diff --git "a/finegym/jm/20250624_101434.log" "b/finegym/jm/20250624_101434.log" new file mode 100644--- /dev/null +++ "b/finegym/jm/20250624_101434.log" @@ -0,0 +1,3486 @@ +2025-06-24 10:14:34,378 - pyskl - INFO - Environment info: +------------------------------------------------------------ +sys.platform: linux +Python: 3.7.11 (default, Jul 27 2021, 14:32:16) [GCC 7.5.0] +CUDA available: True +GPU 0: Tesla V100-PCIE-32GB +CUDA_HOME: /usr/local/cuda-11.7 +NVCC: Cuda compilation tools, release 11.7, V11.7.64 +GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0 +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: 4.8.0 +MMCV: 1.5.0 +MMCV Compiler: GCC 7.3 +MMCV CUDA Compiler: 11.3 +pyskl: 0.1.0+ +------------------------------------------------------------ + +2025-06-24 10:14:34,679 - pyskl - INFO - Config: modality = 'jm' +graph = 'coco_new' +work_dir = './work_dirs/test_aclnet/finegym/jm' +model = dict( + type='RecognizerGCN', + backbone=dict( + type='GCN_Module', + gcn_ratio=0.125, + gcn_ctr='T', + gcn_ada='T', + tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'], + graph_cfg=dict( + layout='coco_new', + mode='random', + num_filter=8, + init_off=0.04, + init_std=0.02)), + cls_head=dict(type='SimpleHead', data_cfg='finegym', num_classes=99, in_channels=384)) +dataset_type = 'PoseDataset' +ann_file = '/data/lhd/pyskl_data/gym/gym_hrnet.pkl' +left_kp = [1, 3, 5, 7, 9, 11, 13, 15] +right_kp = [2, 4, 6, 8, 10, 12, 14, 16] +train_pipeline = [ + dict(type='UniformSampleFrames', clip_len=100), + dict(type='PoseDecode'), + dict( + type='Flip', + flip_ratio=0.5, + left_kp=[1, 3, 5, 7, 9, 11, 13, 15], + right_kp=[2, 4, 6, 8, 10, 12, 14, 16]), + dict(type='Kinetics_Transform'), + dict(type='GenSkeFeat', dataset='coco_new', feats=['jm']), + dict(type='FormatGCNInput', num_person=2), + dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]), + dict(type='ToTensor', keys=['keypoint']) +] +val_pipeline = [ + dict(type='UniformSampleFrames', clip_len=100, num_clips=1), + dict(type='PoseDecode'), + dict(type='Kinetics_Transform'), + dict(type='GenSkeFeat', dataset='coco_new', feats=['jm']), + dict(type='FormatGCNInput', num_person=2), + dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]), + dict(type='ToTensor', keys=['keypoint']) +] +test_pipeline = [ + dict(type='UniformSampleFrames', clip_len=100, num_clips=10), + dict(type='PoseDecode'), + dict(type='Kinetics_Transform'), + dict(type='GenSkeFeat', dataset='coco_new', feats=['jm']), + dict(type='FormatGCNInput', num_person=2), + dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]), + dict(type='ToTensor', keys=['keypoint']) +] +data = dict( + videos_per_gpu=16, + workers_per_gpu=4, + test_dataloader=dict(videos_per_gpu=1), + train=dict( + type='PoseDataset', + ann_file='/data/lhd/pyskl_data/gym/gym_hrnet.pkl', + pipeline=[ + dict(type='UniformSampleFrames', clip_len=100), + dict(type='PoseDecode'), + dict( + type='Flip', + flip_ratio=0.5, + left_kp=[1, 3, 5, 7, 9, 11, 13, 15], + right_kp=[2, 4, 6, 8, 10, 12, 14, 16]), + dict(type='Kinetics_Transform'), + dict(type='GenSkeFeat', dataset='coco_new', feats=['jm']), + dict(type='FormatGCNInput', num_person=2), + dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]), + dict(type='ToTensor', keys=['keypoint']) + ], + split='train'), + val=dict( + type='PoseDataset', + ann_file='/data/lhd/pyskl_data/gym/gym_hrnet.pkl', + pipeline=[ + dict(type='UniformSampleFrames', clip_len=100, num_clips=1), + dict(type='PoseDecode'), + dict(type='Kinetics_Transform'), + dict(type='GenSkeFeat', dataset='coco_new', feats=['jm']), + dict(type='FormatGCNInput', num_person=2), + dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]), + dict(type='ToTensor', keys=['keypoint']) + ], + split='val'), + test=dict( + type='PoseDataset', + ann_file='/data/lhd/pyskl_data/gym/gym_hrnet.pkl', + pipeline=[ + dict(type='UniformSampleFrames', clip_len=100, num_clips=10), + dict(type='PoseDecode'), + dict(type='Kinetics_Transform'), + dict(type='GenSkeFeat', dataset='coco_new', feats=['jm']), + dict(type='FormatGCNInput', num_person=2), + dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]), + dict(type='ToTensor', keys=['keypoint']) + ], + split='val')) +optimizer = dict( + type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True) +optimizer_config = dict(grad_clip=None) +lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False) +total_epochs = 150 +checkpoint_config = dict(interval=1) +evaluation = dict( + interval=1, metrics=['top_k_accuracy', 'mean_class_accuracy'], topk=(1, 5)) +log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')]) +dist_params = dict(backend='nccl') +gpu_ids = range(0, 1) + +2025-06-24 10:14:34,680 - pyskl - INFO - Set random seed to 1178020540, deterministic: False +2025-06-24 10:14:36,228 - pyskl - INFO - 20484 videos remain after valid thresholding +2025-06-24 10:14:42,100 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-06-24 10:14:42,101 - pyskl - INFO - Start running, host: lhd@zkyd, work_dir: /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm +2025-06-24 10:14:42,101 - pyskl - INFO - Hooks will be executed in the following order: +before_run: +(VERY_HIGH ) CosineAnnealingLrUpdaterHook +(NORMAL ) CustomCheckpointHook +(NORMAL ) DistEvalHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_train_epoch: +(VERY_HIGH ) CosineAnnealingLrUpdaterHook +(NORMAL ) DistSamplerSeedHook +(NORMAL ) DistEvalHook +(LOW ) IterTimerHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_train_iter: +(VERY_HIGH ) CosineAnnealingLrUpdaterHook +(NORMAL ) DistEvalHook +(LOW ) IterTimerHook + -------------------- +after_train_iter: +(ABOVE_NORMAL) OptimizerHook +(NORMAL ) CustomCheckpointHook +(NORMAL ) DistEvalHook +(LOW ) IterTimerHook +(VERY_LOW ) TextLoggerHook + -------------------- +after_train_epoch: +(NORMAL ) CustomCheckpointHook +(NORMAL ) DistEvalHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_val_epoch: +(NORMAL ) DistSamplerSeedHook +(LOW ) IterTimerHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_val_iter: +(LOW ) IterTimerHook + -------------------- +after_val_iter: +(LOW ) IterTimerHook + -------------------- +after_val_epoch: +(VERY_LOW ) TextLoggerHook + -------------------- +after_run: +(VERY_LOW ) TextLoggerHook + -------------------- +2025-06-24 10:14:42,101 - pyskl - INFO - workflow: [('train', 1)], max: 150 epochs +2025-06-24 10:14:42,101 - pyskl - INFO - Checkpoints will be saved to /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm by HardDiskBackend. +2025-06-24 10:15:44,403 - pyskl - INFO - Epoch [1][100/1281] lr: 2.500e-02, eta: 1 day, 9:14:00, time: 0.623, data_time: 0.199, memory: 4082, top1_acc: 0.0606, top5_acc: 0.1988, loss_cls: 4.6087, loss: 4.6087 +2025-06-24 10:16:26,118 - pyskl - INFO - Epoch [1][200/1281] lr: 2.500e-02, eta: 1 day, 3:43:43, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.0688, top5_acc: 0.2838, loss_cls: 4.6863, loss: 4.6863 +2025-06-24 10:17:07,794 - pyskl - INFO - Epoch [1][300/1281] lr: 2.500e-02, eta: 1 day, 1:52:45, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.1100, top5_acc: 0.3262, loss_cls: 4.5120, loss: 4.5120 +2025-06-24 10:17:49,265 - pyskl - INFO - Epoch [1][400/1281] lr: 2.500e-02, eta: 1 day, 0:55:18, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.1031, top5_acc: 0.3650, loss_cls: 4.3571, loss: 4.3571 +2025-06-24 10:18:30,728 - pyskl - INFO - Epoch [1][500/1281] lr: 2.500e-02, eta: 1 day, 0:20:28, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.1494, top5_acc: 0.3906, loss_cls: 4.2050, loss: 4.2050 +2025-06-24 10:19:12,294 - pyskl - INFO - Epoch [1][600/1281] lr: 2.500e-02, eta: 23:57:35, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.1575, top5_acc: 0.4531, loss_cls: 4.0568, loss: 4.0568 +2025-06-24 10:19:54,019 - pyskl - INFO - Epoch [1][700/1281] lr: 2.500e-02, eta: 23:41:46, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.2100, top5_acc: 0.5238, loss_cls: 3.7875, loss: 3.7875 +2025-06-24 10:20:35,514 - pyskl - INFO - Epoch [1][800/1281] lr: 2.500e-02, eta: 23:28:48, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.2375, top5_acc: 0.5994, loss_cls: 3.4488, loss: 3.4488 +2025-06-24 10:21:17,024 - pyskl - INFO - Epoch [1][900/1281] lr: 2.500e-02, eta: 23:18:38, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.2712, top5_acc: 0.6194, loss_cls: 3.2879, loss: 3.2879 +2025-06-24 10:21:58,619 - pyskl - INFO - Epoch [1][1000/1281] lr: 2.500e-02, eta: 23:10:37, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.2712, top5_acc: 0.6475, loss_cls: 3.1791, loss: 3.1791 +2025-06-24 10:22:40,239 - pyskl - INFO - Epoch [1][1100/1281] lr: 2.500e-02, eta: 23:04:01, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.3350, top5_acc: 0.7037, loss_cls: 2.9595, loss: 2.9595 +2025-06-24 10:23:05,888 - pyskl - INFO - Epoch [1][1200/1281] lr: 2.500e-02, eta: 22:16:02, time: 0.256, data_time: 0.000, memory: 4082, top1_acc: 0.3369, top5_acc: 0.7113, loss_cls: 2.9039, loss: 2.9039 +2025-06-24 10:23:43,396 - pyskl - INFO - Saving checkpoint at 1 epochs +2025-06-24 10:24:47,207 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:24:47,263 - pyskl - INFO - +top1_acc 0.2720 +top5_acc 0.6755 +2025-06-24 10:24:47,263 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:24:47,270 - pyskl - INFO - +mean_acc 0.1362 +2025-06-24 10:24:47,437 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_1.pth. +2025-06-24 10:24:47,437 - pyskl - INFO - Best top1_acc is 0.2720 at 1 epoch. +2025-06-24 10:24:47,440 - pyskl - INFO - Epoch(val) [1][533] top1_acc: 0.2720, top5_acc: 0.6755, mean_class_accuracy: 0.1362 +2025-06-24 10:25:48,656 - pyskl - INFO - Epoch [2][100/1281] lr: 2.500e-02, eta: 21:40:45, time: 0.612, data_time: 0.195, memory: 4082, top1_acc: 0.3831, top5_acc: 0.7706, loss_cls: 2.6356, loss: 2.6356 +2025-06-24 10:26:30,333 - pyskl - INFO - Epoch [2][200/1281] lr: 2.500e-02, eta: 21:41:43, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.4138, top5_acc: 0.7900, loss_cls: 2.4917, loss: 2.4917 +2025-06-24 10:27:11,919 - pyskl - INFO - Epoch [2][300/1281] lr: 2.500e-02, eta: 21:42:17, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.3944, top5_acc: 0.7950, loss_cls: 2.4871, loss: 2.4871 +2025-06-24 10:27:53,525 - pyskl - INFO - Epoch [2][400/1281] lr: 2.500e-02, eta: 21:42:44, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.4575, top5_acc: 0.8244, loss_cls: 2.3178, loss: 2.3178 +2025-06-24 10:28:35,189 - pyskl - INFO - Epoch [2][500/1281] lr: 2.499e-02, eta: 21:43:10, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.4288, top5_acc: 0.8387, loss_cls: 2.3096, loss: 2.3096 +2025-06-24 10:29:17,059 - pyskl - INFO - Epoch [2][600/1281] lr: 2.499e-02, eta: 21:43:49, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.4631, top5_acc: 0.8581, loss_cls: 2.1788, loss: 2.1788 +2025-06-24 10:29:58,869 - pyskl - INFO - Epoch [2][700/1281] lr: 2.499e-02, eta: 21:44:15, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.4225, top5_acc: 0.8450, loss_cls: 2.3018, loss: 2.3018 +2025-06-24 10:30:40,524 - pyskl - INFO - Epoch [2][800/1281] lr: 2.499e-02, eta: 21:44:20, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.4694, top5_acc: 0.8875, loss_cls: 2.0834, loss: 2.0834 +2025-06-24 10:31:22,999 - pyskl - INFO - Epoch [2][900/1281] lr: 2.499e-02, eta: 21:45:32, time: 0.425, data_time: 0.000, memory: 4082, top1_acc: 0.4775, top5_acc: 0.8706, loss_cls: 2.0662, loss: 2.0662 +2025-06-24 10:32:06,323 - pyskl - INFO - Epoch [2][1000/1281] lr: 2.499e-02, eta: 21:47:44, time: 0.433, data_time: 0.000, memory: 4082, top1_acc: 0.4900, top5_acc: 0.8956, loss_cls: 2.0584, loss: 2.0584 +2025-06-24 10:32:48,720 - pyskl - INFO - Epoch [2][1100/1281] lr: 2.499e-02, eta: 21:48:28, time: 0.424, data_time: 0.000, memory: 4082, top1_acc: 0.4956, top5_acc: 0.8888, loss_cls: 2.0153, loss: 2.0153 +2025-06-24 10:33:14,911 - pyskl - INFO - Epoch [2][1200/1281] lr: 2.499e-02, eta: 21:28:26, time: 0.262, data_time: 0.000, memory: 4082, top1_acc: 0.5050, top5_acc: 0.8875, loss_cls: 1.9377, loss: 1.9377 +2025-06-24 10:33:52,621 - pyskl - INFO - Saving checkpoint at 2 epochs +2025-06-24 10:34:57,024 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:34:57,081 - pyskl - INFO - +top1_acc 0.4342 +top5_acc 0.8507 +2025-06-24 10:34:57,081 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:34:57,088 - pyskl - INFO - +mean_acc 0.2392 +2025-06-24 10:34:57,092 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_1.pth was removed +2025-06-24 10:34:57,293 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_2.pth. +2025-06-24 10:34:57,294 - pyskl - INFO - Best top1_acc is 0.4342 at 2 epoch. +2025-06-24 10:34:57,297 - pyskl - INFO - Epoch(val) [2][533] top1_acc: 0.4342, top5_acc: 0.8507, mean_class_accuracy: 0.2392 +2025-06-24 10:36:00,816 - pyskl - INFO - Epoch [3][100/1281] lr: 2.499e-02, eta: 21:15:02, time: 0.635, data_time: 0.198, memory: 4082, top1_acc: 0.4875, top5_acc: 0.8894, loss_cls: 1.9883, loss: 1.9883 +2025-06-24 10:36:42,708 - pyskl - INFO - Epoch [3][200/1281] lr: 2.499e-02, eta: 21:16:06, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.5150, top5_acc: 0.8981, loss_cls: 1.9194, loss: 1.9194 +2025-06-24 10:37:24,303 - pyskl - INFO - Epoch [3][300/1281] lr: 2.499e-02, eta: 21:16:42, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.5225, top5_acc: 0.9244, loss_cls: 1.8270, loss: 1.8270 +2025-06-24 10:38:05,676 - pyskl - INFO - Epoch [3][400/1281] lr: 2.499e-02, eta: 21:16:59, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.5594, top5_acc: 0.8988, loss_cls: 1.8624, loss: 1.8624 +2025-06-24 10:38:47,292 - pyskl - INFO - Epoch [3][500/1281] lr: 2.498e-02, eta: 21:17:28, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.5387, top5_acc: 0.9206, loss_cls: 1.7888, loss: 1.7888 +2025-06-24 10:39:28,781 - pyskl - INFO - Epoch [3][600/1281] lr: 2.498e-02, eta: 21:17:44, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.5406, top5_acc: 0.9419, loss_cls: 1.7638, loss: 1.7638 +2025-06-24 10:40:10,242 - pyskl - INFO - Epoch [3][700/1281] lr: 2.498e-02, eta: 21:17:55, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.5619, top5_acc: 0.9144, loss_cls: 1.7412, loss: 1.7412 +2025-06-24 10:40:51,698 - pyskl - INFO - Epoch [3][800/1281] lr: 2.498e-02, eta: 21:18:03, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.5825, top5_acc: 0.9363, loss_cls: 1.6820, loss: 1.6820 +2025-06-24 10:41:33,206 - pyskl - INFO - Epoch [3][900/1281] lr: 2.498e-02, eta: 21:18:11, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.5594, top5_acc: 0.9287, loss_cls: 1.7365, loss: 1.7365 +2025-06-24 10:42:15,433 - pyskl - INFO - Epoch [3][1000/1281] lr: 2.498e-02, eta: 21:18:54, time: 0.422, data_time: 0.000, memory: 4082, top1_acc: 0.5787, top5_acc: 0.9300, loss_cls: 1.6970, loss: 1.6970 +2025-06-24 10:42:56,804 - pyskl - INFO - Epoch [3][1100/1281] lr: 2.498e-02, eta: 21:18:49, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.5625, top5_acc: 0.9256, loss_cls: 1.7353, loss: 1.7353 +2025-06-24 10:43:23,676 - pyskl - INFO - Epoch [3][1200/1281] lr: 2.498e-02, eta: 21:06:35, time: 0.269, data_time: 0.000, memory: 4082, top1_acc: 0.5863, top5_acc: 0.9350, loss_cls: 1.6415, loss: 1.6415 +2025-06-24 10:44:00,960 - pyskl - INFO - Saving checkpoint at 3 epochs +2025-06-24 10:45:06,321 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:45:06,390 - pyskl - INFO - +top1_acc 0.5509 +top5_acc 0.9161 +2025-06-24 10:45:06,391 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:45:06,399 - pyskl - INFO - +mean_acc 0.3698 +2025-06-24 10:45:06,404 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_2.pth was removed +2025-06-24 10:45:06,612 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_3.pth. +2025-06-24 10:45:06,612 - pyskl - INFO - Best top1_acc is 0.5509 at 3 epoch. +2025-06-24 10:45:06,615 - pyskl - INFO - Epoch(val) [3][533] top1_acc: 0.5509, top5_acc: 0.9161, mean_class_accuracy: 0.3698 +2025-06-24 10:46:08,245 - pyskl - INFO - Epoch [4][100/1281] lr: 2.497e-02, eta: 20:56:18, time: 0.616, data_time: 0.201, memory: 4082, top1_acc: 0.5944, top5_acc: 0.9481, loss_cls: 1.6106, loss: 1.6106 +2025-06-24 10:46:49,707 - pyskl - INFO - Epoch [4][200/1281] lr: 2.497e-02, eta: 20:56:44, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.5894, top5_acc: 0.9463, loss_cls: 1.5935, loss: 1.5935 +2025-06-24 10:47:31,245 - pyskl - INFO - Epoch [4][300/1281] lr: 2.497e-02, eta: 20:57:09, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.5962, top5_acc: 0.9369, loss_cls: 1.5912, loss: 1.5912 +2025-06-24 10:48:12,755 - pyskl - INFO - Epoch [4][400/1281] lr: 2.497e-02, eta: 20:57:31, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6081, top5_acc: 0.9563, loss_cls: 1.4982, loss: 1.4982 +2025-06-24 10:48:54,333 - pyskl - INFO - Epoch [4][500/1281] lr: 2.497e-02, eta: 20:57:52, time: 0.416, data_time: 0.001, memory: 4082, top1_acc: 0.6044, top5_acc: 0.9513, loss_cls: 1.5454, loss: 1.5454 +2025-06-24 10:49:35,831 - pyskl - INFO - Epoch [4][600/1281] lr: 2.497e-02, eta: 20:58:07, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6088, top5_acc: 0.9463, loss_cls: 1.5437, loss: 1.5437 +2025-06-24 10:50:17,384 - pyskl - INFO - Epoch [4][700/1281] lr: 2.497e-02, eta: 20:58:22, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.5938, top5_acc: 0.9500, loss_cls: 1.5752, loss: 1.5752 +2025-06-24 10:50:58,907 - pyskl - INFO - Epoch [4][800/1281] lr: 2.496e-02, eta: 20:58:34, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6281, top5_acc: 0.9494, loss_cls: 1.4871, loss: 1.4871 +2025-06-24 10:51:40,479 - pyskl - INFO - Epoch [4][900/1281] lr: 2.496e-02, eta: 20:58:45, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.6169, top5_acc: 0.9563, loss_cls: 1.5108, loss: 1.5108 +2025-06-24 10:52:21,992 - pyskl - INFO - Epoch [4][1000/1281] lr: 2.496e-02, eta: 20:58:51, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6162, top5_acc: 0.9506, loss_cls: 1.5131, loss: 1.5131 +2025-06-24 10:53:02,029 - pyskl - INFO - Epoch [4][1100/1281] lr: 2.496e-02, eta: 20:58:00, time: 0.400, data_time: 0.000, memory: 4082, top1_acc: 0.6081, top5_acc: 0.9556, loss_cls: 1.4998, loss: 1.4998 +2025-06-24 10:53:30,258 - pyskl - INFO - Epoch [4][1200/1281] lr: 2.496e-02, eta: 20:49:51, time: 0.282, data_time: 0.001, memory: 4082, top1_acc: 0.6138, top5_acc: 0.9600, loss_cls: 1.4727, loss: 1.4727 +2025-06-24 10:54:07,690 - pyskl - INFO - Saving checkpoint at 4 epochs +2025-06-24 10:55:16,334 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:55:16,400 - pyskl - INFO - +top1_acc 0.5601 +top5_acc 0.9313 +2025-06-24 10:55:16,400 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:55:16,408 - pyskl - INFO - +mean_acc 0.4340 +2025-06-24 10:55:16,413 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_3.pth was removed +2025-06-24 10:55:16,667 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_4.pth. +2025-06-24 10:55:16,667 - pyskl - INFO - Best top1_acc is 0.5601 at 4 epoch. +2025-06-24 10:55:16,670 - pyskl - INFO - Epoch(val) [4][533] top1_acc: 0.5601, top5_acc: 0.9313, mean_class_accuracy: 0.4340 +2025-06-24 10:56:20,751 - pyskl - INFO - Epoch [5][100/1281] lr: 2.495e-02, eta: 20:43:35, time: 0.641, data_time: 0.202, memory: 4082, top1_acc: 0.6169, top5_acc: 0.9594, loss_cls: 1.4467, loss: 1.4467 +2025-06-24 10:57:02,550 - pyskl - INFO - Epoch [5][200/1281] lr: 2.495e-02, eta: 20:44:02, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.6394, top5_acc: 0.9619, loss_cls: 1.3867, loss: 1.3867 +2025-06-24 10:57:43,959 - pyskl - INFO - Epoch [5][300/1281] lr: 2.495e-02, eta: 20:44:12, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.6356, top5_acc: 0.9619, loss_cls: 1.4081, loss: 1.4081 +2025-06-24 10:58:25,327 - pyskl - INFO - Epoch [5][400/1281] lr: 2.495e-02, eta: 20:44:19, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.6562, top5_acc: 0.9600, loss_cls: 1.3816, loss: 1.3816 +2025-06-24 10:59:06,758 - pyskl - INFO - Epoch [5][500/1281] lr: 2.495e-02, eta: 20:44:26, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.6462, top5_acc: 0.9675, loss_cls: 1.3707, loss: 1.3707 +2025-06-24 10:59:48,195 - pyskl - INFO - Epoch [5][600/1281] lr: 2.495e-02, eta: 20:44:32, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.6519, top5_acc: 0.9644, loss_cls: 1.4061, loss: 1.4061 +2025-06-24 11:00:29,626 - pyskl - INFO - Epoch [5][700/1281] lr: 2.494e-02, eta: 20:44:36, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.6300, top5_acc: 0.9631, loss_cls: 1.4142, loss: 1.4142 +2025-06-24 11:01:11,096 - pyskl - INFO - Epoch [5][800/1281] lr: 2.494e-02, eta: 20:44:39, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6544, top5_acc: 0.9613, loss_cls: 1.3797, loss: 1.3797 +2025-06-24 11:01:52,682 - pyskl - INFO - Epoch [5][900/1281] lr: 2.494e-02, eta: 20:44:45, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.6706, top5_acc: 0.9669, loss_cls: 1.3090, loss: 1.3090 +2025-06-24 11:02:34,061 - pyskl - INFO - Epoch [5][1000/1281] lr: 2.494e-02, eta: 20:44:43, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.6575, top5_acc: 0.9631, loss_cls: 1.3704, loss: 1.3704 +2025-06-24 11:03:12,407 - pyskl - INFO - Epoch [5][1100/1281] lr: 2.494e-02, eta: 20:43:09, time: 0.383, data_time: 0.001, memory: 4082, top1_acc: 0.6406, top5_acc: 0.9594, loss_cls: 1.4377, loss: 1.4377 +2025-06-24 11:03:42,221 - pyskl - INFO - Epoch [5][1200/1281] lr: 2.493e-02, eta: 20:37:26, time: 0.298, data_time: 0.000, memory: 4082, top1_acc: 0.6594, top5_acc: 0.9637, loss_cls: 1.3650, loss: 1.3650 +2025-06-24 11:04:19,660 - pyskl - INFO - Saving checkpoint at 5 epochs +2025-06-24 11:05:28,856 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:05:28,925 - pyskl - INFO - +top1_acc 0.6533 +top5_acc 0.9586 +2025-06-24 11:05:28,925 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:05:28,933 - pyskl - INFO - +mean_acc 0.5117 +2025-06-24 11:05:28,937 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_4.pth was removed +2025-06-24 11:05:29,162 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_5.pth. +2025-06-24 11:05:29,162 - pyskl - INFO - Best top1_acc is 0.6533 at 5 epoch. +2025-06-24 11:05:29,166 - pyskl - INFO - Epoch(val) [5][533] top1_acc: 0.6533, top5_acc: 0.9586, mean_class_accuracy: 0.5117 +2025-06-24 11:06:30,077 - pyskl - INFO - Epoch [6][100/1281] lr: 2.493e-02, eta: 20:30:48, time: 0.609, data_time: 0.193, memory: 4082, top1_acc: 0.6900, top5_acc: 0.9688, loss_cls: 1.2917, loss: 1.2917 +2025-06-24 11:07:11,651 - pyskl - INFO - Epoch [6][200/1281] lr: 2.493e-02, eta: 20:30:59, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.6837, top5_acc: 0.9656, loss_cls: 1.2952, loss: 1.2952 +2025-06-24 11:07:53,195 - pyskl - INFO - Epoch [6][300/1281] lr: 2.492e-02, eta: 20:31:07, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6881, top5_acc: 0.9681, loss_cls: 1.2876, loss: 1.2876 +2025-06-24 11:08:34,585 - pyskl - INFO - Epoch [6][400/1281] lr: 2.492e-02, eta: 20:31:09, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.6956, top5_acc: 0.9681, loss_cls: 1.2804, loss: 1.2804 +2025-06-24 11:09:16,254 - pyskl - INFO - Epoch [6][500/1281] lr: 2.492e-02, eta: 20:31:18, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.6756, top5_acc: 0.9669, loss_cls: 1.3109, loss: 1.3109 +2025-06-24 11:09:57,849 - pyskl - INFO - Epoch [6][600/1281] lr: 2.492e-02, eta: 20:31:23, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.6562, top5_acc: 0.9656, loss_cls: 1.3498, loss: 1.3498 +2025-06-24 11:10:39,314 - pyskl - INFO - Epoch [6][700/1281] lr: 2.492e-02, eta: 20:31:24, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6819, top5_acc: 0.9694, loss_cls: 1.2829, loss: 1.2829 +2025-06-24 11:11:20,794 - pyskl - INFO - Epoch [6][800/1281] lr: 2.491e-02, eta: 20:31:24, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6781, top5_acc: 0.9744, loss_cls: 1.3209, loss: 1.3209 +2025-06-24 11:12:04,256 - pyskl - INFO - Epoch [6][900/1281] lr: 2.491e-02, eta: 20:32:13, time: 0.435, data_time: 0.000, memory: 4082, top1_acc: 0.6937, top5_acc: 0.9706, loss_cls: 1.2598, loss: 1.2598 +2025-06-24 11:12:46,728 - pyskl - INFO - Epoch [6][1000/1281] lr: 2.491e-02, eta: 20:32:34, time: 0.425, data_time: 0.001, memory: 4082, top1_acc: 0.7119, top5_acc: 0.9788, loss_cls: 1.1968, loss: 1.1968 +2025-06-24 11:13:24,864 - pyskl - INFO - Epoch [6][1100/1281] lr: 2.491e-02, eta: 20:31:08, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.6944, top5_acc: 0.9719, loss_cls: 1.2408, loss: 1.2408 +2025-06-24 11:13:54,785 - pyskl - INFO - Epoch [6][1200/1281] lr: 2.490e-02, eta: 20:26:23, time: 0.299, data_time: 0.000, memory: 4082, top1_acc: 0.6894, top5_acc: 0.9762, loss_cls: 1.2676, loss: 1.2676 +2025-06-24 11:14:32,232 - pyskl - INFO - Saving checkpoint at 6 epochs +2025-06-24 11:15:40,830 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:15:40,898 - pyskl - INFO - +top1_acc 0.6506 +top5_acc 0.9589 +2025-06-24 11:15:40,899 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:15:40,906 - pyskl - INFO - +mean_acc 0.5182 +2025-06-24 11:15:40,908 - pyskl - INFO - Epoch(val) [6][533] top1_acc: 0.6506, top5_acc: 0.9589, mean_class_accuracy: 0.5182 +2025-06-24 11:16:42,511 - pyskl - INFO - Epoch [7][100/1281] lr: 2.490e-02, eta: 20:21:01, time: 0.616, data_time: 0.203, memory: 4082, top1_acc: 0.7069, top5_acc: 0.9719, loss_cls: 1.2502, loss: 1.2502 +2025-06-24 11:17:23,965 - pyskl - INFO - Epoch [7][200/1281] lr: 2.490e-02, eta: 20:21:01, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6963, top5_acc: 0.9769, loss_cls: 1.2100, loss: 1.2100 +2025-06-24 11:18:05,298 - pyskl - INFO - Epoch [7][300/1281] lr: 2.489e-02, eta: 20:20:58, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.7150, top5_acc: 0.9838, loss_cls: 1.1585, loss: 1.1585 +2025-06-24 11:18:46,611 - pyskl - INFO - Epoch [7][400/1281] lr: 2.489e-02, eta: 20:20:53, time: 0.413, data_time: 0.001, memory: 4082, top1_acc: 0.6937, top5_acc: 0.9781, loss_cls: 1.2047, loss: 1.2047 +2025-06-24 11:19:28,381 - pyskl - INFO - Epoch [7][500/1281] lr: 2.489e-02, eta: 20:20:57, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.7200, top5_acc: 0.9788, loss_cls: 1.1765, loss: 1.1765 +2025-06-24 11:20:09,862 - pyskl - INFO - Epoch [7][600/1281] lr: 2.489e-02, eta: 20:20:54, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6737, top5_acc: 0.9719, loss_cls: 1.2674, loss: 1.2674 +2025-06-24 11:20:51,231 - pyskl - INFO - Epoch [7][700/1281] lr: 2.488e-02, eta: 20:20:48, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7069, top5_acc: 0.9781, loss_cls: 1.1891, loss: 1.1891 +2025-06-24 11:21:32,769 - pyskl - INFO - Epoch [7][800/1281] lr: 2.488e-02, eta: 20:20:44, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7044, top5_acc: 0.9725, loss_cls: 1.2247, loss: 1.2247 +2025-06-24 11:22:14,146 - pyskl - INFO - Epoch [7][900/1281] lr: 2.488e-02, eta: 20:20:36, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7106, top5_acc: 0.9731, loss_cls: 1.2044, loss: 1.2044 +2025-06-24 11:22:55,703 - pyskl - INFO - Epoch [7][1000/1281] lr: 2.487e-02, eta: 20:20:31, time: 0.416, data_time: 0.001, memory: 4082, top1_acc: 0.7113, top5_acc: 0.9831, loss_cls: 1.1664, loss: 1.1664 +2025-06-24 11:23:33,539 - pyskl - INFO - Epoch [7][1100/1281] lr: 2.487e-02, eta: 20:19:08, time: 0.378, data_time: 0.000, memory: 4082, top1_acc: 0.7056, top5_acc: 0.9775, loss_cls: 1.2015, loss: 1.2015 +2025-06-24 11:24:04,338 - pyskl - INFO - Epoch [7][1200/1281] lr: 2.487e-02, eta: 20:15:21, time: 0.308, data_time: 0.000, memory: 4082, top1_acc: 0.7037, top5_acc: 0.9731, loss_cls: 1.2317, loss: 1.2317 +2025-06-24 11:24:41,651 - pyskl - INFO - Saving checkpoint at 7 epochs +2025-06-24 11:25:50,637 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:25:50,715 - pyskl - INFO - +top1_acc 0.6890 +top5_acc 0.9700 +2025-06-24 11:25:50,715 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:25:50,722 - pyskl - INFO - +mean_acc 0.5179 +2025-06-24 11:25:50,726 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_5.pth was removed +2025-06-24 11:25:50,954 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_7.pth. +2025-06-24 11:25:50,954 - pyskl - INFO - Best top1_acc is 0.6890 at 7 epoch. +2025-06-24 11:25:50,957 - pyskl - INFO - Epoch(val) [7][533] top1_acc: 0.6890, top5_acc: 0.9700, mean_class_accuracy: 0.5179 +2025-06-24 11:26:52,861 - pyskl - INFO - Epoch [8][100/1281] lr: 2.486e-02, eta: 20:10:44, time: 0.619, data_time: 0.205, memory: 4082, top1_acc: 0.7250, top5_acc: 0.9794, loss_cls: 1.1057, loss: 1.1057 +2025-06-24 11:27:34,333 - pyskl - INFO - Epoch [8][200/1281] lr: 2.486e-02, eta: 20:10:40, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7331, top5_acc: 0.9806, loss_cls: 1.1107, loss: 1.1107 +2025-06-24 11:28:15,866 - pyskl - INFO - Epoch [8][300/1281] lr: 2.486e-02, eta: 20:10:37, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7188, top5_acc: 0.9750, loss_cls: 1.1826, loss: 1.1826 +2025-06-24 11:28:57,230 - pyskl - INFO - Epoch [8][400/1281] lr: 2.485e-02, eta: 20:10:29, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7163, top5_acc: 0.9762, loss_cls: 1.2037, loss: 1.2037 +2025-06-24 11:29:38,868 - pyskl - INFO - Epoch [8][500/1281] lr: 2.485e-02, eta: 20:10:26, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7338, top5_acc: 0.9775, loss_cls: 1.1203, loss: 1.1203 +2025-06-24 11:30:20,535 - pyskl - INFO - Epoch [8][600/1281] lr: 2.485e-02, eta: 20:10:23, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7331, top5_acc: 0.9844, loss_cls: 1.0974, loss: 1.0974 +2025-06-24 11:31:02,066 - pyskl - INFO - Epoch [8][700/1281] lr: 2.484e-02, eta: 20:10:16, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7119, top5_acc: 0.9812, loss_cls: 1.1360, loss: 1.1360 +2025-06-24 11:31:43,716 - pyskl - INFO - Epoch [8][800/1281] lr: 2.484e-02, eta: 20:10:11, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7150, top5_acc: 0.9788, loss_cls: 1.1247, loss: 1.1247 +2025-06-24 11:32:25,360 - pyskl - INFO - Epoch [8][900/1281] lr: 2.484e-02, eta: 20:10:05, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7325, top5_acc: 0.9788, loss_cls: 1.1183, loss: 1.1183 +2025-06-24 11:33:07,166 - pyskl - INFO - Epoch [8][1000/1281] lr: 2.483e-02, eta: 20:10:01, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.7194, top5_acc: 0.9775, loss_cls: 1.1597, loss: 1.1597 +2025-06-24 11:33:45,533 - pyskl - INFO - Epoch [8][1100/1281] lr: 2.483e-02, eta: 20:08:55, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.7281, top5_acc: 0.9744, loss_cls: 1.1282, loss: 1.1282 +2025-06-24 11:34:17,385 - pyskl - INFO - Epoch [8][1200/1281] lr: 2.483e-02, eta: 20:05:52, time: 0.319, data_time: 0.001, memory: 4082, top1_acc: 0.7163, top5_acc: 0.9769, loss_cls: 1.1643, loss: 1.1643 +2025-06-24 11:34:53,659 - pyskl - INFO - Saving checkpoint at 8 epochs +2025-06-24 11:36:03,745 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:36:03,801 - pyskl - INFO - +top1_acc 0.6540 +top5_acc 0.9568 +2025-06-24 11:36:03,801 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:36:03,808 - pyskl - INFO - +mean_acc 0.5454 +2025-06-24 11:36:03,811 - pyskl - INFO - Epoch(val) [8][533] top1_acc: 0.6540, top5_acc: 0.9568, mean_class_accuracy: 0.5454 +2025-06-24 11:37:05,275 - pyskl - INFO - Epoch [9][100/1281] lr: 2.482e-02, eta: 20:01:35, time: 0.615, data_time: 0.200, memory: 4082, top1_acc: 0.7500, top5_acc: 0.9856, loss_cls: 1.0595, loss: 1.0595 +2025-06-24 11:37:46,725 - pyskl - INFO - Epoch [9][200/1281] lr: 2.482e-02, eta: 20:01:27, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7350, top5_acc: 0.9844, loss_cls: 1.0677, loss: 1.0677 +2025-06-24 11:38:28,219 - pyskl - INFO - Epoch [9][300/1281] lr: 2.481e-02, eta: 20:01:19, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7300, top5_acc: 0.9888, loss_cls: 1.0861, loss: 1.0861 +2025-06-24 11:39:09,710 - pyskl - INFO - Epoch [9][400/1281] lr: 2.481e-02, eta: 20:01:10, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7288, top5_acc: 0.9769, loss_cls: 1.1041, loss: 1.1041 +2025-06-24 11:39:51,246 - pyskl - INFO - Epoch [9][500/1281] lr: 2.481e-02, eta: 20:01:01, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7388, top5_acc: 0.9831, loss_cls: 1.0833, loss: 1.0833 +2025-06-24 11:40:32,838 - pyskl - INFO - Epoch [9][600/1281] lr: 2.480e-02, eta: 20:00:52, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7319, top5_acc: 0.9806, loss_cls: 1.0828, loss: 1.0828 +2025-06-24 11:41:14,198 - pyskl - INFO - Epoch [9][700/1281] lr: 2.480e-02, eta: 20:00:39, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7269, top5_acc: 0.9794, loss_cls: 1.1082, loss: 1.1082 +2025-06-24 11:41:55,533 - pyskl - INFO - Epoch [9][800/1281] lr: 2.480e-02, eta: 20:00:25, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.7506, top5_acc: 0.9869, loss_cls: 1.0261, loss: 1.0261 +2025-06-24 11:42:36,910 - pyskl - INFO - Epoch [9][900/1281] lr: 2.479e-02, eta: 20:00:12, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7531, top5_acc: 0.9788, loss_cls: 1.0407, loss: 1.0407 +2025-06-24 11:43:18,916 - pyskl - INFO - Epoch [9][1000/1281] lr: 2.479e-02, eta: 20:00:07, time: 0.420, data_time: 0.000, memory: 4082, top1_acc: 0.7369, top5_acc: 0.9788, loss_cls: 1.1042, loss: 1.1042 +2025-06-24 11:43:55,859 - pyskl - INFO - Epoch [9][1100/1281] lr: 2.479e-02, eta: 19:58:42, time: 0.369, data_time: 0.000, memory: 4082, top1_acc: 0.7412, top5_acc: 0.9788, loss_cls: 1.0980, loss: 1.0980 +2025-06-24 11:44:26,561 - pyskl - INFO - Epoch [9][1200/1281] lr: 2.478e-02, eta: 19:55:39, time: 0.307, data_time: 0.001, memory: 4082, top1_acc: 0.7275, top5_acc: 0.9806, loss_cls: 1.1116, loss: 1.1116 +2025-06-24 11:45:03,877 - pyskl - INFO - Saving checkpoint at 9 epochs +2025-06-24 11:46:14,262 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:46:14,337 - pyskl - INFO - +top1_acc 0.6633 +top5_acc 0.9565 +2025-06-24 11:46:14,337 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:46:14,346 - pyskl - INFO - +mean_acc 0.5738 +2025-06-24 11:46:14,348 - pyskl - INFO - Epoch(val) [9][533] top1_acc: 0.6633, top5_acc: 0.9565, mean_class_accuracy: 0.5738 +2025-06-24 11:47:16,133 - pyskl - INFO - Epoch [10][100/1281] lr: 2.477e-02, eta: 19:51:51, time: 0.618, data_time: 0.203, memory: 4082, top1_acc: 0.7600, top5_acc: 0.9838, loss_cls: 1.0180, loss: 1.0180 +2025-06-24 11:47:57,735 - pyskl - INFO - Epoch [10][200/1281] lr: 2.477e-02, eta: 19:51:42, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7700, top5_acc: 0.9812, loss_cls: 1.0235, loss: 1.0235 +2025-06-24 11:48:39,160 - pyskl - INFO - Epoch [10][300/1281] lr: 2.477e-02, eta: 19:51:29, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7631, top5_acc: 0.9888, loss_cls: 0.9847, loss: 0.9847 +2025-06-24 11:49:20,600 - pyskl - INFO - Epoch [10][400/1281] lr: 2.476e-02, eta: 19:51:17, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7525, top5_acc: 0.9794, loss_cls: 1.0588, loss: 1.0588 +2025-06-24 11:50:01,991 - pyskl - INFO - Epoch [10][500/1281] lr: 2.476e-02, eta: 19:51:03, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7438, top5_acc: 0.9781, loss_cls: 1.0803, loss: 1.0803 +2025-06-24 11:50:43,493 - pyskl - INFO - Epoch [10][600/1281] lr: 2.476e-02, eta: 19:50:50, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7550, top5_acc: 0.9838, loss_cls: 1.0275, loss: 1.0275 +2025-06-24 11:51:24,920 - pyskl - INFO - Epoch [10][700/1281] lr: 2.475e-02, eta: 19:50:36, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7631, top5_acc: 0.9856, loss_cls: 0.9857, loss: 0.9857 +2025-06-24 11:52:06,428 - pyskl - INFO - Epoch [10][800/1281] lr: 2.475e-02, eta: 19:50:23, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7544, top5_acc: 0.9869, loss_cls: 1.0814, loss: 1.0814 +2025-06-24 11:52:47,972 - pyskl - INFO - Epoch [10][900/1281] lr: 2.474e-02, eta: 19:50:09, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7562, top5_acc: 0.9825, loss_cls: 1.0014, loss: 1.0014 +2025-06-24 11:53:29,528 - pyskl - INFO - Epoch [10][1000/1281] lr: 2.474e-02, eta: 19:49:56, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7425, top5_acc: 0.9838, loss_cls: 1.0386, loss: 1.0386 +2025-06-24 11:54:06,395 - pyskl - INFO - Epoch [10][1100/1281] lr: 2.473e-02, eta: 19:48:35, time: 0.369, data_time: 0.001, memory: 4082, top1_acc: 0.7250, top5_acc: 0.9719, loss_cls: 1.1340, loss: 1.1340 +2025-06-24 11:54:36,946 - pyskl - INFO - Epoch [10][1200/1281] lr: 2.473e-02, eta: 19:45:46, time: 0.305, data_time: 0.000, memory: 4082, top1_acc: 0.7362, top5_acc: 0.9844, loss_cls: 1.0696, loss: 1.0696 +2025-06-24 11:55:14,345 - pyskl - INFO - Saving checkpoint at 10 epochs +2025-06-24 11:56:24,580 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:56:24,650 - pyskl - INFO - +top1_acc 0.7185 +top5_acc 0.9735 +2025-06-24 11:56:24,650 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:56:24,658 - pyskl - INFO - +mean_acc 0.6015 +2025-06-24 11:56:24,663 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_7.pth was removed +2025-06-24 11:56:24,867 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_10.pth. +2025-06-24 11:56:24,868 - pyskl - INFO - Best top1_acc is 0.7185 at 10 epoch. +2025-06-24 11:56:24,870 - pyskl - INFO - Epoch(val) [10][533] top1_acc: 0.7185, top5_acc: 0.9735, mean_class_accuracy: 0.6015 +2025-06-24 11:57:26,159 - pyskl - INFO - Epoch [11][100/1281] lr: 2.472e-02, eta: 19:42:09, time: 0.613, data_time: 0.200, memory: 4082, top1_acc: 0.7856, top5_acc: 0.9838, loss_cls: 0.9238, loss: 0.9238 +2025-06-24 11:58:07,772 - pyskl - INFO - Epoch [11][200/1281] lr: 2.472e-02, eta: 19:41:57, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7644, top5_acc: 0.9831, loss_cls: 0.9367, loss: 0.9367 +2025-06-24 11:58:49,255 - pyskl - INFO - Epoch [11][300/1281] lr: 2.471e-02, eta: 19:41:43, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7556, top5_acc: 0.9869, loss_cls: 1.0295, loss: 1.0295 +2025-06-24 11:59:30,830 - pyskl - INFO - Epoch [11][400/1281] lr: 2.471e-02, eta: 19:41:31, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7844, top5_acc: 0.9869, loss_cls: 0.9485, loss: 0.9485 +2025-06-24 12:00:12,613 - pyskl - INFO - Epoch [11][500/1281] lr: 2.471e-02, eta: 19:41:20, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.7581, top5_acc: 0.9825, loss_cls: 1.0113, loss: 1.0113 +2025-06-24 12:00:55,867 - pyskl - INFO - Epoch [11][600/1281] lr: 2.470e-02, eta: 19:41:29, time: 0.433, data_time: 0.000, memory: 4082, top1_acc: 0.7694, top5_acc: 0.9881, loss_cls: 0.9721, loss: 0.9721 +2025-06-24 12:01:39,560 - pyskl - INFO - Epoch [11][700/1281] lr: 2.470e-02, eta: 19:41:42, time: 0.437, data_time: 0.000, memory: 4082, top1_acc: 0.7638, top5_acc: 0.9869, loss_cls: 0.9841, loss: 0.9841 +2025-06-24 12:02:21,244 - pyskl - INFO - Epoch [11][800/1281] lr: 2.469e-02, eta: 19:41:29, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7750, top5_acc: 0.9844, loss_cls: 0.9516, loss: 0.9516 +2025-06-24 12:03:02,902 - pyskl - INFO - Epoch [11][900/1281] lr: 2.469e-02, eta: 19:41:14, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7819, top5_acc: 0.9831, loss_cls: 0.9699, loss: 0.9699 +2025-06-24 12:03:44,331 - pyskl - INFO - Epoch [11][1000/1281] lr: 2.468e-02, eta: 19:40:57, time: 0.414, data_time: 0.001, memory: 4082, top1_acc: 0.7831, top5_acc: 0.9850, loss_cls: 0.9745, loss: 0.9745 +2025-06-24 12:04:21,395 - pyskl - INFO - Epoch [11][1100/1281] lr: 2.468e-02, eta: 19:39:43, time: 0.371, data_time: 0.000, memory: 4082, top1_acc: 0.7812, top5_acc: 0.9869, loss_cls: 0.9409, loss: 0.9409 +2025-06-24 12:04:52,840 - pyskl - INFO - Epoch [11][1200/1281] lr: 2.467e-02, eta: 19:37:18, time: 0.314, data_time: 0.000, memory: 4082, top1_acc: 0.7525, top5_acc: 0.9838, loss_cls: 1.0304, loss: 1.0304 +2025-06-24 12:05:29,311 - pyskl - INFO - Saving checkpoint at 11 epochs +2025-06-24 12:06:39,188 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:06:39,261 - pyskl - INFO - +top1_acc 0.7531 +top5_acc 0.9798 +2025-06-24 12:06:39,261 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:06:39,269 - pyskl - INFO - +mean_acc 0.6502 +2025-06-24 12:06:39,274 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_10.pth was removed +2025-06-24 12:06:39,616 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_11.pth. +2025-06-24 12:06:39,617 - pyskl - INFO - Best top1_acc is 0.7531 at 11 epoch. +2025-06-24 12:06:39,619 - pyskl - INFO - Epoch(val) [11][533] top1_acc: 0.7531, top5_acc: 0.9798, mean_class_accuracy: 0.6502 +2025-06-24 12:07:42,426 - pyskl - INFO - Epoch [12][100/1281] lr: 2.467e-02, eta: 19:34:14, time: 0.628, data_time: 0.194, memory: 4082, top1_acc: 0.7731, top5_acc: 0.9900, loss_cls: 0.9400, loss: 0.9400 +2025-06-24 12:08:23,884 - pyskl - INFO - Epoch [12][200/1281] lr: 2.466e-02, eta: 19:33:57, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7788, top5_acc: 0.9856, loss_cls: 0.9830, loss: 0.9830 +2025-06-24 12:09:05,162 - pyskl - INFO - Epoch [12][300/1281] lr: 2.466e-02, eta: 19:33:38, time: 0.413, data_time: 0.001, memory: 4082, top1_acc: 0.7731, top5_acc: 0.9925, loss_cls: 0.9285, loss: 0.9285 +2025-06-24 12:09:46,599 - pyskl - INFO - Epoch [12][400/1281] lr: 2.465e-02, eta: 19:33:21, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7800, top5_acc: 0.9850, loss_cls: 0.9648, loss: 0.9648 +2025-06-24 12:10:27,953 - pyskl - INFO - Epoch [12][500/1281] lr: 2.465e-02, eta: 19:33:03, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7631, top5_acc: 0.9831, loss_cls: 0.9792, loss: 0.9792 +2025-06-24 12:11:09,407 - pyskl - INFO - Epoch [12][600/1281] lr: 2.464e-02, eta: 19:32:45, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7438, top5_acc: 0.9844, loss_cls: 1.0035, loss: 1.0035 +2025-06-24 12:11:51,121 - pyskl - INFO - Epoch [12][700/1281] lr: 2.464e-02, eta: 19:32:30, time: 0.417, data_time: 0.001, memory: 4082, top1_acc: 0.7800, top5_acc: 0.9862, loss_cls: 0.8916, loss: 0.8916 +2025-06-24 12:12:32,781 - pyskl - INFO - Epoch [12][800/1281] lr: 2.463e-02, eta: 19:32:14, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7738, top5_acc: 0.9838, loss_cls: 1.0051, loss: 1.0051 +2025-06-24 12:13:14,261 - pyskl - INFO - Epoch [12][900/1281] lr: 2.463e-02, eta: 19:31:56, time: 0.415, data_time: 0.001, memory: 4082, top1_acc: 0.7863, top5_acc: 0.9881, loss_cls: 0.9071, loss: 0.9071 +2025-06-24 12:13:55,725 - pyskl - INFO - Epoch [12][1000/1281] lr: 2.462e-02, eta: 19:31:37, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7575, top5_acc: 0.9850, loss_cls: 1.0189, loss: 1.0189 +2025-06-24 12:14:33,026 - pyskl - INFO - Epoch [12][1100/1281] lr: 2.462e-02, eta: 19:30:29, time: 0.373, data_time: 0.000, memory: 4082, top1_acc: 0.7725, top5_acc: 0.9825, loss_cls: 0.9789, loss: 0.9789 +2025-06-24 12:15:04,972 - pyskl - INFO - Epoch [12][1200/1281] lr: 2.461e-02, eta: 19:28:20, time: 0.319, data_time: 0.000, memory: 4082, top1_acc: 0.7894, top5_acc: 0.9819, loss_cls: 0.9501, loss: 0.9501 +2025-06-24 12:15:40,783 - pyskl - INFO - Saving checkpoint at 12 epochs +2025-06-24 12:16:51,811 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:16:51,868 - pyskl - INFO - +top1_acc 0.7068 +top5_acc 0.9749 +2025-06-24 12:16:51,868 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:16:51,875 - pyskl - INFO - +mean_acc 0.6042 +2025-06-24 12:16:51,878 - pyskl - INFO - Epoch(val) [12][533] top1_acc: 0.7068, top5_acc: 0.9749, mean_class_accuracy: 0.6042 +2025-06-24 12:17:52,937 - pyskl - INFO - Epoch [13][100/1281] lr: 2.460e-02, eta: 19:25:06, time: 0.611, data_time: 0.196, memory: 4082, top1_acc: 0.7869, top5_acc: 0.9938, loss_cls: 0.9066, loss: 0.9066 +2025-06-24 12:18:34,523 - pyskl - INFO - Epoch [13][200/1281] lr: 2.460e-02, eta: 19:24:49, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7875, top5_acc: 0.9906, loss_cls: 0.9399, loss: 0.9399 +2025-06-24 12:19:16,091 - pyskl - INFO - Epoch [13][300/1281] lr: 2.459e-02, eta: 19:24:32, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7750, top5_acc: 0.9850, loss_cls: 0.9212, loss: 0.9212 +2025-06-24 12:19:57,612 - pyskl - INFO - Epoch [13][400/1281] lr: 2.459e-02, eta: 19:24:14, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7681, top5_acc: 0.9869, loss_cls: 0.9673, loss: 0.9673 +2025-06-24 12:20:39,072 - pyskl - INFO - Epoch [13][500/1281] lr: 2.458e-02, eta: 19:23:55, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7881, top5_acc: 0.9844, loss_cls: 0.9220, loss: 0.9220 +2025-06-24 12:21:21,160 - pyskl - INFO - Epoch [13][600/1281] lr: 2.458e-02, eta: 19:23:43, time: 0.421, data_time: 0.000, memory: 4082, top1_acc: 0.7887, top5_acc: 0.9888, loss_cls: 0.9226, loss: 0.9226 +2025-06-24 12:22:02,642 - pyskl - INFO - Epoch [13][700/1281] lr: 2.457e-02, eta: 19:23:23, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7913, top5_acc: 0.9912, loss_cls: 0.9008, loss: 0.9008 +2025-06-24 12:22:44,152 - pyskl - INFO - Epoch [13][800/1281] lr: 2.457e-02, eta: 19:23:04, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7831, top5_acc: 0.9800, loss_cls: 0.9654, loss: 0.9654 +2025-06-24 12:23:25,561 - pyskl - INFO - Epoch [13][900/1281] lr: 2.456e-02, eta: 19:22:43, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7825, top5_acc: 0.9800, loss_cls: 0.9686, loss: 0.9686 +2025-06-24 12:24:07,109 - pyskl - INFO - Epoch [13][1000/1281] lr: 2.455e-02, eta: 19:22:24, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7894, top5_acc: 0.9844, loss_cls: 0.9263, loss: 0.9263 +2025-06-24 12:24:43,526 - pyskl - INFO - Epoch [13][1100/1281] lr: 2.455e-02, eta: 19:21:09, time: 0.364, data_time: 0.000, memory: 4082, top1_acc: 0.7819, top5_acc: 0.9862, loss_cls: 0.9400, loss: 0.9400 +2025-06-24 12:25:15,014 - pyskl - INFO - Epoch [13][1200/1281] lr: 2.454e-02, eta: 19:19:03, time: 0.315, data_time: 0.000, memory: 4082, top1_acc: 0.7769, top5_acc: 0.9838, loss_cls: 0.9623, loss: 0.9623 +2025-06-24 12:25:51,250 - pyskl - INFO - Saving checkpoint at 13 epochs +2025-06-24 12:26:50,857 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:26:50,912 - pyskl - INFO - +top1_acc 0.7432 +top5_acc 0.9757 +2025-06-24 12:26:50,912 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:26:50,919 - pyskl - INFO - +mean_acc 0.6460 +2025-06-24 12:26:50,920 - pyskl - INFO - Epoch(val) [13][533] top1_acc: 0.7432, top5_acc: 0.9757, mean_class_accuracy: 0.6460 +2025-06-24 12:27:50,477 - pyskl - INFO - Epoch [14][100/1281] lr: 2.453e-02, eta: 19:15:44, time: 0.596, data_time: 0.198, memory: 4082, top1_acc: 0.7937, top5_acc: 0.9906, loss_cls: 0.8664, loss: 0.8664 +2025-06-24 12:28:30,391 - pyskl - INFO - Epoch [14][200/1281] lr: 2.453e-02, eta: 19:15:09, time: 0.399, data_time: 0.000, memory: 4082, top1_acc: 0.7812, top5_acc: 0.9919, loss_cls: 0.9032, loss: 0.9032 +2025-06-24 12:29:09,707 - pyskl - INFO - Epoch [14][300/1281] lr: 2.452e-02, eta: 19:14:27, time: 0.393, data_time: 0.000, memory: 4082, top1_acc: 0.7975, top5_acc: 0.9906, loss_cls: 0.8643, loss: 0.8643 +2025-06-24 12:29:49,601 - pyskl - INFO - Epoch [14][400/1281] lr: 2.452e-02, eta: 19:13:51, time: 0.399, data_time: 0.000, memory: 4082, top1_acc: 0.7856, top5_acc: 0.9856, loss_cls: 0.9461, loss: 0.9461 +2025-06-24 12:30:29,133 - pyskl - INFO - Epoch [14][500/1281] lr: 2.451e-02, eta: 19:13:11, time: 0.395, data_time: 0.000, memory: 4082, top1_acc: 0.7944, top5_acc: 0.9881, loss_cls: 0.8868, loss: 0.8868 +2025-06-24 12:31:09,892 - pyskl - INFO - Epoch [14][600/1281] lr: 2.451e-02, eta: 19:12:44, time: 0.408, data_time: 0.000, memory: 4082, top1_acc: 0.7856, top5_acc: 0.9900, loss_cls: 0.8963, loss: 0.8963 +2025-06-24 12:31:50,764 - pyskl - INFO - Epoch [14][700/1281] lr: 2.450e-02, eta: 19:12:18, time: 0.409, data_time: 0.000, memory: 4082, top1_acc: 0.7881, top5_acc: 0.9850, loss_cls: 0.8946, loss: 0.8946 +2025-06-24 12:32:30,872 - pyskl - INFO - Epoch [14][800/1281] lr: 2.449e-02, eta: 19:11:44, time: 0.401, data_time: 0.000, memory: 4082, top1_acc: 0.7994, top5_acc: 0.9850, loss_cls: 0.8874, loss: 0.8874 +2025-06-24 12:33:10,570 - pyskl - INFO - Epoch [14][900/1281] lr: 2.449e-02, eta: 19:11:06, time: 0.397, data_time: 0.000, memory: 4082, top1_acc: 0.7837, top5_acc: 0.9856, loss_cls: 0.9210, loss: 0.9210 +2025-06-24 12:33:49,785 - pyskl - INFO - Epoch [14][1000/1281] lr: 2.448e-02, eta: 19:10:23, time: 0.392, data_time: 0.000, memory: 4082, top1_acc: 0.7900, top5_acc: 0.9875, loss_cls: 0.9274, loss: 0.9274 +2025-06-24 12:34:29,949 - pyskl - INFO - Epoch [14][1100/1281] lr: 2.448e-02, eta: 19:09:49, time: 0.402, data_time: 0.001, memory: 4082, top1_acc: 0.8106, top5_acc: 0.9850, loss_cls: 0.8691, loss: 0.8691 +2025-06-24 12:35:09,432 - pyskl - INFO - Epoch [14][1200/1281] lr: 2.447e-02, eta: 19:09:09, time: 0.395, data_time: 0.001, memory: 4082, top1_acc: 0.7837, top5_acc: 0.9850, loss_cls: 0.9152, loss: 0.9152 +2025-06-24 12:35:42,100 - pyskl - INFO - Saving checkpoint at 14 epochs +2025-06-24 12:36:33,955 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:36:34,026 - pyskl - INFO - +top1_acc 0.7586 +top5_acc 0.9758 +2025-06-24 12:36:34,027 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:36:34,038 - pyskl - INFO - +mean_acc 0.6565 +2025-06-24 12:36:34,044 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_11.pth was removed +2025-06-24 12:36:34,264 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_14.pth. +2025-06-24 12:36:34,264 - pyskl - INFO - Best top1_acc is 0.7586 at 14 epoch. +2025-06-24 12:36:34,267 - pyskl - INFO - Epoch(val) [14][533] top1_acc: 0.7586, top5_acc: 0.9758, mean_class_accuracy: 0.6565 +2025-06-24 12:37:16,258 - pyskl - INFO - Epoch [15][100/1281] lr: 2.446e-02, eta: 19:03:11, time: 0.420, data_time: 0.189, memory: 4082, top1_acc: 0.8019, top5_acc: 0.9906, loss_cls: 0.8763, loss: 0.8763 +2025-06-24 12:37:49,144 - pyskl - INFO - Epoch [15][200/1281] lr: 2.445e-02, eta: 19:01:29, time: 0.329, data_time: 0.000, memory: 4082, top1_acc: 0.7950, top5_acc: 0.9881, loss_cls: 0.9266, loss: 0.9266 +2025-06-24 12:38:27,736 - pyskl - INFO - Epoch [15][300/1281] lr: 2.445e-02, eta: 19:00:43, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8044, top5_acc: 0.9869, loss_cls: 0.9004, loss: 0.9004 +2025-06-24 12:39:06,118 - pyskl - INFO - Epoch [15][400/1281] lr: 2.444e-02, eta: 18:59:54, time: 0.384, data_time: 0.001, memory: 4082, top1_acc: 0.7963, top5_acc: 0.9862, loss_cls: 0.8693, loss: 0.8693 +2025-06-24 12:39:43,695 - pyskl - INFO - Epoch [15][500/1281] lr: 2.444e-02, eta: 18:58:58, time: 0.376, data_time: 0.000, memory: 4082, top1_acc: 0.8019, top5_acc: 0.9881, loss_cls: 0.8854, loss: 0.8854 +2025-06-24 12:40:22,543 - pyskl - INFO - Epoch [15][600/1281] lr: 2.443e-02, eta: 18:58:14, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8037, top5_acc: 0.9875, loss_cls: 0.8634, loss: 0.8634 +2025-06-24 12:41:01,823 - pyskl - INFO - Epoch [15][700/1281] lr: 2.442e-02, eta: 18:57:34, time: 0.393, data_time: 0.000, memory: 4082, top1_acc: 0.7894, top5_acc: 0.9862, loss_cls: 0.9298, loss: 0.9298 +2025-06-24 12:41:41,540 - pyskl - INFO - Epoch [15][800/1281] lr: 2.442e-02, eta: 18:56:59, time: 0.397, data_time: 0.000, memory: 4082, top1_acc: 0.7994, top5_acc: 0.9881, loss_cls: 0.8826, loss: 0.8826 +2025-06-24 12:42:20,433 - pyskl - INFO - Epoch [15][900/1281] lr: 2.441e-02, eta: 18:56:15, time: 0.389, data_time: 0.000, memory: 4082, top1_acc: 0.7950, top5_acc: 0.9838, loss_cls: 0.8968, loss: 0.8968 +2025-06-24 12:42:58,907 - pyskl - INFO - Epoch [15][1000/1281] lr: 2.441e-02, eta: 18:55:28, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.8000, top5_acc: 0.9888, loss_cls: 0.8611, loss: 0.8611 +2025-06-24 12:43:38,320 - pyskl - INFO - Epoch [15][1100/1281] lr: 2.440e-02, eta: 18:54:49, time: 0.394, data_time: 0.000, memory: 4082, top1_acc: 0.8000, top5_acc: 0.9894, loss_cls: 0.8498, loss: 0.8498 +2025-06-24 12:44:16,469 - pyskl - INFO - Epoch [15][1200/1281] lr: 2.439e-02, eta: 18:53:59, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8150, top5_acc: 0.9881, loss_cls: 0.8350, loss: 0.8350 +2025-06-24 12:44:48,377 - pyskl - INFO - Saving checkpoint at 15 epochs +2025-06-24 12:45:48,240 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:45:48,298 - pyskl - INFO - +top1_acc 0.7552 +top5_acc 0.9820 +2025-06-24 12:45:48,298 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:45:48,305 - pyskl - INFO - +mean_acc 0.6584 +2025-06-24 12:45:48,307 - pyskl - INFO - Epoch(val) [15][533] top1_acc: 0.7552, top5_acc: 0.9820, mean_class_accuracy: 0.6584 +2025-06-24 12:46:47,701 - pyskl - INFO - Epoch [16][100/1281] lr: 2.438e-02, eta: 18:51:03, time: 0.594, data_time: 0.199, memory: 4082, top1_acc: 0.8137, top5_acc: 0.9900, loss_cls: 0.8038, loss: 0.8038 +2025-06-24 12:47:26,390 - pyskl - INFO - Epoch [16][200/1281] lr: 2.438e-02, eta: 18:50:18, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.8081, top5_acc: 0.9888, loss_cls: 0.8510, loss: 0.8510 +2025-06-24 12:47:54,981 - pyskl - INFO - Epoch [16][300/1281] lr: 2.437e-02, eta: 18:48:04, time: 0.286, data_time: 0.000, memory: 4082, top1_acc: 0.7913, top5_acc: 0.9838, loss_cls: 0.9279, loss: 0.9279 +2025-06-24 12:48:34,213 - pyskl - INFO - Epoch [16][400/1281] lr: 2.436e-02, eta: 18:47:25, time: 0.392, data_time: 0.000, memory: 4082, top1_acc: 0.8231, top5_acc: 0.9888, loss_cls: 0.7820, loss: 0.7820 +2025-06-24 12:49:06,129 - pyskl - INFO - Epoch [16][500/1281] lr: 2.436e-02, eta: 18:45:42, time: 0.319, data_time: 0.000, memory: 4082, top1_acc: 0.7850, top5_acc: 0.9856, loss_cls: 0.9150, loss: 0.9150 +2025-06-24 12:49:31,331 - pyskl - INFO - Epoch [16][600/1281] lr: 2.435e-02, eta: 18:43:02, time: 0.252, data_time: 0.000, memory: 4082, top1_acc: 0.7969, top5_acc: 0.9900, loss_cls: 0.9077, loss: 0.9077 +2025-06-24 12:50:09,878 - pyskl - INFO - Epoch [16][700/1281] lr: 2.434e-02, eta: 18:42:18, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.7969, top5_acc: 0.9900, loss_cls: 0.8727, loss: 0.8727 +2025-06-24 12:50:48,092 - pyskl - INFO - Epoch [16][800/1281] lr: 2.434e-02, eta: 18:41:31, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8119, top5_acc: 0.9912, loss_cls: 0.7954, loss: 0.7954 +2025-06-24 12:51:26,824 - pyskl - INFO - Epoch [16][900/1281] lr: 2.433e-02, eta: 18:40:49, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.8031, top5_acc: 0.9881, loss_cls: 0.8417, loss: 0.8417 +2025-06-24 12:52:05,846 - pyskl - INFO - Epoch [16][1000/1281] lr: 2.432e-02, eta: 18:40:09, time: 0.390, data_time: 0.000, memory: 4082, top1_acc: 0.8025, top5_acc: 0.9931, loss_cls: 0.8393, loss: 0.8393 +2025-06-24 12:52:45,056 - pyskl - INFO - Epoch [16][1100/1281] lr: 2.432e-02, eta: 18:39:31, time: 0.392, data_time: 0.000, memory: 4082, top1_acc: 0.8056, top5_acc: 0.9825, loss_cls: 0.8591, loss: 0.8591 +2025-06-24 12:53:23,664 - pyskl - INFO - Epoch [16][1200/1281] lr: 2.431e-02, eta: 18:38:48, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8144, top5_acc: 0.9931, loss_cls: 0.7984, loss: 0.7984 +2025-06-24 12:53:55,511 - pyskl - INFO - Saving checkpoint at 16 epochs +2025-06-24 12:54:54,874 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:54:54,930 - pyskl - INFO - +top1_acc 0.7731 +top5_acc 0.9778 +2025-06-24 12:54:54,930 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:54:54,937 - pyskl - INFO - +mean_acc 0.7008 +2025-06-24 12:54:54,941 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_14.pth was removed +2025-06-24 12:54:55,119 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_16.pth. +2025-06-24 12:54:55,119 - pyskl - INFO - Best top1_acc is 0.7731 at 16 epoch. +2025-06-24 12:54:55,122 - pyskl - INFO - Epoch(val) [16][533] top1_acc: 0.7731, top5_acc: 0.9778, mean_class_accuracy: 0.7008 +2025-06-24 12:55:53,351 - pyskl - INFO - Epoch [17][100/1281] lr: 2.430e-02, eta: 18:35:53, time: 0.582, data_time: 0.195, memory: 4082, top1_acc: 0.8037, top5_acc: 0.9931, loss_cls: 0.8498, loss: 0.8498 +2025-06-24 12:56:31,389 - pyskl - INFO - Epoch [17][200/1281] lr: 2.429e-02, eta: 18:35:06, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8181, top5_acc: 0.9900, loss_cls: 0.7757, loss: 0.7757 +2025-06-24 12:57:10,532 - pyskl - INFO - Epoch [17][300/1281] lr: 2.428e-02, eta: 18:34:28, time: 0.391, data_time: 0.000, memory: 4082, top1_acc: 0.8181, top5_acc: 0.9900, loss_cls: 0.7807, loss: 0.7807 +2025-06-24 12:57:48,659 - pyskl - INFO - Epoch [17][400/1281] lr: 2.428e-02, eta: 18:33:41, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8294, top5_acc: 0.9894, loss_cls: 0.7662, loss: 0.7662 +2025-06-24 12:58:27,581 - pyskl - INFO - Epoch [17][500/1281] lr: 2.427e-02, eta: 18:33:02, time: 0.389, data_time: 0.000, memory: 4082, top1_acc: 0.8000, top5_acc: 0.9875, loss_cls: 0.8347, loss: 0.8347 +2025-06-24 12:59:05,382 - pyskl - INFO - Epoch [17][600/1281] lr: 2.426e-02, eta: 18:32:13, time: 0.378, data_time: 0.000, memory: 4082, top1_acc: 0.8063, top5_acc: 0.9912, loss_cls: 0.8783, loss: 0.8783 +2025-06-24 12:59:43,560 - pyskl - INFO - Epoch [17][700/1281] lr: 2.426e-02, eta: 18:31:27, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8194, top5_acc: 0.9906, loss_cls: 0.8202, loss: 0.8202 +2025-06-24 13:00:08,803 - pyskl - INFO - Epoch [17][800/1281] lr: 2.425e-02, eta: 18:28:57, time: 0.252, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9944, loss_cls: 0.7552, loss: 0.7552 +2025-06-24 13:00:54,153 - pyskl - INFO - Epoch [17][900/1281] lr: 2.424e-02, eta: 18:29:10, time: 0.453, data_time: 0.000, memory: 4082, top1_acc: 0.8069, top5_acc: 0.9900, loss_cls: 0.8306, loss: 0.8306 +2025-06-24 13:01:17,768 - pyskl - INFO - Epoch [17][1000/1281] lr: 2.424e-02, eta: 18:26:29, time: 0.236, data_time: 0.001, memory: 4082, top1_acc: 0.8250, top5_acc: 0.9912, loss_cls: 0.8004, loss: 0.8004 +2025-06-24 13:01:51,188 - pyskl - INFO - Epoch [17][1100/1281] lr: 2.423e-02, eta: 18:25:06, time: 0.334, data_time: 0.000, memory: 4082, top1_acc: 0.8094, top5_acc: 0.9906, loss_cls: 0.8179, loss: 0.8179 +2025-06-24 13:02:29,534 - pyskl - INFO - Epoch [17][1200/1281] lr: 2.422e-02, eta: 18:24:23, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.7887, top5_acc: 0.9881, loss_cls: 0.9059, loss: 0.9059 +2025-06-24 13:03:01,717 - pyskl - INFO - Saving checkpoint at 17 epochs +2025-06-24 13:04:01,149 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:04:01,218 - pyskl - INFO - +top1_acc 0.7778 +top5_acc 0.9838 +2025-06-24 13:04:01,218 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:04:01,227 - pyskl - INFO - +mean_acc 0.6760 +2025-06-24 13:04:01,232 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_16.pth was removed +2025-06-24 13:04:01,410 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_17.pth. +2025-06-24 13:04:01,410 - pyskl - INFO - Best top1_acc is 0.7778 at 17 epoch. +2025-06-24 13:04:01,413 - pyskl - INFO - Epoch(val) [17][533] top1_acc: 0.7778, top5_acc: 0.9838, mean_class_accuracy: 0.6760 +2025-06-24 13:04:59,488 - pyskl - INFO - Epoch [18][100/1281] lr: 2.421e-02, eta: 18:21:37, time: 0.581, data_time: 0.196, memory: 4082, top1_acc: 0.8187, top5_acc: 0.9844, loss_cls: 0.8274, loss: 0.8274 +2025-06-24 13:05:38,196 - pyskl - INFO - Epoch [18][200/1281] lr: 2.420e-02, eta: 18:20:58, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9931, loss_cls: 0.7543, loss: 0.7543 +2025-06-24 13:06:16,846 - pyskl - INFO - Epoch [18][300/1281] lr: 2.419e-02, eta: 18:20:18, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.7944, top5_acc: 0.9894, loss_cls: 0.8378, loss: 0.8378 +2025-06-24 13:06:55,184 - pyskl - INFO - Epoch [18][400/1281] lr: 2.419e-02, eta: 18:19:35, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.8256, top5_acc: 0.9894, loss_cls: 0.7895, loss: 0.7895 +2025-06-24 13:07:34,324 - pyskl - INFO - Epoch [18][500/1281] lr: 2.418e-02, eta: 18:18:59, time: 0.391, data_time: 0.000, memory: 4082, top1_acc: 0.8100, top5_acc: 0.9912, loss_cls: 0.8133, loss: 0.8133 +2025-06-24 13:08:13,799 - pyskl - INFO - Epoch [18][600/1281] lr: 2.417e-02, eta: 18:18:25, time: 0.395, data_time: 0.000, memory: 4082, top1_acc: 0.8219, top5_acc: 0.9894, loss_cls: 0.7973, loss: 0.7973 +2025-06-24 13:08:52,507 - pyskl - INFO - Epoch [18][700/1281] lr: 2.417e-02, eta: 18:17:45, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.8237, top5_acc: 0.9900, loss_cls: 0.7832, loss: 0.7832 +2025-06-24 13:09:30,686 - pyskl - INFO - Epoch [18][800/1281] lr: 2.416e-02, eta: 18:17:02, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8181, top5_acc: 0.9906, loss_cls: 0.8195, loss: 0.8195 +2025-06-24 13:10:08,966 - pyskl - INFO - Epoch [18][900/1281] lr: 2.415e-02, eta: 18:16:19, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.8025, top5_acc: 0.9881, loss_cls: 0.8634, loss: 0.8634 +2025-06-24 13:10:47,914 - pyskl - INFO - Epoch [18][1000/1281] lr: 2.414e-02, eta: 18:15:41, time: 0.389, data_time: 0.000, memory: 4082, top1_acc: 0.8225, top5_acc: 0.9906, loss_cls: 0.7859, loss: 0.7859 +2025-06-24 13:11:27,726 - pyskl - INFO - Epoch [18][1100/1281] lr: 2.414e-02, eta: 18:15:09, time: 0.398, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9925, loss_cls: 0.7380, loss: 0.7380 +2025-06-24 13:11:55,288 - pyskl - INFO - Epoch [18][1200/1281] lr: 2.413e-02, eta: 18:13:08, time: 0.276, data_time: 0.000, memory: 4082, top1_acc: 0.7994, top5_acc: 0.9900, loss_cls: 0.8620, loss: 0.8620 +2025-06-24 13:12:30,035 - pyskl - INFO - Saving checkpoint at 18 epochs +2025-06-24 13:13:16,764 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:13:16,834 - pyskl - INFO - +top1_acc 0.7645 +top5_acc 0.9840 +2025-06-24 13:13:16,835 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:13:16,845 - pyskl - INFO - +mean_acc 0.6910 +2025-06-24 13:13:16,848 - pyskl - INFO - Epoch(val) [18][533] top1_acc: 0.7645, top5_acc: 0.9840, mean_class_accuracy: 0.6910 +2025-06-24 13:14:16,122 - pyskl - INFO - Epoch [19][100/1281] lr: 2.411e-02, eta: 18:10:38, time: 0.593, data_time: 0.196, memory: 4082, top1_acc: 0.7963, top5_acc: 0.9919, loss_cls: 0.8468, loss: 0.8468 +2025-06-24 13:14:54,489 - pyskl - INFO - Epoch [19][200/1281] lr: 2.411e-02, eta: 18:09:57, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8306, top5_acc: 0.9906, loss_cls: 0.7984, loss: 0.7984 +2025-06-24 13:15:32,557 - pyskl - INFO - Epoch [19][300/1281] lr: 2.410e-02, eta: 18:09:13, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8231, top5_acc: 0.9906, loss_cls: 0.7982, loss: 0.7982 +2025-06-24 13:16:10,605 - pyskl - INFO - Epoch [19][400/1281] lr: 2.409e-02, eta: 18:08:30, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8306, top5_acc: 0.9894, loss_cls: 0.7604, loss: 0.7604 +2025-06-24 13:16:49,279 - pyskl - INFO - Epoch [19][500/1281] lr: 2.408e-02, eta: 18:07:51, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.8119, top5_acc: 0.9931, loss_cls: 0.7905, loss: 0.7905 +2025-06-24 13:17:28,244 - pyskl - INFO - Epoch [19][600/1281] lr: 2.408e-02, eta: 18:07:14, time: 0.390, data_time: 0.000, memory: 4082, top1_acc: 0.8275, top5_acc: 0.9931, loss_cls: 0.7789, loss: 0.7789 +2025-06-24 13:18:06,920 - pyskl - INFO - Epoch [19][700/1281] lr: 2.407e-02, eta: 18:06:35, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.8106, top5_acc: 0.9919, loss_cls: 0.8201, loss: 0.8201 +2025-06-24 13:18:45,795 - pyskl - INFO - Epoch [19][800/1281] lr: 2.406e-02, eta: 18:05:57, time: 0.389, data_time: 0.000, memory: 4082, top1_acc: 0.8175, top5_acc: 0.9925, loss_cls: 0.7819, loss: 0.7819 +2025-06-24 13:19:24,358 - pyskl - INFO - Epoch [19][900/1281] lr: 2.405e-02, eta: 18:05:17, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8144, top5_acc: 0.9931, loss_cls: 0.7894, loss: 0.7894 +2025-06-24 13:20:03,100 - pyskl - INFO - Epoch [19][1000/1281] lr: 2.405e-02, eta: 18:04:39, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.8194, top5_acc: 0.9900, loss_cls: 0.7955, loss: 0.7955 +2025-06-24 13:20:41,670 - pyskl - INFO - Epoch [19][1100/1281] lr: 2.404e-02, eta: 18:03:59, time: 0.386, data_time: 0.001, memory: 4082, top1_acc: 0.8231, top5_acc: 0.9881, loss_cls: 0.8236, loss: 0.8236 +2025-06-24 13:21:19,968 - pyskl - INFO - Epoch [19][1200/1281] lr: 2.403e-02, eta: 18:03:17, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9938, loss_cls: 0.7383, loss: 0.7383 +2025-06-24 13:21:51,980 - pyskl - INFO - Saving checkpoint at 19 epochs +2025-06-24 13:22:51,617 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:22:51,687 - pyskl - INFO - +top1_acc 0.7511 +top5_acc 0.9755 +2025-06-24 13:22:51,687 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:22:51,696 - pyskl - INFO - +mean_acc 0.6504 +2025-06-24 13:22:51,698 - pyskl - INFO - Epoch(val) [19][533] top1_acc: 0.7511, top5_acc: 0.9755, mean_class_accuracy: 0.6504 +2025-06-24 13:23:37,065 - pyskl - INFO - Epoch [20][100/1281] lr: 2.402e-02, eta: 17:59:18, time: 0.454, data_time: 0.191, memory: 4082, top1_acc: 0.8281, top5_acc: 0.9925, loss_cls: 0.7515, loss: 0.7515 +2025-06-24 13:24:22,085 - pyskl - INFO - Epoch [20][200/1281] lr: 2.401e-02, eta: 17:59:23, time: 0.450, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9938, loss_cls: 0.7437, loss: 0.7437 +2025-06-24 13:24:44,593 - pyskl - INFO - Epoch [20][300/1281] lr: 2.400e-02, eta: 17:56:55, time: 0.225, data_time: 0.000, memory: 4082, top1_acc: 0.8169, top5_acc: 0.9912, loss_cls: 0.7946, loss: 0.7946 +2025-06-24 13:25:17,930 - pyskl - INFO - Epoch [20][400/1281] lr: 2.399e-02, eta: 17:55:41, time: 0.333, data_time: 0.000, memory: 4082, top1_acc: 0.8225, top5_acc: 0.9925, loss_cls: 0.7970, loss: 0.7970 +2025-06-24 13:25:56,168 - pyskl - INFO - Epoch [20][500/1281] lr: 2.398e-02, eta: 17:55:00, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9900, loss_cls: 0.7613, loss: 0.7613 +2025-06-24 13:26:33,566 - pyskl - INFO - Epoch [20][600/1281] lr: 2.398e-02, eta: 17:54:14, time: 0.374, data_time: 0.000, memory: 4082, top1_acc: 0.8163, top5_acc: 0.9919, loss_cls: 0.8164, loss: 0.8164 +2025-06-24 13:27:12,365 - pyskl - INFO - Epoch [20][700/1281] lr: 2.397e-02, eta: 17:53:37, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8237, top5_acc: 0.9894, loss_cls: 0.8109, loss: 0.8109 +2025-06-24 13:27:50,416 - pyskl - INFO - Epoch [20][800/1281] lr: 2.396e-02, eta: 17:52:55, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8069, top5_acc: 0.9912, loss_cls: 0.7956, loss: 0.7956 +2025-06-24 13:28:28,512 - pyskl - INFO - Epoch [20][900/1281] lr: 2.395e-02, eta: 17:52:13, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8250, top5_acc: 0.9900, loss_cls: 0.7912, loss: 0.7912 +2025-06-24 13:29:07,339 - pyskl - INFO - Epoch [20][1000/1281] lr: 2.394e-02, eta: 17:51:37, time: 0.388, data_time: 0.001, memory: 4082, top1_acc: 0.8219, top5_acc: 0.9875, loss_cls: 0.8105, loss: 0.8105 +2025-06-24 13:29:45,391 - pyskl - INFO - Epoch [20][1100/1281] lr: 2.393e-02, eta: 17:50:55, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8131, top5_acc: 0.9919, loss_cls: 0.7963, loss: 0.7963 +2025-06-24 13:30:23,580 - pyskl - INFO - Epoch [20][1200/1281] lr: 2.393e-02, eta: 17:50:14, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8200, top5_acc: 0.9881, loss_cls: 0.7832, loss: 0.7832 +2025-06-24 13:30:55,294 - pyskl - INFO - Saving checkpoint at 20 epochs +2025-06-24 13:31:54,626 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:31:54,705 - pyskl - INFO - +top1_acc 0.8013 +top5_acc 0.9878 +2025-06-24 13:31:54,705 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:31:54,715 - pyskl - INFO - +mean_acc 0.7120 +2025-06-24 13:31:54,721 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_17.pth was removed +2025-06-24 13:31:54,896 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_20.pth. +2025-06-24 13:31:54,896 - pyskl - INFO - Best top1_acc is 0.8013 at 20 epoch. +2025-06-24 13:31:54,900 - pyskl - INFO - Epoch(val) [20][533] top1_acc: 0.8013, top5_acc: 0.9878, mean_class_accuracy: 0.7120 +2025-06-24 13:32:53,178 - pyskl - INFO - Epoch [21][100/1281] lr: 2.391e-02, eta: 17:47:50, time: 0.583, data_time: 0.196, memory: 4082, top1_acc: 0.8344, top5_acc: 0.9944, loss_cls: 0.7240, loss: 0.7240 +2025-06-24 13:33:31,304 - pyskl - INFO - Epoch [21][200/1281] lr: 2.390e-02, eta: 17:47:09, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8350, top5_acc: 0.9925, loss_cls: 0.7389, loss: 0.7389 +2025-06-24 13:34:09,333 - pyskl - INFO - Epoch [21][300/1281] lr: 2.389e-02, eta: 17:46:28, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8494, top5_acc: 0.9919, loss_cls: 0.7057, loss: 0.7057 +2025-06-24 13:34:46,942 - pyskl - INFO - Epoch [21][400/1281] lr: 2.389e-02, eta: 17:45:43, time: 0.376, data_time: 0.000, memory: 4082, top1_acc: 0.7963, top5_acc: 0.9894, loss_cls: 0.8048, loss: 0.8048 +2025-06-24 13:35:23,216 - pyskl - INFO - Epoch [21][500/1281] lr: 2.388e-02, eta: 17:44:51, time: 0.363, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9931, loss_cls: 0.7566, loss: 0.7566 +2025-06-24 13:35:52,327 - pyskl - INFO - Epoch [21][600/1281] lr: 2.387e-02, eta: 17:43:13, time: 0.291, data_time: 0.000, memory: 4082, top1_acc: 0.8406, top5_acc: 0.9950, loss_cls: 0.7032, loss: 0.7032 +2025-06-24 13:36:34,544 - pyskl - INFO - Epoch [21][700/1281] lr: 2.386e-02, eta: 17:42:58, time: 0.422, data_time: 0.000, memory: 4082, top1_acc: 0.8150, top5_acc: 0.9912, loss_cls: 0.8116, loss: 0.8116 +2025-06-24 13:36:57,358 - pyskl - INFO - Epoch [21][800/1281] lr: 2.385e-02, eta: 17:40:42, time: 0.228, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9906, loss_cls: 0.7607, loss: 0.7607 +2025-06-24 13:37:31,630 - pyskl - INFO - Epoch [21][900/1281] lr: 2.384e-02, eta: 17:39:38, time: 0.343, data_time: 0.000, memory: 4082, top1_acc: 0.8269, top5_acc: 0.9894, loss_cls: 0.7842, loss: 0.7842 +2025-06-24 13:38:09,616 - pyskl - INFO - Epoch [21][1000/1281] lr: 2.383e-02, eta: 17:38:57, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8094, top5_acc: 0.9856, loss_cls: 0.8296, loss: 0.8296 +2025-06-24 13:38:47,882 - pyskl - INFO - Epoch [21][1100/1281] lr: 2.383e-02, eta: 17:38:18, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.8244, top5_acc: 0.9906, loss_cls: 0.7680, loss: 0.7680 +2025-06-24 13:39:25,980 - pyskl - INFO - Epoch [21][1200/1281] lr: 2.382e-02, eta: 17:37:37, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9900, loss_cls: 0.7526, loss: 0.7526 +2025-06-24 13:39:58,011 - pyskl - INFO - Saving checkpoint at 21 epochs +2025-06-24 13:40:57,807 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:40:57,864 - pyskl - INFO - +top1_acc 0.7715 +top5_acc 0.9805 +2025-06-24 13:40:57,864 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:40:57,872 - pyskl - INFO - +mean_acc 0.6570 +2025-06-24 13:40:57,874 - pyskl - INFO - Epoch(val) [21][533] top1_acc: 0.7715, top5_acc: 0.9805, mean_class_accuracy: 0.6570 +2025-06-24 13:41:56,823 - pyskl - INFO - Epoch [22][100/1281] lr: 2.380e-02, eta: 17:35:24, time: 0.589, data_time: 0.196, memory: 4082, top1_acc: 0.8325, top5_acc: 0.9944, loss_cls: 0.7342, loss: 0.7342 +2025-06-24 13:42:35,551 - pyskl - INFO - Epoch [22][200/1281] lr: 2.379e-02, eta: 17:34:47, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.8344, top5_acc: 0.9906, loss_cls: 0.7298, loss: 0.7298 +2025-06-24 13:43:14,514 - pyskl - INFO - Epoch [22][300/1281] lr: 2.378e-02, eta: 17:34:13, time: 0.390, data_time: 0.000, memory: 4082, top1_acc: 0.8488, top5_acc: 0.9919, loss_cls: 0.7250, loss: 0.7250 +2025-06-24 13:43:52,882 - pyskl - INFO - Epoch [22][400/1281] lr: 2.378e-02, eta: 17:33:35, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8600, top5_acc: 0.9944, loss_cls: 0.6808, loss: 0.6808 +2025-06-24 13:44:30,927 - pyskl - INFO - Epoch [22][500/1281] lr: 2.377e-02, eta: 17:32:54, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8144, top5_acc: 0.9925, loss_cls: 0.7766, loss: 0.7766 +2025-06-24 13:45:09,249 - pyskl - INFO - Epoch [22][600/1281] lr: 2.376e-02, eta: 17:32:16, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9856, loss_cls: 0.7868, loss: 0.7868 +2025-06-24 13:45:48,068 - pyskl - INFO - Epoch [22][700/1281] lr: 2.375e-02, eta: 17:31:40, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9931, loss_cls: 0.7771, loss: 0.7771 +2025-06-24 13:46:26,847 - pyskl - INFO - Epoch [22][800/1281] lr: 2.374e-02, eta: 17:31:05, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8263, top5_acc: 0.9919, loss_cls: 0.7640, loss: 0.7640 +2025-06-24 13:47:06,031 - pyskl - INFO - Epoch [22][900/1281] lr: 2.373e-02, eta: 17:30:31, time: 0.392, data_time: 0.000, memory: 4082, top1_acc: 0.8363, top5_acc: 0.9931, loss_cls: 0.7299, loss: 0.7299 +2025-06-24 13:47:35,033 - pyskl - INFO - Epoch [22][1000/1281] lr: 2.372e-02, eta: 17:28:58, time: 0.290, data_time: 0.000, memory: 4082, top1_acc: 0.8444, top5_acc: 0.9912, loss_cls: 0.7041, loss: 0.7041 +2025-06-24 13:48:13,835 - pyskl - INFO - Epoch [22][1100/1281] lr: 2.371e-02, eta: 17:28:22, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8063, top5_acc: 0.9919, loss_cls: 0.8226, loss: 0.8226 +2025-06-24 13:48:46,291 - pyskl - INFO - Epoch [22][1200/1281] lr: 2.370e-02, eta: 17:27:10, time: 0.325, data_time: 0.000, memory: 4082, top1_acc: 0.8256, top5_acc: 0.9888, loss_cls: 0.7781, loss: 0.7781 +2025-06-24 13:49:06,340 - pyskl - INFO - Saving checkpoint at 22 epochs +2025-06-24 13:50:05,952 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:50:06,026 - pyskl - INFO - +top1_acc 0.7693 +top5_acc 0.9786 +2025-06-24 13:50:06,026 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:50:06,036 - pyskl - INFO - +mean_acc 0.7044 +2025-06-24 13:50:06,039 - pyskl - INFO - Epoch(val) [22][533] top1_acc: 0.7693, top5_acc: 0.9786, mean_class_accuracy: 0.7044 +2025-06-24 13:51:04,314 - pyskl - INFO - Epoch [23][100/1281] lr: 2.369e-02, eta: 17:24:56, time: 0.583, data_time: 0.195, memory: 4082, top1_acc: 0.8450, top5_acc: 0.9931, loss_cls: 0.7030, loss: 0.7030 +2025-06-24 13:51:42,463 - pyskl - INFO - Epoch [23][200/1281] lr: 2.368e-02, eta: 17:24:17, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8425, top5_acc: 0.9925, loss_cls: 0.6803, loss: 0.6803 +2025-06-24 13:52:20,988 - pyskl - INFO - Epoch [23][300/1281] lr: 2.367e-02, eta: 17:23:41, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.8337, top5_acc: 0.9938, loss_cls: 0.7372, loss: 0.7372 +2025-06-24 13:52:58,188 - pyskl - INFO - Epoch [23][400/1281] lr: 2.366e-02, eta: 17:22:56, time: 0.372, data_time: 0.000, memory: 4082, top1_acc: 0.8450, top5_acc: 0.9950, loss_cls: 0.7332, loss: 0.7332 +2025-06-24 13:53:36,400 - pyskl - INFO - Epoch [23][500/1281] lr: 2.365e-02, eta: 17:22:18, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8231, top5_acc: 0.9906, loss_cls: 0.7841, loss: 0.7841 +2025-06-24 13:54:14,595 - pyskl - INFO - Epoch [23][600/1281] lr: 2.364e-02, eta: 17:21:39, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8356, top5_acc: 0.9944, loss_cls: 0.7445, loss: 0.7445 +2025-06-24 13:54:53,010 - pyskl - INFO - Epoch [23][700/1281] lr: 2.363e-02, eta: 17:21:02, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8369, top5_acc: 0.9869, loss_cls: 0.7820, loss: 0.7820 +2025-06-24 13:55:31,330 - pyskl - INFO - Epoch [23][800/1281] lr: 2.362e-02, eta: 17:20:24, time: 0.383, data_time: 0.001, memory: 4082, top1_acc: 0.8075, top5_acc: 0.9894, loss_cls: 0.8107, loss: 0.8107 +2025-06-24 13:56:10,360 - pyskl - INFO - Epoch [23][900/1281] lr: 2.361e-02, eta: 17:19:50, time: 0.390, data_time: 0.000, memory: 4082, top1_acc: 0.8363, top5_acc: 0.9925, loss_cls: 0.7441, loss: 0.7441 +2025-06-24 13:56:48,173 - pyskl - INFO - Epoch [23][1000/1281] lr: 2.360e-02, eta: 17:19:09, time: 0.378, data_time: 0.000, memory: 4082, top1_acc: 0.8331, top5_acc: 0.9919, loss_cls: 0.7483, loss: 0.7483 +2025-06-24 13:57:26,544 - pyskl - INFO - Epoch [23][1100/1281] lr: 2.359e-02, eta: 17:18:32, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8250, top5_acc: 0.9856, loss_cls: 0.7751, loss: 0.7751 +2025-06-24 13:58:04,742 - pyskl - INFO - Epoch [23][1200/1281] lr: 2.359e-02, eta: 17:17:53, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8169, top5_acc: 0.9894, loss_cls: 0.7777, loss: 0.7777 +2025-06-24 13:58:36,534 - pyskl - INFO - Saving checkpoint at 23 epochs +2025-06-24 13:59:26,753 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:59:26,809 - pyskl - INFO - +top1_acc 0.8064 +top5_acc 0.9887 +2025-06-24 13:59:26,809 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:59:26,816 - pyskl - INFO - +mean_acc 0.7265 +2025-06-24 13:59:26,821 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_20.pth was removed +2025-06-24 13:59:27,000 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_23.pth. +2025-06-24 13:59:27,000 - pyskl - INFO - Best top1_acc is 0.8064 at 23 epoch. +2025-06-24 13:59:27,003 - pyskl - INFO - Epoch(val) [23][533] top1_acc: 0.8064, top5_acc: 0.9887, mean_class_accuracy: 0.7265 +2025-06-24 14:00:15,430 - pyskl - INFO - Epoch [24][100/1281] lr: 2.357e-02, eta: 17:14:49, time: 0.484, data_time: 0.201, memory: 4082, top1_acc: 0.8606, top5_acc: 0.9931, loss_cls: 0.6464, loss: 0.6464 +2025-06-24 14:00:44,066 - pyskl - INFO - Epoch [24][200/1281] lr: 2.356e-02, eta: 17:13:19, time: 0.286, data_time: 0.000, memory: 4082, top1_acc: 0.8438, top5_acc: 0.9938, loss_cls: 0.6927, loss: 0.6927 +2025-06-24 14:01:22,949 - pyskl - INFO - Epoch [24][300/1281] lr: 2.355e-02, eta: 17:12:45, time: 0.389, data_time: 0.000, memory: 4082, top1_acc: 0.8406, top5_acc: 0.9894, loss_cls: 0.7261, loss: 0.7261 +2025-06-24 14:02:00,933 - pyskl - INFO - Epoch [24][400/1281] lr: 2.354e-02, eta: 17:12:05, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8325, top5_acc: 0.9950, loss_cls: 0.7077, loss: 0.7077 +2025-06-24 14:02:39,805 - pyskl - INFO - Epoch [24][500/1281] lr: 2.353e-02, eta: 17:11:31, time: 0.389, data_time: 0.000, memory: 4082, top1_acc: 0.8519, top5_acc: 0.9931, loss_cls: 0.6881, loss: 0.6881 +2025-06-24 14:03:18,083 - pyskl - INFO - Epoch [24][600/1281] lr: 2.352e-02, eta: 17:10:54, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.8256, top5_acc: 0.9931, loss_cls: 0.7471, loss: 0.7471 +2025-06-24 14:03:57,779 - pyskl - INFO - Epoch [24][700/1281] lr: 2.351e-02, eta: 17:10:24, time: 0.397, data_time: 0.000, memory: 4082, top1_acc: 0.8263, top5_acc: 0.9944, loss_cls: 0.7313, loss: 0.7313 +2025-06-24 14:04:36,545 - pyskl - INFO - Epoch [24][800/1281] lr: 2.350e-02, eta: 17:09:49, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8406, top5_acc: 0.9906, loss_cls: 0.7248, loss: 0.7248 +2025-06-24 14:05:14,726 - pyskl - INFO - Epoch [24][900/1281] lr: 2.349e-02, eta: 17:09:11, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8137, top5_acc: 0.9900, loss_cls: 0.8056, loss: 0.8056 +2025-06-24 14:05:52,089 - pyskl - INFO - Epoch [24][1000/1281] lr: 2.348e-02, eta: 17:08:28, time: 0.374, data_time: 0.000, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9912, loss_cls: 0.7282, loss: 0.7282 +2025-06-24 14:06:29,962 - pyskl - INFO - Epoch [24][1100/1281] lr: 2.347e-02, eta: 17:07:48, time: 0.379, data_time: 0.000, memory: 4082, top1_acc: 0.8475, top5_acc: 0.9938, loss_cls: 0.7163, loss: 0.7163 +2025-06-24 14:07:08,377 - pyskl - INFO - Epoch [24][1200/1281] lr: 2.346e-02, eta: 17:07:12, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8294, top5_acc: 0.9919, loss_cls: 0.7390, loss: 0.7390 +2025-06-24 14:07:39,780 - pyskl - INFO - Saving checkpoint at 24 epochs +2025-06-24 14:08:39,185 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:08:39,252 - pyskl - INFO - +top1_acc 0.7717 +top5_acc 0.9799 +2025-06-24 14:08:39,252 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:08:39,260 - pyskl - INFO - +mean_acc 0.7182 +2025-06-24 14:08:39,261 - pyskl - INFO - Epoch(val) [24][533] top1_acc: 0.7717, top5_acc: 0.9799, mean_class_accuracy: 0.7182 +2025-06-24 14:09:37,827 - pyskl - INFO - Epoch [25][100/1281] lr: 2.344e-02, eta: 17:05:08, time: 0.586, data_time: 0.198, memory: 4082, top1_acc: 0.8444, top5_acc: 0.9938, loss_cls: 0.7071, loss: 0.7071 +2025-06-24 14:10:16,276 - pyskl - INFO - Epoch [25][200/1281] lr: 2.343e-02, eta: 17:04:31, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8331, top5_acc: 0.9962, loss_cls: 0.7075, loss: 0.7075 +2025-06-24 14:10:53,561 - pyskl - INFO - Epoch [25][300/1281] lr: 2.342e-02, eta: 17:03:48, time: 0.373, data_time: 0.000, memory: 4082, top1_acc: 0.8313, top5_acc: 0.9925, loss_cls: 0.7319, loss: 0.7319 +2025-06-24 14:11:20,840 - pyskl - INFO - Epoch [25][400/1281] lr: 2.341e-02, eta: 17:02:14, time: 0.273, data_time: 0.000, memory: 4082, top1_acc: 0.8394, top5_acc: 0.9962, loss_cls: 0.6952, loss: 0.6952 +2025-06-24 14:12:04,690 - pyskl - INFO - Epoch [25][500/1281] lr: 2.340e-02, eta: 17:02:06, time: 0.439, data_time: 0.000, memory: 4082, top1_acc: 0.8488, top5_acc: 0.9931, loss_cls: 0.6763, loss: 0.6763 +2025-06-24 14:12:27,063 - pyskl - INFO - Epoch [25][600/1281] lr: 2.339e-02, eta: 17:00:07, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.8381, top5_acc: 0.9906, loss_cls: 0.7392, loss: 0.7392 +2025-06-24 14:13:00,876 - pyskl - INFO - Epoch [25][700/1281] lr: 2.338e-02, eta: 16:59:07, time: 0.338, data_time: 0.000, memory: 4082, top1_acc: 0.8263, top5_acc: 0.9919, loss_cls: 0.7653, loss: 0.7653 +2025-06-24 14:13:39,392 - pyskl - INFO - Epoch [25][800/1281] lr: 2.337e-02, eta: 16:58:31, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.8638, top5_acc: 0.9956, loss_cls: 0.6336, loss: 0.6336 +2025-06-24 14:14:17,543 - pyskl - INFO - Epoch [25][900/1281] lr: 2.336e-02, eta: 16:57:54, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8269, top5_acc: 0.9900, loss_cls: 0.7721, loss: 0.7721 +2025-06-24 14:14:56,204 - pyskl - INFO - Epoch [25][1000/1281] lr: 2.335e-02, eta: 16:57:19, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.8281, top5_acc: 0.9950, loss_cls: 0.7280, loss: 0.7280 +2025-06-24 14:15:34,382 - pyskl - INFO - Epoch [25][1100/1281] lr: 2.334e-02, eta: 16:56:42, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8369, top5_acc: 0.9931, loss_cls: 0.7249, loss: 0.7249 +2025-06-24 14:16:13,180 - pyskl - INFO - Epoch [25][1200/1281] lr: 2.333e-02, eta: 16:56:07, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8356, top5_acc: 0.9869, loss_cls: 0.7631, loss: 0.7631 +2025-06-24 14:16:44,661 - pyskl - INFO - Saving checkpoint at 25 epochs +2025-06-24 14:17:44,133 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:17:44,188 - pyskl - INFO - +top1_acc 0.8062 +top5_acc 0.9877 +2025-06-24 14:17:44,188 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:17:44,196 - pyskl - INFO - +mean_acc 0.7263 +2025-06-24 14:17:44,198 - pyskl - INFO - Epoch(val) [25][533] top1_acc: 0.8062, top5_acc: 0.9877, mean_class_accuracy: 0.7263 +2025-06-24 14:18:41,812 - pyskl - INFO - Epoch [26][100/1281] lr: 2.332e-02, eta: 16:54:02, time: 0.576, data_time: 0.190, memory: 4082, top1_acc: 0.8556, top5_acc: 0.9962, loss_cls: 0.6353, loss: 0.6353 +2025-06-24 14:19:20,197 - pyskl - INFO - Epoch [26][200/1281] lr: 2.330e-02, eta: 16:53:26, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8325, top5_acc: 0.9931, loss_cls: 0.7212, loss: 0.7212 +2025-06-24 14:19:58,667 - pyskl - INFO - Epoch [26][300/1281] lr: 2.329e-02, eta: 16:52:50, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.8325, top5_acc: 0.9919, loss_cls: 0.7138, loss: 0.7138 +2025-06-24 14:20:37,278 - pyskl - INFO - Epoch [26][400/1281] lr: 2.328e-02, eta: 16:52:15, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8569, top5_acc: 0.9925, loss_cls: 0.6873, loss: 0.6873 +2025-06-24 14:21:16,262 - pyskl - INFO - Epoch [26][500/1281] lr: 2.327e-02, eta: 16:51:42, time: 0.390, data_time: 0.000, memory: 4082, top1_acc: 0.8369, top5_acc: 0.9931, loss_cls: 0.7345, loss: 0.7345 +2025-06-24 14:21:54,989 - pyskl - INFO - Epoch [26][600/1281] lr: 2.326e-02, eta: 16:51:07, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.8450, top5_acc: 0.9944, loss_cls: 0.6592, loss: 0.6592 +2025-06-24 14:22:33,149 - pyskl - INFO - Epoch [26][700/1281] lr: 2.325e-02, eta: 16:50:30, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8612, top5_acc: 0.9919, loss_cls: 0.6807, loss: 0.6807 +2025-06-24 14:23:04,623 - pyskl - INFO - Epoch [26][800/1281] lr: 2.324e-02, eta: 16:49:20, time: 0.315, data_time: 0.000, memory: 4082, top1_acc: 0.8369, top5_acc: 0.9925, loss_cls: 0.7329, loss: 0.7329 +2025-06-24 14:23:41,162 - pyskl - INFO - Epoch [26][900/1281] lr: 2.323e-02, eta: 16:48:35, time: 0.365, data_time: 0.000, memory: 4082, top1_acc: 0.8294, top5_acc: 0.9900, loss_cls: 0.7554, loss: 0.7554 +2025-06-24 14:24:15,619 - pyskl - INFO - Epoch [26][1000/1281] lr: 2.322e-02, eta: 16:47:40, time: 0.345, data_time: 0.000, memory: 4082, top1_acc: 0.8500, top5_acc: 0.9912, loss_cls: 0.7007, loss: 0.7007 +2025-06-24 14:24:41,085 - pyskl - INFO - Epoch [26][1100/1281] lr: 2.321e-02, eta: 16:46:01, time: 0.255, data_time: 0.001, memory: 4082, top1_acc: 0.8325, top5_acc: 0.9956, loss_cls: 0.7421, loss: 0.7421 +2025-06-24 14:25:19,613 - pyskl - INFO - Epoch [26][1200/1281] lr: 2.320e-02, eta: 16:45:26, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.8494, top5_acc: 0.9919, loss_cls: 0.6783, loss: 0.6783 +2025-06-24 14:25:50,862 - pyskl - INFO - Saving checkpoint at 26 epochs +2025-06-24 14:26:50,486 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:26:50,556 - pyskl - INFO - +top1_acc 0.8040 +top5_acc 0.9839 +2025-06-24 14:26:50,556 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:26:50,564 - pyskl - INFO - +mean_acc 0.7119 +2025-06-24 14:26:50,567 - pyskl - INFO - Epoch(val) [26][533] top1_acc: 0.8040, top5_acc: 0.9839, mean_class_accuracy: 0.7119 +2025-06-24 14:27:49,299 - pyskl - INFO - Epoch [27][100/1281] lr: 2.318e-02, eta: 16:43:30, time: 0.587, data_time: 0.193, memory: 4082, top1_acc: 0.8394, top5_acc: 0.9944, loss_cls: 0.7032, loss: 0.7032 +2025-06-24 14:28:27,905 - pyskl - INFO - Epoch [27][200/1281] lr: 2.317e-02, eta: 16:42:55, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8581, top5_acc: 0.9919, loss_cls: 0.6528, loss: 0.6528 +2025-06-24 14:29:05,864 - pyskl - INFO - Epoch [27][300/1281] lr: 2.316e-02, eta: 16:42:18, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8431, top5_acc: 0.9925, loss_cls: 0.7137, loss: 0.7137 +2025-06-24 14:29:44,613 - pyskl - INFO - Epoch [27][400/1281] lr: 2.315e-02, eta: 16:41:43, time: 0.387, data_time: 0.001, memory: 4082, top1_acc: 0.8438, top5_acc: 0.9956, loss_cls: 0.6844, loss: 0.6844 +2025-06-24 14:30:23,127 - pyskl - INFO - Epoch [27][500/1281] lr: 2.314e-02, eta: 16:41:08, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.8481, top5_acc: 0.9888, loss_cls: 0.6829, loss: 0.6829 +2025-06-24 14:31:01,613 - pyskl - INFO - Epoch [27][600/1281] lr: 2.313e-02, eta: 16:40:33, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.8337, top5_acc: 0.9956, loss_cls: 0.7164, loss: 0.7164 +2025-06-24 14:31:40,095 - pyskl - INFO - Epoch [27][700/1281] lr: 2.312e-02, eta: 16:39:57, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9969, loss_cls: 0.7049, loss: 0.7049 +2025-06-24 14:32:18,536 - pyskl - INFO - Epoch [27][800/1281] lr: 2.311e-02, eta: 16:39:22, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8594, top5_acc: 0.9956, loss_cls: 0.6561, loss: 0.6561 +2025-06-24 14:32:57,565 - pyskl - INFO - Epoch [27][900/1281] lr: 2.310e-02, eta: 16:38:49, time: 0.390, data_time: 0.000, memory: 4082, top1_acc: 0.8556, top5_acc: 0.9962, loss_cls: 0.6613, loss: 0.6613 +2025-06-24 14:33:35,651 - pyskl - INFO - Epoch [27][1000/1281] lr: 2.308e-02, eta: 16:38:12, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8369, top5_acc: 0.9944, loss_cls: 0.7131, loss: 0.7131 +2025-06-24 14:34:13,858 - pyskl - INFO - Epoch [27][1100/1281] lr: 2.307e-02, eta: 16:37:35, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8575, top5_acc: 0.9906, loss_cls: 0.6840, loss: 0.6840 +2025-06-24 14:34:52,629 - pyskl - INFO - Epoch [27][1200/1281] lr: 2.306e-02, eta: 16:37:01, time: 0.388, data_time: 0.001, memory: 4082, top1_acc: 0.8350, top5_acc: 0.9894, loss_cls: 0.7519, loss: 0.7519 +2025-06-24 14:35:12,236 - pyskl - INFO - Saving checkpoint at 27 epochs +2025-06-24 14:36:07,497 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:36:07,567 - pyskl - INFO - +top1_acc 0.7776 +top5_acc 0.9738 +2025-06-24 14:36:07,567 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:36:07,577 - pyskl - INFO - +mean_acc 0.6715 +2025-06-24 14:36:07,579 - pyskl - INFO - Epoch(val) [27][533] top1_acc: 0.7776, top5_acc: 0.9738, mean_class_accuracy: 0.6715 +2025-06-24 14:37:05,553 - pyskl - INFO - Epoch [28][100/1281] lr: 2.304e-02, eta: 16:35:03, time: 0.580, data_time: 0.191, memory: 4082, top1_acc: 0.8644, top5_acc: 0.9956, loss_cls: 0.6247, loss: 0.6247 +2025-06-24 14:37:43,699 - pyskl - INFO - Epoch [28][200/1281] lr: 2.303e-02, eta: 16:34:26, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8444, top5_acc: 0.9975, loss_cls: 0.6563, loss: 0.6563 +2025-06-24 14:38:22,278 - pyskl - INFO - Epoch [28][300/1281] lr: 2.302e-02, eta: 16:33:52, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8625, top5_acc: 0.9931, loss_cls: 0.6247, loss: 0.6247 +2025-06-24 14:39:00,029 - pyskl - INFO - Epoch [28][400/1281] lr: 2.301e-02, eta: 16:33:13, time: 0.378, data_time: 0.000, memory: 4082, top1_acc: 0.8525, top5_acc: 0.9888, loss_cls: 0.6727, loss: 0.6727 +2025-06-24 14:39:37,932 - pyskl - INFO - Epoch [28][500/1281] lr: 2.300e-02, eta: 16:32:35, time: 0.379, data_time: 0.001, memory: 4082, top1_acc: 0.8194, top5_acc: 0.9906, loss_cls: 0.7907, loss: 0.7907 +2025-06-24 14:40:16,288 - pyskl - INFO - Epoch [28][600/1281] lr: 2.299e-02, eta: 16:31:59, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8638, top5_acc: 0.9912, loss_cls: 0.6613, loss: 0.6613 +2025-06-24 14:40:54,657 - pyskl - INFO - Epoch [28][700/1281] lr: 2.298e-02, eta: 16:31:23, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8350, top5_acc: 0.9938, loss_cls: 0.7177, loss: 0.7177 +2025-06-24 14:41:32,798 - pyskl - INFO - Epoch [28][800/1281] lr: 2.297e-02, eta: 16:30:46, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8381, top5_acc: 0.9919, loss_cls: 0.7407, loss: 0.7407 +2025-06-24 14:42:11,054 - pyskl - INFO - Epoch [28][900/1281] lr: 2.295e-02, eta: 16:30:10, time: 0.383, data_time: 0.001, memory: 4082, top1_acc: 0.8444, top5_acc: 0.9944, loss_cls: 0.7168, loss: 0.7168 +2025-06-24 14:42:49,521 - pyskl - INFO - Epoch [28][1000/1281] lr: 2.294e-02, eta: 16:29:34, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.8369, top5_acc: 0.9888, loss_cls: 0.7583, loss: 0.7583 +2025-06-24 14:43:27,409 - pyskl - INFO - Epoch [28][1100/1281] lr: 2.293e-02, eta: 16:28:56, time: 0.379, data_time: 0.000, memory: 4082, top1_acc: 0.8381, top5_acc: 0.9956, loss_cls: 0.7060, loss: 0.7060 +2025-06-24 14:44:05,295 - pyskl - INFO - Epoch [28][1200/1281] lr: 2.292e-02, eta: 16:28:18, time: 0.379, data_time: 0.000, memory: 4082, top1_acc: 0.8462, top5_acc: 0.9894, loss_cls: 0.7048, loss: 0.7048 +2025-06-24 14:44:36,916 - pyskl - INFO - Saving checkpoint at 28 epochs +2025-06-24 14:45:35,910 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:45:35,968 - pyskl - INFO - +top1_acc 0.7937 +top5_acc 0.9844 +2025-06-24 14:45:35,968 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:45:35,976 - pyskl - INFO - +mean_acc 0.7228 +2025-06-24 14:45:35,978 - pyskl - INFO - Epoch(val) [28][533] top1_acc: 0.7937, top5_acc: 0.9844, mean_class_accuracy: 0.7228 +2025-06-24 14:46:25,988 - pyskl - INFO - Epoch [29][100/1281] lr: 2.290e-02, eta: 16:25:48, time: 0.500, data_time: 0.195, memory: 4082, top1_acc: 0.8481, top5_acc: 0.9944, loss_cls: 0.6490, loss: 0.6490 +2025-06-24 14:47:03,139 - pyskl - INFO - Epoch [29][200/1281] lr: 2.289e-02, eta: 16:25:07, time: 0.371, data_time: 0.000, memory: 4082, top1_acc: 0.8531, top5_acc: 0.9944, loss_cls: 0.6291, loss: 0.6291 +2025-06-24 14:47:37,002 - pyskl - INFO - Epoch [29][300/1281] lr: 2.288e-02, eta: 16:24:12, time: 0.339, data_time: 0.000, memory: 4082, top1_acc: 0.8538, top5_acc: 0.9962, loss_cls: 0.6609, loss: 0.6609 +2025-06-24 14:48:00,863 - pyskl - INFO - Epoch [29][400/1281] lr: 2.287e-02, eta: 16:22:34, time: 0.239, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9938, loss_cls: 0.6386, loss: 0.6386 +2025-06-24 14:48:39,967 - pyskl - INFO - Epoch [29][500/1281] lr: 2.285e-02, eta: 16:22:02, time: 0.391, data_time: 0.000, memory: 4082, top1_acc: 0.8581, top5_acc: 0.9931, loss_cls: 0.6252, loss: 0.6252 +2025-06-24 14:49:18,335 - pyskl - INFO - Epoch [29][600/1281] lr: 2.284e-02, eta: 16:21:26, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9925, loss_cls: 0.6168, loss: 0.6168 +2025-06-24 14:49:56,460 - pyskl - INFO - Epoch [29][700/1281] lr: 2.283e-02, eta: 16:20:50, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8425, top5_acc: 0.9944, loss_cls: 0.6735, loss: 0.6735 +2025-06-24 14:50:34,421 - pyskl - INFO - Epoch [29][800/1281] lr: 2.282e-02, eta: 16:20:12, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8562, top5_acc: 0.9906, loss_cls: 0.6873, loss: 0.6873 +2025-06-24 14:51:11,963 - pyskl - INFO - Epoch [29][900/1281] lr: 2.281e-02, eta: 16:19:33, time: 0.375, data_time: 0.000, memory: 4082, top1_acc: 0.8594, top5_acc: 0.9962, loss_cls: 0.6746, loss: 0.6746 +2025-06-24 14:51:51,023 - pyskl - INFO - Epoch [29][1000/1281] lr: 2.280e-02, eta: 16:19:01, time: 0.391, data_time: 0.000, memory: 4082, top1_acc: 0.8475, top5_acc: 0.9919, loss_cls: 0.6751, loss: 0.6751 +2025-06-24 14:52:29,745 - pyskl - INFO - Epoch [29][1100/1281] lr: 2.279e-02, eta: 16:18:27, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9931, loss_cls: 0.7163, loss: 0.7163 +2025-06-24 14:53:07,811 - pyskl - INFO - Epoch [29][1200/1281] lr: 2.277e-02, eta: 16:17:50, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8500, top5_acc: 0.9931, loss_cls: 0.6666, loss: 0.6666 +2025-06-24 14:53:39,977 - pyskl - INFO - Saving checkpoint at 29 epochs +2025-06-24 14:54:40,101 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:54:40,166 - pyskl - INFO - +top1_acc 0.7954 +top5_acc 0.9851 +2025-06-24 14:54:40,166 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:54:40,173 - pyskl - INFO - +mean_acc 0.7026 +2025-06-24 14:54:40,176 - pyskl - INFO - Epoch(val) [29][533] top1_acc: 0.7954, top5_acc: 0.9851, mean_class_accuracy: 0.7026 +2025-06-24 14:55:47,698 - pyskl - INFO - Epoch [30][100/1281] lr: 2.275e-02, eta: 16:16:37, time: 0.675, data_time: 0.189, memory: 4082, top1_acc: 0.8506, top5_acc: 0.9938, loss_cls: 0.6790, loss: 0.6790 +2025-06-24 14:56:35,746 - pyskl - INFO - Epoch [30][200/1281] lr: 2.274e-02, eta: 16:16:42, time: 0.480, data_time: 0.000, memory: 4082, top1_acc: 0.8675, top5_acc: 0.9944, loss_cls: 0.6282, loss: 0.6282 +2025-06-24 14:57:23,902 - pyskl - INFO - Epoch [30][300/1281] lr: 2.273e-02, eta: 16:16:47, time: 0.482, data_time: 0.000, memory: 4082, top1_acc: 0.8656, top5_acc: 0.9944, loss_cls: 0.6035, loss: 0.6035 +2025-06-24 14:58:09,165 - pyskl - INFO - Epoch [30][400/1281] lr: 2.272e-02, eta: 16:16:39, time: 0.453, data_time: 0.000, memory: 4082, top1_acc: 0.8444, top5_acc: 0.9938, loss_cls: 0.6967, loss: 0.6967 +2025-06-24 14:58:46,788 - pyskl - INFO - Epoch [30][500/1281] lr: 2.271e-02, eta: 16:16:00, time: 0.376, data_time: 0.000, memory: 4082, top1_acc: 0.8438, top5_acc: 0.9881, loss_cls: 0.7332, loss: 0.7332 +2025-06-24 14:59:23,060 - pyskl - INFO - Epoch [30][600/1281] lr: 2.269e-02, eta: 16:15:15, time: 0.363, data_time: 0.001, memory: 4082, top1_acc: 0.8337, top5_acc: 0.9931, loss_cls: 0.7225, loss: 0.7225 +2025-06-24 15:00:00,388 - pyskl - INFO - Epoch [30][700/1281] lr: 2.268e-02, eta: 16:14:35, time: 0.373, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9925, loss_cls: 0.7285, loss: 0.7285 +2025-06-24 15:00:48,834 - pyskl - INFO - Epoch [30][800/1281] lr: 2.267e-02, eta: 16:14:40, time: 0.484, data_time: 0.000, memory: 4082, top1_acc: 0.8638, top5_acc: 0.9969, loss_cls: 0.6158, loss: 0.6158 +2025-06-24 15:01:37,063 - pyskl - INFO - Epoch [30][900/1281] lr: 2.266e-02, eta: 16:14:44, time: 0.482, data_time: 0.000, memory: 4082, top1_acc: 0.8538, top5_acc: 0.9938, loss_cls: 0.6783, loss: 0.6783 +2025-06-24 15:02:25,398 - pyskl - INFO - Epoch [30][1000/1281] lr: 2.265e-02, eta: 16:14:48, time: 0.483, data_time: 0.000, memory: 4082, top1_acc: 0.8556, top5_acc: 0.9906, loss_cls: 0.6608, loss: 0.6608 +2025-06-24 15:03:13,512 - pyskl - INFO - Epoch [30][1100/1281] lr: 2.263e-02, eta: 16:14:51, time: 0.481, data_time: 0.000, memory: 4082, top1_acc: 0.8456, top5_acc: 0.9938, loss_cls: 0.6944, loss: 0.6944 +2025-06-24 15:04:01,862 - pyskl - INFO - Epoch [30][1200/1281] lr: 2.262e-02, eta: 16:14:54, time: 0.484, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9938, loss_cls: 0.7179, loss: 0.7179 +2025-06-24 15:04:41,725 - pyskl - INFO - Saving checkpoint at 30 epochs +2025-06-24 15:05:41,358 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:05:41,423 - pyskl - INFO - +top1_acc 0.7967 +top5_acc 0.9862 +2025-06-24 15:05:41,423 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:05:41,431 - pyskl - INFO - +mean_acc 0.7230 +2025-06-24 15:05:41,434 - pyskl - INFO - Epoch(val) [30][533] top1_acc: 0.7967, top5_acc: 0.9862, mean_class_accuracy: 0.7230 +2025-06-24 15:07:07,820 - pyskl - INFO - Epoch [31][100/1281] lr: 2.260e-02, eta: 16:14:55, time: 0.864, data_time: 0.196, memory: 4083, top1_acc: 0.8606, top5_acc: 0.9931, loss_cls: 0.7820, loss: 0.7820 +2025-06-24 15:07:56,784 - pyskl - INFO - Epoch [31][200/1281] lr: 2.259e-02, eta: 16:15:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8575, top5_acc: 0.9944, loss_cls: 0.7714, loss: 0.7714 +2025-06-24 15:08:46,227 - pyskl - INFO - Epoch [31][300/1281] lr: 2.258e-02, eta: 16:15:07, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8600, top5_acc: 0.9956, loss_cls: 0.7954, loss: 0.7954 +2025-06-24 15:09:26,343 - pyskl - INFO - Epoch [31][400/1281] lr: 2.256e-02, eta: 16:14:37, time: 0.401, data_time: 0.000, memory: 4083, top1_acc: 0.8413, top5_acc: 0.9912, loss_cls: 0.8339, loss: 0.8339 +2025-06-24 15:10:16,168 - pyskl - INFO - Epoch [31][500/1281] lr: 2.255e-02, eta: 16:14:45, time: 0.498, data_time: 0.000, memory: 4083, top1_acc: 0.8475, top5_acc: 0.9900, loss_cls: 0.8336, loss: 0.8336 +2025-06-24 15:10:40,597 - pyskl - INFO - Epoch [31][600/1281] lr: 2.254e-02, eta: 16:13:13, time: 0.244, data_time: 0.000, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9969, loss_cls: 0.7817, loss: 0.7817 +2025-06-24 15:11:22,624 - pyskl - INFO - Epoch [31][700/1281] lr: 2.253e-02, eta: 16:12:50, time: 0.420, data_time: 0.000, memory: 4083, top1_acc: 0.8538, top5_acc: 0.9925, loss_cls: 0.8310, loss: 0.8310 +2025-06-24 15:12:11,612 - pyskl - INFO - Epoch [31][800/1281] lr: 2.252e-02, eta: 16:12:54, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8575, top5_acc: 0.9925, loss_cls: 0.7877, loss: 0.7877 +2025-06-24 15:13:00,771 - pyskl - INFO - Epoch [31][900/1281] lr: 2.250e-02, eta: 16:12:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8644, top5_acc: 0.9969, loss_cls: 0.7510, loss: 0.7510 +2025-06-24 15:13:50,024 - pyskl - INFO - Epoch [31][1000/1281] lr: 2.249e-02, eta: 16:13:03, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8456, top5_acc: 0.9938, loss_cls: 0.8398, loss: 0.8398 +2025-06-24 15:14:38,923 - pyskl - INFO - Epoch [31][1100/1281] lr: 2.248e-02, eta: 16:13:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8313, top5_acc: 0.9912, loss_cls: 0.8799, loss: 0.8799 +2025-06-24 15:15:27,897 - pyskl - INFO - Epoch [31][1200/1281] lr: 2.247e-02, eta: 16:13:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8612, top5_acc: 0.9931, loss_cls: 0.7771, loss: 0.7771 +2025-06-24 15:16:08,223 - pyskl - INFO - Saving checkpoint at 31 epochs +2025-06-24 15:17:07,785 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:17:07,840 - pyskl - INFO - +top1_acc 0.8001 +top5_acc 0.9853 +2025-06-24 15:17:07,840 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:17:07,847 - pyskl - INFO - +mean_acc 0.7506 +2025-06-24 15:17:07,849 - pyskl - INFO - Epoch(val) [31][533] top1_acc: 0.8001, top5_acc: 0.9853, mean_class_accuracy: 0.7506 +2025-06-24 15:18:28,019 - pyskl - INFO - Epoch [32][100/1281] lr: 2.244e-02, eta: 16:12:41, time: 0.802, data_time: 0.192, memory: 4083, top1_acc: 0.8569, top5_acc: 0.9938, loss_cls: 0.7428, loss: 0.7428 +2025-06-24 15:19:16,911 - pyskl - INFO - Epoch [32][200/1281] lr: 2.243e-02, eta: 16:12:43, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9950, loss_cls: 0.6915, loss: 0.6915 +2025-06-24 15:20:05,651 - pyskl - INFO - Epoch [32][300/1281] lr: 2.242e-02, eta: 16:12:45, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8512, top5_acc: 0.9944, loss_cls: 0.7425, loss: 0.7425 +2025-06-24 15:20:46,555 - pyskl - INFO - Epoch [32][400/1281] lr: 2.241e-02, eta: 16:12:16, time: 0.409, data_time: 0.000, memory: 4083, top1_acc: 0.8562, top5_acc: 0.9925, loss_cls: 0.7446, loss: 0.7446 +2025-06-24 15:21:36,119 - pyskl - INFO - Epoch [32][500/1281] lr: 2.239e-02, eta: 16:12:20, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8450, top5_acc: 0.9950, loss_cls: 0.7738, loss: 0.7738 +2025-06-24 15:22:01,018 - pyskl - INFO - Epoch [32][600/1281] lr: 2.238e-02, eta: 16:10:51, time: 0.249, data_time: 0.000, memory: 4083, top1_acc: 0.8544, top5_acc: 0.9925, loss_cls: 0.7475, loss: 0.7475 +2025-06-24 15:22:43,338 - pyskl - INFO - Epoch [32][700/1281] lr: 2.237e-02, eta: 16:10:27, time: 0.423, data_time: 0.000, memory: 4083, top1_acc: 0.8462, top5_acc: 0.9956, loss_cls: 0.7684, loss: 0.7684 +2025-06-24 15:23:32,487 - pyskl - INFO - Epoch [32][800/1281] lr: 2.236e-02, eta: 16:10:29, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8644, top5_acc: 0.9956, loss_cls: 0.6845, loss: 0.6845 +2025-06-24 15:24:21,641 - pyskl - INFO - Epoch [32][900/1281] lr: 2.234e-02, eta: 16:10:31, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8594, top5_acc: 0.9962, loss_cls: 0.7016, loss: 0.7016 +2025-06-24 15:25:10,991 - pyskl - INFO - Epoch [32][1000/1281] lr: 2.233e-02, eta: 16:10:33, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8531, top5_acc: 0.9944, loss_cls: 0.7463, loss: 0.7463 +2025-06-24 15:26:00,112 - pyskl - INFO - Epoch [32][1100/1281] lr: 2.232e-02, eta: 16:10:34, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9956, loss_cls: 0.7000, loss: 0.7000 +2025-06-24 15:26:48,996 - pyskl - INFO - Epoch [32][1200/1281] lr: 2.231e-02, eta: 16:10:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8387, top5_acc: 0.9944, loss_cls: 0.7497, loss: 0.7497 +2025-06-24 15:27:29,082 - pyskl - INFO - Saving checkpoint at 32 epochs +2025-06-24 15:28:27,898 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:28:27,964 - pyskl - INFO - +top1_acc 0.8253 +top5_acc 0.9889 +2025-06-24 15:28:27,964 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:28:27,974 - pyskl - INFO - +mean_acc 0.7624 +2025-06-24 15:28:27,979 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_23.pth was removed +2025-06-24 15:28:28,169 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_32.pth. +2025-06-24 15:28:28,169 - pyskl - INFO - Best top1_acc is 0.8253 at 32 epoch. +2025-06-24 15:28:28,172 - pyskl - INFO - Epoch(val) [32][533] top1_acc: 0.8253, top5_acc: 0.9889, mean_class_accuracy: 0.7624 +2025-06-24 15:29:48,619 - pyskl - INFO - Epoch [33][100/1281] lr: 2.228e-02, eta: 16:10:04, time: 0.804, data_time: 0.191, memory: 4083, top1_acc: 0.8569, top5_acc: 0.9944, loss_cls: 0.6815, loss: 0.6815 +2025-06-24 15:30:37,750 - pyskl - INFO - Epoch [33][200/1281] lr: 2.227e-02, eta: 16:10:04, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8519, top5_acc: 0.9944, loss_cls: 0.7240, loss: 0.7240 +2025-06-24 15:31:26,939 - pyskl - INFO - Epoch [33][300/1281] lr: 2.226e-02, eta: 16:10:04, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8600, top5_acc: 0.9912, loss_cls: 0.7351, loss: 0.7351 +2025-06-24 15:32:07,646 - pyskl - INFO - Epoch [33][400/1281] lr: 2.225e-02, eta: 16:09:34, time: 0.407, data_time: 0.000, memory: 4083, top1_acc: 0.8369, top5_acc: 0.9919, loss_cls: 0.7760, loss: 0.7760 +2025-06-24 15:32:57,042 - pyskl - INFO - Epoch [33][500/1281] lr: 2.223e-02, eta: 16:09:34, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8600, top5_acc: 0.9925, loss_cls: 0.6931, loss: 0.6931 +2025-06-24 15:33:21,769 - pyskl - INFO - Epoch [33][600/1281] lr: 2.222e-02, eta: 16:08:05, time: 0.247, data_time: 0.000, memory: 4083, top1_acc: 0.8494, top5_acc: 0.9962, loss_cls: 0.7523, loss: 0.7523 +2025-06-24 15:34:04,073 - pyskl - INFO - Epoch [33][700/1281] lr: 2.221e-02, eta: 16:07:40, time: 0.423, data_time: 0.000, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9956, loss_cls: 0.6806, loss: 0.6806 +2025-06-24 15:34:53,016 - pyskl - INFO - Epoch [33][800/1281] lr: 2.219e-02, eta: 16:07:39, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8456, top5_acc: 0.9906, loss_cls: 0.7973, loss: 0.7973 +2025-06-24 15:35:42,300 - pyskl - INFO - Epoch [33][900/1281] lr: 2.218e-02, eta: 16:07:38, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8544, top5_acc: 0.9962, loss_cls: 0.7191, loss: 0.7191 +2025-06-24 15:36:32,033 - pyskl - INFO - Epoch [33][1000/1281] lr: 2.217e-02, eta: 16:07:40, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.8481, top5_acc: 0.9925, loss_cls: 0.7115, loss: 0.7115 +2025-06-24 15:37:21,228 - pyskl - INFO - Epoch [33][1100/1281] lr: 2.216e-02, eta: 16:07:38, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8531, top5_acc: 0.9912, loss_cls: 0.7268, loss: 0.7268 +2025-06-24 15:38:10,178 - pyskl - INFO - Epoch [33][1200/1281] lr: 2.214e-02, eta: 16:07:36, time: 0.490, data_time: 0.001, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9944, loss_cls: 0.7021, loss: 0.7021 +2025-06-24 15:38:50,612 - pyskl - INFO - Saving checkpoint at 33 epochs +2025-06-24 15:39:49,267 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:39:49,334 - pyskl - INFO - +top1_acc 0.8001 +top5_acc 0.9836 +2025-06-24 15:39:49,334 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:39:49,342 - pyskl - INFO - +mean_acc 0.7396 +2025-06-24 15:39:49,344 - pyskl - INFO - Epoch(val) [33][533] top1_acc: 0.8001, top5_acc: 0.9836, mean_class_accuracy: 0.7396 +2025-06-24 15:41:10,407 - pyskl - INFO - Epoch [34][100/1281] lr: 2.212e-02, eta: 16:07:05, time: 0.811, data_time: 0.198, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9956, loss_cls: 0.6792, loss: 0.6792 +2025-06-24 15:41:59,547 - pyskl - INFO - Epoch [34][200/1281] lr: 2.211e-02, eta: 16:07:03, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8650, top5_acc: 0.9956, loss_cls: 0.6509, loss: 0.6509 +2025-06-24 15:42:48,722 - pyskl - INFO - Epoch [34][300/1281] lr: 2.209e-02, eta: 16:07:01, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8581, top5_acc: 0.9956, loss_cls: 0.6802, loss: 0.6802 +2025-06-24 15:43:30,644 - pyskl - INFO - Epoch [34][400/1281] lr: 2.208e-02, eta: 16:06:33, time: 0.419, data_time: 0.000, memory: 4083, top1_acc: 0.8581, top5_acc: 0.9944, loss_cls: 0.7134, loss: 0.7134 +2025-06-24 15:44:17,457 - pyskl - INFO - Epoch [34][500/1281] lr: 2.207e-02, eta: 16:06:22, time: 0.468, data_time: 0.001, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9912, loss_cls: 0.6763, loss: 0.6763 +2025-06-24 15:44:44,496 - pyskl - INFO - Epoch [34][600/1281] lr: 2.205e-02, eta: 16:05:02, time: 0.270, data_time: 0.000, memory: 4083, top1_acc: 0.8625, top5_acc: 0.9956, loss_cls: 0.7046, loss: 0.7046 +2025-06-24 15:45:26,763 - pyskl - INFO - Epoch [34][700/1281] lr: 2.204e-02, eta: 16:04:35, time: 0.423, data_time: 0.000, memory: 4083, top1_acc: 0.8562, top5_acc: 0.9950, loss_cls: 0.7101, loss: 0.7101 +2025-06-24 15:46:15,806 - pyskl - INFO - Epoch [34][800/1281] lr: 2.203e-02, eta: 16:04:32, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8531, top5_acc: 0.9931, loss_cls: 0.7011, loss: 0.7011 +2025-06-24 15:47:04,819 - pyskl - INFO - Epoch [34][900/1281] lr: 2.201e-02, eta: 16:04:28, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8494, top5_acc: 0.9944, loss_cls: 0.7300, loss: 0.7300 +2025-06-24 15:47:54,560 - pyskl - INFO - Epoch [34][1000/1281] lr: 2.200e-02, eta: 16:04:27, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.8525, top5_acc: 0.9906, loss_cls: 0.7107, loss: 0.7107 +2025-06-24 15:48:43,617 - pyskl - INFO - Epoch [34][1100/1281] lr: 2.199e-02, eta: 16:04:23, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8606, top5_acc: 0.9950, loss_cls: 0.6931, loss: 0.6931 +2025-06-24 15:49:32,190 - pyskl - INFO - Epoch [34][1200/1281] lr: 2.197e-02, eta: 16:04:17, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.8556, top5_acc: 0.9925, loss_cls: 0.7235, loss: 0.7235 +2025-06-24 15:50:12,867 - pyskl - INFO - Saving checkpoint at 34 epochs +2025-06-24 15:51:12,481 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:51:12,539 - pyskl - INFO - +top1_acc 0.7862 +top5_acc 0.9854 +2025-06-24 15:51:12,540 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:51:12,549 - pyskl - INFO - +mean_acc 0.7245 +2025-06-24 15:51:12,552 - pyskl - INFO - Epoch(val) [34][533] top1_acc: 0.7862, top5_acc: 0.9854, mean_class_accuracy: 0.7245 +2025-06-24 15:52:32,088 - pyskl - INFO - Epoch [35][100/1281] lr: 2.195e-02, eta: 16:03:38, time: 0.795, data_time: 0.194, memory: 4083, top1_acc: 0.8631, top5_acc: 0.9969, loss_cls: 0.6823, loss: 0.6823 +2025-06-24 15:53:21,098 - pyskl - INFO - Epoch [35][200/1281] lr: 2.194e-02, eta: 16:03:33, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9950, loss_cls: 0.6154, loss: 0.6154 +2025-06-24 15:54:10,394 - pyskl - INFO - Epoch [35][300/1281] lr: 2.192e-02, eta: 16:03:29, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9956, loss_cls: 0.5960, loss: 0.5960 +2025-06-24 15:54:52,601 - pyskl - INFO - Epoch [35][400/1281] lr: 2.191e-02, eta: 16:03:01, time: 0.422, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9944, loss_cls: 0.6273, loss: 0.6273 +2025-06-24 15:55:39,703 - pyskl - INFO - Epoch [35][500/1281] lr: 2.190e-02, eta: 16:02:49, time: 0.471, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9938, loss_cls: 0.6612, loss: 0.6612 +2025-06-24 15:56:06,270 - pyskl - INFO - Epoch [35][600/1281] lr: 2.188e-02, eta: 16:01:29, time: 0.266, data_time: 0.000, memory: 4083, top1_acc: 0.8387, top5_acc: 0.9894, loss_cls: 0.7711, loss: 0.7711 +2025-06-24 15:56:48,128 - pyskl - INFO - Epoch [35][700/1281] lr: 2.187e-02, eta: 16:00:59, time: 0.419, data_time: 0.000, memory: 4083, top1_acc: 0.8556, top5_acc: 0.9931, loss_cls: 0.7314, loss: 0.7314 +2025-06-24 15:57:37,460 - pyskl - INFO - Epoch [35][800/1281] lr: 2.185e-02, eta: 16:00:55, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8425, top5_acc: 0.9925, loss_cls: 0.7464, loss: 0.7464 +2025-06-24 15:58:26,758 - pyskl - INFO - Epoch [35][900/1281] lr: 2.184e-02, eta: 16:00:50, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8556, top5_acc: 0.9956, loss_cls: 0.7106, loss: 0.7106 +2025-06-24 15:59:16,192 - pyskl - INFO - Epoch [35][1000/1281] lr: 2.183e-02, eta: 16:00:45, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8550, top5_acc: 0.9944, loss_cls: 0.7115, loss: 0.7115 +2025-06-24 16:00:05,005 - pyskl - INFO - Epoch [35][1100/1281] lr: 2.181e-02, eta: 16:00:38, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8650, top5_acc: 0.9956, loss_cls: 0.6897, loss: 0.6897 +2025-06-24 16:00:54,044 - pyskl - INFO - Epoch [35][1200/1281] lr: 2.180e-02, eta: 16:00:32, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8656, top5_acc: 0.9962, loss_cls: 0.6774, loss: 0.6774 +2025-06-24 16:01:34,553 - pyskl - INFO - Saving checkpoint at 35 epochs +2025-06-24 16:02:33,625 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:02:33,685 - pyskl - INFO - +top1_acc 0.8104 +top5_acc 0.9859 +2025-06-24 16:02:33,685 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:02:33,693 - pyskl - INFO - +mean_acc 0.7451 +2025-06-24 16:02:33,695 - pyskl - INFO - Epoch(val) [35][533] top1_acc: 0.8104, top5_acc: 0.9859, mean_class_accuracy: 0.7451 +2025-06-24 16:03:54,301 - pyskl - INFO - Epoch [36][100/1281] lr: 2.178e-02, eta: 15:59:54, time: 0.806, data_time: 0.194, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9950, loss_cls: 0.6085, loss: 0.6085 +2025-06-24 16:04:43,340 - pyskl - INFO - Epoch [36][200/1281] lr: 2.176e-02, eta: 15:59:47, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9950, loss_cls: 0.6485, loss: 0.6485 +2025-06-24 16:05:32,385 - pyskl - INFO - Epoch [36][300/1281] lr: 2.175e-02, eta: 15:59:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9962, loss_cls: 0.6270, loss: 0.6270 +2025-06-24 16:06:13,542 - pyskl - INFO - Epoch [36][400/1281] lr: 2.173e-02, eta: 15:59:07, time: 0.412, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9956, loss_cls: 0.6223, loss: 0.6223 +2025-06-24 16:07:03,279 - pyskl - INFO - Epoch [36][500/1281] lr: 2.172e-02, eta: 15:59:02, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.8481, top5_acc: 0.9938, loss_cls: 0.7251, loss: 0.7251 +2025-06-24 16:07:27,860 - pyskl - INFO - Epoch [36][600/1281] lr: 2.171e-02, eta: 15:57:36, time: 0.246, data_time: 0.000, memory: 4083, top1_acc: 0.8606, top5_acc: 0.9906, loss_cls: 0.7055, loss: 0.7055 +2025-06-24 16:08:10,981 - pyskl - INFO - Epoch [36][700/1281] lr: 2.169e-02, eta: 15:57:09, time: 0.431, data_time: 0.000, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9944, loss_cls: 0.6655, loss: 0.6655 +2025-06-24 16:09:00,014 - pyskl - INFO - Epoch [36][800/1281] lr: 2.168e-02, eta: 15:57:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8675, top5_acc: 0.9950, loss_cls: 0.6706, loss: 0.6706 +2025-06-24 16:09:48,797 - pyskl - INFO - Epoch [36][900/1281] lr: 2.167e-02, eta: 15:56:53, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9956, loss_cls: 0.6368, loss: 0.6368 +2025-06-24 16:10:38,070 - pyskl - INFO - Epoch [36][1000/1281] lr: 2.165e-02, eta: 15:56:46, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8331, top5_acc: 0.9938, loss_cls: 0.7684, loss: 0.7684 +2025-06-24 16:11:26,980 - pyskl - INFO - Epoch [36][1100/1281] lr: 2.164e-02, eta: 15:56:38, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8562, top5_acc: 0.9956, loss_cls: 0.7364, loss: 0.7364 +2025-06-24 16:12:16,048 - pyskl - INFO - Epoch [36][1200/1281] lr: 2.162e-02, eta: 15:56:30, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8612, top5_acc: 0.9938, loss_cls: 0.6780, loss: 0.6780 +2025-06-24 16:12:56,560 - pyskl - INFO - Saving checkpoint at 36 epochs +2025-06-24 16:13:56,136 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:13:56,207 - pyskl - INFO - +top1_acc 0.8058 +top5_acc 0.9840 +2025-06-24 16:13:56,208 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:13:56,215 - pyskl - INFO - +mean_acc 0.7386 +2025-06-24 16:13:56,217 - pyskl - INFO - Epoch(val) [36][533] top1_acc: 0.8058, top5_acc: 0.9840, mean_class_accuracy: 0.7386 +2025-06-24 16:15:16,207 - pyskl - INFO - Epoch [37][100/1281] lr: 2.160e-02, eta: 15:55:47, time: 0.800, data_time: 0.197, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9988, loss_cls: 0.6081, loss: 0.6081 +2025-06-24 16:16:05,683 - pyskl - INFO - Epoch [37][200/1281] lr: 2.158e-02, eta: 15:55:40, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9969, loss_cls: 0.5496, loss: 0.5496 +2025-06-24 16:16:54,957 - pyskl - INFO - Epoch [37][300/1281] lr: 2.157e-02, eta: 15:55:31, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9988, loss_cls: 0.6249, loss: 0.6249 +2025-06-24 16:17:35,220 - pyskl - INFO - Epoch [37][400/1281] lr: 2.156e-02, eta: 15:54:55, time: 0.403, data_time: 0.000, memory: 4083, top1_acc: 0.8581, top5_acc: 0.9919, loss_cls: 0.7072, loss: 0.7072 +2025-06-24 16:18:25,837 - pyskl - INFO - Epoch [37][500/1281] lr: 2.154e-02, eta: 15:54:51, time: 0.506, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9931, loss_cls: 0.6375, loss: 0.6375 +2025-06-24 16:18:50,112 - pyskl - INFO - Epoch [37][600/1281] lr: 2.153e-02, eta: 15:53:25, time: 0.243, data_time: 0.000, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9938, loss_cls: 0.6408, loss: 0.6408 +2025-06-24 16:19:34,194 - pyskl - INFO - Epoch [37][700/1281] lr: 2.151e-02, eta: 15:53:00, time: 0.441, data_time: 0.000, memory: 4083, top1_acc: 0.8631, top5_acc: 0.9981, loss_cls: 0.6842, loss: 0.6842 +2025-06-24 16:20:23,171 - pyskl - INFO - Epoch [37][800/1281] lr: 2.150e-02, eta: 15:52:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8456, top5_acc: 0.9931, loss_cls: 0.7346, loss: 0.7346 +2025-06-24 16:21:12,481 - pyskl - INFO - Epoch [37][900/1281] lr: 2.149e-02, eta: 15:52:42, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8644, top5_acc: 0.9962, loss_cls: 0.6640, loss: 0.6640 +2025-06-24 16:22:01,619 - pyskl - INFO - Epoch [37][1000/1281] lr: 2.147e-02, eta: 15:52:32, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9938, loss_cls: 0.6601, loss: 0.6601 +2025-06-24 16:22:50,703 - pyskl - INFO - Epoch [37][1100/1281] lr: 2.146e-02, eta: 15:52:23, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8562, top5_acc: 0.9919, loss_cls: 0.7210, loss: 0.7210 +2025-06-24 16:23:39,747 - pyskl - INFO - Epoch [37][1200/1281] lr: 2.144e-02, eta: 15:52:13, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8600, top5_acc: 0.9956, loss_cls: 0.7032, loss: 0.7032 +2025-06-24 16:24:20,397 - pyskl - INFO - Saving checkpoint at 37 epochs +2025-06-24 16:25:19,902 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:25:19,957 - pyskl - INFO - +top1_acc 0.8303 +top5_acc 0.9896 +2025-06-24 16:25:19,957 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:25:19,965 - pyskl - INFO - +mean_acc 0.7729 +2025-06-24 16:25:19,969 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_32.pth was removed +2025-06-24 16:25:20,145 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_37.pth. +2025-06-24 16:25:20,145 - pyskl - INFO - Best top1_acc is 0.8303 at 37 epoch. +2025-06-24 16:25:20,148 - pyskl - INFO - Epoch(val) [37][533] top1_acc: 0.8303, top5_acc: 0.9896, mean_class_accuracy: 0.7729 +2025-06-24 16:26:40,673 - pyskl - INFO - Epoch [38][100/1281] lr: 2.142e-02, eta: 15:51:29, time: 0.805, data_time: 0.195, memory: 4083, top1_acc: 0.8688, top5_acc: 0.9975, loss_cls: 0.6514, loss: 0.6514 +2025-06-24 16:27:29,610 - pyskl - INFO - Epoch [38][200/1281] lr: 2.140e-02, eta: 15:51:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9938, loss_cls: 0.6174, loss: 0.6174 +2025-06-24 16:28:18,573 - pyskl - INFO - Epoch [38][300/1281] lr: 2.139e-02, eta: 15:51:08, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9950, loss_cls: 0.5936, loss: 0.5936 +2025-06-24 16:28:55,405 - pyskl - INFO - Epoch [38][400/1281] lr: 2.137e-02, eta: 15:50:20, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9938, loss_cls: 0.6419, loss: 0.6419 +2025-06-24 16:29:46,373 - pyskl - INFO - Epoch [38][500/1281] lr: 2.136e-02, eta: 15:50:15, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.8612, top5_acc: 0.9950, loss_cls: 0.6682, loss: 0.6682 +2025-06-24 16:30:10,747 - pyskl - INFO - Epoch [38][600/1281] lr: 2.134e-02, eta: 15:48:50, time: 0.244, data_time: 0.000, memory: 4083, top1_acc: 0.8612, top5_acc: 0.9931, loss_cls: 0.6872, loss: 0.6872 +2025-06-24 16:30:57,198 - pyskl - INFO - Epoch [38][700/1281] lr: 2.133e-02, eta: 15:48:31, time: 0.464, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9950, loss_cls: 0.6267, loss: 0.6267 +2025-06-24 16:31:46,467 - pyskl - INFO - Epoch [38][800/1281] lr: 2.132e-02, eta: 15:48:21, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9906, loss_cls: 0.6297, loss: 0.6297 +2025-06-24 16:32:35,214 - pyskl - INFO - Epoch [38][900/1281] lr: 2.130e-02, eta: 15:48:09, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8656, top5_acc: 0.9938, loss_cls: 0.6522, loss: 0.6522 +2025-06-24 16:33:24,229 - pyskl - INFO - Epoch [38][1000/1281] lr: 2.129e-02, eta: 15:47:57, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9956, loss_cls: 0.6196, loss: 0.6196 +2025-06-24 16:34:13,295 - pyskl - INFO - Epoch [38][1100/1281] lr: 2.127e-02, eta: 15:47:46, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9938, loss_cls: 0.6697, loss: 0.6697 +2025-06-24 16:35:02,591 - pyskl - INFO - Epoch [38][1200/1281] lr: 2.126e-02, eta: 15:47:35, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8469, top5_acc: 0.9900, loss_cls: 0.7539, loss: 0.7539 +2025-06-24 16:35:42,620 - pyskl - INFO - Saving checkpoint at 38 epochs +2025-06-24 16:36:41,425 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:36:41,489 - pyskl - INFO - +top1_acc 0.7809 +top5_acc 0.9835 +2025-06-24 16:36:41,489 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:36:41,498 - pyskl - INFO - +mean_acc 0.7355 +2025-06-24 16:36:41,500 - pyskl - INFO - Epoch(val) [38][533] top1_acc: 0.7809, top5_acc: 0.9835, mean_class_accuracy: 0.7355 +2025-06-24 16:38:01,103 - pyskl - INFO - Epoch [39][100/1281] lr: 2.123e-02, eta: 15:46:47, time: 0.796, data_time: 0.192, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9981, loss_cls: 0.6611, loss: 0.6611 +2025-06-24 16:38:50,322 - pyskl - INFO - Epoch [39][200/1281] lr: 2.122e-02, eta: 15:46:35, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8581, top5_acc: 0.9938, loss_cls: 0.7161, loss: 0.7161 +2025-06-24 16:39:39,187 - pyskl - INFO - Epoch [39][300/1281] lr: 2.120e-02, eta: 15:46:22, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9956, loss_cls: 0.6271, loss: 0.6271 +2025-06-24 16:40:16,525 - pyskl - INFO - Epoch [39][400/1281] lr: 2.119e-02, eta: 15:45:36, time: 0.373, data_time: 0.001, memory: 4083, top1_acc: 0.8675, top5_acc: 0.9956, loss_cls: 0.6678, loss: 0.6678 +2025-06-24 16:41:07,756 - pyskl - INFO - Epoch [39][500/1281] lr: 2.117e-02, eta: 15:45:30, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8531, top5_acc: 0.9950, loss_cls: 0.7005, loss: 0.7005 +2025-06-24 16:41:32,871 - pyskl - INFO - Epoch [39][600/1281] lr: 2.116e-02, eta: 15:44:08, time: 0.251, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9975, loss_cls: 0.6019, loss: 0.6019 +2025-06-24 16:42:20,269 - pyskl - INFO - Epoch [39][700/1281] lr: 2.114e-02, eta: 15:43:51, time: 0.474, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9962, loss_cls: 0.6497, loss: 0.6497 +2025-06-24 16:43:08,980 - pyskl - INFO - Epoch [39][800/1281] lr: 2.113e-02, eta: 15:43:37, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8688, top5_acc: 0.9919, loss_cls: 0.6514, loss: 0.6514 +2025-06-24 16:43:58,072 - pyskl - INFO - Epoch [39][900/1281] lr: 2.111e-02, eta: 15:43:25, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8600, top5_acc: 0.9962, loss_cls: 0.6846, loss: 0.6846 +2025-06-24 16:44:47,023 - pyskl - INFO - Epoch [39][1000/1281] lr: 2.110e-02, eta: 15:43:11, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8625, top5_acc: 0.9956, loss_cls: 0.6450, loss: 0.6450 +2025-06-24 16:45:35,904 - pyskl - INFO - Epoch [39][1100/1281] lr: 2.108e-02, eta: 15:42:58, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8688, top5_acc: 0.9925, loss_cls: 0.6705, loss: 0.6705 +2025-06-24 16:46:24,678 - pyskl - INFO - Epoch [39][1200/1281] lr: 2.107e-02, eta: 15:42:44, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8469, top5_acc: 0.9931, loss_cls: 0.7185, loss: 0.7185 +2025-06-24 16:47:04,836 - pyskl - INFO - Saving checkpoint at 39 epochs +2025-06-24 16:48:03,180 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:48:03,275 - pyskl - INFO - +top1_acc 0.8187 +top5_acc 0.9878 +2025-06-24 16:48:03,275 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:48:03,285 - pyskl - INFO - +mean_acc 0.7664 +2025-06-24 16:48:03,287 - pyskl - INFO - Epoch(val) [39][533] top1_acc: 0.8187, top5_acc: 0.9878, mean_class_accuracy: 0.7664 +2025-06-24 16:49:22,673 - pyskl - INFO - Epoch [40][100/1281] lr: 2.104e-02, eta: 15:41:53, time: 0.794, data_time: 0.190, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9950, loss_cls: 0.5685, loss: 0.5685 +2025-06-24 16:50:11,500 - pyskl - INFO - Epoch [40][200/1281] lr: 2.103e-02, eta: 15:41:39, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9969, loss_cls: 0.5829, loss: 0.5829 +2025-06-24 16:51:00,757 - pyskl - INFO - Epoch [40][300/1281] lr: 2.101e-02, eta: 15:41:26, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9944, loss_cls: 0.6365, loss: 0.6365 +2025-06-24 16:51:37,060 - pyskl - INFO - Epoch [40][400/1281] lr: 2.100e-02, eta: 15:40:36, time: 0.363, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9962, loss_cls: 0.5819, loss: 0.5819 +2025-06-24 16:52:28,408 - pyskl - INFO - Epoch [40][500/1281] lr: 2.098e-02, eta: 15:40:29, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.8681, top5_acc: 0.9950, loss_cls: 0.6390, loss: 0.6390 +2025-06-24 16:52:53,231 - pyskl - INFO - Epoch [40][600/1281] lr: 2.097e-02, eta: 15:39:07, time: 0.248, data_time: 0.000, memory: 4083, top1_acc: 0.8631, top5_acc: 0.9919, loss_cls: 0.6880, loss: 0.6880 +2025-06-24 16:53:40,109 - pyskl - INFO - Epoch [40][700/1281] lr: 2.095e-02, eta: 15:38:47, time: 0.469, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9956, loss_cls: 0.6208, loss: 0.6208 +2025-06-24 16:54:29,559 - pyskl - INFO - Epoch [40][800/1281] lr: 2.094e-02, eta: 15:38:34, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9969, loss_cls: 0.6719, loss: 0.6719 +2025-06-24 16:55:19,061 - pyskl - INFO - Epoch [40][900/1281] lr: 2.092e-02, eta: 15:38:21, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9988, loss_cls: 0.6354, loss: 0.6354 +2025-06-24 16:56:08,269 - pyskl - INFO - Epoch [40][1000/1281] lr: 2.091e-02, eta: 15:38:07, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8631, top5_acc: 0.9944, loss_cls: 0.6697, loss: 0.6697 +2025-06-24 16:56:57,145 - pyskl - INFO - Epoch [40][1100/1281] lr: 2.089e-02, eta: 15:37:52, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9950, loss_cls: 0.6797, loss: 0.6797 +2025-06-24 16:57:46,273 - pyskl - INFO - Epoch [40][1200/1281] lr: 2.088e-02, eta: 15:37:38, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9925, loss_cls: 0.6512, loss: 0.6512 +2025-06-24 16:58:26,753 - pyskl - INFO - Saving checkpoint at 40 epochs +2025-06-24 16:59:26,489 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:59:26,558 - pyskl - INFO - +top1_acc 0.8331 +top5_acc 0.9894 +2025-06-24 16:59:26,558 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:59:26,566 - pyskl - INFO - +mean_acc 0.7708 +2025-06-24 16:59:26,570 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_37.pth was removed +2025-06-24 16:59:26,752 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_40.pth. +2025-06-24 16:59:26,753 - pyskl - INFO - Best top1_acc is 0.8331 at 40 epoch. +2025-06-24 16:59:26,755 - pyskl - INFO - Epoch(val) [40][533] top1_acc: 0.8331, top5_acc: 0.9894, mean_class_accuracy: 0.7708 +2025-06-24 17:00:46,110 - pyskl - INFO - Epoch [41][100/1281] lr: 2.085e-02, eta: 15:36:45, time: 0.793, data_time: 0.193, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9944, loss_cls: 0.6197, loss: 0.6197 +2025-06-24 17:01:35,223 - pyskl - INFO - Epoch [41][200/1281] lr: 2.083e-02, eta: 15:36:30, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8688, top5_acc: 0.9956, loss_cls: 0.6447, loss: 0.6447 +2025-06-24 17:02:24,233 - pyskl - INFO - Epoch [41][300/1281] lr: 2.082e-02, eta: 15:36:15, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9962, loss_cls: 0.6288, loss: 0.6288 +2025-06-24 17:02:59,086 - pyskl - INFO - Epoch [41][400/1281] lr: 2.080e-02, eta: 15:35:21, time: 0.349, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9950, loss_cls: 0.6250, loss: 0.6250 +2025-06-24 17:03:50,260 - pyskl - INFO - Epoch [41][500/1281] lr: 2.079e-02, eta: 15:35:12, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9969, loss_cls: 0.6504, loss: 0.6504 +2025-06-24 17:04:15,285 - pyskl - INFO - Epoch [41][600/1281] lr: 2.077e-02, eta: 15:33:51, time: 0.250, data_time: 0.000, memory: 4083, top1_acc: 0.8612, top5_acc: 0.9981, loss_cls: 0.6448, loss: 0.6448 +2025-06-24 17:05:02,893 - pyskl - INFO - Epoch [41][700/1281] lr: 2.076e-02, eta: 15:33:32, time: 0.476, data_time: 0.000, memory: 4083, top1_acc: 0.8544, top5_acc: 0.9962, loss_cls: 0.7119, loss: 0.7119 +2025-06-24 17:05:51,943 - pyskl - INFO - Epoch [41][800/1281] lr: 2.074e-02, eta: 15:33:17, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9944, loss_cls: 0.6748, loss: 0.6748 +2025-06-24 17:06:41,433 - pyskl - INFO - Epoch [41][900/1281] lr: 2.073e-02, eta: 15:33:02, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9944, loss_cls: 0.6268, loss: 0.6268 +2025-06-24 17:07:30,812 - pyskl - INFO - Epoch [41][1000/1281] lr: 2.071e-02, eta: 15:32:48, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9962, loss_cls: 0.6088, loss: 0.6088 +2025-06-24 17:08:20,124 - pyskl - INFO - Epoch [41][1100/1281] lr: 2.070e-02, eta: 15:32:32, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9962, loss_cls: 0.6278, loss: 0.6278 +2025-06-24 17:09:09,123 - pyskl - INFO - Epoch [41][1200/1281] lr: 2.068e-02, eta: 15:32:16, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9950, loss_cls: 0.6205, loss: 0.6205 +2025-06-24 17:09:49,501 - pyskl - INFO - Saving checkpoint at 41 epochs +2025-06-24 17:10:48,780 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:10:48,841 - pyskl - INFO - +top1_acc 0.8207 +top5_acc 0.9837 +2025-06-24 17:10:48,842 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:10:48,851 - pyskl - INFO - +mean_acc 0.7509 +2025-06-24 17:10:48,853 - pyskl - INFO - Epoch(val) [41][533] top1_acc: 0.8207, top5_acc: 0.9837, mean_class_accuracy: 0.7509 +2025-06-24 17:12:08,764 - pyskl - INFO - Epoch [42][100/1281] lr: 2.065e-02, eta: 15:31:24, time: 0.799, data_time: 0.193, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9988, loss_cls: 0.5453, loss: 0.5453 +2025-06-24 17:12:58,152 - pyskl - INFO - Epoch [42][200/1281] lr: 2.064e-02, eta: 15:31:08, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9950, loss_cls: 0.6132, loss: 0.6132 +2025-06-24 17:13:47,275 - pyskl - INFO - Epoch [42][300/1281] lr: 2.062e-02, eta: 15:30:52, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9938, loss_cls: 0.7126, loss: 0.7126 +2025-06-24 17:14:20,209 - pyskl - INFO - Epoch [42][400/1281] lr: 2.061e-02, eta: 15:29:53, time: 0.329, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 1.0000, loss_cls: 0.6172, loss: 0.6172 +2025-06-24 17:15:11,513 - pyskl - INFO - Epoch [42][500/1281] lr: 2.059e-02, eta: 15:29:42, time: 0.513, data_time: 0.001, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9950, loss_cls: 0.6493, loss: 0.6493 +2025-06-24 17:15:37,383 - pyskl - INFO - Epoch [42][600/1281] lr: 2.057e-02, eta: 15:28:25, time: 0.259, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9956, loss_cls: 0.5995, loss: 0.5995 +2025-06-24 17:16:26,316 - pyskl - INFO - Epoch [42][700/1281] lr: 2.056e-02, eta: 15:28:08, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9988, loss_cls: 0.6119, loss: 0.6119 +2025-06-24 17:17:15,238 - pyskl - INFO - Epoch [42][800/1281] lr: 2.054e-02, eta: 15:27:51, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9938, loss_cls: 0.6643, loss: 0.6643 +2025-06-24 17:18:04,562 - pyskl - INFO - Epoch [42][900/1281] lr: 2.053e-02, eta: 15:27:35, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8650, top5_acc: 0.9969, loss_cls: 0.6728, loss: 0.6728 +2025-06-24 17:18:53,928 - pyskl - INFO - Epoch [42][1000/1281] lr: 2.051e-02, eta: 15:27:19, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9981, loss_cls: 0.5839, loss: 0.5839 +2025-06-24 17:19:42,885 - pyskl - INFO - Epoch [42][1100/1281] lr: 2.050e-02, eta: 15:27:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8575, top5_acc: 0.9931, loss_cls: 0.6976, loss: 0.6976 +2025-06-24 17:20:31,667 - pyskl - INFO - Epoch [42][1200/1281] lr: 2.048e-02, eta: 15:26:44, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8650, top5_acc: 0.9962, loss_cls: 0.6646, loss: 0.6646 +2025-06-24 17:21:11,964 - pyskl - INFO - Saving checkpoint at 42 epochs +2025-06-24 17:22:11,335 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:22:11,390 - pyskl - INFO - +top1_acc 0.8113 +top5_acc 0.9846 +2025-06-24 17:22:11,390 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:22:11,398 - pyskl - INFO - +mean_acc 0.7349 +2025-06-24 17:22:11,399 - pyskl - INFO - Epoch(val) [42][533] top1_acc: 0.8113, top5_acc: 0.9846, mean_class_accuracy: 0.7349 +2025-06-24 17:23:30,896 - pyskl - INFO - Epoch [43][100/1281] lr: 2.045e-02, eta: 15:25:48, time: 0.795, data_time: 0.193, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9962, loss_cls: 0.5772, loss: 0.5772 +2025-06-24 17:24:20,378 - pyskl - INFO - Epoch [43][200/1281] lr: 2.044e-02, eta: 15:25:32, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9969, loss_cls: 0.5788, loss: 0.5788 +2025-06-24 17:25:09,301 - pyskl - INFO - Epoch [43][300/1281] lr: 2.042e-02, eta: 15:25:14, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9962, loss_cls: 0.5820, loss: 0.5820 +2025-06-24 17:25:41,594 - pyskl - INFO - Epoch [43][400/1281] lr: 2.040e-02, eta: 15:24:14, time: 0.323, data_time: 0.000, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9962, loss_cls: 0.6005, loss: 0.6005 +2025-06-24 17:26:32,651 - pyskl - INFO - Epoch [43][500/1281] lr: 2.039e-02, eta: 15:24:01, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9938, loss_cls: 0.6602, loss: 0.6602 +2025-06-24 17:27:00,509 - pyskl - INFO - Epoch [43][600/1281] lr: 2.037e-02, eta: 15:22:49, time: 0.279, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9925, loss_cls: 0.6651, loss: 0.6651 +2025-06-24 17:27:49,269 - pyskl - INFO - Epoch [43][700/1281] lr: 2.036e-02, eta: 15:22:31, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9962, loss_cls: 0.6332, loss: 0.6332 +2025-06-24 17:28:38,392 - pyskl - INFO - Epoch [43][800/1281] lr: 2.034e-02, eta: 15:22:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9938, loss_cls: 0.6244, loss: 0.6244 +2025-06-24 17:29:27,505 - pyskl - INFO - Epoch [43][900/1281] lr: 2.033e-02, eta: 15:21:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9969, loss_cls: 0.5377, loss: 0.5377 +2025-06-24 17:30:16,770 - pyskl - INFO - Epoch [43][1000/1281] lr: 2.031e-02, eta: 15:21:38, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9975, loss_cls: 0.6294, loss: 0.6294 +2025-06-24 17:31:05,955 - pyskl - INFO - Epoch [43][1100/1281] lr: 2.029e-02, eta: 15:21:20, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9931, loss_cls: 0.6404, loss: 0.6404 +2025-06-24 17:31:55,067 - pyskl - INFO - Epoch [43][1200/1281] lr: 2.028e-02, eta: 15:21:01, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8688, top5_acc: 0.9988, loss_cls: 0.6581, loss: 0.6581 +2025-06-24 17:32:35,287 - pyskl - INFO - Saving checkpoint at 43 epochs +2025-06-24 17:33:34,967 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:33:35,023 - pyskl - INFO - +top1_acc 0.8425 +top5_acc 0.9872 +2025-06-24 17:33:35,023 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:33:35,032 - pyskl - INFO - +mean_acc 0.7756 +2025-06-24 17:33:35,036 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_40.pth was removed +2025-06-24 17:33:35,210 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_43.pth. +2025-06-24 17:33:35,210 - pyskl - INFO - Best top1_acc is 0.8425 at 43 epoch. +2025-06-24 17:33:35,213 - pyskl - INFO - Epoch(val) [43][533] top1_acc: 0.8425, top5_acc: 0.9872, mean_class_accuracy: 0.7756 +2025-06-24 17:34:56,174 - pyskl - INFO - Epoch [44][100/1281] lr: 2.025e-02, eta: 15:20:08, time: 0.810, data_time: 0.201, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9969, loss_cls: 0.5587, loss: 0.5587 +2025-06-24 17:35:45,304 - pyskl - INFO - Epoch [44][200/1281] lr: 2.023e-02, eta: 15:19:50, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9944, loss_cls: 0.5478, loss: 0.5478 +2025-06-24 17:36:34,524 - pyskl - INFO - Epoch [44][300/1281] lr: 2.022e-02, eta: 15:19:31, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9969, loss_cls: 0.5412, loss: 0.5412 +2025-06-24 17:37:02,637 - pyskl - INFO - Epoch [44][400/1281] lr: 2.020e-02, eta: 15:18:21, time: 0.281, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9956, loss_cls: 0.5898, loss: 0.5898 +2025-06-24 17:37:53,887 - pyskl - INFO - Epoch [44][500/1281] lr: 2.018e-02, eta: 15:18:08, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9962, loss_cls: 0.6071, loss: 0.6071 +2025-06-24 17:38:24,183 - pyskl - INFO - Epoch [44][600/1281] lr: 2.017e-02, eta: 15:17:03, time: 0.303, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9981, loss_cls: 0.5987, loss: 0.5987 +2025-06-24 17:39:13,186 - pyskl - INFO - Epoch [44][700/1281] lr: 2.015e-02, eta: 15:16:43, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9944, loss_cls: 0.5934, loss: 0.5934 +2025-06-24 17:40:02,302 - pyskl - INFO - Epoch [44][800/1281] lr: 2.014e-02, eta: 15:16:25, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9912, loss_cls: 0.6000, loss: 0.6000 +2025-06-24 17:40:51,202 - pyskl - INFO - Epoch [44][900/1281] lr: 2.012e-02, eta: 15:16:05, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9975, loss_cls: 0.6000, loss: 0.6000 +2025-06-24 17:41:40,291 - pyskl - INFO - Epoch [44][1000/1281] lr: 2.010e-02, eta: 15:15:46, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9975, loss_cls: 0.6067, loss: 0.6067 +2025-06-24 17:42:29,898 - pyskl - INFO - Epoch [44][1100/1281] lr: 2.009e-02, eta: 15:15:28, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9925, loss_cls: 0.5967, loss: 0.5967 +2025-06-24 17:43:18,830 - pyskl - INFO - Epoch [44][1200/1281] lr: 2.007e-02, eta: 15:15:08, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8650, top5_acc: 0.9944, loss_cls: 0.6774, loss: 0.6774 +2025-06-24 17:43:59,221 - pyskl - INFO - Saving checkpoint at 44 epochs +2025-06-24 17:44:58,404 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:44:58,465 - pyskl - INFO - +top1_acc 0.8118 +top5_acc 0.9886 +2025-06-24 17:44:58,466 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:44:58,472 - pyskl - INFO - +mean_acc 0.7470 +2025-06-24 17:44:58,474 - pyskl - INFO - Epoch(val) [44][533] top1_acc: 0.8118, top5_acc: 0.9886, mean_class_accuracy: 0.7470 +2025-06-24 17:46:17,654 - pyskl - INFO - Epoch [45][100/1281] lr: 2.004e-02, eta: 15:14:09, time: 0.792, data_time: 0.191, memory: 4083, top1_acc: 0.8738, top5_acc: 0.9956, loss_cls: 0.6263, loss: 0.6263 +2025-06-24 17:47:06,606 - pyskl - INFO - Epoch [45][200/1281] lr: 2.003e-02, eta: 15:13:49, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9962, loss_cls: 0.5588, loss: 0.5588 +2025-06-24 17:47:55,911 - pyskl - INFO - Epoch [45][300/1281] lr: 2.001e-02, eta: 15:13:30, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9969, loss_cls: 0.5009, loss: 0.5009 +2025-06-24 17:48:24,228 - pyskl - INFO - Epoch [45][400/1281] lr: 1.999e-02, eta: 15:12:21, time: 0.283, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9975, loss_cls: 0.5869, loss: 0.5869 +2025-06-24 17:49:15,246 - pyskl - INFO - Epoch [45][500/1281] lr: 1.998e-02, eta: 15:12:05, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9981, loss_cls: 0.5512, loss: 0.5512 +2025-06-24 17:49:46,526 - pyskl - INFO - Epoch [45][600/1281] lr: 1.996e-02, eta: 15:11:03, time: 0.313, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9944, loss_cls: 0.5901, loss: 0.5901 +2025-06-24 17:50:35,783 - pyskl - INFO - Epoch [45][700/1281] lr: 1.994e-02, eta: 15:10:44, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8638, top5_acc: 0.9938, loss_cls: 0.6374, loss: 0.6374 +2025-06-24 17:51:25,013 - pyskl - INFO - Epoch [45][800/1281] lr: 1.993e-02, eta: 15:10:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8631, top5_acc: 0.9950, loss_cls: 0.6596, loss: 0.6596 +2025-06-24 17:52:14,713 - pyskl - INFO - Epoch [45][900/1281] lr: 1.991e-02, eta: 15:10:05, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9950, loss_cls: 0.5793, loss: 0.5793 +2025-06-24 17:53:03,790 - pyskl - INFO - Epoch [45][1000/1281] lr: 1.989e-02, eta: 15:09:45, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9950, loss_cls: 0.6470, loss: 0.6470 +2025-06-24 17:53:52,918 - pyskl - INFO - Epoch [45][1100/1281] lr: 1.988e-02, eta: 15:09:25, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9944, loss_cls: 0.6537, loss: 0.6537 +2025-06-24 17:54:42,093 - pyskl - INFO - Epoch [45][1200/1281] lr: 1.986e-02, eta: 15:09:04, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9975, loss_cls: 0.6156, loss: 0.6156 +2025-06-24 17:55:22,287 - pyskl - INFO - Saving checkpoint at 45 epochs +2025-06-24 17:56:21,616 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:56:21,712 - pyskl - INFO - +top1_acc 0.8405 +top5_acc 0.9887 +2025-06-24 17:56:21,712 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:56:21,732 - pyskl - INFO - +mean_acc 0.7759 +2025-06-24 17:56:21,735 - pyskl - INFO - Epoch(val) [45][533] top1_acc: 0.8405, top5_acc: 0.9887, mean_class_accuracy: 0.7759 +2025-06-24 17:57:42,416 - pyskl - INFO - Epoch [46][100/1281] lr: 1.983e-02, eta: 15:08:08, time: 0.807, data_time: 0.198, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9956, loss_cls: 0.6165, loss: 0.6165 +2025-06-24 17:58:31,560 - pyskl - INFO - Epoch [46][200/1281] lr: 1.981e-02, eta: 15:07:47, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9956, loss_cls: 0.5359, loss: 0.5359 +2025-06-24 17:59:21,089 - pyskl - INFO - Epoch [46][300/1281] lr: 1.980e-02, eta: 15:07:28, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8594, top5_acc: 0.9950, loss_cls: 0.6650, loss: 0.6650 +2025-06-24 17:59:50,824 - pyskl - INFO - Epoch [46][400/1281] lr: 1.978e-02, eta: 15:06:22, time: 0.297, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9975, loss_cls: 0.6455, loss: 0.6455 +2025-06-24 18:00:37,288 - pyskl - INFO - Epoch [46][500/1281] lr: 1.976e-02, eta: 15:05:55, time: 0.465, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9994, loss_cls: 0.5861, loss: 0.5861 +2025-06-24 18:01:09,340 - pyskl - INFO - Epoch [46][600/1281] lr: 1.975e-02, eta: 15:04:55, time: 0.320, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9975, loss_cls: 0.5642, loss: 0.5642 +2025-06-24 18:01:58,515 - pyskl - INFO - Epoch [46][700/1281] lr: 1.973e-02, eta: 15:04:34, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9988, loss_cls: 0.5148, loss: 0.5148 +2025-06-24 18:02:47,281 - pyskl - INFO - Epoch [46][800/1281] lr: 1.971e-02, eta: 15:04:12, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9962, loss_cls: 0.5813, loss: 0.5813 +2025-06-24 18:03:36,437 - pyskl - INFO - Epoch [46][900/1281] lr: 1.970e-02, eta: 15:03:51, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9962, loss_cls: 0.6275, loss: 0.6275 +2025-06-24 18:04:25,880 - pyskl - INFO - Epoch [46][1000/1281] lr: 1.968e-02, eta: 15:03:31, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9975, loss_cls: 0.6286, loss: 0.6286 +2025-06-24 18:05:14,919 - pyskl - INFO - Epoch [46][1100/1281] lr: 1.966e-02, eta: 15:03:10, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9956, loss_cls: 0.6279, loss: 0.6279 +2025-06-24 18:06:03,881 - pyskl - INFO - Epoch [46][1200/1281] lr: 1.965e-02, eta: 15:02:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9950, loss_cls: 0.6084, loss: 0.6084 +2025-06-24 18:06:43,941 - pyskl - INFO - Saving checkpoint at 46 epochs +2025-06-24 18:07:43,196 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:07:43,252 - pyskl - INFO - +top1_acc 0.7766 +top5_acc 0.9838 +2025-06-24 18:07:43,252 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:07:43,259 - pyskl - INFO - +mean_acc 0.7093 +2025-06-24 18:07:43,261 - pyskl - INFO - Epoch(val) [46][533] top1_acc: 0.7766, top5_acc: 0.9838, mean_class_accuracy: 0.7093 +2025-06-24 18:09:03,116 - pyskl - INFO - Epoch [47][100/1281] lr: 1.962e-02, eta: 15:01:48, time: 0.798, data_time: 0.197, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9975, loss_cls: 0.5566, loss: 0.5566 +2025-06-24 18:09:52,466 - pyskl - INFO - Epoch [47][200/1281] lr: 1.960e-02, eta: 15:01:27, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9975, loss_cls: 0.4896, loss: 0.4896 +2025-06-24 18:10:41,753 - pyskl - INFO - Epoch [47][300/1281] lr: 1.958e-02, eta: 15:01:06, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9975, loss_cls: 0.5704, loss: 0.5704 +2025-06-24 18:11:10,628 - pyskl - INFO - Epoch [47][400/1281] lr: 1.957e-02, eta: 14:59:59, time: 0.289, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9975, loss_cls: 0.5586, loss: 0.5586 +2025-06-24 18:11:58,907 - pyskl - INFO - Epoch [47][500/1281] lr: 1.955e-02, eta: 14:59:35, time: 0.483, data_time: 0.001, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9925, loss_cls: 0.6016, loss: 0.6016 +2025-06-24 18:12:31,693 - pyskl - INFO - Epoch [47][600/1281] lr: 1.953e-02, eta: 14:58:37, time: 0.328, data_time: 0.001, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9975, loss_cls: 0.5490, loss: 0.5490 +2025-06-24 18:13:20,649 - pyskl - INFO - Epoch [47][700/1281] lr: 1.952e-02, eta: 14:58:15, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8600, top5_acc: 0.9944, loss_cls: 0.6840, loss: 0.6840 +2025-06-24 18:14:09,406 - pyskl - INFO - Epoch [47][800/1281] lr: 1.950e-02, eta: 14:57:52, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9962, loss_cls: 0.6317, loss: 0.6317 +2025-06-24 18:14:58,487 - pyskl - INFO - Epoch [47][900/1281] lr: 1.948e-02, eta: 14:57:30, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9944, loss_cls: 0.6140, loss: 0.6140 +2025-06-24 18:15:47,615 - pyskl - INFO - Epoch [47][1000/1281] lr: 1.947e-02, eta: 14:57:08, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8675, top5_acc: 0.9962, loss_cls: 0.6748, loss: 0.6748 +2025-06-24 18:16:36,331 - pyskl - INFO - Epoch [47][1100/1281] lr: 1.945e-02, eta: 14:56:45, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9975, loss_cls: 0.5759, loss: 0.5759 +2025-06-24 18:17:25,326 - pyskl - INFO - Epoch [47][1200/1281] lr: 1.943e-02, eta: 14:56:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9956, loss_cls: 0.6423, loss: 0.6423 +2025-06-24 18:18:05,561 - pyskl - INFO - Saving checkpoint at 47 epochs +2025-06-24 18:19:05,003 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:19:05,076 - pyskl - INFO - +top1_acc 0.8150 +top5_acc 0.9843 +2025-06-24 18:19:05,076 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:19:05,085 - pyskl - INFO - +mean_acc 0.7581 +2025-06-24 18:19:05,088 - pyskl - INFO - Epoch(val) [47][533] top1_acc: 0.8150, top5_acc: 0.9843, mean_class_accuracy: 0.7581 +2025-06-24 18:20:23,923 - pyskl - INFO - Epoch [48][100/1281] lr: 1.940e-02, eta: 14:55:20, time: 0.788, data_time: 0.194, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9975, loss_cls: 0.6071, loss: 0.6071 +2025-06-24 18:21:12,992 - pyskl - INFO - Epoch [48][200/1281] lr: 1.938e-02, eta: 14:54:57, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9956, loss_cls: 0.5317, loss: 0.5317 +2025-06-24 18:22:02,333 - pyskl - INFO - Epoch [48][300/1281] lr: 1.937e-02, eta: 14:54:35, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9962, loss_cls: 0.5683, loss: 0.5683 +2025-06-24 18:22:31,302 - pyskl - INFO - Epoch [48][400/1281] lr: 1.935e-02, eta: 14:53:29, time: 0.290, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9956, loss_cls: 0.6047, loss: 0.6047 +2025-06-24 18:23:19,533 - pyskl - INFO - Epoch [48][500/1281] lr: 1.933e-02, eta: 14:53:04, time: 0.482, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9944, loss_cls: 0.5972, loss: 0.5972 +2025-06-24 18:23:52,294 - pyskl - INFO - Epoch [48][600/1281] lr: 1.932e-02, eta: 14:52:06, time: 0.328, data_time: 0.000, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9988, loss_cls: 0.5600, loss: 0.5600 +2025-06-24 18:24:41,345 - pyskl - INFO - Epoch [48][700/1281] lr: 1.930e-02, eta: 14:51:43, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9956, loss_cls: 0.6229, loss: 0.6229 +2025-06-24 18:25:30,664 - pyskl - INFO - Epoch [48][800/1281] lr: 1.928e-02, eta: 14:51:21, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9975, loss_cls: 0.5673, loss: 0.5673 +2025-06-24 18:26:19,540 - pyskl - INFO - Epoch [48][900/1281] lr: 1.926e-02, eta: 14:50:57, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9975, loss_cls: 0.5822, loss: 0.5822 +2025-06-24 18:27:08,142 - pyskl - INFO - Epoch [48][1000/1281] lr: 1.925e-02, eta: 14:50:33, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9962, loss_cls: 0.5515, loss: 0.5515 +2025-06-24 18:27:56,867 - pyskl - INFO - Epoch [48][1100/1281] lr: 1.923e-02, eta: 14:50:09, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9950, loss_cls: 0.5974, loss: 0.5974 +2025-06-24 18:28:45,655 - pyskl - INFO - Epoch [48][1200/1281] lr: 1.921e-02, eta: 14:49:46, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9919, loss_cls: 0.6691, loss: 0.6691 +2025-06-24 18:29:26,491 - pyskl - INFO - Saving checkpoint at 48 epochs +2025-06-24 18:30:25,203 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:30:25,274 - pyskl - INFO - +top1_acc 0.8431 +top5_acc 0.9907 +2025-06-24 18:30:25,275 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:30:25,285 - pyskl - INFO - +mean_acc 0.7678 +2025-06-24 18:30:25,291 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_43.pth was removed +2025-06-24 18:30:25,466 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_48.pth. +2025-06-24 18:30:25,467 - pyskl - INFO - Best top1_acc is 0.8431 at 48 epoch. +2025-06-24 18:30:25,469 - pyskl - INFO - Epoch(val) [48][533] top1_acc: 0.8431, top5_acc: 0.9907, mean_class_accuracy: 0.7678 +2025-06-24 18:31:45,105 - pyskl - INFO - Epoch [49][100/1281] lr: 1.918e-02, eta: 14:48:44, time: 0.796, data_time: 0.199, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9994, loss_cls: 0.5404, loss: 0.5404 +2025-06-24 18:32:34,296 - pyskl - INFO - Epoch [49][200/1281] lr: 1.916e-02, eta: 14:48:21, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9962, loss_cls: 0.5547, loss: 0.5547 +2025-06-24 18:33:23,528 - pyskl - INFO - Epoch [49][300/1281] lr: 1.915e-02, eta: 14:47:57, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9975, loss_cls: 0.5404, loss: 0.5404 +2025-06-24 18:33:54,722 - pyskl - INFO - Epoch [49][400/1281] lr: 1.913e-02, eta: 14:46:56, time: 0.312, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9969, loss_cls: 0.5583, loss: 0.5583 +2025-06-24 18:34:39,258 - pyskl - INFO - Epoch [49][500/1281] lr: 1.911e-02, eta: 14:46:23, time: 0.445, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9956, loss_cls: 0.6038, loss: 0.6038 +2025-06-24 18:35:12,892 - pyskl - INFO - Epoch [49][600/1281] lr: 1.909e-02, eta: 14:45:27, time: 0.336, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9956, loss_cls: 0.5986, loss: 0.5986 +2025-06-24 18:36:01,970 - pyskl - INFO - Epoch [49][700/1281] lr: 1.908e-02, eta: 14:45:03, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9956, loss_cls: 0.5382, loss: 0.5382 +2025-06-24 18:36:50,753 - pyskl - INFO - Epoch [49][800/1281] lr: 1.906e-02, eta: 14:44:39, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9950, loss_cls: 0.5724, loss: 0.5724 +2025-06-24 18:37:39,983 - pyskl - INFO - Epoch [49][900/1281] lr: 1.904e-02, eta: 14:44:16, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9994, loss_cls: 0.5607, loss: 0.5607 +2025-06-24 18:38:29,734 - pyskl - INFO - Epoch [49][1000/1281] lr: 1.902e-02, eta: 14:43:53, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9944, loss_cls: 0.5933, loss: 0.5933 +2025-06-24 18:39:19,096 - pyskl - INFO - Epoch [49][1100/1281] lr: 1.901e-02, eta: 14:43:30, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9988, loss_cls: 0.5772, loss: 0.5772 +2025-06-24 18:40:07,702 - pyskl - INFO - Epoch [49][1200/1281] lr: 1.899e-02, eta: 14:43:05, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9962, loss_cls: 0.5925, loss: 0.5925 +2025-06-24 18:40:48,266 - pyskl - INFO - Saving checkpoint at 49 epochs +2025-06-24 18:41:47,775 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:41:47,851 - pyskl - INFO - +top1_acc 0.8031 +top5_acc 0.9846 +2025-06-24 18:41:47,851 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:41:47,860 - pyskl - INFO - +mean_acc 0.7190 +2025-06-24 18:41:47,864 - pyskl - INFO - Epoch(val) [49][533] top1_acc: 0.8031, top5_acc: 0.9846, mean_class_accuracy: 0.7190 +2025-06-24 18:43:08,569 - pyskl - INFO - Epoch [50][100/1281] lr: 1.896e-02, eta: 14:42:04, time: 0.807, data_time: 0.201, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9956, loss_cls: 0.6131, loss: 0.6131 +2025-06-24 18:43:57,822 - pyskl - INFO - Epoch [50][200/1281] lr: 1.894e-02, eta: 14:41:40, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9956, loss_cls: 0.5704, loss: 0.5704 +2025-06-24 18:44:47,123 - pyskl - INFO - Epoch [50][300/1281] lr: 1.892e-02, eta: 14:41:16, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9956, loss_cls: 0.5126, loss: 0.5126 +2025-06-24 18:45:18,604 - pyskl - INFO - Epoch [50][400/1281] lr: 1.891e-02, eta: 14:40:16, time: 0.315, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9962, loss_cls: 0.5371, loss: 0.5371 +2025-06-24 18:46:00,929 - pyskl - INFO - Epoch [50][500/1281] lr: 1.889e-02, eta: 14:39:38, time: 0.423, data_time: 0.000, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9944, loss_cls: 0.6030, loss: 0.6030 +2025-06-24 18:46:36,306 - pyskl - INFO - Epoch [50][600/1281] lr: 1.887e-02, eta: 14:38:46, time: 0.354, data_time: 0.001, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9956, loss_cls: 0.5019, loss: 0.5019 +2025-06-24 18:47:25,588 - pyskl - INFO - Epoch [50][700/1281] lr: 1.885e-02, eta: 14:38:22, time: 0.493, data_time: 0.001, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9944, loss_cls: 0.6119, loss: 0.6119 +2025-06-24 18:48:14,633 - pyskl - INFO - Epoch [50][800/1281] lr: 1.884e-02, eta: 14:37:57, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8738, top5_acc: 0.9944, loss_cls: 0.6524, loss: 0.6524 +2025-06-24 18:49:03,862 - pyskl - INFO - Epoch [50][900/1281] lr: 1.882e-02, eta: 14:37:33, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9962, loss_cls: 0.5780, loss: 0.5780 +2025-06-24 18:49:53,096 - pyskl - INFO - Epoch [50][1000/1281] lr: 1.880e-02, eta: 14:37:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9962, loss_cls: 0.5603, loss: 0.5603 +2025-06-24 18:50:41,957 - pyskl - INFO - Epoch [50][1100/1281] lr: 1.878e-02, eta: 14:36:43, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9975, loss_cls: 0.5948, loss: 0.5948 +2025-06-24 18:51:30,921 - pyskl - INFO - Epoch [50][1200/1281] lr: 1.876e-02, eta: 14:36:18, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9975, loss_cls: 0.5768, loss: 0.5768 +2025-06-24 18:52:11,069 - pyskl - INFO - Saving checkpoint at 50 epochs +2025-06-24 18:53:09,121 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:53:09,178 - pyskl - INFO - +top1_acc 0.8366 +top5_acc 0.9898 +2025-06-24 18:53:09,179 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:53:09,186 - pyskl - INFO - +mean_acc 0.7778 +2025-06-24 18:53:09,188 - pyskl - INFO - Epoch(val) [50][533] top1_acc: 0.8366, top5_acc: 0.9898, mean_class_accuracy: 0.7778 +2025-06-24 18:54:29,274 - pyskl - INFO - Epoch [51][100/1281] lr: 1.873e-02, eta: 14:35:15, time: 0.801, data_time: 0.194, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9962, loss_cls: 0.5472, loss: 0.5472 +2025-06-24 18:55:18,652 - pyskl - INFO - Epoch [51][200/1281] lr: 1.871e-02, eta: 14:34:51, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9981, loss_cls: 0.5182, loss: 0.5182 +2025-06-24 18:56:07,777 - pyskl - INFO - Epoch [51][300/1281] lr: 1.870e-02, eta: 14:34:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9988, loss_cls: 0.5005, loss: 0.5005 +2025-06-24 18:56:37,347 - pyskl - INFO - Epoch [51][400/1281] lr: 1.868e-02, eta: 14:33:22, time: 0.296, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9975, loss_cls: 0.5208, loss: 0.5208 +2025-06-24 18:57:22,918 - pyskl - INFO - Epoch [51][500/1281] lr: 1.866e-02, eta: 14:32:50, time: 0.456, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9975, loss_cls: 0.5250, loss: 0.5250 +2025-06-24 18:57:56,161 - pyskl - INFO - Epoch [51][600/1281] lr: 1.864e-02, eta: 14:31:54, time: 0.332, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9962, loss_cls: 0.5334, loss: 0.5334 +2025-06-24 18:58:45,379 - pyskl - INFO - Epoch [51][700/1281] lr: 1.863e-02, eta: 14:31:29, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9975, loss_cls: 0.5147, loss: 0.5147 +2025-06-24 18:59:34,680 - pyskl - INFO - Epoch [51][800/1281] lr: 1.861e-02, eta: 14:31:04, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8738, top5_acc: 0.9969, loss_cls: 0.5923, loss: 0.5923 +2025-06-24 19:00:23,884 - pyskl - INFO - Epoch [51][900/1281] lr: 1.859e-02, eta: 14:30:39, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9956, loss_cls: 0.5666, loss: 0.5666 +2025-06-24 19:01:12,839 - pyskl - INFO - Epoch [51][1000/1281] lr: 1.857e-02, eta: 14:30:13, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9956, loss_cls: 0.5669, loss: 0.5669 +2025-06-24 19:02:01,920 - pyskl - INFO - Epoch [51][1100/1281] lr: 1.855e-02, eta: 14:29:48, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9919, loss_cls: 0.6121, loss: 0.6121 +2025-06-24 19:02:51,109 - pyskl - INFO - Epoch [51][1200/1281] lr: 1.854e-02, eta: 14:29:22, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9938, loss_cls: 0.5731, loss: 0.5731 +2025-06-24 19:03:31,712 - pyskl - INFO - Saving checkpoint at 51 epochs +2025-06-24 19:04:31,197 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:04:31,263 - pyskl - INFO - +top1_acc 0.8114 +top5_acc 0.9854 +2025-06-24 19:04:31,263 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:04:31,270 - pyskl - INFO - +mean_acc 0.7535 +2025-06-24 19:04:31,272 - pyskl - INFO - Epoch(val) [51][533] top1_acc: 0.8114, top5_acc: 0.9854, mean_class_accuracy: 0.7535 +2025-06-24 19:05:50,915 - pyskl - INFO - Epoch [52][100/1281] lr: 1.850e-02, eta: 14:28:18, time: 0.796, data_time: 0.196, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9969, loss_cls: 0.5778, loss: 0.5778 +2025-06-24 19:06:40,010 - pyskl - INFO - Epoch [52][200/1281] lr: 1.849e-02, eta: 14:27:52, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9969, loss_cls: 0.5581, loss: 0.5581 +2025-06-24 19:07:29,173 - pyskl - INFO - Epoch [52][300/1281] lr: 1.847e-02, eta: 14:27:27, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9962, loss_cls: 0.5422, loss: 0.5422 +2025-06-24 19:07:57,521 - pyskl - INFO - Epoch [52][400/1281] lr: 1.845e-02, eta: 14:26:21, time: 0.283, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9962, loss_cls: 0.5166, loss: 0.5166 +2025-06-24 19:08:44,872 - pyskl - INFO - Epoch [52][500/1281] lr: 1.843e-02, eta: 14:25:52, time: 0.474, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9956, loss_cls: 0.5580, loss: 0.5580 +2025-06-24 19:09:17,521 - pyskl - INFO - Epoch [52][600/1281] lr: 1.841e-02, eta: 14:24:55, time: 0.326, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9962, loss_cls: 0.5861, loss: 0.5861 +2025-06-24 19:10:07,022 - pyskl - INFO - Epoch [52][700/1281] lr: 1.840e-02, eta: 14:24:29, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9981, loss_cls: 0.5821, loss: 0.5821 +2025-06-24 19:10:56,495 - pyskl - INFO - Epoch [52][800/1281] lr: 1.838e-02, eta: 14:24:04, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9981, loss_cls: 0.5742, loss: 0.5742 +2025-06-24 19:11:45,564 - pyskl - INFO - Epoch [52][900/1281] lr: 1.836e-02, eta: 14:23:38, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9962, loss_cls: 0.5686, loss: 0.5686 +2025-06-24 19:12:34,759 - pyskl - INFO - Epoch [52][1000/1281] lr: 1.834e-02, eta: 14:23:12, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9975, loss_cls: 0.5946, loss: 0.5946 +2025-06-24 19:13:24,001 - pyskl - INFO - Epoch [52][1100/1281] lr: 1.832e-02, eta: 14:22:46, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9894, loss_cls: 0.6932, loss: 0.6932 +2025-06-24 19:14:12,913 - pyskl - INFO - Epoch [52][1200/1281] lr: 1.831e-02, eta: 14:22:20, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9962, loss_cls: 0.5629, loss: 0.5629 +2025-06-24 19:14:53,333 - pyskl - INFO - Saving checkpoint at 52 epochs +2025-06-24 19:15:53,137 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:15:53,192 - pyskl - INFO - +top1_acc 0.8274 +top5_acc 0.9866 +2025-06-24 19:15:53,192 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:15:53,199 - pyskl - INFO - +mean_acc 0.7607 +2025-06-24 19:15:53,201 - pyskl - INFO - Epoch(val) [52][533] top1_acc: 0.8274, top5_acc: 0.9866, mean_class_accuracy: 0.7607 +2025-06-24 19:17:11,819 - pyskl - INFO - Epoch [53][100/1281] lr: 1.827e-02, eta: 14:21:13, time: 0.786, data_time: 0.191, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9938, loss_cls: 0.5336, loss: 0.5336 +2025-06-24 19:18:00,975 - pyskl - INFO - Epoch [53][200/1281] lr: 1.826e-02, eta: 14:20:47, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9994, loss_cls: 0.5128, loss: 0.5128 +2025-06-24 19:18:50,598 - pyskl - INFO - Epoch [53][300/1281] lr: 1.824e-02, eta: 14:20:21, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9994, loss_cls: 0.5257, loss: 0.5257 +2025-06-24 19:19:18,315 - pyskl - INFO - Epoch [53][400/1281] lr: 1.822e-02, eta: 14:19:15, time: 0.277, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9956, loss_cls: 0.5551, loss: 0.5551 +2025-06-24 19:20:07,713 - pyskl - INFO - Epoch [53][500/1281] lr: 1.820e-02, eta: 14:18:49, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9938, loss_cls: 0.5778, loss: 0.5778 +2025-06-24 19:20:40,735 - pyskl - INFO - Epoch [53][600/1281] lr: 1.818e-02, eta: 14:17:52, time: 0.330, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9956, loss_cls: 0.5450, loss: 0.5450 +2025-06-24 19:21:29,318 - pyskl - INFO - Epoch [53][700/1281] lr: 1.816e-02, eta: 14:17:25, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9931, loss_cls: 0.6078, loss: 0.6078 +2025-06-24 19:22:18,704 - pyskl - INFO - Epoch [53][800/1281] lr: 1.815e-02, eta: 14:16:59, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9975, loss_cls: 0.5247, loss: 0.5247 +2025-06-24 19:23:08,117 - pyskl - INFO - Epoch [53][900/1281] lr: 1.813e-02, eta: 14:16:33, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9981, loss_cls: 0.5323, loss: 0.5323 +2025-06-24 19:23:57,612 - pyskl - INFO - Epoch [53][1000/1281] lr: 1.811e-02, eta: 14:16:07, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9962, loss_cls: 0.5455, loss: 0.5455 +2025-06-24 19:24:46,455 - pyskl - INFO - Epoch [53][1100/1281] lr: 1.809e-02, eta: 14:15:39, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9975, loss_cls: 0.5229, loss: 0.5229 +2025-06-24 19:25:35,421 - pyskl - INFO - Epoch [53][1200/1281] lr: 1.807e-02, eta: 14:15:12, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9975, loss_cls: 0.5623, loss: 0.5623 +2025-06-24 19:26:15,987 - pyskl - INFO - Saving checkpoint at 53 epochs +2025-06-24 19:27:15,198 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:27:15,269 - pyskl - INFO - +top1_acc 0.8415 +top5_acc 0.9889 +2025-06-24 19:27:15,269 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:27:15,278 - pyskl - INFO - +mean_acc 0.7918 +2025-06-24 19:27:15,281 - pyskl - INFO - Epoch(val) [53][533] top1_acc: 0.8415, top5_acc: 0.9889, mean_class_accuracy: 0.7918 +2025-06-24 19:28:35,090 - pyskl - INFO - Epoch [54][100/1281] lr: 1.804e-02, eta: 14:14:07, time: 0.798, data_time: 0.195, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9994, loss_cls: 0.4649, loss: 0.4649 +2025-06-24 19:29:24,258 - pyskl - INFO - Epoch [54][200/1281] lr: 1.802e-02, eta: 14:13:40, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9962, loss_cls: 0.5496, loss: 0.5496 +2025-06-24 19:30:13,424 - pyskl - INFO - Epoch [54][300/1281] lr: 1.800e-02, eta: 14:13:13, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9969, loss_cls: 0.5192, loss: 0.5192 +2025-06-24 19:30:43,583 - pyskl - INFO - Epoch [54][400/1281] lr: 1.798e-02, eta: 14:12:12, time: 0.302, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9981, loss_cls: 0.4819, loss: 0.4819 +2025-06-24 19:31:29,132 - pyskl - INFO - Epoch [54][500/1281] lr: 1.797e-02, eta: 14:11:38, time: 0.455, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9969, loss_cls: 0.5753, loss: 0.5753 +2025-06-24 19:32:03,928 - pyskl - INFO - Epoch [54][600/1281] lr: 1.795e-02, eta: 14:10:45, time: 0.348, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9962, loss_cls: 0.5680, loss: 0.5680 +2025-06-24 19:32:53,091 - pyskl - INFO - Epoch [54][700/1281] lr: 1.793e-02, eta: 14:10:18, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9962, loss_cls: 0.5766, loss: 0.5766 +2025-06-24 19:33:41,817 - pyskl - INFO - Epoch [54][800/1281] lr: 1.791e-02, eta: 14:09:50, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9975, loss_cls: 0.5860, loss: 0.5860 +2025-06-24 19:34:31,094 - pyskl - INFO - Epoch [54][900/1281] lr: 1.789e-02, eta: 14:09:23, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9962, loss_cls: 0.5657, loss: 0.5657 +2025-06-24 19:35:19,934 - pyskl - INFO - Epoch [54][1000/1281] lr: 1.787e-02, eta: 14:08:55, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9975, loss_cls: 0.5407, loss: 0.5407 +2025-06-24 19:36:08,967 - pyskl - INFO - Epoch [54][1100/1281] lr: 1.786e-02, eta: 14:08:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9938, loss_cls: 0.6032, loss: 0.6032 +2025-06-24 19:36:58,114 - pyskl - INFO - Epoch [54][1200/1281] lr: 1.784e-02, eta: 14:08:00, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9956, loss_cls: 0.5804, loss: 0.5804 +2025-06-24 19:37:38,467 - pyskl - INFO - Saving checkpoint at 54 epochs +2025-06-24 19:38:38,033 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:38:38,090 - pyskl - INFO - +top1_acc 0.8610 +top5_acc 0.9926 +2025-06-24 19:38:38,090 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:38:38,096 - pyskl - INFO - +mean_acc 0.8049 +2025-06-24 19:38:38,101 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_48.pth was removed +2025-06-24 19:38:38,277 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_54.pth. +2025-06-24 19:38:38,278 - pyskl - INFO - Best top1_acc is 0.8610 at 54 epoch. +2025-06-24 19:38:38,281 - pyskl - INFO - Epoch(val) [54][533] top1_acc: 0.8610, top5_acc: 0.9926, mean_class_accuracy: 0.8049 +2025-06-24 19:39:58,195 - pyskl - INFO - Epoch [55][100/1281] lr: 1.780e-02, eta: 14:06:54, time: 0.799, data_time: 0.199, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9981, loss_cls: 0.4932, loss: 0.4932 +2025-06-24 19:40:47,149 - pyskl - INFO - Epoch [55][200/1281] lr: 1.779e-02, eta: 14:06:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9975, loss_cls: 0.5345, loss: 0.5345 +2025-06-24 19:41:35,618 - pyskl - INFO - Epoch [55][300/1281] lr: 1.777e-02, eta: 14:05:57, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9962, loss_cls: 0.5348, loss: 0.5348 +2025-06-24 19:42:10,652 - pyskl - INFO - Epoch [55][400/1281] lr: 1.775e-02, eta: 14:05:05, time: 0.350, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9981, loss_cls: 0.5454, loss: 0.5454 +2025-06-24 19:42:49,149 - pyskl - INFO - Epoch [55][500/1281] lr: 1.773e-02, eta: 14:04:19, time: 0.385, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9956, loss_cls: 0.5308, loss: 0.5308 +2025-06-24 19:43:26,725 - pyskl - INFO - Epoch [55][600/1281] lr: 1.771e-02, eta: 14:03:31, time: 0.376, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9988, loss_cls: 0.5256, loss: 0.5256 +2025-06-24 19:44:16,081 - pyskl - INFO - Epoch [55][700/1281] lr: 1.769e-02, eta: 14:03:03, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9944, loss_cls: 0.5651, loss: 0.5651 +2025-06-24 19:45:04,824 - pyskl - INFO - Epoch [55][800/1281] lr: 1.767e-02, eta: 14:02:35, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9956, loss_cls: 0.5350, loss: 0.5350 +2025-06-24 19:45:54,415 - pyskl - INFO - Epoch [55][900/1281] lr: 1.766e-02, eta: 14:02:08, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9975, loss_cls: 0.5154, loss: 0.5154 +2025-06-24 19:46:43,812 - pyskl - INFO - Epoch [55][1000/1281] lr: 1.764e-02, eta: 14:01:40, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9950, loss_cls: 0.5286, loss: 0.5286 +2025-06-24 19:47:32,485 - pyskl - INFO - Epoch [55][1100/1281] lr: 1.762e-02, eta: 14:01:11, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9975, loss_cls: 0.5837, loss: 0.5837 +2025-06-24 19:48:21,485 - pyskl - INFO - Epoch [55][1200/1281] lr: 1.760e-02, eta: 14:00:43, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9962, loss_cls: 0.5187, loss: 0.5187 +2025-06-24 19:49:02,004 - pyskl - INFO - Saving checkpoint at 55 epochs +2025-06-24 19:50:01,122 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:50:01,194 - pyskl - INFO - +top1_acc 0.8345 +top5_acc 0.9873 +2025-06-24 19:50:01,194 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:50:01,212 - pyskl - INFO - +mean_acc 0.7548 +2025-06-24 19:50:01,217 - pyskl - INFO - Epoch(val) [55][533] top1_acc: 0.8345, top5_acc: 0.9873, mean_class_accuracy: 0.7548 +2025-06-24 19:51:20,733 - pyskl - INFO - Epoch [56][100/1281] lr: 1.757e-02, eta: 13:59:36, time: 0.795, data_time: 0.191, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9969, loss_cls: 0.5136, loss: 0.5136 +2025-06-24 19:52:09,733 - pyskl - INFO - Epoch [56][200/1281] lr: 1.755e-02, eta: 13:59:07, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9975, loss_cls: 0.5431, loss: 0.5431 +2025-06-24 19:52:56,451 - pyskl - INFO - Epoch [56][300/1281] lr: 1.753e-02, eta: 13:58:35, time: 0.467, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9950, loss_cls: 0.5043, loss: 0.5043 +2025-06-24 19:53:32,829 - pyskl - INFO - Epoch [56][400/1281] lr: 1.751e-02, eta: 13:57:45, time: 0.364, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9975, loss_cls: 0.4907, loss: 0.4907 +2025-06-24 19:54:10,109 - pyskl - INFO - Epoch [56][500/1281] lr: 1.749e-02, eta: 13:56:56, time: 0.373, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9962, loss_cls: 0.5240, loss: 0.5240 +2025-06-24 19:54:46,786 - pyskl - INFO - Epoch [56][600/1281] lr: 1.747e-02, eta: 13:56:07, time: 0.367, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9981, loss_cls: 0.4986, loss: 0.4986 +2025-06-24 19:55:35,844 - pyskl - INFO - Epoch [56][700/1281] lr: 1.745e-02, eta: 13:55:38, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9969, loss_cls: 0.5302, loss: 0.5302 +2025-06-24 19:56:25,135 - pyskl - INFO - Epoch [56][800/1281] lr: 1.743e-02, eta: 13:55:10, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9969, loss_cls: 0.5113, loss: 0.5113 +2025-06-24 19:57:14,723 - pyskl - INFO - Epoch [56][900/1281] lr: 1.742e-02, eta: 13:54:43, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9969, loss_cls: 0.5396, loss: 0.5396 +2025-06-24 19:58:03,822 - pyskl - INFO - Epoch [56][1000/1281] lr: 1.740e-02, eta: 13:54:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9956, loss_cls: 0.5463, loss: 0.5463 +2025-06-24 19:58:52,572 - pyskl - INFO - Epoch [56][1100/1281] lr: 1.738e-02, eta: 13:53:45, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9938, loss_cls: 0.5236, loss: 0.5236 +2025-06-24 19:59:41,370 - pyskl - INFO - Epoch [56][1200/1281] lr: 1.736e-02, eta: 13:53:16, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9988, loss_cls: 0.5055, loss: 0.5055 +2025-06-24 20:00:21,541 - pyskl - INFO - Saving checkpoint at 56 epochs +2025-06-24 20:01:20,331 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:01:20,398 - pyskl - INFO - +top1_acc 0.8613 +top5_acc 0.9908 +2025-06-24 20:01:20,398 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:01:20,406 - pyskl - INFO - +mean_acc 0.8021 +2025-06-24 20:01:20,411 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_54.pth was removed +2025-06-24 20:01:20,609 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_56.pth. +2025-06-24 20:01:20,609 - pyskl - INFO - Best top1_acc is 0.8613 at 56 epoch. +2025-06-24 20:01:20,613 - pyskl - INFO - Epoch(val) [56][533] top1_acc: 0.8613, top5_acc: 0.9908, mean_class_accuracy: 0.8021 +2025-06-24 20:02:40,496 - pyskl - INFO - Epoch [57][100/1281] lr: 1.733e-02, eta: 13:52:09, time: 0.799, data_time: 0.195, memory: 4083, top1_acc: 0.9113, top5_acc: 1.0000, loss_cls: 0.4793, loss: 0.4793 +2025-06-24 20:03:29,861 - pyskl - INFO - Epoch [57][200/1281] lr: 1.731e-02, eta: 13:51:40, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9981, loss_cls: 0.5104, loss: 0.5104 +2025-06-24 20:04:17,682 - pyskl - INFO - Epoch [57][300/1281] lr: 1.729e-02, eta: 13:51:09, time: 0.478, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9981, loss_cls: 0.4956, loss: 0.4956 +2025-06-24 20:04:52,339 - pyskl - INFO - Epoch [57][400/1281] lr: 1.727e-02, eta: 13:50:16, time: 0.347, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9950, loss_cls: 0.5430, loss: 0.5430 +2025-06-24 20:05:31,374 - pyskl - INFO - Epoch [57][500/1281] lr: 1.725e-02, eta: 13:49:31, time: 0.390, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9944, loss_cls: 0.5319, loss: 0.5319 +2025-06-24 20:06:08,483 - pyskl - INFO - Epoch [57][600/1281] lr: 1.723e-02, eta: 13:48:42, time: 0.371, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9956, loss_cls: 0.5692, loss: 0.5692 +2025-06-24 20:06:57,059 - pyskl - INFO - Epoch [57][700/1281] lr: 1.721e-02, eta: 13:48:12, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9969, loss_cls: 0.5448, loss: 0.5448 +2025-06-24 20:07:46,305 - pyskl - INFO - Epoch [57][800/1281] lr: 1.719e-02, eta: 13:47:43, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9969, loss_cls: 0.5340, loss: 0.5340 +2025-06-24 20:08:35,736 - pyskl - INFO - Epoch [57][900/1281] lr: 1.717e-02, eta: 13:47:15, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9962, loss_cls: 0.5333, loss: 0.5333 +2025-06-24 20:09:25,024 - pyskl - INFO - Epoch [57][1000/1281] lr: 1.716e-02, eta: 13:46:46, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9944, loss_cls: 0.5960, loss: 0.5960 +2025-06-24 20:10:13,726 - pyskl - INFO - Epoch [57][1100/1281] lr: 1.714e-02, eta: 13:46:16, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9944, loss_cls: 0.6182, loss: 0.6182 +2025-06-24 20:11:02,734 - pyskl - INFO - Epoch [57][1200/1281] lr: 1.712e-02, eta: 13:45:47, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9969, loss_cls: 0.5308, loss: 0.5308 +2025-06-24 20:11:43,135 - pyskl - INFO - Saving checkpoint at 57 epochs +2025-06-24 20:12:42,050 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:12:42,118 - pyskl - INFO - +top1_acc 0.8135 +top5_acc 0.9829 +2025-06-24 20:12:42,118 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:12:42,126 - pyskl - INFO - +mean_acc 0.7860 +2025-06-24 20:12:42,129 - pyskl - INFO - Epoch(val) [57][533] top1_acc: 0.8135, top5_acc: 0.9829, mean_class_accuracy: 0.7860 +2025-06-24 20:14:01,307 - pyskl - INFO - Epoch [58][100/1281] lr: 1.708e-02, eta: 13:44:38, time: 0.792, data_time: 0.190, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9969, loss_cls: 0.4849, loss: 0.4849 +2025-06-24 20:14:50,632 - pyskl - INFO - Epoch [58][200/1281] lr: 1.706e-02, eta: 13:44:09, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9988, loss_cls: 0.5368, loss: 0.5368 +2025-06-24 20:15:39,183 - pyskl - INFO - Epoch [58][300/1281] lr: 1.704e-02, eta: 13:43:39, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9944, loss_cls: 0.5084, loss: 0.5084 +2025-06-24 20:16:11,754 - pyskl - INFO - Epoch [58][400/1281] lr: 1.703e-02, eta: 13:42:43, time: 0.326, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9969, loss_cls: 0.5080, loss: 0.5080 +2025-06-24 20:16:52,764 - pyskl - INFO - Epoch [58][500/1281] lr: 1.701e-02, eta: 13:42:00, time: 0.410, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9975, loss_cls: 0.4957, loss: 0.4957 +2025-06-24 20:17:29,142 - pyskl - INFO - Epoch [58][600/1281] lr: 1.699e-02, eta: 13:41:10, time: 0.364, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9956, loss_cls: 0.4706, loss: 0.4706 +2025-06-24 20:18:18,419 - pyskl - INFO - Epoch [58][700/1281] lr: 1.697e-02, eta: 13:40:41, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9969, loss_cls: 0.5060, loss: 0.5060 +2025-06-24 20:19:07,602 - pyskl - INFO - Epoch [58][800/1281] lr: 1.695e-02, eta: 13:40:12, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9981, loss_cls: 0.5458, loss: 0.5458 +2025-06-24 20:19:56,599 - pyskl - INFO - Epoch [58][900/1281] lr: 1.693e-02, eta: 13:39:42, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9975, loss_cls: 0.5214, loss: 0.5214 +2025-06-24 20:20:45,499 - pyskl - INFO - Epoch [58][1000/1281] lr: 1.691e-02, eta: 13:39:12, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9938, loss_cls: 0.5202, loss: 0.5202 +2025-06-24 20:21:34,430 - pyskl - INFO - Epoch [58][1100/1281] lr: 1.689e-02, eta: 13:38:42, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9956, loss_cls: 0.5360, loss: 0.5360 +2025-06-24 20:22:23,301 - pyskl - INFO - Epoch [58][1200/1281] lr: 1.687e-02, eta: 13:38:12, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9969, loss_cls: 0.5452, loss: 0.5452 +2025-06-24 20:23:03,695 - pyskl - INFO - Saving checkpoint at 58 epochs +2025-06-24 20:24:02,364 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:24:02,419 - pyskl - INFO - +top1_acc 0.8535 +top5_acc 0.9921 +2025-06-24 20:24:02,420 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:24:02,426 - pyskl - INFO - +mean_acc 0.8037 +2025-06-24 20:24:02,428 - pyskl - INFO - Epoch(val) [58][533] top1_acc: 0.8535, top5_acc: 0.9921, mean_class_accuracy: 0.8037 +2025-06-24 20:25:21,806 - pyskl - INFO - Epoch [59][100/1281] lr: 1.684e-02, eta: 13:37:03, time: 0.794, data_time: 0.189, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9988, loss_cls: 0.4859, loss: 0.4859 +2025-06-24 20:26:10,702 - pyskl - INFO - Epoch [59][200/1281] lr: 1.682e-02, eta: 13:36:33, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9988, loss_cls: 0.5181, loss: 0.5181 +2025-06-24 20:26:59,623 - pyskl - INFO - Epoch [59][300/1281] lr: 1.680e-02, eta: 13:36:03, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9975, loss_cls: 0.4805, loss: 0.4805 +2025-06-24 20:27:31,656 - pyskl - INFO - Epoch [59][400/1281] lr: 1.678e-02, eta: 13:35:06, time: 0.320, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9988, loss_cls: 0.5130, loss: 0.5130 +2025-06-24 20:28:13,131 - pyskl - INFO - Epoch [59][500/1281] lr: 1.676e-02, eta: 13:34:24, time: 0.415, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9956, loss_cls: 0.5243, loss: 0.5243 +2025-06-24 20:28:49,984 - pyskl - INFO - Epoch [59][600/1281] lr: 1.674e-02, eta: 13:33:35, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9950, loss_cls: 0.5340, loss: 0.5340 +2025-06-24 20:29:39,045 - pyskl - INFO - Epoch [59][700/1281] lr: 1.672e-02, eta: 13:33:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9975, loss_cls: 0.4873, loss: 0.4873 +2025-06-24 20:30:28,194 - pyskl - INFO - Epoch [59][800/1281] lr: 1.670e-02, eta: 13:32:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9981, loss_cls: 0.4826, loss: 0.4826 +2025-06-24 20:31:17,312 - pyskl - INFO - Epoch [59][900/1281] lr: 1.668e-02, eta: 13:32:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9962, loss_cls: 0.4792, loss: 0.4792 +2025-06-24 20:32:05,920 - pyskl - INFO - Epoch [59][1000/1281] lr: 1.667e-02, eta: 13:31:34, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9975, loss_cls: 0.5840, loss: 0.5840 +2025-06-24 20:32:54,655 - pyskl - INFO - Epoch [59][1100/1281] lr: 1.665e-02, eta: 13:31:03, time: 0.487, data_time: 0.001, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9975, loss_cls: 0.5609, loss: 0.5609 +2025-06-24 20:33:43,802 - pyskl - INFO - Epoch [59][1200/1281] lr: 1.663e-02, eta: 13:30:33, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9988, loss_cls: 0.5477, loss: 0.5477 +2025-06-24 20:34:24,320 - pyskl - INFO - Saving checkpoint at 59 epochs +2025-06-24 20:35:23,432 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:35:23,505 - pyskl - INFO - +top1_acc 0.8607 +top5_acc 0.9910 +2025-06-24 20:35:23,505 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:35:23,514 - pyskl - INFO - +mean_acc 0.8194 +2025-06-24 20:35:23,517 - pyskl - INFO - Epoch(val) [59][533] top1_acc: 0.8607, top5_acc: 0.9910, mean_class_accuracy: 0.8194 +2025-06-24 20:36:43,507 - pyskl - INFO - Epoch [60][100/1281] lr: 1.659e-02, eta: 13:29:24, time: 0.800, data_time: 0.199, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9950, loss_cls: 0.5383, loss: 0.5383 +2025-06-24 20:37:32,534 - pyskl - INFO - Epoch [60][200/1281] lr: 1.657e-02, eta: 13:28:54, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9994, loss_cls: 0.5185, loss: 0.5185 +2025-06-24 20:38:19,887 - pyskl - INFO - Epoch [60][300/1281] lr: 1.655e-02, eta: 13:28:21, time: 0.474, data_time: 0.001, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9969, loss_cls: 0.5243, loss: 0.5243 +2025-06-24 20:38:55,833 - pyskl - INFO - Epoch [60][400/1281] lr: 1.653e-02, eta: 13:27:30, time: 0.359, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9969, loss_cls: 0.5312, loss: 0.5312 +2025-06-24 20:39:33,653 - pyskl - INFO - Epoch [60][500/1281] lr: 1.651e-02, eta: 13:26:43, time: 0.378, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9962, loss_cls: 0.5727, loss: 0.5727 +2025-06-24 20:40:10,811 - pyskl - INFO - Epoch [60][600/1281] lr: 1.650e-02, eta: 13:25:54, time: 0.372, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9969, loss_cls: 0.4592, loss: 0.4592 +2025-06-24 20:40:59,711 - pyskl - INFO - Epoch [60][700/1281] lr: 1.648e-02, eta: 13:25:23, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9994, loss_cls: 0.4334, loss: 0.4334 +2025-06-24 20:41:48,896 - pyskl - INFO - Epoch [60][800/1281] lr: 1.646e-02, eta: 13:24:53, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9962, loss_cls: 0.5273, loss: 0.5273 +2025-06-24 20:42:38,090 - pyskl - INFO - Epoch [60][900/1281] lr: 1.644e-02, eta: 13:24:23, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9950, loss_cls: 0.5104, loss: 0.5104 +2025-06-24 20:43:27,331 - pyskl - INFO - Epoch [60][1000/1281] lr: 1.642e-02, eta: 13:23:52, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9969, loss_cls: 0.5199, loss: 0.5199 +2025-06-24 20:44:16,139 - pyskl - INFO - Epoch [60][1100/1281] lr: 1.640e-02, eta: 13:23:21, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9969, loss_cls: 0.5433, loss: 0.5433 +2025-06-24 20:45:05,059 - pyskl - INFO - Epoch [60][1200/1281] lr: 1.638e-02, eta: 13:22:50, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9969, loss_cls: 0.5030, loss: 0.5030 +2025-06-24 20:45:45,316 - pyskl - INFO - Saving checkpoint at 60 epochs +2025-06-24 20:46:44,411 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:46:44,476 - pyskl - INFO - +top1_acc 0.8484 +top5_acc 0.9901 +2025-06-24 20:46:44,477 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:46:44,484 - pyskl - INFO - +mean_acc 0.7961 +2025-06-24 20:46:44,486 - pyskl - INFO - Epoch(val) [60][533] top1_acc: 0.8484, top5_acc: 0.9901, mean_class_accuracy: 0.7961 +2025-06-24 20:48:04,563 - pyskl - INFO - Epoch [61][100/1281] lr: 1.634e-02, eta: 13:21:41, time: 0.801, data_time: 0.196, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9969, loss_cls: 0.4959, loss: 0.4959 +2025-06-24 20:48:53,605 - pyskl - INFO - Epoch [61][200/1281] lr: 1.632e-02, eta: 13:21:11, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9981, loss_cls: 0.4874, loss: 0.4874 +2025-06-24 20:49:40,206 - pyskl - INFO - Epoch [61][300/1281] lr: 1.630e-02, eta: 13:20:36, time: 0.466, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9981, loss_cls: 0.4795, loss: 0.4795 +2025-06-24 20:50:17,710 - pyskl - INFO - Epoch [61][400/1281] lr: 1.629e-02, eta: 13:19:48, time: 0.375, data_time: 0.001, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9969, loss_cls: 0.5036, loss: 0.5036 +2025-06-24 20:50:53,818 - pyskl - INFO - Epoch [61][500/1281] lr: 1.627e-02, eta: 13:18:58, time: 0.361, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9962, loss_cls: 0.5809, loss: 0.5809 +2025-06-24 20:51:31,036 - pyskl - INFO - Epoch [61][600/1281] lr: 1.625e-02, eta: 13:18:09, time: 0.372, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9994, loss_cls: 0.4661, loss: 0.4661 +2025-06-24 20:52:19,915 - pyskl - INFO - Epoch [61][700/1281] lr: 1.623e-02, eta: 13:17:38, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9975, loss_cls: 0.4920, loss: 0.4920 +2025-06-24 20:53:08,889 - pyskl - INFO - Epoch [61][800/1281] lr: 1.621e-02, eta: 13:17:07, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9988, loss_cls: 0.4512, loss: 0.4512 +2025-06-24 20:53:57,883 - pyskl - INFO - Epoch [61][900/1281] lr: 1.619e-02, eta: 13:16:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9962, loss_cls: 0.5145, loss: 0.5145 +2025-06-24 20:54:46,924 - pyskl - INFO - Epoch [61][1000/1281] lr: 1.617e-02, eta: 13:16:04, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9981, loss_cls: 0.5116, loss: 0.5116 +2025-06-24 20:55:36,232 - pyskl - INFO - Epoch [61][1100/1281] lr: 1.615e-02, eta: 13:15:34, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9956, loss_cls: 0.5189, loss: 0.5189 +2025-06-24 20:56:24,849 - pyskl - INFO - Epoch [61][1200/1281] lr: 1.613e-02, eta: 13:15:02, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9962, loss_cls: 0.5074, loss: 0.5074 +2025-06-24 20:57:05,551 - pyskl - INFO - Saving checkpoint at 61 epochs +2025-06-24 20:58:05,234 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:58:05,293 - pyskl - INFO - +top1_acc 0.8407 +top5_acc 0.9894 +2025-06-24 20:58:05,293 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:58:05,300 - pyskl - INFO - +mean_acc 0.7668 +2025-06-24 20:58:05,301 - pyskl - INFO - Epoch(val) [61][533] top1_acc: 0.8407, top5_acc: 0.9894, mean_class_accuracy: 0.7668 +2025-06-24 20:59:24,643 - pyskl - INFO - Epoch [62][100/1281] lr: 1.609e-02, eta: 13:13:52, time: 0.793, data_time: 0.194, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 0.4349, loss: 0.4349 +2025-06-24 21:00:13,742 - pyskl - INFO - Epoch [62][200/1281] lr: 1.607e-02, eta: 13:13:20, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9962, loss_cls: 0.4096, loss: 0.4096 +2025-06-24 21:01:01,498 - pyskl - INFO - Epoch [62][300/1281] lr: 1.605e-02, eta: 13:12:47, time: 0.478, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9969, loss_cls: 0.4378, loss: 0.4378 +2025-06-24 21:01:37,698 - pyskl - INFO - Epoch [62][400/1281] lr: 1.603e-02, eta: 13:11:57, time: 0.362, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9988, loss_cls: 0.4334, loss: 0.4334 +2025-06-24 21:02:15,186 - pyskl - INFO - Epoch [62][500/1281] lr: 1.602e-02, eta: 13:11:09, time: 0.375, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9981, loss_cls: 0.4929, loss: 0.4929 +2025-06-24 21:02:53,223 - pyskl - INFO - Epoch [62][600/1281] lr: 1.600e-02, eta: 13:10:22, time: 0.380, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9969, loss_cls: 0.4898, loss: 0.4898 +2025-06-24 21:03:42,455 - pyskl - INFO - Epoch [62][700/1281] lr: 1.598e-02, eta: 13:09:51, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9988, loss_cls: 0.4969, loss: 0.4969 +2025-06-24 21:04:31,320 - pyskl - INFO - Epoch [62][800/1281] lr: 1.596e-02, eta: 13:09:19, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9988, loss_cls: 0.5024, loss: 0.5024 +2025-06-24 21:05:20,561 - pyskl - INFO - Epoch [62][900/1281] lr: 1.594e-02, eta: 13:08:48, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9956, loss_cls: 0.5599, loss: 0.5599 +2025-06-24 21:06:10,101 - pyskl - INFO - Epoch [62][1000/1281] lr: 1.592e-02, eta: 13:08:17, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9988, loss_cls: 0.4675, loss: 0.4675 +2025-06-24 21:06:58,751 - pyskl - INFO - Epoch [62][1100/1281] lr: 1.590e-02, eta: 13:07:45, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9988, loss_cls: 0.5881, loss: 0.5881 +2025-06-24 21:07:47,966 - pyskl - INFO - Epoch [62][1200/1281] lr: 1.588e-02, eta: 13:07:13, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9956, loss_cls: 0.5617, loss: 0.5617 +2025-06-24 21:08:28,612 - pyskl - INFO - Saving checkpoint at 62 epochs +2025-06-24 21:09:28,237 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:09:28,293 - pyskl - INFO - +top1_acc 0.8559 +top5_acc 0.9921 +2025-06-24 21:09:28,294 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:09:28,300 - pyskl - INFO - +mean_acc 0.8185 +2025-06-24 21:09:28,302 - pyskl - INFO - Epoch(val) [62][533] top1_acc: 0.8559, top5_acc: 0.9921, mean_class_accuracy: 0.8185 +2025-06-24 21:10:48,078 - pyskl - INFO - Epoch [63][100/1281] lr: 1.584e-02, eta: 13:06:03, time: 0.798, data_time: 0.190, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9975, loss_cls: 0.4129, loss: 0.4129 +2025-06-24 21:11:37,430 - pyskl - INFO - Epoch [63][200/1281] lr: 1.582e-02, eta: 13:05:32, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9981, loss_cls: 0.4577, loss: 0.4577 +2025-06-24 21:12:24,017 - pyskl - INFO - Epoch [63][300/1281] lr: 1.580e-02, eta: 13:04:56, time: 0.466, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9994, loss_cls: 0.4976, loss: 0.4976 +2025-06-24 21:13:00,460 - pyskl - INFO - Epoch [63][400/1281] lr: 1.578e-02, eta: 13:04:07, time: 0.364, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9956, loss_cls: 0.4696, loss: 0.4696 +2025-06-24 21:13:37,318 - pyskl - INFO - Epoch [63][500/1281] lr: 1.576e-02, eta: 13:03:18, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9969, loss_cls: 0.4321, loss: 0.4321 +2025-06-24 21:14:14,900 - pyskl - INFO - Epoch [63][600/1281] lr: 1.574e-02, eta: 13:02:30, time: 0.376, data_time: 0.001, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9988, loss_cls: 0.4310, loss: 0.4310 +2025-06-24 21:15:03,890 - pyskl - INFO - Epoch [63][700/1281] lr: 1.572e-02, eta: 13:01:58, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9975, loss_cls: 0.4778, loss: 0.4778 +2025-06-24 21:15:53,278 - pyskl - INFO - Epoch [63][800/1281] lr: 1.570e-02, eta: 13:01:27, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9994, loss_cls: 0.4446, loss: 0.4446 +2025-06-24 21:16:42,758 - pyskl - INFO - Epoch [63][900/1281] lr: 1.568e-02, eta: 13:00:55, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9981, loss_cls: 0.5629, loss: 0.5629 +2025-06-24 21:17:32,138 - pyskl - INFO - Epoch [63][1000/1281] lr: 1.566e-02, eta: 13:00:24, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9950, loss_cls: 0.4928, loss: 0.4928 +2025-06-24 21:18:21,035 - pyskl - INFO - Epoch [63][1100/1281] lr: 1.564e-02, eta: 12:59:52, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9944, loss_cls: 0.5149, loss: 0.5149 +2025-06-24 21:19:10,283 - pyskl - INFO - Epoch [63][1200/1281] lr: 1.562e-02, eta: 12:59:20, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9950, loss_cls: 0.4840, loss: 0.4840 +2025-06-24 21:19:51,107 - pyskl - INFO - Saving checkpoint at 63 epochs +2025-06-24 21:20:50,285 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:20:50,339 - pyskl - INFO - +top1_acc 0.8515 +top5_acc 0.9910 +2025-06-24 21:20:50,340 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:20:50,347 - pyskl - INFO - +mean_acc 0.8012 +2025-06-24 21:20:50,349 - pyskl - INFO - Epoch(val) [63][533] top1_acc: 0.8515, top5_acc: 0.9910, mean_class_accuracy: 0.8012 +2025-06-24 21:22:08,886 - pyskl - INFO - Epoch [64][100/1281] lr: 1.559e-02, eta: 12:58:08, time: 0.785, data_time: 0.191, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9994, loss_cls: 0.4616, loss: 0.4616 +2025-06-24 21:22:58,101 - pyskl - INFO - Epoch [64][200/1281] lr: 1.557e-02, eta: 12:57:36, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9969, loss_cls: 0.4365, loss: 0.4365 +2025-06-24 21:23:46,161 - pyskl - INFO - Epoch [64][300/1281] lr: 1.555e-02, eta: 12:57:02, time: 0.481, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9981, loss_cls: 0.4670, loss: 0.4670 +2025-06-24 21:24:20,545 - pyskl - INFO - Epoch [64][400/1281] lr: 1.553e-02, eta: 12:56:10, time: 0.344, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9988, loss_cls: 0.4696, loss: 0.4696 +2025-06-24 21:24:59,662 - pyskl - INFO - Epoch [64][500/1281] lr: 1.551e-02, eta: 12:55:24, time: 0.391, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9988, loss_cls: 0.4411, loss: 0.4411 +2025-06-24 21:25:36,896 - pyskl - INFO - Epoch [64][600/1281] lr: 1.549e-02, eta: 12:54:36, time: 0.372, data_time: 0.001, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9988, loss_cls: 0.4693, loss: 0.4693 +2025-06-24 21:26:26,048 - pyskl - INFO - Epoch [64][700/1281] lr: 1.547e-02, eta: 12:54:04, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9975, loss_cls: 0.4291, loss: 0.4291 +2025-06-24 21:27:15,248 - pyskl - INFO - Epoch [64][800/1281] lr: 1.545e-02, eta: 12:53:32, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9975, loss_cls: 0.4758, loss: 0.4758 +2025-06-24 21:28:04,379 - pyskl - INFO - Epoch [64][900/1281] lr: 1.543e-02, eta: 12:52:59, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9944, loss_cls: 0.5259, loss: 0.5259 +2025-06-24 21:28:53,485 - pyskl - INFO - Epoch [64][1000/1281] lr: 1.541e-02, eta: 12:52:27, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9975, loss_cls: 0.5033, loss: 0.5033 +2025-06-24 21:29:42,364 - pyskl - INFO - Epoch [64][1100/1281] lr: 1.539e-02, eta: 12:51:54, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9981, loss_cls: 0.5349, loss: 0.5349 +2025-06-24 21:30:31,337 - pyskl - INFO - Epoch [64][1200/1281] lr: 1.537e-02, eta: 12:51:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9981, loss_cls: 0.4747, loss: 0.4747 +2025-06-24 21:31:11,446 - pyskl - INFO - Saving checkpoint at 64 epochs +2025-06-24 21:32:10,634 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:32:10,688 - pyskl - INFO - +top1_acc 0.8540 +top5_acc 0.9879 +2025-06-24 21:32:10,689 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:32:10,695 - pyskl - INFO - +mean_acc 0.7913 +2025-06-24 21:32:10,697 - pyskl - INFO - Epoch(val) [64][533] top1_acc: 0.8540, top5_acc: 0.9879, mean_class_accuracy: 0.7913 +2025-06-24 21:33:31,533 - pyskl - INFO - Epoch [65][100/1281] lr: 1.533e-02, eta: 12:50:12, time: 0.808, data_time: 0.201, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9975, loss_cls: 0.4843, loss: 0.4843 +2025-06-24 21:34:20,848 - pyskl - INFO - Epoch [65][200/1281] lr: 1.531e-02, eta: 12:49:40, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9994, loss_cls: 0.4278, loss: 0.4278 +2025-06-24 21:35:07,096 - pyskl - INFO - Epoch [65][300/1281] lr: 1.529e-02, eta: 12:49:04, time: 0.462, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9981, loss_cls: 0.4339, loss: 0.4339 +2025-06-24 21:35:44,656 - pyskl - INFO - Epoch [65][400/1281] lr: 1.527e-02, eta: 12:48:16, time: 0.376, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9969, loss_cls: 0.5034, loss: 0.5034 +2025-06-24 21:36:20,565 - pyskl - INFO - Epoch [65][500/1281] lr: 1.526e-02, eta: 12:47:26, time: 0.359, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9988, loss_cls: 0.4435, loss: 0.4435 +2025-06-24 21:36:58,884 - pyskl - INFO - Epoch [65][600/1281] lr: 1.524e-02, eta: 12:46:39, time: 0.383, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9956, loss_cls: 0.4878, loss: 0.4878 +2025-06-24 21:37:47,757 - pyskl - INFO - Epoch [65][700/1281] lr: 1.522e-02, eta: 12:46:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9944, loss_cls: 0.4698, loss: 0.4698 +2025-06-24 21:38:37,133 - pyskl - INFO - Epoch [65][800/1281] lr: 1.520e-02, eta: 12:45:34, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9962, loss_cls: 0.4775, loss: 0.4775 +2025-06-24 21:39:26,023 - pyskl - INFO - Epoch [65][900/1281] lr: 1.518e-02, eta: 12:45:01, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 1.0000, loss_cls: 0.4439, loss: 0.4439 +2025-06-24 21:40:15,187 - pyskl - INFO - Epoch [65][1000/1281] lr: 1.516e-02, eta: 12:44:28, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9969, loss_cls: 0.5052, loss: 0.5052 +2025-06-24 21:41:04,371 - pyskl - INFO - Epoch [65][1100/1281] lr: 1.514e-02, eta: 12:43:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9975, loss_cls: 0.4398, loss: 0.4398 +2025-06-24 21:41:53,293 - pyskl - INFO - Epoch [65][1200/1281] lr: 1.512e-02, eta: 12:43:23, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9962, loss_cls: 0.4698, loss: 0.4698 +2025-06-24 21:42:33,773 - pyskl - INFO - Saving checkpoint at 65 epochs +2025-06-24 21:43:33,045 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:43:33,100 - pyskl - INFO - +top1_acc 0.8480 +top5_acc 0.9892 +2025-06-24 21:43:33,100 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:43:33,107 - pyskl - INFO - +mean_acc 0.8049 +2025-06-24 21:43:33,109 - pyskl - INFO - Epoch(val) [65][533] top1_acc: 0.8480, top5_acc: 0.9892, mean_class_accuracy: 0.8049 +2025-06-24 21:44:52,304 - pyskl - INFO - Epoch [66][100/1281] lr: 1.508e-02, eta: 12:42:11, time: 0.792, data_time: 0.199, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9962, loss_cls: 0.4788, loss: 0.4788 +2025-06-24 21:45:41,548 - pyskl - INFO - Epoch [66][200/1281] lr: 1.506e-02, eta: 12:41:38, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9969, loss_cls: 0.4484, loss: 0.4484 +2025-06-24 21:46:27,868 - pyskl - INFO - Epoch [66][300/1281] lr: 1.504e-02, eta: 12:41:02, time: 0.463, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9994, loss_cls: 0.4581, loss: 0.4581 +2025-06-24 21:47:04,659 - pyskl - INFO - Epoch [66][400/1281] lr: 1.502e-02, eta: 12:40:13, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9988, loss_cls: 0.4027, loss: 0.4027 +2025-06-24 21:47:41,565 - pyskl - INFO - Epoch [66][500/1281] lr: 1.500e-02, eta: 12:39:24, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9988, loss_cls: 0.4218, loss: 0.4218 +2025-06-24 21:48:19,365 - pyskl - INFO - Epoch [66][600/1281] lr: 1.498e-02, eta: 12:38:37, time: 0.378, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9975, loss_cls: 0.3988, loss: 0.3988 +2025-06-24 21:49:08,610 - pyskl - INFO - Epoch [66][700/1281] lr: 1.496e-02, eta: 12:38:04, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9962, loss_cls: 0.4699, loss: 0.4699 +2025-06-24 21:49:57,974 - pyskl - INFO - Epoch [66][800/1281] lr: 1.494e-02, eta: 12:37:31, time: 0.494, data_time: 0.001, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9962, loss_cls: 0.4403, loss: 0.4403 +2025-06-24 21:50:47,036 - pyskl - INFO - Epoch [66][900/1281] lr: 1.492e-02, eta: 12:36:58, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9981, loss_cls: 0.4350, loss: 0.4350 +2025-06-24 21:51:36,299 - pyskl - INFO - Epoch [66][1000/1281] lr: 1.490e-02, eta: 12:36:25, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9969, loss_cls: 0.5008, loss: 0.5008 +2025-06-24 21:52:25,386 - pyskl - INFO - Epoch [66][1100/1281] lr: 1.488e-02, eta: 12:35:52, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9975, loss_cls: 0.4293, loss: 0.4293 +2025-06-24 21:53:14,674 - pyskl - INFO - Epoch [66][1200/1281] lr: 1.486e-02, eta: 12:35:19, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9988, loss_cls: 0.5476, loss: 0.5476 +2025-06-24 21:53:54,797 - pyskl - INFO - Saving checkpoint at 66 epochs +2025-06-24 21:54:53,781 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:54:53,836 - pyskl - INFO - +top1_acc 0.8443 +top5_acc 0.9907 +2025-06-24 21:54:53,836 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:54:53,844 - pyskl - INFO - +mean_acc 0.7832 +2025-06-24 21:54:53,846 - pyskl - INFO - Epoch(val) [66][533] top1_acc: 0.8443, top5_acc: 0.9907, mean_class_accuracy: 0.7832 +2025-06-24 21:56:13,090 - pyskl - INFO - Epoch [67][100/1281] lr: 1.482e-02, eta: 12:34:07, time: 0.792, data_time: 0.188, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9981, loss_cls: 0.4689, loss: 0.4689 +2025-06-24 21:57:02,223 - pyskl - INFO - Epoch [67][200/1281] lr: 1.480e-02, eta: 12:33:34, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9988, loss_cls: 0.4168, loss: 0.4168 +2025-06-24 21:57:49,914 - pyskl - INFO - Epoch [67][300/1281] lr: 1.478e-02, eta: 12:32:59, time: 0.477, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 1.0000, loss_cls: 0.4386, loss: 0.4386 +2025-06-24 21:58:25,879 - pyskl - INFO - Epoch [67][400/1281] lr: 1.476e-02, eta: 12:32:09, time: 0.360, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9975, loss_cls: 0.4561, loss: 0.4561 +2025-06-24 21:59:03,516 - pyskl - INFO - Epoch [67][500/1281] lr: 1.474e-02, eta: 12:31:21, time: 0.376, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9988, loss_cls: 0.3982, loss: 0.3982 +2025-06-24 21:59:39,928 - pyskl - INFO - Epoch [67][600/1281] lr: 1.472e-02, eta: 12:30:32, time: 0.364, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9962, loss_cls: 0.4578, loss: 0.4578 +2025-06-24 22:00:29,046 - pyskl - INFO - Epoch [67][700/1281] lr: 1.470e-02, eta: 12:29:59, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9956, loss_cls: 0.4369, loss: 0.4369 +2025-06-24 22:01:18,053 - pyskl - INFO - Epoch [67][800/1281] lr: 1.468e-02, eta: 12:29:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9981, loss_cls: 0.4327, loss: 0.4327 +2025-06-24 22:02:07,665 - pyskl - INFO - Epoch [67][900/1281] lr: 1.466e-02, eta: 12:28:53, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9962, loss_cls: 0.4715, loss: 0.4715 +2025-06-24 22:02:56,710 - pyskl - INFO - Epoch [67][1000/1281] lr: 1.464e-02, eta: 12:28:19, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9969, loss_cls: 0.5079, loss: 0.5079 +2025-06-24 22:03:45,691 - pyskl - INFO - Epoch [67][1100/1281] lr: 1.462e-02, eta: 12:27:46, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9969, loss_cls: 0.4988, loss: 0.4988 +2025-06-24 22:04:34,928 - pyskl - INFO - Epoch [67][1200/1281] lr: 1.460e-02, eta: 12:27:12, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 1.0000, loss_cls: 0.4378, loss: 0.4378 +2025-06-24 22:05:15,498 - pyskl - INFO - Saving checkpoint at 67 epochs +2025-06-24 22:06:14,301 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:06:14,358 - pyskl - INFO - +top1_acc 0.8625 +top5_acc 0.9893 +2025-06-24 22:06:14,358 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:06:14,367 - pyskl - INFO - +mean_acc 0.7984 +2025-06-24 22:06:14,371 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_56.pth was removed +2025-06-24 22:06:14,542 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_67.pth. +2025-06-24 22:06:14,542 - pyskl - INFO - Best top1_acc is 0.8625 at 67 epoch. +2025-06-24 22:06:14,545 - pyskl - INFO - Epoch(val) [67][533] top1_acc: 0.8625, top5_acc: 0.9893, mean_class_accuracy: 0.7984 +2025-06-24 22:07:34,621 - pyskl - INFO - Epoch [68][100/1281] lr: 1.456e-02, eta: 12:26:01, time: 0.801, data_time: 0.190, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9994, loss_cls: 0.4286, loss: 0.4286 +2025-06-24 22:08:23,344 - pyskl - INFO - Epoch [68][200/1281] lr: 1.454e-02, eta: 12:25:27, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9981, loss_cls: 0.4390, loss: 0.4390 +2025-06-24 22:09:11,357 - pyskl - INFO - Epoch [68][300/1281] lr: 1.452e-02, eta: 12:24:52, time: 0.480, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9975, loss_cls: 0.4447, loss: 0.4447 +2025-06-24 22:09:44,309 - pyskl - INFO - Epoch [68][400/1281] lr: 1.450e-02, eta: 12:23:58, time: 0.330, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9975, loss_cls: 0.4433, loss: 0.4433 +2025-06-24 22:10:24,984 - pyskl - INFO - Epoch [68][500/1281] lr: 1.448e-02, eta: 12:23:14, time: 0.407, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9962, loss_cls: 0.4688, loss: 0.4688 +2025-06-24 22:11:01,259 - pyskl - INFO - Epoch [68][600/1281] lr: 1.446e-02, eta: 12:22:25, time: 0.363, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9975, loss_cls: 0.4295, loss: 0.4295 +2025-06-24 22:11:50,496 - pyskl - INFO - Epoch [68][700/1281] lr: 1.444e-02, eta: 12:21:52, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9988, loss_cls: 0.4581, loss: 0.4581 +2025-06-24 22:12:39,938 - pyskl - INFO - Epoch [68][800/1281] lr: 1.442e-02, eta: 12:21:18, time: 0.494, data_time: 0.001, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 0.4022, loss: 0.4022 +2025-06-24 22:13:28,913 - pyskl - INFO - Epoch [68][900/1281] lr: 1.440e-02, eta: 12:20:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9969, loss_cls: 0.4527, loss: 0.4527 +2025-06-24 22:14:18,072 - pyskl - INFO - Epoch [68][1000/1281] lr: 1.438e-02, eta: 12:20:11, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9981, loss_cls: 0.4627, loss: 0.4627 +2025-06-24 22:15:06,869 - pyskl - INFO - Epoch [68][1100/1281] lr: 1.436e-02, eta: 12:19:37, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9962, loss_cls: 0.5223, loss: 0.5223 +2025-06-24 22:15:55,779 - pyskl - INFO - Epoch [68][1200/1281] lr: 1.434e-02, eta: 12:19:03, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9975, loss_cls: 0.4435, loss: 0.4435 +2025-06-24 22:16:36,099 - pyskl - INFO - Saving checkpoint at 68 epochs +2025-06-24 22:17:35,630 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:17:35,688 - pyskl - INFO - +top1_acc 0.8418 +top5_acc 0.9852 +2025-06-24 22:17:35,688 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:17:35,695 - pyskl - INFO - +mean_acc 0.8044 +2025-06-24 22:17:35,697 - pyskl - INFO - Epoch(val) [68][533] top1_acc: 0.8418, top5_acc: 0.9852, mean_class_accuracy: 0.8044 +2025-06-24 22:18:55,268 - pyskl - INFO - Epoch [69][100/1281] lr: 1.431e-02, eta: 12:17:50, time: 0.796, data_time: 0.189, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9988, loss_cls: 0.4551, loss: 0.4551 +2025-06-24 22:19:44,355 - pyskl - INFO - Epoch [69][200/1281] lr: 1.429e-02, eta: 12:17:16, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9988, loss_cls: 0.3474, loss: 0.3474 +2025-06-24 22:20:32,692 - pyskl - INFO - Epoch [69][300/1281] lr: 1.427e-02, eta: 12:16:41, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9969, loss_cls: 0.4037, loss: 0.4037 +2025-06-24 22:21:06,405 - pyskl - INFO - Epoch [69][400/1281] lr: 1.425e-02, eta: 12:15:49, time: 0.337, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9962, loss_cls: 0.4297, loss: 0.4297 +2025-06-24 22:21:46,183 - pyskl - INFO - Epoch [69][500/1281] lr: 1.423e-02, eta: 12:15:04, time: 0.398, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9988, loss_cls: 0.4284, loss: 0.4284 +2025-06-24 22:22:23,044 - pyskl - INFO - Epoch [69][600/1281] lr: 1.420e-02, eta: 12:14:15, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9944, loss_cls: 0.4557, loss: 0.4557 +2025-06-24 22:23:12,019 - pyskl - INFO - Epoch [69][700/1281] lr: 1.418e-02, eta: 12:13:41, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9981, loss_cls: 0.4560, loss: 0.4560 +2025-06-24 22:24:01,283 - pyskl - INFO - Epoch [69][800/1281] lr: 1.416e-02, eta: 12:13:07, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9994, loss_cls: 0.4375, loss: 0.4375 +2025-06-24 22:24:50,159 - pyskl - INFO - Epoch [69][900/1281] lr: 1.414e-02, eta: 12:12:33, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9975, loss_cls: 0.4600, loss: 0.4600 +2025-06-24 22:25:39,604 - pyskl - INFO - Epoch [69][1000/1281] lr: 1.412e-02, eta: 12:12:00, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9969, loss_cls: 0.4538, loss: 0.4538 +2025-06-24 22:26:28,372 - pyskl - INFO - Epoch [69][1100/1281] lr: 1.410e-02, eta: 12:11:25, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9975, loss_cls: 0.5118, loss: 0.5118 +2025-06-24 22:27:17,568 - pyskl - INFO - Epoch [69][1200/1281] lr: 1.408e-02, eta: 12:10:51, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9988, loss_cls: 0.4616, loss: 0.4616 +2025-06-24 22:27:57,850 - pyskl - INFO - Saving checkpoint at 69 epochs +2025-06-24 22:28:56,245 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:28:56,300 - pyskl - INFO - +top1_acc 0.8628 +top5_acc 0.9910 +2025-06-24 22:28:56,301 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:28:56,308 - pyskl - INFO - +mean_acc 0.7979 +2025-06-24 22:28:56,312 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_67.pth was removed +2025-06-24 22:28:56,486 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_69.pth. +2025-06-24 22:28:56,487 - pyskl - INFO - Best top1_acc is 0.8628 at 69 epoch. +2025-06-24 22:28:56,492 - pyskl - INFO - Epoch(val) [69][533] top1_acc: 0.8628, top5_acc: 0.9910, mean_class_accuracy: 0.7979 +2025-06-24 22:30:15,394 - pyskl - INFO - Epoch [70][100/1281] lr: 1.405e-02, eta: 12:09:37, time: 0.789, data_time: 0.195, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9988, loss_cls: 0.4495, loss: 0.4495 +2025-06-24 22:31:04,345 - pyskl - INFO - Epoch [70][200/1281] lr: 1.403e-02, eta: 12:09:03, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9975, loss_cls: 0.3377, loss: 0.3377 +2025-06-24 22:31:53,165 - pyskl - INFO - Epoch [70][300/1281] lr: 1.401e-02, eta: 12:08:29, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9975, loss_cls: 0.4467, loss: 0.4467 +2025-06-24 22:32:23,232 - pyskl - INFO - Epoch [70][400/1281] lr: 1.399e-02, eta: 12:07:32, time: 0.301, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9988, loss_cls: 0.3870, loss: 0.3870 +2025-06-24 22:33:07,370 - pyskl - INFO - Epoch [70][500/1281] lr: 1.397e-02, eta: 12:06:52, time: 0.441, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9988, loss_cls: 0.4073, loss: 0.4073 +2025-06-24 22:33:40,348 - pyskl - INFO - Epoch [70][600/1281] lr: 1.395e-02, eta: 12:05:59, time: 0.330, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9975, loss_cls: 0.4358, loss: 0.4358 +2025-06-24 22:34:29,526 - pyskl - INFO - Epoch [70][700/1281] lr: 1.392e-02, eta: 12:05:25, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9981, loss_cls: 0.3758, loss: 0.3758 +2025-06-24 22:35:19,036 - pyskl - INFO - Epoch [70][800/1281] lr: 1.390e-02, eta: 12:04:51, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9962, loss_cls: 0.4677, loss: 0.4677 +2025-06-24 22:36:08,431 - pyskl - INFO - Epoch [70][900/1281] lr: 1.388e-02, eta: 12:04:17, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9975, loss_cls: 0.5411, loss: 0.5411 +2025-06-24 22:36:57,640 - pyskl - INFO - Epoch [70][1000/1281] lr: 1.386e-02, eta: 12:03:43, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9956, loss_cls: 0.5205, loss: 0.5205 +2025-06-24 22:37:46,843 - pyskl - INFO - Epoch [70][1100/1281] lr: 1.384e-02, eta: 12:03:09, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9981, loss_cls: 0.4261, loss: 0.4261 +2025-06-24 22:38:35,860 - pyskl - INFO - Epoch [70][1200/1281] lr: 1.382e-02, eta: 12:02:34, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9956, loss_cls: 0.4448, loss: 0.4448 +2025-06-24 22:39:16,533 - pyskl - INFO - Saving checkpoint at 70 epochs +2025-06-24 22:40:15,802 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:40:15,869 - pyskl - INFO - +top1_acc 0.8505 +top5_acc 0.9900 +2025-06-24 22:40:15,869 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:40:15,877 - pyskl - INFO - +mean_acc 0.8115 +2025-06-24 22:40:15,879 - pyskl - INFO - Epoch(val) [70][533] top1_acc: 0.8505, top5_acc: 0.9900, mean_class_accuracy: 0.8115 +2025-06-24 22:41:34,954 - pyskl - INFO - Epoch [71][100/1281] lr: 1.379e-02, eta: 12:01:20, time: 0.791, data_time: 0.191, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9988, loss_cls: 0.4056, loss: 0.4056 +2025-06-24 22:42:24,259 - pyskl - INFO - Epoch [71][200/1281] lr: 1.377e-02, eta: 12:00:46, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 1.0000, loss_cls: 0.3480, loss: 0.3480 +2025-06-24 22:43:13,241 - pyskl - INFO - Epoch [71][300/1281] lr: 1.375e-02, eta: 12:00:11, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 0.3714, loss: 0.3714 +2025-06-24 22:43:42,177 - pyskl - INFO - Epoch [71][400/1281] lr: 1.373e-02, eta: 11:59:14, time: 0.289, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9994, loss_cls: 0.4141, loss: 0.4141 +2025-06-24 22:44:29,590 - pyskl - INFO - Epoch [71][500/1281] lr: 1.371e-02, eta: 11:58:38, time: 0.474, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9975, loss_cls: 0.4359, loss: 0.4359 +2025-06-24 22:45:02,462 - pyskl - INFO - Epoch [71][600/1281] lr: 1.368e-02, eta: 11:57:45, time: 0.329, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9981, loss_cls: 0.3816, loss: 0.3816 +2025-06-24 22:45:51,543 - pyskl - INFO - Epoch [71][700/1281] lr: 1.366e-02, eta: 11:57:10, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9988, loss_cls: 0.4854, loss: 0.4854 +2025-06-24 22:46:41,093 - pyskl - INFO - Epoch [71][800/1281] lr: 1.364e-02, eta: 11:56:36, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9969, loss_cls: 0.5222, loss: 0.5222 +2025-06-24 22:47:30,115 - pyskl - INFO - Epoch [71][900/1281] lr: 1.362e-02, eta: 11:56:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9969, loss_cls: 0.4931, loss: 0.4931 +2025-06-24 22:48:19,603 - pyskl - INFO - Epoch [71][1000/1281] lr: 1.360e-02, eta: 11:55:27, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9962, loss_cls: 0.4433, loss: 0.4433 +2025-06-24 22:49:08,811 - pyskl - INFO - Epoch [71][1100/1281] lr: 1.358e-02, eta: 11:54:52, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 0.3535, loss: 0.3535 +2025-06-24 22:49:57,955 - pyskl - INFO - Epoch [71][1200/1281] lr: 1.356e-02, eta: 11:54:18, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9975, loss_cls: 0.4103, loss: 0.4103 +2025-06-24 22:50:38,217 - pyskl - INFO - Saving checkpoint at 71 epochs +2025-06-24 22:51:37,008 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:51:37,076 - pyskl - INFO - +top1_acc 0.8608 +top5_acc 0.9907 +2025-06-24 22:51:37,076 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:51:37,084 - pyskl - INFO - +mean_acc 0.8246 +2025-06-24 22:51:37,086 - pyskl - INFO - Epoch(val) [71][533] top1_acc: 0.8608, top5_acc: 0.9907, mean_class_accuracy: 0.8246 +2025-06-24 22:52:57,097 - pyskl - INFO - Epoch [72][100/1281] lr: 1.353e-02, eta: 11:53:05, time: 0.800, data_time: 0.190, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9981, loss_cls: 0.4173, loss: 0.4173 +2025-06-24 22:53:46,680 - pyskl - INFO - Epoch [72][200/1281] lr: 1.351e-02, eta: 11:52:31, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9969, loss_cls: 0.4040, loss: 0.4040 +2025-06-24 22:54:35,897 - pyskl - INFO - Epoch [72][300/1281] lr: 1.349e-02, eta: 11:51:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 0.3416, loss: 0.3416 +2025-06-24 22:55:05,977 - pyskl - INFO - Epoch [72][400/1281] lr: 1.346e-02, eta: 11:51:00, time: 0.301, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 1.0000, loss_cls: 0.3392, loss: 0.3392 +2025-06-24 22:55:51,564 - pyskl - INFO - Epoch [72][500/1281] lr: 1.344e-02, eta: 11:50:21, time: 0.456, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9975, loss_cls: 0.4598, loss: 0.4598 +2025-06-24 22:56:23,115 - pyskl - INFO - Epoch [72][600/1281] lr: 1.342e-02, eta: 11:49:27, time: 0.315, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9975, loss_cls: 0.4390, loss: 0.4390 +2025-06-24 22:57:12,300 - pyskl - INFO - Epoch [72][700/1281] lr: 1.340e-02, eta: 11:48:52, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9975, loss_cls: 0.4157, loss: 0.4157 +2025-06-24 22:58:01,801 - pyskl - INFO - Epoch [72][800/1281] lr: 1.338e-02, eta: 11:48:18, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9981, loss_cls: 0.4454, loss: 0.4454 +2025-06-24 22:58:51,029 - pyskl - INFO - Epoch [72][900/1281] lr: 1.336e-02, eta: 11:47:43, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9981, loss_cls: 0.4755, loss: 0.4755 +2025-06-24 22:59:40,216 - pyskl - INFO - Epoch [72][1000/1281] lr: 1.334e-02, eta: 11:47:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9988, loss_cls: 0.4668, loss: 0.4668 +2025-06-24 23:00:29,326 - pyskl - INFO - Epoch [72][1100/1281] lr: 1.332e-02, eta: 11:46:33, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9988, loss_cls: 0.4745, loss: 0.4745 +2025-06-24 23:01:18,516 - pyskl - INFO - Epoch [72][1200/1281] lr: 1.330e-02, eta: 11:45:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9956, loss_cls: 0.4398, loss: 0.4398 +2025-06-24 23:01:58,909 - pyskl - INFO - Saving checkpoint at 72 epochs +2025-06-24 23:02:57,555 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:02:57,613 - pyskl - INFO - +top1_acc 0.8661 +top5_acc 0.9912 +2025-06-24 23:02:57,613 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:02:57,619 - pyskl - INFO - +mean_acc 0.8170 +2025-06-24 23:02:57,623 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_69.pth was removed +2025-06-24 23:02:57,793 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_72.pth. +2025-06-24 23:02:57,793 - pyskl - INFO - Best top1_acc is 0.8661 at 72 epoch. +2025-06-24 23:02:57,796 - pyskl - INFO - Epoch(val) [72][533] top1_acc: 0.8661, top5_acc: 0.9912, mean_class_accuracy: 0.8170 +2025-06-24 23:04:16,871 - pyskl - INFO - Epoch [73][100/1281] lr: 1.326e-02, eta: 11:44:44, time: 0.791, data_time: 0.195, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9994, loss_cls: 0.3899, loss: 0.3899 +2025-06-24 23:05:06,140 - pyskl - INFO - Epoch [73][200/1281] lr: 1.324e-02, eta: 11:44:09, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9975, loss_cls: 0.4112, loss: 0.4112 +2025-06-24 23:05:55,022 - pyskl - INFO - Epoch [73][300/1281] lr: 1.322e-02, eta: 11:43:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 1.0000, loss_cls: 0.3876, loss: 0.3876 +2025-06-24 23:06:22,597 - pyskl - INFO - Epoch [73][400/1281] lr: 1.320e-02, eta: 11:42:36, time: 0.276, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 1.0000, loss_cls: 0.4183, loss: 0.4183 +2025-06-24 23:07:13,658 - pyskl - INFO - Epoch [73][500/1281] lr: 1.318e-02, eta: 11:42:03, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 1.0000, loss_cls: 0.3956, loss: 0.3956 +2025-06-24 23:07:45,625 - pyskl - INFO - Epoch [73][600/1281] lr: 1.316e-02, eta: 11:41:09, time: 0.320, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9975, loss_cls: 0.4381, loss: 0.4381 +2025-06-24 23:08:35,020 - pyskl - INFO - Epoch [73][700/1281] lr: 1.314e-02, eta: 11:40:34, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9981, loss_cls: 0.4231, loss: 0.4231 +2025-06-24 23:09:24,107 - pyskl - INFO - Epoch [73][800/1281] lr: 1.312e-02, eta: 11:39:59, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9988, loss_cls: 0.4239, loss: 0.4239 +2025-06-24 23:10:13,610 - pyskl - INFO - Epoch [73][900/1281] lr: 1.310e-02, eta: 11:39:24, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9994, loss_cls: 0.3900, loss: 0.3900 +2025-06-24 23:11:02,835 - pyskl - INFO - Epoch [73][1000/1281] lr: 1.308e-02, eta: 11:38:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9962, loss_cls: 0.4486, loss: 0.4486 +2025-06-24 23:11:52,395 - pyskl - INFO - Epoch [73][1100/1281] lr: 1.306e-02, eta: 11:38:14, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9981, loss_cls: 0.3865, loss: 0.3865 +2025-06-24 23:12:41,538 - pyskl - INFO - Epoch [73][1200/1281] lr: 1.304e-02, eta: 11:37:39, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9994, loss_cls: 0.4157, loss: 0.4157 +2025-06-24 23:13:21,902 - pyskl - INFO - Saving checkpoint at 73 epochs +2025-06-24 23:14:21,187 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:14:21,242 - pyskl - INFO - +top1_acc 0.8851 +top5_acc 0.9945 +2025-06-24 23:14:21,242 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:14:21,249 - pyskl - INFO - +mean_acc 0.8492 +2025-06-24 23:14:21,253 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_72.pth was removed +2025-06-24 23:14:21,445 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_73.pth. +2025-06-24 23:14:21,446 - pyskl - INFO - Best top1_acc is 0.8851 at 73 epoch. +2025-06-24 23:14:21,448 - pyskl - INFO - Epoch(val) [73][533] top1_acc: 0.8851, top5_acc: 0.9945, mean_class_accuracy: 0.8492 +2025-06-24 23:15:42,001 - pyskl - INFO - Epoch [74][100/1281] lr: 1.300e-02, eta: 11:36:26, time: 0.805, data_time: 0.194, memory: 4083, top1_acc: 0.9337, top5_acc: 1.0000, loss_cls: 0.3670, loss: 0.3670 +2025-06-24 23:16:31,101 - pyskl - INFO - Epoch [74][200/1281] lr: 1.298e-02, eta: 11:35:51, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9988, loss_cls: 0.4139, loss: 0.4139 +2025-06-24 23:17:20,090 - pyskl - INFO - Epoch [74][300/1281] lr: 1.296e-02, eta: 11:35:15, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9969, loss_cls: 0.3892, loss: 0.3892 +2025-06-24 23:17:50,348 - pyskl - INFO - Epoch [74][400/1281] lr: 1.294e-02, eta: 11:34:20, time: 0.303, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9975, loss_cls: 0.3838, loss: 0.3838 +2025-06-24 23:18:35,541 - pyskl - INFO - Epoch [74][500/1281] lr: 1.292e-02, eta: 11:33:41, time: 0.452, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 1.0000, loss_cls: 0.3680, loss: 0.3680 +2025-06-24 23:19:09,264 - pyskl - INFO - Epoch [74][600/1281] lr: 1.290e-02, eta: 11:32:49, time: 0.337, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9981, loss_cls: 0.3737, loss: 0.3737 +2025-06-24 23:19:58,197 - pyskl - INFO - Epoch [74][700/1281] lr: 1.288e-02, eta: 11:32:14, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9969, loss_cls: 0.4435, loss: 0.4435 +2025-06-24 23:20:47,192 - pyskl - INFO - Epoch [74][800/1281] lr: 1.286e-02, eta: 11:31:38, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9981, loss_cls: 0.4144, loss: 0.4144 +2025-06-24 23:21:36,387 - pyskl - INFO - Epoch [74][900/1281] lr: 1.284e-02, eta: 11:31:03, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9975, loss_cls: 0.4595, loss: 0.4595 +2025-06-24 23:22:25,383 - pyskl - INFO - Epoch [74][1000/1281] lr: 1.282e-02, eta: 11:30:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 0.4200, loss: 0.4200 +2025-06-24 23:23:14,149 - pyskl - INFO - Epoch [74][1100/1281] lr: 1.280e-02, eta: 11:29:51, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9981, loss_cls: 0.4487, loss: 0.4487 +2025-06-24 23:24:03,330 - pyskl - INFO - Epoch [74][1200/1281] lr: 1.278e-02, eta: 11:29:16, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9988, loss_cls: 0.4366, loss: 0.4366 +2025-06-24 23:24:44,117 - pyskl - INFO - Saving checkpoint at 74 epochs +2025-06-24 23:25:42,962 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:25:43,017 - pyskl - INFO - +top1_acc 0.8715 +top5_acc 0.9914 +2025-06-24 23:25:43,017 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:25:43,024 - pyskl - INFO - +mean_acc 0.8280 +2025-06-24 23:25:43,026 - pyskl - INFO - Epoch(val) [74][533] top1_acc: 0.8715, top5_acc: 0.9914, mean_class_accuracy: 0.8280 +2025-06-24 23:27:02,131 - pyskl - INFO - Epoch [75][100/1281] lr: 1.274e-02, eta: 11:28:01, time: 0.791, data_time: 0.187, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9975, loss_cls: 0.3588, loss: 0.3588 +2025-06-24 23:27:51,091 - pyskl - INFO - Epoch [75][200/1281] lr: 1.272e-02, eta: 11:27:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9981, loss_cls: 0.3935, loss: 0.3935 +2025-06-24 23:28:40,062 - pyskl - INFO - Epoch [75][300/1281] lr: 1.270e-02, eta: 11:26:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9988, loss_cls: 0.3905, loss: 0.3905 +2025-06-24 23:29:09,366 - pyskl - INFO - Epoch [75][400/1281] lr: 1.268e-02, eta: 11:25:54, time: 0.293, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9975, loss_cls: 0.4140, loss: 0.4140 +2025-06-24 23:29:56,588 - pyskl - INFO - Epoch [75][500/1281] lr: 1.266e-02, eta: 11:25:16, time: 0.472, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9994, loss_cls: 0.4780, loss: 0.4780 +2025-06-24 23:30:28,949 - pyskl - INFO - Epoch [75][600/1281] lr: 1.264e-02, eta: 11:24:24, time: 0.324, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9981, loss_cls: 0.4055, loss: 0.4055 +2025-06-24 23:31:18,243 - pyskl - INFO - Epoch [75][700/1281] lr: 1.262e-02, eta: 11:23:48, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9988, loss_cls: 0.3637, loss: 0.3637 +2025-06-24 23:32:07,734 - pyskl - INFO - Epoch [75][800/1281] lr: 1.260e-02, eta: 11:23:13, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 1.0000, loss_cls: 0.3518, loss: 0.3518 +2025-06-24 23:32:57,052 - pyskl - INFO - Epoch [75][900/1281] lr: 1.258e-02, eta: 11:22:37, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9975, loss_cls: 0.3951, loss: 0.3951 +2025-06-24 23:33:45,816 - pyskl - INFO - Epoch [75][1000/1281] lr: 1.256e-02, eta: 11:22:01, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9981, loss_cls: 0.3811, loss: 0.3811 +2025-06-24 23:34:34,783 - pyskl - INFO - Epoch [75][1100/1281] lr: 1.254e-02, eta: 11:21:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9988, loss_cls: 0.4161, loss: 0.4161 +2025-06-24 23:35:23,646 - pyskl - INFO - Epoch [75][1200/1281] lr: 1.252e-02, eta: 11:20:49, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9981, loss_cls: 0.4312, loss: 0.4312 +2025-06-24 23:36:03,916 - pyskl - INFO - Saving checkpoint at 75 epochs +2025-06-24 23:37:02,525 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:37:02,592 - pyskl - INFO - +top1_acc 0.8767 +top5_acc 0.9930 +2025-06-24 23:37:02,592 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:37:02,601 - pyskl - INFO - +mean_acc 0.8332 +2025-06-24 23:37:02,603 - pyskl - INFO - Epoch(val) [75][533] top1_acc: 0.8767, top5_acc: 0.9930, mean_class_accuracy: 0.8332 +2025-06-24 23:38:22,331 - pyskl - INFO - Epoch [76][100/1281] lr: 1.248e-02, eta: 11:19:35, time: 0.797, data_time: 0.189, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9994, loss_cls: 0.3629, loss: 0.3629 +2025-06-24 23:39:11,506 - pyskl - INFO - Epoch [76][200/1281] lr: 1.246e-02, eta: 11:18:59, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9994, loss_cls: 0.3411, loss: 0.3411 +2025-06-24 23:40:01,028 - pyskl - INFO - Epoch [76][300/1281] lr: 1.244e-02, eta: 11:18:24, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9994, loss_cls: 0.3643, loss: 0.3643 +2025-06-24 23:40:29,656 - pyskl - INFO - Epoch [76][400/1281] lr: 1.242e-02, eta: 11:17:27, time: 0.286, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9962, loss_cls: 0.4496, loss: 0.4496 +2025-06-24 23:41:18,234 - pyskl - INFO - Epoch [76][500/1281] lr: 1.240e-02, eta: 11:16:51, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9994, loss_cls: 0.4023, loss: 0.4023 +2025-06-24 23:41:50,437 - pyskl - INFO - Epoch [76][600/1281] lr: 1.238e-02, eta: 11:15:58, time: 0.322, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9988, loss_cls: 0.4117, loss: 0.4117 +2025-06-24 23:42:39,493 - pyskl - INFO - Epoch [76][700/1281] lr: 1.236e-02, eta: 11:15:22, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9981, loss_cls: 0.3533, loss: 0.3533 +2025-06-24 23:43:28,325 - pyskl - INFO - Epoch [76][800/1281] lr: 1.234e-02, eta: 11:14:46, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9962, loss_cls: 0.4103, loss: 0.4103 +2025-06-24 23:44:17,297 - pyskl - INFO - Epoch [76][900/1281] lr: 1.232e-02, eta: 11:14:10, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9981, loss_cls: 0.4089, loss: 0.4089 +2025-06-24 23:45:06,593 - pyskl - INFO - Epoch [76][1000/1281] lr: 1.230e-02, eta: 11:13:34, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9988, loss_cls: 0.3921, loss: 0.3921 +2025-06-24 23:45:55,687 - pyskl - INFO - Epoch [76][1100/1281] lr: 1.228e-02, eta: 11:12:58, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9988, loss_cls: 0.4180, loss: 0.4180 +2025-06-24 23:46:44,904 - pyskl - INFO - Epoch [76][1200/1281] lr: 1.225e-02, eta: 11:12:22, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9962, loss_cls: 0.4287, loss: 0.4287 +2025-06-24 23:47:25,197 - pyskl - INFO - Saving checkpoint at 76 epochs +2025-06-24 23:48:23,303 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:48:23,357 - pyskl - INFO - +top1_acc 0.8668 +top5_acc 0.9914 +2025-06-24 23:48:23,357 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:48:23,364 - pyskl - INFO - +mean_acc 0.8338 +2025-06-24 23:48:23,366 - pyskl - INFO - Epoch(val) [76][533] top1_acc: 0.8668, top5_acc: 0.9914, mean_class_accuracy: 0.8338 +2025-06-24 23:49:42,059 - pyskl - INFO - Epoch [77][100/1281] lr: 1.222e-02, eta: 11:11:07, time: 0.787, data_time: 0.184, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9969, loss_cls: 0.3440, loss: 0.3440 +2025-06-24 23:50:31,113 - pyskl - INFO - Epoch [77][200/1281] lr: 1.220e-02, eta: 11:10:30, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9975, loss_cls: 0.3362, loss: 0.3362 +2025-06-24 23:51:20,227 - pyskl - INFO - Epoch [77][300/1281] lr: 1.218e-02, eta: 11:09:54, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 1.0000, loss_cls: 0.3627, loss: 0.3627 +2025-06-24 23:51:47,720 - pyskl - INFO - Epoch [77][400/1281] lr: 1.216e-02, eta: 11:08:57, time: 0.275, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9994, loss_cls: 0.3757, loss: 0.3757 +2025-06-24 23:52:38,549 - pyskl - INFO - Epoch [77][500/1281] lr: 1.214e-02, eta: 11:08:23, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9994, loss_cls: 0.3925, loss: 0.3925 +2025-06-24 23:53:06,454 - pyskl - INFO - Epoch [77][600/1281] lr: 1.212e-02, eta: 11:07:26, time: 0.279, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 0.3976, loss: 0.3976 +2025-06-24 23:53:55,479 - pyskl - INFO - Epoch [77][700/1281] lr: 1.210e-02, eta: 11:06:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9994, loss_cls: 0.4126, loss: 0.4126 +2025-06-24 23:54:45,087 - pyskl - INFO - Epoch [77][800/1281] lr: 1.207e-02, eta: 11:06:14, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9994, loss_cls: 0.4013, loss: 0.4013 +2025-06-24 23:55:34,544 - pyskl - INFO - Epoch [77][900/1281] lr: 1.205e-02, eta: 11:05:38, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9988, loss_cls: 0.3737, loss: 0.3737 +2025-06-24 23:56:23,727 - pyskl - INFO - Epoch [77][1000/1281] lr: 1.203e-02, eta: 11:05:02, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9988, loss_cls: 0.3933, loss: 0.3933 +2025-06-24 23:57:12,734 - pyskl - INFO - Epoch [77][1100/1281] lr: 1.201e-02, eta: 11:04:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 0.3871, loss: 0.3871 +2025-06-24 23:58:01,573 - pyskl - INFO - Epoch [77][1200/1281] lr: 1.199e-02, eta: 11:03:49, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9969, loss_cls: 0.4095, loss: 0.4095 +2025-06-24 23:58:42,042 - pyskl - INFO - Saving checkpoint at 77 epochs +2025-06-24 23:59:40,724 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:59:40,779 - pyskl - INFO - +top1_acc 0.8873 +top5_acc 0.9928 +2025-06-24 23:59:40,779 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:59:40,785 - pyskl - INFO - +mean_acc 0.8440 +2025-06-24 23:59:40,788 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_73.pth was removed +2025-06-24 23:59:40,966 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_77.pth. +2025-06-24 23:59:40,967 - pyskl - INFO - Best top1_acc is 0.8873 at 77 epoch. +2025-06-24 23:59:40,969 - pyskl - INFO - Epoch(val) [77][533] top1_acc: 0.8873, top5_acc: 0.9928, mean_class_accuracy: 0.8440 +2025-06-25 00:01:00,540 - pyskl - INFO - Epoch [78][100/1281] lr: 1.196e-02, eta: 11:02:34, time: 0.796, data_time: 0.186, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9994, loss_cls: 0.3105, loss: 0.3105 +2025-06-25 00:01:49,724 - pyskl - INFO - Epoch [78][200/1281] lr: 1.194e-02, eta: 11:01:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9981, loss_cls: 0.3415, loss: 0.3415 +2025-06-25 00:02:39,069 - pyskl - INFO - Epoch [78][300/1281] lr: 1.192e-02, eta: 11:01:22, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9975, loss_cls: 0.3428, loss: 0.3428 +2025-06-25 00:03:09,635 - pyskl - INFO - Epoch [78][400/1281] lr: 1.190e-02, eta: 11:00:28, time: 0.306, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9988, loss_cls: 0.3160, loss: 0.3160 +2025-06-25 00:04:00,761 - pyskl - INFO - Epoch [78][500/1281] lr: 1.187e-02, eta: 10:59:54, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9969, loss_cls: 0.3498, loss: 0.3498 +2025-06-25 00:04:27,520 - pyskl - INFO - Epoch [78][600/1281] lr: 1.185e-02, eta: 10:58:56, time: 0.268, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9981, loss_cls: 0.3899, loss: 0.3899 +2025-06-25 00:05:16,672 - pyskl - INFO - Epoch [78][700/1281] lr: 1.183e-02, eta: 10:58:20, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9994, loss_cls: 0.3479, loss: 0.3479 +2025-06-25 00:06:05,759 - pyskl - INFO - Epoch [78][800/1281] lr: 1.181e-02, eta: 10:57:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 0.3841, loss: 0.3841 +2025-06-25 00:06:54,737 - pyskl - INFO - Epoch [78][900/1281] lr: 1.179e-02, eta: 10:57:07, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9994, loss_cls: 0.3406, loss: 0.3406 +2025-06-25 00:07:43,600 - pyskl - INFO - Epoch [78][1000/1281] lr: 1.177e-02, eta: 10:56:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9975, loss_cls: 0.4295, loss: 0.4295 +2025-06-25 00:08:32,645 - pyskl - INFO - Epoch [78][1100/1281] lr: 1.175e-02, eta: 10:55:53, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9962, loss_cls: 0.3959, loss: 0.3959 +2025-06-25 00:09:21,556 - pyskl - INFO - Epoch [78][1200/1281] lr: 1.173e-02, eta: 10:55:17, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9981, loss_cls: 0.3751, loss: 0.3751 +2025-06-25 00:10:01,688 - pyskl - INFO - Saving checkpoint at 78 epochs +2025-06-25 00:11:00,234 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:11:00,289 - pyskl - INFO - +top1_acc 0.8856 +top5_acc 0.9927 +2025-06-25 00:11:00,289 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:11:00,296 - pyskl - INFO - +mean_acc 0.8430 +2025-06-25 00:11:00,298 - pyskl - INFO - Epoch(val) [78][533] top1_acc: 0.8856, top5_acc: 0.9927, mean_class_accuracy: 0.8430 +2025-06-25 00:12:20,616 - pyskl - INFO - Epoch [79][100/1281] lr: 1.169e-02, eta: 10:54:03, time: 0.803, data_time: 0.194, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9994, loss_cls: 0.3670, loss: 0.3670 +2025-06-25 00:13:09,752 - pyskl - INFO - Epoch [79][200/1281] lr: 1.167e-02, eta: 10:53:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 1.0000, loss_cls: 0.3601, loss: 0.3601 +2025-06-25 00:13:58,956 - pyskl - INFO - Epoch [79][300/1281] lr: 1.165e-02, eta: 10:52:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9981, loss_cls: 0.2939, loss: 0.2939 +2025-06-25 00:14:29,098 - pyskl - INFO - Epoch [79][400/1281] lr: 1.163e-02, eta: 10:51:55, time: 0.301, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 1.0000, loss_cls: 0.3229, loss: 0.3229 +2025-06-25 00:15:20,097 - pyskl - INFO - Epoch [79][500/1281] lr: 1.161e-02, eta: 10:51:20, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 1.0000, loss_cls: 0.3718, loss: 0.3718 +2025-06-25 00:15:46,491 - pyskl - INFO - Epoch [79][600/1281] lr: 1.159e-02, eta: 10:50:23, time: 0.264, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9994, loss_cls: 0.3422, loss: 0.3422 +2025-06-25 00:16:35,671 - pyskl - INFO - Epoch [79][700/1281] lr: 1.157e-02, eta: 10:49:46, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9981, loss_cls: 0.3118, loss: 0.3118 +2025-06-25 00:17:24,618 - pyskl - INFO - Epoch [79][800/1281] lr: 1.155e-02, eta: 10:49:10, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 0.3209, loss: 0.3209 +2025-06-25 00:18:13,526 - pyskl - INFO - Epoch [79][900/1281] lr: 1.153e-02, eta: 10:48:33, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9969, loss_cls: 0.4042, loss: 0.4042 +2025-06-25 00:19:02,654 - pyskl - INFO - Epoch [79][1000/1281] lr: 1.151e-02, eta: 10:47:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9994, loss_cls: 0.4076, loss: 0.4076 +2025-06-25 00:19:51,856 - pyskl - INFO - Epoch [79][1100/1281] lr: 1.149e-02, eta: 10:47:19, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.9350, top5_acc: 1.0000, loss_cls: 0.3509, loss: 0.3509 +2025-06-25 00:20:40,797 - pyskl - INFO - Epoch [79][1200/1281] lr: 1.147e-02, eta: 10:46:42, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9988, loss_cls: 0.3971, loss: 0.3971 +2025-06-25 00:21:20,957 - pyskl - INFO - Saving checkpoint at 79 epochs +2025-06-25 00:22:18,851 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:22:18,906 - pyskl - INFO - +top1_acc 0.8422 +top5_acc 0.9891 +2025-06-25 00:22:18,906 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:22:18,912 - pyskl - INFO - +mean_acc 0.8079 +2025-06-25 00:22:18,914 - pyskl - INFO - Epoch(val) [79][533] top1_acc: 0.8422, top5_acc: 0.9891, mean_class_accuracy: 0.8079 +2025-06-25 00:23:39,362 - pyskl - INFO - Epoch [80][100/1281] lr: 1.143e-02, eta: 10:45:28, time: 0.804, data_time: 0.188, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9988, loss_cls: 0.3493, loss: 0.3493 +2025-06-25 00:24:28,730 - pyskl - INFO - Epoch [80][200/1281] lr: 1.141e-02, eta: 10:44:52, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 1.0000, loss_cls: 0.3393, loss: 0.3393 +2025-06-25 00:25:17,737 - pyskl - INFO - Epoch [80][300/1281] lr: 1.139e-02, eta: 10:44:15, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9988, loss_cls: 0.3323, loss: 0.3323 +2025-06-25 00:25:50,030 - pyskl - INFO - Epoch [80][400/1281] lr: 1.137e-02, eta: 10:43:23, time: 0.323, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9988, loss_cls: 0.3125, loss: 0.3125 +2025-06-25 00:26:40,992 - pyskl - INFO - Epoch [80][500/1281] lr: 1.135e-02, eta: 10:42:48, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 1.0000, loss_cls: 0.3418, loss: 0.3418 +2025-06-25 00:27:06,040 - pyskl - INFO - Epoch [80][600/1281] lr: 1.133e-02, eta: 10:41:49, time: 0.250, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 0.3674, loss: 0.3674 +2025-06-25 00:27:53,390 - pyskl - INFO - Epoch [80][700/1281] lr: 1.131e-02, eta: 10:41:11, time: 0.473, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9994, loss_cls: 0.4228, loss: 0.4228 +2025-06-25 00:28:42,404 - pyskl - INFO - Epoch [80][800/1281] lr: 1.129e-02, eta: 10:40:34, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9988, loss_cls: 0.4190, loss: 0.4190 +2025-06-25 00:29:31,787 - pyskl - INFO - Epoch [80][900/1281] lr: 1.127e-02, eta: 10:39:57, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9981, loss_cls: 0.3962, loss: 0.3962 +2025-06-25 00:30:20,800 - pyskl - INFO - Epoch [80][1000/1281] lr: 1.125e-02, eta: 10:39:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9981, loss_cls: 0.2911, loss: 0.2911 +2025-06-25 00:31:09,502 - pyskl - INFO - Epoch [80][1100/1281] lr: 1.123e-02, eta: 10:38:43, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9994, loss_cls: 0.3603, loss: 0.3603 +2025-06-25 00:31:58,430 - pyskl - INFO - Epoch [80][1200/1281] lr: 1.121e-02, eta: 10:38:06, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9981, loss_cls: 0.3474, loss: 0.3474 +2025-06-25 00:32:39,024 - pyskl - INFO - Saving checkpoint at 80 epochs +2025-06-25 00:33:37,828 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:33:37,891 - pyskl - INFO - +top1_acc 0.8648 +top5_acc 0.9908 +2025-06-25 00:33:37,892 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:33:37,901 - pyskl - INFO - +mean_acc 0.8328 +2025-06-25 00:33:37,903 - pyskl - INFO - Epoch(val) [80][533] top1_acc: 0.8648, top5_acc: 0.9908, mean_class_accuracy: 0.8328 +2025-06-25 00:34:57,910 - pyskl - INFO - Epoch [81][100/1281] lr: 1.117e-02, eta: 10:36:51, time: 0.800, data_time: 0.189, memory: 4083, top1_acc: 0.9381, top5_acc: 1.0000, loss_cls: 0.3554, loss: 0.3554 +2025-06-25 00:35:47,125 - pyskl - INFO - Epoch [81][200/1281] lr: 1.115e-02, eta: 10:36:14, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 1.0000, loss_cls: 0.3077, loss: 0.3077 +2025-06-25 00:36:36,113 - pyskl - INFO - Epoch [81][300/1281] lr: 1.113e-02, eta: 10:35:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9981, loss_cls: 0.3997, loss: 0.3997 +2025-06-25 00:37:09,890 - pyskl - INFO - Epoch [81][400/1281] lr: 1.111e-02, eta: 10:34:46, time: 0.338, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 1.0000, loss_cls: 0.3043, loss: 0.3043 +2025-06-25 00:38:00,727 - pyskl - INFO - Epoch [81][500/1281] lr: 1.109e-02, eta: 10:34:11, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9969, loss_cls: 0.4025, loss: 0.4025 +2025-06-25 00:38:25,437 - pyskl - INFO - Epoch [81][600/1281] lr: 1.107e-02, eta: 10:33:13, time: 0.247, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 1.0000, loss_cls: 0.3565, loss: 0.3565 +2025-06-25 00:39:12,787 - pyskl - INFO - Epoch [81][700/1281] lr: 1.105e-02, eta: 10:32:34, time: 0.473, data_time: 0.001, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9981, loss_cls: 0.3368, loss: 0.3368 +2025-06-25 00:40:01,942 - pyskl - INFO - Epoch [81][800/1281] lr: 1.103e-02, eta: 10:31:57, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9981, loss_cls: 0.3664, loss: 0.3664 +2025-06-25 00:40:50,999 - pyskl - INFO - Epoch [81][900/1281] lr: 1.101e-02, eta: 10:31:20, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9969, loss_cls: 0.3617, loss: 0.3617 +2025-06-25 00:41:40,119 - pyskl - INFO - Epoch [81][1000/1281] lr: 1.099e-02, eta: 10:30:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9988, loss_cls: 0.4033, loss: 0.4033 +2025-06-25 00:42:29,221 - pyskl - INFO - Epoch [81][1100/1281] lr: 1.097e-02, eta: 10:30:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9975, loss_cls: 0.4167, loss: 0.4167 +2025-06-25 00:43:18,377 - pyskl - INFO - Epoch [81][1200/1281] lr: 1.095e-02, eta: 10:29:28, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9975, loss_cls: 0.4207, loss: 0.4207 +2025-06-25 00:43:58,543 - pyskl - INFO - Saving checkpoint at 81 epochs +2025-06-25 00:44:56,420 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:44:56,490 - pyskl - INFO - +top1_acc 0.8797 +top5_acc 0.9928 +2025-06-25 00:44:56,490 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:44:56,499 - pyskl - INFO - +mean_acc 0.8329 +2025-06-25 00:44:56,501 - pyskl - INFO - Epoch(val) [81][533] top1_acc: 0.8797, top5_acc: 0.9928, mean_class_accuracy: 0.8329 +2025-06-25 00:46:14,207 - pyskl - INFO - Epoch [82][100/1281] lr: 1.091e-02, eta: 10:28:11, time: 0.777, data_time: 0.182, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9994, loss_cls: 0.3414, loss: 0.3414 +2025-06-25 00:47:03,208 - pyskl - INFO - Epoch [82][200/1281] lr: 1.089e-02, eta: 10:27:34, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 1.0000, loss_cls: 0.3386, loss: 0.3386 +2025-06-25 00:47:52,352 - pyskl - INFO - Epoch [82][300/1281] lr: 1.087e-02, eta: 10:26:57, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 0.3115, loss: 0.3115 +2025-06-25 00:48:30,391 - pyskl - INFO - Epoch [82][400/1281] lr: 1.085e-02, eta: 10:26:10, time: 0.380, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9994, loss_cls: 0.2998, loss: 0.2998 +2025-06-25 00:49:21,523 - pyskl - INFO - Epoch [82][500/1281] lr: 1.083e-02, eta: 10:25:35, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.2794, loss: 0.2794 +2025-06-25 00:49:45,259 - pyskl - INFO - Epoch [82][600/1281] lr: 1.081e-02, eta: 10:24:36, time: 0.237, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 0.3031, loss: 0.3031 +2025-06-25 00:50:29,462 - pyskl - INFO - Epoch [82][700/1281] lr: 1.079e-02, eta: 10:23:55, time: 0.442, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9988, loss_cls: 0.3992, loss: 0.3992 +2025-06-25 00:51:18,856 - pyskl - INFO - Epoch [82][800/1281] lr: 1.077e-02, eta: 10:23:17, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3506, loss: 0.3506 +2025-06-25 00:52:07,871 - pyskl - INFO - Epoch [82][900/1281] lr: 1.075e-02, eta: 10:22:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9994, loss_cls: 0.3995, loss: 0.3995 +2025-06-25 00:52:56,845 - pyskl - INFO - Epoch [82][1000/1281] lr: 1.073e-02, eta: 10:22:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9981, loss_cls: 0.3585, loss: 0.3585 +2025-06-25 00:53:45,884 - pyskl - INFO - Epoch [82][1100/1281] lr: 1.071e-02, eta: 10:21:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9988, loss_cls: 0.3264, loss: 0.3264 +2025-06-25 00:54:34,877 - pyskl - INFO - Epoch [82][1200/1281] lr: 1.069e-02, eta: 10:20:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9975, loss_cls: 0.3658, loss: 0.3658 +2025-06-25 00:55:15,430 - pyskl - INFO - Saving checkpoint at 82 epochs +2025-06-25 00:56:13,415 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:56:13,471 - pyskl - INFO - +top1_acc 0.8843 +top5_acc 0.9926 +2025-06-25 00:56:13,471 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:56:13,478 - pyskl - INFO - +mean_acc 0.8508 +2025-06-25 00:56:13,480 - pyskl - INFO - Epoch(val) [82][533] top1_acc: 0.8843, top5_acc: 0.9926, mean_class_accuracy: 0.8508 +2025-06-25 00:57:33,736 - pyskl - INFO - Epoch [83][100/1281] lr: 1.065e-02, eta: 10:19:33, time: 0.803, data_time: 0.182, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9994, loss_cls: 0.2863, loss: 0.2863 +2025-06-25 00:58:23,067 - pyskl - INFO - Epoch [83][200/1281] lr: 1.063e-02, eta: 10:18:55, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9981, loss_cls: 0.3243, loss: 0.3243 +2025-06-25 00:59:12,225 - pyskl - INFO - Epoch [83][300/1281] lr: 1.061e-02, eta: 10:18:18, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 1.0000, loss_cls: 0.3182, loss: 0.3182 +2025-06-25 00:59:52,271 - pyskl - INFO - Epoch [83][400/1281] lr: 1.059e-02, eta: 10:17:33, time: 0.400, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 0.9994, loss_cls: 0.2701, loss: 0.2701 +2025-06-25 01:00:42,217 - pyskl - INFO - Epoch [83][500/1281] lr: 1.057e-02, eta: 10:16:56, time: 0.499, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 1.0000, loss_cls: 0.3334, loss: 0.3334 +2025-06-25 01:01:05,778 - pyskl - INFO - Epoch [83][600/1281] lr: 1.055e-02, eta: 10:15:58, time: 0.236, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9981, loss_cls: 0.2985, loss: 0.2985 +2025-06-25 01:01:49,458 - pyskl - INFO - Epoch [83][700/1281] lr: 1.053e-02, eta: 10:15:16, time: 0.437, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9994, loss_cls: 0.3759, loss: 0.3759 +2025-06-25 01:02:38,237 - pyskl - INFO - Epoch [83][800/1281] lr: 1.051e-02, eta: 10:14:38, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9994, loss_cls: 0.3470, loss: 0.3470 +2025-06-25 01:03:27,227 - pyskl - INFO - Epoch [83][900/1281] lr: 1.049e-02, eta: 10:14:00, time: 0.490, data_time: 0.001, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9962, loss_cls: 0.3735, loss: 0.3735 +2025-06-25 01:04:16,148 - pyskl - INFO - Epoch [83][1000/1281] lr: 1.047e-02, eta: 10:13:23, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9988, loss_cls: 0.3379, loss: 0.3379 +2025-06-25 01:05:05,564 - pyskl - INFO - Epoch [83][1100/1281] lr: 1.045e-02, eta: 10:12:45, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 0.2995, loss: 0.2995 +2025-06-25 01:05:54,227 - pyskl - INFO - Epoch [83][1200/1281] lr: 1.043e-02, eta: 10:12:07, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9994, loss_cls: 0.3757, loss: 0.3757 +2025-06-25 01:06:34,504 - pyskl - INFO - Saving checkpoint at 83 epochs +2025-06-25 01:07:32,207 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:07:32,261 - pyskl - INFO - +top1_acc 0.8859 +top5_acc 0.9912 +2025-06-25 01:07:32,261 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:07:32,267 - pyskl - INFO - +mean_acc 0.8593 +2025-06-25 01:07:32,269 - pyskl - INFO - Epoch(val) [83][533] top1_acc: 0.8859, top5_acc: 0.9912, mean_class_accuracy: 0.8593 +2025-06-25 01:08:51,949 - pyskl - INFO - Epoch [84][100/1281] lr: 1.040e-02, eta: 10:10:52, time: 0.797, data_time: 0.182, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.2771, loss: 0.2771 +2025-06-25 01:09:41,006 - pyskl - INFO - Epoch [84][200/1281] lr: 1.038e-02, eta: 10:10:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9988, loss_cls: 0.2680, loss: 0.2680 +2025-06-25 01:10:29,854 - pyskl - INFO - Epoch [84][300/1281] lr: 1.036e-02, eta: 10:09:36, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 1.0000, loss_cls: 0.2925, loss: 0.2925 +2025-06-25 01:11:10,373 - pyskl - INFO - Epoch [84][400/1281] lr: 1.034e-02, eta: 10:08:52, time: 0.405, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9994, loss_cls: 0.2904, loss: 0.2904 +2025-06-25 01:11:59,793 - pyskl - INFO - Epoch [84][500/1281] lr: 1.031e-02, eta: 10:08:14, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9981, loss_cls: 0.3201, loss: 0.3201 +2025-06-25 01:12:24,167 - pyskl - INFO - Epoch [84][600/1281] lr: 1.029e-02, eta: 10:07:17, time: 0.244, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9975, loss_cls: 0.3719, loss: 0.3719 +2025-06-25 01:13:06,364 - pyskl - INFO - Epoch [84][700/1281] lr: 1.027e-02, eta: 10:06:34, time: 0.422, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9981, loss_cls: 0.3296, loss: 0.3296 +2025-06-25 01:13:54,804 - pyskl - INFO - Epoch [84][800/1281] lr: 1.025e-02, eta: 10:05:55, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9981, loss_cls: 0.3581, loss: 0.3581 +2025-06-25 01:14:43,634 - pyskl - INFO - Epoch [84][900/1281] lr: 1.023e-02, eta: 10:05:17, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9994, loss_cls: 0.3283, loss: 0.3283 +2025-06-25 01:15:32,634 - pyskl - INFO - Epoch [84][1000/1281] lr: 1.021e-02, eta: 10:04:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9988, loss_cls: 0.3585, loss: 0.3585 +2025-06-25 01:16:21,492 - pyskl - INFO - Epoch [84][1100/1281] lr: 1.019e-02, eta: 10:04:02, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9994, loss_cls: 0.3546, loss: 0.3546 +2025-06-25 01:17:10,421 - pyskl - INFO - Epoch [84][1200/1281] lr: 1.017e-02, eta: 10:03:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9981, loss_cls: 0.3918, loss: 0.3918 +2025-06-25 01:17:50,881 - pyskl - INFO - Saving checkpoint at 84 epochs +2025-06-25 01:18:48,421 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:18:48,479 - pyskl - INFO - +top1_acc 0.8764 +top5_acc 0.9919 +2025-06-25 01:18:48,479 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:18:48,488 - pyskl - INFO - +mean_acc 0.8455 +2025-06-25 01:18:48,490 - pyskl - INFO - Epoch(val) [84][533] top1_acc: 0.8764, top5_acc: 0.9919, mean_class_accuracy: 0.8455 +2025-06-25 01:20:07,134 - pyskl - INFO - Epoch [85][100/1281] lr: 1.014e-02, eta: 10:02:07, time: 0.786, data_time: 0.184, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.2823, loss: 0.2823 +2025-06-25 01:20:56,368 - pyskl - INFO - Epoch [85][200/1281] lr: 1.012e-02, eta: 10:01:30, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9994, loss_cls: 0.2978, loss: 0.2978 +2025-06-25 01:21:45,663 - pyskl - INFO - Epoch [85][300/1281] lr: 1.010e-02, eta: 10:00:52, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 1.0000, loss_cls: 0.2787, loss: 0.2787 +2025-06-25 01:22:28,733 - pyskl - INFO - Epoch [85][400/1281] lr: 1.008e-02, eta: 10:00:09, time: 0.431, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 0.2980, loss: 0.2980 +2025-06-25 01:23:13,032 - pyskl - INFO - Epoch [85][500/1281] lr: 1.006e-02, eta: 9:59:28, time: 0.443, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9994, loss_cls: 0.3529, loss: 0.3529 +2025-06-25 01:23:41,659 - pyskl - INFO - Epoch [85][600/1281] lr: 1.004e-02, eta: 9:58:34, time: 0.286, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9988, loss_cls: 0.2760, loss: 0.2760 +2025-06-25 01:24:22,691 - pyskl - INFO - Epoch [85][700/1281] lr: 1.002e-02, eta: 9:57:50, time: 0.410, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 1.0000, loss_cls: 0.3570, loss: 0.3570 +2025-06-25 01:25:11,540 - pyskl - INFO - Epoch [85][800/1281] lr: 9.998e-03, eta: 9:57:12, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9975, loss_cls: 0.3414, loss: 0.3414 +2025-06-25 01:26:00,262 - pyskl - INFO - Epoch [85][900/1281] lr: 9.978e-03, eta: 9:56:33, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9988, loss_cls: 0.3310, loss: 0.3310 +2025-06-25 01:26:49,451 - pyskl - INFO - Epoch [85][1000/1281] lr: 9.958e-03, eta: 9:55:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 0.3282, loss: 0.3282 +2025-06-25 01:27:38,342 - pyskl - INFO - Epoch [85][1100/1281] lr: 9.937e-03, eta: 9:55:17, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9994, loss_cls: 0.3143, loss: 0.3143 +2025-06-25 01:28:27,627 - pyskl - INFO - Epoch [85][1200/1281] lr: 9.917e-03, eta: 9:54:40, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 0.2978, loss: 0.2978 +2025-06-25 01:29:07,622 - pyskl - INFO - Saving checkpoint at 85 epochs +2025-06-25 01:30:05,613 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:30:05,677 - pyskl - INFO - +top1_acc 0.8803 +top5_acc 0.9930 +2025-06-25 01:30:05,677 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:30:05,686 - pyskl - INFO - +mean_acc 0.8376 +2025-06-25 01:30:05,690 - pyskl - INFO - Epoch(val) [85][533] top1_acc: 0.8803, top5_acc: 0.9930, mean_class_accuracy: 0.8376 +2025-06-25 01:31:25,320 - pyskl - INFO - Epoch [86][100/1281] lr: 9.881e-03, eta: 9:53:24, time: 0.796, data_time: 0.184, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2429, loss: 0.2429 +2025-06-25 01:32:14,059 - pyskl - INFO - Epoch [86][200/1281] lr: 9.861e-03, eta: 9:52:45, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 1.0000, loss_cls: 0.2957, loss: 0.2957 +2025-06-25 01:33:03,287 - pyskl - INFO - Epoch [86][300/1281] lr: 9.841e-03, eta: 9:52:07, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2623, loss: 0.2623 +2025-06-25 01:33:47,076 - pyskl - INFO - Epoch [86][400/1281] lr: 9.821e-03, eta: 9:51:25, time: 0.438, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 0.2789, loss: 0.2789 +2025-06-25 01:34:28,542 - pyskl - INFO - Epoch [86][500/1281] lr: 9.801e-03, eta: 9:50:42, time: 0.415, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 0.9994, loss_cls: 0.2737, loss: 0.2737 +2025-06-25 01:34:59,985 - pyskl - INFO - Epoch [86][600/1281] lr: 9.781e-03, eta: 9:49:50, time: 0.314, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 0.2551, loss: 0.2551 +2025-06-25 01:35:41,116 - pyskl - INFO - Epoch [86][700/1281] lr: 9.762e-03, eta: 9:49:06, time: 0.411, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9988, loss_cls: 0.3402, loss: 0.3402 +2025-06-25 01:36:30,314 - pyskl - INFO - Epoch [86][800/1281] lr: 9.742e-03, eta: 9:48:28, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9969, loss_cls: 0.3594, loss: 0.3594 +2025-06-25 01:37:19,345 - pyskl - INFO - Epoch [86][900/1281] lr: 9.722e-03, eta: 9:47:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9975, loss_cls: 0.3847, loss: 0.3847 +2025-06-25 01:38:08,183 - pyskl - INFO - Epoch [86][1000/1281] lr: 9.702e-03, eta: 9:47:12, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9994, loss_cls: 0.3573, loss: 0.3573 +2025-06-25 01:38:57,427 - pyskl - INFO - Epoch [86][1100/1281] lr: 9.682e-03, eta: 9:46:33, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 0.2691, loss: 0.2691 +2025-06-25 01:39:46,093 - pyskl - INFO - Epoch [86][1200/1281] lr: 9.662e-03, eta: 9:45:55, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 0.3026, loss: 0.3026 +2025-06-25 01:40:26,255 - pyskl - INFO - Saving checkpoint at 86 epochs +2025-06-25 01:41:24,147 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:41:24,204 - pyskl - INFO - +top1_acc 0.8669 +top5_acc 0.9918 +2025-06-25 01:41:24,204 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:41:24,211 - pyskl - INFO - +mean_acc 0.8130 +2025-06-25 01:41:24,213 - pyskl - INFO - Epoch(val) [86][533] top1_acc: 0.8669, top5_acc: 0.9918, mean_class_accuracy: 0.8130 +2025-06-25 01:42:43,604 - pyskl - INFO - Epoch [87][100/1281] lr: 9.626e-03, eta: 9:44:39, time: 0.794, data_time: 0.187, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9994, loss_cls: 0.3510, loss: 0.3510 +2025-06-25 01:43:33,031 - pyskl - INFO - Epoch [87][200/1281] lr: 9.606e-03, eta: 9:44:01, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 1.0000, loss_cls: 0.2878, loss: 0.2878 +2025-06-25 01:44:21,846 - pyskl - INFO - Epoch [87][300/1281] lr: 9.586e-03, eta: 9:43:22, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 0.2986, loss: 0.2986 +2025-06-25 01:45:06,415 - pyskl - INFO - Epoch [87][400/1281] lr: 9.566e-03, eta: 9:42:41, time: 0.446, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2597, loss: 0.2597 +2025-06-25 01:45:48,440 - pyskl - INFO - Epoch [87][500/1281] lr: 9.546e-03, eta: 9:41:57, time: 0.420, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 0.2645, loss: 0.2645 +2025-06-25 01:46:19,417 - pyskl - INFO - Epoch [87][600/1281] lr: 9.527e-03, eta: 9:41:06, time: 0.310, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 0.2878, loss: 0.2878 +2025-06-25 01:47:00,068 - pyskl - INFO - Epoch [87][700/1281] lr: 9.507e-03, eta: 9:40:21, time: 0.407, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9994, loss_cls: 0.3106, loss: 0.3106 +2025-06-25 01:47:49,023 - pyskl - INFO - Epoch [87][800/1281] lr: 9.487e-03, eta: 9:39:43, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9981, loss_cls: 0.2702, loss: 0.2702 +2025-06-25 01:48:37,805 - pyskl - INFO - Epoch [87][900/1281] lr: 9.467e-03, eta: 9:39:04, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 1.0000, loss_cls: 0.3117, loss: 0.3117 +2025-06-25 01:49:26,829 - pyskl - INFO - Epoch [87][1000/1281] lr: 9.447e-03, eta: 9:38:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2613, loss: 0.2613 +2025-06-25 01:50:15,647 - pyskl - INFO - Epoch [87][1100/1281] lr: 9.427e-03, eta: 9:37:48, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9994, loss_cls: 0.3099, loss: 0.3099 +2025-06-25 01:51:04,475 - pyskl - INFO - Epoch [87][1200/1281] lr: 9.408e-03, eta: 9:37:09, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9988, loss_cls: 0.3472, loss: 0.3472 +2025-06-25 01:51:44,723 - pyskl - INFO - Saving checkpoint at 87 epochs +2025-06-25 01:52:42,205 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:52:42,272 - pyskl - INFO - +top1_acc 0.8676 +top5_acc 0.9930 +2025-06-25 01:52:42,272 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:52:42,280 - pyskl - INFO - +mean_acc 0.8221 +2025-06-25 01:52:42,282 - pyskl - INFO - Epoch(val) [87][533] top1_acc: 0.8676, top5_acc: 0.9930, mean_class_accuracy: 0.8221 +2025-06-25 01:54:02,815 - pyskl - INFO - Epoch [88][100/1281] lr: 9.372e-03, eta: 9:35:54, time: 0.805, data_time: 0.185, memory: 4083, top1_acc: 0.9450, top5_acc: 1.0000, loss_cls: 0.2864, loss: 0.2864 +2025-06-25 01:54:51,768 - pyskl - INFO - Epoch [88][200/1281] lr: 9.352e-03, eta: 9:35:15, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9988, loss_cls: 0.3197, loss: 0.3197 +2025-06-25 01:55:40,828 - pyskl - INFO - Epoch [88][300/1281] lr: 9.332e-03, eta: 9:34:37, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 0.2876, loss: 0.2876 +2025-06-25 01:56:24,964 - pyskl - INFO - Epoch [88][400/1281] lr: 9.312e-03, eta: 9:33:55, time: 0.441, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 1.0000, loss_cls: 0.2909, loss: 0.2909 +2025-06-25 01:57:06,684 - pyskl - INFO - Epoch [88][500/1281] lr: 9.293e-03, eta: 9:33:11, time: 0.417, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9988, loss_cls: 0.3514, loss: 0.3514 +2025-06-25 01:57:38,385 - pyskl - INFO - Epoch [88][600/1281] lr: 9.273e-03, eta: 9:32:20, time: 0.317, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 1.0000, loss_cls: 0.3649, loss: 0.3649 +2025-06-25 01:58:18,821 - pyskl - INFO - Epoch [88][700/1281] lr: 9.253e-03, eta: 9:31:36, time: 0.404, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 1.0000, loss_cls: 0.3004, loss: 0.3004 +2025-06-25 01:59:07,673 - pyskl - INFO - Epoch [88][800/1281] lr: 9.233e-03, eta: 9:30:57, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 0.9988, loss_cls: 0.2638, loss: 0.2638 +2025-06-25 01:59:56,597 - pyskl - INFO - Epoch [88][900/1281] lr: 9.214e-03, eta: 9:30:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 0.3055, loss: 0.3055 +2025-06-25 02:00:45,388 - pyskl - INFO - Epoch [88][1000/1281] lr: 9.194e-03, eta: 9:29:40, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9988, loss_cls: 0.3156, loss: 0.3156 +2025-06-25 02:01:34,200 - pyskl - INFO - Epoch [88][1100/1281] lr: 9.174e-03, eta: 9:29:01, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 0.3052, loss: 0.3052 +2025-06-25 02:02:22,994 - pyskl - INFO - Epoch [88][1200/1281] lr: 9.155e-03, eta: 9:28:22, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9994, loss_cls: 0.3479, loss: 0.3479 +2025-06-25 02:03:03,038 - pyskl - INFO - Saving checkpoint at 88 epochs +2025-06-25 02:04:00,086 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:04:00,140 - pyskl - INFO - +top1_acc 0.8871 +top5_acc 0.9927 +2025-06-25 02:04:00,140 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:04:00,146 - pyskl - INFO - +mean_acc 0.8517 +2025-06-25 02:04:00,147 - pyskl - INFO - Epoch(val) [88][533] top1_acc: 0.8871, top5_acc: 0.9927, mean_class_accuracy: 0.8517 +2025-06-25 02:05:20,059 - pyskl - INFO - Epoch [89][100/1281] lr: 9.119e-03, eta: 9:27:06, time: 0.799, data_time: 0.188, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9994, loss_cls: 0.2800, loss: 0.2800 +2025-06-25 02:06:09,430 - pyskl - INFO - Epoch [89][200/1281] lr: 9.099e-03, eta: 9:26:28, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 1.0000, loss_cls: 0.2574, loss: 0.2574 +2025-06-25 02:06:58,302 - pyskl - INFO - Epoch [89][300/1281] lr: 9.080e-03, eta: 9:25:49, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 1.0000, loss_cls: 0.2989, loss: 0.2989 +2025-06-25 02:07:43,808 - pyskl - INFO - Epoch [89][400/1281] lr: 9.060e-03, eta: 9:25:08, time: 0.455, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9981, loss_cls: 0.2936, loss: 0.2936 +2025-06-25 02:08:24,338 - pyskl - INFO - Epoch [89][500/1281] lr: 9.040e-03, eta: 9:24:23, time: 0.405, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9994, loss_cls: 0.3079, loss: 0.3079 +2025-06-25 02:08:56,721 - pyskl - INFO - Epoch [89][600/1281] lr: 9.021e-03, eta: 9:23:33, time: 0.324, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9988, loss_cls: 0.2584, loss: 0.2584 +2025-06-25 02:09:36,315 - pyskl - INFO - Epoch [89][700/1281] lr: 9.001e-03, eta: 9:22:48, time: 0.396, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 1.0000, loss_cls: 0.2823, loss: 0.2823 +2025-06-25 02:10:25,324 - pyskl - INFO - Epoch [89][800/1281] lr: 8.982e-03, eta: 9:22:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 0.2850, loss: 0.2850 +2025-06-25 02:11:14,520 - pyskl - INFO - Epoch [89][900/1281] lr: 8.962e-03, eta: 9:21:31, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 1.0000, loss_cls: 0.2989, loss: 0.2989 +2025-06-25 02:12:03,448 - pyskl - INFO - Epoch [89][1000/1281] lr: 8.942e-03, eta: 9:20:52, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 1.0000, loss_cls: 0.3018, loss: 0.3018 +2025-06-25 02:12:52,542 - pyskl - INFO - Epoch [89][1100/1281] lr: 8.923e-03, eta: 9:20:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9994, loss_cls: 0.3351, loss: 0.3351 +2025-06-25 02:13:41,722 - pyskl - INFO - Epoch [89][1200/1281] lr: 8.903e-03, eta: 9:19:35, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9994, loss_cls: 0.3066, loss: 0.3066 +2025-06-25 02:14:21,964 - pyskl - INFO - Saving checkpoint at 89 epochs +2025-06-25 02:15:18,968 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:15:19,024 - pyskl - INFO - +top1_acc 0.8899 +top5_acc 0.9927 +2025-06-25 02:15:19,024 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:15:19,030 - pyskl - INFO - +mean_acc 0.8518 +2025-06-25 02:15:19,034 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_77.pth was removed +2025-06-25 02:15:19,197 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_89.pth. +2025-06-25 02:15:19,198 - pyskl - INFO - Best top1_acc is 0.8899 at 89 epoch. +2025-06-25 02:15:19,201 - pyskl - INFO - Epoch(val) [89][533] top1_acc: 0.8899, top5_acc: 0.9927, mean_class_accuracy: 0.8518 +2025-06-25 02:16:38,356 - pyskl - INFO - Epoch [90][100/1281] lr: 8.868e-03, eta: 9:18:18, time: 0.792, data_time: 0.188, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9988, loss_cls: 0.3083, loss: 0.3083 +2025-06-25 02:17:27,329 - pyskl - INFO - Epoch [90][200/1281] lr: 8.848e-03, eta: 9:17:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 0.2720, loss: 0.2720 +2025-06-25 02:18:16,197 - pyskl - INFO - Epoch [90][300/1281] lr: 8.829e-03, eta: 9:17:00, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2497, loss: 0.2497 +2025-06-25 02:19:03,135 - pyskl - INFO - Epoch [90][400/1281] lr: 8.809e-03, eta: 9:16:20, time: 0.469, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 1.0000, loss_cls: 0.2498, loss: 0.2498 +2025-06-25 02:19:38,536 - pyskl - INFO - Epoch [90][500/1281] lr: 8.790e-03, eta: 9:15:32, time: 0.354, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 0.2923, loss: 0.2923 +2025-06-25 02:20:16,128 - pyskl - INFO - Epoch [90][600/1281] lr: 8.770e-03, eta: 9:14:46, time: 0.376, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 0.2525, loss: 0.2525 +2025-06-25 02:20:52,573 - pyskl - INFO - Epoch [90][700/1281] lr: 8.751e-03, eta: 9:13:58, time: 0.364, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2531, loss: 0.2531 +2025-06-25 02:21:41,262 - pyskl - INFO - Epoch [90][800/1281] lr: 8.731e-03, eta: 9:13:19, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 1.0000, loss_cls: 0.2871, loss: 0.2871 +2025-06-25 02:22:30,443 - pyskl - INFO - Epoch [90][900/1281] lr: 8.712e-03, eta: 9:12:41, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9988, loss_cls: 0.3523, loss: 0.3523 +2025-06-25 02:23:18,712 - pyskl - INFO - Epoch [90][1000/1281] lr: 8.692e-03, eta: 9:12:01, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2663, loss: 0.2663 +2025-06-25 02:24:07,417 - pyskl - INFO - Epoch [90][1100/1281] lr: 8.673e-03, eta: 9:11:22, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9988, loss_cls: 0.3206, loss: 0.3206 +2025-06-25 02:24:56,490 - pyskl - INFO - Epoch [90][1200/1281] lr: 8.653e-03, eta: 9:10:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 0.3285, loss: 0.3285 +2025-06-25 02:25:36,571 - pyskl - INFO - Saving checkpoint at 90 epochs +2025-06-25 02:26:34,523 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:26:34,597 - pyskl - INFO - +top1_acc 0.8886 +top5_acc 0.9927 +2025-06-25 02:26:34,597 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:26:34,604 - pyskl - INFO - +mean_acc 0.8509 +2025-06-25 02:26:34,606 - pyskl - INFO - Epoch(val) [90][533] top1_acc: 0.8886, top5_acc: 0.9927, mean_class_accuracy: 0.8509 +2025-06-25 02:27:54,514 - pyskl - INFO - Epoch [91][100/1281] lr: 8.618e-03, eta: 9:09:27, time: 0.799, data_time: 0.184, memory: 4083, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 0.2582, loss: 0.2582 +2025-06-25 02:28:43,519 - pyskl - INFO - Epoch [91][200/1281] lr: 8.599e-03, eta: 9:08:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9981, loss_cls: 0.2779, loss: 0.2779 +2025-06-25 02:29:32,498 - pyskl - INFO - Epoch [91][300/1281] lr: 8.579e-03, eta: 9:08:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9988, loss_cls: 0.2783, loss: 0.2783 +2025-06-25 02:30:21,369 - pyskl - INFO - Epoch [91][400/1281] lr: 8.560e-03, eta: 9:07:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 0.2936, loss: 0.2936 +2025-06-25 02:30:52,048 - pyskl - INFO - Epoch [91][500/1281] lr: 8.540e-03, eta: 9:06:39, time: 0.307, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9988, loss_cls: 0.3279, loss: 0.3279 +2025-06-25 02:31:34,692 - pyskl - INFO - Epoch [91][600/1281] lr: 8.521e-03, eta: 9:05:56, time: 0.426, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 0.9994, loss_cls: 0.2733, loss: 0.2733 +2025-06-25 02:32:08,951 - pyskl - INFO - Epoch [91][700/1281] lr: 8.502e-03, eta: 9:05:07, time: 0.343, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2750, loss: 0.2750 +2025-06-25 02:32:58,056 - pyskl - INFO - Epoch [91][800/1281] lr: 8.482e-03, eta: 9:04:28, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 0.2664, loss: 0.2664 +2025-06-25 02:33:47,349 - pyskl - INFO - Epoch [91][900/1281] lr: 8.463e-03, eta: 9:03:49, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 0.2696, loss: 0.2696 +2025-06-25 02:34:36,000 - pyskl - INFO - Epoch [91][1000/1281] lr: 8.444e-03, eta: 9:03:10, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 0.2898, loss: 0.2898 +2025-06-25 02:35:24,553 - pyskl - INFO - Epoch [91][1100/1281] lr: 8.424e-03, eta: 9:02:31, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.2811, loss: 0.2811 +2025-06-25 02:36:13,226 - pyskl - INFO - Epoch [91][1200/1281] lr: 8.405e-03, eta: 9:01:52, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 0.2793, loss: 0.2793 +2025-06-25 02:36:52,715 - pyskl - INFO - Saving checkpoint at 91 epochs +2025-06-25 02:37:50,183 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:37:50,238 - pyskl - INFO - +top1_acc 0.9034 +top5_acc 0.9939 +2025-06-25 02:37:50,238 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:37:50,244 - pyskl - INFO - +mean_acc 0.8737 +2025-06-25 02:37:50,248 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_89.pth was removed +2025-06-25 02:37:50,416 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_91.pth. +2025-06-25 02:37:50,417 - pyskl - INFO - Best top1_acc is 0.9034 at 91 epoch. +2025-06-25 02:37:50,420 - pyskl - INFO - Epoch(val) [91][533] top1_acc: 0.9034, top5_acc: 0.9939, mean_class_accuracy: 0.8737 +2025-06-25 02:39:10,432 - pyskl - INFO - Epoch [92][100/1281] lr: 8.370e-03, eta: 9:00:35, time: 0.800, data_time: 0.184, memory: 4083, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 0.1910, loss: 0.1910 +2025-06-25 02:39:59,281 - pyskl - INFO - Epoch [92][200/1281] lr: 8.351e-03, eta: 8:59:56, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 0.9994, loss_cls: 0.2096, loss: 0.2096 +2025-06-25 02:40:48,194 - pyskl - INFO - Epoch [92][300/1281] lr: 8.332e-03, eta: 8:59:17, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 0.2676, loss: 0.2676 +2025-06-25 02:41:37,415 - pyskl - INFO - Epoch [92][400/1281] lr: 8.312e-03, eta: 8:58:38, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2484, loss: 0.2484 +2025-06-25 02:42:05,590 - pyskl - INFO - Epoch [92][500/1281] lr: 8.293e-03, eta: 8:57:45, time: 0.282, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 0.9994, loss_cls: 0.2788, loss: 0.2788 +2025-06-25 02:42:53,325 - pyskl - INFO - Epoch [92][600/1281] lr: 8.274e-03, eta: 8:57:06, time: 0.477, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9981, loss_cls: 0.2577, loss: 0.2577 +2025-06-25 02:43:26,102 - pyskl - INFO - Epoch [92][700/1281] lr: 8.255e-03, eta: 8:56:16, time: 0.328, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 0.2292, loss: 0.2292 +2025-06-25 02:44:14,918 - pyskl - INFO - Epoch [92][800/1281] lr: 8.235e-03, eta: 8:55:37, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9988, loss_cls: 0.2759, loss: 0.2759 +2025-06-25 02:45:04,080 - pyskl - INFO - Epoch [92][900/1281] lr: 8.216e-03, eta: 8:54:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 0.2484, loss: 0.2484 +2025-06-25 02:45:52,865 - pyskl - INFO - Epoch [92][1000/1281] lr: 8.197e-03, eta: 8:54:18, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9988, loss_cls: 0.3298, loss: 0.3298 +2025-06-25 02:46:41,861 - pyskl - INFO - Epoch [92][1100/1281] lr: 8.178e-03, eta: 8:53:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9994, loss_cls: 0.3380, loss: 0.3380 +2025-06-25 02:47:30,681 - pyskl - INFO - Epoch [92][1200/1281] lr: 8.159e-03, eta: 8:53:00, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 1.0000, loss_cls: 0.2963, loss: 0.2963 +2025-06-25 02:48:10,872 - pyskl - INFO - Saving checkpoint at 92 epochs +2025-06-25 02:49:08,288 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:49:08,343 - pyskl - INFO - +top1_acc 0.8841 +top5_acc 0.9925 +2025-06-25 02:49:08,343 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:49:08,350 - pyskl - INFO - +mean_acc 0.8346 +2025-06-25 02:49:08,352 - pyskl - INFO - Epoch(val) [92][533] top1_acc: 0.8841, top5_acc: 0.9925, mean_class_accuracy: 0.8346 +2025-06-25 02:50:27,434 - pyskl - INFO - Epoch [93][100/1281] lr: 8.124e-03, eta: 8:51:43, time: 0.791, data_time: 0.186, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.2877, loss: 0.2877 +2025-06-25 02:51:16,536 - pyskl - INFO - Epoch [93][200/1281] lr: 8.105e-03, eta: 8:51:04, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 0.2863, loss: 0.2863 +2025-06-25 02:52:05,660 - pyskl - INFO - Epoch [93][300/1281] lr: 8.086e-03, eta: 8:50:25, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9988, loss_cls: 0.2664, loss: 0.2664 +2025-06-25 02:52:54,428 - pyskl - INFO - Epoch [93][400/1281] lr: 8.067e-03, eta: 8:49:45, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2337, loss: 0.2337 +2025-06-25 02:53:21,632 - pyskl - INFO - Epoch [93][500/1281] lr: 8.047e-03, eta: 8:48:52, time: 0.272, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9988, loss_cls: 0.2662, loss: 0.2662 +2025-06-25 02:54:12,269 - pyskl - INFO - Epoch [93][600/1281] lr: 8.028e-03, eta: 8:48:14, time: 0.506, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2501, loss: 0.2501 +2025-06-25 02:54:42,491 - pyskl - INFO - Epoch [93][700/1281] lr: 8.009e-03, eta: 8:47:23, time: 0.302, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 0.2158, loss: 0.2158 +2025-06-25 02:55:31,445 - pyskl - INFO - Epoch [93][800/1281] lr: 7.990e-03, eta: 8:46:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9988, loss_cls: 0.2731, loss: 0.2731 +2025-06-25 02:56:20,346 - pyskl - INFO - Epoch [93][900/1281] lr: 7.971e-03, eta: 8:46:04, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9988, loss_cls: 0.2525, loss: 0.2525 +2025-06-25 02:57:08,667 - pyskl - INFO - Epoch [93][1000/1281] lr: 7.952e-03, eta: 8:45:25, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9988, loss_cls: 0.2379, loss: 0.2379 +2025-06-25 02:57:57,716 - pyskl - INFO - Epoch [93][1100/1281] lr: 7.933e-03, eta: 8:44:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 0.2458, loss: 0.2458 +2025-06-25 02:58:46,473 - pyskl - INFO - Epoch [93][1200/1281] lr: 7.914e-03, eta: 8:44:06, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9994, loss_cls: 0.2655, loss: 0.2655 +2025-06-25 02:59:26,618 - pyskl - INFO - Saving checkpoint at 93 epochs +2025-06-25 03:00:24,555 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:00:24,612 - pyskl - INFO - +top1_acc 0.8950 +top5_acc 0.9912 +2025-06-25 03:00:24,613 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:00:24,619 - pyskl - INFO - +mean_acc 0.8645 +2025-06-25 03:00:24,620 - pyskl - INFO - Epoch(val) [93][533] top1_acc: 0.8950, top5_acc: 0.9912, mean_class_accuracy: 0.8645 +2025-06-25 03:01:44,383 - pyskl - INFO - Epoch [94][100/1281] lr: 7.880e-03, eta: 8:42:49, time: 0.798, data_time: 0.183, memory: 4083, top1_acc: 0.9600, top5_acc: 0.9988, loss_cls: 0.2454, loss: 0.2454 +2025-06-25 03:02:33,674 - pyskl - INFO - Epoch [94][200/1281] lr: 7.861e-03, eta: 8:42:10, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9994, loss_cls: 0.2548, loss: 0.2548 +2025-06-25 03:03:22,873 - pyskl - INFO - Epoch [94][300/1281] lr: 7.842e-03, eta: 8:41:31, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1963, loss: 0.1963 +2025-06-25 03:04:11,517 - pyskl - INFO - Epoch [94][400/1281] lr: 7.823e-03, eta: 8:40:51, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9988, loss_cls: 0.2687, loss: 0.2687 +2025-06-25 03:04:40,236 - pyskl - INFO - Epoch [94][500/1281] lr: 7.804e-03, eta: 8:39:59, time: 0.287, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 0.2908, loss: 0.2908 +2025-06-25 03:05:31,076 - pyskl - INFO - Epoch [94][600/1281] lr: 7.785e-03, eta: 8:39:21, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9988, loss_cls: 0.2510, loss: 0.2510 +2025-06-25 03:06:00,408 - pyskl - INFO - Epoch [94][700/1281] lr: 7.766e-03, eta: 8:38:30, time: 0.293, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2491, loss: 0.2491 +2025-06-25 03:06:49,512 - pyskl - INFO - Epoch [94][800/1281] lr: 7.747e-03, eta: 8:37:50, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 0.2358, loss: 0.2358 +2025-06-25 03:07:38,051 - pyskl - INFO - Epoch [94][900/1281] lr: 7.728e-03, eta: 8:37:11, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 0.9994, loss_cls: 0.1893, loss: 0.1893 +2025-06-25 03:08:27,266 - pyskl - INFO - Epoch [94][1000/1281] lr: 7.709e-03, eta: 8:36:31, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.2740, loss: 0.2740 +2025-06-25 03:09:16,038 - pyskl - INFO - Epoch [94][1100/1281] lr: 7.690e-03, eta: 8:35:52, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 0.2842, loss: 0.2842 +2025-06-25 03:10:05,087 - pyskl - INFO - Epoch [94][1200/1281] lr: 7.672e-03, eta: 8:35:12, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9994, loss_cls: 0.3101, loss: 0.3101 +2025-06-25 03:10:45,466 - pyskl - INFO - Saving checkpoint at 94 epochs +2025-06-25 03:11:42,925 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:11:42,980 - pyskl - INFO - +top1_acc 0.8997 +top5_acc 0.9946 +2025-06-25 03:11:42,980 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:11:42,987 - pyskl - INFO - +mean_acc 0.8621 +2025-06-25 03:11:42,989 - pyskl - INFO - Epoch(val) [94][533] top1_acc: 0.8997, top5_acc: 0.9946, mean_class_accuracy: 0.8621 +2025-06-25 03:13:03,077 - pyskl - INFO - Epoch [95][100/1281] lr: 7.637e-03, eta: 8:33:56, time: 0.801, data_time: 0.179, memory: 4083, top1_acc: 0.9700, top5_acc: 0.9994, loss_cls: 0.2036, loss: 0.2036 +2025-06-25 03:13:51,872 - pyskl - INFO - Epoch [95][200/1281] lr: 7.619e-03, eta: 8:33:16, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2114, loss: 0.2114 +2025-06-25 03:14:40,882 - pyskl - INFO - Epoch [95][300/1281] lr: 7.600e-03, eta: 8:32:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 0.2132, loss: 0.2132 +2025-06-25 03:15:29,957 - pyskl - INFO - Epoch [95][400/1281] lr: 7.581e-03, eta: 8:31:57, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2160, loss: 0.2160 +2025-06-25 03:15:59,467 - pyskl - INFO - Epoch [95][500/1281] lr: 7.562e-03, eta: 8:31:06, time: 0.295, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9994, loss_cls: 0.2547, loss: 0.2547 +2025-06-25 03:16:50,274 - pyskl - INFO - Epoch [95][600/1281] lr: 7.543e-03, eta: 8:30:28, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 1.0000, loss_cls: 0.2679, loss: 0.2679 +2025-06-25 03:17:18,523 - pyskl - INFO - Epoch [95][700/1281] lr: 7.525e-03, eta: 8:29:36, time: 0.282, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 0.2623, loss: 0.2623 +2025-06-25 03:18:07,239 - pyskl - INFO - Epoch [95][800/1281] lr: 7.506e-03, eta: 8:28:56, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 0.2151, loss: 0.2151 +2025-06-25 03:18:56,775 - pyskl - INFO - Epoch [95][900/1281] lr: 7.487e-03, eta: 8:28:17, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9988, loss_cls: 0.2614, loss: 0.2614 +2025-06-25 03:19:45,673 - pyskl - INFO - Epoch [95][1000/1281] lr: 7.468e-03, eta: 8:27:37, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 1.0000, loss_cls: 0.2571, loss: 0.2571 +2025-06-25 03:20:34,510 - pyskl - INFO - Epoch [95][1100/1281] lr: 7.450e-03, eta: 8:26:57, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 0.2691, loss: 0.2691 +2025-06-25 03:21:23,419 - pyskl - INFO - Epoch [95][1200/1281] lr: 7.431e-03, eta: 8:26:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9988, loss_cls: 0.3083, loss: 0.3083 +2025-06-25 03:22:03,630 - pyskl - INFO - Saving checkpoint at 95 epochs +2025-06-25 03:23:01,472 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:23:01,544 - pyskl - INFO - +top1_acc 0.8814 +top5_acc 0.9926 +2025-06-25 03:23:01,544 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:23:01,555 - pyskl - INFO - +mean_acc 0.8476 +2025-06-25 03:23:01,557 - pyskl - INFO - Epoch(val) [95][533] top1_acc: 0.8814, top5_acc: 0.9926, mean_class_accuracy: 0.8476 +2025-06-25 03:24:21,687 - pyskl - INFO - Epoch [96][100/1281] lr: 7.397e-03, eta: 8:25:01, time: 0.801, data_time: 0.183, memory: 4083, top1_acc: 0.9556, top5_acc: 1.0000, loss_cls: 0.2489, loss: 0.2489 +2025-06-25 03:25:10,942 - pyskl - INFO - Epoch [96][200/1281] lr: 7.379e-03, eta: 8:24:22, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 0.1953, loss: 0.1953 +2025-06-25 03:25:59,884 - pyskl - INFO - Epoch [96][300/1281] lr: 7.360e-03, eta: 8:23:42, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.1978, loss: 0.1978 +2025-06-25 03:26:48,944 - pyskl - INFO - Epoch [96][400/1281] lr: 7.341e-03, eta: 8:23:02, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2274, loss: 0.2274 +2025-06-25 03:27:20,075 - pyskl - INFO - Epoch [96][500/1281] lr: 7.323e-03, eta: 8:22:12, time: 0.311, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2439, loss: 0.2439 +2025-06-25 03:28:10,979 - pyskl - INFO - Epoch [96][600/1281] lr: 7.304e-03, eta: 8:21:34, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2226, loss: 0.2226 +2025-06-25 03:28:38,262 - pyskl - INFO - Epoch [96][700/1281] lr: 7.286e-03, eta: 8:20:42, time: 0.273, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 1.0000, loss_cls: 0.2726, loss: 0.2726 +2025-06-25 03:29:27,357 - pyskl - INFO - Epoch [96][800/1281] lr: 7.267e-03, eta: 8:20:02, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2585, loss: 0.2585 +2025-06-25 03:30:16,317 - pyskl - INFO - Epoch [96][900/1281] lr: 7.249e-03, eta: 8:19:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.2170, loss: 0.2170 +2025-06-25 03:31:04,964 - pyskl - INFO - Epoch [96][1000/1281] lr: 7.230e-03, eta: 8:18:42, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 0.2735, loss: 0.2735 +2025-06-25 03:31:53,905 - pyskl - INFO - Epoch [96][1100/1281] lr: 7.211e-03, eta: 8:18:03, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2189, loss: 0.2189 +2025-06-25 03:32:42,614 - pyskl - INFO - Epoch [96][1200/1281] lr: 7.193e-03, eta: 8:17:23, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 0.2899, loss: 0.2899 +2025-06-25 03:33:22,883 - pyskl - INFO - Saving checkpoint at 96 epochs +2025-06-25 03:34:20,629 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:34:20,684 - pyskl - INFO - +top1_acc 0.9004 +top5_acc 0.9952 +2025-06-25 03:34:20,684 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:34:20,690 - pyskl - INFO - +mean_acc 0.8692 +2025-06-25 03:34:20,691 - pyskl - INFO - Epoch(val) [96][533] top1_acc: 0.9004, top5_acc: 0.9952, mean_class_accuracy: 0.8692 +2025-06-25 03:35:39,480 - pyskl - INFO - Epoch [97][100/1281] lr: 7.159e-03, eta: 8:16:05, time: 0.788, data_time: 0.181, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.2054, loss: 0.2054 +2025-06-25 03:36:28,716 - pyskl - INFO - Epoch [97][200/1281] lr: 7.141e-03, eta: 8:15:25, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2384, loss: 0.2384 +2025-06-25 03:37:17,808 - pyskl - INFO - Epoch [97][300/1281] lr: 7.123e-03, eta: 8:14:46, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 0.2181, loss: 0.2181 +2025-06-25 03:38:06,692 - pyskl - INFO - Epoch [97][400/1281] lr: 7.104e-03, eta: 8:14:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 0.2399, loss: 0.2399 +2025-06-25 03:38:39,501 - pyskl - INFO - Epoch [97][500/1281] lr: 7.086e-03, eta: 8:13:17, time: 0.328, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 0.9988, loss_cls: 0.2187, loss: 0.2187 +2025-06-25 03:39:30,280 - pyskl - INFO - Epoch [97][600/1281] lr: 7.067e-03, eta: 8:12:38, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 0.2582, loss: 0.2582 +2025-06-25 03:39:55,681 - pyskl - INFO - Epoch [97][700/1281] lr: 7.049e-03, eta: 8:11:45, time: 0.254, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9988, loss_cls: 0.2498, loss: 0.2498 +2025-06-25 03:40:43,936 - pyskl - INFO - Epoch [97][800/1281] lr: 7.030e-03, eta: 8:11:05, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1951, loss: 0.1951 +2025-06-25 03:41:32,682 - pyskl - INFO - Epoch [97][900/1281] lr: 7.012e-03, eta: 8:10:25, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2228, loss: 0.2228 +2025-06-25 03:42:21,428 - pyskl - INFO - Epoch [97][1000/1281] lr: 6.994e-03, eta: 8:09:45, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 0.9994, loss_cls: 0.2154, loss: 0.2154 +2025-06-25 03:43:10,284 - pyskl - INFO - Epoch [97][1100/1281] lr: 6.975e-03, eta: 8:09:05, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2233, loss: 0.2233 +2025-06-25 03:43:59,264 - pyskl - INFO - Epoch [97][1200/1281] lr: 6.957e-03, eta: 8:08:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9988, loss_cls: 0.2435, loss: 0.2435 +2025-06-25 03:44:39,849 - pyskl - INFO - Saving checkpoint at 97 epochs +2025-06-25 03:45:37,415 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:45:37,469 - pyskl - INFO - +top1_acc 0.8925 +top5_acc 0.9911 +2025-06-25 03:45:37,469 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:45:37,475 - pyskl - INFO - +mean_acc 0.8634 +2025-06-25 03:45:37,476 - pyskl - INFO - Epoch(val) [97][533] top1_acc: 0.8925, top5_acc: 0.9911, mean_class_accuracy: 0.8634 +2025-06-25 03:46:56,887 - pyskl - INFO - Epoch [98][100/1281] lr: 6.924e-03, eta: 8:07:08, time: 0.794, data_time: 0.185, memory: 4083, top1_acc: 0.9631, top5_acc: 0.9994, loss_cls: 0.2289, loss: 0.2289 +2025-06-25 03:47:45,809 - pyskl - INFO - Epoch [98][200/1281] lr: 6.906e-03, eta: 8:06:28, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 0.9994, loss_cls: 0.1787, loss: 0.1787 +2025-06-25 03:48:34,688 - pyskl - INFO - Epoch [98][300/1281] lr: 6.887e-03, eta: 8:05:48, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 0.9994, loss_cls: 0.1890, loss: 0.1890 +2025-06-25 03:49:23,715 - pyskl - INFO - Epoch [98][400/1281] lr: 6.869e-03, eta: 8:05:08, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 0.2456, loss: 0.2456 +2025-06-25 03:49:58,428 - pyskl - INFO - Epoch [98][500/1281] lr: 6.851e-03, eta: 8:04:20, time: 0.347, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 0.2209, loss: 0.2209 +2025-06-25 03:50:49,176 - pyskl - INFO - Epoch [98][600/1281] lr: 6.833e-03, eta: 8:03:41, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1792, loss: 0.1792 +2025-06-25 03:51:14,703 - pyskl - INFO - Epoch [98][700/1281] lr: 6.814e-03, eta: 8:02:49, time: 0.255, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1710, loss: 0.1710 +2025-06-25 03:52:03,428 - pyskl - INFO - Epoch [98][800/1281] lr: 6.796e-03, eta: 8:02:09, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2314, loss: 0.2314 +2025-06-25 03:52:52,744 - pyskl - INFO - Epoch [98][900/1281] lr: 6.778e-03, eta: 8:01:29, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2181, loss: 0.2181 +2025-06-25 03:53:41,747 - pyskl - INFO - Epoch [98][1000/1281] lr: 6.760e-03, eta: 8:00:49, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2410, loss: 0.2410 +2025-06-25 03:54:30,464 - pyskl - INFO - Epoch [98][1100/1281] lr: 6.742e-03, eta: 8:00:09, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9988, loss_cls: 0.2607, loss: 0.2607 +2025-06-25 03:55:19,273 - pyskl - INFO - Epoch [98][1200/1281] lr: 6.724e-03, eta: 7:59:29, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1945, loss: 0.1945 +2025-06-25 03:55:59,416 - pyskl - INFO - Saving checkpoint at 98 epochs +2025-06-25 03:56:57,946 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:56:58,002 - pyskl - INFO - +top1_acc 0.9032 +top5_acc 0.9939 +2025-06-25 03:56:58,002 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:56:58,008 - pyskl - INFO - +mean_acc 0.8735 +2025-06-25 03:56:58,009 - pyskl - INFO - Epoch(val) [98][533] top1_acc: 0.9032, top5_acc: 0.9939, mean_class_accuracy: 0.8735 +2025-06-25 03:58:17,890 - pyskl - INFO - Epoch [99][100/1281] lr: 6.691e-03, eta: 7:58:11, time: 0.799, data_time: 0.183, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1533, loss: 0.1533 +2025-06-25 03:59:07,292 - pyskl - INFO - Epoch [99][200/1281] lr: 6.673e-03, eta: 7:57:32, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1982, loss: 0.1982 +2025-06-25 03:59:56,368 - pyskl - INFO - Epoch [99][300/1281] lr: 6.655e-03, eta: 7:56:52, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 0.9994, loss_cls: 0.1658, loss: 0.1658 +2025-06-25 04:00:45,771 - pyskl - INFO - Epoch [99][400/1281] lr: 6.637e-03, eta: 7:56:12, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1649, loss: 0.1649 +2025-06-25 04:01:19,190 - pyskl - INFO - Epoch [99][500/1281] lr: 6.619e-03, eta: 7:55:23, time: 0.334, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2156, loss: 0.2156 +2025-06-25 04:02:10,154 - pyskl - INFO - Epoch [99][600/1281] lr: 6.601e-03, eta: 7:54:44, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 0.9988, loss_cls: 0.2117, loss: 0.2117 +2025-06-25 04:02:35,460 - pyskl - INFO - Epoch [99][700/1281] lr: 6.583e-03, eta: 7:53:52, time: 0.253, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 0.9994, loss_cls: 0.2031, loss: 0.2031 +2025-06-25 04:03:24,212 - pyskl - INFO - Epoch [99][800/1281] lr: 6.565e-03, eta: 7:53:12, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 0.2016, loss: 0.2016 +2025-06-25 04:04:13,329 - pyskl - INFO - Epoch [99][900/1281] lr: 6.547e-03, eta: 7:52:32, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2275, loss: 0.2275 +2025-06-25 04:05:02,326 - pyskl - INFO - Epoch [99][1000/1281] lr: 6.529e-03, eta: 7:51:52, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9988, loss_cls: 0.2432, loss: 0.2432 +2025-06-25 04:05:51,586 - pyskl - INFO - Epoch [99][1100/1281] lr: 6.511e-03, eta: 7:51:12, time: 0.493, data_time: 0.001, memory: 4083, top1_acc: 0.9681, top5_acc: 0.9994, loss_cls: 0.2104, loss: 0.2104 +2025-06-25 04:06:40,611 - pyskl - INFO - Epoch [99][1200/1281] lr: 6.493e-03, eta: 7:50:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 0.2164, loss: 0.2164 +2025-06-25 04:07:20,706 - pyskl - INFO - Saving checkpoint at 99 epochs +2025-06-25 04:08:19,404 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:08:19,472 - pyskl - INFO - +top1_acc 0.8887 +top5_acc 0.9925 +2025-06-25 04:08:19,472 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:08:19,479 - pyskl - INFO - +mean_acc 0.8523 +2025-06-25 04:08:19,481 - pyskl - INFO - Epoch(val) [99][533] top1_acc: 0.8887, top5_acc: 0.9925, mean_class_accuracy: 0.8523 +2025-06-25 04:09:39,390 - pyskl - INFO - Epoch [100][100/1281] lr: 6.460e-03, eta: 7:49:14, time: 0.799, data_time: 0.191, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2243, loss: 0.2243 +2025-06-25 04:10:28,281 - pyskl - INFO - Epoch [100][200/1281] lr: 6.442e-03, eta: 7:48:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 0.9988, loss_cls: 0.1927, loss: 0.1927 +2025-06-25 04:11:17,596 - pyskl - INFO - Epoch [100][300/1281] lr: 6.425e-03, eta: 7:47:54, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 0.1950, loss: 0.1950 +2025-06-25 04:12:06,706 - pyskl - INFO - Epoch [100][400/1281] lr: 6.407e-03, eta: 7:47:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2103, loss: 0.2103 +2025-06-25 04:12:39,895 - pyskl - INFO - Epoch [100][500/1281] lr: 6.389e-03, eta: 7:46:26, time: 0.332, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1842, loss: 0.1842 +2025-06-25 04:13:30,698 - pyskl - INFO - Epoch [100][600/1281] lr: 6.371e-03, eta: 7:45:46, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 0.9994, loss_cls: 0.1768, loss: 0.1768 +2025-06-25 04:13:56,141 - pyskl - INFO - Epoch [100][700/1281] lr: 6.353e-03, eta: 7:44:54, time: 0.254, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1712, loss: 0.1712 +2025-06-25 04:14:44,284 - pyskl - INFO - Epoch [100][800/1281] lr: 6.336e-03, eta: 7:44:14, time: 0.481, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1907, loss: 0.1907 +2025-06-25 04:15:33,305 - pyskl - INFO - Epoch [100][900/1281] lr: 6.318e-03, eta: 7:43:33, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 0.2215, loss: 0.2215 +2025-06-25 04:16:22,170 - pyskl - INFO - Epoch [100][1000/1281] lr: 6.300e-03, eta: 7:42:53, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9988, loss_cls: 0.2294, loss: 0.2294 +2025-06-25 04:17:11,106 - pyskl - INFO - Epoch [100][1100/1281] lr: 6.282e-03, eta: 7:42:13, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 0.2071, loss: 0.2071 +2025-06-25 04:18:00,281 - pyskl - INFO - Epoch [100][1200/1281] lr: 6.265e-03, eta: 7:41:33, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2280, loss: 0.2280 +2025-06-25 04:18:40,206 - pyskl - INFO - Saving checkpoint at 100 epochs +2025-06-25 04:19:38,595 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:19:38,650 - pyskl - INFO - +top1_acc 0.8974 +top5_acc 0.9948 +2025-06-25 04:19:38,650 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:19:38,657 - pyskl - INFO - +mean_acc 0.8673 +2025-06-25 04:19:38,659 - pyskl - INFO - Epoch(val) [100][533] top1_acc: 0.8974, top5_acc: 0.9948, mean_class_accuracy: 0.8673 +2025-06-25 04:20:57,028 - pyskl - INFO - Epoch [101][100/1281] lr: 6.232e-03, eta: 7:40:15, time: 0.784, data_time: 0.182, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.2165, loss: 0.2165 +2025-06-25 04:21:45,852 - pyskl - INFO - Epoch [101][200/1281] lr: 6.215e-03, eta: 7:39:34, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1743, loss: 0.1743 +2025-06-25 04:22:35,166 - pyskl - INFO - Epoch [101][300/1281] lr: 6.197e-03, eta: 7:38:54, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1651, loss: 0.1651 +2025-06-25 04:23:24,310 - pyskl - INFO - Epoch [101][400/1281] lr: 6.180e-03, eta: 7:38:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.2113, loss: 0.2113 +2025-06-25 04:24:00,006 - pyskl - INFO - Epoch [101][500/1281] lr: 6.162e-03, eta: 7:37:27, time: 0.357, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2265, loss: 0.2265 +2025-06-25 04:24:50,971 - pyskl - INFO - Epoch [101][600/1281] lr: 6.144e-03, eta: 7:36:48, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2300, loss: 0.2300 +2025-06-25 04:25:15,985 - pyskl - INFO - Epoch [101][700/1281] lr: 6.127e-03, eta: 7:35:55, time: 0.250, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2296, loss: 0.2296 +2025-06-25 04:26:03,765 - pyskl - INFO - Epoch [101][800/1281] lr: 6.109e-03, eta: 7:35:14, time: 0.478, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 0.2269, loss: 0.2269 +2025-06-25 04:26:53,043 - pyskl - INFO - Epoch [101][900/1281] lr: 6.092e-03, eta: 7:34:34, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 0.2028, loss: 0.2028 +2025-06-25 04:27:42,000 - pyskl - INFO - Epoch [101][1000/1281] lr: 6.074e-03, eta: 7:33:54, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 0.9994, loss_cls: 0.1717, loss: 0.1717 +2025-06-25 04:28:31,090 - pyskl - INFO - Epoch [101][1100/1281] lr: 6.057e-03, eta: 7:33:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 0.9994, loss_cls: 0.2017, loss: 0.2017 +2025-06-25 04:29:20,019 - pyskl - INFO - Epoch [101][1200/1281] lr: 6.039e-03, eta: 7:32:33, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 0.1930, loss: 0.1930 +2025-06-25 04:30:00,395 - pyskl - INFO - Saving checkpoint at 101 epochs +2025-06-25 04:30:58,619 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:30:58,673 - pyskl - INFO - +top1_acc 0.8974 +top5_acc 0.9947 +2025-06-25 04:30:58,674 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:30:58,680 - pyskl - INFO - +mean_acc 0.8579 +2025-06-25 04:30:58,682 - pyskl - INFO - Epoch(val) [101][533] top1_acc: 0.8974, top5_acc: 0.9947, mean_class_accuracy: 0.8579 +2025-06-25 04:32:18,300 - pyskl - INFO - Epoch [102][100/1281] lr: 6.007e-03, eta: 7:31:16, time: 0.796, data_time: 0.178, memory: 4083, top1_acc: 0.9637, top5_acc: 0.9994, loss_cls: 0.2163, loss: 0.2163 +2025-06-25 04:33:07,093 - pyskl - INFO - Epoch [102][200/1281] lr: 5.990e-03, eta: 7:30:35, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1858, loss: 0.1858 +2025-06-25 04:33:56,341 - pyskl - INFO - Epoch [102][300/1281] lr: 5.972e-03, eta: 7:29:55, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1584, loss: 0.1584 +2025-06-25 04:34:45,323 - pyskl - INFO - Epoch [102][400/1281] lr: 5.955e-03, eta: 7:29:14, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1663, loss: 0.1663 +2025-06-25 04:35:19,767 - pyskl - INFO - Epoch [102][500/1281] lr: 5.938e-03, eta: 7:28:27, time: 0.344, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1470, loss: 0.1470 +2025-06-25 04:36:10,459 - pyskl - INFO - Epoch [102][600/1281] lr: 5.920e-03, eta: 7:27:47, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1856, loss: 0.1856 +2025-06-25 04:36:35,399 - pyskl - INFO - Epoch [102][700/1281] lr: 5.903e-03, eta: 7:26:55, time: 0.249, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1688, loss: 0.1688 +2025-06-25 04:37:22,444 - pyskl - INFO - Epoch [102][800/1281] lr: 5.886e-03, eta: 7:26:14, time: 0.470, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1961, loss: 0.1961 +2025-06-25 04:38:11,627 - pyskl - INFO - Epoch [102][900/1281] lr: 5.868e-03, eta: 7:25:34, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 0.9988, loss_cls: 0.2172, loss: 0.2172 +2025-06-25 04:39:01,126 - pyskl - INFO - Epoch [102][1000/1281] lr: 5.851e-03, eta: 7:24:53, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 0.2020, loss: 0.2020 +2025-06-25 04:39:50,402 - pyskl - INFO - Epoch [102][1100/1281] lr: 5.834e-03, eta: 7:24:13, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 0.1803, loss: 0.1803 +2025-06-25 04:40:39,370 - pyskl - INFO - Epoch [102][1200/1281] lr: 5.816e-03, eta: 7:23:33, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 0.9994, loss_cls: 0.1804, loss: 0.1804 +2025-06-25 04:41:19,479 - pyskl - INFO - Saving checkpoint at 102 epochs +2025-06-25 04:42:17,538 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:42:17,595 - pyskl - INFO - +top1_acc 0.8977 +top5_acc 0.9927 +2025-06-25 04:42:17,595 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:42:17,601 - pyskl - INFO - +mean_acc 0.8709 +2025-06-25 04:42:17,603 - pyskl - INFO - Epoch(val) [102][533] top1_acc: 0.8977, top5_acc: 0.9927, mean_class_accuracy: 0.8709 +2025-06-25 04:43:36,016 - pyskl - INFO - Epoch [103][100/1281] lr: 5.785e-03, eta: 7:22:14, time: 0.784, data_time: 0.183, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1683, loss: 0.1683 +2025-06-25 04:44:24,910 - pyskl - INFO - Epoch [103][200/1281] lr: 5.768e-03, eta: 7:21:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1675, loss: 0.1675 +2025-06-25 04:45:14,320 - pyskl - INFO - Epoch [103][300/1281] lr: 5.751e-03, eta: 7:20:53, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1525, loss: 0.1525 +2025-06-25 04:46:03,234 - pyskl - INFO - Epoch [103][400/1281] lr: 5.733e-03, eta: 7:20:13, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.2063, loss: 0.2063 +2025-06-25 04:46:40,532 - pyskl - INFO - Epoch [103][500/1281] lr: 5.716e-03, eta: 7:19:27, time: 0.373, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1754, loss: 0.1754 +2025-06-25 04:47:31,345 - pyskl - INFO - Epoch [103][600/1281] lr: 5.699e-03, eta: 7:18:47, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 0.1991, loss: 0.1991 +2025-06-25 04:47:55,145 - pyskl - INFO - Epoch [103][700/1281] lr: 5.682e-03, eta: 7:17:55, time: 0.238, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2064, loss: 0.2064 +2025-06-25 04:48:41,353 - pyskl - INFO - Epoch [103][800/1281] lr: 5.665e-03, eta: 7:17:13, time: 0.462, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 0.9994, loss_cls: 0.1768, loss: 0.1768 +2025-06-25 04:49:30,303 - pyskl - INFO - Epoch [103][900/1281] lr: 5.648e-03, eta: 7:16:32, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 0.9994, loss_cls: 0.1708, loss: 0.1708 +2025-06-25 04:50:19,227 - pyskl - INFO - Epoch [103][1000/1281] lr: 5.631e-03, eta: 7:15:52, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9994, loss_cls: 0.2222, loss: 0.2222 +2025-06-25 04:51:07,943 - pyskl - INFO - Epoch [103][1100/1281] lr: 5.614e-03, eta: 7:15:11, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 0.9994, loss_cls: 0.1866, loss: 0.1866 +2025-06-25 04:51:56,848 - pyskl - INFO - Epoch [103][1200/1281] lr: 5.597e-03, eta: 7:14:30, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2323, loss: 0.2323 +2025-06-25 04:52:37,097 - pyskl - INFO - Saving checkpoint at 103 epochs +2025-06-25 04:53:36,051 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:53:36,119 - pyskl - INFO - +top1_acc 0.8936 +top5_acc 0.9945 +2025-06-25 04:53:36,119 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:53:36,127 - pyskl - INFO - +mean_acc 0.8650 +2025-06-25 04:53:36,129 - pyskl - INFO - Epoch(val) [103][533] top1_acc: 0.8936, top5_acc: 0.9945, mean_class_accuracy: 0.8650 +2025-06-25 04:54:54,760 - pyskl - INFO - Epoch [104][100/1281] lr: 5.566e-03, eta: 7:13:12, time: 0.786, data_time: 0.186, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.1925, loss: 0.1925 +2025-06-25 04:55:43,809 - pyskl - INFO - Epoch [104][200/1281] lr: 5.549e-03, eta: 7:12:32, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 0.9994, loss_cls: 0.1737, loss: 0.1737 +2025-06-25 04:56:33,125 - pyskl - INFO - Epoch [104][300/1281] lr: 5.532e-03, eta: 7:11:51, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1587, loss: 0.1587 +2025-06-25 04:57:22,365 - pyskl - INFO - Epoch [104][400/1281] lr: 5.515e-03, eta: 7:11:11, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1546, loss: 0.1546 +2025-06-25 04:57:59,681 - pyskl - INFO - Epoch [104][500/1281] lr: 5.498e-03, eta: 7:10:25, time: 0.373, data_time: 0.001, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1364, loss: 0.1364 +2025-06-25 04:58:50,484 - pyskl - INFO - Epoch [104][600/1281] lr: 5.481e-03, eta: 7:09:45, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1146, loss: 0.1146 +2025-06-25 04:59:14,259 - pyskl - INFO - Epoch [104][700/1281] lr: 5.464e-03, eta: 7:08:53, time: 0.238, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 0.9994, loss_cls: 0.1630, loss: 0.1630 +2025-06-25 04:59:59,646 - pyskl - INFO - Epoch [104][800/1281] lr: 5.447e-03, eta: 7:08:11, time: 0.454, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1456, loss: 0.1456 +2025-06-25 05:00:48,470 - pyskl - INFO - Epoch [104][900/1281] lr: 5.430e-03, eta: 7:07:30, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1769, loss: 0.1769 +2025-06-25 05:01:37,522 - pyskl - INFO - Epoch [104][1000/1281] lr: 5.413e-03, eta: 7:06:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1873, loss: 0.1873 +2025-06-25 05:02:26,631 - pyskl - INFO - Epoch [104][1100/1281] lr: 5.397e-03, eta: 7:06:09, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1743, loss: 0.1743 +2025-06-25 05:03:15,475 - pyskl - INFO - Epoch [104][1200/1281] lr: 5.380e-03, eta: 7:05:28, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1516, loss: 0.1516 +2025-06-25 05:03:55,459 - pyskl - INFO - Saving checkpoint at 104 epochs +2025-06-25 05:04:53,611 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:04:53,667 - pyskl - INFO - +top1_acc 0.8899 +top5_acc 0.9937 +2025-06-25 05:04:53,667 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:04:53,673 - pyskl - INFO - +mean_acc 0.8531 +2025-06-25 05:04:53,674 - pyskl - INFO - Epoch(val) [104][533] top1_acc: 0.8899, top5_acc: 0.9937, mean_class_accuracy: 0.8531 +2025-06-25 05:06:13,427 - pyskl - INFO - Epoch [105][100/1281] lr: 5.349e-03, eta: 7:04:10, time: 0.797, data_time: 0.190, memory: 4083, top1_acc: 0.9669, top5_acc: 0.9994, loss_cls: 0.1810, loss: 0.1810 +2025-06-25 05:07:02,577 - pyskl - INFO - Epoch [105][200/1281] lr: 5.333e-03, eta: 7:03:29, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1379, loss: 0.1379 +2025-06-25 05:07:51,664 - pyskl - INFO - Epoch [105][300/1281] lr: 5.316e-03, eta: 7:02:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 0.9994, loss_cls: 0.1409, loss: 0.1409 +2025-06-25 05:08:40,994 - pyskl - INFO - Epoch [105][400/1281] lr: 5.299e-03, eta: 7:02:08, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 0.9994, loss_cls: 0.1583, loss: 0.1583 +2025-06-25 05:09:19,280 - pyskl - INFO - Epoch [105][500/1281] lr: 5.283e-03, eta: 7:01:23, time: 0.383, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1585, loss: 0.1585 +2025-06-25 05:10:09,887 - pyskl - INFO - Epoch [105][600/1281] lr: 5.266e-03, eta: 7:00:43, time: 0.506, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2087, loss: 0.2087 +2025-06-25 05:10:33,532 - pyskl - INFO - Epoch [105][700/1281] lr: 5.249e-03, eta: 6:59:51, time: 0.236, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1268, loss: 0.1268 +2025-06-25 05:11:19,255 - pyskl - INFO - Epoch [105][800/1281] lr: 5.233e-03, eta: 6:59:09, time: 0.457, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1750, loss: 0.1750 +2025-06-25 05:12:08,449 - pyskl - INFO - Epoch [105][900/1281] lr: 5.216e-03, eta: 6:58:28, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1427, loss: 0.1427 +2025-06-25 05:12:57,444 - pyskl - INFO - Epoch [105][1000/1281] lr: 5.199e-03, eta: 6:57:47, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1902, loss: 0.1902 +2025-06-25 05:13:46,843 - pyskl - INFO - Epoch [105][1100/1281] lr: 5.183e-03, eta: 6:57:06, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 0.9994, loss_cls: 0.1710, loss: 0.1710 +2025-06-25 05:14:35,984 - pyskl - INFO - Epoch [105][1200/1281] lr: 5.166e-03, eta: 6:56:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1386, loss: 0.1386 +2025-06-25 05:15:15,723 - pyskl - INFO - Saving checkpoint at 105 epochs +2025-06-25 05:16:13,615 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:16:13,671 - pyskl - INFO - +top1_acc 0.8981 +top5_acc 0.9947 +2025-06-25 05:16:13,671 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:16:13,678 - pyskl - INFO - +mean_acc 0.8702 +2025-06-25 05:16:13,679 - pyskl - INFO - Epoch(val) [105][533] top1_acc: 0.8981, top5_acc: 0.9947, mean_class_accuracy: 0.8702 +2025-06-25 05:17:30,771 - pyskl - INFO - Epoch [106][100/1281] lr: 5.136e-03, eta: 6:55:07, time: 0.771, data_time: 0.181, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1262, loss: 0.1262 +2025-06-25 05:18:19,730 - pyskl - INFO - Epoch [106][200/1281] lr: 5.120e-03, eta: 6:54:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1182, loss: 0.1182 +2025-06-25 05:19:09,089 - pyskl - INFO - Epoch [106][300/1281] lr: 5.103e-03, eta: 6:53:45, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1432, loss: 0.1432 +2025-06-25 05:19:57,946 - pyskl - INFO - Epoch [106][400/1281] lr: 5.087e-03, eta: 6:53:04, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1701, loss: 0.1701 +2025-06-25 05:20:38,758 - pyskl - INFO - Epoch [106][500/1281] lr: 5.070e-03, eta: 6:52:20, time: 0.408, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1711, loss: 0.1711 +2025-06-25 05:21:27,737 - pyskl - INFO - Epoch [106][600/1281] lr: 5.054e-03, eta: 6:51:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 0.9994, loss_cls: 0.1700, loss: 0.1700 +2025-06-25 05:21:52,310 - pyskl - INFO - Epoch [106][700/1281] lr: 5.038e-03, eta: 6:50:48, time: 0.246, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1364, loss: 0.1364 +2025-06-25 05:22:34,913 - pyskl - INFO - Epoch [106][800/1281] lr: 5.021e-03, eta: 6:50:04, time: 0.426, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1408, loss: 0.1408 +2025-06-25 05:23:23,806 - pyskl - INFO - Epoch [106][900/1281] lr: 5.005e-03, eta: 6:49:23, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1447, loss: 0.1447 +2025-06-25 05:24:12,612 - pyskl - INFO - Epoch [106][1000/1281] lr: 4.988e-03, eta: 6:48:42, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.1139, loss: 0.1139 +2025-06-25 05:25:01,768 - pyskl - INFO - Epoch [106][1100/1281] lr: 4.972e-03, eta: 6:48:01, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 0.9988, loss_cls: 0.1713, loss: 0.1713 +2025-06-25 05:25:50,662 - pyskl - INFO - Epoch [106][1200/1281] lr: 4.956e-03, eta: 6:47:21, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1346, loss: 0.1346 +2025-06-25 05:26:31,154 - pyskl - INFO - Saving checkpoint at 106 epochs +2025-06-25 05:27:29,118 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:27:29,182 - pyskl - INFO - +top1_acc 0.9085 +top5_acc 0.9953 +2025-06-25 05:27:29,182 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:27:29,189 - pyskl - INFO - +mean_acc 0.8809 +2025-06-25 05:27:29,193 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_91.pth was removed +2025-06-25 05:27:29,357 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_106.pth. +2025-06-25 05:27:29,357 - pyskl - INFO - Best top1_acc is 0.9085 at 106 epoch. +2025-06-25 05:27:29,360 - pyskl - INFO - Epoch(val) [106][533] top1_acc: 0.9085, top5_acc: 0.9953, mean_class_accuracy: 0.8809 +2025-06-25 05:28:49,030 - pyskl - INFO - Epoch [107][100/1281] lr: 4.926e-03, eta: 6:46:03, time: 0.797, data_time: 0.185, memory: 4083, top1_acc: 0.9825, top5_acc: 0.9994, loss_cls: 0.1159, loss: 0.1159 +2025-06-25 05:29:38,090 - pyskl - INFO - Epoch [107][200/1281] lr: 4.910e-03, eta: 6:45:22, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1057, loss: 0.1057 +2025-06-25 05:30:27,252 - pyskl - INFO - Epoch [107][300/1281] lr: 4.894e-03, eta: 6:44:41, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1164, loss: 0.1164 +2025-06-25 05:31:16,530 - pyskl - INFO - Epoch [107][400/1281] lr: 4.878e-03, eta: 6:44:00, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1255, loss: 0.1255 +2025-06-25 05:31:57,426 - pyskl - INFO - Epoch [107][500/1281] lr: 4.862e-03, eta: 6:43:16, time: 0.409, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1223, loss: 0.1223 +2025-06-25 05:32:44,933 - pyskl - INFO - Epoch [107][600/1281] lr: 4.845e-03, eta: 6:42:34, time: 0.475, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1209, loss: 0.1209 +2025-06-25 05:33:10,847 - pyskl - INFO - Epoch [107][700/1281] lr: 4.829e-03, eta: 6:41:44, time: 0.259, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 0.9994, loss_cls: 0.1708, loss: 0.1708 +2025-06-25 05:33:53,946 - pyskl - INFO - Epoch [107][800/1281] lr: 4.813e-03, eta: 6:41:00, time: 0.431, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1333, loss: 0.1333 +2025-06-25 05:34:42,634 - pyskl - INFO - Epoch [107][900/1281] lr: 4.797e-03, eta: 6:40:19, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1185, loss: 0.1185 +2025-06-25 05:35:31,721 - pyskl - INFO - Epoch [107][1000/1281] lr: 4.781e-03, eta: 6:39:38, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 0.9988, loss_cls: 0.1569, loss: 0.1569 +2025-06-25 05:36:20,413 - pyskl - INFO - Epoch [107][1100/1281] lr: 4.765e-03, eta: 6:38:57, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1525, loss: 0.1525 +2025-06-25 05:37:09,517 - pyskl - INFO - Epoch [107][1200/1281] lr: 4.749e-03, eta: 6:38:16, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1505, loss: 0.1505 +2025-06-25 05:37:50,080 - pyskl - INFO - Saving checkpoint at 107 epochs +2025-06-25 05:38:47,440 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:38:47,507 - pyskl - INFO - +top1_acc 0.9013 +top5_acc 0.9917 +2025-06-25 05:38:47,507 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:38:47,514 - pyskl - INFO - +mean_acc 0.8658 +2025-06-25 05:38:47,516 - pyskl - INFO - Epoch(val) [107][533] top1_acc: 0.9013, top5_acc: 0.9917, mean_class_accuracy: 0.8658 +2025-06-25 05:40:07,215 - pyskl - INFO - Epoch [108][100/1281] lr: 4.720e-03, eta: 6:36:58, time: 0.797, data_time: 0.188, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1559, loss: 0.1559 +2025-06-25 05:40:56,419 - pyskl - INFO - Epoch [108][200/1281] lr: 4.704e-03, eta: 6:36:17, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1409, loss: 0.1409 +2025-06-25 05:41:45,573 - pyskl - INFO - Epoch [108][300/1281] lr: 4.688e-03, eta: 6:35:36, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1250, loss: 0.1250 +2025-06-25 05:42:34,892 - pyskl - INFO - Epoch [108][400/1281] lr: 4.672e-03, eta: 6:34:55, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1347, loss: 0.1347 +2025-06-25 05:43:16,917 - pyskl - INFO - Epoch [108][500/1281] lr: 4.656e-03, eta: 6:34:11, time: 0.420, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 0.9994, loss_cls: 0.1111, loss: 0.1111 +2025-06-25 05:44:02,447 - pyskl - INFO - Epoch [108][600/1281] lr: 4.640e-03, eta: 6:33:29, time: 0.455, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 0.9988, loss_cls: 0.1385, loss: 0.1385 +2025-06-25 05:44:30,466 - pyskl - INFO - Epoch [108][700/1281] lr: 4.624e-03, eta: 6:32:40, time: 0.280, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1872, loss: 0.1872 +2025-06-25 05:45:13,287 - pyskl - INFO - Epoch [108][800/1281] lr: 4.608e-03, eta: 6:31:56, time: 0.428, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.2006, loss: 0.2006 +2025-06-25 05:46:02,185 - pyskl - INFO - Epoch [108][900/1281] lr: 4.593e-03, eta: 6:31:15, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1702, loss: 0.1702 +2025-06-25 05:46:51,424 - pyskl - INFO - Epoch [108][1000/1281] lr: 4.577e-03, eta: 6:30:34, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.1059, loss: 0.1059 +2025-06-25 05:47:40,547 - pyskl - INFO - Epoch [108][1100/1281] lr: 4.561e-03, eta: 6:29:53, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 0.9994, loss_cls: 0.1651, loss: 0.1651 +2025-06-25 05:48:29,531 - pyskl - INFO - Epoch [108][1200/1281] lr: 4.545e-03, eta: 6:29:12, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.1662, loss: 0.1662 +2025-06-25 05:49:10,102 - pyskl - INFO - Saving checkpoint at 108 epochs +2025-06-25 05:50:07,962 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:50:08,022 - pyskl - INFO - +top1_acc 0.8986 +top5_acc 0.9911 +2025-06-25 05:50:08,022 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:50:08,029 - pyskl - INFO - +mean_acc 0.8603 +2025-06-25 05:50:08,031 - pyskl - INFO - Epoch(val) [108][533] top1_acc: 0.8986, top5_acc: 0.9911, mean_class_accuracy: 0.8603 +2025-06-25 05:51:28,343 - pyskl - INFO - Epoch [109][100/1281] lr: 4.517e-03, eta: 6:27:54, time: 0.803, data_time: 0.187, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1132, loss: 0.1132 +2025-06-25 05:52:17,286 - pyskl - INFO - Epoch [109][200/1281] lr: 4.501e-03, eta: 6:27:13, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1152, loss: 0.1152 +2025-06-25 05:53:06,300 - pyskl - INFO - Epoch [109][300/1281] lr: 4.485e-03, eta: 6:26:32, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1382, loss: 0.1382 +2025-06-25 05:53:55,350 - pyskl - INFO - Epoch [109][400/1281] lr: 4.470e-03, eta: 6:25:51, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1281, loss: 0.1281 +2025-06-25 05:54:36,891 - pyskl - INFO - Epoch [109][500/1281] lr: 4.454e-03, eta: 6:25:06, time: 0.415, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1123, loss: 0.1123 +2025-06-25 05:55:23,484 - pyskl - INFO - Epoch [109][600/1281] lr: 4.438e-03, eta: 6:24:24, time: 0.466, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 0.9994, loss_cls: 0.1556, loss: 0.1556 +2025-06-25 05:55:50,475 - pyskl - INFO - Epoch [109][700/1281] lr: 4.423e-03, eta: 6:23:35, time: 0.270, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1260, loss: 0.1260 +2025-06-25 05:56:33,215 - pyskl - INFO - Epoch [109][800/1281] lr: 4.407e-03, eta: 6:22:51, time: 0.427, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1247, loss: 0.1247 +2025-06-25 05:57:22,158 - pyskl - INFO - Epoch [109][900/1281] lr: 4.391e-03, eta: 6:22:10, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 0.9994, loss_cls: 0.1502, loss: 0.1502 +2025-06-25 05:58:11,093 - pyskl - INFO - Epoch [109][1000/1281] lr: 4.376e-03, eta: 6:21:29, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1346, loss: 0.1346 +2025-06-25 05:59:00,083 - pyskl - INFO - Epoch [109][1100/1281] lr: 4.360e-03, eta: 6:20:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1060, loss: 0.1060 +2025-06-25 05:59:48,980 - pyskl - INFO - Epoch [109][1200/1281] lr: 4.345e-03, eta: 6:20:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1298, loss: 0.1298 +2025-06-25 06:00:29,163 - pyskl - INFO - Saving checkpoint at 109 epochs +2025-06-25 06:01:26,475 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:01:26,541 - pyskl - INFO - +top1_acc 0.9128 +top5_acc 0.9948 +2025-06-25 06:01:26,542 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:01:26,555 - pyskl - INFO - +mean_acc 0.8804 +2025-06-25 06:01:26,561 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_106.pth was removed +2025-06-25 06:01:26,751 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_109.pth. +2025-06-25 06:01:26,751 - pyskl - INFO - Best top1_acc is 0.9128 at 109 epoch. +2025-06-25 06:01:26,755 - pyskl - INFO - Epoch(val) [109][533] top1_acc: 0.9128, top5_acc: 0.9948, mean_class_accuracy: 0.8804 +2025-06-25 06:02:45,946 - pyskl - INFO - Epoch [110][100/1281] lr: 4.317e-03, eta: 6:18:48, time: 0.792, data_time: 0.183, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1393, loss: 0.1393 +2025-06-25 06:03:35,117 - pyskl - INFO - Epoch [110][200/1281] lr: 4.301e-03, eta: 6:18:07, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1494, loss: 0.1494 +2025-06-25 06:04:24,448 - pyskl - INFO - Epoch [110][300/1281] lr: 4.286e-03, eta: 6:17:26, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1401, loss: 0.1401 +2025-06-25 06:05:13,561 - pyskl - INFO - Epoch [110][400/1281] lr: 4.271e-03, eta: 6:16:45, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1329, loss: 0.1329 +2025-06-25 06:05:56,520 - pyskl - INFO - Epoch [110][500/1281] lr: 4.255e-03, eta: 6:16:01, time: 0.430, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1177, loss: 0.1177 +2025-06-25 06:06:41,549 - pyskl - INFO - Epoch [110][600/1281] lr: 4.240e-03, eta: 6:15:18, time: 0.450, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1417, loss: 0.1417 +2025-06-25 06:07:09,731 - pyskl - INFO - Epoch [110][700/1281] lr: 4.225e-03, eta: 6:14:29, time: 0.282, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1140, loss: 0.1140 +2025-06-25 06:07:51,532 - pyskl - INFO - Epoch [110][800/1281] lr: 4.209e-03, eta: 6:13:45, time: 0.418, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1525, loss: 0.1525 +2025-06-25 06:08:40,499 - pyskl - INFO - Epoch [110][900/1281] lr: 4.194e-03, eta: 6:13:04, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1309, loss: 0.1309 +2025-06-25 06:09:29,700 - pyskl - INFO - Epoch [110][1000/1281] lr: 4.179e-03, eta: 6:12:23, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 0.1337, loss: 0.1337 +2025-06-25 06:10:18,571 - pyskl - INFO - Epoch [110][1100/1281] lr: 4.164e-03, eta: 6:11:41, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1325, loss: 0.1325 +2025-06-25 06:11:07,560 - pyskl - INFO - Epoch [110][1200/1281] lr: 4.148e-03, eta: 6:11:00, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1298, loss: 0.1298 +2025-06-25 06:11:48,008 - pyskl - INFO - Saving checkpoint at 110 epochs +2025-06-25 06:12:45,515 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:12:45,570 - pyskl - INFO - +top1_acc 0.9142 +top5_acc 0.9950 +2025-06-25 06:12:45,570 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:12:45,576 - pyskl - INFO - +mean_acc 0.8803 +2025-06-25 06:12:45,580 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_109.pth was removed +2025-06-25 06:12:45,804 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_110.pth. +2025-06-25 06:12:45,804 - pyskl - INFO - Best top1_acc is 0.9142 at 110 epoch. +2025-06-25 06:12:45,807 - pyskl - INFO - Epoch(val) [110][533] top1_acc: 0.9142, top5_acc: 0.9950, mean_class_accuracy: 0.8803 +2025-06-25 06:14:06,026 - pyskl - INFO - Epoch [111][100/1281] lr: 4.121e-03, eta: 6:09:42, time: 0.802, data_time: 0.187, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1191, loss: 0.1191 +2025-06-25 06:14:55,699 - pyskl - INFO - Epoch [111][200/1281] lr: 4.106e-03, eta: 6:09:01, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 0.9994, loss_cls: 0.1280, loss: 0.1280 +2025-06-25 06:15:44,738 - pyskl - INFO - Epoch [111][300/1281] lr: 4.091e-03, eta: 6:08:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0837, loss: 0.0837 +2025-06-25 06:16:33,376 - pyskl - INFO - Epoch [111][400/1281] lr: 4.075e-03, eta: 6:07:38, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 0.9994, loss_cls: 0.0898, loss: 0.0898 +2025-06-25 06:17:16,409 - pyskl - INFO - Epoch [111][500/1281] lr: 4.060e-03, eta: 6:06:55, time: 0.430, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1040, loss: 0.1040 +2025-06-25 06:17:59,881 - pyskl - INFO - Epoch [111][600/1281] lr: 4.045e-03, eta: 6:06:11, time: 0.435, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.0966, loss: 0.0966 +2025-06-25 06:18:29,275 - pyskl - INFO - Epoch [111][700/1281] lr: 4.030e-03, eta: 6:05:23, time: 0.294, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1146, loss: 0.1146 +2025-06-25 06:19:10,585 - pyskl - INFO - Epoch [111][800/1281] lr: 4.015e-03, eta: 6:04:39, time: 0.413, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1078, loss: 0.1078 +2025-06-25 06:19:59,799 - pyskl - INFO - Epoch [111][900/1281] lr: 4.000e-03, eta: 6:03:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1386, loss: 0.1386 +2025-06-25 06:20:48,558 - pyskl - INFO - Epoch [111][1000/1281] lr: 3.985e-03, eta: 6:03:16, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1194, loss: 0.1194 +2025-06-25 06:21:37,597 - pyskl - INFO - Epoch [111][1100/1281] lr: 3.970e-03, eta: 6:02:35, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1138, loss: 0.1138 +2025-06-25 06:22:26,699 - pyskl - INFO - Epoch [111][1200/1281] lr: 3.955e-03, eta: 6:01:53, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1019, loss: 0.1019 +2025-06-25 06:23:06,626 - pyskl - INFO - Saving checkpoint at 111 epochs +2025-06-25 06:24:04,390 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:24:04,445 - pyskl - INFO - +top1_acc 0.9058 +top5_acc 0.9945 +2025-06-25 06:24:04,445 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:24:04,452 - pyskl - INFO - +mean_acc 0.8787 +2025-06-25 06:24:04,453 - pyskl - INFO - Epoch(val) [111][533] top1_acc: 0.9058, top5_acc: 0.9945, mean_class_accuracy: 0.8787 +2025-06-25 06:25:25,219 - pyskl - INFO - Epoch [112][100/1281] lr: 3.928e-03, eta: 6:00:36, time: 0.808, data_time: 0.185, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0862, loss: 0.0862 +2025-06-25 06:26:14,332 - pyskl - INFO - Epoch [112][200/1281] lr: 3.914e-03, eta: 5:59:54, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.0928, loss: 0.0928 +2025-06-25 06:27:03,404 - pyskl - INFO - Epoch [112][300/1281] lr: 3.899e-03, eta: 5:59:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1065, loss: 0.1065 +2025-06-25 06:27:52,703 - pyskl - INFO - Epoch [112][400/1281] lr: 3.884e-03, eta: 5:58:31, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0812, loss: 0.0812 +2025-06-25 06:28:36,169 - pyskl - INFO - Epoch [112][500/1281] lr: 3.869e-03, eta: 5:57:48, time: 0.435, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1129, loss: 0.1129 +2025-06-25 06:29:19,304 - pyskl - INFO - Epoch [112][600/1281] lr: 3.854e-03, eta: 5:57:05, time: 0.431, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.1085, loss: 0.1085 +2025-06-25 06:29:49,492 - pyskl - INFO - Epoch [112][700/1281] lr: 3.840e-03, eta: 5:56:17, time: 0.302, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.0999, loss: 0.0999 +2025-06-25 06:30:29,928 - pyskl - INFO - Epoch [112][800/1281] lr: 3.825e-03, eta: 5:55:32, time: 0.404, data_time: 0.001, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1071, loss: 0.1071 +2025-06-25 06:31:18,620 - pyskl - INFO - Epoch [112][900/1281] lr: 3.810e-03, eta: 5:54:51, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 0.1278, loss: 0.1278 +2025-06-25 06:32:07,850 - pyskl - INFO - Epoch [112][1000/1281] lr: 3.795e-03, eta: 5:54:09, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1036, loss: 0.1036 +2025-06-25 06:32:57,238 - pyskl - INFO - Epoch [112][1100/1281] lr: 3.781e-03, eta: 5:53:28, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 0.1322, loss: 0.1322 +2025-06-25 06:33:46,101 - pyskl - INFO - Epoch [112][1200/1281] lr: 3.766e-03, eta: 5:52:46, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 0.9994, loss_cls: 0.1460, loss: 0.1460 +2025-06-25 06:34:26,377 - pyskl - INFO - Saving checkpoint at 112 epochs +2025-06-25 06:35:24,636 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:35:24,691 - pyskl - INFO - +top1_acc 0.8995 +top5_acc 0.9939 +2025-06-25 06:35:24,691 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:35:24,698 - pyskl - INFO - +mean_acc 0.8662 +2025-06-25 06:35:24,700 - pyskl - INFO - Epoch(val) [112][533] top1_acc: 0.8995, top5_acc: 0.9939, mean_class_accuracy: 0.8662 +2025-06-25 06:36:43,191 - pyskl - INFO - Epoch [113][100/1281] lr: 3.740e-03, eta: 5:51:28, time: 0.785, data_time: 0.181, memory: 4083, top1_acc: 0.9844, top5_acc: 0.9994, loss_cls: 0.1266, loss: 0.1266 +2025-06-25 06:37:32,014 - pyskl - INFO - Epoch [113][200/1281] lr: 3.725e-03, eta: 5:50:46, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.0941, loss: 0.0941 +2025-06-25 06:38:21,154 - pyskl - INFO - Epoch [113][300/1281] lr: 3.711e-03, eta: 5:50:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0951, loss: 0.0951 +2025-06-25 06:39:10,069 - pyskl - INFO - Epoch [113][400/1281] lr: 3.696e-03, eta: 5:49:23, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0783, loss: 0.0783 +2025-06-25 06:39:55,518 - pyskl - INFO - Epoch [113][500/1281] lr: 3.682e-03, eta: 5:48:40, time: 0.454, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0731, loss: 0.0731 +2025-06-25 06:40:32,447 - pyskl - INFO - Epoch [113][600/1281] lr: 3.667e-03, eta: 5:47:55, time: 0.369, data_time: 0.001, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0774, loss: 0.0774 +2025-06-25 06:41:08,873 - pyskl - INFO - Epoch [113][700/1281] lr: 3.653e-03, eta: 5:47:09, time: 0.364, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1088, loss: 0.1088 +2025-06-25 06:41:46,546 - pyskl - INFO - Epoch [113][800/1281] lr: 3.638e-03, eta: 5:46:24, time: 0.377, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1067, loss: 0.1067 +2025-06-25 06:42:35,334 - pyskl - INFO - Epoch [113][900/1281] lr: 3.624e-03, eta: 5:45:42, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0733, loss: 0.0733 +2025-06-25 06:43:24,268 - pyskl - INFO - Epoch [113][1000/1281] lr: 3.610e-03, eta: 5:45:00, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0695, loss: 0.0695 +2025-06-25 06:44:13,321 - pyskl - INFO - Epoch [113][1100/1281] lr: 3.595e-03, eta: 5:44:19, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0868, loss: 0.0868 +2025-06-25 06:45:02,276 - pyskl - INFO - Epoch [113][1200/1281] lr: 3.581e-03, eta: 5:43:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0917, loss: 0.0917 +2025-06-25 06:45:42,848 - pyskl - INFO - Saving checkpoint at 113 epochs +2025-06-25 06:46:40,482 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:46:40,550 - pyskl - INFO - +top1_acc 0.9100 +top5_acc 0.9939 +2025-06-25 06:46:40,550 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:46:40,557 - pyskl - INFO - +mean_acc 0.8827 +2025-06-25 06:46:40,559 - pyskl - INFO - Epoch(val) [113][533] top1_acc: 0.9100, top5_acc: 0.9939, mean_class_accuracy: 0.8827 +2025-06-25 06:47:59,887 - pyskl - INFO - Epoch [114][100/1281] lr: 3.555e-03, eta: 5:42:19, time: 0.793, data_time: 0.183, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0597, loss: 0.0597 +2025-06-25 06:48:48,790 - pyskl - INFO - Epoch [114][200/1281] lr: 3.541e-03, eta: 5:41:37, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0766, loss: 0.0766 +2025-06-25 06:49:37,803 - pyskl - INFO - Epoch [114][300/1281] lr: 3.526e-03, eta: 5:40:56, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0778, loss: 0.0778 +2025-06-25 06:50:26,696 - pyskl - INFO - Epoch [114][400/1281] lr: 3.512e-03, eta: 5:40:14, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 0.9994, loss_cls: 0.1320, loss: 0.1320 +2025-06-25 06:51:14,763 - pyskl - INFO - Epoch [114][500/1281] lr: 3.498e-03, eta: 5:39:32, time: 0.481, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1551, loss: 0.1551 +2025-06-25 06:51:48,481 - pyskl - INFO - Epoch [114][600/1281] lr: 3.484e-03, eta: 5:38:45, time: 0.337, data_time: 0.001, memory: 4083, top1_acc: 0.9775, top5_acc: 0.9994, loss_cls: 0.1539, loss: 0.1539 +2025-06-25 06:52:28,077 - pyskl - INFO - Epoch [114][700/1281] lr: 3.470e-03, eta: 5:38:01, time: 0.396, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1173, loss: 0.1173 +2025-06-25 06:53:04,760 - pyskl - INFO - Epoch [114][800/1281] lr: 3.456e-03, eta: 5:37:15, time: 0.367, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 0.9994, loss_cls: 0.1334, loss: 0.1334 +2025-06-25 06:53:53,924 - pyskl - INFO - Epoch [114][900/1281] lr: 3.442e-03, eta: 5:36:34, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1136, loss: 0.1136 +2025-06-25 06:54:42,790 - pyskl - INFO - Epoch [114][1000/1281] lr: 3.427e-03, eta: 5:35:52, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0885, loss: 0.0885 +2025-06-25 06:55:31,799 - pyskl - INFO - Epoch [114][1100/1281] lr: 3.413e-03, eta: 5:35:10, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1192, loss: 0.1192 +2025-06-25 06:56:20,719 - pyskl - INFO - Epoch [114][1200/1281] lr: 3.399e-03, eta: 5:34:28, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.0944, loss: 0.0944 +2025-06-25 06:57:00,894 - pyskl - INFO - Saving checkpoint at 114 epochs +2025-06-25 06:57:58,263 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:57:58,331 - pyskl - INFO - +top1_acc 0.9048 +top5_acc 0.9933 +2025-06-25 06:57:58,331 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:57:58,339 - pyskl - INFO - +mean_acc 0.8788 +2025-06-25 06:57:58,341 - pyskl - INFO - Epoch(val) [114][533] top1_acc: 0.9048, top5_acc: 0.9933, mean_class_accuracy: 0.8788 +2025-06-25 06:59:17,481 - pyskl - INFO - Epoch [115][100/1281] lr: 3.374e-03, eta: 5:33:10, time: 0.791, data_time: 0.184, memory: 4083, top1_acc: 0.9756, top5_acc: 0.9988, loss_cls: 0.1618, loss: 0.1618 +2025-06-25 07:00:06,545 - pyskl - INFO - Epoch [115][200/1281] lr: 3.360e-03, eta: 5:32:28, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0868, loss: 0.0868 +2025-06-25 07:00:55,714 - pyskl - INFO - Epoch [115][300/1281] lr: 3.346e-03, eta: 5:31:47, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0810, loss: 0.0810 +2025-06-25 07:01:44,508 - pyskl - INFO - Epoch [115][400/1281] lr: 3.332e-03, eta: 5:31:05, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1106, loss: 0.1106 +2025-06-25 07:02:33,272 - pyskl - INFO - Epoch [115][500/1281] lr: 3.318e-03, eta: 5:30:23, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0848, loss: 0.0848 +2025-06-25 07:03:05,500 - pyskl - INFO - Epoch [115][600/1281] lr: 3.305e-03, eta: 5:29:36, time: 0.322, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1230, loss: 0.1230 +2025-06-25 07:03:47,157 - pyskl - INFO - Epoch [115][700/1281] lr: 3.291e-03, eta: 5:28:52, time: 0.417, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.1001, loss: 0.1001 +2025-06-25 07:04:19,535 - pyskl - INFO - Epoch [115][800/1281] lr: 3.277e-03, eta: 5:28:05, time: 0.324, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0743, loss: 0.0743 +2025-06-25 07:05:08,353 - pyskl - INFO - Epoch [115][900/1281] lr: 3.263e-03, eta: 5:27:23, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0837, loss: 0.0837 +2025-06-25 07:05:57,505 - pyskl - INFO - Epoch [115][1000/1281] lr: 3.249e-03, eta: 5:26:42, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1244, loss: 0.1244 +2025-06-25 07:06:46,261 - pyskl - INFO - Epoch [115][1100/1281] lr: 3.236e-03, eta: 5:26:00, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0819, loss: 0.0819 +2025-06-25 07:07:35,270 - pyskl - INFO - Epoch [115][1200/1281] lr: 3.222e-03, eta: 5:25:18, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0985, loss: 0.0985 +2025-06-25 07:08:15,213 - pyskl - INFO - Saving checkpoint at 115 epochs +2025-06-25 07:09:14,171 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:09:14,249 - pyskl - INFO - +top1_acc 0.9101 +top5_acc 0.9938 +2025-06-25 07:09:14,249 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:09:14,259 - pyskl - INFO - +mean_acc 0.8855 +2025-06-25 07:09:14,262 - pyskl - INFO - Epoch(val) [115][533] top1_acc: 0.9101, top5_acc: 0.9938, mean_class_accuracy: 0.8855 +2025-06-25 07:10:34,554 - pyskl - INFO - Epoch [116][100/1281] lr: 3.197e-03, eta: 5:24:00, time: 0.803, data_time: 0.189, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.0999, loss: 0.0999 +2025-06-25 07:11:23,420 - pyskl - INFO - Epoch [116][200/1281] lr: 3.184e-03, eta: 5:23:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0783, loss: 0.0783 +2025-06-25 07:12:12,622 - pyskl - INFO - Epoch [116][300/1281] lr: 3.170e-03, eta: 5:22:37, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0665, loss: 0.0665 +2025-06-25 07:13:01,387 - pyskl - INFO - Epoch [116][400/1281] lr: 3.156e-03, eta: 5:21:55, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0536, loss: 0.0536 +2025-06-25 07:13:50,162 - pyskl - INFO - Epoch [116][500/1281] lr: 3.143e-03, eta: 5:21:13, time: 0.488, data_time: 0.001, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0773, loss: 0.0773 +2025-06-25 07:14:17,715 - pyskl - INFO - Epoch [116][600/1281] lr: 3.129e-03, eta: 5:20:25, time: 0.276, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 0.9994, loss_cls: 0.0717, loss: 0.0717 +2025-06-25 07:15:05,986 - pyskl - INFO - Epoch [116][700/1281] lr: 3.116e-03, eta: 5:19:42, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0768, loss: 0.0768 +2025-06-25 07:15:37,780 - pyskl - INFO - Epoch [116][800/1281] lr: 3.102e-03, eta: 5:18:56, time: 0.318, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0792, loss: 0.0792 +2025-06-25 07:16:26,664 - pyskl - INFO - Epoch [116][900/1281] lr: 3.089e-03, eta: 5:18:14, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0609, loss: 0.0609 +2025-06-25 07:17:15,629 - pyskl - INFO - Epoch [116][1000/1281] lr: 3.075e-03, eta: 5:17:32, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0603, loss: 0.0603 +2025-06-25 07:18:04,616 - pyskl - INFO - Epoch [116][1100/1281] lr: 3.062e-03, eta: 5:16:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0716, loss: 0.0716 +2025-06-25 07:18:53,510 - pyskl - INFO - Epoch [116][1200/1281] lr: 3.049e-03, eta: 5:16:08, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0811, loss: 0.0811 +2025-06-25 07:19:33,606 - pyskl - INFO - Saving checkpoint at 116 epochs +2025-06-25 07:20:31,929 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:20:31,984 - pyskl - INFO - +top1_acc 0.9202 +top5_acc 0.9953 +2025-06-25 07:20:31,984 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:20:31,991 - pyskl - INFO - +mean_acc 0.8895 +2025-06-25 07:20:31,995 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_110.pth was removed +2025-06-25 07:20:32,371 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_116.pth. +2025-06-25 07:20:32,372 - pyskl - INFO - Best top1_acc is 0.9202 at 116 epoch. +2025-06-25 07:20:32,374 - pyskl - INFO - Epoch(val) [116][533] top1_acc: 0.9202, top5_acc: 0.9953, mean_class_accuracy: 0.8895 +2025-06-25 07:21:52,555 - pyskl - INFO - Epoch [117][100/1281] lr: 3.024e-03, eta: 5:14:50, time: 0.802, data_time: 0.186, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0769, loss: 0.0769 +2025-06-25 07:22:41,389 - pyskl - INFO - Epoch [117][200/1281] lr: 3.011e-03, eta: 5:14:08, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0763, loss: 0.0763 +2025-06-25 07:23:30,497 - pyskl - INFO - Epoch [117][300/1281] lr: 2.998e-03, eta: 5:13:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0765, loss: 0.0765 +2025-06-25 07:24:19,533 - pyskl - INFO - Epoch [117][400/1281] lr: 2.984e-03, eta: 5:12:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0756, loss: 0.0756 +2025-06-25 07:25:08,304 - pyskl - INFO - Epoch [117][500/1281] lr: 2.971e-03, eta: 5:12:02, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0638, loss: 0.0638 +2025-06-25 07:25:35,651 - pyskl - INFO - Epoch [117][600/1281] lr: 2.958e-03, eta: 5:11:14, time: 0.273, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0582, loss: 0.0582 +2025-06-25 07:26:25,795 - pyskl - INFO - Epoch [117][700/1281] lr: 2.945e-03, eta: 5:10:33, time: 0.501, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0636, loss: 0.0636 +2025-06-25 07:26:56,238 - pyskl - INFO - Epoch [117][800/1281] lr: 2.932e-03, eta: 5:09:45, time: 0.304, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0574, loss: 0.0574 +2025-06-25 07:27:44,711 - pyskl - INFO - Epoch [117][900/1281] lr: 2.919e-03, eta: 5:09:03, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0541, loss: 0.0541 +2025-06-25 07:28:33,878 - pyskl - INFO - Epoch [117][1000/1281] lr: 2.905e-03, eta: 5:08:22, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0573, loss: 0.0573 +2025-06-25 07:29:22,690 - pyskl - INFO - Epoch [117][1100/1281] lr: 2.892e-03, eta: 5:07:40, time: 0.488, data_time: 0.001, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0610, loss: 0.0610 +2025-06-25 07:30:11,802 - pyskl - INFO - Epoch [117][1200/1281] lr: 2.879e-03, eta: 5:06:58, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 0.9994, loss_cls: 0.0655, loss: 0.0655 +2025-06-25 07:30:52,291 - pyskl - INFO - Saving checkpoint at 117 epochs +2025-06-25 07:31:50,728 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:31:50,790 - pyskl - INFO - +top1_acc 0.9218 +top5_acc 0.9957 +2025-06-25 07:31:50,790 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:31:50,798 - pyskl - INFO - +mean_acc 0.8947 +2025-06-25 07:31:50,802 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_116.pth was removed +2025-06-25 07:31:50,976 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_117.pth. +2025-06-25 07:31:50,976 - pyskl - INFO - Best top1_acc is 0.9218 at 117 epoch. +2025-06-25 07:31:50,979 - pyskl - INFO - Epoch(val) [117][533] top1_acc: 0.9218, top5_acc: 0.9957, mean_class_accuracy: 0.8947 +2025-06-25 07:33:12,442 - pyskl - INFO - Epoch [118][100/1281] lr: 2.856e-03, eta: 5:05:40, time: 0.815, data_time: 0.190, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0479, loss: 0.0479 +2025-06-25 07:34:01,499 - pyskl - INFO - Epoch [118][200/1281] lr: 2.843e-03, eta: 5:04:58, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0518, loss: 0.0518 +2025-06-25 07:34:50,540 - pyskl - INFO - Epoch [118][300/1281] lr: 2.830e-03, eta: 5:04:16, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0638, loss: 0.0638 +2025-06-25 07:35:39,406 - pyskl - INFO - Epoch [118][400/1281] lr: 2.817e-03, eta: 5:03:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0563, loss: 0.0563 +2025-06-25 07:36:28,192 - pyskl - INFO - Epoch [118][500/1281] lr: 2.804e-03, eta: 5:02:52, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0531, loss: 0.0531 +2025-06-25 07:36:56,335 - pyskl - INFO - Epoch [118][600/1281] lr: 2.791e-03, eta: 5:02:04, time: 0.281, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0753, loss: 0.0753 +2025-06-25 07:37:45,549 - pyskl - INFO - Epoch [118][700/1281] lr: 2.778e-03, eta: 5:01:22, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0476, loss: 0.0476 +2025-06-25 07:38:16,301 - pyskl - INFO - Epoch [118][800/1281] lr: 2.765e-03, eta: 5:00:35, time: 0.308, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0506, loss: 0.0506 +2025-06-25 07:39:05,083 - pyskl - INFO - Epoch [118][900/1281] lr: 2.753e-03, eta: 4:59:53, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0723, loss: 0.0723 +2025-06-25 07:39:54,094 - pyskl - INFO - Epoch [118][1000/1281] lr: 2.740e-03, eta: 4:59:11, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0455, loss: 0.0455 +2025-06-25 07:40:43,104 - pyskl - INFO - Epoch [118][1100/1281] lr: 2.727e-03, eta: 4:58:29, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.0886, loss: 0.0886 +2025-06-25 07:41:31,856 - pyskl - INFO - Epoch [118][1200/1281] lr: 2.714e-03, eta: 4:57:47, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0616, loss: 0.0616 +2025-06-25 07:42:11,850 - pyskl - INFO - Saving checkpoint at 118 epochs +2025-06-25 07:43:09,598 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:43:09,653 - pyskl - INFO - +top1_acc 0.9242 +top5_acc 0.9950 +2025-06-25 07:43:09,653 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:43:09,660 - pyskl - INFO - +mean_acc 0.8947 +2025-06-25 07:43:09,664 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_117.pth was removed +2025-06-25 07:43:10,051 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_118.pth. +2025-06-25 07:43:10,051 - pyskl - INFO - Best top1_acc is 0.9242 at 118 epoch. +2025-06-25 07:43:10,054 - pyskl - INFO - Epoch(val) [118][533] top1_acc: 0.9242, top5_acc: 0.9950, mean_class_accuracy: 0.8947 +2025-06-25 07:44:29,176 - pyskl - INFO - Epoch [119][100/1281] lr: 2.691e-03, eta: 4:56:28, time: 0.791, data_time: 0.185, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0735, loss: 0.0735 +2025-06-25 07:45:18,023 - pyskl - INFO - Epoch [119][200/1281] lr: 2.679e-03, eta: 4:55:46, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0678, loss: 0.0678 +2025-06-25 07:46:06,962 - pyskl - INFO - Epoch [119][300/1281] lr: 2.666e-03, eta: 4:55:04, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0442, loss: 0.0442 +2025-06-25 07:46:56,431 - pyskl - INFO - Epoch [119][400/1281] lr: 2.653e-03, eta: 4:54:22, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0534, loss: 0.0534 +2025-06-25 07:47:45,044 - pyskl - INFO - Epoch [119][500/1281] lr: 2.641e-03, eta: 4:53:40, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0739, loss: 0.0739 +2025-06-25 07:48:14,163 - pyskl - INFO - Epoch [119][600/1281] lr: 2.628e-03, eta: 4:52:53, time: 0.291, data_time: 0.001, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0725, loss: 0.0725 +2025-06-25 07:49:05,193 - pyskl - INFO - Epoch [119][700/1281] lr: 2.616e-03, eta: 4:52:11, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0687, loss: 0.0687 +2025-06-25 07:49:33,131 - pyskl - INFO - Epoch [119][800/1281] lr: 2.603e-03, eta: 4:51:24, time: 0.279, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0657, loss: 0.0657 +2025-06-25 07:50:21,935 - pyskl - INFO - Epoch [119][900/1281] lr: 2.591e-03, eta: 4:50:42, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0756, loss: 0.0756 +2025-06-25 07:51:11,277 - pyskl - INFO - Epoch [119][1000/1281] lr: 2.578e-03, eta: 4:50:00, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0833, loss: 0.0833 +2025-06-25 07:51:59,976 - pyskl - INFO - Epoch [119][1100/1281] lr: 2.566e-03, eta: 4:49:18, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0801, loss: 0.0801 +2025-06-25 07:52:48,764 - pyskl - INFO - Epoch [119][1200/1281] lr: 2.554e-03, eta: 4:48:35, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0793, loss: 0.0793 +2025-06-25 07:53:29,061 - pyskl - INFO - Saving checkpoint at 119 epochs +2025-06-25 07:54:27,728 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:54:27,785 - pyskl - INFO - +top1_acc 0.9176 +top5_acc 0.9950 +2025-06-25 07:54:27,785 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:54:27,792 - pyskl - INFO - +mean_acc 0.8855 +2025-06-25 07:54:27,794 - pyskl - INFO - Epoch(val) [119][533] top1_acc: 0.9176, top5_acc: 0.9950, mean_class_accuracy: 0.8855 +2025-06-25 07:55:48,508 - pyskl - INFO - Epoch [120][100/1281] lr: 2.531e-03, eta: 4:47:17, time: 0.807, data_time: 0.193, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0767, loss: 0.0767 +2025-06-25 07:56:37,619 - pyskl - INFO - Epoch [120][200/1281] lr: 2.519e-03, eta: 4:46:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0459, loss: 0.0459 +2025-06-25 07:57:26,175 - pyskl - INFO - Epoch [120][300/1281] lr: 2.507e-03, eta: 4:45:53, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0539, loss: 0.0539 +2025-06-25 07:58:14,947 - pyskl - INFO - Epoch [120][400/1281] lr: 2.494e-03, eta: 4:45:11, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0540, loss: 0.0540 +2025-06-25 07:59:03,940 - pyskl - INFO - Epoch [120][500/1281] lr: 2.482e-03, eta: 4:44:29, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0429, loss: 0.0429 +2025-06-25 07:59:33,374 - pyskl - INFO - Epoch [120][600/1281] lr: 2.470e-03, eta: 4:43:41, time: 0.294, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0383, loss: 0.0383 +2025-06-25 08:00:24,425 - pyskl - INFO - Epoch [120][700/1281] lr: 2.458e-03, eta: 4:43:00, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0404, loss: 0.0404 +2025-06-25 08:00:51,780 - pyskl - INFO - Epoch [120][800/1281] lr: 2.446e-03, eta: 4:42:12, time: 0.274, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0657, loss: 0.0657 +2025-06-25 08:01:40,838 - pyskl - INFO - Epoch [120][900/1281] lr: 2.433e-03, eta: 4:41:30, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0524, loss: 0.0524 +2025-06-25 08:02:29,870 - pyskl - INFO - Epoch [120][1000/1281] lr: 2.421e-03, eta: 4:40:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0505, loss: 0.0505 +2025-06-25 08:03:18,837 - pyskl - INFO - Epoch [120][1100/1281] lr: 2.409e-03, eta: 4:40:06, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0447, loss: 0.0447 +2025-06-25 08:04:08,079 - pyskl - INFO - Epoch [120][1200/1281] lr: 2.397e-03, eta: 4:39:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0522, loss: 0.0522 +2025-06-25 08:04:48,514 - pyskl - INFO - Saving checkpoint at 120 epochs +2025-06-25 08:05:47,019 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:05:47,086 - pyskl - INFO - +top1_acc 0.9230 +top5_acc 0.9945 +2025-06-25 08:05:47,086 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:05:47,096 - pyskl - INFO - +mean_acc 0.8936 +2025-06-25 08:05:47,099 - pyskl - INFO - Epoch(val) [120][533] top1_acc: 0.9230, top5_acc: 0.9945, mean_class_accuracy: 0.8936 +2025-06-25 08:07:07,649 - pyskl - INFO - Epoch [121][100/1281] lr: 2.375e-03, eta: 4:38:05, time: 0.805, data_time: 0.191, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0457, loss: 0.0457 +2025-06-25 08:07:56,447 - pyskl - INFO - Epoch [121][200/1281] lr: 2.363e-03, eta: 4:37:23, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0343, loss: 0.0343 +2025-06-25 08:08:45,298 - pyskl - INFO - Epoch [121][300/1281] lr: 2.351e-03, eta: 4:36:41, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0362, loss: 0.0362 +2025-06-25 08:09:34,159 - pyskl - INFO - Epoch [121][400/1281] lr: 2.340e-03, eta: 4:35:59, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0316, loss: 0.0316 +2025-06-25 08:10:23,004 - pyskl - INFO - Epoch [121][500/1281] lr: 2.328e-03, eta: 4:35:16, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0374, loss: 0.0374 +2025-06-25 08:10:53,112 - pyskl - INFO - Epoch [121][600/1281] lr: 2.316e-03, eta: 4:34:30, time: 0.301, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0281, loss: 0.0281 +2025-06-25 08:11:44,242 - pyskl - INFO - Epoch [121][700/1281] lr: 2.304e-03, eta: 4:33:48, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0492, loss: 0.0492 +2025-06-25 08:12:09,865 - pyskl - INFO - Epoch [121][800/1281] lr: 2.292e-03, eta: 4:33:00, time: 0.256, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0258, loss: 0.0258 +2025-06-25 08:12:58,200 - pyskl - INFO - Epoch [121][900/1281] lr: 2.280e-03, eta: 4:32:18, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0338, loss: 0.0338 +2025-06-25 08:13:46,996 - pyskl - INFO - Epoch [121][1000/1281] lr: 2.269e-03, eta: 4:31:35, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0290, loss: 0.0290 +2025-06-25 08:14:36,053 - pyskl - INFO - Epoch [121][1100/1281] lr: 2.257e-03, eta: 4:30:53, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0383, loss: 0.0383 +2025-06-25 08:15:25,483 - pyskl - INFO - Epoch [121][1200/1281] lr: 2.245e-03, eta: 4:30:11, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0430, loss: 0.0430 +2025-06-25 08:16:05,541 - pyskl - INFO - Saving checkpoint at 121 epochs +2025-06-25 08:17:03,150 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:17:03,208 - pyskl - INFO - +top1_acc 0.9234 +top5_acc 0.9953 +2025-06-25 08:17:03,208 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:17:03,216 - pyskl - INFO - +mean_acc 0.8953 +2025-06-25 08:17:03,218 - pyskl - INFO - Epoch(val) [121][533] top1_acc: 0.9234, top5_acc: 0.9953, mean_class_accuracy: 0.8953 +2025-06-25 08:18:22,815 - pyskl - INFO - Epoch [122][100/1281] lr: 2.224e-03, eta: 4:28:52, time: 0.796, data_time: 0.190, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0386, loss: 0.0386 +2025-06-25 08:19:11,353 - pyskl - INFO - Epoch [122][200/1281] lr: 2.212e-03, eta: 4:28:10, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0326, loss: 0.0326 +2025-06-25 08:20:00,283 - pyskl - INFO - Epoch [122][300/1281] lr: 2.201e-03, eta: 4:27:28, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0310, loss: 0.0310 +2025-06-25 08:20:49,124 - pyskl - INFO - Epoch [122][400/1281] lr: 2.189e-03, eta: 4:26:46, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0318, loss: 0.0318 +2025-06-25 08:21:38,073 - pyskl - INFO - Epoch [122][500/1281] lr: 2.178e-03, eta: 4:26:03, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0350, loss: 0.0350 +2025-06-25 08:22:12,334 - pyskl - INFO - Epoch [122][600/1281] lr: 2.166e-03, eta: 4:25:17, time: 0.343, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0269, loss: 0.0269 +2025-06-25 08:23:03,499 - pyskl - INFO - Epoch [122][700/1281] lr: 2.155e-03, eta: 4:24:36, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0280, loss: 0.0280 +2025-06-25 08:23:28,495 - pyskl - INFO - Epoch [122][800/1281] lr: 2.143e-03, eta: 4:23:48, time: 0.250, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0286, loss: 0.0286 +2025-06-25 08:24:14,761 - pyskl - INFO - Epoch [122][900/1281] lr: 2.132e-03, eta: 4:23:05, time: 0.463, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0325, loss: 0.0325 +2025-06-25 08:25:04,015 - pyskl - INFO - Epoch [122][1000/1281] lr: 2.120e-03, eta: 4:22:23, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0324, loss: 0.0324 +2025-06-25 08:25:52,873 - pyskl - INFO - Epoch [122][1100/1281] lr: 2.109e-03, eta: 4:21:40, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0372, loss: 0.0372 +2025-06-25 08:26:41,623 - pyskl - INFO - Epoch [122][1200/1281] lr: 2.098e-03, eta: 4:20:58, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0360, loss: 0.0360 +2025-06-25 08:27:21,547 - pyskl - INFO - Saving checkpoint at 122 epochs +2025-06-25 08:28:19,467 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:28:19,523 - pyskl - INFO - +top1_acc 0.9245 +top5_acc 0.9957 +2025-06-25 08:28:19,523 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:28:19,530 - pyskl - INFO - +mean_acc 0.8995 +2025-06-25 08:28:19,534 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_118.pth was removed +2025-06-25 08:28:19,709 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_122.pth. +2025-06-25 08:28:19,709 - pyskl - INFO - Best top1_acc is 0.9245 at 122 epoch. +2025-06-25 08:28:19,712 - pyskl - INFO - Epoch(val) [122][533] top1_acc: 0.9245, top5_acc: 0.9957, mean_class_accuracy: 0.8995 +2025-06-25 08:29:39,317 - pyskl - INFO - Epoch [123][100/1281] lr: 2.077e-03, eta: 4:19:39, time: 0.796, data_time: 0.192, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0549, loss: 0.0549 +2025-06-25 08:30:27,997 - pyskl - INFO - Epoch [123][200/1281] lr: 2.066e-03, eta: 4:18:57, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0419, loss: 0.0419 +2025-06-25 08:31:17,283 - pyskl - INFO - Epoch [123][300/1281] lr: 2.055e-03, eta: 4:18:15, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0337, loss: 0.0337 +2025-06-25 08:32:06,438 - pyskl - INFO - Epoch [123][400/1281] lr: 2.044e-03, eta: 4:17:32, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0394, loss: 0.0394 +2025-06-25 08:32:55,132 - pyskl - INFO - Epoch [123][500/1281] lr: 2.032e-03, eta: 4:16:50, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0283, loss: 0.0283 +2025-06-25 08:33:32,038 - pyskl - INFO - Epoch [123][600/1281] lr: 2.021e-03, eta: 4:16:05, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 0.9994, loss_cls: 0.0417, loss: 0.0417 +2025-06-25 08:34:23,169 - pyskl - INFO - Epoch [123][700/1281] lr: 2.010e-03, eta: 4:15:23, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0321, loss: 0.0321 +2025-06-25 08:34:47,664 - pyskl - INFO - Epoch [123][800/1281] lr: 1.999e-03, eta: 4:14:35, time: 0.245, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0500, loss: 0.0500 +2025-06-25 08:35:33,067 - pyskl - INFO - Epoch [123][900/1281] lr: 1.988e-03, eta: 4:13:52, time: 0.454, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0548, loss: 0.0548 +2025-06-25 08:36:21,912 - pyskl - INFO - Epoch [123][1000/1281] lr: 1.977e-03, eta: 4:13:10, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0516, loss: 0.0516 +2025-06-25 08:37:10,669 - pyskl - INFO - Epoch [123][1100/1281] lr: 1.966e-03, eta: 4:12:27, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0520, loss: 0.0520 +2025-06-25 08:37:59,869 - pyskl - INFO - Epoch [123][1200/1281] lr: 1.955e-03, eta: 4:11:45, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0546, loss: 0.0546 +2025-06-25 08:38:39,988 - pyskl - INFO - Saving checkpoint at 123 epochs +2025-06-25 08:39:38,672 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:39:38,736 - pyskl - INFO - +top1_acc 0.9220 +top5_acc 0.9948 +2025-06-25 08:39:38,737 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:39:38,746 - pyskl - INFO - +mean_acc 0.8957 +2025-06-25 08:39:38,749 - pyskl - INFO - Epoch(val) [123][533] top1_acc: 0.9220, top5_acc: 0.9948, mean_class_accuracy: 0.8957 +2025-06-25 08:40:58,377 - pyskl - INFO - Epoch [124][100/1281] lr: 1.935e-03, eta: 4:10:26, time: 0.796, data_time: 0.193, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0441, loss: 0.0441 +2025-06-25 08:41:47,311 - pyskl - INFO - Epoch [124][200/1281] lr: 1.924e-03, eta: 4:09:44, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0418, loss: 0.0418 +2025-06-25 08:42:36,309 - pyskl - INFO - Epoch [124][300/1281] lr: 1.913e-03, eta: 4:09:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0407, loss: 0.0407 +2025-06-25 08:43:25,268 - pyskl - INFO - Epoch [124][400/1281] lr: 1.902e-03, eta: 4:08:19, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0352, loss: 0.0352 +2025-06-25 08:44:14,185 - pyskl - INFO - Epoch [124][500/1281] lr: 1.892e-03, eta: 4:07:37, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0410, loss: 0.0410 +2025-06-25 08:44:51,210 - pyskl - INFO - Epoch [124][600/1281] lr: 1.881e-03, eta: 4:06:52, time: 0.370, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0438, loss: 0.0438 +2025-06-25 08:45:42,262 - pyskl - INFO - Epoch [124][700/1281] lr: 1.870e-03, eta: 4:06:10, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0302, loss: 0.0302 +2025-06-25 08:46:06,560 - pyskl - INFO - Epoch [124][800/1281] lr: 1.859e-03, eta: 4:05:22, time: 0.243, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0281, loss: 0.0281 +2025-06-25 08:46:52,940 - pyskl - INFO - Epoch [124][900/1281] lr: 1.849e-03, eta: 4:04:39, time: 0.464, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0312, loss: 0.0312 +2025-06-25 08:47:42,249 - pyskl - INFO - Epoch [124][1000/1281] lr: 1.838e-03, eta: 4:03:57, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0346, loss: 0.0346 +2025-06-25 08:48:31,229 - pyskl - INFO - Epoch [124][1100/1281] lr: 1.827e-03, eta: 4:03:14, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0227, loss: 0.0227 +2025-06-25 08:49:19,934 - pyskl - INFO - Epoch [124][1200/1281] lr: 1.817e-03, eta: 4:02:32, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0296, loss: 0.0296 +2025-06-25 08:50:00,509 - pyskl - INFO - Saving checkpoint at 124 epochs +2025-06-25 08:50:58,564 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:50:58,618 - pyskl - INFO - +top1_acc 0.9271 +top5_acc 0.9947 +2025-06-25 08:50:58,619 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:50:58,626 - pyskl - INFO - +mean_acc 0.9020 +2025-06-25 08:50:58,631 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_122.pth was removed +2025-06-25 08:50:58,802 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_124.pth. +2025-06-25 08:50:58,802 - pyskl - INFO - Best top1_acc is 0.9271 at 124 epoch. +2025-06-25 08:50:58,805 - pyskl - INFO - Epoch(val) [124][533] top1_acc: 0.9271, top5_acc: 0.9947, mean_class_accuracy: 0.9020 +2025-06-25 08:52:17,256 - pyskl - INFO - Epoch [125][100/1281] lr: 1.797e-03, eta: 4:01:13, time: 0.784, data_time: 0.185, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0224, loss: 0.0224 +2025-06-25 08:53:06,022 - pyskl - INFO - Epoch [125][200/1281] lr: 1.787e-03, eta: 4:00:30, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0348, loss: 0.0348 +2025-06-25 08:53:54,882 - pyskl - INFO - Epoch [125][300/1281] lr: 1.776e-03, eta: 3:59:48, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0263, loss: 0.0263 +2025-06-25 08:54:44,014 - pyskl - INFO - Epoch [125][400/1281] lr: 1.766e-03, eta: 3:59:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0279, loss: 0.0279 +2025-06-25 08:55:33,139 - pyskl - INFO - Epoch [125][500/1281] lr: 1.755e-03, eta: 3:58:23, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0298, loss: 0.0298 +2025-06-25 08:56:11,639 - pyskl - INFO - Epoch [125][600/1281] lr: 1.745e-03, eta: 3:57:38, time: 0.385, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0302, loss: 0.0302 +2025-06-25 08:57:02,463 - pyskl - INFO - Epoch [125][700/1281] lr: 1.735e-03, eta: 3:56:56, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0355, loss: 0.0355 +2025-06-25 08:57:26,200 - pyskl - INFO - Epoch [125][800/1281] lr: 1.724e-03, eta: 3:56:08, time: 0.237, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0243, loss: 0.0243 +2025-06-25 08:58:10,834 - pyskl - INFO - Epoch [125][900/1281] lr: 1.714e-03, eta: 3:55:25, time: 0.446, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0255, loss: 0.0255 +2025-06-25 08:58:59,872 - pyskl - INFO - Epoch [125][1000/1281] lr: 1.704e-03, eta: 3:54:42, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0272, loss: 0.0272 +2025-06-25 08:59:49,013 - pyskl - INFO - Epoch [125][1100/1281] lr: 1.693e-03, eta: 3:54:00, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0305, loss: 0.0305 +2025-06-25 09:00:37,847 - pyskl - INFO - Epoch [125][1200/1281] lr: 1.683e-03, eta: 3:53:17, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0289, loss: 0.0289 +2025-06-25 09:01:18,004 - pyskl - INFO - Saving checkpoint at 125 epochs +2025-06-25 09:02:15,637 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:02:15,692 - pyskl - INFO - +top1_acc 0.9211 +top5_acc 0.9955 +2025-06-25 09:02:15,692 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:02:15,698 - pyskl - INFO - +mean_acc 0.8958 +2025-06-25 09:02:15,700 - pyskl - INFO - Epoch(val) [125][533] top1_acc: 0.9211, top5_acc: 0.9955, mean_class_accuracy: 0.8958 +2025-06-25 09:03:34,162 - pyskl - INFO - Epoch [126][100/1281] lr: 1.665e-03, eta: 3:51:58, time: 0.785, data_time: 0.186, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0326, loss: 0.0326 +2025-06-25 09:04:23,354 - pyskl - INFO - Epoch [126][200/1281] lr: 1.654e-03, eta: 3:51:16, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0263, loss: 0.0263 +2025-06-25 09:05:12,181 - pyskl - INFO - Epoch [126][300/1281] lr: 1.644e-03, eta: 3:50:33, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0247, loss: 0.0247 +2025-06-25 09:06:01,198 - pyskl - INFO - Epoch [126][400/1281] lr: 1.634e-03, eta: 3:49:51, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0247, loss: 0.0247 +2025-06-25 09:06:50,081 - pyskl - INFO - Epoch [126][500/1281] lr: 1.624e-03, eta: 3:49:08, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0262, loss: 0.0262 +2025-06-25 09:07:30,210 - pyskl - INFO - Epoch [126][600/1281] lr: 1.614e-03, eta: 3:48:24, time: 0.401, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0266, loss: 0.0266 +2025-06-25 09:08:19,451 - pyskl - INFO - Epoch [126][700/1281] lr: 1.604e-03, eta: 3:47:41, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0236, loss: 0.0236 +2025-06-25 09:08:43,812 - pyskl - INFO - Epoch [126][800/1281] lr: 1.594e-03, eta: 3:46:54, time: 0.244, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-25 09:09:26,888 - pyskl - INFO - Epoch [126][900/1281] lr: 1.584e-03, eta: 3:46:10, time: 0.431, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0231, loss: 0.0231 +2025-06-25 09:10:16,183 - pyskl - INFO - Epoch [126][1000/1281] lr: 1.574e-03, eta: 3:45:28, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0232, loss: 0.0232 +2025-06-25 09:11:05,292 - pyskl - INFO - Epoch [126][1100/1281] lr: 1.564e-03, eta: 3:44:45, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0227, loss: 0.0227 +2025-06-25 09:11:54,196 - pyskl - INFO - Epoch [126][1200/1281] lr: 1.554e-03, eta: 3:44:03, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0224, loss: 0.0224 +2025-06-25 09:12:34,306 - pyskl - INFO - Saving checkpoint at 126 epochs +2025-06-25 09:13:32,775 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:13:32,833 - pyskl - INFO - +top1_acc 0.9283 +top5_acc 0.9960 +2025-06-25 09:13:32,833 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:13:32,839 - pyskl - INFO - +mean_acc 0.9022 +2025-06-25 09:13:32,843 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_124.pth was removed +2025-06-25 09:13:33,005 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_126.pth. +2025-06-25 09:13:33,005 - pyskl - INFO - Best top1_acc is 0.9283 at 126 epoch. +2025-06-25 09:13:33,008 - pyskl - INFO - Epoch(val) [126][533] top1_acc: 0.9283, top5_acc: 0.9960, mean_class_accuracy: 0.9022 +2025-06-25 09:14:51,294 - pyskl - INFO - Epoch [127][100/1281] lr: 1.536e-03, eta: 3:42:44, time: 0.783, data_time: 0.183, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0247, loss: 0.0247 +2025-06-25 09:15:40,278 - pyskl - INFO - Epoch [127][200/1281] lr: 1.527e-03, eta: 3:42:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-25 09:16:29,411 - pyskl - INFO - Epoch [127][300/1281] lr: 1.517e-03, eta: 3:41:18, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0238, loss: 0.0238 +2025-06-25 09:17:18,421 - pyskl - INFO - Epoch [127][400/1281] lr: 1.507e-03, eta: 3:40:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0224, loss: 0.0224 +2025-06-25 09:18:07,387 - pyskl - INFO - Epoch [127][500/1281] lr: 1.497e-03, eta: 3:39:53, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0293, loss: 0.0293 +2025-06-25 09:18:49,909 - pyskl - INFO - Epoch [127][600/1281] lr: 1.488e-03, eta: 3:39:09, time: 0.425, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0226, loss: 0.0226 +2025-06-25 09:19:33,689 - pyskl - INFO - Epoch [127][700/1281] lr: 1.478e-03, eta: 3:38:26, time: 0.438, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0272, loss: 0.0272 +2025-06-25 09:20:03,092 - pyskl - INFO - Epoch [127][800/1281] lr: 1.468e-03, eta: 3:37:40, time: 0.294, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0294, loss: 0.0294 +2025-06-25 09:20:45,226 - pyskl - INFO - Epoch [127][900/1281] lr: 1.459e-03, eta: 3:36:56, time: 0.421, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0291, loss: 0.0291 +2025-06-25 09:21:34,307 - pyskl - INFO - Epoch [127][1000/1281] lr: 1.449e-03, eta: 3:36:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0288, loss: 0.0288 +2025-06-25 09:22:23,366 - pyskl - INFO - Epoch [127][1100/1281] lr: 1.440e-03, eta: 3:35:30, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0220, loss: 0.0220 +2025-06-25 09:23:12,413 - pyskl - INFO - Epoch [127][1200/1281] lr: 1.430e-03, eta: 3:34:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0215, loss: 0.0215 +2025-06-25 09:23:52,909 - pyskl - INFO - Saving checkpoint at 127 epochs +2025-06-25 09:24:50,705 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:24:50,761 - pyskl - INFO - +top1_acc 0.9299 +top5_acc 0.9955 +2025-06-25 09:24:50,761 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:24:50,767 - pyskl - INFO - +mean_acc 0.9036 +2025-06-25 09:24:50,771 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_126.pth was removed +2025-06-25 09:24:50,933 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_127.pth. +2025-06-25 09:24:50,933 - pyskl - INFO - Best top1_acc is 0.9299 at 127 epoch. +2025-06-25 09:24:50,936 - pyskl - INFO - Epoch(val) [127][533] top1_acc: 0.9299, top5_acc: 0.9955, mean_class_accuracy: 0.9036 +2025-06-25 09:26:10,125 - pyskl - INFO - Epoch [128][100/1281] lr: 1.413e-03, eta: 3:33:29, time: 0.792, data_time: 0.182, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0245, loss: 0.0245 +2025-06-25 09:26:59,541 - pyskl - INFO - Epoch [128][200/1281] lr: 1.404e-03, eta: 3:32:46, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0247, loss: 0.0247 +2025-06-25 09:27:48,439 - pyskl - INFO - Epoch [128][300/1281] lr: 1.394e-03, eta: 3:32:04, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0383, loss: 0.0383 +2025-06-25 09:28:37,330 - pyskl - INFO - Epoch [128][400/1281] lr: 1.385e-03, eta: 3:31:21, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0244, loss: 0.0244 +2025-06-25 09:29:25,989 - pyskl - INFO - Epoch [128][500/1281] lr: 1.376e-03, eta: 3:30:38, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 09:30:10,360 - pyskl - INFO - Epoch [128][600/1281] lr: 1.366e-03, eta: 3:29:55, time: 0.444, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 09:30:52,196 - pyskl - INFO - Epoch [128][700/1281] lr: 1.357e-03, eta: 3:29:11, time: 0.418, data_time: 0.001, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 09:31:23,224 - pyskl - INFO - Epoch [128][800/1281] lr: 1.348e-03, eta: 3:28:25, time: 0.310, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 09:32:03,785 - pyskl - INFO - Epoch [128][900/1281] lr: 1.339e-03, eta: 3:27:41, time: 0.406, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0235, loss: 0.0235 +2025-06-25 09:32:52,497 - pyskl - INFO - Epoch [128][1000/1281] lr: 1.329e-03, eta: 3:26:58, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 09:33:41,810 - pyskl - INFO - Epoch [128][1100/1281] lr: 1.320e-03, eta: 3:26:15, time: 0.493, data_time: 0.001, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0231, loss: 0.0231 +2025-06-25 09:34:31,151 - pyskl - INFO - Epoch [128][1200/1281] lr: 1.311e-03, eta: 3:25:33, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0278, loss: 0.0278 +2025-06-25 09:35:11,193 - pyskl - INFO - Saving checkpoint at 128 epochs +2025-06-25 09:36:09,386 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:36:09,441 - pyskl - INFO - +top1_acc 0.9292 +top5_acc 0.9967 +2025-06-25 09:36:09,441 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:36:09,447 - pyskl - INFO - +mean_acc 0.9012 +2025-06-25 09:36:09,449 - pyskl - INFO - Epoch(val) [128][533] top1_acc: 0.9292, top5_acc: 0.9967, mean_class_accuracy: 0.9012 +2025-06-25 09:37:27,594 - pyskl - INFO - Epoch [129][100/1281] lr: 1.295e-03, eta: 3:24:14, time: 0.781, data_time: 0.183, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0251, loss: 0.0251 +2025-06-25 09:38:16,434 - pyskl - INFO - Epoch [129][200/1281] lr: 1.286e-03, eta: 3:23:31, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 09:39:05,801 - pyskl - INFO - Epoch [129][300/1281] lr: 1.277e-03, eta: 3:22:48, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 09:39:55,072 - pyskl - INFO - Epoch [129][400/1281] lr: 1.268e-03, eta: 3:22:05, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0205, loss: 0.0205 +2025-06-25 09:40:43,903 - pyskl - INFO - Epoch [129][500/1281] lr: 1.259e-03, eta: 3:21:23, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0251, loss: 0.0251 +2025-06-25 09:41:29,057 - pyskl - INFO - Epoch [129][600/1281] lr: 1.250e-03, eta: 3:20:39, time: 0.452, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0320, loss: 0.0320 +2025-06-25 09:42:09,991 - pyskl - INFO - Epoch [129][700/1281] lr: 1.241e-03, eta: 3:19:55, time: 0.409, data_time: 0.001, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0236, loss: 0.0236 +2025-06-25 09:42:42,358 - pyskl - INFO - Epoch [129][800/1281] lr: 1.232e-03, eta: 3:19:10, time: 0.324, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0252, loss: 0.0252 +2025-06-25 09:43:23,020 - pyskl - INFO - Epoch [129][900/1281] lr: 1.223e-03, eta: 3:18:26, time: 0.407, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 09:44:11,770 - pyskl - INFO - Epoch [129][1000/1281] lr: 1.214e-03, eta: 3:17:43, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 09:45:00,482 - pyskl - INFO - Epoch [129][1100/1281] lr: 1.206e-03, eta: 3:17:00, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-25 09:45:49,290 - pyskl - INFO - Epoch [129][1200/1281] lr: 1.197e-03, eta: 3:16:17, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-25 09:46:29,581 - pyskl - INFO - Saving checkpoint at 129 epochs +2025-06-25 09:47:27,879 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:47:27,936 - pyskl - INFO - +top1_acc 0.9346 +top5_acc 0.9965 +2025-06-25 09:47:27,936 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:47:27,943 - pyskl - INFO - +mean_acc 0.9099 +2025-06-25 09:47:27,948 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_127.pth was removed +2025-06-25 09:47:28,124 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_129.pth. +2025-06-25 09:47:28,124 - pyskl - INFO - Best top1_acc is 0.9346 at 129 epoch. +2025-06-25 09:47:28,127 - pyskl - INFO - Epoch(val) [129][533] top1_acc: 0.9346, top5_acc: 0.9965, mean_class_accuracy: 0.9099 +2025-06-25 09:48:47,220 - pyskl - INFO - Epoch [130][100/1281] lr: 1.181e-03, eta: 3:14:58, time: 0.791, data_time: 0.183, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 09:49:36,385 - pyskl - INFO - Epoch [130][200/1281] lr: 1.172e-03, eta: 3:14:15, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 09:50:25,689 - pyskl - INFO - Epoch [130][300/1281] lr: 1.164e-03, eta: 3:13:33, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 09:51:14,696 - pyskl - INFO - Epoch [130][400/1281] lr: 1.155e-03, eta: 3:12:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0217, loss: 0.0217 +2025-06-25 09:52:03,777 - pyskl - INFO - Epoch [130][500/1281] lr: 1.147e-03, eta: 3:12:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0275, loss: 0.0275 +2025-06-25 09:52:47,568 - pyskl - INFO - Epoch [130][600/1281] lr: 1.138e-03, eta: 3:11:23, time: 0.438, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 09:53:30,116 - pyskl - INFO - Epoch [130][700/1281] lr: 1.130e-03, eta: 3:10:40, time: 0.425, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 09:54:00,597 - pyskl - INFO - Epoch [130][800/1281] lr: 1.121e-03, eta: 3:09:54, time: 0.305, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 09:54:41,292 - pyskl - INFO - Epoch [130][900/1281] lr: 1.113e-03, eta: 3:09:10, time: 0.407, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 09:55:30,037 - pyskl - INFO - Epoch [130][1000/1281] lr: 1.104e-03, eta: 3:08:27, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 09:56:18,867 - pyskl - INFO - Epoch [130][1100/1281] lr: 1.096e-03, eta: 3:07:44, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0227, loss: 0.0227 +2025-06-25 09:57:07,980 - pyskl - INFO - Epoch [130][1200/1281] lr: 1.088e-03, eta: 3:07:01, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 09:57:48,128 - pyskl - INFO - Saving checkpoint at 130 epochs +2025-06-25 09:58:47,189 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:58:47,246 - pyskl - INFO - +top1_acc 0.9316 +top5_acc 0.9958 +2025-06-25 09:58:47,246 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:58:47,253 - pyskl - INFO - +mean_acc 0.9036 +2025-06-25 09:58:47,255 - pyskl - INFO - Epoch(val) [130][533] top1_acc: 0.9316, top5_acc: 0.9958, mean_class_accuracy: 0.9036 +2025-06-25 10:00:07,726 - pyskl - INFO - Epoch [131][100/1281] lr: 1.072e-03, eta: 3:05:42, time: 0.805, data_time: 0.187, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0240, loss: 0.0240 +2025-06-25 10:00:56,316 - pyskl - INFO - Epoch [131][200/1281] lr: 1.064e-03, eta: 3:04:59, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 10:01:45,378 - pyskl - INFO - Epoch [131][300/1281] lr: 1.056e-03, eta: 3:04:17, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0226, loss: 0.0226 +2025-06-25 10:02:34,382 - pyskl - INFO - Epoch [131][400/1281] lr: 1.048e-03, eta: 3:03:34, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 10:03:23,297 - pyskl - INFO - Epoch [131][500/1281] lr: 1.040e-03, eta: 3:02:51, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0235, loss: 0.0235 +2025-06-25 10:04:06,023 - pyskl - INFO - Epoch [131][600/1281] lr: 1.031e-03, eta: 3:02:07, time: 0.427, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 10:04:50,089 - pyskl - INFO - Epoch [131][700/1281] lr: 1.023e-03, eta: 3:01:23, time: 0.441, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 10:05:19,116 - pyskl - INFO - Epoch [131][800/1281] lr: 1.015e-03, eta: 3:00:38, time: 0.290, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0183, loss: 0.0183 +2025-06-25 10:06:02,306 - pyskl - INFO - Epoch [131][900/1281] lr: 1.007e-03, eta: 2:59:54, time: 0.432, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 10:06:51,319 - pyskl - INFO - Epoch [131][1000/1281] lr: 9.992e-04, eta: 2:59:11, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 10:07:40,443 - pyskl - INFO - Epoch [131][1100/1281] lr: 9.912e-04, eta: 2:58:28, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 10:08:29,137 - pyskl - INFO - Epoch [131][1200/1281] lr: 9.832e-04, eta: 2:57:45, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 10:09:09,357 - pyskl - INFO - Saving checkpoint at 131 epochs +2025-06-25 10:10:08,707 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:10:08,764 - pyskl - INFO - +top1_acc 0.9347 +top5_acc 0.9961 +2025-06-25 10:10:08,764 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:10:08,777 - pyskl - INFO - +mean_acc 0.9092 +2025-06-25 10:10:08,782 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_129.pth was removed +2025-06-25 10:10:08,988 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_131.pth. +2025-06-25 10:10:08,989 - pyskl - INFO - Best top1_acc is 0.9347 at 131 epoch. +2025-06-25 10:10:08,992 - pyskl - INFO - Epoch(val) [131][533] top1_acc: 0.9347, top5_acc: 0.9961, mean_class_accuracy: 0.9092 +2025-06-25 10:11:27,851 - pyskl - INFO - Epoch [132][100/1281] lr: 9.689e-04, eta: 2:56:26, time: 0.789, data_time: 0.188, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 10:12:16,753 - pyskl - INFO - Epoch [132][200/1281] lr: 9.610e-04, eta: 2:55:43, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 10:13:06,064 - pyskl - INFO - Epoch [132][300/1281] lr: 9.532e-04, eta: 2:55:00, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 10:13:55,233 - pyskl - INFO - Epoch [132][400/1281] lr: 9.454e-04, eta: 2:54:17, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-25 10:14:44,425 - pyskl - INFO - Epoch [132][500/1281] lr: 9.376e-04, eta: 2:53:34, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0264, loss: 0.0264 +2025-06-25 10:15:24,027 - pyskl - INFO - Epoch [132][600/1281] lr: 9.298e-04, eta: 2:52:50, time: 0.396, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-25 10:16:15,021 - pyskl - INFO - Epoch [132][700/1281] lr: 9.221e-04, eta: 2:52:07, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0183, loss: 0.0183 +2025-06-25 10:16:38,672 - pyskl - INFO - Epoch [132][800/1281] lr: 9.144e-04, eta: 2:51:21, time: 0.237, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 10:17:22,843 - pyskl - INFO - Epoch [132][900/1281] lr: 9.068e-04, eta: 2:50:37, time: 0.442, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 10:18:11,619 - pyskl - INFO - Epoch [132][1000/1281] lr: 8.991e-04, eta: 2:49:54, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-25 10:19:00,759 - pyskl - INFO - Epoch [132][1100/1281] lr: 8.915e-04, eta: 2:49:11, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-25 10:19:49,778 - pyskl - INFO - Epoch [132][1200/1281] lr: 8.840e-04, eta: 2:48:29, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 10:20:30,016 - pyskl - INFO - Saving checkpoint at 132 epochs +2025-06-25 10:21:28,365 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:21:28,421 - pyskl - INFO - +top1_acc 0.9302 +top5_acc 0.9960 +2025-06-25 10:21:28,421 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:21:28,430 - pyskl - INFO - +mean_acc 0.9027 +2025-06-25 10:21:28,433 - pyskl - INFO - Epoch(val) [132][533] top1_acc: 0.9302, top5_acc: 0.9960, mean_class_accuracy: 0.9027 +2025-06-25 10:22:47,958 - pyskl - INFO - Epoch [133][100/1281] lr: 8.704e-04, eta: 2:47:10, time: 0.795, data_time: 0.188, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 10:23:37,055 - pyskl - INFO - Epoch [133][200/1281] lr: 8.629e-04, eta: 2:46:27, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 10:24:26,004 - pyskl - INFO - Epoch [133][300/1281] lr: 8.554e-04, eta: 2:45:44, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 10:25:15,004 - pyskl - INFO - Epoch [133][400/1281] lr: 8.480e-04, eta: 2:45:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 10:26:04,322 - pyskl - INFO - Epoch [133][500/1281] lr: 8.406e-04, eta: 2:44:18, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 10:26:43,901 - pyskl - INFO - Epoch [133][600/1281] lr: 8.333e-04, eta: 2:43:33, time: 0.396, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0219, loss: 0.0219 +2025-06-25 10:27:34,701 - pyskl - INFO - Epoch [133][700/1281] lr: 8.260e-04, eta: 2:42:51, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-25 10:27:57,873 - pyskl - INFO - Epoch [133][800/1281] lr: 8.187e-04, eta: 2:42:04, time: 0.232, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0207, loss: 0.0207 +2025-06-25 10:28:41,629 - pyskl - INFO - Epoch [133][900/1281] lr: 8.114e-04, eta: 2:41:21, time: 0.438, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 10:29:30,224 - pyskl - INFO - Epoch [133][1000/1281] lr: 8.042e-04, eta: 2:40:37, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 10:30:19,400 - pyskl - INFO - Epoch [133][1100/1281] lr: 7.970e-04, eta: 2:39:55, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 10:31:08,197 - pyskl - INFO - Epoch [133][1200/1281] lr: 7.898e-04, eta: 2:39:11, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-25 10:31:48,581 - pyskl - INFO - Saving checkpoint at 133 epochs +2025-06-25 10:32:47,143 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:32:47,205 - pyskl - INFO - +top1_acc 0.9344 +top5_acc 0.9962 +2025-06-25 10:32:47,205 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:32:47,211 - pyskl - INFO - +mean_acc 0.9090 +2025-06-25 10:32:47,213 - pyskl - INFO - Epoch(val) [133][533] top1_acc: 0.9344, top5_acc: 0.9962, mean_class_accuracy: 0.9090 +2025-06-25 10:34:06,977 - pyskl - INFO - Epoch [134][100/1281] lr: 7.769e-04, eta: 2:37:52, time: 0.798, data_time: 0.186, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 10:34:56,306 - pyskl - INFO - Epoch [134][200/1281] lr: 7.699e-04, eta: 2:37:09, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 10:35:45,216 - pyskl - INFO - Epoch [134][300/1281] lr: 7.628e-04, eta: 2:36:26, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 10:36:34,362 - pyskl - INFO - Epoch [134][400/1281] lr: 7.558e-04, eta: 2:35:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-25 10:37:23,385 - pyskl - INFO - Epoch [134][500/1281] lr: 7.488e-04, eta: 2:35:00, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 10:38:03,254 - pyskl - INFO - Epoch [134][600/1281] lr: 7.419e-04, eta: 2:34:16, time: 0.399, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 10:38:54,431 - pyskl - INFO - Epoch [134][700/1281] lr: 7.349e-04, eta: 2:33:33, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0183, loss: 0.0183 +2025-06-25 10:39:18,023 - pyskl - INFO - Epoch [134][800/1281] lr: 7.281e-04, eta: 2:32:47, time: 0.236, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 10:40:01,877 - pyskl - INFO - Epoch [134][900/1281] lr: 7.212e-04, eta: 2:32:03, time: 0.439, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 10:40:50,666 - pyskl - INFO - Epoch [134][1000/1281] lr: 7.144e-04, eta: 2:31:20, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0166, loss: 0.0166 +2025-06-25 10:41:39,695 - pyskl - INFO - Epoch [134][1100/1281] lr: 7.076e-04, eta: 2:30:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 10:42:28,435 - pyskl - INFO - Epoch [134][1200/1281] lr: 7.008e-04, eta: 2:29:54, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0172, loss: 0.0172 +2025-06-25 10:43:08,526 - pyskl - INFO - Saving checkpoint at 134 epochs +2025-06-25 10:44:07,375 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:44:07,433 - pyskl - INFO - +top1_acc 0.9346 +top5_acc 0.9961 +2025-06-25 10:44:07,433 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:44:07,444 - pyskl - INFO - +mean_acc 0.9090 +2025-06-25 10:44:07,447 - pyskl - INFO - Epoch(val) [134][533] top1_acc: 0.9346, top5_acc: 0.9961, mean_class_accuracy: 0.9090 +2025-06-25 10:45:26,539 - pyskl - INFO - Epoch [135][100/1281] lr: 6.887e-04, eta: 2:28:35, time: 0.791, data_time: 0.182, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0215, loss: 0.0215 +2025-06-25 10:46:15,929 - pyskl - INFO - Epoch [135][200/1281] lr: 6.820e-04, eta: 2:27:52, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0170, loss: 0.0170 +2025-06-25 10:47:05,285 - pyskl - INFO - Epoch [135][300/1281] lr: 6.753e-04, eta: 2:27:09, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0170, loss: 0.0170 +2025-06-25 10:47:54,358 - pyskl - INFO - Epoch [135][400/1281] lr: 6.687e-04, eta: 2:26:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 10:48:43,553 - pyskl - INFO - Epoch [135][500/1281] lr: 6.622e-04, eta: 2:25:43, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 10:49:21,969 - pyskl - INFO - Epoch [135][600/1281] lr: 6.556e-04, eta: 2:24:58, time: 0.384, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0170, loss: 0.0170 +2025-06-25 10:50:12,882 - pyskl - INFO - Epoch [135][700/1281] lr: 6.491e-04, eta: 2:24:16, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 10:50:36,795 - pyskl - INFO - Epoch [135][800/1281] lr: 6.426e-04, eta: 2:23:30, time: 0.239, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 10:51:21,530 - pyskl - INFO - Epoch [135][900/1281] lr: 6.362e-04, eta: 2:22:46, time: 0.447, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-25 10:52:10,589 - pyskl - INFO - Epoch [135][1000/1281] lr: 6.297e-04, eta: 2:22:03, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-25 10:52:59,621 - pyskl - INFO - Epoch [135][1100/1281] lr: 6.233e-04, eta: 2:21:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 10:53:48,462 - pyskl - INFO - Epoch [135][1200/1281] lr: 6.170e-04, eta: 2:20:37, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 10:54:28,698 - pyskl - INFO - Saving checkpoint at 135 epochs +2025-06-25 10:55:27,554 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:55:27,609 - pyskl - INFO - +top1_acc 0.9356 +top5_acc 0.9966 +2025-06-25 10:55:27,609 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:55:27,616 - pyskl - INFO - +mean_acc 0.9120 +2025-06-25 10:55:27,620 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_131.pth was removed +2025-06-25 10:55:27,804 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_135.pth. +2025-06-25 10:55:27,804 - pyskl - INFO - Best top1_acc is 0.9356 at 135 epoch. +2025-06-25 10:55:27,807 - pyskl - INFO - Epoch(val) [135][533] top1_acc: 0.9356, top5_acc: 0.9966, mean_class_accuracy: 0.9120 +2025-06-25 10:56:49,908 - pyskl - INFO - Epoch [136][100/1281] lr: 6.056e-04, eta: 2:19:18, time: 0.821, data_time: 0.190, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0253, loss: 0.0253 +2025-06-25 10:57:38,984 - pyskl - INFO - Epoch [136][200/1281] lr: 5.993e-04, eta: 2:18:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0183, loss: 0.0183 +2025-06-25 10:58:27,797 - pyskl - INFO - Epoch [136][300/1281] lr: 5.931e-04, eta: 2:17:51, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 10:59:16,809 - pyskl - INFO - Epoch [136][400/1281] lr: 5.868e-04, eta: 2:17:08, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0221, loss: 0.0221 +2025-06-25 11:00:05,938 - pyskl - INFO - Epoch [136][500/1281] lr: 5.807e-04, eta: 2:16:25, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 11:00:41,733 - pyskl - INFO - Epoch [136][600/1281] lr: 5.745e-04, eta: 2:15:41, time: 0.358, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 11:01:32,602 - pyskl - INFO - Epoch [136][700/1281] lr: 5.684e-04, eta: 2:14:58, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 11:01:57,461 - pyskl - INFO - Epoch [136][800/1281] lr: 5.623e-04, eta: 2:14:12, time: 0.249, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 11:02:44,869 - pyskl - INFO - Epoch [136][900/1281] lr: 5.563e-04, eta: 2:13:29, time: 0.474, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 11:03:33,905 - pyskl - INFO - Epoch [136][1000/1281] lr: 5.503e-04, eta: 2:12:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 11:04:23,318 - pyskl - INFO - Epoch [136][1100/1281] lr: 5.443e-04, eta: 2:12:02, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0166, loss: 0.0166 +2025-06-25 11:05:12,763 - pyskl - INFO - Epoch [136][1200/1281] lr: 5.384e-04, eta: 2:11:19, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 11:05:52,671 - pyskl - INFO - Saving checkpoint at 136 epochs +2025-06-25 11:06:51,024 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:06:51,086 - pyskl - INFO - +top1_acc 0.9331 +top5_acc 0.9961 +2025-06-25 11:06:51,086 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:06:51,093 - pyskl - INFO - +mean_acc 0.9075 +2025-06-25 11:06:51,095 - pyskl - INFO - Epoch(val) [136][533] top1_acc: 0.9331, top5_acc: 0.9961, mean_class_accuracy: 0.9075 +2025-06-25 11:08:10,392 - pyskl - INFO - Epoch [137][100/1281] lr: 5.277e-04, eta: 2:10:00, time: 0.793, data_time: 0.189, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 11:08:59,450 - pyskl - INFO - Epoch [137][200/1281] lr: 5.218e-04, eta: 2:09:17, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 11:09:48,906 - pyskl - INFO - Epoch [137][300/1281] lr: 5.160e-04, eta: 2:08:34, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 11:10:37,931 - pyskl - INFO - Epoch [137][400/1281] lr: 5.102e-04, eta: 2:07:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-25 11:11:27,214 - pyskl - INFO - Epoch [137][500/1281] lr: 5.044e-04, eta: 2:07:07, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 11:12:02,087 - pyskl - INFO - Epoch [137][600/1281] lr: 4.987e-04, eta: 2:06:23, time: 0.349, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 11:12:53,032 - pyskl - INFO - Epoch [137][700/1281] lr: 4.930e-04, eta: 2:05:39, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0148, loss: 0.0148 +2025-06-25 11:13:17,708 - pyskl - INFO - Epoch [137][800/1281] lr: 4.873e-04, eta: 2:04:54, time: 0.247, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 11:14:04,838 - pyskl - INFO - Epoch [137][900/1281] lr: 4.817e-04, eta: 2:04:10, time: 0.471, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 11:14:53,814 - pyskl - INFO - Epoch [137][1000/1281] lr: 4.761e-04, eta: 2:03:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0167, loss: 0.0167 +2025-06-25 11:15:43,098 - pyskl - INFO - Epoch [137][1100/1281] lr: 4.705e-04, eta: 2:02:44, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 11:16:32,053 - pyskl - INFO - Epoch [137][1200/1281] lr: 4.650e-04, eta: 2:02:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 11:17:12,221 - pyskl - INFO - Saving checkpoint at 137 epochs +2025-06-25 11:18:10,922 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:18:10,988 - pyskl - INFO - +top1_acc 0.9356 +top5_acc 0.9962 +2025-06-25 11:18:10,989 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:18:10,995 - pyskl - INFO - +mean_acc 0.9093 +2025-06-25 11:18:10,997 - pyskl - INFO - Epoch(val) [137][533] top1_acc: 0.9356, top5_acc: 0.9962, mean_class_accuracy: 0.9093 +2025-06-25 11:19:30,992 - pyskl - INFO - Epoch [138][100/1281] lr: 4.550e-04, eta: 2:00:42, time: 0.800, data_time: 0.185, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 11:20:20,128 - pyskl - INFO - Epoch [138][200/1281] lr: 4.496e-04, eta: 1:59:58, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 11:21:09,380 - pyskl - INFO - Epoch [138][300/1281] lr: 4.442e-04, eta: 1:59:15, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 11:21:58,634 - pyskl - INFO - Epoch [138][400/1281] lr: 4.388e-04, eta: 1:58:32, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 11:22:47,619 - pyskl - INFO - Epoch [138][500/1281] lr: 4.334e-04, eta: 1:57:49, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 11:23:21,284 - pyskl - INFO - Epoch [138][600/1281] lr: 4.281e-04, eta: 1:57:04, time: 0.337, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 11:24:12,203 - pyskl - INFO - Epoch [138][700/1281] lr: 4.228e-04, eta: 1:56:21, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0171, loss: 0.0171 +2025-06-25 11:24:47,099 - pyskl - INFO - Epoch [138][800/1281] lr: 4.176e-04, eta: 1:55:36, time: 0.349, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 11:25:57,038 - pyskl - INFO - Epoch [138][900/1281] lr: 4.124e-04, eta: 1:54:55, time: 0.699, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0147, loss: 0.0147 +2025-06-25 11:27:08,033 - pyskl - INFO - Epoch [138][1000/1281] lr: 4.072e-04, eta: 1:54:13, time: 0.710, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 11:28:19,432 - pyskl - INFO - Epoch [138][1100/1281] lr: 4.020e-04, eta: 1:53:32, time: 0.714, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0142, loss: 0.0142 +2025-06-25 11:29:29,524 - pyskl - INFO - Epoch [138][1200/1281] lr: 3.969e-04, eta: 1:52:51, time: 0.701, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 11:30:24,806 - pyskl - INFO - Saving checkpoint at 138 epochs +2025-06-25 11:31:39,271 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:31:39,328 - pyskl - INFO - +top1_acc 0.9353 +top5_acc 0.9961 +2025-06-25 11:31:39,328 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:31:39,335 - pyskl - INFO - +mean_acc 0.9104 +2025-06-25 11:31:39,337 - pyskl - INFO - Epoch(val) [138][533] top1_acc: 0.9353, top5_acc: 0.9961, mean_class_accuracy: 0.9104 +2025-06-25 11:32:44,531 - pyskl - INFO - Epoch [139][100/1281] lr: 3.877e-04, eta: 1:51:30, time: 0.652, data_time: 0.182, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0147, loss: 0.0147 +2025-06-25 11:33:55,834 - pyskl - INFO - Epoch [139][200/1281] lr: 3.827e-04, eta: 1:50:49, time: 0.713, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 11:35:06,284 - pyskl - INFO - Epoch [139][300/1281] lr: 3.777e-04, eta: 1:50:07, time: 0.705, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 11:36:16,783 - pyskl - INFO - Epoch [139][400/1281] lr: 3.727e-04, eta: 1:49:26, time: 0.705, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 11:37:27,763 - pyskl - INFO - Epoch [139][500/1281] lr: 3.678e-04, eta: 1:48:44, time: 0.710, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 11:38:37,195 - pyskl - INFO - Epoch [139][600/1281] lr: 3.628e-04, eta: 1:48:02, time: 0.694, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 11:39:37,983 - pyskl - INFO - Epoch [139][700/1281] lr: 3.580e-04, eta: 1:47:20, time: 0.608, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0150, loss: 0.0150 +2025-06-25 11:39:59,965 - pyskl - INFO - Epoch [139][800/1281] lr: 3.531e-04, eta: 1:46:34, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0149, loss: 0.0149 +2025-06-25 11:40:22,094 - pyskl - INFO - Epoch [139][900/1281] lr: 3.483e-04, eta: 1:45:48, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 11:40:44,179 - pyskl - INFO - Epoch [139][1000/1281] lr: 3.436e-04, eta: 1:45:03, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 11:41:06,355 - pyskl - INFO - Epoch [139][1100/1281] lr: 3.388e-04, eta: 1:44:17, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0150, loss: 0.0150 +2025-06-25 11:41:28,489 - pyskl - INFO - Epoch [139][1200/1281] lr: 3.341e-04, eta: 1:43:32, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 11:41:46,722 - pyskl - INFO - Saving checkpoint at 139 epochs +2025-06-25 11:42:29,556 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:42:29,613 - pyskl - INFO - +top1_acc 0.9330 +top5_acc 0.9971 +2025-06-25 11:42:29,613 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:42:29,620 - pyskl - INFO - +mean_acc 0.9053 +2025-06-25 11:42:29,622 - pyskl - INFO - Epoch(val) [139][533] top1_acc: 0.9330, top5_acc: 0.9971, mean_class_accuracy: 0.9053 +2025-06-25 11:43:11,378 - pyskl - INFO - Epoch [140][100/1281] lr: 3.257e-04, eta: 1:42:09, time: 0.418, data_time: 0.181, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 11:43:33,379 - pyskl - INFO - Epoch [140][200/1281] lr: 3.210e-04, eta: 1:41:24, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 11:43:55,489 - pyskl - INFO - Epoch [140][300/1281] lr: 3.165e-04, eta: 1:40:38, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0151, loss: 0.0151 +2025-06-25 11:44:17,280 - pyskl - INFO - Epoch [140][400/1281] lr: 3.119e-04, eta: 1:39:53, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 11:44:39,076 - pyskl - INFO - Epoch [140][500/1281] lr: 3.074e-04, eta: 1:39:07, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 11:45:00,931 - pyskl - INFO - Epoch [140][600/1281] lr: 3.029e-04, eta: 1:38:22, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 11:45:22,781 - pyskl - INFO - Epoch [140][700/1281] lr: 2.984e-04, eta: 1:37:37, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 11:45:44,412 - pyskl - INFO - Epoch [140][800/1281] lr: 2.940e-04, eta: 1:36:51, time: 0.216, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 11:46:06,433 - pyskl - INFO - Epoch [140][900/1281] lr: 2.896e-04, eta: 1:36:06, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 11:46:28,035 - pyskl - INFO - Epoch [140][1000/1281] lr: 2.853e-04, eta: 1:35:20, time: 0.216, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 11:46:49,510 - pyskl - INFO - Epoch [140][1100/1281] lr: 2.809e-04, eta: 1:34:35, time: 0.215, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 11:47:11,388 - pyskl - INFO - Epoch [140][1200/1281] lr: 2.767e-04, eta: 1:33:50, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 11:47:29,624 - pyskl - INFO - Saving checkpoint at 140 epochs +2025-06-25 11:48:12,516 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:48:12,570 - pyskl - INFO - +top1_acc 0.9353 +top5_acc 0.9962 +2025-06-25 11:48:12,571 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:48:12,577 - pyskl - INFO - +mean_acc 0.9068 +2025-06-25 11:48:12,578 - pyskl - INFO - Epoch(val) [140][533] top1_acc: 0.9353, top5_acc: 0.9962, mean_class_accuracy: 0.9068 +2025-06-25 11:48:53,439 - pyskl - INFO - Epoch [141][100/1281] lr: 2.690e-04, eta: 1:32:28, time: 0.409, data_time: 0.180, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 11:49:15,344 - pyskl - INFO - Epoch [141][200/1281] lr: 2.648e-04, eta: 1:31:43, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 11:49:37,381 - pyskl - INFO - Epoch [141][300/1281] lr: 2.606e-04, eta: 1:30:58, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 11:49:59,206 - pyskl - INFO - Epoch [141][400/1281] lr: 2.565e-04, eta: 1:30:13, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 11:50:20,857 - pyskl - INFO - Epoch [141][500/1281] lr: 2.524e-04, eta: 1:29:28, time: 0.217, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0204, loss: 0.0204 +2025-06-25 11:50:42,846 - pyskl - INFO - Epoch [141][600/1281] lr: 2.483e-04, eta: 1:28:42, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 11:51:04,762 - pyskl - INFO - Epoch [141][700/1281] lr: 2.443e-04, eta: 1:27:57, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 11:51:26,603 - pyskl - INFO - Epoch [141][800/1281] lr: 2.402e-04, eta: 1:27:12, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 11:51:48,646 - pyskl - INFO - Epoch [141][900/1281] lr: 2.363e-04, eta: 1:26:27, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0167, loss: 0.0167 +2025-06-25 11:52:10,735 - pyskl - INFO - Epoch [141][1000/1281] lr: 2.323e-04, eta: 1:25:42, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 11:52:32,632 - pyskl - INFO - Epoch [141][1100/1281] lr: 2.284e-04, eta: 1:24:57, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 11:52:55,097 - pyskl - INFO - Epoch [141][1200/1281] lr: 2.246e-04, eta: 1:24:13, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 11:53:13,667 - pyskl - INFO - Saving checkpoint at 141 epochs +2025-06-25 11:53:56,682 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:53:56,754 - pyskl - INFO - +top1_acc 0.9336 +top5_acc 0.9969 +2025-06-25 11:53:56,754 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:53:56,762 - pyskl - INFO - +mean_acc 0.9064 +2025-06-25 11:53:56,765 - pyskl - INFO - Epoch(val) [141][533] top1_acc: 0.9336, top5_acc: 0.9969, mean_class_accuracy: 0.9064 +2025-06-25 11:54:38,577 - pyskl - INFO - Epoch [142][100/1281] lr: 2.176e-04, eta: 1:22:51, time: 0.418, data_time: 0.184, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 11:55:00,665 - pyskl - INFO - Epoch [142][200/1281] lr: 2.139e-04, eta: 1:22:07, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0147, loss: 0.0147 +2025-06-25 11:55:22,323 - pyskl - INFO - Epoch [142][300/1281] lr: 2.101e-04, eta: 1:21:22, time: 0.217, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 11:55:44,264 - pyskl - INFO - Epoch [142][400/1281] lr: 2.064e-04, eta: 1:20:37, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 11:56:06,307 - pyskl - INFO - Epoch [142][500/1281] lr: 2.027e-04, eta: 1:19:52, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0167, loss: 0.0167 +2025-06-25 11:56:28,323 - pyskl - INFO - Epoch [142][600/1281] lr: 1.991e-04, eta: 1:19:07, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 11:56:50,302 - pyskl - INFO - Epoch [142][700/1281] lr: 1.954e-04, eta: 1:18:23, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0150, loss: 0.0150 +2025-06-25 11:57:12,238 - pyskl - INFO - Epoch [142][800/1281] lr: 1.919e-04, eta: 1:17:38, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0171, loss: 0.0171 +2025-06-25 11:57:34,719 - pyskl - INFO - Epoch [142][900/1281] lr: 1.883e-04, eta: 1:16:53, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 11:57:56,753 - pyskl - INFO - Epoch [142][1000/1281] lr: 1.848e-04, eta: 1:16:09, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0148, loss: 0.0148 +2025-06-25 11:58:18,517 - pyskl - INFO - Epoch [142][1100/1281] lr: 1.813e-04, eta: 1:15:24, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 11:58:40,634 - pyskl - INFO - Epoch [142][1200/1281] lr: 1.779e-04, eta: 1:14:40, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0147, loss: 0.0147 +2025-06-25 11:58:59,030 - pyskl - INFO - Saving checkpoint at 142 epochs +2025-06-25 11:59:42,262 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:59:42,318 - pyskl - INFO - +top1_acc 0.9335 +top5_acc 0.9966 +2025-06-25 11:59:42,318 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:59:42,324 - pyskl - INFO - +mean_acc 0.9060 +2025-06-25 11:59:42,326 - pyskl - INFO - Epoch(val) [142][533] top1_acc: 0.9335, top5_acc: 0.9966, mean_class_accuracy: 0.9060 +2025-06-25 12:00:23,647 - pyskl - INFO - Epoch [143][100/1281] lr: 1.717e-04, eta: 1:13:19, time: 0.413, data_time: 0.181, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 12:00:45,647 - pyskl - INFO - Epoch [143][200/1281] lr: 1.683e-04, eta: 1:12:34, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 12:01:07,598 - pyskl - INFO - Epoch [143][300/1281] lr: 1.650e-04, eta: 1:11:50, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 12:01:29,558 - pyskl - INFO - Epoch [143][400/1281] lr: 1.617e-04, eta: 1:11:05, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 12:01:51,531 - pyskl - INFO - Epoch [143][500/1281] lr: 1.585e-04, eta: 1:10:21, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 12:02:13,537 - pyskl - INFO - Epoch [143][600/1281] lr: 1.552e-04, eta: 1:09:37, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 12:02:35,747 - pyskl - INFO - Epoch [143][700/1281] lr: 1.520e-04, eta: 1:08:52, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0142, loss: 0.0142 +2025-06-25 12:02:57,610 - pyskl - INFO - Epoch [143][800/1281] lr: 1.489e-04, eta: 1:08:08, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 12:03:19,930 - pyskl - INFO - Epoch [143][900/1281] lr: 1.457e-04, eta: 1:07:23, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0170, loss: 0.0170 +2025-06-25 12:03:42,206 - pyskl - INFO - Epoch [143][1000/1281] lr: 1.426e-04, eta: 1:06:39, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 12:04:04,173 - pyskl - INFO - Epoch [143][1100/1281] lr: 1.396e-04, eta: 1:05:55, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0166, loss: 0.0166 +2025-06-25 12:04:26,513 - pyskl - INFO - Epoch [143][1200/1281] lr: 1.366e-04, eta: 1:05:10, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 12:04:45,153 - pyskl - INFO - Saving checkpoint at 143 epochs +2025-06-25 12:05:27,848 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:05:27,915 - pyskl - INFO - +top1_acc 0.9356 +top5_acc 0.9966 +2025-06-25 12:05:27,915 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:05:27,925 - pyskl - INFO - +mean_acc 0.9105 +2025-06-25 12:05:27,927 - pyskl - INFO - Epoch(val) [143][533] top1_acc: 0.9356, top5_acc: 0.9966, mean_class_accuracy: 0.9105 +2025-06-25 12:06:09,762 - pyskl - INFO - Epoch [144][100/1281] lr: 1.312e-04, eta: 1:03:50, time: 0.418, data_time: 0.186, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 12:06:32,068 - pyskl - INFO - Epoch [144][200/1281] lr: 1.282e-04, eta: 1:03:06, time: 0.223, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 12:06:53,963 - pyskl - INFO - Epoch [144][300/1281] lr: 1.253e-04, eta: 1:02:22, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0151, loss: 0.0151 +2025-06-25 12:07:15,892 - pyskl - INFO - Epoch [144][400/1281] lr: 1.224e-04, eta: 1:01:38, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0141, loss: 0.0141 +2025-06-25 12:07:38,029 - pyskl - INFO - Epoch [144][500/1281] lr: 1.196e-04, eta: 1:00:54, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 12:07:59,955 - pyskl - INFO - Epoch [144][600/1281] lr: 1.168e-04, eta: 1:00:10, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 12:08:21,913 - pyskl - INFO - Epoch [144][700/1281] lr: 1.140e-04, eta: 0:59:26, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 12:08:43,762 - pyskl - INFO - Epoch [144][800/1281] lr: 1.113e-04, eta: 0:58:41, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 12:09:06,137 - pyskl - INFO - Epoch [144][900/1281] lr: 1.086e-04, eta: 0:57:57, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0147, loss: 0.0147 +2025-06-25 12:09:28,114 - pyskl - INFO - Epoch [144][1000/1281] lr: 1.059e-04, eta: 0:57:13, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0150, loss: 0.0150 +2025-06-25 12:09:50,132 - pyskl - INFO - Epoch [144][1100/1281] lr: 1.033e-04, eta: 0:56:29, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0142, loss: 0.0142 +2025-06-25 12:10:12,004 - pyskl - INFO - Epoch [144][1200/1281] lr: 1.007e-04, eta: 0:55:45, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0170, loss: 0.0170 +2025-06-25 12:10:30,575 - pyskl - INFO - Saving checkpoint at 144 epochs +2025-06-25 12:11:13,162 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:11:13,216 - pyskl - INFO - +top1_acc 0.9343 +top5_acc 0.9961 +2025-06-25 12:11:13,216 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:11:13,223 - pyskl - INFO - +mean_acc 0.9087 +2025-06-25 12:11:13,224 - pyskl - INFO - Epoch(val) [144][533] top1_acc: 0.9343, top5_acc: 0.9961, mean_class_accuracy: 0.9087 +2025-06-25 12:11:54,223 - pyskl - INFO - Epoch [145][100/1281] lr: 9.605e-05, eta: 0:54:26, time: 0.410, data_time: 0.180, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0151, loss: 0.0151 +2025-06-25 12:12:16,331 - pyskl - INFO - Epoch [145][200/1281] lr: 9.353e-05, eta: 0:53:42, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0143, loss: 0.0143 +2025-06-25 12:12:38,453 - pyskl - INFO - Epoch [145][300/1281] lr: 9.106e-05, eta: 0:52:58, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 12:13:00,480 - pyskl - INFO - Epoch [145][400/1281] lr: 8.861e-05, eta: 0:52:14, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0171, loss: 0.0171 +2025-06-25 12:13:22,269 - pyskl - INFO - Epoch [145][500/1281] lr: 8.620e-05, eta: 0:51:30, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 12:13:44,259 - pyskl - INFO - Epoch [145][600/1281] lr: 8.382e-05, eta: 0:50:47, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 12:14:06,535 - pyskl - INFO - Epoch [145][700/1281] lr: 8.147e-05, eta: 0:50:03, time: 0.223, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 12:14:28,464 - pyskl - INFO - Epoch [145][800/1281] lr: 7.916e-05, eta: 0:49:19, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 12:14:50,465 - pyskl - INFO - Epoch [145][900/1281] lr: 7.688e-05, eta: 0:48:35, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0142, loss: 0.0142 +2025-06-25 12:15:12,529 - pyskl - INFO - Epoch [145][1000/1281] lr: 7.463e-05, eta: 0:47:52, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 12:15:34,502 - pyskl - INFO - Epoch [145][1100/1281] lr: 7.242e-05, eta: 0:47:08, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 12:15:56,549 - pyskl - INFO - Epoch [145][1200/1281] lr: 7.024e-05, eta: 0:46:24, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 12:16:15,115 - pyskl - INFO - Saving checkpoint at 145 epochs +2025-06-25 12:16:58,000 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:16:58,056 - pyskl - INFO - +top1_acc 0.9363 +top5_acc 0.9966 +2025-06-25 12:16:58,056 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:16:58,063 - pyskl - INFO - +mean_acc 0.9108 +2025-06-25 12:16:58,067 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_135.pth was removed +2025-06-25 12:16:58,230 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_145.pth. +2025-06-25 12:16:58,231 - pyskl - INFO - Best top1_acc is 0.9363 at 145 epoch. +2025-06-25 12:16:58,234 - pyskl - INFO - Epoch(val) [145][533] top1_acc: 0.9363, top5_acc: 0.9966, mean_class_accuracy: 0.9108 +2025-06-25 12:17:39,614 - pyskl - INFO - Epoch [146][100/1281] lr: 6.638e-05, eta: 0:45:05, time: 0.414, data_time: 0.183, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0146, loss: 0.0146 +2025-06-25 12:18:01,726 - pyskl - INFO - Epoch [146][200/1281] lr: 6.429e-05, eta: 0:44:22, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 12:18:23,831 - pyskl - INFO - Epoch [146][300/1281] lr: 6.224e-05, eta: 0:43:38, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 12:18:45,628 - pyskl - INFO - Epoch [146][400/1281] lr: 6.022e-05, eta: 0:42:54, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 12:19:07,563 - pyskl - INFO - Epoch [146][500/1281] lr: 5.823e-05, eta: 0:42:11, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0144, loss: 0.0144 +2025-06-25 12:19:29,390 - pyskl - INFO - Epoch [146][600/1281] lr: 5.628e-05, eta: 0:41:27, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0138, loss: 0.0138 +2025-06-25 12:19:51,499 - pyskl - INFO - Epoch [146][700/1281] lr: 5.436e-05, eta: 0:40:44, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0143, loss: 0.0143 +2025-06-25 12:20:13,512 - pyskl - INFO - Epoch [146][800/1281] lr: 5.247e-05, eta: 0:40:00, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0167, loss: 0.0167 +2025-06-25 12:20:35,502 - pyskl - INFO - Epoch [146][900/1281] lr: 5.061e-05, eta: 0:39:17, time: 0.220, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0144, loss: 0.0144 +2025-06-25 12:20:57,386 - pyskl - INFO - Epoch [146][1000/1281] lr: 4.879e-05, eta: 0:38:34, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 12:21:19,295 - pyskl - INFO - Epoch [146][1100/1281] lr: 4.701e-05, eta: 0:37:50, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 12:21:41,442 - pyskl - INFO - Epoch [146][1200/1281] lr: 4.525e-05, eta: 0:37:07, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0147, loss: 0.0147 +2025-06-25 12:21:59,877 - pyskl - INFO - Saving checkpoint at 146 epochs +2025-06-25 12:22:42,399 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:22:42,466 - pyskl - INFO - +top1_acc 0.9358 +top5_acc 0.9965 +2025-06-25 12:22:42,467 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:22:42,475 - pyskl - INFO - +mean_acc 0.9107 +2025-06-25 12:22:42,477 - pyskl - INFO - Epoch(val) [146][533] top1_acc: 0.9358, top5_acc: 0.9965, mean_class_accuracy: 0.9107 +2025-06-25 12:23:23,655 - pyskl - INFO - Epoch [147][100/1281] lr: 4.216e-05, eta: 0:35:48, time: 0.412, data_time: 0.182, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0145, loss: 0.0145 +2025-06-25 12:23:45,829 - pyskl - INFO - Epoch [147][200/1281] lr: 4.050e-05, eta: 0:35:05, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 12:24:08,087 - pyskl - INFO - Epoch [147][300/1281] lr: 3.887e-05, eta: 0:34:22, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0166, loss: 0.0166 +2025-06-25 12:24:30,098 - pyskl - INFO - Epoch [147][400/1281] lr: 3.728e-05, eta: 0:33:38, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 12:24:52,085 - pyskl - INFO - Epoch [147][500/1281] lr: 3.572e-05, eta: 0:32:55, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 12:25:14,064 - pyskl - INFO - Epoch [147][600/1281] lr: 3.419e-05, eta: 0:32:12, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 12:25:36,226 - pyskl - INFO - Epoch [147][700/1281] lr: 3.270e-05, eta: 0:31:29, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 12:25:58,281 - pyskl - INFO - Epoch [147][800/1281] lr: 3.124e-05, eta: 0:30:46, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0146, loss: 0.0146 +2025-06-25 12:26:20,205 - pyskl - INFO - Epoch [147][900/1281] lr: 2.981e-05, eta: 0:30:02, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0132, loss: 0.0132 +2025-06-25 12:26:42,134 - pyskl - INFO - Epoch [147][1000/1281] lr: 2.842e-05, eta: 0:29:19, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0142, loss: 0.0142 +2025-06-25 12:27:03,896 - pyskl - INFO - Epoch [147][1100/1281] lr: 2.706e-05, eta: 0:28:36, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 12:27:25,995 - pyskl - INFO - Epoch [147][1200/1281] lr: 2.573e-05, eta: 0:27:53, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 12:27:44,500 - pyskl - INFO - Saving checkpoint at 147 epochs +2025-06-25 12:28:27,612 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:28:27,679 - pyskl - INFO - +top1_acc 0.9364 +top5_acc 0.9966 +2025-06-25 12:28:27,679 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:28:27,687 - pyskl - INFO - +mean_acc 0.9111 +2025-06-25 12:28:27,692 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_145.pth was removed +2025-06-25 12:28:27,863 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_147.pth. +2025-06-25 12:28:27,864 - pyskl - INFO - Best top1_acc is 0.9364 at 147 epoch. +2025-06-25 12:28:27,866 - pyskl - INFO - Epoch(val) [147][533] top1_acc: 0.9364, top5_acc: 0.9966, mean_class_accuracy: 0.9111 +2025-06-25 12:29:09,671 - pyskl - INFO - Epoch [148][100/1281] lr: 2.341e-05, eta: 0:26:35, time: 0.418, data_time: 0.183, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0148, loss: 0.0148 +2025-06-25 12:29:31,602 - pyskl - INFO - Epoch [148][200/1281] lr: 2.218e-05, eta: 0:25:52, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0161, loss: 0.0161 +2025-06-25 12:29:53,584 - pyskl - INFO - Epoch [148][300/1281] lr: 2.098e-05, eta: 0:25:09, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 12:30:15,651 - pyskl - INFO - Epoch [148][400/1281] lr: 1.981e-05, eta: 0:24:26, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0149, loss: 0.0149 +2025-06-25 12:30:37,607 - pyskl - INFO - Epoch [148][500/1281] lr: 1.868e-05, eta: 0:23:43, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 12:30:59,464 - pyskl - INFO - Epoch [148][600/1281] lr: 1.758e-05, eta: 0:23:00, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 12:31:21,396 - pyskl - INFO - Epoch [148][700/1281] lr: 1.651e-05, eta: 0:22:17, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0167, loss: 0.0167 +2025-06-25 12:31:43,212 - pyskl - INFO - Epoch [148][800/1281] lr: 1.548e-05, eta: 0:21:34, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0151, loss: 0.0151 +2025-06-25 12:32:05,377 - pyskl - INFO - Epoch [148][900/1281] lr: 1.448e-05, eta: 0:20:52, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0200, loss: 0.0200 +2025-06-25 12:32:27,476 - pyskl - INFO - Epoch [148][1000/1281] lr: 1.351e-05, eta: 0:20:09, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0145, loss: 0.0145 +2025-06-25 12:32:49,113 - pyskl - INFO - Epoch [148][1100/1281] lr: 1.258e-05, eta: 0:19:26, time: 0.216, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 12:33:11,083 - pyskl - INFO - Epoch [148][1200/1281] lr: 1.168e-05, eta: 0:18:43, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 12:33:29,622 - pyskl - INFO - Saving checkpoint at 148 epochs +2025-06-25 12:34:12,739 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:34:12,826 - pyskl - INFO - +top1_acc 0.9360 +top5_acc 0.9965 +2025-06-25 12:34:12,826 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:34:12,835 - pyskl - INFO - +mean_acc 0.9103 +2025-06-25 12:34:12,838 - pyskl - INFO - Epoch(val) [148][533] top1_acc: 0.9360, top5_acc: 0.9965, mean_class_accuracy: 0.9103 +2025-06-25 12:34:54,659 - pyskl - INFO - Epoch [149][100/1281] lr: 1.013e-05, eta: 0:17:26, time: 0.418, data_time: 0.188, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0143, loss: 0.0143 +2025-06-25 12:35:16,839 - pyskl - INFO - Epoch [149][200/1281] lr: 9.328e-06, eta: 0:16:43, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0150, loss: 0.0150 +2025-06-25 12:35:38,966 - pyskl - INFO - Epoch [149][300/1281] lr: 8.555e-06, eta: 0:16:00, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 12:36:01,016 - pyskl - INFO - Epoch [149][400/1281] lr: 7.816e-06, eta: 0:15:18, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0141, loss: 0.0141 +2025-06-25 12:36:22,947 - pyskl - INFO - Epoch [149][500/1281] lr: 7.110e-06, eta: 0:14:35, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 12:36:44,921 - pyskl - INFO - Epoch [149][600/1281] lr: 6.437e-06, eta: 0:13:52, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 12:37:07,003 - pyskl - INFO - Epoch [149][700/1281] lr: 5.798e-06, eta: 0:13:10, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 12:37:28,802 - pyskl - INFO - Epoch [149][800/1281] lr: 5.192e-06, eta: 0:12:27, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0150, loss: 0.0150 +2025-06-25 12:37:50,811 - pyskl - INFO - Epoch [149][900/1281] lr: 4.620e-06, eta: 0:11:44, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 12:38:12,841 - pyskl - INFO - Epoch [149][1000/1281] lr: 4.081e-06, eta: 0:11:02, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0145, loss: 0.0145 +2025-06-25 12:38:34,747 - pyskl - INFO - Epoch [149][1100/1281] lr: 3.576e-06, eta: 0:10:19, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0166, loss: 0.0166 +2025-06-25 12:38:57,393 - pyskl - INFO - Epoch [149][1200/1281] lr: 3.104e-06, eta: 0:09:37, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 12:39:15,862 - pyskl - INFO - Saving checkpoint at 149 epochs +2025-06-25 12:39:58,102 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:39:58,154 - pyskl - INFO - +top1_acc 0.9345 +top5_acc 0.9961 +2025-06-25 12:39:58,154 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:39:58,160 - pyskl - INFO - +mean_acc 0.9087 +2025-06-25 12:39:58,162 - pyskl - INFO - Epoch(val) [149][533] top1_acc: 0.9345, top5_acc: 0.9961, mean_class_accuracy: 0.9087 +2025-06-25 12:40:39,905 - pyskl - INFO - Epoch [150][100/1281] lr: 2.334e-06, eta: 0:08:20, time: 0.417, data_time: 0.186, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 12:41:02,171 - pyskl - INFO - Epoch [150][200/1281] lr: 1.956e-06, eta: 0:07:37, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 12:41:24,088 - pyskl - INFO - Epoch [150][300/1281] lr: 1.611e-06, eta: 0:06:55, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 12:41:46,273 - pyskl - INFO - Epoch [150][400/1281] lr: 1.300e-06, eta: 0:06:12, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0169, loss: 0.0169 +2025-06-25 12:42:08,426 - pyskl - INFO - Epoch [150][500/1281] lr: 1.022e-06, eta: 0:05:30, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0150, loss: 0.0150 +2025-06-25 12:42:30,626 - pyskl - INFO - Epoch [150][600/1281] lr: 7.771e-07, eta: 0:04:48, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 12:42:52,886 - pyskl - INFO - Epoch [150][700/1281] lr: 5.659e-07, eta: 0:04:05, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0143, loss: 0.0143 +2025-06-25 12:43:14,866 - pyskl - INFO - Epoch [150][800/1281] lr: 3.881e-07, eta: 0:03:23, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 12:43:37,098 - pyskl - INFO - Epoch [150][900/1281] lr: 2.438e-07, eta: 0:02:41, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 12:43:59,298 - pyskl - INFO - Epoch [150][1000/1281] lr: 1.329e-07, eta: 0:01:58, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 12:44:21,002 - pyskl - INFO - Epoch [150][1100/1281] lr: 5.534e-08, eta: 0:01:16, time: 0.217, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0151, loss: 0.0151 +2025-06-25 12:44:42,769 - pyskl - INFO - Epoch [150][1200/1281] lr: 1.123e-08, eta: 0:00:34, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 12:45:01,236 - pyskl - INFO - Saving checkpoint at 150 epochs +2025-06-25 12:45:44,103 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:45:44,154 - pyskl - INFO - +top1_acc 0.9357 +top5_acc 0.9966 +2025-06-25 12:45:44,155 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:45:44,160 - pyskl - INFO - +mean_acc 0.9104 +2025-06-25 12:45:44,162 - pyskl - INFO - Epoch(val) [150][533] top1_acc: 0.9357, top5_acc: 0.9966, mean_class_accuracy: 0.9104 +2025-06-25 12:45:48,645 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-06-25 12:50:58,023 - pyskl - INFO - Testing results of the last checkpoint +2025-06-25 12:50:58,023 - pyskl - INFO - top1_acc: 0.9367 +2025-06-25 12:50:58,024 - pyskl - INFO - top5_acc: 0.9971 +2025-06-25 12:50:58,024 - pyskl - INFO - mean_class_accuracy: 0.9123 +2025-06-25 12:50:58,024 - pyskl - INFO - load checkpoint from local path: ./work_dirs/test_aclnet/finegym/jm/best_top1_acc_epoch_147.pth +2025-06-25 12:56:04,612 - pyskl - INFO - Testing results of the best checkpoint +2025-06-25 12:56:04,612 - pyskl - INFO - top1_acc: 0.9390 +2025-06-25 12:56:04,612 - pyskl - INFO - top5_acc: 0.9975 +2025-06-25 12:56:04,612 - pyskl - INFO - mean_class_accuracy: 0.9149