2022/11/28 19:15:46 - 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: 639147681 GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/petrelfs/share/cuda-11.3 NVCC: Cuda compilation tools, release 11.3, V11.3.109 GCC: gcc (GCC) 5.4.0 PyTorch: 1.11.0 PyTorch compiling details: PyTorch built with: - GCC 7.3 - C++ Version: 201402 - Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.3 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_37,code=compute_37 - CuDNN 8.2 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, TorchVision: 0.12.0 OpenCV: 4.6.0 MMEngine: 0.3.1 Runtime environment: cudnn_benchmark: False mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: None diff_rank_seed: False deterministic: False Distributed launcher: pytorch Distributed training: True GPU number: 8 ------------------------------------------------------------ 2022/11/28 19:15:46 - mmengine - INFO - Config: default_scope = 'mmaction' default_hooks = dict( runtime_info=dict(type='RuntimeInfoHook'), timer=dict(type='IterTimerHook'), logger=dict(type='LoggerHook', interval=100, ignore_last=False), param_scheduler=dict(type='ParamSchedulerHook'), checkpoint=dict(type='CheckpointHook', interval=1, save_best='auto'), sampler_seed=dict(type='DistSamplerSeedHook'), sync_buffers=dict(type='SyncBuffersHook')) env_cfg = dict( cudnn_benchmark=False, mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), dist_cfg=dict(backend='nccl')) log_processor = dict(type='LogProcessor', window_size=20, by_epoch=True) vis_backends = [dict(type='LocalVisBackend')] visualizer = dict( type='ActionVisualizer', vis_backends=[dict(type='LocalVisBackend')]) log_level = 'INFO' load_from = None resume = False model = dict( type='RecognizerGCN', backbone=dict( type='STGCN', graph_cfg=dict(layout='coco', mode='stgcn_spatial')), cls_head=dict(type='GCNHead', num_classes=120, in_channels=256)) dataset_type = 'PoseDataset' ann_file = 'data/skeleton/ntu120_2d.pkl' train_pipeline = [ dict(type='PreNormalize2D'), dict(type='GenSkeFeat', dataset='coco', feats=['jm']), dict(type='UniformSampleFrames', clip_len=100), dict(type='PoseDecode'), dict(type='FormatGCNInput', num_person=2), dict(type='PackActionInputs') ] val_pipeline = [ dict(type='PreNormalize2D'), dict(type='GenSkeFeat', dataset='coco', feats=['jm']), dict( type='UniformSampleFrames', clip_len=100, num_clips=1, test_mode=True), dict(type='PoseDecode'), dict(type='FormatGCNInput', num_person=2), dict(type='PackActionInputs') ] test_pipeline = [ dict(type='PreNormalize2D'), dict(type='GenSkeFeat', dataset='coco', feats=['jm']), dict( type='UniformSampleFrames', clip_len=100, num_clips=10, test_mode=True), dict(type='PoseDecode'), dict(type='FormatGCNInput', num_person=2), dict(type='PackActionInputs') ] train_dataloader = dict( batch_size=16, num_workers=2, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='RepeatDataset', times=5, dataset=dict( type='PoseDataset', ann_file='data/skeleton/ntu120_2d.pkl', pipeline=[ dict(type='PreNormalize2D'), dict(type='GenSkeFeat', dataset='coco', feats=['jm']), dict(type='UniformSampleFrames', clip_len=100), dict(type='PoseDecode'), dict(type='FormatGCNInput', num_person=2), dict(type='PackActionInputs') ], split='xsub_train'))) val_dataloader = dict( batch_size=16, num_workers=2, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='PoseDataset', ann_file='data/skeleton/ntu120_2d.pkl', pipeline=[ dict(type='PreNormalize2D'), dict(type='GenSkeFeat', dataset='coco', feats=['jm']), dict( type='UniformSampleFrames', clip_len=100, num_clips=1, test_mode=True), dict(type='PoseDecode'), dict(type='FormatGCNInput', num_person=2), dict(type='PackActionInputs') ], split='xsub_val', test_mode=True)) test_dataloader = dict( batch_size=1, num_workers=2, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='PoseDataset', ann_file='data/skeleton/ntu120_2d.pkl', pipeline=[ dict(type='PreNormalize2D'), dict(type='GenSkeFeat', dataset='coco', feats=['jm']), 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-joint-motion-u100-80e_ntu120-xsub-keypoint-2d' randomness = dict(seed=None, diff_rank_seed=False, deterministic=False) 2022/11/28 19:15:46 - mmengine - INFO - Result has been saved to /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d/modules_statistic_results.json Name of parameter - Initialization information data_bn.weight - torch.Size([51]): The value is the same before and after calling `init_weights` of STGCN data_bn.bias - torch.Size([51]): The value is the same before and after calling `init_weights` of STGCN gcn.0.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.0.gcn.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.0.gcn.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.0.gcn.conv.weight - torch.Size([192, 3, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.0.gcn.conv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of STGCN gcn.0.tcn.conv.weight - torch.Size([64, 64, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.0.tcn.conv.bias - torch.Size([64]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.0.tcn.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.0.tcn.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.1.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.1.gcn.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.1.gcn.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.1.gcn.conv.weight - torch.Size([192, 64, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.1.gcn.conv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of STGCN gcn.1.tcn.conv.weight - torch.Size([64, 64, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.1.tcn.conv.bias - torch.Size([64]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.1.tcn.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.1.tcn.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.2.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.2.gcn.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.2.gcn.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.2.gcn.conv.weight - torch.Size([192, 64, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.2.gcn.conv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of STGCN gcn.2.tcn.conv.weight - torch.Size([64, 64, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.2.tcn.conv.bias - torch.Size([64]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.2.tcn.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.2.tcn.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.3.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.3.gcn.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.3.gcn.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.3.gcn.conv.weight - torch.Size([192, 64, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.3.gcn.conv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of STGCN gcn.3.tcn.conv.weight - torch.Size([64, 64, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.3.tcn.conv.bias - torch.Size([64]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.3.tcn.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.3.tcn.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of STGCN gcn.4.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.4.gcn.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.4.gcn.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.4.gcn.conv.weight - torch.Size([384, 64, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.4.gcn.conv.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of STGCN gcn.4.tcn.conv.weight - torch.Size([128, 128, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.4.tcn.conv.bias - torch.Size([128]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.4.tcn.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.4.tcn.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.4.residual.conv.weight - torch.Size([128, 64, 1, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.4.residual.conv.bias - torch.Size([128]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.4.residual.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.4.residual.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.5.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.5.gcn.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.5.gcn.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.5.gcn.conv.weight - torch.Size([384, 128, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.5.gcn.conv.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of STGCN gcn.5.tcn.conv.weight - torch.Size([128, 128, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.5.tcn.conv.bias - torch.Size([128]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.5.tcn.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.5.tcn.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.6.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.6.gcn.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.6.gcn.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.6.gcn.conv.weight - torch.Size([384, 128, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.6.gcn.conv.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of STGCN gcn.6.tcn.conv.weight - torch.Size([128, 128, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.6.tcn.conv.bias - torch.Size([128]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.6.tcn.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.6.tcn.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of STGCN gcn.7.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.7.gcn.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.7.gcn.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.7.gcn.conv.weight - torch.Size([768, 128, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.7.gcn.conv.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of STGCN gcn.7.tcn.conv.weight - torch.Size([256, 256, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.7.tcn.conv.bias - torch.Size([256]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.7.tcn.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.7.tcn.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.7.residual.conv.weight - torch.Size([256, 128, 1, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.7.residual.conv.bias - torch.Size([256]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.7.residual.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.7.residual.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.8.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.8.gcn.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.8.gcn.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.8.gcn.conv.weight - torch.Size([768, 256, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.8.gcn.conv.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of STGCN gcn.8.tcn.conv.weight - torch.Size([256, 256, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.8.tcn.conv.bias - torch.Size([256]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.8.tcn.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.8.tcn.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.9.gcn.PA - torch.Size([3, 17, 17]): The value is the same before and after calling `init_weights` of STGCN gcn.9.gcn.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.9.gcn.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.9.gcn.conv.weight - torch.Size([768, 256, 1, 1]): The value is the same before and after calling `init_weights` of STGCN gcn.9.gcn.conv.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of STGCN gcn.9.tcn.conv.weight - torch.Size([256, 256, 9, 1]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.9.tcn.conv.bias - torch.Size([256]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 gcn.9.tcn.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN gcn.9.tcn.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of STGCN Name of parameter - Initialization information fc.weight - torch.Size([120, 256]): NormalInit: mean=0, std=0.01, bias=0 fc.bias - torch.Size([120]): NormalInit: mean=0, std=0.01, bias=0 2022/11/28 19:17:29 - mmengine - INFO - Checkpoints will be saved to /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d. 2022/11/28 19:17:36 - mmengine - INFO - Epoch(train) [1][100/2462] lr: 9.9998e-02 eta: 0:41:51 time: 0.0334 data_time: 0.0058 memory: 1253 loss: 4.0260 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.0260 2022/11/28 19:17:39 - mmengine - INFO - Epoch(train) [1][200/2462] lr: 9.9994e-02 eta: 0:31:57 time: 0.0348 data_time: 0.0067 memory: 1253 loss: 3.2958 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.2958 2022/11/28 19:17:43 - mmengine - INFO - Epoch(train) [1][300/2462] lr: 9.9986e-02 eta: 0:28:35 time: 0.0333 data_time: 0.0060 memory: 1253 loss: 2.6182 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6182 2022/11/28 19:17:46 - mmengine - INFO - Epoch(train) [1][400/2462] lr: 9.9975e-02 eta: 0:26:52 time: 0.0335 data_time: 0.0059 memory: 1253 loss: 2.2377 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.2377 2022/11/28 19:17:49 - mmengine - INFO - Epoch(train) [1][500/2462] lr: 9.9960e-02 eta: 0:25:54 time: 0.0355 data_time: 0.0059 memory: 1253 loss: 1.8350 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.8350 2022/11/28 19:17:53 - mmengine - INFO - Epoch(train) [1][600/2462] lr: 9.9943e-02 eta: 0:25:09 time: 0.0339 data_time: 0.0059 memory: 1253 loss: 1.7386 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7386 2022/11/28 19:17:56 - mmengine - INFO - Epoch(train) [1][700/2462] lr: 9.9922e-02 eta: 0:24:39 time: 0.0338 data_time: 0.0059 memory: 1253 loss: 1.7982 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.7982 2022/11/28 19:18:00 - mmengine - INFO - Epoch(train) [1][800/2462] lr: 9.9899e-02 eta: 0:24:14 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 1.5723 top1_acc: 0.5625 top5_acc: 1.0000 loss_cls: 1.5723 2022/11/28 19:18:03 - mmengine - INFO - Epoch(train) [1][900/2462] lr: 9.9872e-02 eta: 0:23:56 time: 0.0350 data_time: 0.0059 memory: 1253 loss: 1.4920 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4920 2022/11/28 19:18:06 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:18:06 - mmengine - INFO - Epoch(train) [1][1000/2462] lr: 9.9841e-02 eta: 0:23:39 time: 0.0333 data_time: 0.0058 memory: 1253 loss: 1.3820 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3820 2022/11/28 19:18:10 - mmengine - INFO - Epoch(train) [1][1100/2462] lr: 9.9808e-02 eta: 0:23:26 time: 0.0353 data_time: 0.0065 memory: 1253 loss: 1.3641 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3641 2022/11/28 19:18:13 - mmengine - INFO - Epoch(train) [1][1200/2462] lr: 9.9772e-02 eta: 0:23:14 time: 0.0340 data_time: 0.0058 memory: 1253 loss: 1.3042 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.3042 2022/11/28 19:18:17 - mmengine - INFO - Epoch(train) [1][1300/2462] lr: 9.9732e-02 eta: 0:23:02 time: 0.0335 data_time: 0.0059 memory: 1253 loss: 1.2897 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.2897 2022/11/28 19:18:20 - mmengine - INFO - Epoch(train) [1][1400/2462] lr: 9.9689e-02 eta: 0:22:51 time: 0.0346 data_time: 0.0059 memory: 1253 loss: 1.1973 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1973 2022/11/28 19:18:23 - mmengine - INFO - Epoch(train) [1][1500/2462] lr: 9.9643e-02 eta: 0:22:44 time: 0.0332 data_time: 0.0059 memory: 1253 loss: 1.3514 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3514 2022/11/28 19:18:27 - mmengine - INFO - Epoch(train) [1][1600/2462] lr: 9.9594e-02 eta: 0:22:37 time: 0.0353 data_time: 0.0059 memory: 1253 loss: 1.0530 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.0530 2022/11/28 19:18:30 - mmengine - INFO - Epoch(train) [1][1700/2462] lr: 9.9542e-02 eta: 0:22:29 time: 0.0339 data_time: 0.0058 memory: 1253 loss: 1.1981 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1981 2022/11/28 19:18:34 - mmengine - INFO - Epoch(train) [1][1800/2462] lr: 9.9486e-02 eta: 0:22:22 time: 0.0350 data_time: 0.0059 memory: 1253 loss: 1.0620 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.0620 2022/11/28 19:18:37 - mmengine - INFO - Epoch(train) [1][1900/2462] lr: 9.9428e-02 eta: 0:22:14 time: 0.0333 data_time: 0.0057 memory: 1253 loss: 1.2528 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2528 2022/11/28 19:18:40 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:18:40 - mmengine - INFO - Epoch(train) [1][2000/2462] lr: 9.9366e-02 eta: 0:22:08 time: 0.0335 data_time: 0.0058 memory: 1253 loss: 1.1809 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1809 2022/11/28 19:18:44 - mmengine - INFO - Epoch(train) [1][2100/2462] lr: 9.9301e-02 eta: 0:22:03 time: 0.0344 data_time: 0.0059 memory: 1253 loss: 1.0672 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.0672 2022/11/28 19:18:47 - mmengine - INFO - Epoch(train) [1][2200/2462] lr: 9.9233e-02 eta: 0:21:57 time: 0.0336 data_time: 0.0058 memory: 1253 loss: 1.1369 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1369 2022/11/28 19:18:51 - mmengine - INFO - Epoch(train) [1][2300/2462] lr: 9.9162e-02 eta: 0:21:51 time: 0.0335 data_time: 0.0062 memory: 1253 loss: 1.0013 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.0013 2022/11/28 19:18:54 - mmengine - INFO - Epoch(train) [1][2400/2462] lr: 9.9088e-02 eta: 0:21:46 time: 0.0349 data_time: 0.0060 memory: 1253 loss: 1.1227 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.1227 2022/11/28 19:18:56 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:18:56 - mmengine - INFO - Epoch(train) [1][2462/2462] lr: 9.9040e-02 eta: 0:21:42 time: 0.0338 data_time: 0.0060 memory: 1253 loss: 1.0072 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0072 2022/11/28 19:18:56 - mmengine - INFO - Saving checkpoint at 1 epochs 2022/11/28 19:18:59 - mmengine - INFO - Epoch(val) [1][100/398] eta: 0:00:05 time: 0.0153 data_time: 0.0058 memory: 262 2022/11/28 19:19:00 - mmengine - INFO - Epoch(val) [1][200/398] eta: 0:00:03 time: 0.0148 data_time: 0.0057 memory: 262 2022/11/28 19:19:02 - mmengine - INFO - Epoch(val) [1][300/398] eta: 0:00:01 time: 0.0153 data_time: 0.0059 memory: 262 2022/11/28 19:19:04 - mmengine - INFO - Epoch(val) [1][398/398] acc/top1: 0.4880 acc/top5: 0.7933 acc/mean1: 0.5143 2022/11/28 19:19:04 - mmengine - INFO - The best checkpoint with 0.4880 acc/top1 at 1 epoch is saved to best_acc/top1_epoch_1.pth. 2022/11/28 19:19:08 - mmengine - INFO - Epoch(train) [2][100/2462] lr: 9.8961e-02 eta: 0:21:37 time: 0.0335 data_time: 0.0058 memory: 1253 loss: 1.0308 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.0308 2022/11/28 19:19:11 - mmengine - INFO - Epoch(train) [2][200/2462] lr: 9.8878e-02 eta: 0:21:32 time: 0.0336 data_time: 0.0060 memory: 1253 loss: 0.9884 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9884 2022/11/28 19:19:15 - mmengine - INFO - Epoch(train) [2][300/2462] lr: 9.8793e-02 eta: 0:21:27 time: 0.0338 data_time: 0.0059 memory: 1253 loss: 1.0287 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.0287 2022/11/28 19:19:18 - mmengine - INFO - Epoch(train) [2][400/2462] lr: 9.8704e-02 eta: 0:21:22 time: 0.0336 data_time: 0.0058 memory: 1253 loss: 1.0318 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0318 2022/11/28 19:19:21 - mmengine - INFO - Epoch(train) [2][500/2462] lr: 9.8612e-02 eta: 0:21:17 time: 0.0336 data_time: 0.0059 memory: 1253 loss: 0.8904 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.8904 2022/11/28 19:19:23 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:19:25 - mmengine - INFO - Epoch(train) [2][600/2462] lr: 9.8518e-02 eta: 0:21:13 time: 0.0340 data_time: 0.0061 memory: 1253 loss: 1.0594 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0594 2022/11/28 19:19:28 - mmengine - INFO - Epoch(train) [2][700/2462] lr: 9.8420e-02 eta: 0:21:08 time: 0.0334 data_time: 0.0059 memory: 1253 loss: 0.9031 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.9031 2022/11/28 19:19:32 - mmengine - INFO - Epoch(train) [2][800/2462] lr: 9.8319e-02 eta: 0:21:03 time: 0.0340 data_time: 0.0060 memory: 1253 loss: 0.8783 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.8783 2022/11/28 19:19:35 - mmengine - INFO - Epoch(train) [2][900/2462] lr: 9.8215e-02 eta: 0:20:59 time: 0.0345 data_time: 0.0060 memory: 1253 loss: 0.7920 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7920 2022/11/28 19:19:38 - mmengine - INFO - Epoch(train) [2][1000/2462] lr: 9.8107e-02 eta: 0:20:54 time: 0.0335 data_time: 0.0058 memory: 1253 loss: 0.7946 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7946 2022/11/28 19:19:42 - mmengine - INFO - Epoch(train) [2][1100/2462] lr: 9.7997e-02 eta: 0:20:51 time: 0.0360 data_time: 0.0073 memory: 1253 loss: 0.9057 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9057 2022/11/28 19:19:45 - mmengine - INFO - Epoch(train) [2][1200/2462] lr: 9.7884e-02 eta: 0:20:47 time: 0.0334 data_time: 0.0060 memory: 1253 loss: 0.8213 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 0.8213 2022/11/28 19:19:49 - mmengine - INFO - Epoch(train) [2][1300/2462] lr: 9.7768e-02 eta: 0:20:43 time: 0.0331 data_time: 0.0058 memory: 1253 loss: 0.8617 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 0.8617 2022/11/28 19:19:52 - mmengine - INFO - Epoch(train) [2][1400/2462] lr: 9.7648e-02 eta: 0:20:38 time: 0.0332 data_time: 0.0060 memory: 1253 loss: 0.8576 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.8576 2022/11/28 19:19:56 - mmengine - INFO - Epoch(train) [2][1500/2462] lr: 9.7526e-02 eta: 0:20:34 time: 0.0333 data_time: 0.0059 memory: 1253 loss: 0.8366 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.8366 2022/11/28 19:19:57 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:19:59 - mmengine - INFO - Epoch(train) [2][1600/2462] lr: 9.7400e-02 eta: 0:20:29 time: 0.0332 data_time: 0.0059 memory: 1253 loss: 0.7692 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7692 2022/11/28 19:20:02 - mmengine - INFO - Epoch(train) [2][1700/2462] lr: 9.7272e-02 eta: 0:20:25 time: 0.0342 data_time: 0.0061 memory: 1253 loss: 0.7607 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7607 2022/11/28 19:20:06 - mmengine - INFO - Epoch(train) [2][1800/2462] lr: 9.7141e-02 eta: 0:20:20 time: 0.0334 data_time: 0.0058 memory: 1253 loss: 0.8796 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.8796 2022/11/28 19:20:09 - mmengine - INFO - Epoch(train) [2][1900/2462] lr: 9.7006e-02 eta: 0:20:16 time: 0.0339 data_time: 0.0060 memory: 1253 loss: 0.8472 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8472 2022/11/28 19:20:13 - mmengine - INFO - Epoch(train) [2][2000/2462] lr: 9.6869e-02 eta: 0:20:13 time: 0.0342 data_time: 0.0064 memory: 1253 loss: 0.7984 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7984 2022/11/28 19:20:16 - mmengine - INFO - Epoch(train) [2][2100/2462] lr: 9.6728e-02 eta: 0:20:09 time: 0.0341 data_time: 0.0063 memory: 1253 loss: 0.8887 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 0.8887 2022/11/28 19:20:19 - mmengine - INFO - Epoch(train) [2][2200/2462] lr: 9.6585e-02 eta: 0:20:04 time: 0.0332 data_time: 0.0058 memory: 1253 loss: 0.7140 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7140 2022/11/28 19:20:23 - mmengine - INFO - Epoch(train) [2][2300/2462] lr: 9.6439e-02 eta: 0:20:00 time: 0.0334 data_time: 0.0059 memory: 1253 loss: 0.7227 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7227 2022/11/28 19:20:26 - mmengine - INFO - Epoch(train) [2][2400/2462] lr: 9.6290e-02 eta: 0:19:56 time: 0.0332 data_time: 0.0059 memory: 1253 loss: 0.7758 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.7758 2022/11/28 19:20:28 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:20:28 - mmengine - INFO - Epoch(train) [2][2462/2462] lr: 9.6196e-02 eta: 0:19:53 time: 0.0340 data_time: 0.0060 memory: 1253 loss: 0.8019 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.8019 2022/11/28 19:20:28 - mmengine - INFO - Saving checkpoint at 2 epochs 2022/11/28 19:20:30 - mmengine - INFO - Epoch(val) [2][100/398] eta: 0:00:04 time: 0.0150 data_time: 0.0058 memory: 262 2022/11/28 19:20:32 - mmengine - INFO - Epoch(val) [2][200/398] eta: 0:00:03 time: 0.0170 data_time: 0.0067 memory: 262 2022/11/28 19:20:33 - mmengine - INFO - Epoch(val) [2][300/398] eta: 0:00:01 time: 0.0149 data_time: 0.0057 memory: 262 2022/11/28 19:20:36 - mmengine - INFO - Epoch(val) [2][398/398] acc/top1: 0.5510 acc/top5: 0.8343 acc/mean1: 0.5760 2022/11/28 19:20:36 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_1.pth is removed 2022/11/28 19:20:36 - mmengine - INFO - The best checkpoint with 0.5510 acc/top1 at 2 epoch is saved to best_acc/top1_epoch_2.pth. 2022/11/28 19:20:39 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:20:39 - mmengine - INFO - Epoch(train) [3][100/2462] lr: 9.6041e-02 eta: 0:19:50 time: 0.0337 data_time: 0.0059 memory: 1253 loss: 0.7852 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7852 2022/11/28 19:20:43 - mmengine - INFO - Epoch(train) [3][200/2462] lr: 9.5884e-02 eta: 0:19:46 time: 0.0336 data_time: 0.0062 memory: 1253 loss: 0.8435 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8435 2022/11/28 19:20:46 - mmengine - INFO - Epoch(train) [3][300/2462] lr: 9.5725e-02 eta: 0:19:43 time: 0.0334 data_time: 0.0063 memory: 1253 loss: 0.8494 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 0.8494 2022/11/28 19:20:50 - mmengine - INFO - Epoch(train) [3][400/2462] lr: 9.5562e-02 eta: 0:19:40 time: 0.0352 data_time: 0.0062 memory: 1253 loss: 0.8882 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.8882 2022/11/28 19:20:53 - mmengine - INFO - Epoch(train) [3][500/2462] lr: 9.5396e-02 eta: 0:19:36 time: 0.0334 data_time: 0.0062 memory: 1253 loss: 0.7318 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7318 2022/11/28 19:20:57 - mmengine - INFO - Epoch(train) [3][600/2462] lr: 9.5228e-02 eta: 0:19:32 time: 0.0336 data_time: 0.0061 memory: 1253 loss: 0.7980 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7980 2022/11/28 19:21:00 - mmengine - INFO - Epoch(train) [3][700/2462] lr: 9.5056e-02 eta: 0:19:28 time: 0.0340 data_time: 0.0059 memory: 1253 loss: 0.7770 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7770 2022/11/28 19:21:03 - mmengine - INFO - Epoch(train) [3][800/2462] lr: 9.4882e-02 eta: 0:19:25 time: 0.0346 data_time: 0.0060 memory: 1253 loss: 0.7453 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7453 2022/11/28 19:21:07 - mmengine - INFO - Epoch(train) [3][900/2462] lr: 9.4705e-02 eta: 0:19:21 time: 0.0333 data_time: 0.0060 memory: 1253 loss: 0.6604 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6604 2022/11/28 19:21:10 - mmengine - INFO - Epoch(train) [3][1000/2462] lr: 9.4525e-02 eta: 0:19:17 time: 0.0341 data_time: 0.0059 memory: 1253 loss: 0.7523 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7523 2022/11/28 19:21:13 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:21:14 - mmengine - INFO - Epoch(train) [3][1100/2462] lr: 9.4342e-02 eta: 0:19:14 time: 0.0348 data_time: 0.0059 memory: 1253 loss: 0.7098 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7098 2022/11/28 19:21:17 - mmengine - INFO - Epoch(train) [3][1200/2462] lr: 9.4156e-02 eta: 0:19:10 time: 0.0340 data_time: 0.0060 memory: 1253 loss: 0.7475 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7475 2022/11/28 19:21:21 - mmengine - INFO - Epoch(train) [3][1300/2462] lr: 9.3968e-02 eta: 0:19:08 time: 0.0361 data_time: 0.0060 memory: 1253 loss: 0.7080 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7080 2022/11/28 19:21:24 - mmengine - INFO - Epoch(train) [3][1400/2462] lr: 9.3776e-02 eta: 0:19:04 time: 0.0340 data_time: 0.0061 memory: 1253 loss: 0.7867 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7867 2022/11/28 19:21:28 - mmengine - INFO - Epoch(train) [3][1500/2462] lr: 9.3582e-02 eta: 0:19:00 time: 0.0338 data_time: 0.0059 memory: 1253 loss: 0.7610 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 0.7610 2022/11/28 19:21:31 - mmengine - INFO - Epoch(train) [3][1600/2462] lr: 9.3385e-02 eta: 0:18:56 time: 0.0335 data_time: 0.0059 memory: 1253 loss: 0.7408 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7408 2022/11/28 19:21:34 - mmengine - INFO - Epoch(train) [3][1700/2462] lr: 9.3186e-02 eta: 0:18:53 time: 0.0348 data_time: 0.0060 memory: 1253 loss: 0.7684 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7684 2022/11/28 19:21:38 - mmengine - INFO - Epoch(train) [3][1800/2462] lr: 9.2983e-02 eta: 0:18:50 time: 0.0347 data_time: 0.0059 memory: 1253 loss: 0.7213 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7213 2022/11/28 19:21:41 - mmengine - INFO - Epoch(train) [3][1900/2462] lr: 9.2778e-02 eta: 0:18:46 time: 0.0336 data_time: 0.0059 memory: 1253 loss: 0.7139 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7139 2022/11/28 19:21:45 - mmengine - INFO - Epoch(train) [3][2000/2462] lr: 9.2571e-02 eta: 0:18:42 time: 0.0346 data_time: 0.0060 memory: 1253 loss: 0.7281 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7281 2022/11/28 19:21:47 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:21:48 - mmengine - INFO - Epoch(train) [3][2100/2462] lr: 9.2360e-02 eta: 0:18:39 time: 0.0360 data_time: 0.0059 memory: 1253 loss: 0.8441 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.8441 2022/11/28 19:21:52 - mmengine - INFO - Epoch(train) [3][2200/2462] lr: 9.2147e-02 eta: 0:18:36 time: 0.0334 data_time: 0.0060 memory: 1253 loss: 0.6773 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.6773 2022/11/28 19:21:55 - mmengine - INFO - Epoch(train) [3][2300/2462] lr: 9.1931e-02 eta: 0:18:32 time: 0.0344 data_time: 0.0059 memory: 1253 loss: 0.6849 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6849 2022/11/28 19:21:59 - mmengine - INFO - Epoch(train) [3][2400/2462] lr: 9.1713e-02 eta: 0:18:29 time: 0.0343 data_time: 0.0059 memory: 1253 loss: 0.6872 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6872 2022/11/28 19:22:01 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:22:01 - mmengine - INFO - Epoch(train) [3][2462/2462] lr: 9.1576e-02 eta: 0:18:26 time: 0.0340 data_time: 0.0060 memory: 1253 loss: 0.6162 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6162 2022/11/28 19:22:01 - mmengine - INFO - Saving checkpoint at 3 epochs 2022/11/28 19:22:03 - mmengine - INFO - Epoch(val) [3][100/398] eta: 0:00:04 time: 0.0149 data_time: 0.0056 memory: 262 2022/11/28 19:22:04 - mmengine - INFO - Epoch(val) [3][200/398] eta: 0:00:03 time: 0.0148 data_time: 0.0057 memory: 262 2022/11/28 19:22:06 - mmengine - INFO - Epoch(val) [3][300/398] eta: 0:00:01 time: 0.0153 data_time: 0.0059 memory: 262 2022/11/28 19:22:08 - mmengine - INFO - Epoch(val) [3][398/398] acc/top1: 0.5616 acc/top5: 0.8445 acc/mean1: 0.5976 2022/11/28 19:22:08 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_2.pth is removed 2022/11/28 19:22:08 - mmengine - INFO - The best checkpoint with 0.5616 acc/top1 at 3 epoch is saved to best_acc/top1_epoch_3.pth. 2022/11/28 19:22:12 - mmengine - INFO - Epoch(train) [4][100/2462] lr: 9.1353e-02 eta: 0:18:23 time: 0.0337 data_time: 0.0061 memory: 1253 loss: 0.7111 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.7111 2022/11/28 19:22:15 - mmengine - INFO - Epoch(train) [4][200/2462] lr: 9.1127e-02 eta: 0:18:19 time: 0.0341 data_time: 0.0063 memory: 1253 loss: 0.6202 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6202 2022/11/28 19:22:19 - mmengine - INFO - Epoch(train) [4][300/2462] lr: 9.0899e-02 eta: 0:18:16 time: 0.0335 data_time: 0.0061 memory: 1253 loss: 0.5683 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5683 2022/11/28 19:22:22 - mmengine - INFO - Epoch(train) [4][400/2462] lr: 9.0669e-02 eta: 0:18:12 time: 0.0336 data_time: 0.0061 memory: 1253 loss: 0.6604 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6604 2022/11/28 19:22:26 - mmengine - INFO - Epoch(train) [4][500/2462] lr: 9.0435e-02 eta: 0:18:09 time: 0.0345 data_time: 0.0061 memory: 1253 loss: 0.7375 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7375 2022/11/28 19:22:29 - mmengine - INFO - Epoch(train) [4][600/2462] lr: 9.0200e-02 eta: 0:18:05 time: 0.0345 data_time: 0.0061 memory: 1253 loss: 0.7055 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7055 2022/11/28 19:22:30 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:22:33 - mmengine - INFO - Epoch(train) [4][700/2462] lr: 8.9961e-02 eta: 0:18:02 time: 0.0339 data_time: 0.0064 memory: 1253 loss: 0.6424 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.6424 2022/11/28 19:22:36 - mmengine - INFO - Epoch(train) [4][800/2462] lr: 8.9720e-02 eta: 0:17:58 time: 0.0348 data_time: 0.0061 memory: 1253 loss: 0.7267 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.7267 2022/11/28 19:22:39 - mmengine - INFO - Epoch(train) [4][900/2462] lr: 8.9477e-02 eta: 0:17:55 time: 0.0357 data_time: 0.0064 memory: 1253 loss: 0.7729 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.7729 2022/11/28 19:22:43 - mmengine - INFO - Epoch(train) [4][1000/2462] lr: 8.9231e-02 eta: 0:17:51 time: 0.0337 data_time: 0.0061 memory: 1253 loss: 0.6383 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.6383 2022/11/28 19:22:46 - mmengine - INFO - Epoch(train) [4][1100/2462] lr: 8.8982e-02 eta: 0:17:48 time: 0.0351 data_time: 0.0061 memory: 1253 loss: 0.7445 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7445 2022/11/28 19:22:50 - mmengine - INFO - Epoch(train) [4][1200/2462] lr: 8.8731e-02 eta: 0:17:44 time: 0.0334 data_time: 0.0061 memory: 1253 loss: 0.7370 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.7370 2022/11/28 19:22:53 - mmengine - INFO - Epoch(train) [4][1300/2462] lr: 8.8478e-02 eta: 0:17:40 time: 0.0333 data_time: 0.0060 memory: 1253 loss: 0.6650 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.6650 2022/11/28 19:22:57 - mmengine - INFO - Epoch(train) [4][1400/2462] lr: 8.8222e-02 eta: 0:17:38 time: 0.0360 data_time: 0.0060 memory: 1253 loss: 0.7611 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 0.7611 2022/11/28 19:23:00 - mmengine - INFO - Epoch(train) [4][1500/2462] lr: 8.7964e-02 eta: 0:17:34 time: 0.0351 data_time: 0.0060 memory: 1253 loss: 0.6076 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 0.6076 2022/11/28 19:23:04 - mmengine - INFO - Epoch(train) [4][1600/2462] lr: 8.7703e-02 eta: 0:17:31 time: 0.0334 data_time: 0.0060 memory: 1253 loss: 0.7012 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7012 2022/11/28 19:23:04 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:23:07 - mmengine - INFO - Epoch(train) [4][1700/2462] lr: 8.7440e-02 eta: 0:17:27 time: 0.0333 data_time: 0.0061 memory: 1253 loss: 0.8155 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.8155 2022/11/28 19:23:10 - mmengine - INFO - Epoch(train) [4][1800/2462] lr: 8.7174e-02 eta: 0:17:23 time: 0.0338 data_time: 0.0061 memory: 1253 loss: 0.6539 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6539 2022/11/28 19:23:14 - mmengine - INFO - Epoch(train) [4][1900/2462] lr: 8.6907e-02 eta: 0:17:19 time: 0.0338 data_time: 0.0060 memory: 1253 loss: 0.6149 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.6149 2022/11/28 19:23:17 - mmengine - INFO - Epoch(train) [4][2000/2462] lr: 8.6636e-02 eta: 0:17:16 time: 0.0335 data_time: 0.0062 memory: 1253 loss: 0.7224 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7224 2022/11/28 19:23:21 - mmengine - INFO - Epoch(train) [4][2100/2462] lr: 8.6364e-02 eta: 0:17:12 time: 0.0334 data_time: 0.0061 memory: 1253 loss: 0.6710 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6710 2022/11/28 19:23:24 - mmengine - INFO - Epoch(train) [4][2200/2462] lr: 8.6089e-02 eta: 0:17:08 time: 0.0344 data_time: 0.0062 memory: 1253 loss: 0.5958 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5958 2022/11/28 19:23:27 - mmengine - INFO - Epoch(train) [4][2300/2462] lr: 8.5812e-02 eta: 0:17:05 time: 0.0350 data_time: 0.0060 memory: 1253 loss: 0.7119 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7119 2022/11/28 19:23:31 - mmengine - INFO - Epoch(train) [4][2400/2462] lr: 8.5533e-02 eta: 0:17:02 time: 0.0362 data_time: 0.0064 memory: 1253 loss: 0.7937 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7937 2022/11/28 19:23:33 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:23:33 - mmengine - INFO - Epoch(train) [4][2462/2462] lr: 8.5358e-02 eta: 0:17:00 time: 0.0340 data_time: 0.0063 memory: 1253 loss: 0.5703 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5703 2022/11/28 19:23:33 - mmengine - INFO - Saving checkpoint at 4 epochs 2022/11/28 19:23:35 - mmengine - INFO - Epoch(val) [4][100/398] eta: 0:00:04 time: 0.0149 data_time: 0.0057 memory: 262 2022/11/28 19:23:37 - mmengine - INFO - Epoch(val) [4][200/398] eta: 0:00:03 time: 0.0149 data_time: 0.0058 memory: 262 2022/11/28 19:23:38 - mmengine - INFO - Epoch(val) [4][300/398] eta: 0:00:01 time: 0.0152 data_time: 0.0059 memory: 262 2022/11/28 19:23:41 - mmengine - INFO - Epoch(val) [4][398/398] acc/top1: 0.6553 acc/top5: 0.9100 acc/mean1: 0.6805 2022/11/28 19:23:41 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_3.pth is removed 2022/11/28 19:23:41 - mmengine - INFO - The best checkpoint with 0.6553 acc/top1 at 4 epoch is saved to best_acc/top1_epoch_4.pth. 2022/11/28 19:23:44 - mmengine - INFO - Epoch(train) [5][100/2462] lr: 8.5075e-02 eta: 0:16:56 time: 0.0336 data_time: 0.0061 memory: 1253 loss: 0.5817 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5817 2022/11/28 19:23:46 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:23:48 - mmengine - INFO - Epoch(train) [5][200/2462] lr: 8.4790e-02 eta: 0:16:53 time: 0.0338 data_time: 0.0061 memory: 1253 loss: 0.6493 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 0.6493 2022/11/28 19:23:51 - mmengine - INFO - Epoch(train) [5][300/2462] lr: 8.4502e-02 eta: 0:16:49 time: 0.0342 data_time: 0.0061 memory: 1253 loss: 0.6771 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6771 2022/11/28 19:23:55 - mmengine - INFO - Epoch(train) [5][400/2462] lr: 8.4213e-02 eta: 0:16:46 time: 0.0344 data_time: 0.0069 memory: 1253 loss: 0.6539 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.6539 2022/11/28 19:23:58 - mmengine - INFO - Epoch(train) [5][500/2462] lr: 8.3921e-02 eta: 0:16:42 time: 0.0337 data_time: 0.0062 memory: 1253 loss: 0.5270 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.5270 2022/11/28 19:24:01 - mmengine - INFO - Epoch(train) [5][600/2462] lr: 8.3627e-02 eta: 0:16:38 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.8124 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 0.8124 2022/11/28 19:24:05 - mmengine - INFO - Epoch(train) [5][700/2462] lr: 8.3330e-02 eta: 0:16:35 time: 0.0349 data_time: 0.0060 memory: 1253 loss: 0.6817 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.6817 2022/11/28 19:24:08 - mmengine - INFO - Epoch(train) [5][800/2462] lr: 8.3032e-02 eta: 0:16:32 time: 0.0344 data_time: 0.0062 memory: 1253 loss: 0.5840 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5840 2022/11/28 19:24:12 - mmengine - INFO - Epoch(train) [5][900/2462] lr: 8.2732e-02 eta: 0:16:28 time: 0.0349 data_time: 0.0062 memory: 1253 loss: 0.6180 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.6180 2022/11/28 19:24:15 - mmengine - INFO - Epoch(train) [5][1000/2462] lr: 8.2429e-02 eta: 0:16:25 time: 0.0342 data_time: 0.0060 memory: 1253 loss: 0.6495 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.6495 2022/11/28 19:24:19 - mmengine - INFO - Epoch(train) [5][1100/2462] lr: 8.2125e-02 eta: 0:16:22 time: 0.0345 data_time: 0.0062 memory: 1253 loss: 0.5264 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5264 2022/11/28 19:24:21 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:24:22 - mmengine - INFO - Epoch(train) [5][1200/2462] lr: 8.1818e-02 eta: 0:16:18 time: 0.0339 data_time: 0.0063 memory: 1253 loss: 0.6751 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6751 2022/11/28 19:24:26 - mmengine - INFO - Epoch(train) [5][1300/2462] lr: 8.1510e-02 eta: 0:16:15 time: 0.0363 data_time: 0.0063 memory: 1253 loss: 0.6355 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6355 2022/11/28 19:24:29 - mmengine - INFO - Epoch(train) [5][1400/2462] lr: 8.1199e-02 eta: 0:16:11 time: 0.0340 data_time: 0.0062 memory: 1253 loss: 0.5724 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5724 2022/11/28 19:24:33 - mmengine - INFO - Epoch(train) [5][1500/2462] lr: 8.0886e-02 eta: 0:16:08 time: 0.0353 data_time: 0.0061 memory: 1253 loss: 0.5651 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.5651 2022/11/28 19:24:36 - mmengine - INFO - Epoch(train) [5][1600/2462] lr: 8.0572e-02 eta: 0:16:05 time: 0.0354 data_time: 0.0061 memory: 1253 loss: 0.6199 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6199 2022/11/28 19:24:40 - mmengine - INFO - Epoch(train) [5][1700/2462] lr: 8.0255e-02 eta: 0:16:01 time: 0.0352 data_time: 0.0066 memory: 1253 loss: 0.4852 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.4852 2022/11/28 19:24:43 - mmengine - INFO - Epoch(train) [5][1800/2462] lr: 7.9937e-02 eta: 0:15:58 time: 0.0346 data_time: 0.0061 memory: 1253 loss: 0.7231 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.7231 2022/11/28 19:24:47 - mmengine - INFO - Epoch(train) [5][1900/2462] lr: 7.9617e-02 eta: 0:15:55 time: 0.0354 data_time: 0.0063 memory: 1253 loss: 0.6987 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6987 2022/11/28 19:24:50 - mmengine - INFO - Epoch(train) [5][2000/2462] lr: 7.9294e-02 eta: 0:15:51 time: 0.0341 data_time: 0.0062 memory: 1253 loss: 0.7479 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.7479 2022/11/28 19:24:54 - mmengine - INFO - Epoch(train) [5][2100/2462] lr: 7.8970e-02 eta: 0:15:48 time: 0.0356 data_time: 0.0063 memory: 1253 loss: 0.6606 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6606 2022/11/28 19:24:56 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:24:57 - mmengine - INFO - Epoch(train) [5][2200/2462] lr: 7.8644e-02 eta: 0:15:45 time: 0.0347 data_time: 0.0064 memory: 1253 loss: 0.6015 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.6015 2022/11/28 19:25:01 - mmengine - INFO - Epoch(train) [5][2300/2462] lr: 7.8317e-02 eta: 0:15:41 time: 0.0362 data_time: 0.0061 memory: 1253 loss: 0.6480 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6480 2022/11/28 19:25:05 - mmengine - INFO - Epoch(train) [5][2400/2462] lr: 7.7987e-02 eta: 0:15:38 time: 0.0357 data_time: 0.0062 memory: 1253 loss: 0.5376 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5376 2022/11/28 19:25:07 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:25:07 - mmengine - INFO - Epoch(train) [5][2462/2462] lr: 7.7782e-02 eta: 0:15:36 time: 0.0341 data_time: 0.0062 memory: 1253 loss: 0.7022 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7022 2022/11/28 19:25:07 - mmengine - INFO - Saving checkpoint at 5 epochs 2022/11/28 19:25:09 - mmengine - INFO - Epoch(val) [5][100/398] eta: 0:00:04 time: 0.0154 data_time: 0.0061 memory: 262 2022/11/28 19:25:10 - mmengine - INFO - Epoch(val) [5][200/398] eta: 0:00:03 time: 0.0151 data_time: 0.0059 memory: 262 2022/11/28 19:25:12 - mmengine - INFO - Epoch(val) [5][300/398] eta: 0:00:01 time: 0.0153 data_time: 0.0061 memory: 262 2022/11/28 19:25:14 - mmengine - INFO - Epoch(val) [5][398/398] acc/top1: 0.6106 acc/top5: 0.8720 acc/mean1: 0.6458 2022/11/28 19:25:18 - mmengine - INFO - Epoch(train) [6][100/2462] lr: 7.7449e-02 eta: 0:15:33 time: 0.0355 data_time: 0.0062 memory: 1253 loss: 0.5230 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5230 2022/11/28 19:25:21 - mmengine - INFO - Epoch(train) [6][200/2462] lr: 7.7115e-02 eta: 0:15:30 time: 0.0374 data_time: 0.0063 memory: 1253 loss: 0.6754 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6754 2022/11/28 19:25:25 - mmengine - INFO - Epoch(train) [6][300/2462] lr: 7.6779e-02 eta: 0:15:27 time: 0.0350 data_time: 0.0066 memory: 1253 loss: 0.6139 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.6139 2022/11/28 19:25:28 - mmengine - INFO - Epoch(train) [6][400/2462] lr: 7.6442e-02 eta: 0:15:23 time: 0.0358 data_time: 0.0063 memory: 1253 loss: 0.5076 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5076 2022/11/28 19:25:32 - mmengine - INFO - Epoch(train) [6][500/2462] lr: 7.6102e-02 eta: 0:15:20 time: 0.0351 data_time: 0.0066 memory: 1253 loss: 0.5304 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5304 2022/11/28 19:25:35 - mmengine - INFO - Epoch(train) [6][600/2462] lr: 7.5762e-02 eta: 0:15:17 time: 0.0349 data_time: 0.0061 memory: 1253 loss: 0.6596 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6596 2022/11/28 19:25:39 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:25:39 - mmengine - INFO - Epoch(train) [6][700/2462] lr: 7.5419e-02 eta: 0:15:13 time: 0.0354 data_time: 0.0063 memory: 1253 loss: 0.5841 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5841 2022/11/28 19:25:43 - mmengine - INFO - Epoch(train) [6][800/2462] lr: 7.5075e-02 eta: 0:15:10 time: 0.0358 data_time: 0.0062 memory: 1253 loss: 0.6379 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6379 2022/11/28 19:25:46 - mmengine - INFO - Epoch(train) [6][900/2462] lr: 7.4729e-02 eta: 0:15:07 time: 0.0364 data_time: 0.0062 memory: 1253 loss: 0.4527 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.4527 2022/11/28 19:25:50 - mmengine - INFO - Epoch(train) [6][1000/2462] lr: 7.4382e-02 eta: 0:15:04 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.5534 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5534 2022/11/28 19:25:53 - mmengine - INFO - Epoch(train) [6][1100/2462] lr: 7.4033e-02 eta: 0:15:00 time: 0.0349 data_time: 0.0062 memory: 1253 loss: 0.5127 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5127 2022/11/28 19:25:57 - mmengine - INFO - Epoch(train) [6][1200/2462] lr: 7.3682e-02 eta: 0:14:57 time: 0.0340 data_time: 0.0062 memory: 1253 loss: 0.5457 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5457 2022/11/28 19:26:00 - mmengine - INFO - Epoch(train) [6][1300/2462] lr: 7.3330e-02 eta: 0:14:54 time: 0.0355 data_time: 0.0061 memory: 1253 loss: 0.5404 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5404 2022/11/28 19:26:04 - mmengine - INFO - Epoch(train) [6][1400/2462] lr: 7.2977e-02 eta: 0:14:50 time: 0.0361 data_time: 0.0071 memory: 1253 loss: 0.6003 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6003 2022/11/28 19:26:07 - mmengine - INFO - Epoch(train) [6][1500/2462] lr: 7.2622e-02 eta: 0:14:47 time: 0.0359 data_time: 0.0062 memory: 1253 loss: 0.5346 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5346 2022/11/28 19:26:11 - mmengine - INFO - Epoch(train) [6][1600/2462] lr: 7.2266e-02 eta: 0:14:44 time: 0.0347 data_time: 0.0061 memory: 1253 loss: 0.6319 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.6319 2022/11/28 19:26:14 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:26:14 - mmengine - INFO - Epoch(train) [6][1700/2462] lr: 7.1908e-02 eta: 0:14:40 time: 0.0348 data_time: 0.0062 memory: 1253 loss: 0.5501 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5501 2022/11/28 19:26:18 - mmengine - INFO - Epoch(train) [6][1800/2462] lr: 7.1549e-02 eta: 0:14:37 time: 0.0359 data_time: 0.0068 memory: 1253 loss: 0.6145 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6145 2022/11/28 19:26:21 - mmengine - INFO - Epoch(train) [6][1900/2462] lr: 7.1188e-02 eta: 0:14:33 time: 0.0346 data_time: 0.0067 memory: 1253 loss: 0.5420 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.5420 2022/11/28 19:26:25 - mmengine - INFO - Epoch(train) [6][2000/2462] lr: 7.0826e-02 eta: 0:14:30 time: 0.0341 data_time: 0.0062 memory: 1253 loss: 0.5847 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.5847 2022/11/28 19:26:28 - mmengine - INFO - Epoch(train) [6][2100/2462] lr: 7.0463e-02 eta: 0:14:26 time: 0.0344 data_time: 0.0062 memory: 1253 loss: 0.5318 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5318 2022/11/28 19:26:32 - mmengine - INFO - Epoch(train) [6][2200/2462] lr: 7.0099e-02 eta: 0:14:23 time: 0.0346 data_time: 0.0062 memory: 1253 loss: 0.5339 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5339 2022/11/28 19:26:35 - mmengine - INFO - Epoch(train) [6][2300/2462] lr: 6.9733e-02 eta: 0:14:19 time: 0.0349 data_time: 0.0064 memory: 1253 loss: 0.5718 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5718 2022/11/28 19:26:39 - mmengine - INFO - Epoch(train) [6][2400/2462] lr: 6.9366e-02 eta: 0:14:16 time: 0.0358 data_time: 0.0065 memory: 1253 loss: 0.5292 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5292 2022/11/28 19:26:41 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:26:41 - mmengine - INFO - Epoch(train) [6][2462/2462] lr: 6.9138e-02 eta: 0:14:14 time: 0.0366 data_time: 0.0063 memory: 1253 loss: 0.5010 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5010 2022/11/28 19:26:41 - mmengine - INFO - Saving checkpoint at 6 epochs 2022/11/28 19:26:43 - mmengine - INFO - Epoch(val) [6][100/398] eta: 0:00:05 time: 0.0151 data_time: 0.0059 memory: 262 2022/11/28 19:26:45 - mmengine - INFO - Epoch(val) [6][200/398] eta: 0:00:03 time: 0.0148 data_time: 0.0057 memory: 262 2022/11/28 19:26:46 - mmengine - INFO - Epoch(val) [6][300/398] eta: 0:00:01 time: 0.0149 data_time: 0.0057 memory: 262 2022/11/28 19:26:48 - mmengine - INFO - Epoch(val) [6][398/398] acc/top1: 0.6827 acc/top5: 0.9208 acc/mean1: 0.7119 2022/11/28 19:26:48 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_4.pth is removed 2022/11/28 19:26:49 - mmengine - INFO - The best checkpoint with 0.6827 acc/top1 at 6 epoch is saved to best_acc/top1_epoch_6.pth. 2022/11/28 19:26:52 - mmengine - INFO - Epoch(train) [7][100/2462] lr: 6.8769e-02 eta: 0:14:11 time: 0.0352 data_time: 0.0062 memory: 1253 loss: 0.5355 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5355 2022/11/28 19:26:56 - mmengine - INFO - Epoch(train) [7][200/2462] lr: 6.8399e-02 eta: 0:14:07 time: 0.0344 data_time: 0.0062 memory: 1253 loss: 0.6306 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6306 2022/11/28 19:26:57 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:26:59 - mmengine - INFO - Epoch(train) [7][300/2462] lr: 6.8027e-02 eta: 0:14:04 time: 0.0347 data_time: 0.0062 memory: 1253 loss: 0.4866 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4866 2022/11/28 19:27:03 - mmengine - INFO - Epoch(train) [7][400/2462] lr: 6.7655e-02 eta: 0:14:01 time: 0.0365 data_time: 0.0062 memory: 1253 loss: 0.5004 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5004 2022/11/28 19:27:07 - mmengine - INFO - Epoch(train) [7][500/2462] lr: 6.7281e-02 eta: 0:13:57 time: 0.0359 data_time: 0.0061 memory: 1253 loss: 0.4780 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.4780 2022/11/28 19:27:10 - mmengine - INFO - Epoch(train) [7][600/2462] lr: 6.6906e-02 eta: 0:13:54 time: 0.0361 data_time: 0.0062 memory: 1253 loss: 0.4425 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4425 2022/11/28 19:27:14 - mmengine - INFO - Epoch(train) [7][700/2462] lr: 6.6531e-02 eta: 0:13:50 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.5161 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5161 2022/11/28 19:27:17 - mmengine - INFO - Epoch(train) [7][800/2462] lr: 6.6154e-02 eta: 0:13:47 time: 0.0345 data_time: 0.0062 memory: 1253 loss: 0.5699 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5699 2022/11/28 19:27:20 - mmengine - INFO - Epoch(train) [7][900/2462] lr: 6.5776e-02 eta: 0:13:43 time: 0.0341 data_time: 0.0062 memory: 1253 loss: 0.4660 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4660 2022/11/28 19:27:24 - mmengine - INFO - Epoch(train) [7][1000/2462] lr: 6.5397e-02 eta: 0:13:40 time: 0.0353 data_time: 0.0062 memory: 1253 loss: 0.4591 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4591 2022/11/28 19:27:27 - mmengine - INFO - Epoch(train) [7][1100/2462] lr: 6.5017e-02 eta: 0:13:36 time: 0.0354 data_time: 0.0061 memory: 1253 loss: 0.4799 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4799 2022/11/28 19:27:31 - mmengine - INFO - Epoch(train) [7][1200/2462] lr: 6.4636e-02 eta: 0:13:33 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.5445 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5445 2022/11/28 19:27:32 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:27:34 - mmengine - INFO - Epoch(train) [7][1300/2462] lr: 6.4255e-02 eta: 0:13:29 time: 0.0339 data_time: 0.0061 memory: 1253 loss: 0.5976 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5976 2022/11/28 19:27:38 - mmengine - INFO - Epoch(train) [7][1400/2462] lr: 6.3872e-02 eta: 0:13:26 time: 0.0358 data_time: 0.0062 memory: 1253 loss: 0.4969 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4969 2022/11/28 19:27:41 - mmengine - INFO - Epoch(train) [7][1500/2462] lr: 6.3488e-02 eta: 0:13:23 time: 0.0344 data_time: 0.0062 memory: 1253 loss: 0.5414 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5414 2022/11/28 19:27:45 - mmengine - INFO - Epoch(train) [7][1600/2462] lr: 6.3104e-02 eta: 0:13:19 time: 0.0361 data_time: 0.0066 memory: 1253 loss: 0.5218 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5218 2022/11/28 19:27:48 - mmengine - INFO - Epoch(train) [7][1700/2462] lr: 6.2719e-02 eta: 0:13:16 time: 0.0355 data_time: 0.0062 memory: 1253 loss: 0.5931 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5931 2022/11/28 19:27:52 - mmengine - INFO - Epoch(train) [7][1800/2462] lr: 6.2333e-02 eta: 0:13:12 time: 0.0364 data_time: 0.0061 memory: 1253 loss: 0.5882 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5882 2022/11/28 19:27:56 - mmengine - INFO - Epoch(train) [7][1900/2462] lr: 6.1946e-02 eta: 0:13:09 time: 0.0365 data_time: 0.0061 memory: 1253 loss: 0.5555 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5555 2022/11/28 19:27:59 - mmengine - INFO - Epoch(train) [7][2000/2462] lr: 6.1558e-02 eta: 0:13:06 time: 0.0364 data_time: 0.0062 memory: 1253 loss: 0.4937 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.4937 2022/11/28 19:28:03 - mmengine - INFO - Epoch(train) [7][2100/2462] lr: 6.1170e-02 eta: 0:13:03 time: 0.0356 data_time: 0.0065 memory: 1253 loss: 0.5211 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5211 2022/11/28 19:28:06 - mmengine - INFO - Epoch(train) [7][2200/2462] lr: 6.0781e-02 eta: 0:12:59 time: 0.0346 data_time: 0.0061 memory: 1253 loss: 0.4787 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4787 2022/11/28 19:28:07 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:28:10 - mmengine - INFO - Epoch(train) [7][2300/2462] lr: 6.0391e-02 eta: 0:12:56 time: 0.0357 data_time: 0.0062 memory: 1253 loss: 0.4510 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.4510 2022/11/28 19:28:14 - mmengine - INFO - Epoch(train) [7][2400/2462] lr: 6.0001e-02 eta: 0:12:52 time: 0.0346 data_time: 0.0062 memory: 1253 loss: 0.4804 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.4804 2022/11/28 19:28:16 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:28:16 - mmengine - INFO - Epoch(train) [7][2462/2462] lr: 5.9758e-02 eta: 0:12:50 time: 0.0349 data_time: 0.0061 memory: 1253 loss: 0.4164 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.4164 2022/11/28 19:28:16 - mmengine - INFO - Saving checkpoint at 7 epochs 2022/11/28 19:28:18 - mmengine - INFO - Epoch(val) [7][100/398] eta: 0:00:04 time: 0.0150 data_time: 0.0058 memory: 262 2022/11/28 19:28:19 - mmengine - INFO - Epoch(val) [7][200/398] eta: 0:00:03 time: 0.0151 data_time: 0.0059 memory: 262 2022/11/28 19:28:21 - mmengine - INFO - Epoch(val) [7][300/398] eta: 0:00:01 time: 0.0151 data_time: 0.0058 memory: 262 2022/11/28 19:28:23 - mmengine - INFO - Epoch(val) [7][398/398] acc/top1: 0.6578 acc/top5: 0.8970 acc/mean1: 0.6963 2022/11/28 19:28:27 - mmengine - INFO - Epoch(train) [8][100/2462] lr: 5.9367e-02 eta: 0:12:47 time: 0.0356 data_time: 0.0073 memory: 1253 loss: 0.4627 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4627 2022/11/28 19:28:30 - mmengine - INFO - Epoch(train) [8][200/2462] lr: 5.8975e-02 eta: 0:12:44 time: 0.0342 data_time: 0.0062 memory: 1253 loss: 0.4724 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.4724 2022/11/28 19:28:34 - mmengine - INFO - Epoch(train) [8][300/2462] lr: 5.8582e-02 eta: 0:12:40 time: 0.0345 data_time: 0.0063 memory: 1253 loss: 0.4042 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.4042 2022/11/28 19:28:37 - mmengine - INFO - Epoch(train) [8][400/2462] lr: 5.8189e-02 eta: 0:12:37 time: 0.0357 data_time: 0.0061 memory: 1253 loss: 0.5300 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5300 2022/11/28 19:28:41 - mmengine - INFO - Epoch(train) [8][500/2462] lr: 5.7796e-02 eta: 0:12:33 time: 0.0368 data_time: 0.0063 memory: 1253 loss: 0.5174 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5174 2022/11/28 19:28:44 - mmengine - INFO - Epoch(train) [8][600/2462] lr: 5.7402e-02 eta: 0:12:30 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.5768 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5768 2022/11/28 19:28:48 - mmengine - INFO - Epoch(train) [8][700/2462] lr: 5.7007e-02 eta: 0:12:26 time: 0.0346 data_time: 0.0063 memory: 1253 loss: 0.4869 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.4869 2022/11/28 19:28:50 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:28:51 - mmengine - INFO - Epoch(train) [8][800/2462] lr: 5.6612e-02 eta: 0:12:23 time: 0.0341 data_time: 0.0062 memory: 1253 loss: 0.4507 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4507 2022/11/28 19:28:55 - mmengine - INFO - Epoch(train) [8][900/2462] lr: 5.6216e-02 eta: 0:12:19 time: 0.0344 data_time: 0.0059 memory: 1253 loss: 0.5187 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5187 2022/11/28 19:28:58 - mmengine - INFO - Epoch(train) [8][1000/2462] lr: 5.5821e-02 eta: 0:12:16 time: 0.0343 data_time: 0.0061 memory: 1253 loss: 0.4902 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.4902 2022/11/28 19:29:02 - mmengine - INFO - Epoch(train) [8][1100/2462] lr: 5.5424e-02 eta: 0:12:12 time: 0.0354 data_time: 0.0063 memory: 1253 loss: 0.3852 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3852 2022/11/28 19:29:05 - mmengine - INFO - Epoch(train) [8][1200/2462] lr: 5.5028e-02 eta: 0:12:09 time: 0.0356 data_time: 0.0062 memory: 1253 loss: 0.4546 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.4546 2022/11/28 19:29:09 - mmengine - INFO - Epoch(train) [8][1300/2462] lr: 5.4631e-02 eta: 0:12:05 time: 0.0365 data_time: 0.0063 memory: 1253 loss: 0.3888 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.3888 2022/11/28 19:29:12 - mmengine - INFO - Epoch(train) [8][1400/2462] lr: 5.4234e-02 eta: 0:12:02 time: 0.0341 data_time: 0.0061 memory: 1253 loss: 0.4451 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4451 2022/11/28 19:29:16 - mmengine - INFO - Epoch(train) [8][1500/2462] lr: 5.3836e-02 eta: 0:11:58 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.4558 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.4558 2022/11/28 19:29:19 - mmengine - INFO - Epoch(train) [8][1600/2462] lr: 5.3439e-02 eta: 0:11:55 time: 0.0349 data_time: 0.0062 memory: 1253 loss: 0.4964 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4964 2022/11/28 19:29:23 - mmengine - INFO - Epoch(train) [8][1700/2462] lr: 5.3041e-02 eta: 0:11:52 time: 0.0349 data_time: 0.0062 memory: 1253 loss: 0.3943 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3943 2022/11/28 19:29:25 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:29:26 - mmengine - INFO - Epoch(train) [8][1800/2462] lr: 5.2643e-02 eta: 0:11:48 time: 0.0349 data_time: 0.0070 memory: 1253 loss: 0.4759 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4759 2022/11/28 19:29:30 - mmengine - INFO - Epoch(train) [8][1900/2462] lr: 5.2244e-02 eta: 0:11:45 time: 0.0356 data_time: 0.0062 memory: 1253 loss: 0.5495 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.5495 2022/11/28 19:29:34 - mmengine - INFO - Epoch(train) [8][2000/2462] lr: 5.1846e-02 eta: 0:11:41 time: 0.0361 data_time: 0.0062 memory: 1253 loss: 0.4776 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.4776 2022/11/28 19:29:37 - mmengine - INFO - Epoch(train) [8][2100/2462] lr: 5.1447e-02 eta: 0:11:38 time: 0.0358 data_time: 0.0063 memory: 1253 loss: 0.4168 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4168 2022/11/28 19:29:41 - mmengine - INFO - Epoch(train) [8][2200/2462] lr: 5.1049e-02 eta: 0:11:35 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.3909 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3909 2022/11/28 19:29:44 - mmengine - INFO - Epoch(train) [8][2300/2462] lr: 5.0650e-02 eta: 0:11:31 time: 0.0347 data_time: 0.0062 memory: 1253 loss: 0.4464 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4464 2022/11/28 19:29:48 - mmengine - INFO - Epoch(train) [8][2400/2462] lr: 5.0251e-02 eta: 0:11:28 time: 0.0347 data_time: 0.0063 memory: 1253 loss: 0.4169 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4169 2022/11/28 19:29:50 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:29:50 - mmengine - INFO - Epoch(train) [8][2462/2462] lr: 5.0004e-02 eta: 0:11:25 time: 0.0344 data_time: 0.0063 memory: 1253 loss: 0.4031 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4031 2022/11/28 19:29:50 - mmengine - INFO - Saving checkpoint at 8 epochs 2022/11/28 19:29:52 - mmengine - INFO - Epoch(val) [8][100/398] eta: 0:00:04 time: 0.0153 data_time: 0.0059 memory: 262 2022/11/28 19:29:53 - mmengine - INFO - Epoch(val) [8][200/398] eta: 0:00:03 time: 0.0149 data_time: 0.0057 memory: 262 2022/11/28 19:29:55 - mmengine - INFO - Epoch(val) [8][300/398] eta: 0:00:01 time: 0.0159 data_time: 0.0064 memory: 262 2022/11/28 19:29:57 - mmengine - INFO - Epoch(val) [8][398/398] acc/top1: 0.6944 acc/top5: 0.9136 acc/mean1: 0.7125 2022/11/28 19:29:57 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_6.pth is removed 2022/11/28 19:29:58 - mmengine - INFO - The best checkpoint with 0.6944 acc/top1 at 8 epoch is saved to best_acc/top1_epoch_8.pth. 2022/11/28 19:30:01 - mmengine - INFO - Epoch(train) [9][100/2462] lr: 4.9605e-02 eta: 0:11:22 time: 0.0346 data_time: 0.0063 memory: 1253 loss: 0.4376 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.4376 2022/11/28 19:30:05 - mmengine - INFO - Epoch(train) [9][200/2462] lr: 4.9207e-02 eta: 0:11:18 time: 0.0339 data_time: 0.0062 memory: 1253 loss: 0.3635 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.3635 2022/11/28 19:30:08 - mmengine - INFO - Epoch(train) [9][300/2462] lr: 4.8808e-02 eta: 0:11:15 time: 0.0344 data_time: 0.0063 memory: 1253 loss: 0.3339 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3339 2022/11/28 19:30:08 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:30:11 - mmengine - INFO - Epoch(train) [9][400/2462] lr: 4.8409e-02 eta: 0:11:11 time: 0.0356 data_time: 0.0062 memory: 1253 loss: 0.5007 top1_acc: 0.5625 top5_acc: 1.0000 loss_cls: 0.5007 2022/11/28 19:30:15 - mmengine - INFO - Epoch(train) [9][500/2462] lr: 4.8011e-02 eta: 0:11:08 time: 0.0350 data_time: 0.0062 memory: 1253 loss: 0.3767 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3767 2022/11/28 19:30:18 - mmengine - INFO - Epoch(train) [9][600/2462] lr: 4.7612e-02 eta: 0:11:04 time: 0.0349 data_time: 0.0062 memory: 1253 loss: 0.4096 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4096 2022/11/28 19:30:22 - mmengine - INFO - Epoch(train) [9][700/2462] lr: 4.7214e-02 eta: 0:11:01 time: 0.0342 data_time: 0.0061 memory: 1253 loss: 0.4098 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4098 2022/11/28 19:30:25 - mmengine - INFO - Epoch(train) [9][800/2462] lr: 4.6816e-02 eta: 0:10:58 time: 0.0358 data_time: 0.0061 memory: 1253 loss: 0.4019 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.4019 2022/11/28 19:30:29 - mmengine - INFO - Epoch(train) [9][900/2462] lr: 4.6418e-02 eta: 0:10:54 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.4283 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4283 2022/11/28 19:30:33 - mmengine - INFO - Epoch(train) [9][1000/2462] lr: 4.6021e-02 eta: 0:10:51 time: 0.0357 data_time: 0.0061 memory: 1253 loss: 0.3733 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.3733 2022/11/28 19:30:36 - mmengine - INFO - Epoch(train) [9][1100/2462] lr: 4.5623e-02 eta: 0:10:47 time: 0.0345 data_time: 0.0062 memory: 1253 loss: 0.3586 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.3586 2022/11/28 19:30:40 - mmengine - INFO - Epoch(train) [9][1200/2462] lr: 4.5226e-02 eta: 0:10:44 time: 0.0358 data_time: 0.0062 memory: 1253 loss: 0.3799 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3799 2022/11/28 19:30:43 - mmengine - INFO - Epoch(train) [9][1300/2462] lr: 4.4829e-02 eta: 0:10:40 time: 0.0347 data_time: 0.0062 memory: 1253 loss: 0.3496 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3496 2022/11/28 19:30:43 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:30:47 - mmengine - INFO - Epoch(train) [9][1400/2462] lr: 4.4433e-02 eta: 0:10:37 time: 0.0346 data_time: 0.0062 memory: 1253 loss: 0.3966 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.3966 2022/11/28 19:30:50 - mmengine - INFO - Epoch(train) [9][1500/2462] lr: 4.4037e-02 eta: 0:10:33 time: 0.0342 data_time: 0.0061 memory: 1253 loss: 0.3476 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3476 2022/11/28 19:30:54 - mmengine - INFO - Epoch(train) [9][1600/2462] lr: 4.3641e-02 eta: 0:10:30 time: 0.0346 data_time: 0.0062 memory: 1253 loss: 0.4098 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4098 2022/11/28 19:30:57 - mmengine - INFO - Epoch(train) [9][1700/2462] lr: 4.3246e-02 eta: 0:10:26 time: 0.0343 data_time: 0.0061 memory: 1253 loss: 0.4067 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4067 2022/11/28 19:31:01 - mmengine - INFO - Epoch(train) [9][1800/2462] lr: 4.2851e-02 eta: 0:10:23 time: 0.0342 data_time: 0.0062 memory: 1253 loss: 0.4530 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4530 2022/11/28 19:31:04 - mmengine - INFO - Epoch(train) [9][1900/2462] lr: 4.2456e-02 eta: 0:10:19 time: 0.0343 data_time: 0.0061 memory: 1253 loss: 0.3479 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.3479 2022/11/28 19:31:07 - mmengine - INFO - Epoch(train) [9][2000/2462] lr: 4.2063e-02 eta: 0:10:16 time: 0.0339 data_time: 0.0063 memory: 1253 loss: 0.3812 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3812 2022/11/28 19:31:11 - mmengine - INFO - Epoch(train) [9][2100/2462] lr: 4.1669e-02 eta: 0:10:12 time: 0.0346 data_time: 0.0063 memory: 1253 loss: 0.4671 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4671 2022/11/28 19:31:14 - mmengine - INFO - Epoch(train) [9][2200/2462] lr: 4.1276e-02 eta: 0:10:09 time: 0.0357 data_time: 0.0062 memory: 1253 loss: 0.4224 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4224 2022/11/28 19:31:18 - mmengine - INFO - Epoch(train) [9][2300/2462] lr: 4.0884e-02 eta: 0:10:05 time: 0.0350 data_time: 0.0062 memory: 1253 loss: 0.4355 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4355 2022/11/28 19:31:18 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:31:21 - mmengine - INFO - Epoch(train) [9][2400/2462] lr: 4.0492e-02 eta: 0:10:02 time: 0.0346 data_time: 0.0065 memory: 1253 loss: 0.3720 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3720 2022/11/28 19:31:24 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:31:24 - mmengine - INFO - Epoch(train) [9][2462/2462] lr: 4.0249e-02 eta: 0:10:00 time: 0.0342 data_time: 0.0062 memory: 1253 loss: 0.3387 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3387 2022/11/28 19:31:24 - mmengine - INFO - Saving checkpoint at 9 epochs 2022/11/28 19:31:26 - mmengine - INFO - Epoch(val) [9][100/398] eta: 0:00:04 time: 0.0151 data_time: 0.0059 memory: 262 2022/11/28 19:31:27 - mmengine - INFO - Epoch(val) [9][200/398] eta: 0:00:03 time: 0.0156 data_time: 0.0062 memory: 262 2022/11/28 19:31:29 - mmengine - INFO - Epoch(val) [9][300/398] eta: 0:00:01 time: 0.0151 data_time: 0.0058 memory: 262 2022/11/28 19:31:31 - mmengine - INFO - Epoch(val) [9][398/398] acc/top1: 0.7204 acc/top5: 0.9336 acc/mean1: 0.7410 2022/11/28 19:31:31 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_8.pth is removed 2022/11/28 19:31:31 - mmengine - INFO - The best checkpoint with 0.7204 acc/top1 at 9 epoch is saved to best_acc/top1_epoch_9.pth. 2022/11/28 19:31:35 - mmengine - INFO - Epoch(train) [10][100/2462] lr: 3.9859e-02 eta: 0:09:56 time: 0.0341 data_time: 0.0064 memory: 1253 loss: 0.3994 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3994 2022/11/28 19:31:38 - mmengine - INFO - Epoch(train) [10][200/2462] lr: 3.9468e-02 eta: 0:09:53 time: 0.0341 data_time: 0.0061 memory: 1253 loss: 0.3615 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3615 2022/11/28 19:31:42 - mmengine - INFO - Epoch(train) [10][300/2462] lr: 3.9079e-02 eta: 0:09:49 time: 0.0346 data_time: 0.0063 memory: 1253 loss: 0.4334 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4334 2022/11/28 19:31:45 - mmengine - INFO - Epoch(train) [10][400/2462] lr: 3.8690e-02 eta: 0:09:46 time: 0.0342 data_time: 0.0061 memory: 1253 loss: 0.3345 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.3345 2022/11/28 19:31:49 - mmengine - INFO - Epoch(train) [10][500/2462] lr: 3.8302e-02 eta: 0:09:42 time: 0.0344 data_time: 0.0063 memory: 1253 loss: 0.4182 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.4182 2022/11/28 19:31:52 - mmengine - INFO - Epoch(train) [10][600/2462] lr: 3.7915e-02 eta: 0:09:39 time: 0.0341 data_time: 0.0062 memory: 1253 loss: 0.2871 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2871 2022/11/28 19:31:56 - mmengine - INFO - Epoch(train) [10][700/2462] lr: 3.7528e-02 eta: 0:09:35 time: 0.0348 data_time: 0.0061 memory: 1253 loss: 0.3234 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3234 2022/11/28 19:31:59 - mmengine - INFO - Epoch(train) [10][800/2462] lr: 3.7143e-02 eta: 0:09:32 time: 0.0345 data_time: 0.0068 memory: 1253 loss: 0.3788 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.3788 2022/11/28 19:32:01 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:32:03 - mmengine - INFO - Epoch(train) [10][900/2462] lr: 3.6758e-02 eta: 0:09:28 time: 0.0356 data_time: 0.0062 memory: 1253 loss: 0.2968 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.2968 2022/11/28 19:32:06 - mmengine - INFO - Epoch(train) [10][1000/2462] lr: 3.6373e-02 eta: 0:09:25 time: 0.0340 data_time: 0.0061 memory: 1253 loss: 0.3139 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.3139 2022/11/28 19:32:10 - mmengine - INFO - Epoch(train) [10][1100/2462] lr: 3.5990e-02 eta: 0:09:21 time: 0.0359 data_time: 0.0061 memory: 1253 loss: 0.3781 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3781 2022/11/28 19:32:13 - mmengine - INFO - Epoch(train) [10][1200/2462] lr: 3.5608e-02 eta: 0:09:18 time: 0.0344 data_time: 0.0063 memory: 1253 loss: 0.3627 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3627 2022/11/28 19:32:17 - mmengine - INFO - Epoch(train) [10][1300/2462] lr: 3.5226e-02 eta: 0:09:14 time: 0.0349 data_time: 0.0063 memory: 1253 loss: 0.4162 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4162 2022/11/28 19:32:20 - mmengine - INFO - Epoch(train) [10][1400/2462] lr: 3.4846e-02 eta: 0:09:11 time: 0.0344 data_time: 0.0065 memory: 1253 loss: 0.3464 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3464 2022/11/28 19:32:24 - mmengine - INFO - Epoch(train) [10][1500/2462] lr: 3.4466e-02 eta: 0:09:07 time: 0.0340 data_time: 0.0065 memory: 1253 loss: 0.3253 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3253 2022/11/28 19:32:27 - mmengine - INFO - Epoch(train) [10][1600/2462] lr: 3.4088e-02 eta: 0:09:04 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.3008 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3008 2022/11/28 19:32:30 - mmengine - INFO - Epoch(train) [10][1700/2462] lr: 3.3710e-02 eta: 0:09:00 time: 0.0346 data_time: 0.0066 memory: 1253 loss: 0.2971 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2971 2022/11/28 19:32:34 - mmengine - INFO - Epoch(train) [10][1800/2462] lr: 3.3334e-02 eta: 0:08:57 time: 0.0347 data_time: 0.0070 memory: 1253 loss: 0.3115 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3115 2022/11/28 19:32:35 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:32:37 - mmengine - INFO - Epoch(train) [10][1900/2462] lr: 3.2959e-02 eta: 0:08:53 time: 0.0347 data_time: 0.0063 memory: 1253 loss: 0.3527 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3527 2022/11/28 19:32:41 - mmengine - INFO - Epoch(train) [10][2000/2462] lr: 3.2584e-02 eta: 0:08:50 time: 0.0355 data_time: 0.0068 memory: 1253 loss: 0.3114 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.3114 2022/11/28 19:32:44 - mmengine - INFO - Epoch(train) [10][2100/2462] lr: 3.2211e-02 eta: 0:08:46 time: 0.0348 data_time: 0.0062 memory: 1253 loss: 0.2710 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2710 2022/11/28 19:32:48 - mmengine - INFO - Epoch(train) [10][2200/2462] lr: 3.1839e-02 eta: 0:08:43 time: 0.0347 data_time: 0.0068 memory: 1253 loss: 0.3544 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.3544 2022/11/28 19:32:52 - mmengine - INFO - Epoch(train) [10][2300/2462] lr: 3.1468e-02 eta: 0:08:40 time: 0.0360 data_time: 0.0065 memory: 1253 loss: 0.3081 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3081 2022/11/28 19:32:55 - mmengine - INFO - Epoch(train) [10][2400/2462] lr: 3.1098e-02 eta: 0:08:36 time: 0.0347 data_time: 0.0070 memory: 1253 loss: 0.3570 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.3570 2022/11/28 19:32:57 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:32:57 - mmengine - INFO - Epoch(train) [10][2462/2462] lr: 3.0870e-02 eta: 0:08:34 time: 0.0340 data_time: 0.0063 memory: 1253 loss: 0.2680 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.2680 2022/11/28 19:32:57 - mmengine - INFO - Saving checkpoint at 10 epochs 2022/11/28 19:32:59 - mmengine - INFO - Epoch(val) [10][100/398] eta: 0:00:04 time: 0.0149 data_time: 0.0057 memory: 262 2022/11/28 19:33:01 - mmengine - INFO - Epoch(val) [10][200/398] eta: 0:00:03 time: 0.0151 data_time: 0.0059 memory: 262 2022/11/28 19:33:02 - mmengine - INFO - Epoch(val) [10][300/398] eta: 0:00:01 time: 0.0149 data_time: 0.0058 memory: 262 2022/11/28 19:33:05 - mmengine - INFO - Epoch(val) [10][398/398] acc/top1: 0.7349 acc/top5: 0.9374 acc/mean1: 0.7623 2022/11/28 19:33:05 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_9.pth is removed 2022/11/28 19:33:05 - mmengine - INFO - The best checkpoint with 0.7349 acc/top1 at 10 epoch is saved to best_acc/top1_epoch_10.pth. 2022/11/28 19:33:08 - mmengine - INFO - Epoch(train) [11][100/2462] lr: 3.0502e-02 eta: 0:08:30 time: 0.0346 data_time: 0.0061 memory: 1253 loss: 0.3251 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3251 2022/11/28 19:33:12 - mmengine - INFO - Epoch(train) [11][200/2462] lr: 3.0135e-02 eta: 0:08:27 time: 0.0342 data_time: 0.0062 memory: 1253 loss: 0.2683 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2683 2022/11/28 19:33:15 - mmengine - INFO - Epoch(train) [11][300/2462] lr: 2.9770e-02 eta: 0:08:23 time: 0.0347 data_time: 0.0061 memory: 1253 loss: 0.3006 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3006 2022/11/28 19:33:18 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:33:19 - mmengine - INFO - Epoch(train) [11][400/2462] lr: 2.9406e-02 eta: 0:08:20 time: 0.0345 data_time: 0.0061 memory: 1253 loss: 0.3112 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.3112 2022/11/28 19:33:22 - mmengine - INFO - Epoch(train) [11][500/2462] lr: 2.9043e-02 eta: 0:08:16 time: 0.0342 data_time: 0.0062 memory: 1253 loss: 0.2319 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2319 2022/11/28 19:33:26 - mmengine - INFO - Epoch(train) [11][600/2462] lr: 2.8682e-02 eta: 0:08:13 time: 0.0360 data_time: 0.0061 memory: 1253 loss: 0.2760 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.2760 2022/11/28 19:33:29 - mmengine - INFO - Epoch(train) [11][700/2462] lr: 2.8322e-02 eta: 0:08:10 time: 0.0349 data_time: 0.0067 memory: 1253 loss: 0.3240 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.3240 2022/11/28 19:33:33 - mmengine - INFO - Epoch(train) [11][800/2462] lr: 2.7963e-02 eta: 0:08:06 time: 0.0353 data_time: 0.0063 memory: 1253 loss: 0.2987 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2987 2022/11/28 19:33:37 - mmengine - INFO - Epoch(train) [11][900/2462] lr: 2.7606e-02 eta: 0:08:03 time: 0.0344 data_time: 0.0062 memory: 1253 loss: 0.3469 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.3469 2022/11/28 19:33:40 - mmengine - INFO - Epoch(train) [11][1000/2462] lr: 2.7250e-02 eta: 0:07:59 time: 0.0365 data_time: 0.0062 memory: 1253 loss: 0.2910 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.2910 2022/11/28 19:33:44 - mmengine - INFO - Epoch(train) [11][1100/2462] lr: 2.6896e-02 eta: 0:07:56 time: 0.0341 data_time: 0.0061 memory: 1253 loss: 0.2488 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2488 2022/11/28 19:33:47 - mmengine - INFO - Epoch(train) [11][1200/2462] lr: 2.6543e-02 eta: 0:07:52 time: 0.0357 data_time: 0.0065 memory: 1253 loss: 0.2366 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2366 2022/11/28 19:33:51 - mmengine - INFO - Epoch(train) [11][1300/2462] lr: 2.6191e-02 eta: 0:07:49 time: 0.0347 data_time: 0.0064 memory: 1253 loss: 0.1937 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1937 2022/11/28 19:33:53 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:33:54 - mmengine - INFO - Epoch(train) [11][1400/2462] lr: 2.5841e-02 eta: 0:07:45 time: 0.0353 data_time: 0.0064 memory: 1253 loss: 0.2496 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.2496 2022/11/28 19:33:58 - mmengine - INFO - Epoch(train) [11][1500/2462] lr: 2.5493e-02 eta: 0:07:42 time: 0.0360 data_time: 0.0065 memory: 1253 loss: 0.2508 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2508 2022/11/28 19:34:01 - mmengine - INFO - Epoch(train) [11][1600/2462] lr: 2.5146e-02 eta: 0:07:38 time: 0.0345 data_time: 0.0061 memory: 1253 loss: 0.2139 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2139 2022/11/28 19:34:05 - mmengine - INFO - Epoch(train) [11][1700/2462] lr: 2.4801e-02 eta: 0:07:35 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.2208 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2208 2022/11/28 19:34:08 - mmengine - INFO - Epoch(train) [11][1800/2462] lr: 2.4458e-02 eta: 0:07:31 time: 0.0341 data_time: 0.0062 memory: 1253 loss: 0.2222 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2222 2022/11/28 19:34:12 - mmengine - INFO - Epoch(train) [11][1900/2462] lr: 2.4116e-02 eta: 0:07:28 time: 0.0361 data_time: 0.0066 memory: 1253 loss: 0.2273 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2273 2022/11/28 19:34:15 - mmengine - INFO - Epoch(train) [11][2000/2462] lr: 2.3775e-02 eta: 0:07:24 time: 0.0345 data_time: 0.0061 memory: 1253 loss: 0.1735 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1735 2022/11/28 19:34:18 - mmengine - INFO - Epoch(train) [11][2100/2462] lr: 2.3437e-02 eta: 0:07:21 time: 0.0341 data_time: 0.0062 memory: 1253 loss: 0.2301 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2301 2022/11/28 19:34:22 - mmengine - INFO - Epoch(train) [11][2200/2462] lr: 2.3100e-02 eta: 0:07:17 time: 0.0369 data_time: 0.0063 memory: 1253 loss: 0.2733 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2733 2022/11/28 19:34:26 - mmengine - INFO - Epoch(train) [11][2300/2462] lr: 2.2764e-02 eta: 0:07:14 time: 0.0351 data_time: 0.0064 memory: 1253 loss: 0.2323 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2323 2022/11/28 19:34:28 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:34:29 - mmengine - INFO - Epoch(train) [11][2400/2462] lr: 2.2431e-02 eta: 0:07:10 time: 0.0344 data_time: 0.0064 memory: 1253 loss: 0.2131 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2131 2022/11/28 19:34:31 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:34:31 - mmengine - INFO - Epoch(train) [11][2462/2462] lr: 2.2225e-02 eta: 0:07:08 time: 0.0345 data_time: 0.0064 memory: 1253 loss: 0.1995 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1995 2022/11/28 19:34:31 - mmengine - INFO - Saving checkpoint at 11 epochs 2022/11/28 19:34:33 - mmengine - INFO - Epoch(val) [11][100/398] eta: 0:00:04 time: 0.0152 data_time: 0.0059 memory: 262 2022/11/28 19:34:35 - mmengine - INFO - Epoch(val) [11][200/398] eta: 0:00:03 time: 0.0174 data_time: 0.0069 memory: 262 2022/11/28 19:34:36 - mmengine - INFO - Epoch(val) [11][300/398] eta: 0:00:01 time: 0.0152 data_time: 0.0058 memory: 262 2022/11/28 19:34:39 - mmengine - INFO - Epoch(val) [11][398/398] acc/top1: 0.7427 acc/top5: 0.9461 acc/mean1: 0.7648 2022/11/28 19:34:39 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_10.pth is removed 2022/11/28 19:34:39 - mmengine - INFO - The best checkpoint with 0.7427 acc/top1 at 11 epoch is saved to best_acc/top1_epoch_11.pth. 2022/11/28 19:34:43 - mmengine - INFO - Epoch(train) [12][100/2462] lr: 2.1894e-02 eta: 0:07:05 time: 0.0360 data_time: 0.0063 memory: 1253 loss: 0.2365 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2365 2022/11/28 19:34:46 - mmengine - INFO - Epoch(train) [12][200/2462] lr: 2.1565e-02 eta: 0:07:01 time: 0.0350 data_time: 0.0063 memory: 1253 loss: 0.1887 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.1887 2022/11/28 19:34:50 - mmengine - INFO - Epoch(train) [12][300/2462] lr: 2.1238e-02 eta: 0:06:58 time: 0.0359 data_time: 0.0063 memory: 1253 loss: 0.1960 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1960 2022/11/28 19:34:53 - mmengine - INFO - Epoch(train) [12][400/2462] lr: 2.0913e-02 eta: 0:06:55 time: 0.0348 data_time: 0.0065 memory: 1253 loss: 0.2308 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.2308 2022/11/28 19:34:57 - mmengine - INFO - Epoch(train) [12][500/2462] lr: 2.0589e-02 eta: 0:06:51 time: 0.0349 data_time: 0.0062 memory: 1253 loss: 0.1940 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1940 2022/11/28 19:35:01 - mmengine - INFO - Epoch(train) [12][600/2462] lr: 2.0268e-02 eta: 0:06:48 time: 0.0354 data_time: 0.0062 memory: 1253 loss: 0.2270 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2270 2022/11/28 19:35:04 - mmengine - INFO - Epoch(train) [12][700/2462] lr: 1.9948e-02 eta: 0:06:44 time: 0.0369 data_time: 0.0066 memory: 1253 loss: 0.2361 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.2361 2022/11/28 19:35:08 - mmengine - INFO - Epoch(train) [12][800/2462] lr: 1.9631e-02 eta: 0:06:41 time: 0.0361 data_time: 0.0062 memory: 1253 loss: 0.1918 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1918 2022/11/28 19:35:11 - mmengine - INFO - Epoch(train) [12][900/2462] lr: 1.9315e-02 eta: 0:06:37 time: 0.0356 data_time: 0.0062 memory: 1253 loss: 0.1814 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.1814 2022/11/28 19:35:12 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:35:15 - mmengine - INFO - Epoch(train) [12][1000/2462] lr: 1.9001e-02 eta: 0:06:34 time: 0.0361 data_time: 0.0063 memory: 1253 loss: 0.1622 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1622 2022/11/28 19:35:19 - mmengine - INFO - Epoch(train) [12][1100/2462] lr: 1.8689e-02 eta: 0:06:30 time: 0.0359 data_time: 0.0062 memory: 1253 loss: 0.2062 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.2062 2022/11/28 19:35:22 - mmengine - INFO - Epoch(train) [12][1200/2462] lr: 1.8379e-02 eta: 0:06:27 time: 0.0355 data_time: 0.0063 memory: 1253 loss: 0.1621 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1621 2022/11/28 19:35:26 - mmengine - INFO - Epoch(train) [12][1300/2462] lr: 1.8071e-02 eta: 0:06:23 time: 0.0347 data_time: 0.0062 memory: 1253 loss: 0.2172 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.2172 2022/11/28 19:35:29 - mmengine - INFO - Epoch(train) [12][1400/2462] lr: 1.7765e-02 eta: 0:06:20 time: 0.0345 data_time: 0.0063 memory: 1253 loss: 0.1490 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1490 2022/11/28 19:35:33 - mmengine - INFO - Epoch(train) [12][1500/2462] lr: 1.7462e-02 eta: 0:06:16 time: 0.0349 data_time: 0.0062 memory: 1253 loss: 0.1614 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.1614 2022/11/28 19:35:36 - mmengine - INFO - Epoch(train) [12][1600/2462] lr: 1.7160e-02 eta: 0:06:13 time: 0.0349 data_time: 0.0062 memory: 1253 loss: 0.1833 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1833 2022/11/28 19:35:40 - mmengine - INFO - Epoch(train) [12][1700/2462] lr: 1.6860e-02 eta: 0:06:10 time: 0.0351 data_time: 0.0062 memory: 1253 loss: 0.1402 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1402 2022/11/28 19:35:43 - mmengine - INFO - Epoch(train) [12][1800/2462] lr: 1.6563e-02 eta: 0:06:06 time: 0.0350 data_time: 0.0062 memory: 1253 loss: 0.1503 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.1503 2022/11/28 19:35:47 - mmengine - INFO - Epoch(train) [12][1900/2462] lr: 1.6267e-02 eta: 0:06:03 time: 0.0352 data_time: 0.0062 memory: 1253 loss: 0.1595 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1595 2022/11/28 19:35:47 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:35:50 - mmengine - INFO - Epoch(train) [12][2000/2462] lr: 1.5974e-02 eta: 0:05:59 time: 0.0347 data_time: 0.0062 memory: 1253 loss: 0.1755 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1755 2022/11/28 19:35:54 - mmengine - INFO - Epoch(train) [12][2100/2462] lr: 1.5683e-02 eta: 0:05:56 time: 0.0359 data_time: 0.0063 memory: 1253 loss: 0.1134 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1134 2022/11/28 19:35:57 - mmengine - INFO - Epoch(train) [12][2200/2462] lr: 1.5394e-02 eta: 0:05:52 time: 0.0345 data_time: 0.0062 memory: 1253 loss: 0.1454 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1454 2022/11/28 19:36:01 - mmengine - INFO - Epoch(train) [12][2300/2462] lr: 1.5107e-02 eta: 0:05:49 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.1671 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1671 2022/11/28 19:36:04 - mmengine - INFO - Epoch(train) [12][2400/2462] lr: 1.4823e-02 eta: 0:05:45 time: 0.0366 data_time: 0.0062 memory: 1253 loss: 0.1399 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1399 2022/11/28 19:36:06 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:36:06 - mmengine - INFO - Epoch(train) [12][2462/2462] lr: 1.4647e-02 eta: 0:05:43 time: 0.0347 data_time: 0.0063 memory: 1253 loss: 0.1541 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1541 2022/11/28 19:36:06 - mmengine - INFO - Saving checkpoint at 12 epochs 2022/11/28 19:36:08 - mmengine - INFO - Epoch(val) [12][100/398] eta: 0:00:04 time: 0.0148 data_time: 0.0057 memory: 262 2022/11/28 19:36:10 - mmengine - INFO - Epoch(val) [12][200/398] eta: 0:00:03 time: 0.0149 data_time: 0.0058 memory: 262 2022/11/28 19:36:11 - mmengine - INFO - Epoch(val) [12][300/398] eta: 0:00:01 time: 0.0152 data_time: 0.0060 memory: 262 2022/11/28 19:36:14 - mmengine - INFO - Epoch(val) [12][398/398] acc/top1: 0.7588 acc/top5: 0.9505 acc/mean1: 0.7792 2022/11/28 19:36:14 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_11.pth is removed 2022/11/28 19:36:14 - mmengine - INFO - The best checkpoint with 0.7588 acc/top1 at 12 epoch is saved to best_acc/top1_epoch_12.pth. 2022/11/28 19:36:18 - mmengine - INFO - Epoch(train) [13][100/2462] lr: 1.4367e-02 eta: 0:05:40 time: 0.0344 data_time: 0.0063 memory: 1253 loss: 0.1233 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1233 2022/11/28 19:36:21 - mmengine - INFO - Epoch(train) [13][200/2462] lr: 1.4088e-02 eta: 0:05:36 time: 0.0360 data_time: 0.0062 memory: 1253 loss: 0.1139 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1139 2022/11/28 19:36:25 - mmengine - INFO - Epoch(train) [13][300/2462] lr: 1.3812e-02 eta: 0:05:33 time: 0.0346 data_time: 0.0062 memory: 1253 loss: 0.1168 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1168 2022/11/28 19:36:28 - mmengine - INFO - Epoch(train) [13][400/2462] lr: 1.3538e-02 eta: 0:05:29 time: 0.0342 data_time: 0.0062 memory: 1253 loss: 0.1089 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.1089 2022/11/28 19:36:30 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:36:32 - mmengine - INFO - Epoch(train) [13][500/2462] lr: 1.3266e-02 eta: 0:05:26 time: 0.0345 data_time: 0.0062 memory: 1253 loss: 0.1364 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1364 2022/11/28 19:36:35 - mmengine - INFO - Epoch(train) [13][600/2462] lr: 1.2997e-02 eta: 0:05:22 time: 0.0359 data_time: 0.0061 memory: 1253 loss: 0.0784 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0784 2022/11/28 19:36:39 - mmengine - INFO - Epoch(train) [13][700/2462] lr: 1.2730e-02 eta: 0:05:19 time: 0.0349 data_time: 0.0067 memory: 1253 loss: 0.1496 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1496 2022/11/28 19:36:42 - mmengine - INFO - Epoch(train) [13][800/2462] lr: 1.2465e-02 eta: 0:05:15 time: 0.0360 data_time: 0.0062 memory: 1253 loss: 0.1131 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1131 2022/11/28 19:36:46 - mmengine - INFO - Epoch(train) [13][900/2462] lr: 1.2203e-02 eta: 0:05:12 time: 0.0354 data_time: 0.0062 memory: 1253 loss: 0.1077 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1077 2022/11/28 19:36:49 - mmengine - INFO - Epoch(train) [13][1000/2462] lr: 1.1943e-02 eta: 0:05:08 time: 0.0347 data_time: 0.0062 memory: 1253 loss: 0.1149 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1149 2022/11/28 19:36:53 - mmengine - INFO - Epoch(train) [13][1100/2462] lr: 1.1686e-02 eta: 0:05:05 time: 0.0347 data_time: 0.0061 memory: 1253 loss: 0.1117 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1117 2022/11/28 19:36:56 - mmengine - INFO - Epoch(train) [13][1200/2462] lr: 1.1431e-02 eta: 0:05:01 time: 0.0344 data_time: 0.0063 memory: 1253 loss: 0.1209 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1209 2022/11/28 19:37:00 - mmengine - INFO - Epoch(train) [13][1300/2462] lr: 1.1178e-02 eta: 0:04:58 time: 0.0341 data_time: 0.0063 memory: 1253 loss: 0.0665 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0665 2022/11/28 19:37:03 - mmengine - INFO - Epoch(train) [13][1400/2462] lr: 1.0928e-02 eta: 0:04:54 time: 0.0356 data_time: 0.0061 memory: 1253 loss: 0.0788 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0788 2022/11/28 19:37:05 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:37:07 - mmengine - INFO - Epoch(train) [13][1500/2462] lr: 1.0680e-02 eta: 0:04:51 time: 0.0347 data_time: 0.0062 memory: 1253 loss: 0.1061 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.1061 2022/11/28 19:37:11 - mmengine - INFO - Epoch(train) [13][1600/2462] lr: 1.0435e-02 eta: 0:04:47 time: 0.0340 data_time: 0.0063 memory: 1253 loss: 0.0932 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0932 2022/11/28 19:37:14 - mmengine - INFO - Epoch(train) [13][1700/2462] lr: 1.0193e-02 eta: 0:04:44 time: 0.0344 data_time: 0.0063 memory: 1253 loss: 0.0772 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0772 2022/11/28 19:37:18 - mmengine - INFO - Epoch(train) [13][1800/2462] lr: 9.9527e-03 eta: 0:04:40 time: 0.0353 data_time: 0.0064 memory: 1253 loss: 0.0912 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0912 2022/11/28 19:37:21 - mmengine - INFO - Epoch(train) [13][1900/2462] lr: 9.7153e-03 eta: 0:04:37 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.0918 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0918 2022/11/28 19:37:24 - mmengine - INFO - Epoch(train) [13][2000/2462] lr: 9.4804e-03 eta: 0:04:33 time: 0.0345 data_time: 0.0062 memory: 1253 loss: 0.0900 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0900 2022/11/28 19:37:28 - mmengine - INFO - Epoch(train) [13][2100/2462] lr: 9.2480e-03 eta: 0:04:30 time: 0.0342 data_time: 0.0062 memory: 1253 loss: 0.0949 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0949 2022/11/28 19:37:31 - mmengine - INFO - Epoch(train) [13][2200/2462] lr: 9.0183e-03 eta: 0:04:26 time: 0.0345 data_time: 0.0067 memory: 1253 loss: 0.0707 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0707 2022/11/28 19:37:35 - mmengine - INFO - Epoch(train) [13][2300/2462] lr: 8.7911e-03 eta: 0:04:23 time: 0.0346 data_time: 0.0062 memory: 1253 loss: 0.1112 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.1112 2022/11/28 19:37:38 - mmengine - INFO - Epoch(train) [13][2400/2462] lr: 8.5666e-03 eta: 0:04:19 time: 0.0342 data_time: 0.0063 memory: 1253 loss: 0.0925 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0925 2022/11/28 19:37:40 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:37:41 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:37:41 - mmengine - INFO - Epoch(train) [13][2462/2462] lr: 8.4287e-03 eta: 0:04:17 time: 0.0342 data_time: 0.0062 memory: 1253 loss: 0.0399 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0399 2022/11/28 19:37:41 - mmengine - INFO - Saving checkpoint at 13 epochs 2022/11/28 19:37:42 - mmengine - INFO - Epoch(val) [13][100/398] eta: 0:00:04 time: 0.0149 data_time: 0.0057 memory: 262 2022/11/28 19:37:44 - mmengine - INFO - Epoch(val) [13][200/398] eta: 0:00:03 time: 0.0152 data_time: 0.0058 memory: 262 2022/11/28 19:37:46 - mmengine - INFO - Epoch(val) [13][300/398] eta: 0:00:01 time: 0.0153 data_time: 0.0059 memory: 262 2022/11/28 19:37:48 - mmengine - INFO - Epoch(val) [13][398/398] acc/top1: 0.7593 acc/top5: 0.9419 acc/mean1: 0.7843 2022/11/28 19:37:48 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_12.pth is removed 2022/11/28 19:37:48 - mmengine - INFO - The best checkpoint with 0.7593 acc/top1 at 13 epoch is saved to best_acc/top1_epoch_13.pth. 2022/11/28 19:37:52 - mmengine - INFO - Epoch(train) [14][100/2462] lr: 8.2085e-03 eta: 0:04:14 time: 0.0345 data_time: 0.0064 memory: 1253 loss: 0.0617 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0617 2022/11/28 19:37:55 - mmengine - INFO - Epoch(train) [14][200/2462] lr: 7.9909e-03 eta: 0:04:10 time: 0.0344 data_time: 0.0063 memory: 1253 loss: 0.0629 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0629 2022/11/28 19:37:59 - mmengine - INFO - Epoch(train) [14][300/2462] lr: 7.7760e-03 eta: 0:04:07 time: 0.0345 data_time: 0.0065 memory: 1253 loss: 0.0570 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0570 2022/11/28 19:38:02 - mmengine - INFO - Epoch(train) [14][400/2462] lr: 7.5638e-03 eta: 0:04:03 time: 0.0345 data_time: 0.0063 memory: 1253 loss: 0.0658 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0658 2022/11/28 19:38:06 - mmengine - INFO - Epoch(train) [14][500/2462] lr: 7.3542e-03 eta: 0:04:00 time: 0.0361 data_time: 0.0062 memory: 1253 loss: 0.0390 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0390 2022/11/28 19:38:10 - mmengine - INFO - Epoch(train) [14][600/2462] lr: 7.1474e-03 eta: 0:03:56 time: 0.0356 data_time: 0.0063 memory: 1253 loss: 0.0704 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.0704 2022/11/28 19:38:13 - mmengine - INFO - Epoch(train) [14][700/2462] lr: 6.9433e-03 eta: 0:03:53 time: 0.0355 data_time: 0.0062 memory: 1253 loss: 0.0792 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0792 2022/11/28 19:38:17 - mmengine - INFO - Epoch(train) [14][800/2462] lr: 6.7420e-03 eta: 0:03:49 time: 0.0355 data_time: 0.0063 memory: 1253 loss: 0.0325 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0325 2022/11/28 19:38:20 - mmengine - INFO - Epoch(train) [14][900/2462] lr: 6.5434e-03 eta: 0:03:46 time: 0.0348 data_time: 0.0062 memory: 1253 loss: 0.0654 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0654 2022/11/28 19:38:24 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:38:24 - mmengine - INFO - Epoch(train) [14][1000/2462] lr: 6.3476e-03 eta: 0:03:42 time: 0.0363 data_time: 0.0062 memory: 1253 loss: 0.0699 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0699 2022/11/28 19:38:27 - mmengine - INFO - Epoch(train) [14][1100/2462] lr: 6.1545e-03 eta: 0:03:39 time: 0.0342 data_time: 0.0062 memory: 1253 loss: 0.0500 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0500 2022/11/28 19:38:31 - mmengine - INFO - Epoch(train) [14][1200/2462] lr: 5.9642e-03 eta: 0:03:35 time: 0.0348 data_time: 0.0062 memory: 1253 loss: 0.0466 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0466 2022/11/28 19:38:34 - mmengine - INFO - Epoch(train) [14][1300/2462] lr: 5.7768e-03 eta: 0:03:32 time: 0.0341 data_time: 0.0061 memory: 1253 loss: 0.0820 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0820 2022/11/28 19:38:38 - mmengine - INFO - Epoch(train) [14][1400/2462] lr: 5.5921e-03 eta: 0:03:28 time: 0.0345 data_time: 0.0063 memory: 1253 loss: 0.0572 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0572 2022/11/28 19:38:41 - mmengine - INFO - Epoch(train) [14][1500/2462] lr: 5.4103e-03 eta: 0:03:25 time: 0.0350 data_time: 0.0063 memory: 1253 loss: 0.0312 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0312 2022/11/28 19:38:45 - mmengine - INFO - Epoch(train) [14][1600/2462] lr: 5.2313e-03 eta: 0:03:21 time: 0.0344 data_time: 0.0063 memory: 1253 loss: 0.0469 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0469 2022/11/28 19:38:48 - mmengine - INFO - Epoch(train) [14][1700/2462] lr: 5.0551e-03 eta: 0:03:18 time: 0.0360 data_time: 0.0062 memory: 1253 loss: 0.0525 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0525 2022/11/28 19:38:52 - mmengine - INFO - Epoch(train) [14][1800/2462] lr: 4.8818e-03 eta: 0:03:14 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.0535 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0535 2022/11/28 19:38:56 - mmengine - INFO - Epoch(train) [14][1900/2462] lr: 4.7114e-03 eta: 0:03:11 time: 0.0354 data_time: 0.0068 memory: 1253 loss: 0.0488 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0488 2022/11/28 19:38:59 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:38:59 - mmengine - INFO - Epoch(train) [14][2000/2462] lr: 4.5439e-03 eta: 0:03:07 time: 0.0358 data_time: 0.0061 memory: 1253 loss: 0.0490 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0490 2022/11/28 19:39:03 - mmengine - INFO - Epoch(train) [14][2100/2462] lr: 4.3792e-03 eta: 0:03:04 time: 0.0349 data_time: 0.0063 memory: 1253 loss: 0.0352 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0352 2022/11/28 19:39:06 - mmengine - INFO - Epoch(train) [14][2200/2462] lr: 4.2175e-03 eta: 0:03:01 time: 0.0349 data_time: 0.0062 memory: 1253 loss: 0.0347 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0347 2022/11/28 19:39:10 - mmengine - INFO - Epoch(train) [14][2300/2462] lr: 4.0587e-03 eta: 0:02:57 time: 0.0344 data_time: 0.0062 memory: 1253 loss: 0.0255 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0255 2022/11/28 19:39:13 - mmengine - INFO - Epoch(train) [14][2400/2462] lr: 3.9027e-03 eta: 0:02:54 time: 0.0349 data_time: 0.0061 memory: 1253 loss: 0.0500 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0500 2022/11/28 19:39:15 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:39:15 - mmengine - INFO - Epoch(train) [14][2462/2462] lr: 3.8075e-03 eta: 0:02:51 time: 0.0344 data_time: 0.0063 memory: 1253 loss: 0.0608 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0608 2022/11/28 19:39:15 - mmengine - INFO - Saving checkpoint at 14 epochs 2022/11/28 19:39:17 - mmengine - INFO - Epoch(val) [14][100/398] eta: 0:00:04 time: 0.0155 data_time: 0.0064 memory: 262 2022/11/28 19:39:19 - mmengine - INFO - Epoch(val) [14][200/398] eta: 0:00:03 time: 0.0151 data_time: 0.0058 memory: 262 2022/11/28 19:39:20 - mmengine - INFO - Epoch(val) [14][300/398] eta: 0:00:01 time: 0.0150 data_time: 0.0058 memory: 262 2022/11/28 19:39:23 - mmengine - INFO - Epoch(val) [14][398/398] acc/top1: 0.7788 acc/top5: 0.9502 acc/mean1: 0.8000 2022/11/28 19:39:23 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_13.pth is removed 2022/11/28 19:39:23 - mmengine - INFO - The best checkpoint with 0.7788 acc/top1 at 14 epoch is saved to best_acc/top1_epoch_14.pth. 2022/11/28 19:39:27 - mmengine - INFO - Epoch(train) [15][100/2462] lr: 3.6564e-03 eta: 0:02:48 time: 0.0366 data_time: 0.0067 memory: 1253 loss: 0.0259 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0259 2022/11/28 19:39:30 - mmengine - INFO - Epoch(train) [15][200/2462] lr: 3.5082e-03 eta: 0:02:44 time: 0.0352 data_time: 0.0062 memory: 1253 loss: 0.0260 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0260 2022/11/28 19:39:34 - mmengine - INFO - Epoch(train) [15][300/2462] lr: 3.3629e-03 eta: 0:02:41 time: 0.0371 data_time: 0.0072 memory: 1253 loss: 0.0384 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0384 2022/11/28 19:39:38 - mmengine - INFO - Epoch(train) [15][400/2462] lr: 3.2206e-03 eta: 0:02:37 time: 0.0348 data_time: 0.0063 memory: 1253 loss: 0.0415 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0415 2022/11/28 19:39:41 - mmengine - INFO - Epoch(train) [15][500/2462] lr: 3.0813e-03 eta: 0:02:34 time: 0.0359 data_time: 0.0062 memory: 1253 loss: 0.0297 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0297 2022/11/28 19:39:42 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:39:45 - mmengine - INFO - Epoch(train) [15][600/2462] lr: 2.9450e-03 eta: 0:02:30 time: 0.0361 data_time: 0.0062 memory: 1253 loss: 0.0349 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0349 2022/11/28 19:39:48 - mmengine - INFO - Epoch(train) [15][700/2462] lr: 2.8117e-03 eta: 0:02:27 time: 0.0344 data_time: 0.0062 memory: 1253 loss: 0.0372 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0372 2022/11/28 19:39:52 - mmengine - INFO - Epoch(train) [15][800/2462] lr: 2.6813e-03 eta: 0:02:24 time: 0.0345 data_time: 0.0062 memory: 1253 loss: 0.0266 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0266 2022/11/28 19:39:55 - mmengine - INFO - Epoch(train) [15][900/2462] lr: 2.5540e-03 eta: 0:02:20 time: 0.0343 data_time: 0.0061 memory: 1253 loss: 0.0461 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0461 2022/11/28 19:39:59 - mmengine - INFO - Epoch(train) [15][1000/2462] lr: 2.4297e-03 eta: 0:02:17 time: 0.0359 data_time: 0.0062 memory: 1253 loss: 0.0438 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0438 2022/11/28 19:40:02 - mmengine - INFO - Epoch(train) [15][1100/2462] lr: 2.3084e-03 eta: 0:02:13 time: 0.0350 data_time: 0.0063 memory: 1253 loss: 0.0319 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0319 2022/11/28 19:40:06 - mmengine - INFO - Epoch(train) [15][1200/2462] lr: 2.1902e-03 eta: 0:02:10 time: 0.0360 data_time: 0.0062 memory: 1253 loss: 0.0500 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0500 2022/11/28 19:40:10 - mmengine - INFO - Epoch(train) [15][1300/2462] lr: 2.0750e-03 eta: 0:02:06 time: 0.0348 data_time: 0.0063 memory: 1253 loss: 0.0344 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0344 2022/11/28 19:40:13 - mmengine - INFO - Epoch(train) [15][1400/2462] lr: 1.9628e-03 eta: 0:02:03 time: 0.0345 data_time: 0.0063 memory: 1253 loss: 0.0289 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0289 2022/11/28 19:40:17 - mmengine - INFO - Epoch(train) [15][1500/2462] lr: 1.8537e-03 eta: 0:01:59 time: 0.0350 data_time: 0.0062 memory: 1253 loss: 0.0295 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0295 2022/11/28 19:40:18 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:40:20 - mmengine - INFO - Epoch(train) [15][1600/2462] lr: 1.7477e-03 eta: 0:01:56 time: 0.0345 data_time: 0.0062 memory: 1253 loss: 0.0431 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0431 2022/11/28 19:40:24 - mmengine - INFO - Epoch(train) [15][1700/2462] lr: 1.6447e-03 eta: 0:01:52 time: 0.0366 data_time: 0.0064 memory: 1253 loss: 0.0502 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0502 2022/11/28 19:40:27 - mmengine - INFO - Epoch(train) [15][1800/2462] lr: 1.5448e-03 eta: 0:01:49 time: 0.0348 data_time: 0.0062 memory: 1253 loss: 0.0515 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0515 2022/11/28 19:40:31 - mmengine - INFO - Epoch(train) [15][1900/2462] lr: 1.4480e-03 eta: 0:01:45 time: 0.0348 data_time: 0.0071 memory: 1253 loss: 0.0302 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0302 2022/11/28 19:40:34 - mmengine - INFO - Epoch(train) [15][2000/2462] lr: 1.3543e-03 eta: 0:01:42 time: 0.0352 data_time: 0.0062 memory: 1253 loss: 0.0446 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0446 2022/11/28 19:40:38 - mmengine - INFO - Epoch(train) [15][2100/2462] lr: 1.2636e-03 eta: 0:01:38 time: 0.0355 data_time: 0.0063 memory: 1253 loss: 0.0355 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0355 2022/11/28 19:40:41 - mmengine - INFO - Epoch(train) [15][2200/2462] lr: 1.1761e-03 eta: 0:01:35 time: 0.0350 data_time: 0.0066 memory: 1253 loss: 0.0319 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0319 2022/11/28 19:40:45 - mmengine - INFO - Epoch(train) [15][2300/2462] lr: 1.0917e-03 eta: 0:01:31 time: 0.0358 data_time: 0.0062 memory: 1253 loss: 0.0250 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0250 2022/11/28 19:40:48 - mmengine - INFO - Epoch(train) [15][2400/2462] lr: 1.0104e-03 eta: 0:01:28 time: 0.0364 data_time: 0.0062 memory: 1253 loss: 0.0280 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0280 2022/11/28 19:40:51 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:40:51 - mmengine - INFO - Epoch(train) [15][2462/2462] lr: 9.6151e-04 eta: 0:01:26 time: 0.0350 data_time: 0.0063 memory: 1253 loss: 0.0195 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0195 2022/11/28 19:40:51 - mmengine - INFO - Saving checkpoint at 15 epochs 2022/11/28 19:40:53 - mmengine - INFO - Epoch(val) [15][100/398] eta: 0:00:04 time: 0.0149 data_time: 0.0057 memory: 262 2022/11/28 19:40:54 - mmengine - INFO - Epoch(val) [15][200/398] eta: 0:00:03 time: 0.0157 data_time: 0.0063 memory: 262 2022/11/28 19:40:56 - mmengine - INFO - Epoch(val) [15][300/398] eta: 0:00:01 time: 0.0152 data_time: 0.0059 memory: 262 2022/11/28 19:40:58 - mmengine - INFO - Epoch(val) [15][398/398] acc/top1: 0.7827 acc/top5: 0.9509 acc/mean1: 0.8052 2022/11/28 19:40:58 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_14.pth is removed 2022/11/28 19:40:58 - mmengine - INFO - The best checkpoint with 0.7827 acc/top1 at 15 epoch is saved to best_acc/top1_epoch_15.pth. 2022/11/28 19:41:01 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:41:02 - mmengine - INFO - Epoch(train) [16][100/2462] lr: 8.8525e-04 eta: 0:01:22 time: 0.0363 data_time: 0.0063 memory: 1253 loss: 0.0247 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0247 2022/11/28 19:41:06 - mmengine - INFO - Epoch(train) [16][200/2462] lr: 8.1211e-04 eta: 0:01:19 time: 0.0352 data_time: 0.0063 memory: 1253 loss: 0.0344 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0344 2022/11/28 19:41:09 - mmengine - INFO - Epoch(train) [16][300/2462] lr: 7.4209e-04 eta: 0:01:15 time: 0.0359 data_time: 0.0071 memory: 1253 loss: 0.0206 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0206 2022/11/28 19:41:13 - mmengine - INFO - Epoch(train) [16][400/2462] lr: 6.7522e-04 eta: 0:01:12 time: 0.0345 data_time: 0.0063 memory: 1253 loss: 0.0341 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0341 2022/11/28 19:41:16 - mmengine - INFO - Epoch(train) [16][500/2462] lr: 6.1147e-04 eta: 0:01:08 time: 0.0345 data_time: 0.0062 memory: 1253 loss: 0.0332 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0332 2022/11/28 19:41:20 - mmengine - INFO - Epoch(train) [16][600/2462] lr: 5.5087e-04 eta: 0:01:05 time: 0.0349 data_time: 0.0063 memory: 1253 loss: 0.0199 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0199 2022/11/28 19:41:23 - mmengine - INFO - Epoch(train) [16][700/2462] lr: 4.9342e-04 eta: 0:01:01 time: 0.0359 data_time: 0.0064 memory: 1253 loss: 0.0128 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0128 2022/11/28 19:41:27 - mmengine - INFO - Epoch(train) [16][800/2462] lr: 4.3911e-04 eta: 0:00:58 time: 0.0347 data_time: 0.0065 memory: 1253 loss: 0.0238 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0238 2022/11/28 19:41:30 - mmengine - INFO - Epoch(train) [16][900/2462] lr: 3.8795e-04 eta: 0:00:54 time: 0.0345 data_time: 0.0064 memory: 1253 loss: 0.0327 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0327 2022/11/28 19:41:34 - mmengine - INFO - Epoch(train) [16][1000/2462] lr: 3.3995e-04 eta: 0:00:51 time: 0.0347 data_time: 0.0063 memory: 1253 loss: 0.0205 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0205 2022/11/28 19:41:36 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:41:37 - mmengine - INFO - Epoch(train) [16][1100/2462] lr: 2.9511e-04 eta: 0:00:47 time: 0.0343 data_time: 0.0062 memory: 1253 loss: 0.0324 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0324 2022/11/28 19:41:41 - mmengine - INFO - Epoch(train) [16][1200/2462] lr: 2.5343e-04 eta: 0:00:44 time: 0.0365 data_time: 0.0062 memory: 1253 loss: 0.0238 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0238 2022/11/28 19:41:45 - mmengine - INFO - Epoch(train) [16][1300/2462] lr: 2.1492e-04 eta: 0:00:40 time: 0.0346 data_time: 0.0063 memory: 1253 loss: 0.0204 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0204 2022/11/28 19:41:48 - mmengine - INFO - Epoch(train) [16][1400/2462] lr: 1.7957e-04 eta: 0:00:37 time: 0.0362 data_time: 0.0062 memory: 1253 loss: 0.0149 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0149 2022/11/28 19:41:52 - mmengine - INFO - Epoch(train) [16][1500/2462] lr: 1.4739e-04 eta: 0:00:33 time: 0.0347 data_time: 0.0063 memory: 1253 loss: 0.0233 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0233 2022/11/28 19:41:55 - mmengine - INFO - Epoch(train) [16][1600/2462] lr: 1.1838e-04 eta: 0:00:30 time: 0.0372 data_time: 0.0068 memory: 1253 loss: 0.0229 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0229 2022/11/28 19:41:59 - mmengine - INFO - Epoch(train) [16][1700/2462] lr: 9.2542e-05 eta: 0:00:26 time: 0.0351 data_time: 0.0065 memory: 1253 loss: 0.0183 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0183 2022/11/28 19:42:03 - mmengine - INFO - Epoch(train) [16][1800/2462] lr: 6.9879e-05 eta: 0:00:23 time: 0.0370 data_time: 0.0067 memory: 1253 loss: 0.0274 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0274 2022/11/28 19:42:06 - mmengine - INFO - Epoch(train) [16][1900/2462] lr: 5.0393e-05 eta: 0:00:19 time: 0.0354 data_time: 0.0068 memory: 1253 loss: 0.0203 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0203 2022/11/28 19:42:10 - mmengine - INFO - Epoch(train) [16][2000/2462] lr: 3.4083e-05 eta: 0:00:16 time: 0.0371 data_time: 0.0066 memory: 1253 loss: 0.0171 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0171 2022/11/28 19:42:12 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:42:13 - mmengine - INFO - Epoch(train) [16][2100/2462] lr: 2.0951e-05 eta: 0:00:12 time: 0.0353 data_time: 0.0061 memory: 1253 loss: 0.0267 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0267 2022/11/28 19:42:17 - mmengine - INFO - Epoch(train) [16][2200/2462] lr: 1.0998e-05 eta: 0:00:09 time: 0.0359 data_time: 0.0064 memory: 1253 loss: 0.0297 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.0297 2022/11/28 19:42:20 - mmengine - INFO - Epoch(train) [16][2300/2462] lr: 4.2247e-06 eta: 0:00:05 time: 0.0374 data_time: 0.0065 memory: 1253 loss: 0.0369 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0369 2022/11/28 19:42:24 - mmengine - INFO - Epoch(train) [16][2400/2462] lr: 6.3111e-07 eta: 0:00:02 time: 0.0362 data_time: 0.0069 memory: 1253 loss: 0.0253 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0253 2022/11/28 19:42:26 - mmengine - INFO - Exp name: stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d_20221128_191539 2022/11/28 19:42:26 - mmengine - INFO - Epoch(train) [16][2462/2462] lr: 1.5901e-10 eta: 0:00:00 time: 0.0348 data_time: 0.0064 memory: 1253 loss: 0.0263 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.0263 2022/11/28 19:42:26 - mmengine - INFO - Saving checkpoint at 16 epochs 2022/11/28 19:42:28 - mmengine - INFO - Epoch(val) [16][100/398] eta: 0:00:04 time: 0.0150 data_time: 0.0058 memory: 262 2022/11/28 19:42:30 - mmengine - INFO - Epoch(val) [16][200/398] eta: 0:00:03 time: 0.0150 data_time: 0.0058 memory: 262 2022/11/28 19:42:31 - mmengine - INFO - Epoch(val) [16][300/398] eta: 0:00:01 time: 0.0151 data_time: 0.0058 memory: 262 2022/11/28 19:42:34 - mmengine - INFO - Epoch(val) [16][398/398] acc/top1: 0.7830 acc/top5: 0.9503 acc/mean1: 0.8059 2022/11/28 19:42:34 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/daiwenxun/mmlab/mmaction2/work_dirs/stgcn_8xb16-joint-motion-u100-80e_ntu120-xsub-keypoint-2d/best_acc/top1_epoch_15.pth is removed 2022/11/28 19:42:34 - mmengine - INFO - The best checkpoint with 0.7830 acc/top1 at 16 epoch is saved to best_acc/top1_epoch_16.pth.