm: 9.4575 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1989 loss: 1.1989 2022/09/07 21:33:28 - mmengine - INFO - Epoch(train) [39][580/1793] lr: 7.5000e-04 eta: 1:40:55 time: 0.1701 data_time: 0.0067 memory: 10464 grad_norm: 9.4240 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5247 loss: 1.5247 2022/09/07 21:33:32 - mmengine - INFO - Epoch(train) [39][600/1793] lr: 7.5000e-04 eta: 1:40:48 time: 0.1735 data_time: 0.0063 memory: 10464 grad_norm: 9.7120 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2231 loss: 1.2231 2022/09/07 21:33:35 - mmengine - INFO - Epoch(train) [39][620/1793] lr: 7.5000e-04 eta: 1:40:42 time: 0.1754 data_time: 0.0093 memory: 10464 grad_norm: 9.6611 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1393 loss: 1.1393 2022/09/07 21:33:39 - mmengine - INFO - Epoch(train) [39][640/1793] lr: 7.5000e-04 eta: 1:40:35 time: 0.1709 data_time: 0.0063 memory: 10464 grad_norm: 9.5364 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.5470 loss: 1.5470 2022/09/07 21:33:42 - mmengine - INFO - Epoch(train) [39][660/1793] lr: 7.5000e-04 eta: 1:40:29 time: 0.1738 data_time: 0.0063 memory: 10464 grad_norm: 9.4235 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.3561 loss: 1.3561 2022/09/07 21:33:46 - mmengine - INFO - Epoch(train) [39][680/1793] lr: 7.5000e-04 eta: 1:40:22 time: 0.1927 data_time: 0.0131 memory: 10464 grad_norm: 9.3409 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.2728 loss: 1.2728 2022/09/07 21:33:49 - mmengine - INFO - Epoch(train) [39][700/1793] lr: 7.5000e-04 eta: 1:40:16 time: 0.1724 data_time: 0.0061 memory: 10464 grad_norm: 9.3579 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.3137 loss: 1.3137 2022/09/07 21:33:53 - mmengine - INFO - Epoch(train) [39][720/1793] lr: 7.5000e-04 eta: 1:40:09 time: 0.1764 data_time: 0.0067 memory: 10464 grad_norm: 9.2018 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1347 loss: 1.1347 2022/09/07 21:33:57 - mmengine - INFO - Epoch(train) [39][740/1793] lr: 7.5000e-04 eta: 1:40:03 time: 0.1751 data_time: 0.0094 memory: 10464 grad_norm: 9.4865 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4153 loss: 1.4153 2022/09/07 21:34:00 - mmengine - INFO - Epoch(train) [39][760/1793] lr: 7.5000e-04 eta: 1:39:56 time: 0.1702 data_time: 0.0062 memory: 10464 grad_norm: 9.5550 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1689 loss: 1.1689 2022/09/07 21:34:03 - mmengine - INFO - Epoch(train) [39][780/1793] lr: 7.5000e-04 eta: 1:39:50 time: 0.1766 data_time: 0.0067 memory: 10464 grad_norm: 9.8968 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4074 loss: 1.4074 2022/09/07 21:34:07 - mmengine - INFO - Epoch(train) [39][800/1793] lr: 7.5000e-04 eta: 1:39:43 time: 0.1783 data_time: 0.0095 memory: 10464 grad_norm: 9.4000 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3226 loss: 1.3226 2022/09/07 21:34:11 - mmengine - INFO - Epoch(train) [39][820/1793] lr: 7.5000e-04 eta: 1:39:37 time: 0.1732 data_time: 0.0065 memory: 10464 grad_norm: 9.2071 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.1238 loss: 1.1238 2022/09/07 21:34:14 - mmengine - INFO - Epoch(train) [39][840/1793] lr: 7.5000e-04 eta: 1:39:31 time: 0.1733 data_time: 0.0074 memory: 10464 grad_norm: 9.2812 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2223 loss: 1.2223 2022/09/07 21:34:17 - mmengine - INFO - Epoch(train) [39][860/1793] lr: 7.5000e-04 eta: 1:39:24 time: 0.1749 data_time: 0.0101 memory: 10464 grad_norm: 9.6265 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3382 loss: 1.3382 2022/09/07 21:34:19 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:34:21 - mmengine - INFO - Epoch(train) [39][880/1793] lr: 7.5000e-04 eta: 1:39:18 time: 0.1713 data_time: 0.0065 memory: 10464 grad_norm: 9.6045 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.3722 loss: 1.3722 2022/09/07 21:34:25 - mmengine - INFO - Epoch(train) [39][900/1793] lr: 7.5000e-04 eta: 1:39:11 time: 0.1939 data_time: 0.0067 memory: 10464 grad_norm: 9.3322 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 0.9956 loss: 0.9956 2022/09/07 21:34:28 - mmengine - INFO - Epoch(train) [39][920/1793] lr: 7.5000e-04 eta: 1:39:05 time: 0.1750 data_time: 0.0096 memory: 10464 grad_norm: 9.3119 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.3227 loss: 1.3227 2022/09/07 21:34:32 - mmengine - INFO - Epoch(train) [39][940/1793] lr: 7.5000e-04 eta: 1:38:58 time: 0.1731 data_time: 0.0063 memory: 10464 grad_norm: 9.4744 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.1097 loss: 1.1097 2022/09/07 21:34:35 - mmengine - INFO - Epoch(train) [39][960/1793] lr: 7.5000e-04 eta: 1:38:52 time: 0.1720 data_time: 0.0067 memory: 10464 grad_norm: 9.7001 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2461 loss: 1.2461 2022/09/07 21:34:39 - mmengine - INFO - Epoch(train) [39][980/1793] lr: 7.5000e-04 eta: 1:38:45 time: 0.1731 data_time: 0.0087 memory: 10464 grad_norm: 9.4164 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3759 loss: 1.3759 2022/09/07 21:34:42 - mmengine - INFO - Epoch(train) [39][1000/1793] lr: 7.5000e-04 eta: 1:38:39 time: 0.1801 data_time: 0.0065 memory: 10464 grad_norm: 9.9346 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1981 loss: 1.1981 2022/09/07 21:34:46 - mmengine - INFO - Epoch(train) [39][1020/1793] lr: 7.5000e-04 eta: 1:38:33 time: 0.2060 data_time: 0.0072 memory: 10464 grad_norm: 9.5135 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.4397 loss: 1.4397 2022/09/07 21:34:50 - mmengine - INFO - Epoch(train) [39][1040/1793] lr: 7.5000e-04 eta: 1:38:26 time: 0.1738 data_time: 0.0087 memory: 10464 grad_norm: 9.6563 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4626 loss: 1.4626 2022/09/07 21:34:53 - mmengine - INFO - Epoch(train) [39][1060/1793] lr: 7.5000e-04 eta: 1:38:20 time: 0.1732 data_time: 0.0065 memory: 10464 grad_norm: 9.1980 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.4081 loss: 1.4081 2022/09/07 21:34:57 - mmengine - INFO - Epoch(train) [39][1080/1793] lr: 7.5000e-04 eta: 1:38:13 time: 0.1714 data_time: 0.0067 memory: 10464 grad_norm: 9.9571 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.6058 loss: 1.6058 2022/09/07 21:35:00 - mmengine - INFO - Epoch(train) [39][1100/1793] lr: 7.5000e-04 eta: 1:38:07 time: 0.1740 data_time: 0.0089 memory: 10464 grad_norm: 9.5682 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3862 loss: 1.3862 2022/09/07 21:35:04 - mmengine - INFO - Epoch(train) [39][1120/1793] lr: 7.5000e-04 eta: 1:38:01 time: 0.1800 data_time: 0.0066 memory: 10464 grad_norm: 9.8130 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3924 loss: 1.3924 2022/09/07 21:35:07 - mmengine - INFO - Epoch(train) [39][1140/1793] lr: 7.5000e-04 eta: 1:37:54 time: 0.1736 data_time: 0.0081 memory: 10464 grad_norm: 9.8549 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.2922 loss: 1.2922 2022/09/07 21:35:11 - mmengine - INFO - Epoch(train) [39][1160/1793] lr: 7.5000e-04 eta: 1:37:48 time: 0.1728 data_time: 0.0092 memory: 10464 grad_norm: 9.4840 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.2903 loss: 1.2903 2022/09/07 21:35:14 - mmengine - INFO - Epoch(train) [39][1180/1793] lr: 7.5000e-04 eta: 1:37:41 time: 0.1763 data_time: 0.0068 memory: 10464 grad_norm: 9.7340 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.2238 loss: 1.2238 2022/09/07 21:35:18 - mmengine - INFO - Epoch(train) [39][1200/1793] lr: 7.5000e-04 eta: 1:37:35 time: 0.1709 data_time: 0.0067 memory: 10464 grad_norm: 9.5802 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2391 loss: 1.2391 2022/09/07 21:35:21 - mmengine - INFO - Epoch(train) [39][1220/1793] lr: 7.5000e-04 eta: 1:37:28 time: 0.1730 data_time: 0.0089 memory: 10464 grad_norm: 9.5890 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3716 loss: 1.3716 2022/09/07 21:35:25 - mmengine - INFO - Epoch(train) [39][1240/1793] lr: 7.5000e-04 eta: 1:37:22 time: 0.1789 data_time: 0.0069 memory: 10464 grad_norm: 9.5058 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4647 loss: 1.4647 2022/09/07 21:35:28 - mmengine - INFO - Epoch(train) [39][1260/1793] lr: 7.5000e-04 eta: 1:37:16 time: 0.1712 data_time: 0.0064 memory: 10464 grad_norm: 9.7503 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1842 loss: 1.1842 2022/09/07 21:35:32 - mmengine - INFO - Epoch(train) [39][1280/1793] lr: 7.5000e-04 eta: 1:37:09 time: 0.1764 data_time: 0.0089 memory: 10464 grad_norm: 9.4819 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.1776 loss: 1.1776 2022/09/07 21:35:35 - mmengine - INFO - Epoch(train) [39][1300/1793] lr: 7.5000e-04 eta: 1:37:03 time: 0.1723 data_time: 0.0074 memory: 10464 grad_norm: 9.5326 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2181 loss: 1.2181 2022/09/07 21:35:39 - mmengine - INFO - Epoch(train) [39][1320/1793] lr: 7.5000e-04 eta: 1:36:56 time: 0.1721 data_time: 0.0066 memory: 10464 grad_norm: 9.5766 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3341 loss: 1.3341 2022/09/07 21:35:42 - mmengine - INFO - Epoch(train) [39][1340/1793] lr: 7.5000e-04 eta: 1:36:50 time: 0.1767 data_time: 0.0087 memory: 10464 grad_norm: 9.1646 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3019 loss: 1.3019 2022/09/07 21:35:46 - mmengine - INFO - Epoch(train) [39][1360/1793] lr: 7.5000e-04 eta: 1:36:43 time: 0.1803 data_time: 0.0071 memory: 10464 grad_norm: 9.7260 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2007 loss: 1.2007 2022/09/07 21:35:49 - mmengine - INFO - Epoch(train) [39][1380/1793] lr: 7.5000e-04 eta: 1:36:37 time: 0.1706 data_time: 0.0064 memory: 10464 grad_norm: 9.6667 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1570 loss: 1.1570 2022/09/07 21:35:53 - mmengine - INFO - Epoch(train) [39][1400/1793] lr: 7.5000e-04 eta: 1:36:31 time: 0.1856 data_time: 0.0096 memory: 10464 grad_norm: 9.9724 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2455 loss: 1.2455 2022/09/07 21:35:56 - mmengine - INFO - Epoch(train) [39][1420/1793] lr: 7.5000e-04 eta: 1:36:24 time: 0.1715 data_time: 0.0078 memory: 10464 grad_norm: 9.7905 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1455 loss: 1.1455 2022/09/07 21:36:00 - mmengine - INFO - Epoch(train) [39][1440/1793] lr: 7.5000e-04 eta: 1:36:18 time: 0.1734 data_time: 0.0068 memory: 10464 grad_norm: 9.8954 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3334 loss: 1.3334 2022/09/07 21:36:03 - mmengine - INFO - Epoch(train) [39][1460/1793] lr: 7.5000e-04 eta: 1:36:11 time: 0.1770 data_time: 0.0094 memory: 10464 grad_norm: 9.6010 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1793 loss: 1.1793 2022/09/07 21:36:07 - mmengine - INFO - Epoch(train) [39][1480/1793] lr: 7.5000e-04 eta: 1:36:05 time: 0.1894 data_time: 0.0073 memory: 10464 grad_norm: 9.3357 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1641 loss: 1.1641 2022/09/07 21:36:11 - mmengine - INFO - Epoch(train) [39][1500/1793] lr: 7.5000e-04 eta: 1:35:59 time: 0.1708 data_time: 0.0065 memory: 10464 grad_norm: 9.7027 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4334 loss: 1.4334 2022/09/07 21:36:14 - mmengine - INFO - Epoch(train) [39][1520/1793] lr: 7.5000e-04 eta: 1:35:52 time: 0.1802 data_time: 0.0096 memory: 10464 grad_norm: 9.4025 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0903 loss: 1.0903 2022/09/07 21:36:18 - mmengine - INFO - Epoch(train) [39][1540/1793] lr: 7.5000e-04 eta: 1:35:46 time: 0.1712 data_time: 0.0068 memory: 10464 grad_norm: 9.6669 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1891 loss: 1.1891 2022/09/07 21:36:21 - mmengine - INFO - Epoch(train) [39][1560/1793] lr: 7.5000e-04 eta: 1:35:39 time: 0.1715 data_time: 0.0063 memory: 10464 grad_norm: 9.5423 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2909 loss: 1.2909 2022/09/07 21:36:25 - mmengine - INFO - Epoch(train) [39][1580/1793] lr: 7.5000e-04 eta: 1:35:33 time: 0.1978 data_time: 0.0109 memory: 10464 grad_norm: 9.2331 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5867 loss: 1.5867 2022/09/07 21:36:28 - mmengine - INFO - Epoch(train) [39][1600/1793] lr: 7.5000e-04 eta: 1:35:27 time: 0.1713 data_time: 0.0067 memory: 10464 grad_norm: 10.1244 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2476 loss: 1.2476 2022/09/07 21:36:32 - mmengine - INFO - Epoch(train) [39][1620/1793] lr: 7.5000e-04 eta: 1:35:20 time: 0.1745 data_time: 0.0067 memory: 10464 grad_norm: 9.6105 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.4627 loss: 1.4627 2022/09/07 21:36:35 - mmengine - INFO - Epoch(train) [39][1640/1793] lr: 7.5000e-04 eta: 1:35:14 time: 0.1745 data_time: 0.0099 memory: 10464 grad_norm: 9.2957 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.3171 loss: 1.3171 2022/09/07 21:36:39 - mmengine - INFO - Epoch(train) [39][1660/1793] lr: 7.5000e-04 eta: 1:35:08 time: 0.1706 data_time: 0.0063 memory: 10464 grad_norm: 9.6721 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.5603 loss: 1.5603 2022/09/07 21:36:43 - mmengine - INFO - Epoch(train) [39][1680/1793] lr: 7.5000e-04 eta: 1:35:01 time: 0.1807 data_time: 0.0061 memory: 10464 grad_norm: 9.6649 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2968 loss: 1.2968 2022/09/07 21:36:46 - mmengine - INFO - Epoch(train) [39][1700/1793] lr: 7.5000e-04 eta: 1:34:55 time: 0.1803 data_time: 0.0094 memory: 10464 grad_norm: 9.3017 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2204 loss: 1.2204 2022/09/07 21:36:50 - mmengine - INFO - Epoch(train) [39][1720/1793] lr: 7.5000e-04 eta: 1:34:48 time: 0.1717 data_time: 0.0062 memory: 10464 grad_norm: 9.6057 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0732 loss: 1.0732 2022/09/07 21:36:53 - mmengine - INFO - Epoch(train) [39][1740/1793] lr: 7.5000e-04 eta: 1:34:42 time: 0.1739 data_time: 0.0069 memory: 10464 grad_norm: 9.4227 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4632 loss: 1.4632 2022/09/07 21:36:57 - mmengine - INFO - Epoch(train) [39][1760/1793] lr: 7.5000e-04 eta: 1:34:36 time: 0.1741 data_time: 0.0090 memory: 10464 grad_norm: 9.4372 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0582 loss: 1.0582 2022/09/07 21:37:00 - mmengine - INFO - Epoch(train) [39][1780/1793] lr: 7.5000e-04 eta: 1:34:29 time: 0.1715 data_time: 0.0074 memory: 10464 grad_norm: 9.4567 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3731 loss: 1.3731 2022/09/07 21:37:02 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:37:02 - mmengine - INFO - Epoch(train) [39][1793/1793] lr: 7.5000e-04 eta: 1:34:29 time: 0.1739 data_time: 0.0062 memory: 10464 grad_norm: 10.0383 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 1.3824 loss: 1.3824 2022/09/07 21:37:02 - mmengine - INFO - Saving checkpoint at 39 epochs 2022/09/07 21:37:06 - mmengine - INFO - Epoch(val) [39][20/241] eta: 0:00:13 time: 0.0630 data_time: 0.0135 memory: 1482 2022/09/07 21:37:07 - mmengine - INFO - Epoch(val) [39][40/241] eta: 0:00:10 time: 0.0534 data_time: 0.0049 memory: 1482 2022/09/07 21:37:08 - mmengine - INFO - Epoch(val) [39][60/241] eta: 0:00:09 time: 0.0537 data_time: 0.0052 memory: 1482 2022/09/07 21:37:09 - mmengine - INFO - Epoch(val) [39][80/241] eta: 0:00:08 time: 0.0538 data_time: 0.0054 memory: 1482 2022/09/07 21:37:10 - mmengine - INFO - Epoch(val) [39][100/241] eta: 0:00:07 time: 0.0529 data_time: 0.0048 memory: 1482 2022/09/07 21:37:11 - mmengine - INFO - Epoch(val) [39][120/241] eta: 0:00:06 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 21:37:13 - mmengine - INFO - Epoch(val) [39][140/241] eta: 0:00:05 time: 0.0533 data_time: 0.0050 memory: 1482 2022/09/07 21:37:14 - mmengine - INFO - Epoch(val) [39][160/241] eta: 0:00:04 time: 0.0534 data_time: 0.0050 memory: 1482 2022/09/07 21:37:15 - mmengine - INFO - Epoch(val) [39][180/241] eta: 0:00:03 time: 0.0572 data_time: 0.0050 memory: 1482 2022/09/07 21:37:16 - mmengine - INFO - Epoch(val) [39][200/241] eta: 0:00:02 time: 0.0526 data_time: 0.0046 memory: 1482 2022/09/07 21:37:17 - mmengine - INFO - Epoch(val) [39][220/241] eta: 0:00:01 time: 0.0525 data_time: 0.0045 memory: 1482 2022/09/07 21:37:18 - mmengine - INFO - Epoch(val) [39][240/241] eta: 0:00:00 time: 0.0522 data_time: 0.0044 memory: 1482 2022/09/07 21:37:18 - mmengine - INFO - Epoch(val) [39][241/241] acc/top1: 0.4675 acc/top5: 0.7744 acc/mean1: 0.4310 2022/09/07 21:37:22 - mmengine - INFO - Epoch(train) [40][20/1793] lr: 7.5000e-04 eta: 1:34:18 time: 0.1857 data_time: 0.0113 memory: 10464 grad_norm: 9.0322 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1509 loss: 1.1509 2022/09/07 21:37:26 - mmengine - INFO - Epoch(train) [40][40/1793] lr: 7.5000e-04 eta: 1:34:12 time: 0.1706 data_time: 0.0064 memory: 10464 grad_norm: 9.1281 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0391 loss: 1.0391 2022/09/07 21:37:29 - mmengine - INFO - Epoch(train) [40][60/1793] lr: 7.5000e-04 eta: 1:34:05 time: 0.1708 data_time: 0.0068 memory: 10464 grad_norm: 8.9962 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3659 loss: 1.3659 2022/09/07 21:37:31 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:37:33 - mmengine - INFO - Epoch(train) [40][80/1793] lr: 7.5000e-04 eta: 1:33:59 time: 0.1791 data_time: 0.0088 memory: 10464 grad_norm: 9.5954 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1133 loss: 1.1133 2022/09/07 21:37:36 - mmengine - INFO - Epoch(train) [40][100/1793] lr: 7.5000e-04 eta: 1:33:53 time: 0.1771 data_time: 0.0067 memory: 10464 grad_norm: 9.5218 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1002 loss: 1.1002 2022/09/07 21:37:40 - mmengine - INFO - Epoch(train) [40][120/1793] lr: 7.5000e-04 eta: 1:33:46 time: 0.1706 data_time: 0.0065 memory: 10464 grad_norm: 9.5268 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2798 loss: 1.2798 2022/09/07 21:37:43 - mmengine - INFO - Epoch(train) [40][140/1793] lr: 7.5000e-04 eta: 1:33:40 time: 0.1745 data_time: 0.0085 memory: 10464 grad_norm: 9.8742 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3665 loss: 1.3665 2022/09/07 21:37:47 - mmengine - INFO - Epoch(train) [40][160/1793] lr: 7.5000e-04 eta: 1:33:33 time: 0.1719 data_time: 0.0061 memory: 10464 grad_norm: 10.0478 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.4805 loss: 1.4805 2022/09/07 21:37:50 - mmengine - INFO - Epoch(train) [40][180/1793] lr: 7.5000e-04 eta: 1:33:27 time: 0.1738 data_time: 0.0068 memory: 10464 grad_norm: 9.9064 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.4124 loss: 1.4124 2022/09/07 21:37:54 - mmengine - INFO - Epoch(train) [40][200/1793] lr: 7.5000e-04 eta: 1:33:21 time: 0.1771 data_time: 0.0085 memory: 10464 grad_norm: 9.5839 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0981 loss: 1.0981 2022/09/07 21:37:57 - mmengine - INFO - Epoch(train) [40][220/1793] lr: 7.5000e-04 eta: 1:33:14 time: 0.1885 data_time: 0.0095 memory: 10464 grad_norm: 9.4784 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1064 loss: 1.1064 2022/09/07 21:38:01 - mmengine - INFO - Epoch(train) [40][240/1793] lr: 7.5000e-04 eta: 1:33:08 time: 0.1721 data_time: 0.0071 memory: 10464 grad_norm: 9.4919 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3985 loss: 1.3985 2022/09/07 21:38:05 - mmengine - INFO - Epoch(train) [40][260/1793] lr: 7.5000e-04 eta: 1:33:02 time: 0.1811 data_time: 0.0096 memory: 10464 grad_norm: 9.1976 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1774 loss: 1.1774 2022/09/07 21:38:08 - mmengine - INFO - Epoch(train) [40][280/1793] lr: 7.5000e-04 eta: 1:32:55 time: 0.1713 data_time: 0.0070 memory: 10464 grad_norm: 9.1892 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1436 loss: 1.1436 2022/09/07 21:38:11 - mmengine - INFO - Epoch(train) [40][300/1793] lr: 7.5000e-04 eta: 1:32:49 time: 0.1702 data_time: 0.0062 memory: 10464 grad_norm: 9.3862 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1849 loss: 1.1849 2022/09/07 21:38:15 - mmengine - INFO - Epoch(train) [40][320/1793] lr: 7.5000e-04 eta: 1:32:43 time: 0.1780 data_time: 0.0092 memory: 10464 grad_norm: 9.1144 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.1009 loss: 1.1009 2022/09/07 21:38:18 - mmengine - INFO - Epoch(train) [40][340/1793] lr: 7.5000e-04 eta: 1:32:36 time: 0.1724 data_time: 0.0066 memory: 10464 grad_norm: 9.6507 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2316 loss: 1.2316 2022/09/07 21:38:22 - mmengine - INFO - Epoch(train) [40][360/1793] lr: 7.5000e-04 eta: 1:32:30 time: 0.1782 data_time: 0.0061 memory: 10464 grad_norm: 9.8552 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4765 loss: 1.4765 2022/09/07 21:38:26 - mmengine - INFO - Epoch(train) [40][380/1793] lr: 7.5000e-04 eta: 1:32:24 time: 0.1808 data_time: 0.0099 memory: 10464 grad_norm: 9.5226 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.1435 loss: 1.1435 2022/09/07 21:38:29 - mmengine - INFO - Epoch(train) [40][400/1793] lr: 7.5000e-04 eta: 1:32:17 time: 0.1723 data_time: 0.0072 memory: 10464 grad_norm: 9.6258 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.0635 loss: 1.0635 2022/09/07 21:38:32 - mmengine - INFO - Epoch(train) [40][420/1793] lr: 7.5000e-04 eta: 1:32:11 time: 0.1743 data_time: 0.0073 memory: 10464 grad_norm: 9.6932 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0589 loss: 1.0589 2022/09/07 21:38:36 - mmengine - INFO - Epoch(train) [40][440/1793] lr: 7.5000e-04 eta: 1:32:05 time: 0.1819 data_time: 0.0101 memory: 10464 grad_norm: 9.4118 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.0361 loss: 1.0361 2022/09/07 21:38:40 - mmengine - INFO - Epoch(train) [40][460/1793] lr: 7.5000e-04 eta: 1:31:58 time: 0.1713 data_time: 0.0064 memory: 10464 grad_norm: 10.2145 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3449 loss: 1.3449 2022/09/07 21:38:43 - mmengine - INFO - Epoch(train) [40][480/1793] lr: 7.5000e-04 eta: 1:31:52 time: 0.1764 data_time: 0.0064 memory: 10464 grad_norm: 9.8826 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.5151 loss: 1.5151 2022/09/07 21:38:47 - mmengine - INFO - Epoch(train) [40][500/1793] lr: 7.5000e-04 eta: 1:31:46 time: 0.1787 data_time: 0.0091 memory: 10464 grad_norm: 9.8789 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2252 loss: 1.2252 2022/09/07 21:38:50 - mmengine - INFO - Epoch(train) [40][520/1793] lr: 7.5000e-04 eta: 1:31:39 time: 0.1756 data_time: 0.0072 memory: 10464 grad_norm: 9.9997 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5131 loss: 1.5131 2022/09/07 21:38:54 - mmengine - INFO - Epoch(train) [40][540/1793] lr: 7.5000e-04 eta: 1:31:33 time: 0.1732 data_time: 0.0062 memory: 10464 grad_norm: 9.7981 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2785 loss: 1.2785 2022/09/07 21:38:57 - mmengine - INFO - Epoch(train) [40][560/1793] lr: 7.5000e-04 eta: 1:31:27 time: 0.1750 data_time: 0.0091 memory: 10464 grad_norm: 9.5953 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.3639 loss: 1.3639 2022/09/07 21:39:01 - mmengine - INFO - Epoch(train) [40][580/1793] lr: 7.5000e-04 eta: 1:31:20 time: 0.1708 data_time: 0.0062 memory: 10464 grad_norm: 9.5360 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9052 loss: 0.9052 2022/09/07 21:39:04 - mmengine - INFO - Epoch(train) [40][600/1793] lr: 7.5000e-04 eta: 1:31:14 time: 0.1716 data_time: 0.0066 memory: 10464 grad_norm: 9.9188 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3639 loss: 1.3639 2022/09/07 21:39:08 - mmengine - INFO - Epoch(train) [40][620/1793] lr: 7.5000e-04 eta: 1:31:08 time: 0.1902 data_time: 0.0092 memory: 10464 grad_norm: 10.0460 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3042 loss: 1.3042 2022/09/07 21:39:11 - mmengine - INFO - Epoch(train) [40][640/1793] lr: 7.5000e-04 eta: 1:31:01 time: 0.1705 data_time: 0.0065 memory: 10464 grad_norm: 9.6452 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2051 loss: 1.2051 2022/09/07 21:39:15 - mmengine - INFO - Epoch(train) [40][660/1793] lr: 7.5000e-04 eta: 1:30:55 time: 0.1793 data_time: 0.0073 memory: 10464 grad_norm: 9.7890 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0052 loss: 1.0052 2022/09/07 21:39:18 - mmengine - INFO - Epoch(train) [40][680/1793] lr: 7.5000e-04 eta: 1:30:49 time: 0.1725 data_time: 0.0084 memory: 10464 grad_norm: 9.7271 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0779 loss: 1.0779 2022/09/07 21:39:22 - mmengine - INFO - Epoch(train) [40][700/1793] lr: 7.5000e-04 eta: 1:30:42 time: 0.1716 data_time: 0.0065 memory: 10464 grad_norm: 9.8295 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.2088 loss: 1.2088 2022/09/07 21:39:25 - mmengine - INFO - Epoch(train) [40][720/1793] lr: 7.5000e-04 eta: 1:30:36 time: 0.1803 data_time: 0.0084 memory: 10464 grad_norm: 9.7577 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0686 loss: 1.0686 2022/09/07 21:39:29 - mmengine - INFO - Epoch(train) [40][740/1793] lr: 7.5000e-04 eta: 1:30:30 time: 0.1741 data_time: 0.0097 memory: 10464 grad_norm: 9.5702 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2385 loss: 1.2385 2022/09/07 21:39:32 - mmengine - INFO - Epoch(train) [40][760/1793] lr: 7.5000e-04 eta: 1:30:23 time: 0.1727 data_time: 0.0065 memory: 10464 grad_norm: 9.9577 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.1461 loss: 1.1461 2022/09/07 21:39:36 - mmengine - INFO - Epoch(train) [40][780/1793] lr: 7.5000e-04 eta: 1:30:17 time: 0.1749 data_time: 0.0078 memory: 10464 grad_norm: 9.2840 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0792 loss: 1.0792 2022/09/07 21:39:39 - mmengine - INFO - Epoch(train) [40][800/1793] lr: 7.5000e-04 eta: 1:30:11 time: 0.1737 data_time: 0.0096 memory: 10464 grad_norm: 9.5152 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4341 loss: 1.4341 2022/09/07 21:39:43 - mmengine - INFO - Epoch(train) [40][820/1793] lr: 7.5000e-04 eta: 1:30:04 time: 0.1737 data_time: 0.0065 memory: 10464 grad_norm: 9.9710 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.2939 loss: 1.2939 2022/09/07 21:39:46 - mmengine - INFO - Epoch(train) [40][840/1793] lr: 7.5000e-04 eta: 1:29:58 time: 0.1777 data_time: 0.0073 memory: 10464 grad_norm: 9.7562 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0182 loss: 1.0182 2022/09/07 21:39:50 - mmengine - INFO - Epoch(train) [40][860/1793] lr: 7.5000e-04 eta: 1:29:52 time: 0.1736 data_time: 0.0089 memory: 10464 grad_norm: 9.4536 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1245 loss: 1.1245 2022/09/07 21:39:53 - mmengine - INFO - Epoch(train) [40][880/1793] lr: 7.5000e-04 eta: 1:29:46 time: 0.1747 data_time: 0.0064 memory: 10464 grad_norm: 9.8900 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1729 loss: 1.1729 2022/09/07 21:39:57 - mmengine - INFO - Epoch(train) [40][900/1793] lr: 7.5000e-04 eta: 1:29:39 time: 0.1714 data_time: 0.0073 memory: 10464 grad_norm: 9.3027 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1343 loss: 1.1343 2022/09/07 21:40:00 - mmengine - INFO - Epoch(train) [40][920/1793] lr: 7.5000e-04 eta: 1:29:33 time: 0.1728 data_time: 0.0091 memory: 10464 grad_norm: 10.0663 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3650 loss: 1.3650 2022/09/07 21:40:04 - mmengine - INFO - Epoch(train) [40][940/1793] lr: 7.5000e-04 eta: 1:29:27 time: 0.1719 data_time: 0.0065 memory: 10464 grad_norm: 9.5343 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1484 loss: 1.1484 2022/09/07 21:40:07 - mmengine - INFO - Epoch(train) [40][960/1793] lr: 7.5000e-04 eta: 1:29:20 time: 0.1888 data_time: 0.0062 memory: 10464 grad_norm: 10.0729 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.5271 loss: 1.5271 2022/09/07 21:40:11 - mmengine - INFO - Epoch(train) [40][980/1793] lr: 7.5000e-04 eta: 1:29:14 time: 0.1738 data_time: 0.0087 memory: 10464 grad_norm: 10.1327 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2583 loss: 1.2583 2022/09/07 21:40:14 - mmengine - INFO - Epoch(train) [40][1000/1793] lr: 7.5000e-04 eta: 1:29:08 time: 0.1754 data_time: 0.0072 memory: 10464 grad_norm: 9.5648 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2524 loss: 1.2524 2022/09/07 21:40:18 - mmengine - INFO - Epoch(train) [40][1020/1793] lr: 7.5000e-04 eta: 1:29:01 time: 0.1737 data_time: 0.0070 memory: 10464 grad_norm: 9.4903 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0008 loss: 1.0008 2022/09/07 21:40:21 - mmengine - INFO - Epoch(train) [40][1040/1793] lr: 7.5000e-04 eta: 1:28:55 time: 0.1735 data_time: 0.0093 memory: 10464 grad_norm: 9.6705 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.5292 loss: 1.5292 2022/09/07 21:40:25 - mmengine - INFO - Epoch(train) [40][1060/1793] lr: 7.5000e-04 eta: 1:28:49 time: 0.1770 data_time: 0.0069 memory: 10464 grad_norm: 9.8115 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3240 loss: 1.3240 2022/09/07 21:40:27 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:40:28 - mmengine - INFO - Epoch(train) [40][1080/1793] lr: 7.5000e-04 eta: 1:28:43 time: 0.1706 data_time: 0.0066 memory: 10464 grad_norm: 10.1422 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2012 loss: 1.2012 2022/09/07 21:40:32 - mmengine - INFO - Epoch(train) [40][1100/1793] lr: 7.5000e-04 eta: 1:28:36 time: 0.1769 data_time: 0.0094 memory: 10464 grad_norm: 9.8593 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.2102 loss: 1.2102 2022/09/07 21:40:35 - mmengine - INFO - Epoch(train) [40][1120/1793] lr: 7.5000e-04 eta: 1:28:30 time: 0.1726 data_time: 0.0066 memory: 10464 grad_norm: 9.7992 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3799 loss: 1.3799 2022/09/07 21:40:39 - mmengine - INFO - Epoch(train) [40][1140/1793] lr: 7.5000e-04 eta: 1:28:24 time: 0.1733 data_time: 0.0068 memory: 10464 grad_norm: 9.4704 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.2005 loss: 1.2005 2022/09/07 21:40:42 - mmengine - INFO - Epoch(train) [40][1160/1793] lr: 7.5000e-04 eta: 1:28:17 time: 0.1752 data_time: 0.0090 memory: 10464 grad_norm: 10.3259 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4727 loss: 1.4727 2022/09/07 21:40:46 - mmengine - INFO - Epoch(train) [40][1180/1793] lr: 7.5000e-04 eta: 1:28:11 time: 0.1746 data_time: 0.0073 memory: 10464 grad_norm: 9.9133 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.3689 loss: 1.3689 2022/09/07 21:40:49 - mmengine - INFO - Epoch(train) [40][1200/1793] lr: 7.5000e-04 eta: 1:28:05 time: 0.1716 data_time: 0.0064 memory: 10464 grad_norm: 10.1540 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4309 loss: 1.4309 2022/09/07 21:40:53 - mmengine - INFO - Epoch(train) [40][1220/1793] lr: 7.5000e-04 eta: 1:27:59 time: 0.1729 data_time: 0.0089 memory: 10464 grad_norm: 9.8179 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1840 loss: 1.1840 2022/09/07 21:40:56 - mmengine - INFO - Epoch(train) [40][1240/1793] lr: 7.5000e-04 eta: 1:27:52 time: 0.1714 data_time: 0.0065 memory: 10464 grad_norm: 10.2190 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2072 loss: 1.2072 2022/09/07 21:41:00 - mmengine - INFO - Epoch(train) [40][1260/1793] lr: 7.5000e-04 eta: 1:27:46 time: 0.1725 data_time: 0.0063 memory: 10464 grad_norm: 9.9197 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.4218 loss: 1.4218 2022/09/07 21:41:03 - mmengine - INFO - Epoch(train) [40][1280/1793] lr: 7.5000e-04 eta: 1:27:40 time: 0.1735 data_time: 0.0085 memory: 10464 grad_norm: 9.3550 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0965 loss: 1.0965 2022/09/07 21:41:07 - mmengine - INFO - Epoch(train) [40][1300/1793] lr: 7.5000e-04 eta: 1:27:33 time: 0.1870 data_time: 0.0083 memory: 10464 grad_norm: 9.7363 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3188 loss: 1.3188 2022/09/07 21:41:10 - mmengine - INFO - Epoch(train) [40][1320/1793] lr: 7.5000e-04 eta: 1:27:27 time: 0.1712 data_time: 0.0068 memory: 10464 grad_norm: 10.2370 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3938 loss: 1.3938 2022/09/07 21:41:14 - mmengine - INFO - Epoch(train) [40][1340/1793] lr: 7.5000e-04 eta: 1:27:21 time: 0.1784 data_time: 0.0084 memory: 10464 grad_norm: 9.5954 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3453 loss: 1.3453 2022/09/07 21:41:17 - mmengine - INFO - Epoch(train) [40][1360/1793] lr: 7.5000e-04 eta: 1:27:15 time: 0.1723 data_time: 0.0070 memory: 10464 grad_norm: 9.8866 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3462 loss: 1.3462 2022/09/07 21:41:21 - mmengine - INFO - Epoch(train) [40][1380/1793] lr: 7.5000e-04 eta: 1:27:08 time: 0.1712 data_time: 0.0062 memory: 10464 grad_norm: 10.0065 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3903 loss: 1.3903 2022/09/07 21:41:24 - mmengine - INFO - Epoch(train) [40][1400/1793] lr: 7.5000e-04 eta: 1:27:02 time: 0.1756 data_time: 0.0090 memory: 10464 grad_norm: 10.3379 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1410 loss: 1.1410 2022/09/07 21:41:28 - mmengine - INFO - Epoch(train) [40][1420/1793] lr: 7.5000e-04 eta: 1:26:56 time: 0.1799 data_time: 0.0074 memory: 10464 grad_norm: 9.8315 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0856 loss: 1.0856 2022/09/07 21:41:31 - mmengine - INFO - Epoch(train) [40][1440/1793] lr: 7.5000e-04 eta: 1:26:50 time: 0.1726 data_time: 0.0065 memory: 10464 grad_norm: 9.9605 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.6569 loss: 1.6569 2022/09/07 21:41:35 - mmengine - INFO - Epoch(train) [40][1460/1793] lr: 7.5000e-04 eta: 1:26:43 time: 0.1765 data_time: 0.0097 memory: 10464 grad_norm: 10.4825 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3468 loss: 1.3468 2022/09/07 21:41:38 - mmengine - INFO - Epoch(train) [40][1480/1793] lr: 7.5000e-04 eta: 1:26:37 time: 0.1717 data_time: 0.0068 memory: 10464 grad_norm: 9.6841 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2797 loss: 1.2797 2022/09/07 21:41:42 - mmengine - INFO - Epoch(train) [40][1500/1793] lr: 7.5000e-04 eta: 1:26:31 time: 0.1710 data_time: 0.0061 memory: 10464 grad_norm: 10.2128 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3614 loss: 1.3614 2022/09/07 21:41:45 - mmengine - INFO - Epoch(train) [40][1520/1793] lr: 7.5000e-04 eta: 1:26:24 time: 0.1774 data_time: 0.0100 memory: 10464 grad_norm: 10.2787 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2332 loss: 1.2332 2022/09/07 21:41:49 - mmengine - INFO - Epoch(train) [40][1540/1793] lr: 7.5000e-04 eta: 1:26:18 time: 0.1701 data_time: 0.0063 memory: 10464 grad_norm: 10.0120 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2616 loss: 1.2616 2022/09/07 21:41:52 - mmengine - INFO - Epoch(train) [40][1560/1793] lr: 7.5000e-04 eta: 1:26:12 time: 0.1736 data_time: 0.0069 memory: 10464 grad_norm: 9.7542 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2257 loss: 1.2257 2022/09/07 21:41:56 - mmengine - INFO - Epoch(train) [40][1580/1793] lr: 7.5000e-04 eta: 1:26:06 time: 0.1755 data_time: 0.0099 memory: 10464 grad_norm: 10.1254 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4183 loss: 1.4183 2022/09/07 21:41:59 - mmengine - INFO - Epoch(train) [40][1600/1793] lr: 7.5000e-04 eta: 1:25:59 time: 0.1714 data_time: 0.0068 memory: 10464 grad_norm: 9.7217 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.2365 loss: 1.2365 2022/09/07 21:42:02 - mmengine - INFO - Epoch(train) [40][1620/1793] lr: 7.5000e-04 eta: 1:25:53 time: 0.1708 data_time: 0.0063 memory: 10464 grad_norm: 9.6281 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2035 loss: 1.2035 2022/09/07 21:42:06 - mmengine - INFO - Epoch(train) [40][1640/1793] lr: 7.5000e-04 eta: 1:25:47 time: 0.1793 data_time: 0.0103 memory: 10464 grad_norm: 10.0873 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1815 loss: 1.1815 2022/09/07 21:42:09 - mmengine - INFO - Epoch(train) [40][1660/1793] lr: 7.5000e-04 eta: 1:25:41 time: 0.1709 data_time: 0.0065 memory: 10464 grad_norm: 9.8166 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2212 loss: 1.2212 2022/09/07 21:42:13 - mmengine - INFO - Epoch(train) [40][1680/1793] lr: 7.5000e-04 eta: 1:25:34 time: 0.1861 data_time: 0.0068 memory: 10464 grad_norm: 9.5346 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1795 loss: 1.1795 2022/09/07 21:42:17 - mmengine - INFO - Epoch(train) [40][1700/1793] lr: 7.5000e-04 eta: 1:25:28 time: 0.1779 data_time: 0.0094 memory: 10464 grad_norm: 10.3742 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5572 loss: 1.5572 2022/09/07 21:42:20 - mmengine - INFO - Epoch(train) [40][1720/1793] lr: 7.5000e-04 eta: 1:25:22 time: 0.1707 data_time: 0.0066 memory: 10464 grad_norm: 9.9578 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.0923 loss: 1.0923 2022/09/07 21:42:24 - mmengine - INFO - Epoch(train) [40][1740/1793] lr: 7.5000e-04 eta: 1:25:16 time: 0.1748 data_time: 0.0071 memory: 10464 grad_norm: 9.8300 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.3290 loss: 1.3290 2022/09/07 21:42:27 - mmengine - INFO - Epoch(train) [40][1760/1793] lr: 7.5000e-04 eta: 1:25:10 time: 0.1822 data_time: 0.0087 memory: 10464 grad_norm: 10.0678 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2702 loss: 1.2702 2022/09/07 21:42:31 - mmengine - INFO - Epoch(train) [40][1780/1793] lr: 7.5000e-04 eta: 1:25:03 time: 0.1713 data_time: 0.0065 memory: 10464 grad_norm: 9.8338 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4920 loss: 1.4920 2022/09/07 21:42:33 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:42:33 - mmengine - INFO - Epoch(train) [40][1793/1793] lr: 7.5000e-04 eta: 1:25:03 time: 0.1699 data_time: 0.0065 memory: 10464 grad_norm: 11.3983 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 1.5647 loss: 1.5647 2022/09/07 21:42:33 - mmengine - INFO - Saving checkpoint at 40 epochs 2022/09/07 21:42:37 - mmengine - INFO - Epoch(val) [40][20/241] eta: 0:00:12 time: 0.0579 data_time: 0.0090 memory: 1482 2022/09/07 21:42:38 - mmengine - INFO - Epoch(val) [40][40/241] eta: 0:00:10 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 21:42:39 - mmengine - INFO - Epoch(val) [40][60/241] eta: 0:00:09 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 21:42:40 - mmengine - INFO - Epoch(val) [40][80/241] eta: 0:00:08 time: 0.0537 data_time: 0.0052 memory: 1482 2022/09/07 21:42:41 - mmengine - INFO - Epoch(val) [40][100/241] eta: 0:00:07 time: 0.0536 data_time: 0.0050 memory: 1482 2022/09/07 21:42:42 - mmengine - INFO - Epoch(val) [40][120/241] eta: 0:00:06 time: 0.0533 data_time: 0.0048 memory: 1482 2022/09/07 21:42:43 - mmengine - INFO - Epoch(val) [40][140/241] eta: 0:00:05 time: 0.0531 data_time: 0.0048 memory: 1482 2022/09/07 21:42:44 - mmengine - INFO - Epoch(val) [40][160/241] eta: 0:00:04 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 21:42:45 - mmengine - INFO - Epoch(val) [40][180/241] eta: 0:00:03 time: 0.0610 data_time: 0.0049 memory: 1482 2022/09/07 21:42:46 - mmengine - INFO - Epoch(val) [40][200/241] eta: 0:00:02 time: 0.0536 data_time: 0.0056 memory: 1482 2022/09/07 21:42:48 - mmengine - INFO - Epoch(val) [40][220/241] eta: 0:00:01 time: 0.0526 data_time: 0.0045 memory: 1482 2022/09/07 21:42:49 - mmengine - INFO - Epoch(val) [40][240/241] eta: 0:00:00 time: 0.0524 data_time: 0.0045 memory: 1482 2022/09/07 21:42:49 - mmengine - INFO - Epoch(val) [40][241/241] acc/top1: 0.4678 acc/top5: 0.7654 acc/mean1: 0.4321 2022/09/07 21:42:53 - mmengine - INFO - Epoch(train) [41][20/1793] lr: 7.5000e-05 eta: 1:24:52 time: 0.1838 data_time: 0.0167 memory: 10464 grad_norm: 9.6884 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2229 loss: 1.2229 2022/09/07 21:42:56 - mmengine - INFO - Epoch(train) [41][40/1793] lr: 7.5000e-05 eta: 1:24:46 time: 0.1707 data_time: 0.0068 memory: 10464 grad_norm: 9.6196 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9413 loss: 0.9413 2022/09/07 21:43:00 - mmengine - INFO - Epoch(train) [41][60/1793] lr: 7.5000e-05 eta: 1:24:40 time: 0.1704 data_time: 0.0063 memory: 10464 grad_norm: 9.6740 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1393 loss: 1.1393 2022/09/07 21:43:04 - mmengine - INFO - Epoch(train) [41][80/1793] lr: 7.5000e-05 eta: 1:24:34 time: 0.1875 data_time: 0.0086 memory: 10464 grad_norm: 9.6248 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9803 loss: 0.9803 2022/09/07 21:43:07 - mmengine - INFO - Epoch(train) [41][100/1793] lr: 7.5000e-05 eta: 1:24:28 time: 0.1839 data_time: 0.0076 memory: 10464 grad_norm: 9.4605 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0659 loss: 1.0659 2022/09/07 21:43:11 - mmengine - INFO - Epoch(train) [41][120/1793] lr: 7.5000e-05 eta: 1:24:21 time: 0.1711 data_time: 0.0064 memory: 10464 grad_norm: 9.5978 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3234 loss: 1.3234 2022/09/07 21:43:14 - mmengine - INFO - Epoch(train) [41][140/1793] lr: 7.5000e-05 eta: 1:24:15 time: 0.1723 data_time: 0.0084 memory: 10464 grad_norm: 9.8150 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1570 loss: 1.1570 2022/09/07 21:43:18 - mmengine - INFO - Epoch(train) [41][160/1793] lr: 7.5000e-05 eta: 1:24:09 time: 0.1777 data_time: 0.0063 memory: 10464 grad_norm: 10.0965 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1838 loss: 1.1838 2022/09/07 21:43:21 - mmengine - INFO - Epoch(train) [41][180/1793] lr: 7.5000e-05 eta: 1:24:03 time: 0.1716 data_time: 0.0071 memory: 10464 grad_norm: 9.8405 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2098 loss: 1.2098 2022/09/07 21:43:25 - mmengine - INFO - Epoch(train) [41][200/1793] lr: 7.5000e-05 eta: 1:23:57 time: 0.1887 data_time: 0.0089 memory: 10464 grad_norm: 9.5329 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 0.9311 loss: 0.9311 2022/09/07 21:43:28 - mmengine - INFO - Epoch(train) [41][220/1793] lr: 7.5000e-05 eta: 1:23:50 time: 0.1732 data_time: 0.0070 memory: 10464 grad_norm: 9.8609 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0451 loss: 1.0451 2022/09/07 21:43:32 - mmengine - INFO - Epoch(train) [41][240/1793] lr: 7.5000e-05 eta: 1:23:44 time: 0.1717 data_time: 0.0071 memory: 10464 grad_norm: 10.2956 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1781 loss: 1.1781 2022/09/07 21:43:35 - mmengine - INFO - Epoch(train) [41][260/1793] lr: 7.5000e-05 eta: 1:23:38 time: 0.1733 data_time: 0.0089 memory: 10464 grad_norm: 9.4716 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9189 loss: 0.9189 2022/09/07 21:43:39 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:43:39 - mmengine - INFO - Epoch(train) [41][280/1793] lr: 7.5000e-05 eta: 1:23:32 time: 0.1701 data_time: 0.0065 memory: 10464 grad_norm: 9.7922 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1063 loss: 1.1063 2022/09/07 21:43:42 - mmengine - INFO - Epoch(train) [41][300/1793] lr: 7.5000e-05 eta: 1:23:25 time: 0.1838 data_time: 0.0071 memory: 10464 grad_norm: 9.7923 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1302 loss: 1.1302 2022/09/07 21:43:46 - mmengine - INFO - Epoch(train) [41][320/1793] lr: 7.5000e-05 eta: 1:23:19 time: 0.1896 data_time: 0.0086 memory: 10464 grad_norm: 9.7759 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 0.9647 loss: 0.9647 2022/09/07 21:43:50 - mmengine - INFO - Epoch(train) [41][340/1793] lr: 7.5000e-05 eta: 1:23:13 time: 0.1713 data_time: 0.0067 memory: 10464 grad_norm: 9.1272 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1544 loss: 1.1544 2022/09/07 21:43:53 - mmengine - INFO - Epoch(train) [41][360/1793] lr: 7.5000e-05 eta: 1:23:07 time: 0.1715 data_time: 0.0062 memory: 10464 grad_norm: 9.6836 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2603 loss: 1.2603 2022/09/07 21:43:57 - mmengine - INFO - Epoch(train) [41][380/1793] lr: 7.5000e-05 eta: 1:23:01 time: 0.1733 data_time: 0.0092 memory: 10464 grad_norm: 9.5968 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.2269 loss: 1.2269 2022/09/07 21:44:00 - mmengine - INFO - Epoch(train) [41][400/1793] lr: 7.5000e-05 eta: 1:22:54 time: 0.1713 data_time: 0.0063 memory: 10464 grad_norm: 9.7546 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.2774 loss: 1.2774 2022/09/07 21:44:04 - mmengine - INFO - Epoch(train) [41][420/1793] lr: 7.5000e-05 eta: 1:22:48 time: 0.1848 data_time: 0.0063 memory: 10464 grad_norm: 9.6493 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3259 loss: 1.3259 2022/09/07 21:44:07 - mmengine - INFO - Epoch(train) [41][440/1793] lr: 7.5000e-05 eta: 1:22:42 time: 0.1840 data_time: 0.0106 memory: 10464 grad_norm: 9.3525 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.1680 loss: 1.1680 2022/09/07 21:44:11 - mmengine - INFO - Epoch(train) [41][460/1793] lr: 7.5000e-05 eta: 1:22:36 time: 0.1708 data_time: 0.0066 memory: 10464 grad_norm: 9.2150 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2381 loss: 1.2381 2022/09/07 21:44:14 - mmengine - INFO - Epoch(train) [41][480/1793] lr: 7.5000e-05 eta: 1:22:30 time: 0.1712 data_time: 0.0063 memory: 10464 grad_norm: 9.0069 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1014 loss: 1.1014 2022/09/07 21:44:18 - mmengine - INFO - Epoch(train) [41][500/1793] lr: 7.5000e-05 eta: 1:22:23 time: 0.1741 data_time: 0.0095 memory: 10464 grad_norm: 9.5822 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4489 loss: 1.4489 2022/09/07 21:44:21 - mmengine - INFO - Epoch(train) [41][520/1793] lr: 7.5000e-05 eta: 1:22:17 time: 0.1713 data_time: 0.0067 memory: 10464 grad_norm: 9.5346 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.2785 loss: 1.2785 2022/09/07 21:44:25 - mmengine - INFO - Epoch(train) [41][540/1793] lr: 7.5000e-05 eta: 1:22:11 time: 0.1742 data_time: 0.0062 memory: 10464 grad_norm: 9.7328 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3434 loss: 1.3434 2022/09/07 21:44:28 - mmengine - INFO - Epoch(train) [41][560/1793] lr: 7.5000e-05 eta: 1:22:05 time: 0.1799 data_time: 0.0101 memory: 10464 grad_norm: 9.5470 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2652 loss: 1.2652 2022/09/07 21:44:32 - mmengine - INFO - Epoch(train) [41][580/1793] lr: 7.5000e-05 eta: 1:21:59 time: 0.1725 data_time: 0.0066 memory: 10464 grad_norm: 9.8241 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2306 loss: 1.2306 2022/09/07 21:44:35 - mmengine - INFO - Epoch(train) [41][600/1793] lr: 7.5000e-05 eta: 1:21:52 time: 0.1713 data_time: 0.0067 memory: 10464 grad_norm: 9.5012 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.0399 loss: 1.0399 2022/09/07 21:44:39 - mmengine - INFO - Epoch(train) [41][620/1793] lr: 7.5000e-05 eta: 1:21:46 time: 0.1741 data_time: 0.0094 memory: 10464 grad_norm: 9.6261 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1811 loss: 1.1811 2022/09/07 21:44:42 - mmengine - INFO - Epoch(train) [41][640/1793] lr: 7.5000e-05 eta: 1:21:40 time: 0.1703 data_time: 0.0063 memory: 10464 grad_norm: 9.4889 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1999 loss: 1.1999 2022/09/07 21:44:46 - mmengine - INFO - Epoch(train) [41][660/1793] lr: 7.5000e-05 eta: 1:21:34 time: 0.1749 data_time: 0.0073 memory: 10464 grad_norm: 9.3966 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1381 loss: 1.1381 2022/09/07 21:44:49 - mmengine - INFO - Epoch(train) [41][680/1793] lr: 7.5000e-05 eta: 1:21:28 time: 0.1744 data_time: 0.0099 memory: 10464 grad_norm: 9.8749 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3716 loss: 1.3716 2022/09/07 21:44:52 - mmengine - INFO - Epoch(train) [41][700/1793] lr: 7.5000e-05 eta: 1:21:21 time: 0.1720 data_time: 0.0063 memory: 10464 grad_norm: 9.8543 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2502 loss: 1.2502 2022/09/07 21:44:56 - mmengine - INFO - Epoch(train) [41][720/1793] lr: 7.5000e-05 eta: 1:21:15 time: 0.1709 data_time: 0.0066 memory: 10464 grad_norm: 9.3389 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0260 loss: 1.0260 2022/09/07 21:44:59 - mmengine - INFO - Epoch(train) [41][740/1793] lr: 7.5000e-05 eta: 1:21:09 time: 0.1742 data_time: 0.0089 memory: 10464 grad_norm: 9.8332 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1915 loss: 1.1915 2022/09/07 21:45:03 - mmengine - INFO - Epoch(train) [41][760/1793] lr: 7.5000e-05 eta: 1:21:03 time: 0.1781 data_time: 0.0064 memory: 10464 grad_norm: 9.2797 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1164 loss: 1.1164 2022/09/07 21:45:07 - mmengine - INFO - Epoch(train) [41][780/1793] lr: 7.5000e-05 eta: 1:20:57 time: 0.2006 data_time: 0.0075 memory: 10464 grad_norm: 9.4720 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1170 loss: 1.1170 2022/09/07 21:45:10 - mmengine - INFO - Epoch(train) [41][800/1793] lr: 7.5000e-05 eta: 1:20:51 time: 0.1724 data_time: 0.0088 memory: 10464 grad_norm: 9.8172 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2165 loss: 1.2165 2022/09/07 21:45:14 - mmengine - INFO - Epoch(train) [41][820/1793] lr: 7.5000e-05 eta: 1:20:44 time: 0.1701 data_time: 0.0063 memory: 10464 grad_norm: 9.6724 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3021 loss: 1.3021 2022/09/07 21:45:17 - mmengine - INFO - Epoch(train) [41][840/1793] lr: 7.5000e-05 eta: 1:20:38 time: 0.1710 data_time: 0.0069 memory: 10464 grad_norm: 9.5232 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3274 loss: 1.3274 2022/09/07 21:45:21 - mmengine - INFO - Epoch(train) [41][860/1793] lr: 7.5000e-05 eta: 1:20:32 time: 0.1728 data_time: 0.0087 memory: 10464 grad_norm: 9.3565 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0413 loss: 1.0413 2022/09/07 21:45:24 - mmengine - INFO - Epoch(train) [41][880/1793] lr: 7.5000e-05 eta: 1:20:26 time: 0.1707 data_time: 0.0064 memory: 10464 grad_norm: 9.3014 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1150 loss: 1.1150 2022/09/07 21:45:28 - mmengine - INFO - Epoch(train) [41][900/1793] lr: 7.5000e-05 eta: 1:20:20 time: 0.1782 data_time: 0.0071 memory: 10464 grad_norm: 9.3820 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3361 loss: 1.3361 2022/09/07 21:45:31 - mmengine - INFO - Epoch(train) [41][920/1793] lr: 7.5000e-05 eta: 1:20:14 time: 0.1724 data_time: 0.0086 memory: 10464 grad_norm: 9.6242 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1362 loss: 1.1362 2022/09/07 21:45:35 - mmengine - INFO - Epoch(train) [41][940/1793] lr: 7.5000e-05 eta: 1:20:07 time: 0.1741 data_time: 0.0066 memory: 10464 grad_norm: 9.4733 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0480 loss: 1.0480 2022/09/07 21:45:38 - mmengine - INFO - Epoch(train) [41][960/1793] lr: 7.5000e-05 eta: 1:20:01 time: 0.1714 data_time: 0.0069 memory: 10464 grad_norm: 9.6269 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2646 loss: 1.2646 2022/09/07 21:45:42 - mmengine - INFO - Epoch(train) [41][980/1793] lr: 7.5000e-05 eta: 1:19:55 time: 0.1721 data_time: 0.0084 memory: 10464 grad_norm: 9.6470 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4352 loss: 1.4352 2022/09/07 21:45:45 - mmengine - INFO - Epoch(train) [41][1000/1793] lr: 7.5000e-05 eta: 1:19:49 time: 0.1919 data_time: 0.0066 memory: 10464 grad_norm: 9.4717 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1972 loss: 1.1972 2022/09/07 21:45:49 - mmengine - INFO - Epoch(train) [41][1020/1793] lr: 7.5000e-05 eta: 1:19:43 time: 0.1716 data_time: 0.0068 memory: 10464 grad_norm: 9.6660 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 0.9814 loss: 0.9814 2022/09/07 21:45:52 - mmengine - INFO - Epoch(train) [41][1040/1793] lr: 7.5000e-05 eta: 1:19:37 time: 0.1730 data_time: 0.0085 memory: 10464 grad_norm: 9.6133 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2371 loss: 1.2371 2022/09/07 21:45:56 - mmengine - INFO - Epoch(train) [41][1060/1793] lr: 7.5000e-05 eta: 1:19:30 time: 0.1716 data_time: 0.0066 memory: 10464 grad_norm: 9.7595 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3489 loss: 1.3489 2022/09/07 21:45:59 - mmengine - INFO - Epoch(train) [41][1080/1793] lr: 7.5000e-05 eta: 1:19:24 time: 0.1715 data_time: 0.0061 memory: 10464 grad_norm: 9.4855 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.0966 loss: 1.0966 2022/09/07 21:46:03 - mmengine - INFO - Epoch(train) [41][1100/1793] lr: 7.5000e-05 eta: 1:19:18 time: 0.1751 data_time: 0.0092 memory: 10464 grad_norm: 9.6127 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3868 loss: 1.3868 2022/09/07 21:46:06 - mmengine - INFO - Epoch(train) [41][1120/1793] lr: 7.5000e-05 eta: 1:19:12 time: 0.1756 data_time: 0.0076 memory: 10464 grad_norm: 9.3945 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2469 loss: 1.2469 2022/09/07 21:46:10 - mmengine - INFO - Epoch(train) [41][1140/1793] lr: 7.5000e-05 eta: 1:19:06 time: 0.1705 data_time: 0.0065 memory: 10464 grad_norm: 9.6389 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0506 loss: 1.0506 2022/09/07 21:46:13 - mmengine - INFO - Epoch(train) [41][1160/1793] lr: 7.5000e-05 eta: 1:19:00 time: 0.1744 data_time: 0.0091 memory: 10464 grad_norm: 9.4817 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 0.9845 loss: 0.9845 2022/09/07 21:46:16 - mmengine - INFO - Epoch(train) [41][1180/1793] lr: 7.5000e-05 eta: 1:18:53 time: 0.1707 data_time: 0.0069 memory: 10464 grad_norm: 9.4962 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0501 loss: 1.0501 2022/09/07 21:46:20 - mmengine - INFO - Epoch(train) [41][1200/1793] lr: 7.5000e-05 eta: 1:18:47 time: 0.1723 data_time: 0.0065 memory: 10464 grad_norm: 9.5212 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.0762 loss: 1.0762 2022/09/07 21:46:24 - mmengine - INFO - Epoch(train) [41][1220/1793] lr: 7.5000e-05 eta: 1:18:41 time: 0.1841 data_time: 0.0095 memory: 10464 grad_norm: 9.8369 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3030 loss: 1.3030 2022/09/07 21:46:28 - mmengine - INFO - Epoch(train) [41][1240/1793] lr: 7.5000e-05 eta: 1:18:35 time: 0.2005 data_time: 0.0085 memory: 10464 grad_norm: 10.1599 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.1044 loss: 1.1044 2022/09/07 21:46:31 - mmengine - INFO - Epoch(train) [41][1260/1793] lr: 7.5000e-05 eta: 1:18:29 time: 0.1702 data_time: 0.0065 memory: 10464 grad_norm: 9.6484 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2161 loss: 1.2161 2022/09/07 21:46:35 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:46:35 - mmengine - INFO - Epoch(train) [41][1280/1793] lr: 7.5000e-05 eta: 1:18:23 time: 0.1759 data_time: 0.0092 memory: 10464 grad_norm: 9.7623 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1686 loss: 1.1686 2022/09/07 21:46:38 - mmengine - INFO - Epoch(train) [41][1300/1793] lr: 7.5000e-05 eta: 1:18:17 time: 0.1711 data_time: 0.0063 memory: 10464 grad_norm: 9.5525 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1241 loss: 1.1241 2022/09/07 21:46:41 - mmengine - INFO - Epoch(train) [41][1320/1793] lr: 7.5000e-05 eta: 1:18:11 time: 0.1706 data_time: 0.0064 memory: 10464 grad_norm: 9.7251 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1985 loss: 1.1985 2022/09/07 21:46:45 - mmengine - INFO - Epoch(train) [41][1340/1793] lr: 7.5000e-05 eta: 1:18:04 time: 0.1787 data_time: 0.0087 memory: 10464 grad_norm: 9.3749 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1780 loss: 1.1780 2022/09/07 21:46:49 - mmengine - INFO - Epoch(train) [41][1360/1793] lr: 7.5000e-05 eta: 1:17:58 time: 0.1869 data_time: 0.0074 memory: 10464 grad_norm: 9.5698 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0968 loss: 1.0968 2022/09/07 21:46:52 - mmengine - INFO - Epoch(train) [41][1380/1793] lr: 7.5000e-05 eta: 1:17:52 time: 0.1722 data_time: 0.0067 memory: 10464 grad_norm: 9.3872 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.1270 loss: 1.1270 2022/09/07 21:46:56 - mmengine - INFO - Epoch(train) [41][1400/1793] lr: 7.5000e-05 eta: 1:17:46 time: 0.1730 data_time: 0.0088 memory: 10464 grad_norm: 9.2213 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2685 loss: 1.2685 2022/09/07 21:46:59 - mmengine - INFO - Epoch(train) [41][1420/1793] lr: 7.5000e-05 eta: 1:17:40 time: 0.1709 data_time: 0.0066 memory: 10464 grad_norm: 9.6542 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2087 loss: 1.2087 2022/09/07 21:47:03 - mmengine - INFO - Epoch(train) [41][1440/1793] lr: 7.5000e-05 eta: 1:17:34 time: 0.1870 data_time: 0.0072 memory: 10464 grad_norm: 9.4567 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2055 loss: 1.2055 2022/09/07 21:47:07 - mmengine - INFO - Epoch(train) [41][1460/1793] lr: 7.5000e-05 eta: 1:17:28 time: 0.1985 data_time: 0.0110 memory: 10464 grad_norm: 9.5472 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4067 loss: 1.4067 2022/09/07 21:47:10 - mmengine - INFO - Epoch(train) [41][1480/1793] lr: 7.5000e-05 eta: 1:17:22 time: 0.1716 data_time: 0.0067 memory: 10464 grad_norm: 10.1146 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1607 loss: 1.1607 2022/09/07 21:47:14 - mmengine - INFO - Epoch(train) [41][1500/1793] lr: 7.5000e-05 eta: 1:17:16 time: 0.1717 data_time: 0.0071 memory: 10464 grad_norm: 9.7206 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4314 loss: 1.4314 2022/09/07 21:47:17 - mmengine - INFO - Epoch(train) [41][1520/1793] lr: 7.5000e-05 eta: 1:17:09 time: 0.1751 data_time: 0.0084 memory: 10464 grad_norm: 9.9931 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4587 loss: 1.4587 2022/09/07 21:47:21 - mmengine - INFO - Epoch(train) [41][1540/1793] lr: 7.5000e-05 eta: 1:17:03 time: 0.1732 data_time: 0.0064 memory: 10464 grad_norm: 9.8655 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3514 loss: 1.3514 2022/09/07 21:47:24 - mmengine - INFO - Epoch(train) [41][1560/1793] lr: 7.5000e-05 eta: 1:16:57 time: 0.1802 data_time: 0.0071 memory: 10464 grad_norm: 9.5714 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.2318 loss: 1.2318 2022/09/07 21:47:28 - mmengine - INFO - Epoch(train) [41][1580/1793] lr: 7.5000e-05 eta: 1:16:51 time: 0.1786 data_time: 0.0096 memory: 10464 grad_norm: 9.8097 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0327 loss: 1.0327 2022/09/07 21:47:31 - mmengine - INFO - Epoch(train) [41][1600/1793] lr: 7.5000e-05 eta: 1:16:45 time: 0.1707 data_time: 0.0065 memory: 10464 grad_norm: 9.3547 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2545 loss: 1.2545 2022/09/07 21:47:35 - mmengine - INFO - Epoch(train) [41][1620/1793] lr: 7.5000e-05 eta: 1:16:39 time: 0.1711 data_time: 0.0066 memory: 10464 grad_norm: 9.3818 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1592 loss: 1.1592 2022/09/07 21:47:38 - mmengine - INFO - Epoch(train) [41][1640/1793] lr: 7.5000e-05 eta: 1:16:33 time: 0.1741 data_time: 0.0084 memory: 10464 grad_norm: 10.1151 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0306 loss: 1.0306 2022/09/07 21:47:42 - mmengine - INFO - Epoch(train) [41][1660/1793] lr: 7.5000e-05 eta: 1:16:27 time: 0.1718 data_time: 0.0076 memory: 10464 grad_norm: 9.5493 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0658 loss: 1.0658 2022/09/07 21:47:45 - mmengine - INFO - Epoch(train) [41][1680/1793] lr: 7.5000e-05 eta: 1:16:20 time: 0.1723 data_time: 0.0076 memory: 10464 grad_norm: 9.4062 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3013 loss: 1.3013 2022/09/07 21:47:49 - mmengine - INFO - Epoch(train) [41][1700/1793] lr: 7.5000e-05 eta: 1:16:14 time: 0.1752 data_time: 0.0094 memory: 10464 grad_norm: 9.7603 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2598 loss: 1.2598 2022/09/07 21:47:52 - mmengine - INFO - Epoch(train) [41][1720/1793] lr: 7.5000e-05 eta: 1:16:08 time: 0.1709 data_time: 0.0066 memory: 10464 grad_norm: 9.5459 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.5635 loss: 1.5635 2022/09/07 21:47:55 - mmengine - INFO - Epoch(train) [41][1740/1793] lr: 7.5000e-05 eta: 1:16:02 time: 0.1762 data_time: 0.0067 memory: 10464 grad_norm: 9.5120 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0897 loss: 1.0897 2022/09/07 21:47:59 - mmengine - INFO - Epoch(train) [41][1760/1793] lr: 7.5000e-05 eta: 1:15:56 time: 0.1734 data_time: 0.0096 memory: 10464 grad_norm: 9.3430 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2743 loss: 1.2743 2022/09/07 21:48:02 - mmengine - INFO - Epoch(train) [41][1780/1793] lr: 7.5000e-05 eta: 1:15:50 time: 0.1718 data_time: 0.0065 memory: 10464 grad_norm: 9.5912 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0242 loss: 1.0242 2022/09/07 21:48:05 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:48:05 - mmengine - INFO - Epoch(train) [41][1793/1793] lr: 7.5000e-05 eta: 1:15:50 time: 0.1764 data_time: 0.0065 memory: 10464 grad_norm: 9.8806 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 1.2897 loss: 1.2897 2022/09/07 21:48:05 - mmengine - INFO - Saving checkpoint at 41 epochs 2022/09/07 21:48:08 - mmengine - INFO - Epoch(val) [41][20/241] eta: 0:00:12 time: 0.0587 data_time: 0.0096 memory: 1482 2022/09/07 21:48:09 - mmengine - INFO - Epoch(val) [41][40/241] eta: 0:00:10 time: 0.0534 data_time: 0.0050 memory: 1482 2022/09/07 21:48:10 - mmengine - INFO - Epoch(val) [41][60/241] eta: 0:00:09 time: 0.0534 data_time: 0.0049 memory: 1482 2022/09/07 21:48:12 - mmengine - INFO - Epoch(val) [41][80/241] eta: 0:00:08 time: 0.0544 data_time: 0.0055 memory: 1482 2022/09/07 21:48:13 - mmengine - INFO - Epoch(val) [41][100/241] eta: 0:00:07 time: 0.0540 data_time: 0.0055 memory: 1482 2022/09/07 21:48:14 - mmengine - INFO - Epoch(val) [41][120/241] eta: 0:00:06 time: 0.0534 data_time: 0.0051 memory: 1482 2022/09/07 21:48:15 - mmengine - INFO - Epoch(val) [41][140/241] eta: 0:00:05 time: 0.0529 data_time: 0.0047 memory: 1482 2022/09/07 21:48:16 - mmengine - INFO - Epoch(val) [41][160/241] eta: 0:00:04 time: 0.0544 data_time: 0.0051 memory: 1482 2022/09/07 21:48:17 - mmengine - INFO - Epoch(val) [41][180/241] eta: 0:00:03 time: 0.0536 data_time: 0.0050 memory: 1482 2022/09/07 21:48:18 - mmengine - INFO - Epoch(val) [41][200/241] eta: 0:00:02 time: 0.0532 data_time: 0.0049 memory: 1482 2022/09/07 21:48:19 - mmengine - INFO - Epoch(val) [41][220/241] eta: 0:00:01 time: 0.0524 data_time: 0.0045 memory: 1482 2022/09/07 21:48:20 - mmengine - INFO - Epoch(val) [41][240/241] eta: 0:00:00 time: 0.0522 data_time: 0.0043 memory: 1482 2022/09/07 21:48:21 - mmengine - INFO - Epoch(val) [41][241/241] acc/top1: 0.4780 acc/top5: 0.7796 acc/mean1: 0.4410 2022/09/07 21:48:21 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_35.pth is removed 2022/09/07 21:48:23 - mmengine - INFO - The best checkpoint with 0.4780 acc/top1 at 41 epoch is saved to best_acc/top1_epoch_41.pth. 2022/09/07 21:48:26 - mmengine - INFO - Epoch(train) [42][20/1793] lr: 7.5000e-05 eta: 1:15:39 time: 0.1905 data_time: 0.0198 memory: 10464 grad_norm: 9.6245 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9654 loss: 0.9654 2022/09/07 21:48:30 - mmengine - INFO - Epoch(train) [42][40/1793] lr: 7.5000e-05 eta: 1:15:33 time: 0.1740 data_time: 0.0067 memory: 10464 grad_norm: 9.4216 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.2587 loss: 1.2587 2022/09/07 21:48:34 - mmengine - INFO - Epoch(train) [42][60/1793] lr: 7.5000e-05 eta: 1:15:27 time: 0.1855 data_time: 0.0067 memory: 10464 grad_norm: 9.7520 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1408 loss: 1.1408 2022/09/07 21:48:37 - mmengine - INFO - Epoch(train) [42][80/1793] lr: 7.5000e-05 eta: 1:15:21 time: 0.1825 data_time: 0.0095 memory: 10464 grad_norm: 9.5638 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0929 loss: 1.0929 2022/09/07 21:48:41 - mmengine - INFO - Epoch(train) [42][100/1793] lr: 7.5000e-05 eta: 1:15:15 time: 0.1729 data_time: 0.0074 memory: 10464 grad_norm: 9.4562 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1346 loss: 1.1346 2022/09/07 21:48:44 - mmengine - INFO - Epoch(train) [42][120/1793] lr: 7.5000e-05 eta: 1:15:09 time: 0.1734 data_time: 0.0064 memory: 10464 grad_norm: 9.9104 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0721 loss: 1.0721 2022/09/07 21:48:48 - mmengine - INFO - Epoch(train) [42][140/1793] lr: 7.5000e-05 eta: 1:15:03 time: 0.1744 data_time: 0.0092 memory: 10464 grad_norm: 9.0554 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1143 loss: 1.1143 2022/09/07 21:48:51 - mmengine - INFO - Epoch(train) [42][160/1793] lr: 7.5000e-05 eta: 1:14:57 time: 0.1721 data_time: 0.0070 memory: 10464 grad_norm: 9.6874 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0015 loss: 1.0015 2022/09/07 21:48:55 - mmengine - INFO - Epoch(train) [42][180/1793] lr: 7.5000e-05 eta: 1:14:51 time: 0.1752 data_time: 0.0066 memory: 10464 grad_norm: 9.7086 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.2369 loss: 1.2369 2022/09/07 21:48:58 - mmengine - INFO - Epoch(train) [42][200/1793] lr: 7.5000e-05 eta: 1:14:45 time: 0.1811 data_time: 0.0101 memory: 10464 grad_norm: 9.4019 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1209 loss: 1.1209 2022/09/07 21:49:02 - mmengine - INFO - Epoch(train) [42][220/1793] lr: 7.5000e-05 eta: 1:14:39 time: 0.1710 data_time: 0.0064 memory: 10464 grad_norm: 9.3582 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1770 loss: 1.1770 2022/09/07 21:49:05 - mmengine - INFO - Epoch(train) [42][240/1793] lr: 7.5000e-05 eta: 1:14:32 time: 0.1731 data_time: 0.0063 memory: 10464 grad_norm: 9.5773 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1114 loss: 1.1114 2022/09/07 21:49:09 - mmengine - INFO - Epoch(train) [42][260/1793] lr: 7.5000e-05 eta: 1:14:26 time: 0.1783 data_time: 0.0115 memory: 10464 grad_norm: 9.7901 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1430 loss: 1.1430 2022/09/07 21:49:12 - mmengine - INFO - Epoch(train) [42][280/1793] lr: 7.5000e-05 eta: 1:14:20 time: 0.1707 data_time: 0.0064 memory: 10464 grad_norm: 9.4954 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0120 loss: 1.0120 2022/09/07 21:49:16 - mmengine - INFO - Epoch(train) [42][300/1793] lr: 7.5000e-05 eta: 1:14:14 time: 0.1769 data_time: 0.0072 memory: 10464 grad_norm: 9.6481 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.2401 loss: 1.2401 2022/09/07 21:49:19 - mmengine - INFO - Epoch(train) [42][320/1793] lr: 7.5000e-05 eta: 1:14:08 time: 0.1740 data_time: 0.0091 memory: 10464 grad_norm: 9.6456 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1681 loss: 1.1681 2022/09/07 21:49:23 - mmengine - INFO - Epoch(train) [42][340/1793] lr: 7.5000e-05 eta: 1:14:02 time: 0.1731 data_time: 0.0061 memory: 10464 grad_norm: 9.3934 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1471 loss: 1.1471 2022/09/07 21:49:26 - mmengine - INFO - Epoch(train) [42][360/1793] lr: 7.5000e-05 eta: 1:13:56 time: 0.1829 data_time: 0.0075 memory: 10464 grad_norm: 9.9635 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1722 loss: 1.1722 2022/09/07 21:49:30 - mmengine - INFO - Epoch(train) [42][380/1793] lr: 7.5000e-05 eta: 1:13:50 time: 0.1762 data_time: 0.0092 memory: 10464 grad_norm: 9.7493 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0409 loss: 1.0409 2022/09/07 21:49:33 - mmengine - INFO - Epoch(train) [42][400/1793] lr: 7.5000e-05 eta: 1:13:44 time: 0.1735 data_time: 0.0064 memory: 10464 grad_norm: 10.1540 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0117 loss: 1.0117 2022/09/07 21:49:37 - mmengine - INFO - Epoch(train) [42][420/1793] lr: 7.5000e-05 eta: 1:13:38 time: 0.1775 data_time: 0.0063 memory: 10464 grad_norm: 9.6846 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 1.2430 loss: 1.2430 2022/09/07 21:49:40 - mmengine - INFO - Epoch(train) [42][440/1793] lr: 7.5000e-05 eta: 1:13:32 time: 0.1737 data_time: 0.0085 memory: 10464 grad_norm: 9.6396 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2703 loss: 1.2703 2022/09/07 21:49:44 - mmengine - INFO - Epoch(train) [42][460/1793] lr: 7.5000e-05 eta: 1:13:26 time: 0.1753 data_time: 0.0066 memory: 10464 grad_norm: 9.7597 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3312 loss: 1.3312 2022/09/07 21:49:47 - mmengine - INFO - Epoch(train) [42][480/1793] lr: 7.5000e-05 eta: 1:13:20 time: 0.1796 data_time: 0.0071 memory: 10464 grad_norm: 9.5672 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.1091 loss: 1.1091 2022/09/07 21:49:49 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:49:51 - mmengine - INFO - Epoch(train) [42][500/1793] lr: 7.5000e-05 eta: 1:13:13 time: 0.1750 data_time: 0.0091 memory: 10464 grad_norm: 9.5818 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2160 loss: 1.2160 2022/09/07 21:49:54 - mmengine - INFO - Epoch(train) [42][520/1793] lr: 7.5000e-05 eta: 1:13:07 time: 0.1710 data_time: 0.0062 memory: 10464 grad_norm: 9.5961 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3236 loss: 1.3236 2022/09/07 21:49:58 - mmengine - INFO - Epoch(train) [42][540/1793] lr: 7.5000e-05 eta: 1:13:01 time: 0.1739 data_time: 0.0064 memory: 10464 grad_norm: 9.7279 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1466 loss: 1.1466 2022/09/07 21:50:01 - mmengine - INFO - Epoch(train) [42][560/1793] lr: 7.5000e-05 eta: 1:12:55 time: 0.1738 data_time: 0.0088 memory: 10464 grad_norm: 9.8448 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3466 loss: 1.3466 2022/09/07 21:50:05 - mmengine - INFO - Epoch(train) [42][580/1793] lr: 7.5000e-05 eta: 1:12:49 time: 0.1842 data_time: 0.0070 memory: 10464 grad_norm: 9.8657 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1152 loss: 1.1152 2022/09/07 21:50:09 - mmengine - INFO - Epoch(train) [42][600/1793] lr: 7.5000e-05 eta: 1:12:43 time: 0.1729 data_time: 0.0070 memory: 10464 grad_norm: 9.8119 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9567 loss: 0.9567 2022/09/07 21:50:12 - mmengine - INFO - Epoch(train) [42][620/1793] lr: 7.5000e-05 eta: 1:12:37 time: 0.1739 data_time: 0.0097 memory: 10464 grad_norm: 9.6572 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.0841 loss: 1.0841 2022/09/07 21:50:15 - mmengine - INFO - Epoch(train) [42][640/1793] lr: 7.5000e-05 eta: 1:12:31 time: 0.1749 data_time: 0.0065 memory: 10464 grad_norm: 9.6211 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1250 loss: 1.1250 2022/09/07 21:50:19 - mmengine - INFO - Epoch(train) [42][660/1793] lr: 7.5000e-05 eta: 1:12:25 time: 0.1727 data_time: 0.0066 memory: 10464 grad_norm: 9.4707 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.0290 loss: 1.0290 2022/09/07 21:50:22 - mmengine - INFO - Epoch(train) [42][680/1793] lr: 7.5000e-05 eta: 1:12:19 time: 0.1725 data_time: 0.0085 memory: 10464 grad_norm: 9.7576 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1510 loss: 1.1510 2022/09/07 21:50:26 - mmengine - INFO - Epoch(train) [42][700/1793] lr: 7.5000e-05 eta: 1:12:13 time: 0.1813 data_time: 0.0074 memory: 10464 grad_norm: 9.5214 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.8507 loss: 0.8507 2022/09/07 21:50:29 - mmengine - INFO - Epoch(train) [42][720/1793] lr: 7.5000e-05 eta: 1:12:07 time: 0.1720 data_time: 0.0068 memory: 10464 grad_norm: 9.6675 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2089 loss: 1.2089 2022/09/07 21:50:33 - mmengine - INFO - Epoch(train) [42][740/1793] lr: 7.5000e-05 eta: 1:12:01 time: 0.1757 data_time: 0.0090 memory: 10464 grad_norm: 10.1587 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0120 loss: 1.0120 2022/09/07 21:50:37 - mmengine - INFO - Epoch(train) [42][760/1793] lr: 7.5000e-05 eta: 1:11:55 time: 0.1785 data_time: 0.0063 memory: 10464 grad_norm: 9.3319 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9990 loss: 0.9990 2022/09/07 21:50:40 - mmengine - INFO - Epoch(train) [42][780/1793] lr: 7.5000e-05 eta: 1:11:49 time: 0.1713 data_time: 0.0064 memory: 10464 grad_norm: 9.3715 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1345 loss: 1.1345 2022/09/07 21:50:44 - mmengine - INFO - Epoch(train) [42][800/1793] lr: 7.5000e-05 eta: 1:11:43 time: 0.1765 data_time: 0.0093 memory: 10464 grad_norm: 9.7182 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2340 loss: 1.2340 2022/09/07 21:50:47 - mmengine - INFO - Epoch(train) [42][820/1793] lr: 7.5000e-05 eta: 1:11:37 time: 0.1782 data_time: 0.0083 memory: 10464 grad_norm: 10.1237 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2190 loss: 1.2190 2022/09/07 21:50:51 - mmengine - INFO - Epoch(train) [42][840/1793] lr: 7.5000e-05 eta: 1:11:31 time: 0.1724 data_time: 0.0070 memory: 10464 grad_norm: 9.5693 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.0610 loss: 1.0610 2022/09/07 21:50:54 - mmengine - INFO - Epoch(train) [42][860/1793] lr: 7.5000e-05 eta: 1:11:24 time: 0.1772 data_time: 0.0097 memory: 10464 grad_norm: 9.6984 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3670 loss: 1.3670 2022/09/07 21:50:58 - mmengine - INFO - Epoch(train) [42][880/1793] lr: 7.5000e-05 eta: 1:11:18 time: 0.1751 data_time: 0.0068 memory: 10464 grad_norm: 9.4573 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1715 loss: 1.1715 2022/09/07 21:51:01 - mmengine - INFO - Epoch(train) [42][900/1793] lr: 7.5000e-05 eta: 1:11:12 time: 0.1715 data_time: 0.0067 memory: 10464 grad_norm: 9.4015 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1373 loss: 1.1373 2022/09/07 21:51:05 - mmengine - INFO - Epoch(train) [42][920/1793] lr: 7.5000e-05 eta: 1:11:06 time: 0.1813 data_time: 0.0087 memory: 10464 grad_norm: 9.4199 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0270 loss: 1.0270 2022/09/07 21:51:08 - mmengine - INFO - Epoch(train) [42][940/1793] lr: 7.5000e-05 eta: 1:11:00 time: 0.1881 data_time: 0.0074 memory: 10464 grad_norm: 9.3068 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1967 loss: 1.1967 2022/09/07 21:51:12 - mmengine - INFO - Epoch(train) [42][960/1793] lr: 7.5000e-05 eta: 1:10:54 time: 0.1702 data_time: 0.0063 memory: 10464 grad_norm: 9.4034 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2228 loss: 1.2228 2022/09/07 21:51:15 - mmengine - INFO - Epoch(train) [42][980/1793] lr: 7.5000e-05 eta: 1:10:48 time: 0.1742 data_time: 0.0085 memory: 10464 grad_norm: 9.5030 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1010 loss: 1.1010 2022/09/07 21:51:19 - mmengine - INFO - Epoch(train) [42][1000/1793] lr: 7.5000e-05 eta: 1:10:42 time: 0.1743 data_time: 0.0064 memory: 10464 grad_norm: 9.7347 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1551 loss: 1.1551 2022/09/07 21:51:22 - mmengine - INFO - Epoch(train) [42][1020/1793] lr: 7.5000e-05 eta: 1:10:36 time: 0.1720 data_time: 0.0066 memory: 10464 grad_norm: 9.3488 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0972 loss: 1.0972 2022/09/07 21:51:26 - mmengine - INFO - Epoch(train) [42][1040/1793] lr: 7.5000e-05 eta: 1:10:30 time: 0.1983 data_time: 0.0101 memory: 10464 grad_norm: 9.5575 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.1744 loss: 1.1744 2022/09/07 21:51:30 - mmengine - INFO - Epoch(train) [42][1060/1793] lr: 7.5000e-05 eta: 1:10:24 time: 0.1721 data_time: 0.0063 memory: 10464 grad_norm: 9.4820 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1230 loss: 1.1230 2022/09/07 21:51:33 - mmengine - INFO - Epoch(train) [42][1080/1793] lr: 7.5000e-05 eta: 1:10:18 time: 0.1734 data_time: 0.0064 memory: 10464 grad_norm: 10.0323 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2765 loss: 1.2765 2022/09/07 21:51:37 - mmengine - INFO - Epoch(train) [42][1100/1793] lr: 7.5000e-05 eta: 1:10:12 time: 0.1810 data_time: 0.0086 memory: 10464 grad_norm: 9.7268 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3669 loss: 1.3669 2022/09/07 21:51:40 - mmengine - INFO - Epoch(train) [42][1120/1793] lr: 7.5000e-05 eta: 1:10:06 time: 0.1702 data_time: 0.0061 memory: 10464 grad_norm: 9.6615 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.2683 loss: 1.2683 2022/09/07 21:51:44 - mmengine - INFO - Epoch(train) [42][1140/1793] lr: 7.5000e-05 eta: 1:10:00 time: 0.1738 data_time: 0.0068 memory: 10464 grad_norm: 9.7665 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.5921 loss: 1.5921 2022/09/07 21:51:47 - mmengine - INFO - Epoch(train) [42][1160/1793] lr: 7.5000e-05 eta: 1:09:54 time: 0.1769 data_time: 0.0089 memory: 10464 grad_norm: 9.6868 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1285 loss: 1.1285 2022/09/07 21:51:51 - mmengine - INFO - Epoch(train) [42][1180/1793] lr: 7.5000e-05 eta: 1:09:48 time: 0.1712 data_time: 0.0067 memory: 10464 grad_norm: 9.4193 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.3014 loss: 1.3014 2022/09/07 21:51:54 - mmengine - INFO - Epoch(train) [42][1200/1793] lr: 7.5000e-05 eta: 1:09:42 time: 0.1827 data_time: 0.0064 memory: 10464 grad_norm: 9.8108 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0226 loss: 1.0226 2022/09/07 21:51:58 - mmengine - INFO - Epoch(train) [42][1220/1793] lr: 7.5000e-05 eta: 1:09:36 time: 0.1752 data_time: 0.0088 memory: 10464 grad_norm: 9.7158 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.1962 loss: 1.1962 2022/09/07 21:52:01 - mmengine - INFO - Epoch(train) [42][1240/1793] lr: 7.5000e-05 eta: 1:09:30 time: 0.1713 data_time: 0.0066 memory: 10464 grad_norm: 9.7614 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4823 loss: 1.4823 2022/09/07 21:52:05 - mmengine - INFO - Epoch(train) [42][1260/1793] lr: 7.5000e-05 eta: 1:09:24 time: 0.1768 data_time: 0.0063 memory: 10464 grad_norm: 9.9064 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1475 loss: 1.1475 2022/09/07 21:52:08 - mmengine - INFO - Epoch(train) [42][1280/1793] lr: 7.5000e-05 eta: 1:09:18 time: 0.1785 data_time: 0.0099 memory: 10464 grad_norm: 9.3877 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0602 loss: 1.0602 2022/09/07 21:52:12 - mmengine - INFO - Epoch(train) [42][1300/1793] lr: 7.5000e-05 eta: 1:09:12 time: 0.1715 data_time: 0.0076 memory: 10464 grad_norm: 9.6448 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.1449 loss: 1.1449 2022/09/07 21:52:15 - mmengine - INFO - Epoch(train) [42][1320/1793] lr: 7.5000e-05 eta: 1:09:06 time: 0.1717 data_time: 0.0065 memory: 10464 grad_norm: 9.4091 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0748 loss: 1.0748 2022/09/07 21:52:19 - mmengine - INFO - Epoch(train) [42][1340/1793] lr: 7.5000e-05 eta: 1:09:00 time: 0.1816 data_time: 0.0091 memory: 10464 grad_norm: 10.3123 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 0.9618 loss: 0.9618 2022/09/07 21:52:22 - mmengine - INFO - Epoch(train) [42][1360/1793] lr: 7.5000e-05 eta: 1:08:54 time: 0.1723 data_time: 0.0066 memory: 10464 grad_norm: 9.8199 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1603 loss: 1.1603 2022/09/07 21:52:26 - mmengine - INFO - Epoch(train) [42][1380/1793] lr: 7.5000e-05 eta: 1:08:48 time: 0.1786 data_time: 0.0072 memory: 10464 grad_norm: 9.7142 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 0.9253 loss: 0.9253 2022/09/07 21:52:29 - mmengine - INFO - Epoch(train) [42][1400/1793] lr: 7.5000e-05 eta: 1:08:42 time: 0.1737 data_time: 0.0096 memory: 10464 grad_norm: 9.9828 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4698 loss: 1.4698 2022/09/07 21:52:33 - mmengine - INFO - Epoch(train) [42][1420/1793] lr: 7.5000e-05 eta: 1:08:36 time: 0.1708 data_time: 0.0064 memory: 10464 grad_norm: 9.1926 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1425 loss: 1.1425 2022/09/07 21:52:37 - mmengine - INFO - Epoch(train) [42][1440/1793] lr: 7.5000e-05 eta: 1:08:30 time: 0.1900 data_time: 0.0079 memory: 10464 grad_norm: 9.3312 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2053 loss: 1.2053 2022/09/07 21:52:40 - mmengine - INFO - Epoch(train) [42][1460/1793] lr: 7.5000e-05 eta: 1:08:24 time: 0.1743 data_time: 0.0093 memory: 10464 grad_norm: 10.2475 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3702 loss: 1.3702 2022/09/07 21:52:44 - mmengine - INFO - Epoch(train) [42][1480/1793] lr: 7.5000e-05 eta: 1:08:18 time: 0.1773 data_time: 0.0063 memory: 10464 grad_norm: 10.0382 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.3886 loss: 1.3886 2022/09/07 21:52:45 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:52:47 - mmengine - INFO - Epoch(train) [42][1500/1793] lr: 7.5000e-05 eta: 1:08:12 time: 0.1714 data_time: 0.0073 memory: 10464 grad_norm: 9.4733 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0901 loss: 1.0901 2022/09/07 21:52:51 - mmengine - INFO - Epoch(train) [42][1520/1793] lr: 7.5000e-05 eta: 1:08:06 time: 0.1774 data_time: 0.0089 memory: 10464 grad_norm: 9.5276 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 0.8488 loss: 0.8488 2022/09/07 21:52:54 - mmengine - INFO - Epoch(train) [42][1540/1793] lr: 7.5000e-05 eta: 1:08:00 time: 0.1752 data_time: 0.0067 memory: 10464 grad_norm: 9.9467 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.3395 loss: 1.3395 2022/09/07 21:52:58 - mmengine - INFO - Epoch(train) [42][1560/1793] lr: 7.5000e-05 eta: 1:07:54 time: 0.1757 data_time: 0.0073 memory: 10464 grad_norm: 9.7521 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2149 loss: 1.2149 2022/09/07 21:53:01 - mmengine - INFO - Epoch(train) [42][1580/1793] lr: 7.5000e-05 eta: 1:07:48 time: 0.1736 data_time: 0.0097 memory: 10464 grad_norm: 9.4321 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2081 loss: 1.2081 2022/09/07 21:53:05 - mmengine - INFO - Epoch(train) [42][1600/1793] lr: 7.5000e-05 eta: 1:07:42 time: 0.1719 data_time: 0.0064 memory: 10464 grad_norm: 9.4186 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.3818 loss: 1.3818 2022/09/07 21:53:08 - mmengine - INFO - Epoch(train) [42][1620/1793] lr: 7.5000e-05 eta: 1:07:36 time: 0.1739 data_time: 0.0068 memory: 10464 grad_norm: 10.1126 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2092 loss: 1.2092 2022/09/07 21:53:12 - mmengine - INFO - Epoch(train) [42][1640/1793] lr: 7.5000e-05 eta: 1:07:30 time: 0.1726 data_time: 0.0088 memory: 10464 grad_norm: 9.4233 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2323 loss: 1.2323 2022/09/07 21:53:15 - mmengine - INFO - Epoch(train) [42][1660/1793] lr: 7.5000e-05 eta: 1:07:24 time: 0.1722 data_time: 0.0072 memory: 10464 grad_norm: 9.6537 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3885 loss: 1.3885 2022/09/07 21:53:19 - mmengine - INFO - Epoch(train) [42][1680/1793] lr: 7.5000e-05 eta: 1:07:18 time: 0.1802 data_time: 0.0081 memory: 10464 grad_norm: 9.6030 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2475 loss: 1.2475 2022/09/07 21:53:22 - mmengine - INFO - Epoch(train) [42][1700/1793] lr: 7.5000e-05 eta: 1:07:12 time: 0.1758 data_time: 0.0094 memory: 10464 grad_norm: 10.1474 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3551 loss: 1.3551 2022/09/07 21:53:26 - mmengine - INFO - Epoch(train) [42][1720/1793] lr: 7.5000e-05 eta: 1:07:06 time: 0.1712 data_time: 0.0065 memory: 10464 grad_norm: 9.6931 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0787 loss: 1.0787 2022/09/07 21:53:29 - mmengine - INFO - Epoch(train) [42][1740/1793] lr: 7.5000e-05 eta: 1:07:00 time: 0.1717 data_time: 0.0068 memory: 10464 grad_norm: 9.8310 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 0.9987 loss: 0.9987 2022/09/07 21:53:32 - mmengine - INFO - Epoch(train) [42][1760/1793] lr: 7.5000e-05 eta: 1:06:54 time: 0.1746 data_time: 0.0093 memory: 10464 grad_norm: 9.5618 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1233 loss: 1.1233 2022/09/07 21:53:36 - mmengine - INFO - Epoch(train) [42][1780/1793] lr: 7.5000e-05 eta: 1:06:48 time: 0.1759 data_time: 0.0074 memory: 10464 grad_norm: 9.8118 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1459 loss: 1.1459 2022/09/07 21:53:38 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:53:38 - mmengine - INFO - Epoch(train) [42][1793/1793] lr: 7.5000e-05 eta: 1:06:48 time: 0.1719 data_time: 0.0076 memory: 10464 grad_norm: 9.7752 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 1.1987 loss: 1.1987 2022/09/07 21:53:38 - mmengine - INFO - Saving checkpoint at 42 epochs 2022/09/07 21:53:42 - mmengine - INFO - Epoch(val) [42][20/241] eta: 0:00:13 time: 0.0588 data_time: 0.0095 memory: 1482 2022/09/07 21:53:43 - mmengine - INFO - Epoch(val) [42][40/241] eta: 0:00:10 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 21:53:44 - mmengine - INFO - Epoch(val) [42][60/241] eta: 0:00:09 time: 0.0528 data_time: 0.0047 memory: 1482 2022/09/07 21:53:45 - mmengine - INFO - Epoch(val) [42][80/241] eta: 0:00:08 time: 0.0527 data_time: 0.0047 memory: 1482 2022/09/07 21:53:46 - mmengine - INFO - Epoch(val) [42][100/241] eta: 0:00:07 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 21:53:47 - mmengine - INFO - Epoch(val) [42][120/241] eta: 0:00:06 time: 0.0531 data_time: 0.0048 memory: 1482 2022/09/07 21:53:48 - mmengine - INFO - Epoch(val) [42][140/241] eta: 0:00:05 time: 0.0535 data_time: 0.0051 memory: 1482 2022/09/07 21:53:49 - mmengine - INFO - Epoch(val) [42][160/241] eta: 0:00:04 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 21:53:50 - mmengine - INFO - Epoch(val) [42][180/241] eta: 0:00:03 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 21:53:51 - mmengine - INFO - Epoch(val) [42][200/241] eta: 0:00:02 time: 0.0527 data_time: 0.0046 memory: 1482 2022/09/07 21:53:52 - mmengine - INFO - Epoch(val) [42][220/241] eta: 0:00:01 time: 0.0528 data_time: 0.0048 memory: 1482 2022/09/07 21:53:54 - mmengine - INFO - Epoch(val) [42][240/241] eta: 0:00:00 time: 0.0522 data_time: 0.0044 memory: 1482 2022/09/07 21:53:54 - mmengine - INFO - Epoch(val) [42][241/241] acc/top1: 0.4773 acc/top5: 0.7769 acc/mean1: 0.4410 2022/09/07 21:53:58 - mmengine - INFO - Epoch(train) [43][20/1793] lr: 7.5000e-05 eta: 1:06:38 time: 0.1864 data_time: 0.0123 memory: 10464 grad_norm: 9.5772 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1607 loss: 1.1607 2022/09/07 21:54:01 - mmengine - INFO - Epoch(train) [43][40/1793] lr: 7.5000e-05 eta: 1:06:32 time: 0.1733 data_time: 0.0078 memory: 10464 grad_norm: 9.3213 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 0.8492 loss: 0.8492 2022/09/07 21:54:05 - mmengine - INFO - Epoch(train) [43][60/1793] lr: 7.5000e-05 eta: 1:06:26 time: 0.1742 data_time: 0.0066 memory: 10464 grad_norm: 9.9673 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0492 loss: 1.0492 2022/09/07 21:54:08 - mmengine - INFO - Epoch(train) [43][80/1793] lr: 7.5000e-05 eta: 1:06:20 time: 0.1762 data_time: 0.0098 memory: 10464 grad_norm: 9.7655 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3984 loss: 1.3984 2022/09/07 21:54:12 - mmengine - INFO - Epoch(train) [43][100/1793] lr: 7.5000e-05 eta: 1:06:14 time: 0.1716 data_time: 0.0066 memory: 10464 grad_norm: 9.7177 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1676 loss: 1.1676 2022/09/07 21:54:16 - mmengine - INFO - Epoch(train) [43][120/1793] lr: 7.5000e-05 eta: 1:06:08 time: 0.1905 data_time: 0.0066 memory: 10464 grad_norm: 9.2716 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0608 loss: 1.0608 2022/09/07 21:54:19 - mmengine - INFO - Epoch(train) [43][140/1793] lr: 7.5000e-05 eta: 1:06:02 time: 0.1823 data_time: 0.0097 memory: 10464 grad_norm: 9.0429 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0340 loss: 1.0340 2022/09/07 21:54:23 - mmengine - INFO - Epoch(train) [43][160/1793] lr: 7.5000e-05 eta: 1:05:56 time: 0.1727 data_time: 0.0067 memory: 10464 grad_norm: 9.9150 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1399 loss: 1.1399 2022/09/07 21:54:26 - mmengine - INFO - Epoch(train) [43][180/1793] lr: 7.5000e-05 eta: 1:05:50 time: 0.1736 data_time: 0.0064 memory: 10464 grad_norm: 9.9157 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0708 loss: 1.0708 2022/09/07 21:54:30 - mmengine - INFO - Epoch(train) [43][200/1793] lr: 7.5000e-05 eta: 1:05:44 time: 0.1756 data_time: 0.0102 memory: 10464 grad_norm: 9.8605 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1572 loss: 1.1572 2022/09/07 21:54:33 - mmengine - INFO - Epoch(train) [43][220/1793] lr: 7.5000e-05 eta: 1:05:38 time: 0.1741 data_time: 0.0064 memory: 10464 grad_norm: 10.3447 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4978 loss: 1.4978 2022/09/07 21:54:37 - mmengine - INFO - Epoch(train) [43][240/1793] lr: 7.5000e-05 eta: 1:05:32 time: 0.1954 data_time: 0.0078 memory: 10464 grad_norm: 9.3155 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0823 loss: 1.0823 2022/09/07 21:54:41 - mmengine - INFO - Epoch(train) [43][260/1793] lr: 7.5000e-05 eta: 1:05:26 time: 0.1747 data_time: 0.0091 memory: 10464 grad_norm: 9.6594 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1283 loss: 1.1283 2022/09/07 21:54:44 - mmengine - INFO - Epoch(train) [43][280/1793] lr: 7.5000e-05 eta: 1:05:20 time: 0.1730 data_time: 0.0068 memory: 10464 grad_norm: 9.5074 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1557 loss: 1.1557 2022/09/07 21:54:48 - mmengine - INFO - Epoch(train) [43][300/1793] lr: 7.5000e-05 eta: 1:05:14 time: 0.1743 data_time: 0.0073 memory: 10464 grad_norm: 9.5635 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9274 loss: 0.9274 2022/09/07 21:54:51 - mmengine - INFO - Epoch(train) [43][320/1793] lr: 7.5000e-05 eta: 1:05:08 time: 0.1746 data_time: 0.0085 memory: 10464 grad_norm: 9.8601 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0445 loss: 1.0445 2022/09/07 21:54:55 - mmengine - INFO - Epoch(train) [43][340/1793] lr: 7.5000e-05 eta: 1:05:02 time: 0.1759 data_time: 0.0064 memory: 10464 grad_norm: 9.3226 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.2477 loss: 1.2477 2022/09/07 21:54:58 - mmengine - INFO - Epoch(train) [43][360/1793] lr: 7.5000e-05 eta: 1:04:56 time: 0.1820 data_time: 0.0077 memory: 10464 grad_norm: 9.5710 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2883 loss: 1.2883 2022/09/07 21:55:02 - mmengine - INFO - Epoch(train) [43][380/1793] lr: 7.5000e-05 eta: 1:04:51 time: 0.1740 data_time: 0.0090 memory: 10464 grad_norm: 9.3443 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1950 loss: 1.1950 2022/09/07 21:55:05 - mmengine - INFO - Epoch(train) [43][400/1793] lr: 7.5000e-05 eta: 1:04:45 time: 0.1740 data_time: 0.0071 memory: 10464 grad_norm: 9.5888 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0328 loss: 1.0328 2022/09/07 21:55:09 - mmengine - INFO - Epoch(train) [43][420/1793] lr: 7.5000e-05 eta: 1:04:39 time: 0.1724 data_time: 0.0061 memory: 10464 grad_norm: 9.7316 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0498 loss: 1.0498 2022/09/07 21:55:12 - mmengine - INFO - Epoch(train) [43][440/1793] lr: 7.5000e-05 eta: 1:04:33 time: 0.1742 data_time: 0.0092 memory: 10464 grad_norm: 9.4772 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1726 loss: 1.1726 2022/09/07 21:55:16 - mmengine - INFO - Epoch(train) [43][460/1793] lr: 7.5000e-05 eta: 1:04:27 time: 0.1736 data_time: 0.0065 memory: 10464 grad_norm: 9.7630 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1179 loss: 1.1179 2022/09/07 21:55:19 - mmengine - INFO - Epoch(train) [43][480/1793] lr: 7.5000e-05 eta: 1:04:21 time: 0.1919 data_time: 0.0078 memory: 10464 grad_norm: 9.4579 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1110 loss: 1.1110 2022/09/07 21:55:23 - mmengine - INFO - Epoch(train) [43][500/1793] lr: 7.5000e-05 eta: 1:04:15 time: 0.1738 data_time: 0.0094 memory: 10464 grad_norm: 10.0697 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3076 loss: 1.3076 2022/09/07 21:55:27 - mmengine - INFO - Epoch(train) [43][520/1793] lr: 7.5000e-05 eta: 1:04:09 time: 0.1831 data_time: 0.0065 memory: 10464 grad_norm: 10.1416 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1685 loss: 1.1685 2022/09/07 21:55:30 - mmengine - INFO - Epoch(train) [43][540/1793] lr: 7.5000e-05 eta: 1:04:03 time: 0.1723 data_time: 0.0068 memory: 10464 grad_norm: 9.7435 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1488 loss: 1.1488 2022/09/07 21:55:34 - mmengine - INFO - Epoch(train) [43][560/1793] lr: 7.5000e-05 eta: 1:03:57 time: 0.1779 data_time: 0.0087 memory: 10464 grad_norm: 9.7030 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1666 loss: 1.1666 2022/09/07 21:55:37 - mmengine - INFO - Epoch(train) [43][580/1793] lr: 7.5000e-05 eta: 1:03:51 time: 0.1752 data_time: 0.0076 memory: 10464 grad_norm: 9.5387 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1345 loss: 1.1345 2022/09/07 21:55:41 - mmengine - INFO - Epoch(train) [43][600/1793] lr: 7.5000e-05 eta: 1:03:45 time: 0.1715 data_time: 0.0069 memory: 10464 grad_norm: 9.9909 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2375 loss: 1.2375 2022/09/07 21:55:44 - mmengine - INFO - Epoch(train) [43][620/1793] lr: 7.5000e-05 eta: 1:03:39 time: 0.1771 data_time: 0.0088 memory: 10464 grad_norm: 9.8544 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.3350 loss: 1.3350 2022/09/07 21:55:48 - mmengine - INFO - Epoch(train) [43][640/1793] lr: 7.5000e-05 eta: 1:03:33 time: 0.1767 data_time: 0.0067 memory: 10464 grad_norm: 9.6936 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0796 loss: 1.0796 2022/09/07 21:55:51 - mmengine - INFO - Epoch(train) [43][660/1793] lr: 7.5000e-05 eta: 1:03:27 time: 0.1716 data_time: 0.0069 memory: 10464 grad_norm: 9.9131 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1170 loss: 1.1170 2022/09/07 21:55:55 - mmengine - INFO - Epoch(train) [43][680/1793] lr: 7.5000e-05 eta: 1:03:21 time: 0.1769 data_time: 0.0086 memory: 10464 grad_norm: 9.6562 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1506 loss: 1.1506 2022/09/07 21:55:57 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:55:58 - mmengine - INFO - Epoch(train) [43][700/1793] lr: 7.5000e-05 eta: 1:03:15 time: 0.1785 data_time: 0.0078 memory: 10464 grad_norm: 9.8859 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4362 loss: 1.4362 2022/09/07 21:56:02 - mmengine - INFO - Epoch(train) [43][720/1793] lr: 7.5000e-05 eta: 1:03:10 time: 0.1711 data_time: 0.0068 memory: 10464 grad_norm: 9.7336 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0381 loss: 1.0381 2022/09/07 21:56:05 - mmengine - INFO - Epoch(train) [43][740/1793] lr: 7.5000e-05 eta: 1:03:04 time: 0.1771 data_time: 0.0094 memory: 10464 grad_norm: 9.8149 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1529 loss: 1.1529 2022/09/07 21:56:09 - mmengine - INFO - Epoch(train) [43][760/1793] lr: 7.5000e-05 eta: 1:02:58 time: 0.1714 data_time: 0.0065 memory: 10464 grad_norm: 10.1072 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0369 loss: 1.0369 2022/09/07 21:56:12 - mmengine - INFO - Epoch(train) [43][780/1793] lr: 7.5000e-05 eta: 1:02:52 time: 0.1709 data_time: 0.0064 memory: 10464 grad_norm: 9.9142 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3046 loss: 1.3046 2022/09/07 21:56:16 - mmengine - INFO - Epoch(train) [43][800/1793] lr: 7.5000e-05 eta: 1:02:46 time: 0.1782 data_time: 0.0089 memory: 10464 grad_norm: 9.7200 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9031 loss: 0.9031 2022/09/07 21:56:20 - mmengine - INFO - Epoch(train) [43][820/1793] lr: 7.5000e-05 eta: 1:02:40 time: 0.2072 data_time: 0.0081 memory: 10464 grad_norm: 9.4412 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0324 loss: 1.0324 2022/09/07 21:56:23 - mmengine - INFO - Epoch(train) [43][840/1793] lr: 7.5000e-05 eta: 1:02:34 time: 0.1727 data_time: 0.0071 memory: 10464 grad_norm: 9.6474 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0137 loss: 1.0137 2022/09/07 21:56:27 - mmengine - INFO - Epoch(train) [43][860/1793] lr: 7.5000e-05 eta: 1:02:28 time: 0.1756 data_time: 0.0089 memory: 10464 grad_norm: 10.0508 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4538 loss: 1.4538 2022/09/07 21:56:30 - mmengine - INFO - Epoch(train) [43][880/1793] lr: 7.5000e-05 eta: 1:02:22 time: 0.1710 data_time: 0.0065 memory: 10464 grad_norm: 9.9210 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0859 loss: 1.0859 2022/09/07 21:56:34 - mmengine - INFO - Epoch(train) [43][900/1793] lr: 7.5000e-05 eta: 1:02:16 time: 0.1804 data_time: 0.0065 memory: 10464 grad_norm: 10.1064 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1913 loss: 1.1913 2022/09/07 21:56:37 - mmengine - INFO - Epoch(train) [43][920/1793] lr: 7.5000e-05 eta: 1:02:10 time: 0.1772 data_time: 0.0096 memory: 10464 grad_norm: 10.1376 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3030 loss: 1.3030 2022/09/07 21:56:41 - mmengine - INFO - Epoch(train) [43][940/1793] lr: 7.5000e-05 eta: 1:02:04 time: 0.1718 data_time: 0.0066 memory: 10464 grad_norm: 10.1864 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0654 loss: 1.0654 2022/09/07 21:56:44 - mmengine - INFO - Epoch(train) [43][960/1793] lr: 7.5000e-05 eta: 1:01:59 time: 0.1721 data_time: 0.0067 memory: 10464 grad_norm: 9.3129 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0398 loss: 1.0398 2022/09/07 21:56:48 - mmengine - INFO - Epoch(train) [43][980/1793] lr: 7.5000e-05 eta: 1:01:53 time: 0.1770 data_time: 0.0103 memory: 10464 grad_norm: 9.9598 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2072 loss: 1.2072 2022/09/07 21:56:51 - mmengine - INFO - Epoch(train) [43][1000/1793] lr: 7.5000e-05 eta: 1:01:47 time: 0.1713 data_time: 0.0065 memory: 10464 grad_norm: 10.1966 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4994 loss: 1.4994 2022/09/07 21:56:55 - mmengine - INFO - Epoch(train) [43][1020/1793] lr: 7.5000e-05 eta: 1:01:41 time: 0.1792 data_time: 0.0066 memory: 10464 grad_norm: 10.1529 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2954 loss: 1.2954 2022/09/07 21:56:59 - mmengine - INFO - Epoch(train) [43][1040/1793] lr: 7.5000e-05 eta: 1:01:35 time: 0.1917 data_time: 0.0097 memory: 10464 grad_norm: 10.3428 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3847 loss: 1.3847 2022/09/07 21:57:02 - mmengine - INFO - Epoch(train) [43][1060/1793] lr: 7.5000e-05 eta: 1:01:29 time: 0.1706 data_time: 0.0063 memory: 10464 grad_norm: 10.1078 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1282 loss: 1.1282 2022/09/07 21:57:05 - mmengine - INFO - Epoch(train) [43][1080/1793] lr: 7.5000e-05 eta: 1:01:23 time: 0.1714 data_time: 0.0066 memory: 10464 grad_norm: 9.6653 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.1893 loss: 1.1893 2022/09/07 21:57:09 - mmengine - INFO - Epoch(train) [43][1100/1793] lr: 7.5000e-05 eta: 1:01:17 time: 0.1752 data_time: 0.0092 memory: 10464 grad_norm: 9.4917 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2272 loss: 1.2272 2022/09/07 21:57:12 - mmengine - INFO - Epoch(train) [43][1120/1793] lr: 7.5000e-05 eta: 1:01:11 time: 0.1700 data_time: 0.0064 memory: 10464 grad_norm: 9.5026 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0892 loss: 1.0892 2022/09/07 21:57:16 - mmengine - INFO - Epoch(train) [43][1140/1793] lr: 7.5000e-05 eta: 1:01:05 time: 0.2005 data_time: 0.0073 memory: 10464 grad_norm: 10.0416 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9611 loss: 0.9611 2022/09/07 21:57:20 - mmengine - INFO - Epoch(train) [43][1160/1793] lr: 7.5000e-05 eta: 1:01:00 time: 0.1748 data_time: 0.0087 memory: 10464 grad_norm: 9.8751 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2596 loss: 1.2596 2022/09/07 21:57:23 - mmengine - INFO - Epoch(train) [43][1180/1793] lr: 7.5000e-05 eta: 1:00:54 time: 0.1727 data_time: 0.0072 memory: 10464 grad_norm: 9.9248 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.0845 loss: 1.0845 2022/09/07 21:57:27 - mmengine - INFO - Epoch(train) [43][1200/1793] lr: 7.5000e-05 eta: 1:00:48 time: 0.1716 data_time: 0.0065 memory: 10464 grad_norm: 9.5106 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9926 loss: 0.9926 2022/09/07 21:57:30 - mmengine - INFO - Epoch(train) [43][1220/1793] lr: 7.5000e-05 eta: 1:00:42 time: 0.1731 data_time: 0.0091 memory: 10464 grad_norm: 9.6917 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1759 loss: 1.1759 2022/09/07 21:57:34 - mmengine - INFO - Epoch(train) [43][1240/1793] lr: 7.5000e-05 eta: 1:00:36 time: 0.1845 data_time: 0.0068 memory: 10464 grad_norm: 9.3902 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 0.9804 loss: 0.9804 2022/09/07 21:57:37 - mmengine - INFO - Epoch(train) [43][1260/1793] lr: 7.5000e-05 eta: 1:00:30 time: 0.1751 data_time: 0.0068 memory: 10464 grad_norm: 9.8586 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1841 loss: 1.1841 2022/09/07 21:57:41 - mmengine - INFO - Epoch(train) [43][1280/1793] lr: 7.5000e-05 eta: 1:00:24 time: 0.1738 data_time: 0.0095 memory: 10464 grad_norm: 9.7196 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2835 loss: 1.2835 2022/09/07 21:57:44 - mmengine - INFO - Epoch(train) [43][1300/1793] lr: 7.5000e-05 eta: 1:00:18 time: 0.1742 data_time: 0.0067 memory: 10464 grad_norm: 9.3756 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0507 loss: 1.0507 2022/09/07 21:57:48 - mmengine - INFO - Epoch(train) [43][1320/1793] lr: 7.5000e-05 eta: 1:00:12 time: 0.1719 data_time: 0.0068 memory: 10464 grad_norm: 9.8683 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2494 loss: 1.2494 2022/09/07 21:57:51 - mmengine - INFO - Epoch(train) [43][1340/1793] lr: 7.5000e-05 eta: 1:00:06 time: 0.1733 data_time: 0.0096 memory: 10464 grad_norm: 10.1238 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0581 loss: 1.0581 2022/09/07 21:57:55 - mmengine - INFO - Epoch(train) [43][1360/1793] lr: 7.5000e-05 eta: 1:00:00 time: 0.1747 data_time: 0.0060 memory: 10464 grad_norm: 9.5704 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0339 loss: 1.0339 2022/09/07 21:57:58 - mmengine - INFO - Epoch(train) [43][1380/1793] lr: 7.5000e-05 eta: 0:59:55 time: 0.1767 data_time: 0.0076 memory: 10464 grad_norm: 10.5194 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.4177 loss: 1.4177 2022/09/07 21:58:02 - mmengine - INFO - Epoch(train) [43][1400/1793] lr: 7.5000e-05 eta: 0:59:49 time: 0.1731 data_time: 0.0087 memory: 10464 grad_norm: 9.9279 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3452 loss: 1.3452 2022/09/07 21:58:05 - mmengine - INFO - Epoch(train) [43][1420/1793] lr: 7.5000e-05 eta: 0:59:43 time: 0.1722 data_time: 0.0061 memory: 10464 grad_norm: 9.5816 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3309 loss: 1.3309 2022/09/07 21:58:09 - mmengine - INFO - Epoch(train) [43][1440/1793] lr: 7.5000e-05 eta: 0:59:37 time: 0.1821 data_time: 0.0078 memory: 10464 grad_norm: 9.8985 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1232 loss: 1.1232 2022/09/07 21:58:12 - mmengine - INFO - Epoch(train) [43][1460/1793] lr: 7.5000e-05 eta: 0:59:31 time: 0.1739 data_time: 0.0086 memory: 10464 grad_norm: 9.8930 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.2623 loss: 1.2623 2022/09/07 21:58:16 - mmengine - INFO - Epoch(train) [43][1480/1793] lr: 7.5000e-05 eta: 0:59:25 time: 0.1741 data_time: 0.0067 memory: 10464 grad_norm: 9.9425 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2303 loss: 1.2303 2022/09/07 21:58:19 - mmengine - INFO - Epoch(train) [43][1500/1793] lr: 7.5000e-05 eta: 0:59:19 time: 0.1793 data_time: 0.0069 memory: 10464 grad_norm: 9.6598 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1876 loss: 1.1876 2022/09/07 21:58:23 - mmengine - INFO - Epoch(train) [43][1520/1793] lr: 7.5000e-05 eta: 0:59:13 time: 0.1758 data_time: 0.0094 memory: 10464 grad_norm: 9.9599 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0783 loss: 1.0783 2022/09/07 21:58:26 - mmengine - INFO - Epoch(train) [43][1540/1793] lr: 7.5000e-05 eta: 0:59:08 time: 0.1732 data_time: 0.0067 memory: 10464 grad_norm: 9.8042 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1274 loss: 1.1274 2022/09/07 21:58:30 - mmengine - INFO - Epoch(train) [43][1560/1793] lr: 7.5000e-05 eta: 0:59:02 time: 0.1721 data_time: 0.0066 memory: 10464 grad_norm: 9.7177 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1859 loss: 1.1859 2022/09/07 21:58:33 - mmengine - INFO - Epoch(train) [43][1580/1793] lr: 7.5000e-05 eta: 0:58:56 time: 0.1758 data_time: 0.0088 memory: 10464 grad_norm: 10.4460 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1546 loss: 1.1546 2022/09/07 21:58:37 - mmengine - INFO - Epoch(train) [43][1600/1793] lr: 7.5000e-05 eta: 0:58:50 time: 0.1764 data_time: 0.0073 memory: 10464 grad_norm: 10.2736 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3658 loss: 1.3658 2022/09/07 21:58:40 - mmengine - INFO - Epoch(train) [43][1620/1793] lr: 7.5000e-05 eta: 0:58:44 time: 0.1724 data_time: 0.0067 memory: 10464 grad_norm: 9.8729 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1982 loss: 1.1982 2022/09/07 21:58:44 - mmengine - INFO - Epoch(train) [43][1640/1793] lr: 7.5000e-05 eta: 0:58:38 time: 0.1753 data_time: 0.0097 memory: 10464 grad_norm: 9.6722 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0485 loss: 1.0485 2022/09/07 21:58:47 - mmengine - INFO - Epoch(train) [43][1660/1793] lr: 7.5000e-05 eta: 0:58:32 time: 0.1714 data_time: 0.0063 memory: 10464 grad_norm: 9.9837 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1115 loss: 1.1115 2022/09/07 21:58:51 - mmengine - INFO - Epoch(train) [43][1680/1793] lr: 7.5000e-05 eta: 0:58:26 time: 0.1709 data_time: 0.0066 memory: 10464 grad_norm: 9.8446 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3002 loss: 1.3002 2022/09/07 21:58:53 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:58:55 - mmengine - INFO - Epoch(train) [43][1700/1793] lr: 7.5000e-05 eta: 0:58:21 time: 0.1903 data_time: 0.0099 memory: 10464 grad_norm: 10.2101 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2226 loss: 1.2226 2022/09/07 21:58:58 - mmengine - INFO - Epoch(train) [43][1720/1793] lr: 7.5000e-05 eta: 0:58:15 time: 0.1938 data_time: 0.0072 memory: 10464 grad_norm: 10.0356 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1356 loss: 1.1356 2022/09/07 21:59:02 - mmengine - INFO - Epoch(train) [43][1740/1793] lr: 7.5000e-05 eta: 0:58:09 time: 0.1732 data_time: 0.0063 memory: 10464 grad_norm: 10.2061 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3207 loss: 1.3207 2022/09/07 21:59:05 - mmengine - INFO - Epoch(train) [43][1760/1793] lr: 7.5000e-05 eta: 0:58:03 time: 0.1761 data_time: 0.0090 memory: 10464 grad_norm: 9.9293 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0764 loss: 1.0764 2022/09/07 21:59:09 - mmengine - INFO - Epoch(train) [43][1780/1793] lr: 7.5000e-05 eta: 0:57:57 time: 0.1738 data_time: 0.0065 memory: 10464 grad_norm: 9.6630 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8517 loss: 0.8517 2022/09/07 21:59:11 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 21:59:11 - mmengine - INFO - Epoch(train) [43][1793/1793] lr: 7.5000e-05 eta: 0:57:57 time: 0.1677 data_time: 0.0062 memory: 10464 grad_norm: 9.9071 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 1.1401 loss: 1.1401 2022/09/07 21:59:11 - mmengine - INFO - Saving checkpoint at 43 epochs 2022/09/07 21:59:15 - mmengine - INFO - Epoch(val) [43][20/241] eta: 0:00:12 time: 0.0578 data_time: 0.0089 memory: 1482 2022/09/07 21:59:16 - mmengine - INFO - Epoch(val) [43][40/241] eta: 0:00:10 time: 0.0533 data_time: 0.0051 memory: 1482 2022/09/07 21:59:17 - mmengine - INFO - Epoch(val) [43][60/241] eta: 0:00:09 time: 0.0531 data_time: 0.0049 memory: 1482 2022/09/07 21:59:18 - mmengine - INFO - Epoch(val) [43][80/241] eta: 0:00:08 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 21:59:19 - mmengine - INFO - Epoch(val) [43][100/241] eta: 0:00:07 time: 0.0534 data_time: 0.0051 memory: 1482 2022/09/07 21:59:20 - mmengine - INFO - Epoch(val) [43][120/241] eta: 0:00:06 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 21:59:21 - mmengine - INFO - Epoch(val) [43][140/241] eta: 0:00:05 time: 0.0547 data_time: 0.0061 memory: 1482 2022/09/07 21:59:22 - mmengine - INFO - Epoch(val) [43][160/241] eta: 0:00:04 time: 0.0526 data_time: 0.0042 memory: 1482 2022/09/07 21:59:23 - mmengine - INFO - Epoch(val) [43][180/241] eta: 0:00:03 time: 0.0529 data_time: 0.0047 memory: 1482 2022/09/07 21:59:24 - mmengine - INFO - Epoch(val) [43][200/241] eta: 0:00:02 time: 0.0525 data_time: 0.0045 memory: 1482 2022/09/07 21:59:25 - mmengine - INFO - Epoch(val) [43][220/241] eta: 0:00:01 time: 0.0524 data_time: 0.0045 memory: 1482 2022/09/07 21:59:27 - mmengine - INFO - Epoch(val) [43][240/241] eta: 0:00:00 time: 0.0579 data_time: 0.0056 memory: 1482 2022/09/07 21:59:27 - mmengine - INFO - Epoch(val) [43][241/241] acc/top1: 0.4839 acc/top5: 0.7793 acc/mean1: 0.4457 2022/09/07 21:59:27 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb/best_acc/top1_epoch_41.pth is removed 2022/09/07 21:59:29 - mmengine - INFO - The best checkpoint with 0.4839 acc/top1 at 43 epoch is saved to best_acc/top1_epoch_43.pth. 2022/09/07 21:59:32 - mmengine - INFO - Epoch(train) [44][20/1793] lr: 7.5000e-05 eta: 0:57:47 time: 0.1857 data_time: 0.0157 memory: 10464 grad_norm: 9.7080 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1645 loss: 1.1645 2022/09/07 21:59:36 - mmengine - INFO - Epoch(train) [44][40/1793] lr: 7.5000e-05 eta: 0:57:41 time: 0.1732 data_time: 0.0065 memory: 10464 grad_norm: 9.5094 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1042 loss: 1.1042 2022/09/07 21:59:39 - mmengine - INFO - Epoch(train) [44][60/1793] lr: 7.5000e-05 eta: 0:57:35 time: 0.1720 data_time: 0.0060 memory: 10464 grad_norm: 10.1203 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9962 loss: 0.9962 2022/09/07 21:59:43 - mmengine - INFO - Epoch(train) [44][80/1793] lr: 7.5000e-05 eta: 0:57:29 time: 0.1771 data_time: 0.0091 memory: 10464 grad_norm: 10.1912 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0851 loss: 1.0851 2022/09/07 21:59:47 - mmengine - INFO - Epoch(train) [44][100/1793] lr: 7.5000e-05 eta: 0:57:24 time: 0.1863 data_time: 0.0063 memory: 10464 grad_norm: 9.5148 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1655 loss: 1.1655 2022/09/07 21:59:50 - mmengine - INFO - Epoch(train) [44][120/1793] lr: 7.5000e-05 eta: 0:57:18 time: 0.1746 data_time: 0.0062 memory: 10464 grad_norm: 9.6635 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2752 loss: 1.2752 2022/09/07 21:59:54 - mmengine - INFO - Epoch(train) [44][140/1793] lr: 7.5000e-05 eta: 0:57:12 time: 0.1763 data_time: 0.0086 memory: 10464 grad_norm: 9.9124 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2815 loss: 1.2815 2022/09/07 21:59:57 - mmengine - INFO - Epoch(train) [44][160/1793] lr: 7.5000e-05 eta: 0:57:06 time: 0.1729 data_time: 0.0073 memory: 10464 grad_norm: 9.7317 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 0.9222 loss: 0.9222 2022/09/07 22:00:01 - mmengine - INFO - Epoch(train) [44][180/1793] lr: 7.5000e-05 eta: 0:57:00 time: 0.1719 data_time: 0.0062 memory: 10464 grad_norm: 9.6761 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1384 loss: 1.1384 2022/09/07 22:00:04 - mmengine - INFO - Epoch(train) [44][200/1793] lr: 7.5000e-05 eta: 0:56:54 time: 0.1745 data_time: 0.0087 memory: 10464 grad_norm: 9.5508 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1950 loss: 1.1950 2022/09/07 22:00:08 - mmengine - INFO - Epoch(train) [44][220/1793] lr: 7.5000e-05 eta: 0:56:49 time: 0.1800 data_time: 0.0079 memory: 10464 grad_norm: 9.7393 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.0968 loss: 1.0968 2022/09/07 22:00:11 - mmengine - INFO - Epoch(train) [44][240/1793] lr: 7.5000e-05 eta: 0:56:43 time: 0.1708 data_time: 0.0063 memory: 10464 grad_norm: 9.9585 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1216 loss: 1.1216 2022/09/07 22:00:15 - mmengine - INFO - Epoch(train) [44][260/1793] lr: 7.5000e-05 eta: 0:56:37 time: 0.1777 data_time: 0.0097 memory: 10464 grad_norm: 9.8064 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9573 loss: 0.9573 2022/09/07 22:00:18 - mmengine - INFO - Epoch(train) [44][280/1793] lr: 7.5000e-05 eta: 0:56:31 time: 0.1725 data_time: 0.0068 memory: 10464 grad_norm: 9.5482 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5030 loss: 1.5030 2022/09/07 22:00:22 - mmengine - INFO - Epoch(train) [44][300/1793] lr: 7.5000e-05 eta: 0:56:25 time: 0.1708 data_time: 0.0066 memory: 10464 grad_norm: 9.8448 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1439 loss: 1.1439 2022/09/07 22:00:25 - mmengine - INFO - Epoch(train) [44][320/1793] lr: 7.5000e-05 eta: 0:56:19 time: 0.1800 data_time: 0.0089 memory: 10464 grad_norm: 10.0641 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.2645 loss: 1.2645 2022/09/07 22:00:29 - mmengine - INFO - Epoch(train) [44][340/1793] lr: 7.5000e-05 eta: 0:56:13 time: 0.1765 data_time: 0.0075 memory: 10464 grad_norm: 9.9180 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1781 loss: 1.1781 2022/09/07 22:00:32 - mmengine - INFO - Epoch(train) [44][360/1793] lr: 7.5000e-05 eta: 0:56:08 time: 0.1737 data_time: 0.0073 memory: 10464 grad_norm: 9.5643 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 0.7181 loss: 0.7181 2022/09/07 22:00:36 - mmengine - INFO - Epoch(train) [44][380/1793] lr: 7.5000e-05 eta: 0:56:02 time: 0.1779 data_time: 0.0100 memory: 10464 grad_norm: 9.6031 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1691 loss: 1.1691 2022/09/07 22:00:39 - mmengine - INFO - Epoch(train) [44][400/1793] lr: 7.5000e-05 eta: 0:55:56 time: 0.1722 data_time: 0.0073 memory: 10464 grad_norm: 9.8046 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 0.9070 loss: 0.9070 2022/09/07 22:00:43 - mmengine - INFO - Epoch(train) [44][420/1793] lr: 7.5000e-05 eta: 0:55:50 time: 0.1723 data_time: 0.0068 memory: 10464 grad_norm: 9.9756 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2356 loss: 1.2356 2022/09/07 22:00:46 - mmengine - INFO - Epoch(train) [44][440/1793] lr: 7.5000e-05 eta: 0:55:44 time: 0.1776 data_time: 0.0084 memory: 10464 grad_norm: 9.8065 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2181 loss: 1.2181 2022/09/07 22:00:50 - mmengine - INFO - Epoch(train) [44][460/1793] lr: 7.5000e-05 eta: 0:55:38 time: 0.2065 data_time: 0.0082 memory: 10464 grad_norm: 9.7551 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9079 loss: 0.9079 2022/09/07 22:00:54 - mmengine - INFO - Epoch(train) [44][480/1793] lr: 7.5000e-05 eta: 0:55:33 time: 0.1762 data_time: 0.0072 memory: 10464 grad_norm: 9.8364 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2048 loss: 1.2048 2022/09/07 22:00:57 - mmengine - INFO - Epoch(train) [44][500/1793] lr: 7.5000e-05 eta: 0:55:27 time: 0.1744 data_time: 0.0093 memory: 10464 grad_norm: 9.9355 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1679 loss: 1.1679 2022/09/07 22:01:01 - mmengine - INFO - Epoch(train) [44][520/1793] lr: 7.5000e-05 eta: 0:55:21 time: 0.1713 data_time: 0.0067 memory: 10464 grad_norm: 10.0676 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.0945 loss: 1.0945 2022/09/07 22:01:04 - mmengine - INFO - Epoch(train) [44][540/1793] lr: 7.5000e-05 eta: 0:55:15 time: 0.1728 data_time: 0.0062 memory: 10464 grad_norm: 10.0493 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1294 loss: 1.1294 2022/09/07 22:01:08 - mmengine - INFO - Epoch(train) [44][560/1793] lr: 7.5000e-05 eta: 0:55:09 time: 0.1785 data_time: 0.0088 memory: 10464 grad_norm: 9.8188 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9789 loss: 0.9789 2022/09/07 22:01:11 - mmengine - INFO - Epoch(train) [44][580/1793] lr: 7.5000e-05 eta: 0:55:03 time: 0.1719 data_time: 0.0080 memory: 10464 grad_norm: 9.9385 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9951 loss: 0.9951 2022/09/07 22:01:15 - mmengine - INFO - Epoch(train) [44][600/1793] lr: 7.5000e-05 eta: 0:54:58 time: 0.1849 data_time: 0.0068 memory: 10464 grad_norm: 9.7640 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.0992 loss: 1.0992 2022/09/07 22:01:18 - mmengine - INFO - Epoch(train) [44][620/1793] lr: 7.5000e-05 eta: 0:54:52 time: 0.1753 data_time: 0.0090 memory: 10464 grad_norm: 9.8327 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.2426 loss: 1.2426 2022/09/07 22:01:22 - mmengine - INFO - Epoch(train) [44][640/1793] lr: 7.5000e-05 eta: 0:54:46 time: 0.1710 data_time: 0.0066 memory: 10464 grad_norm: 9.8635 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0326 loss: 1.0326 2022/09/07 22:01:26 - mmengine - INFO - Epoch(train) [44][660/1793] lr: 7.5000e-05 eta: 0:54:40 time: 0.1879 data_time: 0.0083 memory: 10464 grad_norm: 10.1033 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.1167 loss: 1.1167 2022/09/07 22:01:29 - mmengine - INFO - Epoch(train) [44][680/1793] lr: 7.5000e-05 eta: 0:54:34 time: 0.1732 data_time: 0.0095 memory: 10464 grad_norm: 9.4516 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.8048 loss: 0.8048 2022/09/07 22:01:33 - mmengine - INFO - Epoch(train) [44][700/1793] lr: 7.5000e-05 eta: 0:54:29 time: 0.1714 data_time: 0.0063 memory: 10464 grad_norm: 10.0715 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3078 loss: 1.3078 2022/09/07 22:01:36 - mmengine - INFO - Epoch(train) [44][720/1793] lr: 7.5000e-05 eta: 0:54:23 time: 0.1744 data_time: 0.0066 memory: 10464 grad_norm: 9.9453 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0590 loss: 1.0590 2022/09/07 22:01:40 - mmengine - INFO - Epoch(train) [44][740/1793] lr: 7.5000e-05 eta: 0:54:17 time: 0.1902 data_time: 0.0104 memory: 10464 grad_norm: 10.3444 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0535 loss: 1.0535 2022/09/07 22:01:43 - mmengine - INFO - Epoch(train) [44][760/1793] lr: 7.5000e-05 eta: 0:54:11 time: 0.1722 data_time: 0.0072 memory: 10464 grad_norm: 9.9664 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1184 loss: 1.1184 2022/09/07 22:01:47 - mmengine - INFO - Epoch(train) [44][780/1793] lr: 7.5000e-05 eta: 0:54:05 time: 0.1787 data_time: 0.0077 memory: 10464 grad_norm: 9.8087 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1647 loss: 1.1647 2022/09/07 22:01:50 - mmengine - INFO - Epoch(train) [44][800/1793] lr: 7.5000e-05 eta: 0:53:59 time: 0.1749 data_time: 0.0099 memory: 10464 grad_norm: 9.7333 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1575 loss: 1.1575 2022/09/07 22:01:54 - mmengine - INFO - Epoch(train) [44][820/1793] lr: 7.5000e-05 eta: 0:53:54 time: 0.1773 data_time: 0.0078 memory: 10464 grad_norm: 10.0778 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1712 loss: 1.1712 2022/09/07 22:01:58 - mmengine - INFO - Epoch(train) [44][840/1793] lr: 7.5000e-05 eta: 0:53:48 time: 0.1853 data_time: 0.0092 memory: 10464 grad_norm: 9.4045 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.1539 loss: 1.1539 2022/09/07 22:02:01 - mmengine - INFO - Epoch(train) [44][860/1793] lr: 7.5000e-05 eta: 0:53:42 time: 0.1749 data_time: 0.0106 memory: 10464 grad_norm: 9.8380 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.0915 loss: 1.0915 2022/09/07 22:02:05 - mmengine - INFO - Epoch(train) [44][880/1793] lr: 7.5000e-05 eta: 0:53:36 time: 0.1771 data_time: 0.0069 memory: 10464 grad_norm: 9.6343 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 0.9737 loss: 0.9737 2022/09/07 22:02:08 - mmengine - INFO - Epoch(train) [44][900/1793] lr: 7.5000e-05 eta: 0:53:30 time: 0.1727 data_time: 0.0070 memory: 10464 grad_norm: 9.9221 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 0.9111 loss: 0.9111 2022/09/07 22:02:08 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:02:12 - mmengine - INFO - Epoch(train) [44][920/1793] lr: 7.5000e-05 eta: 0:53:25 time: 0.1752 data_time: 0.0101 memory: 10464 grad_norm: 10.1559 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2141 loss: 1.2141 2022/09/07 22:02:15 - mmengine - INFO - Epoch(train) [44][940/1793] lr: 7.5000e-05 eta: 0:53:19 time: 0.1759 data_time: 0.0068 memory: 10464 grad_norm: 9.6686 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.2994 loss: 1.2994 2022/09/07 22:02:19 - mmengine - INFO - Epoch(train) [44][960/1793] lr: 7.5000e-05 eta: 0:53:13 time: 0.1775 data_time: 0.0080 memory: 10464 grad_norm: 9.6588 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1848 loss: 1.1848 2022/09/07 22:02:22 - mmengine - INFO - Epoch(train) [44][980/1793] lr: 7.5000e-05 eta: 0:53:07 time: 0.1763 data_time: 0.0107 memory: 10464 grad_norm: 10.4069 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3001 loss: 1.3001 2022/09/07 22:02:26 - mmengine - INFO - Epoch(train) [44][1000/1793] lr: 7.5000e-05 eta: 0:53:01 time: 0.1722 data_time: 0.0067 memory: 10464 grad_norm: 10.1859 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.1608 loss: 1.1608 2022/09/07 22:02:29 - mmengine - INFO - Epoch(train) [44][1020/1793] lr: 7.5000e-05 eta: 0:52:56 time: 0.1720 data_time: 0.0067 memory: 10464 grad_norm: 9.4174 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.9216 loss: 0.9216 2022/09/07 22:02:33 - mmengine - INFO - Epoch(train) [44][1040/1793] lr: 7.5000e-05 eta: 0:52:50 time: 0.1750 data_time: 0.0107 memory: 10464 grad_norm: 9.8013 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1598 loss: 1.1598 2022/09/07 22:02:36 - mmengine - INFO - Epoch(train) [44][1060/1793] lr: 7.5000e-05 eta: 0:52:44 time: 0.1761 data_time: 0.0072 memory: 10464 grad_norm: 9.6578 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0758 loss: 1.0758 2022/09/07 22:02:40 - mmengine - INFO - Epoch(train) [44][1080/1793] lr: 7.5000e-05 eta: 0:52:38 time: 0.1816 data_time: 0.0090 memory: 10464 grad_norm: 9.6705 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 0.9469 loss: 0.9469 2022/09/07 22:02:43 - mmengine - INFO - Epoch(train) [44][1100/1793] lr: 7.5000e-05 eta: 0:52:32 time: 0.1745 data_time: 0.0096 memory: 10464 grad_norm: 9.9954 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3300 loss: 1.3300 2022/09/07 22:02:47 - mmengine - INFO - Epoch(train) [44][1120/1793] lr: 7.5000e-05 eta: 0:52:27 time: 0.1748 data_time: 0.0074 memory: 10464 grad_norm: 10.1012 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.0978 loss: 1.0978 2022/09/07 22:02:50 - mmengine - INFO - Epoch(train) [44][1140/1793] lr: 7.5000e-05 eta: 0:52:21 time: 0.1724 data_time: 0.0074 memory: 10464 grad_norm: 9.5853 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2080 loss: 1.2080 2022/09/07 22:02:54 - mmengine - INFO - Epoch(train) [44][1160/1793] lr: 7.5000e-05 eta: 0:52:15 time: 0.1760 data_time: 0.0092 memory: 10464 grad_norm: 9.8745 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2929 loss: 1.2929 2022/09/07 22:02:58 - mmengine - INFO - Epoch(train) [44][1180/1793] lr: 7.5000e-05 eta: 0:52:09 time: 0.1932 data_time: 0.0076 memory: 10464 grad_norm: 10.4763 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9011 loss: 0.9011 2022/09/07 22:03:01 - mmengine - INFO - Epoch(train) [44][1200/1793] lr: 7.5000e-05 eta: 0:52:03 time: 0.1715 data_time: 0.0074 memory: 10464 grad_norm: 10.5102 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2557 loss: 1.2557 2022/09/07 22:03:05 - mmengine - INFO - Epoch(train) [44][1220/1793] lr: 7.5000e-05 eta: 0:51:58 time: 0.1807 data_time: 0.0091 memory: 10464 grad_norm: 9.7066 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.1122 loss: 1.1122 2022/09/07 22:03:08 - mmengine - INFO - Epoch(train) [44][1240/1793] lr: 7.5000e-05 eta: 0:51:52 time: 0.1745 data_time: 0.0081 memory: 10464 grad_norm: 10.3317 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.3310 loss: 1.3310 2022/09/07 22:03:12 - mmengine - INFO - Epoch(train) [44][1260/1793] lr: 7.5000e-05 eta: 0:51:46 time: 0.1735 data_time: 0.0078 memory: 10464 grad_norm: 10.1574 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0808 loss: 1.0808 2022/09/07 22:03:15 - mmengine - INFO - Epoch(train) [44][1280/1793] lr: 7.5000e-05 eta: 0:51:40 time: 0.1787 data_time: 0.0092 memory: 10464 grad_norm: 9.6655 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9284 loss: 0.9284 2022/09/07 22:03:19 - mmengine - INFO - Epoch(train) [44][1300/1793] lr: 7.5000e-05 eta: 0:51:35 time: 0.1933 data_time: 0.0080 memory: 10464 grad_norm: 9.9581 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0899 loss: 1.0899 2022/09/07 22:03:23 - mmengine - INFO - Epoch(train) [44][1320/1793] lr: 7.5000e-05 eta: 0:51:29 time: 0.1736 data_time: 0.0072 memory: 10464 grad_norm: 10.3705 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3327 loss: 1.3327 2022/09/07 22:03:26 - mmengine - INFO - Epoch(train) [44][1340/1793] lr: 7.5000e-05 eta: 0:51:23 time: 0.1783 data_time: 0.0100 memory: 10464 grad_norm: 10.1632 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 1.3622 loss: 1.3622 2022/09/07 22:03:30 - mmengine - INFO - Epoch(train) [44][1360/1793] lr: 7.5000e-05 eta: 0:51:17 time: 0.1770 data_time: 0.0073 memory: 10464 grad_norm: 9.6653 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0535 loss: 1.0535 2022/09/07 22:03:33 - mmengine - INFO - Epoch(train) [44][1380/1793] lr: 7.5000e-05 eta: 0:51:11 time: 0.1741 data_time: 0.0068 memory: 10464 grad_norm: 9.6719 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 0.9938 loss: 0.9938 2022/09/07 22:03:37 - mmengine - INFO - Epoch(train) [44][1400/1793] lr: 7.5000e-05 eta: 0:51:06 time: 0.1831 data_time: 0.0115 memory: 10464 grad_norm: 10.5628 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4200 loss: 1.4200 2022/09/07 22:03:40 - mmengine - INFO - Epoch(train) [44][1420/1793] lr: 7.5000e-05 eta: 0:51:00 time: 0.1770 data_time: 0.0082 memory: 10464 grad_norm: 9.6828 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0323 loss: 1.0323 2022/09/07 22:03:44 - mmengine - INFO - Epoch(train) [44][1440/1793] lr: 7.5000e-05 eta: 0:50:54 time: 0.1826 data_time: 0.0068 memory: 10464 grad_norm: 10.1683 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1855 loss: 1.1855 2022/09/07 22:03:48 - mmengine - INFO - Epoch(train) [44][1460/1793] lr: 7.5000e-05 eta: 0:50:48 time: 0.1806 data_time: 0.0113 memory: 10464 grad_norm: 10.1770 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3361 loss: 1.3361 2022/09/07 22:03:51 - mmengine - INFO - Epoch(train) [44][1480/1793] lr: 7.5000e-05 eta: 0:50:43 time: 0.1745 data_time: 0.0069 memory: 10464 grad_norm: 9.4326 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.7876 loss: 0.7876 2022/09/07 22:03:55 - mmengine - INFO - Epoch(train) [44][1500/1793] lr: 7.5000e-05 eta: 0:50:37 time: 0.1732 data_time: 0.0068 memory: 10464 grad_norm: 10.0144 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0909 loss: 1.0909 2022/09/07 22:03:59 - mmengine - INFO - Epoch(train) [44][1520/1793] lr: 7.5000e-05 eta: 0:50:31 time: 0.1925 data_time: 0.0121 memory: 10464 grad_norm: 10.1892 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.3301 loss: 1.3301 2022/09/07 22:04:02 - mmengine - INFO - Epoch(train) [44][1540/1793] lr: 7.5000e-05 eta: 0:50:25 time: 0.1733 data_time: 0.0076 memory: 10464 grad_norm: 10.0040 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1428 loss: 1.1428 2022/09/07 22:04:06 - mmengine - INFO - Epoch(train) [44][1560/1793] lr: 7.5000e-05 eta: 0:50:19 time: 0.1805 data_time: 0.0071 memory: 10464 grad_norm: 10.0198 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1990 loss: 1.1990 2022/09/07 22:04:09 - mmengine - INFO - Epoch(train) [44][1580/1793] lr: 7.5000e-05 eta: 0:50:14 time: 0.1772 data_time: 0.0104 memory: 10464 grad_norm: 10.0448 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.0481 loss: 1.0481 2022/09/07 22:04:13 - mmengine - INFO - Epoch(train) [44][1600/1793] lr: 7.5000e-05 eta: 0:50:08 time: 0.1733 data_time: 0.0072 memory: 10464 grad_norm: 10.1868 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.2703 loss: 1.2703 2022/09/07 22:04:16 - mmengine - INFO - Epoch(train) [44][1620/1793] lr: 7.5000e-05 eta: 0:50:02 time: 0.1762 data_time: 0.0073 memory: 10464 grad_norm: 10.0137 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1385 loss: 1.1385 2022/09/07 22:04:20 - mmengine - INFO - Epoch(train) [44][1640/1793] lr: 7.5000e-05 eta: 0:49:56 time: 0.1935 data_time: 0.0104 memory: 10464 grad_norm: 9.7396 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1793 loss: 1.1793 2022/09/07 22:04:24 - mmengine - INFO - Epoch(train) [44][1660/1793] lr: 7.5000e-05 eta: 0:49:51 time: 0.1710 data_time: 0.0068 memory: 10464 grad_norm: 9.9133 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1230 loss: 1.1230 2022/09/07 22:04:27 - mmengine - INFO - Epoch(train) [44][1680/1793] lr: 7.5000e-05 eta: 0:49:45 time: 0.1864 data_time: 0.0076 memory: 10464 grad_norm: 9.8181 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0869 loss: 1.0869 2022/09/07 22:04:31 - mmengine - INFO - Epoch(train) [44][1700/1793] lr: 7.5000e-05 eta: 0:49:39 time: 0.1752 data_time: 0.0099 memory: 10464 grad_norm: 10.0055 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4916 loss: 1.4916 2022/09/07 22:04:34 - mmengine - INFO - Epoch(train) [44][1720/1793] lr: 7.5000e-05 eta: 0:49:33 time: 0.1743 data_time: 0.0070 memory: 10464 grad_norm: 9.6316 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0863 loss: 1.0863 2022/09/07 22:04:38 - mmengine - INFO - Epoch(train) [44][1740/1793] lr: 7.5000e-05 eta: 0:49:28 time: 0.1743 data_time: 0.0070 memory: 10464 grad_norm: 9.7796 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1457 loss: 1.1457 2022/09/07 22:04:41 - mmengine - INFO - Epoch(train) [44][1760/1793] lr: 7.5000e-05 eta: 0:49:22 time: 0.1757 data_time: 0.0096 memory: 10464 grad_norm: 9.9189 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.0522 loss: 1.0522 2022/09/07 22:04:45 - mmengine - INFO - Epoch(train) [44][1780/1793] lr: 7.5000e-05 eta: 0:49:16 time: 0.1750 data_time: 0.0072 memory: 10464 grad_norm: 9.7243 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1366 loss: 1.1366 2022/09/07 22:04:47 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:04:47 - mmengine - INFO - Epoch(train) [44][1793/1793] lr: 7.5000e-05 eta: 0:49:16 time: 0.1916 data_time: 0.0085 memory: 10464 grad_norm: 10.2358 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 1.4020 loss: 1.4020 2022/09/07 22:04:47 - mmengine - INFO - Saving checkpoint at 44 epochs 2022/09/07 22:04:51 - mmengine - INFO - Epoch(val) [44][20/241] eta: 0:00:12 time: 0.0581 data_time: 0.0089 memory: 1482 2022/09/07 22:04:52 - mmengine - INFO - Epoch(val) [44][40/241] eta: 0:00:10 time: 0.0544 data_time: 0.0056 memory: 1482 2022/09/07 22:04:53 - mmengine - INFO - Epoch(val) [44][60/241] eta: 0:00:09 time: 0.0538 data_time: 0.0054 memory: 1482 2022/09/07 22:04:54 - mmengine - INFO - Epoch(val) [44][80/241] eta: 0:00:08 time: 0.0531 data_time: 0.0045 memory: 1482 2022/09/07 22:04:55 - mmengine - INFO - Epoch(val) [44][100/241] eta: 0:00:07 time: 0.0542 data_time: 0.0053 memory: 1482 2022/09/07 22:04:57 - mmengine - INFO - Epoch(val) [44][120/241] eta: 0:00:06 time: 0.0542 data_time: 0.0055 memory: 1482 2022/09/07 22:04:58 - mmengine - INFO - Epoch(val) [44][140/241] eta: 0:00:05 time: 0.0545 data_time: 0.0059 memory: 1482 2022/09/07 22:04:59 - mmengine - INFO - Epoch(val) [44][160/241] eta: 0:00:04 time: 0.0536 data_time: 0.0052 memory: 1482 2022/09/07 22:05:00 - mmengine - INFO - Epoch(val) [44][180/241] eta: 0:00:03 time: 0.0535 data_time: 0.0050 memory: 1482 2022/09/07 22:05:01 - mmengine - INFO - Epoch(val) [44][200/241] eta: 0:00:02 time: 0.0542 data_time: 0.0055 memory: 1482 2022/09/07 22:05:02 - mmengine - INFO - Epoch(val) [44][220/241] eta: 0:00:01 time: 0.0537 data_time: 0.0051 memory: 1482 2022/09/07 22:05:03 - mmengine - INFO - Epoch(val) [44][240/241] eta: 0:00:00 time: 0.0523 data_time: 0.0044 memory: 1482 2022/09/07 22:05:04 - mmengine - INFO - Epoch(val) [44][241/241] acc/top1: 0.4814 acc/top5: 0.7795 acc/mean1: 0.4451 2022/09/07 22:05:07 - mmengine - INFO - Epoch(train) [45][20/1793] lr: 7.5000e-05 eta: 0:49:06 time: 0.1869 data_time: 0.0127 memory: 10464 grad_norm: 10.0970 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4091 loss: 1.4091 2022/09/07 22:05:11 - mmengine - INFO - Epoch(train) [45][40/1793] lr: 7.5000e-05 eta: 0:49:01 time: 0.1776 data_time: 0.0079 memory: 10464 grad_norm: 9.8619 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.2407 loss: 1.2407 2022/09/07 22:05:15 - mmengine - INFO - Epoch(train) [45][60/1793] lr: 7.5000e-05 eta: 0:48:55 time: 0.1773 data_time: 0.0071 memory: 10464 grad_norm: 10.0673 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1958 loss: 1.1958 2022/09/07 22:05:18 - mmengine - INFO - Epoch(train) [45][80/1793] lr: 7.5000e-05 eta: 0:48:49 time: 0.1788 data_time: 0.0104 memory: 10464 grad_norm: 9.7574 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2590 loss: 1.2590 2022/09/07 22:05:22 - mmengine - INFO - Epoch(train) [45][100/1793] lr: 7.5000e-05 eta: 0:48:43 time: 0.1726 data_time: 0.0069 memory: 10464 grad_norm: 10.1607 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.0235 loss: 1.0235 2022/09/07 22:05:23 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:05:25 - mmengine - INFO - Epoch(train) [45][120/1793] lr: 7.5000e-05 eta: 0:48:38 time: 0.1777 data_time: 0.0071 memory: 10464 grad_norm: 9.8600 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0974 loss: 1.0974 2022/09/07 22:05:29 - mmengine - INFO - Epoch(train) [45][140/1793] lr: 7.5000e-05 eta: 0:48:32 time: 0.1782 data_time: 0.0098 memory: 10464 grad_norm: 9.9085 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9453 loss: 0.9453 2022/09/07 22:05:32 - mmengine - INFO - Epoch(train) [45][160/1793] lr: 7.5000e-05 eta: 0:48:26 time: 0.1730 data_time: 0.0070 memory: 10464 grad_norm: 9.8853 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.2727 loss: 1.2727 2022/09/07 22:05:36 - mmengine - INFO - Epoch(train) [45][180/1793] lr: 7.5000e-05 eta: 0:48:20 time: 0.1784 data_time: 0.0069 memory: 10464 grad_norm: 9.2972 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0299 loss: 1.0299 2022/09/07 22:05:40 - mmengine - INFO - Epoch(train) [45][200/1793] lr: 7.5000e-05 eta: 0:48:15 time: 0.1977 data_time: 0.0110 memory: 10464 grad_norm: 10.1045 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2919 loss: 1.2919 2022/09/07 22:05:43 - mmengine - INFO - Epoch(train) [45][220/1793] lr: 7.5000e-05 eta: 0:48:09 time: 0.1747 data_time: 0.0074 memory: 10464 grad_norm: 10.2993 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3414 loss: 1.3414 2022/09/07 22:05:47 - mmengine - INFO - Epoch(train) [45][240/1793] lr: 7.5000e-05 eta: 0:48:03 time: 0.1768 data_time: 0.0070 memory: 10464 grad_norm: 10.2945 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3185 loss: 1.3185 2022/09/07 22:05:50 - mmengine - INFO - Epoch(train) [45][260/1793] lr: 7.5000e-05 eta: 0:47:57 time: 0.1771 data_time: 0.0097 memory: 10464 grad_norm: 10.3191 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0897 loss: 1.0897 2022/09/07 22:05:54 - mmengine - INFO - Epoch(train) [45][280/1793] lr: 7.5000e-05 eta: 0:47:52 time: 0.1732 data_time: 0.0071 memory: 10464 grad_norm: 10.1303 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2748 loss: 1.2748 2022/09/07 22:05:57 - mmengine - INFO - Epoch(train) [45][300/1793] lr: 7.5000e-05 eta: 0:47:46 time: 0.1862 data_time: 0.0090 memory: 10464 grad_norm: 10.3523 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0510 loss: 1.0510 2022/09/07 22:06:01 - mmengine - INFO - Epoch(train) [45][320/1793] lr: 7.5000e-05 eta: 0:47:40 time: 0.1770 data_time: 0.0103 memory: 10464 grad_norm: 9.9070 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 0.9871 loss: 0.9871 2022/09/07 22:06:05 - mmengine - INFO - Epoch(train) [45][340/1793] lr: 7.5000e-05 eta: 0:47:34 time: 0.1748 data_time: 0.0069 memory: 10464 grad_norm: 9.9256 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.2484 loss: 1.2484 2022/09/07 22:06:08 - mmengine - INFO - Epoch(train) [45][360/1793] lr: 7.5000e-05 eta: 0:47:29 time: 0.1746 data_time: 0.0082 memory: 10464 grad_norm: 9.6379 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0333 loss: 1.0333 2022/09/07 22:06:12 - mmengine - INFO - Epoch(train) [45][380/1793] lr: 7.5000e-05 eta: 0:47:23 time: 0.1791 data_time: 0.0100 memory: 10464 grad_norm: 10.2403 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0762 loss: 1.0762 2022/09/07 22:06:15 - mmengine - INFO - Epoch(train) [45][400/1793] lr: 7.5000e-05 eta: 0:47:17 time: 0.1793 data_time: 0.0069 memory: 10464 grad_norm: 10.0852 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 1.2550 loss: 1.2550 2022/09/07 22:06:19 - mmengine - INFO - Epoch(train) [45][420/1793] lr: 7.5000e-05 eta: 0:47:12 time: 0.1861 data_time: 0.0098 memory: 10464 grad_norm: 10.3355 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3122 loss: 1.3122 2022/09/07 22:06:22 - mmengine - INFO - Epoch(train) [45][440/1793] lr: 7.5000e-05 eta: 0:47:06 time: 0.1776 data_time: 0.0097 memory: 10464 grad_norm: 9.6460 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3362 loss: 1.3362 2022/09/07 22:06:26 - mmengine - INFO - Epoch(train) [45][460/1793] lr: 7.5000e-05 eta: 0:47:00 time: 0.1765 data_time: 0.0070 memory: 10464 grad_norm: 9.9034 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0725 loss: 1.0725 2022/09/07 22:06:30 - mmengine - INFO - Epoch(train) [45][480/1793] lr: 7.5000e-05 eta: 0:46:54 time: 0.1751 data_time: 0.0076 memory: 10464 grad_norm: 9.5743 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2951 loss: 1.2951 2022/09/07 22:06:33 - mmengine - INFO - Epoch(train) [45][500/1793] lr: 7.5000e-05 eta: 0:46:49 time: 0.1741 data_time: 0.0098 memory: 10464 grad_norm: 9.9969 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0051 loss: 1.0051 2022/09/07 22:06:37 - mmengine - INFO - Epoch(train) [45][520/1793] lr: 7.5000e-05 eta: 0:46:43 time: 0.1761 data_time: 0.0071 memory: 10464 grad_norm: 9.8221 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4079 loss: 1.4079 2022/09/07 22:06:40 - mmengine - INFO - Epoch(train) [45][540/1793] lr: 7.5000e-05 eta: 0:46:37 time: 0.1743 data_time: 0.0074 memory: 10464 grad_norm: 9.7662 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9949 loss: 0.9949 2022/09/07 22:06:44 - mmengine - INFO - Epoch(train) [45][560/1793] lr: 7.5000e-05 eta: 0:46:31 time: 0.1750 data_time: 0.0093 memory: 10464 grad_norm: 9.9298 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9311 loss: 0.9311 2022/09/07 22:06:47 - mmengine - INFO - Epoch(train) [45][580/1793] lr: 7.5000e-05 eta: 0:46:26 time: 0.1771 data_time: 0.0075 memory: 10464 grad_norm: 9.7398 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2121 loss: 1.2121 2022/09/07 22:06:51 - mmengine - INFO - Epoch(train) [45][600/1793] lr: 7.5000e-05 eta: 0:46:20 time: 0.1727 data_time: 0.0070 memory: 10464 grad_norm: 9.8445 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1050 loss: 1.1050 2022/09/07 22:06:54 - mmengine - INFO - Epoch(train) [45][620/1793] lr: 7.5000e-05 eta: 0:46:14 time: 0.1756 data_time: 0.0105 memory: 10464 grad_norm: 10.0352 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2235 loss: 1.2235 2022/09/07 22:06:58 - mmengine - INFO - Epoch(train) [45][640/1793] lr: 7.5000e-05 eta: 0:46:09 time: 0.1890 data_time: 0.0087 memory: 10464 grad_norm: 10.2182 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.2383 loss: 1.2383 2022/09/07 22:07:01 - mmengine - INFO - Epoch(train) [45][660/1793] lr: 7.5000e-05 eta: 0:46:03 time: 0.1715 data_time: 0.0070 memory: 10464 grad_norm: 9.9332 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0330 loss: 1.0330 2022/09/07 22:07:05 - mmengine - INFO - Epoch(train) [45][680/1793] lr: 7.5000e-05 eta: 0:45:57 time: 0.1788 data_time: 0.0103 memory: 10464 grad_norm: 9.6152 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0159 loss: 1.0159 2022/09/07 22:07:08 - mmengine - INFO - Epoch(train) [45][700/1793] lr: 7.5000e-05 eta: 0:45:51 time: 0.1759 data_time: 0.0078 memory: 10464 grad_norm: 9.7093 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.1147 loss: 1.1147 2022/09/07 22:07:12 - mmengine - INFO - Epoch(train) [45][720/1793] lr: 7.5000e-05 eta: 0:45:46 time: 0.1738 data_time: 0.0072 memory: 10464 grad_norm: 10.2183 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.3622 loss: 1.3622 2022/09/07 22:07:15 - mmengine - INFO - Epoch(train) [45][740/1793] lr: 7.5000e-05 eta: 0:45:40 time: 0.1805 data_time: 0.0096 memory: 10464 grad_norm: 9.5019 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.2794 loss: 1.2794 2022/09/07 22:07:19 - mmengine - INFO - Epoch(train) [45][760/1793] lr: 7.5000e-05 eta: 0:45:34 time: 0.1756 data_time: 0.0076 memory: 10464 grad_norm: 9.6186 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9692 loss: 0.9692 2022/09/07 22:07:22 - mmengine - INFO - Epoch(train) [45][780/1793] lr: 7.5000e-05 eta: 0:45:29 time: 0.1738 data_time: 0.0076 memory: 10464 grad_norm: 10.1222 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9252 loss: 0.9252 2022/09/07 22:07:26 - mmengine - INFO - Epoch(train) [45][800/1793] lr: 7.5000e-05 eta: 0:45:23 time: 0.1830 data_time: 0.0100 memory: 10464 grad_norm: 9.9983 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0847 loss: 1.0847 2022/09/07 22:07:30 - mmengine - INFO - Epoch(train) [45][820/1793] lr: 7.5000e-05 eta: 0:45:17 time: 0.1784 data_time: 0.0079 memory: 10464 grad_norm: 9.6525 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1940 loss: 1.1940 2022/09/07 22:07:33 - mmengine - INFO - Epoch(train) [45][840/1793] lr: 7.5000e-05 eta: 0:45:11 time: 0.1733 data_time: 0.0073 memory: 10464 grad_norm: 9.7403 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0653 loss: 1.0653 2022/09/07 22:07:37 - mmengine - INFO - Epoch(train) [45][860/1793] lr: 7.5000e-05 eta: 0:45:06 time: 0.1757 data_time: 0.0097 memory: 10464 grad_norm: 9.7904 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1812 loss: 1.1812 2022/09/07 22:07:40 - mmengine - INFO - Epoch(train) [45][880/1793] lr: 7.5000e-05 eta: 0:45:00 time: 0.1777 data_time: 0.0073 memory: 10464 grad_norm: 9.3388 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1240 loss: 1.1240 2022/09/07 22:07:44 - mmengine - INFO - Epoch(train) [45][900/1793] lr: 7.5000e-05 eta: 0:44:54 time: 0.1760 data_time: 0.0071 memory: 10464 grad_norm: 10.2440 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.2116 loss: 1.2116 2022/09/07 22:07:47 - mmengine - INFO - Epoch(train) [45][920/1793] lr: 7.5000e-05 eta: 0:44:49 time: 0.1765 data_time: 0.0100 memory: 10464 grad_norm: 10.0525 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0423 loss: 1.0423 2022/09/07 22:07:51 - mmengine - INFO - Epoch(train) [45][940/1793] lr: 7.5000e-05 eta: 0:44:43 time: 0.1738 data_time: 0.0071 memory: 10464 grad_norm: 9.7292 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0972 loss: 1.0972 2022/09/07 22:07:54 - mmengine - INFO - Epoch(train) [45][960/1793] lr: 7.5000e-05 eta: 0:44:37 time: 0.1755 data_time: 0.0078 memory: 10464 grad_norm: 9.9940 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.0675 loss: 1.0675 2022/09/07 22:07:58 - mmengine - INFO - Epoch(train) [45][980/1793] lr: 7.5000e-05 eta: 0:44:32 time: 0.2027 data_time: 0.0095 memory: 10464 grad_norm: 9.9292 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2152 loss: 1.2152 2022/09/07 22:08:02 - mmengine - INFO - Epoch(train) [45][1000/1793] lr: 7.5000e-05 eta: 0:44:26 time: 0.1709 data_time: 0.0068 memory: 10464 grad_norm: 9.9516 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9760 loss: 0.9760 2022/09/07 22:08:05 - mmengine - INFO - Epoch(train) [45][1020/1793] lr: 7.5000e-05 eta: 0:44:20 time: 0.1736 data_time: 0.0071 memory: 10464 grad_norm: 9.6865 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 0.7622 loss: 0.7622 2022/09/07 22:08:09 - mmengine - INFO - Epoch(train) [45][1040/1793] lr: 7.5000e-05 eta: 0:44:14 time: 0.1861 data_time: 0.0099 memory: 10464 grad_norm: 9.8895 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.9651 loss: 0.9651 2022/09/07 22:08:13 - mmengine - INFO - Epoch(train) [45][1060/1793] lr: 7.5000e-05 eta: 0:44:09 time: 0.1757 data_time: 0.0077 memory: 10464 grad_norm: 9.6797 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0911 loss: 1.0911 2022/09/07 22:08:16 - mmengine - INFO - Epoch(train) [45][1080/1793] lr: 7.5000e-05 eta: 0:44:03 time: 0.1750 data_time: 0.0074 memory: 10464 grad_norm: 10.4978 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1780 loss: 1.1780 2022/09/07 22:08:20 - mmengine - INFO - Epoch(train) [45][1100/1793] lr: 7.5000e-05 eta: 0:43:57 time: 0.1742 data_time: 0.0091 memory: 10464 grad_norm: 9.8952 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2405 loss: 1.2405 2022/09/07 22:08:21 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:08:23 - mmengine - INFO - Epoch(train) [45][1120/1793] lr: 7.5000e-05 eta: 0:43:52 time: 0.1734 data_time: 0.0073 memory: 10464 grad_norm: 10.2017 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0569 loss: 1.0569 2022/09/07 22:08:26 - mmengine - INFO - Epoch(train) [45][1140/1793] lr: 7.5000e-05 eta: 0:43:46 time: 0.1748 data_time: 0.0071 memory: 10464 grad_norm: 10.3305 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4152 loss: 1.4152 2022/09/07 22:08:30 - mmengine - INFO - Epoch(train) [45][1160/1793] lr: 7.5000e-05 eta: 0:43:40 time: 0.1799 data_time: 0.0104 memory: 10464 grad_norm: 10.2943 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1778 loss: 1.1778 2022/09/07 22:08:34 - mmengine - INFO - Epoch(train) [45][1180/1793] lr: 7.5000e-05 eta: 0:43:35 time: 0.1738 data_time: 0.0073 memory: 10464 grad_norm: 9.9138 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 0.9854 loss: 0.9854 2022/09/07 22:08:37 - mmengine - INFO - Epoch(train) [45][1200/1793] lr: 7.5000e-05 eta: 0:43:29 time: 0.1807 data_time: 0.0068 memory: 10464 grad_norm: 10.1146 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3674 loss: 1.3674 2022/09/07 22:08:41 - mmengine - INFO - Epoch(train) [45][1220/1793] lr: 7.5000e-05 eta: 0:43:23 time: 0.1807 data_time: 0.0106 memory: 10464 grad_norm: 9.7851 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.0303 loss: 1.0303 2022/09/07 22:08:44 - mmengine - INFO - Epoch(train) [45][1240/1793] lr: 7.5000e-05 eta: 0:43:17 time: 0.1733 data_time: 0.0071 memory: 10464 grad_norm: 9.8992 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0740 loss: 1.0740 2022/09/07 22:08:48 - mmengine - INFO - Epoch(train) [45][1260/1793] lr: 7.5000e-05 eta: 0:43:12 time: 0.1921 data_time: 0.0082 memory: 10464 grad_norm: 9.4414 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.8328 loss: 0.8328 2022/09/07 22:08:52 - mmengine - INFO - Epoch(train) [45][1280/1793] lr: 7.5000e-05 eta: 0:43:06 time: 0.1775 data_time: 0.0102 memory: 10464 grad_norm: 9.6756 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2093 loss: 1.2093 2022/09/07 22:08:55 - mmengine - INFO - Epoch(train) [45][1300/1793] lr: 7.5000e-05 eta: 0:43:00 time: 0.1790 data_time: 0.0070 memory: 10464 grad_norm: 10.1435 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0417 loss: 1.0417 2022/09/07 22:08:59 - mmengine - INFO - Epoch(train) [45][1320/1793] lr: 7.5000e-05 eta: 0:42:55 time: 0.1758 data_time: 0.0079 memory: 10464 grad_norm: 10.2139 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0160 loss: 1.0160 2022/09/07 22:09:02 - mmengine - INFO - Epoch(train) [45][1340/1793] lr: 7.5000e-05 eta: 0:42:49 time: 0.1749 data_time: 0.0088 memory: 10464 grad_norm: 9.8447 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.2720 loss: 1.2720 2022/09/07 22:09:06 - mmengine - INFO - Epoch(train) [45][1360/1793] lr: 7.5000e-05 eta: 0:42:43 time: 0.1758 data_time: 0.0069 memory: 10464 grad_norm: 9.8147 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 0.9344 loss: 0.9344 2022/09/07 22:09:09 - mmengine - INFO - Epoch(train) [45][1380/1793] lr: 7.5000e-05 eta: 0:42:38 time: 0.1780 data_time: 0.0081 memory: 10464 grad_norm: 10.2205 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 0.9833 loss: 0.9833 2022/09/07 22:09:13 - mmengine - INFO - Epoch(train) [45][1400/1793] lr: 7.5000e-05 eta: 0:42:32 time: 0.1763 data_time: 0.0094 memory: 10464 grad_norm: 9.8803 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4154 loss: 1.4154 2022/09/07 22:09:16 - mmengine - INFO - Epoch(train) [45][1420/1793] lr: 7.5000e-05 eta: 0:42:26 time: 0.1761 data_time: 0.0072 memory: 10464 grad_norm: 10.1812 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.3557 loss: 1.3557 2022/09/07 22:09:20 - mmengine - INFO - Epoch(train) [45][1440/1793] lr: 7.5000e-05 eta: 0:42:21 time: 0.1752 data_time: 0.0082 memory: 10464 grad_norm: 10.4541 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3031 loss: 1.3031 2022/09/07 22:09:24 - mmengine - INFO - Epoch(train) [45][1460/1793] lr: 7.5000e-05 eta: 0:42:15 time: 0.1778 data_time: 0.0087 memory: 10464 grad_norm: 9.7380 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0785 loss: 1.0785 2022/09/07 22:09:27 - mmengine - INFO - Epoch(train) [45][1480/1793] lr: 7.5000e-05 eta: 0:42:09 time: 0.1797 data_time: 0.0071 memory: 10464 grad_norm: 10.2744 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2489 loss: 1.2489 2022/09/07 22:09:31 - mmengine - INFO - Epoch(train) [45][1500/1793] lr: 7.5000e-05 eta: 0:42:04 time: 0.1810 data_time: 0.0077 memory: 10464 grad_norm: 10.1315 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2854 loss: 1.2854 2022/09/07 22:09:34 - mmengine - INFO - Epoch(train) [45][1520/1793] lr: 7.5000e-05 eta: 0:41:58 time: 0.1805 data_time: 0.0092 memory: 10464 grad_norm: 9.9879 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1967 loss: 1.1967 2022/09/07 22:09:38 - mmengine - INFO - Epoch(train) [45][1540/1793] lr: 7.5000e-05 eta: 0:41:52 time: 0.1778 data_time: 0.0075 memory: 10464 grad_norm: 10.2324 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.0239 loss: 1.0239 2022/09/07 22:09:41 - mmengine - INFO - Epoch(train) [45][1560/1793] lr: 7.5000e-05 eta: 0:41:47 time: 0.1759 data_time: 0.0078 memory: 10464 grad_norm: 9.7364 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2518 loss: 1.2518 2022/09/07 22:09:45 - mmengine - INFO - Epoch(train) [45][1580/1793] lr: 7.5000e-05 eta: 0:41:41 time: 0.1786 data_time: 0.0092 memory: 10464 grad_norm: 10.1866 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0774 loss: 1.0774 2022/09/07 22:09:49 - mmengine - INFO - Epoch(train) [45][1600/1793] lr: 7.5000e-05 eta: 0:41:35 time: 0.1828 data_time: 0.0076 memory: 10464 grad_norm: 9.7729 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0372 loss: 1.0372 2022/09/07 22:09:52 - mmengine - INFO - Epoch(train) [45][1620/1793] lr: 7.5000e-05 eta: 0:41:30 time: 0.1757 data_time: 0.0072 memory: 10464 grad_norm: 9.8421 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1209 loss: 1.1209 2022/09/07 22:09:56 - mmengine - INFO - Epoch(train) [45][1640/1793] lr: 7.5000e-05 eta: 0:41:24 time: 0.1803 data_time: 0.0103 memory: 10464 grad_norm: 9.4346 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.1327 loss: 1.1327 2022/09/07 22:09:59 - mmengine - INFO - Epoch(train) [45][1660/1793] lr: 7.5000e-05 eta: 0:41:18 time: 0.1763 data_time: 0.0071 memory: 10464 grad_norm: 10.1706 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1192 loss: 1.1192 2022/09/07 22:10:03 - mmengine - INFO - Epoch(train) [45][1680/1793] lr: 7.5000e-05 eta: 0:41:13 time: 0.1760 data_time: 0.0070 memory: 10464 grad_norm: 10.1693 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1487 loss: 1.1487 2022/09/07 22:10:06 - mmengine - INFO - Epoch(train) [45][1700/1793] lr: 7.5000e-05 eta: 0:41:07 time: 0.1805 data_time: 0.0102 memory: 10464 grad_norm: 9.8452 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9757 loss: 0.9757 2022/09/07 22:10:10 - mmengine - INFO - Epoch(train) [45][1720/1793] lr: 7.5000e-05 eta: 0:41:01 time: 0.1772 data_time: 0.0076 memory: 10464 grad_norm: 9.9978 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1076 loss: 1.1076 2022/09/07 22:10:14 - mmengine - INFO - Epoch(train) [45][1740/1793] lr: 7.5000e-05 eta: 0:40:56 time: 0.1762 data_time: 0.0072 memory: 10464 grad_norm: 9.7078 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4868 loss: 1.4868 2022/09/07 22:10:17 - mmengine - INFO - Epoch(train) [45][1760/1793] lr: 7.5000e-05 eta: 0:40:50 time: 0.1819 data_time: 0.0088 memory: 10464 grad_norm: 9.8100 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1206 loss: 1.1206 2022/09/07 22:10:21 - mmengine - INFO - Epoch(train) [45][1780/1793] lr: 7.5000e-05 eta: 0:40:44 time: 0.1767 data_time: 0.0073 memory: 10464 grad_norm: 9.7829 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0201 loss: 1.0201 2022/09/07 22:10:23 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:10:23 - mmengine - INFO - Epoch(train) [45][1793/1793] lr: 7.5000e-05 eta: 0:40:44 time: 0.1718 data_time: 0.0076 memory: 10464 grad_norm: 10.5719 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1178 loss: 1.1178 2022/09/07 22:10:23 - mmengine - INFO - Saving checkpoint at 45 epochs 2022/09/07 22:10:26 - mmengine - INFO - Epoch(val) [45][20/241] eta: 0:00:13 time: 0.0599 data_time: 0.0101 memory: 1482 2022/09/07 22:10:28 - mmengine - INFO - Epoch(val) [45][40/241] eta: 0:00:10 time: 0.0538 data_time: 0.0051 memory: 1482 2022/09/07 22:10:29 - mmengine - INFO - Epoch(val) [45][60/241] eta: 0:00:09 time: 0.0538 data_time: 0.0050 memory: 1482 2022/09/07 22:10:30 - mmengine - INFO - Epoch(val) [45][80/241] eta: 0:00:08 time: 0.0541 data_time: 0.0053 memory: 1482 2022/09/07 22:10:31 - mmengine - INFO - Epoch(val) [45][100/241] eta: 0:00:08 time: 0.0602 data_time: 0.0117 memory: 1482 2022/09/07 22:10:32 - mmengine - INFO - Epoch(val) [45][120/241] eta: 0:00:06 time: 0.0531 data_time: 0.0046 memory: 1482 2022/09/07 22:10:33 - mmengine - INFO - Epoch(val) [45][140/241] eta: 0:00:05 time: 0.0538 data_time: 0.0051 memory: 1482 2022/09/07 22:10:34 - mmengine - INFO - Epoch(val) [45][160/241] eta: 0:00:04 time: 0.0536 data_time: 0.0050 memory: 1482 2022/09/07 22:10:35 - mmengine - INFO - Epoch(val) [45][180/241] eta: 0:00:03 time: 0.0536 data_time: 0.0050 memory: 1482 2022/09/07 22:10:36 - mmengine - INFO - Epoch(val) [45][200/241] eta: 0:00:02 time: 0.0531 data_time: 0.0048 memory: 1482 2022/09/07 22:10:37 - mmengine - INFO - Epoch(val) [45][220/241] eta: 0:00:01 time: 0.0545 data_time: 0.0050 memory: 1482 2022/09/07 22:10:39 - mmengine - INFO - Epoch(val) [45][240/241] eta: 0:00:00 time: 0.0580 data_time: 0.0067 memory: 1482 2022/09/07 22:10:39 - mmengine - INFO - Epoch(val) [45][241/241] acc/top1: 0.4760 acc/top5: 0.7789 acc/mean1: 0.4427 2022/09/07 22:10:43 - mmengine - INFO - Epoch(train) [46][20/1793] lr: 7.5000e-06 eta: 0:40:35 time: 0.1828 data_time: 0.0130 memory: 10464 grad_norm: 10.3184 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.1961 loss: 1.1961 2022/09/07 22:10:46 - mmengine - INFO - Epoch(train) [46][40/1793] lr: 7.5000e-06 eta: 0:40:29 time: 0.1747 data_time: 0.0073 memory: 10464 grad_norm: 10.0276 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9900 loss: 0.9900 2022/09/07 22:10:50 - mmengine - INFO - Epoch(train) [46][60/1793] lr: 7.5000e-06 eta: 0:40:24 time: 0.1774 data_time: 0.0076 memory: 10464 grad_norm: 9.6513 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2855 loss: 1.2855 2022/09/07 22:10:53 - mmengine - INFO - Epoch(train) [46][80/1793] lr: 7.5000e-06 eta: 0:40:18 time: 0.1760 data_time: 0.0103 memory: 10464 grad_norm: 10.0801 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2961 loss: 1.2961 2022/09/07 22:10:58 - mmengine - INFO - Epoch(train) [46][100/1793] lr: 7.5000e-06 eta: 0:40:12 time: 0.2073 data_time: 0.0078 memory: 10464 grad_norm: 10.0487 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3922 loss: 1.3922 2022/09/07 22:11:01 - mmengine - INFO - Epoch(train) [46][120/1793] lr: 7.5000e-06 eta: 0:40:07 time: 0.1738 data_time: 0.0080 memory: 10464 grad_norm: 10.1314 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1014 loss: 1.1014 2022/09/07 22:11:05 - mmengine - INFO - Epoch(train) [46][140/1793] lr: 7.5000e-06 eta: 0:40:01 time: 0.1768 data_time: 0.0110 memory: 10464 grad_norm: 10.0888 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.8160 loss: 0.8160 2022/09/07 22:11:08 - mmengine - INFO - Epoch(train) [46][160/1793] lr: 7.5000e-06 eta: 0:39:55 time: 0.1757 data_time: 0.0073 memory: 10464 grad_norm: 10.2018 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0523 loss: 1.0523 2022/09/07 22:11:12 - mmengine - INFO - Epoch(train) [46][180/1793] lr: 7.5000e-06 eta: 0:39:50 time: 0.1737 data_time: 0.0076 memory: 10464 grad_norm: 10.0668 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0538 loss: 1.0538 2022/09/07 22:11:15 - mmengine - INFO - Epoch(train) [46][200/1793] lr: 7.5000e-06 eta: 0:39:44 time: 0.1834 data_time: 0.0093 memory: 10464 grad_norm: 10.1340 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1576 loss: 1.1576 2022/09/07 22:11:19 - mmengine - INFO - Epoch(train) [46][220/1793] lr: 7.5000e-06 eta: 0:39:38 time: 0.1835 data_time: 0.0087 memory: 10464 grad_norm: 9.9039 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9373 loss: 0.9373 2022/09/07 22:11:22 - mmengine - INFO - Epoch(train) [46][240/1793] lr: 7.5000e-06 eta: 0:39:33 time: 0.1724 data_time: 0.0074 memory: 10464 grad_norm: 10.1865 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3131 loss: 1.3131 2022/09/07 22:11:26 - mmengine - INFO - Epoch(train) [46][260/1793] lr: 7.5000e-06 eta: 0:39:27 time: 0.1844 data_time: 0.0089 memory: 10464 grad_norm: 9.2938 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2127 loss: 1.2127 2022/09/07 22:11:30 - mmengine - INFO - Epoch(train) [46][280/1793] lr: 7.5000e-06 eta: 0:39:21 time: 0.1757 data_time: 0.0071 memory: 10464 grad_norm: 10.1232 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9328 loss: 0.9328 2022/09/07 22:11:33 - mmengine - INFO - Epoch(train) [46][300/1793] lr: 7.5000e-06 eta: 0:39:16 time: 0.1752 data_time: 0.0074 memory: 10464 grad_norm: 9.6651 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.1389 loss: 1.1389 2022/09/07 22:11:36 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:11:37 - mmengine - INFO - Epoch(train) [46][320/1793] lr: 7.5000e-06 eta: 0:39:10 time: 0.1818 data_time: 0.0088 memory: 10464 grad_norm: 9.7691 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 0.9401 loss: 0.9401 2022/09/07 22:11:40 - mmengine - INFO - Epoch(train) [46][340/1793] lr: 7.5000e-06 eta: 0:39:05 time: 0.1824 data_time: 0.0076 memory: 10464 grad_norm: 10.1688 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 0.9242 loss: 0.9242 2022/09/07 22:11:44 - mmengine - INFO - Epoch(train) [46][360/1793] lr: 7.5000e-06 eta: 0:38:59 time: 0.1752 data_time: 0.0073 memory: 10464 grad_norm: 9.9735 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1562 loss: 1.1562 2022/09/07 22:11:48 - mmengine - INFO - Epoch(train) [46][380/1793] lr: 7.5000e-06 eta: 0:38:53 time: 0.1828 data_time: 0.0104 memory: 10464 grad_norm: 9.9474 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1016 loss: 1.1016 2022/09/07 22:11:51 - mmengine - INFO - Epoch(train) [46][400/1793] lr: 7.5000e-06 eta: 0:38:48 time: 0.1738 data_time: 0.0075 memory: 10464 grad_norm: 9.6284 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3049 loss: 1.3049 2022/09/07 22:11:55 - mmengine - INFO - Epoch(train) [46][420/1793] lr: 7.5000e-06 eta: 0:38:42 time: 0.1750 data_time: 0.0066 memory: 10464 grad_norm: 9.9159 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1699 loss: 1.1699 2022/09/07 22:11:59 - mmengine - INFO - Epoch(train) [46][440/1793] lr: 7.5000e-06 eta: 0:38:36 time: 0.1992 data_time: 0.0105 memory: 10464 grad_norm: 10.0512 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4024 loss: 1.4024 2022/09/07 22:12:02 - mmengine - INFO - Epoch(train) [46][460/1793] lr: 7.5000e-06 eta: 0:38:31 time: 0.1730 data_time: 0.0073 memory: 10464 grad_norm: 9.9079 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 0.8968 loss: 0.8968 2022/09/07 22:12:06 - mmengine - INFO - Epoch(train) [46][480/1793] lr: 7.5000e-06 eta: 0:38:25 time: 0.1801 data_time: 0.0067 memory: 10464 grad_norm: 9.7362 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8781 loss: 0.8781 2022/09/07 22:12:09 - mmengine - INFO - Epoch(train) [46][500/1793] lr: 7.5000e-06 eta: 0:38:20 time: 0.1787 data_time: 0.0111 memory: 10464 grad_norm: 10.0538 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0142 loss: 1.0142 2022/09/07 22:12:13 - mmengine - INFO - Epoch(train) [46][520/1793] lr: 7.5000e-06 eta: 0:38:14 time: 0.1734 data_time: 0.0070 memory: 10464 grad_norm: 9.9323 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0645 loss: 1.0645 2022/09/07 22:12:16 - mmengine - INFO - Epoch(train) [46][540/1793] lr: 7.5000e-06 eta: 0:38:08 time: 0.1762 data_time: 0.0078 memory: 10464 grad_norm: 9.3688 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1922 loss: 1.1922 2022/09/07 22:12:20 - mmengine - INFO - Epoch(train) [46][560/1793] lr: 7.5000e-06 eta: 0:38:03 time: 0.1814 data_time: 0.0111 memory: 10464 grad_norm: 10.1164 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2115 loss: 1.2115 2022/09/07 22:12:23 - mmengine - INFO - Epoch(train) [46][580/1793] lr: 7.5000e-06 eta: 0:37:57 time: 0.1729 data_time: 0.0067 memory: 10464 grad_norm: 10.1165 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.1455 loss: 1.1455 2022/09/07 22:12:27 - mmengine - INFO - Epoch(train) [46][600/1793] lr: 7.5000e-06 eta: 0:37:51 time: 0.1756 data_time: 0.0078 memory: 10464 grad_norm: 9.6503 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 0.9586 loss: 0.9586 2022/09/07 22:12:31 - mmengine - INFO - Epoch(train) [46][620/1793] lr: 7.5000e-06 eta: 0:37:46 time: 0.1818 data_time: 0.0103 memory: 10464 grad_norm: 9.7730 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.8932 loss: 0.8932 2022/09/07 22:12:34 - mmengine - INFO - Epoch(train) [46][640/1793] lr: 7.5000e-06 eta: 0:37:40 time: 0.1741 data_time: 0.0074 memory: 10464 grad_norm: 9.8565 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9365 loss: 0.9365 2022/09/07 22:12:38 - mmengine - INFO - Epoch(train) [46][660/1793] lr: 7.5000e-06 eta: 0:37:34 time: 0.1833 data_time: 0.0075 memory: 10464 grad_norm: 10.2359 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2876 loss: 1.2876 2022/09/07 22:12:41 - mmengine - INFO - Epoch(train) [46][680/1793] lr: 7.5000e-06 eta: 0:37:29 time: 0.1772 data_time: 0.0094 memory: 10464 grad_norm: 9.9841 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1519 loss: 1.1519 2022/09/07 22:12:45 - mmengine - INFO - Epoch(train) [46][700/1793] lr: 7.5000e-06 eta: 0:37:23 time: 0.1743 data_time: 0.0073 memory: 10464 grad_norm: 10.1708 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0184 loss: 1.0184 2022/09/07 22:12:48 - mmengine - INFO - Epoch(train) [46][720/1793] lr: 7.5000e-06 eta: 0:37:18 time: 0.1790 data_time: 0.0072 memory: 10464 grad_norm: 10.0768 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0901 loss: 1.0901 2022/09/07 22:12:52 - mmengine - INFO - Epoch(train) [46][740/1793] lr: 7.5000e-06 eta: 0:37:12 time: 0.1764 data_time: 0.0103 memory: 10464 grad_norm: 9.9941 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.9767 loss: 0.9767 2022/09/07 22:12:55 - mmengine - INFO - Epoch(train) [46][760/1793] lr: 7.5000e-06 eta: 0:37:06 time: 0.1792 data_time: 0.0078 memory: 10464 grad_norm: 9.7004 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9889 loss: 0.9889 2022/09/07 22:12:59 - mmengine - INFO - Epoch(train) [46][780/1793] lr: 7.5000e-06 eta: 0:37:01 time: 0.1780 data_time: 0.0079 memory: 10464 grad_norm: 10.0640 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9143 loss: 0.9143 2022/09/07 22:13:03 - mmengine - INFO - Epoch(train) [46][800/1793] lr: 7.5000e-06 eta: 0:36:55 time: 0.1778 data_time: 0.0106 memory: 10464 grad_norm: 10.0844 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3415 loss: 1.3415 2022/09/07 22:13:06 - mmengine - INFO - Epoch(train) [46][820/1793] lr: 7.5000e-06 eta: 0:36:50 time: 0.1759 data_time: 0.0068 memory: 10464 grad_norm: 10.1911 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2303 loss: 1.2303 2022/09/07 22:13:10 - mmengine - INFO - Epoch(train) [46][840/1793] lr: 7.5000e-06 eta: 0:36:44 time: 0.1804 data_time: 0.0076 memory: 10464 grad_norm: 9.8938 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2868 loss: 1.2868 2022/09/07 22:13:13 - mmengine - INFO - Epoch(train) [46][860/1793] lr: 7.5000e-06 eta: 0:36:38 time: 0.1769 data_time: 0.0102 memory: 10464 grad_norm: 9.6611 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.2774 loss: 1.2774 2022/09/07 22:13:17 - mmengine - INFO - Epoch(train) [46][880/1793] lr: 7.5000e-06 eta: 0:36:33 time: 0.1786 data_time: 0.0070 memory: 10464 grad_norm: 9.8515 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1965 loss: 1.1965 2022/09/07 22:13:20 - mmengine - INFO - Epoch(train) [46][900/1793] lr: 7.5000e-06 eta: 0:36:27 time: 0.1775 data_time: 0.0067 memory: 10464 grad_norm: 10.3380 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1036 loss: 1.1036 2022/09/07 22:13:24 - mmengine - INFO - Epoch(train) [46][920/1793] lr: 7.5000e-06 eta: 0:36:21 time: 0.1779 data_time: 0.0108 memory: 10464 grad_norm: 9.7278 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4244 loss: 1.4244 2022/09/07 22:13:28 - mmengine - INFO - Epoch(train) [46][940/1793] lr: 7.5000e-06 eta: 0:36:16 time: 0.1850 data_time: 0.0070 memory: 10464 grad_norm: 9.8176 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.8701 loss: 0.8701 2022/09/07 22:13:31 - mmengine - INFO - Epoch(train) [46][960/1793] lr: 7.5000e-06 eta: 0:36:10 time: 0.1784 data_time: 0.0076 memory: 10464 grad_norm: 10.3189 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2713 loss: 1.2713 2022/09/07 22:13:35 - mmengine - INFO - Epoch(train) [46][980/1793] lr: 7.5000e-06 eta: 0:36:05 time: 0.1781 data_time: 0.0111 memory: 10464 grad_norm: 10.1372 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.4397 loss: 1.4397 2022/09/07 22:13:39 - mmengine - INFO - Epoch(train) [46][1000/1793] lr: 7.5000e-06 eta: 0:35:59 time: 0.1914 data_time: 0.0071 memory: 10464 grad_norm: 9.9435 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1807 loss: 1.1807 2022/09/07 22:13:42 - mmengine - INFO - Epoch(train) [46][1020/1793] lr: 7.5000e-06 eta: 0:35:54 time: 0.1749 data_time: 0.0071 memory: 10464 grad_norm: 10.2692 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1146 loss: 1.1146 2022/09/07 22:13:46 - mmengine - INFO - Epoch(train) [46][1040/1793] lr: 7.5000e-06 eta: 0:35:48 time: 0.1796 data_time: 0.0093 memory: 10464 grad_norm: 10.1781 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.1310 loss: 1.1310 2022/09/07 22:13:49 - mmengine - INFO - Epoch(train) [46][1060/1793] lr: 7.5000e-06 eta: 0:35:42 time: 0.1811 data_time: 0.0092 memory: 10464 grad_norm: 9.8536 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1669 loss: 1.1669 2022/09/07 22:13:53 - mmengine - INFO - Epoch(train) [46][1080/1793] lr: 7.5000e-06 eta: 0:35:37 time: 0.1781 data_time: 0.0076 memory: 10464 grad_norm: 10.1969 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1898 loss: 1.1898 2022/09/07 22:13:57 - mmengine - INFO - Epoch(train) [46][1100/1793] lr: 7.5000e-06 eta: 0:35:31 time: 0.1796 data_time: 0.0092 memory: 10464 grad_norm: 9.7855 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1425 loss: 1.1425 2022/09/07 22:14:00 - mmengine - INFO - Epoch(train) [46][1120/1793] lr: 7.5000e-06 eta: 0:35:26 time: 0.1818 data_time: 0.0094 memory: 10464 grad_norm: 9.6545 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.2407 loss: 1.2407 2022/09/07 22:14:04 - mmengine - INFO - Epoch(train) [46][1140/1793] lr: 7.5000e-06 eta: 0:35:20 time: 0.1768 data_time: 0.0080 memory: 10464 grad_norm: 10.4197 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9962 loss: 0.9962 2022/09/07 22:14:07 - mmengine - INFO - Epoch(train) [46][1160/1793] lr: 7.5000e-06 eta: 0:35:14 time: 0.1765 data_time: 0.0093 memory: 10464 grad_norm: 9.7020 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1015 loss: 1.1015 2022/09/07 22:14:11 - mmengine - INFO - Epoch(train) [46][1180/1793] lr: 7.5000e-06 eta: 0:35:09 time: 0.1746 data_time: 0.0076 memory: 10464 grad_norm: 10.3011 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0473 loss: 1.0473 2022/09/07 22:14:14 - mmengine - INFO - Epoch(train) [46][1200/1793] lr: 7.5000e-06 eta: 0:35:03 time: 0.1745 data_time: 0.0074 memory: 10464 grad_norm: 10.0489 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.0724 loss: 1.0724 2022/09/07 22:14:18 - mmengine - INFO - Epoch(train) [46][1220/1793] lr: 7.5000e-06 eta: 0:34:58 time: 0.1859 data_time: 0.0092 memory: 10464 grad_norm: 10.2393 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.0630 loss: 1.0630 2022/09/07 22:14:21 - mmengine - INFO - Epoch(train) [46][1240/1793] lr: 7.5000e-06 eta: 0:34:52 time: 0.1743 data_time: 0.0070 memory: 10464 grad_norm: 10.2988 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1489 loss: 1.1489 2022/09/07 22:14:25 - mmengine - INFO - Epoch(train) [46][1260/1793] lr: 7.5000e-06 eta: 0:34:46 time: 0.1763 data_time: 0.0072 memory: 10464 grad_norm: 10.1722 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1712 loss: 1.1712 2022/09/07 22:14:29 - mmengine - INFO - Epoch(train) [46][1280/1793] lr: 7.5000e-06 eta: 0:34:41 time: 0.1818 data_time: 0.0111 memory: 10464 grad_norm: 9.7423 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2309 loss: 1.2309 2022/09/07 22:14:32 - mmengine - INFO - Epoch(train) [46][1300/1793] lr: 7.5000e-06 eta: 0:34:35 time: 0.1768 data_time: 0.0078 memory: 10464 grad_norm: 9.9190 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9172 loss: 0.9172 2022/09/07 22:14:35 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:14:36 - mmengine - INFO - Epoch(train) [46][1320/1793] lr: 7.5000e-06 eta: 0:34:30 time: 0.1807 data_time: 0.0073 memory: 10464 grad_norm: 10.1071 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4247 loss: 1.4247 2022/09/07 22:14:39 - mmengine - INFO - Epoch(train) [46][1340/1793] lr: 7.5000e-06 eta: 0:34:24 time: 0.1825 data_time: 0.0105 memory: 10464 grad_norm: 9.5628 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1921 loss: 1.1921 2022/09/07 22:14:43 - mmengine - INFO - Epoch(train) [46][1360/1793] lr: 7.5000e-06 eta: 0:34:18 time: 0.1743 data_time: 0.0077 memory: 10464 grad_norm: 9.7906 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.1856 loss: 1.1856 2022/09/07 22:14:46 - mmengine - INFO - Epoch(train) [46][1380/1793] lr: 7.5000e-06 eta: 0:34:13 time: 0.1754 data_time: 0.0069 memory: 10464 grad_norm: 10.2616 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3028 loss: 1.3028 2022/09/07 22:14:50 - mmengine - INFO - Epoch(train) [46][1400/1793] lr: 7.5000e-06 eta: 0:34:07 time: 0.1821 data_time: 0.0117 memory: 10464 grad_norm: 9.7657 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0722 loss: 1.0722 2022/09/07 22:14:54 - mmengine - INFO - Epoch(train) [46][1420/1793] lr: 7.5000e-06 eta: 0:34:02 time: 0.1774 data_time: 0.0071 memory: 10464 grad_norm: 10.4510 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1628 loss: 1.1628 2022/09/07 22:14:57 - mmengine - INFO - Epoch(train) [46][1440/1793] lr: 7.5000e-06 eta: 0:33:56 time: 0.1766 data_time: 0.0083 memory: 10464 grad_norm: 10.1816 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1619 loss: 1.1619 2022/09/07 22:15:01 - mmengine - INFO - Epoch(train) [46][1460/1793] lr: 7.5000e-06 eta: 0:33:50 time: 0.1783 data_time: 0.0090 memory: 10464 grad_norm: 10.1123 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4722 loss: 1.4722 2022/09/07 22:15:04 - mmengine - INFO - Epoch(train) [46][1480/1793] lr: 7.5000e-06 eta: 0:33:45 time: 0.1748 data_time: 0.0069 memory: 10464 grad_norm: 9.4501 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1408 loss: 1.1408 2022/09/07 22:15:08 - mmengine - INFO - Epoch(train) [46][1500/1793] lr: 7.5000e-06 eta: 0:33:39 time: 0.1849 data_time: 0.0075 memory: 10464 grad_norm: 9.7751 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.9340 loss: 0.9340 2022/09/07 22:15:12 - mmengine - INFO - Epoch(train) [46][1520/1793] lr: 7.5000e-06 eta: 0:33:34 time: 0.1792 data_time: 0.0097 memory: 10464 grad_norm: 10.0814 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0420 loss: 1.0420 2022/09/07 22:15:15 - mmengine - INFO - Epoch(train) [46][1540/1793] lr: 7.5000e-06 eta: 0:33:28 time: 0.1744 data_time: 0.0075 memory: 10464 grad_norm: 9.7942 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1015 loss: 1.1015 2022/09/07 22:15:19 - mmengine - INFO - Epoch(train) [46][1560/1793] lr: 7.5000e-06 eta: 0:33:23 time: 0.1980 data_time: 0.0090 memory: 10464 grad_norm: 10.1229 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.9566 loss: 0.9566 2022/09/07 22:15:23 - mmengine - INFO - Epoch(train) [46][1580/1793] lr: 7.5000e-06 eta: 0:33:17 time: 0.1822 data_time: 0.0093 memory: 10464 grad_norm: 9.9014 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1465 loss: 1.1465 2022/09/07 22:15:26 - mmengine - INFO - Epoch(train) [46][1600/1793] lr: 7.5000e-06 eta: 0:33:11 time: 0.1780 data_time: 0.0067 memory: 10464 grad_norm: 9.7294 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0609 loss: 1.0609 2022/09/07 22:15:30 - mmengine - INFO - Epoch(train) [46][1620/1793] lr: 7.5000e-06 eta: 0:33:06 time: 0.1794 data_time: 0.0082 memory: 10464 grad_norm: 10.0381 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3882 loss: 1.3882 2022/09/07 22:15:33 - mmengine - INFO - Epoch(train) [46][1640/1793] lr: 7.5000e-06 eta: 0:33:00 time: 0.1772 data_time: 0.0093 memory: 10464 grad_norm: 9.7504 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.1288 loss: 1.1288 2022/09/07 22:15:37 - mmengine - INFO - Epoch(train) [46][1660/1793] lr: 7.5000e-06 eta: 0:32:55 time: 0.1786 data_time: 0.0070 memory: 10464 grad_norm: 10.0530 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1026 loss: 1.1026 2022/09/07 22:15:41 - mmengine - INFO - Epoch(train) [46][1680/1793] lr: 7.5000e-06 eta: 0:32:49 time: 0.1768 data_time: 0.0073 memory: 10464 grad_norm: 9.9845 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0283 loss: 1.0283 2022/09/07 22:15:44 - mmengine - INFO - Epoch(train) [46][1700/1793] lr: 7.5000e-06 eta: 0:32:44 time: 0.1822 data_time: 0.0105 memory: 10464 grad_norm: 9.9156 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1990 loss: 1.1990 2022/09/07 22:15:48 - mmengine - INFO - Epoch(train) [46][1720/1793] lr: 7.5000e-06 eta: 0:32:38 time: 0.1782 data_time: 0.0070 memory: 10464 grad_norm: 9.6116 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1269 loss: 1.1269 2022/09/07 22:15:51 - mmengine - INFO - Epoch(train) [46][1740/1793] lr: 7.5000e-06 eta: 0:32:32 time: 0.1801 data_time: 0.0076 memory: 10464 grad_norm: 9.5316 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.0239 loss: 1.0239 2022/09/07 22:15:55 - mmengine - INFO - Epoch(train) [46][1760/1793] lr: 7.5000e-06 eta: 0:32:27 time: 0.1770 data_time: 0.0099 memory: 10464 grad_norm: 10.0340 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2310 loss: 1.2310 2022/09/07 22:15:59 - mmengine - INFO - Epoch(train) [46][1780/1793] lr: 7.5000e-06 eta: 0:32:21 time: 0.1832 data_time: 0.0085 memory: 10464 grad_norm: 10.2569 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2387 loss: 1.2387 2022/09/07 22:16:01 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:16:01 - mmengine - INFO - Epoch(train) [46][1793/1793] lr: 7.5000e-06 eta: 0:32:21 time: 0.1722 data_time: 0.0070 memory: 10464 grad_norm: 10.7571 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 1.1636 loss: 1.1636 2022/09/07 22:16:01 - mmengine - INFO - Saving checkpoint at 46 epochs 2022/09/07 22:16:04 - mmengine - INFO - Epoch(val) [46][20/241] eta: 0:00:13 time: 0.0589 data_time: 0.0097 memory: 1482 2022/09/07 22:16:06 - mmengine - INFO - Epoch(val) [46][40/241] eta: 0:00:10 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 22:16:07 - mmengine - INFO - Epoch(val) [46][60/241] eta: 0:00:09 time: 0.0536 data_time: 0.0051 memory: 1482 2022/09/07 22:16:08 - mmengine - INFO - Epoch(val) [46][80/241] eta: 0:00:08 time: 0.0545 data_time: 0.0058 memory: 1482 2022/09/07 22:16:09 - mmengine - INFO - Epoch(val) [46][100/241] eta: 0:00:07 time: 0.0535 data_time: 0.0051 memory: 1482 2022/09/07 22:16:10 - mmengine - INFO - Epoch(val) [46][120/241] eta: 0:00:06 time: 0.0543 data_time: 0.0057 memory: 1482 2022/09/07 22:16:11 - mmengine - INFO - Epoch(val) [46][140/241] eta: 0:00:05 time: 0.0539 data_time: 0.0054 memory: 1482 2022/09/07 22:16:12 - mmengine - INFO - Epoch(val) [46][160/241] eta: 0:00:04 time: 0.0536 data_time: 0.0051 memory: 1482 2022/09/07 22:16:13 - mmengine - INFO - Epoch(val) [46][180/241] eta: 0:00:03 time: 0.0535 data_time: 0.0050 memory: 1482 2022/09/07 22:16:14 - mmengine - INFO - Epoch(val) [46][200/241] eta: 0:00:02 time: 0.0534 data_time: 0.0050 memory: 1482 2022/09/07 22:16:15 - mmengine - INFO - Epoch(val) [46][220/241] eta: 0:00:01 time: 0.0531 data_time: 0.0048 memory: 1482 2022/09/07 22:16:16 - mmengine - INFO - Epoch(val) [46][240/241] eta: 0:00:00 time: 0.0529 data_time: 0.0050 memory: 1482 2022/09/07 22:16:17 - mmengine - INFO - Epoch(val) [46][241/241] acc/top1: 0.4784 acc/top5: 0.7785 acc/mean1: 0.4412 2022/09/07 22:16:21 - mmengine - INFO - Epoch(train) [47][20/1793] lr: 7.5000e-06 eta: 0:32:12 time: 0.2044 data_time: 0.0125 memory: 10464 grad_norm: 9.4530 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0675 loss: 1.0675 2022/09/07 22:16:24 - mmengine - INFO - Epoch(train) [47][40/1793] lr: 7.5000e-06 eta: 0:32:06 time: 0.1724 data_time: 0.0073 memory: 10464 grad_norm: 10.2407 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.4236 loss: 1.4236 2022/09/07 22:16:28 - mmengine - INFO - Epoch(train) [47][60/1793] lr: 7.5000e-06 eta: 0:32:01 time: 0.1878 data_time: 0.0098 memory: 10464 grad_norm: 10.1393 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2095 loss: 1.2095 2022/09/07 22:16:32 - mmengine - INFO - Epoch(train) [47][80/1793] lr: 7.5000e-06 eta: 0:31:55 time: 0.1783 data_time: 0.0101 memory: 10464 grad_norm: 10.0914 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4333 loss: 1.4333 2022/09/07 22:16:35 - mmengine - INFO - Epoch(train) [47][100/1793] lr: 7.5000e-06 eta: 0:31:50 time: 0.1804 data_time: 0.0068 memory: 10464 grad_norm: 10.0601 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2298 loss: 1.2298 2022/09/07 22:16:39 - mmengine - INFO - Epoch(train) [47][120/1793] lr: 7.5000e-06 eta: 0:31:44 time: 0.1761 data_time: 0.0073 memory: 10464 grad_norm: 10.2059 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0930 loss: 1.0930 2022/09/07 22:16:42 - mmengine - INFO - Epoch(train) [47][140/1793] lr: 7.5000e-06 eta: 0:31:39 time: 0.1750 data_time: 0.0093 memory: 10464 grad_norm: 9.8322 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9776 loss: 0.9776 2022/09/07 22:16:46 - mmengine - INFO - Epoch(train) [47][160/1793] lr: 7.5000e-06 eta: 0:31:33 time: 0.1734 data_time: 0.0070 memory: 10464 grad_norm: 9.8253 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2525 loss: 1.2525 2022/09/07 22:16:50 - mmengine - INFO - Epoch(train) [47][180/1793] lr: 7.5000e-06 eta: 0:31:28 time: 0.1793 data_time: 0.0080 memory: 10464 grad_norm: 9.9916 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 0.8904 loss: 0.8904 2022/09/07 22:16:53 - mmengine - INFO - Epoch(train) [47][200/1793] lr: 7.5000e-06 eta: 0:31:22 time: 0.1773 data_time: 0.0094 memory: 10464 grad_norm: 9.9766 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.4544 loss: 1.4544 2022/09/07 22:16:57 - mmengine - INFO - Epoch(train) [47][220/1793] lr: 7.5000e-06 eta: 0:31:16 time: 0.1844 data_time: 0.0074 memory: 10464 grad_norm: 9.8510 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 0.9277 loss: 0.9277 2022/09/07 22:17:00 - mmengine - INFO - Epoch(train) [47][240/1793] lr: 7.5000e-06 eta: 0:31:11 time: 0.1767 data_time: 0.0082 memory: 10464 grad_norm: 10.2598 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2809 loss: 1.2809 2022/09/07 22:17:04 - mmengine - INFO - Epoch(train) [47][260/1793] lr: 7.5000e-06 eta: 0:31:05 time: 0.1745 data_time: 0.0092 memory: 10464 grad_norm: 9.9692 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2207 loss: 1.2207 2022/09/07 22:17:07 - mmengine - INFO - Epoch(train) [47][280/1793] lr: 7.5000e-06 eta: 0:31:00 time: 0.1743 data_time: 0.0069 memory: 10464 grad_norm: 10.0085 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1782 loss: 1.1782 2022/09/07 22:17:11 - mmengine - INFO - Epoch(train) [47][300/1793] lr: 7.5000e-06 eta: 0:30:54 time: 0.1755 data_time: 0.0073 memory: 10464 grad_norm: 9.6055 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0090 loss: 1.0090 2022/09/07 22:17:14 - mmengine - INFO - Epoch(train) [47][320/1793] lr: 7.5000e-06 eta: 0:30:49 time: 0.1759 data_time: 0.0107 memory: 10464 grad_norm: 10.2038 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0829 loss: 1.0829 2022/09/07 22:17:18 - mmengine - INFO - Epoch(train) [47][340/1793] lr: 7.5000e-06 eta: 0:30:43 time: 0.1987 data_time: 0.0078 memory: 10464 grad_norm: 10.0893 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9679 loss: 0.9679 2022/09/07 22:17:22 - mmengine - INFO - Epoch(train) [47][360/1793] lr: 7.5000e-06 eta: 0:30:38 time: 0.1728 data_time: 0.0067 memory: 10464 grad_norm: 10.1850 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1695 loss: 1.1695 2022/09/07 22:17:25 - mmengine - INFO - Epoch(train) [47][380/1793] lr: 7.5000e-06 eta: 0:30:32 time: 0.1759 data_time: 0.0094 memory: 10464 grad_norm: 10.1668 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3350 loss: 1.3350 2022/09/07 22:17:29 - mmengine - INFO - Epoch(train) [47][400/1793] lr: 7.5000e-06 eta: 0:30:27 time: 0.1844 data_time: 0.0083 memory: 10464 grad_norm: 10.1911 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.0907 loss: 1.0907 2022/09/07 22:17:32 - mmengine - INFO - Epoch(train) [47][420/1793] lr: 7.5000e-06 eta: 0:30:21 time: 0.1756 data_time: 0.0069 memory: 10464 grad_norm: 10.4162 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3228 loss: 1.3228 2022/09/07 22:17:36 - mmengine - INFO - Epoch(train) [47][440/1793] lr: 7.5000e-06 eta: 0:30:15 time: 0.1969 data_time: 0.0106 memory: 10464 grad_norm: 9.9590 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 0.8854 loss: 0.8854 2022/09/07 22:17:40 - mmengine - INFO - Epoch(train) [47][460/1793] lr: 7.5000e-06 eta: 0:30:10 time: 0.1768 data_time: 0.0071 memory: 10464 grad_norm: 10.0377 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3352 loss: 1.3352 2022/09/07 22:17:43 - mmengine - INFO - Epoch(train) [47][480/1793] lr: 7.5000e-06 eta: 0:30:04 time: 0.1753 data_time: 0.0068 memory: 10464 grad_norm: 10.4310 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0794 loss: 1.0794 2022/09/07 22:17:47 - mmengine - INFO - Epoch(train) [47][500/1793] lr: 7.5000e-06 eta: 0:29:59 time: 0.1796 data_time: 0.0105 memory: 10464 grad_norm: 9.8942 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 1.3666 loss: 1.3666 2022/09/07 22:17:51 - mmengine - INFO - Epoch(train) [47][520/1793] lr: 7.5000e-06 eta: 0:29:53 time: 0.1811 data_time: 0.0079 memory: 10464 grad_norm: 10.0350 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2936 loss: 1.2936 2022/09/07 22:17:51 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:17:54 - mmengine - INFO - Epoch(train) [47][540/1793] lr: 7.5000e-06 eta: 0:29:48 time: 0.1743 data_time: 0.0068 memory: 10464 grad_norm: 9.9289 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0119 loss: 1.0119 2022/09/07 22:17:58 - mmengine - INFO - Epoch(train) [47][560/1793] lr: 7.5000e-06 eta: 0:29:42 time: 0.1816 data_time: 0.0099 memory: 10464 grad_norm: 9.8109 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2197 loss: 1.2197 2022/09/07 22:18:01 - mmengine - INFO - Epoch(train) [47][580/1793] lr: 7.5000e-06 eta: 0:29:37 time: 0.1775 data_time: 0.0079 memory: 10464 grad_norm: 9.8857 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5197 loss: 1.5197 2022/09/07 22:18:05 - mmengine - INFO - Epoch(train) [47][600/1793] lr: 7.5000e-06 eta: 0:29:31 time: 0.1773 data_time: 0.0075 memory: 10464 grad_norm: 9.9775 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2200 loss: 1.2200 2022/09/07 22:18:09 - mmengine - INFO - Epoch(train) [47][620/1793] lr: 7.5000e-06 eta: 0:29:26 time: 0.1836 data_time: 0.0112 memory: 10464 grad_norm: 9.9034 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 0.8663 loss: 0.8663 2022/09/07 22:18:12 - mmengine - INFO - Epoch(train) [47][640/1793] lr: 7.5000e-06 eta: 0:29:20 time: 0.1738 data_time: 0.0071 memory: 10464 grad_norm: 9.9250 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0710 loss: 1.0710 2022/09/07 22:18:16 - mmengine - INFO - Epoch(train) [47][660/1793] lr: 7.5000e-06 eta: 0:29:15 time: 0.1840 data_time: 0.0075 memory: 10464 grad_norm: 9.7392 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1336 loss: 1.1336 2022/09/07 22:18:19 - mmengine - INFO - Epoch(train) [47][680/1793] lr: 7.5000e-06 eta: 0:29:09 time: 0.1780 data_time: 0.0097 memory: 10464 grad_norm: 10.4758 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0506 loss: 1.0506 2022/09/07 22:18:23 - mmengine - INFO - Epoch(train) [47][700/1793] lr: 7.5000e-06 eta: 0:29:03 time: 0.1739 data_time: 0.0069 memory: 10464 grad_norm: 10.0853 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 1.2577 loss: 1.2577 2022/09/07 22:18:27 - mmengine - INFO - Epoch(train) [47][720/1793] lr: 7.5000e-06 eta: 0:28:58 time: 0.1828 data_time: 0.0068 memory: 10464 grad_norm: 9.7029 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2284 loss: 1.2284 2022/09/07 22:18:30 - mmengine - INFO - Epoch(train) [47][740/1793] lr: 7.5000e-06 eta: 0:28:52 time: 0.1807 data_time: 0.0101 memory: 10464 grad_norm: 10.2049 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.8929 loss: 0.8929 2022/09/07 22:18:34 - mmengine - INFO - Epoch(train) [47][760/1793] lr: 7.5000e-06 eta: 0:28:47 time: 0.1784 data_time: 0.0075 memory: 10464 grad_norm: 10.2251 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2870 loss: 1.2870 2022/09/07 22:18:37 - mmengine - INFO - Epoch(train) [47][780/1793] lr: 7.5000e-06 eta: 0:28:41 time: 0.1799 data_time: 0.0071 memory: 10464 grad_norm: 9.8402 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0952 loss: 1.0952 2022/09/07 22:18:41 - mmengine - INFO - Epoch(train) [47][800/1793] lr: 7.5000e-06 eta: 0:28:36 time: 0.1810 data_time: 0.0098 memory: 10464 grad_norm: 9.9215 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2639 loss: 1.2639 2022/09/07 22:18:45 - mmengine - INFO - Epoch(train) [47][820/1793] lr: 7.5000e-06 eta: 0:28:30 time: 0.1822 data_time: 0.0077 memory: 10464 grad_norm: 9.4949 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1189 loss: 1.1189 2022/09/07 22:18:48 - mmengine - INFO - Epoch(train) [47][840/1793] lr: 7.5000e-06 eta: 0:28:25 time: 0.1800 data_time: 0.0070 memory: 10464 grad_norm: 10.0981 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1831 loss: 1.1831 2022/09/07 22:18:52 - mmengine - INFO - Epoch(train) [47][860/1793] lr: 7.5000e-06 eta: 0:28:19 time: 0.1769 data_time: 0.0096 memory: 10464 grad_norm: 10.0441 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0582 loss: 1.0582 2022/09/07 22:18:55 - mmengine - INFO - Epoch(train) [47][880/1793] lr: 7.5000e-06 eta: 0:28:14 time: 0.1761 data_time: 0.0069 memory: 10464 grad_norm: 9.6754 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1259 loss: 1.1259 2022/09/07 22:18:59 - mmengine - INFO - Epoch(train) [47][900/1793] lr: 7.5000e-06 eta: 0:28:08 time: 0.1839 data_time: 0.0070 memory: 10464 grad_norm: 9.8026 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.3129 loss: 1.3129 2022/09/07 22:19:02 - mmengine - INFO - Epoch(train) [47][920/1793] lr: 7.5000e-06 eta: 0:28:03 time: 0.1762 data_time: 0.0100 memory: 10464 grad_norm: 9.8601 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0631 loss: 1.0631 2022/09/07 22:19:06 - mmengine - INFO - Epoch(train) [47][940/1793] lr: 7.5000e-06 eta: 0:27:57 time: 0.1776 data_time: 0.0070 memory: 10464 grad_norm: 9.7204 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1084 loss: 1.1084 2022/09/07 22:19:10 - mmengine - INFO - Epoch(train) [47][960/1793] lr: 7.5000e-06 eta: 0:27:52 time: 0.1953 data_time: 0.0094 memory: 10464 grad_norm: 10.3135 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1441 loss: 1.1441 2022/09/07 22:19:14 - mmengine - INFO - Epoch(train) [47][980/1793] lr: 7.5000e-06 eta: 0:27:46 time: 0.1823 data_time: 0.0102 memory: 10464 grad_norm: 9.9309 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 0.9052 loss: 0.9052 2022/09/07 22:19:17 - mmengine - INFO - Epoch(train) [47][1000/1793] lr: 7.5000e-06 eta: 0:27:41 time: 0.1797 data_time: 0.0069 memory: 10464 grad_norm: 10.1279 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2495 loss: 1.2495 2022/09/07 22:19:21 - mmengine - INFO - Epoch(train) [47][1020/1793] lr: 7.5000e-06 eta: 0:27:35 time: 0.1829 data_time: 0.0071 memory: 10464 grad_norm: 9.6417 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1012 loss: 1.1012 2022/09/07 22:19:24 - mmengine - INFO - Epoch(train) [47][1040/1793] lr: 7.5000e-06 eta: 0:27:30 time: 0.1766 data_time: 0.0089 memory: 10464 grad_norm: 10.1581 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0289 loss: 1.0289 2022/09/07 22:19:28 - mmengine - INFO - Epoch(train) [47][1060/1793] lr: 7.5000e-06 eta: 0:27:24 time: 0.1805 data_time: 0.0071 memory: 10464 grad_norm: 9.7849 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0697 loss: 1.0697 2022/09/07 22:19:32 - mmengine - INFO - Epoch(train) [47][1080/1793] lr: 7.5000e-06 eta: 0:27:19 time: 0.1782 data_time: 0.0084 memory: 10464 grad_norm: 10.4765 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1561 loss: 1.1561 2022/09/07 22:19:35 - mmengine - INFO - Epoch(train) [47][1100/1793] lr: 7.5000e-06 eta: 0:27:13 time: 0.1802 data_time: 0.0099 memory: 10464 grad_norm: 10.2918 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0717 loss: 1.0717 2022/09/07 22:19:39 - mmengine - INFO - Epoch(train) [47][1120/1793] lr: 7.5000e-06 eta: 0:27:08 time: 0.1812 data_time: 0.0071 memory: 10464 grad_norm: 9.9836 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1617 loss: 1.1617 2022/09/07 22:19:42 - mmengine - INFO - Epoch(train) [47][1140/1793] lr: 7.5000e-06 eta: 0:27:02 time: 0.1750 data_time: 0.0075 memory: 10464 grad_norm: 9.8391 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.2056 loss: 1.2056 2022/09/07 22:19:46 - mmengine - INFO - Epoch(train) [47][1160/1793] lr: 7.5000e-06 eta: 0:26:57 time: 0.1794 data_time: 0.0099 memory: 10464 grad_norm: 9.7392 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1893 loss: 1.1893 2022/09/07 22:19:49 - mmengine - INFO - Epoch(train) [47][1180/1793] lr: 7.5000e-06 eta: 0:26:51 time: 0.1753 data_time: 0.0076 memory: 10464 grad_norm: 10.5523 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2068 loss: 1.2068 2022/09/07 22:19:53 - mmengine - INFO - Epoch(train) [47][1200/1793] lr: 7.5000e-06 eta: 0:26:46 time: 0.1777 data_time: 0.0069 memory: 10464 grad_norm: 9.4763 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1775 loss: 1.1775 2022/09/07 22:19:57 - mmengine - INFO - Epoch(train) [47][1220/1793] lr: 7.5000e-06 eta: 0:26:40 time: 0.1834 data_time: 0.0091 memory: 10464 grad_norm: 10.4108 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5327 loss: 1.5327 2022/09/07 22:20:00 - mmengine - INFO - Epoch(train) [47][1240/1793] lr: 7.5000e-06 eta: 0:26:35 time: 0.1780 data_time: 0.0068 memory: 10464 grad_norm: 9.9594 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2201 loss: 1.2201 2022/09/07 22:20:04 - mmengine - INFO - Epoch(train) [47][1260/1793] lr: 7.5000e-06 eta: 0:26:29 time: 0.1793 data_time: 0.0084 memory: 10464 grad_norm: 10.1501 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 0.9747 loss: 0.9747 2022/09/07 22:20:07 - mmengine - INFO - Epoch(train) [47][1280/1793] lr: 7.5000e-06 eta: 0:26:24 time: 0.1807 data_time: 0.0091 memory: 10464 grad_norm: 9.7551 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1615 loss: 1.1615 2022/09/07 22:20:11 - mmengine - INFO - Epoch(train) [47][1300/1793] lr: 7.5000e-06 eta: 0:26:18 time: 0.1777 data_time: 0.0078 memory: 10464 grad_norm: 10.0833 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2398 loss: 1.2398 2022/09/07 22:20:15 - mmengine - INFO - Epoch(train) [47][1320/1793] lr: 7.5000e-06 eta: 0:26:13 time: 0.1762 data_time: 0.0069 memory: 10464 grad_norm: 9.5179 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0313 loss: 1.0313 2022/09/07 22:20:18 - mmengine - INFO - Epoch(train) [47][1340/1793] lr: 7.5000e-06 eta: 0:26:07 time: 0.1796 data_time: 0.0090 memory: 10464 grad_norm: 10.0841 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0119 loss: 1.0119 2022/09/07 22:20:22 - mmengine - INFO - Epoch(train) [47][1360/1793] lr: 7.5000e-06 eta: 0:26:02 time: 0.1786 data_time: 0.0080 memory: 10464 grad_norm: 9.7377 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2525 loss: 1.2525 2022/09/07 22:20:25 - mmengine - INFO - Epoch(train) [47][1380/1793] lr: 7.5000e-06 eta: 0:25:56 time: 0.1785 data_time: 0.0072 memory: 10464 grad_norm: 9.9754 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2112 loss: 1.2112 2022/09/07 22:20:29 - mmengine - INFO - Epoch(train) [47][1400/1793] lr: 7.5000e-06 eta: 0:25:51 time: 0.1840 data_time: 0.0095 memory: 10464 grad_norm: 10.1035 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0442 loss: 1.0442 2022/09/07 22:20:32 - mmengine - INFO - Epoch(train) [47][1420/1793] lr: 7.5000e-06 eta: 0:25:45 time: 0.1763 data_time: 0.0078 memory: 10464 grad_norm: 9.8687 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.0964 loss: 1.0964 2022/09/07 22:20:36 - mmengine - INFO - Epoch(train) [47][1440/1793] lr: 7.5000e-06 eta: 0:25:40 time: 0.1769 data_time: 0.0067 memory: 10464 grad_norm: 9.5392 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1602 loss: 1.1602 2022/09/07 22:20:40 - mmengine - INFO - Epoch(train) [47][1460/1793] lr: 7.5000e-06 eta: 0:25:34 time: 0.1833 data_time: 0.0106 memory: 10464 grad_norm: 9.9037 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2785 loss: 1.2785 2022/09/07 22:20:43 - mmengine - INFO - Epoch(train) [47][1480/1793] lr: 7.5000e-06 eta: 0:25:29 time: 0.1787 data_time: 0.0069 memory: 10464 grad_norm: 9.8482 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.1336 loss: 1.1336 2022/09/07 22:20:47 - mmengine - INFO - Epoch(train) [47][1500/1793] lr: 7.5000e-06 eta: 0:25:23 time: 0.1783 data_time: 0.0073 memory: 10464 grad_norm: 9.7795 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.0800 loss: 1.0800 2022/09/07 22:20:51 - mmengine - INFO - Epoch(train) [47][1520/1793] lr: 7.5000e-06 eta: 0:25:18 time: 0.1838 data_time: 0.0106 memory: 10464 grad_norm: 9.6096 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.0667 loss: 1.0667 2022/09/07 22:20:51 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:20:54 - mmengine - INFO - Epoch(train) [47][1540/1793] lr: 7.5000e-06 eta: 0:25:12 time: 0.1768 data_time: 0.0073 memory: 10464 grad_norm: 9.8483 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0968 loss: 1.0968 2022/09/07 22:20:58 - mmengine - INFO - Epoch(train) [47][1560/1793] lr: 7.5000e-06 eta: 0:25:07 time: 0.1793 data_time: 0.0071 memory: 10464 grad_norm: 9.9102 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2619 loss: 1.2619 2022/09/07 22:21:01 - mmengine - INFO - Epoch(train) [47][1580/1793] lr: 7.5000e-06 eta: 0:25:01 time: 0.1859 data_time: 0.0102 memory: 10464 grad_norm: 10.0762 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9983 loss: 0.9983 2022/09/07 22:21:05 - mmengine - INFO - Epoch(train) [47][1600/1793] lr: 7.5000e-06 eta: 0:24:56 time: 0.1773 data_time: 0.0069 memory: 10464 grad_norm: 10.5697 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0497 loss: 1.0497 2022/09/07 22:21:09 - mmengine - INFO - Epoch(train) [47][1620/1793] lr: 7.5000e-06 eta: 0:24:50 time: 0.1809 data_time: 0.0075 memory: 10464 grad_norm: 10.0092 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4148 loss: 1.4148 2022/09/07 22:21:12 - mmengine - INFO - Epoch(train) [47][1640/1793] lr: 7.5000e-06 eta: 0:24:45 time: 0.1807 data_time: 0.0090 memory: 10464 grad_norm: 9.5750 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.3837 loss: 1.3837 2022/09/07 22:21:16 - mmengine - INFO - Epoch(train) [47][1660/1793] lr: 7.5000e-06 eta: 0:24:39 time: 0.1799 data_time: 0.0077 memory: 10464 grad_norm: 9.6831 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0826 loss: 1.0826 2022/09/07 22:21:19 - mmengine - INFO - Epoch(train) [47][1680/1793] lr: 7.5000e-06 eta: 0:24:34 time: 0.1794 data_time: 0.0071 memory: 10464 grad_norm: 9.7173 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0653 loss: 1.0653 2022/09/07 22:21:23 - mmengine - INFO - Epoch(train) [47][1700/1793] lr: 7.5000e-06 eta: 0:24:28 time: 0.1750 data_time: 0.0091 memory: 10464 grad_norm: 10.0737 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8806 loss: 0.8806 2022/09/07 22:21:26 - mmengine - INFO - Epoch(train) [47][1720/1793] lr: 7.5000e-06 eta: 0:24:23 time: 0.1773 data_time: 0.0069 memory: 10464 grad_norm: 9.5917 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9882 loss: 0.9882 2022/09/07 22:21:30 - mmengine - INFO - Epoch(train) [47][1740/1793] lr: 7.5000e-06 eta: 0:24:17 time: 0.1800 data_time: 0.0077 memory: 10464 grad_norm: 10.4008 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2108 loss: 1.2108 2022/09/07 22:21:34 - mmengine - INFO - Epoch(train) [47][1760/1793] lr: 7.5000e-06 eta: 0:24:12 time: 0.1768 data_time: 0.0095 memory: 10464 grad_norm: 9.9067 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1277 loss: 1.1277 2022/09/07 22:21:37 - mmengine - INFO - Epoch(train) [47][1780/1793] lr: 7.5000e-06 eta: 0:24:06 time: 0.1776 data_time: 0.0069 memory: 10464 grad_norm: 10.5489 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2199 loss: 1.2199 2022/09/07 22:21:39 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:21:39 - mmengine - INFO - Epoch(train) [47][1793/1793] lr: 7.5000e-06 eta: 0:24:06 time: 0.1759 data_time: 0.0073 memory: 10464 grad_norm: 10.4140 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 1.2878 loss: 1.2878 2022/09/07 22:21:39 - mmengine - INFO - Saving checkpoint at 47 epochs 2022/09/07 22:21:43 - mmengine - INFO - Epoch(val) [47][20/241] eta: 0:00:13 time: 0.0592 data_time: 0.0094 memory: 1482 2022/09/07 22:21:44 - mmengine - INFO - Epoch(val) [47][40/241] eta: 0:00:10 time: 0.0538 data_time: 0.0052 memory: 1482 2022/09/07 22:21:45 - mmengine - INFO - Epoch(val) [47][60/241] eta: 0:00:09 time: 0.0539 data_time: 0.0053 memory: 1482 2022/09/07 22:21:46 - mmengine - INFO - Epoch(val) [47][80/241] eta: 0:00:08 time: 0.0534 data_time: 0.0049 memory: 1482 2022/09/07 22:21:47 - mmengine - INFO - Epoch(val) [47][100/241] eta: 0:00:07 time: 0.0536 data_time: 0.0052 memory: 1482 2022/09/07 22:21:48 - mmengine - INFO - Epoch(val) [47][120/241] eta: 0:00:06 time: 0.0538 data_time: 0.0052 memory: 1482 2022/09/07 22:21:50 - mmengine - INFO - Epoch(val) [47][140/241] eta: 0:00:05 time: 0.0541 data_time: 0.0055 memory: 1482 2022/09/07 22:21:51 - mmengine - INFO - Epoch(val) [47][160/241] eta: 0:00:04 time: 0.0536 data_time: 0.0051 memory: 1482 2022/09/07 22:21:52 - mmengine - INFO - Epoch(val) [47][180/241] eta: 0:00:03 time: 0.0540 data_time: 0.0055 memory: 1482 2022/09/07 22:21:53 - mmengine - INFO - Epoch(val) [47][200/241] eta: 0:00:02 time: 0.0526 data_time: 0.0044 memory: 1482 2022/09/07 22:21:54 - mmengine - INFO - Epoch(val) [47][220/241] eta: 0:00:01 time: 0.0529 data_time: 0.0047 memory: 1482 2022/09/07 22:21:55 - mmengine - INFO - Epoch(val) [47][240/241] eta: 0:00:00 time: 0.0524 data_time: 0.0044 memory: 1482 2022/09/07 22:21:55 - mmengine - INFO - Epoch(val) [47][241/241] acc/top1: 0.4766 acc/top5: 0.7802 acc/mean1: 0.4401 2022/09/07 22:21:59 - mmengine - INFO - Epoch(train) [48][20/1793] lr: 7.5000e-06 eta: 0:23:57 time: 0.1822 data_time: 0.0120 memory: 10464 grad_norm: 9.6079 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2509 loss: 1.2509 2022/09/07 22:22:03 - mmengine - INFO - Epoch(train) [48][40/1793] lr: 7.5000e-06 eta: 0:23:52 time: 0.1743 data_time: 0.0075 memory: 10464 grad_norm: 9.9352 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8729 loss: 0.8729 2022/09/07 22:22:06 - mmengine - INFO - Epoch(train) [48][60/1793] lr: 7.5000e-06 eta: 0:23:46 time: 0.1744 data_time: 0.0070 memory: 10464 grad_norm: 10.3612 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0301 loss: 1.0301 2022/09/07 22:22:10 - mmengine - INFO - Epoch(train) [48][80/1793] lr: 7.5000e-06 eta: 0:23:41 time: 0.1796 data_time: 0.0107 memory: 10464 grad_norm: 10.0261 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0648 loss: 1.0648 2022/09/07 22:22:13 - mmengine - INFO - Epoch(train) [48][100/1793] lr: 7.5000e-06 eta: 0:23:35 time: 0.1737 data_time: 0.0074 memory: 10464 grad_norm: 10.1118 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.0224 loss: 1.0224 2022/09/07 22:22:17 - mmengine - INFO - Epoch(train) [48][120/1793] lr: 7.5000e-06 eta: 0:23:30 time: 0.1790 data_time: 0.0072 memory: 10464 grad_norm: 10.2567 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1208 loss: 1.1208 2022/09/07 22:22:20 - mmengine - INFO - Epoch(train) [48][140/1793] lr: 7.5000e-06 eta: 0:23:24 time: 0.1787 data_time: 0.0100 memory: 10464 grad_norm: 10.2319 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9147 loss: 0.9147 2022/09/07 22:22:24 - mmengine - INFO - Epoch(train) [48][160/1793] lr: 7.5000e-06 eta: 0:23:19 time: 0.1745 data_time: 0.0069 memory: 10464 grad_norm: 10.1862 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0372 loss: 1.0372 2022/09/07 22:22:27 - mmengine - INFO - Epoch(train) [48][180/1793] lr: 7.5000e-06 eta: 0:23:13 time: 0.1783 data_time: 0.0073 memory: 10464 grad_norm: 9.7189 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1232 loss: 1.1232 2022/09/07 22:22:31 - mmengine - INFO - Epoch(train) [48][200/1793] lr: 7.5000e-06 eta: 0:23:08 time: 0.1876 data_time: 0.0098 memory: 10464 grad_norm: 9.7353 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1050 loss: 1.1050 2022/09/07 22:22:35 - mmengine - INFO - Epoch(train) [48][220/1793] lr: 7.5000e-06 eta: 0:23:02 time: 0.1766 data_time: 0.0067 memory: 10464 grad_norm: 9.8841 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0708 loss: 1.0708 2022/09/07 22:22:38 - mmengine - INFO - Epoch(train) [48][240/1793] lr: 7.5000e-06 eta: 0:22:57 time: 0.1781 data_time: 0.0072 memory: 10464 grad_norm: 9.9388 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1879 loss: 1.1879 2022/09/07 22:22:42 - mmengine - INFO - Epoch(train) [48][260/1793] lr: 7.5000e-06 eta: 0:22:51 time: 0.1779 data_time: 0.0095 memory: 10464 grad_norm: 9.1686 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.8902 loss: 0.8902 2022/09/07 22:22:45 - mmengine - INFO - Epoch(train) [48][280/1793] lr: 7.5000e-06 eta: 0:22:46 time: 0.1743 data_time: 0.0072 memory: 10464 grad_norm: 10.0737 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1653 loss: 1.1653 2022/09/07 22:22:49 - mmengine - INFO - Epoch(train) [48][300/1793] lr: 7.5000e-06 eta: 0:22:40 time: 0.1884 data_time: 0.0079 memory: 10464 grad_norm: 10.0195 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1431 loss: 1.1431 2022/09/07 22:22:53 - mmengine - INFO - Epoch(train) [48][320/1793] lr: 7.5000e-06 eta: 0:22:35 time: 0.1751 data_time: 0.0092 memory: 10464 grad_norm: 10.1829 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1475 loss: 1.1475 2022/09/07 22:22:56 - mmengine - INFO - Epoch(train) [48][340/1793] lr: 7.5000e-06 eta: 0:22:29 time: 0.1732 data_time: 0.0072 memory: 10464 grad_norm: 9.8055 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1941 loss: 1.1941 2022/09/07 22:23:00 - mmengine - INFO - Epoch(train) [48][360/1793] lr: 7.5000e-06 eta: 0:22:24 time: 0.1743 data_time: 0.0072 memory: 10464 grad_norm: 9.9392 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0639 loss: 1.0639 2022/09/07 22:23:03 - mmengine - INFO - Epoch(train) [48][380/1793] lr: 7.5000e-06 eta: 0:22:19 time: 0.1759 data_time: 0.0091 memory: 10464 grad_norm: 9.9079 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.1694 loss: 1.1694 2022/09/07 22:23:07 - mmengine - INFO - Epoch(train) [48][400/1793] lr: 7.5000e-06 eta: 0:22:13 time: 0.1778 data_time: 0.0070 memory: 10464 grad_norm: 10.0445 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.1818 loss: 1.1818 2022/09/07 22:23:11 - mmengine - INFO - Epoch(train) [48][420/1793] lr: 7.5000e-06 eta: 0:22:08 time: 0.1909 data_time: 0.0076 memory: 10464 grad_norm: 10.0801 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2521 loss: 1.2521 2022/09/07 22:23:14 - mmengine - INFO - Epoch(train) [48][440/1793] lr: 7.5000e-06 eta: 0:22:02 time: 0.1762 data_time: 0.0105 memory: 10464 grad_norm: 10.1880 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2250 loss: 1.2250 2022/09/07 22:23:18 - mmengine - INFO - Epoch(train) [48][460/1793] lr: 7.5000e-06 eta: 0:21:57 time: 0.1752 data_time: 0.0072 memory: 10464 grad_norm: 10.2548 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.3983 loss: 1.3983 2022/09/07 22:23:21 - mmengine - INFO - Epoch(train) [48][480/1793] lr: 7.5000e-06 eta: 0:21:51 time: 0.1773 data_time: 0.0068 memory: 10464 grad_norm: 9.9593 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2642 loss: 1.2642 2022/09/07 22:23:25 - mmengine - INFO - Epoch(train) [48][500/1793] lr: 7.5000e-06 eta: 0:21:46 time: 0.1771 data_time: 0.0107 memory: 10464 grad_norm: 9.7997 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9607 loss: 0.9607 2022/09/07 22:23:28 - mmengine - INFO - Epoch(train) [48][520/1793] lr: 7.5000e-06 eta: 0:21:40 time: 0.1801 data_time: 0.0070 memory: 10464 grad_norm: 10.0595 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.2762 loss: 1.2762 2022/09/07 22:23:32 - mmengine - INFO - Epoch(train) [48][540/1793] lr: 7.5000e-06 eta: 0:21:35 time: 0.1950 data_time: 0.0074 memory: 10464 grad_norm: 9.8009 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1901 loss: 1.1901 2022/09/07 22:23:36 - mmengine - INFO - Epoch(train) [48][560/1793] lr: 7.5000e-06 eta: 0:21:29 time: 0.1812 data_time: 0.0094 memory: 10464 grad_norm: 10.1497 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1105 loss: 1.1105 2022/09/07 22:23:39 - mmengine - INFO - Epoch(train) [48][580/1793] lr: 7.5000e-06 eta: 0:21:24 time: 0.1784 data_time: 0.0063 memory: 10464 grad_norm: 10.1090 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3136 loss: 1.3136 2022/09/07 22:23:43 - mmengine - INFO - Epoch(train) [48][600/1793] lr: 7.5000e-06 eta: 0:21:19 time: 0.1776 data_time: 0.0071 memory: 10464 grad_norm: 9.7103 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0512 loss: 1.0512 2022/09/07 22:23:47 - mmengine - INFO - Epoch(train) [48][620/1793] lr: 7.5000e-06 eta: 0:21:13 time: 0.1868 data_time: 0.0093 memory: 10464 grad_norm: 9.9611 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2030 loss: 1.2030 2022/09/07 22:23:51 - mmengine - INFO - Epoch(train) [48][640/1793] lr: 7.5000e-06 eta: 0:21:08 time: 0.1938 data_time: 0.0082 memory: 10464 grad_norm: 10.1770 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0812 loss: 1.0812 2022/09/07 22:23:54 - mmengine - INFO - Epoch(train) [48][660/1793] lr: 7.5000e-06 eta: 0:21:02 time: 0.1743 data_time: 0.0069 memory: 10464 grad_norm: 9.6155 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.8465 loss: 0.8465 2022/09/07 22:23:58 - mmengine - INFO - Epoch(train) [48][680/1793] lr: 7.5000e-06 eta: 0:20:57 time: 0.1790 data_time: 0.0095 memory: 10464 grad_norm: 10.2085 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1392 loss: 1.1392 2022/09/07 22:24:01 - mmengine - INFO - Epoch(train) [48][700/1793] lr: 7.5000e-06 eta: 0:20:51 time: 0.1786 data_time: 0.0073 memory: 10464 grad_norm: 9.8439 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0021 loss: 1.0021 2022/09/07 22:24:05 - mmengine - INFO - Epoch(train) [48][720/1793] lr: 7.5000e-06 eta: 0:20:46 time: 0.1759 data_time: 0.0070 memory: 10464 grad_norm: 9.6031 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 0.9675 loss: 0.9675 2022/09/07 22:24:07 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:24:08 - mmengine - INFO - Epoch(train) [48][740/1793] lr: 7.5000e-06 eta: 0:20:40 time: 0.1841 data_time: 0.0103 memory: 10464 grad_norm: 10.1960 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1766 loss: 1.1766 2022/09/07 22:24:12 - mmengine - INFO - Epoch(train) [48][760/1793] lr: 7.5000e-06 eta: 0:20:35 time: 0.1850 data_time: 0.0080 memory: 10464 grad_norm: 9.7219 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 0.9614 loss: 0.9614 2022/09/07 22:24:16 - mmengine - INFO - Epoch(train) [48][780/1793] lr: 7.5000e-06 eta: 0:20:30 time: 0.1745 data_time: 0.0068 memory: 10464 grad_norm: 10.2746 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.1747 loss: 1.1747 2022/09/07 22:24:19 - mmengine - INFO - Epoch(train) [48][800/1793] lr: 7.5000e-06 eta: 0:20:24 time: 0.1844 data_time: 0.0113 memory: 10464 grad_norm: 9.8933 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0256 loss: 1.0256 2022/09/07 22:24:23 - mmengine - INFO - Epoch(train) [48][820/1793] lr: 7.5000e-06 eta: 0:20:19 time: 0.1763 data_time: 0.0072 memory: 10464 grad_norm: 10.2764 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1404 loss: 1.1404 2022/09/07 22:24:27 - mmengine - INFO - Epoch(train) [48][840/1793] lr: 7.5000e-06 eta: 0:20:13 time: 0.1838 data_time: 0.0075 memory: 10464 grad_norm: 9.8667 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0405 loss: 1.0405 2022/09/07 22:24:30 - mmengine - INFO - Epoch(train) [48][860/1793] lr: 7.5000e-06 eta: 0:20:08 time: 0.1803 data_time: 0.0094 memory: 10464 grad_norm: 10.4262 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1070 loss: 1.1070 2022/09/07 22:24:34 - mmengine - INFO - Epoch(train) [48][880/1793] lr: 7.5000e-06 eta: 0:20:02 time: 0.1761 data_time: 0.0071 memory: 10464 grad_norm: 10.2639 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3532 loss: 1.3532 2022/09/07 22:24:37 - mmengine - INFO - Epoch(train) [48][900/1793] lr: 7.5000e-06 eta: 0:19:57 time: 0.1766 data_time: 0.0072 memory: 10464 grad_norm: 9.7699 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.2462 loss: 1.2462 2022/09/07 22:24:41 - mmengine - INFO - Epoch(train) [48][920/1793] lr: 7.5000e-06 eta: 0:19:51 time: 0.1819 data_time: 0.0109 memory: 10464 grad_norm: 9.9283 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1979 loss: 1.1979 2022/09/07 22:24:44 - mmengine - INFO - Epoch(train) [48][940/1793] lr: 7.5000e-06 eta: 0:19:46 time: 0.1749 data_time: 0.0075 memory: 10464 grad_norm: 10.0118 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0852 loss: 1.0852 2022/09/07 22:24:48 - mmengine - INFO - Epoch(train) [48][960/1793] lr: 7.5000e-06 eta: 0:19:41 time: 0.1759 data_time: 0.0067 memory: 10464 grad_norm: 9.9641 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3632 loss: 1.3632 2022/09/07 22:24:52 - mmengine - INFO - Epoch(train) [48][980/1793] lr: 7.5000e-06 eta: 0:19:35 time: 0.1789 data_time: 0.0103 memory: 10464 grad_norm: 9.9632 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9574 loss: 0.9574 2022/09/07 22:24:55 - mmengine - INFO - Epoch(train) [48][1000/1793] lr: 7.5000e-06 eta: 0:19:30 time: 0.1735 data_time: 0.0069 memory: 10464 grad_norm: 9.8085 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3594 loss: 1.3594 2022/09/07 22:24:58 - mmengine - INFO - Epoch(train) [48][1020/1793] lr: 7.5000e-06 eta: 0:19:24 time: 0.1741 data_time: 0.0068 memory: 10464 grad_norm: 9.5923 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.0110 loss: 1.0110 2022/09/07 22:25:02 - mmengine - INFO - Epoch(train) [48][1040/1793] lr: 7.5000e-06 eta: 0:19:19 time: 0.1815 data_time: 0.0125 memory: 10464 grad_norm: 10.3137 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2595 loss: 1.2595 2022/09/07 22:25:06 - mmengine - INFO - Epoch(train) [48][1060/1793] lr: 7.5000e-06 eta: 0:19:13 time: 0.1738 data_time: 0.0073 memory: 10464 grad_norm: 9.8361 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.4286 loss: 1.4286 2022/09/07 22:25:09 - mmengine - INFO - Epoch(train) [48][1080/1793] lr: 7.5000e-06 eta: 0:19:08 time: 0.1857 data_time: 0.0075 memory: 10464 grad_norm: 10.2276 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9558 loss: 0.9558 2022/09/07 22:25:13 - mmengine - INFO - Epoch(train) [48][1100/1793] lr: 7.5000e-06 eta: 0:19:03 time: 0.1797 data_time: 0.0095 memory: 10464 grad_norm: 9.9520 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8502 loss: 0.8502 2022/09/07 22:25:16 - mmengine - INFO - Epoch(train) [48][1120/1793] lr: 7.5000e-06 eta: 0:18:57 time: 0.1768 data_time: 0.0067 memory: 10464 grad_norm: 10.3906 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0415 loss: 1.0415 2022/09/07 22:25:20 - mmengine - INFO - Epoch(train) [48][1140/1793] lr: 7.5000e-06 eta: 0:18:52 time: 0.1827 data_time: 0.0089 memory: 10464 grad_norm: 9.9046 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 0.9521 loss: 0.9521 2022/09/07 22:25:24 - mmengine - INFO - Epoch(train) [48][1160/1793] lr: 7.5000e-06 eta: 0:18:46 time: 0.1758 data_time: 0.0100 memory: 10464 grad_norm: 10.2552 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1417 loss: 1.1417 2022/09/07 22:25:27 - mmengine - INFO - Epoch(train) [48][1180/1793] lr: 7.5000e-06 eta: 0:18:41 time: 0.1794 data_time: 0.0078 memory: 10464 grad_norm: 9.4970 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 0.8717 loss: 0.8717 2022/09/07 22:25:31 - mmengine - INFO - Epoch(train) [48][1200/1793] lr: 7.5000e-06 eta: 0:18:35 time: 0.1755 data_time: 0.0078 memory: 10464 grad_norm: 10.5518 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1125 loss: 1.1125 2022/09/07 22:25:34 - mmengine - INFO - Epoch(train) [48][1220/1793] lr: 7.5000e-06 eta: 0:18:30 time: 0.1752 data_time: 0.0091 memory: 10464 grad_norm: 10.0396 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2274 loss: 1.2274 2022/09/07 22:25:38 - mmengine - INFO - Epoch(train) [48][1240/1793] lr: 7.5000e-06 eta: 0:18:25 time: 0.1962 data_time: 0.0069 memory: 10464 grad_norm: 10.3758 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2396 loss: 1.2396 2022/09/07 22:25:42 - mmengine - INFO - Epoch(train) [48][1260/1793] lr: 7.5000e-06 eta: 0:18:19 time: 0.1782 data_time: 0.0074 memory: 10464 grad_norm: 9.4866 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1921 loss: 1.1921 2022/09/07 22:25:45 - mmengine - INFO - Epoch(train) [48][1280/1793] lr: 7.5000e-06 eta: 0:18:14 time: 0.1766 data_time: 0.0092 memory: 10464 grad_norm: 9.9400 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 1.1513 loss: 1.1513 2022/09/07 22:25:49 - mmengine - INFO - Epoch(train) [48][1300/1793] lr: 7.5000e-06 eta: 0:18:08 time: 0.1754 data_time: 0.0073 memory: 10464 grad_norm: 9.9695 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.3390 loss: 1.3390 2022/09/07 22:25:52 - mmengine - INFO - Epoch(train) [48][1320/1793] lr: 7.5000e-06 eta: 0:18:03 time: 0.1744 data_time: 0.0078 memory: 10464 grad_norm: 10.4891 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.1512 loss: 1.1512 2022/09/07 22:25:56 - mmengine - INFO - Epoch(train) [48][1340/1793] lr: 7.5000e-06 eta: 0:17:57 time: 0.1799 data_time: 0.0100 memory: 10464 grad_norm: 9.7958 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0996 loss: 1.0996 2022/09/07 22:26:00 - mmengine - INFO - Epoch(train) [48][1360/1793] lr: 7.5000e-06 eta: 0:17:52 time: 0.1853 data_time: 0.0077 memory: 10464 grad_norm: 9.9289 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2293 loss: 1.2293 2022/09/07 22:26:03 - mmengine - INFO - Epoch(train) [48][1380/1793] lr: 7.5000e-06 eta: 0:17:47 time: 0.1739 data_time: 0.0070 memory: 10464 grad_norm: 10.2776 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3773 loss: 1.3773 2022/09/07 22:26:07 - mmengine - INFO - Epoch(train) [48][1400/1793] lr: 7.5000e-06 eta: 0:17:41 time: 0.1775 data_time: 0.0098 memory: 10464 grad_norm: 9.6440 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3205 loss: 1.3205 2022/09/07 22:26:10 - mmengine - INFO - Epoch(train) [48][1420/1793] lr: 7.5000e-06 eta: 0:17:36 time: 0.1810 data_time: 0.0084 memory: 10464 grad_norm: 10.1497 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4077 loss: 1.4077 2022/09/07 22:26:14 - mmengine - INFO - Epoch(train) [48][1440/1793] lr: 7.5000e-06 eta: 0:17:30 time: 0.1747 data_time: 0.0069 memory: 10464 grad_norm: 9.8791 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2494 loss: 1.2494 2022/09/07 22:26:17 - mmengine - INFO - Epoch(train) [48][1460/1793] lr: 7.5000e-06 eta: 0:17:25 time: 0.1804 data_time: 0.0101 memory: 10464 grad_norm: 9.8600 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1268 loss: 1.1268 2022/09/07 22:26:21 - mmengine - INFO - Epoch(train) [48][1480/1793] lr: 7.5000e-06 eta: 0:17:19 time: 0.1870 data_time: 0.0069 memory: 10464 grad_norm: 10.5353 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0979 loss: 1.0979 2022/09/07 22:26:25 - mmengine - INFO - Epoch(train) [48][1500/1793] lr: 7.5000e-06 eta: 0:17:14 time: 0.1776 data_time: 0.0074 memory: 10464 grad_norm: 9.9868 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1668 loss: 1.1668 2022/09/07 22:26:28 - mmengine - INFO - Epoch(train) [48][1520/1793] lr: 7.5000e-06 eta: 0:17:09 time: 0.1839 data_time: 0.0090 memory: 10464 grad_norm: 9.9116 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9454 loss: 0.9454 2022/09/07 22:26:32 - mmengine - INFO - Epoch(train) [48][1540/1793] lr: 7.5000e-06 eta: 0:17:03 time: 0.1787 data_time: 0.0078 memory: 10464 grad_norm: 9.7305 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0345 loss: 1.0345 2022/09/07 22:26:36 - mmengine - INFO - Epoch(train) [48][1560/1793] lr: 7.5000e-06 eta: 0:16:58 time: 0.1786 data_time: 0.0069 memory: 10464 grad_norm: 10.1768 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2139 loss: 1.2139 2022/09/07 22:26:39 - mmengine - INFO - Epoch(train) [48][1580/1793] lr: 7.5000e-06 eta: 0:16:52 time: 0.1920 data_time: 0.0101 memory: 10464 grad_norm: 10.0451 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0175 loss: 1.0175 2022/09/07 22:26:43 - mmengine - INFO - Epoch(train) [48][1600/1793] lr: 7.5000e-06 eta: 0:16:47 time: 0.1772 data_time: 0.0071 memory: 10464 grad_norm: 10.1538 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0860 loss: 1.0860 2022/09/07 22:26:46 - mmengine - INFO - Epoch(train) [48][1620/1793] lr: 7.5000e-06 eta: 0:16:42 time: 0.1778 data_time: 0.0073 memory: 10464 grad_norm: 9.8689 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0588 loss: 1.0588 2022/09/07 22:26:50 - mmengine - INFO - Epoch(train) [48][1640/1793] lr: 7.5000e-06 eta: 0:16:36 time: 0.1815 data_time: 0.0096 memory: 10464 grad_norm: 9.7911 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.2674 loss: 1.2674 2022/09/07 22:26:54 - mmengine - INFO - Epoch(train) [48][1660/1793] lr: 7.5000e-06 eta: 0:16:31 time: 0.1762 data_time: 0.0074 memory: 10464 grad_norm: 10.6928 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 0.9247 loss: 0.9247 2022/09/07 22:26:57 - mmengine - INFO - Epoch(train) [48][1680/1793] lr: 7.5000e-06 eta: 0:16:25 time: 0.1834 data_time: 0.0077 memory: 10464 grad_norm: 10.2740 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3119 loss: 1.3119 2022/09/07 22:27:01 - mmengine - INFO - Epoch(train) [48][1700/1793] lr: 7.5000e-06 eta: 0:16:20 time: 0.1817 data_time: 0.0095 memory: 10464 grad_norm: 9.4485 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 0.8064 loss: 0.8064 2022/09/07 22:27:04 - mmengine - INFO - Epoch(train) [48][1720/1793] lr: 7.5000e-06 eta: 0:16:15 time: 0.1749 data_time: 0.0069 memory: 10464 grad_norm: 10.0820 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0869 loss: 1.0869 2022/09/07 22:27:06 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:27:08 - mmengine - INFO - Epoch(train) [48][1740/1793] lr: 7.5000e-06 eta: 0:16:09 time: 0.1804 data_time: 0.0073 memory: 10464 grad_norm: 9.7097 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2991 loss: 1.2991 2022/09/07 22:27:12 - mmengine - INFO - Epoch(train) [48][1760/1793] lr: 7.5000e-06 eta: 0:16:04 time: 0.1879 data_time: 0.0134 memory: 10464 grad_norm: 10.1219 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0524 loss: 1.0524 2022/09/07 22:27:15 - mmengine - INFO - Epoch(train) [48][1780/1793] lr: 7.5000e-06 eta: 0:15:58 time: 0.1743 data_time: 0.0079 memory: 10464 grad_norm: 10.0009 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9906 loss: 0.9906 2022/09/07 22:27:18 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:27:18 - mmengine - INFO - Epoch(train) [48][1793/1793] lr: 7.5000e-06 eta: 0:15:58 time: 0.1745 data_time: 0.0069 memory: 10464 grad_norm: 10.3137 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 1.0874 loss: 1.0874 2022/09/07 22:27:18 - mmengine - INFO - Saving checkpoint at 48 epochs 2022/09/07 22:27:22 - mmengine - INFO - Epoch(val) [48][20/241] eta: 0:00:12 time: 0.0586 data_time: 0.0094 memory: 1482 2022/09/07 22:27:23 - mmengine - INFO - Epoch(val) [48][40/241] eta: 0:00:10 time: 0.0537 data_time: 0.0053 memory: 1482 2022/09/07 22:27:24 - mmengine - INFO - Epoch(val) [48][60/241] eta: 0:00:09 time: 0.0537 data_time: 0.0052 memory: 1482 2022/09/07 22:27:25 - mmengine - INFO - Epoch(val) [48][80/241] eta: 0:00:08 time: 0.0536 data_time: 0.0052 memory: 1482 2022/09/07 22:27:26 - mmengine - INFO - Epoch(val) [48][100/241] eta: 0:00:07 time: 0.0538 data_time: 0.0051 memory: 1482 2022/09/07 22:27:27 - mmengine - INFO - Epoch(val) [48][120/241] eta: 0:00:06 time: 0.0535 data_time: 0.0052 memory: 1482 2022/09/07 22:27:28 - mmengine - INFO - Epoch(val) [48][140/241] eta: 0:00:05 time: 0.0532 data_time: 0.0051 memory: 1482 2022/09/07 22:27:29 - mmengine - INFO - Epoch(val) [48][160/241] eta: 0:00:04 time: 0.0602 data_time: 0.0065 memory: 1482 2022/09/07 22:27:30 - mmengine - INFO - Epoch(val) [48][180/241] eta: 0:00:03 time: 0.0538 data_time: 0.0053 memory: 1482 2022/09/07 22:27:31 - mmengine - INFO - Epoch(val) [48][200/241] eta: 0:00:02 time: 0.0531 data_time: 0.0047 memory: 1482 2022/09/07 22:27:33 - mmengine - INFO - Epoch(val) [48][220/241] eta: 0:00:01 time: 0.0528 data_time: 0.0046 memory: 1482 2022/09/07 22:27:34 - mmengine - INFO - Epoch(val) [48][240/241] eta: 0:00:00 time: 0.0522 data_time: 0.0044 memory: 1482 2022/09/07 22:27:34 - mmengine - INFO - Epoch(val) [48][241/241] acc/top1: 0.4791 acc/top5: 0.7795 acc/mean1: 0.4433 2022/09/07 22:27:38 - mmengine - INFO - Epoch(train) [49][20/1793] lr: 7.5000e-06 eta: 0:15:49 time: 0.1822 data_time: 0.0120 memory: 10464 grad_norm: 10.4589 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1862 loss: 1.1862 2022/09/07 22:27:41 - mmengine - INFO - Epoch(train) [49][40/1793] lr: 7.5000e-06 eta: 0:15:44 time: 0.1741 data_time: 0.0075 memory: 10464 grad_norm: 9.8404 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0994 loss: 1.0994 2022/09/07 22:27:45 - mmengine - INFO - Epoch(train) [49][60/1793] lr: 7.5000e-06 eta: 0:15:39 time: 0.1729 data_time: 0.0072 memory: 10464 grad_norm: 9.9074 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.1166 loss: 1.1166 2022/09/07 22:27:49 - mmengine - INFO - Epoch(train) [49][80/1793] lr: 7.5000e-06 eta: 0:15:33 time: 0.1850 data_time: 0.0097 memory: 10464 grad_norm: 10.0401 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1210 loss: 1.1210 2022/09/07 22:27:52 - mmengine - INFO - Epoch(train) [49][100/1793] lr: 7.5000e-06 eta: 0:15:28 time: 0.1934 data_time: 0.0071 memory: 10464 grad_norm: 10.0167 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0963 loss: 1.0963 2022/09/07 22:27:56 - mmengine - INFO - Epoch(train) [49][120/1793] lr: 7.5000e-06 eta: 0:15:22 time: 0.1746 data_time: 0.0075 memory: 10464 grad_norm: 9.9088 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1745 loss: 1.1745 2022/09/07 22:28:00 - mmengine - INFO - Epoch(train) [49][140/1793] lr: 7.5000e-06 eta: 0:15:17 time: 0.1865 data_time: 0.0101 memory: 10464 grad_norm: 10.3186 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2056 loss: 1.2056 2022/09/07 22:28:03 - mmengine - INFO - Epoch(train) [49][160/1793] lr: 7.5000e-06 eta: 0:15:12 time: 0.1765 data_time: 0.0072 memory: 10464 grad_norm: 10.5353 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0745 loss: 1.0745 2022/09/07 22:28:07 - mmengine - INFO - Epoch(train) [49][180/1793] lr: 7.5000e-06 eta: 0:15:06 time: 0.1742 data_time: 0.0068 memory: 10464 grad_norm: 10.1963 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0046 loss: 1.0046 2022/09/07 22:28:10 - mmengine - INFO - Epoch(train) [49][200/1793] lr: 7.5000e-06 eta: 0:15:01 time: 0.1863 data_time: 0.0105 memory: 10464 grad_norm: 9.8737 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1668 loss: 1.1668 2022/09/07 22:28:14 - mmengine - INFO - Epoch(train) [49][220/1793] lr: 7.5000e-06 eta: 0:14:55 time: 0.1759 data_time: 0.0076 memory: 10464 grad_norm: 9.7967 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9896 loss: 0.9896 2022/09/07 22:28:18 - mmengine - INFO - Epoch(train) [49][240/1793] lr: 7.5000e-06 eta: 0:14:50 time: 0.1798 data_time: 0.0074 memory: 10464 grad_norm: 9.5819 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.1559 loss: 1.1559 2022/09/07 22:28:21 - mmengine - INFO - Epoch(train) [49][260/1793] lr: 7.5000e-06 eta: 0:14:45 time: 0.1806 data_time: 0.0095 memory: 10464 grad_norm: 10.1389 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0595 loss: 1.0595 2022/09/07 22:28:25 - mmengine - INFO - Epoch(train) [49][280/1793] lr: 7.5000e-06 eta: 0:14:39 time: 0.1744 data_time: 0.0065 memory: 10464 grad_norm: 9.9372 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8117 loss: 0.8117 2022/09/07 22:28:28 - mmengine - INFO - Epoch(train) [49][300/1793] lr: 7.5000e-06 eta: 0:14:34 time: 0.1891 data_time: 0.0067 memory: 10464 grad_norm: 10.1663 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.8729 loss: 0.8729 2022/09/07 22:28:32 - mmengine - INFO - Epoch(train) [49][320/1793] lr: 7.5000e-06 eta: 0:14:28 time: 0.1799 data_time: 0.0100 memory: 10464 grad_norm: 9.8709 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0350 loss: 1.0350 2022/09/07 22:28:36 - mmengine - INFO - Epoch(train) [49][340/1793] lr: 7.5000e-06 eta: 0:14:23 time: 0.1749 data_time: 0.0080 memory: 10464 grad_norm: 9.9023 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1276 loss: 1.1276 2022/09/07 22:28:39 - mmengine - INFO - Epoch(train) [49][360/1793] lr: 7.5000e-06 eta: 0:14:18 time: 0.1793 data_time: 0.0067 memory: 10464 grad_norm: 9.9202 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1370 loss: 1.1370 2022/09/07 22:28:43 - mmengine - INFO - Epoch(train) [49][380/1793] lr: 7.5000e-06 eta: 0:14:12 time: 0.1806 data_time: 0.0098 memory: 10464 grad_norm: 9.8710 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1713 loss: 1.1713 2022/09/07 22:28:46 - mmengine - INFO - Epoch(train) [49][400/1793] lr: 7.5000e-06 eta: 0:14:07 time: 0.1749 data_time: 0.0067 memory: 10464 grad_norm: 10.3128 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1431 loss: 1.1431 2022/09/07 22:28:50 - mmengine - INFO - Epoch(train) [49][420/1793] lr: 7.5000e-06 eta: 0:14:02 time: 0.1896 data_time: 0.0081 memory: 10464 grad_norm: 10.1572 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.3127 loss: 1.3127 2022/09/07 22:28:54 - mmengine - INFO - Epoch(train) [49][440/1793] lr: 7.5000e-06 eta: 0:13:56 time: 0.1775 data_time: 0.0105 memory: 10464 grad_norm: 9.4212 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.0577 loss: 1.0577 2022/09/07 22:28:57 - mmengine - INFO - Epoch(train) [49][460/1793] lr: 7.5000e-06 eta: 0:13:51 time: 0.1762 data_time: 0.0072 memory: 10464 grad_norm: 9.9534 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1401 loss: 1.1401 2022/09/07 22:29:01 - mmengine - INFO - Epoch(train) [49][480/1793] lr: 7.5000e-06 eta: 0:13:45 time: 0.1994 data_time: 0.0084 memory: 10464 grad_norm: 9.8038 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0810 loss: 1.0810 2022/09/07 22:29:05 - mmengine - INFO - Epoch(train) [49][500/1793] lr: 7.5000e-06 eta: 0:13:40 time: 0.1774 data_time: 0.0100 memory: 10464 grad_norm: 10.0726 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3507 loss: 1.3507 2022/09/07 22:29:08 - mmengine - INFO - Epoch(train) [49][520/1793] lr: 7.5000e-06 eta: 0:13:35 time: 0.1807 data_time: 0.0067 memory: 10464 grad_norm: 9.8577 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2207 loss: 1.2207 2022/09/07 22:29:12 - mmengine - INFO - Epoch(train) [49][540/1793] lr: 7.5000e-06 eta: 0:13:29 time: 0.1768 data_time: 0.0073 memory: 10464 grad_norm: 10.3535 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1041 loss: 1.1041 2022/09/07 22:29:15 - mmengine - INFO - Epoch(train) [49][560/1793] lr: 7.5000e-06 eta: 0:13:24 time: 0.1815 data_time: 0.0098 memory: 10464 grad_norm: 9.9367 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1250 loss: 1.1250 2022/09/07 22:29:19 - mmengine - INFO - Epoch(train) [49][580/1793] lr: 7.5000e-06 eta: 0:13:19 time: 0.1802 data_time: 0.0067 memory: 10464 grad_norm: 9.6963 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1371 loss: 1.1371 2022/09/07 22:29:23 - mmengine - INFO - Epoch(train) [49][600/1793] lr: 7.5000e-06 eta: 0:13:13 time: 0.1749 data_time: 0.0080 memory: 10464 grad_norm: 10.0256 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.1661 loss: 1.1661 2022/09/07 22:29:26 - mmengine - INFO - Epoch(train) [49][620/1793] lr: 7.5000e-06 eta: 0:13:08 time: 0.1755 data_time: 0.0100 memory: 10464 grad_norm: 9.9234 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0362 loss: 1.0362 2022/09/07 22:29:30 - mmengine - INFO - Epoch(train) [49][640/1793] lr: 7.5000e-06 eta: 0:13:02 time: 0.1773 data_time: 0.0070 memory: 10464 grad_norm: 9.3000 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 0.9593 loss: 0.9593 2022/09/07 22:29:33 - mmengine - INFO - Epoch(train) [49][660/1793] lr: 7.5000e-06 eta: 0:12:57 time: 0.1722 data_time: 0.0070 memory: 10464 grad_norm: 9.9403 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.3350 loss: 1.3350 2022/09/07 22:29:37 - mmengine - INFO - Epoch(train) [49][680/1793] lr: 7.5000e-06 eta: 0:12:52 time: 0.1790 data_time: 0.0089 memory: 10464 grad_norm: 9.8730 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0449 loss: 1.0449 2022/09/07 22:29:40 - mmengine - INFO - Epoch(train) [49][700/1793] lr: 7.5000e-06 eta: 0:12:46 time: 0.1741 data_time: 0.0075 memory: 10464 grad_norm: 9.0832 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9526 loss: 0.9526 2022/09/07 22:29:44 - mmengine - INFO - Epoch(train) [49][720/1793] lr: 7.5000e-06 eta: 0:12:41 time: 0.1732 data_time: 0.0068 memory: 10464 grad_norm: 9.9252 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0044 loss: 1.0044 2022/09/07 22:29:47 - mmengine - INFO - Epoch(train) [49][740/1793] lr: 7.5000e-06 eta: 0:12:36 time: 0.1763 data_time: 0.0094 memory: 10464 grad_norm: 10.0361 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2296 loss: 1.2296 2022/09/07 22:29:51 - mmengine - INFO - Epoch(train) [49][760/1793] lr: 7.5000e-06 eta: 0:12:30 time: 0.1780 data_time: 0.0077 memory: 10464 grad_norm: 10.1883 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1415 loss: 1.1415 2022/09/07 22:29:54 - mmengine - INFO - Epoch(train) [49][780/1793] lr: 7.5000e-06 eta: 0:12:25 time: 0.1726 data_time: 0.0072 memory: 10464 grad_norm: 9.6144 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1477 loss: 1.1477 2022/09/07 22:29:58 - mmengine - INFO - Epoch(train) [49][800/1793] lr: 7.5000e-06 eta: 0:12:19 time: 0.1785 data_time: 0.0093 memory: 10464 grad_norm: 10.1584 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0773 loss: 1.0773 2022/09/07 22:30:01 - mmengine - INFO - Epoch(train) [49][820/1793] lr: 7.5000e-06 eta: 0:12:14 time: 0.1830 data_time: 0.0082 memory: 10464 grad_norm: 9.8425 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0290 loss: 1.0290 2022/09/07 22:30:05 - mmengine - INFO - Epoch(train) [49][840/1793] lr: 7.5000e-06 eta: 0:12:09 time: 0.1755 data_time: 0.0076 memory: 10464 grad_norm: 9.5426 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1097 loss: 1.1097 2022/09/07 22:30:09 - mmengine - INFO - Epoch(train) [49][860/1793] lr: 7.5000e-06 eta: 0:12:03 time: 0.1819 data_time: 0.0089 memory: 10464 grad_norm: 10.0814 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0827 loss: 1.0827 2022/09/07 22:30:12 - mmengine - INFO - Epoch(train) [49][880/1793] lr: 7.5000e-06 eta: 0:11:58 time: 0.1822 data_time: 0.0074 memory: 10464 grad_norm: 9.9346 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.9833 loss: 0.9833 2022/09/07 22:30:16 - mmengine - INFO - Epoch(train) [49][900/1793] lr: 7.5000e-06 eta: 0:11:53 time: 0.1744 data_time: 0.0070 memory: 10464 grad_norm: 9.7781 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2881 loss: 1.2881 2022/09/07 22:30:19 - mmengine - INFO - Epoch(train) [49][920/1793] lr: 7.5000e-06 eta: 0:11:47 time: 0.1794 data_time: 0.0093 memory: 10464 grad_norm: 9.8320 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.1191 loss: 1.1191 2022/09/07 22:30:22 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:30:23 - mmengine - INFO - Epoch(train) [49][940/1793] lr: 7.5000e-06 eta: 0:11:42 time: 0.1768 data_time: 0.0077 memory: 10464 grad_norm: 9.6542 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0873 loss: 1.0873 2022/09/07 22:30:26 - mmengine - INFO - Epoch(train) [49][960/1793] lr: 7.5000e-06 eta: 0:11:37 time: 0.1787 data_time: 0.0070 memory: 10464 grad_norm: 10.1231 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0988 loss: 1.0988 2022/09/07 22:30:30 - mmengine - INFO - Epoch(train) [49][980/1793] lr: 7.5000e-06 eta: 0:11:31 time: 0.1913 data_time: 0.0107 memory: 10464 grad_norm: 9.6630 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1146 loss: 1.1146 2022/09/07 22:30:34 - mmengine - INFO - Epoch(train) [49][1000/1793] lr: 7.5000e-06 eta: 0:11:26 time: 0.1718 data_time: 0.0071 memory: 10464 grad_norm: 9.9943 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0237 loss: 1.0237 2022/09/07 22:30:37 - mmengine - INFO - Epoch(train) [49][1020/1793] lr: 7.5000e-06 eta: 0:11:20 time: 0.1765 data_time: 0.0066 memory: 10464 grad_norm: 10.1702 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9794 loss: 0.9794 2022/09/07 22:30:41 - mmengine - INFO - Epoch(train) [49][1040/1793] lr: 7.5000e-06 eta: 0:11:15 time: 0.1783 data_time: 0.0107 memory: 10464 grad_norm: 10.2986 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1964 loss: 1.1964 2022/09/07 22:30:44 - mmengine - INFO - Epoch(train) [49][1060/1793] lr: 7.5000e-06 eta: 0:11:10 time: 0.1732 data_time: 0.0070 memory: 10464 grad_norm: 10.1214 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0772 loss: 1.0772 2022/09/07 22:30:48 - mmengine - INFO - Epoch(train) [49][1080/1793] lr: 7.5000e-06 eta: 0:11:04 time: 0.1744 data_time: 0.0070 memory: 10464 grad_norm: 10.3024 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.1152 loss: 1.1152 2022/09/07 22:30:51 - mmengine - INFO - Epoch(train) [49][1100/1793] lr: 7.5000e-06 eta: 0:10:59 time: 0.1803 data_time: 0.0098 memory: 10464 grad_norm: 9.8752 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0756 loss: 1.0756 2022/09/07 22:30:55 - mmengine - INFO - Epoch(train) [49][1120/1793] lr: 7.5000e-06 eta: 0:10:54 time: 0.1732 data_time: 0.0077 memory: 10464 grad_norm: 9.8800 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1898 loss: 1.1898 2022/09/07 22:30:58 - mmengine - INFO - Epoch(train) [49][1140/1793] lr: 7.5000e-06 eta: 0:10:48 time: 0.1767 data_time: 0.0071 memory: 10464 grad_norm: 10.1144 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1283 loss: 1.1283 2022/09/07 22:31:02 - mmengine - INFO - Epoch(train) [49][1160/1793] lr: 7.5000e-06 eta: 0:10:43 time: 0.1771 data_time: 0.0100 memory: 10464 grad_norm: 9.8781 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2836 loss: 1.2836 2022/09/07 22:31:05 - mmengine - INFO - Epoch(train) [49][1180/1793] lr: 7.5000e-06 eta: 0:10:38 time: 0.1746 data_time: 0.0070 memory: 10464 grad_norm: 9.7136 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0697 loss: 1.0697 2022/09/07 22:31:09 - mmengine - INFO - Epoch(train) [49][1200/1793] lr: 7.5000e-06 eta: 0:10:32 time: 0.1782 data_time: 0.0071 memory: 10464 grad_norm: 9.9929 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.8646 loss: 0.8646 2022/09/07 22:31:13 - mmengine - INFO - Epoch(train) [49][1220/1793] lr: 7.5000e-06 eta: 0:10:27 time: 0.1825 data_time: 0.0112 memory: 10464 grad_norm: 10.4490 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2646 loss: 1.2646 2022/09/07 22:31:16 - mmengine - INFO - Epoch(train) [49][1240/1793] lr: 7.5000e-06 eta: 0:10:22 time: 0.1777 data_time: 0.0076 memory: 10464 grad_norm: 10.3501 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0756 loss: 1.0756 2022/09/07 22:31:20 - mmengine - INFO - Epoch(train) [49][1260/1793] lr: 7.5000e-06 eta: 0:10:16 time: 0.1785 data_time: 0.0078 memory: 10464 grad_norm: 10.3055 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0896 loss: 1.0896 2022/09/07 22:31:23 - mmengine - INFO - Epoch(train) [49][1280/1793] lr: 7.5000e-06 eta: 0:10:11 time: 0.1763 data_time: 0.0092 memory: 10464 grad_norm: 10.3546 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2558 loss: 1.2558 2022/09/07 22:31:27 - mmengine - INFO - Epoch(train) [49][1300/1793] lr: 7.5000e-06 eta: 0:10:05 time: 0.1769 data_time: 0.0068 memory: 10464 grad_norm: 9.8807 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.0539 loss: 1.0539 2022/09/07 22:31:30 - mmengine - INFO - Epoch(train) [49][1320/1793] lr: 7.5000e-06 eta: 0:10:00 time: 0.1755 data_time: 0.0069 memory: 10464 grad_norm: 10.0435 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8147 loss: 0.8147 2022/09/07 22:31:34 - mmengine - INFO - Epoch(train) [49][1340/1793] lr: 7.5000e-06 eta: 0:09:55 time: 0.1787 data_time: 0.0098 memory: 10464 grad_norm: 9.7128 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2383 loss: 1.2383 2022/09/07 22:31:38 - mmengine - INFO - Epoch(train) [49][1360/1793] lr: 7.5000e-06 eta: 0:09:49 time: 0.1760 data_time: 0.0068 memory: 10464 grad_norm: 9.8083 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.8733 loss: 0.8733 2022/09/07 22:31:41 - mmengine - INFO - Epoch(train) [49][1380/1793] lr: 7.5000e-06 eta: 0:09:44 time: 0.1775 data_time: 0.0075 memory: 10464 grad_norm: 10.1237 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3881 loss: 1.3881 2022/09/07 22:31:45 - mmengine - INFO - Epoch(train) [49][1400/1793] lr: 7.5000e-06 eta: 0:09:39 time: 0.1766 data_time: 0.0101 memory: 10464 grad_norm: 9.6042 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0780 loss: 1.0780 2022/09/07 22:31:48 - mmengine - INFO - Epoch(train) [49][1420/1793] lr: 7.5000e-06 eta: 0:09:33 time: 0.1919 data_time: 0.0069 memory: 10464 grad_norm: 9.7360 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 0.9249 loss: 0.9249 2022/09/07 22:31:52 - mmengine - INFO - Epoch(train) [49][1440/1793] lr: 7.5000e-06 eta: 0:09:28 time: 0.1784 data_time: 0.0074 memory: 10464 grad_norm: 10.3821 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3433 loss: 1.3433 2022/09/07 22:31:56 - mmengine - INFO - Epoch(train) [49][1460/1793] lr: 7.5000e-06 eta: 0:09:23 time: 0.1768 data_time: 0.0096 memory: 10464 grad_norm: 9.8156 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1674 loss: 1.1674 2022/09/07 22:31:59 - mmengine - INFO - Epoch(train) [49][1480/1793] lr: 7.5000e-06 eta: 0:09:17 time: 0.1794 data_time: 0.0069 memory: 10464 grad_norm: 9.8561 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0182 loss: 1.0182 2022/09/07 22:32:03 - mmengine - INFO - Epoch(train) [49][1500/1793] lr: 7.5000e-06 eta: 0:09:12 time: 0.1794 data_time: 0.0075 memory: 10464 grad_norm: 9.9380 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0098 loss: 1.0098 2022/09/07 22:32:06 - mmengine - INFO - Epoch(train) [49][1520/1793] lr: 7.5000e-06 eta: 0:09:07 time: 0.1792 data_time: 0.0101 memory: 10464 grad_norm: 10.1405 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.2114 loss: 1.2114 2022/09/07 22:32:10 - mmengine - INFO - Epoch(train) [49][1540/1793] lr: 7.5000e-06 eta: 0:09:01 time: 0.1826 data_time: 0.0077 memory: 10464 grad_norm: 9.6155 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1553 loss: 1.1553 2022/09/07 22:32:14 - mmengine - INFO - Epoch(train) [49][1560/1793] lr: 7.5000e-06 eta: 0:08:56 time: 0.1791 data_time: 0.0077 memory: 10464 grad_norm: 9.9849 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1978 loss: 1.1978 2022/09/07 22:32:17 - mmengine - INFO - Epoch(train) [49][1580/1793] lr: 7.5000e-06 eta: 0:08:51 time: 0.1800 data_time: 0.0097 memory: 10464 grad_norm: 9.9746 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9585 loss: 0.9585 2022/09/07 22:32:21 - mmengine - INFO - Epoch(train) [49][1600/1793] lr: 7.5000e-06 eta: 0:08:45 time: 0.1754 data_time: 0.0074 memory: 10464 grad_norm: 10.2634 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0568 loss: 1.0568 2022/09/07 22:32:24 - mmengine - INFO - Epoch(train) [49][1620/1793] lr: 7.5000e-06 eta: 0:08:40 time: 0.1740 data_time: 0.0070 memory: 10464 grad_norm: 9.5727 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1622 loss: 1.1622 2022/09/07 22:32:28 - mmengine - INFO - Epoch(train) [49][1640/1793] lr: 7.5000e-06 eta: 0:08:35 time: 0.1882 data_time: 0.0122 memory: 10464 grad_norm: 10.1901 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2587 loss: 1.2587 2022/09/07 22:32:32 - mmengine - INFO - Epoch(train) [49][1660/1793] lr: 7.5000e-06 eta: 0:08:29 time: 0.1827 data_time: 0.0071 memory: 10464 grad_norm: 9.8207 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 0.8468 loss: 0.8468 2022/09/07 22:32:35 - mmengine - INFO - Epoch(train) [49][1680/1793] lr: 7.5000e-06 eta: 0:08:24 time: 0.1737 data_time: 0.0073 memory: 10464 grad_norm: 9.6997 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0186 loss: 1.0186 2022/09/07 22:32:39 - mmengine - INFO - Epoch(train) [49][1700/1793] lr: 7.5000e-06 eta: 0:08:19 time: 0.1792 data_time: 0.0092 memory: 10464 grad_norm: 10.3119 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.0385 loss: 1.0385 2022/09/07 22:32:42 - mmengine - INFO - Epoch(train) [49][1720/1793] lr: 7.5000e-06 eta: 0:08:13 time: 0.1779 data_time: 0.0075 memory: 10464 grad_norm: 10.5160 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2319 loss: 1.2319 2022/09/07 22:32:46 - mmengine - INFO - Epoch(train) [49][1740/1793] lr: 7.5000e-06 eta: 0:08:08 time: 0.1752 data_time: 0.0070 memory: 10464 grad_norm: 9.8311 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2083 loss: 1.2083 2022/09/07 22:32:50 - mmengine - INFO - Epoch(train) [49][1760/1793] lr: 7.5000e-06 eta: 0:08:03 time: 0.1876 data_time: 0.0089 memory: 10464 grad_norm: 9.8205 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.7986 loss: 0.7986 2022/09/07 22:32:53 - mmengine - INFO - Epoch(train) [49][1780/1793] lr: 7.5000e-06 eta: 0:07:57 time: 0.1796 data_time: 0.0089 memory: 10464 grad_norm: 10.2555 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0748 loss: 1.0748 2022/09/07 22:32:55 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:32:55 - mmengine - INFO - Epoch(train) [49][1793/1793] lr: 7.5000e-06 eta: 0:07:57 time: 0.1693 data_time: 0.0065 memory: 10464 grad_norm: 10.6102 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 1.3141 loss: 1.3141 2022/09/07 22:32:55 - mmengine - INFO - Saving checkpoint at 49 epochs 2022/09/07 22:32:59 - mmengine - INFO - Epoch(val) [49][20/241] eta: 0:00:12 time: 0.0584 data_time: 0.0092 memory: 1482 2022/09/07 22:33:00 - mmengine - INFO - Epoch(val) [49][40/241] eta: 0:00:10 time: 0.0536 data_time: 0.0050 memory: 1482 2022/09/07 22:33:01 - mmengine - INFO - Epoch(val) [49][60/241] eta: 0:00:09 time: 0.0537 data_time: 0.0050 memory: 1482 2022/09/07 22:33:02 - mmengine - INFO - Epoch(val) [49][80/241] eta: 0:00:08 time: 0.0539 data_time: 0.0053 memory: 1482 2022/09/07 22:33:03 - mmengine - INFO - Epoch(val) [49][100/241] eta: 0:00:07 time: 0.0532 data_time: 0.0047 memory: 1482 2022/09/07 22:33:04 - mmengine - INFO - Epoch(val) [49][120/241] eta: 0:00:06 time: 0.0533 data_time: 0.0050 memory: 1482 2022/09/07 22:33:05 - mmengine - INFO - Epoch(val) [49][140/241] eta: 0:00:05 time: 0.0536 data_time: 0.0051 memory: 1482 2022/09/07 22:33:06 - mmengine - INFO - Epoch(val) [49][160/241] eta: 0:00:04 time: 0.0542 data_time: 0.0056 memory: 1482 2022/09/07 22:33:07 - mmengine - INFO - Epoch(val) [49][180/241] eta: 0:00:03 time: 0.0537 data_time: 0.0052 memory: 1482 2022/09/07 22:33:09 - mmengine - INFO - Epoch(val) [49][200/241] eta: 0:00:02 time: 0.0536 data_time: 0.0051 memory: 1482 2022/09/07 22:33:10 - mmengine - INFO - Epoch(val) [49][220/241] eta: 0:00:01 time: 0.0620 data_time: 0.0054 memory: 1482 2022/09/07 22:33:11 - mmengine - INFO - Epoch(val) [49][240/241] eta: 0:00:00 time: 0.0550 data_time: 0.0065 memory: 1482 2022/09/07 22:33:11 - mmengine - INFO - Epoch(val) [49][241/241] acc/top1: 0.4816 acc/top5: 0.7802 acc/mean1: 0.4463 2022/09/07 22:33:15 - mmengine - INFO - Epoch(train) [50][20/1793] lr: 7.5000e-06 eta: 0:07:49 time: 0.1817 data_time: 0.0126 memory: 10464 grad_norm: 9.8255 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1560 loss: 1.1560 2022/09/07 22:33:19 - mmengine - INFO - Epoch(train) [50][40/1793] lr: 7.5000e-06 eta: 0:07:43 time: 0.1766 data_time: 0.0078 memory: 10464 grad_norm: 10.2760 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 1.2650 loss: 1.2650 2022/09/07 22:33:22 - mmengine - INFO - Epoch(train) [50][60/1793] lr: 7.5000e-06 eta: 0:07:38 time: 0.1727 data_time: 0.0073 memory: 10464 grad_norm: 9.8731 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.8943 loss: 0.8943 2022/09/07 22:33:26 - mmengine - INFO - Epoch(train) [50][80/1793] lr: 7.5000e-06 eta: 0:07:33 time: 0.1812 data_time: 0.0101 memory: 10464 grad_norm: 10.0636 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0576 loss: 1.0576 2022/09/07 22:33:29 - mmengine - INFO - Epoch(train) [50][100/1793] lr: 7.5000e-06 eta: 0:07:27 time: 0.1799 data_time: 0.0073 memory: 10464 grad_norm: 10.5418 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.0285 loss: 1.0285 2022/09/07 22:33:33 - mmengine - INFO - Epoch(train) [50][120/1793] lr: 7.5000e-06 eta: 0:07:22 time: 0.1779 data_time: 0.0077 memory: 10464 grad_norm: 10.1297 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.2060 loss: 1.2060 2022/09/07 22:33:37 - mmengine - INFO - Epoch(train) [50][140/1793] lr: 7.5000e-06 eta: 0:07:17 time: 0.1783 data_time: 0.0114 memory: 10464 grad_norm: 9.9685 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.8205 loss: 0.8205 2022/09/07 22:33:37 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:33:40 - mmengine - INFO - Epoch(train) [50][160/1793] lr: 7.5000e-06 eta: 0:07:11 time: 0.1877 data_time: 0.0076 memory: 10464 grad_norm: 10.0929 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.0721 loss: 1.0721 2022/09/07 22:33:44 - mmengine - INFO - Epoch(train) [50][180/1793] lr: 7.5000e-06 eta: 0:07:06 time: 0.1744 data_time: 0.0071 memory: 10464 grad_norm: 10.0990 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0429 loss: 1.0429 2022/09/07 22:33:47 - mmengine - INFO - Epoch(train) [50][200/1793] lr: 7.5000e-06 eta: 0:07:01 time: 0.1795 data_time: 0.0106 memory: 10464 grad_norm: 9.9025 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1718 loss: 1.1718 2022/09/07 22:33:51 - mmengine - INFO - Epoch(train) [50][220/1793] lr: 7.5000e-06 eta: 0:06:55 time: 0.1892 data_time: 0.0074 memory: 10464 grad_norm: 9.5856 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 0.7243 loss: 0.7243 2022/09/07 22:33:55 - mmengine - INFO - Epoch(train) [50][240/1793] lr: 7.5000e-06 eta: 0:06:50 time: 0.1770 data_time: 0.0068 memory: 10464 grad_norm: 9.6193 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0646 loss: 1.0646 2022/09/07 22:33:58 - mmengine - INFO - Epoch(train) [50][260/1793] lr: 7.5000e-06 eta: 0:06:45 time: 0.1840 data_time: 0.0093 memory: 10464 grad_norm: 10.0365 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 0.9908 loss: 0.9908 2022/09/07 22:34:02 - mmengine - INFO - Epoch(train) [50][280/1793] lr: 7.5000e-06 eta: 0:06:39 time: 0.1780 data_time: 0.0075 memory: 10464 grad_norm: 9.6884 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1523 loss: 1.1523 2022/09/07 22:34:06 - mmengine - INFO - Epoch(train) [50][300/1793] lr: 7.5000e-06 eta: 0:06:34 time: 0.1778 data_time: 0.0076 memory: 10464 grad_norm: 10.1683 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9910 loss: 0.9910 2022/09/07 22:34:09 - mmengine - INFO - Epoch(train) [50][320/1793] lr: 7.5000e-06 eta: 0:06:29 time: 0.1791 data_time: 0.0090 memory: 10464 grad_norm: 9.9354 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8101 loss: 0.8101 2022/09/07 22:34:13 - mmengine - INFO - Epoch(train) [50][340/1793] lr: 7.5000e-06 eta: 0:06:23 time: 0.1805 data_time: 0.0073 memory: 10464 grad_norm: 9.6247 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2656 loss: 1.2656 2022/09/07 22:34:16 - mmengine - INFO - Epoch(train) [50][360/1793] lr: 7.5000e-06 eta: 0:06:18 time: 0.1771 data_time: 0.0070 memory: 10464 grad_norm: 10.0318 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9771 loss: 0.9771 2022/09/07 22:34:20 - mmengine - INFO - Epoch(train) [50][380/1793] lr: 7.5000e-06 eta: 0:06:13 time: 0.1899 data_time: 0.0099 memory: 10464 grad_norm: 10.0828 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1123 loss: 1.1123 2022/09/07 22:34:24 - mmengine - INFO - Epoch(train) [50][400/1793] lr: 7.5000e-06 eta: 0:06:08 time: 0.1750 data_time: 0.0077 memory: 10464 grad_norm: 9.7427 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 0.8853 loss: 0.8853 2022/09/07 22:34:27 - mmengine - INFO - Epoch(train) [50][420/1793] lr: 7.5000e-06 eta: 0:06:02 time: 0.1734 data_time: 0.0070 memory: 10464 grad_norm: 9.6622 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9283 loss: 0.9283 2022/09/07 22:34:31 - mmengine - INFO - Epoch(train) [50][440/1793] lr: 7.5000e-06 eta: 0:05:57 time: 0.1842 data_time: 0.0097 memory: 10464 grad_norm: 10.2927 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2696 loss: 1.2696 2022/09/07 22:34:34 - mmengine - INFO - Epoch(train) [50][460/1793] lr: 7.5000e-06 eta: 0:05:52 time: 0.1747 data_time: 0.0072 memory: 10464 grad_norm: 9.8934 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2432 loss: 1.2432 2022/09/07 22:34:38 - mmengine - INFO - Epoch(train) [50][480/1793] lr: 7.5000e-06 eta: 0:05:46 time: 0.1739 data_time: 0.0067 memory: 10464 grad_norm: 10.1494 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1515 loss: 1.1515 2022/09/07 22:34:42 - mmengine - INFO - Epoch(train) [50][500/1793] lr: 7.5000e-06 eta: 0:05:41 time: 0.1928 data_time: 0.0111 memory: 10464 grad_norm: 10.0366 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2762 loss: 1.2762 2022/09/07 22:34:45 - mmengine - INFO - Epoch(train) [50][520/1793] lr: 7.5000e-06 eta: 0:05:36 time: 0.1739 data_time: 0.0071 memory: 10464 grad_norm: 9.8272 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.0525 loss: 1.0525 2022/09/07 22:34:49 - mmengine - INFO - Epoch(train) [50][540/1793] lr: 7.5000e-06 eta: 0:05:30 time: 0.1727 data_time: 0.0066 memory: 10464 grad_norm: 9.5273 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.0554 loss: 1.0554 2022/09/07 22:34:52 - mmengine - INFO - Epoch(train) [50][560/1793] lr: 7.5000e-06 eta: 0:05:25 time: 0.1844 data_time: 0.0108 memory: 10464 grad_norm: 10.2803 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2141 loss: 1.2141 2022/09/07 22:34:56 - mmengine - INFO - Epoch(train) [50][580/1793] lr: 7.5000e-06 eta: 0:05:20 time: 0.1737 data_time: 0.0070 memory: 10464 grad_norm: 9.8772 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1143 loss: 1.1143 2022/09/07 22:34:59 - mmengine - INFO - Epoch(train) [50][600/1793] lr: 7.5000e-06 eta: 0:05:14 time: 0.1796 data_time: 0.0071 memory: 10464 grad_norm: 10.0321 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9281 loss: 0.9281 2022/09/07 22:35:03 - mmengine - INFO - Epoch(train) [50][620/1793] lr: 7.5000e-06 eta: 0:05:09 time: 0.1777 data_time: 0.0105 memory: 10464 grad_norm: 9.1781 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1031 loss: 1.1031 2022/09/07 22:35:06 - mmengine - INFO - Epoch(train) [50][640/1793] lr: 7.5000e-06 eta: 0:05:04 time: 0.1736 data_time: 0.0072 memory: 10464 grad_norm: 9.8250 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9608 loss: 0.9608 2022/09/07 22:35:10 - mmengine - INFO - Epoch(train) [50][660/1793] lr: 7.5000e-06 eta: 0:04:59 time: 0.1788 data_time: 0.0071 memory: 10464 grad_norm: 9.7074 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1400 loss: 1.1400 2022/09/07 22:35:13 - mmengine - INFO - Epoch(train) [50][680/1793] lr: 7.5000e-06 eta: 0:04:53 time: 0.1763 data_time: 0.0092 memory: 10464 grad_norm: 9.9208 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.1832 loss: 1.1832 2022/09/07 22:35:17 - mmengine - INFO - Epoch(train) [50][700/1793] lr: 7.5000e-06 eta: 0:04:48 time: 0.1734 data_time: 0.0075 memory: 10464 grad_norm: 10.5059 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2537 loss: 1.2537 2022/09/07 22:35:20 - mmengine - INFO - Epoch(train) [50][720/1793] lr: 7.5000e-06 eta: 0:04:43 time: 0.1774 data_time: 0.0081 memory: 10464 grad_norm: 10.0017 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0195 loss: 1.0195 2022/09/07 22:35:24 - mmengine - INFO - Epoch(train) [50][740/1793] lr: 7.5000e-06 eta: 0:04:37 time: 0.1762 data_time: 0.0093 memory: 10464 grad_norm: 9.3011 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1023 loss: 1.1023 2022/09/07 22:35:27 - mmengine - INFO - Epoch(train) [50][760/1793] lr: 7.5000e-06 eta: 0:04:32 time: 0.1739 data_time: 0.0070 memory: 10464 grad_norm: 9.9246 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.0785 loss: 1.0785 2022/09/07 22:35:31 - mmengine - INFO - Epoch(train) [50][780/1793] lr: 7.5000e-06 eta: 0:04:27 time: 0.1754 data_time: 0.0077 memory: 10464 grad_norm: 10.0485 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1505 loss: 1.1505 2022/09/07 22:35:35 - mmengine - INFO - Epoch(train) [50][800/1793] lr: 7.5000e-06 eta: 0:04:21 time: 0.1756 data_time: 0.0097 memory: 10464 grad_norm: 9.6491 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.0769 loss: 1.0769 2022/09/07 22:35:38 - mmengine - INFO - Epoch(train) [50][820/1793] lr: 7.5000e-06 eta: 0:04:16 time: 0.1779 data_time: 0.0069 memory: 10464 grad_norm: 10.0706 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1999 loss: 1.1999 2022/09/07 22:35:42 - mmengine - INFO - Epoch(train) [50][840/1793] lr: 7.5000e-06 eta: 0:04:11 time: 0.1800 data_time: 0.0077 memory: 10464 grad_norm: 9.8700 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2184 loss: 1.2184 2022/09/07 22:35:45 - mmengine - INFO - Epoch(train) [50][860/1793] lr: 7.5000e-06 eta: 0:04:06 time: 0.1768 data_time: 0.0106 memory: 10464 grad_norm: 10.4287 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4822 loss: 1.4822 2022/09/07 22:35:49 - mmengine - INFO - Epoch(train) [50][880/1793] lr: 7.5000e-06 eta: 0:04:00 time: 0.1756 data_time: 0.0070 memory: 10464 grad_norm: 10.0214 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1505 loss: 1.1505 2022/09/07 22:35:52 - mmengine - INFO - Epoch(train) [50][900/1793] lr: 7.5000e-06 eta: 0:03:55 time: 0.1746 data_time: 0.0068 memory: 10464 grad_norm: 9.8736 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0942 loss: 1.0942 2022/09/07 22:35:56 - mmengine - INFO - Epoch(train) [50][920/1793] lr: 7.5000e-06 eta: 0:03:50 time: 0.1764 data_time: 0.0102 memory: 10464 grad_norm: 10.2387 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.2246 loss: 1.2246 2022/09/07 22:35:59 - mmengine - INFO - Epoch(train) [50][940/1793] lr: 7.5000e-06 eta: 0:03:44 time: 0.1824 data_time: 0.0069 memory: 10464 grad_norm: 10.1832 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.1351 loss: 1.1351 2022/09/07 22:36:03 - mmengine - INFO - Epoch(train) [50][960/1793] lr: 7.5000e-06 eta: 0:03:39 time: 0.1820 data_time: 0.0088 memory: 10464 grad_norm: 10.0422 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1694 loss: 1.1694 2022/09/07 22:36:07 - mmengine - INFO - Epoch(train) [50][980/1793] lr: 7.5000e-06 eta: 0:03:34 time: 0.1802 data_time: 0.0102 memory: 10464 grad_norm: 10.1050 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1094 loss: 1.1094 2022/09/07 22:36:10 - mmengine - INFO - Epoch(train) [50][1000/1793] lr: 7.5000e-06 eta: 0:03:29 time: 0.1871 data_time: 0.0066 memory: 10464 grad_norm: 9.7577 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9445 loss: 0.9445 2022/09/07 22:36:14 - mmengine - INFO - Epoch(train) [50][1020/1793] lr: 7.5000e-06 eta: 0:03:23 time: 0.1732 data_time: 0.0079 memory: 10464 grad_norm: 9.9271 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1469 loss: 1.1469 2022/09/07 22:36:18 - mmengine - INFO - Epoch(train) [50][1040/1793] lr: 7.5000e-06 eta: 0:03:18 time: 0.1836 data_time: 0.0092 memory: 10464 grad_norm: 10.2126 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1577 loss: 1.1577 2022/09/07 22:36:21 - mmengine - INFO - Epoch(train) [50][1060/1793] lr: 7.5000e-06 eta: 0:03:13 time: 0.1752 data_time: 0.0073 memory: 10464 grad_norm: 9.9459 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1529 loss: 1.1529 2022/09/07 22:36:25 - mmengine - INFO - Epoch(train) [50][1080/1793] lr: 7.5000e-06 eta: 0:03:07 time: 0.1731 data_time: 0.0071 memory: 10464 grad_norm: 10.1366 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.0371 loss: 1.0371 2022/09/07 22:36:28 - mmengine - INFO - Epoch(train) [50][1100/1793] lr: 7.5000e-06 eta: 0:03:02 time: 0.1866 data_time: 0.0105 memory: 10464 grad_norm: 9.8060 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.0471 loss: 1.0471 2022/09/07 22:36:32 - mmengine - INFO - Epoch(train) [50][1120/1793] lr: 7.5000e-06 eta: 0:02:57 time: 0.1756 data_time: 0.0068 memory: 10464 grad_norm: 9.8445 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.1527 loss: 1.1527 2022/09/07 22:36:35 - mmengine - INFO - Epoch(train) [50][1140/1793] lr: 7.5000e-06 eta: 0:02:52 time: 0.1723 data_time: 0.0068 memory: 10464 grad_norm: 9.9793 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9954 loss: 0.9954 2022/09/07 22:36:36 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:36:39 - mmengine - INFO - Epoch(train) [50][1160/1793] lr: 7.5000e-06 eta: 0:02:46 time: 0.1819 data_time: 0.0101 memory: 10464 grad_norm: 9.9089 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0833 loss: 1.0833 2022/09/07 22:36:43 - mmengine - INFO - Epoch(train) [50][1180/1793] lr: 7.5000e-06 eta: 0:02:41 time: 0.1805 data_time: 0.0077 memory: 10464 grad_norm: 9.9225 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0547 loss: 1.0547 2022/09/07 22:36:46 - mmengine - INFO - Epoch(train) [50][1200/1793] lr: 7.5000e-06 eta: 0:02:36 time: 0.1781 data_time: 0.0074 memory: 10464 grad_norm: 9.9149 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1733 loss: 1.1733 2022/09/07 22:36:50 - mmengine - INFO - Epoch(train) [50][1220/1793] lr: 7.5000e-06 eta: 0:02:30 time: 0.1782 data_time: 0.0092 memory: 10464 grad_norm: 10.2598 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.2301 loss: 1.2301 2022/09/07 22:36:53 - mmengine - INFO - Epoch(train) [50][1240/1793] lr: 7.5000e-06 eta: 0:02:25 time: 0.1792 data_time: 0.0073 memory: 10464 grad_norm: 10.2841 top1_acc: 0.1667 top5_acc: 1.0000 loss_cls: 1.2131 loss: 1.2131 2022/09/07 22:36:57 - mmengine - INFO - Epoch(train) [50][1260/1793] lr: 7.5000e-06 eta: 0:02:20 time: 0.1775 data_time: 0.0074 memory: 10464 grad_norm: 9.7841 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0151 loss: 1.0151 2022/09/07 22:37:01 - mmengine - INFO - Epoch(train) [50][1280/1793] lr: 7.5000e-06 eta: 0:02:15 time: 0.1872 data_time: 0.0098 memory: 10464 grad_norm: 9.6053 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0282 loss: 1.0282 2022/09/07 22:37:04 - mmengine - INFO - Epoch(train) [50][1300/1793] lr: 7.5000e-06 eta: 0:02:09 time: 0.1773 data_time: 0.0074 memory: 10464 grad_norm: 10.1329 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0945 loss: 1.0945 2022/09/07 22:37:08 - mmengine - INFO - Epoch(train) [50][1320/1793] lr: 7.5000e-06 eta: 0:02:04 time: 0.1798 data_time: 0.0070 memory: 10464 grad_norm: 9.9012 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8751 loss: 0.8751 2022/09/07 22:37:11 - mmengine - INFO - Epoch(train) [50][1340/1793] lr: 7.5000e-06 eta: 0:01:59 time: 0.1878 data_time: 0.0098 memory: 10464 grad_norm: 9.8745 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.3302 loss: 1.3302 2022/09/07 22:37:15 - mmengine - INFO - Epoch(train) [50][1360/1793] lr: 7.5000e-06 eta: 0:01:53 time: 0.1770 data_time: 0.0070 memory: 10464 grad_norm: 9.6412 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0496 loss: 1.0496 2022/09/07 22:37:19 - mmengine - INFO - Epoch(train) [50][1380/1793] lr: 7.5000e-06 eta: 0:01:48 time: 0.1780 data_time: 0.0066 memory: 10464 grad_norm: 9.6758 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9588 loss: 0.9588 2022/09/07 22:37:22 - mmengine - INFO - Epoch(train) [50][1400/1793] lr: 7.5000e-06 eta: 0:01:43 time: 0.1856 data_time: 0.0118 memory: 10464 grad_norm: 10.1449 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0416 loss: 1.0416 2022/09/07 22:37:26 - mmengine - INFO - Epoch(train) [50][1420/1793] lr: 7.5000e-06 eta: 0:01:38 time: 0.1741 data_time: 0.0072 memory: 10464 grad_norm: 10.1447 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0072 loss: 1.0072 2022/09/07 22:37:29 - mmengine - INFO - Epoch(train) [50][1440/1793] lr: 7.5000e-06 eta: 0:01:32 time: 0.1743 data_time: 0.0078 memory: 10464 grad_norm: 10.2973 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1441 loss: 1.1441 2022/09/07 22:37:33 - mmengine - INFO - Epoch(train) [50][1460/1793] lr: 7.5000e-06 eta: 0:01:27 time: 0.1800 data_time: 0.0094 memory: 10464 grad_norm: 10.1722 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2785 loss: 1.2785 2022/09/07 22:37:36 - mmengine - INFO - Epoch(train) [50][1480/1793] lr: 7.5000e-06 eta: 0:01:22 time: 0.1735 data_time: 0.0068 memory: 10464 grad_norm: 10.1292 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9537 loss: 0.9537 2022/09/07 22:37:40 - mmengine - INFO - Epoch(train) [50][1500/1793] lr: 7.5000e-06 eta: 0:01:17 time: 0.1810 data_time: 0.0066 memory: 10464 grad_norm: 10.0928 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.2586 loss: 1.2586 2022/09/07 22:37:44 - mmengine - INFO - Epoch(train) [50][1520/1793] lr: 7.5000e-06 eta: 0:01:11 time: 0.1786 data_time: 0.0130 memory: 10464 grad_norm: 10.4505 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0475 loss: 1.0475 2022/09/07 22:37:47 - mmengine - INFO - Epoch(train) [50][1540/1793] lr: 7.5000e-06 eta: 0:01:06 time: 0.1774 data_time: 0.0076 memory: 10464 grad_norm: 10.1568 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2120 loss: 1.2120 2022/09/07 22:37:51 - mmengine - INFO - Epoch(train) [50][1560/1793] lr: 7.5000e-06 eta: 0:01:01 time: 0.1827 data_time: 0.0068 memory: 10464 grad_norm: 10.2813 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1379 loss: 1.1379 2022/09/07 22:37:54 - mmengine - INFO - Epoch(train) [50][1580/1793] lr: 7.5000e-06 eta: 0:00:56 time: 0.1777 data_time: 0.0100 memory: 10464 grad_norm: 9.7011 top1_acc: 0.3333 top5_acc: 1.0000 loss_cls: 0.8841 loss: 0.8841 2022/09/07 22:37:58 - mmengine - INFO - Epoch(train) [50][1600/1793] lr: 7.5000e-06 eta: 0:00:50 time: 0.1923 data_time: 0.0072 memory: 10464 grad_norm: 9.7711 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1478 loss: 1.1478 2022/09/07 22:38:02 - mmengine - INFO - Epoch(train) [50][1620/1793] lr: 7.5000e-06 eta: 0:00:45 time: 0.1759 data_time: 0.0077 memory: 10464 grad_norm: 9.8920 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9950 loss: 0.9950 2022/09/07 22:38:05 - mmengine - INFO - Epoch(train) [50][1640/1793] lr: 7.5000e-06 eta: 0:00:40 time: 0.1784 data_time: 0.0096 memory: 10464 grad_norm: 10.2306 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0651 loss: 1.0651 2022/09/07 22:38:09 - mmengine - INFO - Epoch(train) [50][1660/1793] lr: 7.5000e-06 eta: 0:00:34 time: 0.1742 data_time: 0.0069 memory: 10464 grad_norm: 9.8711 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 1.1219 loss: 1.1219 2022/09/07 22:38:12 - mmengine - INFO - Epoch(train) [50][1680/1793] lr: 7.5000e-06 eta: 0:00:29 time: 0.1808 data_time: 0.0078 memory: 10464 grad_norm: 10.3171 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.3936 loss: 1.3936 2022/09/07 22:38:16 - mmengine - INFO - Epoch(train) [50][1700/1793] lr: 7.5000e-06 eta: 0:00:24 time: 0.1761 data_time: 0.0091 memory: 10464 grad_norm: 10.2097 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.1832 loss: 1.1832 2022/09/07 22:38:20 - mmengine - INFO - Epoch(train) [50][1720/1793] lr: 7.5000e-06 eta: 0:00:19 time: 0.1810 data_time: 0.0070 memory: 10464 grad_norm: 9.5966 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0732 loss: 1.0732 2022/09/07 22:38:23 - mmengine - INFO - Epoch(train) [50][1740/1793] lr: 7.5000e-06 eta: 0:00:13 time: 0.1767 data_time: 0.0073 memory: 10464 grad_norm: 9.8877 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0155 loss: 1.0155 2022/09/07 22:38:27 - mmengine - INFO - Epoch(train) [50][1760/1793] lr: 7.5000e-06 eta: 0:00:08 time: 0.1781 data_time: 0.0098 memory: 10464 grad_norm: 10.1037 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0168 loss: 1.0168 2022/09/07 22:38:30 - mmengine - INFO - Epoch(train) [50][1780/1793] lr: 7.5000e-06 eta: 0:00:03 time: 0.1774 data_time: 0.0068 memory: 10464 grad_norm: 9.8920 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.1018 loss: 1.1018 2022/09/07 22:38:32 - mmengine - INFO - Exp name: tanet_imagenet-pretrained-r50_8xb6-1x1x16-50e_sthv1-rgb_20220907_154426 2022/09/07 22:38:32 - mmengine - INFO - Epoch(train) [50][1793/1793] lr: 7.5000e-06 eta: 0:00:03 time: 0.1750 data_time: 0.0069 memory: 10464 grad_norm: 9.9140 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 1.4164 loss: 1.4164 2022/09/07 22:38:32 - mmengine - INFO - Saving checkpoint at 50 epochs 2022/09/07 22:38:37 - mmengine - INFO - Epoch(val) [50][20/241] eta: 0:00:13 time: 0.0591 data_time: 0.0094 memory: 1482 2022/09/07 22:38:38 - mmengine - INFO - Epoch(val) [50][40/241] eta: 0:00:10 time: 0.0532 data_time: 0.0049 memory: 1482 2022/09/07 22:38:39 - mmengine - INFO - Epoch(val) [50][60/241] eta: 0:00:09 time: 0.0531 data_time: 0.0048 memory: 1482 2022/09/07 22:38:40 - mmengine - INFO - Epoch(val) [50][80/241] eta: 0:00:08 time: 0.0536 data_time: 0.0052 memory: 1482 2022/09/07 22:38:41 - mmengine - INFO - Epoch(val) [50][100/241] eta: 0:00:07 time: 0.0537 data_time: 0.0052 memory: 1482 2022/09/07 22:38:42 - mmengine - INFO - Epoch(val) [50][120/241] eta: 0:00:06 time: 0.0538 data_time: 0.0053 memory: 1482 2022/09/07 22:38:43 - mmengine - INFO - Epoch(val) [50][140/241] eta: 0:00:05 time: 0.0536 data_time: 0.0050 memory: 1482 2022/09/07 22:38:44 - mmengine - INFO - Epoch(val) [50][160/241] eta: 0:00:04 time: 0.0534 data_time: 0.0051 memory: 1482 2022/09/07 22:38:45 - mmengine - INFO - Epoch(val) [50][180/241] eta: 0:00:03 time: 0.0533 data_time: 0.0049 memory: 1482 2022/09/07 22:38:46 - mmengine - INFO - Epoch(val) [50][200/241] eta: 0:00:02 time: 0.0539 data_time: 0.0052 memory: 1482 2022/09/07 22:38:47 - mmengine - INFO - Epoch(val) [50][220/241] eta: 0:00:01 time: 0.0536 data_time: 0.0050 memory: 1482 2022/09/07 22:38:48 - mmengine - INFO - Epoch(val) [50][240/241] eta: 0:00:00 time: 0.0532 data_time: 0.0048 memory: 1482 2022/09/07 22:38:49 - mmengine - INFO - Epoch(val) [50][241/241] acc/top1: 0.4824 acc/top5: 0.7816 acc/mean1: 0.4457