2022/11/28 17:24:44 - 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: 784504161 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 17:24:45 - 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='nturgb+d', mode='stgcn_spatial')), cls_head=dict(type='GCNHead', num_classes=120, in_channels=256)) dataset_type = 'PoseDataset' ann_file = 'data/skeleton/ntu120_3d.pkl' train_pipeline = [ dict(type='PreNormalize3D'), dict(type='GenSkeFeat', dataset='nturgb+d', feats=['bm']), dict(type='UniformSampleFrames', clip_len=100), dict(type='PoseDecode'), dict(type='FormatGCNInput', num_person=2), dict(type='PackActionInputs') ] val_pipeline = [ dict(type='PreNormalize3D'), dict(type='GenSkeFeat', dataset='nturgb+d', 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='PreNormalize3D'), dict(type='GenSkeFeat', dataset='nturgb+d', 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_3d.pkl', pipeline=[ dict(type='PreNormalize3D'), dict(type='GenSkeFeat', dataset='nturgb+d', 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_3d.pkl', pipeline=[ dict(type='PreNormalize3D'), dict(type='GenSkeFeat', dataset='nturgb+d', 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_3d.pkl', pipeline=[ dict(type='PreNormalize3D'), dict(type='GenSkeFeat', dataset='nturgb+d', 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-3d' randomness = dict(seed=None, diff_rank_seed=False, deterministic=False) 2022/11/28 17:24:45 - mmengine - INFO - Result has been saved to /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d/modules_statistic_results.json Name of parameter - Initialization information data_bn.weight - torch.Size([75]): The value is the same before and after calling `init_weights` of STGCN data_bn.bias - torch.Size([75]): The value is the same before and after calling `init_weights` of STGCN gcn.0.gcn.PA - torch.Size([3, 25, 25]): 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, 25, 25]): 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, 25, 25]): 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, 25, 25]): 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, 25, 25]): 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, 25, 25]): 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, 25, 25]): 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, 25, 25]): 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, 25, 25]): 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, 25, 25]): 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 17:26:41 - mmengine - INFO - Checkpoints will be saved to /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d. 2022/11/28 17:26:49 - mmengine - INFO - Epoch(train) [1][100/2462] lr: 9.9998e-02 eta: 0:51:49 time: 0.0434 data_time: 0.0067 memory: 1794 loss: 4.0331 top1_acc: 0.0625 top5_acc: 0.1250 loss_cls: 4.0331 2022/11/28 17:26:53 - mmengine - INFO - Epoch(train) [1][200/2462] lr: 9.9994e-02 eta: 0:40:17 time: 0.0434 data_time: 0.0060 memory: 1794 loss: 3.4131 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.4131 2022/11/28 17:26:58 - mmengine - INFO - Epoch(train) [1][300/2462] lr: 9.9986e-02 eta: 0:36:27 time: 0.0442 data_time: 0.0059 memory: 1794 loss: 2.9281 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9281 2022/11/28 17:27:02 - mmengine - INFO - Epoch(train) [1][400/2462] lr: 9.9975e-02 eta: 0:34:23 time: 0.0437 data_time: 0.0060 memory: 1794 loss: 2.4697 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4697 2022/11/28 17:27:07 - mmengine - INFO - Epoch(train) [1][500/2462] lr: 9.9960e-02 eta: 0:33:08 time: 0.0433 data_time: 0.0069 memory: 1794 loss: 2.1006 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.1006 2022/11/28 17:27:11 - mmengine - INFO - Epoch(train) [1][600/2462] lr: 9.9943e-02 eta: 0:32:15 time: 0.0434 data_time: 0.0060 memory: 1794 loss: 2.0363 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0363 2022/11/28 17:27:15 - mmengine - INFO - Epoch(train) [1][700/2462] lr: 9.9922e-02 eta: 0:31:35 time: 0.0434 data_time: 0.0059 memory: 1794 loss: 1.8998 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8998 2022/11/28 17:27:20 - mmengine - INFO - Epoch(train) [1][800/2462] lr: 9.9899e-02 eta: 0:31:05 time: 0.0443 data_time: 0.0059 memory: 1794 loss: 1.8323 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8323 2022/11/28 17:27:24 - mmengine - INFO - Epoch(train) [1][900/2462] lr: 9.9872e-02 eta: 0:30:41 time: 0.0438 data_time: 0.0064 memory: 1794 loss: 1.7315 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.7315 2022/11/28 17:27:29 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:27:29 - mmengine - INFO - Epoch(train) [1][1000/2462] lr: 9.9841e-02 eta: 0:30:23 time: 0.0450 data_time: 0.0059 memory: 1794 loss: 1.5521 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5521 2022/11/28 17:27:33 - mmengine - INFO - Epoch(train) [1][1100/2462] lr: 9.9808e-02 eta: 0:30:04 time: 0.0437 data_time: 0.0068 memory: 1794 loss: 1.5213 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5213 2022/11/28 17:27:37 - mmengine - INFO - Epoch(train) [1][1200/2462] lr: 9.9772e-02 eta: 0:29:46 time: 0.0429 data_time: 0.0060 memory: 1794 loss: 1.5103 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5103 2022/11/28 17:27:42 - mmengine - INFO - Epoch(train) [1][1300/2462] lr: 9.9732e-02 eta: 0:29:32 time: 0.0438 data_time: 0.0064 memory: 1794 loss: 1.4178 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.4178 2022/11/28 17:27:46 - mmengine - INFO - Epoch(train) [1][1400/2462] lr: 9.9689e-02 eta: 0:29:17 time: 0.0427 data_time: 0.0060 memory: 1794 loss: 1.3782 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3782 2022/11/28 17:27:50 - mmengine - INFO - Epoch(train) [1][1500/2462] lr: 9.9643e-02 eta: 0:29:05 time: 0.0431 data_time: 0.0066 memory: 1794 loss: 1.5576 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5576 2022/11/28 17:27:55 - mmengine - INFO - Epoch(train) [1][1600/2462] lr: 9.9594e-02 eta: 0:28:54 time: 0.0439 data_time: 0.0059 memory: 1794 loss: 1.2722 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.2722 2022/11/28 17:27:59 - mmengine - INFO - Epoch(train) [1][1700/2462] lr: 9.9542e-02 eta: 0:28:43 time: 0.0426 data_time: 0.0059 memory: 1794 loss: 1.4169 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.4169 2022/11/28 17:28:03 - mmengine - INFO - Epoch(train) [1][1800/2462] lr: 9.9486e-02 eta: 0:28:34 time: 0.0432 data_time: 0.0060 memory: 1794 loss: 1.3870 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3870 2022/11/28 17:28:08 - mmengine - INFO - Epoch(train) [1][1900/2462] lr: 9.9428e-02 eta: 0:28:25 time: 0.0432 data_time: 0.0059 memory: 1794 loss: 1.5418 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5418 2022/11/28 17:28:12 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:28:12 - mmengine - INFO - Epoch(train) [1][2000/2462] lr: 9.9366e-02 eta: 0:28:17 time: 0.0437 data_time: 0.0060 memory: 1794 loss: 1.3987 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3987 2022/11/28 17:28:16 - mmengine - INFO - Epoch(train) [1][2100/2462] lr: 9.9301e-02 eta: 0:28:09 time: 0.0429 data_time: 0.0059 memory: 1794 loss: 1.3031 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3031 2022/11/28 17:28:21 - mmengine - INFO - Epoch(train) [1][2200/2462] lr: 9.9233e-02 eta: 0:28:02 time: 0.0434 data_time: 0.0065 memory: 1794 loss: 1.1771 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1771 2022/11/28 17:28:25 - mmengine - INFO - Epoch(train) [1][2300/2462] lr: 9.9162e-02 eta: 0:27:54 time: 0.0435 data_time: 0.0060 memory: 1794 loss: 1.2302 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2302 2022/11/28 17:28:29 - mmengine - INFO - Epoch(train) [1][2400/2462] lr: 9.9088e-02 eta: 0:27:47 time: 0.0433 data_time: 0.0063 memory: 1794 loss: 1.0838 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.0838 2022/11/28 17:28:32 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:28:32 - mmengine - INFO - Epoch(train) [1][2462/2462] lr: 9.9040e-02 eta: 0:27:43 time: 0.0439 data_time: 0.0062 memory: 1794 loss: 1.2012 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2012 2022/11/28 17:28:32 - mmengine - INFO - Saving checkpoint at 1 epochs 2022/11/28 17:28:36 - mmengine - INFO - Epoch(val) [1][100/398] eta: 0:00:11 time: 0.0353 data_time: 0.0220 memory: 364 2022/11/28 17:28:39 - mmengine - INFO - Epoch(val) [1][200/398] eta: 0:00:06 time: 0.0259 data_time: 0.0127 memory: 364 2022/11/28 17:28:42 - mmengine - INFO - Epoch(val) [1][300/398] eta: 0:00:03 time: 0.0263 data_time: 0.0137 memory: 364 2022/11/28 17:28:46 - mmengine - INFO - Epoch(val) [1][398/398] acc/top1: 0.5158 acc/top5: 0.8237 acc/mean1: 0.5259 2022/11/28 17:28:46 - mmengine - INFO - The best checkpoint with 0.5158 acc/top1 at 1 epoch is saved to best_acc/top1_epoch_1.pth. 2022/11/28 17:28:51 - mmengine - INFO - Epoch(train) [2][100/2462] lr: 9.8961e-02 eta: 0:27:39 time: 0.0437 data_time: 0.0066 memory: 1794 loss: 1.0583 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0583 2022/11/28 17:28:55 - mmengine - INFO - Epoch(train) [2][200/2462] lr: 9.8878e-02 eta: 0:27:33 time: 0.0443 data_time: 0.0059 memory: 1794 loss: 1.1811 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1811 2022/11/28 17:28:59 - mmengine - INFO - Epoch(train) [2][300/2462] lr: 9.8793e-02 eta: 0:27:27 time: 0.0431 data_time: 0.0060 memory: 1794 loss: 1.2345 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.2345 2022/11/28 17:29:04 - mmengine - INFO - Epoch(train) [2][400/2462] lr: 9.8704e-02 eta: 0:27:21 time: 0.0431 data_time: 0.0060 memory: 1794 loss: 1.1631 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1631 2022/11/28 17:29:08 - mmengine - INFO - Epoch(train) [2][500/2462] lr: 9.8612e-02 eta: 0:27:15 time: 0.0436 data_time: 0.0060 memory: 1794 loss: 1.0806 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0806 2022/11/28 17:29:10 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:29:12 - mmengine - INFO - Epoch(train) [2][600/2462] lr: 9.8518e-02 eta: 0:27:09 time: 0.0435 data_time: 0.0061 memory: 1794 loss: 1.2278 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2278 2022/11/28 17:29:17 - mmengine - INFO - Epoch(train) [2][700/2462] lr: 9.8420e-02 eta: 0:27:03 time: 0.0438 data_time: 0.0061 memory: 1794 loss: 1.1376 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1376 2022/11/28 17:29:21 - mmengine - INFO - Epoch(train) [2][800/2462] lr: 9.8319e-02 eta: 0:26:58 time: 0.0435 data_time: 0.0060 memory: 1794 loss: 1.0579 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0579 2022/11/28 17:29:26 - mmengine - INFO - Epoch(train) [2][900/2462] lr: 9.8215e-02 eta: 0:26:52 time: 0.0434 data_time: 0.0061 memory: 1794 loss: 1.1315 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.1315 2022/11/28 17:29:30 - mmengine - INFO - Epoch(train) [2][1000/2462] lr: 9.8107e-02 eta: 0:26:46 time: 0.0431 data_time: 0.0060 memory: 1794 loss: 1.0743 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0743 2022/11/28 17:29:34 - mmengine - INFO - Epoch(train) [2][1100/2462] lr: 9.7997e-02 eta: 0:26:41 time: 0.0457 data_time: 0.0060 memory: 1794 loss: 1.0840 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0840 2022/11/28 17:29:39 - mmengine - INFO - Epoch(train) [2][1200/2462] lr: 9.7884e-02 eta: 0:26:35 time: 0.0446 data_time: 0.0066 memory: 1794 loss: 0.9264 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.9264 2022/11/28 17:29:43 - mmengine - INFO - Epoch(train) [2][1300/2462] lr: 9.7768e-02 eta: 0:26:30 time: 0.0431 data_time: 0.0060 memory: 1794 loss: 1.0551 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0551 2022/11/28 17:29:47 - mmengine - INFO - Epoch(train) [2][1400/2462] lr: 9.7648e-02 eta: 0:26:25 time: 0.0443 data_time: 0.0060 memory: 1794 loss: 0.8807 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8807 2022/11/28 17:29:52 - mmengine - INFO - Epoch(train) [2][1500/2462] lr: 9.7526e-02 eta: 0:26:19 time: 0.0431 data_time: 0.0060 memory: 1794 loss: 1.1273 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1273 2022/11/28 17:29:53 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:29:56 - mmengine - INFO - Epoch(train) [2][1600/2462] lr: 9.7400e-02 eta: 0:26:14 time: 0.0441 data_time: 0.0064 memory: 1794 loss: 0.8984 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8984 2022/11/28 17:30:00 - mmengine - INFO - Epoch(train) [2][1700/2462] lr: 9.7272e-02 eta: 0:26:08 time: 0.0433 data_time: 0.0059 memory: 1794 loss: 1.0320 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0320 2022/11/28 17:30:05 - mmengine - INFO - Epoch(train) [2][1800/2462] lr: 9.7141e-02 eta: 0:26:03 time: 0.0436 data_time: 0.0061 memory: 1794 loss: 1.0601 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.0601 2022/11/28 17:30:09 - mmengine - INFO - Epoch(train) [2][1900/2462] lr: 9.7006e-02 eta: 0:25:58 time: 0.0461 data_time: 0.0086 memory: 1794 loss: 1.1100 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.1100 2022/11/28 17:30:14 - mmengine - INFO - Epoch(train) [2][2000/2462] lr: 9.6869e-02 eta: 0:25:53 time: 0.0433 data_time: 0.0060 memory: 1794 loss: 0.9910 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 0.9910 2022/11/28 17:30:18 - mmengine - INFO - Epoch(train) [2][2100/2462] lr: 9.6728e-02 eta: 0:25:48 time: 0.0446 data_time: 0.0065 memory: 1794 loss: 0.9040 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9040 2022/11/28 17:30:22 - mmengine - INFO - Epoch(train) [2][2200/2462] lr: 9.6585e-02 eta: 0:25:43 time: 0.0431 data_time: 0.0062 memory: 1794 loss: 1.0165 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.0165 2022/11/28 17:30:27 - mmengine - INFO - Epoch(train) [2][2300/2462] lr: 9.6439e-02 eta: 0:25:38 time: 0.0434 data_time: 0.0060 memory: 1794 loss: 1.0442 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.0442 2022/11/28 17:30:31 - mmengine - INFO - Epoch(train) [2][2400/2462] lr: 9.6290e-02 eta: 0:25:33 time: 0.0435 data_time: 0.0061 memory: 1794 loss: 0.9796 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.9796 2022/11/28 17:30:34 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:30:34 - mmengine - INFO - Epoch(train) [2][2462/2462] lr: 9.6196e-02 eta: 0:25:30 time: 0.0436 data_time: 0.0061 memory: 1794 loss: 0.9468 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 0.9468 2022/11/28 17:30:34 - mmengine - INFO - Saving checkpoint at 2 epochs 2022/11/28 17:30:38 - mmengine - INFO - Epoch(val) [2][100/398] eta: 0:00:10 time: 0.0343 data_time: 0.0208 memory: 364 2022/11/28 17:30:41 - mmengine - INFO - Epoch(val) [2][200/398] eta: 0:00:06 time: 0.0252 data_time: 0.0123 memory: 364 2022/11/28 17:30:43 - mmengine - INFO - Epoch(val) [2][300/398] eta: 0:00:02 time: 0.0263 data_time: 0.0134 memory: 364 2022/11/28 17:30:47 - mmengine - INFO - Epoch(val) [2][398/398] acc/top1: 0.5762 acc/top5: 0.8731 acc/mean1: 0.6059 2022/11/28 17:30:47 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d/best_acc/top1_epoch_1.pth is removed 2022/11/28 17:30:47 - mmengine - INFO - The best checkpoint with 0.5762 acc/top1 at 2 epoch is saved to best_acc/top1_epoch_2.pth. 2022/11/28 17:30:51 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:30:52 - mmengine - INFO - Epoch(train) [3][100/2462] lr: 9.6041e-02 eta: 0:25:26 time: 0.0432 data_time: 0.0061 memory: 1794 loss: 0.8320 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.8320 2022/11/28 17:30:56 - mmengine - INFO - Epoch(train) [3][200/2462] lr: 9.5884e-02 eta: 0:25:21 time: 0.0441 data_time: 0.0062 memory: 1794 loss: 0.8460 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8460 2022/11/28 17:31:00 - mmengine - INFO - Epoch(train) [3][300/2462] lr: 9.5725e-02 eta: 0:25:16 time: 0.0436 data_time: 0.0062 memory: 1794 loss: 1.0000 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0000 2022/11/28 17:31:05 - mmengine - INFO - Epoch(train) [3][400/2462] lr: 9.5562e-02 eta: 0:25:12 time: 0.0439 data_time: 0.0061 memory: 1794 loss: 0.9864 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.9864 2022/11/28 17:31:09 - mmengine - INFO - Epoch(train) [3][500/2462] lr: 9.5396e-02 eta: 0:25:07 time: 0.0441 data_time: 0.0061 memory: 1794 loss: 0.9504 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9504 2022/11/28 17:31:14 - mmengine - INFO - Epoch(train) [3][600/2462] lr: 9.5228e-02 eta: 0:25:02 time: 0.0438 data_time: 0.0061 memory: 1794 loss: 0.9596 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.9596 2022/11/28 17:31:18 - mmengine - INFO - Epoch(train) [3][700/2462] lr: 9.5056e-02 eta: 0:24:57 time: 0.0434 data_time: 0.0066 memory: 1794 loss: 1.0029 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0029 2022/11/28 17:31:22 - mmengine - INFO - Epoch(train) [3][800/2462] lr: 9.4882e-02 eta: 0:24:52 time: 0.0433 data_time: 0.0067 memory: 1794 loss: 0.9352 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.9352 2022/11/28 17:31:27 - mmengine - INFO - Epoch(train) [3][900/2462] lr: 9.4705e-02 eta: 0:24:48 time: 0.0441 data_time: 0.0066 memory: 1794 loss: 1.0117 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0117 2022/11/28 17:31:31 - mmengine - INFO - Epoch(train) [3][1000/2462] lr: 9.4525e-02 eta: 0:24:43 time: 0.0440 data_time: 0.0066 memory: 1794 loss: 0.9333 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9333 2022/11/28 17:31:35 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:31:36 - mmengine - INFO - Epoch(train) [3][1100/2462] lr: 9.4342e-02 eta: 0:24:39 time: 0.0434 data_time: 0.0061 memory: 1794 loss: 0.9779 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.9779 2022/11/28 17:31:40 - mmengine - INFO - Epoch(train) [3][1200/2462] lr: 9.4156e-02 eta: 0:24:34 time: 0.0442 data_time: 0.0067 memory: 1794 loss: 0.8305 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.8305 2022/11/28 17:31:45 - mmengine - INFO - Epoch(train) [3][1300/2462] lr: 9.3968e-02 eta: 0:24:30 time: 0.0437 data_time: 0.0060 memory: 1794 loss: 0.9347 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 0.9347 2022/11/28 17:31:49 - mmengine - INFO - Epoch(train) [3][1400/2462] lr: 9.3776e-02 eta: 0:24:26 time: 0.0448 data_time: 0.0060 memory: 1794 loss: 0.8431 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8431 2022/11/28 17:31:53 - mmengine - INFO - Epoch(train) [3][1500/2462] lr: 9.3582e-02 eta: 0:24:21 time: 0.0433 data_time: 0.0061 memory: 1794 loss: 0.8902 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8902 2022/11/28 17:31:58 - mmengine - INFO - Epoch(train) [3][1600/2462] lr: 9.3385e-02 eta: 0:24:16 time: 0.0438 data_time: 0.0063 memory: 1794 loss: 1.0569 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.0569 2022/11/28 17:32:02 - mmengine - INFO - Epoch(train) [3][1700/2462] lr: 9.3186e-02 eta: 0:24:11 time: 0.0443 data_time: 0.0065 memory: 1794 loss: 0.9307 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9307 2022/11/28 17:32:06 - mmengine - INFO - Epoch(train) [3][1800/2462] lr: 9.2983e-02 eta: 0:24:06 time: 0.0432 data_time: 0.0061 memory: 1794 loss: 1.0265 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.0265 2022/11/28 17:32:11 - mmengine - INFO - Epoch(train) [3][1900/2462] lr: 9.2778e-02 eta: 0:24:02 time: 0.0433 data_time: 0.0062 memory: 1794 loss: 0.8678 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.8678 2022/11/28 17:32:15 - mmengine - INFO - Epoch(train) [3][2000/2462] lr: 9.2571e-02 eta: 0:23:57 time: 0.0435 data_time: 0.0066 memory: 1794 loss: 0.7137 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.7137 2022/11/28 17:32:19 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:32:20 - mmengine - INFO - Epoch(train) [3][2100/2462] lr: 9.2360e-02 eta: 0:23:52 time: 0.0430 data_time: 0.0061 memory: 1794 loss: 0.8551 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 0.8551 2022/11/28 17:32:24 - mmengine - INFO - Epoch(train) [3][2200/2462] lr: 9.2147e-02 eta: 0:23:48 time: 0.0440 data_time: 0.0071 memory: 1794 loss: 0.8978 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 0.8978 2022/11/28 17:32:28 - mmengine - INFO - Epoch(train) [3][2300/2462] lr: 9.1931e-02 eta: 0:23:43 time: 0.0433 data_time: 0.0068 memory: 1794 loss: 0.8660 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 0.8660 2022/11/28 17:32:33 - mmengine - INFO - Epoch(train) [3][2400/2462] lr: 9.1713e-02 eta: 0:23:39 time: 0.0437 data_time: 0.0061 memory: 1794 loss: 0.8253 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8253 2022/11/28 17:32:35 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:32:35 - mmengine - INFO - Epoch(train) [3][2462/2462] lr: 9.1576e-02 eta: 0:23:36 time: 0.0440 data_time: 0.0061 memory: 1794 loss: 0.8264 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 0.8264 2022/11/28 17:32:35 - mmengine - INFO - Saving checkpoint at 3 epochs 2022/11/28 17:32:39 - mmengine - INFO - Epoch(val) [3][100/398] eta: 0:00:10 time: 0.0341 data_time: 0.0209 memory: 364 2022/11/28 17:32:42 - mmengine - INFO - Epoch(val) [3][200/398] eta: 0:00:06 time: 0.0251 data_time: 0.0120 memory: 364 2022/11/28 17:32:45 - mmengine - INFO - Epoch(val) [3][300/398] eta: 0:00:02 time: 0.0256 data_time: 0.0130 memory: 364 2022/11/28 17:32:49 - mmengine - INFO - Epoch(val) [3][398/398] acc/top1: 0.4735 acc/top5: 0.7680 acc/mean1: 0.5003 2022/11/28 17:32:53 - mmengine - INFO - Epoch(train) [4][100/2462] lr: 9.1353e-02 eta: 0:23:32 time: 0.0448 data_time: 0.0066 memory: 1794 loss: 0.8304 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 0.8304 2022/11/28 17:32:58 - mmengine - INFO - Epoch(train) [4][200/2462] lr: 9.1127e-02 eta: 0:23:27 time: 0.0434 data_time: 0.0061 memory: 1794 loss: 0.7376 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7376 2022/11/28 17:33:02 - mmengine - INFO - Epoch(train) [4][300/2462] lr: 9.0899e-02 eta: 0:23:23 time: 0.0442 data_time: 0.0062 memory: 1794 loss: 0.7476 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7476 2022/11/28 17:33:06 - mmengine - INFO - Epoch(train) [4][400/2462] lr: 9.0669e-02 eta: 0:23:18 time: 0.0435 data_time: 0.0061 memory: 1794 loss: 0.9221 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9221 2022/11/28 17:33:11 - mmengine - INFO - Epoch(train) [4][500/2462] lr: 9.0435e-02 eta: 0:23:14 time: 0.0436 data_time: 0.0067 memory: 1794 loss: 0.8645 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.8645 2022/11/28 17:33:15 - mmengine - INFO - Epoch(train) [4][600/2462] lr: 9.0200e-02 eta: 0:23:09 time: 0.0431 data_time: 0.0060 memory: 1794 loss: 0.7088 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7088 2022/11/28 17:33:16 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:33:19 - mmengine - INFO - Epoch(train) [4][700/2462] lr: 8.9961e-02 eta: 0:23:05 time: 0.0431 data_time: 0.0060 memory: 1794 loss: 0.7889 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 0.7889 2022/11/28 17:33:24 - mmengine - INFO - Epoch(train) [4][800/2462] lr: 8.9720e-02 eta: 0:23:00 time: 0.0439 data_time: 0.0063 memory: 1794 loss: 0.7586 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 0.7586 2022/11/28 17:33:28 - mmengine - INFO - Epoch(train) [4][900/2462] lr: 8.9477e-02 eta: 0:22:55 time: 0.0435 data_time: 0.0060 memory: 1794 loss: 0.8580 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8580 2022/11/28 17:33:33 - mmengine - INFO - Epoch(train) [4][1000/2462] lr: 8.9231e-02 eta: 0:22:51 time: 0.0444 data_time: 0.0067 memory: 1794 loss: 0.8340 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.8340 2022/11/28 17:33:37 - mmengine - INFO - Epoch(train) [4][1100/2462] lr: 8.8982e-02 eta: 0:22:46 time: 0.0439 data_time: 0.0069 memory: 1794 loss: 0.7785 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 0.7785 2022/11/28 17:33:41 - mmengine - INFO - Epoch(train) [4][1200/2462] lr: 8.8731e-02 eta: 0:22:42 time: 0.0436 data_time: 0.0062 memory: 1794 loss: 0.8826 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8826 2022/11/28 17:33:46 - mmengine - INFO - Epoch(train) [4][1300/2462] lr: 8.8478e-02 eta: 0:22:37 time: 0.0438 data_time: 0.0060 memory: 1794 loss: 0.8009 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.8009 2022/11/28 17:33:50 - mmengine - INFO - Epoch(train) [4][1400/2462] lr: 8.8222e-02 eta: 0:22:33 time: 0.0436 data_time: 0.0060 memory: 1794 loss: 0.9364 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9364 2022/11/28 17:33:55 - mmengine - INFO - Epoch(train) [4][1500/2462] lr: 8.7964e-02 eta: 0:22:28 time: 0.0431 data_time: 0.0060 memory: 1794 loss: 0.8572 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8572 2022/11/28 17:33:59 - mmengine - INFO - Epoch(train) [4][1600/2462] lr: 8.7703e-02 eta: 0:22:24 time: 0.0431 data_time: 0.0060 memory: 1794 loss: 0.7471 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.7471 2022/11/28 17:34:00 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:34:03 - mmengine - INFO - Epoch(train) [4][1700/2462] lr: 8.7440e-02 eta: 0:22:19 time: 0.0437 data_time: 0.0061 memory: 1794 loss: 0.7399 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7399 2022/11/28 17:34:08 - mmengine - INFO - Epoch(train) [4][1800/2462] lr: 8.7174e-02 eta: 0:22:14 time: 0.0435 data_time: 0.0060 memory: 1794 loss: 0.6944 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.6944 2022/11/28 17:34:12 - mmengine - INFO - Epoch(train) [4][1900/2462] lr: 8.6907e-02 eta: 0:22:10 time: 0.0443 data_time: 0.0068 memory: 1794 loss: 0.7007 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7007 2022/11/28 17:34:17 - mmengine - INFO - Epoch(train) [4][2000/2462] lr: 8.6636e-02 eta: 0:22:05 time: 0.0441 data_time: 0.0066 memory: 1794 loss: 0.8067 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 0.8067 2022/11/28 17:34:21 - mmengine - INFO - Epoch(train) [4][2100/2462] lr: 8.6364e-02 eta: 0:22:01 time: 0.0480 data_time: 0.0060 memory: 1794 loss: 0.7850 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7850 2022/11/28 17:34:26 - mmengine - INFO - Epoch(train) [4][2200/2462] lr: 8.6089e-02 eta: 0:21:57 time: 0.0434 data_time: 0.0060 memory: 1794 loss: 0.8915 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.8915 2022/11/28 17:34:30 - mmengine - INFO - Epoch(train) [4][2300/2462] lr: 8.5812e-02 eta: 0:21:52 time: 0.0435 data_time: 0.0061 memory: 1794 loss: 0.8332 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.8332 2022/11/28 17:34:34 - mmengine - INFO - Epoch(train) [4][2400/2462] lr: 8.5533e-02 eta: 0:21:48 time: 0.0432 data_time: 0.0060 memory: 1794 loss: 0.7933 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7933 2022/11/28 17:34:37 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:34:37 - mmengine - INFO - Epoch(train) [4][2462/2462] lr: 8.5358e-02 eta: 0:21:45 time: 0.0435 data_time: 0.0060 memory: 1794 loss: 0.7031 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7031 2022/11/28 17:34:37 - mmengine - INFO - Saving checkpoint at 4 epochs 2022/11/28 17:34:41 - mmengine - INFO - Epoch(val) [4][100/398] eta: 0:00:10 time: 0.0336 data_time: 0.0205 memory: 364 2022/11/28 17:34:44 - mmengine - INFO - Epoch(val) [4][200/398] eta: 0:00:06 time: 0.0251 data_time: 0.0116 memory: 364 2022/11/28 17:34:47 - mmengine - INFO - Epoch(val) [4][300/398] eta: 0:00:02 time: 0.0258 data_time: 0.0138 memory: 364 2022/11/28 17:34:50 - mmengine - INFO - Epoch(val) [4][398/398] acc/top1: 0.6387 acc/top5: 0.8620 acc/mean1: 0.6545 2022/11/28 17:34:50 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d/best_acc/top1_epoch_2.pth is removed 2022/11/28 17:34:51 - mmengine - INFO - The best checkpoint with 0.6387 acc/top1 at 4 epoch is saved to best_acc/top1_epoch_4.pth. 2022/11/28 17:34:56 - mmengine - INFO - Epoch(train) [5][100/2462] lr: 8.5075e-02 eta: 0:21:41 time: 0.0437 data_time: 0.0060 memory: 1794 loss: 0.8013 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8013 2022/11/28 17:34:58 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:35:00 - mmengine - INFO - Epoch(train) [5][200/2462] lr: 8.4790e-02 eta: 0:21:37 time: 0.0440 data_time: 0.0060 memory: 1794 loss: 0.8040 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.8040 2022/11/28 17:35:04 - mmengine - INFO - Epoch(train) [5][300/2462] lr: 8.4502e-02 eta: 0:21:32 time: 0.0434 data_time: 0.0061 memory: 1794 loss: 0.6910 top1_acc: 0.5625 top5_acc: 1.0000 loss_cls: 0.6910 2022/11/28 17:35:09 - mmengine - INFO - Epoch(train) [5][400/2462] lr: 8.4213e-02 eta: 0:21:27 time: 0.0444 data_time: 0.0067 memory: 1794 loss: 0.6969 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.6969 2022/11/28 17:35:13 - mmengine - INFO - Epoch(train) [5][500/2462] lr: 8.3921e-02 eta: 0:21:23 time: 0.0441 data_time: 0.0066 memory: 1794 loss: 0.7485 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 0.7485 2022/11/28 17:35:18 - mmengine - INFO - Epoch(train) [5][600/2462] lr: 8.3627e-02 eta: 0:21:18 time: 0.0433 data_time: 0.0060 memory: 1794 loss: 0.7627 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7627 2022/11/28 17:35:22 - mmengine - INFO - Epoch(train) [5][700/2462] lr: 8.3330e-02 eta: 0:21:14 time: 0.0431 data_time: 0.0059 memory: 1794 loss: 0.8853 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.8853 2022/11/28 17:35:26 - mmengine - INFO - Epoch(train) [5][800/2462] lr: 8.3032e-02 eta: 0:21:09 time: 0.0436 data_time: 0.0065 memory: 1794 loss: 0.8205 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8205 2022/11/28 17:35:31 - mmengine - INFO - Epoch(train) [5][900/2462] lr: 8.2732e-02 eta: 0:21:05 time: 0.0435 data_time: 0.0065 memory: 1794 loss: 0.7139 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7139 2022/11/28 17:35:35 - mmengine - INFO - Epoch(train) [5][1000/2462] lr: 8.2429e-02 eta: 0:21:00 time: 0.0437 data_time: 0.0064 memory: 1794 loss: 0.7212 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 0.7212 2022/11/28 17:35:39 - mmengine - INFO - Epoch(train) [5][1100/2462] lr: 8.2125e-02 eta: 0:20:55 time: 0.0448 data_time: 0.0065 memory: 1794 loss: 0.6927 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 0.6927 2022/11/28 17:35:42 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:35:44 - mmengine - INFO - Epoch(train) [5][1200/2462] lr: 8.1818e-02 eta: 0:20:51 time: 0.0438 data_time: 0.0061 memory: 1794 loss: 0.7145 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7145 2022/11/28 17:35:48 - mmengine - INFO - Epoch(train) [5][1300/2462] lr: 8.1510e-02 eta: 0:20:47 time: 0.0437 data_time: 0.0059 memory: 1794 loss: 0.6909 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6909 2022/11/28 17:35:53 - mmengine - INFO - Epoch(train) [5][1400/2462] lr: 8.1199e-02 eta: 0:20:42 time: 0.0436 data_time: 0.0067 memory: 1794 loss: 0.6899 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 0.6899 2022/11/28 17:35:57 - mmengine - INFO - Epoch(train) [5][1500/2462] lr: 8.0886e-02 eta: 0:20:38 time: 0.0430 data_time: 0.0060 memory: 1794 loss: 0.7346 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.7346 2022/11/28 17:36:01 - mmengine - INFO - Epoch(train) [5][1600/2462] lr: 8.0572e-02 eta: 0:20:33 time: 0.0435 data_time: 0.0066 memory: 1794 loss: 0.7505 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.7505 2022/11/28 17:36:06 - mmengine - INFO - Epoch(train) [5][1700/2462] lr: 8.0255e-02 eta: 0:20:29 time: 0.0432 data_time: 0.0061 memory: 1794 loss: 0.6871 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.6871 2022/11/28 17:36:10 - mmengine - INFO - Epoch(train) [5][1800/2462] lr: 7.9937e-02 eta: 0:20:24 time: 0.0434 data_time: 0.0060 memory: 1794 loss: 0.7018 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7018 2022/11/28 17:36:14 - mmengine - INFO - Epoch(train) [5][1900/2462] lr: 7.9617e-02 eta: 0:20:20 time: 0.0434 data_time: 0.0067 memory: 1794 loss: 0.6435 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.6435 2022/11/28 17:36:19 - mmengine - INFO - Epoch(train) [5][2000/2462] lr: 7.9294e-02 eta: 0:20:15 time: 0.0436 data_time: 0.0060 memory: 1794 loss: 0.7112 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7112 2022/11/28 17:36:23 - mmengine - INFO - Epoch(train) [5][2100/2462] lr: 7.8970e-02 eta: 0:20:10 time: 0.0430 data_time: 0.0059 memory: 1794 loss: 0.7812 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7812 2022/11/28 17:36:25 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:36:28 - mmengine - INFO - Epoch(train) [5][2200/2462] lr: 7.8644e-02 eta: 0:20:06 time: 0.0433 data_time: 0.0064 memory: 1794 loss: 0.7881 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7881 2022/11/28 17:36:32 - mmengine - INFO - Epoch(train) [5][2300/2462] lr: 7.8317e-02 eta: 0:20:01 time: 0.0437 data_time: 0.0061 memory: 1794 loss: 0.7407 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7407 2022/11/28 17:36:36 - mmengine - INFO - Epoch(train) [5][2400/2462] lr: 7.7987e-02 eta: 0:19:57 time: 0.0429 data_time: 0.0061 memory: 1794 loss: 0.8010 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.8010 2022/11/28 17:36:39 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:36:39 - mmengine - INFO - Epoch(train) [5][2462/2462] lr: 7.7782e-02 eta: 0:19:54 time: 0.0448 data_time: 0.0070 memory: 1794 loss: 0.7900 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7900 2022/11/28 17:36:39 - mmengine - INFO - Saving checkpoint at 5 epochs 2022/11/28 17:36:43 - mmengine - INFO - Epoch(val) [5][100/398] eta: 0:00:10 time: 0.0341 data_time: 0.0206 memory: 364 2022/11/28 17:36:46 - mmengine - INFO - Epoch(val) [5][200/398] eta: 0:00:06 time: 0.0246 data_time: 0.0117 memory: 364 2022/11/28 17:36:48 - mmengine - INFO - Epoch(val) [5][300/398] eta: 0:00:02 time: 0.0262 data_time: 0.0141 memory: 364 2022/11/28 17:36:52 - mmengine - INFO - Epoch(val) [5][398/398] acc/top1: 0.6424 acc/top5: 0.8893 acc/mean1: 0.6711 2022/11/28 17:36:52 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d/best_acc/top1_epoch_4.pth is removed 2022/11/28 17:36:52 - mmengine - INFO - The best checkpoint with 0.6424 acc/top1 at 5 epoch is saved to best_acc/top1_epoch_5.pth. 2022/11/28 17:36:57 - mmengine - INFO - Epoch(train) [6][100/2462] lr: 7.7449e-02 eta: 0:19:50 time: 0.0461 data_time: 0.0065 memory: 1794 loss: 0.6745 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6745 2022/11/28 17:37:01 - mmengine - INFO - Epoch(train) [6][200/2462] lr: 7.7115e-02 eta: 0:19:46 time: 0.0455 data_time: 0.0062 memory: 1794 loss: 0.6103 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.6103 2022/11/28 17:37:06 - mmengine - INFO - Epoch(train) [6][300/2462] lr: 7.6779e-02 eta: 0:19:41 time: 0.0452 data_time: 0.0064 memory: 1794 loss: 0.7115 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 0.7115 2022/11/28 17:37:10 - mmengine - INFO - Epoch(train) [6][400/2462] lr: 7.6442e-02 eta: 0:19:37 time: 0.0444 data_time: 0.0061 memory: 1794 loss: 0.6845 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6845 2022/11/28 17:37:15 - mmengine - INFO - Epoch(train) [6][500/2462] lr: 7.6102e-02 eta: 0:19:32 time: 0.0436 data_time: 0.0060 memory: 1794 loss: 0.6790 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 0.6790 2022/11/28 17:37:19 - mmengine - INFO - Epoch(train) [6][600/2462] lr: 7.5762e-02 eta: 0:19:28 time: 0.0430 data_time: 0.0061 memory: 1794 loss: 0.6047 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6047 2022/11/28 17:37:23 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:37:23 - mmengine - INFO - Epoch(train) [6][700/2462] lr: 7.5419e-02 eta: 0:19:23 time: 0.0438 data_time: 0.0061 memory: 1794 loss: 0.6379 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6379 2022/11/28 17:37:28 - mmengine - INFO - Epoch(train) [6][800/2462] lr: 7.5075e-02 eta: 0:19:19 time: 0.0441 data_time: 0.0061 memory: 1794 loss: 0.6573 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 0.6573 2022/11/28 17:37:32 - mmengine - INFO - Epoch(train) [6][900/2462] lr: 7.4729e-02 eta: 0:19:14 time: 0.0435 data_time: 0.0062 memory: 1794 loss: 0.7166 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7166 2022/11/28 17:37:37 - mmengine - INFO - Epoch(train) [6][1000/2462] lr: 7.4382e-02 eta: 0:19:10 time: 0.0432 data_time: 0.0061 memory: 1794 loss: 0.7263 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 0.7263 2022/11/28 17:37:41 - mmengine - INFO - Epoch(train) [6][1100/2462] lr: 7.4033e-02 eta: 0:19:05 time: 0.0441 data_time: 0.0062 memory: 1794 loss: 0.7328 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.7328 2022/11/28 17:37:45 - mmengine - INFO - Epoch(train) [6][1200/2462] lr: 7.3682e-02 eta: 0:19:01 time: 0.0438 data_time: 0.0064 memory: 1794 loss: 0.7399 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 0.7399 2022/11/28 17:37:50 - mmengine - INFO - Epoch(train) [6][1300/2462] lr: 7.3330e-02 eta: 0:18:57 time: 0.0434 data_time: 0.0066 memory: 1794 loss: 0.5485 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5485 2022/11/28 17:37:54 - mmengine - INFO - Epoch(train) [6][1400/2462] lr: 7.2977e-02 eta: 0:18:52 time: 0.0445 data_time: 0.0065 memory: 1794 loss: 0.6513 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 0.6513 2022/11/28 17:37:59 - mmengine - INFO - Epoch(train) [6][1500/2462] lr: 7.2622e-02 eta: 0:18:48 time: 0.0440 data_time: 0.0064 memory: 1794 loss: 0.6698 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6698 2022/11/28 17:38:03 - mmengine - INFO - Epoch(train) [6][1600/2462] lr: 7.2266e-02 eta: 0:18:43 time: 0.0440 data_time: 0.0061 memory: 1794 loss: 0.6408 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.6408 2022/11/28 17:38:07 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:38:07 - mmengine - INFO - Epoch(train) [6][1700/2462] lr: 7.1908e-02 eta: 0:18:39 time: 0.0435 data_time: 0.0060 memory: 1794 loss: 0.6355 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6355 2022/11/28 17:38:12 - mmengine - INFO - Epoch(train) [6][1800/2462] lr: 7.1549e-02 eta: 0:18:34 time: 0.0447 data_time: 0.0060 memory: 1794 loss: 0.7029 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7029 2022/11/28 17:38:16 - mmengine - INFO - Epoch(train) [6][1900/2462] lr: 7.1188e-02 eta: 0:18:30 time: 0.0442 data_time: 0.0060 memory: 1794 loss: 0.7336 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.7336 2022/11/28 17:38:21 - mmengine - INFO - Epoch(train) [6][2000/2462] lr: 7.0826e-02 eta: 0:18:25 time: 0.0435 data_time: 0.0060 memory: 1794 loss: 0.6350 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.6350 2022/11/28 17:38:25 - mmengine - INFO - Epoch(train) [6][2100/2462] lr: 7.0463e-02 eta: 0:18:21 time: 0.0435 data_time: 0.0062 memory: 1794 loss: 0.6989 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6989 2022/11/28 17:38:29 - mmengine - INFO - Epoch(train) [6][2200/2462] lr: 7.0099e-02 eta: 0:18:16 time: 0.0432 data_time: 0.0061 memory: 1794 loss: 0.5050 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.5050 2022/11/28 17:38:34 - mmengine - INFO - Epoch(train) [6][2300/2462] lr: 6.9733e-02 eta: 0:18:12 time: 0.0441 data_time: 0.0066 memory: 1794 loss: 0.7348 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.7348 2022/11/28 17:38:38 - mmengine - INFO - Epoch(train) [6][2400/2462] lr: 6.9366e-02 eta: 0:18:08 time: 0.0436 data_time: 0.0061 memory: 1794 loss: 0.5938 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5938 2022/11/28 17:38:41 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:38:41 - mmengine - INFO - Epoch(train) [6][2462/2462] lr: 6.9138e-02 eta: 0:18:05 time: 0.0443 data_time: 0.0061 memory: 1794 loss: 0.6982 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6982 2022/11/28 17:38:41 - mmengine - INFO - Saving checkpoint at 6 epochs 2022/11/28 17:38:45 - mmengine - INFO - Epoch(val) [6][100/398] eta: 0:00:10 time: 0.0333 data_time: 0.0201 memory: 364 2022/11/28 17:38:48 - mmengine - INFO - Epoch(val) [6][200/398] eta: 0:00:06 time: 0.0251 data_time: 0.0122 memory: 364 2022/11/28 17:38:50 - mmengine - INFO - Epoch(val) [6][300/398] eta: 0:00:02 time: 0.0253 data_time: 0.0133 memory: 364 2022/11/28 17:38:54 - mmengine - INFO - Epoch(val) [6][398/398] acc/top1: 0.6582 acc/top5: 0.8996 acc/mean1: 0.6837 2022/11/28 17:38:54 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d/best_acc/top1_epoch_5.pth is removed 2022/11/28 17:38:54 - mmengine - INFO - The best checkpoint with 0.6582 acc/top1 at 6 epoch is saved to best_acc/top1_epoch_6.pth. 2022/11/28 17:38:59 - mmengine - INFO - Epoch(train) [7][100/2462] lr: 6.8769e-02 eta: 0:18:01 time: 0.0435 data_time: 0.0061 memory: 1794 loss: 0.6530 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6530 2022/11/28 17:39:03 - mmengine - INFO - Epoch(train) [7][200/2462] lr: 6.8399e-02 eta: 0:17:56 time: 0.0443 data_time: 0.0068 memory: 1794 loss: 0.6293 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6293 2022/11/28 17:39:04 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:39:07 - mmengine - INFO - Epoch(train) [7][300/2462] lr: 6.8027e-02 eta: 0:17:52 time: 0.0432 data_time: 0.0061 memory: 1794 loss: 0.5481 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5481 2022/11/28 17:39:12 - mmengine - INFO - Epoch(train) [7][400/2462] lr: 6.7655e-02 eta: 0:17:47 time: 0.0440 data_time: 0.0067 memory: 1794 loss: 0.5662 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5662 2022/11/28 17:39:16 - mmengine - INFO - Epoch(train) [7][500/2462] lr: 6.7281e-02 eta: 0:17:43 time: 0.0444 data_time: 0.0068 memory: 1794 loss: 0.6997 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.6997 2022/11/28 17:39:21 - mmengine - INFO - Epoch(train) [7][600/2462] lr: 6.6906e-02 eta: 0:17:39 time: 0.0431 data_time: 0.0061 memory: 1794 loss: 0.5839 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.5839 2022/11/28 17:39:25 - mmengine - INFO - Epoch(train) [7][700/2462] lr: 6.6531e-02 eta: 0:17:34 time: 0.0437 data_time: 0.0064 memory: 1794 loss: 0.6190 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.6190 2022/11/28 17:39:29 - mmengine - INFO - Epoch(train) [7][800/2462] lr: 6.6154e-02 eta: 0:17:30 time: 0.0439 data_time: 0.0061 memory: 1794 loss: 0.7037 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7037 2022/11/28 17:39:34 - mmengine - INFO - Epoch(train) [7][900/2462] lr: 6.5776e-02 eta: 0:17:25 time: 0.0437 data_time: 0.0068 memory: 1794 loss: 0.6593 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.6593 2022/11/28 17:39:38 - mmengine - INFO - Epoch(train) [7][1000/2462] lr: 6.5397e-02 eta: 0:17:21 time: 0.0453 data_time: 0.0071 memory: 1794 loss: 0.6046 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 0.6046 2022/11/28 17:39:43 - mmengine - INFO - Epoch(train) [7][1100/2462] lr: 6.5017e-02 eta: 0:17:17 time: 0.0439 data_time: 0.0063 memory: 1794 loss: 0.5680 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.5680 2022/11/28 17:39:47 - mmengine - INFO - Epoch(train) [7][1200/2462] lr: 6.4636e-02 eta: 0:17:12 time: 0.0461 data_time: 0.0063 memory: 1794 loss: 0.5663 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.5663 2022/11/28 17:39:48 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:39:51 - mmengine - INFO - Epoch(train) [7][1300/2462] lr: 6.4255e-02 eta: 0:17:08 time: 0.0433 data_time: 0.0061 memory: 1794 loss: 0.6082 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6082 2022/11/28 17:39:56 - mmengine - INFO - Epoch(train) [7][1400/2462] lr: 6.3872e-02 eta: 0:17:03 time: 0.0437 data_time: 0.0065 memory: 1794 loss: 0.5680 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5680 2022/11/28 17:40:00 - mmengine - INFO - Epoch(train) [7][1500/2462] lr: 6.3488e-02 eta: 0:16:59 time: 0.0434 data_time: 0.0060 memory: 1794 loss: 0.6520 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.6520 2022/11/28 17:40:05 - mmengine - INFO - Epoch(train) [7][1600/2462] lr: 6.3104e-02 eta: 0:16:54 time: 0.0435 data_time: 0.0061 memory: 1794 loss: 0.5288 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5288 2022/11/28 17:40:09 - mmengine - INFO - Epoch(train) [7][1700/2462] lr: 6.2719e-02 eta: 0:16:50 time: 0.0438 data_time: 0.0061 memory: 1794 loss: 0.5461 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5461 2022/11/28 17:40:13 - mmengine - INFO - Epoch(train) [7][1800/2462] lr: 6.2333e-02 eta: 0:16:45 time: 0.0446 data_time: 0.0060 memory: 1794 loss: 0.5707 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5707 2022/11/28 17:40:18 - mmengine - INFO - Epoch(train) [7][1900/2462] lr: 6.1946e-02 eta: 0:16:41 time: 0.0437 data_time: 0.0063 memory: 1794 loss: 0.6718 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.6718 2022/11/28 17:40:22 - mmengine - INFO - Epoch(train) [7][2000/2462] lr: 6.1558e-02 eta: 0:16:37 time: 0.0440 data_time: 0.0066 memory: 1794 loss: 0.6206 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6206 2022/11/28 17:40:27 - mmengine - INFO - Epoch(train) [7][2100/2462] lr: 6.1170e-02 eta: 0:16:32 time: 0.0440 data_time: 0.0067 memory: 1794 loss: 0.4649 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.4649 2022/11/28 17:40:31 - mmengine - INFO - Epoch(train) [7][2200/2462] lr: 6.0781e-02 eta: 0:16:28 time: 0.0436 data_time: 0.0060 memory: 1794 loss: 0.5856 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5856 2022/11/28 17:40:32 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:40:36 - mmengine - INFO - Epoch(train) [7][2300/2462] lr: 6.0391e-02 eta: 0:16:23 time: 0.0440 data_time: 0.0063 memory: 1794 loss: 0.5468 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5468 2022/11/28 17:40:40 - mmengine - INFO - Epoch(train) [7][2400/2462] lr: 6.0001e-02 eta: 0:16:19 time: 0.0438 data_time: 0.0060 memory: 1794 loss: 0.6265 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.6265 2022/11/28 17:40:43 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:40:43 - mmengine - INFO - Epoch(train) [7][2462/2462] lr: 5.9758e-02 eta: 0:16:16 time: 0.0436 data_time: 0.0061 memory: 1794 loss: 0.5642 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.5642 2022/11/28 17:40:43 - mmengine - INFO - Saving checkpoint at 7 epochs 2022/11/28 17:40:47 - mmengine - INFO - Epoch(val) [7][100/398] eta: 0:00:10 time: 0.0332 data_time: 0.0201 memory: 364 2022/11/28 17:40:49 - mmengine - INFO - Epoch(val) [7][200/398] eta: 0:00:06 time: 0.0247 data_time: 0.0116 memory: 364 2022/11/28 17:40:52 - mmengine - INFO - Epoch(val) [7][300/398] eta: 0:00:02 time: 0.0252 data_time: 0.0131 memory: 364 2022/11/28 17:40:56 - mmengine - INFO - Epoch(val) [7][398/398] acc/top1: 0.6781 acc/top5: 0.9056 acc/mean1: 0.7004 2022/11/28 17:40:56 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d/best_acc/top1_epoch_6.pth is removed 2022/11/28 17:40:56 - mmengine - INFO - The best checkpoint with 0.6781 acc/top1 at 7 epoch is saved to best_acc/top1_epoch_7.pth. 2022/11/28 17:41:01 - mmengine - INFO - Epoch(train) [8][100/2462] lr: 5.9367e-02 eta: 0:16:12 time: 0.0445 data_time: 0.0061 memory: 1794 loss: 0.5030 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5030 2022/11/28 17:41:05 - mmengine - INFO - Epoch(train) [8][200/2462] lr: 5.8975e-02 eta: 0:16:08 time: 0.0439 data_time: 0.0066 memory: 1794 loss: 0.6095 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.6095 2022/11/28 17:41:09 - mmengine - INFO - Epoch(train) [8][300/2462] lr: 5.8582e-02 eta: 0:16:03 time: 0.0450 data_time: 0.0062 memory: 1794 loss: 0.5646 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5646 2022/11/28 17:41:14 - mmengine - INFO - Epoch(train) [8][400/2462] lr: 5.8189e-02 eta: 0:15:59 time: 0.0437 data_time: 0.0060 memory: 1794 loss: 0.4928 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4928 2022/11/28 17:41:18 - mmengine - INFO - Epoch(train) [8][500/2462] lr: 5.7796e-02 eta: 0:15:54 time: 0.0438 data_time: 0.0062 memory: 1794 loss: 0.5513 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5513 2022/11/28 17:41:22 - mmengine - INFO - Epoch(train) [8][600/2462] lr: 5.7402e-02 eta: 0:15:50 time: 0.0434 data_time: 0.0061 memory: 1794 loss: 0.5624 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5624 2022/11/28 17:41:27 - mmengine - INFO - Epoch(train) [8][700/2462] lr: 5.7007e-02 eta: 0:15:45 time: 0.0440 data_time: 0.0060 memory: 1794 loss: 0.5175 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5175 2022/11/28 17:41:30 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:41:31 - mmengine - INFO - Epoch(train) [8][800/2462] lr: 5.6612e-02 eta: 0:15:41 time: 0.0441 data_time: 0.0061 memory: 1794 loss: 0.6124 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6124 2022/11/28 17:41:36 - mmengine - INFO - Epoch(train) [8][900/2462] lr: 5.6216e-02 eta: 0:15:37 time: 0.0437 data_time: 0.0061 memory: 1794 loss: 0.5216 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5216 2022/11/28 17:41:40 - mmengine - INFO - Epoch(train) [8][1000/2462] lr: 5.5821e-02 eta: 0:15:32 time: 0.0442 data_time: 0.0068 memory: 1794 loss: 0.6269 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6269 2022/11/28 17:41:45 - mmengine - INFO - Epoch(train) [8][1100/2462] lr: 5.5424e-02 eta: 0:15:28 time: 0.0438 data_time: 0.0061 memory: 1794 loss: 0.4842 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4842 2022/11/28 17:41:49 - mmengine - INFO - Epoch(train) [8][1200/2462] lr: 5.5028e-02 eta: 0:15:23 time: 0.0434 data_time: 0.0061 memory: 1794 loss: 0.5139 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5139 2022/11/28 17:41:53 - mmengine - INFO - Epoch(train) [8][1300/2462] lr: 5.4631e-02 eta: 0:15:19 time: 0.0435 data_time: 0.0061 memory: 1794 loss: 0.4723 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4723 2022/11/28 17:41:58 - mmengine - INFO - Epoch(train) [8][1400/2462] lr: 5.4234e-02 eta: 0:15:15 time: 0.0442 data_time: 0.0073 memory: 1794 loss: 0.4935 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4935 2022/11/28 17:42:02 - mmengine - INFO - Epoch(train) [8][1500/2462] lr: 5.3836e-02 eta: 0:15:10 time: 0.0444 data_time: 0.0061 memory: 1794 loss: 0.6544 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6544 2022/11/28 17:42:07 - mmengine - INFO - Epoch(train) [8][1600/2462] lr: 5.3439e-02 eta: 0:15:06 time: 0.0458 data_time: 0.0061 memory: 1794 loss: 0.4774 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.4774 2022/11/28 17:42:11 - mmengine - INFO - Epoch(train) [8][1700/2462] lr: 5.3041e-02 eta: 0:15:02 time: 0.0443 data_time: 0.0065 memory: 1794 loss: 0.5226 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5226 2022/11/28 17:42:14 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:42:16 - mmengine - INFO - Epoch(train) [8][1800/2462] lr: 5.2643e-02 eta: 0:14:57 time: 0.0438 data_time: 0.0064 memory: 1794 loss: 0.5751 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5751 2022/11/28 17:42:20 - mmengine - INFO - Epoch(train) [8][1900/2462] lr: 5.2244e-02 eta: 0:14:53 time: 0.0440 data_time: 0.0061 memory: 1794 loss: 0.5306 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5306 2022/11/28 17:42:24 - mmengine - INFO - Epoch(train) [8][2000/2462] lr: 5.1846e-02 eta: 0:14:48 time: 0.0445 data_time: 0.0062 memory: 1794 loss: 0.4161 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4161 2022/11/28 17:42:29 - mmengine - INFO - Epoch(train) [8][2100/2462] lr: 5.1447e-02 eta: 0:14:44 time: 0.0436 data_time: 0.0060 memory: 1794 loss: 0.5402 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5402 2022/11/28 17:42:33 - mmengine - INFO - Epoch(train) [8][2200/2462] lr: 5.1049e-02 eta: 0:14:39 time: 0.0446 data_time: 0.0061 memory: 1794 loss: 0.5589 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5589 2022/11/28 17:42:38 - mmengine - INFO - Epoch(train) [8][2300/2462] lr: 5.0650e-02 eta: 0:14:35 time: 0.0465 data_time: 0.0061 memory: 1794 loss: 0.4866 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4866 2022/11/28 17:42:42 - mmengine - INFO - Epoch(train) [8][2400/2462] lr: 5.0251e-02 eta: 0:14:31 time: 0.0437 data_time: 0.0061 memory: 1794 loss: 0.4842 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.4842 2022/11/28 17:42:45 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:42:45 - mmengine - INFO - Epoch(train) [8][2462/2462] lr: 5.0004e-02 eta: 0:14:28 time: 0.0439 data_time: 0.0062 memory: 1794 loss: 0.5981 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 0.5981 2022/11/28 17:42:45 - mmengine - INFO - Saving checkpoint at 8 epochs 2022/11/28 17:42:49 - mmengine - INFO - Epoch(val) [8][100/398] eta: 0:00:10 time: 0.0338 data_time: 0.0201 memory: 364 2022/11/28 17:42:52 - mmengine - INFO - Epoch(val) [8][200/398] eta: 0:00:06 time: 0.0249 data_time: 0.0120 memory: 364 2022/11/28 17:42:54 - mmengine - INFO - Epoch(val) [8][300/398] eta: 0:00:02 time: 0.0261 data_time: 0.0140 memory: 364 2022/11/28 17:42:58 - mmengine - INFO - Epoch(val) [8][398/398] acc/top1: 0.7229 acc/top5: 0.9258 acc/mean1: 0.7405 2022/11/28 17:42:58 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d/best_acc/top1_epoch_7.pth is removed 2022/11/28 17:42:58 - mmengine - INFO - The best checkpoint with 0.7229 acc/top1 at 8 epoch is saved to best_acc/top1_epoch_8.pth. 2022/11/28 17:43:03 - mmengine - INFO - Epoch(train) [9][100/2462] lr: 4.9605e-02 eta: 0:14:24 time: 0.0442 data_time: 0.0062 memory: 1794 loss: 0.5271 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5271 2022/11/28 17:43:08 - mmengine - INFO - Epoch(train) [9][200/2462] lr: 4.9207e-02 eta: 0:14:19 time: 0.0437 data_time: 0.0062 memory: 1794 loss: 0.5443 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5443 2022/11/28 17:43:12 - mmengine - INFO - Epoch(train) [9][300/2462] lr: 4.8808e-02 eta: 0:14:15 time: 0.0444 data_time: 0.0062 memory: 1794 loss: 0.5347 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5347 2022/11/28 17:43:12 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:43:16 - mmengine - INFO - Epoch(train) [9][400/2462] lr: 4.8409e-02 eta: 0:14:11 time: 0.0440 data_time: 0.0065 memory: 1794 loss: 0.4356 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4356 2022/11/28 17:43:21 - mmengine - INFO - Epoch(train) [9][500/2462] lr: 4.8011e-02 eta: 0:14:06 time: 0.0433 data_time: 0.0061 memory: 1794 loss: 0.5478 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5478 2022/11/28 17:43:25 - mmengine - INFO - Epoch(train) [9][600/2462] lr: 4.7612e-02 eta: 0:14:02 time: 0.0445 data_time: 0.0064 memory: 1794 loss: 0.5163 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5163 2022/11/28 17:43:30 - mmengine - INFO - Epoch(train) [9][700/2462] lr: 4.7214e-02 eta: 0:13:57 time: 0.0440 data_time: 0.0060 memory: 1794 loss: 0.4561 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4561 2022/11/28 17:43:34 - mmengine - INFO - Epoch(train) [9][800/2462] lr: 4.6816e-02 eta: 0:13:53 time: 0.0437 data_time: 0.0061 memory: 1794 loss: 0.4613 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.4613 2022/11/28 17:43:38 - mmengine - INFO - Epoch(train) [9][900/2462] lr: 4.6418e-02 eta: 0:13:49 time: 0.0431 data_time: 0.0062 memory: 1794 loss: 0.6038 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.6038 2022/11/28 17:43:43 - mmengine - INFO - Epoch(train) [9][1000/2462] lr: 4.6021e-02 eta: 0:13:44 time: 0.0440 data_time: 0.0061 memory: 1794 loss: 0.5418 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5418 2022/11/28 17:43:47 - mmengine - INFO - Epoch(train) [9][1100/2462] lr: 4.5623e-02 eta: 0:13:40 time: 0.0446 data_time: 0.0067 memory: 1794 loss: 0.4365 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4365 2022/11/28 17:43:52 - mmengine - INFO - Epoch(train) [9][1200/2462] lr: 4.5226e-02 eta: 0:13:35 time: 0.0435 data_time: 0.0061 memory: 1794 loss: 0.3886 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3886 2022/11/28 17:43:56 - mmengine - INFO - Epoch(train) [9][1300/2462] lr: 4.4829e-02 eta: 0:13:31 time: 0.0436 data_time: 0.0061 memory: 1794 loss: 0.4719 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4719 2022/11/28 17:43:56 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:44:00 - mmengine - INFO - Epoch(train) [9][1400/2462] lr: 4.4433e-02 eta: 0:13:26 time: 0.0437 data_time: 0.0061 memory: 1794 loss: 0.4545 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.4545 2022/11/28 17:44:05 - mmengine - INFO - Epoch(train) [9][1500/2462] lr: 4.4037e-02 eta: 0:13:22 time: 0.0432 data_time: 0.0061 memory: 1794 loss: 0.4754 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4754 2022/11/28 17:44:09 - mmengine - INFO - Epoch(train) [9][1600/2462] lr: 4.3641e-02 eta: 0:13:18 time: 0.0456 data_time: 0.0062 memory: 1794 loss: 0.4414 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4414 2022/11/28 17:44:14 - mmengine - INFO - Epoch(train) [9][1700/2462] lr: 4.3246e-02 eta: 0:13:13 time: 0.0434 data_time: 0.0061 memory: 1794 loss: 0.3646 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3646 2022/11/28 17:44:18 - mmengine - INFO - Epoch(train) [9][1800/2462] lr: 4.2851e-02 eta: 0:13:09 time: 0.0441 data_time: 0.0064 memory: 1794 loss: 0.5272 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5272 2022/11/28 17:44:22 - mmengine - INFO - Epoch(train) [9][1900/2462] lr: 4.2456e-02 eta: 0:13:04 time: 0.0441 data_time: 0.0061 memory: 1794 loss: 0.5250 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5250 2022/11/28 17:44:27 - mmengine - INFO - Epoch(train) [9][2000/2462] lr: 4.2063e-02 eta: 0:13:00 time: 0.0436 data_time: 0.0061 memory: 1794 loss: 0.4116 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4116 2022/11/28 17:44:31 - mmengine - INFO - Epoch(train) [9][2100/2462] lr: 4.1669e-02 eta: 0:12:55 time: 0.0438 data_time: 0.0061 memory: 1794 loss: 0.5167 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5167 2022/11/28 17:44:36 - mmengine - INFO - Epoch(train) [9][2200/2462] lr: 4.1276e-02 eta: 0:12:51 time: 0.0432 data_time: 0.0061 memory: 1794 loss: 0.4951 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4951 2022/11/28 17:44:40 - mmengine - INFO - Epoch(train) [9][2300/2462] lr: 4.0884e-02 eta: 0:12:47 time: 0.0444 data_time: 0.0069 memory: 1794 loss: 0.4002 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4002 2022/11/28 17:44:40 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:44:45 - mmengine - INFO - Epoch(train) [9][2400/2462] lr: 4.0492e-02 eta: 0:12:42 time: 0.0442 data_time: 0.0061 memory: 1794 loss: 0.3766 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.3766 2022/11/28 17:44:47 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:44:47 - mmengine - INFO - Epoch(train) [9][2462/2462] lr: 4.0249e-02 eta: 0:12:40 time: 0.0443 data_time: 0.0063 memory: 1794 loss: 0.4297 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4297 2022/11/28 17:44:47 - mmengine - INFO - Saving checkpoint at 9 epochs 2022/11/28 17:44:51 - mmengine - INFO - Epoch(val) [9][100/398] eta: 0:00:10 time: 0.0333 data_time: 0.0201 memory: 364 2022/11/28 17:44:54 - mmengine - INFO - Epoch(val) [9][200/398] eta: 0:00:06 time: 0.0244 data_time: 0.0116 memory: 364 2022/11/28 17:44:57 - mmengine - INFO - Epoch(val) [9][300/398] eta: 0:00:02 time: 0.0256 data_time: 0.0136 memory: 364 2022/11/28 17:45:00 - mmengine - INFO - Epoch(val) [9][398/398] acc/top1: 0.7576 acc/top5: 0.9449 acc/mean1: 0.7654 2022/11/28 17:45:00 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d/best_acc/top1_epoch_8.pth is removed 2022/11/28 17:45:01 - mmengine - INFO - The best checkpoint with 0.7576 acc/top1 at 9 epoch is saved to best_acc/top1_epoch_9.pth. 2022/11/28 17:45:06 - mmengine - INFO - Epoch(train) [10][100/2462] lr: 3.9859e-02 eta: 0:12:35 time: 0.0441 data_time: 0.0064 memory: 1794 loss: 0.4327 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4327 2022/11/28 17:45:10 - mmengine - INFO - Epoch(train) [10][200/2462] lr: 3.9468e-02 eta: 0:12:31 time: 0.0442 data_time: 0.0061 memory: 1794 loss: 0.5185 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5185 2022/11/28 17:45:14 - mmengine - INFO - Epoch(train) [10][300/2462] lr: 3.9079e-02 eta: 0:12:27 time: 0.0451 data_time: 0.0067 memory: 1794 loss: 0.3964 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.3964 2022/11/28 17:45:19 - mmengine - INFO - Epoch(train) [10][400/2462] lr: 3.8690e-02 eta: 0:12:22 time: 0.0433 data_time: 0.0061 memory: 1794 loss: 0.4642 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.4642 2022/11/28 17:45:23 - mmengine - INFO - Epoch(train) [10][500/2462] lr: 3.8302e-02 eta: 0:12:18 time: 0.0439 data_time: 0.0060 memory: 1794 loss: 0.3885 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3885 2022/11/28 17:45:28 - mmengine - INFO - Epoch(train) [10][600/2462] lr: 3.7915e-02 eta: 0:12:13 time: 0.0447 data_time: 0.0062 memory: 1794 loss: 0.4204 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.4204 2022/11/28 17:45:32 - mmengine - INFO - Epoch(train) [10][700/2462] lr: 3.7528e-02 eta: 0:12:09 time: 0.0451 data_time: 0.0061 memory: 1794 loss: 0.4392 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.4392 2022/11/28 17:45:37 - mmengine - INFO - Epoch(train) [10][800/2462] lr: 3.7143e-02 eta: 0:12:05 time: 0.0438 data_time: 0.0060 memory: 1794 loss: 0.3458 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.3458 2022/11/28 17:45:38 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:45:41 - mmengine - INFO - Epoch(train) [10][900/2462] lr: 3.6758e-02 eta: 0:12:00 time: 0.0439 data_time: 0.0061 memory: 1794 loss: 0.4593 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4593 2022/11/28 17:45:45 - mmengine - INFO - Epoch(train) [10][1000/2462] lr: 3.6373e-02 eta: 0:11:56 time: 0.0443 data_time: 0.0061 memory: 1794 loss: 0.3709 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3709 2022/11/28 17:45:50 - mmengine - INFO - Epoch(train) [10][1100/2462] lr: 3.5990e-02 eta: 0:11:51 time: 0.0436 data_time: 0.0061 memory: 1794 loss: 0.4112 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4112 2022/11/28 17:45:54 - mmengine - INFO - Epoch(train) [10][1200/2462] lr: 3.5608e-02 eta: 0:11:47 time: 0.0444 data_time: 0.0064 memory: 1794 loss: 0.4162 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4162 2022/11/28 17:45:59 - mmengine - INFO - Epoch(train) [10][1300/2462] lr: 3.5226e-02 eta: 0:11:42 time: 0.0441 data_time: 0.0061 memory: 1794 loss: 0.3702 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3702 2022/11/28 17:46:03 - mmengine - INFO - Epoch(train) [10][1400/2462] lr: 3.4846e-02 eta: 0:11:38 time: 0.0444 data_time: 0.0065 memory: 1794 loss: 0.3818 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3818 2022/11/28 17:46:08 - mmengine - INFO - Epoch(train) [10][1500/2462] lr: 3.4466e-02 eta: 0:11:34 time: 0.0446 data_time: 0.0061 memory: 1794 loss: 0.3855 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.3855 2022/11/28 17:46:12 - mmengine - INFO - Epoch(train) [10][1600/2462] lr: 3.4088e-02 eta: 0:11:29 time: 0.0441 data_time: 0.0061 memory: 1794 loss: 0.3431 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3431 2022/11/28 17:46:17 - mmengine - INFO - Epoch(train) [10][1700/2462] lr: 3.3710e-02 eta: 0:11:25 time: 0.0435 data_time: 0.0061 memory: 1794 loss: 0.3865 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.3865 2022/11/28 17:46:21 - mmengine - INFO - Epoch(train) [10][1800/2462] lr: 3.3334e-02 eta: 0:11:21 time: 0.0437 data_time: 0.0067 memory: 1794 loss: 0.4010 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4010 2022/11/28 17:46:23 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:46:25 - mmengine - INFO - Epoch(train) [10][1900/2462] lr: 3.2959e-02 eta: 0:11:16 time: 0.0445 data_time: 0.0060 memory: 1794 loss: 0.4361 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.4361 2022/11/28 17:46:30 - mmengine - INFO - Epoch(train) [10][2000/2462] lr: 3.2584e-02 eta: 0:11:12 time: 0.0442 data_time: 0.0072 memory: 1794 loss: 0.4187 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4187 2022/11/28 17:46:34 - mmengine - INFO - Epoch(train) [10][2100/2462] lr: 3.2211e-02 eta: 0:11:07 time: 0.0438 data_time: 0.0061 memory: 1794 loss: 0.3696 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.3696 2022/11/28 17:46:39 - mmengine - INFO - Epoch(train) [10][2200/2462] lr: 3.1839e-02 eta: 0:11:03 time: 0.0493 data_time: 0.0091 memory: 1794 loss: 0.4401 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4401 2022/11/28 17:46:43 - mmengine - INFO - Epoch(train) [10][2300/2462] lr: 3.1468e-02 eta: 0:10:59 time: 0.0436 data_time: 0.0061 memory: 1794 loss: 0.3836 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.3836 2022/11/28 17:46:48 - mmengine - INFO - Epoch(train) [10][2400/2462] lr: 3.1098e-02 eta: 0:10:54 time: 0.0442 data_time: 0.0062 memory: 1794 loss: 0.4116 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.4116 2022/11/28 17:46:51 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:46:51 - mmengine - INFO - Epoch(train) [10][2462/2462] lr: 3.0870e-02 eta: 0:10:52 time: 0.0442 data_time: 0.0064 memory: 1794 loss: 0.3471 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3471 2022/11/28 17:46:51 - mmengine - INFO - Saving checkpoint at 10 epochs 2022/11/28 17:46:55 - mmengine - INFO - Epoch(val) [10][100/398] eta: 0:00:10 time: 0.0336 data_time: 0.0204 memory: 364 2022/11/28 17:46:58 - mmengine - INFO - Epoch(val) [10][200/398] eta: 0:00:06 time: 0.0250 data_time: 0.0119 memory: 364 2022/11/28 17:47:00 - mmengine - INFO - Epoch(val) [10][300/398] eta: 0:00:02 time: 0.0278 data_time: 0.0157 memory: 364 2022/11/28 17:47:04 - mmengine - INFO - Epoch(val) [10][398/398] acc/top1: 0.6754 acc/top5: 0.8938 acc/mean1: 0.6956 2022/11/28 17:47:08 - mmengine - INFO - Epoch(train) [11][100/2462] lr: 3.0502e-02 eta: 0:10:47 time: 0.0446 data_time: 0.0061 memory: 1794 loss: 0.3513 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 0.3513 2022/11/28 17:47:13 - mmengine - INFO - Epoch(train) [11][200/2462] lr: 3.0135e-02 eta: 0:10:43 time: 0.0437 data_time: 0.0060 memory: 1794 loss: 0.3233 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3233 2022/11/28 17:47:17 - mmengine - INFO - Epoch(train) [11][300/2462] lr: 2.9770e-02 eta: 0:10:39 time: 0.0442 data_time: 0.0061 memory: 1794 loss: 0.3641 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.3641 2022/11/28 17:47:21 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:47:22 - mmengine - INFO - Epoch(train) [11][400/2462] lr: 2.9406e-02 eta: 0:10:34 time: 0.0437 data_time: 0.0062 memory: 1794 loss: 0.2333 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.2333 2022/11/28 17:47:26 - mmengine - INFO - Epoch(train) [11][500/2462] lr: 2.9043e-02 eta: 0:10:30 time: 0.0444 data_time: 0.0062 memory: 1794 loss: 0.3337 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.3337 2022/11/28 17:47:31 - mmengine - INFO - Epoch(train) [11][600/2462] lr: 2.8682e-02 eta: 0:10:25 time: 0.0439 data_time: 0.0061 memory: 1794 loss: 0.3172 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.3172 2022/11/28 17:47:35 - mmengine - INFO - Epoch(train) [11][700/2462] lr: 2.8322e-02 eta: 0:10:21 time: 0.0440 data_time: 0.0060 memory: 1794 loss: 0.3419 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3419 2022/11/28 17:47:40 - mmengine - INFO - Epoch(train) [11][800/2462] lr: 2.7963e-02 eta: 0:10:17 time: 0.0440 data_time: 0.0068 memory: 1794 loss: 0.3633 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3633 2022/11/28 17:47:44 - mmengine - INFO - Epoch(train) [11][900/2462] lr: 2.7606e-02 eta: 0:10:12 time: 0.0439 data_time: 0.0062 memory: 1794 loss: 0.3128 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3128 2022/11/28 17:47:48 - mmengine - INFO - Epoch(train) [11][1000/2462] lr: 2.7250e-02 eta: 0:10:08 time: 0.0433 data_time: 0.0061 memory: 1794 loss: 0.2844 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2844 2022/11/28 17:47:53 - mmengine - INFO - Epoch(train) [11][1100/2462] lr: 2.6896e-02 eta: 0:10:03 time: 0.0433 data_time: 0.0061 memory: 1794 loss: 0.3451 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3451 2022/11/28 17:47:57 - mmengine - INFO - Epoch(train) [11][1200/2462] lr: 2.6543e-02 eta: 0:09:59 time: 0.0434 data_time: 0.0061 memory: 1794 loss: 0.3597 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3597 2022/11/28 17:48:02 - mmengine - INFO - Epoch(train) [11][1300/2462] lr: 2.6191e-02 eta: 0:09:54 time: 0.0441 data_time: 0.0061 memory: 1794 loss: 0.3232 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3232 2022/11/28 17:48:05 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:48:06 - mmengine - INFO - Epoch(train) [11][1400/2462] lr: 2.5841e-02 eta: 0:09:50 time: 0.0442 data_time: 0.0061 memory: 1794 loss: 0.3231 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.3231 2022/11/28 17:48:10 - mmengine - INFO - Epoch(train) [11][1500/2462] lr: 2.5493e-02 eta: 0:09:46 time: 0.0441 data_time: 0.0061 memory: 1794 loss: 0.3070 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.3070 2022/11/28 17:48:15 - mmengine - INFO - Epoch(train) [11][1600/2462] lr: 2.5146e-02 eta: 0:09:41 time: 0.0435 data_time: 0.0061 memory: 1794 loss: 0.3064 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3064 2022/11/28 17:48:19 - mmengine - INFO - Epoch(train) [11][1700/2462] lr: 2.4801e-02 eta: 0:09:37 time: 0.0440 data_time: 0.0061 memory: 1794 loss: 0.2512 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2512 2022/11/28 17:48:24 - mmengine - INFO - Epoch(train) [11][1800/2462] lr: 2.4458e-02 eta: 0:09:32 time: 0.0442 data_time: 0.0067 memory: 1794 loss: 0.2251 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2251 2022/11/28 17:48:28 - mmengine - INFO - Epoch(train) [11][1900/2462] lr: 2.4116e-02 eta: 0:09:28 time: 0.0436 data_time: 0.0060 memory: 1794 loss: 0.2918 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2918 2022/11/28 17:48:32 - mmengine - INFO - Epoch(train) [11][2000/2462] lr: 2.3775e-02 eta: 0:09:23 time: 0.0446 data_time: 0.0063 memory: 1794 loss: 0.2912 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.2912 2022/11/28 17:48:37 - mmengine - INFO - Epoch(train) [11][2100/2462] lr: 2.3437e-02 eta: 0:09:19 time: 0.0436 data_time: 0.0062 memory: 1794 loss: 0.2835 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2835 2022/11/28 17:48:41 - mmengine - INFO - Epoch(train) [11][2200/2462] lr: 2.3100e-02 eta: 0:09:15 time: 0.0441 data_time: 0.0062 memory: 1794 loss: 0.2720 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.2720 2022/11/28 17:48:46 - mmengine - INFO - Epoch(train) [11][2300/2462] lr: 2.2764e-02 eta: 0:09:10 time: 0.0447 data_time: 0.0068 memory: 1794 loss: 0.2477 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2477 2022/11/28 17:48:50 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:48:50 - mmengine - INFO - Epoch(train) [11][2400/2462] lr: 2.2431e-02 eta: 0:09:06 time: 0.0435 data_time: 0.0061 memory: 1794 loss: 0.2878 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2878 2022/11/28 17:48:53 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:48:53 - mmengine - INFO - Epoch(train) [11][2462/2462] lr: 2.2225e-02 eta: 0:09:03 time: 0.0436 data_time: 0.0061 memory: 1794 loss: 0.2271 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.2271 2022/11/28 17:48:53 - mmengine - INFO - Saving checkpoint at 11 epochs 2022/11/28 17:48:57 - mmengine - INFO - Epoch(val) [11][100/398] eta: 0:00:10 time: 0.0335 data_time: 0.0203 memory: 364 2022/11/28 17:49:00 - mmengine - INFO - Epoch(val) [11][200/398] eta: 0:00:06 time: 0.0246 data_time: 0.0118 memory: 364 2022/11/28 17:49:03 - mmengine - INFO - Epoch(val) [11][300/398] eta: 0:00:02 time: 0.0259 data_time: 0.0139 memory: 364 2022/11/28 17:49:06 - mmengine - INFO - Epoch(val) [11][398/398] acc/top1: 0.7079 acc/top5: 0.9215 acc/mean1: 0.7243 2022/11/28 17:49:11 - mmengine - INFO - Epoch(train) [12][100/2462] lr: 2.1894e-02 eta: 0:08:59 time: 0.0444 data_time: 0.0060 memory: 1794 loss: 0.2912 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2912 2022/11/28 17:49:15 - mmengine - INFO - Epoch(train) [12][200/2462] lr: 2.1565e-02 eta: 0:08:54 time: 0.0438 data_time: 0.0061 memory: 1794 loss: 0.2677 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2677 2022/11/28 17:49:20 - mmengine - INFO - Epoch(train) [12][300/2462] lr: 2.1238e-02 eta: 0:08:50 time: 0.0450 data_time: 0.0066 memory: 1794 loss: 0.2781 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2781 2022/11/28 17:49:24 - mmengine - INFO - Epoch(train) [12][400/2462] lr: 2.0913e-02 eta: 0:08:46 time: 0.0474 data_time: 0.0062 memory: 1794 loss: 0.2583 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2583 2022/11/28 17:49:29 - mmengine - INFO - Epoch(train) [12][500/2462] lr: 2.0589e-02 eta: 0:08:41 time: 0.0440 data_time: 0.0061 memory: 1794 loss: 0.2636 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2636 2022/11/28 17:49:33 - mmengine - INFO - Epoch(train) [12][600/2462] lr: 2.0268e-02 eta: 0:08:37 time: 0.0450 data_time: 0.0066 memory: 1794 loss: 0.2171 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2171 2022/11/28 17:49:38 - mmengine - INFO - Epoch(train) [12][700/2462] lr: 1.9948e-02 eta: 0:08:33 time: 0.0441 data_time: 0.0067 memory: 1794 loss: 0.2001 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.2001 2022/11/28 17:49:42 - mmengine - INFO - Epoch(train) [12][800/2462] lr: 1.9631e-02 eta: 0:08:28 time: 0.0442 data_time: 0.0061 memory: 1794 loss: 0.2807 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2807 2022/11/28 17:49:47 - mmengine - INFO - Epoch(train) [12][900/2462] lr: 1.9315e-02 eta: 0:08:24 time: 0.0451 data_time: 0.0070 memory: 1794 loss: 0.2401 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.2401 2022/11/28 17:49:48 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:49:51 - mmengine - INFO - Epoch(train) [12][1000/2462] lr: 1.9001e-02 eta: 0:08:19 time: 0.0440 data_time: 0.0067 memory: 1794 loss: 0.2050 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2050 2022/11/28 17:49:56 - mmengine - INFO - Epoch(train) [12][1100/2462] lr: 1.8689e-02 eta: 0:08:15 time: 0.0438 data_time: 0.0061 memory: 1794 loss: 0.2206 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2206 2022/11/28 17:50:00 - mmengine - INFO - Epoch(train) [12][1200/2462] lr: 1.8379e-02 eta: 0:08:11 time: 0.0444 data_time: 0.0060 memory: 1794 loss: 0.2335 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2335 2022/11/28 17:50:05 - mmengine - INFO - Epoch(train) [12][1300/2462] lr: 1.8071e-02 eta: 0:08:06 time: 0.0445 data_time: 0.0067 memory: 1794 loss: 0.2586 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2586 2022/11/28 17:50:09 - mmengine - INFO - Epoch(train) [12][1400/2462] lr: 1.7765e-02 eta: 0:08:02 time: 0.0452 data_time: 0.0067 memory: 1794 loss: 0.1770 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1770 2022/11/28 17:50:14 - mmengine - INFO - Epoch(train) [12][1500/2462] lr: 1.7462e-02 eta: 0:07:57 time: 0.0447 data_time: 0.0061 memory: 1794 loss: 0.2018 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.2018 2022/11/28 17:50:18 - mmengine - INFO - Epoch(train) [12][1600/2462] lr: 1.7160e-02 eta: 0:07:53 time: 0.0445 data_time: 0.0067 memory: 1794 loss: 0.2947 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2947 2022/11/28 17:50:22 - mmengine - INFO - Epoch(train) [12][1700/2462] lr: 1.6860e-02 eta: 0:07:48 time: 0.0438 data_time: 0.0061 memory: 1794 loss: 0.2124 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2124 2022/11/28 17:50:27 - mmengine - INFO - Epoch(train) [12][1800/2462] lr: 1.6563e-02 eta: 0:07:44 time: 0.0455 data_time: 0.0065 memory: 1794 loss: 0.2541 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.2541 2022/11/28 17:50:31 - mmengine - INFO - Epoch(train) [12][1900/2462] lr: 1.6267e-02 eta: 0:07:40 time: 0.0437 data_time: 0.0062 memory: 1794 loss: 0.2012 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2012 2022/11/28 17:50:32 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:50:36 - mmengine - INFO - Epoch(train) [12][2000/2462] lr: 1.5974e-02 eta: 0:07:35 time: 0.0461 data_time: 0.0070 memory: 1794 loss: 0.1860 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.1860 2022/11/28 17:50:40 - mmengine - INFO - Epoch(train) [12][2100/2462] lr: 1.5683e-02 eta: 0:07:31 time: 0.0446 data_time: 0.0061 memory: 1794 loss: 0.1520 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1520 2022/11/28 17:50:45 - mmengine - INFO - Epoch(train) [12][2200/2462] lr: 1.5394e-02 eta: 0:07:26 time: 0.0444 data_time: 0.0062 memory: 1794 loss: 0.2154 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.2154 2022/11/28 17:50:49 - mmengine - INFO - Epoch(train) [12][2300/2462] lr: 1.5107e-02 eta: 0:07:22 time: 0.0441 data_time: 0.0062 memory: 1794 loss: 0.1678 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1678 2022/11/28 17:50:54 - mmengine - INFO - Epoch(train) [12][2400/2462] lr: 1.4823e-02 eta: 0:07:18 time: 0.0450 data_time: 0.0065 memory: 1794 loss: 0.1232 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1232 2022/11/28 17:50:57 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:50:57 - mmengine - INFO - Epoch(train) [12][2462/2462] lr: 1.4647e-02 eta: 0:07:15 time: 0.0448 data_time: 0.0063 memory: 1794 loss: 0.1689 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1689 2022/11/28 17:50:57 - mmengine - INFO - Saving checkpoint at 12 epochs 2022/11/28 17:51:00 - mmengine - INFO - Epoch(val) [12][100/398] eta: 0:00:10 time: 0.0335 data_time: 0.0203 memory: 364 2022/11/28 17:51:03 - mmengine - INFO - Epoch(val) [12][200/398] eta: 0:00:06 time: 0.0248 data_time: 0.0119 memory: 364 2022/11/28 17:51:06 - mmengine - INFO - Epoch(val) [12][300/398] eta: 0:00:02 time: 0.0256 data_time: 0.0135 memory: 364 2022/11/28 17:51:10 - mmengine - INFO - Epoch(val) [12][398/398] acc/top1: 0.7586 acc/top5: 0.9377 acc/mean1: 0.7710 2022/11/28 17:51:10 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d/best_acc/top1_epoch_9.pth is removed 2022/11/28 17:51:10 - mmengine - INFO - The best checkpoint with 0.7586 acc/top1 at 12 epoch is saved to best_acc/top1_epoch_12.pth. 2022/11/28 17:51:14 - mmengine - INFO - Epoch(train) [13][100/2462] lr: 1.4367e-02 eta: 0:07:11 time: 0.0437 data_time: 0.0062 memory: 1794 loss: 0.1521 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1521 2022/11/28 17:51:19 - mmengine - INFO - Epoch(train) [13][200/2462] lr: 1.4088e-02 eta: 0:07:06 time: 0.0441 data_time: 0.0066 memory: 1794 loss: 0.1354 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1354 2022/11/28 17:51:23 - mmengine - INFO - Epoch(train) [13][300/2462] lr: 1.3812e-02 eta: 0:07:02 time: 0.0436 data_time: 0.0062 memory: 1794 loss: 0.1560 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1560 2022/11/28 17:51:28 - mmengine - INFO - Epoch(train) [13][400/2462] lr: 1.3538e-02 eta: 0:06:57 time: 0.0438 data_time: 0.0062 memory: 1794 loss: 0.1483 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1483 2022/11/28 17:51:30 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:51:32 - mmengine - INFO - Epoch(train) [13][500/2462] lr: 1.3266e-02 eta: 0:06:53 time: 0.0442 data_time: 0.0063 memory: 1794 loss: 0.1559 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1559 2022/11/28 17:51:37 - mmengine - INFO - Epoch(train) [13][600/2462] lr: 1.2997e-02 eta: 0:06:48 time: 0.0437 data_time: 0.0063 memory: 1794 loss: 0.1652 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1652 2022/11/28 17:51:41 - mmengine - INFO - Epoch(train) [13][700/2462] lr: 1.2730e-02 eta: 0:06:44 time: 0.0446 data_time: 0.0062 memory: 1794 loss: 0.1148 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1148 2022/11/28 17:51:46 - mmengine - INFO - Epoch(train) [13][800/2462] lr: 1.2465e-02 eta: 0:06:40 time: 0.0443 data_time: 0.0064 memory: 1794 loss: 0.1573 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1573 2022/11/28 17:51:50 - mmengine - INFO - Epoch(train) [13][900/2462] lr: 1.2203e-02 eta: 0:06:35 time: 0.0437 data_time: 0.0062 memory: 1794 loss: 0.1184 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1184 2022/11/28 17:51:55 - mmengine - INFO - Epoch(train) [13][1000/2462] lr: 1.1943e-02 eta: 0:06:31 time: 0.0451 data_time: 0.0062 memory: 1794 loss: 0.1038 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1038 2022/11/28 17:51:59 - mmengine - INFO - Epoch(train) [13][1100/2462] lr: 1.1686e-02 eta: 0:06:26 time: 0.0447 data_time: 0.0062 memory: 1794 loss: 0.1270 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.1270 2022/11/28 17:52:03 - mmengine - INFO - Epoch(train) [13][1200/2462] lr: 1.1431e-02 eta: 0:06:22 time: 0.0450 data_time: 0.0062 memory: 1794 loss: 0.1337 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1337 2022/11/28 17:52:08 - mmengine - INFO - Epoch(train) [13][1300/2462] lr: 1.1178e-02 eta: 0:06:18 time: 0.0439 data_time: 0.0061 memory: 1794 loss: 0.1519 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.1519 2022/11/28 17:52:12 - mmengine - INFO - Epoch(train) [13][1400/2462] lr: 1.0928e-02 eta: 0:06:13 time: 0.0439 data_time: 0.0062 memory: 1794 loss: 0.1634 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1634 2022/11/28 17:52:15 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:52:17 - mmengine - INFO - Epoch(train) [13][1500/2462] lr: 1.0680e-02 eta: 0:06:09 time: 0.0440 data_time: 0.0062 memory: 1794 loss: 0.1333 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1333 2022/11/28 17:52:21 - mmengine - INFO - Epoch(train) [13][1600/2462] lr: 1.0435e-02 eta: 0:06:04 time: 0.0438 data_time: 0.0061 memory: 1794 loss: 0.1316 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1316 2022/11/28 17:52:26 - mmengine - INFO - Epoch(train) [13][1700/2462] lr: 1.0193e-02 eta: 0:06:00 time: 0.0440 data_time: 0.0063 memory: 1794 loss: 0.1598 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1598 2022/11/28 17:52:30 - mmengine - INFO - Epoch(train) [13][1800/2462] lr: 9.9527e-03 eta: 0:05:55 time: 0.0440 data_time: 0.0062 memory: 1794 loss: 0.0973 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0973 2022/11/28 17:52:34 - mmengine - INFO - Epoch(train) [13][1900/2462] lr: 9.7153e-03 eta: 0:05:51 time: 0.0438 data_time: 0.0062 memory: 1794 loss: 0.1328 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1328 2022/11/28 17:52:39 - mmengine - INFO - Epoch(train) [13][2000/2462] lr: 9.4804e-03 eta: 0:05:47 time: 0.0442 data_time: 0.0066 memory: 1794 loss: 0.0965 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0965 2022/11/28 17:52:43 - mmengine - INFO - Epoch(train) [13][2100/2462] lr: 9.2480e-03 eta: 0:05:42 time: 0.0454 data_time: 0.0062 memory: 1794 loss: 0.0914 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0914 2022/11/28 17:52:48 - mmengine - INFO - Epoch(train) [13][2200/2462] lr: 9.0183e-03 eta: 0:05:38 time: 0.0436 data_time: 0.0062 memory: 1794 loss: 0.1114 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1114 2022/11/28 17:52:52 - mmengine - INFO - Epoch(train) [13][2300/2462] lr: 8.7911e-03 eta: 0:05:33 time: 0.0435 data_time: 0.0062 memory: 1794 loss: 0.0939 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0939 2022/11/28 17:52:57 - mmengine - INFO - Epoch(train) [13][2400/2462] lr: 8.5666e-03 eta: 0:05:29 time: 0.0445 data_time: 0.0062 memory: 1794 loss: 0.1078 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1078 2022/11/28 17:52:59 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:53:00 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:53:00 - mmengine - INFO - Epoch(train) [13][2462/2462] lr: 8.4287e-03 eta: 0:05:26 time: 0.0454 data_time: 0.0063 memory: 1794 loss: 0.1228 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1228 2022/11/28 17:53:00 - mmengine - INFO - Saving checkpoint at 13 epochs 2022/11/28 17:53:03 - mmengine - INFO - Epoch(val) [13][100/398] eta: 0:00:10 time: 0.0341 data_time: 0.0207 memory: 364 2022/11/28 17:53:06 - mmengine - INFO - Epoch(val) [13][200/398] eta: 0:00:06 time: 0.0251 data_time: 0.0120 memory: 364 2022/11/28 17:53:09 - mmengine - INFO - Epoch(val) [13][300/398] eta: 0:00:02 time: 0.0261 data_time: 0.0137 memory: 364 2022/11/28 17:53:13 - mmengine - INFO - Epoch(val) [13][398/398] acc/top1: 0.7791 acc/top5: 0.9447 acc/mean1: 0.7933 2022/11/28 17:53:13 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d/best_acc/top1_epoch_12.pth is removed 2022/11/28 17:53:13 - mmengine - INFO - The best checkpoint with 0.7791 acc/top1 at 13 epoch is saved to best_acc/top1_epoch_13.pth. 2022/11/28 17:53:18 - mmengine - INFO - Epoch(train) [14][100/2462] lr: 8.2085e-03 eta: 0:05:22 time: 0.0449 data_time: 0.0066 memory: 1794 loss: 0.0683 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0683 2022/11/28 17:53:22 - mmengine - INFO - Epoch(train) [14][200/2462] lr: 7.9909e-03 eta: 0:05:17 time: 0.0451 data_time: 0.0063 memory: 1794 loss: 0.1064 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1064 2022/11/28 17:53:27 - mmengine - INFO - Epoch(train) [14][300/2462] lr: 7.7760e-03 eta: 0:05:13 time: 0.0442 data_time: 0.0062 memory: 1794 loss: 0.0896 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0896 2022/11/28 17:53:31 - mmengine - INFO - Epoch(train) [14][400/2462] lr: 7.5638e-03 eta: 0:05:09 time: 0.0462 data_time: 0.0062 memory: 1794 loss: 0.0693 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0693 2022/11/28 17:53:36 - mmengine - INFO - Epoch(train) [14][500/2462] lr: 7.3542e-03 eta: 0:05:04 time: 0.0446 data_time: 0.0066 memory: 1794 loss: 0.0602 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0602 2022/11/28 17:53:40 - mmengine - INFO - Epoch(train) [14][600/2462] lr: 7.1474e-03 eta: 0:05:00 time: 0.0468 data_time: 0.0063 memory: 1794 loss: 0.0654 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0654 2022/11/28 17:53:45 - mmengine - INFO - Epoch(train) [14][700/2462] lr: 6.9433e-03 eta: 0:04:55 time: 0.0442 data_time: 0.0062 memory: 1794 loss: 0.0991 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.0991 2022/11/28 17:53:49 - mmengine - INFO - Epoch(train) [14][800/2462] lr: 6.7420e-03 eta: 0:04:51 time: 0.0443 data_time: 0.0061 memory: 1794 loss: 0.0965 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0965 2022/11/28 17:53:54 - mmengine - INFO - Epoch(train) [14][900/2462] lr: 6.5434e-03 eta: 0:04:47 time: 0.0454 data_time: 0.0064 memory: 1794 loss: 0.0779 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0779 2022/11/28 17:53:58 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:53:58 - mmengine - INFO - Epoch(train) [14][1000/2462] lr: 6.3476e-03 eta: 0:04:42 time: 0.0444 data_time: 0.0062 memory: 1794 loss: 0.0562 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0562 2022/11/28 17:54:03 - mmengine - INFO - Epoch(train) [14][1100/2462] lr: 6.1545e-03 eta: 0:04:38 time: 0.0454 data_time: 0.0065 memory: 1794 loss: 0.1000 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1000 2022/11/28 17:54:07 - mmengine - INFO - Epoch(train) [14][1200/2462] lr: 5.9642e-03 eta: 0:04:33 time: 0.0445 data_time: 0.0069 memory: 1794 loss: 0.0809 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0809 2022/11/28 17:54:12 - mmengine - INFO - Epoch(train) [14][1300/2462] lr: 5.7768e-03 eta: 0:04:29 time: 0.0464 data_time: 0.0062 memory: 1794 loss: 0.0831 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0831 2022/11/28 17:54:16 - mmengine - INFO - Epoch(train) [14][1400/2462] lr: 5.5921e-03 eta: 0:04:25 time: 0.0454 data_time: 0.0075 memory: 1794 loss: 0.0680 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.0680 2022/11/28 17:54:21 - mmengine - INFO - Epoch(train) [14][1500/2462] lr: 5.4103e-03 eta: 0:04:20 time: 0.0448 data_time: 0.0074 memory: 1794 loss: 0.0515 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0515 2022/11/28 17:54:25 - mmengine - INFO - Epoch(train) [14][1600/2462] lr: 5.2313e-03 eta: 0:04:16 time: 0.0448 data_time: 0.0063 memory: 1794 loss: 0.1142 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1142 2022/11/28 17:54:30 - mmengine - INFO - Epoch(train) [14][1700/2462] lr: 5.0551e-03 eta: 0:04:11 time: 0.0442 data_time: 0.0067 memory: 1794 loss: 0.0379 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0379 2022/11/28 17:54:34 - mmengine - INFO - Epoch(train) [14][1800/2462] lr: 4.8818e-03 eta: 0:04:07 time: 0.0440 data_time: 0.0062 memory: 1794 loss: 0.0448 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0448 2022/11/28 17:54:39 - mmengine - INFO - Epoch(train) [14][1900/2462] lr: 4.7114e-03 eta: 0:04:02 time: 0.0451 data_time: 0.0070 memory: 1794 loss: 0.0605 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0605 2022/11/28 17:54:43 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:54:44 - mmengine - INFO - Epoch(train) [14][2000/2462] lr: 4.5439e-03 eta: 0:03:58 time: 0.0439 data_time: 0.0062 memory: 1794 loss: 0.0543 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0543 2022/11/28 17:54:48 - mmengine - INFO - Epoch(train) [14][2100/2462] lr: 4.3792e-03 eta: 0:03:54 time: 0.0445 data_time: 0.0062 memory: 1794 loss: 0.0596 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0596 2022/11/28 17:54:52 - mmengine - INFO - Epoch(train) [14][2200/2462] lr: 4.2175e-03 eta: 0:03:49 time: 0.0442 data_time: 0.0063 memory: 1794 loss: 0.0459 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0459 2022/11/28 17:54:57 - mmengine - INFO - Epoch(train) [14][2300/2462] lr: 4.0587e-03 eta: 0:03:45 time: 0.0442 data_time: 0.0062 memory: 1794 loss: 0.0307 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0307 2022/11/28 17:55:01 - mmengine - INFO - Epoch(train) [14][2400/2462] lr: 3.9027e-03 eta: 0:03:40 time: 0.0437 data_time: 0.0063 memory: 1794 loss: 0.0370 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0370 2022/11/28 17:55:04 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:55:04 - mmengine - INFO - Epoch(train) [14][2462/2462] lr: 3.8075e-03 eta: 0:03:38 time: 0.0439 data_time: 0.0063 memory: 1794 loss: 0.0399 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0399 2022/11/28 17:55:04 - mmengine - INFO - Saving checkpoint at 14 epochs 2022/11/28 17:55:08 - mmengine - INFO - Epoch(val) [14][100/398] eta: 0:00:10 time: 0.0336 data_time: 0.0203 memory: 364 2022/11/28 17:55:11 - mmengine - INFO - Epoch(val) [14][200/398] eta: 0:00:06 time: 0.0247 data_time: 0.0120 memory: 364 2022/11/28 17:55:14 - mmengine - INFO - Epoch(val) [14][300/398] eta: 0:00:02 time: 0.0252 data_time: 0.0132 memory: 364 2022/11/28 17:55:17 - mmengine - INFO - Epoch(val) [14][398/398] acc/top1: 0.7906 acc/top5: 0.9488 acc/mean1: 0.8028 2022/11/28 17:55:17 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d/best_acc/top1_epoch_13.pth is removed 2022/11/28 17:55:17 - mmengine - INFO - The best checkpoint with 0.7906 acc/top1 at 14 epoch is saved to best_acc/top1_epoch_14.pth. 2022/11/28 17:55:22 - mmengine - INFO - Epoch(train) [15][100/2462] lr: 3.6564e-03 eta: 0:03:33 time: 0.0440 data_time: 0.0063 memory: 1794 loss: 0.0596 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0596 2022/11/28 17:55:27 - mmengine - INFO - Epoch(train) [15][200/2462] lr: 3.5082e-03 eta: 0:03:29 time: 0.0445 data_time: 0.0062 memory: 1794 loss: 0.0480 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0480 2022/11/28 17:55:31 - mmengine - INFO - Epoch(train) [15][300/2462] lr: 3.3629e-03 eta: 0:03:24 time: 0.0452 data_time: 0.0062 memory: 1794 loss: 0.0292 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0292 2022/11/28 17:55:36 - mmengine - INFO - Epoch(train) [15][400/2462] lr: 3.2206e-03 eta: 0:03:20 time: 0.0442 data_time: 0.0062 memory: 1794 loss: 0.0414 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0414 2022/11/28 17:55:40 - mmengine - INFO - Epoch(train) [15][500/2462] lr: 3.0813e-03 eta: 0:03:16 time: 0.0453 data_time: 0.0064 memory: 1794 loss: 0.0527 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0527 2022/11/28 17:55:42 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:55:45 - mmengine - INFO - Epoch(train) [15][600/2462] lr: 2.9450e-03 eta: 0:03:11 time: 0.0442 data_time: 0.0062 memory: 1794 loss: 0.0519 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0519 2022/11/28 17:55:49 - mmengine - INFO - Epoch(train) [15][700/2462] lr: 2.8117e-03 eta: 0:03:07 time: 0.0440 data_time: 0.0062 memory: 1794 loss: 0.0760 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0760 2022/11/28 17:55:53 - mmengine - INFO - Epoch(train) [15][800/2462] lr: 2.6813e-03 eta: 0:03:02 time: 0.0444 data_time: 0.0061 memory: 1794 loss: 0.0608 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0608 2022/11/28 17:55:58 - mmengine - INFO - Epoch(train) [15][900/2462] lr: 2.5540e-03 eta: 0:02:58 time: 0.0459 data_time: 0.0062 memory: 1794 loss: 0.0402 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0402 2022/11/28 17:56:02 - mmengine - INFO - Epoch(train) [15][1000/2462] lr: 2.4297e-03 eta: 0:02:53 time: 0.0454 data_time: 0.0064 memory: 1794 loss: 0.0329 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0329 2022/11/28 17:56:07 - mmengine - INFO - Epoch(train) [15][1100/2462] lr: 2.3084e-03 eta: 0:02:49 time: 0.0444 data_time: 0.0061 memory: 1794 loss: 0.0482 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0482 2022/11/28 17:56:11 - mmengine - INFO - Epoch(train) [15][1200/2462] lr: 2.1902e-03 eta: 0:02:45 time: 0.0446 data_time: 0.0063 memory: 1794 loss: 0.0345 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0345 2022/11/28 17:56:16 - mmengine - INFO - Epoch(train) [15][1300/2462] lr: 2.0750e-03 eta: 0:02:40 time: 0.0447 data_time: 0.0063 memory: 1794 loss: 0.0391 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0391 2022/11/28 17:56:20 - mmengine - INFO - Epoch(train) [15][1400/2462] lr: 1.9628e-03 eta: 0:02:36 time: 0.0447 data_time: 0.0064 memory: 1794 loss: 0.0722 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0722 2022/11/28 17:56:25 - mmengine - INFO - Epoch(train) [15][1500/2462] lr: 1.8537e-03 eta: 0:02:31 time: 0.0472 data_time: 0.0062 memory: 1794 loss: 0.0486 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0486 2022/11/28 17:56:26 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:56:29 - mmengine - INFO - Epoch(train) [15][1600/2462] lr: 1.7477e-03 eta: 0:02:27 time: 0.0443 data_time: 0.0066 memory: 1794 loss: 0.0500 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0500 2022/11/28 17:56:34 - mmengine - INFO - Epoch(train) [15][1700/2462] lr: 1.6447e-03 eta: 0:02:22 time: 0.0451 data_time: 0.0062 memory: 1794 loss: 0.0343 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0343 2022/11/28 17:56:38 - mmengine - INFO - Epoch(train) [15][1800/2462] lr: 1.5448e-03 eta: 0:02:18 time: 0.0451 data_time: 0.0063 memory: 1794 loss: 0.0410 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0410 2022/11/28 17:56:43 - mmengine - INFO - Epoch(train) [15][1900/2462] lr: 1.4480e-03 eta: 0:02:14 time: 0.0448 data_time: 0.0069 memory: 1794 loss: 0.0266 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0266 2022/11/28 17:56:48 - mmengine - INFO - Epoch(train) [15][2000/2462] lr: 1.3543e-03 eta: 0:02:09 time: 0.0456 data_time: 0.0063 memory: 1794 loss: 0.0404 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0404 2022/11/28 17:56:52 - mmengine - INFO - Epoch(train) [15][2100/2462] lr: 1.2636e-03 eta: 0:02:05 time: 0.0447 data_time: 0.0062 memory: 1794 loss: 0.0365 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0365 2022/11/28 17:56:57 - mmengine - INFO - Epoch(train) [15][2200/2462] lr: 1.1761e-03 eta: 0:02:00 time: 0.0443 data_time: 0.0064 memory: 1794 loss: 0.0346 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0346 2022/11/28 17:57:01 - mmengine - INFO - Epoch(train) [15][2300/2462] lr: 1.0917e-03 eta: 0:01:56 time: 0.0445 data_time: 0.0061 memory: 1794 loss: 0.0297 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0297 2022/11/28 17:57:05 - mmengine - INFO - Epoch(train) [15][2400/2462] lr: 1.0104e-03 eta: 0:01:51 time: 0.0444 data_time: 0.0062 memory: 1794 loss: 0.0338 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0338 2022/11/28 17:57:08 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:57:08 - mmengine - INFO - Epoch(train) [15][2462/2462] lr: 9.6151e-04 eta: 0:01:49 time: 0.0438 data_time: 0.0063 memory: 1794 loss: 0.0267 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0267 2022/11/28 17:57:08 - mmengine - INFO - Saving checkpoint at 15 epochs 2022/11/28 17:57:12 - mmengine - INFO - Epoch(val) [15][100/398] eta: 0:00:10 time: 0.0333 data_time: 0.0198 memory: 364 2022/11/28 17:57:15 - mmengine - INFO - Epoch(val) [15][200/398] eta: 0:00:06 time: 0.0248 data_time: 0.0119 memory: 364 2022/11/28 17:57:18 - mmengine - INFO - Epoch(val) [15][300/398] eta: 0:00:02 time: 0.0254 data_time: 0.0133 memory: 364 2022/11/28 17:57:21 - mmengine - INFO - Epoch(val) [15][398/398] acc/top1: 0.7943 acc/top5: 0.9501 acc/mean1: 0.8068 2022/11/28 17:57:21 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d/best_acc/top1_epoch_14.pth is removed 2022/11/28 17:57:22 - mmengine - INFO - The best checkpoint with 0.7943 acc/top1 at 15 epoch is saved to best_acc/top1_epoch_15.pth. 2022/11/28 17:57:25 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:57:26 - mmengine - INFO - Epoch(train) [16][100/2462] lr: 8.8525e-04 eta: 0:01:44 time: 0.0458 data_time: 0.0074 memory: 1794 loss: 0.0304 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0304 2022/11/28 17:57:31 - mmengine - INFO - Epoch(train) [16][200/2462] lr: 8.1211e-04 eta: 0:01:40 time: 0.0447 data_time: 0.0062 memory: 1794 loss: 0.0284 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0284 2022/11/28 17:57:35 - mmengine - INFO - Epoch(train) [16][300/2462] lr: 7.4209e-04 eta: 0:01:35 time: 0.0443 data_time: 0.0062 memory: 1794 loss: 0.0381 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0381 2022/11/28 17:57:40 - mmengine - INFO - Epoch(train) [16][400/2462] lr: 6.7522e-04 eta: 0:01:31 time: 0.0443 data_time: 0.0064 memory: 1794 loss: 0.0429 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0429 2022/11/28 17:57:44 - mmengine - INFO - Epoch(train) [16][500/2462] lr: 6.1147e-04 eta: 0:01:26 time: 0.0444 data_time: 0.0062 memory: 1794 loss: 0.0342 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0342 2022/11/28 17:57:49 - mmengine - INFO - Epoch(train) [16][600/2462] lr: 5.5087e-04 eta: 0:01:22 time: 0.0472 data_time: 0.0063 memory: 1794 loss: 0.0349 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0349 2022/11/28 17:57:53 - mmengine - INFO - Epoch(train) [16][700/2462] lr: 4.9342e-04 eta: 0:01:18 time: 0.0461 data_time: 0.0062 memory: 1794 loss: 0.0202 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0202 2022/11/28 17:57:58 - mmengine - INFO - Epoch(train) [16][800/2462] lr: 4.3911e-04 eta: 0:01:13 time: 0.0455 data_time: 0.0086 memory: 1794 loss: 0.0508 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0508 2022/11/28 17:58:02 - mmengine - INFO - Epoch(train) [16][900/2462] lr: 3.8795e-04 eta: 0:01:09 time: 0.0453 data_time: 0.0065 memory: 1794 loss: 0.0246 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0246 2022/11/28 17:58:07 - mmengine - INFO - Epoch(train) [16][1000/2462] lr: 3.3995e-04 eta: 0:01:04 time: 0.0443 data_time: 0.0064 memory: 1794 loss: 0.0315 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0315 2022/11/28 17:58:10 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:58:11 - mmengine - INFO - Epoch(train) [16][1100/2462] lr: 2.9511e-04 eta: 0:01:00 time: 0.0440 data_time: 0.0062 memory: 1794 loss: 0.0254 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0254 2022/11/28 17:58:15 - mmengine - INFO - Epoch(train) [16][1200/2462] lr: 2.5343e-04 eta: 0:00:55 time: 0.0444 data_time: 0.0063 memory: 1794 loss: 0.0223 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0223 2022/11/28 17:58:20 - mmengine - INFO - Epoch(train) [16][1300/2462] lr: 2.1492e-04 eta: 0:00:51 time: 0.0443 data_time: 0.0066 memory: 1794 loss: 0.0248 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0248 2022/11/28 17:58:24 - mmengine - INFO - Epoch(train) [16][1400/2462] lr: 1.7957e-04 eta: 0:00:47 time: 0.0447 data_time: 0.0064 memory: 1794 loss: 0.0365 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0365 2022/11/28 17:58:29 - mmengine - INFO - Epoch(train) [16][1500/2462] lr: 1.4739e-04 eta: 0:00:42 time: 0.0448 data_time: 0.0062 memory: 1794 loss: 0.0400 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0400 2022/11/28 17:58:33 - mmengine - INFO - Epoch(train) [16][1600/2462] lr: 1.1838e-04 eta: 0:00:38 time: 0.0441 data_time: 0.0062 memory: 1794 loss: 0.0319 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0319 2022/11/28 17:58:38 - mmengine - INFO - Epoch(train) [16][1700/2462] lr: 9.2542e-05 eta: 0:00:33 time: 0.0445 data_time: 0.0065 memory: 1794 loss: 0.0272 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0272 2022/11/28 17:58:42 - mmengine - INFO - Epoch(train) [16][1800/2462] lr: 6.9879e-05 eta: 0:00:29 time: 0.0445 data_time: 0.0063 memory: 1794 loss: 0.0404 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.0404 2022/11/28 17:58:47 - mmengine - INFO - Epoch(train) [16][1900/2462] lr: 5.0393e-05 eta: 0:00:24 time: 0.0443 data_time: 0.0065 memory: 1794 loss: 0.0283 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0283 2022/11/28 17:58:51 - mmengine - INFO - Epoch(train) [16][2000/2462] lr: 3.4083e-05 eta: 0:00:20 time: 0.0444 data_time: 0.0062 memory: 1794 loss: 0.0317 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0317 2022/11/28 17:58:54 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:58:56 - mmengine - INFO - Epoch(train) [16][2100/2462] lr: 2.0951e-05 eta: 0:00:16 time: 0.0447 data_time: 0.0063 memory: 1794 loss: 0.0281 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0281 2022/11/28 17:59:00 - mmengine - INFO - Epoch(train) [16][2200/2462] lr: 1.0998e-05 eta: 0:00:11 time: 0.0457 data_time: 0.0074 memory: 1794 loss: 0.0396 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0396 2022/11/28 17:59:05 - mmengine - INFO - Epoch(train) [16][2300/2462] lr: 4.2247e-06 eta: 0:00:07 time: 0.0451 data_time: 0.0071 memory: 1794 loss: 0.0416 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0416 2022/11/28 17:59:10 - mmengine - INFO - Epoch(train) [16][2400/2462] lr: 6.3111e-07 eta: 0:00:02 time: 0.0447 data_time: 0.0062 memory: 1794 loss: 0.0261 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0261 2022/11/28 17:59:12 - mmengine - INFO - Exp name: stgcn_8xb16-bone-motion-u100-80e_ntu120-xsub-keypoint-3d_20221128_172438 2022/11/28 17:59:12 - mmengine - INFO - Epoch(train) [16][2462/2462] lr: 1.5901e-10 eta: 0:00:00 time: 0.0460 data_time: 0.0063 memory: 1794 loss: 0.0676 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0676 2022/11/28 17:59:12 - mmengine - INFO - Saving checkpoint at 16 epochs 2022/11/28 17:59:16 - mmengine - INFO - Epoch(val) [16][100/398] eta: 0:00:10 time: 0.0338 data_time: 0.0203 memory: 364 2022/11/28 17:59:19 - mmengine - INFO - Epoch(val) [16][200/398] eta: 0:00:06 time: 0.0263 data_time: 0.0132 memory: 364 2022/11/28 17:59:22 - mmengine - INFO - Epoch(val) [16][300/398] eta: 0:00:02 time: 0.0250 data_time: 0.0130 memory: 364 2022/11/28 17:59:25 - mmengine - INFO - Epoch(val) [16][398/398] acc/top1: 0.7940 acc/top5: 0.9490 acc/mean1: 0.8061