2022/10/09 05:50:34 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.7.13 (default, Mar 29 2022, 02:18:16) [GCC 7.5.0] CUDA available: True numpy_random_seed: 1539895354 GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/cache/share/cuda-11.1 NVCC: Cuda compilation tools, release 11.1, V11.1.74 GCC: gcc (GCC) 5.4.0 PyTorch: 1.10.0+cu111 PyTorch compiling details: PyTorch built with: - GCC 7.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.2.3 (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 11.1 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 - CuDNN 8.0.5 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -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+cu111 OpenCV: 4.5.5 MMEngine: 0.1.0 Runtime environment: cudnn_benchmark: False mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: None Distributed launcher: slurm Distributed training: True GPU number: 16 ------------------------------------------------------------ 2022/10/09 05:50:35 - mmengine - INFO - Config: preprocess_cfg = dict( mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], format_shape='NCTHW') model = dict( type='Recognizer3D', backbone=dict( type='ResNet3dSlowOnly', depth=50, pretrained='https://download.pytorch.org/models/resnet50-11ad3fa6.pth', lateral=False, conv1_kernel=(1, 7, 7), conv1_stride_t=1, pool1_stride_t=1, inflate=(0, 0, 1, 1), norm_eval=False), cls_head=dict( type='I3DHead', in_channels=2048, num_classes=700, spatial_type='avg', dropout_ratio=0.5, average_clips='prob'), data_preprocessor=dict( type='ActionDataPreprocessor', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], format_shape='NCTHW'), train_cfg=None, test_cfg=None) default_scope = 'mmaction' default_hooks = dict( runtime_info=dict(type='RuntimeInfoHook'), timer=dict(type='IterTimerHook'), logger=dict(type='LoggerHook', interval=20, ignore_last=False), param_scheduler=dict(type='ParamSchedulerHook'), checkpoint=dict( type='CheckpointHook', interval=4, 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 dataset_type = 'VideoDataset' data_root = 'data/kinetics700/videos_train' data_root_val = 'data/kinetics700/videos_val' ann_file_train = 'data/kinetics700/kinetics700_train_list_videos.txt' ann_file_val = 'data/kinetics700/kinetics700_val_list_videos.txt' train_pipeline = [ dict( type='DecordInit', io_backend='petrel', path_mapping=dict( {'data/kinetics700': 's3://openmmlab/datasets/action/Kinetics700'})), dict(type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ] val_pipeline = [ dict( type='DecordInit', io_backend='petrel', path_mapping=dict( {'data/kinetics700': 's3://openmmlab/datasets/action/Kinetics700'})), 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='NCTHW'), dict(type='PackActionInputs') ] test_pipeline = [ dict( type='DecordInit', io_backend='petrel', path_mapping=dict( {'data/kinetics700': 's3://openmmlab/datasets/action/Kinetics700'})), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ] train_dataloader = dict( batch_size=16, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='VideoDataset', ann_file='data/kinetics700/kinetics700_train_list_videos.txt', data_prefix=dict(video='data/kinetics700/videos_train'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics700': 's3://openmmlab/datasets/action/Kinetics700' })), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ])) val_dataloader = dict( batch_size=16, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='VideoDataset', ann_file='data/kinetics700/kinetics700_val_list_videos.txt', data_prefix=dict(video='data/kinetics700/videos_val'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics700': 's3://openmmlab/datasets/action/Kinetics700' })), 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='NCTHW'), dict(type='PackActionInputs') ], test_mode=True)) test_dataloader = dict( batch_size=1, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='VideoDataset', ann_file='data/kinetics700/kinetics700_val_list_videos.txt', data_prefix=dict(video='data/kinetics700/videos_val'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics700': 's3://openmmlab/datasets/action/Kinetics700' })), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True)) val_evaluator = dict(type='AccMetric') test_evaluator = dict(type='AccMetric') train_cfg = dict( type='EpochBasedTrainLoop', max_epochs=150, val_begin=1, val_interval=5) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') param_scheduler = [ dict(type='LinearLR', start_factor=0.1, by_epoch=True, begin=0, end=10), dict( type='MultiStepLR', begin=10, end=150, by_epoch=True, milestones=[90, 130], gamma=0.1) ] optim_wrapper = dict( optimizer=dict(type='SGD', lr=0.04, momentum=0.9, weight_decay=0.0001), clip_grad=dict(max_norm=40, norm_type=2)) file_client_args = dict( io_backend='petrel', path_mapping=dict( {'data/kinetics700': 's3://openmmlab/datasets/action/Kinetics700'})) launcher = 'slurm' work_dir = './work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb.py' 2022/10/09 05:50:39 - mmengine - INFO - load model from: https://download.pytorch.org/models/resnet50-11ad3fa6.pth 2022/10/09 05:50:41 - mmengine - INFO - These parameters in the 2d checkpoint are not loaded: {'fc.bias', 'fc.weight'} 2022/10/09 05:50:41 - mmengine - INFO - Checkpoints will be saved to /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb.py by HardDiskBackend. 2022/10/09 05:51:38 - mmengine - INFO - Epoch(train) [1][20/2119] lr: 4.0000e-03 eta: 10 days, 12:21:54 time: 2.8585 data_time: 2.4400 memory: 11108 grad_norm: 0.9825 top1_acc: 0.0000 top5_acc: 0.0625 loss_cls: 6.5605 loss: 6.5605 2022/10/09 05:51:45 - mmengine - INFO - Epoch(train) [1][40/2119] lr: 4.0000e-03 eta: 5 days, 22:06:57 time: 0.3612 data_time: 0.0223 memory: 11108 grad_norm: 0.9179 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.5595 loss: 6.5595 2022/10/09 05:51:52 - mmengine - INFO - Epoch(train) [1][60/2119] lr: 4.0000e-03 eta: 4 days, 9:36:24 time: 0.3694 data_time: 0.0188 memory: 11108 grad_norm: 0.9236 top1_acc: 0.0000 top5_acc: 0.0625 loss_cls: 6.5373 loss: 6.5373 2022/10/09 05:51:59 - mmengine - INFO - Epoch(train) [1][80/2119] lr: 4.0000e-03 eta: 3 days, 14:55:19 time: 0.3499 data_time: 0.0192 memory: 11108 grad_norm: 0.9333 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.5428 loss: 6.5428 2022/10/09 05:52:07 - mmengine - INFO - Epoch(train) [1][100/2119] lr: 4.0000e-03 eta: 3 days, 4:01:55 time: 0.3681 data_time: 0.0204 memory: 11108 grad_norm: 0.9851 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.5167 loss: 6.5167 2022/10/09 05:52:14 - mmengine - INFO - Epoch(train) [1][120/2119] lr: 4.0000e-03 eta: 2 days, 20:32:48 time: 0.3529 data_time: 0.0217 memory: 11108 grad_norm: 1.0739 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.5201 loss: 6.5201 2022/10/09 05:52:21 - mmengine - INFO - Epoch(train) [1][140/2119] lr: 4.0000e-03 eta: 2 days, 15:15:19 time: 0.3573 data_time: 0.0220 memory: 11108 grad_norm: 1.1734 top1_acc: 0.0000 top5_acc: 0.0625 loss_cls: 6.5020 loss: 6.5020 2022/10/09 05:52:28 - mmengine - INFO - Epoch(train) [1][160/2119] lr: 4.0000e-03 eta: 2 days, 11:20:22 time: 0.3621 data_time: 0.0185 memory: 11108 grad_norm: 1.2484 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.4693 loss: 6.4693 2022/10/09 05:52:35 - mmengine - INFO - Epoch(train) [1][180/2119] lr: 4.0000e-03 eta: 2 days, 8:12:50 time: 0.3540 data_time: 0.0185 memory: 11108 grad_norm: 1.3301 top1_acc: 0.0000 top5_acc: 0.0625 loss_cls: 6.4867 loss: 6.4867 2022/10/09 05:52:42 - mmengine - INFO - Epoch(train) [1][200/2119] lr: 4.0000e-03 eta: 2 days, 5:46:28 time: 0.3610 data_time: 0.0225 memory: 11108 grad_norm: 1.4084 top1_acc: 0.0000 top5_acc: 0.0625 loss_cls: 6.3937 loss: 6.3937 2022/10/09 05:52:50 - mmengine - INFO - Epoch(train) [1][220/2119] lr: 4.0000e-03 eta: 2 days, 3:49:29 time: 0.3668 data_time: 0.0236 memory: 11108 grad_norm: 1.5062 top1_acc: 0.0625 top5_acc: 0.0625 loss_cls: 6.4074 loss: 6.4074 2022/10/09 05:52:57 - mmengine - INFO - Epoch(train) [1][240/2119] lr: 4.0000e-03 eta: 2 days, 2:07:18 time: 0.3562 data_time: 0.0238 memory: 11108 grad_norm: 1.5963 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.3580 loss: 6.3580 2022/10/09 05:53:04 - mmengine - INFO - Epoch(train) [1][260/2119] lr: 4.0000e-03 eta: 2 days, 0:42:49 time: 0.3611 data_time: 0.0257 memory: 11108 grad_norm: 1.6969 top1_acc: 0.0000 top5_acc: 0.0625 loss_cls: 6.2922 loss: 6.2922 2022/10/09 05:53:11 - mmengine - INFO - Epoch(train) [1][280/2119] lr: 4.0000e-03 eta: 1 day, 23:28:57 time: 0.3573 data_time: 0.0184 memory: 11108 grad_norm: 1.8079 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 6.2309 loss: 6.2309 2022/10/09 05:53:18 - mmengine - INFO - Epoch(train) [1][300/2119] lr: 4.0000e-03 eta: 1 day, 22:24:32 time: 0.3562 data_time: 0.0171 memory: 11108 grad_norm: 1.9128 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.1963 loss: 6.1963 2022/10/09 05:53:26 - mmengine - INFO - Epoch(train) [1][320/2119] lr: 4.0000e-03 eta: 1 day, 21:30:05 time: 0.3620 data_time: 0.0196 memory: 11108 grad_norm: 2.0073 top1_acc: 0.0000 top5_acc: 0.0625 loss_cls: 6.0992 loss: 6.0992 2022/10/09 05:53:33 - mmengine - INFO - Epoch(train) [1][340/2119] lr: 4.0000e-03 eta: 1 day, 20:40:53 time: 0.3584 data_time: 0.0234 memory: 11108 grad_norm: 2.1192 top1_acc: 0.0625 top5_acc: 0.0625 loss_cls: 6.0835 loss: 6.0835 2022/10/09 05:53:40 - mmengine - INFO - Epoch(train) [1][360/2119] lr: 4.0000e-03 eta: 1 day, 19:55:51 time: 0.3540 data_time: 0.0194 memory: 11108 grad_norm: 2.2285 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 5.9166 loss: 5.9166 2022/10/09 05:53:47 - mmengine - INFO - Epoch(train) [1][380/2119] lr: 4.0000e-03 eta: 1 day, 19:17:50 time: 0.3622 data_time: 0.0214 memory: 11108 grad_norm: 2.3315 top1_acc: 0.0625 top5_acc: 0.0625 loss_cls: 5.8279 loss: 5.8279 2022/10/09 05:53:54 - mmengine - INFO - Epoch(train) [1][400/2119] lr: 4.0000e-03 eta: 1 day, 18:43:01 time: 0.3600 data_time: 0.0256 memory: 11108 grad_norm: 2.4498 top1_acc: 0.0000 top5_acc: 0.1875 loss_cls: 5.7158 loss: 5.7158 2022/10/09 05:54:01 - mmengine - INFO - Epoch(train) [1][420/2119] lr: 4.0000e-03 eta: 1 day, 18:10:10 time: 0.3546 data_time: 0.0248 memory: 11108 grad_norm: 2.5375 top1_acc: 0.0625 top5_acc: 0.0625 loss_cls: 5.7230 loss: 5.7230 2022/10/09 05:54:09 - mmengine - INFO - Epoch(train) [1][440/2119] lr: 4.0000e-03 eta: 1 day, 17:41:26 time: 0.3595 data_time: 0.0235 memory: 11108 grad_norm: 2.6409 top1_acc: 0.0625 top5_acc: 0.2500 loss_cls: 5.6377 loss: 5.6377 2022/10/09 05:54:18 - mmengine - INFO - Epoch(train) [1][460/2119] lr: 4.0000e-03 eta: 1 day, 17:40:57 time: 0.4714 data_time: 0.1436 memory: 11108 grad_norm: 2.7206 top1_acc: 0.0000 top5_acc: 0.1875 loss_cls: 5.5651 loss: 5.5651 2022/10/09 05:54:25 - mmengine - INFO - Epoch(train) [1][480/2119] lr: 4.0000e-03 eta: 1 day, 17:15:04 time: 0.3560 data_time: 0.0187 memory: 11108 grad_norm: 2.8043 top1_acc: 0.0625 top5_acc: 0.1250 loss_cls: 5.4941 loss: 5.4941 2022/10/09 05:54:32 - mmengine - INFO - Epoch(train) [1][500/2119] lr: 4.0000e-03 eta: 1 day, 16:51:33 time: 0.3575 data_time: 0.0236 memory: 11108 grad_norm: 2.8559 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 5.3539 loss: 5.3539 2022/10/09 05:54:39 - mmengine - INFO - Epoch(train) [1][520/2119] lr: 4.0000e-03 eta: 1 day, 16:29:27 time: 0.3556 data_time: 0.0194 memory: 11108 grad_norm: 2.9216 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 5.3599 loss: 5.3599 2022/10/09 05:54:47 - mmengine - INFO - Epoch(train) [1][540/2119] lr: 4.0000e-03 eta: 1 day, 16:10:53 time: 0.3653 data_time: 0.0199 memory: 11108 grad_norm: 2.9840 top1_acc: 0.0000 top5_acc: 0.0625 loss_cls: 5.1612 loss: 5.1612 2022/10/09 05:54:54 - mmengine - INFO - Epoch(train) [1][560/2119] lr: 4.0000e-03 eta: 1 day, 15:51:48 time: 0.3557 data_time: 0.0192 memory: 11108 grad_norm: 3.0461 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 5.1814 loss: 5.1814 2022/10/09 05:55:01 - mmengine - INFO - Epoch(train) [1][580/2119] lr: 4.0000e-03 eta: 1 day, 15:34:42 time: 0.3593 data_time: 0.0225 memory: 11108 grad_norm: 3.0787 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 5.1274 loss: 5.1274 2022/10/09 05:55:08 - mmengine - INFO - Epoch(train) [1][600/2119] lr: 4.0000e-03 eta: 1 day, 15:20:21 time: 0.3685 data_time: 0.0230 memory: 11108 grad_norm: 3.1355 top1_acc: 0.0625 top5_acc: 0.1250 loss_cls: 5.0000 loss: 5.0000 2022/10/09 05:55:18 - mmengine - INFO - Epoch(train) [1][620/2119] lr: 4.0000e-03 eta: 1 day, 15:24:09 time: 0.4696 data_time: 0.1374 memory: 11108 grad_norm: 3.2137 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 5.0418 loss: 5.0418 2022/10/09 05:55:25 - mmengine - INFO - Epoch(train) [1][640/2119] lr: 4.0000e-03 eta: 1 day, 15:09:48 time: 0.3612 data_time: 0.0204 memory: 11108 grad_norm: 3.2335 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 4.8468 loss: 4.8468 2022/10/09 05:55:32 - mmengine - INFO - Epoch(train) [1][660/2119] lr: 4.0000e-03 eta: 1 day, 14:56:29 time: 0.3622 data_time: 0.0268 memory: 11108 grad_norm: 3.2640 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 4.9129 loss: 4.9129 2022/10/09 05:55:39 - mmengine - INFO - Epoch(train) [1][680/2119] lr: 4.0000e-03 eta: 1 day, 14:42:40 time: 0.3540 data_time: 0.0193 memory: 11108 grad_norm: 3.3032 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 4.7841 loss: 4.7841 2022/10/09 05:55:47 - mmengine - INFO - Epoch(train) [1][700/2119] lr: 4.0000e-03 eta: 1 day, 14:30:56 time: 0.3627 data_time: 0.0229 memory: 11108 grad_norm: 3.3509 top1_acc: 0.0625 top5_acc: 0.0625 loss_cls: 4.9967 loss: 4.9967 2022/10/09 05:55:54 - mmengine - INFO - Epoch(train) [1][720/2119] lr: 4.0000e-03 eta: 1 day, 14:18:53 time: 0.3561 data_time: 0.0221 memory: 11108 grad_norm: 3.3785 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 4.6625 loss: 4.6625 2022/10/09 05:56:01 - mmengine - INFO - Epoch(train) [1][740/2119] lr: 4.0000e-03 eta: 1 day, 14:07:29 time: 0.3562 data_time: 0.0183 memory: 11108 grad_norm: 3.4316 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 4.7033 loss: 4.7033 2022/10/09 05:56:08 - mmengine - INFO - Epoch(train) [1][760/2119] lr: 4.0000e-03 eta: 1 day, 13:57:02 time: 0.3587 data_time: 0.0213 memory: 11108 grad_norm: 3.4197 top1_acc: 0.0625 top5_acc: 0.1875 loss_cls: 4.6334 loss: 4.6334 2022/10/09 05:56:15 - mmengine - INFO - Epoch(train) [1][780/2119] lr: 4.0000e-03 eta: 1 day, 13:47:10 time: 0.3591 data_time: 0.0196 memory: 11108 grad_norm: 3.4640 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 4.7984 loss: 4.7984 2022/10/09 05:56:22 - mmengine - INFO - Epoch(train) [1][800/2119] lr: 4.0000e-03 eta: 1 day, 13:37:39 time: 0.3580 data_time: 0.0204 memory: 11108 grad_norm: 3.4844 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 4.5338 loss: 4.5338 2022/10/09 05:56:29 - mmengine - INFO - Epoch(train) [1][820/2119] lr: 4.0000e-03 eta: 1 day, 13:28:31 time: 0.3575 data_time: 0.0204 memory: 11108 grad_norm: 3.5090 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 4.5246 loss: 4.5246 2022/10/09 05:56:37 - mmengine - INFO - Epoch(train) [1][840/2119] lr: 4.0000e-03 eta: 1 day, 13:19:39 time: 0.3562 data_time: 0.0219 memory: 11108 grad_norm: 3.5269 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 4.5884 loss: 4.5884 2022/10/09 05:56:44 - mmengine - INFO - Epoch(train) [1][860/2119] lr: 4.0000e-03 eta: 1 day, 13:12:01 time: 0.3628 data_time: 0.0196 memory: 11108 grad_norm: 3.5392 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 4.4240 loss: 4.4240 2022/10/09 05:56:51 - mmengine - INFO - Epoch(train) [1][880/2119] lr: 4.0000e-03 eta: 1 day, 13:03:34 time: 0.3534 data_time: 0.0246 memory: 11108 grad_norm: 3.5419 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 4.4917 loss: 4.4917 2022/10/09 05:56:58 - mmengine - INFO - Epoch(train) [1][900/2119] lr: 4.0000e-03 eta: 1 day, 12:56:14 time: 0.3596 data_time: 0.0279 memory: 11108 grad_norm: 3.5821 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.4226 loss: 4.4226 2022/10/09 05:57:05 - mmengine - INFO - Epoch(train) [1][920/2119] lr: 4.0000e-03 eta: 1 day, 12:49:17 time: 0.3603 data_time: 0.0215 memory: 11108 grad_norm: 3.5905 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 4.5335 loss: 4.5335 2022/10/09 05:57:12 - mmengine - INFO - Epoch(train) [1][940/2119] lr: 4.0000e-03 eta: 1 day, 12:41:59 time: 0.3545 data_time: 0.0215 memory: 11108 grad_norm: 3.6004 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.5077 loss: 4.5077 2022/10/09 05:57:20 - mmengine - INFO - Epoch(train) [1][960/2119] lr: 4.0000e-03 eta: 1 day, 12:35:13 time: 0.3565 data_time: 0.0190 memory: 11108 grad_norm: 3.6074 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.3527 loss: 4.3527 2022/10/09 05:57:27 - mmengine - INFO - Epoch(train) [1][980/2119] lr: 4.0000e-03 eta: 1 day, 12:28:56 time: 0.3588 data_time: 0.0198 memory: 11108 grad_norm: 3.6065 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.2999 loss: 4.2999 2022/10/09 05:57:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 05:57:34 - mmengine - INFO - Epoch(train) [1][1000/2119] lr: 4.0000e-03 eta: 1 day, 12:23:04 time: 0.3602 data_time: 0.0232 memory: 11108 grad_norm: 3.6150 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 4.4091 loss: 4.4091 2022/10/09 05:57:41 - mmengine - INFO - Epoch(train) [1][1020/2119] lr: 4.0000e-03 eta: 1 day, 12:16:49 time: 0.3544 data_time: 0.0180 memory: 11108 grad_norm: 3.6618 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 4.3862 loss: 4.3862 2022/10/09 05:57:48 - mmengine - INFO - Epoch(train) [1][1040/2119] lr: 4.0000e-03 eta: 1 day, 12:11:18 time: 0.3593 data_time: 0.0223 memory: 11108 grad_norm: 3.6937 top1_acc: 0.0625 top5_acc: 0.5000 loss_cls: 4.3609 loss: 4.3609 2022/10/09 05:57:55 - mmengine - INFO - Epoch(train) [1][1060/2119] lr: 4.0000e-03 eta: 1 day, 12:05:31 time: 0.3545 data_time: 0.0228 memory: 11108 grad_norm: 3.6841 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 4.3013 loss: 4.3013 2022/10/09 05:58:02 - mmengine - INFO - Epoch(train) [1][1080/2119] lr: 4.0000e-03 eta: 1 day, 12:00:25 time: 0.3593 data_time: 0.0203 memory: 11108 grad_norm: 3.6864 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 4.3888 loss: 4.3888 2022/10/09 05:58:10 - mmengine - INFO - Epoch(train) [1][1100/2119] lr: 4.0000e-03 eta: 1 day, 11:54:44 time: 0.3514 data_time: 0.0188 memory: 11108 grad_norm: 3.7151 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 4.3012 loss: 4.3012 2022/10/09 05:58:17 - mmengine - INFO - Epoch(train) [1][1120/2119] lr: 4.0000e-03 eta: 1 day, 11:49:56 time: 0.3587 data_time: 0.0205 memory: 11108 grad_norm: 3.7135 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.2533 loss: 4.2533 2022/10/09 05:58:24 - mmengine - INFO - Epoch(train) [1][1140/2119] lr: 4.0000e-03 eta: 1 day, 11:45:53 time: 0.3650 data_time: 0.0295 memory: 11108 grad_norm: 3.7212 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 4.1401 loss: 4.1401 2022/10/09 05:58:31 - mmengine - INFO - Epoch(train) [1][1160/2119] lr: 4.0000e-03 eta: 1 day, 11:41:20 time: 0.3579 data_time: 0.0245 memory: 11108 grad_norm: 3.7566 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 4.0471 loss: 4.0471 2022/10/09 05:58:38 - mmengine - INFO - Epoch(train) [1][1180/2119] lr: 4.0000e-03 eta: 1 day, 11:36:36 time: 0.3543 data_time: 0.0173 memory: 11108 grad_norm: 3.7399 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 4.3532 loss: 4.3532 2022/10/09 05:58:45 - mmengine - INFO - Epoch(train) [1][1200/2119] lr: 4.0000e-03 eta: 1 day, 11:32:26 time: 0.3590 data_time: 0.0222 memory: 11108 grad_norm: 3.7471 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 4.2856 loss: 4.2856 2022/10/09 05:58:53 - mmengine - INFO - Epoch(train) [1][1220/2119] lr: 4.0000e-03 eta: 1 day, 11:28:06 time: 0.3556 data_time: 0.0187 memory: 11108 grad_norm: 3.7800 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 4.2815 loss: 4.2815 2022/10/09 05:59:00 - mmengine - INFO - Epoch(train) [1][1240/2119] lr: 4.0000e-03 eta: 1 day, 11:23:48 time: 0.3543 data_time: 0.0238 memory: 11108 grad_norm: 3.7936 top1_acc: 0.1875 top5_acc: 0.2500 loss_cls: 4.3957 loss: 4.3957 2022/10/09 05:59:07 - mmengine - INFO - Epoch(train) [1][1260/2119] lr: 4.0000e-03 eta: 1 day, 11:19:52 time: 0.3571 data_time: 0.0218 memory: 11108 grad_norm: 3.7670 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.4150 loss: 4.4150 2022/10/09 05:59:14 - mmengine - INFO - Epoch(train) [1][1280/2119] lr: 4.0000e-03 eta: 1 day, 11:16:02 time: 0.3569 data_time: 0.0202 memory: 11108 grad_norm: 3.7940 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 4.1157 loss: 4.1157 2022/10/09 05:59:21 - mmengine - INFO - Epoch(train) [1][1300/2119] lr: 4.0000e-03 eta: 1 day, 11:12:21 time: 0.3574 data_time: 0.0202 memory: 11108 grad_norm: 3.7987 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 4.2298 loss: 4.2298 2022/10/09 05:59:28 - mmengine - INFO - Epoch(train) [1][1320/2119] lr: 4.0000e-03 eta: 1 day, 11:08:42 time: 0.3564 data_time: 0.0218 memory: 11108 grad_norm: 3.7715 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 4.0798 loss: 4.0798 2022/10/09 05:59:35 - mmengine - INFO - Epoch(train) [1][1340/2119] lr: 4.0000e-03 eta: 1 day, 11:05:12 time: 0.3569 data_time: 0.0235 memory: 11108 grad_norm: 3.8278 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 4.0828 loss: 4.0828 2022/10/09 05:59:43 - mmengine - INFO - Epoch(train) [1][1360/2119] lr: 4.0000e-03 eta: 1 day, 11:02:04 time: 0.3603 data_time: 0.0233 memory: 11108 grad_norm: 3.8361 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 4.0076 loss: 4.0076 2022/10/09 05:59:50 - mmengine - INFO - Epoch(train) [1][1380/2119] lr: 4.0000e-03 eta: 1 day, 10:58:44 time: 0.3568 data_time: 0.0282 memory: 11108 grad_norm: 3.8492 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 4.0063 loss: 4.0063 2022/10/09 05:59:57 - mmengine - INFO - Epoch(train) [1][1400/2119] lr: 4.0000e-03 eta: 1 day, 10:55:20 time: 0.3544 data_time: 0.0192 memory: 11108 grad_norm: 3.8637 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 4.0216 loss: 4.0216 2022/10/09 06:00:06 - mmengine - INFO - Epoch(train) [1][1420/2119] lr: 4.0000e-03 eta: 1 day, 11:01:25 time: 0.4812 data_time: 0.0363 memory: 11108 grad_norm: 3.8521 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 4.1572 loss: 4.1572 2022/10/09 06:00:13 - mmengine - INFO - Epoch(train) [1][1440/2119] lr: 4.0000e-03 eta: 1 day, 10:58:01 time: 0.3537 data_time: 0.0211 memory: 11108 grad_norm: 3.8447 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 4.0173 loss: 4.0173 2022/10/09 06:00:21 - mmengine - INFO - Epoch(train) [1][1460/2119] lr: 4.0000e-03 eta: 1 day, 10:55:00 time: 0.3579 data_time: 0.0162 memory: 11108 grad_norm: 3.8435 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 4.2205 loss: 4.2205 2022/10/09 06:00:28 - mmengine - INFO - Epoch(train) [1][1480/2119] lr: 4.0000e-03 eta: 1 day, 10:52:09 time: 0.3592 data_time: 0.0270 memory: 11108 grad_norm: 3.8600 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 4.0664 loss: 4.0664 2022/10/09 06:00:35 - mmengine - INFO - Epoch(train) [1][1500/2119] lr: 4.0000e-03 eta: 1 day, 10:49:15 time: 0.3575 data_time: 0.0191 memory: 11108 grad_norm: 3.8704 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 4.0300 loss: 4.0300 2022/10/09 06:00:42 - mmengine - INFO - Epoch(train) [1][1520/2119] lr: 4.0000e-03 eta: 1 day, 10:46:16 time: 0.3551 data_time: 0.0231 memory: 11108 grad_norm: 3.8967 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 3.9089 loss: 3.9089 2022/10/09 06:00:49 - mmengine - INFO - Epoch(train) [1][1540/2119] lr: 4.0000e-03 eta: 1 day, 10:43:23 time: 0.3555 data_time: 0.0224 memory: 11108 grad_norm: 3.8626 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.9399 loss: 3.9399 2022/10/09 06:00:56 - mmengine - INFO - Epoch(train) [1][1560/2119] lr: 4.0000e-03 eta: 1 day, 10:40:48 time: 0.3590 data_time: 0.0200 memory: 11108 grad_norm: 3.9187 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 3.8995 loss: 3.8995 2022/10/09 06:01:03 - mmengine - INFO - Epoch(train) [1][1580/2119] lr: 4.0000e-03 eta: 1 day, 10:37:58 time: 0.3542 data_time: 0.0238 memory: 11108 grad_norm: 3.8831 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.7879 loss: 3.7879 2022/10/09 06:01:10 - mmengine - INFO - Epoch(train) [1][1600/2119] lr: 4.0000e-03 eta: 1 day, 10:35:10 time: 0.3536 data_time: 0.0196 memory: 11108 grad_norm: 3.8785 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.9995 loss: 3.9995 2022/10/09 06:01:18 - mmengine - INFO - Epoch(train) [1][1620/2119] lr: 4.0000e-03 eta: 1 day, 10:32:51 time: 0.3602 data_time: 0.0238 memory: 11108 grad_norm: 3.9227 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.0740 loss: 4.0740 2022/10/09 06:01:25 - mmengine - INFO - Epoch(train) [1][1640/2119] lr: 4.0000e-03 eta: 1 day, 10:30:24 time: 0.3573 data_time: 0.0235 memory: 11108 grad_norm: 3.9280 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 4.0059 loss: 4.0059 2022/10/09 06:01:32 - mmengine - INFO - Epoch(train) [1][1660/2119] lr: 4.0000e-03 eta: 1 day, 10:28:00 time: 0.3570 data_time: 0.0241 memory: 11108 grad_norm: 3.9261 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.9513 loss: 3.9513 2022/10/09 06:01:39 - mmengine - INFO - Epoch(train) [1][1680/2119] lr: 4.0000e-03 eta: 1 day, 10:25:31 time: 0.3549 data_time: 0.0205 memory: 11108 grad_norm: 3.9495 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 4.0576 loss: 4.0576 2022/10/09 06:01:46 - mmengine - INFO - Epoch(train) [1][1700/2119] lr: 4.0000e-03 eta: 1 day, 10:23:23 time: 0.3597 data_time: 0.0238 memory: 11108 grad_norm: 3.9756 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 3.8477 loss: 3.8477 2022/10/09 06:01:53 - mmengine - INFO - Epoch(train) [1][1720/2119] lr: 4.0000e-03 eta: 1 day, 10:21:19 time: 0.3600 data_time: 0.0191 memory: 11108 grad_norm: 3.9119 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.9221 loss: 3.9221 2022/10/09 06:02:01 - mmengine - INFO - Epoch(train) [1][1740/2119] lr: 4.0000e-03 eta: 1 day, 10:19:00 time: 0.3551 data_time: 0.0219 memory: 11108 grad_norm: 3.9140 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.8092 loss: 3.8092 2022/10/09 06:02:08 - mmengine - INFO - Epoch(train) [1][1760/2119] lr: 4.0000e-03 eta: 1 day, 10:16:47 time: 0.3559 data_time: 0.0202 memory: 11108 grad_norm: 3.9235 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.7491 loss: 3.7491 2022/10/09 06:02:15 - mmengine - INFO - Epoch(train) [1][1780/2119] lr: 4.0000e-03 eta: 1 day, 10:14:33 time: 0.3551 data_time: 0.0158 memory: 11108 grad_norm: 3.9564 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 4.0082 loss: 4.0082 2022/10/09 06:02:22 - mmengine - INFO - Epoch(train) [1][1800/2119] lr: 4.0000e-03 eta: 1 day, 10:12:28 time: 0.3566 data_time: 0.0222 memory: 11108 grad_norm: 3.9434 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.6939 loss: 3.6939 2022/10/09 06:02:29 - mmengine - INFO - Epoch(train) [1][1820/2119] lr: 4.0000e-03 eta: 1 day, 10:10:48 time: 0.3630 data_time: 0.0211 memory: 11108 grad_norm: 3.9838 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.8195 loss: 3.8195 2022/10/09 06:02:36 - mmengine - INFO - Epoch(train) [1][1840/2119] lr: 4.0000e-03 eta: 1 day, 10:08:46 time: 0.3560 data_time: 0.0227 memory: 11108 grad_norm: 3.9838 top1_acc: 0.0625 top5_acc: 0.5000 loss_cls: 3.8870 loss: 3.8870 2022/10/09 06:02:44 - mmengine - INFO - Epoch(train) [1][1860/2119] lr: 4.0000e-03 eta: 1 day, 10:07:07 time: 0.3622 data_time: 0.0191 memory: 11108 grad_norm: 4.0208 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 3.9064 loss: 3.9064 2022/10/09 06:02:51 - mmengine - INFO - Epoch(train) [1][1880/2119] lr: 4.0000e-03 eta: 1 day, 10:04:58 time: 0.3526 data_time: 0.0198 memory: 11108 grad_norm: 3.9663 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.7564 loss: 3.7564 2022/10/09 06:02:58 - mmengine - INFO - Epoch(train) [1][1900/2119] lr: 4.0000e-03 eta: 1 day, 10:03:07 time: 0.3574 data_time: 0.0216 memory: 11108 grad_norm: 3.9855 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.8014 loss: 3.8014 2022/10/09 06:03:05 - mmengine - INFO - Epoch(train) [1][1920/2119] lr: 4.0000e-03 eta: 1 day, 10:01:20 time: 0.3578 data_time: 0.0214 memory: 11108 grad_norm: 3.9712 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 3.7498 loss: 3.7498 2022/10/09 06:03:12 - mmengine - INFO - Epoch(train) [1][1940/2119] lr: 4.0000e-03 eta: 1 day, 9:59:35 time: 0.3578 data_time: 0.0211 memory: 11108 grad_norm: 3.9975 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.8300 loss: 3.8300 2022/10/09 06:03:19 - mmengine - INFO - Epoch(train) [1][1960/2119] lr: 4.0000e-03 eta: 1 day, 9:57:45 time: 0.3558 data_time: 0.0196 memory: 11108 grad_norm: 4.0019 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.9071 loss: 3.9071 2022/10/09 06:03:26 - mmengine - INFO - Epoch(train) [1][1980/2119] lr: 4.0000e-03 eta: 1 day, 9:56:01 time: 0.3566 data_time: 0.0205 memory: 11108 grad_norm: 4.0218 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.8005 loss: 3.8005 2022/10/09 06:03:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 06:03:33 - mmengine - INFO - Epoch(train) [1][2000/2119] lr: 4.0000e-03 eta: 1 day, 9:54:21 time: 0.3577 data_time: 0.0202 memory: 11108 grad_norm: 4.0108 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.8431 loss: 3.8431 2022/10/09 06:03:41 - mmengine - INFO - Epoch(train) [1][2020/2119] lr: 4.0000e-03 eta: 1 day, 9:52:29 time: 0.3532 data_time: 0.0201 memory: 11108 grad_norm: 4.0108 top1_acc: 0.0625 top5_acc: 0.1875 loss_cls: 3.7506 loss: 3.7506 2022/10/09 06:03:48 - mmengine - INFO - Epoch(train) [1][2040/2119] lr: 4.0000e-03 eta: 1 day, 9:51:04 time: 0.3611 data_time: 0.0236 memory: 11108 grad_norm: 3.9845 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.9678 loss: 3.9678 2022/10/09 06:03:55 - mmengine - INFO - Epoch(train) [1][2060/2119] lr: 4.0000e-03 eta: 1 day, 9:49:31 time: 0.3579 data_time: 0.0192 memory: 11108 grad_norm: 4.0529 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.8072 loss: 3.8072 2022/10/09 06:04:02 - mmengine - INFO - Epoch(train) [1][2080/2119] lr: 4.0000e-03 eta: 1 day, 9:47:57 time: 0.3572 data_time: 0.0243 memory: 11108 grad_norm: 4.0170 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 3.8175 loss: 3.8175 2022/10/09 06:04:09 - mmengine - INFO - Epoch(train) [1][2100/2119] lr: 4.0000e-03 eta: 1 day, 9:46:19 time: 0.3555 data_time: 0.0201 memory: 11108 grad_norm: 4.0288 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.8606 loss: 3.8606 2022/10/09 06:04:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 06:04:16 - mmengine - INFO - Epoch(train) [1][2119/2119] lr: 4.0000e-03 eta: 1 day, 9:46:19 time: 0.3387 data_time: 0.0202 memory: 11108 grad_norm: 4.0275 top1_acc: 0.4000 top5_acc: 0.6000 loss_cls: 3.6460 loss: 3.6460 2022/10/09 06:04:26 - mmengine - INFO - Epoch(train) [2][20/2119] lr: 8.0000e-03 eta: 1 day, 9:34:43 time: 0.5203 data_time: 0.1207 memory: 11108 grad_norm: 4.0324 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.6386 loss: 3.6386 2022/10/09 06:04:33 - mmengine - INFO - Epoch(train) [2][40/2119] lr: 8.0000e-03 eta: 1 day, 9:33:43 time: 0.3650 data_time: 0.0185 memory: 11108 grad_norm: 4.0867 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 4.0196 loss: 4.0196 2022/10/09 06:04:40 - mmengine - INFO - Epoch(train) [2][60/2119] lr: 8.0000e-03 eta: 1 day, 9:32:13 time: 0.3541 data_time: 0.0203 memory: 11108 grad_norm: 4.0599 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.6000 loss: 3.6000 2022/10/09 06:04:48 - mmengine - INFO - Epoch(train) [2][80/2119] lr: 8.0000e-03 eta: 1 day, 9:30:55 time: 0.3581 data_time: 0.0203 memory: 11108 grad_norm: 4.0353 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 3.9033 loss: 3.9033 2022/10/09 06:04:55 - mmengine - INFO - Epoch(train) [2][100/2119] lr: 8.0000e-03 eta: 1 day, 9:29:44 time: 0.3600 data_time: 0.0205 memory: 11108 grad_norm: 4.0547 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.7997 loss: 3.7997 2022/10/09 06:05:02 - mmengine - INFO - Epoch(train) [2][120/2119] lr: 8.0000e-03 eta: 1 day, 9:28:45 time: 0.3635 data_time: 0.0204 memory: 11108 grad_norm: 4.0813 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.5813 loss: 3.5813 2022/10/09 06:05:09 - mmengine - INFO - Epoch(train) [2][140/2119] lr: 8.0000e-03 eta: 1 day, 9:27:20 time: 0.3545 data_time: 0.0217 memory: 11108 grad_norm: 4.0579 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.5945 loss: 3.5945 2022/10/09 06:05:16 - mmengine - INFO - Epoch(train) [2][160/2119] lr: 8.0000e-03 eta: 1 day, 9:26:06 time: 0.3576 data_time: 0.0227 memory: 11108 grad_norm: 4.0971 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 3.7809 loss: 3.7809 2022/10/09 06:05:23 - mmengine - INFO - Epoch(train) [2][180/2119] lr: 8.0000e-03 eta: 1 day, 9:24:47 time: 0.3553 data_time: 0.0181 memory: 11108 grad_norm: 4.0396 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.8221 loss: 3.8221 2022/10/09 06:05:31 - mmengine - INFO - Epoch(train) [2][200/2119] lr: 8.0000e-03 eta: 1 day, 9:23:33 time: 0.3570 data_time: 0.0267 memory: 11108 grad_norm: 4.0934 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 3.8402 loss: 3.8402 2022/10/09 06:05:38 - mmengine - INFO - Epoch(train) [2][220/2119] lr: 8.0000e-03 eta: 1 day, 9:22:18 time: 0.3557 data_time: 0.0229 memory: 11108 grad_norm: 4.0678 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 3.7837 loss: 3.7837 2022/10/09 06:05:45 - mmengine - INFO - Epoch(train) [2][240/2119] lr: 8.0000e-03 eta: 1 day, 9:21:20 time: 0.3622 data_time: 0.0205 memory: 11108 grad_norm: 4.0169 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.6755 loss: 3.6755 2022/10/09 06:05:52 - mmengine - INFO - Epoch(train) [2][260/2119] lr: 8.0000e-03 eta: 1 day, 9:20:15 time: 0.3590 data_time: 0.0206 memory: 11108 grad_norm: 4.1305 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.7759 loss: 3.7759 2022/10/09 06:05:59 - mmengine - INFO - Epoch(train) [2][280/2119] lr: 8.0000e-03 eta: 1 day, 9:19:09 time: 0.3580 data_time: 0.0211 memory: 11108 grad_norm: 4.1019 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 4.0504 loss: 4.0504 2022/10/09 06:06:06 - mmengine - INFO - Epoch(train) [2][300/2119] lr: 8.0000e-03 eta: 1 day, 9:17:59 time: 0.3565 data_time: 0.0215 memory: 11108 grad_norm: 4.0308 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.7173 loss: 3.7173 2022/10/09 06:06:13 - mmengine - INFO - Epoch(train) [2][320/2119] lr: 8.0000e-03 eta: 1 day, 9:16:48 time: 0.3552 data_time: 0.0192 memory: 11108 grad_norm: 4.0570 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.7863 loss: 3.7863 2022/10/09 06:06:21 - mmengine - INFO - Epoch(train) [2][340/2119] lr: 8.0000e-03 eta: 1 day, 9:15:48 time: 0.3596 data_time: 0.0198 memory: 11108 grad_norm: 4.1030 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.8234 loss: 3.8234 2022/10/09 06:06:28 - mmengine - INFO - Epoch(train) [2][360/2119] lr: 8.0000e-03 eta: 1 day, 9:14:41 time: 0.3564 data_time: 0.0224 memory: 11108 grad_norm: 4.0640 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.4873 loss: 3.4873 2022/10/09 06:06:35 - mmengine - INFO - Epoch(train) [2][380/2119] lr: 8.0000e-03 eta: 1 day, 9:13:52 time: 0.3630 data_time: 0.0187 memory: 11108 grad_norm: 4.0502 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 3.7356 loss: 3.7356 2022/10/09 06:06:42 - mmengine - INFO - Epoch(train) [2][400/2119] lr: 8.0000e-03 eta: 1 day, 9:12:46 time: 0.3560 data_time: 0.0185 memory: 11108 grad_norm: 4.0836 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 3.6577 loss: 3.6577 2022/10/09 06:06:49 - mmengine - INFO - Epoch(train) [2][420/2119] lr: 8.0000e-03 eta: 1 day, 9:11:42 time: 0.3565 data_time: 0.0191 memory: 11108 grad_norm: 4.0958 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.7166 loss: 3.7166 2022/10/09 06:06:56 - mmengine - INFO - Epoch(train) [2][440/2119] lr: 8.0000e-03 eta: 1 day, 9:10:44 time: 0.3585 data_time: 0.0211 memory: 11108 grad_norm: 4.0341 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.3963 loss: 3.3963 2022/10/09 06:07:04 - mmengine - INFO - Epoch(train) [2][460/2119] lr: 8.0000e-03 eta: 1 day, 9:09:56 time: 0.3623 data_time: 0.0199 memory: 11108 grad_norm: 4.1029 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.6519 loss: 3.6519 2022/10/09 06:07:11 - mmengine - INFO - Epoch(train) [2][480/2119] lr: 8.0000e-03 eta: 1 day, 9:08:53 time: 0.3560 data_time: 0.0208 memory: 11108 grad_norm: 4.0615 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.7652 loss: 3.7652 2022/10/09 06:07:18 - mmengine - INFO - Epoch(train) [2][500/2119] lr: 8.0000e-03 eta: 1 day, 9:08:04 time: 0.3614 data_time: 0.0209 memory: 11108 grad_norm: 4.0642 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.6139 loss: 3.6139 2022/10/09 06:07:25 - mmengine - INFO - Epoch(train) [2][520/2119] lr: 8.0000e-03 eta: 1 day, 9:07:05 time: 0.3570 data_time: 0.0187 memory: 11108 grad_norm: 4.0719 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.5887 loss: 3.5887 2022/10/09 06:07:32 - mmengine - INFO - Epoch(train) [2][540/2119] lr: 8.0000e-03 eta: 1 day, 9:06:07 time: 0.3566 data_time: 0.0209 memory: 11108 grad_norm: 4.0814 top1_acc: 0.0000 top5_acc: 0.3125 loss_cls: 3.5370 loss: 3.5370 2022/10/09 06:07:40 - mmengine - INFO - Epoch(train) [2][560/2119] lr: 8.0000e-03 eta: 1 day, 9:05:17 time: 0.3604 data_time: 0.0218 memory: 11108 grad_norm: 4.0810 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.6980 loss: 3.6980 2022/10/09 06:07:47 - mmengine - INFO - Epoch(train) [2][580/2119] lr: 8.0000e-03 eta: 1 day, 9:04:11 time: 0.3527 data_time: 0.0219 memory: 11108 grad_norm: 4.0939 top1_acc: 0.1875 top5_acc: 0.2500 loss_cls: 3.8309 loss: 3.8309 2022/10/09 06:07:54 - mmengine - INFO - Epoch(train) [2][600/2119] lr: 8.0000e-03 eta: 1 day, 9:03:14 time: 0.3565 data_time: 0.0258 memory: 11108 grad_norm: 4.0278 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.4780 loss: 3.4780 2022/10/09 06:08:01 - mmengine - INFO - Epoch(train) [2][620/2119] lr: 8.0000e-03 eta: 1 day, 9:02:16 time: 0.3556 data_time: 0.0205 memory: 11108 grad_norm: 4.0232 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.7422 loss: 3.7422 2022/10/09 06:08:08 - mmengine - INFO - Epoch(train) [2][640/2119] lr: 8.0000e-03 eta: 1 day, 9:01:15 time: 0.3541 data_time: 0.0188 memory: 11108 grad_norm: 4.0763 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.6901 loss: 3.6901 2022/10/09 06:08:15 - mmengine - INFO - Epoch(train) [2][660/2119] lr: 8.0000e-03 eta: 1 day, 9:00:25 time: 0.3586 data_time: 0.0203 memory: 11108 grad_norm: 4.0614 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.5991 loss: 3.5991 2022/10/09 06:08:22 - mmengine - INFO - Epoch(train) [2][680/2119] lr: 8.0000e-03 eta: 1 day, 8:59:52 time: 0.3658 data_time: 0.0204 memory: 11108 grad_norm: 4.0460 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.2604 loss: 3.2604 2022/10/09 06:08:30 - mmengine - INFO - Epoch(train) [2][700/2119] lr: 8.0000e-03 eta: 1 day, 8:58:52 time: 0.3535 data_time: 0.0214 memory: 11108 grad_norm: 4.0792 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.9330 loss: 3.9330 2022/10/09 06:08:37 - mmengine - INFO - Epoch(train) [2][720/2119] lr: 8.0000e-03 eta: 1 day, 8:58:07 time: 0.3599 data_time: 0.0232 memory: 11108 grad_norm: 4.0827 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.3162 loss: 3.3162 2022/10/09 06:08:44 - mmengine - INFO - Epoch(train) [2][740/2119] lr: 8.0000e-03 eta: 1 day, 8:57:09 time: 0.3540 data_time: 0.0153 memory: 11108 grad_norm: 4.0737 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 3.3622 loss: 3.3622 2022/10/09 06:08:51 - mmengine - INFO - Epoch(train) [2][760/2119] lr: 8.0000e-03 eta: 1 day, 8:56:15 time: 0.3554 data_time: 0.0230 memory: 11108 grad_norm: 4.0761 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.3683 loss: 3.3683 2022/10/09 06:08:58 - mmengine - INFO - Epoch(train) [2][780/2119] lr: 8.0000e-03 eta: 1 day, 8:55:27 time: 0.3576 data_time: 0.0230 memory: 11108 grad_norm: 4.0864 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.4955 loss: 3.4955 2022/10/09 06:09:05 - mmengine - INFO - Epoch(train) [2][800/2119] lr: 8.0000e-03 eta: 1 day, 8:54:34 time: 0.3555 data_time: 0.0247 memory: 11108 grad_norm: 4.1045 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.6826 loss: 3.6826 2022/10/09 06:09:12 - mmengine - INFO - Epoch(train) [2][820/2119] lr: 8.0000e-03 eta: 1 day, 8:53:40 time: 0.3544 data_time: 0.0215 memory: 11108 grad_norm: 4.1175 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.5781 loss: 3.5781 2022/10/09 06:09:19 - mmengine - INFO - Epoch(train) [2][840/2119] lr: 8.0000e-03 eta: 1 day, 8:52:53 time: 0.3576 data_time: 0.0197 memory: 11108 grad_norm: 4.1373 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.6105 loss: 3.6105 2022/10/09 06:09:26 - mmengine - INFO - Epoch(train) [2][860/2119] lr: 8.0000e-03 eta: 1 day, 8:51:58 time: 0.3536 data_time: 0.0202 memory: 11108 grad_norm: 4.0854 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.5474 loss: 3.5474 2022/10/09 06:09:34 - mmengine - INFO - Epoch(train) [2][880/2119] lr: 8.0000e-03 eta: 1 day, 8:51:15 time: 0.3589 data_time: 0.0208 memory: 11108 grad_norm: 4.0650 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.4244 loss: 3.4244 2022/10/09 06:09:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 06:09:41 - mmengine - INFO - Epoch(train) [2][900/2119] lr: 8.0000e-03 eta: 1 day, 8:50:22 time: 0.3536 data_time: 0.0187 memory: 11108 grad_norm: 4.0892 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.3844 loss: 3.3844 2022/10/09 06:09:48 - mmengine - INFO - Epoch(train) [2][920/2119] lr: 8.0000e-03 eta: 1 day, 8:49:32 time: 0.3552 data_time: 0.0221 memory: 11108 grad_norm: 4.0436 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 3.3874 loss: 3.3874 2022/10/09 06:09:55 - mmengine - INFO - Epoch(train) [2][940/2119] lr: 8.0000e-03 eta: 1 day, 8:48:37 time: 0.3520 data_time: 0.0205 memory: 11108 grad_norm: 4.0974 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.4351 loss: 3.4351 2022/10/09 06:10:02 - mmengine - INFO - Epoch(train) [2][960/2119] lr: 8.0000e-03 eta: 1 day, 8:47:56 time: 0.3591 data_time: 0.0222 memory: 11108 grad_norm: 4.1151 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.5060 loss: 3.5060 2022/10/09 06:10:09 - mmengine - INFO - Epoch(train) [2][980/2119] lr: 8.0000e-03 eta: 1 day, 8:47:14 time: 0.3580 data_time: 0.0215 memory: 11108 grad_norm: 4.0943 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.3934 loss: 3.3934 2022/10/09 06:10:16 - mmengine - INFO - Epoch(train) [2][1000/2119] lr: 8.0000e-03 eta: 1 day, 8:46:40 time: 0.3619 data_time: 0.0260 memory: 11108 grad_norm: 4.0691 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.6646 loss: 3.6646 2022/10/09 06:10:24 - mmengine - INFO - Epoch(train) [2][1020/2119] lr: 8.0000e-03 eta: 1 day, 8:45:54 time: 0.3558 data_time: 0.0177 memory: 11108 grad_norm: 4.0704 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.3583 loss: 3.3583 2022/10/09 06:10:31 - mmengine - INFO - Epoch(train) [2][1040/2119] lr: 8.0000e-03 eta: 1 day, 8:45:03 time: 0.3526 data_time: 0.0208 memory: 11108 grad_norm: 4.0873 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.4269 loss: 3.4269 2022/10/09 06:10:38 - mmengine - INFO - Epoch(train) [2][1060/2119] lr: 8.0000e-03 eta: 1 day, 8:44:32 time: 0.3628 data_time: 0.0208 memory: 11108 grad_norm: 4.1081 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.5945 loss: 3.5945 2022/10/09 06:10:45 - mmengine - INFO - Epoch(train) [2][1080/2119] lr: 8.0000e-03 eta: 1 day, 8:43:48 time: 0.3561 data_time: 0.0186 memory: 11108 grad_norm: 4.1136 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.6195 loss: 3.6195 2022/10/09 06:10:52 - mmengine - INFO - Epoch(train) [2][1100/2119] lr: 8.0000e-03 eta: 1 day, 8:43:07 time: 0.3573 data_time: 0.0225 memory: 11108 grad_norm: 4.1275 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.5433 loss: 3.5433 2022/10/09 06:10:59 - mmengine - INFO - Epoch(train) [2][1120/2119] lr: 8.0000e-03 eta: 1 day, 8:42:27 time: 0.3578 data_time: 0.0224 memory: 11108 grad_norm: 4.1954 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.4769 loss: 3.4769 2022/10/09 06:11:06 - mmengine - INFO - Epoch(train) [2][1140/2119] lr: 8.0000e-03 eta: 1 day, 8:41:45 time: 0.3566 data_time: 0.0203 memory: 11108 grad_norm: 4.1022 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.5640 loss: 3.5640 2022/10/09 06:11:14 - mmengine - INFO - Epoch(train) [2][1160/2119] lr: 8.0000e-03 eta: 1 day, 8:41:05 time: 0.3572 data_time: 0.0191 memory: 11108 grad_norm: 4.1351 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.4739 loss: 3.4739 2022/10/09 06:11:21 - mmengine - INFO - Epoch(train) [2][1180/2119] lr: 8.0000e-03 eta: 1 day, 8:40:23 time: 0.3555 data_time: 0.0223 memory: 11108 grad_norm: 4.1563 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.7941 loss: 3.7941 2022/10/09 06:11:28 - mmengine - INFO - Epoch(train) [2][1200/2119] lr: 8.0000e-03 eta: 1 day, 8:39:40 time: 0.3556 data_time: 0.0213 memory: 11108 grad_norm: 4.1238 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.2937 loss: 3.2937 2022/10/09 06:11:35 - mmengine - INFO - Epoch(train) [2][1220/2119] lr: 8.0000e-03 eta: 1 day, 8:39:04 time: 0.3584 data_time: 0.0236 memory: 11108 grad_norm: 4.1834 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 3.3824 loss: 3.3824 2022/10/09 06:11:42 - mmengine - INFO - Epoch(train) [2][1240/2119] lr: 8.0000e-03 eta: 1 day, 8:38:21 time: 0.3549 data_time: 0.0241 memory: 11108 grad_norm: 4.0944 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.4346 loss: 3.4346 2022/10/09 06:11:49 - mmengine - INFO - Epoch(train) [2][1260/2119] lr: 8.0000e-03 eta: 1 day, 8:37:37 time: 0.3538 data_time: 0.0196 memory: 11108 grad_norm: 4.0989 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.3526 loss: 3.3526 2022/10/09 06:11:57 - mmengine - INFO - Epoch(train) [2][1280/2119] lr: 8.0000e-03 eta: 1 day, 8:37:21 time: 0.3692 data_time: 0.0212 memory: 11108 grad_norm: 4.1349 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0240 loss: 3.0240 2022/10/09 06:12:04 - mmengine - INFO - Epoch(train) [2][1300/2119] lr: 8.0000e-03 eta: 1 day, 8:36:50 time: 0.3607 data_time: 0.0179 memory: 11108 grad_norm: 4.1237 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.3998 loss: 3.3998 2022/10/09 06:12:11 - mmengine - INFO - Epoch(train) [2][1320/2119] lr: 8.0000e-03 eta: 1 day, 8:36:04 time: 0.3525 data_time: 0.0191 memory: 11108 grad_norm: 4.0807 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.5692 loss: 3.5692 2022/10/09 06:12:18 - mmengine - INFO - Epoch(train) [2][1340/2119] lr: 8.0000e-03 eta: 1 day, 8:35:34 time: 0.3605 data_time: 0.0205 memory: 11108 grad_norm: 4.1631 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.5415 loss: 3.5415 2022/10/09 06:12:25 - mmengine - INFO - Epoch(train) [2][1360/2119] lr: 8.0000e-03 eta: 1 day, 8:34:57 time: 0.3571 data_time: 0.0198 memory: 11108 grad_norm: 4.1353 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.2713 loss: 3.2713 2022/10/09 06:12:32 - mmengine - INFO - Epoch(train) [2][1380/2119] lr: 8.0000e-03 eta: 1 day, 8:34:13 time: 0.3530 data_time: 0.0219 memory: 11108 grad_norm: 4.1753 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.3734 loss: 3.3734 2022/10/09 06:12:39 - mmengine - INFO - Epoch(train) [2][1400/2119] lr: 8.0000e-03 eta: 1 day, 8:33:47 time: 0.3625 data_time: 0.0203 memory: 11108 grad_norm: 4.1122 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.3703 loss: 3.3703 2022/10/09 06:12:47 - mmengine - INFO - Epoch(train) [2][1420/2119] lr: 8.0000e-03 eta: 1 day, 8:33:15 time: 0.3588 data_time: 0.0186 memory: 11108 grad_norm: 4.1265 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.2646 loss: 3.2646 2022/10/09 06:12:54 - mmengine - INFO - Epoch(train) [2][1440/2119] lr: 8.0000e-03 eta: 1 day, 8:32:45 time: 0.3605 data_time: 0.0187 memory: 11108 grad_norm: 4.1310 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 3.6464 loss: 3.6464 2022/10/09 06:13:01 - mmengine - INFO - Epoch(train) [2][1460/2119] lr: 8.0000e-03 eta: 1 day, 8:32:03 time: 0.3530 data_time: 0.0232 memory: 11108 grad_norm: 4.1678 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.3826 loss: 3.3826 2022/10/09 06:13:08 - mmengine - INFO - Epoch(train) [2][1480/2119] lr: 8.0000e-03 eta: 1 day, 8:31:30 time: 0.3578 data_time: 0.0215 memory: 11108 grad_norm: 4.1443 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 3.3634 loss: 3.3634 2022/10/09 06:13:15 - mmengine - INFO - Epoch(train) [2][1500/2119] lr: 8.0000e-03 eta: 1 day, 8:30:59 time: 0.3595 data_time: 0.0231 memory: 11108 grad_norm: 4.1236 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.2799 loss: 3.2799 2022/10/09 06:13:22 - mmengine - INFO - Epoch(train) [2][1520/2119] lr: 8.0000e-03 eta: 1 day, 8:30:24 time: 0.3561 data_time: 0.0218 memory: 11108 grad_norm: 4.1022 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.2018 loss: 3.2018 2022/10/09 06:13:29 - mmengine - INFO - Epoch(train) [2][1540/2119] lr: 8.0000e-03 eta: 1 day, 8:29:46 time: 0.3546 data_time: 0.0166 memory: 11108 grad_norm: 4.1132 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.3243 loss: 3.3243 2022/10/09 06:13:37 - mmengine - INFO - Epoch(train) [2][1560/2119] lr: 8.0000e-03 eta: 1 day, 8:29:16 time: 0.3594 data_time: 0.0251 memory: 11108 grad_norm: 4.1270 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 3.6209 loss: 3.6209 2022/10/09 06:13:44 - mmengine - INFO - Epoch(train) [2][1580/2119] lr: 8.0000e-03 eta: 1 day, 8:28:45 time: 0.3583 data_time: 0.0182 memory: 11108 grad_norm: 4.1698 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.3096 loss: 3.3096 2022/10/09 06:13:51 - mmengine - INFO - Epoch(train) [2][1600/2119] lr: 8.0000e-03 eta: 1 day, 8:28:13 time: 0.3579 data_time: 0.0205 memory: 11108 grad_norm: 4.1516 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.6468 loss: 3.6468 2022/10/09 06:13:58 - mmengine - INFO - Epoch(train) [2][1620/2119] lr: 8.0000e-03 eta: 1 day, 8:27:49 time: 0.3625 data_time: 0.0209 memory: 11108 grad_norm: 4.1647 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.3955 loss: 3.3955 2022/10/09 06:14:05 - mmengine - INFO - Epoch(train) [2][1640/2119] lr: 8.0000e-03 eta: 1 day, 8:27:14 time: 0.3552 data_time: 0.0234 memory: 11108 grad_norm: 4.1450 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.4851 loss: 3.4851 2022/10/09 06:14:12 - mmengine - INFO - Epoch(train) [2][1660/2119] lr: 8.0000e-03 eta: 1 day, 8:26:33 time: 0.3522 data_time: 0.0164 memory: 11108 grad_norm: 4.1414 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.4066 loss: 3.4066 2022/10/09 06:14:20 - mmengine - INFO - Epoch(train) [2][1680/2119] lr: 8.0000e-03 eta: 1 day, 8:26:03 time: 0.3581 data_time: 0.0188 memory: 11108 grad_norm: 4.1667 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.2174 loss: 3.2174 2022/10/09 06:14:27 - mmengine - INFO - Epoch(train) [2][1700/2119] lr: 8.0000e-03 eta: 1 day, 8:25:36 time: 0.3599 data_time: 0.0187 memory: 11108 grad_norm: 4.1393 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2494 loss: 3.2494 2022/10/09 06:14:34 - mmengine - INFO - Epoch(train) [2][1720/2119] lr: 8.0000e-03 eta: 1 day, 8:25:10 time: 0.3601 data_time: 0.0217 memory: 11108 grad_norm: 4.1515 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.2335 loss: 3.2335 2022/10/09 06:14:41 - mmengine - INFO - Epoch(train) [2][1740/2119] lr: 8.0000e-03 eta: 1 day, 8:24:37 time: 0.3559 data_time: 0.0167 memory: 11108 grad_norm: 4.1836 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.4441 loss: 3.4441 2022/10/09 06:14:48 - mmengine - INFO - Epoch(train) [2][1760/2119] lr: 8.0000e-03 eta: 1 day, 8:24:08 time: 0.3587 data_time: 0.0202 memory: 11108 grad_norm: 4.1419 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 3.3907 loss: 3.3907 2022/10/09 06:14:55 - mmengine - INFO - Epoch(train) [2][1780/2119] lr: 8.0000e-03 eta: 1 day, 8:23:40 time: 0.3588 data_time: 0.0180 memory: 11108 grad_norm: 4.1922 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.2121 loss: 3.2121 2022/10/09 06:15:03 - mmengine - INFO - Epoch(train) [2][1800/2119] lr: 8.0000e-03 eta: 1 day, 8:23:12 time: 0.3586 data_time: 0.0195 memory: 11108 grad_norm: 4.1644 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 3.4089 loss: 3.4089 2022/10/09 06:15:10 - mmengine - INFO - Epoch(train) [2][1820/2119] lr: 8.0000e-03 eta: 1 day, 8:22:44 time: 0.3583 data_time: 0.0200 memory: 11108 grad_norm: 4.1232 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.4013 loss: 3.4013 2022/10/09 06:15:17 - mmengine - INFO - Epoch(train) [2][1840/2119] lr: 8.0000e-03 eta: 1 day, 8:22:09 time: 0.3538 data_time: 0.0245 memory: 11108 grad_norm: 4.1521 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.4926 loss: 3.4926 2022/10/09 06:15:24 - mmengine - INFO - Epoch(train) [2][1860/2119] lr: 8.0000e-03 eta: 1 day, 8:21:51 time: 0.3646 data_time: 0.0177 memory: 11108 grad_norm: 4.1475 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.2109 loss: 3.2109 2022/10/09 06:15:31 - mmengine - INFO - Epoch(train) [2][1880/2119] lr: 8.0000e-03 eta: 1 day, 8:21:19 time: 0.3558 data_time: 0.0248 memory: 11108 grad_norm: 4.1358 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.1374 loss: 3.1374 2022/10/09 06:15:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 06:15:38 - mmengine - INFO - Epoch(train) [2][1900/2119] lr: 8.0000e-03 eta: 1 day, 8:20:54 time: 0.3594 data_time: 0.0173 memory: 11108 grad_norm: 4.2041 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.2162 loss: 3.2162 2022/10/09 06:15:46 - mmengine - INFO - Epoch(train) [2][1920/2119] lr: 8.0000e-03 eta: 1 day, 8:20:25 time: 0.3573 data_time: 0.0269 memory: 11108 grad_norm: 4.1271 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.2505 loss: 3.2505 2022/10/09 06:15:53 - mmengine - INFO - Epoch(train) [2][1940/2119] lr: 8.0000e-03 eta: 1 day, 8:19:54 time: 0.3557 data_time: 0.0207 memory: 11108 grad_norm: 4.1482 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.3676 loss: 3.3676 2022/10/09 06:16:00 - mmengine - INFO - Epoch(train) [2][1960/2119] lr: 8.0000e-03 eta: 1 day, 8:19:22 time: 0.3553 data_time: 0.0179 memory: 11108 grad_norm: 4.1515 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.2665 loss: 3.2665 2022/10/09 06:16:07 - mmengine - INFO - Epoch(train) [2][1980/2119] lr: 8.0000e-03 eta: 1 day, 8:18:52 time: 0.3556 data_time: 0.0214 memory: 11108 grad_norm: 4.1557 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.1811 loss: 3.1811 2022/10/09 06:16:14 - mmengine - INFO - Epoch(train) [2][2000/2119] lr: 8.0000e-03 eta: 1 day, 8:18:21 time: 0.3559 data_time: 0.0185 memory: 11108 grad_norm: 4.1786 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1846 loss: 3.1846 2022/10/09 06:16:21 - mmengine - INFO - Epoch(train) [2][2020/2119] lr: 8.0000e-03 eta: 1 day, 8:17:46 time: 0.3524 data_time: 0.0243 memory: 11108 grad_norm: 4.1664 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 3.3386 loss: 3.3386 2022/10/09 06:16:28 - mmengine - INFO - Epoch(train) [2][2040/2119] lr: 8.0000e-03 eta: 1 day, 8:17:27 time: 0.3628 data_time: 0.0196 memory: 11108 grad_norm: 4.1630 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.3007 loss: 3.3007 2022/10/09 06:16:35 - mmengine - INFO - Epoch(train) [2][2060/2119] lr: 8.0000e-03 eta: 1 day, 8:16:57 time: 0.3553 data_time: 0.0187 memory: 11108 grad_norm: 4.1376 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.2847 loss: 3.2847 2022/10/09 06:16:43 - mmengine - INFO - Epoch(train) [2][2080/2119] lr: 8.0000e-03 eta: 1 day, 8:16:26 time: 0.3549 data_time: 0.0198 memory: 11108 grad_norm: 4.2052 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 3.2451 loss: 3.2451 2022/10/09 06:16:50 - mmengine - INFO - Epoch(train) [2][2100/2119] lr: 8.0000e-03 eta: 1 day, 8:15:57 time: 0.3562 data_time: 0.0215 memory: 11108 grad_norm: 4.1590 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 3.3230 loss: 3.3230 2022/10/09 06:16:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 06:16:56 - mmengine - INFO - Epoch(train) [2][2119/2119] lr: 8.0000e-03 eta: 1 day, 8:15:57 time: 0.3442 data_time: 0.0191 memory: 11108 grad_norm: 4.2591 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.3327 loss: 3.3327 2022/10/09 06:17:07 - mmengine - INFO - Epoch(train) [3][20/2119] lr: 1.2000e-02 eta: 1 day, 8:10:56 time: 0.5277 data_time: 0.1373 memory: 11108 grad_norm: 4.1883 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.1579 loss: 3.1579 2022/10/09 06:17:14 - mmengine - INFO - Epoch(train) [3][40/2119] lr: 1.2000e-02 eta: 1 day, 8:10:56 time: 0.3740 data_time: 0.0261 memory: 11108 grad_norm: 4.1869 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.1508 loss: 3.1508 2022/10/09 06:17:21 - mmengine - INFO - Epoch(train) [3][60/2119] lr: 1.2000e-02 eta: 1 day, 8:10:26 time: 0.3543 data_time: 0.0212 memory: 11108 grad_norm: 4.1194 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.6289 loss: 3.6289 2022/10/09 06:17:29 - mmengine - INFO - Epoch(train) [3][80/2119] lr: 1.2000e-02 eta: 1 day, 8:10:07 time: 0.3611 data_time: 0.0234 memory: 11108 grad_norm: 4.1864 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.0832 loss: 3.0832 2022/10/09 06:17:36 - mmengine - INFO - Epoch(train) [3][100/2119] lr: 1.2000e-02 eta: 1 day, 8:09:40 time: 0.3563 data_time: 0.0199 memory: 11108 grad_norm: 4.1543 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.3739 loss: 3.3739 2022/10/09 06:17:43 - mmengine - INFO - Epoch(train) [3][120/2119] lr: 1.2000e-02 eta: 1 day, 8:09:16 time: 0.3574 data_time: 0.0204 memory: 11108 grad_norm: 4.1271 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.1841 loss: 3.1841 2022/10/09 06:17:50 - mmengine - INFO - Epoch(train) [3][140/2119] lr: 1.2000e-02 eta: 1 day, 8:08:53 time: 0.3587 data_time: 0.0223 memory: 11108 grad_norm: 4.1161 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 3.2317 loss: 3.2317 2022/10/09 06:17:57 - mmengine - INFO - Epoch(train) [3][160/2119] lr: 1.2000e-02 eta: 1 day, 8:08:35 time: 0.3611 data_time: 0.0230 memory: 11108 grad_norm: 4.1090 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.3132 loss: 3.3132 2022/10/09 06:18:04 - mmengine - INFO - Epoch(train) [3][180/2119] lr: 1.2000e-02 eta: 1 day, 8:08:08 time: 0.3556 data_time: 0.0229 memory: 11108 grad_norm: 4.1258 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.2827 loss: 3.2827 2022/10/09 06:18:12 - mmengine - INFO - Epoch(train) [3][200/2119] lr: 1.2000e-02 eta: 1 day, 8:07:48 time: 0.3598 data_time: 0.0224 memory: 11108 grad_norm: 4.1081 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.2649 loss: 3.2649 2022/10/09 06:18:19 - mmengine - INFO - Epoch(train) [3][220/2119] lr: 1.2000e-02 eta: 1 day, 8:07:21 time: 0.3557 data_time: 0.0230 memory: 11108 grad_norm: 4.0825 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.1808 loss: 3.1808 2022/10/09 06:18:26 - mmengine - INFO - Epoch(train) [3][240/2119] lr: 1.2000e-02 eta: 1 day, 8:07:00 time: 0.3594 data_time: 0.0233 memory: 11108 grad_norm: 4.1666 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.3686 loss: 3.3686 2022/10/09 06:18:33 - mmengine - INFO - Epoch(train) [3][260/2119] lr: 1.2000e-02 eta: 1 day, 8:06:37 time: 0.3572 data_time: 0.0204 memory: 11108 grad_norm: 4.0614 top1_acc: 0.2500 top5_acc: 0.8125 loss_cls: 3.3005 loss: 3.3005 2022/10/09 06:18:40 - mmengine - INFO - Epoch(train) [3][280/2119] lr: 1.2000e-02 eta: 1 day, 8:06:23 time: 0.3641 data_time: 0.0225 memory: 11108 grad_norm: 4.0920 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.2417 loss: 3.2417 2022/10/09 06:18:47 - mmengine - INFO - Epoch(train) [3][300/2119] lr: 1.2000e-02 eta: 1 day, 8:05:55 time: 0.3542 data_time: 0.0200 memory: 11108 grad_norm: 4.1343 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.2497 loss: 3.2497 2022/10/09 06:18:55 - mmengine - INFO - Epoch(train) [3][320/2119] lr: 1.2000e-02 eta: 1 day, 8:05:34 time: 0.3589 data_time: 0.0215 memory: 11108 grad_norm: 4.0734 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.4513 loss: 3.4513 2022/10/09 06:19:02 - mmengine - INFO - Epoch(train) [3][340/2119] lr: 1.2000e-02 eta: 1 day, 8:05:11 time: 0.3575 data_time: 0.0192 memory: 11108 grad_norm: 4.0977 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.4703 loss: 3.4703 2022/10/09 06:19:09 - mmengine - INFO - Epoch(train) [3][360/2119] lr: 1.2000e-02 eta: 1 day, 8:04:51 time: 0.3596 data_time: 0.0230 memory: 11108 grad_norm: 4.0735 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.3901 loss: 3.3901 2022/10/09 06:19:16 - mmengine - INFO - Epoch(train) [3][380/2119] lr: 1.2000e-02 eta: 1 day, 8:04:31 time: 0.3593 data_time: 0.0238 memory: 11108 grad_norm: 4.1007 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.2318 loss: 3.2318 2022/10/09 06:19:23 - mmengine - INFO - Epoch(train) [3][400/2119] lr: 1.2000e-02 eta: 1 day, 8:04:02 time: 0.3525 data_time: 0.0197 memory: 11108 grad_norm: 4.0883 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0765 loss: 3.0765 2022/10/09 06:19:30 - mmengine - INFO - Epoch(train) [3][420/2119] lr: 1.2000e-02 eta: 1 day, 8:03:43 time: 0.3598 data_time: 0.0183 memory: 11108 grad_norm: 4.0635 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.9063 loss: 2.9063 2022/10/09 06:19:37 - mmengine - INFO - Epoch(train) [3][440/2119] lr: 1.2000e-02 eta: 1 day, 8:03:23 time: 0.3588 data_time: 0.0241 memory: 11108 grad_norm: 4.0755 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.3951 loss: 3.3951 2022/10/09 06:19:45 - mmengine - INFO - Epoch(train) [3][460/2119] lr: 1.2000e-02 eta: 1 day, 8:02:56 time: 0.3541 data_time: 0.0216 memory: 11108 grad_norm: 4.0540 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9577 loss: 2.9577 2022/10/09 06:19:52 - mmengine - INFO - Epoch(train) [3][480/2119] lr: 1.2000e-02 eta: 1 day, 8:02:37 time: 0.3597 data_time: 0.0250 memory: 11108 grad_norm: 4.0293 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.3307 loss: 3.3307 2022/10/09 06:19:59 - mmengine - INFO - Epoch(train) [3][500/2119] lr: 1.2000e-02 eta: 1 day, 8:02:14 time: 0.3567 data_time: 0.0174 memory: 11108 grad_norm: 3.9869 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 3.0707 loss: 3.0707 2022/10/09 06:20:06 - mmengine - INFO - Epoch(train) [3][520/2119] lr: 1.2000e-02 eta: 1 day, 8:01:53 time: 0.3576 data_time: 0.0206 memory: 11108 grad_norm: 4.1218 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.5131 loss: 3.5131 2022/10/09 06:20:13 - mmengine - INFO - Epoch(train) [3][540/2119] lr: 1.2000e-02 eta: 1 day, 8:01:27 time: 0.3545 data_time: 0.0190 memory: 11108 grad_norm: 4.0110 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.2502 loss: 3.2502 2022/10/09 06:20:20 - mmengine - INFO - Epoch(train) [3][560/2119] lr: 1.2000e-02 eta: 1 day, 8:01:13 time: 0.3629 data_time: 0.0187 memory: 11108 grad_norm: 4.0535 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.2397 loss: 3.2397 2022/10/09 06:20:28 - mmengine - INFO - Epoch(train) [3][580/2119] lr: 1.2000e-02 eta: 1 day, 8:00:54 time: 0.3591 data_time: 0.0202 memory: 11108 grad_norm: 4.0268 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.2282 loss: 3.2282 2022/10/09 06:20:35 - mmengine - INFO - Epoch(train) [3][600/2119] lr: 1.2000e-02 eta: 1 day, 8:00:38 time: 0.3619 data_time: 0.0245 memory: 11108 grad_norm: 4.0621 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.3434 loss: 3.3434 2022/10/09 06:20:42 - mmengine - INFO - Epoch(train) [3][620/2119] lr: 1.2000e-02 eta: 1 day, 8:00:11 time: 0.3524 data_time: 0.0191 memory: 11108 grad_norm: 4.0128 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2442 loss: 3.2442 2022/10/09 06:20:49 - mmengine - INFO - Epoch(train) [3][640/2119] lr: 1.2000e-02 eta: 1 day, 7:59:52 time: 0.3594 data_time: 0.0225 memory: 11108 grad_norm: 4.0606 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.1489 loss: 3.1489 2022/10/09 06:20:56 - mmengine - INFO - Epoch(train) [3][660/2119] lr: 1.2000e-02 eta: 1 day, 7:59:34 time: 0.3596 data_time: 0.0237 memory: 11108 grad_norm: 4.0445 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.2711 loss: 3.2711 2022/10/09 06:21:03 - mmengine - INFO - Epoch(train) [3][680/2119] lr: 1.2000e-02 eta: 1 day, 7:59:12 time: 0.3563 data_time: 0.0201 memory: 11108 grad_norm: 4.0847 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0148 loss: 3.0148 2022/10/09 06:21:10 - mmengine - INFO - Epoch(train) [3][700/2119] lr: 1.2000e-02 eta: 1 day, 7:58:49 time: 0.3564 data_time: 0.0190 memory: 11108 grad_norm: 4.0824 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.2097 loss: 3.2097 2022/10/09 06:21:18 - mmengine - INFO - Epoch(train) [3][720/2119] lr: 1.2000e-02 eta: 1 day, 7:58:29 time: 0.3576 data_time: 0.0209 memory: 11108 grad_norm: 4.1040 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.1439 loss: 3.1439 2022/10/09 06:21:25 - mmengine - INFO - Epoch(train) [3][740/2119] lr: 1.2000e-02 eta: 1 day, 7:58:12 time: 0.3599 data_time: 0.0189 memory: 11108 grad_norm: 4.0335 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0998 loss: 3.0998 2022/10/09 06:21:32 - mmengine - INFO - Epoch(train) [3][760/2119] lr: 1.2000e-02 eta: 1 day, 7:57:50 time: 0.3567 data_time: 0.0221 memory: 11108 grad_norm: 4.0424 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.1518 loss: 3.1518 2022/10/09 06:21:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 06:21:39 - mmengine - INFO - Epoch(train) [3][780/2119] lr: 1.2000e-02 eta: 1 day, 7:57:32 time: 0.3592 data_time: 0.0178 memory: 11108 grad_norm: 4.0834 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 3.2512 loss: 3.2512 2022/10/09 06:21:46 - mmengine - INFO - Epoch(train) [3][800/2119] lr: 1.2000e-02 eta: 1 day, 7:57:17 time: 0.3616 data_time: 0.0197 memory: 11108 grad_norm: 4.0582 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1876 loss: 3.1876 2022/10/09 06:21:54 - mmengine - INFO - Epoch(train) [3][820/2119] lr: 1.2000e-02 eta: 1 day, 7:56:55 time: 0.3555 data_time: 0.0214 memory: 11108 grad_norm: 4.0407 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.1408 loss: 3.1408 2022/10/09 06:22:01 - mmengine - INFO - Epoch(train) [3][840/2119] lr: 1.2000e-02 eta: 1 day, 7:56:34 time: 0.3570 data_time: 0.0195 memory: 11108 grad_norm: 4.1042 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.3703 loss: 3.3703 2022/10/09 06:22:08 - mmengine - INFO - Epoch(train) [3][860/2119] lr: 1.2000e-02 eta: 1 day, 7:56:22 time: 0.3639 data_time: 0.0192 memory: 11108 grad_norm: 4.0486 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0284 loss: 3.0284 2022/10/09 06:22:15 - mmengine - INFO - Epoch(train) [3][880/2119] lr: 1.2000e-02 eta: 1 day, 7:56:00 time: 0.3556 data_time: 0.0205 memory: 11108 grad_norm: 4.1541 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2020 loss: 3.2020 2022/10/09 06:22:22 - mmengine - INFO - Epoch(train) [3][900/2119] lr: 1.2000e-02 eta: 1 day, 7:55:38 time: 0.3553 data_time: 0.0233 memory: 11108 grad_norm: 4.0720 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 3.3183 loss: 3.3183 2022/10/09 06:22:29 - mmengine - INFO - Epoch(train) [3][920/2119] lr: 1.2000e-02 eta: 1 day, 7:55:18 time: 0.3577 data_time: 0.0202 memory: 11108 grad_norm: 4.0389 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.2647 loss: 3.2647 2022/10/09 06:22:36 - mmengine - INFO - Epoch(train) [3][940/2119] lr: 1.2000e-02 eta: 1 day, 7:54:58 time: 0.3568 data_time: 0.0225 memory: 11108 grad_norm: 3.9679 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.1296 loss: 3.1296 2022/10/09 06:22:44 - mmengine - INFO - Epoch(train) [3][960/2119] lr: 1.2000e-02 eta: 1 day, 7:54:37 time: 0.3560 data_time: 0.0185 memory: 11108 grad_norm: 4.0151 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 3.2193 loss: 3.2193 2022/10/09 06:22:51 - mmengine - INFO - Epoch(train) [3][980/2119] lr: 1.2000e-02 eta: 1 day, 7:54:17 time: 0.3570 data_time: 0.0224 memory: 11108 grad_norm: 4.0614 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1055 loss: 3.1055 2022/10/09 06:22:58 - mmengine - INFO - Epoch(train) [3][1000/2119] lr: 1.2000e-02 eta: 1 day, 7:54:09 time: 0.3669 data_time: 0.0209 memory: 11108 grad_norm: 4.1147 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.1287 loss: 3.1287 2022/10/09 06:23:05 - mmengine - INFO - Epoch(train) [3][1020/2119] lr: 1.2000e-02 eta: 1 day, 7:53:45 time: 0.3530 data_time: 0.0202 memory: 11108 grad_norm: 4.0836 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2506 loss: 3.2506 2022/10/09 06:23:12 - mmengine - INFO - Epoch(train) [3][1040/2119] lr: 1.2000e-02 eta: 1 day, 7:53:27 time: 0.3587 data_time: 0.0181 memory: 11108 grad_norm: 3.9788 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.2812 loss: 3.2812 2022/10/09 06:23:19 - mmengine - INFO - Epoch(train) [3][1060/2119] lr: 1.2000e-02 eta: 1 day, 7:53:10 time: 0.3588 data_time: 0.0188 memory: 11108 grad_norm: 4.0557 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.1070 loss: 3.1070 2022/10/09 06:23:27 - mmengine - INFO - Epoch(train) [3][1080/2119] lr: 1.2000e-02 eta: 1 day, 7:52:50 time: 0.3571 data_time: 0.0205 memory: 11108 grad_norm: 4.0485 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.3024 loss: 3.3024 2022/10/09 06:23:34 - mmengine - INFO - Epoch(train) [3][1100/2119] lr: 1.2000e-02 eta: 1 day, 7:52:31 time: 0.3567 data_time: 0.0214 memory: 11108 grad_norm: 4.0080 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9028 loss: 2.9028 2022/10/09 06:23:41 - mmengine - INFO - Epoch(train) [3][1120/2119] lr: 1.2000e-02 eta: 1 day, 7:52:08 time: 0.3541 data_time: 0.0204 memory: 11108 grad_norm: 4.0119 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.1526 loss: 3.1526 2022/10/09 06:23:48 - mmengine - INFO - Epoch(train) [3][1140/2119] lr: 1.2000e-02 eta: 1 day, 7:51:52 time: 0.3593 data_time: 0.0197 memory: 11108 grad_norm: 4.0160 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.2562 loss: 3.2562 2022/10/09 06:23:55 - mmengine - INFO - Epoch(train) [3][1160/2119] lr: 1.2000e-02 eta: 1 day, 7:51:49 time: 0.3712 data_time: 0.0216 memory: 11108 grad_norm: 4.0438 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1378 loss: 3.1378 2022/10/09 06:24:03 - mmengine - INFO - Epoch(train) [3][1180/2119] lr: 1.2000e-02 eta: 1 day, 7:51:30 time: 0.3567 data_time: 0.0200 memory: 11108 grad_norm: 3.9803 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2610 loss: 3.2610 2022/10/09 06:24:10 - mmengine - INFO - Epoch(train) [3][1200/2119] lr: 1.2000e-02 eta: 1 day, 7:51:10 time: 0.3565 data_time: 0.0212 memory: 11108 grad_norm: 4.0914 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1552 loss: 3.1552 2022/10/09 06:24:17 - mmengine - INFO - Epoch(train) [3][1220/2119] lr: 1.2000e-02 eta: 1 day, 7:50:54 time: 0.3591 data_time: 0.0217 memory: 11108 grad_norm: 4.0509 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.3877 loss: 3.3877 2022/10/09 06:24:24 - mmengine - INFO - Epoch(train) [3][1240/2119] lr: 1.2000e-02 eta: 1 day, 7:50:34 time: 0.3562 data_time: 0.0226 memory: 11108 grad_norm: 4.0088 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 3.0376 loss: 3.0376 2022/10/09 06:24:31 - mmengine - INFO - Epoch(train) [3][1260/2119] lr: 1.2000e-02 eta: 1 day, 7:50:14 time: 0.3557 data_time: 0.0226 memory: 11108 grad_norm: 4.0086 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 3.2889 loss: 3.2889 2022/10/09 06:24:38 - mmengine - INFO - Epoch(train) [3][1280/2119] lr: 1.2000e-02 eta: 1 day, 7:49:55 time: 0.3570 data_time: 0.0231 memory: 11108 grad_norm: 3.9983 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1565 loss: 3.1565 2022/10/09 06:24:45 - mmengine - INFO - Epoch(train) [3][1300/2119] lr: 1.2000e-02 eta: 1 day, 7:49:34 time: 0.3546 data_time: 0.0176 memory: 11108 grad_norm: 4.0429 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.1919 loss: 3.1919 2022/10/09 06:24:52 - mmengine - INFO - Epoch(train) [3][1320/2119] lr: 1.2000e-02 eta: 1 day, 7:49:15 time: 0.3564 data_time: 0.0185 memory: 11108 grad_norm: 3.9899 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.3111 loss: 3.3111 2022/10/09 06:25:00 - mmengine - INFO - Epoch(train) [3][1340/2119] lr: 1.2000e-02 eta: 1 day, 7:48:58 time: 0.3587 data_time: 0.0198 memory: 11108 grad_norm: 4.0425 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9718 loss: 2.9718 2022/10/09 06:25:07 - mmengine - INFO - Epoch(train) [3][1360/2119] lr: 1.2000e-02 eta: 1 day, 7:48:41 time: 0.3575 data_time: 0.0240 memory: 11108 grad_norm: 3.9796 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8487 loss: 2.8487 2022/10/09 06:25:14 - mmengine - INFO - Epoch(train) [3][1380/2119] lr: 1.2000e-02 eta: 1 day, 7:48:20 time: 0.3548 data_time: 0.0196 memory: 11108 grad_norm: 4.0582 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.2125 loss: 3.2125 2022/10/09 06:25:21 - mmengine - INFO - Epoch(train) [3][1400/2119] lr: 1.2000e-02 eta: 1 day, 7:48:05 time: 0.3596 data_time: 0.0198 memory: 11108 grad_norm: 4.0282 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 3.0840 loss: 3.0840 2022/10/09 06:25:28 - mmengine - INFO - Epoch(train) [3][1420/2119] lr: 1.2000e-02 eta: 1 day, 7:47:44 time: 0.3541 data_time: 0.0197 memory: 11108 grad_norm: 4.0573 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1837 loss: 3.1837 2022/10/09 06:25:35 - mmengine - INFO - Epoch(train) [3][1440/2119] lr: 1.2000e-02 eta: 1 day, 7:47:27 time: 0.3579 data_time: 0.0242 memory: 11108 grad_norm: 3.9869 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9823 loss: 2.9823 2022/10/09 06:25:42 - mmengine - INFO - Epoch(train) [3][1460/2119] lr: 1.2000e-02 eta: 1 day, 7:47:08 time: 0.3561 data_time: 0.0229 memory: 11108 grad_norm: 3.9606 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.3146 loss: 3.3146 2022/10/09 06:25:50 - mmengine - INFO - Epoch(train) [3][1480/2119] lr: 1.2000e-02 eta: 1 day, 7:46:54 time: 0.3609 data_time: 0.0186 memory: 11108 grad_norm: 4.0362 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 3.1528 loss: 3.1528 2022/10/09 06:25:57 - mmengine - INFO - Epoch(train) [3][1500/2119] lr: 1.2000e-02 eta: 1 day, 7:46:37 time: 0.3578 data_time: 0.0232 memory: 11108 grad_norm: 3.9976 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 3.0234 loss: 3.0234 2022/10/09 06:26:04 - mmengine - INFO - Epoch(train) [3][1520/2119] lr: 1.2000e-02 eta: 1 day, 7:46:21 time: 0.3577 data_time: 0.0239 memory: 11108 grad_norm: 4.0303 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9584 loss: 2.9584 2022/10/09 06:26:11 - mmengine - INFO - Epoch(train) [3][1540/2119] lr: 1.2000e-02 eta: 1 day, 7:46:01 time: 0.3556 data_time: 0.0191 memory: 11108 grad_norm: 4.0448 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.0920 loss: 3.0920 2022/10/09 06:26:18 - mmengine - INFO - Epoch(train) [3][1560/2119] lr: 1.2000e-02 eta: 1 day, 7:45:49 time: 0.3617 data_time: 0.0223 memory: 11108 grad_norm: 4.0300 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.1318 loss: 3.1318 2022/10/09 06:26:26 - mmengine - INFO - Epoch(train) [3][1580/2119] lr: 1.2000e-02 eta: 1 day, 7:45:35 time: 0.3603 data_time: 0.0187 memory: 11108 grad_norm: 4.0602 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.9743 loss: 2.9743 2022/10/09 06:26:33 - mmengine - INFO - Epoch(train) [3][1600/2119] lr: 1.2000e-02 eta: 1 day, 7:45:14 time: 0.3532 data_time: 0.0201 memory: 11108 grad_norm: 4.0726 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8595 loss: 2.8595 2022/10/09 06:26:40 - mmengine - INFO - Epoch(train) [3][1620/2119] lr: 1.2000e-02 eta: 1 day, 7:45:00 time: 0.3607 data_time: 0.0191 memory: 11108 grad_norm: 3.9758 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9729 loss: 2.9729 2022/10/09 06:26:47 - mmengine - INFO - Epoch(train) [3][1640/2119] lr: 1.2000e-02 eta: 1 day, 7:44:46 time: 0.3599 data_time: 0.0214 memory: 11108 grad_norm: 4.0076 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0618 loss: 3.0618 2022/10/09 06:26:54 - mmengine - INFO - Epoch(train) [3][1660/2119] lr: 1.2000e-02 eta: 1 day, 7:44:27 time: 0.3557 data_time: 0.0235 memory: 11108 grad_norm: 4.0686 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.1430 loss: 3.1430 2022/10/09 06:27:01 - mmengine - INFO - Epoch(train) [3][1680/2119] lr: 1.2000e-02 eta: 1 day, 7:44:10 time: 0.3568 data_time: 0.0204 memory: 11108 grad_norm: 4.0124 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.1754 loss: 3.1754 2022/10/09 06:27:08 - mmengine - INFO - Epoch(train) [3][1700/2119] lr: 1.2000e-02 eta: 1 day, 7:43:52 time: 0.3557 data_time: 0.0240 memory: 11108 grad_norm: 4.0210 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 3.3386 loss: 3.3386 2022/10/09 06:27:16 - mmengine - INFO - Epoch(train) [3][1720/2119] lr: 1.2000e-02 eta: 1 day, 7:43:36 time: 0.3579 data_time: 0.0224 memory: 11108 grad_norm: 4.0024 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.1557 loss: 3.1557 2022/10/09 06:27:23 - mmengine - INFO - Epoch(train) [3][1740/2119] lr: 1.2000e-02 eta: 1 day, 7:43:16 time: 0.3541 data_time: 0.0211 memory: 11108 grad_norm: 4.0327 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.1901 loss: 3.1901 2022/10/09 06:27:30 - mmengine - INFO - Epoch(train) [3][1760/2119] lr: 1.2000e-02 eta: 1 day, 7:43:01 time: 0.3596 data_time: 0.0221 memory: 11108 grad_norm: 4.0372 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 3.1631 loss: 3.1631 2022/10/09 06:27:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 06:27:37 - mmengine - INFO - Epoch(train) [3][1780/2119] lr: 1.2000e-02 eta: 1 day, 7:42:49 time: 0.3614 data_time: 0.0188 memory: 11108 grad_norm: 4.0487 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1341 loss: 3.1341 2022/10/09 06:27:44 - mmengine - INFO - Epoch(train) [3][1800/2119] lr: 1.2000e-02 eta: 1 day, 7:42:35 time: 0.3594 data_time: 0.0238 memory: 11108 grad_norm: 4.0869 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 3.0764 loss: 3.0764 2022/10/09 06:27:51 - mmengine - INFO - Epoch(train) [3][1820/2119] lr: 1.2000e-02 eta: 1 day, 7:42:15 time: 0.3538 data_time: 0.0194 memory: 11108 grad_norm: 4.0555 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0387 loss: 3.0387 2022/10/09 06:27:58 - mmengine - INFO - Epoch(train) [3][1840/2119] lr: 1.2000e-02 eta: 1 day, 7:42:00 time: 0.3586 data_time: 0.0201 memory: 11108 grad_norm: 4.0395 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.2351 loss: 3.2351 2022/10/09 06:28:06 - mmengine - INFO - Epoch(train) [3][1860/2119] lr: 1.2000e-02 eta: 1 day, 7:41:44 time: 0.3570 data_time: 0.0202 memory: 11108 grad_norm: 3.9761 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.3438 loss: 3.3438 2022/10/09 06:28:13 - mmengine - INFO - Epoch(train) [3][1880/2119] lr: 1.2000e-02 eta: 1 day, 7:41:23 time: 0.3534 data_time: 0.0207 memory: 11108 grad_norm: 4.0483 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.0879 loss: 3.0879 2022/10/09 06:28:20 - mmengine - INFO - Epoch(train) [3][1900/2119] lr: 1.2000e-02 eta: 1 day, 7:41:08 time: 0.3580 data_time: 0.0221 memory: 11108 grad_norm: 4.0598 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.4139 loss: 3.4139 2022/10/09 06:28:27 - mmengine - INFO - Epoch(train) [3][1920/2119] lr: 1.2000e-02 eta: 1 day, 7:40:53 time: 0.3581 data_time: 0.0216 memory: 11108 grad_norm: 4.0134 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1711 loss: 3.1711 2022/10/09 06:28:34 - mmengine - INFO - Epoch(train) [3][1940/2119] lr: 1.2000e-02 eta: 1 day, 7:40:32 time: 0.3527 data_time: 0.0230 memory: 11108 grad_norm: 3.9538 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.0780 loss: 3.0780 2022/10/09 06:28:41 - mmengine - INFO - Epoch(train) [3][1960/2119] lr: 1.2000e-02 eta: 1 day, 7:40:18 time: 0.3592 data_time: 0.0227 memory: 11108 grad_norm: 4.0226 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0319 loss: 3.0319 2022/10/09 06:28:48 - mmengine - INFO - Epoch(train) [3][1980/2119] lr: 1.2000e-02 eta: 1 day, 7:40:03 time: 0.3585 data_time: 0.0229 memory: 11108 grad_norm: 4.0068 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9400 loss: 2.9400 2022/10/09 06:28:56 - mmengine - INFO - Epoch(train) [3][2000/2119] lr: 1.2000e-02 eta: 1 day, 7:39:46 time: 0.3555 data_time: 0.0218 memory: 11108 grad_norm: 4.0233 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.1523 loss: 3.1523 2022/10/09 06:29:03 - mmengine - INFO - Epoch(train) [3][2020/2119] lr: 1.2000e-02 eta: 1 day, 7:39:26 time: 0.3534 data_time: 0.0230 memory: 11108 grad_norm: 4.0460 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9068 loss: 2.9068 2022/10/09 06:29:10 - mmengine - INFO - Epoch(train) [3][2040/2119] lr: 1.2000e-02 eta: 1 day, 7:39:13 time: 0.3602 data_time: 0.0233 memory: 11108 grad_norm: 4.0679 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0705 loss: 3.0705 2022/10/09 06:29:17 - mmengine - INFO - Epoch(train) [3][2060/2119] lr: 1.2000e-02 eta: 1 day, 7:38:57 time: 0.3570 data_time: 0.0190 memory: 11108 grad_norm: 4.0191 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0210 loss: 3.0210 2022/10/09 06:29:24 - mmengine - INFO - Epoch(train) [3][2080/2119] lr: 1.2000e-02 eta: 1 day, 7:38:37 time: 0.3530 data_time: 0.0176 memory: 11108 grad_norm: 4.0266 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8146 loss: 2.8146 2022/10/09 06:29:31 - mmengine - INFO - Epoch(train) [3][2100/2119] lr: 1.2000e-02 eta: 1 day, 7:38:21 time: 0.3564 data_time: 0.0191 memory: 11108 grad_norm: 3.9756 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.1892 loss: 3.1892 2022/10/09 06:29:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 06:29:38 - mmengine - INFO - Epoch(train) [3][2119/2119] lr: 1.2000e-02 eta: 1 day, 7:38:21 time: 0.3534 data_time: 0.0177 memory: 11108 grad_norm: 3.9898 top1_acc: 0.5000 top5_acc: 0.7000 loss_cls: 2.8897 loss: 2.8897 2022/10/09 06:29:48 - mmengine - INFO - Epoch(train) [4][20/2119] lr: 1.6000e-02 eta: 1 day, 7:34:46 time: 0.5074 data_time: 0.1316 memory: 11108 grad_norm: 4.0117 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 3.1333 loss: 3.1333 2022/10/09 06:29:55 - mmengine - INFO - Epoch(train) [4][40/2119] lr: 1.6000e-02 eta: 1 day, 7:34:47 time: 0.3738 data_time: 0.0219 memory: 11108 grad_norm: 4.0360 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0064 loss: 3.0064 2022/10/09 06:30:03 - mmengine - INFO - Epoch(train) [4][60/2119] lr: 1.6000e-02 eta: 1 day, 7:34:32 time: 0.3574 data_time: 0.0174 memory: 11108 grad_norm: 3.9844 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9785 loss: 2.9785 2022/10/09 06:30:10 - mmengine - INFO - Epoch(train) [4][80/2119] lr: 1.6000e-02 eta: 1 day, 7:34:23 time: 0.3628 data_time: 0.0227 memory: 11108 grad_norm: 4.0138 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0548 loss: 3.0548 2022/10/09 06:30:17 - mmengine - INFO - Epoch(train) [4][100/2119] lr: 1.6000e-02 eta: 1 day, 7:34:14 time: 0.3631 data_time: 0.0216 memory: 11108 grad_norm: 3.9713 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.0388 loss: 3.0388 2022/10/09 06:30:24 - mmengine - INFO - Epoch(train) [4][120/2119] lr: 1.6000e-02 eta: 1 day, 7:34:04 time: 0.3622 data_time: 0.0248 memory: 11108 grad_norm: 3.9281 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.3326 loss: 3.3326 2022/10/09 06:30:32 - mmengine - INFO - Epoch(train) [4][140/2119] lr: 1.6000e-02 eta: 1 day, 7:33:49 time: 0.3568 data_time: 0.0227 memory: 11108 grad_norm: 3.9779 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 3.1350 loss: 3.1350 2022/10/09 06:30:39 - mmengine - INFO - Epoch(train) [4][160/2119] lr: 1.6000e-02 eta: 1 day, 7:33:34 time: 0.3575 data_time: 0.0225 memory: 11108 grad_norm: 3.9673 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8623 loss: 2.8623 2022/10/09 06:30:46 - mmengine - INFO - Epoch(train) [4][180/2119] lr: 1.6000e-02 eta: 1 day, 7:33:21 time: 0.3582 data_time: 0.0260 memory: 11108 grad_norm: 3.9366 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9991 loss: 2.9991 2022/10/09 06:30:53 - mmengine - INFO - Epoch(train) [4][200/2119] lr: 1.6000e-02 eta: 1 day, 7:33:05 time: 0.3561 data_time: 0.0223 memory: 11108 grad_norm: 3.9419 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0423 loss: 3.0423 2022/10/09 06:31:00 - mmengine - INFO - Epoch(train) [4][220/2119] lr: 1.6000e-02 eta: 1 day, 7:32:50 time: 0.3564 data_time: 0.0187 memory: 11108 grad_norm: 4.0012 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 3.2226 loss: 3.2226 2022/10/09 06:31:07 - mmengine - INFO - Epoch(train) [4][240/2119] lr: 1.6000e-02 eta: 1 day, 7:32:36 time: 0.3577 data_time: 0.0214 memory: 11108 grad_norm: 4.0072 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9809 loss: 2.9809 2022/10/09 06:31:14 - mmengine - INFO - Epoch(train) [4][260/2119] lr: 1.6000e-02 eta: 1 day, 7:32:19 time: 0.3549 data_time: 0.0166 memory: 11108 grad_norm: 3.9161 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0751 loss: 3.0751 2022/10/09 06:31:22 - mmengine - INFO - Epoch(train) [4][280/2119] lr: 1.6000e-02 eta: 1 day, 7:32:11 time: 0.3639 data_time: 0.0204 memory: 11108 grad_norm: 3.8648 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9497 loss: 2.9497 2022/10/09 06:31:29 - mmengine - INFO - Epoch(train) [4][300/2119] lr: 1.6000e-02 eta: 1 day, 7:31:53 time: 0.3536 data_time: 0.0215 memory: 11108 grad_norm: 3.9442 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1795 loss: 3.1795 2022/10/09 06:31:36 - mmengine - INFO - Epoch(train) [4][320/2119] lr: 1.6000e-02 eta: 1 day, 7:31:40 time: 0.3587 data_time: 0.0196 memory: 11108 grad_norm: 3.9184 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8229 loss: 2.8229 2022/10/09 06:31:43 - mmengine - INFO - Epoch(train) [4][340/2119] lr: 1.6000e-02 eta: 1 day, 7:31:28 time: 0.3597 data_time: 0.0202 memory: 11108 grad_norm: 3.8973 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 3.0461 loss: 3.0461 2022/10/09 06:31:50 - mmengine - INFO - Epoch(train) [4][360/2119] lr: 1.6000e-02 eta: 1 day, 7:31:13 time: 0.3564 data_time: 0.0237 memory: 11108 grad_norm: 3.9540 top1_acc: 0.1250 top5_acc: 0.1875 loss_cls: 3.1206 loss: 3.1206 2022/10/09 06:31:57 - mmengine - INFO - Epoch(train) [4][380/2119] lr: 1.6000e-02 eta: 1 day, 7:31:00 time: 0.3582 data_time: 0.0187 memory: 11108 grad_norm: 3.9706 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1832 loss: 3.1832 2022/10/09 06:32:05 - mmengine - INFO - Epoch(train) [4][400/2119] lr: 1.6000e-02 eta: 1 day, 7:30:52 time: 0.3641 data_time: 0.0193 memory: 11108 grad_norm: 3.9486 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 3.2700 loss: 3.2700 2022/10/09 06:32:12 - mmengine - INFO - Epoch(train) [4][420/2119] lr: 1.6000e-02 eta: 1 day, 7:30:35 time: 0.3536 data_time: 0.0188 memory: 11108 grad_norm: 3.9430 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 3.0668 loss: 3.0668 2022/10/09 06:32:19 - mmengine - INFO - Epoch(train) [4][440/2119] lr: 1.6000e-02 eta: 1 day, 7:30:23 time: 0.3598 data_time: 0.0202 memory: 11108 grad_norm: 3.8822 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.0159 loss: 3.0159 2022/10/09 06:32:26 - mmengine - INFO - Epoch(train) [4][460/2119] lr: 1.6000e-02 eta: 1 day, 7:30:10 time: 0.3587 data_time: 0.0230 memory: 11108 grad_norm: 3.9002 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0463 loss: 3.0463 2022/10/09 06:32:33 - mmengine - INFO - Epoch(train) [4][480/2119] lr: 1.6000e-02 eta: 1 day, 7:29:55 time: 0.3562 data_time: 0.0209 memory: 11108 grad_norm: 3.8919 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 3.2236 loss: 3.2236 2022/10/09 06:32:41 - mmengine - INFO - Epoch(train) [4][500/2119] lr: 1.6000e-02 eta: 1 day, 7:29:51 time: 0.3677 data_time: 0.0197 memory: 11108 grad_norm: 3.8493 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0490 loss: 3.0490 2022/10/09 06:32:48 - mmengine - INFO - Epoch(train) [4][520/2119] lr: 1.6000e-02 eta: 1 day, 7:29:43 time: 0.3636 data_time: 0.0270 memory: 11108 grad_norm: 3.8843 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.1107 loss: 3.1107 2022/10/09 06:32:55 - mmengine - INFO - Epoch(train) [4][540/2119] lr: 1.6000e-02 eta: 1 day, 7:29:26 time: 0.3545 data_time: 0.0205 memory: 11108 grad_norm: 3.9377 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0324 loss: 3.0324 2022/10/09 06:33:02 - mmengine - INFO - Epoch(train) [4][560/2119] lr: 1.6000e-02 eta: 1 day, 7:29:14 time: 0.3598 data_time: 0.0184 memory: 11108 grad_norm: 3.8878 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8430 loss: 2.8430 2022/10/09 06:33:09 - mmengine - INFO - Epoch(train) [4][580/2119] lr: 1.6000e-02 eta: 1 day, 7:29:06 time: 0.3629 data_time: 0.0192 memory: 11108 grad_norm: 3.9598 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.8448 loss: 2.8448 2022/10/09 06:33:17 - mmengine - INFO - Epoch(train) [4][600/2119] lr: 1.6000e-02 eta: 1 day, 7:28:55 time: 0.3604 data_time: 0.0187 memory: 11108 grad_norm: 3.9278 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0476 loss: 3.0476 2022/10/09 06:33:24 - mmengine - INFO - Epoch(train) [4][620/2119] lr: 1.6000e-02 eta: 1 day, 7:28:37 time: 0.3527 data_time: 0.0210 memory: 11108 grad_norm: 3.9281 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 3.1154 loss: 3.1154 2022/10/09 06:33:31 - mmengine - INFO - Epoch(train) [4][640/2119] lr: 1.6000e-02 eta: 1 day, 7:28:26 time: 0.3601 data_time: 0.0207 memory: 11108 grad_norm: 3.9241 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.1114 loss: 3.1114 2022/10/09 06:33:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 06:33:38 - mmengine - INFO - Epoch(train) [4][660/2119] lr: 1.6000e-02 eta: 1 day, 7:28:13 time: 0.3588 data_time: 0.0197 memory: 11108 grad_norm: 3.9134 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0659 loss: 3.0659 2022/10/09 06:33:45 - mmengine - INFO - Epoch(train) [4][680/2119] lr: 1.6000e-02 eta: 1 day, 7:28:05 time: 0.3637 data_time: 0.0233 memory: 11108 grad_norm: 3.8913 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0793 loss: 3.0793 2022/10/09 06:33:52 - mmengine - INFO - Epoch(train) [4][700/2119] lr: 1.6000e-02 eta: 1 day, 7:27:53 time: 0.3588 data_time: 0.0185 memory: 11108 grad_norm: 3.8794 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9383 loss: 2.9383 2022/10/09 06:34:00 - mmengine - INFO - Epoch(train) [4][720/2119] lr: 1.6000e-02 eta: 1 day, 7:27:40 time: 0.3582 data_time: 0.0243 memory: 11108 grad_norm: 3.9028 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8450 loss: 2.8450 2022/10/09 06:34:07 - mmengine - INFO - Epoch(train) [4][740/2119] lr: 1.6000e-02 eta: 1 day, 7:27:29 time: 0.3597 data_time: 0.0208 memory: 11108 grad_norm: 3.9141 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9367 loss: 2.9367 2022/10/09 06:34:14 - mmengine - INFO - Epoch(train) [4][760/2119] lr: 1.6000e-02 eta: 1 day, 7:27:15 time: 0.3573 data_time: 0.0180 memory: 11108 grad_norm: 3.8683 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1307 loss: 3.1307 2022/10/09 06:34:21 - mmengine - INFO - Epoch(train) [4][780/2119] lr: 1.6000e-02 eta: 1 day, 7:27:02 time: 0.3581 data_time: 0.0186 memory: 11108 grad_norm: 3.8533 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1811 loss: 3.1811 2022/10/09 06:34:28 - mmengine - INFO - Epoch(train) [4][800/2119] lr: 1.6000e-02 eta: 1 day, 7:26:54 time: 0.3629 data_time: 0.0218 memory: 11108 grad_norm: 3.8827 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 3.0472 loss: 3.0472 2022/10/09 06:34:36 - mmengine - INFO - Epoch(train) [4][820/2119] lr: 1.6000e-02 eta: 1 day, 7:26:43 time: 0.3602 data_time: 0.0224 memory: 11108 grad_norm: 3.8676 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8664 loss: 2.8664 2022/10/09 06:34:43 - mmengine - INFO - Epoch(train) [4][840/2119] lr: 1.6000e-02 eta: 1 day, 7:26:28 time: 0.3551 data_time: 0.0211 memory: 11108 grad_norm: 3.9155 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.1666 loss: 3.1666 2022/10/09 06:34:50 - mmengine - INFO - Epoch(train) [4][860/2119] lr: 1.6000e-02 eta: 1 day, 7:26:13 time: 0.3554 data_time: 0.0217 memory: 11108 grad_norm: 3.8503 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 3.1387 loss: 3.1387 2022/10/09 06:34:57 - mmengine - INFO - Epoch(train) [4][880/2119] lr: 1.6000e-02 eta: 1 day, 7:25:59 time: 0.3572 data_time: 0.0198 memory: 11108 grad_norm: 3.8207 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9486 loss: 2.9486 2022/10/09 06:35:04 - mmengine - INFO - Epoch(train) [4][900/2119] lr: 1.6000e-02 eta: 1 day, 7:25:46 time: 0.3571 data_time: 0.0209 memory: 11108 grad_norm: 3.8610 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7941 loss: 2.7941 2022/10/09 06:35:11 - mmengine - INFO - Epoch(train) [4][920/2119] lr: 1.6000e-02 eta: 1 day, 7:25:34 time: 0.3596 data_time: 0.0214 memory: 11108 grad_norm: 3.8290 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9905 loss: 2.9905 2022/10/09 06:35:19 - mmengine - INFO - Epoch(train) [4][940/2119] lr: 1.6000e-02 eta: 1 day, 7:25:25 time: 0.3617 data_time: 0.0184 memory: 11108 grad_norm: 3.9037 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.1252 loss: 3.1252 2022/10/09 06:35:26 - mmengine - INFO - Epoch(train) [4][960/2119] lr: 1.6000e-02 eta: 1 day, 7:25:10 time: 0.3553 data_time: 0.0205 memory: 11108 grad_norm: 3.8753 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9918 loss: 2.9918 2022/10/09 06:35:33 - mmengine - INFO - Epoch(train) [4][980/2119] lr: 1.6000e-02 eta: 1 day, 7:24:56 time: 0.3558 data_time: 0.0226 memory: 11108 grad_norm: 3.8983 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.1137 loss: 3.1137 2022/10/09 06:35:40 - mmengine - INFO - Epoch(train) [4][1000/2119] lr: 1.6000e-02 eta: 1 day, 7:24:40 time: 0.3550 data_time: 0.0223 memory: 11108 grad_norm: 3.8785 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.2896 loss: 3.2896 2022/10/09 06:35:47 - mmengine - INFO - Epoch(train) [4][1020/2119] lr: 1.6000e-02 eta: 1 day, 7:24:31 time: 0.3612 data_time: 0.0221 memory: 11108 grad_norm: 3.9137 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.0279 loss: 3.0279 2022/10/09 06:35:54 - mmengine - INFO - Epoch(train) [4][1040/2119] lr: 1.6000e-02 eta: 1 day, 7:24:16 time: 0.3556 data_time: 0.0194 memory: 11108 grad_norm: 3.8364 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9645 loss: 2.9645 2022/10/09 06:36:01 - mmengine - INFO - Epoch(train) [4][1060/2119] lr: 1.6000e-02 eta: 1 day, 7:24:08 time: 0.3626 data_time: 0.0217 memory: 11108 grad_norm: 3.8547 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.2859 loss: 3.2859 2022/10/09 06:36:09 - mmengine - INFO - Epoch(train) [4][1080/2119] lr: 1.6000e-02 eta: 1 day, 7:23:58 time: 0.3610 data_time: 0.0223 memory: 11108 grad_norm: 3.8332 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0226 loss: 3.0226 2022/10/09 06:36:16 - mmengine - INFO - Epoch(train) [4][1100/2119] lr: 1.6000e-02 eta: 1 day, 7:23:48 time: 0.3613 data_time: 0.0190 memory: 11108 grad_norm: 3.8577 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9815 loss: 2.9815 2022/10/09 06:36:23 - mmengine - INFO - Epoch(train) [4][1120/2119] lr: 1.6000e-02 eta: 1 day, 7:23:33 time: 0.3554 data_time: 0.0184 memory: 11108 grad_norm: 3.8748 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1177 loss: 3.1177 2022/10/09 06:36:30 - mmengine - INFO - Epoch(train) [4][1140/2119] lr: 1.6000e-02 eta: 1 day, 7:23:23 time: 0.3608 data_time: 0.0187 memory: 11108 grad_norm: 3.7912 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9756 loss: 2.9756 2022/10/09 06:36:37 - mmengine - INFO - Epoch(train) [4][1160/2119] lr: 1.6000e-02 eta: 1 day, 7:23:11 time: 0.3585 data_time: 0.0241 memory: 11108 grad_norm: 3.8388 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0044 loss: 3.0044 2022/10/09 06:36:45 - mmengine - INFO - Epoch(train) [4][1180/2119] lr: 1.6000e-02 eta: 1 day, 7:23:00 time: 0.3596 data_time: 0.0187 memory: 11108 grad_norm: 3.8727 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9755 loss: 2.9755 2022/10/09 06:36:52 - mmengine - INFO - Epoch(train) [4][1200/2119] lr: 1.6000e-02 eta: 1 day, 7:22:47 time: 0.3568 data_time: 0.0187 memory: 11108 grad_norm: 3.7854 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9862 loss: 2.9862 2022/10/09 06:36:59 - mmengine - INFO - Epoch(train) [4][1220/2119] lr: 1.6000e-02 eta: 1 day, 7:22:38 time: 0.3619 data_time: 0.0198 memory: 11108 grad_norm: 3.8106 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9240 loss: 2.9240 2022/10/09 06:37:06 - mmengine - INFO - Epoch(train) [4][1240/2119] lr: 1.6000e-02 eta: 1 day, 7:22:27 time: 0.3598 data_time: 0.0261 memory: 11108 grad_norm: 3.8621 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8777 loss: 2.8777 2022/10/09 06:37:13 - mmengine - INFO - Epoch(train) [4][1260/2119] lr: 1.6000e-02 eta: 1 day, 7:22:11 time: 0.3528 data_time: 0.0168 memory: 11108 grad_norm: 3.8532 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0900 loss: 3.0900 2022/10/09 06:37:20 - mmengine - INFO - Epoch(train) [4][1280/2119] lr: 1.6000e-02 eta: 1 day, 7:22:02 time: 0.3617 data_time: 0.0232 memory: 11108 grad_norm: 3.8250 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9025 loss: 2.9025 2022/10/09 06:37:28 - mmengine - INFO - Epoch(train) [4][1300/2119] lr: 1.6000e-02 eta: 1 day, 7:21:47 time: 0.3548 data_time: 0.0185 memory: 11108 grad_norm: 3.8527 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 3.0397 loss: 3.0397 2022/10/09 06:37:35 - mmengine - INFO - Epoch(train) [4][1320/2119] lr: 1.6000e-02 eta: 1 day, 7:21:33 time: 0.3562 data_time: 0.0201 memory: 11108 grad_norm: 3.8511 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0838 loss: 3.0838 2022/10/09 06:37:42 - mmengine - INFO - Epoch(train) [4][1340/2119] lr: 1.6000e-02 eta: 1 day, 7:21:22 time: 0.3590 data_time: 0.0174 memory: 11108 grad_norm: 3.8797 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7882 loss: 2.7882 2022/10/09 06:37:49 - mmengine - INFO - Epoch(train) [4][1360/2119] lr: 1.6000e-02 eta: 1 day, 7:21:09 time: 0.3564 data_time: 0.0218 memory: 11108 grad_norm: 3.8477 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0056 loss: 3.0056 2022/10/09 06:37:56 - mmengine - INFO - Epoch(train) [4][1380/2119] lr: 1.6000e-02 eta: 1 day, 7:20:56 time: 0.3568 data_time: 0.0207 memory: 11108 grad_norm: 3.8502 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9074 loss: 2.9074 2022/10/09 06:38:03 - mmengine - INFO - Epoch(train) [4][1400/2119] lr: 1.6000e-02 eta: 1 day, 7:20:44 time: 0.3578 data_time: 0.0196 memory: 11108 grad_norm: 3.8840 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8012 loss: 2.8012 2022/10/09 06:38:10 - mmengine - INFO - Epoch(train) [4][1420/2119] lr: 1.6000e-02 eta: 1 day, 7:20:32 time: 0.3589 data_time: 0.0185 memory: 11108 grad_norm: 3.8932 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.9678 loss: 2.9678 2022/10/09 06:38:18 - mmengine - INFO - Epoch(train) [4][1440/2119] lr: 1.6000e-02 eta: 1 day, 7:20:20 time: 0.3578 data_time: 0.0227 memory: 11108 grad_norm: 3.8345 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.1073 loss: 3.1073 2022/10/09 06:38:25 - mmengine - INFO - Epoch(train) [4][1460/2119] lr: 1.6000e-02 eta: 1 day, 7:20:07 time: 0.3567 data_time: 0.0223 memory: 11108 grad_norm: 3.8540 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0485 loss: 3.0485 2022/10/09 06:38:32 - mmengine - INFO - Epoch(train) [4][1480/2119] lr: 1.6000e-02 eta: 1 day, 7:19:53 time: 0.3549 data_time: 0.0213 memory: 11108 grad_norm: 3.8089 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8982 loss: 2.8982 2022/10/09 06:38:39 - mmengine - INFO - Epoch(train) [4][1500/2119] lr: 1.6000e-02 eta: 1 day, 7:19:41 time: 0.3581 data_time: 0.0180 memory: 11108 grad_norm: 3.8299 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8516 loss: 2.8516 2022/10/09 06:38:46 - mmengine - INFO - Epoch(train) [4][1520/2119] lr: 1.6000e-02 eta: 1 day, 7:19:26 time: 0.3542 data_time: 0.0230 memory: 11108 grad_norm: 3.7324 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8738 loss: 2.8738 2022/10/09 06:38:53 - mmengine - INFO - Epoch(train) [4][1540/2119] lr: 1.6000e-02 eta: 1 day, 7:19:14 time: 0.3570 data_time: 0.0164 memory: 11108 grad_norm: 3.7991 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 3.0755 loss: 3.0755 2022/10/09 06:39:00 - mmengine - INFO - Epoch(train) [4][1560/2119] lr: 1.6000e-02 eta: 1 day, 7:19:01 time: 0.3563 data_time: 0.0241 memory: 11108 grad_norm: 3.8123 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9878 loss: 2.9878 2022/10/09 06:39:07 - mmengine - INFO - Epoch(train) [4][1580/2119] lr: 1.6000e-02 eta: 1 day, 7:18:46 time: 0.3551 data_time: 0.0201 memory: 11108 grad_norm: 3.8352 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0155 loss: 3.0155 2022/10/09 06:39:15 - mmengine - INFO - Epoch(train) [4][1600/2119] lr: 1.6000e-02 eta: 1 day, 7:18:31 time: 0.3533 data_time: 0.0245 memory: 11108 grad_norm: 3.7957 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9330 loss: 2.9330 2022/10/09 06:39:22 - mmengine - INFO - Epoch(train) [4][1620/2119] lr: 1.6000e-02 eta: 1 day, 7:18:16 time: 0.3532 data_time: 0.0219 memory: 11108 grad_norm: 3.7551 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.9384 loss: 2.9384 2022/10/09 06:39:29 - mmengine - INFO - Epoch(train) [4][1640/2119] lr: 1.6000e-02 eta: 1 day, 7:18:11 time: 0.3675 data_time: 0.0195 memory: 11108 grad_norm: 3.8134 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9940 loss: 2.9940 2022/10/09 06:39:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 06:39:36 - mmengine - INFO - Epoch(train) [4][1660/2119] lr: 1.6000e-02 eta: 1 day, 7:17:56 time: 0.3533 data_time: 0.0167 memory: 11108 grad_norm: 3.7828 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9623 loss: 2.9623 2022/10/09 06:39:43 - mmengine - INFO - Epoch(train) [4][1680/2119] lr: 1.6000e-02 eta: 1 day, 7:17:40 time: 0.3530 data_time: 0.0215 memory: 11108 grad_norm: 3.8194 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0515 loss: 3.0515 2022/10/09 06:39:50 - mmengine - INFO - Epoch(train) [4][1700/2119] lr: 1.6000e-02 eta: 1 day, 7:17:29 time: 0.3585 data_time: 0.0228 memory: 11108 grad_norm: 3.8468 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9986 loss: 2.9986 2022/10/09 06:39:57 - mmengine - INFO - Epoch(train) [4][1720/2119] lr: 1.6000e-02 eta: 1 day, 7:17:17 time: 0.3573 data_time: 0.0213 memory: 11108 grad_norm: 3.8218 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8194 loss: 2.8194 2022/10/09 06:40:04 - mmengine - INFO - Epoch(train) [4][1740/2119] lr: 1.6000e-02 eta: 1 day, 7:17:03 time: 0.3544 data_time: 0.0175 memory: 11108 grad_norm: 3.8422 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.0426 loss: 3.0426 2022/10/09 06:40:12 - mmengine - INFO - Epoch(train) [4][1760/2119] lr: 1.6000e-02 eta: 1 day, 7:16:52 time: 0.3584 data_time: 0.0187 memory: 11108 grad_norm: 3.8204 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7665 loss: 2.7665 2022/10/09 06:40:19 - mmengine - INFO - Epoch(train) [4][1780/2119] lr: 1.6000e-02 eta: 1 day, 7:16:47 time: 0.3672 data_time: 0.0218 memory: 11108 grad_norm: 3.8033 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9017 loss: 2.9017 2022/10/09 06:40:26 - mmengine - INFO - Epoch(train) [4][1800/2119] lr: 1.6000e-02 eta: 1 day, 7:16:39 time: 0.3627 data_time: 0.0221 memory: 11108 grad_norm: 3.7582 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9736 loss: 2.9736 2022/10/09 06:40:33 - mmengine - INFO - Epoch(train) [4][1820/2119] lr: 1.6000e-02 eta: 1 day, 7:16:23 time: 0.3523 data_time: 0.0195 memory: 11108 grad_norm: 3.7565 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7707 loss: 2.7707 2022/10/09 06:40:40 - mmengine - INFO - Epoch(train) [4][1840/2119] lr: 1.6000e-02 eta: 1 day, 7:16:10 time: 0.3560 data_time: 0.0224 memory: 11108 grad_norm: 3.7374 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 3.0860 loss: 3.0860 2022/10/09 06:40:48 - mmengine - INFO - Epoch(train) [4][1860/2119] lr: 1.6000e-02 eta: 1 day, 7:16:00 time: 0.3588 data_time: 0.0187 memory: 11108 grad_norm: 3.8457 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9482 loss: 2.9482 2022/10/09 06:40:55 - mmengine - INFO - Epoch(train) [4][1880/2119] lr: 1.6000e-02 eta: 1 day, 7:15:45 time: 0.3533 data_time: 0.0229 memory: 11108 grad_norm: 3.8267 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7792 loss: 2.7792 2022/10/09 06:41:02 - mmengine - INFO - Epoch(train) [4][1900/2119] lr: 1.6000e-02 eta: 1 day, 7:15:32 time: 0.3559 data_time: 0.0204 memory: 11108 grad_norm: 3.8174 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.2487 loss: 3.2487 2022/10/09 06:41:09 - mmengine - INFO - Epoch(train) [4][1920/2119] lr: 1.6000e-02 eta: 1 day, 7:15:22 time: 0.3598 data_time: 0.0235 memory: 11108 grad_norm: 3.8379 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8497 loss: 2.8497 2022/10/09 06:41:16 - mmengine - INFO - Epoch(train) [4][1940/2119] lr: 1.6000e-02 eta: 1 day, 7:15:09 time: 0.3567 data_time: 0.0156 memory: 11108 grad_norm: 3.8929 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.1662 loss: 3.1662 2022/10/09 06:41:23 - mmengine - INFO - Epoch(train) [4][1960/2119] lr: 1.6000e-02 eta: 1 day, 7:14:56 time: 0.3555 data_time: 0.0240 memory: 11108 grad_norm: 3.7847 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.0172 loss: 3.0172 2022/10/09 06:41:30 - mmengine - INFO - Epoch(train) [4][1980/2119] lr: 1.6000e-02 eta: 1 day, 7:14:48 time: 0.3618 data_time: 0.0173 memory: 11108 grad_norm: 3.7967 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0198 loss: 3.0198 2022/10/09 06:41:38 - mmengine - INFO - Epoch(train) [4][2000/2119] lr: 1.6000e-02 eta: 1 day, 7:14:36 time: 0.3582 data_time: 0.0212 memory: 11108 grad_norm: 3.7723 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9466 loss: 2.9466 2022/10/09 06:41:45 - mmengine - INFO - Epoch(train) [4][2020/2119] lr: 1.6000e-02 eta: 1 day, 7:14:21 time: 0.3518 data_time: 0.0205 memory: 11108 grad_norm: 3.8644 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9500 loss: 2.9500 2022/10/09 06:41:52 - mmengine - INFO - Epoch(train) [4][2040/2119] lr: 1.6000e-02 eta: 1 day, 7:14:13 time: 0.3628 data_time: 0.0200 memory: 11108 grad_norm: 3.8241 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9852 loss: 2.9852 2022/10/09 06:41:59 - mmengine - INFO - Epoch(train) [4][2060/2119] lr: 1.6000e-02 eta: 1 day, 7:14:03 time: 0.3593 data_time: 0.0208 memory: 11108 grad_norm: 3.8012 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0171 loss: 3.0171 2022/10/09 06:42:06 - mmengine - INFO - Epoch(train) [4][2080/2119] lr: 1.6000e-02 eta: 1 day, 7:13:49 time: 0.3551 data_time: 0.0194 memory: 11108 grad_norm: 3.7440 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8553 loss: 2.8553 2022/10/09 06:42:13 - mmengine - INFO - Epoch(train) [4][2100/2119] lr: 1.6000e-02 eta: 1 day, 7:13:38 time: 0.3583 data_time: 0.0161 memory: 11108 grad_norm: 3.8035 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9456 loss: 2.9456 2022/10/09 06:42:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 06:42:20 - mmengine - INFO - Epoch(train) [4][2119/2119] lr: 1.6000e-02 eta: 1 day, 7:13:38 time: 0.3424 data_time: 0.0207 memory: 11108 grad_norm: 3.8223 top1_acc: 0.3000 top5_acc: 0.4000 loss_cls: 2.8802 loss: 2.8802 2022/10/09 06:42:20 - mmengine - INFO - Saving checkpoint at 4 epochs 2022/10/09 06:42:31 - mmengine - INFO - Epoch(train) [5][20/2119] lr: 2.0000e-02 eta: 1 day, 7:10:12 time: 0.4447 data_time: 0.1107 memory: 11108 grad_norm: 3.8096 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8332 loss: 2.8332 2022/10/09 06:42:39 - mmengine - INFO - Epoch(train) [5][40/2119] lr: 2.0000e-02 eta: 1 day, 7:10:08 time: 0.3672 data_time: 0.0193 memory: 11108 grad_norm: 3.7874 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.9887 loss: 2.9887 2022/10/09 06:42:46 - mmengine - INFO - Epoch(train) [5][60/2119] lr: 2.0000e-02 eta: 1 day, 7:09:55 time: 0.3547 data_time: 0.0212 memory: 11108 grad_norm: 3.7609 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0132 loss: 3.0132 2022/10/09 06:42:53 - mmengine - INFO - Epoch(train) [5][80/2119] lr: 2.0000e-02 eta: 1 day, 7:09:43 time: 0.3558 data_time: 0.0205 memory: 11108 grad_norm: 3.8129 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8866 loss: 2.8866 2022/10/09 06:43:00 - mmengine - INFO - Epoch(train) [5][100/2119] lr: 2.0000e-02 eta: 1 day, 7:09:32 time: 0.3575 data_time: 0.0206 memory: 11108 grad_norm: 3.8274 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8090 loss: 2.8090 2022/10/09 06:43:07 - mmengine - INFO - Epoch(train) [5][120/2119] lr: 2.0000e-02 eta: 1 day, 7:09:21 time: 0.3586 data_time: 0.0247 memory: 11108 grad_norm: 3.7425 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9283 loss: 2.9283 2022/10/09 06:43:14 - mmengine - INFO - Epoch(train) [5][140/2119] lr: 2.0000e-02 eta: 1 day, 7:09:08 time: 0.3545 data_time: 0.0179 memory: 11108 grad_norm: 3.7719 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8754 loss: 2.8754 2022/10/09 06:43:21 - mmengine - INFO - Epoch(train) [5][160/2119] lr: 2.0000e-02 eta: 1 day, 7:08:58 time: 0.3584 data_time: 0.0209 memory: 11108 grad_norm: 3.7691 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9980 loss: 2.9980 2022/10/09 06:43:29 - mmengine - INFO - Epoch(train) [5][180/2119] lr: 2.0000e-02 eta: 1 day, 7:08:46 time: 0.3554 data_time: 0.0213 memory: 11108 grad_norm: 3.7658 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7908 loss: 2.7908 2022/10/09 06:43:36 - mmengine - INFO - Epoch(train) [5][200/2119] lr: 2.0000e-02 eta: 1 day, 7:08:35 time: 0.3582 data_time: 0.0202 memory: 11108 grad_norm: 3.7655 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9395 loss: 2.9395 2022/10/09 06:43:43 - mmengine - INFO - Epoch(train) [5][220/2119] lr: 2.0000e-02 eta: 1 day, 7:08:27 time: 0.3620 data_time: 0.0207 memory: 11108 grad_norm: 3.8012 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1794 loss: 3.1794 2022/10/09 06:43:50 - mmengine - INFO - Epoch(train) [5][240/2119] lr: 2.0000e-02 eta: 1 day, 7:08:16 time: 0.3571 data_time: 0.0233 memory: 11108 grad_norm: 3.6966 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8283 loss: 2.8283 2022/10/09 06:43:57 - mmengine - INFO - Epoch(train) [5][260/2119] lr: 2.0000e-02 eta: 1 day, 7:08:07 time: 0.3598 data_time: 0.0210 memory: 11108 grad_norm: 3.7882 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9810 loss: 2.9810 2022/10/09 06:44:04 - mmengine - INFO - Epoch(train) [5][280/2119] lr: 2.0000e-02 eta: 1 day, 7:07:56 time: 0.3576 data_time: 0.0231 memory: 11108 grad_norm: 3.7840 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7425 loss: 2.7425 2022/10/09 06:44:12 - mmengine - INFO - Epoch(train) [5][300/2119] lr: 2.0000e-02 eta: 1 day, 7:07:45 time: 0.3572 data_time: 0.0212 memory: 11108 grad_norm: 3.7924 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0794 loss: 3.0794 2022/10/09 06:44:19 - mmengine - INFO - Epoch(train) [5][320/2119] lr: 2.0000e-02 eta: 1 day, 7:07:36 time: 0.3593 data_time: 0.0195 memory: 11108 grad_norm: 3.7027 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9275 loss: 2.9275 2022/10/09 06:44:26 - mmengine - INFO - Epoch(train) [5][340/2119] lr: 2.0000e-02 eta: 1 day, 7:07:22 time: 0.3538 data_time: 0.0208 memory: 11108 grad_norm: 3.6579 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.1248 loss: 3.1248 2022/10/09 06:44:33 - mmengine - INFO - Epoch(train) [5][360/2119] lr: 2.0000e-02 eta: 1 day, 7:07:11 time: 0.3564 data_time: 0.0223 memory: 11108 grad_norm: 3.7263 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8720 loss: 2.8720 2022/10/09 06:44:40 - mmengine - INFO - Epoch(train) [5][380/2119] lr: 2.0000e-02 eta: 1 day, 7:07:01 time: 0.3586 data_time: 0.0204 memory: 11108 grad_norm: 3.7635 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9835 loss: 2.9835 2022/10/09 06:44:47 - mmengine - INFO - Epoch(train) [5][400/2119] lr: 2.0000e-02 eta: 1 day, 7:06:54 time: 0.3638 data_time: 0.0253 memory: 11108 grad_norm: 3.7215 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8519 loss: 2.8519 2022/10/09 06:44:54 - mmengine - INFO - Epoch(train) [5][420/2119] lr: 2.0000e-02 eta: 1 day, 7:06:41 time: 0.3542 data_time: 0.0186 memory: 11108 grad_norm: 3.7094 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1415 loss: 3.1415 2022/10/09 06:45:02 - mmengine - INFO - Epoch(train) [5][440/2119] lr: 2.0000e-02 eta: 1 day, 7:06:32 time: 0.3589 data_time: 0.0204 memory: 11108 grad_norm: 3.7700 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0193 loss: 3.0193 2022/10/09 06:45:09 - mmengine - INFO - Epoch(train) [5][460/2119] lr: 2.0000e-02 eta: 1 day, 7:06:22 time: 0.3595 data_time: 0.0217 memory: 11108 grad_norm: 3.7627 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8451 loss: 2.8451 2022/10/09 06:45:16 - mmengine - INFO - Epoch(train) [5][480/2119] lr: 2.0000e-02 eta: 1 day, 7:06:13 time: 0.3592 data_time: 0.0221 memory: 11108 grad_norm: 3.7732 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8381 loss: 2.8381 2022/10/09 06:45:23 - mmengine - INFO - Epoch(train) [5][500/2119] lr: 2.0000e-02 eta: 1 day, 7:06:04 time: 0.3602 data_time: 0.0213 memory: 11108 grad_norm: 3.7897 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0675 loss: 3.0675 2022/10/09 06:45:31 - mmengine - INFO - Epoch(train) [5][520/2119] lr: 2.0000e-02 eta: 1 day, 7:05:57 time: 0.3631 data_time: 0.0244 memory: 11108 grad_norm: 3.6976 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9858 loss: 2.9858 2022/10/09 06:45:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 06:45:38 - mmengine - INFO - Epoch(train) [5][540/2119] lr: 2.0000e-02 eta: 1 day, 7:05:46 time: 0.3564 data_time: 0.0282 memory: 11108 grad_norm: 3.7132 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.9335 loss: 2.9335 2022/10/09 06:45:45 - mmengine - INFO - Epoch(train) [5][560/2119] lr: 2.0000e-02 eta: 1 day, 7:05:33 time: 0.3544 data_time: 0.0244 memory: 11108 grad_norm: 3.7172 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0390 loss: 3.0390 2022/10/09 06:45:52 - mmengine - INFO - Epoch(train) [5][580/2119] lr: 2.0000e-02 eta: 1 day, 7:05:26 time: 0.3630 data_time: 0.0197 memory: 11108 grad_norm: 3.6647 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7447 loss: 2.7447 2022/10/09 06:45:59 - mmengine - INFO - Epoch(train) [5][600/2119] lr: 2.0000e-02 eta: 1 day, 7:05:16 time: 0.3587 data_time: 0.0218 memory: 11108 grad_norm: 3.7656 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9735 loss: 2.9735 2022/10/09 06:46:06 - mmengine - INFO - Epoch(train) [5][620/2119] lr: 2.0000e-02 eta: 1 day, 7:05:03 time: 0.3533 data_time: 0.0186 memory: 11108 grad_norm: 3.6471 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7065 loss: 2.7065 2022/10/09 06:46:13 - mmengine - INFO - Epoch(train) [5][640/2119] lr: 2.0000e-02 eta: 1 day, 7:04:51 time: 0.3563 data_time: 0.0191 memory: 11108 grad_norm: 3.7389 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9830 loss: 2.9830 2022/10/09 06:46:21 - mmengine - INFO - Epoch(train) [5][660/2119] lr: 2.0000e-02 eta: 1 day, 7:04:42 time: 0.3593 data_time: 0.0220 memory: 11108 grad_norm: 3.6922 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.0690 loss: 3.0690 2022/10/09 06:46:28 - mmengine - INFO - Epoch(train) [5][680/2119] lr: 2.0000e-02 eta: 1 day, 7:04:32 time: 0.3579 data_time: 0.0258 memory: 11108 grad_norm: 3.6729 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0672 loss: 3.0672 2022/10/09 06:46:35 - mmengine - INFO - Epoch(train) [5][700/2119] lr: 2.0000e-02 eta: 1 day, 7:04:20 time: 0.3559 data_time: 0.0183 memory: 11108 grad_norm: 3.6342 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8861 loss: 2.8861 2022/10/09 06:46:42 - mmengine - INFO - Epoch(train) [5][720/2119] lr: 2.0000e-02 eta: 1 day, 7:04:12 time: 0.3620 data_time: 0.0229 memory: 11108 grad_norm: 3.6678 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 3.0858 loss: 3.0858 2022/10/09 06:46:49 - mmengine - INFO - Epoch(train) [5][740/2119] lr: 2.0000e-02 eta: 1 day, 7:04:02 time: 0.3579 data_time: 0.0202 memory: 11108 grad_norm: 3.6744 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7091 loss: 2.7091 2022/10/09 06:46:56 - mmengine - INFO - Epoch(train) [5][760/2119] lr: 2.0000e-02 eta: 1 day, 7:03:52 time: 0.3584 data_time: 0.0260 memory: 11108 grad_norm: 3.7359 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9020 loss: 2.9020 2022/10/09 06:47:04 - mmengine - INFO - Epoch(train) [5][780/2119] lr: 2.0000e-02 eta: 1 day, 7:03:42 time: 0.3585 data_time: 0.0225 memory: 11108 grad_norm: 3.6766 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0697 loss: 3.0697 2022/10/09 06:47:11 - mmengine - INFO - Epoch(train) [5][800/2119] lr: 2.0000e-02 eta: 1 day, 7:03:31 time: 0.3555 data_time: 0.0208 memory: 11108 grad_norm: 3.7314 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0564 loss: 3.0564 2022/10/09 06:47:18 - mmengine - INFO - Epoch(train) [5][820/2119] lr: 2.0000e-02 eta: 1 day, 7:03:22 time: 0.3598 data_time: 0.0205 memory: 11108 grad_norm: 3.7525 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9152 loss: 2.9152 2022/10/09 06:47:25 - mmengine - INFO - Epoch(train) [5][840/2119] lr: 2.0000e-02 eta: 1 day, 7:03:09 time: 0.3539 data_time: 0.0201 memory: 11108 grad_norm: 3.7062 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 3.0689 loss: 3.0689 2022/10/09 06:47:32 - mmengine - INFO - Epoch(train) [5][860/2119] lr: 2.0000e-02 eta: 1 day, 7:02:56 time: 0.3533 data_time: 0.0231 memory: 11108 grad_norm: 3.7607 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9853 loss: 2.9853 2022/10/09 06:47:39 - mmengine - INFO - Epoch(train) [5][880/2119] lr: 2.0000e-02 eta: 1 day, 7:02:50 time: 0.3652 data_time: 0.0221 memory: 11108 grad_norm: 3.6403 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1347 loss: 3.1347 2022/10/09 06:47:46 - mmengine - INFO - Epoch(train) [5][900/2119] lr: 2.0000e-02 eta: 1 day, 7:02:38 time: 0.3546 data_time: 0.0181 memory: 11108 grad_norm: 3.6881 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9938 loss: 2.9938 2022/10/09 06:47:54 - mmengine - INFO - Epoch(train) [5][920/2119] lr: 2.0000e-02 eta: 1 day, 7:02:27 time: 0.3558 data_time: 0.0261 memory: 11108 grad_norm: 3.6151 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6097 loss: 2.6097 2022/10/09 06:48:01 - mmengine - INFO - Epoch(train) [5][940/2119] lr: 2.0000e-02 eta: 1 day, 7:02:17 time: 0.3595 data_time: 0.0221 memory: 11108 grad_norm: 3.6853 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7771 loss: 2.7771 2022/10/09 06:48:08 - mmengine - INFO - Epoch(train) [5][960/2119] lr: 2.0000e-02 eta: 1 day, 7:02:07 time: 0.3573 data_time: 0.0209 memory: 11108 grad_norm: 3.6625 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0922 loss: 3.0922 2022/10/09 06:48:15 - mmengine - INFO - Epoch(train) [5][980/2119] lr: 2.0000e-02 eta: 1 day, 7:01:55 time: 0.3551 data_time: 0.0190 memory: 11108 grad_norm: 3.6857 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 3.0974 loss: 3.0974 2022/10/09 06:48:22 - mmengine - INFO - Epoch(train) [5][1000/2119] lr: 2.0000e-02 eta: 1 day, 7:01:47 time: 0.3613 data_time: 0.0217 memory: 11108 grad_norm: 3.6100 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8106 loss: 2.8106 2022/10/09 06:48:29 - mmengine - INFO - Epoch(train) [5][1020/2119] lr: 2.0000e-02 eta: 1 day, 7:01:38 time: 0.3587 data_time: 0.0244 memory: 11108 grad_norm: 3.6439 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0066 loss: 3.0066 2022/10/09 06:48:37 - mmengine - INFO - Epoch(train) [5][1040/2119] lr: 2.0000e-02 eta: 1 day, 7:01:32 time: 0.3655 data_time: 0.0175 memory: 11108 grad_norm: 3.6601 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0754 loss: 3.0754 2022/10/09 06:48:44 - mmengine - INFO - Epoch(train) [5][1060/2119] lr: 2.0000e-02 eta: 1 day, 7:01:20 time: 0.3548 data_time: 0.0176 memory: 11108 grad_norm: 3.6433 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.0054 loss: 3.0054 2022/10/09 06:48:51 - mmengine - INFO - Epoch(train) [5][1080/2119] lr: 2.0000e-02 eta: 1 day, 7:01:07 time: 0.3523 data_time: 0.0214 memory: 11108 grad_norm: 3.7604 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8709 loss: 2.8709 2022/10/09 06:48:58 - mmengine - INFO - Epoch(train) [5][1100/2119] lr: 2.0000e-02 eta: 1 day, 7:00:56 time: 0.3568 data_time: 0.0219 memory: 11108 grad_norm: 3.6210 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9795 loss: 2.9795 2022/10/09 06:49:05 - mmengine - INFO - Epoch(train) [5][1120/2119] lr: 2.0000e-02 eta: 1 day, 7:00:46 time: 0.3575 data_time: 0.0224 memory: 11108 grad_norm: 3.6220 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.2386 loss: 3.2386 2022/10/09 06:49:12 - mmengine - INFO - Epoch(train) [5][1140/2119] lr: 2.0000e-02 eta: 1 day, 7:00:36 time: 0.3579 data_time: 0.0183 memory: 11108 grad_norm: 3.6724 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8648 loss: 2.8648 2022/10/09 06:49:20 - mmengine - INFO - Epoch(train) [5][1160/2119] lr: 2.0000e-02 eta: 1 day, 7:00:30 time: 0.3648 data_time: 0.0225 memory: 11108 grad_norm: 3.6565 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7858 loss: 2.7858 2022/10/09 06:49:27 - mmengine - INFO - Epoch(train) [5][1180/2119] lr: 2.0000e-02 eta: 1 day, 7:00:18 time: 0.3539 data_time: 0.0201 memory: 11108 grad_norm: 3.7362 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9026 loss: 2.9026 2022/10/09 06:49:34 - mmengine - INFO - Epoch(train) [5][1200/2119] lr: 2.0000e-02 eta: 1 day, 7:00:06 time: 0.3557 data_time: 0.0252 memory: 11108 grad_norm: 3.6566 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9255 loss: 2.9255 2022/10/09 06:49:41 - mmengine - INFO - Epoch(train) [5][1220/2119] lr: 2.0000e-02 eta: 1 day, 6:59:57 time: 0.3595 data_time: 0.0203 memory: 11108 grad_norm: 3.6899 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7704 loss: 2.7704 2022/10/09 06:49:48 - mmengine - INFO - Epoch(train) [5][1240/2119] lr: 2.0000e-02 eta: 1 day, 6:59:48 time: 0.3583 data_time: 0.0179 memory: 11108 grad_norm: 3.6886 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9931 loss: 2.9931 2022/10/09 06:49:55 - mmengine - INFO - Epoch(train) [5][1260/2119] lr: 2.0000e-02 eta: 1 day, 6:59:36 time: 0.3550 data_time: 0.0176 memory: 11108 grad_norm: 3.6053 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 3.0270 loss: 3.0270 2022/10/09 06:50:02 - mmengine - INFO - Epoch(train) [5][1280/2119] lr: 2.0000e-02 eta: 1 day, 6:59:28 time: 0.3611 data_time: 0.0224 memory: 11108 grad_norm: 3.6710 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9355 loss: 2.9355 2022/10/09 06:50:10 - mmengine - INFO - Epoch(train) [5][1300/2119] lr: 2.0000e-02 eta: 1 day, 6:59:18 time: 0.3569 data_time: 0.0173 memory: 11108 grad_norm: 3.6268 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9201 loss: 2.9201 2022/10/09 06:50:17 - mmengine - INFO - Epoch(train) [5][1320/2119] lr: 2.0000e-02 eta: 1 day, 6:59:07 time: 0.3572 data_time: 0.0202 memory: 11108 grad_norm: 3.6835 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 3.1645 loss: 3.1645 2022/10/09 06:50:24 - mmengine - INFO - Epoch(train) [5][1340/2119] lr: 2.0000e-02 eta: 1 day, 6:58:59 time: 0.3614 data_time: 0.0193 memory: 11108 grad_norm: 3.6346 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9730 loss: 2.9730 2022/10/09 06:50:31 - mmengine - INFO - Epoch(train) [5][1360/2119] lr: 2.0000e-02 eta: 1 day, 6:58:50 time: 0.3580 data_time: 0.0178 memory: 11108 grad_norm: 3.6537 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.2107 loss: 3.2107 2022/10/09 06:50:38 - mmengine - INFO - Epoch(train) [5][1380/2119] lr: 2.0000e-02 eta: 1 day, 6:58:47 time: 0.3687 data_time: 0.0239 memory: 11108 grad_norm: 3.6299 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8973 loss: 2.8973 2022/10/09 06:50:46 - mmengine - INFO - Epoch(train) [5][1400/2119] lr: 2.0000e-02 eta: 1 day, 6:58:36 time: 0.3561 data_time: 0.0210 memory: 11108 grad_norm: 3.6513 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0040 loss: 3.0040 2022/10/09 06:50:53 - mmengine - INFO - Epoch(train) [5][1420/2119] lr: 2.0000e-02 eta: 1 day, 6:58:24 time: 0.3558 data_time: 0.0213 memory: 11108 grad_norm: 3.6283 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8671 loss: 2.8671 2022/10/09 06:51:00 - mmengine - INFO - Epoch(train) [5][1440/2119] lr: 2.0000e-02 eta: 1 day, 6:58:20 time: 0.3673 data_time: 0.0199 memory: 11108 grad_norm: 3.6108 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0095 loss: 3.0095 2022/10/09 06:51:07 - mmengine - INFO - Epoch(train) [5][1460/2119] lr: 2.0000e-02 eta: 1 day, 6:58:08 time: 0.3541 data_time: 0.0194 memory: 11108 grad_norm: 3.7149 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7799 loss: 2.7799 2022/10/09 06:51:14 - mmengine - INFO - Epoch(train) [5][1480/2119] lr: 2.0000e-02 eta: 1 day, 6:57:56 time: 0.3541 data_time: 0.0217 memory: 11108 grad_norm: 3.5629 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9922 loss: 2.9922 2022/10/09 06:51:21 - mmengine - INFO - Epoch(train) [5][1500/2119] lr: 2.0000e-02 eta: 1 day, 6:57:48 time: 0.3607 data_time: 0.0241 memory: 11108 grad_norm: 3.6115 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8626 loss: 2.8626 2022/10/09 06:51:29 - mmengine - INFO - Epoch(train) [5][1520/2119] lr: 2.0000e-02 eta: 1 day, 6:57:37 time: 0.3560 data_time: 0.0225 memory: 11108 grad_norm: 3.6347 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 2.8886 loss: 2.8886 2022/10/09 06:51:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 06:51:36 - mmengine - INFO - Epoch(train) [5][1540/2119] lr: 2.0000e-02 eta: 1 day, 6:57:25 time: 0.3546 data_time: 0.0238 memory: 11108 grad_norm: 3.5650 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 3.0035 loss: 3.0035 2022/10/09 06:51:43 - mmengine - INFO - Epoch(train) [5][1560/2119] lr: 2.0000e-02 eta: 1 day, 6:57:22 time: 0.3691 data_time: 0.0225 memory: 11108 grad_norm: 3.6061 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8308 loss: 2.8308 2022/10/09 06:51:50 - mmengine - INFO - Epoch(train) [5][1580/2119] lr: 2.0000e-02 eta: 1 day, 6:57:11 time: 0.3558 data_time: 0.0209 memory: 11108 grad_norm: 3.7125 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8892 loss: 2.8892 2022/10/09 06:51:57 - mmengine - INFO - Epoch(train) [5][1600/2119] lr: 2.0000e-02 eta: 1 day, 6:57:04 time: 0.3617 data_time: 0.0242 memory: 11108 grad_norm: 3.6432 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 3.1247 loss: 3.1247 2022/10/09 06:52:04 - mmengine - INFO - Epoch(train) [5][1620/2119] lr: 2.0000e-02 eta: 1 day, 6:56:53 time: 0.3556 data_time: 0.0196 memory: 11108 grad_norm: 3.5296 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9639 loss: 2.9639 2022/10/09 06:52:12 - mmengine - INFO - Epoch(train) [5][1640/2119] lr: 2.0000e-02 eta: 1 day, 6:56:41 time: 0.3552 data_time: 0.0196 memory: 11108 grad_norm: 3.6376 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8435 loss: 2.8435 2022/10/09 06:52:19 - mmengine - INFO - Epoch(train) [5][1660/2119] lr: 2.0000e-02 eta: 1 day, 6:56:32 time: 0.3584 data_time: 0.0255 memory: 11108 grad_norm: 3.6647 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0438 loss: 3.0438 2022/10/09 06:52:26 - mmengine - INFO - Epoch(train) [5][1680/2119] lr: 2.0000e-02 eta: 1 day, 6:56:20 time: 0.3551 data_time: 0.0224 memory: 11108 grad_norm: 3.5598 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8318 loss: 2.8318 2022/10/09 06:52:33 - mmengine - INFO - Epoch(train) [5][1700/2119] lr: 2.0000e-02 eta: 1 day, 6:56:08 time: 0.3538 data_time: 0.0180 memory: 11108 grad_norm: 3.5799 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9139 loss: 2.9139 2022/10/09 06:52:40 - mmengine - INFO - Epoch(train) [5][1720/2119] lr: 2.0000e-02 eta: 1 day, 6:56:00 time: 0.3607 data_time: 0.0196 memory: 11108 grad_norm: 3.5736 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.0859 loss: 3.0859 2022/10/09 06:52:47 - mmengine - INFO - Epoch(train) [5][1740/2119] lr: 2.0000e-02 eta: 1 day, 6:55:48 time: 0.3545 data_time: 0.0186 memory: 11108 grad_norm: 3.5990 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8795 loss: 2.8795 2022/10/09 06:52:54 - mmengine - INFO - Epoch(train) [5][1760/2119] lr: 2.0000e-02 eta: 1 day, 6:55:36 time: 0.3525 data_time: 0.0196 memory: 11108 grad_norm: 3.6456 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7317 loss: 2.7317 2022/10/09 06:53:02 - mmengine - INFO - Epoch(train) [5][1780/2119] lr: 2.0000e-02 eta: 1 day, 6:55:31 time: 0.3668 data_time: 0.0227 memory: 11108 grad_norm: 3.6242 top1_acc: 0.0625 top5_acc: 0.5000 loss_cls: 3.0743 loss: 3.0743 2022/10/09 06:53:09 - mmengine - INFO - Epoch(train) [5][1800/2119] lr: 2.0000e-02 eta: 1 day, 6:55:20 time: 0.3559 data_time: 0.0227 memory: 11108 grad_norm: 3.5860 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8261 loss: 2.8261 2022/10/09 06:53:16 - mmengine - INFO - Epoch(train) [5][1820/2119] lr: 2.0000e-02 eta: 1 day, 6:55:19 time: 0.3722 data_time: 0.0202 memory: 11108 grad_norm: 3.5950 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7192 loss: 2.7192 2022/10/09 06:53:23 - mmengine - INFO - Epoch(train) [5][1840/2119] lr: 2.0000e-02 eta: 1 day, 6:55:12 time: 0.3628 data_time: 0.0226 memory: 11108 grad_norm: 3.6003 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.0380 loss: 3.0380 2022/10/09 06:53:31 - mmengine - INFO - Epoch(train) [5][1860/2119] lr: 2.0000e-02 eta: 1 day, 6:55:00 time: 0.3531 data_time: 0.0188 memory: 11108 grad_norm: 3.6280 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9239 loss: 2.9239 2022/10/09 06:53:38 - mmengine - INFO - Epoch(train) [5][1880/2119] lr: 2.0000e-02 eta: 1 day, 6:54:53 time: 0.3631 data_time: 0.0198 memory: 11108 grad_norm: 3.5874 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.2037 loss: 3.2037 2022/10/09 06:53:45 - mmengine - INFO - Epoch(train) [5][1900/2119] lr: 2.0000e-02 eta: 1 day, 6:54:40 time: 0.3516 data_time: 0.0183 memory: 11108 grad_norm: 3.6283 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7609 loss: 2.7609 2022/10/09 06:53:52 - mmengine - INFO - Epoch(train) [5][1920/2119] lr: 2.0000e-02 eta: 1 day, 6:54:30 time: 0.3564 data_time: 0.0187 memory: 11108 grad_norm: 3.5901 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0744 loss: 3.0744 2022/10/09 06:53:59 - mmengine - INFO - Epoch(train) [5][1940/2119] lr: 2.0000e-02 eta: 1 day, 6:54:22 time: 0.3614 data_time: 0.0189 memory: 11108 grad_norm: 3.6696 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8636 loss: 2.8636 2022/10/09 06:54:06 - mmengine - INFO - Epoch(train) [5][1960/2119] lr: 2.0000e-02 eta: 1 day, 6:54:10 time: 0.3530 data_time: 0.0193 memory: 11108 grad_norm: 3.6937 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.2260 loss: 3.2260 2022/10/09 06:54:13 - mmengine - INFO - Epoch(train) [5][1980/2119] lr: 2.0000e-02 eta: 1 day, 6:53:59 time: 0.3556 data_time: 0.0208 memory: 11108 grad_norm: 3.6184 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7974 loss: 2.7974 2022/10/09 06:54:21 - mmengine - INFO - Epoch(train) [5][2000/2119] lr: 2.0000e-02 eta: 1 day, 6:53:49 time: 0.3587 data_time: 0.0224 memory: 11108 grad_norm: 3.5760 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8003 loss: 2.8003 2022/10/09 06:54:28 - mmengine - INFO - Epoch(train) [5][2020/2119] lr: 2.0000e-02 eta: 1 day, 6:53:37 time: 0.3526 data_time: 0.0186 memory: 11108 grad_norm: 3.6138 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9834 loss: 2.9834 2022/10/09 06:54:35 - mmengine - INFO - Epoch(train) [5][2040/2119] lr: 2.0000e-02 eta: 1 day, 6:53:29 time: 0.3615 data_time: 0.0200 memory: 11108 grad_norm: 3.5840 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0505 loss: 3.0505 2022/10/09 06:54:42 - mmengine - INFO - Epoch(train) [5][2060/2119] lr: 2.0000e-02 eta: 1 day, 6:53:19 time: 0.3564 data_time: 0.0221 memory: 11108 grad_norm: 3.6090 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0571 loss: 3.0571 2022/10/09 06:54:49 - mmengine - INFO - Epoch(train) [5][2080/2119] lr: 2.0000e-02 eta: 1 day, 6:53:14 time: 0.3651 data_time: 0.0274 memory: 11108 grad_norm: 3.6110 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8556 loss: 2.8556 2022/10/09 06:54:56 - mmengine - INFO - Epoch(train) [5][2100/2119] lr: 2.0000e-02 eta: 1 day, 6:53:05 time: 0.3587 data_time: 0.0199 memory: 11108 grad_norm: 3.5711 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6101 loss: 2.6101 2022/10/09 06:55:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 06:55:03 - mmengine - INFO - Epoch(train) [5][2119/2119] lr: 2.0000e-02 eta: 1 day, 6:53:05 time: 0.3399 data_time: 0.0181 memory: 11108 grad_norm: 3.6360 top1_acc: 0.5000 top5_acc: 0.8000 loss_cls: 2.9378 loss: 2.9378 2022/10/09 06:55:51 - mmengine - INFO - Epoch(val) [5][20/137] eta: 0:04:44 time: 2.4290 data_time: 2.2968 memory: 1961 2022/10/09 06:55:57 - mmengine - INFO - Epoch(val) [5][40/137] eta: 0:00:25 time: 0.2630 data_time: 0.1454 memory: 1961 2022/10/09 06:56:02 - mmengine - INFO - Epoch(val) [5][60/137] eta: 0:00:22 time: 0.2881 data_time: 0.1723 memory: 1961 2022/10/09 06:56:07 - mmengine - INFO - Epoch(val) [5][80/137] eta: 0:00:13 time: 0.2362 data_time: 0.1187 memory: 1961 2022/10/09 06:56:13 - mmengine - INFO - Epoch(val) [5][100/137] eta: 0:00:10 time: 0.2838 data_time: 0.1706 memory: 1961 2022/10/09 06:56:18 - mmengine - INFO - Epoch(val) [5][120/137] eta: 0:00:04 time: 0.2775 data_time: 0.1622 memory: 1961 2022/10/09 06:56:33 - mmengine - INFO - Epoch(val) [5][137/137] acc/top1: 0.4012 acc/top5: 0.6492 acc/mean1: 0.4011 2022/10/09 06:56:35 - mmengine - INFO - The best checkpoint with 0.4012 acc/top1 at 5 epoch is saved to best_acc/top1_epoch_5.pth. 2022/10/09 06:56:44 - mmengine - INFO - Epoch(train) [6][20/2119] lr: 2.4000e-02 eta: 1 day, 6:50:27 time: 0.4579 data_time: 0.1052 memory: 11108 grad_norm: 3.6554 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7476 loss: 2.7476 2022/10/09 06:56:51 - mmengine - INFO - Epoch(train) [6][40/2119] lr: 2.4000e-02 eta: 1 day, 6:50:17 time: 0.3566 data_time: 0.0198 memory: 11108 grad_norm: 3.6204 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8444 loss: 2.8444 2022/10/09 06:56:58 - mmengine - INFO - Epoch(train) [6][60/2119] lr: 2.4000e-02 eta: 1 day, 6:50:05 time: 0.3526 data_time: 0.0179 memory: 11108 grad_norm: 3.5500 top1_acc: 0.3125 top5_acc: 0.8750 loss_cls: 3.0393 loss: 3.0393 2022/10/09 06:57:05 - mmengine - INFO - Epoch(train) [6][80/2119] lr: 2.4000e-02 eta: 1 day, 6:49:54 time: 0.3557 data_time: 0.0202 memory: 11108 grad_norm: 3.5615 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9114 loss: 2.9114 2022/10/09 06:57:12 - mmengine - INFO - Epoch(train) [6][100/2119] lr: 2.4000e-02 eta: 1 day, 6:49:45 time: 0.3581 data_time: 0.0169 memory: 11108 grad_norm: 3.5764 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.9075 loss: 2.9075 2022/10/09 06:57:19 - mmengine - INFO - Epoch(train) [6][120/2119] lr: 2.4000e-02 eta: 1 day, 6:49:34 time: 0.3549 data_time: 0.0218 memory: 11108 grad_norm: 3.6162 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7744 loss: 2.7744 2022/10/09 06:57:27 - mmengine - INFO - Epoch(train) [6][140/2119] lr: 2.4000e-02 eta: 1 day, 6:49:25 time: 0.3582 data_time: 0.0206 memory: 11108 grad_norm: 3.5628 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9306 loss: 2.9306 2022/10/09 06:57:34 - mmengine - INFO - Epoch(train) [6][160/2119] lr: 2.4000e-02 eta: 1 day, 6:49:17 time: 0.3590 data_time: 0.0225 memory: 11108 grad_norm: 3.5590 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9758 loss: 2.9758 2022/10/09 06:57:41 - mmengine - INFO - Epoch(train) [6][180/2119] lr: 2.4000e-02 eta: 1 day, 6:49:07 time: 0.3577 data_time: 0.0223 memory: 11108 grad_norm: 3.5460 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9885 loss: 2.9885 2022/10/09 06:57:48 - mmengine - INFO - Epoch(train) [6][200/2119] lr: 2.4000e-02 eta: 1 day, 6:48:59 time: 0.3599 data_time: 0.0233 memory: 11108 grad_norm: 3.5990 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.8660 loss: 2.8660 2022/10/09 06:57:55 - mmengine - INFO - Epoch(train) [6][220/2119] lr: 2.4000e-02 eta: 1 day, 6:48:51 time: 0.3586 data_time: 0.0249 memory: 11108 grad_norm: 3.5560 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7837 loss: 2.7837 2022/10/09 06:58:02 - mmengine - INFO - Epoch(train) [6][240/2119] lr: 2.4000e-02 eta: 1 day, 6:48:40 time: 0.3553 data_time: 0.0197 memory: 11108 grad_norm: 3.5683 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8266 loss: 2.8266 2022/10/09 06:58:10 - mmengine - INFO - Epoch(train) [6][260/2119] lr: 2.4000e-02 eta: 1 day, 6:48:32 time: 0.3601 data_time: 0.0225 memory: 11108 grad_norm: 3.5964 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8433 loss: 2.8433 2022/10/09 06:58:17 - mmengine - INFO - Epoch(train) [6][280/2119] lr: 2.4000e-02 eta: 1 day, 6:48:22 time: 0.3557 data_time: 0.0197 memory: 11108 grad_norm: 3.5362 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7695 loss: 2.7695 2022/10/09 06:58:24 - mmengine - INFO - Epoch(train) [6][300/2119] lr: 2.4000e-02 eta: 1 day, 6:48:12 time: 0.3564 data_time: 0.0194 memory: 11108 grad_norm: 3.6310 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8979 loss: 2.8979 2022/10/09 06:58:31 - mmengine - INFO - Epoch(train) [6][320/2119] lr: 2.4000e-02 eta: 1 day, 6:48:02 time: 0.3560 data_time: 0.0188 memory: 11108 grad_norm: 3.5319 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.0748 loss: 3.0748 2022/10/09 06:58:38 - mmengine - INFO - Epoch(train) [6][340/2119] lr: 2.4000e-02 eta: 1 day, 6:47:50 time: 0.3541 data_time: 0.0178 memory: 11108 grad_norm: 3.5418 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.9530 loss: 2.9530 2022/10/09 06:58:45 - mmengine - INFO - Epoch(train) [6][360/2119] lr: 2.4000e-02 eta: 1 day, 6:47:39 time: 0.3544 data_time: 0.0193 memory: 11108 grad_norm: 3.5477 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.1257 loss: 3.1257 2022/10/09 06:58:52 - mmengine - INFO - Epoch(train) [6][380/2119] lr: 2.4000e-02 eta: 1 day, 6:47:30 time: 0.3571 data_time: 0.0202 memory: 11108 grad_norm: 3.5241 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9635 loss: 2.9635 2022/10/09 06:58:59 - mmengine - INFO - Epoch(train) [6][400/2119] lr: 2.4000e-02 eta: 1 day, 6:47:19 time: 0.3555 data_time: 0.0224 memory: 11108 grad_norm: 3.5740 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8315 loss: 2.8315 2022/10/09 06:59:01 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 06:59:06 - mmengine - INFO - Epoch(train) [6][420/2119] lr: 2.4000e-02 eta: 1 day, 6:47:10 time: 0.3568 data_time: 0.0254 memory: 11108 grad_norm: 3.5793 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0114 loss: 3.0114 2022/10/09 06:59:14 - mmengine - INFO - Epoch(train) [6][440/2119] lr: 2.4000e-02 eta: 1 day, 6:47:02 time: 0.3598 data_time: 0.0186 memory: 11108 grad_norm: 3.5135 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7291 loss: 2.7291 2022/10/09 06:59:21 - mmengine - INFO - Epoch(train) [6][460/2119] lr: 2.4000e-02 eta: 1 day, 6:46:53 time: 0.3584 data_time: 0.0208 memory: 11108 grad_norm: 3.6100 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9542 loss: 2.9542 2022/10/09 06:59:28 - mmengine - INFO - Epoch(train) [6][480/2119] lr: 2.4000e-02 eta: 1 day, 6:46:43 time: 0.3564 data_time: 0.0224 memory: 11108 grad_norm: 3.5248 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0384 loss: 3.0384 2022/10/09 06:59:35 - mmengine - INFO - Epoch(train) [6][500/2119] lr: 2.4000e-02 eta: 1 day, 6:46:33 time: 0.3565 data_time: 0.0233 memory: 11108 grad_norm: 3.4967 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9759 loss: 2.9759 2022/10/09 06:59:42 - mmengine - INFO - Epoch(train) [6][520/2119] lr: 2.4000e-02 eta: 1 day, 6:46:25 time: 0.3601 data_time: 0.0201 memory: 11108 grad_norm: 3.5233 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8440 loss: 2.8440 2022/10/09 06:59:49 - mmengine - INFO - Epoch(train) [6][540/2119] lr: 2.4000e-02 eta: 1 day, 6:46:15 time: 0.3555 data_time: 0.0182 memory: 11108 grad_norm: 3.5488 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8437 loss: 2.8437 2022/10/09 06:59:57 - mmengine - INFO - Epoch(train) [6][560/2119] lr: 2.4000e-02 eta: 1 day, 6:46:05 time: 0.3558 data_time: 0.0198 memory: 11108 grad_norm: 3.5718 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.0805 loss: 3.0805 2022/10/09 07:00:04 - mmengine - INFO - Epoch(train) [6][580/2119] lr: 2.4000e-02 eta: 1 day, 6:45:55 time: 0.3565 data_time: 0.0197 memory: 11108 grad_norm: 3.5209 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7592 loss: 2.7592 2022/10/09 07:00:11 - mmengine - INFO - Epoch(train) [6][600/2119] lr: 2.4000e-02 eta: 1 day, 6:45:46 time: 0.3571 data_time: 0.0209 memory: 11108 grad_norm: 3.5042 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7863 loss: 2.7863 2022/10/09 07:00:18 - mmengine - INFO - Epoch(train) [6][620/2119] lr: 2.4000e-02 eta: 1 day, 6:45:36 time: 0.3574 data_time: 0.0238 memory: 11108 grad_norm: 3.5515 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8569 loss: 2.8569 2022/10/09 07:00:25 - mmengine - INFO - Epoch(train) [6][640/2119] lr: 2.4000e-02 eta: 1 day, 6:45:32 time: 0.3665 data_time: 0.0239 memory: 11108 grad_norm: 3.5041 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0885 loss: 3.0885 2022/10/09 07:00:32 - mmengine - INFO - Epoch(train) [6][660/2119] lr: 2.4000e-02 eta: 1 day, 6:45:23 time: 0.3582 data_time: 0.0210 memory: 11108 grad_norm: 3.5063 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9775 loss: 2.9775 2022/10/09 07:00:40 - mmengine - INFO - Epoch(train) [6][680/2119] lr: 2.4000e-02 eta: 1 day, 6:45:14 time: 0.3565 data_time: 0.0183 memory: 11108 grad_norm: 3.4838 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8362 loss: 2.8362 2022/10/09 07:00:47 - mmengine - INFO - Epoch(train) [6][700/2119] lr: 2.4000e-02 eta: 1 day, 6:45:07 time: 0.3625 data_time: 0.0225 memory: 11108 grad_norm: 3.5658 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9305 loss: 2.9305 2022/10/09 07:00:54 - mmengine - INFO - Epoch(train) [6][720/2119] lr: 2.4000e-02 eta: 1 day, 6:44:58 time: 0.3582 data_time: 0.0194 memory: 11108 grad_norm: 3.4573 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9270 loss: 2.9270 2022/10/09 07:01:01 - mmengine - INFO - Epoch(train) [6][740/2119] lr: 2.4000e-02 eta: 1 day, 6:44:48 time: 0.3560 data_time: 0.0225 memory: 11108 grad_norm: 3.5202 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8462 loss: 2.8462 2022/10/09 07:01:08 - mmengine - INFO - Epoch(train) [6][760/2119] lr: 2.4000e-02 eta: 1 day, 6:44:38 time: 0.3554 data_time: 0.0193 memory: 11108 grad_norm: 3.4682 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7503 loss: 2.7503 2022/10/09 07:01:15 - mmengine - INFO - Epoch(train) [6][780/2119] lr: 2.4000e-02 eta: 1 day, 6:44:32 time: 0.3629 data_time: 0.0256 memory: 11108 grad_norm: 3.5053 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8812 loss: 2.8812 2022/10/09 07:01:23 - mmengine - INFO - Epoch(train) [6][800/2119] lr: 2.4000e-02 eta: 1 day, 6:44:24 time: 0.3600 data_time: 0.0227 memory: 11108 grad_norm: 3.5301 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7149 loss: 2.7149 2022/10/09 07:01:30 - mmengine - INFO - Epoch(train) [6][820/2119] lr: 2.4000e-02 eta: 1 day, 6:44:15 time: 0.3578 data_time: 0.0206 memory: 11108 grad_norm: 3.5867 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 3.0090 loss: 3.0090 2022/10/09 07:01:37 - mmengine - INFO - Epoch(train) [6][840/2119] lr: 2.4000e-02 eta: 1 day, 6:44:04 time: 0.3533 data_time: 0.0218 memory: 11108 grad_norm: 3.4649 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8375 loss: 2.8375 2022/10/09 07:01:44 - mmengine - INFO - Epoch(train) [6][860/2119] lr: 2.4000e-02 eta: 1 day, 6:43:56 time: 0.3611 data_time: 0.0179 memory: 11108 grad_norm: 3.5315 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8636 loss: 2.8636 2022/10/09 07:01:51 - mmengine - INFO - Epoch(train) [6][880/2119] lr: 2.4000e-02 eta: 1 day, 6:43:48 time: 0.3593 data_time: 0.0198 memory: 11108 grad_norm: 3.5058 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.1064 loss: 3.1064 2022/10/09 07:01:59 - mmengine - INFO - Epoch(train) [6][900/2119] lr: 2.4000e-02 eta: 1 day, 6:43:40 time: 0.3593 data_time: 0.0191 memory: 11108 grad_norm: 3.4656 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1409 loss: 3.1409 2022/10/09 07:02:06 - mmengine - INFO - Epoch(train) [6][920/2119] lr: 2.4000e-02 eta: 1 day, 6:43:31 time: 0.3575 data_time: 0.0211 memory: 11108 grad_norm: 3.5252 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8894 loss: 2.8894 2022/10/09 07:02:13 - mmengine - INFO - Epoch(train) [6][940/2119] lr: 2.4000e-02 eta: 1 day, 6:43:21 time: 0.3556 data_time: 0.0156 memory: 11108 grad_norm: 3.5514 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7603 loss: 2.7603 2022/10/09 07:02:20 - mmengine - INFO - Epoch(train) [6][960/2119] lr: 2.4000e-02 eta: 1 day, 6:43:13 time: 0.3594 data_time: 0.0212 memory: 11108 grad_norm: 3.5789 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9342 loss: 2.9342 2022/10/09 07:02:27 - mmengine - INFO - Epoch(train) [6][980/2119] lr: 2.4000e-02 eta: 1 day, 6:43:03 time: 0.3574 data_time: 0.0206 memory: 11108 grad_norm: 3.5297 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.9374 loss: 2.9374 2022/10/09 07:02:34 - mmengine - INFO - Epoch(train) [6][1000/2119] lr: 2.4000e-02 eta: 1 day, 6:42:55 time: 0.3584 data_time: 0.0245 memory: 11108 grad_norm: 3.4832 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7802 loss: 2.7802 2022/10/09 07:02:41 - mmengine - INFO - Epoch(train) [6][1020/2119] lr: 2.4000e-02 eta: 1 day, 6:42:47 time: 0.3599 data_time: 0.0210 memory: 11108 grad_norm: 3.4568 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.9098 loss: 2.9098 2022/10/09 07:02:49 - mmengine - INFO - Epoch(train) [6][1040/2119] lr: 2.4000e-02 eta: 1 day, 6:42:36 time: 0.3544 data_time: 0.0219 memory: 11108 grad_norm: 3.5042 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8342 loss: 2.8342 2022/10/09 07:02:56 - mmengine - INFO - Epoch(train) [6][1060/2119] lr: 2.4000e-02 eta: 1 day, 6:42:26 time: 0.3561 data_time: 0.0221 memory: 11108 grad_norm: 3.5152 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8531 loss: 2.8531 2022/10/09 07:03:03 - mmengine - INFO - Epoch(train) [6][1080/2119] lr: 2.4000e-02 eta: 1 day, 6:42:16 time: 0.3551 data_time: 0.0225 memory: 11108 grad_norm: 3.4565 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8768 loss: 2.8768 2022/10/09 07:03:10 - mmengine - INFO - Epoch(train) [6][1100/2119] lr: 2.4000e-02 eta: 1 day, 6:42:08 time: 0.3592 data_time: 0.0246 memory: 11108 grad_norm: 3.4729 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9038 loss: 2.9038 2022/10/09 07:03:17 - mmengine - INFO - Epoch(train) [6][1120/2119] lr: 2.4000e-02 eta: 1 day, 6:41:57 time: 0.3537 data_time: 0.0232 memory: 11108 grad_norm: 3.4927 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8619 loss: 2.8619 2022/10/09 07:03:24 - mmengine - INFO - Epoch(train) [6][1140/2119] lr: 2.4000e-02 eta: 1 day, 6:41:51 time: 0.3635 data_time: 0.0198 memory: 11108 grad_norm: 3.4773 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9954 loss: 2.9954 2022/10/09 07:03:31 - mmengine - INFO - Epoch(train) [6][1160/2119] lr: 2.4000e-02 eta: 1 day, 6:41:41 time: 0.3554 data_time: 0.0226 memory: 11108 grad_norm: 3.4582 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9706 loss: 2.9706 2022/10/09 07:03:39 - mmengine - INFO - Epoch(train) [6][1180/2119] lr: 2.4000e-02 eta: 1 day, 6:41:34 time: 0.3627 data_time: 0.0197 memory: 11108 grad_norm: 3.5159 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9668 loss: 2.9668 2022/10/09 07:03:46 - mmengine - INFO - Epoch(train) [6][1200/2119] lr: 2.4000e-02 eta: 1 day, 6:41:24 time: 0.3552 data_time: 0.0199 memory: 11108 grad_norm: 3.4688 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0862 loss: 3.0862 2022/10/09 07:03:53 - mmengine - INFO - Epoch(train) [6][1220/2119] lr: 2.4000e-02 eta: 1 day, 6:41:15 time: 0.3571 data_time: 0.0210 memory: 11108 grad_norm: 3.4979 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9652 loss: 2.9652 2022/10/09 07:04:00 - mmengine - INFO - Epoch(train) [6][1240/2119] lr: 2.4000e-02 eta: 1 day, 6:41:12 time: 0.3688 data_time: 0.0230 memory: 11108 grad_norm: 3.4710 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9415 loss: 2.9415 2022/10/09 07:04:07 - mmengine - INFO - Epoch(train) [6][1260/2119] lr: 2.4000e-02 eta: 1 day, 6:41:01 time: 0.3549 data_time: 0.0209 memory: 11108 grad_norm: 3.4526 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.9213 loss: 2.9213 2022/10/09 07:04:14 - mmengine - INFO - Epoch(train) [6][1280/2119] lr: 2.4000e-02 eta: 1 day, 6:40:51 time: 0.3539 data_time: 0.0209 memory: 11108 grad_norm: 3.4526 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8072 loss: 2.8072 2022/10/09 07:04:22 - mmengine - INFO - Epoch(train) [6][1300/2119] lr: 2.4000e-02 eta: 1 day, 6:40:46 time: 0.3659 data_time: 0.0221 memory: 11108 grad_norm: 3.4770 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8019 loss: 2.8019 2022/10/09 07:04:29 - mmengine - INFO - Epoch(train) [6][1320/2119] lr: 2.4000e-02 eta: 1 day, 6:40:41 time: 0.3647 data_time: 0.0188 memory: 11108 grad_norm: 3.4650 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8297 loss: 2.8297 2022/10/09 07:04:36 - mmengine - INFO - Epoch(train) [6][1340/2119] lr: 2.4000e-02 eta: 1 day, 6:40:30 time: 0.3543 data_time: 0.0237 memory: 11108 grad_norm: 3.4481 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8817 loss: 2.8817 2022/10/09 07:04:44 - mmengine - INFO - Epoch(train) [6][1360/2119] lr: 2.4000e-02 eta: 1 day, 6:40:30 time: 0.3749 data_time: 0.0210 memory: 11108 grad_norm: 3.5045 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 2.8068 loss: 2.8068 2022/10/09 07:04:51 - mmengine - INFO - Epoch(train) [6][1380/2119] lr: 2.4000e-02 eta: 1 day, 6:40:25 time: 0.3651 data_time: 0.0247 memory: 11108 grad_norm: 3.5021 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7758 loss: 2.7758 2022/10/09 07:04:58 - mmengine - INFO - Epoch(train) [6][1400/2119] lr: 2.4000e-02 eta: 1 day, 6:40:13 time: 0.3514 data_time: 0.0182 memory: 11108 grad_norm: 3.4735 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.9462 loss: 2.9462 2022/10/09 07:05:00 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 07:05:05 - mmengine - INFO - Epoch(train) [6][1420/2119] lr: 2.4000e-02 eta: 1 day, 6:40:06 time: 0.3616 data_time: 0.0191 memory: 11108 grad_norm: 3.4581 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8068 loss: 2.8068 2022/10/09 07:05:12 - mmengine - INFO - Epoch(train) [6][1440/2119] lr: 2.4000e-02 eta: 1 day, 6:39:56 time: 0.3561 data_time: 0.0232 memory: 11108 grad_norm: 3.5092 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.0078 loss: 3.0078 2022/10/09 07:05:20 - mmengine - INFO - Epoch(train) [6][1460/2119] lr: 2.4000e-02 eta: 1 day, 6:39:51 time: 0.3659 data_time: 0.0210 memory: 11108 grad_norm: 3.4950 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8960 loss: 2.8960 2022/10/09 07:05:27 - mmengine - INFO - Epoch(train) [6][1480/2119] lr: 2.4000e-02 eta: 1 day, 6:39:44 time: 0.3606 data_time: 0.0208 memory: 11108 grad_norm: 3.4576 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8773 loss: 2.8773 2022/10/09 07:05:34 - mmengine - INFO - Epoch(train) [6][1500/2119] lr: 2.4000e-02 eta: 1 day, 6:39:35 time: 0.3578 data_time: 0.0211 memory: 11108 grad_norm: 3.4891 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.0737 loss: 3.0737 2022/10/09 07:05:41 - mmengine - INFO - Epoch(train) [6][1520/2119] lr: 2.4000e-02 eta: 1 day, 6:39:30 time: 0.3653 data_time: 0.0216 memory: 11108 grad_norm: 3.4976 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8278 loss: 2.8278 2022/10/09 07:05:49 - mmengine - INFO - Epoch(train) [6][1540/2119] lr: 2.4000e-02 eta: 1 day, 6:39:21 time: 0.3568 data_time: 0.0150 memory: 11108 grad_norm: 3.4649 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8767 loss: 2.8767 2022/10/09 07:05:56 - mmengine - INFO - Epoch(train) [6][1560/2119] lr: 2.4000e-02 eta: 1 day, 6:39:10 time: 0.3550 data_time: 0.0240 memory: 11108 grad_norm: 3.4660 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9207 loss: 2.9207 2022/10/09 07:06:03 - mmengine - INFO - Epoch(train) [6][1580/2119] lr: 2.4000e-02 eta: 1 day, 6:39:01 time: 0.3572 data_time: 0.0166 memory: 11108 grad_norm: 3.5183 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7467 loss: 2.7467 2022/10/09 07:06:10 - mmengine - INFO - Epoch(train) [6][1600/2119] lr: 2.4000e-02 eta: 1 day, 6:38:56 time: 0.3659 data_time: 0.0216 memory: 11108 grad_norm: 3.4222 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8056 loss: 2.8056 2022/10/09 07:06:17 - mmengine - INFO - Epoch(train) [6][1620/2119] lr: 2.4000e-02 eta: 1 day, 6:38:50 time: 0.3635 data_time: 0.0224 memory: 11108 grad_norm: 3.4447 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8817 loss: 2.8817 2022/10/09 07:06:24 - mmengine - INFO - Epoch(train) [6][1640/2119] lr: 2.4000e-02 eta: 1 day, 6:38:40 time: 0.3550 data_time: 0.0204 memory: 11108 grad_norm: 3.4460 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 3.0897 loss: 3.0897 2022/10/09 07:06:32 - mmengine - INFO - Epoch(train) [6][1660/2119] lr: 2.4000e-02 eta: 1 day, 6:38:31 time: 0.3566 data_time: 0.0201 memory: 11108 grad_norm: 3.4604 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7962 loss: 2.7962 2022/10/09 07:06:39 - mmengine - INFO - Epoch(train) [6][1680/2119] lr: 2.4000e-02 eta: 1 day, 6:38:21 time: 0.3561 data_time: 0.0239 memory: 11108 grad_norm: 3.4238 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.9292 loss: 2.9292 2022/10/09 07:06:46 - mmengine - INFO - Epoch(train) [6][1700/2119] lr: 2.4000e-02 eta: 1 day, 6:38:10 time: 0.3537 data_time: 0.0186 memory: 11108 grad_norm: 3.4836 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.0373 loss: 3.0373 2022/10/09 07:06:53 - mmengine - INFO - Epoch(train) [6][1720/2119] lr: 2.4000e-02 eta: 1 day, 6:38:05 time: 0.3655 data_time: 0.0277 memory: 11108 grad_norm: 3.4426 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8559 loss: 2.8559 2022/10/09 07:07:00 - mmengine - INFO - Epoch(train) [6][1740/2119] lr: 2.4000e-02 eta: 1 day, 6:37:56 time: 0.3566 data_time: 0.0218 memory: 11108 grad_norm: 3.4478 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5983 loss: 2.5983 2022/10/09 07:07:07 - mmengine - INFO - Epoch(train) [6][1760/2119] lr: 2.4000e-02 eta: 1 day, 6:37:46 time: 0.3555 data_time: 0.0217 memory: 11108 grad_norm: 3.4894 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7519 loss: 2.7519 2022/10/09 07:07:15 - mmengine - INFO - Epoch(train) [6][1780/2119] lr: 2.4000e-02 eta: 1 day, 6:37:38 time: 0.3599 data_time: 0.0231 memory: 11108 grad_norm: 3.4366 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9641 loss: 2.9641 2022/10/09 07:07:22 - mmengine - INFO - Epoch(train) [6][1800/2119] lr: 2.4000e-02 eta: 1 day, 6:37:29 time: 0.3554 data_time: 0.0178 memory: 11108 grad_norm: 3.4120 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8499 loss: 2.8499 2022/10/09 07:07:29 - mmengine - INFO - Epoch(train) [6][1820/2119] lr: 2.4000e-02 eta: 1 day, 6:37:21 time: 0.3593 data_time: 0.0190 memory: 11108 grad_norm: 3.4439 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9512 loss: 2.9512 2022/10/09 07:07:36 - mmengine - INFO - Epoch(train) [6][1840/2119] lr: 2.4000e-02 eta: 1 day, 6:37:12 time: 0.3579 data_time: 0.0230 memory: 11108 grad_norm: 3.5545 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8920 loss: 2.8920 2022/10/09 07:07:43 - mmengine - INFO - Epoch(train) [6][1860/2119] lr: 2.4000e-02 eta: 1 day, 6:37:05 time: 0.3617 data_time: 0.0193 memory: 11108 grad_norm: 3.4590 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.2546 loss: 3.2546 2022/10/09 07:07:50 - mmengine - INFO - Epoch(train) [6][1880/2119] lr: 2.4000e-02 eta: 1 day, 6:36:58 time: 0.3608 data_time: 0.0208 memory: 11108 grad_norm: 3.5142 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9160 loss: 2.9160 2022/10/09 07:07:58 - mmengine - INFO - Epoch(train) [6][1900/2119] lr: 2.4000e-02 eta: 1 day, 6:36:49 time: 0.3571 data_time: 0.0207 memory: 11108 grad_norm: 3.5018 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8274 loss: 2.8274 2022/10/09 07:08:05 - mmengine - INFO - Epoch(train) [6][1920/2119] lr: 2.4000e-02 eta: 1 day, 6:36:40 time: 0.3576 data_time: 0.0217 memory: 11108 grad_norm: 3.5121 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0114 loss: 3.0114 2022/10/09 07:08:12 - mmengine - INFO - Epoch(train) [6][1940/2119] lr: 2.4000e-02 eta: 1 day, 6:36:32 time: 0.3589 data_time: 0.0213 memory: 11108 grad_norm: 3.4362 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8387 loss: 2.8387 2022/10/09 07:08:19 - mmengine - INFO - Epoch(train) [6][1960/2119] lr: 2.4000e-02 eta: 1 day, 6:36:24 time: 0.3607 data_time: 0.0215 memory: 11108 grad_norm: 3.4323 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7280 loss: 2.7280 2022/10/09 07:08:26 - mmengine - INFO - Epoch(train) [6][1980/2119] lr: 2.4000e-02 eta: 1 day, 6:36:14 time: 0.3543 data_time: 0.0189 memory: 11108 grad_norm: 3.4830 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8546 loss: 2.8546 2022/10/09 07:08:33 - mmengine - INFO - Epoch(train) [6][2000/2119] lr: 2.4000e-02 eta: 1 day, 6:36:05 time: 0.3575 data_time: 0.0215 memory: 11108 grad_norm: 3.4484 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0559 loss: 3.0559 2022/10/09 07:08:41 - mmengine - INFO - Epoch(train) [6][2020/2119] lr: 2.4000e-02 eta: 1 day, 6:35:58 time: 0.3611 data_time: 0.0227 memory: 11108 grad_norm: 3.4672 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8528 loss: 2.8528 2022/10/09 07:08:48 - mmengine - INFO - Epoch(train) [6][2040/2119] lr: 2.4000e-02 eta: 1 day, 6:35:49 time: 0.3568 data_time: 0.0235 memory: 11108 grad_norm: 3.4326 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7727 loss: 2.7727 2022/10/09 07:08:55 - mmengine - INFO - Epoch(train) [6][2060/2119] lr: 2.4000e-02 eta: 1 day, 6:35:41 time: 0.3593 data_time: 0.0193 memory: 11108 grad_norm: 3.4283 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.9244 loss: 2.9244 2022/10/09 07:09:02 - mmengine - INFO - Epoch(train) [6][2080/2119] lr: 2.4000e-02 eta: 1 day, 6:35:32 time: 0.3578 data_time: 0.0223 memory: 11108 grad_norm: 3.3825 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.9256 loss: 2.9256 2022/10/09 07:09:09 - mmengine - INFO - Epoch(train) [6][2100/2119] lr: 2.4000e-02 eta: 1 day, 6:35:22 time: 0.3555 data_time: 0.0190 memory: 11108 grad_norm: 3.4441 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0128 loss: 3.0128 2022/10/09 07:09:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 07:09:16 - mmengine - INFO - Epoch(train) [6][2119/2119] lr: 2.4000e-02 eta: 1 day, 6:35:22 time: 0.3402 data_time: 0.0171 memory: 11108 grad_norm: 3.4870 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 3.0107 loss: 3.0107 2022/10/09 07:09:26 - mmengine - INFO - Epoch(train) [7][20/2119] lr: 2.8000e-02 eta: 1 day, 6:33:36 time: 0.5112 data_time: 0.1268 memory: 11108 grad_norm: 3.4309 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9604 loss: 2.9604 2022/10/09 07:09:33 - mmengine - INFO - Epoch(train) [7][40/2119] lr: 2.8000e-02 eta: 1 day, 6:33:34 time: 0.3727 data_time: 0.0182 memory: 11108 grad_norm: 3.4954 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9155 loss: 2.9155 2022/10/09 07:09:40 - mmengine - INFO - Epoch(train) [7][60/2119] lr: 2.8000e-02 eta: 1 day, 6:33:26 time: 0.3580 data_time: 0.0281 memory: 11108 grad_norm: 3.4212 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8894 loss: 2.8894 2022/10/09 07:09:48 - mmengine - INFO - Epoch(train) [7][80/2119] lr: 2.8000e-02 eta: 1 day, 6:33:17 time: 0.3560 data_time: 0.0220 memory: 11108 grad_norm: 3.4313 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8315 loss: 2.8315 2022/10/09 07:09:55 - mmengine - INFO - Epoch(train) [7][100/2119] lr: 2.8000e-02 eta: 1 day, 6:33:10 time: 0.3626 data_time: 0.0190 memory: 11108 grad_norm: 3.4617 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7463 loss: 2.7463 2022/10/09 07:10:02 - mmengine - INFO - Epoch(train) [7][120/2119] lr: 2.8000e-02 eta: 1 day, 6:33:05 time: 0.3635 data_time: 0.0272 memory: 11108 grad_norm: 3.4126 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6155 loss: 2.6155 2022/10/09 07:10:09 - mmengine - INFO - Epoch(train) [7][140/2119] lr: 2.8000e-02 eta: 1 day, 6:32:57 time: 0.3590 data_time: 0.0230 memory: 11108 grad_norm: 3.3994 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7746 loss: 2.7746 2022/10/09 07:10:16 - mmengine - INFO - Epoch(train) [7][160/2119] lr: 2.8000e-02 eta: 1 day, 6:32:46 time: 0.3532 data_time: 0.0189 memory: 11108 grad_norm: 3.4288 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9780 loss: 2.9780 2022/10/09 07:10:24 - mmengine - INFO - Epoch(train) [7][180/2119] lr: 2.8000e-02 eta: 1 day, 6:32:38 time: 0.3584 data_time: 0.0193 memory: 11108 grad_norm: 3.4052 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7735 loss: 2.7735 2022/10/09 07:10:31 - mmengine - INFO - Epoch(train) [7][200/2119] lr: 2.8000e-02 eta: 1 day, 6:32:31 time: 0.3606 data_time: 0.0186 memory: 11108 grad_norm: 3.3898 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1259 loss: 3.1259 2022/10/09 07:10:38 - mmengine - INFO - Epoch(train) [7][220/2119] lr: 2.8000e-02 eta: 1 day, 6:32:27 time: 0.3689 data_time: 0.0208 memory: 11108 grad_norm: 3.4332 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9461 loss: 2.9461 2022/10/09 07:10:45 - mmengine - INFO - Epoch(train) [7][240/2119] lr: 2.8000e-02 eta: 1 day, 6:32:18 time: 0.3552 data_time: 0.0187 memory: 11108 grad_norm: 3.4048 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.9668 loss: 2.9668 2022/10/09 07:10:52 - mmengine - INFO - Epoch(train) [7][260/2119] lr: 2.8000e-02 eta: 1 day, 6:32:08 time: 0.3560 data_time: 0.0195 memory: 11108 grad_norm: 3.3395 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8057 loss: 2.8057 2022/10/09 07:11:00 - mmengine - INFO - Epoch(train) [7][280/2119] lr: 2.8000e-02 eta: 1 day, 6:32:00 time: 0.3588 data_time: 0.0207 memory: 11108 grad_norm: 3.3489 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9905 loss: 2.9905 2022/10/09 07:11:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 07:11:07 - mmengine - INFO - Epoch(train) [7][300/2119] lr: 2.8000e-02 eta: 1 day, 6:31:49 time: 0.3526 data_time: 0.0172 memory: 11108 grad_norm: 3.4059 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6530 loss: 2.6530 2022/10/09 07:11:14 - mmengine - INFO - Epoch(train) [7][320/2119] lr: 2.8000e-02 eta: 1 day, 6:31:45 time: 0.3670 data_time: 0.0199 memory: 11108 grad_norm: 3.4215 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.1111 loss: 3.1111 2022/10/09 07:11:21 - mmengine - INFO - Epoch(train) [7][340/2119] lr: 2.8000e-02 eta: 1 day, 6:31:38 time: 0.3604 data_time: 0.0195 memory: 11108 grad_norm: 3.4078 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9190 loss: 2.9190 2022/10/09 07:11:28 - mmengine - INFO - Epoch(train) [7][360/2119] lr: 2.8000e-02 eta: 1 day, 6:31:30 time: 0.3594 data_time: 0.0220 memory: 11108 grad_norm: 3.3452 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0258 loss: 3.0258 2022/10/09 07:11:35 - mmengine - INFO - Epoch(train) [7][380/2119] lr: 2.8000e-02 eta: 1 day, 6:31:20 time: 0.3541 data_time: 0.0191 memory: 11108 grad_norm: 3.4368 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8386 loss: 2.8386 2022/10/09 07:11:43 - mmengine - INFO - Epoch(train) [7][400/2119] lr: 2.8000e-02 eta: 1 day, 6:31:11 time: 0.3573 data_time: 0.0249 memory: 11108 grad_norm: 3.3965 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8203 loss: 2.8203 2022/10/09 07:11:50 - mmengine - INFO - Epoch(train) [7][420/2119] lr: 2.8000e-02 eta: 1 day, 6:31:02 time: 0.3579 data_time: 0.0211 memory: 11108 grad_norm: 3.4107 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.7970 loss: 2.7970 2022/10/09 07:11:57 - mmengine - INFO - Epoch(train) [7][440/2119] lr: 2.8000e-02 eta: 1 day, 6:30:53 time: 0.3565 data_time: 0.0206 memory: 11108 grad_norm: 3.3554 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8884 loss: 2.8884 2022/10/09 07:12:04 - mmengine - INFO - Epoch(train) [7][460/2119] lr: 2.8000e-02 eta: 1 day, 6:30:48 time: 0.3637 data_time: 0.0163 memory: 11108 grad_norm: 3.4168 top1_acc: 0.2500 top5_acc: 0.8125 loss_cls: 2.7281 loss: 2.7281 2022/10/09 07:12:11 - mmengine - INFO - Epoch(train) [7][480/2119] lr: 2.8000e-02 eta: 1 day, 6:30:40 time: 0.3588 data_time: 0.0205 memory: 11108 grad_norm: 3.4277 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9350 loss: 2.9350 2022/10/09 07:12:19 - mmengine - INFO - Epoch(train) [7][500/2119] lr: 2.8000e-02 eta: 1 day, 6:30:38 time: 0.3732 data_time: 0.0204 memory: 11108 grad_norm: 3.3282 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6776 loss: 2.6776 2022/10/09 07:12:26 - mmengine - INFO - Epoch(train) [7][520/2119] lr: 2.8000e-02 eta: 1 day, 6:30:28 time: 0.3544 data_time: 0.0198 memory: 11108 grad_norm: 3.3962 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8227 loss: 2.8227 2022/10/09 07:12:33 - mmengine - INFO - Epoch(train) [7][540/2119] lr: 2.8000e-02 eta: 1 day, 6:30:20 time: 0.3593 data_time: 0.0193 memory: 11108 grad_norm: 3.3537 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9311 loss: 2.9311 2022/10/09 07:12:41 - mmengine - INFO - Epoch(train) [7][560/2119] lr: 2.8000e-02 eta: 1 day, 6:30:21 time: 0.3783 data_time: 0.0242 memory: 11108 grad_norm: 3.3662 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9336 loss: 2.9336 2022/10/09 07:12:48 - mmengine - INFO - Epoch(train) [7][580/2119] lr: 2.8000e-02 eta: 1 day, 6:30:11 time: 0.3541 data_time: 0.0181 memory: 11108 grad_norm: 3.4114 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8920 loss: 2.8920 2022/10/09 07:12:55 - mmengine - INFO - Epoch(train) [7][600/2119] lr: 2.8000e-02 eta: 1 day, 6:30:05 time: 0.3617 data_time: 0.0185 memory: 11108 grad_norm: 3.3685 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.1312 loss: 3.1312 2022/10/09 07:13:02 - mmengine - INFO - Epoch(train) [7][620/2119] lr: 2.8000e-02 eta: 1 day, 6:29:54 time: 0.3536 data_time: 0.0199 memory: 11108 grad_norm: 3.3761 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8084 loss: 2.8084 2022/10/09 07:13:09 - mmengine - INFO - Epoch(train) [7][640/2119] lr: 2.8000e-02 eta: 1 day, 6:29:50 time: 0.3677 data_time: 0.0239 memory: 11108 grad_norm: 3.3727 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0600 loss: 3.0600 2022/10/09 07:13:16 - mmengine - INFO - Epoch(train) [7][660/2119] lr: 2.8000e-02 eta: 1 day, 6:29:41 time: 0.3566 data_time: 0.0172 memory: 11108 grad_norm: 3.4204 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.8845 loss: 2.8845 2022/10/09 07:13:24 - mmengine - INFO - Epoch(train) [7][680/2119] lr: 2.8000e-02 eta: 1 day, 6:29:31 time: 0.3545 data_time: 0.0198 memory: 11108 grad_norm: 3.3475 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6933 loss: 2.6933 2022/10/09 07:13:31 - mmengine - INFO - Epoch(train) [7][700/2119] lr: 2.8000e-02 eta: 1 day, 6:29:24 time: 0.3597 data_time: 0.0189 memory: 11108 grad_norm: 3.3854 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0360 loss: 3.0360 2022/10/09 07:13:38 - mmengine - INFO - Epoch(train) [7][720/2119] lr: 2.8000e-02 eta: 1 day, 6:29:16 time: 0.3590 data_time: 0.0214 memory: 11108 grad_norm: 3.3385 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.1118 loss: 3.1118 2022/10/09 07:13:45 - mmengine - INFO - Epoch(train) [7][740/2119] lr: 2.8000e-02 eta: 1 day, 6:29:09 time: 0.3625 data_time: 0.0204 memory: 11108 grad_norm: 3.3449 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0175 loss: 3.0175 2022/10/09 07:13:52 - mmengine - INFO - Epoch(train) [7][760/2119] lr: 2.8000e-02 eta: 1 day, 6:29:00 time: 0.3561 data_time: 0.0198 memory: 11108 grad_norm: 3.2997 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8942 loss: 2.8942 2022/10/09 07:14:00 - mmengine - INFO - Epoch(train) [7][780/2119] lr: 2.8000e-02 eta: 1 day, 6:28:53 time: 0.3603 data_time: 0.0245 memory: 11108 grad_norm: 3.3023 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.0807 loss: 3.0807 2022/10/09 07:14:07 - mmengine - INFO - Epoch(train) [7][800/2119] lr: 2.8000e-02 eta: 1 day, 6:28:45 time: 0.3583 data_time: 0.0218 memory: 11108 grad_norm: 3.3722 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.0399 loss: 3.0399 2022/10/09 07:14:14 - mmengine - INFO - Epoch(train) [7][820/2119] lr: 2.8000e-02 eta: 1 day, 6:28:34 time: 0.3527 data_time: 0.0181 memory: 11108 grad_norm: 3.3749 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7702 loss: 2.7702 2022/10/09 07:14:21 - mmengine - INFO - Epoch(train) [7][840/2119] lr: 2.8000e-02 eta: 1 day, 6:28:26 time: 0.3596 data_time: 0.0228 memory: 11108 grad_norm: 3.3142 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0417 loss: 3.0417 2022/10/09 07:14:28 - mmengine - INFO - Epoch(train) [7][860/2119] lr: 2.8000e-02 eta: 1 day, 6:28:18 time: 0.3575 data_time: 0.0170 memory: 11108 grad_norm: 3.3555 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8114 loss: 2.8114 2022/10/09 07:14:35 - mmengine - INFO - Epoch(train) [7][880/2119] lr: 2.8000e-02 eta: 1 day, 6:28:09 time: 0.3569 data_time: 0.0210 memory: 11108 grad_norm: 3.3768 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9868 loss: 2.9868 2022/10/09 07:14:42 - mmengine - INFO - Epoch(train) [7][900/2119] lr: 2.8000e-02 eta: 1 day, 6:27:59 time: 0.3555 data_time: 0.0257 memory: 11108 grad_norm: 3.3174 top1_acc: 0.1875 top5_acc: 0.2500 loss_cls: 2.9279 loss: 2.9279 2022/10/09 07:14:50 - mmengine - INFO - Epoch(train) [7][920/2119] lr: 2.8000e-02 eta: 1 day, 6:27:52 time: 0.3598 data_time: 0.0208 memory: 11108 grad_norm: 3.3519 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8692 loss: 2.8692 2022/10/09 07:14:57 - mmengine - INFO - Epoch(train) [7][940/2119] lr: 2.8000e-02 eta: 1 day, 6:27:42 time: 0.3548 data_time: 0.0162 memory: 11108 grad_norm: 3.3617 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9819 loss: 2.9819 2022/10/09 07:15:04 - mmengine - INFO - Epoch(train) [7][960/2119] lr: 2.8000e-02 eta: 1 day, 6:27:36 time: 0.3641 data_time: 0.0239 memory: 11108 grad_norm: 3.3002 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.0149 loss: 3.0149 2022/10/09 07:15:11 - mmengine - INFO - Epoch(train) [7][980/2119] lr: 2.8000e-02 eta: 1 day, 6:27:28 time: 0.3587 data_time: 0.0175 memory: 11108 grad_norm: 3.3400 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.0463 loss: 3.0463 2022/10/09 07:15:18 - mmengine - INFO - Epoch(train) [7][1000/2119] lr: 2.8000e-02 eta: 1 day, 6:27:20 time: 0.3581 data_time: 0.0202 memory: 11108 grad_norm: 3.3534 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8354 loss: 2.8354 2022/10/09 07:15:25 - mmengine - INFO - Epoch(train) [7][1020/2119] lr: 2.8000e-02 eta: 1 day, 6:27:12 time: 0.3590 data_time: 0.0236 memory: 11108 grad_norm: 3.3883 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9410 loss: 2.9410 2022/10/09 07:15:33 - mmengine - INFO - Epoch(train) [7][1040/2119] lr: 2.8000e-02 eta: 1 day, 6:27:05 time: 0.3612 data_time: 0.0196 memory: 11108 grad_norm: 3.3629 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8450 loss: 2.8450 2022/10/09 07:15:40 - mmengine - INFO - Epoch(train) [7][1060/2119] lr: 2.8000e-02 eta: 1 day, 6:26:57 time: 0.3586 data_time: 0.0237 memory: 11108 grad_norm: 3.3635 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0191 loss: 3.0191 2022/10/09 07:15:47 - mmengine - INFO - Epoch(train) [7][1080/2119] lr: 2.8000e-02 eta: 1 day, 6:26:49 time: 0.3585 data_time: 0.0196 memory: 11108 grad_norm: 3.3120 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7177 loss: 2.7177 2022/10/09 07:15:54 - mmengine - INFO - Epoch(train) [7][1100/2119] lr: 2.8000e-02 eta: 1 day, 6:26:41 time: 0.3589 data_time: 0.0186 memory: 11108 grad_norm: 3.3309 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9212 loss: 2.9212 2022/10/09 07:16:01 - mmengine - INFO - Epoch(train) [7][1120/2119] lr: 2.8000e-02 eta: 1 day, 6:26:33 time: 0.3585 data_time: 0.0261 memory: 11108 grad_norm: 3.2979 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6920 loss: 2.6920 2022/10/09 07:16:08 - mmengine - INFO - Epoch(train) [7][1140/2119] lr: 2.8000e-02 eta: 1 day, 6:26:23 time: 0.3533 data_time: 0.0190 memory: 11108 grad_norm: 3.3265 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7849 loss: 2.7849 2022/10/09 07:16:16 - mmengine - INFO - Epoch(train) [7][1160/2119] lr: 2.8000e-02 eta: 1 day, 6:26:15 time: 0.3597 data_time: 0.0204 memory: 11108 grad_norm: 3.3071 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8092 loss: 2.8092 2022/10/09 07:16:23 - mmengine - INFO - Epoch(train) [7][1180/2119] lr: 2.8000e-02 eta: 1 day, 6:26:06 time: 0.3565 data_time: 0.0175 memory: 11108 grad_norm: 3.3174 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8598 loss: 2.8598 2022/10/09 07:16:30 - mmengine - INFO - Epoch(train) [7][1200/2119] lr: 2.8000e-02 eta: 1 day, 6:25:57 time: 0.3566 data_time: 0.0190 memory: 11108 grad_norm: 3.3343 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7279 loss: 2.7279 2022/10/09 07:16:37 - mmengine - INFO - Epoch(train) [7][1220/2119] lr: 2.8000e-02 eta: 1 day, 6:25:49 time: 0.3573 data_time: 0.0229 memory: 11108 grad_norm: 3.3701 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8167 loss: 2.8167 2022/10/09 07:16:44 - mmengine - INFO - Epoch(train) [7][1240/2119] lr: 2.8000e-02 eta: 1 day, 6:25:40 time: 0.3556 data_time: 0.0233 memory: 11108 grad_norm: 3.2899 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7066 loss: 2.7066 2022/10/09 07:16:51 - mmengine - INFO - Epoch(train) [7][1260/2119] lr: 2.8000e-02 eta: 1 day, 6:25:33 time: 0.3609 data_time: 0.0229 memory: 11108 grad_norm: 3.4022 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.1472 loss: 3.1472 2022/10/09 07:16:59 - mmengine - INFO - Epoch(train) [7][1280/2119] lr: 2.8000e-02 eta: 1 day, 6:25:24 time: 0.3576 data_time: 0.0205 memory: 11108 grad_norm: 3.3297 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0348 loss: 3.0348 2022/10/09 07:17:01 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 07:17:06 - mmengine - INFO - Epoch(train) [7][1300/2119] lr: 2.8000e-02 eta: 1 day, 6:25:19 time: 0.3642 data_time: 0.0222 memory: 11108 grad_norm: 3.3874 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0400 loss: 3.0400 2022/10/09 07:17:13 - mmengine - INFO - Epoch(train) [7][1320/2119] lr: 2.8000e-02 eta: 1 day, 6:25:11 time: 0.3595 data_time: 0.0233 memory: 11108 grad_norm: 3.2765 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8620 loss: 2.8620 2022/10/09 07:17:20 - mmengine - INFO - Epoch(train) [7][1340/2119] lr: 2.8000e-02 eta: 1 day, 6:25:04 time: 0.3603 data_time: 0.0214 memory: 11108 grad_norm: 3.2677 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7829 loss: 2.7829 2022/10/09 07:17:27 - mmengine - INFO - Epoch(train) [7][1360/2119] lr: 2.8000e-02 eta: 1 day, 6:24:54 time: 0.3548 data_time: 0.0260 memory: 11108 grad_norm: 3.3228 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9261 loss: 2.9261 2022/10/09 07:17:35 - mmengine - INFO - Epoch(train) [7][1380/2119] lr: 2.8000e-02 eta: 1 day, 6:24:48 time: 0.3636 data_time: 0.0204 memory: 11108 grad_norm: 3.3105 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9580 loss: 2.9580 2022/10/09 07:17:42 - mmengine - INFO - Epoch(train) [7][1400/2119] lr: 2.8000e-02 eta: 1 day, 6:24:42 time: 0.3640 data_time: 0.0215 memory: 11108 grad_norm: 3.2701 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8314 loss: 2.8314 2022/10/09 07:17:49 - mmengine - INFO - Epoch(train) [7][1420/2119] lr: 2.8000e-02 eta: 1 day, 6:24:32 time: 0.3541 data_time: 0.0213 memory: 11108 grad_norm: 3.3390 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7276 loss: 2.7276 2022/10/09 07:17:56 - mmengine - INFO - Epoch(train) [7][1440/2119] lr: 2.8000e-02 eta: 1 day, 6:24:25 time: 0.3587 data_time: 0.0181 memory: 11108 grad_norm: 3.3130 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9447 loss: 2.9447 2022/10/09 07:18:03 - mmengine - INFO - Epoch(train) [7][1460/2119] lr: 2.8000e-02 eta: 1 day, 6:24:18 time: 0.3622 data_time: 0.0252 memory: 11108 grad_norm: 3.3334 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7037 loss: 2.7037 2022/10/09 07:18:10 - mmengine - INFO - Epoch(train) [7][1480/2119] lr: 2.8000e-02 eta: 1 day, 6:24:09 time: 0.3563 data_time: 0.0209 memory: 11108 grad_norm: 3.3002 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7701 loss: 2.7701 2022/10/09 07:18:18 - mmengine - INFO - Epoch(train) [7][1500/2119] lr: 2.8000e-02 eta: 1 day, 6:23:59 time: 0.3543 data_time: 0.0220 memory: 11108 grad_norm: 3.3595 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8651 loss: 2.8651 2022/10/09 07:18:25 - mmengine - INFO - Epoch(train) [7][1520/2119] lr: 2.8000e-02 eta: 1 day, 6:23:51 time: 0.3581 data_time: 0.0208 memory: 11108 grad_norm: 3.2915 top1_acc: 0.0625 top5_acc: 0.3750 loss_cls: 2.9523 loss: 2.9523 2022/10/09 07:18:32 - mmengine - INFO - Epoch(train) [7][1540/2119] lr: 2.8000e-02 eta: 1 day, 6:23:43 time: 0.3584 data_time: 0.0237 memory: 11108 grad_norm: 3.3066 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8850 loss: 2.8850 2022/10/09 07:18:39 - mmengine - INFO - Epoch(train) [7][1560/2119] lr: 2.8000e-02 eta: 1 day, 6:23:35 time: 0.3585 data_time: 0.0205 memory: 11108 grad_norm: 3.2781 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7790 loss: 2.7790 2022/10/09 07:18:46 - mmengine - INFO - Epoch(train) [7][1580/2119] lr: 2.8000e-02 eta: 1 day, 6:23:26 time: 0.3564 data_time: 0.0188 memory: 11108 grad_norm: 3.3108 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0561 loss: 3.0561 2022/10/09 07:18:53 - mmengine - INFO - Epoch(train) [7][1600/2119] lr: 2.8000e-02 eta: 1 day, 6:23:18 time: 0.3587 data_time: 0.0222 memory: 11108 grad_norm: 3.3369 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9751 loss: 2.9751 2022/10/09 07:19:00 - mmengine - INFO - Epoch(train) [7][1620/2119] lr: 2.8000e-02 eta: 1 day, 6:23:08 time: 0.3549 data_time: 0.0229 memory: 11108 grad_norm: 3.2937 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5956 loss: 2.5956 2022/10/09 07:19:08 - mmengine - INFO - Epoch(train) [7][1640/2119] lr: 2.8000e-02 eta: 1 day, 6:23:00 time: 0.3564 data_time: 0.0194 memory: 11108 grad_norm: 3.3347 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7033 loss: 2.7033 2022/10/09 07:19:15 - mmengine - INFO - Epoch(train) [7][1660/2119] lr: 2.8000e-02 eta: 1 day, 6:22:51 time: 0.3562 data_time: 0.0179 memory: 11108 grad_norm: 3.2799 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8064 loss: 2.8064 2022/10/09 07:19:22 - mmengine - INFO - Epoch(train) [7][1680/2119] lr: 2.8000e-02 eta: 1 day, 6:22:43 time: 0.3597 data_time: 0.0215 memory: 11108 grad_norm: 3.2924 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0093 loss: 3.0093 2022/10/09 07:19:29 - mmengine - INFO - Epoch(train) [7][1700/2119] lr: 2.8000e-02 eta: 1 day, 6:22:34 time: 0.3552 data_time: 0.0169 memory: 11108 grad_norm: 3.2537 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8334 loss: 2.8334 2022/10/09 07:19:36 - mmengine - INFO - Epoch(train) [7][1720/2119] lr: 2.8000e-02 eta: 1 day, 6:22:27 time: 0.3608 data_time: 0.0278 memory: 11108 grad_norm: 3.2996 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8044 loss: 2.8044 2022/10/09 07:19:43 - mmengine - INFO - Epoch(train) [7][1740/2119] lr: 2.8000e-02 eta: 1 day, 6:22:20 time: 0.3607 data_time: 0.0198 memory: 11108 grad_norm: 3.2630 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9777 loss: 2.9777 2022/10/09 07:19:51 - mmengine - INFO - Epoch(train) [7][1760/2119] lr: 2.8000e-02 eta: 1 day, 6:22:14 time: 0.3654 data_time: 0.0267 memory: 11108 grad_norm: 3.2823 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8028 loss: 2.8028 2022/10/09 07:19:58 - mmengine - INFO - Epoch(train) [7][1780/2119] lr: 2.8000e-02 eta: 1 day, 6:22:06 time: 0.3565 data_time: 0.0207 memory: 11108 grad_norm: 3.3382 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9285 loss: 2.9285 2022/10/09 07:20:05 - mmengine - INFO - Epoch(train) [7][1800/2119] lr: 2.8000e-02 eta: 1 day, 6:21:57 time: 0.3569 data_time: 0.0178 memory: 11108 grad_norm: 3.2949 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7787 loss: 2.7787 2022/10/09 07:20:12 - mmengine - INFO - Epoch(train) [7][1820/2119] lr: 2.8000e-02 eta: 1 day, 6:21:50 time: 0.3608 data_time: 0.0229 memory: 11108 grad_norm: 3.2335 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8391 loss: 2.8391 2022/10/09 07:20:19 - mmengine - INFO - Epoch(train) [7][1840/2119] lr: 2.8000e-02 eta: 1 day, 6:21:41 time: 0.3557 data_time: 0.0210 memory: 11108 grad_norm: 3.2781 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8869 loss: 2.8869 2022/10/09 07:20:27 - mmengine - INFO - Epoch(train) [7][1860/2119] lr: 2.8000e-02 eta: 1 day, 6:21:35 time: 0.3646 data_time: 0.0203 memory: 11108 grad_norm: 3.3247 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8970 loss: 2.8970 2022/10/09 07:20:34 - mmengine - INFO - Epoch(train) [7][1880/2119] lr: 2.8000e-02 eta: 1 day, 6:21:28 time: 0.3590 data_time: 0.0206 memory: 11108 grad_norm: 3.2574 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0603 loss: 3.0603 2022/10/09 07:20:41 - mmengine - INFO - Epoch(train) [7][1900/2119] lr: 2.8000e-02 eta: 1 day, 6:21:18 time: 0.3546 data_time: 0.0185 memory: 11108 grad_norm: 3.2893 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8791 loss: 2.8791 2022/10/09 07:20:48 - mmengine - INFO - Epoch(train) [7][1920/2119] lr: 2.8000e-02 eta: 1 day, 6:21:09 time: 0.3565 data_time: 0.0207 memory: 11108 grad_norm: 3.2982 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8558 loss: 2.8558 2022/10/09 07:20:55 - mmengine - INFO - Epoch(train) [7][1940/2119] lr: 2.8000e-02 eta: 1 day, 6:21:01 time: 0.3591 data_time: 0.0186 memory: 11108 grad_norm: 3.2911 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6375 loss: 2.6375 2022/10/09 07:21:02 - mmengine - INFO - Epoch(train) [7][1960/2119] lr: 2.8000e-02 eta: 1 day, 6:20:54 time: 0.3605 data_time: 0.0213 memory: 11108 grad_norm: 3.3059 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9162 loss: 2.9162 2022/10/09 07:21:10 - mmengine - INFO - Epoch(train) [7][1980/2119] lr: 2.8000e-02 eta: 1 day, 6:20:47 time: 0.3604 data_time: 0.0190 memory: 11108 grad_norm: 3.3061 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7195 loss: 2.7195 2022/10/09 07:21:17 - mmengine - INFO - Epoch(train) [7][2000/2119] lr: 2.8000e-02 eta: 1 day, 6:20:37 time: 0.3540 data_time: 0.0252 memory: 11108 grad_norm: 3.3010 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.8631 loss: 2.8631 2022/10/09 07:21:24 - mmengine - INFO - Epoch(train) [7][2020/2119] lr: 2.8000e-02 eta: 1 day, 6:20:30 time: 0.3611 data_time: 0.0186 memory: 11108 grad_norm: 3.2137 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7496 loss: 2.7496 2022/10/09 07:21:31 - mmengine - INFO - Epoch(train) [7][2040/2119] lr: 2.8000e-02 eta: 1 day, 6:20:21 time: 0.3553 data_time: 0.0230 memory: 11108 grad_norm: 3.2801 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6655 loss: 2.6655 2022/10/09 07:21:38 - mmengine - INFO - Epoch(train) [7][2060/2119] lr: 2.8000e-02 eta: 1 day, 6:20:12 time: 0.3562 data_time: 0.0187 memory: 11108 grad_norm: 3.2808 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7397 loss: 2.7397 2022/10/09 07:21:45 - mmengine - INFO - Epoch(train) [7][2080/2119] lr: 2.8000e-02 eta: 1 day, 6:20:04 time: 0.3583 data_time: 0.0197 memory: 11108 grad_norm: 3.2654 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7936 loss: 2.7936 2022/10/09 07:21:52 - mmengine - INFO - Epoch(train) [7][2100/2119] lr: 2.8000e-02 eta: 1 day, 6:19:56 time: 0.3572 data_time: 0.0205 memory: 11108 grad_norm: 3.3180 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6542 loss: 2.6542 2022/10/09 07:21:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 07:21:59 - mmengine - INFO - Epoch(train) [7][2119/2119] lr: 2.8000e-02 eta: 1 day, 6:19:56 time: 0.3356 data_time: 0.0163 memory: 11108 grad_norm: 3.3376 top1_acc: 0.6000 top5_acc: 1.0000 loss_cls: 2.9445 loss: 2.9445 2022/10/09 07:22:09 - mmengine - INFO - Epoch(train) [8][20/2119] lr: 3.2000e-02 eta: 1 day, 6:18:28 time: 0.5226 data_time: 0.1440 memory: 11108 grad_norm: 3.3029 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9623 loss: 2.9623 2022/10/09 07:22:17 - mmengine - INFO - Epoch(train) [8][40/2119] lr: 3.2000e-02 eta: 1 day, 6:18:22 time: 0.3632 data_time: 0.0239 memory: 11108 grad_norm: 3.2772 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9920 loss: 2.9920 2022/10/09 07:22:24 - mmengine - INFO - Epoch(train) [8][60/2119] lr: 3.2000e-02 eta: 1 day, 6:18:17 time: 0.3647 data_time: 0.0223 memory: 11108 grad_norm: 3.2162 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6510 loss: 2.6510 2022/10/09 07:22:31 - mmengine - INFO - Epoch(train) [8][80/2119] lr: 3.2000e-02 eta: 1 day, 6:18:10 time: 0.3604 data_time: 0.0272 memory: 11108 grad_norm: 3.2917 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8355 loss: 2.8355 2022/10/09 07:22:38 - mmengine - INFO - Epoch(train) [8][100/2119] lr: 3.2000e-02 eta: 1 day, 6:18:00 time: 0.3541 data_time: 0.0246 memory: 11108 grad_norm: 3.2862 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6838 loss: 2.6838 2022/10/09 07:22:45 - mmengine - INFO - Epoch(train) [8][120/2119] lr: 3.2000e-02 eta: 1 day, 6:17:53 time: 0.3597 data_time: 0.0251 memory: 11108 grad_norm: 3.2778 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6694 loss: 2.6694 2022/10/09 07:22:53 - mmengine - INFO - Epoch(train) [8][140/2119] lr: 3.2000e-02 eta: 1 day, 6:17:46 time: 0.3608 data_time: 0.0220 memory: 11108 grad_norm: 3.2389 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0126 loss: 3.0126 2022/10/09 07:23:00 - mmengine - INFO - Epoch(train) [8][160/2119] lr: 3.2000e-02 eta: 1 day, 6:17:37 time: 0.3573 data_time: 0.0224 memory: 11108 grad_norm: 3.3252 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8610 loss: 2.8610 2022/10/09 07:23:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 07:23:07 - mmengine - INFO - Epoch(train) [8][180/2119] lr: 3.2000e-02 eta: 1 day, 6:17:30 time: 0.3599 data_time: 0.0198 memory: 11108 grad_norm: 3.2828 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9143 loss: 2.9143 2022/10/09 07:23:14 - mmengine - INFO - Epoch(train) [8][200/2119] lr: 3.2000e-02 eta: 1 day, 6:17:21 time: 0.3562 data_time: 0.0214 memory: 11108 grad_norm: 3.2772 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7535 loss: 2.7535 2022/10/09 07:23:21 - mmengine - INFO - Epoch(train) [8][220/2119] lr: 3.2000e-02 eta: 1 day, 6:17:12 time: 0.3540 data_time: 0.0193 memory: 11108 grad_norm: 3.2378 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6177 loss: 2.6177 2022/10/09 07:23:28 - mmengine - INFO - Epoch(train) [8][240/2119] lr: 3.2000e-02 eta: 1 day, 6:17:04 time: 0.3594 data_time: 0.0218 memory: 11108 grad_norm: 3.3392 top1_acc: 0.3125 top5_acc: 0.8750 loss_cls: 2.8946 loss: 2.8946 2022/10/09 07:23:35 - mmengine - INFO - Epoch(train) [8][260/2119] lr: 3.2000e-02 eta: 1 day, 6:16:56 time: 0.3579 data_time: 0.0186 memory: 11108 grad_norm: 3.2739 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7675 loss: 2.7675 2022/10/09 07:23:43 - mmengine - INFO - Epoch(train) [8][280/2119] lr: 3.2000e-02 eta: 1 day, 6:16:49 time: 0.3596 data_time: 0.0241 memory: 11108 grad_norm: 3.2258 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7055 loss: 2.7055 2022/10/09 07:23:50 - mmengine - INFO - Epoch(train) [8][300/2119] lr: 3.2000e-02 eta: 1 day, 6:16:44 time: 0.3648 data_time: 0.0233 memory: 11108 grad_norm: 3.2178 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 3.0762 loss: 3.0762 2022/10/09 07:23:57 - mmengine - INFO - Epoch(train) [8][320/2119] lr: 3.2000e-02 eta: 1 day, 6:16:35 time: 0.3566 data_time: 0.0212 memory: 11108 grad_norm: 3.2661 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0543 loss: 3.0543 2022/10/09 07:24:04 - mmengine - INFO - Epoch(train) [8][340/2119] lr: 3.2000e-02 eta: 1 day, 6:16:25 time: 0.3531 data_time: 0.0165 memory: 11108 grad_norm: 3.3001 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7824 loss: 2.7824 2022/10/09 07:24:11 - mmengine - INFO - Epoch(train) [8][360/2119] lr: 3.2000e-02 eta: 1 day, 6:16:19 time: 0.3626 data_time: 0.0183 memory: 11108 grad_norm: 3.3075 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8698 loss: 2.8698 2022/10/09 07:24:19 - mmengine - INFO - Epoch(train) [8][380/2119] lr: 3.2000e-02 eta: 1 day, 6:16:09 time: 0.3545 data_time: 0.0220 memory: 11108 grad_norm: 3.2339 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9360 loss: 2.9360 2022/10/09 07:24:26 - mmengine - INFO - Epoch(train) [8][400/2119] lr: 3.2000e-02 eta: 1 day, 6:16:02 time: 0.3595 data_time: 0.0231 memory: 11108 grad_norm: 3.2796 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9187 loss: 2.9187 2022/10/09 07:24:33 - mmengine - INFO - Epoch(train) [8][420/2119] lr: 3.2000e-02 eta: 1 day, 6:15:54 time: 0.3589 data_time: 0.0197 memory: 11108 grad_norm: 3.2589 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9867 loss: 2.9867 2022/10/09 07:24:40 - mmengine - INFO - Epoch(train) [8][440/2119] lr: 3.2000e-02 eta: 1 day, 6:15:45 time: 0.3544 data_time: 0.0187 memory: 11108 grad_norm: 3.1650 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9845 loss: 2.9845 2022/10/09 07:24:47 - mmengine - INFO - Epoch(train) [8][460/2119] lr: 3.2000e-02 eta: 1 day, 6:15:36 time: 0.3552 data_time: 0.0198 memory: 11108 grad_norm: 3.2340 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7254 loss: 2.7254 2022/10/09 07:24:54 - mmengine - INFO - Epoch(train) [8][480/2119] lr: 3.2000e-02 eta: 1 day, 6:15:28 time: 0.3580 data_time: 0.0251 memory: 11108 grad_norm: 3.2953 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.1526 loss: 3.1526 2022/10/09 07:25:01 - mmengine - INFO - Epoch(train) [8][500/2119] lr: 3.2000e-02 eta: 1 day, 6:15:19 time: 0.3570 data_time: 0.0204 memory: 11108 grad_norm: 3.2581 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.9187 loss: 2.9187 2022/10/09 07:25:09 - mmengine - INFO - Epoch(train) [8][520/2119] lr: 3.2000e-02 eta: 1 day, 6:15:12 time: 0.3590 data_time: 0.0234 memory: 11108 grad_norm: 3.2534 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9113 loss: 2.9113 2022/10/09 07:25:16 - mmengine - INFO - Epoch(train) [8][540/2119] lr: 3.2000e-02 eta: 1 day, 6:15:03 time: 0.3559 data_time: 0.0271 memory: 11108 grad_norm: 3.1616 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7690 loss: 2.7690 2022/10/09 07:25:23 - mmengine - INFO - Epoch(train) [8][560/2119] lr: 3.2000e-02 eta: 1 day, 6:14:54 time: 0.3554 data_time: 0.0216 memory: 11108 grad_norm: 3.1912 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6056 loss: 2.6056 2022/10/09 07:25:30 - mmengine - INFO - Epoch(train) [8][580/2119] lr: 3.2000e-02 eta: 1 day, 6:14:47 time: 0.3617 data_time: 0.0175 memory: 11108 grad_norm: 3.2325 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9429 loss: 2.9429 2022/10/09 07:25:37 - mmengine - INFO - Epoch(train) [8][600/2119] lr: 3.2000e-02 eta: 1 day, 6:14:40 time: 0.3611 data_time: 0.0220 memory: 11108 grad_norm: 3.2530 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9654 loss: 2.9654 2022/10/09 07:25:44 - mmengine - INFO - Epoch(train) [8][620/2119] lr: 3.2000e-02 eta: 1 day, 6:14:31 time: 0.3556 data_time: 0.0196 memory: 11108 grad_norm: 3.1981 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8945 loss: 2.8945 2022/10/09 07:25:51 - mmengine - INFO - Epoch(train) [8][640/2119] lr: 3.2000e-02 eta: 1 day, 6:14:22 time: 0.3545 data_time: 0.0199 memory: 11108 grad_norm: 3.2248 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8794 loss: 2.8794 2022/10/09 07:25:59 - mmengine - INFO - Epoch(train) [8][660/2119] lr: 3.2000e-02 eta: 1 day, 6:14:13 time: 0.3552 data_time: 0.0169 memory: 11108 grad_norm: 3.1645 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8419 loss: 2.8419 2022/10/09 07:26:06 - mmengine - INFO - Epoch(train) [8][680/2119] lr: 3.2000e-02 eta: 1 day, 6:14:04 time: 0.3545 data_time: 0.0202 memory: 11108 grad_norm: 3.2164 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7081 loss: 2.7081 2022/10/09 07:26:13 - mmengine - INFO - Epoch(train) [8][700/2119] lr: 3.2000e-02 eta: 1 day, 6:13:55 time: 0.3572 data_time: 0.0229 memory: 11108 grad_norm: 3.2610 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8809 loss: 2.8809 2022/10/09 07:26:20 - mmengine - INFO - Epoch(train) [8][720/2119] lr: 3.2000e-02 eta: 1 day, 6:13:47 time: 0.3562 data_time: 0.0255 memory: 11108 grad_norm: 3.1912 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9704 loss: 2.9704 2022/10/09 07:26:27 - mmengine - INFO - Epoch(train) [8][740/2119] lr: 3.2000e-02 eta: 1 day, 6:13:40 time: 0.3623 data_time: 0.0189 memory: 11108 grad_norm: 3.2610 top1_acc: 0.2500 top5_acc: 0.8125 loss_cls: 2.9088 loss: 2.9088 2022/10/09 07:26:34 - mmengine - INFO - Epoch(train) [8][760/2119] lr: 3.2000e-02 eta: 1 day, 6:13:31 time: 0.3556 data_time: 0.0222 memory: 11108 grad_norm: 3.2693 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7715 loss: 2.7715 2022/10/09 07:26:42 - mmengine - INFO - Epoch(train) [8][780/2119] lr: 3.2000e-02 eta: 1 day, 6:13:27 time: 0.3666 data_time: 0.0272 memory: 11108 grad_norm: 3.1944 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6884 loss: 2.6884 2022/10/09 07:26:49 - mmengine - INFO - Epoch(train) [8][800/2119] lr: 3.2000e-02 eta: 1 day, 6:13:17 time: 0.3543 data_time: 0.0226 memory: 11108 grad_norm: 3.2130 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8620 loss: 2.8620 2022/10/09 07:26:56 - mmengine - INFO - Epoch(train) [8][820/2119] lr: 3.2000e-02 eta: 1 day, 6:13:10 time: 0.3590 data_time: 0.0201 memory: 11108 grad_norm: 3.1821 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7780 loss: 2.7780 2022/10/09 07:27:03 - mmengine - INFO - Epoch(train) [8][840/2119] lr: 3.2000e-02 eta: 1 day, 6:13:02 time: 0.3572 data_time: 0.0220 memory: 11108 grad_norm: 3.2308 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7085 loss: 2.7085 2022/10/09 07:27:10 - mmengine - INFO - Epoch(train) [8][860/2119] lr: 3.2000e-02 eta: 1 day, 6:12:53 time: 0.3563 data_time: 0.0217 memory: 11108 grad_norm: 3.1668 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.9410 loss: 2.9410 2022/10/09 07:27:17 - mmengine - INFO - Epoch(train) [8][880/2119] lr: 3.2000e-02 eta: 1 day, 6:12:45 time: 0.3591 data_time: 0.0215 memory: 11108 grad_norm: 3.1970 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8132 loss: 2.8132 2022/10/09 07:27:25 - mmengine - INFO - Epoch(train) [8][900/2119] lr: 3.2000e-02 eta: 1 day, 6:12:38 time: 0.3591 data_time: 0.0227 memory: 11108 grad_norm: 3.1956 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.9336 loss: 2.9336 2022/10/09 07:27:32 - mmengine - INFO - Epoch(train) [8][920/2119] lr: 3.2000e-02 eta: 1 day, 6:12:29 time: 0.3568 data_time: 0.0183 memory: 11108 grad_norm: 3.2327 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9617 loss: 2.9617 2022/10/09 07:27:39 - mmengine - INFO - Epoch(train) [8][940/2119] lr: 3.2000e-02 eta: 1 day, 6:12:20 time: 0.3529 data_time: 0.0201 memory: 11108 grad_norm: 3.1882 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0642 loss: 3.0642 2022/10/09 07:27:46 - mmengine - INFO - Epoch(train) [8][960/2119] lr: 3.2000e-02 eta: 1 day, 6:12:12 time: 0.3600 data_time: 0.0236 memory: 11108 grad_norm: 3.2356 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8850 loss: 2.8850 2022/10/09 07:27:53 - mmengine - INFO - Epoch(train) [8][980/2119] lr: 3.2000e-02 eta: 1 day, 6:12:05 time: 0.3593 data_time: 0.0191 memory: 11108 grad_norm: 3.2123 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.6680 loss: 2.6680 2022/10/09 07:28:00 - mmengine - INFO - Epoch(train) [8][1000/2119] lr: 3.2000e-02 eta: 1 day, 6:11:55 time: 0.3540 data_time: 0.0222 memory: 11108 grad_norm: 3.2048 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9537 loss: 2.9537 2022/10/09 07:28:07 - mmengine - INFO - Epoch(train) [8][1020/2119] lr: 3.2000e-02 eta: 1 day, 6:11:47 time: 0.3567 data_time: 0.0215 memory: 11108 grad_norm: 3.1625 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9331 loss: 2.9331 2022/10/09 07:28:15 - mmengine - INFO - Epoch(train) [8][1040/2119] lr: 3.2000e-02 eta: 1 day, 6:11:40 time: 0.3599 data_time: 0.0205 memory: 11108 grad_norm: 3.1654 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6393 loss: 2.6393 2022/10/09 07:28:22 - mmengine - INFO - Epoch(train) [8][1060/2119] lr: 3.2000e-02 eta: 1 day, 6:11:31 time: 0.3570 data_time: 0.0200 memory: 11108 grad_norm: 3.1915 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8150 loss: 2.8150 2022/10/09 07:28:29 - mmengine - INFO - Epoch(train) [8][1080/2119] lr: 3.2000e-02 eta: 1 day, 6:11:24 time: 0.3600 data_time: 0.0184 memory: 11108 grad_norm: 3.2569 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0594 loss: 3.0594 2022/10/09 07:28:36 - mmengine - INFO - Epoch(train) [8][1100/2119] lr: 3.2000e-02 eta: 1 day, 6:11:15 time: 0.3555 data_time: 0.0214 memory: 11108 grad_norm: 3.2372 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.1405 loss: 3.1405 2022/10/09 07:28:43 - mmengine - INFO - Epoch(train) [8][1120/2119] lr: 3.2000e-02 eta: 1 day, 6:11:08 time: 0.3586 data_time: 0.0224 memory: 11108 grad_norm: 3.2036 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0135 loss: 3.0135 2022/10/09 07:28:50 - mmengine - INFO - Epoch(train) [8][1140/2119] lr: 3.2000e-02 eta: 1 day, 6:11:00 time: 0.3586 data_time: 0.0228 memory: 11108 grad_norm: 3.2054 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7399 loss: 2.7399 2022/10/09 07:28:57 - mmengine - INFO - Epoch(train) [8][1160/2119] lr: 3.2000e-02 eta: 1 day, 6:10:50 time: 0.3542 data_time: 0.0231 memory: 11108 grad_norm: 3.2227 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8094 loss: 2.8094 2022/10/09 07:29:00 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 07:29:05 - mmengine - INFO - Epoch(train) [8][1180/2119] lr: 3.2000e-02 eta: 1 day, 6:10:46 time: 0.3659 data_time: 0.0186 memory: 11108 grad_norm: 3.2084 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8425 loss: 2.8425 2022/10/09 07:29:12 - mmengine - INFO - Epoch(train) [8][1200/2119] lr: 3.2000e-02 eta: 1 day, 6:10:37 time: 0.3565 data_time: 0.0206 memory: 11108 grad_norm: 3.2186 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9144 loss: 2.9144 2022/10/09 07:29:19 - mmengine - INFO - Epoch(train) [8][1220/2119] lr: 3.2000e-02 eta: 1 day, 6:10:30 time: 0.3615 data_time: 0.0182 memory: 11108 grad_norm: 3.1798 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6453 loss: 2.6453 2022/10/09 07:29:26 - mmengine - INFO - Epoch(train) [8][1240/2119] lr: 3.2000e-02 eta: 1 day, 6:10:22 time: 0.3570 data_time: 0.0218 memory: 11108 grad_norm: 3.2105 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7373 loss: 2.7373 2022/10/09 07:29:33 - mmengine - INFO - Epoch(train) [8][1260/2119] lr: 3.2000e-02 eta: 1 day, 6:10:15 time: 0.3609 data_time: 0.0231 memory: 11108 grad_norm: 3.1421 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9509 loss: 2.9509 2022/10/09 07:29:41 - mmengine - INFO - Epoch(train) [8][1280/2119] lr: 3.2000e-02 eta: 1 day, 6:10:08 time: 0.3586 data_time: 0.0196 memory: 11108 grad_norm: 3.1891 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4814 loss: 2.4814 2022/10/09 07:29:48 - mmengine - INFO - Epoch(train) [8][1300/2119] lr: 3.2000e-02 eta: 1 day, 6:10:00 time: 0.3592 data_time: 0.0219 memory: 11108 grad_norm: 3.2264 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8153 loss: 2.8153 2022/10/09 07:29:55 - mmengine - INFO - Epoch(train) [8][1320/2119] lr: 3.2000e-02 eta: 1 day, 6:09:50 time: 0.3519 data_time: 0.0211 memory: 11108 grad_norm: 3.2149 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6901 loss: 2.6901 2022/10/09 07:30:02 - mmengine - INFO - Epoch(train) [8][1340/2119] lr: 3.2000e-02 eta: 1 day, 6:09:45 time: 0.3669 data_time: 0.0311 memory: 11108 grad_norm: 3.1915 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7779 loss: 2.7779 2022/10/09 07:30:09 - mmengine - INFO - Epoch(train) [8][1360/2119] lr: 3.2000e-02 eta: 1 day, 6:09:38 time: 0.3584 data_time: 0.0193 memory: 11108 grad_norm: 3.1727 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0701 loss: 3.0701 2022/10/09 07:30:17 - mmengine - INFO - Epoch(train) [8][1380/2119] lr: 3.2000e-02 eta: 1 day, 6:09:30 time: 0.3599 data_time: 0.0179 memory: 11108 grad_norm: 3.1839 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8291 loss: 2.8291 2022/10/09 07:30:24 - mmengine - INFO - Epoch(train) [8][1400/2119] lr: 3.2000e-02 eta: 1 day, 6:09:24 time: 0.3628 data_time: 0.0252 memory: 11108 grad_norm: 3.1530 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8602 loss: 2.8602 2022/10/09 07:30:31 - mmengine - INFO - Epoch(train) [8][1420/2119] lr: 3.2000e-02 eta: 1 day, 6:09:16 time: 0.3572 data_time: 0.0184 memory: 11108 grad_norm: 3.1709 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8723 loss: 2.8723 2022/10/09 07:30:38 - mmengine - INFO - Epoch(train) [8][1440/2119] lr: 3.2000e-02 eta: 1 day, 6:09:07 time: 0.3551 data_time: 0.0213 memory: 11108 grad_norm: 3.1759 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8946 loss: 2.8946 2022/10/09 07:30:45 - mmengine - INFO - Epoch(train) [8][1460/2119] lr: 3.2000e-02 eta: 1 day, 6:09:00 time: 0.3596 data_time: 0.0227 memory: 11108 grad_norm: 3.1626 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.9421 loss: 2.9421 2022/10/09 07:30:52 - mmengine - INFO - Epoch(train) [8][1480/2119] lr: 3.2000e-02 eta: 1 day, 6:08:53 time: 0.3614 data_time: 0.0193 memory: 11108 grad_norm: 3.1919 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6904 loss: 2.6904 2022/10/09 07:31:00 - mmengine - INFO - Epoch(train) [8][1500/2119] lr: 3.2000e-02 eta: 1 day, 6:08:45 time: 0.3574 data_time: 0.0198 memory: 11108 grad_norm: 3.2187 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8212 loss: 2.8212 2022/10/09 07:31:07 - mmengine - INFO - Epoch(train) [8][1520/2119] lr: 3.2000e-02 eta: 1 day, 6:08:38 time: 0.3595 data_time: 0.0219 memory: 11108 grad_norm: 3.1636 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9075 loss: 2.9075 2022/10/09 07:31:14 - mmengine - INFO - Epoch(train) [8][1540/2119] lr: 3.2000e-02 eta: 1 day, 6:08:28 time: 0.3536 data_time: 0.0172 memory: 11108 grad_norm: 3.1783 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8348 loss: 2.8348 2022/10/09 07:31:21 - mmengine - INFO - Epoch(train) [8][1560/2119] lr: 3.2000e-02 eta: 1 day, 6:08:20 time: 0.3579 data_time: 0.0212 memory: 11108 grad_norm: 3.2030 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7456 loss: 2.7456 2022/10/09 07:31:28 - mmengine - INFO - Epoch(train) [8][1580/2119] lr: 3.2000e-02 eta: 1 day, 6:08:13 time: 0.3596 data_time: 0.0243 memory: 11108 grad_norm: 3.1820 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.9506 loss: 2.9506 2022/10/09 07:31:35 - mmengine - INFO - Epoch(train) [8][1600/2119] lr: 3.2000e-02 eta: 1 day, 6:08:04 time: 0.3560 data_time: 0.0228 memory: 11108 grad_norm: 3.1163 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.5910 loss: 2.5910 2022/10/09 07:31:43 - mmengine - INFO - Epoch(train) [8][1620/2119] lr: 3.2000e-02 eta: 1 day, 6:07:57 time: 0.3612 data_time: 0.0221 memory: 11108 grad_norm: 3.2098 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7363 loss: 2.7363 2022/10/09 07:31:50 - mmengine - INFO - Epoch(train) [8][1640/2119] lr: 3.2000e-02 eta: 1 day, 6:07:48 time: 0.3552 data_time: 0.0230 memory: 11108 grad_norm: 3.1236 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.0305 loss: 3.0305 2022/10/09 07:31:57 - mmengine - INFO - Epoch(train) [8][1660/2119] lr: 3.2000e-02 eta: 1 day, 6:07:39 time: 0.3541 data_time: 0.0222 memory: 11108 grad_norm: 3.2041 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.4642 loss: 2.4642 2022/10/09 07:32:04 - mmengine - INFO - Epoch(train) [8][1680/2119] lr: 3.2000e-02 eta: 1 day, 6:07:32 time: 0.3603 data_time: 0.0240 memory: 11108 grad_norm: 3.1784 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9745 loss: 2.9745 2022/10/09 07:32:11 - mmengine - INFO - Epoch(train) [8][1700/2119] lr: 3.2000e-02 eta: 1 day, 6:07:24 time: 0.3575 data_time: 0.0194 memory: 11108 grad_norm: 3.1925 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7712 loss: 2.7712 2022/10/09 07:32:18 - mmengine - INFO - Epoch(train) [8][1720/2119] lr: 3.2000e-02 eta: 1 day, 6:07:15 time: 0.3537 data_time: 0.0254 memory: 11108 grad_norm: 3.2321 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8441 loss: 2.8441 2022/10/09 07:32:25 - mmengine - INFO - Epoch(train) [8][1740/2119] lr: 3.2000e-02 eta: 1 day, 6:07:06 time: 0.3563 data_time: 0.0212 memory: 11108 grad_norm: 3.1750 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.5145 loss: 2.5145 2022/10/09 07:32:32 - mmengine - INFO - Epoch(train) [8][1760/2119] lr: 3.2000e-02 eta: 1 day, 6:06:58 time: 0.3564 data_time: 0.0226 memory: 11108 grad_norm: 3.1180 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6523 loss: 2.6523 2022/10/09 07:32:40 - mmengine - INFO - Epoch(train) [8][1780/2119] lr: 3.2000e-02 eta: 1 day, 6:06:48 time: 0.3548 data_time: 0.0180 memory: 11108 grad_norm: 3.1634 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8132 loss: 2.8132 2022/10/09 07:32:47 - mmengine - INFO - Epoch(train) [8][1800/2119] lr: 3.2000e-02 eta: 1 day, 6:06:40 time: 0.3577 data_time: 0.0220 memory: 11108 grad_norm: 3.1894 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8818 loss: 2.8818 2022/10/09 07:32:54 - mmengine - INFO - Epoch(train) [8][1820/2119] lr: 3.2000e-02 eta: 1 day, 6:06:33 time: 0.3600 data_time: 0.0187 memory: 11108 grad_norm: 3.1982 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5825 loss: 2.5825 2022/10/09 07:33:01 - mmengine - INFO - Epoch(train) [8][1840/2119] lr: 3.2000e-02 eta: 1 day, 6:06:27 time: 0.3624 data_time: 0.0217 memory: 11108 grad_norm: 3.1551 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8164 loss: 2.8164 2022/10/09 07:33:08 - mmengine - INFO - Epoch(train) [8][1860/2119] lr: 3.2000e-02 eta: 1 day, 6:06:20 time: 0.3603 data_time: 0.0184 memory: 11108 grad_norm: 3.1168 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6881 loss: 2.6881 2022/10/09 07:33:16 - mmengine - INFO - Epoch(train) [8][1880/2119] lr: 3.2000e-02 eta: 1 day, 6:06:13 time: 0.3590 data_time: 0.0205 memory: 11108 grad_norm: 3.1650 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7538 loss: 2.7538 2022/10/09 07:33:23 - mmengine - INFO - Epoch(train) [8][1900/2119] lr: 3.2000e-02 eta: 1 day, 6:06:03 time: 0.3535 data_time: 0.0198 memory: 11108 grad_norm: 3.1565 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8604 loss: 2.8604 2022/10/09 07:33:30 - mmengine - INFO - Epoch(train) [8][1920/2119] lr: 3.2000e-02 eta: 1 day, 6:05:55 time: 0.3568 data_time: 0.0232 memory: 11108 grad_norm: 3.1436 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9531 loss: 2.9531 2022/10/09 07:33:37 - mmengine - INFO - Epoch(train) [8][1940/2119] lr: 3.2000e-02 eta: 1 day, 6:05:47 time: 0.3598 data_time: 0.0213 memory: 11108 grad_norm: 3.1926 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8629 loss: 2.8629 2022/10/09 07:33:44 - mmengine - INFO - Epoch(train) [8][1960/2119] lr: 3.2000e-02 eta: 1 day, 6:05:39 time: 0.3577 data_time: 0.0232 memory: 11108 grad_norm: 3.1421 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7909 loss: 2.7909 2022/10/09 07:33:51 - mmengine - INFO - Epoch(train) [8][1980/2119] lr: 3.2000e-02 eta: 1 day, 6:05:31 time: 0.3575 data_time: 0.0215 memory: 11108 grad_norm: 3.1467 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7519 loss: 2.7519 2022/10/09 07:33:58 - mmengine - INFO - Epoch(train) [8][2000/2119] lr: 3.2000e-02 eta: 1 day, 6:05:24 time: 0.3583 data_time: 0.0235 memory: 11108 grad_norm: 3.1423 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8587 loss: 2.8587 2022/10/09 07:34:06 - mmengine - INFO - Epoch(train) [8][2020/2119] lr: 3.2000e-02 eta: 1 day, 6:05:15 time: 0.3557 data_time: 0.0186 memory: 11108 grad_norm: 3.1466 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.2060 loss: 3.2060 2022/10/09 07:34:13 - mmengine - INFO - Epoch(train) [8][2040/2119] lr: 3.2000e-02 eta: 1 day, 6:05:07 time: 0.3576 data_time: 0.0209 memory: 11108 grad_norm: 3.1605 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8251 loss: 2.8251 2022/10/09 07:34:20 - mmengine - INFO - Epoch(train) [8][2060/2119] lr: 3.2000e-02 eta: 1 day, 6:04:57 time: 0.3517 data_time: 0.0221 memory: 11108 grad_norm: 3.1607 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7097 loss: 2.7097 2022/10/09 07:34:27 - mmengine - INFO - Epoch(train) [8][2080/2119] lr: 3.2000e-02 eta: 1 day, 6:04:51 time: 0.3635 data_time: 0.0210 memory: 11108 grad_norm: 3.1050 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7493 loss: 2.7493 2022/10/09 07:34:34 - mmengine - INFO - Epoch(train) [8][2100/2119] lr: 3.2000e-02 eta: 1 day, 6:04:43 time: 0.3567 data_time: 0.0193 memory: 11108 grad_norm: 3.1166 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6607 loss: 2.6607 2022/10/09 07:34:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 07:34:41 - mmengine - INFO - Epoch(train) [8][2119/2119] lr: 3.2000e-02 eta: 1 day, 6:04:43 time: 0.3416 data_time: 0.0185 memory: 11108 grad_norm: 3.1502 top1_acc: 0.4000 top5_acc: 0.8000 loss_cls: 2.9821 loss: 2.9821 2022/10/09 07:34:41 - mmengine - INFO - Saving checkpoint at 8 epochs 2022/10/09 07:34:52 - mmengine - INFO - Epoch(train) [9][20/2119] lr: 3.6000e-02 eta: 1 day, 6:03:04 time: 0.4636 data_time: 0.1276 memory: 11108 grad_norm: 3.1253 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 3.0950 loss: 3.0950 2022/10/09 07:35:00 - mmengine - INFO - Epoch(train) [9][40/2119] lr: 3.6000e-02 eta: 1 day, 6:02:59 time: 0.3639 data_time: 0.0299 memory: 11108 grad_norm: 3.1157 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5625 loss: 2.5625 2022/10/09 07:35:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 07:35:07 - mmengine - INFO - Epoch(train) [9][60/2119] lr: 3.6000e-02 eta: 1 day, 6:02:50 time: 0.3567 data_time: 0.0208 memory: 11108 grad_norm: 3.1799 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8496 loss: 2.8496 2022/10/09 07:35:14 - mmengine - INFO - Epoch(train) [9][80/2119] lr: 3.6000e-02 eta: 1 day, 6:02:43 time: 0.3579 data_time: 0.0177 memory: 11108 grad_norm: 3.1537 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8671 loss: 2.8671 2022/10/09 07:35:21 - mmengine - INFO - Epoch(train) [9][100/2119] lr: 3.6000e-02 eta: 1 day, 6:02:35 time: 0.3583 data_time: 0.0211 memory: 11108 grad_norm: 3.1514 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6592 loss: 2.6592 2022/10/09 07:35:28 - mmengine - INFO - Epoch(train) [9][120/2119] lr: 3.6000e-02 eta: 1 day, 6:02:28 time: 0.3606 data_time: 0.0197 memory: 11108 grad_norm: 3.1527 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9095 loss: 2.9095 2022/10/09 07:35:35 - mmengine - INFO - Epoch(train) [9][140/2119] lr: 3.6000e-02 eta: 1 day, 6:02:20 time: 0.3572 data_time: 0.0197 memory: 11108 grad_norm: 3.1134 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9898 loss: 2.9898 2022/10/09 07:35:42 - mmengine - INFO - Epoch(train) [9][160/2119] lr: 3.6000e-02 eta: 1 day, 6:02:12 time: 0.3573 data_time: 0.0233 memory: 11108 grad_norm: 3.1424 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5697 loss: 2.5697 2022/10/09 07:35:50 - mmengine - INFO - Epoch(train) [9][180/2119] lr: 3.6000e-02 eta: 1 day, 6:02:03 time: 0.3549 data_time: 0.0237 memory: 11108 grad_norm: 3.1362 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6342 loss: 2.6342 2022/10/09 07:35:57 - mmengine - INFO - Epoch(train) [9][200/2119] lr: 3.6000e-02 eta: 1 day, 6:01:55 time: 0.3559 data_time: 0.0216 memory: 11108 grad_norm: 3.1835 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8550 loss: 2.8550 2022/10/09 07:36:04 - mmengine - INFO - Epoch(train) [9][220/2119] lr: 3.6000e-02 eta: 1 day, 6:01:47 time: 0.3574 data_time: 0.0187 memory: 11108 grad_norm: 3.1344 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7908 loss: 2.7908 2022/10/09 07:36:11 - mmengine - INFO - Epoch(train) [9][240/2119] lr: 3.6000e-02 eta: 1 day, 6:01:39 time: 0.3561 data_time: 0.0202 memory: 11108 grad_norm: 3.0994 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 3.0735 loss: 3.0735 2022/10/09 07:36:18 - mmengine - INFO - Epoch(train) [9][260/2119] lr: 3.6000e-02 eta: 1 day, 6:01:32 time: 0.3606 data_time: 0.0192 memory: 11108 grad_norm: 3.0877 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7896 loss: 2.7896 2022/10/09 07:36:25 - mmengine - INFO - Epoch(train) [9][280/2119] lr: 3.6000e-02 eta: 1 day, 6:01:24 time: 0.3576 data_time: 0.0219 memory: 11108 grad_norm: 3.1407 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8400 loss: 2.8400 2022/10/09 07:36:33 - mmengine - INFO - Epoch(train) [9][300/2119] lr: 3.6000e-02 eta: 1 day, 6:01:18 time: 0.3625 data_time: 0.0201 memory: 11108 grad_norm: 3.1196 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6411 loss: 2.6411 2022/10/09 07:36:40 - mmengine - INFO - Epoch(train) [9][320/2119] lr: 3.6000e-02 eta: 1 day, 6:01:10 time: 0.3580 data_time: 0.0187 memory: 11108 grad_norm: 3.1280 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8890 loss: 2.8890 2022/10/09 07:36:47 - mmengine - INFO - Epoch(train) [9][340/2119] lr: 3.6000e-02 eta: 1 day, 6:01:02 time: 0.3563 data_time: 0.0190 memory: 11108 grad_norm: 3.1486 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7473 loss: 2.7473 2022/10/09 07:36:54 - mmengine - INFO - Epoch(train) [9][360/2119] lr: 3.6000e-02 eta: 1 day, 6:00:52 time: 0.3535 data_time: 0.0195 memory: 11108 grad_norm: 3.1290 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7957 loss: 2.7957 2022/10/09 07:37:01 - mmengine - INFO - Epoch(train) [9][380/2119] lr: 3.6000e-02 eta: 1 day, 6:00:45 time: 0.3578 data_time: 0.0232 memory: 11108 grad_norm: 3.1137 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9142 loss: 2.9142 2022/10/09 07:37:08 - mmengine - INFO - Epoch(train) [9][400/2119] lr: 3.6000e-02 eta: 1 day, 6:00:38 time: 0.3618 data_time: 0.0197 memory: 11108 grad_norm: 3.0983 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5480 loss: 2.5480 2022/10/09 07:37:15 - mmengine - INFO - Epoch(train) [9][420/2119] lr: 3.6000e-02 eta: 1 day, 6:00:30 time: 0.3556 data_time: 0.0169 memory: 11108 grad_norm: 3.1382 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9313 loss: 2.9313 2022/10/09 07:37:23 - mmengine - INFO - Epoch(train) [9][440/2119] lr: 3.6000e-02 eta: 1 day, 6:00:22 time: 0.3583 data_time: 0.0189 memory: 11108 grad_norm: 3.1700 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9909 loss: 2.9909 2022/10/09 07:37:30 - mmengine - INFO - Epoch(train) [9][460/2119] lr: 3.6000e-02 eta: 1 day, 6:00:13 time: 0.3555 data_time: 0.0214 memory: 11108 grad_norm: 3.1266 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9507 loss: 2.9507 2022/10/09 07:37:37 - mmengine - INFO - Epoch(train) [9][480/2119] lr: 3.6000e-02 eta: 1 day, 6:00:04 time: 0.3529 data_time: 0.0192 memory: 11108 grad_norm: 3.1018 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8988 loss: 2.8988 2022/10/09 07:37:44 - mmengine - INFO - Epoch(train) [9][500/2119] lr: 3.6000e-02 eta: 1 day, 5:59:57 time: 0.3607 data_time: 0.0187 memory: 11108 grad_norm: 3.1042 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8540 loss: 2.8540 2022/10/09 07:37:51 - mmengine - INFO - Epoch(train) [9][520/2119] lr: 3.6000e-02 eta: 1 day, 5:59:48 time: 0.3545 data_time: 0.0188 memory: 11108 grad_norm: 3.1453 top1_acc: 0.1875 top5_acc: 0.8125 loss_cls: 3.0097 loss: 3.0097 2022/10/09 07:37:58 - mmengine - INFO - Epoch(train) [9][540/2119] lr: 3.6000e-02 eta: 1 day, 5:59:41 time: 0.3585 data_time: 0.0243 memory: 11108 grad_norm: 3.0648 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7575 loss: 2.7575 2022/10/09 07:38:05 - mmengine - INFO - Epoch(train) [9][560/2119] lr: 3.6000e-02 eta: 1 day, 5:59:34 time: 0.3595 data_time: 0.0198 memory: 11108 grad_norm: 3.1701 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9912 loss: 2.9912 2022/10/09 07:38:13 - mmengine - INFO - Epoch(train) [9][580/2119] lr: 3.6000e-02 eta: 1 day, 5:59:25 time: 0.3568 data_time: 0.0195 memory: 11108 grad_norm: 3.1082 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0237 loss: 3.0237 2022/10/09 07:38:20 - mmengine - INFO - Epoch(train) [9][600/2119] lr: 3.6000e-02 eta: 1 day, 5:59:17 time: 0.3563 data_time: 0.0182 memory: 11108 grad_norm: 3.1479 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7368 loss: 2.7368 2022/10/09 07:38:27 - mmengine - INFO - Epoch(train) [9][620/2119] lr: 3.6000e-02 eta: 1 day, 5:59:09 time: 0.3575 data_time: 0.0249 memory: 11108 grad_norm: 3.1347 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9470 loss: 2.9470 2022/10/09 07:38:34 - mmengine - INFO - Epoch(train) [9][640/2119] lr: 3.6000e-02 eta: 1 day, 5:59:02 time: 0.3593 data_time: 0.0175 memory: 11108 grad_norm: 3.1369 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9951 loss: 2.9951 2022/10/09 07:38:41 - mmengine - INFO - Epoch(train) [9][660/2119] lr: 3.6000e-02 eta: 1 day, 5:58:54 time: 0.3574 data_time: 0.0202 memory: 11108 grad_norm: 3.0455 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9094 loss: 2.9094 2022/10/09 07:38:48 - mmengine - INFO - Epoch(train) [9][680/2119] lr: 3.6000e-02 eta: 1 day, 5:58:45 time: 0.3541 data_time: 0.0186 memory: 11108 grad_norm: 3.0910 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 3.0974 loss: 3.0974 2022/10/09 07:38:55 - mmengine - INFO - Epoch(train) [9][700/2119] lr: 3.6000e-02 eta: 1 day, 5:58:38 time: 0.3595 data_time: 0.0181 memory: 11108 grad_norm: 3.0641 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8354 loss: 2.8354 2022/10/09 07:39:03 - mmengine - INFO - Epoch(train) [9][720/2119] lr: 3.6000e-02 eta: 1 day, 5:58:29 time: 0.3554 data_time: 0.0214 memory: 11108 grad_norm: 3.0848 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 2.9313 loss: 2.9313 2022/10/09 07:39:10 - mmengine - INFO - Epoch(train) [9][740/2119] lr: 3.6000e-02 eta: 1 day, 5:58:21 time: 0.3565 data_time: 0.0213 memory: 11108 grad_norm: 3.1060 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.0398 loss: 3.0398 2022/10/09 07:39:17 - mmengine - INFO - Epoch(train) [9][760/2119] lr: 3.6000e-02 eta: 1 day, 5:58:13 time: 0.3554 data_time: 0.0238 memory: 11108 grad_norm: 3.0743 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9091 loss: 2.9091 2022/10/09 07:39:24 - mmengine - INFO - Epoch(train) [9][780/2119] lr: 3.6000e-02 eta: 1 day, 5:58:05 time: 0.3597 data_time: 0.0231 memory: 11108 grad_norm: 3.0876 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8065 loss: 2.8065 2022/10/09 07:39:31 - mmengine - INFO - Epoch(train) [9][800/2119] lr: 3.6000e-02 eta: 1 day, 5:57:57 time: 0.3551 data_time: 0.0188 memory: 11108 grad_norm: 3.0952 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7977 loss: 2.7977 2022/10/09 07:39:38 - mmengine - INFO - Epoch(train) [9][820/2119] lr: 3.6000e-02 eta: 1 day, 5:57:50 time: 0.3598 data_time: 0.0180 memory: 11108 grad_norm: 3.0544 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7929 loss: 2.7929 2022/10/09 07:39:45 - mmengine - INFO - Epoch(train) [9][840/2119] lr: 3.6000e-02 eta: 1 day, 5:57:41 time: 0.3539 data_time: 0.0203 memory: 11108 grad_norm: 3.1014 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5611 loss: 2.5611 2022/10/09 07:39:53 - mmengine - INFO - Epoch(train) [9][860/2119] lr: 3.6000e-02 eta: 1 day, 5:57:34 time: 0.3598 data_time: 0.0232 memory: 11108 grad_norm: 3.0280 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9169 loss: 2.9169 2022/10/09 07:40:00 - mmengine - INFO - Epoch(train) [9][880/2119] lr: 3.6000e-02 eta: 1 day, 5:57:24 time: 0.3519 data_time: 0.0198 memory: 11108 grad_norm: 3.0455 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9029 loss: 2.9029 2022/10/09 07:40:07 - mmengine - INFO - Epoch(train) [9][900/2119] lr: 3.6000e-02 eta: 1 day, 5:57:16 time: 0.3578 data_time: 0.0205 memory: 11108 grad_norm: 3.0643 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8763 loss: 2.8763 2022/10/09 07:40:14 - mmengine - INFO - Epoch(train) [9][920/2119] lr: 3.6000e-02 eta: 1 day, 5:57:08 time: 0.3579 data_time: 0.0222 memory: 11108 grad_norm: 3.0422 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4894 loss: 2.4894 2022/10/09 07:40:21 - mmengine - INFO - Epoch(train) [9][940/2119] lr: 3.6000e-02 eta: 1 day, 5:57:02 time: 0.3618 data_time: 0.0279 memory: 11108 grad_norm: 3.0654 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8538 loss: 2.8538 2022/10/09 07:40:28 - mmengine - INFO - Epoch(train) [9][960/2119] lr: 3.6000e-02 eta: 1 day, 5:56:55 time: 0.3614 data_time: 0.0200 memory: 11108 grad_norm: 3.1111 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7042 loss: 2.7042 2022/10/09 07:40:36 - mmengine - INFO - Epoch(train) [9][980/2119] lr: 3.6000e-02 eta: 1 day, 5:56:50 time: 0.3643 data_time: 0.0219 memory: 11108 grad_norm: 3.0719 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5815 loss: 2.5815 2022/10/09 07:40:43 - mmengine - INFO - Epoch(train) [9][1000/2119] lr: 3.6000e-02 eta: 1 day, 5:56:45 time: 0.3665 data_time: 0.0228 memory: 11108 grad_norm: 3.0337 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7493 loss: 2.7493 2022/10/09 07:40:50 - mmengine - INFO - Epoch(train) [9][1020/2119] lr: 3.6000e-02 eta: 1 day, 5:56:36 time: 0.3534 data_time: 0.0204 memory: 11108 grad_norm: 3.0603 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9642 loss: 2.9642 2022/10/09 07:40:57 - mmengine - INFO - Epoch(train) [9][1040/2119] lr: 3.6000e-02 eta: 1 day, 5:56:27 time: 0.3560 data_time: 0.0220 memory: 11108 grad_norm: 3.0602 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9163 loss: 2.9163 2022/10/09 07:41:00 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 07:41:04 - mmengine - INFO - Epoch(train) [9][1060/2119] lr: 3.6000e-02 eta: 1 day, 5:56:20 time: 0.3590 data_time: 0.0201 memory: 11108 grad_norm: 3.0831 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5545 loss: 2.5545 2022/10/09 07:41:12 - mmengine - INFO - Epoch(train) [9][1080/2119] lr: 3.6000e-02 eta: 1 day, 5:56:12 time: 0.3576 data_time: 0.0200 memory: 11108 grad_norm: 3.0766 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7629 loss: 2.7629 2022/10/09 07:41:19 - mmengine - INFO - Epoch(train) [9][1100/2119] lr: 3.6000e-02 eta: 1 day, 5:56:04 time: 0.3571 data_time: 0.0179 memory: 11108 grad_norm: 3.0704 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 3.0337 loss: 3.0337 2022/10/09 07:41:26 - mmengine - INFO - Epoch(train) [9][1120/2119] lr: 3.6000e-02 eta: 1 day, 5:55:56 time: 0.3559 data_time: 0.0232 memory: 11108 grad_norm: 3.0761 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8008 loss: 2.8008 2022/10/09 07:41:33 - mmengine - INFO - Epoch(train) [9][1140/2119] lr: 3.6000e-02 eta: 1 day, 5:55:53 time: 0.3735 data_time: 0.0204 memory: 11108 grad_norm: 3.0658 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7723 loss: 2.7723 2022/10/09 07:41:40 - mmengine - INFO - Epoch(train) [9][1160/2119] lr: 3.6000e-02 eta: 1 day, 5:55:45 time: 0.3561 data_time: 0.0231 memory: 11108 grad_norm: 3.0477 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9570 loss: 2.9570 2022/10/09 07:41:48 - mmengine - INFO - Epoch(train) [9][1180/2119] lr: 3.6000e-02 eta: 1 day, 5:55:39 time: 0.3635 data_time: 0.0234 memory: 11108 grad_norm: 3.0610 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8077 loss: 2.8077 2022/10/09 07:41:55 - mmengine - INFO - Epoch(train) [9][1200/2119] lr: 3.6000e-02 eta: 1 day, 5:55:32 time: 0.3582 data_time: 0.0207 memory: 11108 grad_norm: 3.0695 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9663 loss: 2.9663 2022/10/09 07:42:02 - mmengine - INFO - Epoch(train) [9][1220/2119] lr: 3.6000e-02 eta: 1 day, 5:55:27 time: 0.3665 data_time: 0.0193 memory: 11108 grad_norm: 3.0342 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8248 loss: 2.8248 2022/10/09 07:42:09 - mmengine - INFO - Epoch(train) [9][1240/2119] lr: 3.6000e-02 eta: 1 day, 5:55:18 time: 0.3550 data_time: 0.0225 memory: 11108 grad_norm: 3.0491 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7719 loss: 2.7719 2022/10/09 07:42:16 - mmengine - INFO - Epoch(train) [9][1260/2119] lr: 3.6000e-02 eta: 1 day, 5:55:09 time: 0.3549 data_time: 0.0189 memory: 11108 grad_norm: 3.0917 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7165 loss: 2.7165 2022/10/09 07:42:24 - mmengine - INFO - Epoch(train) [9][1280/2119] lr: 3.6000e-02 eta: 1 day, 5:55:02 time: 0.3584 data_time: 0.0189 memory: 11108 grad_norm: 3.0775 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7705 loss: 2.7705 2022/10/09 07:42:31 - mmengine - INFO - Epoch(train) [9][1300/2119] lr: 3.6000e-02 eta: 1 day, 5:54:53 time: 0.3544 data_time: 0.0204 memory: 11108 grad_norm: 3.0894 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8321 loss: 2.8321 2022/10/09 07:42:38 - mmengine - INFO - Epoch(train) [9][1320/2119] lr: 3.6000e-02 eta: 1 day, 5:54:46 time: 0.3590 data_time: 0.0222 memory: 11108 grad_norm: 2.9838 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8893 loss: 2.8893 2022/10/09 07:42:45 - mmengine - INFO - Epoch(train) [9][1340/2119] lr: 3.6000e-02 eta: 1 day, 5:54:38 time: 0.3587 data_time: 0.0209 memory: 11108 grad_norm: 3.0746 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7799 loss: 2.7799 2022/10/09 07:42:52 - mmengine - INFO - Epoch(train) [9][1360/2119] lr: 3.6000e-02 eta: 1 day, 5:54:31 time: 0.3600 data_time: 0.0199 memory: 11108 grad_norm: 3.1142 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0115 loss: 3.0115 2022/10/09 07:42:59 - mmengine - INFO - Epoch(train) [9][1380/2119] lr: 3.6000e-02 eta: 1 day, 5:54:24 time: 0.3586 data_time: 0.0185 memory: 11108 grad_norm: 3.0735 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9328 loss: 2.9328 2022/10/09 07:43:07 - mmengine - INFO - Epoch(train) [9][1400/2119] lr: 3.6000e-02 eta: 1 day, 5:54:16 time: 0.3587 data_time: 0.0207 memory: 11108 grad_norm: 3.1119 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8425 loss: 2.8425 2022/10/09 07:43:14 - mmengine - INFO - Epoch(train) [9][1420/2119] lr: 3.6000e-02 eta: 1 day, 5:54:09 time: 0.3581 data_time: 0.0193 memory: 11108 grad_norm: 3.0572 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8579 loss: 2.8579 2022/10/09 07:43:21 - mmengine - INFO - Epoch(train) [9][1440/2119] lr: 3.6000e-02 eta: 1 day, 5:54:00 time: 0.3564 data_time: 0.0184 memory: 11108 grad_norm: 3.0292 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8099 loss: 2.8099 2022/10/09 07:43:28 - mmengine - INFO - Epoch(train) [9][1460/2119] lr: 3.6000e-02 eta: 1 day, 5:53:54 time: 0.3631 data_time: 0.0217 memory: 11108 grad_norm: 3.0600 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1272 loss: 3.1272 2022/10/09 07:43:35 - mmengine - INFO - Epoch(train) [9][1480/2119] lr: 3.6000e-02 eta: 1 day, 5:53:47 time: 0.3573 data_time: 0.0217 memory: 11108 grad_norm: 3.0556 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8435 loss: 2.8435 2022/10/09 07:43:42 - mmengine - INFO - Epoch(train) [9][1500/2119] lr: 3.6000e-02 eta: 1 day, 5:53:38 time: 0.3547 data_time: 0.0214 memory: 11108 grad_norm: 2.9888 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5189 loss: 2.5189 2022/10/09 07:43:49 - mmengine - INFO - Epoch(train) [9][1520/2119] lr: 3.6000e-02 eta: 1 day, 5:53:29 time: 0.3553 data_time: 0.0212 memory: 11108 grad_norm: 3.0504 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7198 loss: 2.7198 2022/10/09 07:43:57 - mmengine - INFO - Epoch(train) [9][1540/2119] lr: 3.6000e-02 eta: 1 day, 5:53:22 time: 0.3592 data_time: 0.0196 memory: 11108 grad_norm: 3.0426 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.9802 loss: 2.9802 2022/10/09 07:44:04 - mmengine - INFO - Epoch(train) [9][1560/2119] lr: 3.6000e-02 eta: 1 day, 5:53:16 time: 0.3635 data_time: 0.0201 memory: 11108 grad_norm: 3.0480 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.9694 loss: 2.9694 2022/10/09 07:44:11 - mmengine - INFO - Epoch(train) [9][1580/2119] lr: 3.6000e-02 eta: 1 day, 5:53:08 time: 0.3551 data_time: 0.0198 memory: 11108 grad_norm: 3.0910 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6340 loss: 2.6340 2022/10/09 07:44:18 - mmengine - INFO - Epoch(train) [9][1600/2119] lr: 3.6000e-02 eta: 1 day, 5:53:00 time: 0.3573 data_time: 0.0197 memory: 11108 grad_norm: 3.0969 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7270 loss: 2.7270 2022/10/09 07:44:25 - mmengine - INFO - Epoch(train) [9][1620/2119] lr: 3.6000e-02 eta: 1 day, 5:52:52 time: 0.3566 data_time: 0.0190 memory: 11108 grad_norm: 3.0039 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6621 loss: 2.6621 2022/10/09 07:44:32 - mmengine - INFO - Epoch(train) [9][1640/2119] lr: 3.6000e-02 eta: 1 day, 5:52:44 time: 0.3576 data_time: 0.0215 memory: 11108 grad_norm: 3.0169 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8144 loss: 2.8144 2022/10/09 07:44:40 - mmengine - INFO - Epoch(train) [9][1660/2119] lr: 3.6000e-02 eta: 1 day, 5:52:36 time: 0.3560 data_time: 0.0180 memory: 11108 grad_norm: 3.0299 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7389 loss: 2.7389 2022/10/09 07:44:47 - mmengine - INFO - Epoch(train) [9][1680/2119] lr: 3.6000e-02 eta: 1 day, 5:52:27 time: 0.3556 data_time: 0.0199 memory: 11108 grad_norm: 3.0276 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7153 loss: 2.7153 2022/10/09 07:44:54 - mmengine - INFO - Epoch(train) [9][1700/2119] lr: 3.6000e-02 eta: 1 day, 5:52:19 time: 0.3561 data_time: 0.0201 memory: 11108 grad_norm: 3.0856 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9665 loss: 2.9665 2022/10/09 07:45:01 - mmengine - INFO - Epoch(train) [9][1720/2119] lr: 3.6000e-02 eta: 1 day, 5:52:10 time: 0.3533 data_time: 0.0209 memory: 11108 grad_norm: 3.0383 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8370 loss: 2.8370 2022/10/09 07:45:08 - mmengine - INFO - Epoch(train) [9][1740/2119] lr: 3.6000e-02 eta: 1 day, 5:52:01 time: 0.3549 data_time: 0.0191 memory: 11108 grad_norm: 3.0246 top1_acc: 0.0625 top5_acc: 0.6250 loss_cls: 2.8537 loss: 2.8537 2022/10/09 07:45:15 - mmengine - INFO - Epoch(train) [9][1760/2119] lr: 3.6000e-02 eta: 1 day, 5:51:56 time: 0.3651 data_time: 0.0280 memory: 11108 grad_norm: 3.0390 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9520 loss: 2.9520 2022/10/09 07:45:22 - mmengine - INFO - Epoch(train) [9][1780/2119] lr: 3.6000e-02 eta: 1 day, 5:51:49 time: 0.3598 data_time: 0.0199 memory: 11108 grad_norm: 3.0347 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6562 loss: 2.6562 2022/10/09 07:45:30 - mmengine - INFO - Epoch(train) [9][1800/2119] lr: 3.6000e-02 eta: 1 day, 5:51:41 time: 0.3575 data_time: 0.0225 memory: 11108 grad_norm: 3.0048 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7275 loss: 2.7275 2022/10/09 07:45:37 - mmengine - INFO - Epoch(train) [9][1820/2119] lr: 3.6000e-02 eta: 1 day, 5:51:34 time: 0.3595 data_time: 0.0211 memory: 11108 grad_norm: 3.0860 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8982 loss: 2.8982 2022/10/09 07:45:44 - mmengine - INFO - Epoch(train) [9][1840/2119] lr: 3.6000e-02 eta: 1 day, 5:51:27 time: 0.3606 data_time: 0.0231 memory: 11108 grad_norm: 3.0442 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8382 loss: 2.8382 2022/10/09 07:45:51 - mmengine - INFO - Epoch(train) [9][1860/2119] lr: 3.6000e-02 eta: 1 day, 5:51:19 time: 0.3575 data_time: 0.0236 memory: 11108 grad_norm: 2.9864 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5771 loss: 2.5771 2022/10/09 07:45:58 - mmengine - INFO - Epoch(train) [9][1880/2119] lr: 3.6000e-02 eta: 1 day, 5:51:11 time: 0.3569 data_time: 0.0254 memory: 11108 grad_norm: 3.0272 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7285 loss: 2.7285 2022/10/09 07:46:05 - mmengine - INFO - Epoch(train) [9][1900/2119] lr: 3.6000e-02 eta: 1 day, 5:51:02 time: 0.3543 data_time: 0.0200 memory: 11108 grad_norm: 3.0090 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6989 loss: 2.6989 2022/10/09 07:46:12 - mmengine - INFO - Epoch(train) [9][1920/2119] lr: 3.6000e-02 eta: 1 day, 5:50:53 time: 0.3541 data_time: 0.0229 memory: 11108 grad_norm: 3.0688 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8672 loss: 2.8672 2022/10/09 07:46:20 - mmengine - INFO - Epoch(train) [9][1940/2119] lr: 3.6000e-02 eta: 1 day, 5:50:46 time: 0.3574 data_time: 0.0197 memory: 11108 grad_norm: 3.0197 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7920 loss: 2.7920 2022/10/09 07:46:27 - mmengine - INFO - Epoch(train) [9][1960/2119] lr: 3.6000e-02 eta: 1 day, 5:50:38 time: 0.3593 data_time: 0.0178 memory: 11108 grad_norm: 3.0581 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7543 loss: 2.7543 2022/10/09 07:46:34 - mmengine - INFO - Epoch(train) [9][1980/2119] lr: 3.6000e-02 eta: 1 day, 5:50:30 time: 0.3565 data_time: 0.0197 memory: 11108 grad_norm: 3.0464 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7181 loss: 2.7181 2022/10/09 07:46:41 - mmengine - INFO - Epoch(train) [9][2000/2119] lr: 3.6000e-02 eta: 1 day, 5:50:22 time: 0.3547 data_time: 0.0191 memory: 11108 grad_norm: 3.0407 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0225 loss: 3.0225 2022/10/09 07:46:48 - mmengine - INFO - Epoch(train) [9][2020/2119] lr: 3.6000e-02 eta: 1 day, 5:50:14 time: 0.3584 data_time: 0.0207 memory: 11108 grad_norm: 3.0490 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7168 loss: 2.7168 2022/10/09 07:46:55 - mmengine - INFO - Epoch(train) [9][2040/2119] lr: 3.6000e-02 eta: 1 day, 5:50:06 time: 0.3556 data_time: 0.0208 memory: 11108 grad_norm: 3.0230 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.5334 loss: 2.5334 2022/10/09 07:46:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 07:47:03 - mmengine - INFO - Epoch(train) [9][2060/2119] lr: 3.6000e-02 eta: 1 day, 5:49:58 time: 0.3592 data_time: 0.0216 memory: 11108 grad_norm: 3.0414 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5137 loss: 2.5137 2022/10/09 07:47:10 - mmengine - INFO - Epoch(train) [9][2080/2119] lr: 3.6000e-02 eta: 1 day, 5:49:50 time: 0.3550 data_time: 0.0204 memory: 11108 grad_norm: 2.9855 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8800 loss: 2.8800 2022/10/09 07:47:17 - mmengine - INFO - Epoch(train) [9][2100/2119] lr: 3.6000e-02 eta: 1 day, 5:49:43 time: 0.3606 data_time: 0.0201 memory: 11108 grad_norm: 3.0102 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9739 loss: 2.9739 2022/10/09 07:47:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 07:47:23 - mmengine - INFO - Epoch(train) [9][2119/2119] lr: 3.6000e-02 eta: 1 day, 5:49:43 time: 0.3464 data_time: 0.0204 memory: 11108 grad_norm: 3.0320 top1_acc: 0.3000 top5_acc: 0.5000 loss_cls: 2.9534 loss: 2.9534 2022/10/09 07:47:34 - mmengine - INFO - Epoch(train) [10][20/2119] lr: 4.0000e-02 eta: 1 day, 5:48:41 time: 0.5462 data_time: 0.1481 memory: 11108 grad_norm: 2.9546 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6439 loss: 2.6439 2022/10/09 07:47:42 - mmengine - INFO - Epoch(train) [10][40/2119] lr: 4.0000e-02 eta: 1 day, 5:48:34 time: 0.3612 data_time: 0.0202 memory: 11108 grad_norm: 3.0132 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7041 loss: 2.7041 2022/10/09 07:47:49 - mmengine - INFO - Epoch(train) [10][60/2119] lr: 4.0000e-02 eta: 1 day, 5:48:26 time: 0.3562 data_time: 0.0184 memory: 11108 grad_norm: 3.0567 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9161 loss: 2.9161 2022/10/09 07:47:56 - mmengine - INFO - Epoch(train) [10][80/2119] lr: 4.0000e-02 eta: 1 day, 5:48:19 time: 0.3600 data_time: 0.0213 memory: 11108 grad_norm: 3.0578 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7252 loss: 2.7252 2022/10/09 07:48:03 - mmengine - INFO - Epoch(train) [10][100/2119] lr: 4.0000e-02 eta: 1 day, 5:48:11 time: 0.3557 data_time: 0.0198 memory: 11108 grad_norm: 3.0866 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0430 loss: 3.0430 2022/10/09 07:48:10 - mmengine - INFO - Epoch(train) [10][120/2119] lr: 4.0000e-02 eta: 1 day, 5:48:03 time: 0.3585 data_time: 0.0196 memory: 11108 grad_norm: 3.0331 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9135 loss: 2.9135 2022/10/09 07:48:17 - mmengine - INFO - Epoch(train) [10][140/2119] lr: 4.0000e-02 eta: 1 day, 5:47:55 time: 0.3547 data_time: 0.0193 memory: 11108 grad_norm: 3.0324 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8853 loss: 2.8853 2022/10/09 07:48:25 - mmengine - INFO - Epoch(train) [10][160/2119] lr: 4.0000e-02 eta: 1 day, 5:47:48 time: 0.3620 data_time: 0.0246 memory: 11108 grad_norm: 3.0017 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6764 loss: 2.6764 2022/10/09 07:48:32 - mmengine - INFO - Epoch(train) [10][180/2119] lr: 4.0000e-02 eta: 1 day, 5:47:39 time: 0.3527 data_time: 0.0180 memory: 11108 grad_norm: 3.0192 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8406 loss: 2.8406 2022/10/09 07:48:39 - mmengine - INFO - Epoch(train) [10][200/2119] lr: 4.0000e-02 eta: 1 day, 5:47:33 time: 0.3616 data_time: 0.0218 memory: 11108 grad_norm: 3.0107 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7388 loss: 2.7388 2022/10/09 07:48:46 - mmengine - INFO - Epoch(train) [10][220/2119] lr: 4.0000e-02 eta: 1 day, 5:47:26 time: 0.3620 data_time: 0.0215 memory: 11108 grad_norm: 3.0708 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.7035 loss: 2.7035 2022/10/09 07:48:53 - mmengine - INFO - Epoch(train) [10][240/2119] lr: 4.0000e-02 eta: 1 day, 5:47:19 time: 0.3582 data_time: 0.0234 memory: 11108 grad_norm: 3.0447 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7718 loss: 2.7718 2022/10/09 07:49:00 - mmengine - INFO - Epoch(train) [10][260/2119] lr: 4.0000e-02 eta: 1 day, 5:47:11 time: 0.3560 data_time: 0.0207 memory: 11108 grad_norm: 2.9398 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0217 loss: 3.0217 2022/10/09 07:49:08 - mmengine - INFO - Epoch(train) [10][280/2119] lr: 4.0000e-02 eta: 1 day, 5:47:04 time: 0.3606 data_time: 0.0227 memory: 11108 grad_norm: 2.9635 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7635 loss: 2.7635 2022/10/09 07:49:15 - mmengine - INFO - Epoch(train) [10][300/2119] lr: 4.0000e-02 eta: 1 day, 5:46:56 time: 0.3574 data_time: 0.0189 memory: 11108 grad_norm: 3.0177 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7366 loss: 2.7366 2022/10/09 07:49:22 - mmengine - INFO - Epoch(train) [10][320/2119] lr: 4.0000e-02 eta: 1 day, 5:46:50 time: 0.3605 data_time: 0.0187 memory: 11108 grad_norm: 3.0661 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6306 loss: 2.6306 2022/10/09 07:49:29 - mmengine - INFO - Epoch(train) [10][340/2119] lr: 4.0000e-02 eta: 1 day, 5:46:41 time: 0.3551 data_time: 0.0204 memory: 11108 grad_norm: 3.0068 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9318 loss: 2.9318 2022/10/09 07:49:36 - mmengine - INFO - Epoch(train) [10][360/2119] lr: 4.0000e-02 eta: 1 day, 5:46:33 time: 0.3578 data_time: 0.0191 memory: 11108 grad_norm: 3.0044 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.2273 loss: 3.2273 2022/10/09 07:49:43 - mmengine - INFO - Epoch(train) [10][380/2119] lr: 4.0000e-02 eta: 1 day, 5:46:27 time: 0.3607 data_time: 0.0216 memory: 11108 grad_norm: 2.9649 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7686 loss: 2.7686 2022/10/09 07:49:50 - mmengine - INFO - Epoch(train) [10][400/2119] lr: 4.0000e-02 eta: 1 day, 5:46:17 time: 0.3525 data_time: 0.0232 memory: 11108 grad_norm: 3.0624 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8746 loss: 2.8746 2022/10/09 07:49:58 - mmengine - INFO - Epoch(train) [10][420/2119] lr: 4.0000e-02 eta: 1 day, 5:46:11 time: 0.3610 data_time: 0.0222 memory: 11108 grad_norm: 3.0009 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8285 loss: 2.8285 2022/10/09 07:50:05 - mmengine - INFO - Epoch(train) [10][440/2119] lr: 4.0000e-02 eta: 1 day, 5:46:04 time: 0.3619 data_time: 0.0217 memory: 11108 grad_norm: 3.0200 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7696 loss: 2.7696 2022/10/09 07:50:12 - mmengine - INFO - Epoch(train) [10][460/2119] lr: 4.0000e-02 eta: 1 day, 5:45:57 time: 0.3570 data_time: 0.0187 memory: 11108 grad_norm: 2.9965 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6421 loss: 2.6421 2022/10/09 07:50:19 - mmengine - INFO - Epoch(train) [10][480/2119] lr: 4.0000e-02 eta: 1 day, 5:45:49 time: 0.3581 data_time: 0.0218 memory: 11108 grad_norm: 2.9558 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7814 loss: 2.7814 2022/10/09 07:50:26 - mmengine - INFO - Epoch(train) [10][500/2119] lr: 4.0000e-02 eta: 1 day, 5:45:42 time: 0.3597 data_time: 0.0238 memory: 11108 grad_norm: 2.9998 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0196 loss: 3.0196 2022/10/09 07:50:34 - mmengine - INFO - Epoch(train) [10][520/2119] lr: 4.0000e-02 eta: 1 day, 5:45:35 time: 0.3584 data_time: 0.0185 memory: 11108 grad_norm: 3.0033 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8494 loss: 2.8494 2022/10/09 07:50:41 - mmengine - INFO - Epoch(train) [10][540/2119] lr: 4.0000e-02 eta: 1 day, 5:45:26 time: 0.3543 data_time: 0.0224 memory: 11108 grad_norm: 2.9796 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9243 loss: 2.9243 2022/10/09 07:50:48 - mmengine - INFO - Epoch(train) [10][560/2119] lr: 4.0000e-02 eta: 1 day, 5:45:18 time: 0.3576 data_time: 0.0210 memory: 11108 grad_norm: 2.9627 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7048 loss: 2.7048 2022/10/09 07:50:55 - mmengine - INFO - Epoch(train) [10][580/2119] lr: 4.0000e-02 eta: 1 day, 5:45:10 time: 0.3554 data_time: 0.0206 memory: 11108 grad_norm: 3.0669 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7829 loss: 2.7829 2022/10/09 07:51:02 - mmengine - INFO - Epoch(train) [10][600/2119] lr: 4.0000e-02 eta: 1 day, 5:45:03 time: 0.3590 data_time: 0.0205 memory: 11108 grad_norm: 3.0261 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0054 loss: 3.0054 2022/10/09 07:51:09 - mmengine - INFO - Epoch(train) [10][620/2119] lr: 4.0000e-02 eta: 1 day, 5:44:57 time: 0.3626 data_time: 0.0217 memory: 11108 grad_norm: 2.9770 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7608 loss: 2.7608 2022/10/09 07:51:16 - mmengine - INFO - Epoch(train) [10][640/2119] lr: 4.0000e-02 eta: 1 day, 5:44:48 time: 0.3545 data_time: 0.0191 memory: 11108 grad_norm: 2.9417 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9480 loss: 2.9480 2022/10/09 07:51:24 - mmengine - INFO - Epoch(train) [10][660/2119] lr: 4.0000e-02 eta: 1 day, 5:44:40 time: 0.3561 data_time: 0.0200 memory: 11108 grad_norm: 2.9918 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8783 loss: 2.8783 2022/10/09 07:51:31 - mmengine - INFO - Epoch(train) [10][680/2119] lr: 4.0000e-02 eta: 1 day, 5:44:32 time: 0.3559 data_time: 0.0187 memory: 11108 grad_norm: 3.0241 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7325 loss: 2.7325 2022/10/09 07:51:38 - mmengine - INFO - Epoch(train) [10][700/2119] lr: 4.0000e-02 eta: 1 day, 5:44:24 time: 0.3568 data_time: 0.0198 memory: 11108 grad_norm: 3.0458 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6688 loss: 2.6688 2022/10/09 07:51:45 - mmengine - INFO - Epoch(train) [10][720/2119] lr: 4.0000e-02 eta: 1 day, 5:44:16 time: 0.3571 data_time: 0.0257 memory: 11108 grad_norm: 2.9802 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7988 loss: 2.7988 2022/10/09 07:51:52 - mmengine - INFO - Epoch(train) [10][740/2119] lr: 4.0000e-02 eta: 1 day, 5:44:06 time: 0.3514 data_time: 0.0213 memory: 11108 grad_norm: 2.9327 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7814 loss: 2.7814 2022/10/09 07:51:59 - mmengine - INFO - Epoch(train) [10][760/2119] lr: 4.0000e-02 eta: 1 day, 5:43:58 time: 0.3555 data_time: 0.0187 memory: 11108 grad_norm: 2.9472 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8587 loss: 2.8587 2022/10/09 07:52:06 - mmengine - INFO - Epoch(train) [10][780/2119] lr: 4.0000e-02 eta: 1 day, 5:43:51 time: 0.3593 data_time: 0.0235 memory: 11108 grad_norm: 2.9987 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4933 loss: 2.4933 2022/10/09 07:52:13 - mmengine - INFO - Epoch(train) [10][800/2119] lr: 4.0000e-02 eta: 1 day, 5:43:43 time: 0.3548 data_time: 0.0181 memory: 11108 grad_norm: 2.9655 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7521 loss: 2.7521 2022/10/09 07:52:21 - mmengine - INFO - Epoch(train) [10][820/2119] lr: 4.0000e-02 eta: 1 day, 5:43:34 time: 0.3560 data_time: 0.0273 memory: 11108 grad_norm: 2.9915 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8578 loss: 2.8578 2022/10/09 07:52:28 - mmengine - INFO - Epoch(train) [10][840/2119] lr: 4.0000e-02 eta: 1 day, 5:43:28 time: 0.3619 data_time: 0.0188 memory: 11108 grad_norm: 2.9919 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7315 loss: 2.7315 2022/10/09 07:52:35 - mmengine - INFO - Epoch(train) [10][860/2119] lr: 4.0000e-02 eta: 1 day, 5:43:21 time: 0.3599 data_time: 0.0228 memory: 11108 grad_norm: 2.9760 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8292 loss: 2.8292 2022/10/09 07:52:42 - mmengine - INFO - Epoch(train) [10][880/2119] lr: 4.0000e-02 eta: 1 day, 5:43:13 time: 0.3545 data_time: 0.0261 memory: 11108 grad_norm: 2.9173 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6726 loss: 2.6726 2022/10/09 07:52:49 - mmengine - INFO - Epoch(train) [10][900/2119] lr: 4.0000e-02 eta: 1 day, 5:43:06 time: 0.3598 data_time: 0.0164 memory: 11108 grad_norm: 2.9141 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8244 loss: 2.8244 2022/10/09 07:52:56 - mmengine - INFO - Epoch(train) [10][920/2119] lr: 4.0000e-02 eta: 1 day, 5:42:58 time: 0.3565 data_time: 0.0202 memory: 11108 grad_norm: 2.9715 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9079 loss: 2.9079 2022/10/09 07:53:00 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 07:53:04 - mmengine - INFO - Epoch(train) [10][940/2119] lr: 4.0000e-02 eta: 1 day, 5:42:53 time: 0.3666 data_time: 0.0215 memory: 11108 grad_norm: 2.9618 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8597 loss: 2.8597 2022/10/09 07:53:11 - mmengine - INFO - Epoch(train) [10][960/2119] lr: 4.0000e-02 eta: 1 day, 5:42:44 time: 0.3557 data_time: 0.0184 memory: 11108 grad_norm: 2.9705 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6890 loss: 2.6890 2022/10/09 07:53:18 - mmengine - INFO - Epoch(train) [10][980/2119] lr: 4.0000e-02 eta: 1 day, 5:42:37 time: 0.3578 data_time: 0.0177 memory: 11108 grad_norm: 2.9773 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9005 loss: 2.9005 2022/10/09 07:53:25 - mmengine - INFO - Epoch(train) [10][1000/2119] lr: 4.0000e-02 eta: 1 day, 5:42:33 time: 0.3709 data_time: 0.0196 memory: 11108 grad_norm: 2.9527 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7520 loss: 2.7520 2022/10/09 07:53:32 - mmengine - INFO - Epoch(train) [10][1020/2119] lr: 4.0000e-02 eta: 1 day, 5:42:24 time: 0.3537 data_time: 0.0211 memory: 11108 grad_norm: 2.9441 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6847 loss: 2.6847 2022/10/09 07:53:40 - mmengine - INFO - Epoch(train) [10][1040/2119] lr: 4.0000e-02 eta: 1 day, 5:42:18 time: 0.3607 data_time: 0.0252 memory: 11108 grad_norm: 2.9207 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9961 loss: 2.9961 2022/10/09 07:53:47 - mmengine - INFO - Epoch(train) [10][1060/2119] lr: 4.0000e-02 eta: 1 day, 5:42:13 time: 0.3684 data_time: 0.0208 memory: 11108 grad_norm: 2.9356 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0020 loss: 3.0020 2022/10/09 07:53:54 - mmengine - INFO - Epoch(train) [10][1080/2119] lr: 4.0000e-02 eta: 1 day, 5:42:04 time: 0.3538 data_time: 0.0253 memory: 11108 grad_norm: 2.9647 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1965 loss: 3.1965 2022/10/09 07:54:01 - mmengine - INFO - Epoch(train) [10][1100/2119] lr: 4.0000e-02 eta: 1 day, 5:41:56 time: 0.3551 data_time: 0.0224 memory: 11108 grad_norm: 2.9781 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6250 loss: 2.6250 2022/10/09 07:54:08 - mmengine - INFO - Epoch(train) [10][1120/2119] lr: 4.0000e-02 eta: 1 day, 5:41:49 time: 0.3612 data_time: 0.0172 memory: 11108 grad_norm: 2.9682 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.1240 loss: 3.1240 2022/10/09 07:54:16 - mmengine - INFO - Epoch(train) [10][1140/2119] lr: 4.0000e-02 eta: 1 day, 5:41:41 time: 0.3555 data_time: 0.0179 memory: 11108 grad_norm: 2.9954 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8141 loss: 2.8141 2022/10/09 07:54:23 - mmengine - INFO - Epoch(train) [10][1160/2119] lr: 4.0000e-02 eta: 1 day, 5:41:34 time: 0.3601 data_time: 0.0240 memory: 11108 grad_norm: 2.9673 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.7940 loss: 2.7940 2022/10/09 07:54:30 - mmengine - INFO - Epoch(train) [10][1180/2119] lr: 4.0000e-02 eta: 1 day, 5:41:26 time: 0.3556 data_time: 0.0194 memory: 11108 grad_norm: 2.9775 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9253 loss: 2.9253 2022/10/09 07:54:37 - mmengine - INFO - Epoch(train) [10][1200/2119] lr: 4.0000e-02 eta: 1 day, 5:41:18 time: 0.3579 data_time: 0.0220 memory: 11108 grad_norm: 2.9669 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8490 loss: 2.8490 2022/10/09 07:54:44 - mmengine - INFO - Epoch(train) [10][1220/2119] lr: 4.0000e-02 eta: 1 day, 5:41:11 time: 0.3577 data_time: 0.0202 memory: 11108 grad_norm: 2.9765 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6221 loss: 2.6221 2022/10/09 07:54:51 - mmengine - INFO - Epoch(train) [10][1240/2119] lr: 4.0000e-02 eta: 1 day, 5:41:03 time: 0.3571 data_time: 0.0192 memory: 11108 grad_norm: 3.0257 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8639 loss: 2.8639 2022/10/09 07:54:58 - mmengine - INFO - Epoch(train) [10][1260/2119] lr: 4.0000e-02 eta: 1 day, 5:40:55 time: 0.3562 data_time: 0.0208 memory: 11108 grad_norm: 3.0038 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9940 loss: 2.9940 2022/10/09 07:55:06 - mmengine - INFO - Epoch(train) [10][1280/2119] lr: 4.0000e-02 eta: 1 day, 5:40:49 time: 0.3632 data_time: 0.0200 memory: 11108 grad_norm: 2.9962 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9587 loss: 2.9587 2022/10/09 07:55:13 - mmengine - INFO - Epoch(train) [10][1300/2119] lr: 4.0000e-02 eta: 1 day, 5:40:40 time: 0.3534 data_time: 0.0240 memory: 11108 grad_norm: 2.9311 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 3.0419 loss: 3.0419 2022/10/09 07:55:20 - mmengine - INFO - Epoch(train) [10][1320/2119] lr: 4.0000e-02 eta: 1 day, 5:40:32 time: 0.3573 data_time: 0.0196 memory: 11108 grad_norm: 2.9338 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8240 loss: 2.8240 2022/10/09 07:55:27 - mmengine - INFO - Epoch(train) [10][1340/2119] lr: 4.0000e-02 eta: 1 day, 5:40:27 time: 0.3648 data_time: 0.0202 memory: 11108 grad_norm: 2.9328 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 3.2253 loss: 3.2253 2022/10/09 07:55:34 - mmengine - INFO - Epoch(train) [10][1360/2119] lr: 4.0000e-02 eta: 1 day, 5:40:18 time: 0.3530 data_time: 0.0198 memory: 11108 grad_norm: 2.9183 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7876 loss: 2.7876 2022/10/09 07:55:41 - mmengine - INFO - Epoch(train) [10][1380/2119] lr: 4.0000e-02 eta: 1 day, 5:40:09 time: 0.3546 data_time: 0.0203 memory: 11108 grad_norm: 2.9401 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9458 loss: 2.9458 2022/10/09 07:55:49 - mmengine - INFO - Epoch(train) [10][1400/2119] lr: 4.0000e-02 eta: 1 day, 5:40:03 time: 0.3635 data_time: 0.0212 memory: 11108 grad_norm: 2.9445 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9159 loss: 2.9159 2022/10/09 07:55:56 - mmengine - INFO - Epoch(train) [10][1420/2119] lr: 4.0000e-02 eta: 1 day, 5:39:56 time: 0.3588 data_time: 0.0217 memory: 11108 grad_norm: 2.9555 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8185 loss: 2.8185 2022/10/09 07:56:03 - mmengine - INFO - Epoch(train) [10][1440/2119] lr: 4.0000e-02 eta: 1 day, 5:39:48 time: 0.3577 data_time: 0.0234 memory: 11108 grad_norm: 2.9487 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8090 loss: 2.8090 2022/10/09 07:56:10 - mmengine - INFO - Epoch(train) [10][1460/2119] lr: 4.0000e-02 eta: 1 day, 5:39:41 time: 0.3572 data_time: 0.0208 memory: 11108 grad_norm: 2.9014 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8529 loss: 2.8529 2022/10/09 07:56:17 - mmengine - INFO - Epoch(train) [10][1480/2119] lr: 4.0000e-02 eta: 1 day, 5:39:35 time: 0.3626 data_time: 0.0239 memory: 11108 grad_norm: 2.9139 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9008 loss: 2.9008 2022/10/09 07:56:25 - mmengine - INFO - Epoch(train) [10][1500/2119] lr: 4.0000e-02 eta: 1 day, 5:39:27 time: 0.3593 data_time: 0.0215 memory: 11108 grad_norm: 2.9257 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7941 loss: 2.7941 2022/10/09 07:56:32 - mmengine - INFO - Epoch(train) [10][1520/2119] lr: 4.0000e-02 eta: 1 day, 5:39:19 time: 0.3546 data_time: 0.0199 memory: 11108 grad_norm: 2.9629 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8524 loss: 2.8524 2022/10/09 07:56:39 - mmengine - INFO - Epoch(train) [10][1540/2119] lr: 4.0000e-02 eta: 1 day, 5:39:12 time: 0.3599 data_time: 0.0195 memory: 11108 grad_norm: 2.9186 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8294 loss: 2.8294 2022/10/09 07:56:46 - mmengine - INFO - Epoch(train) [10][1560/2119] lr: 4.0000e-02 eta: 1 day, 5:39:05 time: 0.3615 data_time: 0.0212 memory: 11108 grad_norm: 2.9271 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7655 loss: 2.7655 2022/10/09 07:56:53 - mmengine - INFO - Epoch(train) [10][1580/2119] lr: 4.0000e-02 eta: 1 day, 5:38:58 time: 0.3576 data_time: 0.0274 memory: 11108 grad_norm: 2.9459 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9179 loss: 2.9179 2022/10/09 07:57:00 - mmengine - INFO - Epoch(train) [10][1600/2119] lr: 4.0000e-02 eta: 1 day, 5:38:51 time: 0.3590 data_time: 0.0215 memory: 11108 grad_norm: 2.9377 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7810 loss: 2.7810 2022/10/09 07:57:08 - mmengine - INFO - Epoch(train) [10][1620/2119] lr: 4.0000e-02 eta: 1 day, 5:38:43 time: 0.3579 data_time: 0.0198 memory: 11108 grad_norm: 2.9432 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.1069 loss: 3.1069 2022/10/09 07:57:15 - mmengine - INFO - Epoch(train) [10][1640/2119] lr: 4.0000e-02 eta: 1 day, 5:38:35 time: 0.3573 data_time: 0.0237 memory: 11108 grad_norm: 2.9318 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.8611 loss: 2.8611 2022/10/09 07:57:22 - mmengine - INFO - Epoch(train) [10][1660/2119] lr: 4.0000e-02 eta: 1 day, 5:38:27 time: 0.3551 data_time: 0.0177 memory: 11108 grad_norm: 2.9427 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8182 loss: 2.8182 2022/10/09 07:57:29 - mmengine - INFO - Epoch(train) [10][1680/2119] lr: 4.0000e-02 eta: 1 day, 5:38:19 time: 0.3579 data_time: 0.0237 memory: 11108 grad_norm: 2.9454 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8217 loss: 2.8217 2022/10/09 07:57:36 - mmengine - INFO - Epoch(train) [10][1700/2119] lr: 4.0000e-02 eta: 1 day, 5:38:12 time: 0.3582 data_time: 0.0220 memory: 11108 grad_norm: 2.9492 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9238 loss: 2.9238 2022/10/09 07:57:43 - mmengine - INFO - Epoch(train) [10][1720/2119] lr: 4.0000e-02 eta: 1 day, 5:38:03 time: 0.3522 data_time: 0.0182 memory: 11108 grad_norm: 2.9306 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8117 loss: 2.8117 2022/10/09 07:57:50 - mmengine - INFO - Epoch(train) [10][1740/2119] lr: 4.0000e-02 eta: 1 day, 5:37:56 time: 0.3602 data_time: 0.0200 memory: 11108 grad_norm: 2.9820 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8348 loss: 2.8348 2022/10/09 07:57:58 - mmengine - INFO - Epoch(train) [10][1760/2119] lr: 4.0000e-02 eta: 1 day, 5:37:49 time: 0.3598 data_time: 0.0205 memory: 11108 grad_norm: 2.9132 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7283 loss: 2.7283 2022/10/09 07:58:05 - mmengine - INFO - Epoch(train) [10][1780/2119] lr: 4.0000e-02 eta: 1 day, 5:37:44 time: 0.3658 data_time: 0.0195 memory: 11108 grad_norm: 2.9552 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.7654 loss: 2.7654 2022/10/09 07:58:12 - mmengine - INFO - Epoch(train) [10][1800/2119] lr: 4.0000e-02 eta: 1 day, 5:37:36 time: 0.3584 data_time: 0.0188 memory: 11108 grad_norm: 2.9412 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0509 loss: 3.0509 2022/10/09 07:58:19 - mmengine - INFO - Epoch(train) [10][1820/2119] lr: 4.0000e-02 eta: 1 day, 5:37:29 time: 0.3577 data_time: 0.0235 memory: 11108 grad_norm: 2.8947 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7380 loss: 2.7380 2022/10/09 07:58:26 - mmengine - INFO - Epoch(train) [10][1840/2119] lr: 4.0000e-02 eta: 1 day, 5:37:20 time: 0.3550 data_time: 0.0206 memory: 11108 grad_norm: 2.9749 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7086 loss: 2.7086 2022/10/09 07:58:34 - mmengine - INFO - Epoch(train) [10][1860/2119] lr: 4.0000e-02 eta: 1 day, 5:37:13 time: 0.3583 data_time: 0.0176 memory: 11108 grad_norm: 2.9353 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.7792 loss: 2.7792 2022/10/09 07:58:41 - mmengine - INFO - Epoch(train) [10][1880/2119] lr: 4.0000e-02 eta: 1 day, 5:37:06 time: 0.3588 data_time: 0.0238 memory: 11108 grad_norm: 2.9174 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5618 loss: 2.5618 2022/10/09 07:58:48 - mmengine - INFO - Epoch(train) [10][1900/2119] lr: 4.0000e-02 eta: 1 day, 5:36:58 time: 0.3572 data_time: 0.0247 memory: 11108 grad_norm: 2.9073 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7584 loss: 2.7584 2022/10/09 07:58:55 - mmengine - INFO - Epoch(train) [10][1920/2119] lr: 4.0000e-02 eta: 1 day, 5:36:51 time: 0.3593 data_time: 0.0270 memory: 11108 grad_norm: 2.9535 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7939 loss: 2.7939 2022/10/09 07:58:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 07:59:02 - mmengine - INFO - Epoch(train) [10][1940/2119] lr: 4.0000e-02 eta: 1 day, 5:36:43 time: 0.3563 data_time: 0.0223 memory: 11108 grad_norm: 2.9336 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0118 loss: 3.0118 2022/10/09 07:59:09 - mmengine - INFO - Epoch(train) [10][1960/2119] lr: 4.0000e-02 eta: 1 day, 5:36:35 time: 0.3571 data_time: 0.0175 memory: 11108 grad_norm: 2.9223 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8260 loss: 2.8260 2022/10/09 07:59:17 - mmengine - INFO - Epoch(train) [10][1980/2119] lr: 4.0000e-02 eta: 1 day, 5:36:28 time: 0.3594 data_time: 0.0205 memory: 11108 grad_norm: 2.9208 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.8085 loss: 2.8085 2022/10/09 07:59:24 - mmengine - INFO - Epoch(train) [10][2000/2119] lr: 4.0000e-02 eta: 1 day, 5:36:22 time: 0.3620 data_time: 0.0230 memory: 11108 grad_norm: 2.9552 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8697 loss: 2.8697 2022/10/09 07:59:31 - mmengine - INFO - Epoch(train) [10][2020/2119] lr: 4.0000e-02 eta: 1 day, 5:36:15 time: 0.3619 data_time: 0.0232 memory: 11108 grad_norm: 2.9320 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0373 loss: 3.0373 2022/10/09 07:59:38 - mmengine - INFO - Epoch(train) [10][2040/2119] lr: 4.0000e-02 eta: 1 day, 5:36:08 time: 0.3576 data_time: 0.0236 memory: 11108 grad_norm: 2.8907 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8822 loss: 2.8822 2022/10/09 07:59:45 - mmengine - INFO - Epoch(train) [10][2060/2119] lr: 4.0000e-02 eta: 1 day, 5:36:02 time: 0.3653 data_time: 0.0211 memory: 11108 grad_norm: 2.9285 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0821 loss: 3.0821 2022/10/09 07:59:53 - mmengine - INFO - Epoch(train) [10][2080/2119] lr: 4.0000e-02 eta: 1 day, 5:35:54 time: 0.3552 data_time: 0.0198 memory: 11108 grad_norm: 2.8509 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8632 loss: 2.8632 2022/10/09 08:00:00 - mmengine - INFO - Epoch(train) [10][2100/2119] lr: 4.0000e-02 eta: 1 day, 5:35:47 time: 0.3619 data_time: 0.0181 memory: 11108 grad_norm: 2.8741 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8162 loss: 2.8162 2022/10/09 08:00:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 08:00:06 - mmengine - INFO - Epoch(train) [10][2119/2119] lr: 4.0000e-02 eta: 1 day, 5:35:47 time: 0.3438 data_time: 0.0189 memory: 11108 grad_norm: 2.9543 top1_acc: 0.6000 top5_acc: 0.7000 loss_cls: 2.6606 loss: 2.6606 2022/10/09 08:00:13 - mmengine - INFO - Epoch(val) [10][20/137] eta: 0:00:40 time: 0.3491 data_time: 0.2307 memory: 1961 2022/10/09 08:00:18 - mmengine - INFO - Epoch(val) [10][40/137] eta: 0:00:25 time: 0.2590 data_time: 0.1446 memory: 1961 2022/10/09 08:00:24 - mmengine - INFO - Epoch(val) [10][60/137] eta: 0:00:22 time: 0.2913 data_time: 0.1741 memory: 1961 2022/10/09 08:00:29 - mmengine - INFO - Epoch(val) [10][80/137] eta: 0:00:13 time: 0.2357 data_time: 0.1221 memory: 1961 2022/10/09 08:00:35 - mmengine - INFO - Epoch(val) [10][100/137] eta: 0:00:11 time: 0.3076 data_time: 0.1937 memory: 1961 2022/10/09 08:00:40 - mmengine - INFO - Epoch(val) [10][120/137] eta: 0:00:03 time: 0.2214 data_time: 0.1061 memory: 1961 2022/10/09 08:00:56 - mmengine - INFO - Epoch(val) [10][137/137] acc/top1: 0.4212 acc/top5: 0.6678 acc/mean1: 0.4211 2022/10/09 08:00:56 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb.py/best_acc/top1_epoch_5.pth is removed 2022/10/09 08:00:58 - mmengine - INFO - The best checkpoint with 0.4212 acc/top1 at 10 epoch is saved to best_acc/top1_epoch_10.pth. 2022/10/09 08:01:08 - mmengine - INFO - Epoch(train) [11][20/2119] lr: 4.0000e-02 eta: 1 day, 5:34:30 time: 0.4738 data_time: 0.1263 memory: 11108 grad_norm: 2.8797 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5666 loss: 2.5666 2022/10/09 08:01:15 - mmengine - INFO - Epoch(train) [11][40/2119] lr: 4.0000e-02 eta: 1 day, 5:34:24 time: 0.3622 data_time: 0.0215 memory: 11108 grad_norm: 2.8936 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6792 loss: 2.6792 2022/10/09 08:01:22 - mmengine - INFO - Epoch(train) [11][60/2119] lr: 4.0000e-02 eta: 1 day, 5:34:16 time: 0.3564 data_time: 0.0223 memory: 11108 grad_norm: 2.9662 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7511 loss: 2.7511 2022/10/09 08:01:29 - mmengine - INFO - Epoch(train) [11][80/2119] lr: 4.0000e-02 eta: 1 day, 5:34:08 time: 0.3570 data_time: 0.0205 memory: 11108 grad_norm: 2.9453 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0827 loss: 3.0827 2022/10/09 08:01:36 - mmengine - INFO - Epoch(train) [11][100/2119] lr: 4.0000e-02 eta: 1 day, 5:34:02 time: 0.3628 data_time: 0.0188 memory: 11108 grad_norm: 2.9358 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7261 loss: 2.7261 2022/10/09 08:01:44 - mmengine - INFO - Epoch(train) [11][120/2119] lr: 4.0000e-02 eta: 1 day, 5:33:54 time: 0.3552 data_time: 0.0198 memory: 11108 grad_norm: 2.9928 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7834 loss: 2.7834 2022/10/09 08:01:51 - mmengine - INFO - Epoch(train) [11][140/2119] lr: 4.0000e-02 eta: 1 day, 5:33:47 time: 0.3597 data_time: 0.0223 memory: 11108 grad_norm: 2.9280 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9195 loss: 2.9195 2022/10/09 08:01:58 - mmengine - INFO - Epoch(train) [11][160/2119] lr: 4.0000e-02 eta: 1 day, 5:33:41 time: 0.3643 data_time: 0.0208 memory: 11108 grad_norm: 2.9821 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8640 loss: 2.8640 2022/10/09 08:02:05 - mmengine - INFO - Epoch(train) [11][180/2119] lr: 4.0000e-02 eta: 1 day, 5:33:33 time: 0.3545 data_time: 0.0160 memory: 11108 grad_norm: 2.8673 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8148 loss: 2.8148 2022/10/09 08:02:12 - mmengine - INFO - Epoch(train) [11][200/2119] lr: 4.0000e-02 eta: 1 day, 5:33:25 time: 0.3565 data_time: 0.0180 memory: 11108 grad_norm: 2.8725 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8969 loss: 2.8969 2022/10/09 08:02:19 - mmengine - INFO - Epoch(train) [11][220/2119] lr: 4.0000e-02 eta: 1 day, 5:33:18 time: 0.3584 data_time: 0.0177 memory: 11108 grad_norm: 2.9191 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8567 loss: 2.8567 2022/10/09 08:02:27 - mmengine - INFO - Epoch(train) [11][240/2119] lr: 4.0000e-02 eta: 1 day, 5:33:10 time: 0.3575 data_time: 0.0247 memory: 11108 grad_norm: 2.8727 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8090 loss: 2.8090 2022/10/09 08:02:34 - mmengine - INFO - Epoch(train) [11][260/2119] lr: 4.0000e-02 eta: 1 day, 5:33:01 time: 0.3520 data_time: 0.0228 memory: 11108 grad_norm: 2.8899 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 3.0935 loss: 3.0935 2022/10/09 08:02:41 - mmengine - INFO - Epoch(train) [11][280/2119] lr: 4.0000e-02 eta: 1 day, 5:32:53 time: 0.3546 data_time: 0.0207 memory: 11108 grad_norm: 2.8659 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6766 loss: 2.6766 2022/10/09 08:02:48 - mmengine - INFO - Epoch(train) [11][300/2119] lr: 4.0000e-02 eta: 1 day, 5:32:44 time: 0.3557 data_time: 0.0210 memory: 11108 grad_norm: 2.9308 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5471 loss: 2.5471 2022/10/09 08:02:55 - mmengine - INFO - Epoch(train) [11][320/2119] lr: 4.0000e-02 eta: 1 day, 5:32:38 time: 0.3601 data_time: 0.0196 memory: 11108 grad_norm: 2.8972 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7663 loss: 2.7663 2022/10/09 08:03:02 - mmengine - INFO - Epoch(train) [11][340/2119] lr: 4.0000e-02 eta: 1 day, 5:32:30 time: 0.3572 data_time: 0.0231 memory: 11108 grad_norm: 2.9139 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6916 loss: 2.6916 2022/10/09 08:03:09 - mmengine - INFO - Epoch(train) [11][360/2119] lr: 4.0000e-02 eta: 1 day, 5:32:23 time: 0.3597 data_time: 0.0210 memory: 11108 grad_norm: 2.8773 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8495 loss: 2.8495 2022/10/09 08:03:16 - mmengine - INFO - Epoch(train) [11][380/2119] lr: 4.0000e-02 eta: 1 day, 5:32:15 time: 0.3575 data_time: 0.0209 memory: 11108 grad_norm: 2.9122 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0489 loss: 3.0489 2022/10/09 08:03:24 - mmengine - INFO - Epoch(train) [11][400/2119] lr: 4.0000e-02 eta: 1 day, 5:32:07 time: 0.3526 data_time: 0.0217 memory: 11108 grad_norm: 2.8753 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7572 loss: 2.7572 2022/10/09 08:03:31 - mmengine - INFO - Epoch(train) [11][420/2119] lr: 4.0000e-02 eta: 1 day, 5:31:58 time: 0.3554 data_time: 0.0192 memory: 11108 grad_norm: 2.9836 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7592 loss: 2.7592 2022/10/09 08:03:38 - mmengine - INFO - Epoch(train) [11][440/2119] lr: 4.0000e-02 eta: 1 day, 5:31:51 time: 0.3567 data_time: 0.0204 memory: 11108 grad_norm: 2.9339 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8225 loss: 2.8225 2022/10/09 08:03:45 - mmengine - INFO - Epoch(train) [11][460/2119] lr: 4.0000e-02 eta: 1 day, 5:31:42 time: 0.3550 data_time: 0.0194 memory: 11108 grad_norm: 2.9363 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6210 loss: 2.6210 2022/10/09 08:03:52 - mmengine - INFO - Epoch(train) [11][480/2119] lr: 4.0000e-02 eta: 1 day, 5:31:34 time: 0.3554 data_time: 0.0220 memory: 11108 grad_norm: 2.8939 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8137 loss: 2.8137 2022/10/09 08:03:59 - mmengine - INFO - Epoch(train) [11][500/2119] lr: 4.0000e-02 eta: 1 day, 5:31:28 time: 0.3607 data_time: 0.0189 memory: 11108 grad_norm: 2.9050 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8708 loss: 2.8708 2022/10/09 08:04:06 - mmengine - INFO - Epoch(train) [11][520/2119] lr: 4.0000e-02 eta: 1 day, 5:31:20 time: 0.3581 data_time: 0.0210 memory: 11108 grad_norm: 2.9192 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8872 loss: 2.8872 2022/10/09 08:04:14 - mmengine - INFO - Epoch(train) [11][540/2119] lr: 4.0000e-02 eta: 1 day, 5:31:13 time: 0.3598 data_time: 0.0198 memory: 11108 grad_norm: 2.9114 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8986 loss: 2.8986 2022/10/09 08:04:21 - mmengine - INFO - Epoch(train) [11][560/2119] lr: 4.0000e-02 eta: 1 day, 5:31:05 time: 0.3557 data_time: 0.0220 memory: 11108 grad_norm: 2.8630 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9415 loss: 2.9415 2022/10/09 08:04:28 - mmengine - INFO - Epoch(train) [11][580/2119] lr: 4.0000e-02 eta: 1 day, 5:30:57 time: 0.3557 data_time: 0.0182 memory: 11108 grad_norm: 2.8847 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7976 loss: 2.7976 2022/10/09 08:04:35 - mmengine - INFO - Epoch(train) [11][600/2119] lr: 4.0000e-02 eta: 1 day, 5:30:52 time: 0.3673 data_time: 0.0229 memory: 11108 grad_norm: 2.9507 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7820 loss: 2.7820 2022/10/09 08:04:42 - mmengine - INFO - Epoch(train) [11][620/2119] lr: 4.0000e-02 eta: 1 day, 5:30:44 time: 0.3535 data_time: 0.0187 memory: 11108 grad_norm: 2.9031 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8612 loss: 2.8612 2022/10/09 08:04:49 - mmengine - INFO - Epoch(train) [11][640/2119] lr: 4.0000e-02 eta: 1 day, 5:30:37 time: 0.3601 data_time: 0.0242 memory: 11108 grad_norm: 2.8931 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8559 loss: 2.8559 2022/10/09 08:04:57 - mmengine - INFO - Epoch(train) [11][660/2119] lr: 4.0000e-02 eta: 1 day, 5:30:31 time: 0.3634 data_time: 0.0201 memory: 11108 grad_norm: 2.9371 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8621 loss: 2.8621 2022/10/09 08:05:04 - mmengine - INFO - Epoch(train) [11][680/2119] lr: 4.0000e-02 eta: 1 day, 5:30:23 time: 0.3556 data_time: 0.0218 memory: 11108 grad_norm: 2.9446 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7584 loss: 2.7584 2022/10/09 08:05:11 - mmengine - INFO - Epoch(train) [11][700/2119] lr: 4.0000e-02 eta: 1 day, 5:30:15 time: 0.3556 data_time: 0.0208 memory: 11108 grad_norm: 2.9121 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.9009 loss: 2.9009 2022/10/09 08:05:18 - mmengine - INFO - Epoch(train) [11][720/2119] lr: 4.0000e-02 eta: 1 day, 5:30:07 time: 0.3581 data_time: 0.0214 memory: 11108 grad_norm: 2.8735 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0596 loss: 3.0596 2022/10/09 08:05:25 - mmengine - INFO - Epoch(train) [11][740/2119] lr: 4.0000e-02 eta: 1 day, 5:29:59 time: 0.3552 data_time: 0.0174 memory: 11108 grad_norm: 2.9102 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8461 loss: 2.8461 2022/10/09 08:05:32 - mmengine - INFO - Epoch(train) [11][760/2119] lr: 4.0000e-02 eta: 1 day, 5:29:51 time: 0.3541 data_time: 0.0248 memory: 11108 grad_norm: 2.8923 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7269 loss: 2.7269 2022/10/09 08:05:40 - mmengine - INFO - Epoch(train) [11][780/2119] lr: 4.0000e-02 eta: 1 day, 5:29:44 time: 0.3622 data_time: 0.0209 memory: 11108 grad_norm: 2.8966 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7027 loss: 2.7027 2022/10/09 08:05:47 - mmengine - INFO - Epoch(train) [11][800/2119] lr: 4.0000e-02 eta: 1 day, 5:29:36 time: 0.3561 data_time: 0.0199 memory: 11108 grad_norm: 2.9344 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5273 loss: 2.5273 2022/10/09 08:05:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 08:05:54 - mmengine - INFO - Epoch(train) [11][820/2119] lr: 4.0000e-02 eta: 1 day, 5:29:28 time: 0.3559 data_time: 0.0234 memory: 11108 grad_norm: 2.8988 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6964 loss: 2.6964 2022/10/09 08:06:01 - mmengine - INFO - Epoch(train) [11][840/2119] lr: 4.0000e-02 eta: 1 day, 5:29:20 time: 0.3555 data_time: 0.0207 memory: 11108 grad_norm: 2.8917 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.4100 loss: 2.4100 2022/10/09 08:06:08 - mmengine - INFO - Epoch(train) [11][860/2119] lr: 4.0000e-02 eta: 1 day, 5:29:13 time: 0.3569 data_time: 0.0222 memory: 11108 grad_norm: 2.9163 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.6547 loss: 2.6547 2022/10/09 08:06:15 - mmengine - INFO - Epoch(train) [11][880/2119] lr: 4.0000e-02 eta: 1 day, 5:29:05 time: 0.3569 data_time: 0.0198 memory: 11108 grad_norm: 2.8613 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4240 loss: 2.4240 2022/10/09 08:06:22 - mmengine - INFO - Epoch(train) [11][900/2119] lr: 4.0000e-02 eta: 1 day, 5:28:57 time: 0.3558 data_time: 0.0193 memory: 11108 grad_norm: 2.9016 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9003 loss: 2.9003 2022/10/09 08:06:29 - mmengine - INFO - Epoch(train) [11][920/2119] lr: 4.0000e-02 eta: 1 day, 5:28:49 time: 0.3571 data_time: 0.0202 memory: 11108 grad_norm: 2.9037 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7862 loss: 2.7862 2022/10/09 08:06:37 - mmengine - INFO - Epoch(train) [11][940/2119] lr: 4.0000e-02 eta: 1 day, 5:28:42 time: 0.3572 data_time: 0.0261 memory: 11108 grad_norm: 2.8889 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7614 loss: 2.7614 2022/10/09 08:06:44 - mmengine - INFO - Epoch(train) [11][960/2119] lr: 4.0000e-02 eta: 1 day, 5:28:34 time: 0.3555 data_time: 0.0178 memory: 11108 grad_norm: 2.9154 top1_acc: 0.0625 top5_acc: 0.4375 loss_cls: 2.7735 loss: 2.7735 2022/10/09 08:06:51 - mmengine - INFO - Epoch(train) [11][980/2119] lr: 4.0000e-02 eta: 1 day, 5:28:26 time: 0.3561 data_time: 0.0165 memory: 11108 grad_norm: 2.8813 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.9274 loss: 2.9274 2022/10/09 08:06:58 - mmengine - INFO - Epoch(train) [11][1000/2119] lr: 4.0000e-02 eta: 1 day, 5:28:18 time: 0.3571 data_time: 0.0218 memory: 11108 grad_norm: 2.8899 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7600 loss: 2.7600 2022/10/09 08:07:05 - mmengine - INFO - Epoch(train) [11][1020/2119] lr: 4.0000e-02 eta: 1 day, 5:28:10 time: 0.3560 data_time: 0.0205 memory: 11108 grad_norm: 2.9234 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7725 loss: 2.7725 2022/10/09 08:07:12 - mmengine - INFO - Epoch(train) [11][1040/2119] lr: 4.0000e-02 eta: 1 day, 5:28:03 time: 0.3574 data_time: 0.0205 memory: 11108 grad_norm: 2.9074 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7093 loss: 2.7093 2022/10/09 08:07:20 - mmengine - INFO - Epoch(train) [11][1060/2119] lr: 4.0000e-02 eta: 1 day, 5:27:57 time: 0.3656 data_time: 0.0191 memory: 11108 grad_norm: 2.8813 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6612 loss: 2.6612 2022/10/09 08:07:27 - mmengine - INFO - Epoch(train) [11][1080/2119] lr: 4.0000e-02 eta: 1 day, 5:27:51 time: 0.3615 data_time: 0.0199 memory: 11108 grad_norm: 2.9007 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7651 loss: 2.7651 2022/10/09 08:07:34 - mmengine - INFO - Epoch(train) [11][1100/2119] lr: 4.0000e-02 eta: 1 day, 5:27:43 time: 0.3569 data_time: 0.0207 memory: 11108 grad_norm: 2.9640 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8625 loss: 2.8625 2022/10/09 08:07:41 - mmengine - INFO - Epoch(train) [11][1120/2119] lr: 4.0000e-02 eta: 1 day, 5:27:35 time: 0.3565 data_time: 0.0198 memory: 11108 grad_norm: 2.9007 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8202 loss: 2.8202 2022/10/09 08:07:48 - mmengine - INFO - Epoch(train) [11][1140/2119] lr: 4.0000e-02 eta: 1 day, 5:27:29 time: 0.3623 data_time: 0.0168 memory: 11108 grad_norm: 2.8521 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8554 loss: 2.8554 2022/10/09 08:07:55 - mmengine - INFO - Epoch(train) [11][1160/2119] lr: 4.0000e-02 eta: 1 day, 5:27:22 time: 0.3581 data_time: 0.0202 memory: 11108 grad_norm: 2.8582 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7381 loss: 2.7381 2022/10/09 08:08:03 - mmengine - INFO - Epoch(train) [11][1180/2119] lr: 4.0000e-02 eta: 1 day, 5:27:13 time: 0.3548 data_time: 0.0179 memory: 11108 grad_norm: 2.9066 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7474 loss: 2.7474 2022/10/09 08:08:10 - mmengine - INFO - Epoch(train) [11][1200/2119] lr: 4.0000e-02 eta: 1 day, 5:27:05 time: 0.3552 data_time: 0.0192 memory: 11108 grad_norm: 2.8887 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7992 loss: 2.7992 2022/10/09 08:08:17 - mmengine - INFO - Epoch(train) [11][1220/2119] lr: 4.0000e-02 eta: 1 day, 5:26:57 time: 0.3547 data_time: 0.0216 memory: 11108 grad_norm: 2.9224 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7493 loss: 2.7493 2022/10/09 08:08:24 - mmengine - INFO - Epoch(train) [11][1240/2119] lr: 4.0000e-02 eta: 1 day, 5:26:49 time: 0.3577 data_time: 0.0255 memory: 11108 grad_norm: 2.9080 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7421 loss: 2.7421 2022/10/09 08:08:31 - mmengine - INFO - Epoch(train) [11][1260/2119] lr: 4.0000e-02 eta: 1 day, 5:26:42 time: 0.3561 data_time: 0.0180 memory: 11108 grad_norm: 2.9403 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8064 loss: 2.8064 2022/10/09 08:08:38 - mmengine - INFO - Epoch(train) [11][1280/2119] lr: 4.0000e-02 eta: 1 day, 5:26:34 time: 0.3564 data_time: 0.0214 memory: 11108 grad_norm: 2.8932 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8836 loss: 2.8836 2022/10/09 08:08:45 - mmengine - INFO - Epoch(train) [11][1300/2119] lr: 4.0000e-02 eta: 1 day, 5:26:26 time: 0.3578 data_time: 0.0234 memory: 11108 grad_norm: 2.8820 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8961 loss: 2.8961 2022/10/09 08:08:52 - mmengine - INFO - Epoch(train) [11][1320/2119] lr: 4.0000e-02 eta: 1 day, 5:26:18 time: 0.3535 data_time: 0.0214 memory: 11108 grad_norm: 2.8455 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7032 loss: 2.7032 2022/10/09 08:09:00 - mmengine - INFO - Epoch(train) [11][1340/2119] lr: 4.0000e-02 eta: 1 day, 5:26:11 time: 0.3616 data_time: 0.0182 memory: 11108 grad_norm: 2.8752 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.9768 loss: 2.9768 2022/10/09 08:09:07 - mmengine - INFO - Epoch(train) [11][1360/2119] lr: 4.0000e-02 eta: 1 day, 5:26:06 time: 0.3664 data_time: 0.0210 memory: 11108 grad_norm: 2.9085 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8292 loss: 2.8292 2022/10/09 08:09:14 - mmengine - INFO - Epoch(train) [11][1380/2119] lr: 4.0000e-02 eta: 1 day, 5:25:58 time: 0.3546 data_time: 0.0200 memory: 11108 grad_norm: 2.8512 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7887 loss: 2.7887 2022/10/09 08:09:21 - mmengine - INFO - Epoch(train) [11][1400/2119] lr: 4.0000e-02 eta: 1 day, 5:25:49 time: 0.3543 data_time: 0.0231 memory: 11108 grad_norm: 2.8867 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7399 loss: 2.7399 2022/10/09 08:09:28 - mmengine - INFO - Epoch(train) [11][1420/2119] lr: 4.0000e-02 eta: 1 day, 5:25:44 time: 0.3662 data_time: 0.0202 memory: 11108 grad_norm: 2.9294 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8384 loss: 2.8384 2022/10/09 08:09:35 - mmengine - INFO - Epoch(train) [11][1440/2119] lr: 4.0000e-02 eta: 1 day, 5:25:36 time: 0.3538 data_time: 0.0189 memory: 11108 grad_norm: 2.9174 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5083 loss: 2.5083 2022/10/09 08:09:43 - mmengine - INFO - Epoch(train) [11][1460/2119] lr: 4.0000e-02 eta: 1 day, 5:25:27 time: 0.3519 data_time: 0.0198 memory: 11108 grad_norm: 2.9610 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7053 loss: 2.7053 2022/10/09 08:09:50 - mmengine - INFO - Epoch(train) [11][1480/2119] lr: 4.0000e-02 eta: 1 day, 5:25:21 time: 0.3628 data_time: 0.0196 memory: 11108 grad_norm: 2.8861 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6090 loss: 2.6090 2022/10/09 08:09:57 - mmengine - INFO - Epoch(train) [11][1500/2119] lr: 4.0000e-02 eta: 1 day, 5:25:14 time: 0.3602 data_time: 0.0242 memory: 11108 grad_norm: 2.9579 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6590 loss: 2.6590 2022/10/09 08:10:04 - mmengine - INFO - Epoch(train) [11][1520/2119] lr: 4.0000e-02 eta: 1 day, 5:25:07 time: 0.3596 data_time: 0.0217 memory: 11108 grad_norm: 2.8625 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5886 loss: 2.5886 2022/10/09 08:10:11 - mmengine - INFO - Epoch(train) [11][1540/2119] lr: 4.0000e-02 eta: 1 day, 5:25:00 time: 0.3605 data_time: 0.0255 memory: 11108 grad_norm: 2.8982 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9717 loss: 2.9717 2022/10/09 08:10:19 - mmengine - INFO - Epoch(train) [11][1560/2119] lr: 4.0000e-02 eta: 1 day, 5:24:53 time: 0.3593 data_time: 0.0199 memory: 11108 grad_norm: 2.9229 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9714 loss: 2.9714 2022/10/09 08:10:26 - mmengine - INFO - Epoch(train) [11][1580/2119] lr: 4.0000e-02 eta: 1 day, 5:24:46 time: 0.3613 data_time: 0.0192 memory: 11108 grad_norm: 2.9005 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5962 loss: 2.5962 2022/10/09 08:10:33 - mmengine - INFO - Epoch(train) [11][1600/2119] lr: 4.0000e-02 eta: 1 day, 5:24:38 time: 0.3559 data_time: 0.0203 memory: 11108 grad_norm: 2.8764 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5762 loss: 2.5762 2022/10/09 08:10:40 - mmengine - INFO - Epoch(train) [11][1620/2119] lr: 4.0000e-02 eta: 1 day, 5:24:32 time: 0.3625 data_time: 0.0209 memory: 11108 grad_norm: 2.8890 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9404 loss: 2.9404 2022/10/09 08:10:47 - mmengine - INFO - Epoch(train) [11][1640/2119] lr: 4.0000e-02 eta: 1 day, 5:24:25 time: 0.3575 data_time: 0.0207 memory: 11108 grad_norm: 2.8700 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7722 loss: 2.7722 2022/10/09 08:10:54 - mmengine - INFO - Epoch(train) [11][1660/2119] lr: 4.0000e-02 eta: 1 day, 5:24:17 time: 0.3556 data_time: 0.0171 memory: 11108 grad_norm: 2.9146 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5665 loss: 2.5665 2022/10/09 08:11:02 - mmengine - INFO - Epoch(train) [11][1680/2119] lr: 4.0000e-02 eta: 1 day, 5:24:09 time: 0.3563 data_time: 0.0193 memory: 11108 grad_norm: 2.8494 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 2.5614 loss: 2.5614 2022/10/09 08:11:09 - mmengine - INFO - Epoch(train) [11][1700/2119] lr: 4.0000e-02 eta: 1 day, 5:24:01 time: 0.3565 data_time: 0.0219 memory: 11108 grad_norm: 2.8951 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8422 loss: 2.8422 2022/10/09 08:11:16 - mmengine - INFO - Epoch(train) [11][1720/2119] lr: 4.0000e-02 eta: 1 day, 5:23:53 time: 0.3563 data_time: 0.0256 memory: 11108 grad_norm: 2.8367 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7547 loss: 2.7547 2022/10/09 08:11:23 - mmengine - INFO - Epoch(train) [11][1740/2119] lr: 4.0000e-02 eta: 1 day, 5:23:45 time: 0.3563 data_time: 0.0216 memory: 11108 grad_norm: 2.9029 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8485 loss: 2.8485 2022/10/09 08:11:30 - mmengine - INFO - Epoch(train) [11][1760/2119] lr: 4.0000e-02 eta: 1 day, 5:23:37 time: 0.3548 data_time: 0.0201 memory: 11108 grad_norm: 2.9174 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7225 loss: 2.7225 2022/10/09 08:11:37 - mmengine - INFO - Epoch(train) [11][1780/2119] lr: 4.0000e-02 eta: 1 day, 5:23:29 time: 0.3565 data_time: 0.0200 memory: 11108 grad_norm: 2.8474 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.8405 loss: 2.8405 2022/10/09 08:11:44 - mmengine - INFO - Epoch(train) [11][1800/2119] lr: 4.0000e-02 eta: 1 day, 5:23:21 time: 0.3549 data_time: 0.0187 memory: 11108 grad_norm: 2.9115 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6836 loss: 2.6836 2022/10/09 08:11:48 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 08:11:51 - mmengine - INFO - Epoch(train) [11][1820/2119] lr: 4.0000e-02 eta: 1 day, 5:23:14 time: 0.3598 data_time: 0.0191 memory: 11108 grad_norm: 2.8735 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6822 loss: 2.6822 2022/10/09 08:11:59 - mmengine - INFO - Epoch(train) [11][1840/2119] lr: 4.0000e-02 eta: 1 day, 5:23:07 time: 0.3569 data_time: 0.0199 memory: 11108 grad_norm: 2.9107 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7182 loss: 2.7182 2022/10/09 08:12:06 - mmengine - INFO - Epoch(train) [11][1860/2119] lr: 4.0000e-02 eta: 1 day, 5:22:59 time: 0.3560 data_time: 0.0207 memory: 11108 grad_norm: 2.8735 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8063 loss: 2.8063 2022/10/09 08:12:13 - mmengine - INFO - Epoch(train) [11][1880/2119] lr: 4.0000e-02 eta: 1 day, 5:22:55 time: 0.3727 data_time: 0.0206 memory: 11108 grad_norm: 2.8703 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7356 loss: 2.7356 2022/10/09 08:12:20 - mmengine - INFO - Epoch(train) [11][1900/2119] lr: 4.0000e-02 eta: 1 day, 5:22:48 time: 0.3575 data_time: 0.0207 memory: 11108 grad_norm: 2.8685 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8391 loss: 2.8391 2022/10/09 08:12:27 - mmengine - INFO - Epoch(train) [11][1920/2119] lr: 4.0000e-02 eta: 1 day, 5:22:40 time: 0.3569 data_time: 0.0202 memory: 11108 grad_norm: 2.8399 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6445 loss: 2.6445 2022/10/09 08:12:35 - mmengine - INFO - Epoch(train) [11][1940/2119] lr: 4.0000e-02 eta: 1 day, 5:22:32 time: 0.3547 data_time: 0.0197 memory: 11108 grad_norm: 2.8712 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.5611 loss: 2.5611 2022/10/09 08:12:42 - mmengine - INFO - Epoch(train) [11][1960/2119] lr: 4.0000e-02 eta: 1 day, 5:22:24 time: 0.3569 data_time: 0.0249 memory: 11108 grad_norm: 2.8272 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7293 loss: 2.7293 2022/10/09 08:12:49 - mmengine - INFO - Epoch(train) [11][1980/2119] lr: 4.0000e-02 eta: 1 day, 5:22:16 time: 0.3561 data_time: 0.0185 memory: 11108 grad_norm: 2.9295 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8254 loss: 2.8254 2022/10/09 08:12:56 - mmengine - INFO - Epoch(train) [11][2000/2119] lr: 4.0000e-02 eta: 1 day, 5:22:09 time: 0.3579 data_time: 0.0230 memory: 11108 grad_norm: 2.8908 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8115 loss: 2.8115 2022/10/09 08:13:03 - mmengine - INFO - Epoch(train) [11][2020/2119] lr: 4.0000e-02 eta: 1 day, 5:22:01 time: 0.3580 data_time: 0.0202 memory: 11108 grad_norm: 2.8911 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9166 loss: 2.9166 2022/10/09 08:13:10 - mmengine - INFO - Epoch(train) [11][2040/2119] lr: 4.0000e-02 eta: 1 day, 5:21:55 time: 0.3621 data_time: 0.0239 memory: 11108 grad_norm: 2.8911 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5966 loss: 2.5966 2022/10/09 08:13:18 - mmengine - INFO - Epoch(train) [11][2060/2119] lr: 4.0000e-02 eta: 1 day, 5:21:47 time: 0.3558 data_time: 0.0205 memory: 11108 grad_norm: 2.8774 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6514 loss: 2.6514 2022/10/09 08:13:25 - mmengine - INFO - Epoch(train) [11][2080/2119] lr: 4.0000e-02 eta: 1 day, 5:21:41 time: 0.3627 data_time: 0.0282 memory: 11108 grad_norm: 2.9350 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.8271 loss: 2.8271 2022/10/09 08:13:32 - mmengine - INFO - Epoch(train) [11][2100/2119] lr: 4.0000e-02 eta: 1 day, 5:21:33 time: 0.3553 data_time: 0.0206 memory: 11108 grad_norm: 2.8708 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6774 loss: 2.6774 2022/10/09 08:13:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 08:13:38 - mmengine - INFO - Epoch(train) [11][2119/2119] lr: 4.0000e-02 eta: 1 day, 5:21:33 time: 0.3479 data_time: 0.0166 memory: 11108 grad_norm: 2.8958 top1_acc: 0.4000 top5_acc: 0.4000 loss_cls: 2.5794 loss: 2.5794 2022/10/09 08:13:49 - mmengine - INFO - Epoch(train) [12][20/2119] lr: 4.0000e-02 eta: 1 day, 5:20:38 time: 0.5365 data_time: 0.1399 memory: 11108 grad_norm: 2.9247 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6010 loss: 2.6010 2022/10/09 08:13:57 - mmengine - INFO - Epoch(train) [12][40/2119] lr: 4.0000e-02 eta: 1 day, 5:20:33 time: 0.3674 data_time: 0.0275 memory: 11108 grad_norm: 2.8605 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6851 loss: 2.6851 2022/10/09 08:14:04 - mmengine - INFO - Epoch(train) [12][60/2119] lr: 4.0000e-02 eta: 1 day, 5:20:25 time: 0.3586 data_time: 0.0179 memory: 11108 grad_norm: 2.8599 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5653 loss: 2.5653 2022/10/09 08:14:11 - mmengine - INFO - Epoch(train) [12][80/2119] lr: 4.0000e-02 eta: 1 day, 5:20:18 time: 0.3576 data_time: 0.0217 memory: 11108 grad_norm: 2.8851 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6439 loss: 2.6439 2022/10/09 08:14:18 - mmengine - INFO - Epoch(train) [12][100/2119] lr: 4.0000e-02 eta: 1 day, 5:20:10 time: 0.3554 data_time: 0.0221 memory: 11108 grad_norm: 2.8867 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.5691 loss: 2.5691 2022/10/09 08:14:25 - mmengine - INFO - Epoch(train) [12][120/2119] lr: 4.0000e-02 eta: 1 day, 5:20:05 time: 0.3662 data_time: 0.0244 memory: 11108 grad_norm: 2.8764 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8389 loss: 2.8389 2022/10/09 08:14:33 - mmengine - INFO - Epoch(train) [12][140/2119] lr: 4.0000e-02 eta: 1 day, 5:19:57 time: 0.3564 data_time: 0.0206 memory: 11108 grad_norm: 2.8220 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6109 loss: 2.6109 2022/10/09 08:14:40 - mmengine - INFO - Epoch(train) [12][160/2119] lr: 4.0000e-02 eta: 1 day, 5:19:50 time: 0.3607 data_time: 0.0220 memory: 11108 grad_norm: 2.8764 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7109 loss: 2.7109 2022/10/09 08:14:47 - mmengine - INFO - Epoch(train) [12][180/2119] lr: 4.0000e-02 eta: 1 day, 5:19:42 time: 0.3550 data_time: 0.0221 memory: 11108 grad_norm: 2.8535 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5644 loss: 2.5644 2022/10/09 08:14:54 - mmengine - INFO - Epoch(train) [12][200/2119] lr: 4.0000e-02 eta: 1 day, 5:19:35 time: 0.3583 data_time: 0.0196 memory: 11108 grad_norm: 2.8876 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8122 loss: 2.8122 2022/10/09 08:15:01 - mmengine - INFO - Epoch(train) [12][220/2119] lr: 4.0000e-02 eta: 1 day, 5:19:28 time: 0.3606 data_time: 0.0187 memory: 11108 grad_norm: 2.8571 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7402 loss: 2.7402 2022/10/09 08:15:08 - mmengine - INFO - Epoch(train) [12][240/2119] lr: 4.0000e-02 eta: 1 day, 5:19:20 time: 0.3554 data_time: 0.0254 memory: 11108 grad_norm: 2.8461 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5792 loss: 2.5792 2022/10/09 08:15:16 - mmengine - INFO - Epoch(train) [12][260/2119] lr: 4.0000e-02 eta: 1 day, 5:19:13 time: 0.3601 data_time: 0.0245 memory: 11108 grad_norm: 2.8845 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.6288 loss: 2.6288 2022/10/09 08:15:23 - mmengine - INFO - Epoch(train) [12][280/2119] lr: 4.0000e-02 eta: 1 day, 5:19:06 time: 0.3564 data_time: 0.0223 memory: 11108 grad_norm: 2.8690 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6728 loss: 2.6728 2022/10/09 08:15:30 - mmengine - INFO - Epoch(train) [12][300/2119] lr: 4.0000e-02 eta: 1 day, 5:18:59 time: 0.3609 data_time: 0.0244 memory: 11108 grad_norm: 2.8682 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5279 loss: 2.5279 2022/10/09 08:15:37 - mmengine - INFO - Epoch(train) [12][320/2119] lr: 4.0000e-02 eta: 1 day, 5:18:51 time: 0.3569 data_time: 0.0187 memory: 11108 grad_norm: 2.8401 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7419 loss: 2.7419 2022/10/09 08:15:44 - mmengine - INFO - Epoch(train) [12][340/2119] lr: 4.0000e-02 eta: 1 day, 5:18:44 time: 0.3568 data_time: 0.0175 memory: 11108 grad_norm: 2.8827 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7256 loss: 2.7256 2022/10/09 08:15:51 - mmengine - INFO - Epoch(train) [12][360/2119] lr: 4.0000e-02 eta: 1 day, 5:18:36 time: 0.3575 data_time: 0.0189 memory: 11108 grad_norm: 2.9396 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6171 loss: 2.6171 2022/10/09 08:15:58 - mmengine - INFO - Epoch(train) [12][380/2119] lr: 4.0000e-02 eta: 1 day, 5:18:29 time: 0.3576 data_time: 0.0227 memory: 11108 grad_norm: 2.8970 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.5436 loss: 2.5436 2022/10/09 08:16:06 - mmengine - INFO - Epoch(train) [12][400/2119] lr: 4.0000e-02 eta: 1 day, 5:18:22 time: 0.3597 data_time: 0.0202 memory: 11108 grad_norm: 2.9027 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7247 loss: 2.7247 2022/10/09 08:16:13 - mmengine - INFO - Epoch(train) [12][420/2119] lr: 4.0000e-02 eta: 1 day, 5:18:13 time: 0.3533 data_time: 0.0180 memory: 11108 grad_norm: 2.8625 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6933 loss: 2.6933 2022/10/09 08:16:20 - mmengine - INFO - Epoch(train) [12][440/2119] lr: 4.0000e-02 eta: 1 day, 5:18:08 time: 0.3650 data_time: 0.0212 memory: 11108 grad_norm: 2.8557 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8483 loss: 2.8483 2022/10/09 08:16:27 - mmengine - INFO - Epoch(train) [12][460/2119] lr: 4.0000e-02 eta: 1 day, 5:18:00 time: 0.3560 data_time: 0.0225 memory: 11108 grad_norm: 2.8653 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7085 loss: 2.7085 2022/10/09 08:16:34 - mmengine - INFO - Epoch(train) [12][480/2119] lr: 4.0000e-02 eta: 1 day, 5:17:52 time: 0.3555 data_time: 0.0233 memory: 11108 grad_norm: 2.8536 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5805 loss: 2.5805 2022/10/09 08:16:42 - mmengine - INFO - Epoch(train) [12][500/2119] lr: 4.0000e-02 eta: 1 day, 5:17:48 time: 0.3730 data_time: 0.0183 memory: 11108 grad_norm: 2.9060 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5441 loss: 2.5441 2022/10/09 08:16:49 - mmengine - INFO - Epoch(train) [12][520/2119] lr: 4.0000e-02 eta: 1 day, 5:17:40 time: 0.3545 data_time: 0.0192 memory: 11108 grad_norm: 2.9377 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7306 loss: 2.7306 2022/10/09 08:16:56 - mmengine - INFO - Epoch(train) [12][540/2119] lr: 4.0000e-02 eta: 1 day, 5:17:36 time: 0.3689 data_time: 0.0205 memory: 11108 grad_norm: 2.8650 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7911 loss: 2.7911 2022/10/09 08:17:03 - mmengine - INFO - Epoch(train) [12][560/2119] lr: 4.0000e-02 eta: 1 day, 5:17:27 time: 0.3535 data_time: 0.0230 memory: 11108 grad_norm: 2.8702 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9387 loss: 2.9387 2022/10/09 08:17:10 - mmengine - INFO - Epoch(train) [12][580/2119] lr: 4.0000e-02 eta: 1 day, 5:17:18 time: 0.3527 data_time: 0.0185 memory: 11108 grad_norm: 2.9018 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8342 loss: 2.8342 2022/10/09 08:17:18 - mmengine - INFO - Epoch(train) [12][600/2119] lr: 4.0000e-02 eta: 1 day, 5:17:13 time: 0.3669 data_time: 0.0205 memory: 11108 grad_norm: 2.8556 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7451 loss: 2.7451 2022/10/09 08:17:25 - mmengine - INFO - Epoch(train) [12][620/2119] lr: 4.0000e-02 eta: 1 day, 5:17:05 time: 0.3557 data_time: 0.0250 memory: 11108 grad_norm: 2.8761 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8729 loss: 2.8729 2022/10/09 08:17:32 - mmengine - INFO - Epoch(train) [12][640/2119] lr: 4.0000e-02 eta: 1 day, 5:16:59 time: 0.3611 data_time: 0.0206 memory: 11108 grad_norm: 2.8638 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9413 loss: 2.9413 2022/10/09 08:17:39 - mmengine - INFO - Epoch(train) [12][660/2119] lr: 4.0000e-02 eta: 1 day, 5:16:52 time: 0.3593 data_time: 0.0253 memory: 11108 grad_norm: 2.8453 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.4360 loss: 2.4360 2022/10/09 08:17:46 - mmengine - INFO - Epoch(train) [12][680/2119] lr: 4.0000e-02 eta: 1 day, 5:16:45 time: 0.3614 data_time: 0.0210 memory: 11108 grad_norm: 2.8589 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6711 loss: 2.6711 2022/10/09 08:17:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 08:17:53 - mmengine - INFO - Epoch(train) [12][700/2119] lr: 4.0000e-02 eta: 1 day, 5:16:37 time: 0.3551 data_time: 0.0188 memory: 11108 grad_norm: 2.8612 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6525 loss: 2.6525 2022/10/09 08:18:01 - mmengine - INFO - Epoch(train) [12][720/2119] lr: 4.0000e-02 eta: 1 day, 5:16:35 time: 0.3785 data_time: 0.0200 memory: 11108 grad_norm: 2.9102 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8543 loss: 2.8543 2022/10/09 08:18:08 - mmengine - INFO - Epoch(train) [12][740/2119] lr: 4.0000e-02 eta: 1 day, 5:16:27 time: 0.3557 data_time: 0.0223 memory: 11108 grad_norm: 2.8777 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 2.6672 loss: 2.6672 2022/10/09 08:18:15 - mmengine - INFO - Epoch(train) [12][760/2119] lr: 4.0000e-02 eta: 1 day, 5:16:19 time: 0.3550 data_time: 0.0237 memory: 11108 grad_norm: 2.8523 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6439 loss: 2.6439 2022/10/09 08:18:22 - mmengine - INFO - Epoch(train) [12][780/2119] lr: 4.0000e-02 eta: 1 day, 5:16:11 time: 0.3565 data_time: 0.0192 memory: 11108 grad_norm: 2.8915 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8336 loss: 2.8336 2022/10/09 08:18:30 - mmengine - INFO - Epoch(train) [12][800/2119] lr: 4.0000e-02 eta: 1 day, 5:16:04 time: 0.3575 data_time: 0.0241 memory: 11108 grad_norm: 2.8727 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6848 loss: 2.6848 2022/10/09 08:18:37 - mmengine - INFO - Epoch(train) [12][820/2119] lr: 4.0000e-02 eta: 1 day, 5:15:56 time: 0.3582 data_time: 0.0163 memory: 11108 grad_norm: 2.8840 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.9195 loss: 2.9195 2022/10/09 08:18:44 - mmengine - INFO - Epoch(train) [12][840/2119] lr: 4.0000e-02 eta: 1 day, 5:15:48 time: 0.3528 data_time: 0.0195 memory: 11108 grad_norm: 2.8254 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6372 loss: 2.6372 2022/10/09 08:18:51 - mmengine - INFO - Epoch(train) [12][860/2119] lr: 4.0000e-02 eta: 1 day, 5:15:40 time: 0.3553 data_time: 0.0189 memory: 11108 grad_norm: 2.9257 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8559 loss: 2.8559 2022/10/09 08:18:58 - mmengine - INFO - Epoch(train) [12][880/2119] lr: 4.0000e-02 eta: 1 day, 5:15:32 time: 0.3572 data_time: 0.0225 memory: 11108 grad_norm: 2.8677 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7664 loss: 2.7664 2022/10/09 08:19:05 - mmengine - INFO - Epoch(train) [12][900/2119] lr: 4.0000e-02 eta: 1 day, 5:15:25 time: 0.3570 data_time: 0.0221 memory: 11108 grad_norm: 2.8710 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8863 loss: 2.8863 2022/10/09 08:19:12 - mmengine - INFO - Epoch(train) [12][920/2119] lr: 4.0000e-02 eta: 1 day, 5:15:17 time: 0.3558 data_time: 0.0211 memory: 11108 grad_norm: 2.8297 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6827 loss: 2.6827 2022/10/09 08:19:19 - mmengine - INFO - Epoch(train) [12][940/2119] lr: 4.0000e-02 eta: 1 day, 5:15:10 time: 0.3590 data_time: 0.0198 memory: 11108 grad_norm: 2.8544 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9337 loss: 2.9337 2022/10/09 08:19:27 - mmengine - INFO - Epoch(train) [12][960/2119] lr: 4.0000e-02 eta: 1 day, 5:15:03 time: 0.3589 data_time: 0.0208 memory: 11108 grad_norm: 2.8819 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5960 loss: 2.5960 2022/10/09 08:19:34 - mmengine - INFO - Epoch(train) [12][980/2119] lr: 4.0000e-02 eta: 1 day, 5:14:55 time: 0.3567 data_time: 0.0233 memory: 11108 grad_norm: 2.8858 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7649 loss: 2.7649 2022/10/09 08:19:41 - mmengine - INFO - Epoch(train) [12][1000/2119] lr: 4.0000e-02 eta: 1 day, 5:14:50 time: 0.3682 data_time: 0.0317 memory: 11108 grad_norm: 2.8611 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7701 loss: 2.7701 2022/10/09 08:19:48 - mmengine - INFO - Epoch(train) [12][1020/2119] lr: 4.0000e-02 eta: 1 day, 5:14:43 time: 0.3578 data_time: 0.0222 memory: 11108 grad_norm: 2.8910 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6784 loss: 2.6784 2022/10/09 08:19:56 - mmengine - INFO - Epoch(train) [12][1040/2119] lr: 4.0000e-02 eta: 1 day, 5:14:37 time: 0.3649 data_time: 0.0309 memory: 11108 grad_norm: 2.8749 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8104 loss: 2.8104 2022/10/09 08:20:03 - mmengine - INFO - Epoch(train) [12][1060/2119] lr: 4.0000e-02 eta: 1 day, 5:14:29 time: 0.3552 data_time: 0.0208 memory: 11108 grad_norm: 2.8467 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5522 loss: 2.5522 2022/10/09 08:20:10 - mmengine - INFO - Epoch(train) [12][1080/2119] lr: 4.0000e-02 eta: 1 day, 5:14:22 time: 0.3584 data_time: 0.0220 memory: 11108 grad_norm: 2.8593 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6841 loss: 2.6841 2022/10/09 08:20:17 - mmengine - INFO - Epoch(train) [12][1100/2119] lr: 4.0000e-02 eta: 1 day, 5:14:14 time: 0.3576 data_time: 0.0235 memory: 11108 grad_norm: 2.8533 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7588 loss: 2.7588 2022/10/09 08:20:24 - mmengine - INFO - Epoch(train) [12][1120/2119] lr: 4.0000e-02 eta: 1 day, 5:14:08 time: 0.3617 data_time: 0.0165 memory: 11108 grad_norm: 2.9038 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4997 loss: 2.4997 2022/10/09 08:20:32 - mmengine - INFO - Epoch(train) [12][1140/2119] lr: 4.0000e-02 eta: 1 day, 5:14:02 time: 0.3645 data_time: 0.0203 memory: 11108 grad_norm: 2.8665 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7937 loss: 2.7937 2022/10/09 08:20:39 - mmengine - INFO - Epoch(train) [12][1160/2119] lr: 4.0000e-02 eta: 1 day, 5:13:56 time: 0.3629 data_time: 0.0212 memory: 11108 grad_norm: 2.8221 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9081 loss: 2.9081 2022/10/09 08:20:46 - mmengine - INFO - Epoch(train) [12][1180/2119] lr: 4.0000e-02 eta: 1 day, 5:13:49 time: 0.3589 data_time: 0.0201 memory: 11108 grad_norm: 2.8289 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.4836 loss: 2.4836 2022/10/09 08:20:53 - mmengine - INFO - Epoch(train) [12][1200/2119] lr: 4.0000e-02 eta: 1 day, 5:13:41 time: 0.3553 data_time: 0.0196 memory: 11108 grad_norm: 2.8984 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6481 loss: 2.6481 2022/10/09 08:21:00 - mmengine - INFO - Epoch(train) [12][1220/2119] lr: 4.0000e-02 eta: 1 day, 5:13:33 time: 0.3577 data_time: 0.0183 memory: 11108 grad_norm: 2.8479 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7042 loss: 2.7042 2022/10/09 08:21:07 - mmengine - INFO - Epoch(train) [12][1240/2119] lr: 4.0000e-02 eta: 1 day, 5:13:26 time: 0.3583 data_time: 0.0198 memory: 11108 grad_norm: 2.9078 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6584 loss: 2.6584 2022/10/09 08:21:14 - mmengine - INFO - Epoch(train) [12][1260/2119] lr: 4.0000e-02 eta: 1 day, 5:13:18 time: 0.3539 data_time: 0.0179 memory: 11108 grad_norm: 2.8519 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7345 loss: 2.7345 2022/10/09 08:21:22 - mmengine - INFO - Epoch(train) [12][1280/2119] lr: 4.0000e-02 eta: 1 day, 5:13:12 time: 0.3635 data_time: 0.0231 memory: 11108 grad_norm: 2.8668 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9315 loss: 2.9315 2022/10/09 08:21:29 - mmengine - INFO - Epoch(train) [12][1300/2119] lr: 4.0000e-02 eta: 1 day, 5:13:04 time: 0.3552 data_time: 0.0213 memory: 11108 grad_norm: 2.8193 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5883 loss: 2.5883 2022/10/09 08:21:36 - mmengine - INFO - Epoch(train) [12][1320/2119] lr: 4.0000e-02 eta: 1 day, 5:12:58 time: 0.3639 data_time: 0.0244 memory: 11108 grad_norm: 2.8374 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6525 loss: 2.6525 2022/10/09 08:21:43 - mmengine - INFO - Epoch(train) [12][1340/2119] lr: 4.0000e-02 eta: 1 day, 5:12:49 time: 0.3528 data_time: 0.0211 memory: 11108 grad_norm: 2.8037 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5932 loss: 2.5932 2022/10/09 08:21:50 - mmengine - INFO - Epoch(train) [12][1360/2119] lr: 4.0000e-02 eta: 1 day, 5:12:41 time: 0.3564 data_time: 0.0210 memory: 11108 grad_norm: 2.8888 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.4977 loss: 2.4977 2022/10/09 08:21:58 - mmengine - INFO - Epoch(train) [12][1380/2119] lr: 4.0000e-02 eta: 1 day, 5:12:35 time: 0.3601 data_time: 0.0205 memory: 11108 grad_norm: 2.7976 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8255 loss: 2.8255 2022/10/09 08:22:05 - mmengine - INFO - Epoch(train) [12][1400/2119] lr: 4.0000e-02 eta: 1 day, 5:12:26 time: 0.3539 data_time: 0.0209 memory: 11108 grad_norm: 2.8956 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8294 loss: 2.8294 2022/10/09 08:22:12 - mmengine - INFO - Epoch(train) [12][1420/2119] lr: 4.0000e-02 eta: 1 day, 5:12:18 time: 0.3535 data_time: 0.0174 memory: 11108 grad_norm: 2.8124 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6947 loss: 2.6947 2022/10/09 08:22:19 - mmengine - INFO - Epoch(train) [12][1440/2119] lr: 4.0000e-02 eta: 1 day, 5:12:10 time: 0.3570 data_time: 0.0202 memory: 11108 grad_norm: 2.8409 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5755 loss: 2.5755 2022/10/09 08:22:26 - mmengine - INFO - Epoch(train) [12][1460/2119] lr: 4.0000e-02 eta: 1 day, 5:12:02 time: 0.3542 data_time: 0.0193 memory: 11108 grad_norm: 2.8965 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8498 loss: 2.8498 2022/10/09 08:22:33 - mmengine - INFO - Epoch(train) [12][1480/2119] lr: 4.0000e-02 eta: 1 day, 5:11:54 time: 0.3565 data_time: 0.0208 memory: 11108 grad_norm: 2.9357 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6955 loss: 2.6955 2022/10/09 08:22:40 - mmengine - INFO - Epoch(train) [12][1500/2119] lr: 4.0000e-02 eta: 1 day, 5:11:47 time: 0.3590 data_time: 0.0208 memory: 11108 grad_norm: 2.8967 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6737 loss: 2.6737 2022/10/09 08:22:47 - mmengine - INFO - Epoch(train) [12][1520/2119] lr: 4.0000e-02 eta: 1 day, 5:11:39 time: 0.3540 data_time: 0.0195 memory: 11108 grad_norm: 2.8523 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8647 loss: 2.8647 2022/10/09 08:22:55 - mmengine - INFO - Epoch(train) [12][1540/2119] lr: 4.0000e-02 eta: 1 day, 5:11:32 time: 0.3600 data_time: 0.0173 memory: 11108 grad_norm: 2.8569 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7245 loss: 2.7245 2022/10/09 08:23:02 - mmengine - INFO - Epoch(train) [12][1560/2119] lr: 4.0000e-02 eta: 1 day, 5:11:25 time: 0.3569 data_time: 0.0199 memory: 11108 grad_norm: 2.8627 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6058 loss: 2.6058 2022/10/09 08:23:09 - mmengine - INFO - Epoch(train) [12][1580/2119] lr: 4.0000e-02 eta: 1 day, 5:11:17 time: 0.3549 data_time: 0.0194 memory: 11108 grad_norm: 2.8209 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7786 loss: 2.7786 2022/10/09 08:23:16 - mmengine - INFO - Epoch(train) [12][1600/2119] lr: 4.0000e-02 eta: 1 day, 5:11:10 time: 0.3622 data_time: 0.0205 memory: 11108 grad_norm: 2.8598 top1_acc: 0.1875 top5_acc: 0.7500 loss_cls: 2.8312 loss: 2.8312 2022/10/09 08:23:23 - mmengine - INFO - Epoch(train) [12][1620/2119] lr: 4.0000e-02 eta: 1 day, 5:11:02 time: 0.3552 data_time: 0.0216 memory: 11108 grad_norm: 2.8380 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5293 loss: 2.5293 2022/10/09 08:23:30 - mmengine - INFO - Epoch(train) [12][1640/2119] lr: 4.0000e-02 eta: 1 day, 5:10:55 time: 0.3588 data_time: 0.0217 memory: 11108 grad_norm: 2.8597 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0227 loss: 3.0227 2022/10/09 08:23:37 - mmengine - INFO - Epoch(train) [12][1660/2119] lr: 4.0000e-02 eta: 1 day, 5:10:46 time: 0.3528 data_time: 0.0203 memory: 11108 grad_norm: 2.8081 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9660 loss: 2.9660 2022/10/09 08:23:44 - mmengine - INFO - Epoch(train) [12][1680/2119] lr: 4.0000e-02 eta: 1 day, 5:10:39 time: 0.3575 data_time: 0.0195 memory: 11108 grad_norm: 2.9011 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.7823 loss: 2.7823 2022/10/09 08:23:48 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 08:23:52 - mmengine - INFO - Epoch(train) [12][1700/2119] lr: 4.0000e-02 eta: 1 day, 5:10:32 time: 0.3583 data_time: 0.0214 memory: 11108 grad_norm: 2.8613 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6395 loss: 2.6395 2022/10/09 08:23:59 - mmengine - INFO - Epoch(train) [12][1720/2119] lr: 4.0000e-02 eta: 1 day, 5:10:25 time: 0.3619 data_time: 0.0210 memory: 11108 grad_norm: 2.8618 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5879 loss: 2.5879 2022/10/09 08:24:06 - mmengine - INFO - Epoch(train) [12][1740/2119] lr: 4.0000e-02 eta: 1 day, 5:10:18 time: 0.3560 data_time: 0.0189 memory: 11108 grad_norm: 2.8664 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8088 loss: 2.8088 2022/10/09 08:24:13 - mmengine - INFO - Epoch(train) [12][1760/2119] lr: 4.0000e-02 eta: 1 day, 5:10:10 time: 0.3561 data_time: 0.0213 memory: 11108 grad_norm: 2.8666 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7223 loss: 2.7223 2022/10/09 08:24:20 - mmengine - INFO - Epoch(train) [12][1780/2119] lr: 4.0000e-02 eta: 1 day, 5:10:02 time: 0.3557 data_time: 0.0190 memory: 11108 grad_norm: 2.8772 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7333 loss: 2.7333 2022/10/09 08:24:28 - mmengine - INFO - Epoch(train) [12][1800/2119] lr: 4.0000e-02 eta: 1 day, 5:09:57 time: 0.3678 data_time: 0.0254 memory: 11108 grad_norm: 2.8496 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8400 loss: 2.8400 2022/10/09 08:24:35 - mmengine - INFO - Epoch(train) [12][1820/2119] lr: 4.0000e-02 eta: 1 day, 5:09:49 time: 0.3551 data_time: 0.0196 memory: 11108 grad_norm: 2.7748 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6713 loss: 2.6713 2022/10/09 08:24:42 - mmengine - INFO - Epoch(train) [12][1840/2119] lr: 4.0000e-02 eta: 1 day, 5:09:41 time: 0.3576 data_time: 0.0255 memory: 11108 grad_norm: 2.8842 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7262 loss: 2.7262 2022/10/09 08:24:49 - mmengine - INFO - Epoch(train) [12][1860/2119] lr: 4.0000e-02 eta: 1 day, 5:09:34 time: 0.3553 data_time: 0.0208 memory: 11108 grad_norm: 2.8467 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0242 loss: 3.0242 2022/10/09 08:24:56 - mmengine - INFO - Epoch(train) [12][1880/2119] lr: 4.0000e-02 eta: 1 day, 5:09:26 time: 0.3552 data_time: 0.0173 memory: 11108 grad_norm: 2.8435 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7451 loss: 2.7451 2022/10/09 08:25:03 - mmengine - INFO - Epoch(train) [12][1900/2119] lr: 4.0000e-02 eta: 1 day, 5:09:18 time: 0.3569 data_time: 0.0228 memory: 11108 grad_norm: 2.8297 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8708 loss: 2.8708 2022/10/09 08:25:10 - mmengine - INFO - Epoch(train) [12][1920/2119] lr: 4.0000e-02 eta: 1 day, 5:09:11 time: 0.3591 data_time: 0.0221 memory: 11108 grad_norm: 2.8850 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7819 loss: 2.7819 2022/10/09 08:25:18 - mmengine - INFO - Epoch(train) [12][1940/2119] lr: 4.0000e-02 eta: 1 day, 5:09:04 time: 0.3587 data_time: 0.0194 memory: 11108 grad_norm: 2.8166 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6946 loss: 2.6946 2022/10/09 08:25:25 - mmengine - INFO - Epoch(train) [12][1960/2119] lr: 4.0000e-02 eta: 1 day, 5:08:56 time: 0.3578 data_time: 0.0188 memory: 11108 grad_norm: 2.8760 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8079 loss: 2.8079 2022/10/09 08:25:32 - mmengine - INFO - Epoch(train) [12][1980/2119] lr: 4.0000e-02 eta: 1 day, 5:08:50 time: 0.3634 data_time: 0.0193 memory: 11108 grad_norm: 2.9066 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0613 loss: 3.0613 2022/10/09 08:25:39 - mmengine - INFO - Epoch(train) [12][2000/2119] lr: 4.0000e-02 eta: 1 day, 5:08:44 time: 0.3644 data_time: 0.0203 memory: 11108 grad_norm: 2.8444 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5595 loss: 2.5595 2022/10/09 08:25:46 - mmengine - INFO - Epoch(train) [12][2020/2119] lr: 4.0000e-02 eta: 1 day, 5:08:37 time: 0.3576 data_time: 0.0180 memory: 11108 grad_norm: 2.8252 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7015 loss: 2.7015 2022/10/09 08:25:54 - mmengine - INFO - Epoch(train) [12][2040/2119] lr: 4.0000e-02 eta: 1 day, 5:08:30 time: 0.3584 data_time: 0.0189 memory: 11108 grad_norm: 2.8286 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7790 loss: 2.7790 2022/10/09 08:26:01 - mmengine - INFO - Epoch(train) [12][2060/2119] lr: 4.0000e-02 eta: 1 day, 5:08:22 time: 0.3577 data_time: 0.0200 memory: 11108 grad_norm: 2.9089 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.7721 loss: 2.7721 2022/10/09 08:26:08 - mmengine - INFO - Epoch(train) [12][2080/2119] lr: 4.0000e-02 eta: 1 day, 5:08:16 time: 0.3622 data_time: 0.0226 memory: 11108 grad_norm: 2.7822 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7258 loss: 2.7258 2022/10/09 08:26:15 - mmengine - INFO - Epoch(train) [12][2100/2119] lr: 4.0000e-02 eta: 1 day, 5:08:08 time: 0.3556 data_time: 0.0216 memory: 11108 grad_norm: 2.8379 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6109 loss: 2.6109 2022/10/09 08:26:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 08:26:22 - mmengine - INFO - Epoch(train) [12][2119/2119] lr: 4.0000e-02 eta: 1 day, 5:08:08 time: 0.3421 data_time: 0.0179 memory: 11108 grad_norm: 2.8558 top1_acc: 0.5000 top5_acc: 0.8000 loss_cls: 2.8119 loss: 2.8119 2022/10/09 08:26:22 - mmengine - INFO - Saving checkpoint at 12 epochs 2022/10/09 08:26:33 - mmengine - INFO - Epoch(train) [13][20/2119] lr: 4.0000e-02 eta: 1 day, 5:06:56 time: 0.4452 data_time: 0.1093 memory: 11108 grad_norm: 2.8715 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5808 loss: 2.5808 2022/10/09 08:26:40 - mmengine - INFO - Epoch(train) [13][40/2119] lr: 4.0000e-02 eta: 1 day, 5:06:48 time: 0.3571 data_time: 0.0212 memory: 11108 grad_norm: 2.9232 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7836 loss: 2.7836 2022/10/09 08:26:47 - mmengine - INFO - Epoch(train) [13][60/2119] lr: 4.0000e-02 eta: 1 day, 5:06:41 time: 0.3567 data_time: 0.0219 memory: 11108 grad_norm: 2.8745 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.8933 loss: 2.8933 2022/10/09 08:26:54 - mmengine - INFO - Epoch(train) [13][80/2119] lr: 4.0000e-02 eta: 1 day, 5:06:32 time: 0.3531 data_time: 0.0182 memory: 11108 grad_norm: 2.8576 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8336 loss: 2.8336 2022/10/09 08:27:01 - mmengine - INFO - Epoch(train) [13][100/2119] lr: 4.0000e-02 eta: 1 day, 5:06:24 time: 0.3556 data_time: 0.0186 memory: 11108 grad_norm: 2.8185 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7350 loss: 2.7350 2022/10/09 08:27:08 - mmengine - INFO - Epoch(train) [13][120/2119] lr: 4.0000e-02 eta: 1 day, 5:06:18 time: 0.3598 data_time: 0.0246 memory: 11108 grad_norm: 2.8366 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7461 loss: 2.7461 2022/10/09 08:27:15 - mmengine - INFO - Epoch(train) [13][140/2119] lr: 4.0000e-02 eta: 1 day, 5:06:09 time: 0.3504 data_time: 0.0190 memory: 11108 grad_norm: 2.8482 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7397 loss: 2.7397 2022/10/09 08:27:23 - mmengine - INFO - Epoch(train) [13][160/2119] lr: 4.0000e-02 eta: 1 day, 5:06:02 time: 0.3609 data_time: 0.0264 memory: 11108 grad_norm: 2.8141 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6794 loss: 2.6794 2022/10/09 08:27:30 - mmengine - INFO - Epoch(train) [13][180/2119] lr: 4.0000e-02 eta: 1 day, 5:05:55 time: 0.3575 data_time: 0.0181 memory: 11108 grad_norm: 2.8657 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4962 loss: 2.4962 2022/10/09 08:27:37 - mmengine - INFO - Epoch(train) [13][200/2119] lr: 4.0000e-02 eta: 1 day, 5:05:48 time: 0.3595 data_time: 0.0206 memory: 11108 grad_norm: 2.8630 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6313 loss: 2.6313 2022/10/09 08:27:44 - mmengine - INFO - Epoch(train) [13][220/2119] lr: 4.0000e-02 eta: 1 day, 5:05:40 time: 0.3564 data_time: 0.0202 memory: 11108 grad_norm: 2.9036 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6248 loss: 2.6248 2022/10/09 08:27:51 - mmengine - INFO - Epoch(train) [13][240/2119] lr: 4.0000e-02 eta: 1 day, 5:05:33 time: 0.3609 data_time: 0.0190 memory: 11108 grad_norm: 2.8483 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8163 loss: 2.8163 2022/10/09 08:27:58 - mmengine - INFO - Epoch(train) [13][260/2119] lr: 4.0000e-02 eta: 1 day, 5:05:26 time: 0.3561 data_time: 0.0180 memory: 11108 grad_norm: 2.8388 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8116 loss: 2.8116 2022/10/09 08:28:05 - mmengine - INFO - Epoch(train) [13][280/2119] lr: 4.0000e-02 eta: 1 day, 5:05:18 time: 0.3571 data_time: 0.0191 memory: 11108 grad_norm: 2.8831 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9578 loss: 2.9578 2022/10/09 08:28:13 - mmengine - INFO - Epoch(train) [13][300/2119] lr: 4.0000e-02 eta: 1 day, 5:05:11 time: 0.3571 data_time: 0.0176 memory: 11108 grad_norm: 2.8421 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6423 loss: 2.6423 2022/10/09 08:28:20 - mmengine - INFO - Epoch(train) [13][320/2119] lr: 4.0000e-02 eta: 1 day, 5:05:06 time: 0.3671 data_time: 0.0189 memory: 11108 grad_norm: 2.8573 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5906 loss: 2.5906 2022/10/09 08:28:27 - mmengine - INFO - Epoch(train) [13][340/2119] lr: 4.0000e-02 eta: 1 day, 5:04:59 time: 0.3597 data_time: 0.0183 memory: 11108 grad_norm: 2.8216 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8189 loss: 2.8189 2022/10/09 08:28:34 - mmengine - INFO - Epoch(train) [13][360/2119] lr: 4.0000e-02 eta: 1 day, 5:04:51 time: 0.3551 data_time: 0.0210 memory: 11108 grad_norm: 2.8209 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.6445 loss: 2.6445 2022/10/09 08:28:42 - mmengine - INFO - Epoch(train) [13][380/2119] lr: 4.0000e-02 eta: 1 day, 5:04:46 time: 0.3701 data_time: 0.0203 memory: 11108 grad_norm: 2.8497 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7889 loss: 2.7889 2022/10/09 08:28:49 - mmengine - INFO - Epoch(train) [13][400/2119] lr: 4.0000e-02 eta: 1 day, 5:04:39 time: 0.3572 data_time: 0.0207 memory: 11108 grad_norm: 2.8800 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8378 loss: 2.8378 2022/10/09 08:28:56 - mmengine - INFO - Epoch(train) [13][420/2119] lr: 4.0000e-02 eta: 1 day, 5:04:32 time: 0.3599 data_time: 0.0185 memory: 11108 grad_norm: 2.8951 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7293 loss: 2.7293 2022/10/09 08:29:03 - mmengine - INFO - Epoch(train) [13][440/2119] lr: 4.0000e-02 eta: 1 day, 5:04:24 time: 0.3535 data_time: 0.0192 memory: 11108 grad_norm: 2.8358 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6323 loss: 2.6323 2022/10/09 08:29:10 - mmengine - INFO - Epoch(train) [13][460/2119] lr: 4.0000e-02 eta: 1 day, 5:04:16 time: 0.3570 data_time: 0.0157 memory: 11108 grad_norm: 2.8146 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7422 loss: 2.7422 2022/10/09 08:29:18 - mmengine - INFO - Epoch(train) [13][480/2119] lr: 4.0000e-02 eta: 1 day, 5:04:11 time: 0.3659 data_time: 0.0198 memory: 11108 grad_norm: 2.8088 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6146 loss: 2.6146 2022/10/09 08:29:25 - mmengine - INFO - Epoch(train) [13][500/2119] lr: 4.0000e-02 eta: 1 day, 5:04:02 time: 0.3519 data_time: 0.0216 memory: 11108 grad_norm: 2.8602 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6231 loss: 2.6231 2022/10/09 08:29:32 - mmengine - INFO - Epoch(train) [13][520/2119] lr: 4.0000e-02 eta: 1 day, 5:03:55 time: 0.3593 data_time: 0.0183 memory: 11108 grad_norm: 2.8728 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8136 loss: 2.8136 2022/10/09 08:29:39 - mmengine - INFO - Epoch(train) [13][540/2119] lr: 4.0000e-02 eta: 1 day, 5:03:47 time: 0.3539 data_time: 0.0181 memory: 11108 grad_norm: 2.8594 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.4695 loss: 2.4695 2022/10/09 08:29:46 - mmengine - INFO - Epoch(train) [13][560/2119] lr: 4.0000e-02 eta: 1 day, 5:03:39 time: 0.3557 data_time: 0.0180 memory: 11108 grad_norm: 2.9143 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7239 loss: 2.7239 2022/10/09 08:29:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 08:29:53 - mmengine - INFO - Epoch(train) [13][580/2119] lr: 4.0000e-02 eta: 1 day, 5:03:31 time: 0.3561 data_time: 0.0217 memory: 11108 grad_norm: 2.8544 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7636 loss: 2.7636 2022/10/09 08:30:00 - mmengine - INFO - Epoch(train) [13][600/2119] lr: 4.0000e-02 eta: 1 day, 5:03:24 time: 0.3585 data_time: 0.0201 memory: 11108 grad_norm: 2.8093 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7725 loss: 2.7725 2022/10/09 08:30:07 - mmengine - INFO - Epoch(train) [13][620/2119] lr: 4.0000e-02 eta: 1 day, 5:03:17 time: 0.3593 data_time: 0.0210 memory: 11108 grad_norm: 2.8342 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7392 loss: 2.7392 2022/10/09 08:30:15 - mmengine - INFO - Epoch(train) [13][640/2119] lr: 4.0000e-02 eta: 1 day, 5:03:09 time: 0.3548 data_time: 0.0184 memory: 11108 grad_norm: 2.8079 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9853 loss: 2.9853 2022/10/09 08:30:22 - mmengine - INFO - Epoch(train) [13][660/2119] lr: 4.0000e-02 eta: 1 day, 5:03:02 time: 0.3575 data_time: 0.0174 memory: 11108 grad_norm: 2.8699 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9219 loss: 2.9219 2022/10/09 08:30:29 - mmengine - INFO - Epoch(train) [13][680/2119] lr: 4.0000e-02 eta: 1 day, 5:02:54 time: 0.3567 data_time: 0.0221 memory: 11108 grad_norm: 2.8634 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7040 loss: 2.7040 2022/10/09 08:30:36 - mmengine - INFO - Epoch(train) [13][700/2119] lr: 4.0000e-02 eta: 1 day, 5:02:47 time: 0.3602 data_time: 0.0284 memory: 11108 grad_norm: 2.8506 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6312 loss: 2.6312 2022/10/09 08:30:43 - mmengine - INFO - Epoch(train) [13][720/2119] lr: 4.0000e-02 eta: 1 day, 5:02:41 time: 0.3639 data_time: 0.0221 memory: 11108 grad_norm: 2.8930 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9591 loss: 2.9591 2022/10/09 08:30:51 - mmengine - INFO - Epoch(train) [13][740/2119] lr: 4.0000e-02 eta: 1 day, 5:02:35 time: 0.3620 data_time: 0.0202 memory: 11108 grad_norm: 2.8190 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6970 loss: 2.6970 2022/10/09 08:30:58 - mmengine - INFO - Epoch(train) [13][760/2119] lr: 4.0000e-02 eta: 1 day, 5:02:28 time: 0.3587 data_time: 0.0221 memory: 11108 grad_norm: 2.8342 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6629 loss: 2.6629 2022/10/09 08:31:05 - mmengine - INFO - Epoch(train) [13][780/2119] lr: 4.0000e-02 eta: 1 day, 5:02:20 time: 0.3570 data_time: 0.0212 memory: 11108 grad_norm: 2.8682 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7575 loss: 2.7575 2022/10/09 08:31:12 - mmengine - INFO - Epoch(train) [13][800/2119] lr: 4.0000e-02 eta: 1 day, 5:02:13 time: 0.3572 data_time: 0.0223 memory: 11108 grad_norm: 2.8692 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7315 loss: 2.7315 2022/10/09 08:31:19 - mmengine - INFO - Epoch(train) [13][820/2119] lr: 4.0000e-02 eta: 1 day, 5:02:08 time: 0.3694 data_time: 0.0242 memory: 11108 grad_norm: 2.8458 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7223 loss: 2.7223 2022/10/09 08:31:27 - mmengine - INFO - Epoch(train) [13][840/2119] lr: 4.0000e-02 eta: 1 day, 5:02:01 time: 0.3572 data_time: 0.0181 memory: 11108 grad_norm: 2.8433 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5356 loss: 2.5356 2022/10/09 08:31:34 - mmengine - INFO - Epoch(train) [13][860/2119] lr: 4.0000e-02 eta: 1 day, 5:01:54 time: 0.3586 data_time: 0.0243 memory: 11108 grad_norm: 2.8308 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5419 loss: 2.5419 2022/10/09 08:31:41 - mmengine - INFO - Epoch(train) [13][880/2119] lr: 4.0000e-02 eta: 1 day, 5:01:46 time: 0.3573 data_time: 0.0194 memory: 11108 grad_norm: 2.8436 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6929 loss: 2.6929 2022/10/09 08:31:48 - mmengine - INFO - Epoch(train) [13][900/2119] lr: 4.0000e-02 eta: 1 day, 5:01:39 time: 0.3593 data_time: 0.0232 memory: 11108 grad_norm: 2.8580 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8605 loss: 2.8605 2022/10/09 08:31:55 - mmengine - INFO - Epoch(train) [13][920/2119] lr: 4.0000e-02 eta: 1 day, 5:01:32 time: 0.3576 data_time: 0.0209 memory: 11108 grad_norm: 2.8485 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.8077 loss: 2.8077 2022/10/09 08:32:02 - mmengine - INFO - Epoch(train) [13][940/2119] lr: 4.0000e-02 eta: 1 day, 5:01:25 time: 0.3596 data_time: 0.0190 memory: 11108 grad_norm: 2.8065 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.9793 loss: 2.9793 2022/10/09 08:32:10 - mmengine - INFO - Epoch(train) [13][960/2119] lr: 4.0000e-02 eta: 1 day, 5:01:18 time: 0.3576 data_time: 0.0200 memory: 11108 grad_norm: 2.8452 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6619 loss: 2.6619 2022/10/09 08:32:17 - mmengine - INFO - Epoch(train) [13][980/2119] lr: 4.0000e-02 eta: 1 day, 5:01:11 time: 0.3627 data_time: 0.0210 memory: 11108 grad_norm: 2.8552 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7833 loss: 2.7833 2022/10/09 08:32:24 - mmengine - INFO - Epoch(train) [13][1000/2119] lr: 4.0000e-02 eta: 1 day, 5:01:03 time: 0.3538 data_time: 0.0188 memory: 11108 grad_norm: 2.8482 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6126 loss: 2.6126 2022/10/09 08:32:31 - mmengine - INFO - Epoch(train) [13][1020/2119] lr: 4.0000e-02 eta: 1 day, 5:00:55 time: 0.3554 data_time: 0.0194 memory: 11108 grad_norm: 2.8474 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5070 loss: 2.5070 2022/10/09 08:32:38 - mmengine - INFO - Epoch(train) [13][1040/2119] lr: 4.0000e-02 eta: 1 day, 5:00:49 time: 0.3612 data_time: 0.0193 memory: 11108 grad_norm: 2.8717 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5941 loss: 2.5941 2022/10/09 08:32:45 - mmengine - INFO - Epoch(train) [13][1060/2119] lr: 4.0000e-02 eta: 1 day, 5:00:41 time: 0.3560 data_time: 0.0200 memory: 11108 grad_norm: 2.8044 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6738 loss: 2.6738 2022/10/09 08:32:53 - mmengine - INFO - Epoch(train) [13][1080/2119] lr: 4.0000e-02 eta: 1 day, 5:00:34 time: 0.3610 data_time: 0.0262 memory: 11108 grad_norm: 2.8352 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7473 loss: 2.7473 2022/10/09 08:33:00 - mmengine - INFO - Epoch(train) [13][1100/2119] lr: 4.0000e-02 eta: 1 day, 5:00:27 time: 0.3580 data_time: 0.0180 memory: 11108 grad_norm: 2.8403 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9582 loss: 2.9582 2022/10/09 08:33:07 - mmengine - INFO - Epoch(train) [13][1120/2119] lr: 4.0000e-02 eta: 1 day, 5:00:20 time: 0.3575 data_time: 0.0232 memory: 11108 grad_norm: 2.8826 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6284 loss: 2.6284 2022/10/09 08:33:14 - mmengine - INFO - Epoch(train) [13][1140/2119] lr: 4.0000e-02 eta: 1 day, 5:00:12 time: 0.3556 data_time: 0.0208 memory: 11108 grad_norm: 2.8264 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7837 loss: 2.7837 2022/10/09 08:33:21 - mmengine - INFO - Epoch(train) [13][1160/2119] lr: 4.0000e-02 eta: 1 day, 5:00:06 time: 0.3633 data_time: 0.0196 memory: 11108 grad_norm: 2.8365 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7180 loss: 2.7180 2022/10/09 08:33:28 - mmengine - INFO - Epoch(train) [13][1180/2119] lr: 4.0000e-02 eta: 1 day, 4:59:58 time: 0.3559 data_time: 0.0207 memory: 11108 grad_norm: 2.8817 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7397 loss: 2.7397 2022/10/09 08:33:35 - mmengine - INFO - Epoch(train) [13][1200/2119] lr: 4.0000e-02 eta: 1 day, 4:59:50 time: 0.3549 data_time: 0.0227 memory: 11108 grad_norm: 2.8834 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7463 loss: 2.7463 2022/10/09 08:33:43 - mmengine - INFO - Epoch(train) [13][1220/2119] lr: 4.0000e-02 eta: 1 day, 4:59:43 time: 0.3596 data_time: 0.0238 memory: 11108 grad_norm: 2.8309 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7148 loss: 2.7148 2022/10/09 08:33:50 - mmengine - INFO - Epoch(train) [13][1240/2119] lr: 4.0000e-02 eta: 1 day, 4:59:36 time: 0.3587 data_time: 0.0216 memory: 11108 grad_norm: 2.8881 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7279 loss: 2.7279 2022/10/09 08:33:57 - mmengine - INFO - Epoch(train) [13][1260/2119] lr: 4.0000e-02 eta: 1 day, 4:59:28 time: 0.3545 data_time: 0.0199 memory: 11108 grad_norm: 2.8497 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.7046 loss: 2.7046 2022/10/09 08:34:04 - mmengine - INFO - Epoch(train) [13][1280/2119] lr: 4.0000e-02 eta: 1 day, 4:59:23 time: 0.3661 data_time: 0.0301 memory: 11108 grad_norm: 2.8318 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0319 loss: 3.0319 2022/10/09 08:34:11 - mmengine - INFO - Epoch(train) [13][1300/2119] lr: 4.0000e-02 eta: 1 day, 4:59:15 time: 0.3581 data_time: 0.0208 memory: 11108 grad_norm: 2.7913 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6702 loss: 2.6702 2022/10/09 08:34:19 - mmengine - INFO - Epoch(train) [13][1320/2119] lr: 4.0000e-02 eta: 1 day, 4:59:08 time: 0.3560 data_time: 0.0205 memory: 11108 grad_norm: 2.8878 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.6575 loss: 2.6575 2022/10/09 08:34:26 - mmengine - INFO - Epoch(train) [13][1340/2119] lr: 4.0000e-02 eta: 1 day, 4:58:59 time: 0.3535 data_time: 0.0182 memory: 11108 grad_norm: 2.7927 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7687 loss: 2.7687 2022/10/09 08:34:33 - mmengine - INFO - Epoch(train) [13][1360/2119] lr: 4.0000e-02 eta: 1 day, 4:58:52 time: 0.3566 data_time: 0.0197 memory: 11108 grad_norm: 2.8510 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9441 loss: 2.9441 2022/10/09 08:34:40 - mmengine - INFO - Epoch(train) [13][1380/2119] lr: 4.0000e-02 eta: 1 day, 4:58:45 time: 0.3596 data_time: 0.0226 memory: 11108 grad_norm: 2.8136 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7555 loss: 2.7555 2022/10/09 08:34:47 - mmengine - INFO - Epoch(train) [13][1400/2119] lr: 4.0000e-02 eta: 1 day, 4:58:37 time: 0.3553 data_time: 0.0214 memory: 11108 grad_norm: 2.8563 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7493 loss: 2.7493 2022/10/09 08:34:54 - mmengine - INFO - Epoch(train) [13][1420/2119] lr: 4.0000e-02 eta: 1 day, 4:58:30 time: 0.3566 data_time: 0.0181 memory: 11108 grad_norm: 2.8226 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6127 loss: 2.6127 2022/10/09 08:35:01 - mmengine - INFO - Epoch(train) [13][1440/2119] lr: 4.0000e-02 eta: 1 day, 4:58:22 time: 0.3589 data_time: 0.0200 memory: 11108 grad_norm: 2.8926 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7790 loss: 2.7790 2022/10/09 08:35:09 - mmengine - INFO - Epoch(train) [13][1460/2119] lr: 4.0000e-02 eta: 1 day, 4:58:16 time: 0.3607 data_time: 0.0187 memory: 11108 grad_norm: 2.8318 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.7712 loss: 2.7712 2022/10/09 08:35:16 - mmengine - INFO - Epoch(train) [13][1480/2119] lr: 4.0000e-02 eta: 1 day, 4:58:08 time: 0.3573 data_time: 0.0191 memory: 11108 grad_norm: 2.7963 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9120 loss: 2.9120 2022/10/09 08:35:23 - mmengine - INFO - Epoch(train) [13][1500/2119] lr: 4.0000e-02 eta: 1 day, 4:58:02 time: 0.3628 data_time: 0.0202 memory: 11108 grad_norm: 2.8336 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7359 loss: 2.7359 2022/10/09 08:35:30 - mmengine - INFO - Epoch(train) [13][1520/2119] lr: 4.0000e-02 eta: 1 day, 4:57:54 time: 0.3557 data_time: 0.0185 memory: 11108 grad_norm: 2.8084 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5644 loss: 2.5644 2022/10/09 08:35:37 - mmengine - INFO - Epoch(train) [13][1540/2119] lr: 4.0000e-02 eta: 1 day, 4:57:48 time: 0.3613 data_time: 0.0220 memory: 11108 grad_norm: 2.8617 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7666 loss: 2.7666 2022/10/09 08:35:44 - mmengine - INFO - Epoch(train) [13][1560/2119] lr: 4.0000e-02 eta: 1 day, 4:57:41 time: 0.3582 data_time: 0.0211 memory: 11108 grad_norm: 2.8229 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 2.5833 loss: 2.5833 2022/10/09 08:35:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 08:35:52 - mmengine - INFO - Epoch(train) [13][1580/2119] lr: 4.0000e-02 eta: 1 day, 4:57:34 time: 0.3604 data_time: 0.0235 memory: 11108 grad_norm: 2.7581 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6968 loss: 2.6968 2022/10/09 08:35:59 - mmengine - INFO - Epoch(train) [13][1600/2119] lr: 4.0000e-02 eta: 1 day, 4:57:30 time: 0.3747 data_time: 0.0239 memory: 11108 grad_norm: 2.7932 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5695 loss: 2.5695 2022/10/09 08:36:06 - mmengine - INFO - Epoch(train) [13][1620/2119] lr: 4.0000e-02 eta: 1 day, 4:57:22 time: 0.3529 data_time: 0.0181 memory: 11108 grad_norm: 2.8269 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6107 loss: 2.6107 2022/10/09 08:36:13 - mmengine - INFO - Epoch(train) [13][1640/2119] lr: 4.0000e-02 eta: 1 day, 4:57:15 time: 0.3588 data_time: 0.0208 memory: 11108 grad_norm: 2.7675 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6071 loss: 2.6071 2022/10/09 08:36:21 - mmengine - INFO - Epoch(train) [13][1660/2119] lr: 4.0000e-02 eta: 1 day, 4:57:07 time: 0.3568 data_time: 0.0199 memory: 11108 grad_norm: 2.8278 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6166 loss: 2.6166 2022/10/09 08:36:28 - mmengine - INFO - Epoch(train) [13][1680/2119] lr: 4.0000e-02 eta: 1 day, 4:57:01 time: 0.3623 data_time: 0.0220 memory: 11108 grad_norm: 2.8411 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6334 loss: 2.6334 2022/10/09 08:36:35 - mmengine - INFO - Epoch(train) [13][1700/2119] lr: 4.0000e-02 eta: 1 day, 4:56:52 time: 0.3531 data_time: 0.0180 memory: 11108 grad_norm: 2.8800 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8266 loss: 2.8266 2022/10/09 08:36:42 - mmengine - INFO - Epoch(train) [13][1720/2119] lr: 4.0000e-02 eta: 1 day, 4:56:45 time: 0.3591 data_time: 0.0216 memory: 11108 grad_norm: 2.8619 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6615 loss: 2.6615 2022/10/09 08:36:49 - mmengine - INFO - Epoch(train) [13][1740/2119] lr: 4.0000e-02 eta: 1 day, 4:56:41 time: 0.3720 data_time: 0.0201 memory: 11108 grad_norm: 2.8122 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8250 loss: 2.8250 2022/10/09 08:36:57 - mmengine - INFO - Epoch(train) [13][1760/2119] lr: 4.0000e-02 eta: 1 day, 4:56:34 time: 0.3565 data_time: 0.0211 memory: 11108 grad_norm: 2.8897 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8194 loss: 2.8194 2022/10/09 08:37:04 - mmengine - INFO - Epoch(train) [13][1780/2119] lr: 4.0000e-02 eta: 1 day, 4:56:26 time: 0.3586 data_time: 0.0195 memory: 11108 grad_norm: 2.8450 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.4332 loss: 2.4332 2022/10/09 08:37:11 - mmengine - INFO - Epoch(train) [13][1800/2119] lr: 4.0000e-02 eta: 1 day, 4:56:19 time: 0.3556 data_time: 0.0222 memory: 11108 grad_norm: 2.7811 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6671 loss: 2.6671 2022/10/09 08:37:18 - mmengine - INFO - Epoch(train) [13][1820/2119] lr: 4.0000e-02 eta: 1 day, 4:56:11 time: 0.3571 data_time: 0.0241 memory: 11108 grad_norm: 2.8164 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7085 loss: 2.7085 2022/10/09 08:37:25 - mmengine - INFO - Epoch(train) [13][1840/2119] lr: 4.0000e-02 eta: 1 day, 4:56:04 time: 0.3567 data_time: 0.0210 memory: 11108 grad_norm: 2.8282 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6677 loss: 2.6677 2022/10/09 08:37:32 - mmengine - INFO - Epoch(train) [13][1860/2119] lr: 4.0000e-02 eta: 1 day, 4:55:57 time: 0.3628 data_time: 0.0213 memory: 11108 grad_norm: 2.8122 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6485 loss: 2.6485 2022/10/09 08:37:40 - mmengine - INFO - Epoch(train) [13][1880/2119] lr: 4.0000e-02 eta: 1 day, 4:55:50 time: 0.3569 data_time: 0.0227 memory: 11108 grad_norm: 2.9226 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5951 loss: 2.5951 2022/10/09 08:37:47 - mmengine - INFO - Epoch(train) [13][1900/2119] lr: 4.0000e-02 eta: 1 day, 4:55:42 time: 0.3538 data_time: 0.0202 memory: 11108 grad_norm: 2.8019 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.6519 loss: 2.6519 2022/10/09 08:37:54 - mmengine - INFO - Epoch(train) [13][1920/2119] lr: 4.0000e-02 eta: 1 day, 4:55:34 time: 0.3537 data_time: 0.0204 memory: 11108 grad_norm: 2.7931 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5316 loss: 2.5316 2022/10/09 08:38:01 - mmengine - INFO - Epoch(train) [13][1940/2119] lr: 4.0000e-02 eta: 1 day, 4:55:27 time: 0.3604 data_time: 0.0244 memory: 11108 grad_norm: 2.8049 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6231 loss: 2.6231 2022/10/09 08:38:08 - mmengine - INFO - Epoch(train) [13][1960/2119] lr: 4.0000e-02 eta: 1 day, 4:55:20 time: 0.3588 data_time: 0.0222 memory: 11108 grad_norm: 2.8251 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6275 loss: 2.6275 2022/10/09 08:38:15 - mmengine - INFO - Epoch(train) [13][1980/2119] lr: 4.0000e-02 eta: 1 day, 4:55:12 time: 0.3580 data_time: 0.0215 memory: 11108 grad_norm: 2.8953 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5413 loss: 2.5413 2022/10/09 08:38:22 - mmengine - INFO - Epoch(train) [13][2000/2119] lr: 4.0000e-02 eta: 1 day, 4:55:05 time: 0.3586 data_time: 0.0227 memory: 11108 grad_norm: 2.8658 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4617 loss: 2.4617 2022/10/09 08:38:30 - mmengine - INFO - Epoch(train) [13][2020/2119] lr: 4.0000e-02 eta: 1 day, 4:54:58 time: 0.3564 data_time: 0.0211 memory: 11108 grad_norm: 2.8205 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8423 loss: 2.8423 2022/10/09 08:38:37 - mmengine - INFO - Epoch(train) [13][2040/2119] lr: 4.0000e-02 eta: 1 day, 4:54:50 time: 0.3546 data_time: 0.0232 memory: 11108 grad_norm: 2.8266 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7227 loss: 2.7227 2022/10/09 08:38:44 - mmengine - INFO - Epoch(train) [13][2060/2119] lr: 4.0000e-02 eta: 1 day, 4:54:43 time: 0.3597 data_time: 0.0192 memory: 11108 grad_norm: 2.7823 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.4694 loss: 2.4694 2022/10/09 08:38:51 - mmengine - INFO - Epoch(train) [13][2080/2119] lr: 4.0000e-02 eta: 1 day, 4:54:35 time: 0.3574 data_time: 0.0199 memory: 11108 grad_norm: 2.7997 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8037 loss: 2.8037 2022/10/09 08:38:58 - mmengine - INFO - Epoch(train) [13][2100/2119] lr: 4.0000e-02 eta: 1 day, 4:54:27 time: 0.3533 data_time: 0.0227 memory: 11108 grad_norm: 2.8115 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8640 loss: 2.8640 2022/10/09 08:39:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 08:39:04 - mmengine - INFO - Epoch(train) [13][2119/2119] lr: 4.0000e-02 eta: 1 day, 4:54:27 time: 0.3392 data_time: 0.0204 memory: 11108 grad_norm: 2.8519 top1_acc: 0.6000 top5_acc: 0.7000 loss_cls: 2.5945 loss: 2.5945 2022/10/09 08:39:15 - mmengine - INFO - Epoch(train) [14][20/2119] lr: 4.0000e-02 eta: 1 day, 4:53:38 time: 0.5305 data_time: 0.1272 memory: 11108 grad_norm: 2.7778 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5890 loss: 2.5890 2022/10/09 08:39:22 - mmengine - INFO - Epoch(train) [14][40/2119] lr: 4.0000e-02 eta: 1 day, 4:53:30 time: 0.3577 data_time: 0.0187 memory: 11108 grad_norm: 2.8198 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7965 loss: 2.7965 2022/10/09 08:39:29 - mmengine - INFO - Epoch(train) [14][60/2119] lr: 4.0000e-02 eta: 1 day, 4:53:22 time: 0.3549 data_time: 0.0207 memory: 11108 grad_norm: 2.8329 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.6467 loss: 2.6467 2022/10/09 08:39:37 - mmengine - INFO - Epoch(train) [14][80/2119] lr: 4.0000e-02 eta: 1 day, 4:53:15 time: 0.3556 data_time: 0.0231 memory: 11108 grad_norm: 2.8665 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4115 loss: 2.4115 2022/10/09 08:39:44 - mmengine - INFO - Epoch(train) [14][100/2119] lr: 4.0000e-02 eta: 1 day, 4:53:08 time: 0.3603 data_time: 0.0208 memory: 11108 grad_norm: 2.8132 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7425 loss: 2.7425 2022/10/09 08:39:51 - mmengine - INFO - Epoch(train) [14][120/2119] lr: 4.0000e-02 eta: 1 day, 4:53:01 time: 0.3579 data_time: 0.0224 memory: 11108 grad_norm: 2.8423 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6240 loss: 2.6240 2022/10/09 08:39:58 - mmengine - INFO - Epoch(train) [14][140/2119] lr: 4.0000e-02 eta: 1 day, 4:52:53 time: 0.3562 data_time: 0.0195 memory: 11108 grad_norm: 2.8304 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7499 loss: 2.7499 2022/10/09 08:40:05 - mmengine - INFO - Epoch(train) [14][160/2119] lr: 4.0000e-02 eta: 1 day, 4:52:47 time: 0.3616 data_time: 0.0204 memory: 11108 grad_norm: 2.8537 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7063 loss: 2.7063 2022/10/09 08:40:12 - mmengine - INFO - Epoch(train) [14][180/2119] lr: 4.0000e-02 eta: 1 day, 4:52:40 time: 0.3585 data_time: 0.0209 memory: 11108 grad_norm: 2.8395 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8408 loss: 2.8408 2022/10/09 08:40:20 - mmengine - INFO - Epoch(train) [14][200/2119] lr: 4.0000e-02 eta: 1 day, 4:52:32 time: 0.3571 data_time: 0.0193 memory: 11108 grad_norm: 2.8733 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5817 loss: 2.5817 2022/10/09 08:40:27 - mmengine - INFO - Epoch(train) [14][220/2119] lr: 4.0000e-02 eta: 1 day, 4:52:26 time: 0.3611 data_time: 0.0206 memory: 11108 grad_norm: 2.8327 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7023 loss: 2.7023 2022/10/09 08:40:34 - mmengine - INFO - Epoch(train) [14][240/2119] lr: 4.0000e-02 eta: 1 day, 4:52:19 time: 0.3597 data_time: 0.0222 memory: 11108 grad_norm: 2.8014 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7065 loss: 2.7065 2022/10/09 08:40:41 - mmengine - INFO - Epoch(train) [14][260/2119] lr: 4.0000e-02 eta: 1 day, 4:52:11 time: 0.3565 data_time: 0.0187 memory: 11108 grad_norm: 2.8027 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8405 loss: 2.8405 2022/10/09 08:40:48 - mmengine - INFO - Epoch(train) [14][280/2119] lr: 4.0000e-02 eta: 1 day, 4:52:05 time: 0.3622 data_time: 0.0177 memory: 11108 grad_norm: 2.8395 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5054 loss: 2.5054 2022/10/09 08:40:55 - mmengine - INFO - Epoch(train) [14][300/2119] lr: 4.0000e-02 eta: 1 day, 4:51:57 time: 0.3552 data_time: 0.0231 memory: 11108 grad_norm: 2.8535 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5005 loss: 2.5005 2022/10/09 08:41:03 - mmengine - INFO - Epoch(train) [14][320/2119] lr: 4.0000e-02 eta: 1 day, 4:51:50 time: 0.3589 data_time: 0.0225 memory: 11108 grad_norm: 2.8578 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8353 loss: 2.8353 2022/10/09 08:41:10 - mmengine - INFO - Epoch(train) [14][340/2119] lr: 4.0000e-02 eta: 1 day, 4:51:43 time: 0.3579 data_time: 0.0221 memory: 11108 grad_norm: 2.8541 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6758 loss: 2.6758 2022/10/09 08:41:17 - mmengine - INFO - Epoch(train) [14][360/2119] lr: 4.0000e-02 eta: 1 day, 4:51:35 time: 0.3562 data_time: 0.0206 memory: 11108 grad_norm: 2.8369 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7036 loss: 2.7036 2022/10/09 08:41:24 - mmengine - INFO - Epoch(train) [14][380/2119] lr: 4.0000e-02 eta: 1 day, 4:51:28 time: 0.3595 data_time: 0.0237 memory: 11108 grad_norm: 2.8217 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6841 loss: 2.6841 2022/10/09 08:41:31 - mmengine - INFO - Epoch(train) [14][400/2119] lr: 4.0000e-02 eta: 1 day, 4:51:20 time: 0.3545 data_time: 0.0232 memory: 11108 grad_norm: 2.8367 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8205 loss: 2.8205 2022/10/09 08:41:38 - mmengine - INFO - Epoch(train) [14][420/2119] lr: 4.0000e-02 eta: 1 day, 4:51:13 time: 0.3568 data_time: 0.0194 memory: 11108 grad_norm: 2.8265 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6102 loss: 2.6102 2022/10/09 08:41:46 - mmengine - INFO - Epoch(train) [14][440/2119] lr: 4.0000e-02 eta: 1 day, 4:51:06 time: 0.3611 data_time: 0.0270 memory: 11108 grad_norm: 2.8497 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8971 loss: 2.8971 2022/10/09 08:41:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 08:41:53 - mmengine - INFO - Epoch(train) [14][460/2119] lr: 4.0000e-02 eta: 1 day, 4:50:59 time: 0.3570 data_time: 0.0170 memory: 11108 grad_norm: 2.8183 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5811 loss: 2.5811 2022/10/09 08:42:00 - mmengine - INFO - Epoch(train) [14][480/2119] lr: 4.0000e-02 eta: 1 day, 4:50:51 time: 0.3567 data_time: 0.0221 memory: 11108 grad_norm: 2.8625 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6127 loss: 2.6127 2022/10/09 08:42:07 - mmengine - INFO - Epoch(train) [14][500/2119] lr: 4.0000e-02 eta: 1 day, 4:50:44 time: 0.3573 data_time: 0.0210 memory: 11108 grad_norm: 2.8658 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8560 loss: 2.8560 2022/10/09 08:42:14 - mmengine - INFO - Epoch(train) [14][520/2119] lr: 4.0000e-02 eta: 1 day, 4:50:36 time: 0.3568 data_time: 0.0215 memory: 11108 grad_norm: 2.8582 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7148 loss: 2.7148 2022/10/09 08:42:21 - mmengine - INFO - Epoch(train) [14][540/2119] lr: 4.0000e-02 eta: 1 day, 4:50:29 time: 0.3579 data_time: 0.0269 memory: 11108 grad_norm: 2.7981 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6853 loss: 2.6853 2022/10/09 08:42:29 - mmengine - INFO - Epoch(train) [14][560/2119] lr: 4.0000e-02 eta: 1 day, 4:50:23 time: 0.3660 data_time: 0.0213 memory: 11108 grad_norm: 2.8713 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5155 loss: 2.5155 2022/10/09 08:42:36 - mmengine - INFO - Epoch(train) [14][580/2119] lr: 4.0000e-02 eta: 1 day, 4:50:17 time: 0.3601 data_time: 0.0219 memory: 11108 grad_norm: 2.8738 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8059 loss: 2.8059 2022/10/09 08:42:43 - mmengine - INFO - Epoch(train) [14][600/2119] lr: 4.0000e-02 eta: 1 day, 4:50:10 time: 0.3593 data_time: 0.0190 memory: 11108 grad_norm: 2.8092 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4469 loss: 2.4469 2022/10/09 08:42:50 - mmengine - INFO - Epoch(train) [14][620/2119] lr: 4.0000e-02 eta: 1 day, 4:50:04 time: 0.3638 data_time: 0.0217 memory: 11108 grad_norm: 2.8205 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6099 loss: 2.6099 2022/10/09 08:42:57 - mmengine - INFO - Epoch(train) [14][640/2119] lr: 4.0000e-02 eta: 1 day, 4:49:56 time: 0.3561 data_time: 0.0225 memory: 11108 grad_norm: 2.7922 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6161 loss: 2.6161 2022/10/09 08:43:05 - mmengine - INFO - Epoch(train) [14][660/2119] lr: 4.0000e-02 eta: 1 day, 4:49:50 time: 0.3624 data_time: 0.0191 memory: 11108 grad_norm: 2.8309 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9259 loss: 2.9259 2022/10/09 08:43:12 - mmengine - INFO - Epoch(train) [14][680/2119] lr: 4.0000e-02 eta: 1 day, 4:49:43 time: 0.3588 data_time: 0.0244 memory: 11108 grad_norm: 2.8025 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7541 loss: 2.7541 2022/10/09 08:43:19 - mmengine - INFO - Epoch(train) [14][700/2119] lr: 4.0000e-02 eta: 1 day, 4:49:34 time: 0.3540 data_time: 0.0195 memory: 11108 grad_norm: 2.8138 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5163 loss: 2.5163 2022/10/09 08:43:26 - mmengine - INFO - Epoch(train) [14][720/2119] lr: 4.0000e-02 eta: 1 day, 4:49:27 time: 0.3550 data_time: 0.0212 memory: 11108 grad_norm: 2.8694 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6683 loss: 2.6683 2022/10/09 08:43:33 - mmengine - INFO - Epoch(train) [14][740/2119] lr: 4.0000e-02 eta: 1 day, 4:49:21 time: 0.3638 data_time: 0.0227 memory: 11108 grad_norm: 2.8099 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5854 loss: 2.5854 2022/10/09 08:43:40 - mmengine - INFO - Epoch(train) [14][760/2119] lr: 4.0000e-02 eta: 1 day, 4:49:13 time: 0.3550 data_time: 0.0196 memory: 11108 grad_norm: 2.7487 top1_acc: 0.1875 top5_acc: 0.7500 loss_cls: 2.6052 loss: 2.6052 2022/10/09 08:43:48 - mmengine - INFO - Epoch(train) [14][780/2119] lr: 4.0000e-02 eta: 1 day, 4:49:06 time: 0.3598 data_time: 0.0205 memory: 11108 grad_norm: 2.8048 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6721 loss: 2.6721 2022/10/09 08:43:55 - mmengine - INFO - Epoch(train) [14][800/2119] lr: 4.0000e-02 eta: 1 day, 4:48:59 time: 0.3583 data_time: 0.0225 memory: 11108 grad_norm: 2.8730 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4960 loss: 2.4960 2022/10/09 08:44:02 - mmengine - INFO - Epoch(train) [14][820/2119] lr: 4.0000e-02 eta: 1 day, 4:48:51 time: 0.3560 data_time: 0.0206 memory: 11108 grad_norm: 2.8741 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5457 loss: 2.5457 2022/10/09 08:44:09 - mmengine - INFO - Epoch(train) [14][840/2119] lr: 4.0000e-02 eta: 1 day, 4:48:44 time: 0.3589 data_time: 0.0225 memory: 11108 grad_norm: 2.8601 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6611 loss: 2.6611 2022/10/09 08:44:16 - mmengine - INFO - Epoch(train) [14][860/2119] lr: 4.0000e-02 eta: 1 day, 4:48:36 time: 0.3560 data_time: 0.0187 memory: 11108 grad_norm: 2.8357 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4436 loss: 2.4436 2022/10/09 08:44:23 - mmengine - INFO - Epoch(train) [14][880/2119] lr: 4.0000e-02 eta: 1 day, 4:48:29 time: 0.3597 data_time: 0.0209 memory: 11108 grad_norm: 2.8713 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6481 loss: 2.6481 2022/10/09 08:44:30 - mmengine - INFO - Epoch(train) [14][900/2119] lr: 4.0000e-02 eta: 1 day, 4:48:21 time: 0.3518 data_time: 0.0204 memory: 11108 grad_norm: 2.8916 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6106 loss: 2.6106 2022/10/09 08:44:38 - mmengine - INFO - Epoch(train) [14][920/2119] lr: 4.0000e-02 eta: 1 day, 4:48:14 time: 0.3572 data_time: 0.0214 memory: 11108 grad_norm: 2.8069 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7887 loss: 2.7887 2022/10/09 08:44:45 - mmengine - INFO - Epoch(train) [14][940/2119] lr: 4.0000e-02 eta: 1 day, 4:48:07 time: 0.3611 data_time: 0.0226 memory: 11108 grad_norm: 2.7929 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6451 loss: 2.6451 2022/10/09 08:44:52 - mmengine - INFO - Epoch(train) [14][960/2119] lr: 4.0000e-02 eta: 1 day, 4:48:00 time: 0.3583 data_time: 0.0246 memory: 11108 grad_norm: 2.8298 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6896 loss: 2.6896 2022/10/09 08:44:59 - mmengine - INFO - Epoch(train) [14][980/2119] lr: 4.0000e-02 eta: 1 day, 4:47:52 time: 0.3554 data_time: 0.0211 memory: 11108 grad_norm: 2.8137 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6605 loss: 2.6605 2022/10/09 08:45:06 - mmengine - INFO - Epoch(train) [14][1000/2119] lr: 4.0000e-02 eta: 1 day, 4:47:46 time: 0.3620 data_time: 0.0187 memory: 11108 grad_norm: 2.8200 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5505 loss: 2.5505 2022/10/09 08:45:14 - mmengine - INFO - Epoch(train) [14][1020/2119] lr: 4.0000e-02 eta: 1 day, 4:47:40 time: 0.3654 data_time: 0.0233 memory: 11108 grad_norm: 2.8174 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6680 loss: 2.6680 2022/10/09 08:45:21 - mmengine - INFO - Epoch(train) [14][1040/2119] lr: 4.0000e-02 eta: 1 day, 4:47:33 time: 0.3597 data_time: 0.0231 memory: 11108 grad_norm: 2.8460 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4908 loss: 2.4908 2022/10/09 08:45:28 - mmengine - INFO - Epoch(train) [14][1060/2119] lr: 4.0000e-02 eta: 1 day, 4:47:27 time: 0.3617 data_time: 0.0217 memory: 11108 grad_norm: 2.8030 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7845 loss: 2.7845 2022/10/09 08:45:35 - mmengine - INFO - Epoch(train) [14][1080/2119] lr: 4.0000e-02 eta: 1 day, 4:47:18 time: 0.3536 data_time: 0.0242 memory: 11108 grad_norm: 2.8608 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5614 loss: 2.5614 2022/10/09 08:45:42 - mmengine - INFO - Epoch(train) [14][1100/2119] lr: 4.0000e-02 eta: 1 day, 4:47:12 time: 0.3597 data_time: 0.0172 memory: 11108 grad_norm: 2.8263 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4431 loss: 2.4431 2022/10/09 08:45:50 - mmengine - INFO - Epoch(train) [14][1120/2119] lr: 4.0000e-02 eta: 1 day, 4:47:06 time: 0.3644 data_time: 0.0251 memory: 11108 grad_norm: 2.7886 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8128 loss: 2.8128 2022/10/09 08:45:57 - mmengine - INFO - Epoch(train) [14][1140/2119] lr: 4.0000e-02 eta: 1 day, 4:46:57 time: 0.3537 data_time: 0.0179 memory: 11108 grad_norm: 2.8288 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9052 loss: 2.9052 2022/10/09 08:46:04 - mmengine - INFO - Epoch(train) [14][1160/2119] lr: 4.0000e-02 eta: 1 day, 4:46:51 time: 0.3601 data_time: 0.0232 memory: 11108 grad_norm: 2.8558 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6413 loss: 2.6413 2022/10/09 08:46:11 - mmengine - INFO - Epoch(train) [14][1180/2119] lr: 4.0000e-02 eta: 1 day, 4:46:43 time: 0.3547 data_time: 0.0182 memory: 11108 grad_norm: 2.8387 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6570 loss: 2.6570 2022/10/09 08:46:18 - mmengine - INFO - Epoch(train) [14][1200/2119] lr: 4.0000e-02 eta: 1 day, 4:46:36 time: 0.3598 data_time: 0.0191 memory: 11108 grad_norm: 2.8325 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6848 loss: 2.6848 2022/10/09 08:46:25 - mmengine - INFO - Epoch(train) [14][1220/2119] lr: 4.0000e-02 eta: 1 day, 4:46:28 time: 0.3562 data_time: 0.0181 memory: 11108 grad_norm: 2.8711 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5813 loss: 2.5813 2022/10/09 08:46:33 - mmengine - INFO - Epoch(train) [14][1240/2119] lr: 4.0000e-02 eta: 1 day, 4:46:22 time: 0.3620 data_time: 0.0197 memory: 11108 grad_norm: 2.8282 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8601 loss: 2.8601 2022/10/09 08:46:40 - mmengine - INFO - Epoch(train) [14][1260/2119] lr: 4.0000e-02 eta: 1 day, 4:46:16 time: 0.3625 data_time: 0.0188 memory: 11108 grad_norm: 2.7891 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9418 loss: 2.9418 2022/10/09 08:46:47 - mmengine - INFO - Epoch(train) [14][1280/2119] lr: 4.0000e-02 eta: 1 day, 4:46:08 time: 0.3561 data_time: 0.0217 memory: 11108 grad_norm: 2.7540 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6180 loss: 2.6180 2022/10/09 08:46:54 - mmengine - INFO - Epoch(train) [14][1300/2119] lr: 4.0000e-02 eta: 1 day, 4:46:00 time: 0.3564 data_time: 0.0186 memory: 11108 grad_norm: 2.8331 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5696 loss: 2.5696 2022/10/09 08:47:01 - mmengine - INFO - Epoch(train) [14][1320/2119] lr: 4.0000e-02 eta: 1 day, 4:45:54 time: 0.3606 data_time: 0.0239 memory: 11108 grad_norm: 2.8122 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6646 loss: 2.6646 2022/10/09 08:47:08 - mmengine - INFO - Epoch(train) [14][1340/2119] lr: 4.0000e-02 eta: 1 day, 4:45:46 time: 0.3558 data_time: 0.0180 memory: 11108 grad_norm: 2.7903 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6097 loss: 2.6097 2022/10/09 08:47:16 - mmengine - INFO - Epoch(train) [14][1360/2119] lr: 4.0000e-02 eta: 1 day, 4:45:39 time: 0.3612 data_time: 0.0293 memory: 11108 grad_norm: 2.8012 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.4946 loss: 2.4946 2022/10/09 08:47:23 - mmengine - INFO - Epoch(train) [14][1380/2119] lr: 4.0000e-02 eta: 1 day, 4:45:32 time: 0.3595 data_time: 0.0186 memory: 11108 grad_norm: 2.8743 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6424 loss: 2.6424 2022/10/09 08:47:30 - mmengine - INFO - Epoch(train) [14][1400/2119] lr: 4.0000e-02 eta: 1 day, 4:45:27 time: 0.3651 data_time: 0.0202 memory: 11108 grad_norm: 2.7886 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6325 loss: 2.6325 2022/10/09 08:47:37 - mmengine - INFO - Epoch(train) [14][1420/2119] lr: 4.0000e-02 eta: 1 day, 4:45:19 time: 0.3582 data_time: 0.0216 memory: 11108 grad_norm: 2.7962 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8396 loss: 2.8396 2022/10/09 08:47:45 - mmengine - INFO - Epoch(train) [14][1440/2119] lr: 4.0000e-02 eta: 1 day, 4:45:14 time: 0.3650 data_time: 0.0209 memory: 11108 grad_norm: 2.8607 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5772 loss: 2.5772 2022/10/09 08:47:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 08:47:52 - mmengine - INFO - Epoch(train) [14][1460/2119] lr: 4.0000e-02 eta: 1 day, 4:45:06 time: 0.3545 data_time: 0.0234 memory: 11108 grad_norm: 2.8247 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6024 loss: 2.6024 2022/10/09 08:47:59 - mmengine - INFO - Epoch(train) [14][1480/2119] lr: 4.0000e-02 eta: 1 day, 4:44:58 time: 0.3580 data_time: 0.0193 memory: 11108 grad_norm: 2.8622 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8766 loss: 2.8766 2022/10/09 08:48:06 - mmengine - INFO - Epoch(train) [14][1500/2119] lr: 4.0000e-02 eta: 1 day, 4:44:52 time: 0.3597 data_time: 0.0174 memory: 11108 grad_norm: 2.8095 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.8629 loss: 2.8629 2022/10/09 08:48:13 - mmengine - INFO - Epoch(train) [14][1520/2119] lr: 4.0000e-02 eta: 1 day, 4:44:44 time: 0.3562 data_time: 0.0177 memory: 11108 grad_norm: 2.8043 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6190 loss: 2.6190 2022/10/09 08:48:20 - mmengine - INFO - Epoch(train) [14][1540/2119] lr: 4.0000e-02 eta: 1 day, 4:44:38 time: 0.3646 data_time: 0.0236 memory: 11108 grad_norm: 2.7975 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7129 loss: 2.7129 2022/10/09 08:48:28 - mmengine - INFO - Epoch(train) [14][1560/2119] lr: 4.0000e-02 eta: 1 day, 4:44:31 time: 0.3569 data_time: 0.0209 memory: 11108 grad_norm: 2.8226 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.9151 loss: 2.9151 2022/10/09 08:48:35 - mmengine - INFO - Epoch(train) [14][1580/2119] lr: 4.0000e-02 eta: 1 day, 4:44:23 time: 0.3561 data_time: 0.0236 memory: 11108 grad_norm: 2.8223 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6069 loss: 2.6069 2022/10/09 08:48:42 - mmengine - INFO - Epoch(train) [14][1600/2119] lr: 4.0000e-02 eta: 1 day, 4:44:16 time: 0.3613 data_time: 0.0216 memory: 11108 grad_norm: 2.8459 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7895 loss: 2.7895 2022/10/09 08:48:49 - mmengine - INFO - Epoch(train) [14][1620/2119] lr: 4.0000e-02 eta: 1 day, 4:44:09 time: 0.3555 data_time: 0.0207 memory: 11108 grad_norm: 2.8304 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7724 loss: 2.7724 2022/10/09 08:48:56 - mmengine - INFO - Epoch(train) [14][1640/2119] lr: 4.0000e-02 eta: 1 day, 4:44:01 time: 0.3581 data_time: 0.0219 memory: 11108 grad_norm: 2.7891 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.9110 loss: 2.9110 2022/10/09 08:49:03 - mmengine - INFO - Epoch(train) [14][1660/2119] lr: 4.0000e-02 eta: 1 day, 4:43:54 time: 0.3568 data_time: 0.0191 memory: 11108 grad_norm: 2.8213 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6746 loss: 2.6746 2022/10/09 08:49:11 - mmengine - INFO - Epoch(train) [14][1680/2119] lr: 4.0000e-02 eta: 1 day, 4:43:47 time: 0.3612 data_time: 0.0221 memory: 11108 grad_norm: 2.8071 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.9150 loss: 2.9150 2022/10/09 08:49:18 - mmengine - INFO - Epoch(train) [14][1700/2119] lr: 4.0000e-02 eta: 1 day, 4:43:40 time: 0.3595 data_time: 0.0191 memory: 11108 grad_norm: 2.8191 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5352 loss: 2.5352 2022/10/09 08:49:25 - mmengine - INFO - Epoch(train) [14][1720/2119] lr: 4.0000e-02 eta: 1 day, 4:43:33 time: 0.3570 data_time: 0.0196 memory: 11108 grad_norm: 2.8121 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7294 loss: 2.7294 2022/10/09 08:49:32 - mmengine - INFO - Epoch(train) [14][1740/2119] lr: 4.0000e-02 eta: 1 day, 4:43:25 time: 0.3567 data_time: 0.0212 memory: 11108 grad_norm: 2.8387 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.6520 loss: 2.6520 2022/10/09 08:49:39 - mmengine - INFO - Epoch(train) [14][1760/2119] lr: 4.0000e-02 eta: 1 day, 4:43:20 time: 0.3661 data_time: 0.0228 memory: 11108 grad_norm: 2.7947 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7358 loss: 2.7358 2022/10/09 08:49:46 - mmengine - INFO - Epoch(train) [14][1780/2119] lr: 4.0000e-02 eta: 1 day, 4:43:13 time: 0.3585 data_time: 0.0201 memory: 11108 grad_norm: 2.8175 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8536 loss: 2.8536 2022/10/09 08:49:54 - mmengine - INFO - Epoch(train) [14][1800/2119] lr: 4.0000e-02 eta: 1 day, 4:43:05 time: 0.3563 data_time: 0.0219 memory: 11108 grad_norm: 2.8007 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8214 loss: 2.8214 2022/10/09 08:50:01 - mmengine - INFO - Epoch(train) [14][1820/2119] lr: 4.0000e-02 eta: 1 day, 4:42:57 time: 0.3558 data_time: 0.0217 memory: 11108 grad_norm: 2.8476 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6369 loss: 2.6369 2022/10/09 08:50:08 - mmengine - INFO - Epoch(train) [14][1840/2119] lr: 4.0000e-02 eta: 1 day, 4:42:50 time: 0.3575 data_time: 0.0249 memory: 11108 grad_norm: 2.8374 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8431 loss: 2.8431 2022/10/09 08:50:15 - mmengine - INFO - Epoch(train) [14][1860/2119] lr: 4.0000e-02 eta: 1 day, 4:42:43 time: 0.3610 data_time: 0.0214 memory: 11108 grad_norm: 2.8393 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5799 loss: 2.5799 2022/10/09 08:50:22 - mmengine - INFO - Epoch(train) [14][1880/2119] lr: 4.0000e-02 eta: 1 day, 4:42:37 time: 0.3622 data_time: 0.0190 memory: 11108 grad_norm: 2.8194 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7007 loss: 2.7007 2022/10/09 08:50:30 - mmengine - INFO - Epoch(train) [14][1900/2119] lr: 4.0000e-02 eta: 1 day, 4:42:30 time: 0.3604 data_time: 0.0191 memory: 11108 grad_norm: 2.7804 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9242 loss: 2.9242 2022/10/09 08:50:37 - mmengine - INFO - Epoch(train) [14][1920/2119] lr: 4.0000e-02 eta: 1 day, 4:42:24 time: 0.3608 data_time: 0.0191 memory: 11108 grad_norm: 2.8688 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7376 loss: 2.7376 2022/10/09 08:50:44 - mmengine - INFO - Epoch(train) [14][1940/2119] lr: 4.0000e-02 eta: 1 day, 4:42:16 time: 0.3555 data_time: 0.0220 memory: 11108 grad_norm: 2.7787 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6928 loss: 2.6928 2022/10/09 08:50:51 - mmengine - INFO - Epoch(train) [14][1960/2119] lr: 4.0000e-02 eta: 1 day, 4:42:08 time: 0.3571 data_time: 0.0255 memory: 11108 grad_norm: 2.7853 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5463 loss: 2.5463 2022/10/09 08:50:58 - mmengine - INFO - Epoch(train) [14][1980/2119] lr: 4.0000e-02 eta: 1 day, 4:42:01 time: 0.3580 data_time: 0.0210 memory: 11108 grad_norm: 2.8262 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6708 loss: 2.6708 2022/10/09 08:51:05 - mmengine - INFO - Epoch(train) [14][2000/2119] lr: 4.0000e-02 eta: 1 day, 4:41:53 time: 0.3543 data_time: 0.0246 memory: 11108 grad_norm: 2.8722 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5093 loss: 2.5093 2022/10/09 08:51:13 - mmengine - INFO - Epoch(train) [14][2020/2119] lr: 4.0000e-02 eta: 1 day, 4:41:47 time: 0.3640 data_time: 0.0192 memory: 11108 grad_norm: 2.8466 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8677 loss: 2.8677 2022/10/09 08:51:20 - mmengine - INFO - Epoch(train) [14][2040/2119] lr: 4.0000e-02 eta: 1 day, 4:41:40 time: 0.3559 data_time: 0.0235 memory: 11108 grad_norm: 2.8342 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9638 loss: 2.9638 2022/10/09 08:51:27 - mmengine - INFO - Epoch(train) [14][2060/2119] lr: 4.0000e-02 eta: 1 day, 4:41:33 time: 0.3614 data_time: 0.0274 memory: 11108 grad_norm: 2.7631 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4664 loss: 2.4664 2022/10/09 08:51:34 - mmengine - INFO - Epoch(train) [14][2080/2119] lr: 4.0000e-02 eta: 1 day, 4:41:26 time: 0.3594 data_time: 0.0201 memory: 11108 grad_norm: 2.7786 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4222 loss: 2.4222 2022/10/09 08:51:41 - mmengine - INFO - Epoch(train) [14][2100/2119] lr: 4.0000e-02 eta: 1 day, 4:41:18 time: 0.3539 data_time: 0.0177 memory: 11108 grad_norm: 2.8683 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5202 loss: 2.5202 2022/10/09 08:51:48 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 08:51:48 - mmengine - INFO - Epoch(train) [14][2119/2119] lr: 4.0000e-02 eta: 1 day, 4:41:18 time: 0.3411 data_time: 0.0186 memory: 11108 grad_norm: 2.8670 top1_acc: 0.7000 top5_acc: 0.8000 loss_cls: 2.5147 loss: 2.5147 2022/10/09 08:51:58 - mmengine - INFO - Epoch(train) [15][20/2119] lr: 4.0000e-02 eta: 1 day, 4:40:26 time: 0.5049 data_time: 0.1372 memory: 11108 grad_norm: 2.7567 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4022 loss: 2.4022 2022/10/09 08:52:05 - mmengine - INFO - Epoch(train) [15][40/2119] lr: 4.0000e-02 eta: 1 day, 4:40:22 time: 0.3709 data_time: 0.0206 memory: 11108 grad_norm: 2.8280 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8120 loss: 2.8120 2022/10/09 08:52:12 - mmengine - INFO - Epoch(train) [15][60/2119] lr: 4.0000e-02 eta: 1 day, 4:40:15 time: 0.3611 data_time: 0.0209 memory: 11108 grad_norm: 2.8187 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7507 loss: 2.7507 2022/10/09 08:52:20 - mmengine - INFO - Epoch(train) [15][80/2119] lr: 4.0000e-02 eta: 1 day, 4:40:08 time: 0.3573 data_time: 0.0214 memory: 11108 grad_norm: 2.7781 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6744 loss: 2.6744 2022/10/09 08:52:27 - mmengine - INFO - Epoch(train) [15][100/2119] lr: 4.0000e-02 eta: 1 day, 4:40:01 time: 0.3606 data_time: 0.0185 memory: 11108 grad_norm: 2.8020 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7077 loss: 2.7077 2022/10/09 08:52:34 - mmengine - INFO - Epoch(train) [15][120/2119] lr: 4.0000e-02 eta: 1 day, 4:39:54 time: 0.3609 data_time: 0.0263 memory: 11108 grad_norm: 2.8118 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7408 loss: 2.7408 2022/10/09 08:52:41 - mmengine - INFO - Epoch(train) [15][140/2119] lr: 4.0000e-02 eta: 1 day, 4:39:47 time: 0.3587 data_time: 0.0179 memory: 11108 grad_norm: 2.8053 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7359 loss: 2.7359 2022/10/09 08:52:48 - mmengine - INFO - Epoch(train) [15][160/2119] lr: 4.0000e-02 eta: 1 day, 4:39:40 time: 0.3558 data_time: 0.0191 memory: 11108 grad_norm: 2.8244 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6751 loss: 2.6751 2022/10/09 08:52:55 - mmengine - INFO - Epoch(train) [15][180/2119] lr: 4.0000e-02 eta: 1 day, 4:39:32 time: 0.3559 data_time: 0.0176 memory: 11108 grad_norm: 2.8739 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6681 loss: 2.6681 2022/10/09 08:53:03 - mmengine - INFO - Epoch(train) [15][200/2119] lr: 4.0000e-02 eta: 1 day, 4:39:25 time: 0.3580 data_time: 0.0199 memory: 11108 grad_norm: 2.7864 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7511 loss: 2.7511 2022/10/09 08:53:10 - mmengine - INFO - Epoch(train) [15][220/2119] lr: 4.0000e-02 eta: 1 day, 4:39:17 time: 0.3563 data_time: 0.0215 memory: 11108 grad_norm: 2.8183 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7517 loss: 2.7517 2022/10/09 08:53:17 - mmengine - INFO - Epoch(train) [15][240/2119] lr: 4.0000e-02 eta: 1 day, 4:39:10 time: 0.3594 data_time: 0.0205 memory: 11108 grad_norm: 2.8228 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7847 loss: 2.7847 2022/10/09 08:53:24 - mmengine - INFO - Epoch(train) [15][260/2119] lr: 4.0000e-02 eta: 1 day, 4:39:03 time: 0.3553 data_time: 0.0185 memory: 11108 grad_norm: 2.8295 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5268 loss: 2.5268 2022/10/09 08:53:31 - mmengine - INFO - Epoch(train) [15][280/2119] lr: 4.0000e-02 eta: 1 day, 4:38:56 time: 0.3598 data_time: 0.0220 memory: 11108 grad_norm: 2.8475 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6389 loss: 2.6389 2022/10/09 08:53:38 - mmengine - INFO - Epoch(train) [15][300/2119] lr: 4.0000e-02 eta: 1 day, 4:38:48 time: 0.3578 data_time: 0.0212 memory: 11108 grad_norm: 2.7615 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7182 loss: 2.7182 2022/10/09 08:53:45 - mmengine - INFO - Epoch(train) [15][320/2119] lr: 4.0000e-02 eta: 1 day, 4:38:41 time: 0.3544 data_time: 0.0201 memory: 11108 grad_norm: 2.8183 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6974 loss: 2.6974 2022/10/09 08:53:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 08:53:53 - mmengine - INFO - Epoch(train) [15][340/2119] lr: 4.0000e-02 eta: 1 day, 4:38:34 time: 0.3597 data_time: 0.0189 memory: 11108 grad_norm: 2.8075 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7188 loss: 2.7188 2022/10/09 08:54:00 - mmengine - INFO - Epoch(train) [15][360/2119] lr: 4.0000e-02 eta: 1 day, 4:38:26 time: 0.3579 data_time: 0.0215 memory: 11108 grad_norm: 2.8480 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5787 loss: 2.5787 2022/10/09 08:54:07 - mmengine - INFO - Epoch(train) [15][380/2119] lr: 4.0000e-02 eta: 1 day, 4:38:19 time: 0.3562 data_time: 0.0210 memory: 11108 grad_norm: 2.7994 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7691 loss: 2.7691 2022/10/09 08:54:14 - mmengine - INFO - Epoch(train) [15][400/2119] lr: 4.0000e-02 eta: 1 day, 4:38:12 time: 0.3593 data_time: 0.0230 memory: 11108 grad_norm: 2.8026 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7094 loss: 2.7094 2022/10/09 08:54:21 - mmengine - INFO - Epoch(train) [15][420/2119] lr: 4.0000e-02 eta: 1 day, 4:38:05 time: 0.3613 data_time: 0.0272 memory: 11108 grad_norm: 2.8066 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.4914 loss: 2.4914 2022/10/09 08:54:28 - mmengine - INFO - Epoch(train) [15][440/2119] lr: 4.0000e-02 eta: 1 day, 4:37:58 time: 0.3555 data_time: 0.0226 memory: 11108 grad_norm: 2.7595 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.7258 loss: 2.7258 2022/10/09 08:54:36 - mmengine - INFO - Epoch(train) [15][460/2119] lr: 4.0000e-02 eta: 1 day, 4:37:52 time: 0.3642 data_time: 0.0211 memory: 11108 grad_norm: 2.7911 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7119 loss: 2.7119 2022/10/09 08:54:43 - mmengine - INFO - Epoch(train) [15][480/2119] lr: 4.0000e-02 eta: 1 day, 4:37:44 time: 0.3567 data_time: 0.0226 memory: 11108 grad_norm: 2.8283 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7507 loss: 2.7507 2022/10/09 08:54:50 - mmengine - INFO - Epoch(train) [15][500/2119] lr: 4.0000e-02 eta: 1 day, 4:37:37 time: 0.3573 data_time: 0.0222 memory: 11108 grad_norm: 2.7791 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6207 loss: 2.6207 2022/10/09 08:54:57 - mmengine - INFO - Epoch(train) [15][520/2119] lr: 4.0000e-02 eta: 1 day, 4:37:31 time: 0.3635 data_time: 0.0218 memory: 11108 grad_norm: 2.8238 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7542 loss: 2.7542 2022/10/09 08:55:05 - mmengine - INFO - Epoch(train) [15][540/2119] lr: 4.0000e-02 eta: 1 day, 4:37:24 time: 0.3609 data_time: 0.0234 memory: 11108 grad_norm: 2.8448 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7998 loss: 2.7998 2022/10/09 08:55:12 - mmengine - INFO - Epoch(train) [15][560/2119] lr: 4.0000e-02 eta: 1 day, 4:37:17 time: 0.3589 data_time: 0.0206 memory: 11108 grad_norm: 2.8250 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7098 loss: 2.7098 2022/10/09 08:55:19 - mmengine - INFO - Epoch(train) [15][580/2119] lr: 4.0000e-02 eta: 1 day, 4:37:10 time: 0.3576 data_time: 0.0171 memory: 11108 grad_norm: 2.8017 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7677 loss: 2.7677 2022/10/09 08:55:26 - mmengine - INFO - Epoch(train) [15][600/2119] lr: 4.0000e-02 eta: 1 day, 4:37:02 time: 0.3562 data_time: 0.0253 memory: 11108 grad_norm: 2.8005 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5796 loss: 2.5796 2022/10/09 08:55:33 - mmengine - INFO - Epoch(train) [15][620/2119] lr: 4.0000e-02 eta: 1 day, 4:36:55 time: 0.3575 data_time: 0.0180 memory: 11108 grad_norm: 2.7662 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4359 loss: 2.4359 2022/10/09 08:55:40 - mmengine - INFO - Epoch(train) [15][640/2119] lr: 4.0000e-02 eta: 1 day, 4:36:47 time: 0.3545 data_time: 0.0222 memory: 11108 grad_norm: 2.8394 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.5184 loss: 2.5184 2022/10/09 08:55:47 - mmengine - INFO - Epoch(train) [15][660/2119] lr: 4.0000e-02 eta: 1 day, 4:36:39 time: 0.3565 data_time: 0.0198 memory: 11108 grad_norm: 2.8671 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9584 loss: 2.9584 2022/10/09 08:55:54 - mmengine - INFO - Epoch(train) [15][680/2119] lr: 4.0000e-02 eta: 1 day, 4:36:32 time: 0.3567 data_time: 0.0197 memory: 11108 grad_norm: 2.7922 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7281 loss: 2.7281 2022/10/09 08:56:02 - mmengine - INFO - Epoch(train) [15][700/2119] lr: 4.0000e-02 eta: 1 day, 4:36:24 time: 0.3556 data_time: 0.0207 memory: 11108 grad_norm: 2.8014 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7574 loss: 2.7574 2022/10/09 08:56:09 - mmengine - INFO - Epoch(train) [15][720/2119] lr: 4.0000e-02 eta: 1 day, 4:36:18 time: 0.3638 data_time: 0.0212 memory: 11108 grad_norm: 2.8390 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9579 loss: 2.9579 2022/10/09 08:56:16 - mmengine - INFO - Epoch(train) [15][740/2119] lr: 4.0000e-02 eta: 1 day, 4:36:11 time: 0.3556 data_time: 0.0246 memory: 11108 grad_norm: 2.8039 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6159 loss: 2.6159 2022/10/09 08:56:23 - mmengine - INFO - Epoch(train) [15][760/2119] lr: 4.0000e-02 eta: 1 day, 4:36:04 time: 0.3594 data_time: 0.0227 memory: 11108 grad_norm: 2.8457 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8391 loss: 2.8391 2022/10/09 08:56:30 - mmengine - INFO - Epoch(train) [15][780/2119] lr: 4.0000e-02 eta: 1 day, 4:35:56 time: 0.3573 data_time: 0.0170 memory: 11108 grad_norm: 2.8408 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2835 loss: 2.2835 2022/10/09 08:56:37 - mmengine - INFO - Epoch(train) [15][800/2119] lr: 4.0000e-02 eta: 1 day, 4:35:49 time: 0.3569 data_time: 0.0204 memory: 11108 grad_norm: 2.8637 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6111 loss: 2.6111 2022/10/09 08:56:45 - mmengine - INFO - Epoch(train) [15][820/2119] lr: 4.0000e-02 eta: 1 day, 4:35:42 time: 0.3617 data_time: 0.0163 memory: 11108 grad_norm: 2.8247 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7845 loss: 2.7845 2022/10/09 08:56:52 - mmengine - INFO - Epoch(train) [15][840/2119] lr: 4.0000e-02 eta: 1 day, 4:35:35 time: 0.3574 data_time: 0.0233 memory: 11108 grad_norm: 2.8041 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6877 loss: 2.6877 2022/10/09 08:56:59 - mmengine - INFO - Epoch(train) [15][860/2119] lr: 4.0000e-02 eta: 1 day, 4:35:28 time: 0.3561 data_time: 0.0227 memory: 11108 grad_norm: 2.8295 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6957 loss: 2.6957 2022/10/09 08:57:06 - mmengine - INFO - Epoch(train) [15][880/2119] lr: 4.0000e-02 eta: 1 day, 4:35:21 time: 0.3623 data_time: 0.0195 memory: 11108 grad_norm: 2.7977 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.3458 loss: 2.3458 2022/10/09 08:57:13 - mmengine - INFO - Epoch(train) [15][900/2119] lr: 4.0000e-02 eta: 1 day, 4:35:14 time: 0.3584 data_time: 0.0196 memory: 11108 grad_norm: 2.8334 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6224 loss: 2.6224 2022/10/09 08:57:21 - mmengine - INFO - Epoch(train) [15][920/2119] lr: 4.0000e-02 eta: 1 day, 4:35:07 time: 0.3597 data_time: 0.0210 memory: 11108 grad_norm: 2.8545 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8001 loss: 2.8001 2022/10/09 08:57:28 - mmengine - INFO - Epoch(train) [15][940/2119] lr: 4.0000e-02 eta: 1 day, 4:34:59 time: 0.3549 data_time: 0.0213 memory: 11108 grad_norm: 2.8725 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8327 loss: 2.8327 2022/10/09 08:57:35 - mmengine - INFO - Epoch(train) [15][960/2119] lr: 4.0000e-02 eta: 1 day, 4:34:52 time: 0.3601 data_time: 0.0214 memory: 11108 grad_norm: 2.8124 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8063 loss: 2.8063 2022/10/09 08:57:42 - mmengine - INFO - Epoch(train) [15][980/2119] lr: 4.0000e-02 eta: 1 day, 4:34:45 time: 0.3580 data_time: 0.0201 memory: 11108 grad_norm: 2.7932 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.8209 loss: 2.8209 2022/10/09 08:57:49 - mmengine - INFO - Epoch(train) [15][1000/2119] lr: 4.0000e-02 eta: 1 day, 4:34:39 time: 0.3618 data_time: 0.0252 memory: 11108 grad_norm: 2.8362 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5452 loss: 2.5452 2022/10/09 08:57:56 - mmengine - INFO - Epoch(train) [15][1020/2119] lr: 4.0000e-02 eta: 1 day, 4:34:31 time: 0.3549 data_time: 0.0196 memory: 11108 grad_norm: 2.7987 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4382 loss: 2.4382 2022/10/09 08:58:04 - mmengine - INFO - Epoch(train) [15][1040/2119] lr: 4.0000e-02 eta: 1 day, 4:34:24 time: 0.3587 data_time: 0.0198 memory: 11108 grad_norm: 2.8564 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7208 loss: 2.7208 2022/10/09 08:58:11 - mmengine - INFO - Epoch(train) [15][1060/2119] lr: 4.0000e-02 eta: 1 day, 4:34:17 time: 0.3572 data_time: 0.0176 memory: 11108 grad_norm: 2.8371 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4199 loss: 2.4199 2022/10/09 08:58:18 - mmengine - INFO - Epoch(train) [15][1080/2119] lr: 4.0000e-02 eta: 1 day, 4:34:09 time: 0.3552 data_time: 0.0235 memory: 11108 grad_norm: 2.8413 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9522 loss: 2.9522 2022/10/09 08:58:25 - mmengine - INFO - Epoch(train) [15][1100/2119] lr: 4.0000e-02 eta: 1 day, 4:34:03 time: 0.3629 data_time: 0.0214 memory: 11108 grad_norm: 2.8456 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4820 loss: 2.4820 2022/10/09 08:58:32 - mmengine - INFO - Epoch(train) [15][1120/2119] lr: 4.0000e-02 eta: 1 day, 4:33:57 time: 0.3645 data_time: 0.0226 memory: 11108 grad_norm: 2.8488 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7976 loss: 2.7976 2022/10/09 08:58:39 - mmengine - INFO - Epoch(train) [15][1140/2119] lr: 4.0000e-02 eta: 1 day, 4:33:49 time: 0.3556 data_time: 0.0199 memory: 11108 grad_norm: 2.8603 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7661 loss: 2.7661 2022/10/09 08:58:47 - mmengine - INFO - Epoch(train) [15][1160/2119] lr: 4.0000e-02 eta: 1 day, 4:33:41 time: 0.3562 data_time: 0.0231 memory: 11108 grad_norm: 2.8081 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6428 loss: 2.6428 2022/10/09 08:58:54 - mmengine - INFO - Epoch(train) [15][1180/2119] lr: 4.0000e-02 eta: 1 day, 4:33:35 time: 0.3615 data_time: 0.0209 memory: 11108 grad_norm: 2.8674 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0020 loss: 3.0020 2022/10/09 08:59:01 - mmengine - INFO - Epoch(train) [15][1200/2119] lr: 4.0000e-02 eta: 1 day, 4:33:27 time: 0.3569 data_time: 0.0219 memory: 11108 grad_norm: 2.8148 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.4918 loss: 2.4918 2022/10/09 08:59:08 - mmengine - INFO - Epoch(train) [15][1220/2119] lr: 4.0000e-02 eta: 1 day, 4:33:20 time: 0.3555 data_time: 0.0171 memory: 11108 grad_norm: 2.8337 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7110 loss: 2.7110 2022/10/09 08:59:15 - mmengine - INFO - Epoch(train) [15][1240/2119] lr: 4.0000e-02 eta: 1 day, 4:33:13 time: 0.3578 data_time: 0.0216 memory: 11108 grad_norm: 2.8386 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5798 loss: 2.5798 2022/10/09 08:59:23 - mmengine - INFO - Epoch(train) [15][1260/2119] lr: 4.0000e-02 eta: 1 day, 4:33:08 time: 0.3701 data_time: 0.0228 memory: 11108 grad_norm: 2.7543 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7573 loss: 2.7573 2022/10/09 08:59:30 - mmengine - INFO - Epoch(train) [15][1280/2119] lr: 4.0000e-02 eta: 1 day, 4:33:00 time: 0.3578 data_time: 0.0216 memory: 11108 grad_norm: 2.8168 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7551 loss: 2.7551 2022/10/09 08:59:37 - mmengine - INFO - Epoch(train) [15][1300/2119] lr: 4.0000e-02 eta: 1 day, 4:32:52 time: 0.3529 data_time: 0.0194 memory: 11108 grad_norm: 2.8565 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7980 loss: 2.7980 2022/10/09 08:59:44 - mmengine - INFO - Epoch(train) [15][1320/2119] lr: 4.0000e-02 eta: 1 day, 4:32:45 time: 0.3584 data_time: 0.0193 memory: 11108 grad_norm: 2.8202 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8135 loss: 2.8135 2022/10/09 08:59:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 08:59:51 - mmengine - INFO - Epoch(train) [15][1340/2119] lr: 4.0000e-02 eta: 1 day, 4:32:38 time: 0.3595 data_time: 0.0182 memory: 11108 grad_norm: 2.8267 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7796 loss: 2.7796 2022/10/09 08:59:58 - mmengine - INFO - Epoch(train) [15][1360/2119] lr: 4.0000e-02 eta: 1 day, 4:32:31 time: 0.3595 data_time: 0.0240 memory: 11108 grad_norm: 2.8235 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6304 loss: 2.6304 2022/10/09 09:00:06 - mmengine - INFO - Epoch(train) [15][1380/2119] lr: 4.0000e-02 eta: 1 day, 4:32:27 time: 0.3727 data_time: 0.0177 memory: 11108 grad_norm: 2.8121 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.4704 loss: 2.4704 2022/10/09 09:00:13 - mmengine - INFO - Epoch(train) [15][1400/2119] lr: 4.0000e-02 eta: 1 day, 4:32:19 time: 0.3577 data_time: 0.0219 memory: 11108 grad_norm: 2.8174 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9031 loss: 2.9031 2022/10/09 09:00:20 - mmengine - INFO - Epoch(train) [15][1420/2119] lr: 4.0000e-02 eta: 1 day, 4:32:13 time: 0.3613 data_time: 0.0203 memory: 11108 grad_norm: 2.8214 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8644 loss: 2.8644 2022/10/09 09:00:27 - mmengine - INFO - Epoch(train) [15][1440/2119] lr: 4.0000e-02 eta: 1 day, 4:32:05 time: 0.3557 data_time: 0.0209 memory: 11108 grad_norm: 2.8031 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6031 loss: 2.6031 2022/10/09 09:00:34 - mmengine - INFO - Epoch(train) [15][1460/2119] lr: 4.0000e-02 eta: 1 day, 4:31:58 time: 0.3570 data_time: 0.0190 memory: 11108 grad_norm: 2.7763 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.5489 loss: 2.5489 2022/10/09 09:00:42 - mmengine - INFO - Epoch(train) [15][1480/2119] lr: 4.0000e-02 eta: 1 day, 4:31:53 time: 0.3696 data_time: 0.0272 memory: 11108 grad_norm: 2.8034 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7077 loss: 2.7077 2022/10/09 09:00:49 - mmengine - INFO - Epoch(train) [15][1500/2119] lr: 4.0000e-02 eta: 1 day, 4:31:46 time: 0.3586 data_time: 0.0178 memory: 11108 grad_norm: 2.8254 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.4772 loss: 2.4772 2022/10/09 09:00:56 - mmengine - INFO - Epoch(train) [15][1520/2119] lr: 4.0000e-02 eta: 1 day, 4:31:39 time: 0.3590 data_time: 0.0199 memory: 11108 grad_norm: 2.8108 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5457 loss: 2.5457 2022/10/09 09:01:03 - mmengine - INFO - Epoch(train) [15][1540/2119] lr: 4.0000e-02 eta: 1 day, 4:31:31 time: 0.3566 data_time: 0.0205 memory: 11108 grad_norm: 2.8335 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6924 loss: 2.6924 2022/10/09 09:01:11 - mmengine - INFO - Epoch(train) [15][1560/2119] lr: 4.0000e-02 eta: 1 day, 4:31:25 time: 0.3630 data_time: 0.0220 memory: 11108 grad_norm: 2.7836 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4907 loss: 2.4907 2022/10/09 09:01:18 - mmengine - INFO - Epoch(train) [15][1580/2119] lr: 4.0000e-02 eta: 1 day, 4:31:17 time: 0.3527 data_time: 0.0189 memory: 11108 grad_norm: 2.7710 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6830 loss: 2.6830 2022/10/09 09:01:25 - mmengine - INFO - Epoch(train) [15][1600/2119] lr: 4.0000e-02 eta: 1 day, 4:31:10 time: 0.3631 data_time: 0.0204 memory: 11108 grad_norm: 2.8421 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7588 loss: 2.7588 2022/10/09 09:01:32 - mmengine - INFO - Epoch(train) [15][1620/2119] lr: 4.0000e-02 eta: 1 day, 4:31:04 time: 0.3637 data_time: 0.0185 memory: 11108 grad_norm: 2.8422 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7070 loss: 2.7070 2022/10/09 09:01:39 - mmengine - INFO - Epoch(train) [15][1640/2119] lr: 4.0000e-02 eta: 1 day, 4:30:57 time: 0.3600 data_time: 0.0248 memory: 11108 grad_norm: 2.7892 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.4795 loss: 2.4795 2022/10/09 09:01:47 - mmengine - INFO - Epoch(train) [15][1660/2119] lr: 4.0000e-02 eta: 1 day, 4:30:50 time: 0.3560 data_time: 0.0209 memory: 11108 grad_norm: 2.7805 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8379 loss: 2.8379 2022/10/09 09:01:54 - mmengine - INFO - Epoch(train) [15][1680/2119] lr: 4.0000e-02 eta: 1 day, 4:30:43 time: 0.3610 data_time: 0.0208 memory: 11108 grad_norm: 2.8192 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5892 loss: 2.5892 2022/10/09 09:02:01 - mmengine - INFO - Epoch(train) [15][1700/2119] lr: 4.0000e-02 eta: 1 day, 4:30:36 time: 0.3605 data_time: 0.0276 memory: 11108 grad_norm: 2.8199 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6953 loss: 2.6953 2022/10/09 09:02:08 - mmengine - INFO - Epoch(train) [15][1720/2119] lr: 4.0000e-02 eta: 1 day, 4:30:29 time: 0.3576 data_time: 0.0200 memory: 11108 grad_norm: 2.8381 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4311 loss: 2.4311 2022/10/09 09:02:15 - mmengine - INFO - Epoch(train) [15][1740/2119] lr: 4.0000e-02 eta: 1 day, 4:30:22 time: 0.3614 data_time: 0.0205 memory: 11108 grad_norm: 2.8286 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.6567 loss: 2.6567 2022/10/09 09:02:22 - mmengine - INFO - Epoch(train) [15][1760/2119] lr: 4.0000e-02 eta: 1 day, 4:30:15 time: 0.3560 data_time: 0.0185 memory: 11108 grad_norm: 2.7861 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7956 loss: 2.7956 2022/10/09 09:02:30 - mmengine - INFO - Epoch(train) [15][1780/2119] lr: 4.0000e-02 eta: 1 day, 4:30:08 time: 0.3595 data_time: 0.0182 memory: 11108 grad_norm: 2.8227 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7708 loss: 2.7708 2022/10/09 09:02:37 - mmengine - INFO - Epoch(train) [15][1800/2119] lr: 4.0000e-02 eta: 1 day, 4:30:00 time: 0.3557 data_time: 0.0176 memory: 11108 grad_norm: 2.8082 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5992 loss: 2.5992 2022/10/09 09:02:44 - mmengine - INFO - Epoch(train) [15][1820/2119] lr: 4.0000e-02 eta: 1 day, 4:29:54 time: 0.3651 data_time: 0.0243 memory: 11108 grad_norm: 2.7940 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7433 loss: 2.7433 2022/10/09 09:02:52 - mmengine - INFO - Epoch(train) [15][1840/2119] lr: 4.0000e-02 eta: 1 day, 4:29:49 time: 0.3706 data_time: 0.0208 memory: 11108 grad_norm: 2.8357 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6714 loss: 2.6714 2022/10/09 09:02:59 - mmengine - INFO - Epoch(train) [15][1860/2119] lr: 4.0000e-02 eta: 1 day, 4:29:42 time: 0.3561 data_time: 0.0159 memory: 11108 grad_norm: 2.8623 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7098 loss: 2.7098 2022/10/09 09:03:06 - mmengine - INFO - Epoch(train) [15][1880/2119] lr: 4.0000e-02 eta: 1 day, 4:29:35 time: 0.3593 data_time: 0.0211 memory: 11108 grad_norm: 2.8470 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6803 loss: 2.6803 2022/10/09 09:03:13 - mmengine - INFO - Epoch(train) [15][1900/2119] lr: 4.0000e-02 eta: 1 day, 4:29:28 time: 0.3604 data_time: 0.0172 memory: 11108 grad_norm: 2.7866 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5110 loss: 2.5110 2022/10/09 09:03:20 - mmengine - INFO - Epoch(train) [15][1920/2119] lr: 4.0000e-02 eta: 1 day, 4:29:20 time: 0.3549 data_time: 0.0207 memory: 11108 grad_norm: 2.8262 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9416 loss: 2.9416 2022/10/09 09:03:27 - mmengine - INFO - Epoch(train) [15][1940/2119] lr: 4.0000e-02 eta: 1 day, 4:29:13 time: 0.3568 data_time: 0.0217 memory: 11108 grad_norm: 2.7890 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7652 loss: 2.7652 2022/10/09 09:03:34 - mmengine - INFO - Epoch(train) [15][1960/2119] lr: 4.0000e-02 eta: 1 day, 4:29:06 time: 0.3586 data_time: 0.0191 memory: 11108 grad_norm: 2.8491 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6907 loss: 2.6907 2022/10/09 09:03:42 - mmengine - INFO - Epoch(train) [15][1980/2119] lr: 4.0000e-02 eta: 1 day, 4:28:59 time: 0.3590 data_time: 0.0190 memory: 11108 grad_norm: 2.8462 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7955 loss: 2.7955 2022/10/09 09:03:49 - mmengine - INFO - Epoch(train) [15][2000/2119] lr: 4.0000e-02 eta: 1 day, 4:28:52 time: 0.3588 data_time: 0.0195 memory: 11108 grad_norm: 2.8051 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8076 loss: 2.8076 2022/10/09 09:03:56 - mmengine - INFO - Epoch(train) [15][2020/2119] lr: 4.0000e-02 eta: 1 day, 4:28:44 time: 0.3569 data_time: 0.0189 memory: 11108 grad_norm: 2.7571 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6864 loss: 2.6864 2022/10/09 09:04:03 - mmengine - INFO - Epoch(train) [15][2040/2119] lr: 4.0000e-02 eta: 1 day, 4:28:37 time: 0.3566 data_time: 0.0187 memory: 11108 grad_norm: 2.7893 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6080 loss: 2.6080 2022/10/09 09:04:10 - mmengine - INFO - Epoch(train) [15][2060/2119] lr: 4.0000e-02 eta: 1 day, 4:28:29 time: 0.3564 data_time: 0.0202 memory: 11108 grad_norm: 2.8113 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6976 loss: 2.6976 2022/10/09 09:04:17 - mmengine - INFO - Epoch(train) [15][2080/2119] lr: 4.0000e-02 eta: 1 day, 4:28:22 time: 0.3556 data_time: 0.0199 memory: 11108 grad_norm: 2.8124 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.3501 loss: 2.3501 2022/10/09 09:04:25 - mmengine - INFO - Epoch(train) [15][2100/2119] lr: 4.0000e-02 eta: 1 day, 4:28:16 time: 0.3648 data_time: 0.0209 memory: 11108 grad_norm: 2.7866 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5665 loss: 2.5665 2022/10/09 09:04:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 09:04:31 - mmengine - INFO - Epoch(train) [15][2119/2119] lr: 4.0000e-02 eta: 1 day, 4:28:16 time: 0.3536 data_time: 0.0184 memory: 11108 grad_norm: 2.8212 top1_acc: 0.2000 top5_acc: 0.3000 loss_cls: 2.6133 loss: 2.6133 2022/10/09 09:04:38 - mmengine - INFO - Epoch(val) [15][20/137] eta: 0:00:40 time: 0.3434 data_time: 0.2267 memory: 1961 2022/10/09 09:04:44 - mmengine - INFO - Epoch(val) [15][40/137] eta: 0:00:27 time: 0.2787 data_time: 0.1619 memory: 1961 2022/10/09 09:04:50 - mmengine - INFO - Epoch(val) [15][60/137] eta: 0:00:22 time: 0.2867 data_time: 0.1723 memory: 1961 2022/10/09 09:04:54 - mmengine - INFO - Epoch(val) [15][80/137] eta: 0:00:13 time: 0.2345 data_time: 0.1202 memory: 1961 2022/10/09 09:05:00 - mmengine - INFO - Epoch(val) [15][100/137] eta: 0:00:10 time: 0.2917 data_time: 0.1753 memory: 1961 2022/10/09 09:05:05 - mmengine - INFO - Epoch(val) [15][120/137] eta: 0:00:03 time: 0.2239 data_time: 0.1091 memory: 1961 2022/10/09 09:05:20 - mmengine - INFO - Epoch(val) [15][137/137] acc/top1: 0.4427 acc/top5: 0.6852 acc/mean1: 0.4426 2022/10/09 09:05:20 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb.py/best_acc/top1_epoch_10.pth is removed 2022/10/09 09:05:22 - mmengine - INFO - The best checkpoint with 0.4427 acc/top1 at 15 epoch is saved to best_acc/top1_epoch_15.pth. 2022/10/09 09:05:31 - mmengine - INFO - Epoch(train) [16][20/2119] lr: 4.0000e-02 eta: 1 day, 4:27:19 time: 0.4638 data_time: 0.1222 memory: 11108 grad_norm: 2.8133 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6032 loss: 2.6032 2022/10/09 09:05:38 - mmengine - INFO - Epoch(train) [16][40/2119] lr: 4.0000e-02 eta: 1 day, 4:27:13 time: 0.3600 data_time: 0.0196 memory: 11108 grad_norm: 2.8499 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7398 loss: 2.7398 2022/10/09 09:05:45 - mmengine - INFO - Epoch(train) [16][60/2119] lr: 4.0000e-02 eta: 1 day, 4:27:05 time: 0.3566 data_time: 0.0206 memory: 11108 grad_norm: 2.8208 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4989 loss: 2.4989 2022/10/09 09:05:53 - mmengine - INFO - Epoch(train) [16][80/2119] lr: 4.0000e-02 eta: 1 day, 4:26:58 time: 0.3567 data_time: 0.0258 memory: 11108 grad_norm: 2.8273 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8144 loss: 2.8144 2022/10/09 09:06:00 - mmengine - INFO - Epoch(train) [16][100/2119] lr: 4.0000e-02 eta: 1 day, 4:26:50 time: 0.3563 data_time: 0.0206 memory: 11108 grad_norm: 2.7887 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7147 loss: 2.7147 2022/10/09 09:06:07 - mmengine - INFO - Epoch(train) [16][120/2119] lr: 4.0000e-02 eta: 1 day, 4:26:43 time: 0.3572 data_time: 0.0194 memory: 11108 grad_norm: 2.8045 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4673 loss: 2.4673 2022/10/09 09:06:14 - mmengine - INFO - Epoch(train) [16][140/2119] lr: 4.0000e-02 eta: 1 day, 4:26:35 time: 0.3553 data_time: 0.0171 memory: 11108 grad_norm: 2.8280 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6207 loss: 2.6207 2022/10/09 09:06:21 - mmengine - INFO - Epoch(train) [16][160/2119] lr: 4.0000e-02 eta: 1 day, 4:26:28 time: 0.3588 data_time: 0.0201 memory: 11108 grad_norm: 2.8200 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6675 loss: 2.6675 2022/10/09 09:06:28 - mmengine - INFO - Epoch(train) [16][180/2119] lr: 4.0000e-02 eta: 1 day, 4:26:20 time: 0.3545 data_time: 0.0220 memory: 11108 grad_norm: 2.7659 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5539 loss: 2.5539 2022/10/09 09:06:35 - mmengine - INFO - Epoch(train) [16][200/2119] lr: 4.0000e-02 eta: 1 day, 4:26:13 time: 0.3563 data_time: 0.0194 memory: 11108 grad_norm: 2.7949 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8239 loss: 2.8239 2022/10/09 09:06:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 09:06:42 - mmengine - INFO - Epoch(train) [16][220/2119] lr: 4.0000e-02 eta: 1 day, 4:26:06 time: 0.3590 data_time: 0.0192 memory: 11108 grad_norm: 2.8070 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6601 loss: 2.6601 2022/10/09 09:06:50 - mmengine - INFO - Epoch(train) [16][240/2119] lr: 4.0000e-02 eta: 1 day, 4:25:58 time: 0.3559 data_time: 0.0195 memory: 11108 grad_norm: 2.8106 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5848 loss: 2.5848 2022/10/09 09:06:57 - mmengine - INFO - Epoch(train) [16][260/2119] lr: 4.0000e-02 eta: 1 day, 4:25:50 time: 0.3539 data_time: 0.0198 memory: 11108 grad_norm: 2.8221 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4200 loss: 2.4200 2022/10/09 09:07:04 - mmengine - INFO - Epoch(train) [16][280/2119] lr: 4.0000e-02 eta: 1 day, 4:25:43 time: 0.3566 data_time: 0.0210 memory: 11108 grad_norm: 2.8125 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7025 loss: 2.7025 2022/10/09 09:07:11 - mmengine - INFO - Epoch(train) [16][300/2119] lr: 4.0000e-02 eta: 1 day, 4:25:35 time: 0.3545 data_time: 0.0193 memory: 11108 grad_norm: 2.8317 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7608 loss: 2.7608 2022/10/09 09:07:18 - mmengine - INFO - Epoch(train) [16][320/2119] lr: 4.0000e-02 eta: 1 day, 4:25:28 time: 0.3574 data_time: 0.0197 memory: 11108 grad_norm: 2.8387 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5358 loss: 2.5358 2022/10/09 09:07:25 - mmengine - INFO - Epoch(train) [16][340/2119] lr: 4.0000e-02 eta: 1 day, 4:25:22 time: 0.3632 data_time: 0.0182 memory: 11108 grad_norm: 2.8760 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8108 loss: 2.8108 2022/10/09 09:07:33 - mmengine - INFO - Epoch(train) [16][360/2119] lr: 4.0000e-02 eta: 1 day, 4:25:15 time: 0.3590 data_time: 0.0174 memory: 11108 grad_norm: 2.7913 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6522 loss: 2.6522 2022/10/09 09:07:40 - mmengine - INFO - Epoch(train) [16][380/2119] lr: 4.0000e-02 eta: 1 day, 4:25:08 time: 0.3599 data_time: 0.0249 memory: 11108 grad_norm: 2.7401 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7139 loss: 2.7139 2022/10/09 09:07:47 - mmengine - INFO - Epoch(train) [16][400/2119] lr: 4.0000e-02 eta: 1 day, 4:25:00 time: 0.3571 data_time: 0.0205 memory: 11108 grad_norm: 2.8429 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5325 loss: 2.5325 2022/10/09 09:07:54 - mmengine - INFO - Epoch(train) [16][420/2119] lr: 4.0000e-02 eta: 1 day, 4:24:53 time: 0.3560 data_time: 0.0203 memory: 11108 grad_norm: 2.8005 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7163 loss: 2.7163 2022/10/09 09:08:01 - mmengine - INFO - Epoch(train) [16][440/2119] lr: 4.0000e-02 eta: 1 day, 4:24:46 time: 0.3573 data_time: 0.0214 memory: 11108 grad_norm: 2.7571 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6063 loss: 2.6063 2022/10/09 09:08:08 - mmengine - INFO - Epoch(train) [16][460/2119] lr: 4.0000e-02 eta: 1 day, 4:24:39 time: 0.3583 data_time: 0.0198 memory: 11108 grad_norm: 2.8203 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7727 loss: 2.7727 2022/10/09 09:08:15 - mmengine - INFO - Epoch(train) [16][480/2119] lr: 4.0000e-02 eta: 1 day, 4:24:31 time: 0.3569 data_time: 0.0216 memory: 11108 grad_norm: 2.8246 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6485 loss: 2.6485 2022/10/09 09:08:23 - mmengine - INFO - Epoch(train) [16][500/2119] lr: 4.0000e-02 eta: 1 day, 4:24:24 time: 0.3566 data_time: 0.0170 memory: 11108 grad_norm: 2.7885 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6522 loss: 2.6522 2022/10/09 09:08:30 - mmengine - INFO - Epoch(train) [16][520/2119] lr: 4.0000e-02 eta: 1 day, 4:24:16 time: 0.3571 data_time: 0.0220 memory: 11108 grad_norm: 2.7795 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7621 loss: 2.7621 2022/10/09 09:08:37 - mmengine - INFO - Epoch(train) [16][540/2119] lr: 4.0000e-02 eta: 1 day, 4:24:09 time: 0.3574 data_time: 0.0225 memory: 11108 grad_norm: 2.8001 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6163 loss: 2.6163 2022/10/09 09:08:44 - mmengine - INFO - Epoch(train) [16][560/2119] lr: 4.0000e-02 eta: 1 day, 4:24:02 time: 0.3590 data_time: 0.0188 memory: 11108 grad_norm: 2.8815 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7779 loss: 2.7779 2022/10/09 09:08:51 - mmengine - INFO - Epoch(train) [16][580/2119] lr: 4.0000e-02 eta: 1 day, 4:23:55 time: 0.3612 data_time: 0.0203 memory: 11108 grad_norm: 2.8380 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6100 loss: 2.6100 2022/10/09 09:08:58 - mmengine - INFO - Epoch(train) [16][600/2119] lr: 4.0000e-02 eta: 1 day, 4:23:48 time: 0.3551 data_time: 0.0220 memory: 11108 grad_norm: 2.8376 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7293 loss: 2.7293 2022/10/09 09:09:05 - mmengine - INFO - Epoch(train) [16][620/2119] lr: 4.0000e-02 eta: 1 day, 4:23:41 time: 0.3579 data_time: 0.0153 memory: 11108 grad_norm: 2.8412 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6661 loss: 2.6661 2022/10/09 09:09:13 - mmengine - INFO - Epoch(train) [16][640/2119] lr: 4.0000e-02 eta: 1 day, 4:23:33 time: 0.3576 data_time: 0.0236 memory: 11108 grad_norm: 2.8184 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0974 loss: 2.0974 2022/10/09 09:09:20 - mmengine - INFO - Epoch(train) [16][660/2119] lr: 4.0000e-02 eta: 1 day, 4:23:26 time: 0.3556 data_time: 0.0208 memory: 11108 grad_norm: 2.7864 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7444 loss: 2.7444 2022/10/09 09:09:27 - mmengine - INFO - Epoch(train) [16][680/2119] lr: 4.0000e-02 eta: 1 day, 4:23:19 time: 0.3615 data_time: 0.0190 memory: 11108 grad_norm: 2.8151 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6988 loss: 2.6988 2022/10/09 09:09:34 - mmengine - INFO - Epoch(train) [16][700/2119] lr: 4.0000e-02 eta: 1 day, 4:23:15 time: 0.3738 data_time: 0.0202 memory: 11108 grad_norm: 2.8249 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6489 loss: 2.6489 2022/10/09 09:09:42 - mmengine - INFO - Epoch(train) [16][720/2119] lr: 4.0000e-02 eta: 1 day, 4:23:07 time: 0.3559 data_time: 0.0258 memory: 11108 grad_norm: 2.8043 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5014 loss: 2.5014 2022/10/09 09:09:49 - mmengine - INFO - Epoch(train) [16][740/2119] lr: 4.0000e-02 eta: 1 day, 4:23:00 time: 0.3568 data_time: 0.0211 memory: 11108 grad_norm: 2.8519 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8007 loss: 2.8007 2022/10/09 09:09:56 - mmengine - INFO - Epoch(train) [16][760/2119] lr: 4.0000e-02 eta: 1 day, 4:22:53 time: 0.3624 data_time: 0.0211 memory: 11108 grad_norm: 2.8741 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7632 loss: 2.7632 2022/10/09 09:10:03 - mmengine - INFO - Epoch(train) [16][780/2119] lr: 4.0000e-02 eta: 1 day, 4:22:46 time: 0.3594 data_time: 0.0205 memory: 11108 grad_norm: 2.7846 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6308 loss: 2.6308 2022/10/09 09:10:10 - mmengine - INFO - Epoch(train) [16][800/2119] lr: 4.0000e-02 eta: 1 day, 4:22:40 time: 0.3612 data_time: 0.0223 memory: 11108 grad_norm: 2.7880 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6107 loss: 2.6107 2022/10/09 09:10:17 - mmengine - INFO - Epoch(train) [16][820/2119] lr: 4.0000e-02 eta: 1 day, 4:22:32 time: 0.3552 data_time: 0.0168 memory: 11108 grad_norm: 2.8042 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5456 loss: 2.5456 2022/10/09 09:10:25 - mmengine - INFO - Epoch(train) [16][840/2119] lr: 4.0000e-02 eta: 1 day, 4:22:25 time: 0.3572 data_time: 0.0200 memory: 11108 grad_norm: 2.7505 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5878 loss: 2.5878 2022/10/09 09:10:32 - mmengine - INFO - Epoch(train) [16][860/2119] lr: 4.0000e-02 eta: 1 day, 4:22:18 time: 0.3608 data_time: 0.0267 memory: 11108 grad_norm: 2.8126 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.8198 loss: 2.8198 2022/10/09 09:10:39 - mmengine - INFO - Epoch(train) [16][880/2119] lr: 4.0000e-02 eta: 1 day, 4:22:10 time: 0.3545 data_time: 0.0177 memory: 11108 grad_norm: 2.8711 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8584 loss: 2.8584 2022/10/09 09:10:46 - mmengine - INFO - Epoch(train) [16][900/2119] lr: 4.0000e-02 eta: 1 day, 4:22:03 time: 0.3597 data_time: 0.0196 memory: 11108 grad_norm: 2.8647 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5410 loss: 2.5410 2022/10/09 09:10:53 - mmengine - INFO - Epoch(train) [16][920/2119] lr: 4.0000e-02 eta: 1 day, 4:21:57 time: 0.3599 data_time: 0.0206 memory: 11108 grad_norm: 2.8137 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6435 loss: 2.6435 2022/10/09 09:11:00 - mmengine - INFO - Epoch(train) [16][940/2119] lr: 4.0000e-02 eta: 1 day, 4:21:49 time: 0.3559 data_time: 0.0239 memory: 11108 grad_norm: 2.8097 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7544 loss: 2.7544 2022/10/09 09:11:08 - mmengine - INFO - Epoch(train) [16][960/2119] lr: 4.0000e-02 eta: 1 day, 4:21:42 time: 0.3611 data_time: 0.0233 memory: 11108 grad_norm: 2.9045 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7347 loss: 2.7347 2022/10/09 09:11:15 - mmengine - INFO - Epoch(train) [16][980/2119] lr: 4.0000e-02 eta: 1 day, 4:21:35 time: 0.3570 data_time: 0.0165 memory: 11108 grad_norm: 2.8856 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6516 loss: 2.6516 2022/10/09 09:11:22 - mmengine - INFO - Epoch(train) [16][1000/2119] lr: 4.0000e-02 eta: 1 day, 4:21:28 time: 0.3613 data_time: 0.0211 memory: 11108 grad_norm: 2.8002 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.5579 loss: 2.5579 2022/10/09 09:11:29 - mmengine - INFO - Epoch(train) [16][1020/2119] lr: 4.0000e-02 eta: 1 day, 4:21:21 time: 0.3550 data_time: 0.0174 memory: 11108 grad_norm: 2.7850 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7821 loss: 2.7821 2022/10/09 09:11:36 - mmengine - INFO - Epoch(train) [16][1040/2119] lr: 4.0000e-02 eta: 1 day, 4:21:14 time: 0.3582 data_time: 0.0220 memory: 11108 grad_norm: 2.8442 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5200 loss: 2.5200 2022/10/09 09:11:43 - mmengine - INFO - Epoch(train) [16][1060/2119] lr: 4.0000e-02 eta: 1 day, 4:21:07 time: 0.3595 data_time: 0.0197 memory: 11108 grad_norm: 2.8363 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6226 loss: 2.6226 2022/10/09 09:11:51 - mmengine - INFO - Epoch(train) [16][1080/2119] lr: 4.0000e-02 eta: 1 day, 4:20:59 time: 0.3580 data_time: 0.0250 memory: 11108 grad_norm: 2.8232 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5345 loss: 2.5345 2022/10/09 09:11:58 - mmengine - INFO - Epoch(train) [16][1100/2119] lr: 4.0000e-02 eta: 1 day, 4:20:52 time: 0.3549 data_time: 0.0181 memory: 11108 grad_norm: 2.8280 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6699 loss: 2.6699 2022/10/09 09:12:05 - mmengine - INFO - Epoch(train) [16][1120/2119] lr: 4.0000e-02 eta: 1 day, 4:20:44 time: 0.3572 data_time: 0.0202 memory: 11108 grad_norm: 2.8269 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6685 loss: 2.6685 2022/10/09 09:12:12 - mmengine - INFO - Epoch(train) [16][1140/2119] lr: 4.0000e-02 eta: 1 day, 4:20:37 time: 0.3558 data_time: 0.0216 memory: 11108 grad_norm: 2.7839 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8963 loss: 2.8963 2022/10/09 09:12:19 - mmengine - INFO - Epoch(train) [16][1160/2119] lr: 4.0000e-02 eta: 1 day, 4:20:30 time: 0.3579 data_time: 0.0210 memory: 11108 grad_norm: 2.8343 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5377 loss: 2.5377 2022/10/09 09:12:27 - mmengine - INFO - Epoch(train) [16][1180/2119] lr: 4.0000e-02 eta: 1 day, 4:20:24 time: 0.3678 data_time: 0.0219 memory: 11108 grad_norm: 2.8410 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7655 loss: 2.7655 2022/10/09 09:12:34 - mmengine - INFO - Epoch(train) [16][1200/2119] lr: 4.0000e-02 eta: 1 day, 4:20:17 time: 0.3599 data_time: 0.0231 memory: 11108 grad_norm: 2.8032 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5135 loss: 2.5135 2022/10/09 09:12:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 09:12:41 - mmengine - INFO - Epoch(train) [16][1220/2119] lr: 4.0000e-02 eta: 1 day, 4:20:10 time: 0.3561 data_time: 0.0198 memory: 11108 grad_norm: 2.8096 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6187 loss: 2.6187 2022/10/09 09:12:48 - mmengine - INFO - Epoch(train) [16][1240/2119] lr: 4.0000e-02 eta: 1 day, 4:20:03 time: 0.3578 data_time: 0.0232 memory: 11108 grad_norm: 2.7647 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6004 loss: 2.6004 2022/10/09 09:12:55 - mmengine - INFO - Epoch(train) [16][1260/2119] lr: 4.0000e-02 eta: 1 day, 4:19:55 time: 0.3554 data_time: 0.0192 memory: 11108 grad_norm: 2.8233 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6780 loss: 2.6780 2022/10/09 09:13:02 - mmengine - INFO - Epoch(train) [16][1280/2119] lr: 4.0000e-02 eta: 1 day, 4:19:48 time: 0.3582 data_time: 0.0197 memory: 11108 grad_norm: 2.8019 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8001 loss: 2.8001 2022/10/09 09:13:09 - mmengine - INFO - Epoch(train) [16][1300/2119] lr: 4.0000e-02 eta: 1 day, 4:19:40 time: 0.3549 data_time: 0.0206 memory: 11108 grad_norm: 2.8409 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7175 loss: 2.7175 2022/10/09 09:13:17 - mmengine - INFO - Epoch(train) [16][1320/2119] lr: 4.0000e-02 eta: 1 day, 4:19:33 time: 0.3596 data_time: 0.0195 memory: 11108 grad_norm: 2.8638 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9316 loss: 2.9316 2022/10/09 09:13:24 - mmengine - INFO - Epoch(train) [16][1340/2119] lr: 4.0000e-02 eta: 1 day, 4:19:27 time: 0.3620 data_time: 0.0214 memory: 11108 grad_norm: 2.8095 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7136 loss: 2.7136 2022/10/09 09:13:31 - mmengine - INFO - Epoch(train) [16][1360/2119] lr: 4.0000e-02 eta: 1 day, 4:19:19 time: 0.3570 data_time: 0.0246 memory: 11108 grad_norm: 2.8356 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5579 loss: 2.5579 2022/10/09 09:13:38 - mmengine - INFO - Epoch(train) [16][1380/2119] lr: 4.0000e-02 eta: 1 day, 4:19:12 time: 0.3577 data_time: 0.0197 memory: 11108 grad_norm: 2.7922 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.3399 loss: 2.3399 2022/10/09 09:13:45 - mmengine - INFO - Epoch(train) [16][1400/2119] lr: 4.0000e-02 eta: 1 day, 4:19:06 time: 0.3627 data_time: 0.0214 memory: 11108 grad_norm: 2.8037 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4695 loss: 2.4695 2022/10/09 09:13:53 - mmengine - INFO - Epoch(train) [16][1420/2119] lr: 4.0000e-02 eta: 1 day, 4:18:59 time: 0.3607 data_time: 0.0202 memory: 11108 grad_norm: 2.8428 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8454 loss: 2.8454 2022/10/09 09:14:00 - mmengine - INFO - Epoch(train) [16][1440/2119] lr: 4.0000e-02 eta: 1 day, 4:18:51 time: 0.3539 data_time: 0.0201 memory: 11108 grad_norm: 2.8456 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8204 loss: 2.8204 2022/10/09 09:14:07 - mmengine - INFO - Epoch(train) [16][1460/2119] lr: 4.0000e-02 eta: 1 day, 4:18:44 time: 0.3591 data_time: 0.0172 memory: 11108 grad_norm: 2.8339 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6540 loss: 2.6540 2022/10/09 09:14:14 - mmengine - INFO - Epoch(train) [16][1480/2119] lr: 4.0000e-02 eta: 1 day, 4:18:37 time: 0.3580 data_time: 0.0198 memory: 11108 grad_norm: 2.8441 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6678 loss: 2.6678 2022/10/09 09:14:21 - mmengine - INFO - Epoch(train) [16][1500/2119] lr: 4.0000e-02 eta: 1 day, 4:18:29 time: 0.3567 data_time: 0.0190 memory: 11108 grad_norm: 2.8476 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.3800 loss: 2.3800 2022/10/09 09:14:28 - mmengine - INFO - Epoch(train) [16][1520/2119] lr: 4.0000e-02 eta: 1 day, 4:18:22 time: 0.3568 data_time: 0.0194 memory: 11108 grad_norm: 2.8058 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5490 loss: 2.5490 2022/10/09 09:14:35 - mmengine - INFO - Epoch(train) [16][1540/2119] lr: 4.0000e-02 eta: 1 day, 4:18:15 time: 0.3576 data_time: 0.0182 memory: 11108 grad_norm: 2.8306 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7406 loss: 2.7406 2022/10/09 09:14:43 - mmengine - INFO - Epoch(train) [16][1560/2119] lr: 4.0000e-02 eta: 1 day, 4:18:07 time: 0.3567 data_time: 0.0213 memory: 11108 grad_norm: 2.7788 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6312 loss: 2.6312 2022/10/09 09:14:50 - mmengine - INFO - Epoch(train) [16][1580/2119] lr: 4.0000e-02 eta: 1 day, 4:18:00 time: 0.3567 data_time: 0.0187 memory: 11108 grad_norm: 2.8350 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5214 loss: 2.5214 2022/10/09 09:14:57 - mmengine - INFO - Epoch(train) [16][1600/2119] lr: 4.0000e-02 eta: 1 day, 4:17:53 time: 0.3575 data_time: 0.0219 memory: 11108 grad_norm: 2.8272 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5935 loss: 2.5935 2022/10/09 09:15:04 - mmengine - INFO - Epoch(train) [16][1620/2119] lr: 4.0000e-02 eta: 1 day, 4:17:47 time: 0.3653 data_time: 0.0186 memory: 11108 grad_norm: 2.8195 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5441 loss: 2.5441 2022/10/09 09:15:11 - mmengine - INFO - Epoch(train) [16][1640/2119] lr: 4.0000e-02 eta: 1 day, 4:17:40 time: 0.3578 data_time: 0.0207 memory: 11108 grad_norm: 2.8254 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6857 loss: 2.6857 2022/10/09 09:15:18 - mmengine - INFO - Epoch(train) [16][1660/2119] lr: 4.0000e-02 eta: 1 day, 4:17:32 time: 0.3538 data_time: 0.0202 memory: 11108 grad_norm: 2.8275 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6422 loss: 2.6422 2022/10/09 09:15:26 - mmengine - INFO - Epoch(train) [16][1680/2119] lr: 4.0000e-02 eta: 1 day, 4:17:25 time: 0.3629 data_time: 0.0187 memory: 11108 grad_norm: 2.8433 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.3856 loss: 2.3856 2022/10/09 09:15:33 - mmengine - INFO - Epoch(train) [16][1700/2119] lr: 4.0000e-02 eta: 1 day, 4:17:18 time: 0.3548 data_time: 0.0182 memory: 11108 grad_norm: 2.8725 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6241 loss: 2.6241 2022/10/09 09:15:40 - mmengine - INFO - Epoch(train) [16][1720/2119] lr: 4.0000e-02 eta: 1 day, 4:17:10 time: 0.3561 data_time: 0.0186 memory: 11108 grad_norm: 2.8716 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5515 loss: 2.5515 2022/10/09 09:15:47 - mmengine - INFO - Epoch(train) [16][1740/2119] lr: 4.0000e-02 eta: 1 day, 4:17:03 time: 0.3588 data_time: 0.0224 memory: 11108 grad_norm: 2.8207 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.5181 loss: 2.5181 2022/10/09 09:15:54 - mmengine - INFO - Epoch(train) [16][1760/2119] lr: 4.0000e-02 eta: 1 day, 4:16:55 time: 0.3546 data_time: 0.0179 memory: 11108 grad_norm: 2.8613 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5131 loss: 2.5131 2022/10/09 09:16:01 - mmengine - INFO - Epoch(train) [16][1780/2119] lr: 4.0000e-02 eta: 1 day, 4:16:49 time: 0.3640 data_time: 0.0206 memory: 11108 grad_norm: 2.8415 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3151 loss: 2.3151 2022/10/09 09:16:09 - mmengine - INFO - Epoch(train) [16][1800/2119] lr: 4.0000e-02 eta: 1 day, 4:16:42 time: 0.3596 data_time: 0.0206 memory: 11108 grad_norm: 2.7974 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6940 loss: 2.6940 2022/10/09 09:16:16 - mmengine - INFO - Epoch(train) [16][1820/2119] lr: 4.0000e-02 eta: 1 day, 4:16:35 time: 0.3551 data_time: 0.0190 memory: 11108 grad_norm: 2.7881 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6869 loss: 2.6869 2022/10/09 09:16:23 - mmengine - INFO - Epoch(train) [16][1840/2119] lr: 4.0000e-02 eta: 1 day, 4:16:27 time: 0.3581 data_time: 0.0233 memory: 11108 grad_norm: 2.8237 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4934 loss: 2.4934 2022/10/09 09:16:30 - mmengine - INFO - Epoch(train) [16][1860/2119] lr: 4.0000e-02 eta: 1 day, 4:16:21 time: 0.3599 data_time: 0.0206 memory: 11108 grad_norm: 2.8141 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7918 loss: 2.7918 2022/10/09 09:16:37 - mmengine - INFO - Epoch(train) [16][1880/2119] lr: 4.0000e-02 eta: 1 day, 4:16:13 time: 0.3571 data_time: 0.0197 memory: 11108 grad_norm: 2.7462 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7168 loss: 2.7168 2022/10/09 09:16:45 - mmengine - INFO - Epoch(train) [16][1900/2119] lr: 4.0000e-02 eta: 1 day, 4:16:07 time: 0.3666 data_time: 0.0296 memory: 11108 grad_norm: 2.8373 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5362 loss: 2.5362 2022/10/09 09:16:52 - mmengine - INFO - Epoch(train) [16][1920/2119] lr: 4.0000e-02 eta: 1 day, 4:16:01 time: 0.3595 data_time: 0.0216 memory: 11108 grad_norm: 2.9001 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7768 loss: 2.7768 2022/10/09 09:16:59 - mmengine - INFO - Epoch(train) [16][1940/2119] lr: 4.0000e-02 eta: 1 day, 4:15:53 time: 0.3557 data_time: 0.0205 memory: 11108 grad_norm: 2.7982 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5828 loss: 2.5828 2022/10/09 09:17:06 - mmengine - INFO - Epoch(train) [16][1960/2119] lr: 4.0000e-02 eta: 1 day, 4:15:47 time: 0.3647 data_time: 0.0232 memory: 11108 grad_norm: 2.8274 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.6260 loss: 2.6260 2022/10/09 09:17:13 - mmengine - INFO - Epoch(train) [16][1980/2119] lr: 4.0000e-02 eta: 1 day, 4:15:40 time: 0.3618 data_time: 0.0191 memory: 11108 grad_norm: 2.8164 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5464 loss: 2.5464 2022/10/09 09:17:21 - mmengine - INFO - Epoch(train) [16][2000/2119] lr: 4.0000e-02 eta: 1 day, 4:15:33 time: 0.3569 data_time: 0.0193 memory: 11108 grad_norm: 2.8455 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6372 loss: 2.6372 2022/10/09 09:17:28 - mmengine - INFO - Epoch(train) [16][2020/2119] lr: 4.0000e-02 eta: 1 day, 4:15:27 time: 0.3661 data_time: 0.0251 memory: 11108 grad_norm: 2.7896 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6777 loss: 2.6777 2022/10/09 09:17:35 - mmengine - INFO - Epoch(train) [16][2040/2119] lr: 4.0000e-02 eta: 1 day, 4:15:20 time: 0.3591 data_time: 0.0220 memory: 11108 grad_norm: 2.8742 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.4829 loss: 2.4829 2022/10/09 09:17:42 - mmengine - INFO - Epoch(train) [16][2060/2119] lr: 4.0000e-02 eta: 1 day, 4:15:13 time: 0.3563 data_time: 0.0194 memory: 11108 grad_norm: 2.8531 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6232 loss: 2.6232 2022/10/09 09:17:49 - mmengine - INFO - Epoch(train) [16][2080/2119] lr: 4.0000e-02 eta: 1 day, 4:15:05 time: 0.3532 data_time: 0.0235 memory: 11108 grad_norm: 2.7841 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5785 loss: 2.5785 2022/10/09 09:17:56 - mmengine - INFO - Epoch(train) [16][2100/2119] lr: 4.0000e-02 eta: 1 day, 4:14:57 time: 0.3569 data_time: 0.0231 memory: 11108 grad_norm: 2.8409 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8783 loss: 2.8783 2022/10/09 09:18:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 09:18:03 - mmengine - INFO - Epoch(train) [16][2119/2119] lr: 4.0000e-02 eta: 1 day, 4:14:57 time: 0.3538 data_time: 0.0205 memory: 11108 grad_norm: 2.8595 top1_acc: 0.4000 top5_acc: 0.9000 loss_cls: 2.4221 loss: 2.4221 2022/10/09 09:18:03 - mmengine - INFO - Saving checkpoint at 16 epochs 2022/10/09 09:18:16 - mmengine - INFO - Epoch(train) [17][20/2119] lr: 4.0000e-02 eta: 1 day, 4:14:01 time: 0.4427 data_time: 0.1083 memory: 11108 grad_norm: 2.7875 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7054 loss: 2.7054 2022/10/09 09:18:23 - mmengine - INFO - Epoch(train) [17][40/2119] lr: 4.0000e-02 eta: 1 day, 4:13:54 time: 0.3638 data_time: 0.0203 memory: 11108 grad_norm: 2.7633 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5620 loss: 2.5620 2022/10/09 09:18:30 - mmengine - INFO - Epoch(train) [17][60/2119] lr: 4.0000e-02 eta: 1 day, 4:13:47 time: 0.3579 data_time: 0.0202 memory: 11108 grad_norm: 2.8233 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5822 loss: 2.5822 2022/10/09 09:18:37 - mmengine - INFO - Epoch(train) [17][80/2119] lr: 4.0000e-02 eta: 1 day, 4:13:40 time: 0.3594 data_time: 0.0194 memory: 11108 grad_norm: 2.8353 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6175 loss: 2.6175 2022/10/09 09:18:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 09:18:44 - mmengine - INFO - Epoch(train) [17][100/2119] lr: 4.0000e-02 eta: 1 day, 4:13:33 time: 0.3560 data_time: 0.0187 memory: 11108 grad_norm: 2.8130 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7397 loss: 2.7397 2022/10/09 09:18:52 - mmengine - INFO - Epoch(train) [17][120/2119] lr: 4.0000e-02 eta: 1 day, 4:13:27 time: 0.3654 data_time: 0.0237 memory: 11108 grad_norm: 2.8472 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7088 loss: 2.7088 2022/10/09 09:18:59 - mmengine - INFO - Epoch(train) [17][140/2119] lr: 4.0000e-02 eta: 1 day, 4:13:20 time: 0.3580 data_time: 0.0167 memory: 11108 grad_norm: 2.7795 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4837 loss: 2.4837 2022/10/09 09:19:06 - mmengine - INFO - Epoch(train) [17][160/2119] lr: 4.0000e-02 eta: 1 day, 4:13:14 time: 0.3640 data_time: 0.0182 memory: 11108 grad_norm: 2.7808 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8859 loss: 2.8859 2022/10/09 09:19:13 - mmengine - INFO - Epoch(train) [17][180/2119] lr: 4.0000e-02 eta: 1 day, 4:13:06 time: 0.3573 data_time: 0.0183 memory: 11108 grad_norm: 2.8614 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.4716 loss: 2.4716 2022/10/09 09:19:21 - mmengine - INFO - Epoch(train) [17][200/2119] lr: 4.0000e-02 eta: 1 day, 4:13:00 time: 0.3624 data_time: 0.0203 memory: 11108 grad_norm: 2.8051 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5105 loss: 2.5105 2022/10/09 09:19:28 - mmengine - INFO - Epoch(train) [17][220/2119] lr: 4.0000e-02 eta: 1 day, 4:12:53 time: 0.3575 data_time: 0.0213 memory: 11108 grad_norm: 2.8355 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5651 loss: 2.5651 2022/10/09 09:19:35 - mmengine - INFO - Epoch(train) [17][240/2119] lr: 4.0000e-02 eta: 1 day, 4:12:45 time: 0.3577 data_time: 0.0214 memory: 11108 grad_norm: 2.7938 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6577 loss: 2.6577 2022/10/09 09:19:42 - mmengine - INFO - Epoch(train) [17][260/2119] lr: 4.0000e-02 eta: 1 day, 4:12:38 time: 0.3557 data_time: 0.0172 memory: 11108 grad_norm: 2.8522 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5047 loss: 2.5047 2022/10/09 09:19:49 - mmengine - INFO - Epoch(train) [17][280/2119] lr: 4.0000e-02 eta: 1 day, 4:12:30 time: 0.3554 data_time: 0.0181 memory: 11108 grad_norm: 2.8094 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.9342 loss: 2.9342 2022/10/09 09:19:56 - mmengine - INFO - Epoch(train) [17][300/2119] lr: 4.0000e-02 eta: 1 day, 4:12:24 time: 0.3618 data_time: 0.0253 memory: 11108 grad_norm: 2.8374 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6807 loss: 2.6807 2022/10/09 09:20:04 - mmengine - INFO - Epoch(train) [17][320/2119] lr: 4.0000e-02 eta: 1 day, 4:12:18 time: 0.3645 data_time: 0.0205 memory: 11108 grad_norm: 2.8742 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6581 loss: 2.6581 2022/10/09 09:20:11 - mmengine - INFO - Epoch(train) [17][340/2119] lr: 4.0000e-02 eta: 1 day, 4:12:10 time: 0.3548 data_time: 0.0215 memory: 11108 grad_norm: 2.8781 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7802 loss: 2.7802 2022/10/09 09:20:18 - mmengine - INFO - Epoch(train) [17][360/2119] lr: 4.0000e-02 eta: 1 day, 4:12:03 time: 0.3598 data_time: 0.0218 memory: 11108 grad_norm: 2.8589 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7104 loss: 2.7104 2022/10/09 09:20:25 - mmengine - INFO - Epoch(train) [17][380/2119] lr: 4.0000e-02 eta: 1 day, 4:11:57 time: 0.3614 data_time: 0.0204 memory: 11108 grad_norm: 2.7712 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4263 loss: 2.4263 2022/10/09 09:20:33 - mmengine - INFO - Epoch(train) [17][400/2119] lr: 4.0000e-02 eta: 1 day, 4:11:51 time: 0.3688 data_time: 0.0230 memory: 11108 grad_norm: 2.8110 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6831 loss: 2.6831 2022/10/09 09:20:40 - mmengine - INFO - Epoch(train) [17][420/2119] lr: 4.0000e-02 eta: 1 day, 4:11:43 time: 0.3549 data_time: 0.0179 memory: 11108 grad_norm: 2.8472 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0126 loss: 3.0126 2022/10/09 09:20:47 - mmengine - INFO - Epoch(train) [17][440/2119] lr: 4.0000e-02 eta: 1 day, 4:11:36 time: 0.3591 data_time: 0.0226 memory: 11108 grad_norm: 2.8283 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6678 loss: 2.6678 2022/10/09 09:20:54 - mmengine - INFO - Epoch(train) [17][460/2119] lr: 4.0000e-02 eta: 1 day, 4:11:29 time: 0.3573 data_time: 0.0195 memory: 11108 grad_norm: 2.8334 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6266 loss: 2.6266 2022/10/09 09:21:01 - mmengine - INFO - Epoch(train) [17][480/2119] lr: 4.0000e-02 eta: 1 day, 4:11:22 time: 0.3595 data_time: 0.0227 memory: 11108 grad_norm: 2.8838 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9005 loss: 2.9005 2022/10/09 09:21:08 - mmengine - INFO - Epoch(train) [17][500/2119] lr: 4.0000e-02 eta: 1 day, 4:11:15 time: 0.3554 data_time: 0.0188 memory: 11108 grad_norm: 2.7708 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.5665 loss: 2.5665 2022/10/09 09:21:15 - mmengine - INFO - Epoch(train) [17][520/2119] lr: 4.0000e-02 eta: 1 day, 4:11:07 time: 0.3542 data_time: 0.0205 memory: 11108 grad_norm: 2.7738 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6968 loss: 2.6968 2022/10/09 09:21:23 - mmengine - INFO - Epoch(train) [17][540/2119] lr: 4.0000e-02 eta: 1 day, 4:11:00 time: 0.3607 data_time: 0.0210 memory: 11108 grad_norm: 2.8069 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6319 loss: 2.6319 2022/10/09 09:21:30 - mmengine - INFO - Epoch(train) [17][560/2119] lr: 4.0000e-02 eta: 1 day, 4:10:53 time: 0.3550 data_time: 0.0233 memory: 11108 grad_norm: 2.8104 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6500 loss: 2.6500 2022/10/09 09:21:37 - mmengine - INFO - Epoch(train) [17][580/2119] lr: 4.0000e-02 eta: 1 day, 4:10:46 time: 0.3604 data_time: 0.0207 memory: 11108 grad_norm: 2.8641 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5721 loss: 2.5721 2022/10/09 09:21:44 - mmengine - INFO - Epoch(train) [17][600/2119] lr: 4.0000e-02 eta: 1 day, 4:10:39 time: 0.3599 data_time: 0.0190 memory: 11108 grad_norm: 2.8948 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9899 loss: 2.9899 2022/10/09 09:21:51 - mmengine - INFO - Epoch(train) [17][620/2119] lr: 4.0000e-02 eta: 1 day, 4:10:31 time: 0.3563 data_time: 0.0212 memory: 11108 grad_norm: 2.8415 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.6740 loss: 2.6740 2022/10/09 09:21:58 - mmengine - INFO - Epoch(train) [17][640/2119] lr: 4.0000e-02 eta: 1 day, 4:10:24 time: 0.3581 data_time: 0.0181 memory: 11108 grad_norm: 2.8069 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6809 loss: 2.6809 2022/10/09 09:22:06 - mmengine - INFO - Epoch(train) [17][660/2119] lr: 4.0000e-02 eta: 1 day, 4:10:17 time: 0.3597 data_time: 0.0191 memory: 11108 grad_norm: 2.7644 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6679 loss: 2.6679 2022/10/09 09:22:13 - mmengine - INFO - Epoch(train) [17][680/2119] lr: 4.0000e-02 eta: 1 day, 4:10:10 time: 0.3562 data_time: 0.0224 memory: 11108 grad_norm: 2.8558 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7071 loss: 2.7071 2022/10/09 09:22:20 - mmengine - INFO - Epoch(train) [17][700/2119] lr: 4.0000e-02 eta: 1 day, 4:10:03 time: 0.3598 data_time: 0.0168 memory: 11108 grad_norm: 2.8183 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6492 loss: 2.6492 2022/10/09 09:22:27 - mmengine - INFO - Epoch(train) [17][720/2119] lr: 4.0000e-02 eta: 1 day, 4:09:56 time: 0.3599 data_time: 0.0208 memory: 11108 grad_norm: 2.7583 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7419 loss: 2.7419 2022/10/09 09:22:34 - mmengine - INFO - Epoch(train) [17][740/2119] lr: 4.0000e-02 eta: 1 day, 4:09:49 time: 0.3599 data_time: 0.0178 memory: 11108 grad_norm: 2.8415 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5755 loss: 2.5755 2022/10/09 09:22:42 - mmengine - INFO - Epoch(train) [17][760/2119] lr: 4.0000e-02 eta: 1 day, 4:09:44 time: 0.3695 data_time: 0.0204 memory: 11108 grad_norm: 2.7990 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6670 loss: 2.6670 2022/10/09 09:22:49 - mmengine - INFO - Epoch(train) [17][780/2119] lr: 4.0000e-02 eta: 1 day, 4:09:37 time: 0.3553 data_time: 0.0201 memory: 11108 grad_norm: 2.8375 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5464 loss: 2.5464 2022/10/09 09:22:56 - mmengine - INFO - Epoch(train) [17][800/2119] lr: 4.0000e-02 eta: 1 day, 4:09:29 time: 0.3572 data_time: 0.0214 memory: 11108 grad_norm: 2.8709 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.3771 loss: 2.3771 2022/10/09 09:23:03 - mmengine - INFO - Epoch(train) [17][820/2119] lr: 4.0000e-02 eta: 1 day, 4:09:23 time: 0.3619 data_time: 0.0201 memory: 11108 grad_norm: 2.8285 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.9114 loss: 2.9114 2022/10/09 09:23:10 - mmengine - INFO - Epoch(train) [17][840/2119] lr: 4.0000e-02 eta: 1 day, 4:09:15 time: 0.3572 data_time: 0.0273 memory: 11108 grad_norm: 2.7854 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7662 loss: 2.7662 2022/10/09 09:23:18 - mmengine - INFO - Epoch(train) [17][860/2119] lr: 4.0000e-02 eta: 1 day, 4:09:09 time: 0.3632 data_time: 0.0232 memory: 11108 grad_norm: 2.7734 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4810 loss: 2.4810 2022/10/09 09:23:25 - mmengine - INFO - Epoch(train) [17][880/2119] lr: 4.0000e-02 eta: 1 day, 4:09:02 time: 0.3569 data_time: 0.0213 memory: 11108 grad_norm: 2.8115 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6525 loss: 2.6525 2022/10/09 09:23:32 - mmengine - INFO - Epoch(train) [17][900/2119] lr: 4.0000e-02 eta: 1 day, 4:08:54 time: 0.3564 data_time: 0.0203 memory: 11108 grad_norm: 2.7942 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6436 loss: 2.6436 2022/10/09 09:23:39 - mmengine - INFO - Epoch(train) [17][920/2119] lr: 4.0000e-02 eta: 1 day, 4:08:47 time: 0.3567 data_time: 0.0185 memory: 11108 grad_norm: 2.7714 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5202 loss: 2.5202 2022/10/09 09:23:46 - mmengine - INFO - Epoch(train) [17][940/2119] lr: 4.0000e-02 eta: 1 day, 4:08:40 time: 0.3579 data_time: 0.0217 memory: 11108 grad_norm: 2.8549 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6502 loss: 2.6502 2022/10/09 09:23:53 - mmengine - INFO - Epoch(train) [17][960/2119] lr: 4.0000e-02 eta: 1 day, 4:08:33 time: 0.3600 data_time: 0.0199 memory: 11108 grad_norm: 2.7954 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5955 loss: 2.5955 2022/10/09 09:24:00 - mmengine - INFO - Epoch(train) [17][980/2119] lr: 4.0000e-02 eta: 1 day, 4:08:25 time: 0.3556 data_time: 0.0201 memory: 11108 grad_norm: 2.8318 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.5477 loss: 2.5477 2022/10/09 09:24:08 - mmengine - INFO - Epoch(train) [17][1000/2119] lr: 4.0000e-02 eta: 1 day, 4:08:18 time: 0.3566 data_time: 0.0251 memory: 11108 grad_norm: 2.8683 top1_acc: 0.3750 top5_acc: 0.9375 loss_cls: 2.4807 loss: 2.4807 2022/10/09 09:24:15 - mmengine - INFO - Epoch(train) [17][1020/2119] lr: 4.0000e-02 eta: 1 day, 4:08:13 time: 0.3719 data_time: 0.0189 memory: 11108 grad_norm: 2.8541 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5821 loss: 2.5821 2022/10/09 09:24:22 - mmengine - INFO - Epoch(train) [17][1040/2119] lr: 4.0000e-02 eta: 1 day, 4:08:07 time: 0.3641 data_time: 0.0219 memory: 11108 grad_norm: 2.8265 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8477 loss: 2.8477 2022/10/09 09:24:29 - mmengine - INFO - Epoch(train) [17][1060/2119] lr: 4.0000e-02 eta: 1 day, 4:07:59 time: 0.3558 data_time: 0.0183 memory: 11108 grad_norm: 2.8500 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8025 loss: 2.8025 2022/10/09 09:24:37 - mmengine - INFO - Epoch(train) [17][1080/2119] lr: 4.0000e-02 eta: 1 day, 4:07:52 time: 0.3587 data_time: 0.0216 memory: 11108 grad_norm: 2.8913 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6341 loss: 2.6341 2022/10/09 09:24:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 09:24:44 - mmengine - INFO - Epoch(train) [17][1100/2119] lr: 4.0000e-02 eta: 1 day, 4:07:45 time: 0.3597 data_time: 0.0210 memory: 11108 grad_norm: 2.7911 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4860 loss: 2.4860 2022/10/09 09:24:51 - mmengine - INFO - Epoch(train) [17][1120/2119] lr: 4.0000e-02 eta: 1 day, 4:07:38 time: 0.3537 data_time: 0.0192 memory: 11108 grad_norm: 2.7670 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5924 loss: 2.5924 2022/10/09 09:24:58 - mmengine - INFO - Epoch(train) [17][1140/2119] lr: 4.0000e-02 eta: 1 day, 4:07:30 time: 0.3562 data_time: 0.0186 memory: 11108 grad_norm: 2.8477 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4838 loss: 2.4838 2022/10/09 09:25:05 - mmengine - INFO - Epoch(train) [17][1160/2119] lr: 4.0000e-02 eta: 1 day, 4:07:23 time: 0.3581 data_time: 0.0205 memory: 11108 grad_norm: 2.8107 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8751 loss: 2.8751 2022/10/09 09:25:12 - mmengine - INFO - Epoch(train) [17][1180/2119] lr: 4.0000e-02 eta: 1 day, 4:07:15 time: 0.3535 data_time: 0.0196 memory: 11108 grad_norm: 2.8322 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5683 loss: 2.5683 2022/10/09 09:25:19 - mmengine - INFO - Epoch(train) [17][1200/2119] lr: 4.0000e-02 eta: 1 day, 4:07:08 time: 0.3563 data_time: 0.0210 memory: 11108 grad_norm: 2.8567 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9899 loss: 2.9899 2022/10/09 09:25:26 - mmengine - INFO - Epoch(train) [17][1220/2119] lr: 4.0000e-02 eta: 1 day, 4:07:00 time: 0.3553 data_time: 0.0208 memory: 11108 grad_norm: 2.8849 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5647 loss: 2.5647 2022/10/09 09:25:34 - mmengine - INFO - Epoch(train) [17][1240/2119] lr: 4.0000e-02 eta: 1 day, 4:06:54 time: 0.3632 data_time: 0.0260 memory: 11108 grad_norm: 2.8115 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6506 loss: 2.6506 2022/10/09 09:25:41 - mmengine - INFO - Epoch(train) [17][1260/2119] lr: 4.0000e-02 eta: 1 day, 4:06:46 time: 0.3552 data_time: 0.0197 memory: 11108 grad_norm: 2.8275 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6393 loss: 2.6393 2022/10/09 09:25:48 - mmengine - INFO - Epoch(train) [17][1280/2119] lr: 4.0000e-02 eta: 1 day, 4:06:40 time: 0.3649 data_time: 0.0189 memory: 11108 grad_norm: 2.8543 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7022 loss: 2.7022 2022/10/09 09:25:55 - mmengine - INFO - Epoch(train) [17][1300/2119] lr: 4.0000e-02 eta: 1 day, 4:06:34 time: 0.3629 data_time: 0.0207 memory: 11108 grad_norm: 2.8742 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7940 loss: 2.7940 2022/10/09 09:26:03 - mmengine - INFO - Epoch(train) [17][1320/2119] lr: 4.0000e-02 eta: 1 day, 4:06:27 time: 0.3591 data_time: 0.0209 memory: 11108 grad_norm: 2.8537 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7754 loss: 2.7754 2022/10/09 09:26:10 - mmengine - INFO - Epoch(train) [17][1340/2119] lr: 4.0000e-02 eta: 1 day, 4:06:19 time: 0.3566 data_time: 0.0197 memory: 11108 grad_norm: 2.8428 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.6973 loss: 2.6973 2022/10/09 09:26:17 - mmengine - INFO - Epoch(train) [17][1360/2119] lr: 4.0000e-02 eta: 1 day, 4:06:13 time: 0.3630 data_time: 0.0216 memory: 11108 grad_norm: 2.8455 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6229 loss: 2.6229 2022/10/09 09:26:24 - mmengine - INFO - Epoch(train) [17][1380/2119] lr: 4.0000e-02 eta: 1 day, 4:06:06 time: 0.3608 data_time: 0.0187 memory: 11108 grad_norm: 2.8433 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5994 loss: 2.5994 2022/10/09 09:26:31 - mmengine - INFO - Epoch(train) [17][1400/2119] lr: 4.0000e-02 eta: 1 day, 4:05:58 time: 0.3533 data_time: 0.0236 memory: 11108 grad_norm: 2.8620 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4887 loss: 2.4887 2022/10/09 09:26:38 - mmengine - INFO - Epoch(train) [17][1420/2119] lr: 4.0000e-02 eta: 1 day, 4:05:51 time: 0.3564 data_time: 0.0174 memory: 11108 grad_norm: 2.8417 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4379 loss: 2.4379 2022/10/09 09:26:46 - mmengine - INFO - Epoch(train) [17][1440/2119] lr: 4.0000e-02 eta: 1 day, 4:05:44 time: 0.3576 data_time: 0.0211 memory: 11108 grad_norm: 2.8248 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.3661 loss: 2.3661 2022/10/09 09:26:53 - mmengine - INFO - Epoch(train) [17][1460/2119] lr: 4.0000e-02 eta: 1 day, 4:05:37 time: 0.3609 data_time: 0.0210 memory: 11108 grad_norm: 2.8327 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5684 loss: 2.5684 2022/10/09 09:27:00 - mmengine - INFO - Epoch(train) [17][1480/2119] lr: 4.0000e-02 eta: 1 day, 4:05:29 time: 0.3531 data_time: 0.0186 memory: 11108 grad_norm: 2.8823 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0890 loss: 3.0890 2022/10/09 09:27:07 - mmengine - INFO - Epoch(train) [17][1500/2119] lr: 4.0000e-02 eta: 1 day, 4:05:22 time: 0.3602 data_time: 0.0216 memory: 11108 grad_norm: 2.8589 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6160 loss: 2.6160 2022/10/09 09:27:14 - mmengine - INFO - Epoch(train) [17][1520/2119] lr: 4.0000e-02 eta: 1 day, 4:05:15 time: 0.3555 data_time: 0.0199 memory: 11108 grad_norm: 2.8346 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.5915 loss: 2.5915 2022/10/09 09:27:21 - mmengine - INFO - Epoch(train) [17][1540/2119] lr: 4.0000e-02 eta: 1 day, 4:05:08 time: 0.3591 data_time: 0.0241 memory: 11108 grad_norm: 2.8427 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6528 loss: 2.6528 2022/10/09 09:27:28 - mmengine - INFO - Epoch(train) [17][1560/2119] lr: 4.0000e-02 eta: 1 day, 4:05:00 time: 0.3561 data_time: 0.0208 memory: 11108 grad_norm: 2.8069 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.6995 loss: 2.6995 2022/10/09 09:27:36 - mmengine - INFO - Epoch(train) [17][1580/2119] lr: 4.0000e-02 eta: 1 day, 4:04:53 time: 0.3566 data_time: 0.0198 memory: 11108 grad_norm: 2.8284 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6520 loss: 2.6520 2022/10/09 09:27:43 - mmengine - INFO - Epoch(train) [17][1600/2119] lr: 4.0000e-02 eta: 1 day, 4:04:46 time: 0.3602 data_time: 0.0228 memory: 11108 grad_norm: 2.8065 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7512 loss: 2.7512 2022/10/09 09:27:50 - mmengine - INFO - Epoch(train) [17][1620/2119] lr: 4.0000e-02 eta: 1 day, 4:04:39 time: 0.3583 data_time: 0.0229 memory: 11108 grad_norm: 2.8841 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8614 loss: 2.8614 2022/10/09 09:27:57 - mmengine - INFO - Epoch(train) [17][1640/2119] lr: 4.0000e-02 eta: 1 day, 4:04:31 time: 0.3558 data_time: 0.0206 memory: 11108 grad_norm: 2.8004 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4788 loss: 2.4788 2022/10/09 09:28:05 - mmengine - INFO - Epoch(train) [17][1660/2119] lr: 4.0000e-02 eta: 1 day, 4:04:27 time: 0.3728 data_time: 0.0207 memory: 11108 grad_norm: 2.8182 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8601 loss: 2.8601 2022/10/09 09:28:12 - mmengine - INFO - Epoch(train) [17][1680/2119] lr: 4.0000e-02 eta: 1 day, 4:04:19 time: 0.3544 data_time: 0.0235 memory: 11108 grad_norm: 2.8389 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7755 loss: 2.7755 2022/10/09 09:28:19 - mmengine - INFO - Epoch(train) [17][1700/2119] lr: 4.0000e-02 eta: 1 day, 4:04:11 time: 0.3566 data_time: 0.0211 memory: 11108 grad_norm: 2.8447 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7062 loss: 2.7062 2022/10/09 09:28:26 - mmengine - INFO - Epoch(train) [17][1720/2119] lr: 4.0000e-02 eta: 1 day, 4:04:05 time: 0.3600 data_time: 0.0205 memory: 11108 grad_norm: 2.7669 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5270 loss: 2.5270 2022/10/09 09:28:33 - mmengine - INFO - Epoch(train) [17][1740/2119] lr: 4.0000e-02 eta: 1 day, 4:03:59 time: 0.3705 data_time: 0.0226 memory: 11108 grad_norm: 2.8349 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5416 loss: 2.5416 2022/10/09 09:28:40 - mmengine - INFO - Epoch(train) [17][1760/2119] lr: 4.0000e-02 eta: 1 day, 4:03:52 time: 0.3559 data_time: 0.0188 memory: 11108 grad_norm: 2.8192 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.4782 loss: 2.4782 2022/10/09 09:28:48 - mmengine - INFO - Epoch(train) [17][1780/2119] lr: 4.0000e-02 eta: 1 day, 4:03:45 time: 0.3629 data_time: 0.0318 memory: 11108 grad_norm: 2.8070 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6592 loss: 2.6592 2022/10/09 09:28:55 - mmengine - INFO - Epoch(train) [17][1800/2119] lr: 4.0000e-02 eta: 1 day, 4:03:38 time: 0.3581 data_time: 0.0218 memory: 11108 grad_norm: 2.7785 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.5040 loss: 2.5040 2022/10/09 09:29:02 - mmengine - INFO - Epoch(train) [17][1820/2119] lr: 4.0000e-02 eta: 1 day, 4:03:31 time: 0.3584 data_time: 0.0211 memory: 11108 grad_norm: 2.8361 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5861 loss: 2.5861 2022/10/09 09:29:09 - mmengine - INFO - Epoch(train) [17][1840/2119] lr: 4.0000e-02 eta: 1 day, 4:03:24 time: 0.3584 data_time: 0.0181 memory: 11108 grad_norm: 2.8098 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7422 loss: 2.7422 2022/10/09 09:29:16 - mmengine - INFO - Epoch(train) [17][1860/2119] lr: 4.0000e-02 eta: 1 day, 4:03:17 time: 0.3583 data_time: 0.0236 memory: 11108 grad_norm: 2.7958 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7928 loss: 2.7928 2022/10/09 09:29:24 - mmengine - INFO - Epoch(train) [17][1880/2119] lr: 4.0000e-02 eta: 1 day, 4:03:10 time: 0.3564 data_time: 0.0213 memory: 11108 grad_norm: 2.8070 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8407 loss: 2.8407 2022/10/09 09:29:31 - mmengine - INFO - Epoch(train) [17][1900/2119] lr: 4.0000e-02 eta: 1 day, 4:03:02 time: 0.3539 data_time: 0.0176 memory: 11108 grad_norm: 2.8091 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6864 loss: 2.6864 2022/10/09 09:29:38 - mmengine - INFO - Epoch(train) [17][1920/2119] lr: 4.0000e-02 eta: 1 day, 4:02:55 time: 0.3597 data_time: 0.0220 memory: 11108 grad_norm: 2.8115 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7820 loss: 2.7820 2022/10/09 09:29:45 - mmengine - INFO - Epoch(train) [17][1940/2119] lr: 4.0000e-02 eta: 1 day, 4:02:47 time: 0.3547 data_time: 0.0234 memory: 11108 grad_norm: 2.7621 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8179 loss: 2.8179 2022/10/09 09:29:52 - mmengine - INFO - Epoch(train) [17][1960/2119] lr: 4.0000e-02 eta: 1 day, 4:02:40 time: 0.3607 data_time: 0.0226 memory: 11108 grad_norm: 2.7888 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5470 loss: 2.5470 2022/10/09 09:29:59 - mmengine - INFO - Epoch(train) [17][1980/2119] lr: 4.0000e-02 eta: 1 day, 4:02:33 time: 0.3560 data_time: 0.0171 memory: 11108 grad_norm: 2.8874 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4905 loss: 2.4905 2022/10/09 09:30:06 - mmengine - INFO - Epoch(train) [17][2000/2119] lr: 4.0000e-02 eta: 1 day, 4:02:25 time: 0.3545 data_time: 0.0184 memory: 11108 grad_norm: 2.7995 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5207 loss: 2.5207 2022/10/09 09:30:14 - mmengine - INFO - Epoch(train) [17][2020/2119] lr: 4.0000e-02 eta: 1 day, 4:02:19 time: 0.3621 data_time: 0.0187 memory: 11108 grad_norm: 2.7961 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4990 loss: 2.4990 2022/10/09 09:30:21 - mmengine - INFO - Epoch(train) [17][2040/2119] lr: 4.0000e-02 eta: 1 day, 4:02:12 time: 0.3588 data_time: 0.0259 memory: 11108 grad_norm: 2.7816 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6465 loss: 2.6465 2022/10/09 09:30:28 - mmengine - INFO - Epoch(train) [17][2060/2119] lr: 4.0000e-02 eta: 1 day, 4:02:05 time: 0.3614 data_time: 0.0237 memory: 11108 grad_norm: 2.8022 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5613 loss: 2.5613 2022/10/09 09:30:35 - mmengine - INFO - Epoch(train) [17][2080/2119] lr: 4.0000e-02 eta: 1 day, 4:01:58 time: 0.3573 data_time: 0.0221 memory: 11108 grad_norm: 2.7381 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6220 loss: 2.6220 2022/10/09 09:30:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 09:30:42 - mmengine - INFO - Epoch(train) [17][2100/2119] lr: 4.0000e-02 eta: 1 day, 4:01:50 time: 0.3544 data_time: 0.0195 memory: 11108 grad_norm: 2.8024 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6855 loss: 2.6855 2022/10/09 09:30:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 09:30:49 - mmengine - INFO - Epoch(train) [17][2119/2119] lr: 4.0000e-02 eta: 1 day, 4:01:50 time: 0.3405 data_time: 0.0185 memory: 11108 grad_norm: 2.9292 top1_acc: 0.5000 top5_acc: 0.7000 loss_cls: 2.6576 loss: 2.6576 2022/10/09 09:30:59 - mmengine - INFO - Epoch(train) [18][20/2119] lr: 4.0000e-02 eta: 1 day, 4:01:06 time: 0.5029 data_time: 0.1277 memory: 11108 grad_norm: 2.8565 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5685 loss: 2.5685 2022/10/09 09:31:06 - mmengine - INFO - Epoch(train) [18][40/2119] lr: 4.0000e-02 eta: 1 day, 4:01:00 time: 0.3690 data_time: 0.0217 memory: 11108 grad_norm: 2.8282 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6422 loss: 2.6422 2022/10/09 09:31:13 - mmengine - INFO - Epoch(train) [18][60/2119] lr: 4.0000e-02 eta: 1 day, 4:00:53 time: 0.3561 data_time: 0.0204 memory: 11108 grad_norm: 2.8172 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6306 loss: 2.6306 2022/10/09 09:31:20 - mmengine - INFO - Epoch(train) [18][80/2119] lr: 4.0000e-02 eta: 1 day, 4:00:45 time: 0.3562 data_time: 0.0213 memory: 11108 grad_norm: 2.8931 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.3891 loss: 2.3891 2022/10/09 09:31:28 - mmengine - INFO - Epoch(train) [18][100/2119] lr: 4.0000e-02 eta: 1 day, 4:00:38 time: 0.3570 data_time: 0.0191 memory: 11108 grad_norm: 2.8310 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5353 loss: 2.5353 2022/10/09 09:31:35 - mmengine - INFO - Epoch(train) [18][120/2119] lr: 4.0000e-02 eta: 1 day, 4:00:32 time: 0.3660 data_time: 0.0202 memory: 11108 grad_norm: 2.8393 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4810 loss: 2.4810 2022/10/09 09:31:42 - mmengine - INFO - Epoch(train) [18][140/2119] lr: 4.0000e-02 eta: 1 day, 4:00:24 time: 0.3533 data_time: 0.0212 memory: 11108 grad_norm: 2.8356 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6846 loss: 2.6846 2022/10/09 09:31:49 - mmengine - INFO - Epoch(train) [18][160/2119] lr: 4.0000e-02 eta: 1 day, 4:00:17 time: 0.3584 data_time: 0.0216 memory: 11108 grad_norm: 2.8106 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5914 loss: 2.5914 2022/10/09 09:31:56 - mmengine - INFO - Epoch(train) [18][180/2119] lr: 4.0000e-02 eta: 1 day, 4:00:10 time: 0.3596 data_time: 0.0205 memory: 11108 grad_norm: 2.8370 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7364 loss: 2.7364 2022/10/09 09:32:03 - mmengine - INFO - Epoch(train) [18][200/2119] lr: 4.0000e-02 eta: 1 day, 4:00:03 time: 0.3580 data_time: 0.0215 memory: 11108 grad_norm: 2.8882 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9119 loss: 2.9119 2022/10/09 09:32:11 - mmengine - INFO - Epoch(train) [18][220/2119] lr: 4.0000e-02 eta: 1 day, 3:59:56 time: 0.3595 data_time: 0.0197 memory: 11108 grad_norm: 2.8659 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7483 loss: 2.7483 2022/10/09 09:32:18 - mmengine - INFO - Epoch(train) [18][240/2119] lr: 4.0000e-02 eta: 1 day, 3:59:49 time: 0.3602 data_time: 0.0216 memory: 11108 grad_norm: 2.8189 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5284 loss: 2.5284 2022/10/09 09:32:25 - mmengine - INFO - Epoch(train) [18][260/2119] lr: 4.0000e-02 eta: 1 day, 3:59:43 time: 0.3611 data_time: 0.0184 memory: 11108 grad_norm: 2.8985 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6668 loss: 2.6668 2022/10/09 09:32:32 - mmengine - INFO - Epoch(train) [18][280/2119] lr: 4.0000e-02 eta: 1 day, 3:59:36 time: 0.3607 data_time: 0.0238 memory: 11108 grad_norm: 2.8590 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5811 loss: 2.5811 2022/10/09 09:32:39 - mmengine - INFO - Epoch(train) [18][300/2119] lr: 4.0000e-02 eta: 1 day, 3:59:28 time: 0.3541 data_time: 0.0186 memory: 11108 grad_norm: 2.8306 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.5699 loss: 2.5699 2022/10/09 09:32:47 - mmengine - INFO - Epoch(train) [18][320/2119] lr: 4.0000e-02 eta: 1 day, 3:59:22 time: 0.3660 data_time: 0.0253 memory: 11108 grad_norm: 2.8353 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6176 loss: 2.6176 2022/10/09 09:32:54 - mmengine - INFO - Epoch(train) [18][340/2119] lr: 4.0000e-02 eta: 1 day, 3:59:15 time: 0.3593 data_time: 0.0225 memory: 11108 grad_norm: 2.7988 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5728 loss: 2.5728 2022/10/09 09:33:01 - mmengine - INFO - Epoch(train) [18][360/2119] lr: 4.0000e-02 eta: 1 day, 3:59:08 time: 0.3569 data_time: 0.0224 memory: 11108 grad_norm: 2.8375 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6237 loss: 2.6237 2022/10/09 09:33:08 - mmengine - INFO - Epoch(train) [18][380/2119] lr: 4.0000e-02 eta: 1 day, 3:59:03 time: 0.3699 data_time: 0.0206 memory: 11108 grad_norm: 2.7947 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.5959 loss: 2.5959 2022/10/09 09:33:16 - mmengine - INFO - Epoch(train) [18][400/2119] lr: 4.0000e-02 eta: 1 day, 3:58:55 time: 0.3544 data_time: 0.0229 memory: 11108 grad_norm: 2.8059 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5912 loss: 2.5912 2022/10/09 09:33:23 - mmengine - INFO - Epoch(train) [18][420/2119] lr: 4.0000e-02 eta: 1 day, 3:58:48 time: 0.3607 data_time: 0.0190 memory: 11108 grad_norm: 2.8427 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6644 loss: 2.6644 2022/10/09 09:33:30 - mmengine - INFO - Epoch(train) [18][440/2119] lr: 4.0000e-02 eta: 1 day, 3:58:41 time: 0.3557 data_time: 0.0236 memory: 11108 grad_norm: 2.8310 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7192 loss: 2.7192 2022/10/09 09:33:37 - mmengine - INFO - Epoch(train) [18][460/2119] lr: 4.0000e-02 eta: 1 day, 3:58:33 time: 0.3572 data_time: 0.0215 memory: 11108 grad_norm: 2.8419 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5472 loss: 2.5472 2022/10/09 09:33:44 - mmengine - INFO - Epoch(train) [18][480/2119] lr: 4.0000e-02 eta: 1 day, 3:58:27 time: 0.3629 data_time: 0.0201 memory: 11108 grad_norm: 2.7734 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5852 loss: 2.5852 2022/10/09 09:33:51 - mmengine - INFO - Epoch(train) [18][500/2119] lr: 4.0000e-02 eta: 1 day, 3:58:19 time: 0.3551 data_time: 0.0226 memory: 11108 grad_norm: 2.8000 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8081 loss: 2.8081 2022/10/09 09:33:59 - mmengine - INFO - Epoch(train) [18][520/2119] lr: 4.0000e-02 eta: 1 day, 3:58:13 time: 0.3601 data_time: 0.0270 memory: 11108 grad_norm: 2.8961 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6813 loss: 2.6813 2022/10/09 09:34:06 - mmengine - INFO - Epoch(train) [18][540/2119] lr: 4.0000e-02 eta: 1 day, 3:58:06 time: 0.3607 data_time: 0.0201 memory: 11108 grad_norm: 2.8400 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.4299 loss: 2.4299 2022/10/09 09:34:13 - mmengine - INFO - Epoch(train) [18][560/2119] lr: 4.0000e-02 eta: 1 day, 3:57:59 time: 0.3582 data_time: 0.0214 memory: 11108 grad_norm: 2.8728 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.5577 loss: 2.5577 2022/10/09 09:34:20 - mmengine - INFO - Epoch(train) [18][580/2119] lr: 4.0000e-02 eta: 1 day, 3:57:52 time: 0.3610 data_time: 0.0205 memory: 11108 grad_norm: 2.8047 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5935 loss: 2.5935 2022/10/09 09:34:27 - mmengine - INFO - Epoch(train) [18][600/2119] lr: 4.0000e-02 eta: 1 day, 3:57:45 time: 0.3578 data_time: 0.0197 memory: 11108 grad_norm: 2.7990 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6523 loss: 2.6523 2022/10/09 09:34:35 - mmengine - INFO - Epoch(train) [18][620/2119] lr: 4.0000e-02 eta: 1 day, 3:57:38 time: 0.3597 data_time: 0.0182 memory: 11108 grad_norm: 2.8254 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6521 loss: 2.6521 2022/10/09 09:34:42 - mmengine - INFO - Epoch(train) [18][640/2119] lr: 4.0000e-02 eta: 1 day, 3:57:31 time: 0.3573 data_time: 0.0186 memory: 11108 grad_norm: 2.8011 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6985 loss: 2.6985 2022/10/09 09:34:49 - mmengine - INFO - Epoch(train) [18][660/2119] lr: 4.0000e-02 eta: 1 day, 3:57:24 time: 0.3587 data_time: 0.0206 memory: 11108 grad_norm: 2.8053 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8017 loss: 2.8017 2022/10/09 09:34:56 - mmengine - INFO - Epoch(train) [18][680/2119] lr: 4.0000e-02 eta: 1 day, 3:57:17 time: 0.3575 data_time: 0.0239 memory: 11108 grad_norm: 2.7876 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6708 loss: 2.6708 2022/10/09 09:35:03 - mmengine - INFO - Epoch(train) [18][700/2119] lr: 4.0000e-02 eta: 1 day, 3:57:09 time: 0.3571 data_time: 0.0240 memory: 11108 grad_norm: 2.7796 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6978 loss: 2.6978 2022/10/09 09:35:10 - mmengine - INFO - Epoch(train) [18][720/2119] lr: 4.0000e-02 eta: 1 day, 3:57:02 time: 0.3558 data_time: 0.0210 memory: 11108 grad_norm: 2.8516 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6528 loss: 2.6528 2022/10/09 09:35:17 - mmengine - INFO - Epoch(train) [18][740/2119] lr: 4.0000e-02 eta: 1 day, 3:56:55 time: 0.3578 data_time: 0.0215 memory: 11108 grad_norm: 2.8208 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4396 loss: 2.4396 2022/10/09 09:35:25 - mmengine - INFO - Epoch(train) [18][760/2119] lr: 4.0000e-02 eta: 1 day, 3:56:48 time: 0.3589 data_time: 0.0236 memory: 11108 grad_norm: 2.8266 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.4886 loss: 2.4886 2022/10/09 09:35:32 - mmengine - INFO - Epoch(train) [18][780/2119] lr: 4.0000e-02 eta: 1 day, 3:56:40 time: 0.3584 data_time: 0.0242 memory: 11108 grad_norm: 2.8775 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4697 loss: 2.4697 2022/10/09 09:35:39 - mmengine - INFO - Epoch(train) [18][800/2119] lr: 4.0000e-02 eta: 1 day, 3:56:33 time: 0.3545 data_time: 0.0243 memory: 11108 grad_norm: 2.8105 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6317 loss: 2.6317 2022/10/09 09:35:46 - mmengine - INFO - Epoch(train) [18][820/2119] lr: 4.0000e-02 eta: 1 day, 3:56:26 time: 0.3612 data_time: 0.0188 memory: 11108 grad_norm: 2.8300 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5650 loss: 2.5650 2022/10/09 09:35:53 - mmengine - INFO - Epoch(train) [18][840/2119] lr: 4.0000e-02 eta: 1 day, 3:56:20 time: 0.3652 data_time: 0.0197 memory: 11108 grad_norm: 2.8309 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6541 loss: 2.6541 2022/10/09 09:36:00 - mmengine - INFO - Epoch(train) [18][860/2119] lr: 4.0000e-02 eta: 1 day, 3:56:12 time: 0.3548 data_time: 0.0190 memory: 11108 grad_norm: 2.8432 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5164 loss: 2.5164 2022/10/09 09:36:08 - mmengine - INFO - Epoch(train) [18][880/2119] lr: 4.0000e-02 eta: 1 day, 3:56:06 time: 0.3597 data_time: 0.0244 memory: 11108 grad_norm: 2.8490 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6523 loss: 2.6523 2022/10/09 09:36:15 - mmengine - INFO - Epoch(train) [18][900/2119] lr: 4.0000e-02 eta: 1 day, 3:55:58 time: 0.3539 data_time: 0.0214 memory: 11108 grad_norm: 2.8544 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4566 loss: 2.4566 2022/10/09 09:36:22 - mmengine - INFO - Epoch(train) [18][920/2119] lr: 4.0000e-02 eta: 1 day, 3:55:51 time: 0.3583 data_time: 0.0187 memory: 11108 grad_norm: 2.8251 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7165 loss: 2.7165 2022/10/09 09:36:29 - mmengine - INFO - Epoch(train) [18][940/2119] lr: 4.0000e-02 eta: 1 day, 3:55:43 time: 0.3563 data_time: 0.0203 memory: 11108 grad_norm: 2.8248 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7295 loss: 2.7295 2022/10/09 09:36:36 - mmengine - INFO - Epoch(train) [18][960/2119] lr: 4.0000e-02 eta: 1 day, 3:55:36 time: 0.3599 data_time: 0.0227 memory: 11108 grad_norm: 2.8114 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6974 loss: 2.6974 2022/10/09 09:36:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 09:36:43 - mmengine - INFO - Epoch(train) [18][980/2119] lr: 4.0000e-02 eta: 1 day, 3:55:29 time: 0.3560 data_time: 0.0217 memory: 11108 grad_norm: 2.8277 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5486 loss: 2.5486 2022/10/09 09:36:51 - mmengine - INFO - Epoch(train) [18][1000/2119] lr: 4.0000e-02 eta: 1 day, 3:55:22 time: 0.3573 data_time: 0.0197 memory: 11108 grad_norm: 2.7818 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6099 loss: 2.6099 2022/10/09 09:36:58 - mmengine - INFO - Epoch(train) [18][1020/2119] lr: 4.0000e-02 eta: 1 day, 3:55:14 time: 0.3568 data_time: 0.0187 memory: 11108 grad_norm: 2.8643 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6609 loss: 2.6609 2022/10/09 09:37:05 - mmengine - INFO - Epoch(train) [18][1040/2119] lr: 4.0000e-02 eta: 1 day, 3:55:07 time: 0.3542 data_time: 0.0226 memory: 11108 grad_norm: 2.8521 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7435 loss: 2.7435 2022/10/09 09:37:12 - mmengine - INFO - Epoch(train) [18][1060/2119] lr: 4.0000e-02 eta: 1 day, 3:54:59 time: 0.3581 data_time: 0.0213 memory: 11108 grad_norm: 2.8847 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6013 loss: 2.6013 2022/10/09 09:37:19 - mmengine - INFO - Epoch(train) [18][1080/2119] lr: 4.0000e-02 eta: 1 day, 3:54:53 time: 0.3598 data_time: 0.0218 memory: 11108 grad_norm: 2.8279 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6265 loss: 2.6265 2022/10/09 09:37:26 - mmengine - INFO - Epoch(train) [18][1100/2119] lr: 4.0000e-02 eta: 1 day, 3:54:46 time: 0.3609 data_time: 0.0247 memory: 11108 grad_norm: 2.7881 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7231 loss: 2.7231 2022/10/09 09:37:33 - mmengine - INFO - Epoch(train) [18][1120/2119] lr: 4.0000e-02 eta: 1 day, 3:54:38 time: 0.3557 data_time: 0.0222 memory: 11108 grad_norm: 2.8848 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6572 loss: 2.6572 2022/10/09 09:37:41 - mmengine - INFO - Epoch(train) [18][1140/2119] lr: 4.0000e-02 eta: 1 day, 3:54:31 time: 0.3587 data_time: 0.0190 memory: 11108 grad_norm: 2.7755 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5847 loss: 2.5847 2022/10/09 09:37:48 - mmengine - INFO - Epoch(train) [18][1160/2119] lr: 4.0000e-02 eta: 1 day, 3:54:24 time: 0.3585 data_time: 0.0228 memory: 11108 grad_norm: 2.8423 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7271 loss: 2.7271 2022/10/09 09:37:55 - mmengine - INFO - Epoch(train) [18][1180/2119] lr: 4.0000e-02 eta: 1 day, 3:54:17 time: 0.3594 data_time: 0.0226 memory: 11108 grad_norm: 2.8584 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6227 loss: 2.6227 2022/10/09 09:38:02 - mmengine - INFO - Epoch(train) [18][1200/2119] lr: 4.0000e-02 eta: 1 day, 3:54:10 time: 0.3589 data_time: 0.0201 memory: 11108 grad_norm: 2.8225 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8367 loss: 2.8367 2022/10/09 09:38:09 - mmengine - INFO - Epoch(train) [18][1220/2119] lr: 4.0000e-02 eta: 1 day, 3:54:03 time: 0.3590 data_time: 0.0170 memory: 11108 grad_norm: 2.8173 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5913 loss: 2.5913 2022/10/09 09:38:16 - mmengine - INFO - Epoch(train) [18][1240/2119] lr: 4.0000e-02 eta: 1 day, 3:53:55 time: 0.3529 data_time: 0.0227 memory: 11108 grad_norm: 2.8446 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6915 loss: 2.6915 2022/10/09 09:38:24 - mmengine - INFO - Epoch(train) [18][1260/2119] lr: 4.0000e-02 eta: 1 day, 3:53:48 time: 0.3594 data_time: 0.0234 memory: 11108 grad_norm: 2.8216 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5396 loss: 2.5396 2022/10/09 09:38:31 - mmengine - INFO - Epoch(train) [18][1280/2119] lr: 4.0000e-02 eta: 1 day, 3:53:41 time: 0.3558 data_time: 0.0258 memory: 11108 grad_norm: 2.7906 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6677 loss: 2.6677 2022/10/09 09:38:38 - mmengine - INFO - Epoch(train) [18][1300/2119] lr: 4.0000e-02 eta: 1 day, 3:53:34 time: 0.3567 data_time: 0.0183 memory: 11108 grad_norm: 2.8235 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6209 loss: 2.6209 2022/10/09 09:38:45 - mmengine - INFO - Epoch(train) [18][1320/2119] lr: 4.0000e-02 eta: 1 day, 3:53:27 time: 0.3629 data_time: 0.0258 memory: 11108 grad_norm: 2.8733 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7554 loss: 2.7554 2022/10/09 09:38:52 - mmengine - INFO - Epoch(train) [18][1340/2119] lr: 4.0000e-02 eta: 1 day, 3:53:19 time: 0.3542 data_time: 0.0219 memory: 11108 grad_norm: 2.8284 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5752 loss: 2.5752 2022/10/09 09:38:59 - mmengine - INFO - Epoch(train) [18][1360/2119] lr: 4.0000e-02 eta: 1 day, 3:53:12 time: 0.3583 data_time: 0.0257 memory: 11108 grad_norm: 2.8487 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5653 loss: 2.5653 2022/10/09 09:39:07 - mmengine - INFO - Epoch(train) [18][1380/2119] lr: 4.0000e-02 eta: 1 day, 3:53:07 time: 0.3668 data_time: 0.0165 memory: 11108 grad_norm: 2.8269 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8689 loss: 2.8689 2022/10/09 09:39:14 - mmengine - INFO - Epoch(train) [18][1400/2119] lr: 4.0000e-02 eta: 1 day, 3:52:59 time: 0.3584 data_time: 0.0180 memory: 11108 grad_norm: 2.7818 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6249 loss: 2.6249 2022/10/09 09:39:21 - mmengine - INFO - Epoch(train) [18][1420/2119] lr: 4.0000e-02 eta: 1 day, 3:52:53 time: 0.3607 data_time: 0.0222 memory: 11108 grad_norm: 2.8270 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8068 loss: 2.8068 2022/10/09 09:39:28 - mmengine - INFO - Epoch(train) [18][1440/2119] lr: 4.0000e-02 eta: 1 day, 3:52:45 time: 0.3556 data_time: 0.0198 memory: 11108 grad_norm: 2.7793 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.5620 loss: 2.5620 2022/10/09 09:39:35 - mmengine - INFO - Epoch(train) [18][1460/2119] lr: 4.0000e-02 eta: 1 day, 3:52:38 time: 0.3590 data_time: 0.0249 memory: 11108 grad_norm: 2.8317 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5340 loss: 2.5340 2022/10/09 09:39:43 - mmengine - INFO - Epoch(train) [18][1480/2119] lr: 4.0000e-02 eta: 1 day, 3:52:32 time: 0.3675 data_time: 0.0204 memory: 11108 grad_norm: 2.8703 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6092 loss: 2.6092 2022/10/09 09:39:50 - mmengine - INFO - Epoch(train) [18][1500/2119] lr: 4.0000e-02 eta: 1 day, 3:52:25 time: 0.3560 data_time: 0.0196 memory: 11108 grad_norm: 2.8574 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6216 loss: 2.6216 2022/10/09 09:39:57 - mmengine - INFO - Epoch(train) [18][1520/2119] lr: 4.0000e-02 eta: 1 day, 3:52:18 time: 0.3603 data_time: 0.0187 memory: 11108 grad_norm: 2.8260 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7335 loss: 2.7335 2022/10/09 09:40:04 - mmengine - INFO - Epoch(train) [18][1540/2119] lr: 4.0000e-02 eta: 1 day, 3:52:11 time: 0.3597 data_time: 0.0185 memory: 11108 grad_norm: 2.8141 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7011 loss: 2.7011 2022/10/09 09:40:11 - mmengine - INFO - Epoch(train) [18][1560/2119] lr: 4.0000e-02 eta: 1 day, 3:52:03 time: 0.3533 data_time: 0.0210 memory: 11108 grad_norm: 2.7952 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8291 loss: 2.8291 2022/10/09 09:40:19 - mmengine - INFO - Epoch(train) [18][1580/2119] lr: 4.0000e-02 eta: 1 day, 3:51:59 time: 0.3728 data_time: 0.0219 memory: 11108 grad_norm: 2.7996 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8501 loss: 2.8501 2022/10/09 09:40:26 - mmengine - INFO - Epoch(train) [18][1600/2119] lr: 4.0000e-02 eta: 1 day, 3:51:50 time: 0.3518 data_time: 0.0182 memory: 11108 grad_norm: 2.8837 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.3867 loss: 2.3867 2022/10/09 09:40:33 - mmengine - INFO - Epoch(train) [18][1620/2119] lr: 4.0000e-02 eta: 1 day, 3:51:44 time: 0.3615 data_time: 0.0183 memory: 11108 grad_norm: 2.8372 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7010 loss: 2.7010 2022/10/09 09:40:40 - mmengine - INFO - Epoch(train) [18][1640/2119] lr: 4.0000e-02 eta: 1 day, 3:51:37 time: 0.3574 data_time: 0.0214 memory: 11108 grad_norm: 2.7943 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7053 loss: 2.7053 2022/10/09 09:40:47 - mmengine - INFO - Epoch(train) [18][1660/2119] lr: 4.0000e-02 eta: 1 day, 3:51:29 time: 0.3559 data_time: 0.0201 memory: 11108 grad_norm: 2.7751 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6157 loss: 2.6157 2022/10/09 09:40:54 - mmengine - INFO - Epoch(train) [18][1680/2119] lr: 4.0000e-02 eta: 1 day, 3:51:22 time: 0.3561 data_time: 0.0231 memory: 11108 grad_norm: 2.8257 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7513 loss: 2.7513 2022/10/09 09:41:02 - mmengine - INFO - Epoch(train) [18][1700/2119] lr: 4.0000e-02 eta: 1 day, 3:51:14 time: 0.3568 data_time: 0.0213 memory: 11108 grad_norm: 2.8175 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4546 loss: 2.4546 2022/10/09 09:41:09 - mmengine - INFO - Epoch(train) [18][1720/2119] lr: 4.0000e-02 eta: 1 day, 3:51:07 time: 0.3569 data_time: 0.0219 memory: 11108 grad_norm: 2.7663 top1_acc: 0.0625 top5_acc: 0.6250 loss_cls: 2.6889 loss: 2.6889 2022/10/09 09:41:16 - mmengine - INFO - Epoch(train) [18][1740/2119] lr: 4.0000e-02 eta: 1 day, 3:51:01 time: 0.3637 data_time: 0.0206 memory: 11108 grad_norm: 2.8903 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6436 loss: 2.6436 2022/10/09 09:41:23 - mmengine - INFO - Epoch(train) [18][1760/2119] lr: 4.0000e-02 eta: 1 day, 3:50:54 time: 0.3583 data_time: 0.0195 memory: 11108 grad_norm: 2.8632 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5616 loss: 2.5616 2022/10/09 09:41:30 - mmengine - INFO - Epoch(train) [18][1780/2119] lr: 4.0000e-02 eta: 1 day, 3:50:47 time: 0.3597 data_time: 0.0162 memory: 11108 grad_norm: 2.8279 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.8037 loss: 2.8037 2022/10/09 09:41:38 - mmengine - INFO - Epoch(train) [18][1800/2119] lr: 4.0000e-02 eta: 1 day, 3:50:41 time: 0.3673 data_time: 0.0229 memory: 11108 grad_norm: 2.8243 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5857 loss: 2.5857 2022/10/09 09:41:45 - mmengine - INFO - Epoch(train) [18][1820/2119] lr: 4.0000e-02 eta: 1 day, 3:50:34 time: 0.3568 data_time: 0.0212 memory: 11108 grad_norm: 2.8819 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7365 loss: 2.7365 2022/10/09 09:41:52 - mmengine - INFO - Epoch(train) [18][1840/2119] lr: 4.0000e-02 eta: 1 day, 3:50:26 time: 0.3548 data_time: 0.0204 memory: 11108 grad_norm: 2.8363 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5690 loss: 2.5690 2022/10/09 09:41:59 - mmengine - INFO - Epoch(train) [18][1860/2119] lr: 4.0000e-02 eta: 1 day, 3:50:19 time: 0.3621 data_time: 0.0222 memory: 11108 grad_norm: 2.8514 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6697 loss: 2.6697 2022/10/09 09:42:06 - mmengine - INFO - Epoch(train) [18][1880/2119] lr: 4.0000e-02 eta: 1 day, 3:50:12 time: 0.3577 data_time: 0.0213 memory: 11108 grad_norm: 2.8023 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6810 loss: 2.6810 2022/10/09 09:42:14 - mmengine - INFO - Epoch(train) [18][1900/2119] lr: 4.0000e-02 eta: 1 day, 3:50:05 time: 0.3602 data_time: 0.0183 memory: 11108 grad_norm: 2.8187 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6686 loss: 2.6686 2022/10/09 09:42:21 - mmengine - INFO - Epoch(train) [18][1920/2119] lr: 4.0000e-02 eta: 1 day, 3:49:58 time: 0.3561 data_time: 0.0202 memory: 11108 grad_norm: 2.8345 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7762 loss: 2.7762 2022/10/09 09:42:28 - mmengine - INFO - Epoch(train) [18][1940/2119] lr: 4.0000e-02 eta: 1 day, 3:49:51 time: 0.3613 data_time: 0.0183 memory: 11108 grad_norm: 2.8567 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7642 loss: 2.7642 2022/10/09 09:42:35 - mmengine - INFO - Epoch(train) [18][1960/2119] lr: 4.0000e-02 eta: 1 day, 3:49:45 time: 0.3615 data_time: 0.0213 memory: 11108 grad_norm: 2.8271 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6521 loss: 2.6521 2022/10/09 09:42:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 09:42:42 - mmengine - INFO - Epoch(train) [18][1980/2119] lr: 4.0000e-02 eta: 1 day, 3:49:37 time: 0.3557 data_time: 0.0178 memory: 11108 grad_norm: 2.7974 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7460 loss: 2.7460 2022/10/09 09:42:50 - mmengine - INFO - Epoch(train) [18][2000/2119] lr: 4.0000e-02 eta: 1 day, 3:49:31 time: 0.3650 data_time: 0.0221 memory: 11108 grad_norm: 2.8088 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5879 loss: 2.5879 2022/10/09 09:42:57 - mmengine - INFO - Epoch(train) [18][2020/2119] lr: 4.0000e-02 eta: 1 day, 3:49:24 time: 0.3600 data_time: 0.0196 memory: 11108 grad_norm: 2.8394 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6823 loss: 2.6823 2022/10/09 09:43:04 - mmengine - INFO - Epoch(train) [18][2040/2119] lr: 4.0000e-02 eta: 1 day, 3:49:17 time: 0.3587 data_time: 0.0211 memory: 11108 grad_norm: 2.8508 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6340 loss: 2.6340 2022/10/09 09:43:11 - mmengine - INFO - Epoch(train) [18][2060/2119] lr: 4.0000e-02 eta: 1 day, 3:49:10 time: 0.3559 data_time: 0.0184 memory: 11108 grad_norm: 2.7644 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5277 loss: 2.5277 2022/10/09 09:43:18 - mmengine - INFO - Epoch(train) [18][2080/2119] lr: 4.0000e-02 eta: 1 day, 3:49:03 time: 0.3644 data_time: 0.0202 memory: 11108 grad_norm: 2.8200 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7677 loss: 2.7677 2022/10/09 09:43:25 - mmengine - INFO - Epoch(train) [18][2100/2119] lr: 4.0000e-02 eta: 1 day, 3:48:56 time: 0.3549 data_time: 0.0224 memory: 11108 grad_norm: 2.8235 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.6166 loss: 2.6166 2022/10/09 09:43:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 09:43:32 - mmengine - INFO - Epoch(train) [18][2119/2119] lr: 4.0000e-02 eta: 1 day, 3:48:56 time: 0.3400 data_time: 0.0191 memory: 11108 grad_norm: 2.8721 top1_acc: 0.3000 top5_acc: 0.8000 loss_cls: 2.6227 loss: 2.6227 2022/10/09 09:43:42 - mmengine - INFO - Epoch(train) [19][20/2119] lr: 4.0000e-02 eta: 1 day, 3:48:14 time: 0.5075 data_time: 0.1329 memory: 11108 grad_norm: 2.7968 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5651 loss: 2.5651 2022/10/09 09:43:49 - mmengine - INFO - Epoch(train) [19][40/2119] lr: 4.0000e-02 eta: 1 day, 3:48:08 time: 0.3642 data_time: 0.0208 memory: 11108 grad_norm: 2.8377 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5386 loss: 2.5386 2022/10/09 09:43:57 - mmengine - INFO - Epoch(train) [19][60/2119] lr: 4.0000e-02 eta: 1 day, 3:48:00 time: 0.3574 data_time: 0.0198 memory: 11108 grad_norm: 2.8109 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5020 loss: 2.5020 2022/10/09 09:44:04 - mmengine - INFO - Epoch(train) [19][80/2119] lr: 4.0000e-02 eta: 1 day, 3:47:53 time: 0.3579 data_time: 0.0218 memory: 11108 grad_norm: 2.8370 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.6577 loss: 2.6577 2022/10/09 09:44:11 - mmengine - INFO - Epoch(train) [19][100/2119] lr: 4.0000e-02 eta: 1 day, 3:47:48 time: 0.3695 data_time: 0.0174 memory: 11108 grad_norm: 2.8479 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6463 loss: 2.6463 2022/10/09 09:44:18 - mmengine - INFO - Epoch(train) [19][120/2119] lr: 4.0000e-02 eta: 1 day, 3:47:41 time: 0.3614 data_time: 0.0186 memory: 11108 grad_norm: 2.8308 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.6429 loss: 2.6429 2022/10/09 09:44:25 - mmengine - INFO - Epoch(train) [19][140/2119] lr: 4.0000e-02 eta: 1 day, 3:47:34 time: 0.3591 data_time: 0.0236 memory: 11108 grad_norm: 2.8215 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6834 loss: 2.6834 2022/10/09 09:44:33 - mmengine - INFO - Epoch(train) [19][160/2119] lr: 4.0000e-02 eta: 1 day, 3:47:27 time: 0.3581 data_time: 0.0216 memory: 11108 grad_norm: 2.8532 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6020 loss: 2.6020 2022/10/09 09:44:40 - mmengine - INFO - Epoch(train) [19][180/2119] lr: 4.0000e-02 eta: 1 day, 3:47:20 time: 0.3587 data_time: 0.0201 memory: 11108 grad_norm: 2.7466 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6430 loss: 2.6430 2022/10/09 09:44:47 - mmengine - INFO - Epoch(train) [19][200/2119] lr: 4.0000e-02 eta: 1 day, 3:47:12 time: 0.3546 data_time: 0.0216 memory: 11108 grad_norm: 2.8263 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8123 loss: 2.8123 2022/10/09 09:44:54 - mmengine - INFO - Epoch(train) [19][220/2119] lr: 4.0000e-02 eta: 1 day, 3:47:06 time: 0.3646 data_time: 0.0222 memory: 11108 grad_norm: 2.8035 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5659 loss: 2.5659 2022/10/09 09:45:01 - mmengine - INFO - Epoch(train) [19][240/2119] lr: 4.0000e-02 eta: 1 day, 3:46:59 time: 0.3556 data_time: 0.0213 memory: 11108 grad_norm: 2.7990 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6518 loss: 2.6518 2022/10/09 09:45:09 - mmengine - INFO - Epoch(train) [19][260/2119] lr: 4.0000e-02 eta: 1 day, 3:46:53 time: 0.3649 data_time: 0.0195 memory: 11108 grad_norm: 2.8038 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4450 loss: 2.4450 2022/10/09 09:45:16 - mmengine - INFO - Epoch(train) [19][280/2119] lr: 4.0000e-02 eta: 1 day, 3:46:45 time: 0.3587 data_time: 0.0190 memory: 11108 grad_norm: 2.8174 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.4598 loss: 2.4598 2022/10/09 09:45:23 - mmengine - INFO - Epoch(train) [19][300/2119] lr: 4.0000e-02 eta: 1 day, 3:46:40 time: 0.3707 data_time: 0.0270 memory: 11108 grad_norm: 2.8067 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6107 loss: 2.6107 2022/10/09 09:45:30 - mmengine - INFO - Epoch(train) [19][320/2119] lr: 4.0000e-02 eta: 1 day, 3:46:32 time: 0.3537 data_time: 0.0189 memory: 11108 grad_norm: 2.7590 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4033 loss: 2.4033 2022/10/09 09:45:38 - mmengine - INFO - Epoch(train) [19][340/2119] lr: 4.0000e-02 eta: 1 day, 3:46:26 time: 0.3601 data_time: 0.0204 memory: 11108 grad_norm: 2.8371 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4077 loss: 2.4077 2022/10/09 09:45:45 - mmengine - INFO - Epoch(train) [19][360/2119] lr: 4.0000e-02 eta: 1 day, 3:46:18 time: 0.3583 data_time: 0.0209 memory: 11108 grad_norm: 2.8779 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5820 loss: 2.5820 2022/10/09 09:45:52 - mmengine - INFO - Epoch(train) [19][380/2119] lr: 4.0000e-02 eta: 1 day, 3:46:11 time: 0.3535 data_time: 0.0207 memory: 11108 grad_norm: 2.8611 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7662 loss: 2.7662 2022/10/09 09:45:59 - mmengine - INFO - Epoch(train) [19][400/2119] lr: 4.0000e-02 eta: 1 day, 3:46:04 time: 0.3602 data_time: 0.0195 memory: 11108 grad_norm: 2.8328 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5644 loss: 2.5644 2022/10/09 09:46:06 - mmengine - INFO - Epoch(train) [19][420/2119] lr: 4.0000e-02 eta: 1 day, 3:45:57 time: 0.3599 data_time: 0.0199 memory: 11108 grad_norm: 2.8989 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.3739 loss: 2.3739 2022/10/09 09:46:13 - mmengine - INFO - Epoch(train) [19][440/2119] lr: 4.0000e-02 eta: 1 day, 3:45:50 time: 0.3564 data_time: 0.0214 memory: 11108 grad_norm: 2.8559 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6687 loss: 2.6687 2022/10/09 09:46:20 - mmengine - INFO - Epoch(train) [19][460/2119] lr: 4.0000e-02 eta: 1 day, 3:45:42 time: 0.3564 data_time: 0.0194 memory: 11108 grad_norm: 2.8109 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6504 loss: 2.6504 2022/10/09 09:46:28 - mmengine - INFO - Epoch(train) [19][480/2119] lr: 4.0000e-02 eta: 1 day, 3:45:36 time: 0.3610 data_time: 0.0206 memory: 11108 grad_norm: 2.8843 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6155 loss: 2.6155 2022/10/09 09:46:35 - mmengine - INFO - Epoch(train) [19][500/2119] lr: 4.0000e-02 eta: 1 day, 3:45:29 time: 0.3622 data_time: 0.0201 memory: 11108 grad_norm: 2.8362 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6685 loss: 2.6685 2022/10/09 09:46:42 - mmengine - INFO - Epoch(train) [19][520/2119] lr: 4.0000e-02 eta: 1 day, 3:45:22 time: 0.3562 data_time: 0.0216 memory: 11108 grad_norm: 2.8210 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8135 loss: 2.8135 2022/10/09 09:46:49 - mmengine - INFO - Epoch(train) [19][540/2119] lr: 4.0000e-02 eta: 1 day, 3:45:15 time: 0.3623 data_time: 0.0205 memory: 11108 grad_norm: 2.8657 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6694 loss: 2.6694 2022/10/09 09:46:57 - mmengine - INFO - Epoch(train) [19][560/2119] lr: 4.0000e-02 eta: 1 day, 3:45:09 time: 0.3639 data_time: 0.0210 memory: 11108 grad_norm: 2.8705 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6818 loss: 2.6818 2022/10/09 09:47:04 - mmengine - INFO - Epoch(train) [19][580/2119] lr: 4.0000e-02 eta: 1 day, 3:45:01 time: 0.3568 data_time: 0.0231 memory: 11108 grad_norm: 2.8795 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5864 loss: 2.5864 2022/10/09 09:47:11 - mmengine - INFO - Epoch(train) [19][600/2119] lr: 4.0000e-02 eta: 1 day, 3:44:54 time: 0.3551 data_time: 0.0200 memory: 11108 grad_norm: 2.8686 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4365 loss: 2.4365 2022/10/09 09:47:18 - mmengine - INFO - Epoch(train) [19][620/2119] lr: 4.0000e-02 eta: 1 day, 3:44:47 time: 0.3581 data_time: 0.0222 memory: 11108 grad_norm: 2.8440 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6202 loss: 2.6202 2022/10/09 09:47:25 - mmengine - INFO - Epoch(train) [19][640/2119] lr: 4.0000e-02 eta: 1 day, 3:44:39 time: 0.3567 data_time: 0.0213 memory: 11108 grad_norm: 2.7780 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8586 loss: 2.8586 2022/10/09 09:47:32 - mmengine - INFO - Epoch(train) [19][660/2119] lr: 4.0000e-02 eta: 1 day, 3:44:32 time: 0.3529 data_time: 0.0207 memory: 11108 grad_norm: 2.8170 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6163 loss: 2.6163 2022/10/09 09:47:39 - mmengine - INFO - Epoch(train) [19][680/2119] lr: 4.0000e-02 eta: 1 day, 3:44:25 time: 0.3620 data_time: 0.0242 memory: 11108 grad_norm: 2.8917 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7542 loss: 2.7542 2022/10/09 09:47:47 - mmengine - INFO - Epoch(train) [19][700/2119] lr: 4.0000e-02 eta: 1 day, 3:44:18 time: 0.3601 data_time: 0.0206 memory: 11108 grad_norm: 2.8543 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.5185 loss: 2.5185 2022/10/09 09:47:54 - mmengine - INFO - Epoch(train) [19][720/2119] lr: 4.0000e-02 eta: 1 day, 3:44:11 time: 0.3553 data_time: 0.0217 memory: 11108 grad_norm: 2.8278 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6430 loss: 2.6430 2022/10/09 09:48:01 - mmengine - INFO - Epoch(train) [19][740/2119] lr: 4.0000e-02 eta: 1 day, 3:44:03 time: 0.3556 data_time: 0.0198 memory: 11108 grad_norm: 2.8350 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7007 loss: 2.7007 2022/10/09 09:48:08 - mmengine - INFO - Epoch(train) [19][760/2119] lr: 4.0000e-02 eta: 1 day, 3:43:56 time: 0.3574 data_time: 0.0213 memory: 11108 grad_norm: 2.8291 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5897 loss: 2.5897 2022/10/09 09:48:15 - mmengine - INFO - Epoch(train) [19][780/2119] lr: 4.0000e-02 eta: 1 day, 3:43:49 time: 0.3599 data_time: 0.0283 memory: 11108 grad_norm: 2.8451 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8330 loss: 2.8330 2022/10/09 09:48:22 - mmengine - INFO - Epoch(train) [19][800/2119] lr: 4.0000e-02 eta: 1 day, 3:43:42 time: 0.3587 data_time: 0.0226 memory: 11108 grad_norm: 2.8064 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.7906 loss: 2.7906 2022/10/09 09:48:29 - mmengine - INFO - Epoch(train) [19][820/2119] lr: 4.0000e-02 eta: 1 day, 3:43:35 time: 0.3568 data_time: 0.0171 memory: 11108 grad_norm: 2.8667 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7082 loss: 2.7082 2022/10/09 09:48:37 - mmengine - INFO - Epoch(train) [19][840/2119] lr: 4.0000e-02 eta: 1 day, 3:43:28 time: 0.3586 data_time: 0.0209 memory: 11108 grad_norm: 2.8875 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6363 loss: 2.6363 2022/10/09 09:48:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 09:48:44 - mmengine - INFO - Epoch(train) [19][860/2119] lr: 4.0000e-02 eta: 1 day, 3:43:21 time: 0.3596 data_time: 0.0165 memory: 11108 grad_norm: 2.8580 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6110 loss: 2.6110 2022/10/09 09:48:51 - mmengine - INFO - Epoch(train) [19][880/2119] lr: 4.0000e-02 eta: 1 day, 3:43:13 time: 0.3546 data_time: 0.0195 memory: 11108 grad_norm: 2.8559 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7829 loss: 2.7829 2022/10/09 09:48:58 - mmengine - INFO - Epoch(train) [19][900/2119] lr: 4.0000e-02 eta: 1 day, 3:43:06 time: 0.3606 data_time: 0.0180 memory: 11108 grad_norm: 2.8308 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6786 loss: 2.6786 2022/10/09 09:49:05 - mmengine - INFO - Epoch(train) [19][920/2119] lr: 4.0000e-02 eta: 1 day, 3:42:59 time: 0.3598 data_time: 0.0260 memory: 11108 grad_norm: 2.8015 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3874 loss: 2.3874 2022/10/09 09:49:12 - mmengine - INFO - Epoch(train) [19][940/2119] lr: 4.0000e-02 eta: 1 day, 3:42:52 time: 0.3543 data_time: 0.0189 memory: 11108 grad_norm: 2.8706 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3647 loss: 2.3647 2022/10/09 09:49:20 - mmengine - INFO - Epoch(train) [19][960/2119] lr: 4.0000e-02 eta: 1 day, 3:42:45 time: 0.3603 data_time: 0.0237 memory: 11108 grad_norm: 2.8443 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6834 loss: 2.6834 2022/10/09 09:49:27 - mmengine - INFO - Epoch(train) [19][980/2119] lr: 4.0000e-02 eta: 1 day, 3:42:38 time: 0.3589 data_time: 0.0189 memory: 11108 grad_norm: 2.8796 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9721 loss: 2.9721 2022/10/09 09:49:34 - mmengine - INFO - Epoch(train) [19][1000/2119] lr: 4.0000e-02 eta: 1 day, 3:42:32 time: 0.3637 data_time: 0.0225 memory: 11108 grad_norm: 2.8101 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6043 loss: 2.6043 2022/10/09 09:49:41 - mmengine - INFO - Epoch(train) [19][1020/2119] lr: 4.0000e-02 eta: 1 day, 3:42:24 time: 0.3528 data_time: 0.0198 memory: 11108 grad_norm: 2.8156 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6592 loss: 2.6592 2022/10/09 09:49:48 - mmengine - INFO - Epoch(train) [19][1040/2119] lr: 4.0000e-02 eta: 1 day, 3:42:17 time: 0.3588 data_time: 0.0196 memory: 11108 grad_norm: 2.8791 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7700 loss: 2.7700 2022/10/09 09:49:55 - mmengine - INFO - Epoch(train) [19][1060/2119] lr: 4.0000e-02 eta: 1 day, 3:42:10 time: 0.3592 data_time: 0.0199 memory: 11108 grad_norm: 2.8525 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7502 loss: 2.7502 2022/10/09 09:50:03 - mmengine - INFO - Epoch(train) [19][1080/2119] lr: 4.0000e-02 eta: 1 day, 3:42:02 time: 0.3541 data_time: 0.0212 memory: 11108 grad_norm: 2.8709 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8288 loss: 2.8288 2022/10/09 09:50:10 - mmengine - INFO - Epoch(train) [19][1100/2119] lr: 4.0000e-02 eta: 1 day, 3:41:55 time: 0.3590 data_time: 0.0177 memory: 11108 grad_norm: 2.8684 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5490 loss: 2.5490 2022/10/09 09:50:17 - mmengine - INFO - Epoch(train) [19][1120/2119] lr: 4.0000e-02 eta: 1 day, 3:41:50 time: 0.3729 data_time: 0.0206 memory: 11108 grad_norm: 2.8656 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6085 loss: 2.6085 2022/10/09 09:50:24 - mmengine - INFO - Epoch(train) [19][1140/2119] lr: 4.0000e-02 eta: 1 day, 3:41:42 time: 0.3546 data_time: 0.0209 memory: 11108 grad_norm: 2.8701 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7275 loss: 2.7275 2022/10/09 09:50:31 - mmengine - INFO - Epoch(train) [19][1160/2119] lr: 4.0000e-02 eta: 1 day, 3:41:35 time: 0.3568 data_time: 0.0213 memory: 11108 grad_norm: 2.8606 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8781 loss: 2.8781 2022/10/09 09:50:39 - mmengine - INFO - Epoch(train) [19][1180/2119] lr: 4.0000e-02 eta: 1 day, 3:41:28 time: 0.3618 data_time: 0.0257 memory: 11108 grad_norm: 2.8609 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9657 loss: 2.9657 2022/10/09 09:50:46 - mmengine - INFO - Epoch(train) [19][1200/2119] lr: 4.0000e-02 eta: 1 day, 3:41:21 time: 0.3566 data_time: 0.0222 memory: 11108 grad_norm: 2.8060 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6254 loss: 2.6254 2022/10/09 09:50:53 - mmengine - INFO - Epoch(train) [19][1220/2119] lr: 4.0000e-02 eta: 1 day, 3:41:14 time: 0.3561 data_time: 0.0209 memory: 11108 grad_norm: 2.8221 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7108 loss: 2.7108 2022/10/09 09:51:00 - mmengine - INFO - Epoch(train) [19][1240/2119] lr: 4.0000e-02 eta: 1 day, 3:41:07 time: 0.3634 data_time: 0.0237 memory: 11108 grad_norm: 2.8424 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.3616 loss: 2.3616 2022/10/09 09:51:07 - mmengine - INFO - Epoch(train) [19][1260/2119] lr: 4.0000e-02 eta: 1 day, 3:41:00 time: 0.3558 data_time: 0.0189 memory: 11108 grad_norm: 2.8285 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6023 loss: 2.6023 2022/10/09 09:51:14 - mmengine - INFO - Epoch(train) [19][1280/2119] lr: 4.0000e-02 eta: 1 day, 3:40:52 time: 0.3565 data_time: 0.0188 memory: 11108 grad_norm: 2.7927 top1_acc: 0.2500 top5_acc: 0.8125 loss_cls: 2.4680 loss: 2.4680 2022/10/09 09:51:22 - mmengine - INFO - Epoch(train) [19][1300/2119] lr: 4.0000e-02 eta: 1 day, 3:40:45 time: 0.3586 data_time: 0.0188 memory: 11108 grad_norm: 2.8134 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6778 loss: 2.6778 2022/10/09 09:51:31 - mmengine - INFO - Epoch(train) [19][1320/2119] lr: 4.0000e-02 eta: 1 day, 3:40:55 time: 0.4787 data_time: 0.0303 memory: 11108 grad_norm: 2.8501 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.4444 loss: 2.4444 2022/10/09 09:51:42 - mmengine - INFO - Epoch(train) [19][1340/2119] lr: 4.0000e-02 eta: 1 day, 3:41:11 time: 0.5208 data_time: 0.0426 memory: 11108 grad_norm: 2.8231 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4464 loss: 2.4464 2022/10/09 09:51:49 - mmengine - INFO - Epoch(train) [19][1360/2119] lr: 4.0000e-02 eta: 1 day, 3:41:07 time: 0.3798 data_time: 0.0278 memory: 11108 grad_norm: 2.8788 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7093 loss: 2.7093 2022/10/09 09:51:57 - mmengine - INFO - Epoch(train) [19][1380/2119] lr: 4.0000e-02 eta: 1 day, 3:41:03 time: 0.3783 data_time: 0.0343 memory: 11108 grad_norm: 2.7738 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5593 loss: 2.5593 2022/10/09 09:52:04 - mmengine - INFO - Epoch(train) [19][1400/2119] lr: 4.0000e-02 eta: 1 day, 3:40:56 time: 0.3631 data_time: 0.0289 memory: 11108 grad_norm: 2.8557 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7354 loss: 2.7354 2022/10/09 09:52:11 - mmengine - INFO - Epoch(train) [19][1420/2119] lr: 4.0000e-02 eta: 1 day, 3:40:50 time: 0.3674 data_time: 0.0212 memory: 11108 grad_norm: 2.8443 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5561 loss: 2.5561 2022/10/09 09:52:19 - mmengine - INFO - Epoch(train) [19][1440/2119] lr: 4.0000e-02 eta: 1 day, 3:40:44 time: 0.3637 data_time: 0.0210 memory: 11108 grad_norm: 2.8464 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5984 loss: 2.5984 2022/10/09 09:52:26 - mmengine - INFO - Epoch(train) [19][1460/2119] lr: 4.0000e-02 eta: 1 day, 3:40:37 time: 0.3563 data_time: 0.0200 memory: 11108 grad_norm: 2.8373 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7570 loss: 2.7570 2022/10/09 09:52:33 - mmengine - INFO - Epoch(train) [19][1480/2119] lr: 4.0000e-02 eta: 1 day, 3:40:29 time: 0.3565 data_time: 0.0201 memory: 11108 grad_norm: 2.8351 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.7140 loss: 2.7140 2022/10/09 09:52:40 - mmengine - INFO - Epoch(train) [19][1500/2119] lr: 4.0000e-02 eta: 1 day, 3:40:23 time: 0.3631 data_time: 0.0208 memory: 11108 grad_norm: 2.8044 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6038 loss: 2.6038 2022/10/09 09:52:47 - mmengine - INFO - Epoch(train) [19][1520/2119] lr: 4.0000e-02 eta: 1 day, 3:40:16 time: 0.3630 data_time: 0.0214 memory: 11108 grad_norm: 2.8449 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6243 loss: 2.6243 2022/10/09 09:52:55 - mmengine - INFO - Epoch(train) [19][1540/2119] lr: 4.0000e-02 eta: 1 day, 3:40:09 time: 0.3569 data_time: 0.0215 memory: 11108 grad_norm: 2.8506 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5292 loss: 2.5292 2022/10/09 09:53:02 - mmengine - INFO - Epoch(train) [19][1560/2119] lr: 4.0000e-02 eta: 1 day, 3:40:02 time: 0.3600 data_time: 0.0195 memory: 11108 grad_norm: 2.9011 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6246 loss: 2.6246 2022/10/09 09:53:09 - mmengine - INFO - Epoch(train) [19][1580/2119] lr: 4.0000e-02 eta: 1 day, 3:39:55 time: 0.3592 data_time: 0.0184 memory: 11108 grad_norm: 2.8651 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.3686 loss: 2.3686 2022/10/09 09:53:16 - mmengine - INFO - Epoch(train) [19][1600/2119] lr: 4.0000e-02 eta: 1 day, 3:39:49 time: 0.3632 data_time: 0.0217 memory: 11108 grad_norm: 2.9036 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5987 loss: 2.5987 2022/10/09 09:53:23 - mmengine - INFO - Epoch(train) [19][1620/2119] lr: 4.0000e-02 eta: 1 day, 3:39:41 time: 0.3574 data_time: 0.0164 memory: 11108 grad_norm: 2.8686 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4682 loss: 2.4682 2022/10/09 09:53:31 - mmengine - INFO - Epoch(train) [19][1640/2119] lr: 4.0000e-02 eta: 1 day, 3:39:34 time: 0.3562 data_time: 0.0210 memory: 11108 grad_norm: 2.8802 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6650 loss: 2.6650 2022/10/09 09:53:38 - mmengine - INFO - Epoch(train) [19][1660/2119] lr: 4.0000e-02 eta: 1 day, 3:39:26 time: 0.3533 data_time: 0.0196 memory: 11108 grad_norm: 2.8665 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6258 loss: 2.6258 2022/10/09 09:53:45 - mmengine - INFO - Epoch(train) [19][1680/2119] lr: 4.0000e-02 eta: 1 day, 3:39:20 time: 0.3652 data_time: 0.0221 memory: 11108 grad_norm: 2.8170 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6728 loss: 2.6728 2022/10/09 09:53:52 - mmengine - INFO - Epoch(train) [19][1700/2119] lr: 4.0000e-02 eta: 1 day, 3:39:13 time: 0.3568 data_time: 0.0200 memory: 11108 grad_norm: 2.8125 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4722 loss: 2.4722 2022/10/09 09:54:00 - mmengine - INFO - Epoch(train) [19][1720/2119] lr: 4.0000e-02 eta: 1 day, 3:39:08 time: 0.3751 data_time: 0.0223 memory: 11108 grad_norm: 2.8373 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5842 loss: 2.5842 2022/10/09 09:54:07 - mmengine - INFO - Epoch(train) [19][1740/2119] lr: 4.0000e-02 eta: 1 day, 3:39:01 time: 0.3581 data_time: 0.0207 memory: 11108 grad_norm: 2.8734 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8209 loss: 2.8209 2022/10/09 09:54:14 - mmengine - INFO - Epoch(train) [19][1760/2119] lr: 4.0000e-02 eta: 1 day, 3:38:53 time: 0.3565 data_time: 0.0189 memory: 11108 grad_norm: 2.8226 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5703 loss: 2.5703 2022/10/09 09:54:21 - mmengine - INFO - Epoch(train) [19][1780/2119] lr: 4.0000e-02 eta: 1 day, 3:38:46 time: 0.3591 data_time: 0.0192 memory: 11108 grad_norm: 2.8456 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.7418 loss: 2.7418 2022/10/09 09:54:28 - mmengine - INFO - Epoch(train) [19][1800/2119] lr: 4.0000e-02 eta: 1 day, 3:38:39 time: 0.3585 data_time: 0.0190 memory: 11108 grad_norm: 2.7984 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7485 loss: 2.7485 2022/10/09 09:54:35 - mmengine - INFO - Epoch(train) [19][1820/2119] lr: 4.0000e-02 eta: 1 day, 3:38:32 time: 0.3607 data_time: 0.0192 memory: 11108 grad_norm: 2.8033 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6388 loss: 2.6388 2022/10/09 09:54:43 - mmengine - INFO - Epoch(train) [19][1840/2119] lr: 4.0000e-02 eta: 1 day, 3:38:25 time: 0.3582 data_time: 0.0215 memory: 11108 grad_norm: 2.8224 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6228 loss: 2.6228 2022/10/09 09:54:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 09:54:50 - mmengine - INFO - Epoch(train) [19][1860/2119] lr: 4.0000e-02 eta: 1 day, 3:38:18 time: 0.3574 data_time: 0.0198 memory: 11108 grad_norm: 2.7934 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7399 loss: 2.7399 2022/10/09 09:54:57 - mmengine - INFO - Epoch(train) [19][1880/2119] lr: 4.0000e-02 eta: 1 day, 3:38:11 time: 0.3572 data_time: 0.0191 memory: 11108 grad_norm: 2.8606 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.6209 loss: 2.6209 2022/10/09 09:55:04 - mmengine - INFO - Epoch(train) [19][1900/2119] lr: 4.0000e-02 eta: 1 day, 3:38:03 time: 0.3569 data_time: 0.0225 memory: 11108 grad_norm: 2.8590 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9209 loss: 2.9209 2022/10/09 09:55:11 - mmengine - INFO - Epoch(train) [19][1920/2119] lr: 4.0000e-02 eta: 1 day, 3:37:57 time: 0.3638 data_time: 0.0221 memory: 11108 grad_norm: 2.7957 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4995 loss: 2.4995 2022/10/09 09:55:18 - mmengine - INFO - Epoch(train) [19][1940/2119] lr: 4.0000e-02 eta: 1 day, 3:37:50 time: 0.3594 data_time: 0.0235 memory: 11108 grad_norm: 2.8640 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6004 loss: 2.6004 2022/10/09 09:55:26 - mmengine - INFO - Epoch(train) [19][1960/2119] lr: 4.0000e-02 eta: 1 day, 3:37:44 time: 0.3656 data_time: 0.0207 memory: 11108 grad_norm: 2.8687 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6956 loss: 2.6956 2022/10/09 09:55:33 - mmengine - INFO - Epoch(train) [19][1980/2119] lr: 4.0000e-02 eta: 1 day, 3:37:36 time: 0.3532 data_time: 0.0166 memory: 11108 grad_norm: 2.8504 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6708 loss: 2.6708 2022/10/09 09:55:40 - mmengine - INFO - Epoch(train) [19][2000/2119] lr: 4.0000e-02 eta: 1 day, 3:37:29 time: 0.3607 data_time: 0.0193 memory: 11108 grad_norm: 2.8079 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6236 loss: 2.6236 2022/10/09 09:55:47 - mmengine - INFO - Epoch(train) [19][2020/2119] lr: 4.0000e-02 eta: 1 day, 3:37:22 time: 0.3611 data_time: 0.0196 memory: 11108 grad_norm: 2.8362 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6002 loss: 2.6002 2022/10/09 09:55:55 - mmengine - INFO - Epoch(train) [19][2040/2119] lr: 4.0000e-02 eta: 1 day, 3:37:20 time: 0.3928 data_time: 0.0180 memory: 11108 grad_norm: 2.8352 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5236 loss: 2.5236 2022/10/09 09:56:07 - mmengine - INFO - Epoch(train) [19][2060/2119] lr: 4.0000e-02 eta: 1 day, 3:37:43 time: 0.5762 data_time: 0.1096 memory: 11108 grad_norm: 2.8481 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6366 loss: 2.6366 2022/10/09 09:56:23 - mmengine - INFO - Epoch(train) [19][2080/2119] lr: 4.0000e-02 eta: 1 day, 3:38:38 time: 0.8112 data_time: 0.0230 memory: 11108 grad_norm: 2.8757 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7096 loss: 2.7096 2022/10/09 09:56:30 - mmengine - INFO - Epoch(train) [19][2100/2119] lr: 4.0000e-02 eta: 1 day, 3:38:33 time: 0.3722 data_time: 0.0310 memory: 11108 grad_norm: 2.8344 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6022 loss: 2.6022 2022/10/09 09:56:37 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 09:56:37 - mmengine - INFO - Epoch(train) [19][2119/2119] lr: 4.0000e-02 eta: 1 day, 3:38:33 time: 0.3421 data_time: 0.0223 memory: 11108 grad_norm: 2.8417 top1_acc: 0.5000 top5_acc: 0.6000 loss_cls: 2.7104 loss: 2.7104 2022/10/09 09:56:48 - mmengine - INFO - Epoch(train) [20][20/2119] lr: 4.0000e-02 eta: 1 day, 3:37:56 time: 0.5313 data_time: 0.1676 memory: 11108 grad_norm: 2.7861 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6047 loss: 2.6047 2022/10/09 09:56:55 - mmengine - INFO - Epoch(train) [20][40/2119] lr: 4.0000e-02 eta: 1 day, 3:37:51 time: 0.3718 data_time: 0.0187 memory: 11108 grad_norm: 2.7856 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5875 loss: 2.5875 2022/10/09 09:57:02 - mmengine - INFO - Epoch(train) [20][60/2119] lr: 4.0000e-02 eta: 1 day, 3:37:44 time: 0.3627 data_time: 0.0204 memory: 11108 grad_norm: 2.8276 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5407 loss: 2.5407 2022/10/09 09:57:09 - mmengine - INFO - Epoch(train) [20][80/2119] lr: 4.0000e-02 eta: 1 day, 3:37:37 time: 0.3572 data_time: 0.0229 memory: 11108 grad_norm: 2.8769 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6460 loss: 2.6460 2022/10/09 09:57:17 - mmengine - INFO - Epoch(train) [20][100/2119] lr: 4.0000e-02 eta: 1 day, 3:37:31 time: 0.3709 data_time: 0.0202 memory: 11108 grad_norm: 2.8182 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4631 loss: 2.4631 2022/10/09 09:57:24 - mmengine - INFO - Epoch(train) [20][120/2119] lr: 4.0000e-02 eta: 1 day, 3:37:24 time: 0.3547 data_time: 0.0208 memory: 11108 grad_norm: 2.8845 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5767 loss: 2.5767 2022/10/09 09:57:31 - mmengine - INFO - Epoch(train) [20][140/2119] lr: 4.0000e-02 eta: 1 day, 3:37:16 time: 0.3586 data_time: 0.0184 memory: 11108 grad_norm: 2.8386 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8675 loss: 2.8675 2022/10/09 09:57:38 - mmengine - INFO - Epoch(train) [20][160/2119] lr: 4.0000e-02 eta: 1 day, 3:37:10 time: 0.3631 data_time: 0.0227 memory: 11108 grad_norm: 2.8068 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.3980 loss: 2.3980 2022/10/09 09:57:45 - mmengine - INFO - Epoch(train) [20][180/2119] lr: 4.0000e-02 eta: 1 day, 3:37:03 time: 0.3582 data_time: 0.0274 memory: 11108 grad_norm: 2.8339 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6498 loss: 2.6498 2022/10/09 09:57:53 - mmengine - INFO - Epoch(train) [20][200/2119] lr: 4.0000e-02 eta: 1 day, 3:36:55 time: 0.3548 data_time: 0.0211 memory: 11108 grad_norm: 2.8302 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7585 loss: 2.7585 2022/10/09 09:58:00 - mmengine - INFO - Epoch(train) [20][220/2119] lr: 4.0000e-02 eta: 1 day, 3:36:48 time: 0.3600 data_time: 0.0223 memory: 11108 grad_norm: 2.8249 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6419 loss: 2.6419 2022/10/09 09:58:07 - mmengine - INFO - Epoch(train) [20][240/2119] lr: 4.0000e-02 eta: 1 day, 3:36:41 time: 0.3577 data_time: 0.0187 memory: 11108 grad_norm: 2.8536 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4850 loss: 2.4850 2022/10/09 09:58:14 - mmengine - INFO - Epoch(train) [20][260/2119] lr: 4.0000e-02 eta: 1 day, 3:36:35 time: 0.3651 data_time: 0.0196 memory: 11108 grad_norm: 2.8027 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5915 loss: 2.5915 2022/10/09 09:58:21 - mmengine - INFO - Epoch(train) [20][280/2119] lr: 4.0000e-02 eta: 1 day, 3:36:27 time: 0.3580 data_time: 0.0200 memory: 11108 grad_norm: 2.8204 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.3376 loss: 2.3376 2022/10/09 09:58:29 - mmengine - INFO - Epoch(train) [20][300/2119] lr: 4.0000e-02 eta: 1 day, 3:36:20 time: 0.3557 data_time: 0.0185 memory: 11108 grad_norm: 2.8179 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6383 loss: 2.6383 2022/10/09 09:58:36 - mmengine - INFO - Epoch(train) [20][320/2119] lr: 4.0000e-02 eta: 1 day, 3:36:14 time: 0.3708 data_time: 0.0237 memory: 11108 grad_norm: 2.8312 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6631 loss: 2.6631 2022/10/09 09:58:43 - mmengine - INFO - Epoch(train) [20][340/2119] lr: 4.0000e-02 eta: 1 day, 3:36:07 time: 0.3597 data_time: 0.0215 memory: 11108 grad_norm: 2.8223 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2380 loss: 2.2380 2022/10/09 09:58:50 - mmengine - INFO - Epoch(train) [20][360/2119] lr: 4.0000e-02 eta: 1 day, 3:36:00 time: 0.3568 data_time: 0.0213 memory: 11108 grad_norm: 2.8634 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5796 loss: 2.5796 2022/10/09 09:58:58 - mmengine - INFO - Epoch(train) [20][380/2119] lr: 4.0000e-02 eta: 1 day, 3:35:54 time: 0.3676 data_time: 0.0197 memory: 11108 grad_norm: 2.8497 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 2.5043 loss: 2.5043 2022/10/09 09:59:05 - mmengine - INFO - Epoch(train) [20][400/2119] lr: 4.0000e-02 eta: 1 day, 3:35:47 time: 0.3577 data_time: 0.0225 memory: 11108 grad_norm: 2.8944 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6149 loss: 2.6149 2022/10/09 09:59:12 - mmengine - INFO - Epoch(train) [20][420/2119] lr: 4.0000e-02 eta: 1 day, 3:35:39 time: 0.3566 data_time: 0.0186 memory: 11108 grad_norm: 2.8683 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6090 loss: 2.6090 2022/10/09 09:59:19 - mmengine - INFO - Epoch(train) [20][440/2119] lr: 4.0000e-02 eta: 1 day, 3:35:33 time: 0.3611 data_time: 0.0229 memory: 11108 grad_norm: 2.8604 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4192 loss: 2.4192 2022/10/09 09:59:26 - mmengine - INFO - Epoch(train) [20][460/2119] lr: 4.0000e-02 eta: 1 day, 3:35:25 time: 0.3568 data_time: 0.0218 memory: 11108 grad_norm: 2.8540 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5296 loss: 2.5296 2022/10/09 09:59:33 - mmengine - INFO - Epoch(train) [20][480/2119] lr: 4.0000e-02 eta: 1 day, 3:35:18 time: 0.3560 data_time: 0.0238 memory: 11108 grad_norm: 2.8615 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5194 loss: 2.5194 2022/10/09 09:59:41 - mmengine - INFO - Epoch(train) [20][500/2119] lr: 4.0000e-02 eta: 1 day, 3:35:11 time: 0.3596 data_time: 0.0155 memory: 11108 grad_norm: 2.8452 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6784 loss: 2.6784 2022/10/09 09:59:48 - mmengine - INFO - Epoch(train) [20][520/2119] lr: 4.0000e-02 eta: 1 day, 3:35:04 time: 0.3598 data_time: 0.0264 memory: 11108 grad_norm: 2.8173 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6304 loss: 2.6304 2022/10/09 09:59:55 - mmengine - INFO - Epoch(train) [20][540/2119] lr: 4.0000e-02 eta: 1 day, 3:34:58 time: 0.3688 data_time: 0.0202 memory: 11108 grad_norm: 2.8291 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7594 loss: 2.7594 2022/10/09 10:00:02 - mmengine - INFO - Epoch(train) [20][560/2119] lr: 4.0000e-02 eta: 1 day, 3:34:50 time: 0.3557 data_time: 0.0206 memory: 11108 grad_norm: 2.8906 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4791 loss: 2.4791 2022/10/09 10:00:10 - mmengine - INFO - Epoch(train) [20][580/2119] lr: 4.0000e-02 eta: 1 day, 3:34:44 time: 0.3612 data_time: 0.0203 memory: 11108 grad_norm: 2.8440 top1_acc: 0.1875 top5_acc: 0.8125 loss_cls: 2.6591 loss: 2.6591 2022/10/09 10:00:17 - mmengine - INFO - Epoch(train) [20][600/2119] lr: 4.0000e-02 eta: 1 day, 3:34:37 time: 0.3593 data_time: 0.0195 memory: 11108 grad_norm: 2.8723 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3909 loss: 2.3909 2022/10/09 10:00:24 - mmengine - INFO - Epoch(train) [20][620/2119] lr: 4.0000e-02 eta: 1 day, 3:34:30 time: 0.3600 data_time: 0.0191 memory: 11108 grad_norm: 2.8344 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.2790 loss: 2.2790 2022/10/09 10:00:41 - mmengine - INFO - Epoch(train) [20][640/2119] lr: 4.0000e-02 eta: 1 day, 3:35:27 time: 0.8326 data_time: 0.0195 memory: 11108 grad_norm: 2.8825 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7655 loss: 2.7655 2022/10/09 10:00:48 - mmengine - INFO - Epoch(train) [20][660/2119] lr: 4.0000e-02 eta: 1 day, 3:35:21 time: 0.3695 data_time: 0.0284 memory: 11108 grad_norm: 2.8710 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6257 loss: 2.6257 2022/10/09 10:00:56 - mmengine - INFO - Epoch(train) [20][680/2119] lr: 4.0000e-02 eta: 1 day, 3:35:21 time: 0.4098 data_time: 0.0258 memory: 11108 grad_norm: 2.8838 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5340 loss: 2.5340 2022/10/09 10:01:03 - mmengine - INFO - Epoch(train) [20][700/2119] lr: 4.0000e-02 eta: 1 day, 3:35:14 time: 0.3623 data_time: 0.0185 memory: 11108 grad_norm: 2.8510 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5008 loss: 2.5008 2022/10/09 10:01:11 - mmengine - INFO - Epoch(train) [20][720/2119] lr: 4.0000e-02 eta: 1 day, 3:35:08 time: 0.3656 data_time: 0.0222 memory: 11108 grad_norm: 2.8922 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4956 loss: 2.4956 2022/10/09 10:01:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 10:01:20 - mmengine - INFO - Epoch(train) [20][740/2119] lr: 4.0000e-02 eta: 1 day, 3:35:15 time: 0.4622 data_time: 0.0360 memory: 11108 grad_norm: 2.9167 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6126 loss: 2.6126 2022/10/09 10:01:27 - mmengine - INFO - Epoch(train) [20][760/2119] lr: 4.0000e-02 eta: 1 day, 3:35:09 time: 0.3684 data_time: 0.0273 memory: 11108 grad_norm: 2.8697 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6714 loss: 2.6714 2022/10/09 10:01:38 - mmengine - INFO - Epoch(train) [20][780/2119] lr: 4.0000e-02 eta: 1 day, 3:35:25 time: 0.5344 data_time: 0.0230 memory: 11108 grad_norm: 2.8296 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6808 loss: 2.6808 2022/10/09 10:01:52 - mmengine - INFO - Epoch(train) [20][800/2119] lr: 4.0000e-02 eta: 1 day, 3:36:06 time: 0.7119 data_time: 0.0274 memory: 11108 grad_norm: 2.8329 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6511 loss: 2.6511 2022/10/09 10:02:20 - mmengine - INFO - Epoch(train) [20][820/2119] lr: 4.0000e-02 eta: 1 day, 3:38:19 time: 1.3997 data_time: 0.0327 memory: 11108 grad_norm: 2.8469 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5523 loss: 2.5523 2022/10/09 10:02:31 - mmengine - INFO - Epoch(train) [20][840/2119] lr: 4.0000e-02 eta: 1 day, 3:38:37 time: 0.5493 data_time: 0.1177 memory: 11108 grad_norm: 2.8288 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7105 loss: 2.7105 2022/10/09 10:04:11 - mmengine - INFO - Epoch(train) [20][860/2119] lr: 4.0000e-02 eta: 1 day, 3:48:55 time: 5.0048 data_time: 0.0274 memory: 11108 grad_norm: 2.8025 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6530 loss: 2.6530 2022/10/09 10:04:19 - mmengine - INFO - Epoch(train) [20][880/2119] lr: 4.0000e-02 eta: 1 day, 3:48:49 time: 0.3687 data_time: 0.0267 memory: 11108 grad_norm: 2.8830 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7167 loss: 2.7167 2022/10/09 10:04:26 - mmengine - INFO - Epoch(train) [20][900/2119] lr: 4.0000e-02 eta: 1 day, 3:48:42 time: 0.3646 data_time: 0.0165 memory: 11108 grad_norm: 2.8351 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8366 loss: 2.8366 2022/10/09 10:04:33 - mmengine - INFO - Epoch(train) [20][920/2119] lr: 4.0000e-02 eta: 1 day, 3:48:34 time: 0.3557 data_time: 0.0222 memory: 11108 grad_norm: 2.8825 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6220 loss: 2.6220 2022/10/09 10:04:40 - mmengine - INFO - Epoch(train) [20][940/2119] lr: 4.0000e-02 eta: 1 day, 3:48:26 time: 0.3544 data_time: 0.0162 memory: 11108 grad_norm: 2.8356 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5974 loss: 2.5974 2022/10/09 10:04:48 - mmengine - INFO - Epoch(train) [20][960/2119] lr: 4.0000e-02 eta: 1 day, 3:48:19 time: 0.3655 data_time: 0.0205 memory: 11108 grad_norm: 2.8691 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6758 loss: 2.6758 2022/10/09 10:04:55 - mmengine - INFO - Epoch(train) [20][980/2119] lr: 4.0000e-02 eta: 1 day, 3:48:11 time: 0.3547 data_time: 0.0187 memory: 11108 grad_norm: 2.8082 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8058 loss: 2.8058 2022/10/09 10:05:02 - mmengine - INFO - Epoch(train) [20][1000/2119] lr: 4.0000e-02 eta: 1 day, 3:48:03 time: 0.3579 data_time: 0.0207 memory: 11108 grad_norm: 2.8570 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5275 loss: 2.5275 2022/10/09 10:05:09 - mmengine - INFO - Epoch(train) [20][1020/2119] lr: 4.0000e-02 eta: 1 day, 3:47:56 time: 0.3669 data_time: 0.0206 memory: 11108 grad_norm: 2.8713 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6002 loss: 2.6002 2022/10/09 10:05:16 - mmengine - INFO - Epoch(train) [20][1040/2119] lr: 4.0000e-02 eta: 1 day, 3:47:50 time: 0.3648 data_time: 0.0210 memory: 11108 grad_norm: 2.7579 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6166 loss: 2.6166 2022/10/09 10:05:24 - mmengine - INFO - Epoch(train) [20][1060/2119] lr: 4.0000e-02 eta: 1 day, 3:47:42 time: 0.3610 data_time: 0.0211 memory: 11108 grad_norm: 2.8536 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4824 loss: 2.4824 2022/10/09 10:05:38 - mmengine - INFO - Epoch(train) [20][1080/2119] lr: 4.0000e-02 eta: 1 day, 3:48:20 time: 0.6979 data_time: 0.0575 memory: 11108 grad_norm: 2.8811 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7420 loss: 2.7420 2022/10/09 10:05:45 - mmengine - INFO - Epoch(train) [20][1100/2119] lr: 4.0000e-02 eta: 1 day, 3:48:15 time: 0.3769 data_time: 0.0334 memory: 11108 grad_norm: 2.9052 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5107 loss: 2.5107 2022/10/09 10:05:52 - mmengine - INFO - Epoch(train) [20][1120/2119] lr: 4.0000e-02 eta: 1 day, 3:48:08 time: 0.3670 data_time: 0.0192 memory: 11108 grad_norm: 2.8258 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.8007 loss: 2.8007 2022/10/09 10:06:00 - mmengine - INFO - Epoch(train) [20][1140/2119] lr: 4.0000e-02 eta: 1 day, 3:48:03 time: 0.3793 data_time: 0.0238 memory: 11108 grad_norm: 2.8364 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.5846 loss: 2.5846 2022/10/09 10:06:07 - mmengine - INFO - Epoch(train) [20][1160/2119] lr: 4.0000e-02 eta: 1 day, 3:47:55 time: 0.3579 data_time: 0.0208 memory: 11108 grad_norm: 2.8360 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7227 loss: 2.7227 2022/10/09 10:06:14 - mmengine - INFO - Epoch(train) [20][1180/2119] lr: 4.0000e-02 eta: 1 day, 3:47:47 time: 0.3558 data_time: 0.0239 memory: 11108 grad_norm: 2.8804 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7034 loss: 2.7034 2022/10/09 10:06:21 - mmengine - INFO - Epoch(train) [20][1200/2119] lr: 4.0000e-02 eta: 1 day, 3:47:39 time: 0.3568 data_time: 0.0204 memory: 11108 grad_norm: 2.8459 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7281 loss: 2.7281 2022/10/09 10:06:29 - mmengine - INFO - Epoch(train) [20][1220/2119] lr: 4.0000e-02 eta: 1 day, 3:47:32 time: 0.3617 data_time: 0.0244 memory: 11108 grad_norm: 2.8398 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7632 loss: 2.7632 2022/10/09 10:06:36 - mmengine - INFO - Epoch(train) [20][1240/2119] lr: 4.0000e-02 eta: 1 day, 3:47:24 time: 0.3559 data_time: 0.0199 memory: 11108 grad_norm: 2.8218 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6845 loss: 2.6845 2022/10/09 10:06:43 - mmengine - INFO - Epoch(train) [20][1260/2119] lr: 4.0000e-02 eta: 1 day, 3:47:16 time: 0.3592 data_time: 0.0233 memory: 11108 grad_norm: 2.7971 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6905 loss: 2.6905 2022/10/09 10:06:50 - mmengine - INFO - Epoch(train) [20][1280/2119] lr: 4.0000e-02 eta: 1 day, 3:47:09 time: 0.3585 data_time: 0.0245 memory: 11108 grad_norm: 2.8515 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.5556 loss: 2.5556 2022/10/09 10:06:57 - mmengine - INFO - Epoch(train) [20][1300/2119] lr: 4.0000e-02 eta: 1 day, 3:47:01 time: 0.3588 data_time: 0.0220 memory: 11108 grad_norm: 2.8106 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7123 loss: 2.7123 2022/10/09 10:07:04 - mmengine - INFO - Epoch(train) [20][1320/2119] lr: 4.0000e-02 eta: 1 day, 3:46:53 time: 0.3552 data_time: 0.0195 memory: 11108 grad_norm: 2.7958 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7034 loss: 2.7034 2022/10/09 10:07:12 - mmengine - INFO - Epoch(train) [20][1340/2119] lr: 4.0000e-02 eta: 1 day, 3:46:45 time: 0.3593 data_time: 0.0204 memory: 11108 grad_norm: 2.8256 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6824 loss: 2.6824 2022/10/09 10:07:19 - mmengine - INFO - Epoch(train) [20][1360/2119] lr: 4.0000e-02 eta: 1 day, 3:46:39 time: 0.3697 data_time: 0.0304 memory: 11108 grad_norm: 2.8631 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6351 loss: 2.6351 2022/10/09 10:07:26 - mmengine - INFO - Epoch(train) [20][1380/2119] lr: 4.0000e-02 eta: 1 day, 3:46:31 time: 0.3559 data_time: 0.0201 memory: 11108 grad_norm: 2.8047 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5621 loss: 2.5621 2022/10/09 10:07:33 - mmengine - INFO - Epoch(train) [20][1400/2119] lr: 4.0000e-02 eta: 1 day, 3:46:23 time: 0.3581 data_time: 0.0195 memory: 11108 grad_norm: 2.8394 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8188 loss: 2.8188 2022/10/09 10:07:41 - mmengine - INFO - Epoch(train) [20][1420/2119] lr: 4.0000e-02 eta: 1 day, 3:46:16 time: 0.3602 data_time: 0.0214 memory: 11108 grad_norm: 2.8361 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4697 loss: 2.4697 2022/10/09 10:07:48 - mmengine - INFO - Epoch(train) [20][1440/2119] lr: 4.0000e-02 eta: 1 day, 3:46:09 time: 0.3629 data_time: 0.0169 memory: 11108 grad_norm: 2.8268 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5216 loss: 2.5216 2022/10/09 10:07:55 - mmengine - INFO - Epoch(train) [20][1460/2119] lr: 4.0000e-02 eta: 1 day, 3:46:01 time: 0.3571 data_time: 0.0214 memory: 11108 grad_norm: 2.8741 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6545 loss: 2.6545 2022/10/09 10:08:02 - mmengine - INFO - Epoch(train) [20][1480/2119] lr: 4.0000e-02 eta: 1 day, 3:45:53 time: 0.3606 data_time: 0.0254 memory: 11108 grad_norm: 2.8349 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9104 loss: 2.9104 2022/10/09 10:08:09 - mmengine - INFO - Epoch(train) [20][1500/2119] lr: 4.0000e-02 eta: 1 day, 3:45:46 time: 0.3593 data_time: 0.0243 memory: 11108 grad_norm: 2.9050 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5272 loss: 2.5272 2022/10/09 10:08:17 - mmengine - INFO - Epoch(train) [20][1520/2119] lr: 4.0000e-02 eta: 1 day, 3:45:38 time: 0.3600 data_time: 0.0199 memory: 11108 grad_norm: 2.8893 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.3681 loss: 2.3681 2022/10/09 10:08:24 - mmengine - INFO - Epoch(train) [20][1540/2119] lr: 4.0000e-02 eta: 1 day, 3:45:31 time: 0.3589 data_time: 0.0234 memory: 11108 grad_norm: 2.8600 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.5802 loss: 2.5802 2022/10/09 10:08:31 - mmengine - INFO - Epoch(train) [20][1560/2119] lr: 4.0000e-02 eta: 1 day, 3:45:23 time: 0.3626 data_time: 0.0256 memory: 11108 grad_norm: 2.8545 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8468 loss: 2.8468 2022/10/09 10:08:38 - mmengine - INFO - Epoch(train) [20][1580/2119] lr: 4.0000e-02 eta: 1 day, 3:45:16 time: 0.3610 data_time: 0.0196 memory: 11108 grad_norm: 2.8293 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5574 loss: 2.5574 2022/10/09 10:08:46 - mmengine - INFO - Epoch(train) [20][1600/2119] lr: 4.0000e-02 eta: 1 day, 3:45:15 time: 0.4104 data_time: 0.0289 memory: 11108 grad_norm: 2.8664 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.6884 loss: 2.6884 2022/10/09 10:08:58 - mmengine - INFO - Epoch(train) [20][1620/2119] lr: 4.0000e-02 eta: 1 day, 3:45:36 time: 0.5722 data_time: 0.0396 memory: 11108 grad_norm: 2.8729 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5529 loss: 2.5529 2022/10/09 10:09:05 - mmengine - INFO - Epoch(train) [20][1640/2119] lr: 4.0000e-02 eta: 1 day, 3:45:28 time: 0.3583 data_time: 0.0200 memory: 11108 grad_norm: 2.8294 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6955 loss: 2.6955 2022/10/09 10:09:12 - mmengine - INFO - Epoch(train) [20][1660/2119] lr: 4.0000e-02 eta: 1 day, 3:45:21 time: 0.3612 data_time: 0.0205 memory: 11108 grad_norm: 2.8627 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5823 loss: 2.5823 2022/10/09 10:09:20 - mmengine - INFO - Epoch(train) [20][1680/2119] lr: 4.0000e-02 eta: 1 day, 3:45:14 time: 0.3676 data_time: 0.0239 memory: 11108 grad_norm: 2.8667 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.3836 loss: 2.3836 2022/10/09 10:09:29 - mmengine - INFO - Epoch(train) [20][1700/2119] lr: 4.0000e-02 eta: 1 day, 3:45:24 time: 0.4915 data_time: 0.0217 memory: 11108 grad_norm: 2.8327 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6785 loss: 2.6785 2022/10/09 10:09:37 - mmengine - INFO - Epoch(train) [20][1720/2119] lr: 4.0000e-02 eta: 1 day, 3:45:16 time: 0.3551 data_time: 0.0219 memory: 11108 grad_norm: 2.8274 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5200 loss: 2.5200 2022/10/09 10:09:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 10:09:44 - mmengine - INFO - Epoch(train) [20][1740/2119] lr: 4.0000e-02 eta: 1 day, 3:45:08 time: 0.3577 data_time: 0.0213 memory: 11108 grad_norm: 2.8691 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6777 loss: 2.6777 2022/10/09 10:09:51 - mmengine - INFO - Epoch(train) [20][1760/2119] lr: 4.0000e-02 eta: 1 day, 3:45:01 time: 0.3632 data_time: 0.0202 memory: 11108 grad_norm: 2.8397 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6525 loss: 2.6525 2022/10/09 10:09:58 - mmengine - INFO - Epoch(train) [20][1780/2119] lr: 4.0000e-02 eta: 1 day, 3:44:53 time: 0.3614 data_time: 0.0213 memory: 11108 grad_norm: 2.9216 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6900 loss: 2.6900 2022/10/09 10:10:05 - mmengine - INFO - Epoch(train) [20][1800/2119] lr: 4.0000e-02 eta: 1 day, 3:44:45 time: 0.3574 data_time: 0.0243 memory: 11108 grad_norm: 2.8740 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7665 loss: 2.7665 2022/10/09 10:10:13 - mmengine - INFO - Epoch(train) [20][1820/2119] lr: 4.0000e-02 eta: 1 day, 3:44:38 time: 0.3591 data_time: 0.0216 memory: 11108 grad_norm: 2.8505 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6217 loss: 2.6217 2022/10/09 10:10:20 - mmengine - INFO - Epoch(train) [20][1840/2119] lr: 4.0000e-02 eta: 1 day, 3:44:31 time: 0.3661 data_time: 0.0227 memory: 11108 grad_norm: 2.8141 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5683 loss: 2.5683 2022/10/09 10:10:27 - mmengine - INFO - Epoch(train) [20][1860/2119] lr: 4.0000e-02 eta: 1 day, 3:44:23 time: 0.3598 data_time: 0.0210 memory: 11108 grad_norm: 2.8443 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.8100 loss: 2.8100 2022/10/09 10:10:34 - mmengine - INFO - Epoch(train) [20][1880/2119] lr: 4.0000e-02 eta: 1 day, 3:44:15 time: 0.3549 data_time: 0.0210 memory: 11108 grad_norm: 2.8451 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6873 loss: 2.6873 2022/10/09 10:10:41 - mmengine - INFO - Epoch(train) [20][1900/2119] lr: 4.0000e-02 eta: 1 day, 3:44:08 time: 0.3640 data_time: 0.0188 memory: 11108 grad_norm: 2.8585 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5600 loss: 2.5600 2022/10/09 10:10:49 - mmengine - INFO - Epoch(train) [20][1920/2119] lr: 4.0000e-02 eta: 1 day, 3:44:01 time: 0.3593 data_time: 0.0221 memory: 11108 grad_norm: 2.8715 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5396 loss: 2.5396 2022/10/09 10:10:56 - mmengine - INFO - Epoch(train) [20][1940/2119] lr: 4.0000e-02 eta: 1 day, 3:43:53 time: 0.3590 data_time: 0.0218 memory: 11108 grad_norm: 2.8188 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4632 loss: 2.4632 2022/10/09 10:11:03 - mmengine - INFO - Epoch(train) [20][1960/2119] lr: 4.0000e-02 eta: 1 day, 3:43:46 time: 0.3634 data_time: 0.0204 memory: 11108 grad_norm: 2.8316 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6034 loss: 2.6034 2022/10/09 10:11:10 - mmengine - INFO - Epoch(train) [20][1980/2119] lr: 4.0000e-02 eta: 1 day, 3:43:38 time: 0.3566 data_time: 0.0264 memory: 11108 grad_norm: 2.8383 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7381 loss: 2.7381 2022/10/09 10:11:18 - mmengine - INFO - Epoch(train) [20][2000/2119] lr: 4.0000e-02 eta: 1 day, 3:43:32 time: 0.3753 data_time: 0.0188 memory: 11108 grad_norm: 2.8477 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5104 loss: 2.5104 2022/10/09 10:11:25 - mmengine - INFO - Epoch(train) [20][2020/2119] lr: 4.0000e-02 eta: 1 day, 3:43:24 time: 0.3563 data_time: 0.0191 memory: 11108 grad_norm: 2.8484 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5559 loss: 2.5559 2022/10/09 10:11:32 - mmengine - INFO - Epoch(train) [20][2040/2119] lr: 4.0000e-02 eta: 1 day, 3:43:17 time: 0.3587 data_time: 0.0182 memory: 11108 grad_norm: 2.8490 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5450 loss: 2.5450 2022/10/09 10:11:39 - mmengine - INFO - Epoch(train) [20][2060/2119] lr: 4.0000e-02 eta: 1 day, 3:43:10 time: 0.3663 data_time: 0.0210 memory: 11108 grad_norm: 2.7979 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4270 loss: 2.4270 2022/10/09 10:11:46 - mmengine - INFO - Epoch(train) [20][2080/2119] lr: 4.0000e-02 eta: 1 day, 3:43:02 time: 0.3567 data_time: 0.0188 memory: 11108 grad_norm: 2.7647 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4017 loss: 2.4017 2022/10/09 10:11:54 - mmengine - INFO - Epoch(train) [20][2100/2119] lr: 4.0000e-02 eta: 1 day, 3:42:54 time: 0.3577 data_time: 0.0222 memory: 11108 grad_norm: 2.8153 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5496 loss: 2.5496 2022/10/09 10:12:00 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 10:12:00 - mmengine - INFO - Epoch(train) [20][2119/2119] lr: 4.0000e-02 eta: 1 day, 3:42:54 time: 0.3500 data_time: 0.0316 memory: 11108 grad_norm: 2.8900 top1_acc: 0.4000 top5_acc: 0.9000 loss_cls: 2.7169 loss: 2.7169 2022/10/09 10:12:00 - mmengine - INFO - Saving checkpoint at 20 epochs 2022/10/09 10:12:21 - mmengine - INFO - Epoch(val) [20][20/137] eta: 0:00:42 time: 0.3601 data_time: 0.2443 memory: 1961 2022/10/09 10:12:26 - mmengine - INFO - Epoch(val) [20][40/137] eta: 0:00:23 time: 0.2467 data_time: 0.1317 memory: 1961 2022/10/09 10:12:32 - mmengine - INFO - Epoch(val) [20][60/137] eta: 0:00:23 time: 0.3090 data_time: 0.1934 memory: 1961 2022/10/09 10:12:37 - mmengine - INFO - Epoch(val) [20][80/137] eta: 0:00:14 time: 0.2571 data_time: 0.1368 memory: 1961 2022/10/09 10:12:42 - mmengine - INFO - Epoch(val) [20][100/137] eta: 0:00:09 time: 0.2597 data_time: 0.1476 memory: 1961 2022/10/09 10:12:47 - mmengine - INFO - Epoch(val) [20][120/137] eta: 0:00:03 time: 0.2274 data_time: 0.1131 memory: 1961 2022/10/09 10:12:55 - mmengine - INFO - Epoch(val) [20][137/137] acc/top1: 0.4533 acc/top5: 0.7000 acc/mean1: 0.4533 2022/10/09 10:12:55 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb.py/best_acc/top1_epoch_15.pth is removed 2022/10/09 10:13:00 - mmengine - INFO - The best checkpoint with 0.4533 acc/top1 at 20 epoch is saved to best_acc/top1_epoch_20.pth. 2022/10/09 10:13:09 - mmengine - INFO - Epoch(train) [21][20/2119] lr: 4.0000e-02 eta: 1 day, 3:42:08 time: 0.4584 data_time: 0.1100 memory: 11108 grad_norm: 2.8171 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6485 loss: 2.6485 2022/10/09 10:13:17 - mmengine - INFO - Epoch(train) [21][40/2119] lr: 4.0000e-02 eta: 1 day, 3:42:02 time: 0.3747 data_time: 0.0244 memory: 11108 grad_norm: 2.8785 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4386 loss: 2.4386 2022/10/09 10:13:24 - mmengine - INFO - Epoch(train) [21][60/2119] lr: 4.0000e-02 eta: 1 day, 3:41:54 time: 0.3535 data_time: 0.0229 memory: 11108 grad_norm: 2.8483 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5987 loss: 2.5987 2022/10/09 10:13:31 - mmengine - INFO - Epoch(train) [21][80/2119] lr: 4.0000e-02 eta: 1 day, 3:41:47 time: 0.3645 data_time: 0.0198 memory: 11108 grad_norm: 2.8834 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8428 loss: 2.8428 2022/10/09 10:13:38 - mmengine - INFO - Epoch(train) [21][100/2119] lr: 4.0000e-02 eta: 1 day, 3:41:40 time: 0.3617 data_time: 0.0182 memory: 11108 grad_norm: 2.8680 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5872 loss: 2.5872 2022/10/09 10:13:46 - mmengine - INFO - Epoch(train) [21][120/2119] lr: 4.0000e-02 eta: 1 day, 3:41:32 time: 0.3609 data_time: 0.0220 memory: 11108 grad_norm: 2.8455 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.4217 loss: 2.4217 2022/10/09 10:13:53 - mmengine - INFO - Epoch(train) [21][140/2119] lr: 4.0000e-02 eta: 1 day, 3:41:24 time: 0.3539 data_time: 0.0163 memory: 11108 grad_norm: 2.8326 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5376 loss: 2.5376 2022/10/09 10:14:00 - mmengine - INFO - Epoch(train) [21][160/2119] lr: 4.0000e-02 eta: 1 day, 3:41:16 time: 0.3577 data_time: 0.0246 memory: 11108 grad_norm: 2.8049 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5097 loss: 2.5097 2022/10/09 10:14:07 - mmengine - INFO - Epoch(train) [21][180/2119] lr: 4.0000e-02 eta: 1 day, 3:41:09 time: 0.3595 data_time: 0.0198 memory: 11108 grad_norm: 2.8433 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6724 loss: 2.6724 2022/10/09 10:14:14 - mmengine - INFO - Epoch(train) [21][200/2119] lr: 4.0000e-02 eta: 1 day, 3:41:01 time: 0.3567 data_time: 0.0207 memory: 11108 grad_norm: 2.8466 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5418 loss: 2.5418 2022/10/09 10:14:21 - mmengine - INFO - Epoch(train) [21][220/2119] lr: 4.0000e-02 eta: 1 day, 3:40:53 time: 0.3594 data_time: 0.0182 memory: 11108 grad_norm: 2.8908 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6311 loss: 2.6311 2022/10/09 10:14:29 - mmengine - INFO - Epoch(train) [21][240/2119] lr: 4.0000e-02 eta: 1 day, 3:40:45 time: 0.3566 data_time: 0.0196 memory: 11108 grad_norm: 2.8296 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6152 loss: 2.6152 2022/10/09 10:14:36 - mmengine - INFO - Epoch(train) [21][260/2119] lr: 4.0000e-02 eta: 1 day, 3:40:37 time: 0.3558 data_time: 0.0200 memory: 11108 grad_norm: 2.8361 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6035 loss: 2.6035 2022/10/09 10:14:43 - mmengine - INFO - Epoch(train) [21][280/2119] lr: 4.0000e-02 eta: 1 day, 3:40:30 time: 0.3622 data_time: 0.0218 memory: 11108 grad_norm: 2.7776 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5025 loss: 2.5025 2022/10/09 10:14:50 - mmengine - INFO - Epoch(train) [21][300/2119] lr: 4.0000e-02 eta: 1 day, 3:40:22 time: 0.3589 data_time: 0.0245 memory: 11108 grad_norm: 2.7930 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5311 loss: 2.5311 2022/10/09 10:14:58 - mmengine - INFO - Epoch(train) [21][320/2119] lr: 4.0000e-02 eta: 1 day, 3:40:16 time: 0.3700 data_time: 0.0229 memory: 11108 grad_norm: 2.8335 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5272 loss: 2.5272 2022/10/09 10:15:05 - mmengine - INFO - Epoch(train) [21][340/2119] lr: 4.0000e-02 eta: 1 day, 3:40:08 time: 0.3542 data_time: 0.0190 memory: 11108 grad_norm: 2.9008 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.4465 loss: 2.4465 2022/10/09 10:15:12 - mmengine - INFO - Epoch(train) [21][360/2119] lr: 4.0000e-02 eta: 1 day, 3:40:00 time: 0.3612 data_time: 0.0214 memory: 11108 grad_norm: 2.8310 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8365 loss: 2.8365 2022/10/09 10:15:19 - mmengine - INFO - Epoch(train) [21][380/2119] lr: 4.0000e-02 eta: 1 day, 3:39:53 time: 0.3611 data_time: 0.0198 memory: 11108 grad_norm: 2.8144 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6559 loss: 2.6559 2022/10/09 10:15:26 - mmengine - INFO - Epoch(train) [21][400/2119] lr: 4.0000e-02 eta: 1 day, 3:39:46 time: 0.3641 data_time: 0.0299 memory: 11108 grad_norm: 2.8481 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7136 loss: 2.7136 2022/10/09 10:15:34 - mmengine - INFO - Epoch(train) [21][420/2119] lr: 4.0000e-02 eta: 1 day, 3:39:38 time: 0.3586 data_time: 0.0205 memory: 11108 grad_norm: 2.8827 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6669 loss: 2.6669 2022/10/09 10:15:41 - mmengine - INFO - Epoch(train) [21][440/2119] lr: 4.0000e-02 eta: 1 day, 3:39:31 time: 0.3613 data_time: 0.0222 memory: 11108 grad_norm: 2.8776 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4415 loss: 2.4415 2022/10/09 10:15:48 - mmengine - INFO - Epoch(train) [21][460/2119] lr: 4.0000e-02 eta: 1 day, 3:39:24 time: 0.3621 data_time: 0.0290 memory: 11108 grad_norm: 2.9102 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7216 loss: 2.7216 2022/10/09 10:15:55 - mmengine - INFO - Epoch(train) [21][480/2119] lr: 4.0000e-02 eta: 1 day, 3:39:16 time: 0.3583 data_time: 0.0185 memory: 11108 grad_norm: 2.8913 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7399 loss: 2.7399 2022/10/09 10:16:02 - mmengine - INFO - Epoch(train) [21][500/2119] lr: 4.0000e-02 eta: 1 day, 3:39:08 time: 0.3577 data_time: 0.0170 memory: 11108 grad_norm: 2.8243 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5289 loss: 2.5289 2022/10/09 10:16:10 - mmengine - INFO - Epoch(train) [21][520/2119] lr: 4.0000e-02 eta: 1 day, 3:39:01 time: 0.3626 data_time: 0.0275 memory: 11108 grad_norm: 2.8177 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7234 loss: 2.7234 2022/10/09 10:16:17 - mmengine - INFO - Epoch(train) [21][540/2119] lr: 4.0000e-02 eta: 1 day, 3:38:54 time: 0.3601 data_time: 0.0186 memory: 11108 grad_norm: 2.7891 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5171 loss: 2.5171 2022/10/09 10:16:24 - mmengine - INFO - Epoch(train) [21][560/2119] lr: 4.0000e-02 eta: 1 day, 3:38:46 time: 0.3571 data_time: 0.0240 memory: 11108 grad_norm: 2.8516 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6258 loss: 2.6258 2022/10/09 10:16:31 - mmengine - INFO - Epoch(train) [21][580/2119] lr: 4.0000e-02 eta: 1 day, 3:38:39 time: 0.3631 data_time: 0.0193 memory: 11108 grad_norm: 2.8813 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6029 loss: 2.6029 2022/10/09 10:16:38 - mmengine - INFO - Epoch(train) [21][600/2119] lr: 4.0000e-02 eta: 1 day, 3:38:32 time: 0.3636 data_time: 0.0206 memory: 11108 grad_norm: 2.8457 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4630 loss: 2.4630 2022/10/09 10:16:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 10:16:46 - mmengine - INFO - Epoch(train) [21][620/2119] lr: 4.0000e-02 eta: 1 day, 3:38:23 time: 0.3527 data_time: 0.0176 memory: 11108 grad_norm: 2.8716 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9472 loss: 2.9472 2022/10/09 10:16:53 - mmengine - INFO - Epoch(train) [21][640/2119] lr: 4.0000e-02 eta: 1 day, 3:38:16 time: 0.3611 data_time: 0.0231 memory: 11108 grad_norm: 2.8554 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6867 loss: 2.6867 2022/10/09 10:18:40 - mmengine - INFO - Epoch(train) [21][660/2119] lr: 4.0000e-02 eta: 1 day, 3:48:47 time: 5.3580 data_time: 4.9056 memory: 11108 grad_norm: 2.8738 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7535 loss: 2.7535 2022/10/09 10:18:47 - mmengine - INFO - Epoch(train) [21][680/2119] lr: 4.0000e-02 eta: 1 day, 3:48:40 time: 0.3689 data_time: 0.0254 memory: 11108 grad_norm: 2.8077 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4722 loss: 2.4722 2022/10/09 10:18:54 - mmengine - INFO - Epoch(train) [21][700/2119] lr: 4.0000e-02 eta: 1 day, 3:48:32 time: 0.3555 data_time: 0.0173 memory: 11108 grad_norm: 2.9013 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5314 loss: 2.5314 2022/10/09 10:19:02 - mmengine - INFO - Epoch(train) [21][720/2119] lr: 4.0000e-02 eta: 1 day, 3:48:24 time: 0.3600 data_time: 0.0197 memory: 11108 grad_norm: 2.8509 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8950 loss: 2.8950 2022/10/09 10:19:09 - mmengine - INFO - Epoch(train) [21][740/2119] lr: 4.0000e-02 eta: 1 day, 3:48:16 time: 0.3594 data_time: 0.0203 memory: 11108 grad_norm: 2.8951 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6765 loss: 2.6765 2022/10/09 10:19:16 - mmengine - INFO - Epoch(train) [21][760/2119] lr: 4.0000e-02 eta: 1 day, 3:48:10 time: 0.3747 data_time: 0.0215 memory: 11108 grad_norm: 2.8317 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6277 loss: 2.6277 2022/10/09 10:19:23 - mmengine - INFO - Epoch(train) [21][780/2119] lr: 4.0000e-02 eta: 1 day, 3:48:01 time: 0.3543 data_time: 0.0199 memory: 11108 grad_norm: 2.8649 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9366 loss: 2.9366 2022/10/09 10:19:31 - mmengine - INFO - Epoch(train) [21][800/2119] lr: 4.0000e-02 eta: 1 day, 3:47:55 time: 0.3694 data_time: 0.0188 memory: 11108 grad_norm: 2.9043 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6374 loss: 2.6374 2022/10/09 10:19:38 - mmengine - INFO - Epoch(train) [21][820/2119] lr: 4.0000e-02 eta: 1 day, 3:47:46 time: 0.3572 data_time: 0.0192 memory: 11108 grad_norm: 2.8404 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6355 loss: 2.6355 2022/10/09 10:19:45 - mmengine - INFO - Epoch(train) [21][840/2119] lr: 4.0000e-02 eta: 1 day, 3:47:38 time: 0.3558 data_time: 0.0247 memory: 11108 grad_norm: 2.8242 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.5028 loss: 2.5028 2022/10/09 10:19:52 - mmengine - INFO - Epoch(train) [21][860/2119] lr: 4.0000e-02 eta: 1 day, 3:47:31 time: 0.3641 data_time: 0.0217 memory: 11108 grad_norm: 2.8621 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6350 loss: 2.6350 2022/10/09 10:20:00 - mmengine - INFO - Epoch(train) [21][880/2119] lr: 4.0000e-02 eta: 1 day, 3:47:24 time: 0.3684 data_time: 0.0229 memory: 11108 grad_norm: 2.8677 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8232 loss: 2.8232 2022/10/09 10:20:07 - mmengine - INFO - Epoch(train) [21][900/2119] lr: 4.0000e-02 eta: 1 day, 3:47:17 time: 0.3692 data_time: 0.0263 memory: 11108 grad_norm: 2.8822 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5513 loss: 2.5513 2022/10/09 10:20:14 - mmengine - INFO - Epoch(train) [21][920/2119] lr: 4.0000e-02 eta: 1 day, 3:47:09 time: 0.3596 data_time: 0.0181 memory: 11108 grad_norm: 2.8911 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5109 loss: 2.5109 2022/10/09 10:20:22 - mmengine - INFO - Epoch(train) [21][940/2119] lr: 4.0000e-02 eta: 1 day, 3:47:02 time: 0.3632 data_time: 0.0200 memory: 11108 grad_norm: 2.8324 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6377 loss: 2.6377 2022/10/09 10:20:29 - mmengine - INFO - Epoch(train) [21][960/2119] lr: 4.0000e-02 eta: 1 day, 3:46:55 time: 0.3641 data_time: 0.0220 memory: 11108 grad_norm: 2.8771 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7007 loss: 2.7007 2022/10/09 10:20:36 - mmengine - INFO - Epoch(train) [21][980/2119] lr: 4.0000e-02 eta: 1 day, 3:46:46 time: 0.3577 data_time: 0.0233 memory: 11108 grad_norm: 2.8502 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4937 loss: 2.4937 2022/10/09 10:20:43 - mmengine - INFO - Epoch(train) [21][1000/2119] lr: 4.0000e-02 eta: 1 day, 3:46:39 time: 0.3658 data_time: 0.0204 memory: 11108 grad_norm: 2.8301 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.5758 loss: 2.5758 2022/10/09 10:20:50 - mmengine - INFO - Epoch(train) [21][1020/2119] lr: 4.0000e-02 eta: 1 day, 3:46:31 time: 0.3585 data_time: 0.0190 memory: 11108 grad_norm: 2.8606 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4750 loss: 2.4750 2022/10/09 10:20:58 - mmengine - INFO - Epoch(train) [21][1040/2119] lr: 4.0000e-02 eta: 1 day, 3:46:23 time: 0.3561 data_time: 0.0187 memory: 11108 grad_norm: 2.9330 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5328 loss: 2.5328 2022/10/09 10:21:05 - mmengine - INFO - Epoch(train) [21][1060/2119] lr: 4.0000e-02 eta: 1 day, 3:46:15 time: 0.3620 data_time: 0.0226 memory: 11108 grad_norm: 2.8744 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5181 loss: 2.5181 2022/10/09 10:21:12 - mmengine - INFO - Epoch(train) [21][1080/2119] lr: 4.0000e-02 eta: 1 day, 3:46:08 time: 0.3599 data_time: 0.0169 memory: 11108 grad_norm: 2.8631 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6791 loss: 2.6791 2022/10/09 10:21:19 - mmengine - INFO - Epoch(train) [21][1100/2119] lr: 4.0000e-02 eta: 1 day, 3:46:00 time: 0.3586 data_time: 0.0198 memory: 11108 grad_norm: 2.9168 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5349 loss: 2.5349 2022/10/09 10:21:26 - mmengine - INFO - Epoch(train) [21][1120/2119] lr: 4.0000e-02 eta: 1 day, 3:45:51 time: 0.3572 data_time: 0.0195 memory: 11108 grad_norm: 2.9124 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6993 loss: 2.6993 2022/10/09 10:21:34 - mmengine - INFO - Epoch(train) [21][1140/2119] lr: 4.0000e-02 eta: 1 day, 3:45:43 time: 0.3586 data_time: 0.0185 memory: 11108 grad_norm: 2.8699 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.8051 loss: 2.8051 2022/10/09 10:21:41 - mmengine - INFO - Epoch(train) [21][1160/2119] lr: 4.0000e-02 eta: 1 day, 3:45:35 time: 0.3565 data_time: 0.0176 memory: 11108 grad_norm: 2.8460 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7503 loss: 2.7503 2022/10/09 10:21:48 - mmengine - INFO - Epoch(train) [21][1180/2119] lr: 4.0000e-02 eta: 1 day, 3:45:27 time: 0.3615 data_time: 0.0242 memory: 11108 grad_norm: 2.8624 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6539 loss: 2.6539 2022/10/09 10:21:55 - mmengine - INFO - Epoch(train) [21][1200/2119] lr: 4.0000e-02 eta: 1 day, 3:45:19 time: 0.3551 data_time: 0.0210 memory: 11108 grad_norm: 2.8560 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5600 loss: 2.5600 2022/10/09 10:22:02 - mmengine - INFO - Epoch(train) [21][1220/2119] lr: 4.0000e-02 eta: 1 day, 3:45:11 time: 0.3559 data_time: 0.0196 memory: 11108 grad_norm: 2.8782 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6886 loss: 2.6886 2022/10/09 10:22:09 - mmengine - INFO - Epoch(train) [21][1240/2119] lr: 4.0000e-02 eta: 1 day, 3:45:03 time: 0.3582 data_time: 0.0184 memory: 11108 grad_norm: 2.8324 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7021 loss: 2.7021 2022/10/09 10:22:16 - mmengine - INFO - Epoch(train) [21][1260/2119] lr: 4.0000e-02 eta: 1 day, 3:44:54 time: 0.3562 data_time: 0.0210 memory: 11108 grad_norm: 2.8742 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5707 loss: 2.5707 2022/10/09 10:22:24 - mmengine - INFO - Epoch(train) [21][1280/2119] lr: 4.0000e-02 eta: 1 day, 3:44:46 time: 0.3581 data_time: 0.0198 memory: 11108 grad_norm: 2.8130 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7871 loss: 2.7871 2022/10/09 10:22:31 - mmengine - INFO - Epoch(train) [21][1300/2119] lr: 4.0000e-02 eta: 1 day, 3:44:38 time: 0.3573 data_time: 0.0176 memory: 11108 grad_norm: 2.8685 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5545 loss: 2.5545 2022/10/09 10:22:38 - mmengine - INFO - Epoch(train) [21][1320/2119] lr: 4.0000e-02 eta: 1 day, 3:44:30 time: 0.3592 data_time: 0.0218 memory: 11108 grad_norm: 2.8410 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5064 loss: 2.5064 2022/10/09 10:22:45 - mmengine - INFO - Epoch(train) [21][1340/2119] lr: 4.0000e-02 eta: 1 day, 3:44:22 time: 0.3568 data_time: 0.0224 memory: 11108 grad_norm: 2.8623 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6027 loss: 2.6027 2022/10/09 10:22:52 - mmengine - INFO - Epoch(train) [21][1360/2119] lr: 4.0000e-02 eta: 1 day, 3:44:14 time: 0.3555 data_time: 0.0201 memory: 11108 grad_norm: 2.8550 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0299 loss: 3.0299 2022/10/09 10:22:59 - mmengine - INFO - Epoch(train) [21][1380/2119] lr: 4.0000e-02 eta: 1 day, 3:44:05 time: 0.3529 data_time: 0.0217 memory: 11108 grad_norm: 2.8673 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.7697 loss: 2.7697 2022/10/09 10:23:06 - mmengine - INFO - Epoch(train) [21][1400/2119] lr: 4.0000e-02 eta: 1 day, 3:43:57 time: 0.3604 data_time: 0.0211 memory: 11108 grad_norm: 2.8672 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5727 loss: 2.5727 2022/10/09 10:23:14 - mmengine - INFO - Epoch(train) [21][1420/2119] lr: 4.0000e-02 eta: 1 day, 3:43:49 time: 0.3570 data_time: 0.0207 memory: 11108 grad_norm: 2.8397 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 2.6629 loss: 2.6629 2022/10/09 10:23:21 - mmengine - INFO - Epoch(train) [21][1440/2119] lr: 4.0000e-02 eta: 1 day, 3:43:41 time: 0.3631 data_time: 0.0241 memory: 11108 grad_norm: 2.8462 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7882 loss: 2.7882 2022/10/09 10:23:28 - mmengine - INFO - Epoch(train) [21][1460/2119] lr: 4.0000e-02 eta: 1 day, 3:43:33 time: 0.3583 data_time: 0.0183 memory: 11108 grad_norm: 2.8977 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8469 loss: 2.8469 2022/10/09 10:23:35 - mmengine - INFO - Epoch(train) [21][1480/2119] lr: 4.0000e-02 eta: 1 day, 3:43:25 time: 0.3590 data_time: 0.0215 memory: 11108 grad_norm: 2.8586 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7695 loss: 2.7695 2022/10/09 10:23:42 - mmengine - INFO - Epoch(train) [21][1500/2119] lr: 4.0000e-02 eta: 1 day, 3:43:18 time: 0.3588 data_time: 0.0205 memory: 11108 grad_norm: 2.8129 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6494 loss: 2.6494 2022/10/09 10:23:49 - mmengine - INFO - Epoch(train) [21][1520/2119] lr: 4.0000e-02 eta: 1 day, 3:43:09 time: 0.3554 data_time: 0.0168 memory: 11108 grad_norm: 2.8187 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.4414 loss: 2.4414 2022/10/09 10:23:57 - mmengine - INFO - Epoch(train) [21][1540/2119] lr: 4.0000e-02 eta: 1 day, 3:43:02 time: 0.3658 data_time: 0.0182 memory: 11108 grad_norm: 2.8709 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8904 loss: 2.8904 2022/10/09 10:24:04 - mmengine - INFO - Epoch(train) [21][1560/2119] lr: 4.0000e-02 eta: 1 day, 3:42:54 time: 0.3587 data_time: 0.0195 memory: 11108 grad_norm: 2.8932 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7496 loss: 2.7496 2022/10/09 10:24:11 - mmengine - INFO - Epoch(train) [21][1580/2119] lr: 4.0000e-02 eta: 1 day, 3:42:46 time: 0.3570 data_time: 0.0193 memory: 11108 grad_norm: 2.8982 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4831 loss: 2.4831 2022/10/09 10:24:18 - mmengine - INFO - Epoch(train) [21][1600/2119] lr: 4.0000e-02 eta: 1 day, 3:42:38 time: 0.3587 data_time: 0.0221 memory: 11108 grad_norm: 2.8012 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.3788 loss: 2.3788 2022/10/09 10:24:25 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 10:24:25 - mmengine - INFO - Epoch(train) [21][1620/2119] lr: 4.0000e-02 eta: 1 day, 3:42:29 time: 0.3536 data_time: 0.0217 memory: 11108 grad_norm: 2.8070 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5740 loss: 2.5740 2022/10/09 10:24:33 - mmengine - INFO - Epoch(train) [21][1640/2119] lr: 4.0000e-02 eta: 1 day, 3:42:22 time: 0.3625 data_time: 0.0176 memory: 11108 grad_norm: 2.8662 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6384 loss: 2.6384 2022/10/09 10:24:40 - mmengine - INFO - Epoch(train) [21][1660/2119] lr: 4.0000e-02 eta: 1 day, 3:42:13 time: 0.3561 data_time: 0.0276 memory: 11108 grad_norm: 2.8179 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5900 loss: 2.5900 2022/10/09 10:24:47 - mmengine - INFO - Epoch(train) [21][1680/2119] lr: 4.0000e-02 eta: 1 day, 3:42:06 time: 0.3628 data_time: 0.0176 memory: 11108 grad_norm: 2.8453 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6934 loss: 2.6934 2022/10/09 10:24:54 - mmengine - INFO - Epoch(train) [21][1700/2119] lr: 4.0000e-02 eta: 1 day, 3:41:58 time: 0.3611 data_time: 0.0210 memory: 11108 grad_norm: 2.8534 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7302 loss: 2.7302 2022/10/09 10:25:01 - mmengine - INFO - Epoch(train) [21][1720/2119] lr: 4.0000e-02 eta: 1 day, 3:41:50 time: 0.3567 data_time: 0.0198 memory: 11108 grad_norm: 2.8650 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.4611 loss: 2.4611 2022/10/09 10:25:09 - mmengine - INFO - Epoch(train) [21][1740/2119] lr: 4.0000e-02 eta: 1 day, 3:41:42 time: 0.3609 data_time: 0.0226 memory: 11108 grad_norm: 2.8840 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9848 loss: 2.9848 2022/10/09 10:25:16 - mmengine - INFO - Epoch(train) [21][1760/2119] lr: 4.0000e-02 eta: 1 day, 3:41:34 time: 0.3551 data_time: 0.0187 memory: 11108 grad_norm: 2.8093 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5023 loss: 2.5023 2022/10/09 10:25:23 - mmengine - INFO - Epoch(train) [21][1780/2119] lr: 4.0000e-02 eta: 1 day, 3:41:27 time: 0.3632 data_time: 0.0234 memory: 11108 grad_norm: 2.8313 top1_acc: 0.2500 top5_acc: 0.8125 loss_cls: 2.6421 loss: 2.6421 2022/10/09 10:25:30 - mmengine - INFO - Epoch(train) [21][1800/2119] lr: 4.0000e-02 eta: 1 day, 3:41:19 time: 0.3630 data_time: 0.0181 memory: 11108 grad_norm: 2.8635 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5820 loss: 2.5820 2022/10/09 10:25:37 - mmengine - INFO - Epoch(train) [21][1820/2119] lr: 4.0000e-02 eta: 1 day, 3:41:11 time: 0.3541 data_time: 0.0258 memory: 11108 grad_norm: 2.8123 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8232 loss: 2.8232 2022/10/09 10:25:44 - mmengine - INFO - Epoch(train) [21][1840/2119] lr: 4.0000e-02 eta: 1 day, 3:41:02 time: 0.3560 data_time: 0.0174 memory: 11108 grad_norm: 2.8417 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8889 loss: 2.8889 2022/10/09 10:25:52 - mmengine - INFO - Epoch(train) [21][1860/2119] lr: 4.0000e-02 eta: 1 day, 3:40:54 time: 0.3594 data_time: 0.0192 memory: 11108 grad_norm: 2.8584 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5742 loss: 2.5742 2022/10/09 10:25:59 - mmengine - INFO - Epoch(train) [21][1880/2119] lr: 4.0000e-02 eta: 1 day, 3:40:46 time: 0.3569 data_time: 0.0211 memory: 11108 grad_norm: 2.8204 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6090 loss: 2.6090 2022/10/09 10:26:06 - mmengine - INFO - Epoch(train) [21][1900/2119] lr: 4.0000e-02 eta: 1 day, 3:40:38 time: 0.3559 data_time: 0.0202 memory: 11108 grad_norm: 2.8315 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6732 loss: 2.6732 2022/10/09 10:26:13 - mmengine - INFO - Epoch(train) [21][1920/2119] lr: 4.0000e-02 eta: 1 day, 3:40:30 time: 0.3612 data_time: 0.0153 memory: 11108 grad_norm: 2.9045 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6169 loss: 2.6169 2022/10/09 10:26:20 - mmengine - INFO - Epoch(train) [21][1940/2119] lr: 4.0000e-02 eta: 1 day, 3:40:22 time: 0.3594 data_time: 0.0224 memory: 11108 grad_norm: 2.8441 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6814 loss: 2.6814 2022/10/09 10:26:27 - mmengine - INFO - Epoch(train) [21][1960/2119] lr: 4.0000e-02 eta: 1 day, 3:40:14 time: 0.3583 data_time: 0.0201 memory: 11108 grad_norm: 2.8191 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6405 loss: 2.6405 2022/10/09 10:26:35 - mmengine - INFO - Epoch(train) [21][1980/2119] lr: 4.0000e-02 eta: 1 day, 3:40:06 time: 0.3570 data_time: 0.0210 memory: 11108 grad_norm: 2.8428 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5099 loss: 2.5099 2022/10/09 10:26:42 - mmengine - INFO - Epoch(train) [21][2000/2119] lr: 4.0000e-02 eta: 1 day, 3:39:58 time: 0.3571 data_time: 0.0199 memory: 11108 grad_norm: 2.9268 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8691 loss: 2.8691 2022/10/09 10:26:49 - mmengine - INFO - Epoch(train) [21][2020/2119] lr: 4.0000e-02 eta: 1 day, 3:39:51 time: 0.3625 data_time: 0.0206 memory: 11108 grad_norm: 2.8554 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5655 loss: 2.5655 2022/10/09 10:26:56 - mmengine - INFO - Epoch(train) [21][2040/2119] lr: 4.0000e-02 eta: 1 day, 3:39:42 time: 0.3560 data_time: 0.0196 memory: 11108 grad_norm: 2.8050 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7009 loss: 2.7009 2022/10/09 10:27:03 - mmengine - INFO - Epoch(train) [21][2060/2119] lr: 4.0000e-02 eta: 1 day, 3:39:35 time: 0.3630 data_time: 0.0208 memory: 11108 grad_norm: 2.8449 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8576 loss: 2.8576 2022/10/09 10:27:10 - mmengine - INFO - Epoch(train) [21][2080/2119] lr: 4.0000e-02 eta: 1 day, 3:39:27 time: 0.3582 data_time: 0.0202 memory: 11108 grad_norm: 2.8108 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8534 loss: 2.8534 2022/10/09 10:27:18 - mmengine - INFO - Epoch(train) [21][2100/2119] lr: 4.0000e-02 eta: 1 day, 3:39:19 time: 0.3594 data_time: 0.0266 memory: 11108 grad_norm: 2.8809 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6952 loss: 2.6952 2022/10/09 10:27:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 10:27:24 - mmengine - INFO - Epoch(train) [21][2119/2119] lr: 4.0000e-02 eta: 1 day, 3:39:19 time: 0.3359 data_time: 0.0182 memory: 11108 grad_norm: 2.8654 top1_acc: 0.2000 top5_acc: 0.4000 loss_cls: 2.6059 loss: 2.6059 2022/10/09 10:27:34 - mmengine - INFO - Epoch(train) [22][20/2119] lr: 4.0000e-02 eta: 1 day, 3:38:40 time: 0.5076 data_time: 0.1075 memory: 11108 grad_norm: 2.8082 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6541 loss: 2.6541 2022/10/09 10:27:42 - mmengine - INFO - Epoch(train) [22][40/2119] lr: 4.0000e-02 eta: 1 day, 3:38:33 time: 0.3695 data_time: 0.0213 memory: 11108 grad_norm: 2.8111 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8540 loss: 2.8540 2022/10/09 10:27:49 - mmengine - INFO - Epoch(train) [22][60/2119] lr: 4.0000e-02 eta: 1 day, 3:38:28 time: 0.3787 data_time: 0.0197 memory: 11108 grad_norm: 2.8809 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6560 loss: 2.6560 2022/10/09 10:27:56 - mmengine - INFO - Epoch(train) [22][80/2119] lr: 4.0000e-02 eta: 1 day, 3:38:19 time: 0.3560 data_time: 0.0223 memory: 11108 grad_norm: 2.8735 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6541 loss: 2.6541 2022/10/09 10:28:04 - mmengine - INFO - Epoch(train) [22][100/2119] lr: 4.0000e-02 eta: 1 day, 3:38:11 time: 0.3571 data_time: 0.0179 memory: 11108 grad_norm: 2.8480 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6885 loss: 2.6885 2022/10/09 10:28:11 - mmengine - INFO - Epoch(train) [22][120/2119] lr: 4.0000e-02 eta: 1 day, 3:38:03 time: 0.3581 data_time: 0.0200 memory: 11108 grad_norm: 2.8567 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6461 loss: 2.6461 2022/10/09 10:28:18 - mmengine - INFO - Epoch(train) [22][140/2119] lr: 4.0000e-02 eta: 1 day, 3:37:55 time: 0.3574 data_time: 0.0180 memory: 11108 grad_norm: 2.8820 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6557 loss: 2.6557 2022/10/09 10:28:25 - mmengine - INFO - Epoch(train) [22][160/2119] lr: 4.0000e-02 eta: 1 day, 3:37:47 time: 0.3584 data_time: 0.0252 memory: 11108 grad_norm: 2.8554 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.5907 loss: 2.5907 2022/10/09 10:28:32 - mmengine - INFO - Epoch(train) [22][180/2119] lr: 4.0000e-02 eta: 1 day, 3:37:40 time: 0.3607 data_time: 0.0201 memory: 11108 grad_norm: 2.8509 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6826 loss: 2.6826 2022/10/09 10:28:39 - mmengine - INFO - Epoch(train) [22][200/2119] lr: 4.0000e-02 eta: 1 day, 3:37:31 time: 0.3568 data_time: 0.0202 memory: 11108 grad_norm: 2.8652 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6714 loss: 2.6714 2022/10/09 10:28:46 - mmengine - INFO - Epoch(train) [22][220/2119] lr: 4.0000e-02 eta: 1 day, 3:37:23 time: 0.3571 data_time: 0.0161 memory: 11108 grad_norm: 2.7963 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.4730 loss: 2.4730 2022/10/09 10:28:54 - mmengine - INFO - Epoch(train) [22][240/2119] lr: 4.0000e-02 eta: 1 day, 3:37:15 time: 0.3571 data_time: 0.0199 memory: 11108 grad_norm: 2.8289 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.7658 loss: 2.7658 2022/10/09 10:29:01 - mmengine - INFO - Epoch(train) [22][260/2119] lr: 4.0000e-02 eta: 1 day, 3:37:07 time: 0.3601 data_time: 0.0191 memory: 11108 grad_norm: 2.8683 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5998 loss: 2.5998 2022/10/09 10:29:08 - mmengine - INFO - Epoch(train) [22][280/2119] lr: 4.0000e-02 eta: 1 day, 3:36:59 time: 0.3584 data_time: 0.0181 memory: 11108 grad_norm: 2.8287 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6015 loss: 2.6015 2022/10/09 10:29:15 - mmengine - INFO - Epoch(train) [22][300/2119] lr: 4.0000e-02 eta: 1 day, 3:36:51 time: 0.3570 data_time: 0.0198 memory: 11108 grad_norm: 2.8610 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6752 loss: 2.6752 2022/10/09 10:29:22 - mmengine - INFO - Epoch(train) [22][320/2119] lr: 4.0000e-02 eta: 1 day, 3:36:43 time: 0.3582 data_time: 0.0213 memory: 11108 grad_norm: 2.8518 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7122 loss: 2.7122 2022/10/09 10:29:30 - mmengine - INFO - Epoch(train) [22][340/2119] lr: 4.0000e-02 eta: 1 day, 3:36:35 time: 0.3597 data_time: 0.0217 memory: 11108 grad_norm: 2.8932 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6162 loss: 2.6162 2022/10/09 10:29:37 - mmengine - INFO - Epoch(train) [22][360/2119] lr: 4.0000e-02 eta: 1 day, 3:36:27 time: 0.3525 data_time: 0.0223 memory: 11108 grad_norm: 2.8906 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8861 loss: 2.8861 2022/10/09 10:29:44 - mmengine - INFO - Epoch(train) [22][380/2119] lr: 4.0000e-02 eta: 1 day, 3:36:18 time: 0.3545 data_time: 0.0181 memory: 11108 grad_norm: 2.8858 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7355 loss: 2.7355 2022/10/09 10:29:51 - mmengine - INFO - Epoch(train) [22][400/2119] lr: 4.0000e-02 eta: 1 day, 3:36:11 time: 0.3630 data_time: 0.0203 memory: 11108 grad_norm: 2.8900 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7332 loss: 2.7332 2022/10/09 10:29:58 - mmengine - INFO - Epoch(train) [22][420/2119] lr: 4.0000e-02 eta: 1 day, 3:36:03 time: 0.3598 data_time: 0.0200 memory: 11108 grad_norm: 2.8658 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6681 loss: 2.6681 2022/10/09 10:30:05 - mmengine - INFO - Epoch(train) [22][440/2119] lr: 4.0000e-02 eta: 1 day, 3:35:55 time: 0.3588 data_time: 0.0217 memory: 11108 grad_norm: 2.8914 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6039 loss: 2.6039 2022/10/09 10:30:12 - mmengine - INFO - Epoch(train) [22][460/2119] lr: 4.0000e-02 eta: 1 day, 3:35:47 time: 0.3584 data_time: 0.0233 memory: 11108 grad_norm: 2.8870 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5761 loss: 2.5761 2022/10/09 10:30:20 - mmengine - INFO - Epoch(train) [22][480/2119] lr: 4.0000e-02 eta: 1 day, 3:35:39 time: 0.3587 data_time: 0.0218 memory: 11108 grad_norm: 2.8857 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8728 loss: 2.8728 2022/10/09 10:30:27 - mmengine - INFO - Epoch(train) [22][500/2119] lr: 4.0000e-02 eta: 1 day, 3:35:31 time: 0.3598 data_time: 0.0169 memory: 11108 grad_norm: 2.8796 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7389 loss: 2.7389 2022/10/09 10:30:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 10:30:34 - mmengine - INFO - Epoch(train) [22][520/2119] lr: 4.0000e-02 eta: 1 day, 3:35:24 time: 0.3611 data_time: 0.0194 memory: 11108 grad_norm: 2.8649 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4830 loss: 2.4830 2022/10/09 10:30:41 - mmengine - INFO - Epoch(train) [22][540/2119] lr: 4.0000e-02 eta: 1 day, 3:35:16 time: 0.3601 data_time: 0.0293 memory: 11108 grad_norm: 2.8619 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6614 loss: 2.6614 2022/10/09 10:30:48 - mmengine - INFO - Epoch(train) [22][560/2119] lr: 4.0000e-02 eta: 1 day, 3:35:08 time: 0.3602 data_time: 0.0195 memory: 11108 grad_norm: 2.8825 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5049 loss: 2.5049 2022/10/09 10:30:56 - mmengine - INFO - Epoch(train) [22][580/2119] lr: 4.0000e-02 eta: 1 day, 3:35:00 time: 0.3541 data_time: 0.0177 memory: 11108 grad_norm: 2.8018 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.5385 loss: 2.5385 2022/10/09 10:31:03 - mmengine - INFO - Epoch(train) [22][600/2119] lr: 4.0000e-02 eta: 1 day, 3:34:52 time: 0.3569 data_time: 0.0192 memory: 11108 grad_norm: 2.8508 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6884 loss: 2.6884 2022/10/09 10:31:10 - mmengine - INFO - Epoch(train) [22][620/2119] lr: 4.0000e-02 eta: 1 day, 3:34:44 time: 0.3640 data_time: 0.0202 memory: 11108 grad_norm: 2.9143 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7048 loss: 2.7048 2022/10/09 10:31:17 - mmengine - INFO - Epoch(train) [22][640/2119] lr: 4.0000e-02 eta: 1 day, 3:34:36 time: 0.3557 data_time: 0.0252 memory: 11108 grad_norm: 2.8200 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7874 loss: 2.7874 2022/10/09 10:31:24 - mmengine - INFO - Epoch(train) [22][660/2119] lr: 4.0000e-02 eta: 1 day, 3:34:28 time: 0.3571 data_time: 0.0196 memory: 11108 grad_norm: 2.8692 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.8091 loss: 2.8091 2022/10/09 10:31:31 - mmengine - INFO - Epoch(train) [22][680/2119] lr: 4.0000e-02 eta: 1 day, 3:34:20 time: 0.3565 data_time: 0.0217 memory: 11108 grad_norm: 2.8470 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6424 loss: 2.6424 2022/10/09 10:31:38 - mmengine - INFO - Epoch(train) [22][700/2119] lr: 4.0000e-02 eta: 1 day, 3:34:12 time: 0.3569 data_time: 0.0190 memory: 11108 grad_norm: 2.8342 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.9307 loss: 2.9307 2022/10/09 10:31:46 - mmengine - INFO - Epoch(train) [22][720/2119] lr: 4.0000e-02 eta: 1 day, 3:34:03 time: 0.3555 data_time: 0.0202 memory: 11108 grad_norm: 2.8453 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8670 loss: 2.8670 2022/10/09 10:31:53 - mmengine - INFO - Epoch(train) [22][740/2119] lr: 4.0000e-02 eta: 1 day, 3:33:56 time: 0.3632 data_time: 0.0207 memory: 11108 grad_norm: 2.8573 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.3796 loss: 2.3796 2022/10/09 10:32:00 - mmengine - INFO - Epoch(train) [22][760/2119] lr: 4.0000e-02 eta: 1 day, 3:33:48 time: 0.3567 data_time: 0.0180 memory: 11108 grad_norm: 2.8430 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5104 loss: 2.5104 2022/10/09 10:32:07 - mmengine - INFO - Epoch(train) [22][780/2119] lr: 4.0000e-02 eta: 1 day, 3:33:40 time: 0.3577 data_time: 0.0211 memory: 11108 grad_norm: 2.8654 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.4154 loss: 2.4154 2022/10/09 10:32:14 - mmengine - INFO - Epoch(train) [22][800/2119] lr: 4.0000e-02 eta: 1 day, 3:33:32 time: 0.3565 data_time: 0.0209 memory: 11108 grad_norm: 2.8755 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6754 loss: 2.6754 2022/10/09 10:32:22 - mmengine - INFO - Epoch(train) [22][820/2119] lr: 4.0000e-02 eta: 1 day, 3:33:24 time: 0.3609 data_time: 0.0189 memory: 11108 grad_norm: 2.8854 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6356 loss: 2.6356 2022/10/09 10:32:29 - mmengine - INFO - Epoch(train) [22][840/2119] lr: 4.0000e-02 eta: 1 day, 3:33:16 time: 0.3574 data_time: 0.0246 memory: 11108 grad_norm: 2.8844 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5609 loss: 2.5609 2022/10/09 10:32:36 - mmengine - INFO - Epoch(train) [22][860/2119] lr: 4.0000e-02 eta: 1 day, 3:33:08 time: 0.3575 data_time: 0.0199 memory: 11108 grad_norm: 2.8810 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6786 loss: 2.6786 2022/10/09 10:32:43 - mmengine - INFO - Epoch(train) [22][880/2119] lr: 4.0000e-02 eta: 1 day, 3:33:00 time: 0.3566 data_time: 0.0243 memory: 11108 grad_norm: 2.8638 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.4837 loss: 2.4837 2022/10/09 10:32:50 - mmengine - INFO - Epoch(train) [22][900/2119] lr: 4.0000e-02 eta: 1 day, 3:32:52 time: 0.3598 data_time: 0.0231 memory: 11108 grad_norm: 2.8589 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6154 loss: 2.6154 2022/10/09 10:32:57 - mmengine - INFO - Epoch(train) [22][920/2119] lr: 4.0000e-02 eta: 1 day, 3:32:44 time: 0.3597 data_time: 0.0177 memory: 11108 grad_norm: 2.8698 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5757 loss: 2.5757 2022/10/09 10:33:05 - mmengine - INFO - Epoch(train) [22][940/2119] lr: 4.0000e-02 eta: 1 day, 3:32:36 time: 0.3581 data_time: 0.0182 memory: 11108 grad_norm: 2.8676 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8141 loss: 2.8141 2022/10/09 10:33:12 - mmengine - INFO - Epoch(train) [22][960/2119] lr: 4.0000e-02 eta: 1 day, 3:32:28 time: 0.3571 data_time: 0.0182 memory: 11108 grad_norm: 2.8658 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5391 loss: 2.5391 2022/10/09 10:33:19 - mmengine - INFO - Epoch(train) [22][980/2119] lr: 4.0000e-02 eta: 1 day, 3:32:20 time: 0.3588 data_time: 0.0197 memory: 11108 grad_norm: 2.8523 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6365 loss: 2.6365 2022/10/09 10:33:26 - mmengine - INFO - Epoch(train) [22][1000/2119] lr: 4.0000e-02 eta: 1 day, 3:32:12 time: 0.3610 data_time: 0.0210 memory: 11108 grad_norm: 2.8568 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.2520 loss: 2.2520 2022/10/09 10:33:33 - mmengine - INFO - Epoch(train) [22][1020/2119] lr: 4.0000e-02 eta: 1 day, 3:32:04 time: 0.3568 data_time: 0.0225 memory: 11108 grad_norm: 2.8835 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5473 loss: 2.5473 2022/10/09 10:33:40 - mmengine - INFO - Epoch(train) [22][1040/2119] lr: 4.0000e-02 eta: 1 day, 3:31:57 time: 0.3602 data_time: 0.0246 memory: 11108 grad_norm: 2.8589 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.4554 loss: 2.4554 2022/10/09 10:33:48 - mmengine - INFO - Epoch(train) [22][1060/2119] lr: 4.0000e-02 eta: 1 day, 3:31:49 time: 0.3582 data_time: 0.0177 memory: 11108 grad_norm: 2.8694 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6384 loss: 2.6384 2022/10/09 10:33:55 - mmengine - INFO - Epoch(train) [22][1080/2119] lr: 4.0000e-02 eta: 1 day, 3:31:40 time: 0.3555 data_time: 0.0181 memory: 11108 grad_norm: 2.9199 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5921 loss: 2.5921 2022/10/09 10:34:02 - mmengine - INFO - Epoch(train) [22][1100/2119] lr: 4.0000e-02 eta: 1 day, 3:31:33 time: 0.3677 data_time: 0.0170 memory: 11108 grad_norm: 2.8860 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8306 loss: 2.8306 2022/10/09 10:34:09 - mmengine - INFO - Epoch(train) [22][1120/2119] lr: 4.0000e-02 eta: 1 day, 3:31:25 time: 0.3570 data_time: 0.0202 memory: 11108 grad_norm: 2.8901 top1_acc: 0.3125 top5_acc: 0.8750 loss_cls: 2.3785 loss: 2.3785 2022/10/09 10:34:16 - mmengine - INFO - Epoch(train) [22][1140/2119] lr: 4.0000e-02 eta: 1 day, 3:31:17 time: 0.3535 data_time: 0.0183 memory: 11108 grad_norm: 2.9151 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8049 loss: 2.8049 2022/10/09 10:34:23 - mmengine - INFO - Epoch(train) [22][1160/2119] lr: 4.0000e-02 eta: 1 day, 3:31:09 time: 0.3618 data_time: 0.0192 memory: 11108 grad_norm: 2.8156 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8334 loss: 2.8334 2022/10/09 10:34:31 - mmengine - INFO - Epoch(train) [22][1180/2119] lr: 4.0000e-02 eta: 1 day, 3:31:01 time: 0.3552 data_time: 0.0197 memory: 11108 grad_norm: 2.9215 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6925 loss: 2.6925 2022/10/09 10:34:38 - mmengine - INFO - Epoch(train) [22][1200/2119] lr: 4.0000e-02 eta: 1 day, 3:30:53 time: 0.3609 data_time: 0.0254 memory: 11108 grad_norm: 2.9349 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5960 loss: 2.5960 2022/10/09 10:34:45 - mmengine - INFO - Epoch(train) [22][1220/2119] lr: 4.0000e-02 eta: 1 day, 3:30:45 time: 0.3556 data_time: 0.0196 memory: 11108 grad_norm: 2.8984 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7685 loss: 2.7685 2022/10/09 10:34:52 - mmengine - INFO - Epoch(train) [22][1240/2119] lr: 4.0000e-02 eta: 1 day, 3:30:37 time: 0.3557 data_time: 0.0211 memory: 11108 grad_norm: 2.8502 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6261 loss: 2.6261 2022/10/09 10:34:59 - mmengine - INFO - Epoch(train) [22][1260/2119] lr: 4.0000e-02 eta: 1 day, 3:30:29 time: 0.3631 data_time: 0.0185 memory: 11108 grad_norm: 2.8718 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5662 loss: 2.5662 2022/10/09 10:35:06 - mmengine - INFO - Epoch(train) [22][1280/2119] lr: 4.0000e-02 eta: 1 day, 3:30:21 time: 0.3569 data_time: 0.0274 memory: 11108 grad_norm: 2.8189 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5814 loss: 2.5814 2022/10/09 10:35:14 - mmengine - INFO - Epoch(train) [22][1300/2119] lr: 4.0000e-02 eta: 1 day, 3:30:14 time: 0.3617 data_time: 0.0165 memory: 11108 grad_norm: 2.8135 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.7054 loss: 2.7054 2022/10/09 10:35:21 - mmengine - INFO - Epoch(train) [22][1320/2119] lr: 4.0000e-02 eta: 1 day, 3:30:06 time: 0.3608 data_time: 0.0243 memory: 11108 grad_norm: 2.8672 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5498 loss: 2.5498 2022/10/09 10:35:28 - mmengine - INFO - Epoch(train) [22][1340/2119] lr: 4.0000e-02 eta: 1 day, 3:29:58 time: 0.3542 data_time: 0.0188 memory: 11108 grad_norm: 2.8165 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7763 loss: 2.7763 2022/10/09 10:35:35 - mmengine - INFO - Epoch(train) [22][1360/2119] lr: 4.0000e-02 eta: 1 day, 3:29:49 time: 0.3544 data_time: 0.0211 memory: 11108 grad_norm: 2.8363 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7415 loss: 2.7415 2022/10/09 10:35:42 - mmengine - INFO - Epoch(train) [22][1380/2119] lr: 4.0000e-02 eta: 1 day, 3:29:41 time: 0.3591 data_time: 0.0225 memory: 11108 grad_norm: 2.8389 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6786 loss: 2.6786 2022/10/09 10:35:49 - mmengine - INFO - Epoch(train) [22][1400/2119] lr: 4.0000e-02 eta: 1 day, 3:29:34 time: 0.3602 data_time: 0.0199 memory: 11108 grad_norm: 2.8438 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8621 loss: 2.8621 2022/10/09 10:35:57 - mmengine - INFO - Epoch(train) [22][1420/2119] lr: 4.0000e-02 eta: 1 day, 3:29:26 time: 0.3584 data_time: 0.0243 memory: 11108 grad_norm: 2.8191 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.3484 loss: 2.3484 2022/10/09 10:36:04 - mmengine - INFO - Epoch(train) [22][1440/2119] lr: 4.0000e-02 eta: 1 day, 3:29:18 time: 0.3586 data_time: 0.0212 memory: 11108 grad_norm: 2.9084 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7687 loss: 2.7687 2022/10/09 10:36:11 - mmengine - INFO - Epoch(train) [22][1460/2119] lr: 4.0000e-02 eta: 1 day, 3:29:10 time: 0.3575 data_time: 0.0226 memory: 11108 grad_norm: 2.8612 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6590 loss: 2.6590 2022/10/09 10:36:18 - mmengine - INFO - Epoch(train) [22][1480/2119] lr: 4.0000e-02 eta: 1 day, 3:29:03 time: 0.3710 data_time: 0.0348 memory: 11108 grad_norm: 2.8651 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7758 loss: 2.7758 2022/10/09 10:36:26 - mmengine - INFO - Epoch(train) [22][1500/2119] lr: 4.0000e-02 eta: 1 day, 3:28:56 time: 0.3611 data_time: 0.0191 memory: 11108 grad_norm: 2.8388 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6983 loss: 2.6983 2022/10/09 10:36:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 10:36:33 - mmengine - INFO - Epoch(train) [22][1520/2119] lr: 4.0000e-02 eta: 1 day, 3:28:48 time: 0.3583 data_time: 0.0203 memory: 11108 grad_norm: 2.8719 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6968 loss: 2.6968 2022/10/09 10:36:40 - mmengine - INFO - Epoch(train) [22][1540/2119] lr: 4.0000e-02 eta: 1 day, 3:28:41 time: 0.3704 data_time: 0.0172 memory: 11108 grad_norm: 2.8724 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6418 loss: 2.6418 2022/10/09 10:36:47 - mmengine - INFO - Epoch(train) [22][1560/2119] lr: 4.0000e-02 eta: 1 day, 3:28:33 time: 0.3537 data_time: 0.0204 memory: 11108 grad_norm: 2.8417 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6662 loss: 2.6662 2022/10/09 10:36:54 - mmengine - INFO - Epoch(train) [22][1580/2119] lr: 4.0000e-02 eta: 1 day, 3:28:25 time: 0.3591 data_time: 0.0210 memory: 11108 grad_norm: 2.8188 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7883 loss: 2.7883 2022/10/09 10:37:02 - mmengine - INFO - Epoch(train) [22][1600/2119] lr: 4.0000e-02 eta: 1 day, 3:28:18 time: 0.3652 data_time: 0.0221 memory: 11108 grad_norm: 2.8422 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6677 loss: 2.6677 2022/10/09 10:37:09 - mmengine - INFO - Epoch(train) [22][1620/2119] lr: 4.0000e-02 eta: 1 day, 3:28:10 time: 0.3593 data_time: 0.0212 memory: 11108 grad_norm: 2.8648 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5092 loss: 2.5092 2022/10/09 10:37:16 - mmengine - INFO - Epoch(train) [22][1640/2119] lr: 4.0000e-02 eta: 1 day, 3:28:02 time: 0.3553 data_time: 0.0227 memory: 11108 grad_norm: 2.8656 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7429 loss: 2.7429 2022/10/09 10:37:23 - mmengine - INFO - Epoch(train) [22][1660/2119] lr: 4.0000e-02 eta: 1 day, 3:27:54 time: 0.3581 data_time: 0.0177 memory: 11108 grad_norm: 2.9101 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6462 loss: 2.6462 2022/10/09 10:37:30 - mmengine - INFO - Epoch(train) [22][1680/2119] lr: 4.0000e-02 eta: 1 day, 3:27:46 time: 0.3609 data_time: 0.0187 memory: 11108 grad_norm: 2.8984 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8712 loss: 2.8712 2022/10/09 10:37:37 - mmengine - INFO - Epoch(train) [22][1700/2119] lr: 4.0000e-02 eta: 1 day, 3:27:38 time: 0.3544 data_time: 0.0192 memory: 11108 grad_norm: 2.8335 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.6066 loss: 2.6066 2022/10/09 10:37:45 - mmengine - INFO - Epoch(train) [22][1720/2119] lr: 4.0000e-02 eta: 1 day, 3:27:31 time: 0.3665 data_time: 0.0216 memory: 11108 grad_norm: 2.8949 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8536 loss: 2.8536 2022/10/09 10:37:52 - mmengine - INFO - Epoch(train) [22][1740/2119] lr: 4.0000e-02 eta: 1 day, 3:27:22 time: 0.3551 data_time: 0.0187 memory: 11108 grad_norm: 2.8820 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7364 loss: 2.7364 2022/10/09 10:37:59 - mmengine - INFO - Epoch(train) [22][1760/2119] lr: 4.0000e-02 eta: 1 day, 3:27:15 time: 0.3619 data_time: 0.0227 memory: 11108 grad_norm: 2.8024 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5981 loss: 2.5981 2022/10/09 10:38:06 - mmengine - INFO - Epoch(train) [22][1780/2119] lr: 4.0000e-02 eta: 1 day, 3:27:07 time: 0.3565 data_time: 0.0193 memory: 11108 grad_norm: 2.8231 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5334 loss: 2.5334 2022/10/09 10:38:14 - mmengine - INFO - Epoch(train) [22][1800/2119] lr: 4.0000e-02 eta: 1 day, 3:26:59 time: 0.3605 data_time: 0.0199 memory: 11108 grad_norm: 2.8804 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5068 loss: 2.5068 2022/10/09 10:38:21 - mmengine - INFO - Epoch(train) [22][1820/2119] lr: 4.0000e-02 eta: 1 day, 3:26:51 time: 0.3560 data_time: 0.0187 memory: 11108 grad_norm: 2.8566 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5957 loss: 2.5957 2022/10/09 10:38:28 - mmengine - INFO - Epoch(train) [22][1840/2119] lr: 4.0000e-02 eta: 1 day, 3:26:43 time: 0.3596 data_time: 0.0184 memory: 11108 grad_norm: 2.8740 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8469 loss: 2.8469 2022/10/09 10:38:35 - mmengine - INFO - Epoch(train) [22][1860/2119] lr: 4.0000e-02 eta: 1 day, 3:26:35 time: 0.3575 data_time: 0.0206 memory: 11108 grad_norm: 2.8676 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7707 loss: 2.7707 2022/10/09 10:38:42 - mmengine - INFO - Epoch(train) [22][1880/2119] lr: 4.0000e-02 eta: 1 day, 3:26:26 time: 0.3530 data_time: 0.0182 memory: 11108 grad_norm: 2.8819 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6959 loss: 2.6959 2022/10/09 10:38:49 - mmengine - INFO - Epoch(train) [22][1900/2119] lr: 4.0000e-02 eta: 1 day, 3:26:19 time: 0.3592 data_time: 0.0206 memory: 11108 grad_norm: 2.8357 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7180 loss: 2.7180 2022/10/09 10:38:56 - mmengine - INFO - Epoch(train) [22][1920/2119] lr: 4.0000e-02 eta: 1 day, 3:26:11 time: 0.3622 data_time: 0.0179 memory: 11108 grad_norm: 2.8215 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5886 loss: 2.5886 2022/10/09 10:39:04 - mmengine - INFO - Epoch(train) [22][1940/2119] lr: 4.0000e-02 eta: 1 day, 3:26:03 time: 0.3543 data_time: 0.0210 memory: 11108 grad_norm: 2.8804 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7148 loss: 2.7148 2022/10/09 10:39:11 - mmengine - INFO - Epoch(train) [22][1960/2119] lr: 4.0000e-02 eta: 1 day, 3:25:56 time: 0.3668 data_time: 0.0243 memory: 11108 grad_norm: 2.8783 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5864 loss: 2.5864 2022/10/09 10:39:18 - mmengine - INFO - Epoch(train) [22][1980/2119] lr: 4.0000e-02 eta: 1 day, 3:25:48 time: 0.3558 data_time: 0.0189 memory: 11108 grad_norm: 2.8692 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7723 loss: 2.7723 2022/10/09 10:39:25 - mmengine - INFO - Epoch(train) [22][2000/2119] lr: 4.0000e-02 eta: 1 day, 3:25:40 time: 0.3599 data_time: 0.0258 memory: 11108 grad_norm: 2.8700 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8806 loss: 2.8806 2022/10/09 10:39:32 - mmengine - INFO - Epoch(train) [22][2020/2119] lr: 4.0000e-02 eta: 1 day, 3:25:32 time: 0.3600 data_time: 0.0218 memory: 11108 grad_norm: 2.8220 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5709 loss: 2.5709 2022/10/09 10:39:40 - mmengine - INFO - Epoch(train) [22][2040/2119] lr: 4.0000e-02 eta: 1 day, 3:25:24 time: 0.3570 data_time: 0.0181 memory: 11108 grad_norm: 2.8731 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6327 loss: 2.6327 2022/10/09 10:39:47 - mmengine - INFO - Epoch(train) [22][2060/2119] lr: 4.0000e-02 eta: 1 day, 3:25:16 time: 0.3550 data_time: 0.0193 memory: 11108 grad_norm: 2.8265 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5540 loss: 2.5540 2022/10/09 10:39:54 - mmengine - INFO - Epoch(train) [22][2080/2119] lr: 4.0000e-02 eta: 1 day, 3:25:08 time: 0.3638 data_time: 0.0209 memory: 11108 grad_norm: 2.8578 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6848 loss: 2.6848 2022/10/09 10:40:01 - mmengine - INFO - Epoch(train) [22][2100/2119] lr: 4.0000e-02 eta: 1 day, 3:25:00 time: 0.3553 data_time: 0.0186 memory: 11108 grad_norm: 2.8408 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6368 loss: 2.6368 2022/10/09 10:40:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 10:40:08 - mmengine - INFO - Epoch(train) [22][2119/2119] lr: 4.0000e-02 eta: 1 day, 3:25:00 time: 0.3422 data_time: 0.0205 memory: 11108 grad_norm: 2.8924 top1_acc: 0.6000 top5_acc: 0.7000 loss_cls: 2.5873 loss: 2.5873 2022/10/09 10:40:18 - mmengine - INFO - Epoch(train) [23][20/2119] lr: 4.0000e-02 eta: 1 day, 3:24:23 time: 0.5092 data_time: 0.1269 memory: 11108 grad_norm: 2.7491 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5308 loss: 2.5308 2022/10/09 10:40:25 - mmengine - INFO - Epoch(train) [23][40/2119] lr: 4.0000e-02 eta: 1 day, 3:24:16 time: 0.3683 data_time: 0.0245 memory: 11108 grad_norm: 2.8112 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4403 loss: 2.4403 2022/10/09 10:40:32 - mmengine - INFO - Epoch(train) [23][60/2119] lr: 4.0000e-02 eta: 1 day, 3:24:08 time: 0.3576 data_time: 0.0198 memory: 11108 grad_norm: 2.8766 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6900 loss: 2.6900 2022/10/09 10:40:40 - mmengine - INFO - Epoch(train) [23][80/2119] lr: 4.0000e-02 eta: 1 day, 3:24:01 time: 0.3629 data_time: 0.0268 memory: 11108 grad_norm: 2.8683 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6566 loss: 2.6566 2022/10/09 10:40:47 - mmengine - INFO - Epoch(train) [23][100/2119] lr: 4.0000e-02 eta: 1 day, 3:23:52 time: 0.3570 data_time: 0.0200 memory: 11108 grad_norm: 2.8418 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7066 loss: 2.7066 2022/10/09 10:40:54 - mmengine - INFO - Epoch(train) [23][120/2119] lr: 4.0000e-02 eta: 1 day, 3:23:44 time: 0.3562 data_time: 0.0232 memory: 11108 grad_norm: 2.8333 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5485 loss: 2.5485 2022/10/09 10:41:01 - mmengine - INFO - Epoch(train) [23][140/2119] lr: 4.0000e-02 eta: 1 day, 3:23:36 time: 0.3558 data_time: 0.0221 memory: 11108 grad_norm: 2.8650 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6808 loss: 2.6808 2022/10/09 10:41:08 - mmengine - INFO - Epoch(train) [23][160/2119] lr: 4.0000e-02 eta: 1 day, 3:23:28 time: 0.3550 data_time: 0.0211 memory: 11108 grad_norm: 2.8823 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7407 loss: 2.7407 2022/10/09 10:41:15 - mmengine - INFO - Epoch(train) [23][180/2119] lr: 4.0000e-02 eta: 1 day, 3:23:20 time: 0.3584 data_time: 0.0206 memory: 11108 grad_norm: 2.8761 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4335 loss: 2.4335 2022/10/09 10:41:22 - mmengine - INFO - Epoch(train) [23][200/2119] lr: 4.0000e-02 eta: 1 day, 3:23:13 time: 0.3649 data_time: 0.0183 memory: 11108 grad_norm: 2.8722 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5783 loss: 2.5783 2022/10/09 10:41:30 - mmengine - INFO - Epoch(train) [23][220/2119] lr: 4.0000e-02 eta: 1 day, 3:23:05 time: 0.3578 data_time: 0.0179 memory: 11108 grad_norm: 2.8976 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5744 loss: 2.5744 2022/10/09 10:41:37 - mmengine - INFO - Epoch(train) [23][240/2119] lr: 4.0000e-02 eta: 1 day, 3:22:57 time: 0.3591 data_time: 0.0216 memory: 11108 grad_norm: 2.8434 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.4334 loss: 2.4334 2022/10/09 10:41:44 - mmengine - INFO - Epoch(train) [23][260/2119] lr: 4.0000e-02 eta: 1 day, 3:22:49 time: 0.3601 data_time: 0.0182 memory: 11108 grad_norm: 2.8380 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7525 loss: 2.7525 2022/10/09 10:41:51 - mmengine - INFO - Epoch(train) [23][280/2119] lr: 4.0000e-02 eta: 1 day, 3:22:41 time: 0.3574 data_time: 0.0240 memory: 11108 grad_norm: 2.8642 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4796 loss: 2.4796 2022/10/09 10:41:58 - mmengine - INFO - Epoch(train) [23][300/2119] lr: 4.0000e-02 eta: 1 day, 3:22:33 time: 0.3546 data_time: 0.0186 memory: 11108 grad_norm: 2.8839 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6707 loss: 2.6707 2022/10/09 10:42:05 - mmengine - INFO - Epoch(train) [23][320/2119] lr: 4.0000e-02 eta: 1 day, 3:22:25 time: 0.3598 data_time: 0.0190 memory: 11108 grad_norm: 2.9096 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5191 loss: 2.5191 2022/10/09 10:42:13 - mmengine - INFO - Epoch(train) [23][340/2119] lr: 4.0000e-02 eta: 1 day, 3:22:17 time: 0.3594 data_time: 0.0213 memory: 11108 grad_norm: 2.9099 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6862 loss: 2.6862 2022/10/09 10:42:20 - mmengine - INFO - Epoch(train) [23][360/2119] lr: 4.0000e-02 eta: 1 day, 3:22:10 time: 0.3611 data_time: 0.0225 memory: 11108 grad_norm: 2.8951 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6784 loss: 2.6784 2022/10/09 10:42:27 - mmengine - INFO - Epoch(train) [23][380/2119] lr: 4.0000e-02 eta: 1 day, 3:22:02 time: 0.3569 data_time: 0.0190 memory: 11108 grad_norm: 2.9255 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.4871 loss: 2.4871 2022/10/09 10:42:28 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 10:42:34 - mmengine - INFO - Epoch(train) [23][400/2119] lr: 4.0000e-02 eta: 1 day, 3:21:54 time: 0.3592 data_time: 0.0206 memory: 11108 grad_norm: 2.9274 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4738 loss: 2.4738 2022/10/09 10:42:41 - mmengine - INFO - Epoch(train) [23][420/2119] lr: 4.0000e-02 eta: 1 day, 3:21:47 time: 0.3635 data_time: 0.0242 memory: 11108 grad_norm: 2.8302 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6730 loss: 2.6730 2022/10/09 10:42:49 - mmengine - INFO - Epoch(train) [23][440/2119] lr: 4.0000e-02 eta: 1 day, 3:21:39 time: 0.3579 data_time: 0.0247 memory: 11108 grad_norm: 2.8448 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6726 loss: 2.6726 2022/10/09 10:42:56 - mmengine - INFO - Epoch(train) [23][460/2119] lr: 4.0000e-02 eta: 1 day, 3:21:31 time: 0.3608 data_time: 0.0214 memory: 11108 grad_norm: 2.8485 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.4197 loss: 2.4197 2022/10/09 10:43:03 - mmengine - INFO - Epoch(train) [23][480/2119] lr: 4.0000e-02 eta: 1 day, 3:21:23 time: 0.3596 data_time: 0.0203 memory: 11108 grad_norm: 2.9065 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6845 loss: 2.6845 2022/10/09 10:43:10 - mmengine - INFO - Epoch(train) [23][500/2119] lr: 4.0000e-02 eta: 1 day, 3:21:16 time: 0.3635 data_time: 0.0207 memory: 11108 grad_norm: 2.8808 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7709 loss: 2.7709 2022/10/09 10:43:17 - mmengine - INFO - Epoch(train) [23][520/2119] lr: 4.0000e-02 eta: 1 day, 3:21:08 time: 0.3567 data_time: 0.0238 memory: 11108 grad_norm: 2.8667 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5458 loss: 2.5458 2022/10/09 10:43:25 - mmengine - INFO - Epoch(train) [23][540/2119] lr: 4.0000e-02 eta: 1 day, 3:21:00 time: 0.3599 data_time: 0.0174 memory: 11108 grad_norm: 2.8828 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7966 loss: 2.7966 2022/10/09 10:43:32 - mmengine - INFO - Epoch(train) [23][560/2119] lr: 4.0000e-02 eta: 1 day, 3:20:52 time: 0.3593 data_time: 0.0209 memory: 11108 grad_norm: 2.9019 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7060 loss: 2.7060 2022/10/09 10:43:39 - mmengine - INFO - Epoch(train) [23][580/2119] lr: 4.0000e-02 eta: 1 day, 3:20:45 time: 0.3612 data_time: 0.0188 memory: 11108 grad_norm: 2.8754 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6228 loss: 2.6228 2022/10/09 10:43:46 - mmengine - INFO - Epoch(train) [23][600/2119] lr: 4.0000e-02 eta: 1 day, 3:20:37 time: 0.3564 data_time: 0.0200 memory: 11108 grad_norm: 2.8345 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5191 loss: 2.5191 2022/10/09 10:43:53 - mmengine - INFO - Epoch(train) [23][620/2119] lr: 4.0000e-02 eta: 1 day, 3:20:29 time: 0.3595 data_time: 0.0194 memory: 11108 grad_norm: 2.9272 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6787 loss: 2.6787 2022/10/09 10:44:01 - mmengine - INFO - Epoch(train) [23][640/2119] lr: 4.0000e-02 eta: 1 day, 3:20:21 time: 0.3589 data_time: 0.0204 memory: 11108 grad_norm: 2.8632 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6978 loss: 2.6978 2022/10/09 10:44:08 - mmengine - INFO - Epoch(train) [23][660/2119] lr: 4.0000e-02 eta: 1 day, 3:20:13 time: 0.3546 data_time: 0.0229 memory: 11108 grad_norm: 2.8500 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6811 loss: 2.6811 2022/10/09 10:44:15 - mmengine - INFO - Epoch(train) [23][680/2119] lr: 4.0000e-02 eta: 1 day, 3:20:05 time: 0.3599 data_time: 0.0189 memory: 11108 grad_norm: 2.8267 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6857 loss: 2.6857 2022/10/09 10:44:22 - mmengine - INFO - Epoch(train) [23][700/2119] lr: 4.0000e-02 eta: 1 day, 3:19:57 time: 0.3553 data_time: 0.0233 memory: 11108 grad_norm: 2.8940 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4574 loss: 2.4574 2022/10/09 10:44:29 - mmengine - INFO - Epoch(train) [23][720/2119] lr: 4.0000e-02 eta: 1 day, 3:19:49 time: 0.3558 data_time: 0.0210 memory: 11108 grad_norm: 2.8220 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.3080 loss: 2.3080 2022/10/09 10:44:36 - mmengine - INFO - Epoch(train) [23][740/2119] lr: 4.0000e-02 eta: 1 day, 3:19:41 time: 0.3573 data_time: 0.0176 memory: 11108 grad_norm: 2.8470 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5938 loss: 2.5938 2022/10/09 10:44:44 - mmengine - INFO - Epoch(train) [23][760/2119] lr: 4.0000e-02 eta: 1 day, 3:19:34 time: 0.3717 data_time: 0.0337 memory: 11108 grad_norm: 2.8888 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7174 loss: 2.7174 2022/10/09 10:44:51 - mmengine - INFO - Epoch(train) [23][780/2119] lr: 4.0000e-02 eta: 1 day, 3:19:27 time: 0.3593 data_time: 0.0189 memory: 11108 grad_norm: 2.8889 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8363 loss: 2.8363 2022/10/09 10:44:58 - mmengine - INFO - Epoch(train) [23][800/2119] lr: 4.0000e-02 eta: 1 day, 3:19:19 time: 0.3570 data_time: 0.0203 memory: 11108 grad_norm: 2.9069 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5031 loss: 2.5031 2022/10/09 10:45:05 - mmengine - INFO - Epoch(train) [23][820/2119] lr: 4.0000e-02 eta: 1 day, 3:19:11 time: 0.3603 data_time: 0.0175 memory: 11108 grad_norm: 2.8133 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7134 loss: 2.7134 2022/10/09 10:45:12 - mmengine - INFO - Epoch(train) [23][840/2119] lr: 4.0000e-02 eta: 1 day, 3:19:03 time: 0.3577 data_time: 0.0208 memory: 11108 grad_norm: 2.8771 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.6240 loss: 2.6240 2022/10/09 10:45:20 - mmengine - INFO - Epoch(train) [23][860/2119] lr: 4.0000e-02 eta: 1 day, 3:18:55 time: 0.3584 data_time: 0.0191 memory: 11108 grad_norm: 2.8762 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.5001 loss: 2.5001 2022/10/09 10:45:27 - mmengine - INFO - Epoch(train) [23][880/2119] lr: 4.0000e-02 eta: 1 day, 3:18:47 time: 0.3570 data_time: 0.0205 memory: 11108 grad_norm: 2.8950 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4839 loss: 2.4839 2022/10/09 10:45:34 - mmengine - INFO - Epoch(train) [23][900/2119] lr: 4.0000e-02 eta: 1 day, 3:18:39 time: 0.3568 data_time: 0.0196 memory: 11108 grad_norm: 2.9207 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.6211 loss: 2.6211 2022/10/09 10:45:41 - mmengine - INFO - Epoch(train) [23][920/2119] lr: 4.0000e-02 eta: 1 day, 3:18:31 time: 0.3602 data_time: 0.0222 memory: 11108 grad_norm: 2.8899 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3312 loss: 2.3312 2022/10/09 10:45:48 - mmengine - INFO - Epoch(train) [23][940/2119] lr: 4.0000e-02 eta: 1 day, 3:18:23 time: 0.3567 data_time: 0.0213 memory: 11108 grad_norm: 2.8504 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8213 loss: 2.8213 2022/10/09 10:45:55 - mmengine - INFO - Epoch(train) [23][960/2119] lr: 4.0000e-02 eta: 1 day, 3:18:15 time: 0.3561 data_time: 0.0215 memory: 11108 grad_norm: 2.9025 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5977 loss: 2.5977 2022/10/09 10:46:02 - mmengine - INFO - Epoch(train) [23][980/2119] lr: 4.0000e-02 eta: 1 day, 3:18:07 time: 0.3603 data_time: 0.0201 memory: 11108 grad_norm: 2.8681 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7234 loss: 2.7234 2022/10/09 10:46:10 - mmengine - INFO - Epoch(train) [23][1000/2119] lr: 4.0000e-02 eta: 1 day, 3:17:59 time: 0.3566 data_time: 0.0214 memory: 11108 grad_norm: 2.8419 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7916 loss: 2.7916 2022/10/09 10:46:17 - mmengine - INFO - Epoch(train) [23][1020/2119] lr: 4.0000e-02 eta: 1 day, 3:17:51 time: 0.3548 data_time: 0.0159 memory: 11108 grad_norm: 2.8676 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5291 loss: 2.5291 2022/10/09 10:46:24 - mmengine - INFO - Epoch(train) [23][1040/2119] lr: 4.0000e-02 eta: 1 day, 3:17:44 time: 0.3664 data_time: 0.0234 memory: 11108 grad_norm: 2.7993 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6507 loss: 2.6507 2022/10/09 10:46:31 - mmengine - INFO - Epoch(train) [23][1060/2119] lr: 4.0000e-02 eta: 1 day, 3:17:36 time: 0.3606 data_time: 0.0195 memory: 11108 grad_norm: 2.9190 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6513 loss: 2.6513 2022/10/09 10:46:38 - mmengine - INFO - Epoch(train) [23][1080/2119] lr: 4.0000e-02 eta: 1 day, 3:17:29 time: 0.3583 data_time: 0.0237 memory: 11108 grad_norm: 2.9296 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8392 loss: 2.8392 2022/10/09 10:46:46 - mmengine - INFO - Epoch(train) [23][1100/2119] lr: 4.0000e-02 eta: 1 day, 3:17:21 time: 0.3578 data_time: 0.0188 memory: 11108 grad_norm: 2.8958 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5968 loss: 2.5968 2022/10/09 10:46:53 - mmengine - INFO - Epoch(train) [23][1120/2119] lr: 4.0000e-02 eta: 1 day, 3:17:13 time: 0.3585 data_time: 0.0230 memory: 11108 grad_norm: 2.9178 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6612 loss: 2.6612 2022/10/09 10:47:00 - mmengine - INFO - Epoch(train) [23][1140/2119] lr: 4.0000e-02 eta: 1 day, 3:17:05 time: 0.3605 data_time: 0.0180 memory: 11108 grad_norm: 2.8776 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5366 loss: 2.5366 2022/10/09 10:47:07 - mmengine - INFO - Epoch(train) [23][1160/2119] lr: 4.0000e-02 eta: 1 day, 3:16:57 time: 0.3551 data_time: 0.0216 memory: 11108 grad_norm: 2.8922 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5169 loss: 2.5169 2022/10/09 10:47:14 - mmengine - INFO - Epoch(train) [23][1180/2119] lr: 4.0000e-02 eta: 1 day, 3:16:49 time: 0.3609 data_time: 0.0195 memory: 11108 grad_norm: 2.8820 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5542 loss: 2.5542 2022/10/09 10:47:21 - mmengine - INFO - Epoch(train) [23][1200/2119] lr: 4.0000e-02 eta: 1 day, 3:16:41 time: 0.3584 data_time: 0.0223 memory: 11108 grad_norm: 2.8707 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6052 loss: 2.6052 2022/10/09 10:47:29 - mmengine - INFO - Epoch(train) [23][1220/2119] lr: 4.0000e-02 eta: 1 day, 3:16:34 time: 0.3614 data_time: 0.0194 memory: 11108 grad_norm: 2.8937 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6593 loss: 2.6593 2022/10/09 10:47:36 - mmengine - INFO - Epoch(train) [23][1240/2119] lr: 4.0000e-02 eta: 1 day, 3:16:26 time: 0.3580 data_time: 0.0215 memory: 11108 grad_norm: 2.9115 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6345 loss: 2.6345 2022/10/09 10:47:43 - mmengine - INFO - Epoch(train) [23][1260/2119] lr: 4.0000e-02 eta: 1 day, 3:16:18 time: 0.3567 data_time: 0.0184 memory: 11108 grad_norm: 2.8714 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7160 loss: 2.7160 2022/10/09 10:47:50 - mmengine - INFO - Epoch(train) [23][1280/2119] lr: 4.0000e-02 eta: 1 day, 3:16:11 time: 0.3627 data_time: 0.0199 memory: 11108 grad_norm: 2.8164 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9147 loss: 2.9147 2022/10/09 10:47:57 - mmengine - INFO - Epoch(train) [23][1300/2119] lr: 4.0000e-02 eta: 1 day, 3:16:02 time: 0.3546 data_time: 0.0153 memory: 11108 grad_norm: 2.8260 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6776 loss: 2.6776 2022/10/09 10:48:05 - mmengine - INFO - Epoch(train) [23][1320/2119] lr: 4.0000e-02 eta: 1 day, 3:15:55 time: 0.3595 data_time: 0.0200 memory: 11108 grad_norm: 2.8722 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5040 loss: 2.5040 2022/10/09 10:48:12 - mmengine - INFO - Epoch(train) [23][1340/2119] lr: 4.0000e-02 eta: 1 day, 3:15:47 time: 0.3580 data_time: 0.0211 memory: 11108 grad_norm: 2.8940 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7615 loss: 2.7615 2022/10/09 10:48:19 - mmengine - INFO - Epoch(train) [23][1360/2119] lr: 4.0000e-02 eta: 1 day, 3:15:39 time: 0.3564 data_time: 0.0188 memory: 11108 grad_norm: 2.8539 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6436 loss: 2.6436 2022/10/09 10:48:26 - mmengine - INFO - Epoch(train) [23][1380/2119] lr: 4.0000e-02 eta: 1 day, 3:15:31 time: 0.3630 data_time: 0.0239 memory: 11108 grad_norm: 2.8820 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7667 loss: 2.7667 2022/10/09 10:48:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 10:48:33 - mmengine - INFO - Epoch(train) [23][1400/2119] lr: 4.0000e-02 eta: 1 day, 3:15:23 time: 0.3594 data_time: 0.0190 memory: 11108 grad_norm: 2.9294 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6306 loss: 2.6306 2022/10/09 10:48:40 - mmengine - INFO - Epoch(train) [23][1420/2119] lr: 4.0000e-02 eta: 1 day, 3:15:16 time: 0.3614 data_time: 0.0207 memory: 11108 grad_norm: 2.8906 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6212 loss: 2.6212 2022/10/09 10:48:48 - mmengine - INFO - Epoch(train) [23][1440/2119] lr: 4.0000e-02 eta: 1 day, 3:15:08 time: 0.3578 data_time: 0.0215 memory: 11108 grad_norm: 2.8855 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6875 loss: 2.6875 2022/10/09 10:48:55 - mmengine - INFO - Epoch(train) [23][1460/2119] lr: 4.0000e-02 eta: 1 day, 3:15:00 time: 0.3571 data_time: 0.0168 memory: 11108 grad_norm: 2.8495 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7033 loss: 2.7033 2022/10/09 10:49:02 - mmengine - INFO - Epoch(train) [23][1480/2119] lr: 4.0000e-02 eta: 1 day, 3:14:53 time: 0.3631 data_time: 0.0227 memory: 11108 grad_norm: 2.9100 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6200 loss: 2.6200 2022/10/09 10:49:09 - mmengine - INFO - Epoch(train) [23][1500/2119] lr: 4.0000e-02 eta: 1 day, 3:14:45 time: 0.3560 data_time: 0.0162 memory: 11108 grad_norm: 2.8073 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7332 loss: 2.7332 2022/10/09 10:49:16 - mmengine - INFO - Epoch(train) [23][1520/2119] lr: 4.0000e-02 eta: 1 day, 3:14:37 time: 0.3605 data_time: 0.0201 memory: 11108 grad_norm: 2.8360 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7186 loss: 2.7186 2022/10/09 10:49:24 - mmengine - INFO - Epoch(train) [23][1540/2119] lr: 4.0000e-02 eta: 1 day, 3:14:29 time: 0.3574 data_time: 0.0193 memory: 11108 grad_norm: 2.8690 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5232 loss: 2.5232 2022/10/09 10:49:31 - mmengine - INFO - Epoch(train) [23][1560/2119] lr: 4.0000e-02 eta: 1 day, 3:14:21 time: 0.3606 data_time: 0.0252 memory: 11108 grad_norm: 2.9197 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.4454 loss: 2.4454 2022/10/09 10:49:38 - mmengine - INFO - Epoch(train) [23][1580/2119] lr: 4.0000e-02 eta: 1 day, 3:14:13 time: 0.3559 data_time: 0.0206 memory: 11108 grad_norm: 2.8754 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.8125 loss: 2.8125 2022/10/09 10:49:45 - mmengine - INFO - Epoch(train) [23][1600/2119] lr: 4.0000e-02 eta: 1 day, 3:14:07 time: 0.3713 data_time: 0.0236 memory: 11108 grad_norm: 2.9147 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6467 loss: 2.6467 2022/10/09 10:49:52 - mmengine - INFO - Epoch(train) [23][1620/2119] lr: 4.0000e-02 eta: 1 day, 3:13:59 time: 0.3563 data_time: 0.0182 memory: 11108 grad_norm: 2.8624 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4388 loss: 2.4388 2022/10/09 10:50:00 - mmengine - INFO - Epoch(train) [23][1640/2119] lr: 4.0000e-02 eta: 1 day, 3:13:50 time: 0.3542 data_time: 0.0228 memory: 11108 grad_norm: 2.9287 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4868 loss: 2.4868 2022/10/09 10:50:07 - mmengine - INFO - Epoch(train) [23][1660/2119] lr: 4.0000e-02 eta: 1 day, 3:13:43 time: 0.3635 data_time: 0.0212 memory: 11108 grad_norm: 2.8078 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4876 loss: 2.4876 2022/10/09 10:50:14 - mmengine - INFO - Epoch(train) [23][1680/2119] lr: 4.0000e-02 eta: 1 day, 3:13:35 time: 0.3578 data_time: 0.0196 memory: 11108 grad_norm: 2.8459 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7439 loss: 2.7439 2022/10/09 10:50:21 - mmengine - INFO - Epoch(train) [23][1700/2119] lr: 4.0000e-02 eta: 1 day, 3:13:27 time: 0.3584 data_time: 0.0217 memory: 11108 grad_norm: 2.8700 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.6331 loss: 2.6331 2022/10/09 10:50:28 - mmengine - INFO - Epoch(train) [23][1720/2119] lr: 4.0000e-02 eta: 1 day, 3:13:20 time: 0.3592 data_time: 0.0212 memory: 11108 grad_norm: 2.8959 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6126 loss: 2.6126 2022/10/09 10:50:35 - mmengine - INFO - Epoch(train) [23][1740/2119] lr: 4.0000e-02 eta: 1 day, 3:13:11 time: 0.3521 data_time: 0.0211 memory: 11108 grad_norm: 2.8933 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4955 loss: 2.4955 2022/10/09 10:50:43 - mmengine - INFO - Epoch(train) [23][1760/2119] lr: 4.0000e-02 eta: 1 day, 3:13:04 time: 0.3624 data_time: 0.0225 memory: 11108 grad_norm: 2.8461 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4651 loss: 2.4651 2022/10/09 10:50:50 - mmengine - INFO - Epoch(train) [23][1780/2119] lr: 4.0000e-02 eta: 1 day, 3:12:55 time: 0.3551 data_time: 0.0175 memory: 11108 grad_norm: 2.9281 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7367 loss: 2.7367 2022/10/09 10:50:57 - mmengine - INFO - Epoch(train) [23][1800/2119] lr: 4.0000e-02 eta: 1 day, 3:12:47 time: 0.3567 data_time: 0.0260 memory: 11108 grad_norm: 2.9003 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6358 loss: 2.6358 2022/10/09 10:51:04 - mmengine - INFO - Epoch(train) [23][1820/2119] lr: 4.0000e-02 eta: 1 day, 3:12:40 time: 0.3611 data_time: 0.0204 memory: 11108 grad_norm: 2.8778 top1_acc: 0.5625 top5_acc: 1.0000 loss_cls: 2.7219 loss: 2.7219 2022/10/09 10:51:11 - mmengine - INFO - Epoch(train) [23][1840/2119] lr: 4.0000e-02 eta: 1 day, 3:12:32 time: 0.3617 data_time: 0.0180 memory: 11108 grad_norm: 2.8649 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8220 loss: 2.8220 2022/10/09 10:51:18 - mmengine - INFO - Epoch(train) [23][1860/2119] lr: 4.0000e-02 eta: 1 day, 3:12:24 time: 0.3559 data_time: 0.0221 memory: 11108 grad_norm: 2.8533 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5383 loss: 2.5383 2022/10/09 10:51:26 - mmengine - INFO - Epoch(train) [23][1880/2119] lr: 4.0000e-02 eta: 1 day, 3:12:17 time: 0.3644 data_time: 0.0176 memory: 11108 grad_norm: 2.8716 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5452 loss: 2.5452 2022/10/09 10:51:33 - mmengine - INFO - Epoch(train) [23][1900/2119] lr: 4.0000e-02 eta: 1 day, 3:12:09 time: 0.3615 data_time: 0.0228 memory: 11108 grad_norm: 2.8591 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9437 loss: 2.9437 2022/10/09 10:51:40 - mmengine - INFO - Epoch(train) [23][1920/2119] lr: 4.0000e-02 eta: 1 day, 3:12:02 time: 0.3598 data_time: 0.0228 memory: 11108 grad_norm: 2.8761 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8779 loss: 2.8779 2022/10/09 10:51:47 - mmengine - INFO - Epoch(train) [23][1940/2119] lr: 4.0000e-02 eta: 1 day, 3:11:54 time: 0.3574 data_time: 0.0215 memory: 11108 grad_norm: 2.8653 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5459 loss: 2.5459 2022/10/09 10:51:54 - mmengine - INFO - Epoch(train) [23][1960/2119] lr: 4.0000e-02 eta: 1 day, 3:11:46 time: 0.3595 data_time: 0.0179 memory: 11108 grad_norm: 2.8583 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8549 loss: 2.8549 2022/10/09 10:52:02 - mmengine - INFO - Epoch(train) [23][1980/2119] lr: 4.0000e-02 eta: 1 day, 3:11:38 time: 0.3573 data_time: 0.0211 memory: 11108 grad_norm: 2.8558 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6059 loss: 2.6059 2022/10/09 10:52:09 - mmengine - INFO - Epoch(train) [23][2000/2119] lr: 4.0000e-02 eta: 1 day, 3:11:30 time: 0.3581 data_time: 0.0216 memory: 11108 grad_norm: 2.8508 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4521 loss: 2.4521 2022/10/09 10:52:16 - mmengine - INFO - Epoch(train) [23][2020/2119] lr: 4.0000e-02 eta: 1 day, 3:11:22 time: 0.3573 data_time: 0.0189 memory: 11108 grad_norm: 2.8721 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7183 loss: 2.7183 2022/10/09 10:52:23 - mmengine - INFO - Epoch(train) [23][2040/2119] lr: 4.0000e-02 eta: 1 day, 3:11:14 time: 0.3590 data_time: 0.0202 memory: 11108 grad_norm: 2.8569 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7748 loss: 2.7748 2022/10/09 10:52:30 - mmengine - INFO - Epoch(train) [23][2060/2119] lr: 4.0000e-02 eta: 1 day, 3:11:07 time: 0.3663 data_time: 0.0286 memory: 11108 grad_norm: 2.8860 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7047 loss: 2.7047 2022/10/09 10:52:38 - mmengine - INFO - Epoch(train) [23][2080/2119] lr: 4.0000e-02 eta: 1 day, 3:10:59 time: 0.3548 data_time: 0.0201 memory: 11108 grad_norm: 2.9101 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5535 loss: 2.5535 2022/10/09 10:52:45 - mmengine - INFO - Epoch(train) [23][2100/2119] lr: 4.0000e-02 eta: 1 day, 3:10:51 time: 0.3544 data_time: 0.0220 memory: 11108 grad_norm: 2.8435 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5981 loss: 2.5981 2022/10/09 10:52:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 10:52:52 - mmengine - INFO - Epoch(train) [23][2119/2119] lr: 4.0000e-02 eta: 1 day, 3:10:51 time: 0.3649 data_time: 0.0203 memory: 11108 grad_norm: 2.9016 top1_acc: 0.7000 top5_acc: 0.8000 loss_cls: 2.3998 loss: 2.3998 2022/10/09 10:53:02 - mmengine - INFO - Epoch(train) [24][20/2119] lr: 4.0000e-02 eta: 1 day, 3:10:19 time: 0.5435 data_time: 0.1276 memory: 11108 grad_norm: 2.8268 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6390 loss: 2.6390 2022/10/09 10:53:10 - mmengine - INFO - Epoch(train) [24][40/2119] lr: 4.0000e-02 eta: 1 day, 3:10:11 time: 0.3608 data_time: 0.0238 memory: 11108 grad_norm: 2.8469 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6419 loss: 2.6419 2022/10/09 10:53:17 - mmengine - INFO - Epoch(train) [24][60/2119] lr: 4.0000e-02 eta: 1 day, 3:10:04 time: 0.3624 data_time: 0.0197 memory: 11108 grad_norm: 2.8316 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5632 loss: 2.5632 2022/10/09 10:53:24 - mmengine - INFO - Epoch(train) [24][80/2119] lr: 4.0000e-02 eta: 1 day, 3:09:55 time: 0.3535 data_time: 0.0207 memory: 11108 grad_norm: 2.9042 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5319 loss: 2.5319 2022/10/09 10:53:31 - mmengine - INFO - Epoch(train) [24][100/2119] lr: 4.0000e-02 eta: 1 day, 3:09:48 time: 0.3625 data_time: 0.0200 memory: 11108 grad_norm: 2.9140 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6269 loss: 2.6269 2022/10/09 10:53:38 - mmengine - INFO - Epoch(train) [24][120/2119] lr: 4.0000e-02 eta: 1 day, 3:09:40 time: 0.3582 data_time: 0.0197 memory: 11108 grad_norm: 2.9288 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5777 loss: 2.5777 2022/10/09 10:53:46 - mmengine - INFO - Epoch(train) [24][140/2119] lr: 4.0000e-02 eta: 1 day, 3:09:33 time: 0.3649 data_time: 0.0179 memory: 11108 grad_norm: 2.9149 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6440 loss: 2.6440 2022/10/09 10:53:53 - mmengine - INFO - Epoch(train) [24][160/2119] lr: 4.0000e-02 eta: 1 day, 3:09:25 time: 0.3610 data_time: 0.0197 memory: 11108 grad_norm: 2.9055 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6402 loss: 2.6402 2022/10/09 10:54:00 - mmengine - INFO - Epoch(train) [24][180/2119] lr: 4.0000e-02 eta: 1 day, 3:09:17 time: 0.3546 data_time: 0.0211 memory: 11108 grad_norm: 2.8829 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5938 loss: 2.5938 2022/10/09 10:54:07 - mmengine - INFO - Epoch(train) [24][200/2119] lr: 4.0000e-02 eta: 1 day, 3:09:09 time: 0.3557 data_time: 0.0183 memory: 11108 grad_norm: 2.9246 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7118 loss: 2.7118 2022/10/09 10:54:14 - mmengine - INFO - Epoch(train) [24][220/2119] lr: 4.0000e-02 eta: 1 day, 3:09:01 time: 0.3616 data_time: 0.0193 memory: 11108 grad_norm: 2.8185 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5160 loss: 2.5160 2022/10/09 10:54:22 - mmengine - INFO - Epoch(train) [24][240/2119] lr: 4.0000e-02 eta: 1 day, 3:08:53 time: 0.3550 data_time: 0.0211 memory: 11108 grad_norm: 2.9002 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.3613 loss: 2.3613 2022/10/09 10:54:29 - mmengine - INFO - Epoch(train) [24][260/2119] lr: 4.0000e-02 eta: 1 day, 3:08:45 time: 0.3578 data_time: 0.0171 memory: 11108 grad_norm: 2.8757 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5845 loss: 2.5845 2022/10/09 10:54:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 10:54:36 - mmengine - INFO - Epoch(train) [24][280/2119] lr: 4.0000e-02 eta: 1 day, 3:08:37 time: 0.3561 data_time: 0.0212 memory: 11108 grad_norm: 2.8581 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.6297 loss: 2.6297 2022/10/09 10:54:43 - mmengine - INFO - Epoch(train) [24][300/2119] lr: 4.0000e-02 eta: 1 day, 3:08:29 time: 0.3586 data_time: 0.0238 memory: 11108 grad_norm: 2.9023 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5027 loss: 2.5027 2022/10/09 10:54:50 - mmengine - INFO - Epoch(train) [24][320/2119] lr: 4.0000e-02 eta: 1 day, 3:08:22 time: 0.3578 data_time: 0.0214 memory: 11108 grad_norm: 2.8478 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6465 loss: 2.6465 2022/10/09 10:54:57 - mmengine - INFO - Epoch(train) [24][340/2119] lr: 4.0000e-02 eta: 1 day, 3:08:13 time: 0.3557 data_time: 0.0204 memory: 11108 grad_norm: 2.8278 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4375 loss: 2.4375 2022/10/09 10:55:04 - mmengine - INFO - Epoch(train) [24][360/2119] lr: 4.0000e-02 eta: 1 day, 3:08:06 time: 0.3577 data_time: 0.0212 memory: 11108 grad_norm: 2.8472 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7310 loss: 2.7310 2022/10/09 10:55:12 - mmengine - INFO - Epoch(train) [24][380/2119] lr: 4.0000e-02 eta: 1 day, 3:07:58 time: 0.3592 data_time: 0.0214 memory: 11108 grad_norm: 2.8633 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7119 loss: 2.7119 2022/10/09 10:55:19 - mmengine - INFO - Epoch(train) [24][400/2119] lr: 4.0000e-02 eta: 1 day, 3:07:50 time: 0.3574 data_time: 0.0190 memory: 11108 grad_norm: 2.8722 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5105 loss: 2.5105 2022/10/09 10:55:26 - mmengine - INFO - Epoch(train) [24][420/2119] lr: 4.0000e-02 eta: 1 day, 3:07:42 time: 0.3610 data_time: 0.0173 memory: 11108 grad_norm: 2.8581 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4696 loss: 2.4696 2022/10/09 10:55:33 - mmengine - INFO - Epoch(train) [24][440/2119] lr: 4.0000e-02 eta: 1 day, 3:07:35 time: 0.3597 data_time: 0.0222 memory: 11108 grad_norm: 2.8732 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6891 loss: 2.6891 2022/10/09 10:55:40 - mmengine - INFO - Epoch(train) [24][460/2119] lr: 4.0000e-02 eta: 1 day, 3:07:27 time: 0.3558 data_time: 0.0205 memory: 11108 grad_norm: 2.8708 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.5161 loss: 2.5161 2022/10/09 10:55:47 - mmengine - INFO - Epoch(train) [24][480/2119] lr: 4.0000e-02 eta: 1 day, 3:07:19 time: 0.3615 data_time: 0.0214 memory: 11108 grad_norm: 2.8448 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6598 loss: 2.6598 2022/10/09 10:55:55 - mmengine - INFO - Epoch(train) [24][500/2119] lr: 4.0000e-02 eta: 1 day, 3:07:11 time: 0.3592 data_time: 0.0217 memory: 11108 grad_norm: 2.8669 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5396 loss: 2.5396 2022/10/09 10:56:02 - mmengine - INFO - Epoch(train) [24][520/2119] lr: 4.0000e-02 eta: 1 day, 3:07:03 time: 0.3568 data_time: 0.0209 memory: 11108 grad_norm: 2.9071 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.6670 loss: 2.6670 2022/10/09 10:56:09 - mmengine - INFO - Epoch(train) [24][540/2119] lr: 4.0000e-02 eta: 1 day, 3:06:56 time: 0.3592 data_time: 0.0182 memory: 11108 grad_norm: 2.9361 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5673 loss: 2.5673 2022/10/09 10:56:16 - mmengine - INFO - Epoch(train) [24][560/2119] lr: 4.0000e-02 eta: 1 day, 3:06:48 time: 0.3574 data_time: 0.0224 memory: 11108 grad_norm: 2.8829 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5740 loss: 2.5740 2022/10/09 10:56:23 - mmengine - INFO - Epoch(train) [24][580/2119] lr: 4.0000e-02 eta: 1 day, 3:06:40 time: 0.3593 data_time: 0.0176 memory: 11108 grad_norm: 2.8974 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4574 loss: 2.4574 2022/10/09 10:56:31 - mmengine - INFO - Epoch(train) [24][600/2119] lr: 4.0000e-02 eta: 1 day, 3:06:32 time: 0.3619 data_time: 0.0216 memory: 11108 grad_norm: 2.8805 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.4497 loss: 2.4497 2022/10/09 10:56:38 - mmengine - INFO - Epoch(train) [24][620/2119] lr: 4.0000e-02 eta: 1 day, 3:06:24 time: 0.3558 data_time: 0.0193 memory: 11108 grad_norm: 2.9037 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5797 loss: 2.5797 2022/10/09 10:56:45 - mmengine - INFO - Epoch(train) [24][640/2119] lr: 4.0000e-02 eta: 1 day, 3:06:17 time: 0.3635 data_time: 0.0209 memory: 11108 grad_norm: 2.8165 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4071 loss: 2.4071 2022/10/09 10:56:52 - mmengine - INFO - Epoch(train) [24][660/2119] lr: 4.0000e-02 eta: 1 day, 3:06:09 time: 0.3550 data_time: 0.0174 memory: 11108 grad_norm: 2.8591 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.4409 loss: 2.4409 2022/10/09 10:56:59 - mmengine - INFO - Epoch(train) [24][680/2119] lr: 4.0000e-02 eta: 1 day, 3:06:01 time: 0.3570 data_time: 0.0218 memory: 11108 grad_norm: 2.8422 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5406 loss: 2.5406 2022/10/09 10:57:06 - mmengine - INFO - Epoch(train) [24][700/2119] lr: 4.0000e-02 eta: 1 day, 3:05:53 time: 0.3586 data_time: 0.0234 memory: 11108 grad_norm: 2.8632 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7638 loss: 2.7638 2022/10/09 10:57:14 - mmengine - INFO - Epoch(train) [24][720/2119] lr: 4.0000e-02 eta: 1 day, 3:05:45 time: 0.3589 data_time: 0.0205 memory: 11108 grad_norm: 2.8832 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7313 loss: 2.7313 2022/10/09 10:57:21 - mmengine - INFO - Epoch(train) [24][740/2119] lr: 4.0000e-02 eta: 1 day, 3:05:38 time: 0.3582 data_time: 0.0218 memory: 11108 grad_norm: 2.8420 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6628 loss: 2.6628 2022/10/09 10:57:28 - mmengine - INFO - Epoch(train) [24][760/2119] lr: 4.0000e-02 eta: 1 day, 3:05:30 time: 0.3633 data_time: 0.0212 memory: 11108 grad_norm: 2.9421 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7000 loss: 2.7000 2022/10/09 10:57:35 - mmengine - INFO - Epoch(train) [24][780/2119] lr: 4.0000e-02 eta: 1 day, 3:05:22 time: 0.3552 data_time: 0.0161 memory: 11108 grad_norm: 2.8604 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5955 loss: 2.5955 2022/10/09 10:57:42 - mmengine - INFO - Epoch(train) [24][800/2119] lr: 4.0000e-02 eta: 1 day, 3:05:14 time: 0.3588 data_time: 0.0227 memory: 11108 grad_norm: 2.8438 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6465 loss: 2.6465 2022/10/09 10:57:49 - mmengine - INFO - Epoch(train) [24][820/2119] lr: 4.0000e-02 eta: 1 day, 3:05:07 time: 0.3604 data_time: 0.0224 memory: 11108 grad_norm: 2.8448 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5873 loss: 2.5873 2022/10/09 10:57:57 - mmengine - INFO - Epoch(train) [24][840/2119] lr: 4.0000e-02 eta: 1 day, 3:04:59 time: 0.3589 data_time: 0.0213 memory: 11108 grad_norm: 2.8970 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5158 loss: 2.5158 2022/10/09 10:58:04 - mmengine - INFO - Epoch(train) [24][860/2119] lr: 4.0000e-02 eta: 1 day, 3:04:51 time: 0.3565 data_time: 0.0148 memory: 11108 grad_norm: 2.9077 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6097 loss: 2.6097 2022/10/09 10:58:11 - mmengine - INFO - Epoch(train) [24][880/2119] lr: 4.0000e-02 eta: 1 day, 3:04:43 time: 0.3579 data_time: 0.0201 memory: 11108 grad_norm: 2.8452 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6084 loss: 2.6084 2022/10/09 10:58:18 - mmengine - INFO - Epoch(train) [24][900/2119] lr: 4.0000e-02 eta: 1 day, 3:04:35 time: 0.3570 data_time: 0.0211 memory: 11108 grad_norm: 2.8511 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.4902 loss: 2.4902 2022/10/09 10:58:25 - mmengine - INFO - Epoch(train) [24][920/2119] lr: 4.0000e-02 eta: 1 day, 3:04:27 time: 0.3537 data_time: 0.0201 memory: 11108 grad_norm: 2.8854 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7517 loss: 2.7517 2022/10/09 10:58:32 - mmengine - INFO - Epoch(train) [24][940/2119] lr: 4.0000e-02 eta: 1 day, 3:04:19 time: 0.3561 data_time: 0.0210 memory: 11108 grad_norm: 2.8875 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8244 loss: 2.8244 2022/10/09 10:58:39 - mmengine - INFO - Epoch(train) [24][960/2119] lr: 4.0000e-02 eta: 1 day, 3:04:11 time: 0.3571 data_time: 0.0251 memory: 11108 grad_norm: 2.8640 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.2375 loss: 2.2375 2022/10/09 10:58:47 - mmengine - INFO - Epoch(train) [24][980/2119] lr: 4.0000e-02 eta: 1 day, 3:04:03 time: 0.3577 data_time: 0.0201 memory: 11108 grad_norm: 2.8700 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4733 loss: 2.4733 2022/10/09 10:58:54 - mmengine - INFO - Epoch(train) [24][1000/2119] lr: 4.0000e-02 eta: 1 day, 3:03:55 time: 0.3555 data_time: 0.0197 memory: 11108 grad_norm: 2.8673 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.4199 loss: 2.4199 2022/10/09 10:59:01 - mmengine - INFO - Epoch(train) [24][1020/2119] lr: 4.0000e-02 eta: 1 day, 3:03:47 time: 0.3586 data_time: 0.0205 memory: 11108 grad_norm: 2.8531 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5550 loss: 2.5550 2022/10/09 10:59:08 - mmengine - INFO - Epoch(train) [24][1040/2119] lr: 4.0000e-02 eta: 1 day, 3:03:39 time: 0.3591 data_time: 0.0225 memory: 11108 grad_norm: 2.8662 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5813 loss: 2.5813 2022/10/09 10:59:15 - mmengine - INFO - Epoch(train) [24][1060/2119] lr: 4.0000e-02 eta: 1 day, 3:03:31 time: 0.3571 data_time: 0.0174 memory: 11108 grad_norm: 2.8299 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4962 loss: 2.4962 2022/10/09 10:59:22 - mmengine - INFO - Epoch(train) [24][1080/2119] lr: 4.0000e-02 eta: 1 day, 3:03:24 time: 0.3597 data_time: 0.0212 memory: 11108 grad_norm: 2.8848 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.6456 loss: 2.6456 2022/10/09 10:59:30 - mmengine - INFO - Epoch(train) [24][1100/2119] lr: 4.0000e-02 eta: 1 day, 3:03:16 time: 0.3574 data_time: 0.0190 memory: 11108 grad_norm: 2.8908 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5738 loss: 2.5738 2022/10/09 10:59:37 - mmengine - INFO - Epoch(train) [24][1120/2119] lr: 4.0000e-02 eta: 1 day, 3:03:08 time: 0.3610 data_time: 0.0210 memory: 11108 grad_norm: 2.9409 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7189 loss: 2.7189 2022/10/09 10:59:44 - mmengine - INFO - Epoch(train) [24][1140/2119] lr: 4.0000e-02 eta: 1 day, 3:03:00 time: 0.3570 data_time: 0.0184 memory: 11108 grad_norm: 2.8728 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4638 loss: 2.4638 2022/10/09 10:59:51 - mmengine - INFO - Epoch(train) [24][1160/2119] lr: 4.0000e-02 eta: 1 day, 3:02:54 time: 0.3714 data_time: 0.0254 memory: 11108 grad_norm: 2.9064 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5858 loss: 2.5858 2022/10/09 10:59:58 - mmengine - INFO - Epoch(train) [24][1180/2119] lr: 4.0000e-02 eta: 1 day, 3:02:46 time: 0.3562 data_time: 0.0156 memory: 11108 grad_norm: 2.8641 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7606 loss: 2.7606 2022/10/09 11:00:06 - mmengine - INFO - Epoch(train) [24][1200/2119] lr: 4.0000e-02 eta: 1 day, 3:02:38 time: 0.3625 data_time: 0.0198 memory: 11108 grad_norm: 2.9384 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7023 loss: 2.7023 2022/10/09 11:00:13 - mmengine - INFO - Epoch(train) [24][1220/2119] lr: 4.0000e-02 eta: 1 day, 3:02:32 time: 0.3676 data_time: 0.0198 memory: 11108 grad_norm: 2.8737 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7223 loss: 2.7223 2022/10/09 11:00:20 - mmengine - INFO - Epoch(train) [24][1240/2119] lr: 4.0000e-02 eta: 1 day, 3:02:23 time: 0.3548 data_time: 0.0229 memory: 11108 grad_norm: 2.9290 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7159 loss: 2.7159 2022/10/09 11:00:27 - mmengine - INFO - Epoch(train) [24][1260/2119] lr: 4.0000e-02 eta: 1 day, 3:02:16 time: 0.3656 data_time: 0.0208 memory: 11108 grad_norm: 2.8908 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6400 loss: 2.6400 2022/10/09 11:00:29 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 11:00:35 - mmengine - INFO - Epoch(train) [24][1280/2119] lr: 4.0000e-02 eta: 1 day, 3:02:09 time: 0.3583 data_time: 0.0192 memory: 11108 grad_norm: 2.9185 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6721 loss: 2.6721 2022/10/09 11:00:42 - mmengine - INFO - Epoch(train) [24][1300/2119] lr: 4.0000e-02 eta: 1 day, 3:02:01 time: 0.3610 data_time: 0.0198 memory: 11108 grad_norm: 2.9194 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8370 loss: 2.8370 2022/10/09 11:00:49 - mmengine - INFO - Epoch(train) [24][1320/2119] lr: 4.0000e-02 eta: 1 day, 3:01:54 time: 0.3612 data_time: 0.0251 memory: 11108 grad_norm: 2.9564 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7819 loss: 2.7819 2022/10/09 11:00:56 - mmengine - INFO - Epoch(train) [24][1340/2119] lr: 4.0000e-02 eta: 1 day, 3:01:46 time: 0.3557 data_time: 0.0185 memory: 11108 grad_norm: 2.9227 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8039 loss: 2.8039 2022/10/09 11:01:03 - mmengine - INFO - Epoch(train) [24][1360/2119] lr: 4.0000e-02 eta: 1 day, 3:01:38 time: 0.3575 data_time: 0.0237 memory: 11108 grad_norm: 2.8607 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4522 loss: 2.4522 2022/10/09 11:01:11 - mmengine - INFO - Epoch(train) [24][1380/2119] lr: 4.0000e-02 eta: 1 day, 3:01:30 time: 0.3568 data_time: 0.0229 memory: 11108 grad_norm: 2.8342 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7362 loss: 2.7362 2022/10/09 11:01:18 - mmengine - INFO - Epoch(train) [24][1400/2119] lr: 4.0000e-02 eta: 1 day, 3:01:22 time: 0.3566 data_time: 0.0192 memory: 11108 grad_norm: 2.8610 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5606 loss: 2.5606 2022/10/09 11:01:25 - mmengine - INFO - Epoch(train) [24][1420/2119] lr: 4.0000e-02 eta: 1 day, 3:01:14 time: 0.3590 data_time: 0.0196 memory: 11108 grad_norm: 2.9158 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.7528 loss: 2.7528 2022/10/09 11:01:32 - mmengine - INFO - Epoch(train) [24][1440/2119] lr: 4.0000e-02 eta: 1 day, 3:01:06 time: 0.3584 data_time: 0.0182 memory: 11108 grad_norm: 2.9097 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7651 loss: 2.7651 2022/10/09 11:01:39 - mmengine - INFO - Epoch(train) [24][1460/2119] lr: 4.0000e-02 eta: 1 day, 3:00:58 time: 0.3549 data_time: 0.0181 memory: 11108 grad_norm: 2.8676 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6255 loss: 2.6255 2022/10/09 11:01:46 - mmengine - INFO - Epoch(train) [24][1480/2119] lr: 4.0000e-02 eta: 1 day, 3:00:51 time: 0.3633 data_time: 0.0203 memory: 11108 grad_norm: 2.9182 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6365 loss: 2.6365 2022/10/09 11:01:54 - mmengine - INFO - Epoch(train) [24][1500/2119] lr: 4.0000e-02 eta: 1 day, 3:00:43 time: 0.3581 data_time: 0.0169 memory: 11108 grad_norm: 2.8903 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4917 loss: 2.4917 2022/10/09 11:02:01 - mmengine - INFO - Epoch(train) [24][1520/2119] lr: 4.0000e-02 eta: 1 day, 3:00:36 time: 0.3630 data_time: 0.0203 memory: 11108 grad_norm: 2.8716 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.5105 loss: 2.5105 2022/10/09 11:02:08 - mmengine - INFO - Epoch(train) [24][1540/2119] lr: 4.0000e-02 eta: 1 day, 3:00:27 time: 0.3560 data_time: 0.0196 memory: 11108 grad_norm: 2.8786 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.7608 loss: 2.7608 2022/10/09 11:02:15 - mmengine - INFO - Epoch(train) [24][1560/2119] lr: 4.0000e-02 eta: 1 day, 3:00:20 time: 0.3578 data_time: 0.0238 memory: 11108 grad_norm: 2.8943 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5670 loss: 2.5670 2022/10/09 11:02:22 - mmengine - INFO - Epoch(train) [24][1580/2119] lr: 4.0000e-02 eta: 1 day, 3:00:12 time: 0.3592 data_time: 0.0201 memory: 11108 grad_norm: 2.8984 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7202 loss: 2.7202 2022/10/09 11:02:29 - mmengine - INFO - Epoch(train) [24][1600/2119] lr: 4.0000e-02 eta: 1 day, 3:00:04 time: 0.3602 data_time: 0.0207 memory: 11108 grad_norm: 2.8784 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7491 loss: 2.7491 2022/10/09 11:02:37 - mmengine - INFO - Epoch(train) [24][1620/2119] lr: 4.0000e-02 eta: 1 day, 2:59:56 time: 0.3550 data_time: 0.0204 memory: 11108 grad_norm: 2.8903 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6964 loss: 2.6964 2022/10/09 11:02:44 - mmengine - INFO - Epoch(train) [24][1640/2119] lr: 4.0000e-02 eta: 1 day, 2:59:48 time: 0.3584 data_time: 0.0247 memory: 11108 grad_norm: 2.8296 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7241 loss: 2.7241 2022/10/09 11:02:51 - mmengine - INFO - Epoch(train) [24][1660/2119] lr: 4.0000e-02 eta: 1 day, 2:59:40 time: 0.3568 data_time: 0.0215 memory: 11108 grad_norm: 2.9373 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8140 loss: 2.8140 2022/10/09 11:02:58 - mmengine - INFO - Epoch(train) [24][1680/2119] lr: 4.0000e-02 eta: 1 day, 2:59:32 time: 0.3554 data_time: 0.0217 memory: 11108 grad_norm: 2.8742 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5475 loss: 2.5475 2022/10/09 11:03:05 - mmengine - INFO - Epoch(train) [24][1700/2119] lr: 4.0000e-02 eta: 1 day, 2:59:25 time: 0.3611 data_time: 0.0175 memory: 11108 grad_norm: 2.8868 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5612 loss: 2.5612 2022/10/09 11:03:12 - mmengine - INFO - Epoch(train) [24][1720/2119] lr: 4.0000e-02 eta: 1 day, 2:59:17 time: 0.3593 data_time: 0.0205 memory: 11108 grad_norm: 2.8982 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6419 loss: 2.6419 2022/10/09 11:03:20 - mmengine - INFO - Epoch(train) [24][1740/2119] lr: 4.0000e-02 eta: 1 day, 2:59:10 time: 0.3617 data_time: 0.0229 memory: 11108 grad_norm: 2.8834 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6798 loss: 2.6798 2022/10/09 11:03:27 - mmengine - INFO - Epoch(train) [24][1760/2119] lr: 4.0000e-02 eta: 1 day, 2:59:02 time: 0.3617 data_time: 0.0221 memory: 11108 grad_norm: 2.8542 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7065 loss: 2.7065 2022/10/09 11:03:34 - mmengine - INFO - Epoch(train) [24][1780/2119] lr: 4.0000e-02 eta: 1 day, 2:58:55 time: 0.3619 data_time: 0.0228 memory: 11108 grad_norm: 2.8881 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6732 loss: 2.6732 2022/10/09 11:03:41 - mmengine - INFO - Epoch(train) [24][1800/2119] lr: 4.0000e-02 eta: 1 day, 2:58:47 time: 0.3570 data_time: 0.0179 memory: 11108 grad_norm: 2.8943 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.3807 loss: 2.3807 2022/10/09 11:03:48 - mmengine - INFO - Epoch(train) [24][1820/2119] lr: 4.0000e-02 eta: 1 day, 2:58:39 time: 0.3587 data_time: 0.0194 memory: 11108 grad_norm: 2.8824 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6280 loss: 2.6280 2022/10/09 11:03:56 - mmengine - INFO - Epoch(train) [24][1840/2119] lr: 4.0000e-02 eta: 1 day, 2:58:31 time: 0.3582 data_time: 0.0196 memory: 11108 grad_norm: 2.8660 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4450 loss: 2.4450 2022/10/09 11:04:03 - mmengine - INFO - Epoch(train) [24][1860/2119] lr: 4.0000e-02 eta: 1 day, 2:58:23 time: 0.3582 data_time: 0.0176 memory: 11108 grad_norm: 2.9000 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5810 loss: 2.5810 2022/10/09 11:04:10 - mmengine - INFO - Epoch(train) [24][1880/2119] lr: 4.0000e-02 eta: 1 day, 2:58:16 time: 0.3592 data_time: 0.0196 memory: 11108 grad_norm: 2.8636 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6310 loss: 2.6310 2022/10/09 11:04:17 - mmengine - INFO - Epoch(train) [24][1900/2119] lr: 4.0000e-02 eta: 1 day, 2:58:08 time: 0.3605 data_time: 0.0199 memory: 11108 grad_norm: 2.8805 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7127 loss: 2.7127 2022/10/09 11:04:24 - mmengine - INFO - Epoch(train) [24][1920/2119] lr: 4.0000e-02 eta: 1 day, 2:58:00 time: 0.3595 data_time: 0.0232 memory: 11108 grad_norm: 2.8484 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4610 loss: 2.4610 2022/10/09 11:04:32 - mmengine - INFO - Epoch(train) [24][1940/2119] lr: 4.0000e-02 eta: 1 day, 2:57:53 time: 0.3635 data_time: 0.0208 memory: 11108 grad_norm: 2.8887 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4974 loss: 2.4974 2022/10/09 11:04:39 - mmengine - INFO - Epoch(train) [24][1960/2119] lr: 4.0000e-02 eta: 1 day, 2:57:45 time: 0.3545 data_time: 0.0234 memory: 11108 grad_norm: 2.8289 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7677 loss: 2.7677 2022/10/09 11:04:46 - mmengine - INFO - Epoch(train) [24][1980/2119] lr: 4.0000e-02 eta: 1 day, 2:57:37 time: 0.3580 data_time: 0.0245 memory: 11108 grad_norm: 2.8798 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5666 loss: 2.5666 2022/10/09 11:04:53 - mmengine - INFO - Epoch(train) [24][2000/2119] lr: 4.0000e-02 eta: 1 day, 2:57:31 time: 0.3750 data_time: 0.0266 memory: 11108 grad_norm: 2.8537 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6020 loss: 2.6020 2022/10/09 11:05:00 - mmengine - INFO - Epoch(train) [24][2020/2119] lr: 4.0000e-02 eta: 1 day, 2:57:23 time: 0.3537 data_time: 0.0197 memory: 11108 grad_norm: 2.8890 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5724 loss: 2.5724 2022/10/09 11:05:08 - mmengine - INFO - Epoch(train) [24][2040/2119] lr: 4.0000e-02 eta: 1 day, 2:57:16 time: 0.3624 data_time: 0.0204 memory: 11108 grad_norm: 2.8917 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.8373 loss: 2.8373 2022/10/09 11:05:15 - mmengine - INFO - Epoch(train) [24][2060/2119] lr: 4.0000e-02 eta: 1 day, 2:57:08 time: 0.3633 data_time: 0.0200 memory: 11108 grad_norm: 2.8814 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5157 loss: 2.5157 2022/10/09 11:05:22 - mmengine - INFO - Epoch(train) [24][2080/2119] lr: 4.0000e-02 eta: 1 day, 2:57:01 time: 0.3666 data_time: 0.0226 memory: 11108 grad_norm: 2.8287 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7086 loss: 2.7086 2022/10/09 11:05:29 - mmengine - INFO - Epoch(train) [24][2100/2119] lr: 4.0000e-02 eta: 1 day, 2:56:53 time: 0.3576 data_time: 0.0196 memory: 11108 grad_norm: 2.8512 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5248 loss: 2.5248 2022/10/09 11:05:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 11:05:36 - mmengine - INFO - Epoch(train) [24][2119/2119] lr: 4.0000e-02 eta: 1 day, 2:56:53 time: 0.3503 data_time: 0.0170 memory: 11108 grad_norm: 2.9054 top1_acc: 0.2000 top5_acc: 0.6000 loss_cls: 2.6084 loss: 2.6084 2022/10/09 11:05:36 - mmengine - INFO - Saving checkpoint at 24 epochs 2022/10/09 11:05:48 - mmengine - INFO - Epoch(train) [25][20/2119] lr: 4.0000e-02 eta: 1 day, 2:56:12 time: 0.4529 data_time: 0.1209 memory: 11108 grad_norm: 2.8840 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5840 loss: 2.5840 2022/10/09 11:05:55 - mmengine - INFO - Epoch(train) [25][40/2119] lr: 4.0000e-02 eta: 1 day, 2:56:05 time: 0.3626 data_time: 0.0196 memory: 11108 grad_norm: 2.8539 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7757 loss: 2.7757 2022/10/09 11:06:03 - mmengine - INFO - Epoch(train) [25][60/2119] lr: 4.0000e-02 eta: 1 day, 2:55:58 time: 0.3664 data_time: 0.0251 memory: 11108 grad_norm: 2.9065 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5108 loss: 2.5108 2022/10/09 11:06:10 - mmengine - INFO - Epoch(train) [25][80/2119] lr: 4.0000e-02 eta: 1 day, 2:55:50 time: 0.3583 data_time: 0.0196 memory: 11108 grad_norm: 2.8584 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5823 loss: 2.5823 2022/10/09 11:06:17 - mmengine - INFO - Epoch(train) [25][100/2119] lr: 4.0000e-02 eta: 1 day, 2:55:43 time: 0.3593 data_time: 0.0199 memory: 11108 grad_norm: 2.8692 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6778 loss: 2.6778 2022/10/09 11:06:24 - mmengine - INFO - Epoch(train) [25][120/2119] lr: 4.0000e-02 eta: 1 day, 2:55:35 time: 0.3574 data_time: 0.0230 memory: 11108 grad_norm: 2.8689 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6849 loss: 2.6849 2022/10/09 11:06:31 - mmengine - INFO - Epoch(train) [25][140/2119] lr: 4.0000e-02 eta: 1 day, 2:55:27 time: 0.3585 data_time: 0.0195 memory: 11108 grad_norm: 2.8683 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4615 loss: 2.4615 2022/10/09 11:06:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 11:06:39 - mmengine - INFO - Epoch(train) [25][160/2119] lr: 4.0000e-02 eta: 1 day, 2:55:19 time: 0.3558 data_time: 0.0194 memory: 11108 grad_norm: 2.8688 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4569 loss: 2.4569 2022/10/09 11:06:46 - mmengine - INFO - Epoch(train) [25][180/2119] lr: 4.0000e-02 eta: 1 day, 2:55:12 time: 0.3633 data_time: 0.0186 memory: 11108 grad_norm: 2.8872 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6397 loss: 2.6397 2022/10/09 11:06:53 - mmengine - INFO - Epoch(train) [25][200/2119] lr: 4.0000e-02 eta: 1 day, 2:55:05 time: 0.3648 data_time: 0.0177 memory: 11108 grad_norm: 2.8920 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8903 loss: 2.8903 2022/10/09 11:07:00 - mmengine - INFO - Epoch(train) [25][220/2119] lr: 4.0000e-02 eta: 1 day, 2:54:57 time: 0.3558 data_time: 0.0218 memory: 11108 grad_norm: 2.8450 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7070 loss: 2.7070 2022/10/09 11:07:07 - mmengine - INFO - Epoch(train) [25][240/2119] lr: 4.0000e-02 eta: 1 day, 2:54:49 time: 0.3599 data_time: 0.0233 memory: 11108 grad_norm: 2.8826 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.5954 loss: 2.5954 2022/10/09 11:07:15 - mmengine - INFO - Epoch(train) [25][260/2119] lr: 4.0000e-02 eta: 1 day, 2:54:41 time: 0.3586 data_time: 0.0196 memory: 11108 grad_norm: 2.8339 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6596 loss: 2.6596 2022/10/09 11:07:22 - mmengine - INFO - Epoch(train) [25][280/2119] lr: 4.0000e-02 eta: 1 day, 2:54:34 time: 0.3635 data_time: 0.0192 memory: 11108 grad_norm: 2.8736 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7633 loss: 2.7633 2022/10/09 11:07:29 - mmengine - INFO - Epoch(train) [25][300/2119] lr: 4.0000e-02 eta: 1 day, 2:54:26 time: 0.3554 data_time: 0.0207 memory: 11108 grad_norm: 2.9053 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8763 loss: 2.8763 2022/10/09 11:07:36 - mmengine - INFO - Epoch(train) [25][320/2119] lr: 4.0000e-02 eta: 1 day, 2:54:19 time: 0.3657 data_time: 0.0204 memory: 11108 grad_norm: 2.9020 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6292 loss: 2.6292 2022/10/09 11:07:43 - mmengine - INFO - Epoch(train) [25][340/2119] lr: 4.0000e-02 eta: 1 day, 2:54:11 time: 0.3578 data_time: 0.0175 memory: 11108 grad_norm: 2.8337 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6142 loss: 2.6142 2022/10/09 11:07:51 - mmengine - INFO - Epoch(train) [25][360/2119] lr: 4.0000e-02 eta: 1 day, 2:54:04 time: 0.3590 data_time: 0.0230 memory: 11108 grad_norm: 2.8393 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5085 loss: 2.5085 2022/10/09 11:07:58 - mmengine - INFO - Epoch(train) [25][380/2119] lr: 4.0000e-02 eta: 1 day, 2:53:56 time: 0.3572 data_time: 0.0174 memory: 11108 grad_norm: 2.8738 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6637 loss: 2.6637 2022/10/09 11:08:05 - mmengine - INFO - Epoch(train) [25][400/2119] lr: 4.0000e-02 eta: 1 day, 2:53:48 time: 0.3564 data_time: 0.0213 memory: 11108 grad_norm: 2.8912 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6166 loss: 2.6166 2022/10/09 11:08:12 - mmengine - INFO - Epoch(train) [25][420/2119] lr: 4.0000e-02 eta: 1 day, 2:53:40 time: 0.3570 data_time: 0.0195 memory: 11108 grad_norm: 2.9217 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7373 loss: 2.7373 2022/10/09 11:08:19 - mmengine - INFO - Epoch(train) [25][440/2119] lr: 4.0000e-02 eta: 1 day, 2:53:32 time: 0.3602 data_time: 0.0181 memory: 11108 grad_norm: 2.8917 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6048 loss: 2.6048 2022/10/09 11:08:26 - mmengine - INFO - Epoch(train) [25][460/2119] lr: 4.0000e-02 eta: 1 day, 2:53:24 time: 0.3548 data_time: 0.0192 memory: 11108 grad_norm: 2.8940 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.3845 loss: 2.3845 2022/10/09 11:08:34 - mmengine - INFO - Epoch(train) [25][480/2119] lr: 4.0000e-02 eta: 1 day, 2:53:16 time: 0.3596 data_time: 0.0233 memory: 11108 grad_norm: 2.8939 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5890 loss: 2.5890 2022/10/09 11:08:41 - mmengine - INFO - Epoch(train) [25][500/2119] lr: 4.0000e-02 eta: 1 day, 2:53:08 time: 0.3560 data_time: 0.0201 memory: 11108 grad_norm: 2.8998 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5680 loss: 2.5680 2022/10/09 11:08:48 - mmengine - INFO - Epoch(train) [25][520/2119] lr: 4.0000e-02 eta: 1 day, 2:53:01 time: 0.3668 data_time: 0.0187 memory: 11108 grad_norm: 2.9024 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8967 loss: 2.8967 2022/10/09 11:08:55 - mmengine - INFO - Epoch(train) [25][540/2119] lr: 4.0000e-02 eta: 1 day, 2:52:54 time: 0.3571 data_time: 0.0195 memory: 11108 grad_norm: 2.8424 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4759 loss: 2.4759 2022/10/09 11:09:02 - mmengine - INFO - Epoch(train) [25][560/2119] lr: 4.0000e-02 eta: 1 day, 2:52:46 time: 0.3618 data_time: 0.0219 memory: 11108 grad_norm: 2.9412 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6746 loss: 2.6746 2022/10/09 11:09:10 - mmengine - INFO - Epoch(train) [25][580/2119] lr: 4.0000e-02 eta: 1 day, 2:52:38 time: 0.3571 data_time: 0.0198 memory: 11108 grad_norm: 2.9085 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7652 loss: 2.7652 2022/10/09 11:09:17 - mmengine - INFO - Epoch(train) [25][600/2119] lr: 4.0000e-02 eta: 1 day, 2:52:31 time: 0.3608 data_time: 0.0187 memory: 11108 grad_norm: 2.8457 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9209 loss: 2.9209 2022/10/09 11:09:24 - mmengine - INFO - Epoch(train) [25][620/2119] lr: 4.0000e-02 eta: 1 day, 2:52:23 time: 0.3632 data_time: 0.0169 memory: 11108 grad_norm: 2.8950 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7246 loss: 2.7246 2022/10/09 11:09:31 - mmengine - INFO - Epoch(train) [25][640/2119] lr: 4.0000e-02 eta: 1 day, 2:52:16 time: 0.3573 data_time: 0.0227 memory: 11108 grad_norm: 2.8799 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6259 loss: 2.6259 2022/10/09 11:09:38 - mmengine - INFO - Epoch(train) [25][660/2119] lr: 4.0000e-02 eta: 1 day, 2:52:08 time: 0.3562 data_time: 0.0209 memory: 11108 grad_norm: 2.8986 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6309 loss: 2.6309 2022/10/09 11:09:45 - mmengine - INFO - Epoch(train) [25][680/2119] lr: 4.0000e-02 eta: 1 day, 2:52:00 time: 0.3602 data_time: 0.0199 memory: 11108 grad_norm: 2.8860 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5995 loss: 2.5995 2022/10/09 11:09:53 - mmengine - INFO - Epoch(train) [25][700/2119] lr: 4.0000e-02 eta: 1 day, 2:51:52 time: 0.3571 data_time: 0.0198 memory: 11108 grad_norm: 2.9091 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6176 loss: 2.6176 2022/10/09 11:10:00 - mmengine - INFO - Epoch(train) [25][720/2119] lr: 4.0000e-02 eta: 1 day, 2:51:44 time: 0.3555 data_time: 0.0181 memory: 11108 grad_norm: 2.9549 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5870 loss: 2.5870 2022/10/09 11:10:07 - mmengine - INFO - Epoch(train) [25][740/2119] lr: 4.0000e-02 eta: 1 day, 2:51:38 time: 0.3740 data_time: 0.0190 memory: 11108 grad_norm: 2.9087 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7122 loss: 2.7122 2022/10/09 11:10:14 - mmengine - INFO - Epoch(train) [25][760/2119] lr: 4.0000e-02 eta: 1 day, 2:51:30 time: 0.3606 data_time: 0.0209 memory: 11108 grad_norm: 2.8942 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7555 loss: 2.7555 2022/10/09 11:10:22 - mmengine - INFO - Epoch(train) [25][780/2119] lr: 4.0000e-02 eta: 1 day, 2:51:22 time: 0.3560 data_time: 0.0181 memory: 11108 grad_norm: 2.8293 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.3718 loss: 2.3718 2022/10/09 11:10:29 - mmengine - INFO - Epoch(train) [25][800/2119] lr: 4.0000e-02 eta: 1 day, 2:51:15 time: 0.3585 data_time: 0.0207 memory: 11108 grad_norm: 2.8675 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7877 loss: 2.7877 2022/10/09 11:10:36 - mmengine - INFO - Epoch(train) [25][820/2119] lr: 4.0000e-02 eta: 1 day, 2:51:07 time: 0.3601 data_time: 0.0183 memory: 11108 grad_norm: 2.9187 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9263 loss: 2.9263 2022/10/09 11:10:43 - mmengine - INFO - Epoch(train) [25][840/2119] lr: 4.0000e-02 eta: 1 day, 2:50:59 time: 0.3575 data_time: 0.0189 memory: 11108 grad_norm: 2.8516 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5970 loss: 2.5970 2022/10/09 11:10:50 - mmengine - INFO - Epoch(train) [25][860/2119] lr: 4.0000e-02 eta: 1 day, 2:50:51 time: 0.3580 data_time: 0.0209 memory: 11108 grad_norm: 2.9198 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7501 loss: 2.7501 2022/10/09 11:10:57 - mmengine - INFO - Epoch(train) [25][880/2119] lr: 4.0000e-02 eta: 1 day, 2:50:43 time: 0.3560 data_time: 0.0248 memory: 11108 grad_norm: 2.9181 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7381 loss: 2.7381 2022/10/09 11:11:05 - mmengine - INFO - Epoch(train) [25][900/2119] lr: 4.0000e-02 eta: 1 day, 2:50:36 time: 0.3588 data_time: 0.0201 memory: 11108 grad_norm: 2.9435 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7634 loss: 2.7634 2022/10/09 11:11:12 - mmengine - INFO - Epoch(train) [25][920/2119] lr: 4.0000e-02 eta: 1 day, 2:50:28 time: 0.3571 data_time: 0.0257 memory: 11108 grad_norm: 2.8789 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5668 loss: 2.5668 2022/10/09 11:11:19 - mmengine - INFO - Epoch(train) [25][940/2119] lr: 4.0000e-02 eta: 1 day, 2:50:20 time: 0.3537 data_time: 0.0189 memory: 11108 grad_norm: 2.9312 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.3696 loss: 2.3696 2022/10/09 11:11:26 - mmengine - INFO - Epoch(train) [25][960/2119] lr: 4.0000e-02 eta: 1 day, 2:50:12 time: 0.3583 data_time: 0.0196 memory: 11108 grad_norm: 2.8748 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8689 loss: 2.8689 2022/10/09 11:11:33 - mmengine - INFO - Epoch(train) [25][980/2119] lr: 4.0000e-02 eta: 1 day, 2:50:04 time: 0.3579 data_time: 0.0188 memory: 11108 grad_norm: 2.9160 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4493 loss: 2.4493 2022/10/09 11:11:40 - mmengine - INFO - Epoch(train) [25][1000/2119] lr: 4.0000e-02 eta: 1 day, 2:49:57 time: 0.3607 data_time: 0.0237 memory: 11108 grad_norm: 2.8797 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.3932 loss: 2.3932 2022/10/09 11:11:47 - mmengine - INFO - Epoch(train) [25][1020/2119] lr: 4.0000e-02 eta: 1 day, 2:49:49 time: 0.3567 data_time: 0.0195 memory: 11108 grad_norm: 2.8866 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5573 loss: 2.5573 2022/10/09 11:11:55 - mmengine - INFO - Epoch(train) [25][1040/2119] lr: 4.0000e-02 eta: 1 day, 2:49:42 time: 0.3644 data_time: 0.0190 memory: 11108 grad_norm: 2.9365 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7528 loss: 2.7528 2022/10/09 11:12:02 - mmengine - INFO - Epoch(train) [25][1060/2119] lr: 4.0000e-02 eta: 1 day, 2:49:33 time: 0.3555 data_time: 0.0220 memory: 11108 grad_norm: 2.8656 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6053 loss: 2.6053 2022/10/09 11:12:09 - mmengine - INFO - Epoch(train) [25][1080/2119] lr: 4.0000e-02 eta: 1 day, 2:49:26 time: 0.3574 data_time: 0.0253 memory: 11108 grad_norm: 2.8958 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5662 loss: 2.5662 2022/10/09 11:12:16 - mmengine - INFO - Epoch(train) [25][1100/2119] lr: 4.0000e-02 eta: 1 day, 2:49:19 time: 0.3695 data_time: 0.0188 memory: 11108 grad_norm: 2.9359 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5854 loss: 2.5854 2022/10/09 11:12:24 - mmengine - INFO - Epoch(train) [25][1120/2119] lr: 4.0000e-02 eta: 1 day, 2:49:11 time: 0.3595 data_time: 0.0184 memory: 11108 grad_norm: 2.8321 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.4409 loss: 2.4409 2022/10/09 11:12:31 - mmengine - INFO - Epoch(train) [25][1140/2119] lr: 4.0000e-02 eta: 1 day, 2:49:03 time: 0.3571 data_time: 0.0198 memory: 11108 grad_norm: 2.8454 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6829 loss: 2.6829 2022/10/09 11:12:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 11:12:38 - mmengine - INFO - Epoch(train) [25][1160/2119] lr: 4.0000e-02 eta: 1 day, 2:48:56 time: 0.3623 data_time: 0.0210 memory: 11108 grad_norm: 2.8477 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7997 loss: 2.7997 2022/10/09 11:12:45 - mmengine - INFO - Epoch(train) [25][1180/2119] lr: 4.0000e-02 eta: 1 day, 2:48:48 time: 0.3538 data_time: 0.0217 memory: 11108 grad_norm: 2.9071 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.4728 loss: 2.4728 2022/10/09 11:12:52 - mmengine - INFO - Epoch(train) [25][1200/2119] lr: 4.0000e-02 eta: 1 day, 2:48:40 time: 0.3565 data_time: 0.0186 memory: 11108 grad_norm: 2.8589 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.4751 loss: 2.4751 2022/10/09 11:12:59 - mmengine - INFO - Epoch(train) [25][1220/2119] lr: 4.0000e-02 eta: 1 day, 2:48:32 time: 0.3569 data_time: 0.0217 memory: 11108 grad_norm: 2.8601 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4812 loss: 2.4812 2022/10/09 11:13:06 - mmengine - INFO - Epoch(train) [25][1240/2119] lr: 4.0000e-02 eta: 1 day, 2:48:24 time: 0.3578 data_time: 0.0201 memory: 11108 grad_norm: 2.8842 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4762 loss: 2.4762 2022/10/09 11:13:14 - mmengine - INFO - Epoch(train) [25][1260/2119] lr: 4.0000e-02 eta: 1 day, 2:48:17 time: 0.3642 data_time: 0.0232 memory: 11108 grad_norm: 2.9185 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6194 loss: 2.6194 2022/10/09 11:13:21 - mmengine - INFO - Epoch(train) [25][1280/2119] lr: 4.0000e-02 eta: 1 day, 2:48:09 time: 0.3572 data_time: 0.0221 memory: 11108 grad_norm: 2.9130 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5772 loss: 2.5772 2022/10/09 11:13:28 - mmengine - INFO - Epoch(train) [25][1300/2119] lr: 4.0000e-02 eta: 1 day, 2:48:02 time: 0.3584 data_time: 0.0233 memory: 11108 grad_norm: 2.8529 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6141 loss: 2.6141 2022/10/09 11:13:35 - mmengine - INFO - Epoch(train) [25][1320/2119] lr: 4.0000e-02 eta: 1 day, 2:47:54 time: 0.3592 data_time: 0.0207 memory: 11108 grad_norm: 2.9052 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.3316 loss: 2.3316 2022/10/09 11:13:43 - mmengine - INFO - Epoch(train) [25][1340/2119] lr: 4.0000e-02 eta: 1 day, 2:47:47 time: 0.3667 data_time: 0.0185 memory: 11108 grad_norm: 2.9201 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6322 loss: 2.6322 2022/10/09 11:13:50 - mmengine - INFO - Epoch(train) [25][1360/2119] lr: 4.0000e-02 eta: 1 day, 2:47:39 time: 0.3544 data_time: 0.0192 memory: 11108 grad_norm: 2.9098 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5899 loss: 2.5899 2022/10/09 11:13:57 - mmengine - INFO - Epoch(train) [25][1380/2119] lr: 4.0000e-02 eta: 1 day, 2:47:31 time: 0.3615 data_time: 0.0226 memory: 11108 grad_norm: 2.9689 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5315 loss: 2.5315 2022/10/09 11:14:04 - mmengine - INFO - Epoch(train) [25][1400/2119] lr: 4.0000e-02 eta: 1 day, 2:47:23 time: 0.3570 data_time: 0.0165 memory: 11108 grad_norm: 2.8812 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6958 loss: 2.6958 2022/10/09 11:14:11 - mmengine - INFO - Epoch(train) [25][1420/2119] lr: 4.0000e-02 eta: 1 day, 2:47:16 time: 0.3593 data_time: 0.0221 memory: 11108 grad_norm: 2.8458 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5965 loss: 2.5965 2022/10/09 11:14:18 - mmengine - INFO - Epoch(train) [25][1440/2119] lr: 4.0000e-02 eta: 1 day, 2:47:08 time: 0.3585 data_time: 0.0220 memory: 11108 grad_norm: 2.9270 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.7657 loss: 2.7657 2022/10/09 11:14:26 - mmengine - INFO - Epoch(train) [25][1460/2119] lr: 4.0000e-02 eta: 1 day, 2:47:01 time: 0.3689 data_time: 0.0201 memory: 11108 grad_norm: 2.8773 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.2568 loss: 2.2568 2022/10/09 11:14:33 - mmengine - INFO - Epoch(train) [25][1480/2119] lr: 4.0000e-02 eta: 1 day, 2:46:54 time: 0.3637 data_time: 0.0188 memory: 11108 grad_norm: 2.8815 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5751 loss: 2.5751 2022/10/09 11:14:40 - mmengine - INFO - Epoch(train) [25][1500/2119] lr: 4.0000e-02 eta: 1 day, 2:46:46 time: 0.3538 data_time: 0.0213 memory: 11108 grad_norm: 2.8813 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6778 loss: 2.6778 2022/10/09 11:14:47 - mmengine - INFO - Epoch(train) [25][1520/2119] lr: 4.0000e-02 eta: 1 day, 2:46:38 time: 0.3581 data_time: 0.0202 memory: 11108 grad_norm: 2.8649 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5874 loss: 2.5874 2022/10/09 11:14:55 - mmengine - INFO - Epoch(train) [25][1540/2119] lr: 4.0000e-02 eta: 1 day, 2:46:31 time: 0.3671 data_time: 0.0178 memory: 11108 grad_norm: 2.9279 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5813 loss: 2.5813 2022/10/09 11:15:02 - mmengine - INFO - Epoch(train) [25][1560/2119] lr: 4.0000e-02 eta: 1 day, 2:46:23 time: 0.3528 data_time: 0.0185 memory: 11108 grad_norm: 2.9201 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7502 loss: 2.7502 2022/10/09 11:15:09 - mmengine - INFO - Epoch(train) [25][1580/2119] lr: 4.0000e-02 eta: 1 day, 2:46:15 time: 0.3585 data_time: 0.0171 memory: 11108 grad_norm: 2.8938 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8380 loss: 2.8380 2022/10/09 11:15:16 - mmengine - INFO - Epoch(train) [25][1600/2119] lr: 4.0000e-02 eta: 1 day, 2:46:08 time: 0.3645 data_time: 0.0184 memory: 11108 grad_norm: 2.9021 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6679 loss: 2.6679 2022/10/09 11:15:23 - mmengine - INFO - Epoch(train) [25][1620/2119] lr: 4.0000e-02 eta: 1 day, 2:46:00 time: 0.3552 data_time: 0.0185 memory: 11108 grad_norm: 2.9472 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6136 loss: 2.6136 2022/10/09 11:15:30 - mmengine - INFO - Epoch(train) [25][1640/2119] lr: 4.0000e-02 eta: 1 day, 2:45:53 time: 0.3595 data_time: 0.0199 memory: 11108 grad_norm: 2.9106 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7845 loss: 2.7845 2022/10/09 11:15:38 - mmengine - INFO - Epoch(train) [25][1660/2119] lr: 4.0000e-02 eta: 1 day, 2:45:45 time: 0.3627 data_time: 0.0208 memory: 11108 grad_norm: 2.9118 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.5103 loss: 2.5103 2022/10/09 11:15:45 - mmengine - INFO - Epoch(train) [25][1680/2119] lr: 4.0000e-02 eta: 1 day, 2:45:37 time: 0.3548 data_time: 0.0189 memory: 11108 grad_norm: 2.9099 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8761 loss: 2.8761 2022/10/09 11:15:52 - mmengine - INFO - Epoch(train) [25][1700/2119] lr: 4.0000e-02 eta: 1 day, 2:45:29 time: 0.3568 data_time: 0.0199 memory: 11108 grad_norm: 2.8661 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5172 loss: 2.5172 2022/10/09 11:15:59 - mmengine - INFO - Epoch(train) [25][1720/2119] lr: 4.0000e-02 eta: 1 day, 2:45:22 time: 0.3594 data_time: 0.0219 memory: 11108 grad_norm: 2.9389 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5010 loss: 2.5010 2022/10/09 11:16:06 - mmengine - INFO - Epoch(train) [25][1740/2119] lr: 4.0000e-02 eta: 1 day, 2:45:14 time: 0.3579 data_time: 0.0208 memory: 11108 grad_norm: 2.8928 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8363 loss: 2.8363 2022/10/09 11:16:14 - mmengine - INFO - Epoch(train) [25][1760/2119] lr: 4.0000e-02 eta: 1 day, 2:45:06 time: 0.3604 data_time: 0.0219 memory: 11108 grad_norm: 2.9002 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4963 loss: 2.4963 2022/10/09 11:16:21 - mmengine - INFO - Epoch(train) [25][1780/2119] lr: 4.0000e-02 eta: 1 day, 2:44:58 time: 0.3561 data_time: 0.0221 memory: 11108 grad_norm: 2.9050 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7018 loss: 2.7018 2022/10/09 11:16:28 - mmengine - INFO - Epoch(train) [25][1800/2119] lr: 4.0000e-02 eta: 1 day, 2:44:51 time: 0.3585 data_time: 0.0213 memory: 11108 grad_norm: 2.9086 top1_acc: 0.1875 top5_acc: 0.7500 loss_cls: 2.4296 loss: 2.4296 2022/10/09 11:16:35 - mmengine - INFO - Epoch(train) [25][1820/2119] lr: 4.0000e-02 eta: 1 day, 2:44:43 time: 0.3603 data_time: 0.0207 memory: 11108 grad_norm: 2.8839 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8868 loss: 2.8868 2022/10/09 11:16:42 - mmengine - INFO - Epoch(train) [25][1840/2119] lr: 4.0000e-02 eta: 1 day, 2:44:36 time: 0.3623 data_time: 0.0209 memory: 11108 grad_norm: 2.8540 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6169 loss: 2.6169 2022/10/09 11:16:49 - mmengine - INFO - Epoch(train) [25][1860/2119] lr: 4.0000e-02 eta: 1 day, 2:44:27 time: 0.3537 data_time: 0.0196 memory: 11108 grad_norm: 2.8903 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6961 loss: 2.6961 2022/10/09 11:16:57 - mmengine - INFO - Epoch(train) [25][1880/2119] lr: 4.0000e-02 eta: 1 day, 2:44:20 time: 0.3608 data_time: 0.0207 memory: 11108 grad_norm: 2.8668 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6873 loss: 2.6873 2022/10/09 11:17:04 - mmengine - INFO - Epoch(train) [25][1900/2119] lr: 4.0000e-02 eta: 1 day, 2:44:12 time: 0.3562 data_time: 0.0221 memory: 11108 grad_norm: 2.8529 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7093 loss: 2.7093 2022/10/09 11:17:11 - mmengine - INFO - Epoch(train) [25][1920/2119] lr: 4.0000e-02 eta: 1 day, 2:44:04 time: 0.3572 data_time: 0.0207 memory: 11108 grad_norm: 2.8837 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7308 loss: 2.7308 2022/10/09 11:17:18 - mmengine - INFO - Epoch(train) [25][1940/2119] lr: 4.0000e-02 eta: 1 day, 2:43:57 time: 0.3621 data_time: 0.0205 memory: 11108 grad_norm: 2.9516 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8007 loss: 2.8007 2022/10/09 11:17:25 - mmengine - INFO - Epoch(train) [25][1960/2119] lr: 4.0000e-02 eta: 1 day, 2:43:49 time: 0.3580 data_time: 0.0203 memory: 11108 grad_norm: 2.8456 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8367 loss: 2.8367 2022/10/09 11:17:33 - mmengine - INFO - Epoch(train) [25][1980/2119] lr: 4.0000e-02 eta: 1 day, 2:43:42 time: 0.3644 data_time: 0.0218 memory: 11108 grad_norm: 2.8479 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5218 loss: 2.5218 2022/10/09 11:17:40 - mmengine - INFO - Epoch(train) [25][2000/2119] lr: 4.0000e-02 eta: 1 day, 2:43:34 time: 0.3542 data_time: 0.0198 memory: 11108 grad_norm: 2.9107 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7249 loss: 2.7249 2022/10/09 11:17:47 - mmengine - INFO - Epoch(train) [25][2020/2119] lr: 4.0000e-02 eta: 1 day, 2:43:26 time: 0.3575 data_time: 0.0220 memory: 11108 grad_norm: 2.8710 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5867 loss: 2.5867 2022/10/09 11:17:54 - mmengine - INFO - Epoch(train) [25][2040/2119] lr: 4.0000e-02 eta: 1 day, 2:43:18 time: 0.3596 data_time: 0.0223 memory: 11108 grad_norm: 2.8875 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6518 loss: 2.6518 2022/10/09 11:18:01 - mmengine - INFO - Epoch(train) [25][2060/2119] lr: 4.0000e-02 eta: 1 day, 2:43:10 time: 0.3571 data_time: 0.0247 memory: 11108 grad_norm: 2.8684 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4507 loss: 2.4507 2022/10/09 11:18:08 - mmengine - INFO - Epoch(train) [25][2080/2119] lr: 4.0000e-02 eta: 1 day, 2:43:03 time: 0.3576 data_time: 0.0198 memory: 11108 grad_norm: 2.9432 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5726 loss: 2.5726 2022/10/09 11:18:16 - mmengine - INFO - Epoch(train) [25][2100/2119] lr: 4.0000e-02 eta: 1 day, 2:42:55 time: 0.3626 data_time: 0.0171 memory: 11108 grad_norm: 2.8625 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5700 loss: 2.5700 2022/10/09 11:18:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 11:18:22 - mmengine - INFO - Epoch(train) [25][2119/2119] lr: 4.0000e-02 eta: 1 day, 2:42:55 time: 0.3426 data_time: 0.0182 memory: 11108 grad_norm: 2.9297 top1_acc: 0.5000 top5_acc: 0.7000 loss_cls: 2.5666 loss: 2.5666 2022/10/09 11:18:29 - mmengine - INFO - Epoch(val) [25][20/137] eta: 0:00:41 time: 0.3583 data_time: 0.2393 memory: 1961 2022/10/09 11:18:34 - mmengine - INFO - Epoch(val) [25][40/137] eta: 0:00:25 time: 0.2614 data_time: 0.1451 memory: 1961 2022/10/09 11:18:40 - mmengine - INFO - Epoch(val) [25][60/137] eta: 0:00:22 time: 0.2869 data_time: 0.1721 memory: 1961 2022/10/09 11:18:45 - mmengine - INFO - Epoch(val) [25][80/137] eta: 0:00:13 time: 0.2371 data_time: 0.1227 memory: 1961 2022/10/09 11:18:51 - mmengine - INFO - Epoch(val) [25][100/137] eta: 0:00:10 time: 0.2781 data_time: 0.1644 memory: 1961 2022/10/09 11:18:55 - mmengine - INFO - Epoch(val) [25][120/137] eta: 0:00:03 time: 0.2211 data_time: 0.1065 memory: 1961 2022/10/09 11:19:11 - mmengine - INFO - Epoch(val) [25][137/137] acc/top1: 0.4430 acc/top5: 0.6875 acc/mean1: 0.4428 2022/10/09 11:19:21 - mmengine - INFO - Epoch(train) [26][20/2119] lr: 4.0000e-02 eta: 1 day, 2:42:21 time: 0.5094 data_time: 0.1364 memory: 11108 grad_norm: 2.9367 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5679 loss: 2.5679 2022/10/09 11:19:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 11:19:28 - mmengine - INFO - Epoch(train) [26][40/2119] lr: 4.0000e-02 eta: 1 day, 2:42:14 time: 0.3633 data_time: 0.0238 memory: 11108 grad_norm: 2.9173 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7186 loss: 2.7186 2022/10/09 11:19:36 - mmengine - INFO - Epoch(train) [26][60/2119] lr: 4.0000e-02 eta: 1 day, 2:42:07 time: 0.3645 data_time: 0.0230 memory: 11108 grad_norm: 2.8592 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4564 loss: 2.4564 2022/10/09 11:19:43 - mmengine - INFO - Epoch(train) [26][80/2119] lr: 4.0000e-02 eta: 1 day, 2:41:59 time: 0.3598 data_time: 0.0209 memory: 11108 grad_norm: 2.8585 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6145 loss: 2.6145 2022/10/09 11:19:50 - mmengine - INFO - Epoch(train) [26][100/2119] lr: 4.0000e-02 eta: 1 day, 2:41:52 time: 0.3571 data_time: 0.0284 memory: 11108 grad_norm: 2.8725 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5488 loss: 2.5488 2022/10/09 11:19:57 - mmengine - INFO - Epoch(train) [26][120/2119] lr: 4.0000e-02 eta: 1 day, 2:41:44 time: 0.3604 data_time: 0.0231 memory: 11108 grad_norm: 2.8650 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7398 loss: 2.7398 2022/10/09 11:20:05 - mmengine - INFO - Epoch(train) [26][140/2119] lr: 4.0000e-02 eta: 1 day, 2:41:37 time: 0.3687 data_time: 0.0215 memory: 11108 grad_norm: 2.9214 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4274 loss: 2.4274 2022/10/09 11:20:12 - mmengine - INFO - Epoch(train) [26][160/2119] lr: 4.0000e-02 eta: 1 day, 2:41:29 time: 0.3552 data_time: 0.0219 memory: 11108 grad_norm: 2.9638 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8690 loss: 2.8690 2022/10/09 11:20:19 - mmengine - INFO - Epoch(train) [26][180/2119] lr: 4.0000e-02 eta: 1 day, 2:41:22 time: 0.3613 data_time: 0.0191 memory: 11108 grad_norm: 2.8959 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3858 loss: 2.3858 2022/10/09 11:20:26 - mmengine - INFO - Epoch(train) [26][200/2119] lr: 4.0000e-02 eta: 1 day, 2:41:15 time: 0.3619 data_time: 0.0220 memory: 11108 grad_norm: 2.8585 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7065 loss: 2.7065 2022/10/09 11:20:33 - mmengine - INFO - Epoch(train) [26][220/2119] lr: 4.0000e-02 eta: 1 day, 2:41:07 time: 0.3600 data_time: 0.0223 memory: 11108 grad_norm: 2.9027 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.4619 loss: 2.4619 2022/10/09 11:20:40 - mmengine - INFO - Epoch(train) [26][240/2119] lr: 4.0000e-02 eta: 1 day, 2:40:59 time: 0.3577 data_time: 0.0203 memory: 11108 grad_norm: 2.8883 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7168 loss: 2.7168 2022/10/09 11:20:48 - mmengine - INFO - Epoch(train) [26][260/2119] lr: 4.0000e-02 eta: 1 day, 2:40:52 time: 0.3588 data_time: 0.0199 memory: 11108 grad_norm: 2.8492 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6112 loss: 2.6112 2022/10/09 11:20:55 - mmengine - INFO - Epoch(train) [26][280/2119] lr: 4.0000e-02 eta: 1 day, 2:40:44 time: 0.3597 data_time: 0.0219 memory: 11108 grad_norm: 2.8281 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6793 loss: 2.6793 2022/10/09 11:21:02 - mmengine - INFO - Epoch(train) [26][300/2119] lr: 4.0000e-02 eta: 1 day, 2:40:36 time: 0.3534 data_time: 0.0193 memory: 11108 grad_norm: 2.9103 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6947 loss: 2.6947 2022/10/09 11:21:09 - mmengine - INFO - Epoch(train) [26][320/2119] lr: 4.0000e-02 eta: 1 day, 2:40:28 time: 0.3555 data_time: 0.0188 memory: 11108 grad_norm: 2.8988 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.4180 loss: 2.4180 2022/10/09 11:21:16 - mmengine - INFO - Epoch(train) [26][340/2119] lr: 4.0000e-02 eta: 1 day, 2:40:20 time: 0.3630 data_time: 0.0202 memory: 11108 grad_norm: 2.9351 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.3465 loss: 2.3465 2022/10/09 11:21:23 - mmengine - INFO - Epoch(train) [26][360/2119] lr: 4.0000e-02 eta: 1 day, 2:40:13 time: 0.3569 data_time: 0.0179 memory: 11108 grad_norm: 2.9035 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4233 loss: 2.4233 2022/10/09 11:21:31 - mmengine - INFO - Epoch(train) [26][380/2119] lr: 4.0000e-02 eta: 1 day, 2:40:05 time: 0.3561 data_time: 0.0228 memory: 11108 grad_norm: 2.8938 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7750 loss: 2.7750 2022/10/09 11:21:38 - mmengine - INFO - Epoch(train) [26][400/2119] lr: 4.0000e-02 eta: 1 day, 2:39:57 time: 0.3595 data_time: 0.0209 memory: 11108 grad_norm: 2.9256 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6444 loss: 2.6444 2022/10/09 11:21:45 - mmengine - INFO - Epoch(train) [26][420/2119] lr: 4.0000e-02 eta: 1 day, 2:39:49 time: 0.3545 data_time: 0.0200 memory: 11108 grad_norm: 2.9335 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5835 loss: 2.5835 2022/10/09 11:21:52 - mmengine - INFO - Epoch(train) [26][440/2119] lr: 4.0000e-02 eta: 1 day, 2:39:41 time: 0.3589 data_time: 0.0189 memory: 11108 grad_norm: 2.8645 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5362 loss: 2.5362 2022/10/09 11:21:59 - mmengine - INFO - Epoch(train) [26][460/2119] lr: 4.0000e-02 eta: 1 day, 2:39:33 time: 0.3563 data_time: 0.0162 memory: 11108 grad_norm: 2.9053 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.5423 loss: 2.5423 2022/10/09 11:22:07 - mmengine - INFO - Epoch(train) [26][480/2119] lr: 4.0000e-02 eta: 1 day, 2:39:27 time: 0.3704 data_time: 0.0202 memory: 11108 grad_norm: 2.9670 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.3724 loss: 2.3724 2022/10/09 11:22:14 - mmengine - INFO - Epoch(train) [26][500/2119] lr: 4.0000e-02 eta: 1 day, 2:39:19 time: 0.3564 data_time: 0.0198 memory: 11108 grad_norm: 2.9438 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7365 loss: 2.7365 2022/10/09 11:22:21 - mmengine - INFO - Epoch(train) [26][520/2119] lr: 4.0000e-02 eta: 1 day, 2:39:11 time: 0.3574 data_time: 0.0222 memory: 11108 grad_norm: 2.8804 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7292 loss: 2.7292 2022/10/09 11:22:28 - mmengine - INFO - Epoch(train) [26][540/2119] lr: 4.0000e-02 eta: 1 day, 2:39:03 time: 0.3555 data_time: 0.0221 memory: 11108 grad_norm: 2.9608 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6836 loss: 2.6836 2022/10/09 11:22:35 - mmengine - INFO - Epoch(train) [26][560/2119] lr: 4.0000e-02 eta: 1 day, 2:38:56 time: 0.3598 data_time: 0.0240 memory: 11108 grad_norm: 2.9164 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7327 loss: 2.7327 2022/10/09 11:22:42 - mmengine - INFO - Epoch(train) [26][580/2119] lr: 4.0000e-02 eta: 1 day, 2:38:48 time: 0.3560 data_time: 0.0172 memory: 11108 grad_norm: 2.8797 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5184 loss: 2.5184 2022/10/09 11:22:49 - mmengine - INFO - Epoch(train) [26][600/2119] lr: 4.0000e-02 eta: 1 day, 2:38:40 time: 0.3606 data_time: 0.0190 memory: 11108 grad_norm: 2.9202 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5795 loss: 2.5795 2022/10/09 11:22:57 - mmengine - INFO - Epoch(train) [26][620/2119] lr: 4.0000e-02 eta: 1 day, 2:38:33 time: 0.3618 data_time: 0.0199 memory: 11108 grad_norm: 2.8372 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7641 loss: 2.7641 2022/10/09 11:23:04 - mmengine - INFO - Epoch(train) [26][640/2119] lr: 4.0000e-02 eta: 1 day, 2:38:25 time: 0.3597 data_time: 0.0269 memory: 11108 grad_norm: 2.9084 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8461 loss: 2.8461 2022/10/09 11:23:11 - mmengine - INFO - Epoch(train) [26][660/2119] lr: 4.0000e-02 eta: 1 day, 2:38:18 time: 0.3620 data_time: 0.0204 memory: 11108 grad_norm: 2.8662 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.4768 loss: 2.4768 2022/10/09 11:23:18 - mmengine - INFO - Epoch(train) [26][680/2119] lr: 4.0000e-02 eta: 1 day, 2:38:10 time: 0.3550 data_time: 0.0212 memory: 11108 grad_norm: 2.9284 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9751 loss: 2.9751 2022/10/09 11:23:25 - mmengine - INFO - Epoch(train) [26][700/2119] lr: 4.0000e-02 eta: 1 day, 2:38:02 time: 0.3595 data_time: 0.0194 memory: 11108 grad_norm: 2.9301 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4810 loss: 2.4810 2022/10/09 11:23:33 - mmengine - INFO - Epoch(train) [26][720/2119] lr: 4.0000e-02 eta: 1 day, 2:37:54 time: 0.3554 data_time: 0.0190 memory: 11108 grad_norm: 2.8974 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7145 loss: 2.7145 2022/10/09 11:23:40 - mmengine - INFO - Epoch(train) [26][740/2119] lr: 4.0000e-02 eta: 1 day, 2:37:47 time: 0.3591 data_time: 0.0214 memory: 11108 grad_norm: 2.8981 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4856 loss: 2.4856 2022/10/09 11:23:47 - mmengine - INFO - Epoch(train) [26][760/2119] lr: 4.0000e-02 eta: 1 day, 2:37:38 time: 0.3547 data_time: 0.0195 memory: 11108 grad_norm: 2.9691 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6780 loss: 2.6780 2022/10/09 11:23:54 - mmengine - INFO - Epoch(train) [26][780/2119] lr: 4.0000e-02 eta: 1 day, 2:37:31 time: 0.3578 data_time: 0.0263 memory: 11108 grad_norm: 2.9140 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1212 loss: 2.1212 2022/10/09 11:24:01 - mmengine - INFO - Epoch(train) [26][800/2119] lr: 4.0000e-02 eta: 1 day, 2:37:23 time: 0.3552 data_time: 0.0202 memory: 11108 grad_norm: 2.8551 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6534 loss: 2.6534 2022/10/09 11:24:08 - mmengine - INFO - Epoch(train) [26][820/2119] lr: 4.0000e-02 eta: 1 day, 2:37:15 time: 0.3580 data_time: 0.0197 memory: 11108 grad_norm: 2.8679 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6855 loss: 2.6855 2022/10/09 11:24:15 - mmengine - INFO - Epoch(train) [26][840/2119] lr: 4.0000e-02 eta: 1 day, 2:37:07 time: 0.3571 data_time: 0.0207 memory: 11108 grad_norm: 2.9488 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.5173 loss: 2.5173 2022/10/09 11:24:23 - mmengine - INFO - Epoch(train) [26][860/2119] lr: 4.0000e-02 eta: 1 day, 2:37:00 time: 0.3634 data_time: 0.0217 memory: 11108 grad_norm: 2.9435 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6026 loss: 2.6026 2022/10/09 11:24:30 - mmengine - INFO - Epoch(train) [26][880/2119] lr: 4.0000e-02 eta: 1 day, 2:36:52 time: 0.3590 data_time: 0.0198 memory: 11108 grad_norm: 2.9375 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4431 loss: 2.4431 2022/10/09 11:24:37 - mmengine - INFO - Epoch(train) [26][900/2119] lr: 4.0000e-02 eta: 1 day, 2:36:45 time: 0.3591 data_time: 0.0202 memory: 11108 grad_norm: 2.9536 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6068 loss: 2.6068 2022/10/09 11:24:44 - mmengine - INFO - Epoch(train) [26][920/2119] lr: 4.0000e-02 eta: 1 day, 2:36:37 time: 0.3612 data_time: 0.0193 memory: 11108 grad_norm: 2.9462 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6325 loss: 2.6325 2022/10/09 11:24:51 - mmengine - INFO - Epoch(train) [26][940/2119] lr: 4.0000e-02 eta: 1 day, 2:36:29 time: 0.3551 data_time: 0.0213 memory: 11108 grad_norm: 2.8816 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.4363 loss: 2.4363 2022/10/09 11:24:59 - mmengine - INFO - Epoch(train) [26][960/2119] lr: 4.0000e-02 eta: 1 day, 2:36:21 time: 0.3586 data_time: 0.0221 memory: 11108 grad_norm: 2.8877 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5206 loss: 2.5206 2022/10/09 11:25:06 - mmengine - INFO - Epoch(train) [26][980/2119] lr: 4.0000e-02 eta: 1 day, 2:36:14 time: 0.3643 data_time: 0.0169 memory: 11108 grad_norm: 2.9964 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9811 loss: 2.9811 2022/10/09 11:25:13 - mmengine - INFO - Epoch(train) [26][1000/2119] lr: 4.0000e-02 eta: 1 day, 2:36:06 time: 0.3562 data_time: 0.0236 memory: 11108 grad_norm: 2.9372 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7693 loss: 2.7693 2022/10/09 11:25:20 - mmengine - INFO - Epoch(train) [26][1020/2119] lr: 4.0000e-02 eta: 1 day, 2:35:59 time: 0.3636 data_time: 0.0208 memory: 11108 grad_norm: 2.9361 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6378 loss: 2.6378 2022/10/09 11:25:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 11:25:27 - mmengine - INFO - Epoch(train) [26][1040/2119] lr: 4.0000e-02 eta: 1 day, 2:35:52 time: 0.3604 data_time: 0.0181 memory: 11108 grad_norm: 2.9344 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4713 loss: 2.4713 2022/10/09 11:25:35 - mmengine - INFO - Epoch(train) [26][1060/2119] lr: 4.0000e-02 eta: 1 day, 2:35:44 time: 0.3577 data_time: 0.0183 memory: 11108 grad_norm: 2.8554 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7325 loss: 2.7325 2022/10/09 11:25:42 - mmengine - INFO - Epoch(train) [26][1080/2119] lr: 4.0000e-02 eta: 1 day, 2:35:36 time: 0.3550 data_time: 0.0203 memory: 11108 grad_norm: 2.9665 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.4795 loss: 2.4795 2022/10/09 11:25:49 - mmengine - INFO - Epoch(train) [26][1100/2119] lr: 4.0000e-02 eta: 1 day, 2:35:29 time: 0.3662 data_time: 0.0236 memory: 11108 grad_norm: 2.9220 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5664 loss: 2.5664 2022/10/09 11:25:56 - mmengine - INFO - Epoch(train) [26][1120/2119] lr: 4.0000e-02 eta: 1 day, 2:35:21 time: 0.3565 data_time: 0.0195 memory: 11108 grad_norm: 2.9271 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7459 loss: 2.7459 2022/10/09 11:26:03 - mmengine - INFO - Epoch(train) [26][1140/2119] lr: 4.0000e-02 eta: 1 day, 2:35:13 time: 0.3580 data_time: 0.0212 memory: 11108 grad_norm: 2.8447 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8431 loss: 2.8431 2022/10/09 11:26:10 - mmengine - INFO - Epoch(train) [26][1160/2119] lr: 4.0000e-02 eta: 1 day, 2:35:06 time: 0.3575 data_time: 0.0204 memory: 11108 grad_norm: 2.8606 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5222 loss: 2.5222 2022/10/09 11:26:18 - mmengine - INFO - Epoch(train) [26][1180/2119] lr: 4.0000e-02 eta: 1 day, 2:34:58 time: 0.3565 data_time: 0.0239 memory: 11108 grad_norm: 2.9120 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6661 loss: 2.6661 2022/10/09 11:26:25 - mmengine - INFO - Epoch(train) [26][1200/2119] lr: 4.0000e-02 eta: 1 day, 2:34:51 time: 0.3679 data_time: 0.0212 memory: 11108 grad_norm: 2.9492 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7652 loss: 2.7652 2022/10/09 11:26:32 - mmengine - INFO - Epoch(train) [26][1220/2119] lr: 4.0000e-02 eta: 1 day, 2:34:43 time: 0.3607 data_time: 0.0184 memory: 11108 grad_norm: 2.8991 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6152 loss: 2.6152 2022/10/09 11:26:40 - mmengine - INFO - Epoch(train) [26][1240/2119] lr: 4.0000e-02 eta: 1 day, 2:34:37 time: 0.3717 data_time: 0.0204 memory: 11108 grad_norm: 2.8397 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8751 loss: 2.8751 2022/10/09 11:26:47 - mmengine - INFO - Epoch(train) [26][1260/2119] lr: 4.0000e-02 eta: 1 day, 2:34:29 time: 0.3551 data_time: 0.0210 memory: 11108 grad_norm: 2.9036 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7841 loss: 2.7841 2022/10/09 11:26:54 - mmengine - INFO - Epoch(train) [26][1280/2119] lr: 4.0000e-02 eta: 1 day, 2:34:21 time: 0.3587 data_time: 0.0196 memory: 11108 grad_norm: 2.9475 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6715 loss: 2.6715 2022/10/09 11:27:01 - mmengine - INFO - Epoch(train) [26][1300/2119] lr: 4.0000e-02 eta: 1 day, 2:34:13 time: 0.3566 data_time: 0.0225 memory: 11108 grad_norm: 2.9015 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6153 loss: 2.6153 2022/10/09 11:27:08 - mmengine - INFO - Epoch(train) [26][1320/2119] lr: 4.0000e-02 eta: 1 day, 2:34:06 time: 0.3623 data_time: 0.0207 memory: 11108 grad_norm: 2.8654 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5372 loss: 2.5372 2022/10/09 11:27:15 - mmengine - INFO - Epoch(train) [26][1340/2119] lr: 4.0000e-02 eta: 1 day, 2:33:59 time: 0.3600 data_time: 0.0227 memory: 11108 grad_norm: 2.8972 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4972 loss: 2.4972 2022/10/09 11:27:23 - mmengine - INFO - Epoch(train) [26][1360/2119] lr: 4.0000e-02 eta: 1 day, 2:33:51 time: 0.3557 data_time: 0.0186 memory: 11108 grad_norm: 2.8820 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5940 loss: 2.5940 2022/10/09 11:27:30 - mmengine - INFO - Epoch(train) [26][1380/2119] lr: 4.0000e-02 eta: 1 day, 2:33:43 time: 0.3561 data_time: 0.0167 memory: 11108 grad_norm: 2.9058 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6931 loss: 2.6931 2022/10/09 11:27:37 - mmengine - INFO - Epoch(train) [26][1400/2119] lr: 4.0000e-02 eta: 1 day, 2:33:35 time: 0.3615 data_time: 0.0252 memory: 11108 grad_norm: 2.9471 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7117 loss: 2.7117 2022/10/09 11:27:44 - mmengine - INFO - Epoch(train) [26][1420/2119] lr: 4.0000e-02 eta: 1 day, 2:33:28 time: 0.3602 data_time: 0.0222 memory: 11108 grad_norm: 2.9912 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7946 loss: 2.7946 2022/10/09 11:27:51 - mmengine - INFO - Epoch(train) [26][1440/2119] lr: 4.0000e-02 eta: 1 day, 2:33:20 time: 0.3543 data_time: 0.0228 memory: 11108 grad_norm: 2.9318 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6494 loss: 2.6494 2022/10/09 11:27:58 - mmengine - INFO - Epoch(train) [26][1460/2119] lr: 4.0000e-02 eta: 1 day, 2:33:12 time: 0.3606 data_time: 0.0213 memory: 11108 grad_norm: 2.8891 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6770 loss: 2.6770 2022/10/09 11:28:06 - mmengine - INFO - Epoch(train) [26][1480/2119] lr: 4.0000e-02 eta: 1 day, 2:33:05 time: 0.3580 data_time: 0.0193 memory: 11108 grad_norm: 2.8518 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5226 loss: 2.5226 2022/10/09 11:28:13 - mmengine - INFO - Epoch(train) [26][1500/2119] lr: 4.0000e-02 eta: 1 day, 2:32:57 time: 0.3567 data_time: 0.0169 memory: 11108 grad_norm: 2.9214 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7128 loss: 2.7128 2022/10/09 11:28:20 - mmengine - INFO - Epoch(train) [26][1520/2119] lr: 4.0000e-02 eta: 1 day, 2:32:49 time: 0.3622 data_time: 0.0196 memory: 11108 grad_norm: 2.9317 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4765 loss: 2.4765 2022/10/09 11:28:27 - mmengine - INFO - Epoch(train) [26][1540/2119] lr: 4.0000e-02 eta: 1 day, 2:32:41 time: 0.3566 data_time: 0.0176 memory: 11108 grad_norm: 2.9460 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8718 loss: 2.8718 2022/10/09 11:28:34 - mmengine - INFO - Epoch(train) [26][1560/2119] lr: 4.0000e-02 eta: 1 day, 2:32:34 time: 0.3637 data_time: 0.0222 memory: 11108 grad_norm: 2.9232 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7627 loss: 2.7627 2022/10/09 11:28:41 - mmengine - INFO - Epoch(train) [26][1580/2119] lr: 4.0000e-02 eta: 1 day, 2:32:26 time: 0.3562 data_time: 0.0191 memory: 11108 grad_norm: 2.8604 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4109 loss: 2.4109 2022/10/09 11:28:49 - mmengine - INFO - Epoch(train) [26][1600/2119] lr: 4.0000e-02 eta: 1 day, 2:32:19 time: 0.3580 data_time: 0.0233 memory: 11108 grad_norm: 2.9329 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7190 loss: 2.7190 2022/10/09 11:28:56 - mmengine - INFO - Epoch(train) [26][1620/2119] lr: 4.0000e-02 eta: 1 day, 2:32:11 time: 0.3636 data_time: 0.0200 memory: 11108 grad_norm: 2.8701 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5215 loss: 2.5215 2022/10/09 11:29:03 - mmengine - INFO - Epoch(train) [26][1640/2119] lr: 4.0000e-02 eta: 1 day, 2:32:03 time: 0.3553 data_time: 0.0225 memory: 11108 grad_norm: 2.8857 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.4704 loss: 2.4704 2022/10/09 11:29:10 - mmengine - INFO - Epoch(train) [26][1660/2119] lr: 4.0000e-02 eta: 1 day, 2:31:56 time: 0.3577 data_time: 0.0231 memory: 11108 grad_norm: 2.9239 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8490 loss: 2.8490 2022/10/09 11:29:17 - mmengine - INFO - Epoch(train) [26][1680/2119] lr: 4.0000e-02 eta: 1 day, 2:31:48 time: 0.3597 data_time: 0.0201 memory: 11108 grad_norm: 2.8632 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6317 loss: 2.6317 2022/10/09 11:29:25 - mmengine - INFO - Epoch(train) [26][1700/2119] lr: 4.0000e-02 eta: 1 day, 2:31:40 time: 0.3581 data_time: 0.0215 memory: 11108 grad_norm: 2.8944 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6276 loss: 2.6276 2022/10/09 11:29:32 - mmengine - INFO - Epoch(train) [26][1720/2119] lr: 4.0000e-02 eta: 1 day, 2:31:33 time: 0.3577 data_time: 0.0209 memory: 11108 grad_norm: 2.9663 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4867 loss: 2.4867 2022/10/09 11:29:39 - mmengine - INFO - Epoch(train) [26][1740/2119] lr: 4.0000e-02 eta: 1 day, 2:31:25 time: 0.3591 data_time: 0.0233 memory: 11108 grad_norm: 2.9073 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8004 loss: 2.8004 2022/10/09 11:29:46 - mmengine - INFO - Epoch(train) [26][1760/2119] lr: 4.0000e-02 eta: 1 day, 2:31:17 time: 0.3557 data_time: 0.0207 memory: 11108 grad_norm: 2.8780 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6453 loss: 2.6453 2022/10/09 11:29:53 - mmengine - INFO - Epoch(train) [26][1780/2119] lr: 4.0000e-02 eta: 1 day, 2:31:09 time: 0.3562 data_time: 0.0202 memory: 11108 grad_norm: 2.9082 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5294 loss: 2.5294 2022/10/09 11:30:00 - mmengine - INFO - Epoch(train) [26][1800/2119] lr: 4.0000e-02 eta: 1 day, 2:31:02 time: 0.3600 data_time: 0.0201 memory: 11108 grad_norm: 2.8917 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5565 loss: 2.5565 2022/10/09 11:30:08 - mmengine - INFO - Epoch(train) [26][1820/2119] lr: 4.0000e-02 eta: 1 day, 2:30:54 time: 0.3614 data_time: 0.0187 memory: 11108 grad_norm: 2.9087 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.4029 loss: 2.4029 2022/10/09 11:30:15 - mmengine - INFO - Epoch(train) [26][1840/2119] lr: 4.0000e-02 eta: 1 day, 2:30:47 time: 0.3608 data_time: 0.0202 memory: 11108 grad_norm: 2.9566 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4434 loss: 2.4434 2022/10/09 11:30:22 - mmengine - INFO - Epoch(train) [26][1860/2119] lr: 4.0000e-02 eta: 1 day, 2:30:39 time: 0.3609 data_time: 0.0251 memory: 11108 grad_norm: 2.9413 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7832 loss: 2.7832 2022/10/09 11:30:29 - mmengine - INFO - Epoch(train) [26][1880/2119] lr: 4.0000e-02 eta: 1 day, 2:30:32 time: 0.3630 data_time: 0.0238 memory: 11108 grad_norm: 2.8909 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6259 loss: 2.6259 2022/10/09 11:30:36 - mmengine - INFO - Epoch(train) [26][1900/2119] lr: 4.0000e-02 eta: 1 day, 2:30:24 time: 0.3550 data_time: 0.0209 memory: 11108 grad_norm: 2.8605 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.8913 loss: 2.8913 2022/10/09 11:30:43 - mmengine - INFO - Epoch(train) [26][1920/2119] lr: 4.0000e-02 eta: 1 day, 2:30:16 time: 0.3558 data_time: 0.0194 memory: 11108 grad_norm: 2.9103 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4399 loss: 2.4399 2022/10/09 11:30:51 - mmengine - INFO - Epoch(train) [26][1940/2119] lr: 4.0000e-02 eta: 1 day, 2:30:08 time: 0.3584 data_time: 0.0191 memory: 11108 grad_norm: 2.8711 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7553 loss: 2.7553 2022/10/09 11:30:58 - mmengine - INFO - Epoch(train) [26][1960/2119] lr: 4.0000e-02 eta: 1 day, 2:30:01 time: 0.3572 data_time: 0.0196 memory: 11108 grad_norm: 2.9309 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5002 loss: 2.5002 2022/10/09 11:31:05 - mmengine - INFO - Epoch(train) [26][1980/2119] lr: 4.0000e-02 eta: 1 day, 2:29:53 time: 0.3551 data_time: 0.0214 memory: 11108 grad_norm: 2.8888 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5614 loss: 2.5614 2022/10/09 11:31:12 - mmengine - INFO - Epoch(train) [26][2000/2119] lr: 4.0000e-02 eta: 1 day, 2:29:45 time: 0.3567 data_time: 0.0189 memory: 11108 grad_norm: 2.8892 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4676 loss: 2.4676 2022/10/09 11:31:19 - mmengine - INFO - Epoch(train) [26][2020/2119] lr: 4.0000e-02 eta: 1 day, 2:29:38 time: 0.3628 data_time: 0.0217 memory: 11108 grad_norm: 2.9184 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6543 loss: 2.6543 2022/10/09 11:31:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 11:31:26 - mmengine - INFO - Epoch(train) [26][2040/2119] lr: 4.0000e-02 eta: 1 day, 2:29:30 time: 0.3552 data_time: 0.0222 memory: 11108 grad_norm: 2.9429 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4957 loss: 2.4957 2022/10/09 11:31:34 - mmengine - INFO - Epoch(train) [26][2060/2119] lr: 4.0000e-02 eta: 1 day, 2:29:22 time: 0.3602 data_time: 0.0183 memory: 11108 grad_norm: 2.9470 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7920 loss: 2.7920 2022/10/09 11:31:41 - mmengine - INFO - Epoch(train) [26][2080/2119] lr: 4.0000e-02 eta: 1 day, 2:29:15 time: 0.3626 data_time: 0.0216 memory: 11108 grad_norm: 2.8653 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7778 loss: 2.7778 2022/10/09 11:31:48 - mmengine - INFO - Epoch(train) [26][2100/2119] lr: 4.0000e-02 eta: 1 day, 2:29:07 time: 0.3580 data_time: 0.0220 memory: 11108 grad_norm: 2.9230 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7575 loss: 2.7575 2022/10/09 11:31:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 11:31:55 - mmengine - INFO - Epoch(train) [26][2119/2119] lr: 4.0000e-02 eta: 1 day, 2:29:07 time: 0.3644 data_time: 0.0192 memory: 11108 grad_norm: 2.9392 top1_acc: 0.5000 top5_acc: 0.7000 loss_cls: 2.5971 loss: 2.5971 2022/10/09 11:32:05 - mmengine - INFO - Epoch(train) [27][20/2119] lr: 4.0000e-02 eta: 1 day, 2:28:35 time: 0.5217 data_time: 0.1506 memory: 11108 grad_norm: 2.8378 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4675 loss: 2.4675 2022/10/09 11:32:13 - mmengine - INFO - Epoch(train) [27][40/2119] lr: 4.0000e-02 eta: 1 day, 2:28:29 time: 0.3747 data_time: 0.0245 memory: 11108 grad_norm: 2.9352 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6442 loss: 2.6442 2022/10/09 11:32:20 - mmengine - INFO - Epoch(train) [27][60/2119] lr: 4.0000e-02 eta: 1 day, 2:28:22 time: 0.3648 data_time: 0.0221 memory: 11108 grad_norm: 2.9015 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5291 loss: 2.5291 2022/10/09 11:32:27 - mmengine - INFO - Epoch(train) [27][80/2119] lr: 4.0000e-02 eta: 1 day, 2:28:14 time: 0.3581 data_time: 0.0181 memory: 11108 grad_norm: 2.9009 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5101 loss: 2.5101 2022/10/09 11:32:35 - mmengine - INFO - Epoch(train) [27][100/2119] lr: 4.0000e-02 eta: 1 day, 2:28:07 time: 0.3626 data_time: 0.0190 memory: 11108 grad_norm: 2.9208 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.5243 loss: 2.5243 2022/10/09 11:32:42 - mmengine - INFO - Epoch(train) [27][120/2119] lr: 4.0000e-02 eta: 1 day, 2:27:59 time: 0.3576 data_time: 0.0201 memory: 11108 grad_norm: 2.9135 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4864 loss: 2.4864 2022/10/09 11:32:49 - mmengine - INFO - Epoch(train) [27][140/2119] lr: 4.0000e-02 eta: 1 day, 2:27:52 time: 0.3586 data_time: 0.0215 memory: 11108 grad_norm: 2.8444 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.3955 loss: 2.3955 2022/10/09 11:32:56 - mmengine - INFO - Epoch(train) [27][160/2119] lr: 4.0000e-02 eta: 1 day, 2:27:44 time: 0.3627 data_time: 0.0204 memory: 11108 grad_norm: 2.9250 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6411 loss: 2.6411 2022/10/09 11:33:03 - mmengine - INFO - Epoch(train) [27][180/2119] lr: 4.0000e-02 eta: 1 day, 2:27:37 time: 0.3585 data_time: 0.0202 memory: 11108 grad_norm: 2.9224 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5525 loss: 2.5525 2022/10/09 11:33:11 - mmengine - INFO - Epoch(train) [27][200/2119] lr: 4.0000e-02 eta: 1 day, 2:27:29 time: 0.3576 data_time: 0.0192 memory: 11108 grad_norm: 2.9050 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6029 loss: 2.6029 2022/10/09 11:33:18 - mmengine - INFO - Epoch(train) [27][220/2119] lr: 4.0000e-02 eta: 1 day, 2:27:21 time: 0.3582 data_time: 0.0199 memory: 11108 grad_norm: 2.8759 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5924 loss: 2.5924 2022/10/09 11:33:25 - mmengine - INFO - Epoch(train) [27][240/2119] lr: 4.0000e-02 eta: 1 day, 2:27:14 time: 0.3596 data_time: 0.0190 memory: 11108 grad_norm: 2.8991 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5296 loss: 2.5296 2022/10/09 11:33:32 - mmengine - INFO - Epoch(train) [27][260/2119] lr: 4.0000e-02 eta: 1 day, 2:27:06 time: 0.3600 data_time: 0.0199 memory: 11108 grad_norm: 2.8944 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5652 loss: 2.5652 2022/10/09 11:33:39 - mmengine - INFO - Epoch(train) [27][280/2119] lr: 4.0000e-02 eta: 1 day, 2:26:58 time: 0.3572 data_time: 0.0230 memory: 11108 grad_norm: 2.9121 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6835 loss: 2.6835 2022/10/09 11:33:46 - mmengine - INFO - Epoch(train) [27][300/2119] lr: 4.0000e-02 eta: 1 day, 2:26:51 time: 0.3562 data_time: 0.0207 memory: 11108 grad_norm: 2.9315 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.5139 loss: 2.5139 2022/10/09 11:33:54 - mmengine - INFO - Epoch(train) [27][320/2119] lr: 4.0000e-02 eta: 1 day, 2:26:43 time: 0.3568 data_time: 0.0245 memory: 11108 grad_norm: 2.8826 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6993 loss: 2.6993 2022/10/09 11:34:01 - mmengine - INFO - Epoch(train) [27][340/2119] lr: 4.0000e-02 eta: 1 day, 2:26:35 time: 0.3556 data_time: 0.0187 memory: 11108 grad_norm: 2.9365 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4457 loss: 2.4457 2022/10/09 11:34:08 - mmengine - INFO - Epoch(train) [27][360/2119] lr: 4.0000e-02 eta: 1 day, 2:26:27 time: 0.3550 data_time: 0.0225 memory: 11108 grad_norm: 2.9265 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6903 loss: 2.6903 2022/10/09 11:34:15 - mmengine - INFO - Epoch(train) [27][380/2119] lr: 4.0000e-02 eta: 1 day, 2:26:19 time: 0.3594 data_time: 0.0159 memory: 11108 grad_norm: 2.9162 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7329 loss: 2.7329 2022/10/09 11:34:22 - mmengine - INFO - Epoch(train) [27][400/2119] lr: 4.0000e-02 eta: 1 day, 2:26:12 time: 0.3578 data_time: 0.0233 memory: 11108 grad_norm: 2.9145 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5853 loss: 2.5853 2022/10/09 11:34:29 - mmengine - INFO - Epoch(train) [27][420/2119] lr: 4.0000e-02 eta: 1 day, 2:26:04 time: 0.3612 data_time: 0.0177 memory: 11108 grad_norm: 2.8712 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5791 loss: 2.5791 2022/10/09 11:34:36 - mmengine - INFO - Epoch(train) [27][440/2119] lr: 4.0000e-02 eta: 1 day, 2:25:56 time: 0.3547 data_time: 0.0204 memory: 11108 grad_norm: 2.8815 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4208 loss: 2.4208 2022/10/09 11:34:44 - mmengine - INFO - Epoch(train) [27][460/2119] lr: 4.0000e-02 eta: 1 day, 2:25:49 time: 0.3597 data_time: 0.0235 memory: 11108 grad_norm: 2.9563 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.4708 loss: 2.4708 2022/10/09 11:34:51 - mmengine - INFO - Epoch(train) [27][480/2119] lr: 4.0000e-02 eta: 1 day, 2:25:41 time: 0.3587 data_time: 0.0206 memory: 11108 grad_norm: 2.9050 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5425 loss: 2.5425 2022/10/09 11:34:58 - mmengine - INFO - Epoch(train) [27][500/2119] lr: 4.0000e-02 eta: 1 day, 2:25:34 time: 0.3653 data_time: 0.0326 memory: 11108 grad_norm: 2.9552 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7452 loss: 2.7452 2022/10/09 11:35:05 - mmengine - INFO - Epoch(train) [27][520/2119] lr: 4.0000e-02 eta: 1 day, 2:25:27 time: 0.3613 data_time: 0.0195 memory: 11108 grad_norm: 2.8946 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6110 loss: 2.6110 2022/10/09 11:35:12 - mmengine - INFO - Epoch(train) [27][540/2119] lr: 4.0000e-02 eta: 1 day, 2:25:18 time: 0.3542 data_time: 0.0172 memory: 11108 grad_norm: 2.8691 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7263 loss: 2.7263 2022/10/09 11:35:20 - mmengine - INFO - Epoch(train) [27][560/2119] lr: 4.0000e-02 eta: 1 day, 2:25:12 time: 0.3672 data_time: 0.0238 memory: 11108 grad_norm: 2.8913 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5291 loss: 2.5291 2022/10/09 11:35:27 - mmengine - INFO - Epoch(train) [27][580/2119] lr: 4.0000e-02 eta: 1 day, 2:25:04 time: 0.3584 data_time: 0.0192 memory: 11108 grad_norm: 2.9240 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.5897 loss: 2.5897 2022/10/09 11:35:34 - mmengine - INFO - Epoch(train) [27][600/2119] lr: 4.0000e-02 eta: 1 day, 2:24:56 time: 0.3553 data_time: 0.0231 memory: 11108 grad_norm: 2.9015 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6273 loss: 2.6273 2022/10/09 11:35:41 - mmengine - INFO - Epoch(train) [27][620/2119] lr: 4.0000e-02 eta: 1 day, 2:24:49 time: 0.3605 data_time: 0.0219 memory: 11108 grad_norm: 2.9066 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5829 loss: 2.5829 2022/10/09 11:35:48 - mmengine - INFO - Epoch(train) [27][640/2119] lr: 4.0000e-02 eta: 1 day, 2:24:41 time: 0.3545 data_time: 0.0216 memory: 11108 grad_norm: 2.9279 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5343 loss: 2.5343 2022/10/09 11:35:55 - mmengine - INFO - Epoch(train) [27][660/2119] lr: 4.0000e-02 eta: 1 day, 2:24:33 time: 0.3552 data_time: 0.0207 memory: 11108 grad_norm: 2.9046 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5862 loss: 2.5862 2022/10/09 11:36:03 - mmengine - INFO - Epoch(train) [27][680/2119] lr: 4.0000e-02 eta: 1 day, 2:24:25 time: 0.3588 data_time: 0.0210 memory: 11108 grad_norm: 2.9243 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.4282 loss: 2.4282 2022/10/09 11:36:10 - mmengine - INFO - Epoch(train) [27][700/2119] lr: 4.0000e-02 eta: 1 day, 2:24:17 time: 0.3577 data_time: 0.0211 memory: 11108 grad_norm: 2.9197 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6584 loss: 2.6584 2022/10/09 11:36:17 - mmengine - INFO - Epoch(train) [27][720/2119] lr: 4.0000e-02 eta: 1 day, 2:24:10 time: 0.3601 data_time: 0.0197 memory: 11108 grad_norm: 2.8845 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5041 loss: 2.5041 2022/10/09 11:36:24 - mmengine - INFO - Epoch(train) [27][740/2119] lr: 4.0000e-02 eta: 1 day, 2:24:02 time: 0.3614 data_time: 0.0191 memory: 11108 grad_norm: 2.8680 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5363 loss: 2.5363 2022/10/09 11:36:31 - mmengine - INFO - Epoch(train) [27][760/2119] lr: 4.0000e-02 eta: 1 day, 2:23:55 time: 0.3583 data_time: 0.0227 memory: 11108 grad_norm: 2.9170 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7937 loss: 2.7937 2022/10/09 11:36:39 - mmengine - INFO - Epoch(train) [27][780/2119] lr: 4.0000e-02 eta: 1 day, 2:23:47 time: 0.3622 data_time: 0.0235 memory: 11108 grad_norm: 2.9242 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6945 loss: 2.6945 2022/10/09 11:36:46 - mmengine - INFO - Epoch(train) [27][800/2119] lr: 4.0000e-02 eta: 1 day, 2:23:40 time: 0.3609 data_time: 0.0184 memory: 11108 grad_norm: 2.9044 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7135 loss: 2.7135 2022/10/09 11:36:53 - mmengine - INFO - Epoch(train) [27][820/2119] lr: 4.0000e-02 eta: 1 day, 2:23:32 time: 0.3542 data_time: 0.0205 memory: 11108 grad_norm: 2.8942 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.3467 loss: 2.3467 2022/10/09 11:37:00 - mmengine - INFO - Epoch(train) [27][840/2119] lr: 4.0000e-02 eta: 1 day, 2:23:24 time: 0.3609 data_time: 0.0210 memory: 11108 grad_norm: 2.9181 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7567 loss: 2.7567 2022/10/09 11:37:07 - mmengine - INFO - Epoch(train) [27][860/2119] lr: 4.0000e-02 eta: 1 day, 2:23:17 time: 0.3579 data_time: 0.0217 memory: 11108 grad_norm: 2.8599 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7181 loss: 2.7181 2022/10/09 11:37:15 - mmengine - INFO - Epoch(train) [27][880/2119] lr: 4.0000e-02 eta: 1 day, 2:23:10 time: 0.3658 data_time: 0.0256 memory: 11108 grad_norm: 2.8070 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6495 loss: 2.6495 2022/10/09 11:37:22 - mmengine - INFO - Epoch(train) [27][900/2119] lr: 4.0000e-02 eta: 1 day, 2:23:02 time: 0.3595 data_time: 0.0188 memory: 11108 grad_norm: 2.9362 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7963 loss: 2.7963 2022/10/09 11:37:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 11:37:29 - mmengine - INFO - Epoch(train) [27][920/2119] lr: 4.0000e-02 eta: 1 day, 2:22:54 time: 0.3565 data_time: 0.0260 memory: 11108 grad_norm: 2.9343 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5367 loss: 2.5367 2022/10/09 11:37:36 - mmengine - INFO - Epoch(train) [27][940/2119] lr: 4.0000e-02 eta: 1 day, 2:22:47 time: 0.3568 data_time: 0.0218 memory: 11108 grad_norm: 2.9177 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4266 loss: 2.4266 2022/10/09 11:37:43 - mmengine - INFO - Epoch(train) [27][960/2119] lr: 4.0000e-02 eta: 1 day, 2:22:39 time: 0.3616 data_time: 0.0264 memory: 11108 grad_norm: 2.8850 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4716 loss: 2.4716 2022/10/09 11:37:51 - mmengine - INFO - Epoch(train) [27][980/2119] lr: 4.0000e-02 eta: 1 day, 2:22:32 time: 0.3600 data_time: 0.0184 memory: 11108 grad_norm: 2.9043 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6748 loss: 2.6748 2022/10/09 11:37:58 - mmengine - INFO - Epoch(train) [27][1000/2119] lr: 4.0000e-02 eta: 1 day, 2:22:24 time: 0.3628 data_time: 0.0256 memory: 11108 grad_norm: 2.9124 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6318 loss: 2.6318 2022/10/09 11:38:05 - mmengine - INFO - Epoch(train) [27][1020/2119] lr: 4.0000e-02 eta: 1 day, 2:22:16 time: 0.3542 data_time: 0.0204 memory: 11108 grad_norm: 2.9162 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3441 loss: 2.3441 2022/10/09 11:38:12 - mmengine - INFO - Epoch(train) [27][1040/2119] lr: 4.0000e-02 eta: 1 day, 2:22:09 time: 0.3636 data_time: 0.0220 memory: 11108 grad_norm: 2.9072 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8302 loss: 2.8302 2022/10/09 11:38:19 - mmengine - INFO - Epoch(train) [27][1060/2119] lr: 4.0000e-02 eta: 1 day, 2:22:02 time: 0.3579 data_time: 0.0208 memory: 11108 grad_norm: 2.9302 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4816 loss: 2.4816 2022/10/09 11:38:27 - mmengine - INFO - Epoch(train) [27][1080/2119] lr: 4.0000e-02 eta: 1 day, 2:21:55 time: 0.3673 data_time: 0.0215 memory: 11108 grad_norm: 2.9225 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7494 loss: 2.7494 2022/10/09 11:38:34 - mmengine - INFO - Epoch(train) [27][1100/2119] lr: 4.0000e-02 eta: 1 day, 2:21:47 time: 0.3543 data_time: 0.0190 memory: 11108 grad_norm: 2.9491 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8098 loss: 2.8098 2022/10/09 11:38:41 - mmengine - INFO - Epoch(train) [27][1120/2119] lr: 4.0000e-02 eta: 1 day, 2:21:39 time: 0.3577 data_time: 0.0222 memory: 11108 grad_norm: 2.9035 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6758 loss: 2.6758 2022/10/09 11:38:48 - mmengine - INFO - Epoch(train) [27][1140/2119] lr: 4.0000e-02 eta: 1 day, 2:21:31 time: 0.3573 data_time: 0.0185 memory: 11108 grad_norm: 2.9513 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.3804 loss: 2.3804 2022/10/09 11:38:55 - mmengine - INFO - Epoch(train) [27][1160/2119] lr: 4.0000e-02 eta: 1 day, 2:21:24 time: 0.3588 data_time: 0.0218 memory: 11108 grad_norm: 2.8582 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4256 loss: 2.4256 2022/10/09 11:39:02 - mmengine - INFO - Epoch(train) [27][1180/2119] lr: 4.0000e-02 eta: 1 day, 2:21:16 time: 0.3549 data_time: 0.0195 memory: 11108 grad_norm: 2.8683 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.4728 loss: 2.4728 2022/10/09 11:39:10 - mmengine - INFO - Epoch(train) [27][1200/2119] lr: 4.0000e-02 eta: 1 day, 2:21:09 time: 0.3646 data_time: 0.0181 memory: 11108 grad_norm: 2.9413 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8053 loss: 2.8053 2022/10/09 11:39:17 - mmengine - INFO - Epoch(train) [27][1220/2119] lr: 4.0000e-02 eta: 1 day, 2:21:01 time: 0.3631 data_time: 0.0277 memory: 11108 grad_norm: 2.9479 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7120 loss: 2.7120 2022/10/09 11:39:24 - mmengine - INFO - Epoch(train) [27][1240/2119] lr: 4.0000e-02 eta: 1 day, 2:20:53 time: 0.3553 data_time: 0.0247 memory: 11108 grad_norm: 2.9141 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4684 loss: 2.4684 2022/10/09 11:39:31 - mmengine - INFO - Epoch(train) [27][1260/2119] lr: 4.0000e-02 eta: 1 day, 2:20:46 time: 0.3598 data_time: 0.0247 memory: 11108 grad_norm: 2.9265 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5771 loss: 2.5771 2022/10/09 11:39:39 - mmengine - INFO - Epoch(train) [27][1280/2119] lr: 4.0000e-02 eta: 1 day, 2:20:39 time: 0.3678 data_time: 0.0228 memory: 11108 grad_norm: 2.9116 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7926 loss: 2.7926 2022/10/09 11:39:46 - mmengine - INFO - Epoch(train) [27][1300/2119] lr: 4.0000e-02 eta: 1 day, 2:20:31 time: 0.3529 data_time: 0.0207 memory: 11108 grad_norm: 2.9180 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5556 loss: 2.5556 2022/10/09 11:39:53 - mmengine - INFO - Epoch(train) [27][1320/2119] lr: 4.0000e-02 eta: 1 day, 2:20:23 time: 0.3599 data_time: 0.0219 memory: 11108 grad_norm: 2.9119 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4460 loss: 2.4460 2022/10/09 11:40:00 - mmengine - INFO - Epoch(train) [27][1340/2119] lr: 4.0000e-02 eta: 1 day, 2:20:16 time: 0.3588 data_time: 0.0204 memory: 11108 grad_norm: 2.9230 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5924 loss: 2.5924 2022/10/09 11:40:07 - mmengine - INFO - Epoch(train) [27][1360/2119] lr: 4.0000e-02 eta: 1 day, 2:20:08 time: 0.3607 data_time: 0.0241 memory: 11108 grad_norm: 2.9224 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6299 loss: 2.6299 2022/10/09 11:40:14 - mmengine - INFO - Epoch(train) [27][1380/2119] lr: 4.0000e-02 eta: 1 day, 2:20:00 time: 0.3568 data_time: 0.0171 memory: 11108 grad_norm: 2.9182 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5204 loss: 2.5204 2022/10/09 11:40:21 - mmengine - INFO - Epoch(train) [27][1400/2119] lr: 4.0000e-02 eta: 1 day, 2:19:53 time: 0.3595 data_time: 0.0216 memory: 11108 grad_norm: 2.9682 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7058 loss: 2.7058 2022/10/09 11:40:29 - mmengine - INFO - Epoch(train) [27][1420/2119] lr: 4.0000e-02 eta: 1 day, 2:19:46 time: 0.3635 data_time: 0.0200 memory: 11108 grad_norm: 2.8847 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7207 loss: 2.7207 2022/10/09 11:40:36 - mmengine - INFO - Epoch(train) [27][1440/2119] lr: 4.0000e-02 eta: 1 day, 2:19:38 time: 0.3567 data_time: 0.0217 memory: 11108 grad_norm: 2.9185 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5914 loss: 2.5914 2022/10/09 11:40:43 - mmengine - INFO - Epoch(train) [27][1460/2119] lr: 4.0000e-02 eta: 1 day, 2:19:30 time: 0.3596 data_time: 0.0231 memory: 11108 grad_norm: 2.8789 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6473 loss: 2.6473 2022/10/09 11:40:50 - mmengine - INFO - Epoch(train) [27][1480/2119] lr: 4.0000e-02 eta: 1 day, 2:19:23 time: 0.3569 data_time: 0.0216 memory: 11108 grad_norm: 2.9148 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.6948 loss: 2.6948 2022/10/09 11:40:57 - mmengine - INFO - Epoch(train) [27][1500/2119] lr: 4.0000e-02 eta: 1 day, 2:19:15 time: 0.3615 data_time: 0.0258 memory: 11108 grad_norm: 2.9338 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.4801 loss: 2.4801 2022/10/09 11:41:05 - mmengine - INFO - Epoch(train) [27][1520/2119] lr: 4.0000e-02 eta: 1 day, 2:19:08 time: 0.3640 data_time: 0.0242 memory: 11108 grad_norm: 2.9069 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7159 loss: 2.7159 2022/10/09 11:41:12 - mmengine - INFO - Epoch(train) [27][1540/2119] lr: 4.0000e-02 eta: 1 day, 2:19:00 time: 0.3557 data_time: 0.0209 memory: 11108 grad_norm: 2.9290 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8230 loss: 2.8230 2022/10/09 11:41:19 - mmengine - INFO - Epoch(train) [27][1560/2119] lr: 4.0000e-02 eta: 1 day, 2:18:52 time: 0.3567 data_time: 0.0199 memory: 11108 grad_norm: 2.9037 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5562 loss: 2.5562 2022/10/09 11:41:26 - mmengine - INFO - Epoch(train) [27][1580/2119] lr: 4.0000e-02 eta: 1 day, 2:18:45 time: 0.3660 data_time: 0.0196 memory: 11108 grad_norm: 2.8514 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7071 loss: 2.7071 2022/10/09 11:41:33 - mmengine - INFO - Epoch(train) [27][1600/2119] lr: 4.0000e-02 eta: 1 day, 2:18:38 time: 0.3575 data_time: 0.0205 memory: 11108 grad_norm: 2.9051 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5627 loss: 2.5627 2022/10/09 11:41:41 - mmengine - INFO - Epoch(train) [27][1620/2119] lr: 4.0000e-02 eta: 1 day, 2:18:30 time: 0.3550 data_time: 0.0169 memory: 11108 grad_norm: 2.9275 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7665 loss: 2.7665 2022/10/09 11:41:48 - mmengine - INFO - Epoch(train) [27][1640/2119] lr: 4.0000e-02 eta: 1 day, 2:18:22 time: 0.3602 data_time: 0.0218 memory: 11108 grad_norm: 2.8701 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8562 loss: 2.8562 2022/10/09 11:41:55 - mmengine - INFO - Epoch(train) [27][1660/2119] lr: 4.0000e-02 eta: 1 day, 2:18:15 time: 0.3584 data_time: 0.0202 memory: 11108 grad_norm: 2.9012 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7490 loss: 2.7490 2022/10/09 11:42:02 - mmengine - INFO - Epoch(train) [27][1680/2119] lr: 4.0000e-02 eta: 1 day, 2:18:07 time: 0.3555 data_time: 0.0211 memory: 11108 grad_norm: 2.8988 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7122 loss: 2.7122 2022/10/09 11:42:09 - mmengine - INFO - Epoch(train) [27][1700/2119] lr: 4.0000e-02 eta: 1 day, 2:17:59 time: 0.3571 data_time: 0.0211 memory: 11108 grad_norm: 2.9172 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7486 loss: 2.7486 2022/10/09 11:42:16 - mmengine - INFO - Epoch(train) [27][1720/2119] lr: 4.0000e-02 eta: 1 day, 2:17:51 time: 0.3590 data_time: 0.0206 memory: 11108 grad_norm: 2.9727 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6498 loss: 2.6498 2022/10/09 11:42:24 - mmengine - INFO - Epoch(train) [27][1740/2119] lr: 4.0000e-02 eta: 1 day, 2:17:44 time: 0.3565 data_time: 0.0197 memory: 11108 grad_norm: 2.9005 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6447 loss: 2.6447 2022/10/09 11:42:31 - mmengine - INFO - Epoch(train) [27][1760/2119] lr: 4.0000e-02 eta: 1 day, 2:17:36 time: 0.3626 data_time: 0.0233 memory: 11108 grad_norm: 2.9016 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6109 loss: 2.6109 2022/10/09 11:42:38 - mmengine - INFO - Epoch(train) [27][1780/2119] lr: 4.0000e-02 eta: 1 day, 2:17:29 time: 0.3585 data_time: 0.0262 memory: 11108 grad_norm: 2.9170 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7922 loss: 2.7922 2022/10/09 11:42:45 - mmengine - INFO - Epoch(train) [27][1800/2119] lr: 4.0000e-02 eta: 1 day, 2:17:21 time: 0.3579 data_time: 0.0205 memory: 11108 grad_norm: 2.9444 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5239 loss: 2.5239 2022/10/09 11:42:52 - mmengine - INFO - Epoch(train) [27][1820/2119] lr: 4.0000e-02 eta: 1 day, 2:17:13 time: 0.3566 data_time: 0.0194 memory: 11108 grad_norm: 2.9316 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5831 loss: 2.5831 2022/10/09 11:42:59 - mmengine - INFO - Epoch(train) [27][1840/2119] lr: 4.0000e-02 eta: 1 day, 2:17:06 time: 0.3617 data_time: 0.0255 memory: 11108 grad_norm: 2.9383 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.4428 loss: 2.4428 2022/10/09 11:43:07 - mmengine - INFO - Epoch(train) [27][1860/2119] lr: 4.0000e-02 eta: 1 day, 2:16:58 time: 0.3571 data_time: 0.0210 memory: 11108 grad_norm: 2.8694 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4749 loss: 2.4749 2022/10/09 11:43:14 - mmengine - INFO - Epoch(train) [27][1880/2119] lr: 4.0000e-02 eta: 1 day, 2:16:50 time: 0.3537 data_time: 0.0196 memory: 11108 grad_norm: 2.9358 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5437 loss: 2.5437 2022/10/09 11:43:21 - mmengine - INFO - Epoch(train) [27][1900/2119] lr: 4.0000e-02 eta: 1 day, 2:16:42 time: 0.3543 data_time: 0.0219 memory: 11108 grad_norm: 2.9813 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8304 loss: 2.8304 2022/10/09 11:43:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 11:43:28 - mmengine - INFO - Epoch(train) [27][1920/2119] lr: 4.0000e-02 eta: 1 day, 2:16:34 time: 0.3578 data_time: 0.0209 memory: 11108 grad_norm: 2.9352 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6440 loss: 2.6440 2022/10/09 11:43:35 - mmengine - INFO - Epoch(train) [27][1940/2119] lr: 4.0000e-02 eta: 1 day, 2:16:27 time: 0.3587 data_time: 0.0216 memory: 11108 grad_norm: 2.9361 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7757 loss: 2.7757 2022/10/09 11:43:42 - mmengine - INFO - Epoch(train) [27][1960/2119] lr: 4.0000e-02 eta: 1 day, 2:16:19 time: 0.3557 data_time: 0.0219 memory: 11108 grad_norm: 2.8596 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5593 loss: 2.5593 2022/10/09 11:43:49 - mmengine - INFO - Epoch(train) [27][1980/2119] lr: 4.0000e-02 eta: 1 day, 2:16:11 time: 0.3620 data_time: 0.0273 memory: 11108 grad_norm: 2.9334 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.6708 loss: 2.6708 2022/10/09 11:43:57 - mmengine - INFO - Epoch(train) [27][2000/2119] lr: 4.0000e-02 eta: 1 day, 2:16:04 time: 0.3558 data_time: 0.0189 memory: 11108 grad_norm: 2.9205 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5898 loss: 2.5898 2022/10/09 11:44:04 - mmengine - INFO - Epoch(train) [27][2020/2119] lr: 4.0000e-02 eta: 1 day, 2:15:56 time: 0.3577 data_time: 0.0217 memory: 11108 grad_norm: 2.9639 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7712 loss: 2.7712 2022/10/09 11:44:11 - mmengine - INFO - Epoch(train) [27][2040/2119] lr: 4.0000e-02 eta: 1 day, 2:15:48 time: 0.3592 data_time: 0.0233 memory: 11108 grad_norm: 2.9370 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5886 loss: 2.5886 2022/10/09 11:44:18 - mmengine - INFO - Epoch(train) [27][2060/2119] lr: 4.0000e-02 eta: 1 day, 2:15:41 time: 0.3643 data_time: 0.0191 memory: 11108 grad_norm: 2.9030 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6778 loss: 2.6778 2022/10/09 11:44:25 - mmengine - INFO - Epoch(train) [27][2080/2119] lr: 4.0000e-02 eta: 1 day, 2:15:33 time: 0.3558 data_time: 0.0190 memory: 11108 grad_norm: 2.9216 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6568 loss: 2.6568 2022/10/09 11:44:33 - mmengine - INFO - Epoch(train) [27][2100/2119] lr: 4.0000e-02 eta: 1 day, 2:15:26 time: 0.3619 data_time: 0.0208 memory: 11108 grad_norm: 2.8959 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4044 loss: 2.4044 2022/10/09 11:44:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 11:44:40 - mmengine - INFO - Epoch(train) [27][2119/2119] lr: 4.0000e-02 eta: 1 day, 2:15:26 time: 0.3863 data_time: 0.0565 memory: 11108 grad_norm: 2.9437 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6079 loss: 2.6079 2022/10/09 11:44:50 - mmengine - INFO - Epoch(train) [28][20/2119] lr: 4.0000e-02 eta: 1 day, 2:14:54 time: 0.5070 data_time: 0.1299 memory: 11108 grad_norm: 2.8785 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5950 loss: 2.5950 2022/10/09 11:44:57 - mmengine - INFO - Epoch(train) [28][40/2119] lr: 4.0000e-02 eta: 1 day, 2:14:47 time: 0.3667 data_time: 0.0209 memory: 11108 grad_norm: 2.9382 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6451 loss: 2.6451 2022/10/09 11:45:05 - mmengine - INFO - Epoch(train) [28][60/2119] lr: 4.0000e-02 eta: 1 day, 2:14:39 time: 0.3589 data_time: 0.0221 memory: 11108 grad_norm: 2.8898 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6212 loss: 2.6212 2022/10/09 11:45:12 - mmengine - INFO - Epoch(train) [28][80/2119] lr: 4.0000e-02 eta: 1 day, 2:14:32 time: 0.3614 data_time: 0.0214 memory: 11108 grad_norm: 2.9040 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7054 loss: 2.7054 2022/10/09 11:45:19 - mmengine - INFO - Epoch(train) [28][100/2119] lr: 4.0000e-02 eta: 1 day, 2:14:24 time: 0.3615 data_time: 0.0228 memory: 11108 grad_norm: 2.9484 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5225 loss: 2.5225 2022/10/09 11:45:26 - mmengine - INFO - Epoch(train) [28][120/2119] lr: 4.0000e-02 eta: 1 day, 2:14:17 time: 0.3640 data_time: 0.0242 memory: 11108 grad_norm: 2.9294 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5704 loss: 2.5704 2022/10/09 11:45:33 - mmengine - INFO - Epoch(train) [28][140/2119] lr: 4.0000e-02 eta: 1 day, 2:14:09 time: 0.3532 data_time: 0.0198 memory: 11108 grad_norm: 2.9078 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.4509 loss: 2.4509 2022/10/09 11:45:41 - mmengine - INFO - Epoch(train) [28][160/2119] lr: 4.0000e-02 eta: 1 day, 2:14:02 time: 0.3684 data_time: 0.0220 memory: 11108 grad_norm: 2.9097 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.5128 loss: 2.5128 2022/10/09 11:45:48 - mmengine - INFO - Epoch(train) [28][180/2119] lr: 4.0000e-02 eta: 1 day, 2:13:55 time: 0.3586 data_time: 0.0234 memory: 11108 grad_norm: 2.8696 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.6601 loss: 2.6601 2022/10/09 11:45:55 - mmengine - INFO - Epoch(train) [28][200/2119] lr: 4.0000e-02 eta: 1 day, 2:13:47 time: 0.3552 data_time: 0.0185 memory: 11108 grad_norm: 2.8850 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.5496 loss: 2.5496 2022/10/09 11:46:02 - mmengine - INFO - Epoch(train) [28][220/2119] lr: 4.0000e-02 eta: 1 day, 2:13:39 time: 0.3570 data_time: 0.0231 memory: 11108 grad_norm: 2.8637 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5009 loss: 2.5009 2022/10/09 11:46:09 - mmengine - INFO - Epoch(train) [28][240/2119] lr: 4.0000e-02 eta: 1 day, 2:13:32 time: 0.3595 data_time: 0.0189 memory: 11108 grad_norm: 2.9043 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7011 loss: 2.7011 2022/10/09 11:46:17 - mmengine - INFO - Epoch(train) [28][260/2119] lr: 4.0000e-02 eta: 1 day, 2:13:24 time: 0.3628 data_time: 0.0171 memory: 11108 grad_norm: 2.8785 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6088 loss: 2.6088 2022/10/09 11:46:24 - mmengine - INFO - Epoch(train) [28][280/2119] lr: 4.0000e-02 eta: 1 day, 2:13:17 time: 0.3570 data_time: 0.0184 memory: 11108 grad_norm: 2.9059 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6358 loss: 2.6358 2022/10/09 11:46:31 - mmengine - INFO - Epoch(train) [28][300/2119] lr: 4.0000e-02 eta: 1 day, 2:13:09 time: 0.3623 data_time: 0.0198 memory: 11108 grad_norm: 2.9278 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5628 loss: 2.5628 2022/10/09 11:46:38 - mmengine - INFO - Epoch(train) [28][320/2119] lr: 4.0000e-02 eta: 1 day, 2:13:02 time: 0.3581 data_time: 0.0205 memory: 11108 grad_norm: 2.9292 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7909 loss: 2.7909 2022/10/09 11:46:45 - mmengine - INFO - Epoch(train) [28][340/2119] lr: 4.0000e-02 eta: 1 day, 2:12:54 time: 0.3599 data_time: 0.0182 memory: 11108 grad_norm: 2.9532 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.6873 loss: 2.6873 2022/10/09 11:46:53 - mmengine - INFO - Epoch(train) [28][360/2119] lr: 4.0000e-02 eta: 1 day, 2:12:47 time: 0.3576 data_time: 0.0188 memory: 11108 grad_norm: 2.9889 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.4944 loss: 2.4944 2022/10/09 11:47:00 - mmengine - INFO - Epoch(train) [28][380/2119] lr: 4.0000e-02 eta: 1 day, 2:12:39 time: 0.3567 data_time: 0.0187 memory: 11108 grad_norm: 2.9322 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5971 loss: 2.5971 2022/10/09 11:47:07 - mmengine - INFO - Epoch(train) [28][400/2119] lr: 4.0000e-02 eta: 1 day, 2:12:31 time: 0.3600 data_time: 0.0247 memory: 11108 grad_norm: 2.9326 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7205 loss: 2.7205 2022/10/09 11:47:14 - mmengine - INFO - Epoch(train) [28][420/2119] lr: 4.0000e-02 eta: 1 day, 2:12:24 time: 0.3630 data_time: 0.0190 memory: 11108 grad_norm: 2.9961 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8049 loss: 2.8049 2022/10/09 11:47:21 - mmengine - INFO - Epoch(train) [28][440/2119] lr: 4.0000e-02 eta: 1 day, 2:12:16 time: 0.3535 data_time: 0.0206 memory: 11108 grad_norm: 2.8853 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6378 loss: 2.6378 2022/10/09 11:47:28 - mmengine - INFO - Epoch(train) [28][460/2119] lr: 4.0000e-02 eta: 1 day, 2:12:08 time: 0.3560 data_time: 0.0213 memory: 11108 grad_norm: 2.9780 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5290 loss: 2.5290 2022/10/09 11:47:35 - mmengine - INFO - Epoch(train) [28][480/2119] lr: 4.0000e-02 eta: 1 day, 2:12:00 time: 0.3547 data_time: 0.0186 memory: 11108 grad_norm: 3.0314 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5969 loss: 2.5969 2022/10/09 11:47:43 - mmengine - INFO - Epoch(train) [28][500/2119] lr: 4.0000e-02 eta: 1 day, 2:11:52 time: 0.3548 data_time: 0.0182 memory: 11108 grad_norm: 2.9102 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5695 loss: 2.5695 2022/10/09 11:47:50 - mmengine - INFO - Epoch(train) [28][520/2119] lr: 4.0000e-02 eta: 1 day, 2:11:45 time: 0.3619 data_time: 0.0222 memory: 11108 grad_norm: 2.9052 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.3103 loss: 2.3103 2022/10/09 11:47:57 - mmengine - INFO - Epoch(train) [28][540/2119] lr: 4.0000e-02 eta: 1 day, 2:11:37 time: 0.3569 data_time: 0.0204 memory: 11108 grad_norm: 2.9179 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6099 loss: 2.6099 2022/10/09 11:48:04 - mmengine - INFO - Epoch(train) [28][560/2119] lr: 4.0000e-02 eta: 1 day, 2:11:30 time: 0.3589 data_time: 0.0237 memory: 11108 grad_norm: 2.9892 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.4610 loss: 2.4610 2022/10/09 11:48:11 - mmengine - INFO - Epoch(train) [28][580/2119] lr: 4.0000e-02 eta: 1 day, 2:11:22 time: 0.3581 data_time: 0.0166 memory: 11108 grad_norm: 2.9199 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9648 loss: 2.9648 2022/10/09 11:48:19 - mmengine - INFO - Epoch(train) [28][600/2119] lr: 4.0000e-02 eta: 1 day, 2:11:14 time: 0.3602 data_time: 0.0223 memory: 11108 grad_norm: 2.9448 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4801 loss: 2.4801 2022/10/09 11:48:26 - mmengine - INFO - Epoch(train) [28][620/2119] lr: 4.0000e-02 eta: 1 day, 2:11:07 time: 0.3565 data_time: 0.0182 memory: 11108 grad_norm: 2.9394 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7624 loss: 2.7624 2022/10/09 11:48:33 - mmengine - INFO - Epoch(train) [28][640/2119] lr: 4.0000e-02 eta: 1 day, 2:10:59 time: 0.3564 data_time: 0.0243 memory: 11108 grad_norm: 2.8923 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5958 loss: 2.5958 2022/10/09 11:48:40 - mmengine - INFO - Epoch(train) [28][660/2119] lr: 4.0000e-02 eta: 1 day, 2:10:51 time: 0.3586 data_time: 0.0208 memory: 11108 grad_norm: 2.9011 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4429 loss: 2.4429 2022/10/09 11:48:48 - mmengine - INFO - Epoch(train) [28][680/2119] lr: 4.0000e-02 eta: 1 day, 2:10:47 time: 0.3984 data_time: 0.0310 memory: 11108 grad_norm: 3.0009 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7862 loss: 2.7862 2022/10/09 11:48:58 - mmengine - INFO - Epoch(train) [28][700/2119] lr: 4.0000e-02 eta: 1 day, 2:10:53 time: 0.5113 data_time: 0.0225 memory: 11108 grad_norm: 2.9635 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5825 loss: 2.5825 2022/10/09 11:49:10 - mmengine - INFO - Epoch(train) [28][720/2119] lr: 4.0000e-02 eta: 1 day, 2:11:06 time: 0.5899 data_time: 0.0354 memory: 11108 grad_norm: 2.9737 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.4898 loss: 2.4898 2022/10/09 11:49:17 - mmengine - INFO - Epoch(train) [28][740/2119] lr: 4.0000e-02 eta: 1 day, 2:10:59 time: 0.3596 data_time: 0.0230 memory: 11108 grad_norm: 2.9533 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7331 loss: 2.7331 2022/10/09 11:49:26 - mmengine - INFO - Epoch(train) [28][760/2119] lr: 4.0000e-02 eta: 1 day, 2:10:58 time: 0.4344 data_time: 0.0225 memory: 11108 grad_norm: 2.9556 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6574 loss: 2.6574 2022/10/09 11:49:33 - mmengine - INFO - Epoch(train) [28][780/2119] lr: 4.0000e-02 eta: 1 day, 2:10:50 time: 0.3546 data_time: 0.0208 memory: 11108 grad_norm: 2.9712 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5683 loss: 2.5683 2022/10/09 11:49:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 11:49:40 - mmengine - INFO - Epoch(train) [28][800/2119] lr: 4.0000e-02 eta: 1 day, 2:10:43 time: 0.3635 data_time: 0.0254 memory: 11108 grad_norm: 2.9587 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7176 loss: 2.7176 2022/10/09 11:49:47 - mmengine - INFO - Epoch(train) [28][820/2119] lr: 4.0000e-02 eta: 1 day, 2:10:36 time: 0.3625 data_time: 0.0199 memory: 11108 grad_norm: 2.8818 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7585 loss: 2.7585 2022/10/09 11:49:55 - mmengine - INFO - Epoch(train) [28][840/2119] lr: 4.0000e-02 eta: 1 day, 2:10:28 time: 0.3558 data_time: 0.0194 memory: 11108 grad_norm: 2.9242 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6722 loss: 2.6722 2022/10/09 11:50:02 - mmengine - INFO - Epoch(train) [28][860/2119] lr: 4.0000e-02 eta: 1 day, 2:10:21 time: 0.3654 data_time: 0.0183 memory: 11108 grad_norm: 2.9249 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.9486 loss: 2.9486 2022/10/09 11:50:10 - mmengine - INFO - Epoch(train) [28][880/2119] lr: 4.0000e-02 eta: 1 day, 2:10:16 time: 0.3874 data_time: 0.0214 memory: 11108 grad_norm: 2.9894 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5992 loss: 2.5992 2022/10/09 11:50:25 - mmengine - INFO - Epoch(train) [28][900/2119] lr: 4.0000e-02 eta: 1 day, 2:10:44 time: 0.7652 data_time: 0.0322 memory: 11108 grad_norm: 2.9068 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6818 loss: 2.6818 2022/10/09 11:50:41 - mmengine - INFO - Epoch(train) [28][920/2119] lr: 4.0000e-02 eta: 1 day, 2:11:16 time: 0.7948 data_time: 0.0265 memory: 11108 grad_norm: 2.9574 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7068 loss: 2.7068 2022/10/09 11:50:48 - mmengine - INFO - Epoch(train) [28][940/2119] lr: 4.0000e-02 eta: 1 day, 2:11:08 time: 0.3564 data_time: 0.0206 memory: 11108 grad_norm: 2.9235 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5249 loss: 2.5249 2022/10/09 11:50:55 - mmengine - INFO - Epoch(train) [28][960/2119] lr: 4.0000e-02 eta: 1 day, 2:11:01 time: 0.3624 data_time: 0.0250 memory: 11108 grad_norm: 2.9554 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7355 loss: 2.7355 2022/10/09 11:51:02 - mmengine - INFO - Epoch(train) [28][980/2119] lr: 4.0000e-02 eta: 1 day, 2:10:53 time: 0.3619 data_time: 0.0205 memory: 11108 grad_norm: 2.9307 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7414 loss: 2.7414 2022/10/09 11:51:10 - mmengine - INFO - Epoch(train) [28][1000/2119] lr: 4.0000e-02 eta: 1 day, 2:10:45 time: 0.3544 data_time: 0.0232 memory: 11108 grad_norm: 2.8791 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6276 loss: 2.6276 2022/10/09 11:51:17 - mmengine - INFO - Epoch(train) [28][1020/2119] lr: 4.0000e-02 eta: 1 day, 2:10:38 time: 0.3667 data_time: 0.0220 memory: 11108 grad_norm: 2.8914 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5230 loss: 2.5230 2022/10/09 11:51:24 - mmengine - INFO - Epoch(train) [28][1040/2119] lr: 4.0000e-02 eta: 1 day, 2:10:31 time: 0.3565 data_time: 0.0206 memory: 11108 grad_norm: 2.8856 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4989 loss: 2.4989 2022/10/09 11:51:31 - mmengine - INFO - Epoch(train) [28][1060/2119] lr: 4.0000e-02 eta: 1 day, 2:10:23 time: 0.3633 data_time: 0.0211 memory: 11108 grad_norm: 2.9793 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6242 loss: 2.6242 2022/10/09 11:51:38 - mmengine - INFO - Epoch(train) [28][1080/2119] lr: 4.0000e-02 eta: 1 day, 2:10:16 time: 0.3602 data_time: 0.0187 memory: 11108 grad_norm: 2.8903 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5565 loss: 2.5565 2022/10/09 11:51:46 - mmengine - INFO - Epoch(train) [28][1100/2119] lr: 4.0000e-02 eta: 1 day, 2:10:08 time: 0.3570 data_time: 0.0196 memory: 11108 grad_norm: 2.9286 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5976 loss: 2.5976 2022/10/09 11:51:53 - mmengine - INFO - Epoch(train) [28][1120/2119] lr: 4.0000e-02 eta: 1 day, 2:10:00 time: 0.3575 data_time: 0.0206 memory: 11108 grad_norm: 2.9330 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6232 loss: 2.6232 2022/10/09 11:52:00 - mmengine - INFO - Epoch(train) [28][1140/2119] lr: 4.0000e-02 eta: 1 day, 2:09:53 time: 0.3643 data_time: 0.0216 memory: 11108 grad_norm: 2.9307 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5250 loss: 2.5250 2022/10/09 11:52:07 - mmengine - INFO - Epoch(train) [28][1160/2119] lr: 4.0000e-02 eta: 1 day, 2:09:45 time: 0.3577 data_time: 0.0188 memory: 11108 grad_norm: 2.9306 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.6304 loss: 2.6304 2022/10/09 11:52:14 - mmengine - INFO - Epoch(train) [28][1180/2119] lr: 4.0000e-02 eta: 1 day, 2:09:37 time: 0.3554 data_time: 0.0222 memory: 11108 grad_norm: 2.9521 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4631 loss: 2.4631 2022/10/09 11:52:22 - mmengine - INFO - Epoch(train) [28][1200/2119] lr: 4.0000e-02 eta: 1 day, 2:09:32 time: 0.3805 data_time: 0.0220 memory: 11108 grad_norm: 2.9856 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.4795 loss: 2.4795 2022/10/09 11:52:29 - mmengine - INFO - Epoch(train) [28][1220/2119] lr: 4.0000e-02 eta: 1 day, 2:09:24 time: 0.3559 data_time: 0.0206 memory: 11108 grad_norm: 2.9140 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8850 loss: 2.8850 2022/10/09 11:52:36 - mmengine - INFO - Epoch(train) [28][1240/2119] lr: 4.0000e-02 eta: 1 day, 2:09:17 time: 0.3684 data_time: 0.0220 memory: 11108 grad_norm: 2.9463 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5400 loss: 2.5400 2022/10/09 11:52:44 - mmengine - INFO - Epoch(train) [28][1260/2119] lr: 4.0000e-02 eta: 1 day, 2:09:09 time: 0.3536 data_time: 0.0222 memory: 11108 grad_norm: 2.9010 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4752 loss: 2.4752 2022/10/09 11:52:51 - mmengine - INFO - Epoch(train) [28][1280/2119] lr: 4.0000e-02 eta: 1 day, 2:09:01 time: 0.3584 data_time: 0.0187 memory: 11108 grad_norm: 2.9295 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6571 loss: 2.6571 2022/10/09 11:52:58 - mmengine - INFO - Epoch(train) [28][1300/2119] lr: 4.0000e-02 eta: 1 day, 2:08:54 time: 0.3627 data_time: 0.0193 memory: 11108 grad_norm: 2.9624 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4563 loss: 2.4563 2022/10/09 11:53:05 - mmengine - INFO - Epoch(train) [28][1320/2119] lr: 4.0000e-02 eta: 1 day, 2:08:46 time: 0.3562 data_time: 0.0189 memory: 11108 grad_norm: 2.9398 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.3987 loss: 2.3987 2022/10/09 11:53:12 - mmengine - INFO - Epoch(train) [28][1340/2119] lr: 4.0000e-02 eta: 1 day, 2:08:38 time: 0.3575 data_time: 0.0229 memory: 11108 grad_norm: 2.9739 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8226 loss: 2.8226 2022/10/09 11:53:20 - mmengine - INFO - Epoch(train) [28][1360/2119] lr: 4.0000e-02 eta: 1 day, 2:08:31 time: 0.3645 data_time: 0.0265 memory: 11108 grad_norm: 2.9259 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4597 loss: 2.4597 2022/10/09 11:53:27 - mmengine - INFO - Epoch(train) [28][1380/2119] lr: 4.0000e-02 eta: 1 day, 2:08:23 time: 0.3549 data_time: 0.0197 memory: 11108 grad_norm: 2.9065 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7476 loss: 2.7476 2022/10/09 11:53:34 - mmengine - INFO - Epoch(train) [28][1400/2119] lr: 4.0000e-02 eta: 1 day, 2:08:16 time: 0.3593 data_time: 0.0183 memory: 11108 grad_norm: 2.9204 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6686 loss: 2.6686 2022/10/09 11:53:41 - mmengine - INFO - Epoch(train) [28][1420/2119] lr: 4.0000e-02 eta: 1 day, 2:08:08 time: 0.3614 data_time: 0.0227 memory: 11108 grad_norm: 2.9057 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4698 loss: 2.4698 2022/10/09 11:53:48 - mmengine - INFO - Epoch(train) [28][1440/2119] lr: 4.0000e-02 eta: 1 day, 2:08:00 time: 0.3536 data_time: 0.0172 memory: 11108 grad_norm: 2.8842 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7077 loss: 2.7077 2022/10/09 11:53:55 - mmengine - INFO - Epoch(train) [28][1460/2119] lr: 4.0000e-02 eta: 1 day, 2:07:53 time: 0.3606 data_time: 0.0221 memory: 11108 grad_norm: 2.9067 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7695 loss: 2.7695 2022/10/09 11:54:02 - mmengine - INFO - Epoch(train) [28][1480/2119] lr: 4.0000e-02 eta: 1 day, 2:07:45 time: 0.3574 data_time: 0.0202 memory: 11108 grad_norm: 2.9417 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6599 loss: 2.6599 2022/10/09 11:54:10 - mmengine - INFO - Epoch(train) [28][1500/2119] lr: 4.0000e-02 eta: 1 day, 2:07:38 time: 0.3612 data_time: 0.0213 memory: 11108 grad_norm: 2.9040 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7909 loss: 2.7909 2022/10/09 11:54:17 - mmengine - INFO - Epoch(train) [28][1520/2119] lr: 4.0000e-02 eta: 1 day, 2:07:30 time: 0.3575 data_time: 0.0199 memory: 11108 grad_norm: 2.8566 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6496 loss: 2.6496 2022/10/09 11:54:24 - mmengine - INFO - Epoch(train) [28][1540/2119] lr: 4.0000e-02 eta: 1 day, 2:07:22 time: 0.3580 data_time: 0.0200 memory: 11108 grad_norm: 2.9207 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4227 loss: 2.4227 2022/10/09 11:54:31 - mmengine - INFO - Epoch(train) [28][1560/2119] lr: 4.0000e-02 eta: 1 day, 2:07:14 time: 0.3579 data_time: 0.0194 memory: 11108 grad_norm: 2.9603 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5806 loss: 2.5806 2022/10/09 11:54:38 - mmengine - INFO - Epoch(train) [28][1580/2119] lr: 4.0000e-02 eta: 1 day, 2:07:07 time: 0.3622 data_time: 0.0208 memory: 11108 grad_norm: 2.9034 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6741 loss: 2.6741 2022/10/09 11:54:46 - mmengine - INFO - Epoch(train) [28][1600/2119] lr: 4.0000e-02 eta: 1 day, 2:06:59 time: 0.3589 data_time: 0.0202 memory: 11108 grad_norm: 2.9543 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 2.8386 loss: 2.8386 2022/10/09 11:54:53 - mmengine - INFO - Epoch(train) [28][1620/2119] lr: 4.0000e-02 eta: 1 day, 2:06:51 time: 0.3542 data_time: 0.0186 memory: 11108 grad_norm: 2.9546 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7633 loss: 2.7633 2022/10/09 11:55:00 - mmengine - INFO - Epoch(train) [28][1640/2119] lr: 4.0000e-02 eta: 1 day, 2:06:44 time: 0.3655 data_time: 0.0202 memory: 11108 grad_norm: 2.9301 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6056 loss: 2.6056 2022/10/09 11:55:07 - mmengine - INFO - Epoch(train) [28][1660/2119] lr: 4.0000e-02 eta: 1 day, 2:06:37 time: 0.3555 data_time: 0.0225 memory: 11108 grad_norm: 2.9175 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5835 loss: 2.5835 2022/10/09 11:55:14 - mmengine - INFO - Epoch(train) [28][1680/2119] lr: 4.0000e-02 eta: 1 day, 2:06:29 time: 0.3571 data_time: 0.0205 memory: 11108 grad_norm: 2.9121 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.4445 loss: 2.4445 2022/10/09 11:55:22 - mmengine - INFO - Epoch(train) [28][1700/2119] lr: 4.0000e-02 eta: 1 day, 2:06:22 time: 0.3642 data_time: 0.0209 memory: 11108 grad_norm: 2.9736 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.4992 loss: 2.4992 2022/10/09 11:55:29 - mmengine - INFO - Epoch(train) [28][1720/2119] lr: 4.0000e-02 eta: 1 day, 2:06:14 time: 0.3595 data_time: 0.0196 memory: 11108 grad_norm: 2.9431 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7011 loss: 2.7011 2022/10/09 11:55:36 - mmengine - INFO - Epoch(train) [28][1740/2119] lr: 4.0000e-02 eta: 1 day, 2:06:06 time: 0.3556 data_time: 0.0205 memory: 11108 grad_norm: 2.9450 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6323 loss: 2.6323 2022/10/09 11:55:43 - mmengine - INFO - Epoch(train) [28][1760/2119] lr: 4.0000e-02 eta: 1 day, 2:05:59 time: 0.3601 data_time: 0.0211 memory: 11108 grad_norm: 2.8525 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4545 loss: 2.4545 2022/10/09 11:55:50 - mmengine - INFO - Epoch(train) [28][1780/2119] lr: 4.0000e-02 eta: 1 day, 2:05:51 time: 0.3574 data_time: 0.0231 memory: 11108 grad_norm: 2.9148 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8142 loss: 2.8142 2022/10/09 11:55:53 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 11:55:57 - mmengine - INFO - Epoch(train) [28][1800/2119] lr: 4.0000e-02 eta: 1 day, 2:05:44 time: 0.3653 data_time: 0.0227 memory: 11108 grad_norm: 2.9398 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5526 loss: 2.5526 2022/10/09 11:56:05 - mmengine - INFO - Epoch(train) [28][1820/2119] lr: 4.0000e-02 eta: 1 day, 2:05:36 time: 0.3596 data_time: 0.0233 memory: 11108 grad_norm: 2.9677 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6922 loss: 2.6922 2022/10/09 11:56:12 - mmengine - INFO - Epoch(train) [28][1840/2119] lr: 4.0000e-02 eta: 1 day, 2:05:29 time: 0.3579 data_time: 0.0173 memory: 11108 grad_norm: 2.9573 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4281 loss: 2.4281 2022/10/09 11:56:19 - mmengine - INFO - Epoch(train) [28][1860/2119] lr: 4.0000e-02 eta: 1 day, 2:05:21 time: 0.3629 data_time: 0.0198 memory: 11108 grad_norm: 2.9652 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4654 loss: 2.4654 2022/10/09 11:56:26 - mmengine - INFO - Epoch(train) [28][1880/2119] lr: 4.0000e-02 eta: 1 day, 2:05:13 time: 0.3557 data_time: 0.0194 memory: 11108 grad_norm: 2.9691 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7842 loss: 2.7842 2022/10/09 11:56:33 - mmengine - INFO - Epoch(train) [28][1900/2119] lr: 4.0000e-02 eta: 1 day, 2:05:06 time: 0.3566 data_time: 0.0211 memory: 11108 grad_norm: 2.9402 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6173 loss: 2.6173 2022/10/09 11:56:41 - mmengine - INFO - Epoch(train) [28][1920/2119] lr: 4.0000e-02 eta: 1 day, 2:04:58 time: 0.3606 data_time: 0.0170 memory: 11108 grad_norm: 2.9164 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8934 loss: 2.8934 2022/10/09 11:56:48 - mmengine - INFO - Epoch(train) [28][1940/2119] lr: 4.0000e-02 eta: 1 day, 2:04:50 time: 0.3585 data_time: 0.0235 memory: 11108 grad_norm: 2.8846 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6342 loss: 2.6342 2022/10/09 11:56:55 - mmengine - INFO - Epoch(train) [28][1960/2119] lr: 4.0000e-02 eta: 1 day, 2:04:43 time: 0.3579 data_time: 0.0202 memory: 11108 grad_norm: 2.9555 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7019 loss: 2.7019 2022/10/09 11:57:02 - mmengine - INFO - Epoch(train) [28][1980/2119] lr: 4.0000e-02 eta: 1 day, 2:04:35 time: 0.3581 data_time: 0.0196 memory: 11108 grad_norm: 2.9188 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6694 loss: 2.6694 2022/10/09 11:57:09 - mmengine - INFO - Epoch(train) [28][2000/2119] lr: 4.0000e-02 eta: 1 day, 2:04:28 time: 0.3610 data_time: 0.0209 memory: 11108 grad_norm: 2.8623 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4372 loss: 2.4372 2022/10/09 11:57:16 - mmengine - INFO - Epoch(train) [28][2020/2119] lr: 4.0000e-02 eta: 1 day, 2:04:20 time: 0.3578 data_time: 0.0219 memory: 11108 grad_norm: 2.8868 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6006 loss: 2.6006 2022/10/09 11:57:24 - mmengine - INFO - Epoch(train) [28][2040/2119] lr: 4.0000e-02 eta: 1 day, 2:04:12 time: 0.3601 data_time: 0.0197 memory: 11108 grad_norm: 2.9380 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5018 loss: 2.5018 2022/10/09 11:57:31 - mmengine - INFO - Epoch(train) [28][2060/2119] lr: 4.0000e-02 eta: 1 day, 2:04:05 time: 0.3583 data_time: 0.0201 memory: 11108 grad_norm: 2.9720 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5056 loss: 2.5056 2022/10/09 11:57:38 - mmengine - INFO - Epoch(train) [28][2080/2119] lr: 4.0000e-02 eta: 1 day, 2:03:57 time: 0.3570 data_time: 0.0181 memory: 11108 grad_norm: 2.9046 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3665 loss: 2.3665 2022/10/09 11:57:45 - mmengine - INFO - Epoch(train) [28][2100/2119] lr: 4.0000e-02 eta: 1 day, 2:03:49 time: 0.3567 data_time: 0.0204 memory: 11108 grad_norm: 2.9390 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.3709 loss: 2.3709 2022/10/09 11:57:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 11:57:52 - mmengine - INFO - Epoch(train) [28][2119/2119] lr: 4.0000e-02 eta: 1 day, 2:03:49 time: 0.3401 data_time: 0.0179 memory: 11108 grad_norm: 3.0003 top1_acc: 0.6000 top5_acc: 0.8000 loss_cls: 2.6691 loss: 2.6691 2022/10/09 11:57:52 - mmengine - INFO - Saving checkpoint at 28 epochs 2022/10/09 11:58:04 - mmengine - INFO - Epoch(train) [29][20/2119] lr: 4.0000e-02 eta: 1 day, 2:03:13 time: 0.4588 data_time: 0.1192 memory: 11108 grad_norm: 2.9085 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.5652 loss: 2.5652 2022/10/09 11:58:11 - mmengine - INFO - Epoch(train) [29][40/2119] lr: 4.0000e-02 eta: 1 day, 2:03:06 time: 0.3660 data_time: 0.0220 memory: 11108 grad_norm: 2.8756 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4263 loss: 2.4263 2022/10/09 11:58:18 - mmengine - INFO - Epoch(train) [29][60/2119] lr: 4.0000e-02 eta: 1 day, 2:02:59 time: 0.3574 data_time: 0.0217 memory: 11108 grad_norm: 2.9147 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.4400 loss: 2.4400 2022/10/09 11:58:25 - mmengine - INFO - Epoch(train) [29][80/2119] lr: 4.0000e-02 eta: 1 day, 2:02:51 time: 0.3624 data_time: 0.0204 memory: 11108 grad_norm: 2.9023 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4656 loss: 2.4656 2022/10/09 11:58:33 - mmengine - INFO - Epoch(train) [29][100/2119] lr: 4.0000e-02 eta: 1 day, 2:02:44 time: 0.3585 data_time: 0.0237 memory: 11108 grad_norm: 2.9320 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5415 loss: 2.5415 2022/10/09 11:58:40 - mmengine - INFO - Epoch(train) [29][120/2119] lr: 4.0000e-02 eta: 1 day, 2:02:36 time: 0.3631 data_time: 0.0212 memory: 11108 grad_norm: 2.9623 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6667 loss: 2.6667 2022/10/09 11:58:47 - mmengine - INFO - Epoch(train) [29][140/2119] lr: 4.0000e-02 eta: 1 day, 2:02:29 time: 0.3577 data_time: 0.0186 memory: 11108 grad_norm: 2.9350 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7503 loss: 2.7503 2022/10/09 11:58:54 - mmengine - INFO - Epoch(train) [29][160/2119] lr: 4.0000e-02 eta: 1 day, 2:02:21 time: 0.3587 data_time: 0.0243 memory: 11108 grad_norm: 2.9217 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6054 loss: 2.6054 2022/10/09 11:59:02 - mmengine - INFO - Epoch(train) [29][180/2119] lr: 4.0000e-02 eta: 1 day, 2:02:15 time: 0.3707 data_time: 0.0255 memory: 11108 grad_norm: 2.9657 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6282 loss: 2.6282 2022/10/09 11:59:09 - mmengine - INFO - Epoch(train) [29][200/2119] lr: 4.0000e-02 eta: 1 day, 2:02:07 time: 0.3611 data_time: 0.0266 memory: 11108 grad_norm: 2.8927 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5932 loss: 2.5932 2022/10/09 11:59:16 - mmengine - INFO - Epoch(train) [29][220/2119] lr: 4.0000e-02 eta: 1 day, 2:01:59 time: 0.3557 data_time: 0.0235 memory: 11108 grad_norm: 2.9118 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5651 loss: 2.5651 2022/10/09 11:59:23 - mmengine - INFO - Epoch(train) [29][240/2119] lr: 4.0000e-02 eta: 1 day, 2:01:52 time: 0.3588 data_time: 0.0187 memory: 11108 grad_norm: 2.9905 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6272 loss: 2.6272 2022/10/09 11:59:30 - mmengine - INFO - Epoch(train) [29][260/2119] lr: 4.0000e-02 eta: 1 day, 2:01:44 time: 0.3578 data_time: 0.0229 memory: 11108 grad_norm: 2.8878 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8608 loss: 2.8608 2022/10/09 11:59:37 - mmengine - INFO - Epoch(train) [29][280/2119] lr: 4.0000e-02 eta: 1 day, 2:01:36 time: 0.3588 data_time: 0.0201 memory: 11108 grad_norm: 2.9579 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5541 loss: 2.5541 2022/10/09 11:59:45 - mmengine - INFO - Epoch(train) [29][300/2119] lr: 4.0000e-02 eta: 1 day, 2:01:29 time: 0.3584 data_time: 0.0217 memory: 11108 grad_norm: 2.8791 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5812 loss: 2.5812 2022/10/09 11:59:52 - mmengine - INFO - Epoch(train) [29][320/2119] lr: 4.0000e-02 eta: 1 day, 2:01:21 time: 0.3584 data_time: 0.0205 memory: 11108 grad_norm: 2.9926 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6720 loss: 2.6720 2022/10/09 11:59:59 - mmengine - INFO - Epoch(train) [29][340/2119] lr: 4.0000e-02 eta: 1 day, 2:01:14 time: 0.3603 data_time: 0.0181 memory: 11108 grad_norm: 2.9467 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8195 loss: 2.8195 2022/10/09 12:00:09 - mmengine - INFO - Epoch(train) [29][360/2119] lr: 4.0000e-02 eta: 1 day, 2:01:16 time: 0.4775 data_time: 0.0216 memory: 11108 grad_norm: 2.9027 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6722 loss: 2.6722 2022/10/09 12:00:16 - mmengine - INFO - Epoch(train) [29][380/2119] lr: 4.0000e-02 eta: 1 day, 2:01:09 time: 0.3587 data_time: 0.0182 memory: 11108 grad_norm: 2.8833 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4601 loss: 2.4601 2022/10/09 12:00:23 - mmengine - INFO - Epoch(train) [29][400/2119] lr: 4.0000e-02 eta: 1 day, 2:01:01 time: 0.3623 data_time: 0.0178 memory: 11108 grad_norm: 2.8950 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7502 loss: 2.7502 2022/10/09 12:00:30 - mmengine - INFO - Epoch(train) [29][420/2119] lr: 4.0000e-02 eta: 1 day, 2:00:54 time: 0.3592 data_time: 0.0218 memory: 11108 grad_norm: 2.9743 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5781 loss: 2.5781 2022/10/09 12:00:37 - mmengine - INFO - Epoch(train) [29][440/2119] lr: 4.0000e-02 eta: 1 day, 2:00:46 time: 0.3589 data_time: 0.0202 memory: 11108 grad_norm: 2.9283 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5163 loss: 2.5163 2022/10/09 12:00:44 - mmengine - INFO - Epoch(train) [29][460/2119] lr: 4.0000e-02 eta: 1 day, 2:00:39 time: 0.3589 data_time: 0.0172 memory: 11108 grad_norm: 2.9629 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7036 loss: 2.7036 2022/10/09 12:00:52 - mmengine - INFO - Epoch(train) [29][480/2119] lr: 4.0000e-02 eta: 1 day, 2:00:31 time: 0.3627 data_time: 0.0207 memory: 11108 grad_norm: 2.9769 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6908 loss: 2.6908 2022/10/09 12:00:59 - mmengine - INFO - Epoch(train) [29][500/2119] lr: 4.0000e-02 eta: 1 day, 2:00:24 time: 0.3575 data_time: 0.0210 memory: 11108 grad_norm: 2.9440 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7436 loss: 2.7436 2022/10/09 12:01:06 - mmengine - INFO - Epoch(train) [29][520/2119] lr: 4.0000e-02 eta: 1 day, 2:00:17 time: 0.3646 data_time: 0.0253 memory: 11108 grad_norm: 2.9012 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7343 loss: 2.7343 2022/10/09 12:01:13 - mmengine - INFO - Epoch(train) [29][540/2119] lr: 4.0000e-02 eta: 1 day, 2:00:09 time: 0.3638 data_time: 0.0187 memory: 11108 grad_norm: 2.9685 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5372 loss: 2.5372 2022/10/09 12:01:21 - mmengine - INFO - Epoch(train) [29][560/2119] lr: 4.0000e-02 eta: 1 day, 2:00:02 time: 0.3561 data_time: 0.0204 memory: 11108 grad_norm: 2.8894 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6411 loss: 2.6411 2022/10/09 12:01:28 - mmengine - INFO - Epoch(train) [29][580/2119] lr: 4.0000e-02 eta: 1 day, 1:59:54 time: 0.3619 data_time: 0.0191 memory: 11108 grad_norm: 2.9732 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6880 loss: 2.6880 2022/10/09 12:01:35 - mmengine - INFO - Epoch(train) [29][600/2119] lr: 4.0000e-02 eta: 1 day, 1:59:47 time: 0.3586 data_time: 0.0208 memory: 11108 grad_norm: 2.9194 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8405 loss: 2.8405 2022/10/09 12:01:42 - mmengine - INFO - Epoch(train) [29][620/2119] lr: 4.0000e-02 eta: 1 day, 1:59:39 time: 0.3565 data_time: 0.0182 memory: 11108 grad_norm: 2.9128 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5349 loss: 2.5349 2022/10/09 12:01:49 - mmengine - INFO - Epoch(train) [29][640/2119] lr: 4.0000e-02 eta: 1 day, 1:59:31 time: 0.3627 data_time: 0.0194 memory: 11108 grad_norm: 2.9671 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8016 loss: 2.8016 2022/10/09 12:01:57 - mmengine - INFO - Epoch(train) [29][660/2119] lr: 4.0000e-02 eta: 1 day, 1:59:24 time: 0.3571 data_time: 0.0189 memory: 11108 grad_norm: 2.8674 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7687 loss: 2.7687 2022/10/09 12:01:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 12:02:04 - mmengine - INFO - Epoch(train) [29][680/2119] lr: 4.0000e-02 eta: 1 day, 1:59:16 time: 0.3591 data_time: 0.0223 memory: 11108 grad_norm: 2.8851 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5628 loss: 2.5628 2022/10/09 12:02:11 - mmengine - INFO - Epoch(train) [29][700/2119] lr: 4.0000e-02 eta: 1 day, 1:59:08 time: 0.3569 data_time: 0.0250 memory: 11108 grad_norm: 2.9502 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6810 loss: 2.6810 2022/10/09 12:02:18 - mmengine - INFO - Epoch(train) [29][720/2119] lr: 4.0000e-02 eta: 1 day, 1:59:00 time: 0.3542 data_time: 0.0176 memory: 11108 grad_norm: 2.8824 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6258 loss: 2.6258 2022/10/09 12:02:25 - mmengine - INFO - Epoch(train) [29][740/2119] lr: 4.0000e-02 eta: 1 day, 1:58:53 time: 0.3560 data_time: 0.0232 memory: 11108 grad_norm: 2.9349 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 2.6029 loss: 2.6029 2022/10/09 12:02:32 - mmengine - INFO - Epoch(train) [29][760/2119] lr: 4.0000e-02 eta: 1 day, 1:58:46 time: 0.3667 data_time: 0.0176 memory: 11108 grad_norm: 2.9441 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6165 loss: 2.6165 2022/10/09 12:02:39 - mmengine - INFO - Epoch(train) [29][780/2119] lr: 4.0000e-02 eta: 1 day, 1:58:38 time: 0.3551 data_time: 0.0208 memory: 11108 grad_norm: 2.9132 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5895 loss: 2.5895 2022/10/09 12:02:47 - mmengine - INFO - Epoch(train) [29][800/2119] lr: 4.0000e-02 eta: 1 day, 1:58:30 time: 0.3607 data_time: 0.0203 memory: 11108 grad_norm: 2.8826 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.3859 loss: 2.3859 2022/10/09 12:02:54 - mmengine - INFO - Epoch(train) [29][820/2119] lr: 4.0000e-02 eta: 1 day, 1:58:22 time: 0.3550 data_time: 0.0213 memory: 11108 grad_norm: 2.9414 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7159 loss: 2.7159 2022/10/09 12:03:01 - mmengine - INFO - Epoch(train) [29][840/2119] lr: 4.0000e-02 eta: 1 day, 1:58:14 time: 0.3547 data_time: 0.0174 memory: 11108 grad_norm: 2.9267 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.4503 loss: 2.4503 2022/10/09 12:03:08 - mmengine - INFO - Epoch(train) [29][860/2119] lr: 4.0000e-02 eta: 1 day, 1:58:06 time: 0.3559 data_time: 0.0212 memory: 11108 grad_norm: 2.9476 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5967 loss: 2.5967 2022/10/09 12:03:15 - mmengine - INFO - Epoch(train) [29][880/2119] lr: 4.0000e-02 eta: 1 day, 1:57:59 time: 0.3624 data_time: 0.0227 memory: 11108 grad_norm: 2.8861 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6905 loss: 2.6905 2022/10/09 12:03:22 - mmengine - INFO - Epoch(train) [29][900/2119] lr: 4.0000e-02 eta: 1 day, 1:57:51 time: 0.3557 data_time: 0.0204 memory: 11108 grad_norm: 2.9506 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6100 loss: 2.6100 2022/10/09 12:03:30 - mmengine - INFO - Epoch(train) [29][920/2119] lr: 4.0000e-02 eta: 1 day, 1:57:44 time: 0.3596 data_time: 0.0226 memory: 11108 grad_norm: 2.9375 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7464 loss: 2.7464 2022/10/09 12:03:37 - mmengine - INFO - Epoch(train) [29][940/2119] lr: 4.0000e-02 eta: 1 day, 1:57:36 time: 0.3548 data_time: 0.0219 memory: 11108 grad_norm: 2.8603 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.5732 loss: 2.5732 2022/10/09 12:03:44 - mmengine - INFO - Epoch(train) [29][960/2119] lr: 4.0000e-02 eta: 1 day, 1:57:29 time: 0.3617 data_time: 0.0221 memory: 11108 grad_norm: 2.8950 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6782 loss: 2.6782 2022/10/09 12:03:51 - mmengine - INFO - Epoch(train) [29][980/2119] lr: 4.0000e-02 eta: 1 day, 1:57:21 time: 0.3576 data_time: 0.0215 memory: 11108 grad_norm: 2.9285 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5850 loss: 2.5850 2022/10/09 12:03:58 - mmengine - INFO - Epoch(train) [29][1000/2119] lr: 4.0000e-02 eta: 1 day, 1:57:13 time: 0.3568 data_time: 0.0196 memory: 11108 grad_norm: 2.9231 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6731 loss: 2.6731 2022/10/09 12:04:05 - mmengine - INFO - Epoch(train) [29][1020/2119] lr: 4.0000e-02 eta: 1 day, 1:57:06 time: 0.3621 data_time: 0.0204 memory: 11108 grad_norm: 2.9028 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6612 loss: 2.6612 2022/10/09 12:04:13 - mmengine - INFO - Epoch(train) [29][1040/2119] lr: 4.0000e-02 eta: 1 day, 1:56:58 time: 0.3597 data_time: 0.0211 memory: 11108 grad_norm: 2.9539 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8121 loss: 2.8121 2022/10/09 12:04:20 - mmengine - INFO - Epoch(train) [29][1060/2119] lr: 4.0000e-02 eta: 1 day, 1:56:51 time: 0.3587 data_time: 0.0198 memory: 11108 grad_norm: 2.9177 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3308 loss: 2.3308 2022/10/09 12:04:27 - mmengine - INFO - Epoch(train) [29][1080/2119] lr: 4.0000e-02 eta: 1 day, 1:56:43 time: 0.3583 data_time: 0.0203 memory: 11108 grad_norm: 2.9590 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5117 loss: 2.5117 2022/10/09 12:04:34 - mmengine - INFO - Epoch(train) [29][1100/2119] lr: 4.0000e-02 eta: 1 day, 1:56:36 time: 0.3608 data_time: 0.0244 memory: 11108 grad_norm: 2.9329 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8038 loss: 2.8038 2022/10/09 12:04:41 - mmengine - INFO - Epoch(train) [29][1120/2119] lr: 4.0000e-02 eta: 1 day, 1:56:28 time: 0.3563 data_time: 0.0211 memory: 11108 grad_norm: 2.8240 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9619 loss: 2.9619 2022/10/09 12:04:49 - mmengine - INFO - Epoch(train) [29][1140/2119] lr: 4.0000e-02 eta: 1 day, 1:56:20 time: 0.3623 data_time: 0.0215 memory: 11108 grad_norm: 2.8825 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7203 loss: 2.7203 2022/10/09 12:04:56 - mmengine - INFO - Epoch(train) [29][1160/2119] lr: 4.0000e-02 eta: 1 day, 1:56:13 time: 0.3560 data_time: 0.0185 memory: 11108 grad_norm: 2.9570 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7676 loss: 2.7676 2022/10/09 12:05:03 - mmengine - INFO - Epoch(train) [29][1180/2119] lr: 4.0000e-02 eta: 1 day, 1:56:05 time: 0.3564 data_time: 0.0202 memory: 11108 grad_norm: 2.9812 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4839 loss: 2.4839 2022/10/09 12:05:10 - mmengine - INFO - Epoch(train) [29][1200/2119] lr: 4.0000e-02 eta: 1 day, 1:55:57 time: 0.3589 data_time: 0.0219 memory: 11108 grad_norm: 2.9965 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.6336 loss: 2.6336 2022/10/09 12:05:17 - mmengine - INFO - Epoch(train) [29][1220/2119] lr: 4.0000e-02 eta: 1 day, 1:55:49 time: 0.3567 data_time: 0.0199 memory: 11108 grad_norm: 2.8974 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6421 loss: 2.6421 2022/10/09 12:05:24 - mmengine - INFO - Epoch(train) [29][1240/2119] lr: 4.0000e-02 eta: 1 day, 1:55:42 time: 0.3573 data_time: 0.0204 memory: 11108 grad_norm: 2.9396 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.6700 loss: 2.6700 2022/10/09 12:05:32 - mmengine - INFO - Epoch(train) [29][1260/2119] lr: 4.0000e-02 eta: 1 day, 1:55:34 time: 0.3625 data_time: 0.0221 memory: 11108 grad_norm: 2.9250 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.3824 loss: 2.3824 2022/10/09 12:05:39 - mmengine - INFO - Epoch(train) [29][1280/2119] lr: 4.0000e-02 eta: 1 day, 1:55:26 time: 0.3553 data_time: 0.0198 memory: 11108 grad_norm: 2.9260 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6387 loss: 2.6387 2022/10/09 12:05:46 - mmengine - INFO - Epoch(train) [29][1300/2119] lr: 4.0000e-02 eta: 1 day, 1:55:19 time: 0.3578 data_time: 0.0244 memory: 11108 grad_norm: 2.9639 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7685 loss: 2.7685 2022/10/09 12:05:53 - mmengine - INFO - Epoch(train) [29][1320/2119] lr: 4.0000e-02 eta: 1 day, 1:55:11 time: 0.3564 data_time: 0.0175 memory: 11108 grad_norm: 2.9421 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7174 loss: 2.7174 2022/10/09 12:06:00 - mmengine - INFO - Epoch(train) [29][1340/2119] lr: 4.0000e-02 eta: 1 day, 1:55:04 time: 0.3601 data_time: 0.0222 memory: 11108 grad_norm: 2.9613 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4348 loss: 2.4348 2022/10/09 12:06:07 - mmengine - INFO - Epoch(train) [29][1360/2119] lr: 4.0000e-02 eta: 1 day, 1:54:56 time: 0.3599 data_time: 0.0223 memory: 11108 grad_norm: 2.9452 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.4869 loss: 2.4869 2022/10/09 12:06:15 - mmengine - INFO - Epoch(train) [29][1380/2119] lr: 4.0000e-02 eta: 1 day, 1:54:48 time: 0.3575 data_time: 0.0174 memory: 11108 grad_norm: 2.9808 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5943 loss: 2.5943 2022/10/09 12:06:22 - mmengine - INFO - Epoch(train) [29][1400/2119] lr: 4.0000e-02 eta: 1 day, 1:54:41 time: 0.3604 data_time: 0.0194 memory: 11108 grad_norm: 3.0008 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9025 loss: 2.9025 2022/10/09 12:06:29 - mmengine - INFO - Epoch(train) [29][1420/2119] lr: 4.0000e-02 eta: 1 day, 1:54:33 time: 0.3597 data_time: 0.0184 memory: 11108 grad_norm: 2.9656 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8659 loss: 2.8659 2022/10/09 12:06:36 - mmengine - INFO - Epoch(train) [29][1440/2119] lr: 4.0000e-02 eta: 1 day, 1:54:25 time: 0.3550 data_time: 0.0220 memory: 11108 grad_norm: 2.9194 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.6568 loss: 2.6568 2022/10/09 12:06:43 - mmengine - INFO - Epoch(train) [29][1460/2119] lr: 4.0000e-02 eta: 1 day, 1:54:18 time: 0.3615 data_time: 0.0256 memory: 11108 grad_norm: 2.9541 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.5859 loss: 2.5859 2022/10/09 12:06:50 - mmengine - INFO - Epoch(train) [29][1480/2119] lr: 4.0000e-02 eta: 1 day, 1:54:10 time: 0.3552 data_time: 0.0211 memory: 11108 grad_norm: 2.9817 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6816 loss: 2.6816 2022/10/09 12:06:58 - mmengine - INFO - Epoch(train) [29][1500/2119] lr: 4.0000e-02 eta: 1 day, 1:54:03 time: 0.3615 data_time: 0.0229 memory: 11108 grad_norm: 2.9246 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8885 loss: 2.8885 2022/10/09 12:07:05 - mmengine - INFO - Epoch(train) [29][1520/2119] lr: 4.0000e-02 eta: 1 day, 1:53:55 time: 0.3585 data_time: 0.0211 memory: 11108 grad_norm: 2.8835 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4522 loss: 2.4522 2022/10/09 12:07:12 - mmengine - INFO - Epoch(train) [29][1540/2119] lr: 4.0000e-02 eta: 1 day, 1:53:48 time: 0.3619 data_time: 0.0192 memory: 11108 grad_norm: 2.9765 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7413 loss: 2.7413 2022/10/09 12:07:19 - mmengine - INFO - Epoch(train) [29][1560/2119] lr: 4.0000e-02 eta: 1 day, 1:53:41 time: 0.3628 data_time: 0.0169 memory: 11108 grad_norm: 2.8971 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6426 loss: 2.6426 2022/10/09 12:07:26 - mmengine - INFO - Epoch(train) [29][1580/2119] lr: 4.0000e-02 eta: 1 day, 1:53:33 time: 0.3546 data_time: 0.0182 memory: 11108 grad_norm: 2.8899 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5475 loss: 2.5475 2022/10/09 12:07:34 - mmengine - INFO - Epoch(train) [29][1600/2119] lr: 4.0000e-02 eta: 1 day, 1:53:25 time: 0.3589 data_time: 0.0236 memory: 11108 grad_norm: 2.9845 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7614 loss: 2.7614 2022/10/09 12:07:41 - mmengine - INFO - Epoch(train) [29][1620/2119] lr: 4.0000e-02 eta: 1 day, 1:53:17 time: 0.3583 data_time: 0.0184 memory: 11108 grad_norm: 2.9778 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6963 loss: 2.6963 2022/10/09 12:07:48 - mmengine - INFO - Epoch(train) [29][1640/2119] lr: 4.0000e-02 eta: 1 day, 1:53:10 time: 0.3582 data_time: 0.0201 memory: 11108 grad_norm: 2.9693 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.5877 loss: 2.5877 2022/10/09 12:07:55 - mmengine - INFO - Epoch(train) [29][1660/2119] lr: 4.0000e-02 eta: 1 day, 1:53:02 time: 0.3560 data_time: 0.0219 memory: 11108 grad_norm: 2.9500 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6409 loss: 2.6409 2022/10/09 12:07:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 12:08:02 - mmengine - INFO - Epoch(train) [29][1680/2119] lr: 4.0000e-02 eta: 1 day, 1:52:55 time: 0.3623 data_time: 0.0207 memory: 11108 grad_norm: 2.9127 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8067 loss: 2.8067 2022/10/09 12:08:09 - mmengine - INFO - Epoch(train) [29][1700/2119] lr: 4.0000e-02 eta: 1 day, 1:52:47 time: 0.3581 data_time: 0.0211 memory: 11108 grad_norm: 2.9311 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8668 loss: 2.8668 2022/10/09 12:08:17 - mmengine - INFO - Epoch(train) [29][1720/2119] lr: 4.0000e-02 eta: 1 day, 1:52:40 time: 0.3617 data_time: 0.0270 memory: 11108 grad_norm: 2.8820 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8824 loss: 2.8824 2022/10/09 12:08:24 - mmengine - INFO - Epoch(train) [29][1740/2119] lr: 4.0000e-02 eta: 1 day, 1:52:32 time: 0.3553 data_time: 0.0182 memory: 11108 grad_norm: 2.9282 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5643 loss: 2.5643 2022/10/09 12:08:31 - mmengine - INFO - Epoch(train) [29][1760/2119] lr: 4.0000e-02 eta: 1 day, 1:52:24 time: 0.3572 data_time: 0.0217 memory: 11108 grad_norm: 2.9366 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7941 loss: 2.7941 2022/10/09 12:08:38 - mmengine - INFO - Epoch(train) [29][1780/2119] lr: 4.0000e-02 eta: 1 day, 1:52:16 time: 0.3578 data_time: 0.0206 memory: 11108 grad_norm: 2.9816 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5772 loss: 2.5772 2022/10/09 12:08:45 - mmengine - INFO - Epoch(train) [29][1800/2119] lr: 4.0000e-02 eta: 1 day, 1:52:09 time: 0.3558 data_time: 0.0192 memory: 11108 grad_norm: 2.9470 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5515 loss: 2.5515 2022/10/09 12:08:52 - mmengine - INFO - Epoch(train) [29][1820/2119] lr: 4.0000e-02 eta: 1 day, 1:52:01 time: 0.3587 data_time: 0.0190 memory: 11108 grad_norm: 2.9595 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7182 loss: 2.7182 2022/10/09 12:08:59 - mmengine - INFO - Epoch(train) [29][1840/2119] lr: 4.0000e-02 eta: 1 day, 1:51:53 time: 0.3559 data_time: 0.0207 memory: 11108 grad_norm: 2.8789 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7079 loss: 2.7079 2022/10/09 12:09:07 - mmengine - INFO - Epoch(train) [29][1860/2119] lr: 4.0000e-02 eta: 1 day, 1:51:46 time: 0.3588 data_time: 0.0231 memory: 11108 grad_norm: 2.9971 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7563 loss: 2.7563 2022/10/09 12:09:14 - mmengine - INFO - Epoch(train) [29][1880/2119] lr: 4.0000e-02 eta: 1 day, 1:51:38 time: 0.3615 data_time: 0.0205 memory: 11108 grad_norm: 2.9132 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5442 loss: 2.5442 2022/10/09 12:09:21 - mmengine - INFO - Epoch(train) [29][1900/2119] lr: 4.0000e-02 eta: 1 day, 1:51:30 time: 0.3562 data_time: 0.0193 memory: 11108 grad_norm: 2.9190 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4683 loss: 2.4683 2022/10/09 12:09:28 - mmengine - INFO - Epoch(train) [29][1920/2119] lr: 4.0000e-02 eta: 1 day, 1:51:23 time: 0.3621 data_time: 0.0181 memory: 11108 grad_norm: 2.8848 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6390 loss: 2.6390 2022/10/09 12:09:35 - mmengine - INFO - Epoch(train) [29][1940/2119] lr: 4.0000e-02 eta: 1 day, 1:51:15 time: 0.3550 data_time: 0.0199 memory: 11108 grad_norm: 2.9247 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.8430 loss: 2.8430 2022/10/09 12:09:43 - mmengine - INFO - Epoch(train) [29][1960/2119] lr: 4.0000e-02 eta: 1 day, 1:51:08 time: 0.3660 data_time: 0.0222 memory: 11108 grad_norm: 2.9951 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8252 loss: 2.8252 2022/10/09 12:09:50 - mmengine - INFO - Epoch(train) [29][1980/2119] lr: 4.0000e-02 eta: 1 day, 1:51:00 time: 0.3555 data_time: 0.0220 memory: 11108 grad_norm: 2.9387 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8959 loss: 2.8959 2022/10/09 12:09:57 - mmengine - INFO - Epoch(train) [29][2000/2119] lr: 4.0000e-02 eta: 1 day, 1:50:52 time: 0.3540 data_time: 0.0203 memory: 11108 grad_norm: 2.9066 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6584 loss: 2.6584 2022/10/09 12:10:04 - mmengine - INFO - Epoch(train) [29][2020/2119] lr: 4.0000e-02 eta: 1 day, 1:50:45 time: 0.3584 data_time: 0.0198 memory: 11108 grad_norm: 2.9386 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6000 loss: 2.6000 2022/10/09 12:10:11 - mmengine - INFO - Epoch(train) [29][2040/2119] lr: 4.0000e-02 eta: 1 day, 1:50:38 time: 0.3653 data_time: 0.0211 memory: 11108 grad_norm: 2.9661 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5222 loss: 2.5222 2022/10/09 12:10:19 - mmengine - INFO - Epoch(train) [29][2060/2119] lr: 4.0000e-02 eta: 1 day, 1:50:31 time: 0.3655 data_time: 0.0255 memory: 11108 grad_norm: 2.9474 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7048 loss: 2.7048 2022/10/09 12:10:26 - mmengine - INFO - Epoch(train) [29][2080/2119] lr: 4.0000e-02 eta: 1 day, 1:50:23 time: 0.3618 data_time: 0.0196 memory: 11108 grad_norm: 2.9544 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8705 loss: 2.8705 2022/10/09 12:10:33 - mmengine - INFO - Epoch(train) [29][2100/2119] lr: 4.0000e-02 eta: 1 day, 1:50:16 time: 0.3602 data_time: 0.0196 memory: 11108 grad_norm: 2.9792 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5179 loss: 2.5179 2022/10/09 12:10:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 12:10:40 - mmengine - INFO - Epoch(train) [29][2119/2119] lr: 4.0000e-02 eta: 1 day, 1:50:16 time: 0.3545 data_time: 0.0200 memory: 11108 grad_norm: 3.0411 top1_acc: 0.2000 top5_acc: 0.7000 loss_cls: 2.5836 loss: 2.5836 2022/10/09 12:10:50 - mmengine - INFO - Epoch(train) [30][20/2119] lr: 4.0000e-02 eta: 1 day, 1:49:46 time: 0.5144 data_time: 0.1261 memory: 11108 grad_norm: 2.9122 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5644 loss: 2.5644 2022/10/09 12:10:58 - mmengine - INFO - Epoch(train) [30][40/2119] lr: 4.0000e-02 eta: 1 day, 1:49:39 time: 0.3701 data_time: 0.0201 memory: 11108 grad_norm: 2.9070 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5158 loss: 2.5158 2022/10/09 12:11:05 - mmengine - INFO - Epoch(train) [30][60/2119] lr: 4.0000e-02 eta: 1 day, 1:49:31 time: 0.3597 data_time: 0.0220 memory: 11108 grad_norm: 2.9462 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6788 loss: 2.6788 2022/10/09 12:11:12 - mmengine - INFO - Epoch(train) [30][80/2119] lr: 4.0000e-02 eta: 1 day, 1:49:24 time: 0.3612 data_time: 0.0246 memory: 11108 grad_norm: 2.9372 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.4001 loss: 2.4001 2022/10/09 12:11:19 - mmengine - INFO - Epoch(train) [30][100/2119] lr: 4.0000e-02 eta: 1 day, 1:49:17 time: 0.3611 data_time: 0.0178 memory: 11108 grad_norm: 2.9783 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5165 loss: 2.5165 2022/10/09 12:11:26 - mmengine - INFO - Epoch(train) [30][120/2119] lr: 4.0000e-02 eta: 1 day, 1:49:09 time: 0.3554 data_time: 0.0264 memory: 11108 grad_norm: 2.8891 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6370 loss: 2.6370 2022/10/09 12:11:34 - mmengine - INFO - Epoch(train) [30][140/2119] lr: 4.0000e-02 eta: 1 day, 1:49:01 time: 0.3587 data_time: 0.0194 memory: 11108 grad_norm: 2.9230 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6499 loss: 2.6499 2022/10/09 12:11:41 - mmengine - INFO - Epoch(train) [30][160/2119] lr: 4.0000e-02 eta: 1 day, 1:48:54 time: 0.3597 data_time: 0.0200 memory: 11108 grad_norm: 2.9345 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6641 loss: 2.6641 2022/10/09 12:11:48 - mmengine - INFO - Epoch(train) [30][180/2119] lr: 4.0000e-02 eta: 1 day, 1:48:46 time: 0.3603 data_time: 0.0226 memory: 11108 grad_norm: 2.9303 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.4331 loss: 2.4331 2022/10/09 12:11:55 - mmengine - INFO - Epoch(train) [30][200/2119] lr: 4.0000e-02 eta: 1 day, 1:48:39 time: 0.3609 data_time: 0.0217 memory: 11108 grad_norm: 2.9550 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5571 loss: 2.5571 2022/10/09 12:12:02 - mmengine - INFO - Epoch(train) [30][220/2119] lr: 4.0000e-02 eta: 1 day, 1:48:31 time: 0.3581 data_time: 0.0218 memory: 11108 grad_norm: 2.9194 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5210 loss: 2.5210 2022/10/09 12:12:10 - mmengine - INFO - Epoch(train) [30][240/2119] lr: 4.0000e-02 eta: 1 day, 1:48:24 time: 0.3618 data_time: 0.0227 memory: 11108 grad_norm: 2.9218 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5011 loss: 2.5011 2022/10/09 12:12:17 - mmengine - INFO - Epoch(train) [30][260/2119] lr: 4.0000e-02 eta: 1 day, 1:48:17 time: 0.3613 data_time: 0.0212 memory: 11108 grad_norm: 2.9413 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5344 loss: 2.5344 2022/10/09 12:12:24 - mmengine - INFO - Epoch(train) [30][280/2119] lr: 4.0000e-02 eta: 1 day, 1:48:09 time: 0.3598 data_time: 0.0200 memory: 11108 grad_norm: 2.9294 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6541 loss: 2.6541 2022/10/09 12:12:31 - mmengine - INFO - Epoch(train) [30][300/2119] lr: 4.0000e-02 eta: 1 day, 1:48:02 time: 0.3602 data_time: 0.0225 memory: 11108 grad_norm: 2.9719 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5976 loss: 2.5976 2022/10/09 12:12:38 - mmengine - INFO - Epoch(train) [30][320/2119] lr: 4.0000e-02 eta: 1 day, 1:47:54 time: 0.3596 data_time: 0.0206 memory: 11108 grad_norm: 2.9625 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7704 loss: 2.7704 2022/10/09 12:12:45 - mmengine - INFO - Epoch(train) [30][340/2119] lr: 4.0000e-02 eta: 1 day, 1:47:46 time: 0.3560 data_time: 0.0185 memory: 11108 grad_norm: 2.9158 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7996 loss: 2.7996 2022/10/09 12:12:53 - mmengine - INFO - Epoch(train) [30][360/2119] lr: 4.0000e-02 eta: 1 day, 1:47:39 time: 0.3587 data_time: 0.0212 memory: 11108 grad_norm: 2.9484 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7371 loss: 2.7371 2022/10/09 12:13:00 - mmengine - INFO - Epoch(train) [30][380/2119] lr: 4.0000e-02 eta: 1 day, 1:47:31 time: 0.3586 data_time: 0.0167 memory: 11108 grad_norm: 3.0089 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9447 loss: 2.9447 2022/10/09 12:13:07 - mmengine - INFO - Epoch(train) [30][400/2119] lr: 4.0000e-02 eta: 1 day, 1:47:23 time: 0.3571 data_time: 0.0190 memory: 11108 grad_norm: 2.9162 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5075 loss: 2.5075 2022/10/09 12:13:14 - mmengine - INFO - Epoch(train) [30][420/2119] lr: 4.0000e-02 eta: 1 day, 1:47:16 time: 0.3618 data_time: 0.0227 memory: 11108 grad_norm: 2.9098 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8561 loss: 2.8561 2022/10/09 12:13:21 - mmengine - INFO - Epoch(train) [30][440/2119] lr: 4.0000e-02 eta: 1 day, 1:47:09 time: 0.3613 data_time: 0.0203 memory: 11108 grad_norm: 3.0136 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8240 loss: 2.8240 2022/10/09 12:13:29 - mmengine - INFO - Epoch(train) [30][460/2119] lr: 4.0000e-02 eta: 1 day, 1:47:01 time: 0.3616 data_time: 0.0199 memory: 11108 grad_norm: 2.9015 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6621 loss: 2.6621 2022/10/09 12:13:36 - mmengine - INFO - Epoch(train) [30][480/2119] lr: 4.0000e-02 eta: 1 day, 1:46:54 time: 0.3575 data_time: 0.0211 memory: 11108 grad_norm: 2.9415 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6779 loss: 2.6779 2022/10/09 12:13:43 - mmengine - INFO - Epoch(train) [30][500/2119] lr: 4.0000e-02 eta: 1 day, 1:46:46 time: 0.3601 data_time: 0.0211 memory: 11108 grad_norm: 2.9913 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4408 loss: 2.4408 2022/10/09 12:13:50 - mmengine - INFO - Epoch(train) [30][520/2119] lr: 4.0000e-02 eta: 1 day, 1:46:39 time: 0.3603 data_time: 0.0199 memory: 11108 grad_norm: 3.0036 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7685 loss: 2.7685 2022/10/09 12:13:57 - mmengine - INFO - Epoch(train) [30][540/2119] lr: 4.0000e-02 eta: 1 day, 1:46:31 time: 0.3555 data_time: 0.0222 memory: 11108 grad_norm: 2.9448 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6336 loss: 2.6336 2022/10/09 12:14:01 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 12:14:05 - mmengine - INFO - Epoch(train) [30][560/2119] lr: 4.0000e-02 eta: 1 day, 1:46:23 time: 0.3572 data_time: 0.0232 memory: 11108 grad_norm: 2.9451 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5203 loss: 2.5203 2022/10/09 12:14:12 - mmengine - INFO - Epoch(train) [30][580/2119] lr: 4.0000e-02 eta: 1 day, 1:46:16 time: 0.3581 data_time: 0.0213 memory: 11108 grad_norm: 2.9592 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7587 loss: 2.7587 2022/10/09 12:14:19 - mmengine - INFO - Epoch(train) [30][600/2119] lr: 4.0000e-02 eta: 1 day, 1:46:08 time: 0.3590 data_time: 0.0194 memory: 11108 grad_norm: 2.9291 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5389 loss: 2.5389 2022/10/09 12:14:26 - mmengine - INFO - Epoch(train) [30][620/2119] lr: 4.0000e-02 eta: 1 day, 1:46:00 time: 0.3567 data_time: 0.0184 memory: 11108 grad_norm: 2.9857 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4471 loss: 2.4471 2022/10/09 12:14:33 - mmengine - INFO - Epoch(train) [30][640/2119] lr: 4.0000e-02 eta: 1 day, 1:45:53 time: 0.3606 data_time: 0.0233 memory: 11108 grad_norm: 2.9635 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5309 loss: 2.5309 2022/10/09 12:14:40 - mmengine - INFO - Epoch(train) [30][660/2119] lr: 4.0000e-02 eta: 1 day, 1:45:45 time: 0.3571 data_time: 0.0180 memory: 11108 grad_norm: 2.9307 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6020 loss: 2.6020 2022/10/09 12:14:48 - mmengine - INFO - Epoch(train) [30][680/2119] lr: 4.0000e-02 eta: 1 day, 1:45:38 time: 0.3593 data_time: 0.0202 memory: 11108 grad_norm: 2.8981 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5747 loss: 2.5747 2022/10/09 12:14:55 - mmengine - INFO - Epoch(train) [30][700/2119] lr: 4.0000e-02 eta: 1 day, 1:45:30 time: 0.3561 data_time: 0.0189 memory: 11108 grad_norm: 2.9508 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5569 loss: 2.5569 2022/10/09 12:15:02 - mmengine - INFO - Epoch(train) [30][720/2119] lr: 4.0000e-02 eta: 1 day, 1:45:22 time: 0.3602 data_time: 0.0216 memory: 11108 grad_norm: 2.8958 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7748 loss: 2.7748 2022/10/09 12:15:09 - mmengine - INFO - Epoch(train) [30][740/2119] lr: 4.0000e-02 eta: 1 day, 1:45:15 time: 0.3607 data_time: 0.0199 memory: 11108 grad_norm: 2.9737 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7002 loss: 2.7002 2022/10/09 12:15:16 - mmengine - INFO - Epoch(train) [30][760/2119] lr: 4.0000e-02 eta: 1 day, 1:45:07 time: 0.3568 data_time: 0.0228 memory: 11108 grad_norm: 2.8869 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6728 loss: 2.6728 2022/10/09 12:15:23 - mmengine - INFO - Epoch(train) [30][780/2119] lr: 4.0000e-02 eta: 1 day, 1:45:00 time: 0.3592 data_time: 0.0219 memory: 11108 grad_norm: 2.9150 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6988 loss: 2.6988 2022/10/09 12:15:31 - mmengine - INFO - Epoch(train) [30][800/2119] lr: 4.0000e-02 eta: 1 day, 1:44:53 time: 0.3654 data_time: 0.0199 memory: 11108 grad_norm: 2.9585 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5576 loss: 2.5576 2022/10/09 12:15:38 - mmengine - INFO - Epoch(train) [30][820/2119] lr: 4.0000e-02 eta: 1 day, 1:44:45 time: 0.3558 data_time: 0.0183 memory: 11108 grad_norm: 3.0304 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7122 loss: 2.7122 2022/10/09 12:15:45 - mmengine - INFO - Epoch(train) [30][840/2119] lr: 4.0000e-02 eta: 1 day, 1:44:37 time: 0.3553 data_time: 0.0192 memory: 11108 grad_norm: 2.9362 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5531 loss: 2.5531 2022/10/09 12:15:52 - mmengine - INFO - Epoch(train) [30][860/2119] lr: 4.0000e-02 eta: 1 day, 1:44:30 time: 0.3635 data_time: 0.0215 memory: 11108 grad_norm: 2.9375 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4556 loss: 2.4556 2022/10/09 12:15:59 - mmengine - INFO - Epoch(train) [30][880/2119] lr: 4.0000e-02 eta: 1 day, 1:44:22 time: 0.3538 data_time: 0.0247 memory: 11108 grad_norm: 2.9542 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7126 loss: 2.7126 2022/10/09 12:16:06 - mmengine - INFO - Epoch(train) [30][900/2119] lr: 4.0000e-02 eta: 1 day, 1:44:14 time: 0.3569 data_time: 0.0187 memory: 11108 grad_norm: 2.8986 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5179 loss: 2.5179 2022/10/09 12:16:14 - mmengine - INFO - Epoch(train) [30][920/2119] lr: 4.0000e-02 eta: 1 day, 1:44:07 time: 0.3584 data_time: 0.0201 memory: 11108 grad_norm: 2.8978 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7567 loss: 2.7567 2022/10/09 12:16:21 - mmengine - INFO - Epoch(train) [30][940/2119] lr: 4.0000e-02 eta: 1 day, 1:43:59 time: 0.3546 data_time: 0.0211 memory: 11108 grad_norm: 2.9326 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.7004 loss: 2.7004 2022/10/09 12:16:28 - mmengine - INFO - Epoch(train) [30][960/2119] lr: 4.0000e-02 eta: 1 day, 1:43:51 time: 0.3613 data_time: 0.0201 memory: 11108 grad_norm: 2.9197 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.7555 loss: 2.7555 2022/10/09 12:16:35 - mmengine - INFO - Epoch(train) [30][980/2119] lr: 4.0000e-02 eta: 1 day, 1:43:44 time: 0.3594 data_time: 0.0189 memory: 11108 grad_norm: 2.8955 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7064 loss: 2.7064 2022/10/09 12:16:42 - mmengine - INFO - Epoch(train) [30][1000/2119] lr: 4.0000e-02 eta: 1 day, 1:43:36 time: 0.3554 data_time: 0.0187 memory: 11108 grad_norm: 2.9239 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5691 loss: 2.5691 2022/10/09 12:16:49 - mmengine - INFO - Epoch(train) [30][1020/2119] lr: 4.0000e-02 eta: 1 day, 1:43:28 time: 0.3596 data_time: 0.0257 memory: 11108 grad_norm: 2.9382 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7488 loss: 2.7488 2022/10/09 12:16:57 - mmengine - INFO - Epoch(train) [30][1040/2119] lr: 4.0000e-02 eta: 1 day, 1:43:20 time: 0.3547 data_time: 0.0218 memory: 11108 grad_norm: 3.0059 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6951 loss: 2.6951 2022/10/09 12:17:04 - mmengine - INFO - Epoch(train) [30][1060/2119] lr: 4.0000e-02 eta: 1 day, 1:43:13 time: 0.3569 data_time: 0.0181 memory: 11108 grad_norm: 2.9203 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.8547 loss: 2.8547 2022/10/09 12:17:11 - mmengine - INFO - Epoch(train) [30][1080/2119] lr: 4.0000e-02 eta: 1 day, 1:43:06 time: 0.3637 data_time: 0.0215 memory: 11108 grad_norm: 2.9156 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6328 loss: 2.6328 2022/10/09 12:17:18 - mmengine - INFO - Epoch(train) [30][1100/2119] lr: 4.0000e-02 eta: 1 day, 1:42:58 time: 0.3561 data_time: 0.0174 memory: 11108 grad_norm: 2.9472 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6929 loss: 2.6929 2022/10/09 12:17:25 - mmengine - INFO - Epoch(train) [30][1120/2119] lr: 4.0000e-02 eta: 1 day, 1:42:51 time: 0.3622 data_time: 0.0201 memory: 11108 grad_norm: 2.9504 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5567 loss: 2.5567 2022/10/09 12:17:33 - mmengine - INFO - Epoch(train) [30][1140/2119] lr: 4.0000e-02 eta: 1 day, 1:42:43 time: 0.3610 data_time: 0.0222 memory: 11108 grad_norm: 2.9531 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.3004 loss: 2.3004 2022/10/09 12:17:40 - mmengine - INFO - Epoch(train) [30][1160/2119] lr: 4.0000e-02 eta: 1 day, 1:42:35 time: 0.3569 data_time: 0.0186 memory: 11108 grad_norm: 2.8985 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5704 loss: 2.5704 2022/10/09 12:17:47 - mmengine - INFO - Epoch(train) [30][1180/2119] lr: 4.0000e-02 eta: 1 day, 1:42:28 time: 0.3583 data_time: 0.0212 memory: 11108 grad_norm: 2.9452 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7655 loss: 2.7655 2022/10/09 12:17:54 - mmengine - INFO - Epoch(train) [30][1200/2119] lr: 4.0000e-02 eta: 1 day, 1:42:21 time: 0.3625 data_time: 0.0207 memory: 11108 grad_norm: 2.9234 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4561 loss: 2.4561 2022/10/09 12:18:01 - mmengine - INFO - Epoch(train) [30][1220/2119] lr: 4.0000e-02 eta: 1 day, 1:42:13 time: 0.3553 data_time: 0.0179 memory: 11108 grad_norm: 2.9008 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6179 loss: 2.6179 2022/10/09 12:18:08 - mmengine - INFO - Epoch(train) [30][1240/2119] lr: 4.0000e-02 eta: 1 day, 1:42:05 time: 0.3622 data_time: 0.0238 memory: 11108 grad_norm: 2.9525 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7235 loss: 2.7235 2022/10/09 12:18:16 - mmengine - INFO - Epoch(train) [30][1260/2119] lr: 4.0000e-02 eta: 1 day, 1:41:57 time: 0.3537 data_time: 0.0225 memory: 11108 grad_norm: 2.9653 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5704 loss: 2.5704 2022/10/09 12:18:23 - mmengine - INFO - Epoch(train) [30][1280/2119] lr: 4.0000e-02 eta: 1 day, 1:41:50 time: 0.3583 data_time: 0.0202 memory: 11108 grad_norm: 2.9425 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6212 loss: 2.6212 2022/10/09 12:18:30 - mmengine - INFO - Epoch(train) [30][1300/2119] lr: 4.0000e-02 eta: 1 day, 1:41:42 time: 0.3610 data_time: 0.0193 memory: 11108 grad_norm: 2.9618 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6048 loss: 2.6048 2022/10/09 12:18:37 - mmengine - INFO - Epoch(train) [30][1320/2119] lr: 4.0000e-02 eta: 1 day, 1:41:35 time: 0.3566 data_time: 0.0221 memory: 11108 grad_norm: 2.9607 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6606 loss: 2.6606 2022/10/09 12:18:44 - mmengine - INFO - Epoch(train) [30][1340/2119] lr: 4.0000e-02 eta: 1 day, 1:41:27 time: 0.3590 data_time: 0.0209 memory: 11108 grad_norm: 2.9364 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.2318 loss: 2.2318 2022/10/09 12:18:51 - mmengine - INFO - Epoch(train) [30][1360/2119] lr: 4.0000e-02 eta: 1 day, 1:41:19 time: 0.3564 data_time: 0.0207 memory: 11108 grad_norm: 3.0172 top1_acc: 0.3750 top5_acc: 0.9375 loss_cls: 2.5060 loss: 2.5060 2022/10/09 12:18:59 - mmengine - INFO - Epoch(train) [30][1380/2119] lr: 4.0000e-02 eta: 1 day, 1:41:12 time: 0.3581 data_time: 0.0211 memory: 11108 grad_norm: 2.9225 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.3029 loss: 2.3029 2022/10/09 12:19:06 - mmengine - INFO - Epoch(train) [30][1400/2119] lr: 4.0000e-02 eta: 1 day, 1:41:04 time: 0.3585 data_time: 0.0201 memory: 11108 grad_norm: 2.9641 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6013 loss: 2.6013 2022/10/09 12:19:13 - mmengine - INFO - Epoch(train) [30][1420/2119] lr: 4.0000e-02 eta: 1 day, 1:40:56 time: 0.3534 data_time: 0.0193 memory: 11108 grad_norm: 2.9339 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4464 loss: 2.4464 2022/10/09 12:19:20 - mmengine - INFO - Epoch(train) [30][1440/2119] lr: 4.0000e-02 eta: 1 day, 1:40:49 time: 0.3592 data_time: 0.0214 memory: 11108 grad_norm: 2.9420 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.4889 loss: 2.4889 2022/10/09 12:19:27 - mmengine - INFO - Epoch(train) [30][1460/2119] lr: 4.0000e-02 eta: 1 day, 1:40:41 time: 0.3555 data_time: 0.0205 memory: 11108 grad_norm: 2.9396 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6922 loss: 2.6922 2022/10/09 12:19:34 - mmengine - INFO - Epoch(train) [30][1480/2119] lr: 4.0000e-02 eta: 1 day, 1:40:33 time: 0.3608 data_time: 0.0205 memory: 11108 grad_norm: 2.9577 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7802 loss: 2.7802 2022/10/09 12:19:41 - mmengine - INFO - Epoch(train) [30][1500/2119] lr: 4.0000e-02 eta: 1 day, 1:40:26 time: 0.3581 data_time: 0.0190 memory: 11108 grad_norm: 2.9619 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.8133 loss: 2.8133 2022/10/09 12:19:49 - mmengine - INFO - Epoch(train) [30][1520/2119] lr: 4.0000e-02 eta: 1 day, 1:40:18 time: 0.3569 data_time: 0.0229 memory: 11108 grad_norm: 2.9543 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9675 loss: 2.9675 2022/10/09 12:19:56 - mmengine - INFO - Epoch(train) [30][1540/2119] lr: 4.0000e-02 eta: 1 day, 1:40:10 time: 0.3547 data_time: 0.0198 memory: 11108 grad_norm: 2.9399 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6504 loss: 2.6504 2022/10/09 12:19:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 12:20:03 - mmengine - INFO - Epoch(train) [30][1560/2119] lr: 4.0000e-02 eta: 1 day, 1:40:03 time: 0.3585 data_time: 0.0227 memory: 11108 grad_norm: 2.9294 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.8680 loss: 2.8680 2022/10/09 12:20:10 - mmengine - INFO - Epoch(train) [30][1580/2119] lr: 4.0000e-02 eta: 1 day, 1:39:55 time: 0.3597 data_time: 0.0179 memory: 11108 grad_norm: 2.9465 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6430 loss: 2.6430 2022/10/09 12:20:17 - mmengine - INFO - Epoch(train) [30][1600/2119] lr: 4.0000e-02 eta: 1 day, 1:39:48 time: 0.3590 data_time: 0.0240 memory: 11108 grad_norm: 2.9359 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2764 loss: 2.2764 2022/10/09 12:20:24 - mmengine - INFO - Epoch(train) [30][1620/2119] lr: 4.0000e-02 eta: 1 day, 1:39:40 time: 0.3563 data_time: 0.0184 memory: 11108 grad_norm: 2.9515 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7448 loss: 2.7448 2022/10/09 12:20:32 - mmengine - INFO - Epoch(train) [30][1640/2119] lr: 4.0000e-02 eta: 1 day, 1:39:33 time: 0.3723 data_time: 0.0227 memory: 11108 grad_norm: 2.9324 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5902 loss: 2.5902 2022/10/09 12:20:39 - mmengine - INFO - Epoch(train) [30][1660/2119] lr: 4.0000e-02 eta: 1 day, 1:39:26 time: 0.3568 data_time: 0.0193 memory: 11108 grad_norm: 2.9099 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6671 loss: 2.6671 2022/10/09 12:20:46 - mmengine - INFO - Epoch(train) [30][1680/2119] lr: 4.0000e-02 eta: 1 day, 1:39:18 time: 0.3590 data_time: 0.0214 memory: 11108 grad_norm: 2.8895 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6935 loss: 2.6935 2022/10/09 12:20:53 - mmengine - INFO - Epoch(train) [30][1700/2119] lr: 4.0000e-02 eta: 1 day, 1:39:10 time: 0.3578 data_time: 0.0170 memory: 11108 grad_norm: 3.0044 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6587 loss: 2.6587 2022/10/09 12:21:01 - mmengine - INFO - Epoch(train) [30][1720/2119] lr: 4.0000e-02 eta: 1 day, 1:39:03 time: 0.3637 data_time: 0.0221 memory: 11108 grad_norm: 2.9651 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6426 loss: 2.6426 2022/10/09 12:21:08 - mmengine - INFO - Epoch(train) [30][1740/2119] lr: 4.0000e-02 eta: 1 day, 1:38:56 time: 0.3555 data_time: 0.0183 memory: 11108 grad_norm: 2.8863 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9115 loss: 2.9115 2022/10/09 12:21:15 - mmengine - INFO - Epoch(train) [30][1760/2119] lr: 4.0000e-02 eta: 1 day, 1:38:48 time: 0.3556 data_time: 0.0248 memory: 11108 grad_norm: 2.8919 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5960 loss: 2.5960 2022/10/09 12:21:22 - mmengine - INFO - Epoch(train) [30][1780/2119] lr: 4.0000e-02 eta: 1 day, 1:38:40 time: 0.3553 data_time: 0.0241 memory: 11108 grad_norm: 2.9378 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9234 loss: 2.9234 2022/10/09 12:21:29 - mmengine - INFO - Epoch(train) [30][1800/2119] lr: 4.0000e-02 eta: 1 day, 1:38:33 time: 0.3622 data_time: 0.0202 memory: 11108 grad_norm: 2.9372 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6355 loss: 2.6355 2022/10/09 12:21:36 - mmengine - INFO - Epoch(train) [30][1820/2119] lr: 4.0000e-02 eta: 1 day, 1:38:25 time: 0.3581 data_time: 0.0247 memory: 11108 grad_norm: 2.9348 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6147 loss: 2.6147 2022/10/09 12:21:43 - mmengine - INFO - Epoch(train) [30][1840/2119] lr: 4.0000e-02 eta: 1 day, 1:38:17 time: 0.3588 data_time: 0.0230 memory: 11108 grad_norm: 2.9680 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7838 loss: 2.7838 2022/10/09 12:21:51 - mmengine - INFO - Epoch(train) [30][1860/2119] lr: 4.0000e-02 eta: 1 day, 1:38:10 time: 0.3592 data_time: 0.0236 memory: 11108 grad_norm: 2.9479 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5525 loss: 2.5525 2022/10/09 12:21:58 - mmengine - INFO - Epoch(train) [30][1880/2119] lr: 4.0000e-02 eta: 1 day, 1:38:02 time: 0.3601 data_time: 0.0205 memory: 11108 grad_norm: 2.8938 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6849 loss: 2.6849 2022/10/09 12:22:05 - mmengine - INFO - Epoch(train) [30][1900/2119] lr: 4.0000e-02 eta: 1 day, 1:37:55 time: 0.3602 data_time: 0.0237 memory: 11108 grad_norm: 2.9462 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5139 loss: 2.5139 2022/10/09 12:22:12 - mmengine - INFO - Epoch(train) [30][1920/2119] lr: 4.0000e-02 eta: 1 day, 1:37:47 time: 0.3565 data_time: 0.0197 memory: 11108 grad_norm: 2.9458 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6161 loss: 2.6161 2022/10/09 12:22:19 - mmengine - INFO - Epoch(train) [30][1940/2119] lr: 4.0000e-02 eta: 1 day, 1:37:40 time: 0.3582 data_time: 0.0223 memory: 11108 grad_norm: 2.8916 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7241 loss: 2.7241 2022/10/09 12:22:27 - mmengine - INFO - Epoch(train) [30][1960/2119] lr: 4.0000e-02 eta: 1 day, 1:37:32 time: 0.3591 data_time: 0.0209 memory: 11108 grad_norm: 2.9743 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8337 loss: 2.8337 2022/10/09 12:22:34 - mmengine - INFO - Epoch(train) [30][1980/2119] lr: 4.0000e-02 eta: 1 day, 1:37:24 time: 0.3579 data_time: 0.0190 memory: 11108 grad_norm: 2.9512 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4246 loss: 2.4246 2022/10/09 12:22:41 - mmengine - INFO - Epoch(train) [30][2000/2119] lr: 4.0000e-02 eta: 1 day, 1:37:17 time: 0.3580 data_time: 0.0236 memory: 11108 grad_norm: 2.9213 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6745 loss: 2.6745 2022/10/09 12:22:48 - mmengine - INFO - Epoch(train) [30][2020/2119] lr: 4.0000e-02 eta: 1 day, 1:37:09 time: 0.3583 data_time: 0.0234 memory: 11108 grad_norm: 3.0040 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6117 loss: 2.6117 2022/10/09 12:22:55 - mmengine - INFO - Epoch(train) [30][2040/2119] lr: 4.0000e-02 eta: 1 day, 1:37:02 time: 0.3575 data_time: 0.0205 memory: 11108 grad_norm: 2.9777 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9422 loss: 2.9422 2022/10/09 12:23:03 - mmengine - INFO - Epoch(train) [30][2060/2119] lr: 4.0000e-02 eta: 1 day, 1:36:55 time: 0.3696 data_time: 0.0213 memory: 11108 grad_norm: 2.9717 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8316 loss: 2.8316 2022/10/09 12:23:10 - mmengine - INFO - Epoch(train) [30][2080/2119] lr: 4.0000e-02 eta: 1 day, 1:36:47 time: 0.3546 data_time: 0.0223 memory: 11108 grad_norm: 2.8991 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5899 loss: 2.5899 2022/10/09 12:23:17 - mmengine - INFO - Epoch(train) [30][2100/2119] lr: 4.0000e-02 eta: 1 day, 1:36:39 time: 0.3592 data_time: 0.0181 memory: 11108 grad_norm: 2.9514 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6042 loss: 2.6042 2022/10/09 12:23:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 12:23:24 - mmengine - INFO - Epoch(train) [30][2119/2119] lr: 4.0000e-02 eta: 1 day, 1:36:39 time: 0.3512 data_time: 0.0181 memory: 11108 grad_norm: 2.9506 top1_acc: 0.5000 top5_acc: 0.6000 loss_cls: 2.6663 loss: 2.6663 2022/10/09 12:23:30 - mmengine - INFO - Epoch(val) [30][20/137] eta: 0:00:39 time: 0.3355 data_time: 0.2204 memory: 1961 2022/10/09 12:23:35 - mmengine - INFO - Epoch(val) [30][40/137] eta: 0:00:25 time: 0.2586 data_time: 0.1417 memory: 1961 2022/10/09 12:23:42 - mmengine - INFO - Epoch(val) [30][60/137] eta: 0:00:24 time: 0.3136 data_time: 0.1931 memory: 1961 2022/10/09 12:23:46 - mmengine - INFO - Epoch(val) [30][80/137] eta: 0:00:13 time: 0.2381 data_time: 0.1214 memory: 1961 2022/10/09 12:23:52 - mmengine - INFO - Epoch(val) [30][100/137] eta: 0:00:10 time: 0.2860 data_time: 0.1727 memory: 1961 2022/10/09 12:23:57 - mmengine - INFO - Epoch(val) [30][120/137] eta: 0:00:03 time: 0.2232 data_time: 0.1072 memory: 1961 2022/10/09 12:24:12 - mmengine - INFO - Epoch(val) [30][137/137] acc/top1: 0.4461 acc/top5: 0.6914 acc/mean1: 0.4460 2022/10/09 12:24:22 - mmengine - INFO - Epoch(train) [31][20/2119] lr: 4.0000e-02 eta: 1 day, 1:36:09 time: 0.5076 data_time: 0.1380 memory: 11108 grad_norm: 2.9365 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5681 loss: 2.5681 2022/10/09 12:24:30 - mmengine - INFO - Epoch(train) [31][40/2119] lr: 4.0000e-02 eta: 1 day, 1:36:03 time: 0.3738 data_time: 0.0216 memory: 11108 grad_norm: 2.9864 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.6732 loss: 2.6732 2022/10/09 12:24:37 - mmengine - INFO - Epoch(train) [31][60/2119] lr: 4.0000e-02 eta: 1 day, 1:35:55 time: 0.3584 data_time: 0.0218 memory: 11108 grad_norm: 2.9478 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6689 loss: 2.6689 2022/10/09 12:24:44 - mmengine - INFO - Epoch(train) [31][80/2119] lr: 4.0000e-02 eta: 1 day, 1:35:48 time: 0.3589 data_time: 0.0194 memory: 11108 grad_norm: 2.9885 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5468 loss: 2.5468 2022/10/09 12:24:51 - mmengine - INFO - Epoch(train) [31][100/2119] lr: 4.0000e-02 eta: 1 day, 1:35:41 time: 0.3606 data_time: 0.0198 memory: 11108 grad_norm: 2.9481 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3238 loss: 2.3238 2022/10/09 12:24:59 - mmengine - INFO - Epoch(train) [31][120/2119] lr: 4.0000e-02 eta: 1 day, 1:35:33 time: 0.3572 data_time: 0.0271 memory: 11108 grad_norm: 2.9790 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7239 loss: 2.7239 2022/10/09 12:25:06 - mmengine - INFO - Epoch(train) [31][140/2119] lr: 4.0000e-02 eta: 1 day, 1:35:25 time: 0.3579 data_time: 0.0221 memory: 11108 grad_norm: 2.9876 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7198 loss: 2.7198 2022/10/09 12:25:13 - mmengine - INFO - Epoch(train) [31][160/2119] lr: 4.0000e-02 eta: 1 day, 1:35:18 time: 0.3627 data_time: 0.0225 memory: 11108 grad_norm: 2.9182 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5439 loss: 2.5439 2022/10/09 12:25:20 - mmengine - INFO - Epoch(train) [31][180/2119] lr: 4.0000e-02 eta: 1 day, 1:35:10 time: 0.3588 data_time: 0.0190 memory: 11108 grad_norm: 2.8989 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.4594 loss: 2.4594 2022/10/09 12:25:27 - mmengine - INFO - Epoch(train) [31][200/2119] lr: 4.0000e-02 eta: 1 day, 1:35:03 time: 0.3616 data_time: 0.0203 memory: 11108 grad_norm: 2.9723 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4959 loss: 2.4959 2022/10/09 12:25:35 - mmengine - INFO - Epoch(train) [31][220/2119] lr: 4.0000e-02 eta: 1 day, 1:34:56 time: 0.3592 data_time: 0.0220 memory: 11108 grad_norm: 2.9495 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4771 loss: 2.4771 2022/10/09 12:25:42 - mmengine - INFO - Epoch(train) [31][240/2119] lr: 4.0000e-02 eta: 1 day, 1:34:48 time: 0.3559 data_time: 0.0209 memory: 11108 grad_norm: 2.9532 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6182 loss: 2.6182 2022/10/09 12:25:49 - mmengine - INFO - Epoch(train) [31][260/2119] lr: 4.0000e-02 eta: 1 day, 1:34:40 time: 0.3585 data_time: 0.0218 memory: 11108 grad_norm: 2.9618 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5387 loss: 2.5387 2022/10/09 12:25:56 - mmengine - INFO - Epoch(train) [31][280/2119] lr: 4.0000e-02 eta: 1 day, 1:34:34 time: 0.3706 data_time: 0.0191 memory: 11108 grad_norm: 3.0378 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8077 loss: 2.8077 2022/10/09 12:26:03 - mmengine - INFO - Epoch(train) [31][300/2119] lr: 4.0000e-02 eta: 1 day, 1:34:26 time: 0.3566 data_time: 0.0195 memory: 11108 grad_norm: 2.9765 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5718 loss: 2.5718 2022/10/09 12:26:11 - mmengine - INFO - Epoch(train) [31][320/2119] lr: 4.0000e-02 eta: 1 day, 1:34:18 time: 0.3586 data_time: 0.0205 memory: 11108 grad_norm: 3.0345 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6425 loss: 2.6425 2022/10/09 12:26:18 - mmengine - INFO - Epoch(train) [31][340/2119] lr: 4.0000e-02 eta: 1 day, 1:34:11 time: 0.3558 data_time: 0.0213 memory: 11108 grad_norm: 3.0108 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5511 loss: 2.5511 2022/10/09 12:26:25 - mmengine - INFO - Epoch(train) [31][360/2119] lr: 4.0000e-02 eta: 1 day, 1:34:03 time: 0.3556 data_time: 0.0238 memory: 11108 grad_norm: 2.9903 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7412 loss: 2.7412 2022/10/09 12:26:32 - mmengine - INFO - Epoch(train) [31][380/2119] lr: 4.0000e-02 eta: 1 day, 1:33:55 time: 0.3606 data_time: 0.0223 memory: 11108 grad_norm: 2.9332 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7951 loss: 2.7951 2022/10/09 12:26:39 - mmengine - INFO - Epoch(train) [31][400/2119] lr: 4.0000e-02 eta: 1 day, 1:33:48 time: 0.3568 data_time: 0.0215 memory: 11108 grad_norm: 2.9228 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4856 loss: 2.4856 2022/10/09 12:26:46 - mmengine - INFO - Epoch(train) [31][420/2119] lr: 4.0000e-02 eta: 1 day, 1:33:40 time: 0.3576 data_time: 0.0226 memory: 11108 grad_norm: 2.9071 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6381 loss: 2.6381 2022/10/09 12:26:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 12:26:54 - mmengine - INFO - Epoch(train) [31][440/2119] lr: 4.0000e-02 eta: 1 day, 1:33:32 time: 0.3577 data_time: 0.0185 memory: 11108 grad_norm: 3.0625 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8569 loss: 2.8569 2022/10/09 12:27:01 - mmengine - INFO - Epoch(train) [31][460/2119] lr: 4.0000e-02 eta: 1 day, 1:33:25 time: 0.3563 data_time: 0.0180 memory: 11108 grad_norm: 2.9791 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6904 loss: 2.6904 2022/10/09 12:27:08 - mmengine - INFO - Epoch(train) [31][480/2119] lr: 4.0000e-02 eta: 1 day, 1:33:17 time: 0.3581 data_time: 0.0223 memory: 11108 grad_norm: 2.9295 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8751 loss: 2.8751 2022/10/09 12:27:15 - mmengine - INFO - Epoch(train) [31][500/2119] lr: 4.0000e-02 eta: 1 day, 1:33:10 time: 0.3599 data_time: 0.0190 memory: 11108 grad_norm: 2.9436 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5908 loss: 2.5908 2022/10/09 12:27:22 - mmengine - INFO - Epoch(train) [31][520/2119] lr: 4.0000e-02 eta: 1 day, 1:33:02 time: 0.3625 data_time: 0.0222 memory: 11108 grad_norm: 2.9526 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5068 loss: 2.5068 2022/10/09 12:27:29 - mmengine - INFO - Epoch(train) [31][540/2119] lr: 4.0000e-02 eta: 1 day, 1:32:55 time: 0.3586 data_time: 0.0207 memory: 11108 grad_norm: 2.9813 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3453 loss: 2.3453 2022/10/09 12:27:36 - mmengine - INFO - Epoch(train) [31][560/2119] lr: 4.0000e-02 eta: 1 day, 1:32:47 time: 0.3531 data_time: 0.0207 memory: 11108 grad_norm: 2.9632 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5576 loss: 2.5576 2022/10/09 12:27:44 - mmengine - INFO - Epoch(train) [31][580/2119] lr: 4.0000e-02 eta: 1 day, 1:32:40 time: 0.3637 data_time: 0.0200 memory: 11108 grad_norm: 2.9602 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.3957 loss: 2.3957 2022/10/09 12:27:51 - mmengine - INFO - Epoch(train) [31][600/2119] lr: 4.0000e-02 eta: 1 day, 1:32:32 time: 0.3598 data_time: 0.0230 memory: 11108 grad_norm: 2.9553 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5318 loss: 2.5318 2022/10/09 12:27:58 - mmengine - INFO - Epoch(train) [31][620/2119] lr: 4.0000e-02 eta: 1 day, 1:32:25 time: 0.3588 data_time: 0.0206 memory: 11108 grad_norm: 2.9707 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6485 loss: 2.6485 2022/10/09 12:28:05 - mmengine - INFO - Epoch(train) [31][640/2119] lr: 4.0000e-02 eta: 1 day, 1:32:17 time: 0.3610 data_time: 0.0207 memory: 11108 grad_norm: 2.9680 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6175 loss: 2.6175 2022/10/09 12:28:13 - mmengine - INFO - Epoch(train) [31][660/2119] lr: 4.0000e-02 eta: 1 day, 1:32:10 time: 0.3593 data_time: 0.0181 memory: 11108 grad_norm: 2.9621 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4890 loss: 2.4890 2022/10/09 12:28:20 - mmengine - INFO - Epoch(train) [31][680/2119] lr: 4.0000e-02 eta: 1 day, 1:32:02 time: 0.3600 data_time: 0.0189 memory: 11108 grad_norm: 2.9583 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6155 loss: 2.6155 2022/10/09 12:28:27 - mmengine - INFO - Epoch(train) [31][700/2119] lr: 4.0000e-02 eta: 1 day, 1:31:55 time: 0.3582 data_time: 0.0199 memory: 11108 grad_norm: 3.0093 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4118 loss: 2.4118 2022/10/09 12:28:34 - mmengine - INFO - Epoch(train) [31][720/2119] lr: 4.0000e-02 eta: 1 day, 1:31:47 time: 0.3597 data_time: 0.0224 memory: 11108 grad_norm: 2.9229 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6610 loss: 2.6610 2022/10/09 12:28:41 - mmengine - INFO - Epoch(train) [31][740/2119] lr: 4.0000e-02 eta: 1 day, 1:31:40 time: 0.3549 data_time: 0.0186 memory: 11108 grad_norm: 3.0290 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7349 loss: 2.7349 2022/10/09 12:28:48 - mmengine - INFO - Epoch(train) [31][760/2119] lr: 4.0000e-02 eta: 1 day, 1:31:32 time: 0.3601 data_time: 0.0211 memory: 11108 grad_norm: 2.9419 top1_acc: 0.0625 top5_acc: 0.5000 loss_cls: 2.6232 loss: 2.6232 2022/10/09 12:28:56 - mmengine - INFO - Epoch(train) [31][780/2119] lr: 4.0000e-02 eta: 1 day, 1:31:25 time: 0.3584 data_time: 0.0216 memory: 11108 grad_norm: 2.9902 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5785 loss: 2.5785 2022/10/09 12:29:03 - mmengine - INFO - Epoch(train) [31][800/2119] lr: 4.0000e-02 eta: 1 day, 1:31:17 time: 0.3559 data_time: 0.0204 memory: 11108 grad_norm: 3.0135 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6216 loss: 2.6216 2022/10/09 12:29:10 - mmengine - INFO - Epoch(train) [31][820/2119] lr: 4.0000e-02 eta: 1 day, 1:31:09 time: 0.3570 data_time: 0.0199 memory: 11108 grad_norm: 2.9555 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4060 loss: 2.4060 2022/10/09 12:29:17 - mmengine - INFO - Epoch(train) [31][840/2119] lr: 4.0000e-02 eta: 1 day, 1:31:02 time: 0.3594 data_time: 0.0202 memory: 11108 grad_norm: 2.9719 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7569 loss: 2.7569 2022/10/09 12:29:24 - mmengine - INFO - Epoch(train) [31][860/2119] lr: 4.0000e-02 eta: 1 day, 1:30:54 time: 0.3576 data_time: 0.0182 memory: 11108 grad_norm: 2.9725 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7853 loss: 2.7853 2022/10/09 12:29:31 - mmengine - INFO - Epoch(train) [31][880/2119] lr: 4.0000e-02 eta: 1 day, 1:30:47 time: 0.3645 data_time: 0.0276 memory: 11108 grad_norm: 2.8823 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5480 loss: 2.5480 2022/10/09 12:29:39 - mmengine - INFO - Epoch(train) [31][900/2119] lr: 4.0000e-02 eta: 1 day, 1:30:39 time: 0.3578 data_time: 0.0190 memory: 11108 grad_norm: 2.9738 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7003 loss: 2.7003 2022/10/09 12:29:46 - mmengine - INFO - Epoch(train) [31][920/2119] lr: 4.0000e-02 eta: 1 day, 1:30:32 time: 0.3568 data_time: 0.0206 memory: 11108 grad_norm: 2.9392 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5045 loss: 2.5045 2022/10/09 12:29:53 - mmengine - INFO - Epoch(train) [31][940/2119] lr: 4.0000e-02 eta: 1 day, 1:30:24 time: 0.3610 data_time: 0.0245 memory: 11108 grad_norm: 2.9679 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.3008 loss: 2.3008 2022/10/09 12:30:00 - mmengine - INFO - Epoch(train) [31][960/2119] lr: 4.0000e-02 eta: 1 day, 1:30:17 time: 0.3628 data_time: 0.0221 memory: 11108 grad_norm: 2.9625 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4970 loss: 2.4970 2022/10/09 12:30:07 - mmengine - INFO - Epoch(train) [31][980/2119] lr: 4.0000e-02 eta: 1 day, 1:30:09 time: 0.3592 data_time: 0.0185 memory: 11108 grad_norm: 2.9968 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6074 loss: 2.6074 2022/10/09 12:30:15 - mmengine - INFO - Epoch(train) [31][1000/2119] lr: 4.0000e-02 eta: 1 day, 1:30:02 time: 0.3618 data_time: 0.0221 memory: 11108 grad_norm: 2.9463 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6030 loss: 2.6030 2022/10/09 12:30:22 - mmengine - INFO - Epoch(train) [31][1020/2119] lr: 4.0000e-02 eta: 1 day, 1:29:54 time: 0.3571 data_time: 0.0202 memory: 11108 grad_norm: 2.9468 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5041 loss: 2.5041 2022/10/09 12:30:29 - mmengine - INFO - Epoch(train) [31][1040/2119] lr: 4.0000e-02 eta: 1 day, 1:29:47 time: 0.3582 data_time: 0.0192 memory: 11108 grad_norm: 2.9852 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5396 loss: 2.5396 2022/10/09 12:30:36 - mmengine - INFO - Epoch(train) [31][1060/2119] lr: 4.0000e-02 eta: 1 day, 1:29:40 time: 0.3618 data_time: 0.0206 memory: 11108 grad_norm: 2.9997 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5585 loss: 2.5585 2022/10/09 12:30:43 - mmengine - INFO - Epoch(train) [31][1080/2119] lr: 4.0000e-02 eta: 1 day, 1:29:32 time: 0.3521 data_time: 0.0175 memory: 11108 grad_norm: 2.9667 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7569 loss: 2.7569 2022/10/09 12:30:51 - mmengine - INFO - Epoch(train) [31][1100/2119] lr: 4.0000e-02 eta: 1 day, 1:29:26 time: 0.3798 data_time: 0.0184 memory: 11108 grad_norm: 2.9589 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4996 loss: 2.4996 2022/10/09 12:30:58 - mmengine - INFO - Epoch(train) [31][1120/2119] lr: 4.0000e-02 eta: 1 day, 1:29:18 time: 0.3545 data_time: 0.0211 memory: 11108 grad_norm: 2.9489 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4685 loss: 2.4685 2022/10/09 12:31:05 - mmengine - INFO - Epoch(train) [31][1140/2119] lr: 4.0000e-02 eta: 1 day, 1:29:10 time: 0.3604 data_time: 0.0236 memory: 11108 grad_norm: 2.9436 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5720 loss: 2.5720 2022/10/09 12:31:12 - mmengine - INFO - Epoch(train) [31][1160/2119] lr: 4.0000e-02 eta: 1 day, 1:29:03 time: 0.3600 data_time: 0.0219 memory: 11108 grad_norm: 2.9638 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6673 loss: 2.6673 2022/10/09 12:31:20 - mmengine - INFO - Epoch(train) [31][1180/2119] lr: 4.0000e-02 eta: 1 day, 1:28:56 time: 0.3644 data_time: 0.0247 memory: 11108 grad_norm: 2.9189 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8004 loss: 2.8004 2022/10/09 12:31:27 - mmengine - INFO - Epoch(train) [31][1200/2119] lr: 4.0000e-02 eta: 1 day, 1:28:48 time: 0.3568 data_time: 0.0184 memory: 11108 grad_norm: 2.9307 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.6683 loss: 2.6683 2022/10/09 12:31:34 - mmengine - INFO - Epoch(train) [31][1220/2119] lr: 4.0000e-02 eta: 1 day, 1:28:41 time: 0.3638 data_time: 0.0196 memory: 11108 grad_norm: 2.9578 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5642 loss: 2.5642 2022/10/09 12:31:41 - mmengine - INFO - Epoch(train) [31][1240/2119] lr: 4.0000e-02 eta: 1 day, 1:28:33 time: 0.3585 data_time: 0.0211 memory: 11108 grad_norm: 2.9478 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5358 loss: 2.5358 2022/10/09 12:31:48 - mmengine - INFO - Epoch(train) [31][1260/2119] lr: 4.0000e-02 eta: 1 day, 1:28:26 time: 0.3570 data_time: 0.0181 memory: 11108 grad_norm: 2.9121 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6025 loss: 2.6025 2022/10/09 12:31:56 - mmengine - INFO - Epoch(train) [31][1280/2119] lr: 4.0000e-02 eta: 1 day, 1:28:18 time: 0.3602 data_time: 0.0243 memory: 11108 grad_norm: 2.9038 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5003 loss: 2.5003 2022/10/09 12:32:03 - mmengine - INFO - Epoch(train) [31][1300/2119] lr: 4.0000e-02 eta: 1 day, 1:28:11 time: 0.3646 data_time: 0.0199 memory: 11108 grad_norm: 2.9856 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7267 loss: 2.7267 2022/10/09 12:32:10 - mmengine - INFO - Epoch(train) [31][1320/2119] lr: 4.0000e-02 eta: 1 day, 1:28:04 time: 0.3612 data_time: 0.0240 memory: 11108 grad_norm: 3.0444 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5924 loss: 2.5924 2022/10/09 12:32:17 - mmengine - INFO - Epoch(train) [31][1340/2119] lr: 4.0000e-02 eta: 1 day, 1:27:56 time: 0.3588 data_time: 0.0183 memory: 11108 grad_norm: 2.9867 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.6623 loss: 2.6623 2022/10/09 12:32:24 - mmengine - INFO - Epoch(train) [31][1360/2119] lr: 4.0000e-02 eta: 1 day, 1:27:49 time: 0.3551 data_time: 0.0197 memory: 11108 grad_norm: 3.0185 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6094 loss: 2.6094 2022/10/09 12:32:32 - mmengine - INFO - Epoch(train) [31][1380/2119] lr: 4.0000e-02 eta: 1 day, 1:27:42 time: 0.3648 data_time: 0.0197 memory: 11108 grad_norm: 2.9516 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.4805 loss: 2.4805 2022/10/09 12:32:39 - mmengine - INFO - Epoch(train) [31][1400/2119] lr: 4.0000e-02 eta: 1 day, 1:27:33 time: 0.3519 data_time: 0.0203 memory: 11108 grad_norm: 3.0168 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4341 loss: 2.4341 2022/10/09 12:32:46 - mmengine - INFO - Epoch(train) [31][1420/2119] lr: 4.0000e-02 eta: 1 day, 1:27:26 time: 0.3616 data_time: 0.0222 memory: 11108 grad_norm: 2.9904 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.8798 loss: 2.8798 2022/10/09 12:32:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 12:32:53 - mmengine - INFO - Epoch(train) [31][1440/2119] lr: 4.0000e-02 eta: 1 day, 1:27:18 time: 0.3550 data_time: 0.0193 memory: 11108 grad_norm: 2.9680 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4517 loss: 2.4517 2022/10/09 12:33:00 - mmengine - INFO - Epoch(train) [31][1460/2119] lr: 4.0000e-02 eta: 1 day, 1:27:11 time: 0.3577 data_time: 0.0215 memory: 11108 grad_norm: 2.9614 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7824 loss: 2.7824 2022/10/09 12:33:07 - mmengine - INFO - Epoch(train) [31][1480/2119] lr: 4.0000e-02 eta: 1 day, 1:27:03 time: 0.3581 data_time: 0.0190 memory: 11108 grad_norm: 2.9144 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6925 loss: 2.6925 2022/10/09 12:33:15 - mmengine - INFO - Epoch(train) [31][1500/2119] lr: 4.0000e-02 eta: 1 day, 1:26:55 time: 0.3561 data_time: 0.0164 memory: 11108 grad_norm: 2.9757 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7503 loss: 2.7503 2022/10/09 12:33:22 - mmengine - INFO - Epoch(train) [31][1520/2119] lr: 4.0000e-02 eta: 1 day, 1:26:48 time: 0.3592 data_time: 0.0210 memory: 11108 grad_norm: 2.9144 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6790 loss: 2.6790 2022/10/09 12:33:29 - mmengine - INFO - Epoch(train) [31][1540/2119] lr: 4.0000e-02 eta: 1 day, 1:26:40 time: 0.3594 data_time: 0.0232 memory: 11108 grad_norm: 2.9326 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.6761 loss: 2.6761 2022/10/09 12:33:36 - mmengine - INFO - Epoch(train) [31][1560/2119] lr: 4.0000e-02 eta: 1 day, 1:26:33 time: 0.3567 data_time: 0.0214 memory: 11108 grad_norm: 2.8961 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.3137 loss: 2.3137 2022/10/09 12:33:43 - mmengine - INFO - Epoch(train) [31][1580/2119] lr: 4.0000e-02 eta: 1 day, 1:26:25 time: 0.3619 data_time: 0.0184 memory: 11108 grad_norm: 2.9130 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5408 loss: 2.5408 2022/10/09 12:33:50 - mmengine - INFO - Epoch(train) [31][1600/2119] lr: 4.0000e-02 eta: 1 day, 1:26:18 time: 0.3597 data_time: 0.0210 memory: 11108 grad_norm: 2.9762 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.6328 loss: 2.6328 2022/10/09 12:33:58 - mmengine - INFO - Epoch(train) [31][1620/2119] lr: 4.0000e-02 eta: 1 day, 1:26:11 time: 0.3636 data_time: 0.0157 memory: 11108 grad_norm: 3.0026 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5983 loss: 2.5983 2022/10/09 12:34:05 - mmengine - INFO - Epoch(train) [31][1640/2119] lr: 4.0000e-02 eta: 1 day, 1:26:03 time: 0.3586 data_time: 0.0197 memory: 11108 grad_norm: 2.9574 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5003 loss: 2.5003 2022/10/09 12:34:12 - mmengine - INFO - Epoch(train) [31][1660/2119] lr: 4.0000e-02 eta: 1 day, 1:25:56 time: 0.3632 data_time: 0.0264 memory: 11108 grad_norm: 2.9767 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5689 loss: 2.5689 2022/10/09 12:34:19 - mmengine - INFO - Epoch(train) [31][1680/2119] lr: 4.0000e-02 eta: 1 day, 1:25:48 time: 0.3581 data_time: 0.0200 memory: 11108 grad_norm: 2.9299 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9359 loss: 2.9359 2022/10/09 12:34:27 - mmengine - INFO - Epoch(train) [31][1700/2119] lr: 4.0000e-02 eta: 1 day, 1:25:41 time: 0.3615 data_time: 0.0187 memory: 11108 grad_norm: 2.9406 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4846 loss: 2.4846 2022/10/09 12:34:34 - mmengine - INFO - Epoch(train) [31][1720/2119] lr: 4.0000e-02 eta: 1 day, 1:25:34 time: 0.3627 data_time: 0.0231 memory: 11108 grad_norm: 2.9045 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.4259 loss: 2.4259 2022/10/09 12:34:41 - mmengine - INFO - Epoch(train) [31][1740/2119] lr: 4.0000e-02 eta: 1 day, 1:25:26 time: 0.3533 data_time: 0.0189 memory: 11108 grad_norm: 2.9598 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3917 loss: 2.3917 2022/10/09 12:34:48 - mmengine - INFO - Epoch(train) [31][1760/2119] lr: 4.0000e-02 eta: 1 day, 1:25:18 time: 0.3596 data_time: 0.0210 memory: 11108 grad_norm: 2.9738 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6588 loss: 2.6588 2022/10/09 12:34:55 - mmengine - INFO - Epoch(train) [31][1780/2119] lr: 4.0000e-02 eta: 1 day, 1:25:11 time: 0.3607 data_time: 0.0170 memory: 11108 grad_norm: 2.9437 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7220 loss: 2.7220 2022/10/09 12:35:03 - mmengine - INFO - Epoch(train) [31][1800/2119] lr: 4.0000e-02 eta: 1 day, 1:25:04 time: 0.3611 data_time: 0.0186 memory: 11108 grad_norm: 2.9269 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6830 loss: 2.6830 2022/10/09 12:35:10 - mmengine - INFO - Epoch(train) [31][1820/2119] lr: 4.0000e-02 eta: 1 day, 1:24:56 time: 0.3598 data_time: 0.0210 memory: 11108 grad_norm: 2.9824 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5669 loss: 2.5669 2022/10/09 12:35:17 - mmengine - INFO - Epoch(train) [31][1840/2119] lr: 4.0000e-02 eta: 1 day, 1:24:49 time: 0.3567 data_time: 0.0251 memory: 11108 grad_norm: 2.9363 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7382 loss: 2.7382 2022/10/09 12:35:24 - mmengine - INFO - Epoch(train) [31][1860/2119] lr: 4.0000e-02 eta: 1 day, 1:24:41 time: 0.3579 data_time: 0.0176 memory: 11108 grad_norm: 2.9121 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5341 loss: 2.5341 2022/10/09 12:35:31 - mmengine - INFO - Epoch(train) [31][1880/2119] lr: 4.0000e-02 eta: 1 day, 1:24:33 time: 0.3579 data_time: 0.0223 memory: 11108 grad_norm: 2.9668 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8344 loss: 2.8344 2022/10/09 12:35:38 - mmengine - INFO - Epoch(train) [31][1900/2119] lr: 4.0000e-02 eta: 1 day, 1:24:26 time: 0.3543 data_time: 0.0193 memory: 11108 grad_norm: 2.9187 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8251 loss: 2.8251 2022/10/09 12:35:45 - mmengine - INFO - Epoch(train) [31][1920/2119] lr: 4.0000e-02 eta: 1 day, 1:24:18 time: 0.3597 data_time: 0.0217 memory: 11108 grad_norm: 2.9897 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7579 loss: 2.7579 2022/10/09 12:35:53 - mmengine - INFO - Epoch(train) [31][1940/2119] lr: 4.0000e-02 eta: 1 day, 1:24:10 time: 0.3567 data_time: 0.0206 memory: 11108 grad_norm: 2.8680 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5695 loss: 2.5695 2022/10/09 12:36:00 - mmengine - INFO - Epoch(train) [31][1960/2119] lr: 4.0000e-02 eta: 1 day, 1:24:03 time: 0.3600 data_time: 0.0242 memory: 11108 grad_norm: 2.9828 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.5602 loss: 2.5602 2022/10/09 12:36:07 - mmengine - INFO - Epoch(train) [31][1980/2119] lr: 4.0000e-02 eta: 1 day, 1:23:55 time: 0.3576 data_time: 0.0215 memory: 11108 grad_norm: 2.9711 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6496 loss: 2.6496 2022/10/09 12:36:14 - mmengine - INFO - Epoch(train) [31][2000/2119] lr: 4.0000e-02 eta: 1 day, 1:23:48 time: 0.3566 data_time: 0.0219 memory: 11108 grad_norm: 2.9526 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.6546 loss: 2.6546 2022/10/09 12:36:21 - mmengine - INFO - Epoch(train) [31][2020/2119] lr: 4.0000e-02 eta: 1 day, 1:23:40 time: 0.3583 data_time: 0.0220 memory: 11108 grad_norm: 2.9741 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6935 loss: 2.6935 2022/10/09 12:36:28 - mmengine - INFO - Epoch(train) [31][2040/2119] lr: 4.0000e-02 eta: 1 day, 1:23:32 time: 0.3574 data_time: 0.0220 memory: 11108 grad_norm: 2.9174 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7349 loss: 2.7349 2022/10/09 12:36:36 - mmengine - INFO - Epoch(train) [31][2060/2119] lr: 4.0000e-02 eta: 1 day, 1:23:25 time: 0.3573 data_time: 0.0178 memory: 11108 grad_norm: 2.9571 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5995 loss: 2.5995 2022/10/09 12:36:43 - mmengine - INFO - Epoch(train) [31][2080/2119] lr: 4.0000e-02 eta: 1 day, 1:23:17 time: 0.3567 data_time: 0.0198 memory: 11108 grad_norm: 2.9542 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8915 loss: 2.8915 2022/10/09 12:36:50 - mmengine - INFO - Epoch(train) [31][2100/2119] lr: 4.0000e-02 eta: 1 day, 1:23:10 time: 0.3687 data_time: 0.0199 memory: 11108 grad_norm: 2.9744 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5925 loss: 2.5925 2022/10/09 12:36:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 12:36:56 - mmengine - INFO - Epoch(train) [31][2119/2119] lr: 4.0000e-02 eta: 1 day, 1:23:10 time: 0.3368 data_time: 0.0175 memory: 11108 grad_norm: 2.9881 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 2.9316 loss: 2.9316 2022/10/09 12:37:07 - mmengine - INFO - Epoch(train) [32][20/2119] lr: 4.0000e-02 eta: 1 day, 1:22:42 time: 0.5207 data_time: 0.1136 memory: 11108 grad_norm: 2.9115 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6624 loss: 2.6624 2022/10/09 12:37:14 - mmengine - INFO - Epoch(train) [32][40/2119] lr: 4.0000e-02 eta: 1 day, 1:22:35 time: 0.3619 data_time: 0.0213 memory: 11108 grad_norm: 2.9653 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7574 loss: 2.7574 2022/10/09 12:37:22 - mmengine - INFO - Epoch(train) [32][60/2119] lr: 4.0000e-02 eta: 1 day, 1:22:28 time: 0.3761 data_time: 0.0361 memory: 11108 grad_norm: 2.9695 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7433 loss: 2.7433 2022/10/09 12:37:29 - mmengine - INFO - Epoch(train) [32][80/2119] lr: 4.0000e-02 eta: 1 day, 1:22:21 time: 0.3556 data_time: 0.0192 memory: 11108 grad_norm: 3.0048 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6420 loss: 2.6420 2022/10/09 12:37:36 - mmengine - INFO - Epoch(train) [32][100/2119] lr: 4.0000e-02 eta: 1 day, 1:22:13 time: 0.3593 data_time: 0.0206 memory: 11108 grad_norm: 2.9612 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.5618 loss: 2.5618 2022/10/09 12:37:43 - mmengine - INFO - Epoch(train) [32][120/2119] lr: 4.0000e-02 eta: 1 day, 1:22:06 time: 0.3612 data_time: 0.0206 memory: 11108 grad_norm: 2.9348 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4745 loss: 2.4745 2022/10/09 12:37:50 - mmengine - INFO - Epoch(train) [32][140/2119] lr: 4.0000e-02 eta: 1 day, 1:21:58 time: 0.3583 data_time: 0.0195 memory: 11108 grad_norm: 2.9748 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4439 loss: 2.4439 2022/10/09 12:37:58 - mmengine - INFO - Epoch(train) [32][160/2119] lr: 4.0000e-02 eta: 1 day, 1:21:51 time: 0.3645 data_time: 0.0272 memory: 11108 grad_norm: 2.9646 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6826 loss: 2.6826 2022/10/09 12:38:05 - mmengine - INFO - Epoch(train) [32][180/2119] lr: 4.0000e-02 eta: 1 day, 1:21:44 time: 0.3604 data_time: 0.0218 memory: 11108 grad_norm: 2.9311 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5637 loss: 2.5637 2022/10/09 12:38:12 - mmengine - INFO - Epoch(train) [32][200/2119] lr: 4.0000e-02 eta: 1 day, 1:21:37 time: 0.3636 data_time: 0.0198 memory: 11108 grad_norm: 2.9282 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7380 loss: 2.7380 2022/10/09 12:38:19 - mmengine - INFO - Epoch(train) [32][220/2119] lr: 4.0000e-02 eta: 1 day, 1:21:29 time: 0.3559 data_time: 0.0194 memory: 11108 grad_norm: 2.9497 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6802 loss: 2.6802 2022/10/09 12:38:27 - mmengine - INFO - Epoch(train) [32][240/2119] lr: 4.0000e-02 eta: 1 day, 1:21:22 time: 0.3632 data_time: 0.0247 memory: 11108 grad_norm: 2.9258 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3972 loss: 2.3972 2022/10/09 12:38:34 - mmengine - INFO - Epoch(train) [32][260/2119] lr: 4.0000e-02 eta: 1 day, 1:21:15 time: 0.3643 data_time: 0.0180 memory: 11108 grad_norm: 2.9461 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6388 loss: 2.6388 2022/10/09 12:38:41 - mmengine - INFO - Epoch(train) [32][280/2119] lr: 4.0000e-02 eta: 1 day, 1:21:07 time: 0.3552 data_time: 0.0223 memory: 11108 grad_norm: 2.9703 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6062 loss: 2.6062 2022/10/09 12:38:48 - mmengine - INFO - Epoch(train) [32][300/2119] lr: 4.0000e-02 eta: 1 day, 1:20:59 time: 0.3588 data_time: 0.0190 memory: 11108 grad_norm: 2.9108 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4197 loss: 2.4197 2022/10/09 12:38:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 12:38:55 - mmengine - INFO - Epoch(train) [32][320/2119] lr: 4.0000e-02 eta: 1 day, 1:20:52 time: 0.3620 data_time: 0.0192 memory: 11108 grad_norm: 3.0311 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6986 loss: 2.6986 2022/10/09 12:39:03 - mmengine - INFO - Epoch(train) [32][340/2119] lr: 4.0000e-02 eta: 1 day, 1:20:45 time: 0.3579 data_time: 0.0195 memory: 11108 grad_norm: 2.9653 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6602 loss: 2.6602 2022/10/09 12:39:10 - mmengine - INFO - Epoch(train) [32][360/2119] lr: 4.0000e-02 eta: 1 day, 1:20:37 time: 0.3599 data_time: 0.0212 memory: 11108 grad_norm: 2.9463 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7553 loss: 2.7553 2022/10/09 12:39:17 - mmengine - INFO - Epoch(train) [32][380/2119] lr: 4.0000e-02 eta: 1 day, 1:20:30 time: 0.3593 data_time: 0.0226 memory: 11108 grad_norm: 2.9642 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5020 loss: 2.5020 2022/10/09 12:39:24 - mmengine - INFO - Epoch(train) [32][400/2119] lr: 4.0000e-02 eta: 1 day, 1:20:22 time: 0.3579 data_time: 0.0205 memory: 11108 grad_norm: 2.9832 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.9967 loss: 2.9967 2022/10/09 12:39:31 - mmengine - INFO - Epoch(train) [32][420/2119] lr: 4.0000e-02 eta: 1 day, 1:20:15 time: 0.3597 data_time: 0.0210 memory: 11108 grad_norm: 2.9365 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6555 loss: 2.6555 2022/10/09 12:39:38 - mmengine - INFO - Epoch(train) [32][440/2119] lr: 4.0000e-02 eta: 1 day, 1:20:07 time: 0.3539 data_time: 0.0204 memory: 11108 grad_norm: 2.9490 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7836 loss: 2.7836 2022/10/09 12:39:46 - mmengine - INFO - Epoch(train) [32][460/2119] lr: 4.0000e-02 eta: 1 day, 1:19:59 time: 0.3577 data_time: 0.0191 memory: 11108 grad_norm: 2.9899 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7048 loss: 2.7048 2022/10/09 12:39:53 - mmengine - INFO - Epoch(train) [32][480/2119] lr: 4.0000e-02 eta: 1 day, 1:19:52 time: 0.3597 data_time: 0.0201 memory: 11108 grad_norm: 2.9527 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6027 loss: 2.6027 2022/10/09 12:40:00 - mmengine - INFO - Epoch(train) [32][500/2119] lr: 4.0000e-02 eta: 1 day, 1:19:44 time: 0.3581 data_time: 0.0200 memory: 11108 grad_norm: 2.9841 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6682 loss: 2.6682 2022/10/09 12:40:07 - mmengine - INFO - Epoch(train) [32][520/2119] lr: 4.0000e-02 eta: 1 day, 1:19:37 time: 0.3595 data_time: 0.0179 memory: 11108 grad_norm: 2.9374 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7215 loss: 2.7215 2022/10/09 12:40:14 - mmengine - INFO - Epoch(train) [32][540/2119] lr: 4.0000e-02 eta: 1 day, 1:19:29 time: 0.3609 data_time: 0.0180 memory: 11108 grad_norm: 2.9252 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6016 loss: 2.6016 2022/10/09 12:40:21 - mmengine - INFO - Epoch(train) [32][560/2119] lr: 4.0000e-02 eta: 1 day, 1:19:21 time: 0.3550 data_time: 0.0227 memory: 11108 grad_norm: 2.9432 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.6602 loss: 2.6602 2022/10/09 12:40:29 - mmengine - INFO - Epoch(train) [32][580/2119] lr: 4.0000e-02 eta: 1 day, 1:19:14 time: 0.3585 data_time: 0.0200 memory: 11108 grad_norm: 2.9780 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.4213 loss: 2.4213 2022/10/09 12:40:36 - mmengine - INFO - Epoch(train) [32][600/2119] lr: 4.0000e-02 eta: 1 day, 1:19:07 time: 0.3631 data_time: 0.0210 memory: 11108 grad_norm: 2.9974 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6531 loss: 2.6531 2022/10/09 12:40:43 - mmengine - INFO - Epoch(train) [32][620/2119] lr: 4.0000e-02 eta: 1 day, 1:18:59 time: 0.3575 data_time: 0.0193 memory: 11108 grad_norm: 3.0099 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.4623 loss: 2.4623 2022/10/09 12:40:50 - mmengine - INFO - Epoch(train) [32][640/2119] lr: 4.0000e-02 eta: 1 day, 1:18:52 time: 0.3579 data_time: 0.0209 memory: 11108 grad_norm: 2.9780 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4479 loss: 2.4479 2022/10/09 12:40:57 - mmengine - INFO - Epoch(train) [32][660/2119] lr: 4.0000e-02 eta: 1 day, 1:18:44 time: 0.3616 data_time: 0.0206 memory: 11108 grad_norm: 2.9918 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6162 loss: 2.6162 2022/10/09 12:41:05 - mmengine - INFO - Epoch(train) [32][680/2119] lr: 4.0000e-02 eta: 1 day, 1:18:38 time: 0.3788 data_time: 0.0235 memory: 11108 grad_norm: 2.9688 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7736 loss: 2.7736 2022/10/09 12:41:12 - mmengine - INFO - Epoch(train) [32][700/2119] lr: 4.0000e-02 eta: 1 day, 1:18:31 time: 0.3591 data_time: 0.0199 memory: 11108 grad_norm: 2.9670 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8088 loss: 2.8088 2022/10/09 12:41:19 - mmengine - INFO - Epoch(train) [32][720/2119] lr: 4.0000e-02 eta: 1 day, 1:18:23 time: 0.3557 data_time: 0.0248 memory: 11108 grad_norm: 3.0450 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7336 loss: 2.7336 2022/10/09 12:41:26 - mmengine - INFO - Epoch(train) [32][740/2119] lr: 4.0000e-02 eta: 1 day, 1:18:15 time: 0.3567 data_time: 0.0143 memory: 11108 grad_norm: 2.9948 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6508 loss: 2.6508 2022/10/09 12:41:34 - mmengine - INFO - Epoch(train) [32][760/2119] lr: 4.0000e-02 eta: 1 day, 1:18:08 time: 0.3623 data_time: 0.0229 memory: 11108 grad_norm: 2.9951 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4702 loss: 2.4702 2022/10/09 12:41:41 - mmengine - INFO - Epoch(train) [32][780/2119] lr: 4.0000e-02 eta: 1 day, 1:18:01 time: 0.3587 data_time: 0.0204 memory: 11108 grad_norm: 2.9405 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6973 loss: 2.6973 2022/10/09 12:41:48 - mmengine - INFO - Epoch(train) [32][800/2119] lr: 4.0000e-02 eta: 1 day, 1:17:53 time: 0.3611 data_time: 0.0246 memory: 11108 grad_norm: 2.9249 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5222 loss: 2.5222 2022/10/09 12:41:55 - mmengine - INFO - Epoch(train) [32][820/2119] lr: 4.0000e-02 eta: 1 day, 1:17:46 time: 0.3609 data_time: 0.0210 memory: 11108 grad_norm: 2.9862 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5616 loss: 2.5616 2022/10/09 12:42:02 - mmengine - INFO - Epoch(train) [32][840/2119] lr: 4.0000e-02 eta: 1 day, 1:17:38 time: 0.3554 data_time: 0.0199 memory: 11108 grad_norm: 2.8759 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4908 loss: 2.4908 2022/10/09 12:42:10 - mmengine - INFO - Epoch(train) [32][860/2119] lr: 4.0000e-02 eta: 1 day, 1:17:31 time: 0.3603 data_time: 0.0219 memory: 11108 grad_norm: 2.9776 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7822 loss: 2.7822 2022/10/09 12:42:17 - mmengine - INFO - Epoch(train) [32][880/2119] lr: 4.0000e-02 eta: 1 day, 1:17:23 time: 0.3567 data_time: 0.0211 memory: 11108 grad_norm: 2.9020 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6427 loss: 2.6427 2022/10/09 12:42:24 - mmengine - INFO - Epoch(train) [32][900/2119] lr: 4.0000e-02 eta: 1 day, 1:17:16 time: 0.3594 data_time: 0.0192 memory: 11108 grad_norm: 2.9333 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5099 loss: 2.5099 2022/10/09 12:42:31 - mmengine - INFO - Epoch(train) [32][920/2119] lr: 4.0000e-02 eta: 1 day, 1:17:08 time: 0.3600 data_time: 0.0194 memory: 11108 grad_norm: 2.9983 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6274 loss: 2.6274 2022/10/09 12:42:38 - mmengine - INFO - Epoch(train) [32][940/2119] lr: 4.0000e-02 eta: 1 day, 1:17:00 time: 0.3546 data_time: 0.0203 memory: 11108 grad_norm: 2.9430 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.4545 loss: 2.4545 2022/10/09 12:42:45 - mmengine - INFO - Epoch(train) [32][960/2119] lr: 4.0000e-02 eta: 1 day, 1:16:53 time: 0.3612 data_time: 0.0198 memory: 11108 grad_norm: 2.9776 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.7489 loss: 2.7489 2022/10/09 12:42:53 - mmengine - INFO - Epoch(train) [32][980/2119] lr: 4.0000e-02 eta: 1 day, 1:16:46 time: 0.3594 data_time: 0.0188 memory: 11108 grad_norm: 3.0100 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.7126 loss: 2.7126 2022/10/09 12:43:00 - mmengine - INFO - Epoch(train) [32][1000/2119] lr: 4.0000e-02 eta: 1 day, 1:16:38 time: 0.3573 data_time: 0.0188 memory: 11108 grad_norm: 2.9742 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6592 loss: 2.6592 2022/10/09 12:43:07 - mmengine - INFO - Epoch(train) [32][1020/2119] lr: 4.0000e-02 eta: 1 day, 1:16:30 time: 0.3565 data_time: 0.0223 memory: 11108 grad_norm: 2.9550 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6226 loss: 2.6226 2022/10/09 12:43:14 - mmengine - INFO - Epoch(train) [32][1040/2119] lr: 4.0000e-02 eta: 1 day, 1:16:23 time: 0.3602 data_time: 0.0216 memory: 11108 grad_norm: 2.9845 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5600 loss: 2.5600 2022/10/09 12:43:21 - mmengine - INFO - Epoch(train) [32][1060/2119] lr: 4.0000e-02 eta: 1 day, 1:16:16 time: 0.3660 data_time: 0.0197 memory: 11108 grad_norm: 2.9138 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6482 loss: 2.6482 2022/10/09 12:43:29 - mmengine - INFO - Epoch(train) [32][1080/2119] lr: 4.0000e-02 eta: 1 day, 1:16:08 time: 0.3551 data_time: 0.0207 memory: 11108 grad_norm: 2.9588 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8129 loss: 2.8129 2022/10/09 12:43:36 - mmengine - INFO - Epoch(train) [32][1100/2119] lr: 4.0000e-02 eta: 1 day, 1:16:01 time: 0.3648 data_time: 0.0208 memory: 11108 grad_norm: 3.0044 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6323 loss: 2.6323 2022/10/09 12:43:43 - mmengine - INFO - Epoch(train) [32][1120/2119] lr: 4.0000e-02 eta: 1 day, 1:15:53 time: 0.3585 data_time: 0.0224 memory: 11108 grad_norm: 2.9408 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7603 loss: 2.7603 2022/10/09 12:43:50 - mmengine - INFO - Epoch(train) [32][1140/2119] lr: 4.0000e-02 eta: 1 day, 1:15:46 time: 0.3619 data_time: 0.0199 memory: 11108 grad_norm: 2.9639 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.5701 loss: 2.5701 2022/10/09 12:43:57 - mmengine - INFO - Epoch(train) [32][1160/2119] lr: 4.0000e-02 eta: 1 day, 1:15:39 time: 0.3610 data_time: 0.0190 memory: 11108 grad_norm: 2.9833 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5991 loss: 2.5991 2022/10/09 12:44:05 - mmengine - INFO - Epoch(train) [32][1180/2119] lr: 4.0000e-02 eta: 1 day, 1:15:31 time: 0.3563 data_time: 0.0184 memory: 11108 grad_norm: 3.0555 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.4764 loss: 2.4764 2022/10/09 12:44:12 - mmengine - INFO - Epoch(train) [32][1200/2119] lr: 4.0000e-02 eta: 1 day, 1:15:23 time: 0.3571 data_time: 0.0174 memory: 11108 grad_norm: 3.0133 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7001 loss: 2.7001 2022/10/09 12:44:19 - mmengine - INFO - Epoch(train) [32][1220/2119] lr: 4.0000e-02 eta: 1 day, 1:15:16 time: 0.3613 data_time: 0.0227 memory: 11108 grad_norm: 2.9757 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7294 loss: 2.7294 2022/10/09 12:44:26 - mmengine - INFO - Epoch(train) [32][1240/2119] lr: 4.0000e-02 eta: 1 day, 1:15:09 time: 0.3579 data_time: 0.0215 memory: 11108 grad_norm: 2.9363 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6639 loss: 2.6639 2022/10/09 12:44:33 - mmengine - INFO - Epoch(train) [32][1260/2119] lr: 4.0000e-02 eta: 1 day, 1:15:02 time: 0.3662 data_time: 0.0171 memory: 11108 grad_norm: 2.9362 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5867 loss: 2.5867 2022/10/09 12:44:41 - mmengine - INFO - Epoch(train) [32][1280/2119] lr: 4.0000e-02 eta: 1 day, 1:14:55 time: 0.3665 data_time: 0.0198 memory: 11108 grad_norm: 2.9774 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6939 loss: 2.6939 2022/10/09 12:44:48 - mmengine - INFO - Epoch(train) [32][1300/2119] lr: 4.0000e-02 eta: 1 day, 1:14:47 time: 0.3586 data_time: 0.0181 memory: 11108 grad_norm: 2.9693 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7384 loss: 2.7384 2022/10/09 12:44:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 12:44:55 - mmengine - INFO - Epoch(train) [32][1320/2119] lr: 4.0000e-02 eta: 1 day, 1:14:39 time: 0.3546 data_time: 0.0203 memory: 11108 grad_norm: 2.9636 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7986 loss: 2.7986 2022/10/09 12:45:02 - mmengine - INFO - Epoch(train) [32][1340/2119] lr: 4.0000e-02 eta: 1 day, 1:14:32 time: 0.3610 data_time: 0.0241 memory: 11108 grad_norm: 2.9108 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8137 loss: 2.8137 2022/10/09 12:45:09 - mmengine - INFO - Epoch(train) [32][1360/2119] lr: 4.0000e-02 eta: 1 day, 1:14:24 time: 0.3574 data_time: 0.0197 memory: 11108 grad_norm: 2.9522 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6726 loss: 2.6726 2022/10/09 12:45:17 - mmengine - INFO - Epoch(train) [32][1380/2119] lr: 4.0000e-02 eta: 1 day, 1:14:17 time: 0.3585 data_time: 0.0226 memory: 11108 grad_norm: 2.9801 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6966 loss: 2.6966 2022/10/09 12:45:24 - mmengine - INFO - Epoch(train) [32][1400/2119] lr: 4.0000e-02 eta: 1 day, 1:14:10 time: 0.3607 data_time: 0.0231 memory: 11108 grad_norm: 2.9936 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5992 loss: 2.5992 2022/10/09 12:45:31 - mmengine - INFO - Epoch(train) [32][1420/2119] lr: 4.0000e-02 eta: 1 day, 1:14:02 time: 0.3623 data_time: 0.0217 memory: 11108 grad_norm: 2.9428 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7929 loss: 2.7929 2022/10/09 12:45:38 - mmengine - INFO - Epoch(train) [32][1440/2119] lr: 4.0000e-02 eta: 1 day, 1:13:55 time: 0.3564 data_time: 0.0239 memory: 11108 grad_norm: 2.9908 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5476 loss: 2.5476 2022/10/09 12:45:45 - mmengine - INFO - Epoch(train) [32][1460/2119] lr: 4.0000e-02 eta: 1 day, 1:13:47 time: 0.3563 data_time: 0.0191 memory: 11108 grad_norm: 2.9143 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6130 loss: 2.6130 2022/10/09 12:45:52 - mmengine - INFO - Epoch(train) [32][1480/2119] lr: 4.0000e-02 eta: 1 day, 1:13:39 time: 0.3592 data_time: 0.0217 memory: 11108 grad_norm: 2.9220 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5349 loss: 2.5349 2022/10/09 12:46:00 - mmengine - INFO - Epoch(train) [32][1500/2119] lr: 4.0000e-02 eta: 1 day, 1:13:32 time: 0.3544 data_time: 0.0189 memory: 11108 grad_norm: 2.9793 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7281 loss: 2.7281 2022/10/09 12:46:07 - mmengine - INFO - Epoch(train) [32][1520/2119] lr: 4.0000e-02 eta: 1 day, 1:13:24 time: 0.3600 data_time: 0.0222 memory: 11108 grad_norm: 2.9050 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.6729 loss: 2.6729 2022/10/09 12:46:14 - mmengine - INFO - Epoch(train) [32][1540/2119] lr: 4.0000e-02 eta: 1 day, 1:13:17 time: 0.3572 data_time: 0.0232 memory: 11108 grad_norm: 2.9751 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6741 loss: 2.6741 2022/10/09 12:46:21 - mmengine - INFO - Epoch(train) [32][1560/2119] lr: 4.0000e-02 eta: 1 day, 1:13:09 time: 0.3583 data_time: 0.0207 memory: 11108 grad_norm: 2.9635 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8340 loss: 2.8340 2022/10/09 12:46:28 - mmengine - INFO - Epoch(train) [32][1580/2119] lr: 4.0000e-02 eta: 1 day, 1:13:02 time: 0.3636 data_time: 0.0181 memory: 11108 grad_norm: 3.0233 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.6127 loss: 2.6127 2022/10/09 12:46:35 - mmengine - INFO - Epoch(train) [32][1600/2119] lr: 4.0000e-02 eta: 1 day, 1:12:54 time: 0.3557 data_time: 0.0201 memory: 11108 grad_norm: 2.9834 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6798 loss: 2.6798 2022/10/09 12:46:43 - mmengine - INFO - Epoch(train) [32][1620/2119] lr: 4.0000e-02 eta: 1 day, 1:12:46 time: 0.3557 data_time: 0.0204 memory: 11108 grad_norm: 2.9665 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7277 loss: 2.7277 2022/10/09 12:46:50 - mmengine - INFO - Epoch(train) [32][1640/2119] lr: 4.0000e-02 eta: 1 day, 1:12:39 time: 0.3575 data_time: 0.0183 memory: 11108 grad_norm: 2.9915 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7668 loss: 2.7668 2022/10/09 12:46:57 - mmengine - INFO - Epoch(train) [32][1660/2119] lr: 4.0000e-02 eta: 1 day, 1:12:31 time: 0.3575 data_time: 0.0208 memory: 11108 grad_norm: 2.9717 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5265 loss: 2.5265 2022/10/09 12:47:04 - mmengine - INFO - Epoch(train) [32][1680/2119] lr: 4.0000e-02 eta: 1 day, 1:12:24 time: 0.3578 data_time: 0.0226 memory: 11108 grad_norm: 3.0608 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6320 loss: 2.6320 2022/10/09 12:47:11 - mmengine - INFO - Epoch(train) [32][1700/2119] lr: 4.0000e-02 eta: 1 day, 1:12:16 time: 0.3562 data_time: 0.0197 memory: 11108 grad_norm: 2.9891 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8189 loss: 2.8189 2022/10/09 12:47:18 - mmengine - INFO - Epoch(train) [32][1720/2119] lr: 4.0000e-02 eta: 1 day, 1:12:08 time: 0.3578 data_time: 0.0207 memory: 11108 grad_norm: 2.8893 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.4925 loss: 2.4925 2022/10/09 12:47:26 - mmengine - INFO - Epoch(train) [32][1740/2119] lr: 4.0000e-02 eta: 1 day, 1:12:01 time: 0.3651 data_time: 0.0205 memory: 11108 grad_norm: 2.9604 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6815 loss: 2.6815 2022/10/09 12:47:33 - mmengine - INFO - Epoch(train) [32][1760/2119] lr: 4.0000e-02 eta: 1 day, 1:11:54 time: 0.3589 data_time: 0.0224 memory: 11108 grad_norm: 2.9335 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7079 loss: 2.7079 2022/10/09 12:47:40 - mmengine - INFO - Epoch(train) [32][1780/2119] lr: 4.0000e-02 eta: 1 day, 1:11:46 time: 0.3540 data_time: 0.0235 memory: 11108 grad_norm: 3.0005 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6216 loss: 2.6216 2022/10/09 12:47:47 - mmengine - INFO - Epoch(train) [32][1800/2119] lr: 4.0000e-02 eta: 1 day, 1:11:39 time: 0.3639 data_time: 0.0196 memory: 11108 grad_norm: 2.9316 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7000 loss: 2.7000 2022/10/09 12:47:54 - mmengine - INFO - Epoch(train) [32][1820/2119] lr: 4.0000e-02 eta: 1 day, 1:11:32 time: 0.3615 data_time: 0.0196 memory: 11108 grad_norm: 2.9051 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6764 loss: 2.6764 2022/10/09 12:48:02 - mmengine - INFO - Epoch(train) [32][1840/2119] lr: 4.0000e-02 eta: 1 day, 1:11:24 time: 0.3626 data_time: 0.0214 memory: 11108 grad_norm: 2.9426 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3126 loss: 2.3126 2022/10/09 12:48:09 - mmengine - INFO - Epoch(train) [32][1860/2119] lr: 4.0000e-02 eta: 1 day, 1:11:17 time: 0.3631 data_time: 0.0179 memory: 11108 grad_norm: 2.9821 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5887 loss: 2.5887 2022/10/09 12:48:16 - mmengine - INFO - Epoch(train) [32][1880/2119] lr: 4.0000e-02 eta: 1 day, 1:11:09 time: 0.3557 data_time: 0.0185 memory: 11108 grad_norm: 2.9431 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5113 loss: 2.5113 2022/10/09 12:48:23 - mmengine - INFO - Epoch(train) [32][1900/2119] lr: 4.0000e-02 eta: 1 day, 1:11:02 time: 0.3569 data_time: 0.0198 memory: 11108 grad_norm: 2.9527 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6422 loss: 2.6422 2022/10/09 12:48:31 - mmengine - INFO - Epoch(train) [32][1920/2119] lr: 4.0000e-02 eta: 1 day, 1:10:55 time: 0.3680 data_time: 0.0243 memory: 11108 grad_norm: 2.9599 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6326 loss: 2.6326 2022/10/09 12:48:38 - mmengine - INFO - Epoch(train) [32][1940/2119] lr: 4.0000e-02 eta: 1 day, 1:10:47 time: 0.3558 data_time: 0.0213 memory: 11108 grad_norm: 2.9788 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6156 loss: 2.6156 2022/10/09 12:48:45 - mmengine - INFO - Epoch(train) [32][1960/2119] lr: 4.0000e-02 eta: 1 day, 1:10:40 time: 0.3649 data_time: 0.0250 memory: 11108 grad_norm: 2.9392 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.5036 loss: 2.5036 2022/10/09 12:48:52 - mmengine - INFO - Epoch(train) [32][1980/2119] lr: 4.0000e-02 eta: 1 day, 1:10:32 time: 0.3559 data_time: 0.0222 memory: 11108 grad_norm: 2.9832 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6772 loss: 2.6772 2022/10/09 12:48:59 - mmengine - INFO - Epoch(train) [32][2000/2119] lr: 4.0000e-02 eta: 1 day, 1:10:25 time: 0.3570 data_time: 0.0206 memory: 11108 grad_norm: 3.0449 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6385 loss: 2.6385 2022/10/09 12:49:06 - mmengine - INFO - Epoch(train) [32][2020/2119] lr: 4.0000e-02 eta: 1 day, 1:10:17 time: 0.3595 data_time: 0.0233 memory: 11108 grad_norm: 2.9160 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6067 loss: 2.6067 2022/10/09 12:49:14 - mmengine - INFO - Epoch(train) [32][2040/2119] lr: 4.0000e-02 eta: 1 day, 1:10:10 time: 0.3566 data_time: 0.0200 memory: 11108 grad_norm: 2.9516 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.3222 loss: 2.3222 2022/10/09 12:49:21 - mmengine - INFO - Epoch(train) [32][2060/2119] lr: 4.0000e-02 eta: 1 day, 1:10:02 time: 0.3607 data_time: 0.0281 memory: 11108 grad_norm: 2.9858 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6059 loss: 2.6059 2022/10/09 12:49:28 - mmengine - INFO - Epoch(train) [32][2080/2119] lr: 4.0000e-02 eta: 1 day, 1:09:55 time: 0.3590 data_time: 0.0198 memory: 11108 grad_norm: 2.9589 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7807 loss: 2.7807 2022/10/09 12:49:35 - mmengine - INFO - Epoch(train) [32][2100/2119] lr: 4.0000e-02 eta: 1 day, 1:09:47 time: 0.3559 data_time: 0.0212 memory: 11108 grad_norm: 2.8709 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4902 loss: 2.4902 2022/10/09 12:49:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 12:49:42 - mmengine - INFO - Epoch(train) [32][2119/2119] lr: 4.0000e-02 eta: 1 day, 1:09:47 time: 0.3475 data_time: 0.0172 memory: 11108 grad_norm: 2.9661 top1_acc: 0.2000 top5_acc: 0.6000 loss_cls: 2.6883 loss: 2.6883 2022/10/09 12:49:42 - mmengine - INFO - Saving checkpoint at 32 epochs 2022/10/09 12:49:55 - mmengine - INFO - Epoch(train) [33][20/2119] lr: 4.0000e-02 eta: 1 day, 1:09:13 time: 0.4391 data_time: 0.1085 memory: 11108 grad_norm: 2.9158 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6734 loss: 2.6734 2022/10/09 12:50:02 - mmengine - INFO - Epoch(train) [33][40/2119] lr: 4.0000e-02 eta: 1 day, 1:09:06 time: 0.3670 data_time: 0.0297 memory: 11108 grad_norm: 2.9846 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5808 loss: 2.5808 2022/10/09 12:50:09 - mmengine - INFO - Epoch(train) [33][60/2119] lr: 4.0000e-02 eta: 1 day, 1:08:59 time: 0.3565 data_time: 0.0225 memory: 11108 grad_norm: 2.8781 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5528 loss: 2.5528 2022/10/09 12:50:16 - mmengine - INFO - Epoch(train) [33][80/2119] lr: 4.0000e-02 eta: 1 day, 1:08:51 time: 0.3576 data_time: 0.0227 memory: 11108 grad_norm: 2.9503 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6321 loss: 2.6321 2022/10/09 12:50:23 - mmengine - INFO - Epoch(train) [33][100/2119] lr: 4.0000e-02 eta: 1 day, 1:08:44 time: 0.3607 data_time: 0.0195 memory: 11108 grad_norm: 3.0065 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4139 loss: 2.4139 2022/10/09 12:50:31 - mmengine - INFO - Epoch(train) [33][120/2119] lr: 4.0000e-02 eta: 1 day, 1:08:37 time: 0.3619 data_time: 0.0245 memory: 11108 grad_norm: 3.0098 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4920 loss: 2.4920 2022/10/09 12:50:38 - mmengine - INFO - Epoch(train) [33][140/2119] lr: 4.0000e-02 eta: 1 day, 1:08:29 time: 0.3599 data_time: 0.0225 memory: 11108 grad_norm: 2.9385 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5045 loss: 2.5045 2022/10/09 12:50:45 - mmengine - INFO - Epoch(train) [33][160/2119] lr: 4.0000e-02 eta: 1 day, 1:08:22 time: 0.3641 data_time: 0.0232 memory: 11108 grad_norm: 2.9866 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5701 loss: 2.5701 2022/10/09 12:50:52 - mmengine - INFO - Epoch(train) [33][180/2119] lr: 4.0000e-02 eta: 1 day, 1:08:15 time: 0.3600 data_time: 0.0225 memory: 11108 grad_norm: 2.9379 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5292 loss: 2.5292 2022/10/09 12:50:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 12:51:00 - mmengine - INFO - Epoch(train) [33][200/2119] lr: 4.0000e-02 eta: 1 day, 1:08:08 time: 0.3665 data_time: 0.0230 memory: 11108 grad_norm: 2.9417 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7052 loss: 2.7052 2022/10/09 12:51:07 - mmengine - INFO - Epoch(train) [33][220/2119] lr: 4.0000e-02 eta: 1 day, 1:08:00 time: 0.3620 data_time: 0.0219 memory: 11108 grad_norm: 2.9697 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7397 loss: 2.7397 2022/10/09 12:51:14 - mmengine - INFO - Epoch(train) [33][240/2119] lr: 4.0000e-02 eta: 1 day, 1:07:53 time: 0.3583 data_time: 0.0217 memory: 11108 grad_norm: 2.9404 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6551 loss: 2.6551 2022/10/09 12:51:21 - mmengine - INFO - Epoch(train) [33][260/2119] lr: 4.0000e-02 eta: 1 day, 1:07:45 time: 0.3579 data_time: 0.0207 memory: 11108 grad_norm: 2.9848 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7785 loss: 2.7785 2022/10/09 12:51:28 - mmengine - INFO - Epoch(train) [33][280/2119] lr: 4.0000e-02 eta: 1 day, 1:07:38 time: 0.3572 data_time: 0.0217 memory: 11108 grad_norm: 3.0056 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8308 loss: 2.8308 2022/10/09 12:51:36 - mmengine - INFO - Epoch(train) [33][300/2119] lr: 4.0000e-02 eta: 1 day, 1:07:30 time: 0.3567 data_time: 0.0178 memory: 11108 grad_norm: 2.9960 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4335 loss: 2.4335 2022/10/09 12:51:43 - mmengine - INFO - Epoch(train) [33][320/2119] lr: 4.0000e-02 eta: 1 day, 1:07:23 time: 0.3586 data_time: 0.0260 memory: 11108 grad_norm: 3.0469 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9483 loss: 2.9483 2022/10/09 12:51:50 - mmengine - INFO - Epoch(train) [33][340/2119] lr: 4.0000e-02 eta: 1 day, 1:07:15 time: 0.3564 data_time: 0.0202 memory: 11108 grad_norm: 2.9543 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5557 loss: 2.5557 2022/10/09 12:51:57 - mmengine - INFO - Epoch(train) [33][360/2119] lr: 4.0000e-02 eta: 1 day, 1:07:07 time: 0.3587 data_time: 0.0225 memory: 11108 grad_norm: 2.9388 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6003 loss: 2.6003 2022/10/09 12:52:04 - mmengine - INFO - Epoch(train) [33][380/2119] lr: 4.0000e-02 eta: 1 day, 1:07:00 time: 0.3544 data_time: 0.0225 memory: 11108 grad_norm: 2.9009 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.3579 loss: 2.3579 2022/10/09 12:52:11 - mmengine - INFO - Epoch(train) [33][400/2119] lr: 4.0000e-02 eta: 1 day, 1:06:52 time: 0.3580 data_time: 0.0194 memory: 11108 grad_norm: 3.0091 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7161 loss: 2.7161 2022/10/09 12:52:19 - mmengine - INFO - Epoch(train) [33][420/2119] lr: 4.0000e-02 eta: 1 day, 1:06:45 time: 0.3607 data_time: 0.0215 memory: 11108 grad_norm: 3.0121 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5359 loss: 2.5359 2022/10/09 12:52:26 - mmengine - INFO - Epoch(train) [33][440/2119] lr: 4.0000e-02 eta: 1 day, 1:06:37 time: 0.3613 data_time: 0.0264 memory: 11108 grad_norm: 2.9985 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5923 loss: 2.5923 2022/10/09 12:52:33 - mmengine - INFO - Epoch(train) [33][460/2119] lr: 4.0000e-02 eta: 1 day, 1:06:30 time: 0.3581 data_time: 0.0206 memory: 11108 grad_norm: 3.0248 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8502 loss: 2.8502 2022/10/09 12:52:40 - mmengine - INFO - Epoch(train) [33][480/2119] lr: 4.0000e-02 eta: 1 day, 1:06:22 time: 0.3551 data_time: 0.0188 memory: 11108 grad_norm: 2.9550 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8212 loss: 2.8212 2022/10/09 12:52:47 - mmengine - INFO - Epoch(train) [33][500/2119] lr: 4.0000e-02 eta: 1 day, 1:06:15 time: 0.3588 data_time: 0.0209 memory: 11108 grad_norm: 2.9656 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5142 loss: 2.5142 2022/10/09 12:52:54 - mmengine - INFO - Epoch(train) [33][520/2119] lr: 4.0000e-02 eta: 1 day, 1:06:07 time: 0.3635 data_time: 0.0213 memory: 11108 grad_norm: 2.9125 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5524 loss: 2.5524 2022/10/09 12:53:02 - mmengine - INFO - Epoch(train) [33][540/2119] lr: 4.0000e-02 eta: 1 day, 1:06:00 time: 0.3560 data_time: 0.0217 memory: 11108 grad_norm: 3.0041 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8105 loss: 2.8105 2022/10/09 12:53:09 - mmengine - INFO - Epoch(train) [33][560/2119] lr: 4.0000e-02 eta: 1 day, 1:05:52 time: 0.3564 data_time: 0.0197 memory: 11108 grad_norm: 3.0362 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7596 loss: 2.7596 2022/10/09 12:53:16 - mmengine - INFO - Epoch(train) [33][580/2119] lr: 4.0000e-02 eta: 1 day, 1:05:45 time: 0.3593 data_time: 0.0207 memory: 11108 grad_norm: 3.0023 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6058 loss: 2.6058 2022/10/09 12:53:23 - mmengine - INFO - Epoch(train) [33][600/2119] lr: 4.0000e-02 eta: 1 day, 1:05:37 time: 0.3559 data_time: 0.0243 memory: 11108 grad_norm: 2.9670 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7496 loss: 2.7496 2022/10/09 12:53:30 - mmengine - INFO - Epoch(train) [33][620/2119] lr: 4.0000e-02 eta: 1 day, 1:05:29 time: 0.3568 data_time: 0.0194 memory: 11108 grad_norm: 2.9731 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5448 loss: 2.5448 2022/10/09 12:53:37 - mmengine - INFO - Epoch(train) [33][640/2119] lr: 4.0000e-02 eta: 1 day, 1:05:22 time: 0.3606 data_time: 0.0228 memory: 11108 grad_norm: 3.0055 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7900 loss: 2.7900 2022/10/09 12:53:45 - mmengine - INFO - Epoch(train) [33][660/2119] lr: 4.0000e-02 eta: 1 day, 1:05:14 time: 0.3568 data_time: 0.0200 memory: 11108 grad_norm: 2.9701 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.1630 loss: 2.1630 2022/10/09 12:53:52 - mmengine - INFO - Epoch(train) [33][680/2119] lr: 4.0000e-02 eta: 1 day, 1:05:07 time: 0.3640 data_time: 0.0219 memory: 11108 grad_norm: 2.9334 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6527 loss: 2.6527 2022/10/09 12:53:59 - mmengine - INFO - Epoch(train) [33][700/2119] lr: 4.0000e-02 eta: 1 day, 1:05:00 time: 0.3565 data_time: 0.0253 memory: 11108 grad_norm: 2.9544 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.4430 loss: 2.4430 2022/10/09 12:54:06 - mmengine - INFO - Epoch(train) [33][720/2119] lr: 4.0000e-02 eta: 1 day, 1:04:52 time: 0.3603 data_time: 0.0230 memory: 11108 grad_norm: 3.0170 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.6748 loss: 2.6748 2022/10/09 12:54:13 - mmengine - INFO - Epoch(train) [33][740/2119] lr: 4.0000e-02 eta: 1 day, 1:04:45 time: 0.3560 data_time: 0.0210 memory: 11108 grad_norm: 2.9617 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4672 loss: 2.4672 2022/10/09 12:54:20 - mmengine - INFO - Epoch(train) [33][760/2119] lr: 4.0000e-02 eta: 1 day, 1:04:37 time: 0.3568 data_time: 0.0204 memory: 11108 grad_norm: 3.0139 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5560 loss: 2.5560 2022/10/09 12:54:28 - mmengine - INFO - Epoch(train) [33][780/2119] lr: 4.0000e-02 eta: 1 day, 1:04:29 time: 0.3589 data_time: 0.0218 memory: 11108 grad_norm: 2.9931 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4942 loss: 2.4942 2022/10/09 12:54:35 - mmengine - INFO - Epoch(train) [33][800/2119] lr: 4.0000e-02 eta: 1 day, 1:04:22 time: 0.3610 data_time: 0.0224 memory: 11108 grad_norm: 2.9830 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5395 loss: 2.5395 2022/10/09 12:54:42 - mmengine - INFO - Epoch(train) [33][820/2119] lr: 4.0000e-02 eta: 1 day, 1:04:14 time: 0.3571 data_time: 0.0186 memory: 11108 grad_norm: 2.9947 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5595 loss: 2.5595 2022/10/09 12:54:49 - mmengine - INFO - Epoch(train) [33][840/2119] lr: 4.0000e-02 eta: 1 day, 1:04:07 time: 0.3619 data_time: 0.0194 memory: 11108 grad_norm: 3.0051 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5792 loss: 2.5792 2022/10/09 12:54:56 - mmengine - INFO - Epoch(train) [33][860/2119] lr: 4.0000e-02 eta: 1 day, 1:04:00 time: 0.3581 data_time: 0.0197 memory: 11108 grad_norm: 2.9913 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5608 loss: 2.5608 2022/10/09 12:55:04 - mmengine - INFO - Epoch(train) [33][880/2119] lr: 4.0000e-02 eta: 1 day, 1:03:52 time: 0.3608 data_time: 0.0223 memory: 11108 grad_norm: 2.9484 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6018 loss: 2.6018 2022/10/09 12:55:11 - mmengine - INFO - Epoch(train) [33][900/2119] lr: 4.0000e-02 eta: 1 day, 1:03:45 time: 0.3576 data_time: 0.0223 memory: 11108 grad_norm: 2.9240 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6778 loss: 2.6778 2022/10/09 12:55:18 - mmengine - INFO - Epoch(train) [33][920/2119] lr: 4.0000e-02 eta: 1 day, 1:03:37 time: 0.3585 data_time: 0.0226 memory: 11108 grad_norm: 3.0107 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6430 loss: 2.6430 2022/10/09 12:55:25 - mmengine - INFO - Epoch(train) [33][940/2119] lr: 4.0000e-02 eta: 1 day, 1:03:30 time: 0.3572 data_time: 0.0191 memory: 11108 grad_norm: 2.9941 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.3979 loss: 2.3979 2022/10/09 12:55:33 - mmengine - INFO - Epoch(train) [33][960/2119] lr: 4.0000e-02 eta: 1 day, 1:03:23 time: 0.3775 data_time: 0.0231 memory: 11108 grad_norm: 2.9384 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5363 loss: 2.5363 2022/10/09 12:55:40 - mmengine - INFO - Epoch(train) [33][980/2119] lr: 4.0000e-02 eta: 1 day, 1:03:16 time: 0.3557 data_time: 0.0201 memory: 11108 grad_norm: 3.0370 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7567 loss: 2.7567 2022/10/09 12:55:47 - mmengine - INFO - Epoch(train) [33][1000/2119] lr: 4.0000e-02 eta: 1 day, 1:03:08 time: 0.3601 data_time: 0.0184 memory: 11108 grad_norm: 2.9541 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6553 loss: 2.6553 2022/10/09 12:55:54 - mmengine - INFO - Epoch(train) [33][1020/2119] lr: 4.0000e-02 eta: 1 day, 1:03:01 time: 0.3579 data_time: 0.0248 memory: 11108 grad_norm: 2.9382 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7894 loss: 2.7894 2022/10/09 12:56:01 - mmengine - INFO - Epoch(train) [33][1040/2119] lr: 4.0000e-02 eta: 1 day, 1:02:53 time: 0.3606 data_time: 0.0276 memory: 11108 grad_norm: 2.9591 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6031 loss: 2.6031 2022/10/09 12:56:08 - mmengine - INFO - Epoch(train) [33][1060/2119] lr: 4.0000e-02 eta: 1 day, 1:02:46 time: 0.3590 data_time: 0.0229 memory: 11108 grad_norm: 2.9302 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.5757 loss: 2.5757 2022/10/09 12:56:16 - mmengine - INFO - Epoch(train) [33][1080/2119] lr: 4.0000e-02 eta: 1 day, 1:02:39 time: 0.3595 data_time: 0.0204 memory: 11108 grad_norm: 2.9773 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5280 loss: 2.5280 2022/10/09 12:56:23 - mmengine - INFO - Epoch(train) [33][1100/2119] lr: 4.0000e-02 eta: 1 day, 1:02:31 time: 0.3560 data_time: 0.0199 memory: 11108 grad_norm: 2.9692 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5941 loss: 2.5941 2022/10/09 12:56:30 - mmengine - INFO - Epoch(train) [33][1120/2119] lr: 4.0000e-02 eta: 1 day, 1:02:23 time: 0.3571 data_time: 0.0250 memory: 11108 grad_norm: 3.0075 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6587 loss: 2.6587 2022/10/09 12:56:37 - mmengine - INFO - Epoch(train) [33][1140/2119] lr: 4.0000e-02 eta: 1 day, 1:02:16 time: 0.3629 data_time: 0.0186 memory: 11108 grad_norm: 2.9940 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7752 loss: 2.7752 2022/10/09 12:56:44 - mmengine - INFO - Epoch(train) [33][1160/2119] lr: 4.0000e-02 eta: 1 day, 1:02:09 time: 0.3575 data_time: 0.0217 memory: 11108 grad_norm: 2.9798 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5926 loss: 2.5926 2022/10/09 12:56:52 - mmengine - INFO - Epoch(train) [33][1180/2119] lr: 4.0000e-02 eta: 1 day, 1:02:01 time: 0.3596 data_time: 0.0211 memory: 11108 grad_norm: 3.0288 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6881 loss: 2.6881 2022/10/09 12:56:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 12:56:59 - mmengine - INFO - Epoch(train) [33][1200/2119] lr: 4.0000e-02 eta: 1 day, 1:01:54 time: 0.3588 data_time: 0.0200 memory: 11108 grad_norm: 2.9620 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.3380 loss: 2.3380 2022/10/09 12:57:06 - mmengine - INFO - Epoch(train) [33][1220/2119] lr: 4.0000e-02 eta: 1 day, 1:01:46 time: 0.3586 data_time: 0.0216 memory: 11108 grad_norm: 2.9814 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3981 loss: 2.3981 2022/10/09 12:57:13 - mmengine - INFO - Epoch(train) [33][1240/2119] lr: 4.0000e-02 eta: 1 day, 1:01:39 time: 0.3610 data_time: 0.0215 memory: 11108 grad_norm: 2.9506 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5867 loss: 2.5867 2022/10/09 12:57:20 - mmengine - INFO - Epoch(train) [33][1260/2119] lr: 4.0000e-02 eta: 1 day, 1:01:31 time: 0.3564 data_time: 0.0232 memory: 11108 grad_norm: 2.9014 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.7761 loss: 2.7761 2022/10/09 12:57:27 - mmengine - INFO - Epoch(train) [33][1280/2119] lr: 4.0000e-02 eta: 1 day, 1:01:24 time: 0.3586 data_time: 0.0222 memory: 11108 grad_norm: 2.9283 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7085 loss: 2.7085 2022/10/09 12:57:35 - mmengine - INFO - Epoch(train) [33][1300/2119] lr: 4.0000e-02 eta: 1 day, 1:01:17 time: 0.3650 data_time: 0.0205 memory: 11108 grad_norm: 2.9700 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4045 loss: 2.4045 2022/10/09 12:57:42 - mmengine - INFO - Epoch(train) [33][1320/2119] lr: 4.0000e-02 eta: 1 day, 1:01:09 time: 0.3549 data_time: 0.0229 memory: 11108 grad_norm: 2.9382 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4341 loss: 2.4341 2022/10/09 12:57:49 - mmengine - INFO - Epoch(train) [33][1340/2119] lr: 4.0000e-02 eta: 1 day, 1:01:01 time: 0.3570 data_time: 0.0198 memory: 11108 grad_norm: 2.9847 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6629 loss: 2.6629 2022/10/09 12:57:56 - mmengine - INFO - Epoch(train) [33][1360/2119] lr: 4.0000e-02 eta: 1 day, 1:00:54 time: 0.3610 data_time: 0.0211 memory: 11108 grad_norm: 3.0049 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5091 loss: 2.5091 2022/10/09 12:58:03 - mmengine - INFO - Epoch(train) [33][1380/2119] lr: 4.0000e-02 eta: 1 day, 1:00:46 time: 0.3579 data_time: 0.0185 memory: 11108 grad_norm: 2.9545 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5589 loss: 2.5589 2022/10/09 12:58:10 - mmengine - INFO - Epoch(train) [33][1400/2119] lr: 4.0000e-02 eta: 1 day, 1:00:39 time: 0.3562 data_time: 0.0210 memory: 11108 grad_norm: 2.9534 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7607 loss: 2.7607 2022/10/09 12:58:18 - mmengine - INFO - Epoch(train) [33][1420/2119] lr: 4.0000e-02 eta: 1 day, 1:00:32 time: 0.3662 data_time: 0.0237 memory: 11108 grad_norm: 2.9422 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5475 loss: 2.5475 2022/10/09 12:58:25 - mmengine - INFO - Epoch(train) [33][1440/2119] lr: 4.0000e-02 eta: 1 day, 1:00:24 time: 0.3554 data_time: 0.0191 memory: 11108 grad_norm: 2.9758 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4872 loss: 2.4872 2022/10/09 12:58:32 - mmengine - INFO - Epoch(train) [33][1460/2119] lr: 4.0000e-02 eta: 1 day, 1:00:17 time: 0.3601 data_time: 0.0303 memory: 11108 grad_norm: 2.9271 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6356 loss: 2.6356 2022/10/09 12:58:39 - mmengine - INFO - Epoch(train) [33][1480/2119] lr: 4.0000e-02 eta: 1 day, 1:00:09 time: 0.3594 data_time: 0.0216 memory: 11108 grad_norm: 2.9742 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5954 loss: 2.5954 2022/10/09 12:58:46 - mmengine - INFO - Epoch(train) [33][1500/2119] lr: 4.0000e-02 eta: 1 day, 1:00:02 time: 0.3571 data_time: 0.0225 memory: 11108 grad_norm: 2.9803 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5230 loss: 2.5230 2022/10/09 12:58:54 - mmengine - INFO - Epoch(train) [33][1520/2119] lr: 4.0000e-02 eta: 1 day, 0:59:54 time: 0.3591 data_time: 0.0203 memory: 11108 grad_norm: 2.9825 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.7437 loss: 2.7437 2022/10/09 12:59:01 - mmengine - INFO - Epoch(train) [33][1540/2119] lr: 4.0000e-02 eta: 1 day, 0:59:47 time: 0.3570 data_time: 0.0215 memory: 11108 grad_norm: 2.9839 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8248 loss: 2.8248 2022/10/09 12:59:08 - mmengine - INFO - Epoch(train) [33][1560/2119] lr: 4.0000e-02 eta: 1 day, 0:59:39 time: 0.3601 data_time: 0.0204 memory: 11108 grad_norm: 2.9229 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7152 loss: 2.7152 2022/10/09 12:59:15 - mmengine - INFO - Epoch(train) [33][1580/2119] lr: 4.0000e-02 eta: 1 day, 0:59:32 time: 0.3640 data_time: 0.0227 memory: 11108 grad_norm: 2.9620 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8195 loss: 2.8195 2022/10/09 12:59:22 - mmengine - INFO - Epoch(train) [33][1600/2119] lr: 4.0000e-02 eta: 1 day, 0:59:25 time: 0.3580 data_time: 0.0243 memory: 11108 grad_norm: 2.9406 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7004 loss: 2.7004 2022/10/09 12:59:30 - mmengine - INFO - Epoch(train) [33][1620/2119] lr: 4.0000e-02 eta: 1 day, 0:59:17 time: 0.3553 data_time: 0.0228 memory: 11108 grad_norm: 2.9604 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6080 loss: 2.6080 2022/10/09 12:59:37 - mmengine - INFO - Epoch(train) [33][1640/2119] lr: 4.0000e-02 eta: 1 day, 0:59:09 time: 0.3552 data_time: 0.0204 memory: 11108 grad_norm: 2.9186 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4579 loss: 2.4579 2022/10/09 12:59:44 - mmengine - INFO - Epoch(train) [33][1660/2119] lr: 4.0000e-02 eta: 1 day, 0:59:02 time: 0.3605 data_time: 0.0206 memory: 11108 grad_norm: 2.9366 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4238 loss: 2.4238 2022/10/09 12:59:51 - mmengine - INFO - Epoch(train) [33][1680/2119] lr: 4.0000e-02 eta: 1 day, 0:58:54 time: 0.3564 data_time: 0.0219 memory: 11108 grad_norm: 2.9266 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4808 loss: 2.4808 2022/10/09 12:59:58 - mmengine - INFO - Epoch(train) [33][1700/2119] lr: 4.0000e-02 eta: 1 day, 0:58:47 time: 0.3647 data_time: 0.0202 memory: 11108 grad_norm: 2.9590 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6377 loss: 2.6377 2022/10/09 13:00:05 - mmengine - INFO - Epoch(train) [33][1720/2119] lr: 4.0000e-02 eta: 1 day, 0:58:40 time: 0.3603 data_time: 0.0206 memory: 11108 grad_norm: 2.9950 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7204 loss: 2.7204 2022/10/09 13:00:13 - mmengine - INFO - Epoch(train) [33][1740/2119] lr: 4.0000e-02 eta: 1 day, 0:58:32 time: 0.3585 data_time: 0.0177 memory: 11108 grad_norm: 2.9907 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8015 loss: 2.8015 2022/10/09 13:00:20 - mmengine - INFO - Epoch(train) [33][1760/2119] lr: 4.0000e-02 eta: 1 day, 0:58:25 time: 0.3607 data_time: 0.0223 memory: 11108 grad_norm: 2.9549 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6722 loss: 2.6722 2022/10/09 13:00:27 - mmengine - INFO - Epoch(train) [33][1780/2119] lr: 4.0000e-02 eta: 1 day, 0:58:17 time: 0.3611 data_time: 0.0207 memory: 11108 grad_norm: 2.9784 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5876 loss: 2.5876 2022/10/09 13:00:34 - mmengine - INFO - Epoch(train) [33][1800/2119] lr: 4.0000e-02 eta: 1 day, 0:58:10 time: 0.3595 data_time: 0.0204 memory: 11108 grad_norm: 3.0123 top1_acc: 0.3125 top5_acc: 0.9375 loss_cls: 2.6585 loss: 2.6585 2022/10/09 13:00:41 - mmengine - INFO - Epoch(train) [33][1820/2119] lr: 4.0000e-02 eta: 1 day, 0:58:02 time: 0.3581 data_time: 0.0208 memory: 11108 grad_norm: 2.9479 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7518 loss: 2.7518 2022/10/09 13:00:49 - mmengine - INFO - Epoch(train) [33][1840/2119] lr: 4.0000e-02 eta: 1 day, 0:57:55 time: 0.3580 data_time: 0.0211 memory: 11108 grad_norm: 2.9404 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.4983 loss: 2.4983 2022/10/09 13:00:56 - mmengine - INFO - Epoch(train) [33][1860/2119] lr: 4.0000e-02 eta: 1 day, 0:57:48 time: 0.3607 data_time: 0.0220 memory: 11108 grad_norm: 2.9940 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8081 loss: 2.8081 2022/10/09 13:01:03 - mmengine - INFO - Epoch(train) [33][1880/2119] lr: 4.0000e-02 eta: 1 day, 0:57:40 time: 0.3550 data_time: 0.0196 memory: 11108 grad_norm: 3.0216 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6374 loss: 2.6374 2022/10/09 13:01:10 - mmengine - INFO - Epoch(train) [33][1900/2119] lr: 4.0000e-02 eta: 1 day, 0:57:33 time: 0.3633 data_time: 0.0258 memory: 11108 grad_norm: 2.9450 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5870 loss: 2.5870 2022/10/09 13:01:17 - mmengine - INFO - Epoch(train) [33][1920/2119] lr: 4.0000e-02 eta: 1 day, 0:57:25 time: 0.3619 data_time: 0.0238 memory: 11108 grad_norm: 2.9449 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6309 loss: 2.6309 2022/10/09 13:01:25 - mmengine - INFO - Epoch(train) [33][1940/2119] lr: 4.0000e-02 eta: 1 day, 0:57:18 time: 0.3596 data_time: 0.0211 memory: 11108 grad_norm: 2.9838 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7360 loss: 2.7360 2022/10/09 13:01:32 - mmengine - INFO - Epoch(train) [33][1960/2119] lr: 4.0000e-02 eta: 1 day, 0:57:11 time: 0.3614 data_time: 0.0189 memory: 11108 grad_norm: 3.0058 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7714 loss: 2.7714 2022/10/09 13:01:39 - mmengine - INFO - Epoch(train) [33][1980/2119] lr: 4.0000e-02 eta: 1 day, 0:57:03 time: 0.3597 data_time: 0.0217 memory: 11108 grad_norm: 3.0274 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6882 loss: 2.6882 2022/10/09 13:01:46 - mmengine - INFO - Epoch(train) [33][2000/2119] lr: 4.0000e-02 eta: 1 day, 0:56:56 time: 0.3616 data_time: 0.0218 memory: 11108 grad_norm: 3.0172 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7184 loss: 2.7184 2022/10/09 13:01:53 - mmengine - INFO - Epoch(train) [33][2020/2119] lr: 4.0000e-02 eta: 1 day, 0:56:49 time: 0.3597 data_time: 0.0192 memory: 11108 grad_norm: 2.9384 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5763 loss: 2.5763 2022/10/09 13:02:01 - mmengine - INFO - Epoch(train) [33][2040/2119] lr: 4.0000e-02 eta: 1 day, 0:56:41 time: 0.3581 data_time: 0.0213 memory: 11108 grad_norm: 2.9542 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.7640 loss: 2.7640 2022/10/09 13:02:08 - mmengine - INFO - Epoch(train) [33][2060/2119] lr: 4.0000e-02 eta: 1 day, 0:56:33 time: 0.3554 data_time: 0.0227 memory: 11108 grad_norm: 3.0288 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6986 loss: 2.6986 2022/10/09 13:02:15 - mmengine - INFO - Epoch(train) [33][2080/2119] lr: 4.0000e-02 eta: 1 day, 0:56:26 time: 0.3588 data_time: 0.0193 memory: 11108 grad_norm: 2.9535 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7552 loss: 2.7552 2022/10/09 13:02:22 - mmengine - INFO - Epoch(train) [33][2100/2119] lr: 4.0000e-02 eta: 1 day, 0:56:18 time: 0.3545 data_time: 0.0215 memory: 11108 grad_norm: 2.9273 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7819 loss: 2.7819 2022/10/09 13:02:28 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 13:02:28 - mmengine - INFO - Epoch(train) [33][2119/2119] lr: 4.0000e-02 eta: 1 day, 0:56:18 time: 0.3394 data_time: 0.0177 memory: 11108 grad_norm: 3.0282 top1_acc: 0.4000 top5_acc: 0.6000 loss_cls: 2.8088 loss: 2.8088 2022/10/09 13:02:39 - mmengine - INFO - Epoch(train) [34][20/2119] lr: 4.0000e-02 eta: 1 day, 0:55:49 time: 0.4952 data_time: 0.1227 memory: 11108 grad_norm: 2.9603 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5523 loss: 2.5523 2022/10/09 13:02:46 - mmengine - INFO - Epoch(train) [34][40/2119] lr: 4.0000e-02 eta: 1 day, 0:55:43 time: 0.3748 data_time: 0.0211 memory: 11108 grad_norm: 2.9442 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4145 loss: 2.4145 2022/10/09 13:02:53 - mmengine - INFO - Epoch(train) [34][60/2119] lr: 4.0000e-02 eta: 1 day, 0:55:36 time: 0.3649 data_time: 0.0203 memory: 11108 grad_norm: 3.0256 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4552 loss: 2.4552 2022/10/09 13:02:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 13:03:01 - mmengine - INFO - Epoch(train) [34][80/2119] lr: 4.0000e-02 eta: 1 day, 0:55:28 time: 0.3593 data_time: 0.0211 memory: 11108 grad_norm: 2.9634 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5085 loss: 2.5085 2022/10/09 13:03:08 - mmengine - INFO - Epoch(train) [34][100/2119] lr: 4.0000e-02 eta: 1 day, 0:55:21 time: 0.3602 data_time: 0.0199 memory: 11108 grad_norm: 3.0126 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6215 loss: 2.6215 2022/10/09 13:03:15 - mmengine - INFO - Epoch(train) [34][120/2119] lr: 4.0000e-02 eta: 1 day, 0:55:14 time: 0.3663 data_time: 0.0306 memory: 11108 grad_norm: 3.0073 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5945 loss: 2.5945 2022/10/09 13:03:22 - mmengine - INFO - Epoch(train) [34][140/2119] lr: 4.0000e-02 eta: 1 day, 0:55:06 time: 0.3558 data_time: 0.0205 memory: 11108 grad_norm: 2.9696 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7537 loss: 2.7537 2022/10/09 13:03:29 - mmengine - INFO - Epoch(train) [34][160/2119] lr: 4.0000e-02 eta: 1 day, 0:54:59 time: 0.3594 data_time: 0.0213 memory: 11108 grad_norm: 2.9451 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5847 loss: 2.5847 2022/10/09 13:03:37 - mmengine - INFO - Epoch(train) [34][180/2119] lr: 4.0000e-02 eta: 1 day, 0:54:52 time: 0.3642 data_time: 0.0172 memory: 11108 grad_norm: 2.9490 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7382 loss: 2.7382 2022/10/09 13:03:44 - mmengine - INFO - Epoch(train) [34][200/2119] lr: 4.0000e-02 eta: 1 day, 0:54:44 time: 0.3601 data_time: 0.0206 memory: 11108 grad_norm: 2.9923 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5169 loss: 2.5169 2022/10/09 13:03:51 - mmengine - INFO - Epoch(train) [34][220/2119] lr: 4.0000e-02 eta: 1 day, 0:54:37 time: 0.3571 data_time: 0.0193 memory: 11108 grad_norm: 2.9997 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7283 loss: 2.7283 2022/10/09 13:03:58 - mmengine - INFO - Epoch(train) [34][240/2119] lr: 4.0000e-02 eta: 1 day, 0:54:29 time: 0.3578 data_time: 0.0212 memory: 11108 grad_norm: 2.9806 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.4635 loss: 2.4635 2022/10/09 13:04:05 - mmengine - INFO - Epoch(train) [34][260/2119] lr: 4.0000e-02 eta: 1 day, 0:54:22 time: 0.3598 data_time: 0.0163 memory: 11108 grad_norm: 2.9884 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5687 loss: 2.5687 2022/10/09 13:04:12 - mmengine - INFO - Epoch(train) [34][280/2119] lr: 4.0000e-02 eta: 1 day, 0:54:14 time: 0.3560 data_time: 0.0214 memory: 11108 grad_norm: 3.0132 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.4788 loss: 2.4788 2022/10/09 13:04:20 - mmengine - INFO - Epoch(train) [34][300/2119] lr: 4.0000e-02 eta: 1 day, 0:54:07 time: 0.3581 data_time: 0.0240 memory: 11108 grad_norm: 3.0234 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6772 loss: 2.6772 2022/10/09 13:04:27 - mmengine - INFO - Epoch(train) [34][320/2119] lr: 4.0000e-02 eta: 1 day, 0:53:59 time: 0.3620 data_time: 0.0245 memory: 11108 grad_norm: 2.9954 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6244 loss: 2.6244 2022/10/09 13:04:34 - mmengine - INFO - Epoch(train) [34][340/2119] lr: 4.0000e-02 eta: 1 day, 0:53:52 time: 0.3590 data_time: 0.0179 memory: 11108 grad_norm: 2.9543 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4839 loss: 2.4839 2022/10/09 13:04:41 - mmengine - INFO - Epoch(train) [34][360/2119] lr: 4.0000e-02 eta: 1 day, 0:53:44 time: 0.3553 data_time: 0.0226 memory: 11108 grad_norm: 3.0358 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7809 loss: 2.7809 2022/10/09 13:04:48 - mmengine - INFO - Epoch(train) [34][380/2119] lr: 4.0000e-02 eta: 1 day, 0:53:37 time: 0.3556 data_time: 0.0172 memory: 11108 grad_norm: 2.9950 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6444 loss: 2.6444 2022/10/09 13:04:56 - mmengine - INFO - Epoch(train) [34][400/2119] lr: 4.0000e-02 eta: 1 day, 0:53:30 time: 0.3660 data_time: 0.0257 memory: 11108 grad_norm: 2.9167 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5898 loss: 2.5898 2022/10/09 13:05:03 - mmengine - INFO - Epoch(train) [34][420/2119] lr: 4.0000e-02 eta: 1 day, 0:53:22 time: 0.3626 data_time: 0.0192 memory: 11108 grad_norm: 2.9927 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5834 loss: 2.5834 2022/10/09 13:05:10 - mmengine - INFO - Epoch(train) [34][440/2119] lr: 4.0000e-02 eta: 1 day, 0:53:15 time: 0.3557 data_time: 0.0219 memory: 11108 grad_norm: 2.9903 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3417 loss: 2.3417 2022/10/09 13:05:17 - mmengine - INFO - Epoch(train) [34][460/2119] lr: 4.0000e-02 eta: 1 day, 0:53:08 time: 0.3653 data_time: 0.0220 memory: 11108 grad_norm: 3.0324 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5434 loss: 2.5434 2022/10/09 13:05:24 - mmengine - INFO - Epoch(train) [34][480/2119] lr: 4.0000e-02 eta: 1 day, 0:53:00 time: 0.3589 data_time: 0.0203 memory: 11108 grad_norm: 2.9990 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8107 loss: 2.8107 2022/10/09 13:05:32 - mmengine - INFO - Epoch(train) [34][500/2119] lr: 4.0000e-02 eta: 1 day, 0:52:53 time: 0.3606 data_time: 0.0191 memory: 11108 grad_norm: 2.9791 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7870 loss: 2.7870 2022/10/09 13:05:39 - mmengine - INFO - Epoch(train) [34][520/2119] lr: 4.0000e-02 eta: 1 day, 0:52:45 time: 0.3577 data_time: 0.0193 memory: 11108 grad_norm: 2.9962 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5090 loss: 2.5090 2022/10/09 13:05:46 - mmengine - INFO - Epoch(train) [34][540/2119] lr: 4.0000e-02 eta: 1 day, 0:52:38 time: 0.3638 data_time: 0.0219 memory: 11108 grad_norm: 2.9498 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.4975 loss: 2.4975 2022/10/09 13:05:53 - mmengine - INFO - Epoch(train) [34][560/2119] lr: 4.0000e-02 eta: 1 day, 0:52:31 time: 0.3654 data_time: 0.0311 memory: 11108 grad_norm: 2.9614 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6356 loss: 2.6356 2022/10/09 13:06:01 - mmengine - INFO - Epoch(train) [34][580/2119] lr: 4.0000e-02 eta: 1 day, 0:52:24 time: 0.3574 data_time: 0.0188 memory: 11108 grad_norm: 3.0320 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7835 loss: 2.7835 2022/10/09 13:06:08 - mmengine - INFO - Epoch(train) [34][600/2119] lr: 4.0000e-02 eta: 1 day, 0:52:16 time: 0.3598 data_time: 0.0185 memory: 11108 grad_norm: 2.9726 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7025 loss: 2.7025 2022/10/09 13:06:15 - mmengine - INFO - Epoch(train) [34][620/2119] lr: 4.0000e-02 eta: 1 day, 0:52:09 time: 0.3614 data_time: 0.0202 memory: 11108 grad_norm: 2.9580 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6018 loss: 2.6018 2022/10/09 13:06:22 - mmengine - INFO - Epoch(train) [34][640/2119] lr: 4.0000e-02 eta: 1 day, 0:52:01 time: 0.3541 data_time: 0.0182 memory: 11108 grad_norm: 3.0112 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5924 loss: 2.5924 2022/10/09 13:06:29 - mmengine - INFO - Epoch(train) [34][660/2119] lr: 4.0000e-02 eta: 1 day, 0:51:54 time: 0.3603 data_time: 0.0210 memory: 11108 grad_norm: 3.0466 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5903 loss: 2.5903 2022/10/09 13:06:36 - mmengine - INFO - Epoch(train) [34][680/2119] lr: 4.0000e-02 eta: 1 day, 0:51:46 time: 0.3587 data_time: 0.0202 memory: 11108 grad_norm: 2.9952 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.8946 loss: 2.8946 2022/10/09 13:06:44 - mmengine - INFO - Epoch(train) [34][700/2119] lr: 4.0000e-02 eta: 1 day, 0:51:39 time: 0.3586 data_time: 0.0167 memory: 11108 grad_norm: 3.0415 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5522 loss: 2.5522 2022/10/09 13:06:51 - mmengine - INFO - Epoch(train) [34][720/2119] lr: 4.0000e-02 eta: 1 day, 0:51:31 time: 0.3563 data_time: 0.0228 memory: 11108 grad_norm: 3.0206 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4588 loss: 2.4588 2022/10/09 13:06:58 - mmengine - INFO - Epoch(train) [34][740/2119] lr: 4.0000e-02 eta: 1 day, 0:51:24 time: 0.3628 data_time: 0.0192 memory: 11108 grad_norm: 2.9800 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4695 loss: 2.4695 2022/10/09 13:07:05 - mmengine - INFO - Epoch(train) [34][760/2119] lr: 4.0000e-02 eta: 1 day, 0:51:17 time: 0.3582 data_time: 0.0210 memory: 11108 grad_norm: 2.9597 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 2.4794 loss: 2.4794 2022/10/09 13:07:12 - mmengine - INFO - Epoch(train) [34][780/2119] lr: 4.0000e-02 eta: 1 day, 0:51:09 time: 0.3609 data_time: 0.0204 memory: 11108 grad_norm: 2.9943 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6981 loss: 2.6981 2022/10/09 13:07:20 - mmengine - INFO - Epoch(train) [34][800/2119] lr: 4.0000e-02 eta: 1 day, 0:51:02 time: 0.3589 data_time: 0.0212 memory: 11108 grad_norm: 2.9938 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6171 loss: 2.6171 2022/10/09 13:07:27 - mmengine - INFO - Epoch(train) [34][820/2119] lr: 4.0000e-02 eta: 1 day, 0:50:54 time: 0.3573 data_time: 0.0208 memory: 11108 grad_norm: 2.9605 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5608 loss: 2.5608 2022/10/09 13:07:34 - mmengine - INFO - Epoch(train) [34][840/2119] lr: 4.0000e-02 eta: 1 day, 0:50:47 time: 0.3651 data_time: 0.0259 memory: 11108 grad_norm: 2.9751 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5100 loss: 2.5100 2022/10/09 13:07:41 - mmengine - INFO - Epoch(train) [34][860/2119] lr: 4.0000e-02 eta: 1 day, 0:50:39 time: 0.3557 data_time: 0.0176 memory: 11108 grad_norm: 2.9366 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7137 loss: 2.7137 2022/10/09 13:07:48 - mmengine - INFO - Epoch(train) [34][880/2119] lr: 4.0000e-02 eta: 1 day, 0:50:32 time: 0.3561 data_time: 0.0204 memory: 11108 grad_norm: 3.0192 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5026 loss: 2.5026 2022/10/09 13:07:55 - mmengine - INFO - Epoch(train) [34][900/2119] lr: 4.0000e-02 eta: 1 day, 0:50:24 time: 0.3557 data_time: 0.0200 memory: 11108 grad_norm: 3.0025 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7642 loss: 2.7642 2022/10/09 13:08:03 - mmengine - INFO - Epoch(train) [34][920/2119] lr: 4.0000e-02 eta: 1 day, 0:50:17 time: 0.3569 data_time: 0.0210 memory: 11108 grad_norm: 2.9703 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6382 loss: 2.6382 2022/10/09 13:08:10 - mmengine - INFO - Epoch(train) [34][940/2119] lr: 4.0000e-02 eta: 1 day, 0:50:09 time: 0.3590 data_time: 0.0200 memory: 11108 grad_norm: 3.0016 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6055 loss: 2.6055 2022/10/09 13:08:17 - mmengine - INFO - Epoch(train) [34][960/2119] lr: 4.0000e-02 eta: 1 day, 0:50:02 time: 0.3626 data_time: 0.0230 memory: 11108 grad_norm: 3.0240 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.5506 loss: 2.5506 2022/10/09 13:08:24 - mmengine - INFO - Epoch(train) [34][980/2119] lr: 4.0000e-02 eta: 1 day, 0:49:54 time: 0.3594 data_time: 0.0201 memory: 11108 grad_norm: 2.9682 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7375 loss: 2.7375 2022/10/09 13:08:31 - mmengine - INFO - Epoch(train) [34][1000/2119] lr: 4.0000e-02 eta: 1 day, 0:49:47 time: 0.3578 data_time: 0.0230 memory: 11108 grad_norm: 2.9689 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9458 loss: 2.9458 2022/10/09 13:08:39 - mmengine - INFO - Epoch(train) [34][1020/2119] lr: 4.0000e-02 eta: 1 day, 0:49:40 time: 0.3622 data_time: 0.0205 memory: 11108 grad_norm: 2.9848 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6515 loss: 2.6515 2022/10/09 13:08:46 - mmengine - INFO - Epoch(train) [34][1040/2119] lr: 4.0000e-02 eta: 1 day, 0:49:32 time: 0.3587 data_time: 0.0204 memory: 11108 grad_norm: 2.9584 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5103 loss: 2.5103 2022/10/09 13:08:53 - mmengine - INFO - Epoch(train) [34][1060/2119] lr: 4.0000e-02 eta: 1 day, 0:49:26 time: 0.3701 data_time: 0.0193 memory: 11108 grad_norm: 2.9734 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6124 loss: 2.6124 2022/10/09 13:08:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 13:09:00 - mmengine - INFO - Epoch(train) [34][1080/2119] lr: 4.0000e-02 eta: 1 day, 0:49:18 time: 0.3554 data_time: 0.0208 memory: 11108 grad_norm: 3.0071 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5083 loss: 2.5083 2022/10/09 13:09:07 - mmengine - INFO - Epoch(train) [34][1100/2119] lr: 4.0000e-02 eta: 1 day, 0:49:10 time: 0.3545 data_time: 0.0170 memory: 11108 grad_norm: 3.0029 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8913 loss: 2.8913 2022/10/09 13:09:15 - mmengine - INFO - Epoch(train) [34][1120/2119] lr: 4.0000e-02 eta: 1 day, 0:49:03 time: 0.3617 data_time: 0.0243 memory: 11108 grad_norm: 3.0211 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6924 loss: 2.6924 2022/10/09 13:09:22 - mmengine - INFO - Epoch(train) [34][1140/2119] lr: 4.0000e-02 eta: 1 day, 0:48:55 time: 0.3583 data_time: 0.0193 memory: 11108 grad_norm: 2.9458 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6804 loss: 2.6804 2022/10/09 13:09:29 - mmengine - INFO - Epoch(train) [34][1160/2119] lr: 4.0000e-02 eta: 1 day, 0:48:48 time: 0.3566 data_time: 0.0233 memory: 11108 grad_norm: 3.0030 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6297 loss: 2.6297 2022/10/09 13:09:36 - mmengine - INFO - Epoch(train) [34][1180/2119] lr: 4.0000e-02 eta: 1 day, 0:48:40 time: 0.3596 data_time: 0.0242 memory: 11108 grad_norm: 2.9875 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6334 loss: 2.6334 2022/10/09 13:09:43 - mmengine - INFO - Epoch(train) [34][1200/2119] lr: 4.0000e-02 eta: 1 day, 0:48:33 time: 0.3630 data_time: 0.0197 memory: 11108 grad_norm: 2.9945 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6663 loss: 2.6663 2022/10/09 13:09:50 - mmengine - INFO - Epoch(train) [34][1220/2119] lr: 4.0000e-02 eta: 1 day, 0:48:25 time: 0.3542 data_time: 0.0232 memory: 11108 grad_norm: 2.9563 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7004 loss: 2.7004 2022/10/09 13:09:58 - mmengine - INFO - Epoch(train) [34][1240/2119] lr: 4.0000e-02 eta: 1 day, 0:48:18 time: 0.3586 data_time: 0.0195 memory: 11108 grad_norm: 3.0084 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.3793 loss: 2.3793 2022/10/09 13:10:05 - mmengine - INFO - Epoch(train) [34][1260/2119] lr: 4.0000e-02 eta: 1 day, 0:48:11 time: 0.3620 data_time: 0.0211 memory: 11108 grad_norm: 2.9722 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6028 loss: 2.6028 2022/10/09 13:10:12 - mmengine - INFO - Epoch(train) [34][1280/2119] lr: 4.0000e-02 eta: 1 day, 0:48:03 time: 0.3553 data_time: 0.0192 memory: 11108 grad_norm: 3.0153 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7648 loss: 2.7648 2022/10/09 13:10:19 - mmengine - INFO - Epoch(train) [34][1300/2119] lr: 4.0000e-02 eta: 1 day, 0:47:56 time: 0.3593 data_time: 0.0200 memory: 11108 grad_norm: 2.9269 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.6424 loss: 2.6424 2022/10/09 13:10:26 - mmengine - INFO - Epoch(train) [34][1320/2119] lr: 4.0000e-02 eta: 1 day, 0:47:48 time: 0.3599 data_time: 0.0206 memory: 11108 grad_norm: 2.9606 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6785 loss: 2.6785 2022/10/09 13:10:33 - mmengine - INFO - Epoch(train) [34][1340/2119] lr: 4.0000e-02 eta: 1 day, 0:47:40 time: 0.3541 data_time: 0.0194 memory: 11108 grad_norm: 3.0208 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4286 loss: 2.4286 2022/10/09 13:10:41 - mmengine - INFO - Epoch(train) [34][1360/2119] lr: 4.0000e-02 eta: 1 day, 0:47:33 time: 0.3566 data_time: 0.0204 memory: 11108 grad_norm: 3.0397 top1_acc: 0.2500 top5_acc: 0.8125 loss_cls: 2.7353 loss: 2.7353 2022/10/09 13:10:48 - mmengine - INFO - Epoch(train) [34][1380/2119] lr: 4.0000e-02 eta: 1 day, 0:47:25 time: 0.3592 data_time: 0.0207 memory: 11108 grad_norm: 2.9805 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7641 loss: 2.7641 2022/10/09 13:10:55 - mmengine - INFO - Epoch(train) [34][1400/2119] lr: 4.0000e-02 eta: 1 day, 0:47:18 time: 0.3565 data_time: 0.0213 memory: 11108 grad_norm: 2.9180 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5530 loss: 2.5530 2022/10/09 13:11:02 - mmengine - INFO - Epoch(train) [34][1420/2119] lr: 4.0000e-02 eta: 1 day, 0:47:10 time: 0.3561 data_time: 0.0212 memory: 11108 grad_norm: 3.0156 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5955 loss: 2.5955 2022/10/09 13:11:09 - mmengine - INFO - Epoch(train) [34][1440/2119] lr: 4.0000e-02 eta: 1 day, 0:47:03 time: 0.3614 data_time: 0.0231 memory: 11108 grad_norm: 2.9817 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6496 loss: 2.6496 2022/10/09 13:11:16 - mmengine - INFO - Epoch(train) [34][1460/2119] lr: 4.0000e-02 eta: 1 day, 0:46:55 time: 0.3572 data_time: 0.0270 memory: 11108 grad_norm: 2.9805 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5166 loss: 2.5166 2022/10/09 13:11:24 - mmengine - INFO - Epoch(train) [34][1480/2119] lr: 4.0000e-02 eta: 1 day, 0:46:48 time: 0.3570 data_time: 0.0215 memory: 11108 grad_norm: 3.0085 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5810 loss: 2.5810 2022/10/09 13:11:31 - mmengine - INFO - Epoch(train) [34][1500/2119] lr: 4.0000e-02 eta: 1 day, 0:46:40 time: 0.3578 data_time: 0.0204 memory: 11108 grad_norm: 2.9919 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6281 loss: 2.6281 2022/10/09 13:11:38 - mmengine - INFO - Epoch(train) [34][1520/2119] lr: 4.0000e-02 eta: 1 day, 0:46:33 time: 0.3590 data_time: 0.0200 memory: 11108 grad_norm: 2.9475 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6532 loss: 2.6532 2022/10/09 13:11:45 - mmengine - INFO - Epoch(train) [34][1540/2119] lr: 4.0000e-02 eta: 1 day, 0:46:25 time: 0.3559 data_time: 0.0226 memory: 11108 grad_norm: 3.0302 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7998 loss: 2.7998 2022/10/09 13:11:52 - mmengine - INFO - Epoch(train) [34][1560/2119] lr: 4.0000e-02 eta: 1 day, 0:46:18 time: 0.3602 data_time: 0.0205 memory: 11108 grad_norm: 3.0573 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6220 loss: 2.6220 2022/10/09 13:11:59 - mmengine - INFO - Epoch(train) [34][1580/2119] lr: 4.0000e-02 eta: 1 day, 0:46:10 time: 0.3562 data_time: 0.0198 memory: 11108 grad_norm: 2.9694 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6441 loss: 2.6441 2022/10/09 13:12:06 - mmengine - INFO - Epoch(train) [34][1600/2119] lr: 4.0000e-02 eta: 1 day, 0:46:03 time: 0.3591 data_time: 0.0237 memory: 11108 grad_norm: 2.9704 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8015 loss: 2.8015 2022/10/09 13:12:14 - mmengine - INFO - Epoch(train) [34][1620/2119] lr: 4.0000e-02 eta: 1 day, 0:45:55 time: 0.3591 data_time: 0.0222 memory: 11108 grad_norm: 2.9995 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5645 loss: 2.5645 2022/10/09 13:12:21 - mmengine - INFO - Epoch(train) [34][1640/2119] lr: 4.0000e-02 eta: 1 day, 0:45:47 time: 0.3567 data_time: 0.0213 memory: 11108 grad_norm: 3.0165 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8965 loss: 2.8965 2022/10/09 13:12:28 - mmengine - INFO - Epoch(train) [34][1660/2119] lr: 4.0000e-02 eta: 1 day, 0:45:40 time: 0.3593 data_time: 0.0211 memory: 11108 grad_norm: 3.0168 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.4364 loss: 2.4364 2022/10/09 13:12:35 - mmengine - INFO - Epoch(train) [34][1680/2119] lr: 4.0000e-02 eta: 1 day, 0:45:33 time: 0.3583 data_time: 0.0205 memory: 11108 grad_norm: 2.9882 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5894 loss: 2.5894 2022/10/09 13:12:42 - mmengine - INFO - Epoch(train) [34][1700/2119] lr: 4.0000e-02 eta: 1 day, 0:45:25 time: 0.3582 data_time: 0.0220 memory: 11108 grad_norm: 3.0302 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6163 loss: 2.6163 2022/10/09 13:12:50 - mmengine - INFO - Epoch(train) [34][1720/2119] lr: 4.0000e-02 eta: 1 day, 0:45:18 time: 0.3624 data_time: 0.0225 memory: 11108 grad_norm: 2.9906 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5816 loss: 2.5816 2022/10/09 13:12:57 - mmengine - INFO - Epoch(train) [34][1740/2119] lr: 4.0000e-02 eta: 1 day, 0:45:10 time: 0.3587 data_time: 0.0159 memory: 11108 grad_norm: 2.9513 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6784 loss: 2.6784 2022/10/09 13:13:04 - mmengine - INFO - Epoch(train) [34][1760/2119] lr: 4.0000e-02 eta: 1 day, 0:45:03 time: 0.3668 data_time: 0.0192 memory: 11108 grad_norm: 2.9894 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4488 loss: 2.4488 2022/10/09 13:13:11 - mmengine - INFO - Epoch(train) [34][1780/2119] lr: 4.0000e-02 eta: 1 day, 0:44:56 time: 0.3540 data_time: 0.0200 memory: 11108 grad_norm: 2.9772 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.7037 loss: 2.7037 2022/10/09 13:13:18 - mmengine - INFO - Epoch(train) [34][1800/2119] lr: 4.0000e-02 eta: 1 day, 0:44:48 time: 0.3594 data_time: 0.0206 memory: 11108 grad_norm: 2.9475 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7194 loss: 2.7194 2022/10/09 13:13:26 - mmengine - INFO - Epoch(train) [34][1820/2119] lr: 4.0000e-02 eta: 1 day, 0:44:41 time: 0.3655 data_time: 0.0196 memory: 11108 grad_norm: 3.0514 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3763 loss: 2.3763 2022/10/09 13:13:33 - mmengine - INFO - Epoch(train) [34][1840/2119] lr: 4.0000e-02 eta: 1 day, 0:44:34 time: 0.3594 data_time: 0.0193 memory: 11108 grad_norm: 3.0077 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6183 loss: 2.6183 2022/10/09 13:13:40 - mmengine - INFO - Epoch(train) [34][1860/2119] lr: 4.0000e-02 eta: 1 day, 0:44:27 time: 0.3607 data_time: 0.0214 memory: 11108 grad_norm: 3.0540 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3857 loss: 2.3857 2022/10/09 13:13:48 - mmengine - INFO - Epoch(train) [34][1880/2119] lr: 4.0000e-02 eta: 1 day, 0:44:20 time: 0.3730 data_time: 0.0307 memory: 11108 grad_norm: 3.0102 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7443 loss: 2.7443 2022/10/09 13:13:55 - mmengine - INFO - Epoch(train) [34][1900/2119] lr: 4.0000e-02 eta: 1 day, 0:44:13 time: 0.3576 data_time: 0.0198 memory: 11108 grad_norm: 2.9762 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6039 loss: 2.6039 2022/10/09 13:14:02 - mmengine - INFO - Epoch(train) [34][1920/2119] lr: 4.0000e-02 eta: 1 day, 0:44:05 time: 0.3564 data_time: 0.0178 memory: 11108 grad_norm: 3.0123 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8246 loss: 2.8246 2022/10/09 13:14:09 - mmengine - INFO - Epoch(train) [34][1940/2119] lr: 4.0000e-02 eta: 1 day, 0:43:58 time: 0.3626 data_time: 0.0234 memory: 11108 grad_norm: 2.9961 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7125 loss: 2.7125 2022/10/09 13:14:16 - mmengine - INFO - Epoch(train) [34][1960/2119] lr: 4.0000e-02 eta: 1 day, 0:43:50 time: 0.3593 data_time: 0.0187 memory: 11108 grad_norm: 3.0263 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.7220 loss: 2.7220 2022/10/09 13:14:23 - mmengine - INFO - Epoch(train) [34][1980/2119] lr: 4.0000e-02 eta: 1 day, 0:43:43 time: 0.3567 data_time: 0.0217 memory: 11108 grad_norm: 3.0276 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6090 loss: 2.6090 2022/10/09 13:14:31 - mmengine - INFO - Epoch(train) [34][2000/2119] lr: 4.0000e-02 eta: 1 day, 0:43:36 time: 0.3642 data_time: 0.0295 memory: 11108 grad_norm: 3.0397 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5248 loss: 2.5248 2022/10/09 13:14:38 - mmengine - INFO - Epoch(train) [34][2020/2119] lr: 4.0000e-02 eta: 1 day, 0:43:28 time: 0.3568 data_time: 0.0220 memory: 11108 grad_norm: 2.9636 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5804 loss: 2.5804 2022/10/09 13:14:45 - mmengine - INFO - Epoch(train) [34][2040/2119] lr: 4.0000e-02 eta: 1 day, 0:43:21 time: 0.3720 data_time: 0.0204 memory: 11108 grad_norm: 3.0445 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6362 loss: 2.6362 2022/10/09 13:14:52 - mmengine - INFO - Epoch(train) [34][2060/2119] lr: 4.0000e-02 eta: 1 day, 0:43:14 time: 0.3541 data_time: 0.0174 memory: 11108 grad_norm: 2.9760 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7520 loss: 2.7520 2022/10/09 13:14:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 13:15:00 - mmengine - INFO - Epoch(train) [34][2080/2119] lr: 4.0000e-02 eta: 1 day, 0:43:06 time: 0.3589 data_time: 0.0210 memory: 11108 grad_norm: 2.9752 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6246 loss: 2.6246 2022/10/09 13:15:07 - mmengine - INFO - Epoch(train) [34][2100/2119] lr: 4.0000e-02 eta: 1 day, 0:42:59 time: 0.3604 data_time: 0.0187 memory: 11108 grad_norm: 2.9390 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5135 loss: 2.5135 2022/10/09 13:15:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 13:15:13 - mmengine - INFO - Epoch(train) [34][2119/2119] lr: 4.0000e-02 eta: 1 day, 0:42:59 time: 0.3517 data_time: 0.0186 memory: 11108 grad_norm: 3.0191 top1_acc: 0.1000 top5_acc: 0.5000 loss_cls: 2.7315 loss: 2.7315 2022/10/09 13:15:24 - mmengine - INFO - Epoch(train) [35][20/2119] lr: 4.0000e-02 eta: 1 day, 0:42:33 time: 0.5280 data_time: 0.1566 memory: 11108 grad_norm: 2.9586 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7368 loss: 2.7368 2022/10/09 13:15:31 - mmengine - INFO - Epoch(train) [35][40/2119] lr: 4.0000e-02 eta: 1 day, 0:42:26 time: 0.3672 data_time: 0.0192 memory: 11108 grad_norm: 3.0126 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7648 loss: 2.7648 2022/10/09 13:15:39 - mmengine - INFO - Epoch(train) [35][60/2119] lr: 4.0000e-02 eta: 1 day, 0:42:19 time: 0.3674 data_time: 0.0215 memory: 11108 grad_norm: 3.0535 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5905 loss: 2.5905 2022/10/09 13:15:46 - mmengine - INFO - Epoch(train) [35][80/2119] lr: 4.0000e-02 eta: 1 day, 0:42:12 time: 0.3608 data_time: 0.0191 memory: 11108 grad_norm: 2.9738 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5991 loss: 2.5991 2022/10/09 13:15:53 - mmengine - INFO - Epoch(train) [35][100/2119] lr: 4.0000e-02 eta: 1 day, 0:42:04 time: 0.3589 data_time: 0.0220 memory: 11108 grad_norm: 2.9382 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5613 loss: 2.5613 2022/10/09 13:16:00 - mmengine - INFO - Epoch(train) [35][120/2119] lr: 4.0000e-02 eta: 1 day, 0:41:57 time: 0.3655 data_time: 0.0209 memory: 11108 grad_norm: 3.0507 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5374 loss: 2.5374 2022/10/09 13:16:08 - mmengine - INFO - Epoch(train) [35][140/2119] lr: 4.0000e-02 eta: 1 day, 0:41:49 time: 0.3556 data_time: 0.0174 memory: 11108 grad_norm: 2.9783 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5449 loss: 2.5449 2022/10/09 13:16:15 - mmengine - INFO - Epoch(train) [35][160/2119] lr: 4.0000e-02 eta: 1 day, 0:41:42 time: 0.3612 data_time: 0.0228 memory: 11108 grad_norm: 3.0080 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4349 loss: 2.4349 2022/10/09 13:16:22 - mmengine - INFO - Epoch(train) [35][180/2119] lr: 4.0000e-02 eta: 1 day, 0:41:35 time: 0.3594 data_time: 0.0207 memory: 11108 grad_norm: 3.0241 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6172 loss: 2.6172 2022/10/09 13:16:29 - mmengine - INFO - Epoch(train) [35][200/2119] lr: 4.0000e-02 eta: 1 day, 0:41:27 time: 0.3561 data_time: 0.0205 memory: 11108 grad_norm: 3.0156 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.3736 loss: 2.3736 2022/10/09 13:16:36 - mmengine - INFO - Epoch(train) [35][220/2119] lr: 4.0000e-02 eta: 1 day, 0:41:20 time: 0.3644 data_time: 0.0244 memory: 11108 grad_norm: 2.9992 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.5782 loss: 2.5782 2022/10/09 13:16:44 - mmengine - INFO - Epoch(train) [35][240/2119] lr: 4.0000e-02 eta: 1 day, 0:41:12 time: 0.3571 data_time: 0.0213 memory: 11108 grad_norm: 2.9695 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5980 loss: 2.5980 2022/10/09 13:16:51 - mmengine - INFO - Epoch(train) [35][260/2119] lr: 4.0000e-02 eta: 1 day, 0:41:05 time: 0.3589 data_time: 0.0203 memory: 11108 grad_norm: 3.0427 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8833 loss: 2.8833 2022/10/09 13:16:58 - mmengine - INFO - Epoch(train) [35][280/2119] lr: 4.0000e-02 eta: 1 day, 0:40:58 time: 0.3606 data_time: 0.0242 memory: 11108 grad_norm: 3.0061 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6411 loss: 2.6411 2022/10/09 13:17:05 - mmengine - INFO - Epoch(train) [35][300/2119] lr: 4.0000e-02 eta: 1 day, 0:40:50 time: 0.3561 data_time: 0.0181 memory: 11108 grad_norm: 3.0472 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6606 loss: 2.6606 2022/10/09 13:17:12 - mmengine - INFO - Epoch(train) [35][320/2119] lr: 4.0000e-02 eta: 1 day, 0:40:43 time: 0.3653 data_time: 0.0205 memory: 11108 grad_norm: 2.9486 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.5750 loss: 2.5750 2022/10/09 13:17:20 - mmengine - INFO - Epoch(train) [35][340/2119] lr: 4.0000e-02 eta: 1 day, 0:40:36 time: 0.3610 data_time: 0.0212 memory: 11108 grad_norm: 2.9482 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7146 loss: 2.7146 2022/10/09 13:17:27 - mmengine - INFO - Epoch(train) [35][360/2119] lr: 4.0000e-02 eta: 1 day, 0:40:28 time: 0.3597 data_time: 0.0206 memory: 11108 grad_norm: 2.9837 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7515 loss: 2.7515 2022/10/09 13:17:34 - mmengine - INFO - Epoch(train) [35][380/2119] lr: 4.0000e-02 eta: 1 day, 0:40:21 time: 0.3652 data_time: 0.0202 memory: 11108 grad_norm: 3.0421 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6295 loss: 2.6295 2022/10/09 13:17:41 - mmengine - INFO - Epoch(train) [35][400/2119] lr: 4.0000e-02 eta: 1 day, 0:40:14 time: 0.3549 data_time: 0.0199 memory: 11108 grad_norm: 3.0216 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5323 loss: 2.5323 2022/10/09 13:17:49 - mmengine - INFO - Epoch(train) [35][420/2119] lr: 4.0000e-02 eta: 1 day, 0:40:07 time: 0.3648 data_time: 0.0173 memory: 11108 grad_norm: 3.0062 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7072 loss: 2.7072 2022/10/09 13:17:56 - mmengine - INFO - Epoch(train) [35][440/2119] lr: 4.0000e-02 eta: 1 day, 0:39:59 time: 0.3585 data_time: 0.0230 memory: 11108 grad_norm: 2.9533 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8231 loss: 2.8231 2022/10/09 13:18:03 - mmengine - INFO - Epoch(train) [35][460/2119] lr: 4.0000e-02 eta: 1 day, 0:39:51 time: 0.3541 data_time: 0.0196 memory: 11108 grad_norm: 2.9590 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5756 loss: 2.5756 2022/10/09 13:18:10 - mmengine - INFO - Epoch(train) [35][480/2119] lr: 4.0000e-02 eta: 1 day, 0:39:44 time: 0.3657 data_time: 0.0298 memory: 11108 grad_norm: 2.9868 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6814 loss: 2.6814 2022/10/09 13:18:17 - mmengine - INFO - Epoch(train) [35][500/2119] lr: 4.0000e-02 eta: 1 day, 0:39:37 time: 0.3570 data_time: 0.0175 memory: 11108 grad_norm: 2.9886 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5549 loss: 2.5549 2022/10/09 13:18:24 - mmengine - INFO - Epoch(train) [35][520/2119] lr: 4.0000e-02 eta: 1 day, 0:39:30 time: 0.3606 data_time: 0.0198 memory: 11108 grad_norm: 2.9990 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4982 loss: 2.4982 2022/10/09 13:18:32 - mmengine - INFO - Epoch(train) [35][540/2119] lr: 4.0000e-02 eta: 1 day, 0:39:22 time: 0.3568 data_time: 0.0217 memory: 11108 grad_norm: 3.0673 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7309 loss: 2.7309 2022/10/09 13:18:39 - mmengine - INFO - Epoch(train) [35][560/2119] lr: 4.0000e-02 eta: 1 day, 0:39:15 time: 0.3621 data_time: 0.0220 memory: 11108 grad_norm: 2.9820 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6925 loss: 2.6925 2022/10/09 13:18:47 - mmengine - INFO - Epoch(train) [35][580/2119] lr: 4.0000e-02 eta: 1 day, 0:39:11 time: 0.4088 data_time: 0.0327 memory: 11108 grad_norm: 3.0464 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6805 loss: 2.6805 2022/10/09 13:18:59 - mmengine - INFO - Epoch(train) [35][600/2119] lr: 4.0000e-02 eta: 1 day, 0:39:20 time: 0.6118 data_time: 0.0350 memory: 11108 grad_norm: 3.0194 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6646 loss: 2.6646 2022/10/09 13:19:08 - mmengine - INFO - Epoch(train) [35][620/2119] lr: 4.0000e-02 eta: 1 day, 0:39:18 time: 0.4332 data_time: 0.0217 memory: 11108 grad_norm: 3.0342 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5336 loss: 2.5336 2022/10/09 13:19:15 - mmengine - INFO - Epoch(train) [35][640/2119] lr: 4.0000e-02 eta: 1 day, 0:39:11 time: 0.3613 data_time: 0.0168 memory: 11108 grad_norm: 2.9936 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5043 loss: 2.5043 2022/10/09 13:19:22 - mmengine - INFO - Epoch(train) [35][660/2119] lr: 4.0000e-02 eta: 1 day, 0:39:03 time: 0.3578 data_time: 0.0259 memory: 11108 grad_norm: 3.0196 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7060 loss: 2.7060 2022/10/09 13:19:29 - mmengine - INFO - Epoch(train) [35][680/2119] lr: 4.0000e-02 eta: 1 day, 0:38:56 time: 0.3598 data_time: 0.0189 memory: 11108 grad_norm: 3.0599 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5542 loss: 2.5542 2022/10/09 13:19:37 - mmengine - INFO - Epoch(train) [35][700/2119] lr: 4.0000e-02 eta: 1 day, 0:38:48 time: 0.3621 data_time: 0.0209 memory: 11108 grad_norm: 2.9714 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6121 loss: 2.6121 2022/10/09 13:19:44 - mmengine - INFO - Epoch(train) [35][720/2119] lr: 4.0000e-02 eta: 1 day, 0:38:41 time: 0.3624 data_time: 0.0198 memory: 11108 grad_norm: 3.0410 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7744 loss: 2.7744 2022/10/09 13:19:51 - mmengine - INFO - Epoch(train) [35][740/2119] lr: 4.0000e-02 eta: 1 day, 0:38:34 time: 0.3575 data_time: 0.0204 memory: 11108 grad_norm: 2.9755 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4305 loss: 2.4305 2022/10/09 13:19:58 - mmengine - INFO - Epoch(train) [35][760/2119] lr: 4.0000e-02 eta: 1 day, 0:38:26 time: 0.3577 data_time: 0.0188 memory: 11108 grad_norm: 3.0510 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8620 loss: 2.8620 2022/10/09 13:20:05 - mmengine - INFO - Epoch(train) [35][780/2119] lr: 4.0000e-02 eta: 1 day, 0:38:19 time: 0.3576 data_time: 0.0222 memory: 11108 grad_norm: 2.9484 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6180 loss: 2.6180 2022/10/09 13:20:13 - mmengine - INFO - Epoch(train) [35][800/2119] lr: 4.0000e-02 eta: 1 day, 0:38:11 time: 0.3588 data_time: 0.0192 memory: 11108 grad_norm: 3.0175 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6007 loss: 2.6007 2022/10/09 13:20:20 - mmengine - INFO - Epoch(train) [35][820/2119] lr: 4.0000e-02 eta: 1 day, 0:38:04 time: 0.3628 data_time: 0.0230 memory: 11108 grad_norm: 3.0316 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.5318 loss: 2.5318 2022/10/09 13:20:27 - mmengine - INFO - Epoch(train) [35][840/2119] lr: 4.0000e-02 eta: 1 day, 0:37:56 time: 0.3571 data_time: 0.0225 memory: 11108 grad_norm: 3.0396 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.4754 loss: 2.4754 2022/10/09 13:20:34 - mmengine - INFO - Epoch(train) [35][860/2119] lr: 4.0000e-02 eta: 1 day, 0:37:49 time: 0.3622 data_time: 0.0190 memory: 11108 grad_norm: 2.9966 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6137 loss: 2.6137 2022/10/09 13:20:41 - mmengine - INFO - Epoch(train) [35][880/2119] lr: 4.0000e-02 eta: 1 day, 0:37:42 time: 0.3602 data_time: 0.0198 memory: 11108 grad_norm: 2.9943 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6299 loss: 2.6299 2022/10/09 13:20:49 - mmengine - INFO - Epoch(train) [35][900/2119] lr: 4.0000e-02 eta: 1 day, 0:37:34 time: 0.3584 data_time: 0.0207 memory: 11108 grad_norm: 2.9758 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.5636 loss: 2.5636 2022/10/09 13:20:56 - mmengine - INFO - Epoch(train) [35][920/2119] lr: 4.0000e-02 eta: 1 day, 0:37:27 time: 0.3638 data_time: 0.0233 memory: 11108 grad_norm: 3.0274 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4750 loss: 2.4750 2022/10/09 13:21:03 - mmengine - INFO - Epoch(train) [35][940/2119] lr: 4.0000e-02 eta: 1 day, 0:37:20 time: 0.3579 data_time: 0.0175 memory: 11108 grad_norm: 3.0303 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5380 loss: 2.5380 2022/10/09 13:21:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 13:21:10 - mmengine - INFO - Epoch(train) [35][960/2119] lr: 4.0000e-02 eta: 1 day, 0:37:12 time: 0.3593 data_time: 0.0173 memory: 11108 grad_norm: 3.0628 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6665 loss: 2.6665 2022/10/09 13:21:18 - mmengine - INFO - Epoch(train) [35][980/2119] lr: 4.0000e-02 eta: 1 day, 0:37:05 time: 0.3615 data_time: 0.0226 memory: 11108 grad_norm: 3.0025 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6073 loss: 2.6073 2022/10/09 13:21:25 - mmengine - INFO - Epoch(train) [35][1000/2119] lr: 4.0000e-02 eta: 1 day, 0:36:58 time: 0.3649 data_time: 0.0235 memory: 11108 grad_norm: 2.9418 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.7037 loss: 2.7037 2022/10/09 13:21:32 - mmengine - INFO - Epoch(train) [35][1020/2119] lr: 4.0000e-02 eta: 1 day, 0:36:50 time: 0.3550 data_time: 0.0191 memory: 11108 grad_norm: 2.9522 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5012 loss: 2.5012 2022/10/09 13:21:39 - mmengine - INFO - Epoch(train) [35][1040/2119] lr: 4.0000e-02 eta: 1 day, 0:36:43 time: 0.3624 data_time: 0.0210 memory: 11108 grad_norm: 2.9966 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5092 loss: 2.5092 2022/10/09 13:21:46 - mmengine - INFO - Epoch(train) [35][1060/2119] lr: 4.0000e-02 eta: 1 day, 0:36:35 time: 0.3568 data_time: 0.0213 memory: 11108 grad_norm: 2.9427 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7835 loss: 2.7835 2022/10/09 13:21:54 - mmengine - INFO - Epoch(train) [35][1080/2119] lr: 4.0000e-02 eta: 1 day, 0:36:28 time: 0.3611 data_time: 0.0181 memory: 11108 grad_norm: 3.0038 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6524 loss: 2.6524 2022/10/09 13:22:01 - mmengine - INFO - Epoch(train) [35][1100/2119] lr: 4.0000e-02 eta: 1 day, 0:36:21 time: 0.3583 data_time: 0.0204 memory: 11108 grad_norm: 2.9642 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6481 loss: 2.6481 2022/10/09 13:22:08 - mmengine - INFO - Epoch(train) [35][1120/2119] lr: 4.0000e-02 eta: 1 day, 0:36:13 time: 0.3598 data_time: 0.0205 memory: 11108 grad_norm: 2.9559 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6933 loss: 2.6933 2022/10/09 13:22:15 - mmengine - INFO - Epoch(train) [35][1140/2119] lr: 4.0000e-02 eta: 1 day, 0:36:06 time: 0.3636 data_time: 0.0282 memory: 11108 grad_norm: 3.0167 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7962 loss: 2.7962 2022/10/09 13:22:22 - mmengine - INFO - Epoch(train) [35][1160/2119] lr: 4.0000e-02 eta: 1 day, 0:35:58 time: 0.3533 data_time: 0.0203 memory: 11108 grad_norm: 3.0085 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5320 loss: 2.5320 2022/10/09 13:22:29 - mmengine - INFO - Epoch(train) [35][1180/2119] lr: 4.0000e-02 eta: 1 day, 0:35:51 time: 0.3559 data_time: 0.0236 memory: 11108 grad_norm: 3.0271 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6190 loss: 2.6190 2022/10/09 13:22:37 - mmengine - INFO - Epoch(train) [35][1200/2119] lr: 4.0000e-02 eta: 1 day, 0:35:43 time: 0.3602 data_time: 0.0201 memory: 11108 grad_norm: 2.9877 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.6975 loss: 2.6975 2022/10/09 13:22:44 - mmengine - INFO - Epoch(train) [35][1220/2119] lr: 4.0000e-02 eta: 1 day, 0:35:36 time: 0.3592 data_time: 0.0190 memory: 11108 grad_norm: 3.0258 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9667 loss: 2.9667 2022/10/09 13:22:51 - mmengine - INFO - Epoch(train) [35][1240/2119] lr: 4.0000e-02 eta: 1 day, 0:35:28 time: 0.3564 data_time: 0.0211 memory: 11108 grad_norm: 3.0182 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7654 loss: 2.7654 2022/10/09 13:22:58 - mmengine - INFO - Epoch(train) [35][1260/2119] lr: 4.0000e-02 eta: 1 day, 0:35:21 time: 0.3605 data_time: 0.0183 memory: 11108 grad_norm: 2.9468 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3436 loss: 2.3436 2022/10/09 13:23:05 - mmengine - INFO - Epoch(train) [35][1280/2119] lr: 4.0000e-02 eta: 1 day, 0:35:13 time: 0.3560 data_time: 0.0187 memory: 11108 grad_norm: 2.9627 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5681 loss: 2.5681 2022/10/09 13:23:12 - mmengine - INFO - Epoch(train) [35][1300/2119] lr: 4.0000e-02 eta: 1 day, 0:35:06 time: 0.3575 data_time: 0.0209 memory: 11108 grad_norm: 2.9981 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3655 loss: 2.3655 2022/10/09 13:23:20 - mmengine - INFO - Epoch(train) [35][1320/2119] lr: 4.0000e-02 eta: 1 day, 0:34:59 time: 0.3626 data_time: 0.0181 memory: 11108 grad_norm: 2.9651 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7821 loss: 2.7821 2022/10/09 13:23:27 - mmengine - INFO - Epoch(train) [35][1340/2119] lr: 4.0000e-02 eta: 1 day, 0:34:51 time: 0.3644 data_time: 0.0216 memory: 11108 grad_norm: 2.9932 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5038 loss: 2.5038 2022/10/09 13:23:34 - mmengine - INFO - Epoch(train) [35][1360/2119] lr: 4.0000e-02 eta: 1 day, 0:34:44 time: 0.3542 data_time: 0.0181 memory: 11108 grad_norm: 2.9863 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5806 loss: 2.5806 2022/10/09 13:23:41 - mmengine - INFO - Epoch(train) [35][1380/2119] lr: 4.0000e-02 eta: 1 day, 0:34:36 time: 0.3594 data_time: 0.0205 memory: 11108 grad_norm: 2.9954 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3108 loss: 2.3108 2022/10/09 13:23:48 - mmengine - INFO - Epoch(train) [35][1400/2119] lr: 4.0000e-02 eta: 1 day, 0:34:29 time: 0.3597 data_time: 0.0198 memory: 11108 grad_norm: 3.0069 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5888 loss: 2.5888 2022/10/09 13:23:56 - mmengine - INFO - Epoch(train) [35][1420/2119] lr: 4.0000e-02 eta: 1 day, 0:34:22 time: 0.3684 data_time: 0.0229 memory: 11108 grad_norm: 2.9420 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7946 loss: 2.7946 2022/10/09 13:24:03 - mmengine - INFO - Epoch(train) [35][1440/2119] lr: 4.0000e-02 eta: 1 day, 0:34:14 time: 0.3547 data_time: 0.0196 memory: 11108 grad_norm: 2.9457 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5708 loss: 2.5708 2022/10/09 13:24:10 - mmengine - INFO - Epoch(train) [35][1460/2119] lr: 4.0000e-02 eta: 1 day, 0:34:07 time: 0.3602 data_time: 0.0184 memory: 11108 grad_norm: 2.9884 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5146 loss: 2.5146 2022/10/09 13:24:17 - mmengine - INFO - Epoch(train) [35][1480/2119] lr: 4.0000e-02 eta: 1 day, 0:33:59 time: 0.3562 data_time: 0.0182 memory: 11108 grad_norm: 2.9705 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5492 loss: 2.5492 2022/10/09 13:24:24 - mmengine - INFO - Epoch(train) [35][1500/2119] lr: 4.0000e-02 eta: 1 day, 0:33:52 time: 0.3615 data_time: 0.0220 memory: 11108 grad_norm: 3.0246 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7306 loss: 2.7306 2022/10/09 13:24:32 - mmengine - INFO - Epoch(train) [35][1520/2119] lr: 4.0000e-02 eta: 1 day, 0:33:45 time: 0.3584 data_time: 0.0181 memory: 11108 grad_norm: 3.0753 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9236 loss: 2.9236 2022/10/09 13:24:39 - mmengine - INFO - Epoch(train) [35][1540/2119] lr: 4.0000e-02 eta: 1 day, 0:33:37 time: 0.3585 data_time: 0.0238 memory: 11108 grad_norm: 3.0142 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6951 loss: 2.6951 2022/10/09 13:24:46 - mmengine - INFO - Epoch(train) [35][1560/2119] lr: 4.0000e-02 eta: 1 day, 0:33:29 time: 0.3560 data_time: 0.0206 memory: 11108 grad_norm: 3.0488 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6665 loss: 2.6665 2022/10/09 13:24:53 - mmengine - INFO - Epoch(train) [35][1580/2119] lr: 4.0000e-02 eta: 1 day, 0:33:22 time: 0.3613 data_time: 0.0219 memory: 11108 grad_norm: 3.0337 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7713 loss: 2.7713 2022/10/09 13:25:00 - mmengine - INFO - Epoch(train) [35][1600/2119] lr: 4.0000e-02 eta: 1 day, 0:33:15 time: 0.3589 data_time: 0.0168 memory: 11108 grad_norm: 3.0199 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8500 loss: 2.8500 2022/10/09 13:25:08 - mmengine - INFO - Epoch(train) [35][1620/2119] lr: 4.0000e-02 eta: 1 day, 0:33:08 time: 0.3701 data_time: 0.0269 memory: 11108 grad_norm: 3.0386 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6878 loss: 2.6878 2022/10/09 13:25:15 - mmengine - INFO - Epoch(train) [35][1640/2119] lr: 4.0000e-02 eta: 1 day, 0:33:00 time: 0.3562 data_time: 0.0179 memory: 11108 grad_norm: 3.0325 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7266 loss: 2.7266 2022/10/09 13:25:22 - mmengine - INFO - Epoch(train) [35][1660/2119] lr: 4.0000e-02 eta: 1 day, 0:32:53 time: 0.3602 data_time: 0.0196 memory: 11108 grad_norm: 2.9342 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.4731 loss: 2.4731 2022/10/09 13:25:29 - mmengine - INFO - Epoch(train) [35][1680/2119] lr: 4.0000e-02 eta: 1 day, 0:32:46 time: 0.3577 data_time: 0.0187 memory: 11108 grad_norm: 2.9766 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6818 loss: 2.6818 2022/10/09 13:25:36 - mmengine - INFO - Epoch(train) [35][1700/2119] lr: 4.0000e-02 eta: 1 day, 0:32:38 time: 0.3563 data_time: 0.0208 memory: 11108 grad_norm: 3.0577 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7305 loss: 2.7305 2022/10/09 13:25:43 - mmengine - INFO - Epoch(train) [35][1720/2119] lr: 4.0000e-02 eta: 1 day, 0:32:30 time: 0.3545 data_time: 0.0184 memory: 11108 grad_norm: 3.0021 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6916 loss: 2.6916 2022/10/09 13:25:51 - mmengine - INFO - Epoch(train) [35][1740/2119] lr: 4.0000e-02 eta: 1 day, 0:32:23 time: 0.3608 data_time: 0.0216 memory: 11108 grad_norm: 2.9788 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8653 loss: 2.8653 2022/10/09 13:25:58 - mmengine - INFO - Epoch(train) [35][1760/2119] lr: 4.0000e-02 eta: 1 day, 0:32:15 time: 0.3576 data_time: 0.0205 memory: 11108 grad_norm: 3.0317 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9077 loss: 2.9077 2022/10/09 13:26:05 - mmengine - INFO - Epoch(train) [35][1780/2119] lr: 4.0000e-02 eta: 1 day, 0:32:08 time: 0.3650 data_time: 0.0200 memory: 11108 grad_norm: 2.9467 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7522 loss: 2.7522 2022/10/09 13:26:12 - mmengine - INFO - Epoch(train) [35][1800/2119] lr: 4.0000e-02 eta: 1 day, 0:32:00 time: 0.3522 data_time: 0.0196 memory: 11108 grad_norm: 2.9499 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5696 loss: 2.5696 2022/10/09 13:26:19 - mmengine - INFO - Epoch(train) [35][1820/2119] lr: 4.0000e-02 eta: 1 day, 0:31:53 time: 0.3589 data_time: 0.0201 memory: 11108 grad_norm: 2.9827 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7386 loss: 2.7386 2022/10/09 13:26:26 - mmengine - INFO - Epoch(train) [35][1840/2119] lr: 4.0000e-02 eta: 1 day, 0:31:46 time: 0.3599 data_time: 0.0194 memory: 11108 grad_norm: 2.9931 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.6874 loss: 2.6874 2022/10/09 13:26:34 - mmengine - INFO - Epoch(train) [35][1860/2119] lr: 4.0000e-02 eta: 1 day, 0:31:38 time: 0.3564 data_time: 0.0215 memory: 11108 grad_norm: 2.9864 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6562 loss: 2.6562 2022/10/09 13:26:41 - mmengine - INFO - Epoch(train) [35][1880/2119] lr: 4.0000e-02 eta: 1 day, 0:31:31 time: 0.3596 data_time: 0.0180 memory: 11108 grad_norm: 2.9616 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.4330 loss: 2.4330 2022/10/09 13:26:48 - mmengine - INFO - Epoch(train) [35][1900/2119] lr: 4.0000e-02 eta: 1 day, 0:31:24 time: 0.3735 data_time: 0.0227 memory: 11108 grad_norm: 3.0208 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6607 loss: 2.6607 2022/10/09 13:26:55 - mmengine - INFO - Epoch(train) [35][1920/2119] lr: 4.0000e-02 eta: 1 day, 0:31:17 time: 0.3567 data_time: 0.0177 memory: 11108 grad_norm: 2.9842 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5193 loss: 2.5193 2022/10/09 13:27:03 - mmengine - INFO - Epoch(train) [35][1940/2119] lr: 4.0000e-02 eta: 1 day, 0:31:09 time: 0.3582 data_time: 0.0199 memory: 11108 grad_norm: 2.9715 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8913 loss: 2.8913 2022/10/09 13:27:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 13:27:10 - mmengine - INFO - Epoch(train) [35][1960/2119] lr: 4.0000e-02 eta: 1 day, 0:31:02 time: 0.3677 data_time: 0.0190 memory: 11108 grad_norm: 2.9789 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7906 loss: 2.7906 2022/10/09 13:27:17 - mmengine - INFO - Epoch(train) [35][1980/2119] lr: 4.0000e-02 eta: 1 day, 0:30:55 time: 0.3559 data_time: 0.0211 memory: 11108 grad_norm: 3.0197 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7148 loss: 2.7148 2022/10/09 13:27:24 - mmengine - INFO - Epoch(train) [35][2000/2119] lr: 4.0000e-02 eta: 1 day, 0:30:47 time: 0.3629 data_time: 0.0206 memory: 11108 grad_norm: 2.9457 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8243 loss: 2.8243 2022/10/09 13:27:31 - mmengine - INFO - Epoch(train) [35][2020/2119] lr: 4.0000e-02 eta: 1 day, 0:30:40 time: 0.3560 data_time: 0.0186 memory: 11108 grad_norm: 2.9507 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5851 loss: 2.5851 2022/10/09 13:27:39 - mmengine - INFO - Epoch(train) [35][2040/2119] lr: 4.0000e-02 eta: 1 day, 0:30:32 time: 0.3549 data_time: 0.0198 memory: 11108 grad_norm: 2.9862 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6789 loss: 2.6789 2022/10/09 13:27:48 - mmengine - INFO - Epoch(train) [35][2060/2119] lr: 4.0000e-02 eta: 1 day, 0:30:31 time: 0.4594 data_time: 0.0185 memory: 11108 grad_norm: 3.0086 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7623 loss: 2.7623 2022/10/09 13:27:56 - mmengine - INFO - Epoch(train) [35][2080/2119] lr: 4.0000e-02 eta: 1 day, 0:30:28 time: 0.4157 data_time: 0.0416 memory: 11108 grad_norm: 2.9719 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7412 loss: 2.7412 2022/10/09 13:28:05 - mmengine - INFO - Epoch(train) [35][2100/2119] lr: 4.0000e-02 eta: 1 day, 0:30:27 time: 0.4660 data_time: 0.0423 memory: 11108 grad_norm: 2.9955 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7029 loss: 2.7029 2022/10/09 13:28:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 13:28:12 - mmengine - INFO - Epoch(train) [35][2119/2119] lr: 4.0000e-02 eta: 1 day, 0:30:27 time: 0.3424 data_time: 0.0197 memory: 11108 grad_norm: 3.0352 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 2.6775 loss: 2.6775 2022/10/09 13:28:19 - mmengine - INFO - Epoch(val) [35][20/137] eta: 0:00:41 time: 0.3524 data_time: 0.2334 memory: 1961 2022/10/09 13:28:24 - mmengine - INFO - Epoch(val) [35][40/137] eta: 0:00:24 time: 0.2562 data_time: 0.1391 memory: 1961 2022/10/09 13:28:30 - mmengine - INFO - Epoch(val) [35][60/137] eta: 0:00:23 time: 0.2999 data_time: 0.1846 memory: 1961 2022/10/09 13:28:35 - mmengine - INFO - Epoch(val) [35][80/137] eta: 0:00:14 time: 0.2459 data_time: 0.1310 memory: 1961 2022/10/09 13:28:41 - mmengine - INFO - Epoch(val) [35][100/137] eta: 0:00:10 time: 0.2725 data_time: 0.1574 memory: 1961 2022/10/09 13:28:45 - mmengine - INFO - Epoch(val) [35][120/137] eta: 0:00:03 time: 0.2244 data_time: 0.1108 memory: 1961 2022/10/09 13:29:01 - mmengine - INFO - Epoch(val) [35][137/137] acc/top1: 0.4425 acc/top5: 0.6892 acc/mean1: 0.4424 2022/10/09 13:29:11 - mmengine - INFO - Epoch(train) [36][20/2119] lr: 4.0000e-02 eta: 1 day, 0:30:00 time: 0.5060 data_time: 0.1417 memory: 11108 grad_norm: 2.9674 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5951 loss: 2.5951 2022/10/09 13:29:18 - mmengine - INFO - Epoch(train) [36][40/2119] lr: 4.0000e-02 eta: 1 day, 0:29:53 time: 0.3669 data_time: 0.0319 memory: 11108 grad_norm: 2.9660 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.4504 loss: 2.4504 2022/10/09 13:29:26 - mmengine - INFO - Epoch(train) [36][60/2119] lr: 4.0000e-02 eta: 1 day, 0:29:45 time: 0.3585 data_time: 0.0187 memory: 11108 grad_norm: 3.0043 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4718 loss: 2.4718 2022/10/09 13:29:33 - mmengine - INFO - Epoch(train) [36][80/2119] lr: 4.0000e-02 eta: 1 day, 0:29:38 time: 0.3550 data_time: 0.0210 memory: 11108 grad_norm: 3.0457 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4512 loss: 2.4512 2022/10/09 13:29:40 - mmengine - INFO - Epoch(train) [36][100/2119] lr: 4.0000e-02 eta: 1 day, 0:29:31 time: 0.3656 data_time: 0.0226 memory: 11108 grad_norm: 2.9947 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7000 loss: 2.7000 2022/10/09 13:29:47 - mmengine - INFO - Epoch(train) [36][120/2119] lr: 4.0000e-02 eta: 1 day, 0:29:23 time: 0.3606 data_time: 0.0259 memory: 11108 grad_norm: 2.9414 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6690 loss: 2.6690 2022/10/09 13:29:54 - mmengine - INFO - Epoch(train) [36][140/2119] lr: 4.0000e-02 eta: 1 day, 0:29:16 time: 0.3599 data_time: 0.0191 memory: 11108 grad_norm: 3.0240 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6204 loss: 2.6204 2022/10/09 13:30:02 - mmengine - INFO - Epoch(train) [36][160/2119] lr: 4.0000e-02 eta: 1 day, 0:29:09 time: 0.3577 data_time: 0.0202 memory: 11108 grad_norm: 3.0376 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5034 loss: 2.5034 2022/10/09 13:30:09 - mmengine - INFO - Epoch(train) [36][180/2119] lr: 4.0000e-02 eta: 1 day, 0:29:01 time: 0.3629 data_time: 0.0253 memory: 11108 grad_norm: 2.9658 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5090 loss: 2.5090 2022/10/09 13:30:16 - mmengine - INFO - Epoch(train) [36][200/2119] lr: 4.0000e-02 eta: 1 day, 0:28:54 time: 0.3625 data_time: 0.0190 memory: 11108 grad_norm: 2.9429 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5292 loss: 2.5292 2022/10/09 13:30:23 - mmengine - INFO - Epoch(train) [36][220/2119] lr: 4.0000e-02 eta: 1 day, 0:28:47 time: 0.3579 data_time: 0.0182 memory: 11108 grad_norm: 3.0191 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4530 loss: 2.4530 2022/10/09 13:30:30 - mmengine - INFO - Epoch(train) [36][240/2119] lr: 4.0000e-02 eta: 1 day, 0:28:39 time: 0.3570 data_time: 0.0182 memory: 11108 grad_norm: 3.0112 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6965 loss: 2.6965 2022/10/09 13:30:38 - mmengine - INFO - Epoch(train) [36][260/2119] lr: 4.0000e-02 eta: 1 day, 0:28:33 time: 0.3720 data_time: 0.0226 memory: 11108 grad_norm: 2.9892 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8648 loss: 2.8648 2022/10/09 13:30:45 - mmengine - INFO - Epoch(train) [36][280/2119] lr: 4.0000e-02 eta: 1 day, 0:28:25 time: 0.3571 data_time: 0.0220 memory: 11108 grad_norm: 3.0052 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6251 loss: 2.6251 2022/10/09 13:30:52 - mmengine - INFO - Epoch(train) [36][300/2119] lr: 4.0000e-02 eta: 1 day, 0:28:17 time: 0.3574 data_time: 0.0199 memory: 11108 grad_norm: 2.9659 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5906 loss: 2.5906 2022/10/09 13:30:59 - mmengine - INFO - Epoch(train) [36][320/2119] lr: 4.0000e-02 eta: 1 day, 0:28:10 time: 0.3613 data_time: 0.0201 memory: 11108 grad_norm: 3.0311 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6514 loss: 2.6514 2022/10/09 13:31:06 - mmengine - INFO - Epoch(train) [36][340/2119] lr: 4.0000e-02 eta: 1 day, 0:28:03 time: 0.3558 data_time: 0.0200 memory: 11108 grad_norm: 3.0119 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6997 loss: 2.6997 2022/10/09 13:31:14 - mmengine - INFO - Epoch(train) [36][360/2119] lr: 4.0000e-02 eta: 1 day, 0:27:55 time: 0.3600 data_time: 0.0194 memory: 11108 grad_norm: 3.0338 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7102 loss: 2.7102 2022/10/09 13:31:21 - mmengine - INFO - Epoch(train) [36][380/2119] lr: 4.0000e-02 eta: 1 day, 0:27:48 time: 0.3595 data_time: 0.0220 memory: 11108 grad_norm: 2.9772 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6725 loss: 2.6725 2022/10/09 13:31:28 - mmengine - INFO - Epoch(train) [36][400/2119] lr: 4.0000e-02 eta: 1 day, 0:27:41 time: 0.3622 data_time: 0.0228 memory: 11108 grad_norm: 2.9659 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.6381 loss: 2.6381 2022/10/09 13:31:35 - mmengine - INFO - Epoch(train) [36][420/2119] lr: 4.0000e-02 eta: 1 day, 0:27:33 time: 0.3576 data_time: 0.0196 memory: 11108 grad_norm: 2.9632 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5714 loss: 2.5714 2022/10/09 13:31:42 - mmengine - INFO - Epoch(train) [36][440/2119] lr: 4.0000e-02 eta: 1 day, 0:27:26 time: 0.3587 data_time: 0.0234 memory: 11108 grad_norm: 3.0370 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4852 loss: 2.4852 2022/10/09 13:31:50 - mmengine - INFO - Epoch(train) [36][460/2119] lr: 4.0000e-02 eta: 1 day, 0:27:18 time: 0.3559 data_time: 0.0212 memory: 11108 grad_norm: 3.0365 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6387 loss: 2.6387 2022/10/09 13:31:57 - mmengine - INFO - Epoch(train) [36][480/2119] lr: 4.0000e-02 eta: 1 day, 0:27:11 time: 0.3621 data_time: 0.0225 memory: 11108 grad_norm: 3.0126 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4522 loss: 2.4522 2022/10/09 13:32:04 - mmengine - INFO - Epoch(train) [36][500/2119] lr: 4.0000e-02 eta: 1 day, 0:27:03 time: 0.3611 data_time: 0.0211 memory: 11108 grad_norm: 2.9837 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5372 loss: 2.5372 2022/10/09 13:32:11 - mmengine - INFO - Epoch(train) [36][520/2119] lr: 4.0000e-02 eta: 1 day, 0:26:56 time: 0.3591 data_time: 0.0194 memory: 11108 grad_norm: 3.0342 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5910 loss: 2.5910 2022/10/09 13:32:18 - mmengine - INFO - Epoch(train) [36][540/2119] lr: 4.0000e-02 eta: 1 day, 0:26:49 time: 0.3605 data_time: 0.0254 memory: 11108 grad_norm: 2.9903 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5861 loss: 2.5861 2022/10/09 13:32:26 - mmengine - INFO - Epoch(train) [36][560/2119] lr: 4.0000e-02 eta: 1 day, 0:26:41 time: 0.3614 data_time: 0.0208 memory: 11108 grad_norm: 3.0112 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6522 loss: 2.6522 2022/10/09 13:32:33 - mmengine - INFO - Epoch(train) [36][580/2119] lr: 4.0000e-02 eta: 1 day, 0:26:34 time: 0.3599 data_time: 0.0169 memory: 11108 grad_norm: 3.0014 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5974 loss: 2.5974 2022/10/09 13:32:40 - mmengine - INFO - Epoch(train) [36][600/2119] lr: 4.0000e-02 eta: 1 day, 0:26:27 time: 0.3595 data_time: 0.0189 memory: 11108 grad_norm: 3.0345 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5647 loss: 2.5647 2022/10/09 13:32:47 - mmengine - INFO - Epoch(train) [36][620/2119] lr: 4.0000e-02 eta: 1 day, 0:26:19 time: 0.3634 data_time: 0.0203 memory: 11108 grad_norm: 3.0301 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7825 loss: 2.7825 2022/10/09 13:32:54 - mmengine - INFO - Epoch(train) [36][640/2119] lr: 4.0000e-02 eta: 1 day, 0:26:12 time: 0.3576 data_time: 0.0192 memory: 11108 grad_norm: 3.0245 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6645 loss: 2.6645 2022/10/09 13:33:02 - mmengine - INFO - Epoch(train) [36][660/2119] lr: 4.0000e-02 eta: 1 day, 0:26:05 time: 0.3628 data_time: 0.0217 memory: 11108 grad_norm: 3.0454 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8367 loss: 2.8367 2022/10/09 13:33:09 - mmengine - INFO - Epoch(train) [36][680/2119] lr: 4.0000e-02 eta: 1 day, 0:25:57 time: 0.3599 data_time: 0.0217 memory: 11108 grad_norm: 3.0033 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7804 loss: 2.7804 2022/10/09 13:33:16 - mmengine - INFO - Epoch(train) [36][700/2119] lr: 4.0000e-02 eta: 1 day, 0:25:50 time: 0.3539 data_time: 0.0179 memory: 11108 grad_norm: 3.0333 top1_acc: 0.2500 top5_acc: 0.8125 loss_cls: 2.6504 loss: 2.6504 2022/10/09 13:33:23 - mmengine - INFO - Epoch(train) [36][720/2119] lr: 4.0000e-02 eta: 1 day, 0:25:42 time: 0.3589 data_time: 0.0230 memory: 11108 grad_norm: 2.9982 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.4989 loss: 2.4989 2022/10/09 13:33:30 - mmengine - INFO - Epoch(train) [36][740/2119] lr: 4.0000e-02 eta: 1 day, 0:25:35 time: 0.3568 data_time: 0.0196 memory: 11108 grad_norm: 3.0612 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5576 loss: 2.5576 2022/10/09 13:33:38 - mmengine - INFO - Epoch(train) [36][760/2119] lr: 4.0000e-02 eta: 1 day, 0:25:27 time: 0.3588 data_time: 0.0225 memory: 11108 grad_norm: 2.9865 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7435 loss: 2.7435 2022/10/09 13:33:45 - mmengine - INFO - Epoch(train) [36][780/2119] lr: 4.0000e-02 eta: 1 day, 0:25:21 time: 0.3749 data_time: 0.0196 memory: 11108 grad_norm: 2.9450 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8598 loss: 2.8598 2022/10/09 13:33:52 - mmengine - INFO - Epoch(train) [36][800/2119] lr: 4.0000e-02 eta: 1 day, 0:25:13 time: 0.3562 data_time: 0.0239 memory: 11108 grad_norm: 2.9926 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4528 loss: 2.4528 2022/10/09 13:33:59 - mmengine - INFO - Epoch(train) [36][820/2119] lr: 4.0000e-02 eta: 1 day, 0:25:06 time: 0.3579 data_time: 0.0221 memory: 11108 grad_norm: 2.9962 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6821 loss: 2.6821 2022/10/09 13:34:05 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 13:34:07 - mmengine - INFO - Epoch(train) [36][840/2119] lr: 4.0000e-02 eta: 1 day, 0:24:59 time: 0.3733 data_time: 0.0210 memory: 11108 grad_norm: 2.9696 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5500 loss: 2.5500 2022/10/09 13:34:14 - mmengine - INFO - Epoch(train) [36][860/2119] lr: 4.0000e-02 eta: 1 day, 0:24:51 time: 0.3547 data_time: 0.0220 memory: 11108 grad_norm: 2.9725 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7549 loss: 2.7549 2022/10/09 13:34:21 - mmengine - INFO - Epoch(train) [36][880/2119] lr: 4.0000e-02 eta: 1 day, 0:24:44 time: 0.3618 data_time: 0.0252 memory: 11108 grad_norm: 3.0427 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4571 loss: 2.4571 2022/10/09 13:34:29 - mmengine - INFO - Epoch(train) [36][900/2119] lr: 4.0000e-02 eta: 1 day, 0:24:38 time: 0.3746 data_time: 0.0188 memory: 11108 grad_norm: 3.0146 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5876 loss: 2.5876 2022/10/09 13:34:36 - mmengine - INFO - Epoch(train) [36][920/2119] lr: 4.0000e-02 eta: 1 day, 0:24:30 time: 0.3610 data_time: 0.0232 memory: 11108 grad_norm: 3.0255 top1_acc: 0.0000 top5_acc: 0.4375 loss_cls: 2.6892 loss: 2.6892 2022/10/09 13:34:43 - mmengine - INFO - Epoch(train) [36][940/2119] lr: 4.0000e-02 eta: 1 day, 0:24:23 time: 0.3574 data_time: 0.0214 memory: 11108 grad_norm: 2.9823 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5975 loss: 2.5975 2022/10/09 13:34:50 - mmengine - INFO - Epoch(train) [36][960/2119] lr: 4.0000e-02 eta: 1 day, 0:24:15 time: 0.3593 data_time: 0.0226 memory: 11108 grad_norm: 2.9879 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4405 loss: 2.4405 2022/10/09 13:34:57 - mmengine - INFO - Epoch(train) [36][980/2119] lr: 4.0000e-02 eta: 1 day, 0:24:08 time: 0.3571 data_time: 0.0188 memory: 11108 grad_norm: 2.9598 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5732 loss: 2.5732 2022/10/09 13:35:05 - mmengine - INFO - Epoch(train) [36][1000/2119] lr: 4.0000e-02 eta: 1 day, 0:24:02 time: 0.3786 data_time: 0.0211 memory: 11108 grad_norm: 3.0847 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6765 loss: 2.6765 2022/10/09 13:35:12 - mmengine - INFO - Epoch(train) [36][1020/2119] lr: 4.0000e-02 eta: 1 day, 0:23:54 time: 0.3559 data_time: 0.0192 memory: 11108 grad_norm: 3.0556 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8593 loss: 2.8593 2022/10/09 13:35:19 - mmengine - INFO - Epoch(train) [36][1040/2119] lr: 4.0000e-02 eta: 1 day, 0:23:47 time: 0.3613 data_time: 0.0199 memory: 11108 grad_norm: 3.0654 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5195 loss: 2.5195 2022/10/09 13:35:27 - mmengine - INFO - Epoch(train) [36][1060/2119] lr: 4.0000e-02 eta: 1 day, 0:23:40 time: 0.3638 data_time: 0.0273 memory: 11108 grad_norm: 3.0479 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9120 loss: 2.9120 2022/10/09 13:35:34 - mmengine - INFO - Epoch(train) [36][1080/2119] lr: 4.0000e-02 eta: 1 day, 0:23:32 time: 0.3570 data_time: 0.0224 memory: 11108 grad_norm: 3.0153 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5640 loss: 2.5640 2022/10/09 13:35:41 - mmengine - INFO - Epoch(train) [36][1100/2119] lr: 4.0000e-02 eta: 1 day, 0:23:25 time: 0.3622 data_time: 0.0181 memory: 11108 grad_norm: 3.0004 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5455 loss: 2.5455 2022/10/09 13:35:48 - mmengine - INFO - Epoch(train) [36][1120/2119] lr: 4.0000e-02 eta: 1 day, 0:23:18 time: 0.3613 data_time: 0.0199 memory: 11108 grad_norm: 2.9642 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5842 loss: 2.5842 2022/10/09 13:35:55 - mmengine - INFO - Epoch(train) [36][1140/2119] lr: 4.0000e-02 eta: 1 day, 0:23:10 time: 0.3562 data_time: 0.0182 memory: 11108 grad_norm: 3.0006 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6532 loss: 2.6532 2022/10/09 13:36:02 - mmengine - INFO - Epoch(train) [36][1160/2119] lr: 4.0000e-02 eta: 1 day, 0:23:03 time: 0.3610 data_time: 0.0221 memory: 11108 grad_norm: 3.0444 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5662 loss: 2.5662 2022/10/09 13:36:10 - mmengine - INFO - Epoch(train) [36][1180/2119] lr: 4.0000e-02 eta: 1 day, 0:22:56 time: 0.3652 data_time: 0.0186 memory: 11108 grad_norm: 2.9537 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6389 loss: 2.6389 2022/10/09 13:36:17 - mmengine - INFO - Epoch(train) [36][1200/2119] lr: 4.0000e-02 eta: 1 day, 0:22:49 time: 0.3627 data_time: 0.0222 memory: 11108 grad_norm: 2.9900 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5219 loss: 2.5219 2022/10/09 13:36:24 - mmengine - INFO - Epoch(train) [36][1220/2119] lr: 4.0000e-02 eta: 1 day, 0:22:41 time: 0.3575 data_time: 0.0187 memory: 11108 grad_norm: 3.0169 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6597 loss: 2.6597 2022/10/09 13:36:31 - mmengine - INFO - Epoch(train) [36][1240/2119] lr: 4.0000e-02 eta: 1 day, 0:22:33 time: 0.3571 data_time: 0.0201 memory: 11108 grad_norm: 2.9788 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5527 loss: 2.5527 2022/10/09 13:36:39 - mmengine - INFO - Epoch(train) [36][1260/2119] lr: 4.0000e-02 eta: 1 day, 0:22:26 time: 0.3596 data_time: 0.0218 memory: 11108 grad_norm: 3.0089 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5647 loss: 2.5647 2022/10/09 13:36:46 - mmengine - INFO - Epoch(train) [36][1280/2119] lr: 4.0000e-02 eta: 1 day, 0:22:20 time: 0.3751 data_time: 0.0332 memory: 11108 grad_norm: 2.9896 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8383 loss: 2.8383 2022/10/09 13:36:55 - mmengine - INFO - Epoch(train) [36][1300/2119] lr: 4.0000e-02 eta: 1 day, 0:22:19 time: 0.4621 data_time: 0.0428 memory: 11108 grad_norm: 3.0653 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6428 loss: 2.6428 2022/10/09 13:37:03 - mmengine - INFO - Epoch(train) [36][1320/2119] lr: 4.0000e-02 eta: 1 day, 0:22:13 time: 0.3848 data_time: 0.0421 memory: 11108 grad_norm: 2.9758 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8676 loss: 2.8676 2022/10/09 13:37:11 - mmengine - INFO - Epoch(train) [36][1340/2119] lr: 4.0000e-02 eta: 1 day, 0:22:09 time: 0.4102 data_time: 0.0250 memory: 11108 grad_norm: 2.9958 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6629 loss: 2.6629 2022/10/09 13:37:18 - mmengine - INFO - Epoch(train) [36][1360/2119] lr: 4.0000e-02 eta: 1 day, 0:22:01 time: 0.3589 data_time: 0.0212 memory: 11108 grad_norm: 2.9935 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6950 loss: 2.6950 2022/10/09 13:37:26 - mmengine - INFO - Epoch(train) [36][1380/2119] lr: 4.0000e-02 eta: 1 day, 0:21:54 time: 0.3597 data_time: 0.0212 memory: 11108 grad_norm: 2.9560 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.4437 loss: 2.4437 2022/10/09 13:37:33 - mmengine - INFO - Epoch(train) [36][1400/2119] lr: 4.0000e-02 eta: 1 day, 0:21:47 time: 0.3650 data_time: 0.0206 memory: 11108 grad_norm: 2.9806 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5031 loss: 2.5031 2022/10/09 13:37:40 - mmengine - INFO - Epoch(train) [36][1420/2119] lr: 4.0000e-02 eta: 1 day, 0:21:40 time: 0.3582 data_time: 0.0243 memory: 11108 grad_norm: 3.0337 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.3659 loss: 2.3659 2022/10/09 13:37:47 - mmengine - INFO - Epoch(train) [36][1440/2119] lr: 4.0000e-02 eta: 1 day, 0:21:32 time: 0.3606 data_time: 0.0224 memory: 11108 grad_norm: 3.0263 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5703 loss: 2.5703 2022/10/09 13:37:54 - mmengine - INFO - Epoch(train) [36][1460/2119] lr: 4.0000e-02 eta: 1 day, 0:21:25 time: 0.3565 data_time: 0.0220 memory: 11108 grad_norm: 2.9976 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6524 loss: 2.6524 2022/10/09 13:38:02 - mmengine - INFO - Epoch(train) [36][1480/2119] lr: 4.0000e-02 eta: 1 day, 0:21:17 time: 0.3578 data_time: 0.0191 memory: 11108 grad_norm: 2.9909 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.5238 loss: 2.5238 2022/10/09 13:38:09 - mmengine - INFO - Epoch(train) [36][1500/2119] lr: 4.0000e-02 eta: 1 day, 0:21:10 time: 0.3575 data_time: 0.0266 memory: 11108 grad_norm: 3.0091 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4047 loss: 2.4047 2022/10/09 13:38:16 - mmengine - INFO - Epoch(train) [36][1520/2119] lr: 4.0000e-02 eta: 1 day, 0:21:02 time: 0.3586 data_time: 0.0219 memory: 11108 grad_norm: 2.9799 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7280 loss: 2.7280 2022/10/09 13:38:23 - mmengine - INFO - Epoch(train) [36][1540/2119] lr: 4.0000e-02 eta: 1 day, 0:20:55 time: 0.3561 data_time: 0.0181 memory: 11108 grad_norm: 2.9666 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5624 loss: 2.5624 2022/10/09 13:38:30 - mmengine - INFO - Epoch(train) [36][1560/2119] lr: 4.0000e-02 eta: 1 day, 0:20:47 time: 0.3573 data_time: 0.0211 memory: 11108 grad_norm: 3.0591 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7352 loss: 2.7352 2022/10/09 13:38:37 - mmengine - INFO - Epoch(train) [36][1580/2119] lr: 4.0000e-02 eta: 1 day, 0:20:39 time: 0.3549 data_time: 0.0240 memory: 11108 grad_norm: 3.0089 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6307 loss: 2.6307 2022/10/09 13:38:44 - mmengine - INFO - Epoch(train) [36][1600/2119] lr: 4.0000e-02 eta: 1 day, 0:20:32 time: 0.3558 data_time: 0.0184 memory: 11108 grad_norm: 3.0197 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8851 loss: 2.8851 2022/10/09 13:38:52 - mmengine - INFO - Epoch(train) [36][1620/2119] lr: 4.0000e-02 eta: 1 day, 0:20:24 time: 0.3630 data_time: 0.0286 memory: 11108 grad_norm: 2.9901 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5991 loss: 2.5991 2022/10/09 13:38:59 - mmengine - INFO - Epoch(train) [36][1640/2119] lr: 4.0000e-02 eta: 1 day, 0:20:17 time: 0.3551 data_time: 0.0204 memory: 11108 grad_norm: 2.9778 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6515 loss: 2.6515 2022/10/09 13:39:06 - mmengine - INFO - Epoch(train) [36][1660/2119] lr: 4.0000e-02 eta: 1 day, 0:20:09 time: 0.3564 data_time: 0.0218 memory: 11108 grad_norm: 3.0003 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5269 loss: 2.5269 2022/10/09 13:39:13 - mmengine - INFO - Epoch(train) [36][1680/2119] lr: 4.0000e-02 eta: 1 day, 0:20:02 time: 0.3591 data_time: 0.0222 memory: 11108 grad_norm: 3.0308 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7668 loss: 2.7668 2022/10/09 13:39:20 - mmengine - INFO - Epoch(train) [36][1700/2119] lr: 4.0000e-02 eta: 1 day, 0:19:54 time: 0.3582 data_time: 0.0207 memory: 11108 grad_norm: 3.0527 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6390 loss: 2.6390 2022/10/09 13:39:27 - mmengine - INFO - Epoch(train) [36][1720/2119] lr: 4.0000e-02 eta: 1 day, 0:19:47 time: 0.3557 data_time: 0.0275 memory: 11108 grad_norm: 2.9844 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5371 loss: 2.5371 2022/10/09 13:39:35 - mmengine - INFO - Epoch(train) [36][1740/2119] lr: 4.0000e-02 eta: 1 day, 0:19:39 time: 0.3616 data_time: 0.0168 memory: 11108 grad_norm: 3.0320 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5275 loss: 2.5275 2022/10/09 13:39:42 - mmengine - INFO - Epoch(train) [36][1760/2119] lr: 4.0000e-02 eta: 1 day, 0:19:32 time: 0.3585 data_time: 0.0212 memory: 11108 grad_norm: 3.0332 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6419 loss: 2.6419 2022/10/09 13:39:49 - mmengine - INFO - Epoch(train) [36][1780/2119] lr: 4.0000e-02 eta: 1 day, 0:19:24 time: 0.3580 data_time: 0.0176 memory: 11108 grad_norm: 2.9595 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6096 loss: 2.6096 2022/10/09 13:39:56 - mmengine - INFO - Epoch(train) [36][1800/2119] lr: 4.0000e-02 eta: 1 day, 0:19:17 time: 0.3578 data_time: 0.0208 memory: 11108 grad_norm: 3.0690 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9407 loss: 2.9407 2022/10/09 13:40:03 - mmengine - INFO - Epoch(train) [36][1820/2119] lr: 4.0000e-02 eta: 1 day, 0:19:10 time: 0.3602 data_time: 0.0261 memory: 11108 grad_norm: 3.0062 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5524 loss: 2.5524 2022/10/09 13:40:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 13:40:10 - mmengine - INFO - Epoch(train) [36][1840/2119] lr: 4.0000e-02 eta: 1 day, 0:19:02 time: 0.3548 data_time: 0.0242 memory: 11108 grad_norm: 2.9864 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6132 loss: 2.6132 2022/10/09 13:40:18 - mmengine - INFO - Epoch(train) [36][1860/2119] lr: 4.0000e-02 eta: 1 day, 0:18:55 time: 0.3603 data_time: 0.0202 memory: 11108 grad_norm: 3.0060 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4854 loss: 2.4854 2022/10/09 13:40:25 - mmengine - INFO - Epoch(train) [36][1880/2119] lr: 4.0000e-02 eta: 1 day, 0:18:47 time: 0.3613 data_time: 0.0190 memory: 11108 grad_norm: 3.0324 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.9114 loss: 2.9114 2022/10/09 13:40:32 - mmengine - INFO - Epoch(train) [36][1900/2119] lr: 4.0000e-02 eta: 1 day, 0:18:40 time: 0.3620 data_time: 0.0189 memory: 11108 grad_norm: 2.9624 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4974 loss: 2.4974 2022/10/09 13:40:39 - mmengine - INFO - Epoch(train) [36][1920/2119] lr: 4.0000e-02 eta: 1 day, 0:18:33 time: 0.3652 data_time: 0.0272 memory: 11108 grad_norm: 2.9806 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6888 loss: 2.6888 2022/10/09 13:40:47 - mmengine - INFO - Epoch(train) [36][1940/2119] lr: 4.0000e-02 eta: 1 day, 0:18:26 time: 0.3587 data_time: 0.0201 memory: 11108 grad_norm: 3.0282 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.8267 loss: 2.8267 2022/10/09 13:40:54 - mmengine - INFO - Epoch(train) [36][1960/2119] lr: 4.0000e-02 eta: 1 day, 0:18:18 time: 0.3561 data_time: 0.0225 memory: 11108 grad_norm: 3.0386 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5583 loss: 2.5583 2022/10/09 13:41:01 - mmengine - INFO - Epoch(train) [36][1980/2119] lr: 4.0000e-02 eta: 1 day, 0:18:11 time: 0.3612 data_time: 0.0221 memory: 11108 grad_norm: 3.0169 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6013 loss: 2.6013 2022/10/09 13:41:08 - mmengine - INFO - Epoch(train) [36][2000/2119] lr: 4.0000e-02 eta: 1 day, 0:18:03 time: 0.3574 data_time: 0.0194 memory: 11108 grad_norm: 2.9612 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9310 loss: 2.9310 2022/10/09 13:41:15 - mmengine - INFO - Epoch(train) [36][2020/2119] lr: 4.0000e-02 eta: 1 day, 0:17:55 time: 0.3558 data_time: 0.0178 memory: 11108 grad_norm: 2.9974 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5964 loss: 2.5964 2022/10/09 13:41:22 - mmengine - INFO - Epoch(train) [36][2040/2119] lr: 4.0000e-02 eta: 1 day, 0:17:48 time: 0.3598 data_time: 0.0210 memory: 11108 grad_norm: 3.0215 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.5378 loss: 2.5378 2022/10/09 13:41:30 - mmengine - INFO - Epoch(train) [36][2060/2119] lr: 4.0000e-02 eta: 1 day, 0:17:41 time: 0.3591 data_time: 0.0193 memory: 11108 grad_norm: 3.0253 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7620 loss: 2.7620 2022/10/09 13:41:37 - mmengine - INFO - Epoch(train) [36][2080/2119] lr: 4.0000e-02 eta: 1 day, 0:17:34 time: 0.3632 data_time: 0.0276 memory: 11108 grad_norm: 3.0118 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6554 loss: 2.6554 2022/10/09 13:41:44 - mmengine - INFO - Epoch(train) [36][2100/2119] lr: 4.0000e-02 eta: 1 day, 0:17:26 time: 0.3563 data_time: 0.0213 memory: 11108 grad_norm: 2.9791 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5812 loss: 2.5812 2022/10/09 13:41:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 13:41:50 - mmengine - INFO - Epoch(train) [36][2119/2119] lr: 4.0000e-02 eta: 1 day, 0:17:26 time: 0.3435 data_time: 0.0195 memory: 11108 grad_norm: 3.0701 top1_acc: 0.4000 top5_acc: 0.9000 loss_cls: 2.5678 loss: 2.5678 2022/10/09 13:41:50 - mmengine - INFO - Saving checkpoint at 36 epochs 2022/10/09 13:42:02 - mmengine - INFO - Epoch(train) [37][20/2119] lr: 4.0000e-02 eta: 1 day, 0:16:56 time: 0.4524 data_time: 0.1137 memory: 11108 grad_norm: 2.9657 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6536 loss: 2.6536 2022/10/09 13:42:09 - mmengine - INFO - Epoch(train) [37][40/2119] lr: 4.0000e-02 eta: 1 day, 0:16:48 time: 0.3549 data_time: 0.0221 memory: 11108 grad_norm: 2.9768 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7440 loss: 2.7440 2022/10/09 13:42:16 - mmengine - INFO - Epoch(train) [37][60/2119] lr: 4.0000e-02 eta: 1 day, 0:16:41 time: 0.3591 data_time: 0.0211 memory: 11108 grad_norm: 3.0508 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9081 loss: 2.9081 2022/10/09 13:42:23 - mmengine - INFO - Epoch(train) [37][80/2119] lr: 4.0000e-02 eta: 1 day, 0:16:33 time: 0.3573 data_time: 0.0221 memory: 11108 grad_norm: 3.0613 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6140 loss: 2.6140 2022/10/09 13:42:31 - mmengine - INFO - Epoch(train) [37][100/2119] lr: 4.0000e-02 eta: 1 day, 0:16:26 time: 0.3595 data_time: 0.0221 memory: 11108 grad_norm: 2.9406 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.4498 loss: 2.4498 2022/10/09 13:42:38 - mmengine - INFO - Epoch(train) [37][120/2119] lr: 4.0000e-02 eta: 1 day, 0:16:19 time: 0.3632 data_time: 0.0214 memory: 11108 grad_norm: 2.9955 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7240 loss: 2.7240 2022/10/09 13:42:45 - mmengine - INFO - Epoch(train) [37][140/2119] lr: 4.0000e-02 eta: 1 day, 0:16:11 time: 0.3570 data_time: 0.0182 memory: 11108 grad_norm: 2.9583 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6273 loss: 2.6273 2022/10/09 13:42:52 - mmengine - INFO - Epoch(train) [37][160/2119] lr: 4.0000e-02 eta: 1 day, 0:16:04 time: 0.3596 data_time: 0.0225 memory: 11108 grad_norm: 3.0167 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5802 loss: 2.5802 2022/10/09 13:43:00 - mmengine - INFO - Epoch(train) [37][180/2119] lr: 4.0000e-02 eta: 1 day, 0:15:57 time: 0.3655 data_time: 0.0251 memory: 11108 grad_norm: 3.0132 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7956 loss: 2.7956 2022/10/09 13:43:07 - mmengine - INFO - Epoch(train) [37][200/2119] lr: 4.0000e-02 eta: 1 day, 0:15:49 time: 0.3583 data_time: 0.0186 memory: 11108 grad_norm: 3.0048 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5593 loss: 2.5593 2022/10/09 13:43:14 - mmengine - INFO - Epoch(train) [37][220/2119] lr: 4.0000e-02 eta: 1 day, 0:15:42 time: 0.3564 data_time: 0.0218 memory: 11108 grad_norm: 2.9830 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5913 loss: 2.5913 2022/10/09 13:43:21 - mmengine - INFO - Epoch(train) [37][240/2119] lr: 4.0000e-02 eta: 1 day, 0:15:34 time: 0.3593 data_time: 0.0230 memory: 11108 grad_norm: 3.0606 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7143 loss: 2.7143 2022/10/09 13:43:28 - mmengine - INFO - Epoch(train) [37][260/2119] lr: 4.0000e-02 eta: 1 day, 0:15:27 time: 0.3584 data_time: 0.0222 memory: 11108 grad_norm: 3.0058 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4742 loss: 2.4742 2022/10/09 13:43:35 - mmengine - INFO - Epoch(train) [37][280/2119] lr: 4.0000e-02 eta: 1 day, 0:15:19 time: 0.3548 data_time: 0.0192 memory: 11108 grad_norm: 3.0052 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6460 loss: 2.6460 2022/10/09 13:43:43 - mmengine - INFO - Epoch(train) [37][300/2119] lr: 4.0000e-02 eta: 1 day, 0:15:12 time: 0.3616 data_time: 0.0200 memory: 11108 grad_norm: 2.9471 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6203 loss: 2.6203 2022/10/09 13:43:50 - mmengine - INFO - Epoch(train) [37][320/2119] lr: 4.0000e-02 eta: 1 day, 0:15:05 time: 0.3675 data_time: 0.0205 memory: 11108 grad_norm: 2.9952 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7761 loss: 2.7761 2022/10/09 13:43:57 - mmengine - INFO - Epoch(train) [37][340/2119] lr: 4.0000e-02 eta: 1 day, 0:14:58 time: 0.3595 data_time: 0.0226 memory: 11108 grad_norm: 3.0440 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.4076 loss: 2.4076 2022/10/09 13:44:04 - mmengine - INFO - Epoch(train) [37][360/2119] lr: 4.0000e-02 eta: 1 day, 0:14:50 time: 0.3627 data_time: 0.0251 memory: 11108 grad_norm: 3.0045 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5661 loss: 2.5661 2022/10/09 13:44:12 - mmengine - INFO - Epoch(train) [37][380/2119] lr: 4.0000e-02 eta: 1 day, 0:14:43 time: 0.3585 data_time: 0.0226 memory: 11108 grad_norm: 3.0667 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7585 loss: 2.7585 2022/10/09 13:44:19 - mmengine - INFO - Epoch(train) [37][400/2119] lr: 4.0000e-02 eta: 1 day, 0:14:36 time: 0.3608 data_time: 0.0271 memory: 11108 grad_norm: 3.0299 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4096 loss: 2.4096 2022/10/09 13:44:26 - mmengine - INFO - Epoch(train) [37][420/2119] lr: 4.0000e-02 eta: 1 day, 0:14:28 time: 0.3563 data_time: 0.0210 memory: 11108 grad_norm: 3.0626 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8897 loss: 2.8897 2022/10/09 13:44:33 - mmengine - INFO - Epoch(train) [37][440/2119] lr: 4.0000e-02 eta: 1 day, 0:14:20 time: 0.3557 data_time: 0.0201 memory: 11108 grad_norm: 3.0254 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6734 loss: 2.6734 2022/10/09 13:44:40 - mmengine - INFO - Epoch(train) [37][460/2119] lr: 4.0000e-02 eta: 1 day, 0:14:13 time: 0.3599 data_time: 0.0203 memory: 11108 grad_norm: 3.0703 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4396 loss: 2.4396 2022/10/09 13:44:47 - mmengine - INFO - Epoch(train) [37][480/2119] lr: 4.0000e-02 eta: 1 day, 0:14:06 time: 0.3576 data_time: 0.0186 memory: 11108 grad_norm: 3.0569 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5339 loss: 2.5339 2022/10/09 13:44:55 - mmengine - INFO - Epoch(train) [37][500/2119] lr: 4.0000e-02 eta: 1 day, 0:13:58 time: 0.3614 data_time: 0.0267 memory: 11108 grad_norm: 3.0300 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6539 loss: 2.6539 2022/10/09 13:45:02 - mmengine - INFO - Epoch(train) [37][520/2119] lr: 4.0000e-02 eta: 1 day, 0:13:51 time: 0.3627 data_time: 0.0193 memory: 11108 grad_norm: 2.9547 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4759 loss: 2.4759 2022/10/09 13:45:09 - mmengine - INFO - Epoch(train) [37][540/2119] lr: 4.0000e-02 eta: 1 day, 0:13:44 time: 0.3606 data_time: 0.0185 memory: 11108 grad_norm: 3.0425 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7276 loss: 2.7276 2022/10/09 13:45:16 - mmengine - INFO - Epoch(train) [37][560/2119] lr: 4.0000e-02 eta: 1 day, 0:13:36 time: 0.3606 data_time: 0.0215 memory: 11108 grad_norm: 3.0384 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6917 loss: 2.6917 2022/10/09 13:45:23 - mmengine - INFO - Epoch(train) [37][580/2119] lr: 4.0000e-02 eta: 1 day, 0:13:29 time: 0.3604 data_time: 0.0167 memory: 11108 grad_norm: 3.0675 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5333 loss: 2.5333 2022/10/09 13:45:31 - mmengine - INFO - Epoch(train) [37][600/2119] lr: 4.0000e-02 eta: 1 day, 0:13:21 time: 0.3558 data_time: 0.0206 memory: 11108 grad_norm: 3.0369 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8624 loss: 2.8624 2022/10/09 13:45:38 - mmengine - INFO - Epoch(train) [37][620/2119] lr: 4.0000e-02 eta: 1 day, 0:13:14 time: 0.3615 data_time: 0.0205 memory: 11108 grad_norm: 3.0175 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7612 loss: 2.7612 2022/10/09 13:45:45 - mmengine - INFO - Epoch(train) [37][640/2119] lr: 4.0000e-02 eta: 1 day, 0:13:07 time: 0.3568 data_time: 0.0178 memory: 11108 grad_norm: 3.0268 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5322 loss: 2.5322 2022/10/09 13:45:52 - mmengine - INFO - Epoch(train) [37][660/2119] lr: 4.0000e-02 eta: 1 day, 0:12:59 time: 0.3609 data_time: 0.0237 memory: 11108 grad_norm: 3.0301 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7723 loss: 2.7723 2022/10/09 13:45:59 - mmengine - INFO - Epoch(train) [37][680/2119] lr: 4.0000e-02 eta: 1 day, 0:12:52 time: 0.3596 data_time: 0.0207 memory: 11108 grad_norm: 3.0484 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3642 loss: 2.3642 2022/10/09 13:46:06 - mmengine - INFO - Epoch(train) [37][700/2119] lr: 4.0000e-02 eta: 1 day, 0:12:44 time: 0.3566 data_time: 0.0202 memory: 11108 grad_norm: 3.0411 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5216 loss: 2.5216 2022/10/09 13:46:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 13:46:14 - mmengine - INFO - Epoch(train) [37][720/2119] lr: 4.0000e-02 eta: 1 day, 0:12:37 time: 0.3577 data_time: 0.0219 memory: 11108 grad_norm: 3.0739 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.7925 loss: 2.7925 2022/10/09 13:46:21 - mmengine - INFO - Epoch(train) [37][740/2119] lr: 4.0000e-02 eta: 1 day, 0:12:30 time: 0.3595 data_time: 0.0204 memory: 11108 grad_norm: 3.0030 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0534 loss: 3.0534 2022/10/09 13:46:28 - mmengine - INFO - Epoch(train) [37][760/2119] lr: 4.0000e-02 eta: 1 day, 0:12:22 time: 0.3593 data_time: 0.0220 memory: 11108 grad_norm: 3.0094 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7481 loss: 2.7481 2022/10/09 13:46:35 - mmengine - INFO - Epoch(train) [37][780/2119] lr: 4.0000e-02 eta: 1 day, 0:12:15 time: 0.3576 data_time: 0.0209 memory: 11108 grad_norm: 2.9883 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7853 loss: 2.7853 2022/10/09 13:46:42 - mmengine - INFO - Epoch(train) [37][800/2119] lr: 4.0000e-02 eta: 1 day, 0:12:07 time: 0.3555 data_time: 0.0220 memory: 11108 grad_norm: 2.9745 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4588 loss: 2.4588 2022/10/09 13:46:49 - mmengine - INFO - Epoch(train) [37][820/2119] lr: 4.0000e-02 eta: 1 day, 0:11:59 time: 0.3561 data_time: 0.0194 memory: 11108 grad_norm: 3.0063 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5142 loss: 2.5142 2022/10/09 13:46:57 - mmengine - INFO - Epoch(train) [37][840/2119] lr: 4.0000e-02 eta: 1 day, 0:11:52 time: 0.3586 data_time: 0.0207 memory: 11108 grad_norm: 2.9976 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7035 loss: 2.7035 2022/10/09 13:47:04 - mmengine - INFO - Epoch(train) [37][860/2119] lr: 4.0000e-02 eta: 1 day, 0:11:44 time: 0.3585 data_time: 0.0185 memory: 11108 grad_norm: 2.9780 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5858 loss: 2.5858 2022/10/09 13:47:11 - mmengine - INFO - Epoch(train) [37][880/2119] lr: 4.0000e-02 eta: 1 day, 0:11:37 time: 0.3567 data_time: 0.0232 memory: 11108 grad_norm: 3.0487 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7012 loss: 2.7012 2022/10/09 13:47:18 - mmengine - INFO - Epoch(train) [37][900/2119] lr: 4.0000e-02 eta: 1 day, 0:11:29 time: 0.3565 data_time: 0.0223 memory: 11108 grad_norm: 2.9909 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5563 loss: 2.5563 2022/10/09 13:47:25 - mmengine - INFO - Epoch(train) [37][920/2119] lr: 4.0000e-02 eta: 1 day, 0:11:22 time: 0.3566 data_time: 0.0210 memory: 11108 grad_norm: 2.9680 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6168 loss: 2.6168 2022/10/09 13:47:32 - mmengine - INFO - Epoch(train) [37][940/2119] lr: 4.0000e-02 eta: 1 day, 0:11:14 time: 0.3587 data_time: 0.0197 memory: 11108 grad_norm: 2.9773 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7614 loss: 2.7614 2022/10/09 13:47:40 - mmengine - INFO - Epoch(train) [37][960/2119] lr: 4.0000e-02 eta: 1 day, 0:11:07 time: 0.3672 data_time: 0.0238 memory: 11108 grad_norm: 3.0213 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7344 loss: 2.7344 2022/10/09 13:47:47 - mmengine - INFO - Epoch(train) [37][980/2119] lr: 4.0000e-02 eta: 1 day, 0:11:00 time: 0.3547 data_time: 0.0170 memory: 11108 grad_norm: 3.0515 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7834 loss: 2.7834 2022/10/09 13:47:54 - mmengine - INFO - Epoch(train) [37][1000/2119] lr: 4.0000e-02 eta: 1 day, 0:10:52 time: 0.3561 data_time: 0.0212 memory: 11108 grad_norm: 3.0095 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7509 loss: 2.7509 2022/10/09 13:48:01 - mmengine - INFO - Epoch(train) [37][1020/2119] lr: 4.0000e-02 eta: 1 day, 0:10:45 time: 0.3666 data_time: 0.0197 memory: 11108 grad_norm: 3.0023 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7592 loss: 2.7592 2022/10/09 13:48:08 - mmengine - INFO - Epoch(train) [37][1040/2119] lr: 4.0000e-02 eta: 1 day, 0:10:38 time: 0.3603 data_time: 0.0190 memory: 11108 grad_norm: 2.9753 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5516 loss: 2.5516 2022/10/09 13:48:16 - mmengine - INFO - Epoch(train) [37][1060/2119] lr: 4.0000e-02 eta: 1 day, 0:10:31 time: 0.3611 data_time: 0.0263 memory: 11108 grad_norm: 3.0453 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6597 loss: 2.6597 2022/10/09 13:48:23 - mmengine - INFO - Epoch(train) [37][1080/2119] lr: 4.0000e-02 eta: 1 day, 0:10:23 time: 0.3630 data_time: 0.0199 memory: 11108 grad_norm: 3.0061 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5440 loss: 2.5440 2022/10/09 13:48:30 - mmengine - INFO - Epoch(train) [37][1100/2119] lr: 4.0000e-02 eta: 1 day, 0:10:16 time: 0.3620 data_time: 0.0170 memory: 11108 grad_norm: 3.0089 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5431 loss: 2.5431 2022/10/09 13:48:37 - mmengine - INFO - Epoch(train) [37][1120/2119] lr: 4.0000e-02 eta: 1 day, 0:10:09 time: 0.3586 data_time: 0.0225 memory: 11108 grad_norm: 3.0413 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5541 loss: 2.5541 2022/10/09 13:48:45 - mmengine - INFO - Epoch(train) [37][1140/2119] lr: 4.0000e-02 eta: 1 day, 0:10:01 time: 0.3598 data_time: 0.0210 memory: 11108 grad_norm: 3.0985 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7704 loss: 2.7704 2022/10/09 13:48:52 - mmengine - INFO - Epoch(train) [37][1160/2119] lr: 4.0000e-02 eta: 1 day, 0:09:54 time: 0.3598 data_time: 0.0180 memory: 11108 grad_norm: 3.0132 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8094 loss: 2.8094 2022/10/09 13:48:59 - mmengine - INFO - Epoch(train) [37][1180/2119] lr: 4.0000e-02 eta: 1 day, 0:09:47 time: 0.3666 data_time: 0.0184 memory: 11108 grad_norm: 2.9965 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.5171 loss: 2.5171 2022/10/09 13:49:06 - mmengine - INFO - Epoch(train) [37][1200/2119] lr: 4.0000e-02 eta: 1 day, 0:09:40 time: 0.3576 data_time: 0.0214 memory: 11108 grad_norm: 3.0291 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5682 loss: 2.5682 2022/10/09 13:49:13 - mmengine - INFO - Epoch(train) [37][1220/2119] lr: 4.0000e-02 eta: 1 day, 0:09:32 time: 0.3584 data_time: 0.0176 memory: 11108 grad_norm: 3.0288 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7181 loss: 2.7181 2022/10/09 13:49:21 - mmengine - INFO - Epoch(train) [37][1240/2119] lr: 4.0000e-02 eta: 1 day, 0:09:25 time: 0.3625 data_time: 0.0180 memory: 11108 grad_norm: 2.9967 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6305 loss: 2.6305 2022/10/09 13:49:28 - mmengine - INFO - Epoch(train) [37][1260/2119] lr: 4.0000e-02 eta: 1 day, 0:09:18 time: 0.3615 data_time: 0.0237 memory: 11108 grad_norm: 3.0158 top1_acc: 0.1875 top5_acc: 0.7500 loss_cls: 2.6555 loss: 2.6555 2022/10/09 13:49:35 - mmengine - INFO - Epoch(train) [37][1280/2119] lr: 4.0000e-02 eta: 1 day, 0:09:10 time: 0.3536 data_time: 0.0183 memory: 11108 grad_norm: 3.0866 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8174 loss: 2.8174 2022/10/09 13:49:42 - mmengine - INFO - Epoch(train) [37][1300/2119] lr: 4.0000e-02 eta: 1 day, 0:09:02 time: 0.3580 data_time: 0.0182 memory: 11108 grad_norm: 2.9872 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7072 loss: 2.7072 2022/10/09 13:49:49 - mmengine - INFO - Epoch(train) [37][1320/2119] lr: 4.0000e-02 eta: 1 day, 0:08:55 time: 0.3626 data_time: 0.0226 memory: 11108 grad_norm: 3.0506 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6724 loss: 2.6724 2022/10/09 13:49:57 - mmengine - INFO - Epoch(train) [37][1340/2119] lr: 4.0000e-02 eta: 1 day, 0:08:48 time: 0.3556 data_time: 0.0202 memory: 11108 grad_norm: 3.0565 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7063 loss: 2.7063 2022/10/09 13:50:04 - mmengine - INFO - Epoch(train) [37][1360/2119] lr: 4.0000e-02 eta: 1 day, 0:08:40 time: 0.3607 data_time: 0.0221 memory: 11108 grad_norm: 2.9760 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 2.5541 loss: 2.5541 2022/10/09 13:50:11 - mmengine - INFO - Epoch(train) [37][1380/2119] lr: 4.0000e-02 eta: 1 day, 0:08:33 time: 0.3606 data_time: 0.0205 memory: 11108 grad_norm: 3.0461 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7455 loss: 2.7455 2022/10/09 13:50:18 - mmengine - INFO - Epoch(train) [37][1400/2119] lr: 4.0000e-02 eta: 1 day, 0:08:26 time: 0.3600 data_time: 0.0220 memory: 11108 grad_norm: 3.0960 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8841 loss: 2.8841 2022/10/09 13:50:25 - mmengine - INFO - Epoch(train) [37][1420/2119] lr: 4.0000e-02 eta: 1 day, 0:08:19 time: 0.3665 data_time: 0.0229 memory: 11108 grad_norm: 2.9746 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5434 loss: 2.5434 2022/10/09 13:50:33 - mmengine - INFO - Epoch(train) [37][1440/2119] lr: 4.0000e-02 eta: 1 day, 0:08:12 time: 0.3634 data_time: 0.0272 memory: 11108 grad_norm: 3.0290 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4738 loss: 2.4738 2022/10/09 13:50:40 - mmengine - INFO - Epoch(train) [37][1460/2119] lr: 4.0000e-02 eta: 1 day, 0:08:04 time: 0.3570 data_time: 0.0199 memory: 11108 grad_norm: 2.9775 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5134 loss: 2.5134 2022/10/09 13:50:47 - mmengine - INFO - Epoch(train) [37][1480/2119] lr: 4.0000e-02 eta: 1 day, 0:07:57 time: 0.3616 data_time: 0.0212 memory: 11108 grad_norm: 3.0300 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.4915 loss: 2.4915 2022/10/09 13:50:54 - mmengine - INFO - Epoch(train) [37][1500/2119] lr: 4.0000e-02 eta: 1 day, 0:07:49 time: 0.3599 data_time: 0.0184 memory: 11108 grad_norm: 3.0772 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5427 loss: 2.5427 2022/10/09 13:51:02 - mmengine - INFO - Epoch(train) [37][1520/2119] lr: 4.0000e-02 eta: 1 day, 0:07:42 time: 0.3606 data_time: 0.0201 memory: 11108 grad_norm: 3.0319 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5614 loss: 2.5614 2022/10/09 13:51:09 - mmengine - INFO - Epoch(train) [37][1540/2119] lr: 4.0000e-02 eta: 1 day, 0:07:35 time: 0.3586 data_time: 0.0206 memory: 11108 grad_norm: 2.9855 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6104 loss: 2.6104 2022/10/09 13:51:16 - mmengine - INFO - Epoch(train) [37][1560/2119] lr: 4.0000e-02 eta: 1 day, 0:07:27 time: 0.3562 data_time: 0.0207 memory: 11108 grad_norm: 3.0888 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7904 loss: 2.7904 2022/10/09 13:51:23 - mmengine - INFO - Epoch(train) [37][1580/2119] lr: 4.0000e-02 eta: 1 day, 0:07:20 time: 0.3607 data_time: 0.0189 memory: 11108 grad_norm: 3.0445 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5511 loss: 2.5511 2022/10/09 13:51:30 - mmengine - INFO - Epoch(train) [37][1600/2119] lr: 4.0000e-02 eta: 1 day, 0:07:12 time: 0.3556 data_time: 0.0185 memory: 11108 grad_norm: 3.0814 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6794 loss: 2.6794 2022/10/09 13:51:37 - mmengine - INFO - Epoch(train) [37][1620/2119] lr: 4.0000e-02 eta: 1 day, 0:07:05 time: 0.3608 data_time: 0.0199 memory: 11108 grad_norm: 3.0322 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7277 loss: 2.7277 2022/10/09 13:51:45 - mmengine - INFO - Epoch(train) [37][1640/2119] lr: 4.0000e-02 eta: 1 day, 0:06:58 time: 0.3624 data_time: 0.0253 memory: 11108 grad_norm: 3.0258 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7535 loss: 2.7535 2022/10/09 13:51:52 - mmengine - INFO - Epoch(train) [37][1660/2119] lr: 4.0000e-02 eta: 1 day, 0:06:50 time: 0.3602 data_time: 0.0253 memory: 11108 grad_norm: 3.0069 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6980 loss: 2.6980 2022/10/09 13:51:59 - mmengine - INFO - Epoch(train) [37][1680/2119] lr: 4.0000e-02 eta: 1 day, 0:06:43 time: 0.3569 data_time: 0.0175 memory: 11108 grad_norm: 3.0099 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6853 loss: 2.6853 2022/10/09 13:52:06 - mmengine - INFO - Epoch(train) [37][1700/2119] lr: 4.0000e-02 eta: 1 day, 0:06:35 time: 0.3576 data_time: 0.0225 memory: 11108 grad_norm: 3.0390 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5854 loss: 2.5854 2022/10/09 13:52:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 13:52:14 - mmengine - INFO - Epoch(train) [37][1720/2119] lr: 4.0000e-02 eta: 1 day, 0:06:29 time: 0.3742 data_time: 0.0189 memory: 11108 grad_norm: 3.0091 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7250 loss: 2.7250 2022/10/09 13:52:21 - mmengine - INFO - Epoch(train) [37][1740/2119] lr: 4.0000e-02 eta: 1 day, 0:06:21 time: 0.3599 data_time: 0.0215 memory: 11108 grad_norm: 3.0514 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5470 loss: 2.5470 2022/10/09 13:52:28 - mmengine - INFO - Epoch(train) [37][1760/2119] lr: 4.0000e-02 eta: 1 day, 0:06:14 time: 0.3573 data_time: 0.0206 memory: 11108 grad_norm: 2.9729 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6154 loss: 2.6154 2022/10/09 13:52:35 - mmengine - INFO - Epoch(train) [37][1780/2119] lr: 4.0000e-02 eta: 1 day, 0:06:07 time: 0.3608 data_time: 0.0278 memory: 11108 grad_norm: 2.9537 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6685 loss: 2.6685 2022/10/09 13:52:42 - mmengine - INFO - Epoch(train) [37][1800/2119] lr: 4.0000e-02 eta: 1 day, 0:05:59 time: 0.3631 data_time: 0.0217 memory: 11108 grad_norm: 3.0103 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7628 loss: 2.7628 2022/10/09 13:52:50 - mmengine - INFO - Epoch(train) [37][1820/2119] lr: 4.0000e-02 eta: 1 day, 0:05:52 time: 0.3657 data_time: 0.0229 memory: 11108 grad_norm: 2.9926 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6643 loss: 2.6643 2022/10/09 13:52:57 - mmengine - INFO - Epoch(train) [37][1840/2119] lr: 4.0000e-02 eta: 1 day, 0:05:45 time: 0.3588 data_time: 0.0221 memory: 11108 grad_norm: 3.0120 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6466 loss: 2.6466 2022/10/09 13:53:04 - mmengine - INFO - Epoch(train) [37][1860/2119] lr: 4.0000e-02 eta: 1 day, 0:05:38 time: 0.3589 data_time: 0.0215 memory: 11108 grad_norm: 3.0124 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5341 loss: 2.5341 2022/10/09 13:53:11 - mmengine - INFO - Epoch(train) [37][1880/2119] lr: 4.0000e-02 eta: 1 day, 0:05:30 time: 0.3620 data_time: 0.0198 memory: 11108 grad_norm: 3.0680 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8107 loss: 2.8107 2022/10/09 13:53:19 - mmengine - INFO - Epoch(train) [37][1900/2119] lr: 4.0000e-02 eta: 1 day, 0:05:23 time: 0.3613 data_time: 0.0180 memory: 11108 grad_norm: 3.0057 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5675 loss: 2.5675 2022/10/09 13:53:26 - mmengine - INFO - Epoch(train) [37][1920/2119] lr: 4.0000e-02 eta: 1 day, 0:05:15 time: 0.3539 data_time: 0.0196 memory: 11108 grad_norm: 2.9719 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6775 loss: 2.6775 2022/10/09 13:53:33 - mmengine - INFO - Epoch(train) [37][1940/2119] lr: 4.0000e-02 eta: 1 day, 0:05:08 time: 0.3589 data_time: 0.0172 memory: 11108 grad_norm: 3.0225 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7629 loss: 2.7629 2022/10/09 13:53:40 - mmengine - INFO - Epoch(train) [37][1960/2119] lr: 4.0000e-02 eta: 1 day, 0:05:01 time: 0.3582 data_time: 0.0191 memory: 11108 grad_norm: 3.0500 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5931 loss: 2.5931 2022/10/09 13:53:47 - mmengine - INFO - Epoch(train) [37][1980/2119] lr: 4.0000e-02 eta: 1 day, 0:04:53 time: 0.3576 data_time: 0.0196 memory: 11108 grad_norm: 3.0225 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.6206 loss: 2.6206 2022/10/09 13:53:54 - mmengine - INFO - Epoch(train) [37][2000/2119] lr: 4.0000e-02 eta: 1 day, 0:04:46 time: 0.3617 data_time: 0.0192 memory: 11108 grad_norm: 3.0315 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6561 loss: 2.6561 2022/10/09 13:54:02 - mmengine - INFO - Epoch(train) [37][2020/2119] lr: 4.0000e-02 eta: 1 day, 0:04:38 time: 0.3578 data_time: 0.0201 memory: 11108 grad_norm: 3.0344 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7869 loss: 2.7869 2022/10/09 13:54:09 - mmengine - INFO - Epoch(train) [37][2040/2119] lr: 4.0000e-02 eta: 1 day, 0:04:31 time: 0.3581 data_time: 0.0199 memory: 11108 grad_norm: 2.9743 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6630 loss: 2.6630 2022/10/09 13:54:16 - mmengine - INFO - Epoch(train) [37][2060/2119] lr: 4.0000e-02 eta: 1 day, 0:04:23 time: 0.3595 data_time: 0.0191 memory: 11108 grad_norm: 3.0401 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6904 loss: 2.6904 2022/10/09 13:54:23 - mmengine - INFO - Epoch(train) [37][2080/2119] lr: 4.0000e-02 eta: 1 day, 0:04:16 time: 0.3594 data_time: 0.0189 memory: 11108 grad_norm: 3.0845 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6386 loss: 2.6386 2022/10/09 13:54:30 - mmengine - INFO - Epoch(train) [37][2100/2119] lr: 4.0000e-02 eta: 1 day, 0:04:09 time: 0.3601 data_time: 0.0187 memory: 11108 grad_norm: 3.0413 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7567 loss: 2.7567 2022/10/09 13:54:37 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 13:54:37 - mmengine - INFO - Epoch(train) [37][2119/2119] lr: 4.0000e-02 eta: 1 day, 0:04:09 time: 0.3454 data_time: 0.0179 memory: 11108 grad_norm: 2.9747 top1_acc: 0.2000 top5_acc: 0.4000 loss_cls: 2.6273 loss: 2.6273 2022/10/09 13:54:47 - mmengine - INFO - Epoch(train) [38][20/2119] lr: 4.0000e-02 eta: 1 day, 0:03:43 time: 0.5191 data_time: 0.1372 memory: 11108 grad_norm: 2.9898 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5034 loss: 2.5034 2022/10/09 13:54:55 - mmengine - INFO - Epoch(train) [38][40/2119] lr: 4.0000e-02 eta: 1 day, 0:03:36 time: 0.3672 data_time: 0.0226 memory: 11108 grad_norm: 3.0288 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7109 loss: 2.7109 2022/10/09 13:55:02 - mmengine - INFO - Epoch(train) [38][60/2119] lr: 4.0000e-02 eta: 1 day, 0:03:29 time: 0.3585 data_time: 0.0171 memory: 11108 grad_norm: 3.0131 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6348 loss: 2.6348 2022/10/09 13:55:09 - mmengine - INFO - Epoch(train) [38][80/2119] lr: 4.0000e-02 eta: 1 day, 0:03:21 time: 0.3548 data_time: 0.0229 memory: 11108 grad_norm: 2.9676 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.3681 loss: 2.3681 2022/10/09 13:55:16 - mmengine - INFO - Epoch(train) [38][100/2119] lr: 4.0000e-02 eta: 1 day, 0:03:14 time: 0.3576 data_time: 0.0215 memory: 11108 grad_norm: 3.0425 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6363 loss: 2.6363 2022/10/09 13:55:23 - mmengine - INFO - Epoch(train) [38][120/2119] lr: 4.0000e-02 eta: 1 day, 0:03:07 time: 0.3623 data_time: 0.0268 memory: 11108 grad_norm: 2.9830 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7134 loss: 2.7134 2022/10/09 13:55:31 - mmengine - INFO - Epoch(train) [38][140/2119] lr: 4.0000e-02 eta: 1 day, 0:02:59 time: 0.3591 data_time: 0.0211 memory: 11108 grad_norm: 2.9800 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.3935 loss: 2.3935 2022/10/09 13:55:38 - mmengine - INFO - Epoch(train) [38][160/2119] lr: 4.0000e-02 eta: 1 day, 0:02:52 time: 0.3625 data_time: 0.0203 memory: 11108 grad_norm: 2.9824 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5673 loss: 2.5673 2022/10/09 13:55:45 - mmengine - INFO - Epoch(train) [38][180/2119] lr: 4.0000e-02 eta: 1 day, 0:02:44 time: 0.3542 data_time: 0.0208 memory: 11108 grad_norm: 3.0699 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5881 loss: 2.5881 2022/10/09 13:55:52 - mmengine - INFO - Epoch(train) [38][200/2119] lr: 4.0000e-02 eta: 1 day, 0:02:37 time: 0.3613 data_time: 0.0201 memory: 11108 grad_norm: 3.0629 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6084 loss: 2.6084 2022/10/09 13:55:59 - mmengine - INFO - Epoch(train) [38][220/2119] lr: 4.0000e-02 eta: 1 day, 0:02:29 time: 0.3554 data_time: 0.0240 memory: 11108 grad_norm: 3.0414 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5413 loss: 2.5413 2022/10/09 13:56:06 - mmengine - INFO - Epoch(train) [38][240/2119] lr: 4.0000e-02 eta: 1 day, 0:02:22 time: 0.3556 data_time: 0.0237 memory: 11108 grad_norm: 3.0843 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6165 loss: 2.6165 2022/10/09 13:56:14 - mmengine - INFO - Epoch(train) [38][260/2119] lr: 4.0000e-02 eta: 1 day, 0:02:15 time: 0.3626 data_time: 0.0201 memory: 11108 grad_norm: 3.0027 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.4554 loss: 2.4554 2022/10/09 13:56:21 - mmengine - INFO - Epoch(train) [38][280/2119] lr: 4.0000e-02 eta: 1 day, 0:02:07 time: 0.3555 data_time: 0.0187 memory: 11108 grad_norm: 3.0266 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4379 loss: 2.4379 2022/10/09 13:56:28 - mmengine - INFO - Epoch(train) [38][300/2119] lr: 4.0000e-02 eta: 1 day, 0:01:59 time: 0.3574 data_time: 0.0220 memory: 11108 grad_norm: 3.0277 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7958 loss: 2.7958 2022/10/09 13:56:35 - mmengine - INFO - Epoch(train) [38][320/2119] lr: 4.0000e-02 eta: 1 day, 0:01:52 time: 0.3609 data_time: 0.0277 memory: 11108 grad_norm: 3.0166 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6671 loss: 2.6671 2022/10/09 13:56:42 - mmengine - INFO - Epoch(train) [38][340/2119] lr: 4.0000e-02 eta: 1 day, 0:01:45 time: 0.3562 data_time: 0.0207 memory: 11108 grad_norm: 3.0682 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.5260 loss: 2.5260 2022/10/09 13:56:49 - mmengine - INFO - Epoch(train) [38][360/2119] lr: 4.0000e-02 eta: 1 day, 0:01:37 time: 0.3621 data_time: 0.0218 memory: 11108 grad_norm: 2.9987 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5929 loss: 2.5929 2022/10/09 13:56:57 - mmengine - INFO - Epoch(train) [38][380/2119] lr: 4.0000e-02 eta: 1 day, 0:01:30 time: 0.3614 data_time: 0.0185 memory: 11108 grad_norm: 3.0391 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.3985 loss: 2.3985 2022/10/09 13:57:04 - mmengine - INFO - Epoch(train) [38][400/2119] lr: 4.0000e-02 eta: 1 day, 0:01:22 time: 0.3556 data_time: 0.0218 memory: 11108 grad_norm: 3.0315 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4752 loss: 2.4752 2022/10/09 13:57:11 - mmengine - INFO - Epoch(train) [38][420/2119] lr: 4.0000e-02 eta: 1 day, 0:01:15 time: 0.3601 data_time: 0.0214 memory: 11108 grad_norm: 2.9943 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5821 loss: 2.5821 2022/10/09 13:57:18 - mmengine - INFO - Epoch(train) [38][440/2119] lr: 4.0000e-02 eta: 1 day, 0:01:08 time: 0.3605 data_time: 0.0195 memory: 11108 grad_norm: 3.0626 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.3350 loss: 2.3350 2022/10/09 13:57:25 - mmengine - INFO - Epoch(train) [38][460/2119] lr: 4.0000e-02 eta: 1 day, 0:01:00 time: 0.3547 data_time: 0.0225 memory: 11108 grad_norm: 3.0261 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6074 loss: 2.6074 2022/10/09 13:57:33 - mmengine - INFO - Epoch(train) [38][480/2119] lr: 4.0000e-02 eta: 1 day, 0:00:53 time: 0.3624 data_time: 0.0244 memory: 11108 grad_norm: 3.0066 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7084 loss: 2.7084 2022/10/09 13:57:40 - mmengine - INFO - Epoch(train) [38][500/2119] lr: 4.0000e-02 eta: 1 day, 0:00:45 time: 0.3562 data_time: 0.0190 memory: 11108 grad_norm: 3.0314 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5261 loss: 2.5261 2022/10/09 13:57:47 - mmengine - INFO - Epoch(train) [38][520/2119] lr: 4.0000e-02 eta: 1 day, 0:00:38 time: 0.3577 data_time: 0.0213 memory: 11108 grad_norm: 2.9849 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3930 loss: 2.3930 2022/10/09 13:57:54 - mmengine - INFO - Epoch(train) [38][540/2119] lr: 4.0000e-02 eta: 1 day, 0:00:31 time: 0.3599 data_time: 0.0181 memory: 11108 grad_norm: 3.0068 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8857 loss: 2.8857 2022/10/09 13:58:01 - mmengine - INFO - Epoch(train) [38][560/2119] lr: 4.0000e-02 eta: 1 day, 0:00:24 time: 0.3653 data_time: 0.0204 memory: 11108 grad_norm: 3.0200 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 2.6679 loss: 2.6679 2022/10/09 13:58:09 - mmengine - INFO - Epoch(train) [38][580/2119] lr: 4.0000e-02 eta: 1 day, 0:00:16 time: 0.3586 data_time: 0.0207 memory: 11108 grad_norm: 2.9957 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8430 loss: 2.8430 2022/10/09 13:58:15 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 13:58:16 - mmengine - INFO - Epoch(train) [38][600/2119] lr: 4.0000e-02 eta: 1 day, 0:00:08 time: 0.3542 data_time: 0.0183 memory: 11108 grad_norm: 2.9702 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6942 loss: 2.6942 2022/10/09 13:58:23 - mmengine - INFO - Epoch(train) [38][620/2119] lr: 4.0000e-02 eta: 1 day, 0:00:01 time: 0.3576 data_time: 0.0151 memory: 11108 grad_norm: 3.0442 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.4876 loss: 2.4876 2022/10/09 13:58:30 - mmengine - INFO - Epoch(train) [38][640/2119] lr: 4.0000e-02 eta: 23:59:54 time: 0.3686 data_time: 0.0208 memory: 11108 grad_norm: 2.9688 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7170 loss: 2.7170 2022/10/09 13:58:37 - mmengine - INFO - Epoch(train) [38][660/2119] lr: 4.0000e-02 eta: 23:59:47 time: 0.3586 data_time: 0.0207 memory: 11108 grad_norm: 3.0060 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.4908 loss: 2.4908 2022/10/09 13:58:45 - mmengine - INFO - Epoch(train) [38][680/2119] lr: 4.0000e-02 eta: 23:59:39 time: 0.3597 data_time: 0.0192 memory: 11108 grad_norm: 2.9267 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6752 loss: 2.6752 2022/10/09 13:58:52 - mmengine - INFO - Epoch(train) [38][700/2119] lr: 4.0000e-02 eta: 23:59:32 time: 0.3563 data_time: 0.0194 memory: 11108 grad_norm: 3.0286 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5577 loss: 2.5577 2022/10/09 13:58:59 - mmengine - INFO - Epoch(train) [38][720/2119] lr: 4.0000e-02 eta: 23:59:24 time: 0.3567 data_time: 0.0236 memory: 11108 grad_norm: 2.9727 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6700 loss: 2.6700 2022/10/09 13:59:06 - mmengine - INFO - Epoch(train) [38][740/2119] lr: 4.0000e-02 eta: 23:59:17 time: 0.3595 data_time: 0.0242 memory: 11108 grad_norm: 2.9922 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3906 loss: 2.3906 2022/10/09 13:59:13 - mmengine - INFO - Epoch(train) [38][760/2119] lr: 4.0000e-02 eta: 23:59:09 time: 0.3591 data_time: 0.0205 memory: 11108 grad_norm: 3.0800 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5241 loss: 2.5241 2022/10/09 13:59:20 - mmengine - INFO - Epoch(train) [38][780/2119] lr: 4.0000e-02 eta: 23:59:02 time: 0.3590 data_time: 0.0253 memory: 11108 grad_norm: 3.0896 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7283 loss: 2.7283 2022/10/09 13:59:27 - mmengine - INFO - Epoch(train) [38][800/2119] lr: 4.0000e-02 eta: 23:58:54 time: 0.3554 data_time: 0.0190 memory: 11108 grad_norm: 3.0188 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6552 loss: 2.6552 2022/10/09 13:59:35 - mmengine - INFO - Epoch(train) [38][820/2119] lr: 4.0000e-02 eta: 23:58:47 time: 0.3601 data_time: 0.0198 memory: 11108 grad_norm: 3.0139 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6227 loss: 2.6227 2022/10/09 13:59:42 - mmengine - INFO - Epoch(train) [38][840/2119] lr: 4.0000e-02 eta: 23:58:40 time: 0.3567 data_time: 0.0245 memory: 11108 grad_norm: 3.0355 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5124 loss: 2.5124 2022/10/09 13:59:49 - mmengine - INFO - Epoch(train) [38][860/2119] lr: 4.0000e-02 eta: 23:58:32 time: 0.3612 data_time: 0.0223 memory: 11108 grad_norm: 3.1045 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6060 loss: 2.6060 2022/10/09 13:59:56 - mmengine - INFO - Epoch(train) [38][880/2119] lr: 4.0000e-02 eta: 23:58:25 time: 0.3533 data_time: 0.0202 memory: 11108 grad_norm: 3.0372 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7964 loss: 2.7964 2022/10/09 14:00:03 - mmengine - INFO - Epoch(train) [38][900/2119] lr: 4.0000e-02 eta: 23:58:17 time: 0.3591 data_time: 0.0217 memory: 11108 grad_norm: 2.9755 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5993 loss: 2.5993 2022/10/09 14:00:10 - mmengine - INFO - Epoch(train) [38][920/2119] lr: 4.0000e-02 eta: 23:58:10 time: 0.3572 data_time: 0.0227 memory: 11108 grad_norm: 3.0533 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7435 loss: 2.7435 2022/10/09 14:00:18 - mmengine - INFO - Epoch(train) [38][940/2119] lr: 4.0000e-02 eta: 23:58:02 time: 0.3620 data_time: 0.0192 memory: 11108 grad_norm: 3.0665 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4519 loss: 2.4519 2022/10/09 14:00:25 - mmengine - INFO - Epoch(train) [38][960/2119] lr: 4.0000e-02 eta: 23:57:56 time: 0.3678 data_time: 0.0205 memory: 11108 grad_norm: 3.0180 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6727 loss: 2.6727 2022/10/09 14:00:32 - mmengine - INFO - Epoch(train) [38][980/2119] lr: 4.0000e-02 eta: 23:57:48 time: 0.3584 data_time: 0.0183 memory: 11108 grad_norm: 3.0219 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.3834 loss: 2.3834 2022/10/09 14:00:40 - mmengine - INFO - Epoch(train) [38][1000/2119] lr: 4.0000e-02 eta: 23:57:41 time: 0.3672 data_time: 0.0236 memory: 11108 grad_norm: 3.0358 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4227 loss: 2.4227 2022/10/09 14:00:47 - mmengine - INFO - Epoch(train) [38][1020/2119] lr: 4.0000e-02 eta: 23:57:34 time: 0.3596 data_time: 0.0181 memory: 11108 grad_norm: 3.0216 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5110 loss: 2.5110 2022/10/09 14:00:54 - mmengine - INFO - Epoch(train) [38][1040/2119] lr: 4.0000e-02 eta: 23:57:27 time: 0.3703 data_time: 0.0197 memory: 11108 grad_norm: 3.0555 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6924 loss: 2.6924 2022/10/09 14:01:01 - mmengine - INFO - Epoch(train) [38][1060/2119] lr: 4.0000e-02 eta: 23:57:20 time: 0.3597 data_time: 0.0197 memory: 11108 grad_norm: 3.0423 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4969 loss: 2.4969 2022/10/09 14:01:09 - mmengine - INFO - Epoch(train) [38][1080/2119] lr: 4.0000e-02 eta: 23:57:13 time: 0.3631 data_time: 0.0222 memory: 11108 grad_norm: 3.0787 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.4247 loss: 2.4247 2022/10/09 14:01:16 - mmengine - INFO - Epoch(train) [38][1100/2119] lr: 4.0000e-02 eta: 23:57:05 time: 0.3551 data_time: 0.0183 memory: 11108 grad_norm: 3.0710 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5724 loss: 2.5724 2022/10/09 14:01:23 - mmengine - INFO - Epoch(train) [38][1120/2119] lr: 4.0000e-02 eta: 23:56:58 time: 0.3591 data_time: 0.0202 memory: 11108 grad_norm: 3.0177 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5853 loss: 2.5853 2022/10/09 14:01:30 - mmengine - INFO - Epoch(train) [38][1140/2119] lr: 4.0000e-02 eta: 23:56:50 time: 0.3608 data_time: 0.0227 memory: 11108 grad_norm: 3.0743 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5254 loss: 2.5254 2022/10/09 14:01:37 - mmengine - INFO - Epoch(train) [38][1160/2119] lr: 4.0000e-02 eta: 23:56:43 time: 0.3571 data_time: 0.0201 memory: 11108 grad_norm: 2.9939 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6212 loss: 2.6212 2022/10/09 14:01:44 - mmengine - INFO - Epoch(train) [38][1180/2119] lr: 4.0000e-02 eta: 23:56:35 time: 0.3556 data_time: 0.0205 memory: 11108 grad_norm: 3.0663 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.6803 loss: 2.6803 2022/10/09 14:01:52 - mmengine - INFO - Epoch(train) [38][1200/2119] lr: 4.0000e-02 eta: 23:56:28 time: 0.3638 data_time: 0.0228 memory: 11108 grad_norm: 2.9895 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7154 loss: 2.7154 2022/10/09 14:01:59 - mmengine - INFO - Epoch(train) [38][1220/2119] lr: 4.0000e-02 eta: 23:56:20 time: 0.3559 data_time: 0.0207 memory: 11108 grad_norm: 3.0740 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4339 loss: 2.4339 2022/10/09 14:02:06 - mmengine - INFO - Epoch(train) [38][1240/2119] lr: 4.0000e-02 eta: 23:56:13 time: 0.3598 data_time: 0.0220 memory: 11108 grad_norm: 3.1065 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6999 loss: 2.6999 2022/10/09 14:02:13 - mmengine - INFO - Epoch(train) [38][1260/2119] lr: 4.0000e-02 eta: 23:56:06 time: 0.3596 data_time: 0.0233 memory: 11108 grad_norm: 3.0292 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7387 loss: 2.7387 2022/10/09 14:02:20 - mmengine - INFO - Epoch(train) [38][1280/2119] lr: 4.0000e-02 eta: 23:55:59 time: 0.3670 data_time: 0.0259 memory: 11108 grad_norm: 3.0262 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4648 loss: 2.4648 2022/10/09 14:02:28 - mmengine - INFO - Epoch(train) [38][1300/2119] lr: 4.0000e-02 eta: 23:55:52 time: 0.3611 data_time: 0.0216 memory: 11108 grad_norm: 3.0303 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6380 loss: 2.6380 2022/10/09 14:02:35 - mmengine - INFO - Epoch(train) [38][1320/2119] lr: 4.0000e-02 eta: 23:55:44 time: 0.3560 data_time: 0.0204 memory: 11108 grad_norm: 3.0235 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6326 loss: 2.6326 2022/10/09 14:02:42 - mmengine - INFO - Epoch(train) [38][1340/2119] lr: 4.0000e-02 eta: 23:55:37 time: 0.3610 data_time: 0.0176 memory: 11108 grad_norm: 3.0101 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9648 loss: 2.9648 2022/10/09 14:02:49 - mmengine - INFO - Epoch(train) [38][1360/2119] lr: 4.0000e-02 eta: 23:55:29 time: 0.3588 data_time: 0.0194 memory: 11108 grad_norm: 2.9867 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5308 loss: 2.5308 2022/10/09 14:02:56 - mmengine - INFO - Epoch(train) [38][1380/2119] lr: 4.0000e-02 eta: 23:55:22 time: 0.3559 data_time: 0.0163 memory: 11108 grad_norm: 2.9884 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.3140 loss: 2.3140 2022/10/09 14:03:04 - mmengine - INFO - Epoch(train) [38][1400/2119] lr: 4.0000e-02 eta: 23:55:14 time: 0.3607 data_time: 0.0208 memory: 11108 grad_norm: 3.0682 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6081 loss: 2.6081 2022/10/09 14:03:11 - mmengine - INFO - Epoch(train) [38][1420/2119] lr: 4.0000e-02 eta: 23:55:07 time: 0.3602 data_time: 0.0179 memory: 11108 grad_norm: 3.0403 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5953 loss: 2.5953 2022/10/09 14:03:18 - mmengine - INFO - Epoch(train) [38][1440/2119] lr: 4.0000e-02 eta: 23:55:00 time: 0.3573 data_time: 0.0231 memory: 11108 grad_norm: 3.0238 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6815 loss: 2.6815 2022/10/09 14:03:25 - mmengine - INFO - Epoch(train) [38][1460/2119] lr: 4.0000e-02 eta: 23:54:53 time: 0.3687 data_time: 0.0199 memory: 11108 grad_norm: 2.9640 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.7895 loss: 2.7895 2022/10/09 14:03:33 - mmengine - INFO - Epoch(train) [38][1480/2119] lr: 4.0000e-02 eta: 23:54:45 time: 0.3600 data_time: 0.0191 memory: 11108 grad_norm: 3.0207 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7851 loss: 2.7851 2022/10/09 14:03:40 - mmengine - INFO - Epoch(train) [38][1500/2119] lr: 4.0000e-02 eta: 23:54:38 time: 0.3634 data_time: 0.0192 memory: 11108 grad_norm: 2.9987 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.4381 loss: 2.4381 2022/10/09 14:03:47 - mmengine - INFO - Epoch(train) [38][1520/2119] lr: 4.0000e-02 eta: 23:54:31 time: 0.3579 data_time: 0.0195 memory: 11108 grad_norm: 2.9876 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5407 loss: 2.5407 2022/10/09 14:03:54 - mmengine - INFO - Epoch(train) [38][1540/2119] lr: 4.0000e-02 eta: 23:54:23 time: 0.3585 data_time: 0.0225 memory: 11108 grad_norm: 2.9653 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6078 loss: 2.6078 2022/10/09 14:04:01 - mmengine - INFO - Epoch(train) [38][1560/2119] lr: 4.0000e-02 eta: 23:54:16 time: 0.3607 data_time: 0.0195 memory: 11108 grad_norm: 3.0349 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.7093 loss: 2.7093 2022/10/09 14:04:09 - mmengine - INFO - Epoch(train) [38][1580/2119] lr: 4.0000e-02 eta: 23:54:09 time: 0.3661 data_time: 0.0168 memory: 11108 grad_norm: 3.0068 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5475 loss: 2.5475 2022/10/09 14:04:15 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 14:04:16 - mmengine - INFO - Epoch(train) [38][1600/2119] lr: 4.0000e-02 eta: 23:54:02 time: 0.3628 data_time: 0.0217 memory: 11108 grad_norm: 2.9928 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5361 loss: 2.5361 2022/10/09 14:04:23 - mmengine - INFO - Epoch(train) [38][1620/2119] lr: 4.0000e-02 eta: 23:53:55 time: 0.3656 data_time: 0.0219 memory: 11108 grad_norm: 3.0304 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5786 loss: 2.5786 2022/10/09 14:04:30 - mmengine - INFO - Epoch(train) [38][1640/2119] lr: 4.0000e-02 eta: 23:53:47 time: 0.3585 data_time: 0.0204 memory: 11108 grad_norm: 3.0427 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7518 loss: 2.7518 2022/10/09 14:04:38 - mmengine - INFO - Epoch(train) [38][1660/2119] lr: 4.0000e-02 eta: 23:53:40 time: 0.3578 data_time: 0.0203 memory: 11108 grad_norm: 3.0395 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7953 loss: 2.7953 2022/10/09 14:04:45 - mmengine - INFO - Epoch(train) [38][1680/2119] lr: 4.0000e-02 eta: 23:53:33 time: 0.3648 data_time: 0.0195 memory: 11108 grad_norm: 3.0085 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6124 loss: 2.6124 2022/10/09 14:04:52 - mmengine - INFO - Epoch(train) [38][1700/2119] lr: 4.0000e-02 eta: 23:53:26 time: 0.3585 data_time: 0.0224 memory: 11108 grad_norm: 3.0102 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4630 loss: 2.4630 2022/10/09 14:04:59 - mmengine - INFO - Epoch(train) [38][1720/2119] lr: 4.0000e-02 eta: 23:53:18 time: 0.3570 data_time: 0.0208 memory: 11108 grad_norm: 2.9807 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5408 loss: 2.5408 2022/10/09 14:05:06 - mmengine - INFO - Epoch(train) [38][1740/2119] lr: 4.0000e-02 eta: 23:53:11 time: 0.3597 data_time: 0.0208 memory: 11108 grad_norm: 3.0383 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6904 loss: 2.6904 2022/10/09 14:05:14 - mmengine - INFO - Epoch(train) [38][1760/2119] lr: 4.0000e-02 eta: 23:53:03 time: 0.3592 data_time: 0.0199 memory: 11108 grad_norm: 3.0209 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5976 loss: 2.5976 2022/10/09 14:05:21 - mmengine - INFO - Epoch(train) [38][1780/2119] lr: 4.0000e-02 eta: 23:52:56 time: 0.3592 data_time: 0.0184 memory: 11108 grad_norm: 3.0273 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6374 loss: 2.6374 2022/10/09 14:05:28 - mmengine - INFO - Epoch(train) [38][1800/2119] lr: 4.0000e-02 eta: 23:52:49 time: 0.3624 data_time: 0.0215 memory: 11108 grad_norm: 3.0398 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5680 loss: 2.5680 2022/10/09 14:05:35 - mmengine - INFO - Epoch(train) [38][1820/2119] lr: 4.0000e-02 eta: 23:52:41 time: 0.3575 data_time: 0.0178 memory: 11108 grad_norm: 3.0369 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.4795 loss: 2.4795 2022/10/09 14:05:42 - mmengine - INFO - Epoch(train) [38][1840/2119] lr: 4.0000e-02 eta: 23:52:34 time: 0.3611 data_time: 0.0205 memory: 11108 grad_norm: 2.9648 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6345 loss: 2.6345 2022/10/09 14:05:50 - mmengine - INFO - Epoch(train) [38][1860/2119] lr: 4.0000e-02 eta: 23:52:26 time: 0.3577 data_time: 0.0223 memory: 11108 grad_norm: 3.0536 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7713 loss: 2.7713 2022/10/09 14:05:57 - mmengine - INFO - Epoch(train) [38][1880/2119] lr: 4.0000e-02 eta: 23:52:19 time: 0.3541 data_time: 0.0228 memory: 11108 grad_norm: 3.0116 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5134 loss: 2.5134 2022/10/09 14:06:04 - mmengine - INFO - Epoch(train) [38][1900/2119] lr: 4.0000e-02 eta: 23:52:12 time: 0.3671 data_time: 0.0194 memory: 11108 grad_norm: 3.0115 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8856 loss: 2.8856 2022/10/09 14:06:11 - mmengine - INFO - Epoch(train) [38][1920/2119] lr: 4.0000e-02 eta: 23:52:04 time: 0.3546 data_time: 0.0204 memory: 11108 grad_norm: 3.0141 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6815 loss: 2.6815 2022/10/09 14:06:18 - mmengine - INFO - Epoch(train) [38][1940/2119] lr: 4.0000e-02 eta: 23:51:57 time: 0.3554 data_time: 0.0205 memory: 11108 grad_norm: 3.0727 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5133 loss: 2.5133 2022/10/09 14:06:25 - mmengine - INFO - Epoch(train) [38][1960/2119] lr: 4.0000e-02 eta: 23:51:49 time: 0.3599 data_time: 0.0239 memory: 11108 grad_norm: 3.0297 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6968 loss: 2.6968 2022/10/09 14:06:33 - mmengine - INFO - Epoch(train) [38][1980/2119] lr: 4.0000e-02 eta: 23:51:42 time: 0.3605 data_time: 0.0242 memory: 11108 grad_norm: 3.0117 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6300 loss: 2.6300 2022/10/09 14:06:40 - mmengine - INFO - Epoch(train) [38][2000/2119] lr: 4.0000e-02 eta: 23:51:35 time: 0.3655 data_time: 0.0196 memory: 11108 grad_norm: 3.0497 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6344 loss: 2.6344 2022/10/09 14:06:47 - mmengine - INFO - Epoch(train) [38][2020/2119] lr: 4.0000e-02 eta: 23:51:27 time: 0.3560 data_time: 0.0237 memory: 11108 grad_norm: 3.0562 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7070 loss: 2.7070 2022/10/09 14:06:54 - mmengine - INFO - Epoch(train) [38][2040/2119] lr: 4.0000e-02 eta: 23:51:20 time: 0.3569 data_time: 0.0244 memory: 11108 grad_norm: 3.0322 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5032 loss: 2.5032 2022/10/09 14:07:01 - mmengine - INFO - Epoch(train) [38][2060/2119] lr: 4.0000e-02 eta: 23:51:12 time: 0.3599 data_time: 0.0230 memory: 11108 grad_norm: 3.0663 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8278 loss: 2.8278 2022/10/09 14:07:08 - mmengine - INFO - Epoch(train) [38][2080/2119] lr: 4.0000e-02 eta: 23:51:05 time: 0.3549 data_time: 0.0192 memory: 11108 grad_norm: 3.0130 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6650 loss: 2.6650 2022/10/09 14:07:16 - mmengine - INFO - Epoch(train) [38][2100/2119] lr: 4.0000e-02 eta: 23:50:58 time: 0.3617 data_time: 0.0193 memory: 11108 grad_norm: 3.0368 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5500 loss: 2.5500 2022/10/09 14:07:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 14:07:22 - mmengine - INFO - Epoch(train) [38][2119/2119] lr: 4.0000e-02 eta: 23:50:58 time: 0.3425 data_time: 0.0182 memory: 11108 grad_norm: 3.0672 top1_acc: 0.5000 top5_acc: 0.7000 loss_cls: 2.8749 loss: 2.8749 2022/10/09 14:07:33 - mmengine - INFO - Epoch(train) [39][20/2119] lr: 4.0000e-02 eta: 23:50:33 time: 0.5335 data_time: 0.1173 memory: 11108 grad_norm: 2.9860 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4432 loss: 2.4432 2022/10/09 14:07:40 - mmengine - INFO - Epoch(train) [39][40/2119] lr: 4.0000e-02 eta: 23:50:26 time: 0.3634 data_time: 0.0217 memory: 11108 grad_norm: 3.0579 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5176 loss: 2.5176 2022/10/09 14:07:47 - mmengine - INFO - Epoch(train) [39][60/2119] lr: 4.0000e-02 eta: 23:50:19 time: 0.3571 data_time: 0.0182 memory: 11108 grad_norm: 3.0507 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7712 loss: 2.7712 2022/10/09 14:07:55 - mmengine - INFO - Epoch(train) [39][80/2119] lr: 4.0000e-02 eta: 23:50:11 time: 0.3611 data_time: 0.0204 memory: 11108 grad_norm: 3.0023 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7258 loss: 2.7258 2022/10/09 14:08:02 - mmengine - INFO - Epoch(train) [39][100/2119] lr: 4.0000e-02 eta: 23:50:04 time: 0.3600 data_time: 0.0189 memory: 11108 grad_norm: 2.9738 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7130 loss: 2.7130 2022/10/09 14:08:09 - mmengine - INFO - Epoch(train) [39][120/2119] lr: 4.0000e-02 eta: 23:49:57 time: 0.3609 data_time: 0.0258 memory: 11108 grad_norm: 2.9986 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5161 loss: 2.5161 2022/10/09 14:08:16 - mmengine - INFO - Epoch(train) [39][140/2119] lr: 4.0000e-02 eta: 23:49:49 time: 0.3598 data_time: 0.0221 memory: 11108 grad_norm: 2.9874 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7359 loss: 2.7359 2022/10/09 14:08:23 - mmengine - INFO - Epoch(train) [39][160/2119] lr: 4.0000e-02 eta: 23:49:42 time: 0.3580 data_time: 0.0208 memory: 11108 grad_norm: 3.0388 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4328 loss: 2.4328 2022/10/09 14:08:30 - mmengine - INFO - Epoch(train) [39][180/2119] lr: 4.0000e-02 eta: 23:49:34 time: 0.3559 data_time: 0.0194 memory: 11108 grad_norm: 3.0171 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6137 loss: 2.6137 2022/10/09 14:08:38 - mmengine - INFO - Epoch(train) [39][200/2119] lr: 4.0000e-02 eta: 23:49:27 time: 0.3576 data_time: 0.0207 memory: 11108 grad_norm: 2.9768 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4804 loss: 2.4804 2022/10/09 14:08:45 - mmengine - INFO - Epoch(train) [39][220/2119] lr: 4.0000e-02 eta: 23:49:20 time: 0.3615 data_time: 0.0205 memory: 11108 grad_norm: 2.9986 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4604 loss: 2.4604 2022/10/09 14:08:52 - mmengine - INFO - Epoch(train) [39][240/2119] lr: 4.0000e-02 eta: 23:49:12 time: 0.3578 data_time: 0.0232 memory: 11108 grad_norm: 3.0365 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6780 loss: 2.6780 2022/10/09 14:08:59 - mmengine - INFO - Epoch(train) [39][260/2119] lr: 4.0000e-02 eta: 23:49:05 time: 0.3570 data_time: 0.0207 memory: 11108 grad_norm: 3.0370 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4113 loss: 2.4113 2022/10/09 14:09:06 - mmengine - INFO - Epoch(train) [39][280/2119] lr: 4.0000e-02 eta: 23:48:57 time: 0.3580 data_time: 0.0202 memory: 11108 grad_norm: 3.0708 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4309 loss: 2.4309 2022/10/09 14:09:13 - mmengine - INFO - Epoch(train) [39][300/2119] lr: 4.0000e-02 eta: 23:48:50 time: 0.3573 data_time: 0.0197 memory: 11108 grad_norm: 3.0953 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6407 loss: 2.6407 2022/10/09 14:09:21 - mmengine - INFO - Epoch(train) [39][320/2119] lr: 4.0000e-02 eta: 23:48:42 time: 0.3574 data_time: 0.0255 memory: 11108 grad_norm: 3.0360 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8241 loss: 2.8241 2022/10/09 14:09:28 - mmengine - INFO - Epoch(train) [39][340/2119] lr: 4.0000e-02 eta: 23:48:35 time: 0.3566 data_time: 0.0227 memory: 11108 grad_norm: 3.0047 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6840 loss: 2.6840 2022/10/09 14:09:35 - mmengine - INFO - Epoch(train) [39][360/2119] lr: 4.0000e-02 eta: 23:48:28 time: 0.3693 data_time: 0.0173 memory: 11108 grad_norm: 3.0069 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7917 loss: 2.7917 2022/10/09 14:09:42 - mmengine - INFO - Epoch(train) [39][380/2119] lr: 4.0000e-02 eta: 23:48:21 time: 0.3623 data_time: 0.0237 memory: 11108 grad_norm: 3.0573 top1_acc: 0.1875 top5_acc: 0.8750 loss_cls: 2.7606 loss: 2.7606 2022/10/09 14:09:50 - mmengine - INFO - Epoch(train) [39][400/2119] lr: 4.0000e-02 eta: 23:48:13 time: 0.3581 data_time: 0.0198 memory: 11108 grad_norm: 3.0376 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5509 loss: 2.5509 2022/10/09 14:09:57 - mmengine - INFO - Epoch(train) [39][420/2119] lr: 4.0000e-02 eta: 23:48:06 time: 0.3578 data_time: 0.0198 memory: 11108 grad_norm: 2.9903 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3107 loss: 2.3107 2022/10/09 14:10:04 - mmengine - INFO - Epoch(train) [39][440/2119] lr: 4.0000e-02 eta: 23:47:59 time: 0.3594 data_time: 0.0196 memory: 11108 grad_norm: 3.0139 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7215 loss: 2.7215 2022/10/09 14:10:11 - mmengine - INFO - Epoch(train) [39][460/2119] lr: 4.0000e-02 eta: 23:47:51 time: 0.3581 data_time: 0.0191 memory: 11108 grad_norm: 3.0029 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4769 loss: 2.4769 2022/10/09 14:10:17 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 14:10:18 - mmengine - INFO - Epoch(train) [39][480/2119] lr: 4.0000e-02 eta: 23:47:44 time: 0.3560 data_time: 0.0219 memory: 11108 grad_norm: 3.0333 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.3684 loss: 2.3684 2022/10/09 14:10:25 - mmengine - INFO - Epoch(train) [39][500/2119] lr: 4.0000e-02 eta: 23:47:36 time: 0.3578 data_time: 0.0198 memory: 11108 grad_norm: 2.9835 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6952 loss: 2.6952 2022/10/09 14:10:32 - mmengine - INFO - Epoch(train) [39][520/2119] lr: 4.0000e-02 eta: 23:47:29 time: 0.3576 data_time: 0.0207 memory: 11108 grad_norm: 3.0157 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4048 loss: 2.4048 2022/10/09 14:10:40 - mmengine - INFO - Epoch(train) [39][540/2119] lr: 4.0000e-02 eta: 23:47:22 time: 0.3705 data_time: 0.0200 memory: 11108 grad_norm: 3.0447 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5689 loss: 2.5689 2022/10/09 14:10:47 - mmengine - INFO - Epoch(train) [39][560/2119] lr: 4.0000e-02 eta: 23:47:15 time: 0.3601 data_time: 0.0261 memory: 11108 grad_norm: 2.9868 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4117 loss: 2.4117 2022/10/09 14:10:54 - mmengine - INFO - Epoch(train) [39][580/2119] lr: 4.0000e-02 eta: 23:47:07 time: 0.3563 data_time: 0.0224 memory: 11108 grad_norm: 2.9738 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5790 loss: 2.5790 2022/10/09 14:11:02 - mmengine - INFO - Epoch(train) [39][600/2119] lr: 4.0000e-02 eta: 23:47:00 time: 0.3667 data_time: 0.0197 memory: 11108 grad_norm: 3.0394 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3992 loss: 2.3992 2022/10/09 14:11:09 - mmengine - INFO - Epoch(train) [39][620/2119] lr: 4.0000e-02 eta: 23:46:52 time: 0.3549 data_time: 0.0193 memory: 11108 grad_norm: 3.0278 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6490 loss: 2.6490 2022/10/09 14:11:16 - mmengine - INFO - Epoch(train) [39][640/2119] lr: 4.0000e-02 eta: 23:46:45 time: 0.3642 data_time: 0.0201 memory: 11108 grad_norm: 2.9635 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6291 loss: 2.6291 2022/10/09 14:11:23 - mmengine - INFO - Epoch(train) [39][660/2119] lr: 4.0000e-02 eta: 23:46:38 time: 0.3620 data_time: 0.0225 memory: 11108 grad_norm: 2.9872 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6549 loss: 2.6549 2022/10/09 14:11:30 - mmengine - INFO - Epoch(train) [39][680/2119] lr: 4.0000e-02 eta: 23:46:31 time: 0.3588 data_time: 0.0234 memory: 11108 grad_norm: 3.0164 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5565 loss: 2.5565 2022/10/09 14:11:38 - mmengine - INFO - Epoch(train) [39][700/2119] lr: 4.0000e-02 eta: 23:46:23 time: 0.3613 data_time: 0.0212 memory: 11108 grad_norm: 3.0091 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7388 loss: 2.7388 2022/10/09 14:11:45 - mmengine - INFO - Epoch(train) [39][720/2119] lr: 4.0000e-02 eta: 23:46:16 time: 0.3560 data_time: 0.0214 memory: 11108 grad_norm: 3.0466 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6742 loss: 2.6742 2022/10/09 14:11:52 - mmengine - INFO - Epoch(train) [39][740/2119] lr: 4.0000e-02 eta: 23:46:09 time: 0.3584 data_time: 0.0213 memory: 11108 grad_norm: 3.0446 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6792 loss: 2.6792 2022/10/09 14:11:59 - mmengine - INFO - Epoch(train) [39][760/2119] lr: 4.0000e-02 eta: 23:46:01 time: 0.3631 data_time: 0.0253 memory: 11108 grad_norm: 3.0034 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5566 loss: 2.5566 2022/10/09 14:12:06 - mmengine - INFO - Epoch(train) [39][780/2119] lr: 4.0000e-02 eta: 23:45:54 time: 0.3582 data_time: 0.0173 memory: 11108 grad_norm: 3.0618 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6448 loss: 2.6448 2022/10/09 14:12:13 - mmengine - INFO - Epoch(train) [39][800/2119] lr: 4.0000e-02 eta: 23:45:46 time: 0.3576 data_time: 0.0218 memory: 11108 grad_norm: 3.0158 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7478 loss: 2.7478 2022/10/09 14:12:21 - mmengine - INFO - Epoch(train) [39][820/2119] lr: 4.0000e-02 eta: 23:45:39 time: 0.3634 data_time: 0.0189 memory: 11108 grad_norm: 2.9961 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7308 loss: 2.7308 2022/10/09 14:12:28 - mmengine - INFO - Epoch(train) [39][840/2119] lr: 4.0000e-02 eta: 23:45:32 time: 0.3575 data_time: 0.0196 memory: 11108 grad_norm: 2.9450 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5011 loss: 2.5011 2022/10/09 14:12:35 - mmengine - INFO - Epoch(train) [39][860/2119] lr: 4.0000e-02 eta: 23:45:24 time: 0.3599 data_time: 0.0207 memory: 11108 grad_norm: 3.0473 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5029 loss: 2.5029 2022/10/09 14:12:42 - mmengine - INFO - Epoch(train) [39][880/2119] lr: 4.0000e-02 eta: 23:45:17 time: 0.3573 data_time: 0.0248 memory: 11108 grad_norm: 3.1026 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6457 loss: 2.6457 2022/10/09 14:12:49 - mmengine - INFO - Epoch(train) [39][900/2119] lr: 4.0000e-02 eta: 23:45:10 time: 0.3587 data_time: 0.0207 memory: 11108 grad_norm: 3.0560 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7115 loss: 2.7115 2022/10/09 14:12:57 - mmengine - INFO - Epoch(train) [39][920/2119] lr: 4.0000e-02 eta: 23:45:03 time: 0.3668 data_time: 0.0221 memory: 11108 grad_norm: 2.9976 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 3.0091 loss: 3.0091 2022/10/09 14:13:04 - mmengine - INFO - Epoch(train) [39][940/2119] lr: 4.0000e-02 eta: 23:44:55 time: 0.3563 data_time: 0.0234 memory: 11108 grad_norm: 2.9757 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5480 loss: 2.5480 2022/10/09 14:13:11 - mmengine - INFO - Epoch(train) [39][960/2119] lr: 4.0000e-02 eta: 23:44:48 time: 0.3617 data_time: 0.0202 memory: 11108 grad_norm: 3.0576 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6847 loss: 2.6847 2022/10/09 14:13:18 - mmengine - INFO - Epoch(train) [39][980/2119] lr: 4.0000e-02 eta: 23:44:40 time: 0.3551 data_time: 0.0202 memory: 11108 grad_norm: 3.0632 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6804 loss: 2.6804 2022/10/09 14:13:26 - mmengine - INFO - Epoch(train) [39][1000/2119] lr: 4.0000e-02 eta: 23:44:33 time: 0.3660 data_time: 0.0194 memory: 11108 grad_norm: 3.0072 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7624 loss: 2.7624 2022/10/09 14:13:33 - mmengine - INFO - Epoch(train) [39][1020/2119] lr: 4.0000e-02 eta: 23:44:26 time: 0.3578 data_time: 0.0207 memory: 11108 grad_norm: 3.0404 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7661 loss: 2.7661 2022/10/09 14:13:40 - mmengine - INFO - Epoch(train) [39][1040/2119] lr: 4.0000e-02 eta: 23:44:18 time: 0.3555 data_time: 0.0194 memory: 11108 grad_norm: 3.0808 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8313 loss: 2.8313 2022/10/09 14:13:47 - mmengine - INFO - Epoch(train) [39][1060/2119] lr: 4.0000e-02 eta: 23:44:11 time: 0.3608 data_time: 0.0186 memory: 11108 grad_norm: 3.0122 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7328 loss: 2.7328 2022/10/09 14:13:54 - mmengine - INFO - Epoch(train) [39][1080/2119] lr: 4.0000e-02 eta: 23:44:03 time: 0.3572 data_time: 0.0204 memory: 11108 grad_norm: 2.9691 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.3682 loss: 2.3682 2022/10/09 14:14:01 - mmengine - INFO - Epoch(train) [39][1100/2119] lr: 4.0000e-02 eta: 23:43:56 time: 0.3561 data_time: 0.0218 memory: 11108 grad_norm: 3.0382 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6173 loss: 2.6173 2022/10/09 14:14:09 - mmengine - INFO - Epoch(train) [39][1120/2119] lr: 4.0000e-02 eta: 23:43:49 time: 0.3587 data_time: 0.0226 memory: 11108 grad_norm: 3.0459 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.4898 loss: 2.4898 2022/10/09 14:14:16 - mmengine - INFO - Epoch(train) [39][1140/2119] lr: 4.0000e-02 eta: 23:43:41 time: 0.3586 data_time: 0.0187 memory: 11108 grad_norm: 3.0605 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6102 loss: 2.6102 2022/10/09 14:14:23 - mmengine - INFO - Epoch(train) [39][1160/2119] lr: 4.0000e-02 eta: 23:43:34 time: 0.3591 data_time: 0.0199 memory: 11108 grad_norm: 3.0068 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5239 loss: 2.5239 2022/10/09 14:14:30 - mmengine - INFO - Epoch(train) [39][1180/2119] lr: 4.0000e-02 eta: 23:43:26 time: 0.3603 data_time: 0.0183 memory: 11108 grad_norm: 3.0089 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6912 loss: 2.6912 2022/10/09 14:14:37 - mmengine - INFO - Epoch(train) [39][1200/2119] lr: 4.0000e-02 eta: 23:43:19 time: 0.3535 data_time: 0.0206 memory: 11108 grad_norm: 3.0385 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6713 loss: 2.6713 2022/10/09 14:14:44 - mmengine - INFO - Epoch(train) [39][1220/2119] lr: 4.0000e-02 eta: 23:43:11 time: 0.3617 data_time: 0.0235 memory: 11108 grad_norm: 3.0228 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6414 loss: 2.6414 2022/10/09 14:14:52 - mmengine - INFO - Epoch(train) [39][1240/2119] lr: 4.0000e-02 eta: 23:43:04 time: 0.3609 data_time: 0.0209 memory: 11108 grad_norm: 3.0244 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4151 loss: 2.4151 2022/10/09 14:14:59 - mmengine - INFO - Epoch(train) [39][1260/2119] lr: 4.0000e-02 eta: 23:42:57 time: 0.3571 data_time: 0.0196 memory: 11108 grad_norm: 3.0016 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6751 loss: 2.6751 2022/10/09 14:15:06 - mmengine - INFO - Epoch(train) [39][1280/2119] lr: 4.0000e-02 eta: 23:42:50 time: 0.3623 data_time: 0.0252 memory: 11108 grad_norm: 3.0148 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5087 loss: 2.5087 2022/10/09 14:15:13 - mmengine - INFO - Epoch(train) [39][1300/2119] lr: 4.0000e-02 eta: 23:42:42 time: 0.3568 data_time: 0.0179 memory: 11108 grad_norm: 2.9731 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6538 loss: 2.6538 2022/10/09 14:15:20 - mmengine - INFO - Epoch(train) [39][1320/2119] lr: 4.0000e-02 eta: 23:42:35 time: 0.3600 data_time: 0.0206 memory: 11108 grad_norm: 3.0620 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6798 loss: 2.6798 2022/10/09 14:15:28 - mmengine - INFO - Epoch(train) [39][1340/2119] lr: 4.0000e-02 eta: 23:42:27 time: 0.3594 data_time: 0.0180 memory: 11108 grad_norm: 3.0739 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6390 loss: 2.6390 2022/10/09 14:15:35 - mmengine - INFO - Epoch(train) [39][1360/2119] lr: 4.0000e-02 eta: 23:42:20 time: 0.3620 data_time: 0.0193 memory: 11108 grad_norm: 3.0264 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5382 loss: 2.5382 2022/10/09 14:15:42 - mmengine - INFO - Epoch(train) [39][1380/2119] lr: 4.0000e-02 eta: 23:42:12 time: 0.3552 data_time: 0.0204 memory: 11108 grad_norm: 2.9905 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5749 loss: 2.5749 2022/10/09 14:15:49 - mmengine - INFO - Epoch(train) [39][1400/2119] lr: 4.0000e-02 eta: 23:42:05 time: 0.3533 data_time: 0.0201 memory: 11108 grad_norm: 3.0540 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7645 loss: 2.7645 2022/10/09 14:15:56 - mmengine - INFO - Epoch(train) [39][1420/2119] lr: 4.0000e-02 eta: 23:41:58 time: 0.3678 data_time: 0.0197 memory: 11108 grad_norm: 2.9954 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5321 loss: 2.5321 2022/10/09 14:16:04 - mmengine - INFO - Epoch(train) [39][1440/2119] lr: 4.0000e-02 eta: 23:41:51 time: 0.3603 data_time: 0.0199 memory: 11108 grad_norm: 2.9976 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6909 loss: 2.6909 2022/10/09 14:16:11 - mmengine - INFO - Epoch(train) [39][1460/2119] lr: 4.0000e-02 eta: 23:41:43 time: 0.3560 data_time: 0.0190 memory: 11108 grad_norm: 3.0029 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6409 loss: 2.6409 2022/10/09 14:16:17 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 14:16:18 - mmengine - INFO - Epoch(train) [39][1480/2119] lr: 4.0000e-02 eta: 23:41:36 time: 0.3575 data_time: 0.0215 memory: 11108 grad_norm: 3.0882 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6090 loss: 2.6090 2022/10/09 14:16:25 - mmengine - INFO - Epoch(train) [39][1500/2119] lr: 4.0000e-02 eta: 23:41:28 time: 0.3545 data_time: 0.0208 memory: 11108 grad_norm: 3.0772 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6509 loss: 2.6509 2022/10/09 14:16:32 - mmengine - INFO - Epoch(train) [39][1520/2119] lr: 4.0000e-02 eta: 23:41:21 time: 0.3599 data_time: 0.0221 memory: 11108 grad_norm: 2.9754 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6114 loss: 2.6114 2022/10/09 14:16:39 - mmengine - INFO - Epoch(train) [39][1540/2119] lr: 4.0000e-02 eta: 23:41:13 time: 0.3571 data_time: 0.0205 memory: 11108 grad_norm: 3.0160 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5750 loss: 2.5750 2022/10/09 14:16:46 - mmengine - INFO - Epoch(train) [39][1560/2119] lr: 4.0000e-02 eta: 23:41:06 time: 0.3586 data_time: 0.0230 memory: 11108 grad_norm: 2.9702 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7241 loss: 2.7241 2022/10/09 14:16:54 - mmengine - INFO - Epoch(train) [39][1580/2119] lr: 4.0000e-02 eta: 23:40:58 time: 0.3594 data_time: 0.0222 memory: 11108 grad_norm: 3.0742 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7054 loss: 2.7054 2022/10/09 14:17:01 - mmengine - INFO - Epoch(train) [39][1600/2119] lr: 4.0000e-02 eta: 23:40:51 time: 0.3621 data_time: 0.0191 memory: 11108 grad_norm: 3.0904 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6666 loss: 2.6666 2022/10/09 14:17:08 - mmengine - INFO - Epoch(train) [39][1620/2119] lr: 4.0000e-02 eta: 23:40:43 time: 0.3538 data_time: 0.0207 memory: 11108 grad_norm: 3.0411 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5996 loss: 2.5996 2022/10/09 14:17:15 - mmengine - INFO - Epoch(train) [39][1640/2119] lr: 4.0000e-02 eta: 23:40:36 time: 0.3611 data_time: 0.0231 memory: 11108 grad_norm: 2.9967 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6278 loss: 2.6278 2022/10/09 14:17:22 - mmengine - INFO - Epoch(train) [39][1660/2119] lr: 4.0000e-02 eta: 23:40:29 time: 0.3635 data_time: 0.0206 memory: 11108 grad_norm: 3.0789 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.5480 loss: 2.5480 2022/10/09 14:17:30 - mmengine - INFO - Epoch(train) [39][1680/2119] lr: 4.0000e-02 eta: 23:40:22 time: 0.3616 data_time: 0.0227 memory: 11108 grad_norm: 3.0107 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5744 loss: 2.5744 2022/10/09 14:17:37 - mmengine - INFO - Epoch(train) [39][1700/2119] lr: 4.0000e-02 eta: 23:40:14 time: 0.3537 data_time: 0.0214 memory: 11108 grad_norm: 3.0509 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8089 loss: 2.8089 2022/10/09 14:17:44 - mmengine - INFO - Epoch(train) [39][1720/2119] lr: 4.0000e-02 eta: 23:40:07 time: 0.3689 data_time: 0.0239 memory: 11108 grad_norm: 3.0227 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5679 loss: 2.5679 2022/10/09 14:17:51 - mmengine - INFO - Epoch(train) [39][1740/2119] lr: 4.0000e-02 eta: 23:40:00 time: 0.3594 data_time: 0.0196 memory: 11108 grad_norm: 3.0979 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8317 loss: 2.8317 2022/10/09 14:17:58 - mmengine - INFO - Epoch(train) [39][1760/2119] lr: 4.0000e-02 eta: 23:39:52 time: 0.3542 data_time: 0.0190 memory: 11108 grad_norm: 3.0856 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4787 loss: 2.4787 2022/10/09 14:18:06 - mmengine - INFO - Epoch(train) [39][1780/2119] lr: 4.0000e-02 eta: 23:39:45 time: 0.3649 data_time: 0.0196 memory: 11108 grad_norm: 3.0188 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6609 loss: 2.6609 2022/10/09 14:18:13 - mmengine - INFO - Epoch(train) [39][1800/2119] lr: 4.0000e-02 eta: 23:39:38 time: 0.3572 data_time: 0.0188 memory: 11108 grad_norm: 3.0366 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7055 loss: 2.7055 2022/10/09 14:18:20 - mmengine - INFO - Epoch(train) [39][1820/2119] lr: 4.0000e-02 eta: 23:39:30 time: 0.3575 data_time: 0.0239 memory: 11108 grad_norm: 3.1409 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7098 loss: 2.7098 2022/10/09 14:18:27 - mmengine - INFO - Epoch(train) [39][1840/2119] lr: 4.0000e-02 eta: 23:39:23 time: 0.3579 data_time: 0.0204 memory: 11108 grad_norm: 3.0021 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6872 loss: 2.6872 2022/10/09 14:18:34 - mmengine - INFO - Epoch(train) [39][1860/2119] lr: 4.0000e-02 eta: 23:39:16 time: 0.3621 data_time: 0.0194 memory: 11108 grad_norm: 3.0060 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.2966 loss: 2.2966 2022/10/09 14:18:42 - mmengine - INFO - Epoch(train) [39][1880/2119] lr: 4.0000e-02 eta: 23:39:08 time: 0.3575 data_time: 0.0219 memory: 11108 grad_norm: 2.9885 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6701 loss: 2.6701 2022/10/09 14:18:49 - mmengine - INFO - Epoch(train) [39][1900/2119] lr: 4.0000e-02 eta: 23:39:01 time: 0.3590 data_time: 0.0196 memory: 11108 grad_norm: 3.0356 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.3494 loss: 2.3494 2022/10/09 14:18:56 - mmengine - INFO - Epoch(train) [39][1920/2119] lr: 4.0000e-02 eta: 23:38:53 time: 0.3599 data_time: 0.0212 memory: 11108 grad_norm: 3.0266 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.5317 loss: 2.5317 2022/10/09 14:19:03 - mmengine - INFO - Epoch(train) [39][1940/2119] lr: 4.0000e-02 eta: 23:38:46 time: 0.3624 data_time: 0.0209 memory: 11108 grad_norm: 3.0274 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7306 loss: 2.7306 2022/10/09 14:19:10 - mmengine - INFO - Epoch(train) [39][1960/2119] lr: 4.0000e-02 eta: 23:38:39 time: 0.3582 data_time: 0.0222 memory: 11108 grad_norm: 2.9907 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7234 loss: 2.7234 2022/10/09 14:19:17 - mmengine - INFO - Epoch(train) [39][1980/2119] lr: 4.0000e-02 eta: 23:38:31 time: 0.3549 data_time: 0.0209 memory: 11108 grad_norm: 3.0528 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6424 loss: 2.6424 2022/10/09 14:19:25 - mmengine - INFO - Epoch(train) [39][2000/2119] lr: 4.0000e-02 eta: 23:38:24 time: 0.3642 data_time: 0.0231 memory: 11108 grad_norm: 3.0533 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5766 loss: 2.5766 2022/10/09 14:19:32 - mmengine - INFO - Epoch(train) [39][2020/2119] lr: 4.0000e-02 eta: 23:38:17 time: 0.3586 data_time: 0.0242 memory: 11108 grad_norm: 3.0160 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6058 loss: 2.6058 2022/10/09 14:19:39 - mmengine - INFO - Epoch(train) [39][2040/2119] lr: 4.0000e-02 eta: 23:38:09 time: 0.3578 data_time: 0.0249 memory: 11108 grad_norm: 2.9845 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5471 loss: 2.5471 2022/10/09 14:19:46 - mmengine - INFO - Epoch(train) [39][2060/2119] lr: 4.0000e-02 eta: 23:38:02 time: 0.3630 data_time: 0.0275 memory: 11108 grad_norm: 2.9342 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.3807 loss: 2.3807 2022/10/09 14:19:54 - mmengine - INFO - Epoch(train) [39][2080/2119] lr: 4.0000e-02 eta: 23:37:55 time: 0.3623 data_time: 0.0261 memory: 11108 grad_norm: 3.0228 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5186 loss: 2.5186 2022/10/09 14:20:01 - mmengine - INFO - Epoch(train) [39][2100/2119] lr: 4.0000e-02 eta: 23:37:47 time: 0.3583 data_time: 0.0195 memory: 11108 grad_norm: 3.0301 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5186 loss: 2.5186 2022/10/09 14:20:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 14:20:07 - mmengine - INFO - Epoch(train) [39][2119/2119] lr: 4.0000e-02 eta: 23:37:47 time: 0.3403 data_time: 0.0201 memory: 11108 grad_norm: 3.0363 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6046 loss: 2.6046 2022/10/09 14:20:18 - mmengine - INFO - Epoch(train) [40][20/2119] lr: 4.0000e-02 eta: 23:37:23 time: 0.5154 data_time: 0.1141 memory: 11108 grad_norm: 2.9920 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4660 loss: 2.4660 2022/10/09 14:20:25 - mmengine - INFO - Epoch(train) [40][40/2119] lr: 4.0000e-02 eta: 23:37:16 time: 0.3677 data_time: 0.0209 memory: 11108 grad_norm: 3.0244 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7174 loss: 2.7174 2022/10/09 14:20:32 - mmengine - INFO - Epoch(train) [40][60/2119] lr: 4.0000e-02 eta: 23:37:08 time: 0.3615 data_time: 0.0216 memory: 11108 grad_norm: 3.0432 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 2.6587 loss: 2.6587 2022/10/09 14:20:39 - mmengine - INFO - Epoch(train) [40][80/2119] lr: 4.0000e-02 eta: 23:37:01 time: 0.3597 data_time: 0.0191 memory: 11108 grad_norm: 2.9801 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7120 loss: 2.7120 2022/10/09 14:20:47 - mmengine - INFO - Epoch(train) [40][100/2119] lr: 4.0000e-02 eta: 23:36:54 time: 0.3589 data_time: 0.0196 memory: 11108 grad_norm: 3.0252 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6575 loss: 2.6575 2022/10/09 14:20:54 - mmengine - INFO - Epoch(train) [40][120/2119] lr: 4.0000e-02 eta: 23:36:47 time: 0.3621 data_time: 0.0225 memory: 11108 grad_norm: 3.0837 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4315 loss: 2.4315 2022/10/09 14:21:01 - mmengine - INFO - Epoch(train) [40][140/2119] lr: 4.0000e-02 eta: 23:36:39 time: 0.3584 data_time: 0.0192 memory: 11108 grad_norm: 3.0071 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6982 loss: 2.6982 2022/10/09 14:21:08 - mmengine - INFO - Epoch(train) [40][160/2119] lr: 4.0000e-02 eta: 23:36:32 time: 0.3599 data_time: 0.0187 memory: 11108 grad_norm: 3.0591 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.6145 loss: 2.6145 2022/10/09 14:21:15 - mmengine - INFO - Epoch(train) [40][180/2119] lr: 4.0000e-02 eta: 23:36:25 time: 0.3621 data_time: 0.0174 memory: 11108 grad_norm: 3.0565 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8961 loss: 2.8961 2022/10/09 14:21:23 - mmengine - INFO - Epoch(train) [40][200/2119] lr: 4.0000e-02 eta: 23:36:17 time: 0.3593 data_time: 0.0194 memory: 11108 grad_norm: 3.0278 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4537 loss: 2.4537 2022/10/09 14:21:30 - mmengine - INFO - Epoch(train) [40][220/2119] lr: 4.0000e-02 eta: 23:36:10 time: 0.3585 data_time: 0.0193 memory: 11108 grad_norm: 3.0146 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6964 loss: 2.6964 2022/10/09 14:21:37 - mmengine - INFO - Epoch(train) [40][240/2119] lr: 4.0000e-02 eta: 23:36:02 time: 0.3578 data_time: 0.0210 memory: 11108 grad_norm: 3.1111 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6601 loss: 2.6601 2022/10/09 14:21:44 - mmengine - INFO - Epoch(train) [40][260/2119] lr: 4.0000e-02 eta: 23:35:55 time: 0.3599 data_time: 0.0234 memory: 11108 grad_norm: 3.0143 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6670 loss: 2.6670 2022/10/09 14:21:51 - mmengine - INFO - Epoch(train) [40][280/2119] lr: 4.0000e-02 eta: 23:35:48 time: 0.3578 data_time: 0.0204 memory: 11108 grad_norm: 3.0400 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7270 loss: 2.7270 2022/10/09 14:21:58 - mmengine - INFO - Epoch(train) [40][300/2119] lr: 4.0000e-02 eta: 23:35:40 time: 0.3553 data_time: 0.0216 memory: 11108 grad_norm: 3.0510 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5681 loss: 2.5681 2022/10/09 14:22:06 - mmengine - INFO - Epoch(train) [40][320/2119] lr: 4.0000e-02 eta: 23:35:33 time: 0.3650 data_time: 0.0230 memory: 11108 grad_norm: 3.0309 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7490 loss: 2.7490 2022/10/09 14:22:13 - mmengine - INFO - Epoch(train) [40][340/2119] lr: 4.0000e-02 eta: 23:35:26 time: 0.3618 data_time: 0.0206 memory: 11108 grad_norm: 3.0543 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6823 loss: 2.6823 2022/10/09 14:22:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 14:22:20 - mmengine - INFO - Epoch(train) [40][360/2119] lr: 4.0000e-02 eta: 23:35:18 time: 0.3603 data_time: 0.0223 memory: 11108 grad_norm: 3.0258 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4391 loss: 2.4391 2022/10/09 14:22:27 - mmengine - INFO - Epoch(train) [40][380/2119] lr: 4.0000e-02 eta: 23:35:11 time: 0.3590 data_time: 0.0216 memory: 11108 grad_norm: 3.0414 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6740 loss: 2.6740 2022/10/09 14:22:34 - mmengine - INFO - Epoch(train) [40][400/2119] lr: 4.0000e-02 eta: 23:35:04 time: 0.3574 data_time: 0.0207 memory: 11108 grad_norm: 3.0339 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6390 loss: 2.6390 2022/10/09 14:22:42 - mmengine - INFO - Epoch(train) [40][420/2119] lr: 4.0000e-02 eta: 23:34:56 time: 0.3565 data_time: 0.0212 memory: 11108 grad_norm: 3.0671 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6921 loss: 2.6921 2022/10/09 14:22:49 - mmengine - INFO - Epoch(train) [40][440/2119] lr: 4.0000e-02 eta: 23:34:49 time: 0.3597 data_time: 0.0188 memory: 11108 grad_norm: 3.0696 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4681 loss: 2.4681 2022/10/09 14:22:56 - mmengine - INFO - Epoch(train) [40][460/2119] lr: 4.0000e-02 eta: 23:34:41 time: 0.3545 data_time: 0.0155 memory: 11108 grad_norm: 3.0099 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6125 loss: 2.6125 2022/10/09 14:23:03 - mmengine - INFO - Epoch(train) [40][480/2119] lr: 4.0000e-02 eta: 23:34:34 time: 0.3589 data_time: 0.0229 memory: 11108 grad_norm: 2.9990 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.3069 loss: 2.3069 2022/10/09 14:23:10 - mmengine - INFO - Epoch(train) [40][500/2119] lr: 4.0000e-02 eta: 23:34:27 time: 0.3648 data_time: 0.0190 memory: 11108 grad_norm: 3.0877 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7417 loss: 2.7417 2022/10/09 14:23:17 - mmengine - INFO - Epoch(train) [40][520/2119] lr: 4.0000e-02 eta: 23:34:19 time: 0.3565 data_time: 0.0182 memory: 11108 grad_norm: 2.9960 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.4601 loss: 2.4601 2022/10/09 14:23:25 - mmengine - INFO - Epoch(train) [40][540/2119] lr: 4.0000e-02 eta: 23:34:12 time: 0.3577 data_time: 0.0198 memory: 11108 grad_norm: 3.0686 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7458 loss: 2.7458 2022/10/09 14:23:32 - mmengine - INFO - Epoch(train) [40][560/2119] lr: 4.0000e-02 eta: 23:34:05 time: 0.3626 data_time: 0.0209 memory: 11108 grad_norm: 3.0684 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5193 loss: 2.5193 2022/10/09 14:23:39 - mmengine - INFO - Epoch(train) [40][580/2119] lr: 4.0000e-02 eta: 23:33:57 time: 0.3545 data_time: 0.0181 memory: 11108 grad_norm: 3.0290 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7210 loss: 2.7210 2022/10/09 14:23:46 - mmengine - INFO - Epoch(train) [40][600/2119] lr: 4.0000e-02 eta: 23:33:50 time: 0.3592 data_time: 0.0188 memory: 11108 grad_norm: 3.0429 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6203 loss: 2.6203 2022/10/09 14:23:53 - mmengine - INFO - Epoch(train) [40][620/2119] lr: 4.0000e-02 eta: 23:33:42 time: 0.3623 data_time: 0.0263 memory: 11108 grad_norm: 2.9959 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6991 loss: 2.6991 2022/10/09 14:24:01 - mmengine - INFO - Epoch(train) [40][640/2119] lr: 4.0000e-02 eta: 23:33:35 time: 0.3676 data_time: 0.0225 memory: 11108 grad_norm: 3.0028 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6387 loss: 2.6387 2022/10/09 14:24:08 - mmengine - INFO - Epoch(train) [40][660/2119] lr: 4.0000e-02 eta: 23:33:28 time: 0.3592 data_time: 0.0234 memory: 11108 grad_norm: 3.0059 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6662 loss: 2.6662 2022/10/09 14:24:15 - mmengine - INFO - Epoch(train) [40][680/2119] lr: 4.0000e-02 eta: 23:33:21 time: 0.3631 data_time: 0.0200 memory: 11108 grad_norm: 3.0344 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4931 loss: 2.4931 2022/10/09 14:24:22 - mmengine - INFO - Epoch(train) [40][700/2119] lr: 4.0000e-02 eta: 23:33:14 time: 0.3636 data_time: 0.0197 memory: 11108 grad_norm: 3.0280 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5486 loss: 2.5486 2022/10/09 14:24:30 - mmengine - INFO - Epoch(train) [40][720/2119] lr: 4.0000e-02 eta: 23:33:06 time: 0.3562 data_time: 0.0201 memory: 11108 grad_norm: 3.0511 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6039 loss: 2.6039 2022/10/09 14:24:37 - mmengine - INFO - Epoch(train) [40][740/2119] lr: 4.0000e-02 eta: 23:32:59 time: 0.3666 data_time: 0.0205 memory: 11108 grad_norm: 3.0291 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6104 loss: 2.6104 2022/10/09 14:24:44 - mmengine - INFO - Epoch(train) [40][760/2119] lr: 4.0000e-02 eta: 23:32:52 time: 0.3594 data_time: 0.0195 memory: 11108 grad_norm: 3.0145 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6202 loss: 2.6202 2022/10/09 14:24:51 - mmengine - INFO - Epoch(train) [40][780/2119] lr: 4.0000e-02 eta: 23:32:44 time: 0.3567 data_time: 0.0183 memory: 11108 grad_norm: 3.0158 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4914 loss: 2.4914 2022/10/09 14:24:58 - mmengine - INFO - Epoch(train) [40][800/2119] lr: 4.0000e-02 eta: 23:32:37 time: 0.3569 data_time: 0.0217 memory: 11108 grad_norm: 3.0543 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5369 loss: 2.5369 2022/10/09 14:25:06 - mmengine - INFO - Epoch(train) [40][820/2119] lr: 4.0000e-02 eta: 23:32:30 time: 0.3576 data_time: 0.0235 memory: 11108 grad_norm: 2.9928 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.5468 loss: 2.5468 2022/10/09 14:25:13 - mmengine - INFO - Epoch(train) [40][840/2119] lr: 4.0000e-02 eta: 23:32:22 time: 0.3573 data_time: 0.0220 memory: 11108 grad_norm: 3.0744 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5269 loss: 2.5269 2022/10/09 14:25:20 - mmengine - INFO - Epoch(train) [40][860/2119] lr: 4.0000e-02 eta: 23:32:15 time: 0.3595 data_time: 0.0220 memory: 11108 grad_norm: 3.0243 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.4989 loss: 2.4989 2022/10/09 14:25:27 - mmengine - INFO - Epoch(train) [40][880/2119] lr: 4.0000e-02 eta: 23:32:07 time: 0.3580 data_time: 0.0212 memory: 11108 grad_norm: 3.0486 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8051 loss: 2.8051 2022/10/09 14:25:34 - mmengine - INFO - Epoch(train) [40][900/2119] lr: 4.0000e-02 eta: 23:32:00 time: 0.3563 data_time: 0.0223 memory: 11108 grad_norm: 3.0536 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.6877 loss: 2.6877 2022/10/09 14:25:41 - mmengine - INFO - Epoch(train) [40][920/2119] lr: 4.0000e-02 eta: 23:31:52 time: 0.3555 data_time: 0.0215 memory: 11108 grad_norm: 3.0526 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6230 loss: 2.6230 2022/10/09 14:25:49 - mmengine - INFO - Epoch(train) [40][940/2119] lr: 4.0000e-02 eta: 23:31:45 time: 0.3635 data_time: 0.0269 memory: 11108 grad_norm: 3.0326 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5564 loss: 2.5564 2022/10/09 14:25:56 - mmengine - INFO - Epoch(train) [40][960/2119] lr: 4.0000e-02 eta: 23:31:38 time: 0.3570 data_time: 0.0219 memory: 11108 grad_norm: 2.9985 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7290 loss: 2.7290 2022/10/09 14:26:03 - mmengine - INFO - Epoch(train) [40][980/2119] lr: 4.0000e-02 eta: 23:31:30 time: 0.3539 data_time: 0.0178 memory: 11108 grad_norm: 3.0286 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8274 loss: 2.8274 2022/10/09 14:26:10 - mmengine - INFO - Epoch(train) [40][1000/2119] lr: 4.0000e-02 eta: 23:31:23 time: 0.3645 data_time: 0.0220 memory: 11108 grad_norm: 2.9672 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5735 loss: 2.5735 2022/10/09 14:26:17 - mmengine - INFO - Epoch(train) [40][1020/2119] lr: 4.0000e-02 eta: 23:31:15 time: 0.3559 data_time: 0.0228 memory: 11108 grad_norm: 3.0440 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6986 loss: 2.6986 2022/10/09 14:26:25 - mmengine - INFO - Epoch(train) [40][1040/2119] lr: 4.0000e-02 eta: 23:31:09 time: 0.3720 data_time: 0.0227 memory: 11108 grad_norm: 3.0123 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8109 loss: 2.8109 2022/10/09 14:26:32 - mmengine - INFO - Epoch(train) [40][1060/2119] lr: 4.0000e-02 eta: 23:31:01 time: 0.3574 data_time: 0.0174 memory: 11108 grad_norm: 3.0403 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6684 loss: 2.6684 2022/10/09 14:26:39 - mmengine - INFO - Epoch(train) [40][1080/2119] lr: 4.0000e-02 eta: 23:30:54 time: 0.3580 data_time: 0.0189 memory: 11108 grad_norm: 2.9974 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.9637 loss: 2.9637 2022/10/09 14:26:46 - mmengine - INFO - Epoch(train) [40][1100/2119] lr: 4.0000e-02 eta: 23:30:46 time: 0.3579 data_time: 0.0214 memory: 11108 grad_norm: 3.0189 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8282 loss: 2.8282 2022/10/09 14:26:53 - mmengine - INFO - Epoch(train) [40][1120/2119] lr: 4.0000e-02 eta: 23:30:39 time: 0.3564 data_time: 0.0203 memory: 11108 grad_norm: 3.0221 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6648 loss: 2.6648 2022/10/09 14:27:00 - mmengine - INFO - Epoch(train) [40][1140/2119] lr: 4.0000e-02 eta: 23:30:31 time: 0.3576 data_time: 0.0205 memory: 11108 grad_norm: 3.0402 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6410 loss: 2.6410 2022/10/09 14:27:08 - mmengine - INFO - Epoch(train) [40][1160/2119] lr: 4.0000e-02 eta: 23:30:24 time: 0.3579 data_time: 0.0231 memory: 11108 grad_norm: 2.9965 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.4426 loss: 2.4426 2022/10/09 14:27:15 - mmengine - INFO - Epoch(train) [40][1180/2119] lr: 4.0000e-02 eta: 23:30:16 time: 0.3566 data_time: 0.0175 memory: 11108 grad_norm: 3.1309 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 2.6969 loss: 2.6969 2022/10/09 14:27:22 - mmengine - INFO - Epoch(train) [40][1200/2119] lr: 4.0000e-02 eta: 23:30:09 time: 0.3593 data_time: 0.0228 memory: 11108 grad_norm: 3.0950 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5157 loss: 2.5157 2022/10/09 14:27:29 - mmengine - INFO - Epoch(train) [40][1220/2119] lr: 4.0000e-02 eta: 23:30:01 time: 0.3560 data_time: 0.0170 memory: 11108 grad_norm: 3.0190 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8102 loss: 2.8102 2022/10/09 14:27:36 - mmengine - INFO - Epoch(train) [40][1240/2119] lr: 4.0000e-02 eta: 23:29:54 time: 0.3611 data_time: 0.0240 memory: 11108 grad_norm: 2.9837 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5255 loss: 2.5255 2022/10/09 14:27:43 - mmengine - INFO - Epoch(train) [40][1260/2119] lr: 4.0000e-02 eta: 23:29:47 time: 0.3554 data_time: 0.0209 memory: 11108 grad_norm: 3.0465 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6848 loss: 2.6848 2022/10/09 14:27:51 - mmengine - INFO - Epoch(train) [40][1280/2119] lr: 4.0000e-02 eta: 23:29:39 time: 0.3584 data_time: 0.0224 memory: 11108 grad_norm: 3.0329 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.5665 loss: 2.5665 2022/10/09 14:27:58 - mmengine - INFO - Epoch(train) [40][1300/2119] lr: 4.0000e-02 eta: 23:29:32 time: 0.3613 data_time: 0.0206 memory: 11108 grad_norm: 3.0336 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2894 loss: 2.2894 2022/10/09 14:28:05 - mmengine - INFO - Epoch(train) [40][1320/2119] lr: 4.0000e-02 eta: 23:29:24 time: 0.3538 data_time: 0.0206 memory: 11108 grad_norm: 3.0542 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6121 loss: 2.6121 2022/10/09 14:28:12 - mmengine - INFO - Epoch(train) [40][1340/2119] lr: 4.0000e-02 eta: 23:29:17 time: 0.3560 data_time: 0.0255 memory: 11108 grad_norm: 3.0221 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7274 loss: 2.7274 2022/10/09 14:28:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics700-rgb_20221009_055025 2022/10/09 14:28:19 - mmengine - INFO - Epoch(train) [40][1360/2119] lr: 4.0000e-02 eta: 23:29:09 time: 0.3576 data_time: 0.0195 memory: 11108 grad_norm: 2.9912 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7204 loss: 2.7204 2022/10/09 14:28:26 - mmengine - INFO - Epoch(train) [40][1380/2119] lr: 4.0000e-02 eta: 23:29:02 time: 0.3573 data_time: 0.0261 memory: 11108 grad_norm: 3.0663 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6335 loss: 2.6335 2022/10/09 14:28:34 - mmengine - INFO - Epoch(train) [40][1400/2119] lr: 4.0000e-02 eta: 23:28:55 time: 0.3608 data_time: 0.0230 memory: 11108 grad_norm: 3.0195 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5542 loss: 2.5542 2022/10/09 14:28:41 - mmengine - INFO - Epoch(train) [40][1420/2119] lr: 4.0000e-02 eta: 23:28:47 time: 0.3571 data_time: 0.0189 memory: 11108 grad_norm: 3.1005 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6548 loss: 2.6548 2022/10/09 14:28:48 - mmengine - INFO - Epoch(train) [40][1440/2119] lr: 4.0000e-02 eta: 23:28:40 time: 0.3585 data_time: 0.0199 memory: 11108 grad_norm: 3.0478 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4925 loss: 2.4925 2022/10/09 14:28:55 - mmengine - INFO - Epoch(train) [40][1460/2119] lr: 4.0000e-02 eta: 23:28:33 time: 0.3665 data_time: 0.0190 memory: 11108 grad_norm: 3.0543 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.5270 loss: 2.5270 2022/10/09 14:29:02 - mmengine - INFO - Epoch(train) [40][1480/2119] lr: 4.0000e-02 eta: 23:28:26 time: 0.3616 data_time: 0.0233 memory: 11108 grad_norm: 3.0033 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8428 loss: 2.8428 2022/10/09 14:29:10 - mmengine - INFO - Epoch(train) [40][1500/2119] lr: 4.0000e-02 eta: 23:28:18 time: 0.3575 data_time: 0.0180 memory: 11108 grad_norm: 2.9925 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7987 loss: 2.7987 2022/10/09 14:29:17 - mmengine - INFO - Epoch(train) [40][1520/2119] lr: 4.0000e-02 eta: 23:28:11 time: 0.3605 data_time: 0.0195 memory: 11108 grad_norm: 3.0266 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4246 loss: 2.4246 2022/10/09 14:29:24 - mmengine - INFO - Epoch(train) [40][1540/2119] lr: 4.0000e-02 eta: 23:28:03 time: 0.3574 data_time: 0.0201 memory: 11108 grad_norm: 2.9808 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7144 loss: 2.7144 2022/10/09 14:29:31 - mmengine - INFO - Epoch(train) [40][1560/2119] lr: 4.0000e-02 eta: 23:27:56 time: 0.3610 data_time: 0.0248 memory: 11108 grad_norm: 3.0379 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4208 loss: 2.4208 2022/10/09 14:29:38 - mmengine - INFO - Epoch(train) [40][1580/2119] lr: 4.0000e-02 eta: 23:27:49 time: 0.3595 data_time: 0.0201 memory: 11108 grad_norm: 3.0796 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7908 loss: 2.7908 2022/10/09 14:29:45 - mmengine - INFO - Epoch(train) [40][1600/2119] lr: 4.0000e-02 eta: 23:27:41 time: 0.3576 data_time: 0.0231 memory: 11108 grad_norm: 3.0119 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7234 loss: 2.7234 2022/10/09 14:29:53 - mmengine - INFO - Epoch(train) [40][1620/2119] lr: 4.0000e-02 eta: 23:27:34 time: 0.3575 data_time: 0.0223 memory: 11108 grad_norm: 3.0111 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8177 loss: 2.8177 2022/10/09 14:30:00 - mmengine - INFO - Epoch(train) [40][1640/2119] lr: 4.0000e-02 eta: 23:27:26 time: 0.3566 data_time: 0.0232 memory: 11108 grad_norm: 3.0430 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4411 loss: 2.4411 2022/10/09 14:30:07 - mmengine - INFO - Epoch(train) [40][1660/2119] lr: 4.0000e-02 eta: 23:27:19 time: 0.3626 data_time: 0.0255 memory: 11108 grad_norm: 3.0240 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6245 loss: 2.6245 2022/10/09 14:30:14 - mmengine - INFO - Epoch(train) [40][1680/2119] lr: 4.0000e-02 eta: 23:27:12 time: 0.3596 data_time: 0.0208 memory: 11108 grad_norm: 2.9970 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4699 loss: 2.4699 2022/10/09 14:30:22 - mmengine - INFO - Epoch(train) [40][1700/2119] lr: 4.0000e-02 eta: 23:27:05 time: 0.3650 data_time: 0.0212 memory: 11108 grad_norm: 3.0432 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5543 loss: 2.5543 2022/10/09 14:30:29 - mmeng