2022/11/28 19:44:58 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.9.13 (main, Aug 25 2022, 23:26:10) [GCC 11.2.0] CUDA available: True numpy_random_seed: 852224141 GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/petrelfs/share/cuda-11.3 NVCC: Cuda compilation tools, release 11.3, V11.3.109 GCC: gcc (GCC) 5.4.0 PyTorch: 1.11.0 PyTorch compiling details: PyTorch built with: - GCC 7.3 - C++ Version: 201402 - Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.3 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_37,code=compute_37 - CuDNN 8.2 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, TorchVision: 0.12.0 OpenCV: 4.6.0 MMEngine: 0.3.1 Runtime environment: cudnn_benchmark: False mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: None diff_rank_seed: False deterministic: False Distributed launcher: pytorch Distributed training: True GPU number: 8 ------------------------------------------------------------ 2022/11/28 19:44:58 - mmengine - INFO - Config: default_scope = 'mmaction' default_hooks = dict( runtime_info=dict(type='RuntimeInfoHook'), timer=dict(type='IterTimerHook'), logger=dict(type='LoggerHook', interval=100, ignore_last=False), param_scheduler=dict(type='ParamSchedulerHook'), checkpoint=dict(type='CheckpointHook', interval=1, save_best='auto'), sampler_seed=dict(type='DistSamplerSeedHook'), sync_buffers=dict(type='SyncBuffersHook')) 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 model = dict( type='RecognizerGCN', backbone=dict( type='STGCN', graph_cfg=dict(layout='coco', mode='stgcn_spatial')), cls_head=dict(type='GCNHead', num_classes=120, in_channels=256)) dataset_type = 'PoseDataset' ann_file = 'data/skeleton/ntu120_2d.pkl' train_pipeline = [ dict(type='PreNormalize2D'), dict(type='GenSkeFeat', dataset='coco', feats=['bm']), dict(type='UniformSampleFrames', clip_len=100), dict(type='PoseDecode'), dict(type='FormatGCNInput', num_person=2), dict(type='PackActionInputs') ] val_pipeline = [ dict(type='PreNormalize2D'), dict(type='GenSkeFeat', dataset='coco', feats=['bm']), dict( type='UniformSampleFrames', clip_len=100, num_clips=1, test_mode=True), dict(type='PoseDecode'), dict(type='FormatGCNInput', num_person=2), dict(type='PackActionInputs') ] test_pipeline = [ dict(type='PreNormalize2D'), dict(type='GenSkeFeat', dataset='coco', feats=['bm']), dict( type='UniformSampleFrames', clip_len=100, num_clips=10, test_mode=True), dict(type='PoseDecode'), dict(type='FormatGCNInput', num_person=2), dict(type='PackActionInputs') ] train_dataloader = dict( batch_size=16, num_workers=2, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='RepeatDataset', times=5, dataset=dict( type='PoseDataset', ann_file='data/skeleton/ntu120_2d.pkl', pipeline=[ dict(type='PreNormalize2D'), dict(type='GenSkeFeat', dataset='coco', feats=['bm']), dict(type='UniformSampleFrames', clip_len=100), dict(type='PoseDecode'), dict(type='FormatGCNInput', num_person=2), dict(type='PackActionInputs') ], split='xsub_train'))) val_dataloader = dict( batch_size=16, num_workers=2, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='PoseDataset', ann_file='data/skeleton/ntu120_2d.pkl', pipeline=[ dict(type='PreNormalize2D'), dict(type='GenSkeFeat', dataset='coco', feats=['bm']), dict( type='UniformSampleFrames', clip_len=100, num_clips=1, test_mode=True), dict(type='PoseDecode'), dict(type='FormatGCNInput', num_person=2), dict(type='PackActionInputs') ], split='xsub_val', test_mode=True)) test_dataloader = dict( batch_size=1, num_workers=2, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='PoseDataset', ann_file='data/skeleton/ntu120_2d.pkl', pipeline=[ dict(type='PreNormalize2D'), dict(type='GenSkeFeat', dataset='coco', feats=['bm']), dict( type='UniformSampleFrames', clip_len=100, num_clips=10, test_mode=True), dict(type='PoseDecode'), dict(type='FormatGCNInput', num_person=2), dict(type='PackActionInputs') ], split='xsub_val', test_mode=True)) val_evaluator = [dict(type='AccMetric')] test_evaluator = [dict(type='AccMetric')] train_cfg = dict( type='EpochBasedTrainLoop', max_epochs=16, val_begin=1, val_interval=1) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') param_scheduler = [ dict( type='CosineAnnealingLR', eta_min=0, T_max=16, by_epoch=True, convert_to_iter_based=True) ] optim_wrapper = dict( optimizer=dict( type='SGD', lr=0.1, momentum=0.9, weight_decay=0.0005, nesterov=True)) auto_scale_lr = dict(enable=False, base_batch_size=128) launcher = 'pytorch' work_dir = './work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d' randomness = dict(seed=None, diff_rank_seed=False, deterministic=False) 2022/11/28 19:44:58 - mmengine - INFO - Result has been saved to /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d/modules_statistic_results.json Name of parameter - Initialization information data_bn.weight - torch.Size([51]): The value is the same before and after calling `init_weights` of STGCN data_bn.bias - torch.Size([51]): The value is the same before and after calling `init_weights` of STGCN gcn.0.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.0.gcn.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.0.gcn.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.0.gcn.conv.weight - torch.Size([192, 3, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.0.gcn.conv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of STGCN gcn.0.tcn.conv.weight - torch.Size([64, 64, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.0.tcn.conv.bias - torch.Size([64]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.0.tcn.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.0.tcn.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.1.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.1.gcn.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.1.gcn.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.1.gcn.conv.weight - torch.Size([192, 64, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.1.gcn.conv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of STGCN gcn.1.tcn.conv.weight - torch.Size([64, 64, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.1.tcn.conv.bias - torch.Size([64]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.1.tcn.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.1.tcn.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.2.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.2.gcn.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.2.gcn.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.2.gcn.conv.weight - torch.Size([192, 64, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.2.gcn.conv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of STGCN gcn.2.tcn.conv.weight - torch.Size([64, 64, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.2.tcn.conv.bias - torch.Size([64]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.2.tcn.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.2.tcn.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.3.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.3.gcn.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.3.gcn.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.3.gcn.conv.weight - torch.Size([192, 64, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.3.gcn.conv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of STGCN gcn.3.tcn.conv.weight - torch.Size([64, 64, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.3.tcn.conv.bias - torch.Size([64]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.3.tcn.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.3.tcn.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.4.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.4.gcn.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.4.gcn.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.4.gcn.conv.weight - torch.Size([384, 64, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.4.gcn.conv.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of STGCN gcn.4.tcn.conv.weight - torch.Size([128, 128, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.4.tcn.conv.bias - torch.Size([128]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.4.tcn.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.4.tcn.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.4.residual.conv.weight - torch.Size([128, 64, 1, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.4.residual.conv.bias - torch.Size([128]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.4.residual.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.4.residual.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.5.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.5.gcn.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.5.gcn.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.5.gcn.conv.weight - torch.Size([384, 128, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.5.gcn.conv.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of STGCN gcn.5.tcn.conv.weight - torch.Size([128, 128, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.5.tcn.conv.bias - torch.Size([128]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.5.tcn.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.5.tcn.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.6.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.6.gcn.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.6.gcn.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.6.gcn.conv.weight - torch.Size([384, 128, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.6.gcn.conv.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of STGCN gcn.6.tcn.conv.weight - torch.Size([128, 128, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.6.tcn.conv.bias - torch.Size([128]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.6.tcn.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.6.tcn.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.7.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.7.gcn.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.7.gcn.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.7.gcn.conv.weight - torch.Size([768, 128, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.7.gcn.conv.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of STGCN gcn.7.tcn.conv.weight - torch.Size([256, 256, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.7.tcn.conv.bias - torch.Size([256]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.7.tcn.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.7.tcn.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.7.residual.conv.weight - torch.Size([256, 128, 1, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.7.residual.conv.bias - torch.Size([256]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.7.residual.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.7.residual.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.8.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.8.gcn.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.8.gcn.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.8.gcn.conv.weight - torch.Size([768, 256, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.8.gcn.conv.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of STGCN gcn.8.tcn.conv.weight - torch.Size([256, 256, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.8.tcn.conv.bias - torch.Size([256]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.8.tcn.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.8.tcn.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.9.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.9.gcn.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.9.gcn.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.9.gcn.conv.weight - torch.Size([768, 256, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.9.gcn.conv.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of STGCN gcn.9.tcn.conv.weight - torch.Size([256, 256, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.9.tcn.conv.bias - torch.Size([256]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.9.tcn.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.9.tcn.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN Name of parameter - Initialization information fc.weight - torch.Size([120, 256]): NormalInit: mean=0, std=0.01, bias=0 fc.bias - torch.Size([120]): NormalInit: mean=0, std=0.01, bias=0 2022/11/28 19:46:41 - mmengine - INFO - Checkpoints will be saved to /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d. 2022/11/28 19:46:47 - mmengine - INFO - Epoch(train) [1][100/2462] lr: 9.9998e-02 eta: 0:39:35 time: 0.0334 data_time: 0.0059 memory: 1253 loss: 3.8847 top1_acc: 0.0625 top5_acc: 0.0625 loss_cls: 3.8847 2022/11/28 19:46:51 - mmengine - INFO - Epoch(train) [1][200/2462] lr: 9.9994e-02 eta: 0:30:45 time: 0.0336 data_time: 0.0059 memory: 1253 loss: 3.2753 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.2753 2022/11/28 19:46:54 - mmengine - INFO - Epoch(train) [1][300/2462] lr: 9.9986e-02 eta: 0:27:52 time: 0.0349 data_time: 0.0060 memory: 1253 loss: 2.5445 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5445 2022/11/28 19:46:57 - mmengine - INFO - Epoch(train) [1][400/2462] lr: 9.9975e-02 eta: 0:26:15 time: 0.0329 data_time: 0.0058 memory: 1253 loss: 2.2598 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.2598 2022/11/28 19:47:01 - mmengine - INFO - Epoch(train) [1][500/2462] lr: 9.9960e-02 eta: 0:25:24 time: 0.0347 data_time: 0.0058 memory: 1253 loss: 1.9539 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9539 2022/11/28 19:47:04 - mmengine - INFO - Epoch(train) [1][600/2462] lr: 9.9943e-02 eta: 0:24:47 time: 0.0337 data_time: 0.0061 memory: 1253 loss: 1.6555 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6555 2022/11/28 19:47:08 - mmengine - INFO - Epoch(train) [1][700/2462] lr: 9.9922e-02 eta: 0:24:18 time: 0.0335 data_time: 0.0060 memory: 1253 loss: 1.5560 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5560 2022/11/28 19:47:11 - mmengine - INFO - Epoch(train) [1][800/2462] lr: 9.9899e-02 eta: 0:23:58 time: 0.0341 data_time: 0.0060 memory: 1253 loss: 1.4853 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.4853 2022/11/28 19:47:14 - mmengine - INFO - Epoch(train) [1][900/2462] lr: 9.9872e-02 eta: 0:23:40 time: 0.0340 data_time: 0.0061 memory: 1253 loss: 1.3719 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.3719 2022/11/28 19:47:18 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:47:18 - mmengine - INFO - Epoch(train) [1][1000/2462] lr: 9.9841e-02 eta: 0:23:26 time: 0.0338 data_time: 0.0059 memory: 1253 loss: 1.4890 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4890 2022/11/28 19:47:21 - mmengine - INFO - Epoch(train) [1][1100/2462] lr: 9.9808e-02 eta: 0:23:13 time: 0.0337 data_time: 0.0059 memory: 1253 loss: 1.2752 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.2752 2022/11/28 19:47:25 - mmengine - INFO - Epoch(train) [1][1200/2462] lr: 9.9772e-02 eta: 0:23:04 time: 0.0339 data_time: 0.0058 memory: 1253 loss: 1.2964 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2964 2022/11/28 19:47:28 - mmengine - INFO - Epoch(train) [1][1300/2462] lr: 9.9732e-02 eta: 0:22:54 time: 0.0334 data_time: 0.0059 memory: 1253 loss: 1.1092 top1_acc: 0.5625 top5_acc: 1.0000 loss_cls: 1.1092 2022/11/28 19:47:32 - mmengine - INFO - Epoch(train) [1][1400/2462] lr: 9.9689e-02 eta: 0:22:45 time: 0.0340 data_time: 0.0061 memory: 1253 loss: 1.1266 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 1.1266 2022/11/28 19:47:35 - mmengine - INFO - Epoch(train) [1][1500/2462] lr: 9.9643e-02 eta: 0:22:37 time: 0.0349 data_time: 0.0059 memory: 1253 loss: 1.2102 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.2102 2022/11/28 19:47:38 - mmengine - INFO - Epoch(train) [1][1600/2462] lr: 9.9594e-02 eta: 0:22:30 time: 0.0338 data_time: 0.0061 memory: 1253 loss: 0.9593 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 0.9593 2022/11/28 19:47:42 - mmengine - INFO - Epoch(train) [1][1700/2462] lr: 9.9542e-02 eta: 0:22:24 time: 0.0343 data_time: 0.0060 memory: 1253 loss: 1.0032 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0032 2022/11/28 19:47:45 - mmengine - INFO - Epoch(train) [1][1800/2462] lr: 9.9486e-02 eta: 0:22:17 time: 0.0343 data_time: 0.0061 memory: 1253 loss: 1.1919 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.1919 2022/11/28 19:47:49 - mmengine - INFO - Epoch(train) [1][1900/2462] lr: 9.9428e-02 eta: 0:22:10 time: 0.0334 data_time: 0.0060 memory: 1253 loss: 1.0559 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0559 2022/11/28 19:47:52 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:47:52 - mmengine - INFO - Epoch(train) [1][2000/2462] lr: 9.9366e-02 eta: 0:22:03 time: 0.0337 data_time: 0.0062 memory: 1253 loss: 0.9785 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.9785 2022/11/28 19:47:55 - mmengine - INFO - Epoch(train) [1][2100/2462] lr: 9.9301e-02 eta: 0:21:57 time: 0.0344 data_time: 0.0059 memory: 1253 loss: 1.0077 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0077 2022/11/28 19:47:59 - mmengine - INFO - Epoch(train) [1][2200/2462] lr: 9.9233e-02 eta: 0:21:52 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.9810 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9810 2022/11/28 19:48:02 - mmengine - INFO - Epoch(train) [1][2300/2462] lr: 9.9162e-02 eta: 0:21:47 time: 0.0337 data_time: 0.0060 memory: 1253 loss: 0.9906 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9906 2022/11/28 19:48:06 - mmengine - INFO - Epoch(train) [1][2400/2462] lr: 9.9088e-02 eta: 0:21:42 time: 0.0336 data_time: 0.0060 memory: 1253 loss: 0.9788 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.9788 2022/11/28 19:48:08 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:48:08 - mmengine - INFO - Epoch(train) [1][2462/2462] lr: 9.9040e-02 eta: 0:21:38 time: 0.0331 data_time: 0.0061 memory: 1253 loss: 0.9071 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9071 2022/11/28 19:48:08 - mmengine - INFO - Saving checkpoint at 1 epochs 2022/11/28 19:48:10 - mmengine - INFO - Epoch(val) [1][100/398] eta: 0:00:05 time: 0.0149 data_time: 0.0057 memory: 262 2022/11/28 19:48:12 - mmengine - INFO - Epoch(val) [1][200/398] eta: 0:00:03 time: 0.0149 data_time: 0.0057 memory: 262 2022/11/28 19:48:13 - mmengine - INFO - Epoch(val) [1][300/398] eta: 0:00:01 time: 0.0152 data_time: 0.0058 memory: 262 2022/11/28 19:48:15 - mmengine - INFO - Epoch(val) [1][398/398] acc/top1: 0.5084 acc/top5: 0.8234 acc/mean1: 0.5134 2022/11/28 19:48:16 - mmengine - INFO - The best checkpoint with 0.5084 acc/top1 at 1 epoch is saved to best_acc/top1_epoch_1.pth. 2022/11/28 19:48:19 - mmengine - INFO - Epoch(train) [2][100/2462] lr: 9.8961e-02 eta: 0:21:34 time: 0.0341 data_time: 0.0063 memory: 1253 loss: 1.0247 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0247 2022/11/28 19:48:23 - mmengine - INFO - Epoch(train) [2][200/2462] lr: 9.8878e-02 eta: 0:21:29 time: 0.0338 data_time: 0.0060 memory: 1253 loss: 0.8595 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.8595 2022/11/28 19:48:26 - mmengine - INFO - Epoch(train) [2][300/2462] lr: 9.8793e-02 eta: 0:21:25 time: 0.0344 data_time: 0.0062 memory: 1253 loss: 0.8203 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.8203 2022/11/28 19:48:30 - mmengine - INFO - Epoch(train) [2][400/2462] lr: 9.8704e-02 eta: 0:21:21 time: 0.0344 data_time: 0.0060 memory: 1253 loss: 0.9218 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.9218 2022/11/28 19:48:33 - mmengine - INFO - Epoch(train) [2][500/2462] lr: 9.8612e-02 eta: 0:21:17 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.7949 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7949 2022/11/28 19:48:35 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:48:37 - mmengine - INFO - Epoch(train) [2][600/2462] lr: 9.8518e-02 eta: 0:21:14 time: 0.0345 data_time: 0.0060 memory: 1253 loss: 0.8243 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.8243 2022/11/28 19:48:40 - mmengine - INFO - Epoch(train) [2][700/2462] lr: 9.8420e-02 eta: 0:21:11 time: 0.0354 data_time: 0.0060 memory: 1253 loss: 0.9285 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.9285 2022/11/28 19:48:44 - mmengine - INFO - Epoch(train) [2][800/2462] lr: 9.8319e-02 eta: 0:21:08 time: 0.0349 data_time: 0.0060 memory: 1253 loss: 0.9712 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9712 2022/11/28 19:48:47 - mmengine - INFO - Epoch(train) [2][900/2462] lr: 9.8215e-02 eta: 0:21:04 time: 0.0345 data_time: 0.0064 memory: 1253 loss: 0.9283 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9283 2022/11/28 19:48:51 - mmengine - INFO - Epoch(train) [2][1000/2462] lr: 9.8107e-02 eta: 0:20:59 time: 0.0339 data_time: 0.0059 memory: 1253 loss: 0.9339 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9339 2022/11/28 19:48:54 - mmengine - INFO - Epoch(train) [2][1100/2462] lr: 9.7997e-02 eta: 0:20:55 time: 0.0344 data_time: 0.0067 memory: 1253 loss: 0.7370 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7370 2022/11/28 19:48:58 - mmengine - INFO - Epoch(train) [2][1200/2462] lr: 9.7884e-02 eta: 0:20:51 time: 0.0349 data_time: 0.0066 memory: 1253 loss: 0.8021 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8021 2022/11/28 19:49:01 - mmengine - INFO - Epoch(train) [2][1300/2462] lr: 9.7768e-02 eta: 0:20:47 time: 0.0337 data_time: 0.0059 memory: 1253 loss: 0.8658 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.8658 2022/11/28 19:49:05 - mmengine - INFO - Epoch(train) [2][1400/2462] lr: 9.7648e-02 eta: 0:20:43 time: 0.0349 data_time: 0.0060 memory: 1253 loss: 0.8792 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.8792 2022/11/28 19:49:08 - mmengine - INFO - Epoch(train) [2][1500/2462] lr: 9.7526e-02 eta: 0:20:40 time: 0.0354 data_time: 0.0067 memory: 1253 loss: 0.7212 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7212 2022/11/28 19:49:09 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:49:12 - mmengine - INFO - Epoch(train) [2][1600/2462] lr: 9.7400e-02 eta: 0:20:36 time: 0.0342 data_time: 0.0067 memory: 1253 loss: 0.7907 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7907 2022/11/28 19:49:15 - mmengine - INFO - Epoch(train) [2][1700/2462] lr: 9.7272e-02 eta: 0:20:31 time: 0.0338 data_time: 0.0060 memory: 1253 loss: 0.8013 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8013 2022/11/28 19:49:18 - mmengine - INFO - Epoch(train) [2][1800/2462] lr: 9.7141e-02 eta: 0:20:27 time: 0.0334 data_time: 0.0060 memory: 1253 loss: 0.7479 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7479 2022/11/28 19:49:22 - mmengine - INFO - Epoch(train) [2][1900/2462] lr: 9.7006e-02 eta: 0:20:22 time: 0.0335 data_time: 0.0060 memory: 1253 loss: 0.7883 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7883 2022/11/28 19:49:25 - mmengine - INFO - Epoch(train) [2][2000/2462] lr: 9.6869e-02 eta: 0:20:19 time: 0.0348 data_time: 0.0068 memory: 1253 loss: 0.8504 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 0.8504 2022/11/28 19:49:29 - mmengine - INFO - Epoch(train) [2][2100/2462] lr: 9.6728e-02 eta: 0:20:15 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.8426 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8426 2022/11/28 19:49:32 - mmengine - INFO - Epoch(train) [2][2200/2462] lr: 9.6585e-02 eta: 0:20:11 time: 0.0347 data_time: 0.0063 memory: 1253 loss: 0.8536 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.8536 2022/11/28 19:49:36 - mmengine - INFO - Epoch(train) [2][2300/2462] lr: 9.6439e-02 eta: 0:20:08 time: 0.0357 data_time: 0.0060 memory: 1253 loss: 0.7083 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 0.7083 2022/11/28 19:49:39 - mmengine - INFO - Epoch(train) [2][2400/2462] lr: 9.6290e-02 eta: 0:20:05 time: 0.0342 data_time: 0.0062 memory: 1253 loss: 0.8163 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8163 2022/11/28 19:49:41 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:49:41 - mmengine - INFO - Epoch(train) [2][2462/2462] lr: 9.6196e-02 eta: 0:20:02 time: 0.0347 data_time: 0.0063 memory: 1253 loss: 0.7709 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7709 2022/11/28 19:49:41 - mmengine - INFO - Saving checkpoint at 2 epochs 2022/11/28 19:49:43 - mmengine - INFO - Epoch(val) [2][100/398] eta: 0:00:04 time: 0.0147 data_time: 0.0056 memory: 262 2022/11/28 19:49:45 - mmengine - INFO - Epoch(val) [2][200/398] eta: 0:00:03 time: 0.0148 data_time: 0.0057 memory: 262 2022/11/28 19:49:46 - mmengine - INFO - Epoch(val) [2][300/398] eta: 0:00:01 time: 0.0148 data_time: 0.0057 memory: 262 2022/11/28 19:49:49 - mmengine - INFO - Epoch(val) [2][398/398] acc/top1: 0.6028 acc/top5: 0.8631 acc/mean1: 0.6223 2022/11/28 19:49:49 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_1.pth is removed 2022/11/28 19:49:49 - mmengine - INFO - The best checkpoint with 0.6028 acc/top1 at 2 epoch is saved to best_acc/top1_epoch_2.pth. 2022/11/28 19:49:51 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:49:52 - mmengine - INFO - Epoch(train) [3][100/2462] lr: 9.6041e-02 eta: 0:19:59 time: 0.0337 data_time: 0.0060 memory: 1253 loss: 0.6981 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.6981 2022/11/28 19:49:56 - mmengine - INFO - Epoch(train) [3][200/2462] lr: 9.5884e-02 eta: 0:19:55 time: 0.0344 data_time: 0.0060 memory: 1253 loss: 0.7443 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7443 2022/11/28 19:49:59 - mmengine - INFO - Epoch(train) [3][300/2462] lr: 9.5725e-02 eta: 0:19:52 time: 0.0340 data_time: 0.0065 memory: 1253 loss: 0.7264 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7264 2022/11/28 19:50:03 - mmengine - INFO - Epoch(train) [3][400/2462] lr: 9.5562e-02 eta: 0:19:48 time: 0.0336 data_time: 0.0061 memory: 1253 loss: 0.7763 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7763 2022/11/28 19:50:06 - mmengine - INFO - Epoch(train) [3][500/2462] lr: 9.5396e-02 eta: 0:19:43 time: 0.0337 data_time: 0.0061 memory: 1253 loss: 0.7583 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7583 2022/11/28 19:50:09 - mmengine - INFO - Epoch(train) [3][600/2462] lr: 9.5228e-02 eta: 0:19:40 time: 0.0347 data_time: 0.0060 memory: 1253 loss: 0.7724 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7724 2022/11/28 19:50:13 - mmengine - INFO - Epoch(train) [3][700/2462] lr: 9.5056e-02 eta: 0:19:36 time: 0.0359 data_time: 0.0061 memory: 1253 loss: 0.6753 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6753 2022/11/28 19:50:17 - mmengine - INFO - Epoch(train) [3][800/2462] lr: 9.4882e-02 eta: 0:19:33 time: 0.0357 data_time: 0.0061 memory: 1253 loss: 0.6735 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.6735 2022/11/28 19:50:20 - mmengine - INFO - Epoch(train) [3][900/2462] lr: 9.4705e-02 eta: 0:19:30 time: 0.0334 data_time: 0.0061 memory: 1253 loss: 0.7367 top1_acc: 0.5625 top5_acc: 1.0000 loss_cls: 0.7367 2022/11/28 19:50:23 - mmengine - INFO - Epoch(train) [3][1000/2462] lr: 9.4525e-02 eta: 0:19:25 time: 0.0335 data_time: 0.0061 memory: 1253 loss: 0.7699 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7699 2022/11/28 19:50:26 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:50:27 - mmengine - INFO - Epoch(train) [3][1100/2462] lr: 9.4342e-02 eta: 0:19:21 time: 0.0346 data_time: 0.0060 memory: 1253 loss: 0.6759 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6759 2022/11/28 19:50:30 - mmengine - INFO - Epoch(train) [3][1200/2462] lr: 9.4156e-02 eta: 0:19:18 time: 0.0337 data_time: 0.0060 memory: 1253 loss: 0.7650 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7650 2022/11/28 19:50:34 - mmengine - INFO - Epoch(train) [3][1300/2462] lr: 9.3968e-02 eta: 0:19:14 time: 0.0347 data_time: 0.0060 memory: 1253 loss: 0.7177 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.7177 2022/11/28 19:50:37 - mmengine - INFO - Epoch(train) [3][1400/2462] lr: 9.3776e-02 eta: 0:19:10 time: 0.0333 data_time: 0.0061 memory: 1253 loss: 0.7137 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7137 2022/11/28 19:50:41 - mmengine - INFO - Epoch(train) [3][1500/2462] lr: 9.3582e-02 eta: 0:19:06 time: 0.0342 data_time: 0.0061 memory: 1253 loss: 0.7547 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 0.7547 2022/11/28 19:50:44 - mmengine - INFO - Epoch(train) [3][1600/2462] lr: 9.3385e-02 eta: 0:19:03 time: 0.0345 data_time: 0.0060 memory: 1253 loss: 0.7083 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7083 2022/11/28 19:50:47 - mmengine - INFO - Epoch(train) [3][1700/2462] lr: 9.3186e-02 eta: 0:18:59 time: 0.0335 data_time: 0.0061 memory: 1253 loss: 0.6898 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 0.6898 2022/11/28 19:50:51 - mmengine - INFO - Epoch(train) [3][1800/2462] lr: 9.2983e-02 eta: 0:18:55 time: 0.0336 data_time: 0.0061 memory: 1253 loss: 0.7505 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7505 2022/11/28 19:50:54 - mmengine - INFO - Epoch(train) [3][1900/2462] lr: 9.2778e-02 eta: 0:18:51 time: 0.0343 data_time: 0.0063 memory: 1253 loss: 0.7243 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 0.7243 2022/11/28 19:50:58 - mmengine - INFO - Epoch(train) [3][2000/2462] lr: 9.2571e-02 eta: 0:18:47 time: 0.0340 data_time: 0.0061 memory: 1253 loss: 0.7302 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7302 2022/11/28 19:51:00 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:51:01 - mmengine - INFO - Epoch(train) [3][2100/2462] lr: 9.2360e-02 eta: 0:18:44 time: 0.0341 data_time: 0.0065 memory: 1253 loss: 0.6705 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6705 2022/11/28 19:51:04 - mmengine - INFO - Epoch(train) [3][2200/2462] lr: 9.2147e-02 eta: 0:18:40 time: 0.0342 data_time: 0.0060 memory: 1253 loss: 0.7204 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7204 2022/11/28 19:51:08 - mmengine - INFO - Epoch(train) [3][2300/2462] lr: 9.1931e-02 eta: 0:18:36 time: 0.0333 data_time: 0.0061 memory: 1253 loss: 0.6931 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6931 2022/11/28 19:51:11 - mmengine - INFO - Epoch(train) [3][2400/2462] lr: 9.1713e-02 eta: 0:18:33 time: 0.0376 data_time: 0.0076 memory: 1253 loss: 0.7721 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 0.7721 2022/11/28 19:51:14 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:51:14 - mmengine - INFO - Epoch(train) [3][2462/2462] lr: 9.1576e-02 eta: 0:18:31 time: 0.0338 data_time: 0.0061 memory: 1253 loss: 0.7505 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.7505 2022/11/28 19:51:14 - mmengine - INFO - Saving checkpoint at 3 epochs 2022/11/28 19:51:16 - mmengine - INFO - Epoch(val) [3][100/398] eta: 0:00:04 time: 0.0150 data_time: 0.0057 memory: 262 2022/11/28 19:51:17 - mmengine - INFO - Epoch(val) [3][200/398] eta: 0:00:03 time: 0.0148 data_time: 0.0057 memory: 262 2022/11/28 19:51:19 - mmengine - INFO - Epoch(val) [3][300/398] eta: 0:00:01 time: 0.0149 data_time: 0.0057 memory: 262 2022/11/28 19:51:21 - mmengine - INFO - Epoch(val) [3][398/398] acc/top1: 0.6883 acc/top5: 0.9239 acc/mean1: 0.7085 2022/11/28 19:51:21 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_2.pth is removed 2022/11/28 19:51:21 - mmengine - INFO - The best checkpoint with 0.6883 acc/top1 at 3 epoch is saved to best_acc/top1_epoch_3.pth. 2022/11/28 19:51:25 - mmengine - INFO - Epoch(train) [4][100/2462] lr: 9.1353e-02 eta: 0:18:28 time: 0.0363 data_time: 0.0061 memory: 1253 loss: 0.6959 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6959 2022/11/28 19:51:28 - mmengine - INFO - Epoch(train) [4][200/2462] lr: 9.1127e-02 eta: 0:18:24 time: 0.0351 data_time: 0.0067 memory: 1253 loss: 0.6491 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6491 2022/11/28 19:51:32 - mmengine - INFO - Epoch(train) [4][300/2462] lr: 9.0899e-02 eta: 0:18:21 time: 0.0347 data_time: 0.0061 memory: 1253 loss: 0.7456 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7456 2022/11/28 19:51:35 - mmengine - INFO - Epoch(train) [4][400/2462] lr: 9.0669e-02 eta: 0:18:17 time: 0.0363 data_time: 0.0060 memory: 1253 loss: 0.6218 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6218 2022/11/28 19:51:39 - mmengine - INFO - Epoch(train) [4][500/2462] lr: 9.0435e-02 eta: 0:18:14 time: 0.0343 data_time: 0.0061 memory: 1253 loss: 0.8110 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 0.8110 2022/11/28 19:51:42 - mmengine - INFO - Epoch(train) [4][600/2462] lr: 9.0200e-02 eta: 0:18:10 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.7209 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7209 2022/11/28 19:51:43 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:51:46 - mmengine - INFO - Epoch(train) [4][700/2462] lr: 8.9961e-02 eta: 0:18:06 time: 0.0343 data_time: 0.0059 memory: 1253 loss: 0.6371 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 0.6371 2022/11/28 19:51:49 - mmengine - INFO - Epoch(train) [4][800/2462] lr: 8.9720e-02 eta: 0:18:03 time: 0.0359 data_time: 0.0064 memory: 1253 loss: 0.7049 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 0.7049 2022/11/28 19:51:52 - mmengine - INFO - Epoch(train) [4][900/2462] lr: 8.9477e-02 eta: 0:17:59 time: 0.0350 data_time: 0.0060 memory: 1253 loss: 0.7052 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 0.7052 2022/11/28 19:51:56 - mmengine - INFO - Epoch(train) [4][1000/2462] lr: 8.9231e-02 eta: 0:17:55 time: 0.0335 data_time: 0.0059 memory: 1253 loss: 0.6750 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.6750 2022/11/28 19:51:59 - mmengine - INFO - Epoch(train) [4][1100/2462] lr: 8.8982e-02 eta: 0:17:51 time: 0.0334 data_time: 0.0060 memory: 1253 loss: 0.6479 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6479 2022/11/28 19:52:02 - mmengine - INFO - Epoch(train) [4][1200/2462] lr: 8.8731e-02 eta: 0:17:48 time: 0.0341 data_time: 0.0068 memory: 1253 loss: 0.6186 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.6186 2022/11/28 19:52:06 - mmengine - INFO - Epoch(train) [4][1300/2462] lr: 8.8478e-02 eta: 0:17:44 time: 0.0334 data_time: 0.0061 memory: 1253 loss: 0.6280 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6280 2022/11/28 19:52:09 - mmengine - INFO - Epoch(train) [4][1400/2462] lr: 8.8222e-02 eta: 0:17:40 time: 0.0352 data_time: 0.0060 memory: 1253 loss: 0.7490 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.7490 2022/11/28 19:52:13 - mmengine - INFO - Epoch(train) [4][1500/2462] lr: 8.7964e-02 eta: 0:17:37 time: 0.0340 data_time: 0.0060 memory: 1253 loss: 0.7212 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 0.7212 2022/11/28 19:52:16 - mmengine - INFO - Epoch(train) [4][1600/2462] lr: 8.7703e-02 eta: 0:17:33 time: 0.0339 data_time: 0.0060 memory: 1253 loss: 0.6541 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6541 2022/11/28 19:52:17 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:52:19 - mmengine - INFO - Epoch(train) [4][1700/2462] lr: 8.7440e-02 eta: 0:17:29 time: 0.0333 data_time: 0.0061 memory: 1253 loss: 0.6136 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6136 2022/11/28 19:52:23 - mmengine - INFO - Epoch(train) [4][1800/2462] lr: 8.7174e-02 eta: 0:17:25 time: 0.0333 data_time: 0.0061 memory: 1253 loss: 0.5993 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5993 2022/11/28 19:52:26 - mmengine - INFO - Epoch(train) [4][1900/2462] lr: 8.6907e-02 eta: 0:17:22 time: 0.0339 data_time: 0.0060 memory: 1253 loss: 0.6393 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6393 2022/11/28 19:52:30 - mmengine - INFO - Epoch(train) [4][2000/2462] lr: 8.6636e-02 eta: 0:17:18 time: 0.0333 data_time: 0.0060 memory: 1253 loss: 0.6673 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6673 2022/11/28 19:52:33 - mmengine - INFO - Epoch(train) [4][2100/2462] lr: 8.6364e-02 eta: 0:17:14 time: 0.0338 data_time: 0.0061 memory: 1253 loss: 0.6652 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.6652 2022/11/28 19:52:36 - mmengine - INFO - Epoch(train) [4][2200/2462] lr: 8.6089e-02 eta: 0:17:10 time: 0.0335 data_time: 0.0060 memory: 1253 loss: 0.6659 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6659 2022/11/28 19:52:40 - mmengine - INFO - Epoch(train) [4][2300/2462] lr: 8.5812e-02 eta: 0:17:07 time: 0.0341 data_time: 0.0061 memory: 1253 loss: 0.5362 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5362 2022/11/28 19:52:43 - mmengine - INFO - Epoch(train) [4][2400/2462] lr: 8.5533e-02 eta: 0:17:03 time: 0.0335 data_time: 0.0061 memory: 1253 loss: 0.6291 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6291 2022/11/28 19:52:45 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:52:45 - mmengine - INFO - Epoch(train) [4][2462/2462] lr: 8.5358e-02 eta: 0:17:01 time: 0.0334 data_time: 0.0061 memory: 1253 loss: 0.6168 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.6168 2022/11/28 19:52:45 - mmengine - INFO - Saving checkpoint at 4 epochs 2022/11/28 19:52:47 - mmengine - INFO - Epoch(val) [4][100/398] eta: 0:00:04 time: 0.0148 data_time: 0.0057 memory: 262 2022/11/28 19:52:49 - mmengine - INFO - Epoch(val) [4][200/398] eta: 0:00:03 time: 0.0149 data_time: 0.0058 memory: 262 2022/11/28 19:52:50 - mmengine - INFO - Epoch(val) [4][300/398] eta: 0:00:01 time: 0.0151 data_time: 0.0060 memory: 262 2022/11/28 19:52:53 - mmengine - INFO - Epoch(val) [4][398/398] acc/top1: 0.6784 acc/top5: 0.9220 acc/mean1: 0.7001 2022/11/28 19:52:56 - mmengine - INFO - Epoch(train) [5][100/2462] lr: 8.5075e-02 eta: 0:16:58 time: 0.0340 data_time: 0.0061 memory: 1253 loss: 0.6769 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6769 2022/11/28 19:52:58 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:53:00 - mmengine - INFO - Epoch(train) [5][200/2462] lr: 8.4790e-02 eta: 0:16:54 time: 0.0348 data_time: 0.0060 memory: 1253 loss: 0.6862 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6862 2022/11/28 19:53:03 - mmengine - INFO - Epoch(train) [5][300/2462] lr: 8.4502e-02 eta: 0:16:51 time: 0.0340 data_time: 0.0068 memory: 1253 loss: 0.5823 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5823 2022/11/28 19:53:07 - mmengine - INFO - Epoch(train) [5][400/2462] lr: 8.4213e-02 eta: 0:16:47 time: 0.0335 data_time: 0.0061 memory: 1253 loss: 0.7722 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.7722 2022/11/28 19:53:10 - mmengine - INFO - Epoch(train) [5][500/2462] lr: 8.3921e-02 eta: 0:16:44 time: 0.0335 data_time: 0.0061 memory: 1253 loss: 0.6338 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6338 2022/11/28 19:53:13 - mmengine - INFO - Epoch(train) [5][600/2462] lr: 8.3627e-02 eta: 0:16:40 time: 0.0333 data_time: 0.0060 memory: 1253 loss: 0.6104 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6104 2022/11/28 19:53:17 - mmengine - INFO - Epoch(train) [5][700/2462] lr: 8.3330e-02 eta: 0:16:36 time: 0.0344 data_time: 0.0065 memory: 1253 loss: 0.6245 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6245 2022/11/28 19:53:20 - mmengine - INFO - Epoch(train) [5][800/2462] lr: 8.3032e-02 eta: 0:16:33 time: 0.0334 data_time: 0.0061 memory: 1253 loss: 0.6590 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6590 2022/11/28 19:53:24 - mmengine - INFO - Epoch(train) [5][900/2462] lr: 8.2732e-02 eta: 0:16:29 time: 0.0336 data_time: 0.0061 memory: 1253 loss: 0.5401 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5401 2022/11/28 19:53:27 - mmengine - INFO - Epoch(train) [5][1000/2462] lr: 8.2429e-02 eta: 0:16:25 time: 0.0334 data_time: 0.0060 memory: 1253 loss: 0.6753 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.6753 2022/11/28 19:53:30 - mmengine - INFO - Epoch(train) [5][1100/2462] lr: 8.2125e-02 eta: 0:16:22 time: 0.0335 data_time: 0.0060 memory: 1253 loss: 0.5524 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5524 2022/11/28 19:53:32 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:53:34 - mmengine - INFO - Epoch(train) [5][1200/2462] lr: 8.1818e-02 eta: 0:16:18 time: 0.0358 data_time: 0.0060 memory: 1253 loss: 0.5708 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5708 2022/11/28 19:53:37 - mmengine - INFO - Epoch(train) [5][1300/2462] lr: 8.1510e-02 eta: 0:16:15 time: 0.0344 data_time: 0.0062 memory: 1253 loss: 0.6315 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.6315 2022/11/28 19:53:41 - mmengine - INFO - Epoch(train) [5][1400/2462] lr: 8.1199e-02 eta: 0:16:11 time: 0.0343 data_time: 0.0060 memory: 1253 loss: 0.6295 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6295 2022/11/28 19:53:44 - mmengine - INFO - Epoch(train) [5][1500/2462] lr: 8.0886e-02 eta: 0:16:08 time: 0.0364 data_time: 0.0063 memory: 1253 loss: 0.5735 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5735 2022/11/28 19:53:48 - mmengine - INFO - Epoch(train) [5][1600/2462] lr: 8.0572e-02 eta: 0:16:05 time: 0.0352 data_time: 0.0060 memory: 1253 loss: 0.6027 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.6027 2022/11/28 19:53:51 - mmengine - INFO - Epoch(train) [5][1700/2462] lr: 8.0255e-02 eta: 0:16:01 time: 0.0338 data_time: 0.0061 memory: 1253 loss: 0.6615 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6615 2022/11/28 19:53:55 - mmengine - INFO - Epoch(train) [5][1800/2462] lr: 7.9937e-02 eta: 0:15:58 time: 0.0343 data_time: 0.0060 memory: 1253 loss: 0.6054 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6054 2022/11/28 19:53:58 - mmengine - INFO - Epoch(train) [5][1900/2462] lr: 7.9617e-02 eta: 0:15:54 time: 0.0334 data_time: 0.0060 memory: 1253 loss: 0.7019 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7019 2022/11/28 19:54:01 - mmengine - INFO - Epoch(train) [5][2000/2462] lr: 7.9294e-02 eta: 0:15:50 time: 0.0337 data_time: 0.0060 memory: 1253 loss: 0.4685 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.4685 2022/11/28 19:54:05 - mmengine - INFO - Epoch(train) [5][2100/2462] lr: 7.8970e-02 eta: 0:15:47 time: 0.0338 data_time: 0.0061 memory: 1253 loss: 0.6254 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6254 2022/11/28 19:54:07 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:54:08 - mmengine - INFO - Epoch(train) [5][2200/2462] lr: 7.8644e-02 eta: 0:15:43 time: 0.0333 data_time: 0.0060 memory: 1253 loss: 0.6691 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6691 2022/11/28 19:54:12 - mmengine - INFO - Epoch(train) [5][2300/2462] lr: 7.8317e-02 eta: 0:15:40 time: 0.0335 data_time: 0.0061 memory: 1253 loss: 0.5665 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5665 2022/11/28 19:54:15 - mmengine - INFO - Epoch(train) [5][2400/2462] lr: 7.7987e-02 eta: 0:15:36 time: 0.0335 data_time: 0.0060 memory: 1253 loss: 0.6986 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6986 2022/11/28 19:54:17 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:54:17 - mmengine - INFO - Epoch(train) [5][2462/2462] lr: 7.7782e-02 eta: 0:15:34 time: 0.0347 data_time: 0.0062 memory: 1253 loss: 0.6636 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.6636 2022/11/28 19:54:17 - mmengine - INFO - Saving checkpoint at 5 epochs 2022/11/28 19:54:19 - mmengine - INFO - Epoch(val) [5][100/398] eta: 0:00:04 time: 0.0150 data_time: 0.0057 memory: 262 2022/11/28 19:54:21 - mmengine - INFO - Epoch(val) [5][200/398] eta: 0:00:03 time: 0.0150 data_time: 0.0057 memory: 262 2022/11/28 19:54:22 - mmengine - INFO - Epoch(val) [5][300/398] eta: 0:00:01 time: 0.0152 data_time: 0.0059 memory: 262 2022/11/28 19:54:24 - mmengine - INFO - Epoch(val) [5][398/398] acc/top1: 0.6437 acc/top5: 0.8923 acc/mean1: 0.6574 2022/11/28 19:54:28 - mmengine - INFO - Epoch(train) [6][100/2462] lr: 7.7449e-02 eta: 0:15:30 time: 0.0336 data_time: 0.0061 memory: 1253 loss: 0.5686 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5686 2022/11/28 19:54:31 - mmengine - INFO - Epoch(train) [6][200/2462] lr: 7.7115e-02 eta: 0:15:27 time: 0.0348 data_time: 0.0061 memory: 1253 loss: 0.5843 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.5843 2022/11/28 19:54:35 - mmengine - INFO - Epoch(train) [6][300/2462] lr: 7.6779e-02 eta: 0:15:23 time: 0.0354 data_time: 0.0060 memory: 1253 loss: 0.5873 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5873 2022/11/28 19:54:38 - mmengine - INFO - Epoch(train) [6][400/2462] lr: 7.6442e-02 eta: 0:15:20 time: 0.0336 data_time: 0.0060 memory: 1253 loss: 0.5862 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5862 2022/11/28 19:54:42 - mmengine - INFO - Epoch(train) [6][500/2462] lr: 7.6102e-02 eta: 0:15:17 time: 0.0355 data_time: 0.0068 memory: 1253 loss: 0.6213 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 0.6213 2022/11/28 19:54:45 - mmengine - INFO - Epoch(train) [6][600/2462] lr: 7.5762e-02 eta: 0:15:13 time: 0.0343 data_time: 0.0068 memory: 1253 loss: 0.6004 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6004 2022/11/28 19:54:48 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:54:49 - mmengine - INFO - Epoch(train) [6][700/2462] lr: 7.5419e-02 eta: 0:15:10 time: 0.0351 data_time: 0.0060 memory: 1253 loss: 0.6043 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6043 2022/11/28 19:54:52 - mmengine - INFO - Epoch(train) [6][800/2462] lr: 7.5075e-02 eta: 0:15:06 time: 0.0341 data_time: 0.0061 memory: 1253 loss: 0.5134 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5134 2022/11/28 19:54:56 - mmengine - INFO - Epoch(train) [6][900/2462] lr: 7.4729e-02 eta: 0:15:03 time: 0.0351 data_time: 0.0061 memory: 1253 loss: 0.6360 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6360 2022/11/28 19:54:59 - mmengine - INFO - Epoch(train) [6][1000/2462] lr: 7.4382e-02 eta: 0:14:59 time: 0.0334 data_time: 0.0060 memory: 1253 loss: 0.4934 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4934 2022/11/28 19:55:03 - mmengine - INFO - Epoch(train) [6][1100/2462] lr: 7.4033e-02 eta: 0:14:56 time: 0.0337 data_time: 0.0062 memory: 1253 loss: 0.5468 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5468 2022/11/28 19:55:06 - mmengine - INFO - Epoch(train) [6][1200/2462] lr: 7.3682e-02 eta: 0:14:52 time: 0.0348 data_time: 0.0067 memory: 1253 loss: 0.5363 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5363 2022/11/28 19:55:09 - mmengine - INFO - Epoch(train) [6][1300/2462] lr: 7.3330e-02 eta: 0:14:49 time: 0.0341 data_time: 0.0063 memory: 1253 loss: 0.4921 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4921 2022/11/28 19:55:13 - mmengine - INFO - Epoch(train) [6][1400/2462] lr: 7.2977e-02 eta: 0:14:46 time: 0.0343 data_time: 0.0067 memory: 1253 loss: 0.5687 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5687 2022/11/28 19:55:16 - mmengine - INFO - Epoch(train) [6][1500/2462] lr: 7.2622e-02 eta: 0:14:42 time: 0.0337 data_time: 0.0061 memory: 1253 loss: 0.6071 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.6071 2022/11/28 19:55:20 - mmengine - INFO - Epoch(train) [6][1600/2462] lr: 7.2266e-02 eta: 0:14:39 time: 0.0348 data_time: 0.0060 memory: 1253 loss: 0.6435 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6435 2022/11/28 19:55:23 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:55:23 - mmengine - INFO - Epoch(train) [6][1700/2462] lr: 7.1908e-02 eta: 0:14:35 time: 0.0340 data_time: 0.0061 memory: 1253 loss: 0.4851 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4851 2022/11/28 19:55:27 - mmengine - INFO - Epoch(train) [6][1800/2462] lr: 7.1549e-02 eta: 0:14:32 time: 0.0337 data_time: 0.0061 memory: 1253 loss: 0.5535 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5535 2022/11/28 19:55:30 - mmengine - INFO - Epoch(train) [6][1900/2462] lr: 7.1188e-02 eta: 0:14:28 time: 0.0351 data_time: 0.0061 memory: 1253 loss: 0.5055 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5055 2022/11/28 19:55:34 - mmengine - INFO - Epoch(train) [6][2000/2462] lr: 7.0826e-02 eta: 0:14:25 time: 0.0336 data_time: 0.0061 memory: 1253 loss: 0.4682 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.4682 2022/11/28 19:55:37 - mmengine - INFO - Epoch(train) [6][2100/2462] lr: 7.0463e-02 eta: 0:14:21 time: 0.0349 data_time: 0.0061 memory: 1253 loss: 0.5006 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5006 2022/11/28 19:55:40 - mmengine - INFO - Epoch(train) [6][2200/2462] lr: 7.0099e-02 eta: 0:14:18 time: 0.0341 data_time: 0.0060 memory: 1253 loss: 0.5625 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.5625 2022/11/28 19:55:44 - mmengine - INFO - Epoch(train) [6][2300/2462] lr: 6.9733e-02 eta: 0:14:14 time: 0.0334 data_time: 0.0061 memory: 1253 loss: 0.6148 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6148 2022/11/28 19:55:47 - mmengine - INFO - Epoch(train) [6][2400/2462] lr: 6.9366e-02 eta: 0:14:11 time: 0.0343 data_time: 0.0061 memory: 1253 loss: 0.4904 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4904 2022/11/28 19:55:49 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:55:49 - mmengine - INFO - Epoch(train) [6][2462/2462] lr: 6.9138e-02 eta: 0:14:09 time: 0.0335 data_time: 0.0062 memory: 1253 loss: 0.6230 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 0.6230 2022/11/28 19:55:49 - mmengine - INFO - Saving checkpoint at 6 epochs 2022/11/28 19:55:51 - mmengine - INFO - Epoch(val) [6][100/398] eta: 0:00:04 time: 0.0148 data_time: 0.0057 memory: 262 2022/11/28 19:55:53 - mmengine - INFO - Epoch(val) [6][200/398] eta: 0:00:03 time: 0.0149 data_time: 0.0057 memory: 262 2022/11/28 19:55:54 - mmengine - INFO - Epoch(val) [6][300/398] eta: 0:00:01 time: 0.0164 data_time: 0.0073 memory: 262 2022/11/28 19:55:57 - mmengine - INFO - Epoch(val) [6][398/398] acc/top1: 0.6724 acc/top5: 0.9031 acc/mean1: 0.7008 2022/11/28 19:56:01 - mmengine - INFO - Epoch(train) [7][100/2462] lr: 6.8769e-02 eta: 0:14:05 time: 0.0345 data_time: 0.0061 memory: 1253 loss: 0.5023 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5023 2022/11/28 19:56:04 - mmengine - INFO - Epoch(train) [7][200/2462] lr: 6.8399e-02 eta: 0:14:02 time: 0.0338 data_time: 0.0064 memory: 1253 loss: 0.5940 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5940 2022/11/28 19:56:05 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:56:07 - mmengine - INFO - Epoch(train) [7][300/2462] lr: 6.8027e-02 eta: 0:13:58 time: 0.0337 data_time: 0.0061 memory: 1253 loss: 0.5158 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5158 2022/11/28 19:56:11 - mmengine - INFO - Epoch(train) [7][400/2462] lr: 6.7655e-02 eta: 0:13:55 time: 0.0339 data_time: 0.0060 memory: 1253 loss: 0.4658 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4658 2022/11/28 19:56:14 - mmengine - INFO - Epoch(train) [7][500/2462] lr: 6.7281e-02 eta: 0:13:51 time: 0.0340 data_time: 0.0061 memory: 1253 loss: 0.5105 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5105 2022/11/28 19:56:18 - mmengine - INFO - Epoch(train) [7][600/2462] lr: 6.6906e-02 eta: 0:13:48 time: 0.0346 data_time: 0.0060 memory: 1253 loss: 0.4262 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4262 2022/11/28 19:56:21 - mmengine - INFO - Epoch(train) [7][700/2462] lr: 6.6531e-02 eta: 0:13:45 time: 0.0346 data_time: 0.0060 memory: 1253 loss: 0.5122 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5122 2022/11/28 19:56:25 - mmengine - INFO - Epoch(train) [7][800/2462] lr: 6.6154e-02 eta: 0:13:41 time: 0.0340 data_time: 0.0061 memory: 1253 loss: 0.4576 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4576 2022/11/28 19:56:28 - mmengine - INFO - Epoch(train) [7][900/2462] lr: 6.5776e-02 eta: 0:13:38 time: 0.0340 data_time: 0.0061 memory: 1253 loss: 0.5732 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 0.5732 2022/11/28 19:56:32 - mmengine - INFO - Epoch(train) [7][1000/2462] lr: 6.5397e-02 eta: 0:13:34 time: 0.0344 data_time: 0.0061 memory: 1253 loss: 0.5132 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5132 2022/11/28 19:56:35 - mmengine - INFO - Epoch(train) [7][1100/2462] lr: 6.5017e-02 eta: 0:13:31 time: 0.0334 data_time: 0.0060 memory: 1253 loss: 0.3982 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.3982 2022/11/28 19:56:38 - mmengine - INFO - Epoch(train) [7][1200/2462] lr: 6.4636e-02 eta: 0:13:27 time: 0.0343 data_time: 0.0060 memory: 1253 loss: 0.4418 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.4418 2022/11/28 19:56:39 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:56:42 - mmengine - INFO - Epoch(train) [7][1300/2462] lr: 6.4255e-02 eta: 0:13:24 time: 0.0338 data_time: 0.0060 memory: 1253 loss: 0.4298 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4298 2022/11/28 19:56:45 - mmengine - INFO - Epoch(train) [7][1400/2462] lr: 6.3872e-02 eta: 0:13:20 time: 0.0335 data_time: 0.0061 memory: 1253 loss: 0.5088 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 0.5088 2022/11/28 19:56:49 - mmengine - INFO - Epoch(train) [7][1500/2462] lr: 6.3488e-02 eta: 0:13:17 time: 0.0335 data_time: 0.0061 memory: 1253 loss: 0.6647 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.6647 2022/11/28 19:56:52 - mmengine - INFO - Epoch(train) [7][1600/2462] lr: 6.3104e-02 eta: 0:13:13 time: 0.0335 data_time: 0.0060 memory: 1253 loss: 0.5099 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5099 2022/11/28 19:56:55 - mmengine - INFO - Epoch(train) [7][1700/2462] lr: 6.2719e-02 eta: 0:13:10 time: 0.0363 data_time: 0.0060 memory: 1253 loss: 0.4727 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.4727 2022/11/28 19:56:59 - mmengine - INFO - Epoch(train) [7][1800/2462] lr: 6.2333e-02 eta: 0:13:06 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.4352 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4352 2022/11/28 19:57:02 - mmengine - INFO - Epoch(train) [7][1900/2462] lr: 6.1946e-02 eta: 0:13:03 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.5463 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5463 2022/11/28 19:57:06 - mmengine - INFO - Epoch(train) [7][2000/2462] lr: 6.1558e-02 eta: 0:12:59 time: 0.0340 data_time: 0.0061 memory: 1253 loss: 0.4944 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.4944 2022/11/28 19:57:09 - mmengine - INFO - Epoch(train) [7][2100/2462] lr: 6.1170e-02 eta: 0:12:56 time: 0.0375 data_time: 0.0064 memory: 1253 loss: 0.5231 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5231 2022/11/28 19:57:13 - mmengine - INFO - Epoch(train) [7][2200/2462] lr: 6.0781e-02 eta: 0:12:53 time: 0.0356 data_time: 0.0061 memory: 1253 loss: 0.4187 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4187 2022/11/28 19:57:14 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:57:16 - mmengine - INFO - Epoch(train) [7][2300/2462] lr: 6.0391e-02 eta: 0:12:49 time: 0.0338 data_time: 0.0064 memory: 1253 loss: 0.5534 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5534 2022/11/28 19:57:20 - mmengine - INFO - Epoch(train) [7][2400/2462] lr: 6.0001e-02 eta: 0:12:46 time: 0.0347 data_time: 0.0072 memory: 1253 loss: 0.5164 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5164 2022/11/28 19:57:22 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:57:22 - mmengine - INFO - Epoch(train) [7][2462/2462] lr: 5.9758e-02 eta: 0:12:44 time: 0.0373 data_time: 0.0075 memory: 1253 loss: 0.4520 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4520 2022/11/28 19:57:22 - mmengine - INFO - Saving checkpoint at 7 epochs 2022/11/28 19:57:24 - mmengine - INFO - Epoch(val) [7][100/398] eta: 0:00:04 time: 0.0162 data_time: 0.0071 memory: 262 2022/11/28 19:57:26 - mmengine - INFO - Epoch(val) [7][200/398] eta: 0:00:03 time: 0.0160 data_time: 0.0065 memory: 262 2022/11/28 19:57:27 - mmengine - INFO - Epoch(val) [7][300/398] eta: 0:00:01 time: 0.0151 data_time: 0.0058 memory: 262 2022/11/28 19:57:29 - mmengine - INFO - Epoch(val) [7][398/398] acc/top1: 0.6794 acc/top5: 0.9154 acc/mean1: 0.7053 2022/11/28 19:57:33 - mmengine - INFO - Epoch(train) [8][100/2462] lr: 5.9367e-02 eta: 0:12:40 time: 0.0341 data_time: 0.0060 memory: 1253 loss: 0.4159 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.4159 2022/11/28 19:57:36 - mmengine - INFO - Epoch(train) [8][200/2462] lr: 5.8975e-02 eta: 0:12:37 time: 0.0337 data_time: 0.0061 memory: 1253 loss: 0.4864 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4864 2022/11/28 19:57:40 - mmengine - INFO - Epoch(train) [8][300/2462] lr: 5.8582e-02 eta: 0:12:33 time: 0.0355 data_time: 0.0065 memory: 1253 loss: 0.5942 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5942 2022/11/28 19:57:43 - mmengine - INFO - Epoch(train) [8][400/2462] lr: 5.8189e-02 eta: 0:12:30 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.4489 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4489 2022/11/28 19:57:47 - mmengine - INFO - Epoch(train) [8][500/2462] lr: 5.7796e-02 eta: 0:12:27 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.4521 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.4521 2022/11/28 19:57:50 - mmengine - INFO - Epoch(train) [8][600/2462] lr: 5.7402e-02 eta: 0:12:23 time: 0.0338 data_time: 0.0062 memory: 1253 loss: 0.4260 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4260 2022/11/28 19:57:54 - mmengine - INFO - Epoch(train) [8][700/2462] lr: 5.7007e-02 eta: 0:12:20 time: 0.0353 data_time: 0.0070 memory: 1253 loss: 0.5043 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5043 2022/11/28 19:57:56 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:57:57 - mmengine - INFO - Epoch(train) [8][800/2462] lr: 5.6612e-02 eta: 0:12:16 time: 0.0343 data_time: 0.0061 memory: 1253 loss: 0.3798 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3798 2022/11/28 19:58:01 - mmengine - INFO - Epoch(train) [8][900/2462] lr: 5.6216e-02 eta: 0:12:13 time: 0.0371 data_time: 0.0060 memory: 1253 loss: 0.4056 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4056 2022/11/28 19:58:04 - mmengine - INFO - Epoch(train) [8][1000/2462] lr: 5.5821e-02 eta: 0:12:10 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.5191 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5191 2022/11/28 19:58:08 - mmengine - INFO - Epoch(train) [8][1100/2462] lr: 5.5424e-02 eta: 0:12:06 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.5416 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 0.5416 2022/11/28 19:58:11 - mmengine - INFO - Epoch(train) [8][1200/2462] lr: 5.5028e-02 eta: 0:12:03 time: 0.0350 data_time: 0.0061 memory: 1253 loss: 0.4886 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4886 2022/11/28 19:58:15 - mmengine - INFO - Epoch(train) [8][1300/2462] lr: 5.4631e-02 eta: 0:11:59 time: 0.0342 data_time: 0.0060 memory: 1253 loss: 0.4989 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4989 2022/11/28 19:58:18 - mmengine - INFO - Epoch(train) [8][1400/2462] lr: 5.4234e-02 eta: 0:11:56 time: 0.0348 data_time: 0.0060 memory: 1253 loss: 0.4166 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4166 2022/11/28 19:58:22 - mmengine - INFO - Epoch(train) [8][1500/2462] lr: 5.3836e-02 eta: 0:11:52 time: 0.0359 data_time: 0.0060 memory: 1253 loss: 0.4750 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 0.4750 2022/11/28 19:58:25 - mmengine - INFO - Epoch(train) [8][1600/2462] lr: 5.3439e-02 eta: 0:11:49 time: 0.0345 data_time: 0.0068 memory: 1253 loss: 0.3848 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3848 2022/11/28 19:58:29 - mmengine - INFO - Epoch(train) [8][1700/2462] lr: 5.3041e-02 eta: 0:11:46 time: 0.0342 data_time: 0.0068 memory: 1253 loss: 0.4485 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.4485 2022/11/28 19:58:31 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:58:32 - mmengine - INFO - Epoch(train) [8][1800/2462] lr: 5.2643e-02 eta: 0:11:42 time: 0.0357 data_time: 0.0062 memory: 1253 loss: 0.3879 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3879 2022/11/28 19:58:36 - mmengine - INFO - Epoch(train) [8][1900/2462] lr: 5.2244e-02 eta: 0:11:39 time: 0.0346 data_time: 0.0061 memory: 1253 loss: 0.5170 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5170 2022/11/28 19:58:39 - mmengine - INFO - Epoch(train) [8][2000/2462] lr: 5.1846e-02 eta: 0:11:35 time: 0.0343 data_time: 0.0060 memory: 1253 loss: 0.4693 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4693 2022/11/28 19:58:43 - mmengine - INFO - Epoch(train) [8][2100/2462] lr: 5.1447e-02 eta: 0:11:32 time: 0.0342 data_time: 0.0061 memory: 1253 loss: 0.4003 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 0.4003 2022/11/28 19:58:46 - mmengine - INFO - Epoch(train) [8][2200/2462] lr: 5.1049e-02 eta: 0:11:28 time: 0.0341 data_time: 0.0060 memory: 1253 loss: 0.4379 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.4379 2022/11/28 19:58:50 - mmengine - INFO - Epoch(train) [8][2300/2462] lr: 5.0650e-02 eta: 0:11:25 time: 0.0344 data_time: 0.0061 memory: 1253 loss: 0.4913 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4913 2022/11/28 19:58:53 - mmengine - INFO - Epoch(train) [8][2400/2462] lr: 5.0251e-02 eta: 0:11:22 time: 0.0342 data_time: 0.0061 memory: 1253 loss: 0.4368 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4368 2022/11/28 19:58:55 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:58:55 - mmengine - INFO - Epoch(train) [8][2462/2462] lr: 5.0004e-02 eta: 0:11:19 time: 0.0344 data_time: 0.0069 memory: 1253 loss: 0.3742 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3742 2022/11/28 19:58:55 - mmengine - INFO - Saving checkpoint at 8 epochs 2022/11/28 19:58:57 - mmengine - INFO - Epoch(val) [8][100/398] eta: 0:00:04 time: 0.0149 data_time: 0.0057 memory: 262 2022/11/28 19:58:59 - mmengine - INFO - Epoch(val) [8][200/398] eta: 0:00:02 time: 0.0149 data_time: 0.0057 memory: 262 2022/11/28 19:59:00 - mmengine - INFO - Epoch(val) [8][300/398] eta: 0:00:01 time: 0.0147 data_time: 0.0057 memory: 262 2022/11/28 19:59:03 - mmengine - INFO - Epoch(val) [8][398/398] acc/top1: 0.7050 acc/top5: 0.9239 acc/mean1: 0.7288 2022/11/28 19:59:03 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_3.pth is removed 2022/11/28 19:59:03 - mmengine - INFO - The best checkpoint with 0.7050 acc/top1 at 8 epoch is saved to best_acc/top1_epoch_8.pth. 2022/11/28 19:59:06 - mmengine - INFO - Epoch(train) [9][100/2462] lr: 4.9605e-02 eta: 0:11:16 time: 0.0338 data_time: 0.0061 memory: 1253 loss: 0.3607 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3607 2022/11/28 19:59:10 - mmengine - INFO - Epoch(train) [9][200/2462] lr: 4.9207e-02 eta: 0:11:13 time: 0.0341 data_time: 0.0062 memory: 1253 loss: 0.4764 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4764 2022/11/28 19:59:13 - mmengine - INFO - Epoch(train) [9][300/2462] lr: 4.8808e-02 eta: 0:11:09 time: 0.0356 data_time: 0.0067 memory: 1253 loss: 0.4797 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 0.4797 2022/11/28 19:59:13 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:59:17 - mmengine - INFO - Epoch(train) [9][400/2462] lr: 4.8409e-02 eta: 0:11:06 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.4019 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.4019 2022/11/28 19:59:20 - mmengine - INFO - Epoch(train) [9][500/2462] lr: 4.8011e-02 eta: 0:11:02 time: 0.0338 data_time: 0.0061 memory: 1253 loss: 0.3651 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.3651 2022/11/28 19:59:24 - mmengine - INFO - Epoch(train) [9][600/2462] lr: 4.7612e-02 eta: 0:10:59 time: 0.0343 data_time: 0.0064 memory: 1253 loss: 0.4168 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4168 2022/11/28 19:59:27 - mmengine - INFO - Epoch(train) [9][700/2462] lr: 4.7214e-02 eta: 0:10:55 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.3686 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.3686 2022/11/28 19:59:31 - mmengine - INFO - Epoch(train) [9][800/2462] lr: 4.6816e-02 eta: 0:10:52 time: 0.0341 data_time: 0.0062 memory: 1253 loss: 0.4184 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4184 2022/11/28 19:59:34 - mmengine - INFO - Epoch(train) [9][900/2462] lr: 4.6418e-02 eta: 0:10:48 time: 0.0341 data_time: 0.0067 memory: 1253 loss: 0.3607 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3607 2022/11/28 19:59:37 - mmengine - INFO - Epoch(train) [9][1000/2462] lr: 4.6021e-02 eta: 0:10:45 time: 0.0341 data_time: 0.0067 memory: 1253 loss: 0.4111 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.4111 2022/11/28 19:59:41 - mmengine - INFO - Epoch(train) [9][1100/2462] lr: 4.5623e-02 eta: 0:10:42 time: 0.0346 data_time: 0.0073 memory: 1253 loss: 0.3620 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3620 2022/11/28 19:59:44 - mmengine - INFO - Epoch(train) [9][1200/2462] lr: 4.5226e-02 eta: 0:10:38 time: 0.0341 data_time: 0.0067 memory: 1253 loss: 0.3420 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3420 2022/11/28 19:59:48 - mmengine - INFO - Epoch(train) [9][1300/2462] lr: 4.4829e-02 eta: 0:10:35 time: 0.0356 data_time: 0.0067 memory: 1253 loss: 0.4350 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4350 2022/11/28 19:59:48 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 19:59:51 - mmengine - INFO - Epoch(train) [9][1400/2462] lr: 4.4433e-02 eta: 0:10:31 time: 0.0345 data_time: 0.0067 memory: 1253 loss: 0.4253 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.4253 2022/11/28 19:59:55 - mmengine - INFO - Epoch(train) [9][1500/2462] lr: 4.4037e-02 eta: 0:10:28 time: 0.0351 data_time: 0.0061 memory: 1253 loss: 0.4587 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4587 2022/11/28 19:59:58 - mmengine - INFO - Epoch(train) [9][1600/2462] lr: 4.3641e-02 eta: 0:10:24 time: 0.0341 data_time: 0.0067 memory: 1253 loss: 0.4254 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4254 2022/11/28 20:00:02 - mmengine - INFO - Epoch(train) [9][1700/2462] lr: 4.3246e-02 eta: 0:10:21 time: 0.0356 data_time: 0.0068 memory: 1253 loss: 0.3975 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3975 2022/11/28 20:00:05 - mmengine - INFO - Epoch(train) [9][1800/2462] lr: 4.2851e-02 eta: 0:10:17 time: 0.0340 data_time: 0.0062 memory: 1253 loss: 0.3666 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3666 2022/11/28 20:00:09 - mmengine - INFO - Epoch(train) [9][1900/2462] lr: 4.2456e-02 eta: 0:10:14 time: 0.0341 data_time: 0.0062 memory: 1253 loss: 0.3336 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3336 2022/11/28 20:00:12 - mmengine - INFO - Epoch(train) [9][2000/2462] lr: 4.2063e-02 eta: 0:10:11 time: 0.0339 data_time: 0.0062 memory: 1253 loss: 0.3932 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3932 2022/11/28 20:00:16 - mmengine - INFO - Epoch(train) [9][2100/2462] lr: 4.1669e-02 eta: 0:10:07 time: 0.0338 data_time: 0.0062 memory: 1253 loss: 0.3728 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3728 2022/11/28 20:00:19 - mmengine - INFO - Epoch(train) [9][2200/2462] lr: 4.1276e-02 eta: 0:10:04 time: 0.0352 data_time: 0.0061 memory: 1253 loss: 0.3495 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.3495 2022/11/28 20:00:23 - mmengine - INFO - Epoch(train) [9][2300/2462] lr: 4.0884e-02 eta: 0:10:00 time: 0.0338 data_time: 0.0062 memory: 1253 loss: 0.3904 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.3904 2022/11/28 20:00:23 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:00:26 - mmengine - INFO - Epoch(train) [9][2400/2462] lr: 4.0492e-02 eta: 0:09:57 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.4237 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4237 2022/11/28 20:00:28 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:00:28 - mmengine - INFO - Epoch(train) [9][2462/2462] lr: 4.0249e-02 eta: 0:09:55 time: 0.0338 data_time: 0.0061 memory: 1253 loss: 0.4200 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4200 2022/11/28 20:00:28 - mmengine - INFO - Saving checkpoint at 9 epochs 2022/11/28 20:00:30 - mmengine - INFO - Epoch(val) [9][100/398] eta: 0:00:04 time: 0.0148 data_time: 0.0057 memory: 262 2022/11/28 20:00:32 - mmengine - INFO - Epoch(val) [9][200/398] eta: 0:00:03 time: 0.0149 data_time: 0.0057 memory: 262 2022/11/28 20:00:33 - mmengine - INFO - Epoch(val) [9][300/398] eta: 0:00:01 time: 0.0147 data_time: 0.0056 memory: 262 2022/11/28 20:00:35 - mmengine - INFO - Epoch(val) [9][398/398] acc/top1: 0.7354 acc/top5: 0.9396 acc/mean1: 0.7552 2022/11/28 20:00:35 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_8.pth is removed 2022/11/28 20:00:36 - mmengine - INFO - The best checkpoint with 0.7354 acc/top1 at 9 epoch is saved to best_acc/top1_epoch_9.pth. 2022/11/28 20:00:39 - mmengine - INFO - Epoch(train) [10][100/2462] lr: 3.9859e-02 eta: 0:09:51 time: 0.0354 data_time: 0.0060 memory: 1253 loss: 0.3286 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3286 2022/11/28 20:00:43 - mmengine - INFO - Epoch(train) [10][200/2462] lr: 3.9468e-02 eta: 0:09:48 time: 0.0344 data_time: 0.0066 memory: 1253 loss: 0.3077 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3077 2022/11/28 20:00:46 - mmengine - INFO - Epoch(train) [10][300/2462] lr: 3.9079e-02 eta: 0:09:44 time: 0.0353 data_time: 0.0062 memory: 1253 loss: 0.3806 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3806 2022/11/28 20:00:50 - mmengine - INFO - Epoch(train) [10][400/2462] lr: 3.8690e-02 eta: 0:09:41 time: 0.0341 data_time: 0.0061 memory: 1253 loss: 0.3610 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3610 2022/11/28 20:00:53 - mmengine - INFO - Epoch(train) [10][500/2462] lr: 3.8302e-02 eta: 0:09:37 time: 0.0339 data_time: 0.0062 memory: 1253 loss: 0.2907 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.2907 2022/11/28 20:00:57 - mmengine - INFO - Epoch(train) [10][600/2462] lr: 3.7915e-02 eta: 0:09:34 time: 0.0357 data_time: 0.0061 memory: 1253 loss: 0.3208 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3208 2022/11/28 20:01:00 - mmengine - INFO - Epoch(train) [10][700/2462] lr: 3.7528e-02 eta: 0:09:31 time: 0.0355 data_time: 0.0061 memory: 1253 loss: 0.3668 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.3668 2022/11/28 20:01:04 - mmengine - INFO - Epoch(train) [10][800/2462] lr: 3.7143e-02 eta: 0:09:27 time: 0.0344 data_time: 0.0062 memory: 1253 loss: 0.3921 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3921 2022/11/28 20:01:05 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:01:07 - mmengine - INFO - Epoch(train) [10][900/2462] lr: 3.6758e-02 eta: 0:09:24 time: 0.0350 data_time: 0.0061 memory: 1253 loss: 0.3488 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3488 2022/11/28 20:01:11 - mmengine - INFO - Epoch(train) [10][1000/2462] lr: 3.6373e-02 eta: 0:09:20 time: 0.0344 data_time: 0.0061 memory: 1253 loss: 0.3419 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3419 2022/11/28 20:01:14 - mmengine - INFO - Epoch(train) [10][1100/2462] lr: 3.5990e-02 eta: 0:09:17 time: 0.0344 data_time: 0.0061 memory: 1253 loss: 0.3210 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3210 2022/11/28 20:01:18 - mmengine - INFO - Epoch(train) [10][1200/2462] lr: 3.5608e-02 eta: 0:09:13 time: 0.0347 data_time: 0.0064 memory: 1253 loss: 0.3430 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.3430 2022/11/28 20:01:21 - mmengine - INFO - Epoch(train) [10][1300/2462] lr: 3.5226e-02 eta: 0:09:10 time: 0.0340 data_time: 0.0062 memory: 1253 loss: 0.3844 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3844 2022/11/28 20:01:25 - mmengine - INFO - Epoch(train) [10][1400/2462] lr: 3.4846e-02 eta: 0:09:07 time: 0.0356 data_time: 0.0062 memory: 1253 loss: 0.3788 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3788 2022/11/28 20:01:28 - mmengine - INFO - Epoch(train) [10][1500/2462] lr: 3.4466e-02 eta: 0:09:03 time: 0.0359 data_time: 0.0067 memory: 1253 loss: 0.2702 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.2702 2022/11/28 20:01:32 - mmengine - INFO - Epoch(train) [10][1600/2462] lr: 3.4088e-02 eta: 0:09:00 time: 0.0352 data_time: 0.0068 memory: 1253 loss: 0.2564 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2564 2022/11/28 20:01:35 - mmengine - INFO - Epoch(train) [10][1700/2462] lr: 3.3710e-02 eta: 0:08:56 time: 0.0343 data_time: 0.0068 memory: 1253 loss: 0.3259 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3259 2022/11/28 20:01:39 - mmengine - INFO - Epoch(train) [10][1800/2462] lr: 3.3334e-02 eta: 0:08:53 time: 0.0357 data_time: 0.0072 memory: 1253 loss: 0.4019 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4019 2022/11/28 20:01:40 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:01:42 - mmengine - INFO - Epoch(train) [10][1900/2462] lr: 3.2959e-02 eta: 0:08:49 time: 0.0344 data_time: 0.0067 memory: 1253 loss: 0.3341 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3341 2022/11/28 20:01:46 - mmengine - INFO - Epoch(train) [10][2000/2462] lr: 3.2584e-02 eta: 0:08:46 time: 0.0349 data_time: 0.0073 memory: 1253 loss: 0.3070 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.3070 2022/11/28 20:01:49 - mmengine - INFO - Epoch(train) [10][2100/2462] lr: 3.2211e-02 eta: 0:08:43 time: 0.0359 data_time: 0.0061 memory: 1253 loss: 0.2924 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.2924 2022/11/28 20:01:53 - mmengine - INFO - Epoch(train) [10][2200/2462] lr: 3.1839e-02 eta: 0:08:39 time: 0.0343 data_time: 0.0061 memory: 1253 loss: 0.2616 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2616 2022/11/28 20:01:56 - mmengine - INFO - Epoch(train) [10][2300/2462] lr: 3.1468e-02 eta: 0:08:36 time: 0.0355 data_time: 0.0061 memory: 1253 loss: 0.2588 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.2588 2022/11/28 20:02:00 - mmengine - INFO - Epoch(train) [10][2400/2462] lr: 3.1098e-02 eta: 0:08:32 time: 0.0361 data_time: 0.0067 memory: 1253 loss: 0.2999 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2999 2022/11/28 20:02:02 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:02:02 - mmengine - INFO - Epoch(train) [10][2462/2462] lr: 3.0870e-02 eta: 0:08:30 time: 0.0349 data_time: 0.0065 memory: 1253 loss: 0.2844 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.2844 2022/11/28 20:02:02 - mmengine - INFO - Saving checkpoint at 10 epochs 2022/11/28 20:02:04 - mmengine - INFO - Epoch(val) [10][100/398] eta: 0:00:04 time: 0.0148 data_time: 0.0057 memory: 262 2022/11/28 20:02:06 - mmengine - INFO - Epoch(val) [10][200/398] eta: 0:00:03 time: 0.0152 data_time: 0.0059 memory: 262 2022/11/28 20:02:07 - mmengine - INFO - Epoch(val) [10][300/398] eta: 0:00:01 time: 0.0146 data_time: 0.0056 memory: 262 2022/11/28 20:02:09 - mmengine - INFO - Epoch(val) [10][398/398] acc/top1: 0.6996 acc/top5: 0.9190 acc/mean1: 0.7198 2022/11/28 20:02:13 - mmengine - INFO - Epoch(train) [11][100/2462] lr: 3.0502e-02 eta: 0:08:27 time: 0.0344 data_time: 0.0061 memory: 1253 loss: 0.2949 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2949 2022/11/28 20:02:16 - mmengine - INFO - Epoch(train) [11][200/2462] lr: 3.0135e-02 eta: 0:08:23 time: 0.0350 data_time: 0.0061 memory: 1253 loss: 0.2137 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2137 2022/11/28 20:02:20 - mmengine - INFO - Epoch(train) [11][300/2462] lr: 2.9770e-02 eta: 0:08:20 time: 0.0342 data_time: 0.0061 memory: 1253 loss: 0.3362 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.3362 2022/11/28 20:02:23 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:02:23 - mmengine - INFO - Epoch(train) [11][400/2462] lr: 2.9406e-02 eta: 0:08:16 time: 0.0343 data_time: 0.0060 memory: 1253 loss: 0.3260 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.3260 2022/11/28 20:02:27 - mmengine - INFO - Epoch(train) [11][500/2462] lr: 2.9043e-02 eta: 0:08:13 time: 0.0358 data_time: 0.0061 memory: 1253 loss: 0.3343 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3343 2022/11/28 20:02:30 - mmengine - INFO - Epoch(train) [11][600/2462] lr: 2.8682e-02 eta: 0:08:10 time: 0.0345 data_time: 0.0061 memory: 1253 loss: 0.2307 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.2307 2022/11/28 20:02:34 - mmengine - INFO - Epoch(train) [11][700/2462] lr: 2.8322e-02 eta: 0:08:06 time: 0.0338 data_time: 0.0060 memory: 1253 loss: 0.2816 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2816 2022/11/28 20:02:37 - mmengine - INFO - Epoch(train) [11][800/2462] lr: 2.7963e-02 eta: 0:08:03 time: 0.0343 data_time: 0.0061 memory: 1253 loss: 0.2464 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2464 2022/11/28 20:02:41 - mmengine - INFO - Epoch(train) [11][900/2462] lr: 2.7606e-02 eta: 0:07:59 time: 0.0344 data_time: 0.0061 memory: 1253 loss: 0.2621 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2621 2022/11/28 20:02:44 - mmengine - INFO - Epoch(train) [11][1000/2462] lr: 2.7250e-02 eta: 0:07:56 time: 0.0342 data_time: 0.0060 memory: 1253 loss: 0.2973 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2973 2022/11/28 20:02:48 - mmengine - INFO - Epoch(train) [11][1100/2462] lr: 2.6896e-02 eta: 0:07:52 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.2751 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.2751 2022/11/28 20:02:51 - mmengine - INFO - Epoch(train) [11][1200/2462] lr: 2.6543e-02 eta: 0:07:49 time: 0.0346 data_time: 0.0062 memory: 1253 loss: 0.3158 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3158 2022/11/28 20:02:55 - mmengine - INFO - Epoch(train) [11][1300/2462] lr: 2.6191e-02 eta: 0:07:45 time: 0.0338 data_time: 0.0060 memory: 1253 loss: 0.3282 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3282 2022/11/28 20:02:57 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:02:58 - mmengine - INFO - Epoch(train) [11][1400/2462] lr: 2.5841e-02 eta: 0:07:42 time: 0.0343 data_time: 0.0068 memory: 1253 loss: 0.2543 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2543 2022/11/28 20:03:01 - mmengine - INFO - Epoch(train) [11][1500/2462] lr: 2.5493e-02 eta: 0:07:38 time: 0.0344 data_time: 0.0066 memory: 1253 loss: 0.2661 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.2661 2022/11/28 20:03:05 - mmengine - INFO - Epoch(train) [11][1600/2462] lr: 2.5146e-02 eta: 0:07:35 time: 0.0344 data_time: 0.0061 memory: 1253 loss: 0.2735 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2735 2022/11/28 20:03:08 - mmengine - INFO - Epoch(train) [11][1700/2462] lr: 2.4801e-02 eta: 0:07:31 time: 0.0340 data_time: 0.0062 memory: 1253 loss: 0.3095 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3095 2022/11/28 20:03:12 - mmengine - INFO - Epoch(train) [11][1800/2462] lr: 2.4458e-02 eta: 0:07:28 time: 0.0342 data_time: 0.0061 memory: 1253 loss: 0.2823 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2823 2022/11/28 20:03:15 - mmengine - INFO - Epoch(train) [11][1900/2462] lr: 2.4116e-02 eta: 0:07:25 time: 0.0340 data_time: 0.0061 memory: 1253 loss: 0.2523 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.2523 2022/11/28 20:03:19 - mmengine - INFO - Epoch(train) [11][2000/2462] lr: 2.3775e-02 eta: 0:07:21 time: 0.0341 data_time: 0.0061 memory: 1253 loss: 0.3231 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3231 2022/11/28 20:03:22 - mmengine - INFO - Epoch(train) [11][2100/2462] lr: 2.3437e-02 eta: 0:07:18 time: 0.0360 data_time: 0.0062 memory: 1253 loss: 0.2535 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2535 2022/11/28 20:03:26 - mmengine - INFO - Epoch(train) [11][2200/2462] lr: 2.3100e-02 eta: 0:07:14 time: 0.0342 data_time: 0.0061 memory: 1253 loss: 0.2297 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2297 2022/11/28 20:03:29 - mmengine - INFO - Epoch(train) [11][2300/2462] lr: 2.2764e-02 eta: 0:07:11 time: 0.0342 data_time: 0.0062 memory: 1253 loss: 0.2583 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.2583 2022/11/28 20:03:32 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:03:33 - mmengine - INFO - Epoch(train) [11][2400/2462] lr: 2.2431e-02 eta: 0:07:07 time: 0.0356 data_time: 0.0062 memory: 1253 loss: 0.2448 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.2448 2022/11/28 20:03:35 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:03:35 - mmengine - INFO - Epoch(train) [11][2462/2462] lr: 2.2225e-02 eta: 0:07:05 time: 0.0351 data_time: 0.0062 memory: 1253 loss: 0.2354 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2354 2022/11/28 20:03:35 - mmengine - INFO - Saving checkpoint at 11 epochs 2022/11/28 20:03:37 - mmengine - INFO - Epoch(val) [11][100/398] eta: 0:00:04 time: 0.0148 data_time: 0.0057 memory: 262 2022/11/28 20:03:38 - mmengine - INFO - Epoch(val) [11][200/398] eta: 0:00:03 time: 0.0156 data_time: 0.0061 memory: 262 2022/11/28 20:03:40 - mmengine - INFO - Epoch(val) [11][300/398] eta: 0:00:01 time: 0.0149 data_time: 0.0057 memory: 262 2022/11/28 20:03:42 - mmengine - INFO - Epoch(val) [11][398/398] acc/top1: 0.7373 acc/top5: 0.9361 acc/mean1: 0.7599 2022/11/28 20:03:42 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_9.pth is removed 2022/11/28 20:03:43 - mmengine - INFO - The best checkpoint with 0.7373 acc/top1 at 11 epoch is saved to best_acc/top1_epoch_11.pth. 2022/11/28 20:03:46 - mmengine - INFO - Epoch(train) [12][100/2462] lr: 2.1894e-02 eta: 0:07:02 time: 0.0357 data_time: 0.0061 memory: 1253 loss: 0.1649 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1649 2022/11/28 20:03:50 - mmengine - INFO - Epoch(train) [12][200/2462] lr: 2.1565e-02 eta: 0:06:58 time: 0.0358 data_time: 0.0061 memory: 1253 loss: 0.2640 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2640 2022/11/28 20:03:53 - mmengine - INFO - Epoch(train) [12][300/2462] lr: 2.1238e-02 eta: 0:06:55 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.2332 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2332 2022/11/28 20:03:57 - mmengine - INFO - Epoch(train) [12][400/2462] lr: 2.0913e-02 eta: 0:06:52 time: 0.0363 data_time: 0.0067 memory: 1253 loss: 0.2046 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2046 2022/11/28 20:04:01 - mmengine - INFO - Epoch(train) [12][500/2462] lr: 2.0589e-02 eta: 0:06:48 time: 0.0347 data_time: 0.0068 memory: 1253 loss: 0.2034 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.2034 2022/11/28 20:04:04 - mmengine - INFO - Epoch(train) [12][600/2462] lr: 2.0268e-02 eta: 0:06:45 time: 0.0341 data_time: 0.0063 memory: 1253 loss: 0.1611 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1611 2022/11/28 20:04:07 - mmengine - INFO - Epoch(train) [12][700/2462] lr: 1.9948e-02 eta: 0:06:41 time: 0.0338 data_time: 0.0061 memory: 1253 loss: 0.2267 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2267 2022/11/28 20:04:11 - mmengine - INFO - Epoch(train) [12][800/2462] lr: 1.9631e-02 eta: 0:06:38 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.2345 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.2345 2022/11/28 20:04:15 - mmengine - INFO - Epoch(train) [12][900/2462] lr: 1.9315e-02 eta: 0:06:34 time: 0.0360 data_time: 0.0062 memory: 1253 loss: 0.1984 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1984 2022/11/28 20:04:15 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:04:18 - mmengine - INFO - Epoch(train) [12][1000/2462] lr: 1.9001e-02 eta: 0:06:31 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.2452 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2452 2022/11/28 20:04:22 - mmengine - INFO - Epoch(train) [12][1100/2462] lr: 1.8689e-02 eta: 0:06:27 time: 0.0357 data_time: 0.0062 memory: 1253 loss: 0.2968 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.2968 2022/11/28 20:04:25 - mmengine - INFO - Epoch(train) [12][1200/2462] lr: 1.8379e-02 eta: 0:06:24 time: 0.0354 data_time: 0.0062 memory: 1253 loss: 0.2309 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.2309 2022/11/28 20:04:29 - mmengine - INFO - Epoch(train) [12][1300/2462] lr: 1.8071e-02 eta: 0:06:21 time: 0.0354 data_time: 0.0067 memory: 1253 loss: 0.2071 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2071 2022/11/28 20:04:32 - mmengine - INFO - Epoch(train) [12][1400/2462] lr: 1.7765e-02 eta: 0:06:17 time: 0.0362 data_time: 0.0069 memory: 1253 loss: 0.1647 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1647 2022/11/28 20:04:36 - mmengine - INFO - Epoch(train) [12][1500/2462] lr: 1.7462e-02 eta: 0:06:14 time: 0.0355 data_time: 0.0063 memory: 1253 loss: 0.2005 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2005 2022/11/28 20:04:39 - mmengine - INFO - Epoch(train) [12][1600/2462] lr: 1.7160e-02 eta: 0:06:10 time: 0.0354 data_time: 0.0067 memory: 1253 loss: 0.1434 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1434 2022/11/28 20:04:43 - mmengine - INFO - Epoch(train) [12][1700/2462] lr: 1.6860e-02 eta: 0:06:07 time: 0.0345 data_time: 0.0061 memory: 1253 loss: 0.1564 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.1564 2022/11/28 20:04:46 - mmengine - INFO - Epoch(train) [12][1800/2462] lr: 1.6563e-02 eta: 0:06:03 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.1796 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1796 2022/11/28 20:04:49 - mmengine - INFO - Epoch(train) [12][1900/2462] lr: 1.6267e-02 eta: 0:06:00 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.1856 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1856 2022/11/28 20:04:50 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:04:53 - mmengine - INFO - Epoch(train) [12][2000/2462] lr: 1.5974e-02 eta: 0:05:56 time: 0.0337 data_time: 0.0062 memory: 1253 loss: 0.1560 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.1560 2022/11/28 20:04:57 - mmengine - INFO - Epoch(train) [12][2100/2462] lr: 1.5683e-02 eta: 0:05:53 time: 0.0350 data_time: 0.0062 memory: 1253 loss: 0.2026 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2026 2022/11/28 20:05:00 - mmengine - INFO - Epoch(train) [12][2200/2462] lr: 1.5394e-02 eta: 0:05:49 time: 0.0338 data_time: 0.0061 memory: 1253 loss: 0.1814 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1814 2022/11/28 20:05:03 - mmengine - INFO - Epoch(train) [12][2300/2462] lr: 1.5107e-02 eta: 0:05:46 time: 0.0341 data_time: 0.0062 memory: 1253 loss: 0.1727 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1727 2022/11/28 20:05:07 - mmengine - INFO - Epoch(train) [12][2400/2462] lr: 1.4823e-02 eta: 0:05:42 time: 0.0340 data_time: 0.0062 memory: 1253 loss: 0.1493 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1493 2022/11/28 20:05:09 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:05:09 - mmengine - INFO - Epoch(train) [12][2462/2462] lr: 1.4647e-02 eta: 0:05:40 time: 0.0351 data_time: 0.0063 memory: 1253 loss: 0.1358 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1358 2022/11/28 20:05:09 - mmengine - INFO - Saving checkpoint at 12 epochs 2022/11/28 20:05:11 - mmengine - INFO - Epoch(val) [12][100/398] eta: 0:00:04 time: 0.0149 data_time: 0.0058 memory: 262 2022/11/28 20:05:12 - mmengine - INFO - Epoch(val) [12][200/398] eta: 0:00:03 time: 0.0150 data_time: 0.0058 memory: 262 2022/11/28 20:05:14 - mmengine - INFO - Epoch(val) [12][300/398] eta: 0:00:01 time: 0.0149 data_time: 0.0058 memory: 262 2022/11/28 20:05:16 - mmengine - INFO - Epoch(val) [12][398/398] acc/top1: 0.7274 acc/top5: 0.9279 acc/mean1: 0.7536 2022/11/28 20:05:20 - mmengine - INFO - Epoch(train) [13][100/2462] lr: 1.4367e-02 eta: 0:05:37 time: 0.0341 data_time: 0.0061 memory: 1253 loss: 0.1421 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1421 2022/11/28 20:05:23 - mmengine - INFO - Epoch(train) [13][200/2462] lr: 1.4088e-02 eta: 0:05:33 time: 0.0347 data_time: 0.0062 memory: 1253 loss: 0.0889 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0889 2022/11/28 20:05:27 - mmengine - INFO - Epoch(train) [13][300/2462] lr: 1.3812e-02 eta: 0:05:30 time: 0.0345 data_time: 0.0065 memory: 1253 loss: 0.1427 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1427 2022/11/28 20:05:30 - mmengine - INFO - Epoch(train) [13][400/2462] lr: 1.3538e-02 eta: 0:05:26 time: 0.0348 data_time: 0.0067 memory: 1253 loss: 0.1256 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1256 2022/11/28 20:05:32 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:05:34 - mmengine - INFO - Epoch(train) [13][500/2462] lr: 1.3266e-02 eta: 0:05:23 time: 0.0351 data_time: 0.0067 memory: 1253 loss: 0.0903 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0903 2022/11/28 20:05:37 - mmengine - INFO - Epoch(train) [13][600/2462] lr: 1.2997e-02 eta: 0:05:20 time: 0.0340 data_time: 0.0061 memory: 1253 loss: 0.1416 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1416 2022/11/28 20:05:41 - mmengine - INFO - Epoch(train) [13][700/2462] lr: 1.2730e-02 eta: 0:05:16 time: 0.0353 data_time: 0.0061 memory: 1253 loss: 0.1569 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.1569 2022/11/28 20:05:44 - mmengine - INFO - Epoch(train) [13][800/2462] lr: 1.2465e-02 eta: 0:05:13 time: 0.0356 data_time: 0.0061 memory: 1253 loss: 0.1561 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1561 2022/11/28 20:05:48 - mmengine - INFO - Epoch(train) [13][900/2462] lr: 1.2203e-02 eta: 0:05:09 time: 0.0358 data_time: 0.0061 memory: 1253 loss: 0.1183 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1183 2022/11/28 20:05:52 - mmengine - INFO - Epoch(train) [13][1000/2462] lr: 1.1943e-02 eta: 0:05:06 time: 0.0357 data_time: 0.0061 memory: 1253 loss: 0.1061 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.1061 2022/11/28 20:05:55 - mmengine - INFO - Epoch(train) [13][1100/2462] lr: 1.1686e-02 eta: 0:05:02 time: 0.0344 data_time: 0.0061 memory: 1253 loss: 0.1084 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1084 2022/11/28 20:05:59 - mmengine - INFO - Epoch(train) [13][1200/2462] lr: 1.1431e-02 eta: 0:04:59 time: 0.0348 data_time: 0.0061 memory: 1253 loss: 0.1359 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1359 2022/11/28 20:06:02 - mmengine - INFO - Epoch(train) [13][1300/2462] lr: 1.1178e-02 eta: 0:04:55 time: 0.0354 data_time: 0.0062 memory: 1253 loss: 0.1795 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1795 2022/11/28 20:06:06 - mmengine - INFO - Epoch(train) [13][1400/2462] lr: 1.0928e-02 eta: 0:04:52 time: 0.0342 data_time: 0.0067 memory: 1253 loss: 0.0973 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0973 2022/11/28 20:06:07 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:06:09 - mmengine - INFO - Epoch(train) [13][1500/2462] lr: 1.0680e-02 eta: 0:04:49 time: 0.0345 data_time: 0.0064 memory: 1253 loss: 0.1000 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1000 2022/11/28 20:06:13 - mmengine - INFO - Epoch(train) [13][1600/2462] lr: 1.0435e-02 eta: 0:04:45 time: 0.0340 data_time: 0.0062 memory: 1253 loss: 0.1036 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1036 2022/11/28 20:06:16 - mmengine - INFO - Epoch(train) [13][1700/2462] lr: 1.0193e-02 eta: 0:04:42 time: 0.0341 data_time: 0.0062 memory: 1253 loss: 0.1320 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1320 2022/11/28 20:06:19 - mmengine - INFO - Epoch(train) [13][1800/2462] lr: 9.9527e-03 eta: 0:04:38 time: 0.0364 data_time: 0.0062 memory: 1253 loss: 0.0941 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0941 2022/11/28 20:06:23 - mmengine - INFO - Epoch(train) [13][1900/2462] lr: 9.7153e-03 eta: 0:04:35 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.0977 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0977 2022/11/28 20:06:26 - mmengine - INFO - Epoch(train) [13][2000/2462] lr: 9.4804e-03 eta: 0:04:31 time: 0.0350 data_time: 0.0062 memory: 1253 loss: 0.1137 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1137 2022/11/28 20:06:30 - mmengine - INFO - Epoch(train) [13][2100/2462] lr: 9.2480e-03 eta: 0:04:28 time: 0.0341 data_time: 0.0061 memory: 1253 loss: 0.0837 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0837 2022/11/28 20:06:33 - mmengine - INFO - Epoch(train) [13][2200/2462] lr: 9.0183e-03 eta: 0:04:24 time: 0.0352 data_time: 0.0061 memory: 1253 loss: 0.0850 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0850 2022/11/28 20:06:37 - mmengine - INFO - Epoch(train) [13][2300/2462] lr: 8.7911e-03 eta: 0:04:21 time: 0.0341 data_time: 0.0064 memory: 1253 loss: 0.0897 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0897 2022/11/28 20:06:40 - mmengine - INFO - Epoch(train) [13][2400/2462] lr: 8.5666e-03 eta: 0:04:17 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.1262 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1262 2022/11/28 20:06:42 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:06:42 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:06:42 - mmengine - INFO - Epoch(train) [13][2462/2462] lr: 8.4287e-03 eta: 0:04:15 time: 0.0340 data_time: 0.0062 memory: 1253 loss: 0.0886 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0886 2022/11/28 20:06:42 - mmengine - INFO - Saving checkpoint at 13 epochs 2022/11/28 20:06:44 - mmengine - INFO - Epoch(val) [13][100/398] eta: 0:00:04 time: 0.0150 data_time: 0.0060 memory: 262 2022/11/28 20:06:46 - mmengine - INFO - Epoch(val) [13][200/398] eta: 0:00:03 time: 0.0151 data_time: 0.0060 memory: 262 2022/11/28 20:06:48 - mmengine - INFO - Epoch(val) [13][300/398] eta: 0:00:01 time: 0.0153 data_time: 0.0060 memory: 262 2022/11/28 20:06:50 - mmengine - INFO - Epoch(val) [13][398/398] acc/top1: 0.7767 acc/top5: 0.9524 acc/mean1: 0.7961 2022/11/28 20:06:50 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_11.pth is removed 2022/11/28 20:06:50 - mmengine - INFO - The best checkpoint with 0.7767 acc/top1 at 13 epoch is saved to best_acc/top1_epoch_13.pth. 2022/11/28 20:06:54 - mmengine - INFO - Epoch(train) [14][100/2462] lr: 8.2085e-03 eta: 0:04:12 time: 0.0361 data_time: 0.0065 memory: 1253 loss: 0.0682 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0682 2022/11/28 20:06:57 - mmengine - INFO - Epoch(train) [14][200/2462] lr: 7.9909e-03 eta: 0:04:08 time: 0.0346 data_time: 0.0062 memory: 1253 loss: 0.0730 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0730 2022/11/28 20:07:01 - mmengine - INFO - Epoch(train) [14][300/2462] lr: 7.7760e-03 eta: 0:04:05 time: 0.0343 data_time: 0.0063 memory: 1253 loss: 0.0927 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0927 2022/11/28 20:07:04 - mmengine - INFO - Epoch(train) [14][400/2462] lr: 7.5638e-03 eta: 0:04:01 time: 0.0346 data_time: 0.0067 memory: 1253 loss: 0.1092 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1092 2022/11/28 20:07:08 - mmengine - INFO - Epoch(train) [14][500/2462] lr: 7.3542e-03 eta: 0:03:58 time: 0.0346 data_time: 0.0062 memory: 1253 loss: 0.1167 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1167 2022/11/28 20:07:11 - mmengine - INFO - Epoch(train) [14][600/2462] lr: 7.1474e-03 eta: 0:03:55 time: 0.0354 data_time: 0.0077 memory: 1253 loss: 0.0677 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0677 2022/11/28 20:07:15 - mmengine - INFO - Epoch(train) [14][700/2462] lr: 6.9433e-03 eta: 0:03:51 time: 0.0346 data_time: 0.0062 memory: 1253 loss: 0.0760 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0760 2022/11/28 20:07:18 - mmengine - INFO - Epoch(train) [14][800/2462] lr: 6.7420e-03 eta: 0:03:48 time: 0.0345 data_time: 0.0062 memory: 1253 loss: 0.0613 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0613 2022/11/28 20:07:22 - mmengine - INFO - Epoch(train) [14][900/2462] lr: 6.5434e-03 eta: 0:03:44 time: 0.0346 data_time: 0.0062 memory: 1253 loss: 0.0734 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0734 2022/11/28 20:07:25 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:07:25 - mmengine - INFO - Epoch(train) [14][1000/2462] lr: 6.3476e-03 eta: 0:03:41 time: 0.0355 data_time: 0.0061 memory: 1253 loss: 0.0787 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0787 2022/11/28 20:07:29 - mmengine - INFO - Epoch(train) [14][1100/2462] lr: 6.1545e-03 eta: 0:03:37 time: 0.0342 data_time: 0.0063 memory: 1253 loss: 0.0730 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0730 2022/11/28 20:07:32 - mmengine - INFO - Epoch(train) [14][1200/2462] lr: 5.9642e-03 eta: 0:03:34 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.0635 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0635 2022/11/28 20:07:36 - mmengine - INFO - Epoch(train) [14][1300/2462] lr: 5.7768e-03 eta: 0:03:30 time: 0.0358 data_time: 0.0062 memory: 1253 loss: 0.0656 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0656 2022/11/28 20:07:39 - mmengine - INFO - Epoch(train) [14][1400/2462] lr: 5.5921e-03 eta: 0:03:27 time: 0.0347 data_time: 0.0062 memory: 1253 loss: 0.0558 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0558 2022/11/28 20:07:43 - mmengine - INFO - Epoch(train) [14][1500/2462] lr: 5.4103e-03 eta: 0:03:23 time: 0.0356 data_time: 0.0063 memory: 1253 loss: 0.0751 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0751 2022/11/28 20:07:47 - mmengine - INFO - Epoch(train) [14][1600/2462] lr: 5.2313e-03 eta: 0:03:20 time: 0.0351 data_time: 0.0063 memory: 1253 loss: 0.0640 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0640 2022/11/28 20:07:50 - mmengine - INFO - Epoch(train) [14][1700/2462] lr: 5.0551e-03 eta: 0:03:17 time: 0.0344 data_time: 0.0062 memory: 1253 loss: 0.0601 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0601 2022/11/28 20:07:54 - mmengine - INFO - Epoch(train) [14][1800/2462] lr: 4.8818e-03 eta: 0:03:13 time: 0.0347 data_time: 0.0063 memory: 1253 loss: 0.0410 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0410 2022/11/28 20:07:57 - mmengine - INFO - Epoch(train) [14][1900/2462] lr: 4.7114e-03 eta: 0:03:10 time: 0.0342 data_time: 0.0062 memory: 1253 loss: 0.0496 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0496 2022/11/28 20:08:00 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:08:01 - mmengine - INFO - Epoch(train) [14][2000/2462] lr: 4.5439e-03 eta: 0:03:06 time: 0.0342 data_time: 0.0062 memory: 1253 loss: 0.0678 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0678 2022/11/28 20:08:04 - mmengine - INFO - Epoch(train) [14][2100/2462] lr: 4.3792e-03 eta: 0:03:03 time: 0.0342 data_time: 0.0061 memory: 1253 loss: 0.0802 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0802 2022/11/28 20:08:08 - mmengine - INFO - Epoch(train) [14][2200/2462] lr: 4.2175e-03 eta: 0:02:59 time: 0.0342 data_time: 0.0060 memory: 1253 loss: 0.0610 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0610 2022/11/28 20:08:11 - mmengine - INFO - Epoch(train) [14][2300/2462] lr: 4.0587e-03 eta: 0:02:56 time: 0.0351 data_time: 0.0062 memory: 1253 loss: 0.0364 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0364 2022/11/28 20:08:15 - mmengine - INFO - Epoch(train) [14][2400/2462] lr: 3.9027e-03 eta: 0:02:52 time: 0.0354 data_time: 0.0062 memory: 1253 loss: 0.0994 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0994 2022/11/28 20:08:17 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:08:17 - mmengine - INFO - Epoch(train) [14][2462/2462] lr: 3.8075e-03 eta: 0:02:50 time: 0.0357 data_time: 0.0063 memory: 1253 loss: 0.0620 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0620 2022/11/28 20:08:17 - mmengine - INFO - Saving checkpoint at 14 epochs 2022/11/28 20:08:19 - mmengine - INFO - Epoch(val) [14][100/398] eta: 0:00:04 time: 0.0150 data_time: 0.0057 memory: 262 2022/11/28 20:08:20 - mmengine - INFO - Epoch(val) [14][200/398] eta: 0:00:03 time: 0.0148 data_time: 0.0057 memory: 262 2022/11/28 20:08:22 - mmengine - INFO - Epoch(val) [14][300/398] eta: 0:00:01 time: 0.0149 data_time: 0.0057 memory: 262 2022/11/28 20:08:24 - mmengine - INFO - Epoch(val) [14][398/398] acc/top1: 0.7836 acc/top5: 0.9504 acc/mean1: 0.8059 2022/11/28 20:08:24 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_13.pth is removed 2022/11/28 20:08:25 - mmengine - INFO - The best checkpoint with 0.7836 acc/top1 at 14 epoch is saved to best_acc/top1_epoch_14.pth. 2022/11/28 20:08:28 - mmengine - INFO - Epoch(train) [15][100/2462] lr: 3.6564e-03 eta: 0:02:47 time: 0.0348 data_time: 0.0061 memory: 1253 loss: 0.0244 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0244 2022/11/28 20:08:32 - mmengine - INFO - Epoch(train) [15][200/2462] lr: 3.5082e-03 eta: 0:02:43 time: 0.0357 data_time: 0.0069 memory: 1253 loss: 0.0344 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0344 2022/11/28 20:08:35 - mmengine - INFO - Epoch(train) [15][300/2462] lr: 3.3629e-03 eta: 0:02:40 time: 0.0352 data_time: 0.0062 memory: 1253 loss: 0.0480 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0480 2022/11/28 20:08:39 - mmengine - INFO - Epoch(train) [15][400/2462] lr: 3.2206e-03 eta: 0:02:36 time: 0.0351 data_time: 0.0063 memory: 1253 loss: 0.0640 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0640 2022/11/28 20:08:42 - mmengine - INFO - Epoch(train) [15][500/2462] lr: 3.0813e-03 eta: 0:02:33 time: 0.0348 data_time: 0.0063 memory: 1253 loss: 0.0584 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0584 2022/11/28 20:08:43 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:08:46 - mmengine - INFO - Epoch(train) [15][600/2462] lr: 2.9450e-03 eta: 0:02:29 time: 0.0351 data_time: 0.0063 memory: 1253 loss: 0.0566 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0566 2022/11/28 20:08:49 - mmengine - INFO - Epoch(train) [15][700/2462] lr: 2.8117e-03 eta: 0:02:26 time: 0.0351 data_time: 0.0062 memory: 1253 loss: 0.0592 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0592 2022/11/28 20:08:53 - mmengine - INFO - Epoch(train) [15][800/2462] lr: 2.6813e-03 eta: 0:02:22 time: 0.0344 data_time: 0.0063 memory: 1253 loss: 0.0429 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0429 2022/11/28 20:08:56 - mmengine - INFO - Epoch(train) [15][900/2462] lr: 2.5540e-03 eta: 0:02:19 time: 0.0353 data_time: 0.0063 memory: 1253 loss: 0.0309 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0309 2022/11/28 20:09:00 - mmengine - INFO - Epoch(train) [15][1000/2462] lr: 2.4297e-03 eta: 0:02:16 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.0508 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0508 2022/11/28 20:09:03 - mmengine - INFO - Epoch(train) [15][1100/2462] lr: 2.3084e-03 eta: 0:02:12 time: 0.0345 data_time: 0.0062 memory: 1253 loss: 0.0776 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0776 2022/11/28 20:09:07 - mmengine - INFO - Epoch(train) [15][1200/2462] lr: 2.1902e-03 eta: 0:02:09 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.0408 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0408 2022/11/28 20:09:10 - mmengine - INFO - Epoch(train) [15][1300/2462] lr: 2.0750e-03 eta: 0:02:05 time: 0.0351 data_time: 0.0070 memory: 1253 loss: 0.0365 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0365 2022/11/28 20:09:14 - mmengine - INFO - Epoch(train) [15][1400/2462] lr: 1.9628e-03 eta: 0:02:02 time: 0.0340 data_time: 0.0061 memory: 1253 loss: 0.0406 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0406 2022/11/28 20:09:17 - mmengine - INFO - Epoch(train) [15][1500/2462] lr: 1.8537e-03 eta: 0:01:58 time: 0.0344 data_time: 0.0062 memory: 1253 loss: 0.0323 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0323 2022/11/28 20:09:18 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:09:21 - mmengine - INFO - Epoch(train) [15][1600/2462] lr: 1.7477e-03 eta: 0:01:55 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.0596 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0596 2022/11/28 20:09:24 - mmengine - INFO - Epoch(train) [15][1700/2462] lr: 1.6447e-03 eta: 0:01:51 time: 0.0346 data_time: 0.0062 memory: 1253 loss: 0.0363 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0363 2022/11/28 20:09:27 - mmengine - INFO - Epoch(train) [15][1800/2462] lr: 1.5448e-03 eta: 0:01:48 time: 0.0341 data_time: 0.0062 memory: 1253 loss: 0.0401 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0401 2022/11/28 20:09:31 - mmengine - INFO - Epoch(train) [15][1900/2462] lr: 1.4480e-03 eta: 0:01:44 time: 0.0344 data_time: 0.0061 memory: 1253 loss: 0.0473 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0473 2022/11/28 20:09:35 - mmengine - INFO - Epoch(train) [15][2000/2462] lr: 1.3543e-03 eta: 0:01:41 time: 0.0366 data_time: 0.0061 memory: 1253 loss: 0.0584 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0584 2022/11/28 20:09:38 - mmengine - INFO - Epoch(train) [15][2100/2462] lr: 1.2636e-03 eta: 0:01:37 time: 0.0342 data_time: 0.0062 memory: 1253 loss: 0.0451 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0451 2022/11/28 20:09:42 - mmengine - INFO - Epoch(train) [15][2200/2462] lr: 1.1761e-03 eta: 0:01:34 time: 0.0353 data_time: 0.0062 memory: 1253 loss: 0.0393 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0393 2022/11/28 20:09:45 - mmengine - INFO - Epoch(train) [15][2300/2462] lr: 1.0917e-03 eta: 0:01:30 time: 0.0344 data_time: 0.0062 memory: 1253 loss: 0.0228 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0228 2022/11/28 20:09:49 - mmengine - INFO - Epoch(train) [15][2400/2462] lr: 1.0104e-03 eta: 0:01:27 time: 0.0342 data_time: 0.0063 memory: 1253 loss: 0.0271 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0271 2022/11/28 20:09:51 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:09:51 - mmengine - INFO - Epoch(train) [15][2462/2462] lr: 9.6151e-04 eta: 0:01:25 time: 0.0343 data_time: 0.0063 memory: 1253 loss: 0.0320 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0320 2022/11/28 20:09:51 - mmengine - INFO - Saving checkpoint at 15 epochs 2022/11/28 20:09:53 - mmengine - INFO - Epoch(val) [15][100/398] eta: 0:00:04 time: 0.0148 data_time: 0.0057 memory: 262 2022/11/28 20:09:54 - mmengine - INFO - Epoch(val) [15][200/398] eta: 0:00:03 time: 0.0152 data_time: 0.0060 memory: 262 2022/11/28 20:09:56 - mmengine - INFO - Epoch(val) [15][300/398] eta: 0:00:01 time: 0.0150 data_time: 0.0058 memory: 262 2022/11/28 20:09:58 - mmengine - INFO - Epoch(val) [15][398/398] acc/top1: 0.7833 acc/top5: 0.9496 acc/mean1: 0.8050 2022/11/28 20:10:01 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:10:02 - mmengine - INFO - Epoch(train) [16][100/2462] lr: 8.8525e-04 eta: 0:01:21 time: 0.0355 data_time: 0.0062 memory: 1253 loss: 0.0209 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0209 2022/11/28 20:10:05 - mmengine - INFO - Epoch(train) [16][200/2462] lr: 8.1211e-04 eta: 0:01:18 time: 0.0344 data_time: 0.0062 memory: 1253 loss: 0.0266 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0266 2022/11/28 20:10:09 - mmengine - INFO - Epoch(train) [16][300/2462] lr: 7.4209e-04 eta: 0:01:14 time: 0.0356 data_time: 0.0069 memory: 1253 loss: 0.0333 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0333 2022/11/28 20:10:12 - mmengine - INFO - Epoch(train) [16][400/2462] lr: 6.7522e-04 eta: 0:01:11 time: 0.0346 data_time: 0.0061 memory: 1253 loss: 0.0349 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0349 2022/11/28 20:10:16 - mmengine - INFO - Epoch(train) [16][500/2462] lr: 6.1147e-04 eta: 0:01:08 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.0400 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0400 2022/11/28 20:10:19 - mmengine - INFO - Epoch(train) [16][600/2462] lr: 5.5087e-04 eta: 0:01:04 time: 0.0364 data_time: 0.0063 memory: 1253 loss: 0.0268 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0268 2022/11/28 20:10:23 - mmengine - INFO - Epoch(train) [16][700/2462] lr: 4.9342e-04 eta: 0:01:01 time: 0.0350 data_time: 0.0073 memory: 1253 loss: 0.0242 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0242 2022/11/28 20:10:27 - mmengine - INFO - Epoch(train) [16][800/2462] lr: 4.3911e-04 eta: 0:00:57 time: 0.0347 data_time: 0.0070 memory: 1253 loss: 0.0465 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0465 2022/11/28 20:10:30 - mmengine - INFO - Epoch(train) [16][900/2462] lr: 3.8795e-04 eta: 0:00:54 time: 0.0351 data_time: 0.0070 memory: 1253 loss: 0.0277 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0277 2022/11/28 20:10:34 - mmengine - INFO - Epoch(train) [16][1000/2462] lr: 3.3995e-04 eta: 0:00:50 time: 0.0363 data_time: 0.0061 memory: 1253 loss: 0.0509 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0509 2022/11/28 20:10:36 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:10:37 - mmengine - INFO - Epoch(train) [16][1100/2462] lr: 2.9511e-04 eta: 0:00:47 time: 0.0347 data_time: 0.0063 memory: 1253 loss: 0.0359 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0359 2022/11/28 20:10:41 - mmengine - INFO - Epoch(train) [16][1200/2462] lr: 2.5343e-04 eta: 0:00:43 time: 0.0348 data_time: 0.0069 memory: 1253 loss: 0.0587 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.0587 2022/11/28 20:10:44 - mmengine - INFO - Epoch(train) [16][1300/2462] lr: 2.1492e-04 eta: 0:00:40 time: 0.0345 data_time: 0.0062 memory: 1253 loss: 0.0341 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0341 2022/11/28 20:10:48 - mmengine - INFO - Epoch(train) [16][1400/2462] lr: 1.7957e-04 eta: 0:00:36 time: 0.0345 data_time: 0.0062 memory: 1253 loss: 0.0554 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0554 2022/11/28 20:10:51 - mmengine - INFO - Epoch(train) [16][1500/2462] lr: 1.4739e-04 eta: 0:00:33 time: 0.0341 data_time: 0.0062 memory: 1253 loss: 0.0442 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0442 2022/11/28 20:10:55 - mmengine - INFO - Epoch(train) [16][1600/2462] lr: 1.1838e-04 eta: 0:00:29 time: 0.0355 data_time: 0.0061 memory: 1253 loss: 0.0336 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0336 2022/11/28 20:10:58 - mmengine - INFO - Epoch(train) [16][1700/2462] lr: 9.2542e-05 eta: 0:00:26 time: 0.0352 data_time: 0.0062 memory: 1253 loss: 0.0246 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0246 2022/11/28 20:11:02 - mmengine - INFO - Epoch(train) [16][1800/2462] lr: 6.9879e-05 eta: 0:00:22 time: 0.0359 data_time: 0.0065 memory: 1253 loss: 0.0195 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0195 2022/11/28 20:11:05 - mmengine - INFO - Epoch(train) [16][1900/2462] lr: 5.0393e-05 eta: 0:00:19 time: 0.0343 data_time: 0.0061 memory: 1253 loss: 0.0209 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0209 2022/11/28 20:11:09 - mmengine - INFO - Epoch(train) [16][2000/2462] lr: 3.4083e-05 eta: 0:00:16 time: 0.0352 data_time: 0.0065 memory: 1253 loss: 0.0303 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0303 2022/11/28 20:11:11 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:11:12 - mmengine - INFO - Epoch(train) [16][2100/2462] lr: 2.0951e-05 eta: 0:00:12 time: 0.0350 data_time: 0.0067 memory: 1253 loss: 0.0293 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0293 2022/11/28 20:11:16 - mmengine - INFO - Epoch(train) [16][2200/2462] lr: 1.0998e-05 eta: 0:00:09 time: 0.0352 data_time: 0.0067 memory: 1253 loss: 0.0472 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0472 2022/11/28 20:11:19 - mmengine - INFO - Epoch(train) [16][2300/2462] lr: 4.2247e-06 eta: 0:00:05 time: 0.0346 data_time: 0.0062 memory: 1253 loss: 0.0276 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0276 2022/11/28 20:11:23 - mmengine - INFO - Epoch(train) [16][2400/2462] lr: 6.3111e-07 eta: 0:00:02 time: 0.0344 data_time: 0.0062 memory: 1253 loss: 0.0276 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0276 2022/11/28 20:11:25 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_194451 2022/11/28 20:11:25 - mmengine - INFO - Epoch(train) [16][2462/2462] lr: 1.5901e-10 eta: 0:00:00 time: 0.0360 data_time: 0.0071 memory: 1253 loss: 0.0485 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0485 2022/11/28 20:11:25 - mmengine - INFO - Saving checkpoint at 16 epochs 2022/11/28 20:11:27 - mmengine - INFO - Epoch(val) [16][100/398] eta: 0:00:04 time: 0.0145 data_time: 0.0056 memory: 262 2022/11/28 20:11:29 - mmengine - INFO - Epoch(val) [16][200/398] eta: 0:00:03 time: 0.0146 data_time: 0.0056 memory: 262 2022/11/28 20:11:30 - mmengine - INFO - Epoch(val) [16][300/398] eta: 0:00:01 time: 0.0147 data_time: 0.0056 memory: 262 2022/11/28 20:11:33 - mmengine - INFO - Epoch(val) [16][398/398] acc/top1: 0.7881 acc/top5: 0.9529 acc/mean1: 0.8087 2022/11/28 20:11:33 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_14.pth is removed 2022/11/28 20:11:33 - mmengine - INFO - The best checkpoint with 0.7881 acc/top1 at 16 epoch is saved to best_acc/top1_epoch_16.pth.