2022/10/09 21:24:02 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.8.13 (default, Mar 28 2022, 11:38:47) [GCC 7.5.0] CUDA available: True numpy_random_seed: 1804182679 GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 11.2, V11.2.152 GCC: gcc (GCC) 5.4.0 PyTorch: 1.10.0+cu113 PyTorch compiling details: PyTorch built with: - GCC 7.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.2.3 (Git Hash 7336ca9f055cf1bfa13efb658fe15dc9b41f0740) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.3 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 - CuDNN 8.2 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.10.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, TorchVision: 0.11.0+cu113 OpenCV: 4.6.0 MMEngine: 0.1.0 Runtime environment: cudnn_benchmark: False mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: None Distributed launcher: slurm Distributed training: True GPU number: 8 ------------------------------------------------------------ 2022/10/09 21:24:02 - mmengine - INFO - Config: model = dict( type='Recognizer2D', backbone=dict( type='ResNet', pretrained='https://download.pytorch.org/models/resnet50-11ad3fa6.pth', depth=50, norm_eval=False), cls_head=dict( type='TSNHead', num_classes=400, in_channels=2048, spatial_type='avg', consensus=dict(type='AvgConsensus', dim=1), dropout_ratio=0.4, init_std=0.01, average_clips=None), data_preprocessor=dict( type='ActionDataPreprocessor', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], format_shape='NCHW'), train_cfg=None, test_cfg=None) train_cfg = dict( type='EpochBasedTrainLoop', max_epochs=100, val_begin=1, val_interval=1) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') param_scheduler = [ dict( type='MultiStepLR', begin=0, end=100, by_epoch=True, milestones=[40, 80], gamma=0.1) ] optim_wrapper = dict( optimizer=dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001), clip_grad=dict(max_norm=40, norm_type=2)) default_scope = 'mmaction' default_hooks = dict( runtime_info=dict(type='RuntimeInfoHook'), timer=dict(type='IterTimerHook'), logger=dict(type='LoggerHook', interval=20, ignore_last=False), param_scheduler=dict(type='ParamSchedulerHook'), checkpoint=dict( type='CheckpointHook', interval=3, save_best='auto', max_keep_ckpts=3), sampler_seed=dict(type='DistSamplerSeedHook')) env_cfg = dict( cudnn_benchmark=False, mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), dist_cfg=dict(backend='nccl')) log_processor = dict(type='LogProcessor', window_size=20, by_epoch=True) vis_backends = [dict(type='LocalVisBackend')] visualizer = dict( type='ActionVisualizer', vis_backends=[dict(type='LocalVisBackend')]) log_level = 'INFO' load_from = None resume = False file_client_args = dict( io_backend='petrel', path_mapping=dict( {'data/kinetics400': 's3://openmmlab/datasets/action/Kinetics400'})) dataset_type = 'VideoDataset' data_root = 'data/kinetics400/videos_train' data_root_val = 'data/kinetics400/videos_val' ann_file_train = 'data/kinetics400/kinetics400_train_list_videos.txt' ann_file_val = 'data/kinetics400/kinetics400_val_list_videos.txt' train_pipeline = [ dict( type='DecordInit', io_backend='petrel', path_mapping=dict( {'data/kinetics400': 's3://openmmlab/datasets/action/Kinetics400'})), dict(type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict( type='MultiScaleCrop', input_size=224, scales=(1, 0.875, 0.75, 0.66), random_crop=False, max_wh_scale_gap=1), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ] val_pipeline = [ dict( type='DecordInit', io_backend='petrel', path_mapping=dict( {'data/kinetics400': 's3://openmmlab/datasets/action/Kinetics400'})), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ] test_pipeline = [ dict( type='DecordInit', io_backend='petrel', path_mapping=dict( {'data/kinetics400': 's3://openmmlab/datasets/action/Kinetics400'})), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 224)), dict(type='ThreeCrop', crop_size=224), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ] train_dataloader = dict( batch_size=32, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='VideoDataset', ann_file='data/kinetics400/kinetics400_train_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_train'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics400': 's3://openmmlab/datasets/action/Kinetics400' })), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict( type='MultiScaleCrop', input_size=224, scales=(1, 0.875, 0.75, 0.66), random_crop=False, max_wh_scale_gap=1), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ])) val_dataloader = dict( batch_size=32, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='VideoDataset', ann_file='data/kinetics400/kinetics400_val_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_val'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics400': 's3://openmmlab/datasets/action/Kinetics400' })), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ], test_mode=True)) test_dataloader = dict( batch_size=1, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='VideoDataset', ann_file='data/kinetics400/kinetics400_val_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_val'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics400': 's3://openmmlab/datasets/action/Kinetics400' })), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 224)), dict(type='ThreeCrop', crop_size=224), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ], test_mode=True)) val_evaluator = dict(type='AccMetric') test_evaluator = dict(type='AccMetric') launcher = 'slurm' work_dir = './work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph' 2022/10/09 21:24:04 - mmengine - INFO - These parameters in pretrained checkpoint are not loaded: {'fc.bias', 'fc.weight'} 2022/10/09 21:24:04 - mmengine - INFO - Checkpoints will be saved to /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph. 2022/10/09 21:24:25 - mmengine - INFO - Epoch(train) [1][20/940] lr: 1.0000e-02 eta: 1 day, 2:19:15 time: 1.0083 data_time: 0.5456 memory: 21547 grad_norm: 0.8813 top1_acc: 0.0312 top5_acc: 0.0625 loss_cls: 5.9866 loss: 5.9866 2022/10/09 21:24:34 - mmengine - INFO - Epoch(train) [1][40/940] lr: 1.0000e-02 eta: 19:13:42 time: 0.4652 data_time: 0.0352 memory: 21547 grad_norm: 0.9348 top1_acc: 0.0312 top5_acc: 0.1562 loss_cls: 5.9166 loss: 5.9166 2022/10/09 21:24:45 - mmengine - INFO - Epoch(train) [1][60/940] lr: 1.0000e-02 eta: 17:36:40 time: 0.5513 data_time: 0.0405 memory: 21547 grad_norm: 1.1697 top1_acc: 0.0312 top5_acc: 0.0938 loss_cls: 5.7967 loss: 5.7967 2022/10/09 21:24:54 - mmengine - INFO - Epoch(train) [1][80/940] lr: 1.0000e-02 eta: 16:15:04 time: 0.4669 data_time: 0.0370 memory: 21547 grad_norm: 1.4310 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 5.6139 loss: 5.6139 2022/10/09 21:25:05 - mmengine - INFO - Epoch(train) [1][100/940] lr: 1.0000e-02 eta: 15:52:54 time: 0.5527 data_time: 0.0379 memory: 21547 grad_norm: 1.6848 top1_acc: 0.1562 top5_acc: 0.3438 loss_cls: 5.3469 loss: 5.3469 2022/10/09 21:25:15 - mmengine - INFO - Epoch(train) [1][120/940] lr: 1.0000e-02 eta: 15:15:45 time: 0.4672 data_time: 0.0242 memory: 21547 grad_norm: 1.9435 top1_acc: 0.1875 top5_acc: 0.2500 loss_cls: 5.0328 loss: 5.0328 2022/10/09 21:25:25 - mmengine - INFO - Epoch(train) [1][140/940] lr: 1.0000e-02 eta: 15:03:17 time: 0.5304 data_time: 0.0458 memory: 21547 grad_norm: 2.1696 top1_acc: 0.0938 top5_acc: 0.3125 loss_cls: 4.6468 loss: 4.6468 2022/10/09 21:25:35 - mmengine - INFO - Epoch(train) [1][160/940] lr: 1.0000e-02 eta: 14:49:17 time: 0.5068 data_time: 0.0240 memory: 21547 grad_norm: 2.3216 top1_acc: 0.0938 top5_acc: 0.4062 loss_cls: 4.3829 loss: 4.3829 2022/10/09 21:25:46 - mmengine - INFO - Epoch(train) [1][180/940] lr: 1.0000e-02 eta: 14:42:49 time: 0.5325 data_time: 0.0326 memory: 21547 grad_norm: 2.4438 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 4.2436 loss: 4.2436 2022/10/09 21:25:55 - mmengine - INFO - Epoch(train) [1][200/940] lr: 1.0000e-02 eta: 14:27:10 time: 0.4656 data_time: 0.0333 memory: 21547 grad_norm: 2.5159 top1_acc: 0.2188 top5_acc: 0.5312 loss_cls: 4.1071 loss: 4.1071 2022/10/09 21:26:06 - mmengine - INFO - Epoch(train) [1][220/940] lr: 1.0000e-02 eta: 14:24:08 time: 0.5347 data_time: 0.0267 memory: 21547 grad_norm: 2.5799 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.8828 loss: 3.8828 2022/10/09 21:26:16 - mmengine - INFO - Epoch(train) [1][240/940] lr: 1.0000e-02 eta: 14:19:31 time: 0.5188 data_time: 0.0264 memory: 21547 grad_norm: 2.6281 top1_acc: 0.2812 top5_acc: 0.5000 loss_cls: 3.8591 loss: 3.8591 2022/10/09 21:26:26 - mmengine - INFO - Epoch(train) [1][260/940] lr: 1.0000e-02 eta: 14:13:28 time: 0.5012 data_time: 0.0287 memory: 21547 grad_norm: 2.6878 top1_acc: 0.2812 top5_acc: 0.5000 loss_cls: 3.6184 loss: 3.6184 2022/10/09 21:26:37 - mmengine - INFO - Epoch(train) [1][280/940] lr: 1.0000e-02 eta: 14:08:33 time: 0.5039 data_time: 0.0250 memory: 21547 grad_norm: 2.7410 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 3.5696 loss: 3.5696 2022/10/09 21:26:47 - mmengine - INFO - Epoch(train) [1][300/940] lr: 1.0000e-02 eta: 14:05:59 time: 0.5203 data_time: 0.0278 memory: 21547 grad_norm: 2.7439 top1_acc: 0.2188 top5_acc: 0.4688 loss_cls: 3.4425 loss: 3.4425 2022/10/09 21:26:57 - mmengine - INFO - Epoch(train) [1][320/940] lr: 1.0000e-02 eta: 14:02:55 time: 0.5122 data_time: 0.0289 memory: 21547 grad_norm: 2.7891 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 3.5117 loss: 3.5117 2022/10/09 21:27:08 - mmengine - INFO - Epoch(train) [1][340/940] lr: 1.0000e-02 eta: 14:02:01 time: 0.5321 data_time: 0.0257 memory: 21547 grad_norm: 2.8022 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 3.4558 loss: 3.4558 2022/10/09 21:27:18 - mmengine - INFO - Epoch(train) [1][360/940] lr: 1.0000e-02 eta: 13:57:54 time: 0.4940 data_time: 0.0311 memory: 21547 grad_norm: 2.8199 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.4500 loss: 3.4500 2022/10/09 21:27:28 - mmengine - INFO - Epoch(train) [1][380/940] lr: 1.0000e-02 eta: 13:57:03 time: 0.5286 data_time: 0.0304 memory: 21547 grad_norm: 2.8376 top1_acc: 0.3125 top5_acc: 0.4688 loss_cls: 3.1719 loss: 3.1719 2022/10/09 21:27:37 - mmengine - INFO - Epoch(train) [1][400/940] lr: 1.0000e-02 eta: 13:50:53 time: 0.4597 data_time: 0.0279 memory: 21547 grad_norm: 2.8363 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 3.2247 loss: 3.2247 2022/10/09 21:27:48 - mmengine - INFO - Epoch(train) [1][420/940] lr: 1.0000e-02 eta: 13:50:07 time: 0.5248 data_time: 0.0262 memory: 21547 grad_norm: 2.8780 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.1126 loss: 3.1126 2022/10/09 21:27:57 - mmengine - INFO - Epoch(train) [1][440/940] lr: 1.0000e-02 eta: 13:42:45 time: 0.4308 data_time: 0.0311 memory: 21547 grad_norm: 2.8699 top1_acc: 0.1875 top5_acc: 0.5938 loss_cls: 3.2568 loss: 3.2568 2022/10/09 21:28:07 - mmengine - INFO - Epoch(train) [1][460/940] lr: 1.0000e-02 eta: 13:42:32 time: 0.5271 data_time: 0.0291 memory: 21547 grad_norm: 2.8664 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 3.2998 loss: 3.2998 2022/10/09 21:28:17 - mmengine - INFO - Epoch(train) [1][480/940] lr: 1.0000e-02 eta: 13:41:03 time: 0.5074 data_time: 0.0348 memory: 21547 grad_norm: 2.9210 top1_acc: 0.2812 top5_acc: 0.5625 loss_cls: 3.1241 loss: 3.1241 2022/10/09 21:28:28 - mmengine - INFO - Epoch(train) [1][500/940] lr: 1.0000e-02 eta: 13:40:21 time: 0.5182 data_time: 0.0376 memory: 21547 grad_norm: 2.9093 top1_acc: 0.2500 top5_acc: 0.5312 loss_cls: 3.0413 loss: 3.0413 2022/10/09 21:28:38 - mmengine - INFO - Epoch(train) [1][520/940] lr: 1.0000e-02 eta: 13:40:21 time: 0.5295 data_time: 0.0352 memory: 21547 grad_norm: 2.9052 top1_acc: 0.1875 top5_acc: 0.5938 loss_cls: 3.0821 loss: 3.0821 2022/10/09 21:28:48 - mmengine - INFO - Epoch(train) [1][540/940] lr: 1.0000e-02 eta: 13:37:50 time: 0.4860 data_time: 0.0284 memory: 21547 grad_norm: 2.9385 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.2830 loss: 3.2830 2022/10/09 21:28:58 - mmengine - INFO - Epoch(train) [1][560/940] lr: 1.0000e-02 eta: 13:35:23 time: 0.4840 data_time: 0.0362 memory: 21547 grad_norm: 2.9256 top1_acc: 0.4375 top5_acc: 0.5938 loss_cls: 2.9947 loss: 2.9947 2022/10/09 21:29:08 - mmengine - INFO - Epoch(train) [1][580/940] lr: 1.0000e-02 eta: 13:35:08 time: 0.5224 data_time: 0.0944 memory: 21547 grad_norm: 2.9373 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.0336 loss: 3.0336 2022/10/09 21:29:18 - mmengine - INFO - Epoch(train) [1][600/940] lr: 1.0000e-02 eta: 13:33:34 time: 0.4966 data_time: 0.0597 memory: 21547 grad_norm: 2.9502 top1_acc: 0.2188 top5_acc: 0.4688 loss_cls: 3.1057 loss: 3.1057 2022/10/09 21:29:28 - mmengine - INFO - Epoch(train) [1][620/940] lr: 1.0000e-02 eta: 13:32:56 time: 0.5136 data_time: 0.0329 memory: 21547 grad_norm: 2.9542 top1_acc: 0.2812 top5_acc: 0.5938 loss_cls: 3.0903 loss: 3.0903 2022/10/09 21:29:39 - mmengine - INFO - Epoch(train) [1][640/940] lr: 1.0000e-02 eta: 13:33:19 time: 0.5338 data_time: 0.0364 memory: 21547 grad_norm: 2.9718 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9108 loss: 2.9108 2022/10/09 21:29:50 - mmengine - INFO - Epoch(train) [1][660/940] lr: 1.0000e-02 eta: 13:34:52 time: 0.5590 data_time: 0.0293 memory: 21547 grad_norm: 2.9658 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 2.8961 loss: 2.8961 2022/10/09 21:29:59 - mmengine - INFO - Epoch(train) [1][680/940] lr: 1.0000e-02 eta: 13:32:05 time: 0.4671 data_time: 0.0237 memory: 21547 grad_norm: 3.0105 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9492 loss: 2.9492 2022/10/09 21:30:10 - mmengine - INFO - Epoch(train) [1][700/940] lr: 1.0000e-02 eta: 13:32:47 time: 0.5418 data_time: 0.0700 memory: 21547 grad_norm: 2.9825 top1_acc: 0.2500 top5_acc: 0.5938 loss_cls: 2.8538 loss: 2.8538 2022/10/09 21:30:20 - mmengine - INFO - Epoch(train) [1][720/940] lr: 1.0000e-02 eta: 13:30:55 time: 0.4835 data_time: 0.0223 memory: 21547 grad_norm: 3.0174 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.8324 loss: 2.8324 2022/10/09 21:30:30 - mmengine - INFO - Epoch(train) [1][740/940] lr: 1.0000e-02 eta: 13:29:48 time: 0.4991 data_time: 0.0793 memory: 21547 grad_norm: 3.0149 top1_acc: 0.3125 top5_acc: 0.7188 loss_cls: 2.8764 loss: 2.8764 2022/10/09 21:30:40 - mmengine - INFO - Epoch(train) [1][760/940] lr: 1.0000e-02 eta: 13:28:52 time: 0.5026 data_time: 0.0440 memory: 21547 grad_norm: 3.0139 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9205 loss: 2.9205 2022/10/09 21:30:50 - mmengine - INFO - Epoch(train) [1][780/940] lr: 1.0000e-02 eta: 13:28:22 time: 0.5122 data_time: 0.0292 memory: 21547 grad_norm: 3.0257 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8785 loss: 2.8785 2022/10/09 21:31:00 - mmengine - INFO - Epoch(train) [1][800/940] lr: 1.0000e-02 eta: 13:27:41 time: 0.5071 data_time: 0.0238 memory: 21547 grad_norm: 3.0508 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.9105 loss: 2.9105 2022/10/09 21:31:10 - mmengine - INFO - Epoch(train) [1][820/940] lr: 1.0000e-02 eta: 13:26:20 time: 0.4888 data_time: 0.0276 memory: 21547 grad_norm: 3.0820 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.8519 loss: 2.8519 2022/10/09 21:31:20 - mmengine - INFO - Epoch(train) [1][840/940] lr: 1.0000e-02 eta: 13:25:40 time: 0.5062 data_time: 0.0246 memory: 21547 grad_norm: 3.0094 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8201 loss: 2.8201 2022/10/09 21:31:30 - mmengine - INFO - Epoch(train) [1][860/940] lr: 1.0000e-02 eta: 13:24:42 time: 0.4968 data_time: 0.0276 memory: 21547 grad_norm: 3.0532 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8502 loss: 2.8502 2022/10/09 21:31:41 - mmengine - INFO - Epoch(train) [1][880/940] lr: 1.0000e-02 eta: 13:24:40 time: 0.5222 data_time: 0.0264 memory: 21547 grad_norm: 3.0694 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 2.8444 loss: 2.8444 2022/10/09 21:31:50 - mmengine - INFO - Epoch(train) [1][900/940] lr: 1.0000e-02 eta: 13:23:24 time: 0.4866 data_time: 0.0273 memory: 21547 grad_norm: 3.0680 top1_acc: 0.5000 top5_acc: 0.5938 loss_cls: 2.8361 loss: 2.8361 2022/10/09 21:32:01 - mmengine - INFO - Epoch(train) [1][920/940] lr: 1.0000e-02 eta: 13:23:21 time: 0.5217 data_time: 0.0268 memory: 21547 grad_norm: 3.0506 top1_acc: 0.2812 top5_acc: 0.5000 loss_cls: 2.7775 loss: 2.7775 2022/10/09 21:32:10 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 21:32:10 - mmengine - INFO - Epoch(train) [1][940/940] lr: 1.0000e-02 eta: 13:20:34 time: 0.4384 data_time: 0.0243 memory: 21547 grad_norm: 3.3189 top1_acc: 0.2857 top5_acc: 0.5714 loss_cls: 2.9281 loss: 2.9281 2022/10/09 21:32:26 - mmengine - INFO - Epoch(val) [1][20/78] eta: 0:00:45 time: 0.7930 data_time: 0.6865 memory: 3269 2022/10/09 21:32:34 - mmengine - INFO - Epoch(val) [1][40/78] eta: 0:00:16 time: 0.4248 data_time: 0.3197 memory: 3269 2022/10/09 21:32:45 - mmengine - INFO - Epoch(val) [1][60/78] eta: 0:00:09 time: 0.5460 data_time: 0.4399 memory: 3269 2022/10/09 21:32:55 - mmengine - INFO - Epoch(val) [1][78/78] acc/top1: 0.4502 acc/top5: 0.7218 acc/mean1: 0.4499 2022/10/09 21:32:56 - mmengine - INFO - The best checkpoint with 0.4502 acc/top1 at 1 epoch is saved to best_acc/top1_epoch_1.pth. 2022/10/09 21:33:09 - mmengine - INFO - Epoch(train) [2][20/940] lr: 1.0000e-02 eta: 13:25:54 time: 0.6865 data_time: 0.3201 memory: 21547 grad_norm: 3.0626 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8116 loss: 2.8116 2022/10/09 21:33:19 - mmengine - INFO - Epoch(train) [2][40/940] lr: 1.0000e-02 eta: 13:24:09 time: 0.4702 data_time: 0.0982 memory: 21547 grad_norm: 3.0584 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.8114 loss: 2.8114 2022/10/09 21:33:30 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 21:33:30 - mmengine - INFO - Epoch(train) [2][60/940] lr: 1.0000e-02 eta: 13:25:40 time: 0.5733 data_time: 0.1268 memory: 21547 grad_norm: 3.0861 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.6804 loss: 2.6804 2022/10/09 21:33:40 - mmengine - INFO - Epoch(train) [2][80/940] lr: 1.0000e-02 eta: 13:23:59 time: 0.4698 data_time: 0.0239 memory: 21547 grad_norm: 3.0758 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 2.7134 loss: 2.7134 2022/10/09 21:33:51 - mmengine - INFO - Epoch(train) [2][100/940] lr: 1.0000e-02 eta: 13:24:57 time: 0.5571 data_time: 0.0272 memory: 21547 grad_norm: 3.0666 top1_acc: 0.3125 top5_acc: 0.6562 loss_cls: 2.7355 loss: 2.7355 2022/10/09 21:34:00 - mmengine - INFO - Epoch(train) [2][120/940] lr: 1.0000e-02 eta: 13:23:29 time: 0.4754 data_time: 0.0328 memory: 21547 grad_norm: 3.0658 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.6966 loss: 2.6966 2022/10/09 21:34:11 - mmengine - INFO - Epoch(train) [2][140/940] lr: 1.0000e-02 eta: 13:24:06 time: 0.5465 data_time: 0.0262 memory: 21547 grad_norm: 3.0946 top1_acc: 0.3125 top5_acc: 0.4688 loss_cls: 2.7245 loss: 2.7245 2022/10/09 21:34:21 - mmengine - INFO - Epoch(train) [2][160/940] lr: 1.0000e-02 eta: 13:22:29 time: 0.4678 data_time: 0.0260 memory: 21547 grad_norm: 3.0839 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.8370 loss: 2.8370 2022/10/09 21:34:32 - mmengine - INFO - Epoch(train) [2][180/940] lr: 1.0000e-02 eta: 13:23:18 time: 0.5537 data_time: 0.0285 memory: 21547 grad_norm: 3.0900 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 2.8140 loss: 2.8140 2022/10/09 21:34:41 - mmengine - INFO - Epoch(train) [2][200/940] lr: 1.0000e-02 eta: 13:22:01 time: 0.4783 data_time: 0.0253 memory: 21547 grad_norm: 3.1266 top1_acc: 0.2500 top5_acc: 0.5312 loss_cls: 2.7150 loss: 2.7150 2022/10/09 21:34:51 - mmengine - INFO - Epoch(train) [2][220/940] lr: 1.0000e-02 eta: 13:20:44 time: 0.4767 data_time: 0.0256 memory: 21547 grad_norm: 3.1250 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.5357 loss: 2.5357 2022/10/09 21:35:00 - mmengine - INFO - Epoch(train) [2][240/940] lr: 1.0000e-02 eta: 13:19:15 time: 0.4674 data_time: 0.0264 memory: 21547 grad_norm: 3.1388 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.5670 loss: 2.5670 2022/10/09 21:35:10 - mmengine - INFO - Epoch(train) [2][260/940] lr: 1.0000e-02 eta: 13:18:58 time: 0.5124 data_time: 0.0296 memory: 21547 grad_norm: 3.1325 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.6996 loss: 2.6996 2022/10/09 21:35:21 - mmengine - INFO - Epoch(train) [2][280/940] lr: 1.0000e-02 eta: 13:18:35 time: 0.5083 data_time: 0.0276 memory: 21547 grad_norm: 3.1562 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 2.6701 loss: 2.6701 2022/10/09 21:35:32 - mmengine - INFO - Epoch(train) [2][300/940] lr: 1.0000e-02 eta: 13:19:33 time: 0.5622 data_time: 0.0289 memory: 21547 grad_norm: 3.1392 top1_acc: 0.3438 top5_acc: 0.5312 loss_cls: 2.5624 loss: 2.5624 2022/10/09 21:35:41 - mmengine - INFO - Epoch(train) [2][320/940] lr: 1.0000e-02 eta: 13:17:31 time: 0.4409 data_time: 0.0238 memory: 21547 grad_norm: 3.1640 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.5510 loss: 2.5510 2022/10/09 21:35:51 - mmengine - INFO - Epoch(train) [2][340/940] lr: 1.0000e-02 eta: 13:17:59 time: 0.5428 data_time: 0.0879 memory: 21547 grad_norm: 3.0972 top1_acc: 0.3125 top5_acc: 0.4688 loss_cls: 2.5698 loss: 2.5698 2022/10/09 21:36:01 - mmengine - INFO - Epoch(train) [2][360/940] lr: 1.0000e-02 eta: 13:17:01 time: 0.4826 data_time: 0.0319 memory: 21547 grad_norm: 3.1497 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.7098 loss: 2.7098 2022/10/09 21:36:12 - mmengine - INFO - Epoch(train) [2][380/940] lr: 1.0000e-02 eta: 13:16:56 time: 0.5197 data_time: 0.0292 memory: 21547 grad_norm: 3.1371 top1_acc: 0.3125 top5_acc: 0.5312 loss_cls: 2.6774 loss: 2.6774 2022/10/09 21:36:21 - mmengine - INFO - Epoch(train) [2][400/940] lr: 1.0000e-02 eta: 13:15:46 time: 0.4728 data_time: 0.0353 memory: 21547 grad_norm: 3.1248 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.6018 loss: 2.6018 2022/10/09 21:36:31 - mmengine - INFO - Epoch(train) [2][420/940] lr: 1.0000e-02 eta: 13:15:28 time: 0.5097 data_time: 0.0370 memory: 21547 grad_norm: 3.1751 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.6714 loss: 2.6714 2022/10/09 21:36:41 - mmengine - INFO - Epoch(train) [2][440/940] lr: 1.0000e-02 eta: 13:14:52 time: 0.4959 data_time: 0.0266 memory: 21547 grad_norm: 3.1495 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.6843 loss: 2.6843 2022/10/09 21:36:51 - mmengine - INFO - Epoch(train) [2][460/940] lr: 1.0000e-02 eta: 13:14:27 time: 0.5042 data_time: 0.0285 memory: 21547 grad_norm: 3.1631 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.5657 loss: 2.5657 2022/10/09 21:37:02 - mmengine - INFO - Epoch(train) [2][480/940] lr: 1.0000e-02 eta: 13:14:26 time: 0.5215 data_time: 0.0220 memory: 21547 grad_norm: 3.1508 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.5263 loss: 2.5263 2022/10/09 21:37:12 - mmengine - INFO - Epoch(train) [2][500/940] lr: 1.0000e-02 eta: 13:13:56 time: 0.4999 data_time: 0.0313 memory: 21547 grad_norm: 3.1786 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.6629 loss: 2.6629 2022/10/09 21:37:21 - mmengine - INFO - Epoch(train) [2][520/940] lr: 1.0000e-02 eta: 13:13:06 time: 0.4834 data_time: 0.0286 memory: 21547 grad_norm: 3.1611 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5156 loss: 2.5156 2022/10/09 21:37:32 - mmengine - INFO - Epoch(train) [2][540/940] lr: 1.0000e-02 eta: 13:13:52 time: 0.5587 data_time: 0.0310 memory: 21547 grad_norm: 3.1833 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5868 loss: 2.5868 2022/10/09 21:37:42 - mmengine - INFO - Epoch(train) [2][560/940] lr: 1.0000e-02 eta: 13:12:38 time: 0.4632 data_time: 0.0222 memory: 21547 grad_norm: 3.1824 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4912 loss: 2.4912 2022/10/09 21:37:53 - mmengine - INFO - Epoch(train) [2][580/940] lr: 1.0000e-02 eta: 13:13:22 time: 0.5589 data_time: 0.0271 memory: 21547 grad_norm: 3.1852 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.6513 loss: 2.6513 2022/10/09 21:38:02 - mmengine - INFO - Epoch(train) [2][600/940] lr: 1.0000e-02 eta: 13:12:10 time: 0.4631 data_time: 0.0255 memory: 21547 grad_norm: 3.1509 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6031 loss: 2.6031 2022/10/09 21:38:12 - mmengine - INFO - Epoch(train) [2][620/940] lr: 1.0000e-02 eta: 13:11:59 time: 0.5136 data_time: 0.0275 memory: 21547 grad_norm: 3.1636 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.4479 loss: 2.4479 2022/10/09 21:38:22 - mmengine - INFO - Epoch(train) [2][640/940] lr: 1.0000e-02 eta: 13:10:44 time: 0.4594 data_time: 0.0272 memory: 21547 grad_norm: 3.2128 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.5255 loss: 2.5255 2022/10/09 21:38:32 - mmengine - INFO - Epoch(train) [2][660/940] lr: 1.0000e-02 eta: 13:10:42 time: 0.5197 data_time: 0.0340 memory: 21547 grad_norm: 3.1798 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5637 loss: 2.5637 2022/10/09 21:38:42 - mmengine - INFO - Epoch(train) [2][680/940] lr: 1.0000e-02 eta: 13:10:31 time: 0.5132 data_time: 0.0283 memory: 21547 grad_norm: 3.1775 top1_acc: 0.3750 top5_acc: 0.5312 loss_cls: 2.7051 loss: 2.7051 2022/10/09 21:38:52 - mmengine - INFO - Epoch(train) [2][700/940] lr: 1.0000e-02 eta: 13:09:39 time: 0.4759 data_time: 0.0286 memory: 21547 grad_norm: 3.1815 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 2.5595 loss: 2.5595 2022/10/09 21:39:02 - mmengine - INFO - Epoch(train) [2][720/940] lr: 1.0000e-02 eta: 13:09:25 time: 0.5105 data_time: 0.0240 memory: 21547 grad_norm: 3.2146 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5611 loss: 2.5611 2022/10/09 21:39:12 - mmengine - INFO - Epoch(train) [2][740/940] lr: 1.0000e-02 eta: 13:08:37 time: 0.4781 data_time: 0.0278 memory: 21547 grad_norm: 3.2400 top1_acc: 0.5312 top5_acc: 0.5938 loss_cls: 2.5823 loss: 2.5823 2022/10/09 21:39:22 - mmengine - INFO - Epoch(train) [2][760/940] lr: 1.0000e-02 eta: 13:08:29 time: 0.5149 data_time: 0.0271 memory: 21547 grad_norm: 3.1860 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.4538 loss: 2.4538 2022/10/09 21:39:32 - mmengine - INFO - Epoch(train) [2][780/940] lr: 1.0000e-02 eta: 13:07:57 time: 0.4924 data_time: 0.0277 memory: 21547 grad_norm: 3.1905 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4869 loss: 2.4869 2022/10/09 21:39:42 - mmengine - INFO - Epoch(train) [2][800/940] lr: 1.0000e-02 eta: 13:07:36 time: 0.5022 data_time: 0.0252 memory: 21547 grad_norm: 3.2090 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4052 loss: 2.4052 2022/10/09 21:39:52 - mmengine - INFO - Epoch(train) [2][820/940] lr: 1.0000e-02 eta: 13:07:13 time: 0.5000 data_time: 0.0281 memory: 21547 grad_norm: 3.1932 top1_acc: 0.3125 top5_acc: 0.5312 loss_cls: 2.5102 loss: 2.5102 2022/10/09 21:40:01 - mmengine - INFO - Epoch(train) [2][840/940] lr: 1.0000e-02 eta: 13:06:21 time: 0.4711 data_time: 0.0267 memory: 21547 grad_norm: 3.2393 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 2.5635 loss: 2.5635 2022/10/09 21:40:12 - mmengine - INFO - Epoch(train) [2][860/940] lr: 1.0000e-02 eta: 13:06:22 time: 0.5229 data_time: 0.0485 memory: 21547 grad_norm: 3.2260 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 2.6185 loss: 2.6185 2022/10/09 21:40:21 - mmengine - INFO - Epoch(train) [2][880/940] lr: 1.0000e-02 eta: 13:05:51 time: 0.4913 data_time: 0.0740 memory: 21547 grad_norm: 3.1771 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 2.4642 loss: 2.4642 2022/10/09 21:40:32 - mmengine - INFO - Epoch(train) [2][900/940] lr: 1.0000e-02 eta: 13:06:10 time: 0.5406 data_time: 0.1418 memory: 21547 grad_norm: 3.2380 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.5561 loss: 2.5561 2022/10/09 21:40:42 - mmengine - INFO - Epoch(train) [2][920/940] lr: 1.0000e-02 eta: 13:05:18 time: 0.4694 data_time: 0.0696 memory: 21547 grad_norm: 3.2053 top1_acc: 0.3438 top5_acc: 0.6250 loss_cls: 2.5966 loss: 2.5966 2022/10/09 21:40:50 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 21:40:50 - mmengine - INFO - Epoch(train) [2][940/940] lr: 1.0000e-02 eta: 13:03:59 time: 0.4411 data_time: 0.0736 memory: 21547 grad_norm: 3.3758 top1_acc: 0.0000 top5_acc: 0.2857 loss_cls: 2.6786 loss: 2.6786 2022/10/09 21:41:03 - mmengine - INFO - Epoch(val) [2][20/78] eta: 0:00:35 time: 0.6036 data_time: 0.4938 memory: 3269 2022/10/09 21:41:11 - mmengine - INFO - Epoch(val) [2][40/78] eta: 0:00:16 time: 0.4229 data_time: 0.3159 memory: 3269 2022/10/09 21:41:23 - mmengine - INFO - Epoch(val) [2][60/78] eta: 0:00:10 time: 0.5780 data_time: 0.4719 memory: 3269 2022/10/09 21:41:32 - mmengine - INFO - Epoch(val) [2][78/78] acc/top1: 0.5168 acc/top5: 0.7715 acc/mean1: 0.5166 2022/10/09 21:41:32 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_1.pth is removed 2022/10/09 21:41:33 - mmengine - INFO - The best checkpoint with 0.5168 acc/top1 at 2 epoch is saved to best_acc/top1_epoch_2.pth. 2022/10/09 21:41:47 - mmengine - INFO - Epoch(train) [3][20/940] lr: 1.0000e-02 eta: 13:06:45 time: 0.6932 data_time: 0.2394 memory: 21547 grad_norm: 3.2817 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.4473 loss: 2.4473 2022/10/09 21:41:56 - mmengine - INFO - Epoch(train) [3][40/940] lr: 1.0000e-02 eta: 13:05:44 time: 0.4596 data_time: 0.0541 memory: 21547 grad_norm: 3.2170 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4480 loss: 2.4480 2022/10/09 21:42:07 - mmengine - INFO - Epoch(train) [3][60/940] lr: 1.0000e-02 eta: 13:05:57 time: 0.5361 data_time: 0.1092 memory: 21547 grad_norm: 3.2308 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4989 loss: 2.4989 2022/10/09 21:42:16 - mmengine - INFO - Epoch(train) [3][80/940] lr: 1.0000e-02 eta: 13:05:12 time: 0.4749 data_time: 0.0327 memory: 21547 grad_norm: 3.2150 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.6101 loss: 2.6101 2022/10/09 21:42:28 - mmengine - INFO - Epoch(train) [3][100/940] lr: 1.0000e-02 eta: 13:05:59 time: 0.5733 data_time: 0.0328 memory: 21547 grad_norm: 3.2370 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.3845 loss: 2.3845 2022/10/09 21:42:37 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 21:42:37 - mmengine - INFO - Epoch(train) [3][120/940] lr: 1.0000e-02 eta: 13:05:32 time: 0.4949 data_time: 0.0221 memory: 21547 grad_norm: 3.2305 top1_acc: 0.4062 top5_acc: 0.5625 loss_cls: 2.5452 loss: 2.5452 2022/10/09 21:42:47 - mmengine - INFO - Epoch(train) [3][140/940] lr: 1.0000e-02 eta: 13:05:11 time: 0.5003 data_time: 0.0302 memory: 21547 grad_norm: 3.2446 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.4005 loss: 2.4005 2022/10/09 21:42:57 - mmengine - INFO - Epoch(train) [3][160/940] lr: 1.0000e-02 eta: 13:04:21 time: 0.4684 data_time: 0.0249 memory: 21547 grad_norm: 3.2729 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.3774 loss: 2.3774 2022/10/09 21:43:07 - mmengine - INFO - Epoch(train) [3][180/940] lr: 1.0000e-02 eta: 13:04:03 time: 0.5023 data_time: 0.0282 memory: 21547 grad_norm: 3.2648 top1_acc: 0.4375 top5_acc: 0.5938 loss_cls: 2.5555 loss: 2.5555 2022/10/09 21:43:16 - mmengine - INFO - Epoch(train) [3][200/940] lr: 1.0000e-02 eta: 13:03:22 time: 0.4769 data_time: 0.0244 memory: 21547 grad_norm: 3.2020 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.4513 loss: 2.4513 2022/10/09 21:43:27 - mmengine - INFO - Epoch(train) [3][220/940] lr: 1.0000e-02 eta: 13:03:18 time: 0.5186 data_time: 0.0296 memory: 21547 grad_norm: 3.2059 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.4658 loss: 2.4658 2022/10/09 21:43:37 - mmengine - INFO - Epoch(train) [3][240/940] lr: 1.0000e-02 eta: 13:03:05 time: 0.5086 data_time: 0.0256 memory: 21547 grad_norm: 3.2349 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4083 loss: 2.4083 2022/10/09 21:43:47 - mmengine - INFO - Epoch(train) [3][260/940] lr: 1.0000e-02 eta: 13:02:55 time: 0.5114 data_time: 0.0299 memory: 21547 grad_norm: 3.2474 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 2.4265 loss: 2.4265 2022/10/09 21:43:57 - mmengine - INFO - Epoch(train) [3][280/940] lr: 1.0000e-02 eta: 13:02:17 time: 0.4788 data_time: 0.0290 memory: 21547 grad_norm: 3.2316 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.2955 loss: 2.2955 2022/10/09 21:44:06 - mmengine - INFO - Epoch(train) [3][300/940] lr: 1.0000e-02 eta: 13:01:44 time: 0.4845 data_time: 0.0281 memory: 21547 grad_norm: 3.2600 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.3923 loss: 2.3923 2022/10/09 21:44:20 - mmengine - INFO - Epoch(train) [3][320/940] lr: 1.0000e-02 eta: 13:03:57 time: 0.6823 data_time: 0.2526 memory: 21547 grad_norm: 3.2216 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.3589 loss: 2.3589 2022/10/09 21:44:30 - mmengine - INFO - Epoch(train) [3][340/940] lr: 1.0000e-02 eta: 13:03:52 time: 0.5179 data_time: 0.1336 memory: 21547 grad_norm: 3.2783 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4836 loss: 2.4836 2022/10/09 21:44:41 - mmengine - INFO - Epoch(train) [3][360/940] lr: 1.0000e-02 eta: 13:03:46 time: 0.5180 data_time: 0.1381 memory: 21547 grad_norm: 3.1859 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.5169 loss: 2.5169 2022/10/09 21:44:51 - mmengine - INFO - Epoch(train) [3][380/940] lr: 1.0000e-02 eta: 13:03:47 time: 0.5268 data_time: 0.1442 memory: 21547 grad_norm: 3.2260 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 2.4378 loss: 2.4378 2022/10/09 21:45:01 - mmengine - INFO - Epoch(train) [3][400/940] lr: 1.0000e-02 eta: 13:03:06 time: 0.4739 data_time: 0.0863 memory: 21547 grad_norm: 3.2723 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4471 loss: 2.4471 2022/10/09 21:45:11 - mmengine - INFO - Epoch(train) [3][420/940] lr: 1.0000e-02 eta: 13:03:00 time: 0.5181 data_time: 0.1407 memory: 21547 grad_norm: 3.2643 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 2.4162 loss: 2.4162 2022/10/09 21:45:20 - mmengine - INFO - Epoch(train) [3][440/940] lr: 1.0000e-02 eta: 13:01:35 time: 0.4179 data_time: 0.0412 memory: 21547 grad_norm: 3.2428 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4059 loss: 2.4059 2022/10/09 21:45:30 - mmengine - INFO - Epoch(train) [3][460/940] lr: 1.0000e-02 eta: 13:01:37 time: 0.5262 data_time: 0.1441 memory: 21547 grad_norm: 3.2770 top1_acc: 0.3438 top5_acc: 0.6250 loss_cls: 2.5155 loss: 2.5155 2022/10/09 21:45:40 - mmengine - INFO - Epoch(train) [3][480/940] lr: 1.0000e-02 eta: 13:01:05 time: 0.4841 data_time: 0.0933 memory: 21547 grad_norm: 3.2617 top1_acc: 0.5000 top5_acc: 0.9062 loss_cls: 2.1682 loss: 2.1682 2022/10/09 21:45:50 - mmengine - INFO - Epoch(train) [3][500/940] lr: 1.0000e-02 eta: 13:00:52 time: 0.5078 data_time: 0.1227 memory: 21547 grad_norm: 3.2687 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 2.4992 loss: 2.4992 2022/10/09 21:46:01 - mmengine - INFO - Epoch(train) [3][520/940] lr: 1.0000e-02 eta: 13:01:05 time: 0.5413 data_time: 0.0563 memory: 21547 grad_norm: 3.2687 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3064 loss: 2.3064 2022/10/09 21:46:11 - mmengine - INFO - Epoch(train) [3][540/940] lr: 1.0000e-02 eta: 13:01:00 time: 0.5194 data_time: 0.0302 memory: 21547 grad_norm: 3.2783 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4975 loss: 2.4975 2022/10/09 21:46:22 - mmengine - INFO - Epoch(train) [3][560/940] lr: 1.0000e-02 eta: 13:01:00 time: 0.5246 data_time: 0.0302 memory: 21547 grad_norm: 3.2469 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.3801 loss: 2.3801 2022/10/09 21:46:31 - mmengine - INFO - Epoch(train) [3][580/940] lr: 1.0000e-02 eta: 13:00:29 time: 0.4842 data_time: 0.0260 memory: 21547 grad_norm: 3.2763 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.4928 loss: 2.4928 2022/10/09 21:46:41 - mmengine - INFO - Epoch(train) [3][600/940] lr: 1.0000e-02 eta: 13:00:00 time: 0.4866 data_time: 0.0285 memory: 21547 grad_norm: 3.2909 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.6460 loss: 2.6460 2022/10/09 21:46:51 - mmengine - INFO - Epoch(train) [3][620/940] lr: 1.0000e-02 eta: 12:59:43 time: 0.5024 data_time: 0.0560 memory: 21547 grad_norm: 3.2288 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 2.5558 loss: 2.5558 2022/10/09 21:47:01 - mmengine - INFO - Epoch(train) [3][640/940] lr: 1.0000e-02 eta: 12:59:34 time: 0.5118 data_time: 0.1310 memory: 21547 grad_norm: 3.2872 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.4133 loss: 2.4133 2022/10/09 21:47:11 - mmengine - INFO - Epoch(train) [3][660/940] lr: 1.0000e-02 eta: 12:59:21 time: 0.5078 data_time: 0.1104 memory: 21547 grad_norm: 3.2843 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4416 loss: 2.4416 2022/10/09 21:47:20 - mmengine - INFO - Epoch(train) [3][680/940] lr: 1.0000e-02 eta: 12:58:25 time: 0.4480 data_time: 0.0639 memory: 21547 grad_norm: 3.2868 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3116 loss: 2.3116 2022/10/09 21:47:30 - mmengine - INFO - Epoch(train) [3][700/940] lr: 1.0000e-02 eta: 12:58:08 time: 0.5010 data_time: 0.0951 memory: 21547 grad_norm: 3.2909 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4462 loss: 2.4462 2022/10/09 21:47:41 - mmengine - INFO - Epoch(train) [3][720/940] lr: 1.0000e-02 eta: 12:57:55 time: 0.5066 data_time: 0.0250 memory: 21547 grad_norm: 3.3126 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3244 loss: 2.3244 2022/10/09 21:47:51 - mmengine - INFO - Epoch(train) [3][740/940] lr: 1.0000e-02 eta: 12:57:41 time: 0.5050 data_time: 0.0291 memory: 21547 grad_norm: 3.3107 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 2.4437 loss: 2.4437 2022/10/09 21:48:00 - mmengine - INFO - Epoch(train) [3][760/940] lr: 1.0000e-02 eta: 12:57:14 time: 0.4858 data_time: 0.0258 memory: 21547 grad_norm: 3.3048 top1_acc: 0.3438 top5_acc: 0.7500 loss_cls: 2.3552 loss: 2.3552 2022/10/09 21:48:11 - mmengine - INFO - Epoch(train) [3][780/940] lr: 1.0000e-02 eta: 12:57:12 time: 0.5227 data_time: 0.0275 memory: 21547 grad_norm: 3.3069 top1_acc: 0.2812 top5_acc: 0.6875 loss_cls: 2.5016 loss: 2.5016 2022/10/09 21:48:21 - mmengine - INFO - Epoch(train) [3][800/940] lr: 1.0000e-02 eta: 12:56:46 time: 0.4881 data_time: 0.0259 memory: 21547 grad_norm: 3.2827 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.4316 loss: 2.4316 2022/10/09 21:48:31 - mmengine - INFO - Epoch(train) [3][820/940] lr: 1.0000e-02 eta: 12:56:48 time: 0.5273 data_time: 0.0326 memory: 21547 grad_norm: 3.3271 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.4886 loss: 2.4886 2022/10/09 21:48:41 - mmengine - INFO - Epoch(train) [3][840/940] lr: 1.0000e-02 eta: 12:56:34 time: 0.5061 data_time: 0.0218 memory: 21547 grad_norm: 3.3023 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 2.3774 loss: 2.3774 2022/10/09 21:48:52 - mmengine - INFO - Epoch(train) [3][860/940] lr: 1.0000e-02 eta: 12:56:36 time: 0.5275 data_time: 0.0287 memory: 21547 grad_norm: 3.2903 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 2.3581 loss: 2.3581 2022/10/09 21:49:02 - mmengine - INFO - Epoch(train) [3][880/940] lr: 1.0000e-02 eta: 12:56:10 time: 0.4872 data_time: 0.0204 memory: 21547 grad_norm: 3.2719 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2755 loss: 2.2755 2022/10/09 21:49:12 - mmengine - INFO - Epoch(train) [3][900/940] lr: 1.0000e-02 eta: 12:56:04 time: 0.5177 data_time: 0.0276 memory: 21547 grad_norm: 3.3438 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.4037 loss: 2.4037 2022/10/09 21:49:22 - mmengine - INFO - Epoch(train) [3][920/940] lr: 1.0000e-02 eta: 12:55:39 time: 0.4864 data_time: 0.0330 memory: 21547 grad_norm: 3.3469 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.2810 loss: 2.2810 2022/10/09 21:49:31 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 21:49:31 - mmengine - INFO - Epoch(train) [3][940/940] lr: 1.0000e-02 eta: 12:54:59 time: 0.4648 data_time: 0.0237 memory: 21547 grad_norm: 3.4740 top1_acc: 0.4286 top5_acc: 0.4286 loss_cls: 2.3246 loss: 2.3246 2022/10/09 21:49:31 - mmengine - INFO - Saving checkpoint at 3 epochs 2022/10/09 21:49:44 - mmengine - INFO - Epoch(val) [3][20/78] eta: 0:00:35 time: 0.6124 data_time: 0.5081 memory: 3269 2022/10/09 21:49:52 - mmengine - INFO - Epoch(val) [3][40/78] eta: 0:00:15 time: 0.4188 data_time: 0.3147 memory: 3269 2022/10/09 21:50:04 - mmengine - INFO - Epoch(val) [3][60/78] eta: 0:00:10 time: 0.5600 data_time: 0.4566 memory: 3269 2022/10/09 21:50:13 - mmengine - INFO - Epoch(val) [3][78/78] acc/top1: 0.5349 acc/top5: 0.7847 acc/mean1: 0.5346 2022/10/09 21:50:13 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_2.pth is removed 2022/10/09 21:50:13 - mmengine - INFO - The best checkpoint with 0.5349 acc/top1 at 3 epoch is saved to best_acc/top1_epoch_3.pth. 2022/10/09 21:50:26 - mmengine - INFO - Epoch(train) [4][20/940] lr: 1.0000e-02 eta: 12:56:28 time: 0.6646 data_time: 0.2623 memory: 21547 grad_norm: 3.3154 top1_acc: 0.5312 top5_acc: 0.6250 loss_cls: 2.4062 loss: 2.4062 2022/10/09 21:50:36 - mmengine - INFO - Epoch(train) [4][40/940] lr: 1.0000e-02 eta: 12:55:53 time: 0.4715 data_time: 0.0588 memory: 21547 grad_norm: 3.2995 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 2.3418 loss: 2.3418 2022/10/09 21:50:47 - mmengine - INFO - Epoch(train) [4][60/940] lr: 1.0000e-02 eta: 12:56:20 time: 0.5699 data_time: 0.0397 memory: 21547 grad_norm: 3.3465 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.2238 loss: 2.2238 2022/10/09 21:50:57 - mmengine - INFO - Epoch(train) [4][80/940] lr: 1.0000e-02 eta: 12:55:40 time: 0.4634 data_time: 0.0232 memory: 21547 grad_norm: 3.2397 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.2005 loss: 2.2005 2022/10/09 21:51:07 - mmengine - INFO - Epoch(train) [4][100/940] lr: 1.0000e-02 eta: 12:55:43 time: 0.5322 data_time: 0.0331 memory: 21547 grad_norm: 3.3153 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4278 loss: 2.4278 2022/10/09 21:51:18 - mmengine - INFO - Epoch(train) [4][120/940] lr: 1.0000e-02 eta: 12:55:37 time: 0.5187 data_time: 0.0232 memory: 21547 grad_norm: 3.3419 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.3662 loss: 2.3662 2022/10/09 21:51:28 - mmengine - INFO - Epoch(train) [4][140/940] lr: 1.0000e-02 eta: 12:55:33 time: 0.5217 data_time: 0.0306 memory: 21547 grad_norm: 3.3176 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.2114 loss: 2.2114 2022/10/09 21:51:38 - mmengine - INFO - Epoch(train) [4][160/940] lr: 1.0000e-02 eta: 12:55:31 time: 0.5237 data_time: 0.0318 memory: 21547 grad_norm: 3.3028 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2885 loss: 2.2885 2022/10/09 21:51:49 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 21:51:49 - mmengine - INFO - Epoch(train) [4][180/940] lr: 1.0000e-02 eta: 12:55:27 time: 0.5224 data_time: 0.0301 memory: 21547 grad_norm: 3.2849 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 2.5024 loss: 2.5024 2022/10/09 21:51:59 - mmengine - INFO - Epoch(train) [4][200/940] lr: 1.0000e-02 eta: 12:55:08 time: 0.4958 data_time: 0.0242 memory: 21547 grad_norm: 3.3102 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.2186 loss: 2.2186 2022/10/09 21:52:09 - mmengine - INFO - Epoch(train) [4][220/940] lr: 1.0000e-02 eta: 12:55:01 time: 0.5166 data_time: 0.0282 memory: 21547 grad_norm: 3.3240 top1_acc: 0.2812 top5_acc: 0.5000 loss_cls: 2.4011 loss: 2.4011 2022/10/09 21:52:19 - mmengine - INFO - Epoch(train) [4][240/940] lr: 1.0000e-02 eta: 12:54:30 time: 0.4767 data_time: 0.0265 memory: 21547 grad_norm: 3.2980 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.3368 loss: 2.3368 2022/10/09 21:52:29 - mmengine - INFO - Epoch(train) [4][260/940] lr: 1.0000e-02 eta: 12:54:21 time: 0.5122 data_time: 0.0298 memory: 21547 grad_norm: 3.3560 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 2.2775 loss: 2.2775 2022/10/09 21:52:39 - mmengine - INFO - Epoch(train) [4][280/940] lr: 1.0000e-02 eta: 12:53:59 time: 0.4922 data_time: 0.0227 memory: 21547 grad_norm: 3.2914 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 2.3504 loss: 2.3504 2022/10/09 21:52:48 - mmengine - INFO - Epoch(train) [4][300/940] lr: 1.0000e-02 eta: 12:53:31 time: 0.4799 data_time: 0.0301 memory: 21547 grad_norm: 3.3007 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 2.4677 loss: 2.4677 2022/10/09 21:52:58 - mmengine - INFO - Epoch(train) [4][320/940] lr: 1.0000e-02 eta: 12:53:14 time: 0.4990 data_time: 0.0249 memory: 21547 grad_norm: 3.3385 top1_acc: 0.4062 top5_acc: 0.5625 loss_cls: 2.3052 loss: 2.3052 2022/10/09 21:53:09 - mmengine - INFO - Epoch(train) [4][340/940] lr: 1.0000e-02 eta: 12:53:10 time: 0.5218 data_time: 0.0275 memory: 21547 grad_norm: 3.3008 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3336 loss: 2.3336 2022/10/09 21:53:18 - mmengine - INFO - Epoch(train) [4][360/940] lr: 1.0000e-02 eta: 12:52:38 time: 0.4724 data_time: 0.0306 memory: 21547 grad_norm: 3.3515 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.2140 loss: 2.2140 2022/10/09 21:53:29 - mmengine - INFO - Epoch(train) [4][380/940] lr: 1.0000e-02 eta: 12:52:33 time: 0.5186 data_time: 0.0335 memory: 21547 grad_norm: 3.3575 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.2913 loss: 2.2913 2022/10/09 21:53:38 - mmengine - INFO - Epoch(train) [4][400/940] lr: 1.0000e-02 eta: 12:52:09 time: 0.4867 data_time: 0.0294 memory: 21547 grad_norm: 3.3469 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.3077 loss: 2.3077 2022/10/09 21:53:49 - mmengine - INFO - Epoch(train) [4][420/940] lr: 1.0000e-02 eta: 12:51:58 time: 0.5083 data_time: 0.0247 memory: 21547 grad_norm: 3.3171 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.0433 loss: 2.0433 2022/10/09 21:53:59 - mmengine - INFO - Epoch(train) [4][440/940] lr: 1.0000e-02 eta: 12:51:48 time: 0.5116 data_time: 0.0294 memory: 21547 grad_norm: 3.3391 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.3552 loss: 2.3552 2022/10/09 21:54:09 - mmengine - INFO - Epoch(train) [4][460/940] lr: 1.0000e-02 eta: 12:51:31 time: 0.4979 data_time: 0.0316 memory: 21547 grad_norm: 3.2819 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.2837 loss: 2.2837 2022/10/09 21:54:19 - mmengine - INFO - Epoch(train) [4][480/940] lr: 1.0000e-02 eta: 12:51:28 time: 0.5225 data_time: 0.0306 memory: 21547 grad_norm: 3.3909 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.4151 loss: 2.4151 2022/10/09 21:54:29 - mmengine - INFO - Epoch(train) [4][500/940] lr: 1.0000e-02 eta: 12:51:00 time: 0.4782 data_time: 0.0289 memory: 21547 grad_norm: 3.3761 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.3543 loss: 2.3543 2022/10/09 21:54:39 - mmengine - INFO - Epoch(train) [4][520/940] lr: 1.0000e-02 eta: 12:50:56 time: 0.5219 data_time: 0.0342 memory: 21547 grad_norm: 3.3110 top1_acc: 0.2500 top5_acc: 0.5938 loss_cls: 2.4416 loss: 2.4416 2022/10/09 21:54:49 - mmengine - INFO - Epoch(train) [4][540/940] lr: 1.0000e-02 eta: 12:50:46 time: 0.5114 data_time: 0.0252 memory: 21547 grad_norm: 3.3403 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.3964 loss: 2.3964 2022/10/09 21:55:00 - mmengine - INFO - Epoch(train) [4][560/940] lr: 1.0000e-02 eta: 12:50:54 time: 0.5432 data_time: 0.0254 memory: 21547 grad_norm: 3.3018 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.2509 loss: 2.2509 2022/10/09 21:55:10 - mmengine - INFO - Epoch(train) [4][580/940] lr: 1.0000e-02 eta: 12:50:20 time: 0.4655 data_time: 0.0255 memory: 21547 grad_norm: 3.3638 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.2672 loss: 2.2672 2022/10/09 21:55:20 - mmengine - INFO - Epoch(train) [4][600/940] lr: 1.0000e-02 eta: 12:50:11 time: 0.5127 data_time: 0.0259 memory: 21547 grad_norm: 3.2946 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 2.2980 loss: 2.2980 2022/10/09 21:55:30 - mmengine - INFO - Epoch(train) [4][620/940] lr: 1.0000e-02 eta: 12:49:54 time: 0.4980 data_time: 0.0224 memory: 21547 grad_norm: 3.3066 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3341 loss: 2.3341 2022/10/09 21:55:40 - mmengine - INFO - Epoch(train) [4][640/940] lr: 1.0000e-02 eta: 12:49:50 time: 0.5206 data_time: 0.0271 memory: 21547 grad_norm: 3.3381 top1_acc: 0.5312 top5_acc: 0.6250 loss_cls: 2.3690 loss: 2.3690 2022/10/09 21:55:50 - mmengine - INFO - Epoch(train) [4][660/940] lr: 1.0000e-02 eta: 12:49:32 time: 0.4954 data_time: 0.0276 memory: 21547 grad_norm: 3.3283 top1_acc: 0.3438 top5_acc: 0.8750 loss_cls: 2.2854 loss: 2.2854 2022/10/09 21:56:00 - mmengine - INFO - Epoch(train) [4][680/940] lr: 1.0000e-02 eta: 12:49:11 time: 0.4905 data_time: 0.0231 memory: 21547 grad_norm: 3.3165 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 2.2743 loss: 2.2743 2022/10/09 21:56:10 - mmengine - INFO - Epoch(train) [4][700/940] lr: 1.0000e-02 eta: 12:49:10 time: 0.5269 data_time: 0.0280 memory: 21547 grad_norm: 3.3074 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.3458 loss: 2.3458 2022/10/09 21:56:21 - mmengine - INFO - Epoch(train) [4][720/940] lr: 1.0000e-02 eta: 12:49:03 time: 0.5157 data_time: 0.0264 memory: 21547 grad_norm: 3.3771 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.1771 loss: 2.1771 2022/10/09 21:56:30 - mmengine - INFO - Epoch(train) [4][740/940] lr: 1.0000e-02 eta: 12:48:28 time: 0.4625 data_time: 0.0264 memory: 21547 grad_norm: 3.3862 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3569 loss: 2.3569 2022/10/09 21:56:40 - mmengine - INFO - Epoch(train) [4][760/940] lr: 1.0000e-02 eta: 12:48:10 time: 0.4939 data_time: 0.0246 memory: 21547 grad_norm: 3.2836 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.5009 loss: 2.5009 2022/10/09 21:56:49 - mmengine - INFO - Epoch(train) [4][780/940] lr: 1.0000e-02 eta: 12:47:41 time: 0.4715 data_time: 0.0318 memory: 21547 grad_norm: 3.3689 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1275 loss: 2.1275 2022/10/09 21:57:00 - mmengine - INFO - Epoch(train) [4][800/940] lr: 1.0000e-02 eta: 12:47:34 time: 0.5164 data_time: 0.0261 memory: 21547 grad_norm: 3.3438 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.1558 loss: 2.1558 2022/10/09 21:57:10 - mmengine - INFO - Epoch(train) [4][820/940] lr: 1.0000e-02 eta: 12:47:17 time: 0.4957 data_time: 0.0524 memory: 21547 grad_norm: 3.3511 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4130 loss: 2.4130 2022/10/09 21:57:20 - mmengine - INFO - Epoch(train) [4][840/940] lr: 1.0000e-02 eta: 12:47:13 time: 0.5219 data_time: 0.0769 memory: 21547 grad_norm: 3.3110 top1_acc: 0.4375 top5_acc: 0.5312 loss_cls: 2.1965 loss: 2.1965 2022/10/09 21:57:31 - mmengine - INFO - Epoch(train) [4][860/940] lr: 1.0000e-02 eta: 12:47:12 time: 0.5283 data_time: 0.1400 memory: 21547 grad_norm: 3.2817 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.2492 loss: 2.2492 2022/10/09 21:57:41 - mmengine - INFO - Epoch(train) [4][880/940] lr: 1.0000e-02 eta: 12:47:01 time: 0.5087 data_time: 0.1105 memory: 21547 grad_norm: 3.3360 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.1844 loss: 2.1844 2022/10/09 21:57:51 - mmengine - INFO - Epoch(train) [4][900/940] lr: 1.0000e-02 eta: 12:46:43 time: 0.4928 data_time: 0.0936 memory: 21547 grad_norm: 3.3333 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.2917 loss: 2.2917 2022/10/09 21:58:01 - mmengine - INFO - Epoch(train) [4][920/940] lr: 1.0000e-02 eta: 12:46:28 time: 0.4994 data_time: 0.0241 memory: 21547 grad_norm: 3.3538 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.2338 loss: 2.2338 2022/10/09 21:58:09 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 21:58:09 - mmengine - INFO - Epoch(train) [4][940/940] lr: 1.0000e-02 eta: 12:45:46 time: 0.4443 data_time: 0.0250 memory: 21547 grad_norm: 3.5366 top1_acc: 0.2857 top5_acc: 0.8571 loss_cls: 2.2518 loss: 2.2518 2022/10/09 21:58:21 - mmengine - INFO - Epoch(val) [4][20/78] eta: 0:00:34 time: 0.5983 data_time: 0.4891 memory: 3269 2022/10/09 21:58:30 - mmengine - INFO - Epoch(val) [4][40/78] eta: 0:00:16 time: 0.4219 data_time: 0.3159 memory: 3269 2022/10/09 21:58:41 - mmengine - INFO - Epoch(val) [4][60/78] eta: 0:00:10 time: 0.5726 data_time: 0.4667 memory: 3269 2022/10/09 21:58:51 - mmengine - INFO - Epoch(val) [4][78/78] acc/top1: 0.5524 acc/top5: 0.7968 acc/mean1: 0.5523 2022/10/09 21:58:51 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_3.pth is removed 2022/10/09 21:58:52 - mmengine - INFO - The best checkpoint with 0.5524 acc/top1 at 4 epoch is saved to best_acc/top1_epoch_4.pth. 2022/10/09 21:59:05 - mmengine - INFO - Epoch(train) [5][20/940] lr: 1.0000e-02 eta: 12:47:01 time: 0.6872 data_time: 0.2502 memory: 21547 grad_norm: 3.2964 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.1472 loss: 2.1472 2022/10/09 21:59:15 - mmengine - INFO - Epoch(train) [5][40/940] lr: 1.0000e-02 eta: 12:46:27 time: 0.4597 data_time: 0.0779 memory: 21547 grad_norm: 3.3323 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.2591 loss: 2.2591 2022/10/09 21:59:26 - mmengine - INFO - Epoch(train) [5][60/940] lr: 1.0000e-02 eta: 12:46:34 time: 0.5475 data_time: 0.1799 memory: 21547 grad_norm: 3.3399 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.0919 loss: 2.0919 2022/10/09 21:59:35 - mmengine - INFO - Epoch(train) [5][80/940] lr: 1.0000e-02 eta: 12:45:59 time: 0.4554 data_time: 0.0821 memory: 21547 grad_norm: 3.3071 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.3772 loss: 2.3772 2022/10/09 21:59:46 - mmengine - INFO - Epoch(train) [5][100/940] lr: 1.0000e-02 eta: 12:46:10 time: 0.5561 data_time: 0.1758 memory: 21547 grad_norm: 3.3653 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.1535 loss: 2.1535 2022/10/09 21:59:55 - mmengine - INFO - Epoch(train) [5][120/940] lr: 1.0000e-02 eta: 12:45:37 time: 0.4605 data_time: 0.0859 memory: 21547 grad_norm: 3.3374 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1047 loss: 2.1047 2022/10/09 22:00:06 - mmengine - INFO - Epoch(train) [5][140/940] lr: 1.0000e-02 eta: 12:45:51 time: 0.5633 data_time: 0.1749 memory: 21547 grad_norm: 3.3352 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.2600 loss: 2.2600 2022/10/09 22:00:16 - mmengine - INFO - Epoch(train) [5][160/940] lr: 1.0000e-02 eta: 12:45:28 time: 0.4809 data_time: 0.0495 memory: 21547 grad_norm: 3.4397 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.3379 loss: 2.3379 2022/10/09 22:00:26 - mmengine - INFO - Epoch(train) [5][180/940] lr: 1.0000e-02 eta: 12:45:23 time: 0.5207 data_time: 0.0315 memory: 21547 grad_norm: 3.3332 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.1733 loss: 2.1733 2022/10/09 22:00:36 - mmengine - INFO - Epoch(train) [5][200/940] lr: 1.0000e-02 eta: 12:45:06 time: 0.4956 data_time: 0.0248 memory: 21547 grad_norm: 3.2962 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1195 loss: 2.1195 2022/10/09 22:00:47 - mmengine - INFO - Epoch(train) [5][220/940] lr: 1.0000e-02 eta: 12:45:05 time: 0.5300 data_time: 0.0302 memory: 21547 grad_norm: 3.3761 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1258 loss: 2.1258 2022/10/09 22:00:57 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 22:00:57 - mmengine - INFO - Epoch(train) [5][240/940] lr: 1.0000e-02 eta: 12:44:44 time: 0.4861 data_time: 0.0303 memory: 21547 grad_norm: 3.3967 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.2895 loss: 2.2895 2022/10/09 22:01:07 - mmengine - INFO - Epoch(train) [5][260/940] lr: 1.0000e-02 eta: 12:44:42 time: 0.5296 data_time: 0.0377 memory: 21547 grad_norm: 3.3333 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1073 loss: 2.1073 2022/10/09 22:01:16 - mmengine - INFO - Epoch(train) [5][280/940] lr: 1.0000e-02 eta: 12:44:11 time: 0.4615 data_time: 0.0235 memory: 21547 grad_norm: 3.3408 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1880 loss: 2.1880 2022/10/09 22:01:28 - mmengine - INFO - Epoch(train) [5][300/940] lr: 1.0000e-02 eta: 12:44:23 time: 0.5599 data_time: 0.0259 memory: 21547 grad_norm: 3.3446 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0326 loss: 2.0326 2022/10/09 22:01:37 - mmengine - INFO - Epoch(train) [5][320/940] lr: 1.0000e-02 eta: 12:43:45 time: 0.4482 data_time: 0.0253 memory: 21547 grad_norm: 3.4057 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.2475 loss: 2.2475 2022/10/09 22:01:48 - mmengine - INFO - Epoch(train) [5][340/940] lr: 1.0000e-02 eta: 12:44:02 time: 0.5706 data_time: 0.0289 memory: 21547 grad_norm: 3.3113 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.2379 loss: 2.2379 2022/10/09 22:01:57 - mmengine - INFO - Epoch(train) [5][360/940] lr: 1.0000e-02 eta: 12:43:32 time: 0.4653 data_time: 0.0268 memory: 21547 grad_norm: 3.3709 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0748 loss: 2.0748 2022/10/09 22:02:07 - mmengine - INFO - Epoch(train) [5][380/940] lr: 1.0000e-02 eta: 12:43:06 time: 0.4726 data_time: 0.0284 memory: 21547 grad_norm: 3.3723 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 2.0930 loss: 2.0930 2022/10/09 22:02:16 - mmengine - INFO - Epoch(train) [5][400/940] lr: 1.0000e-02 eta: 12:42:34 time: 0.4581 data_time: 0.0289 memory: 21547 grad_norm: 3.3358 top1_acc: 0.5312 top5_acc: 0.6250 loss_cls: 2.1882 loss: 2.1882 2022/10/09 22:02:27 - mmengine - INFO - Epoch(train) [5][420/940] lr: 1.0000e-02 eta: 12:42:50 time: 0.5706 data_time: 0.0294 memory: 21547 grad_norm: 3.4119 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 2.1878 loss: 2.1878 2022/10/09 22:02:37 - mmengine - INFO - Epoch(train) [5][440/940] lr: 1.0000e-02 eta: 12:42:20 time: 0.4643 data_time: 0.0247 memory: 21547 grad_norm: 3.3886 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.2638 loss: 2.2638 2022/10/09 22:02:47 - mmengine - INFO - Epoch(train) [5][460/940] lr: 1.0000e-02 eta: 12:42:20 time: 0.5319 data_time: 0.0307 memory: 21547 grad_norm: 3.3485 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.1857 loss: 2.1857 2022/10/09 22:02:58 - mmengine - INFO - Epoch(train) [5][480/940] lr: 1.0000e-02 eta: 12:42:10 time: 0.5118 data_time: 0.0301 memory: 21547 grad_norm: 3.3844 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.3384 loss: 2.3384 2022/10/09 22:03:08 - mmengine - INFO - Epoch(train) [5][500/940] lr: 1.0000e-02 eta: 12:41:58 time: 0.5037 data_time: 0.0308 memory: 21547 grad_norm: 3.4207 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.2396 loss: 2.2396 2022/10/09 22:03:18 - mmengine - INFO - Epoch(train) [5][520/940] lr: 1.0000e-02 eta: 12:41:47 time: 0.5088 data_time: 0.0277 memory: 21547 grad_norm: 3.4219 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.9937 loss: 1.9937 2022/10/09 22:03:28 - mmengine - INFO - Epoch(train) [5][540/940] lr: 1.0000e-02 eta: 12:41:39 time: 0.5138 data_time: 0.0295 memory: 21547 grad_norm: 3.4152 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.3272 loss: 2.3272 2022/10/09 22:03:37 - mmengine - INFO - Epoch(train) [5][560/940] lr: 1.0000e-02 eta: 12:40:57 time: 0.4336 data_time: 0.0249 memory: 21547 grad_norm: 3.3829 top1_acc: 0.3125 top5_acc: 0.7188 loss_cls: 2.2449 loss: 2.2449 2022/10/09 22:03:47 - mmengine - INFO - Epoch(train) [5][580/940] lr: 1.0000e-02 eta: 12:40:46 time: 0.5072 data_time: 0.0373 memory: 21547 grad_norm: 3.4234 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 2.1386 loss: 2.1386 2022/10/09 22:03:57 - mmengine - INFO - Epoch(train) [5][600/940] lr: 1.0000e-02 eta: 12:40:28 time: 0.4906 data_time: 0.0257 memory: 21547 grad_norm: 3.3811 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.0780 loss: 2.0780 2022/10/09 22:04:07 - mmengine - INFO - Epoch(train) [5][620/940] lr: 1.0000e-02 eta: 12:40:20 time: 0.5123 data_time: 0.0290 memory: 21547 grad_norm: 3.3136 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 2.1829 loss: 2.1829 2022/10/09 22:04:17 - mmengine - INFO - Epoch(train) [5][640/940] lr: 1.0000e-02 eta: 12:40:10 time: 0.5117 data_time: 0.0267 memory: 21547 grad_norm: 3.4079 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.3001 loss: 2.3001 2022/10/09 22:04:27 - mmengine - INFO - Epoch(train) [5][660/940] lr: 1.0000e-02 eta: 12:40:04 time: 0.5177 data_time: 0.0315 memory: 21547 grad_norm: 3.4392 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3621 loss: 2.3621 2022/10/09 22:04:37 - mmengine - INFO - Epoch(train) [5][680/940] lr: 1.0000e-02 eta: 12:39:33 time: 0.4590 data_time: 0.0298 memory: 21547 grad_norm: 3.3930 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.2544 loss: 2.2544 2022/10/09 22:04:47 - mmengine - INFO - Epoch(train) [5][700/940] lr: 1.0000e-02 eta: 12:39:21 time: 0.5022 data_time: 0.0331 memory: 21547 grad_norm: 3.4362 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.3334 loss: 2.3334 2022/10/09 22:04:56 - mmengine - INFO - Epoch(train) [5][720/940] lr: 1.0000e-02 eta: 12:38:56 time: 0.4724 data_time: 0.0310 memory: 21547 grad_norm: 3.4314 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.1611 loss: 2.1611 2022/10/09 22:05:06 - mmengine - INFO - Epoch(train) [5][740/940] lr: 1.0000e-02 eta: 12:38:47 time: 0.5114 data_time: 0.0286 memory: 21547 grad_norm: 3.3619 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2244 loss: 2.2244 2022/10/09 22:05:17 - mmengine - INFO - Epoch(train) [5][760/940] lr: 1.0000e-02 eta: 12:38:39 time: 0.5148 data_time: 0.0261 memory: 21547 grad_norm: 3.3925 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1625 loss: 2.1625 2022/10/09 22:05:27 - mmengine - INFO - Epoch(train) [5][780/940] lr: 1.0000e-02 eta: 12:38:30 time: 0.5130 data_time: 0.0305 memory: 21547 grad_norm: 3.3719 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.1619 loss: 2.1619 2022/10/09 22:05:37 - mmengine - INFO - Epoch(train) [5][800/940] lr: 1.0000e-02 eta: 12:38:25 time: 0.5208 data_time: 0.0268 memory: 21547 grad_norm: 3.3908 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.2252 loss: 2.2252 2022/10/09 22:05:47 - mmengine - INFO - Epoch(train) [5][820/940] lr: 1.0000e-02 eta: 12:38:13 time: 0.5052 data_time: 0.0297 memory: 21547 grad_norm: 3.4558 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.2090 loss: 2.2090 2022/10/09 22:05:58 - mmengine - INFO - Epoch(train) [5][840/940] lr: 1.0000e-02 eta: 12:38:03 time: 0.5081 data_time: 0.0301 memory: 21547 grad_norm: 3.4135 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.2098 loss: 2.2098 2022/10/09 22:06:08 - mmengine - INFO - Epoch(train) [5][860/940] lr: 1.0000e-02 eta: 12:37:54 time: 0.5106 data_time: 0.0321 memory: 21547 grad_norm: 3.4550 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 2.0566 loss: 2.0566 2022/10/09 22:06:18 - mmengine - INFO - Epoch(train) [5][880/940] lr: 1.0000e-02 eta: 12:37:36 time: 0.4904 data_time: 0.0377 memory: 21547 grad_norm: 3.3616 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.0875 loss: 2.0875 2022/10/09 22:06:29 - mmengine - INFO - Epoch(train) [5][900/940] lr: 1.0000e-02 eta: 12:37:39 time: 0.5430 data_time: 0.0279 memory: 21547 grad_norm: 3.4305 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.1942 loss: 2.1942 2022/10/09 22:06:38 - mmengine - INFO - Epoch(train) [5][920/940] lr: 1.0000e-02 eta: 12:37:22 time: 0.4903 data_time: 0.0235 memory: 21547 grad_norm: 3.3589 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0218 loss: 2.0218 2022/10/09 22:06:47 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 22:06:47 - mmengine - INFO - Epoch(train) [5][940/940] lr: 1.0000e-02 eta: 12:36:42 time: 0.4289 data_time: 0.0247 memory: 21547 grad_norm: 3.5396 top1_acc: 0.1429 top5_acc: 0.2857 loss_cls: 2.3549 loss: 2.3549 2022/10/09 22:06:59 - mmengine - INFO - Epoch(val) [5][20/78] eta: 0:00:35 time: 0.6129 data_time: 0.5010 memory: 3269 2022/10/09 22:07:08 - mmengine - INFO - Epoch(val) [5][40/78] eta: 0:00:16 time: 0.4217 data_time: 0.3158 memory: 3269 2022/10/09 22:07:19 - mmengine - INFO - Epoch(val) [5][60/78] eta: 0:00:10 time: 0.5567 data_time: 0.4491 memory: 3269 2022/10/09 22:07:28 - mmengine - INFO - Epoch(val) [5][78/78] acc/top1: 0.5706 acc/top5: 0.8077 acc/mean1: 0.5704 2022/10/09 22:07:28 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_4.pth is removed 2022/10/09 22:07:29 - mmengine - INFO - The best checkpoint with 0.5706 acc/top1 at 5 epoch is saved to best_acc/top1_epoch_5.pth. 2022/10/09 22:07:42 - mmengine - INFO - Epoch(train) [6][20/940] lr: 1.0000e-02 eta: 12:37:31 time: 0.6658 data_time: 0.3076 memory: 21547 grad_norm: 3.3801 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0903 loss: 2.0903 2022/10/09 22:07:52 - mmengine - INFO - Epoch(train) [6][40/940] lr: 1.0000e-02 eta: 12:37:10 time: 0.4814 data_time: 0.1029 memory: 21547 grad_norm: 3.4190 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.0969 loss: 2.0969 2022/10/09 22:08:02 - mmengine - INFO - Epoch(train) [6][60/940] lr: 1.0000e-02 eta: 12:37:04 time: 0.5198 data_time: 0.1259 memory: 21547 grad_norm: 3.3369 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 2.0287 loss: 2.0287 2022/10/09 22:08:12 - mmengine - INFO - Epoch(train) [6][80/940] lr: 1.0000e-02 eta: 12:36:36 time: 0.4604 data_time: 0.0324 memory: 21547 grad_norm: 3.4380 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.1233 loss: 2.1233 2022/10/09 22:08:22 - mmengine - INFO - Epoch(train) [6][100/940] lr: 1.0000e-02 eta: 12:36:39 time: 0.5455 data_time: 0.0320 memory: 21547 grad_norm: 3.4305 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 2.1414 loss: 2.1414 2022/10/09 22:08:31 - mmengine - INFO - Epoch(train) [6][120/940] lr: 1.0000e-02 eta: 12:36:06 time: 0.4464 data_time: 0.0244 memory: 21547 grad_norm: 3.3985 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.0751 loss: 2.0751 2022/10/09 22:08:43 - mmengine - INFO - Epoch(train) [6][140/940] lr: 1.0000e-02 eta: 12:36:15 time: 0.5595 data_time: 0.0326 memory: 21547 grad_norm: 3.4355 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9917 loss: 1.9917 2022/10/09 22:08:52 - mmengine - INFO - Epoch(train) [6][160/940] lr: 1.0000e-02 eta: 12:35:58 time: 0.4915 data_time: 0.0256 memory: 21547 grad_norm: 3.4133 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.1607 loss: 2.1607 2022/10/09 22:09:04 - mmengine - INFO - Epoch(train) [6][180/940] lr: 1.0000e-02 eta: 12:36:12 time: 0.5740 data_time: 0.0333 memory: 21547 grad_norm: 3.4612 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.1814 loss: 2.1814 2022/10/09 22:09:14 - mmengine - INFO - Epoch(train) [6][200/940] lr: 1.0000e-02 eta: 12:35:52 time: 0.4833 data_time: 0.0242 memory: 21547 grad_norm: 3.3804 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 2.1357 loss: 2.1357 2022/10/09 22:09:23 - mmengine - INFO - Epoch(train) [6][220/940] lr: 1.0000e-02 eta: 12:35:34 time: 0.4878 data_time: 0.0271 memory: 21547 grad_norm: 3.4139 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.2359 loss: 2.2359 2022/10/09 22:09:33 - mmengine - INFO - Epoch(train) [6][240/940] lr: 1.0000e-02 eta: 12:35:21 time: 0.5001 data_time: 0.0282 memory: 21547 grad_norm: 3.4091 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.1930 loss: 2.1930 2022/10/09 22:09:44 - mmengine - INFO - Epoch(train) [6][260/940] lr: 1.0000e-02 eta: 12:35:20 time: 0.5343 data_time: 0.0238 memory: 21547 grad_norm: 3.4954 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.1868 loss: 2.1868 2022/10/09 22:09:53 - mmengine - INFO - Epoch(train) [6][280/940] lr: 1.0000e-02 eta: 12:34:52 time: 0.4612 data_time: 0.0307 memory: 21547 grad_norm: 3.4408 top1_acc: 0.2188 top5_acc: 0.6250 loss_cls: 2.3641 loss: 2.3641 2022/10/09 22:10:04 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 22:10:04 - mmengine - INFO - Epoch(train) [6][300/940] lr: 1.0000e-02 eta: 12:34:46 time: 0.5203 data_time: 0.0234 memory: 21547 grad_norm: 3.3760 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.1355 loss: 2.1355 2022/10/09 22:10:13 - mmengine - INFO - Epoch(train) [6][320/940] lr: 1.0000e-02 eta: 12:34:16 time: 0.4532 data_time: 0.0270 memory: 21547 grad_norm: 3.4391 top1_acc: 0.3438 top5_acc: 0.7500 loss_cls: 2.1033 loss: 2.1033 2022/10/09 22:10:22 - mmengine - INFO - Epoch(train) [6][340/940] lr: 1.0000e-02 eta: 12:33:56 time: 0.4781 data_time: 0.0235 memory: 21547 grad_norm: 3.4352 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.2280 loss: 2.2280 2022/10/09 22:10:32 - mmengine - INFO - Epoch(train) [6][360/940] lr: 1.0000e-02 eta: 12:33:44 time: 0.5052 data_time: 0.0267 memory: 21547 grad_norm: 3.3833 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2680 loss: 2.2680 2022/10/09 22:10:42 - mmengine - INFO - Epoch(train) [6][380/940] lr: 1.0000e-02 eta: 12:33:33 time: 0.5055 data_time: 0.0263 memory: 21547 grad_norm: 3.3816 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.2614 loss: 2.2614 2022/10/09 22:10:53 - mmengine - INFO - Epoch(train) [6][400/940] lr: 1.0000e-02 eta: 12:33:23 time: 0.5082 data_time: 0.0351 memory: 21547 grad_norm: 3.3817 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 2.0938 loss: 2.0938 2022/10/09 22:11:03 - mmengine - INFO - Epoch(train) [6][420/940] lr: 1.0000e-02 eta: 12:33:10 time: 0.5012 data_time: 0.0314 memory: 21547 grad_norm: 3.4700 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2160 loss: 2.2160 2022/10/09 22:11:14 - mmengine - INFO - Epoch(train) [6][440/940] lr: 1.0000e-02 eta: 12:33:14 time: 0.5485 data_time: 0.0247 memory: 21547 grad_norm: 3.4421 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.2394 loss: 2.2394 2022/10/09 22:11:24 - mmengine - INFO - Epoch(train) [6][460/940] lr: 1.0000e-02 eta: 12:33:03 time: 0.5082 data_time: 0.0303 memory: 21547 grad_norm: 3.4023 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0771 loss: 2.0771 2022/10/09 22:11:34 - mmengine - INFO - Epoch(train) [6][480/940] lr: 1.0000e-02 eta: 12:32:55 time: 0.5126 data_time: 0.0250 memory: 21547 grad_norm: 3.4720 top1_acc: 0.5938 top5_acc: 0.9688 loss_cls: 2.0928 loss: 2.0928 2022/10/09 22:11:44 - mmengine - INFO - Epoch(train) [6][500/940] lr: 1.0000e-02 eta: 12:32:40 time: 0.4950 data_time: 0.0252 memory: 21547 grad_norm: 3.4430 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.1779 loss: 2.1779 2022/10/09 22:11:53 - mmengine - INFO - Epoch(train) [6][520/940] lr: 1.0000e-02 eta: 12:32:18 time: 0.4741 data_time: 0.0277 memory: 21547 grad_norm: 3.3774 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 2.0954 loss: 2.0954 2022/10/09 22:12:04 - mmengine - INFO - Epoch(train) [6][540/940] lr: 1.0000e-02 eta: 12:32:07 time: 0.5067 data_time: 0.0269 memory: 21547 grad_norm: 3.4863 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1329 loss: 2.1329 2022/10/09 22:12:14 - mmengine - INFO - Epoch(train) [6][560/940] lr: 1.0000e-02 eta: 12:31:59 time: 0.5147 data_time: 0.0297 memory: 21547 grad_norm: 3.4450 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0991 loss: 2.0991 2022/10/09 22:12:23 - mmengine - INFO - Epoch(train) [6][580/940] lr: 1.0000e-02 eta: 12:31:38 time: 0.4754 data_time: 0.0240 memory: 21547 grad_norm: 3.4155 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 2.0374 loss: 2.0374 2022/10/09 22:12:33 - mmengine - INFO - Epoch(train) [6][600/940] lr: 1.0000e-02 eta: 12:31:24 time: 0.4960 data_time: 0.0317 memory: 21547 grad_norm: 3.4656 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.3084 loss: 2.3084 2022/10/09 22:12:43 - mmengine - INFO - Epoch(train) [6][620/940] lr: 1.0000e-02 eta: 12:31:08 time: 0.4915 data_time: 0.0244 memory: 21547 grad_norm: 3.4811 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3378 loss: 2.3378 2022/10/09 22:12:54 - mmengine - INFO - Epoch(train) [6][640/940] lr: 1.0000e-02 eta: 12:31:06 time: 0.5348 data_time: 0.0328 memory: 21547 grad_norm: 3.4259 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.2372 loss: 2.2372 2022/10/09 22:13:03 - mmengine - INFO - Epoch(train) [6][660/940] lr: 1.0000e-02 eta: 12:30:48 time: 0.4820 data_time: 0.0250 memory: 21547 grad_norm: 3.3865 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.3080 loss: 2.3080 2022/10/09 22:13:13 - mmengine - INFO - Epoch(train) [6][680/940] lr: 1.0000e-02 eta: 12:30:27 time: 0.4781 data_time: 0.0370 memory: 21547 grad_norm: 3.4751 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1762 loss: 2.1762 2022/10/09 22:13:24 - mmengine - INFO - Epoch(train) [6][700/940] lr: 1.0000e-02 eta: 12:30:27 time: 0.5390 data_time: 0.0228 memory: 21547 grad_norm: 3.4203 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.3771 loss: 2.3771 2022/10/09 22:13:33 - mmengine - INFO - Epoch(train) [6][720/940] lr: 1.0000e-02 eta: 12:30:05 time: 0.4696 data_time: 0.0305 memory: 21547 grad_norm: 3.4984 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.2396 loss: 2.2396 2022/10/09 22:13:43 - mmengine - INFO - Epoch(train) [6][740/940] lr: 1.0000e-02 eta: 12:29:55 time: 0.5084 data_time: 0.0225 memory: 21547 grad_norm: 3.4609 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.0923 loss: 2.0923 2022/10/09 22:13:53 - mmengine - INFO - Epoch(train) [6][760/940] lr: 1.0000e-02 eta: 12:29:42 time: 0.5014 data_time: 0.0271 memory: 21547 grad_norm: 3.4325 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 2.3663 loss: 2.3663 2022/10/09 22:14:04 - mmengine - INFO - Epoch(train) [6][780/940] lr: 1.0000e-02 eta: 12:29:45 time: 0.5467 data_time: 0.0245 memory: 21547 grad_norm: 3.4126 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 2.2739 loss: 2.2739 2022/10/09 22:14:14 - mmengine - INFO - Epoch(train) [6][800/940] lr: 1.0000e-02 eta: 12:29:21 time: 0.4658 data_time: 0.0290 memory: 21547 grad_norm: 3.4470 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 2.1647 loss: 2.1647 2022/10/09 22:14:24 - mmengine - INFO - Epoch(train) [6][820/940] lr: 1.0000e-02 eta: 12:29:19 time: 0.5349 data_time: 0.0293 memory: 21547 grad_norm: 3.4146 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 2.1120 loss: 2.1120 2022/10/09 22:14:34 - mmengine - INFO - Epoch(train) [6][840/940] lr: 1.0000e-02 eta: 12:29:03 time: 0.4884 data_time: 0.0289 memory: 21547 grad_norm: 3.4785 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.1283 loss: 2.1283 2022/10/09 22:14:45 - mmengine - INFO - Epoch(train) [6][860/940] lr: 1.0000e-02 eta: 12:28:59 time: 0.5278 data_time: 0.0320 memory: 21547 grad_norm: 3.4173 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9555 loss: 1.9555 2022/10/09 22:14:54 - mmengine - INFO - Epoch(train) [6][880/940] lr: 1.0000e-02 eta: 12:28:40 time: 0.4813 data_time: 0.0323 memory: 21547 grad_norm: 3.4724 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1667 loss: 2.1667 2022/10/09 22:15:04 - mmengine - INFO - Epoch(train) [6][900/940] lr: 1.0000e-02 eta: 12:28:29 time: 0.5051 data_time: 0.0301 memory: 21547 grad_norm: 3.4227 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.0729 loss: 2.0729 2022/10/09 22:15:15 - mmengine - INFO - Epoch(train) [6][920/940] lr: 1.0000e-02 eta: 12:28:23 time: 0.5220 data_time: 0.0259 memory: 21547 grad_norm: 3.4112 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.2192 loss: 2.2192 2022/10/09 22:15:24 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 22:15:24 - mmengine - INFO - Epoch(train) [6][940/940] lr: 1.0000e-02 eta: 12:28:00 time: 0.4670 data_time: 0.0195 memory: 21547 grad_norm: 3.6068 top1_acc: 0.1429 top5_acc: 0.7143 loss_cls: 2.3045 loss: 2.3045 2022/10/09 22:15:24 - mmengine - INFO - Saving checkpoint at 6 epochs 2022/10/09 22:15:37 - mmengine - INFO - Epoch(val) [6][20/78] eta: 0:00:35 time: 0.6083 data_time: 0.5031 memory: 3269 2022/10/09 22:15:46 - mmengine - INFO - Epoch(val) [6][40/78] eta: 0:00:15 time: 0.4167 data_time: 0.3119 memory: 3269 2022/10/09 22:15:57 - mmengine - INFO - Epoch(val) [6][60/78] eta: 0:00:10 time: 0.5642 data_time: 0.4569 memory: 3269 2022/10/09 22:16:06 - mmengine - INFO - Epoch(val) [6][78/78] acc/top1: 0.5630 acc/top5: 0.8025 acc/mean1: 0.5629 2022/10/09 22:16:21 - mmengine - INFO - Epoch(train) [7][20/940] lr: 1.0000e-02 eta: 12:28:58 time: 0.7268 data_time: 0.2187 memory: 21547 grad_norm: 3.3981 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.2292 loss: 2.2292 2022/10/09 22:16:30 - mmengine - INFO - Epoch(train) [7][40/940] lr: 1.0000e-02 eta: 12:28:27 time: 0.4411 data_time: 0.0245 memory: 21547 grad_norm: 3.4055 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1496 loss: 2.1496 2022/10/09 22:16:41 - mmengine - INFO - Epoch(train) [7][60/940] lr: 1.0000e-02 eta: 12:28:35 time: 0.5662 data_time: 0.0539 memory: 21547 grad_norm: 3.4479 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0968 loss: 2.0968 2022/10/09 22:16:50 - mmengine - INFO - Epoch(train) [7][80/940] lr: 1.0000e-02 eta: 12:28:15 time: 0.4759 data_time: 0.0250 memory: 21547 grad_norm: 3.4268 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.9670 loss: 1.9670 2022/10/09 22:17:01 - mmengine - INFO - Epoch(train) [7][100/940] lr: 1.0000e-02 eta: 12:28:07 time: 0.5172 data_time: 0.0314 memory: 21547 grad_norm: 3.4131 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.1547 loss: 2.1547 2022/10/09 22:17:11 - mmengine - INFO - Epoch(train) [7][120/940] lr: 1.0000e-02 eta: 12:27:53 time: 0.4949 data_time: 0.0245 memory: 21547 grad_norm: 3.4795 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.2333 loss: 2.2333 2022/10/09 22:17:21 - mmengine - INFO - Epoch(train) [7][140/940] lr: 1.0000e-02 eta: 12:27:45 time: 0.5164 data_time: 0.0436 memory: 21547 grad_norm: 3.5022 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.1506 loss: 2.1506 2022/10/09 22:17:31 - mmengine - INFO - Epoch(train) [7][160/940] lr: 1.0000e-02 eta: 12:27:37 time: 0.5147 data_time: 0.0490 memory: 21547 grad_norm: 3.4529 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.1885 loss: 2.1885 2022/10/09 22:17:42 - mmengine - INFO - Epoch(train) [7][180/940] lr: 1.0000e-02 eta: 12:27:27 time: 0.5103 data_time: 0.0323 memory: 21547 grad_norm: 3.4767 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 2.2483 loss: 2.2483 2022/10/09 22:17:52 - mmengine - INFO - Epoch(train) [7][200/940] lr: 1.0000e-02 eta: 12:27:15 time: 0.5038 data_time: 0.0243 memory: 21547 grad_norm: 3.5018 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0065 loss: 2.0065 2022/10/09 22:18:02 - mmengine - INFO - Epoch(train) [7][220/940] lr: 1.0000e-02 eta: 12:27:09 time: 0.5218 data_time: 0.0299 memory: 21547 grad_norm: 3.4444 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.1869 loss: 2.1869 2022/10/09 22:18:12 - mmengine - INFO - Epoch(train) [7][240/940] lr: 1.0000e-02 eta: 12:26:52 time: 0.4859 data_time: 0.0294 memory: 21547 grad_norm: 3.4129 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0113 loss: 2.0113 2022/10/09 22:18:22 - mmengine - INFO - Epoch(train) [7][260/940] lr: 1.0000e-02 eta: 12:26:48 time: 0.5279 data_time: 0.0294 memory: 21547 grad_norm: 3.4302 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0339 loss: 2.0339 2022/10/09 22:18:32 - mmengine - INFO - Epoch(train) [7][280/940] lr: 1.0000e-02 eta: 12:26:35 time: 0.5005 data_time: 0.0280 memory: 21547 grad_norm: 3.4580 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9216 loss: 1.9216 2022/10/09 22:18:43 - mmengine - INFO - Epoch(train) [7][300/940] lr: 1.0000e-02 eta: 12:26:27 time: 0.5158 data_time: 0.0276 memory: 21547 grad_norm: 3.4957 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.1457 loss: 2.1457 2022/10/09 22:18:52 - mmengine - INFO - Epoch(train) [7][320/940] lr: 1.0000e-02 eta: 12:26:08 time: 0.4771 data_time: 0.0288 memory: 21547 grad_norm: 3.4367 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1310 loss: 2.1310 2022/10/09 22:19:02 - mmengine - INFO - Epoch(train) [7][340/940] lr: 1.0000e-02 eta: 12:25:53 time: 0.4937 data_time: 0.0284 memory: 21547 grad_norm: 3.4428 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.1462 loss: 2.1462 2022/10/09 22:19:12 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 22:19:12 - mmengine - INFO - Epoch(train) [7][360/940] lr: 1.0000e-02 eta: 12:25:33 time: 0.4747 data_time: 0.0272 memory: 21547 grad_norm: 3.4788 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0203 loss: 2.0203 2022/10/09 22:19:21 - mmengine - INFO - Epoch(train) [7][380/940] lr: 1.0000e-02 eta: 12:25:18 time: 0.4909 data_time: 0.0315 memory: 21547 grad_norm: 3.4526 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.0087 loss: 2.0087 2022/10/09 22:19:32 - mmengine - INFO - Epoch(train) [7][400/940] lr: 1.0000e-02 eta: 12:25:12 time: 0.5212 data_time: 0.0291 memory: 21547 grad_norm: 3.4413 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0240 loss: 2.0240 2022/10/09 22:19:42 - mmengine - INFO - Epoch(train) [7][420/940] lr: 1.0000e-02 eta: 12:24:58 time: 0.4977 data_time: 0.0304 memory: 21547 grad_norm: 3.4361 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.0631 loss: 2.0631 2022/10/09 22:19:51 - mmengine - INFO - Epoch(train) [7][440/940] lr: 1.0000e-02 eta: 12:24:39 time: 0.4766 data_time: 0.0257 memory: 21547 grad_norm: 3.4268 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0913 loss: 2.0913 2022/10/09 22:20:01 - mmengine - INFO - Epoch(train) [7][460/940] lr: 1.0000e-02 eta: 12:24:27 time: 0.5030 data_time: 0.0473 memory: 21547 grad_norm: 3.4818 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 2.0950 loss: 2.0950 2022/10/09 22:20:11 - mmengine - INFO - Epoch(train) [7][480/940] lr: 1.0000e-02 eta: 12:24:12 time: 0.4903 data_time: 0.0416 memory: 21547 grad_norm: 3.3961 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.0461 loss: 2.0461 2022/10/09 22:20:21 - mmengine - INFO - Epoch(train) [7][500/940] lr: 1.0000e-02 eta: 12:24:04 time: 0.5164 data_time: 0.0867 memory: 21547 grad_norm: 3.5015 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.1576 loss: 2.1576 2022/10/09 22:20:31 - mmengine - INFO - Epoch(train) [7][520/940] lr: 1.0000e-02 eta: 12:23:50 time: 0.4932 data_time: 0.0438 memory: 21547 grad_norm: 3.4276 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.1408 loss: 2.1408 2022/10/09 22:20:42 - mmengine - INFO - Epoch(train) [7][540/940] lr: 1.0000e-02 eta: 12:23:50 time: 0.5434 data_time: 0.0465 memory: 21547 grad_norm: 3.4511 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.0332 loss: 2.0332 2022/10/09 22:20:52 - mmengine - INFO - Epoch(train) [7][560/940] lr: 1.0000e-02 eta: 12:23:36 time: 0.4955 data_time: 0.0260 memory: 21547 grad_norm: 3.4173 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.9969 loss: 1.9969 2022/10/09 22:21:02 - mmengine - INFO - Epoch(train) [7][580/940] lr: 1.0000e-02 eta: 12:23:18 time: 0.4808 data_time: 0.0366 memory: 21547 grad_norm: 3.4822 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0462 loss: 2.0462 2022/10/09 22:21:12 - mmengine - INFO - Epoch(train) [7][600/940] lr: 1.0000e-02 eta: 12:23:14 time: 0.5301 data_time: 0.0241 memory: 21547 grad_norm: 3.4875 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0969 loss: 2.0969 2022/10/09 22:21:22 - mmengine - INFO - Epoch(train) [7][620/940] lr: 1.0000e-02 eta: 12:22:57 time: 0.4833 data_time: 0.0511 memory: 21547 grad_norm: 3.4952 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.0990 loss: 2.0990 2022/10/09 22:21:32 - mmengine - INFO - Epoch(train) [7][640/940] lr: 1.0000e-02 eta: 12:22:43 time: 0.4943 data_time: 0.0327 memory: 21547 grad_norm: 3.4594 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 2.0314 loss: 2.0314 2022/10/09 22:21:43 - mmengine - INFO - Epoch(train) [7][660/940] lr: 1.0000e-02 eta: 12:22:40 time: 0.5348 data_time: 0.0290 memory: 21547 grad_norm: 3.4357 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.1178 loss: 2.1178 2022/10/09 22:21:52 - mmengine - INFO - Epoch(train) [7][680/940] lr: 1.0000e-02 eta: 12:22:22 time: 0.4796 data_time: 0.0224 memory: 21547 grad_norm: 3.5000 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.2320 loss: 2.2320 2022/10/09 22:22:02 - mmengine - INFO - Epoch(train) [7][700/940] lr: 1.0000e-02 eta: 12:22:07 time: 0.4916 data_time: 0.0305 memory: 21547 grad_norm: 3.5412 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.4003 loss: 2.4003 2022/10/09 22:22:12 - mmengine - INFO - Epoch(train) [7][720/940] lr: 1.0000e-02 eta: 12:21:51 time: 0.4869 data_time: 0.0264 memory: 21547 grad_norm: 3.4024 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1043 loss: 2.1043 2022/10/09 22:22:22 - mmengine - INFO - Epoch(train) [7][740/940] lr: 1.0000e-02 eta: 12:21:45 time: 0.5199 data_time: 0.0332 memory: 21547 grad_norm: 3.4480 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.0445 loss: 2.0445 2022/10/09 22:22:32 - mmengine - INFO - Epoch(train) [7][760/940] lr: 1.0000e-02 eta: 12:21:32 time: 0.4991 data_time: 0.0239 memory: 21547 grad_norm: 3.4900 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.1716 loss: 2.1716 2022/10/09 22:22:42 - mmengine - INFO - Epoch(train) [7][780/940] lr: 1.0000e-02 eta: 12:21:18 time: 0.4930 data_time: 0.0336 memory: 21547 grad_norm: 3.4873 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0197 loss: 2.0197 2022/10/09 22:22:51 - mmengine - INFO - Epoch(train) [7][800/940] lr: 1.0000e-02 eta: 12:20:55 time: 0.4597 data_time: 0.0244 memory: 21547 grad_norm: 3.5202 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.9989 loss: 1.9989 2022/10/09 22:23:02 - mmengine - INFO - Epoch(train) [7][820/940] lr: 1.0000e-02 eta: 12:20:55 time: 0.5454 data_time: 0.0258 memory: 21547 grad_norm: 3.4881 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 2.0535 loss: 2.0535 2022/10/09 22:23:12 - mmengine - INFO - Epoch(train) [7][840/940] lr: 1.0000e-02 eta: 12:20:39 time: 0.4858 data_time: 0.0307 memory: 21547 grad_norm: 3.5100 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.0404 loss: 2.0404 2022/10/09 22:23:22 - mmengine - INFO - Epoch(train) [7][860/940] lr: 1.0000e-02 eta: 12:20:30 time: 0.5157 data_time: 0.0291 memory: 21547 grad_norm: 3.5180 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.0892 loss: 2.0892 2022/10/09 22:23:32 - mmengine - INFO - Epoch(train) [7][880/940] lr: 1.0000e-02 eta: 12:20:23 time: 0.5177 data_time: 0.0287 memory: 21547 grad_norm: 3.4772 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.2300 loss: 2.2300 2022/10/09 22:23:42 - mmengine - INFO - Epoch(train) [7][900/940] lr: 1.0000e-02 eta: 12:20:06 time: 0.4837 data_time: 0.0316 memory: 21547 grad_norm: 3.4811 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.1371 loss: 2.1371 2022/10/09 22:23:52 - mmengine - INFO - Epoch(train) [7][920/940] lr: 1.0000e-02 eta: 12:19:52 time: 0.4908 data_time: 0.0215 memory: 21547 grad_norm: 3.4904 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0359 loss: 2.0359 2022/10/09 22:24:01 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 22:24:01 - mmengine - INFO - Epoch(train) [7][940/940] lr: 1.0000e-02 eta: 12:19:24 time: 0.4429 data_time: 0.0259 memory: 21547 grad_norm: 3.6408 top1_acc: 0.1429 top5_acc: 0.7143 loss_cls: 2.1114 loss: 2.1114 2022/10/09 22:24:13 - mmengine - INFO - Epoch(val) [7][20/78] eta: 0:00:35 time: 0.6096 data_time: 0.4992 memory: 3269 2022/10/09 22:24:22 - mmengine - INFO - Epoch(val) [7][40/78] eta: 0:00:16 time: 0.4268 data_time: 0.3179 memory: 3269 2022/10/09 22:24:32 - mmengine - INFO - Epoch(val) [7][60/78] eta: 0:00:09 time: 0.5455 data_time: 0.4390 memory: 3269 2022/10/09 22:24:42 - mmengine - INFO - Epoch(val) [7][78/78] acc/top1: 0.5807 acc/top5: 0.8122 acc/mean1: 0.5805 2022/10/09 22:24:43 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_5.pth is removed 2022/10/09 22:24:43 - mmengine - INFO - The best checkpoint with 0.5807 acc/top1 at 7 epoch is saved to best_acc/top1_epoch_7.pth. 2022/10/09 22:24:57 - mmengine - INFO - Epoch(train) [8][20/940] lr: 1.0000e-02 eta: 12:19:58 time: 0.6734 data_time: 0.2956 memory: 21547 grad_norm: 3.5091 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.2615 loss: 2.2615 2022/10/09 22:25:06 - mmengine - INFO - Epoch(train) [8][40/940] lr: 1.0000e-02 eta: 12:19:38 time: 0.4702 data_time: 0.0760 memory: 21547 grad_norm: 3.4428 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.0586 loss: 2.0586 2022/10/09 22:25:17 - mmengine - INFO - Epoch(train) [8][60/940] lr: 1.0000e-02 eta: 12:19:36 time: 0.5408 data_time: 0.0319 memory: 21547 grad_norm: 3.4717 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.9923 loss: 1.9923 2022/10/09 22:25:26 - mmengine - INFO - Epoch(train) [8][80/940] lr: 1.0000e-02 eta: 12:19:16 time: 0.4669 data_time: 0.0271 memory: 21547 grad_norm: 3.4448 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0978 loss: 2.0978 2022/10/09 22:25:36 - mmengine - INFO - Epoch(train) [8][100/940] lr: 1.0000e-02 eta: 12:19:05 time: 0.5070 data_time: 0.0443 memory: 21547 grad_norm: 3.4334 top1_acc: 0.3438 top5_acc: 0.6250 loss_cls: 2.0843 loss: 2.0843 2022/10/09 22:25:46 - mmengine - INFO - Epoch(train) [8][120/940] lr: 1.0000e-02 eta: 12:18:50 time: 0.4868 data_time: 0.0406 memory: 21547 grad_norm: 3.4738 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 2.0481 loss: 2.0481 2022/10/09 22:25:57 - mmengine - INFO - Epoch(train) [8][140/940] lr: 1.0000e-02 eta: 12:18:43 time: 0.5200 data_time: 0.0366 memory: 21547 grad_norm: 3.4950 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.0887 loss: 2.0887 2022/10/09 22:26:06 - mmengine - INFO - Epoch(train) [8][160/940] lr: 1.0000e-02 eta: 12:18:26 time: 0.4842 data_time: 0.0263 memory: 21547 grad_norm: 3.5368 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0578 loss: 2.0578 2022/10/09 22:26:17 - mmengine - INFO - Epoch(train) [8][180/940] lr: 1.0000e-02 eta: 12:18:25 time: 0.5417 data_time: 0.0264 memory: 21547 grad_norm: 3.5127 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.2185 loss: 2.2185 2022/10/09 22:26:27 - mmengine - INFO - Epoch(train) [8][200/940] lr: 1.0000e-02 eta: 12:18:11 time: 0.4950 data_time: 0.0258 memory: 21547 grad_norm: 3.5106 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.1331 loss: 2.1331 2022/10/09 22:26:38 - mmengine - INFO - Epoch(train) [8][220/940] lr: 1.0000e-02 eta: 12:18:07 time: 0.5302 data_time: 0.0326 memory: 21547 grad_norm: 3.6293 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0781 loss: 2.0781 2022/10/09 22:26:47 - mmengine - INFO - Epoch(train) [8][240/940] lr: 1.0000e-02 eta: 12:17:47 time: 0.4675 data_time: 0.0281 memory: 21547 grad_norm: 3.4973 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0855 loss: 2.0855 2022/10/09 22:26:57 - mmengine - INFO - Epoch(train) [8][260/940] lr: 1.0000e-02 eta: 12:17:41 time: 0.5250 data_time: 0.0282 memory: 21547 grad_norm: 3.4597 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.0547 loss: 2.0547 2022/10/09 22:27:07 - mmengine - INFO - Epoch(train) [8][280/940] lr: 1.0000e-02 eta: 12:17:21 time: 0.4700 data_time: 0.0265 memory: 21547 grad_norm: 3.5204 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.0020 loss: 2.0020 2022/10/09 22:27:17 - mmengine - INFO - Epoch(train) [8][300/940] lr: 1.0000e-02 eta: 12:17:17 time: 0.5341 data_time: 0.0264 memory: 21547 grad_norm: 3.5790 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 2.1352 loss: 2.1352 2022/10/09 22:27:26 - mmengine - INFO - Epoch(train) [8][320/940] lr: 1.0000e-02 eta: 12:16:51 time: 0.4432 data_time: 0.0261 memory: 21547 grad_norm: 3.4668 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.9909 loss: 1.9909 2022/10/09 22:27:36 - mmengine - INFO - Epoch(train) [8][340/940] lr: 1.0000e-02 eta: 12:16:39 time: 0.4984 data_time: 0.0312 memory: 21547 grad_norm: 3.5640 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 2.0125 loss: 2.0125 2022/10/09 22:27:47 - mmengine - INFO - Epoch(train) [8][360/940] lr: 1.0000e-02 eta: 12:16:36 time: 0.5390 data_time: 0.0265 memory: 21547 grad_norm: 3.5555 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9747 loss: 1.9747 2022/10/09 22:27:57 - mmengine - INFO - Epoch(train) [8][380/940] lr: 1.0000e-02 eta: 12:16:23 time: 0.4961 data_time: 0.0314 memory: 21547 grad_norm: 3.4610 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.0606 loss: 2.0606 2022/10/09 22:28:07 - mmengine - INFO - Epoch(train) [8][400/940] lr: 1.0000e-02 eta: 12:16:10 time: 0.4952 data_time: 0.0287 memory: 21547 grad_norm: 3.5078 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 2.1866 loss: 2.1866 2022/10/09 22:28:17 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 22:28:17 - mmengine - INFO - Epoch(train) [8][420/940] lr: 1.0000e-02 eta: 12:16:03 time: 0.5188 data_time: 0.0315 memory: 21547 grad_norm: 3.5139 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.1499 loss: 2.1499 2022/10/09 22:28:28 - mmengine - INFO - Epoch(train) [8][440/940] lr: 1.0000e-02 eta: 12:16:01 time: 0.5400 data_time: 0.0293 memory: 21547 grad_norm: 3.5116 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 2.0870 loss: 2.0870 2022/10/09 22:28:37 - mmengine - INFO - Epoch(train) [8][460/940] lr: 1.0000e-02 eta: 12:15:38 time: 0.4583 data_time: 0.0287 memory: 21547 grad_norm: 3.5209 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0133 loss: 2.0133 2022/10/09 22:28:48 - mmengine - INFO - Epoch(train) [8][480/940] lr: 1.0000e-02 eta: 12:15:31 time: 0.5187 data_time: 0.0252 memory: 21547 grad_norm: 3.4633 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 2.0698 loss: 2.0698 2022/10/09 22:28:58 - mmengine - INFO - Epoch(train) [8][500/940] lr: 1.0000e-02 eta: 12:15:22 time: 0.5119 data_time: 0.0281 memory: 21547 grad_norm: 3.5395 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.1155 loss: 2.1155 2022/10/09 22:29:08 - mmengine - INFO - Epoch(train) [8][520/940] lr: 1.0000e-02 eta: 12:15:09 time: 0.4978 data_time: 0.0327 memory: 21547 grad_norm: 3.4658 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0025 loss: 2.0025 2022/10/09 22:29:19 - mmengine - INFO - Epoch(train) [8][540/940] lr: 1.0000e-02 eta: 12:15:09 time: 0.5473 data_time: 0.0255 memory: 21547 grad_norm: 3.5010 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.9152 loss: 1.9152 2022/10/09 22:29:28 - mmengine - INFO - Epoch(train) [8][560/940] lr: 1.0000e-02 eta: 12:14:52 time: 0.4832 data_time: 0.0278 memory: 21547 grad_norm: 3.4811 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0769 loss: 2.0769 2022/10/09 22:29:38 - mmengine - INFO - Epoch(train) [8][580/940] lr: 1.0000e-02 eta: 12:14:38 time: 0.4913 data_time: 0.0346 memory: 21547 grad_norm: 3.5085 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0611 loss: 2.0611 2022/10/09 22:29:49 - mmengine - INFO - Epoch(train) [8][600/940] lr: 1.0000e-02 eta: 12:14:36 time: 0.5380 data_time: 0.0231 memory: 21547 grad_norm: 3.4794 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0080 loss: 2.0080 2022/10/09 22:29:59 - mmengine - INFO - Epoch(train) [8][620/940] lr: 1.0000e-02 eta: 12:14:22 time: 0.4953 data_time: 0.0327 memory: 21547 grad_norm: 3.4606 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9740 loss: 1.9740 2022/10/09 22:30:09 - mmengine - INFO - Epoch(train) [8][640/940] lr: 1.0000e-02 eta: 12:14:15 time: 0.5199 data_time: 0.0343 memory: 21547 grad_norm: 3.5502 top1_acc: 0.4062 top5_acc: 0.4688 loss_cls: 2.0143 loss: 2.0143 2022/10/09 22:30:19 - mmengine - INFO - Epoch(train) [8][660/940] lr: 1.0000e-02 eta: 12:14:03 time: 0.5010 data_time: 0.0300 memory: 21547 grad_norm: 3.5023 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0127 loss: 2.0127 2022/10/09 22:30:29 - mmengine - INFO - Epoch(train) [8][680/940] lr: 1.0000e-02 eta: 12:13:50 time: 0.4953 data_time: 0.0293 memory: 21547 grad_norm: 3.5227 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0004 loss: 2.0004 2022/10/09 22:30:39 - mmengine - INFO - Epoch(train) [8][700/940] lr: 1.0000e-02 eta: 12:13:33 time: 0.4780 data_time: 0.0275 memory: 21547 grad_norm: 3.5565 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9953 loss: 1.9953 2022/10/09 22:30:50 - mmengine - INFO - Epoch(train) [8][720/940] lr: 1.0000e-02 eta: 12:13:31 time: 0.5429 data_time: 0.0347 memory: 21547 grad_norm: 3.5522 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.1923 loss: 2.1923 2022/10/09 22:31:00 - mmengine - INFO - Epoch(train) [8][740/940] lr: 1.0000e-02 eta: 12:13:17 time: 0.4915 data_time: 0.0308 memory: 21547 grad_norm: 3.5085 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.9969 loss: 1.9969 2022/10/09 22:31:11 - mmengine - INFO - Epoch(train) [8][760/940] lr: 1.0000e-02 eta: 12:13:20 time: 0.5619 data_time: 0.0293 memory: 21547 grad_norm: 3.4932 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.1291 loss: 2.1291 2022/10/09 22:31:20 - mmengine - INFO - Epoch(train) [8][780/940] lr: 1.0000e-02 eta: 12:13:02 time: 0.4742 data_time: 0.0272 memory: 21547 grad_norm: 3.5452 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.9822 loss: 1.9822 2022/10/09 22:31:31 - mmengine - INFO - Epoch(train) [8][800/940] lr: 1.0000e-02 eta: 12:12:57 time: 0.5297 data_time: 0.0308 memory: 21547 grad_norm: 3.5046 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.1462 loss: 2.1462 2022/10/09 22:31:40 - mmengine - INFO - Epoch(train) [8][820/940] lr: 1.0000e-02 eta: 12:12:40 time: 0.4765 data_time: 0.0283 memory: 21547 grad_norm: 3.5204 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9756 loss: 1.9756 2022/10/09 22:31:52 - mmengine - INFO - Epoch(train) [8][840/940] lr: 1.0000e-02 eta: 12:12:42 time: 0.5603 data_time: 0.0240 memory: 21547 grad_norm: 3.5365 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.1996 loss: 2.1996 2022/10/09 22:32:01 - mmengine - INFO - Epoch(train) [8][860/940] lr: 1.0000e-02 eta: 12:12:23 time: 0.4708 data_time: 0.0297 memory: 21547 grad_norm: 3.4914 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.0996 loss: 2.0996 2022/10/09 22:32:12 - mmengine - INFO - Epoch(train) [8][880/940] lr: 1.0000e-02 eta: 12:12:17 time: 0.5268 data_time: 0.0304 memory: 21547 grad_norm: 3.5374 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.0950 loss: 2.0950 2022/10/09 22:32:21 - mmengine - INFO - Epoch(train) [8][900/940] lr: 1.0000e-02 eta: 12:12:02 time: 0.4858 data_time: 0.0300 memory: 21547 grad_norm: 3.4737 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9339 loss: 1.9339 2022/10/09 22:32:32 - mmengine - INFO - Epoch(train) [8][920/940] lr: 1.0000e-02 eta: 12:11:57 time: 0.5312 data_time: 0.0376 memory: 21547 grad_norm: 3.4862 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0318 loss: 2.0318 2022/10/09 22:32:41 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 22:32:41 - mmengine - INFO - Epoch(train) [8][940/940] lr: 1.0000e-02 eta: 12:11:30 time: 0.4333 data_time: 0.0238 memory: 21547 grad_norm: 3.7023 top1_acc: 0.2857 top5_acc: 0.4286 loss_cls: 2.0802 loss: 2.0802 2022/10/09 22:32:53 - mmengine - INFO - Epoch(val) [8][20/78] eta: 0:00:35 time: 0.6111 data_time: 0.5002 memory: 3269 2022/10/09 22:33:01 - mmengine - INFO - Epoch(val) [8][40/78] eta: 0:00:16 time: 0.4217 data_time: 0.3134 memory: 3269 2022/10/09 22:33:12 - mmengine - INFO - Epoch(val) [8][60/78] eta: 0:00:09 time: 0.5496 data_time: 0.4424 memory: 3269 2022/10/09 22:33:22 - mmengine - INFO - Epoch(val) [8][78/78] acc/top1: 0.5904 acc/top5: 0.8242 acc/mean1: 0.5904 2022/10/09 22:33:22 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_7.pth is removed 2022/10/09 22:33:23 - mmengine - INFO - The best checkpoint with 0.5904 acc/top1 at 8 epoch is saved to best_acc/top1_epoch_8.pth. 2022/10/09 22:33:36 - mmengine - INFO - Epoch(train) [9][20/940] lr: 1.0000e-02 eta: 12:11:59 time: 0.6778 data_time: 0.2611 memory: 21547 grad_norm: 3.5012 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0048 loss: 2.0048 2022/10/09 22:33:46 - mmengine - INFO - Epoch(train) [9][40/940] lr: 1.0000e-02 eta: 12:11:41 time: 0.4747 data_time: 0.0428 memory: 21547 grad_norm: 3.4801 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 2.0585 loss: 2.0585 2022/10/09 22:33:57 - mmengine - INFO - Epoch(train) [9][60/940] lr: 1.0000e-02 eta: 12:11:40 time: 0.5491 data_time: 0.0922 memory: 21547 grad_norm: 3.4709 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9405 loss: 1.9405 2022/10/09 22:34:06 - mmengine - INFO - Epoch(train) [9][80/940] lr: 1.0000e-02 eta: 12:11:23 time: 0.4774 data_time: 0.0315 memory: 21547 grad_norm: 3.5295 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.9836 loss: 1.9836 2022/10/09 22:34:17 - mmengine - INFO - Epoch(train) [9][100/940] lr: 1.0000e-02 eta: 12:11:19 time: 0.5333 data_time: 0.0317 memory: 21547 grad_norm: 3.4266 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9555 loss: 1.9555 2022/10/09 22:34:27 - mmengine - INFO - Epoch(train) [9][120/940] lr: 1.0000e-02 eta: 12:11:04 time: 0.4886 data_time: 0.0250 memory: 21547 grad_norm: 3.4895 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1156 loss: 2.1156 2022/10/09 22:34:37 - mmengine - INFO - Epoch(train) [9][140/940] lr: 1.0000e-02 eta: 12:10:58 time: 0.5257 data_time: 0.0301 memory: 21547 grad_norm: 3.4901 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.9580 loss: 1.9580 2022/10/09 22:34:47 - mmengine - INFO - Epoch(train) [9][160/940] lr: 1.0000e-02 eta: 12:10:38 time: 0.4647 data_time: 0.0459 memory: 21547 grad_norm: 3.4890 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7696 loss: 1.7696 2022/10/09 22:34:58 - mmengine - INFO - Epoch(train) [9][180/940] lr: 1.0000e-02 eta: 12:10:40 time: 0.5592 data_time: 0.0484 memory: 21547 grad_norm: 3.5684 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.8932 loss: 1.8932 2022/10/09 22:35:08 - mmengine - INFO - Epoch(train) [9][200/940] lr: 1.0000e-02 eta: 12:10:28 time: 0.4992 data_time: 0.0258 memory: 21547 grad_norm: 3.5421 top1_acc: 0.3750 top5_acc: 0.7812 loss_cls: 1.9302 loss: 1.9302 2022/10/09 22:35:18 - mmengine - INFO - Epoch(train) [9][220/940] lr: 1.0000e-02 eta: 12:10:16 time: 0.5032 data_time: 0.0303 memory: 21547 grad_norm: 3.5292 top1_acc: 0.2188 top5_acc: 0.6562 loss_cls: 2.0420 loss: 2.0420 2022/10/09 22:35:27 - mmengine - INFO - Epoch(train) [9][240/940] lr: 1.0000e-02 eta: 12:10:02 time: 0.4873 data_time: 0.0290 memory: 21547 grad_norm: 3.5498 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9610 loss: 1.9610 2022/10/09 22:35:38 - mmengine - INFO - Epoch(train) [9][260/940] lr: 1.0000e-02 eta: 12:09:56 time: 0.5277 data_time: 0.0311 memory: 21547 grad_norm: 3.5919 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 2.1114 loss: 2.1114 2022/10/09 22:35:47 - mmengine - INFO - Epoch(train) [9][280/940] lr: 1.0000e-02 eta: 12:09:35 time: 0.4598 data_time: 0.0247 memory: 21547 grad_norm: 3.5753 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.0661 loss: 2.0661 2022/10/09 22:35:58 - mmengine - INFO - Epoch(train) [9][300/940] lr: 1.0000e-02 eta: 12:09:29 time: 0.5244 data_time: 0.0252 memory: 21547 grad_norm: 3.5478 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.0747 loss: 2.0747 2022/10/09 22:36:08 - mmengine - INFO - Epoch(train) [9][320/940] lr: 1.0000e-02 eta: 12:09:16 time: 0.4973 data_time: 0.0247 memory: 21547 grad_norm: 3.4765 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.9686 loss: 1.9686 2022/10/09 22:36:18 - mmengine - INFO - Epoch(train) [9][340/940] lr: 1.0000e-02 eta: 12:09:13 time: 0.5400 data_time: 0.0304 memory: 21547 grad_norm: 3.5637 top1_acc: 0.3438 top5_acc: 0.5625 loss_cls: 2.1104 loss: 2.1104 2022/10/09 22:36:29 - mmengine - INFO - Epoch(train) [9][360/940] lr: 1.0000e-02 eta: 12:09:05 time: 0.5173 data_time: 0.0284 memory: 21547 grad_norm: 3.4891 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.9830 loss: 1.9830 2022/10/09 22:36:39 - mmengine - INFO - Epoch(train) [9][380/940] lr: 1.0000e-02 eta: 12:08:54 time: 0.5041 data_time: 0.0247 memory: 21547 grad_norm: 3.5357 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9192 loss: 1.9192 2022/10/09 22:36:48 - mmengine - INFO - Epoch(train) [9][400/940] lr: 1.0000e-02 eta: 12:08:34 time: 0.4625 data_time: 0.0262 memory: 21547 grad_norm: 3.5332 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.0710 loss: 2.0710 2022/10/09 22:36:58 - mmengine - INFO - Epoch(train) [9][420/940] lr: 1.0000e-02 eta: 12:08:25 time: 0.5154 data_time: 0.0307 memory: 21547 grad_norm: 3.5202 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.0142 loss: 2.0142 2022/10/09 22:37:08 - mmengine - INFO - Epoch(train) [9][440/940] lr: 1.0000e-02 eta: 12:08:12 time: 0.4918 data_time: 0.0296 memory: 21547 grad_norm: 3.5407 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8592 loss: 1.8592 2022/10/09 22:37:19 - mmengine - INFO - Epoch(train) [9][460/940] lr: 1.0000e-02 eta: 12:08:08 time: 0.5379 data_time: 0.0311 memory: 21547 grad_norm: 3.5647 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.0704 loss: 2.0704 2022/10/09 22:37:29 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 22:37:29 - mmengine - INFO - Epoch(train) [9][480/940] lr: 1.0000e-02 eta: 12:07:51 time: 0.4764 data_time: 0.0269 memory: 21547 grad_norm: 3.4820 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0902 loss: 2.0902 2022/10/09 22:37:40 - mmengine - INFO - Epoch(train) [9][500/940] lr: 1.0000e-02 eta: 12:07:52 time: 0.5585 data_time: 0.0249 memory: 21547 grad_norm: 3.5455 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9710 loss: 1.9710 2022/10/09 22:37:50 - mmengine - INFO - Epoch(train) [9][520/940] lr: 1.0000e-02 eta: 12:07:39 time: 0.4981 data_time: 0.0246 memory: 21547 grad_norm: 3.5933 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.0769 loss: 2.0769 2022/10/09 22:37:59 - mmengine - INFO - Epoch(train) [9][540/940] lr: 1.0000e-02 eta: 12:07:23 time: 0.4773 data_time: 0.0257 memory: 21547 grad_norm: 3.5411 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.0239 loss: 2.0239 2022/10/09 22:38:10 - mmengine - INFO - Epoch(train) [9][560/940] lr: 1.0000e-02 eta: 12:07:17 time: 0.5305 data_time: 0.0318 memory: 21547 grad_norm: 3.5566 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 2.0140 loss: 2.0140 2022/10/09 22:38:20 - mmengine - INFO - Epoch(train) [9][580/940] lr: 1.0000e-02 eta: 12:07:06 time: 0.5005 data_time: 0.0228 memory: 21547 grad_norm: 3.5093 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.0589 loss: 2.0589 2022/10/09 22:38:30 - mmengine - INFO - Epoch(train) [9][600/940] lr: 1.0000e-02 eta: 12:06:58 time: 0.5177 data_time: 0.0377 memory: 21547 grad_norm: 3.5633 top1_acc: 0.4375 top5_acc: 0.9062 loss_cls: 2.1219 loss: 2.1219 2022/10/09 22:38:40 - mmengine - INFO - Epoch(train) [9][620/940] lr: 1.0000e-02 eta: 12:06:42 time: 0.4828 data_time: 0.0283 memory: 21547 grad_norm: 3.5592 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 2.0722 loss: 2.0722 2022/10/09 22:38:51 - mmengine - INFO - Epoch(train) [9][640/940] lr: 1.0000e-02 eta: 12:06:41 time: 0.5515 data_time: 0.0266 memory: 21547 grad_norm: 3.5782 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9259 loss: 1.9259 2022/10/09 22:39:00 - mmengine - INFO - Epoch(train) [9][660/940] lr: 1.0000e-02 eta: 12:06:25 time: 0.4768 data_time: 0.0246 memory: 21547 grad_norm: 3.5349 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0823 loss: 2.0823 2022/10/09 22:39:11 - mmengine - INFO - Epoch(train) [9][680/940] lr: 1.0000e-02 eta: 12:06:15 time: 0.5109 data_time: 0.0255 memory: 21547 grad_norm: 3.5082 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.0469 loss: 2.0469 2022/10/09 22:39:21 - mmengine - INFO - Epoch(train) [9][700/940] lr: 1.0000e-02 eta: 12:06:06 time: 0.5115 data_time: 0.0329 memory: 21547 grad_norm: 3.5988 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 2.1336 loss: 2.1336 2022/10/09 22:39:31 - mmengine - INFO - Epoch(train) [9][720/940] lr: 1.0000e-02 eta: 12:05:57 time: 0.5149 data_time: 0.0289 memory: 21547 grad_norm: 3.5417 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.0794 loss: 2.0794 2022/10/09 22:39:42 - mmengine - INFO - Epoch(train) [9][740/940] lr: 1.0000e-02 eta: 12:05:50 time: 0.5220 data_time: 0.0244 memory: 21547 grad_norm: 3.5472 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9099 loss: 1.9099 2022/10/09 22:39:51 - mmengine - INFO - Epoch(train) [9][760/940] lr: 1.0000e-02 eta: 12:05:35 time: 0.4846 data_time: 0.0301 memory: 21547 grad_norm: 3.5676 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9972 loss: 1.9972 2022/10/09 22:40:01 - mmengine - INFO - Epoch(train) [9][780/940] lr: 1.0000e-02 eta: 12:05:18 time: 0.4772 data_time: 0.0229 memory: 21547 grad_norm: 3.6021 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.0213 loss: 2.0213 2022/10/09 22:40:10 - mmengine - INFO - Epoch(train) [9][800/940] lr: 1.0000e-02 eta: 12:05:02 time: 0.4784 data_time: 0.0257 memory: 21547 grad_norm: 3.5732 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.0806 loss: 2.0806 2022/10/09 22:40:20 - mmengine - INFO - Epoch(train) [9][820/940] lr: 1.0000e-02 eta: 12:04:47 time: 0.4859 data_time: 0.0238 memory: 21547 grad_norm: 3.6099 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.0185 loss: 2.0185 2022/10/09 22:40:31 - mmengine - INFO - Epoch(train) [9][840/940] lr: 1.0000e-02 eta: 12:04:47 time: 0.5546 data_time: 0.0274 memory: 21547 grad_norm: 3.6033 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 2.0179 loss: 2.0179 2022/10/09 22:40:40 - mmengine - INFO - Epoch(train) [9][860/940] lr: 1.0000e-02 eta: 12:04:27 time: 0.4587 data_time: 0.0340 memory: 21547 grad_norm: 3.5971 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.0528 loss: 2.0528 2022/10/09 22:40:51 - mmengine - INFO - Epoch(train) [9][880/940] lr: 1.0000e-02 eta: 12:04:22 time: 0.5324 data_time: 0.0276 memory: 21547 grad_norm: 3.5223 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.0834 loss: 2.0834 2022/10/09 22:41:01 - mmengine - INFO - Epoch(train) [9][900/940] lr: 1.0000e-02 eta: 12:04:12 time: 0.5089 data_time: 0.0323 memory: 21547 grad_norm: 3.5993 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.8892 loss: 1.8892 2022/10/09 22:41:11 - mmengine - INFO - Epoch(train) [9][920/940] lr: 1.0000e-02 eta: 12:03:59 time: 0.4966 data_time: 0.0235 memory: 21547 grad_norm: 3.5336 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1670 loss: 2.1670 2022/10/09 22:41:20 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 22:41:20 - mmengine - INFO - Epoch(train) [9][940/940] lr: 1.0000e-02 eta: 12:03:33 time: 0.4299 data_time: 0.0248 memory: 21547 grad_norm: 3.8200 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.9891 loss: 1.9891 2022/10/09 22:41:20 - mmengine - INFO - Saving checkpoint at 9 epochs 2022/10/09 22:41:33 - mmengine - INFO - Epoch(val) [9][20/78] eta: 0:00:35 time: 0.6115 data_time: 0.5069 memory: 3269 2022/10/09 22:41:41 - mmengine - INFO - Epoch(val) [9][40/78] eta: 0:00:15 time: 0.4197 data_time: 0.3150 memory: 3269 2022/10/09 22:41:52 - mmengine - INFO - Epoch(val) [9][60/78] eta: 0:00:09 time: 0.5545 data_time: 0.4477 memory: 3269 2022/10/09 22:42:02 - mmengine - INFO - Epoch(val) [9][78/78] acc/top1: 0.6000 acc/top5: 0.8254 acc/mean1: 0.5999 2022/10/09 22:42:02 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_8.pth is removed 2022/10/09 22:42:03 - mmengine - INFO - The best checkpoint with 0.6000 acc/top1 at 9 epoch is saved to best_acc/top1_epoch_9.pth. 2022/10/09 22:42:16 - mmengine - INFO - Epoch(train) [10][20/940] lr: 1.0000e-02 eta: 12:03:56 time: 0.6691 data_time: 0.2576 memory: 21547 grad_norm: 3.5274 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.9391 loss: 1.9391 2022/10/09 22:42:25 - mmengine - INFO - Epoch(train) [10][40/940] lr: 1.0000e-02 eta: 12:03:38 time: 0.4682 data_time: 0.0265 memory: 21547 grad_norm: 3.5326 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.9828 loss: 1.9828 2022/10/09 22:42:36 - mmengine - INFO - Epoch(train) [10][60/940] lr: 1.0000e-02 eta: 12:03:33 time: 0.5360 data_time: 0.0310 memory: 21547 grad_norm: 3.5574 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0423 loss: 2.0423 2022/10/09 22:42:46 - mmengine - INFO - Epoch(train) [10][80/940] lr: 1.0000e-02 eta: 12:03:23 time: 0.5090 data_time: 0.0253 memory: 21547 grad_norm: 3.5586 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8443 loss: 1.8443 2022/10/09 22:42:57 - mmengine - INFO - Epoch(train) [10][100/940] lr: 1.0000e-02 eta: 12:03:20 time: 0.5433 data_time: 0.0365 memory: 21547 grad_norm: 3.5545 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.9186 loss: 1.9186 2022/10/09 22:43:06 - mmengine - INFO - Epoch(train) [10][120/940] lr: 1.0000e-02 eta: 12:02:53 time: 0.4248 data_time: 0.0256 memory: 21547 grad_norm: 3.5345 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.9373 loss: 1.9373 2022/10/09 22:43:17 - mmengine - INFO - Epoch(train) [10][140/940] lr: 1.0000e-02 eta: 12:02:52 time: 0.5532 data_time: 0.0277 memory: 21547 grad_norm: 3.5431 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0788 loss: 2.0788 2022/10/09 22:43:26 - mmengine - INFO - Epoch(train) [10][160/940] lr: 1.0000e-02 eta: 12:02:32 time: 0.4547 data_time: 0.0290 memory: 21547 grad_norm: 3.5267 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0686 loss: 2.0686 2022/10/09 22:43:36 - mmengine - INFO - Epoch(train) [10][180/940] lr: 1.0000e-02 eta: 12:02:22 time: 0.5114 data_time: 0.0306 memory: 21547 grad_norm: 3.6110 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 2.0945 loss: 2.0945 2022/10/09 22:43:46 - mmengine - INFO - Epoch(train) [10][200/940] lr: 1.0000e-02 eta: 12:02:08 time: 0.4899 data_time: 0.0286 memory: 21547 grad_norm: 3.5677 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8737 loss: 1.8737 2022/10/09 22:43:56 - mmengine - INFO - Epoch(train) [10][220/940] lr: 1.0000e-02 eta: 12:02:02 time: 0.5286 data_time: 0.0270 memory: 21547 grad_norm: 3.5121 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0199 loss: 2.0199 2022/10/09 22:44:06 - mmengine - INFO - Epoch(train) [10][240/940] lr: 1.0000e-02 eta: 12:01:53 time: 0.5093 data_time: 0.0309 memory: 21547 grad_norm: 3.5383 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.9481 loss: 1.9481 2022/10/09 22:44:17 - mmengine - INFO - Epoch(train) [10][260/940] lr: 1.0000e-02 eta: 12:01:44 time: 0.5174 data_time: 0.0278 memory: 21547 grad_norm: 3.5414 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.0016 loss: 2.0016 2022/10/09 22:44:27 - mmengine - INFO - Epoch(train) [10][280/940] lr: 1.0000e-02 eta: 12:01:35 time: 0.5120 data_time: 0.0317 memory: 21547 grad_norm: 3.4977 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.0332 loss: 2.0332 2022/10/09 22:44:38 - mmengine - INFO - Epoch(train) [10][300/940] lr: 1.0000e-02 eta: 12:01:28 time: 0.5257 data_time: 0.0256 memory: 21547 grad_norm: 3.5387 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0358 loss: 2.0358 2022/10/09 22:44:47 - mmengine - INFO - Epoch(train) [10][320/940] lr: 1.0000e-02 eta: 12:01:08 time: 0.4561 data_time: 0.0323 memory: 21547 grad_norm: 3.5163 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.9517 loss: 1.9517 2022/10/09 22:44:57 - mmengine - INFO - Epoch(train) [10][340/940] lr: 1.0000e-02 eta: 12:01:00 time: 0.5185 data_time: 0.0255 memory: 21547 grad_norm: 3.5646 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.9352 loss: 1.9352 2022/10/09 22:45:06 - mmengine - INFO - Epoch(train) [10][360/940] lr: 1.0000e-02 eta: 12:00:40 time: 0.4558 data_time: 0.0277 memory: 21547 grad_norm: 3.5131 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0189 loss: 2.0189 2022/10/09 22:45:16 - mmengine - INFO - Epoch(train) [10][380/940] lr: 1.0000e-02 eta: 12:00:30 time: 0.5104 data_time: 0.0232 memory: 21547 grad_norm: 3.5363 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.8897 loss: 1.8897 2022/10/09 22:45:26 - mmengine - INFO - Epoch(train) [10][400/940] lr: 1.0000e-02 eta: 12:00:15 time: 0.4799 data_time: 0.0291 memory: 21547 grad_norm: 3.5117 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.0092 loss: 2.0092 2022/10/09 22:45:37 - mmengine - INFO - Epoch(train) [10][420/940] lr: 1.0000e-02 eta: 12:00:15 time: 0.5599 data_time: 0.0292 memory: 21547 grad_norm: 3.5488 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9952 loss: 1.9952 2022/10/09 22:45:47 - mmengine - INFO - Epoch(train) [10][440/940] lr: 1.0000e-02 eta: 11:59:59 time: 0.4795 data_time: 0.0237 memory: 21547 grad_norm: 3.5226 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.9940 loss: 1.9940 2022/10/09 22:45:57 - mmengine - INFO - Epoch(train) [10][460/940] lr: 1.0000e-02 eta: 11:59:46 time: 0.4901 data_time: 0.0277 memory: 21547 grad_norm: 3.5651 top1_acc: 0.5000 top5_acc: 0.9062 loss_cls: 2.0044 loss: 2.0044 2022/10/09 22:46:07 - mmengine - INFO - Epoch(train) [10][480/940] lr: 1.0000e-02 eta: 11:59:36 time: 0.5114 data_time: 0.0254 memory: 21547 grad_norm: 3.5931 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9377 loss: 1.9377 2022/10/09 22:46:17 - mmengine - INFO - Epoch(train) [10][500/940] lr: 1.0000e-02 eta: 11:59:29 time: 0.5241 data_time: 0.0299 memory: 21547 grad_norm: 3.6509 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9398 loss: 1.9398 2022/10/09 22:46:27 - mmengine - INFO - Epoch(train) [10][520/940] lr: 1.0000e-02 eta: 11:59:16 time: 0.4922 data_time: 0.0289 memory: 21547 grad_norm: 3.6446 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9591 loss: 1.9591 2022/10/09 22:46:37 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 22:46:37 - mmengine - INFO - Epoch(train) [10][540/940] lr: 1.0000e-02 eta: 11:59:00 time: 0.4784 data_time: 0.0249 memory: 21547 grad_norm: 3.5492 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.9461 loss: 1.9461 2022/10/09 22:46:46 - mmengine - INFO - Epoch(train) [10][560/940] lr: 1.0000e-02 eta: 11:58:46 time: 0.4827 data_time: 0.0282 memory: 21547 grad_norm: 3.6388 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.9275 loss: 1.9275 2022/10/09 22:46:57 - mmengine - INFO - Epoch(train) [10][580/940] lr: 1.0000e-02 eta: 11:58:38 time: 0.5199 data_time: 0.0277 memory: 21547 grad_norm: 3.5793 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 2.0464 loss: 2.0464 2022/10/09 22:47:06 - mmengine - INFO - Epoch(train) [10][600/940] lr: 1.0000e-02 eta: 11:58:19 time: 0.4615 data_time: 0.0334 memory: 21547 grad_norm: 3.5451 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 1.9949 loss: 1.9949 2022/10/09 22:47:16 - mmengine - INFO - Epoch(train) [10][620/940] lr: 1.0000e-02 eta: 11:58:10 time: 0.5144 data_time: 0.0245 memory: 21547 grad_norm: 3.5590 top1_acc: 0.4375 top5_acc: 0.8438 loss_cls: 2.0646 loss: 2.0646 2022/10/09 22:47:26 - mmengine - INFO - Epoch(train) [10][640/940] lr: 1.0000e-02 eta: 11:57:58 time: 0.4955 data_time: 0.0315 memory: 21547 grad_norm: 3.5774 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.9541 loss: 1.9541 2022/10/09 22:47:37 - mmengine - INFO - Epoch(train) [10][660/940] lr: 1.0000e-02 eta: 11:57:51 time: 0.5281 data_time: 0.0308 memory: 21547 grad_norm: 3.5967 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.9144 loss: 1.9144 2022/10/09 22:47:47 - mmengine - INFO - Epoch(train) [10][680/940] lr: 1.0000e-02 eta: 11:57:39 time: 0.4966 data_time: 0.0265 memory: 21547 grad_norm: 3.6876 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 2.0632 loss: 2.0632 2022/10/09 22:47:56 - mmengine - INFO - Epoch(train) [10][700/940] lr: 1.0000e-02 eta: 11:57:25 time: 0.4855 data_time: 0.0269 memory: 21547 grad_norm: 3.5892 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 2.0205 loss: 2.0205 2022/10/09 22:48:07 - mmengine - INFO - Epoch(train) [10][720/940] lr: 1.0000e-02 eta: 11:57:22 time: 0.5435 data_time: 0.0347 memory: 21547 grad_norm: 3.5503 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9235 loss: 1.9235 2022/10/09 22:48:17 - mmengine - INFO - Epoch(train) [10][740/940] lr: 1.0000e-02 eta: 11:57:10 time: 0.4978 data_time: 0.0225 memory: 21547 grad_norm: 3.5902 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.1436 loss: 2.1436 2022/10/09 22:48:27 - mmengine - INFO - Epoch(train) [10][760/940] lr: 1.0000e-02 eta: 11:57:01 time: 0.5129 data_time: 0.0297 memory: 21547 grad_norm: 3.5282 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.0280 loss: 2.0280 2022/10/09 22:48:37 - mmengine - INFO - Epoch(train) [10][780/940] lr: 1.0000e-02 eta: 11:56:48 time: 0.4943 data_time: 0.0248 memory: 21547 grad_norm: 3.5447 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.9116 loss: 1.9116 2022/10/09 22:48:48 - mmengine - INFO - Epoch(train) [10][800/940] lr: 1.0000e-02 eta: 11:56:46 time: 0.5540 data_time: 0.0310 memory: 21547 grad_norm: 3.6464 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.1046 loss: 2.1046 2022/10/09 22:48:58 - mmengine - INFO - Epoch(train) [10][820/940] lr: 1.0000e-02 eta: 11:56:33 time: 0.4890 data_time: 0.0328 memory: 21547 grad_norm: 3.5924 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.9497 loss: 1.9497 2022/10/09 22:49:09 - mmengine - INFO - Epoch(train) [10][840/940] lr: 1.0000e-02 eta: 11:56:24 time: 0.5137 data_time: 0.0222 memory: 21547 grad_norm: 3.5687 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.9338 loss: 1.9338 2022/10/09 22:49:18 - mmengine - INFO - Epoch(train) [10][860/940] lr: 1.0000e-02 eta: 11:56:10 time: 0.4897 data_time: 0.0343 memory: 21547 grad_norm: 3.5918 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.1568 loss: 2.1568 2022/10/09 22:49:28 - mmengine - INFO - Epoch(train) [10][880/940] lr: 1.0000e-02 eta: 11:55:57 time: 0.4895 data_time: 0.0264 memory: 21547 grad_norm: 3.5440 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9736 loss: 1.9736 2022/10/09 22:49:38 - mmengine - INFO - Epoch(train) [10][900/940] lr: 1.0000e-02 eta: 11:55:42 time: 0.4820 data_time: 0.0235 memory: 21547 grad_norm: 3.6336 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.9395 loss: 1.9395 2022/10/09 22:49:49 - mmengine - INFO - Epoch(train) [10][920/940] lr: 1.0000e-02 eta: 11:55:38 time: 0.5407 data_time: 0.0299 memory: 21547 grad_norm: 3.5544 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9088 loss: 1.9088 2022/10/09 22:49:57 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 22:49:57 - mmengine - INFO - Epoch(train) [10][940/940] lr: 1.0000e-02 eta: 11:55:14 time: 0.4324 data_time: 0.0246 memory: 21547 grad_norm: 3.7060 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 2.1446 loss: 2.1446 2022/10/09 22:50:09 - mmengine - INFO - Epoch(val) [10][20/78] eta: 0:00:35 time: 0.6049 data_time: 0.4939 memory: 3269 2022/10/09 22:50:18 - mmengine - INFO - Epoch(val) [10][40/78] eta: 0:00:16 time: 0.4284 data_time: 0.3200 memory: 3269 2022/10/09 22:50:29 - mmengine - INFO - Epoch(val) [10][60/78] eta: 0:00:09 time: 0.5485 data_time: 0.4415 memory: 3269 2022/10/09 22:50:39 - mmengine - INFO - Epoch(val) [10][78/78] acc/top1: 0.5987 acc/top5: 0.8265 acc/mean1: 0.5986 2022/10/09 22:50:53 - mmengine - INFO - Epoch(train) [11][20/940] lr: 1.0000e-02 eta: 11:55:40 time: 0.7081 data_time: 0.3271 memory: 21547 grad_norm: 3.5661 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8768 loss: 1.8768 2022/10/09 22:51:03 - mmengine - INFO - Epoch(train) [11][40/940] lr: 1.0000e-02 eta: 11:55:25 time: 0.4763 data_time: 0.0859 memory: 21547 grad_norm: 3.5512 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.9233 loss: 1.9233 2022/10/09 22:51:13 - mmengine - INFO - Epoch(train) [11][60/940] lr: 1.0000e-02 eta: 11:55:20 time: 0.5374 data_time: 0.1616 memory: 21547 grad_norm: 3.5522 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 1.7377 loss: 1.7377 2022/10/09 22:51:24 - mmengine - INFO - Epoch(train) [11][80/940] lr: 1.0000e-02 eta: 11:55:11 time: 0.5133 data_time: 0.0899 memory: 21547 grad_norm: 3.5224 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9255 loss: 1.9255 2022/10/09 22:51:35 - mmengine - INFO - Epoch(train) [11][100/940] lr: 1.0000e-02 eta: 11:55:07 time: 0.5429 data_time: 0.0434 memory: 21547 grad_norm: 3.5294 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.0142 loss: 2.0142 2022/10/09 22:51:44 - mmengine - INFO - Epoch(train) [11][120/940] lr: 1.0000e-02 eta: 11:54:54 time: 0.4907 data_time: 0.0271 memory: 21547 grad_norm: 3.6576 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9849 loss: 1.9849 2022/10/09 22:51:55 - mmengine - INFO - Epoch(train) [11][140/940] lr: 1.0000e-02 eta: 11:54:50 time: 0.5433 data_time: 0.0280 memory: 21547 grad_norm: 3.6253 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.0438 loss: 2.0438 2022/10/09 22:52:04 - mmengine - INFO - Epoch(train) [11][160/940] lr: 1.0000e-02 eta: 11:54:31 time: 0.4568 data_time: 0.0260 memory: 21547 grad_norm: 3.5236 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8993 loss: 1.8993 2022/10/09 22:52:15 - mmengine - INFO - Epoch(train) [11][180/940] lr: 1.0000e-02 eta: 11:54:24 time: 0.5303 data_time: 0.0289 memory: 21547 grad_norm: 3.5810 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8699 loss: 1.8699 2022/10/09 22:52:25 - mmengine - INFO - Epoch(train) [11][200/940] lr: 1.0000e-02 eta: 11:54:09 time: 0.4773 data_time: 0.0297 memory: 21547 grad_norm: 3.5480 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.9446 loss: 1.9446 2022/10/09 22:52:35 - mmengine - INFO - Epoch(train) [11][220/940] lr: 1.0000e-02 eta: 11:54:03 time: 0.5341 data_time: 0.0291 memory: 21547 grad_norm: 3.6097 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.0466 loss: 2.0466 2022/10/09 22:52:44 - mmengine - INFO - Epoch(train) [11][240/940] lr: 1.0000e-02 eta: 11:53:46 time: 0.4647 data_time: 0.0349 memory: 21547 grad_norm: 3.6291 top1_acc: 0.3750 top5_acc: 0.8438 loss_cls: 1.9747 loss: 1.9747 2022/10/09 22:52:55 - mmengine - INFO - Epoch(train) [11][260/940] lr: 1.0000e-02 eta: 11:53:41 time: 0.5394 data_time: 0.0292 memory: 21547 grad_norm: 3.5277 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9555 loss: 1.9555 2022/10/09 22:53:05 - mmengine - INFO - Epoch(train) [11][280/940] lr: 1.0000e-02 eta: 11:53:24 time: 0.4656 data_time: 0.0262 memory: 21547 grad_norm: 3.6147 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8791 loss: 1.8791 2022/10/09 22:53:15 - mmengine - INFO - Epoch(train) [11][300/940] lr: 1.0000e-02 eta: 11:53:20 time: 0.5437 data_time: 0.0302 memory: 21547 grad_norm: 3.6714 top1_acc: 0.3750 top5_acc: 0.7812 loss_cls: 1.9960 loss: 1.9960 2022/10/09 22:53:26 - mmengine - INFO - Epoch(train) [11][320/940] lr: 1.0000e-02 eta: 11:53:09 time: 0.5070 data_time: 0.0254 memory: 21547 grad_norm: 3.6511 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9249 loss: 1.9249 2022/10/09 22:53:35 - mmengine - INFO - Epoch(train) [11][340/940] lr: 1.0000e-02 eta: 11:52:54 time: 0.4776 data_time: 0.0250 memory: 21547 grad_norm: 3.5376 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7456 loss: 1.7456 2022/10/09 22:53:45 - mmengine - INFO - Epoch(train) [11][360/940] lr: 1.0000e-02 eta: 11:52:43 time: 0.5010 data_time: 0.0331 memory: 21547 grad_norm: 3.5889 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8715 loss: 1.8715 2022/10/09 22:53:56 - mmengine - INFO - Epoch(train) [11][380/940] lr: 1.0000e-02 eta: 11:52:35 time: 0.5211 data_time: 0.0272 memory: 21547 grad_norm: 3.5900 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9440 loss: 1.9440 2022/10/09 22:54:05 - mmengine - INFO - Epoch(train) [11][400/940] lr: 1.0000e-02 eta: 11:52:20 time: 0.4772 data_time: 0.0276 memory: 21547 grad_norm: 3.5894 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 2.0051 loss: 2.0051 2022/10/09 22:54:16 - mmengine - INFO - Epoch(train) [11][420/940] lr: 1.0000e-02 eta: 11:52:15 time: 0.5380 data_time: 0.0293 memory: 21547 grad_norm: 3.6436 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.0146 loss: 2.0146 2022/10/09 22:54:25 - mmengine - INFO - Epoch(train) [11][440/940] lr: 1.0000e-02 eta: 11:51:56 time: 0.4575 data_time: 0.0281 memory: 21547 grad_norm: 3.6316 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8083 loss: 1.8083 2022/10/09 22:54:35 - mmengine - INFO - Epoch(train) [11][460/940] lr: 1.0000e-02 eta: 11:51:46 time: 0.5067 data_time: 0.0270 memory: 21547 grad_norm: 3.6570 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.9081 loss: 1.9081 2022/10/09 22:54:45 - mmengine - INFO - Epoch(train) [11][480/940] lr: 1.0000e-02 eta: 11:51:33 time: 0.4923 data_time: 0.0311 memory: 21547 grad_norm: 3.6269 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0147 loss: 2.0147 2022/10/09 22:54:56 - mmengine - INFO - Epoch(train) [11][500/940] lr: 1.0000e-02 eta: 11:51:31 time: 0.5543 data_time: 0.0272 memory: 21547 grad_norm: 3.5422 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8542 loss: 1.8542 2022/10/09 22:55:05 - mmengine - INFO - Epoch(train) [11][520/940] lr: 1.0000e-02 eta: 11:51:10 time: 0.4481 data_time: 0.0288 memory: 21547 grad_norm: 3.5761 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9636 loss: 1.9636 2022/10/09 22:55:16 - mmengine - INFO - Epoch(train) [11][540/940] lr: 1.0000e-02 eta: 11:51:03 time: 0.5245 data_time: 0.0311 memory: 21547 grad_norm: 3.5983 top1_acc: 0.4375 top5_acc: 0.5938 loss_cls: 1.9341 loss: 1.9341 2022/10/09 22:55:25 - mmengine - INFO - Epoch(train) [11][560/940] lr: 1.0000e-02 eta: 11:50:48 time: 0.4778 data_time: 0.0313 memory: 21547 grad_norm: 3.5557 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9699 loss: 1.9699 2022/10/09 22:55:35 - mmengine - INFO - Epoch(train) [11][580/940] lr: 1.0000e-02 eta: 11:50:39 time: 0.5156 data_time: 0.0288 memory: 21547 grad_norm: 3.6780 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9723 loss: 1.9723 2022/10/09 22:55:46 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 22:55:46 - mmengine - INFO - Epoch(train) [11][600/940] lr: 1.0000e-02 eta: 11:50:30 time: 0.5157 data_time: 0.0262 memory: 21547 grad_norm: 3.6720 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.9321 loss: 1.9321 2022/10/09 22:55:56 - mmengine - INFO - Epoch(train) [11][620/940] lr: 1.0000e-02 eta: 11:50:18 time: 0.4921 data_time: 0.0513 memory: 21547 grad_norm: 3.5797 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 2.1170 loss: 2.1170 2022/10/09 22:56:06 - mmengine - INFO - Epoch(train) [11][640/940] lr: 1.0000e-02 eta: 11:50:09 time: 0.5154 data_time: 0.0926 memory: 21547 grad_norm: 3.6232 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.1215 loss: 2.1215 2022/10/09 22:56:16 - mmengine - INFO - Epoch(train) [11][660/940] lr: 1.0000e-02 eta: 11:49:58 time: 0.5008 data_time: 0.1003 memory: 21547 grad_norm: 3.5447 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.8616 loss: 1.8616 2022/10/09 22:56:25 - mmengine - INFO - Epoch(train) [11][680/940] lr: 1.0000e-02 eta: 11:49:41 time: 0.4714 data_time: 0.0448 memory: 21547 grad_norm: 3.6303 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.0864 loss: 2.0864 2022/10/09 22:56:35 - mmengine - INFO - Epoch(train) [11][700/940] lr: 1.0000e-02 eta: 11:49:28 time: 0.4866 data_time: 0.0643 memory: 21547 grad_norm: 3.6248 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9631 loss: 1.9631 2022/10/09 22:56:45 - mmengine - INFO - Epoch(train) [11][720/940] lr: 1.0000e-02 eta: 11:49:17 time: 0.5022 data_time: 0.0222 memory: 21547 grad_norm: 3.6007 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.0395 loss: 2.0395 2022/10/09 22:56:56 - mmengine - INFO - Epoch(train) [11][740/940] lr: 1.0000e-02 eta: 11:49:11 time: 0.5334 data_time: 0.0359 memory: 21547 grad_norm: 3.5513 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.9289 loss: 1.9289 2022/10/09 22:57:06 - mmengine - INFO - Epoch(train) [11][760/940] lr: 1.0000e-02 eta: 11:49:01 time: 0.5103 data_time: 0.0332 memory: 21547 grad_norm: 3.6652 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.0271 loss: 2.0271 2022/10/09 22:57:16 - mmengine - INFO - Epoch(train) [11][780/940] lr: 1.0000e-02 eta: 11:48:48 time: 0.4863 data_time: 0.0372 memory: 21547 grad_norm: 3.6812 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 2.0220 loss: 2.0220 2022/10/09 22:57:26 - mmengine - INFO - Epoch(train) [11][800/940] lr: 1.0000e-02 eta: 11:48:40 time: 0.5212 data_time: 0.0264 memory: 21547 grad_norm: 3.5764 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.9084 loss: 1.9084 2022/10/09 22:57:36 - mmengine - INFO - Epoch(train) [11][820/940] lr: 1.0000e-02 eta: 11:48:25 time: 0.4766 data_time: 0.0434 memory: 21547 grad_norm: 3.5093 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1185 loss: 2.1185 2022/10/09 22:57:46 - mmengine - INFO - Epoch(train) [11][840/940] lr: 1.0000e-02 eta: 11:48:17 time: 0.5225 data_time: 0.0685 memory: 21547 grad_norm: 3.6062 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0522 loss: 2.0522 2022/10/09 22:57:57 - mmengine - INFO - Epoch(train) [11][860/940] lr: 1.0000e-02 eta: 11:48:10 time: 0.5295 data_time: 0.1034 memory: 21547 grad_norm: 3.5388 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9583 loss: 1.9583 2022/10/09 22:58:07 - mmengine - INFO - Epoch(train) [11][880/940] lr: 1.0000e-02 eta: 11:48:04 time: 0.5329 data_time: 0.0240 memory: 21547 grad_norm: 3.6844 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9445 loss: 1.9445 2022/10/09 22:58:18 - mmengine - INFO - Epoch(train) [11][900/940] lr: 1.0000e-02 eta: 11:47:56 time: 0.5169 data_time: 0.0313 memory: 21547 grad_norm: 3.5631 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.0907 loss: 2.0907 2022/10/09 22:58:28 - mmengine - INFO - Epoch(train) [11][920/940] lr: 1.0000e-02 eta: 11:47:43 time: 0.4890 data_time: 0.0233 memory: 21547 grad_norm: 3.5402 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.9438 loss: 1.9438 2022/10/09 22:58:36 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 22:58:36 - mmengine - INFO - Epoch(train) [11][940/940] lr: 1.0000e-02 eta: 11:47:22 time: 0.4427 data_time: 0.0235 memory: 21547 grad_norm: 3.6355 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.8799 loss: 1.8799 2022/10/09 22:58:49 - mmengine - INFO - Epoch(val) [11][20/78] eta: 0:00:35 time: 0.6175 data_time: 0.5068 memory: 3269 2022/10/09 22:58:57 - mmengine - INFO - Epoch(val) [11][40/78] eta: 0:00:15 time: 0.4179 data_time: 0.3109 memory: 3269 2022/10/09 22:59:09 - mmengine - INFO - Epoch(val) [11][60/78] eta: 0:00:10 time: 0.5786 data_time: 0.4714 memory: 3269 2022/10/09 22:59:18 - mmengine - INFO - Epoch(val) [11][78/78] acc/top1: 0.5949 acc/top5: 0.8246 acc/mean1: 0.5948 2022/10/09 22:59:32 - mmengine - INFO - Epoch(train) [12][20/940] lr: 1.0000e-02 eta: 11:47:41 time: 0.6878 data_time: 0.1955 memory: 21547 grad_norm: 3.5149 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.9393 loss: 1.9393 2022/10/09 22:59:41 - mmengine - INFO - Epoch(train) [12][40/940] lr: 1.0000e-02 eta: 11:47:25 time: 0.4707 data_time: 0.0260 memory: 21547 grad_norm: 3.5793 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8627 loss: 1.8627 2022/10/09 22:59:52 - mmengine - INFO - Epoch(train) [12][60/940] lr: 1.0000e-02 eta: 11:47:16 time: 0.5149 data_time: 0.0416 memory: 21547 grad_norm: 3.6229 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.0516 loss: 2.0516 2022/10/09 23:00:02 - mmengine - INFO - Epoch(train) [12][80/940] lr: 1.0000e-02 eta: 11:47:06 time: 0.5109 data_time: 0.0288 memory: 21547 grad_norm: 3.5950 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9612 loss: 1.9612 2022/10/09 23:00:12 - mmengine - INFO - Epoch(train) [12][100/940] lr: 1.0000e-02 eta: 11:46:59 time: 0.5268 data_time: 0.0308 memory: 21547 grad_norm: 3.6173 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8999 loss: 1.8999 2022/10/09 23:00:22 - mmengine - INFO - Epoch(train) [12][120/940] lr: 1.0000e-02 eta: 11:46:47 time: 0.4972 data_time: 0.0267 memory: 21547 grad_norm: 3.6506 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8990 loss: 1.8990 2022/10/09 23:00:33 - mmengine - INFO - Epoch(train) [12][140/940] lr: 1.0000e-02 eta: 11:46:41 time: 0.5319 data_time: 0.0281 memory: 21547 grad_norm: 3.6883 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 2.0668 loss: 2.0668 2022/10/09 23:00:42 - mmengine - INFO - Epoch(train) [12][160/940] lr: 1.0000e-02 eta: 11:46:26 time: 0.4765 data_time: 0.0284 memory: 21547 grad_norm: 3.5996 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 2.0275 loss: 2.0275 2022/10/09 23:00:53 - mmengine - INFO - Epoch(train) [12][180/940] lr: 1.0000e-02 eta: 11:46:16 time: 0.5122 data_time: 0.0277 memory: 21547 grad_norm: 3.5387 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.8540 loss: 1.8540 2022/10/09 23:01:03 - mmengine - INFO - Epoch(train) [12][200/940] lr: 1.0000e-02 eta: 11:46:06 time: 0.5052 data_time: 0.0286 memory: 21547 grad_norm: 3.5329 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.9405 loss: 1.9405 2022/10/09 23:01:13 - mmengine - INFO - Epoch(train) [12][220/940] lr: 1.0000e-02 eta: 11:45:54 time: 0.4984 data_time: 0.0279 memory: 21547 grad_norm: 3.7020 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 2.0816 loss: 2.0816 2022/10/09 23:01:23 - mmengine - INFO - Epoch(train) [12][240/940] lr: 1.0000e-02 eta: 11:45:41 time: 0.4891 data_time: 0.0284 memory: 21547 grad_norm: 3.5610 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9372 loss: 1.9372 2022/10/09 23:01:33 - mmengine - INFO - Epoch(train) [12][260/940] lr: 1.0000e-02 eta: 11:45:32 time: 0.5135 data_time: 0.0311 memory: 21547 grad_norm: 3.6760 top1_acc: 0.3750 top5_acc: 0.7812 loss_cls: 2.0314 loss: 2.0314 2022/10/09 23:01:42 - mmengine - INFO - Epoch(train) [12][280/940] lr: 1.0000e-02 eta: 11:45:15 time: 0.4669 data_time: 0.0307 memory: 21547 grad_norm: 3.6921 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.8511 loss: 1.8511 2022/10/09 23:01:53 - mmengine - INFO - Epoch(train) [12][300/940] lr: 1.0000e-02 eta: 11:45:08 time: 0.5249 data_time: 0.0283 memory: 21547 grad_norm: 3.7012 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8674 loss: 1.8674 2022/10/09 23:02:02 - mmengine - INFO - Epoch(train) [12][320/940] lr: 1.0000e-02 eta: 11:44:56 time: 0.4929 data_time: 0.0269 memory: 21547 grad_norm: 3.6783 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.9539 loss: 1.9539 2022/10/09 23:02:13 - mmengine - INFO - Epoch(train) [12][340/940] lr: 1.0000e-02 eta: 11:44:50 time: 0.5343 data_time: 0.0279 memory: 21547 grad_norm: 3.6466 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0487 loss: 2.0487 2022/10/09 23:02:23 - mmengine - INFO - Epoch(train) [12][360/940] lr: 1.0000e-02 eta: 11:44:38 time: 0.5010 data_time: 0.0293 memory: 21547 grad_norm: 3.6583 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.0856 loss: 2.0856 2022/10/09 23:02:34 - mmengine - INFO - Epoch(train) [12][380/940] lr: 1.0000e-02 eta: 11:44:31 time: 0.5225 data_time: 0.0235 memory: 21547 grad_norm: 3.6024 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8439 loss: 1.8439 2022/10/09 23:02:43 - mmengine - INFO - Epoch(train) [12][400/940] lr: 1.0000e-02 eta: 11:44:16 time: 0.4800 data_time: 0.0352 memory: 21547 grad_norm: 3.6664 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8837 loss: 1.8837 2022/10/09 23:02:53 - mmengine - INFO - Epoch(train) [12][420/940] lr: 1.0000e-02 eta: 11:44:04 time: 0.4954 data_time: 0.0395 memory: 21547 grad_norm: 3.6449 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.9356 loss: 1.9356 2022/10/09 23:03:03 - mmengine - INFO - Epoch(train) [12][440/940] lr: 1.0000e-02 eta: 11:43:49 time: 0.4721 data_time: 0.0276 memory: 21547 grad_norm: 3.5974 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9414 loss: 1.9414 2022/10/09 23:03:13 - mmengine - INFO - Epoch(train) [12][460/940] lr: 1.0000e-02 eta: 11:43:41 time: 0.5260 data_time: 0.0332 memory: 21547 grad_norm: 3.6148 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.8800 loss: 1.8800 2022/10/09 23:03:23 - mmengine - INFO - Epoch(train) [12][480/940] lr: 1.0000e-02 eta: 11:43:28 time: 0.4872 data_time: 0.0238 memory: 21547 grad_norm: 3.6045 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.1026 loss: 2.1026 2022/10/09 23:03:34 - mmengine - INFO - Epoch(train) [12][500/940] lr: 1.0000e-02 eta: 11:43:26 time: 0.5573 data_time: 0.0307 memory: 21547 grad_norm: 3.5211 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8967 loss: 1.8967 2022/10/09 23:03:44 - mmengine - INFO - Epoch(train) [12][520/940] lr: 1.0000e-02 eta: 11:43:14 time: 0.4976 data_time: 0.0236 memory: 21547 grad_norm: 3.6710 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.8635 loss: 1.8635 2022/10/09 23:03:55 - mmengine - INFO - Epoch(train) [12][540/940] lr: 1.0000e-02 eta: 11:43:09 time: 0.5403 data_time: 0.0290 memory: 21547 grad_norm: 3.5835 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9585 loss: 1.9585 2022/10/09 23:04:04 - mmengine - INFO - Epoch(train) [12][560/940] lr: 1.0000e-02 eta: 11:42:49 time: 0.4423 data_time: 0.0263 memory: 21547 grad_norm: 3.5564 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9158 loss: 1.9158 2022/10/09 23:04:14 - mmengine - INFO - Epoch(train) [12][580/940] lr: 1.0000e-02 eta: 11:42:39 time: 0.5084 data_time: 0.0283 memory: 21547 grad_norm: 3.6698 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9914 loss: 1.9914 2022/10/09 23:04:24 - mmengine - INFO - Epoch(train) [12][600/940] lr: 1.0000e-02 eta: 11:42:27 time: 0.4957 data_time: 0.0255 memory: 21547 grad_norm: 3.6040 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8365 loss: 1.8365 2022/10/09 23:04:34 - mmengine - INFO - Epoch(train) [12][620/940] lr: 1.0000e-02 eta: 11:42:15 time: 0.4958 data_time: 0.0346 memory: 21547 grad_norm: 3.5815 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.9567 loss: 1.9567 2022/10/09 23:04:43 - mmengine - INFO - Epoch(train) [12][640/940] lr: 1.0000e-02 eta: 11:42:01 time: 0.4810 data_time: 0.0238 memory: 21547 grad_norm: 3.6339 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.0483 loss: 2.0483 2022/10/09 23:04:54 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 23:04:54 - mmengine - INFO - Epoch(train) [12][660/940] lr: 1.0000e-02 eta: 11:41:54 time: 0.5299 data_time: 0.0292 memory: 21547 grad_norm: 3.6469 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8360 loss: 1.8360 2022/10/09 23:05:03 - mmengine - INFO - Epoch(train) [12][680/940] lr: 1.0000e-02 eta: 11:41:40 time: 0.4795 data_time: 0.0285 memory: 21547 grad_norm: 3.6820 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8956 loss: 1.8956 2022/10/09 23:05:12 - mmengine - INFO - Epoch(train) [12][700/940] lr: 1.0000e-02 eta: 11:41:21 time: 0.4520 data_time: 0.0312 memory: 21547 grad_norm: 3.6995 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 2.0283 loss: 2.0283 2022/10/09 23:05:23 - mmengine - INFO - Epoch(train) [12][720/940] lr: 1.0000e-02 eta: 11:41:13 time: 0.5218 data_time: 0.0246 memory: 21547 grad_norm: 3.5798 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9684 loss: 1.9684 2022/10/09 23:05:33 - mmengine - INFO - Epoch(train) [12][740/940] lr: 1.0000e-02 eta: 11:41:05 time: 0.5207 data_time: 0.0324 memory: 21547 grad_norm: 3.6296 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0862 loss: 2.0862 2022/10/09 23:05:43 - mmengine - INFO - Epoch(train) [12][760/940] lr: 1.0000e-02 eta: 11:40:54 time: 0.5004 data_time: 0.0312 memory: 21547 grad_norm: 3.6425 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9504 loss: 1.9504 2022/10/09 23:05:54 - mmengine - INFO - Epoch(train) [12][780/940] lr: 1.0000e-02 eta: 11:40:47 time: 0.5287 data_time: 0.0348 memory: 21547 grad_norm: 3.6650 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8818 loss: 1.8818 2022/10/09 23:06:04 - mmengine - INFO - Epoch(train) [12][800/940] lr: 1.0000e-02 eta: 11:40:33 time: 0.4820 data_time: 0.0271 memory: 21547 grad_norm: 3.6769 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8802 loss: 1.8802 2022/10/09 23:06:14 - mmengine - INFO - Epoch(train) [12][820/940] lr: 1.0000e-02 eta: 11:40:26 time: 0.5318 data_time: 0.0303 memory: 21547 grad_norm: 3.6866 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9828 loss: 1.9828 2022/10/09 23:06:24 - mmengine - INFO - Epoch(train) [12][840/940] lr: 1.0000e-02 eta: 11:40:16 time: 0.5074 data_time: 0.0290 memory: 21547 grad_norm: 3.6043 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0053 loss: 2.0053 2022/10/09 23:06:34 - mmengine - INFO - Epoch(train) [12][860/940] lr: 1.0000e-02 eta: 11:40:05 time: 0.5003 data_time: 0.0308 memory: 21547 grad_norm: 3.5743 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8381 loss: 1.8381 2022/10/09 23:06:44 - mmengine - INFO - Epoch(train) [12][880/940] lr: 1.0000e-02 eta: 11:39:52 time: 0.4895 data_time: 0.0305 memory: 21547 grad_norm: 3.6027 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9051 loss: 1.9051 2022/10/09 23:06:55 - mmengine - INFO - Epoch(train) [12][900/940] lr: 1.0000e-02 eta: 11:39:44 time: 0.5223 data_time: 0.0286 memory: 21547 grad_norm: 3.5932 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.9320 loss: 1.9320 2022/10/09 23:07:04 - mmengine - INFO - Epoch(train) [12][920/940] lr: 1.0000e-02 eta: 11:39:32 time: 0.4903 data_time: 0.0280 memory: 21547 grad_norm: 3.7248 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9083 loss: 1.9083 2022/10/09 23:07:13 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 23:07:13 - mmengine - INFO - Epoch(train) [12][940/940] lr: 1.0000e-02 eta: 11:39:14 time: 0.4527 data_time: 0.0256 memory: 21547 grad_norm: 3.8191 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.9134 loss: 1.9134 2022/10/09 23:07:13 - mmengine - INFO - Saving checkpoint at 12 epochs 2022/10/09 23:07:26 - mmengine - INFO - Epoch(val) [12][20/78] eta: 0:00:35 time: 0.6054 data_time: 0.4987 memory: 3269 2022/10/09 23:07:35 - mmengine - INFO - Epoch(val) [12][40/78] eta: 0:00:15 time: 0.4198 data_time: 0.3143 memory: 3269 2022/10/09 23:07:46 - mmengine - INFO - Epoch(val) [12][60/78] eta: 0:00:10 time: 0.5577 data_time: 0.4506 memory: 3269 2022/10/09 23:07:55 - mmengine - INFO - Epoch(val) [12][78/78] acc/top1: 0.6124 acc/top5: 0.8379 acc/mean1: 0.6123 2022/10/09 23:07:55 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_9.pth is removed 2022/10/09 23:07:56 - mmengine - INFO - The best checkpoint with 0.6124 acc/top1 at 12 epoch is saved to best_acc/top1_epoch_12.pth. 2022/10/09 23:08:10 - mmengine - INFO - Epoch(train) [13][20/940] lr: 1.0000e-02 eta: 11:39:32 time: 0.7015 data_time: 0.3292 memory: 21547 grad_norm: 3.5791 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7925 loss: 1.7925 2022/10/09 23:08:19 - mmengine - INFO - Epoch(train) [13][40/940] lr: 1.0000e-02 eta: 11:39:14 time: 0.4546 data_time: 0.0856 memory: 21547 grad_norm: 3.6005 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.9848 loss: 1.9848 2022/10/09 23:08:31 - mmengine - INFO - Epoch(train) [13][60/940] lr: 1.0000e-02 eta: 11:39:13 time: 0.5695 data_time: 0.1665 memory: 21547 grad_norm: 3.5811 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9006 loss: 1.9006 2022/10/09 23:08:39 - mmengine - INFO - Epoch(train) [13][80/940] lr: 1.0000e-02 eta: 11:38:53 time: 0.4391 data_time: 0.0678 memory: 21547 grad_norm: 3.5957 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.9738 loss: 1.9738 2022/10/09 23:08:50 - mmengine - INFO - Epoch(train) [13][100/940] lr: 1.0000e-02 eta: 11:38:45 time: 0.5258 data_time: 0.1034 memory: 21547 grad_norm: 3.5861 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8173 loss: 1.8173 2022/10/09 23:08:59 - mmengine - INFO - Epoch(train) [13][120/940] lr: 1.0000e-02 eta: 11:38:31 time: 0.4785 data_time: 0.0517 memory: 21547 grad_norm: 3.5347 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8029 loss: 1.8029 2022/10/09 23:09:10 - mmengine - INFO - Epoch(train) [13][140/940] lr: 1.0000e-02 eta: 11:38:22 time: 0.5173 data_time: 0.0859 memory: 21547 grad_norm: 3.6059 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.0804 loss: 2.0804 2022/10/09 23:09:19 - mmengine - INFO - Epoch(train) [13][160/940] lr: 1.0000e-02 eta: 11:38:08 time: 0.4804 data_time: 0.0378 memory: 21547 grad_norm: 3.5517 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9950 loss: 1.9950 2022/10/09 23:09:31 - mmengine - INFO - Epoch(train) [13][180/940] lr: 1.0000e-02 eta: 11:38:05 time: 0.5573 data_time: 0.0497 memory: 21547 grad_norm: 3.6709 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8411 loss: 1.8411 2022/10/09 23:09:40 - mmengine - INFO - Epoch(train) [13][200/940] lr: 1.0000e-02 eta: 11:37:53 time: 0.4935 data_time: 0.0246 memory: 21547 grad_norm: 3.6615 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0175 loss: 2.0175 2022/10/09 23:09:50 - mmengine - INFO - Epoch(train) [13][220/940] lr: 1.0000e-02 eta: 11:37:42 time: 0.5037 data_time: 0.0357 memory: 21547 grad_norm: 3.6354 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8638 loss: 1.8638 2022/10/09 23:09:59 - mmengine - INFO - Epoch(train) [13][240/940] lr: 1.0000e-02 eta: 11:37:24 time: 0.4489 data_time: 0.0303 memory: 21547 grad_norm: 3.6660 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8731 loss: 1.8731 2022/10/09 23:10:10 - mmengine - INFO - Epoch(train) [13][260/940] lr: 1.0000e-02 eta: 11:37:14 time: 0.5089 data_time: 0.0279 memory: 21547 grad_norm: 3.6434 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.0090 loss: 2.0090 2022/10/09 23:10:21 - mmengine - INFO - Epoch(train) [13][280/940] lr: 1.0000e-02 eta: 11:37:11 time: 0.5602 data_time: 0.0345 memory: 21547 grad_norm: 3.6258 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9022 loss: 1.9022 2022/10/09 23:10:30 - mmengine - INFO - Epoch(train) [13][300/940] lr: 1.0000e-02 eta: 11:36:56 time: 0.4734 data_time: 0.0273 memory: 21547 grad_norm: 3.6559 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7986 loss: 1.7986 2022/10/09 23:10:40 - mmengine - INFO - Epoch(train) [13][320/940] lr: 1.0000e-02 eta: 11:36:45 time: 0.5016 data_time: 0.0291 memory: 21547 grad_norm: 3.5570 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8783 loss: 1.8783 2022/10/09 23:10:50 - mmengine - INFO - Epoch(train) [13][340/940] lr: 1.0000e-02 eta: 11:36:29 time: 0.4610 data_time: 0.0304 memory: 21547 grad_norm: 3.6116 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8327 loss: 1.8327 2022/10/09 23:11:00 - mmengine - INFO - Epoch(train) [13][360/940] lr: 1.0000e-02 eta: 11:36:22 time: 0.5282 data_time: 0.0304 memory: 21547 grad_norm: 3.6509 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.7477 loss: 1.7477 2022/10/09 23:11:10 - mmengine - INFO - Epoch(train) [13][380/940] lr: 1.0000e-02 eta: 11:36:07 time: 0.4794 data_time: 0.0307 memory: 21547 grad_norm: 3.6394 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0114 loss: 2.0114 2022/10/09 23:11:21 - mmengine - INFO - Epoch(train) [13][400/940] lr: 1.0000e-02 eta: 11:36:06 time: 0.5661 data_time: 0.0283 memory: 21547 grad_norm: 3.6327 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0116 loss: 2.0116 2022/10/09 23:11:31 - mmengine - INFO - Epoch(train) [13][420/940] lr: 1.0000e-02 eta: 11:35:55 time: 0.5011 data_time: 0.0290 memory: 21547 grad_norm: 3.6557 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0334 loss: 2.0334 2022/10/09 23:11:41 - mmengine - INFO - Epoch(train) [13][440/940] lr: 1.0000e-02 eta: 11:35:45 time: 0.5136 data_time: 0.0257 memory: 21547 grad_norm: 3.6499 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.9315 loss: 1.9315 2022/10/09 23:11:51 - mmengine - INFO - Epoch(train) [13][460/940] lr: 1.0000e-02 eta: 11:35:32 time: 0.4868 data_time: 0.0255 memory: 21547 grad_norm: 3.6678 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 1.9934 loss: 1.9934 2022/10/09 23:12:02 - mmengine - INFO - Epoch(train) [13][480/940] lr: 1.0000e-02 eta: 11:35:28 time: 0.5466 data_time: 0.0258 memory: 21547 grad_norm: 3.7149 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 1.9512 loss: 1.9512 2022/10/09 23:12:12 - mmengine - INFO - Epoch(train) [13][500/940] lr: 1.0000e-02 eta: 11:35:16 time: 0.4949 data_time: 0.0311 memory: 21547 grad_norm: 3.5789 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.9434 loss: 1.9434 2022/10/09 23:12:21 - mmengine - INFO - Epoch(train) [13][520/940] lr: 1.0000e-02 eta: 11:35:01 time: 0.4780 data_time: 0.0269 memory: 21547 grad_norm: 3.6375 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.9583 loss: 1.9583 2022/10/09 23:12:31 - mmengine - INFO - Epoch(train) [13][540/940] lr: 1.0000e-02 eta: 11:34:47 time: 0.4758 data_time: 0.0286 memory: 21547 grad_norm: 3.6424 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.9750 loss: 1.9750 2022/10/09 23:12:42 - mmengine - INFO - Epoch(train) [13][560/940] lr: 1.0000e-02 eta: 11:34:43 time: 0.5547 data_time: 0.0296 memory: 21547 grad_norm: 3.7237 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9829 loss: 1.9829 2022/10/09 23:12:51 - mmengine - INFO - Epoch(train) [13][580/940] lr: 1.0000e-02 eta: 11:34:24 time: 0.4434 data_time: 0.0237 memory: 21547 grad_norm: 3.6764 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0084 loss: 2.0084 2022/10/09 23:13:01 - mmengine - INFO - Epoch(train) [13][600/940] lr: 1.0000e-02 eta: 11:34:16 time: 0.5186 data_time: 0.0287 memory: 21547 grad_norm: 3.7609 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9263 loss: 1.9263 2022/10/09 23:13:12 - mmengine - INFO - Epoch(train) [13][620/940] lr: 1.0000e-02 eta: 11:34:07 time: 0.5139 data_time: 0.0336 memory: 21547 grad_norm: 3.5778 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9590 loss: 1.9590 2022/10/09 23:13:22 - mmengine - INFO - Epoch(train) [13][640/940] lr: 1.0000e-02 eta: 11:34:00 time: 0.5347 data_time: 0.0311 memory: 21547 grad_norm: 3.6698 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0618 loss: 2.0618 2022/10/09 23:13:32 - mmengine - INFO - Epoch(train) [13][660/940] lr: 1.0000e-02 eta: 11:33:46 time: 0.4754 data_time: 0.0283 memory: 21547 grad_norm: 3.6275 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.9442 loss: 1.9442 2022/10/09 23:13:42 - mmengine - INFO - Epoch(train) [13][680/940] lr: 1.0000e-02 eta: 11:33:35 time: 0.5014 data_time: 0.0297 memory: 21547 grad_norm: 3.6415 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7422 loss: 1.7422 2022/10/09 23:13:52 - mmengine - INFO - Epoch(train) [13][700/940] lr: 1.0000e-02 eta: 11:33:28 time: 0.5324 data_time: 0.0294 memory: 21547 grad_norm: 3.6825 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.9710 loss: 1.9710 2022/10/09 23:14:02 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 23:14:02 - mmengine - INFO - Epoch(train) [13][720/940] lr: 1.0000e-02 eta: 11:33:17 time: 0.4992 data_time: 0.0278 memory: 21547 grad_norm: 3.6702 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.0503 loss: 2.0503 2022/10/09 23:14:13 - mmengine - INFO - Epoch(train) [13][740/940] lr: 1.0000e-02 eta: 11:33:10 time: 0.5302 data_time: 0.0271 memory: 21547 grad_norm: 3.6284 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8305 loss: 1.8305 2022/10/09 23:14:23 - mmengine - INFO - Epoch(train) [13][760/940] lr: 1.0000e-02 eta: 11:32:56 time: 0.4838 data_time: 0.0320 memory: 21547 grad_norm: 3.6435 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.1099 loss: 2.1099 2022/10/09 23:14:32 - mmengine - INFO - Epoch(train) [13][780/940] lr: 1.0000e-02 eta: 11:32:41 time: 0.4662 data_time: 0.0285 memory: 21547 grad_norm: 3.6511 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 1.8935 loss: 1.8935 2022/10/09 23:14:42 - mmengine - INFO - Epoch(train) [13][800/940] lr: 1.0000e-02 eta: 11:32:30 time: 0.5045 data_time: 0.0293 memory: 21547 grad_norm: 3.6491 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.9510 loss: 1.9510 2022/10/09 23:14:53 - mmengine - INFO - Epoch(train) [13][820/940] lr: 1.0000e-02 eta: 11:32:22 time: 0.5204 data_time: 0.0267 memory: 21547 grad_norm: 3.6430 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0044 loss: 2.0044 2022/10/09 23:15:03 - mmengine - INFO - Epoch(train) [13][840/940] lr: 1.0000e-02 eta: 11:32:12 time: 0.5125 data_time: 0.0296 memory: 21547 grad_norm: 3.7085 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.9090 loss: 1.9090 2022/10/09 23:15:13 - mmengine - INFO - Epoch(train) [13][860/940] lr: 1.0000e-02 eta: 11:32:01 time: 0.4993 data_time: 0.0230 memory: 21547 grad_norm: 3.6960 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.9781 loss: 1.9781 2022/10/09 23:15:23 - mmengine - INFO - Epoch(train) [13][880/940] lr: 1.0000e-02 eta: 11:31:49 time: 0.4954 data_time: 0.0296 memory: 21547 grad_norm: 3.6492 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9464 loss: 1.9464 2022/10/09 23:15:33 - mmengine - INFO - Epoch(train) [13][900/940] lr: 1.0000e-02 eta: 11:31:41 time: 0.5187 data_time: 0.0307 memory: 21547 grad_norm: 3.6334 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.8130 loss: 1.8130 2022/10/09 23:15:43 - mmengine - INFO - Epoch(train) [13][920/940] lr: 1.0000e-02 eta: 11:31:27 time: 0.4813 data_time: 0.0241 memory: 21547 grad_norm: 3.6652 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.8653 loss: 1.8653 2022/10/09 23:15:52 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 23:15:52 - mmengine - INFO - Epoch(train) [13][940/940] lr: 1.0000e-02 eta: 11:31:15 time: 0.4891 data_time: 0.0261 memory: 21547 grad_norm: 3.8765 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.9073 loss: 1.9073 2022/10/09 23:16:05 - mmengine - INFO - Epoch(val) [13][20/78] eta: 0:00:35 time: 0.6065 data_time: 0.4969 memory: 3269 2022/10/09 23:16:13 - mmengine - INFO - Epoch(val) [13][40/78] eta: 0:00:16 time: 0.4245 data_time: 0.3188 memory: 3269 2022/10/09 23:16:24 - mmengine - INFO - Epoch(val) [13][60/78] eta: 0:00:09 time: 0.5531 data_time: 0.4474 memory: 3269 2022/10/09 23:16:34 - mmengine - INFO - Epoch(val) [13][78/78] acc/top1: 0.6116 acc/top5: 0.8343 acc/mean1: 0.6115 2022/10/09 23:16:49 - mmengine - INFO - Epoch(train) [14][20/940] lr: 1.0000e-02 eta: 11:31:38 time: 0.7560 data_time: 0.2065 memory: 21547 grad_norm: 3.5939 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.7731 loss: 1.7731 2022/10/09 23:16:58 - mmengine - INFO - Epoch(train) [14][40/940] lr: 1.0000e-02 eta: 11:31:18 time: 0.4387 data_time: 0.0255 memory: 21547 grad_norm: 3.6276 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.8267 loss: 1.8267 2022/10/09 23:17:09 - mmengine - INFO - Epoch(train) [14][60/940] lr: 1.0000e-02 eta: 11:31:13 time: 0.5421 data_time: 0.0289 memory: 21547 grad_norm: 3.6072 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8196 loss: 1.8196 2022/10/09 23:17:18 - mmengine - INFO - Epoch(train) [14][80/940] lr: 1.0000e-02 eta: 11:30:58 time: 0.4698 data_time: 0.0246 memory: 21547 grad_norm: 3.6384 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.9797 loss: 1.9797 2022/10/09 23:17:29 - mmengine - INFO - Epoch(train) [14][100/940] lr: 1.0000e-02 eta: 11:30:48 time: 0.5085 data_time: 0.0299 memory: 21547 grad_norm: 3.5989 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6187 loss: 1.6187 2022/10/09 23:17:38 - mmengine - INFO - Epoch(train) [14][120/940] lr: 1.0000e-02 eta: 11:30:34 time: 0.4798 data_time: 0.0273 memory: 21547 grad_norm: 3.6715 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.8258 loss: 1.8258 2022/10/09 23:17:48 - mmengine - INFO - Epoch(train) [14][140/940] lr: 1.0000e-02 eta: 11:30:25 time: 0.5190 data_time: 0.0305 memory: 21547 grad_norm: 3.6242 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7987 loss: 1.7987 2022/10/09 23:17:58 - mmengine - INFO - Epoch(train) [14][160/940] lr: 1.0000e-02 eta: 11:30:13 time: 0.4902 data_time: 0.0289 memory: 21547 grad_norm: 3.6627 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9529 loss: 1.9529 2022/10/09 23:18:10 - mmengine - INFO - Epoch(train) [14][180/940] lr: 1.0000e-02 eta: 11:30:10 time: 0.5665 data_time: 0.0286 memory: 21547 grad_norm: 3.6779 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.9314 loss: 1.9314 2022/10/09 23:18:19 - mmengine - INFO - Epoch(train) [14][200/940] lr: 1.0000e-02 eta: 11:29:53 time: 0.4545 data_time: 0.0343 memory: 21547 grad_norm: 3.6815 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7831 loss: 1.7831 2022/10/09 23:18:29 - mmengine - INFO - Epoch(train) [14][220/940] lr: 1.0000e-02 eta: 11:29:43 time: 0.5090 data_time: 0.0278 memory: 21547 grad_norm: 3.6656 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.9209 loss: 1.9209 2022/10/09 23:18:39 - mmengine - INFO - Epoch(train) [14][240/940] lr: 1.0000e-02 eta: 11:29:31 time: 0.4874 data_time: 0.0360 memory: 21547 grad_norm: 3.7346 top1_acc: 0.3438 top5_acc: 0.5312 loss_cls: 1.9344 loss: 1.9344 2022/10/09 23:18:49 - mmengine - INFO - Epoch(train) [14][260/940] lr: 1.0000e-02 eta: 11:29:23 time: 0.5301 data_time: 0.0304 memory: 21547 grad_norm: 3.6478 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.8647 loss: 1.8647 2022/10/09 23:18:59 - mmengine - INFO - Epoch(train) [14][280/940] lr: 1.0000e-02 eta: 11:29:10 time: 0.4801 data_time: 0.0247 memory: 21547 grad_norm: 3.6518 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.9168 loss: 1.9168 2022/10/09 23:19:10 - mmengine - INFO - Epoch(train) [14][300/940] lr: 1.0000e-02 eta: 11:29:07 time: 0.5617 data_time: 0.0307 memory: 21547 grad_norm: 3.6331 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9985 loss: 1.9985 2022/10/09 23:19:19 - mmengine - INFO - Epoch(train) [14][320/940] lr: 1.0000e-02 eta: 11:28:50 time: 0.4581 data_time: 0.0242 memory: 21547 grad_norm: 3.7162 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9346 loss: 1.9346 2022/10/09 23:19:30 - mmengine - INFO - Epoch(train) [14][340/940] lr: 1.0000e-02 eta: 11:28:44 time: 0.5363 data_time: 0.0283 memory: 21547 grad_norm: 3.7150 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8593 loss: 1.8593 2022/10/09 23:19:39 - mmengine - INFO - Epoch(train) [14][360/940] lr: 1.0000e-02 eta: 11:28:29 time: 0.4735 data_time: 0.0262 memory: 21547 grad_norm: 3.6816 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0374 loss: 2.0374 2022/10/09 23:19:50 - mmengine - INFO - Epoch(train) [14][380/940] lr: 1.0000e-02 eta: 11:28:23 time: 0.5403 data_time: 0.0255 memory: 21547 grad_norm: 3.6411 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7025 loss: 1.7025 2022/10/09 23:19:59 - mmengine - INFO - Epoch(train) [14][400/940] lr: 1.0000e-02 eta: 11:28:07 time: 0.4617 data_time: 0.0291 memory: 21547 grad_norm: 3.7064 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.8631 loss: 1.8631 2022/10/09 23:20:10 - mmengine - INFO - Epoch(train) [14][420/940] lr: 1.0000e-02 eta: 11:27:59 time: 0.5244 data_time: 0.0284 memory: 21547 grad_norm: 3.6405 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8901 loss: 1.8901 2022/10/09 23:20:20 - mmengine - INFO - Epoch(train) [14][440/940] lr: 1.0000e-02 eta: 11:27:51 time: 0.5178 data_time: 0.0268 memory: 21547 grad_norm: 3.6668 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.8894 loss: 1.8894 2022/10/09 23:20:31 - mmengine - INFO - Epoch(train) [14][460/940] lr: 1.0000e-02 eta: 11:27:41 time: 0.5107 data_time: 0.0325 memory: 21547 grad_norm: 3.6634 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.8543 loss: 1.8543 2022/10/09 23:20:40 - mmengine - INFO - Epoch(train) [14][480/940] lr: 1.0000e-02 eta: 11:27:26 time: 0.4744 data_time: 0.0257 memory: 21547 grad_norm: 3.6681 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9053 loss: 1.9053 2022/10/09 23:20:50 - mmengine - INFO - Epoch(train) [14][500/940] lr: 1.0000e-02 eta: 11:27:15 time: 0.4942 data_time: 0.0284 memory: 21547 grad_norm: 3.7362 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.8970 loss: 1.8970 2022/10/09 23:21:00 - mmengine - INFO - Epoch(train) [14][520/940] lr: 1.0000e-02 eta: 11:27:02 time: 0.4850 data_time: 0.0265 memory: 21547 grad_norm: 3.6564 top1_acc: 0.5000 top5_acc: 0.9062 loss_cls: 1.8540 loss: 1.8540 2022/10/09 23:21:09 - mmengine - INFO - Epoch(train) [14][540/940] lr: 1.0000e-02 eta: 11:26:48 time: 0.4789 data_time: 0.0276 memory: 21547 grad_norm: 3.6775 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8530 loss: 1.8530 2022/10/09 23:21:19 - mmengine - INFO - Epoch(train) [14][560/940] lr: 1.0000e-02 eta: 11:26:37 time: 0.4984 data_time: 0.0323 memory: 21547 grad_norm: 3.7013 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.8374 loss: 1.8374 2022/10/09 23:21:29 - mmengine - INFO - Epoch(train) [14][580/940] lr: 1.0000e-02 eta: 11:26:25 time: 0.4985 data_time: 0.0307 memory: 21547 grad_norm: 3.7366 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8296 loss: 1.8296 2022/10/09 23:21:40 - mmengine - INFO - Epoch(train) [14][600/940] lr: 1.0000e-02 eta: 11:26:18 time: 0.5269 data_time: 0.0304 memory: 21547 grad_norm: 3.7197 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8999 loss: 1.8999 2022/10/09 23:21:50 - mmengine - INFO - Epoch(train) [14][620/940] lr: 1.0000e-02 eta: 11:26:06 time: 0.4924 data_time: 0.0332 memory: 21547 grad_norm: 3.6804 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7622 loss: 1.7622 2022/10/09 23:22:01 - mmengine - INFO - Epoch(train) [14][640/940] lr: 1.0000e-02 eta: 11:26:01 time: 0.5507 data_time: 0.0257 memory: 21547 grad_norm: 3.6537 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7867 loss: 1.7867 2022/10/09 23:22:10 - mmengine - INFO - Epoch(train) [14][660/940] lr: 1.0000e-02 eta: 11:25:47 time: 0.4729 data_time: 0.0270 memory: 21547 grad_norm: 3.6872 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9238 loss: 1.9238 2022/10/09 23:22:21 - mmengine - INFO - Epoch(train) [14][680/940] lr: 1.0000e-02 eta: 11:25:43 time: 0.5588 data_time: 0.0243 memory: 21547 grad_norm: 3.5784 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.8267 loss: 1.8267 2022/10/09 23:22:31 - mmengine - INFO - Epoch(train) [14][700/940] lr: 1.0000e-02 eta: 11:25:30 time: 0.4832 data_time: 0.0268 memory: 21547 grad_norm: 3.7154 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7734 loss: 1.7734 2022/10/09 23:22:41 - mmengine - INFO - Epoch(train) [14][720/940] lr: 1.0000e-02 eta: 11:25:18 time: 0.4962 data_time: 0.0311 memory: 21547 grad_norm: 3.7195 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9420 loss: 1.9420 2022/10/09 23:22:50 - mmengine - INFO - Epoch(train) [14][740/940] lr: 1.0000e-02 eta: 11:25:04 time: 0.4769 data_time: 0.0236 memory: 21547 grad_norm: 3.6256 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.9385 loss: 1.9385 2022/10/09 23:23:01 - mmengine - INFO - Epoch(train) [14][760/940] lr: 1.0000e-02 eta: 11:24:55 time: 0.5154 data_time: 0.0295 memory: 21547 grad_norm: 3.6619 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8553 loss: 1.8553 2022/10/09 23:23:10 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 23:23:10 - mmengine - INFO - Epoch(train) [14][780/940] lr: 1.0000e-02 eta: 11:24:42 time: 0.4853 data_time: 0.0272 memory: 21547 grad_norm: 3.7155 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8457 loss: 1.8457 2022/10/09 23:23:20 - mmengine - INFO - Epoch(train) [14][800/940] lr: 1.0000e-02 eta: 11:24:31 time: 0.4990 data_time: 0.0300 memory: 21547 grad_norm: 3.6765 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8261 loss: 1.8261 2022/10/09 23:23:30 - mmengine - INFO - Epoch(train) [14][820/940] lr: 1.0000e-02 eta: 11:24:17 time: 0.4779 data_time: 0.0254 memory: 21547 grad_norm: 3.7571 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.9816 loss: 1.9816 2022/10/09 23:23:40 - mmengine - INFO - Epoch(train) [14][840/940] lr: 1.0000e-02 eta: 11:24:09 time: 0.5263 data_time: 0.0293 memory: 21547 grad_norm: 3.6691 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.9093 loss: 1.9093 2022/10/09 23:23:50 - mmengine - INFO - Epoch(train) [14][860/940] lr: 1.0000e-02 eta: 11:23:58 time: 0.5001 data_time: 0.0337 memory: 21547 grad_norm: 3.6248 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.9164 loss: 1.9164 2022/10/09 23:24:01 - mmengine - INFO - Epoch(train) [14][880/940] lr: 1.0000e-02 eta: 11:23:51 time: 0.5319 data_time: 0.0262 memory: 21547 grad_norm: 3.6439 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.9112 loss: 1.9112 2022/10/09 23:24:11 - mmengine - INFO - Epoch(train) [14][900/940] lr: 1.0000e-02 eta: 11:23:38 time: 0.4829 data_time: 0.0306 memory: 21547 grad_norm: 3.7591 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.8620 loss: 1.8620 2022/10/09 23:24:21 - mmengine - INFO - Epoch(train) [14][920/940] lr: 1.0000e-02 eta: 11:23:29 time: 0.5167 data_time: 0.0331 memory: 21547 grad_norm: 3.6581 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.9790 loss: 1.9790 2022/10/09 23:24:29 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 23:24:29 - mmengine - INFO - Epoch(train) [14][940/940] lr: 1.0000e-02 eta: 11:23:09 time: 0.4208 data_time: 0.0311 memory: 21547 grad_norm: 3.8910 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.9218 loss: 1.9218 2022/10/09 23:24:43 - mmengine - INFO - Epoch(val) [14][20/78] eta: 0:00:37 time: 0.6546 data_time: 0.5465 memory: 3269 2022/10/09 23:24:50 - mmengine - INFO - Epoch(val) [14][40/78] eta: 0:00:14 time: 0.3924 data_time: 0.2864 memory: 3269 2022/10/09 23:25:02 - mmengine - INFO - Epoch(val) [14][60/78] eta: 0:00:10 time: 0.5721 data_time: 0.4655 memory: 3269 2022/10/09 23:25:11 - mmengine - INFO - Epoch(val) [14][78/78] acc/top1: 0.6211 acc/top5: 0.8416 acc/mean1: 0.6209 2022/10/09 23:25:11 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_12.pth is removed 2022/10/09 23:25:12 - mmengine - INFO - The best checkpoint with 0.6211 acc/top1 at 14 epoch is saved to best_acc/top1_epoch_14.pth. 2022/10/09 23:25:25 - mmengine - INFO - Epoch(train) [15][20/940] lr: 1.0000e-02 eta: 11:23:19 time: 0.6787 data_time: 0.2898 memory: 21547 grad_norm: 3.6242 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8752 loss: 1.8752 2022/10/09 23:25:35 - mmengine - INFO - Epoch(train) [15][40/940] lr: 1.0000e-02 eta: 11:23:05 time: 0.4685 data_time: 0.0896 memory: 21547 grad_norm: 3.7039 top1_acc: 0.4375 top5_acc: 0.5938 loss_cls: 1.9297 loss: 1.9297 2022/10/09 23:25:46 - mmengine - INFO - Epoch(train) [15][60/940] lr: 1.0000e-02 eta: 11:23:02 time: 0.5692 data_time: 0.1612 memory: 21547 grad_norm: 3.6933 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8066 loss: 1.8066 2022/10/09 23:25:56 - mmengine - INFO - Epoch(train) [15][80/940] lr: 1.0000e-02 eta: 11:22:49 time: 0.4806 data_time: 0.0241 memory: 21547 grad_norm: 3.6642 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.8587 loss: 1.8587 2022/10/09 23:26:07 - mmengine - INFO - Epoch(train) [15][100/940] lr: 1.0000e-02 eta: 11:22:43 time: 0.5431 data_time: 0.0305 memory: 21547 grad_norm: 3.6473 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8794 loss: 1.8794 2022/10/09 23:26:16 - mmengine - INFO - Epoch(train) [15][120/940] lr: 1.0000e-02 eta: 11:22:29 time: 0.4757 data_time: 0.0265 memory: 21547 grad_norm: 3.7565 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7920 loss: 1.7920 2022/10/09 23:26:27 - mmengine - INFO - Epoch(train) [15][140/940] lr: 1.0000e-02 eta: 11:22:25 time: 0.5615 data_time: 0.0313 memory: 21547 grad_norm: 3.6311 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.8209 loss: 1.8209 2022/10/09 23:26:37 - mmengine - INFO - Epoch(train) [15][160/940] lr: 1.0000e-02 eta: 11:22:11 time: 0.4761 data_time: 0.0231 memory: 21547 grad_norm: 3.6837 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7764 loss: 1.7764 2022/10/09 23:26:47 - mmengine - INFO - Epoch(train) [15][180/940] lr: 1.0000e-02 eta: 11:22:02 time: 0.5138 data_time: 0.0227 memory: 21547 grad_norm: 3.6545 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7645 loss: 1.7645 2022/10/09 23:26:57 - mmengine - INFO - Epoch(train) [15][200/940] lr: 1.0000e-02 eta: 11:21:49 time: 0.4847 data_time: 0.0310 memory: 21547 grad_norm: 3.6900 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.9425 loss: 1.9425 2022/10/09 23:27:08 - mmengine - INFO - Epoch(train) [15][220/940] lr: 1.0000e-02 eta: 11:21:44 time: 0.5502 data_time: 0.0301 memory: 21547 grad_norm: 3.7001 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8085 loss: 1.8085 2022/10/09 23:27:17 - mmengine - INFO - Epoch(train) [15][240/940] lr: 1.0000e-02 eta: 11:21:30 time: 0.4709 data_time: 0.0246 memory: 21547 grad_norm: 3.6402 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7651 loss: 1.7651 2022/10/09 23:27:27 - mmengine - INFO - Epoch(train) [15][260/940] lr: 1.0000e-02 eta: 11:21:20 time: 0.5140 data_time: 0.0278 memory: 21547 grad_norm: 3.7250 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8554 loss: 1.8554 2022/10/09 23:27:37 - mmengine - INFO - Epoch(train) [15][280/940] lr: 1.0000e-02 eta: 11:21:07 time: 0.4845 data_time: 0.0306 memory: 21547 grad_norm: 3.7312 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9721 loss: 1.9721 2022/10/09 23:27:48 - mmengine - INFO - Epoch(train) [15][300/940] lr: 1.0000e-02 eta: 11:21:02 time: 0.5483 data_time: 0.0271 memory: 21547 grad_norm: 3.6668 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.0267 loss: 2.0267 2022/10/09 23:27:59 - mmengine - INFO - Epoch(train) [15][320/940] lr: 1.0000e-02 eta: 11:20:53 time: 0.5205 data_time: 0.0275 memory: 21547 grad_norm: 3.7003 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0343 loss: 2.0343 2022/10/09 23:28:09 - mmengine - INFO - Epoch(train) [15][340/940] lr: 1.0000e-02 eta: 11:20:44 time: 0.5088 data_time: 0.0277 memory: 21547 grad_norm: 3.6620 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.8017 loss: 1.8017 2022/10/09 23:28:18 - mmengine - INFO - Epoch(train) [15][360/940] lr: 1.0000e-02 eta: 11:20:27 time: 0.4503 data_time: 0.0251 memory: 21547 grad_norm: 3.8038 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9205 loss: 1.9205 2022/10/09 23:28:28 - mmengine - INFO - Epoch(train) [15][380/940] lr: 1.0000e-02 eta: 11:20:15 time: 0.4958 data_time: 0.0256 memory: 21547 grad_norm: 3.6937 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7816 loss: 1.7816 2022/10/09 23:28:37 - mmengine - INFO - Epoch(train) [15][400/940] lr: 1.0000e-02 eta: 11:20:03 time: 0.4878 data_time: 0.0350 memory: 21547 grad_norm: 3.7417 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.8159 loss: 1.8159 2022/10/09 23:28:48 - mmengine - INFO - Epoch(train) [15][420/940] lr: 1.0000e-02 eta: 11:19:54 time: 0.5218 data_time: 0.0316 memory: 21547 grad_norm: 3.7475 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7518 loss: 1.7518 2022/10/09 23:28:58 - mmengine - INFO - Epoch(train) [15][440/940] lr: 1.0000e-02 eta: 11:19:43 time: 0.5028 data_time: 0.0296 memory: 21547 grad_norm: 3.6293 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7832 loss: 1.7832 2022/10/09 23:29:08 - mmengine - INFO - Epoch(train) [15][460/940] lr: 1.0000e-02 eta: 11:19:31 time: 0.4875 data_time: 0.0290 memory: 21547 grad_norm: 3.7429 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8266 loss: 1.8266 2022/10/09 23:29:18 - mmengine - INFO - Epoch(train) [15][480/940] lr: 1.0000e-02 eta: 11:19:24 time: 0.5318 data_time: 0.0304 memory: 21547 grad_norm: 3.7754 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.9488 loss: 1.9488 2022/10/09 23:29:28 - mmengine - INFO - Epoch(train) [15][500/940] lr: 1.0000e-02 eta: 11:19:10 time: 0.4790 data_time: 0.0254 memory: 21547 grad_norm: 3.7920 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6852 loss: 1.6852 2022/10/09 23:29:38 - mmengine - INFO - Epoch(train) [15][520/940] lr: 1.0000e-02 eta: 11:19:00 time: 0.5098 data_time: 0.0295 memory: 21547 grad_norm: 3.6926 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8691 loss: 1.8691 2022/10/09 23:29:48 - mmengine - INFO - Epoch(train) [15][540/940] lr: 1.0000e-02 eta: 11:18:50 time: 0.5023 data_time: 0.0246 memory: 21547 grad_norm: 3.7048 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7821 loss: 1.7821 2022/10/09 23:29:57 - mmengine - INFO - Epoch(train) [15][560/940] lr: 1.0000e-02 eta: 11:18:35 time: 0.4670 data_time: 0.0266 memory: 21547 grad_norm: 3.8145 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6839 loss: 1.6839 2022/10/09 23:30:07 - mmengine - INFO - Epoch(train) [15][580/940] lr: 1.0000e-02 eta: 11:18:24 time: 0.5014 data_time: 0.0277 memory: 21547 grad_norm: 3.7048 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8599 loss: 1.8599 2022/10/09 23:30:19 - mmengine - INFO - Epoch(train) [15][600/940] lr: 1.0000e-02 eta: 11:18:19 time: 0.5549 data_time: 0.0292 memory: 21547 grad_norm: 3.7437 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8372 loss: 1.8372 2022/10/09 23:30:28 - mmengine - INFO - Epoch(train) [15][620/940] lr: 1.0000e-02 eta: 11:18:07 time: 0.4865 data_time: 0.0266 memory: 21547 grad_norm: 3.7957 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.6442 loss: 1.6442 2022/10/09 23:30:39 - mmengine - INFO - Epoch(train) [15][640/940] lr: 1.0000e-02 eta: 11:17:59 time: 0.5279 data_time: 0.0340 memory: 21547 grad_norm: 3.7585 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.8973 loss: 1.8973 2022/10/09 23:30:48 - mmengine - INFO - Epoch(train) [15][660/940] lr: 1.0000e-02 eta: 11:17:44 time: 0.4668 data_time: 0.0263 memory: 21547 grad_norm: 3.6861 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.7596 loss: 1.7596 2022/10/09 23:30:58 - mmengine - INFO - Epoch(train) [15][680/940] lr: 1.0000e-02 eta: 11:17:33 time: 0.4929 data_time: 0.0299 memory: 21547 grad_norm: 3.7018 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8440 loss: 1.8440 2022/10/09 23:31:08 - mmengine - INFO - Epoch(train) [15][700/940] lr: 1.0000e-02 eta: 11:17:20 time: 0.4831 data_time: 0.0329 memory: 21547 grad_norm: 3.6922 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.8234 loss: 1.8234 2022/10/09 23:31:18 - mmengine - INFO - Epoch(train) [15][720/940] lr: 1.0000e-02 eta: 11:17:10 time: 0.5140 data_time: 0.0309 memory: 21547 grad_norm: 3.7927 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8444 loss: 1.8444 2022/10/09 23:31:29 - mmengine - INFO - Epoch(train) [15][740/940] lr: 1.0000e-02 eta: 11:17:03 time: 0.5329 data_time: 0.0321 memory: 21547 grad_norm: 3.7639 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7909 loss: 1.7909 2022/10/09 23:31:39 - mmengine - INFO - Epoch(train) [15][760/940] lr: 1.0000e-02 eta: 11:16:54 time: 0.5158 data_time: 0.0268 memory: 21547 grad_norm: 3.6894 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.0583 loss: 2.0583 2022/10/09 23:31:49 - mmengine - INFO - Epoch(train) [15][780/940] lr: 1.0000e-02 eta: 11:16:42 time: 0.4953 data_time: 0.0266 memory: 21547 grad_norm: 3.6311 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8957 loss: 1.8957 2022/10/09 23:32:00 - mmengine - INFO - Epoch(train) [15][800/940] lr: 1.0000e-02 eta: 11:16:36 time: 0.5380 data_time: 0.0271 memory: 21547 grad_norm: 3.7936 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8506 loss: 1.8506 2022/10/09 23:32:09 - mmengine - INFO - Epoch(train) [15][820/940] lr: 1.0000e-02 eta: 11:16:20 time: 0.4617 data_time: 0.0267 memory: 21547 grad_norm: 3.7245 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.8664 loss: 1.8664 2022/10/09 23:32:19 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 23:32:19 - mmengine - INFO - Epoch(train) [15][840/940] lr: 1.0000e-02 eta: 11:16:11 time: 0.5102 data_time: 0.0290 memory: 21547 grad_norm: 3.7109 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8701 loss: 1.8701 2022/10/09 23:32:29 - mmengine - INFO - Epoch(train) [15][860/940] lr: 1.0000e-02 eta: 11:15:59 time: 0.4948 data_time: 0.0250 memory: 21547 grad_norm: 3.6876 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9226 loss: 1.9226 2022/10/09 23:32:39 - mmengine - INFO - Epoch(train) [15][880/940] lr: 1.0000e-02 eta: 11:15:48 time: 0.4957 data_time: 0.0266 memory: 21547 grad_norm: 3.6956 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8411 loss: 1.8411 2022/10/09 23:32:49 - mmengine - INFO - Epoch(train) [15][900/940] lr: 1.0000e-02 eta: 11:15:36 time: 0.4946 data_time: 0.0314 memory: 21547 grad_norm: 3.6606 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7318 loss: 1.7318 2022/10/09 23:33:00 - mmengine - INFO - Epoch(train) [15][920/940] lr: 1.0000e-02 eta: 11:15:31 time: 0.5484 data_time: 0.0305 memory: 21547 grad_norm: 3.8235 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0258 loss: 2.0258 2022/10/09 23:33:08 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 23:33:08 - mmengine - INFO - Epoch(train) [15][940/940] lr: 1.0000e-02 eta: 11:15:11 time: 0.4206 data_time: 0.0232 memory: 21547 grad_norm: 3.8916 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.8060 loss: 1.8060 2022/10/09 23:33:08 - mmengine - INFO - Saving checkpoint at 15 epochs 2022/10/09 23:33:21 - mmengine - INFO - Epoch(val) [15][20/78] eta: 0:00:35 time: 0.6150 data_time: 0.5096 memory: 3269 2022/10/09 23:33:30 - mmengine - INFO - Epoch(val) [15][40/78] eta: 0:00:15 time: 0.4181 data_time: 0.3127 memory: 3269 2022/10/09 23:33:41 - mmengine - INFO - Epoch(val) [15][60/78] eta: 0:00:09 time: 0.5529 data_time: 0.4482 memory: 3269 2022/10/09 23:33:50 - mmengine - INFO - Epoch(val) [15][78/78] acc/top1: 0.6158 acc/top5: 0.8376 acc/mean1: 0.6156 2022/10/09 23:34:04 - mmengine - INFO - Epoch(train) [16][20/940] lr: 1.0000e-02 eta: 11:15:25 time: 0.7183 data_time: 0.1956 memory: 21547 grad_norm: 3.6386 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8417 loss: 1.8417 2022/10/09 23:34:14 - mmengine - INFO - Epoch(train) [16][40/940] lr: 1.0000e-02 eta: 11:15:13 time: 0.4957 data_time: 0.0291 memory: 21547 grad_norm: 3.6826 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8913 loss: 1.8913 2022/10/09 23:34:26 - mmengine - INFO - Epoch(train) [16][60/940] lr: 1.0000e-02 eta: 11:15:10 time: 0.5701 data_time: 0.0270 memory: 21547 grad_norm: 3.6242 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.7696 loss: 1.7696 2022/10/09 23:34:36 - mmengine - INFO - Epoch(train) [16][80/940] lr: 1.0000e-02 eta: 11:14:59 time: 0.5035 data_time: 0.0292 memory: 21547 grad_norm: 3.6672 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7987 loss: 1.7987 2022/10/09 23:34:46 - mmengine - INFO - Epoch(train) [16][100/940] lr: 1.0000e-02 eta: 11:14:48 time: 0.4953 data_time: 0.0304 memory: 21547 grad_norm: 3.6814 top1_acc: 0.4062 top5_acc: 0.5625 loss_cls: 1.8310 loss: 1.8310 2022/10/09 23:34:55 - mmengine - INFO - Epoch(train) [16][120/940] lr: 1.0000e-02 eta: 11:14:35 time: 0.4799 data_time: 0.0257 memory: 21547 grad_norm: 3.8102 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8369 loss: 1.8369 2022/10/09 23:35:06 - mmengine - INFO - Epoch(train) [16][140/940] lr: 1.0000e-02 eta: 11:14:27 time: 0.5328 data_time: 0.0259 memory: 21547 grad_norm: 3.7139 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7881 loss: 1.7881 2022/10/09 23:35:16 - mmengine - INFO - Epoch(train) [16][160/940] lr: 1.0000e-02 eta: 11:14:14 time: 0.4817 data_time: 0.0279 memory: 21547 grad_norm: 3.6891 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7442 loss: 1.7442 2022/10/09 23:35:26 - mmengine - INFO - Epoch(train) [16][180/940] lr: 1.0000e-02 eta: 11:14:06 time: 0.5240 data_time: 0.0288 memory: 21547 grad_norm: 3.7285 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.7144 loss: 1.7144 2022/10/09 23:35:36 - mmengine - INFO - Epoch(train) [16][200/940] lr: 1.0000e-02 eta: 11:13:55 time: 0.4993 data_time: 0.0305 memory: 21547 grad_norm: 3.7672 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8183 loss: 1.8183 2022/10/09 23:35:46 - mmengine - INFO - Epoch(train) [16][220/940] lr: 1.0000e-02 eta: 11:13:42 time: 0.4770 data_time: 0.0328 memory: 21547 grad_norm: 3.8039 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8708 loss: 1.8708 2022/10/09 23:35:55 - mmengine - INFO - Epoch(train) [16][240/940] lr: 1.0000e-02 eta: 11:13:28 time: 0.4790 data_time: 0.0261 memory: 21547 grad_norm: 3.7173 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.8138 loss: 1.8138 2022/10/09 23:36:06 - mmengine - INFO - Epoch(train) [16][260/940] lr: 1.0000e-02 eta: 11:13:22 time: 0.5472 data_time: 0.0287 memory: 21547 grad_norm: 3.7019 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.6967 loss: 1.6967 2022/10/09 23:36:16 - mmengine - INFO - Epoch(train) [16][280/940] lr: 1.0000e-02 eta: 11:13:09 time: 0.4781 data_time: 0.0244 memory: 21547 grad_norm: 3.7621 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7634 loss: 1.7634 2022/10/09 23:36:26 - mmengine - INFO - Epoch(train) [16][300/940] lr: 1.0000e-02 eta: 11:12:57 time: 0.4910 data_time: 0.0304 memory: 21547 grad_norm: 3.7083 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8537 loss: 1.8537 2022/10/09 23:36:36 - mmengine - INFO - Epoch(train) [16][320/940] lr: 1.0000e-02 eta: 11:12:50 time: 0.5366 data_time: 0.0321 memory: 21547 grad_norm: 3.7291 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.9355 loss: 1.9355 2022/10/09 23:36:46 - mmengine - INFO - Epoch(train) [16][340/940] lr: 1.0000e-02 eta: 11:12:38 time: 0.4910 data_time: 0.0297 memory: 21547 grad_norm: 3.6442 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.7609 loss: 1.7609 2022/10/09 23:36:56 - mmengine - INFO - Epoch(train) [16][360/940] lr: 1.0000e-02 eta: 11:12:29 time: 0.5119 data_time: 0.0283 memory: 21547 grad_norm: 3.6899 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7836 loss: 1.7836 2022/10/09 23:37:06 - mmengine - INFO - Epoch(train) [16][380/940] lr: 1.0000e-02 eta: 11:12:15 time: 0.4743 data_time: 0.0262 memory: 21547 grad_norm: 3.6938 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8563 loss: 1.8563 2022/10/09 23:37:16 - mmengine - INFO - Epoch(train) [16][400/940] lr: 1.0000e-02 eta: 11:12:03 time: 0.4949 data_time: 0.0302 memory: 21547 grad_norm: 3.7262 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7842 loss: 1.7842 2022/10/09 23:37:27 - mmengine - INFO - Epoch(train) [16][420/940] lr: 1.0000e-02 eta: 11:11:58 time: 0.5498 data_time: 0.0239 memory: 21547 grad_norm: 3.7770 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7498 loss: 1.7498 2022/10/09 23:37:36 - mmengine - INFO - Epoch(train) [16][440/940] lr: 1.0000e-02 eta: 11:11:44 time: 0.4681 data_time: 0.0312 memory: 21547 grad_norm: 3.7410 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8231 loss: 1.8231 2022/10/09 23:37:47 - mmengine - INFO - Epoch(train) [16][460/940] lr: 1.0000e-02 eta: 11:11:35 time: 0.5217 data_time: 0.0267 memory: 21547 grad_norm: 3.7297 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.8562 loss: 1.8562 2022/10/09 23:37:56 - mmengine - INFO - Epoch(train) [16][480/940] lr: 1.0000e-02 eta: 11:11:23 time: 0.4887 data_time: 0.0313 memory: 21547 grad_norm: 3.6909 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7625 loss: 1.7625 2022/10/09 23:38:07 - mmengine - INFO - Epoch(train) [16][500/940] lr: 1.0000e-02 eta: 11:11:15 time: 0.5255 data_time: 0.0239 memory: 21547 grad_norm: 3.8381 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9648 loss: 1.9648 2022/10/09 23:38:17 - mmengine - INFO - Epoch(train) [16][520/940] lr: 1.0000e-02 eta: 11:11:03 time: 0.4923 data_time: 0.0258 memory: 21547 grad_norm: 3.7037 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 1.9476 loss: 1.9476 2022/10/09 23:38:27 - mmengine - INFO - Epoch(train) [16][540/940] lr: 1.0000e-02 eta: 11:10:52 time: 0.4995 data_time: 0.0240 memory: 21547 grad_norm: 3.7788 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.9746 loss: 1.9746 2022/10/09 23:38:37 - mmengine - INFO - Epoch(train) [16][560/940] lr: 1.0000e-02 eta: 11:10:42 time: 0.5093 data_time: 0.0271 memory: 21547 grad_norm: 3.7632 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9033 loss: 1.9033 2022/10/09 23:38:47 - mmengine - INFO - Epoch(train) [16][580/940] lr: 1.0000e-02 eta: 11:10:31 time: 0.5001 data_time: 0.0296 memory: 21547 grad_norm: 3.7591 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9081 loss: 1.9081 2022/10/09 23:38:57 - mmengine - INFO - Epoch(train) [16][600/940] lr: 1.0000e-02 eta: 11:10:20 time: 0.5011 data_time: 0.0317 memory: 21547 grad_norm: 3.7723 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.8690 loss: 1.8690 2022/10/09 23:39:06 - mmengine - INFO - Epoch(train) [16][620/940] lr: 1.0000e-02 eta: 11:10:07 time: 0.4798 data_time: 0.0276 memory: 21547 grad_norm: 3.7037 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.9112 loss: 1.9112 2022/10/09 23:39:18 - mmengine - INFO - Epoch(train) [16][640/940] lr: 1.0000e-02 eta: 11:10:02 time: 0.5568 data_time: 0.0286 memory: 21547 grad_norm: 3.7498 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9130 loss: 1.9130 2022/10/09 23:39:27 - mmengine - INFO - Epoch(train) [16][660/940] lr: 1.0000e-02 eta: 11:09:49 time: 0.4801 data_time: 0.0253 memory: 21547 grad_norm: 3.6897 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.7026 loss: 1.7026 2022/10/09 23:39:38 - mmengine - INFO - Epoch(train) [16][680/940] lr: 1.0000e-02 eta: 11:09:42 time: 0.5350 data_time: 0.0370 memory: 21547 grad_norm: 3.6757 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7190 loss: 1.7190 2022/10/09 23:39:48 - mmengine - INFO - Epoch(train) [16][700/940] lr: 1.0000e-02 eta: 11:09:29 time: 0.4807 data_time: 0.0246 memory: 21547 grad_norm: 3.7230 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7986 loss: 1.7986 2022/10/09 23:39:58 - mmengine - INFO - Epoch(train) [16][720/940] lr: 1.0000e-02 eta: 11:09:19 time: 0.5061 data_time: 0.0359 memory: 21547 grad_norm: 3.6940 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8630 loss: 1.8630 2022/10/09 23:40:09 - mmengine - INFO - Epoch(train) [16][740/940] lr: 1.0000e-02 eta: 11:09:13 time: 0.5494 data_time: 0.0252 memory: 21547 grad_norm: 3.6776 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7372 loss: 1.7372 2022/10/09 23:40:18 - mmengine - INFO - Epoch(train) [16][760/940] lr: 1.0000e-02 eta: 11:09:01 time: 0.4893 data_time: 0.0266 memory: 21547 grad_norm: 3.7381 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9525 loss: 1.9525 2022/10/09 23:40:28 - mmengine - INFO - Epoch(train) [16][780/940] lr: 1.0000e-02 eta: 11:08:46 time: 0.4571 data_time: 0.0312 memory: 21547 grad_norm: 3.7513 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8383 loss: 1.8383 2022/10/09 23:40:37 - mmengine - INFO - Epoch(train) [16][800/940] lr: 1.0000e-02 eta: 11:08:33 time: 0.4854 data_time: 0.0252 memory: 21547 grad_norm: 3.7448 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7345 loss: 1.7345 2022/10/09 23:40:48 - mmengine - INFO - Epoch(train) [16][820/940] lr: 1.0000e-02 eta: 11:08:24 time: 0.5159 data_time: 0.0274 memory: 21547 grad_norm: 3.7456 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.8217 loss: 1.8217 2022/10/09 23:40:57 - mmengine - INFO - Epoch(train) [16][840/940] lr: 1.0000e-02 eta: 11:08:12 time: 0.4919 data_time: 0.0262 memory: 21547 grad_norm: 3.7567 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.7794 loss: 1.7794 2022/10/09 23:41:08 - mmengine - INFO - Epoch(train) [16][860/940] lr: 1.0000e-02 eta: 11:08:04 time: 0.5246 data_time: 0.0305 memory: 21547 grad_norm: 3.7559 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.8306 loss: 1.8306 2022/10/09 23:41:18 - mmengine - INFO - Epoch(train) [16][880/940] lr: 1.0000e-02 eta: 11:07:53 time: 0.5035 data_time: 0.0225 memory: 21547 grad_norm: 3.7041 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9517 loss: 1.9517 2022/10/09 23:41:28 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 23:41:28 - mmengine - INFO - Epoch(train) [16][900/940] lr: 1.0000e-02 eta: 11:07:44 time: 0.5092 data_time: 0.0259 memory: 21547 grad_norm: 3.7197 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.8631 loss: 1.8631 2022/10/09 23:41:38 - mmengine - INFO - Epoch(train) [16][920/940] lr: 1.0000e-02 eta: 11:07:33 time: 0.5029 data_time: 0.0281 memory: 21547 grad_norm: 3.7419 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9210 loss: 1.9210 2022/10/09 23:41:47 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 23:41:47 - mmengine - INFO - Epoch(train) [16][940/940] lr: 1.0000e-02 eta: 11:07:18 time: 0.4571 data_time: 0.0254 memory: 21547 grad_norm: 4.0203 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.7867 loss: 1.7867 2022/10/09 23:42:00 - mmengine - INFO - Epoch(val) [16][20/78] eta: 0:00:35 time: 0.6086 data_time: 0.4973 memory: 3269 2022/10/09 23:42:08 - mmengine - INFO - Epoch(val) [16][40/78] eta: 0:00:15 time: 0.4127 data_time: 0.3045 memory: 3269 2022/10/09 23:42:19 - mmengine - INFO - Epoch(val) [16][60/78] eta: 0:00:10 time: 0.5610 data_time: 0.4538 memory: 3269 2022/10/09 23:42:29 - mmengine - INFO - Epoch(val) [16][78/78] acc/top1: 0.6235 acc/top5: 0.8422 acc/mean1: 0.6233 2022/10/09 23:42:29 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_14.pth is removed 2022/10/09 23:42:30 - mmengine - INFO - The best checkpoint with 0.6235 acc/top1 at 16 epoch is saved to best_acc/top1_epoch_16.pth. 2022/10/09 23:42:43 - mmengine - INFO - Epoch(train) [17][20/940] lr: 1.0000e-02 eta: 11:07:26 time: 0.6830 data_time: 0.2656 memory: 21547 grad_norm: 3.6462 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7956 loss: 1.7956 2022/10/09 23:42:53 - mmengine - INFO - Epoch(train) [17][40/940] lr: 1.0000e-02 eta: 11:07:12 time: 0.4747 data_time: 0.0937 memory: 21547 grad_norm: 3.7262 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7840 loss: 1.7840 2022/10/09 23:43:04 - mmengine - INFO - Epoch(train) [17][60/940] lr: 1.0000e-02 eta: 11:07:08 time: 0.5610 data_time: 0.0722 memory: 21547 grad_norm: 3.7124 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.9357 loss: 1.9357 2022/10/09 23:43:14 - mmengine - INFO - Epoch(train) [17][80/940] lr: 1.0000e-02 eta: 11:06:56 time: 0.4922 data_time: 0.0235 memory: 21547 grad_norm: 3.7566 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8859 loss: 1.8859 2022/10/09 23:43:24 - mmengine - INFO - Epoch(train) [17][100/940] lr: 1.0000e-02 eta: 11:06:48 time: 0.5288 data_time: 0.0317 memory: 21547 grad_norm: 3.6289 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8675 loss: 1.8675 2022/10/09 23:43:34 - mmengine - INFO - Epoch(train) [17][120/940] lr: 1.0000e-02 eta: 11:06:35 time: 0.4789 data_time: 0.0316 memory: 21547 grad_norm: 3.6680 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7051 loss: 1.7051 2022/10/09 23:43:45 - mmengine - INFO - Epoch(train) [17][140/940] lr: 1.0000e-02 eta: 11:06:27 time: 0.5245 data_time: 0.0269 memory: 21547 grad_norm: 3.7517 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.9085 loss: 1.9085 2022/10/09 23:43:55 - mmengine - INFO - Epoch(train) [17][160/940] lr: 1.0000e-02 eta: 11:06:19 time: 0.5271 data_time: 0.0266 memory: 21547 grad_norm: 3.7538 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7384 loss: 1.7384 2022/10/09 23:44:05 - mmengine - INFO - Epoch(train) [17][180/940] lr: 1.0000e-02 eta: 11:06:05 time: 0.4770 data_time: 0.0356 memory: 21547 grad_norm: 3.7570 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7999 loss: 1.7999 2022/10/09 23:44:14 - mmengine - INFO - Epoch(train) [17][200/940] lr: 1.0000e-02 eta: 11:05:52 time: 0.4726 data_time: 0.0272 memory: 21547 grad_norm: 3.7140 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.7995 loss: 1.7995 2022/10/09 23:44:25 - mmengine - INFO - Epoch(train) [17][220/940] lr: 1.0000e-02 eta: 11:05:46 time: 0.5472 data_time: 0.0341 memory: 21547 grad_norm: 3.6990 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7706 loss: 1.7706 2022/10/09 23:44:35 - mmengine - INFO - Epoch(train) [17][240/940] lr: 1.0000e-02 eta: 11:05:32 time: 0.4769 data_time: 0.0272 memory: 21547 grad_norm: 3.7247 top1_acc: 0.3438 top5_acc: 0.7812 loss_cls: 1.8962 loss: 1.8962 2022/10/09 23:44:45 - mmengine - INFO - Epoch(train) [17][260/940] lr: 1.0000e-02 eta: 11:05:22 time: 0.5100 data_time: 0.0287 memory: 21547 grad_norm: 3.7876 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.7951 loss: 1.7951 2022/10/09 23:44:56 - mmengine - INFO - Epoch(train) [17][280/940] lr: 1.0000e-02 eta: 11:05:16 time: 0.5390 data_time: 0.0266 memory: 21547 grad_norm: 3.6902 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7419 loss: 1.7419 2022/10/09 23:45:06 - mmengine - INFO - Epoch(train) [17][300/940] lr: 1.0000e-02 eta: 11:05:06 time: 0.5169 data_time: 0.0255 memory: 21547 grad_norm: 3.7447 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.9712 loss: 1.9712 2022/10/09 23:45:16 - mmengine - INFO - Epoch(train) [17][320/940] lr: 1.0000e-02 eta: 11:04:55 time: 0.4976 data_time: 0.0262 memory: 21547 grad_norm: 3.7641 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9195 loss: 1.9195 2022/10/09 23:45:26 - mmengine - INFO - Epoch(train) [17][340/940] lr: 1.0000e-02 eta: 11:04:46 time: 0.5169 data_time: 0.0278 memory: 21547 grad_norm: 3.8027 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 2.0021 loss: 2.0021 2022/10/09 23:45:35 - mmengine - INFO - Epoch(train) [17][360/940] lr: 1.0000e-02 eta: 11:04:32 time: 0.4644 data_time: 0.0249 memory: 21547 grad_norm: 3.7754 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.8324 loss: 1.8324 2022/10/09 23:45:45 - mmengine - INFO - Epoch(train) [17][380/940] lr: 1.0000e-02 eta: 11:04:18 time: 0.4746 data_time: 0.0290 memory: 21547 grad_norm: 3.7052 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9417 loss: 1.9417 2022/10/09 23:45:55 - mmengine - INFO - Epoch(train) [17][400/940] lr: 1.0000e-02 eta: 11:04:09 time: 0.5152 data_time: 0.0305 memory: 21547 grad_norm: 3.7379 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8178 loss: 1.8178 2022/10/09 23:46:05 - mmengine - INFO - Epoch(train) [17][420/940] lr: 1.0000e-02 eta: 11:03:58 time: 0.4984 data_time: 0.0267 memory: 21547 grad_norm: 3.7145 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.9250 loss: 1.9250 2022/10/09 23:46:15 - mmengine - INFO - Epoch(train) [17][440/940] lr: 1.0000e-02 eta: 11:03:45 time: 0.4861 data_time: 0.0307 memory: 21547 grad_norm: 3.7583 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8118 loss: 1.8118 2022/10/09 23:46:25 - mmengine - INFO - Epoch(train) [17][460/940] lr: 1.0000e-02 eta: 11:03:34 time: 0.4945 data_time: 0.0412 memory: 21547 grad_norm: 3.6954 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8587 loss: 1.8587 2022/10/09 23:46:35 - mmengine - INFO - Epoch(train) [17][480/940] lr: 1.0000e-02 eta: 11:03:23 time: 0.4947 data_time: 0.0359 memory: 21547 grad_norm: 3.8026 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.9214 loss: 1.9214 2022/10/09 23:46:45 - mmengine - INFO - Epoch(train) [17][500/940] lr: 1.0000e-02 eta: 11:03:13 time: 0.5125 data_time: 0.0805 memory: 21547 grad_norm: 3.8297 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7761 loss: 1.7761 2022/10/09 23:46:56 - mmengine - INFO - Epoch(train) [17][520/940] lr: 1.0000e-02 eta: 11:03:06 time: 0.5398 data_time: 0.0754 memory: 21547 grad_norm: 3.7788 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.8418 loss: 1.8418 2022/10/09 23:47:06 - mmengine - INFO - Epoch(train) [17][540/940] lr: 1.0000e-02 eta: 11:02:55 time: 0.4949 data_time: 0.0258 memory: 21547 grad_norm: 3.7915 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.7167 loss: 1.7167 2022/10/09 23:47:17 - mmengine - INFO - Epoch(train) [17][560/940] lr: 1.0000e-02 eta: 11:02:49 time: 0.5554 data_time: 0.0282 memory: 21547 grad_norm: 3.7464 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8116 loss: 1.8116 2022/10/09 23:47:26 - mmengine - INFO - Epoch(train) [17][580/940] lr: 1.0000e-02 eta: 11:02:37 time: 0.4801 data_time: 0.0244 memory: 21547 grad_norm: 3.6884 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.9086 loss: 1.9086 2022/10/09 23:47:37 - mmengine - INFO - Epoch(train) [17][600/940] lr: 1.0000e-02 eta: 11:02:29 time: 0.5368 data_time: 0.0247 memory: 21547 grad_norm: 3.7050 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.8176 loss: 1.8176 2022/10/09 23:47:47 - mmengine - INFO - Epoch(train) [17][620/940] lr: 1.0000e-02 eta: 11:02:16 time: 0.4758 data_time: 0.0270 memory: 21547 grad_norm: 3.7754 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8275 loss: 1.8275 2022/10/09 23:47:57 - mmengine - INFO - Epoch(train) [17][640/940] lr: 1.0000e-02 eta: 11:02:08 time: 0.5280 data_time: 0.0262 memory: 21547 grad_norm: 3.8123 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.9269 loss: 1.9269 2022/10/09 23:48:07 - mmengine - INFO - Epoch(train) [17][660/940] lr: 1.0000e-02 eta: 11:01:55 time: 0.4821 data_time: 0.0303 memory: 21547 grad_norm: 3.8144 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.8646 loss: 1.8646 2022/10/09 23:48:17 - mmengine - INFO - Epoch(train) [17][680/940] lr: 1.0000e-02 eta: 11:01:45 time: 0.5052 data_time: 0.0264 memory: 21547 grad_norm: 3.8050 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8196 loss: 1.8196 2022/10/09 23:48:27 - mmengine - INFO - Epoch(train) [17][700/940] lr: 1.0000e-02 eta: 11:01:36 time: 0.5217 data_time: 0.0318 memory: 21547 grad_norm: 3.8233 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7653 loss: 1.7653 2022/10/09 23:48:38 - mmengine - INFO - Epoch(train) [17][720/940] lr: 1.0000e-02 eta: 11:01:27 time: 0.5190 data_time: 0.0323 memory: 21547 grad_norm: 3.7000 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.8354 loss: 1.8354 2022/10/09 23:48:47 - mmengine - INFO - Epoch(train) [17][740/940] lr: 1.0000e-02 eta: 11:01:11 time: 0.4489 data_time: 0.0246 memory: 21547 grad_norm: 3.7182 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.8812 loss: 1.8812 2022/10/09 23:48:58 - mmengine - INFO - Epoch(train) [17][760/940] lr: 1.0000e-02 eta: 11:01:05 time: 0.5462 data_time: 0.0250 memory: 21547 grad_norm: 3.7643 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.7940 loss: 1.7940 2022/10/09 23:49:08 - mmengine - INFO - Epoch(train) [17][780/940] lr: 1.0000e-02 eta: 11:00:56 time: 0.5164 data_time: 0.0290 memory: 21547 grad_norm: 3.7357 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7501 loss: 1.7501 2022/10/09 23:49:18 - mmengine - INFO - Epoch(train) [17][800/940] lr: 1.0000e-02 eta: 11:00:44 time: 0.4927 data_time: 0.0293 memory: 21547 grad_norm: 3.7711 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8275 loss: 1.8275 2022/10/09 23:49:27 - mmengine - INFO - Epoch(train) [17][820/940] lr: 1.0000e-02 eta: 11:00:29 time: 0.4526 data_time: 0.0307 memory: 21547 grad_norm: 3.7877 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.8113 loss: 1.8113 2022/10/09 23:49:37 - mmengine - INFO - Epoch(train) [17][840/940] lr: 1.0000e-02 eta: 11:00:17 time: 0.4904 data_time: 0.0269 memory: 21547 grad_norm: 3.7579 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.9013 loss: 1.9013 2022/10/09 23:49:46 - mmengine - INFO - Epoch(train) [17][860/940] lr: 1.0000e-02 eta: 11:00:05 time: 0.4859 data_time: 0.0295 memory: 21547 grad_norm: 3.8594 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7046 loss: 1.7046 2022/10/09 23:49:57 - mmengine - INFO - Epoch(train) [17][880/940] lr: 1.0000e-02 eta: 10:59:57 time: 0.5299 data_time: 0.0269 memory: 21547 grad_norm: 3.6434 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7219 loss: 1.7219 2022/10/09 23:50:07 - mmengine - INFO - Epoch(train) [17][900/940] lr: 1.0000e-02 eta: 10:59:48 time: 0.5212 data_time: 0.0256 memory: 21547 grad_norm: 3.7751 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9025 loss: 1.9025 2022/10/09 23:50:18 - mmengine - INFO - Epoch(train) [17][920/940] lr: 1.0000e-02 eta: 10:59:38 time: 0.5104 data_time: 0.0292 memory: 21547 grad_norm: 3.7502 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.7175 loss: 1.7175 2022/10/09 23:50:27 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 23:50:27 - mmengine - INFO - Epoch(train) [17][940/940] lr: 1.0000e-02 eta: 10:59:23 time: 0.4548 data_time: 0.0246 memory: 21547 grad_norm: 3.9877 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.7324 loss: 1.7324 2022/10/09 23:50:39 - mmengine - INFO - Epoch(val) [17][20/78] eta: 0:00:35 time: 0.6090 data_time: 0.4972 memory: 3269 2022/10/09 23:50:47 - mmengine - INFO - Epoch(val) [17][40/78] eta: 0:00:15 time: 0.4180 data_time: 0.3100 memory: 3269 2022/10/09 23:50:58 - mmengine - INFO - Epoch(val) [17][60/78] eta: 0:00:09 time: 0.5528 data_time: 0.4438 memory: 3269 2022/10/09 23:51:08 - mmengine - INFO - Epoch(val) [17][78/78] acc/top1: 0.6210 acc/top5: 0.8398 acc/mean1: 0.6209 2022/10/09 23:51:23 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 23:51:23 - mmengine - INFO - Epoch(train) [18][20/940] lr: 1.0000e-02 eta: 10:59:34 time: 0.7223 data_time: 0.2202 memory: 21547 grad_norm: 3.7213 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.7769 loss: 1.7769 2022/10/09 23:51:33 - mmengine - INFO - Epoch(train) [18][40/940] lr: 1.0000e-02 eta: 10:59:22 time: 0.4915 data_time: 0.0268 memory: 21547 grad_norm: 3.7481 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.7185 loss: 1.7185 2022/10/09 23:51:44 - mmengine - INFO - Epoch(train) [18][60/940] lr: 1.0000e-02 eta: 10:59:17 time: 0.5566 data_time: 0.0300 memory: 21547 grad_norm: 3.7007 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9127 loss: 1.9127 2022/10/09 23:51:54 - mmengine - INFO - Epoch(train) [18][80/940] lr: 1.0000e-02 eta: 10:59:08 time: 0.5253 data_time: 0.0305 memory: 21547 grad_norm: 3.8014 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7741 loss: 1.7741 2022/10/09 23:52:04 - mmengine - INFO - Epoch(train) [18][100/940] lr: 1.0000e-02 eta: 10:58:59 time: 0.5151 data_time: 0.0326 memory: 21547 grad_norm: 3.7854 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7615 loss: 1.7615 2022/10/09 23:52:14 - mmengine - INFO - Epoch(train) [18][120/940] lr: 1.0000e-02 eta: 10:58:46 time: 0.4758 data_time: 0.0338 memory: 21547 grad_norm: 3.7979 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7588 loss: 1.7588 2022/10/09 23:52:24 - mmengine - INFO - Epoch(train) [18][140/940] lr: 1.0000e-02 eta: 10:58:37 time: 0.5201 data_time: 0.0271 memory: 21547 grad_norm: 3.7438 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8462 loss: 1.8462 2022/10/09 23:52:34 - mmengine - INFO - Epoch(train) [18][160/940] lr: 1.0000e-02 eta: 10:58:23 time: 0.4736 data_time: 0.0302 memory: 21547 grad_norm: 3.7273 top1_acc: 0.3438 top5_acc: 0.8750 loss_cls: 1.8340 loss: 1.8340 2022/10/09 23:52:45 - mmengine - INFO - Epoch(train) [18][180/940] lr: 1.0000e-02 eta: 10:58:17 time: 0.5456 data_time: 0.0245 memory: 21547 grad_norm: 3.8058 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.9493 loss: 1.9493 2022/10/09 23:52:55 - mmengine - INFO - Epoch(train) [18][200/940] lr: 1.0000e-02 eta: 10:58:06 time: 0.5032 data_time: 0.0254 memory: 21547 grad_norm: 3.7074 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.7127 loss: 1.7127 2022/10/09 23:53:04 - mmengine - INFO - Epoch(train) [18][220/940] lr: 1.0000e-02 eta: 10:57:50 time: 0.4478 data_time: 0.0256 memory: 21547 grad_norm: 3.7337 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8123 loss: 1.8123 2022/10/09 23:53:14 - mmengine - INFO - Epoch(train) [18][240/940] lr: 1.0000e-02 eta: 10:57:42 time: 0.5255 data_time: 0.0257 memory: 21547 grad_norm: 3.6945 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.6295 loss: 1.6295 2022/10/09 23:53:24 - mmengine - INFO - Epoch(train) [18][260/940] lr: 1.0000e-02 eta: 10:57:31 time: 0.4983 data_time: 0.0252 memory: 21547 grad_norm: 3.7421 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7474 loss: 1.7474 2022/10/09 23:53:34 - mmengine - INFO - Epoch(train) [18][280/940] lr: 1.0000e-02 eta: 10:57:19 time: 0.4831 data_time: 0.0251 memory: 21547 grad_norm: 3.8129 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8802 loss: 1.8802 2022/10/09 23:53:45 - mmengine - INFO - Epoch(train) [18][300/940] lr: 1.0000e-02 eta: 10:57:12 time: 0.5461 data_time: 0.0315 memory: 21547 grad_norm: 3.8359 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.9323 loss: 1.9323 2022/10/09 23:53:55 - mmengine - INFO - Epoch(train) [18][320/940] lr: 1.0000e-02 eta: 10:57:02 time: 0.5100 data_time: 0.0285 memory: 21547 grad_norm: 3.7646 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7305 loss: 1.7305 2022/10/09 23:54:05 - mmengine - INFO - Epoch(train) [18][340/940] lr: 1.0000e-02 eta: 10:56:52 time: 0.5034 data_time: 0.0313 memory: 21547 grad_norm: 3.7133 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.6786 loss: 1.6786 2022/10/09 23:54:15 - mmengine - INFO - Epoch(train) [18][360/940] lr: 1.0000e-02 eta: 10:56:39 time: 0.4820 data_time: 0.0260 memory: 21547 grad_norm: 3.7903 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6441 loss: 1.6441 2022/10/09 23:54:26 - mmengine - INFO - Epoch(train) [18][380/940] lr: 1.0000e-02 eta: 10:56:34 time: 0.5564 data_time: 0.0264 memory: 21547 grad_norm: 3.7994 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8359 loss: 1.8359 2022/10/09 23:54:35 - mmengine - INFO - Epoch(train) [18][400/940] lr: 1.0000e-02 eta: 10:56:20 time: 0.4706 data_time: 0.0308 memory: 21547 grad_norm: 3.7599 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8100 loss: 1.8100 2022/10/09 23:54:46 - mmengine - INFO - Epoch(train) [18][420/940] lr: 1.0000e-02 eta: 10:56:11 time: 0.5231 data_time: 0.0295 memory: 21547 grad_norm: 3.8214 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8042 loss: 1.8042 2022/10/09 23:54:55 - mmengine - INFO - Epoch(train) [18][440/940] lr: 1.0000e-02 eta: 10:55:55 time: 0.4437 data_time: 0.0302 memory: 21547 grad_norm: 3.7700 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.8668 loss: 1.8668 2022/10/09 23:55:05 - mmengine - INFO - Epoch(train) [18][460/940] lr: 1.0000e-02 eta: 10:55:44 time: 0.4942 data_time: 0.0273 memory: 21547 grad_norm: 3.8318 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.8797 loss: 1.8797 2022/10/09 23:55:15 - mmengine - INFO - Epoch(train) [18][480/940] lr: 1.0000e-02 eta: 10:55:34 time: 0.5149 data_time: 0.0243 memory: 21547 grad_norm: 3.6767 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7154 loss: 1.7154 2022/10/09 23:55:24 - mmengine - INFO - Epoch(train) [18][500/940] lr: 1.0000e-02 eta: 10:55:21 time: 0.4748 data_time: 0.0262 memory: 21547 grad_norm: 3.7972 top1_acc: 0.2812 top5_acc: 0.5625 loss_cls: 1.8836 loss: 1.8836 2022/10/09 23:55:35 - mmengine - INFO - Epoch(train) [18][520/940] lr: 1.0000e-02 eta: 10:55:11 time: 0.5083 data_time: 0.0258 memory: 21547 grad_norm: 3.7112 top1_acc: 0.4688 top5_acc: 0.9062 loss_cls: 1.8572 loss: 1.8572 2022/10/09 23:55:44 - mmengine - INFO - Epoch(train) [18][540/940] lr: 1.0000e-02 eta: 10:55:00 time: 0.4950 data_time: 0.0291 memory: 21547 grad_norm: 3.7995 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7151 loss: 1.7151 2022/10/09 23:55:56 - mmengine - INFO - Epoch(train) [18][560/940] lr: 1.0000e-02 eta: 10:54:56 time: 0.5707 data_time: 0.0265 memory: 21547 grad_norm: 3.7614 top1_acc: 0.4375 top5_acc: 0.8438 loss_cls: 1.7061 loss: 1.7061 2022/10/09 23:56:06 - mmengine - INFO - Epoch(train) [18][580/940] lr: 1.0000e-02 eta: 10:54:45 time: 0.5033 data_time: 0.0243 memory: 21547 grad_norm: 3.7447 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8419 loss: 1.8419 2022/10/09 23:56:16 - mmengine - INFO - Epoch(train) [18][600/940] lr: 1.0000e-02 eta: 10:54:37 time: 0.5294 data_time: 0.0235 memory: 21547 grad_norm: 3.8292 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8479 loss: 1.8479 2022/10/09 23:56:26 - mmengine - INFO - Epoch(train) [18][620/940] lr: 1.0000e-02 eta: 10:54:24 time: 0.4741 data_time: 0.0346 memory: 21547 grad_norm: 3.8314 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.8022 loss: 1.8022 2022/10/09 23:56:36 - mmengine - INFO - Epoch(train) [18][640/940] lr: 1.0000e-02 eta: 10:54:14 time: 0.5099 data_time: 0.0279 memory: 21547 grad_norm: 3.7228 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7386 loss: 1.7386 2022/10/09 23:56:46 - mmengine - INFO - Epoch(train) [18][660/940] lr: 1.0000e-02 eta: 10:54:02 time: 0.4914 data_time: 0.0234 memory: 21547 grad_norm: 3.8018 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.7495 loss: 1.7495 2022/10/09 23:56:57 - mmengine - INFO - Epoch(train) [18][680/940] lr: 1.0000e-02 eta: 10:53:55 time: 0.5345 data_time: 0.0251 memory: 21547 grad_norm: 3.7952 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.8961 loss: 1.8961 2022/10/09 23:57:06 - mmengine - INFO - Epoch(train) [18][700/940] lr: 1.0000e-02 eta: 10:53:38 time: 0.4413 data_time: 0.0274 memory: 21547 grad_norm: 3.7784 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9458 loss: 1.9458 2022/10/09 23:57:16 - mmengine - INFO - Epoch(train) [18][720/940] lr: 1.0000e-02 eta: 10:53:28 time: 0.5009 data_time: 0.0318 memory: 21547 grad_norm: 3.7581 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6621 loss: 1.6621 2022/10/09 23:57:25 - mmengine - INFO - Epoch(train) [18][740/940] lr: 1.0000e-02 eta: 10:53:13 time: 0.4602 data_time: 0.0317 memory: 21547 grad_norm: 3.7626 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8204 loss: 1.8204 2022/10/09 23:57:36 - mmengine - INFO - Epoch(train) [18][760/940] lr: 1.0000e-02 eta: 10:53:07 time: 0.5488 data_time: 0.0479 memory: 21547 grad_norm: 3.8576 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8541 loss: 1.8541 2022/10/09 23:57:45 - mmengine - INFO - Epoch(train) [18][780/940] lr: 1.0000e-02 eta: 10:52:54 time: 0.4817 data_time: 0.0443 memory: 21547 grad_norm: 3.7212 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7823 loss: 1.7823 2022/10/09 23:57:56 - mmengine - INFO - Epoch(train) [18][800/940] lr: 1.0000e-02 eta: 10:52:46 time: 0.5291 data_time: 0.0343 memory: 21547 grad_norm: 3.7635 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7918 loss: 1.7918 2022/10/09 23:58:06 - mmengine - INFO - Epoch(train) [18][820/940] lr: 1.0000e-02 eta: 10:52:34 time: 0.4794 data_time: 0.0300 memory: 21547 grad_norm: 3.7360 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7733 loss: 1.7733 2022/10/09 23:58:16 - mmengine - INFO - Epoch(train) [18][840/940] lr: 1.0000e-02 eta: 10:52:23 time: 0.4997 data_time: 0.0328 memory: 21547 grad_norm: 3.8490 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8478 loss: 1.8478 2022/10/09 23:58:26 - mmengine - INFO - Epoch(train) [18][860/940] lr: 1.0000e-02 eta: 10:52:15 time: 0.5300 data_time: 0.0260 memory: 21547 grad_norm: 3.8078 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8476 loss: 1.8476 2022/10/09 23:58:36 - mmengine - INFO - Epoch(train) [18][880/940] lr: 1.0000e-02 eta: 10:52:03 time: 0.4940 data_time: 0.0284 memory: 21547 grad_norm: 3.7265 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8639 loss: 1.8639 2022/10/09 23:58:47 - mmengine - INFO - Epoch(train) [18][900/940] lr: 1.0000e-02 eta: 10:51:56 time: 0.5323 data_time: 0.0286 memory: 21547 grad_norm: 3.7391 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7962 loss: 1.7962 2022/10/09 23:58:57 - mmengine - INFO - Epoch(train) [18][920/940] lr: 1.0000e-02 eta: 10:51:44 time: 0.4936 data_time: 0.0228 memory: 21547 grad_norm: 3.7598 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7729 loss: 1.7729 2022/10/09 23:59:06 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/09 23:59:06 - mmengine - INFO - Epoch(train) [18][940/940] lr: 1.0000e-02 eta: 10:51:30 time: 0.4630 data_time: 0.0246 memory: 21547 grad_norm: 3.9614 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.8038 loss: 1.8038 2022/10/09 23:59:06 - mmengine - INFO - Saving checkpoint at 18 epochs 2022/10/09 23:59:19 - mmengine - INFO - Epoch(val) [18][20/78] eta: 0:00:35 time: 0.6117 data_time: 0.5057 memory: 3269 2022/10/09 23:59:27 - mmengine - INFO - Epoch(val) [18][40/78] eta: 0:00:15 time: 0.4195 data_time: 0.3150 memory: 3269 2022/10/09 23:59:39 - mmengine - INFO - Epoch(val) [18][60/78] eta: 0:00:10 time: 0.5639 data_time: 0.4593 memory: 3269 2022/10/09 23:59:48 - mmengine - INFO - Epoch(val) [18][78/78] acc/top1: 0.6214 acc/top5: 0.8417 acc/mean1: 0.6212 2022/10/10 00:00:02 - mmengine - INFO - Epoch(train) [19][20/940] lr: 1.0000e-02 eta: 10:51:39 time: 0.7175 data_time: 0.2846 memory: 21547 grad_norm: 3.7136 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7263 loss: 1.7263 2022/10/10 00:00:12 - mmengine - INFO - Epoch(train) [19][40/940] lr: 1.0000e-02 eta: 10:51:28 time: 0.4975 data_time: 0.1017 memory: 21547 grad_norm: 3.7390 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.7516 loss: 1.7516 2022/10/10 00:00:22 - mmengine - INFO - Epoch(train) [19][60/940] lr: 1.0000e-02 eta: 10:51:18 time: 0.5120 data_time: 0.1369 memory: 21547 grad_norm: 3.7470 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6540 loss: 1.6540 2022/10/10 00:00:32 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 00:00:32 - mmengine - INFO - Epoch(train) [19][80/940] lr: 1.0000e-02 eta: 10:51:05 time: 0.4692 data_time: 0.0812 memory: 21547 grad_norm: 3.7226 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6633 loss: 1.6633 2022/10/10 00:00:43 - mmengine - INFO - Epoch(train) [19][100/940] lr: 1.0000e-02 eta: 10:50:58 time: 0.5490 data_time: 0.0580 memory: 21547 grad_norm: 3.7700 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8702 loss: 1.8702 2022/10/10 00:00:52 - mmengine - INFO - Epoch(train) [19][120/940] lr: 1.0000e-02 eta: 10:50:45 time: 0.4770 data_time: 0.0275 memory: 21547 grad_norm: 3.7303 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.6406 loss: 1.6406 2022/10/10 00:01:03 - mmengine - INFO - Epoch(train) [19][140/940] lr: 1.0000e-02 eta: 10:50:38 time: 0.5340 data_time: 0.0278 memory: 21547 grad_norm: 3.8707 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7836 loss: 1.7836 2022/10/10 00:01:12 - mmengine - INFO - Epoch(train) [19][160/940] lr: 1.0000e-02 eta: 10:50:24 time: 0.4729 data_time: 0.0244 memory: 21547 grad_norm: 3.8047 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.7848 loss: 1.7848 2022/10/10 00:01:22 - mmengine - INFO - Epoch(train) [19][180/940] lr: 1.0000e-02 eta: 10:50:14 time: 0.5041 data_time: 0.0344 memory: 21547 grad_norm: 3.8090 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.6750 loss: 1.6750 2022/10/10 00:01:33 - mmengine - INFO - Epoch(train) [19][200/940] lr: 1.0000e-02 eta: 10:50:05 time: 0.5217 data_time: 0.0268 memory: 21547 grad_norm: 3.8412 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.8183 loss: 1.8183 2022/10/10 00:01:44 - mmengine - INFO - Epoch(train) [19][220/940] lr: 1.0000e-02 eta: 10:49:57 time: 0.5326 data_time: 0.0292 memory: 21547 grad_norm: 3.6901 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7847 loss: 1.7847 2022/10/10 00:01:53 - mmengine - INFO - Epoch(train) [19][240/940] lr: 1.0000e-02 eta: 10:49:42 time: 0.4515 data_time: 0.0319 memory: 21547 grad_norm: 3.7690 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.8261 loss: 1.8261 2022/10/10 00:02:03 - mmengine - INFO - Epoch(train) [19][260/940] lr: 1.0000e-02 eta: 10:49:33 time: 0.5189 data_time: 0.0261 memory: 21547 grad_norm: 3.7942 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6500 loss: 1.6500 2022/10/10 00:02:12 - mmengine - INFO - Epoch(train) [19][280/940] lr: 1.0000e-02 eta: 10:49:19 time: 0.4621 data_time: 0.0287 memory: 21547 grad_norm: 3.7128 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7104 loss: 1.7104 2022/10/10 00:02:23 - mmengine - INFO - Epoch(train) [19][300/940] lr: 1.0000e-02 eta: 10:49:12 time: 0.5501 data_time: 0.0284 memory: 21547 grad_norm: 3.8380 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.9206 loss: 1.9206 2022/10/10 00:02:33 - mmengine - INFO - Epoch(train) [19][320/940] lr: 1.0000e-02 eta: 10:49:00 time: 0.4797 data_time: 0.0285 memory: 21547 grad_norm: 3.7682 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.7353 loss: 1.7353 2022/10/10 00:02:43 - mmengine - INFO - Epoch(train) [19][340/940] lr: 1.0000e-02 eta: 10:48:50 time: 0.5174 data_time: 0.0307 memory: 21547 grad_norm: 3.7825 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.7539 loss: 1.7539 2022/10/10 00:02:53 - mmengine - INFO - Epoch(train) [19][360/940] lr: 1.0000e-02 eta: 10:48:39 time: 0.4927 data_time: 0.0269 memory: 21547 grad_norm: 3.7659 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8945 loss: 1.8945 2022/10/10 00:03:03 - mmengine - INFO - Epoch(train) [19][380/940] lr: 1.0000e-02 eta: 10:48:30 time: 0.5197 data_time: 0.0319 memory: 21547 grad_norm: 3.7398 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7168 loss: 1.7168 2022/10/10 00:03:14 - mmengine - INFO - Epoch(train) [19][400/940] lr: 1.0000e-02 eta: 10:48:22 time: 0.5268 data_time: 0.0279 memory: 21547 grad_norm: 3.8593 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5973 loss: 1.5973 2022/10/10 00:03:24 - mmengine - INFO - Epoch(train) [19][420/940] lr: 1.0000e-02 eta: 10:48:12 time: 0.5116 data_time: 0.0310 memory: 21547 grad_norm: 3.8366 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8477 loss: 1.8477 2022/10/10 00:03:34 - mmengine - INFO - Epoch(train) [19][440/940] lr: 1.0000e-02 eta: 10:47:58 time: 0.4704 data_time: 0.0285 memory: 21547 grad_norm: 3.7519 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.9483 loss: 1.9483 2022/10/10 00:03:44 - mmengine - INFO - Epoch(train) [19][460/940] lr: 1.0000e-02 eta: 10:47:49 time: 0.5167 data_time: 0.0300 memory: 21547 grad_norm: 3.7991 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8164 loss: 1.8164 2022/10/10 00:03:54 - mmengine - INFO - Epoch(train) [19][480/940] lr: 1.0000e-02 eta: 10:47:39 time: 0.5080 data_time: 0.0276 memory: 21547 grad_norm: 3.7839 top1_acc: 0.4375 top5_acc: 0.8438 loss_cls: 1.8615 loss: 1.8615 2022/10/10 00:04:05 - mmengine - INFO - Epoch(train) [19][500/940] lr: 1.0000e-02 eta: 10:47:31 time: 0.5278 data_time: 0.0266 memory: 21547 grad_norm: 3.8457 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7360 loss: 1.7360 2022/10/10 00:04:14 - mmengine - INFO - Epoch(train) [19][520/940] lr: 1.0000e-02 eta: 10:47:19 time: 0.4904 data_time: 0.0298 memory: 21547 grad_norm: 3.7764 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8769 loss: 1.8769 2022/10/10 00:04:25 - mmengine - INFO - Epoch(train) [19][540/940] lr: 1.0000e-02 eta: 10:47:09 time: 0.5113 data_time: 0.0276 memory: 21547 grad_norm: 3.8070 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6340 loss: 1.6340 2022/10/10 00:04:35 - mmengine - INFO - Epoch(train) [19][560/940] lr: 1.0000e-02 eta: 10:46:58 time: 0.4975 data_time: 0.0276 memory: 21547 grad_norm: 3.8903 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7232 loss: 1.7232 2022/10/10 00:04:45 - mmengine - INFO - Epoch(train) [19][580/940] lr: 1.0000e-02 eta: 10:46:48 time: 0.5096 data_time: 0.0283 memory: 21547 grad_norm: 3.8765 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7632 loss: 1.7632 2022/10/10 00:04:55 - mmengine - INFO - Epoch(train) [19][600/940] lr: 1.0000e-02 eta: 10:46:38 time: 0.5080 data_time: 0.0330 memory: 21547 grad_norm: 3.8273 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8355 loss: 1.8355 2022/10/10 00:05:05 - mmengine - INFO - Epoch(train) [19][620/940] lr: 1.0000e-02 eta: 10:46:25 time: 0.4776 data_time: 0.0283 memory: 21547 grad_norm: 3.8043 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.8023 loss: 1.8023 2022/10/10 00:05:14 - mmengine - INFO - Epoch(train) [19][640/940] lr: 1.0000e-02 eta: 10:46:11 time: 0.4547 data_time: 0.0273 memory: 21547 grad_norm: 3.7715 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8081 loss: 1.8081 2022/10/10 00:05:24 - mmengine - INFO - Epoch(train) [19][660/940] lr: 1.0000e-02 eta: 10:46:02 time: 0.5209 data_time: 0.0276 memory: 21547 grad_norm: 3.8445 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8887 loss: 1.8887 2022/10/10 00:05:33 - mmengine - INFO - Epoch(train) [19][680/940] lr: 1.0000e-02 eta: 10:45:48 time: 0.4598 data_time: 0.0303 memory: 21547 grad_norm: 3.8721 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.8769 loss: 1.8769 2022/10/10 00:05:44 - mmengine - INFO - Epoch(train) [19][700/940] lr: 1.0000e-02 eta: 10:45:39 time: 0.5235 data_time: 0.0299 memory: 21547 grad_norm: 3.7665 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9208 loss: 1.9208 2022/10/10 00:05:54 - mmengine - INFO - Epoch(train) [19][720/940] lr: 1.0000e-02 eta: 10:45:29 time: 0.5129 data_time: 0.0271 memory: 21547 grad_norm: 3.8191 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6825 loss: 1.6825 2022/10/10 00:06:04 - mmengine - INFO - Epoch(train) [19][740/940] lr: 1.0000e-02 eta: 10:45:17 time: 0.4889 data_time: 0.0274 memory: 21547 grad_norm: 3.8404 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6695 loss: 1.6695 2022/10/10 00:06:14 - mmengine - INFO - Epoch(train) [19][760/940] lr: 1.0000e-02 eta: 10:45:09 time: 0.5275 data_time: 0.0255 memory: 21547 grad_norm: 3.8356 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.8114 loss: 1.8114 2022/10/10 00:06:25 - mmengine - INFO - Epoch(train) [19][780/940] lr: 1.0000e-02 eta: 10:45:00 time: 0.5210 data_time: 0.0272 memory: 21547 grad_norm: 3.8935 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9053 loss: 1.9053 2022/10/10 00:06:35 - mmengine - INFO - Epoch(train) [19][800/940] lr: 1.0000e-02 eta: 10:44:50 time: 0.5088 data_time: 0.0288 memory: 21547 grad_norm: 3.8057 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7885 loss: 1.7885 2022/10/10 00:06:44 - mmengine - INFO - Epoch(train) [19][820/940] lr: 1.0000e-02 eta: 10:44:36 time: 0.4601 data_time: 0.0273 memory: 21547 grad_norm: 3.8278 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8010 loss: 1.8010 2022/10/10 00:06:55 - mmengine - INFO - Epoch(train) [19][840/940] lr: 1.0000e-02 eta: 10:44:28 time: 0.5383 data_time: 0.0337 memory: 21547 grad_norm: 3.8523 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9150 loss: 1.9150 2022/10/10 00:07:04 - mmengine - INFO - Epoch(train) [19][860/940] lr: 1.0000e-02 eta: 10:44:15 time: 0.4709 data_time: 0.0237 memory: 21547 grad_norm: 3.8034 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.8422 loss: 1.8422 2022/10/10 00:07:15 - mmengine - INFO - Epoch(train) [19][880/940] lr: 1.0000e-02 eta: 10:44:06 time: 0.5153 data_time: 0.0310 memory: 21547 grad_norm: 3.7546 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6769 loss: 1.6769 2022/10/10 00:07:24 - mmengine - INFO - Epoch(train) [19][900/940] lr: 1.0000e-02 eta: 10:43:53 time: 0.4744 data_time: 0.0288 memory: 21547 grad_norm: 3.8722 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 1.9929 loss: 1.9929 2022/10/10 00:07:35 - mmengine - INFO - Epoch(train) [19][920/940] lr: 1.0000e-02 eta: 10:43:47 time: 0.5580 data_time: 0.0334 memory: 21547 grad_norm: 3.8104 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.7611 loss: 1.7611 2022/10/10 00:07:45 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 00:07:45 - mmengine - INFO - Epoch(train) [19][940/940] lr: 1.0000e-02 eta: 10:43:36 time: 0.4959 data_time: 0.0240 memory: 21547 grad_norm: 4.0619 top1_acc: 0.1429 top5_acc: 0.5714 loss_cls: 1.9492 loss: 1.9492 2022/10/10 00:07:57 - mmengine - INFO - Epoch(val) [19][20/78] eta: 0:00:35 time: 0.6083 data_time: 0.4993 memory: 3269 2022/10/10 00:08:06 - mmengine - INFO - Epoch(val) [19][40/78] eta: 0:00:15 time: 0.4200 data_time: 0.3122 memory: 3269 2022/10/10 00:08:17 - mmengine - INFO - Epoch(val) [19][60/78] eta: 0:00:10 time: 0.5625 data_time: 0.4559 memory: 3269 2022/10/10 00:08:27 - mmengine - INFO - Epoch(val) [19][78/78] acc/top1: 0.6290 acc/top5: 0.8465 acc/mean1: 0.6289 2022/10/10 00:08:27 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_16.pth is removed 2022/10/10 00:08:28 - mmengine - INFO - The best checkpoint with 0.6290 acc/top1 at 19 epoch is saved to best_acc/top1_epoch_19.pth. 2022/10/10 00:08:41 - mmengine - INFO - Epoch(train) [20][20/940] lr: 1.0000e-02 eta: 10:43:40 time: 0.6712 data_time: 0.1803 memory: 21547 grad_norm: 3.6977 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6483 loss: 1.6483 2022/10/10 00:08:51 - mmengine - INFO - Epoch(train) [20][40/940] lr: 1.0000e-02 eta: 10:43:28 time: 0.4858 data_time: 0.0270 memory: 21547 grad_norm: 3.7794 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8057 loss: 1.8057 2022/10/10 00:09:02 - mmengine - INFO - Epoch(train) [20][60/940] lr: 1.0000e-02 eta: 10:43:20 time: 0.5311 data_time: 0.0344 memory: 21547 grad_norm: 3.7968 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6615 loss: 1.6615 2022/10/10 00:09:12 - mmengine - INFO - Epoch(train) [20][80/940] lr: 1.0000e-02 eta: 10:43:10 time: 0.5088 data_time: 0.0250 memory: 21547 grad_norm: 3.7559 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.8427 loss: 1.8427 2022/10/10 00:09:22 - mmengine - INFO - Epoch(train) [20][100/940] lr: 1.0000e-02 eta: 10:43:01 time: 0.5297 data_time: 0.0315 memory: 21547 grad_norm: 3.8776 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.8384 loss: 1.8384 2022/10/10 00:09:32 - mmengine - INFO - Epoch(train) [20][120/940] lr: 1.0000e-02 eta: 10:42:50 time: 0.4969 data_time: 0.0295 memory: 21547 grad_norm: 3.8161 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.7046 loss: 1.7046 2022/10/10 00:09:42 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 00:09:42 - mmengine - INFO - Epoch(train) [20][140/940] lr: 1.0000e-02 eta: 10:42:39 time: 0.4899 data_time: 0.0308 memory: 21547 grad_norm: 3.8007 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6806 loss: 1.6806 2022/10/10 00:09:53 - mmengine - INFO - Epoch(train) [20][160/940] lr: 1.0000e-02 eta: 10:42:30 time: 0.5261 data_time: 0.0314 memory: 21547 grad_norm: 3.8284 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.7346 loss: 1.7346 2022/10/10 00:10:02 - mmengine - INFO - Epoch(train) [20][180/940] lr: 1.0000e-02 eta: 10:42:17 time: 0.4768 data_time: 0.0305 memory: 21547 grad_norm: 3.8145 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7749 loss: 1.7749 2022/10/10 00:10:12 - mmengine - INFO - Epoch(train) [20][200/940] lr: 1.0000e-02 eta: 10:42:05 time: 0.4854 data_time: 0.0269 memory: 21547 grad_norm: 3.7706 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7476 loss: 1.7476 2022/10/10 00:10:23 - mmengine - INFO - Epoch(train) [20][220/940] lr: 1.0000e-02 eta: 10:42:01 time: 0.5753 data_time: 0.0278 memory: 21547 grad_norm: 3.8203 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.6967 loss: 1.6967 2022/10/10 00:10:33 - mmengine - INFO - Epoch(train) [20][240/940] lr: 1.0000e-02 eta: 10:41:48 time: 0.4764 data_time: 0.0273 memory: 21547 grad_norm: 3.8737 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.9574 loss: 1.9574 2022/10/10 00:10:43 - mmengine - INFO - Epoch(train) [20][260/940] lr: 1.0000e-02 eta: 10:41:36 time: 0.4884 data_time: 0.0346 memory: 21547 grad_norm: 3.7291 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7781 loss: 1.7781 2022/10/10 00:10:52 - mmengine - INFO - Epoch(train) [20][280/940] lr: 1.0000e-02 eta: 10:41:24 time: 0.4806 data_time: 0.0331 memory: 21547 grad_norm: 3.7658 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.6879 loss: 1.6879 2022/10/10 00:11:03 - mmengine - INFO - Epoch(train) [20][300/940] lr: 1.0000e-02 eta: 10:41:17 time: 0.5394 data_time: 0.0453 memory: 21547 grad_norm: 3.7717 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8262 loss: 1.8262 2022/10/10 00:11:13 - mmengine - INFO - Epoch(train) [20][320/940] lr: 1.0000e-02 eta: 10:41:04 time: 0.4761 data_time: 0.0279 memory: 21547 grad_norm: 3.8858 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.8744 loss: 1.8744 2022/10/10 00:11:25 - mmengine - INFO - Epoch(train) [20][340/940] lr: 1.0000e-02 eta: 10:41:01 time: 0.6001 data_time: 0.0293 memory: 21547 grad_norm: 3.8014 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8305 loss: 1.8305 2022/10/10 00:11:34 - mmengine - INFO - Epoch(train) [20][360/940] lr: 1.0000e-02 eta: 10:40:47 time: 0.4610 data_time: 0.0245 memory: 21547 grad_norm: 3.8462 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8043 loss: 1.8043 2022/10/10 00:11:44 - mmengine - INFO - Epoch(train) [20][380/940] lr: 1.0000e-02 eta: 10:40:37 time: 0.5100 data_time: 0.0328 memory: 21547 grad_norm: 3.7741 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7213 loss: 1.7213 2022/10/10 00:11:54 - mmengine - INFO - Epoch(train) [20][400/940] lr: 1.0000e-02 eta: 10:40:24 time: 0.4704 data_time: 0.0251 memory: 21547 grad_norm: 3.7550 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8286 loss: 1.8286 2022/10/10 00:12:04 - mmengine - INFO - Epoch(train) [20][420/940] lr: 1.0000e-02 eta: 10:40:15 time: 0.5160 data_time: 0.0845 memory: 21547 grad_norm: 3.8183 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7315 loss: 1.7315 2022/10/10 00:12:13 - mmengine - INFO - Epoch(train) [20][440/940] lr: 1.0000e-02 eta: 10:40:01 time: 0.4637 data_time: 0.0691 memory: 21547 grad_norm: 3.7157 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6278 loss: 1.6278 2022/10/10 00:12:24 - mmengine - INFO - Epoch(train) [20][460/940] lr: 1.0000e-02 eta: 10:39:52 time: 0.5257 data_time: 0.0557 memory: 21547 grad_norm: 3.7757 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 1.8281 loss: 1.8281 2022/10/10 00:12:34 - mmengine - INFO - Epoch(train) [20][480/940] lr: 1.0000e-02 eta: 10:39:41 time: 0.4971 data_time: 0.0292 memory: 21547 grad_norm: 3.7816 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7655 loss: 1.7655 2022/10/10 00:12:44 - mmengine - INFO - Epoch(train) [20][500/940] lr: 1.0000e-02 eta: 10:39:33 time: 0.5254 data_time: 0.0312 memory: 21547 grad_norm: 3.8757 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6434 loss: 1.6434 2022/10/10 00:12:54 - mmengine - INFO - Epoch(train) [20][520/940] lr: 1.0000e-02 eta: 10:39:21 time: 0.4862 data_time: 0.0265 memory: 21547 grad_norm: 3.8059 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8925 loss: 1.8925 2022/10/10 00:13:05 - mmengine - INFO - Epoch(train) [20][540/940] lr: 1.0000e-02 eta: 10:39:13 time: 0.5399 data_time: 0.0297 memory: 21547 grad_norm: 3.8628 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9234 loss: 1.9234 2022/10/10 00:13:14 - mmengine - INFO - Epoch(train) [20][560/940] lr: 1.0000e-02 eta: 10:38:58 time: 0.4444 data_time: 0.0283 memory: 21547 grad_norm: 3.7448 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8164 loss: 1.8164 2022/10/10 00:13:23 - mmengine - INFO - Epoch(train) [20][580/940] lr: 1.0000e-02 eta: 10:38:47 time: 0.4929 data_time: 0.0275 memory: 21547 grad_norm: 3.8265 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8402 loss: 1.8402 2022/10/10 00:13:34 - mmengine - INFO - Epoch(train) [20][600/940] lr: 1.0000e-02 eta: 10:38:38 time: 0.5211 data_time: 0.0611 memory: 21547 grad_norm: 3.7666 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6527 loss: 1.6527 2022/10/10 00:13:44 - mmengine - INFO - Epoch(train) [20][620/940] lr: 1.0000e-02 eta: 10:38:28 time: 0.5111 data_time: 0.0306 memory: 21547 grad_norm: 3.7827 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.6843 loss: 1.6843 2022/10/10 00:13:54 - mmengine - INFO - Epoch(train) [20][640/940] lr: 1.0000e-02 eta: 10:38:17 time: 0.4918 data_time: 0.0270 memory: 21547 grad_norm: 3.8663 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6767 loss: 1.6767 2022/10/10 00:14:03 - mmengine - INFO - Epoch(train) [20][660/940] lr: 1.0000e-02 eta: 10:38:03 time: 0.4616 data_time: 0.0312 memory: 21547 grad_norm: 3.8279 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8590 loss: 1.8590 2022/10/10 00:14:13 - mmengine - INFO - Epoch(train) [20][680/940] lr: 1.0000e-02 eta: 10:37:53 time: 0.5177 data_time: 0.0314 memory: 21547 grad_norm: 3.8195 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8509 loss: 1.8509 2022/10/10 00:14:23 - mmengine - INFO - Epoch(train) [20][700/940] lr: 1.0000e-02 eta: 10:37:41 time: 0.4784 data_time: 0.0260 memory: 21547 grad_norm: 3.8118 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.7963 loss: 1.7963 2022/10/10 00:14:33 - mmengine - INFO - Epoch(train) [20][720/940] lr: 1.0000e-02 eta: 10:37:31 time: 0.5065 data_time: 0.0302 memory: 21547 grad_norm: 3.7273 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7395 loss: 1.7395 2022/10/10 00:14:44 - mmengine - INFO - Epoch(train) [20][740/940] lr: 1.0000e-02 eta: 10:37:22 time: 0.5210 data_time: 0.0278 memory: 21547 grad_norm: 3.8376 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8386 loss: 1.8386 2022/10/10 00:14:54 - mmengine - INFO - Epoch(train) [20][760/940] lr: 1.0000e-02 eta: 10:37:12 time: 0.5109 data_time: 0.0318 memory: 21547 grad_norm: 3.8200 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6698 loss: 1.6698 2022/10/10 00:15:03 - mmengine - INFO - Epoch(train) [20][780/940] lr: 1.0000e-02 eta: 10:36:59 time: 0.4794 data_time: 0.0299 memory: 21547 grad_norm: 3.8516 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8152 loss: 1.8152 2022/10/10 00:15:14 - mmengine - INFO - Epoch(train) [20][800/940] lr: 1.0000e-02 eta: 10:36:50 time: 0.5188 data_time: 0.0307 memory: 21547 grad_norm: 3.7396 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8465 loss: 1.8465 2022/10/10 00:15:23 - mmengine - INFO - Epoch(train) [20][820/940] lr: 1.0000e-02 eta: 10:36:36 time: 0.4541 data_time: 0.0286 memory: 21547 grad_norm: 3.8900 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.7896 loss: 1.7896 2022/10/10 00:15:34 - mmengine - INFO - Epoch(train) [20][840/940] lr: 1.0000e-02 eta: 10:36:28 time: 0.5415 data_time: 0.0254 memory: 21547 grad_norm: 3.8207 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6128 loss: 1.6128 2022/10/10 00:15:44 - mmengine - INFO - Epoch(train) [20][860/940] lr: 1.0000e-02 eta: 10:36:19 time: 0.5175 data_time: 0.0279 memory: 21547 grad_norm: 3.8642 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8799 loss: 1.8799 2022/10/10 00:15:53 - mmengine - INFO - Epoch(train) [20][880/940] lr: 1.0000e-02 eta: 10:36:06 time: 0.4747 data_time: 0.0347 memory: 21547 grad_norm: 3.7884 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7492 loss: 1.7492 2022/10/10 00:16:05 - mmengine - INFO - Epoch(train) [20][900/940] lr: 1.0000e-02 eta: 10:36:01 time: 0.5704 data_time: 0.0275 memory: 21547 grad_norm: 3.8626 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8430 loss: 1.8430 2022/10/10 00:16:14 - mmengine - INFO - Epoch(train) [20][920/940] lr: 1.0000e-02 eta: 10:35:46 time: 0.4483 data_time: 0.0271 memory: 21547 grad_norm: 3.7491 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7614 loss: 1.7614 2022/10/10 00:16:24 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 00:16:24 - mmengine - INFO - Epoch(train) [20][940/940] lr: 1.0000e-02 eta: 10:35:35 time: 0.4921 data_time: 0.0207 memory: 21547 grad_norm: 4.0606 top1_acc: 0.5714 top5_acc: 1.0000 loss_cls: 1.8080 loss: 1.8080 2022/10/10 00:16:36 - mmengine - INFO - Epoch(val) [20][20/78] eta: 0:00:35 time: 0.6060 data_time: 0.4955 memory: 3269 2022/10/10 00:16:44 - mmengine - INFO - Epoch(val) [20][40/78] eta: 0:00:16 time: 0.4255 data_time: 0.3165 memory: 3269 2022/10/10 00:16:56 - mmengine - INFO - Epoch(val) [20][60/78] eta: 0:00:10 time: 0.5753 data_time: 0.4668 memory: 3269 2022/10/10 00:17:05 - mmengine - INFO - Epoch(val) [20][78/78] acc/top1: 0.6277 acc/top5: 0.8429 acc/mean1: 0.6276 2022/10/10 00:17:20 - mmengine - INFO - Epoch(train) [21][20/940] lr: 1.0000e-02 eta: 10:35:42 time: 0.7142 data_time: 0.2947 memory: 21547 grad_norm: 3.7918 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6630 loss: 1.6630 2022/10/10 00:17:30 - mmengine - INFO - Epoch(train) [21][40/940] lr: 1.0000e-02 eta: 10:35:32 time: 0.5167 data_time: 0.0776 memory: 21547 grad_norm: 3.7632 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7371 loss: 1.7371 2022/10/10 00:17:40 - mmengine - INFO - Epoch(train) [21][60/940] lr: 1.0000e-02 eta: 10:35:22 time: 0.5127 data_time: 0.0722 memory: 21547 grad_norm: 3.8367 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7806 loss: 1.7806 2022/10/10 00:17:50 - mmengine - INFO - Epoch(train) [21][80/940] lr: 1.0000e-02 eta: 10:35:09 time: 0.4717 data_time: 0.0980 memory: 21547 grad_norm: 3.8576 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.8524 loss: 1.8524 2022/10/10 00:18:01 - mmengine - INFO - Epoch(train) [21][100/940] lr: 1.0000e-02 eta: 10:35:03 time: 0.5525 data_time: 0.1819 memory: 21547 grad_norm: 3.8783 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7602 loss: 1.7602 2022/10/10 00:18:11 - mmengine - INFO - Epoch(train) [21][120/940] lr: 1.0000e-02 eta: 10:34:51 time: 0.4908 data_time: 0.1208 memory: 21547 grad_norm: 3.7704 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6001 loss: 1.6001 2022/10/10 00:18:21 - mmengine - INFO - Epoch(train) [21][140/940] lr: 1.0000e-02 eta: 10:34:44 time: 0.5414 data_time: 0.1653 memory: 21547 grad_norm: 3.8530 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7423 loss: 1.7423 2022/10/10 00:18:31 - mmengine - INFO - Epoch(train) [21][160/940] lr: 1.0000e-02 eta: 10:34:31 time: 0.4676 data_time: 0.0865 memory: 21547 grad_norm: 3.8131 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7202 loss: 1.7202 2022/10/10 00:18:41 - mmengine - INFO - Epoch(train) [21][180/940] lr: 1.0000e-02 eta: 10:34:21 time: 0.5139 data_time: 0.1295 memory: 21547 grad_norm: 3.8687 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6303 loss: 1.6303 2022/10/10 00:18:51 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 00:18:51 - mmengine - INFO - Epoch(train) [21][200/940] lr: 1.0000e-02 eta: 10:34:09 time: 0.4863 data_time: 0.0259 memory: 21547 grad_norm: 3.8254 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7204 loss: 1.7204 2022/10/10 00:19:01 - mmengine - INFO - Epoch(train) [21][220/940] lr: 1.0000e-02 eta: 10:34:01 time: 0.5378 data_time: 0.0305 memory: 21547 grad_norm: 3.7252 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.7848 loss: 1.7848 2022/10/10 00:19:11 - mmengine - INFO - Epoch(train) [21][240/940] lr: 1.0000e-02 eta: 10:33:49 time: 0.4799 data_time: 0.0247 memory: 21547 grad_norm: 3.8533 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8025 loss: 1.8025 2022/10/10 00:19:21 - mmengine - INFO - Epoch(train) [21][260/940] lr: 1.0000e-02 eta: 10:33:38 time: 0.4929 data_time: 0.0269 memory: 21547 grad_norm: 3.7537 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.6665 loss: 1.6665 2022/10/10 00:19:31 - mmengine - INFO - Epoch(train) [21][280/940] lr: 1.0000e-02 eta: 10:33:27 time: 0.4915 data_time: 0.0694 memory: 21547 grad_norm: 3.7911 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7876 loss: 1.7876 2022/10/10 00:19:41 - mmengine - INFO - Epoch(train) [21][300/940] lr: 1.0000e-02 eta: 10:33:18 time: 0.5318 data_time: 0.0408 memory: 21547 grad_norm: 3.8519 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.7356 loss: 1.7356 2022/10/10 00:19:51 - mmengine - INFO - Epoch(train) [21][320/940] lr: 1.0000e-02 eta: 10:33:06 time: 0.4774 data_time: 0.0268 memory: 21547 grad_norm: 3.7951 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7695 loss: 1.7695 2022/10/10 00:20:01 - mmengine - INFO - Epoch(train) [21][340/940] lr: 1.0000e-02 eta: 10:32:55 time: 0.4949 data_time: 0.0315 memory: 21547 grad_norm: 3.8761 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7612 loss: 1.7612 2022/10/10 00:20:11 - mmengine - INFO - Epoch(train) [21][360/940] lr: 1.0000e-02 eta: 10:32:43 time: 0.4827 data_time: 0.0388 memory: 21547 grad_norm: 3.8503 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.8774 loss: 1.8774 2022/10/10 00:20:22 - mmengine - INFO - Epoch(train) [21][380/940] lr: 1.0000e-02 eta: 10:32:36 time: 0.5548 data_time: 0.0290 memory: 21547 grad_norm: 3.8350 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8247 loss: 1.8247 2022/10/10 00:20:31 - mmengine - INFO - Epoch(train) [21][400/940] lr: 1.0000e-02 eta: 10:32:25 time: 0.4935 data_time: 0.0262 memory: 21547 grad_norm: 3.8597 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7351 loss: 1.7351 2022/10/10 00:20:42 - mmengine - INFO - Epoch(train) [21][420/940] lr: 1.0000e-02 eta: 10:32:15 time: 0.5055 data_time: 0.0290 memory: 21547 grad_norm: 3.8578 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8458 loss: 1.8458 2022/10/10 00:20:52 - mmengine - INFO - Epoch(train) [21][440/940] lr: 1.0000e-02 eta: 10:32:04 time: 0.5060 data_time: 0.0817 memory: 21547 grad_norm: 3.8125 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 1.6791 loss: 1.6791 2022/10/10 00:21:02 - mmengine - INFO - Epoch(train) [21][460/940] lr: 1.0000e-02 eta: 10:31:54 time: 0.5016 data_time: 0.0323 memory: 21547 grad_norm: 3.8477 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7454 loss: 1.7454 2022/10/10 00:21:12 - mmengine - INFO - Epoch(train) [21][480/940] lr: 1.0000e-02 eta: 10:31:43 time: 0.4996 data_time: 0.0338 memory: 21547 grad_norm: 3.7973 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7165 loss: 1.7165 2022/10/10 00:21:22 - mmengine - INFO - Epoch(train) [21][500/940] lr: 1.0000e-02 eta: 10:31:32 time: 0.4990 data_time: 0.0394 memory: 21547 grad_norm: 3.8038 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.7694 loss: 1.7694 2022/10/10 00:21:32 - mmengine - INFO - Epoch(train) [21][520/940] lr: 1.0000e-02 eta: 10:31:21 time: 0.4904 data_time: 0.0235 memory: 21547 grad_norm: 3.9014 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6545 loss: 1.6545 2022/10/10 00:21:41 - mmengine - INFO - Epoch(train) [21][540/940] lr: 1.0000e-02 eta: 10:31:10 time: 0.4975 data_time: 0.0308 memory: 21547 grad_norm: 3.9189 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7917 loss: 1.7917 2022/10/10 00:21:51 - mmengine - INFO - Epoch(train) [21][560/940] lr: 1.0000e-02 eta: 10:30:59 time: 0.4965 data_time: 0.0293 memory: 21547 grad_norm: 3.8201 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7829 loss: 1.7829 2022/10/10 00:22:02 - mmengine - INFO - Epoch(train) [21][580/940] lr: 1.0000e-02 eta: 10:30:49 time: 0.5051 data_time: 0.0308 memory: 21547 grad_norm: 3.8592 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.9069 loss: 1.9069 2022/10/10 00:22:12 - mmengine - INFO - Epoch(train) [21][600/940] lr: 1.0000e-02 eta: 10:30:39 time: 0.5087 data_time: 0.0621 memory: 21547 grad_norm: 3.8410 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8379 loss: 1.8379 2022/10/10 00:22:22 - mmengine - INFO - Epoch(train) [21][620/940] lr: 1.0000e-02 eta: 10:30:28 time: 0.4983 data_time: 0.1044 memory: 21547 grad_norm: 3.8693 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8226 loss: 1.8226 2022/10/10 00:22:32 - mmengine - INFO - Epoch(train) [21][640/940] lr: 1.0000e-02 eta: 10:30:18 time: 0.5162 data_time: 0.1240 memory: 21547 grad_norm: 3.8243 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.7526 loss: 1.7526 2022/10/10 00:22:43 - mmengine - INFO - Epoch(train) [21][660/940] lr: 1.0000e-02 eta: 10:30:12 time: 0.5540 data_time: 0.1582 memory: 21547 grad_norm: 3.9556 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.7130 loss: 1.7130 2022/10/10 00:22:53 - mmengine - INFO - Epoch(train) [21][680/940] lr: 1.0000e-02 eta: 10:30:03 time: 0.5191 data_time: 0.1307 memory: 21547 grad_norm: 3.7940 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6051 loss: 1.6051 2022/10/10 00:23:04 - mmengine - INFO - Epoch(train) [21][700/940] lr: 1.0000e-02 eta: 10:29:53 time: 0.5086 data_time: 0.1300 memory: 21547 grad_norm: 3.7843 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7314 loss: 1.7314 2022/10/10 00:23:13 - mmengine - INFO - Epoch(train) [21][720/940] lr: 1.0000e-02 eta: 10:29:39 time: 0.4592 data_time: 0.0720 memory: 21547 grad_norm: 3.9927 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.7969 loss: 1.7969 2022/10/10 00:23:24 - mmengine - INFO - Epoch(train) [21][740/940] lr: 1.0000e-02 eta: 10:29:31 time: 0.5385 data_time: 0.1465 memory: 21547 grad_norm: 3.8601 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6753 loss: 1.6753 2022/10/10 00:23:33 - mmengine - INFO - Epoch(train) [21][760/940] lr: 1.0000e-02 eta: 10:29:17 time: 0.4536 data_time: 0.0739 memory: 21547 grad_norm: 3.8876 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6246 loss: 1.6246 2022/10/10 00:23:43 - mmengine - INFO - Epoch(train) [21][780/940] lr: 1.0000e-02 eta: 10:29:07 time: 0.5106 data_time: 0.1011 memory: 21547 grad_norm: 3.9495 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7744 loss: 1.7744 2022/10/10 00:23:53 - mmengine - INFO - Epoch(train) [21][800/940] lr: 1.0000e-02 eta: 10:28:56 time: 0.5008 data_time: 0.0418 memory: 21547 grad_norm: 3.8623 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.7245 loss: 1.7245 2022/10/10 00:24:04 - mmengine - INFO - Epoch(train) [21][820/940] lr: 1.0000e-02 eta: 10:28:50 time: 0.5636 data_time: 0.0278 memory: 21547 grad_norm: 3.9331 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8546 loss: 1.8546 2022/10/10 00:24:14 - mmengine - INFO - Epoch(train) [21][840/940] lr: 1.0000e-02 eta: 10:28:38 time: 0.4804 data_time: 0.0264 memory: 21547 grad_norm: 3.8593 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6864 loss: 1.6864 2022/10/10 00:24:24 - mmengine - INFO - Epoch(train) [21][860/940] lr: 1.0000e-02 eta: 10:28:30 time: 0.5293 data_time: 0.0282 memory: 21547 grad_norm: 3.8919 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7892 loss: 1.7892 2022/10/10 00:24:34 - mmengine - INFO - Epoch(train) [21][880/940] lr: 1.0000e-02 eta: 10:28:17 time: 0.4716 data_time: 0.0294 memory: 21547 grad_norm: 3.9553 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8169 loss: 1.8169 2022/10/10 00:24:45 - mmengine - INFO - Epoch(train) [21][900/940] lr: 1.0000e-02 eta: 10:28:12 time: 0.5733 data_time: 0.0282 memory: 21547 grad_norm: 3.8626 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6779 loss: 1.6779 2022/10/10 00:24:55 - mmengine - INFO - Epoch(train) [21][920/940] lr: 1.0000e-02 eta: 10:27:58 time: 0.4631 data_time: 0.0265 memory: 21547 grad_norm: 3.8535 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.8291 loss: 1.8291 2022/10/10 00:25:03 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 00:25:03 - mmengine - INFO - Epoch(train) [21][940/940] lr: 1.0000e-02 eta: 10:27:43 time: 0.4433 data_time: 0.0215 memory: 21547 grad_norm: 4.0014 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.6959 loss: 1.6959 2022/10/10 00:25:03 - mmengine - INFO - Saving checkpoint at 21 epochs 2022/10/10 00:25:16 - mmengine - INFO - Epoch(val) [21][20/78] eta: 0:00:35 time: 0.6088 data_time: 0.5029 memory: 3269 2022/10/10 00:25:25 - mmengine - INFO - Epoch(val) [21][40/78] eta: 0:00:16 time: 0.4227 data_time: 0.3189 memory: 3269 2022/10/10 00:25:36 - mmengine - INFO - Epoch(val) [21][60/78] eta: 0:00:10 time: 0.5588 data_time: 0.4510 memory: 3269 2022/10/10 00:25:45 - mmengine - INFO - Epoch(val) [21][78/78] acc/top1: 0.6322 acc/top5: 0.8441 acc/mean1: 0.6321 2022/10/10 00:25:45 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_19.pth is removed 2022/10/10 00:25:46 - mmengine - INFO - The best checkpoint with 0.6322 acc/top1 at 21 epoch is saved to best_acc/top1_epoch_21.pth. 2022/10/10 00:25:59 - mmengine - INFO - Epoch(train) [22][20/940] lr: 1.0000e-02 eta: 10:27:46 time: 0.6745 data_time: 0.3063 memory: 21547 grad_norm: 3.7855 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.6880 loss: 1.6880 2022/10/10 00:26:10 - mmengine - INFO - Epoch(train) [22][40/940] lr: 1.0000e-02 eta: 10:27:36 time: 0.5184 data_time: 0.1118 memory: 21547 grad_norm: 3.8666 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6317 loss: 1.6317 2022/10/10 00:26:20 - mmengine - INFO - Epoch(train) [22][60/940] lr: 1.0000e-02 eta: 10:27:28 time: 0.5333 data_time: 0.0811 memory: 21547 grad_norm: 3.8620 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.6151 loss: 1.6151 2022/10/10 00:26:30 - mmengine - INFO - Epoch(train) [22][80/940] lr: 1.0000e-02 eta: 10:27:16 time: 0.4773 data_time: 0.0669 memory: 21547 grad_norm: 3.7579 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.6827 loss: 1.6827 2022/10/10 00:26:41 - mmengine - INFO - Epoch(train) [22][100/940] lr: 1.0000e-02 eta: 10:27:08 time: 0.5401 data_time: 0.0462 memory: 21547 grad_norm: 3.8173 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.6971 loss: 1.6971 2022/10/10 00:26:51 - mmengine - INFO - Epoch(train) [22][120/940] lr: 1.0000e-02 eta: 10:26:57 time: 0.4968 data_time: 0.0297 memory: 21547 grad_norm: 3.9040 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7414 loss: 1.7414 2022/10/10 00:27:01 - mmengine - INFO - Epoch(train) [22][140/940] lr: 1.0000e-02 eta: 10:26:49 time: 0.5370 data_time: 0.0275 memory: 21547 grad_norm: 3.8854 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7565 loss: 1.7565 2022/10/10 00:27:11 - mmengine - INFO - Epoch(train) [22][160/940] lr: 1.0000e-02 eta: 10:26:36 time: 0.4643 data_time: 0.0254 memory: 21547 grad_norm: 3.8515 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.6410 loss: 1.6410 2022/10/10 00:27:22 - mmengine - INFO - Epoch(train) [22][180/940] lr: 1.0000e-02 eta: 10:26:29 time: 0.5467 data_time: 0.0260 memory: 21547 grad_norm: 3.8953 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7297 loss: 1.7297 2022/10/10 00:27:32 - mmengine - INFO - Epoch(train) [22][200/940] lr: 1.0000e-02 eta: 10:26:18 time: 0.5049 data_time: 0.0224 memory: 21547 grad_norm: 3.7889 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8272 loss: 1.8272 2022/10/10 00:27:42 - mmengine - INFO - Epoch(train) [22][220/940] lr: 1.0000e-02 eta: 10:26:09 time: 0.5263 data_time: 0.0256 memory: 21547 grad_norm: 3.8573 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6997 loss: 1.6997 2022/10/10 00:27:52 - mmengine - INFO - Epoch(train) [22][240/940] lr: 1.0000e-02 eta: 10:25:59 time: 0.4982 data_time: 0.0269 memory: 21547 grad_norm: 3.9076 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5903 loss: 1.5903 2022/10/10 00:28:03 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 00:28:03 - mmengine - INFO - Epoch(train) [22][260/940] lr: 1.0000e-02 eta: 10:25:50 time: 0.5296 data_time: 0.0263 memory: 21547 grad_norm: 3.9192 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7101 loss: 1.7101 2022/10/10 00:28:12 - mmengine - INFO - Epoch(train) [22][280/940] lr: 1.0000e-02 eta: 10:25:36 time: 0.4475 data_time: 0.0278 memory: 21547 grad_norm: 3.9709 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8386 loss: 1.8386 2022/10/10 00:28:22 - mmengine - INFO - Epoch(train) [22][300/940] lr: 1.0000e-02 eta: 10:25:25 time: 0.5036 data_time: 0.0304 memory: 21547 grad_norm: 3.8752 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6717 loss: 1.6717 2022/10/10 00:28:32 - mmengine - INFO - Epoch(train) [22][320/940] lr: 1.0000e-02 eta: 10:25:16 time: 0.5141 data_time: 0.0215 memory: 21547 grad_norm: 3.8597 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 1.7772 loss: 1.7772 2022/10/10 00:28:43 - mmengine - INFO - Epoch(train) [22][340/940] lr: 1.0000e-02 eta: 10:25:07 time: 0.5274 data_time: 0.0308 memory: 21547 grad_norm: 3.8927 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6742 loss: 1.6742 2022/10/10 00:28:52 - mmengine - INFO - Epoch(train) [22][360/940] lr: 1.0000e-02 eta: 10:24:55 time: 0.4792 data_time: 0.0259 memory: 21547 grad_norm: 3.8097 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7418 loss: 1.7418 2022/10/10 00:29:03 - mmengine - INFO - Epoch(train) [22][380/940] lr: 1.0000e-02 eta: 10:24:47 time: 0.5380 data_time: 0.0319 memory: 21547 grad_norm: 3.7926 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6427 loss: 1.6427 2022/10/10 00:29:12 - mmengine - INFO - Epoch(train) [22][400/940] lr: 1.0000e-02 eta: 10:24:34 time: 0.4729 data_time: 0.0339 memory: 21547 grad_norm: 3.8648 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5362 loss: 1.5362 2022/10/10 00:29:23 - mmengine - INFO - Epoch(train) [22][420/940] lr: 1.0000e-02 eta: 10:24:26 time: 0.5415 data_time: 0.0233 memory: 21547 grad_norm: 3.8617 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.6352 loss: 1.6352 2022/10/10 00:29:33 - mmengine - INFO - Epoch(train) [22][440/940] lr: 1.0000e-02 eta: 10:24:16 time: 0.5034 data_time: 0.0242 memory: 21547 grad_norm: 3.8708 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6754 loss: 1.6754 2022/10/10 00:29:44 - mmengine - INFO - Epoch(train) [22][460/940] lr: 1.0000e-02 eta: 10:24:06 time: 0.5160 data_time: 0.0254 memory: 21547 grad_norm: 3.8268 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7175 loss: 1.7175 2022/10/10 00:29:54 - mmengine - INFO - Epoch(train) [22][480/940] lr: 1.0000e-02 eta: 10:23:56 time: 0.5010 data_time: 0.0258 memory: 21547 grad_norm: 3.8394 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.6536 loss: 1.6536 2022/10/10 00:30:04 - mmengine - INFO - Epoch(train) [22][500/940] lr: 1.0000e-02 eta: 10:23:46 time: 0.5177 data_time: 0.0295 memory: 21547 grad_norm: 3.8544 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.7574 loss: 1.7574 2022/10/10 00:30:14 - mmengine - INFO - Epoch(train) [22][520/940] lr: 1.0000e-02 eta: 10:23:36 time: 0.5004 data_time: 0.0243 memory: 21547 grad_norm: 3.8706 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8349 loss: 1.8349 2022/10/10 00:30:24 - mmengine - INFO - Epoch(train) [22][540/940] lr: 1.0000e-02 eta: 10:23:24 time: 0.4881 data_time: 0.0288 memory: 21547 grad_norm: 3.8729 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6373 loss: 1.6373 2022/10/10 00:30:35 - mmengine - INFO - Epoch(train) [22][560/940] lr: 1.0000e-02 eta: 10:23:16 time: 0.5354 data_time: 0.0262 memory: 21547 grad_norm: 3.8820 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7086 loss: 1.7086 2022/10/10 00:30:46 - mmengine - INFO - Epoch(train) [22][580/940] lr: 1.0000e-02 eta: 10:23:09 time: 0.5516 data_time: 0.0273 memory: 21547 grad_norm: 3.8795 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7876 loss: 1.7876 2022/10/10 00:30:55 - mmengine - INFO - Epoch(train) [22][600/940] lr: 1.0000e-02 eta: 10:22:56 time: 0.4643 data_time: 0.0223 memory: 21547 grad_norm: 3.8073 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.8384 loss: 1.8384 2022/10/10 00:31:05 - mmengine - INFO - Epoch(train) [22][620/940] lr: 1.0000e-02 eta: 10:22:46 time: 0.5066 data_time: 0.0266 memory: 21547 grad_norm: 3.8368 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.8603 loss: 1.8603 2022/10/10 00:31:14 - mmengine - INFO - Epoch(train) [22][640/940] lr: 1.0000e-02 eta: 10:22:32 time: 0.4654 data_time: 0.0346 memory: 21547 grad_norm: 3.8465 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5844 loss: 1.5844 2022/10/10 00:31:24 - mmengine - INFO - Epoch(train) [22][660/940] lr: 1.0000e-02 eta: 10:22:22 time: 0.5043 data_time: 0.0252 memory: 21547 grad_norm: 3.8246 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7748 loss: 1.7748 2022/10/10 00:31:34 - mmengine - INFO - Epoch(train) [22][680/940] lr: 1.0000e-02 eta: 10:22:09 time: 0.4625 data_time: 0.0272 memory: 21547 grad_norm: 3.8789 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7698 loss: 1.7698 2022/10/10 00:31:44 - mmengine - INFO - Epoch(train) [22][700/940] lr: 1.0000e-02 eta: 10:21:59 time: 0.5171 data_time: 0.0288 memory: 21547 grad_norm: 3.8959 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.6498 loss: 1.6498 2022/10/10 00:31:54 - mmengine - INFO - Epoch(train) [22][720/940] lr: 1.0000e-02 eta: 10:21:49 time: 0.5037 data_time: 0.0339 memory: 21547 grad_norm: 3.8763 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.7074 loss: 1.7074 2022/10/10 00:32:04 - mmengine - INFO - Epoch(train) [22][740/940] lr: 1.0000e-02 eta: 10:21:38 time: 0.4997 data_time: 0.0306 memory: 21547 grad_norm: 3.8753 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.9021 loss: 1.9021 2022/10/10 00:32:15 - mmengine - INFO - Epoch(train) [22][760/940] lr: 1.0000e-02 eta: 10:21:30 time: 0.5349 data_time: 0.0353 memory: 21547 grad_norm: 3.8722 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.7629 loss: 1.7629 2022/10/10 00:32:24 - mmengine - INFO - Epoch(train) [22][780/940] lr: 1.0000e-02 eta: 10:21:18 time: 0.4848 data_time: 0.0288 memory: 21547 grad_norm: 3.9453 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9009 loss: 1.9009 2022/10/10 00:32:35 - mmengine - INFO - Epoch(train) [22][800/940] lr: 1.0000e-02 eta: 10:21:11 time: 0.5414 data_time: 0.0262 memory: 21547 grad_norm: 3.8468 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7083 loss: 1.7083 2022/10/10 00:32:44 - mmengine - INFO - Epoch(train) [22][820/940] lr: 1.0000e-02 eta: 10:20:56 time: 0.4526 data_time: 0.0281 memory: 21547 grad_norm: 3.8384 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5946 loss: 1.5946 2022/10/10 00:32:54 - mmengine - INFO - Epoch(train) [22][840/940] lr: 1.0000e-02 eta: 10:20:46 time: 0.5038 data_time: 0.0285 memory: 21547 grad_norm: 3.9152 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7135 loss: 1.7135 2022/10/10 00:33:04 - mmengine - INFO - Epoch(train) [22][860/940] lr: 1.0000e-02 eta: 10:20:35 time: 0.4953 data_time: 0.0271 memory: 21547 grad_norm: 3.8185 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8315 loss: 1.8315 2022/10/10 00:33:14 - mmengine - INFO - Epoch(train) [22][880/940] lr: 1.0000e-02 eta: 10:20:25 time: 0.5022 data_time: 0.0256 memory: 21547 grad_norm: 3.8593 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6552 loss: 1.6552 2022/10/10 00:33:24 - mmengine - INFO - Epoch(train) [22][900/940] lr: 1.0000e-02 eta: 10:20:13 time: 0.4873 data_time: 0.0303 memory: 21547 grad_norm: 3.9080 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8757 loss: 1.8757 2022/10/10 00:33:34 - mmengine - INFO - Epoch(train) [22][920/940] lr: 1.0000e-02 eta: 10:20:03 time: 0.5029 data_time: 0.0309 memory: 21547 grad_norm: 3.8833 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.8693 loss: 1.8693 2022/10/10 00:33:43 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 00:33:43 - mmengine - INFO - Epoch(train) [22][940/940] lr: 1.0000e-02 eta: 10:19:48 time: 0.4416 data_time: 0.0280 memory: 21547 grad_norm: 4.0496 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.9062 loss: 1.9062 2022/10/10 00:33:55 - mmengine - INFO - Epoch(val) [22][20/78] eta: 0:00:35 time: 0.6128 data_time: 0.5023 memory: 3269 2022/10/10 00:34:04 - mmengine - INFO - Epoch(val) [22][40/78] eta: 0:00:15 time: 0.4174 data_time: 0.3095 memory: 3269 2022/10/10 00:34:15 - mmengine - INFO - Epoch(val) [22][60/78] eta: 0:00:10 time: 0.5596 data_time: 0.4541 memory: 3269 2022/10/10 00:34:25 - mmengine - INFO - Epoch(val) [22][78/78] acc/top1: 0.6241 acc/top5: 0.8414 acc/mean1: 0.6240 2022/10/10 00:34:39 - mmengine - INFO - Epoch(train) [23][20/940] lr: 1.0000e-02 eta: 10:19:54 time: 0.7408 data_time: 0.3724 memory: 21547 grad_norm: 3.8378 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6766 loss: 1.6766 2022/10/10 00:34:49 - mmengine - INFO - Epoch(train) [23][40/940] lr: 1.0000e-02 eta: 10:19:41 time: 0.4657 data_time: 0.0830 memory: 21547 grad_norm: 3.8796 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7821 loss: 1.7821 2022/10/10 00:34:59 - mmengine - INFO - Epoch(train) [23][60/940] lr: 1.0000e-02 eta: 10:19:33 time: 0.5331 data_time: 0.0733 memory: 21547 grad_norm: 3.8238 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7598 loss: 1.7598 2022/10/10 00:35:09 - mmengine - INFO - Epoch(train) [23][80/940] lr: 1.0000e-02 eta: 10:19:22 time: 0.4965 data_time: 0.0233 memory: 21547 grad_norm: 3.8569 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6784 loss: 1.6784 2022/10/10 00:35:20 - mmengine - INFO - Epoch(train) [23][100/940] lr: 1.0000e-02 eta: 10:19:15 time: 0.5574 data_time: 0.0297 memory: 21547 grad_norm: 3.8861 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 1.6698 loss: 1.6698 2022/10/10 00:35:30 - mmengine - INFO - Epoch(train) [23][120/940] lr: 1.0000e-02 eta: 10:19:02 time: 0.4646 data_time: 0.0267 memory: 21547 grad_norm: 3.7707 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.6980 loss: 1.6980 2022/10/10 00:35:40 - mmengine - INFO - Epoch(train) [23][140/940] lr: 1.0000e-02 eta: 10:18:50 time: 0.4873 data_time: 0.0437 memory: 21547 grad_norm: 3.8590 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7967 loss: 1.7967 2022/10/10 00:35:49 - mmengine - INFO - Epoch(train) [23][160/940] lr: 1.0000e-02 eta: 10:18:39 time: 0.4883 data_time: 0.0402 memory: 21547 grad_norm: 3.9272 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7606 loss: 1.7606 2022/10/10 00:36:00 - mmengine - INFO - Epoch(train) [23][180/940] lr: 1.0000e-02 eta: 10:18:31 time: 0.5376 data_time: 0.0285 memory: 21547 grad_norm: 3.9504 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7483 loss: 1.7483 2022/10/10 00:36:10 - mmengine - INFO - Epoch(train) [23][200/940] lr: 1.0000e-02 eta: 10:18:19 time: 0.4879 data_time: 0.0283 memory: 21547 grad_norm: 3.8502 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7395 loss: 1.7395 2022/10/10 00:36:20 - mmengine - INFO - Epoch(train) [23][220/940] lr: 1.0000e-02 eta: 10:18:09 time: 0.4997 data_time: 0.0300 memory: 21547 grad_norm: 3.9460 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.7433 loss: 1.7433 2022/10/10 00:36:30 - mmengine - INFO - Epoch(train) [23][240/940] lr: 1.0000e-02 eta: 10:17:57 time: 0.4860 data_time: 0.0283 memory: 21547 grad_norm: 3.8696 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7395 loss: 1.7395 2022/10/10 00:36:40 - mmengine - INFO - Epoch(train) [23][260/940] lr: 1.0000e-02 eta: 10:17:50 time: 0.5462 data_time: 0.0312 memory: 21547 grad_norm: 3.8539 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6089 loss: 1.6089 2022/10/10 00:36:50 - mmengine - INFO - Epoch(train) [23][280/940] lr: 1.0000e-02 eta: 10:17:38 time: 0.4809 data_time: 0.0296 memory: 21547 grad_norm: 3.7867 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5963 loss: 1.5963 2022/10/10 00:37:00 - mmengine - INFO - Epoch(train) [23][300/940] lr: 1.0000e-02 eta: 10:17:28 time: 0.5112 data_time: 0.0288 memory: 21547 grad_norm: 3.8946 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6195 loss: 1.6195 2022/10/10 00:37:10 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 00:37:10 - mmengine - INFO - Epoch(train) [23][320/940] lr: 1.0000e-02 eta: 10:17:17 time: 0.4917 data_time: 0.0282 memory: 21547 grad_norm: 3.9266 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7976 loss: 1.7976 2022/10/10 00:37:21 - mmengine - INFO - Epoch(train) [23][340/940] lr: 1.0000e-02 eta: 10:17:09 time: 0.5382 data_time: 0.0306 memory: 21547 grad_norm: 3.9156 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.6381 loss: 1.6381 2022/10/10 00:37:31 - mmengine - INFO - Epoch(train) [23][360/940] lr: 1.0000e-02 eta: 10:16:57 time: 0.4910 data_time: 0.0283 memory: 21547 grad_norm: 3.8828 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 1.8371 loss: 1.8371 2022/10/10 00:37:41 - mmengine - INFO - Epoch(train) [23][380/940] lr: 1.0000e-02 eta: 10:16:49 time: 0.5291 data_time: 0.0314 memory: 21547 grad_norm: 3.8439 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6166 loss: 1.6166 2022/10/10 00:37:51 - mmengine - INFO - Epoch(train) [23][400/940] lr: 1.0000e-02 eta: 10:16:36 time: 0.4746 data_time: 0.0226 memory: 21547 grad_norm: 3.8004 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6542 loss: 1.6542 2022/10/10 00:38:01 - mmengine - INFO - Epoch(train) [23][420/940] lr: 1.0000e-02 eta: 10:16:26 time: 0.5116 data_time: 0.0297 memory: 21547 grad_norm: 3.8935 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6496 loss: 1.6496 2022/10/10 00:38:10 - mmengine - INFO - Epoch(train) [23][440/940] lr: 1.0000e-02 eta: 10:16:12 time: 0.4541 data_time: 0.0267 memory: 21547 grad_norm: 3.8591 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.7221 loss: 1.7221 2022/10/10 00:38:21 - mmengine - INFO - Epoch(train) [23][460/940] lr: 1.0000e-02 eta: 10:16:06 time: 0.5605 data_time: 0.0247 memory: 21547 grad_norm: 3.8047 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8156 loss: 1.8156 2022/10/10 00:38:31 - mmengine - INFO - Epoch(train) [23][480/940] lr: 1.0000e-02 eta: 10:15:53 time: 0.4651 data_time: 0.0319 memory: 21547 grad_norm: 3.9184 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.8250 loss: 1.8250 2022/10/10 00:38:41 - mmengine - INFO - Epoch(train) [23][500/940] lr: 1.0000e-02 eta: 10:15:42 time: 0.5019 data_time: 0.0279 memory: 21547 grad_norm: 3.9188 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.8110 loss: 1.8110 2022/10/10 00:38:51 - mmengine - INFO - Epoch(train) [23][520/940] lr: 1.0000e-02 eta: 10:15:34 time: 0.5361 data_time: 0.0260 memory: 21547 grad_norm: 3.8018 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7786 loss: 1.7786 2022/10/10 00:39:01 - mmengine - INFO - Epoch(train) [23][540/940] lr: 1.0000e-02 eta: 10:15:24 time: 0.5016 data_time: 0.0261 memory: 21547 grad_norm: 3.8821 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.8517 loss: 1.8517 2022/10/10 00:39:12 - mmengine - INFO - Epoch(train) [23][560/940] lr: 1.0000e-02 eta: 10:15:15 time: 0.5274 data_time: 0.0254 memory: 21547 grad_norm: 3.9271 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6336 loss: 1.6336 2022/10/10 00:39:21 - mmengine - INFO - Epoch(train) [23][580/940] lr: 1.0000e-02 eta: 10:15:02 time: 0.4636 data_time: 0.0263 memory: 21547 grad_norm: 3.9145 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7004 loss: 1.7004 2022/10/10 00:39:31 - mmengine - INFO - Epoch(train) [23][600/940] lr: 1.0000e-02 eta: 10:14:52 time: 0.5084 data_time: 0.0253 memory: 21547 grad_norm: 3.8506 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8008 loss: 1.8008 2022/10/10 00:39:41 - mmengine - INFO - Epoch(train) [23][620/940] lr: 1.0000e-02 eta: 10:14:41 time: 0.4937 data_time: 0.0323 memory: 21547 grad_norm: 3.8615 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5849 loss: 1.5849 2022/10/10 00:39:51 - mmengine - INFO - Epoch(train) [23][640/940] lr: 1.0000e-02 eta: 10:14:31 time: 0.5080 data_time: 0.0325 memory: 21547 grad_norm: 3.9351 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.8287 loss: 1.8287 2022/10/10 00:40:01 - mmengine - INFO - Epoch(train) [23][660/940] lr: 1.0000e-02 eta: 10:14:20 time: 0.4988 data_time: 0.0231 memory: 21547 grad_norm: 3.9295 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.6742 loss: 1.6742 2022/10/10 00:40:12 - mmengine - INFO - Epoch(train) [23][680/940] lr: 1.0000e-02 eta: 10:14:10 time: 0.5170 data_time: 0.0289 memory: 21547 grad_norm: 3.9355 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7942 loss: 1.7942 2022/10/10 00:40:22 - mmengine - INFO - Epoch(train) [23][700/940] lr: 1.0000e-02 eta: 10:14:01 time: 0.5265 data_time: 0.0239 memory: 21547 grad_norm: 3.8600 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6137 loss: 1.6137 2022/10/10 00:40:32 - mmengine - INFO - Epoch(train) [23][720/940] lr: 1.0000e-02 eta: 10:13:50 time: 0.4811 data_time: 0.0274 memory: 21547 grad_norm: 3.8833 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6138 loss: 1.6138 2022/10/10 00:40:43 - mmengine - INFO - Epoch(train) [23][740/940] lr: 1.0000e-02 eta: 10:13:42 time: 0.5445 data_time: 0.0259 memory: 21547 grad_norm: 3.8488 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5574 loss: 1.5574 2022/10/10 00:40:53 - mmengine - INFO - Epoch(train) [23][760/940] lr: 1.0000e-02 eta: 10:13:31 time: 0.4960 data_time: 0.0243 memory: 21547 grad_norm: 3.8302 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7464 loss: 1.7464 2022/10/10 00:41:04 - mmengine - INFO - Epoch(train) [23][780/940] lr: 1.0000e-02 eta: 10:13:23 time: 0.5401 data_time: 0.0279 memory: 21547 grad_norm: 3.8413 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6567 loss: 1.6567 2022/10/10 00:41:13 - mmengine - INFO - Epoch(train) [23][800/940] lr: 1.0000e-02 eta: 10:13:11 time: 0.4777 data_time: 0.0263 memory: 21547 grad_norm: 3.8875 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6747 loss: 1.6747 2022/10/10 00:41:24 - mmengine - INFO - Epoch(train) [23][820/940] lr: 1.0000e-02 eta: 10:13:03 time: 0.5362 data_time: 0.0299 memory: 21547 grad_norm: 3.8942 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6702 loss: 1.6702 2022/10/10 00:41:33 - mmengine - INFO - Epoch(train) [23][840/940] lr: 1.0000e-02 eta: 10:12:51 time: 0.4818 data_time: 0.0308 memory: 21547 grad_norm: 3.8916 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7739 loss: 1.7739 2022/10/10 00:41:44 - mmengine - INFO - Epoch(train) [23][860/940] lr: 1.0000e-02 eta: 10:12:42 time: 0.5280 data_time: 0.0244 memory: 21547 grad_norm: 3.9127 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6902 loss: 1.6902 2022/10/10 00:41:54 - mmengine - INFO - Epoch(train) [23][880/940] lr: 1.0000e-02 eta: 10:12:32 time: 0.5010 data_time: 0.0263 memory: 21547 grad_norm: 3.8984 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6792 loss: 1.6792 2022/10/10 00:42:04 - mmengine - INFO - Epoch(train) [23][900/940] lr: 1.0000e-02 eta: 10:12:22 time: 0.5109 data_time: 0.0295 memory: 21547 grad_norm: 3.8942 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7120 loss: 1.7120 2022/10/10 00:42:13 - mmengine - INFO - Epoch(train) [23][920/940] lr: 1.0000e-02 eta: 10:12:08 time: 0.4557 data_time: 0.0283 memory: 21547 grad_norm: 3.9429 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6918 loss: 1.6918 2022/10/10 00:42:22 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 00:42:22 - mmengine - INFO - Epoch(train) [23][940/940] lr: 1.0000e-02 eta: 10:11:52 time: 0.4134 data_time: 0.0273 memory: 21547 grad_norm: 4.1127 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.9374 loss: 1.9374 2022/10/10 00:42:34 - mmengine - INFO - Epoch(val) [23][20/78] eta: 0:00:35 time: 0.6156 data_time: 0.5057 memory: 3269 2022/10/10 00:42:42 - mmengine - INFO - Epoch(val) [23][40/78] eta: 0:00:16 time: 0.4254 data_time: 0.3172 memory: 3269 2022/10/10 00:42:54 - mmengine - INFO - Epoch(val) [23][60/78] eta: 0:00:09 time: 0.5544 data_time: 0.4467 memory: 3269 2022/10/10 00:43:04 - mmengine - INFO - Epoch(val) [23][78/78] acc/top1: 0.6311 acc/top5: 0.8465 acc/mean1: 0.6310 2022/10/10 00:43:18 - mmengine - INFO - Epoch(train) [24][20/940] lr: 1.0000e-02 eta: 10:11:54 time: 0.7008 data_time: 0.2544 memory: 21547 grad_norm: 3.9032 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5615 loss: 1.5615 2022/10/10 00:43:28 - mmengine - INFO - Epoch(train) [24][40/940] lr: 1.0000e-02 eta: 10:11:44 time: 0.5102 data_time: 0.0338 memory: 21547 grad_norm: 3.7686 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7725 loss: 1.7725 2022/10/10 00:43:39 - mmengine - INFO - Epoch(train) [24][60/940] lr: 1.0000e-02 eta: 10:11:38 time: 0.5647 data_time: 0.0314 memory: 21547 grad_norm: 3.8524 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6757 loss: 1.6757 2022/10/10 00:43:49 - mmengine - INFO - Epoch(train) [24][80/940] lr: 1.0000e-02 eta: 10:11:26 time: 0.4727 data_time: 0.0218 memory: 21547 grad_norm: 3.8998 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.6736 loss: 1.6736 2022/10/10 00:43:59 - mmengine - INFO - Epoch(train) [24][100/940] lr: 1.0000e-02 eta: 10:11:17 time: 0.5316 data_time: 0.0315 memory: 21547 grad_norm: 3.9226 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6697 loss: 1.6697 2022/10/10 00:44:09 - mmengine - INFO - Epoch(train) [24][120/940] lr: 1.0000e-02 eta: 10:11:07 time: 0.5081 data_time: 0.0282 memory: 21547 grad_norm: 3.9211 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8858 loss: 1.8858 2022/10/10 00:44:19 - mmengine - INFO - Epoch(train) [24][140/940] lr: 1.0000e-02 eta: 10:10:55 time: 0.4844 data_time: 0.0268 memory: 21547 grad_norm: 3.8952 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7961 loss: 1.7961 2022/10/10 00:44:29 - mmengine - INFO - Epoch(train) [24][160/940] lr: 1.0000e-02 eta: 10:10:43 time: 0.4755 data_time: 0.0229 memory: 21547 grad_norm: 3.8345 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.5710 loss: 1.5710 2022/10/10 00:44:40 - mmengine - INFO - Epoch(train) [24][180/940] lr: 1.0000e-02 eta: 10:10:38 time: 0.5768 data_time: 0.0286 memory: 21547 grad_norm: 3.7792 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6726 loss: 1.6726 2022/10/10 00:44:51 - mmengine - INFO - Epoch(train) [24][200/940] lr: 1.0000e-02 eta: 10:10:29 time: 0.5309 data_time: 0.0278 memory: 21547 grad_norm: 3.9199 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6035 loss: 1.6035 2022/10/10 00:45:00 - mmengine - INFO - Epoch(train) [24][220/940] lr: 1.0000e-02 eta: 10:10:17 time: 0.4787 data_time: 0.0327 memory: 21547 grad_norm: 3.9150 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.7188 loss: 1.7188 2022/10/10 00:45:10 - mmengine - INFO - Epoch(train) [24][240/940] lr: 1.0000e-02 eta: 10:10:05 time: 0.4788 data_time: 0.0270 memory: 21547 grad_norm: 3.9531 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7105 loss: 1.7105 2022/10/10 00:45:21 - mmengine - INFO - Epoch(train) [24][260/940] lr: 1.0000e-02 eta: 10:09:56 time: 0.5314 data_time: 0.0287 memory: 21547 grad_norm: 3.9052 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6903 loss: 1.6903 2022/10/10 00:45:30 - mmengine - INFO - Epoch(train) [24][280/940] lr: 1.0000e-02 eta: 10:09:44 time: 0.4777 data_time: 0.0358 memory: 21547 grad_norm: 3.9088 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7025 loss: 1.7025 2022/10/10 00:45:41 - mmengine - INFO - Epoch(train) [24][300/940] lr: 1.0000e-02 eta: 10:09:36 time: 0.5430 data_time: 0.0238 memory: 21547 grad_norm: 3.9122 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7140 loss: 1.7140 2022/10/10 00:45:50 - mmengine - INFO - Epoch(train) [24][320/940] lr: 1.0000e-02 eta: 10:09:23 time: 0.4614 data_time: 0.0254 memory: 21547 grad_norm: 3.9558 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8096 loss: 1.8096 2022/10/10 00:46:01 - mmengine - INFO - Epoch(train) [24][340/940] lr: 1.0000e-02 eta: 10:09:15 time: 0.5352 data_time: 0.0295 memory: 21547 grad_norm: 3.8946 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 1.7971 loss: 1.7971 2022/10/10 00:46:11 - mmengine - INFO - Epoch(train) [24][360/940] lr: 1.0000e-02 eta: 10:09:03 time: 0.4823 data_time: 0.0267 memory: 21547 grad_norm: 3.9458 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8648 loss: 1.8648 2022/10/10 00:46:21 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 00:46:21 - mmengine - INFO - Epoch(train) [24][380/940] lr: 1.0000e-02 eta: 10:08:54 time: 0.5203 data_time: 0.0245 memory: 21547 grad_norm: 3.8763 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7560 loss: 1.7560 2022/10/10 00:46:30 - mmengine - INFO - Epoch(train) [24][400/940] lr: 1.0000e-02 eta: 10:08:41 time: 0.4676 data_time: 0.0287 memory: 21547 grad_norm: 3.9514 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.9325 loss: 1.9325 2022/10/10 00:46:40 - mmengine - INFO - Epoch(train) [24][420/940] lr: 1.0000e-02 eta: 10:08:30 time: 0.4969 data_time: 0.0258 memory: 21547 grad_norm: 3.9744 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8436 loss: 1.8436 2022/10/10 00:46:50 - mmengine - INFO - Epoch(train) [24][440/940] lr: 1.0000e-02 eta: 10:08:19 time: 0.4866 data_time: 0.0282 memory: 21547 grad_norm: 3.9687 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 1.8146 loss: 1.8146 2022/10/10 00:47:00 - mmengine - INFO - Epoch(train) [24][460/940] lr: 1.0000e-02 eta: 10:08:09 time: 0.5180 data_time: 0.0271 memory: 21547 grad_norm: 3.9411 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6758 loss: 1.6758 2022/10/10 00:47:10 - mmengine - INFO - Epoch(train) [24][480/940] lr: 1.0000e-02 eta: 10:07:57 time: 0.4698 data_time: 0.0306 memory: 21547 grad_norm: 3.7981 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5910 loss: 1.5910 2022/10/10 00:47:20 - mmengine - INFO - Epoch(train) [24][500/940] lr: 1.0000e-02 eta: 10:07:47 time: 0.5189 data_time: 0.0266 memory: 21547 grad_norm: 3.9718 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7723 loss: 1.7723 2022/10/10 00:47:31 - mmengine - INFO - Epoch(train) [24][520/940] lr: 1.0000e-02 eta: 10:07:39 time: 0.5323 data_time: 0.0307 memory: 21547 grad_norm: 3.8877 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.6608 loss: 1.6608 2022/10/10 00:47:40 - mmengine - INFO - Epoch(train) [24][540/940] lr: 1.0000e-02 eta: 10:07:27 time: 0.4831 data_time: 0.0232 memory: 21547 grad_norm: 3.8601 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6960 loss: 1.6960 2022/10/10 00:47:51 - mmengine - INFO - Epoch(train) [24][560/940] lr: 1.0000e-02 eta: 10:07:19 time: 0.5405 data_time: 0.0317 memory: 21547 grad_norm: 4.0425 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7939 loss: 1.7939 2022/10/10 00:48:01 - mmengine - INFO - Epoch(train) [24][580/940] lr: 1.0000e-02 eta: 10:07:08 time: 0.4925 data_time: 0.0278 memory: 21547 grad_norm: 3.8530 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.8311 loss: 1.8311 2022/10/10 00:48:11 - mmengine - INFO - Epoch(train) [24][600/940] lr: 1.0000e-02 eta: 10:06:58 time: 0.5151 data_time: 0.0343 memory: 21547 grad_norm: 3.9719 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.8555 loss: 1.8555 2022/10/10 00:48:22 - mmengine - INFO - Epoch(train) [24][620/940] lr: 1.0000e-02 eta: 10:06:48 time: 0.5131 data_time: 0.0269 memory: 21547 grad_norm: 3.9580 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.7596 loss: 1.7596 2022/10/10 00:48:31 - mmengine - INFO - Epoch(train) [24][640/940] lr: 1.0000e-02 eta: 10:06:37 time: 0.4940 data_time: 0.0412 memory: 21547 grad_norm: 4.0057 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7855 loss: 1.7855 2022/10/10 00:48:42 - mmengine - INFO - Epoch(train) [24][660/940] lr: 1.0000e-02 eta: 10:06:29 time: 0.5360 data_time: 0.0250 memory: 21547 grad_norm: 3.9998 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.6431 loss: 1.6431 2022/10/10 00:48:52 - mmengine - INFO - Epoch(train) [24][680/940] lr: 1.0000e-02 eta: 10:06:18 time: 0.4946 data_time: 0.0317 memory: 21547 grad_norm: 3.9539 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7032 loss: 1.7032 2022/10/10 00:49:02 - mmengine - INFO - Epoch(train) [24][700/940] lr: 1.0000e-02 eta: 10:06:07 time: 0.4856 data_time: 0.0247 memory: 21547 grad_norm: 3.9934 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.6608 loss: 1.6608 2022/10/10 00:49:12 - mmengine - INFO - Epoch(train) [24][720/940] lr: 1.0000e-02 eta: 10:05:56 time: 0.5054 data_time: 0.0305 memory: 21547 grad_norm: 3.8796 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.7823 loss: 1.7823 2022/10/10 00:49:22 - mmengine - INFO - Epoch(train) [24][740/940] lr: 1.0000e-02 eta: 10:05:46 time: 0.5004 data_time: 0.0235 memory: 21547 grad_norm: 3.9256 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6140 loss: 1.6140 2022/10/10 00:49:32 - mmengine - INFO - Epoch(train) [24][760/940] lr: 1.0000e-02 eta: 10:05:37 time: 0.5254 data_time: 0.0284 memory: 21547 grad_norm: 3.8829 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7268 loss: 1.7268 2022/10/10 00:49:43 - mmengine - INFO - Epoch(train) [24][780/940] lr: 1.0000e-02 eta: 10:05:27 time: 0.5137 data_time: 0.0235 memory: 21547 grad_norm: 3.9182 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.6499 loss: 1.6499 2022/10/10 00:49:53 - mmengine - INFO - Epoch(train) [24][800/940] lr: 1.0000e-02 eta: 10:05:16 time: 0.4909 data_time: 0.0295 memory: 21547 grad_norm: 3.9540 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7709 loss: 1.7709 2022/10/10 00:50:02 - mmengine - INFO - Epoch(train) [24][820/940] lr: 1.0000e-02 eta: 10:05:05 time: 0.4945 data_time: 0.0275 memory: 21547 grad_norm: 3.8502 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6031 loss: 1.6031 2022/10/10 00:50:12 - mmengine - INFO - Epoch(train) [24][840/940] lr: 1.0000e-02 eta: 10:04:54 time: 0.4975 data_time: 0.0297 memory: 21547 grad_norm: 3.8670 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.6580 loss: 1.6580 2022/10/10 00:50:22 - mmengine - INFO - Epoch(train) [24][860/940] lr: 1.0000e-02 eta: 10:04:42 time: 0.4725 data_time: 0.0291 memory: 21547 grad_norm: 4.0108 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5663 loss: 1.5663 2022/10/10 00:50:32 - mmengine - INFO - Epoch(train) [24][880/940] lr: 1.0000e-02 eta: 10:04:31 time: 0.5012 data_time: 0.0284 memory: 21547 grad_norm: 4.0410 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7981 loss: 1.7981 2022/10/10 00:50:42 - mmengine - INFO - Epoch(train) [24][900/940] lr: 1.0000e-02 eta: 10:04:20 time: 0.4917 data_time: 0.0295 memory: 21547 grad_norm: 3.9216 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7463 loss: 1.7463 2022/10/10 00:50:52 - mmengine - INFO - Epoch(train) [24][920/940] lr: 1.0000e-02 eta: 10:04:10 time: 0.5154 data_time: 0.0315 memory: 21547 grad_norm: 3.9653 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.6851 loss: 1.6851 2022/10/10 00:51:01 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 00:51:01 - mmengine - INFO - Epoch(train) [24][940/940] lr: 1.0000e-02 eta: 10:03:56 time: 0.4382 data_time: 0.0250 memory: 21547 grad_norm: 4.2938 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.9955 loss: 1.9955 2022/10/10 00:51:01 - mmengine - INFO - Saving checkpoint at 24 epochs 2022/10/10 00:51:14 - mmengine - INFO - Epoch(val) [24][20/78] eta: 0:00:35 time: 0.6160 data_time: 0.5119 memory: 3269 2022/10/10 00:51:23 - mmengine - INFO - Epoch(val) [24][40/78] eta: 0:00:16 time: 0.4242 data_time: 0.3206 memory: 3269 2022/10/10 00:51:33 - mmengine - INFO - Epoch(val) [24][60/78] eta: 0:00:09 time: 0.5408 data_time: 0.4343 memory: 3269 2022/10/10 00:51:43 - mmengine - INFO - Epoch(val) [24][78/78] acc/top1: 0.6245 acc/top5: 0.8435 acc/mean1: 0.6243 2022/10/10 00:51:57 - mmengine - INFO - Epoch(train) [25][20/940] lr: 1.0000e-02 eta: 10:03:59 time: 0.7224 data_time: 0.2236 memory: 21547 grad_norm: 3.8334 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7243 loss: 1.7243 2022/10/10 00:52:07 - mmengine - INFO - Epoch(train) [25][40/940] lr: 1.0000e-02 eta: 10:03:47 time: 0.4792 data_time: 0.0280 memory: 21547 grad_norm: 3.8088 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5588 loss: 1.5588 2022/10/10 00:52:18 - mmengine - INFO - Epoch(train) [25][60/940] lr: 1.0000e-02 eta: 10:03:39 time: 0.5370 data_time: 0.0312 memory: 21547 grad_norm: 3.8962 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6064 loss: 1.6064 2022/10/10 00:52:27 - mmengine - INFO - Epoch(train) [25][80/940] lr: 1.0000e-02 eta: 10:03:28 time: 0.4846 data_time: 0.0317 memory: 21547 grad_norm: 3.8110 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6197 loss: 1.6197 2022/10/10 00:52:37 - mmengine - INFO - Epoch(train) [25][100/940] lr: 1.0000e-02 eta: 10:03:17 time: 0.5020 data_time: 0.0298 memory: 21547 grad_norm: 3.9331 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6122 loss: 1.6122 2022/10/10 00:52:47 - mmengine - INFO - Epoch(train) [25][120/940] lr: 1.0000e-02 eta: 10:03:06 time: 0.4872 data_time: 0.0330 memory: 21547 grad_norm: 3.9486 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5735 loss: 1.5735 2022/10/10 00:52:58 - mmengine - INFO - Epoch(train) [25][140/940] lr: 1.0000e-02 eta: 10:02:57 time: 0.5326 data_time: 0.0259 memory: 21547 grad_norm: 3.8066 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.6258 loss: 1.6258 2022/10/10 00:53:08 - mmengine - INFO - Epoch(train) [25][160/940] lr: 1.0000e-02 eta: 10:02:46 time: 0.4958 data_time: 0.0340 memory: 21547 grad_norm: 3.9506 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7881 loss: 1.7881 2022/10/10 00:53:19 - mmengine - INFO - Epoch(train) [25][180/940] lr: 1.0000e-02 eta: 10:02:39 time: 0.5580 data_time: 0.0265 memory: 21547 grad_norm: 3.9110 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7947 loss: 1.7947 2022/10/10 00:53:28 - mmengine - INFO - Epoch(train) [25][200/940] lr: 1.0000e-02 eta: 10:02:27 time: 0.4675 data_time: 0.0308 memory: 21547 grad_norm: 3.9337 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7717 loss: 1.7717 2022/10/10 00:53:38 - mmengine - INFO - Epoch(train) [25][220/940] lr: 1.0000e-02 eta: 10:02:14 time: 0.4761 data_time: 0.0287 memory: 21547 grad_norm: 3.9146 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.7600 loss: 1.7600 2022/10/10 00:53:47 - mmengine - INFO - Epoch(train) [25][240/940] lr: 1.0000e-02 eta: 10:02:02 time: 0.4686 data_time: 0.0256 memory: 21547 grad_norm: 3.9296 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6981 loss: 1.6981 2022/10/10 00:53:58 - mmengine - INFO - Epoch(train) [25][260/940] lr: 1.0000e-02 eta: 10:01:53 time: 0.5262 data_time: 0.0308 memory: 21547 grad_norm: 3.9949 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.7222 loss: 1.7222 2022/10/10 00:54:08 - mmengine - INFO - Epoch(train) [25][280/940] lr: 1.0000e-02 eta: 10:01:42 time: 0.4985 data_time: 0.0292 memory: 21547 grad_norm: 3.9656 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7631 loss: 1.7631 2022/10/10 00:54:17 - mmengine - INFO - Epoch(train) [25][300/940] lr: 1.0000e-02 eta: 10:01:30 time: 0.4800 data_time: 0.0264 memory: 21547 grad_norm: 3.9049 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7215 loss: 1.7215 2022/10/10 00:54:27 - mmengine - INFO - Epoch(train) [25][320/940] lr: 1.0000e-02 eta: 10:01:20 time: 0.5099 data_time: 0.0278 memory: 21547 grad_norm: 3.9681 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5417 loss: 1.5417 2022/10/10 00:54:37 - mmengine - INFO - Epoch(train) [25][340/940] lr: 1.0000e-02 eta: 10:01:09 time: 0.4926 data_time: 0.0226 memory: 21547 grad_norm: 3.8338 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.5661 loss: 1.5661 2022/10/10 00:54:48 - mmengine - INFO - Epoch(train) [25][360/940] lr: 1.0000e-02 eta: 10:01:00 time: 0.5191 data_time: 0.0279 memory: 21547 grad_norm: 4.0039 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6427 loss: 1.6427 2022/10/10 00:54:58 - mmengine - INFO - Epoch(train) [25][380/940] lr: 1.0000e-02 eta: 10:00:49 time: 0.4925 data_time: 0.0312 memory: 21547 grad_norm: 3.9722 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6556 loss: 1.6556 2022/10/10 00:55:09 - mmengine - INFO - Epoch(train) [25][400/940] lr: 1.0000e-02 eta: 10:00:42 time: 0.5577 data_time: 0.0301 memory: 21547 grad_norm: 4.0055 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6821 loss: 1.6821 2022/10/10 00:55:19 - mmengine - INFO - Epoch(train) [25][420/940] lr: 1.0000e-02 eta: 10:00:31 time: 0.4947 data_time: 0.0239 memory: 21547 grad_norm: 3.9917 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8300 loss: 1.8300 2022/10/10 00:55:28 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 00:55:28 - mmengine - INFO - Epoch(train) [25][440/940] lr: 1.0000e-02 eta: 10:00:20 time: 0.4910 data_time: 0.0269 memory: 21547 grad_norm: 3.9816 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.5622 loss: 1.5622 2022/10/10 00:55:38 - mmengine - INFO - Epoch(train) [25][460/940] lr: 1.0000e-02 eta: 10:00:07 time: 0.4653 data_time: 0.0262 memory: 21547 grad_norm: 4.0055 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9207 loss: 1.9207 2022/10/10 00:55:48 - mmengine - INFO - Epoch(train) [25][480/940] lr: 1.0000e-02 eta: 9:59:57 time: 0.5117 data_time: 0.0303 memory: 21547 grad_norm: 3.8322 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7894 loss: 1.7894 2022/10/10 00:55:58 - mmengine - INFO - Epoch(train) [25][500/940] lr: 1.0000e-02 eta: 9:59:48 time: 0.5244 data_time: 0.0304 memory: 21547 grad_norm: 3.9333 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7707 loss: 1.7707 2022/10/10 00:56:08 - mmengine - INFO - Epoch(train) [25][520/940] lr: 1.0000e-02 eta: 9:59:36 time: 0.4738 data_time: 0.0278 memory: 21547 grad_norm: 4.0367 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.7015 loss: 1.7015 2022/10/10 00:56:18 - mmengine - INFO - Epoch(train) [25][540/940] lr: 1.0000e-02 eta: 9:59:27 time: 0.5246 data_time: 0.0301 memory: 21547 grad_norm: 3.8524 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7367 loss: 1.7367 2022/10/10 00:56:29 - mmengine - INFO - Epoch(train) [25][560/940] lr: 1.0000e-02 eta: 9:59:17 time: 0.5216 data_time: 0.0243 memory: 21547 grad_norm: 3.9413 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.6868 loss: 1.6868 2022/10/10 00:56:40 - mmengine - INFO - Epoch(train) [25][580/940] lr: 1.0000e-02 eta: 9:59:10 time: 0.5486 data_time: 0.0267 memory: 21547 grad_norm: 3.8829 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.7455 loss: 1.7455 2022/10/10 00:56:48 - mmengine - INFO - Epoch(train) [25][600/940] lr: 1.0000e-02 eta: 9:58:55 time: 0.4320 data_time: 0.0299 memory: 21547 grad_norm: 3.9138 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.6047 loss: 1.6047 2022/10/10 00:56:59 - mmengine - INFO - Epoch(train) [25][620/940] lr: 1.0000e-02 eta: 9:58:46 time: 0.5185 data_time: 0.0265 memory: 21547 grad_norm: 3.9975 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.7414 loss: 1.7414 2022/10/10 00:57:09 - mmengine - INFO - Epoch(train) [25][640/940] lr: 1.0000e-02 eta: 9:58:36 time: 0.5170 data_time: 0.0262 memory: 21547 grad_norm: 3.9409 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6582 loss: 1.6582 2022/10/10 00:57:19 - mmengine - INFO - Epoch(train) [25][660/940] lr: 1.0000e-02 eta: 9:58:24 time: 0.4740 data_time: 0.0293 memory: 21547 grad_norm: 3.9003 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7190 loss: 1.7190 2022/10/10 00:57:29 - mmengine - INFO - Epoch(train) [25][680/940] lr: 1.0000e-02 eta: 9:58:15 time: 0.5298 data_time: 0.0275 memory: 21547 grad_norm: 3.9894 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5654 loss: 1.5654 2022/10/10 00:57:39 - mmengine - INFO - Epoch(train) [25][700/940] lr: 1.0000e-02 eta: 9:58:04 time: 0.4831 data_time: 0.0218 memory: 21547 grad_norm: 3.9919 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6575 loss: 1.6575 2022/10/10 00:57:49 - mmengine - INFO - Epoch(train) [25][720/940] lr: 1.0000e-02 eta: 9:57:53 time: 0.5060 data_time: 0.0264 memory: 21547 grad_norm: 3.9432 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7253 loss: 1.7253 2022/10/10 00:57:59 - mmengine - INFO - Epoch(train) [25][740/940] lr: 1.0000e-02 eta: 9:57:43 time: 0.5042 data_time: 0.0248 memory: 21547 grad_norm: 3.8893 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 1.7615 loss: 1.7615 2022/10/10 00:58:09 - mmengine - INFO - Epoch(train) [25][760/940] lr: 1.0000e-02 eta: 9:57:32 time: 0.4911 data_time: 0.0296 memory: 21547 grad_norm: 3.9839 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6268 loss: 1.6268 2022/10/10 00:58:20 - mmengine - INFO - Epoch(train) [25][780/940] lr: 1.0000e-02 eta: 9:57:23 time: 0.5309 data_time: 0.0249 memory: 21547 grad_norm: 3.8856 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.8090 loss: 1.8090 2022/10/10 00:58:29 - mmengine - INFO - Epoch(train) [25][800/940] lr: 1.0000e-02 eta: 9:57:12 time: 0.4862 data_time: 0.0294 memory: 21547 grad_norm: 3.8677 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6722 loss: 1.6722 2022/10/10 00:58:40 - mmengine - INFO - Epoch(train) [25][820/940] lr: 1.0000e-02 eta: 9:57:02 time: 0.5167 data_time: 0.0290 memory: 21547 grad_norm: 3.9512 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6916 loss: 1.6916 2022/10/10 00:58:49 - mmengine - INFO - Epoch(train) [25][840/940] lr: 1.0000e-02 eta: 9:56:51 time: 0.4836 data_time: 0.0321 memory: 21547 grad_norm: 3.8999 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.6317 loss: 1.6317 2022/10/10 00:59:00 - mmengine - INFO - Epoch(train) [25][860/940] lr: 1.0000e-02 eta: 9:56:42 time: 0.5410 data_time: 0.0299 memory: 21547 grad_norm: 3.9055 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7710 loss: 1.7710 2022/10/10 00:59:10 - mmengine - INFO - Epoch(train) [25][880/940] lr: 1.0000e-02 eta: 9:56:31 time: 0.4845 data_time: 0.0227 memory: 21547 grad_norm: 3.9231 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6126 loss: 1.6126 2022/10/10 00:59:19 - mmengine - INFO - Epoch(train) [25][900/940] lr: 1.0000e-02 eta: 9:56:19 time: 0.4797 data_time: 0.0293 memory: 21547 grad_norm: 4.0124 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5926 loss: 1.5926 2022/10/10 00:59:30 - mmengine - INFO - Epoch(train) [25][920/940] lr: 1.0000e-02 eta: 9:56:11 time: 0.5410 data_time: 0.0256 memory: 21547 grad_norm: 3.9736 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7444 loss: 1.7444 2022/10/10 00:59:39 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 00:59:39 - mmengine - INFO - Epoch(train) [25][940/940] lr: 1.0000e-02 eta: 9:55:56 time: 0.4328 data_time: 0.0241 memory: 21547 grad_norm: 4.1323 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.6984 loss: 1.6984 2022/10/10 00:59:51 - mmengine - INFO - Epoch(val) [25][20/78] eta: 0:00:34 time: 0.6033 data_time: 0.4979 memory: 3269 2022/10/10 00:59:59 - mmengine - INFO - Epoch(val) [25][40/78] eta: 0:00:15 time: 0.4208 data_time: 0.3147 memory: 3269 2022/10/10 01:00:11 - mmengine - INFO - Epoch(val) [25][60/78] eta: 0:00:10 time: 0.5637 data_time: 0.4585 memory: 3269 2022/10/10 01:00:21 - mmengine - INFO - Epoch(val) [25][78/78] acc/top1: 0.6313 acc/top5: 0.8439 acc/mean1: 0.6313 2022/10/10 01:00:35 - mmengine - INFO - Epoch(train) [26][20/940] lr: 1.0000e-02 eta: 9:55:58 time: 0.7039 data_time: 0.2253 memory: 21547 grad_norm: 3.8703 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.5977 loss: 1.5977 2022/10/10 01:00:45 - mmengine - INFO - Epoch(train) [26][40/940] lr: 1.0000e-02 eta: 9:55:48 time: 0.5023 data_time: 0.0531 memory: 21547 grad_norm: 3.9306 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6246 loss: 1.6246 2022/10/10 01:00:55 - mmengine - INFO - Epoch(train) [26][60/940] lr: 1.0000e-02 eta: 9:55:39 time: 0.5268 data_time: 0.0970 memory: 21547 grad_norm: 3.7713 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5568 loss: 1.5568 2022/10/10 01:01:05 - mmengine - INFO - Epoch(train) [26][80/940] lr: 1.0000e-02 eta: 9:55:27 time: 0.4819 data_time: 0.0921 memory: 21547 grad_norm: 3.8833 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6736 loss: 1.6736 2022/10/10 01:01:15 - mmengine - INFO - Epoch(train) [26][100/940] lr: 1.0000e-02 eta: 9:55:17 time: 0.5142 data_time: 0.0873 memory: 21547 grad_norm: 3.9418 top1_acc: 0.5000 top5_acc: 0.9062 loss_cls: 1.6635 loss: 1.6635 2022/10/10 01:01:25 - mmengine - INFO - Epoch(train) [26][120/940] lr: 1.0000e-02 eta: 9:55:05 time: 0.4692 data_time: 0.0500 memory: 21547 grad_norm: 3.9296 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.6629 loss: 1.6629 2022/10/10 01:01:35 - mmengine - INFO - Epoch(train) [26][140/940] lr: 1.0000e-02 eta: 9:54:56 time: 0.5366 data_time: 0.0954 memory: 21547 grad_norm: 3.9135 top1_acc: 0.5312 top5_acc: 0.9375 loss_cls: 1.7303 loss: 1.7303 2022/10/10 01:01:45 - mmengine - INFO - Epoch(train) [26][160/940] lr: 1.0000e-02 eta: 9:54:46 time: 0.4984 data_time: 0.0235 memory: 21547 grad_norm: 3.9265 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6242 loss: 1.6242 2022/10/10 01:01:56 - mmengine - INFO - Epoch(train) [26][180/940] lr: 1.0000e-02 eta: 9:54:37 time: 0.5252 data_time: 0.0308 memory: 21547 grad_norm: 3.9136 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7265 loss: 1.7265 2022/10/10 01:02:06 - mmengine - INFO - Epoch(train) [26][200/940] lr: 1.0000e-02 eta: 9:54:26 time: 0.5024 data_time: 0.0251 memory: 21547 grad_norm: 3.9999 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.6744 loss: 1.6744 2022/10/10 01:02:16 - mmengine - INFO - Epoch(train) [26][220/940] lr: 1.0000e-02 eta: 9:54:17 time: 0.5275 data_time: 0.0254 memory: 21547 grad_norm: 4.0063 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7750 loss: 1.7750 2022/10/10 01:02:26 - mmengine - INFO - Epoch(train) [26][240/940] lr: 1.0000e-02 eta: 9:54:06 time: 0.4892 data_time: 0.0250 memory: 21547 grad_norm: 3.8700 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6858 loss: 1.6858 2022/10/10 01:02:37 - mmengine - INFO - Epoch(train) [26][260/940] lr: 1.0000e-02 eta: 9:53:58 time: 0.5502 data_time: 0.0288 memory: 21547 grad_norm: 3.9654 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5999 loss: 1.5999 2022/10/10 01:02:46 - mmengine - INFO - Epoch(train) [26][280/940] lr: 1.0000e-02 eta: 9:53:45 time: 0.4593 data_time: 0.0282 memory: 21547 grad_norm: 3.9614 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7153 loss: 1.7153 2022/10/10 01:02:57 - mmengine - INFO - Epoch(train) [26][300/940] lr: 1.0000e-02 eta: 9:53:36 time: 0.5128 data_time: 0.0272 memory: 21547 grad_norm: 4.0168 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6326 loss: 1.6326 2022/10/10 01:03:07 - mmengine - INFO - Epoch(train) [26][320/940] lr: 1.0000e-02 eta: 9:53:25 time: 0.5051 data_time: 0.0248 memory: 21547 grad_norm: 3.9406 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5668 loss: 1.5668 2022/10/10 01:03:17 - mmengine - INFO - Epoch(train) [26][340/940] lr: 1.0000e-02 eta: 9:53:16 time: 0.5163 data_time: 0.0334 memory: 21547 grad_norm: 3.9894 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6963 loss: 1.6963 2022/10/10 01:03:27 - mmengine - INFO - Epoch(train) [26][360/940] lr: 1.0000e-02 eta: 9:53:06 time: 0.5094 data_time: 0.0289 memory: 21547 grad_norm: 3.8542 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6042 loss: 1.6042 2022/10/10 01:03:38 - mmengine - INFO - Epoch(train) [26][380/940] lr: 1.0000e-02 eta: 9:52:59 time: 0.5638 data_time: 0.0255 memory: 21547 grad_norm: 4.0062 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6793 loss: 1.6793 2022/10/10 01:03:47 - mmengine - INFO - Epoch(train) [26][400/940] lr: 1.0000e-02 eta: 9:52:44 time: 0.4212 data_time: 0.0244 memory: 21547 grad_norm: 3.9737 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7446 loss: 1.7446 2022/10/10 01:03:57 - mmengine - INFO - Epoch(train) [26][420/940] lr: 1.0000e-02 eta: 9:52:32 time: 0.4882 data_time: 0.0314 memory: 21547 grad_norm: 3.9690 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7719 loss: 1.7719 2022/10/10 01:04:07 - mmengine - INFO - Epoch(train) [26][440/940] lr: 1.0000e-02 eta: 9:52:23 time: 0.5160 data_time: 0.0260 memory: 21547 grad_norm: 3.9328 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.6449 loss: 1.6449 2022/10/10 01:04:17 - mmengine - INFO - Epoch(train) [26][460/940] lr: 1.0000e-02 eta: 9:52:11 time: 0.4860 data_time: 0.0314 memory: 21547 grad_norm: 3.9447 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.6090 loss: 1.6090 2022/10/10 01:04:26 - mmengine - INFO - Epoch(train) [26][480/940] lr: 1.0000e-02 eta: 9:52:00 time: 0.4858 data_time: 0.0317 memory: 21547 grad_norm: 3.9857 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5750 loss: 1.5750 2022/10/10 01:04:38 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 01:04:38 - mmengine - INFO - Epoch(train) [26][500/940] lr: 1.0000e-02 eta: 9:51:53 time: 0.5586 data_time: 0.0319 memory: 21547 grad_norm: 3.9562 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7223 loss: 1.7223 2022/10/10 01:04:47 - mmengine - INFO - Epoch(train) [26][520/940] lr: 1.0000e-02 eta: 9:51:41 time: 0.4875 data_time: 0.0290 memory: 21547 grad_norm: 3.9398 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.6371 loss: 1.6371 2022/10/10 01:04:58 - mmengine - INFO - Epoch(train) [26][540/940] lr: 1.0000e-02 eta: 9:51:32 time: 0.5146 data_time: 0.0585 memory: 21547 grad_norm: 3.9463 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7519 loss: 1.7519 2022/10/10 01:05:07 - mmengine - INFO - Epoch(train) [26][560/940] lr: 1.0000e-02 eta: 9:51:20 time: 0.4799 data_time: 0.0655 memory: 21547 grad_norm: 3.9631 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6651 loss: 1.6651 2022/10/10 01:05:17 - mmengine - INFO - Epoch(train) [26][580/940] lr: 1.0000e-02 eta: 9:51:08 time: 0.4800 data_time: 0.0321 memory: 21547 grad_norm: 3.9903 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7174 loss: 1.7174 2022/10/10 01:05:27 - mmengine - INFO - Epoch(train) [26][600/940] lr: 1.0000e-02 eta: 9:50:57 time: 0.4959 data_time: 0.0276 memory: 21547 grad_norm: 4.0344 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8426 loss: 1.8426 2022/10/10 01:05:37 - mmengine - INFO - Epoch(train) [26][620/940] lr: 1.0000e-02 eta: 9:50:49 time: 0.5318 data_time: 0.0311 memory: 21547 grad_norm: 4.0037 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6273 loss: 1.6273 2022/10/10 01:05:47 - mmengine - INFO - Epoch(train) [26][640/940] lr: 1.0000e-02 eta: 9:50:36 time: 0.4643 data_time: 0.0246 memory: 21547 grad_norm: 3.8757 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6365 loss: 1.6365 2022/10/10 01:05:57 - mmengine - INFO - Epoch(train) [26][660/940] lr: 1.0000e-02 eta: 9:50:26 time: 0.5077 data_time: 0.0278 memory: 21547 grad_norm: 4.0194 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.7545 loss: 1.7545 2022/10/10 01:06:07 - mmengine - INFO - Epoch(train) [26][680/940] lr: 1.0000e-02 eta: 9:50:15 time: 0.4938 data_time: 0.0268 memory: 21547 grad_norm: 3.9068 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6099 loss: 1.6099 2022/10/10 01:06:17 - mmengine - INFO - Epoch(train) [26][700/940] lr: 1.0000e-02 eta: 9:50:04 time: 0.4993 data_time: 0.0289 memory: 21547 grad_norm: 3.9853 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.5571 loss: 1.5571 2022/10/10 01:06:27 - mmengine - INFO - Epoch(train) [26][720/940] lr: 1.0000e-02 eta: 9:49:54 time: 0.5044 data_time: 0.0289 memory: 21547 grad_norm: 3.9727 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.6703 loss: 1.6703 2022/10/10 01:06:37 - mmengine - INFO - Epoch(train) [26][740/940] lr: 1.0000e-02 eta: 9:49:44 time: 0.5087 data_time: 0.0267 memory: 21547 grad_norm: 3.9511 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7696 loss: 1.7696 2022/10/10 01:06:47 - mmengine - INFO - Epoch(train) [26][760/940] lr: 1.0000e-02 eta: 9:49:33 time: 0.4910 data_time: 0.0255 memory: 21547 grad_norm: 3.9639 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7111 loss: 1.7111 2022/10/10 01:06:57 - mmengine - INFO - Epoch(train) [26][780/940] lr: 1.0000e-02 eta: 9:49:24 time: 0.5186 data_time: 0.0327 memory: 21547 grad_norm: 3.9657 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.9542 loss: 1.9542 2022/10/10 01:07:07 - mmengine - INFO - Epoch(train) [26][800/940] lr: 1.0000e-02 eta: 9:49:13 time: 0.5002 data_time: 0.0370 memory: 21547 grad_norm: 4.0261 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.8903 loss: 1.8903 2022/10/10 01:07:17 - mmengine - INFO - Epoch(train) [26][820/940] lr: 1.0000e-02 eta: 9:49:02 time: 0.4853 data_time: 0.0268 memory: 21547 grad_norm: 3.9695 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7130 loss: 1.7130 2022/10/10 01:07:27 - mmengine - INFO - Epoch(train) [26][840/940] lr: 1.0000e-02 eta: 9:48:52 time: 0.5169 data_time: 0.0241 memory: 21547 grad_norm: 3.9118 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7809 loss: 1.7809 2022/10/10 01:07:37 - mmengine - INFO - Epoch(train) [26][860/940] lr: 1.0000e-02 eta: 9:48:42 time: 0.5077 data_time: 0.0351 memory: 21547 grad_norm: 3.8973 top1_acc: 0.3438 top5_acc: 0.7188 loss_cls: 1.6223 loss: 1.6223 2022/10/10 01:07:48 - mmengine - INFO - Epoch(train) [26][880/940] lr: 1.0000e-02 eta: 9:48:32 time: 0.5150 data_time: 0.0309 memory: 21547 grad_norm: 3.9808 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 1.6992 loss: 1.6992 2022/10/10 01:07:58 - mmengine - INFO - Epoch(train) [26][900/940] lr: 1.0000e-02 eta: 9:48:21 time: 0.4978 data_time: 0.0260 memory: 21547 grad_norm: 3.9941 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.7658 loss: 1.7658 2022/10/10 01:08:08 - mmengine - INFO - Epoch(train) [26][920/940] lr: 1.0000e-02 eta: 9:48:13 time: 0.5441 data_time: 0.0291 memory: 21547 grad_norm: 3.9701 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6931 loss: 1.6931 2022/10/10 01:08:17 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 01:08:17 - mmengine - INFO - Epoch(train) [26][940/940] lr: 1.0000e-02 eta: 9:47:59 time: 0.4400 data_time: 0.0220 memory: 21547 grad_norm: 4.1934 top1_acc: 0.2857 top5_acc: 0.5714 loss_cls: 1.7225 loss: 1.7225 2022/10/10 01:08:29 - mmengine - INFO - Epoch(val) [26][20/78] eta: 0:00:35 time: 0.6044 data_time: 0.4964 memory: 3269 2022/10/10 01:08:38 - mmengine - INFO - Epoch(val) [26][40/78] eta: 0:00:16 time: 0.4351 data_time: 0.3271 memory: 3269 2022/10/10 01:08:49 - mmengine - INFO - Epoch(val) [26][60/78] eta: 0:00:10 time: 0.5642 data_time: 0.4577 memory: 3269 2022/10/10 01:08:59 - mmengine - INFO - Epoch(val) [26][78/78] acc/top1: 0.6276 acc/top5: 0.8417 acc/mean1: 0.6274 2022/10/10 01:09:14 - mmengine - INFO - Epoch(train) [27][20/940] lr: 1.0000e-02 eta: 9:48:02 time: 0.7368 data_time: 0.2815 memory: 21547 grad_norm: 3.9425 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6588 loss: 1.6588 2022/10/10 01:09:24 - mmengine - INFO - Epoch(train) [27][40/940] lr: 1.0000e-02 eta: 9:47:52 time: 0.5088 data_time: 0.0249 memory: 21547 grad_norm: 3.8789 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.9008 loss: 1.9008 2022/10/10 01:09:35 - mmengine - INFO - Epoch(train) [27][60/940] lr: 1.0000e-02 eta: 9:47:45 time: 0.5576 data_time: 0.0312 memory: 21547 grad_norm: 3.8768 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6575 loss: 1.6575 2022/10/10 01:09:43 - mmengine - INFO - Epoch(train) [27][80/940] lr: 1.0000e-02 eta: 9:47:29 time: 0.3983 data_time: 0.0245 memory: 21547 grad_norm: 3.9561 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7865 loss: 1.7865 2022/10/10 01:09:54 - mmengine - INFO - Epoch(train) [27][100/940] lr: 1.0000e-02 eta: 9:47:20 time: 0.5334 data_time: 0.0306 memory: 21547 grad_norm: 3.9799 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.6615 loss: 1.6615 2022/10/10 01:10:03 - mmengine - INFO - Epoch(train) [27][120/940] lr: 1.0000e-02 eta: 9:47:08 time: 0.4769 data_time: 0.0280 memory: 21547 grad_norm: 4.0435 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7539 loss: 1.7539 2022/10/10 01:10:14 - mmengine - INFO - Epoch(train) [27][140/940] lr: 1.0000e-02 eta: 9:46:59 time: 0.5209 data_time: 0.0296 memory: 21547 grad_norm: 4.0420 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7089 loss: 1.7089 2022/10/10 01:10:24 - mmengine - INFO - Epoch(train) [27][160/940] lr: 1.0000e-02 eta: 9:46:49 time: 0.5066 data_time: 0.0251 memory: 21547 grad_norm: 3.8315 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6434 loss: 1.6434 2022/10/10 01:10:34 - mmengine - INFO - Epoch(train) [27][180/940] lr: 1.0000e-02 eta: 9:46:38 time: 0.5071 data_time: 0.0297 memory: 21547 grad_norm: 3.9711 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8062 loss: 1.8062 2022/10/10 01:10:45 - mmengine - INFO - Epoch(train) [27][200/940] lr: 1.0000e-02 eta: 9:46:29 time: 0.5271 data_time: 0.0256 memory: 21547 grad_norm: 3.9844 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7373 loss: 1.7373 2022/10/10 01:10:54 - mmengine - INFO - Epoch(train) [27][220/940] lr: 1.0000e-02 eta: 9:46:19 time: 0.4986 data_time: 0.0252 memory: 21547 grad_norm: 3.9719 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.7025 loss: 1.7025 2022/10/10 01:11:05 - mmengine - INFO - Epoch(train) [27][240/940] lr: 1.0000e-02 eta: 9:46:10 time: 0.5265 data_time: 0.0288 memory: 21547 grad_norm: 3.9725 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7176 loss: 1.7176 2022/10/10 01:11:16 - mmengine - INFO - Epoch(train) [27][260/940] lr: 1.0000e-02 eta: 9:46:01 time: 0.5279 data_time: 0.0261 memory: 21547 grad_norm: 3.9738 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5459 loss: 1.5459 2022/10/10 01:11:26 - mmengine - INFO - Epoch(train) [27][280/940] lr: 1.0000e-02 eta: 9:45:50 time: 0.5050 data_time: 0.0220 memory: 21547 grad_norm: 3.9637 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.7857 loss: 1.7857 2022/10/10 01:11:36 - mmengine - INFO - Epoch(train) [27][300/940] lr: 1.0000e-02 eta: 9:45:41 time: 0.5245 data_time: 0.0277 memory: 21547 grad_norm: 3.9828 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.6451 loss: 1.6451 2022/10/10 01:11:47 - mmengine - INFO - Epoch(train) [27][320/940] lr: 1.0000e-02 eta: 9:45:32 time: 0.5278 data_time: 0.0233 memory: 21547 grad_norm: 4.0816 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6372 loss: 1.6372 2022/10/10 01:11:55 - mmengine - INFO - Epoch(train) [27][340/940] lr: 1.0000e-02 eta: 9:45:18 time: 0.4304 data_time: 0.0327 memory: 21547 grad_norm: 3.9701 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6472 loss: 1.6472 2022/10/10 01:12:05 - mmengine - INFO - Epoch(train) [27][360/940] lr: 1.0000e-02 eta: 9:45:07 time: 0.5044 data_time: 0.0279 memory: 21547 grad_norm: 3.9583 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6411 loss: 1.6411 2022/10/10 01:12:15 - mmengine - INFO - Epoch(train) [27][380/940] lr: 1.0000e-02 eta: 9:44:55 time: 0.4608 data_time: 0.0382 memory: 21547 grad_norm: 4.0327 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7367 loss: 1.7367 2022/10/10 01:12:25 - mmengine - INFO - Epoch(train) [27][400/940] lr: 1.0000e-02 eta: 9:44:44 time: 0.4961 data_time: 0.0285 memory: 21547 grad_norm: 3.9491 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6681 loss: 1.6681 2022/10/10 01:12:35 - mmengine - INFO - Epoch(train) [27][420/940] lr: 1.0000e-02 eta: 9:44:35 time: 0.5332 data_time: 0.0268 memory: 21547 grad_norm: 3.9826 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6781 loss: 1.6781 2022/10/10 01:12:45 - mmengine - INFO - Epoch(train) [27][440/940] lr: 1.0000e-02 eta: 9:44:25 time: 0.5023 data_time: 0.0249 memory: 21547 grad_norm: 3.9659 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6216 loss: 1.6216 2022/10/10 01:12:55 - mmengine - INFO - Epoch(train) [27][460/940] lr: 1.0000e-02 eta: 9:44:14 time: 0.4994 data_time: 0.0269 memory: 21547 grad_norm: 3.9814 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6496 loss: 1.6496 2022/10/10 01:13:06 - mmengine - INFO - Epoch(train) [27][480/940] lr: 1.0000e-02 eta: 9:44:06 time: 0.5425 data_time: 0.0303 memory: 21547 grad_norm: 4.0160 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.7189 loss: 1.7189 2022/10/10 01:13:16 - mmengine - INFO - Epoch(train) [27][500/940] lr: 1.0000e-02 eta: 9:43:55 time: 0.4835 data_time: 0.0273 memory: 21547 grad_norm: 3.9132 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.6246 loss: 1.6246 2022/10/10 01:13:26 - mmengine - INFO - Epoch(train) [27][520/940] lr: 1.0000e-02 eta: 9:43:45 time: 0.5264 data_time: 0.0261 memory: 21547 grad_norm: 3.9142 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8143 loss: 1.8143 2022/10/10 01:13:36 - mmengine - INFO - Epoch(train) [27][540/940] lr: 1.0000e-02 eta: 9:43:33 time: 0.4649 data_time: 0.0267 memory: 21547 grad_norm: 3.8982 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6405 loss: 1.6405 2022/10/10 01:13:46 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 01:13:46 - mmengine - INFO - Epoch(train) [27][560/940] lr: 1.0000e-02 eta: 9:43:24 time: 0.5229 data_time: 0.0304 memory: 21547 grad_norm: 3.9936 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8335 loss: 1.8335 2022/10/10 01:13:56 - mmengine - INFO - Epoch(train) [27][580/940] lr: 1.0000e-02 eta: 9:43:13 time: 0.4894 data_time: 0.0268 memory: 21547 grad_norm: 3.9434 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6274 loss: 1.6274 2022/10/10 01:14:06 - mmengine - INFO - Epoch(train) [27][600/940] lr: 1.0000e-02 eta: 9:43:01 time: 0.4895 data_time: 0.0305 memory: 21547 grad_norm: 3.9814 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5948 loss: 1.5948 2022/10/10 01:14:16 - mmengine - INFO - Epoch(train) [27][620/940] lr: 1.0000e-02 eta: 9:42:51 time: 0.4939 data_time: 0.0281 memory: 21547 grad_norm: 3.9857 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6133 loss: 1.6133 2022/10/10 01:14:25 - mmengine - INFO - Epoch(train) [27][640/940] lr: 1.0000e-02 eta: 9:42:39 time: 0.4853 data_time: 0.0299 memory: 21547 grad_norm: 4.0690 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7530 loss: 1.7530 2022/10/10 01:14:35 - mmengine - INFO - Epoch(train) [27][660/940] lr: 1.0000e-02 eta: 9:42:27 time: 0.4784 data_time: 0.0304 memory: 21547 grad_norm: 3.9942 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7180 loss: 1.7180 2022/10/10 01:14:49 - mmengine - INFO - Epoch(train) [27][680/940] lr: 1.0000e-02 eta: 9:42:28 time: 0.6999 data_time: 0.0269 memory: 21547 grad_norm: 3.9490 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.7065 loss: 1.7065 2022/10/10 01:14:59 - mmengine - INFO - Epoch(train) [27][700/940] lr: 1.0000e-02 eta: 9:42:17 time: 0.4936 data_time: 0.0191 memory: 21547 grad_norm: 4.0131 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.6837 loss: 1.6837 2022/10/10 01:15:09 - mmengine - INFO - Epoch(train) [27][720/940] lr: 1.0000e-02 eta: 9:42:07 time: 0.5054 data_time: 0.0279 memory: 21547 grad_norm: 3.8696 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5230 loss: 1.5230 2022/10/10 01:15:18 - mmengine - INFO - Epoch(train) [27][740/940] lr: 1.0000e-02 eta: 9:41:55 time: 0.4774 data_time: 0.0341 memory: 21547 grad_norm: 4.0623 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.6817 loss: 1.6817 2022/10/10 01:15:28 - mmengine - INFO - Epoch(train) [27][760/940] lr: 1.0000e-02 eta: 9:41:44 time: 0.4949 data_time: 0.0248 memory: 21547 grad_norm: 3.9215 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6426 loss: 1.6426 2022/10/10 01:15:39 - mmengine - INFO - Epoch(train) [27][780/940] lr: 1.0000e-02 eta: 9:41:35 time: 0.5256 data_time: 0.0291 memory: 21547 grad_norm: 3.9735 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4806 loss: 1.4806 2022/10/10 01:15:49 - mmengine - INFO - Epoch(train) [27][800/940] lr: 1.0000e-02 eta: 9:41:25 time: 0.5062 data_time: 0.0268 memory: 21547 grad_norm: 3.9610 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.7080 loss: 1.7080 2022/10/10 01:15:59 - mmengine - INFO - Epoch(train) [27][820/940] lr: 1.0000e-02 eta: 9:41:14 time: 0.4940 data_time: 0.0287 memory: 21547 grad_norm: 3.8689 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7076 loss: 1.7076 2022/10/10 01:16:09 - mmengine - INFO - Epoch(train) [27][840/940] lr: 1.0000e-02 eta: 9:41:03 time: 0.4888 data_time: 0.0255 memory: 21547 grad_norm: 4.0103 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6635 loss: 1.6635 2022/10/10 01:16:19 - mmengine - INFO - Epoch(train) [27][860/940] lr: 1.0000e-02 eta: 9:40:53 time: 0.5094 data_time: 0.0245 memory: 21547 grad_norm: 3.9562 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.6906 loss: 1.6906 2022/10/10 01:16:28 - mmengine - INFO - Epoch(train) [27][880/940] lr: 1.0000e-02 eta: 9:40:41 time: 0.4830 data_time: 0.0298 memory: 21547 grad_norm: 3.9451 top1_acc: 0.4062 top5_acc: 0.8438 loss_cls: 1.6913 loss: 1.6913 2022/10/10 01:16:39 - mmengine - INFO - Epoch(train) [27][900/940] lr: 1.0000e-02 eta: 9:40:33 time: 0.5511 data_time: 0.0289 memory: 21547 grad_norm: 3.8555 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6590 loss: 1.6590 2022/10/10 01:16:49 - mmengine - INFO - Epoch(train) [27][920/940] lr: 1.0000e-02 eta: 9:40:22 time: 0.4800 data_time: 0.0292 memory: 21547 grad_norm: 4.0352 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5954 loss: 1.5954 2022/10/10 01:16:58 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 01:16:58 - mmengine - INFO - Epoch(train) [27][940/940] lr: 1.0000e-02 eta: 9:40:08 time: 0.4419 data_time: 0.0279 memory: 21547 grad_norm: 4.2351 top1_acc: 0.4286 top5_acc: 0.5714 loss_cls: 1.8121 loss: 1.8121 2022/10/10 01:16:58 - mmengine - INFO - Saving checkpoint at 27 epochs 2022/10/10 01:17:11 - mmengine - INFO - Epoch(val) [27][20/78] eta: 0:00:35 time: 0.6119 data_time: 0.5057 memory: 3269 2022/10/10 01:17:19 - mmengine - INFO - Epoch(val) [27][40/78] eta: 0:00:15 time: 0.4131 data_time: 0.3086 memory: 3269 2022/10/10 01:17:31 - mmengine - INFO - Epoch(val) [27][60/78] eta: 0:00:10 time: 0.5685 data_time: 0.4632 memory: 3269 2022/10/10 01:17:40 - mmengine - INFO - Epoch(val) [27][78/78] acc/top1: 0.6386 acc/top5: 0.8505 acc/mean1: 0.6385 2022/10/10 01:17:40 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_21.pth is removed 2022/10/10 01:17:40 - mmengine - INFO - The best checkpoint with 0.6386 acc/top1 at 27 epoch is saved to best_acc/top1_epoch_27.pth. 2022/10/10 01:17:54 - mmengine - INFO - Epoch(train) [28][20/940] lr: 1.0000e-02 eta: 9:40:07 time: 0.6674 data_time: 0.2903 memory: 21547 grad_norm: 3.9571 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6790 loss: 1.6790 2022/10/10 01:18:03 - mmengine - INFO - Epoch(train) [28][40/940] lr: 1.0000e-02 eta: 9:39:56 time: 0.4893 data_time: 0.0772 memory: 21547 grad_norm: 3.9297 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6706 loss: 1.6706 2022/10/10 01:18:14 - mmengine - INFO - Epoch(train) [28][60/940] lr: 1.0000e-02 eta: 9:39:46 time: 0.5248 data_time: 0.1210 memory: 21547 grad_norm: 3.9470 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6245 loss: 1.6245 2022/10/10 01:18:24 - mmengine - INFO - Epoch(train) [28][80/940] lr: 1.0000e-02 eta: 9:39:35 time: 0.4890 data_time: 0.0465 memory: 21547 grad_norm: 3.8990 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7636 loss: 1.7636 2022/10/10 01:18:34 - mmengine - INFO - Epoch(train) [28][100/940] lr: 1.0000e-02 eta: 9:39:26 time: 0.5243 data_time: 0.0359 memory: 21547 grad_norm: 3.9953 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6317 loss: 1.6317 2022/10/10 01:18:44 - mmengine - INFO - Epoch(train) [28][120/940] lr: 1.0000e-02 eta: 9:39:14 time: 0.4786 data_time: 0.0378 memory: 21547 grad_norm: 3.8794 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7274 loss: 1.7274 2022/10/10 01:18:54 - mmengine - INFO - Epoch(train) [28][140/940] lr: 1.0000e-02 eta: 9:39:06 time: 0.5372 data_time: 0.0297 memory: 21547 grad_norm: 3.8665 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5854 loss: 1.5854 2022/10/10 01:19:04 - mmengine - INFO - Epoch(train) [28][160/940] lr: 1.0000e-02 eta: 9:38:54 time: 0.4783 data_time: 0.0244 memory: 21547 grad_norm: 3.9694 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5604 loss: 1.5604 2022/10/10 01:19:15 - mmengine - INFO - Epoch(train) [28][180/940] lr: 1.0000e-02 eta: 9:38:46 time: 0.5433 data_time: 0.0334 memory: 21547 grad_norm: 3.8963 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6724 loss: 1.6724 2022/10/10 01:19:24 - mmengine - INFO - Epoch(train) [28][200/940] lr: 1.0000e-02 eta: 9:38:33 time: 0.4629 data_time: 0.0255 memory: 21547 grad_norm: 3.9027 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6414 loss: 1.6414 2022/10/10 01:19:35 - mmengine - INFO - Epoch(train) [28][220/940] lr: 1.0000e-02 eta: 9:38:26 time: 0.5530 data_time: 0.0300 memory: 21547 grad_norm: 4.0349 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.8104 loss: 1.8104 2022/10/10 01:19:45 - mmengine - INFO - Epoch(train) [28][240/940] lr: 1.0000e-02 eta: 9:38:13 time: 0.4708 data_time: 0.0249 memory: 21547 grad_norm: 3.9717 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.6106 loss: 1.6106 2022/10/10 01:19:55 - mmengine - INFO - Epoch(train) [28][260/940] lr: 1.0000e-02 eta: 9:38:04 time: 0.5137 data_time: 0.0325 memory: 21547 grad_norm: 3.9055 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.7265 loss: 1.7265 2022/10/10 01:20:05 - mmengine - INFO - Epoch(train) [28][280/940] lr: 1.0000e-02 eta: 9:37:52 time: 0.4878 data_time: 0.0238 memory: 21547 grad_norm: 4.0360 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7283 loss: 1.7283 2022/10/10 01:20:15 - mmengine - INFO - Epoch(train) [28][300/940] lr: 1.0000e-02 eta: 9:37:43 time: 0.5148 data_time: 0.0365 memory: 21547 grad_norm: 4.0120 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6536 loss: 1.6536 2022/10/10 01:20:24 - mmengine - INFO - Epoch(train) [28][320/940] lr: 1.0000e-02 eta: 9:37:31 time: 0.4707 data_time: 0.0551 memory: 21547 grad_norm: 4.0168 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8410 loss: 1.8410 2022/10/10 01:20:35 - mmengine - INFO - Epoch(train) [28][340/940] lr: 1.0000e-02 eta: 9:37:23 time: 0.5517 data_time: 0.1359 memory: 21547 grad_norm: 3.9523 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7428 loss: 1.7428 2022/10/10 01:20:45 - mmengine - INFO - Epoch(train) [28][360/940] lr: 1.0000e-02 eta: 9:37:12 time: 0.4985 data_time: 0.0896 memory: 21547 grad_norm: 4.0348 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6906 loss: 1.6906 2022/10/10 01:20:56 - mmengine - INFO - Epoch(train) [28][380/940] lr: 1.0000e-02 eta: 9:37:03 time: 0.5314 data_time: 0.0742 memory: 21547 grad_norm: 4.1095 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6982 loss: 1.6982 2022/10/10 01:21:06 - mmengine - INFO - Epoch(train) [28][400/940] lr: 1.0000e-02 eta: 9:36:51 time: 0.4756 data_time: 0.0237 memory: 21547 grad_norm: 3.9944 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.7080 loss: 1.7080 2022/10/10 01:21:16 - mmengine - INFO - Epoch(train) [28][420/940] lr: 1.0000e-02 eta: 9:36:42 time: 0.5219 data_time: 0.0318 memory: 21547 grad_norm: 4.0501 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6432 loss: 1.6432 2022/10/10 01:21:25 - mmengine - INFO - Epoch(train) [28][440/940] lr: 1.0000e-02 eta: 9:36:30 time: 0.4695 data_time: 0.0269 memory: 21547 grad_norm: 4.0187 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6065 loss: 1.6065 2022/10/10 01:21:35 - mmengine - INFO - Epoch(train) [28][460/940] lr: 1.0000e-02 eta: 9:36:18 time: 0.4802 data_time: 0.0285 memory: 21547 grad_norm: 3.9000 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6881 loss: 1.6881 2022/10/10 01:21:45 - mmengine - INFO - Epoch(train) [28][480/940] lr: 1.0000e-02 eta: 9:36:09 time: 0.5174 data_time: 0.0248 memory: 21547 grad_norm: 4.0056 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5862 loss: 1.5862 2022/10/10 01:21:55 - mmengine - INFO - Epoch(train) [28][500/940] lr: 1.0000e-02 eta: 9:35:58 time: 0.4944 data_time: 0.0341 memory: 21547 grad_norm: 3.9728 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.6836 loss: 1.6836 2022/10/10 01:22:05 - mmengine - INFO - Epoch(train) [28][520/940] lr: 1.0000e-02 eta: 9:35:48 time: 0.5123 data_time: 0.0300 memory: 21547 grad_norm: 4.0788 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.6314 loss: 1.6314 2022/10/10 01:22:17 - mmengine - INFO - Epoch(train) [28][540/940] lr: 1.0000e-02 eta: 9:35:41 time: 0.5583 data_time: 0.0258 memory: 21547 grad_norm: 4.0505 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7701 loss: 1.7701 2022/10/10 01:22:26 - mmengine - INFO - Epoch(train) [28][560/940] lr: 1.0000e-02 eta: 9:35:29 time: 0.4881 data_time: 0.0311 memory: 21547 grad_norm: 3.9942 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.6838 loss: 1.6838 2022/10/10 01:22:36 - mmengine - INFO - Epoch(train) [28][580/940] lr: 1.0000e-02 eta: 9:35:19 time: 0.4959 data_time: 0.0288 memory: 21547 grad_norm: 3.9804 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.7391 loss: 1.7391 2022/10/10 01:22:46 - mmengine - INFO - Epoch(train) [28][600/940] lr: 1.0000e-02 eta: 9:35:07 time: 0.4721 data_time: 0.0311 memory: 21547 grad_norm: 4.0001 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.7237 loss: 1.7237 2022/10/10 01:22:57 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 01:22:57 - mmengine - INFO - Epoch(train) [28][620/940] lr: 1.0000e-02 eta: 9:34:58 time: 0.5381 data_time: 0.0225 memory: 21547 grad_norm: 4.0589 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6684 loss: 1.6684 2022/10/10 01:23:06 - mmengine - INFO - Epoch(train) [28][640/940] lr: 1.0000e-02 eta: 9:34:47 time: 0.4830 data_time: 0.0275 memory: 21547 grad_norm: 4.0325 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5753 loss: 1.5753 2022/10/10 01:23:17 - mmengine - INFO - Epoch(train) [28][660/940] lr: 1.0000e-02 eta: 9:34:38 time: 0.5364 data_time: 0.0313 memory: 21547 grad_norm: 3.9450 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6249 loss: 1.6249 2022/10/10 01:23:27 - mmengine - INFO - Epoch(train) [28][680/940] lr: 1.0000e-02 eta: 9:34:28 time: 0.5121 data_time: 0.0227 memory: 21547 grad_norm: 4.1202 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6771 loss: 1.6771 2022/10/10 01:23:37 - mmengine - INFO - Epoch(train) [28][700/940] lr: 1.0000e-02 eta: 9:34:17 time: 0.4906 data_time: 0.0254 memory: 21547 grad_norm: 4.0082 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.6034 loss: 1.6034 2022/10/10 01:23:47 - mmengine - INFO - Epoch(train) [28][720/940] lr: 1.0000e-02 eta: 9:34:06 time: 0.4886 data_time: 0.0253 memory: 21547 grad_norm: 3.9785 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5668 loss: 1.5668 2022/10/10 01:23:58 - mmengine - INFO - Epoch(train) [28][740/940] lr: 1.0000e-02 eta: 9:33:58 time: 0.5492 data_time: 0.0363 memory: 21547 grad_norm: 4.0280 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6431 loss: 1.6431 2022/10/10 01:24:07 - mmengine - INFO - Epoch(train) [28][760/940] lr: 1.0000e-02 eta: 9:33:47 time: 0.4847 data_time: 0.0255 memory: 21547 grad_norm: 4.0791 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.5844 loss: 1.5844 2022/10/10 01:24:18 - mmengine - INFO - Epoch(train) [28][780/940] lr: 1.0000e-02 eta: 9:33:37 time: 0.5179 data_time: 0.0278 memory: 21547 grad_norm: 3.9599 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.7012 loss: 1.7012 2022/10/10 01:24:28 - mmengine - INFO - Epoch(train) [28][800/940] lr: 1.0000e-02 eta: 9:33:27 time: 0.5006 data_time: 0.0281 memory: 21547 grad_norm: 3.9990 top1_acc: 0.3125 top5_acc: 0.7188 loss_cls: 1.8500 loss: 1.8500 2022/10/10 01:24:37 - mmengine - INFO - Epoch(train) [28][820/940] lr: 1.0000e-02 eta: 9:33:15 time: 0.4782 data_time: 0.0244 memory: 21547 grad_norm: 4.0021 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7249 loss: 1.7249 2022/10/10 01:24:46 - mmengine - INFO - Epoch(train) [28][840/940] lr: 1.0000e-02 eta: 9:33:00 time: 0.4165 data_time: 0.0301 memory: 21547 grad_norm: 3.9809 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.7107 loss: 1.7107 2022/10/10 01:24:56 - mmengine - INFO - Epoch(train) [28][860/940] lr: 1.0000e-02 eta: 9:32:51 time: 0.5305 data_time: 0.0278 memory: 21547 grad_norm: 4.0072 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5863 loss: 1.5863 2022/10/10 01:25:06 - mmengine - INFO - Epoch(train) [28][880/940] lr: 1.0000e-02 eta: 9:32:39 time: 0.4761 data_time: 0.0260 memory: 21547 grad_norm: 4.0889 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6196 loss: 1.6196 2022/10/10 01:25:16 - mmengine - INFO - Epoch(train) [28][900/940] lr: 1.0000e-02 eta: 9:32:30 time: 0.5147 data_time: 0.0297 memory: 21547 grad_norm: 4.0131 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7468 loss: 1.7468 2022/10/10 01:25:26 - mmengine - INFO - Epoch(train) [28][920/940] lr: 1.0000e-02 eta: 9:32:19 time: 0.5002 data_time: 0.0436 memory: 21547 grad_norm: 3.9095 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7059 loss: 1.7059 2022/10/10 01:25:36 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 01:25:36 - mmengine - INFO - Epoch(train) [28][940/940] lr: 1.0000e-02 eta: 9:32:08 time: 0.4922 data_time: 0.0357 memory: 21547 grad_norm: 4.1976 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.5463 loss: 1.5463 2022/10/10 01:25:48 - mmengine - INFO - Epoch(val) [28][20/78] eta: 0:00:34 time: 0.6022 data_time: 0.4921 memory: 3269 2022/10/10 01:25:57 - mmengine - INFO - Epoch(val) [28][40/78] eta: 0:00:16 time: 0.4214 data_time: 0.3144 memory: 3269 2022/10/10 01:26:08 - mmengine - INFO - Epoch(val) [28][60/78] eta: 0:00:10 time: 0.5565 data_time: 0.4495 memory: 3269 2022/10/10 01:26:18 - mmengine - INFO - Epoch(val) [28][78/78] acc/top1: 0.6323 acc/top5: 0.8472 acc/mean1: 0.6321 2022/10/10 01:26:31 - mmengine - INFO - Epoch(train) [29][20/940] lr: 1.0000e-02 eta: 9:32:07 time: 0.6867 data_time: 0.3132 memory: 21547 grad_norm: 3.9273 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.6183 loss: 1.6183 2022/10/10 01:26:41 - mmengine - INFO - Epoch(train) [29][40/940] lr: 1.0000e-02 eta: 9:31:57 time: 0.5055 data_time: 0.0752 memory: 21547 grad_norm: 3.9034 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5910 loss: 1.5910 2022/10/10 01:26:52 - mmengine - INFO - Epoch(train) [29][60/940] lr: 1.0000e-02 eta: 9:31:47 time: 0.5166 data_time: 0.0301 memory: 21547 grad_norm: 3.9852 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6360 loss: 1.6360 2022/10/10 01:27:02 - mmengine - INFO - Epoch(train) [29][80/940] lr: 1.0000e-02 eta: 9:31:37 time: 0.4963 data_time: 0.0248 memory: 21547 grad_norm: 3.9871 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6595 loss: 1.6595 2022/10/10 01:27:13 - mmengine - INFO - Epoch(train) [29][100/940] lr: 1.0000e-02 eta: 9:31:29 time: 0.5586 data_time: 0.0283 memory: 21547 grad_norm: 3.9198 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.6981 loss: 1.6981 2022/10/10 01:27:23 - mmengine - INFO - Epoch(train) [29][120/940] lr: 1.0000e-02 eta: 9:31:18 time: 0.4903 data_time: 0.0231 memory: 21547 grad_norm: 3.9542 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6609 loss: 1.6609 2022/10/10 01:27:34 - mmengine - INFO - Epoch(train) [29][140/940] lr: 1.0000e-02 eta: 9:31:10 time: 0.5551 data_time: 0.0258 memory: 21547 grad_norm: 3.8838 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5135 loss: 1.5135 2022/10/10 01:27:43 - mmengine - INFO - Epoch(train) [29][160/940] lr: 1.0000e-02 eta: 9:30:58 time: 0.4638 data_time: 0.0269 memory: 21547 grad_norm: 4.0296 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.6538 loss: 1.6538 2022/10/10 01:27:54 - mmengine - INFO - Epoch(train) [29][180/940] lr: 1.0000e-02 eta: 9:30:49 time: 0.5374 data_time: 0.0274 memory: 21547 grad_norm: 4.0020 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8291 loss: 1.8291 2022/10/10 01:28:04 - mmengine - INFO - Epoch(train) [29][200/940] lr: 1.0000e-02 eta: 9:30:38 time: 0.4862 data_time: 0.0315 memory: 21547 grad_norm: 4.0171 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6187 loss: 1.6187 2022/10/10 01:28:13 - mmengine - INFO - Epoch(train) [29][220/940] lr: 1.0000e-02 eta: 9:30:27 time: 0.4902 data_time: 0.0271 memory: 21547 grad_norm: 4.0377 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6744 loss: 1.6744 2022/10/10 01:28:23 - mmengine - INFO - Epoch(train) [29][240/940] lr: 1.0000e-02 eta: 9:30:15 time: 0.4722 data_time: 0.0306 memory: 21547 grad_norm: 3.9916 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6270 loss: 1.6270 2022/10/10 01:28:33 - mmengine - INFO - Epoch(train) [29][260/940] lr: 1.0000e-02 eta: 9:30:06 time: 0.5169 data_time: 0.0296 memory: 21547 grad_norm: 4.0079 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6233 loss: 1.6233 2022/10/10 01:28:43 - mmengine - INFO - Epoch(train) [29][280/940] lr: 1.0000e-02 eta: 9:29:55 time: 0.4887 data_time: 0.0319 memory: 21547 grad_norm: 3.9283 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5778 loss: 1.5778 2022/10/10 01:28:55 - mmengine - INFO - Epoch(train) [29][300/940] lr: 1.0000e-02 eta: 9:29:49 time: 0.5965 data_time: 0.0277 memory: 21547 grad_norm: 3.9733 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7746 loss: 1.7746 2022/10/10 01:29:05 - mmengine - INFO - Epoch(train) [29][320/940] lr: 1.0000e-02 eta: 9:29:39 time: 0.5049 data_time: 0.0230 memory: 21547 grad_norm: 4.0186 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.6842 loss: 1.6842 2022/10/10 01:29:16 - mmengine - INFO - Epoch(train) [29][340/940] lr: 1.0000e-02 eta: 9:29:30 time: 0.5432 data_time: 0.0239 memory: 21547 grad_norm: 4.0356 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5861 loss: 1.5861 2022/10/10 01:29:25 - mmengine - INFO - Epoch(train) [29][360/940] lr: 1.0000e-02 eta: 9:29:18 time: 0.4679 data_time: 0.0221 memory: 21547 grad_norm: 4.0367 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.6468 loss: 1.6468 2022/10/10 01:29:35 - mmengine - INFO - Epoch(train) [29][380/940] lr: 1.0000e-02 eta: 9:29:08 time: 0.5033 data_time: 0.0249 memory: 21547 grad_norm: 3.9959 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6184 loss: 1.6184 2022/10/10 01:29:45 - mmengine - INFO - Epoch(train) [29][400/940] lr: 1.0000e-02 eta: 9:28:56 time: 0.4701 data_time: 0.0240 memory: 21547 grad_norm: 4.0571 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8819 loss: 1.8819 2022/10/10 01:29:56 - mmengine - INFO - Epoch(train) [29][420/940] lr: 1.0000e-02 eta: 9:28:49 time: 0.5664 data_time: 0.0254 memory: 21547 grad_norm: 3.9888 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7406 loss: 1.7406 2022/10/10 01:30:05 - mmengine - INFO - Epoch(train) [29][440/940] lr: 1.0000e-02 eta: 9:28:36 time: 0.4677 data_time: 0.0317 memory: 21547 grad_norm: 4.0766 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5923 loss: 1.5923 2022/10/10 01:30:16 - mmengine - INFO - Epoch(train) [29][460/940] lr: 1.0000e-02 eta: 9:28:26 time: 0.5099 data_time: 0.0276 memory: 21547 grad_norm: 3.9984 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.5946 loss: 1.5946 2022/10/10 01:30:25 - mmengine - INFO - Epoch(train) [29][480/940] lr: 1.0000e-02 eta: 9:28:15 time: 0.4882 data_time: 0.0281 memory: 21547 grad_norm: 4.0975 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7245 loss: 1.7245 2022/10/10 01:30:35 - mmengine - INFO - Epoch(train) [29][500/940] lr: 1.0000e-02 eta: 9:28:05 time: 0.4982 data_time: 0.0255 memory: 21547 grad_norm: 3.9525 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7002 loss: 1.7002 2022/10/10 01:30:45 - mmengine - INFO - Epoch(train) [29][520/940] lr: 1.0000e-02 eta: 9:27:52 time: 0.4647 data_time: 0.0309 memory: 21547 grad_norm: 3.9880 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7148 loss: 1.7148 2022/10/10 01:30:55 - mmengine - INFO - Epoch(train) [29][540/940] lr: 1.0000e-02 eta: 9:27:43 time: 0.5215 data_time: 0.0269 memory: 21547 grad_norm: 4.0303 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.6538 loss: 1.6538 2022/10/10 01:31:04 - mmengine - INFO - Epoch(train) [29][560/940] lr: 1.0000e-02 eta: 9:27:30 time: 0.4542 data_time: 0.0293 memory: 21547 grad_norm: 4.0143 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6570 loss: 1.6570 2022/10/10 01:31:14 - mmengine - INFO - Epoch(train) [29][580/940] lr: 1.0000e-02 eta: 9:27:20 time: 0.5144 data_time: 0.0269 memory: 21547 grad_norm: 4.0440 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6173 loss: 1.6173 2022/10/10 01:31:24 - mmengine - INFO - Epoch(train) [29][600/940] lr: 1.0000e-02 eta: 9:27:10 time: 0.4978 data_time: 0.0369 memory: 21547 grad_norm: 4.0880 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.7624 loss: 1.7624 2022/10/10 01:31:34 - mmengine - INFO - Epoch(train) [29][620/940] lr: 1.0000e-02 eta: 9:27:00 time: 0.5080 data_time: 0.0280 memory: 21547 grad_norm: 4.0807 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7121 loss: 1.7121 2022/10/10 01:31:44 - mmengine - INFO - Epoch(train) [29][640/940] lr: 1.0000e-02 eta: 9:26:49 time: 0.4958 data_time: 0.0308 memory: 21547 grad_norm: 3.9490 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.6715 loss: 1.6715 2022/10/10 01:31:54 - mmengine - INFO - Epoch(train) [29][660/940] lr: 1.0000e-02 eta: 9:26:37 time: 0.4797 data_time: 0.0242 memory: 21547 grad_norm: 4.1117 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6145 loss: 1.6145 2022/10/10 01:32:04 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 01:32:04 - mmengine - INFO - Epoch(train) [29][680/940] lr: 1.0000e-02 eta: 9:26:27 time: 0.5027 data_time: 0.0329 memory: 21547 grad_norm: 3.9542 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7002 loss: 1.7002 2022/10/10 01:32:14 - mmengine - INFO - Epoch(train) [29][700/940] lr: 1.0000e-02 eta: 9:26:17 time: 0.5182 data_time: 0.0269 memory: 21547 grad_norm: 4.0346 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.5443 loss: 1.5443 2022/10/10 01:32:24 - mmengine - INFO - Epoch(train) [29][720/940] lr: 1.0000e-02 eta: 9:26:07 time: 0.4947 data_time: 0.0289 memory: 21547 grad_norm: 3.9914 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5733 loss: 1.5733 2022/10/10 01:32:35 - mmengine - INFO - Epoch(train) [29][740/940] lr: 1.0000e-02 eta: 9:25:57 time: 0.5166 data_time: 0.0317 memory: 21547 grad_norm: 3.9888 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7071 loss: 1.7071 2022/10/10 01:32:45 - mmengine - INFO - Epoch(train) [29][760/940] lr: 1.0000e-02 eta: 9:25:47 time: 0.5058 data_time: 0.0254 memory: 21547 grad_norm: 4.0018 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.6845 loss: 1.6845 2022/10/10 01:32:55 - mmengine - INFO - Epoch(train) [29][780/940] lr: 1.0000e-02 eta: 9:25:38 time: 0.5308 data_time: 0.0222 memory: 21547 grad_norm: 4.1228 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6170 loss: 1.6170 2022/10/10 01:33:06 - mmengine - INFO - Epoch(train) [29][800/940] lr: 1.0000e-02 eta: 9:25:28 time: 0.5168 data_time: 0.0260 memory: 21547 grad_norm: 4.0150 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6312 loss: 1.6312 2022/10/10 01:33:15 - mmengine - INFO - Epoch(train) [29][820/940] lr: 1.0000e-02 eta: 9:25:17 time: 0.4884 data_time: 0.0263 memory: 21547 grad_norm: 4.0380 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6134 loss: 1.6134 2022/10/10 01:33:25 - mmengine - INFO - Epoch(train) [29][840/940] lr: 1.0000e-02 eta: 9:25:05 time: 0.4644 data_time: 0.0262 memory: 21547 grad_norm: 4.0131 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.7088 loss: 1.7088 2022/10/10 01:33:35 - mmengine - INFO - Epoch(train) [29][860/940] lr: 1.0000e-02 eta: 9:24:55 time: 0.5068 data_time: 0.0275 memory: 21547 grad_norm: 4.1706 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.7563 loss: 1.7563 2022/10/10 01:33:45 - mmengine - INFO - Epoch(train) [29][880/940] lr: 1.0000e-02 eta: 9:24:44 time: 0.5072 data_time: 0.0292 memory: 21547 grad_norm: 4.0302 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.6725 loss: 1.6725 2022/10/10 01:33:55 - mmengine - INFO - Epoch(train) [29][900/940] lr: 1.0000e-02 eta: 9:24:34 time: 0.4984 data_time: 0.0264 memory: 21547 grad_norm: 4.0368 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.5875 loss: 1.5875 2022/10/10 01:34:06 - mmengine - INFO - Epoch(train) [29][920/940] lr: 1.0000e-02 eta: 9:24:25 time: 0.5284 data_time: 0.0368 memory: 21547 grad_norm: 4.0425 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.7037 loss: 1.7037 2022/10/10 01:34:15 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 01:34:15 - mmengine - INFO - Epoch(train) [29][940/940] lr: 1.0000e-02 eta: 9:24:12 time: 0.4558 data_time: 0.0230 memory: 21547 grad_norm: 4.2528 top1_acc: 0.4286 top5_acc: 0.5714 loss_cls: 1.6053 loss: 1.6053 2022/10/10 01:34:27 - mmengine - INFO - Epoch(val) [29][20/78] eta: 0:00:34 time: 0.6016 data_time: 0.4930 memory: 3269 2022/10/10 01:34:35 - mmengine - INFO - Epoch(val) [29][40/78] eta: 0:00:16 time: 0.4251 data_time: 0.3163 memory: 3269 2022/10/10 01:34:46 - mmengine - INFO - Epoch(val) [29][60/78] eta: 0:00:10 time: 0.5579 data_time: 0.4512 memory: 3269 2022/10/10 01:34:56 - mmengine - INFO - Epoch(val) [29][78/78] acc/top1: 0.6263 acc/top5: 0.8409 acc/mean1: 0.6262 2022/10/10 01:35:10 - mmengine - INFO - Epoch(train) [30][20/940] lr: 1.0000e-02 eta: 9:24:11 time: 0.6928 data_time: 0.2464 memory: 21547 grad_norm: 3.9816 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.7725 loss: 1.7725 2022/10/10 01:35:19 - mmengine - INFO - Epoch(train) [30][40/940] lr: 1.0000e-02 eta: 9:23:59 time: 0.4648 data_time: 0.0315 memory: 21547 grad_norm: 4.0232 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.6419 loss: 1.6419 2022/10/10 01:35:30 - mmengine - INFO - Epoch(train) [30][60/940] lr: 1.0000e-02 eta: 9:23:51 time: 0.5527 data_time: 0.0437 memory: 21547 grad_norm: 3.9179 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5969 loss: 1.5969 2022/10/10 01:35:41 - mmengine - INFO - Epoch(train) [30][80/940] lr: 1.0000e-02 eta: 9:23:41 time: 0.5050 data_time: 0.0319 memory: 21547 grad_norm: 3.9740 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5341 loss: 1.5341 2022/10/10 01:35:51 - mmengine - INFO - Epoch(train) [30][100/940] lr: 1.0000e-02 eta: 9:23:30 time: 0.5019 data_time: 0.0301 memory: 21547 grad_norm: 4.0725 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.6293 loss: 1.6293 2022/10/10 01:36:00 - mmengine - INFO - Epoch(train) [30][120/940] lr: 1.0000e-02 eta: 9:23:19 time: 0.4881 data_time: 0.0243 memory: 21547 grad_norm: 4.0165 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5923 loss: 1.5923 2022/10/10 01:36:11 - mmengine - INFO - Epoch(train) [30][140/940] lr: 1.0000e-02 eta: 9:23:11 time: 0.5406 data_time: 0.0301 memory: 21547 grad_norm: 3.9188 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.5379 loss: 1.5379 2022/10/10 01:36:21 - mmengine - INFO - Epoch(train) [30][160/940] lr: 1.0000e-02 eta: 9:22:59 time: 0.4801 data_time: 0.0280 memory: 21547 grad_norm: 4.0976 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7448 loss: 1.7448 2022/10/10 01:36:31 - mmengine - INFO - Epoch(train) [30][180/940] lr: 1.0000e-02 eta: 9:22:50 time: 0.5223 data_time: 0.0351 memory: 21547 grad_norm: 4.0591 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6542 loss: 1.6542 2022/10/10 01:36:41 - mmengine - INFO - Epoch(train) [30][200/940] lr: 1.0000e-02 eta: 9:22:39 time: 0.5005 data_time: 0.0278 memory: 21547 grad_norm: 4.0163 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5585 loss: 1.5585 2022/10/10 01:36:52 - mmengine - INFO - Epoch(train) [30][220/940] lr: 1.0000e-02 eta: 9:22:29 time: 0.5159 data_time: 0.0270 memory: 21547 grad_norm: 4.0183 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.7678 loss: 1.7678 2022/10/10 01:37:01 - mmengine - INFO - Epoch(train) [30][240/940] lr: 1.0000e-02 eta: 9:22:18 time: 0.4786 data_time: 0.0313 memory: 21547 grad_norm: 4.0555 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 1.6926 loss: 1.6926 2022/10/10 01:37:12 - mmengine - INFO - Epoch(train) [30][260/940] lr: 1.0000e-02 eta: 9:22:10 time: 0.5624 data_time: 0.0290 memory: 21547 grad_norm: 3.9891 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6084 loss: 1.6084 2022/10/10 01:37:22 - mmengine - INFO - Epoch(train) [30][280/940] lr: 1.0000e-02 eta: 9:21:59 time: 0.4817 data_time: 0.0316 memory: 21547 grad_norm: 4.0627 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.7226 loss: 1.7226 2022/10/10 01:37:33 - mmengine - INFO - Epoch(train) [30][300/940] lr: 1.0000e-02 eta: 9:21:51 time: 0.5424 data_time: 0.0276 memory: 21547 grad_norm: 4.0340 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6551 loss: 1.6551 2022/10/10 01:37:42 - mmengine - INFO - Epoch(train) [30][320/940] lr: 1.0000e-02 eta: 9:21:39 time: 0.4714 data_time: 0.0256 memory: 21547 grad_norm: 4.0338 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8060 loss: 1.8060 2022/10/10 01:37:52 - mmengine - INFO - Epoch(train) [30][340/940] lr: 1.0000e-02 eta: 9:21:27 time: 0.4750 data_time: 0.0249 memory: 21547 grad_norm: 4.0265 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7757 loss: 1.7757 2022/10/10 01:38:01 - mmengine - INFO - Epoch(train) [30][360/940] lr: 1.0000e-02 eta: 9:21:15 time: 0.4691 data_time: 0.0252 memory: 21547 grad_norm: 4.0243 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6155 loss: 1.6155 2022/10/10 01:38:11 - mmengine - INFO - Epoch(train) [30][380/940] lr: 1.0000e-02 eta: 9:21:05 time: 0.5141 data_time: 0.0249 memory: 21547 grad_norm: 4.0072 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6535 loss: 1.6535 2022/10/10 01:38:21 - mmengine - INFO - Epoch(train) [30][400/940] lr: 1.0000e-02 eta: 9:20:54 time: 0.4862 data_time: 0.0476 memory: 21547 grad_norm: 4.0226 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6324 loss: 1.6324 2022/10/10 01:38:31 - mmengine - INFO - Epoch(train) [30][420/940] lr: 1.0000e-02 eta: 9:20:44 time: 0.5085 data_time: 0.0230 memory: 21547 grad_norm: 3.9397 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7476 loss: 1.7476 2022/10/10 01:38:41 - mmengine - INFO - Epoch(train) [30][440/940] lr: 1.0000e-02 eta: 9:20:33 time: 0.4902 data_time: 0.0266 memory: 21547 grad_norm: 4.0140 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.5745 loss: 1.5745 2022/10/10 01:38:51 - mmengine - INFO - Epoch(train) [30][460/940] lr: 1.0000e-02 eta: 9:20:22 time: 0.4944 data_time: 0.0310 memory: 21547 grad_norm: 3.9908 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7070 loss: 1.7070 2022/10/10 01:39:01 - mmengine - INFO - Epoch(train) [30][480/940] lr: 1.0000e-02 eta: 9:20:11 time: 0.4757 data_time: 0.0288 memory: 21547 grad_norm: 4.0210 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.7405 loss: 1.7405 2022/10/10 01:39:11 - mmengine - INFO - Epoch(train) [30][500/940] lr: 1.0000e-02 eta: 9:20:02 time: 0.5429 data_time: 0.0314 memory: 21547 grad_norm: 4.0919 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.6464 loss: 1.6464 2022/10/10 01:39:22 - mmengine - INFO - Epoch(train) [30][520/940] lr: 1.0000e-02 eta: 9:19:52 time: 0.5081 data_time: 0.0316 memory: 21547 grad_norm: 4.0189 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.6443 loss: 1.6443 2022/10/10 01:39:33 - mmengine - INFO - Epoch(train) [30][540/940] lr: 1.0000e-02 eta: 9:19:44 time: 0.5508 data_time: 0.0258 memory: 21547 grad_norm: 4.0122 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.6496 loss: 1.6496 2022/10/10 01:39:42 - mmengine - INFO - Epoch(train) [30][560/940] lr: 1.0000e-02 eta: 9:19:33 time: 0.4843 data_time: 0.0294 memory: 21547 grad_norm: 3.9801 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6355 loss: 1.6355 2022/10/10 01:39:52 - mmengine - INFO - Epoch(train) [30][580/940] lr: 1.0000e-02 eta: 9:19:23 time: 0.5084 data_time: 0.0290 memory: 21547 grad_norm: 4.1847 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7145 loss: 1.7145 2022/10/10 01:40:02 - mmengine - INFO - Epoch(train) [30][600/940] lr: 1.0000e-02 eta: 9:19:10 time: 0.4587 data_time: 0.0286 memory: 21547 grad_norm: 4.0530 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7021 loss: 1.7021 2022/10/10 01:40:12 - mmengine - INFO - Epoch(train) [30][620/940] lr: 1.0000e-02 eta: 9:19:00 time: 0.5132 data_time: 0.0281 memory: 21547 grad_norm: 4.0767 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6966 loss: 1.6966 2022/10/10 01:40:22 - mmengine - INFO - Epoch(train) [30][640/940] lr: 1.0000e-02 eta: 9:18:51 time: 0.5169 data_time: 0.0278 memory: 21547 grad_norm: 4.0895 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7026 loss: 1.7026 2022/10/10 01:40:32 - mmengine - INFO - Epoch(train) [30][660/940] lr: 1.0000e-02 eta: 9:18:40 time: 0.4995 data_time: 0.0287 memory: 21547 grad_norm: 3.9897 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.5510 loss: 1.5510 2022/10/10 01:40:42 - mmengine - INFO - Epoch(train) [30][680/940] lr: 1.0000e-02 eta: 9:18:29 time: 0.4834 data_time: 0.0294 memory: 21547 grad_norm: 3.9960 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6902 loss: 1.6902 2022/10/10 01:40:52 - mmengine - INFO - Epoch(train) [30][700/940] lr: 1.0000e-02 eta: 9:18:19 time: 0.5213 data_time: 0.0284 memory: 21547 grad_norm: 4.0000 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5686 loss: 1.5686 2022/10/10 01:41:02 - mmengine - INFO - Epoch(train) [30][720/940] lr: 1.0000e-02 eta: 9:18:08 time: 0.4894 data_time: 0.0249 memory: 21547 grad_norm: 3.9637 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.6270 loss: 1.6270 2022/10/10 01:41:12 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 01:41:12 - mmengine - INFO - Epoch(train) [30][740/940] lr: 1.0000e-02 eta: 9:17:59 time: 0.5146 data_time: 0.0248 memory: 21547 grad_norm: 4.1509 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6920 loss: 1.6920 2022/10/10 01:41:23 - mmengine - INFO - Epoch(train) [30][760/940] lr: 1.0000e-02 eta: 9:17:49 time: 0.5210 data_time: 0.0263 memory: 21547 grad_norm: 3.9746 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.6325 loss: 1.6325 2022/10/10 01:41:33 - mmengine - INFO - Epoch(train) [30][780/940] lr: 1.0000e-02 eta: 9:17:40 time: 0.5231 data_time: 0.0251 memory: 21547 grad_norm: 4.0332 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6136 loss: 1.6136 2022/10/10 01:41:43 - mmengine - INFO - Epoch(train) [30][800/940] lr: 1.0000e-02 eta: 9:17:28 time: 0.4749 data_time: 0.0304 memory: 21547 grad_norm: 3.9202 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5863 loss: 1.5863 2022/10/10 01:41:54 - mmengine - INFO - Epoch(train) [30][820/940] lr: 1.0000e-02 eta: 9:17:20 time: 0.5462 data_time: 0.0260 memory: 21547 grad_norm: 4.1222 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6094 loss: 1.6094 2022/10/10 01:42:04 - mmengine - INFO - Epoch(train) [30][840/940] lr: 1.0000e-02 eta: 9:17:10 time: 0.5209 data_time: 0.0273 memory: 21547 grad_norm: 4.1098 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.7675 loss: 1.7675 2022/10/10 01:42:15 - mmengine - INFO - Epoch(train) [30][860/940] lr: 1.0000e-02 eta: 9:17:01 time: 0.5197 data_time: 0.0253 memory: 21547 grad_norm: 4.0976 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.5838 loss: 1.5838 2022/10/10 01:42:25 - mmengine - INFO - Epoch(train) [30][880/940] lr: 1.0000e-02 eta: 9:16:50 time: 0.5036 data_time: 0.0233 memory: 21547 grad_norm: 4.0258 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6306 loss: 1.6306 2022/10/10 01:42:35 - mmengine - INFO - Epoch(train) [30][900/940] lr: 1.0000e-02 eta: 9:16:41 time: 0.5317 data_time: 0.0344 memory: 21547 grad_norm: 4.0922 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7352 loss: 1.7352 2022/10/10 01:42:45 - mmengine - INFO - Epoch(train) [30][920/940] lr: 1.0000e-02 eta: 9:16:30 time: 0.4846 data_time: 0.0285 memory: 21547 grad_norm: 4.0645 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7109 loss: 1.7109 2022/10/10 01:42:54 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 01:42:54 - mmengine - INFO - Epoch(train) [30][940/940] lr: 1.0000e-02 eta: 9:16:17 time: 0.4535 data_time: 0.0228 memory: 21547 grad_norm: 4.3378 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.7224 loss: 1.7224 2022/10/10 01:42:54 - mmengine - INFO - Saving checkpoint at 30 epochs 2022/10/10 01:43:07 - mmengine - INFO - Epoch(val) [30][20/78] eta: 0:00:35 time: 0.6059 data_time: 0.5015 memory: 3269 2022/10/10 01:43:15 - mmengine - INFO - Epoch(val) [30][40/78] eta: 0:00:15 time: 0.4188 data_time: 0.3127 memory: 3269 2022/10/10 01:43:27 - mmengine - INFO - Epoch(val) [30][60/78] eta: 0:00:10 time: 0.5602 data_time: 0.4552 memory: 3269 2022/10/10 01:43:36 - mmengine - INFO - Epoch(val) [30][78/78] acc/top1: 0.6277 acc/top5: 0.8457 acc/mean1: 0.6275 2022/10/10 01:43:50 - mmengine - INFO - Epoch(train) [31][20/940] lr: 1.0000e-02 eta: 9:16:17 time: 0.7055 data_time: 0.2220 memory: 21547 grad_norm: 4.0509 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.7454 loss: 1.7454 2022/10/10 01:44:00 - mmengine - INFO - Epoch(train) [31][40/940] lr: 1.0000e-02 eta: 9:16:05 time: 0.4837 data_time: 0.0221 memory: 21547 grad_norm: 3.9676 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.6400 loss: 1.6400 2022/10/10 01:44:10 - mmengine - INFO - Epoch(train) [31][60/940] lr: 1.0000e-02 eta: 9:15:55 time: 0.5071 data_time: 0.0541 memory: 21547 grad_norm: 4.0178 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6306 loss: 1.6306 2022/10/10 01:44:20 - mmengine - INFO - Epoch(train) [31][80/940] lr: 1.0000e-02 eta: 9:15:44 time: 0.4878 data_time: 0.1098 memory: 21547 grad_norm: 3.9442 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5864 loss: 1.5864 2022/10/10 01:44:30 - mmengine - INFO - Epoch(train) [31][100/940] lr: 1.0000e-02 eta: 9:15:35 time: 0.5331 data_time: 0.0487 memory: 21547 grad_norm: 4.1260 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.6031 loss: 1.6031 2022/10/10 01:44:40 - mmengine - INFO - Epoch(train) [31][120/940] lr: 1.0000e-02 eta: 9:15:24 time: 0.4912 data_time: 0.0251 memory: 21547 grad_norm: 4.0330 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6258 loss: 1.6258 2022/10/10 01:44:51 - mmengine - INFO - Epoch(train) [31][140/940] lr: 1.0000e-02 eta: 9:15:15 time: 0.5347 data_time: 0.0301 memory: 21547 grad_norm: 4.0544 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6347 loss: 1.6347 2022/10/10 01:45:00 - mmengine - INFO - Epoch(train) [31][160/940] lr: 1.0000e-02 eta: 9:15:03 time: 0.4624 data_time: 0.0260 memory: 21547 grad_norm: 3.9370 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.5367 loss: 1.5367 2022/10/10 01:45:11 - mmengine - INFO - Epoch(train) [31][180/940] lr: 1.0000e-02 eta: 9:14:54 time: 0.5407 data_time: 0.0295 memory: 21547 grad_norm: 4.1191 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.5433 loss: 1.5433 2022/10/10 01:45:21 - mmengine - INFO - Epoch(train) [31][200/940] lr: 1.0000e-02 eta: 9:14:44 time: 0.4952 data_time: 0.0259 memory: 21547 grad_norm: 3.9961 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.6272 loss: 1.6272 2022/10/10 01:45:31 - mmengine - INFO - Epoch(train) [31][220/940] lr: 1.0000e-02 eta: 9:14:33 time: 0.4988 data_time: 0.0310 memory: 21547 grad_norm: 3.9927 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5584 loss: 1.5584 2022/10/10 01:45:41 - mmengine - INFO - Epoch(train) [31][240/940] lr: 1.0000e-02 eta: 9:14:23 time: 0.5090 data_time: 0.0253 memory: 21547 grad_norm: 4.0609 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5888 loss: 1.5888 2022/10/10 01:45:51 - mmengine - INFO - Epoch(train) [31][260/940] lr: 1.0000e-02 eta: 9:14:12 time: 0.4898 data_time: 0.0341 memory: 21547 grad_norm: 3.9615 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6956 loss: 1.6956 2022/10/10 01:46:01 - mmengine - INFO - Epoch(train) [31][280/940] lr: 1.0000e-02 eta: 9:14:03 time: 0.5359 data_time: 0.0258 memory: 21547 grad_norm: 3.9453 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5825 loss: 1.5825 2022/10/10 01:46:12 - mmengine - INFO - Epoch(train) [31][300/940] lr: 1.0000e-02 eta: 9:13:53 time: 0.5117 data_time: 0.0245 memory: 21547 grad_norm: 3.9578 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.6319 loss: 1.6319 2022/10/10 01:46:22 - mmengine - INFO - Epoch(train) [31][320/940] lr: 1.0000e-02 eta: 9:13:44 time: 0.5225 data_time: 0.0280 memory: 21547 grad_norm: 4.0625 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5830 loss: 1.5830 2022/10/10 01:46:32 - mmengine - INFO - Epoch(train) [31][340/940] lr: 1.0000e-02 eta: 9:13:32 time: 0.4750 data_time: 0.0260 memory: 21547 grad_norm: 3.9986 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5238 loss: 1.5238 2022/10/10 01:46:42 - mmengine - INFO - Epoch(train) [31][360/940] lr: 1.0000e-02 eta: 9:13:24 time: 0.5390 data_time: 0.0318 memory: 21547 grad_norm: 4.0177 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6032 loss: 1.6032 2022/10/10 01:46:51 - mmengine - INFO - Epoch(train) [31][380/940] lr: 1.0000e-02 eta: 9:13:11 time: 0.4535 data_time: 0.0235 memory: 21547 grad_norm: 4.1814 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7420 loss: 1.7420 2022/10/10 01:47:02 - mmengine - INFO - Epoch(train) [31][400/940] lr: 1.0000e-02 eta: 9:13:01 time: 0.5204 data_time: 0.0260 memory: 21547 grad_norm: 4.0781 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6388 loss: 1.6388 2022/10/10 01:47:12 - mmengine - INFO - Epoch(train) [31][420/940] lr: 1.0000e-02 eta: 9:12:51 time: 0.4923 data_time: 0.0340 memory: 21547 grad_norm: 3.9795 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6359 loss: 1.6359 2022/10/10 01:47:21 - mmengine - INFO - Epoch(train) [31][440/940] lr: 1.0000e-02 eta: 9:12:39 time: 0.4842 data_time: 0.0288 memory: 21547 grad_norm: 3.9569 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.5606 loss: 1.5606 2022/10/10 01:47:31 - mmengine - INFO - Epoch(train) [31][460/940] lr: 1.0000e-02 eta: 9:12:29 time: 0.4912 data_time: 0.0268 memory: 21547 grad_norm: 4.0599 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6222 loss: 1.6222 2022/10/10 01:47:42 - mmengine - INFO - Epoch(train) [31][480/940] lr: 1.0000e-02 eta: 9:12:19 time: 0.5317 data_time: 0.0317 memory: 21547 grad_norm: 4.0739 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.7502 loss: 1.7502 2022/10/10 01:47:52 - mmengine - INFO - Epoch(train) [31][500/940] lr: 1.0000e-02 eta: 9:12:10 time: 0.5289 data_time: 0.0271 memory: 21547 grad_norm: 4.0169 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7473 loss: 1.7473 2022/10/10 01:48:02 - mmengine - INFO - Epoch(train) [31][520/940] lr: 1.0000e-02 eta: 9:11:58 time: 0.4638 data_time: 0.0281 memory: 21547 grad_norm: 4.0694 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6140 loss: 1.6140 2022/10/10 01:48:12 - mmengine - INFO - Epoch(train) [31][540/940] lr: 1.0000e-02 eta: 9:11:48 time: 0.5001 data_time: 0.0262 memory: 21547 grad_norm: 4.0758 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5461 loss: 1.5461 2022/10/10 01:48:23 - mmengine - INFO - Epoch(train) [31][560/940] lr: 1.0000e-02 eta: 9:11:41 time: 0.5897 data_time: 0.0288 memory: 21547 grad_norm: 3.9993 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.5900 loss: 1.5900 2022/10/10 01:48:33 - mmengine - INFO - Epoch(train) [31][580/940] lr: 1.0000e-02 eta: 9:11:29 time: 0.4537 data_time: 0.0255 memory: 21547 grad_norm: 4.0367 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4860 loss: 1.4860 2022/10/10 01:48:42 - mmengine - INFO - Epoch(train) [31][600/940] lr: 1.0000e-02 eta: 9:11:18 time: 0.4872 data_time: 0.0247 memory: 21547 grad_norm: 4.1038 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6474 loss: 1.6474 2022/10/10 01:48:52 - mmengine - INFO - Epoch(train) [31][620/940] lr: 1.0000e-02 eta: 9:11:06 time: 0.4786 data_time: 0.0284 memory: 21547 grad_norm: 4.0087 top1_acc: 0.5312 top5_acc: 0.6250 loss_cls: 1.6961 loss: 1.6961 2022/10/10 01:49:02 - mmengine - INFO - Epoch(train) [31][640/940] lr: 1.0000e-02 eta: 9:10:57 time: 0.5299 data_time: 0.0271 memory: 21547 grad_norm: 4.0513 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6308 loss: 1.6308 2022/10/10 01:49:12 - mmengine - INFO - Epoch(train) [31][660/940] lr: 1.0000e-02 eta: 9:10:45 time: 0.4687 data_time: 0.0250 memory: 21547 grad_norm: 4.0372 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6351 loss: 1.6351 2022/10/10 01:49:23 - mmengine - INFO - Epoch(train) [31][680/940] lr: 1.0000e-02 eta: 9:10:37 time: 0.5567 data_time: 0.0272 memory: 21547 grad_norm: 3.9859 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6298 loss: 1.6298 2022/10/10 01:49:33 - mmengine - INFO - Epoch(train) [31][700/940] lr: 1.0000e-02 eta: 9:10:26 time: 0.4913 data_time: 0.0265 memory: 21547 grad_norm: 4.0214 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6809 loss: 1.6809 2022/10/10 01:49:42 - mmengine - INFO - Epoch(train) [31][720/940] lr: 1.0000e-02 eta: 9:10:15 time: 0.4716 data_time: 0.0366 memory: 21547 grad_norm: 4.0959 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6439 loss: 1.6439 2022/10/10 01:49:52 - mmengine - INFO - Epoch(train) [31][740/940] lr: 1.0000e-02 eta: 9:10:04 time: 0.4971 data_time: 0.0261 memory: 21547 grad_norm: 4.0149 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6629 loss: 1.6629 2022/10/10 01:50:02 - mmengine - INFO - Epoch(train) [31][760/940] lr: 1.0000e-02 eta: 9:09:54 time: 0.5008 data_time: 0.0335 memory: 21547 grad_norm: 4.1138 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.6986 loss: 1.6986 2022/10/10 01:50:12 - mmengine - INFO - Epoch(train) [31][780/940] lr: 1.0000e-02 eta: 9:09:43 time: 0.5024 data_time: 0.0275 memory: 21547 grad_norm: 4.0180 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.6106 loss: 1.6106 2022/10/10 01:50:23 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 01:50:23 - mmengine - INFO - Epoch(train) [31][800/940] lr: 1.0000e-02 eta: 9:09:36 time: 0.5622 data_time: 0.0256 memory: 21547 grad_norm: 4.0195 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6240 loss: 1.6240 2022/10/10 01:50:34 - mmengine - INFO - Epoch(train) [31][820/940] lr: 1.0000e-02 eta: 9:09:25 time: 0.5015 data_time: 0.0318 memory: 21547 grad_norm: 4.0615 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.5159 loss: 1.5159 2022/10/10 01:50:43 - mmengine - INFO - Epoch(train) [31][840/940] lr: 1.0000e-02 eta: 9:09:14 time: 0.4896 data_time: 0.0264 memory: 21547 grad_norm: 4.1169 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.5889 loss: 1.5889 2022/10/10 01:50:53 - mmengine - INFO - Epoch(train) [31][860/940] lr: 1.0000e-02 eta: 9:09:03 time: 0.4849 data_time: 0.0279 memory: 21547 grad_norm: 4.1587 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6994 loss: 1.6994 2022/10/10 01:51:04 - mmengine - INFO - Epoch(train) [31][880/940] lr: 1.0000e-02 eta: 9:08:54 time: 0.5351 data_time: 0.0255 memory: 21547 grad_norm: 4.1171 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6963 loss: 1.6963 2022/10/10 01:51:13 - mmengine - INFO - Epoch(train) [31][900/940] lr: 1.0000e-02 eta: 9:08:43 time: 0.4824 data_time: 0.0351 memory: 21547 grad_norm: 4.0439 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7377 loss: 1.7377 2022/10/10 01:51:24 - mmengine - INFO - Epoch(train) [31][920/940] lr: 1.0000e-02 eta: 9:08:34 time: 0.5312 data_time: 0.0288 memory: 21547 grad_norm: 4.0354 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6483 loss: 1.6483 2022/10/10 01:51:33 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 01:51:33 - mmengine - INFO - Epoch(train) [31][940/940] lr: 1.0000e-02 eta: 9:08:20 time: 0.4276 data_time: 0.0212 memory: 21547 grad_norm: 4.3412 top1_acc: 0.1429 top5_acc: 0.5714 loss_cls: 1.8497 loss: 1.8497 2022/10/10 01:51:45 - mmengine - INFO - Epoch(val) [31][20/78] eta: 0:00:35 time: 0.6069 data_time: 0.4975 memory: 3269 2022/10/10 01:51:53 - mmengine - INFO - Epoch(val) [31][40/78] eta: 0:00:15 time: 0.4165 data_time: 0.3101 memory: 3269 2022/10/10 01:52:04 - mmengine - INFO - Epoch(val) [31][60/78] eta: 0:00:10 time: 0.5630 data_time: 0.4561 memory: 3269 2022/10/10 01:52:14 - mmengine - INFO - Epoch(val) [31][78/78] acc/top1: 0.6347 acc/top5: 0.8479 acc/mean1: 0.6346 2022/10/10 01:52:28 - mmengine - INFO - Epoch(train) [32][20/940] lr: 1.0000e-02 eta: 9:08:19 time: 0.7082 data_time: 0.3252 memory: 21547 grad_norm: 3.9253 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6234 loss: 1.6234 2022/10/10 01:52:38 - mmengine - INFO - Epoch(train) [32][40/940] lr: 1.0000e-02 eta: 9:08:07 time: 0.4698 data_time: 0.0970 memory: 21547 grad_norm: 4.1056 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7025 loss: 1.7025 2022/10/10 01:52:48 - mmengine - INFO - Epoch(train) [32][60/940] lr: 1.0000e-02 eta: 9:07:58 time: 0.5265 data_time: 0.1283 memory: 21547 grad_norm: 3.9869 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6855 loss: 1.6855 2022/10/10 01:52:58 - mmengine - INFO - Epoch(train) [32][80/940] lr: 1.0000e-02 eta: 9:07:47 time: 0.4991 data_time: 0.0305 memory: 21547 grad_norm: 4.0047 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6178 loss: 1.6178 2022/10/10 01:53:10 - mmengine - INFO - Epoch(train) [32][100/940] lr: 1.0000e-02 eta: 9:07:40 time: 0.5704 data_time: 0.0276 memory: 21547 grad_norm: 4.1400 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6412 loss: 1.6412 2022/10/10 01:53:19 - mmengine - INFO - Epoch(train) [32][120/940] lr: 1.0000e-02 eta: 9:07:27 time: 0.4444 data_time: 0.0231 memory: 21547 grad_norm: 4.1094 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.5779 loss: 1.5779 2022/10/10 01:53:29 - mmengine - INFO - Epoch(train) [32][140/940] lr: 1.0000e-02 eta: 9:07:17 time: 0.5006 data_time: 0.0408 memory: 21547 grad_norm: 3.9867 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 1.7212 loss: 1.7212 2022/10/10 01:53:38 - mmengine - INFO - Epoch(train) [32][160/940] lr: 1.0000e-02 eta: 9:07:05 time: 0.4851 data_time: 0.0273 memory: 21547 grad_norm: 4.0026 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6579 loss: 1.6579 2022/10/10 01:53:49 - mmengine - INFO - Epoch(train) [32][180/940] lr: 1.0000e-02 eta: 9:06:56 time: 0.5228 data_time: 0.0316 memory: 21547 grad_norm: 4.0058 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4610 loss: 1.4610 2022/10/10 01:53:59 - mmengine - INFO - Epoch(train) [32][200/940] lr: 1.0000e-02 eta: 9:06:47 time: 0.5264 data_time: 0.0254 memory: 21547 grad_norm: 3.9857 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6970 loss: 1.6970 2022/10/10 01:54:10 - mmengine - INFO - Epoch(train) [32][220/940] lr: 1.0000e-02 eta: 9:06:38 time: 0.5413 data_time: 0.0290 memory: 21547 grad_norm: 4.0064 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5759 loss: 1.5759 2022/10/10 01:54:19 - mmengine - INFO - Epoch(train) [32][240/940] lr: 1.0000e-02 eta: 9:06:26 time: 0.4692 data_time: 0.0272 memory: 21547 grad_norm: 4.0270 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.6883 loss: 1.6883 2022/10/10 01:54:30 - mmengine - INFO - Epoch(train) [32][260/940] lr: 1.0000e-02 eta: 9:06:16 time: 0.5067 data_time: 0.0265 memory: 21547 grad_norm: 4.0792 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7445 loss: 1.7445 2022/10/10 01:54:40 - mmengine - INFO - Epoch(train) [32][280/940] lr: 1.0000e-02 eta: 9:06:07 time: 0.5341 data_time: 0.0295 memory: 21547 grad_norm: 4.0408 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4837 loss: 1.4837 2022/10/10 01:54:51 - mmengine - INFO - Epoch(train) [32][300/940] lr: 1.0000e-02 eta: 9:05:58 time: 0.5330 data_time: 0.0348 memory: 21547 grad_norm: 4.1353 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7080 loss: 1.7080 2022/10/10 01:55:01 - mmengine - INFO - Epoch(train) [32][320/940] lr: 1.0000e-02 eta: 9:05:47 time: 0.4984 data_time: 0.0275 memory: 21547 grad_norm: 4.0798 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5605 loss: 1.5605 2022/10/10 01:55:12 - mmengine - INFO - Epoch(train) [32][340/940] lr: 1.0000e-02 eta: 9:05:38 time: 0.5323 data_time: 0.0237 memory: 21547 grad_norm: 4.1335 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5461 loss: 1.5461 2022/10/10 01:55:21 - mmengine - INFO - Epoch(train) [32][360/940] lr: 1.0000e-02 eta: 9:05:27 time: 0.4892 data_time: 0.0218 memory: 21547 grad_norm: 4.0032 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.6794 loss: 1.6794 2022/10/10 01:55:32 - mmengine - INFO - Epoch(train) [32][380/940] lr: 1.0000e-02 eta: 9:05:19 time: 0.5421 data_time: 0.0318 memory: 21547 grad_norm: 4.0673 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4902 loss: 1.4902 2022/10/10 01:55:42 - mmengine - INFO - Epoch(train) [32][400/940] lr: 1.0000e-02 eta: 9:05:08 time: 0.4879 data_time: 0.0261 memory: 21547 grad_norm: 4.0482 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5505 loss: 1.5505 2022/10/10 01:55:52 - mmengine - INFO - Epoch(train) [32][420/940] lr: 1.0000e-02 eta: 9:04:58 time: 0.5253 data_time: 0.0258 memory: 21547 grad_norm: 3.9461 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6734 loss: 1.6734 2022/10/10 01:56:02 - mmengine - INFO - Epoch(train) [32][440/940] lr: 1.0000e-02 eta: 9:04:47 time: 0.4824 data_time: 0.0246 memory: 21547 grad_norm: 3.9719 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6011 loss: 1.6011 2022/10/10 01:56:12 - mmengine - INFO - Epoch(train) [32][460/940] lr: 1.0000e-02 eta: 9:04:37 time: 0.4977 data_time: 0.0269 memory: 21547 grad_norm: 4.1049 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5749 loss: 1.5749 2022/10/10 01:56:22 - mmengine - INFO - Epoch(train) [32][480/940] lr: 1.0000e-02 eta: 9:04:26 time: 0.4866 data_time: 0.0265 memory: 21547 grad_norm: 4.0639 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5413 loss: 1.5413 2022/10/10 01:56:32 - mmengine - INFO - Epoch(train) [32][500/940] lr: 1.0000e-02 eta: 9:04:15 time: 0.4883 data_time: 0.0278 memory: 21547 grad_norm: 4.1039 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.7410 loss: 1.7410 2022/10/10 01:56:42 - mmengine - INFO - Epoch(train) [32][520/940] lr: 1.0000e-02 eta: 9:04:05 time: 0.5197 data_time: 0.0308 memory: 21547 grad_norm: 4.1019 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.7210 loss: 1.7210 2022/10/10 01:56:52 - mmengine - INFO - Epoch(train) [32][540/940] lr: 1.0000e-02 eta: 9:03:55 time: 0.5022 data_time: 0.0238 memory: 21547 grad_norm: 4.0291 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5978 loss: 1.5978 2022/10/10 01:57:02 - mmengine - INFO - Epoch(train) [32][560/940] lr: 1.0000e-02 eta: 9:03:43 time: 0.4835 data_time: 0.0290 memory: 21547 grad_norm: 4.1067 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6264 loss: 1.6264 2022/10/10 01:57:12 - mmengine - INFO - Epoch(train) [32][580/940] lr: 1.0000e-02 eta: 9:03:33 time: 0.5110 data_time: 0.0269 memory: 21547 grad_norm: 4.1473 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7423 loss: 1.7423 2022/10/10 01:57:22 - mmengine - INFO - Epoch(train) [32][600/940] lr: 1.0000e-02 eta: 9:03:23 time: 0.4996 data_time: 0.0296 memory: 21547 grad_norm: 4.0230 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7644 loss: 1.7644 2022/10/10 01:57:31 - mmengine - INFO - Epoch(train) [32][620/940] lr: 1.0000e-02 eta: 9:03:11 time: 0.4654 data_time: 0.0275 memory: 21547 grad_norm: 4.0586 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5847 loss: 1.5847 2022/10/10 01:57:41 - mmengine - INFO - Epoch(train) [32][640/940] lr: 1.0000e-02 eta: 9:03:01 time: 0.5157 data_time: 0.0268 memory: 21547 grad_norm: 4.1371 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6503 loss: 1.6503 2022/10/10 01:57:52 - mmengine - INFO - Epoch(train) [32][660/940] lr: 1.0000e-02 eta: 9:02:52 time: 0.5274 data_time: 0.0302 memory: 21547 grad_norm: 4.1035 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.7422 loss: 1.7422 2022/10/10 01:58:02 - mmengine - INFO - Epoch(train) [32][680/940] lr: 1.0000e-02 eta: 9:02:41 time: 0.4903 data_time: 0.0299 memory: 21547 grad_norm: 4.0034 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5639 loss: 1.5639 2022/10/10 01:58:12 - mmengine - INFO - Epoch(train) [32][700/940] lr: 1.0000e-02 eta: 9:02:31 time: 0.5066 data_time: 0.0387 memory: 21547 grad_norm: 4.0562 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5898 loss: 1.5898 2022/10/10 01:58:22 - mmengine - INFO - Epoch(train) [32][720/940] lr: 1.0000e-02 eta: 9:02:21 time: 0.5127 data_time: 0.0316 memory: 21547 grad_norm: 4.0827 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6217 loss: 1.6217 2022/10/10 01:58:32 - mmengine - INFO - Epoch(train) [32][740/940] lr: 1.0000e-02 eta: 9:02:11 time: 0.5010 data_time: 0.0258 memory: 21547 grad_norm: 4.0607 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6789 loss: 1.6789 2022/10/10 01:58:43 - mmengine - INFO - Epoch(train) [32][760/940] lr: 1.0000e-02 eta: 9:02:02 time: 0.5479 data_time: 0.0279 memory: 21547 grad_norm: 4.1172 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5757 loss: 1.5757 2022/10/10 01:58:53 - mmengine - INFO - Epoch(train) [32][780/940] lr: 1.0000e-02 eta: 9:01:51 time: 0.4776 data_time: 0.0257 memory: 21547 grad_norm: 4.0291 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7341 loss: 1.7341 2022/10/10 01:59:02 - mmengine - INFO - Epoch(train) [32][800/940] lr: 1.0000e-02 eta: 9:01:40 time: 0.4864 data_time: 0.0286 memory: 21547 grad_norm: 4.0757 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6140 loss: 1.6140 2022/10/10 01:59:13 - mmengine - INFO - Epoch(train) [32][820/940] lr: 1.0000e-02 eta: 9:01:30 time: 0.5154 data_time: 0.0270 memory: 21547 grad_norm: 4.1149 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5399 loss: 1.5399 2022/10/10 01:59:22 - mmengine - INFO - Epoch(train) [32][840/940] lr: 1.0000e-02 eta: 9:01:18 time: 0.4702 data_time: 0.0257 memory: 21547 grad_norm: 4.1326 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7558 loss: 1.7558 2022/10/10 01:59:33 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 01:59:33 - mmengine - INFO - Epoch(train) [32][860/940] lr: 1.0000e-02 eta: 9:01:09 time: 0.5344 data_time: 0.0249 memory: 21547 grad_norm: 4.1863 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6699 loss: 1.6699 2022/10/10 01:59:43 - mmengine - INFO - Epoch(train) [32][880/940] lr: 1.0000e-02 eta: 9:00:58 time: 0.4876 data_time: 0.0274 memory: 21547 grad_norm: 4.1664 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8087 loss: 1.8087 2022/10/10 01:59:52 - mmengine - INFO - Epoch(train) [32][900/940] lr: 1.0000e-02 eta: 9:00:47 time: 0.4930 data_time: 0.0242 memory: 21547 grad_norm: 4.0254 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5604 loss: 1.5604 2022/10/10 02:00:02 - mmengine - INFO - Epoch(train) [32][920/940] lr: 1.0000e-02 eta: 9:00:37 time: 0.4999 data_time: 0.0275 memory: 21547 grad_norm: 4.0428 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6392 loss: 1.6392 2022/10/10 02:00:11 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 02:00:11 - mmengine - INFO - Epoch(train) [32][940/940] lr: 1.0000e-02 eta: 9:00:24 time: 0.4423 data_time: 0.0232 memory: 21547 grad_norm: 4.2536 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.6781 loss: 1.6781 2022/10/10 02:00:23 - mmengine - INFO - Epoch(val) [32][20/78] eta: 0:00:35 time: 0.6042 data_time: 0.4964 memory: 3269 2022/10/10 02:00:32 - mmengine - INFO - Epoch(val) [32][40/78] eta: 0:00:16 time: 0.4219 data_time: 0.3130 memory: 3269 2022/10/10 02:00:43 - mmengine - INFO - Epoch(val) [32][60/78] eta: 0:00:10 time: 0.5603 data_time: 0.4524 memory: 3269 2022/10/10 02:00:53 - mmengine - INFO - Epoch(val) [32][78/78] acc/top1: 0.6355 acc/top5: 0.8498 acc/mean1: 0.6354 2022/10/10 02:01:07 - mmengine - INFO - Epoch(train) [33][20/940] lr: 1.0000e-02 eta: 9:00:23 time: 0.7109 data_time: 0.3119 memory: 21547 grad_norm: 4.1280 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.5831 loss: 1.5831 2022/10/10 02:01:17 - mmengine - INFO - Epoch(train) [33][40/940] lr: 1.0000e-02 eta: 9:00:11 time: 0.4773 data_time: 0.0801 memory: 21547 grad_norm: 4.0580 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.6896 loss: 1.6896 2022/10/10 02:01:27 - mmengine - INFO - Epoch(train) [33][60/940] lr: 1.0000e-02 eta: 9:00:02 time: 0.5414 data_time: 0.1518 memory: 21547 grad_norm: 4.0786 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5661 loss: 1.5661 2022/10/10 02:01:37 - mmengine - INFO - Epoch(train) [33][80/940] lr: 1.0000e-02 eta: 8:59:52 time: 0.4976 data_time: 0.0478 memory: 21547 grad_norm: 4.0781 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6097 loss: 1.6097 2022/10/10 02:01:48 - mmengine - INFO - Epoch(train) [33][100/940] lr: 1.0000e-02 eta: 8:59:42 time: 0.5143 data_time: 0.0383 memory: 21547 grad_norm: 4.0547 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4997 loss: 1.4997 2022/10/10 02:01:57 - mmengine - INFO - Epoch(train) [33][120/940] lr: 1.0000e-02 eta: 8:59:31 time: 0.4835 data_time: 0.0234 memory: 21547 grad_norm: 4.0015 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.5623 loss: 1.5623 2022/10/10 02:02:08 - mmengine - INFO - Epoch(train) [33][140/940] lr: 1.0000e-02 eta: 8:59:21 time: 0.5166 data_time: 0.0299 memory: 21547 grad_norm: 4.0127 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4091 loss: 1.4091 2022/10/10 02:02:18 - mmengine - INFO - Epoch(train) [33][160/940] lr: 1.0000e-02 eta: 8:59:10 time: 0.4915 data_time: 0.0258 memory: 21547 grad_norm: 4.0837 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5793 loss: 1.5793 2022/10/10 02:02:29 - mmengine - INFO - Epoch(train) [33][180/940] lr: 1.0000e-02 eta: 8:59:02 time: 0.5605 data_time: 0.0271 memory: 21547 grad_norm: 4.0175 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6090 loss: 1.6090 2022/10/10 02:02:38 - mmengine - INFO - Epoch(train) [33][200/940] lr: 1.0000e-02 eta: 8:58:51 time: 0.4864 data_time: 0.0300 memory: 21547 grad_norm: 4.0680 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.4997 loss: 1.4997 2022/10/10 02:02:49 - mmengine - INFO - Epoch(train) [33][220/940] lr: 1.0000e-02 eta: 8:58:41 time: 0.5111 data_time: 0.0257 memory: 21547 grad_norm: 4.0764 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.6001 loss: 1.6001 2022/10/10 02:02:58 - mmengine - INFO - Epoch(train) [33][240/940] lr: 1.0000e-02 eta: 8:58:29 time: 0.4580 data_time: 0.0244 memory: 21547 grad_norm: 4.0921 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6025 loss: 1.6025 2022/10/10 02:03:08 - mmengine - INFO - Epoch(train) [33][260/940] lr: 1.0000e-02 eta: 8:58:18 time: 0.4942 data_time: 0.0414 memory: 21547 grad_norm: 4.0583 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.6265 loss: 1.6265 2022/10/10 02:03:18 - mmengine - INFO - Epoch(train) [33][280/940] lr: 1.0000e-02 eta: 8:58:08 time: 0.4911 data_time: 0.0972 memory: 21547 grad_norm: 4.0104 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5141 loss: 1.5141 2022/10/10 02:03:28 - mmengine - INFO - Epoch(train) [33][300/940] lr: 1.0000e-02 eta: 8:57:58 time: 0.5127 data_time: 0.0640 memory: 21547 grad_norm: 4.0108 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.5664 loss: 1.5664 2022/10/10 02:03:37 - mmengine - INFO - Epoch(train) [33][320/940] lr: 1.0000e-02 eta: 8:57:46 time: 0.4773 data_time: 0.0928 memory: 21547 grad_norm: 4.1245 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5809 loss: 1.5809 2022/10/10 02:03:47 - mmengine - INFO - Epoch(train) [33][340/940] lr: 1.0000e-02 eta: 8:57:36 time: 0.4988 data_time: 0.1128 memory: 21547 grad_norm: 4.0052 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4959 loss: 1.4959 2022/10/10 02:03:58 - mmengine - INFO - Epoch(train) [33][360/940] lr: 1.0000e-02 eta: 8:57:26 time: 0.5073 data_time: 0.0470 memory: 21547 grad_norm: 4.1131 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7339 loss: 1.7339 2022/10/10 02:04:08 - mmengine - INFO - Epoch(train) [33][380/940] lr: 1.0000e-02 eta: 8:57:15 time: 0.5091 data_time: 0.0295 memory: 21547 grad_norm: 4.0543 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.6519 loss: 1.6519 2022/10/10 02:04:17 - mmengine - INFO - Epoch(train) [33][400/940] lr: 1.0000e-02 eta: 8:57:04 time: 0.4796 data_time: 0.0300 memory: 21547 grad_norm: 4.0412 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.6401 loss: 1.6401 2022/10/10 02:04:28 - mmengine - INFO - Epoch(train) [33][420/940] lr: 1.0000e-02 eta: 8:56:54 time: 0.5152 data_time: 0.0274 memory: 21547 grad_norm: 4.0396 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7158 loss: 1.7158 2022/10/10 02:04:39 - mmengine - INFO - Epoch(train) [33][440/940] lr: 1.0000e-02 eta: 8:56:46 time: 0.5478 data_time: 0.0265 memory: 21547 grad_norm: 4.1070 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7464 loss: 1.7464 2022/10/10 02:04:48 - mmengine - INFO - Epoch(train) [33][460/940] lr: 1.0000e-02 eta: 8:56:35 time: 0.4864 data_time: 0.0266 memory: 21547 grad_norm: 4.1005 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6825 loss: 1.6825 2022/10/10 02:04:59 - mmengine - INFO - Epoch(train) [33][480/940] lr: 1.0000e-02 eta: 8:56:26 time: 0.5361 data_time: 0.0242 memory: 21547 grad_norm: 4.1446 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.6007 loss: 1.6007 2022/10/10 02:05:09 - mmengine - INFO - Epoch(train) [33][500/940] lr: 1.0000e-02 eta: 8:56:15 time: 0.4894 data_time: 0.0318 memory: 21547 grad_norm: 4.1331 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5553 loss: 1.5553 2022/10/10 02:05:19 - mmengine - INFO - Epoch(train) [33][520/940] lr: 1.0000e-02 eta: 8:56:04 time: 0.4856 data_time: 0.0253 memory: 21547 grad_norm: 3.9846 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.6236 loss: 1.6236 2022/10/10 02:05:29 - mmengine - INFO - Epoch(train) [33][540/940] lr: 1.0000e-02 eta: 8:55:55 time: 0.5251 data_time: 0.0291 memory: 21547 grad_norm: 4.0429 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6085 loss: 1.6085 2022/10/10 02:05:39 - mmengine - INFO - Epoch(train) [33][560/940] lr: 1.0000e-02 eta: 8:55:45 time: 0.5092 data_time: 0.0254 memory: 21547 grad_norm: 4.1155 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6404 loss: 1.6404 2022/10/10 02:05:49 - mmengine - INFO - Epoch(train) [33][580/940] lr: 1.0000e-02 eta: 8:55:33 time: 0.4727 data_time: 0.0319 memory: 21547 grad_norm: 3.9867 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6159 loss: 1.6159 2022/10/10 02:05:58 - mmengine - INFO - Epoch(train) [33][600/940] lr: 1.0000e-02 eta: 8:55:22 time: 0.4865 data_time: 0.0292 memory: 21547 grad_norm: 4.0459 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.6033 loss: 1.6033 2022/10/10 02:06:08 - mmengine - INFO - Epoch(train) [33][620/940] lr: 1.0000e-02 eta: 8:55:12 time: 0.5033 data_time: 0.0291 memory: 21547 grad_norm: 4.0901 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7405 loss: 1.7405 2022/10/10 02:06:18 - mmengine - INFO - Epoch(train) [33][640/940] lr: 1.0000e-02 eta: 8:55:01 time: 0.4955 data_time: 0.0275 memory: 21547 grad_norm: 3.9887 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5504 loss: 1.5504 2022/10/10 02:06:29 - mmengine - INFO - Epoch(train) [33][660/940] lr: 1.0000e-02 eta: 8:54:51 time: 0.5067 data_time: 0.0308 memory: 21547 grad_norm: 4.1160 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.7088 loss: 1.7088 2022/10/10 02:06:39 - mmengine - INFO - Epoch(train) [33][680/940] lr: 1.0000e-02 eta: 8:54:42 time: 0.5462 data_time: 0.0265 memory: 21547 grad_norm: 4.1032 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7180 loss: 1.7180 2022/10/10 02:06:49 - mmengine - INFO - Epoch(train) [33][700/940] lr: 1.0000e-02 eta: 8:54:31 time: 0.4761 data_time: 0.0288 memory: 21547 grad_norm: 4.0600 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6312 loss: 1.6312 2022/10/10 02:06:59 - mmengine - INFO - Epoch(train) [33][720/940] lr: 1.0000e-02 eta: 8:54:20 time: 0.4840 data_time: 0.0327 memory: 21547 grad_norm: 4.0382 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5678 loss: 1.5678 2022/10/10 02:07:09 - mmengine - INFO - Epoch(train) [33][740/940] lr: 1.0000e-02 eta: 8:54:09 time: 0.5018 data_time: 0.0258 memory: 21547 grad_norm: 4.1116 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6283 loss: 1.6283 2022/10/10 02:07:20 - mmengine - INFO - Epoch(train) [33][760/940] lr: 1.0000e-02 eta: 8:54:01 time: 0.5522 data_time: 0.0328 memory: 21547 grad_norm: 4.2405 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.6019 loss: 1.6019 2022/10/10 02:07:30 - mmengine - INFO - Epoch(train) [33][780/940] lr: 1.0000e-02 eta: 8:53:51 time: 0.4970 data_time: 0.0241 memory: 21547 grad_norm: 4.1111 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6753 loss: 1.6753 2022/10/10 02:07:39 - mmengine - INFO - Epoch(train) [33][800/940] lr: 1.0000e-02 eta: 8:53:40 time: 0.4864 data_time: 0.0248 memory: 21547 grad_norm: 4.2107 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7392 loss: 1.7392 2022/10/10 02:07:49 - mmengine - INFO - Epoch(train) [33][820/940] lr: 1.0000e-02 eta: 8:53:29 time: 0.4985 data_time: 0.0265 memory: 21547 grad_norm: 4.1072 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.7694 loss: 1.7694 2022/10/10 02:07:59 - mmengine - INFO - Epoch(train) [33][840/940] lr: 1.0000e-02 eta: 8:53:18 time: 0.4945 data_time: 0.0285 memory: 21547 grad_norm: 4.1243 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6498 loss: 1.6498 2022/10/10 02:08:09 - mmengine - INFO - Epoch(train) [33][860/940] lr: 1.0000e-02 eta: 8:53:07 time: 0.4834 data_time: 0.0224 memory: 21547 grad_norm: 3.9812 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4975 loss: 1.4975 2022/10/10 02:08:19 - mmengine - INFO - Epoch(train) [33][880/940] lr: 1.0000e-02 eta: 8:52:56 time: 0.4926 data_time: 0.0294 memory: 21547 grad_norm: 4.1387 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6086 loss: 1.6086 2022/10/10 02:08:30 - mmengine - INFO - Epoch(train) [33][900/940] lr: 1.0000e-02 eta: 8:52:49 time: 0.5697 data_time: 0.0216 memory: 21547 grad_norm: 4.0933 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5944 loss: 1.5944 2022/10/10 02:08:41 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 02:08:41 - mmengine - INFO - Epoch(train) [33][920/940] lr: 1.0000e-02 eta: 8:52:40 time: 0.5312 data_time: 0.0313 memory: 21547 grad_norm: 4.1687 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6840 loss: 1.6840 2022/10/10 02:08:50 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 02:08:50 - mmengine - INFO - Epoch(train) [33][940/940] lr: 1.0000e-02 eta: 8:52:27 time: 0.4464 data_time: 0.0200 memory: 21547 grad_norm: 4.3813 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.6086 loss: 1.6086 2022/10/10 02:08:50 - mmengine - INFO - Saving checkpoint at 33 epochs 2022/10/10 02:09:03 - mmengine - INFO - Epoch(val) [33][20/78] eta: 0:00:35 time: 0.6124 data_time: 0.5067 memory: 3269 2022/10/10 02:09:11 - mmengine - INFO - Epoch(val) [33][40/78] eta: 0:00:15 time: 0.4210 data_time: 0.3165 memory: 3269 2022/10/10 02:09:22 - mmengine - INFO - Epoch(val) [33][60/78] eta: 0:00:09 time: 0.5524 data_time: 0.4474 memory: 3269 2022/10/10 02:09:32 - mmengine - INFO - Epoch(val) [33][78/78] acc/top1: 0.6275 acc/top5: 0.8405 acc/mean1: 0.6272 2022/10/10 02:09:46 - mmengine - INFO - Epoch(train) [34][20/940] lr: 1.0000e-02 eta: 8:52:25 time: 0.7108 data_time: 0.2020 memory: 21547 grad_norm: 4.0577 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5639 loss: 1.5639 2022/10/10 02:09:56 - mmengine - INFO - Epoch(train) [34][40/940] lr: 1.0000e-02 eta: 8:52:14 time: 0.4910 data_time: 0.0279 memory: 21547 grad_norm: 4.0146 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5891 loss: 1.5891 2022/10/10 02:10:07 - mmengine - INFO - Epoch(train) [34][60/940] lr: 1.0000e-02 eta: 8:52:07 time: 0.5695 data_time: 0.0301 memory: 21547 grad_norm: 4.0827 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6023 loss: 1.6023 2022/10/10 02:10:18 - mmengine - INFO - Epoch(train) [34][80/940] lr: 1.0000e-02 eta: 8:51:57 time: 0.5298 data_time: 0.0333 memory: 21547 grad_norm: 4.1490 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5678 loss: 1.5678 2022/10/10 02:10:28 - mmengine - INFO - Epoch(train) [34][100/940] lr: 1.0000e-02 eta: 8:51:48 time: 0.5119 data_time: 0.0256 memory: 21547 grad_norm: 3.9996 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5525 loss: 1.5525 2022/10/10 02:10:37 - mmengine - INFO - Epoch(train) [34][120/940] lr: 1.0000e-02 eta: 8:51:35 time: 0.4477 data_time: 0.0240 memory: 21547 grad_norm: 4.1394 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.7728 loss: 1.7728 2022/10/10 02:10:47 - mmengine - INFO - Epoch(train) [34][140/940] lr: 1.0000e-02 eta: 8:51:25 time: 0.5170 data_time: 0.0304 memory: 21547 grad_norm: 4.0775 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.5477 loss: 1.5477 2022/10/10 02:10:57 - mmengine - INFO - Epoch(train) [34][160/940] lr: 1.0000e-02 eta: 8:51:14 time: 0.4859 data_time: 0.0304 memory: 21547 grad_norm: 4.1292 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5866 loss: 1.5866 2022/10/10 02:11:08 - mmengine - INFO - Epoch(train) [34][180/940] lr: 1.0000e-02 eta: 8:51:05 time: 0.5408 data_time: 0.0292 memory: 21547 grad_norm: 4.0952 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4886 loss: 1.4886 2022/10/10 02:11:18 - mmengine - INFO - Epoch(train) [34][200/940] lr: 1.0000e-02 eta: 8:50:55 time: 0.5011 data_time: 0.0315 memory: 21547 grad_norm: 4.1264 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.7101 loss: 1.7101 2022/10/10 02:11:29 - mmengine - INFO - Epoch(train) [34][220/940] lr: 1.0000e-02 eta: 8:50:46 time: 0.5459 data_time: 0.0303 memory: 21547 grad_norm: 4.0940 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5952 loss: 1.5952 2022/10/10 02:11:38 - mmengine - INFO - Epoch(train) [34][240/940] lr: 1.0000e-02 eta: 8:50:34 time: 0.4556 data_time: 0.0261 memory: 21547 grad_norm: 4.1327 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6087 loss: 1.6087 2022/10/10 02:11:48 - mmengine - INFO - Epoch(train) [34][260/940] lr: 1.0000e-02 eta: 8:50:24 time: 0.5145 data_time: 0.0364 memory: 21547 grad_norm: 4.0656 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5876 loss: 1.5876 2022/10/10 02:11:58 - mmengine - INFO - Epoch(train) [34][280/940] lr: 1.0000e-02 eta: 8:50:14 time: 0.4997 data_time: 0.0263 memory: 21547 grad_norm: 4.1407 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6292 loss: 1.6292 2022/10/10 02:12:09 - mmengine - INFO - Epoch(train) [34][300/940] lr: 1.0000e-02 eta: 8:50:04 time: 0.5271 data_time: 0.0313 memory: 21547 grad_norm: 4.0603 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6276 loss: 1.6276 2022/10/10 02:12:18 - mmengine - INFO - Epoch(train) [34][320/940] lr: 1.0000e-02 eta: 8:49:53 time: 0.4711 data_time: 0.0395 memory: 21547 grad_norm: 4.1586 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6354 loss: 1.6354 2022/10/10 02:12:28 - mmengine - INFO - Epoch(train) [34][340/940] lr: 1.0000e-02 eta: 8:49:41 time: 0.4723 data_time: 0.0532 memory: 21547 grad_norm: 4.1555 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.6835 loss: 1.6835 2022/10/10 02:12:38 - mmengine - INFO - Epoch(train) [34][360/940] lr: 1.0000e-02 eta: 8:49:31 time: 0.5112 data_time: 0.0724 memory: 21547 grad_norm: 4.0926 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7267 loss: 1.7267 2022/10/10 02:12:48 - mmengine - INFO - Epoch(train) [34][380/940] lr: 1.0000e-02 eta: 8:49:21 time: 0.5052 data_time: 0.0391 memory: 21547 grad_norm: 4.0829 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.7312 loss: 1.7312 2022/10/10 02:12:58 - mmengine - INFO - Epoch(train) [34][400/940] lr: 1.0000e-02 eta: 8:49:11 time: 0.5209 data_time: 0.0260 memory: 21547 grad_norm: 4.1010 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5009 loss: 1.5009 2022/10/10 02:13:08 - mmengine - INFO - Epoch(train) [34][420/940] lr: 1.0000e-02 eta: 8:49:01 time: 0.4965 data_time: 0.0289 memory: 21547 grad_norm: 4.1775 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6106 loss: 1.6106 2022/10/10 02:13:19 - mmengine - INFO - Epoch(train) [34][440/940] lr: 1.0000e-02 eta: 8:48:52 time: 0.5448 data_time: 0.0261 memory: 21547 grad_norm: 4.1270 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7922 loss: 1.7922 2022/10/10 02:13:29 - mmengine - INFO - Epoch(train) [34][460/940] lr: 1.0000e-02 eta: 8:48:42 time: 0.5005 data_time: 0.0309 memory: 21547 grad_norm: 4.1228 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6158 loss: 1.6158 2022/10/10 02:13:39 - mmengine - INFO - Epoch(train) [34][480/940] lr: 1.0000e-02 eta: 8:48:31 time: 0.5012 data_time: 0.0226 memory: 21547 grad_norm: 4.1289 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.6427 loss: 1.6427 2022/10/10 02:13:49 - mmengine - INFO - Epoch(train) [34][500/940] lr: 1.0000e-02 eta: 8:48:20 time: 0.4762 data_time: 0.0272 memory: 21547 grad_norm: 4.1720 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5953 loss: 1.5953 2022/10/10 02:13:59 - mmengine - INFO - Epoch(train) [34][520/940] lr: 1.0000e-02 eta: 8:48:10 time: 0.5210 data_time: 0.0300 memory: 21547 grad_norm: 4.0439 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6307 loss: 1.6307 2022/10/10 02:14:09 - mmengine - INFO - Epoch(train) [34][540/940] lr: 1.0000e-02 eta: 8:48:00 time: 0.4912 data_time: 0.0313 memory: 21547 grad_norm: 4.0644 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.5743 loss: 1.5743 2022/10/10 02:14:19 - mmengine - INFO - Epoch(train) [34][560/940] lr: 1.0000e-02 eta: 8:47:49 time: 0.4978 data_time: 0.0234 memory: 21547 grad_norm: 4.1504 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5920 loss: 1.5920 2022/10/10 02:14:29 - mmengine - INFO - Epoch(train) [34][580/940] lr: 1.0000e-02 eta: 8:47:38 time: 0.4921 data_time: 0.0257 memory: 21547 grad_norm: 4.1373 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6592 loss: 1.6592 2022/10/10 02:14:39 - mmengine - INFO - Epoch(train) [34][600/940] lr: 1.0000e-02 eta: 8:47:29 time: 0.5247 data_time: 0.0285 memory: 21547 grad_norm: 4.1272 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6816 loss: 1.6816 2022/10/10 02:14:49 - mmengine - INFO - Epoch(train) [34][620/940] lr: 1.0000e-02 eta: 8:47:18 time: 0.4828 data_time: 0.0279 memory: 21547 grad_norm: 4.0961 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5578 loss: 1.5578 2022/10/10 02:14:59 - mmengine - INFO - Epoch(train) [34][640/940] lr: 1.0000e-02 eta: 8:47:07 time: 0.4938 data_time: 0.0298 memory: 21547 grad_norm: 4.1828 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.6836 loss: 1.6836 2022/10/10 02:15:10 - mmengine - INFO - Epoch(train) [34][660/940] lr: 1.0000e-02 eta: 8:46:58 time: 0.5419 data_time: 0.0350 memory: 21547 grad_norm: 4.0883 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.4365 loss: 1.4365 2022/10/10 02:15:19 - mmengine - INFO - Epoch(train) [34][680/940] lr: 1.0000e-02 eta: 8:46:47 time: 0.4738 data_time: 0.0263 memory: 21547 grad_norm: 4.0866 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5476 loss: 1.5476 2022/10/10 02:15:30 - mmengine - INFO - Epoch(train) [34][700/940] lr: 1.0000e-02 eta: 8:46:38 time: 0.5361 data_time: 0.0356 memory: 21547 grad_norm: 3.9981 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5579 loss: 1.5579 2022/10/10 02:15:39 - mmengine - INFO - Epoch(train) [34][720/940] lr: 1.0000e-02 eta: 8:46:26 time: 0.4559 data_time: 0.0228 memory: 21547 grad_norm: 4.1484 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6845 loss: 1.6845 2022/10/10 02:15:49 - mmengine - INFO - Epoch(train) [34][740/940] lr: 1.0000e-02 eta: 8:46:16 time: 0.5169 data_time: 0.0274 memory: 21547 grad_norm: 4.0331 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.5604 loss: 1.5604 2022/10/10 02:15:59 - mmengine - INFO - Epoch(train) [34][760/940] lr: 1.0000e-02 eta: 8:46:04 time: 0.4614 data_time: 0.0289 memory: 21547 grad_norm: 4.0770 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5680 loss: 1.5680 2022/10/10 02:16:09 - mmengine - INFO - Epoch(train) [34][780/940] lr: 1.0000e-02 eta: 8:45:55 time: 0.5472 data_time: 0.0273 memory: 21547 grad_norm: 4.1184 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4624 loss: 1.4624 2022/10/10 02:16:19 - mmengine - INFO - Epoch(train) [34][800/940] lr: 1.0000e-02 eta: 8:45:43 time: 0.4541 data_time: 0.0281 memory: 21547 grad_norm: 4.1952 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.7019 loss: 1.7019 2022/10/10 02:16:29 - mmengine - INFO - Epoch(train) [34][820/940] lr: 1.0000e-02 eta: 8:45:34 time: 0.5435 data_time: 0.0319 memory: 21547 grad_norm: 4.0969 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.6783 loss: 1.6783 2022/10/10 02:16:39 - mmengine - INFO - Epoch(train) [34][840/940] lr: 1.0000e-02 eta: 8:45:23 time: 0.4685 data_time: 0.0280 memory: 21547 grad_norm: 4.1473 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6742 loss: 1.6742 2022/10/10 02:16:49 - mmengine - INFO - Epoch(train) [34][860/940] lr: 1.0000e-02 eta: 8:45:13 time: 0.5290 data_time: 0.0250 memory: 21547 grad_norm: 4.1255 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.6059 loss: 1.6059 2022/10/10 02:16:59 - mmengine - INFO - Epoch(train) [34][880/940] lr: 1.0000e-02 eta: 8:45:03 time: 0.4919 data_time: 0.0303 memory: 21547 grad_norm: 4.0995 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7338 loss: 1.7338 2022/10/10 02:17:11 - mmengine - INFO - Epoch(train) [34][900/940] lr: 1.0000e-02 eta: 8:44:55 time: 0.5640 data_time: 0.0322 memory: 21547 grad_norm: 4.1178 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6580 loss: 1.6580 2022/10/10 02:17:20 - mmengine - INFO - Epoch(train) [34][920/940] lr: 1.0000e-02 eta: 8:44:43 time: 0.4703 data_time: 0.0265 memory: 21547 grad_norm: 4.1422 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6521 loss: 1.6521 2022/10/10 02:17:29 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 02:17:29 - mmengine - INFO - Epoch(train) [34][940/940] lr: 1.0000e-02 eta: 8:44:32 time: 0.4701 data_time: 0.0229 memory: 21547 grad_norm: 4.3174 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.5804 loss: 1.5804 2022/10/10 02:17:41 - mmengine - INFO - Epoch(val) [34][20/78] eta: 0:00:35 time: 0.6036 data_time: 0.4944 memory: 3269 2022/10/10 02:17:50 - mmengine - INFO - Epoch(val) [34][40/78] eta: 0:00:16 time: 0.4213 data_time: 0.3145 memory: 3269 2022/10/10 02:18:01 - mmengine - INFO - Epoch(val) [34][60/78] eta: 0:00:09 time: 0.5542 data_time: 0.4481 memory: 3269 2022/10/10 02:18:11 - mmengine - INFO - Epoch(val) [34][78/78] acc/top1: 0.6325 acc/top5: 0.8433 acc/mean1: 0.6323 2022/10/10 02:18:25 - mmengine - INFO - Epoch(train) [35][20/940] lr: 1.0000e-02 eta: 8:44:30 time: 0.7160 data_time: 0.2436 memory: 21547 grad_norm: 4.0990 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5797 loss: 1.5797 2022/10/10 02:18:35 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 02:18:35 - mmengine - INFO - Epoch(train) [35][40/940] lr: 1.0000e-02 eta: 8:44:18 time: 0.4702 data_time: 0.0246 memory: 21547 grad_norm: 4.0916 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5577 loss: 1.5577 2022/10/10 02:18:45 - mmengine - INFO - Epoch(train) [35][60/940] lr: 1.0000e-02 eta: 8:44:09 time: 0.5326 data_time: 0.0288 memory: 21547 grad_norm: 4.0328 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5606 loss: 1.5606 2022/10/10 02:18:56 - mmengine - INFO - Epoch(train) [35][80/940] lr: 1.0000e-02 eta: 8:43:59 time: 0.5114 data_time: 0.0258 memory: 21547 grad_norm: 4.0663 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5418 loss: 1.5418 2022/10/10 02:19:06 - mmengine - INFO - Epoch(train) [35][100/940] lr: 1.0000e-02 eta: 8:43:50 time: 0.5378 data_time: 0.0308 memory: 21547 grad_norm: 4.0945 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.5574 loss: 1.5574 2022/10/10 02:19:16 - mmengine - INFO - Epoch(train) [35][120/940] lr: 1.0000e-02 eta: 8:43:38 time: 0.4676 data_time: 0.0236 memory: 21547 grad_norm: 4.0964 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5295 loss: 1.5295 2022/10/10 02:19:26 - mmengine - INFO - Epoch(train) [35][140/940] lr: 1.0000e-02 eta: 8:43:28 time: 0.4982 data_time: 0.0303 memory: 21547 grad_norm: 4.0883 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5958 loss: 1.5958 2022/10/10 02:19:35 - mmengine - INFO - Epoch(train) [35][160/940] lr: 1.0000e-02 eta: 8:43:17 time: 0.4871 data_time: 0.0240 memory: 21547 grad_norm: 3.9809 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5690 loss: 1.5690 2022/10/10 02:19:46 - mmengine - INFO - Epoch(train) [35][180/940] lr: 1.0000e-02 eta: 8:43:08 time: 0.5426 data_time: 0.0344 memory: 21547 grad_norm: 4.0626 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5308 loss: 1.5308 2022/10/10 02:19:56 - mmengine - INFO - Epoch(train) [35][200/940] lr: 1.0000e-02 eta: 8:42:57 time: 0.4765 data_time: 0.0250 memory: 21547 grad_norm: 4.0881 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.5893 loss: 1.5893 2022/10/10 02:20:07 - mmengine - INFO - Epoch(train) [35][220/940] lr: 1.0000e-02 eta: 8:42:47 time: 0.5346 data_time: 0.0312 memory: 21547 grad_norm: 4.0271 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5867 loss: 1.5867 2022/10/10 02:20:16 - mmengine - INFO - Epoch(train) [35][240/940] lr: 1.0000e-02 eta: 8:42:35 time: 0.4539 data_time: 0.0266 memory: 21547 grad_norm: 4.0898 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4873 loss: 1.4873 2022/10/10 02:20:26 - mmengine - INFO - Epoch(train) [35][260/940] lr: 1.0000e-02 eta: 8:42:26 time: 0.5426 data_time: 0.0350 memory: 21547 grad_norm: 4.1153 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4393 loss: 1.4393 2022/10/10 02:20:36 - mmengine - INFO - Epoch(train) [35][280/940] lr: 1.0000e-02 eta: 8:42:15 time: 0.4706 data_time: 0.0243 memory: 21547 grad_norm: 4.1685 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6249 loss: 1.6249 2022/10/10 02:20:47 - mmengine - INFO - Epoch(train) [35][300/940] lr: 1.0000e-02 eta: 8:42:06 time: 0.5405 data_time: 0.0374 memory: 21547 grad_norm: 4.1030 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5474 loss: 1.5474 2022/10/10 02:20:57 - mmengine - INFO - Epoch(train) [35][320/940] lr: 1.0000e-02 eta: 8:41:56 time: 0.5081 data_time: 0.0255 memory: 21547 grad_norm: 4.0310 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5668 loss: 1.5668 2022/10/10 02:21:08 - mmengine - INFO - Epoch(train) [35][340/940] lr: 1.0000e-02 eta: 8:41:47 time: 0.5475 data_time: 0.0329 memory: 21547 grad_norm: 4.0916 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5893 loss: 1.5893 2022/10/10 02:21:17 - mmengine - INFO - Epoch(train) [35][360/940] lr: 1.0000e-02 eta: 8:41:35 time: 0.4404 data_time: 0.0300 memory: 21547 grad_norm: 4.1942 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6881 loss: 1.6881 2022/10/10 02:21:27 - mmengine - INFO - Epoch(train) [35][380/940] lr: 1.0000e-02 eta: 8:41:25 time: 0.5113 data_time: 0.0329 memory: 21547 grad_norm: 4.1428 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.6368 loss: 1.6368 2022/10/10 02:21:36 - mmengine - INFO - Epoch(train) [35][400/940] lr: 1.0000e-02 eta: 8:41:13 time: 0.4609 data_time: 0.0241 memory: 21547 grad_norm: 4.0226 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.5010 loss: 1.5010 2022/10/10 02:21:46 - mmengine - INFO - Epoch(train) [35][420/940] lr: 1.0000e-02 eta: 8:41:03 time: 0.5203 data_time: 0.0373 memory: 21547 grad_norm: 4.1542 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.6757 loss: 1.6757 2022/10/10 02:21:56 - mmengine - INFO - Epoch(train) [35][440/940] lr: 1.0000e-02 eta: 8:40:52 time: 0.4808 data_time: 0.0306 memory: 21547 grad_norm: 4.1924 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6022 loss: 1.6022 2022/10/10 02:22:06 - mmengine - INFO - Epoch(train) [35][460/940] lr: 1.0000e-02 eta: 8:40:41 time: 0.4990 data_time: 0.0665 memory: 21547 grad_norm: 4.1833 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5105 loss: 1.5105 2022/10/10 02:22:16 - mmengine - INFO - Epoch(train) [35][480/940] lr: 1.0000e-02 eta: 8:40:31 time: 0.5114 data_time: 0.0448 memory: 21547 grad_norm: 4.0635 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5593 loss: 1.5593 2022/10/10 02:22:27 - mmengine - INFO - Epoch(train) [35][500/940] lr: 1.0000e-02 eta: 8:40:23 time: 0.5576 data_time: 0.0256 memory: 21547 grad_norm: 4.0583 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.5019 loss: 1.5019 2022/10/10 02:22:37 - mmengine - INFO - Epoch(train) [35][520/940] lr: 1.0000e-02 eta: 8:40:11 time: 0.4651 data_time: 0.0243 memory: 21547 grad_norm: 4.1885 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.5534 loss: 1.5534 2022/10/10 02:22:47 - mmengine - INFO - Epoch(train) [35][540/940] lr: 1.0000e-02 eta: 8:40:01 time: 0.4985 data_time: 0.0244 memory: 21547 grad_norm: 4.1397 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5845 loss: 1.5845 2022/10/10 02:22:57 - mmengine - INFO - Epoch(train) [35][560/940] lr: 1.0000e-02 eta: 8:39:51 time: 0.5033 data_time: 0.0305 memory: 21547 grad_norm: 4.1148 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6514 loss: 1.6514 2022/10/10 02:23:07 - mmengine - INFO - Epoch(train) [35][580/940] lr: 1.0000e-02 eta: 8:39:41 time: 0.5118 data_time: 0.0305 memory: 21547 grad_norm: 4.1016 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6378 loss: 1.6378 2022/10/10 02:23:18 - mmengine - INFO - Epoch(train) [35][600/940] lr: 1.0000e-02 eta: 8:39:32 time: 0.5468 data_time: 0.0307 memory: 21547 grad_norm: 4.1512 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.5880 loss: 1.5880 2022/10/10 02:23:27 - mmengine - INFO - Epoch(train) [35][620/940] lr: 1.0000e-02 eta: 8:39:21 time: 0.4743 data_time: 0.0275 memory: 21547 grad_norm: 4.2322 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5305 loss: 1.5305 2022/10/10 02:23:38 - mmengine - INFO - Epoch(train) [35][640/940] lr: 1.0000e-02 eta: 8:39:11 time: 0.5090 data_time: 0.0263 memory: 21547 grad_norm: 4.0968 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7234 loss: 1.7234 2022/10/10 02:23:48 - mmengine - INFO - Epoch(train) [35][660/940] lr: 1.0000e-02 eta: 8:39:00 time: 0.4990 data_time: 0.0282 memory: 21547 grad_norm: 4.1173 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6007 loss: 1.6007 2022/10/10 02:23:58 - mmengine - INFO - Epoch(train) [35][680/940] lr: 1.0000e-02 eta: 8:38:50 time: 0.5202 data_time: 0.0258 memory: 21547 grad_norm: 4.0895 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5991 loss: 1.5991 2022/10/10 02:24:07 - mmengine - INFO - Epoch(train) [35][700/940] lr: 1.0000e-02 eta: 8:38:38 time: 0.4388 data_time: 0.0260 memory: 21547 grad_norm: 4.2029 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6154 loss: 1.6154 2022/10/10 02:24:18 - mmengine - INFO - Epoch(train) [35][720/940] lr: 1.0000e-02 eta: 8:38:30 time: 0.5851 data_time: 0.0312 memory: 21547 grad_norm: 4.1475 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5155 loss: 1.5155 2022/10/10 02:24:28 - mmengine - INFO - Epoch(train) [35][740/940] lr: 1.0000e-02 eta: 8:38:20 time: 0.4899 data_time: 0.0230 memory: 21547 grad_norm: 4.1844 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5441 loss: 1.5441 2022/10/10 02:24:38 - mmengine - INFO - Epoch(train) [35][760/940] lr: 1.0000e-02 eta: 8:38:09 time: 0.4995 data_time: 0.0277 memory: 21547 grad_norm: 4.1414 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7431 loss: 1.7431 2022/10/10 02:24:48 - mmengine - INFO - Epoch(train) [35][780/940] lr: 1.0000e-02 eta: 8:37:59 time: 0.5096 data_time: 0.0315 memory: 21547 grad_norm: 4.1282 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7100 loss: 1.7100 2022/10/10 02:24:59 - mmengine - INFO - Epoch(train) [35][800/940] lr: 1.0000e-02 eta: 8:37:50 time: 0.5408 data_time: 0.0264 memory: 21547 grad_norm: 4.1776 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.5162 loss: 1.5162 2022/10/10 02:25:10 - mmengine - INFO - Epoch(train) [35][820/940] lr: 1.0000e-02 eta: 8:37:41 time: 0.5215 data_time: 0.0336 memory: 21547 grad_norm: 4.0591 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5750 loss: 1.5750 2022/10/10 02:25:19 - mmengine - INFO - Epoch(train) [35][840/940] lr: 1.0000e-02 eta: 8:37:29 time: 0.4727 data_time: 0.0253 memory: 21547 grad_norm: 4.1330 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.6275 loss: 1.6275 2022/10/10 02:25:29 - mmengine - INFO - Epoch(train) [35][860/940] lr: 1.0000e-02 eta: 8:37:18 time: 0.4904 data_time: 0.0248 memory: 21547 grad_norm: 4.1379 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5995 loss: 1.5995 2022/10/10 02:25:38 - mmengine - INFO - Epoch(train) [35][880/940] lr: 1.0000e-02 eta: 8:37:06 time: 0.4599 data_time: 0.0315 memory: 21547 grad_norm: 4.1564 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.5873 loss: 1.5873 2022/10/10 02:25:48 - mmengine - INFO - Epoch(train) [35][900/940] lr: 1.0000e-02 eta: 8:36:55 time: 0.4786 data_time: 0.0268 memory: 21547 grad_norm: 4.1789 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.7030 loss: 1.7030 2022/10/10 02:25:58 - mmengine - INFO - Epoch(train) [35][920/940] lr: 1.0000e-02 eta: 8:36:45 time: 0.5014 data_time: 0.0303 memory: 21547 grad_norm: 4.1123 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5704 loss: 1.5704 2022/10/10 02:26:07 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 02:26:07 - mmengine - INFO - Epoch(train) [35][940/940] lr: 1.0000e-02 eta: 8:36:33 time: 0.4696 data_time: 0.0229 memory: 21547 grad_norm: 4.2775 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.5218 loss: 1.5218 2022/10/10 02:26:19 - mmengine - INFO - Epoch(val) [35][20/78] eta: 0:00:35 time: 0.6091 data_time: 0.4991 memory: 3269 2022/10/10 02:26:28 - mmengine - INFO - Epoch(val) [35][40/78] eta: 0:00:16 time: 0.4234 data_time: 0.3159 memory: 3269 2022/10/10 02:26:39 - mmengine - INFO - Epoch(val) [35][60/78] eta: 0:00:10 time: 0.5717 data_time: 0.4637 memory: 3269 2022/10/10 02:26:49 - mmengine - INFO - Epoch(val) [35][78/78] acc/top1: 0.6369 acc/top5: 0.8479 acc/mean1: 0.6368 2022/10/10 02:27:04 - mmengine - INFO - Epoch(train) [36][20/940] lr: 1.0000e-02 eta: 8:36:32 time: 0.7395 data_time: 0.1904 memory: 21547 grad_norm: 4.1105 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5822 loss: 1.5822 2022/10/10 02:27:14 - mmengine - INFO - Epoch(train) [36][40/940] lr: 1.0000e-02 eta: 8:36:21 time: 0.4992 data_time: 0.0239 memory: 21547 grad_norm: 4.0784 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4564 loss: 1.4564 2022/10/10 02:27:24 - mmengine - INFO - Epoch(train) [36][60/940] lr: 1.0000e-02 eta: 8:36:12 time: 0.5349 data_time: 0.0287 memory: 21547 grad_norm: 4.1319 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.6171 loss: 1.6171 2022/10/10 02:27:34 - mmengine - INFO - Epoch(train) [36][80/940] lr: 1.0000e-02 eta: 8:36:02 time: 0.4963 data_time: 0.0255 memory: 21547 grad_norm: 4.1768 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6443 loss: 1.6443 2022/10/10 02:27:44 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 02:27:44 - mmengine - INFO - Epoch(train) [36][100/940] lr: 1.0000e-02 eta: 8:35:52 time: 0.5065 data_time: 0.0314 memory: 21547 grad_norm: 4.0842 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 1.7013 loss: 1.7013 2022/10/10 02:27:54 - mmengine - INFO - Epoch(train) [36][120/940] lr: 1.0000e-02 eta: 8:35:40 time: 0.4656 data_time: 0.0324 memory: 21547 grad_norm: 4.0916 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5241 loss: 1.5241 2022/10/10 02:28:04 - mmengine - INFO - Epoch(train) [36][140/940] lr: 1.0000e-02 eta: 8:35:30 time: 0.5154 data_time: 0.0269 memory: 21547 grad_norm: 4.0900 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4779 loss: 1.4779 2022/10/10 02:28:14 - mmengine - INFO - Epoch(train) [36][160/940] lr: 1.0000e-02 eta: 8:35:19 time: 0.4876 data_time: 0.0272 memory: 21547 grad_norm: 4.1037 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 1.5336 loss: 1.5336 2022/10/10 02:28:24 - mmengine - INFO - Epoch(train) [36][180/940] lr: 1.0000e-02 eta: 8:35:09 time: 0.5102 data_time: 0.0263 memory: 21547 grad_norm: 4.1073 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.4878 loss: 1.4878 2022/10/10 02:28:33 - mmengine - INFO - Epoch(train) [36][200/940] lr: 1.0000e-02 eta: 8:34:57 time: 0.4614 data_time: 0.0253 memory: 21547 grad_norm: 4.1091 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7580 loss: 1.7580 2022/10/10 02:28:44 - mmengine - INFO - Epoch(train) [36][220/940] lr: 1.0000e-02 eta: 8:34:48 time: 0.5205 data_time: 0.0332 memory: 21547 grad_norm: 4.1043 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5773 loss: 1.5773 2022/10/10 02:28:54 - mmengine - INFO - Epoch(train) [36][240/940] lr: 1.0000e-02 eta: 8:34:37 time: 0.5016 data_time: 0.0300 memory: 21547 grad_norm: 4.1143 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6828 loss: 1.6828 2022/10/10 02:29:03 - mmengine - INFO - Epoch(train) [36][260/940] lr: 1.0000e-02 eta: 8:34:26 time: 0.4900 data_time: 0.0274 memory: 21547 grad_norm: 4.1294 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5198 loss: 1.5198 2022/10/10 02:29:14 - mmengine - INFO - Epoch(train) [36][280/940] lr: 1.0000e-02 eta: 8:34:16 time: 0.5018 data_time: 0.0285 memory: 21547 grad_norm: 4.1647 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4866 loss: 1.4866 2022/10/10 02:29:23 - mmengine - INFO - Epoch(train) [36][300/940] lr: 1.0000e-02 eta: 8:34:05 time: 0.4948 data_time: 0.0254 memory: 21547 grad_norm: 4.2717 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5079 loss: 1.5079 2022/10/10 02:29:34 - mmengine - INFO - Epoch(train) [36][320/940] lr: 1.0000e-02 eta: 8:33:55 time: 0.5127 data_time: 0.0301 memory: 21547 grad_norm: 4.0813 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6499 loss: 1.6499 2022/10/10 02:29:44 - mmengine - INFO - Epoch(train) [36][340/940] lr: 1.0000e-02 eta: 8:33:46 time: 0.5137 data_time: 0.0311 memory: 21547 grad_norm: 4.1075 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5120 loss: 1.5120 2022/10/10 02:29:54 - mmengine - INFO - Epoch(train) [36][360/940] lr: 1.0000e-02 eta: 8:33:35 time: 0.4959 data_time: 0.0282 memory: 21547 grad_norm: 4.1914 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5945 loss: 1.5945 2022/10/10 02:30:04 - mmengine - INFO - Epoch(train) [36][380/940] lr: 1.0000e-02 eta: 8:33:25 time: 0.5191 data_time: 0.0295 memory: 21547 grad_norm: 4.1025 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.6874 loss: 1.6874 2022/10/10 02:30:14 - mmengine - INFO - Epoch(train) [36][400/940] lr: 1.0000e-02 eta: 8:33:15 time: 0.4964 data_time: 0.0227 memory: 21547 grad_norm: 4.1853 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7041 loss: 1.7041 2022/10/10 02:30:25 - mmengine - INFO - Epoch(train) [36][420/940] lr: 1.0000e-02 eta: 8:33:06 time: 0.5399 data_time: 0.0269 memory: 21547 grad_norm: 4.1340 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6211 loss: 1.6211 2022/10/10 02:30:35 - mmengine - INFO - Epoch(train) [36][440/940] lr: 1.0000e-02 eta: 8:32:55 time: 0.4991 data_time: 0.0256 memory: 21547 grad_norm: 4.1233 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5553 loss: 1.5553 2022/10/10 02:30:45 - mmengine - INFO - Epoch(train) [36][460/940] lr: 1.0000e-02 eta: 8:32:44 time: 0.4857 data_time: 0.0272 memory: 21547 grad_norm: 4.1517 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.4760 loss: 1.4760 2022/10/10 02:30:55 - mmengine - INFO - Epoch(train) [36][480/940] lr: 1.0000e-02 eta: 8:32:35 time: 0.5236 data_time: 0.0303 memory: 21547 grad_norm: 4.1199 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5412 loss: 1.5412 2022/10/10 02:31:06 - mmengine - INFO - Epoch(train) [36][500/940] lr: 1.0000e-02 eta: 8:32:26 time: 0.5456 data_time: 0.0223 memory: 21547 grad_norm: 4.1796 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6155 loss: 1.6155 2022/10/10 02:31:15 - mmengine - INFO - Epoch(train) [36][520/940] lr: 1.0000e-02 eta: 8:32:14 time: 0.4592 data_time: 0.0288 memory: 21547 grad_norm: 4.2052 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5693 loss: 1.5693 2022/10/10 02:31:25 - mmengine - INFO - Epoch(train) [36][540/940] lr: 1.0000e-02 eta: 8:32:04 time: 0.5074 data_time: 0.0232 memory: 21547 grad_norm: 4.0919 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6135 loss: 1.6135 2022/10/10 02:31:36 - mmengine - INFO - Epoch(train) [36][560/940] lr: 1.0000e-02 eta: 8:31:54 time: 0.5052 data_time: 0.0327 memory: 21547 grad_norm: 4.1642 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.5317 loss: 1.5317 2022/10/10 02:31:45 - mmengine - INFO - Epoch(train) [36][580/940] lr: 1.0000e-02 eta: 8:31:43 time: 0.4881 data_time: 0.0334 memory: 21547 grad_norm: 4.1352 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5136 loss: 1.5136 2022/10/10 02:31:55 - mmengine - INFO - Epoch(train) [36][600/940] lr: 1.0000e-02 eta: 8:31:31 time: 0.4688 data_time: 0.0271 memory: 21547 grad_norm: 4.1364 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6309 loss: 1.6309 2022/10/10 02:32:05 - mmengine - INFO - Epoch(train) [36][620/940] lr: 1.0000e-02 eta: 8:31:22 time: 0.5135 data_time: 0.0298 memory: 21547 grad_norm: 4.1790 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5863 loss: 1.5863 2022/10/10 02:32:15 - mmengine - INFO - Epoch(train) [36][640/940] lr: 1.0000e-02 eta: 8:31:12 time: 0.5172 data_time: 0.0316 memory: 21547 grad_norm: 4.2049 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.5739 loss: 1.5739 2022/10/10 02:32:26 - mmengine - INFO - Epoch(train) [36][660/940] lr: 1.0000e-02 eta: 8:31:03 time: 0.5581 data_time: 0.0257 memory: 21547 grad_norm: 4.1825 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5481 loss: 1.5481 2022/10/10 02:32:35 - mmengine - INFO - Epoch(train) [36][680/940] lr: 1.0000e-02 eta: 8:30:51 time: 0.4457 data_time: 0.0285 memory: 21547 grad_norm: 4.2369 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6739 loss: 1.6739 2022/10/10 02:32:45 - mmengine - INFO - Epoch(train) [36][700/940] lr: 1.0000e-02 eta: 8:30:41 time: 0.4961 data_time: 0.0260 memory: 21547 grad_norm: 4.1656 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6020 loss: 1.6020 2022/10/10 02:32:55 - mmengine - INFO - Epoch(train) [36][720/940] lr: 1.0000e-02 eta: 8:30:30 time: 0.4999 data_time: 0.0293 memory: 21547 grad_norm: 4.1628 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5817 loss: 1.5817 2022/10/10 02:33:06 - mmengine - INFO - Epoch(train) [36][740/940] lr: 1.0000e-02 eta: 8:30:20 time: 0.5150 data_time: 0.0265 memory: 21547 grad_norm: 4.0744 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.5768 loss: 1.5768 2022/10/10 02:33:16 - mmengine - INFO - Epoch(train) [36][760/940] lr: 1.0000e-02 eta: 8:30:11 time: 0.5414 data_time: 0.0325 memory: 21547 grad_norm: 4.1092 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7204 loss: 1.7204 2022/10/10 02:33:26 - mmengine - INFO - Epoch(train) [36][780/940] lr: 1.0000e-02 eta: 8:30:00 time: 0.4731 data_time: 0.0245 memory: 21547 grad_norm: 4.2441 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.5600 loss: 1.5600 2022/10/10 02:33:35 - mmengine - INFO - Epoch(train) [36][800/940] lr: 1.0000e-02 eta: 8:29:49 time: 0.4735 data_time: 0.0265 memory: 21547 grad_norm: 4.0929 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.6504 loss: 1.6504 2022/10/10 02:33:46 - mmengine - INFO - Epoch(train) [36][820/940] lr: 1.0000e-02 eta: 8:29:40 time: 0.5445 data_time: 0.0309 memory: 21547 grad_norm: 4.1800 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.4868 loss: 1.4868 2022/10/10 02:33:56 - mmengine - INFO - Epoch(train) [36][840/940] lr: 1.0000e-02 eta: 8:29:29 time: 0.4907 data_time: 0.0303 memory: 21547 grad_norm: 4.1858 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7274 loss: 1.7274 2022/10/10 02:34:06 - mmengine - INFO - Epoch(train) [36][860/940] lr: 1.0000e-02 eta: 8:29:18 time: 0.4969 data_time: 0.0320 memory: 21547 grad_norm: 4.1524 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6167 loss: 1.6167 2022/10/10 02:34:15 - mmengine - INFO - Epoch(train) [36][880/940] lr: 1.0000e-02 eta: 8:29:07 time: 0.4633 data_time: 0.0311 memory: 21547 grad_norm: 4.1703 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6091 loss: 1.6091 2022/10/10 02:34:26 - mmengine - INFO - Epoch(train) [36][900/940] lr: 1.0000e-02 eta: 8:28:58 time: 0.5413 data_time: 0.0330 memory: 21547 grad_norm: 4.1204 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.5497 loss: 1.5497 2022/10/10 02:34:36 - mmengine - INFO - Epoch(train) [36][920/940] lr: 1.0000e-02 eta: 8:28:46 time: 0.4723 data_time: 0.0318 memory: 21547 grad_norm: 4.2552 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4780 loss: 1.4780 2022/10/10 02:34:45 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 02:34:45 - mmengine - INFO - Epoch(train) [36][940/940] lr: 1.0000e-02 eta: 8:28:36 time: 0.4957 data_time: 0.0233 memory: 21547 grad_norm: 4.4484 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.6272 loss: 1.6272 2022/10/10 02:34:45 - mmengine - INFO - Saving checkpoint at 36 epochs 2022/10/10 02:34:59 - mmengine - INFO - Epoch(val) [36][20/78] eta: 0:00:35 time: 0.6097 data_time: 0.5040 memory: 3269 2022/10/10 02:35:07 - mmengine - INFO - Epoch(val) [36][40/78] eta: 0:00:16 time: 0.4244 data_time: 0.3191 memory: 3269 2022/10/10 02:35:18 - mmengine - INFO - Epoch(val) [36][60/78] eta: 0:00:09 time: 0.5486 data_time: 0.4423 memory: 3269 2022/10/10 02:35:27 - mmengine - INFO - Epoch(val) [36][78/78] acc/top1: 0.6301 acc/top5: 0.8437 acc/mean1: 0.6299 2022/10/10 02:35:41 - mmengine - INFO - Epoch(train) [37][20/940] lr: 1.0000e-02 eta: 8:28:32 time: 0.6970 data_time: 0.2584 memory: 21547 grad_norm: 4.1108 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5127 loss: 1.5127 2022/10/10 02:35:51 - mmengine - INFO - Epoch(train) [37][40/940] lr: 1.0000e-02 eta: 8:28:21 time: 0.4781 data_time: 0.0238 memory: 21547 grad_norm: 4.0511 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5549 loss: 1.5549 2022/10/10 02:36:02 - mmengine - INFO - Epoch(train) [37][60/940] lr: 1.0000e-02 eta: 8:28:13 time: 0.5486 data_time: 0.0354 memory: 21547 grad_norm: 4.0938 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5446 loss: 1.5446 2022/10/10 02:36:11 - mmengine - INFO - Epoch(train) [37][80/940] lr: 1.0000e-02 eta: 8:28:02 time: 0.4801 data_time: 0.0412 memory: 21547 grad_norm: 4.1299 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6724 loss: 1.6724 2022/10/10 02:36:21 - mmengine - INFO - Epoch(train) [37][100/940] lr: 1.0000e-02 eta: 8:27:51 time: 0.5043 data_time: 0.0296 memory: 21547 grad_norm: 4.0532 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5329 loss: 1.5329 2022/10/10 02:36:31 - mmengine - INFO - Epoch(train) [37][120/940] lr: 1.0000e-02 eta: 8:27:40 time: 0.4825 data_time: 0.0259 memory: 21547 grad_norm: 4.0391 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4826 loss: 1.4826 2022/10/10 02:36:42 - mmengine - INFO - Epoch(train) [37][140/940] lr: 1.0000e-02 eta: 8:27:31 time: 0.5453 data_time: 0.0314 memory: 21547 grad_norm: 4.1787 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5329 loss: 1.5329 2022/10/10 02:36:51 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 02:36:51 - mmengine - INFO - Epoch(train) [37][160/940] lr: 1.0000e-02 eta: 8:27:20 time: 0.4650 data_time: 0.0313 memory: 21547 grad_norm: 4.1142 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5896 loss: 1.5896 2022/10/10 02:37:03 - mmengine - INFO - Epoch(train) [37][180/940] lr: 1.0000e-02 eta: 8:27:11 time: 0.5587 data_time: 0.0301 memory: 21547 grad_norm: 4.1973 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5432 loss: 1.5432 2022/10/10 02:37:12 - mmengine - INFO - Epoch(train) [37][200/940] lr: 1.0000e-02 eta: 8:27:00 time: 0.4617 data_time: 0.0304 memory: 21547 grad_norm: 4.1235 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7111 loss: 1.7111 2022/10/10 02:37:22 - mmengine - INFO - Epoch(train) [37][220/940] lr: 1.0000e-02 eta: 8:26:50 time: 0.5231 data_time: 0.0308 memory: 21547 grad_norm: 4.1745 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.4989 loss: 1.4989 2022/10/10 02:37:33 - mmengine - INFO - Epoch(train) [37][240/940] lr: 1.0000e-02 eta: 8:26:40 time: 0.5176 data_time: 0.0271 memory: 21547 grad_norm: 4.0846 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5447 loss: 1.5447 2022/10/10 02:37:42 - mmengine - INFO - Epoch(train) [37][260/940] lr: 1.0000e-02 eta: 8:26:29 time: 0.4722 data_time: 0.0279 memory: 21547 grad_norm: 4.1764 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7428 loss: 1.7428 2022/10/10 02:37:52 - mmengine - INFO - Epoch(train) [37][280/940] lr: 1.0000e-02 eta: 8:26:19 time: 0.5201 data_time: 0.0264 memory: 21547 grad_norm: 4.1633 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7015 loss: 1.7015 2022/10/10 02:38:02 - mmengine - INFO - Epoch(train) [37][300/940] lr: 1.0000e-02 eta: 8:26:09 time: 0.4973 data_time: 0.0254 memory: 21547 grad_norm: 4.1465 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6239 loss: 1.6239 2022/10/10 02:38:13 - mmengine - INFO - Epoch(train) [37][320/940] lr: 1.0000e-02 eta: 8:25:59 time: 0.5126 data_time: 0.0265 memory: 21547 grad_norm: 4.1791 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.4861 loss: 1.4861 2022/10/10 02:38:22 - mmengine - INFO - Epoch(train) [37][340/940] lr: 1.0000e-02 eta: 8:25:47 time: 0.4736 data_time: 0.0284 memory: 21547 grad_norm: 4.0879 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.6320 loss: 1.6320 2022/10/10 02:38:32 - mmengine - INFO - Epoch(train) [37][360/940] lr: 1.0000e-02 eta: 8:25:37 time: 0.4961 data_time: 0.0259 memory: 21547 grad_norm: 4.0923 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5714 loss: 1.5714 2022/10/10 02:38:43 - mmengine - INFO - Epoch(train) [37][380/940] lr: 1.0000e-02 eta: 8:25:27 time: 0.5272 data_time: 0.0269 memory: 21547 grad_norm: 4.0994 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6048 loss: 1.6048 2022/10/10 02:38:53 - mmengine - INFO - Epoch(train) [37][400/940] lr: 1.0000e-02 eta: 8:25:17 time: 0.5085 data_time: 0.0318 memory: 21547 grad_norm: 4.0957 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5397 loss: 1.5397 2022/10/10 02:39:03 - mmengine - INFO - Epoch(train) [37][420/940] lr: 1.0000e-02 eta: 8:25:07 time: 0.5080 data_time: 0.0264 memory: 21547 grad_norm: 4.2054 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.6170 loss: 1.6170 2022/10/10 02:39:13 - mmengine - INFO - Epoch(train) [37][440/940] lr: 1.0000e-02 eta: 8:24:57 time: 0.4967 data_time: 0.0297 memory: 21547 grad_norm: 4.1926 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4824 loss: 1.4824 2022/10/10 02:39:24 - mmengine - INFO - Epoch(train) [37][460/940] lr: 1.0000e-02 eta: 8:24:48 time: 0.5423 data_time: 0.0268 memory: 21547 grad_norm: 4.1683 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5912 loss: 1.5912 2022/10/10 02:39:33 - mmengine - INFO - Epoch(train) [37][480/940] lr: 1.0000e-02 eta: 8:24:36 time: 0.4714 data_time: 0.0342 memory: 21547 grad_norm: 4.1600 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6881 loss: 1.6881 2022/10/10 02:39:43 - mmengine - INFO - Epoch(train) [37][500/940] lr: 1.0000e-02 eta: 8:24:25 time: 0.4838 data_time: 0.0307 memory: 21547 grad_norm: 4.1452 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6296 loss: 1.6296 2022/10/10 02:39:52 - mmengine - INFO - Epoch(train) [37][520/940] lr: 1.0000e-02 eta: 8:24:14 time: 0.4622 data_time: 0.0241 memory: 21547 grad_norm: 4.2396 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5723 loss: 1.5723 2022/10/10 02:40:02 - mmengine - INFO - Epoch(train) [37][540/940] lr: 1.0000e-02 eta: 8:24:04 time: 0.5221 data_time: 0.0276 memory: 21547 grad_norm: 4.2065 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.5246 loss: 1.5246 2022/10/10 02:40:13 - mmengine - INFO - Epoch(train) [37][560/940] lr: 1.0000e-02 eta: 8:23:55 time: 0.5410 data_time: 0.0324 memory: 21547 grad_norm: 4.1537 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5352 loss: 1.5352 2022/10/10 02:40:22 - mmengine - INFO - Epoch(train) [37][580/940] lr: 1.0000e-02 eta: 8:23:43 time: 0.4517 data_time: 0.0238 memory: 21547 grad_norm: 4.2067 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.6680 loss: 1.6680 2022/10/10 02:40:32 - mmengine - INFO - Epoch(train) [37][600/940] lr: 1.0000e-02 eta: 8:23:33 time: 0.5033 data_time: 0.0304 memory: 21547 grad_norm: 4.1767 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7795 loss: 1.7795 2022/10/10 02:40:43 - mmengine - INFO - Epoch(train) [37][620/940] lr: 1.0000e-02 eta: 8:23:23 time: 0.5097 data_time: 0.0322 memory: 21547 grad_norm: 4.2259 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9004 loss: 1.9004 2022/10/10 02:40:52 - mmengine - INFO - Epoch(train) [37][640/940] lr: 1.0000e-02 eta: 8:23:12 time: 0.4928 data_time: 0.0326 memory: 21547 grad_norm: 4.2098 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7094 loss: 1.7094 2022/10/10 02:41:03 - mmengine - INFO - Epoch(train) [37][660/940] lr: 1.0000e-02 eta: 8:23:03 time: 0.5259 data_time: 0.0248 memory: 21547 grad_norm: 4.1207 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5816 loss: 1.5816 2022/10/10 02:41:13 - mmengine - INFO - Epoch(train) [37][680/940] lr: 1.0000e-02 eta: 8:22:52 time: 0.4884 data_time: 0.0272 memory: 21547 grad_norm: 4.2330 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5363 loss: 1.5363 2022/10/10 02:41:23 - mmengine - INFO - Epoch(train) [37][700/940] lr: 1.0000e-02 eta: 8:22:42 time: 0.5098 data_time: 0.0262 memory: 21547 grad_norm: 4.1859 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6839 loss: 1.6839 2022/10/10 02:41:33 - mmengine - INFO - Epoch(train) [37][720/940] lr: 1.0000e-02 eta: 8:22:32 time: 0.5109 data_time: 0.0283 memory: 21547 grad_norm: 4.1149 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7072 loss: 1.7072 2022/10/10 02:41:43 - mmengine - INFO - Epoch(train) [37][740/940] lr: 1.0000e-02 eta: 8:22:21 time: 0.4898 data_time: 0.0269 memory: 21547 grad_norm: 4.1859 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.5112 loss: 1.5112 2022/10/10 02:41:53 - mmengine - INFO - Epoch(train) [37][760/940] lr: 1.0000e-02 eta: 8:22:11 time: 0.5192 data_time: 0.0241 memory: 21547 grad_norm: 4.2073 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6693 loss: 1.6693 2022/10/10 02:42:03 - mmengine - INFO - Epoch(train) [37][780/940] lr: 1.0000e-02 eta: 8:22:00 time: 0.4716 data_time: 0.0316 memory: 21547 grad_norm: 4.2081 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6601 loss: 1.6601 2022/10/10 02:42:13 - mmengine - INFO - Epoch(train) [37][800/940] lr: 1.0000e-02 eta: 8:21:50 time: 0.5286 data_time: 0.0260 memory: 21547 grad_norm: 4.1996 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.6265 loss: 1.6265 2022/10/10 02:42:23 - mmengine - INFO - Epoch(train) [37][820/940] lr: 1.0000e-02 eta: 8:21:40 time: 0.4853 data_time: 0.0334 memory: 21547 grad_norm: 4.1648 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5870 loss: 1.5870 2022/10/10 02:42:33 - mmengine - INFO - Epoch(train) [37][840/940] lr: 1.0000e-02 eta: 8:21:29 time: 0.5021 data_time: 0.0215 memory: 21547 grad_norm: 4.0567 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6360 loss: 1.6360 2022/10/10 02:42:42 - mmengine - INFO - Epoch(train) [37][860/940] lr: 1.0000e-02 eta: 8:21:17 time: 0.4520 data_time: 0.0281 memory: 21547 grad_norm: 4.1977 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6762 loss: 1.6762 2022/10/10 02:42:53 - mmengine - INFO - Epoch(train) [37][880/940] lr: 1.0000e-02 eta: 8:21:08 time: 0.5457 data_time: 0.0269 memory: 21547 grad_norm: 4.1582 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4548 loss: 1.4548 2022/10/10 02:43:03 - mmengine - INFO - Epoch(train) [37][900/940] lr: 1.0000e-02 eta: 8:20:57 time: 0.4872 data_time: 0.0316 memory: 21547 grad_norm: 4.1839 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6946 loss: 1.6946 2022/10/10 02:43:14 - mmengine - INFO - Epoch(train) [37][920/940] lr: 1.0000e-02 eta: 8:20:49 time: 0.5529 data_time: 0.0289 memory: 21547 grad_norm: 4.1656 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.6385 loss: 1.6385 2022/10/10 02:43:22 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 02:43:22 - mmengine - INFO - Epoch(train) [37][940/940] lr: 1.0000e-02 eta: 8:20:36 time: 0.4257 data_time: 0.0263 memory: 21547 grad_norm: 4.3724 top1_acc: 0.4286 top5_acc: 0.4286 loss_cls: 1.6528 loss: 1.6528 2022/10/10 02:43:35 - mmengine - INFO - Epoch(val) [37][20/78] eta: 0:00:35 time: 0.6079 data_time: 0.4987 memory: 3269 2022/10/10 02:43:43 - mmengine - INFO - Epoch(val) [37][40/78] eta: 0:00:16 time: 0.4218 data_time: 0.3139 memory: 3269 2022/10/10 02:43:54 - mmengine - INFO - Epoch(val) [37][60/78] eta: 0:00:09 time: 0.5529 data_time: 0.4472 memory: 3269 2022/10/10 02:44:04 - mmengine - INFO - Epoch(val) [37][78/78] acc/top1: 0.6323 acc/top5: 0.8443 acc/mean1: 0.6322 2022/10/10 02:44:19 - mmengine - INFO - Epoch(train) [38][20/940] lr: 1.0000e-02 eta: 8:20:33 time: 0.7313 data_time: 0.2043 memory: 21547 grad_norm: 4.2623 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6321 loss: 1.6321 2022/10/10 02:44:29 - mmengine - INFO - Epoch(train) [38][40/940] lr: 1.0000e-02 eta: 8:20:23 time: 0.5017 data_time: 0.0286 memory: 21547 grad_norm: 4.0642 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4391 loss: 1.4391 2022/10/10 02:44:39 - mmengine - INFO - Epoch(train) [38][60/940] lr: 1.0000e-02 eta: 8:20:12 time: 0.4836 data_time: 0.0285 memory: 21547 grad_norm: 4.0718 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5989 loss: 1.5989 2022/10/10 02:44:49 - mmengine - INFO - Epoch(train) [38][80/940] lr: 1.0000e-02 eta: 8:20:01 time: 0.4912 data_time: 0.0272 memory: 21547 grad_norm: 4.0822 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6315 loss: 1.6315 2022/10/10 02:44:59 - mmengine - INFO - Epoch(train) [38][100/940] lr: 1.0000e-02 eta: 8:19:52 time: 0.5263 data_time: 0.0280 memory: 21547 grad_norm: 4.1832 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4856 loss: 1.4856 2022/10/10 02:45:09 - mmengine - INFO - Epoch(train) [38][120/940] lr: 1.0000e-02 eta: 8:19:41 time: 0.4737 data_time: 0.0275 memory: 21547 grad_norm: 4.1824 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5882 loss: 1.5882 2022/10/10 02:45:20 - mmengine - INFO - Epoch(train) [38][140/940] lr: 1.0000e-02 eta: 8:19:32 time: 0.5556 data_time: 0.0288 memory: 21547 grad_norm: 4.1311 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.6099 loss: 1.6099 2022/10/10 02:45:29 - mmengine - INFO - Epoch(train) [38][160/940] lr: 1.0000e-02 eta: 8:19:20 time: 0.4617 data_time: 0.0242 memory: 21547 grad_norm: 4.1814 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 1.5678 loss: 1.5678 2022/10/10 02:45:40 - mmengine - INFO - Epoch(train) [38][180/940] lr: 1.0000e-02 eta: 8:19:13 time: 0.5762 data_time: 0.0278 memory: 21547 grad_norm: 4.1795 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6326 loss: 1.6326 2022/10/10 02:45:50 - mmengine - INFO - Epoch(train) [38][200/940] lr: 1.0000e-02 eta: 8:19:02 time: 0.5007 data_time: 0.0270 memory: 21547 grad_norm: 4.2386 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5399 loss: 1.5399 2022/10/10 02:46:00 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 02:46:00 - mmengine - INFO - Epoch(train) [38][220/940] lr: 1.0000e-02 eta: 8:18:52 time: 0.4990 data_time: 0.0269 memory: 21547 grad_norm: 4.0933 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4339 loss: 1.4339 2022/10/10 02:46:11 - mmengine - INFO - Epoch(train) [38][240/940] lr: 1.0000e-02 eta: 8:18:42 time: 0.5235 data_time: 0.0275 memory: 21547 grad_norm: 4.1080 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5616 loss: 1.5616 2022/10/10 02:46:21 - mmengine - INFO - Epoch(train) [38][260/940] lr: 1.0000e-02 eta: 8:18:32 time: 0.4953 data_time: 0.0228 memory: 21547 grad_norm: 4.1642 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6911 loss: 1.6911 2022/10/10 02:46:30 - mmengine - INFO - Epoch(train) [38][280/940] lr: 1.0000e-02 eta: 8:18:20 time: 0.4669 data_time: 0.0233 memory: 21547 grad_norm: 4.0641 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5429 loss: 1.5429 2022/10/10 02:46:40 - mmengine - INFO - Epoch(train) [38][300/940] lr: 1.0000e-02 eta: 8:18:10 time: 0.5041 data_time: 0.0264 memory: 21547 grad_norm: 4.1663 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.4058 loss: 1.4058 2022/10/10 02:46:50 - mmengine - INFO - Epoch(train) [38][320/940] lr: 1.0000e-02 eta: 8:17:59 time: 0.4944 data_time: 0.0319 memory: 21547 grad_norm: 4.1911 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4977 loss: 1.4977 2022/10/10 02:47:00 - mmengine - INFO - Epoch(train) [38][340/940] lr: 1.0000e-02 eta: 8:17:50 time: 0.5183 data_time: 0.0309 memory: 21547 grad_norm: 4.1735 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5921 loss: 1.5921 2022/10/10 02:47:10 - mmengine - INFO - Epoch(train) [38][360/940] lr: 1.0000e-02 eta: 8:17:38 time: 0.4704 data_time: 0.0289 memory: 21547 grad_norm: 4.2420 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6104 loss: 1.6104 2022/10/10 02:47:21 - mmengine - INFO - Epoch(train) [38][380/940] lr: 1.0000e-02 eta: 8:17:29 time: 0.5385 data_time: 0.0260 memory: 21547 grad_norm: 4.1201 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4333 loss: 1.4333 2022/10/10 02:47:30 - mmengine - INFO - Epoch(train) [38][400/940] lr: 1.0000e-02 eta: 8:17:18 time: 0.4921 data_time: 0.0340 memory: 21547 grad_norm: 4.2517 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6179 loss: 1.6179 2022/10/10 02:47:41 - mmengine - INFO - Epoch(train) [38][420/940] lr: 1.0000e-02 eta: 8:17:09 time: 0.5194 data_time: 0.0291 memory: 21547 grad_norm: 4.3252 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5369 loss: 1.5369 2022/10/10 02:47:51 - mmengine - INFO - Epoch(train) [38][440/940] lr: 1.0000e-02 eta: 8:16:58 time: 0.5019 data_time: 0.0281 memory: 21547 grad_norm: 4.1117 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5428 loss: 1.5428 2022/10/10 02:48:00 - mmengine - INFO - Epoch(train) [38][460/940] lr: 1.0000e-02 eta: 8:16:47 time: 0.4800 data_time: 0.0250 memory: 21547 grad_norm: 4.3312 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.4587 loss: 1.4587 2022/10/10 02:48:11 - mmengine - INFO - Epoch(train) [38][480/940] lr: 1.0000e-02 eta: 8:16:37 time: 0.5051 data_time: 0.0280 memory: 21547 grad_norm: 4.1485 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.6236 loss: 1.6236 2022/10/10 02:48:21 - mmengine - INFO - Epoch(train) [38][500/940] lr: 1.0000e-02 eta: 8:16:27 time: 0.5053 data_time: 0.0264 memory: 21547 grad_norm: 4.1447 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6098 loss: 1.6098 2022/10/10 02:48:31 - mmengine - INFO - Epoch(train) [38][520/940] lr: 1.0000e-02 eta: 8:16:17 time: 0.5016 data_time: 0.0321 memory: 21547 grad_norm: 4.1277 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4802 loss: 1.4802 2022/10/10 02:48:41 - mmengine - INFO - Epoch(train) [38][540/940] lr: 1.0000e-02 eta: 8:16:06 time: 0.4969 data_time: 0.0263 memory: 21547 grad_norm: 4.2748 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7691 loss: 1.7691 2022/10/10 02:48:50 - mmengine - INFO - Epoch(train) [38][560/940] lr: 1.0000e-02 eta: 8:15:55 time: 0.4720 data_time: 0.0258 memory: 21547 grad_norm: 4.0794 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4105 loss: 1.4105 2022/10/10 02:49:02 - mmengine - INFO - Epoch(train) [38][580/940] lr: 1.0000e-02 eta: 8:15:47 time: 0.5727 data_time: 0.0302 memory: 21547 grad_norm: 4.1605 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.6428 loss: 1.6428 2022/10/10 02:49:11 - mmengine - INFO - Epoch(train) [38][600/940] lr: 1.0000e-02 eta: 8:15:35 time: 0.4560 data_time: 0.0236 memory: 21547 grad_norm: 4.1985 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6006 loss: 1.6006 2022/10/10 02:49:21 - mmengine - INFO - Epoch(train) [38][620/940] lr: 1.0000e-02 eta: 8:15:25 time: 0.5194 data_time: 0.0279 memory: 21547 grad_norm: 4.0964 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5709 loss: 1.5709 2022/10/10 02:49:31 - mmengine - INFO - Epoch(train) [38][640/940] lr: 1.0000e-02 eta: 8:15:14 time: 0.4744 data_time: 0.0266 memory: 21547 grad_norm: 4.2201 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6415 loss: 1.6415 2022/10/10 02:49:41 - mmengine - INFO - Epoch(train) [38][660/940] lr: 1.0000e-02 eta: 8:15:05 time: 0.5347 data_time: 0.0275 memory: 21547 grad_norm: 4.1259 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.4832 loss: 1.4832 2022/10/10 02:49:51 - mmengine - INFO - Epoch(train) [38][680/940] lr: 1.0000e-02 eta: 8:14:55 time: 0.5066 data_time: 0.0326 memory: 21547 grad_norm: 4.2706 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.5790 loss: 1.5790 2022/10/10 02:50:01 - mmengine - INFO - Epoch(train) [38][700/940] lr: 1.0000e-02 eta: 8:14:44 time: 0.5051 data_time: 0.0306 memory: 21547 grad_norm: 4.2985 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5228 loss: 1.5228 2022/10/10 02:50:11 - mmengine - INFO - Epoch(train) [38][720/940] lr: 1.0000e-02 eta: 8:14:33 time: 0.4600 data_time: 0.0249 memory: 21547 grad_norm: 4.1865 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5860 loss: 1.5860 2022/10/10 02:50:21 - mmengine - INFO - Epoch(train) [38][740/940] lr: 1.0000e-02 eta: 8:14:23 time: 0.5367 data_time: 0.0297 memory: 21547 grad_norm: 4.2018 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4495 loss: 1.4495 2022/10/10 02:50:32 - mmengine - INFO - Epoch(train) [38][760/940] lr: 1.0000e-02 eta: 8:14:14 time: 0.5138 data_time: 0.0278 memory: 21547 grad_norm: 4.1785 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5955 loss: 1.5955 2022/10/10 02:50:41 - mmengine - INFO - Epoch(train) [38][780/940] lr: 1.0000e-02 eta: 8:14:03 time: 0.4801 data_time: 0.0269 memory: 21547 grad_norm: 4.1604 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.6332 loss: 1.6332 2022/10/10 02:50:51 - mmengine - INFO - Epoch(train) [38][800/940] lr: 1.0000e-02 eta: 8:13:52 time: 0.4888 data_time: 0.0307 memory: 21547 grad_norm: 4.1690 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6295 loss: 1.6295 2022/10/10 02:51:01 - mmengine - INFO - Epoch(train) [38][820/940] lr: 1.0000e-02 eta: 8:13:42 time: 0.5178 data_time: 0.0270 memory: 21547 grad_norm: 4.1352 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4974 loss: 1.4974 2022/10/10 02:51:11 - mmengine - INFO - Epoch(train) [38][840/940] lr: 1.0000e-02 eta: 8:13:31 time: 0.4934 data_time: 0.0309 memory: 21547 grad_norm: 4.1977 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5060 loss: 1.5060 2022/10/10 02:51:22 - mmengine - INFO - Epoch(train) [38][860/940] lr: 1.0000e-02 eta: 8:13:22 time: 0.5371 data_time: 0.0267 memory: 21547 grad_norm: 4.1077 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6170 loss: 1.6170 2022/10/10 02:51:32 - mmengine - INFO - Epoch(train) [38][880/940] lr: 1.0000e-02 eta: 8:13:12 time: 0.4975 data_time: 0.0288 memory: 21547 grad_norm: 4.1869 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6870 loss: 1.6870 2022/10/10 02:51:42 - mmengine - INFO - Epoch(train) [38][900/940] lr: 1.0000e-02 eta: 8:13:02 time: 0.5104 data_time: 0.0265 memory: 21547 grad_norm: 4.2142 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5953 loss: 1.5953 2022/10/10 02:51:52 - mmengine - INFO - Epoch(train) [38][920/940] lr: 1.0000e-02 eta: 8:12:50 time: 0.4675 data_time: 0.0270 memory: 21547 grad_norm: 4.1188 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5125 loss: 1.5125 2022/10/10 02:52:00 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 02:52:00 - mmengine - INFO - Epoch(train) [38][940/940] lr: 1.0000e-02 eta: 8:12:38 time: 0.4325 data_time: 0.0241 memory: 21547 grad_norm: 4.4442 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.5669 loss: 1.5669 2022/10/10 02:52:12 - mmengine - INFO - Epoch(val) [38][20/78] eta: 0:00:35 time: 0.6079 data_time: 0.4993 memory: 3269 2022/10/10 02:52:21 - mmengine - INFO - Epoch(val) [38][40/78] eta: 0:00:16 time: 0.4252 data_time: 0.3170 memory: 3269 2022/10/10 02:52:32 - mmengine - INFO - Epoch(val) [38][60/78] eta: 0:00:10 time: 0.5557 data_time: 0.4495 memory: 3269 2022/10/10 02:52:42 - mmengine - INFO - Epoch(val) [38][78/78] acc/top1: 0.6337 acc/top5: 0.8424 acc/mean1: 0.6335 2022/10/10 02:52:56 - mmengine - INFO - Epoch(train) [39][20/940] lr: 1.0000e-02 eta: 8:12:34 time: 0.6978 data_time: 0.3181 memory: 21547 grad_norm: 4.1437 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.5653 loss: 1.5653 2022/10/10 02:53:06 - mmengine - INFO - Epoch(train) [39][40/940] lr: 1.0000e-02 eta: 8:12:23 time: 0.4968 data_time: 0.1267 memory: 21547 grad_norm: 4.0895 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.5390 loss: 1.5390 2022/10/10 02:53:16 - mmengine - INFO - Epoch(train) [39][60/940] lr: 1.0000e-02 eta: 8:12:13 time: 0.5111 data_time: 0.1116 memory: 21547 grad_norm: 4.1213 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.5675 loss: 1.5675 2022/10/10 02:53:26 - mmengine - INFO - Epoch(train) [39][80/940] lr: 1.0000e-02 eta: 8:12:03 time: 0.5053 data_time: 0.0461 memory: 21547 grad_norm: 4.1645 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.4703 loss: 1.4703 2022/10/10 02:53:36 - mmengine - INFO - Epoch(train) [39][100/940] lr: 1.0000e-02 eta: 8:11:53 time: 0.5115 data_time: 0.0294 memory: 21547 grad_norm: 4.2153 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4864 loss: 1.4864 2022/10/10 02:53:45 - mmengine - INFO - Epoch(train) [39][120/940] lr: 1.0000e-02 eta: 8:11:41 time: 0.4575 data_time: 0.0246 memory: 21547 grad_norm: 4.1466 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.5174 loss: 1.5174 2022/10/10 02:53:56 - mmengine - INFO - Epoch(train) [39][140/940] lr: 1.0000e-02 eta: 8:11:32 time: 0.5362 data_time: 0.0306 memory: 21547 grad_norm: 4.0527 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5246 loss: 1.5246 2022/10/10 02:54:06 - mmengine - INFO - Epoch(train) [39][160/940] lr: 1.0000e-02 eta: 8:11:22 time: 0.5218 data_time: 0.0265 memory: 21547 grad_norm: 4.0794 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4975 loss: 1.4975 2022/10/10 02:54:16 - mmengine - INFO - Epoch(train) [39][180/940] lr: 1.0000e-02 eta: 8:11:11 time: 0.4733 data_time: 0.0323 memory: 21547 grad_norm: 4.1804 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6169 loss: 1.6169 2022/10/10 02:54:26 - mmengine - INFO - Epoch(train) [39][200/940] lr: 1.0000e-02 eta: 8:11:01 time: 0.5056 data_time: 0.0271 memory: 21547 grad_norm: 4.1800 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5151 loss: 1.5151 2022/10/10 02:54:36 - mmengine - INFO - Epoch(train) [39][220/940] lr: 1.0000e-02 eta: 8:10:50 time: 0.4781 data_time: 0.0310 memory: 21547 grad_norm: 4.1034 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4465 loss: 1.4465 2022/10/10 02:54:46 - mmengine - INFO - Epoch(train) [39][240/940] lr: 1.0000e-02 eta: 8:10:40 time: 0.5181 data_time: 0.0242 memory: 21547 grad_norm: 4.1841 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4560 loss: 1.4560 2022/10/10 02:54:56 - mmengine - INFO - Epoch(train) [39][260/940] lr: 1.0000e-02 eta: 8:10:29 time: 0.4921 data_time: 0.0334 memory: 21547 grad_norm: 4.1180 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5987 loss: 1.5987 2022/10/10 02:55:06 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 02:55:06 - mmengine - INFO - Epoch(train) [39][280/940] lr: 1.0000e-02 eta: 8:10:20 time: 0.5235 data_time: 0.0281 memory: 21547 grad_norm: 4.1282 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6668 loss: 1.6668 2022/10/10 02:55:15 - mmengine - INFO - Epoch(train) [39][300/940] lr: 1.0000e-02 eta: 8:10:08 time: 0.4462 data_time: 0.0320 memory: 21547 grad_norm: 4.3267 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6676 loss: 1.6676 2022/10/10 02:55:25 - mmengine - INFO - Epoch(train) [39][320/940] lr: 1.0000e-02 eta: 8:09:58 time: 0.5079 data_time: 0.0274 memory: 21547 grad_norm: 4.1538 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.7444 loss: 1.7444 2022/10/10 02:55:36 - mmengine - INFO - Epoch(train) [39][340/940] lr: 1.0000e-02 eta: 8:09:49 time: 0.5416 data_time: 0.0305 memory: 21547 grad_norm: 4.2322 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6935 loss: 1.6935 2022/10/10 02:55:46 - mmengine - INFO - Epoch(train) [39][360/940] lr: 1.0000e-02 eta: 8:09:39 time: 0.5130 data_time: 0.0245 memory: 21547 grad_norm: 4.1469 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.5307 loss: 1.5307 2022/10/10 02:55:57 - mmengine - INFO - Epoch(train) [39][380/940] lr: 1.0000e-02 eta: 8:09:30 time: 0.5490 data_time: 0.0267 memory: 21547 grad_norm: 4.1759 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5379 loss: 1.5379 2022/10/10 02:56:07 - mmengine - INFO - Epoch(train) [39][400/940] lr: 1.0000e-02 eta: 8:09:19 time: 0.4770 data_time: 0.0267 memory: 21547 grad_norm: 4.2214 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6023 loss: 1.6023 2022/10/10 02:56:17 - mmengine - INFO - Epoch(train) [39][420/940] lr: 1.0000e-02 eta: 8:09:09 time: 0.5156 data_time: 0.0276 memory: 21547 grad_norm: 4.2426 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5501 loss: 1.5501 2022/10/10 02:56:27 - mmengine - INFO - Epoch(train) [39][440/940] lr: 1.0000e-02 eta: 8:08:57 time: 0.4684 data_time: 0.0251 memory: 21547 grad_norm: 4.1676 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5765 loss: 1.5765 2022/10/10 02:56:37 - mmengine - INFO - Epoch(train) [39][460/940] lr: 1.0000e-02 eta: 8:08:48 time: 0.5386 data_time: 0.0319 memory: 21547 grad_norm: 4.1691 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.4398 loss: 1.4398 2022/10/10 02:56:47 - mmengine - INFO - Epoch(train) [39][480/940] lr: 1.0000e-02 eta: 8:08:38 time: 0.4986 data_time: 0.0269 memory: 21547 grad_norm: 4.2291 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5585 loss: 1.5585 2022/10/10 02:56:58 - mmengine - INFO - Epoch(train) [39][500/940] lr: 1.0000e-02 eta: 8:08:29 time: 0.5343 data_time: 0.0285 memory: 21547 grad_norm: 4.2192 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5910 loss: 1.5910 2022/10/10 02:57:08 - mmengine - INFO - Epoch(train) [39][520/940] lr: 1.0000e-02 eta: 8:08:18 time: 0.4897 data_time: 0.0245 memory: 21547 grad_norm: 4.2329 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6212 loss: 1.6212 2022/10/10 02:57:18 - mmengine - INFO - Epoch(train) [39][540/940] lr: 1.0000e-02 eta: 8:08:08 time: 0.5167 data_time: 0.0279 memory: 21547 grad_norm: 4.1881 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5158 loss: 1.5158 2022/10/10 02:57:28 - mmengine - INFO - Epoch(train) [39][560/940] lr: 1.0000e-02 eta: 8:07:57 time: 0.4881 data_time: 0.0223 memory: 21547 grad_norm: 4.1995 top1_acc: 0.4062 top5_acc: 0.8438 loss_cls: 1.5347 loss: 1.5347 2022/10/10 02:57:38 - mmengine - INFO - Epoch(train) [39][580/940] lr: 1.0000e-02 eta: 8:07:47 time: 0.4952 data_time: 0.0263 memory: 21547 grad_norm: 4.1359 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.4231 loss: 1.4231 2022/10/10 02:57:48 - mmengine - INFO - Epoch(train) [39][600/940] lr: 1.0000e-02 eta: 8:07:36 time: 0.4955 data_time: 0.0295 memory: 21547 grad_norm: 4.1394 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4981 loss: 1.4981 2022/10/10 02:57:58 - mmengine - INFO - Epoch(train) [39][620/940] lr: 1.0000e-02 eta: 8:07:26 time: 0.5201 data_time: 0.0310 memory: 21547 grad_norm: 4.2376 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.6460 loss: 1.6460 2022/10/10 02:58:07 - mmengine - INFO - Epoch(train) [39][640/940] lr: 1.0000e-02 eta: 8:07:15 time: 0.4627 data_time: 0.0307 memory: 21547 grad_norm: 4.2625 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.5711 loss: 1.5711 2022/10/10 02:58:17 - mmengine - INFO - Epoch(train) [39][660/940] lr: 1.0000e-02 eta: 8:07:04 time: 0.4912 data_time: 0.0260 memory: 21547 grad_norm: 4.1984 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4856 loss: 1.4856 2022/10/10 02:58:27 - mmengine - INFO - Epoch(train) [39][680/940] lr: 1.0000e-02 eta: 8:06:53 time: 0.4729 data_time: 0.0286 memory: 21547 grad_norm: 4.1942 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6503 loss: 1.6503 2022/10/10 02:58:37 - mmengine - INFO - Epoch(train) [39][700/940] lr: 1.0000e-02 eta: 8:06:44 time: 0.5361 data_time: 0.0284 memory: 21547 grad_norm: 4.1712 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6796 loss: 1.6796 2022/10/10 02:58:47 - mmengine - INFO - Epoch(train) [39][720/940] lr: 1.0000e-02 eta: 8:06:33 time: 0.4821 data_time: 0.0280 memory: 21547 grad_norm: 4.3020 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6962 loss: 1.6962 2022/10/10 02:58:58 - mmengine - INFO - Epoch(train) [39][740/940] lr: 1.0000e-02 eta: 8:06:23 time: 0.5222 data_time: 0.0288 memory: 21547 grad_norm: 4.1233 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6270 loss: 1.6270 2022/10/10 02:59:07 - mmengine - INFO - Epoch(train) [39][760/940] lr: 1.0000e-02 eta: 8:06:12 time: 0.4783 data_time: 0.0336 memory: 21547 grad_norm: 4.1195 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4565 loss: 1.4565 2022/10/10 02:59:18 - mmengine - INFO - Epoch(train) [39][780/940] lr: 1.0000e-02 eta: 8:06:03 time: 0.5454 data_time: 0.0240 memory: 21547 grad_norm: 4.1985 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4955 loss: 1.4955 2022/10/10 02:59:28 - mmengine - INFO - Epoch(train) [39][800/940] lr: 1.0000e-02 eta: 8:05:53 time: 0.5058 data_time: 0.0273 memory: 21547 grad_norm: 4.2217 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5192 loss: 1.5192 2022/10/10 02:59:39 - mmengine - INFO - Epoch(train) [39][820/940] lr: 1.0000e-02 eta: 8:05:44 time: 0.5454 data_time: 0.0261 memory: 21547 grad_norm: 4.2129 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.6973 loss: 1.6973 2022/10/10 02:59:49 - mmengine - INFO - Epoch(train) [39][840/940] lr: 1.0000e-02 eta: 8:05:33 time: 0.4804 data_time: 0.0228 memory: 21547 grad_norm: 4.1697 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.7921 loss: 1.7921 2022/10/10 02:59:59 - mmengine - INFO - Epoch(train) [39][860/940] lr: 1.0000e-02 eta: 8:05:23 time: 0.5162 data_time: 0.0315 memory: 21547 grad_norm: 4.2330 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6217 loss: 1.6217 2022/10/10 03:00:08 - mmengine - INFO - Epoch(train) [39][880/940] lr: 1.0000e-02 eta: 8:05:11 time: 0.4551 data_time: 0.0267 memory: 21547 grad_norm: 4.2496 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4778 loss: 1.4778 2022/10/10 03:00:19 - mmengine - INFO - Epoch(train) [39][900/940] lr: 1.0000e-02 eta: 8:05:02 time: 0.5262 data_time: 0.0261 memory: 21547 grad_norm: 4.2814 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6535 loss: 1.6535 2022/10/10 03:00:28 - mmengine - INFO - Epoch(train) [39][920/940] lr: 1.0000e-02 eta: 8:04:50 time: 0.4639 data_time: 0.0285 memory: 21547 grad_norm: 4.1667 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5459 loss: 1.5459 2022/10/10 03:00:37 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 03:00:37 - mmengine - INFO - Epoch(train) [39][940/940] lr: 1.0000e-02 eta: 8:04:39 time: 0.4764 data_time: 0.0221 memory: 21547 grad_norm: 4.4702 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.6042 loss: 1.6042 2022/10/10 03:00:37 - mmengine - INFO - Saving checkpoint at 39 epochs 2022/10/10 03:00:51 - mmengine - INFO - Epoch(val) [39][20/78] eta: 0:00:35 time: 0.6152 data_time: 0.5097 memory: 3269 2022/10/10 03:00:59 - mmengine - INFO - Epoch(val) [39][40/78] eta: 0:00:16 time: 0.4224 data_time: 0.3178 memory: 3269 2022/10/10 03:01:10 - mmengine - INFO - Epoch(val) [39][60/78] eta: 0:00:09 time: 0.5520 data_time: 0.4473 memory: 3269 2022/10/10 03:01:20 - mmengine - INFO - Epoch(val) [39][78/78] acc/top1: 0.6298 acc/top5: 0.8439 acc/mean1: 0.6297 2022/10/10 03:01:33 - mmengine - INFO - Epoch(train) [40][20/940] lr: 1.0000e-02 eta: 8:04:35 time: 0.6859 data_time: 0.2120 memory: 21547 grad_norm: 4.0504 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4308 loss: 1.4308 2022/10/10 03:01:43 - mmengine - INFO - Epoch(train) [40][40/940] lr: 1.0000e-02 eta: 8:04:24 time: 0.4928 data_time: 0.1169 memory: 21547 grad_norm: 4.1526 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5521 loss: 1.5521 2022/10/10 03:01:54 - mmengine - INFO - Epoch(train) [40][60/940] lr: 1.0000e-02 eta: 8:04:15 time: 0.5441 data_time: 0.1695 memory: 21547 grad_norm: 4.2006 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4215 loss: 1.4215 2022/10/10 03:02:04 - mmengine - INFO - Epoch(train) [40][80/940] lr: 1.0000e-02 eta: 8:04:04 time: 0.4814 data_time: 0.0543 memory: 21547 grad_norm: 4.1292 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5091 loss: 1.5091 2022/10/10 03:02:15 - mmengine - INFO - Epoch(train) [40][100/940] lr: 1.0000e-02 eta: 8:03:55 time: 0.5397 data_time: 0.0308 memory: 21547 grad_norm: 4.1026 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4557 loss: 1.4557 2022/10/10 03:02:25 - mmengine - INFO - Epoch(train) [40][120/940] lr: 1.0000e-02 eta: 8:03:46 time: 0.5332 data_time: 0.0275 memory: 21547 grad_norm: 4.2661 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.5512 loss: 1.5512 2022/10/10 03:02:36 - mmengine - INFO - Epoch(train) [40][140/940] lr: 1.0000e-02 eta: 8:03:36 time: 0.5328 data_time: 0.0244 memory: 21547 grad_norm: 4.1266 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.4891 loss: 1.4891 2022/10/10 03:02:45 - mmengine - INFO - Epoch(train) [40][160/940] lr: 1.0000e-02 eta: 8:03:24 time: 0.4344 data_time: 0.0269 memory: 21547 grad_norm: 4.1838 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5716 loss: 1.5716 2022/10/10 03:02:55 - mmengine - INFO - Epoch(train) [40][180/940] lr: 1.0000e-02 eta: 8:03:14 time: 0.5275 data_time: 0.0226 memory: 21547 grad_norm: 4.2403 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.6585 loss: 1.6585 2022/10/10 03:03:04 - mmengine - INFO - Epoch(train) [40][200/940] lr: 1.0000e-02 eta: 8:03:03 time: 0.4668 data_time: 0.0252 memory: 21547 grad_norm: 4.2786 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5266 loss: 1.5266 2022/10/10 03:03:16 - mmengine - INFO - Epoch(train) [40][220/940] lr: 1.0000e-02 eta: 8:02:55 time: 0.5755 data_time: 0.0235 memory: 21547 grad_norm: 4.2020 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5706 loss: 1.5706 2022/10/10 03:03:24 - mmengine - INFO - Epoch(train) [40][240/940] lr: 1.0000e-02 eta: 8:02:42 time: 0.4277 data_time: 0.0245 memory: 21547 grad_norm: 4.2146 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5397 loss: 1.5397 2022/10/10 03:03:36 - mmengine - INFO - Epoch(train) [40][260/940] lr: 1.0000e-02 eta: 8:02:34 time: 0.5586 data_time: 0.0243 memory: 21547 grad_norm: 4.2210 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5342 loss: 1.5342 2022/10/10 03:03:45 - mmengine - INFO - Epoch(train) [40][280/940] lr: 1.0000e-02 eta: 8:02:23 time: 0.4756 data_time: 0.0269 memory: 21547 grad_norm: 4.2612 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.5651 loss: 1.5651 2022/10/10 03:03:55 - mmengine - INFO - Epoch(train) [40][300/940] lr: 1.0000e-02 eta: 8:02:12 time: 0.4876 data_time: 0.0269 memory: 21547 grad_norm: 4.2396 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7114 loss: 1.7114 2022/10/10 03:04:06 - mmengine - INFO - Epoch(train) [40][320/940] lr: 1.0000e-02 eta: 8:02:03 time: 0.5404 data_time: 0.0257 memory: 21547 grad_norm: 4.1871 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.5758 loss: 1.5758 2022/10/10 03:04:16 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 03:04:16 - mmengine - INFO - Epoch(train) [40][340/940] lr: 1.0000e-02 eta: 8:01:53 time: 0.5158 data_time: 0.0238 memory: 21547 grad_norm: 4.1726 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5588 loss: 1.5588 2022/10/10 03:04:25 - mmengine - INFO - Epoch(train) [40][360/940] lr: 1.0000e-02 eta: 8:01:41 time: 0.4584 data_time: 0.0258 memory: 21547 grad_norm: 4.1891 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5682 loss: 1.5682 2022/10/10 03:04:35 - mmengine - INFO - Epoch(train) [40][380/940] lr: 1.0000e-02 eta: 8:01:30 time: 0.4639 data_time: 0.0235 memory: 21547 grad_norm: 4.2201 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6615 loss: 1.6615 2022/10/10 03:04:45 - mmengine - INFO - Epoch(train) [40][400/940] lr: 1.0000e-02 eta: 8:01:20 time: 0.5033 data_time: 0.0334 memory: 21547 grad_norm: 4.2406 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5785 loss: 1.5785 2022/10/10 03:04:55 - mmengine - INFO - Epoch(train) [40][420/940] lr: 1.0000e-02 eta: 8:01:10 time: 0.5247 data_time: 0.0278 memory: 21547 grad_norm: 4.1214 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4303 loss: 1.4303 2022/10/10 03:05:06 - mmengine - INFO - Epoch(train) [40][440/940] lr: 1.0000e-02 eta: 8:01:01 time: 0.5320 data_time: 0.0297 memory: 21547 grad_norm: 4.1965 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6468 loss: 1.6468 2022/10/10 03:05:16 - mmengine - INFO - Epoch(train) [40][460/940] lr: 1.0000e-02 eta: 8:00:51 time: 0.5156 data_time: 0.0272 memory: 21547 grad_norm: 4.1734 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5534 loss: 1.5534 2022/10/10 03:05:26 - mmengine - INFO - Epoch(train) [40][480/940] lr: 1.0000e-02 eta: 8:00:41 time: 0.5159 data_time: 0.0253 memory: 21547 grad_norm: 4.1839 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5096 loss: 1.5096 2022/10/10 03:05:37 - mmengine - INFO - Epoch(train) [40][500/940] lr: 1.0000e-02 eta: 8:00:31 time: 0.5180 data_time: 0.0295 memory: 21547 grad_norm: 4.2332 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5356 loss: 1.5356 2022/10/10 03:05:47 - mmengine - INFO - Epoch(train) [40][520/940] lr: 1.0000e-02 eta: 8:00:20 time: 0.4946 data_time: 0.0280 memory: 21547 grad_norm: 4.0751 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4726 loss: 1.4726 2022/10/10 03:05:56 - mmengine - INFO - Epoch(train) [40][540/940] lr: 1.0000e-02 eta: 8:00:09 time: 0.4683 data_time: 0.0299 memory: 21547 grad_norm: 4.1787 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5891 loss: 1.5891 2022/10/10 03:06:06 - mmengine - INFO - Epoch(train) [40][560/940] lr: 1.0000e-02 eta: 7:59:59 time: 0.5073 data_time: 0.0253 memory: 21547 grad_norm: 4.1426 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6250 loss: 1.6250 2022/10/10 03:06:16 - mmengine - INFO - Epoch(train) [40][580/940] lr: 1.0000e-02 eta: 7:59:48 time: 0.4762 data_time: 0.0244 memory: 21547 grad_norm: 4.1841 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.5405 loss: 1.5405 2022/10/10 03:06:25 - mmengine - INFO - Epoch(train) [40][600/940] lr: 1.0000e-02 eta: 7:59:37 time: 0.4862 data_time: 0.0250 memory: 21547 grad_norm: 4.2922 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6303 loss: 1.6303 2022/10/10 03:06:36 - mmengine - INFO - Epoch(train) [40][620/940] lr: 1.0000e-02 eta: 7:59:28 time: 0.5530 data_time: 0.0277 memory: 21547 grad_norm: 4.2011 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5924 loss: 1.5924 2022/10/10 03:06:45 - mmengine - INFO - Epoch(train) [40][640/940] lr: 1.0000e-02 eta: 7:59:17 time: 0.4533 data_time: 0.0252 memory: 21547 grad_norm: 4.2259 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4778 loss: 1.4778 2022/10/10 03:06:56 - mmengine - INFO - Epoch(train) [40][660/940] lr: 1.0000e-02 eta: 7:59:06 time: 0.5080 data_time: 0.0289 memory: 21547 grad_norm: 4.1278 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4979 loss: 1.4979 2022/10/10 03:07:06 - mmengine - INFO - Epoch(train) [40][680/940] lr: 1.0000e-02 eta: 7:58:57 time: 0.5214 data_time: 0.0375 memory: 21547 grad_norm: 4.2469 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7055 loss: 1.7055 2022/10/10 03:07:17 - mmengine - INFO - Epoch(train) [40][700/940] lr: 1.0000e-02 eta: 7:58:47 time: 0.5324 data_time: 0.0290 memory: 21547 grad_norm: 4.2979 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6823 loss: 1.6823 2022/10/10 03:07:26 - mmengine - INFO - Epoch(train) [40][720/940] lr: 1.0000e-02 eta: 7:58:36 time: 0.4690 data_time: 0.0278 memory: 21547 grad_norm: 4.3413 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5287 loss: 1.5287 2022/10/10 03:07:37 - mmengine - INFO - Epoch(train) [40][740/940] lr: 1.0000e-02 eta: 7:58:27 time: 0.5443 data_time: 0.0379 memory: 21547 grad_norm: 4.1993 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.6160 loss: 1.6160 2022/10/10 03:07:46 - mmengine - INFO - Epoch(train) [40][760/940] lr: 1.0000e-02 eta: 7:58:15 time: 0.4371 data_time: 0.0330 memory: 21547 grad_norm: 4.2068 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5031 loss: 1.5031 2022/10/10 03:07:57 - mmengine - INFO - Epoch(train) [40][780/940] lr: 1.0000e-02 eta: 7:58:06 time: 0.5443 data_time: 0.0372 memory: 21547 grad_norm: 4.2305 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5874 loss: 1.5874 2022/10/10 03:08:06 - mmengine - INFO - Epoch(train) [40][800/940] lr: 1.0000e-02 eta: 7:57:55 time: 0.4789 data_time: 0.0301 memory: 21547 grad_norm: 4.1864 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5536 loss: 1.5536 2022/10/10 03:08:17 - mmengine - INFO - Epoch(train) [40][820/940] lr: 1.0000e-02 eta: 7:57:45 time: 0.5326 data_time: 0.0250 memory: 21547 grad_norm: 4.2849 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5128 loss: 1.5128 2022/10/10 03:08:26 - mmengine - INFO - Epoch(train) [40][840/940] lr: 1.0000e-02 eta: 7:57:34 time: 0.4803 data_time: 0.0295 memory: 21547 grad_norm: 4.2821 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.6798 loss: 1.6798 2022/10/10 03:08:36 - mmengine - INFO - Epoch(train) [40][860/940] lr: 1.0000e-02 eta: 7:57:24 time: 0.4841 data_time: 0.0266 memory: 21547 grad_norm: 4.2560 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.6342 loss: 1.6342 2022/10/10 03:08:46 - mmengine - INFO - Epoch(train) [40][880/940] lr: 1.0000e-02 eta: 7:57:13 time: 0.4825 data_time: 0.0387 memory: 21547 grad_norm: 4.1941 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.5377 loss: 1.5377 2022/10/10 03:08:56 - mmengine - INFO - Epoch(train) [40][900/940] lr: 1.0000e-02 eta: 7:57:03 time: 0.5308 data_time: 0.0311 memory: 21547 grad_norm: 4.2754 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6990 loss: 1.6990 2022/10/10 03:09:06 - mmengine - INFO - Epoch(train) [40][920/940] lr: 1.0000e-02 eta: 7:56:53 time: 0.4859 data_time: 0.0358 memory: 21547 grad_norm: 4.2665 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4487 loss: 1.4487 2022/10/10 03:09:16 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 03:09:16 - mmengine - INFO - Epoch(train) [40][940/940] lr: 1.0000e-02 eta: 7:56:43 time: 0.5155 data_time: 0.0255 memory: 21547 grad_norm: 4.3111 top1_acc: 0.4286 top5_acc: 0.5714 loss_cls: 1.5693 loss: 1.5693 2022/10/10 03:09:29 - mmengine - INFO - Epoch(val) [40][20/78] eta: 0:00:35 time: 0.6035 data_time: 0.4937 memory: 3269 2022/10/10 03:09:37 - mmengine - INFO - Epoch(val) [40][40/78] eta: 0:00:16 time: 0.4234 data_time: 0.3168 memory: 3269 2022/10/10 03:09:48 - mmengine - INFO - Epoch(val) [40][60/78] eta: 0:00:09 time: 0.5554 data_time: 0.4508 memory: 3269 2022/10/10 03:09:58 - mmengine - INFO - Epoch(val) [40][78/78] acc/top1: 0.6317 acc/top5: 0.8439 acc/mean1: 0.6316 2022/10/10 03:10:12 - mmengine - INFO - Epoch(train) [41][20/940] lr: 1.0000e-03 eta: 7:56:39 time: 0.7131 data_time: 0.1986 memory: 21547 grad_norm: 4.1129 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3921 loss: 1.3921 2022/10/10 03:10:22 - mmengine - INFO - Epoch(train) [41][40/940] lr: 1.0000e-03 eta: 7:56:28 time: 0.4753 data_time: 0.0260 memory: 21547 grad_norm: 4.1486 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4707 loss: 1.4707 2022/10/10 03:10:33 - mmengine - INFO - Epoch(train) [41][60/940] lr: 1.0000e-03 eta: 7:56:19 time: 0.5534 data_time: 0.0356 memory: 21547 grad_norm: 4.1768 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5121 loss: 1.5121 2022/10/10 03:10:43 - mmengine - INFO - Epoch(train) [41][80/940] lr: 1.0000e-03 eta: 7:56:08 time: 0.4780 data_time: 0.0231 memory: 21547 grad_norm: 3.9183 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3331 loss: 1.3331 2022/10/10 03:10:53 - mmengine - INFO - Epoch(train) [41][100/940] lr: 1.0000e-03 eta: 7:55:58 time: 0.5068 data_time: 0.0299 memory: 21547 grad_norm: 4.0646 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4656 loss: 1.4656 2022/10/10 03:11:03 - mmengine - INFO - Epoch(train) [41][120/940] lr: 1.0000e-03 eta: 7:55:48 time: 0.5262 data_time: 0.0247 memory: 21547 grad_norm: 3.9505 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4883 loss: 1.4883 2022/10/10 03:11:13 - mmengine - INFO - Epoch(train) [41][140/940] lr: 1.0000e-03 eta: 7:55:37 time: 0.4732 data_time: 0.0350 memory: 21547 grad_norm: 4.0810 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.5025 loss: 1.5025 2022/10/10 03:11:22 - mmengine - INFO - Epoch(train) [41][160/940] lr: 1.0000e-03 eta: 7:55:25 time: 0.4593 data_time: 0.0325 memory: 21547 grad_norm: 3.9805 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.3235 loss: 1.3235 2022/10/10 03:11:32 - mmengine - INFO - Epoch(train) [41][180/940] lr: 1.0000e-03 eta: 7:55:16 time: 0.5314 data_time: 0.0261 memory: 21547 grad_norm: 3.9791 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.3789 loss: 1.3789 2022/10/10 03:11:43 - mmengine - INFO - Epoch(train) [41][200/940] lr: 1.0000e-03 eta: 7:55:06 time: 0.5010 data_time: 0.0286 memory: 21547 grad_norm: 4.0064 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3735 loss: 1.3735 2022/10/10 03:11:53 - mmengine - INFO - Epoch(train) [41][220/940] lr: 1.0000e-03 eta: 7:54:56 time: 0.5334 data_time: 0.0263 memory: 21547 grad_norm: 4.0172 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3482 loss: 1.3482 2022/10/10 03:12:03 - mmengine - INFO - Epoch(train) [41][240/940] lr: 1.0000e-03 eta: 7:54:45 time: 0.4703 data_time: 0.0247 memory: 21547 grad_norm: 4.0181 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5225 loss: 1.5225 2022/10/10 03:12:13 - mmengine - INFO - Epoch(train) [41][260/940] lr: 1.0000e-03 eta: 7:54:35 time: 0.5017 data_time: 0.0241 memory: 21547 grad_norm: 4.0092 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.5588 loss: 1.5588 2022/10/10 03:12:23 - mmengine - INFO - Epoch(train) [41][280/940] lr: 1.0000e-03 eta: 7:54:25 time: 0.5103 data_time: 0.0291 memory: 21547 grad_norm: 4.0651 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4212 loss: 1.4212 2022/10/10 03:12:33 - mmengine - INFO - Epoch(train) [41][300/940] lr: 1.0000e-03 eta: 7:54:14 time: 0.4994 data_time: 0.0261 memory: 21547 grad_norm: 4.0037 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3397 loss: 1.3397 2022/10/10 03:12:43 - mmengine - INFO - Epoch(train) [41][320/940] lr: 1.0000e-03 eta: 7:54:04 time: 0.4973 data_time: 0.0343 memory: 21547 grad_norm: 4.0495 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4794 loss: 1.4794 2022/10/10 03:12:53 - mmengine - INFO - Epoch(train) [41][340/940] lr: 1.0000e-03 eta: 7:53:54 time: 0.5183 data_time: 0.0311 memory: 21547 grad_norm: 4.0437 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.5577 loss: 1.5577 2022/10/10 03:13:04 - mmengine - INFO - Epoch(train) [41][360/940] lr: 1.0000e-03 eta: 7:53:45 time: 0.5347 data_time: 0.0334 memory: 21547 grad_norm: 4.0286 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4473 loss: 1.4473 2022/10/10 03:13:13 - mmengine - INFO - Epoch(train) [41][380/940] lr: 1.0000e-03 eta: 7:53:33 time: 0.4577 data_time: 0.0247 memory: 21547 grad_norm: 3.9286 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4391 loss: 1.4391 2022/10/10 03:13:23 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 03:13:23 - mmengine - INFO - Epoch(train) [41][400/940] lr: 1.0000e-03 eta: 7:53:23 time: 0.5068 data_time: 0.0279 memory: 21547 grad_norm: 3.9671 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3529 loss: 1.3529 2022/10/10 03:13:32 - mmengine - INFO - Epoch(train) [41][420/940] lr: 1.0000e-03 eta: 7:53:11 time: 0.4643 data_time: 0.0331 memory: 21547 grad_norm: 3.9536 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5521 loss: 1.5521 2022/10/10 03:13:43 - mmengine - INFO - Epoch(train) [41][440/940] lr: 1.0000e-03 eta: 7:53:02 time: 0.5154 data_time: 0.0297 memory: 21547 grad_norm: 3.9853 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4343 loss: 1.4343 2022/10/10 03:13:53 - mmengine - INFO - Epoch(train) [41][460/940] lr: 1.0000e-03 eta: 7:52:51 time: 0.5096 data_time: 0.0267 memory: 21547 grad_norm: 4.0208 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4114 loss: 1.4114 2022/10/10 03:14:03 - mmengine - INFO - Epoch(train) [41][480/940] lr: 1.0000e-03 eta: 7:52:41 time: 0.5080 data_time: 0.0279 memory: 21547 grad_norm: 4.0276 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4292 loss: 1.4292 2022/10/10 03:14:14 - mmengine - INFO - Epoch(train) [41][500/940] lr: 1.0000e-03 eta: 7:52:32 time: 0.5442 data_time: 0.0364 memory: 21547 grad_norm: 4.0234 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3870 loss: 1.3870 2022/10/10 03:14:23 - mmengine - INFO - Epoch(train) [41][520/940] lr: 1.0000e-03 eta: 7:52:20 time: 0.4422 data_time: 0.0268 memory: 21547 grad_norm: 3.9359 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4037 loss: 1.4037 2022/10/10 03:14:33 - mmengine - INFO - Epoch(train) [41][540/940] lr: 1.0000e-03 eta: 7:52:11 time: 0.5334 data_time: 0.0270 memory: 21547 grad_norm: 3.9100 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2647 loss: 1.2647 2022/10/10 03:14:43 - mmengine - INFO - Epoch(train) [41][560/940] lr: 1.0000e-03 eta: 7:52:00 time: 0.4898 data_time: 0.0243 memory: 21547 grad_norm: 3.9748 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4403 loss: 1.4403 2022/10/10 03:14:54 - mmengine - INFO - Epoch(train) [41][580/940] lr: 1.0000e-03 eta: 7:51:50 time: 0.5139 data_time: 0.0243 memory: 21547 grad_norm: 3.9581 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.3776 loss: 1.3776 2022/10/10 03:15:03 - mmengine - INFO - Epoch(train) [41][600/940] lr: 1.0000e-03 eta: 7:51:39 time: 0.4725 data_time: 0.0308 memory: 21547 grad_norm: 3.9546 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4918 loss: 1.4918 2022/10/10 03:15:14 - mmengine - INFO - Epoch(train) [41][620/940] lr: 1.0000e-03 eta: 7:51:30 time: 0.5434 data_time: 0.0237 memory: 21547 grad_norm: 3.9988 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4377 loss: 1.4377 2022/10/10 03:15:24 - mmengine - INFO - Epoch(train) [41][640/940] lr: 1.0000e-03 eta: 7:51:19 time: 0.4897 data_time: 0.0296 memory: 21547 grad_norm: 4.0107 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4266 loss: 1.4266 2022/10/10 03:15:34 - mmengine - INFO - Epoch(train) [41][660/940] lr: 1.0000e-03 eta: 7:51:09 time: 0.4988 data_time: 0.0242 memory: 21547 grad_norm: 3.8968 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4687 loss: 1.4687 2022/10/10 03:15:44 - mmengine - INFO - Epoch(train) [41][680/940] lr: 1.0000e-03 eta: 7:50:59 time: 0.4958 data_time: 0.0297 memory: 21547 grad_norm: 3.9629 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3714 loss: 1.3714 2022/10/10 03:15:54 - mmengine - INFO - Epoch(train) [41][700/940] lr: 1.0000e-03 eta: 7:50:49 time: 0.5360 data_time: 0.0238 memory: 21547 grad_norm: 3.8398 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3772 loss: 1.3772 2022/10/10 03:16:04 - mmengine - INFO - Epoch(train) [41][720/940] lr: 1.0000e-03 eta: 7:50:38 time: 0.4691 data_time: 0.0297 memory: 21547 grad_norm: 3.9161 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3461 loss: 1.3461 2022/10/10 03:16:15 - mmengine - INFO - Epoch(train) [41][740/940] lr: 1.0000e-03 eta: 7:50:29 time: 0.5424 data_time: 0.0234 memory: 21547 grad_norm: 3.8956 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3522 loss: 1.3522 2022/10/10 03:16:24 - mmengine - INFO - Epoch(train) [41][760/940] lr: 1.0000e-03 eta: 7:50:18 time: 0.4984 data_time: 0.0315 memory: 21547 grad_norm: 4.0514 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4887 loss: 1.4887 2022/10/10 03:16:34 - mmengine - INFO - Epoch(train) [41][780/940] lr: 1.0000e-03 eta: 7:50:08 time: 0.4961 data_time: 0.0298 memory: 21547 grad_norm: 3.9388 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.4785 loss: 1.4785 2022/10/10 03:16:45 - mmengine - INFO - Epoch(train) [41][800/940] lr: 1.0000e-03 eta: 7:49:58 time: 0.5277 data_time: 0.0350 memory: 21547 grad_norm: 3.9692 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2677 loss: 1.2677 2022/10/10 03:16:55 - mmengine - INFO - Epoch(train) [41][820/940] lr: 1.0000e-03 eta: 7:49:48 time: 0.4810 data_time: 0.0269 memory: 21547 grad_norm: 3.9596 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4085 loss: 1.4085 2022/10/10 03:17:04 - mmengine - INFO - Epoch(train) [41][840/940] lr: 1.0000e-03 eta: 7:49:37 time: 0.4912 data_time: 0.0228 memory: 21547 grad_norm: 3.9094 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3534 loss: 1.3534 2022/10/10 03:17:14 - mmengine - INFO - Epoch(train) [41][860/940] lr: 1.0000e-03 eta: 7:49:26 time: 0.4777 data_time: 0.0337 memory: 21547 grad_norm: 4.1462 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.4890 loss: 1.4890 2022/10/10 03:17:25 - mmengine - INFO - Epoch(train) [41][880/940] lr: 1.0000e-03 eta: 7:49:17 time: 0.5344 data_time: 0.0283 memory: 21547 grad_norm: 4.0787 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3757 loss: 1.3757 2022/10/10 03:17:34 - mmengine - INFO - Epoch(train) [41][900/940] lr: 1.0000e-03 eta: 7:49:06 time: 0.4883 data_time: 0.0295 memory: 21547 grad_norm: 3.9677 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3265 loss: 1.3265 2022/10/10 03:17:44 - mmengine - INFO - Epoch(train) [41][920/940] lr: 1.0000e-03 eta: 7:48:56 time: 0.5025 data_time: 0.0273 memory: 21547 grad_norm: 4.0228 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4549 loss: 1.4549 2022/10/10 03:17:53 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 03:17:53 - mmengine - INFO - Epoch(train) [41][940/940] lr: 1.0000e-03 eta: 7:48:44 time: 0.4505 data_time: 0.0204 memory: 21547 grad_norm: 4.0784 top1_acc: 0.4286 top5_acc: 0.5714 loss_cls: 1.2736 loss: 1.2736 2022/10/10 03:18:06 - mmengine - INFO - Epoch(val) [41][20/78] eta: 0:00:35 time: 0.6049 data_time: 0.4951 memory: 3269 2022/10/10 03:18:14 - mmengine - INFO - Epoch(val) [41][40/78] eta: 0:00:16 time: 0.4250 data_time: 0.3147 memory: 3269 2022/10/10 03:18:25 - mmengine - INFO - Epoch(val) [41][60/78] eta: 0:00:09 time: 0.5515 data_time: 0.4450 memory: 3269 2022/10/10 03:18:35 - mmengine - INFO - Epoch(val) [41][78/78] acc/top1: 0.6682 acc/top5: 0.8674 acc/mean1: 0.6681 2022/10/10 03:18:35 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_27.pth is removed 2022/10/10 03:18:36 - mmengine - INFO - The best checkpoint with 0.6682 acc/top1 at 41 epoch is saved to best_acc/top1_epoch_41.pth. 2022/10/10 03:18:50 - mmengine - INFO - Epoch(train) [42][20/940] lr: 1.0000e-03 eta: 7:48:40 time: 0.7187 data_time: 0.2887 memory: 21547 grad_norm: 3.8743 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3290 loss: 1.3290 2022/10/10 03:19:00 - mmengine - INFO - Epoch(train) [42][40/940] lr: 1.0000e-03 eta: 7:48:29 time: 0.4927 data_time: 0.0781 memory: 21547 grad_norm: 4.0355 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.4946 loss: 1.4946 2022/10/10 03:19:11 - mmengine - INFO - Epoch(train) [42][60/940] lr: 1.0000e-03 eta: 7:48:19 time: 0.5163 data_time: 0.1124 memory: 21547 grad_norm: 4.0546 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4349 loss: 1.4349 2022/10/10 03:19:20 - mmengine - INFO - Epoch(train) [42][80/940] lr: 1.0000e-03 eta: 7:48:08 time: 0.4502 data_time: 0.0444 memory: 21547 grad_norm: 3.9242 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3304 loss: 1.3304 2022/10/10 03:19:31 - mmengine - INFO - Epoch(train) [42][100/940] lr: 1.0000e-03 eta: 7:47:59 time: 0.5468 data_time: 0.1302 memory: 21547 grad_norm: 3.9916 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4244 loss: 1.4244 2022/10/10 03:19:40 - mmengine - INFO - Epoch(train) [42][120/940] lr: 1.0000e-03 eta: 7:47:47 time: 0.4611 data_time: 0.0710 memory: 21547 grad_norm: 4.0667 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3590 loss: 1.3590 2022/10/10 03:19:51 - mmengine - INFO - Epoch(train) [42][140/940] lr: 1.0000e-03 eta: 7:47:38 time: 0.5400 data_time: 0.1292 memory: 21547 grad_norm: 4.0078 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4459 loss: 1.4459 2022/10/10 03:19:59 - mmengine - INFO - Epoch(train) [42][160/940] lr: 1.0000e-03 eta: 7:47:26 time: 0.4404 data_time: 0.0542 memory: 21547 grad_norm: 4.0389 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4069 loss: 1.4069 2022/10/10 03:20:10 - mmengine - INFO - Epoch(train) [42][180/940] lr: 1.0000e-03 eta: 7:47:17 time: 0.5477 data_time: 0.0720 memory: 21547 grad_norm: 4.0015 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3711 loss: 1.3711 2022/10/10 03:20:20 - mmengine - INFO - Epoch(train) [42][200/940] lr: 1.0000e-03 eta: 7:47:05 time: 0.4655 data_time: 0.0614 memory: 21547 grad_norm: 3.9216 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.3999 loss: 1.3999 2022/10/10 03:20:30 - mmengine - INFO - Epoch(train) [42][220/940] lr: 1.0000e-03 eta: 7:46:56 time: 0.5270 data_time: 0.1597 memory: 21547 grad_norm: 3.9666 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2542 loss: 1.2542 2022/10/10 03:20:39 - mmengine - INFO - Epoch(train) [42][240/940] lr: 1.0000e-03 eta: 7:46:45 time: 0.4653 data_time: 0.0902 memory: 21547 grad_norm: 3.9874 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.3230 loss: 1.3230 2022/10/10 03:20:50 - mmengine - INFO - Epoch(train) [42][260/940] lr: 1.0000e-03 eta: 7:46:35 time: 0.5212 data_time: 0.1128 memory: 21547 grad_norm: 3.9542 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3989 loss: 1.3989 2022/10/10 03:21:00 - mmengine - INFO - Epoch(train) [42][280/940] lr: 1.0000e-03 eta: 7:46:25 time: 0.5009 data_time: 0.0499 memory: 21547 grad_norm: 3.9669 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4355 loss: 1.4355 2022/10/10 03:21:11 - mmengine - INFO - Epoch(train) [42][300/940] lr: 1.0000e-03 eta: 7:46:15 time: 0.5385 data_time: 0.0305 memory: 21547 grad_norm: 3.9784 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2849 loss: 1.2849 2022/10/10 03:21:20 - mmengine - INFO - Epoch(train) [42][320/940] lr: 1.0000e-03 eta: 7:46:04 time: 0.4601 data_time: 0.0248 memory: 21547 grad_norm: 3.9805 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3314 loss: 1.3314 2022/10/10 03:21:31 - mmengine - INFO - Epoch(train) [42][340/940] lr: 1.0000e-03 eta: 7:45:55 time: 0.5388 data_time: 0.0348 memory: 21547 grad_norm: 4.0744 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4662 loss: 1.4662 2022/10/10 03:21:41 - mmengine - INFO - Epoch(train) [42][360/940] lr: 1.0000e-03 eta: 7:45:44 time: 0.4959 data_time: 0.0280 memory: 21547 grad_norm: 4.1462 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4427 loss: 1.4427 2022/10/10 03:21:51 - mmengine - INFO - Epoch(train) [42][380/940] lr: 1.0000e-03 eta: 7:45:34 time: 0.5190 data_time: 0.0307 memory: 21547 grad_norm: 4.0088 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3845 loss: 1.3845 2022/10/10 03:22:00 - mmengine - INFO - Epoch(train) [42][400/940] lr: 1.0000e-03 eta: 7:45:23 time: 0.4660 data_time: 0.0247 memory: 21547 grad_norm: 4.0197 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3510 loss: 1.3510 2022/10/10 03:22:12 - mmengine - INFO - Epoch(train) [42][420/940] lr: 1.0000e-03 eta: 7:45:14 time: 0.5657 data_time: 0.0362 memory: 21547 grad_norm: 4.1042 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.3160 loss: 1.3160 2022/10/10 03:22:21 - mmengine - INFO - Epoch(train) [42][440/940] lr: 1.0000e-03 eta: 7:45:03 time: 0.4623 data_time: 0.0252 memory: 21547 grad_norm: 4.0166 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3677 loss: 1.3677 2022/10/10 03:22:31 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 03:22:31 - mmengine - INFO - Epoch(train) [42][460/940] lr: 1.0000e-03 eta: 7:44:54 time: 0.5289 data_time: 0.0311 memory: 21547 grad_norm: 4.1224 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4392 loss: 1.4392 2022/10/10 03:22:41 - mmengine - INFO - Epoch(train) [42][480/940] lr: 1.0000e-03 eta: 7:44:43 time: 0.4766 data_time: 0.0251 memory: 21547 grad_norm: 4.0701 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.4005 loss: 1.4005 2022/10/10 03:22:51 - mmengine - INFO - Epoch(train) [42][500/940] lr: 1.0000e-03 eta: 7:44:32 time: 0.5101 data_time: 0.0364 memory: 21547 grad_norm: 4.0445 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4297 loss: 1.4297 2022/10/10 03:23:01 - mmengine - INFO - Epoch(train) [42][520/940] lr: 1.0000e-03 eta: 7:44:21 time: 0.4754 data_time: 0.0681 memory: 21547 grad_norm: 3.9602 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4228 loss: 1.4228 2022/10/10 03:23:11 - mmengine - INFO - Epoch(train) [42][540/940] lr: 1.0000e-03 eta: 7:44:11 time: 0.5107 data_time: 0.0469 memory: 21547 grad_norm: 4.0530 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4025 loss: 1.4025 2022/10/10 03:23:20 - mmengine - INFO - Epoch(train) [42][560/940] lr: 1.0000e-03 eta: 7:44:00 time: 0.4634 data_time: 0.0263 memory: 21547 grad_norm: 3.9626 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3482 loss: 1.3482 2022/10/10 03:23:31 - mmengine - INFO - Epoch(train) [42][580/940] lr: 1.0000e-03 eta: 7:43:50 time: 0.5219 data_time: 0.0306 memory: 21547 grad_norm: 4.0415 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3390 loss: 1.3390 2022/10/10 03:23:41 - mmengine - INFO - Epoch(train) [42][600/940] lr: 1.0000e-03 eta: 7:43:40 time: 0.5075 data_time: 0.0274 memory: 21547 grad_norm: 4.0567 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3133 loss: 1.3133 2022/10/10 03:23:51 - mmengine - INFO - Epoch(train) [42][620/940] lr: 1.0000e-03 eta: 7:43:30 time: 0.5077 data_time: 0.0273 memory: 21547 grad_norm: 4.0755 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.4921 loss: 1.4921 2022/10/10 03:24:02 - mmengine - INFO - Epoch(train) [42][640/940] lr: 1.0000e-03 eta: 7:43:21 time: 0.5360 data_time: 0.0273 memory: 21547 grad_norm: 3.9593 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 1.4800 loss: 1.4800 2022/10/10 03:24:11 - mmengine - INFO - Epoch(train) [42][660/940] lr: 1.0000e-03 eta: 7:43:09 time: 0.4635 data_time: 0.0255 memory: 21547 grad_norm: 4.0395 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3640 loss: 1.3640 2022/10/10 03:24:21 - mmengine - INFO - Epoch(train) [42][680/940] lr: 1.0000e-03 eta: 7:43:00 time: 0.5241 data_time: 0.0294 memory: 21547 grad_norm: 3.9870 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4561 loss: 1.4561 2022/10/10 03:24:32 - mmengine - INFO - Epoch(train) [42][700/940] lr: 1.0000e-03 eta: 7:42:50 time: 0.5269 data_time: 0.0256 memory: 21547 grad_norm: 4.0431 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2463 loss: 1.2463 2022/10/10 03:24:42 - mmengine - INFO - Epoch(train) [42][720/940] lr: 1.0000e-03 eta: 7:42:40 time: 0.5001 data_time: 0.0275 memory: 21547 grad_norm: 4.1523 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3164 loss: 1.3164 2022/10/10 03:24:52 - mmengine - INFO - Epoch(train) [42][740/940] lr: 1.0000e-03 eta: 7:42:29 time: 0.4849 data_time: 0.0324 memory: 21547 grad_norm: 4.0539 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4499 loss: 1.4499 2022/10/10 03:25:02 - mmengine - INFO - Epoch(train) [42][760/940] lr: 1.0000e-03 eta: 7:42:19 time: 0.5008 data_time: 0.0235 memory: 21547 grad_norm: 4.0821 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3928 loss: 1.3928 2022/10/10 03:25:11 - mmengine - INFO - Epoch(train) [42][780/940] lr: 1.0000e-03 eta: 7:42:08 time: 0.4759 data_time: 0.0325 memory: 21547 grad_norm: 4.1102 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3194 loss: 1.3194 2022/10/10 03:25:21 - mmengine - INFO - Epoch(train) [42][800/940] lr: 1.0000e-03 eta: 7:41:57 time: 0.4967 data_time: 0.0341 memory: 21547 grad_norm: 4.0188 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3596 loss: 1.3596 2022/10/10 03:25:31 - mmengine - INFO - Epoch(train) [42][820/940] lr: 1.0000e-03 eta: 7:41:46 time: 0.4849 data_time: 0.0274 memory: 21547 grad_norm: 4.0199 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2983 loss: 1.2983 2022/10/10 03:25:41 - mmengine - INFO - Epoch(train) [42][840/940] lr: 1.0000e-03 eta: 7:41:36 time: 0.5113 data_time: 0.0329 memory: 21547 grad_norm: 4.0246 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.3758 loss: 1.3758 2022/10/10 03:25:51 - mmengine - INFO - Epoch(train) [42][860/940] lr: 1.0000e-03 eta: 7:41:26 time: 0.5134 data_time: 0.0268 memory: 21547 grad_norm: 4.0019 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3003 loss: 1.3003 2022/10/10 03:26:01 - mmengine - INFO - Epoch(train) [42][880/940] lr: 1.0000e-03 eta: 7:41:16 time: 0.4943 data_time: 0.0602 memory: 21547 grad_norm: 4.0229 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5032 loss: 1.5032 2022/10/10 03:26:11 - mmengine - INFO - Epoch(train) [42][900/940] lr: 1.0000e-03 eta: 7:41:05 time: 0.4943 data_time: 0.0213 memory: 21547 grad_norm: 3.9165 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4430 loss: 1.4430 2022/10/10 03:26:22 - mmengine - INFO - Epoch(train) [42][920/940] lr: 1.0000e-03 eta: 7:40:56 time: 0.5233 data_time: 0.0274 memory: 21547 grad_norm: 4.0257 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3247 loss: 1.3247 2022/10/10 03:26:31 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 03:26:31 - mmengine - INFO - Epoch(train) [42][940/940] lr: 1.0000e-03 eta: 7:40:45 time: 0.4667 data_time: 0.0227 memory: 21547 grad_norm: 4.2795 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.4100 loss: 1.4100 2022/10/10 03:26:31 - mmengine - INFO - Saving checkpoint at 42 epochs 2022/10/10 03:26:44 - mmengine - INFO - Epoch(val) [42][20/78] eta: 0:00:35 time: 0.6059 data_time: 0.5014 memory: 3269 2022/10/10 03:26:53 - mmengine - INFO - Epoch(val) [42][40/78] eta: 0:00:16 time: 0.4301 data_time: 0.3221 memory: 3269 2022/10/10 03:27:04 - mmengine - INFO - Epoch(val) [42][60/78] eta: 0:00:10 time: 0.5630 data_time: 0.4583 memory: 3269 2022/10/10 03:27:13 - mmengine - INFO - Epoch(val) [42][78/78] acc/top1: 0.6717 acc/top5: 0.8683 acc/mean1: 0.6715 2022/10/10 03:27:13 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_41.pth is removed 2022/10/10 03:27:13 - mmengine - INFO - The best checkpoint with 0.6717 acc/top1 at 42 epoch is saved to best_acc/top1_epoch_42.pth. 2022/10/10 03:27:31 - mmengine - INFO - Epoch(train) [43][20/940] lr: 1.0000e-03 eta: 7:40:44 time: 0.8613 data_time: 0.4866 memory: 21547 grad_norm: 4.0146 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.4527 loss: 1.4527 2022/10/10 03:27:41 - mmengine - INFO - Epoch(train) [43][40/940] lr: 1.0000e-03 eta: 7:40:34 time: 0.4954 data_time: 0.1109 memory: 21547 grad_norm: 3.9949 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3336 loss: 1.3336 2022/10/10 03:27:52 - mmengine - INFO - Epoch(train) [43][60/940] lr: 1.0000e-03 eta: 7:40:25 time: 0.5610 data_time: 0.1901 memory: 21547 grad_norm: 4.0338 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2891 loss: 1.2891 2022/10/10 03:28:01 - mmengine - INFO - Epoch(train) [43][80/940] lr: 1.0000e-03 eta: 7:40:13 time: 0.4513 data_time: 0.0832 memory: 21547 grad_norm: 4.0536 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4808 loss: 1.4808 2022/10/10 03:28:12 - mmengine - INFO - Epoch(train) [43][100/940] lr: 1.0000e-03 eta: 7:40:04 time: 0.5315 data_time: 0.1601 memory: 21547 grad_norm: 4.0265 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3592 loss: 1.3592 2022/10/10 03:28:21 - mmengine - INFO - Epoch(train) [43][120/940] lr: 1.0000e-03 eta: 7:39:53 time: 0.4855 data_time: 0.1064 memory: 21547 grad_norm: 4.0228 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4414 loss: 1.4414 2022/10/10 03:28:31 - mmengine - INFO - Epoch(train) [43][140/940] lr: 1.0000e-03 eta: 7:39:42 time: 0.4795 data_time: 0.0897 memory: 21547 grad_norm: 4.0469 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1841 loss: 1.1841 2022/10/10 03:28:40 - mmengine - INFO - Epoch(train) [43][160/940] lr: 1.0000e-03 eta: 7:39:31 time: 0.4732 data_time: 0.0984 memory: 21547 grad_norm: 4.0294 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4160 loss: 1.4160 2022/10/10 03:28:51 - mmengine - INFO - Epoch(train) [43][180/940] lr: 1.0000e-03 eta: 7:39:22 time: 0.5323 data_time: 0.1444 memory: 21547 grad_norm: 3.9808 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4523 loss: 1.4523 2022/10/10 03:29:00 - mmengine - INFO - Epoch(train) [43][200/940] lr: 1.0000e-03 eta: 7:39:10 time: 0.4597 data_time: 0.0597 memory: 21547 grad_norm: 4.0584 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2928 loss: 1.2928 2022/10/10 03:29:11 - mmengine - INFO - Epoch(train) [43][220/940] lr: 1.0000e-03 eta: 7:39:01 time: 0.5451 data_time: 0.0316 memory: 21547 grad_norm: 4.0394 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2697 loss: 1.2697 2022/10/10 03:29:21 - mmengine - INFO - Epoch(train) [43][240/940] lr: 1.0000e-03 eta: 7:38:50 time: 0.4743 data_time: 0.0296 memory: 21547 grad_norm: 4.0007 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3237 loss: 1.3237 2022/10/10 03:29:31 - mmengine - INFO - Epoch(train) [43][260/940] lr: 1.0000e-03 eta: 7:38:40 time: 0.5268 data_time: 0.0291 memory: 21547 grad_norm: 4.0112 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.3511 loss: 1.3511 2022/10/10 03:29:40 - mmengine - INFO - Epoch(train) [43][280/940] lr: 1.0000e-03 eta: 7:38:29 time: 0.4513 data_time: 0.0269 memory: 21547 grad_norm: 3.9979 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3359 loss: 1.3359 2022/10/10 03:29:51 - mmengine - INFO - Epoch(train) [43][300/940] lr: 1.0000e-03 eta: 7:38:19 time: 0.5263 data_time: 0.0392 memory: 21547 grad_norm: 4.0219 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2826 loss: 1.2826 2022/10/10 03:30:01 - mmengine - INFO - Epoch(train) [43][320/940] lr: 1.0000e-03 eta: 7:38:09 time: 0.5184 data_time: 0.0950 memory: 21547 grad_norm: 4.1060 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4052 loss: 1.4052 2022/10/10 03:30:12 - mmengine - INFO - Epoch(train) [43][340/940] lr: 1.0000e-03 eta: 7:38:00 time: 0.5328 data_time: 0.0416 memory: 21547 grad_norm: 4.0087 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3162 loss: 1.3162 2022/10/10 03:30:21 - mmengine - INFO - Epoch(train) [43][360/940] lr: 1.0000e-03 eta: 7:37:49 time: 0.4835 data_time: 0.0273 memory: 21547 grad_norm: 3.9811 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2994 loss: 1.2994 2022/10/10 03:30:31 - mmengine - INFO - Epoch(train) [43][380/940] lr: 1.0000e-03 eta: 7:37:38 time: 0.4857 data_time: 0.0304 memory: 21547 grad_norm: 4.0862 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2995 loss: 1.2995 2022/10/10 03:30:42 - mmengine - INFO - Epoch(train) [43][400/940] lr: 1.0000e-03 eta: 7:37:29 time: 0.5480 data_time: 0.0266 memory: 21547 grad_norm: 4.0248 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3460 loss: 1.3460 2022/10/10 03:30:51 - mmengine - INFO - Epoch(train) [43][420/940] lr: 1.0000e-03 eta: 7:37:18 time: 0.4744 data_time: 0.0301 memory: 21547 grad_norm: 3.9276 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2144 loss: 1.2144 2022/10/10 03:31:02 - mmengine - INFO - Epoch(train) [43][440/940] lr: 1.0000e-03 eta: 7:37:09 time: 0.5224 data_time: 0.0284 memory: 21547 grad_norm: 4.0460 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4082 loss: 1.4082 2022/10/10 03:31:12 - mmengine - INFO - Epoch(train) [43][460/940] lr: 1.0000e-03 eta: 7:36:58 time: 0.5056 data_time: 0.0325 memory: 21547 grad_norm: 4.0961 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3440 loss: 1.3440 2022/10/10 03:31:22 - mmengine - INFO - Epoch(train) [43][480/940] lr: 1.0000e-03 eta: 7:36:48 time: 0.4993 data_time: 0.0301 memory: 21547 grad_norm: 4.0520 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3129 loss: 1.3129 2022/10/10 03:31:32 - mmengine - INFO - Epoch(train) [43][500/940] lr: 1.0000e-03 eta: 7:36:38 time: 0.5020 data_time: 0.0281 memory: 21547 grad_norm: 4.1116 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.4059 loss: 1.4059 2022/10/10 03:31:42 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 03:31:42 - mmengine - INFO - Epoch(train) [43][520/940] lr: 1.0000e-03 eta: 7:36:27 time: 0.4800 data_time: 0.0299 memory: 21547 grad_norm: 3.9585 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3191 loss: 1.3191 2022/10/10 03:31:52 - mmengine - INFO - Epoch(train) [43][540/940] lr: 1.0000e-03 eta: 7:36:17 time: 0.5119 data_time: 0.0244 memory: 21547 grad_norm: 4.0912 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3744 loss: 1.3744 2022/10/10 03:32:02 - mmengine - INFO - Epoch(train) [43][560/940] lr: 1.0000e-03 eta: 7:36:06 time: 0.4850 data_time: 0.0270 memory: 21547 grad_norm: 4.0628 top1_acc: 0.5938 top5_acc: 0.9688 loss_cls: 1.3905 loss: 1.3905 2022/10/10 03:32:12 - mmengine - INFO - Epoch(train) [43][580/940] lr: 1.0000e-03 eta: 7:35:56 time: 0.5032 data_time: 0.0318 memory: 21547 grad_norm: 4.0873 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4902 loss: 1.4902 2022/10/10 03:32:22 - mmengine - INFO - Epoch(train) [43][600/940] lr: 1.0000e-03 eta: 7:35:46 time: 0.5012 data_time: 0.0284 memory: 21547 grad_norm: 4.0133 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.3445 loss: 1.3445 2022/10/10 03:32:32 - mmengine - INFO - Epoch(train) [43][620/940] lr: 1.0000e-03 eta: 7:35:36 time: 0.5213 data_time: 0.0329 memory: 21547 grad_norm: 4.0537 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2846 loss: 1.2846 2022/10/10 03:32:43 - mmengine - INFO - Epoch(train) [43][640/940] lr: 1.0000e-03 eta: 7:35:26 time: 0.5250 data_time: 0.0297 memory: 21547 grad_norm: 4.0951 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3853 loss: 1.3853 2022/10/10 03:32:52 - mmengine - INFO - Epoch(train) [43][660/940] lr: 1.0000e-03 eta: 7:35:15 time: 0.4703 data_time: 0.0299 memory: 21547 grad_norm: 4.1423 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4139 loss: 1.4139 2022/10/10 03:33:02 - mmengine - INFO - Epoch(train) [43][680/940] lr: 1.0000e-03 eta: 7:35:05 time: 0.5193 data_time: 0.0219 memory: 21547 grad_norm: 3.9758 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3360 loss: 1.3360 2022/10/10 03:33:12 - mmengine - INFO - Epoch(train) [43][700/940] lr: 1.0000e-03 eta: 7:34:55 time: 0.4979 data_time: 0.0357 memory: 21547 grad_norm: 4.0641 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.3592 loss: 1.3592 2022/10/10 03:33:23 - mmengine - INFO - Epoch(train) [43][720/940] lr: 1.0000e-03 eta: 7:34:45 time: 0.5288 data_time: 0.0282 memory: 21547 grad_norm: 4.0442 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4084 loss: 1.4084 2022/10/10 03:33:33 - mmengine - INFO - Epoch(train) [43][740/940] lr: 1.0000e-03 eta: 7:34:34 time: 0.4798 data_time: 0.0302 memory: 21547 grad_norm: 4.1424 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3764 loss: 1.3764 2022/10/10 03:33:42 - mmengine - INFO - Epoch(train) [43][760/940] lr: 1.0000e-03 eta: 7:34:23 time: 0.4741 data_time: 0.0279 memory: 21547 grad_norm: 4.1232 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4136 loss: 1.4136 2022/10/10 03:33:52 - mmengine - INFO - Epoch(train) [43][780/940] lr: 1.0000e-03 eta: 7:34:13 time: 0.5056 data_time: 0.0313 memory: 21547 grad_norm: 4.0293 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4385 loss: 1.4385 2022/10/10 03:34:03 - mmengine - INFO - Epoch(train) [43][800/940] lr: 1.0000e-03 eta: 7:34:04 time: 0.5386 data_time: 0.0308 memory: 21547 grad_norm: 4.0813 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3728 loss: 1.3728 2022/10/10 03:34:13 - mmengine - INFO - Epoch(train) [43][820/940] lr: 1.0000e-03 eta: 7:33:53 time: 0.4954 data_time: 0.0298 memory: 21547 grad_norm: 4.1235 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4454 loss: 1.4454 2022/10/10 03:34:23 - mmengine - INFO - Epoch(train) [43][840/940] lr: 1.0000e-03 eta: 7:33:43 time: 0.5133 data_time: 0.0272 memory: 21547 grad_norm: 4.0546 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.3323 loss: 1.3323 2022/10/10 03:34:32 - mmengine - INFO - Epoch(train) [43][860/940] lr: 1.0000e-03 eta: 7:33:32 time: 0.4692 data_time: 0.0277 memory: 21547 grad_norm: 3.9553 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2558 loss: 1.2558 2022/10/10 03:34:44 - mmengine - INFO - Epoch(train) [43][880/940] lr: 1.0000e-03 eta: 7:33:24 time: 0.5606 data_time: 0.0297 memory: 21547 grad_norm: 4.0845 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3391 loss: 1.3391 2022/10/10 03:34:53 - mmengine - INFO - Epoch(train) [43][900/940] lr: 1.0000e-03 eta: 7:33:12 time: 0.4621 data_time: 0.0340 memory: 21547 grad_norm: 4.1428 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4228 loss: 1.4228 2022/10/10 03:35:03 - mmengine - INFO - Epoch(train) [43][920/940] lr: 1.0000e-03 eta: 7:33:02 time: 0.5081 data_time: 0.0283 memory: 21547 grad_norm: 4.0987 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3212 loss: 1.3212 2022/10/10 03:35:12 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 03:35:12 - mmengine - INFO - Epoch(train) [43][940/940] lr: 1.0000e-03 eta: 7:32:50 time: 0.4398 data_time: 0.0250 memory: 21547 grad_norm: 4.2892 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.3353 loss: 1.3353 2022/10/10 03:35:24 - mmengine - INFO - Epoch(val) [43][20/78] eta: 0:00:35 time: 0.6062 data_time: 0.4957 memory: 3269 2022/10/10 03:35:32 - mmengine - INFO - Epoch(val) [43][40/78] eta: 0:00:15 time: 0.4200 data_time: 0.3126 memory: 3269 2022/10/10 03:35:44 - mmengine - INFO - Epoch(val) [43][60/78] eta: 0:00:10 time: 0.5588 data_time: 0.4512 memory: 3269 2022/10/10 03:35:54 - mmengine - INFO - Epoch(val) [43][78/78] acc/top1: 0.6728 acc/top5: 0.8701 acc/mean1: 0.6726 2022/10/10 03:35:54 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_42.pth is removed 2022/10/10 03:35:54 - mmengine - INFO - The best checkpoint with 0.6728 acc/top1 at 43 epoch is saved to best_acc/top1_epoch_43.pth. 2022/10/10 03:36:08 - mmengine - INFO - Epoch(train) [44][20/940] lr: 1.0000e-03 eta: 7:32:45 time: 0.6786 data_time: 0.3028 memory: 21547 grad_norm: 4.0742 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3138 loss: 1.3138 2022/10/10 03:36:17 - mmengine - INFO - Epoch(train) [44][40/940] lr: 1.0000e-03 eta: 7:32:34 time: 0.4873 data_time: 0.1243 memory: 21547 grad_norm: 4.1163 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3593 loss: 1.3593 2022/10/10 03:36:29 - mmengine - INFO - Epoch(train) [44][60/940] lr: 1.0000e-03 eta: 7:32:25 time: 0.5617 data_time: 0.1926 memory: 21547 grad_norm: 4.0840 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2773 loss: 1.2773 2022/10/10 03:36:38 - mmengine - INFO - Epoch(train) [44][80/940] lr: 1.0000e-03 eta: 7:32:14 time: 0.4808 data_time: 0.1051 memory: 21547 grad_norm: 4.0208 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3474 loss: 1.3474 2022/10/10 03:36:49 - mmengine - INFO - Epoch(train) [44][100/940] lr: 1.0000e-03 eta: 7:32:04 time: 0.5111 data_time: 0.1176 memory: 21547 grad_norm: 4.0453 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.4758 loss: 1.4758 2022/10/10 03:36:58 - mmengine - INFO - Epoch(train) [44][120/940] lr: 1.0000e-03 eta: 7:31:53 time: 0.4653 data_time: 0.0708 memory: 21547 grad_norm: 4.1670 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3881 loss: 1.3881 2022/10/10 03:37:08 - mmengine - INFO - Epoch(train) [44][140/940] lr: 1.0000e-03 eta: 7:31:43 time: 0.5172 data_time: 0.1046 memory: 21547 grad_norm: 4.0330 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4154 loss: 1.4154 2022/10/10 03:37:18 - mmengine - INFO - Epoch(train) [44][160/940] lr: 1.0000e-03 eta: 7:31:33 time: 0.5085 data_time: 0.0264 memory: 21547 grad_norm: 4.0496 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2006 loss: 1.2006 2022/10/10 03:37:28 - mmengine - INFO - Epoch(train) [44][180/940] lr: 1.0000e-03 eta: 7:31:22 time: 0.4764 data_time: 0.0604 memory: 21547 grad_norm: 4.0795 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3763 loss: 1.3763 2022/10/10 03:37:38 - mmengine - INFO - Epoch(train) [44][200/940] lr: 1.0000e-03 eta: 7:31:12 time: 0.4943 data_time: 0.0645 memory: 21547 grad_norm: 4.0847 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3798 loss: 1.3798 2022/10/10 03:37:48 - mmengine - INFO - Epoch(train) [44][220/940] lr: 1.0000e-03 eta: 7:31:02 time: 0.5156 data_time: 0.1113 memory: 21547 grad_norm: 4.0635 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3566 loss: 1.3566 2022/10/10 03:37:58 - mmengine - INFO - Epoch(train) [44][240/940] lr: 1.0000e-03 eta: 7:30:52 time: 0.5112 data_time: 0.0530 memory: 21547 grad_norm: 4.0672 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4406 loss: 1.4406 2022/10/10 03:38:09 - mmengine - INFO - Epoch(train) [44][260/940] lr: 1.0000e-03 eta: 7:30:42 time: 0.5194 data_time: 0.0310 memory: 21547 grad_norm: 4.1392 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3342 loss: 1.3342 2022/10/10 03:38:18 - mmengine - INFO - Epoch(train) [44][280/940] lr: 1.0000e-03 eta: 7:30:31 time: 0.4707 data_time: 0.0404 memory: 21547 grad_norm: 3.9829 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2839 loss: 1.2839 2022/10/10 03:38:29 - mmengine - INFO - Epoch(train) [44][300/940] lr: 1.0000e-03 eta: 7:30:21 time: 0.5220 data_time: 0.0358 memory: 21547 grad_norm: 4.0517 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2730 loss: 1.2730 2022/10/10 03:38:38 - mmengine - INFO - Epoch(train) [44][320/940] lr: 1.0000e-03 eta: 7:30:10 time: 0.4603 data_time: 0.0718 memory: 21547 grad_norm: 4.0022 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.3154 loss: 1.3154 2022/10/10 03:38:49 - mmengine - INFO - Epoch(train) [44][340/940] lr: 1.0000e-03 eta: 7:30:01 time: 0.5626 data_time: 0.0561 memory: 21547 grad_norm: 4.0978 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3642 loss: 1.3642 2022/10/10 03:38:58 - mmengine - INFO - Epoch(train) [44][360/940] lr: 1.0000e-03 eta: 7:29:50 time: 0.4582 data_time: 0.0248 memory: 21547 grad_norm: 4.0536 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3619 loss: 1.3619 2022/10/10 03:39:09 - mmengine - INFO - Epoch(train) [44][380/940] lr: 1.0000e-03 eta: 7:29:40 time: 0.5426 data_time: 0.0855 memory: 21547 grad_norm: 3.9442 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2071 loss: 1.2071 2022/10/10 03:39:19 - mmengine - INFO - Epoch(train) [44][400/940] lr: 1.0000e-03 eta: 7:29:30 time: 0.4977 data_time: 0.0273 memory: 21547 grad_norm: 4.1576 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3645 loss: 1.3645 2022/10/10 03:39:29 - mmengine - INFO - Epoch(train) [44][420/940] lr: 1.0000e-03 eta: 7:29:20 time: 0.5046 data_time: 0.0936 memory: 21547 grad_norm: 4.0001 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2952 loss: 1.2952 2022/10/10 03:39:38 - mmengine - INFO - Epoch(train) [44][440/940] lr: 1.0000e-03 eta: 7:29:09 time: 0.4678 data_time: 0.0422 memory: 21547 grad_norm: 4.0528 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3679 loss: 1.3679 2022/10/10 03:39:49 - mmengine - INFO - Epoch(train) [44][460/940] lr: 1.0000e-03 eta: 7:28:59 time: 0.5252 data_time: 0.0773 memory: 21547 grad_norm: 4.0881 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4550 loss: 1.4550 2022/10/10 03:39:58 - mmengine - INFO - Epoch(train) [44][480/940] lr: 1.0000e-03 eta: 7:28:48 time: 0.4710 data_time: 0.0272 memory: 21547 grad_norm: 4.0268 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2998 loss: 1.2998 2022/10/10 03:40:09 - mmengine - INFO - Epoch(train) [44][500/940] lr: 1.0000e-03 eta: 7:28:39 time: 0.5521 data_time: 0.0302 memory: 21547 grad_norm: 4.0781 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2630 loss: 1.2630 2022/10/10 03:40:19 - mmengine - INFO - Epoch(train) [44][520/940] lr: 1.0000e-03 eta: 7:28:28 time: 0.4922 data_time: 0.0542 memory: 21547 grad_norm: 4.1360 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3233 loss: 1.3233 2022/10/10 03:40:31 - mmengine - INFO - Epoch(train) [44][540/940] lr: 1.0000e-03 eta: 7:28:20 time: 0.5744 data_time: 0.0369 memory: 21547 grad_norm: 4.1184 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4053 loss: 1.4053 2022/10/10 03:40:40 - mmengine - INFO - Epoch(train) [44][560/940] lr: 1.0000e-03 eta: 7:28:08 time: 0.4560 data_time: 0.0220 memory: 21547 grad_norm: 4.0928 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4692 loss: 1.4692 2022/10/10 03:40:50 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 03:40:50 - mmengine - INFO - Epoch(train) [44][580/940] lr: 1.0000e-03 eta: 7:27:58 time: 0.5016 data_time: 0.0237 memory: 21547 grad_norm: 4.0769 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3657 loss: 1.3657 2022/10/10 03:41:00 - mmengine - INFO - Epoch(train) [44][600/940] lr: 1.0000e-03 eta: 7:27:47 time: 0.4835 data_time: 0.0273 memory: 21547 grad_norm: 4.1408 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4415 loss: 1.4415 2022/10/10 03:41:10 - mmengine - INFO - Epoch(train) [44][620/940] lr: 1.0000e-03 eta: 7:27:37 time: 0.4985 data_time: 0.0265 memory: 21547 grad_norm: 4.0425 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.3847 loss: 1.3847 2022/10/10 03:41:18 - mmengine - INFO - Epoch(train) [44][640/940] lr: 1.0000e-03 eta: 7:27:25 time: 0.4379 data_time: 0.0259 memory: 21547 grad_norm: 4.1146 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3815 loss: 1.3815 2022/10/10 03:41:29 - mmengine - INFO - Epoch(train) [44][660/940] lr: 1.0000e-03 eta: 7:27:16 time: 0.5332 data_time: 0.0270 memory: 21547 grad_norm: 4.1883 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4621 loss: 1.4621 2022/10/10 03:41:40 - mmengine - INFO - Epoch(train) [44][680/940] lr: 1.0000e-03 eta: 7:27:06 time: 0.5341 data_time: 0.0362 memory: 21547 grad_norm: 4.0525 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2565 loss: 1.2565 2022/10/10 03:41:49 - mmengine - INFO - Epoch(train) [44][700/940] lr: 1.0000e-03 eta: 7:26:55 time: 0.4825 data_time: 0.0297 memory: 21547 grad_norm: 4.0618 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2825 loss: 1.2825 2022/10/10 03:41:59 - mmengine - INFO - Epoch(train) [44][720/940] lr: 1.0000e-03 eta: 7:26:45 time: 0.4987 data_time: 0.0281 memory: 21547 grad_norm: 4.2382 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4262 loss: 1.4262 2022/10/10 03:42:08 - mmengine - INFO - Epoch(train) [44][740/940] lr: 1.0000e-03 eta: 7:26:34 time: 0.4570 data_time: 0.0286 memory: 21547 grad_norm: 4.0400 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4007 loss: 1.4007 2022/10/10 03:42:19 - mmengine - INFO - Epoch(train) [44][760/940] lr: 1.0000e-03 eta: 7:26:24 time: 0.5308 data_time: 0.0315 memory: 21547 grad_norm: 4.1196 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3469 loss: 1.3469 2022/10/10 03:42:29 - mmengine - INFO - Epoch(train) [44][780/940] lr: 1.0000e-03 eta: 7:26:13 time: 0.4757 data_time: 0.0320 memory: 21547 grad_norm: 4.0735 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3512 loss: 1.3512 2022/10/10 03:42:39 - mmengine - INFO - Epoch(train) [44][800/940] lr: 1.0000e-03 eta: 7:26:04 time: 0.5403 data_time: 0.0242 memory: 21547 grad_norm: 4.0556 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4339 loss: 1.4339 2022/10/10 03:42:49 - mmengine - INFO - Epoch(train) [44][820/940] lr: 1.0000e-03 eta: 7:25:53 time: 0.4936 data_time: 0.0270 memory: 21547 grad_norm: 4.1985 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3669 loss: 1.3669 2022/10/10 03:43:00 - mmengine - INFO - Epoch(train) [44][840/940] lr: 1.0000e-03 eta: 7:25:44 time: 0.5245 data_time: 0.0280 memory: 21547 grad_norm: 3.9610 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2410 loss: 1.2410 2022/10/10 03:43:09 - mmengine - INFO - Epoch(train) [44][860/940] lr: 1.0000e-03 eta: 7:25:33 time: 0.4812 data_time: 0.0238 memory: 21547 grad_norm: 4.0987 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2491 loss: 1.2491 2022/10/10 03:43:20 - mmengine - INFO - Epoch(train) [44][880/940] lr: 1.0000e-03 eta: 7:25:23 time: 0.5312 data_time: 0.0278 memory: 21547 grad_norm: 4.0398 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.3174 loss: 1.3174 2022/10/10 03:43:30 - mmengine - INFO - Epoch(train) [44][900/940] lr: 1.0000e-03 eta: 7:25:12 time: 0.4761 data_time: 0.0290 memory: 21547 grad_norm: 4.0992 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.3623 loss: 1.3623 2022/10/10 03:43:40 - mmengine - INFO - Epoch(train) [44][920/940] lr: 1.0000e-03 eta: 7:25:02 time: 0.5028 data_time: 0.0242 memory: 21547 grad_norm: 4.0853 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3011 loss: 1.3011 2022/10/10 03:43:49 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 03:43:49 - mmengine - INFO - Epoch(train) [44][940/940] lr: 1.0000e-03 eta: 7:24:51 time: 0.4632 data_time: 0.0243 memory: 21547 grad_norm: 4.2856 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.2382 loss: 1.2382 2022/10/10 03:44:01 - mmengine - INFO - Epoch(val) [44][20/78] eta: 0:00:35 time: 0.6062 data_time: 0.4997 memory: 3269 2022/10/10 03:44:09 - mmengine - INFO - Epoch(val) [44][40/78] eta: 0:00:16 time: 0.4239 data_time: 0.3165 memory: 3269 2022/10/10 03:44:21 - mmengine - INFO - Epoch(val) [44][60/78] eta: 0:00:10 time: 0.5611 data_time: 0.4532 memory: 3269 2022/10/10 03:44:30 - mmengine - INFO - Epoch(val) [44][78/78] acc/top1: 0.6748 acc/top5: 0.8700 acc/mean1: 0.6747 2022/10/10 03:44:30 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_43.pth is removed 2022/10/10 03:44:31 - mmengine - INFO - The best checkpoint with 0.6748 acc/top1 at 44 epoch is saved to best_acc/top1_epoch_44.pth. 2022/10/10 03:44:45 - mmengine - INFO - Epoch(train) [45][20/940] lr: 1.0000e-03 eta: 7:24:45 time: 0.6922 data_time: 0.3096 memory: 21547 grad_norm: 4.0223 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3971 loss: 1.3971 2022/10/10 03:44:55 - mmengine - INFO - Epoch(train) [45][40/940] lr: 1.0000e-03 eta: 7:24:35 time: 0.4846 data_time: 0.0383 memory: 21547 grad_norm: 3.9704 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3052 loss: 1.3052 2022/10/10 03:45:06 - mmengine - INFO - Epoch(train) [45][60/940] lr: 1.0000e-03 eta: 7:24:26 time: 0.5479 data_time: 0.0964 memory: 21547 grad_norm: 4.1322 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4117 loss: 1.4117 2022/10/10 03:45:15 - mmengine - INFO - Epoch(train) [45][80/940] lr: 1.0000e-03 eta: 7:24:15 time: 0.4836 data_time: 0.1068 memory: 21547 grad_norm: 4.0384 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1894 loss: 1.1894 2022/10/10 03:45:26 - mmengine - INFO - Epoch(train) [45][100/940] lr: 1.0000e-03 eta: 7:24:05 time: 0.5338 data_time: 0.1507 memory: 21547 grad_norm: 4.1194 top1_acc: 0.5312 top5_acc: 0.6250 loss_cls: 1.2302 loss: 1.2302 2022/10/10 03:45:35 - mmengine - INFO - Epoch(train) [45][120/940] lr: 1.0000e-03 eta: 7:23:54 time: 0.4712 data_time: 0.0866 memory: 21547 grad_norm: 4.1481 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3222 loss: 1.3222 2022/10/10 03:45:45 - mmengine - INFO - Epoch(train) [45][140/940] lr: 1.0000e-03 eta: 7:23:44 time: 0.4888 data_time: 0.0953 memory: 21547 grad_norm: 4.0892 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3178 loss: 1.3178 2022/10/10 03:45:55 - mmengine - INFO - Epoch(train) [45][160/940] lr: 1.0000e-03 eta: 7:23:33 time: 0.4995 data_time: 0.0418 memory: 21547 grad_norm: 4.0955 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3292 loss: 1.3292 2022/10/10 03:46:06 - mmengine - INFO - Epoch(train) [45][180/940] lr: 1.0000e-03 eta: 7:23:24 time: 0.5241 data_time: 0.1032 memory: 21547 grad_norm: 4.0996 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2441 loss: 1.2441 2022/10/10 03:46:15 - mmengine - INFO - Epoch(train) [45][200/940] lr: 1.0000e-03 eta: 7:23:13 time: 0.4872 data_time: 0.0421 memory: 21547 grad_norm: 4.1377 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3405 loss: 1.3405 2022/10/10 03:46:25 - mmengine - INFO - Epoch(train) [45][220/940] lr: 1.0000e-03 eta: 7:23:03 time: 0.4930 data_time: 0.0397 memory: 21547 grad_norm: 4.0242 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2537 loss: 1.2537 2022/10/10 03:46:35 - mmengine - INFO - Epoch(train) [45][240/940] lr: 1.0000e-03 eta: 7:22:53 time: 0.5169 data_time: 0.0274 memory: 21547 grad_norm: 3.9836 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3354 loss: 1.3354 2022/10/10 03:46:45 - mmengine - INFO - Epoch(train) [45][260/940] lr: 1.0000e-03 eta: 7:22:41 time: 0.4568 data_time: 0.0301 memory: 21547 grad_norm: 4.0596 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3936 loss: 1.3936 2022/10/10 03:46:54 - mmengine - INFO - Epoch(train) [45][280/940] lr: 1.0000e-03 eta: 7:22:31 time: 0.4868 data_time: 0.0234 memory: 21547 grad_norm: 4.1653 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2922 loss: 1.2922 2022/10/10 03:47:06 - mmengine - INFO - Epoch(train) [45][300/940] lr: 1.0000e-03 eta: 7:22:22 time: 0.5794 data_time: 0.0311 memory: 21547 grad_norm: 4.1054 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3732 loss: 1.3732 2022/10/10 03:47:15 - mmengine - INFO - Epoch(train) [45][320/940] lr: 1.0000e-03 eta: 7:22:11 time: 0.4478 data_time: 0.0250 memory: 21547 grad_norm: 4.1160 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3048 loss: 1.3048 2022/10/10 03:47:25 - mmengine - INFO - Epoch(train) [45][340/940] lr: 1.0000e-03 eta: 7:22:01 time: 0.5111 data_time: 0.0287 memory: 21547 grad_norm: 4.1215 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2781 loss: 1.2781 2022/10/10 03:47:36 - mmengine - INFO - Epoch(train) [45][360/940] lr: 1.0000e-03 eta: 7:21:51 time: 0.5363 data_time: 0.0266 memory: 21547 grad_norm: 4.0928 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3734 loss: 1.3734 2022/10/10 03:47:46 - mmengine - INFO - Epoch(train) [45][380/940] lr: 1.0000e-03 eta: 7:21:40 time: 0.4852 data_time: 0.0308 memory: 21547 grad_norm: 4.0558 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1869 loss: 1.1869 2022/10/10 03:47:55 - mmengine - INFO - Epoch(train) [45][400/940] lr: 1.0000e-03 eta: 7:21:30 time: 0.4809 data_time: 0.0285 memory: 21547 grad_norm: 4.0750 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3722 loss: 1.3722 2022/10/10 03:48:06 - mmengine - INFO - Epoch(train) [45][420/940] lr: 1.0000e-03 eta: 7:21:20 time: 0.5190 data_time: 0.0300 memory: 21547 grad_norm: 4.1689 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2764 loss: 1.2764 2022/10/10 03:48:16 - mmengine - INFO - Epoch(train) [45][440/940] lr: 1.0000e-03 eta: 7:21:10 time: 0.5241 data_time: 0.0282 memory: 21547 grad_norm: 4.0744 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2817 loss: 1.2817 2022/10/10 03:48:26 - mmengine - INFO - Epoch(train) [45][460/940] lr: 1.0000e-03 eta: 7:21:00 time: 0.5020 data_time: 0.0319 memory: 21547 grad_norm: 4.1134 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3738 loss: 1.3738 2022/10/10 03:48:36 - mmengine - INFO - Epoch(train) [45][480/940] lr: 1.0000e-03 eta: 7:20:49 time: 0.4805 data_time: 0.0271 memory: 21547 grad_norm: 4.1260 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3026 loss: 1.3026 2022/10/10 03:48:47 - mmengine - INFO - Epoch(train) [45][500/940] lr: 1.0000e-03 eta: 7:20:40 time: 0.5446 data_time: 0.0299 memory: 21547 grad_norm: 4.0787 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4097 loss: 1.4097 2022/10/10 03:48:56 - mmengine - INFO - Epoch(train) [45][520/940] lr: 1.0000e-03 eta: 7:20:29 time: 0.4940 data_time: 0.0311 memory: 21547 grad_norm: 4.2036 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4187 loss: 1.4187 2022/10/10 03:49:06 - mmengine - INFO - Epoch(train) [45][540/940] lr: 1.0000e-03 eta: 7:20:19 time: 0.4850 data_time: 0.0223 memory: 21547 grad_norm: 4.0822 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3163 loss: 1.3163 2022/10/10 03:49:17 - mmengine - INFO - Epoch(train) [45][560/940] lr: 1.0000e-03 eta: 7:20:10 time: 0.5482 data_time: 0.0317 memory: 21547 grad_norm: 4.0536 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.3979 loss: 1.3979 2022/10/10 03:49:26 - mmengine - INFO - Epoch(train) [45][580/940] lr: 1.0000e-03 eta: 7:19:58 time: 0.4619 data_time: 0.0255 memory: 21547 grad_norm: 4.1437 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3152 loss: 1.3152 2022/10/10 03:49:37 - mmengine - INFO - Epoch(train) [45][600/940] lr: 1.0000e-03 eta: 7:19:49 time: 0.5352 data_time: 0.0370 memory: 21547 grad_norm: 4.0588 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2845 loss: 1.2845 2022/10/10 03:49:47 - mmengine - INFO - Epoch(train) [45][620/940] lr: 1.0000e-03 eta: 7:19:38 time: 0.4722 data_time: 0.0259 memory: 21547 grad_norm: 4.2418 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.2555 loss: 1.2555 2022/10/10 03:49:57 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 03:49:57 - mmengine - INFO - Epoch(train) [45][640/940] lr: 1.0000e-03 eta: 7:19:28 time: 0.5235 data_time: 0.0325 memory: 21547 grad_norm: 4.2129 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4028 loss: 1.4028 2022/10/10 03:50:07 - mmengine - INFO - Epoch(train) [45][660/940] lr: 1.0000e-03 eta: 7:19:17 time: 0.4777 data_time: 0.0232 memory: 21547 grad_norm: 4.1443 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3061 loss: 1.3061 2022/10/10 03:50:17 - mmengine - INFO - Epoch(train) [45][680/940] lr: 1.0000e-03 eta: 7:19:07 time: 0.5083 data_time: 0.0269 memory: 21547 grad_norm: 4.1160 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3177 loss: 1.3177 2022/10/10 03:50:26 - mmengine - INFO - Epoch(train) [45][700/940] lr: 1.0000e-03 eta: 7:18:56 time: 0.4736 data_time: 0.0274 memory: 21547 grad_norm: 4.1311 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.3068 loss: 1.3068 2022/10/10 03:50:37 - mmengine - INFO - Epoch(train) [45][720/940] lr: 1.0000e-03 eta: 7:18:46 time: 0.5237 data_time: 0.0259 memory: 21547 grad_norm: 3.9747 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2524 loss: 1.2524 2022/10/10 03:50:47 - mmengine - INFO - Epoch(train) [45][740/940] lr: 1.0000e-03 eta: 7:18:36 time: 0.4932 data_time: 0.0269 memory: 21547 grad_norm: 4.1784 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.4084 loss: 1.4084 2022/10/10 03:50:56 - mmengine - INFO - Epoch(train) [45][760/940] lr: 1.0000e-03 eta: 7:18:25 time: 0.4685 data_time: 0.0253 memory: 21547 grad_norm: 4.2019 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4336 loss: 1.4336 2022/10/10 03:51:06 - mmengine - INFO - Epoch(train) [45][780/940] lr: 1.0000e-03 eta: 7:18:14 time: 0.4866 data_time: 0.0306 memory: 21547 grad_norm: 4.2015 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3981 loss: 1.3981 2022/10/10 03:51:16 - mmengine - INFO - Epoch(train) [45][800/940] lr: 1.0000e-03 eta: 7:18:05 time: 0.5350 data_time: 0.0274 memory: 21547 grad_norm: 4.2311 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4433 loss: 1.4433 2022/10/10 03:51:26 - mmengine - INFO - Epoch(train) [45][820/940] lr: 1.0000e-03 eta: 7:17:55 time: 0.5044 data_time: 0.0318 memory: 21547 grad_norm: 4.0381 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2640 loss: 1.2640 2022/10/10 03:51:36 - mmengine - INFO - Epoch(train) [45][840/940] lr: 1.0000e-03 eta: 7:17:43 time: 0.4667 data_time: 0.0293 memory: 21547 grad_norm: 4.0865 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4356 loss: 1.4356 2022/10/10 03:51:47 - mmengine - INFO - Epoch(train) [45][860/940] lr: 1.0000e-03 eta: 7:17:34 time: 0.5518 data_time: 0.0322 memory: 21547 grad_norm: 4.1271 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4522 loss: 1.4522 2022/10/10 03:51:57 - mmengine - INFO - Epoch(train) [45][880/940] lr: 1.0000e-03 eta: 7:17:24 time: 0.5086 data_time: 0.0262 memory: 21547 grad_norm: 4.1542 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.4623 loss: 1.4623 2022/10/10 03:52:08 - mmengine - INFO - Epoch(train) [45][900/940] lr: 1.0000e-03 eta: 7:17:15 time: 0.5265 data_time: 0.0329 memory: 21547 grad_norm: 4.1353 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3459 loss: 1.3459 2022/10/10 03:52:17 - mmengine - INFO - Epoch(train) [45][920/940] lr: 1.0000e-03 eta: 7:17:04 time: 0.4735 data_time: 0.0294 memory: 21547 grad_norm: 4.1028 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.4214 loss: 1.4214 2022/10/10 03:52:26 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 03:52:26 - mmengine - INFO - Epoch(train) [45][940/940] lr: 1.0000e-03 eta: 7:16:52 time: 0.4582 data_time: 0.0224 memory: 21547 grad_norm: 4.4675 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.4692 loss: 1.4692 2022/10/10 03:52:26 - mmengine - INFO - Saving checkpoint at 45 epochs 2022/10/10 03:52:39 - mmengine - INFO - Epoch(val) [45][20/78] eta: 0:00:35 time: 0.6102 data_time: 0.5035 memory: 3269 2022/10/10 03:52:48 - mmengine - INFO - Epoch(val) [45][40/78] eta: 0:00:16 time: 0.4282 data_time: 0.3234 memory: 3269 2022/10/10 03:52:59 - mmengine - INFO - Epoch(val) [45][60/78] eta: 0:00:10 time: 0.5566 data_time: 0.4509 memory: 3269 2022/10/10 03:53:08 - mmengine - INFO - Epoch(val) [45][78/78] acc/top1: 0.6725 acc/top5: 0.8692 acc/mean1: 0.6723 2022/10/10 03:53:22 - mmengine - INFO - Epoch(train) [46][20/940] lr: 1.0000e-03 eta: 7:16:47 time: 0.7210 data_time: 0.3485 memory: 21547 grad_norm: 4.0866 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3423 loss: 1.3423 2022/10/10 03:53:32 - mmengine - INFO - Epoch(train) [46][40/940] lr: 1.0000e-03 eta: 7:16:36 time: 0.4752 data_time: 0.0883 memory: 21547 grad_norm: 4.0796 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2771 loss: 1.2771 2022/10/10 03:53:43 - mmengine - INFO - Epoch(train) [46][60/940] lr: 1.0000e-03 eta: 7:16:27 time: 0.5438 data_time: 0.1018 memory: 21547 grad_norm: 4.1738 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1631 loss: 1.1631 2022/10/10 03:53:53 - mmengine - INFO - Epoch(train) [46][80/940] lr: 1.0000e-03 eta: 7:16:17 time: 0.4942 data_time: 0.0324 memory: 21547 grad_norm: 4.0781 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3470 loss: 1.3470 2022/10/10 03:54:04 - mmengine - INFO - Epoch(train) [46][100/940] lr: 1.0000e-03 eta: 7:16:08 time: 0.5514 data_time: 0.0299 memory: 21547 grad_norm: 4.0775 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3202 loss: 1.3202 2022/10/10 03:54:14 - mmengine - INFO - Epoch(train) [46][120/940] lr: 1.0000e-03 eta: 7:15:58 time: 0.5053 data_time: 0.0285 memory: 21547 grad_norm: 4.1290 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3020 loss: 1.3020 2022/10/10 03:54:23 - mmengine - INFO - Epoch(train) [46][140/940] lr: 1.0000e-03 eta: 7:15:47 time: 0.4731 data_time: 0.0270 memory: 21547 grad_norm: 4.1562 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3078 loss: 1.3078 2022/10/10 03:54:33 - mmengine - INFO - Epoch(train) [46][160/940] lr: 1.0000e-03 eta: 7:15:36 time: 0.4875 data_time: 0.0261 memory: 21547 grad_norm: 4.1659 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3111 loss: 1.3111 2022/10/10 03:54:44 - mmengine - INFO - Epoch(train) [46][180/940] lr: 1.0000e-03 eta: 7:15:27 time: 0.5404 data_time: 0.0272 memory: 21547 grad_norm: 4.1330 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4893 loss: 1.4893 2022/10/10 03:54:54 - mmengine - INFO - Epoch(train) [46][200/940] lr: 1.0000e-03 eta: 7:15:16 time: 0.4964 data_time: 0.0271 memory: 21547 grad_norm: 4.0844 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4230 loss: 1.4230 2022/10/10 03:55:04 - mmengine - INFO - Epoch(train) [46][220/940] lr: 1.0000e-03 eta: 7:15:07 time: 0.5273 data_time: 0.0264 memory: 21547 grad_norm: 3.9985 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3102 loss: 1.3102 2022/10/10 03:55:14 - mmengine - INFO - Epoch(train) [46][240/940] lr: 1.0000e-03 eta: 7:14:56 time: 0.4848 data_time: 0.0319 memory: 21547 grad_norm: 4.0592 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2328 loss: 1.2328 2022/10/10 03:55:24 - mmengine - INFO - Epoch(train) [46][260/940] lr: 1.0000e-03 eta: 7:14:45 time: 0.4890 data_time: 0.0301 memory: 21547 grad_norm: 4.1741 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.4089 loss: 1.4089 2022/10/10 03:55:33 - mmengine - INFO - Epoch(train) [46][280/940] lr: 1.0000e-03 eta: 7:14:34 time: 0.4799 data_time: 0.0299 memory: 21547 grad_norm: 4.0900 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3464 loss: 1.3464 2022/10/10 03:55:43 - mmengine - INFO - Epoch(train) [46][300/940] lr: 1.0000e-03 eta: 7:14:23 time: 0.4644 data_time: 0.0285 memory: 21547 grad_norm: 4.1345 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.4572 loss: 1.4572 2022/10/10 03:55:52 - mmengine - INFO - Epoch(train) [46][320/940] lr: 1.0000e-03 eta: 7:14:12 time: 0.4596 data_time: 0.0257 memory: 21547 grad_norm: 4.1091 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2776 loss: 1.2776 2022/10/10 03:56:03 - mmengine - INFO - Epoch(train) [46][340/940] lr: 1.0000e-03 eta: 7:14:03 time: 0.5373 data_time: 0.0304 memory: 21547 grad_norm: 4.1514 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.4111 loss: 1.4111 2022/10/10 03:56:13 - mmengine - INFO - Epoch(train) [46][360/940] lr: 1.0000e-03 eta: 7:13:52 time: 0.5019 data_time: 0.0309 memory: 21547 grad_norm: 4.0370 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3070 loss: 1.3070 2022/10/10 03:56:23 - mmengine - INFO - Epoch(train) [46][380/940] lr: 1.0000e-03 eta: 7:13:43 time: 0.5282 data_time: 0.0331 memory: 21547 grad_norm: 4.1040 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3571 loss: 1.3571 2022/10/10 03:56:33 - mmengine - INFO - Epoch(train) [46][400/940] lr: 1.0000e-03 eta: 7:13:32 time: 0.4813 data_time: 0.0274 memory: 21547 grad_norm: 4.1273 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1447 loss: 1.1447 2022/10/10 03:56:44 - mmengine - INFO - Epoch(train) [46][420/940] lr: 1.0000e-03 eta: 7:13:23 time: 0.5456 data_time: 0.0258 memory: 21547 grad_norm: 4.0740 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2828 loss: 1.2828 2022/10/10 03:56:53 - mmengine - INFO - Epoch(train) [46][440/940] lr: 1.0000e-03 eta: 7:13:11 time: 0.4571 data_time: 0.0326 memory: 21547 grad_norm: 4.0879 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2810 loss: 1.2810 2022/10/10 03:57:04 - mmengine - INFO - Epoch(train) [46][460/940] lr: 1.0000e-03 eta: 7:13:03 time: 0.5721 data_time: 0.0294 memory: 21547 grad_norm: 4.1659 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2726 loss: 1.2726 2022/10/10 03:57:15 - mmengine - INFO - Epoch(train) [46][480/940] lr: 1.0000e-03 eta: 7:12:53 time: 0.5068 data_time: 0.0278 memory: 21547 grad_norm: 4.1582 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2885 loss: 1.2885 2022/10/10 03:57:25 - mmengine - INFO - Epoch(train) [46][500/940] lr: 1.0000e-03 eta: 7:12:43 time: 0.5444 data_time: 0.0290 memory: 21547 grad_norm: 4.1034 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2398 loss: 1.2398 2022/10/10 03:57:36 - mmengine - INFO - Epoch(train) [46][520/940] lr: 1.0000e-03 eta: 7:12:33 time: 0.5108 data_time: 0.0277 memory: 21547 grad_norm: 4.2205 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4285 loss: 1.4285 2022/10/10 03:57:45 - mmengine - INFO - Epoch(train) [46][540/940] lr: 1.0000e-03 eta: 7:12:23 time: 0.4866 data_time: 0.0313 memory: 21547 grad_norm: 4.1649 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3498 loss: 1.3498 2022/10/10 03:57:56 - mmengine - INFO - Epoch(train) [46][560/940] lr: 1.0000e-03 eta: 7:12:13 time: 0.5198 data_time: 0.0271 memory: 21547 grad_norm: 4.1772 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3290 loss: 1.3290 2022/10/10 03:58:05 - mmengine - INFO - Epoch(train) [46][580/940] lr: 1.0000e-03 eta: 7:12:02 time: 0.4829 data_time: 0.0318 memory: 21547 grad_norm: 4.0644 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2773 loss: 1.2773 2022/10/10 03:58:15 - mmengine - INFO - Epoch(train) [46][600/940] lr: 1.0000e-03 eta: 7:11:51 time: 0.4645 data_time: 0.0282 memory: 21547 grad_norm: 4.1675 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5277 loss: 1.5277 2022/10/10 03:58:25 - mmengine - INFO - Epoch(train) [46][620/940] lr: 1.0000e-03 eta: 7:11:41 time: 0.4939 data_time: 0.0326 memory: 21547 grad_norm: 4.0687 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2735 loss: 1.2735 2022/10/10 03:58:35 - mmengine - INFO - Epoch(train) [46][640/940] lr: 1.0000e-03 eta: 7:11:31 time: 0.5339 data_time: 0.0279 memory: 21547 grad_norm: 4.2753 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3633 loss: 1.3633 2022/10/10 03:58:45 - mmengine - INFO - Epoch(train) [46][660/940] lr: 1.0000e-03 eta: 7:11:20 time: 0.4861 data_time: 0.0278 memory: 21547 grad_norm: 4.1898 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4158 loss: 1.4158 2022/10/10 03:58:54 - mmengine - INFO - Epoch(train) [46][680/940] lr: 1.0000e-03 eta: 7:11:09 time: 0.4736 data_time: 0.0320 memory: 21547 grad_norm: 4.0622 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3783 loss: 1.3783 2022/10/10 03:59:05 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 03:59:05 - mmengine - INFO - Epoch(train) [46][700/940] lr: 1.0000e-03 eta: 7:11:00 time: 0.5384 data_time: 0.0277 memory: 21547 grad_norm: 4.1173 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3369 loss: 1.3369 2022/10/10 03:59:15 - mmengine - INFO - Epoch(train) [46][720/940] lr: 1.0000e-03 eta: 7:10:50 time: 0.5115 data_time: 0.0273 memory: 21547 grad_norm: 4.1708 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1310 loss: 1.1310 2022/10/10 03:59:26 - mmengine - INFO - Epoch(train) [46][740/940] lr: 1.0000e-03 eta: 7:10:40 time: 0.5102 data_time: 0.0234 memory: 21547 grad_norm: 4.1347 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3664 loss: 1.3664 2022/10/10 03:59:35 - mmengine - INFO - Epoch(train) [46][760/940] lr: 1.0000e-03 eta: 7:10:29 time: 0.4575 data_time: 0.0242 memory: 21547 grad_norm: 4.1385 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3399 loss: 1.3399 2022/10/10 03:59:45 - mmengine - INFO - Epoch(train) [46][780/940] lr: 1.0000e-03 eta: 7:10:18 time: 0.5022 data_time: 0.0252 memory: 21547 grad_norm: 4.0511 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1965 loss: 1.1965 2022/10/10 03:59:55 - mmengine - INFO - Epoch(train) [46][800/940] lr: 1.0000e-03 eta: 7:10:08 time: 0.4940 data_time: 0.0268 memory: 21547 grad_norm: 4.1854 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2667 loss: 1.2667 2022/10/10 04:00:05 - mmengine - INFO - Epoch(train) [46][820/940] lr: 1.0000e-03 eta: 7:09:58 time: 0.5205 data_time: 0.0286 memory: 21547 grad_norm: 4.2503 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.4049 loss: 1.4049 2022/10/10 04:00:15 - mmengine - INFO - Epoch(train) [46][840/940] lr: 1.0000e-03 eta: 7:09:48 time: 0.5134 data_time: 0.0272 memory: 21547 grad_norm: 4.2165 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3848 loss: 1.3848 2022/10/10 04:00:26 - mmengine - INFO - Epoch(train) [46][860/940] lr: 1.0000e-03 eta: 7:09:39 time: 0.5502 data_time: 0.0298 memory: 21547 grad_norm: 4.0956 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4080 loss: 1.4080 2022/10/10 04:00:36 - mmengine - INFO - Epoch(train) [46][880/940] lr: 1.0000e-03 eta: 7:09:28 time: 0.4792 data_time: 0.0217 memory: 21547 grad_norm: 4.1494 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3239 loss: 1.3239 2022/10/10 04:00:46 - mmengine - INFO - Epoch(train) [46][900/940] lr: 1.0000e-03 eta: 7:09:18 time: 0.4932 data_time: 0.0247 memory: 21547 grad_norm: 4.0776 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.3331 loss: 1.3331 2022/10/10 04:00:56 - mmengine - INFO - Epoch(train) [46][920/940] lr: 1.0000e-03 eta: 7:09:07 time: 0.4818 data_time: 0.0309 memory: 21547 grad_norm: 4.2546 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.3582 loss: 1.3582 2022/10/10 04:01:04 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 04:01:04 - mmengine - INFO - Epoch(train) [46][940/940] lr: 1.0000e-03 eta: 7:08:55 time: 0.4316 data_time: 0.0254 memory: 21547 grad_norm: 4.5092 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.4150 loss: 1.4150 2022/10/10 04:01:16 - mmengine - INFO - Epoch(val) [46][20/78] eta: 0:00:35 time: 0.6070 data_time: 0.5002 memory: 3269 2022/10/10 04:01:25 - mmengine - INFO - Epoch(val) [46][40/78] eta: 0:00:15 time: 0.4206 data_time: 0.3138 memory: 3269 2022/10/10 04:01:36 - mmengine - INFO - Epoch(val) [46][60/78] eta: 0:00:10 time: 0.5622 data_time: 0.4544 memory: 3269 2022/10/10 04:01:46 - mmengine - INFO - Epoch(val) [46][78/78] acc/top1: 0.6748 acc/top5: 0.8703 acc/mean1: 0.6747 2022/10/10 04:02:00 - mmengine - INFO - Epoch(train) [47][20/940] lr: 1.0000e-03 eta: 7:08:49 time: 0.6927 data_time: 0.2332 memory: 21547 grad_norm: 4.0863 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2817 loss: 1.2817 2022/10/10 04:02:10 - mmengine - INFO - Epoch(train) [47][40/940] lr: 1.0000e-03 eta: 7:08:39 time: 0.5070 data_time: 0.0719 memory: 21547 grad_norm: 4.1712 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3943 loss: 1.3943 2022/10/10 04:02:20 - mmengine - INFO - Epoch(train) [47][60/940] lr: 1.0000e-03 eta: 7:08:29 time: 0.5218 data_time: 0.0721 memory: 21547 grad_norm: 4.2408 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3854 loss: 1.3854 2022/10/10 04:02:30 - mmengine - INFO - Epoch(train) [47][80/940] lr: 1.0000e-03 eta: 7:08:18 time: 0.4699 data_time: 0.0620 memory: 21547 grad_norm: 4.0601 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3863 loss: 1.3863 2022/10/10 04:02:40 - mmengine - INFO - Epoch(train) [47][100/940] lr: 1.0000e-03 eta: 7:08:09 time: 0.5306 data_time: 0.1543 memory: 21547 grad_norm: 4.2060 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1989 loss: 1.1989 2022/10/10 04:02:50 - mmengine - INFO - Epoch(train) [47][120/940] lr: 1.0000e-03 eta: 7:07:58 time: 0.4999 data_time: 0.1142 memory: 21547 grad_norm: 4.0939 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2747 loss: 1.2747 2022/10/10 04:03:01 - mmengine - INFO - Epoch(train) [47][140/940] lr: 1.0000e-03 eta: 7:07:49 time: 0.5537 data_time: 0.1660 memory: 21547 grad_norm: 4.1766 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2335 loss: 1.2335 2022/10/10 04:03:11 - mmengine - INFO - Epoch(train) [47][160/940] lr: 1.0000e-03 eta: 7:07:39 time: 0.4799 data_time: 0.0980 memory: 21547 grad_norm: 4.1420 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3207 loss: 1.3207 2022/10/10 04:03:20 - mmengine - INFO - Epoch(train) [47][180/940] lr: 1.0000e-03 eta: 7:07:28 time: 0.4753 data_time: 0.0948 memory: 21547 grad_norm: 4.1596 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2188 loss: 1.2188 2022/10/10 04:03:30 - mmengine - INFO - Epoch(train) [47][200/940] lr: 1.0000e-03 eta: 7:07:17 time: 0.4871 data_time: 0.1087 memory: 21547 grad_norm: 4.1527 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2357 loss: 1.2357 2022/10/10 04:03:40 - mmengine - INFO - Epoch(train) [47][220/940] lr: 1.0000e-03 eta: 7:07:07 time: 0.5052 data_time: 0.0622 memory: 21547 grad_norm: 4.2347 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3887 loss: 1.3887 2022/10/10 04:03:50 - mmengine - INFO - Epoch(train) [47][240/940] lr: 1.0000e-03 eta: 7:06:57 time: 0.5013 data_time: 0.0252 memory: 21547 grad_norm: 4.1087 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2779 loss: 1.2779 2022/10/10 04:04:00 - mmengine - INFO - Epoch(train) [47][260/940] lr: 1.0000e-03 eta: 7:06:46 time: 0.4828 data_time: 0.0281 memory: 21547 grad_norm: 4.0560 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2852 loss: 1.2852 2022/10/10 04:04:10 - mmengine - INFO - Epoch(train) [47][280/940] lr: 1.0000e-03 eta: 7:06:36 time: 0.5015 data_time: 0.0274 memory: 21547 grad_norm: 4.0488 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.3452 loss: 1.3452 2022/10/10 04:04:21 - mmengine - INFO - Epoch(train) [47][300/940] lr: 1.0000e-03 eta: 7:06:26 time: 0.5468 data_time: 0.0284 memory: 21547 grad_norm: 4.1658 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.2694 loss: 1.2694 2022/10/10 04:04:31 - mmengine - INFO - Epoch(train) [47][320/940] lr: 1.0000e-03 eta: 7:06:16 time: 0.4845 data_time: 0.0272 memory: 21547 grad_norm: 4.1388 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3767 loss: 1.3767 2022/10/10 04:04:40 - mmengine - INFO - Epoch(train) [47][340/940] lr: 1.0000e-03 eta: 7:06:05 time: 0.4813 data_time: 0.0263 memory: 21547 grad_norm: 4.1083 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3506 loss: 1.3506 2022/10/10 04:04:50 - mmengine - INFO - Epoch(train) [47][360/940] lr: 1.0000e-03 eta: 7:05:54 time: 0.4709 data_time: 0.0303 memory: 21547 grad_norm: 4.1714 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3418 loss: 1.3418 2022/10/10 04:05:00 - mmengine - INFO - Epoch(train) [47][380/940] lr: 1.0000e-03 eta: 7:05:44 time: 0.5268 data_time: 0.0295 memory: 21547 grad_norm: 4.1384 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.3621 loss: 1.3621 2022/10/10 04:05:11 - mmengine - INFO - Epoch(train) [47][400/940] lr: 1.0000e-03 eta: 7:05:35 time: 0.5187 data_time: 0.0226 memory: 21547 grad_norm: 4.1417 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2122 loss: 1.2122 2022/10/10 04:05:21 - mmengine - INFO - Epoch(train) [47][420/940] lr: 1.0000e-03 eta: 7:05:24 time: 0.5009 data_time: 0.0293 memory: 21547 grad_norm: 4.0996 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.3934 loss: 1.3934 2022/10/10 04:05:31 - mmengine - INFO - Epoch(train) [47][440/940] lr: 1.0000e-03 eta: 7:05:15 time: 0.5411 data_time: 0.0308 memory: 21547 grad_norm: 4.1646 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3870 loss: 1.3870 2022/10/10 04:05:41 - mmengine - INFO - Epoch(train) [47][460/940] lr: 1.0000e-03 eta: 7:05:04 time: 0.4656 data_time: 0.0289 memory: 21547 grad_norm: 4.1653 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.3425 loss: 1.3425 2022/10/10 04:05:51 - mmengine - INFO - Epoch(train) [47][480/940] lr: 1.0000e-03 eta: 7:04:53 time: 0.4946 data_time: 0.0254 memory: 21547 grad_norm: 4.1095 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3399 loss: 1.3399 2022/10/10 04:06:00 - mmengine - INFO - Epoch(train) [47][500/940] lr: 1.0000e-03 eta: 7:04:43 time: 0.4931 data_time: 0.0292 memory: 21547 grad_norm: 4.1982 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3140 loss: 1.3140 2022/10/10 04:06:10 - mmengine - INFO - Epoch(train) [47][520/940] lr: 1.0000e-03 eta: 7:04:32 time: 0.4862 data_time: 0.0285 memory: 21547 grad_norm: 4.1699 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.4852 loss: 1.4852 2022/10/10 04:06:20 - mmengine - INFO - Epoch(train) [47][540/940] lr: 1.0000e-03 eta: 7:04:22 time: 0.4928 data_time: 0.0309 memory: 21547 grad_norm: 4.1235 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.2198 loss: 1.2198 2022/10/10 04:06:30 - mmengine - INFO - Epoch(train) [47][560/940] lr: 1.0000e-03 eta: 7:04:12 time: 0.5050 data_time: 0.0429 memory: 21547 grad_norm: 4.1270 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2644 loss: 1.2644 2022/10/10 04:06:40 - mmengine - INFO - Epoch(train) [47][580/940] lr: 1.0000e-03 eta: 7:04:02 time: 0.5103 data_time: 0.0495 memory: 21547 grad_norm: 4.1632 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.2782 loss: 1.2782 2022/10/10 04:06:52 - mmengine - INFO - Epoch(train) [47][600/940] lr: 1.0000e-03 eta: 7:03:53 time: 0.5756 data_time: 0.0656 memory: 21547 grad_norm: 4.1390 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3219 loss: 1.3219 2022/10/10 04:07:01 - mmengine - INFO - Epoch(train) [47][620/940] lr: 1.0000e-03 eta: 7:03:42 time: 0.4708 data_time: 0.0292 memory: 21547 grad_norm: 4.1783 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2752 loss: 1.2752 2022/10/10 04:07:12 - mmengine - INFO - Epoch(train) [47][640/940] lr: 1.0000e-03 eta: 7:03:33 time: 0.5471 data_time: 0.0268 memory: 21547 grad_norm: 4.1087 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3382 loss: 1.3382 2022/10/10 04:07:22 - mmengine - INFO - Epoch(train) [47][660/940] lr: 1.0000e-03 eta: 7:03:22 time: 0.4956 data_time: 0.0283 memory: 21547 grad_norm: 4.1908 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2769 loss: 1.2769 2022/10/10 04:07:32 - mmengine - INFO - Epoch(train) [47][680/940] lr: 1.0000e-03 eta: 7:03:11 time: 0.4665 data_time: 0.0261 memory: 21547 grad_norm: 4.1494 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3042 loss: 1.3042 2022/10/10 04:07:41 - mmengine - INFO - Epoch(train) [47][700/940] lr: 1.0000e-03 eta: 7:03:00 time: 0.4682 data_time: 0.0298 memory: 21547 grad_norm: 4.1601 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3106 loss: 1.3106 2022/10/10 04:07:51 - mmengine - INFO - Epoch(train) [47][720/940] lr: 1.0000e-03 eta: 7:02:51 time: 0.5214 data_time: 0.0283 memory: 21547 grad_norm: 4.1970 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3678 loss: 1.3678 2022/10/10 04:08:01 - mmengine - INFO - Epoch(train) [47][740/940] lr: 1.0000e-03 eta: 7:02:40 time: 0.4910 data_time: 0.0341 memory: 21547 grad_norm: 4.1925 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3208 loss: 1.3208 2022/10/10 04:08:11 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 04:08:11 - mmengine - INFO - Epoch(train) [47][760/940] lr: 1.0000e-03 eta: 7:02:29 time: 0.4882 data_time: 0.0245 memory: 21547 grad_norm: 4.1451 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2561 loss: 1.2561 2022/10/10 04:08:22 - mmengine - INFO - Epoch(train) [47][780/940] lr: 1.0000e-03 eta: 7:02:20 time: 0.5380 data_time: 0.0308 memory: 21547 grad_norm: 4.1706 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2886 loss: 1.2886 2022/10/10 04:08:32 - mmengine - INFO - Epoch(train) [47][800/940] lr: 1.0000e-03 eta: 7:02:10 time: 0.5199 data_time: 0.0233 memory: 21547 grad_norm: 4.2226 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3867 loss: 1.3867 2022/10/10 04:08:41 - mmengine - INFO - Epoch(train) [47][820/940] lr: 1.0000e-03 eta: 7:01:59 time: 0.4567 data_time: 0.0323 memory: 21547 grad_norm: 4.1969 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4472 loss: 1.4472 2022/10/10 04:08:51 - mmengine - INFO - Epoch(train) [47][840/940] lr: 1.0000e-03 eta: 7:01:49 time: 0.4974 data_time: 0.0324 memory: 21547 grad_norm: 4.1465 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2411 loss: 1.2411 2022/10/10 04:09:01 - mmengine - INFO - Epoch(train) [47][860/940] lr: 1.0000e-03 eta: 7:01:38 time: 0.4950 data_time: 0.0258 memory: 21547 grad_norm: 4.1738 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2852 loss: 1.2852 2022/10/10 04:09:12 - mmengine - INFO - Epoch(train) [47][880/940] lr: 1.0000e-03 eta: 7:01:29 time: 0.5426 data_time: 0.0269 memory: 21547 grad_norm: 4.1499 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.3451 loss: 1.3451 2022/10/10 04:09:22 - mmengine - INFO - Epoch(train) [47][900/940] lr: 1.0000e-03 eta: 7:01:18 time: 0.4848 data_time: 0.0320 memory: 21547 grad_norm: 4.3608 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3481 loss: 1.3481 2022/10/10 04:09:32 - mmengine - INFO - Epoch(train) [47][920/940] lr: 1.0000e-03 eta: 7:01:09 time: 0.5395 data_time: 0.0342 memory: 21547 grad_norm: 4.1299 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2040 loss: 1.2040 2022/10/10 04:09:41 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 04:09:41 - mmengine - INFO - Epoch(train) [47][940/940] lr: 1.0000e-03 eta: 7:00:57 time: 0.4483 data_time: 0.0220 memory: 21547 grad_norm: 4.4753 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.3833 loss: 1.3833 2022/10/10 04:09:54 - mmengine - INFO - Epoch(val) [47][20/78] eta: 0:00:35 time: 0.6116 data_time: 0.5016 memory: 3269 2022/10/10 04:10:02 - mmengine - INFO - Epoch(val) [47][40/78] eta: 0:00:16 time: 0.4244 data_time: 0.3169 memory: 3269 2022/10/10 04:10:13 - mmengine - INFO - Epoch(val) [47][60/78] eta: 0:00:09 time: 0.5551 data_time: 0.4489 memory: 3269 2022/10/10 04:10:23 - mmengine - INFO - Epoch(val) [47][78/78] acc/top1: 0.6719 acc/top5: 0.8697 acc/mean1: 0.6718 2022/10/10 04:10:37 - mmengine - INFO - Epoch(train) [48][20/940] lr: 1.0000e-03 eta: 7:00:51 time: 0.6959 data_time: 0.2640 memory: 21547 grad_norm: 4.1810 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2906 loss: 1.2906 2022/10/10 04:10:47 - mmengine - INFO - Epoch(train) [48][40/940] lr: 1.0000e-03 eta: 7:00:41 time: 0.5034 data_time: 0.0398 memory: 21547 grad_norm: 4.1330 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2819 loss: 1.2819 2022/10/10 04:10:58 - mmengine - INFO - Epoch(train) [48][60/940] lr: 1.0000e-03 eta: 7:00:31 time: 0.5153 data_time: 0.0539 memory: 21547 grad_norm: 4.1359 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1701 loss: 1.1701 2022/10/10 04:11:08 - mmengine - INFO - Epoch(train) [48][80/940] lr: 1.0000e-03 eta: 7:00:21 time: 0.4978 data_time: 0.0309 memory: 21547 grad_norm: 4.1668 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2288 loss: 1.2288 2022/10/10 04:11:18 - mmengine - INFO - Epoch(train) [48][100/940] lr: 1.0000e-03 eta: 7:00:11 time: 0.5086 data_time: 0.0491 memory: 21547 grad_norm: 4.1819 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.1735 loss: 1.1735 2022/10/10 04:11:28 - mmengine - INFO - Epoch(train) [48][120/940] lr: 1.0000e-03 eta: 7:00:01 time: 0.5134 data_time: 0.1174 memory: 21547 grad_norm: 4.1935 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3499 loss: 1.3499 2022/10/10 04:11:39 - mmengine - INFO - Epoch(train) [48][140/940] lr: 1.0000e-03 eta: 6:59:51 time: 0.5268 data_time: 0.0967 memory: 21547 grad_norm: 4.1681 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3136 loss: 1.3136 2022/10/10 04:11:49 - mmengine - INFO - Epoch(train) [48][160/940] lr: 1.0000e-03 eta: 6:59:41 time: 0.5007 data_time: 0.0357 memory: 21547 grad_norm: 4.1512 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3626 loss: 1.3626 2022/10/10 04:12:00 - mmengine - INFO - Epoch(train) [48][180/940] lr: 1.0000e-03 eta: 6:59:32 time: 0.5508 data_time: 0.0223 memory: 21547 grad_norm: 4.2042 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3619 loss: 1.3619 2022/10/10 04:12:09 - mmengine - INFO - Epoch(train) [48][200/940] lr: 1.0000e-03 eta: 6:59:20 time: 0.4542 data_time: 0.0317 memory: 21547 grad_norm: 4.1775 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2245 loss: 1.2245 2022/10/10 04:12:18 - mmengine - INFO - Epoch(train) [48][220/940] lr: 1.0000e-03 eta: 6:59:10 time: 0.4872 data_time: 0.0232 memory: 21547 grad_norm: 4.1993 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3671 loss: 1.3671 2022/10/10 04:12:29 - mmengine - INFO - Epoch(train) [48][240/940] lr: 1.0000e-03 eta: 6:59:00 time: 0.5069 data_time: 0.0272 memory: 21547 grad_norm: 4.1357 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2709 loss: 1.2709 2022/10/10 04:12:39 - mmengine - INFO - Epoch(train) [48][260/940] lr: 1.0000e-03 eta: 6:58:50 time: 0.5438 data_time: 0.0308 memory: 21547 grad_norm: 4.1782 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.4115 loss: 1.4115 2022/10/10 04:12:49 - mmengine - INFO - Epoch(train) [48][280/940] lr: 1.0000e-03 eta: 6:58:40 time: 0.5019 data_time: 0.0283 memory: 21547 grad_norm: 4.2090 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2335 loss: 1.2335 2022/10/10 04:13:00 - mmengine - INFO - Epoch(train) [48][300/940] lr: 1.0000e-03 eta: 6:58:30 time: 0.5052 data_time: 0.0240 memory: 21547 grad_norm: 4.3264 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3870 loss: 1.3870 2022/10/10 04:13:09 - mmengine - INFO - Epoch(train) [48][320/940] lr: 1.0000e-03 eta: 6:58:19 time: 0.4676 data_time: 0.0343 memory: 21547 grad_norm: 4.1825 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3872 loss: 1.3872 2022/10/10 04:13:18 - mmengine - INFO - Epoch(train) [48][340/940] lr: 1.0000e-03 eta: 6:58:07 time: 0.4516 data_time: 0.0233 memory: 21547 grad_norm: 4.2038 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3688 loss: 1.3688 2022/10/10 04:13:27 - mmengine - INFO - Epoch(train) [48][360/940] lr: 1.0000e-03 eta: 6:57:57 time: 0.4746 data_time: 0.0305 memory: 21547 grad_norm: 4.1507 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3483 loss: 1.3483 2022/10/10 04:13:38 - mmengine - INFO - Epoch(train) [48][380/940] lr: 1.0000e-03 eta: 6:57:47 time: 0.5214 data_time: 0.0305 memory: 21547 grad_norm: 4.0801 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3492 loss: 1.3492 2022/10/10 04:13:48 - mmengine - INFO - Epoch(train) [48][400/940] lr: 1.0000e-03 eta: 6:57:37 time: 0.5162 data_time: 0.0309 memory: 21547 grad_norm: 4.2310 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3877 loss: 1.3877 2022/10/10 04:13:59 - mmengine - INFO - Epoch(train) [48][420/940] lr: 1.0000e-03 eta: 6:57:27 time: 0.5449 data_time: 0.0296 memory: 21547 grad_norm: 4.1814 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2642 loss: 1.2642 2022/10/10 04:14:09 - mmengine - INFO - Epoch(train) [48][440/940] lr: 1.0000e-03 eta: 6:57:17 time: 0.4938 data_time: 0.0288 memory: 21547 grad_norm: 4.1076 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3489 loss: 1.3489 2022/10/10 04:14:19 - mmengine - INFO - Epoch(train) [48][460/940] lr: 1.0000e-03 eta: 6:57:07 time: 0.4945 data_time: 0.0324 memory: 21547 grad_norm: 4.1585 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.3496 loss: 1.3496 2022/10/10 04:14:29 - mmengine - INFO - Epoch(train) [48][480/940] lr: 1.0000e-03 eta: 6:56:56 time: 0.5065 data_time: 0.0332 memory: 21547 grad_norm: 4.1907 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3300 loss: 1.3300 2022/10/10 04:14:39 - mmengine - INFO - Epoch(train) [48][500/940] lr: 1.0000e-03 eta: 6:56:46 time: 0.5092 data_time: 0.0319 memory: 21547 grad_norm: 4.2129 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1808 loss: 1.1808 2022/10/10 04:14:49 - mmengine - INFO - Epoch(train) [48][520/940] lr: 1.0000e-03 eta: 6:56:36 time: 0.4866 data_time: 0.0292 memory: 21547 grad_norm: 4.1846 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2736 loss: 1.2736 2022/10/10 04:14:59 - mmengine - INFO - Epoch(train) [48][540/940] lr: 1.0000e-03 eta: 6:56:25 time: 0.4974 data_time: 0.0284 memory: 21547 grad_norm: 4.2752 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3603 loss: 1.3603 2022/10/10 04:15:09 - mmengine - INFO - Epoch(train) [48][560/940] lr: 1.0000e-03 eta: 6:56:15 time: 0.5056 data_time: 0.0307 memory: 21547 grad_norm: 4.1443 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2924 loss: 1.2924 2022/10/10 04:15:19 - mmengine - INFO - Epoch(train) [48][580/940] lr: 1.0000e-03 eta: 6:56:05 time: 0.5098 data_time: 0.0293 memory: 21547 grad_norm: 4.1922 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3039 loss: 1.3039 2022/10/10 04:15:30 - mmengine - INFO - Epoch(train) [48][600/940] lr: 1.0000e-03 eta: 6:55:56 time: 0.5417 data_time: 0.0262 memory: 21547 grad_norm: 4.1852 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.3897 loss: 1.3897 2022/10/10 04:15:40 - mmengine - INFO - Epoch(train) [48][620/940] lr: 1.0000e-03 eta: 6:55:45 time: 0.4988 data_time: 0.0304 memory: 21547 grad_norm: 4.2398 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3508 loss: 1.3508 2022/10/10 04:15:50 - mmengine - INFO - Epoch(train) [48][640/940] lr: 1.0000e-03 eta: 6:55:35 time: 0.5118 data_time: 0.0243 memory: 21547 grad_norm: 4.2326 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2308 loss: 1.2308 2022/10/10 04:15:59 - mmengine - INFO - Epoch(train) [48][660/940] lr: 1.0000e-03 eta: 6:55:23 time: 0.4205 data_time: 0.0265 memory: 21547 grad_norm: 4.0701 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2167 loss: 1.2167 2022/10/10 04:16:08 - mmengine - INFO - Epoch(train) [48][680/940] lr: 1.0000e-03 eta: 6:55:13 time: 0.4916 data_time: 0.0270 memory: 21547 grad_norm: 4.1722 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3621 loss: 1.3621 2022/10/10 04:16:19 - mmengine - INFO - Epoch(train) [48][700/940] lr: 1.0000e-03 eta: 6:55:03 time: 0.5144 data_time: 0.0328 memory: 21547 grad_norm: 4.2353 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1494 loss: 1.1494 2022/10/10 04:16:29 - mmengine - INFO - Epoch(train) [48][720/940] lr: 1.0000e-03 eta: 6:54:53 time: 0.5122 data_time: 0.0262 memory: 21547 grad_norm: 4.1031 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2622 loss: 1.2622 2022/10/10 04:16:39 - mmengine - INFO - Epoch(train) [48][740/940] lr: 1.0000e-03 eta: 6:54:42 time: 0.4852 data_time: 0.0312 memory: 21547 grad_norm: 4.2464 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2528 loss: 1.2528 2022/10/10 04:16:49 - mmengine - INFO - Epoch(train) [48][760/940] lr: 1.0000e-03 eta: 6:54:32 time: 0.5057 data_time: 0.0256 memory: 21547 grad_norm: 4.1221 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2627 loss: 1.2627 2022/10/10 04:16:58 - mmengine - INFO - Epoch(train) [48][780/940] lr: 1.0000e-03 eta: 6:54:22 time: 0.4845 data_time: 0.0345 memory: 21547 grad_norm: 4.2130 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2976 loss: 1.2976 2022/10/10 04:17:09 - mmengine - INFO - Epoch(train) [48][800/940] lr: 1.0000e-03 eta: 6:54:12 time: 0.5308 data_time: 0.0247 memory: 21547 grad_norm: 4.1607 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2839 loss: 1.2839 2022/10/10 04:17:19 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 04:17:19 - mmengine - INFO - Epoch(train) [48][820/940] lr: 1.0000e-03 eta: 6:54:01 time: 0.4786 data_time: 0.0302 memory: 21547 grad_norm: 4.2003 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3012 loss: 1.3012 2022/10/10 04:17:29 - mmengine - INFO - Epoch(train) [48][840/940] lr: 1.0000e-03 eta: 6:53:51 time: 0.5158 data_time: 0.0332 memory: 21547 grad_norm: 4.3324 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3341 loss: 1.3341 2022/10/10 04:17:39 - mmengine - INFO - Epoch(train) [48][860/940] lr: 1.0000e-03 eta: 6:53:41 time: 0.4897 data_time: 0.0284 memory: 21547 grad_norm: 4.2475 top1_acc: 0.5938 top5_acc: 0.9688 loss_cls: 1.4326 loss: 1.4326 2022/10/10 04:17:49 - mmengine - INFO - Epoch(train) [48][880/940] lr: 1.0000e-03 eta: 6:53:31 time: 0.5278 data_time: 0.0348 memory: 21547 grad_norm: 4.3117 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2526 loss: 1.2526 2022/10/10 04:17:59 - mmengine - INFO - Epoch(train) [48][900/940] lr: 1.0000e-03 eta: 6:53:20 time: 0.4881 data_time: 0.0276 memory: 21547 grad_norm: 4.1255 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2553 loss: 1.2553 2022/10/10 04:18:09 - mmengine - INFO - Epoch(train) [48][920/940] lr: 1.0000e-03 eta: 6:53:10 time: 0.4970 data_time: 0.0348 memory: 21547 grad_norm: 4.2724 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4865 loss: 1.4865 2022/10/10 04:18:18 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 04:18:18 - mmengine - INFO - Epoch(train) [48][940/940] lr: 1.0000e-03 eta: 6:52:59 time: 0.4706 data_time: 0.0287 memory: 21547 grad_norm: 4.5125 top1_acc: 0.4286 top5_acc: 0.4286 loss_cls: 1.4738 loss: 1.4738 2022/10/10 04:18:18 - mmengine - INFO - Saving checkpoint at 48 epochs 2022/10/10 04:18:32 - mmengine - INFO - Epoch(val) [48][20/78] eta: 0:00:35 time: 0.6128 data_time: 0.5044 memory: 3269 2022/10/10 04:18:40 - mmengine - INFO - Epoch(val) [48][40/78] eta: 0:00:15 time: 0.4188 data_time: 0.3140 memory: 3269 2022/10/10 04:18:51 - mmengine - INFO - Epoch(val) [48][60/78] eta: 0:00:09 time: 0.5540 data_time: 0.4486 memory: 3269 2022/10/10 04:19:00 - mmengine - INFO - Epoch(val) [48][78/78] acc/top1: 0.6720 acc/top5: 0.8709 acc/mean1: 0.6718 2022/10/10 04:19:14 - mmengine - INFO - Epoch(train) [49][20/940] lr: 1.0000e-03 eta: 6:52:53 time: 0.6878 data_time: 0.3103 memory: 21547 grad_norm: 4.3025 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3039 loss: 1.3039 2022/10/10 04:19:24 - mmengine - INFO - Epoch(train) [49][40/940] lr: 1.0000e-03 eta: 6:52:42 time: 0.4824 data_time: 0.0232 memory: 21547 grad_norm: 4.1481 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.2894 loss: 1.2894 2022/10/10 04:19:35 - mmengine - INFO - Epoch(train) [49][60/940] lr: 1.0000e-03 eta: 6:52:33 time: 0.5548 data_time: 0.0286 memory: 21547 grad_norm: 4.1824 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2302 loss: 1.2302 2022/10/10 04:19:44 - mmengine - INFO - Epoch(train) [49][80/940] lr: 1.0000e-03 eta: 6:52:22 time: 0.4759 data_time: 0.0270 memory: 21547 grad_norm: 4.2198 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3950 loss: 1.3950 2022/10/10 04:19:56 - mmengine - INFO - Epoch(train) [49][100/940] lr: 1.0000e-03 eta: 6:52:14 time: 0.5755 data_time: 0.0335 memory: 21547 grad_norm: 4.1902 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2389 loss: 1.2389 2022/10/10 04:20:06 - mmengine - INFO - Epoch(train) [49][120/940] lr: 1.0000e-03 eta: 6:52:03 time: 0.4816 data_time: 0.0274 memory: 21547 grad_norm: 4.1609 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3303 loss: 1.3303 2022/10/10 04:20:16 - mmengine - INFO - Epoch(train) [49][140/940] lr: 1.0000e-03 eta: 6:51:53 time: 0.5192 data_time: 0.0291 memory: 21547 grad_norm: 4.1696 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3491 loss: 1.3491 2022/10/10 04:20:25 - mmengine - INFO - Epoch(train) [49][160/940] lr: 1.0000e-03 eta: 6:51:41 time: 0.4376 data_time: 0.0278 memory: 21547 grad_norm: 4.1502 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3668 loss: 1.3668 2022/10/10 04:20:36 - mmengine - INFO - Epoch(train) [49][180/940] lr: 1.0000e-03 eta: 6:51:33 time: 0.5881 data_time: 0.0245 memory: 21547 grad_norm: 4.2144 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2962 loss: 1.2962 2022/10/10 04:20:47 - mmengine - INFO - Epoch(train) [49][200/940] lr: 1.0000e-03 eta: 6:51:23 time: 0.5112 data_time: 0.0237 memory: 21547 grad_norm: 4.1514 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.3133 loss: 1.3133 2022/10/10 04:20:57 - mmengine - INFO - Epoch(train) [49][220/940] lr: 1.0000e-03 eta: 6:51:14 time: 0.5402 data_time: 0.0271 memory: 21547 grad_norm: 4.2779 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2509 loss: 1.2509 2022/10/10 04:21:07 - mmengine - INFO - Epoch(train) [49][240/940] lr: 1.0000e-03 eta: 6:51:03 time: 0.4733 data_time: 0.0269 memory: 21547 grad_norm: 4.1608 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2455 loss: 1.2455 2022/10/10 04:21:16 - mmengine - INFO - Epoch(train) [49][260/940] lr: 1.0000e-03 eta: 6:50:52 time: 0.4674 data_time: 0.0271 memory: 21547 grad_norm: 4.2644 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3263 loss: 1.3263 2022/10/10 04:21:27 - mmengine - INFO - Epoch(train) [49][280/940] lr: 1.0000e-03 eta: 6:50:42 time: 0.5263 data_time: 0.0253 memory: 21547 grad_norm: 4.2490 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3011 loss: 1.3011 2022/10/10 04:21:38 - mmengine - INFO - Epoch(train) [49][300/940] lr: 1.0000e-03 eta: 6:50:33 time: 0.5608 data_time: 0.0234 memory: 21547 grad_norm: 4.1603 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.2837 loss: 1.2837 2022/10/10 04:21:47 - mmengine - INFO - Epoch(train) [49][320/940] lr: 1.0000e-03 eta: 6:50:22 time: 0.4478 data_time: 0.0289 memory: 21547 grad_norm: 4.2207 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1950 loss: 1.1950 2022/10/10 04:21:57 - mmengine - INFO - Epoch(train) [49][340/940] lr: 1.0000e-03 eta: 6:50:12 time: 0.5207 data_time: 0.0280 memory: 21547 grad_norm: 4.1486 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2713 loss: 1.2713 2022/10/10 04:22:07 - mmengine - INFO - Epoch(train) [49][360/940] lr: 1.0000e-03 eta: 6:50:01 time: 0.4574 data_time: 0.0289 memory: 21547 grad_norm: 4.1423 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.2939 loss: 1.2939 2022/10/10 04:22:17 - mmengine - INFO - Epoch(train) [49][380/940] lr: 1.0000e-03 eta: 6:49:50 time: 0.4982 data_time: 0.0335 memory: 21547 grad_norm: 4.1883 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2929 loss: 1.2929 2022/10/10 04:22:26 - mmengine - INFO - Epoch(train) [49][400/940] lr: 1.0000e-03 eta: 6:49:39 time: 0.4626 data_time: 0.0269 memory: 21547 grad_norm: 4.1809 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2685 loss: 1.2685 2022/10/10 04:22:37 - mmengine - INFO - Epoch(train) [49][420/940] lr: 1.0000e-03 eta: 6:49:30 time: 0.5631 data_time: 0.0322 memory: 21547 grad_norm: 4.1815 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.2089 loss: 1.2089 2022/10/10 04:22:47 - mmengine - INFO - Epoch(train) [49][440/940] lr: 1.0000e-03 eta: 6:49:19 time: 0.4758 data_time: 0.0271 memory: 21547 grad_norm: 4.2380 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2651 loss: 1.2651 2022/10/10 04:22:57 - mmengine - INFO - Epoch(train) [49][460/940] lr: 1.0000e-03 eta: 6:49:10 time: 0.5342 data_time: 0.0339 memory: 21547 grad_norm: 4.2444 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.3334 loss: 1.3334 2022/10/10 04:23:07 - mmengine - INFO - Epoch(train) [49][480/940] lr: 1.0000e-03 eta: 6:48:59 time: 0.4929 data_time: 0.0295 memory: 21547 grad_norm: 4.2441 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1967 loss: 1.1967 2022/10/10 04:23:18 - mmengine - INFO - Epoch(train) [49][500/940] lr: 1.0000e-03 eta: 6:48:50 time: 0.5630 data_time: 0.0282 memory: 21547 grad_norm: 4.2381 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.3614 loss: 1.3614 2022/10/10 04:23:28 - mmengine - INFO - Epoch(train) [49][520/940] lr: 1.0000e-03 eta: 6:48:40 time: 0.5023 data_time: 0.0250 memory: 21547 grad_norm: 4.2150 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2760 loss: 1.2760 2022/10/10 04:23:39 - mmengine - INFO - Epoch(train) [49][540/940] lr: 1.0000e-03 eta: 6:48:31 time: 0.5338 data_time: 0.0275 memory: 21547 grad_norm: 4.1564 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1611 loss: 1.1611 2022/10/10 04:23:48 - mmengine - INFO - Epoch(train) [49][560/940] lr: 1.0000e-03 eta: 6:48:19 time: 0.4512 data_time: 0.0297 memory: 21547 grad_norm: 4.2042 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3062 loss: 1.3062 2022/10/10 04:23:58 - mmengine - INFO - Epoch(train) [49][580/940] lr: 1.0000e-03 eta: 6:48:09 time: 0.5074 data_time: 0.0280 memory: 21547 grad_norm: 4.1585 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2047 loss: 1.2047 2022/10/10 04:24:07 - mmengine - INFO - Epoch(train) [49][600/940] lr: 1.0000e-03 eta: 6:47:58 time: 0.4568 data_time: 0.0282 memory: 21547 grad_norm: 4.1478 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3504 loss: 1.3504 2022/10/10 04:24:18 - mmengine - INFO - Epoch(train) [49][620/940] lr: 1.0000e-03 eta: 6:47:48 time: 0.5071 data_time: 0.0249 memory: 21547 grad_norm: 4.2409 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2767 loss: 1.2767 2022/10/10 04:24:28 - mmengine - INFO - Epoch(train) [49][640/940] lr: 1.0000e-03 eta: 6:47:38 time: 0.5072 data_time: 0.0295 memory: 21547 grad_norm: 4.2075 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2954 loss: 1.2954 2022/10/10 04:24:37 - mmengine - INFO - Epoch(train) [49][660/940] lr: 1.0000e-03 eta: 6:47:27 time: 0.4876 data_time: 0.0232 memory: 21547 grad_norm: 4.1904 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.3346 loss: 1.3346 2022/10/10 04:24:47 - mmengine - INFO - Epoch(train) [49][680/940] lr: 1.0000e-03 eta: 6:47:16 time: 0.4615 data_time: 0.0274 memory: 21547 grad_norm: 4.2907 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3056 loss: 1.3056 2022/10/10 04:24:57 - mmengine - INFO - Epoch(train) [49][700/940] lr: 1.0000e-03 eta: 6:47:06 time: 0.5111 data_time: 0.0224 memory: 21547 grad_norm: 4.2684 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3236 loss: 1.3236 2022/10/10 04:25:07 - mmengine - INFO - Epoch(train) [49][720/940] lr: 1.0000e-03 eta: 6:46:55 time: 0.4853 data_time: 0.0237 memory: 21547 grad_norm: 4.3920 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3454 loss: 1.3454 2022/10/10 04:25:17 - mmengine - INFO - Epoch(train) [49][740/940] lr: 1.0000e-03 eta: 6:46:46 time: 0.5285 data_time: 0.0225 memory: 21547 grad_norm: 4.2279 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3130 loss: 1.3130 2022/10/10 04:25:28 - mmengine - INFO - Epoch(train) [49][760/940] lr: 1.0000e-03 eta: 6:46:36 time: 0.5173 data_time: 0.0242 memory: 21547 grad_norm: 4.2613 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4339 loss: 1.4339 2022/10/10 04:25:37 - mmengine - INFO - Epoch(train) [49][780/940] lr: 1.0000e-03 eta: 6:46:25 time: 0.4893 data_time: 0.0259 memory: 21547 grad_norm: 4.2103 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2823 loss: 1.2823 2022/10/10 04:25:47 - mmengine - INFO - Epoch(train) [49][800/940] lr: 1.0000e-03 eta: 6:46:15 time: 0.4962 data_time: 0.0306 memory: 21547 grad_norm: 4.2081 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3679 loss: 1.3679 2022/10/10 04:25:57 - mmengine - INFO - Epoch(train) [49][820/940] lr: 1.0000e-03 eta: 6:46:05 time: 0.5026 data_time: 0.0273 memory: 21547 grad_norm: 4.2016 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3151 loss: 1.3151 2022/10/10 04:26:07 - mmengine - INFO - Epoch(train) [49][840/940] lr: 1.0000e-03 eta: 6:45:54 time: 0.4966 data_time: 0.0342 memory: 21547 grad_norm: 4.2410 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2605 loss: 1.2605 2022/10/10 04:26:17 - mmengine - INFO - Epoch(train) [49][860/940] lr: 1.0000e-03 eta: 6:45:44 time: 0.5072 data_time: 0.0320 memory: 21547 grad_norm: 4.2262 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.3227 loss: 1.3227 2022/10/10 04:26:27 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 04:26:27 - mmengine - INFO - Epoch(train) [49][880/940] lr: 1.0000e-03 eta: 6:45:34 time: 0.4947 data_time: 0.0335 memory: 21547 grad_norm: 4.2853 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2833 loss: 1.2833 2022/10/10 04:26:37 - mmengine - INFO - Epoch(train) [49][900/940] lr: 1.0000e-03 eta: 6:45:24 time: 0.5009 data_time: 0.0199 memory: 21547 grad_norm: 4.1817 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.2674 loss: 1.2674 2022/10/10 04:26:47 - mmengine - INFO - Epoch(train) [49][920/940] lr: 1.0000e-03 eta: 6:45:13 time: 0.5056 data_time: 0.0303 memory: 21547 grad_norm: 4.3037 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.4222 loss: 1.4222 2022/10/10 04:26:56 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 04:26:56 - mmengine - INFO - Epoch(train) [49][940/940] lr: 1.0000e-03 eta: 6:45:02 time: 0.4438 data_time: 0.0208 memory: 21547 grad_norm: 4.5013 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.3669 loss: 1.3669 2022/10/10 04:27:08 - mmengine - INFO - Epoch(val) [49][20/78] eta: 0:00:34 time: 0.6012 data_time: 0.4902 memory: 3269 2022/10/10 04:27:17 - mmengine - INFO - Epoch(val) [49][40/78] eta: 0:00:16 time: 0.4281 data_time: 0.3204 memory: 3269 2022/10/10 04:27:28 - mmengine - INFO - Epoch(val) [49][60/78] eta: 0:00:09 time: 0.5495 data_time: 0.4427 memory: 3269 2022/10/10 04:27:38 - mmengine - INFO - Epoch(val) [49][78/78] acc/top1: 0.6741 acc/top5: 0.8702 acc/mean1: 0.6739 2022/10/10 04:27:52 - mmengine - INFO - Epoch(train) [50][20/940] lr: 1.0000e-03 eta: 6:44:56 time: 0.6929 data_time: 0.1969 memory: 21547 grad_norm: 4.1898 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2535 loss: 1.2535 2022/10/10 04:28:02 - mmengine - INFO - Epoch(train) [50][40/940] lr: 1.0000e-03 eta: 6:44:45 time: 0.4936 data_time: 0.0250 memory: 21547 grad_norm: 4.2306 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.3002 loss: 1.3002 2022/10/10 04:28:13 - mmengine - INFO - Epoch(train) [50][60/940] lr: 1.0000e-03 eta: 6:44:36 time: 0.5474 data_time: 0.0365 memory: 21547 grad_norm: 4.2120 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.3662 loss: 1.3662 2022/10/10 04:28:22 - mmengine - INFO - Epoch(train) [50][80/940] lr: 1.0000e-03 eta: 6:44:25 time: 0.4881 data_time: 0.0269 memory: 21547 grad_norm: 4.1697 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2974 loss: 1.2974 2022/10/10 04:28:34 - mmengine - INFO - Epoch(train) [50][100/940] lr: 1.0000e-03 eta: 6:44:16 time: 0.5637 data_time: 0.0389 memory: 21547 grad_norm: 4.2030 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1912 loss: 1.1912 2022/10/10 04:28:43 - mmengine - INFO - Epoch(train) [50][120/940] lr: 1.0000e-03 eta: 6:44:05 time: 0.4613 data_time: 0.0251 memory: 21547 grad_norm: 4.1975 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4152 loss: 1.4152 2022/10/10 04:28:53 - mmengine - INFO - Epoch(train) [50][140/940] lr: 1.0000e-03 eta: 6:43:55 time: 0.5176 data_time: 0.0319 memory: 21547 grad_norm: 4.2499 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3980 loss: 1.3980 2022/10/10 04:29:04 - mmengine - INFO - Epoch(train) [50][160/940] lr: 1.0000e-03 eta: 6:43:46 time: 0.5235 data_time: 0.0257 memory: 21547 grad_norm: 4.3071 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3938 loss: 1.3938 2022/10/10 04:29:13 - mmengine - INFO - Epoch(train) [50][180/940] lr: 1.0000e-03 eta: 6:43:35 time: 0.4861 data_time: 0.0311 memory: 21547 grad_norm: 4.1357 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2784 loss: 1.2784 2022/10/10 04:29:24 - mmengine - INFO - Epoch(train) [50][200/940] lr: 1.0000e-03 eta: 6:43:25 time: 0.5057 data_time: 0.0243 memory: 21547 grad_norm: 4.3208 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2552 loss: 1.2552 2022/10/10 04:29:34 - mmengine - INFO - Epoch(train) [50][220/940] lr: 1.0000e-03 eta: 6:43:15 time: 0.5146 data_time: 0.0242 memory: 21547 grad_norm: 4.1862 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.3193 loss: 1.3193 2022/10/10 04:29:44 - mmengine - INFO - Epoch(train) [50][240/940] lr: 1.0000e-03 eta: 6:43:04 time: 0.4902 data_time: 0.0283 memory: 21547 grad_norm: 4.1067 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3743 loss: 1.3743 2022/10/10 04:29:54 - mmengine - INFO - Epoch(train) [50][260/940] lr: 1.0000e-03 eta: 6:42:54 time: 0.4975 data_time: 0.0269 memory: 21547 grad_norm: 4.2660 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2728 loss: 1.2728 2022/10/10 04:30:03 - mmengine - INFO - Epoch(train) [50][280/940] lr: 1.0000e-03 eta: 6:42:43 time: 0.4720 data_time: 0.0254 memory: 21547 grad_norm: 4.2268 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3210 loss: 1.3210 2022/10/10 04:30:13 - mmengine - INFO - Epoch(train) [50][300/940] lr: 1.0000e-03 eta: 6:42:32 time: 0.4760 data_time: 0.0303 memory: 21547 grad_norm: 4.2405 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1597 loss: 1.1597 2022/10/10 04:30:23 - mmengine - INFO - Epoch(train) [50][320/940] lr: 1.0000e-03 eta: 6:42:22 time: 0.5101 data_time: 0.0284 memory: 21547 grad_norm: 4.1966 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2814 loss: 1.2814 2022/10/10 04:30:33 - mmengine - INFO - Epoch(train) [50][340/940] lr: 1.0000e-03 eta: 6:42:13 time: 0.5215 data_time: 0.0318 memory: 21547 grad_norm: 4.2205 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4348 loss: 1.4348 2022/10/10 04:30:42 - mmengine - INFO - Epoch(train) [50][360/940] lr: 1.0000e-03 eta: 6:42:01 time: 0.4599 data_time: 0.0312 memory: 21547 grad_norm: 4.2751 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3376 loss: 1.3376 2022/10/10 04:30:53 - mmengine - INFO - Epoch(train) [50][380/940] lr: 1.0000e-03 eta: 6:41:51 time: 0.5066 data_time: 0.0331 memory: 21547 grad_norm: 4.2348 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4125 loss: 1.4125 2022/10/10 04:31:03 - mmengine - INFO - Epoch(train) [50][400/940] lr: 1.0000e-03 eta: 6:41:41 time: 0.5211 data_time: 0.0292 memory: 21547 grad_norm: 4.2051 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1622 loss: 1.1622 2022/10/10 04:31:13 - mmengine - INFO - Epoch(train) [50][420/940] lr: 1.0000e-03 eta: 6:41:31 time: 0.4909 data_time: 0.0339 memory: 21547 grad_norm: 4.3201 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2866 loss: 1.2866 2022/10/10 04:31:23 - mmengine - INFO - Epoch(train) [50][440/940] lr: 1.0000e-03 eta: 6:41:21 time: 0.5063 data_time: 0.0470 memory: 21547 grad_norm: 4.2816 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2938 loss: 1.2938 2022/10/10 04:31:33 - mmengine - INFO - Epoch(train) [50][460/940] lr: 1.0000e-03 eta: 6:41:10 time: 0.4835 data_time: 0.0572 memory: 21547 grad_norm: 4.2065 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2651 loss: 1.2651 2022/10/10 04:31:42 - mmengine - INFO - Epoch(train) [50][480/940] lr: 1.0000e-03 eta: 6:40:59 time: 0.4773 data_time: 0.0732 memory: 21547 grad_norm: 4.2587 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2336 loss: 1.2336 2022/10/10 04:31:53 - mmengine - INFO - Epoch(train) [50][500/940] lr: 1.0000e-03 eta: 6:40:50 time: 0.5184 data_time: 0.0409 memory: 21547 grad_norm: 4.2405 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2941 loss: 1.2941 2022/10/10 04:32:02 - mmengine - INFO - Epoch(train) [50][520/940] lr: 1.0000e-03 eta: 6:40:39 time: 0.4910 data_time: 0.0434 memory: 21547 grad_norm: 4.3658 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3147 loss: 1.3147 2022/10/10 04:32:13 - mmengine - INFO - Epoch(train) [50][540/940] lr: 1.0000e-03 eta: 6:40:29 time: 0.5260 data_time: 0.0617 memory: 21547 grad_norm: 4.2758 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1997 loss: 1.1997 2022/10/10 04:32:24 - mmengine - INFO - Epoch(train) [50][560/940] lr: 1.0000e-03 eta: 6:40:20 time: 0.5362 data_time: 0.1385 memory: 21547 grad_norm: 4.1983 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2543 loss: 1.2543 2022/10/10 04:32:34 - mmengine - INFO - Epoch(train) [50][580/940] lr: 1.0000e-03 eta: 6:40:10 time: 0.5043 data_time: 0.0910 memory: 21547 grad_norm: 4.2655 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1900 loss: 1.1900 2022/10/10 04:32:43 - mmengine - INFO - Epoch(train) [50][600/940] lr: 1.0000e-03 eta: 6:39:59 time: 0.4899 data_time: 0.0437 memory: 21547 grad_norm: 4.2541 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2716 loss: 1.2716 2022/10/10 04:32:53 - mmengine - INFO - Epoch(train) [50][620/940] lr: 1.0000e-03 eta: 6:39:49 time: 0.4960 data_time: 0.0618 memory: 21547 grad_norm: 4.1878 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2437 loss: 1.2437 2022/10/10 04:33:03 - mmengine - INFO - Epoch(train) [50][640/940] lr: 1.0000e-03 eta: 6:39:38 time: 0.4710 data_time: 0.0878 memory: 21547 grad_norm: 4.2529 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2266 loss: 1.2266 2022/10/10 04:33:13 - mmengine - INFO - Epoch(train) [50][660/940] lr: 1.0000e-03 eta: 6:39:28 time: 0.5117 data_time: 0.1024 memory: 21547 grad_norm: 4.2976 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2444 loss: 1.2444 2022/10/10 04:33:23 - mmengine - INFO - Epoch(train) [50][680/940] lr: 1.0000e-03 eta: 6:39:17 time: 0.4797 data_time: 0.0303 memory: 21547 grad_norm: 4.2329 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4507 loss: 1.4507 2022/10/10 04:33:33 - mmengine - INFO - Epoch(train) [50][700/940] lr: 1.0000e-03 eta: 6:39:07 time: 0.5227 data_time: 0.0338 memory: 21547 grad_norm: 4.2237 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3344 loss: 1.3344 2022/10/10 04:33:43 - mmengine - INFO - Epoch(train) [50][720/940] lr: 1.0000e-03 eta: 6:38:57 time: 0.4860 data_time: 0.0283 memory: 21547 grad_norm: 4.2845 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2627 loss: 1.2627 2022/10/10 04:33:53 - mmengine - INFO - Epoch(train) [50][740/940] lr: 1.0000e-03 eta: 6:38:47 time: 0.5029 data_time: 0.0296 memory: 21547 grad_norm: 4.1515 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2278 loss: 1.2278 2022/10/10 04:34:03 - mmengine - INFO - Epoch(train) [50][760/940] lr: 1.0000e-03 eta: 6:38:36 time: 0.5072 data_time: 0.0283 memory: 21547 grad_norm: 4.3064 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2252 loss: 1.2252 2022/10/10 04:34:13 - mmengine - INFO - Epoch(train) [50][780/940] lr: 1.0000e-03 eta: 6:38:26 time: 0.4745 data_time: 0.0295 memory: 21547 grad_norm: 4.3051 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2393 loss: 1.2393 2022/10/10 04:34:23 - mmengine - INFO - Epoch(train) [50][800/940] lr: 1.0000e-03 eta: 6:38:15 time: 0.5041 data_time: 0.0276 memory: 21547 grad_norm: 4.3011 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2783 loss: 1.2783 2022/10/10 04:34:33 - mmengine - INFO - Epoch(train) [50][820/940] lr: 1.0000e-03 eta: 6:38:06 time: 0.5305 data_time: 0.0467 memory: 21547 grad_norm: 4.2433 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2312 loss: 1.2312 2022/10/10 04:34:43 - mmengine - INFO - Epoch(train) [50][840/940] lr: 1.0000e-03 eta: 6:37:56 time: 0.5042 data_time: 0.0258 memory: 21547 grad_norm: 4.3052 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2128 loss: 1.2128 2022/10/10 04:34:54 - mmengine - INFO - Epoch(train) [50][860/940] lr: 1.0000e-03 eta: 6:37:46 time: 0.5182 data_time: 0.0332 memory: 21547 grad_norm: 4.2770 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2471 loss: 1.2471 2022/10/10 04:35:03 - mmengine - INFO - Epoch(train) [50][880/940] lr: 1.0000e-03 eta: 6:37:35 time: 0.4756 data_time: 0.0264 memory: 21547 grad_norm: 4.2922 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3494 loss: 1.3494 2022/10/10 04:35:13 - mmengine - INFO - Epoch(train) [50][900/940] lr: 1.0000e-03 eta: 6:37:24 time: 0.4924 data_time: 0.0316 memory: 21547 grad_norm: 4.3236 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4629 loss: 1.4629 2022/10/10 04:35:24 - mmengine - INFO - Epoch(train) [50][920/940] lr: 1.0000e-03 eta: 6:37:15 time: 0.5435 data_time: 0.0284 memory: 21547 grad_norm: 4.2514 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3218 loss: 1.3218 2022/10/10 04:35:33 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 04:35:33 - mmengine - INFO - Epoch(train) [50][940/940] lr: 1.0000e-03 eta: 6:37:04 time: 0.4484 data_time: 0.0295 memory: 21547 grad_norm: 4.4507 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.2455 loss: 1.2455 2022/10/10 04:35:45 - mmengine - INFO - Epoch(val) [50][20/78] eta: 0:00:34 time: 0.6010 data_time: 0.4928 memory: 3269 2022/10/10 04:35:53 - mmengine - INFO - Epoch(val) [50][40/78] eta: 0:00:16 time: 0.4245 data_time: 0.3175 memory: 3269 2022/10/10 04:36:05 - mmengine - INFO - Epoch(val) [50][60/78] eta: 0:00:10 time: 0.5686 data_time: 0.4633 memory: 3269 2022/10/10 04:36:15 - mmengine - INFO - Epoch(val) [50][78/78] acc/top1: 0.6771 acc/top5: 0.8702 acc/mean1: 0.6769 2022/10/10 04:36:15 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_44.pth is removed 2022/10/10 04:36:15 - mmengine - INFO - The best checkpoint with 0.6771 acc/top1 at 50 epoch is saved to best_acc/top1_epoch_50.pth. 2022/10/10 04:36:29 - mmengine - INFO - Epoch(train) [51][20/940] lr: 1.0000e-03 eta: 6:36:57 time: 0.6929 data_time: 0.3246 memory: 21547 grad_norm: 4.2105 top1_acc: 0.6875 top5_acc: 0.7188 loss_cls: 1.3561 loss: 1.3561 2022/10/10 04:36:39 - mmengine - INFO - Epoch(train) [51][40/940] lr: 1.0000e-03 eta: 6:36:47 time: 0.4995 data_time: 0.1105 memory: 21547 grad_norm: 4.1644 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.2101 loss: 1.2101 2022/10/10 04:36:50 - mmengine - INFO - Epoch(train) [51][60/940] lr: 1.0000e-03 eta: 6:36:37 time: 0.5352 data_time: 0.1602 memory: 21547 grad_norm: 4.3304 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2677 loss: 1.2677 2022/10/10 04:37:00 - mmengine - INFO - Epoch(train) [51][80/940] lr: 1.0000e-03 eta: 6:36:27 time: 0.5034 data_time: 0.1244 memory: 21547 grad_norm: 4.1708 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2447 loss: 1.2447 2022/10/10 04:37:10 - mmengine - INFO - Epoch(train) [51][100/940] lr: 1.0000e-03 eta: 6:36:17 time: 0.4880 data_time: 0.1167 memory: 21547 grad_norm: 4.1011 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2617 loss: 1.2617 2022/10/10 04:37:19 - mmengine - INFO - Epoch(train) [51][120/940] lr: 1.0000e-03 eta: 6:36:06 time: 0.4838 data_time: 0.1051 memory: 21547 grad_norm: 4.2779 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.3457 loss: 1.3457 2022/10/10 04:37:30 - mmengine - INFO - Epoch(train) [51][140/940] lr: 1.0000e-03 eta: 6:35:57 time: 0.5392 data_time: 0.1639 memory: 21547 grad_norm: 4.2402 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2782 loss: 1.2782 2022/10/10 04:37:39 - mmengine - INFO - Epoch(train) [51][160/940] lr: 1.0000e-03 eta: 6:35:45 time: 0.4578 data_time: 0.0764 memory: 21547 grad_norm: 4.1942 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2755 loss: 1.2755 2022/10/10 04:37:50 - mmengine - INFO - Epoch(train) [51][180/940] lr: 1.0000e-03 eta: 6:35:36 time: 0.5482 data_time: 0.1789 memory: 21547 grad_norm: 4.3053 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3453 loss: 1.3453 2022/10/10 04:38:00 - mmengine - INFO - Epoch(train) [51][200/940] lr: 1.0000e-03 eta: 6:35:26 time: 0.4947 data_time: 0.1119 memory: 21547 grad_norm: 4.3139 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3250 loss: 1.3250 2022/10/10 04:38:10 - mmengine - INFO - Epoch(train) [51][220/940] lr: 1.0000e-03 eta: 6:35:15 time: 0.4801 data_time: 0.0977 memory: 21547 grad_norm: 4.3582 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.4429 loss: 1.4429 2022/10/10 04:38:20 - mmengine - INFO - Epoch(train) [51][240/940] lr: 1.0000e-03 eta: 6:35:05 time: 0.5096 data_time: 0.0250 memory: 21547 grad_norm: 4.2875 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3545 loss: 1.3545 2022/10/10 04:38:30 - mmengine - INFO - Epoch(train) [51][260/940] lr: 1.0000e-03 eta: 6:34:55 time: 0.5315 data_time: 0.0284 memory: 21547 grad_norm: 4.2489 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2466 loss: 1.2466 2022/10/10 04:38:40 - mmengine - INFO - Epoch(train) [51][280/940] lr: 1.0000e-03 eta: 6:34:44 time: 0.4700 data_time: 0.0265 memory: 21547 grad_norm: 4.2089 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2951 loss: 1.2951 2022/10/10 04:38:50 - mmengine - INFO - Epoch(train) [51][300/940] lr: 1.0000e-03 eta: 6:34:35 time: 0.5244 data_time: 0.0284 memory: 21547 grad_norm: 4.2866 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3919 loss: 1.3919 2022/10/10 04:39:00 - mmengine - INFO - Epoch(train) [51][320/940] lr: 1.0000e-03 eta: 6:34:24 time: 0.4873 data_time: 0.0275 memory: 21547 grad_norm: 4.3081 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1899 loss: 1.1899 2022/10/10 04:39:10 - mmengine - INFO - Epoch(train) [51][340/940] lr: 1.0000e-03 eta: 6:34:14 time: 0.5032 data_time: 0.0297 memory: 21547 grad_norm: 4.2376 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2050 loss: 1.2050 2022/10/10 04:39:20 - mmengine - INFO - Epoch(train) [51][360/940] lr: 1.0000e-03 eta: 6:34:03 time: 0.4734 data_time: 0.0272 memory: 21547 grad_norm: 4.2974 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2694 loss: 1.2694 2022/10/10 04:39:29 - mmengine - INFO - Epoch(train) [51][380/940] lr: 1.0000e-03 eta: 6:33:53 time: 0.4835 data_time: 0.0288 memory: 21547 grad_norm: 4.2829 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2485 loss: 1.2485 2022/10/10 04:39:39 - mmengine - INFO - Epoch(train) [51][400/940] lr: 1.0000e-03 eta: 6:33:42 time: 0.4962 data_time: 0.0303 memory: 21547 grad_norm: 4.3106 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3916 loss: 1.3916 2022/10/10 04:39:50 - mmengine - INFO - Epoch(train) [51][420/940] lr: 1.0000e-03 eta: 6:33:33 time: 0.5419 data_time: 0.0304 memory: 21547 grad_norm: 4.2494 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2034 loss: 1.2034 2022/10/10 04:40:00 - mmengine - INFO - Epoch(train) [51][440/940] lr: 1.0000e-03 eta: 6:33:22 time: 0.4811 data_time: 0.0321 memory: 21547 grad_norm: 4.2187 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2346 loss: 1.2346 2022/10/10 04:40:09 - mmengine - INFO - Epoch(train) [51][460/940] lr: 1.0000e-03 eta: 6:33:11 time: 0.4786 data_time: 0.0245 memory: 21547 grad_norm: 4.2978 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2002 loss: 1.2002 2022/10/10 04:40:19 - mmengine - INFO - Epoch(train) [51][480/940] lr: 1.0000e-03 eta: 6:33:01 time: 0.5050 data_time: 0.0332 memory: 21547 grad_norm: 4.2132 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.2886 loss: 1.2886 2022/10/10 04:40:29 - mmengine - INFO - Epoch(train) [51][500/940] lr: 1.0000e-03 eta: 6:32:51 time: 0.5046 data_time: 0.0226 memory: 21547 grad_norm: 4.2408 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1372 loss: 1.1372 2022/10/10 04:40:40 - mmengine - INFO - Epoch(train) [51][520/940] lr: 1.0000e-03 eta: 6:32:41 time: 0.5144 data_time: 0.0370 memory: 21547 grad_norm: 4.2187 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2056 loss: 1.2056 2022/10/10 04:40:50 - mmengine - INFO - Epoch(train) [51][540/940] lr: 1.0000e-03 eta: 6:32:31 time: 0.5076 data_time: 0.0252 memory: 21547 grad_norm: 4.2060 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3644 loss: 1.3644 2022/10/10 04:41:00 - mmengine - INFO - Epoch(train) [51][560/940] lr: 1.0000e-03 eta: 6:32:21 time: 0.4953 data_time: 0.0314 memory: 21547 grad_norm: 4.2960 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2411 loss: 1.2411 2022/10/10 04:41:10 - mmengine - INFO - Epoch(train) [51][580/940] lr: 1.0000e-03 eta: 6:32:10 time: 0.4846 data_time: 0.0278 memory: 21547 grad_norm: 4.3246 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2300 loss: 1.2300 2022/10/10 04:41:20 - mmengine - INFO - Epoch(train) [51][600/940] lr: 1.0000e-03 eta: 6:32:00 time: 0.5139 data_time: 0.0286 memory: 21547 grad_norm: 4.3521 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3412 loss: 1.3412 2022/10/10 04:41:30 - mmengine - INFO - Epoch(train) [51][620/940] lr: 1.0000e-03 eta: 6:31:50 time: 0.5090 data_time: 0.0300 memory: 21547 grad_norm: 4.2831 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2128 loss: 1.2128 2022/10/10 04:41:40 - mmengine - INFO - Epoch(train) [51][640/940] lr: 1.0000e-03 eta: 6:31:40 time: 0.5031 data_time: 0.0291 memory: 21547 grad_norm: 4.2657 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2473 loss: 1.2473 2022/10/10 04:41:50 - mmengine - INFO - Epoch(train) [51][660/940] lr: 1.0000e-03 eta: 6:31:30 time: 0.5173 data_time: 0.0299 memory: 21547 grad_norm: 4.2931 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.1997 loss: 1.1997 2022/10/10 04:42:00 - mmengine - INFO - Epoch(train) [51][680/940] lr: 1.0000e-03 eta: 6:31:19 time: 0.4849 data_time: 0.0287 memory: 21547 grad_norm: 4.2622 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1940 loss: 1.1940 2022/10/10 04:42:10 - mmengine - INFO - Epoch(train) [51][700/940] lr: 1.0000e-03 eta: 6:31:09 time: 0.4924 data_time: 0.0406 memory: 21547 grad_norm: 4.3051 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2934 loss: 1.2934 2022/10/10 04:42:20 - mmengine - INFO - Epoch(train) [51][720/940] lr: 1.0000e-03 eta: 6:30:58 time: 0.4862 data_time: 0.0385 memory: 21547 grad_norm: 4.3111 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3436 loss: 1.3436 2022/10/10 04:42:30 - mmengine - INFO - Epoch(train) [51][740/940] lr: 1.0000e-03 eta: 6:30:48 time: 0.5088 data_time: 0.0275 memory: 21547 grad_norm: 4.2888 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3207 loss: 1.3207 2022/10/10 04:42:41 - mmengine - INFO - Epoch(train) [51][760/940] lr: 1.0000e-03 eta: 6:30:39 time: 0.5525 data_time: 0.0317 memory: 21547 grad_norm: 4.2111 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3264 loss: 1.3264 2022/10/10 04:42:51 - mmengine - INFO - Epoch(train) [51][780/940] lr: 1.0000e-03 eta: 6:30:29 time: 0.5026 data_time: 0.0238 memory: 21547 grad_norm: 4.3160 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2989 loss: 1.2989 2022/10/10 04:43:02 - mmengine - INFO - Epoch(train) [51][800/940] lr: 1.0000e-03 eta: 6:30:19 time: 0.5527 data_time: 0.0267 memory: 21547 grad_norm: 4.3408 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3506 loss: 1.3506 2022/10/10 04:43:12 - mmengine - INFO - Epoch(train) [51][820/940] lr: 1.0000e-03 eta: 6:30:09 time: 0.4912 data_time: 0.0311 memory: 21547 grad_norm: 4.3473 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4058 loss: 1.4058 2022/10/10 04:43:22 - mmengine - INFO - Epoch(train) [51][840/940] lr: 1.0000e-03 eta: 6:29:59 time: 0.5279 data_time: 0.0453 memory: 21547 grad_norm: 4.2555 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.3701 loss: 1.3701 2022/10/10 04:43:33 - mmengine - INFO - Epoch(train) [51][860/940] lr: 1.0000e-03 eta: 6:29:49 time: 0.5175 data_time: 0.0226 memory: 21547 grad_norm: 4.3468 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2860 loss: 1.2860 2022/10/10 04:43:42 - mmengine - INFO - Epoch(train) [51][880/940] lr: 1.0000e-03 eta: 6:29:38 time: 0.4712 data_time: 0.0263 memory: 21547 grad_norm: 4.2574 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2437 loss: 1.2437 2022/10/10 04:43:52 - mmengine - INFO - Epoch(train) [51][900/940] lr: 1.0000e-03 eta: 6:29:28 time: 0.4811 data_time: 0.0245 memory: 21547 grad_norm: 4.3490 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.4019 loss: 1.4019 2022/10/10 04:44:03 - mmengine - INFO - Epoch(train) [51][920/940] lr: 1.0000e-03 eta: 6:29:19 time: 0.5667 data_time: 0.0276 memory: 21547 grad_norm: 4.3556 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3427 loss: 1.3427 2022/10/10 04:44:11 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 04:44:11 - mmengine - INFO - Epoch(train) [51][940/940] lr: 1.0000e-03 eta: 6:29:06 time: 0.3844 data_time: 0.0242 memory: 21547 grad_norm: 4.4637 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.3176 loss: 1.3176 2022/10/10 04:44:11 - mmengine - INFO - Saving checkpoint at 51 epochs 2022/10/10 04:44:24 - mmengine - INFO - Epoch(val) [51][20/78] eta: 0:00:35 time: 0.6110 data_time: 0.5047 memory: 3269 2022/10/10 04:44:32 - mmengine - INFO - Epoch(val) [51][40/78] eta: 0:00:15 time: 0.4206 data_time: 0.3156 memory: 3269 2022/10/10 04:44:44 - mmengine - INFO - Epoch(val) [51][60/78] eta: 0:00:10 time: 0.5573 data_time: 0.4521 memory: 3269 2022/10/10 04:44:52 - mmengine - INFO - Epoch(val) [51][78/78] acc/top1: 0.6767 acc/top5: 0.8718 acc/mean1: 0.6765 2022/10/10 04:45:07 - mmengine - INFO - Epoch(train) [52][20/940] lr: 1.0000e-03 eta: 6:29:00 time: 0.7266 data_time: 0.2173 memory: 21547 grad_norm: 4.2253 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.2382 loss: 1.2382 2022/10/10 04:45:17 - mmengine - INFO - Epoch(train) [52][40/940] lr: 1.0000e-03 eta: 6:28:51 time: 0.5215 data_time: 0.0306 memory: 21547 grad_norm: 4.3362 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3151 loss: 1.3151 2022/10/10 04:45:28 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 04:45:28 - mmengine - INFO - Epoch(train) [52][60/940] lr: 1.0000e-03 eta: 6:28:41 time: 0.5376 data_time: 0.0267 memory: 21547 grad_norm: 4.2931 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2769 loss: 1.2769 2022/10/10 04:45:37 - mmengine - INFO - Epoch(train) [52][80/940] lr: 1.0000e-03 eta: 6:28:30 time: 0.4529 data_time: 0.0272 memory: 21547 grad_norm: 4.1772 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1744 loss: 1.1744 2022/10/10 04:45:48 - mmengine - INFO - Epoch(train) [52][100/940] lr: 1.0000e-03 eta: 6:28:20 time: 0.5195 data_time: 0.0283 memory: 21547 grad_norm: 4.3425 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2695 loss: 1.2695 2022/10/10 04:45:57 - mmengine - INFO - Epoch(train) [52][120/940] lr: 1.0000e-03 eta: 6:28:09 time: 0.4569 data_time: 0.0287 memory: 21547 grad_norm: 4.2397 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2960 loss: 1.2960 2022/10/10 04:46:07 - mmengine - INFO - Epoch(train) [52][140/940] lr: 1.0000e-03 eta: 6:27:59 time: 0.5093 data_time: 0.0390 memory: 21547 grad_norm: 4.2275 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2297 loss: 1.2297 2022/10/10 04:46:17 - mmengine - INFO - Epoch(train) [52][160/940] lr: 1.0000e-03 eta: 6:27:49 time: 0.5175 data_time: 0.0238 memory: 21547 grad_norm: 4.3006 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3370 loss: 1.3370 2022/10/10 04:46:28 - mmengine - INFO - Epoch(train) [52][180/940] lr: 1.0000e-03 eta: 6:27:39 time: 0.5424 data_time: 0.0277 memory: 21547 grad_norm: 4.2678 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2774 loss: 1.2774 2022/10/10 04:46:38 - mmengine - INFO - Epoch(train) [52][200/940] lr: 1.0000e-03 eta: 6:27:29 time: 0.4810 data_time: 0.0269 memory: 21547 grad_norm: 4.3202 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3820 loss: 1.3820 2022/10/10 04:46:49 - mmengine - INFO - Epoch(train) [52][220/940] lr: 1.0000e-03 eta: 6:27:19 time: 0.5370 data_time: 0.0285 memory: 21547 grad_norm: 4.2859 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2764 loss: 1.2764 2022/10/10 04:46:58 - mmengine - INFO - Epoch(train) [52][240/940] lr: 1.0000e-03 eta: 6:27:08 time: 0.4525 data_time: 0.0289 memory: 21547 grad_norm: 4.2261 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3373 loss: 1.3373 2022/10/10 04:47:08 - mmengine - INFO - Epoch(train) [52][260/940] lr: 1.0000e-03 eta: 6:26:58 time: 0.5122 data_time: 0.0301 memory: 21547 grad_norm: 4.4078 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3393 loss: 1.3393 2022/10/10 04:47:18 - mmengine - INFO - Epoch(train) [52][280/940] lr: 1.0000e-03 eta: 6:26:48 time: 0.5148 data_time: 0.0273 memory: 21547 grad_norm: 4.3833 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3177 loss: 1.3177 2022/10/10 04:47:29 - mmengine - INFO - Epoch(train) [52][300/940] lr: 1.0000e-03 eta: 6:26:38 time: 0.5262 data_time: 0.0328 memory: 21547 grad_norm: 4.2348 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2062 loss: 1.2062 2022/10/10 04:47:39 - mmengine - INFO - Epoch(train) [52][320/940] lr: 1.0000e-03 eta: 6:26:28 time: 0.5255 data_time: 0.0329 memory: 21547 grad_norm: 4.3215 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2258 loss: 1.2258 2022/10/10 04:47:49 - mmengine - INFO - Epoch(train) [52][340/940] lr: 1.0000e-03 eta: 6:26:18 time: 0.4716 data_time: 0.0357 memory: 21547 grad_norm: 4.2300 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1635 loss: 1.1635 2022/10/10 04:47:58 - mmengine - INFO - Epoch(train) [52][360/940] lr: 1.0000e-03 eta: 6:26:07 time: 0.4819 data_time: 0.0240 memory: 21547 grad_norm: 4.2322 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1866 loss: 1.1866 2022/10/10 04:48:09 - mmengine - INFO - Epoch(train) [52][380/940] lr: 1.0000e-03 eta: 6:25:57 time: 0.5426 data_time: 0.0305 memory: 21547 grad_norm: 4.2299 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1952 loss: 1.1952 2022/10/10 04:48:19 - mmengine - INFO - Epoch(train) [52][400/940] lr: 1.0000e-03 eta: 6:25:47 time: 0.4772 data_time: 0.0260 memory: 21547 grad_norm: 4.2776 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.2908 loss: 1.2908 2022/10/10 04:48:29 - mmengine - INFO - Epoch(train) [52][420/940] lr: 1.0000e-03 eta: 6:25:37 time: 0.5002 data_time: 0.0264 memory: 21547 grad_norm: 4.1859 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.3219 loss: 1.3219 2022/10/10 04:48:38 - mmengine - INFO - Epoch(train) [52][440/940] lr: 1.0000e-03 eta: 6:25:26 time: 0.4798 data_time: 0.0246 memory: 21547 grad_norm: 4.3587 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3353 loss: 1.3353 2022/10/10 04:48:48 - mmengine - INFO - Epoch(train) [52][460/940] lr: 1.0000e-03 eta: 6:25:16 time: 0.5006 data_time: 0.0271 memory: 21547 grad_norm: 4.2678 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2812 loss: 1.2812 2022/10/10 04:48:58 - mmengine - INFO - Epoch(train) [52][480/940] lr: 1.0000e-03 eta: 6:25:05 time: 0.5067 data_time: 0.0257 memory: 21547 grad_norm: 4.3286 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2235 loss: 1.2235 2022/10/10 04:49:09 - mmengine - INFO - Epoch(train) [52][500/940] lr: 1.0000e-03 eta: 6:24:55 time: 0.5125 data_time: 0.0267 memory: 21547 grad_norm: 4.2304 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2675 loss: 1.2675 2022/10/10 04:49:18 - mmengine - INFO - Epoch(train) [52][520/940] lr: 1.0000e-03 eta: 6:24:45 time: 0.4876 data_time: 0.0332 memory: 21547 grad_norm: 4.3247 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2291 loss: 1.2291 2022/10/10 04:49:29 - mmengine - INFO - Epoch(train) [52][540/940] lr: 1.0000e-03 eta: 6:24:35 time: 0.5303 data_time: 0.0274 memory: 21547 grad_norm: 4.2314 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3534 loss: 1.3534 2022/10/10 04:49:39 - mmengine - INFO - Epoch(train) [52][560/940] lr: 1.0000e-03 eta: 6:24:25 time: 0.4790 data_time: 0.0274 memory: 21547 grad_norm: 4.3665 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1874 loss: 1.1874 2022/10/10 04:49:49 - mmengine - INFO - Epoch(train) [52][580/940] lr: 1.0000e-03 eta: 6:24:15 time: 0.5133 data_time: 0.0244 memory: 21547 grad_norm: 4.1945 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2610 loss: 1.2610 2022/10/10 04:49:59 - mmengine - INFO - Epoch(train) [52][600/940] lr: 1.0000e-03 eta: 6:24:04 time: 0.4918 data_time: 0.0274 memory: 21547 grad_norm: 4.2938 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3210 loss: 1.3210 2022/10/10 04:50:09 - mmengine - INFO - Epoch(train) [52][620/940] lr: 1.0000e-03 eta: 6:23:55 time: 0.5336 data_time: 0.0292 memory: 21547 grad_norm: 4.2924 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2523 loss: 1.2523 2022/10/10 04:50:19 - mmengine - INFO - Epoch(train) [52][640/940] lr: 1.0000e-03 eta: 6:23:44 time: 0.4969 data_time: 0.0344 memory: 21547 grad_norm: 4.3175 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.2747 loss: 1.2747 2022/10/10 04:50:30 - mmengine - INFO - Epoch(train) [52][660/940] lr: 1.0000e-03 eta: 6:23:34 time: 0.5191 data_time: 0.0276 memory: 21547 grad_norm: 4.3532 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4198 loss: 1.4198 2022/10/10 04:50:39 - mmengine - INFO - Epoch(train) [52][680/940] lr: 1.0000e-03 eta: 6:23:24 time: 0.4840 data_time: 0.0331 memory: 21547 grad_norm: 4.3567 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4367 loss: 1.4367 2022/10/10 04:50:50 - mmengine - INFO - Epoch(train) [52][700/940] lr: 1.0000e-03 eta: 6:23:14 time: 0.5225 data_time: 0.0273 memory: 21547 grad_norm: 4.2683 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3425 loss: 1.3425 2022/10/10 04:51:00 - mmengine - INFO - Epoch(train) [52][720/940] lr: 1.0000e-03 eta: 6:23:04 time: 0.5100 data_time: 0.0299 memory: 21547 grad_norm: 4.3427 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3303 loss: 1.3303 2022/10/10 04:51:10 - mmengine - INFO - Epoch(train) [52][740/940] lr: 1.0000e-03 eta: 6:22:53 time: 0.4783 data_time: 0.0267 memory: 21547 grad_norm: 4.3810 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.1919 loss: 1.1919 2022/10/10 04:51:19 - mmengine - INFO - Epoch(train) [52][760/940] lr: 1.0000e-03 eta: 6:22:43 time: 0.4871 data_time: 0.0299 memory: 21547 grad_norm: 4.3131 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.3182 loss: 1.3182 2022/10/10 04:51:30 - mmengine - INFO - Epoch(train) [52][780/940] lr: 1.0000e-03 eta: 6:22:33 time: 0.5181 data_time: 0.0319 memory: 21547 grad_norm: 4.4416 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1885 loss: 1.1885 2022/10/10 04:51:40 - mmengine - INFO - Epoch(train) [52][800/940] lr: 1.0000e-03 eta: 6:22:22 time: 0.4985 data_time: 0.0291 memory: 21547 grad_norm: 4.3681 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2885 loss: 1.2885 2022/10/10 04:51:50 - mmengine - INFO - Epoch(train) [52][820/940] lr: 1.0000e-03 eta: 6:22:13 time: 0.5316 data_time: 0.0308 memory: 21547 grad_norm: 4.2788 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3430 loss: 1.3430 2022/10/10 04:52:00 - mmengine - INFO - Epoch(train) [52][840/940] lr: 1.0000e-03 eta: 6:22:02 time: 0.4936 data_time: 0.0255 memory: 21547 grad_norm: 4.2755 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3474 loss: 1.3474 2022/10/10 04:52:10 - mmengine - INFO - Epoch(train) [52][860/940] lr: 1.0000e-03 eta: 6:21:52 time: 0.4971 data_time: 0.0241 memory: 21547 grad_norm: 4.3018 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4602 loss: 1.4602 2022/10/10 04:52:20 - mmengine - INFO - Epoch(train) [52][880/940] lr: 1.0000e-03 eta: 6:21:42 time: 0.5124 data_time: 0.0247 memory: 21547 grad_norm: 4.3436 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3072 loss: 1.3072 2022/10/10 04:52:31 - mmengine - INFO - Epoch(train) [52][900/940] lr: 1.0000e-03 eta: 6:21:32 time: 0.5220 data_time: 0.0318 memory: 21547 grad_norm: 4.2601 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3971 loss: 1.3971 2022/10/10 04:52:41 - mmengine - INFO - Epoch(train) [52][920/940] lr: 1.0000e-03 eta: 6:21:22 time: 0.5010 data_time: 0.0232 memory: 21547 grad_norm: 4.4076 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2516 loss: 1.2516 2022/10/10 04:52:50 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 04:52:50 - mmengine - INFO - Epoch(train) [52][940/940] lr: 1.0000e-03 eta: 6:21:11 time: 0.4503 data_time: 0.0236 memory: 21547 grad_norm: 4.5170 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.2818 loss: 1.2818 2022/10/10 04:53:02 - mmengine - INFO - Epoch(val) [52][20/78] eta: 0:00:35 time: 0.6063 data_time: 0.4990 memory: 3269 2022/10/10 04:53:10 - mmengine - INFO - Epoch(val) [52][40/78] eta: 0:00:16 time: 0.4236 data_time: 0.3159 memory: 3269 2022/10/10 04:53:21 - mmengine - INFO - Epoch(val) [52][60/78] eta: 0:00:09 time: 0.5478 data_time: 0.4416 memory: 3269 2022/10/10 04:53:31 - mmengine - INFO - Epoch(val) [52][78/78] acc/top1: 0.6720 acc/top5: 0.8692 acc/mean1: 0.6719 2022/10/10 04:53:46 - mmengine - INFO - Epoch(train) [53][20/940] lr: 1.0000e-03 eta: 6:21:04 time: 0.7193 data_time: 0.2137 memory: 21547 grad_norm: 4.1936 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3305 loss: 1.3305 2022/10/10 04:53:56 - mmengine - INFO - Epoch(train) [53][40/940] lr: 1.0000e-03 eta: 6:20:54 time: 0.5080 data_time: 0.0240 memory: 21547 grad_norm: 4.2367 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2939 loss: 1.2939 2022/10/10 04:54:07 - mmengine - INFO - Epoch(train) [53][60/940] lr: 1.0000e-03 eta: 6:20:45 time: 0.5388 data_time: 0.0328 memory: 21547 grad_norm: 4.3512 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3242 loss: 1.3242 2022/10/10 04:54:17 - mmengine - INFO - Epoch(train) [53][80/940] lr: 1.0000e-03 eta: 6:20:34 time: 0.4885 data_time: 0.0246 memory: 21547 grad_norm: 4.2711 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2967 loss: 1.2967 2022/10/10 04:54:27 - mmengine - INFO - Epoch(train) [53][100/940] lr: 1.0000e-03 eta: 6:20:24 time: 0.5140 data_time: 0.0775 memory: 21547 grad_norm: 4.2924 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1657 loss: 1.1657 2022/10/10 04:54:36 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 04:54:36 - mmengine - INFO - Epoch(train) [53][120/940] lr: 1.0000e-03 eta: 6:20:13 time: 0.4672 data_time: 0.0574 memory: 21547 grad_norm: 4.3815 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3241 loss: 1.3241 2022/10/10 04:54:47 - mmengine - INFO - Epoch(train) [53][140/940] lr: 1.0000e-03 eta: 6:20:04 time: 0.5436 data_time: 0.1459 memory: 21547 grad_norm: 4.2576 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4192 loss: 1.4192 2022/10/10 04:54:56 - mmengine - INFO - Epoch(train) [53][160/940] lr: 1.0000e-03 eta: 6:19:53 time: 0.4435 data_time: 0.0594 memory: 21547 grad_norm: 4.2969 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2361 loss: 1.2361 2022/10/10 04:55:06 - mmengine - INFO - Epoch(train) [53][180/940] lr: 1.0000e-03 eta: 6:19:43 time: 0.5101 data_time: 0.1079 memory: 21547 grad_norm: 4.2460 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2946 loss: 1.2946 2022/10/10 04:55:16 - mmengine - INFO - Epoch(train) [53][200/940] lr: 1.0000e-03 eta: 6:19:32 time: 0.4775 data_time: 0.0766 memory: 21547 grad_norm: 4.3132 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2522 loss: 1.2522 2022/10/10 04:55:27 - mmengine - INFO - Epoch(train) [53][220/940] lr: 1.0000e-03 eta: 6:19:23 time: 0.5550 data_time: 0.0308 memory: 21547 grad_norm: 4.2902 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4176 loss: 1.4176 2022/10/10 04:55:36 - mmengine - INFO - Epoch(train) [53][240/940] lr: 1.0000e-03 eta: 6:19:12 time: 0.4689 data_time: 0.0294 memory: 21547 grad_norm: 4.3391 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3558 loss: 1.3558 2022/10/10 04:55:47 - mmengine - INFO - Epoch(train) [53][260/940] lr: 1.0000e-03 eta: 6:19:02 time: 0.5183 data_time: 0.0300 memory: 21547 grad_norm: 4.2754 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1952 loss: 1.1952 2022/10/10 04:55:56 - mmengine - INFO - Epoch(train) [53][280/940] lr: 1.0000e-03 eta: 6:18:51 time: 0.4742 data_time: 0.0302 memory: 21547 grad_norm: 4.2947 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3583 loss: 1.3583 2022/10/10 04:56:07 - mmengine - INFO - Epoch(train) [53][300/940] lr: 1.0000e-03 eta: 6:18:42 time: 0.5716 data_time: 0.0239 memory: 21547 grad_norm: 4.2992 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2288 loss: 1.2288 2022/10/10 04:56:17 - mmengine - INFO - Epoch(train) [53][320/940] lr: 1.0000e-03 eta: 6:18:31 time: 0.4657 data_time: 0.0310 memory: 21547 grad_norm: 4.3268 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2289 loss: 1.2289 2022/10/10 04:56:27 - mmengine - INFO - Epoch(train) [53][340/940] lr: 1.0000e-03 eta: 6:18:21 time: 0.5035 data_time: 0.0276 memory: 21547 grad_norm: 4.2688 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3059 loss: 1.3059 2022/10/10 04:56:37 - mmengine - INFO - Epoch(train) [53][360/940] lr: 1.0000e-03 eta: 6:18:11 time: 0.5039 data_time: 0.0307 memory: 21547 grad_norm: 4.3808 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1333 loss: 1.1333 2022/10/10 04:56:46 - mmengine - INFO - Epoch(train) [53][380/940] lr: 1.0000e-03 eta: 6:18:00 time: 0.4801 data_time: 0.0261 memory: 21547 grad_norm: 4.3054 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2205 loss: 1.2205 2022/10/10 04:56:56 - mmengine - INFO - Epoch(train) [53][400/940] lr: 1.0000e-03 eta: 6:17:50 time: 0.4795 data_time: 0.0297 memory: 21547 grad_norm: 4.4408 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3766 loss: 1.3766 2022/10/10 04:57:07 - mmengine - INFO - Epoch(train) [53][420/940] lr: 1.0000e-03 eta: 6:17:40 time: 0.5500 data_time: 0.0419 memory: 21547 grad_norm: 4.2952 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2959 loss: 1.2959 2022/10/10 04:57:16 - mmengine - INFO - Epoch(train) [53][440/940] lr: 1.0000e-03 eta: 6:17:29 time: 0.4690 data_time: 0.0442 memory: 21547 grad_norm: 4.2570 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2951 loss: 1.2951 2022/10/10 04:57:27 - mmengine - INFO - Epoch(train) [53][460/940] lr: 1.0000e-03 eta: 6:17:20 time: 0.5306 data_time: 0.0245 memory: 21547 grad_norm: 4.2419 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1962 loss: 1.1962 2022/10/10 04:57:37 - mmengine - INFO - Epoch(train) [53][480/940] lr: 1.0000e-03 eta: 6:17:09 time: 0.4934 data_time: 0.0681 memory: 21547 grad_norm: 4.3841 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2813 loss: 1.2813 2022/10/10 04:57:47 - mmengine - INFO - Epoch(train) [53][500/940] lr: 1.0000e-03 eta: 6:16:59 time: 0.5011 data_time: 0.0384 memory: 21547 grad_norm: 4.2717 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1449 loss: 1.1449 2022/10/10 04:57:58 - mmengine - INFO - Epoch(train) [53][520/940] lr: 1.0000e-03 eta: 6:16:49 time: 0.5299 data_time: 0.0316 memory: 21547 grad_norm: 4.3870 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3686 loss: 1.3686 2022/10/10 04:58:08 - mmengine - INFO - Epoch(train) [53][540/940] lr: 1.0000e-03 eta: 6:16:39 time: 0.5133 data_time: 0.0226 memory: 21547 grad_norm: 4.3614 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3241 loss: 1.3241 2022/10/10 04:58:17 - mmengine - INFO - Epoch(train) [53][560/940] lr: 1.0000e-03 eta: 6:16:29 time: 0.4770 data_time: 0.0292 memory: 21547 grad_norm: 4.1677 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2666 loss: 1.2666 2022/10/10 04:58:28 - mmengine - INFO - Epoch(train) [53][580/940] lr: 1.0000e-03 eta: 6:16:19 time: 0.5498 data_time: 0.0264 memory: 21547 grad_norm: 4.3473 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1844 loss: 1.1844 2022/10/10 04:58:38 - mmengine - INFO - Epoch(train) [53][600/940] lr: 1.0000e-03 eta: 6:16:09 time: 0.5043 data_time: 0.0279 memory: 21547 grad_norm: 4.3687 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3531 loss: 1.3531 2022/10/10 04:58:50 - mmengine - INFO - Epoch(train) [53][620/940] lr: 1.0000e-03 eta: 6:16:00 time: 0.5524 data_time: 0.0248 memory: 21547 grad_norm: 4.3862 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3248 loss: 1.3248 2022/10/10 04:59:00 - mmengine - INFO - Epoch(train) [53][640/940] lr: 1.0000e-03 eta: 6:15:50 time: 0.5205 data_time: 0.0221 memory: 21547 grad_norm: 4.3592 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4127 loss: 1.4127 2022/10/10 04:59:09 - mmengine - INFO - Epoch(train) [53][660/940] lr: 1.0000e-03 eta: 6:15:39 time: 0.4506 data_time: 0.0252 memory: 21547 grad_norm: 4.3232 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2839 loss: 1.2839 2022/10/10 04:59:19 - mmengine - INFO - Epoch(train) [53][680/940] lr: 1.0000e-03 eta: 6:15:28 time: 0.4931 data_time: 0.0280 memory: 21547 grad_norm: 4.4235 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3131 loss: 1.3131 2022/10/10 04:59:29 - mmengine - INFO - Epoch(train) [53][700/940] lr: 1.0000e-03 eta: 6:15:19 time: 0.5325 data_time: 0.0339 memory: 21547 grad_norm: 4.2507 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1871 loss: 1.1871 2022/10/10 04:59:39 - mmengine - INFO - Epoch(train) [53][720/940] lr: 1.0000e-03 eta: 6:15:08 time: 0.4847 data_time: 0.0267 memory: 21547 grad_norm: 4.4315 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3929 loss: 1.3929 2022/10/10 04:59:49 - mmengine - INFO - Epoch(train) [53][740/940] lr: 1.0000e-03 eta: 6:14:58 time: 0.5166 data_time: 0.0308 memory: 21547 grad_norm: 4.2690 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2436 loss: 1.2436 2022/10/10 05:00:00 - mmengine - INFO - Epoch(train) [53][760/940] lr: 1.0000e-03 eta: 6:14:48 time: 0.5227 data_time: 0.0260 memory: 21547 grad_norm: 4.3145 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3125 loss: 1.3125 2022/10/10 05:00:11 - mmengine - INFO - Epoch(train) [53][780/940] lr: 1.0000e-03 eta: 6:14:39 time: 0.5323 data_time: 0.0299 memory: 21547 grad_norm: 4.3514 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.2655 loss: 1.2655 2022/10/10 05:00:20 - mmengine - INFO - Epoch(train) [53][800/940] lr: 1.0000e-03 eta: 6:14:28 time: 0.4902 data_time: 0.0269 memory: 21547 grad_norm: 4.3413 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2774 loss: 1.2774 2022/10/10 05:00:30 - mmengine - INFO - Epoch(train) [53][820/940] lr: 1.0000e-03 eta: 6:14:18 time: 0.4927 data_time: 0.0263 memory: 21547 grad_norm: 4.3245 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3250 loss: 1.3250 2022/10/10 05:00:40 - mmengine - INFO - Epoch(train) [53][840/940] lr: 1.0000e-03 eta: 6:14:07 time: 0.4961 data_time: 0.0289 memory: 21547 grad_norm: 4.3294 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3486 loss: 1.3486 2022/10/10 05:00:51 - mmengine - INFO - Epoch(train) [53][860/940] lr: 1.0000e-03 eta: 6:13:58 time: 0.5410 data_time: 0.0275 memory: 21547 grad_norm: 4.2732 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2201 loss: 1.2201 2022/10/10 05:01:00 - mmengine - INFO - Epoch(train) [53][880/940] lr: 1.0000e-03 eta: 6:13:47 time: 0.4558 data_time: 0.0247 memory: 21547 grad_norm: 4.3296 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2650 loss: 1.2650 2022/10/10 05:01:10 - mmengine - INFO - Epoch(train) [53][900/940] lr: 1.0000e-03 eta: 6:13:36 time: 0.4892 data_time: 0.0241 memory: 21547 grad_norm: 4.2903 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2366 loss: 1.2366 2022/10/10 05:01:19 - mmengine - INFO - Epoch(train) [53][920/940] lr: 1.0000e-03 eta: 6:13:25 time: 0.4492 data_time: 0.0238 memory: 21547 grad_norm: 4.4103 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3758 loss: 1.3758 2022/10/10 05:01:28 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 05:01:28 - mmengine - INFO - Epoch(train) [53][940/940] lr: 1.0000e-03 eta: 6:13:15 time: 0.4740 data_time: 0.0246 memory: 21547 grad_norm: 4.5607 top1_acc: 0.4286 top5_acc: 1.0000 loss_cls: 1.2182 loss: 1.2182 2022/10/10 05:01:40 - mmengine - INFO - Epoch(val) [53][20/78] eta: 0:00:35 time: 0.6044 data_time: 0.4959 memory: 3269 2022/10/10 05:01:49 - mmengine - INFO - Epoch(val) [53][40/78] eta: 0:00:16 time: 0.4216 data_time: 0.3128 memory: 3269 2022/10/10 05:02:00 - mmengine - INFO - Epoch(val) [53][60/78] eta: 0:00:10 time: 0.5566 data_time: 0.4493 memory: 3269 2022/10/10 05:02:11 - mmengine - INFO - Epoch(val) [53][78/78] acc/top1: 0.6760 acc/top5: 0.8712 acc/mean1: 0.6760 2022/10/10 05:02:24 - mmengine - INFO - Epoch(train) [54][20/940] lr: 1.0000e-03 eta: 6:13:08 time: 0.6909 data_time: 0.2205 memory: 21547 grad_norm: 4.2808 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2132 loss: 1.2132 2022/10/10 05:02:34 - mmengine - INFO - Epoch(train) [54][40/940] lr: 1.0000e-03 eta: 6:12:57 time: 0.4913 data_time: 0.0249 memory: 21547 grad_norm: 4.3333 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2887 loss: 1.2887 2022/10/10 05:02:45 - mmengine - INFO - Epoch(train) [54][60/940] lr: 1.0000e-03 eta: 6:12:48 time: 0.5423 data_time: 0.0772 memory: 21547 grad_norm: 4.3453 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2572 loss: 1.2572 2022/10/10 05:02:55 - mmengine - INFO - Epoch(train) [54][80/940] lr: 1.0000e-03 eta: 6:12:37 time: 0.5002 data_time: 0.0505 memory: 21547 grad_norm: 4.2966 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2945 loss: 1.2945 2022/10/10 05:03:06 - mmengine - INFO - Epoch(train) [54][100/940] lr: 1.0000e-03 eta: 6:12:28 time: 0.5684 data_time: 0.0257 memory: 21547 grad_norm: 4.3002 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2820 loss: 1.2820 2022/10/10 05:03:16 - mmengine - INFO - Epoch(train) [54][120/940] lr: 1.0000e-03 eta: 6:12:17 time: 0.4556 data_time: 0.0260 memory: 21547 grad_norm: 4.2846 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2525 loss: 1.2525 2022/10/10 05:03:26 - mmengine - INFO - Epoch(train) [54][140/940] lr: 1.0000e-03 eta: 6:12:08 time: 0.5361 data_time: 0.0276 memory: 21547 grad_norm: 4.3546 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.2965 loss: 1.2965 2022/10/10 05:03:36 - mmengine - INFO - Epoch(train) [54][160/940] lr: 1.0000e-03 eta: 6:11:57 time: 0.4900 data_time: 0.0243 memory: 21547 grad_norm: 4.3131 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3136 loss: 1.3136 2022/10/10 05:03:47 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 05:03:47 - mmengine - INFO - Epoch(train) [54][180/940] lr: 1.0000e-03 eta: 6:11:47 time: 0.5265 data_time: 0.0331 memory: 21547 grad_norm: 4.3836 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2732 loss: 1.2732 2022/10/10 05:03:57 - mmengine - INFO - Epoch(train) [54][200/940] lr: 1.0000e-03 eta: 6:11:37 time: 0.4975 data_time: 0.0250 memory: 21547 grad_norm: 4.1888 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3353 loss: 1.3353 2022/10/10 05:04:07 - mmengine - INFO - Epoch(train) [54][220/940] lr: 1.0000e-03 eta: 6:11:27 time: 0.5309 data_time: 0.0335 memory: 21547 grad_norm: 4.3126 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3623 loss: 1.3623 2022/10/10 05:04:16 - mmengine - INFO - Epoch(train) [54][240/940] lr: 1.0000e-03 eta: 6:11:16 time: 0.4532 data_time: 0.0272 memory: 21547 grad_norm: 4.2958 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.2932 loss: 1.2932 2022/10/10 05:04:26 - mmengine - INFO - Epoch(train) [54][260/940] lr: 1.0000e-03 eta: 6:11:06 time: 0.4824 data_time: 0.0292 memory: 21547 grad_norm: 4.2827 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2692 loss: 1.2692 2022/10/10 05:04:36 - mmengine - INFO - Epoch(train) [54][280/940] lr: 1.0000e-03 eta: 6:10:56 time: 0.5001 data_time: 0.0280 memory: 21547 grad_norm: 4.3383 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3593 loss: 1.3593 2022/10/10 05:04:47 - mmengine - INFO - Epoch(train) [54][300/940] lr: 1.0000e-03 eta: 6:10:46 time: 0.5396 data_time: 0.0323 memory: 21547 grad_norm: 4.2525 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.4117 loss: 1.4117 2022/10/10 05:04:56 - mmengine - INFO - Epoch(train) [54][320/940] lr: 1.0000e-03 eta: 6:10:36 time: 0.4886 data_time: 0.0254 memory: 21547 grad_norm: 4.2089 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2515 loss: 1.2515 2022/10/10 05:05:06 - mmengine - INFO - Epoch(train) [54][340/940] lr: 1.0000e-03 eta: 6:10:25 time: 0.4971 data_time: 0.0281 memory: 21547 grad_norm: 4.3245 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4323 loss: 1.4323 2022/10/10 05:05:17 - mmengine - INFO - Epoch(train) [54][360/940] lr: 1.0000e-03 eta: 6:10:16 time: 0.5406 data_time: 0.0315 memory: 21547 grad_norm: 4.3588 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3721 loss: 1.3721 2022/10/10 05:05:27 - mmengine - INFO - Epoch(train) [54][380/940] lr: 1.0000e-03 eta: 6:10:05 time: 0.4692 data_time: 0.0275 memory: 21547 grad_norm: 4.3643 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3959 loss: 1.3959 2022/10/10 05:05:36 - mmengine - INFO - Epoch(train) [54][400/940] lr: 1.0000e-03 eta: 6:09:54 time: 0.4848 data_time: 0.0285 memory: 21547 grad_norm: 4.2927 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2573 loss: 1.2573 2022/10/10 05:05:47 - mmengine - INFO - Epoch(train) [54][420/940] lr: 1.0000e-03 eta: 6:09:45 time: 0.5505 data_time: 0.0304 memory: 21547 grad_norm: 4.3184 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1834 loss: 1.1834 2022/10/10 05:05:58 - mmengine - INFO - Epoch(train) [54][440/940] lr: 1.0000e-03 eta: 6:09:35 time: 0.5168 data_time: 0.0300 memory: 21547 grad_norm: 4.2833 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1131 loss: 1.1131 2022/10/10 05:06:08 - mmengine - INFO - Epoch(train) [54][460/940] lr: 1.0000e-03 eta: 6:09:25 time: 0.4963 data_time: 0.0270 memory: 21547 grad_norm: 4.2386 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3336 loss: 1.3336 2022/10/10 05:06:17 - mmengine - INFO - Epoch(train) [54][480/940] lr: 1.0000e-03 eta: 6:09:14 time: 0.4837 data_time: 0.0268 memory: 21547 grad_norm: 4.2342 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1971 loss: 1.1971 2022/10/10 05:06:27 - mmengine - INFO - Epoch(train) [54][500/940] lr: 1.0000e-03 eta: 6:09:04 time: 0.5060 data_time: 0.0247 memory: 21547 grad_norm: 4.3065 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3558 loss: 1.3558 2022/10/10 05:06:37 - mmengine - INFO - Epoch(train) [54][520/940] lr: 1.0000e-03 eta: 6:08:54 time: 0.4955 data_time: 0.0288 memory: 21547 grad_norm: 4.3569 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.3533 loss: 1.3533 2022/10/10 05:06:47 - mmengine - INFO - Epoch(train) [54][540/940] lr: 1.0000e-03 eta: 6:08:43 time: 0.5020 data_time: 0.0277 memory: 21547 grad_norm: 4.3554 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3144 loss: 1.3144 2022/10/10 05:06:57 - mmengine - INFO - Epoch(train) [54][560/940] lr: 1.0000e-03 eta: 6:08:33 time: 0.4951 data_time: 0.0274 memory: 21547 grad_norm: 4.3515 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3411 loss: 1.3411 2022/10/10 05:07:08 - mmengine - INFO - Epoch(train) [54][580/940] lr: 1.0000e-03 eta: 6:08:23 time: 0.5294 data_time: 0.0258 memory: 21547 grad_norm: 4.2804 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3303 loss: 1.3303 2022/10/10 05:07:18 - mmengine - INFO - Epoch(train) [54][600/940] lr: 1.0000e-03 eta: 6:08:13 time: 0.4922 data_time: 0.0307 memory: 21547 grad_norm: 4.3238 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4194 loss: 1.4194 2022/10/10 05:07:29 - mmengine - INFO - Epoch(train) [54][620/940] lr: 1.0000e-03 eta: 6:08:04 time: 0.5526 data_time: 0.0303 memory: 21547 grad_norm: 4.2901 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3191 loss: 1.3191 2022/10/10 05:07:38 - mmengine - INFO - Epoch(train) [54][640/940] lr: 1.0000e-03 eta: 6:07:53 time: 0.4747 data_time: 0.0244 memory: 21547 grad_norm: 4.2649 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1223 loss: 1.1223 2022/10/10 05:07:49 - mmengine - INFO - Epoch(train) [54][660/940] lr: 1.0000e-03 eta: 6:07:43 time: 0.5401 data_time: 0.0327 memory: 21547 grad_norm: 4.2928 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3734 loss: 1.3734 2022/10/10 05:07:58 - mmengine - INFO - Epoch(train) [54][680/940] lr: 1.0000e-03 eta: 6:07:32 time: 0.4650 data_time: 0.0241 memory: 21547 grad_norm: 4.3060 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1593 loss: 1.1593 2022/10/10 05:08:09 - mmengine - INFO - Epoch(train) [54][700/940] lr: 1.0000e-03 eta: 6:07:22 time: 0.5169 data_time: 0.0254 memory: 21547 grad_norm: 4.3618 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1932 loss: 1.1932 2022/10/10 05:08:18 - mmengine - INFO - Epoch(train) [54][720/940] lr: 1.0000e-03 eta: 6:07:12 time: 0.4695 data_time: 0.0267 memory: 21547 grad_norm: 4.2910 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2586 loss: 1.2586 2022/10/10 05:08:28 - mmengine - INFO - Epoch(train) [54][740/940] lr: 1.0000e-03 eta: 6:07:01 time: 0.4708 data_time: 0.0302 memory: 21547 grad_norm: 4.3762 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2167 loss: 1.2167 2022/10/10 05:08:38 - mmengine - INFO - Epoch(train) [54][760/940] lr: 1.0000e-03 eta: 6:06:51 time: 0.5051 data_time: 0.0321 memory: 21547 grad_norm: 4.3547 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4316 loss: 1.4316 2022/10/10 05:08:50 - mmengine - INFO - Epoch(train) [54][780/940] lr: 1.0000e-03 eta: 6:06:43 time: 0.6284 data_time: 0.0236 memory: 21547 grad_norm: 4.2944 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2092 loss: 1.2092 2022/10/10 05:09:00 - mmengine - INFO - Epoch(train) [54][800/940] lr: 1.0000e-03 eta: 6:06:33 time: 0.5117 data_time: 0.0241 memory: 21547 grad_norm: 4.3689 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2714 loss: 1.2714 2022/10/10 05:09:10 - mmengine - INFO - Epoch(train) [54][820/940] lr: 1.0000e-03 eta: 6:06:22 time: 0.5002 data_time: 0.0277 memory: 21547 grad_norm: 4.3226 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3145 loss: 1.3145 2022/10/10 05:09:20 - mmengine - INFO - Epoch(train) [54][840/940] lr: 1.0000e-03 eta: 6:06:12 time: 0.5018 data_time: 0.0295 memory: 21547 grad_norm: 4.2635 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1561 loss: 1.1561 2022/10/10 05:09:30 - mmengine - INFO - Epoch(train) [54][860/940] lr: 1.0000e-03 eta: 6:06:02 time: 0.4852 data_time: 0.0233 memory: 21547 grad_norm: 4.5211 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.3047 loss: 1.3047 2022/10/10 05:09:40 - mmengine - INFO - Epoch(train) [54][880/940] lr: 1.0000e-03 eta: 6:05:51 time: 0.4898 data_time: 0.0323 memory: 21547 grad_norm: 4.3485 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1616 loss: 1.1616 2022/10/10 05:09:50 - mmengine - INFO - Epoch(train) [54][900/940] lr: 1.0000e-03 eta: 6:05:41 time: 0.4981 data_time: 0.0244 memory: 21547 grad_norm: 4.3570 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3060 loss: 1.3060 2022/10/10 05:10:00 - mmengine - INFO - Epoch(train) [54][920/940] lr: 1.0000e-03 eta: 6:05:31 time: 0.5199 data_time: 0.0295 memory: 21547 grad_norm: 4.3181 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2586 loss: 1.2586 2022/10/10 05:10:09 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 05:10:09 - mmengine - INFO - Epoch(train) [54][940/940] lr: 1.0000e-03 eta: 6:05:20 time: 0.4467 data_time: 0.0241 memory: 21547 grad_norm: 4.6866 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.2956 loss: 1.2956 2022/10/10 05:10:09 - mmengine - INFO - Saving checkpoint at 54 epochs 2022/10/10 05:10:22 - mmengine - INFO - Epoch(val) [54][20/78] eta: 0:00:35 time: 0.6110 data_time: 0.5054 memory: 3269 2022/10/10 05:10:31 - mmengine - INFO - Epoch(val) [54][40/78] eta: 0:00:15 time: 0.4209 data_time: 0.3165 memory: 3269 2022/10/10 05:10:42 - mmengine - INFO - Epoch(val) [54][60/78] eta: 0:00:10 time: 0.5602 data_time: 0.4542 memory: 3269 2022/10/10 05:10:51 - mmengine - INFO - Epoch(val) [54][78/78] acc/top1: 0.6766 acc/top5: 0.8720 acc/mean1: 0.6764 2022/10/10 05:11:05 - mmengine - INFO - Epoch(train) [55][20/940] lr: 1.0000e-03 eta: 6:05:13 time: 0.6881 data_time: 0.1810 memory: 21547 grad_norm: 4.2822 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2927 loss: 1.2927 2022/10/10 05:11:14 - mmengine - INFO - Epoch(train) [55][40/940] lr: 1.0000e-03 eta: 6:05:02 time: 0.4844 data_time: 0.0260 memory: 21547 grad_norm: 4.2111 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2408 loss: 1.2408 2022/10/10 05:11:25 - mmengine - INFO - Epoch(train) [55][60/940] lr: 1.0000e-03 eta: 6:04:53 time: 0.5361 data_time: 0.0347 memory: 21547 grad_norm: 4.3546 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2301 loss: 1.2301 2022/10/10 05:11:35 - mmengine - INFO - Epoch(train) [55][80/940] lr: 1.0000e-03 eta: 6:04:42 time: 0.4729 data_time: 0.0229 memory: 21547 grad_norm: 4.1992 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2614 loss: 1.2614 2022/10/10 05:11:45 - mmengine - INFO - Epoch(train) [55][100/940] lr: 1.0000e-03 eta: 6:04:32 time: 0.5296 data_time: 0.0335 memory: 21547 grad_norm: 4.3805 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1360 loss: 1.1360 2022/10/10 05:11:55 - mmengine - INFO - Epoch(train) [55][120/940] lr: 1.0000e-03 eta: 6:04:22 time: 0.4839 data_time: 0.0299 memory: 21547 grad_norm: 4.1946 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2401 loss: 1.2401 2022/10/10 05:12:06 - mmengine - INFO - Epoch(train) [55][140/940] lr: 1.0000e-03 eta: 6:04:12 time: 0.5314 data_time: 0.0328 memory: 21547 grad_norm: 4.3102 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.2319 loss: 1.2319 2022/10/10 05:12:15 - mmengine - INFO - Epoch(train) [55][160/940] lr: 1.0000e-03 eta: 6:04:01 time: 0.4910 data_time: 0.0247 memory: 21547 grad_norm: 4.5301 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2072 loss: 1.2072 2022/10/10 05:12:26 - mmengine - INFO - Epoch(train) [55][180/940] lr: 1.0000e-03 eta: 6:03:52 time: 0.5461 data_time: 0.0269 memory: 21547 grad_norm: 4.3888 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3766 loss: 1.3766 2022/10/10 05:12:36 - mmengine - INFO - Epoch(train) [55][200/940] lr: 1.0000e-03 eta: 6:03:41 time: 0.4848 data_time: 0.0267 memory: 21547 grad_norm: 4.3333 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2356 loss: 1.2356 2022/10/10 05:12:46 - mmengine - INFO - Epoch(train) [55][220/940] lr: 1.0000e-03 eta: 6:03:32 time: 0.5229 data_time: 0.0271 memory: 21547 grad_norm: 4.4257 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.2950 loss: 1.2950 2022/10/10 05:12:56 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 05:12:56 - mmengine - INFO - Epoch(train) [55][240/940] lr: 1.0000e-03 eta: 6:03:21 time: 0.4622 data_time: 0.0274 memory: 21547 grad_norm: 4.3161 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3177 loss: 1.3177 2022/10/10 05:13:06 - mmengine - INFO - Epoch(train) [55][260/940] lr: 1.0000e-03 eta: 6:03:11 time: 0.5298 data_time: 0.0299 memory: 21547 grad_norm: 4.3617 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3615 loss: 1.3615 2022/10/10 05:13:16 - mmengine - INFO - Epoch(train) [55][280/940] lr: 1.0000e-03 eta: 6:03:00 time: 0.4815 data_time: 0.0288 memory: 21547 grad_norm: 4.3448 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1797 loss: 1.1797 2022/10/10 05:13:26 - mmengine - INFO - Epoch(train) [55][300/940] lr: 1.0000e-03 eta: 6:02:50 time: 0.4873 data_time: 0.0256 memory: 21547 grad_norm: 4.3301 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2139 loss: 1.2139 2022/10/10 05:13:36 - mmengine - INFO - Epoch(train) [55][320/940] lr: 1.0000e-03 eta: 6:02:40 time: 0.5093 data_time: 0.0240 memory: 21547 grad_norm: 4.3460 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3097 loss: 1.3097 2022/10/10 05:13:47 - mmengine - INFO - Epoch(train) [55][340/940] lr: 1.0000e-03 eta: 6:02:30 time: 0.5434 data_time: 0.0250 memory: 21547 grad_norm: 4.2811 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2458 loss: 1.2458 2022/10/10 05:13:56 - mmengine - INFO - Epoch(train) [55][360/940] lr: 1.0000e-03 eta: 6:02:20 time: 0.4800 data_time: 0.0235 memory: 21547 grad_norm: 4.3649 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3055 loss: 1.3055 2022/10/10 05:14:06 - mmengine - INFO - Epoch(train) [55][380/940] lr: 1.0000e-03 eta: 6:02:09 time: 0.4843 data_time: 0.0254 memory: 21547 grad_norm: 4.4392 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2406 loss: 1.2406 2022/10/10 05:14:16 - mmengine - INFO - Epoch(train) [55][400/940] lr: 1.0000e-03 eta: 6:01:59 time: 0.5059 data_time: 0.0302 memory: 21547 grad_norm: 4.3421 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2552 loss: 1.2552 2022/10/10 05:14:27 - mmengine - INFO - Epoch(train) [55][420/940] lr: 1.0000e-03 eta: 6:01:49 time: 0.5461 data_time: 0.0377 memory: 21547 grad_norm: 4.3181 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3464 loss: 1.3464 2022/10/10 05:14:37 - mmengine - INFO - Epoch(train) [55][440/940] lr: 1.0000e-03 eta: 6:01:39 time: 0.5061 data_time: 0.0287 memory: 21547 grad_norm: 4.4390 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3094 loss: 1.3094 2022/10/10 05:14:47 - mmengine - INFO - Epoch(train) [55][460/940] lr: 1.0000e-03 eta: 6:01:29 time: 0.5052 data_time: 0.0231 memory: 21547 grad_norm: 4.3642 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3646 loss: 1.3646 2022/10/10 05:14:58 - mmengine - INFO - Epoch(train) [55][480/940] lr: 1.0000e-03 eta: 6:01:19 time: 0.5137 data_time: 0.0249 memory: 21547 grad_norm: 4.3346 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2661 loss: 1.2661 2022/10/10 05:15:08 - mmengine - INFO - Epoch(train) [55][500/940] lr: 1.0000e-03 eta: 6:01:09 time: 0.5019 data_time: 0.0261 memory: 21547 grad_norm: 4.3736 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2869 loss: 1.2869 2022/10/10 05:15:18 - mmengine - INFO - Epoch(train) [55][520/940] lr: 1.0000e-03 eta: 6:00:59 time: 0.4970 data_time: 0.0293 memory: 21547 grad_norm: 4.2126 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.1284 loss: 1.1284 2022/10/10 05:15:28 - mmengine - INFO - Epoch(train) [55][540/940] lr: 1.0000e-03 eta: 6:00:48 time: 0.5095 data_time: 0.0280 memory: 21547 grad_norm: 4.3764 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.2824 loss: 1.2824 2022/10/10 05:15:38 - mmengine - INFO - Epoch(train) [55][560/940] lr: 1.0000e-03 eta: 6:00:38 time: 0.4911 data_time: 0.0318 memory: 21547 grad_norm: 4.3220 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2213 loss: 1.2213 2022/10/10 05:15:47 - mmengine - INFO - Epoch(train) [55][580/940] lr: 1.0000e-03 eta: 6:00:28 time: 0.4835 data_time: 0.0253 memory: 21547 grad_norm: 4.4250 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1980 loss: 1.1980 2022/10/10 05:15:58 - mmengine - INFO - Epoch(train) [55][600/940] lr: 1.0000e-03 eta: 6:00:18 time: 0.5135 data_time: 0.0341 memory: 21547 grad_norm: 4.3515 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3502 loss: 1.3502 2022/10/10 05:16:07 - mmengine - INFO - Epoch(train) [55][620/940] lr: 1.0000e-03 eta: 6:00:07 time: 0.4985 data_time: 0.0251 memory: 21547 grad_norm: 4.2306 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.2556 loss: 1.2556 2022/10/10 05:16:17 - mmengine - INFO - Epoch(train) [55][640/940] lr: 1.0000e-03 eta: 5:59:57 time: 0.4838 data_time: 0.0291 memory: 21547 grad_norm: 4.3864 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3394 loss: 1.3394 2022/10/10 05:16:28 - mmengine - INFO - Epoch(train) [55][660/940] lr: 1.0000e-03 eta: 5:59:47 time: 0.5450 data_time: 0.0266 memory: 21547 grad_norm: 4.3039 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2767 loss: 1.2767 2022/10/10 05:16:38 - mmengine - INFO - Epoch(train) [55][680/940] lr: 1.0000e-03 eta: 5:59:37 time: 0.5085 data_time: 0.0319 memory: 21547 grad_norm: 4.2575 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1825 loss: 1.1825 2022/10/10 05:16:48 - mmengine - INFO - Epoch(train) [55][700/940] lr: 1.0000e-03 eta: 5:59:27 time: 0.4977 data_time: 0.0296 memory: 21547 grad_norm: 4.3129 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2139 loss: 1.2139 2022/10/10 05:16:59 - mmengine - INFO - Epoch(train) [55][720/940] lr: 1.0000e-03 eta: 5:59:17 time: 0.5405 data_time: 0.0269 memory: 21547 grad_norm: 4.3261 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3098 loss: 1.3098 2022/10/10 05:17:09 - mmengine - INFO - Epoch(train) [55][740/940] lr: 1.0000e-03 eta: 5:59:07 time: 0.5021 data_time: 0.0249 memory: 21547 grad_norm: 4.3721 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1768 loss: 1.1768 2022/10/10 05:17:19 - mmengine - INFO - Epoch(train) [55][760/940] lr: 1.0000e-03 eta: 5:58:56 time: 0.4771 data_time: 0.0295 memory: 21547 grad_norm: 4.4229 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4254 loss: 1.4254 2022/10/10 05:17:29 - mmengine - INFO - Epoch(train) [55][780/940] lr: 1.0000e-03 eta: 5:58:46 time: 0.5233 data_time: 0.0247 memory: 21547 grad_norm: 4.3397 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3673 loss: 1.3673 2022/10/10 05:17:39 - mmengine - INFO - Epoch(train) [55][800/940] lr: 1.0000e-03 eta: 5:58:36 time: 0.5129 data_time: 0.0276 memory: 21547 grad_norm: 4.3176 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2873 loss: 1.2873 2022/10/10 05:17:50 - mmengine - INFO - Epoch(train) [55][820/940] lr: 1.0000e-03 eta: 5:58:26 time: 0.5175 data_time: 0.0224 memory: 21547 grad_norm: 4.3724 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2806 loss: 1.2806 2022/10/10 05:18:00 - mmengine - INFO - Epoch(train) [55][840/940] lr: 1.0000e-03 eta: 5:58:16 time: 0.5154 data_time: 0.0263 memory: 21547 grad_norm: 4.3139 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1666 loss: 1.1666 2022/10/10 05:18:10 - mmengine - INFO - Epoch(train) [55][860/940] lr: 1.0000e-03 eta: 5:58:06 time: 0.5161 data_time: 0.0306 memory: 21547 grad_norm: 4.3610 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2800 loss: 1.2800 2022/10/10 05:18:20 - mmengine - INFO - Epoch(train) [55][880/940] lr: 1.0000e-03 eta: 5:57:56 time: 0.5003 data_time: 0.0252 memory: 21547 grad_norm: 4.4074 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4451 loss: 1.4451 2022/10/10 05:18:31 - mmengine - INFO - Epoch(train) [55][900/940] lr: 1.0000e-03 eta: 5:57:47 time: 0.5324 data_time: 0.0240 memory: 21547 grad_norm: 4.4054 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2947 loss: 1.2947 2022/10/10 05:18:40 - mmengine - INFO - Epoch(train) [55][920/940] lr: 1.0000e-03 eta: 5:57:35 time: 0.4304 data_time: 0.0280 memory: 21547 grad_norm: 4.2911 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1902 loss: 1.1902 2022/10/10 05:18:48 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 05:18:48 - mmengine - INFO - Epoch(train) [55][940/940] lr: 1.0000e-03 eta: 5:57:24 time: 0.4238 data_time: 0.0224 memory: 21547 grad_norm: 4.5605 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.3611 loss: 1.3611 2022/10/10 05:19:00 - mmengine - INFO - Epoch(val) [55][20/78] eta: 0:00:35 time: 0.6083 data_time: 0.4974 memory: 3269 2022/10/10 05:19:09 - mmengine - INFO - Epoch(val) [55][40/78] eta: 0:00:16 time: 0.4211 data_time: 0.3152 memory: 3269 2022/10/10 05:19:20 - mmengine - INFO - Epoch(val) [55][60/78] eta: 0:00:10 time: 0.5569 data_time: 0.4495 memory: 3269 2022/10/10 05:19:30 - mmengine - INFO - Epoch(val) [55][78/78] acc/top1: 0.6749 acc/top5: 0.8717 acc/mean1: 0.6747 2022/10/10 05:19:44 - mmengine - INFO - Epoch(train) [56][20/940] lr: 1.0000e-03 eta: 5:57:17 time: 0.7325 data_time: 0.2069 memory: 21547 grad_norm: 4.3808 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2003 loss: 1.2003 2022/10/10 05:19:53 - mmengine - INFO - Epoch(train) [56][40/940] lr: 1.0000e-03 eta: 5:57:06 time: 0.4350 data_time: 0.0248 memory: 21547 grad_norm: 4.2942 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1759 loss: 1.1759 2022/10/10 05:20:05 - mmengine - INFO - Epoch(train) [56][60/940] lr: 1.0000e-03 eta: 5:56:57 time: 0.5804 data_time: 0.0339 memory: 21547 grad_norm: 4.4281 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1831 loss: 1.1831 2022/10/10 05:20:14 - mmengine - INFO - Epoch(train) [56][80/940] lr: 1.0000e-03 eta: 5:56:46 time: 0.4676 data_time: 0.0252 memory: 21547 grad_norm: 4.3798 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2688 loss: 1.2688 2022/10/10 05:20:25 - mmengine - INFO - Epoch(train) [56][100/940] lr: 1.0000e-03 eta: 5:56:37 time: 0.5391 data_time: 0.0347 memory: 21547 grad_norm: 4.3103 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1887 loss: 1.1887 2022/10/10 05:20:34 - mmengine - INFO - Epoch(train) [56][120/940] lr: 1.0000e-03 eta: 5:56:26 time: 0.4796 data_time: 0.0284 memory: 21547 grad_norm: 4.3254 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3216 loss: 1.3216 2022/10/10 05:20:45 - mmengine - INFO - Epoch(train) [56][140/940] lr: 1.0000e-03 eta: 5:56:16 time: 0.5243 data_time: 0.0279 memory: 21547 grad_norm: 4.3988 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2859 loss: 1.2859 2022/10/10 05:20:55 - mmengine - INFO - Epoch(train) [56][160/940] lr: 1.0000e-03 eta: 5:56:06 time: 0.5023 data_time: 0.0279 memory: 21547 grad_norm: 4.4755 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2352 loss: 1.2352 2022/10/10 05:21:05 - mmengine - INFO - Epoch(train) [56][180/940] lr: 1.0000e-03 eta: 5:55:56 time: 0.5104 data_time: 0.0281 memory: 21547 grad_norm: 4.3949 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2293 loss: 1.2293 2022/10/10 05:21:15 - mmengine - INFO - Epoch(train) [56][200/940] lr: 1.0000e-03 eta: 5:55:45 time: 0.4819 data_time: 0.0270 memory: 21547 grad_norm: 4.3390 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1680 loss: 1.1680 2022/10/10 05:21:26 - mmengine - INFO - Epoch(train) [56][220/940] lr: 1.0000e-03 eta: 5:55:36 time: 0.5835 data_time: 0.0290 memory: 21547 grad_norm: 4.4025 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.2362 loss: 1.2362 2022/10/10 05:21:36 - mmengine - INFO - Epoch(train) [56][240/940] lr: 1.0000e-03 eta: 5:55:26 time: 0.4871 data_time: 0.0246 memory: 21547 grad_norm: 4.2748 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.1798 loss: 1.1798 2022/10/10 05:21:46 - mmengine - INFO - Epoch(train) [56][260/940] lr: 1.0000e-03 eta: 5:55:16 time: 0.5159 data_time: 0.0240 memory: 21547 grad_norm: 4.4144 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2931 loss: 1.2931 2022/10/10 05:21:56 - mmengine - INFO - Epoch(train) [56][280/940] lr: 1.0000e-03 eta: 5:55:05 time: 0.4797 data_time: 0.0290 memory: 21547 grad_norm: 4.2925 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1790 loss: 1.1790 2022/10/10 05:22:06 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 05:22:06 - mmengine - INFO - Epoch(train) [56][300/940] lr: 1.0000e-03 eta: 5:54:55 time: 0.5197 data_time: 0.0245 memory: 21547 grad_norm: 4.2839 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1817 loss: 1.1817 2022/10/10 05:22:16 - mmengine - INFO - Epoch(train) [56][320/940] lr: 1.0000e-03 eta: 5:54:45 time: 0.4969 data_time: 0.0286 memory: 21547 grad_norm: 4.3419 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1750 loss: 1.1750 2022/10/10 05:22:26 - mmengine - INFO - Epoch(train) [56][340/940] lr: 1.0000e-03 eta: 5:54:35 time: 0.4894 data_time: 0.0278 memory: 21547 grad_norm: 4.3328 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3390 loss: 1.3390 2022/10/10 05:22:37 - mmengine - INFO - Epoch(train) [56][360/940] lr: 1.0000e-03 eta: 5:54:25 time: 0.5298 data_time: 0.0330 memory: 21547 grad_norm: 4.3735 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2634 loss: 1.2634 2022/10/10 05:22:47 - mmengine - INFO - Epoch(train) [56][380/940] lr: 1.0000e-03 eta: 5:54:15 time: 0.5025 data_time: 0.0273 memory: 21547 grad_norm: 4.3759 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1761 loss: 1.1761 2022/10/10 05:22:57 - mmengine - INFO - Epoch(train) [56][400/940] lr: 1.0000e-03 eta: 5:54:04 time: 0.4965 data_time: 0.0283 memory: 21547 grad_norm: 4.3647 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2696 loss: 1.2696 2022/10/10 05:23:07 - mmengine - INFO - Epoch(train) [56][420/940] lr: 1.0000e-03 eta: 5:53:54 time: 0.5122 data_time: 0.0314 memory: 21547 grad_norm: 4.5103 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2787 loss: 1.2787 2022/10/10 05:23:17 - mmengine - INFO - Epoch(train) [56][440/940] lr: 1.0000e-03 eta: 5:53:44 time: 0.4915 data_time: 0.0270 memory: 21547 grad_norm: 4.4853 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3313 loss: 1.3313 2022/10/10 05:23:27 - mmengine - INFO - Epoch(train) [56][460/940] lr: 1.0000e-03 eta: 5:53:34 time: 0.5014 data_time: 0.0267 memory: 21547 grad_norm: 4.3233 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3624 loss: 1.3624 2022/10/10 05:23:36 - mmengine - INFO - Epoch(train) [56][480/940] lr: 1.0000e-03 eta: 5:53:23 time: 0.4713 data_time: 0.0254 memory: 21547 grad_norm: 4.3676 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2417 loss: 1.2417 2022/10/10 05:23:47 - mmengine - INFO - Epoch(train) [56][500/940] lr: 1.0000e-03 eta: 5:53:13 time: 0.5416 data_time: 0.0304 memory: 21547 grad_norm: 4.3859 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3188 loss: 1.3188 2022/10/10 05:23:57 - mmengine - INFO - Epoch(train) [56][520/940] lr: 1.0000e-03 eta: 5:53:03 time: 0.4763 data_time: 0.0293 memory: 21547 grad_norm: 4.3955 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2212 loss: 1.2212 2022/10/10 05:24:07 - mmengine - INFO - Epoch(train) [56][540/940] lr: 1.0000e-03 eta: 5:52:53 time: 0.5170 data_time: 0.0261 memory: 21547 grad_norm: 4.3541 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2486 loss: 1.2486 2022/10/10 05:24:16 - mmengine - INFO - Epoch(train) [56][560/940] lr: 1.0000e-03 eta: 5:52:42 time: 0.4725 data_time: 0.0260 memory: 21547 grad_norm: 4.3027 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2233 loss: 1.2233 2022/10/10 05:24:27 - mmengine - INFO - Epoch(train) [56][580/940] lr: 1.0000e-03 eta: 5:52:33 time: 0.5484 data_time: 0.0299 memory: 21547 grad_norm: 4.3183 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1709 loss: 1.1709 2022/10/10 05:24:37 - mmengine - INFO - Epoch(train) [56][600/940] lr: 1.0000e-03 eta: 5:52:22 time: 0.4944 data_time: 0.0241 memory: 21547 grad_norm: 4.4298 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2997 loss: 1.2997 2022/10/10 05:24:48 - mmengine - INFO - Epoch(train) [56][620/940] lr: 1.0000e-03 eta: 5:52:12 time: 0.5263 data_time: 0.0278 memory: 21547 grad_norm: 4.3847 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2110 loss: 1.2110 2022/10/10 05:24:57 - mmengine - INFO - Epoch(train) [56][640/940] lr: 1.0000e-03 eta: 5:52:02 time: 0.4776 data_time: 0.0252 memory: 21547 grad_norm: 4.3896 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1656 loss: 1.1656 2022/10/10 05:25:08 - mmengine - INFO - Epoch(train) [56][660/940] lr: 1.0000e-03 eta: 5:51:52 time: 0.5325 data_time: 0.0317 memory: 21547 grad_norm: 4.4987 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3232 loss: 1.3232 2022/10/10 05:25:17 - mmengine - INFO - Epoch(train) [56][680/940] lr: 1.0000e-03 eta: 5:51:41 time: 0.4398 data_time: 0.0237 memory: 21547 grad_norm: 4.4883 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3218 loss: 1.3218 2022/10/10 05:25:27 - mmengine - INFO - Epoch(train) [56][700/940] lr: 1.0000e-03 eta: 5:51:31 time: 0.5039 data_time: 0.0484 memory: 21547 grad_norm: 4.3521 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2808 loss: 1.2808 2022/10/10 05:25:37 - mmengine - INFO - Epoch(train) [56][720/940] lr: 1.0000e-03 eta: 5:51:20 time: 0.4921 data_time: 0.0433 memory: 21547 grad_norm: 4.3795 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3547 loss: 1.3547 2022/10/10 05:25:47 - mmengine - INFO - Epoch(train) [56][740/940] lr: 1.0000e-03 eta: 5:51:10 time: 0.4959 data_time: 0.0805 memory: 21547 grad_norm: 4.3744 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1890 loss: 1.1890 2022/10/10 05:25:57 - mmengine - INFO - Epoch(train) [56][760/940] lr: 1.0000e-03 eta: 5:51:00 time: 0.5367 data_time: 0.0261 memory: 21547 grad_norm: 4.3090 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4083 loss: 1.4083 2022/10/10 05:26:08 - mmengine - INFO - Epoch(train) [56][780/940] lr: 1.0000e-03 eta: 5:50:50 time: 0.5106 data_time: 0.0316 memory: 21547 grad_norm: 4.3908 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2306 loss: 1.2306 2022/10/10 05:26:18 - mmengine - INFO - Epoch(train) [56][800/940] lr: 1.0000e-03 eta: 5:50:41 time: 0.5395 data_time: 0.0264 memory: 21547 grad_norm: 4.4020 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1928 loss: 1.1928 2022/10/10 05:26:27 - mmengine - INFO - Epoch(train) [56][820/940] lr: 1.0000e-03 eta: 5:50:30 time: 0.4504 data_time: 0.0269 memory: 21547 grad_norm: 4.5049 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2605 loss: 1.2605 2022/10/10 05:26:38 - mmengine - INFO - Epoch(train) [56][840/940] lr: 1.0000e-03 eta: 5:50:20 time: 0.5201 data_time: 0.0283 memory: 21547 grad_norm: 4.3796 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2446 loss: 1.2446 2022/10/10 05:26:48 - mmengine - INFO - Epoch(train) [56][860/940] lr: 1.0000e-03 eta: 5:50:10 time: 0.5164 data_time: 0.0234 memory: 21547 grad_norm: 4.3054 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2686 loss: 1.2686 2022/10/10 05:26:58 - mmengine - INFO - Epoch(train) [56][880/940] lr: 1.0000e-03 eta: 5:49:59 time: 0.5037 data_time: 0.0287 memory: 21547 grad_norm: 4.3781 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1706 loss: 1.1706 2022/10/10 05:27:08 - mmengine - INFO - Epoch(train) [56][900/940] lr: 1.0000e-03 eta: 5:49:49 time: 0.5104 data_time: 0.0303 memory: 21547 grad_norm: 4.3846 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3086 loss: 1.3086 2022/10/10 05:27:18 - mmengine - INFO - Epoch(train) [56][920/940] lr: 1.0000e-03 eta: 5:49:39 time: 0.4965 data_time: 0.0237 memory: 21547 grad_norm: 4.4151 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.2625 loss: 1.2625 2022/10/10 05:27:29 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 05:27:29 - mmengine - INFO - Epoch(train) [56][940/940] lr: 1.0000e-03 eta: 5:49:29 time: 0.5270 data_time: 0.0199 memory: 21547 grad_norm: 4.5891 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.3178 loss: 1.3178 2022/10/10 05:27:41 - mmengine - INFO - Epoch(val) [56][20/78] eta: 0:00:35 time: 0.6075 data_time: 0.4983 memory: 3269 2022/10/10 05:27:50 - mmengine - INFO - Epoch(val) [56][40/78] eta: 0:00:16 time: 0.4266 data_time: 0.3181 memory: 3269 2022/10/10 05:28:00 - mmengine - INFO - Epoch(val) [56][60/78] eta: 0:00:09 time: 0.5413 data_time: 0.4347 memory: 3269 2022/10/10 05:28:11 - mmengine - INFO - Epoch(val) [56][78/78] acc/top1: 0.6735 acc/top5: 0.8702 acc/mean1: 0.6734 2022/10/10 05:28:25 - mmengine - INFO - Epoch(train) [57][20/940] lr: 1.0000e-03 eta: 5:49:22 time: 0.7036 data_time: 0.2304 memory: 21547 grad_norm: 4.3043 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2515 loss: 1.2515 2022/10/10 05:28:34 - mmengine - INFO - Epoch(train) [57][40/940] lr: 1.0000e-03 eta: 5:49:11 time: 0.4727 data_time: 0.0279 memory: 21547 grad_norm: 4.3721 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3552 loss: 1.3552 2022/10/10 05:28:44 - mmengine - INFO - Epoch(train) [57][60/940] lr: 1.0000e-03 eta: 5:49:01 time: 0.5094 data_time: 0.0989 memory: 21547 grad_norm: 4.3078 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1979 loss: 1.1979 2022/10/10 05:28:54 - mmengine - INFO - Epoch(train) [57][80/940] lr: 1.0000e-03 eta: 5:48:51 time: 0.4959 data_time: 0.1022 memory: 21547 grad_norm: 4.3161 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2516 loss: 1.2516 2022/10/10 05:29:05 - mmengine - INFO - Epoch(train) [57][100/940] lr: 1.0000e-03 eta: 5:48:41 time: 0.5308 data_time: 0.0284 memory: 21547 grad_norm: 4.4214 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.2416 loss: 1.2416 2022/10/10 05:29:15 - mmengine - INFO - Epoch(train) [57][120/940] lr: 1.0000e-03 eta: 5:48:31 time: 0.4962 data_time: 0.0275 memory: 21547 grad_norm: 4.4785 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.3080 loss: 1.3080 2022/10/10 05:29:25 - mmengine - INFO - Epoch(train) [57][140/940] lr: 1.0000e-03 eta: 5:48:21 time: 0.5067 data_time: 0.0999 memory: 21547 grad_norm: 4.3404 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1868 loss: 1.1868 2022/10/10 05:29:35 - mmengine - INFO - Epoch(train) [57][160/940] lr: 1.0000e-03 eta: 5:48:11 time: 0.4992 data_time: 0.1202 memory: 21547 grad_norm: 4.3703 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3726 loss: 1.3726 2022/10/10 05:29:46 - mmengine - INFO - Epoch(train) [57][180/940] lr: 1.0000e-03 eta: 5:48:01 time: 0.5369 data_time: 0.1530 memory: 21547 grad_norm: 4.2785 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2697 loss: 1.2697 2022/10/10 05:29:55 - mmengine - INFO - Epoch(train) [57][200/940] lr: 1.0000e-03 eta: 5:47:50 time: 0.4670 data_time: 0.0791 memory: 21547 grad_norm: 4.3883 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3938 loss: 1.3938 2022/10/10 05:30:05 - mmengine - INFO - Epoch(train) [57][220/940] lr: 1.0000e-03 eta: 5:47:40 time: 0.5130 data_time: 0.0789 memory: 21547 grad_norm: 4.3445 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3129 loss: 1.3129 2022/10/10 05:30:16 - mmengine - INFO - Epoch(train) [57][240/940] lr: 1.0000e-03 eta: 5:47:31 time: 0.5496 data_time: 0.0246 memory: 21547 grad_norm: 4.3616 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2720 loss: 1.2720 2022/10/10 05:30:27 - mmengine - INFO - Epoch(train) [57][260/940] lr: 1.0000e-03 eta: 5:47:21 time: 0.5255 data_time: 0.0374 memory: 21547 grad_norm: 4.3454 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2699 loss: 1.2699 2022/10/10 05:30:37 - mmengine - INFO - Epoch(train) [57][280/940] lr: 1.0000e-03 eta: 5:47:10 time: 0.4971 data_time: 0.0253 memory: 21547 grad_norm: 4.3785 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3270 loss: 1.3270 2022/10/10 05:30:47 - mmengine - INFO - Epoch(train) [57][300/940] lr: 1.0000e-03 eta: 5:47:00 time: 0.4982 data_time: 0.0301 memory: 21547 grad_norm: 4.2708 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2268 loss: 1.2268 2022/10/10 05:30:57 - mmengine - INFO - Epoch(train) [57][320/940] lr: 1.0000e-03 eta: 5:46:50 time: 0.5143 data_time: 0.0267 memory: 21547 grad_norm: 4.4220 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2781 loss: 1.2781 2022/10/10 05:31:07 - mmengine - INFO - Epoch(train) [57][340/940] lr: 1.0000e-03 eta: 5:46:40 time: 0.4880 data_time: 0.0271 memory: 21547 grad_norm: 4.4604 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4555 loss: 1.4555 2022/10/10 05:31:16 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 05:31:16 - mmengine - INFO - Epoch(train) [57][360/940] lr: 1.0000e-03 eta: 5:46:29 time: 0.4864 data_time: 0.0281 memory: 21547 grad_norm: 4.4186 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2643 loss: 1.2643 2022/10/10 05:31:27 - mmengine - INFO - Epoch(train) [57][380/940] lr: 1.0000e-03 eta: 5:46:19 time: 0.5095 data_time: 0.0267 memory: 21547 grad_norm: 4.2022 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.1286 loss: 1.1286 2022/10/10 05:31:37 - mmengine - INFO - Epoch(train) [57][400/940] lr: 1.0000e-03 eta: 5:46:09 time: 0.5181 data_time: 0.0277 memory: 21547 grad_norm: 4.5088 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.2491 loss: 1.2491 2022/10/10 05:31:46 - mmengine - INFO - Epoch(train) [57][420/940] lr: 1.0000e-03 eta: 5:45:58 time: 0.4756 data_time: 0.0250 memory: 21547 grad_norm: 4.4151 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3142 loss: 1.3142 2022/10/10 05:31:57 - mmengine - INFO - Epoch(train) [57][440/940] lr: 1.0000e-03 eta: 5:45:48 time: 0.5112 data_time: 0.0299 memory: 21547 grad_norm: 4.3570 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3100 loss: 1.3100 2022/10/10 05:32:06 - mmengine - INFO - Epoch(train) [57][460/940] lr: 1.0000e-03 eta: 5:45:38 time: 0.4633 data_time: 0.0234 memory: 21547 grad_norm: 4.3335 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.2572 loss: 1.2572 2022/10/10 05:32:17 - mmengine - INFO - Epoch(train) [57][480/940] lr: 1.0000e-03 eta: 5:45:28 time: 0.5292 data_time: 0.0297 memory: 21547 grad_norm: 4.3577 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3206 loss: 1.3206 2022/10/10 05:32:26 - mmengine - INFO - Epoch(train) [57][500/940] lr: 1.0000e-03 eta: 5:45:18 time: 0.4963 data_time: 0.0272 memory: 21547 grad_norm: 4.4613 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3072 loss: 1.3072 2022/10/10 05:32:36 - mmengine - INFO - Epoch(train) [57][520/940] lr: 1.0000e-03 eta: 5:45:07 time: 0.4769 data_time: 0.0316 memory: 21547 grad_norm: 4.4017 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3172 loss: 1.3172 2022/10/10 05:32:46 - mmengine - INFO - Epoch(train) [57][540/940] lr: 1.0000e-03 eta: 5:44:56 time: 0.4870 data_time: 0.0275 memory: 21547 grad_norm: 4.3529 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1970 loss: 1.1970 2022/10/10 05:32:56 - mmengine - INFO - Epoch(train) [57][560/940] lr: 1.0000e-03 eta: 5:44:46 time: 0.5168 data_time: 0.0258 memory: 21547 grad_norm: 4.3095 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0852 loss: 1.0852 2022/10/10 05:33:05 - mmengine - INFO - Epoch(train) [57][580/940] lr: 1.0000e-03 eta: 5:44:36 time: 0.4603 data_time: 0.0346 memory: 21547 grad_norm: 4.4528 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2457 loss: 1.2457 2022/10/10 05:33:16 - mmengine - INFO - Epoch(train) [57][600/940] lr: 1.0000e-03 eta: 5:44:26 time: 0.5126 data_time: 0.0296 memory: 21547 grad_norm: 4.4410 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1029 loss: 1.1029 2022/10/10 05:33:26 - mmengine - INFO - Epoch(train) [57][620/940] lr: 1.0000e-03 eta: 5:44:16 time: 0.5216 data_time: 0.0270 memory: 21547 grad_norm: 4.4072 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2210 loss: 1.2210 2022/10/10 05:33:36 - mmengine - INFO - Epoch(train) [57][640/940] lr: 1.0000e-03 eta: 5:44:06 time: 0.5248 data_time: 0.0302 memory: 21547 grad_norm: 4.3934 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2832 loss: 1.2832 2022/10/10 05:33:46 - mmengine - INFO - Epoch(train) [57][660/940] lr: 1.0000e-03 eta: 5:43:55 time: 0.4873 data_time: 0.0278 memory: 21547 grad_norm: 4.2664 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 1.2224 loss: 1.2224 2022/10/10 05:33:57 - mmengine - INFO - Epoch(train) [57][680/940] lr: 1.0000e-03 eta: 5:43:46 time: 0.5407 data_time: 0.0285 memory: 21547 grad_norm: 4.4625 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3047 loss: 1.3047 2022/10/10 05:34:07 - mmengine - INFO - Epoch(train) [57][700/940] lr: 1.0000e-03 eta: 5:43:35 time: 0.4995 data_time: 0.0241 memory: 21547 grad_norm: 4.3889 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3337 loss: 1.3337 2022/10/10 05:34:17 - mmengine - INFO - Epoch(train) [57][720/940] lr: 1.0000e-03 eta: 5:43:25 time: 0.5161 data_time: 0.0331 memory: 21547 grad_norm: 4.4324 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2913 loss: 1.2913 2022/10/10 05:34:27 - mmengine - INFO - Epoch(train) [57][740/940] lr: 1.0000e-03 eta: 5:43:15 time: 0.4970 data_time: 0.0223 memory: 21547 grad_norm: 4.4109 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2040 loss: 1.2040 2022/10/10 05:34:37 - mmengine - INFO - Epoch(train) [57][760/940] lr: 1.0000e-03 eta: 5:43:05 time: 0.4934 data_time: 0.0288 memory: 21547 grad_norm: 4.4342 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2598 loss: 1.2598 2022/10/10 05:34:47 - mmengine - INFO - Epoch(train) [57][780/940] lr: 1.0000e-03 eta: 5:42:54 time: 0.4724 data_time: 0.0269 memory: 21547 grad_norm: 4.5404 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3568 loss: 1.3568 2022/10/10 05:34:57 - mmengine - INFO - Epoch(train) [57][800/940] lr: 1.0000e-03 eta: 5:42:44 time: 0.5291 data_time: 0.0279 memory: 21547 grad_norm: 4.4186 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1892 loss: 1.1892 2022/10/10 05:35:08 - mmengine - INFO - Epoch(train) [57][820/940] lr: 1.0000e-03 eta: 5:42:34 time: 0.5183 data_time: 0.0253 memory: 21547 grad_norm: 4.4368 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2893 loss: 1.2893 2022/10/10 05:35:18 - mmengine - INFO - Epoch(train) [57][840/940] lr: 1.0000e-03 eta: 5:42:24 time: 0.5021 data_time: 0.0258 memory: 21547 grad_norm: 4.4403 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3952 loss: 1.3952 2022/10/10 05:35:27 - mmengine - INFO - Epoch(train) [57][860/940] lr: 1.0000e-03 eta: 5:42:13 time: 0.4480 data_time: 0.0261 memory: 21547 grad_norm: 4.4358 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2647 loss: 1.2647 2022/10/10 05:35:37 - mmengine - INFO - Epoch(train) [57][880/940] lr: 1.0000e-03 eta: 5:42:03 time: 0.5161 data_time: 0.0285 memory: 21547 grad_norm: 4.2930 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.2825 loss: 1.2825 2022/10/10 05:35:47 - mmengine - INFO - Epoch(train) [57][900/940] lr: 1.0000e-03 eta: 5:41:53 time: 0.5059 data_time: 0.0308 memory: 21547 grad_norm: 4.4502 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2312 loss: 1.2312 2022/10/10 05:35:57 - mmengine - INFO - Epoch(train) [57][920/940] lr: 1.0000e-03 eta: 5:41:43 time: 0.5136 data_time: 0.0360 memory: 21547 grad_norm: 4.3411 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2859 loss: 1.2859 2022/10/10 05:36:05 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 05:36:05 - mmengine - INFO - Epoch(train) [57][940/940] lr: 1.0000e-03 eta: 5:41:31 time: 0.4043 data_time: 0.0217 memory: 21547 grad_norm: 4.6346 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.2504 loss: 1.2504 2022/10/10 05:36:05 - mmengine - INFO - Saving checkpoint at 57 epochs 2022/10/10 05:36:19 - mmengine - INFO - Epoch(val) [57][20/78] eta: 0:00:35 time: 0.6149 data_time: 0.5097 memory: 3269 2022/10/10 05:36:27 - mmengine - INFO - Epoch(val) [57][40/78] eta: 0:00:15 time: 0.4184 data_time: 0.3139 memory: 3269 2022/10/10 05:36:38 - mmengine - INFO - Epoch(val) [57][60/78] eta: 0:00:10 time: 0.5560 data_time: 0.4493 memory: 3269 2022/10/10 05:36:48 - mmengine - INFO - Epoch(val) [57][78/78] acc/top1: 0.6755 acc/top5: 0.8723 acc/mean1: 0.6754 2022/10/10 05:37:02 - mmengine - INFO - Epoch(train) [58][20/940] lr: 1.0000e-03 eta: 5:41:24 time: 0.7154 data_time: 0.2167 memory: 21547 grad_norm: 4.4428 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1880 loss: 1.1880 2022/10/10 05:37:12 - mmengine - INFO - Epoch(train) [58][40/940] lr: 1.0000e-03 eta: 5:41:14 time: 0.4793 data_time: 0.0253 memory: 21547 grad_norm: 4.3536 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2853 loss: 1.2853 2022/10/10 05:37:22 - mmengine - INFO - Epoch(train) [58][60/940] lr: 1.0000e-03 eta: 5:41:04 time: 0.5198 data_time: 0.0306 memory: 21547 grad_norm: 4.3673 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2927 loss: 1.2927 2022/10/10 05:37:31 - mmengine - INFO - Epoch(train) [58][80/940] lr: 1.0000e-03 eta: 5:40:53 time: 0.4489 data_time: 0.0329 memory: 21547 grad_norm: 4.4396 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1483 loss: 1.1483 2022/10/10 05:37:42 - mmengine - INFO - Epoch(train) [58][100/940] lr: 1.0000e-03 eta: 5:40:43 time: 0.5375 data_time: 0.0494 memory: 21547 grad_norm: 4.3557 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0612 loss: 1.0612 2022/10/10 05:37:52 - mmengine - INFO - Epoch(train) [58][120/940] lr: 1.0000e-03 eta: 5:40:33 time: 0.4968 data_time: 0.0286 memory: 21547 grad_norm: 4.4236 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2400 loss: 1.2400 2022/10/10 05:38:02 - mmengine - INFO - Epoch(train) [58][140/940] lr: 1.0000e-03 eta: 5:40:23 time: 0.5115 data_time: 0.0296 memory: 21547 grad_norm: 4.4802 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2810 loss: 1.2810 2022/10/10 05:38:12 - mmengine - INFO - Epoch(train) [58][160/940] lr: 1.0000e-03 eta: 5:40:13 time: 0.5072 data_time: 0.0615 memory: 21547 grad_norm: 4.3225 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2584 loss: 1.2584 2022/10/10 05:38:22 - mmengine - INFO - Epoch(train) [58][180/940] lr: 1.0000e-03 eta: 5:40:03 time: 0.5197 data_time: 0.0569 memory: 21547 grad_norm: 4.2905 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1539 loss: 1.1539 2022/10/10 05:38:32 - mmengine - INFO - Epoch(train) [58][200/940] lr: 1.0000e-03 eta: 5:39:52 time: 0.4732 data_time: 0.0298 memory: 21547 grad_norm: 4.3043 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1356 loss: 1.1356 2022/10/10 05:38:42 - mmengine - INFO - Epoch(train) [58][220/940] lr: 1.0000e-03 eta: 5:39:42 time: 0.5176 data_time: 0.0244 memory: 21547 grad_norm: 4.4138 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.2463 loss: 1.2463 2022/10/10 05:38:53 - mmengine - INFO - Epoch(train) [58][240/940] lr: 1.0000e-03 eta: 5:39:32 time: 0.5191 data_time: 0.0302 memory: 21547 grad_norm: 4.4888 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2964 loss: 1.2964 2022/10/10 05:39:03 - mmengine - INFO - Epoch(train) [58][260/940] lr: 1.0000e-03 eta: 5:39:22 time: 0.5359 data_time: 0.0219 memory: 21547 grad_norm: 4.4304 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2451 loss: 1.2451 2022/10/10 05:39:13 - mmengine - INFO - Epoch(train) [58][280/940] lr: 1.0000e-03 eta: 5:39:11 time: 0.4643 data_time: 0.0254 memory: 21547 grad_norm: 4.3423 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1975 loss: 1.1975 2022/10/10 05:39:23 - mmengine - INFO - Epoch(train) [58][300/940] lr: 1.0000e-03 eta: 5:39:01 time: 0.5091 data_time: 0.0286 memory: 21547 grad_norm: 4.4829 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3097 loss: 1.3097 2022/10/10 05:39:32 - mmengine - INFO - Epoch(train) [58][320/940] lr: 1.0000e-03 eta: 5:38:51 time: 0.4756 data_time: 0.0363 memory: 21547 grad_norm: 4.4311 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3365 loss: 1.3365 2022/10/10 05:39:43 - mmengine - INFO - Epoch(train) [58][340/940] lr: 1.0000e-03 eta: 5:38:41 time: 0.5260 data_time: 0.0239 memory: 21547 grad_norm: 4.3813 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2189 loss: 1.2189 2022/10/10 05:39:52 - mmengine - INFO - Epoch(train) [58][360/940] lr: 1.0000e-03 eta: 5:38:30 time: 0.4684 data_time: 0.0316 memory: 21547 grad_norm: 4.4105 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2216 loss: 1.2216 2022/10/10 05:40:03 - mmengine - INFO - Epoch(train) [58][380/940] lr: 1.0000e-03 eta: 5:38:21 time: 0.5376 data_time: 0.0222 memory: 21547 grad_norm: 4.3214 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2033 loss: 1.2033 2022/10/10 05:40:14 - mmengine - INFO - Epoch(train) [58][400/940] lr: 1.0000e-03 eta: 5:38:11 time: 0.5292 data_time: 0.0269 memory: 21547 grad_norm: 4.3169 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2449 loss: 1.2449 2022/10/10 05:40:25 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 05:40:25 - mmengine - INFO - Epoch(train) [58][420/940] lr: 1.0000e-03 eta: 5:38:01 time: 0.5500 data_time: 0.0240 memory: 21547 grad_norm: 4.4400 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0907 loss: 1.0907 2022/10/10 05:40:34 - mmengine - INFO - Epoch(train) [58][440/940] lr: 1.0000e-03 eta: 5:37:50 time: 0.4674 data_time: 0.0266 memory: 21547 grad_norm: 4.3272 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2609 loss: 1.2609 2022/10/10 05:40:44 - mmengine - INFO - Epoch(train) [58][460/940] lr: 1.0000e-03 eta: 5:37:40 time: 0.5003 data_time: 0.0280 memory: 21547 grad_norm: 4.5025 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1672 loss: 1.1672 2022/10/10 05:40:53 - mmengine - INFO - Epoch(train) [58][480/940] lr: 1.0000e-03 eta: 5:37:29 time: 0.4588 data_time: 0.0256 memory: 21547 grad_norm: 4.4313 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1604 loss: 1.1604 2022/10/10 05:41:03 - mmengine - INFO - Epoch(train) [58][500/940] lr: 1.0000e-03 eta: 5:37:19 time: 0.4937 data_time: 0.0519 memory: 21547 grad_norm: 4.4858 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2858 loss: 1.2858 2022/10/10 05:41:13 - mmengine - INFO - Epoch(train) [58][520/940] lr: 1.0000e-03 eta: 5:37:09 time: 0.4906 data_time: 0.0568 memory: 21547 grad_norm: 4.3553 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2462 loss: 1.2462 2022/10/10 05:41:23 - mmengine - INFO - Epoch(train) [58][540/940] lr: 1.0000e-03 eta: 5:36:59 time: 0.5324 data_time: 0.0818 memory: 21547 grad_norm: 4.4134 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2968 loss: 1.2968 2022/10/10 05:41:33 - mmengine - INFO - Epoch(train) [58][560/940] lr: 1.0000e-03 eta: 5:36:49 time: 0.4967 data_time: 0.0888 memory: 21547 grad_norm: 4.4271 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2929 loss: 1.2929 2022/10/10 05:41:44 - mmengine - INFO - Epoch(train) [58][580/940] lr: 1.0000e-03 eta: 5:36:39 time: 0.5317 data_time: 0.0330 memory: 21547 grad_norm: 4.4842 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2331 loss: 1.2331 2022/10/10 05:41:53 - mmengine - INFO - Epoch(train) [58][600/940] lr: 1.0000e-03 eta: 5:36:28 time: 0.4553 data_time: 0.0260 memory: 21547 grad_norm: 4.4472 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2938 loss: 1.2938 2022/10/10 05:42:04 - mmengine - INFO - Epoch(train) [58][620/940] lr: 1.0000e-03 eta: 5:36:18 time: 0.5376 data_time: 0.0349 memory: 21547 grad_norm: 4.3791 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2333 loss: 1.2333 2022/10/10 05:42:13 - mmengine - INFO - Epoch(train) [58][640/940] lr: 1.0000e-03 eta: 5:36:08 time: 0.4717 data_time: 0.0285 memory: 21547 grad_norm: 4.4725 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3451 loss: 1.3451 2022/10/10 05:42:24 - mmengine - INFO - Epoch(train) [58][660/940] lr: 1.0000e-03 eta: 5:35:58 time: 0.5163 data_time: 0.1043 memory: 21547 grad_norm: 4.3871 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2296 loss: 1.2296 2022/10/10 05:42:34 - mmengine - INFO - Epoch(train) [58][680/940] lr: 1.0000e-03 eta: 5:35:48 time: 0.5294 data_time: 0.1357 memory: 21547 grad_norm: 4.4255 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2984 loss: 1.2984 2022/10/10 05:42:45 - mmengine - INFO - Epoch(train) [58][700/940] lr: 1.0000e-03 eta: 5:35:38 time: 0.5194 data_time: 0.0334 memory: 21547 grad_norm: 4.4084 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3323 loss: 1.3323 2022/10/10 05:42:55 - mmengine - INFO - Epoch(train) [58][720/940] lr: 1.0000e-03 eta: 5:35:28 time: 0.4984 data_time: 0.0267 memory: 21547 grad_norm: 4.3736 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2530 loss: 1.2530 2022/10/10 05:43:04 - mmengine - INFO - Epoch(train) [58][740/940] lr: 1.0000e-03 eta: 5:35:17 time: 0.4867 data_time: 0.0292 memory: 21547 grad_norm: 4.3604 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1974 loss: 1.1974 2022/10/10 05:43:14 - mmengine - INFO - Epoch(train) [58][760/940] lr: 1.0000e-03 eta: 5:35:07 time: 0.4855 data_time: 0.0254 memory: 21547 grad_norm: 4.4461 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1437 loss: 1.1437 2022/10/10 05:43:25 - mmengine - INFO - Epoch(train) [58][780/940] lr: 1.0000e-03 eta: 5:34:57 time: 0.5281 data_time: 0.0349 memory: 21547 grad_norm: 4.4308 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2875 loss: 1.2875 2022/10/10 05:43:34 - mmengine - INFO - Epoch(train) [58][800/940] lr: 1.0000e-03 eta: 5:34:46 time: 0.4768 data_time: 0.0256 memory: 21547 grad_norm: 4.4433 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3296 loss: 1.3296 2022/10/10 05:43:45 - mmengine - INFO - Epoch(train) [58][820/940] lr: 1.0000e-03 eta: 5:34:36 time: 0.5291 data_time: 0.0322 memory: 21547 grad_norm: 4.3772 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3476 loss: 1.3476 2022/10/10 05:43:54 - mmengine - INFO - Epoch(train) [58][840/940] lr: 1.0000e-03 eta: 5:34:26 time: 0.4729 data_time: 0.0315 memory: 21547 grad_norm: 4.4890 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2620 loss: 1.2620 2022/10/10 05:44:05 - mmengine - INFO - Epoch(train) [58][860/940] lr: 1.0000e-03 eta: 5:34:16 time: 0.5387 data_time: 0.0327 memory: 21547 grad_norm: 4.4238 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2597 loss: 1.2597 2022/10/10 05:44:15 - mmengine - INFO - Epoch(train) [58][880/940] lr: 1.0000e-03 eta: 5:34:06 time: 0.5054 data_time: 0.0325 memory: 21547 grad_norm: 4.4474 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3014 loss: 1.3014 2022/10/10 05:44:25 - mmengine - INFO - Epoch(train) [58][900/940] lr: 1.0000e-03 eta: 5:33:56 time: 0.4886 data_time: 0.0258 memory: 21547 grad_norm: 4.5667 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.2955 loss: 1.2955 2022/10/10 05:44:35 - mmengine - INFO - Epoch(train) [58][920/940] lr: 1.0000e-03 eta: 5:33:45 time: 0.5002 data_time: 0.0373 memory: 21547 grad_norm: 4.4132 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.3363 loss: 1.3363 2022/10/10 05:44:44 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 05:44:44 - mmengine - INFO - Epoch(train) [58][940/940] lr: 1.0000e-03 eta: 5:33:34 time: 0.4441 data_time: 0.0288 memory: 21547 grad_norm: 4.7101 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.2171 loss: 1.2171 2022/10/10 05:44:56 - mmengine - INFO - Epoch(val) [58][20/78] eta: 0:00:34 time: 0.6032 data_time: 0.4946 memory: 3269 2022/10/10 05:45:04 - mmengine - INFO - Epoch(val) [58][40/78] eta: 0:00:15 time: 0.4196 data_time: 0.3121 memory: 3269 2022/10/10 05:45:15 - mmengine - INFO - Epoch(val) [58][60/78] eta: 0:00:10 time: 0.5664 data_time: 0.4575 memory: 3269 2022/10/10 05:45:25 - mmengine - INFO - Epoch(val) [58][78/78] acc/top1: 0.6768 acc/top5: 0.8719 acc/mean1: 0.6767 2022/10/10 05:45:39 - mmengine - INFO - Epoch(train) [59][20/940] lr: 1.0000e-03 eta: 5:33:27 time: 0.6971 data_time: 0.2933 memory: 21547 grad_norm: 4.4187 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3521 loss: 1.3521 2022/10/10 05:45:49 - mmengine - INFO - Epoch(train) [59][40/940] lr: 1.0000e-03 eta: 5:33:16 time: 0.4726 data_time: 0.0955 memory: 21547 grad_norm: 4.4581 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2759 loss: 1.2759 2022/10/10 05:46:00 - mmengine - INFO - Epoch(train) [59][60/940] lr: 1.0000e-03 eta: 5:33:07 time: 0.5725 data_time: 0.0704 memory: 21547 grad_norm: 4.3586 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2131 loss: 1.2131 2022/10/10 05:46:09 - mmengine - INFO - Epoch(train) [59][80/940] lr: 1.0000e-03 eta: 5:32:56 time: 0.4560 data_time: 0.0273 memory: 21547 grad_norm: 4.4869 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4048 loss: 1.4048 2022/10/10 05:46:19 - mmengine - INFO - Epoch(train) [59][100/940] lr: 1.0000e-03 eta: 5:32:46 time: 0.5042 data_time: 0.0289 memory: 21547 grad_norm: 4.3546 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3072 loss: 1.3072 2022/10/10 05:46:29 - mmengine - INFO - Epoch(train) [59][120/940] lr: 1.0000e-03 eta: 5:32:36 time: 0.4937 data_time: 0.0253 memory: 21547 grad_norm: 4.4531 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.1489 loss: 1.1489 2022/10/10 05:46:39 - mmengine - INFO - Epoch(train) [59][140/940] lr: 1.0000e-03 eta: 5:32:25 time: 0.5070 data_time: 0.0275 memory: 21547 grad_norm: 4.3441 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2353 loss: 1.2353 2022/10/10 05:46:49 - mmengine - INFO - Epoch(train) [59][160/940] lr: 1.0000e-03 eta: 5:32:15 time: 0.4633 data_time: 0.0286 memory: 21547 grad_norm: 4.3467 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2173 loss: 1.2173 2022/10/10 05:47:00 - mmengine - INFO - Epoch(train) [59][180/940] lr: 1.0000e-03 eta: 5:32:05 time: 0.5467 data_time: 0.0386 memory: 21547 grad_norm: 4.4948 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2238 loss: 1.2238 2022/10/10 05:47:09 - mmengine - INFO - Epoch(train) [59][200/940] lr: 1.0000e-03 eta: 5:31:55 time: 0.4893 data_time: 0.0292 memory: 21547 grad_norm: 4.3387 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0672 loss: 1.0672 2022/10/10 05:47:21 - mmengine - INFO - Epoch(train) [59][220/940] lr: 1.0000e-03 eta: 5:31:45 time: 0.5575 data_time: 0.0315 memory: 21547 grad_norm: 4.3980 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3320 loss: 1.3320 2022/10/10 05:47:31 - mmengine - INFO - Epoch(train) [59][240/940] lr: 1.0000e-03 eta: 5:31:35 time: 0.5021 data_time: 0.0291 memory: 21547 grad_norm: 4.4270 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2711 loss: 1.2711 2022/10/10 05:47:40 - mmengine - INFO - Epoch(train) [59][260/940] lr: 1.0000e-03 eta: 5:31:25 time: 0.4848 data_time: 0.0257 memory: 21547 grad_norm: 4.4674 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3035 loss: 1.3035 2022/10/10 05:47:50 - mmengine - INFO - Epoch(train) [59][280/940] lr: 1.0000e-03 eta: 5:31:14 time: 0.4761 data_time: 0.0277 memory: 21547 grad_norm: 4.4229 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1373 loss: 1.1373 2022/10/10 05:47:59 - mmengine - INFO - Epoch(train) [59][300/940] lr: 1.0000e-03 eta: 5:31:03 time: 0.4731 data_time: 0.0287 memory: 21547 grad_norm: 4.4521 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1608 loss: 1.1608 2022/10/10 05:48:09 - mmengine - INFO - Epoch(train) [59][320/940] lr: 1.0000e-03 eta: 5:30:53 time: 0.4821 data_time: 0.0272 memory: 21547 grad_norm: 4.3699 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2923 loss: 1.2923 2022/10/10 05:48:21 - mmengine - INFO - Epoch(train) [59][340/940] lr: 1.0000e-03 eta: 5:30:44 time: 0.5994 data_time: 0.0260 memory: 21547 grad_norm: 4.3571 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2067 loss: 1.2067 2022/10/10 05:48:31 - mmengine - INFO - Epoch(train) [59][360/940] lr: 1.0000e-03 eta: 5:30:34 time: 0.5198 data_time: 0.0290 memory: 21547 grad_norm: 4.4104 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2206 loss: 1.2206 2022/10/10 05:48:41 - mmengine - INFO - Epoch(train) [59][380/940] lr: 1.0000e-03 eta: 5:30:24 time: 0.4712 data_time: 0.0239 memory: 21547 grad_norm: 4.4638 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2194 loss: 1.2194 2022/10/10 05:48:50 - mmengine - INFO - Epoch(train) [59][400/940] lr: 1.0000e-03 eta: 5:30:13 time: 0.4640 data_time: 0.0284 memory: 21547 grad_norm: 4.3228 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2076 loss: 1.2076 2022/10/10 05:49:00 - mmengine - INFO - Epoch(train) [59][420/940] lr: 1.0000e-03 eta: 5:30:03 time: 0.5082 data_time: 0.0288 memory: 21547 grad_norm: 4.4121 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2219 loss: 1.2219 2022/10/10 05:49:10 - mmengine - INFO - Epoch(train) [59][440/940] lr: 1.0000e-03 eta: 5:29:53 time: 0.5096 data_time: 0.0267 memory: 21547 grad_norm: 4.3827 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.2674 loss: 1.2674 2022/10/10 05:49:20 - mmengine - INFO - Epoch(train) [59][460/940] lr: 1.0000e-03 eta: 5:29:42 time: 0.4841 data_time: 0.0292 memory: 21547 grad_norm: 4.4562 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1546 loss: 1.1546 2022/10/10 05:49:32 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 05:49:32 - mmengine - INFO - Epoch(train) [59][480/940] lr: 1.0000e-03 eta: 5:29:33 time: 0.5764 data_time: 0.0311 memory: 21547 grad_norm: 4.3448 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2164 loss: 1.2164 2022/10/10 05:49:42 - mmengine - INFO - Epoch(train) [59][500/940] lr: 1.0000e-03 eta: 5:29:23 time: 0.4955 data_time: 0.0295 memory: 21547 grad_norm: 4.4513 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.1752 loss: 1.1752 2022/10/10 05:49:52 - mmengine - INFO - Epoch(train) [59][520/940] lr: 1.0000e-03 eta: 5:29:13 time: 0.5365 data_time: 0.0249 memory: 21547 grad_norm: 4.3760 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2228 loss: 1.2228 2022/10/10 05:50:01 - mmengine - INFO - Epoch(train) [59][540/940] lr: 1.0000e-03 eta: 5:29:02 time: 0.4270 data_time: 0.0244 memory: 21547 grad_norm: 4.4975 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1728 loss: 1.1728 2022/10/10 05:50:11 - mmengine - INFO - Epoch(train) [59][560/940] lr: 1.0000e-03 eta: 5:28:52 time: 0.5085 data_time: 0.0252 memory: 21547 grad_norm: 4.3970 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3668 loss: 1.3668 2022/10/10 05:50:21 - mmengine - INFO - Epoch(train) [59][580/940] lr: 1.0000e-03 eta: 5:28:41 time: 0.5012 data_time: 0.0250 memory: 21547 grad_norm: 4.3803 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2030 loss: 1.2030 2022/10/10 05:50:32 - mmengine - INFO - Epoch(train) [59][600/940] lr: 1.0000e-03 eta: 5:28:32 time: 0.5499 data_time: 0.0262 memory: 21547 grad_norm: 4.3927 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2844 loss: 1.2844 2022/10/10 05:50:42 - mmengine - INFO - Epoch(train) [59][620/940] lr: 1.0000e-03 eta: 5:28:22 time: 0.5099 data_time: 0.0326 memory: 21547 grad_norm: 4.4168 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2769 loss: 1.2769 2022/10/10 05:50:53 - mmengine - INFO - Epoch(train) [59][640/940] lr: 1.0000e-03 eta: 5:28:12 time: 0.5252 data_time: 0.0216 memory: 21547 grad_norm: 4.5951 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.5023 loss: 1.5023 2022/10/10 05:51:03 - mmengine - INFO - Epoch(train) [59][660/940] lr: 1.0000e-03 eta: 5:28:01 time: 0.4936 data_time: 0.0250 memory: 21547 grad_norm: 4.4201 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2761 loss: 1.2761 2022/10/10 05:51:14 - mmengine - INFO - Epoch(train) [59][680/940] lr: 1.0000e-03 eta: 5:27:52 time: 0.5522 data_time: 0.0232 memory: 21547 grad_norm: 4.3930 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2877 loss: 1.2877 2022/10/10 05:51:23 - mmengine - INFO - Epoch(train) [59][700/940] lr: 1.0000e-03 eta: 5:27:41 time: 0.4821 data_time: 0.0261 memory: 21547 grad_norm: 4.3557 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2720 loss: 1.2720 2022/10/10 05:51:34 - mmengine - INFO - Epoch(train) [59][720/940] lr: 1.0000e-03 eta: 5:27:31 time: 0.5136 data_time: 0.0273 memory: 21547 grad_norm: 4.4783 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.4244 loss: 1.4244 2022/10/10 05:51:44 - mmengine - INFO - Epoch(train) [59][740/940] lr: 1.0000e-03 eta: 5:27:21 time: 0.5025 data_time: 0.0258 memory: 21547 grad_norm: 4.3255 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0525 loss: 1.0525 2022/10/10 05:51:54 - mmengine - INFO - Epoch(train) [59][760/940] lr: 1.0000e-03 eta: 5:27:11 time: 0.5223 data_time: 0.0270 memory: 21547 grad_norm: 4.4751 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2883 loss: 1.2883 2022/10/10 05:52:04 - mmengine - INFO - Epoch(train) [59][780/940] lr: 1.0000e-03 eta: 5:27:01 time: 0.5001 data_time: 0.0352 memory: 21547 grad_norm: 4.4935 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2846 loss: 1.2846 2022/10/10 05:52:14 - mmengine - INFO - Epoch(train) [59][800/940] lr: 1.0000e-03 eta: 5:26:51 time: 0.5194 data_time: 0.0291 memory: 21547 grad_norm: 4.4321 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2521 loss: 1.2521 2022/10/10 05:52:25 - mmengine - INFO - Epoch(train) [59][820/940] lr: 1.0000e-03 eta: 5:26:41 time: 0.5241 data_time: 0.0236 memory: 21547 grad_norm: 4.4366 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.1631 loss: 1.1631 2022/10/10 05:52:37 - mmengine - INFO - Epoch(train) [59][840/940] lr: 1.0000e-03 eta: 5:26:32 time: 0.5791 data_time: 0.0234 memory: 21547 grad_norm: 4.5158 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2663 loss: 1.2663 2022/10/10 05:52:46 - mmengine - INFO - Epoch(train) [59][860/940] lr: 1.0000e-03 eta: 5:26:21 time: 0.4513 data_time: 0.0324 memory: 21547 grad_norm: 4.3898 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1893 loss: 1.1893 2022/10/10 05:52:56 - mmengine - INFO - Epoch(train) [59][880/940] lr: 1.0000e-03 eta: 5:26:11 time: 0.5018 data_time: 0.0262 memory: 21547 grad_norm: 4.4336 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.3156 loss: 1.3156 2022/10/10 05:53:05 - mmengine - INFO - Epoch(train) [59][900/940] lr: 1.0000e-03 eta: 5:26:00 time: 0.4460 data_time: 0.0335 memory: 21547 grad_norm: 4.4418 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2314 loss: 1.2314 2022/10/10 05:53:15 - mmengine - INFO - Epoch(train) [59][920/940] lr: 1.0000e-03 eta: 5:25:50 time: 0.5400 data_time: 0.0294 memory: 21547 grad_norm: 4.3562 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3429 loss: 1.3429 2022/10/10 05:53:24 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 05:53:24 - mmengine - INFO - Epoch(train) [59][940/940] lr: 1.0000e-03 eta: 5:25:39 time: 0.4335 data_time: 0.0239 memory: 21547 grad_norm: 4.6239 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.0905 loss: 1.0905 2022/10/10 05:53:36 - mmengine - INFO - Epoch(val) [59][20/78] eta: 0:00:35 time: 0.6100 data_time: 0.5029 memory: 3269 2022/10/10 05:53:45 - mmengine - INFO - Epoch(val) [59][40/78] eta: 0:00:15 time: 0.4206 data_time: 0.3155 memory: 3269 2022/10/10 05:53:56 - mmengine - INFO - Epoch(val) [59][60/78] eta: 0:00:10 time: 0.5647 data_time: 0.4572 memory: 3269 2022/10/10 05:54:06 - mmengine - INFO - Epoch(val) [59][78/78] acc/top1: 0.6761 acc/top5: 0.8713 acc/mean1: 0.6760 2022/10/10 05:54:20 - mmengine - INFO - Epoch(train) [60][20/940] lr: 1.0000e-03 eta: 5:25:32 time: 0.6922 data_time: 0.2642 memory: 21547 grad_norm: 4.4103 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1396 loss: 1.1396 2022/10/10 05:54:30 - mmengine - INFO - Epoch(train) [60][40/940] lr: 1.0000e-03 eta: 5:25:21 time: 0.4912 data_time: 0.0598 memory: 21547 grad_norm: 4.3988 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1255 loss: 1.1255 2022/10/10 05:54:40 - mmengine - INFO - Epoch(train) [60][60/940] lr: 1.0000e-03 eta: 5:25:11 time: 0.5329 data_time: 0.0402 memory: 21547 grad_norm: 4.4564 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2513 loss: 1.2513 2022/10/10 05:54:51 - mmengine - INFO - Epoch(train) [60][80/940] lr: 1.0000e-03 eta: 5:25:01 time: 0.5146 data_time: 0.0300 memory: 21547 grad_norm: 4.3563 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.3321 loss: 1.3321 2022/10/10 05:55:01 - mmengine - INFO - Epoch(train) [60][100/940] lr: 1.0000e-03 eta: 5:24:51 time: 0.5055 data_time: 0.0300 memory: 21547 grad_norm: 4.5544 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3055 loss: 1.3055 2022/10/10 05:55:11 - mmengine - INFO - Epoch(train) [60][120/940] lr: 1.0000e-03 eta: 5:24:41 time: 0.4945 data_time: 0.0300 memory: 21547 grad_norm: 4.4037 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3653 loss: 1.3653 2022/10/10 05:55:22 - mmengine - INFO - Epoch(train) [60][140/940] lr: 1.0000e-03 eta: 5:24:31 time: 0.5616 data_time: 0.0268 memory: 21547 grad_norm: 4.4541 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2899 loss: 1.2899 2022/10/10 05:55:32 - mmengine - INFO - Epoch(train) [60][160/940] lr: 1.0000e-03 eta: 5:24:21 time: 0.5052 data_time: 0.0250 memory: 21547 grad_norm: 4.5226 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3004 loss: 1.3004 2022/10/10 05:55:43 - mmengine - INFO - Epoch(train) [60][180/940] lr: 1.0000e-03 eta: 5:24:11 time: 0.5256 data_time: 0.0317 memory: 21547 grad_norm: 4.4455 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1346 loss: 1.1346 2022/10/10 05:55:52 - mmengine - INFO - Epoch(train) [60][200/940] lr: 1.0000e-03 eta: 5:24:01 time: 0.4753 data_time: 0.0272 memory: 21547 grad_norm: 4.3841 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2085 loss: 1.2085 2022/10/10 05:56:03 - mmengine - INFO - Epoch(train) [60][220/940] lr: 1.0000e-03 eta: 5:23:51 time: 0.5227 data_time: 0.0216 memory: 21547 grad_norm: 4.3676 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3519 loss: 1.3519 2022/10/10 05:56:13 - mmengine - INFO - Epoch(train) [60][240/940] lr: 1.0000e-03 eta: 5:23:41 time: 0.5060 data_time: 0.0280 memory: 21547 grad_norm: 4.4224 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2198 loss: 1.2198 2022/10/10 05:56:23 - mmengine - INFO - Epoch(train) [60][260/940] lr: 1.0000e-03 eta: 5:23:31 time: 0.5098 data_time: 0.0244 memory: 21547 grad_norm: 4.5033 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2867 loss: 1.2867 2022/10/10 05:56:33 - mmengine - INFO - Epoch(train) [60][280/940] lr: 1.0000e-03 eta: 5:23:20 time: 0.4842 data_time: 0.0279 memory: 21547 grad_norm: 4.4177 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2943 loss: 1.2943 2022/10/10 05:56:42 - mmengine - INFO - Epoch(train) [60][300/940] lr: 1.0000e-03 eta: 5:23:10 time: 0.4854 data_time: 0.0256 memory: 21547 grad_norm: 4.3800 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1717 loss: 1.1717 2022/10/10 05:56:52 - mmengine - INFO - Epoch(train) [60][320/940] lr: 1.0000e-03 eta: 5:22:59 time: 0.4748 data_time: 0.0296 memory: 21547 grad_norm: 4.5293 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3146 loss: 1.3146 2022/10/10 05:57:01 - mmengine - INFO - Epoch(train) [60][340/940] lr: 1.0000e-03 eta: 5:22:49 time: 0.4801 data_time: 0.0318 memory: 21547 grad_norm: 4.4019 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2182 loss: 1.2182 2022/10/10 05:57:12 - mmengine - INFO - Epoch(train) [60][360/940] lr: 1.0000e-03 eta: 5:22:39 time: 0.5204 data_time: 0.0281 memory: 21547 grad_norm: 4.4803 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3161 loss: 1.3161 2022/10/10 05:57:22 - mmengine - INFO - Epoch(train) [60][380/940] lr: 1.0000e-03 eta: 5:22:29 time: 0.5152 data_time: 0.0281 memory: 21547 grad_norm: 4.4384 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3567 loss: 1.3567 2022/10/10 05:57:33 - mmengine - INFO - Epoch(train) [60][400/940] lr: 1.0000e-03 eta: 5:22:19 time: 0.5483 data_time: 0.0239 memory: 21547 grad_norm: 4.4190 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1709 loss: 1.1709 2022/10/10 05:57:43 - mmengine - INFO - Epoch(train) [60][420/940] lr: 1.0000e-03 eta: 5:22:08 time: 0.4745 data_time: 0.0278 memory: 21547 grad_norm: 4.4181 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2959 loss: 1.2959 2022/10/10 05:57:52 - mmengine - INFO - Epoch(train) [60][440/940] lr: 1.0000e-03 eta: 5:21:58 time: 0.4868 data_time: 0.0266 memory: 21547 grad_norm: 4.4846 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2861 loss: 1.2861 2022/10/10 05:58:02 - mmengine - INFO - Epoch(train) [60][460/940] lr: 1.0000e-03 eta: 5:21:48 time: 0.4954 data_time: 0.0310 memory: 21547 grad_norm: 4.5490 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3020 loss: 1.3020 2022/10/10 05:58:12 - mmengine - INFO - Epoch(train) [60][480/940] lr: 1.0000e-03 eta: 5:21:37 time: 0.4857 data_time: 0.0297 memory: 21547 grad_norm: 4.5195 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2556 loss: 1.2556 2022/10/10 05:58:24 - mmengine - INFO - Epoch(train) [60][500/940] lr: 1.0000e-03 eta: 5:21:29 time: 0.6103 data_time: 0.1336 memory: 21547 grad_norm: 4.3226 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1958 loss: 1.1958 2022/10/10 05:58:35 - mmengine - INFO - Epoch(train) [60][520/940] lr: 1.0000e-03 eta: 5:21:19 time: 0.5438 data_time: 0.1596 memory: 21547 grad_norm: 4.5493 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2911 loss: 1.2911 2022/10/10 05:58:44 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 05:58:44 - mmengine - INFO - Epoch(train) [60][540/940] lr: 1.0000e-03 eta: 5:21:08 time: 0.4540 data_time: 0.0768 memory: 21547 grad_norm: 4.4518 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2488 loss: 1.2488 2022/10/10 05:58:55 - mmengine - INFO - Epoch(train) [60][560/940] lr: 1.0000e-03 eta: 5:20:59 time: 0.5638 data_time: 0.1930 memory: 21547 grad_norm: 4.4680 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1303 loss: 1.1303 2022/10/10 05:59:05 - mmengine - INFO - Epoch(train) [60][580/940] lr: 1.0000e-03 eta: 5:20:48 time: 0.4886 data_time: 0.1051 memory: 21547 grad_norm: 4.5934 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.1079 loss: 1.1079 2022/10/10 05:59:15 - mmengine - INFO - Epoch(train) [60][600/940] lr: 1.0000e-03 eta: 5:20:38 time: 0.4984 data_time: 0.1142 memory: 21547 grad_norm: 4.4158 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2135 loss: 1.2135 2022/10/10 05:59:25 - mmengine - INFO - Epoch(train) [60][620/940] lr: 1.0000e-03 eta: 5:20:28 time: 0.4980 data_time: 0.1105 memory: 21547 grad_norm: 4.4434 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2138 loss: 1.2138 2022/10/10 05:59:36 - mmengine - INFO - Epoch(train) [60][640/940] lr: 1.0000e-03 eta: 5:20:18 time: 0.5353 data_time: 0.1508 memory: 21547 grad_norm: 4.4667 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2020 loss: 1.2020 2022/10/10 05:59:45 - mmengine - INFO - Epoch(train) [60][660/940] lr: 1.0000e-03 eta: 5:20:07 time: 0.4607 data_time: 0.0751 memory: 21547 grad_norm: 4.5256 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2130 loss: 1.2130 2022/10/10 05:59:54 - mmengine - INFO - Epoch(train) [60][680/940] lr: 1.0000e-03 eta: 5:19:57 time: 0.4696 data_time: 0.0888 memory: 21547 grad_norm: 4.4892 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1775 loss: 1.1775 2022/10/10 06:00:04 - mmengine - INFO - Epoch(train) [60][700/940] lr: 1.0000e-03 eta: 5:19:46 time: 0.5044 data_time: 0.1227 memory: 21547 grad_norm: 4.4207 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1937 loss: 1.1937 2022/10/10 06:00:14 - mmengine - INFO - Epoch(train) [60][720/940] lr: 1.0000e-03 eta: 5:19:36 time: 0.4638 data_time: 0.0735 memory: 21547 grad_norm: 4.3195 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2104 loss: 1.2104 2022/10/10 06:00:24 - mmengine - INFO - Epoch(train) [60][740/940] lr: 1.0000e-03 eta: 5:19:26 time: 0.5106 data_time: 0.0458 memory: 21547 grad_norm: 4.4197 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2621 loss: 1.2621 2022/10/10 06:00:34 - mmengine - INFO - Epoch(train) [60][760/940] lr: 1.0000e-03 eta: 5:19:15 time: 0.5064 data_time: 0.0300 memory: 21547 grad_norm: 4.4195 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1684 loss: 1.1684 2022/10/10 06:00:44 - mmengine - INFO - Epoch(train) [60][780/940] lr: 1.0000e-03 eta: 5:19:05 time: 0.4765 data_time: 0.0270 memory: 21547 grad_norm: 4.4859 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2288 loss: 1.2288 2022/10/10 06:00:55 - mmengine - INFO - Epoch(train) [60][800/940] lr: 1.0000e-03 eta: 5:18:56 time: 0.5753 data_time: 0.0324 memory: 21547 grad_norm: 4.4837 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.2672 loss: 1.2672 2022/10/10 06:01:05 - mmengine - INFO - Epoch(train) [60][820/940] lr: 1.0000e-03 eta: 5:18:45 time: 0.4825 data_time: 0.0247 memory: 21547 grad_norm: 4.3867 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1285 loss: 1.1285 2022/10/10 06:01:15 - mmengine - INFO - Epoch(train) [60][840/940] lr: 1.0000e-03 eta: 5:18:35 time: 0.4921 data_time: 0.0298 memory: 21547 grad_norm: 4.4857 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.2133 loss: 1.2133 2022/10/10 06:01:25 - mmengine - INFO - Epoch(train) [60][860/940] lr: 1.0000e-03 eta: 5:18:25 time: 0.5137 data_time: 0.0263 memory: 21547 grad_norm: 4.4644 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1935 loss: 1.1935 2022/10/10 06:01:36 - mmengine - INFO - Epoch(train) [60][880/940] lr: 1.0000e-03 eta: 5:18:15 time: 0.5369 data_time: 0.0335 memory: 21547 grad_norm: 4.5210 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2598 loss: 1.2598 2022/10/10 06:01:45 - mmengine - INFO - Epoch(train) [60][900/940] lr: 1.0000e-03 eta: 5:18:04 time: 0.4637 data_time: 0.0290 memory: 21547 grad_norm: 4.4634 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2183 loss: 1.2183 2022/10/10 06:01:56 - mmengine - INFO - Epoch(train) [60][920/940] lr: 1.0000e-03 eta: 5:17:55 time: 0.5404 data_time: 0.0268 memory: 21547 grad_norm: 4.3610 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2852 loss: 1.2852 2022/10/10 06:02:05 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 06:02:05 - mmengine - INFO - Epoch(train) [60][940/940] lr: 1.0000e-03 eta: 5:17:44 time: 0.4404 data_time: 0.0266 memory: 21547 grad_norm: 4.7458 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.3557 loss: 1.3557 2022/10/10 06:02:05 - mmengine - INFO - Saving checkpoint at 60 epochs 2022/10/10 06:02:18 - mmengine - INFO - Epoch(val) [60][20/78] eta: 0:00:35 time: 0.6089 data_time: 0.5037 memory: 3269 2022/10/10 06:02:26 - mmengine - INFO - Epoch(val) [60][40/78] eta: 0:00:15 time: 0.4178 data_time: 0.3132 memory: 3269 2022/10/10 06:02:37 - mmengine - INFO - Epoch(val) [60][60/78] eta: 0:00:10 time: 0.5573 data_time: 0.4528 memory: 3269 2022/10/10 06:02:46 - mmengine - INFO - Epoch(val) [60][78/78] acc/top1: 0.6774 acc/top5: 0.8708 acc/mean1: 0.6773 2022/10/10 06:02:47 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_50.pth is removed 2022/10/10 06:02:47 - mmengine - INFO - The best checkpoint with 0.6774 acc/top1 at 60 epoch is saved to best_acc/top1_epoch_60.pth. 2022/10/10 06:03:00 - mmengine - INFO - Epoch(train) [61][20/940] lr: 1.0000e-03 eta: 5:17:35 time: 0.6546 data_time: 0.2734 memory: 21547 grad_norm: 4.5366 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2428 loss: 1.2428 2022/10/10 06:03:10 - mmengine - INFO - Epoch(train) [61][40/940] lr: 1.0000e-03 eta: 5:17:25 time: 0.4880 data_time: 0.1172 memory: 21547 grad_norm: 4.4595 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2566 loss: 1.2566 2022/10/10 06:03:21 - mmengine - INFO - Epoch(train) [61][60/940] lr: 1.0000e-03 eta: 5:17:15 time: 0.5352 data_time: 0.1621 memory: 21547 grad_norm: 4.4675 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2588 loss: 1.2588 2022/10/10 06:03:30 - mmengine - INFO - Epoch(train) [61][80/940] lr: 1.0000e-03 eta: 5:17:05 time: 0.4725 data_time: 0.0943 memory: 21547 grad_norm: 4.3441 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1472 loss: 1.1472 2022/10/10 06:03:40 - mmengine - INFO - Epoch(train) [61][100/940] lr: 1.0000e-03 eta: 5:16:55 time: 0.5060 data_time: 0.0332 memory: 21547 grad_norm: 4.4436 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1930 loss: 1.1930 2022/10/10 06:03:51 - mmengine - INFO - Epoch(train) [61][120/940] lr: 1.0000e-03 eta: 5:16:45 time: 0.5248 data_time: 0.0254 memory: 21547 grad_norm: 4.3674 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1825 loss: 1.1825 2022/10/10 06:04:01 - mmengine - INFO - Epoch(train) [61][140/940] lr: 1.0000e-03 eta: 5:16:35 time: 0.5231 data_time: 0.0312 memory: 21547 grad_norm: 4.5534 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3124 loss: 1.3124 2022/10/10 06:04:10 - mmengine - INFO - Epoch(train) [61][160/940] lr: 1.0000e-03 eta: 5:16:24 time: 0.4528 data_time: 0.0243 memory: 21547 grad_norm: 4.4990 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3604 loss: 1.3604 2022/10/10 06:04:21 - mmengine - INFO - Epoch(train) [61][180/940] lr: 1.0000e-03 eta: 5:16:14 time: 0.5346 data_time: 0.0283 memory: 21547 grad_norm: 4.5304 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3975 loss: 1.3975 2022/10/10 06:04:30 - mmengine - INFO - Epoch(train) [61][200/940] lr: 1.0000e-03 eta: 5:16:03 time: 0.4670 data_time: 0.0276 memory: 21547 grad_norm: 4.3978 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1817 loss: 1.1817 2022/10/10 06:04:41 - mmengine - INFO - Epoch(train) [61][220/940] lr: 1.0000e-03 eta: 5:15:54 time: 0.5254 data_time: 0.0266 memory: 21547 grad_norm: 4.5322 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3155 loss: 1.3155 2022/10/10 06:04:51 - mmengine - INFO - Epoch(train) [61][240/940] lr: 1.0000e-03 eta: 5:15:44 time: 0.5194 data_time: 0.0229 memory: 21547 grad_norm: 4.4974 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3158 loss: 1.3158 2022/10/10 06:05:01 - mmengine - INFO - Epoch(train) [61][260/940] lr: 1.0000e-03 eta: 5:15:33 time: 0.5102 data_time: 0.0239 memory: 21547 grad_norm: 4.5106 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1913 loss: 1.1913 2022/10/10 06:05:11 - mmengine - INFO - Epoch(train) [61][280/940] lr: 1.0000e-03 eta: 5:15:23 time: 0.4637 data_time: 0.0245 memory: 21547 grad_norm: 4.4612 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3714 loss: 1.3714 2022/10/10 06:05:21 - mmengine - INFO - Epoch(train) [61][300/940] lr: 1.0000e-03 eta: 5:15:12 time: 0.4965 data_time: 0.0284 memory: 21547 grad_norm: 4.4851 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3028 loss: 1.3028 2022/10/10 06:05:31 - mmengine - INFO - Epoch(train) [61][320/940] lr: 1.0000e-03 eta: 5:15:02 time: 0.5027 data_time: 0.0235 memory: 21547 grad_norm: 4.5323 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2877 loss: 1.2877 2022/10/10 06:05:41 - mmengine - INFO - Epoch(train) [61][340/940] lr: 1.0000e-03 eta: 5:14:52 time: 0.5173 data_time: 0.0327 memory: 21547 grad_norm: 4.4778 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3285 loss: 1.3285 2022/10/10 06:05:51 - mmengine - INFO - Epoch(train) [61][360/940] lr: 1.0000e-03 eta: 5:14:42 time: 0.4740 data_time: 0.0273 memory: 21547 grad_norm: 4.4153 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3310 loss: 1.3310 2022/10/10 06:06:00 - mmengine - INFO - Epoch(train) [61][380/940] lr: 1.0000e-03 eta: 5:14:31 time: 0.4935 data_time: 0.0292 memory: 21547 grad_norm: 4.4217 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2986 loss: 1.2986 2022/10/10 06:06:11 - mmengine - INFO - Epoch(train) [61][400/940] lr: 1.0000e-03 eta: 5:14:21 time: 0.5059 data_time: 0.0334 memory: 21547 grad_norm: 4.4207 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2597 loss: 1.2597 2022/10/10 06:06:21 - mmengine - INFO - Epoch(train) [61][420/940] lr: 1.0000e-03 eta: 5:14:11 time: 0.5164 data_time: 0.0292 memory: 21547 grad_norm: 4.4626 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1658 loss: 1.1658 2022/10/10 06:06:31 - mmengine - INFO - Epoch(train) [61][440/940] lr: 1.0000e-03 eta: 5:14:01 time: 0.4953 data_time: 0.0241 memory: 21547 grad_norm: 4.5079 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2161 loss: 1.2161 2022/10/10 06:06:42 - mmengine - INFO - Epoch(train) [61][460/940] lr: 1.0000e-03 eta: 5:13:51 time: 0.5538 data_time: 0.0277 memory: 21547 grad_norm: 4.4334 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2771 loss: 1.2771 2022/10/10 06:06:51 - mmengine - INFO - Epoch(train) [61][480/940] lr: 1.0000e-03 eta: 5:13:41 time: 0.4643 data_time: 0.0276 memory: 21547 grad_norm: 4.6065 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3409 loss: 1.3409 2022/10/10 06:07:02 - mmengine - INFO - Epoch(train) [61][500/940] lr: 1.0000e-03 eta: 5:13:31 time: 0.5210 data_time: 0.0240 memory: 21547 grad_norm: 4.3723 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1824 loss: 1.1824 2022/10/10 06:07:11 - mmengine - INFO - Epoch(train) [61][520/940] lr: 1.0000e-03 eta: 5:13:20 time: 0.4956 data_time: 0.0303 memory: 21547 grad_norm: 4.6282 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2785 loss: 1.2785 2022/10/10 06:07:22 - mmengine - INFO - Epoch(train) [61][540/940] lr: 1.0000e-03 eta: 5:13:11 time: 0.5278 data_time: 0.0227 memory: 21547 grad_norm: 4.4938 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3032 loss: 1.3032 2022/10/10 06:07:32 - mmengine - INFO - Epoch(train) [61][560/940] lr: 1.0000e-03 eta: 5:13:00 time: 0.5047 data_time: 0.0342 memory: 21547 grad_norm: 4.5288 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3291 loss: 1.3291 2022/10/10 06:07:42 - mmengine - INFO - Epoch(train) [61][580/940] lr: 1.0000e-03 eta: 5:12:50 time: 0.5146 data_time: 0.0322 memory: 21547 grad_norm: 4.4785 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2519 loss: 1.2519 2022/10/10 06:07:52 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 06:07:52 - mmengine - INFO - Epoch(train) [61][600/940] lr: 1.0000e-03 eta: 5:12:40 time: 0.4860 data_time: 0.0250 memory: 21547 grad_norm: 4.5278 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2599 loss: 1.2599 2022/10/10 06:08:03 - mmengine - INFO - Epoch(train) [61][620/940] lr: 1.0000e-03 eta: 5:12:30 time: 0.5485 data_time: 0.0280 memory: 21547 grad_norm: 4.4324 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2457 loss: 1.2457 2022/10/10 06:08:12 - mmengine - INFO - Epoch(train) [61][640/940] lr: 1.0000e-03 eta: 5:12:20 time: 0.4649 data_time: 0.0252 memory: 21547 grad_norm: 4.5161 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1926 loss: 1.1926 2022/10/10 06:08:24 - mmengine - INFO - Epoch(train) [61][660/940] lr: 1.0000e-03 eta: 5:12:10 time: 0.5595 data_time: 0.0331 memory: 21547 grad_norm: 4.4653 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2490 loss: 1.2490 2022/10/10 06:08:32 - mmengine - INFO - Epoch(train) [61][680/940] lr: 1.0000e-03 eta: 5:11:59 time: 0.4435 data_time: 0.0258 memory: 21547 grad_norm: 4.3846 top1_acc: 0.8438 top5_acc: 0.8438 loss_cls: 1.3042 loss: 1.3042 2022/10/10 06:08:43 - mmengine - INFO - Epoch(train) [61][700/940] lr: 1.0000e-03 eta: 5:11:50 time: 0.5477 data_time: 0.0265 memory: 21547 grad_norm: 4.5228 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2212 loss: 1.2212 2022/10/10 06:08:52 - mmengine - INFO - Epoch(train) [61][720/940] lr: 1.0000e-03 eta: 5:11:39 time: 0.4356 data_time: 0.0241 memory: 21547 grad_norm: 4.4544 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2853 loss: 1.2853 2022/10/10 06:09:02 - mmengine - INFO - Epoch(train) [61][740/940] lr: 1.0000e-03 eta: 5:11:28 time: 0.5043 data_time: 0.0239 memory: 21547 grad_norm: 4.4080 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2722 loss: 1.2722 2022/10/10 06:09:12 - mmengine - INFO - Epoch(train) [61][760/940] lr: 1.0000e-03 eta: 5:11:18 time: 0.4684 data_time: 0.0272 memory: 21547 grad_norm: 4.4814 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3186 loss: 1.3186 2022/10/10 06:09:23 - mmengine - INFO - Epoch(train) [61][780/940] lr: 1.0000e-03 eta: 5:11:08 time: 0.5496 data_time: 0.0390 memory: 21547 grad_norm: 4.4632 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2400 loss: 1.2400 2022/10/10 06:09:32 - mmengine - INFO - Epoch(train) [61][800/940] lr: 1.0000e-03 eta: 5:10:58 time: 0.4911 data_time: 0.0231 memory: 21547 grad_norm: 4.4654 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2642 loss: 1.2642 2022/10/10 06:09:42 - mmengine - INFO - Epoch(train) [61][820/940] lr: 1.0000e-03 eta: 5:10:48 time: 0.4995 data_time: 0.0816 memory: 21547 grad_norm: 4.4310 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2051 loss: 1.2051 2022/10/10 06:09:53 - mmengine - INFO - Epoch(train) [61][840/940] lr: 1.0000e-03 eta: 5:10:37 time: 0.5095 data_time: 0.1201 memory: 21547 grad_norm: 4.3643 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2273 loss: 1.2273 2022/10/10 06:10:03 - mmengine - INFO - Epoch(train) [61][860/940] lr: 1.0000e-03 eta: 5:10:27 time: 0.5047 data_time: 0.0322 memory: 21547 grad_norm: 4.4555 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3241 loss: 1.3241 2022/10/10 06:10:12 - mmengine - INFO - Epoch(train) [61][880/940] lr: 1.0000e-03 eta: 5:10:17 time: 0.4863 data_time: 0.0249 memory: 21547 grad_norm: 4.5039 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3242 loss: 1.3242 2022/10/10 06:10:23 - mmengine - INFO - Epoch(train) [61][900/940] lr: 1.0000e-03 eta: 5:10:07 time: 0.5532 data_time: 0.0293 memory: 21547 grad_norm: 4.4127 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2671 loss: 1.2671 2022/10/10 06:10:32 - mmengine - INFO - Epoch(train) [61][920/940] lr: 1.0000e-03 eta: 5:09:56 time: 0.4491 data_time: 0.0299 memory: 21547 grad_norm: 4.5895 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2034 loss: 1.2034 2022/10/10 06:10:42 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 06:10:42 - mmengine - INFO - Epoch(train) [61][940/940] lr: 1.0000e-03 eta: 5:09:46 time: 0.4667 data_time: 0.0234 memory: 21547 grad_norm: 4.8555 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.3350 loss: 1.3350 2022/10/10 06:10:54 - mmengine - INFO - Epoch(val) [61][20/78] eta: 0:00:34 time: 0.6028 data_time: 0.4940 memory: 3269 2022/10/10 06:11:02 - mmengine - INFO - Epoch(val) [61][40/78] eta: 0:00:16 time: 0.4250 data_time: 0.3203 memory: 3269 2022/10/10 06:11:14 - mmengine - INFO - Epoch(val) [61][60/78] eta: 0:00:10 time: 0.5637 data_time: 0.4566 memory: 3269 2022/10/10 06:11:23 - mmengine - INFO - Epoch(val) [61][78/78] acc/top1: 0.6749 acc/top5: 0.8703 acc/mean1: 0.6748 2022/10/10 06:11:37 - mmengine - INFO - Epoch(train) [62][20/940] lr: 1.0000e-03 eta: 5:09:38 time: 0.7060 data_time: 0.3040 memory: 21547 grad_norm: 4.4386 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2260 loss: 1.2260 2022/10/10 06:11:47 - mmengine - INFO - Epoch(train) [62][40/940] lr: 1.0000e-03 eta: 5:09:28 time: 0.4837 data_time: 0.1124 memory: 21547 grad_norm: 4.4025 top1_acc: 0.5312 top5_acc: 0.9375 loss_cls: 1.1211 loss: 1.1211 2022/10/10 06:11:58 - mmengine - INFO - Epoch(train) [62][60/940] lr: 1.0000e-03 eta: 5:09:18 time: 0.5260 data_time: 0.1479 memory: 21547 grad_norm: 4.4597 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2653 loss: 1.2653 2022/10/10 06:12:07 - mmengine - INFO - Epoch(train) [62][80/940] lr: 1.0000e-03 eta: 5:09:07 time: 0.4679 data_time: 0.0829 memory: 21547 grad_norm: 4.4117 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1907 loss: 1.1907 2022/10/10 06:12:18 - mmengine - INFO - Epoch(train) [62][100/940] lr: 1.0000e-03 eta: 5:08:58 time: 0.5564 data_time: 0.0735 memory: 21547 grad_norm: 4.5499 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2916 loss: 1.2916 2022/10/10 06:12:28 - mmengine - INFO - Epoch(train) [62][120/940] lr: 1.0000e-03 eta: 5:08:47 time: 0.4980 data_time: 0.0272 memory: 21547 grad_norm: 4.4800 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1805 loss: 1.1805 2022/10/10 06:12:39 - mmengine - INFO - Epoch(train) [62][140/940] lr: 1.0000e-03 eta: 5:08:38 time: 0.5288 data_time: 0.0273 memory: 21547 grad_norm: 4.4755 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1637 loss: 1.1637 2022/10/10 06:12:48 - mmengine - INFO - Epoch(train) [62][160/940] lr: 1.0000e-03 eta: 5:08:27 time: 0.4556 data_time: 0.0260 memory: 21547 grad_norm: 4.5581 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2948 loss: 1.2948 2022/10/10 06:12:59 - mmengine - INFO - Epoch(train) [62][180/940] lr: 1.0000e-03 eta: 5:08:17 time: 0.5395 data_time: 0.0479 memory: 21547 grad_norm: 4.4844 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1869 loss: 1.1869 2022/10/10 06:13:08 - mmengine - INFO - Epoch(train) [62][200/940] lr: 1.0000e-03 eta: 5:08:07 time: 0.4919 data_time: 0.0248 memory: 21547 grad_norm: 4.5553 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2837 loss: 1.2837 2022/10/10 06:13:18 - mmengine - INFO - Epoch(train) [62][220/940] lr: 1.0000e-03 eta: 5:07:57 time: 0.5027 data_time: 0.0255 memory: 21547 grad_norm: 4.4573 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3561 loss: 1.3561 2022/10/10 06:13:28 - mmengine - INFO - Epoch(train) [62][240/940] lr: 1.0000e-03 eta: 5:07:46 time: 0.4891 data_time: 0.0291 memory: 21547 grad_norm: 4.5495 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2015 loss: 1.2015 2022/10/10 06:13:38 - mmengine - INFO - Epoch(train) [62][260/940] lr: 1.0000e-03 eta: 5:07:36 time: 0.5084 data_time: 0.0286 memory: 21547 grad_norm: 4.5718 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1434 loss: 1.1434 2022/10/10 06:13:48 - mmengine - INFO - Epoch(train) [62][280/940] lr: 1.0000e-03 eta: 5:07:25 time: 0.4575 data_time: 0.0269 memory: 21547 grad_norm: 4.3843 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2711 loss: 1.2711 2022/10/10 06:13:57 - mmengine - INFO - Epoch(train) [62][300/940] lr: 1.0000e-03 eta: 5:07:15 time: 0.4888 data_time: 0.0310 memory: 21547 grad_norm: 4.4369 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2155 loss: 1.2155 2022/10/10 06:14:07 - mmengine - INFO - Epoch(train) [62][320/940] lr: 1.0000e-03 eta: 5:07:05 time: 0.4904 data_time: 0.0304 memory: 21547 grad_norm: 4.5068 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2891 loss: 1.2891 2022/10/10 06:14:18 - mmengine - INFO - Epoch(train) [62][340/940] lr: 1.0000e-03 eta: 5:06:55 time: 0.5486 data_time: 0.0320 memory: 21547 grad_norm: 4.4743 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2750 loss: 1.2750 2022/10/10 06:14:28 - mmengine - INFO - Epoch(train) [62][360/940] lr: 1.0000e-03 eta: 5:06:45 time: 0.5178 data_time: 0.0264 memory: 21547 grad_norm: 4.4751 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0984 loss: 1.0984 2022/10/10 06:14:39 - mmengine - INFO - Epoch(train) [62][380/940] lr: 1.0000e-03 eta: 5:06:35 time: 0.5281 data_time: 0.0345 memory: 21547 grad_norm: 4.4839 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2835 loss: 1.2835 2022/10/10 06:14:48 - mmengine - INFO - Epoch(train) [62][400/940] lr: 1.0000e-03 eta: 5:06:24 time: 0.4407 data_time: 0.0260 memory: 21547 grad_norm: 4.4324 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2249 loss: 1.2249 2022/10/10 06:14:59 - mmengine - INFO - Epoch(train) [62][420/940] lr: 1.0000e-03 eta: 5:06:15 time: 0.5566 data_time: 0.0286 memory: 21547 grad_norm: 4.4843 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3346 loss: 1.3346 2022/10/10 06:15:09 - mmengine - INFO - Epoch(train) [62][440/940] lr: 1.0000e-03 eta: 5:06:04 time: 0.4969 data_time: 0.0281 memory: 21547 grad_norm: 4.4316 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2479 loss: 1.2479 2022/10/10 06:15:19 - mmengine - INFO - Epoch(train) [62][460/940] lr: 1.0000e-03 eta: 5:05:54 time: 0.5157 data_time: 0.0285 memory: 21547 grad_norm: 4.6016 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4277 loss: 1.4277 2022/10/10 06:15:30 - mmengine - INFO - Epoch(train) [62][480/940] lr: 1.0000e-03 eta: 5:05:44 time: 0.5143 data_time: 0.0334 memory: 21547 grad_norm: 4.5579 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2871 loss: 1.2871 2022/10/10 06:15:40 - mmengine - INFO - Epoch(train) [62][500/940] lr: 1.0000e-03 eta: 5:05:34 time: 0.5269 data_time: 0.0261 memory: 21547 grad_norm: 4.3522 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1645 loss: 1.1645 2022/10/10 06:15:50 - mmengine - INFO - Epoch(train) [62][520/940] lr: 1.0000e-03 eta: 5:05:24 time: 0.5009 data_time: 0.0282 memory: 21547 grad_norm: 4.4715 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2502 loss: 1.2502 2022/10/10 06:16:00 - mmengine - INFO - Epoch(train) [62][540/940] lr: 1.0000e-03 eta: 5:05:14 time: 0.4814 data_time: 0.0253 memory: 21547 grad_norm: 4.4099 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2415 loss: 1.2415 2022/10/10 06:16:09 - mmengine - INFO - Epoch(train) [62][560/940] lr: 1.0000e-03 eta: 5:05:03 time: 0.4409 data_time: 0.0249 memory: 21547 grad_norm: 4.5448 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2076 loss: 1.2076 2022/10/10 06:16:18 - mmengine - INFO - Epoch(train) [62][580/940] lr: 1.0000e-03 eta: 5:04:52 time: 0.4874 data_time: 0.0282 memory: 21547 grad_norm: 4.5776 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2383 loss: 1.2383 2022/10/10 06:16:28 - mmengine - INFO - Epoch(train) [62][600/940] lr: 1.0000e-03 eta: 5:04:42 time: 0.4970 data_time: 0.0303 memory: 21547 grad_norm: 4.4484 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2374 loss: 1.2374 2022/10/10 06:16:39 - mmengine - INFO - Epoch(train) [62][620/940] lr: 1.0000e-03 eta: 5:04:32 time: 0.5242 data_time: 0.0301 memory: 21547 grad_norm: 4.5049 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3072 loss: 1.3072 2022/10/10 06:16:50 - mmengine - INFO - Epoch(train) [62][640/940] lr: 1.0000e-03 eta: 5:04:22 time: 0.5490 data_time: 0.0255 memory: 21547 grad_norm: 4.4954 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2431 loss: 1.2431 2022/10/10 06:17:00 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 06:17:00 - mmengine - INFO - Epoch(train) [62][660/940] lr: 1.0000e-03 eta: 5:04:12 time: 0.4970 data_time: 0.0339 memory: 21547 grad_norm: 4.4735 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3929 loss: 1.3929 2022/10/10 06:17:10 - mmengine - INFO - Epoch(train) [62][680/940] lr: 1.0000e-03 eta: 5:04:02 time: 0.5180 data_time: 0.0284 memory: 21547 grad_norm: 4.5393 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1865 loss: 1.1865 2022/10/10 06:17:19 - mmengine - INFO - Epoch(train) [62][700/940] lr: 1.0000e-03 eta: 5:03:52 time: 0.4638 data_time: 0.0273 memory: 21547 grad_norm: 4.5671 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3060 loss: 1.3060 2022/10/10 06:17:29 - mmengine - INFO - Epoch(train) [62][720/940] lr: 1.0000e-03 eta: 5:03:41 time: 0.4794 data_time: 0.0317 memory: 21547 grad_norm: 4.5155 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2650 loss: 1.2650 2022/10/10 06:17:38 - mmengine - INFO - Epoch(train) [62][740/940] lr: 1.0000e-03 eta: 5:03:31 time: 0.4783 data_time: 0.0291 memory: 21547 grad_norm: 4.4870 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2910 loss: 1.2910 2022/10/10 06:17:50 - mmengine - INFO - Epoch(train) [62][760/940] lr: 1.0000e-03 eta: 5:03:21 time: 0.5576 data_time: 0.0270 memory: 21547 grad_norm: 4.5384 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3214 loss: 1.3214 2022/10/10 06:17:59 - mmengine - INFO - Epoch(train) [62][780/940] lr: 1.0000e-03 eta: 5:03:10 time: 0.4739 data_time: 0.0297 memory: 21547 grad_norm: 4.5225 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3435 loss: 1.3435 2022/10/10 06:18:10 - mmengine - INFO - Epoch(train) [62][800/940] lr: 1.0000e-03 eta: 5:03:01 time: 0.5649 data_time: 0.0308 memory: 21547 grad_norm: 4.5400 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2572 loss: 1.2572 2022/10/10 06:18:20 - mmengine - INFO - Epoch(train) [62][820/940] lr: 1.0000e-03 eta: 5:02:50 time: 0.4650 data_time: 0.0271 memory: 21547 grad_norm: 4.4675 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1522 loss: 1.1522 2022/10/10 06:18:29 - mmengine - INFO - Epoch(train) [62][840/940] lr: 1.0000e-03 eta: 5:02:40 time: 0.4920 data_time: 0.0290 memory: 21547 grad_norm: 4.5472 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2458 loss: 1.2458 2022/10/10 06:18:38 - mmengine - INFO - Epoch(train) [62][860/940] lr: 1.0000e-03 eta: 5:02:29 time: 0.4407 data_time: 0.0240 memory: 21547 grad_norm: 4.5926 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2782 loss: 1.2782 2022/10/10 06:18:48 - mmengine - INFO - Epoch(train) [62][880/940] lr: 1.0000e-03 eta: 5:02:19 time: 0.5013 data_time: 0.0318 memory: 21547 grad_norm: 4.5280 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2762 loss: 1.2762 2022/10/10 06:18:58 - mmengine - INFO - Epoch(train) [62][900/940] lr: 1.0000e-03 eta: 5:02:09 time: 0.5056 data_time: 0.0283 memory: 21547 grad_norm: 4.5416 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2657 loss: 1.2657 2022/10/10 06:19:09 - mmengine - INFO - Epoch(train) [62][920/940] lr: 1.0000e-03 eta: 5:01:59 time: 0.5169 data_time: 0.0299 memory: 21547 grad_norm: 4.4771 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2198 loss: 1.2198 2022/10/10 06:19:18 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 06:19:18 - mmengine - INFO - Epoch(train) [62][940/940] lr: 1.0000e-03 eta: 5:01:48 time: 0.4417 data_time: 0.0234 memory: 21547 grad_norm: 4.7814 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.3329 loss: 1.3329 2022/10/10 06:19:30 - mmengine - INFO - Epoch(val) [62][20/78] eta: 0:00:35 time: 0.6085 data_time: 0.4996 memory: 3269 2022/10/10 06:19:38 - mmengine - INFO - Epoch(val) [62][40/78] eta: 0:00:16 time: 0.4229 data_time: 0.3138 memory: 3269 2022/10/10 06:19:50 - mmengine - INFO - Epoch(val) [62][60/78] eta: 0:00:10 time: 0.5685 data_time: 0.4627 memory: 3269 2022/10/10 06:19:59 - mmengine - INFO - Epoch(val) [62][78/78] acc/top1: 0.6789 acc/top5: 0.8715 acc/mean1: 0.6787 2022/10/10 06:19:59 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_60.pth is removed 2022/10/10 06:20:00 - mmengine - INFO - The best checkpoint with 0.6789 acc/top1 at 62 epoch is saved to best_acc/top1_epoch_62.pth. 2022/10/10 06:20:13 - mmengine - INFO - Epoch(train) [63][20/940] lr: 1.0000e-03 eta: 5:01:40 time: 0.6684 data_time: 0.2758 memory: 21547 grad_norm: 4.3843 top1_acc: 0.5625 top5_acc: 0.9688 loss_cls: 1.2711 loss: 1.2711 2022/10/10 06:20:23 - mmengine - INFO - Epoch(train) [63][40/940] lr: 1.0000e-03 eta: 5:01:29 time: 0.4910 data_time: 0.0767 memory: 21547 grad_norm: 4.4793 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3101 loss: 1.3101 2022/10/10 06:20:34 - mmengine - INFO - Epoch(train) [63][60/940] lr: 1.0000e-03 eta: 5:01:19 time: 0.5224 data_time: 0.0268 memory: 21547 grad_norm: 4.5199 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1834 loss: 1.1834 2022/10/10 06:20:43 - mmengine - INFO - Epoch(train) [63][80/940] lr: 1.0000e-03 eta: 5:01:09 time: 0.4726 data_time: 0.0238 memory: 21547 grad_norm: 4.3855 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2083 loss: 1.2083 2022/10/10 06:20:54 - mmengine - INFO - Epoch(train) [63][100/940] lr: 1.0000e-03 eta: 5:00:59 time: 0.5403 data_time: 0.0283 memory: 21547 grad_norm: 4.5501 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1912 loss: 1.1912 2022/10/10 06:21:04 - mmengine - INFO - Epoch(train) [63][120/940] lr: 1.0000e-03 eta: 5:00:49 time: 0.5086 data_time: 0.0273 memory: 21547 grad_norm: 4.4923 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1935 loss: 1.1935 2022/10/10 06:21:14 - mmengine - INFO - Epoch(train) [63][140/940] lr: 1.0000e-03 eta: 5:00:39 time: 0.5213 data_time: 0.0285 memory: 21547 grad_norm: 4.4432 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1680 loss: 1.1680 2022/10/10 06:21:24 - mmengine - INFO - Epoch(train) [63][160/940] lr: 1.0000e-03 eta: 5:00:29 time: 0.4864 data_time: 0.0357 memory: 21547 grad_norm: 4.5322 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3106 loss: 1.3106 2022/10/10 06:21:35 - mmengine - INFO - Epoch(train) [63][180/940] lr: 1.0000e-03 eta: 5:00:19 time: 0.5509 data_time: 0.0300 memory: 21547 grad_norm: 4.5434 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.2680 loss: 1.2680 2022/10/10 06:21:44 - mmengine - INFO - Epoch(train) [63][200/940] lr: 1.0000e-03 eta: 5:00:08 time: 0.4488 data_time: 0.0219 memory: 21547 grad_norm: 4.5205 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2850 loss: 1.2850 2022/10/10 06:21:55 - mmengine - INFO - Epoch(train) [63][220/940] lr: 1.0000e-03 eta: 4:59:58 time: 0.5475 data_time: 0.0261 memory: 21547 grad_norm: 4.4641 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1662 loss: 1.1662 2022/10/10 06:22:04 - mmengine - INFO - Epoch(train) [63][240/940] lr: 1.0000e-03 eta: 4:59:47 time: 0.4387 data_time: 0.0273 memory: 21547 grad_norm: 4.6111 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2190 loss: 1.2190 2022/10/10 06:22:14 - mmengine - INFO - Epoch(train) [63][260/940] lr: 1.0000e-03 eta: 4:59:38 time: 0.5244 data_time: 0.0327 memory: 21547 grad_norm: 4.4310 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2987 loss: 1.2987 2022/10/10 06:22:24 - mmengine - INFO - Epoch(train) [63][280/940] lr: 1.0000e-03 eta: 4:59:27 time: 0.4601 data_time: 0.0256 memory: 21547 grad_norm: 4.6346 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3577 loss: 1.3577 2022/10/10 06:22:34 - mmengine - INFO - Epoch(train) [63][300/940] lr: 1.0000e-03 eta: 4:59:17 time: 0.5297 data_time: 0.0289 memory: 21547 grad_norm: 4.5966 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.2178 loss: 1.2178 2022/10/10 06:22:44 - mmengine - INFO - Epoch(train) [63][320/940] lr: 1.0000e-03 eta: 4:59:07 time: 0.4933 data_time: 0.0274 memory: 21547 grad_norm: 4.4271 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1796 loss: 1.1796 2022/10/10 06:22:55 - mmengine - INFO - Epoch(train) [63][340/940] lr: 1.0000e-03 eta: 4:58:57 time: 0.5412 data_time: 0.0310 memory: 21547 grad_norm: 4.5193 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1568 loss: 1.1568 2022/10/10 06:23:05 - mmengine - INFO - Epoch(train) [63][360/940] lr: 1.0000e-03 eta: 4:58:47 time: 0.4895 data_time: 0.0347 memory: 21547 grad_norm: 4.5259 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1834 loss: 1.1834 2022/10/10 06:23:15 - mmengine - INFO - Epoch(train) [63][380/940] lr: 1.0000e-03 eta: 4:58:36 time: 0.5012 data_time: 0.0228 memory: 21547 grad_norm: 4.5453 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2582 loss: 1.2582 2022/10/10 06:23:24 - mmengine - INFO - Epoch(train) [63][400/940] lr: 1.0000e-03 eta: 4:58:26 time: 0.4854 data_time: 0.0240 memory: 21547 grad_norm: 4.4870 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3206 loss: 1.3206 2022/10/10 06:23:35 - mmengine - INFO - Epoch(train) [63][420/940] lr: 1.0000e-03 eta: 4:58:16 time: 0.5159 data_time: 0.0282 memory: 21547 grad_norm: 4.5067 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1507 loss: 1.1507 2022/10/10 06:23:45 - mmengine - INFO - Epoch(train) [63][440/940] lr: 1.0000e-03 eta: 4:58:06 time: 0.5052 data_time: 0.0221 memory: 21547 grad_norm: 4.4964 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1249 loss: 1.1249 2022/10/10 06:23:55 - mmengine - INFO - Epoch(train) [63][460/940] lr: 1.0000e-03 eta: 4:57:56 time: 0.5078 data_time: 0.0300 memory: 21547 grad_norm: 4.6102 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.1933 loss: 1.1933 2022/10/10 06:24:05 - mmengine - INFO - Epoch(train) [63][480/940] lr: 1.0000e-03 eta: 4:57:45 time: 0.4998 data_time: 0.0244 memory: 21547 grad_norm: 4.4699 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1275 loss: 1.1275 2022/10/10 06:24:16 - mmengine - INFO - Epoch(train) [63][500/940] lr: 1.0000e-03 eta: 4:57:36 time: 0.5426 data_time: 0.0290 memory: 21547 grad_norm: 4.5357 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4144 loss: 1.4144 2022/10/10 06:24:25 - mmengine - INFO - Epoch(train) [63][520/940] lr: 1.0000e-03 eta: 4:57:25 time: 0.4702 data_time: 0.0313 memory: 21547 grad_norm: 4.4334 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2482 loss: 1.2482 2022/10/10 06:24:37 - mmengine - INFO - Epoch(train) [63][540/940] lr: 1.0000e-03 eta: 4:57:16 time: 0.5660 data_time: 0.0307 memory: 21547 grad_norm: 4.4726 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3193 loss: 1.3193 2022/10/10 06:24:45 - mmengine - INFO - Epoch(train) [63][560/940] lr: 1.0000e-03 eta: 4:57:05 time: 0.4412 data_time: 0.0242 memory: 21547 grad_norm: 4.5223 top1_acc: 0.8438 top5_acc: 0.8438 loss_cls: 1.2609 loss: 1.2609 2022/10/10 06:24:56 - mmengine - INFO - Epoch(train) [63][580/940] lr: 1.0000e-03 eta: 4:56:55 time: 0.5111 data_time: 0.0231 memory: 21547 grad_norm: 4.5864 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1747 loss: 1.1747 2022/10/10 06:25:05 - mmengine - INFO - Epoch(train) [63][600/940] lr: 1.0000e-03 eta: 4:56:44 time: 0.4775 data_time: 0.0323 memory: 21547 grad_norm: 4.5373 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3323 loss: 1.3323 2022/10/10 06:25:15 - mmengine - INFO - Epoch(train) [63][620/940] lr: 1.0000e-03 eta: 4:56:34 time: 0.5127 data_time: 0.0240 memory: 21547 grad_norm: 4.4750 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1252 loss: 1.1252 2022/10/10 06:25:26 - mmengine - INFO - Epoch(train) [63][640/940] lr: 1.0000e-03 eta: 4:56:24 time: 0.5210 data_time: 0.0302 memory: 21547 grad_norm: 4.4860 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.2163 loss: 1.2163 2022/10/10 06:25:36 - mmengine - INFO - Epoch(train) [63][660/940] lr: 1.0000e-03 eta: 4:56:14 time: 0.5276 data_time: 0.0300 memory: 21547 grad_norm: 4.4750 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2792 loss: 1.2792 2022/10/10 06:25:46 - mmengine - INFO - Epoch(train) [63][680/940] lr: 1.0000e-03 eta: 4:56:04 time: 0.4597 data_time: 0.0314 memory: 21547 grad_norm: 4.5189 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2700 loss: 1.2700 2022/10/10 06:25:56 - mmengine - INFO - Epoch(train) [63][700/940] lr: 1.0000e-03 eta: 4:55:54 time: 0.5256 data_time: 0.0320 memory: 21547 grad_norm: 4.5427 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2207 loss: 1.2207 2022/10/10 06:26:06 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 06:26:06 - mmengine - INFO - Epoch(train) [63][720/940] lr: 1.0000e-03 eta: 4:55:43 time: 0.4728 data_time: 0.0233 memory: 21547 grad_norm: 4.5190 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2533 loss: 1.2533 2022/10/10 06:26:17 - mmengine - INFO - Epoch(train) [63][740/940] lr: 1.0000e-03 eta: 4:55:33 time: 0.5494 data_time: 0.0296 memory: 21547 grad_norm: 4.5506 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2081 loss: 1.2081 2022/10/10 06:26:27 - mmengine - INFO - Epoch(train) [63][760/940] lr: 1.0000e-03 eta: 4:55:23 time: 0.5189 data_time: 0.0292 memory: 21547 grad_norm: 4.4793 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0230 loss: 1.0230 2022/10/10 06:26:38 - mmengine - INFO - Epoch(train) [63][780/940] lr: 1.0000e-03 eta: 4:55:14 time: 0.5567 data_time: 0.0261 memory: 21547 grad_norm: 4.5070 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1778 loss: 1.1778 2022/10/10 06:26:48 - mmengine - INFO - Epoch(train) [63][800/940] lr: 1.0000e-03 eta: 4:55:03 time: 0.4784 data_time: 0.0290 memory: 21547 grad_norm: 4.5045 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2673 loss: 1.2673 2022/10/10 06:26:58 - mmengine - INFO - Epoch(train) [63][820/940] lr: 1.0000e-03 eta: 4:54:54 time: 0.5234 data_time: 0.0250 memory: 21547 grad_norm: 4.5234 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1748 loss: 1.1748 2022/10/10 06:27:08 - mmengine - INFO - Epoch(train) [63][840/940] lr: 1.0000e-03 eta: 4:54:43 time: 0.4768 data_time: 0.0244 memory: 21547 grad_norm: 4.5485 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3614 loss: 1.3614 2022/10/10 06:27:18 - mmengine - INFO - Epoch(train) [63][860/940] lr: 1.0000e-03 eta: 4:54:33 time: 0.5272 data_time: 0.0249 memory: 21547 grad_norm: 4.5467 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1845 loss: 1.1845 2022/10/10 06:27:28 - mmengine - INFO - Epoch(train) [63][880/940] lr: 1.0000e-03 eta: 4:54:23 time: 0.4682 data_time: 0.0332 memory: 21547 grad_norm: 4.5508 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3217 loss: 1.3217 2022/10/10 06:27:38 - mmengine - INFO - Epoch(train) [63][900/940] lr: 1.0000e-03 eta: 4:54:13 time: 0.5375 data_time: 0.0310 memory: 21547 grad_norm: 4.4560 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2539 loss: 1.2539 2022/10/10 06:27:47 - mmengine - INFO - Epoch(train) [63][920/940] lr: 1.0000e-03 eta: 4:54:02 time: 0.4474 data_time: 0.0267 memory: 21547 grad_norm: 4.4307 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1128 loss: 1.1128 2022/10/10 06:27:57 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 06:27:57 - mmengine - INFO - Epoch(train) [63][940/940] lr: 1.0000e-03 eta: 4:53:52 time: 0.4907 data_time: 0.0219 memory: 21547 grad_norm: 4.6729 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.2462 loss: 1.2462 2022/10/10 06:27:57 - mmengine - INFO - Saving checkpoint at 63 epochs 2022/10/10 06:28:10 - mmengine - INFO - Epoch(val) [63][20/78] eta: 0:00:35 time: 0.6176 data_time: 0.5125 memory: 3269 2022/10/10 06:28:19 - mmengine - INFO - Epoch(val) [63][40/78] eta: 0:00:15 time: 0.4189 data_time: 0.3147 memory: 3269 2022/10/10 06:28:30 - mmengine - INFO - Epoch(val) [63][60/78] eta: 0:00:09 time: 0.5464 data_time: 0.4404 memory: 3269 2022/10/10 06:28:39 - mmengine - INFO - Epoch(val) [63][78/78] acc/top1: 0.6789 acc/top5: 0.8703 acc/mean1: 0.6788 2022/10/10 06:28:39 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_62.pth is removed 2022/10/10 06:28:40 - mmengine - INFO - The best checkpoint with 0.6789 acc/top1 at 63 epoch is saved to best_acc/top1_epoch_63.pth. 2022/10/10 06:28:53 - mmengine - INFO - Epoch(train) [64][20/940] lr: 1.0000e-03 eta: 4:53:43 time: 0.6428 data_time: 0.2423 memory: 21547 grad_norm: 4.4897 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3104 loss: 1.3104 2022/10/10 06:29:03 - mmengine - INFO - Epoch(train) [64][40/940] lr: 1.0000e-03 eta: 4:53:33 time: 0.5154 data_time: 0.0594 memory: 21547 grad_norm: 4.5570 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1881 loss: 1.1881 2022/10/10 06:29:14 - mmengine - INFO - Epoch(train) [64][60/940] lr: 1.0000e-03 eta: 4:53:23 time: 0.5205 data_time: 0.0296 memory: 21547 grad_norm: 4.4398 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.1651 loss: 1.1651 2022/10/10 06:29:23 - mmengine - INFO - Epoch(train) [64][80/940] lr: 1.0000e-03 eta: 4:53:13 time: 0.4808 data_time: 0.0256 memory: 21547 grad_norm: 4.5148 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1635 loss: 1.1635 2022/10/10 06:29:34 - mmengine - INFO - Epoch(train) [64][100/940] lr: 1.0000e-03 eta: 4:53:03 time: 0.5470 data_time: 0.0296 memory: 21547 grad_norm: 4.4680 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2535 loss: 1.2535 2022/10/10 06:29:44 - mmengine - INFO - Epoch(train) [64][120/940] lr: 1.0000e-03 eta: 4:52:53 time: 0.4904 data_time: 0.0240 memory: 21547 grad_norm: 4.5955 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2072 loss: 1.2072 2022/10/10 06:29:54 - mmengine - INFO - Epoch(train) [64][140/940] lr: 1.0000e-03 eta: 4:52:42 time: 0.5147 data_time: 0.0286 memory: 21547 grad_norm: 4.4991 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2287 loss: 1.2287 2022/10/10 06:30:04 - mmengine - INFO - Epoch(train) [64][160/940] lr: 1.0000e-03 eta: 4:52:32 time: 0.4659 data_time: 0.0254 memory: 21547 grad_norm: 4.5003 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2889 loss: 1.2889 2022/10/10 06:30:15 - mmengine - INFO - Epoch(train) [64][180/940] lr: 1.0000e-03 eta: 4:52:22 time: 0.5452 data_time: 0.0216 memory: 21547 grad_norm: 4.5580 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.2599 loss: 1.2599 2022/10/10 06:30:24 - mmengine - INFO - Epoch(train) [64][200/940] lr: 1.0000e-03 eta: 4:52:12 time: 0.4863 data_time: 0.0215 memory: 21547 grad_norm: 4.4563 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2856 loss: 1.2856 2022/10/10 06:30:35 - mmengine - INFO - Epoch(train) [64][220/940] lr: 1.0000e-03 eta: 4:52:02 time: 0.5325 data_time: 0.0257 memory: 21547 grad_norm: 4.5167 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1083 loss: 1.1083 2022/10/10 06:30:44 - mmengine - INFO - Epoch(train) [64][240/940] lr: 1.0000e-03 eta: 4:51:51 time: 0.4496 data_time: 0.0234 memory: 21547 grad_norm: 4.5240 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2929 loss: 1.2929 2022/10/10 06:30:55 - mmengine - INFO - Epoch(train) [64][260/940] lr: 1.0000e-03 eta: 4:51:41 time: 0.5318 data_time: 0.0233 memory: 21547 grad_norm: 4.4362 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2187 loss: 1.2187 2022/10/10 06:31:05 - mmengine - INFO - Epoch(train) [64][280/940] lr: 1.0000e-03 eta: 4:51:31 time: 0.4964 data_time: 0.0281 memory: 21547 grad_norm: 4.4587 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3046 loss: 1.3046 2022/10/10 06:31:15 - mmengine - INFO - Epoch(train) [64][300/940] lr: 1.0000e-03 eta: 4:51:21 time: 0.5223 data_time: 0.0303 memory: 21547 grad_norm: 4.5070 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1565 loss: 1.1565 2022/10/10 06:31:25 - mmengine - INFO - Epoch(train) [64][320/940] lr: 1.0000e-03 eta: 4:51:11 time: 0.4789 data_time: 0.0258 memory: 21547 grad_norm: 4.4615 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2673 loss: 1.2673 2022/10/10 06:31:35 - mmengine - INFO - Epoch(train) [64][340/940] lr: 1.0000e-03 eta: 4:51:00 time: 0.4989 data_time: 0.0279 memory: 21547 grad_norm: 4.4395 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2951 loss: 1.2951 2022/10/10 06:31:45 - mmengine - INFO - Epoch(train) [64][360/940] lr: 1.0000e-03 eta: 4:50:50 time: 0.5100 data_time: 0.0280 memory: 21547 grad_norm: 4.5298 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2650 loss: 1.2650 2022/10/10 06:31:55 - mmengine - INFO - Epoch(train) [64][380/940] lr: 1.0000e-03 eta: 4:50:40 time: 0.4947 data_time: 0.0284 memory: 21547 grad_norm: 4.5223 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1934 loss: 1.1934 2022/10/10 06:32:05 - mmengine - INFO - Epoch(train) [64][400/940] lr: 1.0000e-03 eta: 4:50:30 time: 0.4992 data_time: 0.0265 memory: 21547 grad_norm: 4.5652 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2316 loss: 1.2316 2022/10/10 06:32:16 - mmengine - INFO - Epoch(train) [64][420/940] lr: 1.0000e-03 eta: 4:50:20 time: 0.5434 data_time: 0.0308 memory: 21547 grad_norm: 4.5162 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3103 loss: 1.3103 2022/10/10 06:32:25 - mmengine - INFO - Epoch(train) [64][440/940] lr: 1.0000e-03 eta: 4:50:10 time: 0.4859 data_time: 0.0307 memory: 21547 grad_norm: 4.6585 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1352 loss: 1.1352 2022/10/10 06:32:36 - mmengine - INFO - Epoch(train) [64][460/940] lr: 1.0000e-03 eta: 4:50:00 time: 0.5288 data_time: 0.0298 memory: 21547 grad_norm: 4.5816 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2914 loss: 1.2914 2022/10/10 06:32:46 - mmengine - INFO - Epoch(train) [64][480/940] lr: 1.0000e-03 eta: 4:49:49 time: 0.4882 data_time: 0.0349 memory: 21547 grad_norm: 4.5972 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2097 loss: 1.2097 2022/10/10 06:32:56 - mmengine - INFO - Epoch(train) [64][500/940] lr: 1.0000e-03 eta: 4:49:39 time: 0.5228 data_time: 0.0243 memory: 21547 grad_norm: 4.5070 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2913 loss: 1.2913 2022/10/10 06:33:05 - mmengine - INFO - Epoch(train) [64][520/940] lr: 1.0000e-03 eta: 4:49:29 time: 0.4658 data_time: 0.0266 memory: 21547 grad_norm: 4.4939 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2926 loss: 1.2926 2022/10/10 06:33:15 - mmengine - INFO - Epoch(train) [64][540/940] lr: 1.0000e-03 eta: 4:49:19 time: 0.4955 data_time: 0.0233 memory: 21547 grad_norm: 4.4154 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2305 loss: 1.2305 2022/10/10 06:33:25 - mmengine - INFO - Epoch(train) [64][560/940] lr: 1.0000e-03 eta: 4:49:08 time: 0.4924 data_time: 0.0328 memory: 21547 grad_norm: 4.5531 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2526 loss: 1.2526 2022/10/10 06:33:35 - mmengine - INFO - Epoch(train) [64][580/940] lr: 1.0000e-03 eta: 4:48:58 time: 0.5018 data_time: 0.0265 memory: 21547 grad_norm: 4.5352 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2025 loss: 1.2025 2022/10/10 06:33:45 - mmengine - INFO - Epoch(train) [64][600/940] lr: 1.0000e-03 eta: 4:48:48 time: 0.4880 data_time: 0.0296 memory: 21547 grad_norm: 4.5166 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2271 loss: 1.2271 2022/10/10 06:33:56 - mmengine - INFO - Epoch(train) [64][620/940] lr: 1.0000e-03 eta: 4:48:38 time: 0.5299 data_time: 0.0278 memory: 21547 grad_norm: 4.4953 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3301 loss: 1.3301 2022/10/10 06:34:05 - mmengine - INFO - Epoch(train) [64][640/940] lr: 1.0000e-03 eta: 4:48:27 time: 0.4803 data_time: 0.0313 memory: 21547 grad_norm: 4.5558 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2320 loss: 1.2320 2022/10/10 06:34:16 - mmengine - INFO - Epoch(train) [64][660/940] lr: 1.0000e-03 eta: 4:48:17 time: 0.5263 data_time: 0.0351 memory: 21547 grad_norm: 4.5462 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1896 loss: 1.1896 2022/10/10 06:34:26 - mmengine - INFO - Epoch(train) [64][680/940] lr: 1.0000e-03 eta: 4:48:07 time: 0.4924 data_time: 0.0263 memory: 21547 grad_norm: 4.5088 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2028 loss: 1.2028 2022/10/10 06:34:35 - mmengine - INFO - Epoch(train) [64][700/940] lr: 1.0000e-03 eta: 4:47:57 time: 0.4787 data_time: 0.0334 memory: 21547 grad_norm: 4.5820 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1624 loss: 1.1624 2022/10/10 06:34:45 - mmengine - INFO - Epoch(train) [64][720/940] lr: 1.0000e-03 eta: 4:47:46 time: 0.4764 data_time: 0.0306 memory: 21547 grad_norm: 4.5564 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1907 loss: 1.1907 2022/10/10 06:34:55 - mmengine - INFO - Epoch(train) [64][740/940] lr: 1.0000e-03 eta: 4:47:36 time: 0.5384 data_time: 0.0276 memory: 21547 grad_norm: 4.4831 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2141 loss: 1.2141 2022/10/10 06:35:05 - mmengine - INFO - Epoch(train) [64][760/940] lr: 1.0000e-03 eta: 4:47:26 time: 0.4880 data_time: 0.0289 memory: 21547 grad_norm: 4.6094 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1484 loss: 1.1484 2022/10/10 06:35:15 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 06:35:15 - mmengine - INFO - Epoch(train) [64][780/940] lr: 1.0000e-03 eta: 4:47:16 time: 0.5013 data_time: 0.0283 memory: 21547 grad_norm: 4.4882 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2990 loss: 1.2990 2022/10/10 06:35:25 - mmengine - INFO - Epoch(train) [64][800/940] lr: 1.0000e-03 eta: 4:47:06 time: 0.5028 data_time: 0.0227 memory: 21547 grad_norm: 4.4548 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2984 loss: 1.2984 2022/10/10 06:35:35 - mmengine - INFO - Epoch(train) [64][820/940] lr: 1.0000e-03 eta: 4:46:56 time: 0.5103 data_time: 0.0267 memory: 21547 grad_norm: 4.5547 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3450 loss: 1.3450 2022/10/10 06:35:46 - mmengine - INFO - Epoch(train) [64][840/940] lr: 1.0000e-03 eta: 4:46:45 time: 0.5062 data_time: 0.0277 memory: 21547 grad_norm: 4.5621 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1853 loss: 1.1853 2022/10/10 06:35:56 - mmengine - INFO - Epoch(train) [64][860/940] lr: 1.0000e-03 eta: 4:46:35 time: 0.4998 data_time: 0.0283 memory: 21547 grad_norm: 4.5278 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2860 loss: 1.2860 2022/10/10 06:36:06 - mmengine - INFO - Epoch(train) [64][880/940] lr: 1.0000e-03 eta: 4:46:25 time: 0.5022 data_time: 0.0253 memory: 21547 grad_norm: 4.6415 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3208 loss: 1.3208 2022/10/10 06:36:16 - mmengine - INFO - Epoch(train) [64][900/940] lr: 1.0000e-03 eta: 4:46:15 time: 0.5198 data_time: 0.0292 memory: 21547 grad_norm: 4.4843 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2950 loss: 1.2950 2022/10/10 06:36:26 - mmengine - INFO - Epoch(train) [64][920/940] lr: 1.0000e-03 eta: 4:46:05 time: 0.5156 data_time: 0.0290 memory: 21547 grad_norm: 4.5433 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0891 loss: 1.0891 2022/10/10 06:36:35 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 06:36:35 - mmengine - INFO - Epoch(train) [64][940/940] lr: 1.0000e-03 eta: 4:45:54 time: 0.4208 data_time: 0.0242 memory: 21547 grad_norm: 4.8962 top1_acc: 0.2857 top5_acc: 0.5714 loss_cls: 1.2852 loss: 1.2852 2022/10/10 06:36:47 - mmengine - INFO - Epoch(val) [64][20/78] eta: 0:00:35 time: 0.6158 data_time: 0.5064 memory: 3269 2022/10/10 06:36:56 - mmengine - INFO - Epoch(val) [64][40/78] eta: 0:00:16 time: 0.4222 data_time: 0.3120 memory: 3269 2022/10/10 06:37:06 - mmengine - INFO - Epoch(val) [64][60/78] eta: 0:00:09 time: 0.5471 data_time: 0.4393 memory: 3269 2022/10/10 06:37:16 - mmengine - INFO - Epoch(val) [64][78/78] acc/top1: 0.6775 acc/top5: 0.8703 acc/mean1: 0.6774 2022/10/10 06:37:30 - mmengine - INFO - Epoch(train) [65][20/940] lr: 1.0000e-03 eta: 4:45:46 time: 0.6977 data_time: 0.2303 memory: 21547 grad_norm: 4.5541 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1748 loss: 1.1748 2022/10/10 06:37:40 - mmengine - INFO - Epoch(train) [65][40/940] lr: 1.0000e-03 eta: 4:45:36 time: 0.4935 data_time: 0.0236 memory: 21547 grad_norm: 4.6137 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2010 loss: 1.2010 2022/10/10 06:37:51 - mmengine - INFO - Epoch(train) [65][60/940] lr: 1.0000e-03 eta: 4:45:26 time: 0.5309 data_time: 0.0326 memory: 21547 grad_norm: 4.5025 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.1442 loss: 1.1442 2022/10/10 06:38:01 - mmengine - INFO - Epoch(train) [65][80/940] lr: 1.0000e-03 eta: 4:45:15 time: 0.4851 data_time: 0.0268 memory: 21547 grad_norm: 4.4893 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2778 loss: 1.2778 2022/10/10 06:38:11 - mmengine - INFO - Epoch(train) [65][100/940] lr: 1.0000e-03 eta: 4:45:05 time: 0.5209 data_time: 0.0269 memory: 21547 grad_norm: 4.5543 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1237 loss: 1.1237 2022/10/10 06:38:20 - mmengine - INFO - Epoch(train) [65][120/940] lr: 1.0000e-03 eta: 4:44:55 time: 0.4648 data_time: 0.0230 memory: 21547 grad_norm: 4.5821 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2545 loss: 1.2545 2022/10/10 06:38:32 - mmengine - INFO - Epoch(train) [65][140/940] lr: 1.0000e-03 eta: 4:44:45 time: 0.5718 data_time: 0.0329 memory: 21547 grad_norm: 4.4828 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1401 loss: 1.1401 2022/10/10 06:38:41 - mmengine - INFO - Epoch(train) [65][160/940] lr: 1.0000e-03 eta: 4:44:35 time: 0.4797 data_time: 0.0228 memory: 21547 grad_norm: 4.5590 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2934 loss: 1.2934 2022/10/10 06:38:52 - mmengine - INFO - Epoch(train) [65][180/940] lr: 1.0000e-03 eta: 4:44:25 time: 0.5268 data_time: 0.0292 memory: 21547 grad_norm: 4.4512 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2924 loss: 1.2924 2022/10/10 06:39:01 - mmengine - INFO - Epoch(train) [65][200/940] lr: 1.0000e-03 eta: 4:44:14 time: 0.4680 data_time: 0.0244 memory: 21547 grad_norm: 4.4869 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1367 loss: 1.1367 2022/10/10 06:39:12 - mmengine - INFO - Epoch(train) [65][220/940] lr: 1.0000e-03 eta: 4:44:05 time: 0.5535 data_time: 0.0346 memory: 21547 grad_norm: 4.4949 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2229 loss: 1.2229 2022/10/10 06:39:22 - mmengine - INFO - Epoch(train) [65][240/940] lr: 1.0000e-03 eta: 4:43:54 time: 0.4723 data_time: 0.0372 memory: 21547 grad_norm: 4.5264 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3378 loss: 1.3378 2022/10/10 06:39:32 - mmengine - INFO - Epoch(train) [65][260/940] lr: 1.0000e-03 eta: 4:43:44 time: 0.5293 data_time: 0.0310 memory: 21547 grad_norm: 4.5510 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3136 loss: 1.3136 2022/10/10 06:39:41 - mmengine - INFO - Epoch(train) [65][280/940] lr: 1.0000e-03 eta: 4:43:33 time: 0.4357 data_time: 0.0292 memory: 21547 grad_norm: 4.5528 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1908 loss: 1.1908 2022/10/10 06:39:52 - mmengine - INFO - Epoch(train) [65][300/940] lr: 1.0000e-03 eta: 4:43:24 time: 0.5422 data_time: 0.0259 memory: 21547 grad_norm: 4.5896 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1512 loss: 1.1512 2022/10/10 06:40:02 - mmengine - INFO - Epoch(train) [65][320/940] lr: 1.0000e-03 eta: 4:43:13 time: 0.4786 data_time: 0.0283 memory: 21547 grad_norm: 4.5258 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2966 loss: 1.2966 2022/10/10 06:40:11 - mmengine - INFO - Epoch(train) [65][340/940] lr: 1.0000e-03 eta: 4:43:03 time: 0.4921 data_time: 0.0270 memory: 21547 grad_norm: 4.4602 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2868 loss: 1.2868 2022/10/10 06:40:21 - mmengine - INFO - Epoch(train) [65][360/940] lr: 1.0000e-03 eta: 4:42:53 time: 0.4952 data_time: 0.0276 memory: 21547 grad_norm: 4.5158 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2022 loss: 1.2022 2022/10/10 06:40:31 - mmengine - INFO - Epoch(train) [65][380/940] lr: 1.0000e-03 eta: 4:42:42 time: 0.4991 data_time: 0.0311 memory: 21547 grad_norm: 4.5391 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2859 loss: 1.2859 2022/10/10 06:40:41 - mmengine - INFO - Epoch(train) [65][400/940] lr: 1.0000e-03 eta: 4:42:32 time: 0.4787 data_time: 0.0301 memory: 21547 grad_norm: 4.5024 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1740 loss: 1.1740 2022/10/10 06:40:51 - mmengine - INFO - Epoch(train) [65][420/940] lr: 1.0000e-03 eta: 4:42:22 time: 0.5154 data_time: 0.0266 memory: 21547 grad_norm: 4.4421 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.1573 loss: 1.1573 2022/10/10 06:41:01 - mmengine - INFO - Epoch(train) [65][440/940] lr: 1.0000e-03 eta: 4:42:12 time: 0.5153 data_time: 0.0294 memory: 21547 grad_norm: 4.5703 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2650 loss: 1.2650 2022/10/10 06:41:11 - mmengine - INFO - Epoch(train) [65][460/940] lr: 1.0000e-03 eta: 4:42:02 time: 0.4963 data_time: 0.0226 memory: 21547 grad_norm: 4.4997 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.1365 loss: 1.1365 2022/10/10 06:41:21 - mmengine - INFO - Epoch(train) [65][480/940] lr: 1.0000e-03 eta: 4:41:51 time: 0.4888 data_time: 0.0271 memory: 21547 grad_norm: 4.5162 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1733 loss: 1.1733 2022/10/10 06:41:31 - mmengine - INFO - Epoch(train) [65][500/940] lr: 1.0000e-03 eta: 4:41:41 time: 0.5031 data_time: 0.0226 memory: 21547 grad_norm: 4.5416 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2943 loss: 1.2943 2022/10/10 06:41:42 - mmengine - INFO - Epoch(train) [65][520/940] lr: 1.0000e-03 eta: 4:41:31 time: 0.5177 data_time: 0.0284 memory: 21547 grad_norm: 4.5895 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2015 loss: 1.2015 2022/10/10 06:41:52 - mmengine - INFO - Epoch(train) [65][540/940] lr: 1.0000e-03 eta: 4:41:21 time: 0.5024 data_time: 0.0322 memory: 21547 grad_norm: 4.6247 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2008 loss: 1.2008 2022/10/10 06:42:02 - mmengine - INFO - Epoch(train) [65][560/940] lr: 1.0000e-03 eta: 4:41:11 time: 0.5267 data_time: 0.0326 memory: 21547 grad_norm: 4.6544 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4033 loss: 1.4033 2022/10/10 06:42:12 - mmengine - INFO - Epoch(train) [65][580/940] lr: 1.0000e-03 eta: 4:41:01 time: 0.5074 data_time: 0.0248 memory: 21547 grad_norm: 4.5518 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2060 loss: 1.2060 2022/10/10 06:42:22 - mmengine - INFO - Epoch(train) [65][600/940] lr: 1.0000e-03 eta: 4:40:51 time: 0.4912 data_time: 0.0247 memory: 21547 grad_norm: 4.6024 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3034 loss: 1.3034 2022/10/10 06:42:32 - mmengine - INFO - Epoch(train) [65][620/940] lr: 1.0000e-03 eta: 4:40:40 time: 0.5086 data_time: 0.0238 memory: 21547 grad_norm: 4.5402 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1377 loss: 1.1377 2022/10/10 06:42:43 - mmengine - INFO - Epoch(train) [65][640/940] lr: 1.0000e-03 eta: 4:40:30 time: 0.5220 data_time: 0.0253 memory: 21547 grad_norm: 4.5706 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2335 loss: 1.2335 2022/10/10 06:42:53 - mmengine - INFO - Epoch(train) [65][660/940] lr: 1.0000e-03 eta: 4:40:20 time: 0.5080 data_time: 0.0307 memory: 21547 grad_norm: 4.6028 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2540 loss: 1.2540 2022/10/10 06:43:04 - mmengine - INFO - Epoch(train) [65][680/940] lr: 1.0000e-03 eta: 4:40:11 time: 0.5432 data_time: 0.0293 memory: 21547 grad_norm: 4.5724 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4040 loss: 1.4040 2022/10/10 06:43:14 - mmengine - INFO - Epoch(train) [65][700/940] lr: 1.0000e-03 eta: 4:40:00 time: 0.5027 data_time: 0.0245 memory: 21547 grad_norm: 4.5243 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2592 loss: 1.2592 2022/10/10 06:43:24 - mmengine - INFO - Epoch(train) [65][720/940] lr: 1.0000e-03 eta: 4:39:50 time: 0.5247 data_time: 0.0231 memory: 21547 grad_norm: 4.5483 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2194 loss: 1.2194 2022/10/10 06:43:33 - mmengine - INFO - Epoch(train) [65][740/940] lr: 1.0000e-03 eta: 4:39:40 time: 0.4520 data_time: 0.0276 memory: 21547 grad_norm: 4.4546 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1775 loss: 1.1775 2022/10/10 06:43:43 - mmengine - INFO - Epoch(train) [65][760/940] lr: 1.0000e-03 eta: 4:39:29 time: 0.4789 data_time: 0.0250 memory: 21547 grad_norm: 4.5294 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2361 loss: 1.2361 2022/10/10 06:43:53 - mmengine - INFO - Epoch(train) [65][780/940] lr: 1.0000e-03 eta: 4:39:19 time: 0.5043 data_time: 0.0314 memory: 21547 grad_norm: 4.4272 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0767 loss: 1.0767 2022/10/10 06:44:03 - mmengine - INFO - Epoch(train) [65][800/940] lr: 1.0000e-03 eta: 4:39:09 time: 0.4969 data_time: 0.0294 memory: 21547 grad_norm: 4.4728 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2200 loss: 1.2200 2022/10/10 06:44:14 - mmengine - INFO - Epoch(train) [65][820/940] lr: 1.0000e-03 eta: 4:38:59 time: 0.5494 data_time: 0.0230 memory: 21547 grad_norm: 4.5512 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1491 loss: 1.1491 2022/10/10 06:44:24 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 06:44:24 - mmengine - INFO - Epoch(train) [65][840/940] lr: 1.0000e-03 eta: 4:38:49 time: 0.5009 data_time: 0.0283 memory: 21547 grad_norm: 4.5019 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1705 loss: 1.1705 2022/10/10 06:44:34 - mmengine - INFO - Epoch(train) [65][860/940] lr: 1.0000e-03 eta: 4:38:39 time: 0.5001 data_time: 0.0253 memory: 21547 grad_norm: 4.6593 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3423 loss: 1.3423 2022/10/10 06:44:44 - mmengine - INFO - Epoch(train) [65][880/940] lr: 1.0000e-03 eta: 4:38:28 time: 0.4754 data_time: 0.0345 memory: 21547 grad_norm: 4.5639 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.1919 loss: 1.1919 2022/10/10 06:44:54 - mmengine - INFO - Epoch(train) [65][900/940] lr: 1.0000e-03 eta: 4:38:18 time: 0.5181 data_time: 0.0299 memory: 21547 grad_norm: 4.4370 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2143 loss: 1.2143 2022/10/10 06:45:03 - mmengine - INFO - Epoch(train) [65][920/940] lr: 1.0000e-03 eta: 4:38:08 time: 0.4811 data_time: 0.0262 memory: 21547 grad_norm: 4.6112 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3602 loss: 1.3602 2022/10/10 06:45:13 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 06:45:13 - mmengine - INFO - Epoch(train) [65][940/940] lr: 1.0000e-03 eta: 4:37:57 time: 0.4818 data_time: 0.0231 memory: 21547 grad_norm: 4.8400 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.2968 loss: 1.2968 2022/10/10 06:45:25 - mmengine - INFO - Epoch(val) [65][20/78] eta: 0:00:35 time: 0.6070 data_time: 0.4981 memory: 3269 2022/10/10 06:45:34 - mmengine - INFO - Epoch(val) [65][40/78] eta: 0:00:15 time: 0.4204 data_time: 0.3117 memory: 3269 2022/10/10 06:45:45 - mmengine - INFO - Epoch(val) [65][60/78] eta: 0:00:10 time: 0.5579 data_time: 0.4518 memory: 3269 2022/10/10 06:45:55 - mmengine - INFO - Epoch(val) [65][78/78] acc/top1: 0.6782 acc/top5: 0.8705 acc/mean1: 0.6781 2022/10/10 06:46:09 - mmengine - INFO - Epoch(train) [66][20/940] lr: 1.0000e-03 eta: 4:37:49 time: 0.7120 data_time: 0.2032 memory: 21547 grad_norm: 4.5474 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1396 loss: 1.1396 2022/10/10 06:46:19 - mmengine - INFO - Epoch(train) [66][40/940] lr: 1.0000e-03 eta: 4:37:39 time: 0.4713 data_time: 0.0266 memory: 21547 grad_norm: 4.5185 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1288 loss: 1.1288 2022/10/10 06:46:29 - mmengine - INFO - Epoch(train) [66][60/940] lr: 1.0000e-03 eta: 4:37:29 time: 0.5107 data_time: 0.0290 memory: 21547 grad_norm: 4.5712 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3530 loss: 1.3530 2022/10/10 06:46:39 - mmengine - INFO - Epoch(train) [66][80/940] lr: 1.0000e-03 eta: 4:37:19 time: 0.5061 data_time: 0.0260 memory: 21547 grad_norm: 4.6607 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2730 loss: 1.2730 2022/10/10 06:46:49 - mmengine - INFO - Epoch(train) [66][100/940] lr: 1.0000e-03 eta: 4:37:09 time: 0.5115 data_time: 0.0279 memory: 21547 grad_norm: 4.5727 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1124 loss: 1.1124 2022/10/10 06:46:59 - mmengine - INFO - Epoch(train) [66][120/940] lr: 1.0000e-03 eta: 4:36:58 time: 0.4969 data_time: 0.0276 memory: 21547 grad_norm: 4.5514 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1915 loss: 1.1915 2022/10/10 06:47:10 - mmengine - INFO - Epoch(train) [66][140/940] lr: 1.0000e-03 eta: 4:36:48 time: 0.5326 data_time: 0.0264 memory: 21547 grad_norm: 4.5757 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2095 loss: 1.2095 2022/10/10 06:47:19 - mmengine - INFO - Epoch(train) [66][160/940] lr: 1.0000e-03 eta: 4:36:38 time: 0.4756 data_time: 0.0283 memory: 21547 grad_norm: 4.6715 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2198 loss: 1.2198 2022/10/10 06:47:30 - mmengine - INFO - Epoch(train) [66][180/940] lr: 1.0000e-03 eta: 4:36:28 time: 0.5424 data_time: 0.0288 memory: 21547 grad_norm: 4.6164 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2843 loss: 1.2843 2022/10/10 06:47:41 - mmengine - INFO - Epoch(train) [66][200/940] lr: 1.0000e-03 eta: 4:36:18 time: 0.5273 data_time: 0.0296 memory: 21547 grad_norm: 4.4933 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2261 loss: 1.2261 2022/10/10 06:47:51 - mmengine - INFO - Epoch(train) [66][220/940] lr: 1.0000e-03 eta: 4:36:08 time: 0.5186 data_time: 0.0288 memory: 21547 grad_norm: 4.5671 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2666 loss: 1.2666 2022/10/10 06:48:00 - mmengine - INFO - Epoch(train) [66][240/940] lr: 1.0000e-03 eta: 4:35:58 time: 0.4651 data_time: 0.0268 memory: 21547 grad_norm: 4.5718 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1499 loss: 1.1499 2022/10/10 06:48:10 - mmengine - INFO - Epoch(train) [66][260/940] lr: 1.0000e-03 eta: 4:35:48 time: 0.5064 data_time: 0.0285 memory: 21547 grad_norm: 4.6486 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2820 loss: 1.2820 2022/10/10 06:48:19 - mmengine - INFO - Epoch(train) [66][280/940] lr: 1.0000e-03 eta: 4:35:37 time: 0.4482 data_time: 0.0284 memory: 21547 grad_norm: 4.5106 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2478 loss: 1.2478 2022/10/10 06:48:30 - mmengine - INFO - Epoch(train) [66][300/940] lr: 1.0000e-03 eta: 4:35:27 time: 0.5432 data_time: 0.0301 memory: 21547 grad_norm: 4.5895 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1923 loss: 1.1923 2022/10/10 06:48:40 - mmengine - INFO - Epoch(train) [66][320/940] lr: 1.0000e-03 eta: 4:35:17 time: 0.4761 data_time: 0.0255 memory: 21547 grad_norm: 4.5680 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3439 loss: 1.3439 2022/10/10 06:48:50 - mmengine - INFO - Epoch(train) [66][340/940] lr: 1.0000e-03 eta: 4:35:06 time: 0.4964 data_time: 0.0300 memory: 21547 grad_norm: 4.5919 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1490 loss: 1.1490 2022/10/10 06:49:00 - mmengine - INFO - Epoch(train) [66][360/940] lr: 1.0000e-03 eta: 4:34:56 time: 0.5225 data_time: 0.0247 memory: 21547 grad_norm: 4.5660 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.2333 loss: 1.2333 2022/10/10 06:49:11 - mmengine - INFO - Epoch(train) [66][380/940] lr: 1.0000e-03 eta: 4:34:47 time: 0.5512 data_time: 0.0320 memory: 21547 grad_norm: 4.4961 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3420 loss: 1.3420 2022/10/10 06:49:21 - mmengine - INFO - Epoch(train) [66][400/940] lr: 1.0000e-03 eta: 4:34:36 time: 0.4997 data_time: 0.0249 memory: 21547 grad_norm: 4.5773 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2072 loss: 1.2072 2022/10/10 06:49:31 - mmengine - INFO - Epoch(train) [66][420/940] lr: 1.0000e-03 eta: 4:34:26 time: 0.4819 data_time: 0.0265 memory: 21547 grad_norm: 4.4911 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1688 loss: 1.1688 2022/10/10 06:49:41 - mmengine - INFO - Epoch(train) [66][440/940] lr: 1.0000e-03 eta: 4:34:16 time: 0.4978 data_time: 0.0349 memory: 21547 grad_norm: 4.5240 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2524 loss: 1.2524 2022/10/10 06:49:51 - mmengine - INFO - Epoch(train) [66][460/940] lr: 1.0000e-03 eta: 4:34:06 time: 0.4899 data_time: 0.0259 memory: 21547 grad_norm: 4.5214 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1663 loss: 1.1663 2022/10/10 06:50:00 - mmengine - INFO - Epoch(train) [66][480/940] lr: 1.0000e-03 eta: 4:33:55 time: 0.4944 data_time: 0.0255 memory: 21547 grad_norm: 4.4984 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2097 loss: 1.2097 2022/10/10 06:50:10 - mmengine - INFO - Epoch(train) [66][500/940] lr: 1.0000e-03 eta: 4:33:45 time: 0.4951 data_time: 0.0292 memory: 21547 grad_norm: 4.6096 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1868 loss: 1.1868 2022/10/10 06:50:21 - mmengine - INFO - Epoch(train) [66][520/940] lr: 1.0000e-03 eta: 4:33:35 time: 0.5423 data_time: 0.0337 memory: 21547 grad_norm: 4.5927 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.2706 loss: 1.2706 2022/10/10 06:50:32 - mmengine - INFO - Epoch(train) [66][540/940] lr: 1.0000e-03 eta: 4:33:25 time: 0.5171 data_time: 0.0233 memory: 21547 grad_norm: 4.5546 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1591 loss: 1.1591 2022/10/10 06:50:41 - mmengine - INFO - Epoch(train) [66][560/940] lr: 1.0000e-03 eta: 4:33:15 time: 0.4638 data_time: 0.0281 memory: 21547 grad_norm: 4.5978 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1662 loss: 1.1662 2022/10/10 06:50:51 - mmengine - INFO - Epoch(train) [66][580/940] lr: 1.0000e-03 eta: 4:33:04 time: 0.5052 data_time: 0.0269 memory: 21547 grad_norm: 4.5352 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0964 loss: 1.0964 2022/10/10 06:51:01 - mmengine - INFO - Epoch(train) [66][600/940] lr: 1.0000e-03 eta: 4:32:54 time: 0.4956 data_time: 0.0246 memory: 21547 grad_norm: 4.5457 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.4144 loss: 1.4144 2022/10/10 06:51:11 - mmengine - INFO - Epoch(train) [66][620/940] lr: 1.0000e-03 eta: 4:32:44 time: 0.5116 data_time: 0.0285 memory: 21547 grad_norm: 4.5967 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1503 loss: 1.1503 2022/10/10 06:51:21 - mmengine - INFO - Epoch(train) [66][640/940] lr: 1.0000e-03 eta: 4:32:34 time: 0.5007 data_time: 0.0254 memory: 21547 grad_norm: 4.5784 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2229 loss: 1.2229 2022/10/10 06:51:30 - mmengine - INFO - Epoch(train) [66][660/940] lr: 1.0000e-03 eta: 4:32:23 time: 0.4697 data_time: 0.0245 memory: 21547 grad_norm: 4.6114 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2537 loss: 1.2537 2022/10/10 06:51:41 - mmengine - INFO - Epoch(train) [66][680/940] lr: 1.0000e-03 eta: 4:32:13 time: 0.5186 data_time: 0.0266 memory: 21547 grad_norm: 4.5903 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.2119 loss: 1.2119 2022/10/10 06:51:51 - mmengine - INFO - Epoch(train) [66][700/940] lr: 1.0000e-03 eta: 4:32:03 time: 0.5224 data_time: 0.0247 memory: 21547 grad_norm: 4.5000 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2051 loss: 1.2051 2022/10/10 06:52:02 - mmengine - INFO - Epoch(train) [66][720/940] lr: 1.0000e-03 eta: 4:31:53 time: 0.5099 data_time: 0.0314 memory: 21547 grad_norm: 4.5833 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2042 loss: 1.2042 2022/10/10 06:52:11 - mmengine - INFO - Epoch(train) [66][740/940] lr: 1.0000e-03 eta: 4:31:43 time: 0.4734 data_time: 0.0287 memory: 21547 grad_norm: 4.5525 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1897 loss: 1.1897 2022/10/10 06:52:21 - mmengine - INFO - Epoch(train) [66][760/940] lr: 1.0000e-03 eta: 4:31:32 time: 0.4952 data_time: 0.0272 memory: 21547 grad_norm: 4.6184 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2490 loss: 1.2490 2022/10/10 06:52:31 - mmengine - INFO - Epoch(train) [66][780/940] lr: 1.0000e-03 eta: 4:31:22 time: 0.4942 data_time: 0.0269 memory: 21547 grad_norm: 4.7038 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2531 loss: 1.2531 2022/10/10 06:52:41 - mmengine - INFO - Epoch(train) [66][800/940] lr: 1.0000e-03 eta: 4:31:12 time: 0.5193 data_time: 0.0314 memory: 21547 grad_norm: 4.6170 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2025 loss: 1.2025 2022/10/10 06:52:53 - mmengine - INFO - Epoch(train) [66][820/940] lr: 1.0000e-03 eta: 4:31:03 time: 0.5724 data_time: 0.0246 memory: 21547 grad_norm: 4.5647 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2300 loss: 1.2300 2022/10/10 06:53:02 - mmengine - INFO - Epoch(train) [66][840/940] lr: 1.0000e-03 eta: 4:30:52 time: 0.4702 data_time: 0.0248 memory: 21547 grad_norm: 4.6256 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1950 loss: 1.1950 2022/10/10 06:53:13 - mmengine - INFO - Epoch(train) [66][860/940] lr: 1.0000e-03 eta: 4:30:42 time: 0.5269 data_time: 0.0223 memory: 21547 grad_norm: 4.4620 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3112 loss: 1.3112 2022/10/10 06:53:23 - mmengine - INFO - Epoch(train) [66][880/940] lr: 1.0000e-03 eta: 4:30:32 time: 0.5319 data_time: 0.0259 memory: 21547 grad_norm: 4.5577 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2687 loss: 1.2687 2022/10/10 06:53:32 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 06:53:32 - mmengine - INFO - Epoch(train) [66][900/940] lr: 1.0000e-03 eta: 4:30:22 time: 0.4532 data_time: 0.0302 memory: 21547 grad_norm: 4.5482 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2210 loss: 1.2210 2022/10/10 06:53:42 - mmengine - INFO - Epoch(train) [66][920/940] lr: 1.0000e-03 eta: 4:30:11 time: 0.4884 data_time: 0.0285 memory: 21547 grad_norm: 4.6019 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2077 loss: 1.2077 2022/10/10 06:53:52 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 06:53:52 - mmengine - INFO - Epoch(train) [66][940/940] lr: 1.0000e-03 eta: 4:30:01 time: 0.4755 data_time: 0.0219 memory: 21547 grad_norm: 4.8737 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.2549 loss: 1.2549 2022/10/10 06:53:52 - mmengine - INFO - Saving checkpoint at 66 epochs 2022/10/10 06:54:05 - mmengine - INFO - Epoch(val) [66][20/78] eta: 0:00:35 time: 0.6114 data_time: 0.5070 memory: 3269 2022/10/10 06:54:13 - mmengine - INFO - Epoch(val) [66][40/78] eta: 0:00:15 time: 0.4189 data_time: 0.3140 memory: 3269 2022/10/10 06:54:24 - mmengine - INFO - Epoch(val) [66][60/78] eta: 0:00:10 time: 0.5588 data_time: 0.4540 memory: 3269 2022/10/10 06:54:33 - mmengine - INFO - Epoch(val) [66][78/78] acc/top1: 0.6777 acc/top5: 0.8723 acc/mean1: 0.6776 2022/10/10 06:54:47 - mmengine - INFO - Epoch(train) [67][20/940] lr: 1.0000e-03 eta: 4:29:53 time: 0.6795 data_time: 0.1871 memory: 21547 grad_norm: 4.4940 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2532 loss: 1.2532 2022/10/10 06:54:57 - mmengine - INFO - Epoch(train) [67][40/940] lr: 1.0000e-03 eta: 4:29:42 time: 0.4883 data_time: 0.0305 memory: 21547 grad_norm: 4.5226 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2988 loss: 1.2988 2022/10/10 06:55:07 - mmengine - INFO - Epoch(train) [67][60/940] lr: 1.0000e-03 eta: 4:29:32 time: 0.5342 data_time: 0.0303 memory: 21547 grad_norm: 4.5323 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1576 loss: 1.1576 2022/10/10 06:55:18 - mmengine - INFO - Epoch(train) [67][80/940] lr: 1.0000e-03 eta: 4:29:22 time: 0.5028 data_time: 0.0345 memory: 21547 grad_norm: 4.5354 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2064 loss: 1.2064 2022/10/10 06:55:28 - mmengine - INFO - Epoch(train) [67][100/940] lr: 1.0000e-03 eta: 4:29:12 time: 0.5036 data_time: 0.0492 memory: 21547 grad_norm: 4.5449 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2081 loss: 1.2081 2022/10/10 06:55:37 - mmengine - INFO - Epoch(train) [67][120/940] lr: 1.0000e-03 eta: 4:29:02 time: 0.4932 data_time: 0.0831 memory: 21547 grad_norm: 4.4714 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1411 loss: 1.1411 2022/10/10 06:55:49 - mmengine - INFO - Epoch(train) [67][140/940] lr: 1.0000e-03 eta: 4:28:52 time: 0.5502 data_time: 0.0301 memory: 21547 grad_norm: 4.5102 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2966 loss: 1.2966 2022/10/10 06:55:58 - mmengine - INFO - Epoch(train) [67][160/940] lr: 1.0000e-03 eta: 4:28:42 time: 0.4808 data_time: 0.0276 memory: 21547 grad_norm: 4.5527 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2412 loss: 1.2412 2022/10/10 06:56:09 - mmengine - INFO - Epoch(train) [67][180/940] lr: 1.0000e-03 eta: 4:28:32 time: 0.5624 data_time: 0.0285 memory: 21547 grad_norm: 4.5666 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2308 loss: 1.2308 2022/10/10 06:56:18 - mmengine - INFO - Epoch(train) [67][200/940] lr: 1.0000e-03 eta: 4:28:21 time: 0.4495 data_time: 0.0270 memory: 21547 grad_norm: 4.6175 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2565 loss: 1.2565 2022/10/10 06:56:29 - mmengine - INFO - Epoch(train) [67][220/940] lr: 1.0000e-03 eta: 4:28:11 time: 0.5110 data_time: 0.0311 memory: 21547 grad_norm: 4.6188 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2922 loss: 1.2922 2022/10/10 06:56:38 - mmengine - INFO - Epoch(train) [67][240/940] lr: 1.0000e-03 eta: 4:28:01 time: 0.4900 data_time: 0.0281 memory: 21547 grad_norm: 4.5438 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.2177 loss: 1.2177 2022/10/10 06:56:49 - mmengine - INFO - Epoch(train) [67][260/940] lr: 1.0000e-03 eta: 4:27:51 time: 0.5278 data_time: 0.0266 memory: 21547 grad_norm: 4.5649 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2703 loss: 1.2703 2022/10/10 06:56:58 - mmengine - INFO - Epoch(train) [67][280/940] lr: 1.0000e-03 eta: 4:27:40 time: 0.4439 data_time: 0.0268 memory: 21547 grad_norm: 4.5706 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2159 loss: 1.2159 2022/10/10 06:57:08 - mmengine - INFO - Epoch(train) [67][300/940] lr: 1.0000e-03 eta: 4:27:30 time: 0.5279 data_time: 0.0301 memory: 21547 grad_norm: 4.5094 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2117 loss: 1.2117 2022/10/10 06:57:17 - mmengine - INFO - Epoch(train) [67][320/940] lr: 1.0000e-03 eta: 4:27:20 time: 0.4527 data_time: 0.0335 memory: 21547 grad_norm: 4.5800 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0932 loss: 1.0932 2022/10/10 06:57:28 - mmengine - INFO - Epoch(train) [67][340/940] lr: 1.0000e-03 eta: 4:27:10 time: 0.5296 data_time: 0.0299 memory: 21547 grad_norm: 4.6301 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3056 loss: 1.3056 2022/10/10 06:57:38 - mmengine - INFO - Epoch(train) [67][360/940] lr: 1.0000e-03 eta: 4:26:59 time: 0.4869 data_time: 0.0231 memory: 21547 grad_norm: 4.5716 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1708 loss: 1.1708 2022/10/10 06:57:49 - mmengine - INFO - Epoch(train) [67][380/940] lr: 1.0000e-03 eta: 4:26:50 time: 0.5417 data_time: 0.0277 memory: 21547 grad_norm: 4.4917 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1571 loss: 1.1571 2022/10/10 06:57:58 - mmengine - INFO - Epoch(train) [67][400/940] lr: 1.0000e-03 eta: 4:26:39 time: 0.4872 data_time: 0.0214 memory: 21547 grad_norm: 4.5510 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2513 loss: 1.2513 2022/10/10 06:58:08 - mmengine - INFO - Epoch(train) [67][420/940] lr: 1.0000e-03 eta: 4:26:29 time: 0.4958 data_time: 0.0312 memory: 21547 grad_norm: 4.5755 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.1225 loss: 1.1225 2022/10/10 06:58:18 - mmengine - INFO - Epoch(train) [67][440/940] lr: 1.0000e-03 eta: 4:26:18 time: 0.4647 data_time: 0.0302 memory: 21547 grad_norm: 4.5388 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1720 loss: 1.1720 2022/10/10 06:58:28 - mmengine - INFO - Epoch(train) [67][460/940] lr: 1.0000e-03 eta: 4:26:08 time: 0.5086 data_time: 0.0278 memory: 21547 grad_norm: 4.5497 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2258 loss: 1.2258 2022/10/10 06:58:37 - mmengine - INFO - Epoch(train) [67][480/940] lr: 1.0000e-03 eta: 4:25:58 time: 0.4762 data_time: 0.0262 memory: 21547 grad_norm: 4.6302 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1527 loss: 1.1527 2022/10/10 06:58:47 - mmengine - INFO - Epoch(train) [67][500/940] lr: 1.0000e-03 eta: 4:25:48 time: 0.5035 data_time: 0.0300 memory: 21547 grad_norm: 4.5902 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.2402 loss: 1.2402 2022/10/10 06:58:58 - mmengine - INFO - Epoch(train) [67][520/940] lr: 1.0000e-03 eta: 4:25:38 time: 0.5321 data_time: 0.0855 memory: 21547 grad_norm: 4.5596 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2422 loss: 1.2422 2022/10/10 06:59:09 - mmengine - INFO - Epoch(train) [67][540/940] lr: 1.0000e-03 eta: 4:25:28 time: 0.5674 data_time: 0.0245 memory: 21547 grad_norm: 4.5708 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2003 loss: 1.2003 2022/10/10 06:59:19 - mmengine - INFO - Epoch(train) [67][560/940] lr: 1.0000e-03 eta: 4:25:18 time: 0.4608 data_time: 0.0466 memory: 21547 grad_norm: 4.6683 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2045 loss: 1.2045 2022/10/10 06:59:29 - mmengine - INFO - Epoch(train) [67][580/940] lr: 1.0000e-03 eta: 4:25:08 time: 0.5129 data_time: 0.0526 memory: 21547 grad_norm: 4.5251 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2114 loss: 1.2114 2022/10/10 06:59:38 - mmengine - INFO - Epoch(train) [67][600/940] lr: 1.0000e-03 eta: 4:24:57 time: 0.4480 data_time: 0.0290 memory: 21547 grad_norm: 4.5345 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2082 loss: 1.2082 2022/10/10 06:59:48 - mmengine - INFO - Epoch(train) [67][620/940] lr: 1.0000e-03 eta: 4:24:47 time: 0.4959 data_time: 0.0262 memory: 21547 grad_norm: 4.7832 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2914 loss: 1.2914 2022/10/10 06:59:58 - mmengine - INFO - Epoch(train) [67][640/940] lr: 1.0000e-03 eta: 4:24:37 time: 0.5211 data_time: 0.0365 memory: 21547 grad_norm: 4.6421 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1973 loss: 1.1973 2022/10/10 07:00:09 - mmengine - INFO - Epoch(train) [67][660/940] lr: 1.0000e-03 eta: 4:24:27 time: 0.5296 data_time: 0.0239 memory: 21547 grad_norm: 4.5591 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3250 loss: 1.3250 2022/10/10 07:00:19 - mmengine - INFO - Epoch(train) [67][680/940] lr: 1.0000e-03 eta: 4:24:16 time: 0.4936 data_time: 0.0316 memory: 21547 grad_norm: 4.6003 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2247 loss: 1.2247 2022/10/10 07:00:29 - mmengine - INFO - Epoch(train) [67][700/940] lr: 1.0000e-03 eta: 4:24:06 time: 0.5149 data_time: 0.0259 memory: 21547 grad_norm: 4.5012 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1491 loss: 1.1491 2022/10/10 07:00:40 - mmengine - INFO - Epoch(train) [67][720/940] lr: 1.0000e-03 eta: 4:23:57 time: 0.5445 data_time: 0.0287 memory: 21547 grad_norm: 4.5432 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1869 loss: 1.1869 2022/10/10 07:00:49 - mmengine - INFO - Epoch(train) [67][740/940] lr: 1.0000e-03 eta: 4:23:46 time: 0.4829 data_time: 0.0238 memory: 21547 grad_norm: 4.5433 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1980 loss: 1.1980 2022/10/10 07:01:00 - mmengine - INFO - Epoch(train) [67][760/940] lr: 1.0000e-03 eta: 4:23:36 time: 0.5487 data_time: 0.0254 memory: 21547 grad_norm: 4.5753 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3489 loss: 1.3489 2022/10/10 07:01:11 - mmengine - INFO - Epoch(train) [67][780/940] lr: 1.0000e-03 eta: 4:23:26 time: 0.5138 data_time: 0.0258 memory: 21547 grad_norm: 4.6101 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3391 loss: 1.3391 2022/10/10 07:01:21 - mmengine - INFO - Epoch(train) [67][800/940] lr: 1.0000e-03 eta: 4:23:16 time: 0.5234 data_time: 0.0232 memory: 21547 grad_norm: 4.5138 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1640 loss: 1.1640 2022/10/10 07:01:31 - mmengine - INFO - Epoch(train) [67][820/940] lr: 1.0000e-03 eta: 4:23:06 time: 0.4718 data_time: 0.0221 memory: 21547 grad_norm: 4.6032 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2223 loss: 1.2223 2022/10/10 07:01:41 - mmengine - INFO - Epoch(train) [67][840/940] lr: 1.0000e-03 eta: 4:22:56 time: 0.5257 data_time: 0.0276 memory: 21547 grad_norm: 4.5815 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2602 loss: 1.2602 2022/10/10 07:01:50 - mmengine - INFO - Epoch(train) [67][860/940] lr: 1.0000e-03 eta: 4:22:45 time: 0.4457 data_time: 0.0230 memory: 21547 grad_norm: 4.5476 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0529 loss: 1.0529 2022/10/10 07:02:01 - mmengine - INFO - Epoch(train) [67][880/940] lr: 1.0000e-03 eta: 4:22:36 time: 0.5694 data_time: 0.0266 memory: 21547 grad_norm: 4.6139 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.1709 loss: 1.1709 2022/10/10 07:02:11 - mmengine - INFO - Epoch(train) [67][900/940] lr: 1.0000e-03 eta: 4:22:25 time: 0.4579 data_time: 0.0262 memory: 21547 grad_norm: 4.5934 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3538 loss: 1.3538 2022/10/10 07:02:21 - mmengine - INFO - Epoch(train) [67][920/940] lr: 1.0000e-03 eta: 4:22:15 time: 0.5095 data_time: 0.0285 memory: 21547 grad_norm: 4.6111 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2012 loss: 1.2012 2022/10/10 07:02:29 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 07:02:29 - mmengine - INFO - Epoch(train) [67][940/940] lr: 1.0000e-03 eta: 4:22:04 time: 0.4066 data_time: 0.0299 memory: 21547 grad_norm: 4.8076 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.1999 loss: 1.1999 2022/10/10 07:02:41 - mmengine - INFO - Epoch(val) [67][20/78] eta: 0:00:35 time: 0.6066 data_time: 0.4970 memory: 3269 2022/10/10 07:02:50 - mmengine - INFO - Epoch(val) [67][40/78] eta: 0:00:16 time: 0.4222 data_time: 0.3153 memory: 3269 2022/10/10 07:03:01 - mmengine - INFO - Epoch(val) [67][60/78] eta: 0:00:10 time: 0.5631 data_time: 0.4568 memory: 3269 2022/10/10 07:03:10 - mmengine - INFO - Epoch(val) [67][78/78] acc/top1: 0.6755 acc/top5: 0.8706 acc/mean1: 0.6754 2022/10/10 07:03:24 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 07:03:24 - mmengine - INFO - Epoch(train) [68][20/940] lr: 1.0000e-03 eta: 4:21:56 time: 0.6925 data_time: 0.2184 memory: 21547 grad_norm: 4.5943 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2903 loss: 1.2903 2022/10/10 07:03:34 - mmengine - INFO - Epoch(train) [68][40/940] lr: 1.0000e-03 eta: 4:21:45 time: 0.5024 data_time: 0.0248 memory: 21547 grad_norm: 4.6268 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3450 loss: 1.3450 2022/10/10 07:03:45 - mmengine - INFO - Epoch(train) [68][60/940] lr: 1.0000e-03 eta: 4:21:36 time: 0.5375 data_time: 0.0357 memory: 21547 grad_norm: 4.5455 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2943 loss: 1.2943 2022/10/10 07:03:55 - mmengine - INFO - Epoch(train) [68][80/940] lr: 1.0000e-03 eta: 4:21:25 time: 0.4686 data_time: 0.0265 memory: 21547 grad_norm: 4.5927 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1705 loss: 1.1705 2022/10/10 07:04:05 - mmengine - INFO - Epoch(train) [68][100/940] lr: 1.0000e-03 eta: 4:21:15 time: 0.5358 data_time: 0.0414 memory: 21547 grad_norm: 4.5756 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2261 loss: 1.2261 2022/10/10 07:04:15 - mmengine - INFO - Epoch(train) [68][120/940] lr: 1.0000e-03 eta: 4:21:05 time: 0.5078 data_time: 0.0249 memory: 21547 grad_norm: 4.6809 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.2652 loss: 1.2652 2022/10/10 07:04:25 - mmengine - INFO - Epoch(train) [68][140/940] lr: 1.0000e-03 eta: 4:20:55 time: 0.4904 data_time: 0.0270 memory: 21547 grad_norm: 4.6458 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2271 loss: 1.2271 2022/10/10 07:04:35 - mmengine - INFO - Epoch(train) [68][160/940] lr: 1.0000e-03 eta: 4:20:44 time: 0.4960 data_time: 0.0252 memory: 21547 grad_norm: 4.5787 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2734 loss: 1.2734 2022/10/10 07:04:45 - mmengine - INFO - Epoch(train) [68][180/940] lr: 1.0000e-03 eta: 4:20:34 time: 0.5081 data_time: 0.0315 memory: 21547 grad_norm: 4.6762 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3171 loss: 1.3171 2022/10/10 07:04:55 - mmengine - INFO - Epoch(train) [68][200/940] lr: 1.0000e-03 eta: 4:20:24 time: 0.5010 data_time: 0.0279 memory: 21547 grad_norm: 4.5454 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2033 loss: 1.2033 2022/10/10 07:05:05 - mmengine - INFO - Epoch(train) [68][220/940] lr: 1.0000e-03 eta: 4:20:14 time: 0.4942 data_time: 0.0240 memory: 21547 grad_norm: 4.6523 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3105 loss: 1.3105 2022/10/10 07:05:16 - mmengine - INFO - Epoch(train) [68][240/940] lr: 1.0000e-03 eta: 4:20:04 time: 0.5176 data_time: 0.0268 memory: 21547 grad_norm: 4.7212 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2589 loss: 1.2589 2022/10/10 07:05:25 - mmengine - INFO - Epoch(train) [68][260/940] lr: 1.0000e-03 eta: 4:19:54 time: 0.4968 data_time: 0.0251 memory: 21547 grad_norm: 4.7322 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2349 loss: 1.2349 2022/10/10 07:05:35 - mmengine - INFO - Epoch(train) [68][280/940] lr: 1.0000e-03 eta: 4:19:43 time: 0.4868 data_time: 0.0249 memory: 21547 grad_norm: 4.5899 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.2109 loss: 1.2109 2022/10/10 07:05:46 - mmengine - INFO - Epoch(train) [68][300/940] lr: 1.0000e-03 eta: 4:19:33 time: 0.5405 data_time: 0.0283 memory: 21547 grad_norm: 4.7052 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2579 loss: 1.2579 2022/10/10 07:05:56 - mmengine - INFO - Epoch(train) [68][320/940] lr: 1.0000e-03 eta: 4:19:23 time: 0.4969 data_time: 0.0304 memory: 21547 grad_norm: 4.5671 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0957 loss: 1.0957 2022/10/10 07:06:07 - mmengine - INFO - Epoch(train) [68][340/940] lr: 1.0000e-03 eta: 4:19:14 time: 0.5580 data_time: 0.0265 memory: 21547 grad_norm: 4.5618 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1784 loss: 1.1784 2022/10/10 07:06:17 - mmengine - INFO - Epoch(train) [68][360/940] lr: 1.0000e-03 eta: 4:19:03 time: 0.4902 data_time: 0.0280 memory: 21547 grad_norm: 4.5079 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2881 loss: 1.2881 2022/10/10 07:06:27 - mmengine - INFO - Epoch(train) [68][380/940] lr: 1.0000e-03 eta: 4:18:53 time: 0.5250 data_time: 0.0230 memory: 21547 grad_norm: 4.5159 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1573 loss: 1.1573 2022/10/10 07:06:37 - mmengine - INFO - Epoch(train) [68][400/940] lr: 1.0000e-03 eta: 4:18:43 time: 0.4969 data_time: 0.0288 memory: 21547 grad_norm: 4.6649 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1700 loss: 1.1700 2022/10/10 07:06:48 - mmengine - INFO - Epoch(train) [68][420/940] lr: 1.0000e-03 eta: 4:18:33 time: 0.5128 data_time: 0.0228 memory: 21547 grad_norm: 4.6714 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2245 loss: 1.2245 2022/10/10 07:06:58 - mmengine - INFO - Epoch(train) [68][440/940] lr: 1.0000e-03 eta: 4:18:23 time: 0.4937 data_time: 0.0249 memory: 21547 grad_norm: 4.5847 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2373 loss: 1.2373 2022/10/10 07:07:08 - mmengine - INFO - Epoch(train) [68][460/940] lr: 1.0000e-03 eta: 4:18:13 time: 0.5185 data_time: 0.0235 memory: 21547 grad_norm: 4.6119 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2017 loss: 1.2017 2022/10/10 07:07:18 - mmengine - INFO - Epoch(train) [68][480/940] lr: 1.0000e-03 eta: 4:18:02 time: 0.4824 data_time: 0.0268 memory: 21547 grad_norm: 4.6876 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2005 loss: 1.2005 2022/10/10 07:07:28 - mmengine - INFO - Epoch(train) [68][500/940] lr: 1.0000e-03 eta: 4:17:52 time: 0.5063 data_time: 0.0239 memory: 21547 grad_norm: 4.5786 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3474 loss: 1.3474 2022/10/10 07:07:38 - mmengine - INFO - Epoch(train) [68][520/940] lr: 1.0000e-03 eta: 4:17:42 time: 0.5064 data_time: 0.0350 memory: 21547 grad_norm: 4.6211 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1632 loss: 1.1632 2022/10/10 07:07:49 - mmengine - INFO - Epoch(train) [68][540/940] lr: 1.0000e-03 eta: 4:17:32 time: 0.5586 data_time: 0.0249 memory: 21547 grad_norm: 4.7010 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2248 loss: 1.2248 2022/10/10 07:07:59 - mmengine - INFO - Epoch(train) [68][560/940] lr: 1.0000e-03 eta: 4:17:22 time: 0.4820 data_time: 0.0258 memory: 21547 grad_norm: 4.6078 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1249 loss: 1.1249 2022/10/10 07:08:10 - mmengine - INFO - Epoch(train) [68][580/940] lr: 1.0000e-03 eta: 4:17:12 time: 0.5468 data_time: 0.0283 memory: 21547 grad_norm: 4.6966 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2219 loss: 1.2219 2022/10/10 07:08:20 - mmengine - INFO - Epoch(train) [68][600/940] lr: 1.0000e-03 eta: 4:17:02 time: 0.5017 data_time: 0.0238 memory: 21547 grad_norm: 4.5646 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2579 loss: 1.2579 2022/10/10 07:08:30 - mmengine - INFO - Epoch(train) [68][620/940] lr: 1.0000e-03 eta: 4:16:52 time: 0.5078 data_time: 0.0300 memory: 21547 grad_norm: 4.6120 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2479 loss: 1.2479 2022/10/10 07:08:40 - mmengine - INFO - Epoch(train) [68][640/940] lr: 1.0000e-03 eta: 4:16:42 time: 0.5110 data_time: 0.0230 memory: 21547 grad_norm: 4.6951 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3235 loss: 1.3235 2022/10/10 07:08:50 - mmengine - INFO - Epoch(train) [68][660/940] lr: 1.0000e-03 eta: 4:16:32 time: 0.5158 data_time: 0.0269 memory: 21547 grad_norm: 4.5990 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2330 loss: 1.2330 2022/10/10 07:09:00 - mmengine - INFO - Epoch(train) [68][680/940] lr: 1.0000e-03 eta: 4:16:22 time: 0.5079 data_time: 0.0247 memory: 21547 grad_norm: 4.5721 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3042 loss: 1.3042 2022/10/10 07:09:11 - mmengine - INFO - Epoch(train) [68][700/940] lr: 1.0000e-03 eta: 4:16:12 time: 0.5197 data_time: 0.0307 memory: 21547 grad_norm: 4.6306 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1738 loss: 1.1738 2022/10/10 07:09:21 - mmengine - INFO - Epoch(train) [68][720/940] lr: 1.0000e-03 eta: 4:16:01 time: 0.5069 data_time: 0.0258 memory: 21547 grad_norm: 4.7321 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3085 loss: 1.3085 2022/10/10 07:09:32 - mmengine - INFO - Epoch(train) [68][740/940] lr: 1.0000e-03 eta: 4:15:52 time: 0.5515 data_time: 0.0302 memory: 21547 grad_norm: 4.5865 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1763 loss: 1.1763 2022/10/10 07:09:42 - mmengine - INFO - Epoch(train) [68][760/940] lr: 1.0000e-03 eta: 4:15:42 time: 0.5059 data_time: 0.0285 memory: 21547 grad_norm: 4.6337 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2840 loss: 1.2840 2022/10/10 07:09:52 - mmengine - INFO - Epoch(train) [68][780/940] lr: 1.0000e-03 eta: 4:15:31 time: 0.5108 data_time: 0.0266 memory: 21547 grad_norm: 4.5409 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2861 loss: 1.2861 2022/10/10 07:10:02 - mmengine - INFO - Epoch(train) [68][800/940] lr: 1.0000e-03 eta: 4:15:21 time: 0.4639 data_time: 0.0265 memory: 21547 grad_norm: 4.6077 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2753 loss: 1.2753 2022/10/10 07:10:11 - mmengine - INFO - Epoch(train) [68][820/940] lr: 1.0000e-03 eta: 4:15:11 time: 0.4882 data_time: 0.0260 memory: 21547 grad_norm: 4.5934 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2286 loss: 1.2286 2022/10/10 07:10:21 - mmengine - INFO - Epoch(train) [68][840/940] lr: 1.0000e-03 eta: 4:15:00 time: 0.4908 data_time: 0.0248 memory: 21547 grad_norm: 4.6253 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4046 loss: 1.4046 2022/10/10 07:10:31 - mmengine - INFO - Epoch(train) [68][860/940] lr: 1.0000e-03 eta: 4:14:50 time: 0.4872 data_time: 0.0308 memory: 21547 grad_norm: 4.5942 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3490 loss: 1.3490 2022/10/10 07:10:42 - mmengine - INFO - Epoch(train) [68][880/940] lr: 1.0000e-03 eta: 4:14:40 time: 0.5428 data_time: 0.0241 memory: 21547 grad_norm: 4.7637 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2571 loss: 1.2571 2022/10/10 07:10:52 - mmengine - INFO - Epoch(train) [68][900/940] lr: 1.0000e-03 eta: 4:14:30 time: 0.4954 data_time: 0.0348 memory: 21547 grad_norm: 4.5696 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3309 loss: 1.3309 2022/10/10 07:11:01 - mmengine - INFO - Epoch(train) [68][920/940] lr: 1.0000e-03 eta: 4:14:19 time: 0.4597 data_time: 0.0258 memory: 21547 grad_norm: 4.5895 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2348 loss: 1.2348 2022/10/10 07:11:11 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 07:11:11 - mmengine - INFO - Epoch(train) [68][940/940] lr: 1.0000e-03 eta: 4:14:09 time: 0.4845 data_time: 0.0260 memory: 21547 grad_norm: 4.9365 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.1956 loss: 1.1956 2022/10/10 07:11:23 - mmengine - INFO - Epoch(val) [68][20/78] eta: 0:00:35 time: 0.6048 data_time: 0.4963 memory: 3269 2022/10/10 07:11:31 - mmengine - INFO - Epoch(val) [68][40/78] eta: 0:00:16 time: 0.4234 data_time: 0.3168 memory: 3269 2022/10/10 07:11:42 - mmengine - INFO - Epoch(val) [68][60/78] eta: 0:00:10 time: 0.5594 data_time: 0.4533 memory: 3269 2022/10/10 07:11:52 - mmengine - INFO - Epoch(val) [68][78/78] acc/top1: 0.6786 acc/top5: 0.8717 acc/mean1: 0.6785 2022/10/10 07:12:07 - mmengine - INFO - Epoch(train) [69][20/940] lr: 1.0000e-03 eta: 4:14:01 time: 0.7145 data_time: 0.3120 memory: 21547 grad_norm: 4.5448 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2326 loss: 1.2326 2022/10/10 07:12:16 - mmengine - INFO - Epoch(train) [69][40/940] lr: 1.0000e-03 eta: 4:13:50 time: 0.4700 data_time: 0.1015 memory: 21547 grad_norm: 4.6136 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2905 loss: 1.2905 2022/10/10 07:12:27 - mmengine - INFO - Epoch(train) [69][60/940] lr: 1.0000e-03 eta: 4:13:41 time: 0.5690 data_time: 0.1910 memory: 21547 grad_norm: 4.6062 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2399 loss: 1.2399 2022/10/10 07:12:37 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 07:12:37 - mmengine - INFO - Epoch(train) [69][80/940] lr: 1.0000e-03 eta: 4:13:30 time: 0.4598 data_time: 0.0839 memory: 21547 grad_norm: 4.6561 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1720 loss: 1.1720 2022/10/10 07:12:47 - mmengine - INFO - Epoch(train) [69][100/940] lr: 1.0000e-03 eta: 4:13:20 time: 0.4993 data_time: 0.0670 memory: 21547 grad_norm: 4.6153 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2373 loss: 1.2373 2022/10/10 07:12:57 - mmengine - INFO - Epoch(train) [69][120/940] lr: 1.0000e-03 eta: 4:13:10 time: 0.5037 data_time: 0.0338 memory: 21547 grad_norm: 4.6397 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2435 loss: 1.2435 2022/10/10 07:13:07 - mmengine - INFO - Epoch(train) [69][140/940] lr: 1.0000e-03 eta: 4:13:00 time: 0.5359 data_time: 0.0269 memory: 21547 grad_norm: 4.6590 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1313 loss: 1.1313 2022/10/10 07:13:17 - mmengine - INFO - Epoch(train) [69][160/940] lr: 1.0000e-03 eta: 4:12:50 time: 0.4765 data_time: 0.0295 memory: 21547 grad_norm: 4.7099 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.2899 loss: 1.2899 2022/10/10 07:13:27 - mmengine - INFO - Epoch(train) [69][180/940] lr: 1.0000e-03 eta: 4:12:39 time: 0.5140 data_time: 0.0283 memory: 21547 grad_norm: 4.6505 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2185 loss: 1.2185 2022/10/10 07:13:38 - mmengine - INFO - Epoch(train) [69][200/940] lr: 1.0000e-03 eta: 4:12:29 time: 0.5252 data_time: 0.0272 memory: 21547 grad_norm: 4.7076 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1298 loss: 1.1298 2022/10/10 07:13:48 - mmengine - INFO - Epoch(train) [69][220/940] lr: 1.0000e-03 eta: 4:12:19 time: 0.5199 data_time: 0.0265 memory: 21547 grad_norm: 4.6385 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3230 loss: 1.3230 2022/10/10 07:13:58 - mmengine - INFO - Epoch(train) [69][240/940] lr: 1.0000e-03 eta: 4:12:09 time: 0.4850 data_time: 0.0308 memory: 21547 grad_norm: 4.5985 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.1923 loss: 1.1923 2022/10/10 07:14:07 - mmengine - INFO - Epoch(train) [69][260/940] lr: 1.0000e-03 eta: 4:11:59 time: 0.4810 data_time: 0.0257 memory: 21547 grad_norm: 4.5611 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2007 loss: 1.2007 2022/10/10 07:14:18 - mmengine - INFO - Epoch(train) [69][280/940] lr: 1.0000e-03 eta: 4:11:49 time: 0.5126 data_time: 0.0276 memory: 21547 grad_norm: 4.6674 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.2043 loss: 1.2043 2022/10/10 07:14:28 - mmengine - INFO - Epoch(train) [69][300/940] lr: 1.0000e-03 eta: 4:11:39 time: 0.5204 data_time: 0.0305 memory: 21547 grad_norm: 4.7096 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4137 loss: 1.4137 2022/10/10 07:14:38 - mmengine - INFO - Epoch(train) [69][320/940] lr: 1.0000e-03 eta: 4:11:28 time: 0.4926 data_time: 0.0263 memory: 21547 grad_norm: 4.4893 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1897 loss: 1.1897 2022/10/10 07:14:47 - mmengine - INFO - Epoch(train) [69][340/940] lr: 1.0000e-03 eta: 4:11:18 time: 0.4551 data_time: 0.0297 memory: 21547 grad_norm: 4.6124 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2082 loss: 1.2082 2022/10/10 07:14:58 - mmengine - INFO - Epoch(train) [69][360/940] lr: 1.0000e-03 eta: 4:11:08 time: 0.5549 data_time: 0.0255 memory: 21547 grad_norm: 4.6849 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1720 loss: 1.1720 2022/10/10 07:15:08 - mmengine - INFO - Epoch(train) [69][380/940] lr: 1.0000e-03 eta: 4:10:58 time: 0.4844 data_time: 0.0298 memory: 21547 grad_norm: 4.7338 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1927 loss: 1.1927 2022/10/10 07:15:17 - mmengine - INFO - Epoch(train) [69][400/940] lr: 1.0000e-03 eta: 4:10:47 time: 0.4782 data_time: 0.0278 memory: 21547 grad_norm: 4.5752 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.1049 loss: 1.1049 2022/10/10 07:15:29 - mmengine - INFO - Epoch(train) [69][420/940] lr: 1.0000e-03 eta: 4:10:38 time: 0.5885 data_time: 0.0299 memory: 21547 grad_norm: 4.6270 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2302 loss: 1.2302 2022/10/10 07:15:39 - mmengine - INFO - Epoch(train) [69][440/940] lr: 1.0000e-03 eta: 4:10:28 time: 0.4903 data_time: 0.0247 memory: 21547 grad_norm: 4.5178 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2369 loss: 1.2369 2022/10/10 07:15:49 - mmengine - INFO - Epoch(train) [69][460/940] lr: 1.0000e-03 eta: 4:10:17 time: 0.5028 data_time: 0.0294 memory: 21547 grad_norm: 4.8019 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2908 loss: 1.2908 2022/10/10 07:15:59 - mmengine - INFO - Epoch(train) [69][480/940] lr: 1.0000e-03 eta: 4:10:07 time: 0.5071 data_time: 0.0262 memory: 21547 grad_norm: 4.5837 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1251 loss: 1.1251 2022/10/10 07:16:09 - mmengine - INFO - Epoch(train) [69][500/940] lr: 1.0000e-03 eta: 4:09:57 time: 0.4935 data_time: 0.0237 memory: 21547 grad_norm: 4.5732 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1813 loss: 1.1813 2022/10/10 07:16:18 - mmengine - INFO - Epoch(train) [69][520/940] lr: 1.0000e-03 eta: 4:09:46 time: 0.4506 data_time: 0.0261 memory: 21547 grad_norm: 4.6874 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2775 loss: 1.2775 2022/10/10 07:16:29 - mmengine - INFO - Epoch(train) [69][540/940] lr: 1.0000e-03 eta: 4:09:37 time: 0.5535 data_time: 0.0263 memory: 21547 grad_norm: 4.5704 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2922 loss: 1.2922 2022/10/10 07:16:40 - mmengine - INFO - Epoch(train) [69][560/940] lr: 1.0000e-03 eta: 4:09:27 time: 0.5222 data_time: 0.0326 memory: 21547 grad_norm: 4.5713 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2580 loss: 1.2580 2022/10/10 07:16:50 - mmengine - INFO - Epoch(train) [69][580/940] lr: 1.0000e-03 eta: 4:09:16 time: 0.5030 data_time: 0.0250 memory: 21547 grad_norm: 4.6031 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2233 loss: 1.2233 2022/10/10 07:16:59 - mmengine - INFO - Epoch(train) [69][600/940] lr: 1.0000e-03 eta: 4:09:06 time: 0.4826 data_time: 0.0284 memory: 21547 grad_norm: 4.5955 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3968 loss: 1.3968 2022/10/10 07:17:10 - mmengine - INFO - Epoch(train) [69][620/940] lr: 1.0000e-03 eta: 4:08:56 time: 0.5194 data_time: 0.0234 memory: 21547 grad_norm: 4.6646 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1790 loss: 1.1790 2022/10/10 07:17:20 - mmengine - INFO - Epoch(train) [69][640/940] lr: 1.0000e-03 eta: 4:08:46 time: 0.4993 data_time: 0.0289 memory: 21547 grad_norm: 4.5851 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1507 loss: 1.1507 2022/10/10 07:17:29 - mmengine - INFO - Epoch(train) [69][660/940] lr: 1.0000e-03 eta: 4:08:36 time: 0.4858 data_time: 0.0215 memory: 21547 grad_norm: 4.4690 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.0955 loss: 1.0955 2022/10/10 07:17:39 - mmengine - INFO - Epoch(train) [69][680/940] lr: 1.0000e-03 eta: 4:08:25 time: 0.4697 data_time: 0.0284 memory: 21547 grad_norm: 4.6356 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2329 loss: 1.2329 2022/10/10 07:17:50 - mmengine - INFO - Epoch(train) [69][700/940] lr: 1.0000e-03 eta: 4:08:15 time: 0.5413 data_time: 0.0256 memory: 21547 grad_norm: 4.6415 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2322 loss: 1.2322 2022/10/10 07:17:59 - mmengine - INFO - Epoch(train) [69][720/940] lr: 1.0000e-03 eta: 4:08:05 time: 0.4854 data_time: 0.0294 memory: 21547 grad_norm: 4.7821 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3300 loss: 1.3300 2022/10/10 07:18:10 - mmengine - INFO - Epoch(train) [69][740/940] lr: 1.0000e-03 eta: 4:07:55 time: 0.5117 data_time: 0.0298 memory: 21547 grad_norm: 4.7241 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1855 loss: 1.1855 2022/10/10 07:18:20 - mmengine - INFO - Epoch(train) [69][760/940] lr: 1.0000e-03 eta: 4:07:45 time: 0.5237 data_time: 0.0262 memory: 21547 grad_norm: 4.6187 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2291 loss: 1.2291 2022/10/10 07:18:30 - mmengine - INFO - Epoch(train) [69][780/940] lr: 1.0000e-03 eta: 4:07:35 time: 0.5208 data_time: 0.0281 memory: 21547 grad_norm: 4.7870 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2607 loss: 1.2607 2022/10/10 07:18:41 - mmengine - INFO - Epoch(train) [69][800/940] lr: 1.0000e-03 eta: 4:07:25 time: 0.5072 data_time: 0.0285 memory: 21547 grad_norm: 4.6530 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3030 loss: 1.3030 2022/10/10 07:18:51 - mmengine - INFO - Epoch(train) [69][820/940] lr: 1.0000e-03 eta: 4:07:15 time: 0.5093 data_time: 0.0290 memory: 21547 grad_norm: 4.5777 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1014 loss: 1.1014 2022/10/10 07:19:01 - mmengine - INFO - Epoch(train) [69][840/940] lr: 1.0000e-03 eta: 4:07:04 time: 0.4989 data_time: 0.0248 memory: 21547 grad_norm: 4.6665 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.3608 loss: 1.3608 2022/10/10 07:19:11 - mmengine - INFO - Epoch(train) [69][860/940] lr: 1.0000e-03 eta: 4:06:54 time: 0.5076 data_time: 0.0233 memory: 21547 grad_norm: 4.6356 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2325 loss: 1.2325 2022/10/10 07:19:21 - mmengine - INFO - Epoch(train) [69][880/940] lr: 1.0000e-03 eta: 4:06:44 time: 0.5153 data_time: 0.0305 memory: 21547 grad_norm: 4.6520 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1262 loss: 1.1262 2022/10/10 07:19:31 - mmengine - INFO - Epoch(train) [69][900/940] lr: 1.0000e-03 eta: 4:06:34 time: 0.4847 data_time: 0.0233 memory: 21547 grad_norm: 4.5857 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2726 loss: 1.2726 2022/10/10 07:19:41 - mmengine - INFO - Epoch(train) [69][920/940] lr: 1.0000e-03 eta: 4:06:24 time: 0.5211 data_time: 0.0257 memory: 21547 grad_norm: 4.6602 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2559 loss: 1.2559 2022/10/10 07:19:51 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 07:19:51 - mmengine - INFO - Epoch(train) [69][940/940] lr: 1.0000e-03 eta: 4:06:13 time: 0.4582 data_time: 0.0203 memory: 21547 grad_norm: 4.8262 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.1983 loss: 1.1983 2022/10/10 07:19:51 - mmengine - INFO - Saving checkpoint at 69 epochs 2022/10/10 07:20:04 - mmengine - INFO - Epoch(val) [69][20/78] eta: 0:00:35 time: 0.6053 data_time: 0.4999 memory: 3269 2022/10/10 07:20:12 - mmengine - INFO - Epoch(val) [69][40/78] eta: 0:00:16 time: 0.4216 data_time: 0.3151 memory: 3269 2022/10/10 07:20:23 - mmengine - INFO - Epoch(val) [69][60/78] eta: 0:00:10 time: 0.5557 data_time: 0.4495 memory: 3269 2022/10/10 07:20:32 - mmengine - INFO - Epoch(val) [69][78/78] acc/top1: 0.6759 acc/top5: 0.8701 acc/mean1: 0.6758 2022/10/10 07:20:47 - mmengine - INFO - Epoch(train) [70][20/940] lr: 1.0000e-03 eta: 4:06:05 time: 0.7181 data_time: 0.3366 memory: 21547 grad_norm: 4.5957 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1698 loss: 1.1698 2022/10/10 07:20:57 - mmengine - INFO - Epoch(train) [70][40/940] lr: 1.0000e-03 eta: 4:05:55 time: 0.4810 data_time: 0.0892 memory: 21547 grad_norm: 4.5619 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1218 loss: 1.1218 2022/10/10 07:21:07 - mmengine - INFO - Epoch(train) [70][60/940] lr: 1.0000e-03 eta: 4:05:45 time: 0.5185 data_time: 0.0484 memory: 21547 grad_norm: 4.5719 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.2451 loss: 1.2451 2022/10/10 07:21:17 - mmengine - INFO - Epoch(train) [70][80/940] lr: 1.0000e-03 eta: 4:05:34 time: 0.4853 data_time: 0.0797 memory: 21547 grad_norm: 4.7585 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3510 loss: 1.3510 2022/10/10 07:21:27 - mmengine - INFO - Epoch(train) [70][100/940] lr: 1.0000e-03 eta: 4:05:24 time: 0.5412 data_time: 0.0505 memory: 21547 grad_norm: 4.6784 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2749 loss: 1.2749 2022/10/10 07:21:37 - mmengine - INFO - Epoch(train) [70][120/940] lr: 1.0000e-03 eta: 4:05:14 time: 0.4776 data_time: 0.0229 memory: 21547 grad_norm: 4.5900 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.2745 loss: 1.2745 2022/10/10 07:21:47 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 07:21:47 - mmengine - INFO - Epoch(train) [70][140/940] lr: 1.0000e-03 eta: 4:05:04 time: 0.5204 data_time: 0.0264 memory: 21547 grad_norm: 4.6575 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2206 loss: 1.2206 2022/10/10 07:21:57 - mmengine - INFO - Epoch(train) [70][160/940] lr: 1.0000e-03 eta: 4:04:53 time: 0.4692 data_time: 0.0281 memory: 21547 grad_norm: 4.5329 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3186 loss: 1.3186 2022/10/10 07:22:08 - mmengine - INFO - Epoch(train) [70][180/940] lr: 1.0000e-03 eta: 4:04:44 time: 0.5639 data_time: 0.0282 memory: 21547 grad_norm: 4.5982 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2008 loss: 1.2008 2022/10/10 07:22:17 - mmengine - INFO - Epoch(train) [70][200/940] lr: 1.0000e-03 eta: 4:04:33 time: 0.4709 data_time: 0.0300 memory: 21547 grad_norm: 4.6384 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2291 loss: 1.2291 2022/10/10 07:22:28 - mmengine - INFO - Epoch(train) [70][220/940] lr: 1.0000e-03 eta: 4:04:23 time: 0.5136 data_time: 0.0244 memory: 21547 grad_norm: 4.5883 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2399 loss: 1.2399 2022/10/10 07:22:38 - mmengine - INFO - Epoch(train) [70][240/940] lr: 1.0000e-03 eta: 4:04:13 time: 0.4928 data_time: 0.0285 memory: 21547 grad_norm: 4.4717 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1321 loss: 1.1321 2022/10/10 07:22:48 - mmengine - INFO - Epoch(train) [70][260/940] lr: 1.0000e-03 eta: 4:04:03 time: 0.4995 data_time: 0.0247 memory: 21547 grad_norm: 4.6193 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.3391 loss: 1.3391 2022/10/10 07:22:57 - mmengine - INFO - Epoch(train) [70][280/940] lr: 1.0000e-03 eta: 4:03:52 time: 0.4614 data_time: 0.0359 memory: 21547 grad_norm: 4.6262 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2805 loss: 1.2805 2022/10/10 07:23:07 - mmengine - INFO - Epoch(train) [70][300/940] lr: 1.0000e-03 eta: 4:03:42 time: 0.5061 data_time: 0.0277 memory: 21547 grad_norm: 4.6421 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0500 loss: 1.0500 2022/10/10 07:23:18 - mmengine - INFO - Epoch(train) [70][320/940] lr: 1.0000e-03 eta: 4:03:32 time: 0.5318 data_time: 0.0299 memory: 21547 grad_norm: 4.6314 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.2590 loss: 1.2590 2022/10/10 07:23:27 - mmengine - INFO - Epoch(train) [70][340/940] lr: 1.0000e-03 eta: 4:03:22 time: 0.4639 data_time: 0.0289 memory: 21547 grad_norm: 4.6079 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1555 loss: 1.1555 2022/10/10 07:23:37 - mmengine - INFO - Epoch(train) [70][360/940] lr: 1.0000e-03 eta: 4:03:11 time: 0.4959 data_time: 0.0729 memory: 21547 grad_norm: 4.7259 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1792 loss: 1.1792 2022/10/10 07:23:47 - mmengine - INFO - Epoch(train) [70][380/940] lr: 1.0000e-03 eta: 4:03:01 time: 0.5067 data_time: 0.0639 memory: 21547 grad_norm: 4.5544 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2884 loss: 1.2884 2022/10/10 07:23:57 - mmengine - INFO - Epoch(train) [70][400/940] lr: 1.0000e-03 eta: 4:02:51 time: 0.5206 data_time: 0.1257 memory: 21547 grad_norm: 4.6799 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2474 loss: 1.2474 2022/10/10 07:24:07 - mmengine - INFO - Epoch(train) [70][420/940] lr: 1.0000e-03 eta: 4:02:41 time: 0.5032 data_time: 0.0353 memory: 21547 grad_norm: 4.6884 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2810 loss: 1.2810 2022/10/10 07:24:18 - mmengine - INFO - Epoch(train) [70][440/940] lr: 1.0000e-03 eta: 4:02:31 time: 0.5468 data_time: 0.0319 memory: 21547 grad_norm: 4.5801 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3198 loss: 1.3198 2022/10/10 07:24:28 - mmengine - INFO - Epoch(train) [70][460/940] lr: 1.0000e-03 eta: 4:02:21 time: 0.4814 data_time: 0.0268 memory: 21547 grad_norm: 4.6233 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0716 loss: 1.0716 2022/10/10 07:24:38 - mmengine - INFO - Epoch(train) [70][480/940] lr: 1.0000e-03 eta: 4:02:11 time: 0.5042 data_time: 0.0435 memory: 21547 grad_norm: 4.6709 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2088 loss: 1.2088 2022/10/10 07:24:48 - mmengine - INFO - Epoch(train) [70][500/940] lr: 1.0000e-03 eta: 4:02:01 time: 0.4962 data_time: 0.0363 memory: 21547 grad_norm: 4.6510 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1865 loss: 1.1865 2022/10/10 07:24:58 - mmengine - INFO - Epoch(train) [70][520/940] lr: 1.0000e-03 eta: 4:01:50 time: 0.5118 data_time: 0.0275 memory: 21547 grad_norm: 4.5877 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1590 loss: 1.1590 2022/10/10 07:25:09 - mmengine - INFO - Epoch(train) [70][540/940] lr: 1.0000e-03 eta: 4:01:41 time: 0.5389 data_time: 0.0300 memory: 21547 grad_norm: 4.6556 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1541 loss: 1.1541 2022/10/10 07:25:18 - mmengine - INFO - Epoch(train) [70][560/940] lr: 1.0000e-03 eta: 4:01:30 time: 0.4560 data_time: 0.0286 memory: 21547 grad_norm: 4.6138 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1686 loss: 1.1686 2022/10/10 07:25:28 - mmengine - INFO - Epoch(train) [70][580/940] lr: 1.0000e-03 eta: 4:01:20 time: 0.5121 data_time: 0.0277 memory: 21547 grad_norm: 4.5564 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1246 loss: 1.1246 2022/10/10 07:25:38 - mmengine - INFO - Epoch(train) [70][600/940] lr: 1.0000e-03 eta: 4:01:10 time: 0.4997 data_time: 0.0293 memory: 21547 grad_norm: 4.5685 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2216 loss: 1.2216 2022/10/10 07:25:49 - mmengine - INFO - Epoch(train) [70][620/940] lr: 1.0000e-03 eta: 4:01:00 time: 0.5146 data_time: 0.0279 memory: 21547 grad_norm: 4.6105 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2190 loss: 1.2190 2022/10/10 07:25:58 - mmengine - INFO - Epoch(train) [70][640/940] lr: 1.0000e-03 eta: 4:00:49 time: 0.4853 data_time: 0.0293 memory: 21547 grad_norm: 4.7159 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1088 loss: 1.1088 2022/10/10 07:26:08 - mmengine - INFO - Epoch(train) [70][660/940] lr: 1.0000e-03 eta: 4:00:39 time: 0.5061 data_time: 0.0236 memory: 21547 grad_norm: 4.6190 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1930 loss: 1.1930 2022/10/10 07:26:19 - mmengine - INFO - Epoch(train) [70][680/940] lr: 1.0000e-03 eta: 4:00:29 time: 0.5031 data_time: 0.0295 memory: 21547 grad_norm: 4.6001 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.2221 loss: 1.2221 2022/10/10 07:26:29 - mmengine - INFO - Epoch(train) [70][700/940] lr: 1.0000e-03 eta: 4:00:19 time: 0.5424 data_time: 0.0282 memory: 21547 grad_norm: 4.5687 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2590 loss: 1.2590 2022/10/10 07:26:38 - mmengine - INFO - Epoch(train) [70][720/940] lr: 1.0000e-03 eta: 4:00:08 time: 0.4412 data_time: 0.0291 memory: 21547 grad_norm: 4.6024 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.3156 loss: 1.3156 2022/10/10 07:26:48 - mmengine - INFO - Epoch(train) [70][740/940] lr: 1.0000e-03 eta: 3:59:58 time: 0.5040 data_time: 0.0264 memory: 21547 grad_norm: 4.6431 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1729 loss: 1.1729 2022/10/10 07:26:58 - mmengine - INFO - Epoch(train) [70][760/940] lr: 1.0000e-03 eta: 3:59:48 time: 0.4838 data_time: 0.0252 memory: 21547 grad_norm: 4.7402 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2151 loss: 1.2151 2022/10/10 07:27:09 - mmengine - INFO - Epoch(train) [70][780/940] lr: 1.0000e-03 eta: 3:59:38 time: 0.5372 data_time: 0.0302 memory: 21547 grad_norm: 4.6097 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.1413 loss: 1.1413 2022/10/10 07:27:18 - mmengine - INFO - Epoch(train) [70][800/940] lr: 1.0000e-03 eta: 3:59:28 time: 0.4701 data_time: 0.0274 memory: 21547 grad_norm: 4.6507 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.2260 loss: 1.2260 2022/10/10 07:27:29 - mmengine - INFO - Epoch(train) [70][820/940] lr: 1.0000e-03 eta: 3:59:18 time: 0.5434 data_time: 0.0306 memory: 21547 grad_norm: 4.6020 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2648 loss: 1.2648 2022/10/10 07:27:39 - mmengine - INFO - Epoch(train) [70][840/940] lr: 1.0000e-03 eta: 3:59:08 time: 0.5035 data_time: 0.0300 memory: 21547 grad_norm: 4.6198 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2373 loss: 1.2373 2022/10/10 07:27:48 - mmengine - INFO - Epoch(train) [70][860/940] lr: 1.0000e-03 eta: 3:58:57 time: 0.4661 data_time: 0.0281 memory: 21547 grad_norm: 4.5492 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1827 loss: 1.1827 2022/10/10 07:28:00 - mmengine - INFO - Epoch(train) [70][880/940] lr: 1.0000e-03 eta: 3:58:47 time: 0.5697 data_time: 0.0239 memory: 21547 grad_norm: 4.7411 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3272 loss: 1.3272 2022/10/10 07:28:09 - mmengine - INFO - Epoch(train) [70][900/940] lr: 1.0000e-03 eta: 3:58:37 time: 0.4632 data_time: 0.0265 memory: 21547 grad_norm: 4.5723 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2357 loss: 1.2357 2022/10/10 07:28:19 - mmengine - INFO - Epoch(train) [70][920/940] lr: 1.0000e-03 eta: 3:58:27 time: 0.5064 data_time: 0.0284 memory: 21547 grad_norm: 4.6165 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2813 loss: 1.2813 2022/10/10 07:28:28 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 07:28:28 - mmengine - INFO - Epoch(train) [70][940/940] lr: 1.0000e-03 eta: 3:58:16 time: 0.4586 data_time: 0.0355 memory: 21547 grad_norm: 5.1831 top1_acc: 0.4286 top5_acc: 0.5714 loss_cls: 1.3652 loss: 1.3652 2022/10/10 07:28:41 - mmengine - INFO - Epoch(val) [70][20/78] eta: 0:00:35 time: 0.6078 data_time: 0.5009 memory: 3269 2022/10/10 07:28:49 - mmengine - INFO - Epoch(val) [70][40/78] eta: 0:00:15 time: 0.4197 data_time: 0.3129 memory: 3269 2022/10/10 07:29:00 - mmengine - INFO - Epoch(val) [70][60/78] eta: 0:00:09 time: 0.5528 data_time: 0.4444 memory: 3269 2022/10/10 07:29:10 - mmengine - INFO - Epoch(val) [70][78/78] acc/top1: 0.6782 acc/top5: 0.8708 acc/mean1: 0.6780 2022/10/10 07:29:23 - mmengine - INFO - Epoch(train) [71][20/940] lr: 1.0000e-03 eta: 3:58:08 time: 0.6726 data_time: 0.2302 memory: 21547 grad_norm: 4.5654 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2868 loss: 1.2868 2022/10/10 07:29:34 - mmengine - INFO - Epoch(train) [71][40/940] lr: 1.0000e-03 eta: 3:57:57 time: 0.5092 data_time: 0.0628 memory: 21547 grad_norm: 4.6491 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2210 loss: 1.2210 2022/10/10 07:29:45 - mmengine - INFO - Epoch(train) [71][60/940] lr: 1.0000e-03 eta: 3:57:48 time: 0.5525 data_time: 0.0278 memory: 21547 grad_norm: 4.6107 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1589 loss: 1.1589 2022/10/10 07:29:55 - mmengine - INFO - Epoch(train) [71][80/940] lr: 1.0000e-03 eta: 3:57:37 time: 0.4942 data_time: 0.0271 memory: 21547 grad_norm: 4.6713 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.2516 loss: 1.2516 2022/10/10 07:30:06 - mmengine - INFO - Epoch(train) [71][100/940] lr: 1.0000e-03 eta: 3:57:28 time: 0.5539 data_time: 0.0271 memory: 21547 grad_norm: 4.5643 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0909 loss: 1.0909 2022/10/10 07:30:15 - mmengine - INFO - Epoch(train) [71][120/940] lr: 1.0000e-03 eta: 3:57:17 time: 0.4782 data_time: 0.0287 memory: 21547 grad_norm: 4.6399 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3170 loss: 1.3170 2022/10/10 07:30:25 - mmengine - INFO - Epoch(train) [71][140/940] lr: 1.0000e-03 eta: 3:57:07 time: 0.5128 data_time: 0.0277 memory: 21547 grad_norm: 4.6199 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1370 loss: 1.1370 2022/10/10 07:30:35 - mmengine - INFO - Epoch(train) [71][160/940] lr: 1.0000e-03 eta: 3:56:57 time: 0.4805 data_time: 0.0306 memory: 21547 grad_norm: 4.6903 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2541 loss: 1.2541 2022/10/10 07:30:45 - mmengine - INFO - Epoch(train) [71][180/940] lr: 1.0000e-03 eta: 3:56:47 time: 0.5014 data_time: 0.0293 memory: 21547 grad_norm: 4.7223 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2343 loss: 1.2343 2022/10/10 07:30:55 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 07:30:55 - mmengine - INFO - Epoch(train) [71][200/940] lr: 1.0000e-03 eta: 3:56:36 time: 0.5076 data_time: 0.0268 memory: 21547 grad_norm: 4.5737 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2500 loss: 1.2500 2022/10/10 07:31:06 - mmengine - INFO - Epoch(train) [71][220/940] lr: 1.0000e-03 eta: 3:56:27 time: 0.5245 data_time: 0.0272 memory: 21547 grad_norm: 4.6802 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2384 loss: 1.2384 2022/10/10 07:31:16 - mmengine - INFO - Epoch(train) [71][240/940] lr: 1.0000e-03 eta: 3:56:16 time: 0.4939 data_time: 0.0292 memory: 21547 grad_norm: 4.6833 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1387 loss: 1.1387 2022/10/10 07:31:25 - mmengine - INFO - Epoch(train) [71][260/940] lr: 1.0000e-03 eta: 3:56:06 time: 0.4909 data_time: 0.0285 memory: 21547 grad_norm: 4.7638 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.2757 loss: 1.2757 2022/10/10 07:31:35 - mmengine - INFO - Epoch(train) [71][280/940] lr: 1.0000e-03 eta: 3:55:56 time: 0.4972 data_time: 0.0228 memory: 21547 grad_norm: 4.6002 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.1724 loss: 1.1724 2022/10/10 07:31:46 - mmengine - INFO - Epoch(train) [71][300/940] lr: 1.0000e-03 eta: 3:55:46 time: 0.5197 data_time: 0.0290 memory: 21547 grad_norm: 4.5970 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0582 loss: 1.0582 2022/10/10 07:31:55 - mmengine - INFO - Epoch(train) [71][320/940] lr: 1.0000e-03 eta: 3:55:35 time: 0.4448 data_time: 0.0293 memory: 21547 grad_norm: 4.5826 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1035 loss: 1.1035 2022/10/10 07:32:06 - mmengine - INFO - Epoch(train) [71][340/940] lr: 1.0000e-03 eta: 3:55:25 time: 0.5492 data_time: 0.0267 memory: 21547 grad_norm: 4.5766 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2382 loss: 1.2382 2022/10/10 07:32:14 - mmengine - INFO - Epoch(train) [71][360/940] lr: 1.0000e-03 eta: 3:55:15 time: 0.4405 data_time: 0.0260 memory: 21547 grad_norm: 4.7005 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.3009 loss: 1.3009 2022/10/10 07:32:26 - mmengine - INFO - Epoch(train) [71][380/940] lr: 1.0000e-03 eta: 3:55:05 time: 0.5678 data_time: 0.0304 memory: 21547 grad_norm: 4.6983 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2544 loss: 1.2544 2022/10/10 07:32:36 - mmengine - INFO - Epoch(train) [71][400/940] lr: 1.0000e-03 eta: 3:54:55 time: 0.4866 data_time: 0.0309 memory: 21547 grad_norm: 4.6830 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1640 loss: 1.1640 2022/10/10 07:32:46 - mmengine - INFO - Epoch(train) [71][420/940] lr: 1.0000e-03 eta: 3:54:45 time: 0.5159 data_time: 0.0213 memory: 21547 grad_norm: 4.6818 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0603 loss: 1.0603 2022/10/10 07:32:55 - mmengine - INFO - Epoch(train) [71][440/940] lr: 1.0000e-03 eta: 3:54:34 time: 0.4766 data_time: 0.0479 memory: 21547 grad_norm: 4.7706 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2506 loss: 1.2506 2022/10/10 07:33:05 - mmengine - INFO - Epoch(train) [71][460/940] lr: 1.0000e-03 eta: 3:54:24 time: 0.4559 data_time: 0.0297 memory: 21547 grad_norm: 4.6849 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3695 loss: 1.3695 2022/10/10 07:33:14 - mmengine - INFO - Epoch(train) [71][480/940] lr: 1.0000e-03 eta: 3:54:13 time: 0.4847 data_time: 0.0276 memory: 21547 grad_norm: 4.7036 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1820 loss: 1.1820 2022/10/10 07:33:25 - mmengine - INFO - Epoch(train) [71][500/940] lr: 1.0000e-03 eta: 3:54:03 time: 0.5457 data_time: 0.0278 memory: 21547 grad_norm: 4.7829 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2701 loss: 1.2701 2022/10/10 07:33:35 - mmengine - INFO - Epoch(train) [71][520/940] lr: 1.0000e-03 eta: 3:53:53 time: 0.5007 data_time: 0.0275 memory: 21547 grad_norm: 4.7687 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2683 loss: 1.2683 2022/10/10 07:33:46 - mmengine - INFO - Epoch(train) [71][540/940] lr: 1.0000e-03 eta: 3:53:43 time: 0.5196 data_time: 0.0283 memory: 21547 grad_norm: 4.6281 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1759 loss: 1.1759 2022/10/10 07:33:56 - mmengine - INFO - Epoch(train) [71][560/940] lr: 1.0000e-03 eta: 3:53:33 time: 0.5206 data_time: 0.0278 memory: 21547 grad_norm: 4.7302 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1973 loss: 1.1973 2022/10/10 07:34:06 - mmengine - INFO - Epoch(train) [71][580/940] lr: 1.0000e-03 eta: 3:53:23 time: 0.5234 data_time: 0.0283 memory: 21547 grad_norm: 4.6865 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1030 loss: 1.1030 2022/10/10 07:34:16 - mmengine - INFO - Epoch(train) [71][600/940] lr: 1.0000e-03 eta: 3:53:13 time: 0.4893 data_time: 0.0257 memory: 21547 grad_norm: 4.6302 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1627 loss: 1.1627 2022/10/10 07:34:27 - mmengine - INFO - Epoch(train) [71][620/940] lr: 1.0000e-03 eta: 3:53:03 time: 0.5163 data_time: 0.0288 memory: 21547 grad_norm: 4.5949 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1400 loss: 1.1400 2022/10/10 07:34:38 - mmengine - INFO - Epoch(train) [71][640/940] lr: 1.0000e-03 eta: 3:52:53 time: 0.5717 data_time: 0.0253 memory: 21547 grad_norm: 4.6765 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2326 loss: 1.2326 2022/10/10 07:34:48 - mmengine - INFO - Epoch(train) [71][660/940] lr: 1.0000e-03 eta: 3:52:43 time: 0.5078 data_time: 0.0327 memory: 21547 grad_norm: 4.6363 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3696 loss: 1.3696 2022/10/10 07:34:58 - mmengine - INFO - Epoch(train) [71][680/940] lr: 1.0000e-03 eta: 3:52:33 time: 0.4954 data_time: 0.0268 memory: 21547 grad_norm: 4.6656 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2178 loss: 1.2178 2022/10/10 07:35:08 - mmengine - INFO - Epoch(train) [71][700/940] lr: 1.0000e-03 eta: 3:52:23 time: 0.5003 data_time: 0.0258 memory: 21547 grad_norm: 4.7332 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3215 loss: 1.3215 2022/10/10 07:35:18 - mmengine - INFO - Epoch(train) [71][720/940] lr: 1.0000e-03 eta: 3:52:12 time: 0.4891 data_time: 0.0262 memory: 21547 grad_norm: 4.6414 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2202 loss: 1.2202 2022/10/10 07:35:28 - mmengine - INFO - Epoch(train) [71][740/940] lr: 1.0000e-03 eta: 3:52:02 time: 0.4948 data_time: 0.0338 memory: 21547 grad_norm: 4.7376 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3135 loss: 1.3135 2022/10/10 07:35:37 - mmengine - INFO - Epoch(train) [71][760/940] lr: 1.0000e-03 eta: 3:51:52 time: 0.4656 data_time: 0.0222 memory: 21547 grad_norm: 4.6867 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.1452 loss: 1.1452 2022/10/10 07:35:47 - mmengine - INFO - Epoch(train) [71][780/940] lr: 1.0000e-03 eta: 3:51:41 time: 0.4770 data_time: 0.0261 memory: 21547 grad_norm: 4.6192 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3134 loss: 1.3134 2022/10/10 07:35:58 - mmengine - INFO - Epoch(train) [71][800/940] lr: 1.0000e-03 eta: 3:51:32 time: 0.5542 data_time: 0.0349 memory: 21547 grad_norm: 4.6465 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3179 loss: 1.3179 2022/10/10 07:36:07 - mmengine - INFO - Epoch(train) [71][820/940] lr: 1.0000e-03 eta: 3:51:21 time: 0.4881 data_time: 0.0290 memory: 21547 grad_norm: 4.6524 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2846 loss: 1.2846 2022/10/10 07:36:18 - mmengine - INFO - Epoch(train) [71][840/940] lr: 1.0000e-03 eta: 3:51:11 time: 0.5129 data_time: 0.0232 memory: 21547 grad_norm: 4.6080 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1546 loss: 1.1546 2022/10/10 07:36:28 - mmengine - INFO - Epoch(train) [71][860/940] lr: 1.0000e-03 eta: 3:51:01 time: 0.4916 data_time: 0.0444 memory: 21547 grad_norm: 4.6967 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2261 loss: 1.2261 2022/10/10 07:36:38 - mmengine - INFO - Epoch(train) [71][880/940] lr: 1.0000e-03 eta: 3:50:51 time: 0.5075 data_time: 0.0295 memory: 21547 grad_norm: 4.6424 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1379 loss: 1.1379 2022/10/10 07:36:48 - mmengine - INFO - Epoch(train) [71][900/940] lr: 1.0000e-03 eta: 3:50:41 time: 0.5225 data_time: 0.0310 memory: 21547 grad_norm: 4.7715 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2784 loss: 1.2784 2022/10/10 07:36:59 - mmengine - INFO - Epoch(train) [71][920/940] lr: 1.0000e-03 eta: 3:50:31 time: 0.5588 data_time: 0.0243 memory: 21547 grad_norm: 4.7249 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2760 loss: 1.2760 2022/10/10 07:37:08 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 07:37:08 - mmengine - INFO - Epoch(train) [71][940/940] lr: 1.0000e-03 eta: 3:50:20 time: 0.4400 data_time: 0.0217 memory: 21547 grad_norm: 4.9884 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.2399 loss: 1.2399 2022/10/10 07:37:20 - mmengine - INFO - Epoch(val) [71][20/78] eta: 0:00:35 time: 0.6072 data_time: 0.4933 memory: 3269 2022/10/10 07:37:29 - mmengine - INFO - Epoch(val) [71][40/78] eta: 0:00:16 time: 0.4232 data_time: 0.3161 memory: 3269 2022/10/10 07:37:40 - mmengine - INFO - Epoch(val) [71][60/78] eta: 0:00:09 time: 0.5551 data_time: 0.4491 memory: 3269 2022/10/10 07:37:50 - mmengine - INFO - Epoch(val) [71][78/78] acc/top1: 0.6779 acc/top5: 0.8714 acc/mean1: 0.6778 2022/10/10 07:38:04 - mmengine - INFO - Epoch(train) [72][20/940] lr: 1.0000e-03 eta: 3:50:12 time: 0.7007 data_time: 0.2943 memory: 21547 grad_norm: 4.6365 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2671 loss: 1.2671 2022/10/10 07:38:14 - mmengine - INFO - Epoch(train) [72][40/940] lr: 1.0000e-03 eta: 3:50:02 time: 0.4943 data_time: 0.1209 memory: 21547 grad_norm: 4.5636 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2302 loss: 1.2302 2022/10/10 07:38:25 - mmengine - INFO - Epoch(train) [72][60/940] lr: 1.0000e-03 eta: 3:49:52 time: 0.5794 data_time: 0.0345 memory: 21547 grad_norm: 4.6885 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.0510 loss: 1.0510 2022/10/10 07:38:35 - mmengine - INFO - Epoch(train) [72][80/940] lr: 1.0000e-03 eta: 3:49:41 time: 0.4618 data_time: 0.0241 memory: 21547 grad_norm: 4.7419 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1284 loss: 1.1284 2022/10/10 07:38:45 - mmengine - INFO - Epoch(train) [72][100/940] lr: 1.0000e-03 eta: 3:49:31 time: 0.5056 data_time: 0.0289 memory: 21547 grad_norm: 4.5759 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0942 loss: 1.0942 2022/10/10 07:38:54 - mmengine - INFO - Epoch(train) [72][120/940] lr: 1.0000e-03 eta: 3:49:21 time: 0.4639 data_time: 0.0259 memory: 21547 grad_norm: 4.7351 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2891 loss: 1.2891 2022/10/10 07:39:05 - mmengine - INFO - Epoch(train) [72][140/940] lr: 1.0000e-03 eta: 3:49:11 time: 0.5305 data_time: 0.0263 memory: 21547 grad_norm: 4.6310 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.2085 loss: 1.2085 2022/10/10 07:39:15 - mmengine - INFO - Epoch(train) [72][160/940] lr: 1.0000e-03 eta: 3:49:01 time: 0.4979 data_time: 0.0301 memory: 21547 grad_norm: 4.5752 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1412 loss: 1.1412 2022/10/10 07:39:25 - mmengine - INFO - Epoch(train) [72][180/940] lr: 1.0000e-03 eta: 3:48:51 time: 0.5078 data_time: 0.0291 memory: 21547 grad_norm: 4.7202 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1316 loss: 1.1316 2022/10/10 07:39:34 - mmengine - INFO - Epoch(train) [72][200/940] lr: 1.0000e-03 eta: 3:48:40 time: 0.4652 data_time: 0.0307 memory: 21547 grad_norm: 4.6744 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2212 loss: 1.2212 2022/10/10 07:39:44 - mmengine - INFO - Epoch(train) [72][220/940] lr: 1.0000e-03 eta: 3:48:30 time: 0.5073 data_time: 0.0262 memory: 21547 grad_norm: 4.6191 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2276 loss: 1.2276 2022/10/10 07:39:55 - mmengine - INFO - Epoch(train) [72][240/940] lr: 1.0000e-03 eta: 3:48:20 time: 0.5309 data_time: 0.0307 memory: 21547 grad_norm: 4.5221 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.1969 loss: 1.1969 2022/10/10 07:40:05 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 07:40:05 - mmengine - INFO - Epoch(train) [72][260/940] lr: 1.0000e-03 eta: 3:48:10 time: 0.5311 data_time: 0.0279 memory: 21547 grad_norm: 4.6363 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2920 loss: 1.2920 2022/10/10 07:40:15 - mmengine - INFO - Epoch(train) [72][280/940] lr: 1.0000e-03 eta: 3:48:00 time: 0.4818 data_time: 0.0269 memory: 21547 grad_norm: 4.6845 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.2475 loss: 1.2475 2022/10/10 07:40:25 - mmengine - INFO - Epoch(train) [72][300/940] lr: 1.0000e-03 eta: 3:47:50 time: 0.5150 data_time: 0.0297 memory: 21547 grad_norm: 4.6739 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2276 loss: 1.2276 2022/10/10 07:40:35 - mmengine - INFO - Epoch(train) [72][320/940] lr: 1.0000e-03 eta: 3:47:39 time: 0.4844 data_time: 0.0308 memory: 21547 grad_norm: 4.6895 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2009 loss: 1.2009 2022/10/10 07:40:45 - mmengine - INFO - Epoch(train) [72][340/940] lr: 1.0000e-03 eta: 3:47:29 time: 0.5033 data_time: 0.0253 memory: 21547 grad_norm: 4.6901 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1834 loss: 1.1834 2022/10/10 07:40:55 - mmengine - INFO - Epoch(train) [72][360/940] lr: 1.0000e-03 eta: 3:47:19 time: 0.5074 data_time: 0.1224 memory: 21547 grad_norm: 4.7211 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2639 loss: 1.2639 2022/10/10 07:41:05 - mmengine - INFO - Epoch(train) [72][380/940] lr: 1.0000e-03 eta: 3:47:09 time: 0.4897 data_time: 0.1089 memory: 21547 grad_norm: 4.7236 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2550 loss: 1.2550 2022/10/10 07:41:15 - mmengine - INFO - Epoch(train) [72][400/940] lr: 1.0000e-03 eta: 3:46:59 time: 0.5087 data_time: 0.1372 memory: 21547 grad_norm: 4.7739 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2454 loss: 1.2454 2022/10/10 07:41:25 - mmengine - INFO - Epoch(train) [72][420/940] lr: 1.0000e-03 eta: 3:46:48 time: 0.4754 data_time: 0.0818 memory: 21547 grad_norm: 4.6832 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3070 loss: 1.3070 2022/10/10 07:41:36 - mmengine - INFO - Epoch(train) [72][440/940] lr: 1.0000e-03 eta: 3:46:39 time: 0.5717 data_time: 0.1723 memory: 21547 grad_norm: 4.7239 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3546 loss: 1.3546 2022/10/10 07:41:46 - mmengine - INFO - Epoch(train) [72][460/940] lr: 1.0000e-03 eta: 3:46:28 time: 0.4683 data_time: 0.0598 memory: 21547 grad_norm: 4.6712 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1599 loss: 1.1599 2022/10/10 07:41:56 - mmengine - INFO - Epoch(train) [72][480/940] lr: 1.0000e-03 eta: 3:46:18 time: 0.5130 data_time: 0.1277 memory: 21547 grad_norm: 4.6072 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2626 loss: 1.2626 2022/10/10 07:42:05 - mmengine - INFO - Epoch(train) [72][500/940] lr: 1.0000e-03 eta: 3:46:07 time: 0.4653 data_time: 0.0695 memory: 21547 grad_norm: 4.5820 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1886 loss: 1.1886 2022/10/10 07:42:15 - mmengine - INFO - Epoch(train) [72][520/940] lr: 1.0000e-03 eta: 3:45:57 time: 0.4936 data_time: 0.1180 memory: 21547 grad_norm: 4.6325 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3187 loss: 1.3187 2022/10/10 07:42:25 - mmengine - INFO - Epoch(train) [72][540/940] lr: 1.0000e-03 eta: 3:45:47 time: 0.5013 data_time: 0.0249 memory: 21547 grad_norm: 4.6923 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1663 loss: 1.1663 2022/10/10 07:42:34 - mmengine - INFO - Epoch(train) [72][560/940] lr: 1.0000e-03 eta: 3:45:37 time: 0.4660 data_time: 0.0298 memory: 21547 grad_norm: 4.7194 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2518 loss: 1.2518 2022/10/10 07:42:46 - mmengine - INFO - Epoch(train) [72][580/940] lr: 1.0000e-03 eta: 3:45:27 time: 0.5645 data_time: 0.0254 memory: 21547 grad_norm: 4.7071 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3510 loss: 1.3510 2022/10/10 07:42:55 - mmengine - INFO - Epoch(train) [72][600/940] lr: 1.0000e-03 eta: 3:45:17 time: 0.4887 data_time: 0.0296 memory: 21547 grad_norm: 4.7949 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2203 loss: 1.2203 2022/10/10 07:43:05 - mmengine - INFO - Epoch(train) [72][620/940] lr: 1.0000e-03 eta: 3:45:06 time: 0.4850 data_time: 0.0283 memory: 21547 grad_norm: 4.7300 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.2569 loss: 1.2569 2022/10/10 07:43:16 - mmengine - INFO - Epoch(train) [72][640/940] lr: 1.0000e-03 eta: 3:44:57 time: 0.5567 data_time: 0.0248 memory: 21547 grad_norm: 4.6437 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3600 loss: 1.3600 2022/10/10 07:43:26 - mmengine - INFO - Epoch(train) [72][660/940] lr: 1.0000e-03 eta: 3:44:46 time: 0.4843 data_time: 0.0303 memory: 21547 grad_norm: 4.7992 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2770 loss: 1.2770 2022/10/10 07:43:36 - mmengine - INFO - Epoch(train) [72][680/940] lr: 1.0000e-03 eta: 3:44:36 time: 0.5126 data_time: 0.0283 memory: 21547 grad_norm: 4.6498 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1423 loss: 1.1423 2022/10/10 07:43:46 - mmengine - INFO - Epoch(train) [72][700/940] lr: 1.0000e-03 eta: 3:44:26 time: 0.4816 data_time: 0.0274 memory: 21547 grad_norm: 4.6284 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2792 loss: 1.2792 2022/10/10 07:43:57 - mmengine - INFO - Epoch(train) [72][720/940] lr: 1.0000e-03 eta: 3:44:16 time: 0.5431 data_time: 0.0237 memory: 21547 grad_norm: 4.7323 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2427 loss: 1.2427 2022/10/10 07:44:06 - mmengine - INFO - Epoch(train) [72][740/940] lr: 1.0000e-03 eta: 3:44:06 time: 0.4826 data_time: 0.0271 memory: 21547 grad_norm: 4.5915 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1632 loss: 1.1632 2022/10/10 07:44:16 - mmengine - INFO - Epoch(train) [72][760/940] lr: 1.0000e-03 eta: 3:43:55 time: 0.4801 data_time: 0.0303 memory: 21547 grad_norm: 4.8240 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2070 loss: 1.2070 2022/10/10 07:44:27 - mmengine - INFO - Epoch(train) [72][780/940] lr: 1.0000e-03 eta: 3:43:46 time: 0.5579 data_time: 0.0270 memory: 21547 grad_norm: 4.7502 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3543 loss: 1.3543 2022/10/10 07:44:37 - mmengine - INFO - Epoch(train) [72][800/940] lr: 1.0000e-03 eta: 3:43:35 time: 0.4950 data_time: 0.0243 memory: 21547 grad_norm: 4.6994 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1780 loss: 1.1780 2022/10/10 07:44:47 - mmengine - INFO - Epoch(train) [72][820/940] lr: 1.0000e-03 eta: 3:43:25 time: 0.4835 data_time: 0.0325 memory: 21547 grad_norm: 4.6865 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2866 loss: 1.2866 2022/10/10 07:44:56 - mmengine - INFO - Epoch(train) [72][840/940] lr: 1.0000e-03 eta: 3:43:14 time: 0.4618 data_time: 0.0251 memory: 21547 grad_norm: 4.7793 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.2805 loss: 1.2805 2022/10/10 07:45:05 - mmengine - INFO - Epoch(train) [72][860/940] lr: 1.0000e-03 eta: 3:43:04 time: 0.4762 data_time: 0.0252 memory: 21547 grad_norm: 4.6332 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1213 loss: 1.1213 2022/10/10 07:45:15 - mmengine - INFO - Epoch(train) [72][880/940] lr: 1.0000e-03 eta: 3:42:54 time: 0.4924 data_time: 0.0286 memory: 21547 grad_norm: 4.6946 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2733 loss: 1.2733 2022/10/10 07:45:25 - mmengine - INFO - Epoch(train) [72][900/940] lr: 1.0000e-03 eta: 3:42:44 time: 0.5021 data_time: 0.0286 memory: 21547 grad_norm: 4.6807 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1161 loss: 1.1161 2022/10/10 07:45:35 - mmengine - INFO - Epoch(train) [72][920/940] lr: 1.0000e-03 eta: 3:42:34 time: 0.5060 data_time: 0.0328 memory: 21547 grad_norm: 4.7026 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1777 loss: 1.1777 2022/10/10 07:45:45 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 07:45:45 - mmengine - INFO - Epoch(train) [72][940/940] lr: 1.0000e-03 eta: 3:42:23 time: 0.4603 data_time: 0.0231 memory: 21547 grad_norm: 4.8846 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.2614 loss: 1.2614 2022/10/10 07:45:45 - mmengine - INFO - Saving checkpoint at 72 epochs 2022/10/10 07:45:58 - mmengine - INFO - Epoch(val) [72][20/78] eta: 0:00:35 time: 0.6128 data_time: 0.5088 memory: 3269 2022/10/10 07:46:06 - mmengine - INFO - Epoch(val) [72][40/78] eta: 0:00:16 time: 0.4263 data_time: 0.3189 memory: 3269 2022/10/10 07:46:17 - mmengine - INFO - Epoch(val) [72][60/78] eta: 0:00:09 time: 0.5481 data_time: 0.4429 memory: 3269 2022/10/10 07:46:27 - mmengine - INFO - Epoch(val) [72][78/78] acc/top1: 0.6760 acc/top5: 0.8712 acc/mean1: 0.6759 2022/10/10 07:46:40 - mmengine - INFO - Epoch(train) [73][20/940] lr: 1.0000e-03 eta: 3:42:14 time: 0.6963 data_time: 0.2178 memory: 21547 grad_norm: 4.5389 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1103 loss: 1.1103 2022/10/10 07:46:50 - mmengine - INFO - Epoch(train) [73][40/940] lr: 1.0000e-03 eta: 3:42:04 time: 0.4691 data_time: 0.0268 memory: 21547 grad_norm: 4.6115 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.1619 loss: 1.1619 2022/10/10 07:47:01 - mmengine - INFO - Epoch(train) [73][60/940] lr: 1.0000e-03 eta: 3:41:54 time: 0.5481 data_time: 0.0262 memory: 21547 grad_norm: 4.7154 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2558 loss: 1.2558 2022/10/10 07:47:11 - mmengine - INFO - Epoch(train) [73][80/940] lr: 1.0000e-03 eta: 3:41:44 time: 0.4931 data_time: 0.0279 memory: 21547 grad_norm: 4.6448 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3986 loss: 1.3986 2022/10/10 07:47:22 - mmengine - INFO - Epoch(train) [73][100/940] lr: 1.0000e-03 eta: 3:41:34 time: 0.5448 data_time: 0.0387 memory: 21547 grad_norm: 4.7171 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2628 loss: 1.2628 2022/10/10 07:47:31 - mmengine - INFO - Epoch(train) [73][120/940] lr: 1.0000e-03 eta: 3:41:24 time: 0.4671 data_time: 0.0248 memory: 21547 grad_norm: 4.6586 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2442 loss: 1.2442 2022/10/10 07:47:41 - mmengine - INFO - Epoch(train) [73][140/940] lr: 1.0000e-03 eta: 3:41:13 time: 0.5039 data_time: 0.0276 memory: 21547 grad_norm: 4.6905 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.2686 loss: 1.2686 2022/10/10 07:47:51 - mmengine - INFO - Epoch(train) [73][160/940] lr: 1.0000e-03 eta: 3:41:03 time: 0.4886 data_time: 0.0924 memory: 21547 grad_norm: 4.6936 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2384 loss: 1.2384 2022/10/10 07:48:01 - mmengine - INFO - Epoch(train) [73][180/940] lr: 1.0000e-03 eta: 3:40:53 time: 0.5057 data_time: 0.0757 memory: 21547 grad_norm: 4.6639 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3043 loss: 1.3043 2022/10/10 07:48:11 - mmengine - INFO - Epoch(train) [73][200/940] lr: 1.0000e-03 eta: 3:40:43 time: 0.5123 data_time: 0.0713 memory: 21547 grad_norm: 4.7312 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1759 loss: 1.1759 2022/10/10 07:48:21 - mmengine - INFO - Epoch(train) [73][220/940] lr: 1.0000e-03 eta: 3:40:33 time: 0.4931 data_time: 0.0273 memory: 21547 grad_norm: 4.7291 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.1307 loss: 1.1307 2022/10/10 07:48:31 - mmengine - INFO - Epoch(train) [73][240/940] lr: 1.0000e-03 eta: 3:40:22 time: 0.4865 data_time: 0.0492 memory: 21547 grad_norm: 4.7220 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3534 loss: 1.3534 2022/10/10 07:48:41 - mmengine - INFO - Epoch(train) [73][260/940] lr: 1.0000e-03 eta: 3:40:12 time: 0.5319 data_time: 0.1328 memory: 21547 grad_norm: 4.6958 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2093 loss: 1.2093 2022/10/10 07:48:51 - mmengine - INFO - Epoch(train) [73][280/940] lr: 1.0000e-03 eta: 3:40:02 time: 0.4786 data_time: 0.0537 memory: 21547 grad_norm: 4.6705 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.3329 loss: 1.3329 2022/10/10 07:49:02 - mmengine - INFO - Epoch(train) [73][300/940] lr: 1.0000e-03 eta: 3:39:52 time: 0.5400 data_time: 0.0621 memory: 21547 grad_norm: 4.6331 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.1282 loss: 1.1282 2022/10/10 07:49:12 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 07:49:12 - mmengine - INFO - Epoch(train) [73][320/940] lr: 1.0000e-03 eta: 3:39:42 time: 0.5218 data_time: 0.0238 memory: 21547 grad_norm: 4.6394 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2675 loss: 1.2675 2022/10/10 07:49:23 - mmengine - INFO - Epoch(train) [73][340/940] lr: 1.0000e-03 eta: 3:39:32 time: 0.5186 data_time: 0.0309 memory: 21547 grad_norm: 4.7213 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3481 loss: 1.3481 2022/10/10 07:49:32 - mmengine - INFO - Epoch(train) [73][360/940] lr: 1.0000e-03 eta: 3:39:21 time: 0.4476 data_time: 0.0247 memory: 21547 grad_norm: 4.5955 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0672 loss: 1.0672 2022/10/10 07:49:43 - mmengine - INFO - Epoch(train) [73][380/940] lr: 1.0000e-03 eta: 3:39:12 time: 0.5756 data_time: 0.0315 memory: 21547 grad_norm: 4.6330 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.1377 loss: 1.1377 2022/10/10 07:49:53 - mmengine - INFO - Epoch(train) [73][400/940] lr: 1.0000e-03 eta: 3:39:01 time: 0.4720 data_time: 0.0242 memory: 21547 grad_norm: 4.7603 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2204 loss: 1.2204 2022/10/10 07:50:03 - mmengine - INFO - Epoch(train) [73][420/940] lr: 1.0000e-03 eta: 3:38:51 time: 0.5176 data_time: 0.0296 memory: 21547 grad_norm: 4.5993 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1300 loss: 1.1300 2022/10/10 07:50:13 - mmengine - INFO - Epoch(train) [73][440/940] lr: 1.0000e-03 eta: 3:38:41 time: 0.5304 data_time: 0.0273 memory: 21547 grad_norm: 4.6352 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1799 loss: 1.1799 2022/10/10 07:50:24 - mmengine - INFO - Epoch(train) [73][460/940] lr: 1.0000e-03 eta: 3:38:31 time: 0.5286 data_time: 0.0291 memory: 21547 grad_norm: 4.6986 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2724 loss: 1.2724 2022/10/10 07:50:33 - mmengine - INFO - Epoch(train) [73][480/940] lr: 1.0000e-03 eta: 3:38:21 time: 0.4655 data_time: 0.0335 memory: 21547 grad_norm: 4.6521 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1532 loss: 1.1532 2022/10/10 07:50:43 - mmengine - INFO - Epoch(train) [73][500/940] lr: 1.0000e-03 eta: 3:38:11 time: 0.5015 data_time: 0.0260 memory: 21547 grad_norm: 4.7397 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3013 loss: 1.3013 2022/10/10 07:50:53 - mmengine - INFO - Epoch(train) [73][520/940] lr: 1.0000e-03 eta: 3:38:01 time: 0.5024 data_time: 0.0301 memory: 21547 grad_norm: 4.5922 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1488 loss: 1.1488 2022/10/10 07:51:04 - mmengine - INFO - Epoch(train) [73][540/940] lr: 1.0000e-03 eta: 3:37:50 time: 0.5069 data_time: 0.0276 memory: 21547 grad_norm: 4.6835 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1784 loss: 1.1784 2022/10/10 07:51:14 - mmengine - INFO - Epoch(train) [73][560/940] lr: 1.0000e-03 eta: 3:37:40 time: 0.5006 data_time: 0.0246 memory: 21547 grad_norm: 4.6359 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1713 loss: 1.1713 2022/10/10 07:51:24 - mmengine - INFO - Epoch(train) [73][580/940] lr: 1.0000e-03 eta: 3:37:30 time: 0.5325 data_time: 0.0272 memory: 21547 grad_norm: 4.6937 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3133 loss: 1.3133 2022/10/10 07:51:33 - mmengine - INFO - Epoch(train) [73][600/940] lr: 1.0000e-03 eta: 3:37:20 time: 0.4511 data_time: 0.0279 memory: 21547 grad_norm: 4.6768 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2683 loss: 1.2683 2022/10/10 07:51:43 - mmengine - INFO - Epoch(train) [73][620/940] lr: 1.0000e-03 eta: 3:37:10 time: 0.5069 data_time: 0.0300 memory: 21547 grad_norm: 4.7056 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2619 loss: 1.2619 2022/10/10 07:51:53 - mmengine - INFO - Epoch(train) [73][640/940] lr: 1.0000e-03 eta: 3:36:59 time: 0.4998 data_time: 0.0413 memory: 21547 grad_norm: 4.7347 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2176 loss: 1.2176 2022/10/10 07:52:03 - mmengine - INFO - Epoch(train) [73][660/940] lr: 1.0000e-03 eta: 3:36:49 time: 0.4855 data_time: 0.0265 memory: 21547 grad_norm: 4.7042 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1277 loss: 1.1277 2022/10/10 07:52:13 - mmengine - INFO - Epoch(train) [73][680/940] lr: 1.0000e-03 eta: 3:36:39 time: 0.4825 data_time: 0.0310 memory: 21547 grad_norm: 4.7400 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1577 loss: 1.1577 2022/10/10 07:52:24 - mmengine - INFO - Epoch(train) [73][700/940] lr: 1.0000e-03 eta: 3:36:29 time: 0.5767 data_time: 0.0252 memory: 21547 grad_norm: 4.6867 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1575 loss: 1.1575 2022/10/10 07:52:35 - mmengine - INFO - Epoch(train) [73][720/940] lr: 1.0000e-03 eta: 3:36:19 time: 0.5134 data_time: 0.0361 memory: 21547 grad_norm: 4.8091 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1157 loss: 1.1157 2022/10/10 07:52:44 - mmengine - INFO - Epoch(train) [73][740/940] lr: 1.0000e-03 eta: 3:36:09 time: 0.4789 data_time: 0.0252 memory: 21547 grad_norm: 4.6755 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1556 loss: 1.1556 2022/10/10 07:52:54 - mmengine - INFO - Epoch(train) [73][760/940] lr: 1.0000e-03 eta: 3:35:58 time: 0.4765 data_time: 0.0336 memory: 21547 grad_norm: 4.7191 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2726 loss: 1.2726 2022/10/10 07:53:04 - mmengine - INFO - Epoch(train) [73][780/940] lr: 1.0000e-03 eta: 3:35:48 time: 0.5174 data_time: 0.0293 memory: 21547 grad_norm: 4.7076 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1168 loss: 1.1168 2022/10/10 07:53:14 - mmengine - INFO - Epoch(train) [73][800/940] lr: 1.0000e-03 eta: 3:35:38 time: 0.4991 data_time: 0.0275 memory: 21547 grad_norm: 4.8802 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3266 loss: 1.3266 2022/10/10 07:53:25 - mmengine - INFO - Epoch(train) [73][820/940] lr: 1.0000e-03 eta: 3:35:28 time: 0.5704 data_time: 0.0254 memory: 21547 grad_norm: 4.7292 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2678 loss: 1.2678 2022/10/10 07:53:35 - mmengine - INFO - Epoch(train) [73][840/940] lr: 1.0000e-03 eta: 3:35:18 time: 0.4805 data_time: 0.0222 memory: 21547 grad_norm: 4.8087 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2895 loss: 1.2895 2022/10/10 07:53:46 - mmengine - INFO - Epoch(train) [73][860/940] lr: 1.0000e-03 eta: 3:35:08 time: 0.5422 data_time: 0.0263 memory: 21547 grad_norm: 4.8296 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3895 loss: 1.3895 2022/10/10 07:53:56 - mmengine - INFO - Epoch(train) [73][880/940] lr: 1.0000e-03 eta: 3:34:58 time: 0.5099 data_time: 0.0278 memory: 21547 grad_norm: 4.6531 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2093 loss: 1.2093 2022/10/10 07:54:07 - mmengine - INFO - Epoch(train) [73][900/940] lr: 1.0000e-03 eta: 3:34:48 time: 0.5263 data_time: 0.0244 memory: 21547 grad_norm: 4.7861 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.2371 loss: 1.2371 2022/10/10 07:54:16 - mmengine - INFO - Epoch(train) [73][920/940] lr: 1.0000e-03 eta: 3:34:38 time: 0.4699 data_time: 0.0236 memory: 21547 grad_norm: 4.6462 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1528 loss: 1.1528 2022/10/10 07:54:25 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 07:54:25 - mmengine - INFO - Epoch(train) [73][940/940] lr: 1.0000e-03 eta: 3:34:27 time: 0.4664 data_time: 0.0224 memory: 21547 grad_norm: 5.1361 top1_acc: 0.4286 top5_acc: 1.0000 loss_cls: 1.2441 loss: 1.2441 2022/10/10 07:54:38 - mmengine - INFO - Epoch(val) [73][20/78] eta: 0:00:35 time: 0.6103 data_time: 0.5010 memory: 3269 2022/10/10 07:54:46 - mmengine - INFO - Epoch(val) [73][40/78] eta: 0:00:15 time: 0.4206 data_time: 0.3122 memory: 3269 2022/10/10 07:54:57 - mmengine - INFO - Epoch(val) [73][60/78] eta: 0:00:10 time: 0.5594 data_time: 0.4521 memory: 3269 2022/10/10 07:55:07 - mmengine - INFO - Epoch(val) [73][78/78] acc/top1: 0.6768 acc/top5: 0.8693 acc/mean1: 0.6767 2022/10/10 07:55:21 - mmengine - INFO - Epoch(train) [74][20/940] lr: 1.0000e-03 eta: 3:34:19 time: 0.6974 data_time: 0.2954 memory: 21547 grad_norm: 4.6315 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3480 loss: 1.3480 2022/10/10 07:55:31 - mmengine - INFO - Epoch(train) [74][40/940] lr: 1.0000e-03 eta: 3:34:09 time: 0.5315 data_time: 0.0281 memory: 21547 grad_norm: 4.6793 top1_acc: 0.8438 top5_acc: 0.8438 loss_cls: 1.3177 loss: 1.3177 2022/10/10 07:55:41 - mmengine - INFO - Epoch(train) [74][60/940] lr: 1.0000e-03 eta: 3:33:58 time: 0.5021 data_time: 0.0341 memory: 21547 grad_norm: 4.7184 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1647 loss: 1.1647 2022/10/10 07:55:51 - mmengine - INFO - Epoch(train) [74][80/940] lr: 1.0000e-03 eta: 3:33:48 time: 0.4825 data_time: 0.0235 memory: 21547 grad_norm: 4.6402 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1836 loss: 1.1836 2022/10/10 07:56:02 - mmengine - INFO - Epoch(train) [74][100/940] lr: 1.0000e-03 eta: 3:33:38 time: 0.5663 data_time: 0.0283 memory: 21547 grad_norm: 4.7040 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1861 loss: 1.1861 2022/10/10 07:56:12 - mmengine - INFO - Epoch(train) [74][120/940] lr: 1.0000e-03 eta: 3:33:28 time: 0.4617 data_time: 0.0226 memory: 21547 grad_norm: 4.6980 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3145 loss: 1.3145 2022/10/10 07:56:22 - mmengine - INFO - Epoch(train) [74][140/940] lr: 1.0000e-03 eta: 3:33:18 time: 0.5144 data_time: 0.0275 memory: 21547 grad_norm: 4.6801 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0762 loss: 1.0762 2022/10/10 07:56:32 - mmengine - INFO - Epoch(train) [74][160/940] lr: 1.0000e-03 eta: 3:33:07 time: 0.4827 data_time: 0.0273 memory: 21547 grad_norm: 4.5964 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1730 loss: 1.1730 2022/10/10 07:56:43 - mmengine - INFO - Epoch(train) [74][180/940] lr: 1.0000e-03 eta: 3:32:58 time: 0.5535 data_time: 0.0338 memory: 21547 grad_norm: 4.6248 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1710 loss: 1.1710 2022/10/10 07:56:53 - mmengine - INFO - Epoch(train) [74][200/940] lr: 1.0000e-03 eta: 3:32:47 time: 0.4970 data_time: 0.0287 memory: 21547 grad_norm: 4.8279 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2865 loss: 1.2865 2022/10/10 07:57:03 - mmengine - INFO - Epoch(train) [74][220/940] lr: 1.0000e-03 eta: 3:32:37 time: 0.4999 data_time: 0.0316 memory: 21547 grad_norm: 4.6462 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1660 loss: 1.1660 2022/10/10 07:57:12 - mmengine - INFO - Epoch(train) [74][240/940] lr: 1.0000e-03 eta: 3:32:27 time: 0.4830 data_time: 0.0247 memory: 21547 grad_norm: 4.7464 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1537 loss: 1.1537 2022/10/10 07:57:22 - mmengine - INFO - Epoch(train) [74][260/940] lr: 1.0000e-03 eta: 3:32:17 time: 0.4957 data_time: 0.0303 memory: 21547 grad_norm: 4.8327 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2180 loss: 1.2180 2022/10/10 07:57:32 - mmengine - INFO - Epoch(train) [74][280/940] lr: 1.0000e-03 eta: 3:32:07 time: 0.5086 data_time: 0.0266 memory: 21547 grad_norm: 4.8141 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2622 loss: 1.2622 2022/10/10 07:57:42 - mmengine - INFO - Epoch(train) [74][300/940] lr: 1.0000e-03 eta: 3:31:56 time: 0.4939 data_time: 0.0315 memory: 21547 grad_norm: 4.7340 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2515 loss: 1.2515 2022/10/10 07:57:53 - mmengine - INFO - Epoch(train) [74][320/940] lr: 1.0000e-03 eta: 3:31:46 time: 0.5237 data_time: 0.0251 memory: 21547 grad_norm: 4.7775 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2312 loss: 1.2312 2022/10/10 07:58:04 - mmengine - INFO - Epoch(train) [74][340/940] lr: 1.0000e-03 eta: 3:31:37 time: 0.5556 data_time: 0.0290 memory: 21547 grad_norm: 4.6807 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2032 loss: 1.2032 2022/10/10 07:58:13 - mmengine - INFO - Epoch(train) [74][360/940] lr: 1.0000e-03 eta: 3:31:26 time: 0.4789 data_time: 0.0292 memory: 21547 grad_norm: 4.7642 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3299 loss: 1.3299 2022/10/10 07:58:24 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 07:58:24 - mmengine - INFO - Epoch(train) [74][380/940] lr: 1.0000e-03 eta: 3:31:16 time: 0.5476 data_time: 0.0249 memory: 21547 grad_norm: 4.7882 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1406 loss: 1.1406 2022/10/10 07:58:34 - mmengine - INFO - Epoch(train) [74][400/940] lr: 1.0000e-03 eta: 3:31:06 time: 0.4668 data_time: 0.0274 memory: 21547 grad_norm: 4.7395 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3198 loss: 1.3198 2022/10/10 07:58:43 - mmengine - INFO - Epoch(train) [74][420/940] lr: 1.0000e-03 eta: 3:30:56 time: 0.4720 data_time: 0.0270 memory: 21547 grad_norm: 4.7162 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.1959 loss: 1.1959 2022/10/10 07:58:53 - mmengine - INFO - Epoch(train) [74][440/940] lr: 1.0000e-03 eta: 3:30:45 time: 0.4969 data_time: 0.0261 memory: 21547 grad_norm: 4.7896 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3593 loss: 1.3593 2022/10/10 07:59:04 - mmengine - INFO - Epoch(train) [74][460/940] lr: 1.0000e-03 eta: 3:30:35 time: 0.5199 data_time: 0.0284 memory: 21547 grad_norm: 4.7016 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3242 loss: 1.3242 2022/10/10 07:59:14 - mmengine - INFO - Epoch(train) [74][480/940] lr: 1.0000e-03 eta: 3:30:25 time: 0.5023 data_time: 0.0311 memory: 21547 grad_norm: 4.6527 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2293 loss: 1.2293 2022/10/10 07:59:24 - mmengine - INFO - Epoch(train) [74][500/940] lr: 1.0000e-03 eta: 3:30:15 time: 0.5189 data_time: 0.0222 memory: 21547 grad_norm: 4.7545 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1395 loss: 1.1395 2022/10/10 07:59:35 - mmengine - INFO - Epoch(train) [74][520/940] lr: 1.0000e-03 eta: 3:30:05 time: 0.5322 data_time: 0.0271 memory: 21547 grad_norm: 4.7359 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1360 loss: 1.1360 2022/10/10 07:59:45 - mmengine - INFO - Epoch(train) [74][540/940] lr: 1.0000e-03 eta: 3:29:55 time: 0.4950 data_time: 0.0351 memory: 21547 grad_norm: 4.6962 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1283 loss: 1.1283 2022/10/10 07:59:55 - mmengine - INFO - Epoch(train) [74][560/940] lr: 1.0000e-03 eta: 3:29:45 time: 0.5414 data_time: 0.0250 memory: 21547 grad_norm: 4.6757 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1459 loss: 1.1459 2022/10/10 08:00:05 - mmengine - INFO - Epoch(train) [74][580/940] lr: 1.0000e-03 eta: 3:29:35 time: 0.4710 data_time: 0.0264 memory: 21547 grad_norm: 4.6902 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1824 loss: 1.1824 2022/10/10 08:00:16 - mmengine - INFO - Epoch(train) [74][600/940] lr: 1.0000e-03 eta: 3:29:25 time: 0.5536 data_time: 0.0243 memory: 21547 grad_norm: 4.6722 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2740 loss: 1.2740 2022/10/10 08:00:26 - mmengine - INFO - Epoch(train) [74][620/940] lr: 1.0000e-03 eta: 3:29:15 time: 0.5035 data_time: 0.0266 memory: 21547 grad_norm: 4.7102 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2356 loss: 1.2356 2022/10/10 08:00:37 - mmengine - INFO - Epoch(train) [74][640/940] lr: 1.0000e-03 eta: 3:29:05 time: 0.5361 data_time: 0.0264 memory: 21547 grad_norm: 4.7417 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2038 loss: 1.2038 2022/10/10 08:00:46 - mmengine - INFO - Epoch(train) [74][660/940] lr: 1.0000e-03 eta: 3:28:54 time: 0.4473 data_time: 0.0298 memory: 21547 grad_norm: 4.6561 top1_acc: 0.6562 top5_acc: 1.0000 loss_cls: 1.2526 loss: 1.2526 2022/10/10 08:00:55 - mmengine - INFO - Epoch(train) [74][680/940] lr: 1.0000e-03 eta: 3:28:44 time: 0.4750 data_time: 0.0226 memory: 21547 grad_norm: 4.7052 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1277 loss: 1.1277 2022/10/10 08:01:05 - mmengine - INFO - Epoch(train) [74][700/940] lr: 1.0000e-03 eta: 3:28:34 time: 0.5039 data_time: 0.0287 memory: 21547 grad_norm: 4.7488 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2048 loss: 1.2048 2022/10/10 08:01:16 - mmengine - INFO - Epoch(train) [74][720/940] lr: 1.0000e-03 eta: 3:28:24 time: 0.5474 data_time: 0.0280 memory: 21547 grad_norm: 4.8032 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1805 loss: 1.1805 2022/10/10 08:01:25 - mmengine - INFO - Epoch(train) [74][740/940] lr: 1.0000e-03 eta: 3:28:13 time: 0.4607 data_time: 0.0246 memory: 21547 grad_norm: 4.8518 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3449 loss: 1.3449 2022/10/10 08:01:35 - mmengine - INFO - Epoch(train) [74][760/940] lr: 1.0000e-03 eta: 3:28:03 time: 0.4957 data_time: 0.0393 memory: 21547 grad_norm: 4.8646 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3322 loss: 1.3322 2022/10/10 08:01:45 - mmengine - INFO - Epoch(train) [74][780/940] lr: 1.0000e-03 eta: 3:27:53 time: 0.4903 data_time: 0.0274 memory: 21547 grad_norm: 4.7533 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2502 loss: 1.2502 2022/10/10 08:01:55 - mmengine - INFO - Epoch(train) [74][800/940] lr: 1.0000e-03 eta: 3:27:43 time: 0.4966 data_time: 0.0266 memory: 21547 grad_norm: 4.8128 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1735 loss: 1.1735 2022/10/10 08:02:05 - mmengine - INFO - Epoch(train) [74][820/940] lr: 1.0000e-03 eta: 3:27:32 time: 0.5161 data_time: 0.0302 memory: 21547 grad_norm: 4.7665 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2295 loss: 1.2295 2022/10/10 08:02:15 - mmengine - INFO - Epoch(train) [74][840/940] lr: 1.0000e-03 eta: 3:27:22 time: 0.4642 data_time: 0.0313 memory: 21547 grad_norm: 4.7077 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2908 loss: 1.2908 2022/10/10 08:02:25 - mmengine - INFO - Epoch(train) [74][860/940] lr: 1.0000e-03 eta: 3:27:12 time: 0.4990 data_time: 0.0278 memory: 21547 grad_norm: 4.6105 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0844 loss: 1.0844 2022/10/10 08:02:35 - mmengine - INFO - Epoch(train) [74][880/940] lr: 1.0000e-03 eta: 3:27:02 time: 0.5293 data_time: 0.0296 memory: 21547 grad_norm: 4.7058 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.1462 loss: 1.1462 2022/10/10 08:02:45 - mmengine - INFO - Epoch(train) [74][900/940] lr: 1.0000e-03 eta: 3:26:52 time: 0.4839 data_time: 0.0306 memory: 21547 grad_norm: 4.7787 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1732 loss: 1.1732 2022/10/10 08:02:55 - mmengine - INFO - Epoch(train) [74][920/940] lr: 1.0000e-03 eta: 3:26:41 time: 0.5165 data_time: 0.0296 memory: 21547 grad_norm: 4.7728 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1494 loss: 1.1494 2022/10/10 08:03:05 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 08:03:05 - mmengine - INFO - Epoch(train) [74][940/940] lr: 1.0000e-03 eta: 3:26:31 time: 0.4710 data_time: 0.0262 memory: 21547 grad_norm: 4.9567 top1_acc: 0.2857 top5_acc: 0.8571 loss_cls: 1.3764 loss: 1.3764 2022/10/10 08:03:17 - mmengine - INFO - Epoch(val) [74][20/78] eta: 0:00:35 time: 0.6158 data_time: 0.5052 memory: 3269 2022/10/10 08:03:25 - mmengine - INFO - Epoch(val) [74][40/78] eta: 0:00:16 time: 0.4265 data_time: 0.3222 memory: 3269 2022/10/10 08:03:37 - mmengine - INFO - Epoch(val) [74][60/78] eta: 0:00:10 time: 0.5579 data_time: 0.4517 memory: 3269 2022/10/10 08:03:46 - mmengine - INFO - Epoch(val) [74][78/78] acc/top1: 0.6772 acc/top5: 0.8705 acc/mean1: 0.6771 2022/10/10 08:04:01 - mmengine - INFO - Epoch(train) [75][20/940] lr: 1.0000e-03 eta: 3:26:23 time: 0.7458 data_time: 0.2854 memory: 21547 grad_norm: 4.7060 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1787 loss: 1.1787 2022/10/10 08:04:10 - mmengine - INFO - Epoch(train) [75][40/940] lr: 1.0000e-03 eta: 3:26:12 time: 0.4683 data_time: 0.0289 memory: 21547 grad_norm: 4.6394 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2989 loss: 1.2989 2022/10/10 08:04:22 - mmengine - INFO - Epoch(train) [75][60/940] lr: 1.0000e-03 eta: 3:26:03 time: 0.5851 data_time: 0.0326 memory: 21547 grad_norm: 4.7529 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1621 loss: 1.1621 2022/10/10 08:04:32 - mmengine - INFO - Epoch(train) [75][80/940] lr: 1.0000e-03 eta: 3:25:52 time: 0.4915 data_time: 0.0258 memory: 21547 grad_norm: 4.7454 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1781 loss: 1.1781 2022/10/10 08:04:42 - mmengine - INFO - Epoch(train) [75][100/940] lr: 1.0000e-03 eta: 3:25:42 time: 0.4860 data_time: 0.0228 memory: 21547 grad_norm: 4.6444 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0811 loss: 1.0811 2022/10/10 08:04:52 - mmengine - INFO - Epoch(train) [75][120/940] lr: 1.0000e-03 eta: 3:25:32 time: 0.4959 data_time: 0.0242 memory: 21547 grad_norm: 4.7901 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1764 loss: 1.1764 2022/10/10 08:05:02 - mmengine - INFO - Epoch(train) [75][140/940] lr: 1.0000e-03 eta: 3:25:22 time: 0.5064 data_time: 0.0266 memory: 21547 grad_norm: 4.7344 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0492 loss: 1.0492 2022/10/10 08:05:11 - mmengine - INFO - Epoch(train) [75][160/940] lr: 1.0000e-03 eta: 3:25:11 time: 0.4814 data_time: 0.0280 memory: 21547 grad_norm: 4.6999 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2921 loss: 1.2921 2022/10/10 08:05:22 - mmengine - INFO - Epoch(train) [75][180/940] lr: 1.0000e-03 eta: 3:25:01 time: 0.5091 data_time: 0.0280 memory: 21547 grad_norm: 4.7536 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1348 loss: 1.1348 2022/10/10 08:05:32 - mmengine - INFO - Epoch(train) [75][200/940] lr: 1.0000e-03 eta: 3:24:51 time: 0.4992 data_time: 0.0356 memory: 21547 grad_norm: 4.7555 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2227 loss: 1.2227 2022/10/10 08:05:41 - mmengine - INFO - Epoch(train) [75][220/940] lr: 1.0000e-03 eta: 3:24:41 time: 0.4872 data_time: 0.0337 memory: 21547 grad_norm: 4.6491 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2865 loss: 1.2865 2022/10/10 08:05:51 - mmengine - INFO - Epoch(train) [75][240/940] lr: 1.0000e-03 eta: 3:24:30 time: 0.4902 data_time: 0.0277 memory: 21547 grad_norm: 4.8647 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2992 loss: 1.2992 2022/10/10 08:06:02 - mmengine - INFO - Epoch(train) [75][260/940] lr: 1.0000e-03 eta: 3:24:21 time: 0.5608 data_time: 0.0285 memory: 21547 grad_norm: 4.7364 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2918 loss: 1.2918 2022/10/10 08:06:12 - mmengine - INFO - Epoch(train) [75][280/940] lr: 1.0000e-03 eta: 3:24:10 time: 0.4856 data_time: 0.0376 memory: 21547 grad_norm: 4.7281 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1813 loss: 1.1813 2022/10/10 08:06:23 - mmengine - INFO - Epoch(train) [75][300/940] lr: 1.0000e-03 eta: 3:24:01 time: 0.5446 data_time: 0.0256 memory: 21547 grad_norm: 4.7617 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1000 loss: 1.1000 2022/10/10 08:06:32 - mmengine - INFO - Epoch(train) [75][320/940] lr: 1.0000e-03 eta: 3:23:50 time: 0.4584 data_time: 0.0254 memory: 21547 grad_norm: 4.6786 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1812 loss: 1.1812 2022/10/10 08:06:43 - mmengine - INFO - Epoch(train) [75][340/940] lr: 1.0000e-03 eta: 3:23:40 time: 0.5217 data_time: 0.0238 memory: 21547 grad_norm: 4.6825 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0838 loss: 1.0838 2022/10/10 08:06:53 - mmengine - INFO - Epoch(train) [75][360/940] lr: 1.0000e-03 eta: 3:23:30 time: 0.5168 data_time: 0.0276 memory: 21547 grad_norm: 4.6847 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1874 loss: 1.1874 2022/10/10 08:07:04 - mmengine - INFO - Epoch(train) [75][380/940] lr: 1.0000e-03 eta: 3:23:20 time: 0.5516 data_time: 0.0294 memory: 21547 grad_norm: 4.8113 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2361 loss: 1.2361 2022/10/10 08:07:14 - mmengine - INFO - Epoch(train) [75][400/940] lr: 1.0000e-03 eta: 3:23:10 time: 0.4956 data_time: 0.0377 memory: 21547 grad_norm: 4.7380 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2689 loss: 1.2689 2022/10/10 08:07:24 - mmengine - INFO - Epoch(train) [75][420/940] lr: 1.0000e-03 eta: 3:23:00 time: 0.4907 data_time: 0.0234 memory: 21547 grad_norm: 4.7423 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.2967 loss: 1.2967 2022/10/10 08:07:34 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 08:07:34 - mmengine - INFO - Epoch(train) [75][440/940] lr: 1.0000e-03 eta: 3:22:49 time: 0.4940 data_time: 0.0285 memory: 21547 grad_norm: 4.8426 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3090 loss: 1.3090 2022/10/10 08:07:44 - mmengine - INFO - Epoch(train) [75][460/940] lr: 1.0000e-03 eta: 3:22:39 time: 0.5218 data_time: 0.0256 memory: 21547 grad_norm: 4.8109 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2819 loss: 1.2819 2022/10/10 08:07:53 - mmengine - INFO - Epoch(train) [75][480/940] lr: 1.0000e-03 eta: 3:22:29 time: 0.4519 data_time: 0.0313 memory: 21547 grad_norm: 4.6960 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1808 loss: 1.1808 2022/10/10 08:08:03 - mmengine - INFO - Epoch(train) [75][500/940] lr: 1.0000e-03 eta: 3:22:19 time: 0.5119 data_time: 0.0281 memory: 21547 grad_norm: 4.7474 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1546 loss: 1.1546 2022/10/10 08:08:13 - mmengine - INFO - Epoch(train) [75][520/940] lr: 1.0000e-03 eta: 3:22:08 time: 0.4695 data_time: 0.0275 memory: 21547 grad_norm: 4.7458 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2639 loss: 1.2639 2022/10/10 08:08:24 - mmengine - INFO - Epoch(train) [75][540/940] lr: 1.0000e-03 eta: 3:21:59 time: 0.5536 data_time: 0.0281 memory: 21547 grad_norm: 4.8137 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2536 loss: 1.2536 2022/10/10 08:08:34 - mmengine - INFO - Epoch(train) [75][560/940] lr: 1.0000e-03 eta: 3:21:48 time: 0.5174 data_time: 0.0243 memory: 21547 grad_norm: 4.7594 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2970 loss: 1.2970 2022/10/10 08:08:43 - mmengine - INFO - Epoch(train) [75][580/940] lr: 1.0000e-03 eta: 3:21:38 time: 0.4684 data_time: 0.0296 memory: 21547 grad_norm: 4.6485 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2187 loss: 1.2187 2022/10/10 08:08:53 - mmengine - INFO - Epoch(train) [75][600/940] lr: 1.0000e-03 eta: 3:21:28 time: 0.4952 data_time: 0.0267 memory: 21547 grad_norm: 4.7626 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2899 loss: 1.2899 2022/10/10 08:09:04 - mmengine - INFO - Epoch(train) [75][620/940] lr: 1.0000e-03 eta: 3:21:18 time: 0.5340 data_time: 0.0223 memory: 21547 grad_norm: 4.7547 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1780 loss: 1.1780 2022/10/10 08:09:13 - mmengine - INFO - Epoch(train) [75][640/940] lr: 1.0000e-03 eta: 3:21:07 time: 0.4670 data_time: 0.0237 memory: 21547 grad_norm: 4.7121 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1557 loss: 1.1557 2022/10/10 08:09:24 - mmengine - INFO - Epoch(train) [75][660/940] lr: 1.0000e-03 eta: 3:20:58 time: 0.5466 data_time: 0.0275 memory: 21547 grad_norm: 4.7924 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1402 loss: 1.1402 2022/10/10 08:09:34 - mmengine - INFO - Epoch(train) [75][680/940] lr: 1.0000e-03 eta: 3:20:47 time: 0.4913 data_time: 0.0266 memory: 21547 grad_norm: 4.7480 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2484 loss: 1.2484 2022/10/10 08:09:45 - mmengine - INFO - Epoch(train) [75][700/940] lr: 1.0000e-03 eta: 3:20:37 time: 0.5270 data_time: 0.0264 memory: 21547 grad_norm: 4.7002 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0907 loss: 1.0907 2022/10/10 08:09:54 - mmengine - INFO - Epoch(train) [75][720/940] lr: 1.0000e-03 eta: 3:20:27 time: 0.4520 data_time: 0.0302 memory: 21547 grad_norm: 4.7552 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1980 loss: 1.1980 2022/10/10 08:10:05 - mmengine - INFO - Epoch(train) [75][740/940] lr: 1.0000e-03 eta: 3:20:17 time: 0.5719 data_time: 0.0305 memory: 21547 grad_norm: 4.7421 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1879 loss: 1.1879 2022/10/10 08:10:14 - mmengine - INFO - Epoch(train) [75][760/940] lr: 1.0000e-03 eta: 3:20:07 time: 0.4555 data_time: 0.0307 memory: 21547 grad_norm: 4.8106 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2434 loss: 1.2434 2022/10/10 08:10:24 - mmengine - INFO - Epoch(train) [75][780/940] lr: 1.0000e-03 eta: 3:19:56 time: 0.5082 data_time: 0.0296 memory: 21547 grad_norm: 4.6660 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0826 loss: 1.0826 2022/10/10 08:10:33 - mmengine - INFO - Epoch(train) [75][800/940] lr: 1.0000e-03 eta: 3:19:46 time: 0.4494 data_time: 0.0466 memory: 21547 grad_norm: 4.7186 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2274 loss: 1.2274 2022/10/10 08:10:43 - mmengine - INFO - Epoch(train) [75][820/940] lr: 1.0000e-03 eta: 3:19:36 time: 0.4846 data_time: 0.0426 memory: 21547 grad_norm: 4.8229 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0937 loss: 1.0937 2022/10/10 08:10:54 - mmengine - INFO - Epoch(train) [75][840/940] lr: 1.0000e-03 eta: 3:19:26 time: 0.5397 data_time: 0.0964 memory: 21547 grad_norm: 4.6804 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1473 loss: 1.1473 2022/10/10 08:11:04 - mmengine - INFO - Epoch(train) [75][860/940] lr: 1.0000e-03 eta: 3:19:16 time: 0.5007 data_time: 0.0333 memory: 21547 grad_norm: 4.7772 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1474 loss: 1.1474 2022/10/10 08:11:14 - mmengine - INFO - Epoch(train) [75][880/940] lr: 1.0000e-03 eta: 3:19:05 time: 0.5112 data_time: 0.0328 memory: 21547 grad_norm: 4.8892 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2885 loss: 1.2885 2022/10/10 08:11:24 - mmengine - INFO - Epoch(train) [75][900/940] lr: 1.0000e-03 eta: 3:18:55 time: 0.5026 data_time: 0.0325 memory: 21547 grad_norm: 4.7879 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2961 loss: 1.2961 2022/10/10 08:11:34 - mmengine - INFO - Epoch(train) [75][920/940] lr: 1.0000e-03 eta: 3:18:45 time: 0.4950 data_time: 0.0287 memory: 21547 grad_norm: 4.7736 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1766 loss: 1.1766 2022/10/10 08:11:43 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 08:11:43 - mmengine - INFO - Epoch(train) [75][940/940] lr: 1.0000e-03 eta: 3:18:35 time: 0.4609 data_time: 0.0250 memory: 21547 grad_norm: 4.9623 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.0773 loss: 1.0773 2022/10/10 08:11:43 - mmengine - INFO - Saving checkpoint at 75 epochs 2022/10/10 08:11:57 - mmengine - INFO - Epoch(val) [75][20/78] eta: 0:00:35 time: 0.6084 data_time: 0.5022 memory: 3269 2022/10/10 08:12:05 - mmengine - INFO - Epoch(val) [75][40/78] eta: 0:00:16 time: 0.4251 data_time: 0.3201 memory: 3269 2022/10/10 08:12:16 - mmengine - INFO - Epoch(val) [75][60/78] eta: 0:00:10 time: 0.5580 data_time: 0.4528 memory: 3269 2022/10/10 08:12:25 - mmengine - INFO - Epoch(val) [75][78/78] acc/top1: 0.6779 acc/top5: 0.8702 acc/mean1: 0.6778 2022/10/10 08:12:39 - mmengine - INFO - Epoch(train) [76][20/940] lr: 1.0000e-03 eta: 3:18:26 time: 0.6846 data_time: 0.2736 memory: 21547 grad_norm: 4.8263 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1998 loss: 1.1998 2022/10/10 08:12:50 - mmengine - INFO - Epoch(train) [76][40/940] lr: 1.0000e-03 eta: 3:18:16 time: 0.5381 data_time: 0.0715 memory: 21547 grad_norm: 4.7493 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1663 loss: 1.1663 2022/10/10 08:13:00 - mmengine - INFO - Epoch(train) [76][60/940] lr: 1.0000e-03 eta: 3:18:06 time: 0.5266 data_time: 0.0307 memory: 21547 grad_norm: 4.6495 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2279 loss: 1.2279 2022/10/10 08:13:10 - mmengine - INFO - Epoch(train) [76][80/940] lr: 1.0000e-03 eta: 3:17:55 time: 0.4674 data_time: 0.0510 memory: 21547 grad_norm: 4.7595 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2421 loss: 1.2421 2022/10/10 08:13:21 - mmengine - INFO - Epoch(train) [76][100/940] lr: 1.0000e-03 eta: 3:17:45 time: 0.5483 data_time: 0.1600 memory: 21547 grad_norm: 4.8518 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1914 loss: 1.1914 2022/10/10 08:13:31 - mmengine - INFO - Epoch(train) [76][120/940] lr: 1.0000e-03 eta: 3:17:35 time: 0.4910 data_time: 0.1022 memory: 21547 grad_norm: 4.8016 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2137 loss: 1.2137 2022/10/10 08:13:41 - mmengine - INFO - Epoch(train) [76][140/940] lr: 1.0000e-03 eta: 3:17:25 time: 0.5376 data_time: 0.1511 memory: 21547 grad_norm: 4.8432 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2390 loss: 1.2390 2022/10/10 08:13:51 - mmengine - INFO - Epoch(train) [76][160/940] lr: 1.0000e-03 eta: 3:17:15 time: 0.4741 data_time: 0.0891 memory: 21547 grad_norm: 4.7608 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1874 loss: 1.1874 2022/10/10 08:14:01 - mmengine - INFO - Epoch(train) [76][180/940] lr: 1.0000e-03 eta: 3:17:05 time: 0.5199 data_time: 0.1247 memory: 21547 grad_norm: 4.6303 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2621 loss: 1.2621 2022/10/10 08:14:10 - mmengine - INFO - Epoch(train) [76][200/940] lr: 1.0000e-03 eta: 3:16:54 time: 0.4493 data_time: 0.0687 memory: 21547 grad_norm: 4.6894 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2012 loss: 1.2012 2022/10/10 08:14:21 - mmengine - INFO - Epoch(train) [76][220/940] lr: 1.0000e-03 eta: 3:16:44 time: 0.5310 data_time: 0.1455 memory: 21547 grad_norm: 4.7357 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2277 loss: 1.2277 2022/10/10 08:14:30 - mmengine - INFO - Epoch(train) [76][240/940] lr: 1.0000e-03 eta: 3:16:34 time: 0.4739 data_time: 0.0904 memory: 21547 grad_norm: 4.7681 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2509 loss: 1.2509 2022/10/10 08:14:40 - mmengine - INFO - Epoch(train) [76][260/940] lr: 1.0000e-03 eta: 3:16:24 time: 0.5096 data_time: 0.1173 memory: 21547 grad_norm: 4.8946 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1807 loss: 1.1807 2022/10/10 08:14:50 - mmengine - INFO - Epoch(train) [76][280/940] lr: 1.0000e-03 eta: 3:16:14 time: 0.5002 data_time: 0.0900 memory: 21547 grad_norm: 4.8346 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2068 loss: 1.2068 2022/10/10 08:15:01 - mmengine - INFO - Epoch(train) [76][300/940] lr: 1.0000e-03 eta: 3:16:03 time: 0.5007 data_time: 0.1090 memory: 21547 grad_norm: 4.7335 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2484 loss: 1.2484 2022/10/10 08:15:10 - mmengine - INFO - Epoch(train) [76][320/940] lr: 1.0000e-03 eta: 3:15:53 time: 0.4922 data_time: 0.0767 memory: 21547 grad_norm: 4.7468 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2626 loss: 1.2626 2022/10/10 08:15:21 - mmengine - INFO - Epoch(train) [76][340/940] lr: 1.0000e-03 eta: 3:15:43 time: 0.5260 data_time: 0.0758 memory: 21547 grad_norm: 4.5977 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2706 loss: 1.2706 2022/10/10 08:15:31 - mmengine - INFO - Epoch(train) [76][360/940] lr: 1.0000e-03 eta: 3:15:33 time: 0.5005 data_time: 0.0880 memory: 21547 grad_norm: 4.7825 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1445 loss: 1.1445 2022/10/10 08:15:41 - mmengine - INFO - Epoch(train) [76][380/940] lr: 1.0000e-03 eta: 3:15:23 time: 0.5105 data_time: 0.0514 memory: 21547 grad_norm: 4.8469 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1973 loss: 1.1973 2022/10/10 08:15:51 - mmengine - INFO - Epoch(train) [76][400/940] lr: 1.0000e-03 eta: 3:15:13 time: 0.4940 data_time: 0.0261 memory: 21547 grad_norm: 4.8022 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2426 loss: 1.2426 2022/10/10 08:16:02 - mmengine - INFO - Epoch(train) [76][420/940] lr: 1.0000e-03 eta: 3:15:03 time: 0.5349 data_time: 0.0291 memory: 21547 grad_norm: 4.7782 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0528 loss: 1.0528 2022/10/10 08:16:12 - mmengine - INFO - Epoch(train) [76][440/940] lr: 1.0000e-03 eta: 3:14:53 time: 0.5087 data_time: 0.0320 memory: 21547 grad_norm: 4.8052 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.1752 loss: 1.1752 2022/10/10 08:16:22 - mmengine - INFO - Epoch(train) [76][460/940] lr: 1.0000e-03 eta: 3:14:43 time: 0.5212 data_time: 0.0297 memory: 21547 grad_norm: 4.8324 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2263 loss: 1.2263 2022/10/10 08:16:31 - mmengine - INFO - Epoch(train) [76][480/940] lr: 1.0000e-03 eta: 3:14:32 time: 0.4503 data_time: 0.0393 memory: 21547 grad_norm: 4.8622 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.1622 loss: 1.1622 2022/10/10 08:16:41 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 08:16:41 - mmengine - INFO - Epoch(train) [76][500/940] lr: 1.0000e-03 eta: 3:14:22 time: 0.4856 data_time: 0.0260 memory: 21547 grad_norm: 4.5698 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1294 loss: 1.1294 2022/10/10 08:16:51 - mmengine - INFO - Epoch(train) [76][520/940] lr: 1.0000e-03 eta: 3:14:11 time: 0.4835 data_time: 0.0264 memory: 21547 grad_norm: 4.6131 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.0613 loss: 1.0613 2022/10/10 08:17:01 - mmengine - INFO - Epoch(train) [76][540/940] lr: 1.0000e-03 eta: 3:14:01 time: 0.5372 data_time: 0.0240 memory: 21547 grad_norm: 4.8546 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3291 loss: 1.3291 2022/10/10 08:17:12 - mmengine - INFO - Epoch(train) [76][560/940] lr: 1.0000e-03 eta: 3:13:51 time: 0.5208 data_time: 0.0326 memory: 21547 grad_norm: 4.8456 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2539 loss: 1.2539 2022/10/10 08:17:22 - mmengine - INFO - Epoch(train) [76][580/940] lr: 1.0000e-03 eta: 3:13:41 time: 0.4941 data_time: 0.0242 memory: 21547 grad_norm: 4.7777 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.3513 loss: 1.3513 2022/10/10 08:17:32 - mmengine - INFO - Epoch(train) [76][600/940] lr: 1.0000e-03 eta: 3:13:31 time: 0.4984 data_time: 0.0312 memory: 21547 grad_norm: 4.6767 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2567 loss: 1.2567 2022/10/10 08:17:42 - mmengine - INFO - Epoch(train) [76][620/940] lr: 1.0000e-03 eta: 3:13:21 time: 0.4970 data_time: 0.0244 memory: 21547 grad_norm: 4.8249 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2529 loss: 1.2529 2022/10/10 08:17:52 - mmengine - INFO - Epoch(train) [76][640/940] lr: 1.0000e-03 eta: 3:13:11 time: 0.4945 data_time: 0.0244 memory: 21547 grad_norm: 4.6953 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.0979 loss: 1.0979 2022/10/10 08:18:01 - mmengine - INFO - Epoch(train) [76][660/940] lr: 1.0000e-03 eta: 3:13:00 time: 0.4961 data_time: 0.0257 memory: 21547 grad_norm: 4.8393 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.2493 loss: 1.2493 2022/10/10 08:18:12 - mmengine - INFO - Epoch(train) [76][680/940] lr: 1.0000e-03 eta: 3:12:50 time: 0.5401 data_time: 0.0290 memory: 21547 grad_norm: 4.6123 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1774 loss: 1.1774 2022/10/10 08:18:22 - mmengine - INFO - Epoch(train) [76][700/940] lr: 1.0000e-03 eta: 3:12:40 time: 0.4973 data_time: 0.0294 memory: 21547 grad_norm: 4.6587 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1242 loss: 1.1242 2022/10/10 08:18:33 - mmengine - INFO - Epoch(train) [76][720/940] lr: 1.0000e-03 eta: 3:12:30 time: 0.5477 data_time: 0.0290 memory: 21547 grad_norm: 4.7684 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.1855 loss: 1.1855 2022/10/10 08:18:43 - mmengine - INFO - Epoch(train) [76][740/940] lr: 1.0000e-03 eta: 3:12:20 time: 0.5008 data_time: 0.0248 memory: 21547 grad_norm: 4.6793 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2786 loss: 1.2786 2022/10/10 08:18:54 - mmengine - INFO - Epoch(train) [76][760/940] lr: 1.0000e-03 eta: 3:12:10 time: 0.5436 data_time: 0.0295 memory: 21547 grad_norm: 4.8218 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1833 loss: 1.1833 2022/10/10 08:19:03 - mmengine - INFO - Epoch(train) [76][780/940] lr: 1.0000e-03 eta: 3:12:00 time: 0.4606 data_time: 0.0253 memory: 21547 grad_norm: 4.6976 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1556 loss: 1.1556 2022/10/10 08:19:13 - mmengine - INFO - Epoch(train) [76][800/940] lr: 1.0000e-03 eta: 3:11:50 time: 0.4927 data_time: 0.0314 memory: 21547 grad_norm: 4.8132 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1663 loss: 1.1663 2022/10/10 08:19:23 - mmengine - INFO - Epoch(train) [76][820/940] lr: 1.0000e-03 eta: 3:11:39 time: 0.4949 data_time: 0.0286 memory: 21547 grad_norm: 4.8285 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1402 loss: 1.1402 2022/10/10 08:19:33 - mmengine - INFO - Epoch(train) [76][840/940] lr: 1.0000e-03 eta: 3:11:29 time: 0.5080 data_time: 0.0269 memory: 21547 grad_norm: 4.7788 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3202 loss: 1.3202 2022/10/10 08:19:42 - mmengine - INFO - Epoch(train) [76][860/940] lr: 1.0000e-03 eta: 3:11:19 time: 0.4503 data_time: 0.0304 memory: 21547 grad_norm: 4.6900 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2154 loss: 1.2154 2022/10/10 08:19:53 - mmengine - INFO - Epoch(train) [76][880/940] lr: 1.0000e-03 eta: 3:11:09 time: 0.5225 data_time: 0.0282 memory: 21547 grad_norm: 4.7517 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3515 loss: 1.3515 2022/10/10 08:20:03 - mmengine - INFO - Epoch(train) [76][900/940] lr: 1.0000e-03 eta: 3:10:59 time: 0.5172 data_time: 0.0307 memory: 21547 grad_norm: 4.8036 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2894 loss: 1.2894 2022/10/10 08:20:13 - mmengine - INFO - Epoch(train) [76][920/940] lr: 1.0000e-03 eta: 3:10:49 time: 0.5225 data_time: 0.0264 memory: 21547 grad_norm: 4.7784 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1555 loss: 1.1555 2022/10/10 08:20:23 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 08:20:23 - mmengine - INFO - Epoch(train) [76][940/940] lr: 1.0000e-03 eta: 3:10:38 time: 0.4907 data_time: 0.0244 memory: 21547 grad_norm: 5.0409 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0868 loss: 1.0868 2022/10/10 08:20:35 - mmengine - INFO - Epoch(val) [76][20/78] eta: 0:00:35 time: 0.6060 data_time: 0.4964 memory: 3269 2022/10/10 08:20:44 - mmengine - INFO - Epoch(val) [76][40/78] eta: 0:00:16 time: 0.4224 data_time: 0.3155 memory: 3269 2022/10/10 08:20:55 - mmengine - INFO - Epoch(val) [76][60/78] eta: 0:00:09 time: 0.5530 data_time: 0.4465 memory: 3269 2022/10/10 08:21:05 - mmengine - INFO - Epoch(val) [76][78/78] acc/top1: 0.6773 acc/top5: 0.8693 acc/mean1: 0.6771 2022/10/10 08:21:19 - mmengine - INFO - Epoch(train) [77][20/940] lr: 1.0000e-03 eta: 3:10:29 time: 0.6933 data_time: 0.2151 memory: 21547 grad_norm: 4.7698 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2301 loss: 1.2301 2022/10/10 08:21:29 - mmengine - INFO - Epoch(train) [77][40/940] lr: 1.0000e-03 eta: 3:10:19 time: 0.4871 data_time: 0.0244 memory: 21547 grad_norm: 4.7192 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1341 loss: 1.1341 2022/10/10 08:21:39 - mmengine - INFO - Epoch(train) [77][60/940] lr: 1.0000e-03 eta: 3:10:09 time: 0.5217 data_time: 0.0341 memory: 21547 grad_norm: 4.7627 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0359 loss: 1.0359 2022/10/10 08:21:48 - mmengine - INFO - Epoch(train) [77][80/940] lr: 1.0000e-03 eta: 3:09:59 time: 0.4710 data_time: 0.0479 memory: 21547 grad_norm: 4.7206 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2472 loss: 1.2472 2022/10/10 08:21:59 - mmengine - INFO - Epoch(train) [77][100/940] lr: 1.0000e-03 eta: 3:09:49 time: 0.5335 data_time: 0.1176 memory: 21547 grad_norm: 4.6416 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.1200 loss: 1.1200 2022/10/10 08:22:09 - mmengine - INFO - Epoch(train) [77][120/940] lr: 1.0000e-03 eta: 3:09:39 time: 0.4956 data_time: 0.0768 memory: 21547 grad_norm: 4.8626 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1720 loss: 1.1720 2022/10/10 08:22:19 - mmengine - INFO - Epoch(train) [77][140/940] lr: 1.0000e-03 eta: 3:09:28 time: 0.4964 data_time: 0.1153 memory: 21547 grad_norm: 4.6877 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0749 loss: 1.0749 2022/10/10 08:22:30 - mmengine - INFO - Epoch(train) [77][160/940] lr: 1.0000e-03 eta: 3:09:18 time: 0.5288 data_time: 0.0549 memory: 21547 grad_norm: 4.6281 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1985 loss: 1.1985 2022/10/10 08:22:39 - mmengine - INFO - Epoch(train) [77][180/940] lr: 1.0000e-03 eta: 3:09:08 time: 0.4970 data_time: 0.0393 memory: 21547 grad_norm: 4.8473 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1271 loss: 1.1271 2022/10/10 08:22:50 - mmengine - INFO - Epoch(train) [77][200/940] lr: 1.0000e-03 eta: 3:08:58 time: 0.5078 data_time: 0.0247 memory: 21547 grad_norm: 4.7612 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2130 loss: 1.2130 2022/10/10 08:23:00 - mmengine - INFO - Epoch(train) [77][220/940] lr: 1.0000e-03 eta: 3:08:48 time: 0.5206 data_time: 0.0350 memory: 21547 grad_norm: 4.7140 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.2286 loss: 1.2286 2022/10/10 08:23:11 - mmengine - INFO - Epoch(train) [77][240/940] lr: 1.0000e-03 eta: 3:08:38 time: 0.5594 data_time: 0.0264 memory: 21547 grad_norm: 4.6837 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2138 loss: 1.2138 2022/10/10 08:23:21 - mmengine - INFO - Epoch(train) [77][260/940] lr: 1.0000e-03 eta: 3:08:28 time: 0.4917 data_time: 0.0273 memory: 21547 grad_norm: 4.7681 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1676 loss: 1.1676 2022/10/10 08:23:31 - mmengine - INFO - Epoch(train) [77][280/940] lr: 1.0000e-03 eta: 3:08:18 time: 0.5193 data_time: 0.0270 memory: 21547 grad_norm: 4.7638 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0717 loss: 1.0717 2022/10/10 08:23:41 - mmengine - INFO - Epoch(train) [77][300/940] lr: 1.0000e-03 eta: 3:08:07 time: 0.4646 data_time: 0.0295 memory: 21547 grad_norm: 4.7389 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1807 loss: 1.1807 2022/10/10 08:23:50 - mmengine - INFO - Epoch(train) [77][320/940] lr: 1.0000e-03 eta: 3:07:57 time: 0.4759 data_time: 0.0319 memory: 21547 grad_norm: 4.7554 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1953 loss: 1.1953 2022/10/10 08:24:01 - mmengine - INFO - Epoch(train) [77][340/940] lr: 1.0000e-03 eta: 3:07:47 time: 0.5116 data_time: 0.0305 memory: 21547 grad_norm: 4.6553 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.0742 loss: 1.0742 2022/10/10 08:24:10 - mmengine - INFO - Epoch(train) [77][360/940] lr: 1.0000e-03 eta: 3:07:37 time: 0.4918 data_time: 0.0258 memory: 21547 grad_norm: 4.7862 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1218 loss: 1.1218 2022/10/10 08:24:21 - mmengine - INFO - Epoch(train) [77][380/940] lr: 1.0000e-03 eta: 3:07:27 time: 0.5111 data_time: 0.0330 memory: 21547 grad_norm: 4.8070 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2985 loss: 1.2985 2022/10/10 08:24:31 - mmengine - INFO - Epoch(train) [77][400/940] lr: 1.0000e-03 eta: 3:07:16 time: 0.5087 data_time: 0.0270 memory: 21547 grad_norm: 4.8010 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.2713 loss: 1.2713 2022/10/10 08:24:41 - mmengine - INFO - Epoch(train) [77][420/940] lr: 1.0000e-03 eta: 3:07:06 time: 0.5164 data_time: 0.0279 memory: 21547 grad_norm: 4.6983 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2209 loss: 1.2209 2022/10/10 08:24:51 - mmengine - INFO - Epoch(train) [77][440/940] lr: 1.0000e-03 eta: 3:06:56 time: 0.4757 data_time: 0.0264 memory: 21547 grad_norm: 4.8091 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1892 loss: 1.1892 2022/10/10 08:25:01 - mmengine - INFO - Epoch(train) [77][460/940] lr: 1.0000e-03 eta: 3:06:46 time: 0.5311 data_time: 0.0270 memory: 21547 grad_norm: 4.7448 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2272 loss: 1.2272 2022/10/10 08:25:11 - mmengine - INFO - Epoch(train) [77][480/940] lr: 1.0000e-03 eta: 3:06:36 time: 0.4714 data_time: 0.0283 memory: 21547 grad_norm: 4.8797 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1485 loss: 1.1485 2022/10/10 08:25:20 - mmengine - INFO - Epoch(train) [77][500/940] lr: 1.0000e-03 eta: 3:06:25 time: 0.4645 data_time: 0.0298 memory: 21547 grad_norm: 4.7545 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1271 loss: 1.1271 2022/10/10 08:25:30 - mmengine - INFO - Epoch(train) [77][520/940] lr: 1.0000e-03 eta: 3:06:15 time: 0.5266 data_time: 0.0263 memory: 21547 grad_norm: 4.8097 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2222 loss: 1.2222 2022/10/10 08:25:41 - mmengine - INFO - Epoch(train) [77][540/940] lr: 1.0000e-03 eta: 3:06:05 time: 0.5224 data_time: 0.0283 memory: 21547 grad_norm: 4.8150 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2249 loss: 1.2249 2022/10/10 08:25:51 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 08:25:51 - mmengine - INFO - Epoch(train) [77][560/940] lr: 1.0000e-03 eta: 3:05:55 time: 0.5165 data_time: 0.0269 memory: 21547 grad_norm: 4.8078 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0817 loss: 1.0817 2022/10/10 08:26:01 - mmengine - INFO - Epoch(train) [77][580/940] lr: 1.0000e-03 eta: 3:05:45 time: 0.4647 data_time: 0.0293 memory: 21547 grad_norm: 4.7185 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0531 loss: 1.0531 2022/10/10 08:26:11 - mmengine - INFO - Epoch(train) [77][600/940] lr: 1.0000e-03 eta: 3:05:35 time: 0.5139 data_time: 0.0294 memory: 21547 grad_norm: 4.7442 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.2938 loss: 1.2938 2022/10/10 08:26:21 - mmengine - INFO - Epoch(train) [77][620/940] lr: 1.0000e-03 eta: 3:05:25 time: 0.5274 data_time: 0.0301 memory: 21547 grad_norm: 4.8427 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.2230 loss: 1.2230 2022/10/10 08:26:31 - mmengine - INFO - Epoch(train) [77][640/940] lr: 1.0000e-03 eta: 3:05:14 time: 0.4936 data_time: 0.0284 memory: 21547 grad_norm: 4.7144 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2262 loss: 1.2262 2022/10/10 08:26:42 - mmengine - INFO - Epoch(train) [77][660/940] lr: 1.0000e-03 eta: 3:05:04 time: 0.5319 data_time: 0.0304 memory: 21547 grad_norm: 4.8938 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2294 loss: 1.2294 2022/10/10 08:26:51 - mmengine - INFO - Epoch(train) [77][680/940] lr: 1.0000e-03 eta: 3:04:54 time: 0.4735 data_time: 0.0313 memory: 21547 grad_norm: 4.9171 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1830 loss: 1.1830 2022/10/10 08:27:01 - mmengine - INFO - Epoch(train) [77][700/940] lr: 1.0000e-03 eta: 3:04:44 time: 0.4931 data_time: 0.0254 memory: 21547 grad_norm: 4.9196 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3731 loss: 1.3731 2022/10/10 08:27:11 - mmengine - INFO - Epoch(train) [77][720/940] lr: 1.0000e-03 eta: 3:04:34 time: 0.4932 data_time: 0.0305 memory: 21547 grad_norm: 4.7393 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.2199 loss: 1.2199 2022/10/10 08:27:21 - mmengine - INFO - Epoch(train) [77][740/940] lr: 1.0000e-03 eta: 3:04:23 time: 0.4910 data_time: 0.0253 memory: 21547 grad_norm: 4.7921 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2252 loss: 1.2252 2022/10/10 08:27:32 - mmengine - INFO - Epoch(train) [77][760/940] lr: 1.0000e-03 eta: 3:04:13 time: 0.5558 data_time: 0.0302 memory: 21547 grad_norm: 4.7744 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1376 loss: 1.1376 2022/10/10 08:27:42 - mmengine - INFO - Epoch(train) [77][780/940] lr: 1.0000e-03 eta: 3:04:03 time: 0.4911 data_time: 0.0310 memory: 21547 grad_norm: 4.8177 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3900 loss: 1.3900 2022/10/10 08:27:52 - mmengine - INFO - Epoch(train) [77][800/940] lr: 1.0000e-03 eta: 3:03:53 time: 0.5243 data_time: 0.0232 memory: 21547 grad_norm: 4.8123 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2151 loss: 1.2151 2022/10/10 08:28:02 - mmengine - INFO - Epoch(train) [77][820/940] lr: 1.0000e-03 eta: 3:03:43 time: 0.5062 data_time: 0.0256 memory: 21547 grad_norm: 4.7487 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1658 loss: 1.1658 2022/10/10 08:28:13 - mmengine - INFO - Epoch(train) [77][840/940] lr: 1.0000e-03 eta: 3:03:33 time: 0.5367 data_time: 0.0259 memory: 21547 grad_norm: 4.7536 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1304 loss: 1.1304 2022/10/10 08:28:23 - mmengine - INFO - Epoch(train) [77][860/940] lr: 1.0000e-03 eta: 3:03:23 time: 0.4839 data_time: 0.0316 memory: 21547 grad_norm: 4.7343 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2801 loss: 1.2801 2022/10/10 08:28:33 - mmengine - INFO - Epoch(train) [77][880/940] lr: 1.0000e-03 eta: 3:03:13 time: 0.5044 data_time: 0.0299 memory: 21547 grad_norm: 4.9223 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1648 loss: 1.1648 2022/10/10 08:28:42 - mmengine - INFO - Epoch(train) [77][900/940] lr: 1.0000e-03 eta: 3:03:02 time: 0.4648 data_time: 0.0301 memory: 21547 grad_norm: 4.7983 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1327 loss: 1.1327 2022/10/10 08:28:53 - mmengine - INFO - Epoch(train) [77][920/940] lr: 1.0000e-03 eta: 3:02:52 time: 0.5408 data_time: 0.0329 memory: 21547 grad_norm: 4.7347 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1871 loss: 1.1871 2022/10/10 08:29:02 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 08:29:02 - mmengine - INFO - Epoch(train) [77][940/940] lr: 1.0000e-03 eta: 3:02:42 time: 0.4432 data_time: 0.0254 memory: 21547 grad_norm: 5.2073 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.2212 loss: 1.2212 2022/10/10 08:29:14 - mmengine - INFO - Epoch(val) [77][20/78] eta: 0:00:35 time: 0.6093 data_time: 0.4988 memory: 3269 2022/10/10 08:29:23 - mmengine - INFO - Epoch(val) [77][40/78] eta: 0:00:15 time: 0.4206 data_time: 0.3129 memory: 3269 2022/10/10 08:29:34 - mmengine - INFO - Epoch(val) [77][60/78] eta: 0:00:09 time: 0.5530 data_time: 0.4457 memory: 3269 2022/10/10 08:29:44 - mmengine - INFO - Epoch(val) [77][78/78] acc/top1: 0.6775 acc/top5: 0.8716 acc/mean1: 0.6774 2022/10/10 08:29:58 - mmengine - INFO - Epoch(train) [78][20/940] lr: 1.0000e-03 eta: 3:02:33 time: 0.7244 data_time: 0.2326 memory: 21547 grad_norm: 4.7030 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2133 loss: 1.2133 2022/10/10 08:30:08 - mmengine - INFO - Epoch(train) [78][40/940] lr: 1.0000e-03 eta: 3:02:23 time: 0.4754 data_time: 0.0233 memory: 21547 grad_norm: 4.6693 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0557 loss: 1.0557 2022/10/10 08:30:19 - mmengine - INFO - Epoch(train) [78][60/940] lr: 1.0000e-03 eta: 3:02:13 time: 0.5485 data_time: 0.0258 memory: 21547 grad_norm: 4.8070 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1792 loss: 1.1792 2022/10/10 08:30:28 - mmengine - INFO - Epoch(train) [78][80/940] lr: 1.0000e-03 eta: 3:02:02 time: 0.4792 data_time: 0.0255 memory: 21547 grad_norm: 4.7422 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1536 loss: 1.1536 2022/10/10 08:30:39 - mmengine - INFO - Epoch(train) [78][100/940] lr: 1.0000e-03 eta: 3:01:53 time: 0.5558 data_time: 0.0266 memory: 21547 grad_norm: 4.8420 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2033 loss: 1.2033 2022/10/10 08:30:49 - mmengine - INFO - Epoch(train) [78][120/940] lr: 1.0000e-03 eta: 3:01:42 time: 0.4882 data_time: 0.0327 memory: 21547 grad_norm: 4.7640 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0680 loss: 1.0680 2022/10/10 08:30:59 - mmengine - INFO - Epoch(train) [78][140/940] lr: 1.0000e-03 eta: 3:01:32 time: 0.4909 data_time: 0.0260 memory: 21547 grad_norm: 4.9002 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2365 loss: 1.2365 2022/10/10 08:31:09 - mmengine - INFO - Epoch(train) [78][160/940] lr: 1.0000e-03 eta: 3:01:22 time: 0.4913 data_time: 0.0296 memory: 21547 grad_norm: 4.8334 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2243 loss: 1.2243 2022/10/10 08:31:20 - mmengine - INFO - Epoch(train) [78][180/940] lr: 1.0000e-03 eta: 3:01:12 time: 0.5360 data_time: 0.0335 memory: 21547 grad_norm: 4.7435 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1772 loss: 1.1772 2022/10/10 08:31:30 - mmengine - INFO - Epoch(train) [78][200/940] lr: 1.0000e-03 eta: 3:01:02 time: 0.5024 data_time: 0.0241 memory: 21547 grad_norm: 4.7031 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1366 loss: 1.1366 2022/10/10 08:31:41 - mmengine - INFO - Epoch(train) [78][220/940] lr: 1.0000e-03 eta: 3:00:52 time: 0.5563 data_time: 0.0366 memory: 21547 grad_norm: 4.9201 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1638 loss: 1.1638 2022/10/10 08:31:50 - mmengine - INFO - Epoch(train) [78][240/940] lr: 1.0000e-03 eta: 3:00:41 time: 0.4625 data_time: 0.0266 memory: 21547 grad_norm: 4.8366 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1560 loss: 1.1560 2022/10/10 08:32:00 - mmengine - INFO - Epoch(train) [78][260/940] lr: 1.0000e-03 eta: 3:00:31 time: 0.4952 data_time: 0.0308 memory: 21547 grad_norm: 4.8091 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1025 loss: 1.1025 2022/10/10 08:32:10 - mmengine - INFO - Epoch(train) [78][280/940] lr: 1.0000e-03 eta: 3:00:21 time: 0.5158 data_time: 0.0307 memory: 21547 grad_norm: 4.7510 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2135 loss: 1.2135 2022/10/10 08:32:21 - mmengine - INFO - Epoch(train) [78][300/940] lr: 1.0000e-03 eta: 3:00:11 time: 0.5267 data_time: 0.0275 memory: 21547 grad_norm: 4.7849 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2580 loss: 1.2580 2022/10/10 08:32:30 - mmengine - INFO - Epoch(train) [78][320/940] lr: 1.0000e-03 eta: 3:00:01 time: 0.4631 data_time: 0.0256 memory: 21547 grad_norm: 4.7975 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2557 loss: 1.2557 2022/10/10 08:32:41 - mmengine - INFO - Epoch(train) [78][340/940] lr: 1.0000e-03 eta: 2:59:51 time: 0.5683 data_time: 0.0238 memory: 21547 grad_norm: 4.8778 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1676 loss: 1.1676 2022/10/10 08:32:51 - mmengine - INFO - Epoch(train) [78][360/940] lr: 1.0000e-03 eta: 2:59:41 time: 0.4910 data_time: 0.0219 memory: 21547 grad_norm: 4.7127 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0219 loss: 1.0219 2022/10/10 08:33:02 - mmengine - INFO - Epoch(train) [78][380/940] lr: 1.0000e-03 eta: 2:59:31 time: 0.5366 data_time: 0.0270 memory: 21547 grad_norm: 4.7729 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0896 loss: 1.0896 2022/10/10 08:33:12 - mmengine - INFO - Epoch(train) [78][400/940] lr: 1.0000e-03 eta: 2:59:21 time: 0.5084 data_time: 0.0205 memory: 21547 grad_norm: 4.7584 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1955 loss: 1.1955 2022/10/10 08:33:22 - mmengine - INFO - Epoch(train) [78][420/940] lr: 1.0000e-03 eta: 2:59:10 time: 0.4934 data_time: 0.0237 memory: 21547 grad_norm: 4.7876 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1250 loss: 1.1250 2022/10/10 08:33:32 - mmengine - INFO - Epoch(train) [78][440/940] lr: 1.0000e-03 eta: 2:59:00 time: 0.5124 data_time: 0.0267 memory: 21547 grad_norm: 4.7371 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1625 loss: 1.1625 2022/10/10 08:33:43 - mmengine - INFO - Epoch(train) [78][460/940] lr: 1.0000e-03 eta: 2:58:50 time: 0.5319 data_time: 0.0228 memory: 21547 grad_norm: 4.7490 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.0925 loss: 1.0925 2022/10/10 08:33:52 - mmengine - INFO - Epoch(train) [78][480/940] lr: 1.0000e-03 eta: 2:58:40 time: 0.4817 data_time: 0.0242 memory: 21547 grad_norm: 4.8327 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1061 loss: 1.1061 2022/10/10 08:34:02 - mmengine - INFO - Epoch(train) [78][500/940] lr: 1.0000e-03 eta: 2:58:30 time: 0.4778 data_time: 0.0310 memory: 21547 grad_norm: 4.7076 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2651 loss: 1.2651 2022/10/10 08:34:12 - mmengine - INFO - Epoch(train) [78][520/940] lr: 1.0000e-03 eta: 2:58:19 time: 0.4793 data_time: 0.0291 memory: 21547 grad_norm: 4.7907 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1826 loss: 1.1826 2022/10/10 08:34:21 - mmengine - INFO - Epoch(train) [78][540/940] lr: 1.0000e-03 eta: 2:58:09 time: 0.4880 data_time: 0.0258 memory: 21547 grad_norm: 4.9364 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2334 loss: 1.2334 2022/10/10 08:34:31 - mmengine - INFO - Epoch(train) [78][560/940] lr: 1.0000e-03 eta: 2:57:59 time: 0.4707 data_time: 0.0290 memory: 21547 grad_norm: 4.8317 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2413 loss: 1.2413 2022/10/10 08:34:41 - mmengine - INFO - Epoch(train) [78][580/940] lr: 1.0000e-03 eta: 2:57:49 time: 0.5145 data_time: 0.0263 memory: 21547 grad_norm: 4.8025 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0328 loss: 1.0328 2022/10/10 08:34:52 - mmengine - INFO - Epoch(train) [78][600/940] lr: 1.0000e-03 eta: 2:57:39 time: 0.5282 data_time: 0.0321 memory: 21547 grad_norm: 4.8301 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.2711 loss: 1.2711 2022/10/10 08:35:03 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 08:35:03 - mmengine - INFO - Epoch(train) [78][620/940] lr: 1.0000e-03 eta: 2:57:29 time: 0.5515 data_time: 0.0304 memory: 21547 grad_norm: 4.7512 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0962 loss: 1.0962 2022/10/10 08:35:13 - mmengine - INFO - Epoch(train) [78][640/940] lr: 1.0000e-03 eta: 2:57:19 time: 0.5246 data_time: 0.0255 memory: 21547 grad_norm: 4.7740 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2203 loss: 1.2203 2022/10/10 08:35:23 - mmengine - INFO - Epoch(train) [78][660/940] lr: 1.0000e-03 eta: 2:57:08 time: 0.4771 data_time: 0.0272 memory: 21547 grad_norm: 4.8161 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.2499 loss: 1.2499 2022/10/10 08:35:33 - mmengine - INFO - Epoch(train) [78][680/940] lr: 1.0000e-03 eta: 2:56:58 time: 0.5241 data_time: 0.0240 memory: 21547 grad_norm: 4.8110 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1721 loss: 1.1721 2022/10/10 08:35:43 - mmengine - INFO - Epoch(train) [78][700/940] lr: 1.0000e-03 eta: 2:56:48 time: 0.4935 data_time: 0.0247 memory: 21547 grad_norm: 4.7566 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2925 loss: 1.2925 2022/10/10 08:35:53 - mmengine - INFO - Epoch(train) [78][720/940] lr: 1.0000e-03 eta: 2:56:38 time: 0.5087 data_time: 0.0236 memory: 21547 grad_norm: 4.7634 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2295 loss: 1.2295 2022/10/10 08:36:03 - mmengine - INFO - Epoch(train) [78][740/940] lr: 1.0000e-03 eta: 2:56:28 time: 0.4989 data_time: 0.0280 memory: 21547 grad_norm: 4.8223 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2205 loss: 1.2205 2022/10/10 08:36:13 - mmengine - INFO - Epoch(train) [78][760/940] lr: 1.0000e-03 eta: 2:56:18 time: 0.4950 data_time: 0.0234 memory: 21547 grad_norm: 4.7941 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 1.2113 loss: 1.2113 2022/10/10 08:36:23 - mmengine - INFO - Epoch(train) [78][780/940] lr: 1.0000e-03 eta: 2:56:07 time: 0.4912 data_time: 0.0289 memory: 21547 grad_norm: 4.8447 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1846 loss: 1.1846 2022/10/10 08:36:33 - mmengine - INFO - Epoch(train) [78][800/940] lr: 1.0000e-03 eta: 2:55:57 time: 0.4981 data_time: 0.0307 memory: 21547 grad_norm: 4.8160 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2668 loss: 1.2668 2022/10/10 08:36:43 - mmengine - INFO - Epoch(train) [78][820/940] lr: 1.0000e-03 eta: 2:55:47 time: 0.5047 data_time: 0.0270 memory: 21547 grad_norm: 4.9141 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2706 loss: 1.2706 2022/10/10 08:36:53 - mmengine - INFO - Epoch(train) [78][840/940] lr: 1.0000e-03 eta: 2:55:37 time: 0.5140 data_time: 0.0270 memory: 21547 grad_norm: 4.9193 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2743 loss: 1.2743 2022/10/10 08:37:03 - mmengine - INFO - Epoch(train) [78][860/940] lr: 1.0000e-03 eta: 2:55:27 time: 0.4775 data_time: 0.0240 memory: 21547 grad_norm: 4.9033 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.2656 loss: 1.2656 2022/10/10 08:37:13 - mmengine - INFO - Epoch(train) [78][880/940] lr: 1.0000e-03 eta: 2:55:17 time: 0.5207 data_time: 0.0297 memory: 21547 grad_norm: 4.8815 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1552 loss: 1.1552 2022/10/10 08:37:23 - mmengine - INFO - Epoch(train) [78][900/940] lr: 1.0000e-03 eta: 2:55:06 time: 0.5026 data_time: 0.0240 memory: 21547 grad_norm: 4.7758 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1272 loss: 1.1272 2022/10/10 08:37:33 - mmengine - INFO - Epoch(train) [78][920/940] lr: 1.0000e-03 eta: 2:54:56 time: 0.4773 data_time: 0.0285 memory: 21547 grad_norm: 4.8337 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1390 loss: 1.1390 2022/10/10 08:37:42 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 08:37:42 - mmengine - INFO - Epoch(train) [78][940/940] lr: 1.0000e-03 eta: 2:54:46 time: 0.4402 data_time: 0.0307 memory: 21547 grad_norm: 5.0742 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.2264 loss: 1.2264 2022/10/10 08:37:42 - mmengine - INFO - Saving checkpoint at 78 epochs 2022/10/10 08:37:55 - mmengine - INFO - Epoch(val) [78][20/78] eta: 0:00:35 time: 0.6100 data_time: 0.5048 memory: 3269 2022/10/10 08:38:03 - mmengine - INFO - Epoch(val) [78][40/78] eta: 0:00:16 time: 0.4234 data_time: 0.3194 memory: 3269 2022/10/10 08:38:14 - mmengine - INFO - Epoch(val) [78][60/78] eta: 0:00:09 time: 0.5517 data_time: 0.4471 memory: 3269 2022/10/10 08:38:23 - mmengine - INFO - Epoch(val) [78][78/78] acc/top1: 0.6797 acc/top5: 0.8715 acc/mean1: 0.6796 2022/10/10 08:38:24 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_63.pth is removed 2022/10/10 08:38:24 - mmengine - INFO - The best checkpoint with 0.6797 acc/top1 at 78 epoch is saved to best_acc/top1_epoch_78.pth. 2022/10/10 08:38:38 - mmengine - INFO - Epoch(train) [79][20/940] lr: 1.0000e-03 eta: 2:54:36 time: 0.6960 data_time: 0.3264 memory: 21547 grad_norm: 4.8178 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1503 loss: 1.1503 2022/10/10 08:38:49 - mmengine - INFO - Epoch(train) [79][40/940] lr: 1.0000e-03 eta: 2:54:26 time: 0.5113 data_time: 0.1374 memory: 21547 grad_norm: 4.8261 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2182 loss: 1.2182 2022/10/10 08:38:58 - mmengine - INFO - Epoch(train) [79][60/940] lr: 1.0000e-03 eta: 2:54:16 time: 0.4735 data_time: 0.0872 memory: 21547 grad_norm: 4.9399 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.2473 loss: 1.2473 2022/10/10 08:39:07 - mmengine - INFO - Epoch(train) [79][80/940] lr: 1.0000e-03 eta: 2:54:06 time: 0.4603 data_time: 0.0324 memory: 21547 grad_norm: 4.8662 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0886 loss: 1.0886 2022/10/10 08:39:17 - mmengine - INFO - Epoch(train) [79][100/940] lr: 1.0000e-03 eta: 2:53:55 time: 0.5043 data_time: 0.0324 memory: 21547 grad_norm: 4.7628 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1602 loss: 1.1602 2022/10/10 08:39:27 - mmengine - INFO - Epoch(train) [79][120/940] lr: 1.0000e-03 eta: 2:53:45 time: 0.4795 data_time: 0.0280 memory: 21547 grad_norm: 4.8826 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2353 loss: 1.2353 2022/10/10 08:39:38 - mmengine - INFO - Epoch(train) [79][140/940] lr: 1.0000e-03 eta: 2:53:35 time: 0.5662 data_time: 0.0443 memory: 21547 grad_norm: 4.7430 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.1796 loss: 1.1796 2022/10/10 08:39:48 - mmengine - INFO - Epoch(train) [79][160/940] lr: 1.0000e-03 eta: 2:53:25 time: 0.4892 data_time: 0.0250 memory: 21547 grad_norm: 4.7871 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1179 loss: 1.1179 2022/10/10 08:39:59 - mmengine - INFO - Epoch(train) [79][180/940] lr: 1.0000e-03 eta: 2:53:15 time: 0.5578 data_time: 0.0288 memory: 21547 grad_norm: 4.8584 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1374 loss: 1.1374 2022/10/10 08:40:09 - mmengine - INFO - Epoch(train) [79][200/940] lr: 1.0000e-03 eta: 2:53:05 time: 0.4860 data_time: 0.0257 memory: 21547 grad_norm: 4.7832 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2580 loss: 1.2580 2022/10/10 08:40:20 - mmengine - INFO - Epoch(train) [79][220/940] lr: 1.0000e-03 eta: 2:52:55 time: 0.5270 data_time: 0.0273 memory: 21547 grad_norm: 4.6740 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 1.1686 loss: 1.1686 2022/10/10 08:40:29 - mmengine - INFO - Epoch(train) [79][240/940] lr: 1.0000e-03 eta: 2:52:45 time: 0.4980 data_time: 0.0303 memory: 21547 grad_norm: 4.8496 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1722 loss: 1.1722 2022/10/10 08:40:39 - mmengine - INFO - Epoch(train) [79][260/940] lr: 1.0000e-03 eta: 2:52:34 time: 0.4692 data_time: 0.0313 memory: 21547 grad_norm: 4.8895 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1766 loss: 1.1766 2022/10/10 08:40:49 - mmengine - INFO - Epoch(train) [79][280/940] lr: 1.0000e-03 eta: 2:52:24 time: 0.4953 data_time: 0.0288 memory: 21547 grad_norm: 4.7181 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2248 loss: 1.2248 2022/10/10 08:40:59 - mmengine - INFO - Epoch(train) [79][300/940] lr: 1.0000e-03 eta: 2:52:14 time: 0.5082 data_time: 0.0282 memory: 21547 grad_norm: 4.8080 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2280 loss: 1.2280 2022/10/10 08:41:09 - mmengine - INFO - Epoch(train) [79][320/940] lr: 1.0000e-03 eta: 2:52:04 time: 0.4932 data_time: 0.0271 memory: 21547 grad_norm: 4.7608 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3105 loss: 1.3105 2022/10/10 08:41:19 - mmengine - INFO - Epoch(train) [79][340/940] lr: 1.0000e-03 eta: 2:51:54 time: 0.5106 data_time: 0.0297 memory: 21547 grad_norm: 4.8922 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0924 loss: 1.0924 2022/10/10 08:41:28 - mmengine - INFO - Epoch(train) [79][360/940] lr: 1.0000e-03 eta: 2:51:43 time: 0.4710 data_time: 0.0301 memory: 21547 grad_norm: 4.7288 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2771 loss: 1.2771 2022/10/10 08:41:39 - mmengine - INFO - Epoch(train) [79][380/940] lr: 1.0000e-03 eta: 2:51:33 time: 0.5096 data_time: 0.0281 memory: 21547 grad_norm: 4.8116 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1574 loss: 1.1574 2022/10/10 08:41:48 - mmengine - INFO - Epoch(train) [79][400/940] lr: 1.0000e-03 eta: 2:51:23 time: 0.4866 data_time: 0.0303 memory: 21547 grad_norm: 4.7867 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1634 loss: 1.1634 2022/10/10 08:41:58 - mmengine - INFO - Epoch(train) [79][420/940] lr: 1.0000e-03 eta: 2:51:13 time: 0.5032 data_time: 0.0311 memory: 21547 grad_norm: 4.7953 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1237 loss: 1.1237 2022/10/10 08:42:09 - mmengine - INFO - Epoch(train) [79][440/940] lr: 1.0000e-03 eta: 2:51:03 time: 0.5327 data_time: 0.0285 memory: 21547 grad_norm: 4.9464 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2778 loss: 1.2778 2022/10/10 08:42:19 - mmengine - INFO - Epoch(train) [79][460/940] lr: 1.0000e-03 eta: 2:50:53 time: 0.4769 data_time: 0.0274 memory: 21547 grad_norm: 4.8197 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1375 loss: 1.1375 2022/10/10 08:42:30 - mmengine - INFO - Epoch(train) [79][480/940] lr: 1.0000e-03 eta: 2:50:43 time: 0.5634 data_time: 0.0288 memory: 21547 grad_norm: 4.7205 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1305 loss: 1.1305 2022/10/10 08:42:39 - mmengine - INFO - Epoch(train) [79][500/940] lr: 1.0000e-03 eta: 2:50:32 time: 0.4577 data_time: 0.0231 memory: 21547 grad_norm: 4.7213 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0527 loss: 1.0527 2022/10/10 08:42:50 - mmengine - INFO - Epoch(train) [79][520/940] lr: 1.0000e-03 eta: 2:50:22 time: 0.5519 data_time: 0.0283 memory: 21547 grad_norm: 4.8396 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1193 loss: 1.1193 2022/10/10 08:42:59 - mmengine - INFO - Epoch(train) [79][540/940] lr: 1.0000e-03 eta: 2:50:12 time: 0.4383 data_time: 0.0240 memory: 21547 grad_norm: 4.8538 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1907 loss: 1.1907 2022/10/10 08:43:09 - mmengine - INFO - Epoch(train) [79][560/940] lr: 1.0000e-03 eta: 2:50:02 time: 0.5066 data_time: 0.0264 memory: 21547 grad_norm: 4.9549 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1259 loss: 1.1259 2022/10/10 08:43:18 - mmengine - INFO - Epoch(train) [79][580/940] lr: 1.0000e-03 eta: 2:49:51 time: 0.4624 data_time: 0.0258 memory: 21547 grad_norm: 4.9316 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3052 loss: 1.3052 2022/10/10 08:43:29 - mmengine - INFO - Epoch(train) [79][600/940] lr: 1.0000e-03 eta: 2:49:41 time: 0.5451 data_time: 0.0261 memory: 21547 grad_norm: 4.6841 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.1617 loss: 1.1617 2022/10/10 08:43:40 - mmengine - INFO - Epoch(train) [79][620/940] lr: 1.0000e-03 eta: 2:49:31 time: 0.5302 data_time: 0.0352 memory: 21547 grad_norm: 4.7852 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1500 loss: 1.1500 2022/10/10 08:43:50 - mmengine - INFO - Epoch(train) [79][640/940] lr: 1.0000e-03 eta: 2:49:21 time: 0.5322 data_time: 0.0256 memory: 21547 grad_norm: 4.7257 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1672 loss: 1.1672 2022/10/10 08:44:01 - mmengine - INFO - Epoch(train) [79][660/940] lr: 1.0000e-03 eta: 2:49:11 time: 0.5116 data_time: 0.0244 memory: 21547 grad_norm: 4.8629 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.3010 loss: 1.3010 2022/10/10 08:44:11 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 08:44:11 - mmengine - INFO - Epoch(train) [79][680/940] lr: 1.0000e-03 eta: 2:49:01 time: 0.5027 data_time: 0.0222 memory: 21547 grad_norm: 5.0164 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1292 loss: 1.1292 2022/10/10 08:44:20 - mmengine - INFO - Epoch(train) [79][700/940] lr: 1.0000e-03 eta: 2:48:51 time: 0.4853 data_time: 0.0283 memory: 21547 grad_norm: 4.8459 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0511 loss: 1.0511 2022/10/10 08:44:31 - mmengine - INFO - Epoch(train) [79][720/940] lr: 1.0000e-03 eta: 2:48:41 time: 0.5172 data_time: 0.0306 memory: 21547 grad_norm: 4.7857 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.2901 loss: 1.2901 2022/10/10 08:44:41 - mmengine - INFO - Epoch(train) [79][740/940] lr: 1.0000e-03 eta: 2:48:31 time: 0.5130 data_time: 0.0294 memory: 21547 grad_norm: 4.7239 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0701 loss: 1.0701 2022/10/10 08:44:51 - mmengine - INFO - Epoch(train) [79][760/940] lr: 1.0000e-03 eta: 2:48:21 time: 0.5125 data_time: 0.0293 memory: 21547 grad_norm: 4.8243 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2367 loss: 1.2367 2022/10/10 08:45:01 - mmengine - INFO - Epoch(train) [79][780/940] lr: 1.0000e-03 eta: 2:48:10 time: 0.4947 data_time: 0.0314 memory: 21547 grad_norm: 4.8281 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1436 loss: 1.1436 2022/10/10 08:45:11 - mmengine - INFO - Epoch(train) [79][800/940] lr: 1.0000e-03 eta: 2:48:00 time: 0.5016 data_time: 0.0250 memory: 21547 grad_norm: 4.8580 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2251 loss: 1.2251 2022/10/10 08:45:21 - mmengine - INFO - Epoch(train) [79][820/940] lr: 1.0000e-03 eta: 2:47:50 time: 0.4698 data_time: 0.0329 memory: 21547 grad_norm: 4.8244 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2735 loss: 1.2735 2022/10/10 08:45:32 - mmengine - INFO - Epoch(train) [79][840/940] lr: 1.0000e-03 eta: 2:47:40 time: 0.5673 data_time: 0.0305 memory: 21547 grad_norm: 4.8710 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2144 loss: 1.2144 2022/10/10 08:45:42 - mmengine - INFO - Epoch(train) [79][860/940] lr: 1.0000e-03 eta: 2:47:30 time: 0.4950 data_time: 0.0301 memory: 21547 grad_norm: 4.8702 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2497 loss: 1.2497 2022/10/10 08:45:52 - mmengine - INFO - Epoch(train) [79][880/940] lr: 1.0000e-03 eta: 2:47:20 time: 0.5063 data_time: 0.0299 memory: 21547 grad_norm: 4.7593 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.1687 loss: 1.1687 2022/10/10 08:46:02 - mmengine - INFO - Epoch(train) [79][900/940] lr: 1.0000e-03 eta: 2:47:09 time: 0.4926 data_time: 0.0259 memory: 21547 grad_norm: 4.8062 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1439 loss: 1.1439 2022/10/10 08:46:12 - mmengine - INFO - Epoch(train) [79][920/940] lr: 1.0000e-03 eta: 2:46:59 time: 0.5143 data_time: 0.0263 memory: 21547 grad_norm: 4.8871 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.1318 loss: 1.1318 2022/10/10 08:46:21 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 08:46:21 - mmengine - INFO - Epoch(train) [79][940/940] lr: 1.0000e-03 eta: 2:46:49 time: 0.4484 data_time: 0.0260 memory: 21547 grad_norm: 5.1238 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.2278 loss: 1.2278 2022/10/10 08:46:33 - mmengine - INFO - Epoch(val) [79][20/78] eta: 0:00:35 time: 0.6110 data_time: 0.5040 memory: 3269 2022/10/10 08:46:42 - mmengine - INFO - Epoch(val) [79][40/78] eta: 0:00:16 time: 0.4222 data_time: 0.3150 memory: 3269 2022/10/10 08:46:53 - mmengine - INFO - Epoch(val) [79][60/78] eta: 0:00:09 time: 0.5501 data_time: 0.4432 memory: 3269 2022/10/10 08:47:03 - mmengine - INFO - Epoch(val) [79][78/78] acc/top1: 0.6792 acc/top5: 0.8707 acc/mean1: 0.6791 2022/10/10 08:47:17 - mmengine - INFO - Epoch(train) [80][20/940] lr: 1.0000e-03 eta: 2:46:40 time: 0.7002 data_time: 0.2675 memory: 21547 grad_norm: 4.7796 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0660 loss: 1.0660 2022/10/10 08:47:26 - mmengine - INFO - Epoch(train) [80][40/940] lr: 1.0000e-03 eta: 2:46:30 time: 0.4923 data_time: 0.1004 memory: 21547 grad_norm: 4.6947 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1012 loss: 1.1012 2022/10/10 08:47:37 - mmengine - INFO - Epoch(train) [80][60/940] lr: 1.0000e-03 eta: 2:46:20 time: 0.5293 data_time: 0.0361 memory: 21547 grad_norm: 4.9043 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2143 loss: 1.2143 2022/10/10 08:47:47 - mmengine - INFO - Epoch(train) [80][80/940] lr: 1.0000e-03 eta: 2:46:09 time: 0.4795 data_time: 0.0248 memory: 21547 grad_norm: 4.9098 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0711 loss: 1.0711 2022/10/10 08:47:57 - mmengine - INFO - Epoch(train) [80][100/940] lr: 1.0000e-03 eta: 2:45:59 time: 0.5249 data_time: 0.0312 memory: 21547 grad_norm: 4.7995 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2651 loss: 1.2651 2022/10/10 08:48:07 - mmengine - INFO - Epoch(train) [80][120/940] lr: 1.0000e-03 eta: 2:45:49 time: 0.4744 data_time: 0.0251 memory: 21547 grad_norm: 4.7969 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1739 loss: 1.1739 2022/10/10 08:48:17 - mmengine - INFO - Epoch(train) [80][140/940] lr: 1.0000e-03 eta: 2:45:39 time: 0.5078 data_time: 0.0330 memory: 21547 grad_norm: 4.9078 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3076 loss: 1.3076 2022/10/10 08:48:27 - mmengine - INFO - Epoch(train) [80][160/940] lr: 1.0000e-03 eta: 2:45:28 time: 0.4855 data_time: 0.0281 memory: 21547 grad_norm: 4.9615 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1768 loss: 1.1768 2022/10/10 08:48:37 - mmengine - INFO - Epoch(train) [80][180/940] lr: 1.0000e-03 eta: 2:45:18 time: 0.5086 data_time: 0.0339 memory: 21547 grad_norm: 4.8582 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1911 loss: 1.1911 2022/10/10 08:48:47 - mmengine - INFO - Epoch(train) [80][200/940] lr: 1.0000e-03 eta: 2:45:08 time: 0.5086 data_time: 0.0301 memory: 21547 grad_norm: 4.7488 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1713 loss: 1.1713 2022/10/10 08:48:56 - mmengine - INFO - Epoch(train) [80][220/940] lr: 1.0000e-03 eta: 2:44:58 time: 0.4711 data_time: 0.0384 memory: 21547 grad_norm: 4.7720 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1084 loss: 1.1084 2022/10/10 08:49:07 - mmengine - INFO - Epoch(train) [80][240/940] lr: 1.0000e-03 eta: 2:44:48 time: 0.5205 data_time: 0.0240 memory: 21547 grad_norm: 4.8806 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2974 loss: 1.2974 2022/10/10 08:49:17 - mmengine - INFO - Epoch(train) [80][260/940] lr: 1.0000e-03 eta: 2:44:38 time: 0.5097 data_time: 0.0336 memory: 21547 grad_norm: 4.8021 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1607 loss: 1.1607 2022/10/10 08:49:27 - mmengine - INFO - Epoch(train) [80][280/940] lr: 1.0000e-03 eta: 2:44:28 time: 0.5189 data_time: 0.0277 memory: 21547 grad_norm: 4.8055 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1261 loss: 1.1261 2022/10/10 08:49:37 - mmengine - INFO - Epoch(train) [80][300/940] lr: 1.0000e-03 eta: 2:44:17 time: 0.4726 data_time: 0.0252 memory: 21547 grad_norm: 4.8915 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.1906 loss: 1.1906 2022/10/10 08:49:47 - mmengine - INFO - Epoch(train) [80][320/940] lr: 1.0000e-03 eta: 2:44:07 time: 0.5044 data_time: 0.0255 memory: 21547 grad_norm: 4.7925 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.1015 loss: 1.1015 2022/10/10 08:49:57 - mmengine - INFO - Epoch(train) [80][340/940] lr: 1.0000e-03 eta: 2:43:57 time: 0.5058 data_time: 0.0278 memory: 21547 grad_norm: 4.8656 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1578 loss: 1.1578 2022/10/10 08:50:06 - mmengine - INFO - Epoch(train) [80][360/940] lr: 1.0000e-03 eta: 2:43:47 time: 0.4660 data_time: 0.0259 memory: 21547 grad_norm: 4.8732 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1698 loss: 1.1698 2022/10/10 08:50:16 - mmengine - INFO - Epoch(train) [80][380/940] lr: 1.0000e-03 eta: 2:43:36 time: 0.5118 data_time: 0.0287 memory: 21547 grad_norm: 4.7061 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1242 loss: 1.1242 2022/10/10 08:50:27 - mmengine - INFO - Epoch(train) [80][400/940] lr: 1.0000e-03 eta: 2:43:26 time: 0.5331 data_time: 0.0308 memory: 21547 grad_norm: 4.8783 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2034 loss: 1.2034 2022/10/10 08:50:37 - mmengine - INFO - Epoch(train) [80][420/940] lr: 1.0000e-03 eta: 2:43:16 time: 0.5084 data_time: 0.0301 memory: 21547 grad_norm: 4.8407 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1598 loss: 1.1598 2022/10/10 08:50:48 - mmengine - INFO - Epoch(train) [80][440/940] lr: 1.0000e-03 eta: 2:43:06 time: 0.5409 data_time: 0.0277 memory: 21547 grad_norm: 4.7445 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1138 loss: 1.1138 2022/10/10 08:50:58 - mmengine - INFO - Epoch(train) [80][460/940] lr: 1.0000e-03 eta: 2:42:56 time: 0.5006 data_time: 0.0298 memory: 21547 grad_norm: 5.0112 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2004 loss: 1.2004 2022/10/10 08:51:08 - mmengine - INFO - Epoch(train) [80][480/940] lr: 1.0000e-03 eta: 2:42:46 time: 0.4988 data_time: 0.0273 memory: 21547 grad_norm: 4.8516 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.1299 loss: 1.1299 2022/10/10 08:51:18 - mmengine - INFO - Epoch(train) [80][500/940] lr: 1.0000e-03 eta: 2:42:36 time: 0.4685 data_time: 0.0281 memory: 21547 grad_norm: 4.8447 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1580 loss: 1.1580 2022/10/10 08:51:28 - mmengine - INFO - Epoch(train) [80][520/940] lr: 1.0000e-03 eta: 2:42:26 time: 0.5101 data_time: 0.0274 memory: 21547 grad_norm: 4.7951 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2250 loss: 1.2250 2022/10/10 08:51:37 - mmengine - INFO - Epoch(train) [80][540/940] lr: 1.0000e-03 eta: 2:42:15 time: 0.4719 data_time: 0.0245 memory: 21547 grad_norm: 4.9034 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2828 loss: 1.2828 2022/10/10 08:51:48 - mmengine - INFO - Epoch(train) [80][560/940] lr: 1.0000e-03 eta: 2:42:05 time: 0.5322 data_time: 0.0369 memory: 21547 grad_norm: 4.8777 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2396 loss: 1.2396 2022/10/10 08:51:57 - mmengine - INFO - Epoch(train) [80][580/940] lr: 1.0000e-03 eta: 2:41:55 time: 0.4752 data_time: 0.0308 memory: 21547 grad_norm: 4.9065 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.1516 loss: 1.1516 2022/10/10 08:52:07 - mmengine - INFO - Epoch(train) [80][600/940] lr: 1.0000e-03 eta: 2:41:45 time: 0.5042 data_time: 0.0283 memory: 21547 grad_norm: 4.7510 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2190 loss: 1.2190 2022/10/10 08:52:18 - mmengine - INFO - Epoch(train) [80][620/940] lr: 1.0000e-03 eta: 2:41:35 time: 0.5053 data_time: 0.0289 memory: 21547 grad_norm: 5.0184 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1611 loss: 1.1611 2022/10/10 08:52:28 - mmengine - INFO - Epoch(train) [80][640/940] lr: 1.0000e-03 eta: 2:41:25 time: 0.5447 data_time: 0.0338 memory: 21547 grad_norm: 4.9208 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.3372 loss: 1.3372 2022/10/10 08:52:38 - mmengine - INFO - Epoch(train) [80][660/940] lr: 1.0000e-03 eta: 2:41:14 time: 0.4736 data_time: 0.0233 memory: 21547 grad_norm: 4.7958 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2190 loss: 1.2190 2022/10/10 08:52:48 - mmengine - INFO - Epoch(train) [80][680/940] lr: 1.0000e-03 eta: 2:41:04 time: 0.4989 data_time: 0.0285 memory: 21547 grad_norm: 4.7287 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2775 loss: 1.2775 2022/10/10 08:52:58 - mmengine - INFO - Epoch(train) [80][700/940] lr: 1.0000e-03 eta: 2:40:54 time: 0.4982 data_time: 0.0289 memory: 21547 grad_norm: 4.7834 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1702 loss: 1.1702 2022/10/10 08:53:08 - mmengine - INFO - Epoch(train) [80][720/940] lr: 1.0000e-03 eta: 2:40:44 time: 0.5065 data_time: 0.0279 memory: 21547 grad_norm: 4.8322 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2568 loss: 1.2568 2022/10/10 08:53:18 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 08:53:18 - mmengine - INFO - Epoch(train) [80][740/940] lr: 1.0000e-03 eta: 2:40:34 time: 0.4807 data_time: 0.0329 memory: 21547 grad_norm: 4.8109 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.1342 loss: 1.1342 2022/10/10 08:53:28 - mmengine - INFO - Epoch(train) [80][760/940] lr: 1.0000e-03 eta: 2:40:23 time: 0.5167 data_time: 0.0348 memory: 21547 grad_norm: 4.8663 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1681 loss: 1.1681 2022/10/10 08:53:38 - mmengine - INFO - Epoch(train) [80][780/940] lr: 1.0000e-03 eta: 2:40:13 time: 0.4970 data_time: 0.0297 memory: 21547 grad_norm: 4.8347 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1658 loss: 1.1658 2022/10/10 08:53:49 - mmengine - INFO - Epoch(train) [80][800/940] lr: 1.0000e-03 eta: 2:40:03 time: 0.5338 data_time: 0.0305 memory: 21547 grad_norm: 5.0141 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3436 loss: 1.3436 2022/10/10 08:53:58 - mmengine - INFO - Epoch(train) [80][820/940] lr: 1.0000e-03 eta: 2:39:53 time: 0.4983 data_time: 0.0300 memory: 21547 grad_norm: 4.7824 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.1484 loss: 1.1484 2022/10/10 08:54:08 - mmengine - INFO - Epoch(train) [80][840/940] lr: 1.0000e-03 eta: 2:39:43 time: 0.4923 data_time: 0.0274 memory: 21547 grad_norm: 4.9151 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2325 loss: 1.2325 2022/10/10 08:54:19 - mmengine - INFO - Epoch(train) [80][860/940] lr: 1.0000e-03 eta: 2:39:33 time: 0.5271 data_time: 0.0313 memory: 21547 grad_norm: 4.7749 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1925 loss: 1.1925 2022/10/10 08:54:29 - mmengine - INFO - Epoch(train) [80][880/940] lr: 1.0000e-03 eta: 2:39:23 time: 0.5062 data_time: 0.0292 memory: 21547 grad_norm: 4.8982 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3032 loss: 1.3032 2022/10/10 08:54:39 - mmengine - INFO - Epoch(train) [80][900/940] lr: 1.0000e-03 eta: 2:39:12 time: 0.4836 data_time: 0.0241 memory: 21547 grad_norm: 4.8032 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0939 loss: 1.0939 2022/10/10 08:54:48 - mmengine - INFO - Epoch(train) [80][920/940] lr: 1.0000e-03 eta: 2:39:02 time: 0.4489 data_time: 0.0258 memory: 21547 grad_norm: 4.7862 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1722 loss: 1.1722 2022/10/10 08:54:58 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 08:54:58 - mmengine - INFO - Epoch(train) [80][940/940] lr: 1.0000e-03 eta: 2:38:52 time: 0.5095 data_time: 0.0203 memory: 21547 grad_norm: 5.1078 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.2275 loss: 1.2275 2022/10/10 08:55:10 - mmengine - INFO - Epoch(val) [80][20/78] eta: 0:00:34 time: 0.6006 data_time: 0.4925 memory: 3269 2022/10/10 08:55:18 - mmengine - INFO - Epoch(val) [80][40/78] eta: 0:00:16 time: 0.4237 data_time: 0.3163 memory: 3269 2022/10/10 08:55:29 - mmengine - INFO - Epoch(val) [80][60/78] eta: 0:00:09 time: 0.5554 data_time: 0.4470 memory: 3269 2022/10/10 08:55:39 - mmengine - INFO - Epoch(val) [80][78/78] acc/top1: 0.6766 acc/top5: 0.8694 acc/mean1: 0.6765 2022/10/10 08:55:53 - mmengine - INFO - Epoch(train) [81][20/940] lr: 1.0000e-04 eta: 2:38:43 time: 0.7005 data_time: 0.2375 memory: 21547 grad_norm: 4.7667 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1547 loss: 1.1547 2022/10/10 08:56:03 - mmengine - INFO - Epoch(train) [81][40/940] lr: 1.0000e-04 eta: 2:38:32 time: 0.4745 data_time: 0.0363 memory: 21547 grad_norm: 4.8860 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2218 loss: 1.2218 2022/10/10 08:56:14 - mmengine - INFO - Epoch(train) [81][60/940] lr: 1.0000e-04 eta: 2:38:22 time: 0.5305 data_time: 0.0272 memory: 21547 grad_norm: 4.8020 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1423 loss: 1.1423 2022/10/10 08:56:24 - mmengine - INFO - Epoch(train) [81][80/940] lr: 1.0000e-04 eta: 2:38:12 time: 0.4991 data_time: 0.0272 memory: 21547 grad_norm: 4.7239 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1575 loss: 1.1575 2022/10/10 08:56:35 - mmengine - INFO - Epoch(train) [81][100/940] lr: 1.0000e-04 eta: 2:38:02 time: 0.5682 data_time: 0.0283 memory: 21547 grad_norm: 4.6214 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1407 loss: 1.1407 2022/10/10 08:56:44 - mmengine - INFO - Epoch(train) [81][120/940] lr: 1.0000e-04 eta: 2:37:52 time: 0.4643 data_time: 0.0296 memory: 21547 grad_norm: 4.8783 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1949 loss: 1.1949 2022/10/10 08:56:55 - mmengine - INFO - Epoch(train) [81][140/940] lr: 1.0000e-04 eta: 2:37:42 time: 0.5581 data_time: 0.0273 memory: 21547 grad_norm: 4.7054 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0986 loss: 1.0986 2022/10/10 08:57:04 - mmengine - INFO - Epoch(train) [81][160/940] lr: 1.0000e-04 eta: 2:37:32 time: 0.4519 data_time: 0.0304 memory: 21547 grad_norm: 4.6544 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2691 loss: 1.2691 2022/10/10 08:57:15 - mmengine - INFO - Epoch(train) [81][180/940] lr: 1.0000e-04 eta: 2:37:22 time: 0.5105 data_time: 0.0277 memory: 21547 grad_norm: 4.8315 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0563 loss: 1.0563 2022/10/10 08:57:24 - mmengine - INFO - Epoch(train) [81][200/940] lr: 1.0000e-04 eta: 2:37:11 time: 0.4920 data_time: 0.0305 memory: 21547 grad_norm: 4.8756 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2331 loss: 1.2331 2022/10/10 08:57:34 - mmengine - INFO - Epoch(train) [81][220/940] lr: 1.0000e-04 eta: 2:37:01 time: 0.4586 data_time: 0.0293 memory: 21547 grad_norm: 4.6926 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1155 loss: 1.1155 2022/10/10 08:57:44 - mmengine - INFO - Epoch(train) [81][240/940] lr: 1.0000e-04 eta: 2:36:51 time: 0.5103 data_time: 0.0284 memory: 21547 grad_norm: 4.7821 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0880 loss: 1.0880 2022/10/10 08:57:54 - mmengine - INFO - Epoch(train) [81][260/940] lr: 1.0000e-04 eta: 2:36:41 time: 0.5274 data_time: 0.0280 memory: 21547 grad_norm: 4.8110 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1011 loss: 1.1011 2022/10/10 08:58:04 - mmengine - INFO - Epoch(train) [81][280/940] lr: 1.0000e-04 eta: 2:36:30 time: 0.4650 data_time: 0.0251 memory: 21547 grad_norm: 4.8012 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2058 loss: 1.2058 2022/10/10 08:58:15 - mmengine - INFO - Epoch(train) [81][300/940] lr: 1.0000e-04 eta: 2:36:21 time: 0.5860 data_time: 0.0284 memory: 21547 grad_norm: 4.7712 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2264 loss: 1.2264 2022/10/10 08:58:25 - mmengine - INFO - Epoch(train) [81][320/940] lr: 1.0000e-04 eta: 2:36:10 time: 0.4635 data_time: 0.0302 memory: 21547 grad_norm: 4.7665 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2590 loss: 1.2590 2022/10/10 08:58:35 - mmengine - INFO - Epoch(train) [81][340/940] lr: 1.0000e-04 eta: 2:36:00 time: 0.4951 data_time: 0.0273 memory: 21547 grad_norm: 4.9847 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2290 loss: 1.2290 2022/10/10 08:58:44 - mmengine - INFO - Epoch(train) [81][360/940] lr: 1.0000e-04 eta: 2:35:50 time: 0.4749 data_time: 0.0287 memory: 21547 grad_norm: 4.8288 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1702 loss: 1.1702 2022/10/10 08:58:54 - mmengine - INFO - Epoch(train) [81][380/940] lr: 1.0000e-04 eta: 2:35:40 time: 0.4878 data_time: 0.0287 memory: 21547 grad_norm: 4.6898 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1053 loss: 1.1053 2022/10/10 08:59:04 - mmengine - INFO - Epoch(train) [81][400/940] lr: 1.0000e-04 eta: 2:35:29 time: 0.4963 data_time: 0.0291 memory: 21547 grad_norm: 4.8193 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0880 loss: 1.0880 2022/10/10 08:59:14 - mmengine - INFO - Epoch(train) [81][420/940] lr: 1.0000e-04 eta: 2:35:19 time: 0.5002 data_time: 0.0234 memory: 21547 grad_norm: 4.8325 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1245 loss: 1.1245 2022/10/10 08:59:25 - mmengine - INFO - Epoch(train) [81][440/940] lr: 1.0000e-04 eta: 2:35:09 time: 0.5519 data_time: 0.0324 memory: 21547 grad_norm: 4.8645 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2142 loss: 1.2142 2022/10/10 08:59:35 - mmengine - INFO - Epoch(train) [81][460/940] lr: 1.0000e-04 eta: 2:34:59 time: 0.4897 data_time: 0.0266 memory: 21547 grad_norm: 4.7868 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1428 loss: 1.1428 2022/10/10 08:59:45 - mmengine - INFO - Epoch(train) [81][480/940] lr: 1.0000e-04 eta: 2:34:49 time: 0.5046 data_time: 0.0361 memory: 21547 grad_norm: 4.7855 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1499 loss: 1.1499 2022/10/10 08:59:54 - mmengine - INFO - Epoch(train) [81][500/940] lr: 1.0000e-04 eta: 2:34:39 time: 0.4879 data_time: 0.0294 memory: 21547 grad_norm: 4.7948 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1884 loss: 1.1884 2022/10/10 09:00:05 - mmengine - INFO - Epoch(train) [81][520/940] lr: 1.0000e-04 eta: 2:34:29 time: 0.5221 data_time: 0.0283 memory: 21547 grad_norm: 4.8111 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1084 loss: 1.1084 2022/10/10 09:00:15 - mmengine - INFO - Epoch(train) [81][540/940] lr: 1.0000e-04 eta: 2:34:18 time: 0.4984 data_time: 0.0263 memory: 21547 grad_norm: 4.7502 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0279 loss: 1.0279 2022/10/10 09:00:26 - mmengine - INFO - Epoch(train) [81][560/940] lr: 1.0000e-04 eta: 2:34:08 time: 0.5308 data_time: 0.0243 memory: 21547 grad_norm: 4.8010 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.1258 loss: 1.1258 2022/10/10 09:00:35 - mmengine - INFO - Epoch(train) [81][580/940] lr: 1.0000e-04 eta: 2:33:58 time: 0.4557 data_time: 0.0303 memory: 21547 grad_norm: 4.6874 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.0598 loss: 1.0598 2022/10/10 09:00:45 - mmengine - INFO - Epoch(train) [81][600/940] lr: 1.0000e-04 eta: 2:33:48 time: 0.4968 data_time: 0.0258 memory: 21547 grad_norm: 4.7835 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1545 loss: 1.1545 2022/10/10 09:00:55 - mmengine - INFO - Epoch(train) [81][620/940] lr: 1.0000e-04 eta: 2:33:38 time: 0.5032 data_time: 0.0327 memory: 21547 grad_norm: 4.8009 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2168 loss: 1.2168 2022/10/10 09:01:04 - mmengine - INFO - Epoch(train) [81][640/940] lr: 1.0000e-04 eta: 2:33:27 time: 0.4901 data_time: 0.0298 memory: 21547 grad_norm: 4.7414 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2943 loss: 1.2943 2022/10/10 09:01:14 - mmengine - INFO - Epoch(train) [81][660/940] lr: 1.0000e-04 eta: 2:33:17 time: 0.5017 data_time: 0.0308 memory: 21547 grad_norm: 4.7880 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.2632 loss: 1.2632 2022/10/10 09:01:25 - mmengine - INFO - Epoch(train) [81][680/940] lr: 1.0000e-04 eta: 2:33:07 time: 0.5285 data_time: 0.0217 memory: 21547 grad_norm: 4.8725 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1712 loss: 1.1712 2022/10/10 09:01:35 - mmengine - INFO - Epoch(train) [81][700/940] lr: 1.0000e-04 eta: 2:32:57 time: 0.5021 data_time: 0.0345 memory: 21547 grad_norm: 4.7541 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1871 loss: 1.1871 2022/10/10 09:01:44 - mmengine - INFO - Epoch(train) [81][720/940] lr: 1.0000e-04 eta: 2:32:47 time: 0.4594 data_time: 0.0266 memory: 21547 grad_norm: 4.8516 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0825 loss: 1.0825 2022/10/10 09:01:54 - mmengine - INFO - Epoch(train) [81][740/940] lr: 1.0000e-04 eta: 2:32:37 time: 0.5024 data_time: 0.0280 memory: 21547 grad_norm: 4.8443 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2025 loss: 1.2025 2022/10/10 09:02:05 - mmengine - INFO - Epoch(train) [81][760/940] lr: 1.0000e-04 eta: 2:32:27 time: 0.5467 data_time: 0.0321 memory: 21547 grad_norm: 4.8328 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2205 loss: 1.2205 2022/10/10 09:02:15 - mmengine - INFO - Epoch(train) [81][780/940] lr: 1.0000e-04 eta: 2:32:16 time: 0.5080 data_time: 0.0343 memory: 21547 grad_norm: 4.8841 top1_acc: 0.5938 top5_acc: 1.0000 loss_cls: 1.2260 loss: 1.2260 2022/10/10 09:02:26 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 09:02:26 - mmengine - INFO - Epoch(train) [81][800/940] lr: 1.0000e-04 eta: 2:32:06 time: 0.5121 data_time: 0.0281 memory: 21547 grad_norm: 4.6754 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1876 loss: 1.1876 2022/10/10 09:02:35 - mmengine - INFO - Epoch(train) [81][820/940] lr: 1.0000e-04 eta: 2:31:56 time: 0.4702 data_time: 0.0301 memory: 21547 grad_norm: 4.8129 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1533 loss: 1.1533 2022/10/10 09:02:46 - mmengine - INFO - Epoch(train) [81][840/940] lr: 1.0000e-04 eta: 2:31:46 time: 0.5465 data_time: 0.0232 memory: 21547 grad_norm: 4.8337 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1828 loss: 1.1828 2022/10/10 09:02:55 - mmengine - INFO - Epoch(train) [81][860/940] lr: 1.0000e-04 eta: 2:31:36 time: 0.4715 data_time: 0.0301 memory: 21547 grad_norm: 4.8049 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1899 loss: 1.1899 2022/10/10 09:03:06 - mmengine - INFO - Epoch(train) [81][880/940] lr: 1.0000e-04 eta: 2:31:26 time: 0.5226 data_time: 0.0312 memory: 21547 grad_norm: 4.7230 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1152 loss: 1.1152 2022/10/10 09:03:15 - mmengine - INFO - Epoch(train) [81][900/940] lr: 1.0000e-04 eta: 2:31:15 time: 0.4568 data_time: 0.0317 memory: 21547 grad_norm: 4.8072 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2032 loss: 1.2032 2022/10/10 09:03:25 - mmengine - INFO - Epoch(train) [81][920/940] lr: 1.0000e-04 eta: 2:31:05 time: 0.5091 data_time: 0.0269 memory: 21547 grad_norm: 4.7726 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1183 loss: 1.1183 2022/10/10 09:03:34 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 09:03:34 - mmengine - INFO - Epoch(train) [81][940/940] lr: 1.0000e-04 eta: 2:30:55 time: 0.4426 data_time: 0.0225 memory: 21547 grad_norm: 5.0499 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.1796 loss: 1.1796 2022/10/10 09:03:34 - mmengine - INFO - Saving checkpoint at 81 epochs 2022/10/10 09:03:48 - mmengine - INFO - Epoch(val) [81][20/78] eta: 0:00:36 time: 0.6266 data_time: 0.5218 memory: 3269 2022/10/10 09:03:56 - mmengine - INFO - Epoch(val) [81][40/78] eta: 0:00:16 time: 0.4240 data_time: 0.3199 memory: 3269 2022/10/10 09:04:07 - mmengine - INFO - Epoch(val) [81][60/78] eta: 0:00:09 time: 0.5460 data_time: 0.4391 memory: 3269 2022/10/10 09:04:16 - mmengine - INFO - Epoch(val) [81][78/78] acc/top1: 0.6796 acc/top5: 0.8720 acc/mean1: 0.6795 2022/10/10 09:04:30 - mmengine - INFO - Epoch(train) [82][20/940] lr: 1.0000e-04 eta: 2:30:45 time: 0.6932 data_time: 0.2793 memory: 21547 grad_norm: 4.7730 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1751 loss: 1.1751 2022/10/10 09:04:40 - mmengine - INFO - Epoch(train) [82][40/940] lr: 1.0000e-04 eta: 2:30:35 time: 0.4842 data_time: 0.0317 memory: 21547 grad_norm: 4.7072 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0847 loss: 1.0847 2022/10/10 09:04:50 - mmengine - INFO - Epoch(train) [82][60/940] lr: 1.0000e-04 eta: 2:30:25 time: 0.5155 data_time: 0.0653 memory: 21547 grad_norm: 5.0297 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2473 loss: 1.2473 2022/10/10 09:05:00 - mmengine - INFO - Epoch(train) [82][80/940] lr: 1.0000e-04 eta: 2:30:15 time: 0.5061 data_time: 0.0236 memory: 21547 grad_norm: 4.8773 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1838 loss: 1.1838 2022/10/10 09:05:10 - mmengine - INFO - Epoch(train) [82][100/940] lr: 1.0000e-04 eta: 2:30:05 time: 0.5128 data_time: 0.0319 memory: 21547 grad_norm: 4.7810 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1072 loss: 1.1072 2022/10/10 09:05:20 - mmengine - INFO - Epoch(train) [82][120/940] lr: 1.0000e-04 eta: 2:29:55 time: 0.5038 data_time: 0.0255 memory: 21547 grad_norm: 4.7329 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1502 loss: 1.1502 2022/10/10 09:05:31 - mmengine - INFO - Epoch(train) [82][140/940] lr: 1.0000e-04 eta: 2:29:45 time: 0.5113 data_time: 0.0345 memory: 21547 grad_norm: 4.7910 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1853 loss: 1.1853 2022/10/10 09:05:40 - mmengine - INFO - Epoch(train) [82][160/940] lr: 1.0000e-04 eta: 2:29:34 time: 0.4846 data_time: 0.0244 memory: 21547 grad_norm: 4.7195 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2332 loss: 1.2332 2022/10/10 09:05:51 - mmengine - INFO - Epoch(train) [82][180/940] lr: 1.0000e-04 eta: 2:29:24 time: 0.5529 data_time: 0.0509 memory: 21547 grad_norm: 4.7647 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1556 loss: 1.1556 2022/10/10 09:06:01 - mmengine - INFO - Epoch(train) [82][200/940] lr: 1.0000e-04 eta: 2:29:14 time: 0.4907 data_time: 0.0238 memory: 21547 grad_norm: 4.8588 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2174 loss: 1.2174 2022/10/10 09:06:12 - mmengine - INFO - Epoch(train) [82][220/940] lr: 1.0000e-04 eta: 2:29:04 time: 0.5561 data_time: 0.0280 memory: 21547 grad_norm: 4.8155 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1589 loss: 1.1589 2022/10/10 09:06:22 - mmengine - INFO - Epoch(train) [82][240/940] lr: 1.0000e-04 eta: 2:28:54 time: 0.4741 data_time: 0.0234 memory: 21547 grad_norm: 4.7827 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1571 loss: 1.1571 2022/10/10 09:06:32 - mmengine - INFO - Epoch(train) [82][260/940] lr: 1.0000e-04 eta: 2:28:44 time: 0.5324 data_time: 0.0335 memory: 21547 grad_norm: 4.8484 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.1534 loss: 1.1534 2022/10/10 09:06:42 - mmengine - INFO - Epoch(train) [82][280/940] lr: 1.0000e-04 eta: 2:28:34 time: 0.4603 data_time: 0.0232 memory: 21547 grad_norm: 4.6601 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9787 loss: 0.9787 2022/10/10 09:06:52 - mmengine - INFO - Epoch(train) [82][300/940] lr: 1.0000e-04 eta: 2:28:23 time: 0.4992 data_time: 0.0298 memory: 21547 grad_norm: 4.6972 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1725 loss: 1.1725 2022/10/10 09:07:00 - mmengine - INFO - Epoch(train) [82][320/940] lr: 1.0000e-04 eta: 2:28:13 time: 0.4468 data_time: 0.0256 memory: 21547 grad_norm: 4.8671 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.2201 loss: 1.2201 2022/10/10 09:07:12 - mmengine - INFO - Epoch(train) [82][340/940] lr: 1.0000e-04 eta: 2:28:03 time: 0.5593 data_time: 0.0342 memory: 21547 grad_norm: 4.7700 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0846 loss: 1.0846 2022/10/10 09:07:21 - mmengine - INFO - Epoch(train) [82][360/940] lr: 1.0000e-04 eta: 2:27:53 time: 0.4533 data_time: 0.0281 memory: 21547 grad_norm: 4.6711 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0912 loss: 1.0912 2022/10/10 09:07:31 - mmengine - INFO - Epoch(train) [82][380/940] lr: 1.0000e-04 eta: 2:27:43 time: 0.5064 data_time: 0.0285 memory: 21547 grad_norm: 4.7626 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2193 loss: 1.2193 2022/10/10 09:07:41 - mmengine - INFO - Epoch(train) [82][400/940] lr: 1.0000e-04 eta: 2:27:32 time: 0.4882 data_time: 0.0259 memory: 21547 grad_norm: 4.6674 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.1530 loss: 1.1530 2022/10/10 09:07:51 - mmengine - INFO - Epoch(train) [82][420/940] lr: 1.0000e-04 eta: 2:27:22 time: 0.5253 data_time: 0.0231 memory: 21547 grad_norm: 4.7874 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1978 loss: 1.1978 2022/10/10 09:08:01 - mmengine - INFO - Epoch(train) [82][440/940] lr: 1.0000e-04 eta: 2:27:12 time: 0.4927 data_time: 0.0310 memory: 21547 grad_norm: 4.7947 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0709 loss: 1.0709 2022/10/10 09:08:12 - mmengine - INFO - Epoch(train) [82][460/940] lr: 1.0000e-04 eta: 2:27:02 time: 0.5287 data_time: 0.0242 memory: 21547 grad_norm: 4.7835 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1438 loss: 1.1438 2022/10/10 09:08:21 - mmengine - INFO - Epoch(train) [82][480/940] lr: 1.0000e-04 eta: 2:26:52 time: 0.4897 data_time: 0.0291 memory: 21547 grad_norm: 4.7670 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0908 loss: 1.0908 2022/10/10 09:08:31 - mmengine - INFO - Epoch(train) [82][500/940] lr: 1.0000e-04 eta: 2:26:42 time: 0.4841 data_time: 0.0282 memory: 21547 grad_norm: 4.7578 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0869 loss: 1.0869 2022/10/10 09:08:41 - mmengine - INFO - Epoch(train) [82][520/940] lr: 1.0000e-04 eta: 2:26:31 time: 0.5074 data_time: 0.0305 memory: 21547 grad_norm: 4.7048 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0750 loss: 1.0750 2022/10/10 09:08:52 - mmengine - INFO - Epoch(train) [82][540/940] lr: 1.0000e-04 eta: 2:26:21 time: 0.5238 data_time: 0.0287 memory: 21547 grad_norm: 4.7697 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1964 loss: 1.1964 2022/10/10 09:09:02 - mmengine - INFO - Epoch(train) [82][560/940] lr: 1.0000e-04 eta: 2:26:11 time: 0.4962 data_time: 0.0263 memory: 21547 grad_norm: 4.7161 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1618 loss: 1.1618 2022/10/10 09:09:12 - mmengine - INFO - Epoch(train) [82][580/940] lr: 1.0000e-04 eta: 2:26:01 time: 0.5197 data_time: 0.0253 memory: 21547 grad_norm: 4.8924 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2222 loss: 1.2222 2022/10/10 09:09:23 - mmengine - INFO - Epoch(train) [82][600/940] lr: 1.0000e-04 eta: 2:25:51 time: 0.5419 data_time: 0.0320 memory: 21547 grad_norm: 4.8923 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.2855 loss: 1.2855 2022/10/10 09:09:33 - mmengine - INFO - Epoch(train) [82][620/940] lr: 1.0000e-04 eta: 2:25:41 time: 0.5256 data_time: 0.0321 memory: 21547 grad_norm: 4.7816 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2021 loss: 1.2021 2022/10/10 09:09:43 - mmengine - INFO - Epoch(train) [82][640/940] lr: 1.0000e-04 eta: 2:25:31 time: 0.5046 data_time: 0.0242 memory: 21547 grad_norm: 4.7514 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.3394 loss: 1.3394 2022/10/10 09:09:54 - mmengine - INFO - Epoch(train) [82][660/940] lr: 1.0000e-04 eta: 2:25:21 time: 0.5077 data_time: 0.0257 memory: 21547 grad_norm: 4.8676 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2467 loss: 1.2467 2022/10/10 09:10:03 - mmengine - INFO - Epoch(train) [82][680/940] lr: 1.0000e-04 eta: 2:25:11 time: 0.4877 data_time: 0.0288 memory: 21547 grad_norm: 4.6370 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1877 loss: 1.1877 2022/10/10 09:10:14 - mmengine - INFO - Epoch(train) [82][700/940] lr: 1.0000e-04 eta: 2:25:00 time: 0.5194 data_time: 0.0262 memory: 21547 grad_norm: 4.7176 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.1611 loss: 1.1611 2022/10/10 09:10:24 - mmengine - INFO - Epoch(train) [82][720/940] lr: 1.0000e-04 eta: 2:24:50 time: 0.4900 data_time: 0.0262 memory: 21547 grad_norm: 4.8588 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1813 loss: 1.1813 2022/10/10 09:10:34 - mmengine - INFO - Epoch(train) [82][740/940] lr: 1.0000e-04 eta: 2:24:40 time: 0.5043 data_time: 0.0299 memory: 21547 grad_norm: 4.6251 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0615 loss: 1.0615 2022/10/10 09:10:44 - mmengine - INFO - Epoch(train) [82][760/940] lr: 1.0000e-04 eta: 2:24:30 time: 0.5283 data_time: 0.0235 memory: 21547 grad_norm: 4.7713 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0505 loss: 1.0505 2022/10/10 09:10:54 - mmengine - INFO - Epoch(train) [82][780/940] lr: 1.0000e-04 eta: 2:24:20 time: 0.4709 data_time: 0.0261 memory: 21547 grad_norm: 4.7847 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.1111 loss: 1.1111 2022/10/10 09:11:04 - mmengine - INFO - Epoch(train) [82][800/940] lr: 1.0000e-04 eta: 2:24:10 time: 0.5275 data_time: 0.0249 memory: 21547 grad_norm: 4.7024 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1317 loss: 1.1317 2022/10/10 09:11:14 - mmengine - INFO - Epoch(train) [82][820/940] lr: 1.0000e-04 eta: 2:23:59 time: 0.4813 data_time: 0.0251 memory: 21547 grad_norm: 4.7545 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2282 loss: 1.2282 2022/10/10 09:11:24 - mmengine - INFO - Epoch(train) [82][840/940] lr: 1.0000e-04 eta: 2:23:49 time: 0.5097 data_time: 0.0294 memory: 21547 grad_norm: 4.8339 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2186 loss: 1.2186 2022/10/10 09:11:35 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 09:11:35 - mmengine - INFO - Epoch(train) [82][860/940] lr: 1.0000e-04 eta: 2:23:39 time: 0.5240 data_time: 0.0301 memory: 21547 grad_norm: 4.7377 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1471 loss: 1.1471 2022/10/10 09:11:44 - mmengine - INFO - Epoch(train) [82][880/940] lr: 1.0000e-04 eta: 2:23:29 time: 0.4723 data_time: 0.0310 memory: 21547 grad_norm: 4.8443 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1511 loss: 1.1511 2022/10/10 09:11:55 - mmengine - INFO - Epoch(train) [82][900/940] lr: 1.0000e-04 eta: 2:23:19 time: 0.5270 data_time: 0.0257 memory: 21547 grad_norm: 4.6309 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1769 loss: 1.1769 2022/10/10 09:12:04 - mmengine - INFO - Epoch(train) [82][920/940] lr: 1.0000e-04 eta: 2:23:09 time: 0.4758 data_time: 0.0290 memory: 21547 grad_norm: 4.7641 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1413 loss: 1.1413 2022/10/10 09:12:13 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 09:12:13 - mmengine - INFO - Epoch(train) [82][940/940] lr: 1.0000e-04 eta: 2:22:58 time: 0.4482 data_time: 0.0208 memory: 21547 grad_norm: 5.1209 top1_acc: 0.2857 top5_acc: 1.0000 loss_cls: 1.2248 loss: 1.2248 2022/10/10 09:12:25 - mmengine - INFO - Epoch(val) [82][20/78] eta: 0:00:35 time: 0.6059 data_time: 0.4947 memory: 3269 2022/10/10 09:12:34 - mmengine - INFO - Epoch(val) [82][40/78] eta: 0:00:16 time: 0.4223 data_time: 0.3152 memory: 3269 2022/10/10 09:12:45 - mmengine - INFO - Epoch(val) [82][60/78] eta: 0:00:10 time: 0.5623 data_time: 0.4556 memory: 3269 2022/10/10 09:12:55 - mmengine - INFO - Epoch(val) [82][78/78] acc/top1: 0.6799 acc/top5: 0.8708 acc/mean1: 0.6798 2022/10/10 09:12:55 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_78.pth is removed 2022/10/10 09:12:55 - mmengine - INFO - The best checkpoint with 0.6799 acc/top1 at 82 epoch is saved to best_acc/top1_epoch_82.pth. 2022/10/10 09:13:09 - mmengine - INFO - Epoch(train) [83][20/940] lr: 1.0000e-04 eta: 2:22:49 time: 0.6633 data_time: 0.2857 memory: 21547 grad_norm: 4.8297 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2485 loss: 1.2485 2022/10/10 09:13:19 - mmengine - INFO - Epoch(train) [83][40/940] lr: 1.0000e-04 eta: 2:22:39 time: 0.5123 data_time: 0.1176 memory: 21547 grad_norm: 4.7743 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1418 loss: 1.1418 2022/10/10 09:13:29 - mmengine - INFO - Epoch(train) [83][60/940] lr: 1.0000e-04 eta: 2:22:29 time: 0.5323 data_time: 0.0784 memory: 21547 grad_norm: 4.7167 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2266 loss: 1.2266 2022/10/10 09:13:39 - mmengine - INFO - Epoch(train) [83][80/940] lr: 1.0000e-04 eta: 2:22:18 time: 0.4627 data_time: 0.0343 memory: 21547 grad_norm: 4.6714 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1075 loss: 1.1075 2022/10/10 09:13:49 - mmengine - INFO - Epoch(train) [83][100/940] lr: 1.0000e-04 eta: 2:22:08 time: 0.5358 data_time: 0.0598 memory: 21547 grad_norm: 4.8596 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1542 loss: 1.1542 2022/10/10 09:13:59 - mmengine - INFO - Epoch(train) [83][120/940] lr: 1.0000e-04 eta: 2:21:58 time: 0.4776 data_time: 0.0482 memory: 21547 grad_norm: 4.7215 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0844 loss: 1.0844 2022/10/10 09:14:09 - mmengine - INFO - Epoch(train) [83][140/940] lr: 1.0000e-04 eta: 2:21:48 time: 0.5092 data_time: 0.0858 memory: 21547 grad_norm: 4.7937 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2400 loss: 1.2400 2022/10/10 09:14:20 - mmengine - INFO - Epoch(train) [83][160/940] lr: 1.0000e-04 eta: 2:21:38 time: 0.5330 data_time: 0.1334 memory: 21547 grad_norm: 4.7237 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.2719 loss: 1.2719 2022/10/10 09:14:29 - mmengine - INFO - Epoch(train) [83][180/940] lr: 1.0000e-04 eta: 2:21:28 time: 0.4738 data_time: 0.0724 memory: 21547 grad_norm: 4.7750 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.1949 loss: 1.1949 2022/10/10 09:14:40 - mmengine - INFO - Epoch(train) [83][200/940] lr: 1.0000e-04 eta: 2:21:17 time: 0.5099 data_time: 0.1243 memory: 21547 grad_norm: 4.6946 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0917 loss: 1.0917 2022/10/10 09:14:49 - mmengine - INFO - Epoch(train) [83][220/940] lr: 1.0000e-04 eta: 2:21:07 time: 0.4754 data_time: 0.0494 memory: 21547 grad_norm: 4.7410 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0585 loss: 1.0585 2022/10/10 09:14:59 - mmengine - INFO - Epoch(train) [83][240/940] lr: 1.0000e-04 eta: 2:20:57 time: 0.5083 data_time: 0.0332 memory: 21547 grad_norm: 4.7483 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2649 loss: 1.2649 2022/10/10 09:15:10 - mmengine - INFO - Epoch(train) [83][260/940] lr: 1.0000e-04 eta: 2:20:47 time: 0.5360 data_time: 0.0249 memory: 21547 grad_norm: 4.7961 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1756 loss: 1.1756 2022/10/10 09:15:20 - mmengine - INFO - Epoch(train) [83][280/940] lr: 1.0000e-04 eta: 2:20:37 time: 0.5236 data_time: 0.0822 memory: 21547 grad_norm: 4.8297 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2400 loss: 1.2400 2022/10/10 09:15:31 - mmengine - INFO - Epoch(train) [83][300/940] lr: 1.0000e-04 eta: 2:20:27 time: 0.5314 data_time: 0.0695 memory: 21547 grad_norm: 4.7892 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.2585 loss: 1.2585 2022/10/10 09:15:41 - mmengine - INFO - Epoch(train) [83][320/940] lr: 1.0000e-04 eta: 2:20:17 time: 0.4780 data_time: 0.0300 memory: 21547 grad_norm: 4.8135 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0935 loss: 1.0935 2022/10/10 09:15:51 - mmengine - INFO - Epoch(train) [83][340/940] lr: 1.0000e-04 eta: 2:20:07 time: 0.5132 data_time: 0.0277 memory: 21547 grad_norm: 4.7893 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1035 loss: 1.1035 2022/10/10 09:16:01 - mmengine - INFO - Epoch(train) [83][360/940] lr: 1.0000e-04 eta: 2:19:56 time: 0.4893 data_time: 0.0343 memory: 21547 grad_norm: 4.8283 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2401 loss: 1.2401 2022/10/10 09:16:11 - mmengine - INFO - Epoch(train) [83][380/940] lr: 1.0000e-04 eta: 2:19:46 time: 0.5177 data_time: 0.0255 memory: 21547 grad_norm: 4.8608 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1300 loss: 1.1300 2022/10/10 09:16:21 - mmengine - INFO - Epoch(train) [83][400/940] lr: 1.0000e-04 eta: 2:19:36 time: 0.4791 data_time: 0.0301 memory: 21547 grad_norm: 4.7122 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1153 loss: 1.1153 2022/10/10 09:16:31 - mmengine - INFO - Epoch(train) [83][420/940] lr: 1.0000e-04 eta: 2:19:26 time: 0.5248 data_time: 0.0305 memory: 21547 grad_norm: 4.7466 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2096 loss: 1.2096 2022/10/10 09:16:41 - mmengine - INFO - Epoch(train) [83][440/940] lr: 1.0000e-04 eta: 2:19:16 time: 0.4956 data_time: 0.0266 memory: 21547 grad_norm: 4.7754 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1988 loss: 1.1988 2022/10/10 09:16:52 - mmengine - INFO - Epoch(train) [83][460/940] lr: 1.0000e-04 eta: 2:19:06 time: 0.5242 data_time: 0.0257 memory: 21547 grad_norm: 4.8051 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2064 loss: 1.2064 2022/10/10 09:17:01 - mmengine - INFO - Epoch(train) [83][480/940] lr: 1.0000e-04 eta: 2:18:55 time: 0.4787 data_time: 0.0289 memory: 21547 grad_norm: 4.7433 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.1814 loss: 1.1814 2022/10/10 09:17:11 - mmengine - INFO - Epoch(train) [83][500/940] lr: 1.0000e-04 eta: 2:18:45 time: 0.4908 data_time: 0.0280 memory: 21547 grad_norm: 4.8456 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1490 loss: 1.1490 2022/10/10 09:17:22 - mmengine - INFO - Epoch(train) [83][520/940] lr: 1.0000e-04 eta: 2:18:35 time: 0.5321 data_time: 0.0275 memory: 21547 grad_norm: 4.7562 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2761 loss: 1.2761 2022/10/10 09:17:32 - mmengine - INFO - Epoch(train) [83][540/940] lr: 1.0000e-04 eta: 2:18:25 time: 0.5007 data_time: 0.0261 memory: 21547 grad_norm: 4.7836 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1989 loss: 1.1989 2022/10/10 09:17:41 - mmengine - INFO - Epoch(train) [83][560/940] lr: 1.0000e-04 eta: 2:18:15 time: 0.4834 data_time: 0.0248 memory: 21547 grad_norm: 4.8956 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2177 loss: 1.2177 2022/10/10 09:17:52 - mmengine - INFO - Epoch(train) [83][580/940] lr: 1.0000e-04 eta: 2:18:05 time: 0.5212 data_time: 0.0283 memory: 21547 grad_norm: 4.6749 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1042 loss: 1.1042 2022/10/10 09:18:01 - mmengine - INFO - Epoch(train) [83][600/940] lr: 1.0000e-04 eta: 2:17:54 time: 0.4699 data_time: 0.0299 memory: 21547 grad_norm: 4.7692 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1452 loss: 1.1452 2022/10/10 09:18:12 - mmengine - INFO - Epoch(train) [83][620/940] lr: 1.0000e-04 eta: 2:17:44 time: 0.5553 data_time: 0.0319 memory: 21547 grad_norm: 4.7595 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.2731 loss: 1.2731 2022/10/10 09:18:22 - mmengine - INFO - Epoch(train) [83][640/940] lr: 1.0000e-04 eta: 2:17:34 time: 0.5121 data_time: 0.0264 memory: 21547 grad_norm: 4.7483 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2633 loss: 1.2633 2022/10/10 09:18:34 - mmengine - INFO - Epoch(train) [83][660/940] lr: 1.0000e-04 eta: 2:17:24 time: 0.5538 data_time: 0.0316 memory: 21547 grad_norm: 4.7988 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2051 loss: 1.2051 2022/10/10 09:18:43 - mmengine - INFO - Epoch(train) [83][680/940] lr: 1.0000e-04 eta: 2:17:14 time: 0.4665 data_time: 0.0249 memory: 21547 grad_norm: 4.7204 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1747 loss: 1.1747 2022/10/10 09:18:54 - mmengine - INFO - Epoch(train) [83][700/940] lr: 1.0000e-04 eta: 2:17:04 time: 0.5372 data_time: 0.0284 memory: 21547 grad_norm: 4.7123 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0971 loss: 1.0971 2022/10/10 09:19:03 - mmengine - INFO - Epoch(train) [83][720/940] lr: 1.0000e-04 eta: 2:16:54 time: 0.4858 data_time: 0.0325 memory: 21547 grad_norm: 4.8430 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2396 loss: 1.2396 2022/10/10 09:19:14 - mmengine - INFO - Epoch(train) [83][740/940] lr: 1.0000e-04 eta: 2:16:44 time: 0.5231 data_time: 0.0258 memory: 21547 grad_norm: 4.8339 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1573 loss: 1.1573 2022/10/10 09:19:23 - mmengine - INFO - Epoch(train) [83][760/940] lr: 1.0000e-04 eta: 2:16:33 time: 0.4822 data_time: 0.0318 memory: 21547 grad_norm: 4.6390 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.0640 loss: 1.0640 2022/10/10 09:19:34 - mmengine - INFO - Epoch(train) [83][780/940] lr: 1.0000e-04 eta: 2:16:23 time: 0.5324 data_time: 0.0267 memory: 21547 grad_norm: 4.7451 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2252 loss: 1.2252 2022/10/10 09:19:43 - mmengine - INFO - Epoch(train) [83][800/940] lr: 1.0000e-04 eta: 2:16:13 time: 0.4716 data_time: 0.0260 memory: 21547 grad_norm: 4.8278 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2253 loss: 1.2253 2022/10/10 09:19:54 - mmengine - INFO - Epoch(train) [83][820/940] lr: 1.0000e-04 eta: 2:16:03 time: 0.5125 data_time: 0.0241 memory: 21547 grad_norm: 4.7359 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0264 loss: 1.0264 2022/10/10 09:20:03 - mmengine - INFO - Epoch(train) [83][840/940] lr: 1.0000e-04 eta: 2:15:53 time: 0.4649 data_time: 0.0244 memory: 21547 grad_norm: 4.8611 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1813 loss: 1.1813 2022/10/10 09:20:13 - mmengine - INFO - Epoch(train) [83][860/940] lr: 1.0000e-04 eta: 2:15:42 time: 0.4816 data_time: 0.0261 memory: 21547 grad_norm: 4.7455 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1528 loss: 1.1528 2022/10/10 09:20:23 - mmengine - INFO - Epoch(train) [83][880/940] lr: 1.0000e-04 eta: 2:15:32 time: 0.5055 data_time: 0.0318 memory: 21547 grad_norm: 4.7413 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2458 loss: 1.2458 2022/10/10 09:20:33 - mmengine - INFO - Epoch(train) [83][900/940] lr: 1.0000e-04 eta: 2:15:22 time: 0.5165 data_time: 0.0289 memory: 21547 grad_norm: 4.8294 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3286 loss: 1.3286 2022/10/10 09:20:43 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 09:20:43 - mmengine - INFO - Epoch(train) [83][920/940] lr: 1.0000e-04 eta: 2:15:12 time: 0.4786 data_time: 0.0315 memory: 21547 grad_norm: 4.8207 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.1729 loss: 1.1729 2022/10/10 09:20:51 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 09:20:51 - mmengine - INFO - Epoch(train) [83][940/940] lr: 1.0000e-04 eta: 2:15:02 time: 0.4367 data_time: 0.0236 memory: 21547 grad_norm: 5.0628 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.3042 loss: 1.3042 2022/10/10 09:21:04 - mmengine - INFO - Epoch(val) [83][20/78] eta: 0:00:35 time: 0.6109 data_time: 0.4996 memory: 3269 2022/10/10 09:21:12 - mmengine - INFO - Epoch(val) [83][40/78] eta: 0:00:16 time: 0.4239 data_time: 0.3159 memory: 3269 2022/10/10 09:21:23 - mmengine - INFO - Epoch(val) [83][60/78] eta: 0:00:09 time: 0.5444 data_time: 0.4387 memory: 3269 2022/10/10 09:21:33 - mmengine - INFO - Epoch(val) [83][78/78] acc/top1: 0.6805 acc/top5: 0.8713 acc/mean1: 0.6805 2022/10/10 09:21:33 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_82.pth is removed 2022/10/10 09:21:34 - mmengine - INFO - The best checkpoint with 0.6805 acc/top1 at 83 epoch is saved to best_acc/top1_epoch_83.pth. 2022/10/10 09:21:48 - mmengine - INFO - Epoch(train) [84][20/940] lr: 1.0000e-04 eta: 2:14:52 time: 0.6853 data_time: 0.3311 memory: 21547 grad_norm: 4.7574 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.1723 loss: 1.1723 2022/10/10 09:21:57 - mmengine - INFO - Epoch(train) [84][40/940] lr: 1.0000e-04 eta: 2:14:42 time: 0.4860 data_time: 0.1139 memory: 21547 grad_norm: 4.7813 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.1639 loss: 1.1639 2022/10/10 09:22:08 - mmengine - INFO - Epoch(train) [84][60/940] lr: 1.0000e-04 eta: 2:14:32 time: 0.5230 data_time: 0.1203 memory: 21547 grad_norm: 4.8222 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1630 loss: 1.1630 2022/10/10 09:22:17 - mmengine - INFO - Epoch(train) [84][80/940] lr: 1.0000e-04 eta: 2:14:22 time: 0.4705 data_time: 0.0377 memory: 21547 grad_norm: 4.8149 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2051 loss: 1.2051 2022/10/10 09:22:28 - mmengine - INFO - Epoch(train) [84][100/940] lr: 1.0000e-04 eta: 2:14:11 time: 0.5334 data_time: 0.0386 memory: 21547 grad_norm: 4.8357 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2438 loss: 1.2438 2022/10/10 09:22:38 - mmengine - INFO - Epoch(train) [84][120/940] lr: 1.0000e-04 eta: 2:14:01 time: 0.5214 data_time: 0.0283 memory: 21547 grad_norm: 4.8065 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1914 loss: 1.1914 2022/10/10 09:22:49 - mmengine - INFO - Epoch(train) [84][140/940] lr: 1.0000e-04 eta: 2:13:51 time: 0.5164 data_time: 0.0298 memory: 21547 grad_norm: 4.8515 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2194 loss: 1.2194 2022/10/10 09:22:58 - mmengine - INFO - Epoch(train) [84][160/940] lr: 1.0000e-04 eta: 2:13:41 time: 0.4746 data_time: 0.0296 memory: 21547 grad_norm: 4.7996 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2224 loss: 1.2224 2022/10/10 09:23:08 - mmengine - INFO - Epoch(train) [84][180/940] lr: 1.0000e-04 eta: 2:13:31 time: 0.5223 data_time: 0.0286 memory: 21547 grad_norm: 4.8727 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1870 loss: 1.1870 2022/10/10 09:23:18 - mmengine - INFO - Epoch(train) [84][200/940] lr: 1.0000e-04 eta: 2:13:21 time: 0.4831 data_time: 0.0348 memory: 21547 grad_norm: 4.6480 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1983 loss: 1.1983 2022/10/10 09:23:29 - mmengine - INFO - Epoch(train) [84][220/940] lr: 1.0000e-04 eta: 2:13:11 time: 0.5177 data_time: 0.0288 memory: 21547 grad_norm: 4.7054 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0763 loss: 1.0763 2022/10/10 09:23:38 - mmengine - INFO - Epoch(train) [84][240/940] lr: 1.0000e-04 eta: 2:13:00 time: 0.4774 data_time: 0.0291 memory: 21547 grad_norm: 4.8493 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1876 loss: 1.1876 2022/10/10 09:23:49 - mmengine - INFO - Epoch(train) [84][260/940] lr: 1.0000e-04 eta: 2:12:50 time: 0.5473 data_time: 0.0361 memory: 21547 grad_norm: 4.7477 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0839 loss: 1.0839 2022/10/10 09:23:59 - mmengine - INFO - Epoch(train) [84][280/940] lr: 1.0000e-04 eta: 2:12:40 time: 0.4896 data_time: 0.0315 memory: 21547 grad_norm: 4.8896 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2042 loss: 1.2042 2022/10/10 09:24:09 - mmengine - INFO - Epoch(train) [84][300/940] lr: 1.0000e-04 eta: 2:12:30 time: 0.5195 data_time: 0.0312 memory: 21547 grad_norm: 4.8059 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0700 loss: 1.0700 2022/10/10 09:24:18 - mmengine - INFO - Epoch(train) [84][320/940] lr: 1.0000e-04 eta: 2:12:20 time: 0.4559 data_time: 0.0318 memory: 21547 grad_norm: 4.7106 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1993 loss: 1.1993 2022/10/10 09:24:29 - mmengine - INFO - Epoch(train) [84][340/940] lr: 1.0000e-04 eta: 2:12:10 time: 0.5403 data_time: 0.0289 memory: 21547 grad_norm: 4.8020 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1414 loss: 1.1414 2022/10/10 09:24:39 - mmengine - INFO - Epoch(train) [84][360/940] lr: 1.0000e-04 eta: 2:11:59 time: 0.4896 data_time: 0.0294 memory: 21547 grad_norm: 4.7004 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1081 loss: 1.1081 2022/10/10 09:24:49 - mmengine - INFO - Epoch(train) [84][380/940] lr: 1.0000e-04 eta: 2:11:49 time: 0.4915 data_time: 0.0264 memory: 21547 grad_norm: 4.8541 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2755 loss: 1.2755 2022/10/10 09:24:59 - mmengine - INFO - Epoch(train) [84][400/940] lr: 1.0000e-04 eta: 2:11:39 time: 0.4918 data_time: 0.0302 memory: 21547 grad_norm: 4.9282 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1697 loss: 1.1697 2022/10/10 09:25:09 - mmengine - INFO - Epoch(train) [84][420/940] lr: 1.0000e-04 eta: 2:11:29 time: 0.5412 data_time: 0.0305 memory: 21547 grad_norm: 4.7279 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0871 loss: 1.0871 2022/10/10 09:25:20 - mmengine - INFO - Epoch(train) [84][440/940] lr: 1.0000e-04 eta: 2:11:19 time: 0.5081 data_time: 0.0308 memory: 21547 grad_norm: 4.8313 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1017 loss: 1.1017 2022/10/10 09:25:29 - mmengine - INFO - Epoch(train) [84][460/940] lr: 1.0000e-04 eta: 2:11:09 time: 0.4884 data_time: 0.0255 memory: 21547 grad_norm: 4.8447 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1474 loss: 1.1474 2022/10/10 09:25:38 - mmengine - INFO - Epoch(train) [84][480/940] lr: 1.0000e-04 eta: 2:10:58 time: 0.4458 data_time: 0.0302 memory: 21547 grad_norm: 4.7861 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1505 loss: 1.1505 2022/10/10 09:25:49 - mmengine - INFO - Epoch(train) [84][500/940] lr: 1.0000e-04 eta: 2:10:48 time: 0.5447 data_time: 0.0309 memory: 21547 grad_norm: 4.7197 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2796 loss: 1.2796 2022/10/10 09:25:59 - mmengine - INFO - Epoch(train) [84][520/940] lr: 1.0000e-04 eta: 2:10:38 time: 0.5031 data_time: 0.0279 memory: 21547 grad_norm: 4.7825 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2347 loss: 1.2347 2022/10/10 09:26:09 - mmengine - INFO - Epoch(train) [84][540/940] lr: 1.0000e-04 eta: 2:10:28 time: 0.4779 data_time: 0.0327 memory: 21547 grad_norm: 4.7787 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2054 loss: 1.2054 2022/10/10 09:26:19 - mmengine - INFO - Epoch(train) [84][560/940] lr: 1.0000e-04 eta: 2:10:18 time: 0.4914 data_time: 0.0248 memory: 21547 grad_norm: 4.7714 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0997 loss: 1.0997 2022/10/10 09:26:29 - mmengine - INFO - Epoch(train) [84][580/940] lr: 1.0000e-04 eta: 2:10:08 time: 0.5141 data_time: 0.0276 memory: 21547 grad_norm: 4.7690 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1608 loss: 1.1608 2022/10/10 09:26:40 - mmengine - INFO - Epoch(train) [84][600/940] lr: 1.0000e-04 eta: 2:09:58 time: 0.5633 data_time: 0.0290 memory: 21547 grad_norm: 4.8699 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2958 loss: 1.2958 2022/10/10 09:26:50 - mmengine - INFO - Epoch(train) [84][620/940] lr: 1.0000e-04 eta: 2:09:47 time: 0.4797 data_time: 0.0303 memory: 21547 grad_norm: 4.8396 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0946 loss: 1.0946 2022/10/10 09:27:01 - mmengine - INFO - Epoch(train) [84][640/940] lr: 1.0000e-04 eta: 2:09:37 time: 0.5373 data_time: 0.0264 memory: 21547 grad_norm: 4.7173 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1151 loss: 1.1151 2022/10/10 09:27:11 - mmengine - INFO - Epoch(train) [84][660/940] lr: 1.0000e-04 eta: 2:09:27 time: 0.5120 data_time: 0.0279 memory: 21547 grad_norm: 4.7156 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1384 loss: 1.1384 2022/10/10 09:27:20 - mmengine - INFO - Epoch(train) [84][680/940] lr: 1.0000e-04 eta: 2:09:17 time: 0.4602 data_time: 0.0261 memory: 21547 grad_norm: 4.8354 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1687 loss: 1.1687 2022/10/10 09:27:30 - mmengine - INFO - Epoch(train) [84][700/940] lr: 1.0000e-04 eta: 2:09:07 time: 0.4895 data_time: 0.0245 memory: 21547 grad_norm: 4.8963 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1574 loss: 1.1574 2022/10/10 09:27:40 - mmengine - INFO - Epoch(train) [84][720/940] lr: 1.0000e-04 eta: 2:08:57 time: 0.4936 data_time: 0.0304 memory: 21547 grad_norm: 4.7217 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.1062 loss: 1.1062 2022/10/10 09:27:50 - mmengine - INFO - Epoch(train) [84][740/940] lr: 1.0000e-04 eta: 2:08:46 time: 0.4986 data_time: 0.0247 memory: 21547 grad_norm: 4.7002 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2651 loss: 1.2651 2022/10/10 09:28:00 - mmengine - INFO - Epoch(train) [84][760/940] lr: 1.0000e-04 eta: 2:08:36 time: 0.5160 data_time: 0.0346 memory: 21547 grad_norm: 4.8140 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.2084 loss: 1.2084 2022/10/10 09:28:10 - mmengine - INFO - Epoch(train) [84][780/940] lr: 1.0000e-04 eta: 2:08:26 time: 0.4982 data_time: 0.0309 memory: 21547 grad_norm: 4.8207 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1880 loss: 1.1880 2022/10/10 09:28:21 - mmengine - INFO - Epoch(train) [84][800/940] lr: 1.0000e-04 eta: 2:08:16 time: 0.5537 data_time: 0.0263 memory: 21547 grad_norm: 4.8504 top1_acc: 0.6562 top5_acc: 1.0000 loss_cls: 1.2547 loss: 1.2547 2022/10/10 09:28:31 - mmengine - INFO - Epoch(train) [84][820/940] lr: 1.0000e-04 eta: 2:08:06 time: 0.4871 data_time: 0.0275 memory: 21547 grad_norm: 4.8536 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1253 loss: 1.1253 2022/10/10 09:28:41 - mmengine - INFO - Epoch(train) [84][840/940] lr: 1.0000e-04 eta: 2:07:56 time: 0.5350 data_time: 0.0257 memory: 21547 grad_norm: 4.8421 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2929 loss: 1.2929 2022/10/10 09:28:51 - mmengine - INFO - Epoch(train) [84][860/940] lr: 1.0000e-04 eta: 2:07:46 time: 0.4653 data_time: 0.0281 memory: 21547 grad_norm: 4.7731 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1580 loss: 1.1580 2022/10/10 09:29:01 - mmengine - INFO - Epoch(train) [84][880/940] lr: 1.0000e-04 eta: 2:07:36 time: 0.5340 data_time: 0.0317 memory: 21547 grad_norm: 4.8732 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1392 loss: 1.1392 2022/10/10 09:29:12 - mmengine - INFO - Epoch(train) [84][900/940] lr: 1.0000e-04 eta: 2:07:25 time: 0.5106 data_time: 0.0269 memory: 21547 grad_norm: 4.7927 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1034 loss: 1.1034 2022/10/10 09:29:22 - mmengine - INFO - Epoch(train) [84][920/940] lr: 1.0000e-04 eta: 2:07:15 time: 0.5337 data_time: 0.0258 memory: 21547 grad_norm: 4.8214 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1945 loss: 1.1945 2022/10/10 09:29:31 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 09:29:31 - mmengine - INFO - Epoch(train) [84][940/940] lr: 1.0000e-04 eta: 2:07:05 time: 0.4375 data_time: 0.0273 memory: 21547 grad_norm: 5.0319 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.1723 loss: 1.1723 2022/10/10 09:29:31 - mmengine - INFO - Saving checkpoint at 84 epochs 2022/10/10 09:29:44 - mmengine - INFO - Epoch(val) [84][20/78] eta: 0:00:35 time: 0.6107 data_time: 0.5042 memory: 3269 2022/10/10 09:29:53 - mmengine - INFO - Epoch(val) [84][40/78] eta: 0:00:16 time: 0.4247 data_time: 0.3199 memory: 3269 2022/10/10 09:30:04 - mmengine - INFO - Epoch(val) [84][60/78] eta: 0:00:10 time: 0.5561 data_time: 0.4519 memory: 3269 2022/10/10 09:30:13 - mmengine - INFO - Epoch(val) [84][78/78] acc/top1: 0.6792 acc/top5: 0.8716 acc/mean1: 0.6791 2022/10/10 09:30:27 - mmengine - INFO - Epoch(train) [85][20/940] lr: 1.0000e-04 eta: 2:06:56 time: 0.7162 data_time: 0.2228 memory: 21547 grad_norm: 4.8130 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2343 loss: 1.2343 2022/10/10 09:30:37 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 09:30:37 - mmengine - INFO - Epoch(train) [85][40/940] lr: 1.0000e-04 eta: 2:06:45 time: 0.4760 data_time: 0.0264 memory: 21547 grad_norm: 4.8366 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0788 loss: 1.0788 2022/10/10 09:30:48 - mmengine - INFO - Epoch(train) [85][60/940] lr: 1.0000e-04 eta: 2:06:35 time: 0.5481 data_time: 0.0349 memory: 21547 grad_norm: 4.8053 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2068 loss: 1.2068 2022/10/10 09:30:58 - mmengine - INFO - Epoch(train) [85][80/940] lr: 1.0000e-04 eta: 2:06:25 time: 0.5122 data_time: 0.0254 memory: 21547 grad_norm: 4.6968 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1468 loss: 1.1468 2022/10/10 09:31:09 - mmengine - INFO - Epoch(train) [85][100/940] lr: 1.0000e-04 eta: 2:06:15 time: 0.5271 data_time: 0.0640 memory: 21547 grad_norm: 4.8030 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1871 loss: 1.1871 2022/10/10 09:31:18 - mmengine - INFO - Epoch(train) [85][120/940] lr: 1.0000e-04 eta: 2:06:05 time: 0.4793 data_time: 0.0356 memory: 21547 grad_norm: 4.8341 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1324 loss: 1.1324 2022/10/10 09:31:29 - mmengine - INFO - Epoch(train) [85][140/940] lr: 1.0000e-04 eta: 2:05:55 time: 0.5223 data_time: 0.0292 memory: 21547 grad_norm: 4.9360 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2575 loss: 1.2575 2022/10/10 09:31:39 - mmengine - INFO - Epoch(train) [85][160/940] lr: 1.0000e-04 eta: 2:05:45 time: 0.5049 data_time: 0.0311 memory: 21547 grad_norm: 4.7235 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.0865 loss: 1.0865 2022/10/10 09:31:49 - mmengine - INFO - Epoch(train) [85][180/940] lr: 1.0000e-04 eta: 2:05:35 time: 0.5025 data_time: 0.0273 memory: 21547 grad_norm: 4.9173 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2222 loss: 1.2222 2022/10/10 09:31:59 - mmengine - INFO - Epoch(train) [85][200/940] lr: 1.0000e-04 eta: 2:05:24 time: 0.4906 data_time: 0.0282 memory: 21547 grad_norm: 4.7488 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2521 loss: 1.2521 2022/10/10 09:32:10 - mmengine - INFO - Epoch(train) [85][220/940] lr: 1.0000e-04 eta: 2:05:14 time: 0.5535 data_time: 0.0293 memory: 21547 grad_norm: 4.8137 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2284 loss: 1.2284 2022/10/10 09:32:18 - mmengine - INFO - Epoch(train) [85][240/940] lr: 1.0000e-04 eta: 2:05:04 time: 0.4342 data_time: 0.0281 memory: 21547 grad_norm: 4.8059 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0847 loss: 1.0847 2022/10/10 09:32:29 - mmengine - INFO - Epoch(train) [85][260/940] lr: 1.0000e-04 eta: 2:04:54 time: 0.5160 data_time: 0.0278 memory: 21547 grad_norm: 4.7969 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0993 loss: 1.0993 2022/10/10 09:32:38 - mmengine - INFO - Epoch(train) [85][280/940] lr: 1.0000e-04 eta: 2:04:44 time: 0.4843 data_time: 0.0292 memory: 21547 grad_norm: 4.7819 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2013 loss: 1.2013 2022/10/10 09:32:49 - mmengine - INFO - Epoch(train) [85][300/940] lr: 1.0000e-04 eta: 2:04:34 time: 0.5497 data_time: 0.0278 memory: 21547 grad_norm: 4.8460 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1046 loss: 1.1046 2022/10/10 09:32:59 - mmengine - INFO - Epoch(train) [85][320/940] lr: 1.0000e-04 eta: 2:04:23 time: 0.4731 data_time: 0.0327 memory: 21547 grad_norm: 4.7973 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0948 loss: 1.0948 2022/10/10 09:33:09 - mmengine - INFO - Epoch(train) [85][340/940] lr: 1.0000e-04 eta: 2:04:13 time: 0.4874 data_time: 0.0274 memory: 21547 grad_norm: 4.7975 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.1452 loss: 1.1452 2022/10/10 09:33:19 - mmengine - INFO - Epoch(train) [85][360/940] lr: 1.0000e-04 eta: 2:04:03 time: 0.5108 data_time: 0.0279 memory: 21547 grad_norm: 4.8328 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2221 loss: 1.2221 2022/10/10 09:33:29 - mmengine - INFO - Epoch(train) [85][380/940] lr: 1.0000e-04 eta: 2:03:53 time: 0.5063 data_time: 0.0284 memory: 21547 grad_norm: 4.7713 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2095 loss: 1.2095 2022/10/10 09:33:38 - mmengine - INFO - Epoch(train) [85][400/940] lr: 1.0000e-04 eta: 2:03:43 time: 0.4721 data_time: 0.0279 memory: 21547 grad_norm: 4.7774 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1574 loss: 1.1574 2022/10/10 09:33:48 - mmengine - INFO - Epoch(train) [85][420/940] lr: 1.0000e-04 eta: 2:03:33 time: 0.5065 data_time: 0.0256 memory: 21547 grad_norm: 4.7938 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0629 loss: 1.0629 2022/10/10 09:33:59 - mmengine - INFO - Epoch(train) [85][440/940] lr: 1.0000e-04 eta: 2:03:23 time: 0.5376 data_time: 0.0293 memory: 21547 grad_norm: 4.7677 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1183 loss: 1.1183 2022/10/10 09:34:10 - mmengine - INFO - Epoch(train) [85][460/940] lr: 1.0000e-04 eta: 2:03:12 time: 0.5157 data_time: 0.0341 memory: 21547 grad_norm: 4.7518 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0947 loss: 1.0947 2022/10/10 09:34:20 - mmengine - INFO - Epoch(train) [85][480/940] lr: 1.0000e-04 eta: 2:03:02 time: 0.5145 data_time: 0.0270 memory: 21547 grad_norm: 4.7363 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2572 loss: 1.2572 2022/10/10 09:34:30 - mmengine - INFO - Epoch(train) [85][500/940] lr: 1.0000e-04 eta: 2:02:52 time: 0.5107 data_time: 0.0247 memory: 21547 grad_norm: 4.8565 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2705 loss: 1.2705 2022/10/10 09:34:40 - mmengine - INFO - Epoch(train) [85][520/940] lr: 1.0000e-04 eta: 2:02:42 time: 0.5198 data_time: 0.0276 memory: 21547 grad_norm: 4.8447 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0022 loss: 1.0022 2022/10/10 09:34:49 - mmengine - INFO - Epoch(train) [85][540/940] lr: 1.0000e-04 eta: 2:02:32 time: 0.4476 data_time: 0.0248 memory: 21547 grad_norm: 4.8592 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.2905 loss: 1.2905 2022/10/10 09:35:00 - mmengine - INFO - Epoch(train) [85][560/940] lr: 1.0000e-04 eta: 2:02:22 time: 0.5219 data_time: 0.0289 memory: 21547 grad_norm: 4.7779 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1168 loss: 1.1168 2022/10/10 09:35:09 - mmengine - INFO - Epoch(train) [85][580/940] lr: 1.0000e-04 eta: 2:02:11 time: 0.4802 data_time: 0.0245 memory: 21547 grad_norm: 4.7283 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1126 loss: 1.1126 2022/10/10 09:35:20 - mmengine - INFO - Epoch(train) [85][600/940] lr: 1.0000e-04 eta: 2:02:01 time: 0.5060 data_time: 0.0260 memory: 21547 grad_norm: 4.7726 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2228 loss: 1.2228 2022/10/10 09:35:30 - mmengine - INFO - Epoch(train) [85][620/940] lr: 1.0000e-04 eta: 2:01:51 time: 0.5057 data_time: 0.0280 memory: 21547 grad_norm: 4.7211 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1879 loss: 1.1879 2022/10/10 09:35:39 - mmengine - INFO - Epoch(train) [85][640/940] lr: 1.0000e-04 eta: 2:01:41 time: 0.4817 data_time: 0.0262 memory: 21547 grad_norm: 4.6910 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1825 loss: 1.1825 2022/10/10 09:35:49 - mmengine - INFO - Epoch(train) [85][660/940] lr: 1.0000e-04 eta: 2:01:31 time: 0.4954 data_time: 0.0254 memory: 21547 grad_norm: 4.8266 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0593 loss: 1.0593 2022/10/10 09:35:59 - mmengine - INFO - Epoch(train) [85][680/940] lr: 1.0000e-04 eta: 2:01:21 time: 0.5065 data_time: 0.0279 memory: 21547 grad_norm: 4.7458 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2395 loss: 1.2395 2022/10/10 09:36:09 - mmengine - INFO - Epoch(train) [85][700/940] lr: 1.0000e-04 eta: 2:01:10 time: 0.4903 data_time: 0.0312 memory: 21547 grad_norm: 4.7225 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.1740 loss: 1.1740 2022/10/10 09:36:19 - mmengine - INFO - Epoch(train) [85][720/940] lr: 1.0000e-04 eta: 2:01:00 time: 0.4892 data_time: 0.0330 memory: 21547 grad_norm: 4.7493 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1849 loss: 1.1849 2022/10/10 09:36:29 - mmengine - INFO - Epoch(train) [85][740/940] lr: 1.0000e-04 eta: 2:00:50 time: 0.5084 data_time: 0.0314 memory: 21547 grad_norm: 4.7154 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0751 loss: 1.0751 2022/10/10 09:36:39 - mmengine - INFO - Epoch(train) [85][760/940] lr: 1.0000e-04 eta: 2:00:40 time: 0.5083 data_time: 0.0292 memory: 21547 grad_norm: 4.6191 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1170 loss: 1.1170 2022/10/10 09:36:49 - mmengine - INFO - Epoch(train) [85][780/940] lr: 1.0000e-04 eta: 2:00:30 time: 0.4815 data_time: 0.0262 memory: 21547 grad_norm: 4.8902 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2315 loss: 1.2315 2022/10/10 09:37:00 - mmengine - INFO - Epoch(train) [85][800/940] lr: 1.0000e-04 eta: 2:00:20 time: 0.5356 data_time: 0.0273 memory: 21547 grad_norm: 4.7722 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2074 loss: 1.2074 2022/10/10 09:37:10 - mmengine - INFO - Epoch(train) [85][820/940] lr: 1.0000e-04 eta: 2:00:10 time: 0.5276 data_time: 0.0322 memory: 21547 grad_norm: 4.8245 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1675 loss: 1.1675 2022/10/10 09:37:20 - mmengine - INFO - Epoch(train) [85][840/940] lr: 1.0000e-04 eta: 1:59:59 time: 0.4879 data_time: 0.0263 memory: 21547 grad_norm: 4.9497 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1564 loss: 1.1564 2022/10/10 09:37:30 - mmengine - INFO - Epoch(train) [85][860/940] lr: 1.0000e-04 eta: 1:59:49 time: 0.5176 data_time: 0.0235 memory: 21547 grad_norm: 4.7115 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.0729 loss: 1.0729 2022/10/10 09:37:40 - mmengine - INFO - Epoch(train) [85][880/940] lr: 1.0000e-04 eta: 1:59:39 time: 0.4725 data_time: 0.0267 memory: 21547 grad_norm: 4.8518 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1552 loss: 1.1552 2022/10/10 09:37:51 - mmengine - INFO - Epoch(train) [85][900/940] lr: 1.0000e-04 eta: 1:59:29 time: 0.5487 data_time: 0.0287 memory: 21547 grad_norm: 4.7688 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0607 loss: 1.0607 2022/10/10 09:38:00 - mmengine - INFO - Epoch(train) [85][920/940] lr: 1.0000e-04 eta: 1:59:19 time: 0.4488 data_time: 0.0230 memory: 21547 grad_norm: 4.8423 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0811 loss: 1.0811 2022/10/10 09:38:09 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 09:38:09 - mmengine - INFO - Epoch(train) [85][940/940] lr: 1.0000e-04 eta: 1:59:08 time: 0.4728 data_time: 0.0216 memory: 21547 grad_norm: 5.1494 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.3021 loss: 1.3021 2022/10/10 09:38:21 - mmengine - INFO - Epoch(val) [85][20/78] eta: 0:00:35 time: 0.6080 data_time: 0.4990 memory: 3269 2022/10/10 09:38:30 - mmengine - INFO - Epoch(val) [85][40/78] eta: 0:00:16 time: 0.4228 data_time: 0.3173 memory: 3269 2022/10/10 09:38:41 - mmengine - INFO - Epoch(val) [85][60/78] eta: 0:00:09 time: 0.5500 data_time: 0.4408 memory: 3269 2022/10/10 09:38:51 - mmengine - INFO - Epoch(val) [85][78/78] acc/top1: 0.6806 acc/top5: 0.8714 acc/mean1: 0.6805 2022/10/10 09:38:51 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_83.pth is removed 2022/10/10 09:38:51 - mmengine - INFO - The best checkpoint with 0.6806 acc/top1 at 85 epoch is saved to best_acc/top1_epoch_85.pth. 2022/10/10 09:39:05 - mmengine - INFO - Epoch(train) [86][20/940] lr: 1.0000e-04 eta: 1:58:59 time: 0.6629 data_time: 0.2817 memory: 21547 grad_norm: 4.8051 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2096 loss: 1.2096 2022/10/10 09:39:14 - mmengine - INFO - Epoch(train) [86][40/940] lr: 1.0000e-04 eta: 1:58:49 time: 0.4750 data_time: 0.1144 memory: 21547 grad_norm: 4.7349 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1292 loss: 1.1292 2022/10/10 09:39:25 - mmengine - INFO - Epoch(train) [86][60/940] lr: 1.0000e-04 eta: 1:58:38 time: 0.5306 data_time: 0.1343 memory: 21547 grad_norm: 4.7765 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2360 loss: 1.2360 2022/10/10 09:39:35 - mmengine - INFO - Epoch(train) [86][80/940] lr: 1.0000e-04 eta: 1:58:28 time: 0.4872 data_time: 0.0230 memory: 21547 grad_norm: 4.8611 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2233 loss: 1.2233 2022/10/10 09:39:46 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 09:39:46 - mmengine - INFO - Epoch(train) [86][100/940] lr: 1.0000e-04 eta: 1:58:18 time: 0.5490 data_time: 0.0311 memory: 21547 grad_norm: 4.7500 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1750 loss: 1.1750 2022/10/10 09:39:55 - mmengine - INFO - Epoch(train) [86][120/940] lr: 1.0000e-04 eta: 1:58:08 time: 0.4608 data_time: 0.0260 memory: 21547 grad_norm: 4.9060 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1547 loss: 1.1547 2022/10/10 09:40:06 - mmengine - INFO - Epoch(train) [86][140/940] lr: 1.0000e-04 eta: 1:57:58 time: 0.5550 data_time: 0.0341 memory: 21547 grad_norm: 4.7764 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0548 loss: 1.0548 2022/10/10 09:40:16 - mmengine - INFO - Epoch(train) [86][160/940] lr: 1.0000e-04 eta: 1:57:48 time: 0.5004 data_time: 0.0253 memory: 21547 grad_norm: 4.7032 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3190 loss: 1.3190 2022/10/10 09:40:26 - mmengine - INFO - Epoch(train) [86][180/940] lr: 1.0000e-04 eta: 1:57:38 time: 0.4919 data_time: 0.0340 memory: 21547 grad_norm: 4.7788 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2053 loss: 1.2053 2022/10/10 09:40:35 - mmengine - INFO - Epoch(train) [86][200/940] lr: 1.0000e-04 eta: 1:57:27 time: 0.4729 data_time: 0.0252 memory: 21547 grad_norm: 4.7318 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2115 loss: 1.2115 2022/10/10 09:40:46 - mmengine - INFO - Epoch(train) [86][220/940] lr: 1.0000e-04 eta: 1:57:17 time: 0.5538 data_time: 0.0304 memory: 21547 grad_norm: 4.7207 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0800 loss: 1.0800 2022/10/10 09:40:55 - mmengine - INFO - Epoch(train) [86][240/940] lr: 1.0000e-04 eta: 1:57:07 time: 0.4525 data_time: 0.0295 memory: 21547 grad_norm: 4.8015 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1253 loss: 1.1253 2022/10/10 09:41:06 - mmengine - INFO - Epoch(train) [86][260/940] lr: 1.0000e-04 eta: 1:56:57 time: 0.5436 data_time: 0.0282 memory: 21547 grad_norm: 4.7806 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1066 loss: 1.1066 2022/10/10 09:41:16 - mmengine - INFO - Epoch(train) [86][280/940] lr: 1.0000e-04 eta: 1:56:47 time: 0.5091 data_time: 0.0236 memory: 21547 grad_norm: 4.8221 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1820 loss: 1.1820 2022/10/10 09:41:26 - mmengine - INFO - Epoch(train) [86][300/940] lr: 1.0000e-04 eta: 1:56:37 time: 0.4766 data_time: 0.0312 memory: 21547 grad_norm: 4.8511 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0779 loss: 1.0779 2022/10/10 09:41:35 - mmengine - INFO - Epoch(train) [86][320/940] lr: 1.0000e-04 eta: 1:56:26 time: 0.4658 data_time: 0.0227 memory: 21547 grad_norm: 4.7807 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1863 loss: 1.1863 2022/10/10 09:41:46 - mmengine - INFO - Epoch(train) [86][340/940] lr: 1.0000e-04 eta: 1:56:16 time: 0.5174 data_time: 0.0339 memory: 21547 grad_norm: 4.7064 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0506 loss: 1.0506 2022/10/10 09:41:56 - mmengine - INFO - Epoch(train) [86][360/940] lr: 1.0000e-04 eta: 1:56:06 time: 0.5194 data_time: 0.0242 memory: 21547 grad_norm: 4.7907 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1112 loss: 1.1112 2022/10/10 09:42:07 - mmengine - INFO - Epoch(train) [86][380/940] lr: 1.0000e-04 eta: 1:55:56 time: 0.5663 data_time: 0.0325 memory: 21547 grad_norm: 4.7675 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1142 loss: 1.1142 2022/10/10 09:42:17 - mmengine - INFO - Epoch(train) [86][400/940] lr: 1.0000e-04 eta: 1:55:46 time: 0.4773 data_time: 0.0264 memory: 21547 grad_norm: 4.7467 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.1709 loss: 1.1709 2022/10/10 09:42:27 - mmengine - INFO - Epoch(train) [86][420/940] lr: 1.0000e-04 eta: 1:55:36 time: 0.5050 data_time: 0.0327 memory: 21547 grad_norm: 4.9113 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.2774 loss: 1.2774 2022/10/10 09:42:36 - mmengine - INFO - Epoch(train) [86][440/940] lr: 1.0000e-04 eta: 1:55:26 time: 0.4672 data_time: 0.0252 memory: 21547 grad_norm: 4.7362 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1634 loss: 1.1634 2022/10/10 09:42:47 - mmengine - INFO - Epoch(train) [86][460/940] lr: 1.0000e-04 eta: 1:55:16 time: 0.5335 data_time: 0.0327 memory: 21547 grad_norm: 4.8369 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1778 loss: 1.1778 2022/10/10 09:42:56 - mmengine - INFO - Epoch(train) [86][480/940] lr: 1.0000e-04 eta: 1:55:05 time: 0.4746 data_time: 0.0269 memory: 21547 grad_norm: 4.7480 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1543 loss: 1.1543 2022/10/10 09:43:07 - mmengine - INFO - Epoch(train) [86][500/940] lr: 1.0000e-04 eta: 1:54:55 time: 0.5152 data_time: 0.0340 memory: 21547 grad_norm: 4.6789 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0773 loss: 1.0773 2022/10/10 09:43:17 - mmengine - INFO - Epoch(train) [86][520/940] lr: 1.0000e-04 eta: 1:54:45 time: 0.5114 data_time: 0.0293 memory: 21547 grad_norm: 4.9003 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1738 loss: 1.1738 2022/10/10 09:43:27 - mmengine - INFO - Epoch(train) [86][540/940] lr: 1.0000e-04 eta: 1:54:35 time: 0.4852 data_time: 0.0311 memory: 21547 grad_norm: 4.7649 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2265 loss: 1.2265 2022/10/10 09:43:37 - mmengine - INFO - Epoch(train) [86][560/940] lr: 1.0000e-04 eta: 1:54:25 time: 0.5074 data_time: 0.0325 memory: 21547 grad_norm: 4.8796 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2829 loss: 1.2829 2022/10/10 09:43:47 - mmengine - INFO - Epoch(train) [86][580/940] lr: 1.0000e-04 eta: 1:54:15 time: 0.5248 data_time: 0.0285 memory: 21547 grad_norm: 4.7609 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1975 loss: 1.1975 2022/10/10 09:43:57 - mmengine - INFO - Epoch(train) [86][600/940] lr: 1.0000e-04 eta: 1:54:04 time: 0.5028 data_time: 0.0285 memory: 21547 grad_norm: 4.9436 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1400 loss: 1.1400 2022/10/10 09:44:07 - mmengine - INFO - Epoch(train) [86][620/940] lr: 1.0000e-04 eta: 1:53:54 time: 0.4857 data_time: 0.0296 memory: 21547 grad_norm: 4.7788 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2641 loss: 1.2641 2022/10/10 09:44:18 - mmengine - INFO - Epoch(train) [86][640/940] lr: 1.0000e-04 eta: 1:53:44 time: 0.5303 data_time: 0.0298 memory: 21547 grad_norm: 4.7640 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1303 loss: 1.1303 2022/10/10 09:44:28 - mmengine - INFO - Epoch(train) [86][660/940] lr: 1.0000e-04 eta: 1:53:34 time: 0.4882 data_time: 0.0233 memory: 21547 grad_norm: 4.7223 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9944 loss: 0.9944 2022/10/10 09:44:38 - mmengine - INFO - Epoch(train) [86][680/940] lr: 1.0000e-04 eta: 1:53:24 time: 0.5091 data_time: 0.0254 memory: 21547 grad_norm: 4.9195 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1680 loss: 1.1680 2022/10/10 09:44:47 - mmengine - INFO - Epoch(train) [86][700/940] lr: 1.0000e-04 eta: 1:53:14 time: 0.4694 data_time: 0.0276 memory: 21547 grad_norm: 4.8379 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1919 loss: 1.1919 2022/10/10 09:44:58 - mmengine - INFO - Epoch(train) [86][720/940] lr: 1.0000e-04 eta: 1:53:04 time: 0.5488 data_time: 0.0276 memory: 21547 grad_norm: 4.6005 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1110 loss: 1.1110 2022/10/10 09:45:07 - mmengine - INFO - Epoch(train) [86][740/940] lr: 1.0000e-04 eta: 1:52:53 time: 0.4674 data_time: 0.0276 memory: 21547 grad_norm: 4.8561 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0991 loss: 1.0991 2022/10/10 09:45:18 - mmengine - INFO - Epoch(train) [86][760/940] lr: 1.0000e-04 eta: 1:52:43 time: 0.5496 data_time: 0.0250 memory: 21547 grad_norm: 4.9677 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1854 loss: 1.1854 2022/10/10 09:45:28 - mmengine - INFO - Epoch(train) [86][780/940] lr: 1.0000e-04 eta: 1:52:33 time: 0.4864 data_time: 0.0244 memory: 21547 grad_norm: 4.7827 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1761 loss: 1.1761 2022/10/10 09:45:39 - mmengine - INFO - Epoch(train) [86][800/940] lr: 1.0000e-04 eta: 1:52:23 time: 0.5175 data_time: 0.0254 memory: 21547 grad_norm: 4.8997 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1883 loss: 1.1883 2022/10/10 09:45:48 - mmengine - INFO - Epoch(train) [86][820/940] lr: 1.0000e-04 eta: 1:52:13 time: 0.4722 data_time: 0.0275 memory: 21547 grad_norm: 4.8560 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.0967 loss: 1.0967 2022/10/10 09:45:57 - mmengine - INFO - Epoch(train) [86][840/940] lr: 1.0000e-04 eta: 1:52:02 time: 0.4721 data_time: 0.0244 memory: 21547 grad_norm: 4.8263 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0226 loss: 1.0226 2022/10/10 09:46:08 - mmengine - INFO - Epoch(train) [86][860/940] lr: 1.0000e-04 eta: 1:51:52 time: 0.5237 data_time: 0.0292 memory: 21547 grad_norm: 4.7511 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1692 loss: 1.1692 2022/10/10 09:46:18 - mmengine - INFO - Epoch(train) [86][880/940] lr: 1.0000e-04 eta: 1:51:42 time: 0.4947 data_time: 0.0289 memory: 21547 grad_norm: 4.8714 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1700 loss: 1.1700 2022/10/10 09:46:28 - mmengine - INFO - Epoch(train) [86][900/940] lr: 1.0000e-04 eta: 1:51:32 time: 0.4952 data_time: 0.0259 memory: 21547 grad_norm: 4.8002 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1672 loss: 1.1672 2022/10/10 09:46:38 - mmengine - INFO - Epoch(train) [86][920/940] lr: 1.0000e-04 eta: 1:51:22 time: 0.5188 data_time: 0.0364 memory: 21547 grad_norm: 4.7586 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0856 loss: 1.0856 2022/10/10 09:46:47 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 09:46:47 - mmengine - INFO - Epoch(train) [86][940/940] lr: 1.0000e-04 eta: 1:51:12 time: 0.4434 data_time: 0.0228 memory: 21547 grad_norm: 5.0910 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2027 loss: 1.2027 2022/10/10 09:46:59 - mmengine - INFO - Epoch(val) [86][20/78] eta: 0:00:35 time: 0.6113 data_time: 0.5008 memory: 3269 2022/10/10 09:47:08 - mmengine - INFO - Epoch(val) [86][40/78] eta: 0:00:15 time: 0.4186 data_time: 0.3110 memory: 3269 2022/10/10 09:47:19 - mmengine - INFO - Epoch(val) [86][60/78] eta: 0:00:10 time: 0.5669 data_time: 0.4604 memory: 3269 2022/10/10 09:47:29 - mmengine - INFO - Epoch(val) [86][78/78] acc/top1: 0.6807 acc/top5: 0.8722 acc/mean1: 0.6806 2022/10/10 09:47:29 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_85.pth is removed 2022/10/10 09:47:29 - mmengine - INFO - The best checkpoint with 0.6807 acc/top1 at 86 epoch is saved to best_acc/top1_epoch_86.pth. 2022/10/10 09:47:43 - mmengine - INFO - Epoch(train) [87][20/940] lr: 1.0000e-04 eta: 1:51:02 time: 0.6715 data_time: 0.2994 memory: 21547 grad_norm: 4.7242 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1743 loss: 1.1743 2022/10/10 09:47:54 - mmengine - INFO - Epoch(train) [87][40/940] lr: 1.0000e-04 eta: 1:50:52 time: 0.5610 data_time: 0.0797 memory: 21547 grad_norm: 4.7859 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2885 loss: 1.2885 2022/10/10 09:48:05 - mmengine - INFO - Epoch(train) [87][60/940] lr: 1.0000e-04 eta: 1:50:42 time: 0.5396 data_time: 0.0303 memory: 21547 grad_norm: 4.9652 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1070 loss: 1.1070 2022/10/10 09:48:14 - mmengine - INFO - Epoch(train) [87][80/940] lr: 1.0000e-04 eta: 1:50:32 time: 0.4733 data_time: 0.0288 memory: 21547 grad_norm: 4.7492 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2339 loss: 1.2339 2022/10/10 09:48:25 - mmengine - INFO - Epoch(train) [87][100/940] lr: 1.0000e-04 eta: 1:50:22 time: 0.5609 data_time: 0.0337 memory: 21547 grad_norm: 4.7525 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.0707 loss: 1.0707 2022/10/10 09:48:35 - mmengine - INFO - Epoch(train) [87][120/940] lr: 1.0000e-04 eta: 1:50:12 time: 0.5017 data_time: 0.0256 memory: 21547 grad_norm: 4.8526 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1761 loss: 1.1761 2022/10/10 09:48:46 - mmengine - INFO - Epoch(train) [87][140/940] lr: 1.0000e-04 eta: 1:50:01 time: 0.5029 data_time: 0.0261 memory: 21547 grad_norm: 4.8440 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0763 loss: 1.0763 2022/10/10 09:48:55 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 09:48:55 - mmengine - INFO - Epoch(train) [87][160/940] lr: 1.0000e-04 eta: 1:49:51 time: 0.4749 data_time: 0.0322 memory: 21547 grad_norm: 4.7463 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2508 loss: 1.2508 2022/10/10 09:49:05 - mmengine - INFO - Epoch(train) [87][180/940] lr: 1.0000e-04 eta: 1:49:41 time: 0.5042 data_time: 0.0296 memory: 21547 grad_norm: 4.7863 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1811 loss: 1.1811 2022/10/10 09:49:15 - mmengine - INFO - Epoch(train) [87][200/940] lr: 1.0000e-04 eta: 1:49:31 time: 0.4718 data_time: 0.0289 memory: 21547 grad_norm: 4.9428 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1620 loss: 1.1620 2022/10/10 09:49:25 - mmengine - INFO - Epoch(train) [87][220/940] lr: 1.0000e-04 eta: 1:49:21 time: 0.5328 data_time: 0.0265 memory: 21547 grad_norm: 4.7836 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1598 loss: 1.1598 2022/10/10 09:49:35 - mmengine - INFO - Epoch(train) [87][240/940] lr: 1.0000e-04 eta: 1:49:10 time: 0.4690 data_time: 0.0272 memory: 21547 grad_norm: 4.8014 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1558 loss: 1.1558 2022/10/10 09:49:45 - mmengine - INFO - Epoch(train) [87][260/940] lr: 1.0000e-04 eta: 1:49:00 time: 0.5043 data_time: 0.0316 memory: 21547 grad_norm: 4.8313 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2415 loss: 1.2415 2022/10/10 09:49:55 - mmengine - INFO - Epoch(train) [87][280/940] lr: 1.0000e-04 eta: 1:48:50 time: 0.5007 data_time: 0.0259 memory: 21547 grad_norm: 4.8198 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.0696 loss: 1.0696 2022/10/10 09:50:05 - mmengine - INFO - Epoch(train) [87][300/940] lr: 1.0000e-04 eta: 1:48:40 time: 0.5079 data_time: 0.0445 memory: 21547 grad_norm: 4.7619 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1590 loss: 1.1590 2022/10/10 09:50:15 - mmengine - INFO - Epoch(train) [87][320/940] lr: 1.0000e-04 eta: 1:48:30 time: 0.4880 data_time: 0.0399 memory: 21547 grad_norm: 4.8442 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2446 loss: 1.2446 2022/10/10 09:50:26 - mmengine - INFO - Epoch(train) [87][340/940] lr: 1.0000e-04 eta: 1:48:20 time: 0.5545 data_time: 0.0294 memory: 21547 grad_norm: 4.7683 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0999 loss: 1.0999 2022/10/10 09:50:36 - mmengine - INFO - Epoch(train) [87][360/940] lr: 1.0000e-04 eta: 1:48:10 time: 0.4920 data_time: 0.0289 memory: 21547 grad_norm: 4.6604 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 0.9411 loss: 0.9411 2022/10/10 09:50:46 - mmengine - INFO - Epoch(train) [87][380/940] lr: 1.0000e-04 eta: 1:47:59 time: 0.5140 data_time: 0.0310 memory: 21547 grad_norm: 4.8097 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0842 loss: 1.0842 2022/10/10 09:50:55 - mmengine - INFO - Epoch(train) [87][400/940] lr: 1.0000e-04 eta: 1:47:49 time: 0.4753 data_time: 0.0262 memory: 21547 grad_norm: 4.8686 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1307 loss: 1.1307 2022/10/10 09:51:04 - mmengine - INFO - Epoch(train) [87][420/940] lr: 1.0000e-04 eta: 1:47:39 time: 0.4482 data_time: 0.0339 memory: 21547 grad_norm: 4.8097 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2024 loss: 1.2024 2022/10/10 09:51:16 - mmengine - INFO - Epoch(train) [87][440/940] lr: 1.0000e-04 eta: 1:47:29 time: 0.5659 data_time: 0.0262 memory: 21547 grad_norm: 4.7762 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1699 loss: 1.1699 2022/10/10 09:51:25 - mmengine - INFO - Epoch(train) [87][460/940] lr: 1.0000e-04 eta: 1:47:19 time: 0.4740 data_time: 0.0307 memory: 21547 grad_norm: 4.8259 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1655 loss: 1.1655 2022/10/10 09:51:36 - mmengine - INFO - Epoch(train) [87][480/940] lr: 1.0000e-04 eta: 1:47:09 time: 0.5345 data_time: 0.0240 memory: 21547 grad_norm: 4.7715 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1546 loss: 1.1546 2022/10/10 09:51:46 - mmengine - INFO - Epoch(train) [87][500/940] lr: 1.0000e-04 eta: 1:46:59 time: 0.4994 data_time: 0.0549 memory: 21547 grad_norm: 4.6602 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1752 loss: 1.1752 2022/10/10 09:51:56 - mmengine - INFO - Epoch(train) [87][520/940] lr: 1.0000e-04 eta: 1:46:48 time: 0.4862 data_time: 0.0379 memory: 21547 grad_norm: 4.8485 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.1653 loss: 1.1653 2022/10/10 09:52:06 - mmengine - INFO - Epoch(train) [87][540/940] lr: 1.0000e-04 eta: 1:46:38 time: 0.4982 data_time: 0.0420 memory: 21547 grad_norm: 4.9241 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2329 loss: 1.2329 2022/10/10 09:52:15 - mmengine - INFO - Epoch(train) [87][560/940] lr: 1.0000e-04 eta: 1:46:28 time: 0.4849 data_time: 0.0246 memory: 21547 grad_norm: 4.7878 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2181 loss: 1.2181 2022/10/10 09:52:25 - mmengine - INFO - Epoch(train) [87][580/940] lr: 1.0000e-04 eta: 1:46:18 time: 0.4804 data_time: 0.0282 memory: 21547 grad_norm: 4.7403 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2885 loss: 1.2885 2022/10/10 09:52:35 - mmengine - INFO - Epoch(train) [87][600/940] lr: 1.0000e-04 eta: 1:46:08 time: 0.5026 data_time: 0.0296 memory: 21547 grad_norm: 4.7995 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.1092 loss: 1.1092 2022/10/10 09:52:46 - mmengine - INFO - Epoch(train) [87][620/940] lr: 1.0000e-04 eta: 1:45:58 time: 0.5654 data_time: 0.1039 memory: 21547 grad_norm: 4.7571 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2445 loss: 1.2445 2022/10/10 09:52:56 - mmengine - INFO - Epoch(train) [87][640/940] lr: 1.0000e-04 eta: 1:45:47 time: 0.4751 data_time: 0.0221 memory: 21547 grad_norm: 4.7442 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2010 loss: 1.2010 2022/10/10 09:53:07 - mmengine - INFO - Epoch(train) [87][660/940] lr: 1.0000e-04 eta: 1:45:37 time: 0.5629 data_time: 0.0557 memory: 21547 grad_norm: 4.8098 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1920 loss: 1.1920 2022/10/10 09:53:17 - mmengine - INFO - Epoch(train) [87][680/940] lr: 1.0000e-04 eta: 1:45:27 time: 0.4960 data_time: 0.0235 memory: 21547 grad_norm: 4.7423 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2030 loss: 1.2030 2022/10/10 09:53:28 - mmengine - INFO - Epoch(train) [87][700/940] lr: 1.0000e-04 eta: 1:45:17 time: 0.5445 data_time: 0.0268 memory: 21547 grad_norm: 4.8299 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1604 loss: 1.1604 2022/10/10 09:53:38 - mmengine - INFO - Epoch(train) [87][720/940] lr: 1.0000e-04 eta: 1:45:07 time: 0.4989 data_time: 0.0223 memory: 21547 grad_norm: 4.8254 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1261 loss: 1.1261 2022/10/10 09:53:47 - mmengine - INFO - Epoch(train) [87][740/940] lr: 1.0000e-04 eta: 1:44:57 time: 0.4831 data_time: 0.0266 memory: 21547 grad_norm: 4.8700 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2504 loss: 1.2504 2022/10/10 09:53:57 - mmengine - INFO - Epoch(train) [87][760/940] lr: 1.0000e-04 eta: 1:44:47 time: 0.4997 data_time: 0.0279 memory: 21547 grad_norm: 4.8474 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1293 loss: 1.1293 2022/10/10 09:54:08 - mmengine - INFO - Epoch(train) [87][780/940] lr: 1.0000e-04 eta: 1:44:37 time: 0.5242 data_time: 0.0319 memory: 21547 grad_norm: 4.8429 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1131 loss: 1.1131 2022/10/10 09:54:17 - mmengine - INFO - Epoch(train) [87][800/940] lr: 1.0000e-04 eta: 1:44:26 time: 0.4369 data_time: 0.0259 memory: 21547 grad_norm: 5.0241 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2176 loss: 1.2176 2022/10/10 09:54:26 - mmengine - INFO - Epoch(train) [87][820/940] lr: 1.0000e-04 eta: 1:44:16 time: 0.4814 data_time: 0.0484 memory: 21547 grad_norm: 4.8097 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1686 loss: 1.1686 2022/10/10 09:54:37 - mmengine - INFO - Epoch(train) [87][840/940] lr: 1.0000e-04 eta: 1:44:06 time: 0.5196 data_time: 0.0517 memory: 21547 grad_norm: 4.9303 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1274 loss: 1.1274 2022/10/10 09:54:47 - mmengine - INFO - Epoch(train) [87][860/940] lr: 1.0000e-04 eta: 1:43:56 time: 0.5073 data_time: 0.0284 memory: 21547 grad_norm: 4.8535 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2196 loss: 1.2196 2022/10/10 09:54:57 - mmengine - INFO - Epoch(train) [87][880/940] lr: 1.0000e-04 eta: 1:43:46 time: 0.4959 data_time: 0.0264 memory: 21547 grad_norm: 4.7233 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1966 loss: 1.1966 2022/10/10 09:55:08 - mmengine - INFO - Epoch(train) [87][900/940] lr: 1.0000e-04 eta: 1:43:36 time: 0.5552 data_time: 0.0338 memory: 21547 grad_norm: 4.8439 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1875 loss: 1.1875 2022/10/10 09:55:18 - mmengine - INFO - Epoch(train) [87][920/940] lr: 1.0000e-04 eta: 1:43:25 time: 0.4884 data_time: 0.0245 memory: 21547 grad_norm: 4.8156 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1474 loss: 1.1474 2022/10/10 09:55:27 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 09:55:27 - mmengine - INFO - Epoch(train) [87][940/940] lr: 1.0000e-04 eta: 1:43:15 time: 0.4900 data_time: 0.0233 memory: 21547 grad_norm: 5.1070 top1_acc: 0.2857 top5_acc: 0.5714 loss_cls: 1.2515 loss: 1.2515 2022/10/10 09:55:27 - mmengine - INFO - Saving checkpoint at 87 epochs 2022/10/10 09:55:41 - mmengine - INFO - Epoch(val) [87][20/78] eta: 0:00:35 time: 0.6138 data_time: 0.5064 memory: 3269 2022/10/10 09:55:49 - mmengine - INFO - Epoch(val) [87][40/78] eta: 0:00:15 time: 0.4177 data_time: 0.3147 memory: 3269 2022/10/10 09:56:00 - mmengine - INFO - Epoch(val) [87][60/78] eta: 0:00:09 time: 0.5517 data_time: 0.4484 memory: 3269 2022/10/10 09:56:09 - mmengine - INFO - Epoch(val) [87][78/78] acc/top1: 0.6797 acc/top5: 0.8723 acc/mean1: 0.6796 2022/10/10 09:56:24 - mmengine - INFO - Epoch(train) [88][20/940] lr: 1.0000e-04 eta: 1:43:06 time: 0.7462 data_time: 0.2047 memory: 21547 grad_norm: 4.8488 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2530 loss: 1.2530 2022/10/10 09:56:34 - mmengine - INFO - Epoch(train) [88][40/940] lr: 1.0000e-04 eta: 1:42:56 time: 0.4698 data_time: 0.0297 memory: 21547 grad_norm: 4.8017 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0415 loss: 1.0415 2022/10/10 09:56:43 - mmengine - INFO - Epoch(train) [88][60/940] lr: 1.0000e-04 eta: 1:42:45 time: 0.4979 data_time: 0.0274 memory: 21547 grad_norm: 4.8312 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2169 loss: 1.2169 2022/10/10 09:56:53 - mmengine - INFO - Epoch(train) [88][80/940] lr: 1.0000e-04 eta: 1:42:35 time: 0.4883 data_time: 0.0271 memory: 21547 grad_norm: 4.6976 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1193 loss: 1.1193 2022/10/10 09:57:04 - mmengine - INFO - Epoch(train) [88][100/940] lr: 1.0000e-04 eta: 1:42:25 time: 0.5334 data_time: 0.0306 memory: 21547 grad_norm: 4.9082 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2322 loss: 1.2322 2022/10/10 09:57:14 - mmengine - INFO - Epoch(train) [88][120/940] lr: 1.0000e-04 eta: 1:42:15 time: 0.5074 data_time: 0.0262 memory: 21547 grad_norm: 4.7625 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.1510 loss: 1.1510 2022/10/10 09:57:24 - mmengine - INFO - Epoch(train) [88][140/940] lr: 1.0000e-04 eta: 1:42:05 time: 0.5197 data_time: 0.0376 memory: 21547 grad_norm: 4.7775 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2291 loss: 1.2291 2022/10/10 09:57:34 - mmengine - INFO - Epoch(train) [88][160/940] lr: 1.0000e-04 eta: 1:41:55 time: 0.4872 data_time: 0.0251 memory: 21547 grad_norm: 4.8307 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1906 loss: 1.1906 2022/10/10 09:57:45 - mmengine - INFO - Epoch(train) [88][180/940] lr: 1.0000e-04 eta: 1:41:45 time: 0.5431 data_time: 0.0316 memory: 21547 grad_norm: 4.8453 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1207 loss: 1.1207 2022/10/10 09:57:54 - mmengine - INFO - Epoch(train) [88][200/940] lr: 1.0000e-04 eta: 1:41:34 time: 0.4700 data_time: 0.0274 memory: 21547 grad_norm: 4.7800 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2426 loss: 1.2426 2022/10/10 09:58:05 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 09:58:05 - mmengine - INFO - Epoch(train) [88][220/940] lr: 1.0000e-04 eta: 1:41:24 time: 0.5051 data_time: 0.0253 memory: 21547 grad_norm: 4.8235 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1588 loss: 1.1588 2022/10/10 09:58:15 - mmengine - INFO - Epoch(train) [88][240/940] lr: 1.0000e-04 eta: 1:41:14 time: 0.5299 data_time: 0.0297 memory: 21547 grad_norm: 4.8389 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1127 loss: 1.1127 2022/10/10 09:58:26 - mmengine - INFO - Epoch(train) [88][260/940] lr: 1.0000e-04 eta: 1:41:04 time: 0.5313 data_time: 0.0244 memory: 21547 grad_norm: 4.8560 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1925 loss: 1.1925 2022/10/10 09:58:36 - mmengine - INFO - Epoch(train) [88][280/940] lr: 1.0000e-04 eta: 1:40:54 time: 0.5031 data_time: 0.0279 memory: 21547 grad_norm: 4.8956 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2539 loss: 1.2539 2022/10/10 09:58:46 - mmengine - INFO - Epoch(train) [88][300/940] lr: 1.0000e-04 eta: 1:40:44 time: 0.4836 data_time: 0.0288 memory: 21547 grad_norm: 4.7567 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2245 loss: 1.2245 2022/10/10 09:58:55 - mmengine - INFO - Epoch(train) [88][320/940] lr: 1.0000e-04 eta: 1:40:33 time: 0.4623 data_time: 0.0261 memory: 21547 grad_norm: 4.8096 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2059 loss: 1.2059 2022/10/10 09:59:05 - mmengine - INFO - Epoch(train) [88][340/940] lr: 1.0000e-04 eta: 1:40:23 time: 0.4982 data_time: 0.0239 memory: 21547 grad_norm: 4.7652 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2079 loss: 1.2079 2022/10/10 09:59:14 - mmengine - INFO - Epoch(train) [88][360/940] lr: 1.0000e-04 eta: 1:40:13 time: 0.4783 data_time: 0.0288 memory: 21547 grad_norm: 4.8403 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0899 loss: 1.0899 2022/10/10 09:59:25 - mmengine - INFO - Epoch(train) [88][380/940] lr: 1.0000e-04 eta: 1:40:03 time: 0.5184 data_time: 0.0327 memory: 21547 grad_norm: 4.7975 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1511 loss: 1.1511 2022/10/10 09:59:34 - mmengine - INFO - Epoch(train) [88][400/940] lr: 1.0000e-04 eta: 1:39:53 time: 0.4879 data_time: 0.0290 memory: 21547 grad_norm: 4.6429 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1527 loss: 1.1527 2022/10/10 09:59:45 - mmengine - INFO - Epoch(train) [88][420/940] lr: 1.0000e-04 eta: 1:39:43 time: 0.5350 data_time: 0.0271 memory: 21547 grad_norm: 4.7373 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1402 loss: 1.1402 2022/10/10 09:59:54 - mmengine - INFO - Epoch(train) [88][440/940] lr: 1.0000e-04 eta: 1:39:32 time: 0.4640 data_time: 0.0326 memory: 21547 grad_norm: 4.9334 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.1202 loss: 1.1202 2022/10/10 10:00:05 - mmengine - INFO - Epoch(train) [88][460/940] lr: 1.0000e-04 eta: 1:39:22 time: 0.5164 data_time: 0.0287 memory: 21547 grad_norm: 4.7979 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0867 loss: 1.0867 2022/10/10 10:00:15 - mmengine - INFO - Epoch(train) [88][480/940] lr: 1.0000e-04 eta: 1:39:12 time: 0.4962 data_time: 0.0294 memory: 21547 grad_norm: 4.9066 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.0500 loss: 1.0500 2022/10/10 10:00:25 - mmengine - INFO - Epoch(train) [88][500/940] lr: 1.0000e-04 eta: 1:39:02 time: 0.5179 data_time: 0.0252 memory: 21547 grad_norm: 4.7686 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1388 loss: 1.1388 2022/10/10 10:00:35 - mmengine - INFO - Epoch(train) [88][520/940] lr: 1.0000e-04 eta: 1:38:52 time: 0.4954 data_time: 0.0256 memory: 21547 grad_norm: 4.8696 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1884 loss: 1.1884 2022/10/10 10:00:46 - mmengine - INFO - Epoch(train) [88][540/940] lr: 1.0000e-04 eta: 1:38:42 time: 0.5429 data_time: 0.0299 memory: 21547 grad_norm: 4.8689 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1308 loss: 1.1308 2022/10/10 10:00:55 - mmengine - INFO - Epoch(train) [88][560/940] lr: 1.0000e-04 eta: 1:38:32 time: 0.4669 data_time: 0.0291 memory: 21547 grad_norm: 4.7562 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0362 loss: 1.0362 2022/10/10 10:01:06 - mmengine - INFO - Epoch(train) [88][580/940] lr: 1.0000e-04 eta: 1:38:21 time: 0.5295 data_time: 0.0325 memory: 21547 grad_norm: 4.8828 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2484 loss: 1.2484 2022/10/10 10:01:15 - mmengine - INFO - Epoch(train) [88][600/940] lr: 1.0000e-04 eta: 1:38:11 time: 0.4747 data_time: 0.0266 memory: 21547 grad_norm: 4.8966 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1650 loss: 1.1650 2022/10/10 10:01:26 - mmengine - INFO - Epoch(train) [88][620/940] lr: 1.0000e-04 eta: 1:38:01 time: 0.5572 data_time: 0.0368 memory: 21547 grad_norm: 4.7483 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1312 loss: 1.1312 2022/10/10 10:01:36 - mmengine - INFO - Epoch(train) [88][640/940] lr: 1.0000e-04 eta: 1:37:51 time: 0.4826 data_time: 0.0292 memory: 21547 grad_norm: 4.7599 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0056 loss: 1.0056 2022/10/10 10:01:47 - mmengine - INFO - Epoch(train) [88][660/940] lr: 1.0000e-04 eta: 1:37:41 time: 0.5465 data_time: 0.0337 memory: 21547 grad_norm: 4.6603 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0597 loss: 1.0597 2022/10/10 10:01:57 - mmengine - INFO - Epoch(train) [88][680/940] lr: 1.0000e-04 eta: 1:37:31 time: 0.4910 data_time: 0.0285 memory: 21547 grad_norm: 4.8284 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1887 loss: 1.1887 2022/10/10 10:02:07 - mmengine - INFO - Epoch(train) [88][700/940] lr: 1.0000e-04 eta: 1:37:21 time: 0.5071 data_time: 0.0276 memory: 21547 grad_norm: 4.7970 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2055 loss: 1.2055 2022/10/10 10:02:16 - mmengine - INFO - Epoch(train) [88][720/940] lr: 1.0000e-04 eta: 1:37:10 time: 0.4704 data_time: 0.0356 memory: 21547 grad_norm: 4.8288 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1613 loss: 1.1613 2022/10/10 10:02:27 - mmengine - INFO - Epoch(train) [88][740/940] lr: 1.0000e-04 eta: 1:37:00 time: 0.5333 data_time: 0.0263 memory: 21547 grad_norm: 4.8327 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2123 loss: 1.2123 2022/10/10 10:02:37 - mmengine - INFO - Epoch(train) [88][760/940] lr: 1.0000e-04 eta: 1:36:50 time: 0.4736 data_time: 0.0309 memory: 21547 grad_norm: 4.6908 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1082 loss: 1.1082 2022/10/10 10:02:47 - mmengine - INFO - Epoch(train) [88][780/940] lr: 1.0000e-04 eta: 1:36:40 time: 0.5405 data_time: 0.0249 memory: 21547 grad_norm: 4.6823 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1039 loss: 1.1039 2022/10/10 10:02:57 - mmengine - INFO - Epoch(train) [88][800/940] lr: 1.0000e-04 eta: 1:36:30 time: 0.4761 data_time: 0.0247 memory: 21547 grad_norm: 4.7747 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2005 loss: 1.2005 2022/10/10 10:03:07 - mmengine - INFO - Epoch(train) [88][820/940] lr: 1.0000e-04 eta: 1:36:20 time: 0.5069 data_time: 0.0255 memory: 21547 grad_norm: 4.8739 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1593 loss: 1.1593 2022/10/10 10:03:17 - mmengine - INFO - Epoch(train) [88][840/940] lr: 1.0000e-04 eta: 1:36:09 time: 0.4823 data_time: 0.0293 memory: 21547 grad_norm: 4.7783 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2259 loss: 1.2259 2022/10/10 10:03:27 - mmengine - INFO - Epoch(train) [88][860/940] lr: 1.0000e-04 eta: 1:35:59 time: 0.5193 data_time: 0.0246 memory: 21547 grad_norm: 4.7964 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1869 loss: 1.1869 2022/10/10 10:03:36 - mmengine - INFO - Epoch(train) [88][880/940] lr: 1.0000e-04 eta: 1:35:49 time: 0.4668 data_time: 0.0267 memory: 21547 grad_norm: 4.8097 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1554 loss: 1.1554 2022/10/10 10:03:47 - mmengine - INFO - Epoch(train) [88][900/940] lr: 1.0000e-04 eta: 1:35:39 time: 0.5329 data_time: 0.0298 memory: 21547 grad_norm: 4.9947 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4050 loss: 1.4050 2022/10/10 10:03:56 - mmengine - INFO - Epoch(train) [88][920/940] lr: 1.0000e-04 eta: 1:35:29 time: 0.4595 data_time: 0.0303 memory: 21547 grad_norm: 4.7272 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1453 loss: 1.1453 2022/10/10 10:04:05 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 10:04:05 - mmengine - INFO - Epoch(train) [88][940/940] lr: 1.0000e-04 eta: 1:35:19 time: 0.4574 data_time: 0.0229 memory: 21547 grad_norm: 5.0406 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.1299 loss: 1.1299 2022/10/10 10:04:17 - mmengine - INFO - Epoch(val) [88][20/78] eta: 0:00:35 time: 0.6035 data_time: 0.4942 memory: 3269 2022/10/10 10:04:26 - mmengine - INFO - Epoch(val) [88][40/78] eta: 0:00:16 time: 0.4237 data_time: 0.3175 memory: 3269 2022/10/10 10:04:37 - mmengine - INFO - Epoch(val) [88][60/78] eta: 0:00:09 time: 0.5447 data_time: 0.4390 memory: 3269 2022/10/10 10:04:47 - mmengine - INFO - Epoch(val) [88][78/78] acc/top1: 0.6804 acc/top5: 0.8714 acc/mean1: 0.6803 2022/10/10 10:05:01 - mmengine - INFO - Epoch(train) [89][20/940] lr: 1.0000e-04 eta: 1:35:09 time: 0.7019 data_time: 0.2000 memory: 21547 grad_norm: 4.8688 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2350 loss: 1.2350 2022/10/10 10:05:10 - mmengine - INFO - Epoch(train) [89][40/940] lr: 1.0000e-04 eta: 1:34:59 time: 0.4561 data_time: 0.0230 memory: 21547 grad_norm: 4.9049 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1434 loss: 1.1434 2022/10/10 10:05:21 - mmengine - INFO - Epoch(train) [89][60/940] lr: 1.0000e-04 eta: 1:34:49 time: 0.5237 data_time: 0.0325 memory: 21547 grad_norm: 4.9563 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.1698 loss: 1.1698 2022/10/10 10:05:31 - mmengine - INFO - Epoch(train) [89][80/940] lr: 1.0000e-04 eta: 1:34:38 time: 0.4953 data_time: 0.0266 memory: 21547 grad_norm: 4.7812 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0682 loss: 1.0682 2022/10/10 10:05:42 - mmengine - INFO - Epoch(train) [89][100/940] lr: 1.0000e-04 eta: 1:34:28 time: 0.5525 data_time: 0.0305 memory: 21547 grad_norm: 4.9123 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1154 loss: 1.1154 2022/10/10 10:05:52 - mmengine - INFO - Epoch(train) [89][120/940] lr: 1.0000e-04 eta: 1:34:18 time: 0.5287 data_time: 0.0266 memory: 21547 grad_norm: 4.7923 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2182 loss: 1.2182 2022/10/10 10:06:02 - mmengine - INFO - Epoch(train) [89][140/940] lr: 1.0000e-04 eta: 1:34:08 time: 0.4984 data_time: 0.0314 memory: 21547 grad_norm: 4.7454 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0221 loss: 1.0221 2022/10/10 10:06:12 - mmengine - INFO - Epoch(train) [89][160/940] lr: 1.0000e-04 eta: 1:33:58 time: 0.5096 data_time: 0.0314 memory: 21547 grad_norm: 4.8249 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2235 loss: 1.2235 2022/10/10 10:06:23 - mmengine - INFO - Epoch(train) [89][180/940] lr: 1.0000e-04 eta: 1:33:48 time: 0.5242 data_time: 0.0276 memory: 21547 grad_norm: 4.8323 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0722 loss: 1.0722 2022/10/10 10:06:33 - mmengine - INFO - Epoch(train) [89][200/940] lr: 1.0000e-04 eta: 1:33:38 time: 0.5296 data_time: 0.0314 memory: 21547 grad_norm: 4.8216 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1954 loss: 1.1954 2022/10/10 10:06:43 - mmengine - INFO - Epoch(train) [89][220/940] lr: 1.0000e-04 eta: 1:33:28 time: 0.4721 data_time: 0.0295 memory: 21547 grad_norm: 4.7340 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1751 loss: 1.1751 2022/10/10 10:06:53 - mmengine - INFO - Epoch(train) [89][240/940] lr: 1.0000e-04 eta: 1:33:17 time: 0.5096 data_time: 0.0284 memory: 21547 grad_norm: 4.7372 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1892 loss: 1.1892 2022/10/10 10:07:03 - mmengine - INFO - Epoch(train) [89][260/940] lr: 1.0000e-04 eta: 1:33:07 time: 0.5043 data_time: 0.0296 memory: 21547 grad_norm: 4.6738 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0456 loss: 1.0456 2022/10/10 10:07:13 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 10:07:13 - mmengine - INFO - Epoch(train) [89][280/940] lr: 1.0000e-04 eta: 1:32:57 time: 0.5049 data_time: 0.0346 memory: 21547 grad_norm: 4.8291 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1198 loss: 1.1198 2022/10/10 10:07:24 - mmengine - INFO - Epoch(train) [89][300/940] lr: 1.0000e-04 eta: 1:32:47 time: 0.5122 data_time: 0.0257 memory: 21547 grad_norm: 4.8537 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1189 loss: 1.1189 2022/10/10 10:07:33 - mmengine - INFO - Epoch(train) [89][320/940] lr: 1.0000e-04 eta: 1:32:37 time: 0.4735 data_time: 0.0272 memory: 21547 grad_norm: 4.7286 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0974 loss: 1.0974 2022/10/10 10:07:43 - mmengine - INFO - Epoch(train) [89][340/940] lr: 1.0000e-04 eta: 1:32:27 time: 0.5142 data_time: 0.0325 memory: 21547 grad_norm: 4.8166 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1859 loss: 1.1859 2022/10/10 10:07:53 - mmengine - INFO - Epoch(train) [89][360/940] lr: 1.0000e-04 eta: 1:32:17 time: 0.5082 data_time: 0.0287 memory: 21547 grad_norm: 4.8524 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1683 loss: 1.1683 2022/10/10 10:08:03 - mmengine - INFO - Epoch(train) [89][380/940] lr: 1.0000e-04 eta: 1:32:06 time: 0.4961 data_time: 0.0288 memory: 21547 grad_norm: 4.7687 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1534 loss: 1.1534 2022/10/10 10:08:14 - mmengine - INFO - Epoch(train) [89][400/940] lr: 1.0000e-04 eta: 1:31:56 time: 0.5325 data_time: 0.0273 memory: 21547 grad_norm: 4.7042 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1198 loss: 1.1198 2022/10/10 10:08:24 - mmengine - INFO - Epoch(train) [89][420/940] lr: 1.0000e-04 eta: 1:31:46 time: 0.4773 data_time: 0.0260 memory: 21547 grad_norm: 4.7751 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1188 loss: 1.1188 2022/10/10 10:08:34 - mmengine - INFO - Epoch(train) [89][440/940] lr: 1.0000e-04 eta: 1:31:36 time: 0.5296 data_time: 0.0270 memory: 21547 grad_norm: 4.7567 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2205 loss: 1.2205 2022/10/10 10:08:44 - mmengine - INFO - Epoch(train) [89][460/940] lr: 1.0000e-04 eta: 1:31:26 time: 0.4944 data_time: 0.0294 memory: 21547 grad_norm: 4.8369 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1713 loss: 1.1713 2022/10/10 10:08:54 - mmengine - INFO - Epoch(train) [89][480/940] lr: 1.0000e-04 eta: 1:31:16 time: 0.5125 data_time: 0.0250 memory: 21547 grad_norm: 4.7487 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1226 loss: 1.1226 2022/10/10 10:09:05 - mmengine - INFO - Epoch(train) [89][500/940] lr: 1.0000e-04 eta: 1:31:06 time: 0.5470 data_time: 0.0288 memory: 21547 grad_norm: 4.7257 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1745 loss: 1.1745 2022/10/10 10:09:15 - mmengine - INFO - Epoch(train) [89][520/940] lr: 1.0000e-04 eta: 1:30:55 time: 0.4964 data_time: 0.0227 memory: 21547 grad_norm: 4.8217 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.1593 loss: 1.1593 2022/10/10 10:09:26 - mmengine - INFO - Epoch(train) [89][540/940] lr: 1.0000e-04 eta: 1:30:45 time: 0.5245 data_time: 0.0309 memory: 21547 grad_norm: 4.8387 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0952 loss: 1.0952 2022/10/10 10:09:36 - mmengine - INFO - Epoch(train) [89][560/940] lr: 1.0000e-04 eta: 1:30:35 time: 0.4952 data_time: 0.0280 memory: 21547 grad_norm: 4.8212 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1490 loss: 1.1490 2022/10/10 10:09:46 - mmengine - INFO - Epoch(train) [89][580/940] lr: 1.0000e-04 eta: 1:30:25 time: 0.5015 data_time: 0.0248 memory: 21547 grad_norm: 4.8005 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1661 loss: 1.1661 2022/10/10 10:09:56 - mmengine - INFO - Epoch(train) [89][600/940] lr: 1.0000e-04 eta: 1:30:15 time: 0.5235 data_time: 0.0225 memory: 21547 grad_norm: 4.7062 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2533 loss: 1.2533 2022/10/10 10:10:06 - mmengine - INFO - Epoch(train) [89][620/940] lr: 1.0000e-04 eta: 1:30:05 time: 0.4899 data_time: 0.0248 memory: 21547 grad_norm: 4.7606 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.0982 loss: 1.0982 2022/10/10 10:10:16 - mmengine - INFO - Epoch(train) [89][640/940] lr: 1.0000e-04 eta: 1:29:55 time: 0.5241 data_time: 0.0280 memory: 21547 grad_norm: 4.7415 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1411 loss: 1.1411 2022/10/10 10:10:27 - mmengine - INFO - Epoch(train) [89][660/940] lr: 1.0000e-04 eta: 1:29:45 time: 0.5504 data_time: 0.0297 memory: 21547 grad_norm: 4.7595 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9858 loss: 0.9858 2022/10/10 10:10:37 - mmengine - INFO - Epoch(train) [89][680/940] lr: 1.0000e-04 eta: 1:29:34 time: 0.4981 data_time: 0.0247 memory: 21547 grad_norm: 4.7338 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 1.1950 loss: 1.1950 2022/10/10 10:10:47 - mmengine - INFO - Epoch(train) [89][700/940] lr: 1.0000e-04 eta: 1:29:24 time: 0.4739 data_time: 0.0259 memory: 21547 grad_norm: 4.7688 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0318 loss: 1.0318 2022/10/10 10:10:57 - mmengine - INFO - Epoch(train) [89][720/940] lr: 1.0000e-04 eta: 1:29:14 time: 0.5258 data_time: 0.0294 memory: 21547 grad_norm: 4.9901 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2430 loss: 1.2430 2022/10/10 10:11:07 - mmengine - INFO - Epoch(train) [89][740/940] lr: 1.0000e-04 eta: 1:29:04 time: 0.4818 data_time: 0.0287 memory: 21547 grad_norm: 4.8116 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9946 loss: 0.9946 2022/10/10 10:11:17 - mmengine - INFO - Epoch(train) [89][760/940] lr: 1.0000e-04 eta: 1:28:54 time: 0.5196 data_time: 0.0230 memory: 21547 grad_norm: 4.8903 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2258 loss: 1.2258 2022/10/10 10:11:27 - mmengine - INFO - Epoch(train) [89][780/940] lr: 1.0000e-04 eta: 1:28:44 time: 0.4832 data_time: 0.0241 memory: 21547 grad_norm: 4.7449 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1119 loss: 1.1119 2022/10/10 10:11:37 - mmengine - INFO - Epoch(train) [89][800/940] lr: 1.0000e-04 eta: 1:28:33 time: 0.5006 data_time: 0.0373 memory: 21547 grad_norm: 4.8310 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2632 loss: 1.2632 2022/10/10 10:11:47 - mmengine - INFO - Epoch(train) [89][820/940] lr: 1.0000e-04 eta: 1:28:23 time: 0.4855 data_time: 0.0258 memory: 21547 grad_norm: 4.9062 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2942 loss: 1.2942 2022/10/10 10:11:57 - mmengine - INFO - Epoch(train) [89][840/940] lr: 1.0000e-04 eta: 1:28:13 time: 0.4985 data_time: 0.0309 memory: 21547 grad_norm: 4.7051 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2327 loss: 1.2327 2022/10/10 10:12:07 - mmengine - INFO - Epoch(train) [89][860/940] lr: 1.0000e-04 eta: 1:28:03 time: 0.4888 data_time: 0.0241 memory: 21547 grad_norm: 4.6754 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0227 loss: 1.0227 2022/10/10 10:12:17 - mmengine - INFO - Epoch(train) [89][880/940] lr: 1.0000e-04 eta: 1:27:53 time: 0.5085 data_time: 0.0327 memory: 21547 grad_norm: 4.8462 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2828 loss: 1.2828 2022/10/10 10:12:27 - mmengine - INFO - Epoch(train) [89][900/940] lr: 1.0000e-04 eta: 1:27:43 time: 0.4986 data_time: 0.0268 memory: 21547 grad_norm: 4.7758 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1837 loss: 1.1837 2022/10/10 10:12:37 - mmengine - INFO - Epoch(train) [89][920/940] lr: 1.0000e-04 eta: 1:27:33 time: 0.5387 data_time: 0.0341 memory: 21547 grad_norm: 4.7664 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.0993 loss: 1.0993 2022/10/10 10:12:47 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 10:12:47 - mmengine - INFO - Epoch(train) [89][940/940] lr: 1.0000e-04 eta: 1:27:22 time: 0.4580 data_time: 0.0204 memory: 21547 grad_norm: 5.0400 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.0865 loss: 1.0865 2022/10/10 10:12:59 - mmengine - INFO - Epoch(val) [89][20/78] eta: 0:00:35 time: 0.6094 data_time: 0.4974 memory: 3269 2022/10/10 10:13:07 - mmengine - INFO - Epoch(val) [89][40/78] eta: 0:00:16 time: 0.4255 data_time: 0.3179 memory: 3269 2022/10/10 10:13:19 - mmengine - INFO - Epoch(val) [89][60/78] eta: 0:00:10 time: 0.5594 data_time: 0.4523 memory: 3269 2022/10/10 10:13:28 - mmengine - INFO - Epoch(val) [89][78/78] acc/top1: 0.6806 acc/top5: 0.8711 acc/mean1: 0.6806 2022/10/10 10:13:42 - mmengine - INFO - Epoch(train) [90][20/940] lr: 1.0000e-04 eta: 1:27:13 time: 0.7041 data_time: 0.2212 memory: 21547 grad_norm: 4.7545 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0402 loss: 1.0402 2022/10/10 10:13:52 - mmengine - INFO - Epoch(train) [90][40/940] lr: 1.0000e-04 eta: 1:27:02 time: 0.4832 data_time: 0.0272 memory: 21547 grad_norm: 4.7735 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1295 loss: 1.1295 2022/10/10 10:14:04 - mmengine - INFO - Epoch(train) [90][60/940] lr: 1.0000e-04 eta: 1:26:53 time: 0.5961 data_time: 0.0337 memory: 21547 grad_norm: 4.7140 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2445 loss: 1.2445 2022/10/10 10:14:14 - mmengine - INFO - Epoch(train) [90][80/940] lr: 1.0000e-04 eta: 1:26:42 time: 0.4787 data_time: 0.0236 memory: 21547 grad_norm: 4.9242 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2126 loss: 1.2126 2022/10/10 10:14:24 - mmengine - INFO - Epoch(train) [90][100/940] lr: 1.0000e-04 eta: 1:26:32 time: 0.5109 data_time: 0.0316 memory: 21547 grad_norm: 4.7722 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.0618 loss: 1.0618 2022/10/10 10:14:34 - mmengine - INFO - Epoch(train) [90][120/940] lr: 1.0000e-04 eta: 1:26:22 time: 0.4850 data_time: 0.0219 memory: 21547 grad_norm: 4.9274 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1572 loss: 1.1572 2022/10/10 10:14:43 - mmengine - INFO - Epoch(train) [90][140/940] lr: 1.0000e-04 eta: 1:26:12 time: 0.4921 data_time: 0.0284 memory: 21547 grad_norm: 4.8233 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2247 loss: 1.2247 2022/10/10 10:14:53 - mmengine - INFO - Epoch(train) [90][160/940] lr: 1.0000e-04 eta: 1:26:02 time: 0.4623 data_time: 0.0649 memory: 21547 grad_norm: 4.8908 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1188 loss: 1.1188 2022/10/10 10:15:04 - mmengine - INFO - Epoch(train) [90][180/940] lr: 1.0000e-04 eta: 1:25:52 time: 0.5606 data_time: 0.1738 memory: 21547 grad_norm: 4.7836 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0520 loss: 1.0520 2022/10/10 10:15:14 - mmengine - INFO - Epoch(train) [90][200/940] lr: 1.0000e-04 eta: 1:25:41 time: 0.4888 data_time: 0.0758 memory: 21547 grad_norm: 4.8284 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0831 loss: 1.0831 2022/10/10 10:15:24 - mmengine - INFO - Epoch(train) [90][220/940] lr: 1.0000e-04 eta: 1:25:31 time: 0.5076 data_time: 0.1334 memory: 21547 grad_norm: 4.8925 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1422 loss: 1.1422 2022/10/10 10:15:34 - mmengine - INFO - Epoch(train) [90][240/940] lr: 1.0000e-04 eta: 1:25:21 time: 0.4988 data_time: 0.0463 memory: 21547 grad_norm: 4.7536 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1183 loss: 1.1183 2022/10/10 10:15:44 - mmengine - INFO - Epoch(train) [90][260/940] lr: 1.0000e-04 eta: 1:25:11 time: 0.5010 data_time: 0.0341 memory: 21547 grad_norm: 4.8369 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3256 loss: 1.3256 2022/10/10 10:15:54 - mmengine - INFO - Epoch(train) [90][280/940] lr: 1.0000e-04 eta: 1:25:01 time: 0.5005 data_time: 0.0234 memory: 21547 grad_norm: 4.8995 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1973 loss: 1.1973 2022/10/10 10:16:04 - mmengine - INFO - Epoch(train) [90][300/940] lr: 1.0000e-04 eta: 1:24:51 time: 0.5338 data_time: 0.0291 memory: 21547 grad_norm: 4.9794 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1703 loss: 1.1703 2022/10/10 10:16:14 - mmengine - INFO - Epoch(train) [90][320/940] lr: 1.0000e-04 eta: 1:24:40 time: 0.4936 data_time: 0.0261 memory: 21547 grad_norm: 4.8495 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2394 loss: 1.2394 2022/10/10 10:16:24 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 10:16:24 - mmengine - INFO - Epoch(train) [90][340/940] lr: 1.0000e-04 eta: 1:24:30 time: 0.4767 data_time: 0.0299 memory: 21547 grad_norm: 4.9324 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1946 loss: 1.1946 2022/10/10 10:16:35 - mmengine - INFO - Epoch(train) [90][360/940] lr: 1.0000e-04 eta: 1:24:20 time: 0.5388 data_time: 0.0269 memory: 21547 grad_norm: 4.8588 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1318 loss: 1.1318 2022/10/10 10:16:46 - mmengine - INFO - Epoch(train) [90][380/940] lr: 1.0000e-04 eta: 1:24:10 time: 0.5504 data_time: 0.0308 memory: 21547 grad_norm: 4.8435 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1691 loss: 1.1691 2022/10/10 10:16:55 - mmengine - INFO - Epoch(train) [90][400/940] lr: 1.0000e-04 eta: 1:24:00 time: 0.4898 data_time: 0.0261 memory: 21547 grad_norm: 4.7297 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1139 loss: 1.1139 2022/10/10 10:17:06 - mmengine - INFO - Epoch(train) [90][420/940] lr: 1.0000e-04 eta: 1:23:50 time: 0.5239 data_time: 0.0289 memory: 21547 grad_norm: 4.7987 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2267 loss: 1.2267 2022/10/10 10:17:15 - mmengine - INFO - Epoch(train) [90][440/940] lr: 1.0000e-04 eta: 1:23:40 time: 0.4673 data_time: 0.0260 memory: 21547 grad_norm: 4.7597 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0861 loss: 1.0861 2022/10/10 10:17:27 - mmengine - INFO - Epoch(train) [90][460/940] lr: 1.0000e-04 eta: 1:23:30 time: 0.5696 data_time: 0.0259 memory: 21547 grad_norm: 4.8547 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1262 loss: 1.1262 2022/10/10 10:17:36 - mmengine - INFO - Epoch(train) [90][480/940] lr: 1.0000e-04 eta: 1:23:19 time: 0.4557 data_time: 0.0326 memory: 21547 grad_norm: 4.6918 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0594 loss: 1.0594 2022/10/10 10:17:47 - mmengine - INFO - Epoch(train) [90][500/940] lr: 1.0000e-04 eta: 1:23:09 time: 0.5488 data_time: 0.0258 memory: 21547 grad_norm: 4.8304 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1932 loss: 1.1932 2022/10/10 10:17:57 - mmengine - INFO - Epoch(train) [90][520/940] lr: 1.0000e-04 eta: 1:22:59 time: 0.5050 data_time: 0.0302 memory: 21547 grad_norm: 4.7622 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0513 loss: 1.0513 2022/10/10 10:18:06 - mmengine - INFO - Epoch(train) [90][540/940] lr: 1.0000e-04 eta: 1:22:49 time: 0.4557 data_time: 0.0364 memory: 21547 grad_norm: 4.9277 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2613 loss: 1.2613 2022/10/10 10:18:16 - mmengine - INFO - Epoch(train) [90][560/940] lr: 1.0000e-04 eta: 1:22:39 time: 0.4787 data_time: 0.0301 memory: 21547 grad_norm: 4.7904 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9777 loss: 0.9777 2022/10/10 10:18:26 - mmengine - INFO - Epoch(train) [90][580/940] lr: 1.0000e-04 eta: 1:22:29 time: 0.5291 data_time: 0.0259 memory: 21547 grad_norm: 4.8067 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2144 loss: 1.2144 2022/10/10 10:18:36 - mmengine - INFO - Epoch(train) [90][600/940] lr: 1.0000e-04 eta: 1:22:18 time: 0.4919 data_time: 0.0338 memory: 21547 grad_norm: 4.8174 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.1751 loss: 1.1751 2022/10/10 10:18:46 - mmengine - INFO - Epoch(train) [90][620/940] lr: 1.0000e-04 eta: 1:22:08 time: 0.4752 data_time: 0.0266 memory: 21547 grad_norm: 4.7910 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.0836 loss: 1.0836 2022/10/10 10:18:55 - mmengine - INFO - Epoch(train) [90][640/940] lr: 1.0000e-04 eta: 1:21:58 time: 0.4923 data_time: 0.0276 memory: 21547 grad_norm: 4.7820 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1211 loss: 1.1211 2022/10/10 10:19:06 - mmengine - INFO - Epoch(train) [90][660/940] lr: 1.0000e-04 eta: 1:21:48 time: 0.5320 data_time: 0.0278 memory: 21547 grad_norm: 4.8220 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1719 loss: 1.1719 2022/10/10 10:19:16 - mmengine - INFO - Epoch(train) [90][680/940] lr: 1.0000e-04 eta: 1:21:38 time: 0.4970 data_time: 0.0276 memory: 21547 grad_norm: 4.7525 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1116 loss: 1.1116 2022/10/10 10:19:26 - mmengine - INFO - Epoch(train) [90][700/940] lr: 1.0000e-04 eta: 1:21:28 time: 0.5237 data_time: 0.0304 memory: 21547 grad_norm: 4.7961 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2216 loss: 1.2216 2022/10/10 10:19:36 - mmengine - INFO - Epoch(train) [90][720/940] lr: 1.0000e-04 eta: 1:21:18 time: 0.4907 data_time: 0.0223 memory: 21547 grad_norm: 4.6762 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1995 loss: 1.1995 2022/10/10 10:19:46 - mmengine - INFO - Epoch(train) [90][740/940] lr: 1.0000e-04 eta: 1:21:07 time: 0.4732 data_time: 0.0289 memory: 21547 grad_norm: 4.6778 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0906 loss: 1.0906 2022/10/10 10:19:57 - mmengine - INFO - Epoch(train) [90][760/940] lr: 1.0000e-04 eta: 1:20:57 time: 0.5518 data_time: 0.0233 memory: 21547 grad_norm: 4.8180 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1128 loss: 1.1128 2022/10/10 10:20:07 - mmengine - INFO - Epoch(train) [90][780/940] lr: 1.0000e-04 eta: 1:20:47 time: 0.5082 data_time: 0.0305 memory: 21547 grad_norm: 4.8122 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2416 loss: 1.2416 2022/10/10 10:20:17 - mmengine - INFO - Epoch(train) [90][800/940] lr: 1.0000e-04 eta: 1:20:37 time: 0.5103 data_time: 0.0270 memory: 21547 grad_norm: 4.8201 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1938 loss: 1.1938 2022/10/10 10:20:26 - mmengine - INFO - Epoch(train) [90][820/940] lr: 1.0000e-04 eta: 1:20:27 time: 0.4623 data_time: 0.0327 memory: 21547 grad_norm: 4.7988 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1685 loss: 1.1685 2022/10/10 10:20:37 - mmengine - INFO - Epoch(train) [90][840/940] lr: 1.0000e-04 eta: 1:20:17 time: 0.5261 data_time: 0.0269 memory: 21547 grad_norm: 4.8632 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1677 loss: 1.1677 2022/10/10 10:20:46 - mmengine - INFO - Epoch(train) [90][860/940] lr: 1.0000e-04 eta: 1:20:06 time: 0.4789 data_time: 0.0289 memory: 21547 grad_norm: 4.8443 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1880 loss: 1.1880 2022/10/10 10:20:57 - mmengine - INFO - Epoch(train) [90][880/940] lr: 1.0000e-04 eta: 1:19:56 time: 0.5023 data_time: 0.0316 memory: 21547 grad_norm: 4.7337 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.1602 loss: 1.1602 2022/10/10 10:21:08 - mmengine - INFO - Epoch(train) [90][900/940] lr: 1.0000e-04 eta: 1:19:46 time: 0.5563 data_time: 0.0282 memory: 21547 grad_norm: 4.8769 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3312 loss: 1.3312 2022/10/10 10:21:17 - mmengine - INFO - Epoch(train) [90][920/940] lr: 1.0000e-04 eta: 1:19:36 time: 0.4742 data_time: 0.0270 memory: 21547 grad_norm: 4.8610 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1296 loss: 1.1296 2022/10/10 10:21:27 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 10:21:27 - mmengine - INFO - Epoch(train) [90][940/940] lr: 1.0000e-04 eta: 1:19:26 time: 0.4889 data_time: 0.0243 memory: 21547 grad_norm: 4.9909 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.0743 loss: 1.0743 2022/10/10 10:21:27 - mmengine - INFO - Saving checkpoint at 90 epochs 2022/10/10 10:21:40 - mmengine - INFO - Epoch(val) [90][20/78] eta: 0:00:35 time: 0.6142 data_time: 0.5096 memory: 3269 2022/10/10 10:21:49 - mmengine - INFO - Epoch(val) [90][40/78] eta: 0:00:16 time: 0.4220 data_time: 0.3176 memory: 3269 2022/10/10 10:22:00 - mmengine - INFO - Epoch(val) [90][60/78] eta: 0:00:10 time: 0.5634 data_time: 0.4588 memory: 3269 2022/10/10 10:22:09 - mmengine - INFO - Epoch(val) [90][78/78] acc/top1: 0.6801 acc/top5: 0.8718 acc/mean1: 0.6800 2022/10/10 10:22:23 - mmengine - INFO - Epoch(train) [91][20/940] lr: 1.0000e-04 eta: 1:19:16 time: 0.7175 data_time: 0.1975 memory: 21547 grad_norm: 4.7790 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2240 loss: 1.2240 2022/10/10 10:22:33 - mmengine - INFO - Epoch(train) [91][40/940] lr: 1.0000e-04 eta: 1:19:06 time: 0.5139 data_time: 0.0207 memory: 21547 grad_norm: 4.8286 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1516 loss: 1.1516 2022/10/10 10:22:44 - mmengine - INFO - Epoch(train) [91][60/940] lr: 1.0000e-04 eta: 1:18:56 time: 0.5167 data_time: 0.0287 memory: 21547 grad_norm: 4.7581 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0812 loss: 1.0812 2022/10/10 10:22:53 - mmengine - INFO - Epoch(train) [91][80/940] lr: 1.0000e-04 eta: 1:18:46 time: 0.4673 data_time: 0.0242 memory: 21547 grad_norm: 4.8168 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2491 loss: 1.2491 2022/10/10 10:23:04 - mmengine - INFO - Epoch(train) [91][100/940] lr: 1.0000e-04 eta: 1:18:36 time: 0.5410 data_time: 0.0254 memory: 21547 grad_norm: 4.8021 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1564 loss: 1.1564 2022/10/10 10:23:13 - mmengine - INFO - Epoch(train) [91][120/940] lr: 1.0000e-04 eta: 1:18:25 time: 0.4686 data_time: 0.0245 memory: 21547 grad_norm: 4.8369 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0994 loss: 1.0994 2022/10/10 10:23:24 - mmengine - INFO - Epoch(train) [91][140/940] lr: 1.0000e-04 eta: 1:18:15 time: 0.5295 data_time: 0.0301 memory: 21547 grad_norm: 4.7958 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0692 loss: 1.0692 2022/10/10 10:23:33 - mmengine - INFO - Epoch(train) [91][160/940] lr: 1.0000e-04 eta: 1:18:05 time: 0.4469 data_time: 0.0356 memory: 21547 grad_norm: 4.8000 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0221 loss: 1.0221 2022/10/10 10:23:43 - mmengine - INFO - Epoch(train) [91][180/940] lr: 1.0000e-04 eta: 1:17:55 time: 0.5270 data_time: 0.0239 memory: 21547 grad_norm: 4.7942 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0715 loss: 1.0715 2022/10/10 10:23:54 - mmengine - INFO - Epoch(train) [91][200/940] lr: 1.0000e-04 eta: 1:17:45 time: 0.5050 data_time: 0.0251 memory: 21547 grad_norm: 4.7605 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0492 loss: 1.0492 2022/10/10 10:24:04 - mmengine - INFO - Epoch(train) [91][220/940] lr: 1.0000e-04 eta: 1:17:35 time: 0.5046 data_time: 0.0287 memory: 21547 grad_norm: 4.8683 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1228 loss: 1.1228 2022/10/10 10:24:14 - mmengine - INFO - Epoch(train) [91][240/940] lr: 1.0000e-04 eta: 1:17:25 time: 0.5136 data_time: 0.0239 memory: 21547 grad_norm: 4.7837 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1432 loss: 1.1432 2022/10/10 10:24:24 - mmengine - INFO - Epoch(train) [91][260/940] lr: 1.0000e-04 eta: 1:17:14 time: 0.5024 data_time: 0.0276 memory: 21547 grad_norm: 4.8456 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0555 loss: 1.0555 2022/10/10 10:24:34 - mmengine - INFO - Epoch(train) [91][280/940] lr: 1.0000e-04 eta: 1:17:04 time: 0.4941 data_time: 0.0320 memory: 21547 grad_norm: 4.8168 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1155 loss: 1.1155 2022/10/10 10:24:44 - mmengine - INFO - Epoch(train) [91][300/940] lr: 1.0000e-04 eta: 1:16:54 time: 0.5277 data_time: 0.0308 memory: 21547 grad_norm: 4.7770 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1902 loss: 1.1902 2022/10/10 10:24:54 - mmengine - INFO - Epoch(train) [91][320/940] lr: 1.0000e-04 eta: 1:16:44 time: 0.4903 data_time: 0.0234 memory: 21547 grad_norm: 4.7159 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1705 loss: 1.1705 2022/10/10 10:25:05 - mmengine - INFO - Epoch(train) [91][340/940] lr: 1.0000e-04 eta: 1:16:34 time: 0.5242 data_time: 0.0331 memory: 21547 grad_norm: 4.8455 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0789 loss: 1.0789 2022/10/10 10:25:14 - mmengine - INFO - Epoch(train) [91][360/940] lr: 1.0000e-04 eta: 1:16:24 time: 0.4769 data_time: 0.0247 memory: 21547 grad_norm: 4.9238 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1798 loss: 1.1798 2022/10/10 10:25:25 - mmengine - INFO - Epoch(train) [91][380/940] lr: 1.0000e-04 eta: 1:16:14 time: 0.5532 data_time: 0.0311 memory: 21547 grad_norm: 4.7848 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1731 loss: 1.1731 2022/10/10 10:25:34 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 10:25:34 - mmengine - INFO - Epoch(train) [91][400/940] lr: 1.0000e-04 eta: 1:16:03 time: 0.4431 data_time: 0.0231 memory: 21547 grad_norm: 4.7372 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1261 loss: 1.1261 2022/10/10 10:25:45 - mmengine - INFO - Epoch(train) [91][420/940] lr: 1.0000e-04 eta: 1:15:53 time: 0.5638 data_time: 0.0275 memory: 21547 grad_norm: 4.8357 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2409 loss: 1.2409 2022/10/10 10:25:55 - mmengine - INFO - Epoch(train) [91][440/940] lr: 1.0000e-04 eta: 1:15:43 time: 0.4723 data_time: 0.0223 memory: 21547 grad_norm: 4.8392 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1243 loss: 1.1243 2022/10/10 10:26:06 - mmengine - INFO - Epoch(train) [91][460/940] lr: 1.0000e-04 eta: 1:15:33 time: 0.5786 data_time: 0.0277 memory: 21547 grad_norm: 4.8055 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0341 loss: 1.0341 2022/10/10 10:26:16 - mmengine - INFO - Epoch(train) [91][480/940] lr: 1.0000e-04 eta: 1:15:23 time: 0.4883 data_time: 0.0218 memory: 21547 grad_norm: 4.8113 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9957 loss: 0.9957 2022/10/10 10:26:26 - mmengine - INFO - Epoch(train) [91][500/940] lr: 1.0000e-04 eta: 1:15:13 time: 0.5065 data_time: 0.0248 memory: 21547 grad_norm: 4.7987 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.1821 loss: 1.1821 2022/10/10 10:26:36 - mmengine - INFO - Epoch(train) [91][520/940] lr: 1.0000e-04 eta: 1:15:03 time: 0.4640 data_time: 0.0335 memory: 21547 grad_norm: 4.9002 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1881 loss: 1.1881 2022/10/10 10:26:46 - mmengine - INFO - Epoch(train) [91][540/940] lr: 1.0000e-04 eta: 1:14:52 time: 0.5202 data_time: 0.0228 memory: 21547 grad_norm: 4.8035 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1389 loss: 1.1389 2022/10/10 10:26:56 - mmengine - INFO - Epoch(train) [91][560/940] lr: 1.0000e-04 eta: 1:14:42 time: 0.4818 data_time: 0.0285 memory: 21547 grad_norm: 4.8567 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0899 loss: 1.0899 2022/10/10 10:27:05 - mmengine - INFO - Epoch(train) [91][580/940] lr: 1.0000e-04 eta: 1:14:32 time: 0.4763 data_time: 0.0271 memory: 21547 grad_norm: 4.7700 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1638 loss: 1.1638 2022/10/10 10:27:16 - mmengine - INFO - Epoch(train) [91][600/940] lr: 1.0000e-04 eta: 1:14:22 time: 0.5151 data_time: 0.0295 memory: 21547 grad_norm: 4.6774 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.0281 loss: 1.0281 2022/10/10 10:27:26 - mmengine - INFO - Epoch(train) [91][620/940] lr: 1.0000e-04 eta: 1:14:12 time: 0.5117 data_time: 0.0284 memory: 21547 grad_norm: 4.6973 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1707 loss: 1.1707 2022/10/10 10:27:36 - mmengine - INFO - Epoch(train) [91][640/940] lr: 1.0000e-04 eta: 1:14:02 time: 0.4941 data_time: 0.0308 memory: 21547 grad_norm: 4.9283 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2932 loss: 1.2932 2022/10/10 10:27:45 - mmengine - INFO - Epoch(train) [91][660/940] lr: 1.0000e-04 eta: 1:13:51 time: 0.4737 data_time: 0.0292 memory: 21547 grad_norm: 4.7739 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2299 loss: 1.2299 2022/10/10 10:27:55 - mmengine - INFO - Epoch(train) [91][680/940] lr: 1.0000e-04 eta: 1:13:41 time: 0.5086 data_time: 0.0360 memory: 21547 grad_norm: 4.8213 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1048 loss: 1.1048 2022/10/10 10:28:05 - mmengine - INFO - Epoch(train) [91][700/940] lr: 1.0000e-04 eta: 1:13:31 time: 0.5058 data_time: 0.0276 memory: 21547 grad_norm: 4.8094 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1608 loss: 1.1608 2022/10/10 10:28:16 - mmengine - INFO - Epoch(train) [91][720/940] lr: 1.0000e-04 eta: 1:13:21 time: 0.5066 data_time: 0.0344 memory: 21547 grad_norm: 4.8210 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1400 loss: 1.1400 2022/10/10 10:28:26 - mmengine - INFO - Epoch(train) [91][740/940] lr: 1.0000e-04 eta: 1:13:11 time: 0.4980 data_time: 0.0523 memory: 21547 grad_norm: 4.8399 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1455 loss: 1.1455 2022/10/10 10:28:35 - mmengine - INFO - Epoch(train) [91][760/940] lr: 1.0000e-04 eta: 1:13:01 time: 0.4722 data_time: 0.0353 memory: 21547 grad_norm: 4.6938 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0847 loss: 1.0847 2022/10/10 10:28:45 - mmengine - INFO - Epoch(train) [91][780/940] lr: 1.0000e-04 eta: 1:12:50 time: 0.5207 data_time: 0.0252 memory: 21547 grad_norm: 4.6908 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.0522 loss: 1.0522 2022/10/10 10:28:56 - mmengine - INFO - Epoch(train) [91][800/940] lr: 1.0000e-04 eta: 1:12:40 time: 0.5148 data_time: 0.0352 memory: 21547 grad_norm: 4.8056 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1812 loss: 1.1812 2022/10/10 10:29:07 - mmengine - INFO - Epoch(train) [91][820/940] lr: 1.0000e-04 eta: 1:12:30 time: 0.5431 data_time: 0.0261 memory: 21547 grad_norm: 4.8496 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2361 loss: 1.2361 2022/10/10 10:29:16 - mmengine - INFO - Epoch(train) [91][840/940] lr: 1.0000e-04 eta: 1:12:20 time: 0.4704 data_time: 0.0270 memory: 21547 grad_norm: 4.7179 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.0533 loss: 1.0533 2022/10/10 10:29:26 - mmengine - INFO - Epoch(train) [91][860/940] lr: 1.0000e-04 eta: 1:12:10 time: 0.4858 data_time: 0.0283 memory: 21547 grad_norm: 4.8590 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1981 loss: 1.1981 2022/10/10 10:29:36 - mmengine - INFO - Epoch(train) [91][880/940] lr: 1.0000e-04 eta: 1:12:00 time: 0.5207 data_time: 0.0312 memory: 21547 grad_norm: 4.7629 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1801 loss: 1.1801 2022/10/10 10:29:46 - mmengine - INFO - Epoch(train) [91][900/940] lr: 1.0000e-04 eta: 1:11:50 time: 0.4799 data_time: 0.0319 memory: 21547 grad_norm: 4.9048 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3029 loss: 1.3029 2022/10/10 10:29:56 - mmengine - INFO - Epoch(train) [91][920/940] lr: 1.0000e-04 eta: 1:11:39 time: 0.4930 data_time: 0.0253 memory: 21547 grad_norm: 4.9065 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1158 loss: 1.1158 2022/10/10 10:30:04 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 10:30:04 - mmengine - INFO - Epoch(train) [91][940/940] lr: 1.0000e-04 eta: 1:11:29 time: 0.4258 data_time: 0.0225 memory: 21547 grad_norm: 5.1031 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.1011 loss: 1.1011 2022/10/10 10:30:16 - mmengine - INFO - Epoch(val) [91][20/78] eta: 0:00:35 time: 0.6063 data_time: 0.4940 memory: 3269 2022/10/10 10:30:25 - mmengine - INFO - Epoch(val) [91][40/78] eta: 0:00:15 time: 0.4202 data_time: 0.3128 memory: 3269 2022/10/10 10:30:36 - mmengine - INFO - Epoch(val) [91][60/78] eta: 0:00:10 time: 0.5595 data_time: 0.4526 memory: 3269 2022/10/10 10:30:46 - mmengine - INFO - Epoch(val) [91][78/78] acc/top1: 0.6812 acc/top5: 0.8718 acc/mean1: 0.6811 2022/10/10 10:30:46 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_86.pth is removed 2022/10/10 10:30:47 - mmengine - INFO - The best checkpoint with 0.6812 acc/top1 at 91 epoch is saved to best_acc/top1_epoch_91.pth. 2022/10/10 10:31:00 - mmengine - INFO - Epoch(train) [92][20/940] lr: 1.0000e-04 eta: 1:11:19 time: 0.6728 data_time: 0.3037 memory: 21547 grad_norm: 4.6877 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1656 loss: 1.1656 2022/10/10 10:31:11 - mmengine - INFO - Epoch(train) [92][40/940] lr: 1.0000e-04 eta: 1:11:09 time: 0.5264 data_time: 0.1557 memory: 21547 grad_norm: 4.8587 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1014 loss: 1.1014 2022/10/10 10:31:22 - mmengine - INFO - Epoch(train) [92][60/940] lr: 1.0000e-04 eta: 1:10:59 time: 0.5612 data_time: 0.0926 memory: 21547 grad_norm: 4.7579 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2371 loss: 1.2371 2022/10/10 10:31:33 - mmengine - INFO - Epoch(train) [92][80/940] lr: 1.0000e-04 eta: 1:10:49 time: 0.5653 data_time: 0.0255 memory: 21547 grad_norm: 4.8602 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1195 loss: 1.1195 2022/10/10 10:31:43 - mmengine - INFO - Epoch(train) [92][100/940] lr: 1.0000e-04 eta: 1:10:39 time: 0.5017 data_time: 0.0293 memory: 21547 grad_norm: 4.8574 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0725 loss: 1.0725 2022/10/10 10:31:53 - mmengine - INFO - Epoch(train) [92][120/940] lr: 1.0000e-04 eta: 1:10:29 time: 0.4899 data_time: 0.0307 memory: 21547 grad_norm: 4.7768 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2181 loss: 1.2181 2022/10/10 10:32:02 - mmengine - INFO - Epoch(train) [92][140/940] lr: 1.0000e-04 eta: 1:10:19 time: 0.4736 data_time: 0.0262 memory: 21547 grad_norm: 4.7735 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1441 loss: 1.1441 2022/10/10 10:32:12 - mmengine - INFO - Epoch(train) [92][160/940] lr: 1.0000e-04 eta: 1:10:08 time: 0.4748 data_time: 0.0283 memory: 21547 grad_norm: 4.8812 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1867 loss: 1.1867 2022/10/10 10:32:21 - mmengine - INFO - Epoch(train) [92][180/940] lr: 1.0000e-04 eta: 1:09:58 time: 0.4709 data_time: 0.0361 memory: 21547 grad_norm: 4.7302 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1306 loss: 1.1306 2022/10/10 10:32:32 - mmengine - INFO - Epoch(train) [92][200/940] lr: 1.0000e-04 eta: 1:09:48 time: 0.5419 data_time: 0.0291 memory: 21547 grad_norm: 4.7677 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1073 loss: 1.1073 2022/10/10 10:32:42 - mmengine - INFO - Epoch(train) [92][220/940] lr: 1.0000e-04 eta: 1:09:38 time: 0.4953 data_time: 0.0334 memory: 21547 grad_norm: 4.8147 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1939 loss: 1.1939 2022/10/10 10:32:53 - mmengine - INFO - Epoch(train) [92][240/940] lr: 1.0000e-04 eta: 1:09:28 time: 0.5368 data_time: 0.0282 memory: 21547 grad_norm: 4.7129 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1472 loss: 1.1472 2022/10/10 10:33:03 - mmengine - INFO - Epoch(train) [92][260/940] lr: 1.0000e-04 eta: 1:09:18 time: 0.4942 data_time: 0.0290 memory: 21547 grad_norm: 4.8001 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1458 loss: 1.1458 2022/10/10 10:33:14 - mmengine - INFO - Epoch(train) [92][280/940] lr: 1.0000e-04 eta: 1:09:08 time: 0.5407 data_time: 0.0317 memory: 21547 grad_norm: 4.8709 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2699 loss: 1.2699 2022/10/10 10:33:23 - mmengine - INFO - Epoch(train) [92][300/940] lr: 1.0000e-04 eta: 1:08:57 time: 0.4732 data_time: 0.0313 memory: 21547 grad_norm: 4.7865 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1876 loss: 1.1876 2022/10/10 10:33:34 - mmengine - INFO - Epoch(train) [92][320/940] lr: 1.0000e-04 eta: 1:08:47 time: 0.5351 data_time: 0.0299 memory: 21547 grad_norm: 4.8058 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2829 loss: 1.2829 2022/10/10 10:33:43 - mmengine - INFO - Epoch(train) [92][340/940] lr: 1.0000e-04 eta: 1:08:37 time: 0.4534 data_time: 0.0299 memory: 21547 grad_norm: 4.8689 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.1193 loss: 1.1193 2022/10/10 10:33:53 - mmengine - INFO - Epoch(train) [92][360/940] lr: 1.0000e-04 eta: 1:08:27 time: 0.5321 data_time: 0.0308 memory: 21547 grad_norm: 4.8542 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.0863 loss: 1.0863 2022/10/10 10:34:03 - mmengine - INFO - Epoch(train) [92][380/940] lr: 1.0000e-04 eta: 1:08:17 time: 0.5032 data_time: 0.0247 memory: 21547 grad_norm: 4.8670 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1826 loss: 1.1826 2022/10/10 10:34:14 - mmengine - INFO - Epoch(train) [92][400/940] lr: 1.0000e-04 eta: 1:08:07 time: 0.5325 data_time: 0.0247 memory: 21547 grad_norm: 4.8181 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1855 loss: 1.1855 2022/10/10 10:34:24 - mmengine - INFO - Epoch(train) [92][420/940] lr: 1.0000e-04 eta: 1:07:57 time: 0.4956 data_time: 0.0245 memory: 21547 grad_norm: 4.8605 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2892 loss: 1.2892 2022/10/10 10:34:34 - mmengine - INFO - Epoch(train) [92][440/940] lr: 1.0000e-04 eta: 1:07:46 time: 0.4861 data_time: 0.0328 memory: 21547 grad_norm: 4.8212 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2279 loss: 1.2279 2022/10/10 10:34:43 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 10:34:43 - mmengine - INFO - Epoch(train) [92][460/940] lr: 1.0000e-04 eta: 1:07:36 time: 0.4618 data_time: 0.0231 memory: 21547 grad_norm: 4.7896 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1531 loss: 1.1531 2022/10/10 10:34:54 - mmengine - INFO - Epoch(train) [92][480/940] lr: 1.0000e-04 eta: 1:07:26 time: 0.5455 data_time: 0.0303 memory: 21547 grad_norm: 4.8733 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2518 loss: 1.2518 2022/10/10 10:35:04 - mmengine - INFO - Epoch(train) [92][500/940] lr: 1.0000e-04 eta: 1:07:16 time: 0.4875 data_time: 0.0277 memory: 21547 grad_norm: 4.8939 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0878 loss: 1.0878 2022/10/10 10:35:14 - mmengine - INFO - Epoch(train) [92][520/940] lr: 1.0000e-04 eta: 1:07:06 time: 0.5208 data_time: 0.0249 memory: 21547 grad_norm: 4.7622 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0655 loss: 1.0655 2022/10/10 10:35:25 - mmengine - INFO - Epoch(train) [92][540/940] lr: 1.0000e-04 eta: 1:06:56 time: 0.5216 data_time: 0.0256 memory: 21547 grad_norm: 4.7582 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1707 loss: 1.1707 2022/10/10 10:35:35 - mmengine - INFO - Epoch(train) [92][560/940] lr: 1.0000e-04 eta: 1:06:46 time: 0.5387 data_time: 0.0287 memory: 21547 grad_norm: 4.7589 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0203 loss: 1.0203 2022/10/10 10:35:45 - mmengine - INFO - Epoch(train) [92][580/940] lr: 1.0000e-04 eta: 1:06:35 time: 0.4943 data_time: 0.0247 memory: 21547 grad_norm: 4.8031 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1783 loss: 1.1783 2022/10/10 10:35:55 - mmengine - INFO - Epoch(train) [92][600/940] lr: 1.0000e-04 eta: 1:06:25 time: 0.4923 data_time: 0.0277 memory: 21547 grad_norm: 4.7990 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0110 loss: 1.0110 2022/10/10 10:36:06 - mmengine - INFO - Epoch(train) [92][620/940] lr: 1.0000e-04 eta: 1:06:15 time: 0.5262 data_time: 0.0290 memory: 21547 grad_norm: 4.7356 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1082 loss: 1.1082 2022/10/10 10:36:15 - mmengine - INFO - Epoch(train) [92][640/940] lr: 1.0000e-04 eta: 1:06:05 time: 0.4854 data_time: 0.0309 memory: 21547 grad_norm: 4.9326 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1735 loss: 1.1735 2022/10/10 10:36:25 - mmengine - INFO - Epoch(train) [92][660/940] lr: 1.0000e-04 eta: 1:05:55 time: 0.4866 data_time: 0.0312 memory: 21547 grad_norm: 4.7435 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1770 loss: 1.1770 2022/10/10 10:36:34 - mmengine - INFO - Epoch(train) [92][680/940] lr: 1.0000e-04 eta: 1:05:45 time: 0.4602 data_time: 0.0268 memory: 21547 grad_norm: 4.7154 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2448 loss: 1.2448 2022/10/10 10:36:45 - mmengine - INFO - Epoch(train) [92][700/940] lr: 1.0000e-04 eta: 1:05:34 time: 0.5311 data_time: 0.0261 memory: 21547 grad_norm: 4.7762 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.0841 loss: 1.0841 2022/10/10 10:36:55 - mmengine - INFO - Epoch(train) [92][720/940] lr: 1.0000e-04 eta: 1:05:24 time: 0.4915 data_time: 0.0265 memory: 21547 grad_norm: 4.8651 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1043 loss: 1.1043 2022/10/10 10:37:05 - mmengine - INFO - Epoch(train) [92][740/940] lr: 1.0000e-04 eta: 1:05:14 time: 0.5087 data_time: 0.0276 memory: 21547 grad_norm: 4.8164 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2358 loss: 1.2358 2022/10/10 10:37:15 - mmengine - INFO - Epoch(train) [92][760/940] lr: 1.0000e-04 eta: 1:05:04 time: 0.4948 data_time: 0.0259 memory: 21547 grad_norm: 4.8060 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1258 loss: 1.1258 2022/10/10 10:37:25 - mmengine - INFO - Epoch(train) [92][780/940] lr: 1.0000e-04 eta: 1:04:54 time: 0.5001 data_time: 0.0318 memory: 21547 grad_norm: 4.7391 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.0232 loss: 1.0232 2022/10/10 10:37:34 - mmengine - INFO - Epoch(train) [92][800/940] lr: 1.0000e-04 eta: 1:04:44 time: 0.4640 data_time: 0.0276 memory: 21547 grad_norm: 4.7886 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0923 loss: 1.0923 2022/10/10 10:37:45 - mmengine - INFO - Epoch(train) [92][820/940] lr: 1.0000e-04 eta: 1:04:34 time: 0.5417 data_time: 0.0235 memory: 21547 grad_norm: 4.9122 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2118 loss: 1.2118 2022/10/10 10:37:54 - mmengine - INFO - Epoch(train) [92][840/940] lr: 1.0000e-04 eta: 1:04:23 time: 0.4590 data_time: 0.0311 memory: 21547 grad_norm: 4.8672 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1370 loss: 1.1370 2022/10/10 10:38:04 - mmengine - INFO - Epoch(train) [92][860/940] lr: 1.0000e-04 eta: 1:04:13 time: 0.5203 data_time: 0.0248 memory: 21547 grad_norm: 4.7346 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0607 loss: 1.0607 2022/10/10 10:38:15 - mmengine - INFO - Epoch(train) [92][880/940] lr: 1.0000e-04 eta: 1:04:03 time: 0.5072 data_time: 0.0283 memory: 21547 grad_norm: 4.9124 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1283 loss: 1.1283 2022/10/10 10:38:24 - mmengine - INFO - Epoch(train) [92][900/940] lr: 1.0000e-04 eta: 1:03:53 time: 0.4716 data_time: 0.0298 memory: 21547 grad_norm: 4.9083 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1777 loss: 1.1777 2022/10/10 10:38:35 - mmengine - INFO - Epoch(train) [92][920/940] lr: 1.0000e-04 eta: 1:03:43 time: 0.5421 data_time: 0.0313 memory: 21547 grad_norm: 4.9697 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1962 loss: 1.1962 2022/10/10 10:38:44 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 10:38:44 - mmengine - INFO - Epoch(train) [92][940/940] lr: 1.0000e-04 eta: 1:03:32 time: 0.4342 data_time: 0.0229 memory: 21547 grad_norm: 4.9882 top1_acc: 0.2857 top5_acc: 1.0000 loss_cls: 1.1646 loss: 1.1646 2022/10/10 10:38:56 - mmengine - INFO - Epoch(val) [92][20/78] eta: 0:00:34 time: 0.6032 data_time: 0.4950 memory: 3269 2022/10/10 10:39:04 - mmengine - INFO - Epoch(val) [92][40/78] eta: 0:00:16 time: 0.4223 data_time: 0.3143 memory: 3269 2022/10/10 10:39:15 - mmengine - INFO - Epoch(val) [92][60/78] eta: 0:00:09 time: 0.5479 data_time: 0.4427 memory: 3269 2022/10/10 10:39:25 - mmengine - INFO - Epoch(val) [92][78/78] acc/top1: 0.6820 acc/top5: 0.8705 acc/mean1: 0.6818 2022/10/10 10:39:25 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph/best_acc/top1_epoch_91.pth is removed 2022/10/10 10:39:26 - mmengine - INFO - The best checkpoint with 0.6820 acc/top1 at 92 epoch is saved to best_acc/top1_epoch_92.pth. 2022/10/10 10:39:39 - mmengine - INFO - Epoch(train) [93][20/940] lr: 1.0000e-04 eta: 1:03:23 time: 0.6818 data_time: 0.2850 memory: 21547 grad_norm: 4.7740 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1238 loss: 1.1238 2022/10/10 10:39:50 - mmengine - INFO - Epoch(train) [93][40/940] lr: 1.0000e-04 eta: 1:03:13 time: 0.5084 data_time: 0.1029 memory: 21547 grad_norm: 4.7644 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1544 loss: 1.1544 2022/10/10 10:40:00 - mmengine - INFO - Epoch(train) [93][60/940] lr: 1.0000e-04 eta: 1:03:02 time: 0.5113 data_time: 0.0766 memory: 21547 grad_norm: 4.9104 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0915 loss: 1.0915 2022/10/10 10:40:09 - mmengine - INFO - Epoch(train) [93][80/940] lr: 1.0000e-04 eta: 1:02:52 time: 0.4590 data_time: 0.0233 memory: 21547 grad_norm: 4.8022 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1736 loss: 1.1736 2022/10/10 10:40:19 - mmengine - INFO - Epoch(train) [93][100/940] lr: 1.0000e-04 eta: 1:02:42 time: 0.5212 data_time: 0.0490 memory: 21547 grad_norm: 4.8606 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2230 loss: 1.2230 2022/10/10 10:40:29 - mmengine - INFO - Epoch(train) [93][120/940] lr: 1.0000e-04 eta: 1:02:32 time: 0.4872 data_time: 0.0307 memory: 21547 grad_norm: 4.8006 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1703 loss: 1.1703 2022/10/10 10:40:41 - mmengine - INFO - Epoch(train) [93][140/940] lr: 1.0000e-04 eta: 1:02:22 time: 0.5718 data_time: 0.0276 memory: 21547 grad_norm: 4.8600 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1577 loss: 1.1577 2022/10/10 10:40:50 - mmengine - INFO - Epoch(train) [93][160/940] lr: 1.0000e-04 eta: 1:02:12 time: 0.4469 data_time: 0.0331 memory: 21547 grad_norm: 4.8149 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1139 loss: 1.1139 2022/10/10 10:41:00 - mmengine - INFO - Epoch(train) [93][180/940] lr: 1.0000e-04 eta: 1:02:01 time: 0.5362 data_time: 0.0264 memory: 21547 grad_norm: 4.8182 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0825 loss: 1.0825 2022/10/10 10:41:10 - mmengine - INFO - Epoch(train) [93][200/940] lr: 1.0000e-04 eta: 1:01:51 time: 0.4756 data_time: 0.0303 memory: 21547 grad_norm: 4.9732 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2085 loss: 1.2085 2022/10/10 10:41:20 - mmengine - INFO - Epoch(train) [93][220/940] lr: 1.0000e-04 eta: 1:01:41 time: 0.5166 data_time: 0.0277 memory: 21547 grad_norm: 4.8342 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1205 loss: 1.1205 2022/10/10 10:41:31 - mmengine - INFO - Epoch(train) [93][240/940] lr: 1.0000e-04 eta: 1:01:31 time: 0.5279 data_time: 0.0281 memory: 21547 grad_norm: 4.8800 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1347 loss: 1.1347 2022/10/10 10:41:40 - mmengine - INFO - Epoch(train) [93][260/940] lr: 1.0000e-04 eta: 1:01:21 time: 0.4828 data_time: 0.0300 memory: 21547 grad_norm: 4.8509 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1177 loss: 1.1177 2022/10/10 10:41:50 - mmengine - INFO - Epoch(train) [93][280/940] lr: 1.0000e-04 eta: 1:01:11 time: 0.4860 data_time: 0.0298 memory: 21547 grad_norm: 4.8502 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.0911 loss: 1.0911 2022/10/10 10:42:01 - mmengine - INFO - Epoch(train) [93][300/940] lr: 1.0000e-04 eta: 1:01:01 time: 0.5347 data_time: 0.0311 memory: 21547 grad_norm: 4.6972 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1260 loss: 1.1260 2022/10/10 10:42:11 - mmengine - INFO - Epoch(train) [93][320/940] lr: 1.0000e-04 eta: 1:00:50 time: 0.4924 data_time: 0.0260 memory: 21547 grad_norm: 4.7610 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2419 loss: 1.2419 2022/10/10 10:42:22 - mmengine - INFO - Epoch(train) [93][340/940] lr: 1.0000e-04 eta: 1:00:40 time: 0.5811 data_time: 0.0274 memory: 21547 grad_norm: 4.7036 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1657 loss: 1.1657 2022/10/10 10:42:33 - mmengine - INFO - Epoch(train) [93][360/940] lr: 1.0000e-04 eta: 1:00:30 time: 0.5237 data_time: 0.0215 memory: 21547 grad_norm: 4.7761 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0920 loss: 1.0920 2022/10/10 10:42:42 - mmengine - INFO - Epoch(train) [93][380/940] lr: 1.0000e-04 eta: 1:00:20 time: 0.4387 data_time: 0.0272 memory: 21547 grad_norm: 4.7425 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1347 loss: 1.1347 2022/10/10 10:42:53 - mmengine - INFO - Epoch(train) [93][400/940] lr: 1.0000e-04 eta: 1:00:10 time: 0.5626 data_time: 0.0232 memory: 21547 grad_norm: 4.8513 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1065 loss: 1.1065 2022/10/10 10:43:03 - mmengine - INFO - Epoch(train) [93][420/940] lr: 1.0000e-04 eta: 1:00:00 time: 0.5036 data_time: 0.0221 memory: 21547 grad_norm: 4.8169 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1895 loss: 1.1895 2022/10/10 10:43:13 - mmengine - INFO - Epoch(train) [93][440/940] lr: 1.0000e-04 eta: 0:59:50 time: 0.5165 data_time: 0.0301 memory: 21547 grad_norm: 4.8056 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1895 loss: 1.1895 2022/10/10 10:43:23 - mmengine - INFO - Epoch(train) [93][460/940] lr: 1.0000e-04 eta: 0:59:40 time: 0.4928 data_time: 0.0248 memory: 21547 grad_norm: 4.8237 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1136 loss: 1.1136 2022/10/10 10:43:34 - mmengine - INFO - Epoch(train) [93][480/940] lr: 1.0000e-04 eta: 0:59:29 time: 0.5216 data_time: 0.0281 memory: 21547 grad_norm: 4.8149 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0574 loss: 1.0574 2022/10/10 10:43:44 - mmengine - INFO - Epoch(train) [93][500/940] lr: 1.0000e-04 eta: 0:59:19 time: 0.5018 data_time: 0.0244 memory: 21547 grad_norm: 4.8711 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2095 loss: 1.2095 2022/10/10 10:43:55 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 10:43:55 - mmengine - INFO - Epoch(train) [93][520/940] lr: 1.0000e-04 eta: 0:59:09 time: 0.5665 data_time: 0.0280 memory: 21547 grad_norm: 4.8334 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2337 loss: 1.2337 2022/10/10 10:44:05 - mmengine - INFO - Epoch(train) [93][540/940] lr: 1.0000e-04 eta: 0:58:59 time: 0.4879 data_time: 0.0246 memory: 21547 grad_norm: 4.7117 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.0895 loss: 1.0895 2022/10/10 10:44:15 - mmengine - INFO - Epoch(train) [93][560/940] lr: 1.0000e-04 eta: 0:58:49 time: 0.5283 data_time: 0.0302 memory: 21547 grad_norm: 4.8734 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1945 loss: 1.1945 2022/10/10 10:44:25 - mmengine - INFO - Epoch(train) [93][580/940] lr: 1.0000e-04 eta: 0:58:39 time: 0.4845 data_time: 0.0234 memory: 21547 grad_norm: 4.8646 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1224 loss: 1.1224 2022/10/10 10:44:35 - mmengine - INFO - Epoch(train) [93][600/940] lr: 1.0000e-04 eta: 0:58:29 time: 0.4979 data_time: 0.0280 memory: 21547 grad_norm: 4.7904 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1804 loss: 1.1804 2022/10/10 10:44:45 - mmengine - INFO - Epoch(train) [93][620/940] lr: 1.0000e-04 eta: 0:58:18 time: 0.4860 data_time: 0.0303 memory: 21547 grad_norm: 4.7483 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.1744 loss: 1.1744 2022/10/10 10:44:57 - mmengine - INFO - Epoch(train) [93][640/940] lr: 1.0000e-04 eta: 0:58:08 time: 0.6135 data_time: 0.0309 memory: 21547 grad_norm: 4.7970 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1198 loss: 1.1198 2022/10/10 10:45:07 - mmengine - INFO - Epoch(train) [93][660/940] lr: 1.0000e-04 eta: 0:57:58 time: 0.4979 data_time: 0.0291 memory: 21547 grad_norm: 4.8997 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1419 loss: 1.1419 2022/10/10 10:45:18 - mmengine - INFO - Epoch(train) [93][680/940] lr: 1.0000e-04 eta: 0:57:48 time: 0.5369 data_time: 0.0281 memory: 21547 grad_norm: 4.8031 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1341 loss: 1.1341 2022/10/10 10:45:28 - mmengine - INFO - Epoch(train) [93][700/940] lr: 1.0000e-04 eta: 0:57:38 time: 0.4982 data_time: 0.0254 memory: 21547 grad_norm: 4.8351 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1246 loss: 1.1246 2022/10/10 10:45:38 - mmengine - INFO - Epoch(train) [93][720/940] lr: 1.0000e-04 eta: 0:57:28 time: 0.5278 data_time: 0.0216 memory: 21547 grad_norm: 4.6622 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1725 loss: 1.1725 2022/10/10 10:45:48 - mmengine - INFO - Epoch(train) [93][740/940] lr: 1.0000e-04 eta: 0:57:18 time: 0.4849 data_time: 0.0279 memory: 21547 grad_norm: 4.7865 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1466 loss: 1.1466 2022/10/10 10:45:58 - mmengine - INFO - Epoch(train) [93][760/940] lr: 1.0000e-04 eta: 0:57:08 time: 0.5163 data_time: 0.0267 memory: 21547 grad_norm: 4.8007 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1797 loss: 1.1797 2022/10/10 10:46:08 - mmengine - INFO - Epoch(train) [93][780/940] lr: 1.0000e-04 eta: 0:56:57 time: 0.4926 data_time: 0.0323 memory: 21547 grad_norm: 4.7521 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0429 loss: 1.0429 2022/10/10 10:46:18 - mmengine - INFO - Epoch(train) [93][800/940] lr: 1.0000e-04 eta: 0:56:47 time: 0.4917 data_time: 0.0251 memory: 21547 grad_norm: 4.9777 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.1973 loss: 1.1973 2022/10/10 10:46:28 - mmengine - INFO - Epoch(train) [93][820/940] lr: 1.0000e-04 eta: 0:56:37 time: 0.4953 data_time: 0.0285 memory: 21547 grad_norm: 4.7399 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1462 loss: 1.1462 2022/10/10 10:46:37 - mmengine - INFO - Epoch(train) [93][840/940] lr: 1.0000e-04 eta: 0:56:27 time: 0.4681 data_time: 0.0248 memory: 21547 grad_norm: 4.7294 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1089 loss: 1.1089 2022/10/10 10:46:47 - mmengine - INFO - Epoch(train) [93][860/940] lr: 1.0000e-04 eta: 0:56:17 time: 0.5014 data_time: 0.0326 memory: 21547 grad_norm: 4.8601 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1505 loss: 1.1505 2022/10/10 10:46:57 - mmengine - INFO - Epoch(train) [93][880/940] lr: 1.0000e-04 eta: 0:56:07 time: 0.5191 data_time: 0.0249 memory: 21547 grad_norm: 4.9322 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2486 loss: 1.2486 2022/10/10 10:47:08 - mmengine - INFO - Epoch(train) [93][900/940] lr: 1.0000e-04 eta: 0:55:57 time: 0.5219 data_time: 0.0274 memory: 21547 grad_norm: 4.8077 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9975 loss: 0.9975 2022/10/10 10:47:18 - mmengine - INFO - Epoch(train) [93][920/940] lr: 1.0000e-04 eta: 0:55:46 time: 0.4933 data_time: 0.0277 memory: 21547 grad_norm: 4.9103 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2260 loss: 1.2260 2022/10/10 10:47:27 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 10:47:27 - mmengine - INFO - Epoch(train) [93][940/940] lr: 1.0000e-04 eta: 0:55:36 time: 0.4382 data_time: 0.0236 memory: 21547 grad_norm: 5.3046 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.2277 loss: 1.2277 2022/10/10 10:47:27 - mmengine - INFO - Saving checkpoint at 93 epochs 2022/10/10 10:47:40 - mmengine - INFO - Epoch(val) [93][20/78] eta: 0:00:35 time: 0.6078 data_time: 0.5022 memory: 3269 2022/10/10 10:47:48 - mmengine - INFO - Epoch(val) [93][40/78] eta: 0:00:15 time: 0.4166 data_time: 0.3117 memory: 3269 2022/10/10 10:47:59 - mmengine - INFO - Epoch(val) [93][60/78] eta: 0:00:10 time: 0.5646 data_time: 0.4599 memory: 3269 2022/10/10 10:48:08 - mmengine - INFO - Epoch(val) [93][78/78] acc/top1: 0.6810 acc/top5: 0.8718 acc/mean1: 0.6809 2022/10/10 10:48:22 - mmengine - INFO - Epoch(train) [94][20/940] lr: 1.0000e-04 eta: 0:55:26 time: 0.6816 data_time: 0.3059 memory: 21547 grad_norm: 4.8271 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1552 loss: 1.1552 2022/10/10 10:48:32 - mmengine - INFO - Epoch(train) [94][40/940] lr: 1.0000e-04 eta: 0:55:16 time: 0.5180 data_time: 0.1183 memory: 21547 grad_norm: 4.7295 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0539 loss: 1.0539 2022/10/10 10:48:42 - mmengine - INFO - Epoch(train) [94][60/940] lr: 1.0000e-04 eta: 0:55:06 time: 0.5007 data_time: 0.1149 memory: 21547 grad_norm: 4.7900 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.0526 loss: 1.0526 2022/10/10 10:48:52 - mmengine - INFO - Epoch(train) [94][80/940] lr: 1.0000e-04 eta: 0:54:56 time: 0.4751 data_time: 0.0975 memory: 21547 grad_norm: 4.9587 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0909 loss: 1.0909 2022/10/10 10:49:02 - mmengine - INFO - Epoch(train) [94][100/940] lr: 1.0000e-04 eta: 0:54:46 time: 0.5110 data_time: 0.1259 memory: 21547 grad_norm: 4.9431 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0758 loss: 1.0758 2022/10/10 10:49:12 - mmengine - INFO - Epoch(train) [94][120/940] lr: 1.0000e-04 eta: 0:54:36 time: 0.5120 data_time: 0.0711 memory: 21547 grad_norm: 4.7561 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0876 loss: 1.0876 2022/10/10 10:49:23 - mmengine - INFO - Epoch(train) [94][140/940] lr: 1.0000e-04 eta: 0:54:25 time: 0.5430 data_time: 0.0916 memory: 21547 grad_norm: 4.7638 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0845 loss: 1.0845 2022/10/10 10:49:33 - mmengine - INFO - Epoch(train) [94][160/940] lr: 1.0000e-04 eta: 0:54:15 time: 0.4805 data_time: 0.0225 memory: 21547 grad_norm: 4.8669 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1835 loss: 1.1835 2022/10/10 10:49:43 - mmengine - INFO - Epoch(train) [94][180/940] lr: 1.0000e-04 eta: 0:54:05 time: 0.5290 data_time: 0.0314 memory: 21547 grad_norm: 4.9031 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2482 loss: 1.2482 2022/10/10 10:49:53 - mmengine - INFO - Epoch(train) [94][200/940] lr: 1.0000e-04 eta: 0:53:55 time: 0.4786 data_time: 0.0261 memory: 21547 grad_norm: 4.9298 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2802 loss: 1.2802 2022/10/10 10:50:04 - mmengine - INFO - Epoch(train) [94][220/940] lr: 1.0000e-04 eta: 0:53:45 time: 0.5348 data_time: 0.0342 memory: 21547 grad_norm: 4.7502 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1046 loss: 1.1046 2022/10/10 10:50:12 - mmengine - INFO - Epoch(train) [94][240/940] lr: 1.0000e-04 eta: 0:53:35 time: 0.4285 data_time: 0.0243 memory: 21547 grad_norm: 4.8454 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1064 loss: 1.1064 2022/10/10 10:50:23 - mmengine - INFO - Epoch(train) [94][260/940] lr: 1.0000e-04 eta: 0:53:25 time: 0.5342 data_time: 0.0540 memory: 21547 grad_norm: 4.8225 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2339 loss: 1.2339 2022/10/10 10:50:33 - mmengine - INFO - Epoch(train) [94][280/940] lr: 1.0000e-04 eta: 0:53:14 time: 0.4987 data_time: 0.0282 memory: 21547 grad_norm: 4.8426 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0341 loss: 1.0341 2022/10/10 10:50:43 - mmengine - INFO - Epoch(train) [94][300/940] lr: 1.0000e-04 eta: 0:53:04 time: 0.5128 data_time: 0.0345 memory: 21547 grad_norm: 4.7403 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0812 loss: 1.0812 2022/10/10 10:50:53 - mmengine - INFO - Epoch(train) [94][320/940] lr: 1.0000e-04 eta: 0:52:54 time: 0.4771 data_time: 0.0250 memory: 21547 grad_norm: 4.7599 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.1227 loss: 1.1227 2022/10/10 10:51:03 - mmengine - INFO - Epoch(train) [94][340/940] lr: 1.0000e-04 eta: 0:52:44 time: 0.5200 data_time: 0.0331 memory: 21547 grad_norm: 4.7565 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1730 loss: 1.1730 2022/10/10 10:51:13 - mmengine - INFO - Epoch(train) [94][360/940] lr: 1.0000e-04 eta: 0:52:34 time: 0.4913 data_time: 0.0258 memory: 21547 grad_norm: 4.7841 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1464 loss: 1.1464 2022/10/10 10:51:24 - mmengine - INFO - Epoch(train) [94][380/940] lr: 1.0000e-04 eta: 0:52:24 time: 0.5575 data_time: 0.0355 memory: 21547 grad_norm: 4.7722 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1704 loss: 1.1704 2022/10/10 10:51:35 - mmengine - INFO - Epoch(train) [94][400/940] lr: 1.0000e-04 eta: 0:52:14 time: 0.5195 data_time: 0.0259 memory: 21547 grad_norm: 4.8517 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1472 loss: 1.1472 2022/10/10 10:51:45 - mmengine - INFO - Epoch(train) [94][420/940] lr: 1.0000e-04 eta: 0:52:03 time: 0.4994 data_time: 0.0323 memory: 21547 grad_norm: 4.8268 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1663 loss: 1.1663 2022/10/10 10:51:55 - mmengine - INFO - Epoch(train) [94][440/940] lr: 1.0000e-04 eta: 0:51:53 time: 0.5016 data_time: 0.0239 memory: 21547 grad_norm: 4.7594 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1939 loss: 1.1939 2022/10/10 10:52:05 - mmengine - INFO - Epoch(train) [94][460/940] lr: 1.0000e-04 eta: 0:51:43 time: 0.5273 data_time: 0.0314 memory: 21547 grad_norm: 4.8022 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1576 loss: 1.1576 2022/10/10 10:52:14 - mmengine - INFO - Epoch(train) [94][480/940] lr: 1.0000e-04 eta: 0:51:33 time: 0.4576 data_time: 0.0240 memory: 21547 grad_norm: 4.7420 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1904 loss: 1.1904 2022/10/10 10:52:24 - mmengine - INFO - Epoch(train) [94][500/940] lr: 1.0000e-04 eta: 0:51:23 time: 0.4796 data_time: 0.0278 memory: 21547 grad_norm: 4.7386 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2904 loss: 1.2904 2022/10/10 10:52:37 - mmengine - INFO - Epoch(train) [94][520/940] lr: 1.0000e-04 eta: 0:51:13 time: 0.6484 data_time: 0.0289 memory: 21547 grad_norm: 5.0011 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2045 loss: 1.2045 2022/10/10 10:52:46 - mmengine - INFO - Epoch(train) [94][540/940] lr: 1.0000e-04 eta: 0:51:03 time: 0.4776 data_time: 0.0235 memory: 21547 grad_norm: 4.8311 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1101 loss: 1.1101 2022/10/10 10:52:56 - mmengine - INFO - Epoch(train) [94][560/940] lr: 1.0000e-04 eta: 0:50:52 time: 0.4861 data_time: 0.0275 memory: 21547 grad_norm: 4.9486 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1500 loss: 1.1500 2022/10/10 10:53:05 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 10:53:05 - mmengine - INFO - Epoch(train) [94][580/940] lr: 1.0000e-04 eta: 0:50:42 time: 0.4365 data_time: 0.0374 memory: 21547 grad_norm: 4.8075 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1034 loss: 1.1034 2022/10/10 10:53:15 - mmengine - INFO - Epoch(train) [94][600/940] lr: 1.0000e-04 eta: 0:50:32 time: 0.5048 data_time: 0.0392 memory: 21547 grad_norm: 4.8760 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1561 loss: 1.1561 2022/10/10 10:53:25 - mmengine - INFO - Epoch(train) [94][620/940] lr: 1.0000e-04 eta: 0:50:22 time: 0.5208 data_time: 0.0277 memory: 21547 grad_norm: 4.8204 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0913 loss: 1.0913 2022/10/10 10:53:35 - mmengine - INFO - Epoch(train) [94][640/940] lr: 1.0000e-04 eta: 0:50:12 time: 0.4711 data_time: 0.0344 memory: 21547 grad_norm: 4.7894 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.2087 loss: 1.2087 2022/10/10 10:53:45 - mmengine - INFO - Epoch(train) [94][660/940] lr: 1.0000e-04 eta: 0:50:02 time: 0.5194 data_time: 0.0258 memory: 21547 grad_norm: 4.7538 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0395 loss: 1.0395 2022/10/10 10:53:55 - mmengine - INFO - Epoch(train) [94][680/940] lr: 1.0000e-04 eta: 0:49:51 time: 0.4835 data_time: 0.0300 memory: 21547 grad_norm: 4.7341 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1408 loss: 1.1408 2022/10/10 10:54:05 - mmengine - INFO - Epoch(train) [94][700/940] lr: 1.0000e-04 eta: 0:49:41 time: 0.4942 data_time: 0.0288 memory: 21547 grad_norm: 4.8129 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1106 loss: 1.1106 2022/10/10 10:54:14 - mmengine - INFO - Epoch(train) [94][720/940] lr: 1.0000e-04 eta: 0:49:31 time: 0.4660 data_time: 0.0330 memory: 21547 grad_norm: 4.8940 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0749 loss: 1.0749 2022/10/10 10:54:25 - mmengine - INFO - Epoch(train) [94][740/940] lr: 1.0000e-04 eta: 0:49:21 time: 0.5252 data_time: 0.0300 memory: 21547 grad_norm: 4.7324 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2245 loss: 1.2245 2022/10/10 10:54:35 - mmengine - INFO - Epoch(train) [94][760/940] lr: 1.0000e-04 eta: 0:49:11 time: 0.4974 data_time: 0.0336 memory: 21547 grad_norm: 4.8216 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0620 loss: 1.0620 2022/10/10 10:54:45 - mmengine - INFO - Epoch(train) [94][780/940] lr: 1.0000e-04 eta: 0:49:01 time: 0.5346 data_time: 0.0276 memory: 21547 grad_norm: 4.7181 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0625 loss: 1.0625 2022/10/10 10:54:54 - mmengine - INFO - Epoch(train) [94][800/940] lr: 1.0000e-04 eta: 0:48:51 time: 0.4626 data_time: 0.0291 memory: 21547 grad_norm: 4.8181 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1503 loss: 1.1503 2022/10/10 10:55:04 - mmengine - INFO - Epoch(train) [94][820/940] lr: 1.0000e-04 eta: 0:48:40 time: 0.5001 data_time: 0.0260 memory: 21547 grad_norm: 4.8687 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2707 loss: 1.2707 2022/10/10 10:55:15 - mmengine - INFO - Epoch(train) [94][840/940] lr: 1.0000e-04 eta: 0:48:30 time: 0.5020 data_time: 0.0261 memory: 21547 grad_norm: 4.7315 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1338 loss: 1.1338 2022/10/10 10:55:26 - mmengine - INFO - Epoch(train) [94][860/940] lr: 1.0000e-04 eta: 0:48:20 time: 0.5577 data_time: 0.0307 memory: 21547 grad_norm: 4.8678 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1190 loss: 1.1190 2022/10/10 10:55:35 - mmengine - INFO - Epoch(train) [94][880/940] lr: 1.0000e-04 eta: 0:48:10 time: 0.4473 data_time: 0.0275 memory: 21547 grad_norm: 4.8303 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1223 loss: 1.1223 2022/10/10 10:55:45 - mmengine - INFO - Epoch(train) [94][900/940] lr: 1.0000e-04 eta: 0:48:00 time: 0.5400 data_time: 0.0326 memory: 21547 grad_norm: 4.8050 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2226 loss: 1.2226 2022/10/10 10:55:55 - mmengine - INFO - Epoch(train) [94][920/940] lr: 1.0000e-04 eta: 0:47:50 time: 0.4752 data_time: 0.0257 memory: 21547 grad_norm: 4.9298 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1993 loss: 1.1993 2022/10/10 10:56:04 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 10:56:04 - mmengine - INFO - Epoch(train) [94][940/940] lr: 1.0000e-04 eta: 0:47:39 time: 0.4470 data_time: 0.0225 memory: 21547 grad_norm: 5.2196 top1_acc: 0.5714 top5_acc: 1.0000 loss_cls: 1.1549 loss: 1.1549 2022/10/10 10:56:16 - mmengine - INFO - Epoch(val) [94][20/78] eta: 0:00:35 time: 0.6100 data_time: 0.5008 memory: 3269 2022/10/10 10:56:25 - mmengine - INFO - Epoch(val) [94][40/78] eta: 0:00:16 time: 0.4227 data_time: 0.3138 memory: 3269 2022/10/10 10:56:36 - mmengine - INFO - Epoch(val) [94][60/78] eta: 0:00:10 time: 0.5575 data_time: 0.4481 memory: 3269 2022/10/10 10:56:46 - mmengine - INFO - Epoch(val) [94][78/78] acc/top1: 0.6819 acc/top5: 0.8728 acc/mean1: 0.6817 2022/10/10 10:57:00 - mmengine - INFO - Epoch(train) [95][20/940] lr: 1.0000e-04 eta: 0:47:30 time: 0.6884 data_time: 0.2077 memory: 21547 grad_norm: 4.7616 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1151 loss: 1.1151 2022/10/10 10:57:09 - mmengine - INFO - Epoch(train) [95][40/940] lr: 1.0000e-04 eta: 0:47:19 time: 0.4629 data_time: 0.0287 memory: 21547 grad_norm: 4.8594 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0873 loss: 1.0873 2022/10/10 10:57:20 - mmengine - INFO - Epoch(train) [95][60/940] lr: 1.0000e-04 eta: 0:47:09 time: 0.5676 data_time: 0.0340 memory: 21547 grad_norm: 4.8324 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2231 loss: 1.2231 2022/10/10 10:57:31 - mmengine - INFO - Epoch(train) [95][80/940] lr: 1.0000e-04 eta: 0:46:59 time: 0.5296 data_time: 0.0289 memory: 21547 grad_norm: 4.7786 top1_acc: 0.7812 top5_acc: 0.7812 loss_cls: 1.1766 loss: 1.1766 2022/10/10 10:57:42 - mmengine - INFO - Epoch(train) [95][100/940] lr: 1.0000e-04 eta: 0:46:49 time: 0.5714 data_time: 0.0273 memory: 21547 grad_norm: 4.7397 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2214 loss: 1.2214 2022/10/10 10:57:52 - mmengine - INFO - Epoch(train) [95][120/940] lr: 1.0000e-04 eta: 0:46:39 time: 0.4692 data_time: 0.0272 memory: 21547 grad_norm: 4.9287 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1822 loss: 1.1822 2022/10/10 10:58:02 - mmengine - INFO - Epoch(train) [95][140/940] lr: 1.0000e-04 eta: 0:46:29 time: 0.5169 data_time: 0.0251 memory: 21547 grad_norm: 4.8681 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0917 loss: 1.0917 2022/10/10 10:58:11 - mmengine - INFO - Epoch(train) [95][160/940] lr: 1.0000e-04 eta: 0:46:19 time: 0.4450 data_time: 0.0304 memory: 21547 grad_norm: 4.8125 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0011 loss: 1.0011 2022/10/10 10:58:21 - mmengine - INFO - Epoch(train) [95][180/940] lr: 1.0000e-04 eta: 0:46:08 time: 0.5102 data_time: 0.0342 memory: 21547 grad_norm: 4.6632 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1681 loss: 1.1681 2022/10/10 10:58:31 - mmengine - INFO - Epoch(train) [95][200/940] lr: 1.0000e-04 eta: 0:45:58 time: 0.4911 data_time: 0.0271 memory: 21547 grad_norm: 4.7675 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1204 loss: 1.1204 2022/10/10 10:58:42 - mmengine - INFO - Epoch(train) [95][220/940] lr: 1.0000e-04 eta: 0:45:48 time: 0.5341 data_time: 0.0232 memory: 21547 grad_norm: 4.8282 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2534 loss: 1.2534 2022/10/10 10:58:51 - mmengine - INFO - Epoch(train) [95][240/940] lr: 1.0000e-04 eta: 0:45:38 time: 0.4741 data_time: 0.0287 memory: 21547 grad_norm: 4.8667 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1437 loss: 1.1437 2022/10/10 10:59:02 - mmengine - INFO - Epoch(train) [95][260/940] lr: 1.0000e-04 eta: 0:45:28 time: 0.5251 data_time: 0.0246 memory: 21547 grad_norm: 4.8757 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1125 loss: 1.1125 2022/10/10 10:59:11 - mmengine - INFO - Epoch(train) [95][280/940] lr: 1.0000e-04 eta: 0:45:18 time: 0.4808 data_time: 0.0362 memory: 21547 grad_norm: 4.8577 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.0446 loss: 1.0446 2022/10/10 10:59:22 - mmengine - INFO - Epoch(train) [95][300/940] lr: 1.0000e-04 eta: 0:45:08 time: 0.5326 data_time: 0.0254 memory: 21547 grad_norm: 4.8665 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1580 loss: 1.1580 2022/10/10 10:59:32 - mmengine - INFO - Epoch(train) [95][320/940] lr: 1.0000e-04 eta: 0:44:57 time: 0.5007 data_time: 0.0255 memory: 21547 grad_norm: 4.7925 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1099 loss: 1.1099 2022/10/10 10:59:42 - mmengine - INFO - Epoch(train) [95][340/940] lr: 1.0000e-04 eta: 0:44:47 time: 0.4878 data_time: 0.0287 memory: 21547 grad_norm: 4.7433 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.0984 loss: 1.0984 2022/10/10 10:59:52 - mmengine - INFO - Epoch(train) [95][360/940] lr: 1.0000e-04 eta: 0:44:37 time: 0.5034 data_time: 0.0241 memory: 21547 grad_norm: 4.8041 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1583 loss: 1.1583 2022/10/10 11:00:03 - mmengine - INFO - Epoch(train) [95][380/940] lr: 1.0000e-04 eta: 0:44:27 time: 0.5484 data_time: 0.0265 memory: 21547 grad_norm: 4.8095 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0742 loss: 1.0742 2022/10/10 11:00:12 - mmengine - INFO - Epoch(train) [95][400/940] lr: 1.0000e-04 eta: 0:44:17 time: 0.4656 data_time: 0.0246 memory: 21547 grad_norm: 4.7626 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1792 loss: 1.1792 2022/10/10 11:00:23 - mmengine - INFO - Epoch(train) [95][420/940] lr: 1.0000e-04 eta: 0:44:07 time: 0.5364 data_time: 0.0293 memory: 21547 grad_norm: 4.7041 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1906 loss: 1.1906 2022/10/10 11:00:33 - mmengine - INFO - Epoch(train) [95][440/940] lr: 1.0000e-04 eta: 0:43:57 time: 0.4945 data_time: 0.0225 memory: 21547 grad_norm: 4.6731 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0642 loss: 1.0642 2022/10/10 11:00:44 - mmengine - INFO - Epoch(train) [95][460/940] lr: 1.0000e-04 eta: 0:43:46 time: 0.5461 data_time: 0.0281 memory: 21547 grad_norm: 4.9129 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1416 loss: 1.1416 2022/10/10 11:00:54 - mmengine - INFO - Epoch(train) [95][480/940] lr: 1.0000e-04 eta: 0:43:36 time: 0.5313 data_time: 0.0302 memory: 21547 grad_norm: 4.9474 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2086 loss: 1.2086 2022/10/10 11:01:04 - mmengine - INFO - Epoch(train) [95][500/940] lr: 1.0000e-04 eta: 0:43:26 time: 0.4796 data_time: 0.0244 memory: 21547 grad_norm: 4.8689 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2032 loss: 1.2032 2022/10/10 11:01:13 - mmengine - INFO - Epoch(train) [95][520/940] lr: 1.0000e-04 eta: 0:43:16 time: 0.4615 data_time: 0.0280 memory: 21547 grad_norm: 4.7715 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2360 loss: 1.2360 2022/10/10 11:01:24 - mmengine - INFO - Epoch(train) [95][540/940] lr: 1.0000e-04 eta: 0:43:06 time: 0.5476 data_time: 0.0286 memory: 21547 grad_norm: 4.7611 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1753 loss: 1.1753 2022/10/10 11:01:32 - mmengine - INFO - Epoch(train) [95][560/940] lr: 1.0000e-04 eta: 0:42:56 time: 0.4224 data_time: 0.0361 memory: 21547 grad_norm: 4.8132 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0594 loss: 1.0594 2022/10/10 11:01:44 - mmengine - INFO - Epoch(train) [95][580/940] lr: 1.0000e-04 eta: 0:42:46 time: 0.5736 data_time: 0.0253 memory: 21547 grad_norm: 4.7805 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1399 loss: 1.1399 2022/10/10 11:01:53 - mmengine - INFO - Epoch(train) [95][600/940] lr: 1.0000e-04 eta: 0:42:35 time: 0.4632 data_time: 0.0309 memory: 21547 grad_norm: 4.8384 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1550 loss: 1.1550 2022/10/10 11:02:03 - mmengine - INFO - Epoch(train) [95][620/940] lr: 1.0000e-04 eta: 0:42:25 time: 0.5079 data_time: 0.0265 memory: 21547 grad_norm: 4.8436 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2191 loss: 1.2191 2022/10/10 11:02:13 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 11:02:13 - mmengine - INFO - Epoch(train) [95][640/940] lr: 1.0000e-04 eta: 0:42:15 time: 0.4866 data_time: 0.0330 memory: 21547 grad_norm: 4.7717 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1410 loss: 1.1410 2022/10/10 11:02:23 - mmengine - INFO - Epoch(train) [95][660/940] lr: 1.0000e-04 eta: 0:42:05 time: 0.5121 data_time: 0.0244 memory: 21547 grad_norm: 4.8321 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0129 loss: 1.0129 2022/10/10 11:02:32 - mmengine - INFO - Epoch(train) [95][680/940] lr: 1.0000e-04 eta: 0:41:55 time: 0.4495 data_time: 0.0300 memory: 21547 grad_norm: 4.7620 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1938 loss: 1.1938 2022/10/10 11:02:42 - mmengine - INFO - Epoch(train) [95][700/940] lr: 1.0000e-04 eta: 0:41:45 time: 0.5070 data_time: 0.0257 memory: 21547 grad_norm: 4.8028 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9898 loss: 0.9898 2022/10/10 11:02:52 - mmengine - INFO - Epoch(train) [95][720/940] lr: 1.0000e-04 eta: 0:41:34 time: 0.4891 data_time: 0.0301 memory: 21547 grad_norm: 4.7993 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1670 loss: 1.1670 2022/10/10 11:03:02 - mmengine - INFO - Epoch(train) [95][740/940] lr: 1.0000e-04 eta: 0:41:24 time: 0.5044 data_time: 0.0248 memory: 21547 grad_norm: 4.9240 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1481 loss: 1.1481 2022/10/10 11:03:12 - mmengine - INFO - Epoch(train) [95][760/940] lr: 1.0000e-04 eta: 0:41:14 time: 0.5039 data_time: 0.0275 memory: 21547 grad_norm: 4.7716 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1087 loss: 1.1087 2022/10/10 11:03:23 - mmengine - INFO - Epoch(train) [95][780/940] lr: 1.0000e-04 eta: 0:41:04 time: 0.5178 data_time: 0.0273 memory: 21547 grad_norm: 4.8954 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.3695 loss: 1.3695 2022/10/10 11:03:33 - mmengine - INFO - Epoch(train) [95][800/940] lr: 1.0000e-04 eta: 0:40:54 time: 0.5075 data_time: 0.0261 memory: 21547 grad_norm: 4.8550 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1495 loss: 1.1495 2022/10/10 11:03:44 - mmengine - INFO - Epoch(train) [95][820/940] lr: 1.0000e-04 eta: 0:40:44 time: 0.5539 data_time: 0.0256 memory: 21547 grad_norm: 4.8279 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2182 loss: 1.2182 2022/10/10 11:03:54 - mmengine - INFO - Epoch(train) [95][840/940] lr: 1.0000e-04 eta: 0:40:34 time: 0.4962 data_time: 0.0322 memory: 21547 grad_norm: 4.8400 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1848 loss: 1.1848 2022/10/10 11:04:03 - mmengine - INFO - Epoch(train) [95][860/940] lr: 1.0000e-04 eta: 0:40:23 time: 0.4756 data_time: 0.0239 memory: 21547 grad_norm: 4.7907 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1113 loss: 1.1113 2022/10/10 11:04:14 - mmengine - INFO - Epoch(train) [95][880/940] lr: 1.0000e-04 eta: 0:40:13 time: 0.5183 data_time: 0.0281 memory: 21547 grad_norm: 4.7961 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1072 loss: 1.1072 2022/10/10 11:04:24 - mmengine - INFO - Epoch(train) [95][900/940] lr: 1.0000e-04 eta: 0:40:03 time: 0.5078 data_time: 0.0285 memory: 21547 grad_norm: 4.9466 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1399 loss: 1.1399 2022/10/10 11:04:34 - mmengine - INFO - Epoch(train) [95][920/940] lr: 1.0000e-04 eta: 0:39:53 time: 0.4797 data_time: 0.0275 memory: 21547 grad_norm: 4.8049 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0466 loss: 1.0466 2022/10/10 11:04:43 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 11:04:43 - mmengine - INFO - Epoch(train) [95][940/940] lr: 1.0000e-04 eta: 0:39:43 time: 0.4641 data_time: 0.0209 memory: 21547 grad_norm: 5.1992 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.2759 loss: 1.2759 2022/10/10 11:04:55 - mmengine - INFO - Epoch(val) [95][20/78] eta: 0:00:35 time: 0.6107 data_time: 0.5015 memory: 3269 2022/10/10 11:05:04 - mmengine - INFO - Epoch(val) [95][40/78] eta: 0:00:16 time: 0.4232 data_time: 0.3144 memory: 3269 2022/10/10 11:05:15 - mmengine - INFO - Epoch(val) [95][60/78] eta: 0:00:10 time: 0.5564 data_time: 0.4495 memory: 3269 2022/10/10 11:05:25 - mmengine - INFO - Epoch(val) [95][78/78] acc/top1: 0.6812 acc/top5: 0.8712 acc/mean1: 0.6812 2022/10/10 11:05:39 - mmengine - INFO - Epoch(train) [96][20/940] lr: 1.0000e-04 eta: 0:39:33 time: 0.7041 data_time: 0.3189 memory: 21547 grad_norm: 4.8732 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1445 loss: 1.1445 2022/10/10 11:05:48 - mmengine - INFO - Epoch(train) [96][40/940] lr: 1.0000e-04 eta: 0:39:23 time: 0.4903 data_time: 0.0787 memory: 21547 grad_norm: 4.7115 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9355 loss: 0.9355 2022/10/10 11:06:00 - mmengine - INFO - Epoch(train) [96][60/940] lr: 1.0000e-04 eta: 0:39:13 time: 0.5603 data_time: 0.1254 memory: 21547 grad_norm: 4.7620 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1409 loss: 1.1409 2022/10/10 11:06:10 - mmengine - INFO - Epoch(train) [96][80/940] lr: 1.0000e-04 eta: 0:39:02 time: 0.4933 data_time: 0.1019 memory: 21547 grad_norm: 4.7458 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0972 loss: 1.0972 2022/10/10 11:06:20 - mmengine - INFO - Epoch(train) [96][100/940] lr: 1.0000e-04 eta: 0:38:52 time: 0.4984 data_time: 0.0897 memory: 21547 grad_norm: 4.9013 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2950 loss: 1.2950 2022/10/10 11:06:30 - mmengine - INFO - Epoch(train) [96][120/940] lr: 1.0000e-04 eta: 0:38:42 time: 0.5184 data_time: 0.0456 memory: 21547 grad_norm: 4.8309 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2032 loss: 1.2032 2022/10/10 11:06:40 - mmengine - INFO - Epoch(train) [96][140/940] lr: 1.0000e-04 eta: 0:38:32 time: 0.5239 data_time: 0.0417 memory: 21547 grad_norm: 4.8185 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1237 loss: 1.1237 2022/10/10 11:06:50 - mmengine - INFO - Epoch(train) [96][160/940] lr: 1.0000e-04 eta: 0:38:22 time: 0.4838 data_time: 0.0284 memory: 21547 grad_norm: 4.8318 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.0215 loss: 1.0215 2022/10/10 11:07:00 - mmengine - INFO - Epoch(train) [96][180/940] lr: 1.0000e-04 eta: 0:38:12 time: 0.5137 data_time: 0.0261 memory: 21547 grad_norm: 4.7992 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1128 loss: 1.1128 2022/10/10 11:07:10 - mmengine - INFO - Epoch(train) [96][200/940] lr: 1.0000e-04 eta: 0:38:02 time: 0.5025 data_time: 0.0260 memory: 21547 grad_norm: 4.8417 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1544 loss: 1.1544 2022/10/10 11:07:21 - mmengine - INFO - Epoch(train) [96][220/940] lr: 1.0000e-04 eta: 0:37:51 time: 0.5103 data_time: 0.0288 memory: 21547 grad_norm: 4.9011 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1794 loss: 1.1794 2022/10/10 11:07:30 - mmengine - INFO - Epoch(train) [96][240/940] lr: 1.0000e-04 eta: 0:37:41 time: 0.4899 data_time: 0.0228 memory: 21547 grad_norm: 4.9084 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0925 loss: 1.0925 2022/10/10 11:07:41 - mmengine - INFO - Epoch(train) [96][260/940] lr: 1.0000e-04 eta: 0:37:31 time: 0.5328 data_time: 0.0289 memory: 21547 grad_norm: 4.8013 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1702 loss: 1.1702 2022/10/10 11:07:51 - mmengine - INFO - Epoch(train) [96][280/940] lr: 1.0000e-04 eta: 0:37:21 time: 0.5035 data_time: 0.0266 memory: 21547 grad_norm: 4.9990 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2901 loss: 1.2901 2022/10/10 11:08:01 - mmengine - INFO - Epoch(train) [96][300/940] lr: 1.0000e-04 eta: 0:37:11 time: 0.5101 data_time: 0.0289 memory: 21547 grad_norm: 4.8639 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0784 loss: 1.0784 2022/10/10 11:08:10 - mmengine - INFO - Epoch(train) [96][320/940] lr: 1.0000e-04 eta: 0:37:01 time: 0.4493 data_time: 0.0333 memory: 21547 grad_norm: 4.7709 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2236 loss: 1.2236 2022/10/10 11:08:22 - mmengine - INFO - Epoch(train) [96][340/940] lr: 1.0000e-04 eta: 0:36:51 time: 0.5623 data_time: 0.0302 memory: 21547 grad_norm: 4.8418 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1860 loss: 1.1860 2022/10/10 11:08:32 - mmengine - INFO - Epoch(train) [96][360/940] lr: 1.0000e-04 eta: 0:36:40 time: 0.5033 data_time: 0.0287 memory: 21547 grad_norm: 4.6842 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0071 loss: 1.0071 2022/10/10 11:08:42 - mmengine - INFO - Epoch(train) [96][380/940] lr: 1.0000e-04 eta: 0:36:30 time: 0.5138 data_time: 0.0230 memory: 21547 grad_norm: 4.8687 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1762 loss: 1.1762 2022/10/10 11:08:51 - mmengine - INFO - Epoch(train) [96][400/940] lr: 1.0000e-04 eta: 0:36:20 time: 0.4498 data_time: 0.0302 memory: 21547 grad_norm: 4.7521 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0561 loss: 1.0561 2022/10/10 11:09:02 - mmengine - INFO - Epoch(train) [96][420/940] lr: 1.0000e-04 eta: 0:36:10 time: 0.5441 data_time: 0.0282 memory: 21547 grad_norm: 4.8117 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1143 loss: 1.1143 2022/10/10 11:09:11 - mmengine - INFO - Epoch(train) [96][440/940] lr: 1.0000e-04 eta: 0:36:00 time: 0.4661 data_time: 0.0257 memory: 21547 grad_norm: 4.9017 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1746 loss: 1.1746 2022/10/10 11:09:24 - mmengine - INFO - Epoch(train) [96][460/940] lr: 1.0000e-04 eta: 0:35:50 time: 0.6647 data_time: 0.0273 memory: 21547 grad_norm: 4.8896 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0985 loss: 1.0985 2022/10/10 11:09:34 - mmengine - INFO - Epoch(train) [96][480/940] lr: 1.0000e-04 eta: 0:35:40 time: 0.4868 data_time: 0.0231 memory: 21547 grad_norm: 4.8845 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2041 loss: 1.2041 2022/10/10 11:09:45 - mmengine - INFO - Epoch(train) [96][500/940] lr: 1.0000e-04 eta: 0:35:30 time: 0.5606 data_time: 0.0218 memory: 21547 grad_norm: 4.9316 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0707 loss: 1.0707 2022/10/10 11:09:55 - mmengine - INFO - Epoch(train) [96][520/940] lr: 1.0000e-04 eta: 0:35:19 time: 0.5022 data_time: 0.0268 memory: 21547 grad_norm: 4.9313 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1509 loss: 1.1509 2022/10/10 11:10:05 - mmengine - INFO - Epoch(train) [96][540/940] lr: 1.0000e-04 eta: 0:35:09 time: 0.5044 data_time: 0.0274 memory: 21547 grad_norm: 4.8806 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2354 loss: 1.2354 2022/10/10 11:10:16 - mmengine - INFO - Epoch(train) [96][560/940] lr: 1.0000e-04 eta: 0:34:59 time: 0.5092 data_time: 0.0268 memory: 21547 grad_norm: 4.8373 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0991 loss: 1.0991 2022/10/10 11:10:26 - mmengine - INFO - Epoch(train) [96][580/940] lr: 1.0000e-04 eta: 0:34:49 time: 0.5007 data_time: 0.0281 memory: 21547 grad_norm: 4.7484 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1226 loss: 1.1226 2022/10/10 11:10:34 - mmengine - INFO - Epoch(train) [96][600/940] lr: 1.0000e-04 eta: 0:34:39 time: 0.4342 data_time: 0.0240 memory: 21547 grad_norm: 4.8533 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1890 loss: 1.1890 2022/10/10 11:10:44 - mmengine - INFO - Epoch(train) [96][620/940] lr: 1.0000e-04 eta: 0:34:29 time: 0.4739 data_time: 0.0261 memory: 21547 grad_norm: 4.7540 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.1706 loss: 1.1706 2022/10/10 11:11:05 - mmengine - INFO - Epoch(train) [96][640/940] lr: 1.0000e-04 eta: 0:34:19 time: 1.0768 data_time: 0.0257 memory: 21547 grad_norm: 4.8866 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0263 loss: 1.0263 2022/10/10 11:11:14 - mmengine - INFO - Epoch(train) [96][660/940] lr: 1.0000e-04 eta: 0:34:09 time: 0.4534 data_time: 0.0318 memory: 21547 grad_norm: 4.7719 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1525 loss: 1.1525 2022/10/10 11:11:25 - mmengine - INFO - Epoch(train) [96][680/940] lr: 1.0000e-04 eta: 0:33:59 time: 0.5035 data_time: 0.0265 memory: 21547 grad_norm: 4.8305 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0921 loss: 1.0921 2022/10/10 11:11:34 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 11:11:34 - mmengine - INFO - Epoch(train) [96][700/940] lr: 1.0000e-04 eta: 0:33:48 time: 0.4761 data_time: 0.0278 memory: 21547 grad_norm: 4.7683 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0756 loss: 1.0756 2022/10/10 11:11:44 - mmengine - INFO - Epoch(train) [96][720/940] lr: 1.0000e-04 eta: 0:33:38 time: 0.5122 data_time: 0.0287 memory: 21547 grad_norm: 4.8948 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0973 loss: 1.0973 2022/10/10 11:11:53 - mmengine - INFO - Epoch(train) [96][740/940] lr: 1.0000e-04 eta: 0:33:28 time: 0.4547 data_time: 0.0298 memory: 21547 grad_norm: 4.7903 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1340 loss: 1.1340 2022/10/10 11:12:04 - mmengine - INFO - Epoch(train) [96][760/940] lr: 1.0000e-04 eta: 0:33:18 time: 0.5071 data_time: 0.0258 memory: 21547 grad_norm: 4.7498 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1118 loss: 1.1118 2022/10/10 11:12:13 - mmengine - INFO - Epoch(train) [96][780/940] lr: 1.0000e-04 eta: 0:33:08 time: 0.4918 data_time: 0.0258 memory: 21547 grad_norm: 4.9062 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2547 loss: 1.2547 2022/10/10 11:12:24 - mmengine - INFO - Epoch(train) [96][800/940] lr: 1.0000e-04 eta: 0:32:58 time: 0.5248 data_time: 0.0227 memory: 21547 grad_norm: 4.7352 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0703 loss: 1.0703 2022/10/10 11:12:34 - mmengine - INFO - Epoch(train) [96][820/940] lr: 1.0000e-04 eta: 0:32:48 time: 0.4989 data_time: 0.0271 memory: 21547 grad_norm: 4.8514 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1811 loss: 1.1811 2022/10/10 11:12:44 - mmengine - INFO - Epoch(train) [96][840/940] lr: 1.0000e-04 eta: 0:32:37 time: 0.4933 data_time: 0.0272 memory: 21547 grad_norm: 4.8528 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1767 loss: 1.1767 2022/10/10 11:12:54 - mmengine - INFO - Epoch(train) [96][860/940] lr: 1.0000e-04 eta: 0:32:27 time: 0.5037 data_time: 0.0288 memory: 21547 grad_norm: 4.9399 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.1041 loss: 1.1041 2022/10/10 11:13:04 - mmengine - INFO - Epoch(train) [96][880/940] lr: 1.0000e-04 eta: 0:32:17 time: 0.5256 data_time: 0.0263 memory: 21547 grad_norm: 4.7200 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.1080 loss: 1.1080 2022/10/10 11:13:14 - mmengine - INFO - Epoch(train) [96][900/940] lr: 1.0000e-04 eta: 0:32:07 time: 0.5080 data_time: 0.0308 memory: 21547 grad_norm: 4.7645 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0826 loss: 1.0826 2022/10/10 11:13:25 - mmengine - INFO - Epoch(train) [96][920/940] lr: 1.0000e-04 eta: 0:31:57 time: 0.5132 data_time: 0.0237 memory: 21547 grad_norm: 4.9161 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1195 loss: 1.1195 2022/10/10 11:13:34 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 11:13:34 - mmengine - INFO - Epoch(train) [96][940/940] lr: 1.0000e-04 eta: 0:31:47 time: 0.4765 data_time: 0.0249 memory: 21547 grad_norm: 5.2470 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.1096 loss: 1.1096 2022/10/10 11:13:35 - mmengine - INFO - Saving checkpoint at 96 epochs 2022/10/10 11:13:48 - mmengine - INFO - Epoch(val) [96][20/78] eta: 0:00:35 time: 0.6158 data_time: 0.5113 memory: 3269 2022/10/10 11:13:56 - mmengine - INFO - Epoch(val) [96][40/78] eta: 0:00:16 time: 0.4212 data_time: 0.3171 memory: 3269 2022/10/10 11:14:07 - mmengine - INFO - Epoch(val) [96][60/78] eta: 0:00:09 time: 0.5477 data_time: 0.4428 memory: 3269 2022/10/10 11:14:16 - mmengine - INFO - Epoch(val) [96][78/78] acc/top1: 0.6816 acc/top5: 0.8713 acc/mean1: 0.6815 2022/10/10 11:14:30 - mmengine - INFO - Epoch(train) [97][20/940] lr: 1.0000e-04 eta: 0:31:37 time: 0.6807 data_time: 0.2086 memory: 21547 grad_norm: 4.8993 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2109 loss: 1.2109 2022/10/10 11:14:40 - mmengine - INFO - Epoch(train) [97][40/940] lr: 1.0000e-04 eta: 0:31:26 time: 0.4738 data_time: 0.0580 memory: 21547 grad_norm: 4.8356 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1759 loss: 1.1759 2022/10/10 11:14:51 - mmengine - INFO - Epoch(train) [97][60/940] lr: 1.0000e-04 eta: 0:31:16 time: 0.5678 data_time: 0.0393 memory: 21547 grad_norm: 4.8790 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1401 loss: 1.1401 2022/10/10 11:15:01 - mmengine - INFO - Epoch(train) [97][80/940] lr: 1.0000e-04 eta: 0:31:06 time: 0.4902 data_time: 0.0278 memory: 21547 grad_norm: 4.7054 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1009 loss: 1.1009 2022/10/10 11:15:11 - mmengine - INFO - Epoch(train) [97][100/940] lr: 1.0000e-04 eta: 0:30:56 time: 0.5353 data_time: 0.0285 memory: 21547 grad_norm: 4.7717 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1621 loss: 1.1621 2022/10/10 11:15:21 - mmengine - INFO - Epoch(train) [97][120/940] lr: 1.0000e-04 eta: 0:30:46 time: 0.4879 data_time: 0.0263 memory: 21547 grad_norm: 4.8214 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1442 loss: 1.1442 2022/10/10 11:15:33 - mmengine - INFO - Epoch(train) [97][140/940] lr: 1.0000e-04 eta: 0:30:36 time: 0.5930 data_time: 0.0266 memory: 21547 grad_norm: 4.8911 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1195 loss: 1.1195 2022/10/10 11:15:43 - mmengine - INFO - Epoch(train) [97][160/940] lr: 1.0000e-04 eta: 0:30:26 time: 0.4850 data_time: 0.0319 memory: 21547 grad_norm: 4.6592 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0815 loss: 1.0815 2022/10/10 11:15:53 - mmengine - INFO - Epoch(train) [97][180/940] lr: 1.0000e-04 eta: 0:30:16 time: 0.5063 data_time: 0.0286 memory: 21547 grad_norm: 4.8327 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1438 loss: 1.1438 2022/10/10 11:16:03 - mmengine - INFO - Epoch(train) [97][200/940] lr: 1.0000e-04 eta: 0:30:05 time: 0.4973 data_time: 0.0315 memory: 21547 grad_norm: 4.8777 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.1770 loss: 1.1770 2022/10/10 11:16:14 - mmengine - INFO - Epoch(train) [97][220/940] lr: 1.0000e-04 eta: 0:29:55 time: 0.5520 data_time: 0.0266 memory: 21547 grad_norm: 4.8254 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1599 loss: 1.1599 2022/10/10 11:16:23 - mmengine - INFO - Epoch(train) [97][240/940] lr: 1.0000e-04 eta: 0:29:45 time: 0.4594 data_time: 0.0297 memory: 21547 grad_norm: 4.7818 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0720 loss: 1.0720 2022/10/10 11:16:34 - mmengine - INFO - Epoch(train) [97][260/940] lr: 1.0000e-04 eta: 0:29:35 time: 0.5350 data_time: 0.0294 memory: 21547 grad_norm: 4.8833 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2172 loss: 1.2172 2022/10/10 11:16:43 - mmengine - INFO - Epoch(train) [97][280/940] lr: 1.0000e-04 eta: 0:29:25 time: 0.4676 data_time: 0.0272 memory: 21547 grad_norm: 4.9631 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1429 loss: 1.1429 2022/10/10 11:16:54 - mmengine - INFO - Epoch(train) [97][300/940] lr: 1.0000e-04 eta: 0:29:15 time: 0.5243 data_time: 0.0251 memory: 21547 grad_norm: 4.7983 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0668 loss: 1.0668 2022/10/10 11:17:03 - mmengine - INFO - Epoch(train) [97][320/940] lr: 1.0000e-04 eta: 0:29:05 time: 0.4753 data_time: 0.0291 memory: 21547 grad_norm: 4.7869 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1280 loss: 1.1280 2022/10/10 11:17:14 - mmengine - INFO - Epoch(train) [97][340/940] lr: 1.0000e-04 eta: 0:28:54 time: 0.5386 data_time: 0.0254 memory: 21547 grad_norm: 4.6827 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.0950 loss: 1.0950 2022/10/10 11:17:23 - mmengine - INFO - Epoch(train) [97][360/940] lr: 1.0000e-04 eta: 0:28:44 time: 0.4366 data_time: 0.0306 memory: 21547 grad_norm: 4.8389 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.1612 loss: 1.1612 2022/10/10 11:17:33 - mmengine - INFO - Epoch(train) [97][380/940] lr: 1.0000e-04 eta: 0:28:34 time: 0.4965 data_time: 0.0262 memory: 21547 grad_norm: 4.9144 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1475 loss: 1.1475 2022/10/10 11:17:43 - mmengine - INFO - Epoch(train) [97][400/940] lr: 1.0000e-04 eta: 0:28:24 time: 0.5239 data_time: 0.0273 memory: 21547 grad_norm: 4.8364 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0692 loss: 1.0692 2022/10/10 11:17:53 - mmengine - INFO - Epoch(train) [97][420/940] lr: 1.0000e-04 eta: 0:28:14 time: 0.4953 data_time: 0.0307 memory: 21547 grad_norm: 4.8180 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0685 loss: 1.0685 2022/10/10 11:18:03 - mmengine - INFO - Epoch(train) [97][440/940] lr: 1.0000e-04 eta: 0:28:04 time: 0.5253 data_time: 0.0297 memory: 21547 grad_norm: 4.7484 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2163 loss: 1.2163 2022/10/10 11:18:13 - mmengine - INFO - Epoch(train) [97][460/940] lr: 1.0000e-04 eta: 0:27:53 time: 0.4863 data_time: 0.0347 memory: 21547 grad_norm: 4.8368 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.1812 loss: 1.1812 2022/10/10 11:18:23 - mmengine - INFO - Epoch(train) [97][480/940] lr: 1.0000e-04 eta: 0:27:43 time: 0.4840 data_time: 0.0282 memory: 21547 grad_norm: 4.8864 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2244 loss: 1.2244 2022/10/10 11:18:33 - mmengine - INFO - Epoch(train) [97][500/940] lr: 1.0000e-04 eta: 0:27:33 time: 0.5123 data_time: 0.0326 memory: 21547 grad_norm: 4.9653 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1978 loss: 1.1978 2022/10/10 11:18:43 - mmengine - INFO - Epoch(train) [97][520/940] lr: 1.0000e-04 eta: 0:27:23 time: 0.5030 data_time: 0.0311 memory: 21547 grad_norm: 4.8845 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2314 loss: 1.2314 2022/10/10 11:18:53 - mmengine - INFO - Epoch(train) [97][540/940] lr: 1.0000e-04 eta: 0:27:13 time: 0.5032 data_time: 0.0259 memory: 21547 grad_norm: 4.8437 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1350 loss: 1.1350 2022/10/10 11:19:04 - mmengine - INFO - Epoch(train) [97][560/940] lr: 1.0000e-04 eta: 0:27:03 time: 0.5198 data_time: 0.0244 memory: 21547 grad_norm: 4.9363 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3828 loss: 1.3828 2022/10/10 11:19:14 - mmengine - INFO - Epoch(train) [97][580/940] lr: 1.0000e-04 eta: 0:26:53 time: 0.5088 data_time: 0.0268 memory: 21547 grad_norm: 4.7971 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2587 loss: 1.2587 2022/10/10 11:19:25 - mmengine - INFO - Epoch(train) [97][600/940] lr: 1.0000e-04 eta: 0:26:42 time: 0.5384 data_time: 0.0259 memory: 21547 grad_norm: 4.8090 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1771 loss: 1.1771 2022/10/10 11:19:34 - mmengine - INFO - Epoch(train) [97][620/940] lr: 1.0000e-04 eta: 0:26:32 time: 0.4957 data_time: 0.0335 memory: 21547 grad_norm: 4.7854 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2351 loss: 1.2351 2022/10/10 11:19:44 - mmengine - INFO - Epoch(train) [97][640/940] lr: 1.0000e-04 eta: 0:26:22 time: 0.4761 data_time: 0.0263 memory: 21547 grad_norm: 4.7069 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2414 loss: 1.2414 2022/10/10 11:19:54 - mmengine - INFO - Epoch(train) [97][660/940] lr: 1.0000e-04 eta: 0:26:12 time: 0.4902 data_time: 0.0325 memory: 21547 grad_norm: 4.8792 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2169 loss: 1.2169 2022/10/10 11:20:04 - mmengine - INFO - Epoch(train) [97][680/940] lr: 1.0000e-04 eta: 0:26:02 time: 0.5298 data_time: 0.0254 memory: 21547 grad_norm: 4.7996 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2048 loss: 1.2048 2022/10/10 11:20:15 - mmengine - INFO - Epoch(train) [97][700/940] lr: 1.0000e-04 eta: 0:25:52 time: 0.5475 data_time: 0.0281 memory: 21547 grad_norm: 4.8117 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2719 loss: 1.2719 2022/10/10 11:20:25 - mmengine - INFO - Epoch(train) [97][720/940] lr: 1.0000e-04 eta: 0:25:42 time: 0.4924 data_time: 0.0294 memory: 21547 grad_norm: 4.9580 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1423 loss: 1.1423 2022/10/10 11:20:36 - mmengine - INFO - Epoch(train) [97][740/940] lr: 1.0000e-04 eta: 0:25:31 time: 0.5314 data_time: 0.0309 memory: 21547 grad_norm: 4.8711 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0765 loss: 1.0765 2022/10/10 11:20:45 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 11:20:45 - mmengine - INFO - Epoch(train) [97][760/940] lr: 1.0000e-04 eta: 0:25:21 time: 0.4767 data_time: 0.0249 memory: 21547 grad_norm: 4.8105 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0953 loss: 1.0953 2022/10/10 11:20:55 - mmengine - INFO - Epoch(train) [97][780/940] lr: 1.0000e-04 eta: 0:25:11 time: 0.5042 data_time: 0.0259 memory: 21547 grad_norm: 4.8339 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1884 loss: 1.1884 2022/10/10 11:21:07 - mmengine - INFO - Epoch(train) [97][800/940] lr: 1.0000e-04 eta: 0:25:01 time: 0.5681 data_time: 0.0295 memory: 21547 grad_norm: 4.7843 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1359 loss: 1.1359 2022/10/10 11:21:17 - mmengine - INFO - Epoch(train) [97][820/940] lr: 1.0000e-04 eta: 0:24:51 time: 0.4967 data_time: 0.0261 memory: 21547 grad_norm: 4.8146 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.0917 loss: 1.0917 2022/10/10 11:21:26 - mmengine - INFO - Epoch(train) [97][840/940] lr: 1.0000e-04 eta: 0:24:41 time: 0.4727 data_time: 0.0243 memory: 21547 grad_norm: 4.7963 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2036 loss: 1.2036 2022/10/10 11:21:36 - mmengine - INFO - Epoch(train) [97][860/940] lr: 1.0000e-04 eta: 0:24:31 time: 0.4699 data_time: 0.0350 memory: 21547 grad_norm: 4.8838 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2119 loss: 1.2119 2022/10/10 11:21:46 - mmengine - INFO - Epoch(train) [97][880/940] lr: 1.0000e-04 eta: 0:24:20 time: 0.5217 data_time: 0.0317 memory: 21547 grad_norm: 4.8973 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.1802 loss: 1.1802 2022/10/10 11:21:56 - mmengine - INFO - Epoch(train) [97][900/940] lr: 1.0000e-04 eta: 0:24:10 time: 0.4949 data_time: 0.0275 memory: 21547 grad_norm: 4.9351 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2456 loss: 1.2456 2022/10/10 11:22:06 - mmengine - INFO - Epoch(train) [97][920/940] lr: 1.0000e-04 eta: 0:24:00 time: 0.5089 data_time: 0.0260 memory: 21547 grad_norm: 4.8110 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1731 loss: 1.1731 2022/10/10 11:22:15 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 11:22:15 - mmengine - INFO - Epoch(train) [97][940/940] lr: 1.0000e-04 eta: 0:23:50 time: 0.4346 data_time: 0.0255 memory: 21547 grad_norm: 5.0683 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.1403 loss: 1.1403 2022/10/10 11:22:27 - mmengine - INFO - Epoch(val) [97][20/78] eta: 0:00:35 time: 0.6203 data_time: 0.5115 memory: 3269 2022/10/10 11:22:36 - mmengine - INFO - Epoch(val) [97][40/78] eta: 0:00:15 time: 0.4177 data_time: 0.3089 memory: 3269 2022/10/10 11:22:47 - mmengine - INFO - Epoch(val) [97][60/78] eta: 0:00:09 time: 0.5477 data_time: 0.4432 memory: 3269 2022/10/10 11:22:56 - mmengine - INFO - Epoch(val) [97][78/78] acc/top1: 0.6801 acc/top5: 0.8715 acc/mean1: 0.6800 2022/10/10 11:23:11 - mmengine - INFO - Epoch(train) [98][20/940] lr: 1.0000e-04 eta: 0:23:40 time: 0.7467 data_time: 0.2079 memory: 21547 grad_norm: 4.8328 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2686 loss: 1.2686 2022/10/10 11:23:21 - mmengine - INFO - Epoch(train) [98][40/940] lr: 1.0000e-04 eta: 0:23:30 time: 0.4889 data_time: 0.0235 memory: 21547 grad_norm: 4.8793 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0690 loss: 1.0690 2022/10/10 11:23:32 - mmengine - INFO - Epoch(train) [98][60/940] lr: 1.0000e-04 eta: 0:23:20 time: 0.5393 data_time: 0.0249 memory: 21547 grad_norm: 4.6966 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 0.9980 loss: 0.9980 2022/10/10 11:23:41 - mmengine - INFO - Epoch(train) [98][80/940] lr: 1.0000e-04 eta: 0:23:09 time: 0.4802 data_time: 0.0237 memory: 21547 grad_norm: 4.8178 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0531 loss: 1.0531 2022/10/10 11:23:51 - mmengine - INFO - Epoch(train) [98][100/940] lr: 1.0000e-04 eta: 0:22:59 time: 0.4958 data_time: 0.0261 memory: 21547 grad_norm: 4.8793 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1789 loss: 1.1789 2022/10/10 11:24:01 - mmengine - INFO - Epoch(train) [98][120/940] lr: 1.0000e-04 eta: 0:22:49 time: 0.4689 data_time: 0.0291 memory: 21547 grad_norm: 4.8881 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.0908 loss: 1.0908 2022/10/10 11:24:11 - mmengine - INFO - Epoch(train) [98][140/940] lr: 1.0000e-04 eta: 0:22:39 time: 0.5209 data_time: 0.0308 memory: 21547 grad_norm: 4.8144 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2250 loss: 1.2250 2022/10/10 11:24:20 - mmengine - INFO - Epoch(train) [98][160/940] lr: 1.0000e-04 eta: 0:22:29 time: 0.4582 data_time: 0.0233 memory: 21547 grad_norm: 5.0012 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2256 loss: 1.2256 2022/10/10 11:24:31 - mmengine - INFO - Epoch(train) [98][180/940] lr: 1.0000e-04 eta: 0:22:19 time: 0.5491 data_time: 0.0282 memory: 21547 grad_norm: 4.7808 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1410 loss: 1.1410 2022/10/10 11:24:41 - mmengine - INFO - Epoch(train) [98][200/940] lr: 1.0000e-04 eta: 0:22:09 time: 0.4968 data_time: 0.0265 memory: 21547 grad_norm: 4.8847 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1855 loss: 1.1855 2022/10/10 11:24:51 - mmengine - INFO - Epoch(train) [98][220/940] lr: 1.0000e-04 eta: 0:21:58 time: 0.4944 data_time: 0.0270 memory: 21547 grad_norm: 4.8387 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0583 loss: 1.0583 2022/10/10 11:25:01 - mmengine - INFO - Epoch(train) [98][240/940] lr: 1.0000e-04 eta: 0:21:48 time: 0.4759 data_time: 0.0295 memory: 21547 grad_norm: 4.9320 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1974 loss: 1.1974 2022/10/10 11:25:11 - mmengine - INFO - Epoch(train) [98][260/940] lr: 1.0000e-04 eta: 0:21:38 time: 0.5267 data_time: 0.0262 memory: 21547 grad_norm: 4.7864 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0688 loss: 1.0688 2022/10/10 11:25:21 - mmengine - INFO - Epoch(train) [98][280/940] lr: 1.0000e-04 eta: 0:21:28 time: 0.4777 data_time: 0.0341 memory: 21547 grad_norm: 4.7407 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0971 loss: 1.0971 2022/10/10 11:25:32 - mmengine - INFO - Epoch(train) [98][300/940] lr: 1.0000e-04 eta: 0:21:18 time: 0.5480 data_time: 0.0317 memory: 21547 grad_norm: 4.8680 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2312 loss: 1.2312 2022/10/10 11:25:41 - mmengine - INFO - Epoch(train) [98][320/940] lr: 1.0000e-04 eta: 0:21:08 time: 0.4789 data_time: 0.0308 memory: 21547 grad_norm: 4.9786 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1909 loss: 1.1909 2022/10/10 11:25:51 - mmengine - INFO - Epoch(train) [98][340/940] lr: 1.0000e-04 eta: 0:20:58 time: 0.5127 data_time: 0.0269 memory: 21547 grad_norm: 4.9700 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1308 loss: 1.1308 2022/10/10 11:26:01 - mmengine - INFO - Epoch(train) [98][360/940] lr: 1.0000e-04 eta: 0:20:47 time: 0.4919 data_time: 0.0316 memory: 21547 grad_norm: 4.8362 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1446 loss: 1.1446 2022/10/10 11:26:12 - mmengine - INFO - Epoch(train) [98][380/940] lr: 1.0000e-04 eta: 0:20:37 time: 0.5167 data_time: 0.0299 memory: 21547 grad_norm: 4.8562 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2371 loss: 1.2371 2022/10/10 11:26:22 - mmengine - INFO - Epoch(train) [98][400/940] lr: 1.0000e-04 eta: 0:20:27 time: 0.5327 data_time: 0.0253 memory: 21547 grad_norm: 4.9053 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0935 loss: 1.0935 2022/10/10 11:26:33 - mmengine - INFO - Epoch(train) [98][420/940] lr: 1.0000e-04 eta: 0:20:17 time: 0.5465 data_time: 0.0278 memory: 21547 grad_norm: 4.8633 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2026 loss: 1.2026 2022/10/10 11:26:43 - mmengine - INFO - Epoch(train) [98][440/940] lr: 1.0000e-04 eta: 0:20:07 time: 0.4850 data_time: 0.0261 memory: 21547 grad_norm: 4.7478 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0516 loss: 1.0516 2022/10/10 11:26:53 - mmengine - INFO - Epoch(train) [98][460/940] lr: 1.0000e-04 eta: 0:19:57 time: 0.5254 data_time: 0.0315 memory: 21547 grad_norm: 4.8006 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1811 loss: 1.1811 2022/10/10 11:27:03 - mmengine - INFO - Epoch(train) [98][480/940] lr: 1.0000e-04 eta: 0:19:47 time: 0.4789 data_time: 0.0252 memory: 21547 grad_norm: 4.7677 top1_acc: 0.8438 top5_acc: 0.8438 loss_cls: 1.1329 loss: 1.1329 2022/10/10 11:27:13 - mmengine - INFO - Epoch(train) [98][500/940] lr: 1.0000e-04 eta: 0:19:36 time: 0.5098 data_time: 0.0286 memory: 21547 grad_norm: 4.8357 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2554 loss: 1.2554 2022/10/10 11:27:22 - mmengine - INFO - Epoch(train) [98][520/940] lr: 1.0000e-04 eta: 0:19:26 time: 0.4537 data_time: 0.0273 memory: 21547 grad_norm: 4.7882 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1555 loss: 1.1555 2022/10/10 11:27:33 - mmengine - INFO - Epoch(train) [98][540/940] lr: 1.0000e-04 eta: 0:19:16 time: 0.5152 data_time: 0.0252 memory: 21547 grad_norm: 4.7838 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1692 loss: 1.1692 2022/10/10 11:27:43 - mmengine - INFO - Epoch(train) [98][560/940] lr: 1.0000e-04 eta: 0:19:06 time: 0.5124 data_time: 0.0285 memory: 21547 grad_norm: 4.7588 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9857 loss: 0.9857 2022/10/10 11:27:52 - mmengine - INFO - Epoch(train) [98][580/940] lr: 1.0000e-04 eta: 0:18:56 time: 0.4424 data_time: 0.0255 memory: 21547 grad_norm: 4.9057 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0752 loss: 1.0752 2022/10/10 11:28:03 - mmengine - INFO - Epoch(train) [98][600/940] lr: 1.0000e-04 eta: 0:18:46 time: 0.5454 data_time: 0.0300 memory: 21547 grad_norm: 4.8923 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2249 loss: 1.2249 2022/10/10 11:28:12 - mmengine - INFO - Epoch(train) [98][620/940] lr: 1.0000e-04 eta: 0:18:35 time: 0.4746 data_time: 0.0339 memory: 21547 grad_norm: 4.8041 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2059 loss: 1.2059 2022/10/10 11:28:24 - mmengine - INFO - Epoch(train) [98][640/940] lr: 1.0000e-04 eta: 0:18:25 time: 0.5715 data_time: 0.0248 memory: 21547 grad_norm: 4.9320 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1167 loss: 1.1167 2022/10/10 11:28:34 - mmengine - INFO - Epoch(train) [98][660/940] lr: 1.0000e-04 eta: 0:18:15 time: 0.5082 data_time: 0.0270 memory: 21547 grad_norm: 4.8061 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.1459 loss: 1.1459 2022/10/10 11:28:44 - mmengine - INFO - Epoch(train) [98][680/940] lr: 1.0000e-04 eta: 0:18:05 time: 0.5116 data_time: 0.0284 memory: 21547 grad_norm: 4.8318 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1802 loss: 1.1802 2022/10/10 11:28:54 - mmengine - INFO - Epoch(train) [98][700/940] lr: 1.0000e-04 eta: 0:17:55 time: 0.4911 data_time: 0.0270 memory: 21547 grad_norm: 4.7768 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.1978 loss: 1.1978 2022/10/10 11:29:04 - mmengine - INFO - Epoch(train) [98][720/940] lr: 1.0000e-04 eta: 0:17:45 time: 0.5163 data_time: 0.0255 memory: 21547 grad_norm: 4.9442 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1530 loss: 1.1530 2022/10/10 11:29:14 - mmengine - INFO - Epoch(train) [98][740/940] lr: 1.0000e-04 eta: 0:17:35 time: 0.5036 data_time: 0.0272 memory: 21547 grad_norm: 4.8262 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2690 loss: 1.2690 2022/10/10 11:29:24 - mmengine - INFO - Epoch(train) [98][760/940] lr: 1.0000e-04 eta: 0:17:24 time: 0.4757 data_time: 0.0258 memory: 21547 grad_norm: 4.7951 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0393 loss: 1.0393 2022/10/10 11:29:33 - mmengine - INFO - Epoch(train) [98][780/940] lr: 1.0000e-04 eta: 0:17:14 time: 0.4800 data_time: 0.0256 memory: 21547 grad_norm: 4.7593 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1699 loss: 1.1699 2022/10/10 11:29:44 - mmengine - INFO - Epoch(train) [98][800/940] lr: 1.0000e-04 eta: 0:17:04 time: 0.5501 data_time: 0.0278 memory: 21547 grad_norm: 4.9563 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1851 loss: 1.1851 2022/10/10 11:29:55 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 11:29:55 - mmengine - INFO - Epoch(train) [98][820/940] lr: 1.0000e-04 eta: 0:16:54 time: 0.5298 data_time: 0.0307 memory: 21547 grad_norm: 4.8364 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1599 loss: 1.1599 2022/10/10 11:30:04 - mmengine - INFO - Epoch(train) [98][840/940] lr: 1.0000e-04 eta: 0:16:44 time: 0.4666 data_time: 0.0318 memory: 21547 grad_norm: 4.8647 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0489 loss: 1.0489 2022/10/10 11:30:14 - mmengine - INFO - Epoch(train) [98][860/940] lr: 1.0000e-04 eta: 0:16:34 time: 0.4633 data_time: 0.0261 memory: 21547 grad_norm: 4.8194 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1722 loss: 1.1722 2022/10/10 11:30:24 - mmengine - INFO - Epoch(train) [98][880/940] lr: 1.0000e-04 eta: 0:16:24 time: 0.5161 data_time: 0.0367 memory: 21547 grad_norm: 4.8712 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.2080 loss: 1.2080 2022/10/10 11:30:34 - mmengine - INFO - Epoch(train) [98][900/940] lr: 1.0000e-04 eta: 0:16:13 time: 0.4862 data_time: 0.0263 memory: 21547 grad_norm: 4.8951 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1279 loss: 1.1279 2022/10/10 11:30:44 - mmengine - INFO - Epoch(train) [98][920/940] lr: 1.0000e-04 eta: 0:16:03 time: 0.5072 data_time: 0.0284 memory: 21547 grad_norm: 4.8635 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2032 loss: 1.2032 2022/10/10 11:30:53 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 11:30:53 - mmengine - INFO - Epoch(train) [98][940/940] lr: 1.0000e-04 eta: 0:15:53 time: 0.4646 data_time: 0.0217 memory: 21547 grad_norm: 5.0920 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.0922 loss: 1.0922 2022/10/10 11:31:05 - mmengine - INFO - Epoch(val) [98][20/78] eta: 0:00:34 time: 0.6029 data_time: 0.4950 memory: 3269 2022/10/10 11:31:14 - mmengine - INFO - Epoch(val) [98][40/78] eta: 0:00:16 time: 0.4294 data_time: 0.3222 memory: 3269 2022/10/10 11:31:25 - mmengine - INFO - Epoch(val) [98][60/78] eta: 0:00:10 time: 0.5565 data_time: 0.4506 memory: 3269 2022/10/10 11:31:35 - mmengine - INFO - Epoch(val) [98][78/78] acc/top1: 0.6810 acc/top5: 0.8714 acc/mean1: 0.6809 2022/10/10 11:31:49 - mmengine - INFO - Epoch(train) [99][20/940] lr: 1.0000e-04 eta: 0:15:43 time: 0.7131 data_time: 0.2726 memory: 21547 grad_norm: 4.8464 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1914 loss: 1.1914 2022/10/10 11:31:59 - mmengine - INFO - Epoch(train) [99][40/940] lr: 1.0000e-04 eta: 0:15:33 time: 0.4887 data_time: 0.0762 memory: 21547 grad_norm: 4.8623 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1285 loss: 1.1285 2022/10/10 11:32:09 - mmengine - INFO - Epoch(train) [99][60/940] lr: 1.0000e-04 eta: 0:15:23 time: 0.5225 data_time: 0.0338 memory: 21547 grad_norm: 4.8927 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3315 loss: 1.3315 2022/10/10 11:32:19 - mmengine - INFO - Epoch(train) [99][80/940] lr: 1.0000e-04 eta: 0:15:13 time: 0.4752 data_time: 0.0641 memory: 21547 grad_norm: 4.8450 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1810 loss: 1.1810 2022/10/10 11:32:30 - mmengine - INFO - Epoch(train) [99][100/940] lr: 1.0000e-04 eta: 0:15:02 time: 0.5565 data_time: 0.0712 memory: 21547 grad_norm: 4.7195 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0551 loss: 1.0551 2022/10/10 11:32:39 - mmengine - INFO - Epoch(train) [99][120/940] lr: 1.0000e-04 eta: 0:14:52 time: 0.4591 data_time: 0.0220 memory: 21547 grad_norm: 4.8684 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1327 loss: 1.1327 2022/10/10 11:32:50 - mmengine - INFO - Epoch(train) [99][140/940] lr: 1.0000e-04 eta: 0:14:42 time: 0.5502 data_time: 0.1628 memory: 21547 grad_norm: 4.8579 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1676 loss: 1.1676 2022/10/10 11:33:00 - mmengine - INFO - Epoch(train) [99][160/940] lr: 1.0000e-04 eta: 0:14:32 time: 0.4760 data_time: 0.0809 memory: 21547 grad_norm: 4.8807 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1530 loss: 1.1530 2022/10/10 11:33:10 - mmengine - INFO - Epoch(train) [99][180/940] lr: 1.0000e-04 eta: 0:14:22 time: 0.4917 data_time: 0.0569 memory: 21547 grad_norm: 4.9275 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1706 loss: 1.1706 2022/10/10 11:33:19 - mmengine - INFO - Epoch(train) [99][200/940] lr: 1.0000e-04 eta: 0:14:12 time: 0.4797 data_time: 0.0256 memory: 21547 grad_norm: 4.8601 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0450 loss: 1.0450 2022/10/10 11:33:29 - mmengine - INFO - Epoch(train) [99][220/940] lr: 1.0000e-04 eta: 0:14:02 time: 0.5022 data_time: 0.0763 memory: 21547 grad_norm: 4.8355 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2217 loss: 1.2217 2022/10/10 11:33:39 - mmengine - INFO - Epoch(train) [99][240/940] lr: 1.0000e-04 eta: 0:13:51 time: 0.5114 data_time: 0.0240 memory: 21547 grad_norm: 4.7742 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1565 loss: 1.1565 2022/10/10 11:33:50 - mmengine - INFO - Epoch(train) [99][260/940] lr: 1.0000e-04 eta: 0:13:41 time: 0.5250 data_time: 0.0320 memory: 21547 grad_norm: 4.8407 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.1919 loss: 1.1919 2022/10/10 11:34:00 - mmengine - INFO - Epoch(train) [99][280/940] lr: 1.0000e-04 eta: 0:13:31 time: 0.5134 data_time: 0.0302 memory: 21547 grad_norm: 4.8487 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0590 loss: 1.0590 2022/10/10 11:34:10 - mmengine - INFO - Epoch(train) [99][300/940] lr: 1.0000e-04 eta: 0:13:21 time: 0.4956 data_time: 0.0356 memory: 21547 grad_norm: 4.7433 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0616 loss: 1.0616 2022/10/10 11:34:20 - mmengine - INFO - Epoch(train) [99][320/940] lr: 1.0000e-04 eta: 0:13:11 time: 0.5064 data_time: 0.0308 memory: 21547 grad_norm: 4.8047 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1994 loss: 1.1994 2022/10/10 11:34:31 - mmengine - INFO - Epoch(train) [99][340/940] lr: 1.0000e-04 eta: 0:13:01 time: 0.5456 data_time: 0.0264 memory: 21547 grad_norm: 4.8109 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1833 loss: 1.1833 2022/10/10 11:34:40 - mmengine - INFO - Epoch(train) [99][360/940] lr: 1.0000e-04 eta: 0:12:51 time: 0.4685 data_time: 0.0270 memory: 21547 grad_norm: 4.7508 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0749 loss: 1.0749 2022/10/10 11:34:52 - mmengine - INFO - Epoch(train) [99][380/940] lr: 1.0000e-04 eta: 0:12:40 time: 0.5574 data_time: 0.0288 memory: 21547 grad_norm: 4.8247 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0039 loss: 1.0039 2022/10/10 11:35:01 - mmengine - INFO - Epoch(train) [99][400/940] lr: 1.0000e-04 eta: 0:12:30 time: 0.4666 data_time: 0.0307 memory: 21547 grad_norm: 4.7565 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0831 loss: 1.0831 2022/10/10 11:35:11 - mmengine - INFO - Epoch(train) [99][420/940] lr: 1.0000e-04 eta: 0:12:20 time: 0.4912 data_time: 0.0238 memory: 21547 grad_norm: 4.8114 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0069 loss: 1.0069 2022/10/10 11:35:21 - mmengine - INFO - Epoch(train) [99][440/940] lr: 1.0000e-04 eta: 0:12:10 time: 0.5257 data_time: 0.0288 memory: 21547 grad_norm: 4.8114 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2980 loss: 1.2980 2022/10/10 11:35:32 - mmengine - INFO - Epoch(train) [99][460/940] lr: 1.0000e-04 eta: 0:12:00 time: 0.5439 data_time: 0.0238 memory: 21547 grad_norm: 4.7856 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.0737 loss: 1.0737 2022/10/10 11:35:42 - mmengine - INFO - Epoch(train) [99][480/940] lr: 1.0000e-04 eta: 0:11:50 time: 0.4805 data_time: 0.0271 memory: 21547 grad_norm: 4.7793 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1692 loss: 1.1692 2022/10/10 11:35:52 - mmengine - INFO - Epoch(train) [99][500/940] lr: 1.0000e-04 eta: 0:11:40 time: 0.4860 data_time: 0.0259 memory: 21547 grad_norm: 4.8261 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2035 loss: 1.2035 2022/10/10 11:36:01 - mmengine - INFO - Epoch(train) [99][520/940] lr: 1.0000e-04 eta: 0:11:29 time: 0.4535 data_time: 0.0280 memory: 21547 grad_norm: 4.8418 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1120 loss: 1.1120 2022/10/10 11:36:11 - mmengine - INFO - Epoch(train) [99][540/940] lr: 1.0000e-04 eta: 0:11:19 time: 0.5077 data_time: 0.0263 memory: 21547 grad_norm: 4.7689 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2164 loss: 1.2164 2022/10/10 11:36:21 - mmengine - INFO - Epoch(train) [99][560/940] lr: 1.0000e-04 eta: 0:11:09 time: 0.4991 data_time: 0.0316 memory: 21547 grad_norm: 4.8066 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1985 loss: 1.1985 2022/10/10 11:36:32 - mmengine - INFO - Epoch(train) [99][580/940] lr: 1.0000e-04 eta: 0:10:59 time: 0.5409 data_time: 0.0278 memory: 21547 grad_norm: 4.9012 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.2870 loss: 1.2870 2022/10/10 11:36:41 - mmengine - INFO - Epoch(train) [99][600/940] lr: 1.0000e-04 eta: 0:10:49 time: 0.4697 data_time: 0.0370 memory: 21547 grad_norm: 4.7653 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1310 loss: 1.1310 2022/10/10 11:36:51 - mmengine - INFO - Epoch(train) [99][620/940] lr: 1.0000e-04 eta: 0:10:39 time: 0.4989 data_time: 0.0285 memory: 21547 grad_norm: 4.7907 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1087 loss: 1.1087 2022/10/10 11:37:01 - mmengine - INFO - Epoch(train) [99][640/940] lr: 1.0000e-04 eta: 0:10:28 time: 0.4960 data_time: 0.0292 memory: 21547 grad_norm: 4.8498 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1533 loss: 1.1533 2022/10/10 11:37:11 - mmengine - INFO - Epoch(train) [99][660/940] lr: 1.0000e-04 eta: 0:10:18 time: 0.5006 data_time: 0.0335 memory: 21547 grad_norm: 4.9632 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2456 loss: 1.2456 2022/10/10 11:37:21 - mmengine - INFO - Epoch(train) [99][680/940] lr: 1.0000e-04 eta: 0:10:08 time: 0.5097 data_time: 0.0247 memory: 21547 grad_norm: 4.9323 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1789 loss: 1.1789 2022/10/10 11:37:31 - mmengine - INFO - Epoch(train) [99][700/940] lr: 1.0000e-04 eta: 0:09:58 time: 0.5055 data_time: 0.0290 memory: 21547 grad_norm: 4.8243 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0897 loss: 1.0897 2022/10/10 11:37:41 - mmengine - INFO - Epoch(train) [99][720/940] lr: 1.0000e-04 eta: 0:09:48 time: 0.4916 data_time: 0.0244 memory: 21547 grad_norm: 4.8293 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1053 loss: 1.1053 2022/10/10 11:37:51 - mmengine - INFO - Epoch(train) [99][740/940] lr: 1.0000e-04 eta: 0:09:38 time: 0.5155 data_time: 0.0355 memory: 21547 grad_norm: 4.9269 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1414 loss: 1.1414 2022/10/10 11:38:02 - mmengine - INFO - Epoch(train) [99][760/940] lr: 1.0000e-04 eta: 0:09:28 time: 0.5093 data_time: 0.0305 memory: 21547 grad_norm: 4.8552 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0567 loss: 1.0567 2022/10/10 11:38:12 - mmengine - INFO - Epoch(train) [99][780/940] lr: 1.0000e-04 eta: 0:09:17 time: 0.5425 data_time: 0.0305 memory: 21547 grad_norm: 4.8946 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1377 loss: 1.1377 2022/10/10 11:38:22 - mmengine - INFO - Epoch(train) [99][800/940] lr: 1.0000e-04 eta: 0:09:07 time: 0.4996 data_time: 0.0285 memory: 21547 grad_norm: 4.8066 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1460 loss: 1.1460 2022/10/10 11:38:32 - mmengine - INFO - Epoch(train) [99][820/940] lr: 1.0000e-04 eta: 0:08:57 time: 0.5038 data_time: 0.0320 memory: 21547 grad_norm: 4.8009 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2237 loss: 1.2237 2022/10/10 11:38:42 - mmengine - INFO - Epoch(train) [99][840/940] lr: 1.0000e-04 eta: 0:08:47 time: 0.4884 data_time: 0.0273 memory: 21547 grad_norm: 4.8891 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1686 loss: 1.1686 2022/10/10 11:38:52 - mmengine - INFO - Epoch(train) [99][860/940] lr: 1.0000e-04 eta: 0:08:37 time: 0.4867 data_time: 0.0269 memory: 21547 grad_norm: 4.7990 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2086 loss: 1.2086 2022/10/10 11:39:03 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 11:39:03 - mmengine - INFO - Epoch(train) [99][880/940] lr: 1.0000e-04 eta: 0:08:27 time: 0.5322 data_time: 0.0288 memory: 21547 grad_norm: 4.8458 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2258 loss: 1.2258 2022/10/10 11:39:13 - mmengine - INFO - Epoch(train) [99][900/940] lr: 1.0000e-04 eta: 0:08:17 time: 0.5122 data_time: 0.0220 memory: 21547 grad_norm: 4.8664 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3039 loss: 1.3039 2022/10/10 11:39:22 - mmengine - INFO - Epoch(train) [99][920/940] lr: 1.0000e-04 eta: 0:08:06 time: 0.4501 data_time: 0.0233 memory: 21547 grad_norm: 4.8571 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1339 loss: 1.1339 2022/10/10 11:39:31 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 11:39:31 - mmengine - INFO - Epoch(train) [99][940/940] lr: 1.0000e-04 eta: 0:07:56 time: 0.4597 data_time: 0.0270 memory: 21547 grad_norm: 5.0298 top1_acc: 0.2857 top5_acc: 0.8571 loss_cls: 1.3208 loss: 1.3208 2022/10/10 11:39:31 - mmengine - INFO - Saving checkpoint at 99 epochs 2022/10/10 11:39:44 - mmengine - INFO - Epoch(val) [99][20/78] eta: 0:00:35 time: 0.6122 data_time: 0.5050 memory: 3269 2022/10/10 11:39:53 - mmengine - INFO - Epoch(val) [99][40/78] eta: 0:00:16 time: 0.4230 data_time: 0.3181 memory: 3269 2022/10/10 11:40:04 - mmengine - INFO - Epoch(val) [99][60/78] eta: 0:00:10 time: 0.5596 data_time: 0.4536 memory: 3269 2022/10/10 11:40:13 - mmengine - INFO - Epoch(val) [99][78/78] acc/top1: 0.6790 acc/top5: 0.8716 acc/mean1: 0.6789 2022/10/10 11:40:27 - mmengine - INFO - Epoch(train) [100][20/940] lr: 1.0000e-04 eta: 0:07:46 time: 0.6977 data_time: 0.2675 memory: 21547 grad_norm: 4.7721 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2404 loss: 1.2404 2022/10/10 11:40:37 - mmengine - INFO - Epoch(train) [100][40/940] lr: 1.0000e-04 eta: 0:07:36 time: 0.4995 data_time: 0.0284 memory: 21547 grad_norm: 4.8510 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2744 loss: 1.2744 2022/10/10 11:40:48 - mmengine - INFO - Epoch(train) [100][60/940] lr: 1.0000e-04 eta: 0:07:26 time: 0.5507 data_time: 0.0447 memory: 21547 grad_norm: 4.9032 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1964 loss: 1.1964 2022/10/10 11:40:59 - mmengine - INFO - Epoch(train) [100][80/940] lr: 1.0000e-04 eta: 0:07:16 time: 0.5264 data_time: 0.0227 memory: 21547 grad_norm: 4.8302 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1619 loss: 1.1619 2022/10/10 11:41:08 - mmengine - INFO - Epoch(train) [100][100/940] lr: 1.0000e-04 eta: 0:07:06 time: 0.4902 data_time: 0.0313 memory: 21547 grad_norm: 4.9201 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2303 loss: 1.2303 2022/10/10 11:41:18 - mmengine - INFO - Epoch(train) [100][120/940] lr: 1.0000e-04 eta: 0:06:55 time: 0.4807 data_time: 0.0295 memory: 21547 grad_norm: 4.7669 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0936 loss: 1.0936 2022/10/10 11:41:28 - mmengine - INFO - Epoch(train) [100][140/940] lr: 1.0000e-04 eta: 0:06:45 time: 0.5052 data_time: 0.0300 memory: 21547 grad_norm: 4.8650 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1272 loss: 1.1272 2022/10/10 11:41:38 - mmengine - INFO - Epoch(train) [100][160/940] lr: 1.0000e-04 eta: 0:06:35 time: 0.4961 data_time: 0.0300 memory: 21547 grad_norm: 4.9232 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.2074 loss: 1.2074 2022/10/10 11:41:48 - mmengine - INFO - Epoch(train) [100][180/940] lr: 1.0000e-04 eta: 0:06:25 time: 0.4977 data_time: 0.0262 memory: 21547 grad_norm: 4.9922 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3561 loss: 1.3561 2022/10/10 11:41:57 - mmengine - INFO - Epoch(train) [100][200/940] lr: 1.0000e-04 eta: 0:06:15 time: 0.4778 data_time: 0.0269 memory: 21547 grad_norm: 4.8113 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1124 loss: 1.1124 2022/10/10 11:42:08 - mmengine - INFO - Epoch(train) [100][220/940] lr: 1.0000e-04 eta: 0:06:05 time: 0.5227 data_time: 0.0305 memory: 21547 grad_norm: 4.8712 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2080 loss: 1.2080 2022/10/10 11:42:18 - mmengine - INFO - Epoch(train) [100][240/940] lr: 1.0000e-04 eta: 0:05:55 time: 0.5079 data_time: 0.0268 memory: 21547 grad_norm: 4.8451 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.1387 loss: 1.1387 2022/10/10 11:42:29 - mmengine - INFO - Epoch(train) [100][260/940] lr: 1.0000e-04 eta: 0:05:44 time: 0.5332 data_time: 0.0336 memory: 21547 grad_norm: 4.8560 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2293 loss: 1.2293 2022/10/10 11:42:39 - mmengine - INFO - Epoch(train) [100][280/940] lr: 1.0000e-04 eta: 0:05:34 time: 0.5307 data_time: 0.0291 memory: 21547 grad_norm: 4.8843 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1170 loss: 1.1170 2022/10/10 11:42:50 - mmengine - INFO - Epoch(train) [100][300/940] lr: 1.0000e-04 eta: 0:05:24 time: 0.5352 data_time: 0.0277 memory: 21547 grad_norm: 4.7497 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2447 loss: 1.2447 2022/10/10 11:42:59 - mmengine - INFO - Epoch(train) [100][320/940] lr: 1.0000e-04 eta: 0:05:14 time: 0.4631 data_time: 0.0271 memory: 21547 grad_norm: 4.8345 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1714 loss: 1.1714 2022/10/10 11:43:10 - mmengine - INFO - Epoch(train) [100][340/940] lr: 1.0000e-04 eta: 0:05:04 time: 0.5516 data_time: 0.0267 memory: 21547 grad_norm: 4.8580 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2221 loss: 1.2221 2022/10/10 11:43:20 - mmengine - INFO - Epoch(train) [100][360/940] lr: 1.0000e-04 eta: 0:04:54 time: 0.4813 data_time: 0.0295 memory: 21547 grad_norm: 4.8241 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0330 loss: 1.0330 2022/10/10 11:43:30 - mmengine - INFO - Epoch(train) [100][380/940] lr: 1.0000e-04 eta: 0:04:44 time: 0.4993 data_time: 0.0251 memory: 21547 grad_norm: 4.9100 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2654 loss: 1.2654 2022/10/10 11:43:40 - mmengine - INFO - Epoch(train) [100][400/940] lr: 1.0000e-04 eta: 0:04:33 time: 0.4897 data_time: 0.0272 memory: 21547 grad_norm: 4.8629 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0693 loss: 1.0693 2022/10/10 11:43:51 - mmengine - INFO - Epoch(train) [100][420/940] lr: 1.0000e-04 eta: 0:04:23 time: 0.5400 data_time: 0.0258 memory: 21547 grad_norm: 4.8743 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1375 loss: 1.1375 2022/10/10 11:44:00 - mmengine - INFO - Epoch(train) [100][440/940] lr: 1.0000e-04 eta: 0:04:13 time: 0.4894 data_time: 0.0297 memory: 21547 grad_norm: 4.7916 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1334 loss: 1.1334 2022/10/10 11:44:10 - mmengine - INFO - Epoch(train) [100][460/940] lr: 1.0000e-04 eta: 0:04:03 time: 0.4888 data_time: 0.0385 memory: 21547 grad_norm: 4.8279 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.2080 loss: 1.2080 2022/10/10 11:44:20 - mmengine - INFO - Epoch(train) [100][480/940] lr: 1.0000e-04 eta: 0:03:53 time: 0.4816 data_time: 0.0286 memory: 21547 grad_norm: 4.8089 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.1486 loss: 1.1486 2022/10/10 11:44:30 - mmengine - INFO - Epoch(train) [100][500/940] lr: 1.0000e-04 eta: 0:03:43 time: 0.5123 data_time: 0.0309 memory: 21547 grad_norm: 4.9271 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1767 loss: 1.1767 2022/10/10 11:44:40 - mmengine - INFO - Epoch(train) [100][520/940] lr: 1.0000e-04 eta: 0:03:33 time: 0.4994 data_time: 0.0288 memory: 21547 grad_norm: 4.8534 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1756 loss: 1.1756 2022/10/10 11:44:50 - mmengine - INFO - Epoch(train) [100][540/940] lr: 1.0000e-04 eta: 0:03:22 time: 0.5084 data_time: 0.0339 memory: 21547 grad_norm: 4.8037 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2790 loss: 1.2790 2022/10/10 11:45:00 - mmengine - INFO - Epoch(train) [100][560/940] lr: 1.0000e-04 eta: 0:03:12 time: 0.4913 data_time: 0.0274 memory: 21547 grad_norm: 4.8334 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1739 loss: 1.1739 2022/10/10 11:45:11 - mmengine - INFO - Epoch(train) [100][580/940] lr: 1.0000e-04 eta: 0:03:02 time: 0.5293 data_time: 0.0302 memory: 21547 grad_norm: 4.7700 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0328 loss: 1.0328 2022/10/10 11:45:21 - mmengine - INFO - Epoch(train) [100][600/940] lr: 1.0000e-04 eta: 0:02:52 time: 0.5374 data_time: 0.0304 memory: 21547 grad_norm: 4.9048 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.2489 loss: 1.2489 2022/10/10 11:45:32 - mmengine - INFO - Epoch(train) [100][620/940] lr: 1.0000e-04 eta: 0:02:42 time: 0.5139 data_time: 0.0211 memory: 21547 grad_norm: 4.8902 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2182 loss: 1.2182 2022/10/10 11:45:42 - mmengine - INFO - Epoch(train) [100][640/940] lr: 1.0000e-04 eta: 0:02:32 time: 0.5155 data_time: 0.0261 memory: 21547 grad_norm: 4.8495 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1516 loss: 1.1516 2022/10/10 11:45:52 - mmengine - INFO - Epoch(train) [100][660/940] lr: 1.0000e-04 eta: 0:02:22 time: 0.5148 data_time: 0.0271 memory: 21547 grad_norm: 4.8554 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1028 loss: 1.1028 2022/10/10 11:46:03 - mmengine - INFO - Epoch(train) [100][680/940] lr: 1.0000e-04 eta: 0:02:11 time: 0.5110 data_time: 0.0280 memory: 21547 grad_norm: 4.7564 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0799 loss: 1.0799 2022/10/10 11:46:13 - mmengine - INFO - Epoch(train) [100][700/940] lr: 1.0000e-04 eta: 0:02:01 time: 0.5018 data_time: 0.0223 memory: 21547 grad_norm: 4.7460 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2181 loss: 1.2181 2022/10/10 11:46:22 - mmengine - INFO - Epoch(train) [100][720/940] lr: 1.0000e-04 eta: 0:01:51 time: 0.4698 data_time: 0.0298 memory: 21547 grad_norm: 4.8316 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1314 loss: 1.1314 2022/10/10 11:46:33 - mmengine - INFO - Epoch(train) [100][740/940] lr: 1.0000e-04 eta: 0:01:41 time: 0.5576 data_time: 0.0275 memory: 21547 grad_norm: 4.7881 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0978 loss: 1.0978 2022/10/10 11:46:43 - mmengine - INFO - Epoch(train) [100][760/940] lr: 1.0000e-04 eta: 0:01:31 time: 0.4904 data_time: 0.0258 memory: 21547 grad_norm: 4.8579 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1397 loss: 1.1397 2022/10/10 11:46:53 - mmengine - INFO - Epoch(train) [100][780/940] lr: 1.0000e-04 eta: 0:01:21 time: 0.4998 data_time: 0.0254 memory: 21547 grad_norm: 4.7880 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1761 loss: 1.1761 2022/10/10 11:47:02 - mmengine - INFO - Epoch(train) [100][800/940] lr: 1.0000e-04 eta: 0:01:11 time: 0.4701 data_time: 0.0284 memory: 21547 grad_norm: 4.8176 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0735 loss: 1.0735 2022/10/10 11:47:13 - mmengine - INFO - Epoch(train) [100][820/940] lr: 1.0000e-04 eta: 0:01:00 time: 0.5517 data_time: 0.0289 memory: 21547 grad_norm: 4.8394 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2105 loss: 1.2105 2022/10/10 11:47:23 - mmengine - INFO - Epoch(train) [100][840/940] lr: 1.0000e-04 eta: 0:00:50 time: 0.4872 data_time: 0.0336 memory: 21547 grad_norm: 5.0591 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2187 loss: 1.2187 2022/10/10 11:47:33 - mmengine - INFO - Epoch(train) [100][860/940] lr: 1.0000e-04 eta: 0:00:40 time: 0.5122 data_time: 0.0249 memory: 21547 grad_norm: 4.8293 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2247 loss: 1.2247 2022/10/10 11:47:42 - mmengine - INFO - Epoch(train) [100][880/940] lr: 1.0000e-04 eta: 0:00:30 time: 0.4167 data_time: 0.0319 memory: 21547 grad_norm: 4.8838 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1558 loss: 1.1558 2022/10/10 11:47:52 - mmengine - INFO - Epoch(train) [100][900/940] lr: 1.0000e-04 eta: 0:00:20 time: 0.5133 data_time: 0.0962 memory: 21547 grad_norm: 4.7583 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0308 loss: 1.0308 2022/10/10 11:48:02 - mmengine - INFO - Epoch(train) [100][920/940] lr: 1.0000e-04 eta: 0:00:10 time: 0.5126 data_time: 0.1136 memory: 21547 grad_norm: 4.8305 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1423 loss: 1.1423 2022/10/10 11:48:11 - mmengine - INFO - Exp name: c2d_nopool_imagenet-pretrained-r50_8xb32-8x8x1-100e_kinetics400-rgb_ceph_20221009_212352 2022/10/10 11:48:11 - mmengine - INFO - Epoch(train) [100][940/940] lr: 1.0000e-04 eta: 0:00:00 time: 0.4479 data_time: 0.0581 memory: 21547 grad_norm: 5.0951 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.9957 loss: 0.9957 2022/10/10 11:48:11 - mmengine - INFO - Saving checkpoint at 100 epochs 2022/10/10 11:48:24 - mmengine - INFO - Epoch(val) [100][20/78] eta: 0:00:35 time: 0.6109 data_time: 0.5034 memory: 3269 2022/10/10 11:48:33 - mmengine - INFO - Epoch(val) [100][40/78] eta: 0:00:15 time: 0.4197 data_time: 0.3156 memory: 3269 2022/10/10 11:48:44 - mmengine - INFO - Epoch(val) [100][60/78] eta: 0:00:10 time: 0.5565 data_time: 0.4518 memory: 3269 2022/10/10 11:48:53 - mmengine - INFO - Epoch(val) [100][78/78] acc/top1: 0.6802 acc/top5: 0.8711 acc/mean1: 0.6801