diff --git "a/finegym/k_1/20250624_101323.log" "b/finegym/k_1/20250624_101323.log" new file mode 100644--- /dev/null +++ "b/finegym/k_1/20250624_101323.log" @@ -0,0 +1,3480 @@ +2025-06-24 10:13:23,969 - 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 10:13:24,226 - pyskl - INFO - Config: modality = 'k' +graph = 'coco_new' +work_dir = './work_dirs/test_aclnet/finegym/k_1' +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=['k']), + 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=['k']), + 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=['k']), + 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=['k']), + 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=['k']), + 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=['k']), + 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 10:13:24,226 - pyskl - INFO - Set random seed to 1914909370, deterministic: False +2025-06-24 10:13:25,802 - pyskl - INFO - 20484 videos remain after valid thresholding +2025-06-24 10:13:30,147 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-06-24 10:13:30,148 - pyskl - INFO - Start running, host: lhd@zkyd, work_dir: /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1 +2025-06-24 10:13:30,149 - 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 10:13:30,149 - pyskl - INFO - workflow: [('train', 1)], max: 150 epochs +2025-06-24 10:13:30,149 - pyskl - INFO - Checkpoints will be saved to /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1 by HardDiskBackend. +2025-06-24 10:14:10,416 - pyskl - INFO - Epoch [1][100/1281] lr: 2.500e-02, eta: 21:28:44, time: 0.403, data_time: 0.184, memory: 4082, top1_acc: 0.0631, top5_acc: 0.2506, loss_cls: 4.5008, loss: 4.5008 +2025-06-24 10:14:33,000 - pyskl - INFO - Epoch [1][200/1281] lr: 2.500e-02, eta: 16:45:15, time: 0.226, data_time: 0.001, memory: 4082, top1_acc: 0.0887, top5_acc: 0.3175, loss_cls: 4.5462, loss: 4.5462 +2025-06-24 10:14:55,385 - pyskl - INFO - Epoch [1][300/1281] lr: 2.500e-02, eta: 15:08:23, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.0931, top5_acc: 0.4019, loss_cls: 4.2312, loss: 4.2312 +2025-06-24 10:15:17,459 - pyskl - INFO - Epoch [1][400/1281] lr: 2.500e-02, eta: 14:17:17, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.1219, top5_acc: 0.4219, loss_cls: 4.1323, loss: 4.1323 +2025-06-24 10:15:39,586 - pyskl - INFO - Epoch [1][500/1281] lr: 2.500e-02, eta: 13:46:49, time: 0.221, data_time: 0.001, memory: 4082, top1_acc: 0.1363, top5_acc: 0.4437, loss_cls: 3.9138, loss: 3.9138 +2025-06-24 10:16:01,498 - pyskl - INFO - Epoch [1][600/1281] lr: 2.500e-02, eta: 13:25:15, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.1675, top5_acc: 0.5006, loss_cls: 3.7379, loss: 3.7379 +2025-06-24 10:16:23,485 - pyskl - INFO - Epoch [1][700/1281] lr: 2.500e-02, eta: 13:10:04, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.1825, top5_acc: 0.5275, loss_cls: 3.6024, loss: 3.6024 +2025-06-24 10:16:45,378 - pyskl - INFO - Epoch [1][800/1281] lr: 2.500e-02, eta: 12:58:13, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.2156, top5_acc: 0.5700, loss_cls: 3.5022, loss: 3.5022 +2025-06-24 10:17:07,297 - pyskl - INFO - Epoch [1][900/1281] lr: 2.500e-02, eta: 12:49:01, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.2400, top5_acc: 0.6356, loss_cls: 3.2933, loss: 3.2933 +2025-06-24 10:17:29,389 - pyskl - INFO - Epoch [1][1000/1281] lr: 2.500e-02, eta: 12:42:08, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.2406, top5_acc: 0.6375, loss_cls: 3.2172, loss: 3.2172 +2025-06-24 10:17:51,107 - pyskl - INFO - Epoch [1][1100/1281] lr: 2.500e-02, eta: 12:35:21, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.2469, top5_acc: 0.6756, loss_cls: 3.0984, loss: 3.0984 +2025-06-24 10:18:13,084 - pyskl - INFO - Epoch [1][1200/1281] lr: 2.500e-02, eta: 12:30:19, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.2694, top5_acc: 0.6744, loss_cls: 3.0506, loss: 3.0506 +2025-06-24 10:18:31,324 - pyskl - INFO - Saving checkpoint at 1 epochs +2025-06-24 10:19:15,147 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:19:15,213 - pyskl - INFO - +top1_acc 0.3211 +top5_acc 0.7315 +2025-06-24 10:19:15,213 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:19:15,221 - pyskl - INFO - +mean_acc 0.1662 +2025-06-24 10:19:15,406 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_1.pth. +2025-06-24 10:19:15,406 - pyskl - INFO - Best top1_acc is 0.3211 at 1 epoch. +2025-06-24 10:19:15,409 - pyskl - INFO - Epoch(val) [1][533] top1_acc: 0.3211, top5_acc: 0.7315, mean_class_accuracy: 0.1662 +2025-06-24 10:19:56,409 - pyskl - INFO - Epoch [2][100/1281] lr: 2.500e-02, eta: 12:25:45, time: 0.410, data_time: 0.191, memory: 4082, top1_acc: 0.3394, top5_acc: 0.7494, loss_cls: 2.8379, loss: 2.8379 +2025-06-24 10:20:18,137 - pyskl - INFO - Epoch [2][200/1281] lr: 2.500e-02, eta: 12:21:39, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.3438, top5_acc: 0.7913, loss_cls: 2.7019, loss: 2.7019 +2025-06-24 10:20:39,805 - pyskl - INFO - Epoch [2][300/1281] lr: 2.500e-02, eta: 12:17:54, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.3725, top5_acc: 0.7969, loss_cls: 2.6425, loss: 2.6425 +2025-06-24 10:21:01,617 - pyskl - INFO - Epoch [2][400/1281] lr: 2.500e-02, eta: 12:14:50, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.4106, top5_acc: 0.7994, loss_cls: 2.5375, loss: 2.5375 +2025-06-24 10:21:23,317 - pyskl - INFO - Epoch [2][500/1281] lr: 2.499e-02, eta: 12:11:52, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.3931, top5_acc: 0.8106, loss_cls: 2.5224, loss: 2.5224 +2025-06-24 10:21:45,263 - pyskl - INFO - Epoch [2][600/1281] lr: 2.499e-02, eta: 12:09:35, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.4269, top5_acc: 0.8256, loss_cls: 2.3698, loss: 2.3698 +2025-06-24 10:22:07,243 - pyskl - INFO - Epoch [2][700/1281] lr: 2.499e-02, eta: 12:07:33, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.4288, top5_acc: 0.8419, loss_cls: 2.3224, loss: 2.3224 +2025-06-24 10:22:29,000 - pyskl - INFO - Epoch [2][800/1281] lr: 2.499e-02, eta: 12:05:21, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.4525, top5_acc: 0.8456, loss_cls: 2.2585, loss: 2.2585 +2025-06-24 10:22:51,297 - pyskl - INFO - Epoch [2][900/1281] lr: 2.499e-02, eta: 12:04:06, time: 0.223, data_time: 0.001, memory: 4082, top1_acc: 0.4612, top5_acc: 0.8562, loss_cls: 2.2000, loss: 2.2000 +2025-06-24 10:23:13,487 - pyskl - INFO - Epoch [2][1000/1281] lr: 2.499e-02, eta: 12:02:46, time: 0.222, data_time: 0.001, memory: 4082, top1_acc: 0.4819, top5_acc: 0.8700, loss_cls: 2.1313, loss: 2.1313 +2025-06-24 10:23:35,646 - pyskl - INFO - Epoch [2][1100/1281] lr: 2.499e-02, eta: 12:01:29, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.4856, top5_acc: 0.8812, loss_cls: 2.0934, loss: 2.0934 +2025-06-24 10:23:57,620 - pyskl - INFO - Epoch [2][1200/1281] lr: 2.499e-02, eta: 12:00:02, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5206, top5_acc: 0.8975, loss_cls: 2.0120, loss: 2.0120 +2025-06-24 10:24:15,919 - pyskl - INFO - Saving checkpoint at 2 epochs +2025-06-24 10:25:00,907 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:25:00,966 - pyskl - INFO - +top1_acc 0.4860 +top5_acc 0.8806 +2025-06-24 10:25:00,966 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:25:00,973 - pyskl - INFO - +mean_acc 0.3341 +2025-06-24 10:25:00,977 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_1.pth was removed +2025-06-24 10:25:01,176 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_2.pth. +2025-06-24 10:25:01,176 - pyskl - INFO - Best top1_acc is 0.4860 at 2 epoch. +2025-06-24 10:25:01,179 - pyskl - INFO - Epoch(val) [2][533] top1_acc: 0.4860, top5_acc: 0.8806, mean_class_accuracy: 0.3341 +2025-06-24 10:25:42,297 - pyskl - INFO - Epoch [3][100/1281] lr: 2.499e-02, eta: 11:59:12, time: 0.411, data_time: 0.191, memory: 4082, top1_acc: 0.5200, top5_acc: 0.8950, loss_cls: 1.9662, loss: 1.9662 +2025-06-24 10:26:04,200 - pyskl - INFO - Epoch [3][200/1281] lr: 2.499e-02, eta: 11:57:50, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.5337, top5_acc: 0.9131, loss_cls: 1.9240, loss: 1.9240 +2025-06-24 10:26:26,183 - pyskl - INFO - Epoch [3][300/1281] lr: 2.499e-02, eta: 11:56:37, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5450, top5_acc: 0.9050, loss_cls: 1.8935, loss: 1.8935 +2025-06-24 10:26:48,180 - pyskl - INFO - Epoch [3][400/1281] lr: 2.499e-02, eta: 11:55:28, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5569, top5_acc: 0.9181, loss_cls: 1.8250, loss: 1.8250 +2025-06-24 10:27:09,980 - pyskl - INFO - Epoch [3][500/1281] lr: 2.498e-02, eta: 11:54:11, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.5625, top5_acc: 0.9194, loss_cls: 1.7692, loss: 1.7692 +2025-06-24 10:27:32,061 - pyskl - INFO - Epoch [3][600/1281] lr: 2.498e-02, eta: 11:53:13, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.5506, top5_acc: 0.9150, loss_cls: 1.8507, loss: 1.8507 +2025-06-24 10:27:54,018 - pyskl - INFO - Epoch [3][700/1281] lr: 2.498e-02, eta: 11:52:11, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5481, top5_acc: 0.9031, loss_cls: 1.8963, loss: 1.8963 +2025-06-24 10:28:15,872 - pyskl - INFO - Epoch [3][800/1281] lr: 2.498e-02, eta: 11:51:05, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.5775, top5_acc: 0.9213, loss_cls: 1.7492, loss: 1.7492 +2025-06-24 10:28:37,845 - pyskl - INFO - Epoch [3][900/1281] lr: 2.498e-02, eta: 11:50:08, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5713, top5_acc: 0.9331, loss_cls: 1.7428, loss: 1.7428 +2025-06-24 10:28:59,709 - pyskl - INFO - Epoch [3][1000/1281] lr: 2.498e-02, eta: 11:49:07, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.5756, top5_acc: 0.9219, loss_cls: 1.7473, loss: 1.7473 +2025-06-24 10:29:21,643 - pyskl - INFO - Epoch [3][1100/1281] lr: 2.498e-02, eta: 11:48:12, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6075, top5_acc: 0.9375, loss_cls: 1.6352, loss: 1.6352 +2025-06-24 10:29:43,499 - pyskl - INFO - Epoch [3][1200/1281] lr: 2.498e-02, eta: 11:47:15, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6206, top5_acc: 0.9400, loss_cls: 1.6018, loss: 1.6018 +2025-06-24 10:30:02,205 - pyskl - INFO - Saving checkpoint at 3 epochs +2025-06-24 10:30:46,441 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:30:46,505 - pyskl - INFO - +top1_acc 0.5796 +top5_acc 0.9283 +2025-06-24 10:30:46,505 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:30:46,512 - pyskl - INFO - +mean_acc 0.4355 +2025-06-24 10:30:46,516 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_2.pth was removed +2025-06-24 10:30:46,704 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_3.pth. +2025-06-24 10:30:46,705 - pyskl - INFO - Best top1_acc is 0.5796 at 3 epoch. +2025-06-24 10:30:46,708 - pyskl - INFO - Epoch(val) [3][533] top1_acc: 0.5796, top5_acc: 0.9283, mean_class_accuracy: 0.4355 +2025-06-24 10:31:27,775 - pyskl - INFO - Epoch [4][100/1281] lr: 2.497e-02, eta: 11:46:48, time: 0.411, data_time: 0.190, memory: 4082, top1_acc: 0.5956, top5_acc: 0.9487, loss_cls: 1.6217, loss: 1.6217 +2025-06-24 10:31:49,931 - pyskl - INFO - Epoch [4][200/1281] lr: 2.497e-02, eta: 11:46:08, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.6094, top5_acc: 0.9419, loss_cls: 1.5966, loss: 1.5966 +2025-06-24 10:32:11,928 - pyskl - INFO - Epoch [4][300/1281] lr: 2.497e-02, eta: 11:45:22, time: 0.220, data_time: 0.001, memory: 4082, top1_acc: 0.6169, top5_acc: 0.9437, loss_cls: 1.5618, loss: 1.5618 +2025-06-24 10:32:33,929 - pyskl - INFO - Epoch [4][400/1281] lr: 2.497e-02, eta: 11:44:37, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.6275, top5_acc: 0.9419, loss_cls: 1.5616, loss: 1.5616 +2025-06-24 10:32:56,099 - pyskl - INFO - Epoch [4][500/1281] lr: 2.497e-02, eta: 11:44:00, time: 0.222, data_time: 0.001, memory: 4082, top1_acc: 0.6325, top5_acc: 0.9406, loss_cls: 1.5510, loss: 1.5510 +2025-06-24 10:33:18,549 - pyskl - INFO - Epoch [4][600/1281] lr: 2.497e-02, eta: 11:43:36, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.6169, top5_acc: 0.9375, loss_cls: 1.5528, loss: 1.5528 +2025-06-24 10:33:40,782 - pyskl - INFO - Epoch [4][700/1281] lr: 2.497e-02, eta: 11:43:02, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.6156, top5_acc: 0.9531, loss_cls: 1.5376, loss: 1.5376 +2025-06-24 10:34:02,919 - pyskl - INFO - Epoch [4][800/1281] lr: 2.496e-02, eta: 11:42:26, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.6438, top5_acc: 0.9587, loss_cls: 1.4327, loss: 1.4327 +2025-06-24 10:34:24,966 - pyskl - INFO - Epoch [4][900/1281] lr: 2.496e-02, eta: 11:41:46, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.6400, top5_acc: 0.9463, loss_cls: 1.4947, loss: 1.4947 +2025-06-24 10:34:47,215 - pyskl - INFO - Epoch [4][1000/1281] lr: 2.496e-02, eta: 11:41:15, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.6388, top5_acc: 0.9481, loss_cls: 1.5111, loss: 1.5111 +2025-06-24 10:35:09,179 - pyskl - INFO - Epoch [4][1100/1281] lr: 2.496e-02, eta: 11:40:34, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.6250, top5_acc: 0.9431, loss_cls: 1.5259, loss: 1.5259 +2025-06-24 10:35:30,932 - pyskl - INFO - Epoch [4][1200/1281] lr: 2.496e-02, eta: 11:39:46, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.6438, top5_acc: 0.9550, loss_cls: 1.4622, loss: 1.4622 +2025-06-24 10:35:49,403 - pyskl - INFO - Saving checkpoint at 4 epochs +2025-06-24 10:36:33,994 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:36:34,048 - pyskl - INFO - +top1_acc 0.6268 +top5_acc 0.9522 +2025-06-24 10:36:34,048 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:36:34,057 - pyskl - INFO - +mean_acc 0.4958 +2025-06-24 10:36:34,063 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_3.pth was removed +2025-06-24 10:36:34,277 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_4.pth. +2025-06-24 10:36:34,277 - pyskl - INFO - Best top1_acc is 0.6268 at 4 epoch. +2025-06-24 10:36:34,280 - pyskl - INFO - Epoch(val) [4][533] top1_acc: 0.6268, top5_acc: 0.9522, mean_class_accuracy: 0.4958 +2025-06-24 10:37:15,044 - pyskl - INFO - Epoch [5][100/1281] lr: 2.495e-02, eta: 11:39:10, time: 0.408, data_time: 0.189, memory: 4082, top1_acc: 0.6806, top5_acc: 0.9619, loss_cls: 1.3558, loss: 1.3558 +2025-06-24 10:37:36,817 - pyskl - INFO - Epoch [5][200/1281] lr: 2.495e-02, eta: 11:38:24, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.6750, top5_acc: 0.9531, loss_cls: 1.4216, loss: 1.4216 +2025-06-24 10:37:58,869 - pyskl - INFO - Epoch [5][300/1281] lr: 2.495e-02, eta: 11:37:49, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.6687, top5_acc: 0.9613, loss_cls: 1.3580, loss: 1.3580 +2025-06-24 10:38:20,701 - pyskl - INFO - Epoch [5][400/1281] lr: 2.495e-02, eta: 11:37:06, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.6619, top5_acc: 0.9619, loss_cls: 1.3694, loss: 1.3694 +2025-06-24 10:38:42,848 - pyskl - INFO - Epoch [5][500/1281] lr: 2.495e-02, eta: 11:36:35, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.6544, top5_acc: 0.9600, loss_cls: 1.4321, loss: 1.4321 +2025-06-24 10:39:05,023 - pyskl - INFO - Epoch [5][600/1281] lr: 2.495e-02, eta: 11:36:05, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.6675, top5_acc: 0.9625, loss_cls: 1.3814, loss: 1.3814 +2025-06-24 10:39:27,032 - pyskl - INFO - Epoch [5][700/1281] lr: 2.494e-02, eta: 11:35:30, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.6694, top5_acc: 0.9650, loss_cls: 1.3168, loss: 1.3168 +2025-06-24 10:39:48,846 - pyskl - INFO - Epoch [5][800/1281] lr: 2.494e-02, eta: 11:34:49, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.6500, top5_acc: 0.9650, loss_cls: 1.3709, loss: 1.3709 +2025-06-24 10:40:10,551 - pyskl - INFO - Epoch [5][900/1281] lr: 2.494e-02, eta: 11:34:06, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6750, top5_acc: 0.9625, loss_cls: 1.3212, loss: 1.3212 +2025-06-24 10:40:32,220 - pyskl - INFO - Epoch [5][1000/1281] lr: 2.494e-02, eta: 11:33:22, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6963, top5_acc: 0.9706, loss_cls: 1.2577, loss: 1.2577 +2025-06-24 10:40:54,205 - pyskl - INFO - Epoch [5][1100/1281] lr: 2.494e-02, eta: 11:32:48, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.6694, top5_acc: 0.9675, loss_cls: 1.3099, loss: 1.3099 +2025-06-24 10:41:16,015 - pyskl - INFO - Epoch [5][1200/1281] lr: 2.493e-02, eta: 11:32:10, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.6819, top5_acc: 0.9594, loss_cls: 1.3229, loss: 1.3229 +2025-06-24 10:41:34,442 - pyskl - INFO - Saving checkpoint at 5 epochs +2025-06-24 10:42:19,144 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:42:19,213 - pyskl - INFO - +top1_acc 0.6517 +top5_acc 0.9605 +2025-06-24 10:42:19,214 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:42:19,222 - pyskl - INFO - +mean_acc 0.5148 +2025-06-24 10:42:19,227 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_4.pth was removed +2025-06-24 10:42:19,429 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_5.pth. +2025-06-24 10:42:19,430 - pyskl - INFO - Best top1_acc is 0.6517 at 5 epoch. +2025-06-24 10:42:19,433 - pyskl - INFO - Epoch(val) [5][533] top1_acc: 0.6517, top5_acc: 0.9605, mean_class_accuracy: 0.5148 +2025-06-24 10:43:00,912 - pyskl - INFO - Epoch [6][100/1281] lr: 2.493e-02, eta: 11:31:58, time: 0.415, data_time: 0.194, memory: 4082, top1_acc: 0.6956, top5_acc: 0.9606, loss_cls: 1.2932, loss: 1.2932 +2025-06-24 10:43:22,987 - pyskl - INFO - Epoch [6][200/1281] lr: 2.493e-02, eta: 11:31:28, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.6919, top5_acc: 0.9700, loss_cls: 1.2503, loss: 1.2503 +2025-06-24 10:43:45,292 - pyskl - INFO - Epoch [6][300/1281] lr: 2.492e-02, eta: 11:31:04, time: 0.223, data_time: 0.001, memory: 4082, top1_acc: 0.7087, top5_acc: 0.9731, loss_cls: 1.2092, loss: 1.2092 +2025-06-24 10:44:07,443 - pyskl - INFO - Epoch [6][400/1281] lr: 2.492e-02, eta: 11:30:36, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.6800, top5_acc: 0.9669, loss_cls: 1.3038, loss: 1.3038 +2025-06-24 10:44:29,336 - pyskl - INFO - Epoch [6][500/1281] lr: 2.492e-02, eta: 11:30:01, time: 0.219, data_time: 0.001, memory: 4082, top1_acc: 0.7119, top5_acc: 0.9706, loss_cls: 1.2702, loss: 1.2702 +2025-06-24 10:44:51,510 - pyskl - INFO - Epoch [6][600/1281] lr: 2.492e-02, eta: 11:29:34, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.6850, top5_acc: 0.9663, loss_cls: 1.2600, loss: 1.2600 +2025-06-24 10:45:13,902 - pyskl - INFO - Epoch [6][700/1281] lr: 2.492e-02, eta: 11:29:13, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.7225, top5_acc: 0.9700, loss_cls: 1.2067, loss: 1.2067 +2025-06-24 10:45:36,281 - pyskl - INFO - Epoch [6][800/1281] lr: 2.491e-02, eta: 11:28:51, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.7100, top5_acc: 0.9700, loss_cls: 1.2105, loss: 1.2105 +2025-06-24 10:45:58,093 - pyskl - INFO - Epoch [6][900/1281] lr: 2.491e-02, eta: 11:28:15, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7131, top5_acc: 0.9775, loss_cls: 1.2169, loss: 1.2169 +2025-06-24 10:46:20,299 - pyskl - INFO - Epoch [6][1000/1281] lr: 2.491e-02, eta: 11:27:50, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.7031, top5_acc: 0.9706, loss_cls: 1.2175, loss: 1.2175 +2025-06-24 10:46:42,386 - pyskl - INFO - Epoch [6][1100/1281] lr: 2.491e-02, eta: 11:27:21, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7037, top5_acc: 0.9656, loss_cls: 1.2397, loss: 1.2397 +2025-06-24 10:47:04,246 - pyskl - INFO - Epoch [6][1200/1281] lr: 2.490e-02, eta: 11:26:47, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7262, top5_acc: 0.9694, loss_cls: 1.1857, loss: 1.1857 +2025-06-24 10:47:22,870 - pyskl - INFO - Saving checkpoint at 6 epochs +2025-06-24 10:48:07,560 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:48:07,633 - pyskl - INFO - +top1_acc 0.6871 +top5_acc 0.9669 +2025-06-24 10:48:07,633 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:48:07,641 - pyskl - INFO - +mean_acc 0.5599 +2025-06-24 10:48:07,645 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_5.pth was removed +2025-06-24 10:48:07,861 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_6.pth. +2025-06-24 10:48:07,862 - pyskl - INFO - Best top1_acc is 0.6871 at 6 epoch. +2025-06-24 10:48:07,865 - pyskl - INFO - Epoch(val) [6][533] top1_acc: 0.6871, top5_acc: 0.9669, mean_class_accuracy: 0.5599 +2025-06-24 10:48:49,330 - pyskl - INFO - Epoch [7][100/1281] lr: 2.490e-02, eta: 11:26:31, time: 0.415, data_time: 0.192, memory: 4082, top1_acc: 0.6981, top5_acc: 0.9781, loss_cls: 1.1861, loss: 1.1861 +2025-06-24 10:49:11,300 - pyskl - INFO - Epoch [7][200/1281] lr: 2.490e-02, eta: 11:26:00, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7175, top5_acc: 0.9712, loss_cls: 1.1658, loss: 1.1658 +2025-06-24 10:49:33,444 - pyskl - INFO - Epoch [7][300/1281] lr: 2.489e-02, eta: 11:25:34, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7119, top5_acc: 0.9744, loss_cls: 1.1490, loss: 1.1490 +2025-06-24 10:49:55,449 - pyskl - INFO - Epoch [7][400/1281] lr: 2.489e-02, eta: 11:25:04, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7094, top5_acc: 0.9750, loss_cls: 1.2133, loss: 1.2133 +2025-06-24 10:50:17,428 - pyskl - INFO - Epoch [7][500/1281] lr: 2.489e-02, eta: 11:24:33, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7288, top5_acc: 0.9731, loss_cls: 1.1335, loss: 1.1335 +2025-06-24 10:50:39,520 - pyskl - INFO - Epoch [7][600/1281] lr: 2.489e-02, eta: 11:24:06, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7131, top5_acc: 0.9762, loss_cls: 1.1873, loss: 1.1873 +2025-06-24 10:51:01,602 - pyskl - INFO - Epoch [7][700/1281] lr: 2.488e-02, eta: 11:23:38, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7069, top5_acc: 0.9725, loss_cls: 1.1958, loss: 1.1958 +2025-06-24 10:51:23,582 - pyskl - INFO - Epoch [7][800/1281] lr: 2.488e-02, eta: 11:23:08, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7225, top5_acc: 0.9788, loss_cls: 1.1835, loss: 1.1835 +2025-06-24 10:51:45,595 - pyskl - INFO - Epoch [7][900/1281] lr: 2.488e-02, eta: 11:22:40, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7250, top5_acc: 0.9744, loss_cls: 1.1802, loss: 1.1802 +2025-06-24 10:52:07,962 - pyskl - INFO - Epoch [7][1000/1281] lr: 2.487e-02, eta: 11:22:18, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.7181, top5_acc: 0.9762, loss_cls: 1.1264, loss: 1.1264 +2025-06-24 10:52:30,136 - pyskl - INFO - Epoch [7][1100/1281] lr: 2.487e-02, eta: 11:21:53, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.7275, top5_acc: 0.9788, loss_cls: 1.1281, loss: 1.1281 +2025-06-24 10:52:52,203 - pyskl - INFO - Epoch [7][1200/1281] lr: 2.487e-02, eta: 11:21:26, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7269, top5_acc: 0.9694, loss_cls: 1.1339, loss: 1.1339 +2025-06-24 10:53:10,878 - pyskl - INFO - Saving checkpoint at 7 epochs +2025-06-24 10:53:55,108 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:53:55,170 - pyskl - INFO - +top1_acc 0.6877 +top5_acc 0.9642 +2025-06-24 10:53:55,170 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:53:55,177 - pyskl - INFO - +mean_acc 0.5723 +2025-06-24 10:53:55,181 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_6.pth was removed +2025-06-24 10:53:55,364 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_7.pth. +2025-06-24 10:53:55,364 - pyskl - INFO - Best top1_acc is 0.6877 at 7 epoch. +2025-06-24 10:53:55,368 - pyskl - INFO - Epoch(val) [7][533] top1_acc: 0.6877, top5_acc: 0.9642, mean_class_accuracy: 0.5723 +2025-06-24 10:54:36,365 - pyskl - INFO - Epoch [8][100/1281] lr: 2.486e-02, eta: 11:20:58, time: 0.410, data_time: 0.188, memory: 4082, top1_acc: 0.7444, top5_acc: 0.9781, loss_cls: 1.0802, loss: 1.0802 +2025-06-24 10:54:58,638 - pyskl - INFO - Epoch [8][200/1281] lr: 2.486e-02, eta: 11:20:34, time: 0.223, data_time: 0.000, memory: 4082, top1_acc: 0.7381, top5_acc: 0.9781, loss_cls: 1.0777, loss: 1.0777 +2025-06-24 10:55:20,844 - pyskl - INFO - Epoch [8][300/1281] lr: 2.486e-02, eta: 11:20:10, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.7119, top5_acc: 0.9756, loss_cls: 1.1746, loss: 1.1746 +2025-06-24 10:55:43,202 - pyskl - INFO - Epoch [8][400/1281] lr: 2.485e-02, eta: 11:19:48, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.7400, top5_acc: 0.9725, loss_cls: 1.1369, loss: 1.1369 +2025-06-24 10:56:05,284 - pyskl - INFO - Epoch [8][500/1281] lr: 2.485e-02, eta: 11:19:22, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7288, top5_acc: 0.9750, loss_cls: 1.1199, loss: 1.1199 +2025-06-24 10:56:27,258 - pyskl - INFO - Epoch [8][600/1281] lr: 2.485e-02, eta: 11:18:53, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7550, top5_acc: 0.9781, loss_cls: 1.0827, loss: 1.0827 +2025-06-24 10:56:49,551 - pyskl - INFO - Epoch [8][700/1281] lr: 2.484e-02, eta: 11:18:30, time: 0.223, data_time: 0.000, memory: 4082, top1_acc: 0.7300, top5_acc: 0.9700, loss_cls: 1.1230, loss: 1.1230 +2025-06-24 10:57:11,283 - pyskl - INFO - Epoch [8][800/1281] lr: 2.484e-02, eta: 11:17:57, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7556, top5_acc: 0.9756, loss_cls: 1.0714, loss: 1.0714 +2025-06-24 10:57:33,053 - pyskl - INFO - Epoch [8][900/1281] lr: 2.484e-02, eta: 11:17:25, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7450, top5_acc: 0.9744, loss_cls: 1.0892, loss: 1.0892 +2025-06-24 10:57:54,737 - pyskl - INFO - Epoch [8][1000/1281] lr: 2.483e-02, eta: 11:16:51, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7219, top5_acc: 0.9731, loss_cls: 1.1541, loss: 1.1541 +2025-06-24 10:58:16,703 - pyskl - INFO - Epoch [8][1100/1281] lr: 2.483e-02, eta: 11:16:23, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7475, top5_acc: 0.9794, loss_cls: 1.0647, loss: 1.0647 +2025-06-24 10:58:38,780 - pyskl - INFO - Epoch [8][1200/1281] lr: 2.483e-02, eta: 11:15:57, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7419, top5_acc: 0.9750, loss_cls: 1.0674, loss: 1.0674 +2025-06-24 10:58:57,292 - pyskl - INFO - Saving checkpoint at 8 epochs +2025-06-24 10:59:41,911 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:59:41,972 - pyskl - INFO - +top1_acc 0.7132 +top5_acc 0.9741 +2025-06-24 10:59:41,972 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:59:41,979 - pyskl - INFO - +mean_acc 0.6029 +2025-06-24 10:59:41,983 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_7.pth was removed +2025-06-24 10:59:42,318 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_8.pth. +2025-06-24 10:59:42,318 - pyskl - INFO - Best top1_acc is 0.7132 at 8 epoch. +2025-06-24 10:59:42,321 - pyskl - INFO - Epoch(val) [8][533] top1_acc: 0.7132, top5_acc: 0.9741, mean_class_accuracy: 0.6029 +2025-06-24 11:00:23,917 - pyskl - INFO - Epoch [9][100/1281] lr: 2.482e-02, eta: 11:15:39, time: 0.416, data_time: 0.195, memory: 4082, top1_acc: 0.7538, top5_acc: 0.9806, loss_cls: 1.0702, loss: 1.0702 +2025-06-24 11:00:45,762 - pyskl - INFO - Epoch [9][200/1281] lr: 2.482e-02, eta: 11:15:08, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7506, top5_acc: 0.9794, loss_cls: 1.0238, loss: 1.0238 +2025-06-24 11:01:07,900 - pyskl - INFO - Epoch [9][300/1281] lr: 2.481e-02, eta: 11:14:43, time: 0.221, data_time: 0.001, memory: 4082, top1_acc: 0.7550, top5_acc: 0.9838, loss_cls: 1.0149, loss: 1.0149 +2025-06-24 11:01:30,119 - pyskl - INFO - Epoch [9][400/1281] lr: 2.481e-02, eta: 11:14:20, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.7419, top5_acc: 0.9856, loss_cls: 1.0638, loss: 1.0638 +2025-06-24 11:01:52,193 - pyskl - INFO - Epoch [9][500/1281] lr: 2.481e-02, eta: 11:13:54, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7331, top5_acc: 0.9806, loss_cls: 1.0700, loss: 1.0700 +2025-06-24 11:02:14,396 - pyskl - INFO - Epoch [9][600/1281] lr: 2.480e-02, eta: 11:13:30, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.7394, top5_acc: 0.9812, loss_cls: 1.0898, loss: 1.0898 +2025-06-24 11:02:36,584 - pyskl - INFO - Epoch [9][700/1281] lr: 2.480e-02, eta: 11:13:06, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.7619, top5_acc: 0.9762, loss_cls: 1.0234, loss: 1.0234 +2025-06-24 11:02:58,969 - pyskl - INFO - Epoch [9][800/1281] lr: 2.480e-02, eta: 11:12:45, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.7381, top5_acc: 0.9825, loss_cls: 1.0539, loss: 1.0539 +2025-06-24 11:03:21,602 - pyskl - INFO - Epoch [9][900/1281] lr: 2.479e-02, eta: 11:12:29, time: 0.226, data_time: 0.000, memory: 4082, top1_acc: 0.7444, top5_acc: 0.9819, loss_cls: 1.0650, loss: 1.0650 +2025-06-24 11:03:43,971 - pyskl - INFO - Epoch [9][1000/1281] lr: 2.479e-02, eta: 11:12:08, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.7544, top5_acc: 0.9769, loss_cls: 1.0763, loss: 1.0763 +2025-06-24 11:04:06,484 - pyskl - INFO - Epoch [9][1100/1281] lr: 2.479e-02, eta: 11:11:49, time: 0.225, data_time: 0.000, memory: 4082, top1_acc: 0.7362, top5_acc: 0.9712, loss_cls: 1.1349, loss: 1.1349 +2025-06-24 11:04:28,532 - pyskl - INFO - Epoch [9][1200/1281] lr: 2.478e-02, eta: 11:11:23, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7588, top5_acc: 0.9781, loss_cls: 1.0684, loss: 1.0684 +2025-06-24 11:04:47,097 - pyskl - INFO - Saving checkpoint at 9 epochs +2025-06-24 11:05:31,235 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:05:31,295 - pyskl - INFO - +top1_acc 0.7420 +top5_acc 0.9724 +2025-06-24 11:05:31,295 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:05:31,303 - pyskl - INFO - +mean_acc 0.6104 +2025-06-24 11:05:31,308 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_8.pth was removed +2025-06-24 11:05:31,483 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_9.pth. +2025-06-24 11:05:31,484 - pyskl - INFO - Best top1_acc is 0.7420 at 9 epoch. +2025-06-24 11:05:31,487 - pyskl - INFO - Epoch(val) [9][533] top1_acc: 0.7420, top5_acc: 0.9724, mean_class_accuracy: 0.6104 +2025-06-24 11:06:13,125 - pyskl - INFO - Epoch [10][100/1281] lr: 2.477e-02, eta: 11:11:02, time: 0.416, data_time: 0.196, memory: 4082, top1_acc: 0.7588, top5_acc: 0.9831, loss_cls: 1.0103, loss: 1.0103 +2025-06-24 11:06:34,967 - pyskl - INFO - Epoch [10][200/1281] lr: 2.477e-02, eta: 11:10:33, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7612, top5_acc: 0.9850, loss_cls: 1.0139, loss: 1.0139 +2025-06-24 11:06:57,318 - pyskl - INFO - Epoch [10][300/1281] lr: 2.477e-02, eta: 11:10:11, time: 0.223, data_time: 0.001, memory: 4082, top1_acc: 0.7688, top5_acc: 0.9875, loss_cls: 0.9883, loss: 0.9883 +2025-06-24 11:07:19,358 - pyskl - INFO - Epoch [10][400/1281] lr: 2.476e-02, eta: 11:09:45, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7681, top5_acc: 0.9819, loss_cls: 1.0024, loss: 1.0024 +2025-06-24 11:07:41,362 - pyskl - INFO - Epoch [10][500/1281] lr: 2.476e-02, eta: 11:09:18, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7588, top5_acc: 0.9862, loss_cls: 0.9866, loss: 0.9866 +2025-06-24 11:08:03,290 - pyskl - INFO - Epoch [10][600/1281] lr: 2.476e-02, eta: 11:08:51, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7412, top5_acc: 0.9812, loss_cls: 1.0533, loss: 1.0533 +2025-06-24 11:08:25,363 - pyskl - INFO - Epoch [10][700/1281] lr: 2.475e-02, eta: 11:08:25, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7638, top5_acc: 0.9819, loss_cls: 1.0247, loss: 1.0247 +2025-06-24 11:08:47,497 - pyskl - INFO - Epoch [10][800/1281] lr: 2.475e-02, eta: 11:08:00, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7612, top5_acc: 0.9800, loss_cls: 0.9959, loss: 0.9959 +2025-06-24 11:09:09,427 - pyskl - INFO - Epoch [10][900/1281] lr: 2.474e-02, eta: 11:07:33, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7694, top5_acc: 0.9819, loss_cls: 0.9878, loss: 0.9878 +2025-06-24 11:09:31,427 - pyskl - INFO - Epoch [10][1000/1281] lr: 2.474e-02, eta: 11:07:07, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7506, top5_acc: 0.9775, loss_cls: 1.1042, loss: 1.1042 +2025-06-24 11:09:53,345 - pyskl - INFO - Epoch [10][1100/1281] lr: 2.473e-02, eta: 11:06:39, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7550, top5_acc: 0.9769, loss_cls: 1.0369, loss: 1.0369 +2025-06-24 11:10:15,179 - pyskl - INFO - Epoch [10][1200/1281] lr: 2.473e-02, eta: 11:06:10, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7631, top5_acc: 0.9869, loss_cls: 1.0297, loss: 1.0297 +2025-06-24 11:10:33,573 - pyskl - INFO - Saving checkpoint at 10 epochs +2025-06-24 11:11:17,773 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:11:17,831 - pyskl - INFO - +top1_acc 0.7239 +top5_acc 0.9745 +2025-06-24 11:11:17,831 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:11:17,837 - pyskl - INFO - +mean_acc 0.6346 +2025-06-24 11:11:17,839 - pyskl - INFO - Epoch(val) [10][533] top1_acc: 0.7239, top5_acc: 0.9745, mean_class_accuracy: 0.6346 +2025-06-24 11:11:59,385 - pyskl - INFO - Epoch [11][100/1281] lr: 2.472e-02, eta: 11:05:47, time: 0.415, data_time: 0.193, memory: 4082, top1_acc: 0.7594, top5_acc: 0.9806, loss_cls: 0.9893, loss: 0.9893 +2025-06-24 11:12:21,495 - pyskl - INFO - Epoch [11][200/1281] lr: 2.472e-02, eta: 11:05:22, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7913, top5_acc: 0.9869, loss_cls: 0.9209, loss: 0.9209 +2025-06-24 11:12:43,803 - pyskl - INFO - Epoch [11][300/1281] lr: 2.471e-02, eta: 11:05:00, time: 0.223, data_time: 0.000, memory: 4082, top1_acc: 0.7444, top5_acc: 0.9800, loss_cls: 1.0719, loss: 1.0719 +2025-06-24 11:13:05,894 - pyskl - INFO - Epoch [11][400/1281] lr: 2.471e-02, eta: 11:04:35, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7806, top5_acc: 0.9838, loss_cls: 0.9809, loss: 0.9809 +2025-06-24 11:13:27,989 - pyskl - INFO - Epoch [11][500/1281] lr: 2.471e-02, eta: 11:04:11, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7731, top5_acc: 0.9869, loss_cls: 0.9930, loss: 0.9930 +2025-06-24 11:13:50,500 - pyskl - INFO - Epoch [11][600/1281] lr: 2.470e-02, eta: 11:03:51, time: 0.225, data_time: 0.000, memory: 4082, top1_acc: 0.7588, top5_acc: 0.9831, loss_cls: 1.0136, loss: 1.0136 +2025-06-24 11:14:12,886 - pyskl - INFO - Epoch [11][700/1281] lr: 2.470e-02, eta: 11:03:30, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.7769, top5_acc: 0.9825, loss_cls: 0.9735, loss: 0.9735 +2025-06-24 11:14:35,022 - pyskl - INFO - Epoch [11][800/1281] lr: 2.469e-02, eta: 11:03:06, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7612, top5_acc: 0.9869, loss_cls: 0.9702, loss: 0.9702 +2025-06-24 11:14:57,251 - pyskl - INFO - Epoch [11][900/1281] lr: 2.469e-02, eta: 11:02:43, time: 0.222, data_time: 0.001, memory: 4082, top1_acc: 0.7775, top5_acc: 0.9838, loss_cls: 0.9585, loss: 0.9585 +2025-06-24 11:15:19,523 - pyskl - INFO - Epoch [11][1000/1281] lr: 2.468e-02, eta: 11:02:21, time: 0.223, data_time: 0.000, memory: 4082, top1_acc: 0.7512, top5_acc: 0.9819, loss_cls: 1.0237, loss: 1.0237 +2025-06-24 11:15:41,569 - pyskl - INFO - Epoch [11][1100/1281] lr: 2.468e-02, eta: 11:01:55, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7788, top5_acc: 0.9812, loss_cls: 0.9749, loss: 0.9749 +2025-06-24 11:16:03,720 - pyskl - INFO - Epoch [11][1200/1281] lr: 2.467e-02, eta: 11:01:31, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.7444, top5_acc: 0.9838, loss_cls: 1.0454, loss: 1.0454 +2025-06-24 11:16:22,451 - pyskl - INFO - Saving checkpoint at 11 epochs +2025-06-24 11:17:05,839 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:17:05,899 - pyskl - INFO - +top1_acc 0.7462 +top5_acc 0.9800 +2025-06-24 11:17:05,899 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:17:05,907 - pyskl - INFO - +mean_acc 0.6549 +2025-06-24 11:17:05,911 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_9.pth was removed +2025-06-24 11:17:06,081 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_11.pth. +2025-06-24 11:17:06,081 - pyskl - INFO - Best top1_acc is 0.7462 at 11 epoch. +2025-06-24 11:17:06,084 - pyskl - INFO - Epoch(val) [11][533] top1_acc: 0.7462, top5_acc: 0.9800, mean_class_accuracy: 0.6549 +2025-06-24 11:17:47,576 - pyskl - INFO - Epoch [12][100/1281] lr: 2.467e-02, eta: 11:01:05, time: 0.415, data_time: 0.196, memory: 4082, top1_acc: 0.7800, top5_acc: 0.9869, loss_cls: 0.9396, loss: 0.9396 +2025-06-24 11:18:09,435 - pyskl - INFO - Epoch [12][200/1281] lr: 2.466e-02, eta: 11:00:38, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7750, top5_acc: 0.9869, loss_cls: 0.9469, loss: 0.9469 +2025-06-24 11:18:31,504 - pyskl - INFO - Epoch [12][300/1281] lr: 2.466e-02, eta: 11:00:13, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7881, top5_acc: 0.9819, loss_cls: 0.9414, loss: 0.9414 +2025-06-24 11:18:53,327 - pyskl - INFO - Epoch [12][400/1281] lr: 2.465e-02, eta: 10:59:45, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7825, top5_acc: 0.9844, loss_cls: 0.9291, loss: 0.9291 +2025-06-24 11:19:15,043 - pyskl - INFO - Epoch [12][500/1281] lr: 2.465e-02, eta: 10:59:16, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7788, top5_acc: 0.9856, loss_cls: 0.9481, loss: 0.9481 +2025-06-24 11:19:36,862 - pyskl - INFO - Epoch [12][600/1281] lr: 2.464e-02, eta: 10:58:48, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7937, top5_acc: 0.9831, loss_cls: 0.9233, loss: 0.9233 +2025-06-24 11:19:58,815 - pyskl - INFO - Epoch [12][700/1281] lr: 2.464e-02, eta: 10:58:22, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7919, top5_acc: 0.9856, loss_cls: 0.9388, loss: 0.9388 +2025-06-24 11:20:20,874 - pyskl - INFO - Epoch [12][800/1281] lr: 2.463e-02, eta: 10:57:57, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7612, top5_acc: 0.9825, loss_cls: 1.0287, loss: 1.0287 +2025-06-24 11:20:42,787 - pyskl - INFO - Epoch [12][900/1281] lr: 2.463e-02, eta: 10:57:30, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7744, top5_acc: 0.9869, loss_cls: 0.9343, loss: 0.9343 +2025-06-24 11:21:04,558 - pyskl - INFO - Epoch [12][1000/1281] lr: 2.462e-02, eta: 10:57:02, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7863, top5_acc: 0.9869, loss_cls: 0.9402, loss: 0.9402 +2025-06-24 11:21:26,953 - pyskl - INFO - Epoch [12][1100/1281] lr: 2.462e-02, eta: 10:56:41, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.7887, top5_acc: 0.9825, loss_cls: 0.9259, loss: 0.9259 +2025-06-24 11:21:48,860 - pyskl - INFO - Epoch [12][1200/1281] lr: 2.461e-02, eta: 10:56:15, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7850, top5_acc: 0.9850, loss_cls: 0.9345, loss: 0.9345 +2025-06-24 11:22:07,260 - pyskl - INFO - Saving checkpoint at 12 epochs +2025-06-24 11:22:51,825 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:22:51,882 - pyskl - INFO - +top1_acc 0.7102 +top5_acc 0.9669 +2025-06-24 11:22:51,882 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:22:51,889 - pyskl - INFO - +mean_acc 0.6373 +2025-06-24 11:22:51,890 - pyskl - INFO - Epoch(val) [12][533] top1_acc: 0.7102, top5_acc: 0.9669, mean_class_accuracy: 0.6373 +2025-06-24 11:23:33,168 - pyskl - INFO - Epoch [13][100/1281] lr: 2.460e-02, eta: 10:55:46, time: 0.413, data_time: 0.194, memory: 4082, top1_acc: 0.7825, top5_acc: 0.9881, loss_cls: 0.8999, loss: 0.8999 +2025-06-24 11:23:55,793 - pyskl - INFO - Epoch [13][200/1281] lr: 2.460e-02, eta: 10:55:28, time: 0.226, data_time: 0.000, memory: 4082, top1_acc: 0.7881, top5_acc: 0.9888, loss_cls: 0.8728, loss: 0.8728 +2025-06-24 11:24:18,038 - pyskl - INFO - Epoch [13][300/1281] lr: 2.459e-02, eta: 10:55:05, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.7937, top5_acc: 0.9831, loss_cls: 0.8925, loss: 0.8925 +2025-06-24 11:24:40,028 - pyskl - INFO - Epoch [13][400/1281] lr: 2.459e-02, eta: 10:54:40, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7850, top5_acc: 0.9881, loss_cls: 0.9280, loss: 0.9280 +2025-06-24 11:25:02,467 - pyskl - INFO - Epoch [13][500/1281] lr: 2.458e-02, eta: 10:54:19, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.7781, top5_acc: 0.9888, loss_cls: 0.9185, loss: 0.9185 +2025-06-24 11:25:24,522 - pyskl - INFO - Epoch [13][600/1281] lr: 2.458e-02, eta: 10:53:55, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7925, top5_acc: 0.9869, loss_cls: 0.9135, loss: 0.9135 +2025-06-24 11:25:46,580 - pyskl - INFO - Epoch [13][700/1281] lr: 2.457e-02, eta: 10:53:30, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7756, top5_acc: 0.9819, loss_cls: 0.9596, loss: 0.9596 +2025-06-24 11:26:08,588 - pyskl - INFO - Epoch [13][800/1281] lr: 2.457e-02, eta: 10:53:05, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8037, top5_acc: 0.9856, loss_cls: 0.8730, loss: 0.8730 +2025-06-24 11:26:30,609 - pyskl - INFO - Epoch [13][900/1281] lr: 2.456e-02, eta: 10:52:40, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7944, top5_acc: 0.9844, loss_cls: 0.9052, loss: 0.9052 +2025-06-24 11:26:52,443 - pyskl - INFO - Epoch [13][1000/1281] lr: 2.455e-02, eta: 10:52:13, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7831, top5_acc: 0.9812, loss_cls: 0.9445, loss: 0.9445 +2025-06-24 11:27:14,368 - pyskl - INFO - Epoch [13][1100/1281] lr: 2.455e-02, eta: 10:51:47, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7656, top5_acc: 0.9756, loss_cls: 0.9963, loss: 0.9963 +2025-06-24 11:27:36,409 - pyskl - INFO - Epoch [13][1200/1281] lr: 2.454e-02, eta: 10:51:22, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8019, top5_acc: 0.9875, loss_cls: 0.8912, loss: 0.8912 +2025-06-24 11:27:55,019 - pyskl - INFO - Saving checkpoint at 13 epochs +2025-06-24 11:28:39,360 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:28:39,433 - pyskl - INFO - +top1_acc 0.7397 +top5_acc 0.9728 +2025-06-24 11:28:39,434 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:28:39,443 - pyskl - INFO - +mean_acc 0.6672 +2025-06-24 11:28:39,446 - pyskl - INFO - Epoch(val) [13][533] top1_acc: 0.7397, top5_acc: 0.9728, mean_class_accuracy: 0.6672 +2025-06-24 11:29:21,334 - pyskl - INFO - Epoch [14][100/1281] lr: 2.453e-02, eta: 10:50:59, time: 0.419, data_time: 0.200, memory: 4082, top1_acc: 0.7900, top5_acc: 0.9850, loss_cls: 0.9143, loss: 0.9143 +2025-06-24 11:29:43,270 - pyskl - INFO - Epoch [14][200/1281] lr: 2.453e-02, eta: 10:50:33, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8056, top5_acc: 0.9900, loss_cls: 0.8437, loss: 0.8437 +2025-06-24 11:30:05,278 - pyskl - INFO - Epoch [14][300/1281] lr: 2.452e-02, eta: 10:50:08, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7844, top5_acc: 0.9869, loss_cls: 0.9306, loss: 0.9306 +2025-06-24 11:30:26,833 - pyskl - INFO - Epoch [14][400/1281] lr: 2.452e-02, eta: 10:49:39, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7831, top5_acc: 0.9894, loss_cls: 0.9122, loss: 0.9122 +2025-06-24 11:30:48,573 - pyskl - INFO - Epoch [14][500/1281] lr: 2.451e-02, eta: 10:49:11, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7806, top5_acc: 0.9806, loss_cls: 0.9382, loss: 0.9382 +2025-06-24 11:31:10,351 - pyskl - INFO - Epoch [14][600/1281] lr: 2.451e-02, eta: 10:48:44, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8013, top5_acc: 0.9875, loss_cls: 0.8944, loss: 0.8944 +2025-06-24 11:31:32,205 - pyskl - INFO - Epoch [14][700/1281] lr: 2.450e-02, eta: 10:48:18, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8031, top5_acc: 0.9850, loss_cls: 0.8608, loss: 0.8608 +2025-06-24 11:31:54,134 - pyskl - INFO - Epoch [14][800/1281] lr: 2.449e-02, eta: 10:47:52, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7937, top5_acc: 0.9931, loss_cls: 0.8677, loss: 0.8677 +2025-06-24 11:32:15,877 - pyskl - INFO - Epoch [14][900/1281] lr: 2.449e-02, eta: 10:47:25, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7981, top5_acc: 0.9900, loss_cls: 0.9016, loss: 0.9016 +2025-06-24 11:32:38,172 - pyskl - INFO - Epoch [14][1000/1281] lr: 2.448e-02, eta: 10:47:03, time: 0.223, data_time: 0.001, memory: 4082, top1_acc: 0.7769, top5_acc: 0.9825, loss_cls: 0.9231, loss: 0.9231 +2025-06-24 11:33:00,186 - pyskl - INFO - Epoch [14][1100/1281] lr: 2.448e-02, eta: 10:46:38, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7850, top5_acc: 0.9794, loss_cls: 0.9723, loss: 0.9723 +2025-06-24 11:33:22,123 - pyskl - INFO - Epoch [14][1200/1281] lr: 2.447e-02, eta: 10:46:13, time: 0.219, data_time: 0.001, memory: 4082, top1_acc: 0.8187, top5_acc: 0.9888, loss_cls: 0.8397, loss: 0.8397 +2025-06-24 11:33:40,527 - pyskl - INFO - Saving checkpoint at 14 epochs +2025-06-24 11:34:25,295 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:34:25,351 - pyskl - INFO - +top1_acc 0.7450 +top5_acc 0.9795 +2025-06-24 11:34:25,352 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:34:25,359 - pyskl - INFO - +mean_acc 0.6396 +2025-06-24 11:34:25,361 - pyskl - INFO - Epoch(val) [14][533] top1_acc: 0.7450, top5_acc: 0.9795, mean_class_accuracy: 0.6396 +2025-06-24 11:35:06,389 - pyskl - INFO - Epoch [15][100/1281] lr: 2.446e-02, eta: 10:45:40, time: 0.410, data_time: 0.189, memory: 4082, top1_acc: 0.8081, top5_acc: 0.9894, loss_cls: 0.8244, loss: 0.8244 +2025-06-24 11:35:28,462 - pyskl - INFO - Epoch [15][200/1281] lr: 2.445e-02, eta: 10:45:16, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8119, top5_acc: 0.9894, loss_cls: 0.8222, loss: 0.8222 +2025-06-24 11:35:50,701 - pyskl - INFO - Epoch [15][300/1281] lr: 2.445e-02, eta: 10:44:54, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.8094, top5_acc: 0.9888, loss_cls: 0.8365, loss: 0.8365 +2025-06-24 11:36:12,679 - pyskl - INFO - Epoch [15][400/1281] lr: 2.444e-02, eta: 10:44:29, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8069, top5_acc: 0.9856, loss_cls: 0.8532, loss: 0.8532 +2025-06-24 11:36:34,884 - pyskl - INFO - Epoch [15][500/1281] lr: 2.444e-02, eta: 10:44:06, time: 0.222, data_time: 0.001, memory: 4082, top1_acc: 0.8113, top5_acc: 0.9906, loss_cls: 0.8264, loss: 0.8264 +2025-06-24 11:36:56,685 - pyskl - INFO - Epoch [15][600/1281] lr: 2.443e-02, eta: 10:43:40, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7919, top5_acc: 0.9875, loss_cls: 0.9042, loss: 0.9042 +2025-06-24 11:37:18,618 - pyskl - INFO - Epoch [15][700/1281] lr: 2.442e-02, eta: 10:43:15, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7931, top5_acc: 0.9869, loss_cls: 0.8832, loss: 0.8832 +2025-06-24 11:37:40,764 - pyskl - INFO - Epoch [15][800/1281] lr: 2.442e-02, eta: 10:42:52, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7887, top5_acc: 0.9869, loss_cls: 0.9223, loss: 0.9223 +2025-06-24 11:38:02,687 - pyskl - INFO - Epoch [15][900/1281] lr: 2.441e-02, eta: 10:42:26, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8000, top5_acc: 0.9888, loss_cls: 0.8700, loss: 0.8700 +2025-06-24 11:38:24,576 - pyskl - INFO - Epoch [15][1000/1281] lr: 2.441e-02, eta: 10:42:01, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8075, top5_acc: 0.9888, loss_cls: 0.8552, loss: 0.8552 +2025-06-24 11:38:46,323 - pyskl - INFO - Epoch [15][1100/1281] lr: 2.440e-02, eta: 10:41:34, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8175, top5_acc: 0.9844, loss_cls: 0.8572, loss: 0.8572 +2025-06-24 11:39:08,017 - pyskl - INFO - Epoch [15][1200/1281] lr: 2.439e-02, eta: 10:41:07, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7837, top5_acc: 0.9838, loss_cls: 0.9098, loss: 0.9098 +2025-06-24 11:39:26,454 - pyskl - INFO - Saving checkpoint at 15 epochs +2025-06-24 11:40:10,687 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:40:10,754 - pyskl - INFO - +top1_acc 0.7778 +top5_acc 0.9812 +2025-06-24 11:40:10,755 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:40:10,763 - pyskl - INFO - +mean_acc 0.6808 +2025-06-24 11:40:10,767 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_11.pth was removed +2025-06-24 11:40:10,971 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_15.pth. +2025-06-24 11:40:10,971 - pyskl - INFO - Best top1_acc is 0.7778 at 15 epoch. +2025-06-24 11:40:10,974 - pyskl - INFO - Epoch(val) [15][533] top1_acc: 0.7778, top5_acc: 0.9812, mean_class_accuracy: 0.6808 +2025-06-24 11:40:52,621 - pyskl - INFO - Epoch [16][100/1281] lr: 2.438e-02, eta: 10:40:39, time: 0.416, data_time: 0.195, memory: 4082, top1_acc: 0.7869, top5_acc: 0.9906, loss_cls: 0.8576, loss: 0.8576 +2025-06-24 11:41:14,503 - pyskl - INFO - Epoch [16][200/1281] lr: 2.438e-02, eta: 10:40:14, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8125, top5_acc: 0.9912, loss_cls: 0.8083, loss: 0.8083 +2025-06-24 11:41:36,486 - pyskl - INFO - Epoch [16][300/1281] lr: 2.437e-02, eta: 10:39:49, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8119, top5_acc: 0.9838, loss_cls: 0.8508, loss: 0.8508 +2025-06-24 11:41:58,575 - pyskl - INFO - Epoch [16][400/1281] lr: 2.436e-02, eta: 10:39:26, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8250, top5_acc: 0.9906, loss_cls: 0.8142, loss: 0.8142 +2025-06-24 11:42:20,529 - pyskl - INFO - Epoch [16][500/1281] lr: 2.436e-02, eta: 10:39:01, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8137, top5_acc: 0.9875, loss_cls: 0.8365, loss: 0.8365 +2025-06-24 11:42:42,843 - pyskl - INFO - Epoch [16][600/1281] lr: 2.435e-02, eta: 10:38:40, time: 0.223, data_time: 0.000, memory: 4082, top1_acc: 0.8106, top5_acc: 0.9862, loss_cls: 0.8563, loss: 0.8563 +2025-06-24 11:43:04,926 - pyskl - INFO - Epoch [16][700/1281] lr: 2.434e-02, eta: 10:38:16, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8181, top5_acc: 0.9862, loss_cls: 0.8427, loss: 0.8427 +2025-06-24 11:43:26,998 - pyskl - INFO - Epoch [16][800/1281] lr: 2.434e-02, eta: 10:37:52, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8131, top5_acc: 0.9856, loss_cls: 0.8663, loss: 0.8663 +2025-06-24 11:43:48,870 - pyskl - INFO - Epoch [16][900/1281] lr: 2.433e-02, eta: 10:37:27, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8144, top5_acc: 0.9925, loss_cls: 0.8332, loss: 0.8332 +2025-06-24 11:44:11,080 - pyskl - INFO - Epoch [16][1000/1281] lr: 2.432e-02, eta: 10:37:05, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.8094, top5_acc: 0.9875, loss_cls: 0.8264, loss: 0.8264 +2025-06-24 11:44:33,249 - pyskl - INFO - Epoch [16][1100/1281] lr: 2.432e-02, eta: 10:36:42, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.8100, top5_acc: 0.9900, loss_cls: 0.8550, loss: 0.8550 +2025-06-24 11:44:54,853 - pyskl - INFO - Epoch [16][1200/1281] lr: 2.431e-02, eta: 10:36:14, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8200, top5_acc: 0.9925, loss_cls: 0.8081, loss: 0.8081 +2025-06-24 11:45:13,364 - pyskl - INFO - Saving checkpoint at 16 epochs +2025-06-24 11:45:58,063 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:45:58,120 - pyskl - INFO - +top1_acc 0.7988 +top5_acc 0.9847 +2025-06-24 11:45:58,120 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:45:58,127 - pyskl - INFO - +mean_acc 0.6886 +2025-06-24 11:45:58,131 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_15.pth was removed +2025-06-24 11:45:58,308 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_16.pth. +2025-06-24 11:45:58,308 - pyskl - INFO - Best top1_acc is 0.7988 at 16 epoch. +2025-06-24 11:45:58,311 - pyskl - INFO - Epoch(val) [16][533] top1_acc: 0.7988, top5_acc: 0.9847, mean_class_accuracy: 0.6886 +2025-06-24 11:46:40,082 - pyskl - INFO - Epoch [17][100/1281] lr: 2.430e-02, eta: 10:35:47, time: 0.418, data_time: 0.195, memory: 4082, top1_acc: 0.8231, top5_acc: 0.9912, loss_cls: 0.7861, loss: 0.7861 +2025-06-24 11:47:02,218 - pyskl - INFO - Epoch [17][200/1281] lr: 2.429e-02, eta: 10:35:24, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8281, top5_acc: 0.9881, loss_cls: 0.7825, loss: 0.7825 +2025-06-24 11:47:24,080 - pyskl - INFO - Epoch [17][300/1281] lr: 2.428e-02, eta: 10:34:58, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8281, top5_acc: 0.9844, loss_cls: 0.7876, loss: 0.7876 +2025-06-24 11:47:46,529 - pyskl - INFO - Epoch [17][400/1281] lr: 2.428e-02, eta: 10:34:38, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9900, loss_cls: 0.7412, loss: 0.7412 +2025-06-24 11:48:08,899 - pyskl - INFO - Epoch [17][500/1281] lr: 2.427e-02, eta: 10:34:17, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.8150, top5_acc: 0.9919, loss_cls: 0.7959, loss: 0.7959 +2025-06-24 11:48:30,821 - pyskl - INFO - Epoch [17][600/1281] lr: 2.426e-02, eta: 10:33:52, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8363, top5_acc: 0.9888, loss_cls: 0.7926, loss: 0.7926 +2025-06-24 11:48:52,926 - pyskl - INFO - Epoch [17][700/1281] lr: 2.426e-02, eta: 10:33:29, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8181, top5_acc: 0.9888, loss_cls: 0.8050, loss: 0.8050 +2025-06-24 11:49:14,761 - pyskl - INFO - Epoch [17][800/1281] lr: 2.425e-02, eta: 10:33:03, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8350, top5_acc: 0.9888, loss_cls: 0.7842, loss: 0.7842 +2025-06-24 11:49:36,780 - pyskl - INFO - Epoch [17][900/1281] lr: 2.424e-02, eta: 10:32:39, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8137, top5_acc: 0.9900, loss_cls: 0.8177, loss: 0.8177 +2025-06-24 11:49:58,578 - pyskl - INFO - Epoch [17][1000/1281] lr: 2.424e-02, eta: 10:32:14, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8025, top5_acc: 0.9900, loss_cls: 0.8226, loss: 0.8226 +2025-06-24 11:50:20,520 - pyskl - INFO - Epoch [17][1100/1281] lr: 2.423e-02, eta: 10:31:49, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8006, top5_acc: 0.9875, loss_cls: 0.8441, loss: 0.8441 +2025-06-24 11:50:42,374 - pyskl - INFO - Epoch [17][1200/1281] lr: 2.422e-02, eta: 10:31:24, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8137, top5_acc: 0.9900, loss_cls: 0.8301, loss: 0.8301 +2025-06-24 11:51:00,926 - pyskl - INFO - Saving checkpoint at 17 epochs +2025-06-24 11:51:44,923 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:51:44,979 - pyskl - INFO - +top1_acc 0.7837 +top5_acc 0.9850 +2025-06-24 11:51:44,979 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:51:44,986 - pyskl - INFO - +mean_acc 0.7031 +2025-06-24 11:51:44,988 - pyskl - INFO - Epoch(val) [17][533] top1_acc: 0.7837, top5_acc: 0.9850, mean_class_accuracy: 0.7031 +2025-06-24 11:52:26,536 - pyskl - INFO - Epoch [18][100/1281] lr: 2.421e-02, eta: 10:30:54, time: 0.415, data_time: 0.196, memory: 4082, top1_acc: 0.8194, top5_acc: 0.9888, loss_cls: 0.8309, loss: 0.8309 +2025-06-24 11:52:48,680 - pyskl - INFO - Epoch [18][200/1281] lr: 2.420e-02, eta: 10:30:31, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8081, top5_acc: 0.9888, loss_cls: 0.8395, loss: 0.8395 +2025-06-24 11:53:10,760 - pyskl - INFO - Epoch [18][300/1281] lr: 2.419e-02, eta: 10:30:08, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8100, top5_acc: 0.9900, loss_cls: 0.8393, loss: 0.8393 +2025-06-24 11:53:32,569 - pyskl - INFO - Epoch [18][400/1281] lr: 2.419e-02, eta: 10:29:42, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8337, top5_acc: 0.9875, loss_cls: 0.7647, loss: 0.7647 +2025-06-24 11:53:54,602 - pyskl - INFO - Epoch [18][500/1281] lr: 2.418e-02, eta: 10:29:18, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8250, top5_acc: 0.9900, loss_cls: 0.7780, loss: 0.7780 +2025-06-24 11:54:16,866 - pyskl - INFO - Epoch [18][600/1281] lr: 2.417e-02, eta: 10:28:57, time: 0.223, data_time: 0.000, memory: 4082, top1_acc: 0.8156, top5_acc: 0.9925, loss_cls: 0.7544, loss: 0.7544 +2025-06-24 11:54:38,927 - pyskl - INFO - Epoch [18][700/1281] lr: 2.417e-02, eta: 10:28:33, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8119, top5_acc: 0.9894, loss_cls: 0.8089, loss: 0.8089 +2025-06-24 11:55:00,934 - pyskl - INFO - Epoch [18][800/1281] lr: 2.416e-02, eta: 10:28:09, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8244, top5_acc: 0.9919, loss_cls: 0.7859, loss: 0.7859 +2025-06-24 11:55:22,911 - pyskl - INFO - Epoch [18][900/1281] lr: 2.415e-02, eta: 10:27:45, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8331, top5_acc: 0.9925, loss_cls: 0.7413, loss: 0.7413 +2025-06-24 11:55:44,930 - pyskl - INFO - Epoch [18][1000/1281] lr: 2.414e-02, eta: 10:27:21, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8087, top5_acc: 0.9919, loss_cls: 0.8111, loss: 0.8111 +2025-06-24 11:56:06,960 - pyskl - INFO - Epoch [18][1100/1281] lr: 2.414e-02, eta: 10:26:58, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8094, top5_acc: 0.9869, loss_cls: 0.8428, loss: 0.8428 +2025-06-24 11:56:28,990 - pyskl - INFO - Epoch [18][1200/1281] lr: 2.413e-02, eta: 10:26:34, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9894, loss_cls: 0.7576, loss: 0.7576 +2025-06-24 11:56:47,838 - pyskl - INFO - Saving checkpoint at 18 epochs +2025-06-24 11:57:31,541 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:57:31,595 - pyskl - INFO - +top1_acc 0.7886 +top5_acc 0.9856 +2025-06-24 11:57:31,595 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:57:31,602 - pyskl - INFO - +mean_acc 0.7094 +2025-06-24 11:57:31,604 - pyskl - INFO - Epoch(val) [18][533] top1_acc: 0.7886, top5_acc: 0.9856, mean_class_accuracy: 0.7094 +2025-06-24 11:58:13,064 - pyskl - INFO - Epoch [19][100/1281] lr: 2.411e-02, eta: 10:26:03, time: 0.415, data_time: 0.194, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9950, loss_cls: 0.7544, loss: 0.7544 +2025-06-24 11:58:35,192 - pyskl - INFO - Epoch [19][200/1281] lr: 2.411e-02, eta: 10:25:40, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8306, top5_acc: 0.9825, loss_cls: 0.7810, loss: 0.7810 +2025-06-24 11:58:56,971 - pyskl - INFO - Epoch [19][300/1281] lr: 2.410e-02, eta: 10:25:14, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8444, top5_acc: 0.9906, loss_cls: 0.7261, loss: 0.7261 +2025-06-24 11:59:18,731 - pyskl - INFO - Epoch [19][400/1281] lr: 2.409e-02, eta: 10:24:49, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9938, loss_cls: 0.7888, loss: 0.7888 +2025-06-24 11:59:40,749 - pyskl - INFO - Epoch [19][500/1281] lr: 2.408e-02, eta: 10:24:25, time: 0.220, data_time: 0.001, memory: 4082, top1_acc: 0.8450, top5_acc: 0.9931, loss_cls: 0.7445, loss: 0.7445 +2025-06-24 12:00:02,692 - pyskl - INFO - Epoch [19][600/1281] lr: 2.408e-02, eta: 10:24:01, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8281, top5_acc: 0.9919, loss_cls: 0.7946, loss: 0.7946 +2025-06-24 12:00:24,594 - pyskl - INFO - Epoch [19][700/1281] lr: 2.407e-02, eta: 10:23:36, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8113, top5_acc: 0.9919, loss_cls: 0.8581, loss: 0.8581 +2025-06-24 12:00:46,486 - pyskl - INFO - Epoch [19][800/1281] lr: 2.406e-02, eta: 10:23:12, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8369, top5_acc: 0.9925, loss_cls: 0.7799, loss: 0.7799 +2025-06-24 12:01:08,249 - pyskl - INFO - Epoch [19][900/1281] lr: 2.405e-02, eta: 10:22:46, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8313, top5_acc: 0.9900, loss_cls: 0.7752, loss: 0.7752 +2025-06-24 12:01:30,136 - pyskl - INFO - Epoch [19][1000/1281] lr: 2.405e-02, eta: 10:22:22, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8187, top5_acc: 0.9912, loss_cls: 0.8043, loss: 0.8043 +2025-06-24 12:01:52,054 - pyskl - INFO - Epoch [19][1100/1281] lr: 2.404e-02, eta: 10:21:58, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8081, top5_acc: 0.9888, loss_cls: 0.8664, loss: 0.8664 +2025-06-24 12:02:13,886 - pyskl - INFO - Epoch [19][1200/1281] lr: 2.403e-02, eta: 10:21:33, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8125, top5_acc: 0.9912, loss_cls: 0.8310, loss: 0.8310 +2025-06-24 12:02:32,425 - pyskl - INFO - Saving checkpoint at 19 epochs +2025-06-24 12:03:15,989 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:03:16,045 - pyskl - INFO - +top1_acc 0.7615 +top5_acc 0.9744 +2025-06-24 12:03:16,045 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:03:16,051 - pyskl - INFO - +mean_acc 0.6812 +2025-06-24 12:03:16,053 - pyskl - INFO - Epoch(val) [19][533] top1_acc: 0.7615, top5_acc: 0.9744, mean_class_accuracy: 0.6812 +2025-06-24 12:03:56,878 - pyskl - INFO - Epoch [20][100/1281] lr: 2.402e-02, eta: 10:20:57, time: 0.408, data_time: 0.189, memory: 4082, top1_acc: 0.8263, top5_acc: 0.9925, loss_cls: 0.7758, loss: 0.7758 +2025-06-24 12:04:19,081 - pyskl - INFO - Epoch [20][200/1281] lr: 2.401e-02, eta: 10:20:34, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.8481, top5_acc: 0.9962, loss_cls: 0.7083, loss: 0.7083 +2025-06-24 12:04:41,435 - pyskl - INFO - Epoch [20][300/1281] lr: 2.400e-02, eta: 10:20:13, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.8219, top5_acc: 0.9938, loss_cls: 0.7620, loss: 0.7620 +2025-06-24 12:05:03,532 - pyskl - INFO - Epoch [20][400/1281] lr: 2.399e-02, eta: 10:19:50, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8350, top5_acc: 0.9944, loss_cls: 0.7402, loss: 0.7402 +2025-06-24 12:05:25,358 - pyskl - INFO - Epoch [20][500/1281] lr: 2.398e-02, eta: 10:19:25, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9894, loss_cls: 0.7696, loss: 0.7696 +2025-06-24 12:05:47,588 - pyskl - INFO - Epoch [20][600/1281] lr: 2.398e-02, eta: 10:19:03, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.8219, top5_acc: 0.9869, loss_cls: 0.7990, loss: 0.7990 +2025-06-24 12:06:09,536 - pyskl - INFO - Epoch [20][700/1281] lr: 2.397e-02, eta: 10:18:39, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8213, top5_acc: 0.9925, loss_cls: 0.7745, loss: 0.7745 +2025-06-24 12:06:31,424 - pyskl - INFO - Epoch [20][800/1281] lr: 2.396e-02, eta: 10:18:15, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8506, top5_acc: 0.9956, loss_cls: 0.6976, loss: 0.6976 +2025-06-24 12:06:53,651 - pyskl - INFO - Epoch [20][900/1281] lr: 2.395e-02, eta: 10:17:53, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9938, loss_cls: 0.8165, loss: 0.8165 +2025-06-24 12:07:15,742 - pyskl - INFO - Epoch [20][1000/1281] lr: 2.394e-02, eta: 10:17:30, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8306, top5_acc: 0.9919, loss_cls: 0.7637, loss: 0.7637 +2025-06-24 12:07:37,401 - pyskl - INFO - Epoch [20][1100/1281] lr: 2.393e-02, eta: 10:17:04, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8512, top5_acc: 0.9931, loss_cls: 0.7310, loss: 0.7310 +2025-06-24 12:07:59,337 - pyskl - INFO - Epoch [20][1200/1281] lr: 2.393e-02, eta: 10:16:40, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8400, top5_acc: 0.9925, loss_cls: 0.7352, loss: 0.7352 +2025-06-24 12:08:17,736 - pyskl - INFO - Saving checkpoint at 20 epochs +2025-06-24 12:09:01,990 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:09:02,076 - pyskl - INFO - +top1_acc 0.8121 +top5_acc 0.9865 +2025-06-24 12:09:02,076 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:09:02,084 - pyskl - INFO - +mean_acc 0.7378 +2025-06-24 12:09:02,089 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_16.pth was removed +2025-06-24 12:09:02,294 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_20.pth. +2025-06-24 12:09:02,295 - pyskl - INFO - Best top1_acc is 0.8121 at 20 epoch. +2025-06-24 12:09:02,298 - pyskl - INFO - Epoch(val) [20][533] top1_acc: 0.8121, top5_acc: 0.9865, mean_class_accuracy: 0.7378 +2025-06-24 12:09:44,162 - pyskl - INFO - Epoch [21][100/1281] lr: 2.391e-02, eta: 10:16:10, time: 0.419, data_time: 0.198, memory: 4082, top1_acc: 0.8506, top5_acc: 0.9944, loss_cls: 0.6961, loss: 0.6961 +2025-06-24 12:10:06,253 - pyskl - INFO - Epoch [21][200/1281] lr: 2.390e-02, eta: 10:15:47, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8450, top5_acc: 0.9925, loss_cls: 0.7153, loss: 0.7153 +2025-06-24 12:10:28,292 - pyskl - INFO - Epoch [21][300/1281] lr: 2.389e-02, eta: 10:15:24, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8113, top5_acc: 0.9888, loss_cls: 0.8054, loss: 0.8054 +2025-06-24 12:10:50,289 - pyskl - INFO - Epoch [21][400/1281] lr: 2.389e-02, eta: 10:15:00, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9900, loss_cls: 0.7766, loss: 0.7766 +2025-06-24 12:11:12,141 - pyskl - INFO - Epoch [21][500/1281] lr: 2.388e-02, eta: 10:14:36, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8644, top5_acc: 0.9931, loss_cls: 0.6652, loss: 0.6652 +2025-06-24 12:11:34,213 - pyskl - INFO - Epoch [21][600/1281] lr: 2.387e-02, eta: 10:14:13, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8325, top5_acc: 0.9919, loss_cls: 0.7310, loss: 0.7310 +2025-06-24 12:11:56,185 - pyskl - INFO - Epoch [21][700/1281] lr: 2.386e-02, eta: 10:13:49, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9906, loss_cls: 0.7461, loss: 0.7461 +2025-06-24 12:12:18,019 - pyskl - INFO - Epoch [21][800/1281] lr: 2.385e-02, eta: 10:13:25, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8219, top5_acc: 0.9925, loss_cls: 0.8039, loss: 0.8039 +2025-06-24 12:12:39,781 - pyskl - INFO - Epoch [21][900/1281] lr: 2.384e-02, eta: 10:13:00, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8475, top5_acc: 0.9919, loss_cls: 0.7380, loss: 0.7380 +2025-06-24 12:13:01,888 - pyskl - INFO - Epoch [21][1000/1281] lr: 2.383e-02, eta: 10:12:37, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8325, top5_acc: 0.9944, loss_cls: 0.7547, loss: 0.7547 +2025-06-24 12:13:23,914 - pyskl - INFO - Epoch [21][1100/1281] lr: 2.383e-02, eta: 10:12:13, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8187, top5_acc: 0.9906, loss_cls: 0.8003, loss: 0.8003 +2025-06-24 12:13:45,727 - pyskl - INFO - Epoch [21][1200/1281] lr: 2.382e-02, eta: 10:11:49, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8425, top5_acc: 0.9931, loss_cls: 0.7273, loss: 0.7273 +2025-06-24 12:14:04,440 - pyskl - INFO - Saving checkpoint at 21 epochs +2025-06-24 12:14:48,412 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:14:48,469 - pyskl - INFO - +top1_acc 0.8302 +top5_acc 0.9883 +2025-06-24 12:14:48,470 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:14:48,476 - pyskl - INFO - +mean_acc 0.7640 +2025-06-24 12:14:48,480 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_20.pth was removed +2025-06-24 12:14:48,659 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_21.pth. +2025-06-24 12:14:48,659 - pyskl - INFO - Best top1_acc is 0.8302 at 21 epoch. +2025-06-24 12:14:48,661 - pyskl - INFO - Epoch(val) [21][533] top1_acc: 0.8302, top5_acc: 0.9883, mean_class_accuracy: 0.7640 +2025-06-24 12:15:29,890 - pyskl - INFO - Epoch [22][100/1281] lr: 2.380e-02, eta: 10:11:15, time: 0.412, data_time: 0.189, memory: 4082, top1_acc: 0.8506, top5_acc: 0.9944, loss_cls: 0.6878, loss: 0.6878 +2025-06-24 12:15:52,306 - pyskl - INFO - Epoch [22][200/1281] lr: 2.379e-02, eta: 10:10:54, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9931, loss_cls: 0.6682, loss: 0.6682 +2025-06-24 12:16:14,481 - pyskl - INFO - Epoch [22][300/1281] lr: 2.378e-02, eta: 10:10:32, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.8331, top5_acc: 0.9894, loss_cls: 0.7626, loss: 0.7626 +2025-06-24 12:16:36,644 - pyskl - INFO - Epoch [22][400/1281] lr: 2.378e-02, eta: 10:10:09, time: 0.222, data_time: 0.001, memory: 4082, top1_acc: 0.8400, top5_acc: 0.9912, loss_cls: 0.7660, loss: 0.7660 +2025-06-24 12:16:58,710 - pyskl - INFO - Epoch [22][500/1281] lr: 2.377e-02, eta: 10:09:46, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8500, top5_acc: 0.9931, loss_cls: 0.6812, loss: 0.6812 +2025-06-24 12:17:20,928 - pyskl - INFO - Epoch [22][600/1281] lr: 2.376e-02, eta: 10:09:24, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.8356, top5_acc: 0.9881, loss_cls: 0.7594, loss: 0.7594 +2025-06-24 12:17:42,656 - pyskl - INFO - Epoch [22][700/1281] lr: 2.375e-02, eta: 10:08:59, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8394, top5_acc: 0.9912, loss_cls: 0.6736, loss: 0.6736 +2025-06-24 12:18:04,770 - pyskl - INFO - Epoch [22][800/1281] lr: 2.374e-02, eta: 10:08:36, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9919, loss_cls: 0.7439, loss: 0.7439 +2025-06-24 12:18:26,885 - pyskl - INFO - Epoch [22][900/1281] lr: 2.373e-02, eta: 10:08:13, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8375, top5_acc: 0.9894, loss_cls: 0.7508, loss: 0.7508 +2025-06-24 12:18:48,819 - pyskl - INFO - Epoch [22][1000/1281] lr: 2.372e-02, eta: 10:07:49, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8325, top5_acc: 0.9912, loss_cls: 0.7606, loss: 0.7606 +2025-06-24 12:19:10,685 - pyskl - INFO - Epoch [22][1100/1281] lr: 2.371e-02, eta: 10:07:25, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8275, top5_acc: 0.9931, loss_cls: 0.7529, loss: 0.7529 +2025-06-24 12:19:32,439 - pyskl - INFO - Epoch [22][1200/1281] lr: 2.370e-02, eta: 10:07:00, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8237, top5_acc: 0.9944, loss_cls: 0.7372, loss: 0.7372 +2025-06-24 12:19:50,927 - pyskl - INFO - Saving checkpoint at 22 epochs +2025-06-24 12:20:34,666 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:20:34,745 - pyskl - INFO - +top1_acc 0.8226 +top5_acc 0.9878 +2025-06-24 12:20:34,746 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:20:34,757 - pyskl - INFO - +mean_acc 0.7498 +2025-06-24 12:20:34,759 - pyskl - INFO - Epoch(val) [22][533] top1_acc: 0.8226, top5_acc: 0.9878, mean_class_accuracy: 0.7498 +2025-06-24 12:21:15,815 - pyskl - INFO - Epoch [23][100/1281] lr: 2.369e-02, eta: 10:06:25, time: 0.410, data_time: 0.190, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9931, loss_cls: 0.7422, loss: 0.7422 +2025-06-24 12:21:37,710 - pyskl - INFO - Epoch [23][200/1281] lr: 2.368e-02, eta: 10:06:01, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8569, top5_acc: 0.9931, loss_cls: 0.6580, loss: 0.6580 +2025-06-24 12:21:59,848 - pyskl - INFO - Epoch [23][300/1281] lr: 2.367e-02, eta: 10:05:39, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8181, top5_acc: 0.9900, loss_cls: 0.7645, loss: 0.7645 +2025-06-24 12:22:21,772 - pyskl - INFO - Epoch [23][400/1281] lr: 2.366e-02, eta: 10:05:15, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8606, top5_acc: 0.9931, loss_cls: 0.6496, loss: 0.6496 +2025-06-24 12:22:43,567 - pyskl - INFO - Epoch [23][500/1281] lr: 2.365e-02, eta: 10:04:50, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8350, top5_acc: 0.9938, loss_cls: 0.7402, loss: 0.7402 +2025-06-24 12:23:05,697 - pyskl - INFO - Epoch [23][600/1281] lr: 2.364e-02, eta: 10:04:28, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8469, top5_acc: 0.9912, loss_cls: 0.7174, loss: 0.7174 +2025-06-24 12:23:27,751 - pyskl - INFO - Epoch [23][700/1281] lr: 2.363e-02, eta: 10:04:05, time: 0.221, data_time: 0.001, memory: 4082, top1_acc: 0.8494, top5_acc: 0.9894, loss_cls: 0.7087, loss: 0.7087 +2025-06-24 12:23:49,380 - pyskl - INFO - Epoch [23][800/1281] lr: 2.362e-02, eta: 10:03:39, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8438, top5_acc: 0.9900, loss_cls: 0.7368, loss: 0.7368 +2025-06-24 12:24:11,651 - pyskl - INFO - Epoch [23][900/1281] lr: 2.361e-02, eta: 10:03:17, time: 0.223, data_time: 0.000, memory: 4082, top1_acc: 0.8475, top5_acc: 0.9938, loss_cls: 0.7105, loss: 0.7105 +2025-06-24 12:24:33,864 - pyskl - INFO - Epoch [23][1000/1281] lr: 2.360e-02, eta: 10:02:55, time: 0.222, data_time: 0.001, memory: 4082, top1_acc: 0.8413, top5_acc: 0.9888, loss_cls: 0.7310, loss: 0.7310 +2025-06-24 12:24:55,766 - pyskl - INFO - Epoch [23][1100/1281] lr: 2.359e-02, eta: 10:02:32, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8556, top5_acc: 0.9931, loss_cls: 0.6896, loss: 0.6896 +2025-06-24 12:25:17,434 - pyskl - INFO - Epoch [23][1200/1281] lr: 2.359e-02, eta: 10:02:06, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8325, top5_acc: 0.9900, loss_cls: 0.7895, loss: 0.7895 +2025-06-24 12:25:36,244 - pyskl - INFO - Saving checkpoint at 23 epochs +2025-06-24 12:26:20,556 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:26:20,623 - pyskl - INFO - +top1_acc 0.8223 +top5_acc 0.9876 +2025-06-24 12:26:20,624 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:26:20,632 - pyskl - INFO - +mean_acc 0.7329 +2025-06-24 12:26:20,634 - pyskl - INFO - Epoch(val) [23][533] top1_acc: 0.8223, top5_acc: 0.9876, mean_class_accuracy: 0.7329 +2025-06-24 12:27:01,936 - pyskl - INFO - Epoch [24][100/1281] lr: 2.357e-02, eta: 10:01:32, time: 0.413, data_time: 0.189, memory: 4082, top1_acc: 0.8500, top5_acc: 0.9956, loss_cls: 0.6792, loss: 0.6792 +2025-06-24 12:27:24,379 - pyskl - INFO - Epoch [24][200/1281] lr: 2.356e-02, eta: 10:01:12, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.8606, top5_acc: 0.9925, loss_cls: 0.7045, loss: 0.7045 +2025-06-24 12:27:46,243 - pyskl - INFO - Epoch [24][300/1281] lr: 2.355e-02, eta: 10:00:47, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8519, top5_acc: 0.9919, loss_cls: 0.7194, loss: 0.7194 +2025-06-24 12:28:08,225 - pyskl - INFO - Epoch [24][400/1281] lr: 2.354e-02, eta: 10:00:24, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8644, top5_acc: 0.9938, loss_cls: 0.6378, loss: 0.6378 +2025-06-24 12:28:30,280 - pyskl - INFO - Epoch [24][500/1281] lr: 2.353e-02, eta: 10:00:01, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8294, top5_acc: 0.9869, loss_cls: 0.7653, loss: 0.7653 +2025-06-24 12:28:52,340 - pyskl - INFO - Epoch [24][600/1281] lr: 2.352e-02, eta: 9:59:38, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8425, top5_acc: 0.9950, loss_cls: 0.7127, loss: 0.7127 +2025-06-24 12:29:14,197 - pyskl - INFO - Epoch [24][700/1281] lr: 2.351e-02, eta: 9:59:14, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8525, top5_acc: 0.9931, loss_cls: 0.6653, loss: 0.6653 +2025-06-24 12:29:36,376 - pyskl - INFO - Epoch [24][800/1281] lr: 2.350e-02, eta: 9:58:52, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.8369, top5_acc: 0.9919, loss_cls: 0.7283, loss: 0.7283 +2025-06-24 12:29:58,387 - pyskl - INFO - Epoch [24][900/1281] lr: 2.349e-02, eta: 9:58:29, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8469, top5_acc: 0.9950, loss_cls: 0.7472, loss: 0.7472 +2025-06-24 12:30:20,279 - pyskl - INFO - Epoch [24][1000/1281] lr: 2.348e-02, eta: 9:58:05, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8525, top5_acc: 0.9894, loss_cls: 0.6923, loss: 0.6923 +2025-06-24 12:30:42,245 - pyskl - INFO - Epoch [24][1100/1281] lr: 2.347e-02, eta: 9:57:41, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8444, top5_acc: 0.9950, loss_cls: 0.6875, loss: 0.6875 +2025-06-24 12:31:04,057 - pyskl - INFO - Epoch [24][1200/1281] lr: 2.346e-02, eta: 9:57:17, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8444, top5_acc: 0.9919, loss_cls: 0.7128, loss: 0.7128 +2025-06-24 12:31:22,486 - pyskl - INFO - Saving checkpoint at 24 epochs +2025-06-24 12:32:06,826 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:32:06,893 - pyskl - INFO - +top1_acc 0.7951 +top5_acc 0.9863 +2025-06-24 12:32:06,893 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:32:06,901 - pyskl - INFO - +mean_acc 0.7257 +2025-06-24 12:32:06,903 - pyskl - INFO - Epoch(val) [24][533] top1_acc: 0.7951, top5_acc: 0.9863, mean_class_accuracy: 0.7257 +2025-06-24 12:32:48,078 - pyskl - INFO - Epoch [25][100/1281] lr: 2.344e-02, eta: 9:56:42, time: 0.412, data_time: 0.191, memory: 4082, top1_acc: 0.8256, top5_acc: 0.9925, loss_cls: 0.7476, loss: 0.7476 +2025-06-24 12:33:10,356 - pyskl - INFO - Epoch [25][200/1281] lr: 2.343e-02, eta: 9:56:21, time: 0.223, data_time: 0.000, memory: 4082, top1_acc: 0.8381, top5_acc: 0.9900, loss_cls: 0.7377, loss: 0.7377 +2025-06-24 12:33:32,307 - pyskl - INFO - Epoch [25][300/1281] lr: 2.342e-02, eta: 9:55:57, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8500, top5_acc: 0.9938, loss_cls: 0.6808, loss: 0.6808 +2025-06-24 12:33:54,376 - pyskl - INFO - Epoch [25][400/1281] lr: 2.341e-02, eta: 9:55:34, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8438, top5_acc: 0.9931, loss_cls: 0.7189, loss: 0.7189 +2025-06-24 12:34:16,920 - pyskl - INFO - Epoch [25][500/1281] lr: 2.340e-02, eta: 9:55:14, time: 0.225, data_time: 0.000, memory: 4082, top1_acc: 0.8550, top5_acc: 0.9931, loss_cls: 0.6695, loss: 0.6695 +2025-06-24 12:34:38,910 - pyskl - INFO - Epoch [25][600/1281] lr: 2.339e-02, eta: 9:54:51, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8569, top5_acc: 0.9925, loss_cls: 0.6861, loss: 0.6861 +2025-06-24 12:35:00,967 - pyskl - INFO - Epoch [25][700/1281] lr: 2.338e-02, eta: 9:54:28, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8469, top5_acc: 0.9938, loss_cls: 0.7089, loss: 0.7089 +2025-06-24 12:35:23,225 - pyskl - INFO - Epoch [25][800/1281] lr: 2.337e-02, eta: 9:54:06, time: 0.223, data_time: 0.000, memory: 4082, top1_acc: 0.8469, top5_acc: 0.9925, loss_cls: 0.7025, loss: 0.7025 +2025-06-24 12:35:45,240 - pyskl - INFO - Epoch [25][900/1281] lr: 2.336e-02, eta: 9:53:43, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8694, top5_acc: 0.9888, loss_cls: 0.6588, loss: 0.6588 +2025-06-24 12:36:07,455 - pyskl - INFO - Epoch [25][1000/1281] lr: 2.335e-02, eta: 9:53:21, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.8438, top5_acc: 0.9931, loss_cls: 0.6931, loss: 0.6931 +2025-06-24 12:36:29,548 - pyskl - INFO - Epoch [25][1100/1281] lr: 2.334e-02, eta: 9:52:58, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8581, top5_acc: 0.9912, loss_cls: 0.6854, loss: 0.6854 +2025-06-24 12:36:51,481 - pyskl - INFO - Epoch [25][1200/1281] lr: 2.333e-02, eta: 9:52:34, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8544, top5_acc: 0.9912, loss_cls: 0.6795, loss: 0.6795 +2025-06-24 12:37:10,407 - pyskl - INFO - Saving checkpoint at 25 epochs +2025-06-24 12:37:55,108 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:37:55,164 - pyskl - INFO - +top1_acc 0.7487 +top5_acc 0.9690 +2025-06-24 12:37:55,164 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:37:55,172 - pyskl - INFO - +mean_acc 0.6778 +2025-06-24 12:37:55,173 - pyskl - INFO - Epoch(val) [25][533] top1_acc: 0.7487, top5_acc: 0.9690, mean_class_accuracy: 0.6778 +2025-06-24 12:38:36,844 - pyskl - INFO - Epoch [26][100/1281] lr: 2.332e-02, eta: 9:52:02, time: 0.417, data_time: 0.193, memory: 4082, top1_acc: 0.8406, top5_acc: 0.9950, loss_cls: 0.7070, loss: 0.7070 +2025-06-24 12:38:58,720 - pyskl - INFO - Epoch [26][200/1281] lr: 2.330e-02, eta: 9:51:38, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8562, top5_acc: 0.9906, loss_cls: 0.6380, loss: 0.6380 +2025-06-24 12:39:20,745 - pyskl - INFO - Epoch [26][300/1281] lr: 2.329e-02, eta: 9:51:15, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8488, top5_acc: 0.9938, loss_cls: 0.6810, loss: 0.6810 +2025-06-24 12:39:42,725 - pyskl - INFO - Epoch [26][400/1281] lr: 2.328e-02, eta: 9:50:52, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8688, top5_acc: 0.9931, loss_cls: 0.6374, loss: 0.6374 +2025-06-24 12:40:04,872 - pyskl - INFO - Epoch [26][500/1281] lr: 2.327e-02, eta: 9:50:29, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8512, top5_acc: 0.9912, loss_cls: 0.6942, loss: 0.6942 +2025-06-24 12:40:26,923 - pyskl - INFO - Epoch [26][600/1281] lr: 2.326e-02, eta: 9:50:06, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9938, loss_cls: 0.7080, loss: 0.7080 +2025-06-24 12:40:48,877 - pyskl - INFO - Epoch [26][700/1281] lr: 2.325e-02, eta: 9:49:43, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8381, top5_acc: 0.9925, loss_cls: 0.7158, loss: 0.7158 +2025-06-24 12:41:11,045 - pyskl - INFO - Epoch [26][800/1281] lr: 2.324e-02, eta: 9:49:20, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9919, loss_cls: 0.7619, loss: 0.7619 +2025-06-24 12:41:32,878 - pyskl - INFO - Epoch [26][900/1281] lr: 2.323e-02, eta: 9:48:57, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8569, top5_acc: 0.9912, loss_cls: 0.6925, loss: 0.6925 +2025-06-24 12:41:54,991 - pyskl - INFO - Epoch [26][1000/1281] lr: 2.322e-02, eta: 9:48:34, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8444, top5_acc: 0.9906, loss_cls: 0.7250, loss: 0.7250 +2025-06-24 12:42:17,051 - pyskl - INFO - Epoch [26][1100/1281] lr: 2.321e-02, eta: 9:48:11, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8481, top5_acc: 0.9950, loss_cls: 0.6920, loss: 0.6920 +2025-06-24 12:42:38,987 - pyskl - INFO - Epoch [26][1200/1281] lr: 2.320e-02, eta: 9:47:48, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9931, loss_cls: 0.7263, loss: 0.7263 +2025-06-24 12:42:57,541 - pyskl - INFO - Saving checkpoint at 26 epochs +2025-06-24 12:43:41,985 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:43:42,041 - pyskl - INFO - +top1_acc 0.8341 +top5_acc 0.9869 +2025-06-24 12:43:42,041 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:43:42,048 - pyskl - INFO - +mean_acc 0.7574 +2025-06-24 12:43:42,052 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_21.pth was removed +2025-06-24 12:43:42,218 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_26.pth. +2025-06-24 12:43:42,218 - pyskl - INFO - Best top1_acc is 0.8341 at 26 epoch. +2025-06-24 12:43:42,220 - pyskl - INFO - Epoch(val) [26][533] top1_acc: 0.8341, top5_acc: 0.9869, mean_class_accuracy: 0.7574 +2025-06-24 12:44:23,360 - pyskl - INFO - Epoch [27][100/1281] lr: 2.318e-02, eta: 9:47:12, time: 0.411, data_time: 0.193, memory: 4082, top1_acc: 0.8831, top5_acc: 0.9969, loss_cls: 0.5609, loss: 0.5609 +2025-06-24 12:44:45,613 - pyskl - INFO - Epoch [27][200/1281] lr: 2.317e-02, eta: 9:46:50, time: 0.223, data_time: 0.000, memory: 4082, top1_acc: 0.8369, top5_acc: 0.9956, loss_cls: 0.7135, loss: 0.7135 +2025-06-24 12:45:07,706 - pyskl - INFO - Epoch [27][300/1281] lr: 2.316e-02, eta: 9:46:28, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8600, top5_acc: 0.9925, loss_cls: 0.6599, loss: 0.6599 +2025-06-24 12:45:29,515 - pyskl - INFO - Epoch [27][400/1281] lr: 2.315e-02, eta: 9:46:03, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8506, top5_acc: 0.9888, loss_cls: 0.7025, loss: 0.7025 +2025-06-24 12:45:51,667 - pyskl - INFO - Epoch [27][500/1281] lr: 2.314e-02, eta: 9:45:41, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.8525, top5_acc: 0.9925, loss_cls: 0.6687, loss: 0.6687 +2025-06-24 12:46:13,782 - pyskl - INFO - Epoch [27][600/1281] lr: 2.313e-02, eta: 9:45:19, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8519, top5_acc: 0.9931, loss_cls: 0.6620, loss: 0.6620 +2025-06-24 12:46:35,712 - pyskl - INFO - Epoch [27][700/1281] lr: 2.312e-02, eta: 9:44:55, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8519, top5_acc: 0.9956, loss_cls: 0.6561, loss: 0.6561 +2025-06-24 12:46:57,740 - pyskl - INFO - Epoch [27][800/1281] lr: 2.311e-02, eta: 9:44:32, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8531, top5_acc: 0.9938, loss_cls: 0.7002, loss: 0.7002 +2025-06-24 12:47:19,855 - pyskl - INFO - Epoch [27][900/1281] lr: 2.310e-02, eta: 9:44:10, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8363, top5_acc: 0.9906, loss_cls: 0.7257, loss: 0.7257 +2025-06-24 12:47:42,122 - pyskl - INFO - Epoch [27][1000/1281] lr: 2.308e-02, eta: 9:43:48, time: 0.223, data_time: 0.000, memory: 4082, top1_acc: 0.8650, top5_acc: 0.9944, loss_cls: 0.6333, loss: 0.6333 +2025-06-24 12:48:04,185 - pyskl - INFO - Epoch [27][1100/1281] lr: 2.307e-02, eta: 9:43:25, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8550, top5_acc: 0.9925, loss_cls: 0.6565, loss: 0.6565 +2025-06-24 12:48:26,082 - pyskl - INFO - Epoch [27][1200/1281] lr: 2.306e-02, eta: 9:43:01, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8638, top5_acc: 0.9919, loss_cls: 0.6742, loss: 0.6742 +2025-06-24 12:48:44,685 - pyskl - INFO - Saving checkpoint at 27 epochs +2025-06-24 12:49:29,033 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:49:29,101 - pyskl - INFO - +top1_acc 0.8262 +top5_acc 0.9879 +2025-06-24 12:49:29,101 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:49:29,109 - pyskl - INFO - +mean_acc 0.7527 +2025-06-24 12:49:29,111 - pyskl - INFO - Epoch(val) [27][533] top1_acc: 0.8262, top5_acc: 0.9879, mean_class_accuracy: 0.7527 +2025-06-24 12:50:10,747 - pyskl - INFO - Epoch [28][100/1281] lr: 2.304e-02, eta: 9:42:28, time: 0.416, data_time: 0.192, memory: 4082, top1_acc: 0.8712, top5_acc: 0.9931, loss_cls: 0.6521, loss: 0.6521 +2025-06-24 12:50:32,689 - pyskl - INFO - Epoch [28][200/1281] lr: 2.303e-02, eta: 9:42:05, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8519, top5_acc: 0.9944, loss_cls: 0.6538, loss: 0.6538 +2025-06-24 12:50:54,576 - pyskl - INFO - Epoch [28][300/1281] lr: 2.302e-02, eta: 9:41:41, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8750, top5_acc: 0.9944, loss_cls: 0.6245, loss: 0.6245 +2025-06-24 12:51:16,703 - pyskl - INFO - Epoch [28][400/1281] lr: 2.301e-02, eta: 9:41:19, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8519, top5_acc: 0.9894, loss_cls: 0.6849, loss: 0.6849 +2025-06-24 12:51:38,566 - pyskl - INFO - Epoch [28][500/1281] lr: 2.300e-02, eta: 9:40:55, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8612, top5_acc: 0.9962, loss_cls: 0.6439, loss: 0.6439 +2025-06-24 12:52:00,670 - pyskl - INFO - Epoch [28][600/1281] lr: 2.299e-02, eta: 9:40:32, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8694, top5_acc: 0.9944, loss_cls: 0.6468, loss: 0.6468 +2025-06-24 12:52:22,646 - pyskl - INFO - Epoch [28][700/1281] lr: 2.298e-02, eta: 9:40:09, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8594, top5_acc: 0.9962, loss_cls: 0.6379, loss: 0.6379 +2025-06-24 12:52:44,723 - pyskl - INFO - Epoch [28][800/1281] lr: 2.297e-02, eta: 9:39:46, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8562, top5_acc: 0.9956, loss_cls: 0.6359, loss: 0.6359 +2025-06-24 12:53:07,077 - pyskl - INFO - Epoch [28][900/1281] lr: 2.295e-02, eta: 9:39:25, time: 0.224, data_time: 0.000, memory: 4082, top1_acc: 0.8725, top5_acc: 0.9962, loss_cls: 0.6234, loss: 0.6234 +2025-06-24 12:53:29,174 - pyskl - INFO - Epoch [28][1000/1281] lr: 2.294e-02, eta: 9:39:02, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8694, top5_acc: 0.9906, loss_cls: 0.6810, loss: 0.6810 +2025-06-24 12:53:51,363 - pyskl - INFO - Epoch [28][1100/1281] lr: 2.293e-02, eta: 9:38:40, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.8625, top5_acc: 0.9906, loss_cls: 0.6924, loss: 0.6924 +2025-06-24 12:54:13,474 - pyskl - INFO - Epoch [28][1200/1281] lr: 2.292e-02, eta: 9:38:18, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8456, top5_acc: 0.9919, loss_cls: 0.7075, loss: 0.7075 +2025-06-24 12:54:31,946 - pyskl - INFO - Saving checkpoint at 28 epochs +2025-06-24 12:55:15,643 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:55:15,697 - pyskl - INFO - +top1_acc 0.7223 +top5_acc 0.9572 +2025-06-24 12:55:15,697 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:55:15,704 - pyskl - INFO - +mean_acc 0.6452 +2025-06-24 12:55:15,705 - pyskl - INFO - Epoch(val) [28][533] top1_acc: 0.7223, top5_acc: 0.9572, mean_class_accuracy: 0.6452 +2025-06-24 12:55:57,017 - pyskl - INFO - Epoch [29][100/1281] lr: 2.290e-02, eta: 9:37:42, time: 0.413, data_time: 0.191, memory: 4082, top1_acc: 0.8725, top5_acc: 0.9956, loss_cls: 0.5847, loss: 0.5847 +2025-06-24 12:56:19,013 - pyskl - INFO - Epoch [29][200/1281] lr: 2.289e-02, eta: 9:37:19, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8600, top5_acc: 0.9925, loss_cls: 0.6585, loss: 0.6585 +2025-06-24 12:56:40,759 - pyskl - INFO - Epoch [29][300/1281] lr: 2.288e-02, eta: 9:36:55, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8788, top5_acc: 0.9925, loss_cls: 0.5911, loss: 0.5911 +2025-06-24 12:57:02,767 - pyskl - INFO - Epoch [29][400/1281] lr: 2.287e-02, eta: 9:36:32, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8912, top5_acc: 0.9931, loss_cls: 0.5529, loss: 0.5529 +2025-06-24 12:57:24,662 - pyskl - INFO - Epoch [29][500/1281] lr: 2.285e-02, eta: 9:36:09, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8694, top5_acc: 0.9938, loss_cls: 0.6036, loss: 0.6036 +2025-06-24 12:57:46,533 - pyskl - INFO - Epoch [29][600/1281] lr: 2.284e-02, eta: 9:35:45, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8531, top5_acc: 0.9919, loss_cls: 0.7115, loss: 0.7115 +2025-06-24 12:58:08,403 - pyskl - INFO - Epoch [29][700/1281] lr: 2.283e-02, eta: 9:35:22, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8638, top5_acc: 0.9956, loss_cls: 0.6395, loss: 0.6395 +2025-06-24 12:58:30,238 - pyskl - INFO - Epoch [29][800/1281] lr: 2.282e-02, eta: 9:34:58, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8606, top5_acc: 0.9931, loss_cls: 0.6332, loss: 0.6332 +2025-06-24 12:58:52,457 - pyskl - INFO - Epoch [29][900/1281] lr: 2.281e-02, eta: 9:34:36, time: 0.222, data_time: 0.001, memory: 4082, top1_acc: 0.8656, top5_acc: 0.9900, loss_cls: 0.6541, loss: 0.6541 +2025-06-24 12:59:14,258 - pyskl - INFO - Epoch [29][1000/1281] lr: 2.280e-02, eta: 9:34:12, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8719, top5_acc: 0.9938, loss_cls: 0.6295, loss: 0.6295 +2025-06-24 12:59:36,311 - pyskl - INFO - Epoch [29][1100/1281] lr: 2.279e-02, eta: 9:33:49, time: 0.221, data_time: 0.001, memory: 4082, top1_acc: 0.8494, top5_acc: 0.9944, loss_cls: 0.7016, loss: 0.7016 +2025-06-24 12:59:58,416 - pyskl - INFO - Epoch [29][1200/1281] lr: 2.277e-02, eta: 9:33:27, time: 0.221, data_time: 0.001, memory: 4082, top1_acc: 0.8488, top5_acc: 0.9912, loss_cls: 0.6963, loss: 0.6963 +2025-06-24 13:00:16,981 - pyskl - INFO - Saving checkpoint at 29 epochs +2025-06-24 13:01:01,817 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:01:01,890 - pyskl - INFO - +top1_acc 0.8257 +top5_acc 0.9859 +2025-06-24 13:01:01,890 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:01:01,898 - pyskl - INFO - +mean_acc 0.7710 +2025-06-24 13:01:01,900 - pyskl - INFO - Epoch(val) [29][533] top1_acc: 0.8257, top5_acc: 0.9859, mean_class_accuracy: 0.7710 +2025-06-24 13:01:45,155 - pyskl - INFO - Epoch [30][100/1281] lr: 2.275e-02, eta: 9:32:59, time: 0.433, data_time: 0.204, memory: 4082, top1_acc: 0.8738, top5_acc: 0.9969, loss_cls: 0.5899, loss: 0.5899 +2025-06-24 13:02:07,751 - pyskl - INFO - Epoch [30][200/1281] lr: 2.274e-02, eta: 9:32:39, time: 0.226, data_time: 0.000, memory: 4082, top1_acc: 0.8594, top5_acc: 0.9950, loss_cls: 0.6354, loss: 0.6354 +2025-06-24 13:02:30,708 - pyskl - INFO - Epoch [30][300/1281] lr: 2.273e-02, eta: 9:32:20, time: 0.230, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9912, loss_cls: 0.6431, loss: 0.6431 +2025-06-24 13:02:53,387 - pyskl - INFO - Epoch [30][400/1281] lr: 2.272e-02, eta: 9:32:00, time: 0.227, data_time: 0.000, memory: 4082, top1_acc: 0.8675, top5_acc: 0.9938, loss_cls: 0.6450, loss: 0.6450 +2025-06-24 13:03:16,237 - pyskl - INFO - Epoch [30][500/1281] lr: 2.271e-02, eta: 9:31:40, time: 0.228, data_time: 0.000, memory: 4082, top1_acc: 0.8662, top5_acc: 0.9975, loss_cls: 0.6110, loss: 0.6110 +2025-06-24 13:03:38,932 - pyskl - INFO - Epoch [30][600/1281] lr: 2.269e-02, eta: 9:31:20, time: 0.227, data_time: 0.000, memory: 4082, top1_acc: 0.8606, top5_acc: 0.9925, loss_cls: 0.6482, loss: 0.6482 +2025-06-24 13:04:01,741 - pyskl - INFO - Epoch [30][700/1281] lr: 2.268e-02, eta: 9:31:00, time: 0.228, data_time: 0.000, memory: 4082, top1_acc: 0.8475, top5_acc: 0.9925, loss_cls: 0.7003, loss: 0.7003 +2025-06-24 13:04:24,605 - pyskl - INFO - Epoch [30][800/1281] lr: 2.267e-02, eta: 9:30:41, time: 0.229, data_time: 0.000, memory: 4082, top1_acc: 0.8662, top5_acc: 0.9925, loss_cls: 0.6403, loss: 0.6403 +2025-06-24 13:04:47,518 - pyskl - INFO - Epoch [30][900/1281] lr: 2.266e-02, eta: 9:30:21, time: 0.229, data_time: 0.000, memory: 4082, top1_acc: 0.8638, top5_acc: 0.9912, loss_cls: 0.6235, loss: 0.6235 +2025-06-24 13:05:10,460 - pyskl - INFO - Epoch [30][1000/1281] lr: 2.265e-02, eta: 9:30:02, time: 0.229, data_time: 0.000, memory: 4082, top1_acc: 0.8519, top5_acc: 0.9950, loss_cls: 0.6843, loss: 0.6843 +2025-06-24 13:05:33,247 - pyskl - INFO - Epoch [30][1100/1281] lr: 2.263e-02, eta: 9:29:42, time: 0.228, data_time: 0.000, memory: 4082, top1_acc: 0.8612, top5_acc: 0.9900, loss_cls: 0.6327, loss: 0.6327 +2025-06-24 13:05:55,970 - pyskl - INFO - Epoch [30][1200/1281] lr: 2.262e-02, eta: 9:29:22, time: 0.227, data_time: 0.000, memory: 4082, top1_acc: 0.8531, top5_acc: 0.9906, loss_cls: 0.6743, loss: 0.6743 +2025-06-24 13:06:15,193 - pyskl - INFO - Saving checkpoint at 30 epochs +2025-06-24 13:06:59,164 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:06:59,233 - pyskl - INFO - +top1_acc 0.8235 +top5_acc 0.9866 +2025-06-24 13:06:59,234 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:06:59,241 - pyskl - INFO - +mean_acc 0.7588 +2025-06-24 13:06:59,243 - pyskl - INFO - Epoch(val) [30][533] top1_acc: 0.8235, top5_acc: 0.9866, mean_class_accuracy: 0.7588 +2025-06-24 13:07:42,315 - pyskl - INFO - Epoch [31][100/1281] lr: 2.260e-02, eta: 9:28:53, time: 0.431, data_time: 0.191, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9962, loss_cls: 0.7513, loss: 0.7513 +2025-06-24 13:08:04,480 - pyskl - INFO - Epoch [31][200/1281] lr: 2.259e-02, eta: 9:28:31, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9944, loss_cls: 0.8013, loss: 0.8013 +2025-06-24 13:08:26,855 - pyskl - INFO - Epoch [31][300/1281] lr: 2.258e-02, eta: 9:28:09, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8575, top5_acc: 0.9925, loss_cls: 0.8026, loss: 0.8026 +2025-06-24 13:08:49,092 - pyskl - INFO - Epoch [31][400/1281] lr: 2.256e-02, eta: 9:27:47, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8625, top5_acc: 0.9931, loss_cls: 0.8147, loss: 0.8147 +2025-06-24 13:09:11,563 - pyskl - INFO - Epoch [31][500/1281] lr: 2.255e-02, eta: 9:27:26, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9925, loss_cls: 0.8401, loss: 0.8401 +2025-06-24 13:09:33,696 - pyskl - INFO - Epoch [31][600/1281] lr: 2.254e-02, eta: 9:27:03, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.8462, top5_acc: 0.9888, loss_cls: 0.8723, loss: 0.8723 +2025-06-24 13:09:56,002 - pyskl - INFO - Epoch [31][700/1281] lr: 2.253e-02, eta: 9:26:41, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8506, top5_acc: 0.9925, loss_cls: 0.8384, loss: 0.8384 +2025-06-24 13:10:18,347 - pyskl - INFO - Epoch [31][800/1281] lr: 2.252e-02, eta: 9:26:20, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8538, top5_acc: 0.9956, loss_cls: 0.8297, loss: 0.8297 +2025-06-24 13:10:41,115 - pyskl - INFO - Epoch [31][900/1281] lr: 2.250e-02, eta: 9:26:00, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.8400, top5_acc: 0.9944, loss_cls: 0.8793, loss: 0.8793 +2025-06-24 13:11:03,629 - pyskl - INFO - Epoch [31][1000/1281] lr: 2.249e-02, eta: 9:25:38, time: 0.225, data_time: 0.001, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9962, loss_cls: 0.7534, loss: 0.7534 +2025-06-24 13:11:26,182 - pyskl - INFO - Epoch [31][1100/1281] lr: 2.248e-02, eta: 9:25:17, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8556, top5_acc: 0.9931, loss_cls: 0.8083, loss: 0.8083 +2025-06-24 13:11:48,713 - pyskl - INFO - Epoch [31][1200/1281] lr: 2.247e-02, eta: 9:24:56, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8581, top5_acc: 0.9925, loss_cls: 0.8489, loss: 0.8489 +2025-06-24 13:12:07,769 - pyskl - INFO - Saving checkpoint at 31 epochs +2025-06-24 13:12:51,687 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:12:51,762 - pyskl - INFO - +top1_acc 0.8120 +top5_acc 0.9842 +2025-06-24 13:12:51,762 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:12:51,770 - pyskl - INFO - +mean_acc 0.7507 +2025-06-24 13:12:51,773 - pyskl - INFO - Epoch(val) [31][533] top1_acc: 0.8120, top5_acc: 0.9842, mean_class_accuracy: 0.7507 +2025-06-24 13:13:35,863 - pyskl - INFO - Epoch [32][100/1281] lr: 2.244e-02, eta: 9:24:31, time: 0.441, data_time: 0.197, memory: 4083, top1_acc: 0.8475, top5_acc: 0.9944, loss_cls: 0.7899, loss: 0.7899 +2025-06-24 13:13:58,245 - pyskl - INFO - Epoch [32][200/1281] lr: 2.243e-02, eta: 9:24:09, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8675, top5_acc: 0.9950, loss_cls: 0.7267, loss: 0.7267 +2025-06-24 13:14:20,513 - pyskl - INFO - Epoch [32][300/1281] lr: 2.242e-02, eta: 9:23:47, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9944, loss_cls: 0.6895, loss: 0.6895 +2025-06-24 13:14:43,147 - pyskl - INFO - Epoch [32][400/1281] lr: 2.241e-02, eta: 9:23:26, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8494, top5_acc: 0.9912, loss_cls: 0.7638, loss: 0.7638 +2025-06-24 13:15:05,829 - pyskl - INFO - Epoch [32][500/1281] lr: 2.239e-02, eta: 9:23:06, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.8544, top5_acc: 0.9944, loss_cls: 0.7828, loss: 0.7828 +2025-06-24 13:15:28,685 - pyskl - INFO - Epoch [32][600/1281] lr: 2.238e-02, eta: 9:22:46, time: 0.229, data_time: 0.000, memory: 4083, top1_acc: 0.8738, top5_acc: 0.9962, loss_cls: 0.7065, loss: 0.7065 +2025-06-24 13:15:51,461 - pyskl - INFO - Epoch [32][700/1281] lr: 2.237e-02, eta: 9:22:26, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.8612, top5_acc: 0.9931, loss_cls: 0.7422, loss: 0.7422 +2025-06-24 13:16:13,894 - pyskl - INFO - Epoch [32][800/1281] lr: 2.236e-02, eta: 9:22:04, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8681, top5_acc: 0.9938, loss_cls: 0.7293, loss: 0.7293 +2025-06-24 13:16:37,030 - pyskl - INFO - Epoch [32][900/1281] lr: 2.234e-02, eta: 9:21:45, time: 0.231, data_time: 0.001, memory: 4083, top1_acc: 0.8475, top5_acc: 0.9950, loss_cls: 0.7891, loss: 0.7891 +2025-06-24 13:16:59,643 - pyskl - INFO - Epoch [32][1000/1281] lr: 2.233e-02, eta: 9:21:24, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8550, top5_acc: 0.9925, loss_cls: 0.7694, loss: 0.7694 +2025-06-24 13:17:22,386 - pyskl - INFO - Epoch [32][1100/1281] lr: 2.232e-02, eta: 9:21:04, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.8544, top5_acc: 0.9950, loss_cls: 0.7536, loss: 0.7536 +2025-06-24 13:17:45,015 - pyskl - INFO - Epoch [32][1200/1281] lr: 2.231e-02, eta: 9:20:43, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9894, loss_cls: 0.7170, loss: 0.7170 +2025-06-24 13:18:04,453 - pyskl - INFO - Saving checkpoint at 32 epochs +2025-06-24 13:18:48,501 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:18:48,582 - pyskl - INFO - +top1_acc 0.8186 +top5_acc 0.9881 +2025-06-24 13:18:48,582 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:18:48,593 - pyskl - INFO - +mean_acc 0.7759 +2025-06-24 13:18:48,596 - pyskl - INFO - Epoch(val) [32][533] top1_acc: 0.8186, top5_acc: 0.9881, mean_class_accuracy: 0.7759 +2025-06-24 13:19:31,979 - pyskl - INFO - Epoch [33][100/1281] lr: 2.228e-02, eta: 9:20:14, time: 0.434, data_time: 0.194, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9944, loss_cls: 0.6149, loss: 0.6149 +2025-06-24 13:19:54,752 - pyskl - INFO - Epoch [33][200/1281] lr: 2.227e-02, eta: 9:19:54, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9938, loss_cls: 0.7076, loss: 0.7076 +2025-06-24 13:20:17,147 - pyskl - INFO - Epoch [33][300/1281] lr: 2.226e-02, eta: 9:19:32, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8569, top5_acc: 0.9931, loss_cls: 0.7429, loss: 0.7429 +2025-06-24 13:20:39,994 - pyskl - INFO - Epoch [33][400/1281] lr: 2.225e-02, eta: 9:19:12, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.8562, top5_acc: 0.9956, loss_cls: 0.7157, loss: 0.7157 +2025-06-24 13:21:02,346 - pyskl - INFO - Epoch [33][500/1281] lr: 2.223e-02, eta: 9:18:50, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9981, loss_cls: 0.6444, loss: 0.6444 +2025-06-24 13:21:24,654 - pyskl - INFO - Epoch [33][600/1281] lr: 2.222e-02, eta: 9:18:28, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9919, loss_cls: 0.6718, loss: 0.6718 +2025-06-24 13:21:47,229 - pyskl - INFO - Epoch [33][700/1281] lr: 2.221e-02, eta: 9:18:07, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8356, top5_acc: 0.9919, loss_cls: 0.7920, loss: 0.7920 +2025-06-24 13:22:09,952 - pyskl - INFO - Epoch [33][800/1281] lr: 2.219e-02, eta: 9:17:47, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9975, loss_cls: 0.6509, loss: 0.6509 +2025-06-24 13:22:32,375 - pyskl - INFO - Epoch [33][900/1281] lr: 2.218e-02, eta: 9:17:25, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9950, loss_cls: 0.6666, loss: 0.6666 +2025-06-24 13:22:54,639 - pyskl - INFO - Epoch [33][1000/1281] lr: 2.217e-02, eta: 9:17:03, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9931, loss_cls: 0.6365, loss: 0.6365 +2025-06-24 13:23:17,119 - pyskl - INFO - Epoch [33][1100/1281] lr: 2.216e-02, eta: 9:16:41, time: 0.225, data_time: 0.001, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9925, loss_cls: 0.6998, loss: 0.6998 +2025-06-24 13:23:39,685 - pyskl - INFO - Epoch [33][1200/1281] lr: 2.214e-02, eta: 9:16:20, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8638, top5_acc: 0.9931, loss_cls: 0.6981, loss: 0.6981 +2025-06-24 13:23:58,882 - pyskl - INFO - Saving checkpoint at 33 epochs +2025-06-24 13:24:43,313 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:24:43,379 - pyskl - INFO - +top1_acc 0.7937 +top5_acc 0.9809 +2025-06-24 13:24:43,379 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:24:43,387 - pyskl - INFO - +mean_acc 0.7293 +2025-06-24 13:24:43,389 - pyskl - INFO - Epoch(val) [33][533] top1_acc: 0.7937, top5_acc: 0.9809, mean_class_accuracy: 0.7293 +2025-06-24 13:25:26,193 - pyskl - INFO - Epoch [34][100/1281] lr: 2.212e-02, eta: 9:15:49, time: 0.428, data_time: 0.193, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9956, loss_cls: 0.6350, loss: 0.6350 +2025-06-24 13:25:48,598 - pyskl - INFO - Epoch [34][200/1281] lr: 2.211e-02, eta: 9:15:27, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9919, loss_cls: 0.6850, loss: 0.6850 +2025-06-24 13:26:10,856 - pyskl - INFO - Epoch [34][300/1281] lr: 2.209e-02, eta: 9:15:04, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9950, loss_cls: 0.6616, loss: 0.6616 +2025-06-24 13:26:33,036 - pyskl - INFO - Epoch [34][400/1281] lr: 2.208e-02, eta: 9:14:42, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8556, top5_acc: 0.9912, loss_cls: 0.6931, loss: 0.6931 +2025-06-24 13:26:55,454 - pyskl - INFO - Epoch [34][500/1281] lr: 2.207e-02, eta: 9:14:20, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9944, loss_cls: 0.6552, loss: 0.6552 +2025-06-24 13:27:17,932 - pyskl - INFO - Epoch [34][600/1281] lr: 2.205e-02, eta: 9:13:59, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9925, loss_cls: 0.6362, loss: 0.6362 +2025-06-24 13:27:40,324 - pyskl - INFO - Epoch [34][700/1281] lr: 2.204e-02, eta: 9:13:37, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8738, top5_acc: 0.9938, loss_cls: 0.6545, loss: 0.6545 +2025-06-24 13:28:02,490 - pyskl - INFO - Epoch [34][800/1281] lr: 2.203e-02, eta: 9:13:14, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8462, top5_acc: 0.9900, loss_cls: 0.7330, loss: 0.7330 +2025-06-24 13:28:24,908 - pyskl - INFO - Epoch [34][900/1281] lr: 2.201e-02, eta: 9:12:52, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9962, loss_cls: 0.6426, loss: 0.6426 +2025-06-24 13:28:47,508 - pyskl - INFO - Epoch [34][1000/1281] lr: 2.200e-02, eta: 9:12:31, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8688, top5_acc: 0.9950, loss_cls: 0.6840, loss: 0.6840 +2025-06-24 13:29:10,252 - pyskl - INFO - Epoch [34][1100/1281] lr: 2.199e-02, eta: 9:12:11, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.8656, top5_acc: 0.9962, loss_cls: 0.6736, loss: 0.6736 +2025-06-24 13:29:32,612 - pyskl - INFO - Epoch [34][1200/1281] lr: 2.197e-02, eta: 9:11:49, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8688, top5_acc: 0.9912, loss_cls: 0.6709, loss: 0.6709 +2025-06-24 13:29:51,710 - pyskl - INFO - Saving checkpoint at 34 epochs +2025-06-24 13:30:35,629 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:30:35,686 - pyskl - INFO - +top1_acc 0.8060 +top5_acc 0.9876 +2025-06-24 13:30:35,686 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:30:35,693 - pyskl - INFO - +mean_acc 0.7292 +2025-06-24 13:30:35,696 - pyskl - INFO - Epoch(val) [34][533] top1_acc: 0.8060, top5_acc: 0.9876, mean_class_accuracy: 0.7292 +2025-06-24 13:31:19,536 - pyskl - INFO - Epoch [35][100/1281] lr: 2.195e-02, eta: 9:11:20, time: 0.438, data_time: 0.197, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9962, loss_cls: 0.6219, loss: 0.6219 +2025-06-24 13:31:41,764 - pyskl - INFO - Epoch [35][200/1281] lr: 2.194e-02, eta: 9:10:58, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9962, loss_cls: 0.6346, loss: 0.6346 +2025-06-24 13:32:04,157 - pyskl - INFO - Epoch [35][300/1281] lr: 2.192e-02, eta: 9:10:36, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8656, top5_acc: 0.9962, loss_cls: 0.6689, loss: 0.6689 +2025-06-24 13:32:26,765 - pyskl - INFO - Epoch [35][400/1281] lr: 2.191e-02, eta: 9:10:15, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9950, loss_cls: 0.5887, loss: 0.5887 +2025-06-24 13:32:49,213 - pyskl - INFO - Epoch [35][500/1281] lr: 2.190e-02, eta: 9:09:53, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9931, loss_cls: 0.6600, loss: 0.6600 +2025-06-24 13:33:11,471 - pyskl - INFO - Epoch [35][600/1281] lr: 2.188e-02, eta: 9:09:31, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9950, loss_cls: 0.6519, loss: 0.6519 +2025-06-24 13:33:33,827 - pyskl - INFO - Epoch [35][700/1281] lr: 2.187e-02, eta: 9:09:09, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9975, loss_cls: 0.5819, loss: 0.5819 +2025-06-24 13:33:56,253 - pyskl - INFO - Epoch [35][800/1281] lr: 2.185e-02, eta: 9:08:47, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8606, top5_acc: 0.9931, loss_cls: 0.6755, loss: 0.6755 +2025-06-24 13:34:18,407 - pyskl - INFO - Epoch [35][900/1281] lr: 2.184e-02, eta: 9:08:24, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9938, loss_cls: 0.6611, loss: 0.6611 +2025-06-24 13:34:40,981 - pyskl - INFO - Epoch [35][1000/1281] lr: 2.183e-02, eta: 9:08:03, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9950, loss_cls: 0.6285, loss: 0.6285 +2025-06-24 13:35:03,773 - pyskl - INFO - Epoch [35][1100/1281] lr: 2.181e-02, eta: 9:07:42, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9944, loss_cls: 0.6658, loss: 0.6658 +2025-06-24 13:35:26,209 - pyskl - INFO - Epoch [35][1200/1281] lr: 2.180e-02, eta: 9:07:21, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9938, loss_cls: 0.5984, loss: 0.5984 +2025-06-24 13:35:44,934 - pyskl - INFO - Saving checkpoint at 35 epochs +2025-06-24 13:36:29,189 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:36:29,257 - pyskl - INFO - +top1_acc 0.8147 +top5_acc 0.9827 +2025-06-24 13:36:29,258 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:36:29,266 - pyskl - INFO - +mean_acc 0.7520 +2025-06-24 13:36:29,268 - pyskl - INFO - Epoch(val) [35][533] top1_acc: 0.8147, top5_acc: 0.9827, mean_class_accuracy: 0.7520 +2025-06-24 13:37:11,980 - pyskl - INFO - Epoch [36][100/1281] lr: 2.178e-02, eta: 9:06:48, time: 0.427, data_time: 0.192, memory: 4083, top1_acc: 0.8494, top5_acc: 0.9938, loss_cls: 0.7351, loss: 0.7351 +2025-06-24 13:37:34,574 - pyskl - INFO - Epoch [36][200/1281] lr: 2.176e-02, eta: 9:06:27, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9956, loss_cls: 0.6246, loss: 0.6246 +2025-06-24 13:37:57,070 - pyskl - INFO - Epoch [36][300/1281] lr: 2.175e-02, eta: 9:06:05, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8675, top5_acc: 0.9950, loss_cls: 0.6674, loss: 0.6674 +2025-06-24 13:38:19,570 - pyskl - INFO - Epoch [36][400/1281] lr: 2.173e-02, eta: 9:05:44, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9944, loss_cls: 0.6265, loss: 0.6265 +2025-06-24 13:38:41,957 - pyskl - INFO - Epoch [36][500/1281] lr: 2.172e-02, eta: 9:05:22, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9962, loss_cls: 0.5460, loss: 0.5460 +2025-06-24 13:39:04,364 - pyskl - INFO - Epoch [36][600/1281] lr: 2.171e-02, eta: 9:05:00, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8606, top5_acc: 0.9950, loss_cls: 0.6542, loss: 0.6542 +2025-06-24 13:39:26,622 - pyskl - INFO - Epoch [36][700/1281] lr: 2.169e-02, eta: 9:04:37, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9912, loss_cls: 0.7020, loss: 0.7020 +2025-06-24 13:39:49,334 - pyskl - INFO - Epoch [36][800/1281] lr: 2.168e-02, eta: 9:04:16, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9944, loss_cls: 0.6636, loss: 0.6636 +2025-06-24 13:40:12,068 - pyskl - INFO - Epoch [36][900/1281] lr: 2.167e-02, eta: 9:03:56, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9950, loss_cls: 0.6216, loss: 0.6216 +2025-06-24 13:40:34,494 - pyskl - INFO - Epoch [36][1000/1281] lr: 2.165e-02, eta: 9:03:34, time: 0.224, data_time: 0.001, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9962, loss_cls: 0.6236, loss: 0.6236 +2025-06-24 13:40:56,665 - pyskl - INFO - Epoch [36][1100/1281] lr: 2.164e-02, eta: 9:03:11, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9931, loss_cls: 0.6221, loss: 0.6221 +2025-06-24 13:41:19,589 - pyskl - INFO - Epoch [36][1200/1281] lr: 2.162e-02, eta: 9:02:51, time: 0.229, data_time: 0.000, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9950, loss_cls: 0.6320, loss: 0.6320 +2025-06-24 13:41:38,626 - pyskl - INFO - Saving checkpoint at 36 epochs +2025-06-24 13:42:22,763 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:42:22,824 - pyskl - INFO - +top1_acc 0.8263 +top5_acc 0.9887 +2025-06-24 13:42:22,824 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:42:22,831 - pyskl - INFO - +mean_acc 0.7746 +2025-06-24 13:42:22,833 - pyskl - INFO - Epoch(val) [36][533] top1_acc: 0.8263, top5_acc: 0.9887, mean_class_accuracy: 0.7746 +2025-06-24 13:43:05,821 - pyskl - INFO - Epoch [37][100/1281] lr: 2.160e-02, eta: 9:02:19, time: 0.430, data_time: 0.194, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9931, loss_cls: 0.6624, loss: 0.6624 +2025-06-24 13:43:28,357 - pyskl - INFO - Epoch [37][200/1281] lr: 2.158e-02, eta: 9:01:57, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9956, loss_cls: 0.6163, loss: 0.6163 +2025-06-24 13:43:50,787 - pyskl - INFO - Epoch [37][300/1281] lr: 2.157e-02, eta: 9:01:35, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9962, loss_cls: 0.5922, loss: 0.5922 +2025-06-24 13:44:13,217 - pyskl - INFO - Epoch [37][400/1281] lr: 2.156e-02, eta: 9:01:13, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9925, loss_cls: 0.6627, loss: 0.6627 +2025-06-24 13:44:35,566 - pyskl - INFO - Epoch [37][500/1281] lr: 2.154e-02, eta: 9:00:51, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9944, loss_cls: 0.6507, loss: 0.6507 +2025-06-24 13:44:57,866 - pyskl - INFO - Epoch [37][600/1281] lr: 2.153e-02, eta: 9:00:29, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9956, loss_cls: 0.6412, loss: 0.6412 +2025-06-24 13:45:20,161 - pyskl - INFO - Epoch [37][700/1281] lr: 2.151e-02, eta: 9:00:07, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9931, loss_cls: 0.6164, loss: 0.6164 +2025-06-24 13:45:42,590 - pyskl - INFO - Epoch [37][800/1281] lr: 2.150e-02, eta: 8:59:45, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9925, loss_cls: 0.6716, loss: 0.6716 +2025-06-24 13:46:05,030 - pyskl - INFO - Epoch [37][900/1281] lr: 2.149e-02, eta: 8:59:23, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8581, top5_acc: 0.9931, loss_cls: 0.7001, loss: 0.7001 +2025-06-24 13:46:27,744 - pyskl - INFO - Epoch [37][1000/1281] lr: 2.147e-02, eta: 8:59:02, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9944, loss_cls: 0.6427, loss: 0.6427 +2025-06-24 13:46:50,166 - pyskl - INFO - Epoch [37][1100/1281] lr: 2.146e-02, eta: 8:58:40, time: 0.224, data_time: 0.001, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9931, loss_cls: 0.6044, loss: 0.6044 +2025-06-24 13:47:12,719 - pyskl - INFO - Epoch [37][1200/1281] lr: 2.144e-02, eta: 8:58:18, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9950, loss_cls: 0.6586, loss: 0.6586 +2025-06-24 13:47:31,652 - pyskl - INFO - Saving checkpoint at 37 epochs +2025-06-24 13:48:15,533 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:48:15,590 - pyskl - INFO - +top1_acc 0.8317 +top5_acc 0.9885 +2025-06-24 13:48:15,590 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:48:15,597 - pyskl - INFO - +mean_acc 0.7644 +2025-06-24 13:48:15,600 - pyskl - INFO - Epoch(val) [37][533] top1_acc: 0.8317, top5_acc: 0.9885, mean_class_accuracy: 0.7644 +2025-06-24 13:48:58,890 - pyskl - INFO - Epoch [38][100/1281] lr: 2.142e-02, eta: 8:57:47, time: 0.433, data_time: 0.195, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9944, loss_cls: 0.6097, loss: 0.6097 +2025-06-24 13:49:21,403 - pyskl - INFO - Epoch [38][200/1281] lr: 2.140e-02, eta: 8:57:25, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9962, loss_cls: 0.6323, loss: 0.6323 +2025-06-24 13:49:43,567 - pyskl - INFO - Epoch [38][300/1281] lr: 2.139e-02, eta: 8:57:03, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9950, loss_cls: 0.6007, loss: 0.6007 +2025-06-24 13:50:05,971 - pyskl - INFO - Epoch [38][400/1281] lr: 2.137e-02, eta: 8:56:41, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9956, loss_cls: 0.5811, loss: 0.5811 +2025-06-24 13:50:28,449 - pyskl - INFO - Epoch [38][500/1281] lr: 2.136e-02, eta: 8:56:19, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9950, loss_cls: 0.6426, loss: 0.6426 +2025-06-24 13:50:50,763 - pyskl - INFO - Epoch [38][600/1281] lr: 2.134e-02, eta: 8:55:56, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8688, top5_acc: 0.9962, loss_cls: 0.6662, loss: 0.6662 +2025-06-24 13:51:13,077 - pyskl - INFO - Epoch [38][700/1281] lr: 2.133e-02, eta: 8:55:34, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9950, loss_cls: 0.6469, loss: 0.6469 +2025-06-24 13:51:35,734 - pyskl - INFO - Epoch [38][800/1281] lr: 2.132e-02, eta: 8:55:13, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9906, loss_cls: 0.6118, loss: 0.6118 +2025-06-24 13:51:58,038 - pyskl - INFO - Epoch [38][900/1281] lr: 2.130e-02, eta: 8:54:51, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8556, top5_acc: 0.9950, loss_cls: 0.6718, loss: 0.6718 +2025-06-24 13:52:20,395 - pyskl - INFO - Epoch [38][1000/1281] lr: 2.129e-02, eta: 8:54:28, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9962, loss_cls: 0.6224, loss: 0.6224 +2025-06-24 13:52:42,953 - pyskl - INFO - Epoch [38][1100/1281] lr: 2.127e-02, eta: 8:54:07, time: 0.226, data_time: 0.001, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9950, loss_cls: 0.6319, loss: 0.6319 +2025-06-24 13:53:05,206 - pyskl - INFO - Epoch [38][1200/1281] lr: 2.126e-02, eta: 8:53:44, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9919, loss_cls: 0.6291, loss: 0.6291 +2025-06-24 13:53:24,150 - pyskl - INFO - Saving checkpoint at 38 epochs +2025-06-24 13:54:07,757 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:54:07,812 - pyskl - INFO - +top1_acc 0.8459 +top5_acc 0.9864 +2025-06-24 13:54:07,812 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:54:07,821 - pyskl - INFO - +mean_acc 0.7645 +2025-06-24 13:54:07,825 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_26.pth was removed +2025-06-24 13:54:08,018 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_38.pth. +2025-06-24 13:54:08,018 - pyskl - INFO - Best top1_acc is 0.8459 at 38 epoch. +2025-06-24 13:54:08,021 - pyskl - INFO - Epoch(val) [38][533] top1_acc: 0.8459, top5_acc: 0.9864, mean_class_accuracy: 0.7645 +2025-06-24 13:54:50,992 - pyskl - INFO - Epoch [39][100/1281] lr: 2.123e-02, eta: 8:53:12, time: 0.430, data_time: 0.195, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9981, loss_cls: 0.5782, loss: 0.5782 +2025-06-24 13:55:13,247 - pyskl - INFO - Epoch [39][200/1281] lr: 2.122e-02, eta: 8:52:49, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9938, loss_cls: 0.6455, loss: 0.6455 +2025-06-24 13:55:35,799 - pyskl - INFO - Epoch [39][300/1281] lr: 2.120e-02, eta: 8:52:27, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9944, loss_cls: 0.6266, loss: 0.6266 +2025-06-24 13:55:58,247 - pyskl - INFO - Epoch [39][400/1281] lr: 2.119e-02, eta: 8:52:06, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9956, loss_cls: 0.6225, loss: 0.6225 +2025-06-24 13:56:20,365 - pyskl - INFO - Epoch [39][500/1281] lr: 2.117e-02, eta: 8:51:43, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9950, loss_cls: 0.5824, loss: 0.5824 +2025-06-24 13:56:42,522 - pyskl - INFO - Epoch [39][600/1281] lr: 2.116e-02, eta: 8:51:20, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9944, loss_cls: 0.6234, loss: 0.6234 +2025-06-24 13:57:04,965 - pyskl - INFO - Epoch [39][700/1281] lr: 2.114e-02, eta: 8:50:58, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9944, loss_cls: 0.6103, loss: 0.6103 +2025-06-24 13:57:27,345 - pyskl - INFO - Epoch [39][800/1281] lr: 2.113e-02, eta: 8:50:36, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9950, loss_cls: 0.6524, loss: 0.6524 +2025-06-24 13:57:49,841 - pyskl - INFO - Epoch [39][900/1281] lr: 2.111e-02, eta: 8:50:14, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8650, top5_acc: 0.9938, loss_cls: 0.6715, loss: 0.6715 +2025-06-24 13:58:12,129 - pyskl - INFO - Epoch [39][1000/1281] lr: 2.110e-02, eta: 8:49:52, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9956, loss_cls: 0.6402, loss: 0.6402 +2025-06-24 13:58:34,603 - pyskl - INFO - Epoch [39][1100/1281] lr: 2.108e-02, eta: 8:49:30, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9950, loss_cls: 0.6124, loss: 0.6124 +2025-06-24 13:58:57,295 - pyskl - INFO - Epoch [39][1200/1281] lr: 2.107e-02, eta: 8:49:08, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.8688, top5_acc: 0.9956, loss_cls: 0.6282, loss: 0.6282 +2025-06-24 13:59:15,921 - pyskl - INFO - Saving checkpoint at 39 epochs +2025-06-24 14:00:00,259 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:00:00,323 - pyskl - INFO - +top1_acc 0.8530 +top5_acc 0.9887 +2025-06-24 14:00:00,323 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:00:00,330 - pyskl - INFO - +mean_acc 0.7994 +2025-06-24 14:00:00,334 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_38.pth was removed +2025-06-24 14:00:00,525 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_39.pth. +2025-06-24 14:00:00,525 - pyskl - INFO - Best top1_acc is 0.8530 at 39 epoch. +2025-06-24 14:00:00,528 - pyskl - INFO - Epoch(val) [39][533] top1_acc: 0.8530, top5_acc: 0.9887, mean_class_accuracy: 0.7994 +2025-06-24 14:00:42,921 - pyskl - INFO - Epoch [40][100/1281] lr: 2.104e-02, eta: 8:48:34, time: 0.424, data_time: 0.192, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9950, loss_cls: 0.6073, loss: 0.6073 +2025-06-24 14:01:05,287 - pyskl - INFO - Epoch [40][200/1281] lr: 2.103e-02, eta: 8:48:12, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9981, loss_cls: 0.5861, loss: 0.5861 +2025-06-24 14:01:27,624 - pyskl - INFO - Epoch [40][300/1281] lr: 2.101e-02, eta: 8:47:49, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9969, loss_cls: 0.5703, loss: 0.5703 +2025-06-24 14:01:49,918 - pyskl - INFO - Epoch [40][400/1281] lr: 2.100e-02, eta: 8:47:27, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9969, loss_cls: 0.6144, loss: 0.6144 +2025-06-24 14:02:12,275 - pyskl - INFO - Epoch [40][500/1281] lr: 2.098e-02, eta: 8:47:05, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9988, loss_cls: 0.5718, loss: 0.5718 +2025-06-24 14:02:34,462 - pyskl - INFO - Epoch [40][600/1281] lr: 2.097e-02, eta: 8:46:42, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9962, loss_cls: 0.5839, loss: 0.5839 +2025-06-24 14:02:56,816 - pyskl - INFO - Epoch [40][700/1281] lr: 2.095e-02, eta: 8:46:20, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9950, loss_cls: 0.6392, loss: 0.6392 +2025-06-24 14:03:18,955 - pyskl - INFO - Epoch [40][800/1281] lr: 2.094e-02, eta: 8:45:57, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9962, loss_cls: 0.5611, loss: 0.5611 +2025-06-24 14:03:41,497 - pyskl - INFO - Epoch [40][900/1281] lr: 2.092e-02, eta: 8:45:35, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9962, loss_cls: 0.6155, loss: 0.6155 +2025-06-24 14:04:03,958 - pyskl - INFO - Epoch [40][1000/1281] lr: 2.091e-02, eta: 8:45:13, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9938, loss_cls: 0.6070, loss: 0.6070 +2025-06-24 14:04:26,463 - pyskl - INFO - Epoch [40][1100/1281] lr: 2.089e-02, eta: 8:44:51, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9931, loss_cls: 0.6722, loss: 0.6722 +2025-06-24 14:04:49,075 - pyskl - INFO - Epoch [40][1200/1281] lr: 2.088e-02, eta: 8:44:30, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9962, loss_cls: 0.6781, loss: 0.6781 +2025-06-24 14:05:07,880 - pyskl - INFO - Saving checkpoint at 40 epochs +2025-06-24 14:05:51,476 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:05:51,543 - pyskl - INFO - +top1_acc 0.8265 +top5_acc 0.9862 +2025-06-24 14:05:51,543 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:05:51,551 - pyskl - INFO - +mean_acc 0.7463 +2025-06-24 14:05:51,553 - pyskl - INFO - Epoch(val) [40][533] top1_acc: 0.8265, top5_acc: 0.9862, mean_class_accuracy: 0.7463 +2025-06-24 14:06:34,430 - pyskl - INFO - Epoch [41][100/1281] lr: 2.085e-02, eta: 8:43:56, time: 0.429, data_time: 0.194, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9956, loss_cls: 0.5562, loss: 0.5562 +2025-06-24 14:06:56,704 - pyskl - INFO - Epoch [41][200/1281] lr: 2.083e-02, eta: 8:43:34, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9969, loss_cls: 0.5729, loss: 0.5729 +2025-06-24 14:07:19,263 - pyskl - INFO - Epoch [41][300/1281] lr: 2.082e-02, eta: 8:43:12, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9956, loss_cls: 0.5890, loss: 0.5890 +2025-06-24 14:07:41,619 - pyskl - INFO - Epoch [41][400/1281] lr: 2.080e-02, eta: 8:42:50, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9962, loss_cls: 0.6000, loss: 0.6000 +2025-06-24 14:08:04,087 - pyskl - INFO - Epoch [41][500/1281] lr: 2.079e-02, eta: 8:42:28, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9962, loss_cls: 0.5762, loss: 0.5762 +2025-06-24 14:08:26,424 - pyskl - INFO - Epoch [41][600/1281] lr: 2.077e-02, eta: 8:42:06, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9931, loss_cls: 0.6264, loss: 0.6264 +2025-06-24 14:08:48,648 - pyskl - INFO - Epoch [41][700/1281] lr: 2.076e-02, eta: 8:41:43, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8631, top5_acc: 0.9969, loss_cls: 0.6429, loss: 0.6429 +2025-06-24 14:09:10,943 - pyskl - INFO - Epoch [41][800/1281] lr: 2.074e-02, eta: 8:41:21, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9969, loss_cls: 0.5844, loss: 0.5844 +2025-06-24 14:09:33,226 - pyskl - INFO - Epoch [41][900/1281] lr: 2.073e-02, eta: 8:40:58, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9962, loss_cls: 0.6176, loss: 0.6176 +2025-06-24 14:09:55,422 - pyskl - INFO - Epoch [41][1000/1281] lr: 2.071e-02, eta: 8:40:36, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9975, loss_cls: 0.6441, loss: 0.6441 +2025-06-24 14:10:17,718 - pyskl - INFO - Epoch [41][1100/1281] lr: 2.070e-02, eta: 8:40:13, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9956, loss_cls: 0.6210, loss: 0.6210 +2025-06-24 14:10:39,972 - pyskl - INFO - Epoch [41][1200/1281] lr: 2.068e-02, eta: 8:39:51, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9962, loss_cls: 0.5901, loss: 0.5901 +2025-06-24 14:10:59,200 - pyskl - INFO - Saving checkpoint at 41 epochs +2025-06-24 14:11:42,605 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:11:42,660 - pyskl - INFO - +top1_acc 0.8490 +top5_acc 0.9901 +2025-06-24 14:11:42,660 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:11:42,667 - pyskl - INFO - +mean_acc 0.7873 +2025-06-24 14:11:42,669 - pyskl - INFO - Epoch(val) [41][533] top1_acc: 0.8490, top5_acc: 0.9901, mean_class_accuracy: 0.7873 +2025-06-24 14:12:25,067 - pyskl - INFO - Epoch [42][100/1281] lr: 2.065e-02, eta: 8:39:15, time: 0.424, data_time: 0.188, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9975, loss_cls: 0.5454, loss: 0.5454 +2025-06-24 14:12:47,597 - pyskl - INFO - Epoch [42][200/1281] lr: 2.064e-02, eta: 8:38:54, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9975, loss_cls: 0.5744, loss: 0.5744 +2025-06-24 14:13:09,733 - pyskl - INFO - Epoch [42][300/1281] lr: 2.062e-02, eta: 8:38:31, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9975, loss_cls: 0.6123, loss: 0.6123 +2025-06-24 14:13:32,154 - pyskl - INFO - Epoch [42][400/1281] lr: 2.061e-02, eta: 8:38:09, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9962, loss_cls: 0.5988, loss: 0.5988 +2025-06-24 14:13:54,514 - pyskl - INFO - Epoch [42][500/1281] lr: 2.059e-02, eta: 8:37:46, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9925, loss_cls: 0.5662, loss: 0.5662 +2025-06-24 14:14:16,872 - pyskl - INFO - Epoch [42][600/1281] lr: 2.057e-02, eta: 8:37:24, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9956, loss_cls: 0.5435, loss: 0.5435 +2025-06-24 14:14:39,372 - pyskl - INFO - Epoch [42][700/1281] lr: 2.056e-02, eta: 8:37:02, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9969, loss_cls: 0.6261, loss: 0.6261 +2025-06-24 14:15:01,694 - pyskl - INFO - Epoch [42][800/1281] lr: 2.054e-02, eta: 8:36:40, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9956, loss_cls: 0.6491, loss: 0.6491 +2025-06-24 14:15:24,119 - pyskl - INFO - Epoch [42][900/1281] lr: 2.053e-02, eta: 8:36:18, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9975, loss_cls: 0.6312, loss: 0.6312 +2025-06-24 14:15:46,533 - pyskl - INFO - Epoch [42][1000/1281] lr: 2.051e-02, eta: 8:35:56, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9950, loss_cls: 0.5671, loss: 0.5671 +2025-06-24 14:16:09,046 - pyskl - INFO - Epoch [42][1100/1281] lr: 2.050e-02, eta: 8:35:34, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8644, top5_acc: 0.9938, loss_cls: 0.6483, loss: 0.6483 +2025-06-24 14:16:31,341 - pyskl - INFO - Epoch [42][1200/1281] lr: 2.048e-02, eta: 8:35:12, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9956, loss_cls: 0.6226, loss: 0.6226 +2025-06-24 14:16:50,329 - pyskl - INFO - Saving checkpoint at 42 epochs +2025-06-24 14:17:35,026 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:17:35,080 - pyskl - INFO - +top1_acc 0.8453 +top5_acc 0.9899 +2025-06-24 14:17:35,080 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:17:35,087 - pyskl - INFO - +mean_acc 0.7844 +2025-06-24 14:17:35,089 - pyskl - INFO - Epoch(val) [42][533] top1_acc: 0.8453, top5_acc: 0.9899, mean_class_accuracy: 0.7844 +2025-06-24 14:18:17,960 - pyskl - INFO - Epoch [43][100/1281] lr: 2.045e-02, eta: 8:34:37, time: 0.429, data_time: 0.193, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9981, loss_cls: 0.5291, loss: 0.5291 +2025-06-24 14:18:40,742 - pyskl - INFO - Epoch [43][200/1281] lr: 2.044e-02, eta: 8:34:16, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9981, loss_cls: 0.5132, loss: 0.5132 +2025-06-24 14:19:02,937 - pyskl - INFO - Epoch [43][300/1281] lr: 2.042e-02, eta: 8:33:53, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9969, loss_cls: 0.4999, loss: 0.4999 +2025-06-24 14:19:25,344 - pyskl - INFO - Epoch [43][400/1281] lr: 2.040e-02, eta: 8:33:31, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9944, loss_cls: 0.5875, loss: 0.5875 +2025-06-24 14:19:47,548 - pyskl - INFO - Epoch [43][500/1281] lr: 2.039e-02, eta: 8:33:09, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9962, loss_cls: 0.6346, loss: 0.6346 +2025-06-24 14:20:09,750 - pyskl - INFO - Epoch [43][600/1281] lr: 2.037e-02, eta: 8:32:46, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9931, loss_cls: 0.6065, loss: 0.6065 +2025-06-24 14:20:32,100 - pyskl - INFO - Epoch [43][700/1281] lr: 2.036e-02, eta: 8:32:24, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9950, loss_cls: 0.5629, loss: 0.5629 +2025-06-24 14:20:54,261 - pyskl - INFO - Epoch [43][800/1281] lr: 2.034e-02, eta: 8:32:01, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9969, loss_cls: 0.5923, loss: 0.5923 +2025-06-24 14:21:16,772 - pyskl - INFO - Epoch [43][900/1281] lr: 2.033e-02, eta: 8:31:39, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9956, loss_cls: 0.5597, loss: 0.5597 +2025-06-24 14:21:38,909 - pyskl - INFO - Epoch [43][1000/1281] lr: 2.031e-02, eta: 8:31:16, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9938, loss_cls: 0.6324, loss: 0.6324 +2025-06-24 14:22:01,187 - pyskl - INFO - Epoch [43][1100/1281] lr: 2.029e-02, eta: 8:30:54, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8738, top5_acc: 0.9944, loss_cls: 0.5970, loss: 0.5970 +2025-06-24 14:22:23,601 - pyskl - INFO - Epoch [43][1200/1281] lr: 2.028e-02, eta: 8:30:32, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9975, loss_cls: 0.5989, loss: 0.5989 +2025-06-24 14:22:42,412 - pyskl - INFO - Saving checkpoint at 43 epochs +2025-06-24 14:23:26,525 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:23:26,589 - pyskl - INFO - +top1_acc 0.8478 +top5_acc 0.9904 +2025-06-24 14:23:26,589 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:23:26,599 - pyskl - INFO - +mean_acc 0.7866 +2025-06-24 14:23:26,602 - pyskl - INFO - Epoch(val) [43][533] top1_acc: 0.8478, top5_acc: 0.9904, mean_class_accuracy: 0.7866 +2025-06-24 14:24:08,707 - pyskl - INFO - Epoch [44][100/1281] lr: 2.025e-02, eta: 8:29:55, time: 0.421, data_time: 0.186, memory: 4083, top1_acc: 0.8738, top5_acc: 0.9962, loss_cls: 0.6412, loss: 0.6412 +2025-06-24 14:24:31,581 - pyskl - INFO - Epoch [44][200/1281] lr: 2.023e-02, eta: 8:29:34, time: 0.229, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9969, loss_cls: 0.5588, loss: 0.5588 +2025-06-24 14:24:54,088 - pyskl - INFO - Epoch [44][300/1281] lr: 2.022e-02, eta: 8:29:12, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9931, loss_cls: 0.5655, loss: 0.5655 +2025-06-24 14:25:16,168 - pyskl - INFO - Epoch [44][400/1281] lr: 2.020e-02, eta: 8:28:49, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9962, loss_cls: 0.5734, loss: 0.5734 +2025-06-24 14:25:38,778 - pyskl - INFO - Epoch [44][500/1281] lr: 2.018e-02, eta: 8:28:28, time: 0.226, data_time: 0.001, memory: 4083, top1_acc: 0.8669, top5_acc: 0.9919, loss_cls: 0.6746, loss: 0.6746 +2025-06-24 14:26:01,182 - pyskl - INFO - Epoch [44][600/1281] lr: 2.017e-02, eta: 8:28:05, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9938, loss_cls: 0.5500, loss: 0.5500 +2025-06-24 14:26:23,599 - pyskl - INFO - Epoch [44][700/1281] lr: 2.015e-02, eta: 8:27:43, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9988, loss_cls: 0.5810, loss: 0.5810 +2025-06-24 14:26:45,728 - pyskl - INFO - Epoch [44][800/1281] lr: 2.014e-02, eta: 8:27:20, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9912, loss_cls: 0.6150, loss: 0.6150 +2025-06-24 14:27:08,540 - pyskl - INFO - Epoch [44][900/1281] lr: 2.012e-02, eta: 8:26:59, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9962, loss_cls: 0.6072, loss: 0.6072 +2025-06-24 14:27:30,382 - pyskl - INFO - Epoch [44][1000/1281] lr: 2.010e-02, eta: 8:26:36, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9962, loss_cls: 0.5636, loss: 0.5636 +2025-06-24 14:27:53,011 - pyskl - INFO - Epoch [44][1100/1281] lr: 2.009e-02, eta: 8:26:14, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9975, loss_cls: 0.5534, loss: 0.5534 +2025-06-24 14:28:15,291 - pyskl - INFO - Epoch [44][1200/1281] lr: 2.007e-02, eta: 8:25:52, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9969, loss_cls: 0.5412, loss: 0.5412 +2025-06-24 14:28:33,976 - pyskl - INFO - Saving checkpoint at 44 epochs +2025-06-24 14:29:18,603 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:29:18,657 - pyskl - INFO - +top1_acc 0.8380 +top5_acc 0.9893 +2025-06-24 14:29:18,657 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:29:18,664 - pyskl - INFO - +mean_acc 0.7745 +2025-06-24 14:29:18,666 - pyskl - INFO - Epoch(val) [44][533] top1_acc: 0.8380, top5_acc: 0.9893, mean_class_accuracy: 0.7745 +2025-06-24 14:30:02,205 - pyskl - INFO - Epoch [45][100/1281] lr: 2.004e-02, eta: 8:25:19, time: 0.435, data_time: 0.197, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9988, loss_cls: 0.4760, loss: 0.4760 +2025-06-24 14:30:24,564 - pyskl - INFO - Epoch [45][200/1281] lr: 2.003e-02, eta: 8:24:56, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9962, loss_cls: 0.5366, loss: 0.5366 +2025-06-24 14:30:46,807 - pyskl - INFO - Epoch [45][300/1281] lr: 2.001e-02, eta: 8:24:34, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9962, loss_cls: 0.5631, loss: 0.5631 +2025-06-24 14:31:09,427 - pyskl - INFO - Epoch [45][400/1281] lr: 1.999e-02, eta: 8:24:12, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9950, loss_cls: 0.5301, loss: 0.5301 +2025-06-24 14:31:31,953 - pyskl - INFO - Epoch [45][500/1281] lr: 1.998e-02, eta: 8:23:50, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9962, loss_cls: 0.6163, loss: 0.6163 +2025-06-24 14:31:54,300 - pyskl - INFO - Epoch [45][600/1281] lr: 1.996e-02, eta: 8:23:28, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9944, loss_cls: 0.6257, loss: 0.6257 +2025-06-24 14:32:16,521 - pyskl - INFO - Epoch [45][700/1281] lr: 1.994e-02, eta: 8:23:05, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9956, loss_cls: 0.5774, loss: 0.5774 +2025-06-24 14:32:38,893 - pyskl - INFO - Epoch [45][800/1281] lr: 1.993e-02, eta: 8:22:43, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9969, loss_cls: 0.5715, loss: 0.5715 +2025-06-24 14:33:01,278 - pyskl - INFO - Epoch [45][900/1281] lr: 1.991e-02, eta: 8:22:21, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9962, loss_cls: 0.6235, loss: 0.6235 +2025-06-24 14:33:23,571 - pyskl - INFO - Epoch [45][1000/1281] lr: 1.989e-02, eta: 8:21:58, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9944, loss_cls: 0.5873, loss: 0.5873 +2025-06-24 14:33:46,026 - pyskl - INFO - Epoch [45][1100/1281] lr: 1.988e-02, eta: 8:21:36, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9969, loss_cls: 0.5534, loss: 0.5534 +2025-06-24 14:34:08,452 - pyskl - INFO - Epoch [45][1200/1281] lr: 1.986e-02, eta: 8:21:14, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9912, loss_cls: 0.6110, loss: 0.6110 +2025-06-24 14:34:27,574 - pyskl - INFO - Saving checkpoint at 45 epochs +2025-06-24 14:35:11,877 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:35:11,934 - pyskl - INFO - +top1_acc 0.8429 +top5_acc 0.9897 +2025-06-24 14:35:11,934 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:35:11,942 - pyskl - INFO - +mean_acc 0.8080 +2025-06-24 14:35:11,944 - pyskl - INFO - Epoch(val) [45][533] top1_acc: 0.8429, top5_acc: 0.9897, mean_class_accuracy: 0.8080 +2025-06-24 14:35:54,588 - pyskl - INFO - Epoch [46][100/1281] lr: 1.983e-02, eta: 8:20:39, time: 0.426, data_time: 0.193, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9975, loss_cls: 0.5598, loss: 0.5598 +2025-06-24 14:36:17,012 - pyskl - INFO - Epoch [46][200/1281] lr: 1.981e-02, eta: 8:20:16, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9938, loss_cls: 0.5364, loss: 0.5364 +2025-06-24 14:36:39,331 - pyskl - INFO - Epoch [46][300/1281] lr: 1.980e-02, eta: 8:19:54, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9969, loss_cls: 0.5885, loss: 0.5885 +2025-06-24 14:37:01,860 - pyskl - INFO - Epoch [46][400/1281] lr: 1.978e-02, eta: 8:19:32, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9962, loss_cls: 0.5425, loss: 0.5425 +2025-06-24 14:37:24,033 - pyskl - INFO - Epoch [46][500/1281] lr: 1.976e-02, eta: 8:19:09, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9956, loss_cls: 0.5765, loss: 0.5765 +2025-06-24 14:37:46,441 - pyskl - INFO - Epoch [46][600/1281] lr: 1.975e-02, eta: 8:18:47, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9938, loss_cls: 0.5890, loss: 0.5890 +2025-06-24 14:38:08,480 - pyskl - INFO - Epoch [46][700/1281] lr: 1.973e-02, eta: 8:18:24, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9975, loss_cls: 0.5433, loss: 0.5433 +2025-06-24 14:38:30,666 - pyskl - INFO - Epoch [46][800/1281] lr: 1.971e-02, eta: 8:18:01, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9950, loss_cls: 0.5536, loss: 0.5536 +2025-06-24 14:38:53,051 - pyskl - INFO - Epoch [46][900/1281] lr: 1.970e-02, eta: 8:17:39, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9950, loss_cls: 0.5794, loss: 0.5794 +2025-06-24 14:39:15,254 - pyskl - INFO - Epoch [46][1000/1281] lr: 1.968e-02, eta: 8:17:16, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9962, loss_cls: 0.5614, loss: 0.5614 +2025-06-24 14:39:37,725 - pyskl - INFO - Epoch [46][1100/1281] lr: 1.966e-02, eta: 8:16:54, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9969, loss_cls: 0.5635, loss: 0.5635 +2025-06-24 14:39:59,989 - pyskl - INFO - Epoch [46][1200/1281] lr: 1.965e-02, eta: 8:16:32, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9956, loss_cls: 0.5799, loss: 0.5799 +2025-06-24 14:40:18,744 - pyskl - INFO - Saving checkpoint at 46 epochs +2025-06-24 14:41:02,630 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:41:02,698 - pyskl - INFO - +top1_acc 0.8413 +top5_acc 0.9885 +2025-06-24 14:41:02,698 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:41:02,707 - pyskl - INFO - +mean_acc 0.7930 +2025-06-24 14:41:02,709 - pyskl - INFO - Epoch(val) [46][533] top1_acc: 0.8413, top5_acc: 0.9885, mean_class_accuracy: 0.7930 +2025-06-24 14:41:46,013 - pyskl - INFO - Epoch [47][100/1281] lr: 1.962e-02, eta: 8:15:58, time: 0.433, data_time: 0.198, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9962, loss_cls: 0.5596, loss: 0.5596 +2025-06-24 14:42:08,779 - pyskl - INFO - Epoch [47][200/1281] lr: 1.960e-02, eta: 8:15:36, time: 0.228, data_time: 0.001, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9962, loss_cls: 0.5106, loss: 0.5106 +2025-06-24 14:42:31,273 - pyskl - INFO - Epoch [47][300/1281] lr: 1.958e-02, eta: 8:15:14, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9956, loss_cls: 0.5954, loss: 0.5954 +2025-06-24 14:42:53,501 - pyskl - INFO - Epoch [47][400/1281] lr: 1.957e-02, eta: 8:14:52, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9969, loss_cls: 0.4644, loss: 0.4644 +2025-06-24 14:43:16,456 - pyskl - INFO - Epoch [47][500/1281] lr: 1.955e-02, eta: 8:14:30, time: 0.230, data_time: 0.001, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9956, loss_cls: 0.5542, loss: 0.5542 +2025-06-24 14:43:38,739 - pyskl - INFO - Epoch [47][600/1281] lr: 1.953e-02, eta: 8:14:08, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9950, loss_cls: 0.5724, loss: 0.5724 +2025-06-24 14:44:01,081 - pyskl - INFO - Epoch [47][700/1281] lr: 1.952e-02, eta: 8:13:46, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9962, loss_cls: 0.5504, loss: 0.5504 +2025-06-24 14:44:23,403 - pyskl - INFO - Epoch [47][800/1281] lr: 1.950e-02, eta: 8:13:23, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9962, loss_cls: 0.5561, loss: 0.5561 +2025-06-24 14:44:46,056 - pyskl - INFO - Epoch [47][900/1281] lr: 1.948e-02, eta: 8:13:01, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9962, loss_cls: 0.5274, loss: 0.5274 +2025-06-24 14:45:08,154 - pyskl - INFO - Epoch [47][1000/1281] lr: 1.947e-02, eta: 8:12:39, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9969, loss_cls: 0.5441, loss: 0.5441 +2025-06-24 14:45:30,366 - pyskl - INFO - Epoch [47][1100/1281] lr: 1.945e-02, eta: 8:12:16, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9962, loss_cls: 0.5785, loss: 0.5785 +2025-06-24 14:45:52,913 - pyskl - INFO - Epoch [47][1200/1281] lr: 1.943e-02, eta: 8:11:54, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8738, top5_acc: 0.9975, loss_cls: 0.6418, loss: 0.6418 +2025-06-24 14:46:11,712 - pyskl - INFO - Saving checkpoint at 47 epochs +2025-06-24 14:46:55,393 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:46:55,450 - pyskl - INFO - +top1_acc 0.8474 +top5_acc 0.9900 +2025-06-24 14:46:55,450 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:46:55,457 - pyskl - INFO - +mean_acc 0.8101 +2025-06-24 14:46:55,459 - pyskl - INFO - Epoch(val) [47][533] top1_acc: 0.8474, top5_acc: 0.9900, mean_class_accuracy: 0.8101 +2025-06-24 14:47:37,867 - pyskl - INFO - Epoch [48][100/1281] lr: 1.940e-02, eta: 8:11:18, time: 0.424, data_time: 0.187, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9975, loss_cls: 0.5731, loss: 0.5731 +2025-06-24 14:48:00,336 - pyskl - INFO - Epoch [48][200/1281] lr: 1.938e-02, eta: 8:10:56, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9975, loss_cls: 0.5413, loss: 0.5413 +2025-06-24 14:48:22,637 - pyskl - INFO - Epoch [48][300/1281] lr: 1.937e-02, eta: 8:10:33, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9981, loss_cls: 0.5360, loss: 0.5360 +2025-06-24 14:48:44,902 - pyskl - INFO - Epoch [48][400/1281] lr: 1.935e-02, eta: 8:10:11, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9950, loss_cls: 0.5827, loss: 0.5827 +2025-06-24 14:49:07,263 - pyskl - INFO - Epoch [48][500/1281] lr: 1.933e-02, eta: 8:09:48, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9944, loss_cls: 0.5598, loss: 0.5598 +2025-06-24 14:49:29,488 - pyskl - INFO - Epoch [48][600/1281] lr: 1.932e-02, eta: 8:09:26, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9981, loss_cls: 0.5781, loss: 0.5781 +2025-06-24 14:49:51,459 - pyskl - INFO - Epoch [48][700/1281] lr: 1.930e-02, eta: 8:09:02, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9950, loss_cls: 0.6338, loss: 0.6338 +2025-06-24 14:50:13,716 - pyskl - INFO - Epoch [48][800/1281] lr: 1.928e-02, eta: 8:08:40, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9975, loss_cls: 0.4969, loss: 0.4969 +2025-06-24 14:50:36,142 - pyskl - INFO - Epoch [48][900/1281] lr: 1.926e-02, eta: 8:08:18, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9962, loss_cls: 0.5830, loss: 0.5830 +2025-06-24 14:50:58,403 - pyskl - INFO - Epoch [48][1000/1281] lr: 1.925e-02, eta: 8:07:55, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9962, loss_cls: 0.5167, loss: 0.5167 +2025-06-24 14:51:20,808 - pyskl - INFO - Epoch [48][1100/1281] lr: 1.923e-02, eta: 8:07:33, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9962, loss_cls: 0.5093, loss: 0.5093 +2025-06-24 14:51:43,392 - pyskl - INFO - Epoch [48][1200/1281] lr: 1.921e-02, eta: 8:07:11, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9956, loss_cls: 0.5503, loss: 0.5503 +2025-06-24 14:52:02,287 - pyskl - INFO - Saving checkpoint at 48 epochs +2025-06-24 14:52:46,242 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:52:46,297 - pyskl - INFO - +top1_acc 0.8161 +top5_acc 0.9867 +2025-06-24 14:52:46,297 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:52:46,304 - pyskl - INFO - +mean_acc 0.7379 +2025-06-24 14:52:46,305 - pyskl - INFO - Epoch(val) [48][533] top1_acc: 0.8161, top5_acc: 0.9867, mean_class_accuracy: 0.7379 +2025-06-24 14:53:28,845 - pyskl - INFO - Epoch [49][100/1281] lr: 1.918e-02, eta: 8:06:35, time: 0.425, data_time: 0.191, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9950, loss_cls: 0.4887, loss: 0.4887 +2025-06-24 14:53:51,224 - pyskl - INFO - Epoch [49][200/1281] lr: 1.916e-02, eta: 8:06:12, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9988, loss_cls: 0.4752, loss: 0.4752 +2025-06-24 14:54:13,906 - pyskl - INFO - Epoch [49][300/1281] lr: 1.915e-02, eta: 8:05:51, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9950, loss_cls: 0.5230, loss: 0.5230 +2025-06-24 14:54:36,051 - pyskl - INFO - Epoch [49][400/1281] lr: 1.913e-02, eta: 8:05:28, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9938, loss_cls: 0.6009, loss: 0.6009 +2025-06-24 14:54:58,411 - pyskl - INFO - Epoch [49][500/1281] lr: 1.911e-02, eta: 8:05:06, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9969, loss_cls: 0.5823, loss: 0.5823 +2025-06-24 14:55:20,854 - pyskl - INFO - Epoch [49][600/1281] lr: 1.909e-02, eta: 8:04:43, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9956, loss_cls: 0.5070, loss: 0.5070 +2025-06-24 14:55:43,369 - pyskl - INFO - Epoch [49][700/1281] lr: 1.908e-02, eta: 8:04:21, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9962, loss_cls: 0.5851, loss: 0.5851 +2025-06-24 14:56:05,574 - pyskl - INFO - Epoch [49][800/1281] lr: 1.906e-02, eta: 8:03:59, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9938, loss_cls: 0.5374, loss: 0.5374 +2025-06-24 14:56:27,894 - pyskl - INFO - Epoch [49][900/1281] lr: 1.904e-02, eta: 8:03:36, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9962, loss_cls: 0.5610, loss: 0.5610 +2025-06-24 14:56:49,968 - pyskl - INFO - Epoch [49][1000/1281] lr: 1.902e-02, eta: 8:03:13, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9962, loss_cls: 0.5706, loss: 0.5706 +2025-06-24 14:57:12,318 - pyskl - INFO - Epoch [49][1100/1281] lr: 1.901e-02, eta: 8:02:51, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9962, loss_cls: 0.5660, loss: 0.5660 +2025-06-24 14:57:34,686 - pyskl - INFO - Epoch [49][1200/1281] lr: 1.899e-02, eta: 8:02:28, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9962, loss_cls: 0.5772, loss: 0.5772 +2025-06-24 14:57:53,510 - pyskl - INFO - Saving checkpoint at 49 epochs +2025-06-24 14:58:37,503 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:58:37,569 - pyskl - INFO - +top1_acc 0.8693 +top5_acc 0.9916 +2025-06-24 14:58:37,570 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:58:37,577 - pyskl - INFO - +mean_acc 0.8096 +2025-06-24 14:58:37,582 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_39.pth was removed +2025-06-24 14:58:37,769 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_49.pth. +2025-06-24 14:58:37,770 - pyskl - INFO - Best top1_acc is 0.8693 at 49 epoch. +2025-06-24 14:58:37,772 - pyskl - INFO - Epoch(val) [49][533] top1_acc: 0.8693, top5_acc: 0.9916, mean_class_accuracy: 0.8096 +2025-06-24 14:59:20,090 - pyskl - INFO - Epoch [50][100/1281] lr: 1.896e-02, eta: 8:01:52, time: 0.423, data_time: 0.187, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9988, loss_cls: 0.4953, loss: 0.4953 +2025-06-24 14:59:42,407 - pyskl - INFO - Epoch [50][200/1281] lr: 1.894e-02, eta: 8:01:29, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9975, loss_cls: 0.5103, loss: 0.5103 +2025-06-24 15:00:04,622 - pyskl - INFO - Epoch [50][300/1281] lr: 1.892e-02, eta: 8:01:07, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9950, loss_cls: 0.5467, loss: 0.5467 +2025-06-24 15:00:26,758 - pyskl - INFO - Epoch [50][400/1281] lr: 1.891e-02, eta: 8:00:44, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9975, loss_cls: 0.5358, loss: 0.5358 +2025-06-24 15:00:49,050 - pyskl - INFO - Epoch [50][500/1281] lr: 1.889e-02, eta: 8:00:21, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9975, loss_cls: 0.4994, loss: 0.4994 +2025-06-24 15:01:11,716 - pyskl - INFO - Epoch [50][600/1281] lr: 1.887e-02, eta: 8:00:00, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9925, loss_cls: 0.5429, loss: 0.5429 +2025-06-24 15:01:33,755 - pyskl - INFO - Epoch [50][700/1281] lr: 1.885e-02, eta: 7:59:37, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9962, loss_cls: 0.5888, loss: 0.5888 +2025-06-24 15:01:55,941 - pyskl - INFO - Epoch [50][800/1281] lr: 1.884e-02, eta: 7:59:14, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9962, loss_cls: 0.6081, loss: 0.6081 +2025-06-24 15:02:18,360 - pyskl - INFO - Epoch [50][900/1281] lr: 1.882e-02, eta: 7:58:52, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 1.0000, loss_cls: 0.5081, loss: 0.5081 +2025-06-24 15:02:40,636 - pyskl - INFO - Epoch [50][1000/1281] lr: 1.880e-02, eta: 7:58:29, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9969, loss_cls: 0.6095, loss: 0.6095 +2025-06-24 15:03:03,062 - pyskl - INFO - Epoch [50][1100/1281] lr: 1.878e-02, eta: 7:58:07, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9956, loss_cls: 0.5890, loss: 0.5890 +2025-06-24 15:03:25,683 - pyskl - INFO - Epoch [50][1200/1281] lr: 1.876e-02, eta: 7:57:45, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9969, loss_cls: 0.5268, loss: 0.5268 +2025-06-24 15:03:44,290 - pyskl - INFO - Saving checkpoint at 50 epochs +2025-06-24 15:04:28,688 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:04:28,751 - pyskl - INFO - +top1_acc 0.8630 +top5_acc 0.9910 +2025-06-24 15:04:28,751 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:04:28,759 - pyskl - INFO - +mean_acc 0.8071 +2025-06-24 15:04:28,761 - pyskl - INFO - Epoch(val) [50][533] top1_acc: 0.8630, top5_acc: 0.9910, mean_class_accuracy: 0.8071 +2025-06-24 15:05:11,276 - pyskl - INFO - Epoch [51][100/1281] lr: 1.873e-02, eta: 7:57:09, time: 0.425, data_time: 0.190, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9981, loss_cls: 0.4727, loss: 0.4727 +2025-06-24 15:05:33,738 - pyskl - INFO - Epoch [51][200/1281] lr: 1.871e-02, eta: 7:56:46, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9962, loss_cls: 0.5475, loss: 0.5475 +2025-06-24 15:05:56,534 - pyskl - INFO - Epoch [51][300/1281] lr: 1.870e-02, eta: 7:56:25, time: 0.228, data_time: 0.001, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9969, loss_cls: 0.5307, loss: 0.5307 +2025-06-24 15:06:18,782 - pyskl - INFO - Epoch [51][400/1281] lr: 1.868e-02, eta: 7:56:02, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9975, loss_cls: 0.5764, loss: 0.5764 +2025-06-24 15:06:41,220 - pyskl - INFO - Epoch [51][500/1281] lr: 1.866e-02, eta: 7:55:40, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9969, loss_cls: 0.5163, loss: 0.5163 +2025-06-24 15:07:03,819 - pyskl - INFO - Epoch [51][600/1281] lr: 1.864e-02, eta: 7:55:18, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9944, loss_cls: 0.5361, loss: 0.5361 +2025-06-24 15:07:26,112 - pyskl - INFO - Epoch [51][700/1281] lr: 1.863e-02, eta: 7:54:56, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9950, loss_cls: 0.5482, loss: 0.5482 +2025-06-24 15:07:48,576 - pyskl - INFO - Epoch [51][800/1281] lr: 1.861e-02, eta: 7:54:33, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9950, loss_cls: 0.4855, loss: 0.4855 +2025-06-24 15:08:10,696 - pyskl - INFO - Epoch [51][900/1281] lr: 1.859e-02, eta: 7:54:11, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9950, loss_cls: 0.5178, loss: 0.5178 +2025-06-24 15:08:33,074 - pyskl - INFO - Epoch [51][1000/1281] lr: 1.857e-02, eta: 7:53:48, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9988, loss_cls: 0.4941, loss: 0.4941 +2025-06-24 15:08:55,389 - pyskl - INFO - Epoch [51][1100/1281] lr: 1.855e-02, eta: 7:53:26, time: 0.223, data_time: 0.001, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9969, loss_cls: 0.5584, loss: 0.5584 +2025-06-24 15:09:17,931 - pyskl - INFO - Epoch [51][1200/1281] lr: 1.854e-02, eta: 7:53:04, time: 0.225, data_time: 0.001, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9956, loss_cls: 0.5447, loss: 0.5447 +2025-06-24 15:09:37,177 - pyskl - INFO - Saving checkpoint at 51 epochs +2025-06-24 15:10:20,592 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:10:20,647 - pyskl - INFO - +top1_acc 0.8524 +top5_acc 0.9925 +2025-06-24 15:10:20,647 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:10:20,654 - pyskl - INFO - +mean_acc 0.7978 +2025-06-24 15:10:20,656 - pyskl - INFO - Epoch(val) [51][533] top1_acc: 0.8524, top5_acc: 0.9925, mean_class_accuracy: 0.7978 +2025-06-24 15:11:03,047 - pyskl - INFO - Epoch [52][100/1281] lr: 1.850e-02, eta: 7:52:27, time: 0.424, data_time: 0.192, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9962, loss_cls: 0.5237, loss: 0.5237 +2025-06-24 15:11:25,411 - pyskl - INFO - Epoch [52][200/1281] lr: 1.849e-02, eta: 7:52:04, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9950, loss_cls: 0.5193, loss: 0.5193 +2025-06-24 15:11:47,821 - pyskl - INFO - Epoch [52][300/1281] lr: 1.847e-02, eta: 7:51:42, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9975, loss_cls: 0.5299, loss: 0.5299 +2025-06-24 15:12:10,259 - pyskl - INFO - Epoch [52][400/1281] lr: 1.845e-02, eta: 7:51:20, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9975, loss_cls: 0.4469, loss: 0.4469 +2025-06-24 15:12:32,630 - pyskl - INFO - Epoch [52][500/1281] lr: 1.843e-02, eta: 7:50:58, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9956, loss_cls: 0.5485, loss: 0.5485 +2025-06-24 15:12:54,793 - pyskl - INFO - Epoch [52][600/1281] lr: 1.841e-02, eta: 7:50:35, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9969, loss_cls: 0.4839, loss: 0.4839 +2025-06-24 15:13:17,086 - pyskl - INFO - Epoch [52][700/1281] lr: 1.840e-02, eta: 7:50:12, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9950, loss_cls: 0.5240, loss: 0.5240 +2025-06-24 15:13:39,569 - pyskl - INFO - Epoch [52][800/1281] lr: 1.838e-02, eta: 7:49:50, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9962, loss_cls: 0.5560, loss: 0.5560 +2025-06-24 15:14:01,996 - pyskl - INFO - Epoch [52][900/1281] lr: 1.836e-02, eta: 7:49:28, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9969, loss_cls: 0.5070, loss: 0.5070 +2025-06-24 15:14:24,237 - pyskl - INFO - Epoch [52][1000/1281] lr: 1.834e-02, eta: 7:49:05, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9981, loss_cls: 0.5306, loss: 0.5306 +2025-06-24 15:14:46,373 - pyskl - INFO - Epoch [52][1100/1281] lr: 1.832e-02, eta: 7:48:42, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9944, loss_cls: 0.5889, loss: 0.5889 +2025-06-24 15:15:08,758 - pyskl - INFO - Epoch [52][1200/1281] lr: 1.831e-02, eta: 7:48:20, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9962, loss_cls: 0.5406, loss: 0.5406 +2025-06-24 15:15:28,084 - pyskl - INFO - Saving checkpoint at 52 epochs +2025-06-24 15:16:11,859 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:16:11,922 - pyskl - INFO - +top1_acc 0.8737 +top5_acc 0.9896 +2025-06-24 15:16:11,922 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:16:11,929 - pyskl - INFO - +mean_acc 0.8362 +2025-06-24 15:16:11,933 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_49.pth was removed +2025-06-24 15:16:12,113 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_52.pth. +2025-06-24 15:16:12,113 - pyskl - INFO - Best top1_acc is 0.8737 at 52 epoch. +2025-06-24 15:16:12,116 - pyskl - INFO - Epoch(val) [52][533] top1_acc: 0.8737, top5_acc: 0.9896, mean_class_accuracy: 0.8362 +2025-06-24 15:16:54,880 - pyskl - INFO - Epoch [53][100/1281] lr: 1.827e-02, eta: 7:47:44, time: 0.428, data_time: 0.191, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9969, loss_cls: 0.5357, loss: 0.5357 +2025-06-24 15:17:17,585 - pyskl - INFO - Epoch [53][200/1281] lr: 1.826e-02, eta: 7:47:22, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9994, loss_cls: 0.4927, loss: 0.4927 +2025-06-24 15:17:39,836 - pyskl - INFO - Epoch [53][300/1281] lr: 1.824e-02, eta: 7:47:00, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9950, loss_cls: 0.4795, loss: 0.4795 +2025-06-24 15:18:02,211 - pyskl - INFO - Epoch [53][400/1281] lr: 1.822e-02, eta: 7:46:37, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9994, loss_cls: 0.4704, loss: 0.4704 +2025-06-24 15:18:24,791 - pyskl - INFO - Epoch [53][500/1281] lr: 1.820e-02, eta: 7:46:15, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9981, loss_cls: 0.5175, loss: 0.5175 +2025-06-24 15:18:46,984 - pyskl - INFO - Epoch [53][600/1281] lr: 1.818e-02, eta: 7:45:52, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9981, loss_cls: 0.5343, loss: 0.5343 +2025-06-24 15:19:09,537 - pyskl - INFO - Epoch [53][700/1281] lr: 1.816e-02, eta: 7:45:30, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9975, loss_cls: 0.5276, loss: 0.5276 +2025-06-24 15:19:32,221 - pyskl - INFO - Epoch [53][800/1281] lr: 1.815e-02, eta: 7:45:09, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9975, loss_cls: 0.5573, loss: 0.5573 +2025-06-24 15:19:54,727 - pyskl - INFO - Epoch [53][900/1281] lr: 1.813e-02, eta: 7:44:46, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9994, loss_cls: 0.4982, loss: 0.4982 +2025-06-24 15:20:17,172 - pyskl - INFO - Epoch [53][1000/1281] lr: 1.811e-02, eta: 7:44:24, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9944, loss_cls: 0.5895, loss: 0.5895 +2025-06-24 15:20:39,630 - pyskl - INFO - Epoch [53][1100/1281] lr: 1.809e-02, eta: 7:44:02, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9981, loss_cls: 0.5073, loss: 0.5073 +2025-06-24 15:21:02,409 - pyskl - INFO - Epoch [53][1200/1281] lr: 1.807e-02, eta: 7:43:40, time: 0.228, data_time: 0.001, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9944, loss_cls: 0.5606, loss: 0.5606 +2025-06-24 15:21:21,137 - pyskl - INFO - Saving checkpoint at 53 epochs +2025-06-24 15:22:04,651 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:22:04,706 - pyskl - INFO - +top1_acc 0.8358 +top5_acc 0.9842 +2025-06-24 15:22:04,707 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:22:04,713 - pyskl - INFO - +mean_acc 0.7899 +2025-06-24 15:22:04,715 - pyskl - INFO - Epoch(val) [53][533] top1_acc: 0.8358, top5_acc: 0.9842, mean_class_accuracy: 0.7899 +2025-06-24 15:22:47,846 - pyskl - INFO - Epoch [54][100/1281] lr: 1.804e-02, eta: 7:43:05, time: 0.431, data_time: 0.193, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9975, loss_cls: 0.4968, loss: 0.4968 +2025-06-24 15:23:10,169 - pyskl - INFO - Epoch [54][200/1281] lr: 1.802e-02, eta: 7:42:42, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9969, loss_cls: 0.5271, loss: 0.5271 +2025-06-24 15:23:32,520 - pyskl - INFO - Epoch [54][300/1281] lr: 1.800e-02, eta: 7:42:20, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9962, loss_cls: 0.5935, loss: 0.5935 +2025-06-24 15:23:54,991 - pyskl - INFO - Epoch [54][400/1281] lr: 1.798e-02, eta: 7:41:58, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9956, loss_cls: 0.5190, loss: 0.5190 +2025-06-24 15:24:17,429 - pyskl - INFO - Epoch [54][500/1281] lr: 1.797e-02, eta: 7:41:35, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9975, loss_cls: 0.4497, loss: 0.4497 +2025-06-24 15:24:39,640 - pyskl - INFO - Epoch [54][600/1281] lr: 1.795e-02, eta: 7:41:13, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9969, loss_cls: 0.5256, loss: 0.5256 +2025-06-24 15:25:02,005 - pyskl - INFO - Epoch [54][700/1281] lr: 1.793e-02, eta: 7:40:50, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9988, loss_cls: 0.4699, loss: 0.4699 +2025-06-24 15:25:24,832 - pyskl - INFO - Epoch [54][800/1281] lr: 1.791e-02, eta: 7:40:29, time: 0.228, data_time: 0.001, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9944, loss_cls: 0.4906, loss: 0.4906 +2025-06-24 15:25:47,580 - pyskl - INFO - Epoch [54][900/1281] lr: 1.789e-02, eta: 7:40:07, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9962, loss_cls: 0.5395, loss: 0.5395 +2025-06-24 15:26:10,258 - pyskl - INFO - Epoch [54][1000/1281] lr: 1.787e-02, eta: 7:39:45, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9969, loss_cls: 0.5081, loss: 0.5081 +2025-06-24 15:26:32,882 - pyskl - INFO - Epoch [54][1100/1281] lr: 1.786e-02, eta: 7:39:23, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9962, loss_cls: 0.4910, loss: 0.4910 +2025-06-24 15:26:55,631 - pyskl - INFO - Epoch [54][1200/1281] lr: 1.784e-02, eta: 7:39:01, time: 0.227, data_time: 0.001, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9975, loss_cls: 0.4834, loss: 0.4834 +2025-06-24 15:27:14,569 - pyskl - INFO - Saving checkpoint at 54 epochs +2025-06-24 15:27:59,297 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:27:59,365 - pyskl - INFO - +top1_acc 0.8729 +top5_acc 0.9910 +2025-06-24 15:27:59,365 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:27:59,374 - pyskl - INFO - +mean_acc 0.8289 +2025-06-24 15:27:59,376 - pyskl - INFO - Epoch(val) [54][533] top1_acc: 0.8729, top5_acc: 0.9910, mean_class_accuracy: 0.8289 +2025-06-24 15:28:43,009 - pyskl - INFO - Epoch [55][100/1281] lr: 1.780e-02, eta: 7:38:26, time: 0.436, data_time: 0.197, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9975, loss_cls: 0.4942, loss: 0.4942 +2025-06-24 15:29:05,212 - pyskl - INFO - Epoch [55][200/1281] lr: 1.779e-02, eta: 7:38:04, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9975, loss_cls: 0.4683, loss: 0.4683 +2025-06-24 15:29:27,739 - pyskl - INFO - Epoch [55][300/1281] lr: 1.777e-02, eta: 7:37:42, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9969, loss_cls: 0.4950, loss: 0.4950 +2025-06-24 15:29:50,069 - pyskl - INFO - Epoch [55][400/1281] lr: 1.775e-02, eta: 7:37:19, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9956, loss_cls: 0.4812, loss: 0.4812 +2025-06-24 15:30:12,549 - pyskl - INFO - Epoch [55][500/1281] lr: 1.773e-02, eta: 7:36:57, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9956, loss_cls: 0.5756, loss: 0.5756 +2025-06-24 15:30:35,007 - pyskl - INFO - Epoch [55][600/1281] lr: 1.771e-02, eta: 7:36:35, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9975, loss_cls: 0.5534, loss: 0.5534 +2025-06-24 15:30:57,576 - pyskl - INFO - Epoch [55][700/1281] lr: 1.769e-02, eta: 7:36:12, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9969, loss_cls: 0.4956, loss: 0.4956 +2025-06-24 15:31:20,229 - pyskl - INFO - Epoch [55][800/1281] lr: 1.767e-02, eta: 7:35:51, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9994, loss_cls: 0.4856, loss: 0.4856 +2025-06-24 15:31:42,810 - pyskl - INFO - Epoch [55][900/1281] lr: 1.766e-02, eta: 7:35:29, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9944, loss_cls: 0.5144, loss: 0.5144 +2025-06-24 15:32:05,330 - pyskl - INFO - Epoch [55][1000/1281] lr: 1.764e-02, eta: 7:35:06, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9975, loss_cls: 0.4812, loss: 0.4812 +2025-06-24 15:32:28,024 - pyskl - INFO - Epoch [55][1100/1281] lr: 1.762e-02, eta: 7:34:44, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9969, loss_cls: 0.5348, loss: 0.5348 +2025-06-24 15:32:50,190 - pyskl - INFO - Epoch [55][1200/1281] lr: 1.760e-02, eta: 7:34:22, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9950, loss_cls: 0.5632, loss: 0.5632 +2025-06-24 15:33:09,255 - pyskl - INFO - Saving checkpoint at 55 epochs +2025-06-24 15:33:53,377 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:33:53,432 - pyskl - INFO - +top1_acc 0.8710 +top5_acc 0.9923 +2025-06-24 15:33:53,432 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:33:53,439 - pyskl - INFO - +mean_acc 0.8254 +2025-06-24 15:33:53,441 - pyskl - INFO - Epoch(val) [55][533] top1_acc: 0.8710, top5_acc: 0.9923, mean_class_accuracy: 0.8254 +2025-06-24 15:34:36,033 - pyskl - INFO - Epoch [56][100/1281] lr: 1.757e-02, eta: 7:33:45, time: 0.426, data_time: 0.190, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9969, loss_cls: 0.5207, loss: 0.5207 +2025-06-24 15:34:57,990 - pyskl - INFO - Epoch [56][200/1281] lr: 1.755e-02, eta: 7:33:22, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9994, loss_cls: 0.4379, loss: 0.4379 +2025-06-24 15:35:20,406 - pyskl - INFO - Epoch [56][300/1281] lr: 1.753e-02, eta: 7:32:59, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9981, loss_cls: 0.4660, loss: 0.4660 +2025-06-24 15:35:42,740 - pyskl - INFO - Epoch [56][400/1281] lr: 1.751e-02, eta: 7:32:37, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9956, loss_cls: 0.5790, loss: 0.5790 +2025-06-24 15:36:05,331 - pyskl - INFO - Epoch [56][500/1281] lr: 1.749e-02, eta: 7:32:15, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9962, loss_cls: 0.5137, loss: 0.5137 +2025-06-24 15:36:27,687 - pyskl - INFO - Epoch [56][600/1281] lr: 1.747e-02, eta: 7:31:52, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9956, loss_cls: 0.4468, loss: 0.4468 +2025-06-24 15:36:50,477 - pyskl - INFO - Epoch [56][700/1281] lr: 1.745e-02, eta: 7:31:31, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9988, loss_cls: 0.4963, loss: 0.4963 +2025-06-24 15:37:12,986 - pyskl - INFO - Epoch [56][800/1281] lr: 1.743e-02, eta: 7:31:08, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9969, loss_cls: 0.5148, loss: 0.5148 +2025-06-24 15:37:35,318 - pyskl - INFO - Epoch [56][900/1281] lr: 1.742e-02, eta: 7:30:46, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9975, loss_cls: 0.5123, loss: 0.5123 +2025-06-24 15:37:57,821 - pyskl - INFO - Epoch [56][1000/1281] lr: 1.740e-02, eta: 7:30:24, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9969, loss_cls: 0.4996, loss: 0.4996 +2025-06-24 15:38:20,187 - pyskl - INFO - Epoch [56][1100/1281] lr: 1.738e-02, eta: 7:30:01, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9975, loss_cls: 0.4768, loss: 0.4768 +2025-06-24 15:38:42,583 - pyskl - INFO - Epoch [56][1200/1281] lr: 1.736e-02, eta: 7:29:39, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9944, loss_cls: 0.5558, loss: 0.5558 +2025-06-24 15:39:01,390 - pyskl - INFO - Saving checkpoint at 56 epochs +2025-06-24 15:39:45,443 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:39:45,513 - pyskl - INFO - +top1_acc 0.8032 +top5_acc 0.9783 +2025-06-24 15:39:45,513 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:39:45,521 - pyskl - INFO - +mean_acc 0.7416 +2025-06-24 15:39:45,523 - pyskl - INFO - Epoch(val) [56][533] top1_acc: 0.8032, top5_acc: 0.9783, mean_class_accuracy: 0.7416 +2025-06-24 15:40:28,517 - pyskl - INFO - Epoch [57][100/1281] lr: 1.733e-02, eta: 7:29:02, time: 0.430, data_time: 0.196, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9956, loss_cls: 0.5154, loss: 0.5154 +2025-06-24 15:40:51,132 - pyskl - INFO - Epoch [57][200/1281] lr: 1.731e-02, eta: 7:28:40, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9988, loss_cls: 0.4715, loss: 0.4715 +2025-06-24 15:41:13,700 - pyskl - INFO - Epoch [57][300/1281] lr: 1.729e-02, eta: 7:28:18, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9956, loss_cls: 0.4938, loss: 0.4938 +2025-06-24 15:41:35,947 - pyskl - INFO - Epoch [57][400/1281] lr: 1.727e-02, eta: 7:27:56, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9969, loss_cls: 0.5466, loss: 0.5466 +2025-06-24 15:41:58,385 - pyskl - INFO - Epoch [57][500/1281] lr: 1.725e-02, eta: 7:27:33, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9994, loss_cls: 0.4865, loss: 0.4865 +2025-06-24 15:42:20,800 - pyskl - INFO - Epoch [57][600/1281] lr: 1.723e-02, eta: 7:27:11, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9975, loss_cls: 0.4628, loss: 0.4628 +2025-06-24 15:42:43,282 - pyskl - INFO - Epoch [57][700/1281] lr: 1.721e-02, eta: 7:26:49, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9944, loss_cls: 0.5383, loss: 0.5383 +2025-06-24 15:43:05,618 - pyskl - INFO - Epoch [57][800/1281] lr: 1.719e-02, eta: 7:26:26, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9981, loss_cls: 0.4982, loss: 0.4982 +2025-06-24 15:43:27,946 - pyskl - INFO - Epoch [57][900/1281] lr: 1.717e-02, eta: 7:26:04, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9950, loss_cls: 0.5086, loss: 0.5086 +2025-06-24 15:43:50,427 - pyskl - INFO - Epoch [57][1000/1281] lr: 1.716e-02, eta: 7:25:42, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9969, loss_cls: 0.5666, loss: 0.5666 +2025-06-24 15:44:12,791 - pyskl - INFO - Epoch [57][1100/1281] lr: 1.714e-02, eta: 7:25:19, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9956, loss_cls: 0.5271, loss: 0.5271 +2025-06-24 15:44:35,507 - pyskl - INFO - Epoch [57][1200/1281] lr: 1.712e-02, eta: 7:24:57, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9962, loss_cls: 0.5155, loss: 0.5155 +2025-06-24 15:44:54,451 - pyskl - INFO - Saving checkpoint at 57 epochs +2025-06-24 15:45:38,171 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:45:38,247 - pyskl - INFO - +top1_acc 0.8551 +top5_acc 0.9887 +2025-06-24 15:45:38,247 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:45:38,254 - pyskl - INFO - +mean_acc 0.7997 +2025-06-24 15:45:38,256 - pyskl - INFO - Epoch(val) [57][533] top1_acc: 0.8551, top5_acc: 0.9887, mean_class_accuracy: 0.7997 +2025-06-24 15:46:20,479 - pyskl - INFO - Epoch [58][100/1281] lr: 1.708e-02, eta: 7:24:19, time: 0.422, data_time: 0.189, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9981, loss_cls: 0.4412, loss: 0.4412 +2025-06-24 15:46:43,063 - pyskl - INFO - Epoch [58][200/1281] lr: 1.706e-02, eta: 7:23:57, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9988, loss_cls: 0.4558, loss: 0.4558 +2025-06-24 15:47:05,388 - pyskl - INFO - Epoch [58][300/1281] lr: 1.704e-02, eta: 7:23:35, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9956, loss_cls: 0.4804, loss: 0.4804 +2025-06-24 15:47:27,547 - pyskl - INFO - Epoch [58][400/1281] lr: 1.703e-02, eta: 7:23:12, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9956, loss_cls: 0.5330, loss: 0.5330 +2025-06-24 15:47:49,923 - pyskl - INFO - Epoch [58][500/1281] lr: 1.701e-02, eta: 7:22:50, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9981, loss_cls: 0.4827, loss: 0.4827 +2025-06-24 15:48:12,748 - pyskl - INFO - Epoch [58][600/1281] lr: 1.699e-02, eta: 7:22:28, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9981, loss_cls: 0.3746, loss: 0.3746 +2025-06-24 15:48:35,141 - pyskl - INFO - Epoch [58][700/1281] lr: 1.697e-02, eta: 7:22:05, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9981, loss_cls: 0.5154, loss: 0.5154 +2025-06-24 15:48:57,051 - pyskl - INFO - Epoch [58][800/1281] lr: 1.695e-02, eta: 7:21:42, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9981, loss_cls: 0.4625, loss: 0.4625 +2025-06-24 15:49:19,449 - pyskl - INFO - Epoch [58][900/1281] lr: 1.693e-02, eta: 7:21:20, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9975, loss_cls: 0.5676, loss: 0.5676 +2025-06-24 15:49:41,972 - pyskl - INFO - Epoch [58][1000/1281] lr: 1.691e-02, eta: 7:20:58, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9988, loss_cls: 0.4582, loss: 0.4582 +2025-06-24 15:50:04,270 - pyskl - INFO - Epoch [58][1100/1281] lr: 1.689e-02, eta: 7:20:35, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9988, loss_cls: 0.4983, loss: 0.4983 +2025-06-24 15:50:26,857 - pyskl - INFO - Epoch [58][1200/1281] lr: 1.687e-02, eta: 7:20:13, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9962, loss_cls: 0.4809, loss: 0.4809 +2025-06-24 15:50:45,670 - pyskl - INFO - Saving checkpoint at 58 epochs +2025-06-24 15:51:29,351 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:51:29,409 - pyskl - INFO - +top1_acc 0.8607 +top5_acc 0.9908 +2025-06-24 15:51:29,409 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:51:29,416 - pyskl - INFO - +mean_acc 0.8199 +2025-06-24 15:51:29,417 - pyskl - INFO - Epoch(val) [58][533] top1_acc: 0.8607, top5_acc: 0.9908, mean_class_accuracy: 0.8199 +2025-06-24 15:52:11,797 - pyskl - INFO - Epoch [59][100/1281] lr: 1.684e-02, eta: 7:19:35, time: 0.424, data_time: 0.186, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9988, loss_cls: 0.4725, loss: 0.4725 +2025-06-24 15:52:34,448 - pyskl - INFO - Epoch [59][200/1281] lr: 1.682e-02, eta: 7:19:13, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9962, loss_cls: 0.4440, loss: 0.4440 +2025-06-24 15:52:56,840 - pyskl - INFO - Epoch [59][300/1281] lr: 1.680e-02, eta: 7:18:51, time: 0.224, data_time: 0.001, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9994, loss_cls: 0.4974, loss: 0.4974 +2025-06-24 15:53:18,870 - pyskl - INFO - Epoch [59][400/1281] lr: 1.678e-02, eta: 7:18:28, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9981, loss_cls: 0.4070, loss: 0.4070 +2025-06-24 15:53:41,417 - pyskl - INFO - Epoch [59][500/1281] lr: 1.676e-02, eta: 7:18:06, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9981, loss_cls: 0.4506, loss: 0.4506 +2025-06-24 15:54:03,459 - pyskl - INFO - Epoch [59][600/1281] lr: 1.674e-02, eta: 7:17:43, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9988, loss_cls: 0.4732, loss: 0.4732 +2025-06-24 15:54:25,782 - pyskl - INFO - Epoch [59][700/1281] lr: 1.672e-02, eta: 7:17:20, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9962, loss_cls: 0.4657, loss: 0.4657 +2025-06-24 15:54:48,099 - pyskl - INFO - Epoch [59][800/1281] lr: 1.670e-02, eta: 7:16:58, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9931, loss_cls: 0.5683, loss: 0.5683 +2025-06-24 15:55:10,755 - pyskl - INFO - Epoch [59][900/1281] lr: 1.668e-02, eta: 7:16:36, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9969, loss_cls: 0.4916, loss: 0.4916 +2025-06-24 15:55:33,154 - pyskl - INFO - Epoch [59][1000/1281] lr: 1.667e-02, eta: 7:16:13, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9981, loss_cls: 0.5059, loss: 0.5059 +2025-06-24 15:55:55,397 - pyskl - INFO - Epoch [59][1100/1281] lr: 1.665e-02, eta: 7:15:51, time: 0.222, data_time: 0.001, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9944, loss_cls: 0.5462, loss: 0.5462 +2025-06-24 15:56:17,809 - pyskl - INFO - Epoch [59][1200/1281] lr: 1.663e-02, eta: 7:15:28, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9988, loss_cls: 0.4381, loss: 0.4381 +2025-06-24 15:56:36,568 - pyskl - INFO - Saving checkpoint at 59 epochs +2025-06-24 15:57:19,663 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:57:19,734 - pyskl - INFO - +top1_acc 0.8436 +top5_acc 0.9892 +2025-06-24 15:57:19,734 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:57:19,742 - pyskl - INFO - +mean_acc 0.7901 +2025-06-24 15:57:19,743 - pyskl - INFO - Epoch(val) [59][533] top1_acc: 0.8436, top5_acc: 0.9892, mean_class_accuracy: 0.7901 +2025-06-24 15:58:02,091 - pyskl - INFO - Epoch [60][100/1281] lr: 1.659e-02, eta: 7:14:51, time: 0.423, data_time: 0.190, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9975, loss_cls: 0.4717, loss: 0.4717 +2025-06-24 15:58:24,308 - pyskl - INFO - Epoch [60][200/1281] lr: 1.657e-02, eta: 7:14:28, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9975, loss_cls: 0.4882, loss: 0.4882 +2025-06-24 15:58:46,929 - pyskl - INFO - Epoch [60][300/1281] lr: 1.655e-02, eta: 7:14:06, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9975, loss_cls: 0.4339, loss: 0.4339 +2025-06-24 15:59:09,247 - pyskl - INFO - Epoch [60][400/1281] lr: 1.653e-02, eta: 7:13:43, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9988, loss_cls: 0.5030, loss: 0.5030 +2025-06-24 15:59:31,990 - pyskl - INFO - Epoch [60][500/1281] lr: 1.651e-02, eta: 7:13:21, time: 0.227, data_time: 0.001, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9950, loss_cls: 0.5070, loss: 0.5070 +2025-06-24 15:59:54,264 - pyskl - INFO - Epoch [60][600/1281] lr: 1.650e-02, eta: 7:12:59, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9975, loss_cls: 0.4766, loss: 0.4766 +2025-06-24 16:00:16,512 - pyskl - INFO - Epoch [60][700/1281] lr: 1.648e-02, eta: 7:12:36, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9956, loss_cls: 0.5374, loss: 0.5374 +2025-06-24 16:00:38,947 - pyskl - INFO - Epoch [60][800/1281] lr: 1.646e-02, eta: 7:12:14, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9956, loss_cls: 0.4684, loss: 0.4684 +2025-06-24 16:01:01,499 - pyskl - INFO - Epoch [60][900/1281] lr: 1.644e-02, eta: 7:11:52, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9950, loss_cls: 0.5025, loss: 0.5025 +2025-06-24 16:01:24,007 - pyskl - INFO - Epoch [60][1000/1281] lr: 1.642e-02, eta: 7:11:29, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9969, loss_cls: 0.5120, loss: 0.5120 +2025-06-24 16:01:46,573 - pyskl - INFO - Epoch [60][1100/1281] lr: 1.640e-02, eta: 7:11:07, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9938, loss_cls: 0.5311, loss: 0.5311 +2025-06-24 16:02:08,760 - pyskl - INFO - Epoch [60][1200/1281] lr: 1.638e-02, eta: 7:10:45, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9975, loss_cls: 0.4579, loss: 0.4579 +2025-06-24 16:02:27,442 - pyskl - INFO - Saving checkpoint at 60 epochs +2025-06-24 16:03:11,689 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:03:11,746 - pyskl - INFO - +top1_acc 0.8782 +top5_acc 0.9926 +2025-06-24 16:03:11,746 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:03:11,754 - pyskl - INFO - +mean_acc 0.8300 +2025-06-24 16:03:11,758 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_52.pth was removed +2025-06-24 16:03:11,924 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_60.pth. +2025-06-24 16:03:11,925 - pyskl - INFO - Best top1_acc is 0.8782 at 60 epoch. +2025-06-24 16:03:11,927 - pyskl - INFO - Epoch(val) [60][533] top1_acc: 0.8782, top5_acc: 0.9926, mean_class_accuracy: 0.8300 +2025-06-24 16:03:54,515 - pyskl - INFO - Epoch [61][100/1281] lr: 1.634e-02, eta: 7:10:07, time: 0.426, data_time: 0.191, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9988, loss_cls: 0.4517, loss: 0.4517 +2025-06-24 16:04:16,874 - pyskl - INFO - Epoch [61][200/1281] lr: 1.632e-02, eta: 7:09:45, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9994, loss_cls: 0.4257, loss: 0.4257 +2025-06-24 16:04:39,022 - pyskl - INFO - Epoch [61][300/1281] lr: 1.630e-02, eta: 7:09:22, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9981, loss_cls: 0.4318, loss: 0.4318 +2025-06-24 16:05:01,321 - pyskl - INFO - Epoch [61][400/1281] lr: 1.629e-02, eta: 7:08:59, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9956, loss_cls: 0.5027, loss: 0.5027 +2025-06-24 16:05:23,403 - pyskl - INFO - Epoch [61][500/1281] lr: 1.627e-02, eta: 7:08:36, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9950, loss_cls: 0.4252, loss: 0.4252 +2025-06-24 16:05:45,617 - pyskl - INFO - Epoch [61][600/1281] lr: 1.625e-02, eta: 7:08:14, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9969, loss_cls: 0.4031, loss: 0.4031 +2025-06-24 16:06:08,051 - pyskl - INFO - Epoch [61][700/1281] lr: 1.623e-02, eta: 7:07:51, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9950, loss_cls: 0.5040, loss: 0.5040 +2025-06-24 16:06:30,646 - pyskl - INFO - Epoch [61][800/1281] lr: 1.621e-02, eta: 7:07:29, time: 0.226, data_time: 0.001, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9962, loss_cls: 0.4638, loss: 0.4638 +2025-06-24 16:06:52,599 - pyskl - INFO - Epoch [61][900/1281] lr: 1.619e-02, eta: 7:07:06, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9969, loss_cls: 0.4910, loss: 0.4910 +2025-06-24 16:07:15,228 - pyskl - INFO - Epoch [61][1000/1281] lr: 1.617e-02, eta: 7:06:44, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9975, loss_cls: 0.5466, loss: 0.5466 +2025-06-24 16:07:37,426 - pyskl - INFO - Epoch [61][1100/1281] lr: 1.615e-02, eta: 7:06:21, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9962, loss_cls: 0.4313, loss: 0.4313 +2025-06-24 16:07:59,819 - pyskl - INFO - Epoch [61][1200/1281] lr: 1.613e-02, eta: 7:05:59, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9988, loss_cls: 0.4809, loss: 0.4809 +2025-06-24 16:08:18,937 - pyskl - INFO - Saving checkpoint at 61 epochs +2025-06-24 16:09:02,261 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:09:02,328 - pyskl - INFO - +top1_acc 0.8632 +top5_acc 0.9916 +2025-06-24 16:09:02,329 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:09:02,337 - pyskl - INFO - +mean_acc 0.8136 +2025-06-24 16:09:02,339 - pyskl - INFO - Epoch(val) [61][533] top1_acc: 0.8632, top5_acc: 0.9916, mean_class_accuracy: 0.8136 +2025-06-24 16:09:43,806 - pyskl - INFO - Epoch [62][100/1281] lr: 1.609e-02, eta: 7:05:20, time: 0.415, data_time: 0.184, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9975, loss_cls: 0.4997, loss: 0.4997 +2025-06-24 16:10:06,115 - pyskl - INFO - Epoch [62][200/1281] lr: 1.607e-02, eta: 7:04:57, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9988, loss_cls: 0.4248, loss: 0.4248 +2025-06-24 16:10:28,250 - pyskl - INFO - Epoch [62][300/1281] lr: 1.605e-02, eta: 7:04:34, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9981, loss_cls: 0.4365, loss: 0.4365 +2025-06-24 16:10:50,927 - pyskl - INFO - Epoch [62][400/1281] lr: 1.603e-02, eta: 7:04:12, time: 0.227, data_time: 0.001, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9988, loss_cls: 0.4964, loss: 0.4964 +2025-06-24 16:11:13,717 - pyskl - INFO - Epoch [62][500/1281] lr: 1.602e-02, eta: 7:03:51, time: 0.228, data_time: 0.001, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9975, loss_cls: 0.4635, loss: 0.4635 +2025-06-24 16:11:35,872 - pyskl - INFO - Epoch [62][600/1281] lr: 1.600e-02, eta: 7:03:28, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9975, loss_cls: 0.4423, loss: 0.4423 +2025-06-24 16:11:58,422 - pyskl - INFO - Epoch [62][700/1281] lr: 1.598e-02, eta: 7:03:06, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9950, loss_cls: 0.4704, loss: 0.4704 +2025-06-24 16:12:21,064 - pyskl - INFO - Epoch [62][800/1281] lr: 1.596e-02, eta: 7:02:44, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9981, loss_cls: 0.4213, loss: 0.4213 +2025-06-24 16:12:43,724 - pyskl - INFO - Epoch [62][900/1281] lr: 1.594e-02, eta: 7:02:21, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9956, loss_cls: 0.4812, loss: 0.4812 +2025-06-24 16:13:06,085 - pyskl - INFO - Epoch [62][1000/1281] lr: 1.592e-02, eta: 7:01:59, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9962, loss_cls: 0.4947, loss: 0.4947 +2025-06-24 16:13:28,086 - pyskl - INFO - Epoch [62][1100/1281] lr: 1.590e-02, eta: 7:01:36, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9975, loss_cls: 0.4729, loss: 0.4729 +2025-06-24 16:13:50,192 - pyskl - INFO - Epoch [62][1200/1281] lr: 1.588e-02, eta: 7:01:13, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9969, loss_cls: 0.4637, loss: 0.4637 +2025-06-24 16:14:09,237 - pyskl - INFO - Saving checkpoint at 62 epochs +2025-06-24 16:14:52,970 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:14:53,025 - pyskl - INFO - +top1_acc 0.8811 +top5_acc 0.9942 +2025-06-24 16:14:53,025 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:14:53,033 - pyskl - INFO - +mean_acc 0.8442 +2025-06-24 16:14:53,040 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_60.pth was removed +2025-06-24 16:14:53,213 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_62.pth. +2025-06-24 16:14:53,214 - pyskl - INFO - Best top1_acc is 0.8811 at 62 epoch. +2025-06-24 16:14:53,216 - pyskl - INFO - Epoch(val) [62][533] top1_acc: 0.8811, top5_acc: 0.9942, mean_class_accuracy: 0.8442 +2025-06-24 16:15:35,854 - pyskl - INFO - Epoch [63][100/1281] lr: 1.584e-02, eta: 7:00:36, time: 0.426, data_time: 0.196, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9994, loss_cls: 0.3827, loss: 0.3827 +2025-06-24 16:15:58,337 - pyskl - INFO - Epoch [63][200/1281] lr: 1.582e-02, eta: 7:00:13, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9981, loss_cls: 0.4016, loss: 0.4016 +2025-06-24 16:16:20,639 - pyskl - INFO - Epoch [63][300/1281] lr: 1.580e-02, eta: 6:59:51, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9969, loss_cls: 0.4529, loss: 0.4529 +2025-06-24 16:16:43,170 - pyskl - INFO - Epoch [63][400/1281] lr: 1.578e-02, eta: 6:59:29, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9981, loss_cls: 0.4490, loss: 0.4490 +2025-06-24 16:17:05,506 - pyskl - INFO - Epoch [63][500/1281] lr: 1.576e-02, eta: 6:59:06, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9981, loss_cls: 0.4368, loss: 0.4368 +2025-06-24 16:17:27,822 - pyskl - INFO - Epoch [63][600/1281] lr: 1.574e-02, eta: 6:58:43, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9981, loss_cls: 0.4770, loss: 0.4770 +2025-06-24 16:17:50,440 - pyskl - INFO - Epoch [63][700/1281] lr: 1.572e-02, eta: 6:58:21, time: 0.226, data_time: 0.001, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9962, loss_cls: 0.4999, loss: 0.4999 +2025-06-24 16:18:12,835 - pyskl - INFO - Epoch [63][800/1281] lr: 1.570e-02, eta: 6:57:59, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9975, loss_cls: 0.4215, loss: 0.4215 +2025-06-24 16:18:35,254 - pyskl - INFO - Epoch [63][900/1281] lr: 1.568e-02, eta: 6:57:37, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9975, loss_cls: 0.4642, loss: 0.4642 +2025-06-24 16:18:57,847 - pyskl - INFO - Epoch [63][1000/1281] lr: 1.566e-02, eta: 6:57:14, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9962, loss_cls: 0.4846, loss: 0.4846 +2025-06-24 16:19:19,978 - pyskl - INFO - Epoch [63][1100/1281] lr: 1.564e-02, eta: 6:56:52, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9969, loss_cls: 0.4365, loss: 0.4365 +2025-06-24 16:19:42,218 - pyskl - INFO - Epoch [63][1200/1281] lr: 1.562e-02, eta: 6:56:29, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9975, loss_cls: 0.5009, loss: 0.5009 +2025-06-24 16:20:01,005 - pyskl - INFO - Saving checkpoint at 63 epochs +2025-06-24 16:20:44,832 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:20:44,899 - pyskl - INFO - +top1_acc 0.8659 +top5_acc 0.9923 +2025-06-24 16:20:44,900 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:20:44,908 - pyskl - INFO - +mean_acc 0.8138 +2025-06-24 16:20:44,911 - pyskl - INFO - Epoch(val) [63][533] top1_acc: 0.8659, top5_acc: 0.9923, mean_class_accuracy: 0.8138 +2025-06-24 16:21:27,828 - pyskl - INFO - Epoch [64][100/1281] lr: 1.559e-02, eta: 6:55:52, time: 0.429, data_time: 0.195, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9988, loss_cls: 0.4479, loss: 0.4479 +2025-06-24 16:21:50,063 - pyskl - INFO - Epoch [64][200/1281] lr: 1.557e-02, eta: 6:55:29, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9988, loss_cls: 0.4757, loss: 0.4757 +2025-06-24 16:22:12,619 - pyskl - INFO - Epoch [64][300/1281] lr: 1.555e-02, eta: 6:55:07, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 1.0000, loss_cls: 0.4878, loss: 0.4878 +2025-06-24 16:22:35,309 - pyskl - INFO - Epoch [64][400/1281] lr: 1.553e-02, eta: 6:54:45, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9988, loss_cls: 0.4463, loss: 0.4463 +2025-06-24 16:22:57,573 - pyskl - INFO - Epoch [64][500/1281] lr: 1.551e-02, eta: 6:54:22, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 1.0000, loss_cls: 0.4280, loss: 0.4280 +2025-06-24 16:23:20,145 - pyskl - INFO - Epoch [64][600/1281] lr: 1.549e-02, eta: 6:54:00, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9969, loss_cls: 0.4576, loss: 0.4576 +2025-06-24 16:23:42,730 - pyskl - INFO - Epoch [64][700/1281] lr: 1.547e-02, eta: 6:53:38, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9981, loss_cls: 0.4997, loss: 0.4997 +2025-06-24 16:24:04,866 - pyskl - INFO - Epoch [64][800/1281] lr: 1.545e-02, eta: 6:53:15, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9988, loss_cls: 0.4129, loss: 0.4129 +2025-06-24 16:24:27,480 - pyskl - INFO - Epoch [64][900/1281] lr: 1.543e-02, eta: 6:52:53, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9956, loss_cls: 0.5240, loss: 0.5240 +2025-06-24 16:24:50,136 - pyskl - INFO - Epoch [64][1000/1281] lr: 1.541e-02, eta: 6:52:31, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9994, loss_cls: 0.4715, loss: 0.4715 +2025-06-24 16:25:12,241 - pyskl - INFO - Epoch [64][1100/1281] lr: 1.539e-02, eta: 6:52:08, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9975, loss_cls: 0.4708, loss: 0.4708 +2025-06-24 16:25:34,840 - pyskl - INFO - Epoch [64][1200/1281] lr: 1.537e-02, eta: 6:51:46, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9956, loss_cls: 0.4777, loss: 0.4777 +2025-06-24 16:25:53,526 - pyskl - INFO - Saving checkpoint at 64 epochs +2025-06-24 16:26:37,523 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:26:37,579 - pyskl - INFO - +top1_acc 0.8764 +top5_acc 0.9921 +2025-06-24 16:26:37,579 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:26:37,585 - pyskl - INFO - +mean_acc 0.8279 +2025-06-24 16:26:37,586 - pyskl - INFO - Epoch(val) [64][533] top1_acc: 0.8764, top5_acc: 0.9921, mean_class_accuracy: 0.8279 +2025-06-24 16:27:20,189 - pyskl - INFO - Epoch [65][100/1281] lr: 1.533e-02, eta: 6:51:08, time: 0.426, data_time: 0.194, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9981, loss_cls: 0.4058, loss: 0.4058 +2025-06-24 16:27:42,713 - pyskl - INFO - Epoch [65][200/1281] lr: 1.531e-02, eta: 6:50:46, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9988, loss_cls: 0.4272, loss: 0.4272 +2025-06-24 16:28:05,076 - pyskl - INFO - Epoch [65][300/1281] lr: 1.529e-02, eta: 6:50:23, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9981, loss_cls: 0.4581, loss: 0.4581 +2025-06-24 16:28:27,401 - pyskl - INFO - Epoch [65][400/1281] lr: 1.527e-02, eta: 6:50:01, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9975, loss_cls: 0.5184, loss: 0.5184 +2025-06-24 16:28:49,691 - pyskl - INFO - Epoch [65][500/1281] lr: 1.526e-02, eta: 6:49:38, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9981, loss_cls: 0.4534, loss: 0.4534 +2025-06-24 16:29:12,194 - pyskl - INFO - Epoch [65][600/1281] lr: 1.524e-02, eta: 6:49:16, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9981, loss_cls: 0.4170, loss: 0.4170 +2025-06-24 16:29:34,468 - pyskl - INFO - Epoch [65][700/1281] lr: 1.522e-02, eta: 6:48:53, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9969, loss_cls: 0.5371, loss: 0.5371 +2025-06-24 16:29:56,960 - pyskl - INFO - Epoch [65][800/1281] lr: 1.520e-02, eta: 6:48:31, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9962, loss_cls: 0.4145, loss: 0.4145 +2025-06-24 16:30:19,476 - pyskl - INFO - Epoch [65][900/1281] lr: 1.518e-02, eta: 6:48:09, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9969, loss_cls: 0.5070, loss: 0.5070 +2025-06-24 16:30:41,662 - pyskl - INFO - Epoch [65][1000/1281] lr: 1.516e-02, eta: 6:47:46, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9975, loss_cls: 0.4580, loss: 0.4580 +2025-06-24 16:31:04,020 - pyskl - INFO - Epoch [65][1100/1281] lr: 1.514e-02, eta: 6:47:23, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9981, loss_cls: 0.4424, loss: 0.4424 +2025-06-24 16:31:26,230 - pyskl - INFO - Epoch [65][1200/1281] lr: 1.512e-02, eta: 6:47:01, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9962, loss_cls: 0.4751, loss: 0.4751 +2025-06-24 16:31:44,890 - pyskl - INFO - Saving checkpoint at 65 epochs +2025-06-24 16:32:28,300 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:32:28,355 - pyskl - INFO - +top1_acc 0.8618 +top5_acc 0.9928 +2025-06-24 16:32:28,355 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:32:28,366 - pyskl - INFO - +mean_acc 0.8199 +2025-06-24 16:32:28,369 - pyskl - INFO - Epoch(val) [65][533] top1_acc: 0.8618, top5_acc: 0.9928, mean_class_accuracy: 0.8199 +2025-06-24 16:33:10,412 - pyskl - INFO - Epoch [66][100/1281] lr: 1.508e-02, eta: 6:46:22, time: 0.420, data_time: 0.188, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9981, loss_cls: 0.4654, loss: 0.4654 +2025-06-24 16:33:32,827 - pyskl - INFO - Epoch [66][200/1281] lr: 1.506e-02, eta: 6:46:00, time: 0.224, data_time: 0.001, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9994, loss_cls: 0.3742, loss: 0.3742 +2025-06-24 16:33:55,627 - pyskl - INFO - Epoch [66][300/1281] lr: 1.504e-02, eta: 6:45:38, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9975, loss_cls: 0.4342, loss: 0.4342 +2025-06-24 16:34:18,057 - pyskl - INFO - Epoch [66][400/1281] lr: 1.502e-02, eta: 6:45:15, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 1.0000, loss_cls: 0.4106, loss: 0.4106 +2025-06-24 16:34:40,342 - pyskl - INFO - Epoch [66][500/1281] lr: 1.500e-02, eta: 6:44:53, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9988, loss_cls: 0.4714, loss: 0.4714 +2025-06-24 16:35:02,838 - pyskl - INFO - Epoch [66][600/1281] lr: 1.498e-02, eta: 6:44:31, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9956, loss_cls: 0.4600, loss: 0.4600 +2025-06-24 16:35:25,057 - pyskl - INFO - Epoch [66][700/1281] lr: 1.496e-02, eta: 6:44:08, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9994, loss_cls: 0.4612, loss: 0.4612 +2025-06-24 16:35:47,267 - pyskl - INFO - Epoch [66][800/1281] lr: 1.494e-02, eta: 6:43:45, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9988, loss_cls: 0.4515, loss: 0.4515 +2025-06-24 16:36:09,614 - pyskl - INFO - Epoch [66][900/1281] lr: 1.492e-02, eta: 6:43:23, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9994, loss_cls: 0.4215, loss: 0.4215 +2025-06-24 16:36:31,612 - pyskl - INFO - Epoch [66][1000/1281] lr: 1.490e-02, eta: 6:43:00, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9969, loss_cls: 0.4567, loss: 0.4567 +2025-06-24 16:36:54,066 - pyskl - INFO - Epoch [66][1100/1281] lr: 1.488e-02, eta: 6:42:37, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9944, loss_cls: 0.4798, loss: 0.4798 +2025-06-24 16:37:16,336 - pyskl - INFO - Epoch [66][1200/1281] lr: 1.486e-02, eta: 6:42:15, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9981, loss_cls: 0.4499, loss: 0.4499 +2025-06-24 16:37:35,191 - pyskl - INFO - Saving checkpoint at 66 epochs +2025-06-24 16:38:19,702 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:38:19,757 - pyskl - INFO - +top1_acc 0.8682 +top5_acc 0.9891 +2025-06-24 16:38:19,757 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:38:19,764 - pyskl - INFO - +mean_acc 0.8287 +2025-06-24 16:38:19,769 - pyskl - INFO - Epoch(val) [66][533] top1_acc: 0.8682, top5_acc: 0.9891, mean_class_accuracy: 0.8287 +2025-06-24 16:39:01,765 - pyskl - INFO - Epoch [67][100/1281] lr: 1.482e-02, eta: 6:41:36, time: 0.420, data_time: 0.189, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9981, loss_cls: 0.4272, loss: 0.4272 +2025-06-24 16:39:24,178 - pyskl - INFO - Epoch [67][200/1281] lr: 1.480e-02, eta: 6:41:14, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9962, loss_cls: 0.4008, loss: 0.4008 +2025-06-24 16:39:46,394 - pyskl - INFO - Epoch [67][300/1281] lr: 1.478e-02, eta: 6:40:51, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9988, loss_cls: 0.4185, loss: 0.4185 +2025-06-24 16:40:08,567 - pyskl - INFO - Epoch [67][400/1281] lr: 1.476e-02, eta: 6:40:28, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9975, loss_cls: 0.3816, loss: 0.3816 +2025-06-24 16:40:31,272 - pyskl - INFO - Epoch [67][500/1281] lr: 1.474e-02, eta: 6:40:06, time: 0.227, data_time: 0.001, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9969, loss_cls: 0.3948, loss: 0.3948 +2025-06-24 16:40:53,416 - pyskl - INFO - Epoch [67][600/1281] lr: 1.472e-02, eta: 6:39:43, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9988, loss_cls: 0.4424, loss: 0.4424 +2025-06-24 16:41:15,562 - pyskl - INFO - Epoch [67][700/1281] lr: 1.470e-02, eta: 6:39:21, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9988, loss_cls: 0.3796, loss: 0.3796 +2025-06-24 16:41:38,034 - pyskl - INFO - Epoch [67][800/1281] lr: 1.468e-02, eta: 6:38:58, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9988, loss_cls: 0.4054, loss: 0.4054 +2025-06-24 16:42:00,349 - pyskl - INFO - Epoch [67][900/1281] lr: 1.466e-02, eta: 6:38:36, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9981, loss_cls: 0.4188, loss: 0.4188 +2025-06-24 16:42:22,818 - pyskl - INFO - Epoch [67][1000/1281] lr: 1.464e-02, eta: 6:38:13, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9988, loss_cls: 0.3797, loss: 0.3797 +2025-06-24 16:42:44,892 - pyskl - INFO - Epoch [67][1100/1281] lr: 1.462e-02, eta: 6:37:51, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9962, loss_cls: 0.3963, loss: 0.3963 +2025-06-24 16:43:06,995 - pyskl - INFO - Epoch [67][1200/1281] lr: 1.460e-02, eta: 6:37:28, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9981, loss_cls: 0.3953, loss: 0.3953 +2025-06-24 16:43:25,670 - pyskl - INFO - Saving checkpoint at 67 epochs +2025-06-24 16:44:09,288 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:44:09,345 - pyskl - INFO - +top1_acc 0.8736 +top5_acc 0.9904 +2025-06-24 16:44:09,345 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:44:09,352 - pyskl - INFO - +mean_acc 0.8332 +2025-06-24 16:44:09,353 - pyskl - INFO - Epoch(val) [67][533] top1_acc: 0.8736, top5_acc: 0.9904, mean_class_accuracy: 0.8332 +2025-06-24 16:44:52,005 - pyskl - INFO - Epoch [68][100/1281] lr: 1.456e-02, eta: 6:36:50, time: 0.426, data_time: 0.189, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9969, loss_cls: 0.4716, loss: 0.4716 +2025-06-24 16:45:14,845 - pyskl - INFO - Epoch [68][200/1281] lr: 1.454e-02, eta: 6:36:28, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9994, loss_cls: 0.4375, loss: 0.4375 +2025-06-24 16:45:36,972 - pyskl - INFO - Epoch [68][300/1281] lr: 1.452e-02, eta: 6:36:05, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9975, loss_cls: 0.4687, loss: 0.4687 +2025-06-24 16:45:59,121 - pyskl - INFO - Epoch [68][400/1281] lr: 1.450e-02, eta: 6:35:42, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9981, loss_cls: 0.4327, loss: 0.4327 +2025-06-24 16:46:21,756 - pyskl - INFO - Epoch [68][500/1281] lr: 1.448e-02, eta: 6:35:20, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9969, loss_cls: 0.4768, loss: 0.4768 +2025-06-24 16:46:43,855 - pyskl - INFO - Epoch [68][600/1281] lr: 1.446e-02, eta: 6:34:57, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9988, loss_cls: 0.4124, loss: 0.4124 +2025-06-24 16:47:05,912 - pyskl - INFO - Epoch [68][700/1281] lr: 1.444e-02, eta: 6:34:35, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9956, loss_cls: 0.4431, loss: 0.4431 +2025-06-24 16:47:28,336 - pyskl - INFO - Epoch [68][800/1281] lr: 1.442e-02, eta: 6:34:12, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9962, loss_cls: 0.5027, loss: 0.5027 +2025-06-24 16:47:50,513 - pyskl - INFO - Epoch [68][900/1281] lr: 1.440e-02, eta: 6:33:49, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9969, loss_cls: 0.4605, loss: 0.4605 +2025-06-24 16:48:13,238 - pyskl - INFO - Epoch [68][1000/1281] lr: 1.438e-02, eta: 6:33:27, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9975, loss_cls: 0.4495, loss: 0.4495 +2025-06-24 16:48:35,733 - pyskl - INFO - Epoch [68][1100/1281] lr: 1.436e-02, eta: 6:33:05, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9969, loss_cls: 0.3992, loss: 0.3992 +2025-06-24 16:48:57,890 - pyskl - INFO - Epoch [68][1200/1281] lr: 1.434e-02, eta: 6:32:42, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9981, loss_cls: 0.5003, loss: 0.5003 +2025-06-24 16:49:16,939 - pyskl - INFO - Saving checkpoint at 68 epochs +2025-06-24 16:50:00,689 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:50:00,746 - pyskl - INFO - +top1_acc 0.8737 +top5_acc 0.9923 +2025-06-24 16:50:00,746 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:50:00,754 - pyskl - INFO - +mean_acc 0.8330 +2025-06-24 16:50:00,756 - pyskl - INFO - Epoch(val) [68][533] top1_acc: 0.8737, top5_acc: 0.9923, mean_class_accuracy: 0.8330 +2025-06-24 16:50:43,140 - pyskl - INFO - Epoch [69][100/1281] lr: 1.431e-02, eta: 6:32:04, time: 0.424, data_time: 0.191, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9981, loss_cls: 0.4335, loss: 0.4335 +2025-06-24 16:51:05,343 - pyskl - INFO - Epoch [69][200/1281] lr: 1.429e-02, eta: 6:31:41, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9975, loss_cls: 0.4010, loss: 0.4010 +2025-06-24 16:51:27,521 - pyskl - INFO - Epoch [69][300/1281] lr: 1.427e-02, eta: 6:31:19, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9988, loss_cls: 0.4278, loss: 0.4278 +2025-06-24 16:51:50,196 - pyskl - INFO - Epoch [69][400/1281] lr: 1.425e-02, eta: 6:30:57, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9981, loss_cls: 0.4107, loss: 0.4107 +2025-06-24 16:52:12,420 - pyskl - INFO - Epoch [69][500/1281] lr: 1.423e-02, eta: 6:30:34, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9988, loss_cls: 0.3998, loss: 0.3998 +2025-06-24 16:52:34,910 - pyskl - INFO - Epoch [69][600/1281] lr: 1.420e-02, eta: 6:30:12, time: 0.225, data_time: 0.001, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9975, loss_cls: 0.4780, loss: 0.4780 +2025-06-24 16:52:57,037 - pyskl - INFO - Epoch [69][700/1281] lr: 1.418e-02, eta: 6:29:49, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9969, loss_cls: 0.3813, loss: 0.3813 +2025-06-24 16:53:19,353 - pyskl - INFO - Epoch [69][800/1281] lr: 1.416e-02, eta: 6:29:26, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9962, loss_cls: 0.4257, loss: 0.4257 +2025-06-24 16:53:41,594 - pyskl - INFO - Epoch [69][900/1281] lr: 1.414e-02, eta: 6:29:04, time: 0.222, data_time: 0.001, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9981, loss_cls: 0.4159, loss: 0.4159 +2025-06-24 16:54:03,842 - pyskl - INFO - Epoch [69][1000/1281] lr: 1.412e-02, eta: 6:28:41, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9975, loss_cls: 0.4714, loss: 0.4714 +2025-06-24 16:54:26,164 - pyskl - INFO - Epoch [69][1100/1281] lr: 1.410e-02, eta: 6:28:18, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9975, loss_cls: 0.4200, loss: 0.4200 +2025-06-24 16:54:48,404 - pyskl - INFO - Epoch [69][1200/1281] lr: 1.408e-02, eta: 6:27:56, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9975, loss_cls: 0.4431, loss: 0.4431 +2025-06-24 16:55:07,090 - pyskl - INFO - Saving checkpoint at 69 epochs +2025-06-24 16:55:50,489 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:55:50,544 - pyskl - INFO - +top1_acc 0.8917 +top5_acc 0.9955 +2025-06-24 16:55:50,544 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:55:50,550 - pyskl - INFO - +mean_acc 0.8478 +2025-06-24 16:55:50,554 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_62.pth was removed +2025-06-24 16:55:50,733 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_69.pth. +2025-06-24 16:55:50,733 - pyskl - INFO - Best top1_acc is 0.8917 at 69 epoch. +2025-06-24 16:55:50,736 - pyskl - INFO - Epoch(val) [69][533] top1_acc: 0.8917, top5_acc: 0.9955, mean_class_accuracy: 0.8478 +2025-06-24 16:56:33,377 - pyskl - INFO - Epoch [70][100/1281] lr: 1.405e-02, eta: 6:27:18, time: 0.426, data_time: 0.191, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9994, loss_cls: 0.4025, loss: 0.4025 +2025-06-24 16:56:55,848 - pyskl - INFO - Epoch [70][200/1281] lr: 1.403e-02, eta: 6:26:55, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9988, loss_cls: 0.4215, loss: 0.4215 +2025-06-24 16:57:18,084 - pyskl - INFO - Epoch [70][300/1281] lr: 1.401e-02, eta: 6:26:33, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9981, loss_cls: 0.3861, loss: 0.3861 +2025-06-24 16:57:40,444 - pyskl - INFO - Epoch [70][400/1281] lr: 1.399e-02, eta: 6:26:10, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9994, loss_cls: 0.3257, loss: 0.3257 +2025-06-24 16:58:02,754 - pyskl - INFO - Epoch [70][500/1281] lr: 1.397e-02, eta: 6:25:48, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 0.3547, loss: 0.3547 +2025-06-24 16:58:25,317 - pyskl - INFO - Epoch [70][600/1281] lr: 1.395e-02, eta: 6:25:25, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9988, loss_cls: 0.3389, loss: 0.3389 +2025-06-24 16:58:47,836 - pyskl - INFO - Epoch [70][700/1281] lr: 1.392e-02, eta: 6:25:03, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9956, loss_cls: 0.4215, loss: 0.4215 +2025-06-24 16:59:10,080 - pyskl - INFO - Epoch [70][800/1281] lr: 1.390e-02, eta: 6:24:41, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 1.0000, loss_cls: 0.3599, loss: 0.3599 +2025-06-24 16:59:32,558 - pyskl - INFO - Epoch [70][900/1281] lr: 1.388e-02, eta: 6:24:18, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9975, loss_cls: 0.4068, loss: 0.4068 +2025-06-24 16:59:55,132 - pyskl - INFO - Epoch [70][1000/1281] lr: 1.386e-02, eta: 6:23:56, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9969, loss_cls: 0.4289, loss: 0.4289 +2025-06-24 17:00:17,089 - pyskl - INFO - Epoch [70][1100/1281] lr: 1.384e-02, eta: 6:23:33, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9981, loss_cls: 0.4641, loss: 0.4641 +2025-06-24 17:00:39,532 - pyskl - INFO - Epoch [70][1200/1281] lr: 1.382e-02, eta: 6:23:11, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9975, loss_cls: 0.4724, loss: 0.4724 +2025-06-24 17:00:58,154 - pyskl - INFO - Saving checkpoint at 70 epochs +2025-06-24 17:01:41,895 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:01:41,949 - pyskl - INFO - +top1_acc 0.8799 +top5_acc 0.9941 +2025-06-24 17:01:41,949 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:01:41,956 - pyskl - INFO - +mean_acc 0.8402 +2025-06-24 17:01:41,957 - pyskl - INFO - Epoch(val) [70][533] top1_acc: 0.8799, top5_acc: 0.9941, mean_class_accuracy: 0.8402 +2025-06-24 17:02:23,937 - pyskl - INFO - Epoch [71][100/1281] lr: 1.379e-02, eta: 6:22:32, time: 0.420, data_time: 0.186, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9988, loss_cls: 0.3717, loss: 0.3717 +2025-06-24 17:02:46,240 - pyskl - INFO - Epoch [71][200/1281] lr: 1.377e-02, eta: 6:22:09, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9994, loss_cls: 0.3525, loss: 0.3525 +2025-06-24 17:03:09,011 - pyskl - INFO - Epoch [71][300/1281] lr: 1.375e-02, eta: 6:21:47, time: 0.228, data_time: 0.001, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9988, loss_cls: 0.3894, loss: 0.3894 +2025-06-24 17:03:31,486 - pyskl - INFO - Epoch [71][400/1281] lr: 1.373e-02, eta: 6:21:25, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 1.0000, loss_cls: 0.3580, loss: 0.3580 +2025-06-24 17:03:53,913 - pyskl - INFO - Epoch [71][500/1281] lr: 1.371e-02, eta: 6:21:02, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9994, loss_cls: 0.4239, loss: 0.4239 +2025-06-24 17:04:16,574 - pyskl - INFO - Epoch [71][600/1281] lr: 1.368e-02, eta: 6:20:40, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9969, loss_cls: 0.3996, loss: 0.3996 +2025-06-24 17:04:38,656 - pyskl - INFO - Epoch [71][700/1281] lr: 1.366e-02, eta: 6:20:17, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9944, loss_cls: 0.4488, loss: 0.4488 +2025-06-24 17:05:01,174 - pyskl - INFO - Epoch [71][800/1281] lr: 1.364e-02, eta: 6:19:55, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9988, loss_cls: 0.3903, loss: 0.3903 +2025-06-24 17:05:23,356 - pyskl - INFO - Epoch [71][900/1281] lr: 1.362e-02, eta: 6:19:32, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9981, loss_cls: 0.4366, loss: 0.4366 +2025-06-24 17:05:45,374 - pyskl - INFO - Epoch [71][1000/1281] lr: 1.360e-02, eta: 6:19:09, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9988, loss_cls: 0.3896, loss: 0.3896 +2025-06-24 17:06:07,640 - pyskl - INFO - Epoch [71][1100/1281] lr: 1.358e-02, eta: 6:18:47, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9994, loss_cls: 0.4347, loss: 0.4347 +2025-06-24 17:06:29,690 - pyskl - INFO - Epoch [71][1200/1281] lr: 1.356e-02, eta: 6:18:24, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9975, loss_cls: 0.3906, loss: 0.3906 +2025-06-24 17:06:48,575 - pyskl - INFO - Saving checkpoint at 71 epochs +2025-06-24 17:07:32,174 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:07:32,229 - pyskl - INFO - +top1_acc 0.8823 +top5_acc 0.9924 +2025-06-24 17:07:32,229 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:07:32,236 - pyskl - INFO - +mean_acc 0.8262 +2025-06-24 17:07:32,238 - pyskl - INFO - Epoch(val) [71][533] top1_acc: 0.8823, top5_acc: 0.9924, mean_class_accuracy: 0.8262 +2025-06-24 17:08:15,617 - pyskl - INFO - Epoch [72][100/1281] lr: 1.353e-02, eta: 6:17:47, time: 0.434, data_time: 0.194, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9988, loss_cls: 0.3497, loss: 0.3497 +2025-06-24 17:08:38,077 - pyskl - INFO - Epoch [72][200/1281] lr: 1.351e-02, eta: 6:17:24, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9994, loss_cls: 0.3639, loss: 0.3639 +2025-06-24 17:09:00,834 - pyskl - INFO - Epoch [72][300/1281] lr: 1.349e-02, eta: 6:17:02, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9981, loss_cls: 0.4071, loss: 0.4071 +2025-06-24 17:09:23,158 - pyskl - INFO - Epoch [72][400/1281] lr: 1.346e-02, eta: 6:16:40, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9988, loss_cls: 0.3448, loss: 0.3448 +2025-06-24 17:09:45,383 - pyskl - INFO - Epoch [72][500/1281] lr: 1.344e-02, eta: 6:16:17, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9994, loss_cls: 0.3719, loss: 0.3719 +2025-06-24 17:10:07,843 - pyskl - INFO - Epoch [72][600/1281] lr: 1.342e-02, eta: 6:15:55, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9994, loss_cls: 0.4540, loss: 0.4540 +2025-06-24 17:10:30,157 - pyskl - INFO - Epoch [72][700/1281] lr: 1.340e-02, eta: 6:15:32, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9994, loss_cls: 0.3367, loss: 0.3367 +2025-06-24 17:10:52,672 - pyskl - INFO - Epoch [72][800/1281] lr: 1.338e-02, eta: 6:15:10, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9981, loss_cls: 0.4222, loss: 0.4222 +2025-06-24 17:11:15,002 - pyskl - INFO - Epoch [72][900/1281] lr: 1.336e-02, eta: 6:14:47, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9988, loss_cls: 0.4180, loss: 0.4180 +2025-06-24 17:11:37,225 - pyskl - INFO - Epoch [72][1000/1281] lr: 1.334e-02, eta: 6:14:25, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9956, loss_cls: 0.3989, loss: 0.3989 +2025-06-24 17:11:59,855 - pyskl - INFO - Epoch [72][1100/1281] lr: 1.332e-02, eta: 6:14:02, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9975, loss_cls: 0.4064, loss: 0.4064 +2025-06-24 17:12:22,115 - pyskl - INFO - Epoch [72][1200/1281] lr: 1.330e-02, eta: 6:13:40, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9969, loss_cls: 0.4119, loss: 0.4119 +2025-06-24 17:12:41,075 - pyskl - INFO - Saving checkpoint at 72 epochs +2025-06-24 17:13:24,681 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:13:24,747 - pyskl - INFO - +top1_acc 0.8906 +top5_acc 0.9954 +2025-06-24 17:13:24,747 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:13:24,754 - pyskl - INFO - +mean_acc 0.8519 +2025-06-24 17:13:24,755 - pyskl - INFO - Epoch(val) [72][533] top1_acc: 0.8906, top5_acc: 0.9954, mean_class_accuracy: 0.8519 +2025-06-24 17:14:06,466 - pyskl - INFO - Epoch [73][100/1281] lr: 1.326e-02, eta: 6:13:00, time: 0.417, data_time: 0.185, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9988, loss_cls: 0.3902, loss: 0.3902 +2025-06-24 17:14:29,420 - pyskl - INFO - Epoch [73][200/1281] lr: 1.324e-02, eta: 6:12:39, time: 0.230, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9988, loss_cls: 0.4227, loss: 0.4227 +2025-06-24 17:14:51,633 - pyskl - INFO - Epoch [73][300/1281] lr: 1.322e-02, eta: 6:12:16, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9962, loss_cls: 0.4228, loss: 0.4228 +2025-06-24 17:15:13,820 - pyskl - INFO - Epoch [73][400/1281] lr: 1.320e-02, eta: 6:11:53, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9994, loss_cls: 0.3828, loss: 0.3828 +2025-06-24 17:15:36,471 - pyskl - INFO - Epoch [73][500/1281] lr: 1.318e-02, eta: 6:11:31, time: 0.226, data_time: 0.001, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9988, loss_cls: 0.3889, loss: 0.3889 +2025-06-24 17:15:58,591 - pyskl - INFO - Epoch [73][600/1281] lr: 1.316e-02, eta: 6:11:08, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9969, loss_cls: 0.4352, loss: 0.4352 +2025-06-24 17:16:21,241 - pyskl - INFO - Epoch [73][700/1281] lr: 1.314e-02, eta: 6:10:46, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9988, loss_cls: 0.4106, loss: 0.4106 +2025-06-24 17:16:43,431 - pyskl - INFO - Epoch [73][800/1281] lr: 1.312e-02, eta: 6:10:23, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 1.0000, loss_cls: 0.3846, loss: 0.3846 +2025-06-24 17:17:05,605 - pyskl - INFO - Epoch [73][900/1281] lr: 1.310e-02, eta: 6:10:01, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9994, loss_cls: 0.3778, loss: 0.3778 +2025-06-24 17:17:28,001 - pyskl - INFO - Epoch [73][1000/1281] lr: 1.308e-02, eta: 6:09:38, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9969, loss_cls: 0.3889, loss: 0.3889 +2025-06-24 17:17:50,178 - pyskl - INFO - Epoch [73][1100/1281] lr: 1.306e-02, eta: 6:09:16, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9969, loss_cls: 0.4918, loss: 0.4918 +2025-06-24 17:18:12,415 - pyskl - INFO - Epoch [73][1200/1281] lr: 1.304e-02, eta: 6:08:53, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9994, loss_cls: 0.4296, loss: 0.4296 +2025-06-24 17:18:31,161 - pyskl - INFO - Saving checkpoint at 73 epochs +2025-06-24 17:19:14,801 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:19:14,856 - pyskl - INFO - +top1_acc 0.8801 +top5_acc 0.9944 +2025-06-24 17:19:14,856 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:19:14,862 - pyskl - INFO - +mean_acc 0.8378 +2025-06-24 17:19:14,864 - pyskl - INFO - Epoch(val) [73][533] top1_acc: 0.8801, top5_acc: 0.9944, mean_class_accuracy: 0.8378 +2025-06-24 17:19:57,625 - pyskl - INFO - Epoch [74][100/1281] lr: 1.300e-02, eta: 6:08:15, time: 0.428, data_time: 0.195, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9988, loss_cls: 0.3400, loss: 0.3400 +2025-06-24 17:20:20,060 - pyskl - INFO - Epoch [74][200/1281] lr: 1.298e-02, eta: 6:07:52, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9994, loss_cls: 0.4058, loss: 0.4058 +2025-06-24 17:20:42,479 - pyskl - INFO - Epoch [74][300/1281] lr: 1.296e-02, eta: 6:07:30, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9988, loss_cls: 0.4219, loss: 0.4219 +2025-06-24 17:21:04,795 - pyskl - INFO - Epoch [74][400/1281] lr: 1.294e-02, eta: 6:07:07, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9988, loss_cls: 0.3496, loss: 0.3496 +2025-06-24 17:21:27,250 - pyskl - INFO - Epoch [74][500/1281] lr: 1.292e-02, eta: 6:06:45, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 0.3385, loss: 0.3385 +2025-06-24 17:21:49,514 - pyskl - INFO - Epoch [74][600/1281] lr: 1.290e-02, eta: 6:06:22, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9981, loss_cls: 0.3930, loss: 0.3930 +2025-06-24 17:22:11,946 - pyskl - INFO - Epoch [74][700/1281] lr: 1.288e-02, eta: 6:06:00, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9975, loss_cls: 0.3655, loss: 0.3655 +2025-06-24 17:22:34,703 - pyskl - INFO - Epoch [74][800/1281] lr: 1.286e-02, eta: 6:05:38, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 1.0000, loss_cls: 0.2999, loss: 0.2999 +2025-06-24 17:22:57,136 - pyskl - INFO - Epoch [74][900/1281] lr: 1.284e-02, eta: 6:05:15, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9988, loss_cls: 0.3983, loss: 0.3983 +2025-06-24 17:23:19,544 - pyskl - INFO - Epoch [74][1000/1281] lr: 1.282e-02, eta: 6:04:53, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9988, loss_cls: 0.4042, loss: 0.4042 +2025-06-24 17:23:41,968 - pyskl - INFO - Epoch [74][1100/1281] lr: 1.280e-02, eta: 6:04:31, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9981, loss_cls: 0.4592, loss: 0.4592 +2025-06-24 17:24:04,417 - pyskl - INFO - Epoch [74][1200/1281] lr: 1.278e-02, eta: 6:04:08, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9975, loss_cls: 0.3993, loss: 0.3993 +2025-06-24 17:24:23,175 - pyskl - INFO - Saving checkpoint at 74 epochs +2025-06-24 17:25:06,615 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:25:06,669 - pyskl - INFO - +top1_acc 0.8515 +top5_acc 0.9912 +2025-06-24 17:25:06,670 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:25:06,677 - pyskl - INFO - +mean_acc 0.8028 +2025-06-24 17:25:06,679 - pyskl - INFO - Epoch(val) [74][533] top1_acc: 0.8515, top5_acc: 0.9912, mean_class_accuracy: 0.8028 +2025-06-24 17:25:49,138 - pyskl - INFO - Epoch [75][100/1281] lr: 1.274e-02, eta: 6:03:30, time: 0.425, data_time: 0.188, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9994, loss_cls: 0.3701, loss: 0.3701 +2025-06-24 17:26:11,347 - pyskl - INFO - Epoch [75][200/1281] lr: 1.272e-02, eta: 6:03:07, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9988, loss_cls: 0.3347, loss: 0.3347 +2025-06-24 17:26:33,306 - pyskl - INFO - Epoch [75][300/1281] lr: 1.270e-02, eta: 6:02:44, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9994, loss_cls: 0.3282, loss: 0.3282 +2025-06-24 17:26:55,949 - pyskl - INFO - Epoch [75][400/1281] lr: 1.268e-02, eta: 6:02:22, time: 0.226, data_time: 0.001, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9994, loss_cls: 0.3671, loss: 0.3671 +2025-06-24 17:27:18,050 - pyskl - INFO - Epoch [75][500/1281] lr: 1.266e-02, eta: 6:01:59, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9988, loss_cls: 0.4015, loss: 0.4015 +2025-06-24 17:27:40,349 - pyskl - INFO - Epoch [75][600/1281] lr: 1.264e-02, eta: 6:01:36, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9969, loss_cls: 0.3989, loss: 0.3989 +2025-06-24 17:28:02,813 - pyskl - INFO - Epoch [75][700/1281] lr: 1.262e-02, eta: 6:01:14, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9988, loss_cls: 0.4112, loss: 0.4112 +2025-06-24 17:28:25,137 - pyskl - INFO - Epoch [75][800/1281] lr: 1.260e-02, eta: 6:00:52, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9981, loss_cls: 0.3155, loss: 0.3155 +2025-06-24 17:28:47,683 - pyskl - INFO - Epoch [75][900/1281] lr: 1.258e-02, eta: 6:00:29, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9988, loss_cls: 0.3510, loss: 0.3510 +2025-06-24 17:29:09,733 - pyskl - INFO - Epoch [75][1000/1281] lr: 1.256e-02, eta: 6:00:06, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9994, loss_cls: 0.3829, loss: 0.3829 +2025-06-24 17:29:31,723 - pyskl - INFO - Epoch [75][1100/1281] lr: 1.254e-02, eta: 5:59:44, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9975, loss_cls: 0.3894, loss: 0.3894 +2025-06-24 17:29:54,028 - pyskl - INFO - Epoch [75][1200/1281] lr: 1.252e-02, eta: 5:59:21, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9962, loss_cls: 0.3928, loss: 0.3928 +2025-06-24 17:30:12,887 - pyskl - INFO - Saving checkpoint at 75 epochs +2025-06-24 17:30:56,579 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:30:56,636 - pyskl - INFO - +top1_acc 0.8783 +top5_acc 0.9927 +2025-06-24 17:30:56,636 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:30:56,643 - pyskl - INFO - +mean_acc 0.8439 +2025-06-24 17:30:56,646 - pyskl - INFO - Epoch(val) [75][533] top1_acc: 0.8783, top5_acc: 0.9927, mean_class_accuracy: 0.8439 +2025-06-24 17:31:38,554 - pyskl - INFO - Epoch [76][100/1281] lr: 1.248e-02, eta: 5:58:42, time: 0.419, data_time: 0.182, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9988, loss_cls: 0.3751, loss: 0.3751 +2025-06-24 17:32:01,078 - pyskl - INFO - Epoch [76][200/1281] lr: 1.246e-02, eta: 5:58:19, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 1.0000, loss_cls: 0.3648, loss: 0.3648 +2025-06-24 17:32:23,027 - pyskl - INFO - Epoch [76][300/1281] lr: 1.244e-02, eta: 5:57:57, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9988, loss_cls: 0.3465, loss: 0.3465 +2025-06-24 17:32:45,559 - pyskl - INFO - Epoch [76][400/1281] lr: 1.242e-02, eta: 5:57:34, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9994, loss_cls: 0.3816, loss: 0.3816 +2025-06-24 17:33:08,052 - pyskl - INFO - Epoch [76][500/1281] lr: 1.240e-02, eta: 5:57:12, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9994, loss_cls: 0.4053, loss: 0.4053 +2025-06-24 17:33:30,151 - pyskl - INFO - Epoch [76][600/1281] lr: 1.238e-02, eta: 5:56:49, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9975, loss_cls: 0.3956, loss: 0.3956 +2025-06-24 17:33:52,978 - pyskl - INFO - Epoch [76][700/1281] lr: 1.236e-02, eta: 5:56:27, time: 0.228, data_time: 0.001, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 0.3305, loss: 0.3305 +2025-06-24 17:34:15,099 - pyskl - INFO - Epoch [76][800/1281] lr: 1.234e-02, eta: 5:56:04, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 1.0000, loss_cls: 0.4020, loss: 0.4020 +2025-06-24 17:34:37,606 - pyskl - INFO - Epoch [76][900/1281] lr: 1.232e-02, eta: 5:55:42, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9969, loss_cls: 0.4089, loss: 0.4089 +2025-06-24 17:35:00,093 - pyskl - INFO - Epoch [76][1000/1281] lr: 1.230e-02, eta: 5:55:20, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9969, loss_cls: 0.4070, loss: 0.4070 +2025-06-24 17:35:22,429 - pyskl - INFO - Epoch [76][1100/1281] lr: 1.228e-02, eta: 5:54:57, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9975, loss_cls: 0.4572, loss: 0.4572 +2025-06-24 17:35:44,686 - pyskl - INFO - Epoch [76][1200/1281] lr: 1.225e-02, eta: 5:54:35, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9969, loss_cls: 0.4055, loss: 0.4055 +2025-06-24 17:36:03,467 - pyskl - INFO - Saving checkpoint at 76 epochs +2025-06-24 17:36:46,906 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:36:46,961 - pyskl - INFO - +top1_acc 0.8831 +top5_acc 0.9935 +2025-06-24 17:36:46,961 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:36:46,968 - pyskl - INFO - +mean_acc 0.8471 +2025-06-24 17:36:46,971 - pyskl - INFO - Epoch(val) [76][533] top1_acc: 0.8831, top5_acc: 0.9935, mean_class_accuracy: 0.8471 +2025-06-24 17:37:29,555 - pyskl - INFO - Epoch [77][100/1281] lr: 1.222e-02, eta: 5:53:56, time: 0.426, data_time: 0.193, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9988, loss_cls: 0.3530, loss: 0.3530 +2025-06-24 17:37:52,089 - pyskl - INFO - Epoch [77][200/1281] lr: 1.220e-02, eta: 5:53:34, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9994, loss_cls: 0.3394, loss: 0.3394 +2025-06-24 17:38:14,727 - pyskl - INFO - Epoch [77][300/1281] lr: 1.218e-02, eta: 5:53:11, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9994, loss_cls: 0.3617, loss: 0.3617 +2025-06-24 17:38:37,002 - pyskl - INFO - Epoch [77][400/1281] lr: 1.216e-02, eta: 5:52:49, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9981, loss_cls: 0.3424, loss: 0.3424 +2025-06-24 17:38:59,367 - pyskl - INFO - Epoch [77][500/1281] lr: 1.214e-02, eta: 5:52:26, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 1.0000, loss_cls: 0.3409, loss: 0.3409 +2025-06-24 17:39:21,513 - pyskl - INFO - Epoch [77][600/1281] lr: 1.212e-02, eta: 5:52:04, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9988, loss_cls: 0.3896, loss: 0.3896 +2025-06-24 17:39:43,837 - pyskl - INFO - Epoch [77][700/1281] lr: 1.210e-02, eta: 5:51:41, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9988, loss_cls: 0.3710, loss: 0.3710 +2025-06-24 17:40:06,153 - pyskl - INFO - Epoch [77][800/1281] lr: 1.207e-02, eta: 5:51:19, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9981, loss_cls: 0.3923, loss: 0.3923 +2025-06-24 17:40:28,256 - pyskl - INFO - Epoch [77][900/1281] lr: 1.205e-02, eta: 5:50:56, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9975, loss_cls: 0.3922, loss: 0.3922 +2025-06-24 17:40:50,590 - pyskl - INFO - Epoch [77][1000/1281] lr: 1.203e-02, eta: 5:50:33, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9956, loss_cls: 0.4410, loss: 0.4410 +2025-06-24 17:41:12,610 - pyskl - INFO - Epoch [77][1100/1281] lr: 1.201e-02, eta: 5:50:11, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9969, loss_cls: 0.4266, loss: 0.4266 +2025-06-24 17:41:35,276 - pyskl - INFO - Epoch [77][1200/1281] lr: 1.199e-02, eta: 5:49:48, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9981, loss_cls: 0.4422, loss: 0.4422 +2025-06-24 17:41:54,213 - pyskl - INFO - Saving checkpoint at 77 epochs +2025-06-24 17:42:38,784 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:42:38,841 - pyskl - INFO - +top1_acc 0.8863 +top5_acc 0.9941 +2025-06-24 17:42:38,841 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:42:38,847 - pyskl - INFO - +mean_acc 0.8443 +2025-06-24 17:42:38,849 - pyskl - INFO - Epoch(val) [77][533] top1_acc: 0.8863, top5_acc: 0.9941, mean_class_accuracy: 0.8443 +2025-06-24 17:43:22,195 - pyskl - INFO - Epoch [78][100/1281] lr: 1.196e-02, eta: 5:49:10, time: 0.433, data_time: 0.194, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9994, loss_cls: 0.3231, loss: 0.3231 +2025-06-24 17:43:44,396 - pyskl - INFO - Epoch [78][200/1281] lr: 1.194e-02, eta: 5:48:48, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 0.2514, loss: 0.2514 +2025-06-24 17:44:06,628 - pyskl - INFO - Epoch [78][300/1281] lr: 1.192e-02, eta: 5:48:25, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2943, loss: 0.2943 +2025-06-24 17:44:28,874 - pyskl - INFO - Epoch [78][400/1281] lr: 1.190e-02, eta: 5:48:02, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9981, loss_cls: 0.3257, loss: 0.3257 +2025-06-24 17:44:50,862 - pyskl - INFO - Epoch [78][500/1281] lr: 1.187e-02, eta: 5:47:40, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 1.0000, loss_cls: 0.3336, loss: 0.3336 +2025-06-24 17:45:13,565 - pyskl - INFO - Epoch [78][600/1281] lr: 1.185e-02, eta: 5:47:17, time: 0.227, data_time: 0.001, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9994, loss_cls: 0.3781, loss: 0.3781 +2025-06-24 17:45:35,756 - pyskl - INFO - Epoch [78][700/1281] lr: 1.183e-02, eta: 5:46:55, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9975, loss_cls: 0.3626, loss: 0.3626 +2025-06-24 17:45:57,968 - pyskl - INFO - Epoch [78][800/1281] lr: 1.181e-02, eta: 5:46:32, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9969, loss_cls: 0.4378, loss: 0.4378 +2025-06-24 17:46:20,408 - pyskl - INFO - Epoch [78][900/1281] lr: 1.179e-02, eta: 5:46:10, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 1.0000, loss_cls: 0.4295, loss: 0.4295 +2025-06-24 17:46:42,553 - pyskl - INFO - Epoch [78][1000/1281] lr: 1.177e-02, eta: 5:45:47, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9994, loss_cls: 0.4191, loss: 0.4191 +2025-06-24 17:47:04,828 - pyskl - INFO - Epoch [78][1100/1281] lr: 1.175e-02, eta: 5:45:25, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9975, loss_cls: 0.3605, loss: 0.3605 +2025-06-24 17:47:27,079 - pyskl - INFO - Epoch [78][1200/1281] lr: 1.173e-02, eta: 5:45:02, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9981, loss_cls: 0.3850, loss: 0.3850 +2025-06-24 17:47:46,023 - pyskl - INFO - Saving checkpoint at 78 epochs +2025-06-24 17:48:29,597 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:48:29,654 - pyskl - INFO - +top1_acc 0.8788 +top5_acc 0.9905 +2025-06-24 17:48:29,654 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:48:29,662 - pyskl - INFO - +mean_acc 0.8291 +2025-06-24 17:48:29,664 - pyskl - INFO - Epoch(val) [78][533] top1_acc: 0.8788, top5_acc: 0.9905, mean_class_accuracy: 0.8291 +2025-06-24 17:49:11,500 - pyskl - INFO - Epoch [79][100/1281] lr: 1.169e-02, eta: 5:44:22, time: 0.418, data_time: 0.185, memory: 4083, top1_acc: 0.9387, top5_acc: 1.0000, loss_cls: 0.3483, loss: 0.3483 +2025-06-24 17:49:34,071 - pyskl - INFO - Epoch [79][200/1281] lr: 1.167e-02, eta: 5:44:00, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 1.0000, loss_cls: 0.3417, loss: 0.3417 +2025-06-24 17:49:56,242 - pyskl - INFO - Epoch [79][300/1281] lr: 1.165e-02, eta: 5:43:38, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9994, loss_cls: 0.3116, loss: 0.3116 +2025-06-24 17:50:18,734 - pyskl - INFO - Epoch [79][400/1281] lr: 1.163e-02, eta: 5:43:15, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 1.0000, loss_cls: 0.3340, loss: 0.3340 +2025-06-24 17:50:40,950 - pyskl - INFO - Epoch [79][500/1281] lr: 1.161e-02, eta: 5:42:53, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 1.0000, loss_cls: 0.3211, loss: 0.3211 +2025-06-24 17:51:03,021 - pyskl - INFO - Epoch [79][600/1281] lr: 1.159e-02, eta: 5:42:30, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9988, loss_cls: 0.3572, loss: 0.3572 +2025-06-24 17:51:25,366 - pyskl - INFO - Epoch [79][700/1281] lr: 1.157e-02, eta: 5:42:07, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9981, loss_cls: 0.3535, loss: 0.3535 +2025-06-24 17:51:47,596 - pyskl - INFO - Epoch [79][800/1281] lr: 1.155e-02, eta: 5:41:45, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9981, loss_cls: 0.3204, loss: 0.3204 +2025-06-24 17:52:09,960 - pyskl - INFO - Epoch [79][900/1281] lr: 1.153e-02, eta: 5:41:22, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9994, loss_cls: 0.3677, loss: 0.3677 +2025-06-24 17:52:32,261 - pyskl - INFO - Epoch [79][1000/1281] lr: 1.151e-02, eta: 5:41:00, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9988, loss_cls: 0.3650, loss: 0.3650 +2025-06-24 17:52:54,707 - pyskl - INFO - Epoch [79][1100/1281] lr: 1.149e-02, eta: 5:40:37, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9994, loss_cls: 0.3377, loss: 0.3377 +2025-06-24 17:53:16,906 - pyskl - INFO - Epoch [79][1200/1281] lr: 1.147e-02, eta: 5:40:15, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9975, loss_cls: 0.3406, loss: 0.3406 +2025-06-24 17:53:35,629 - pyskl - INFO - Saving checkpoint at 79 epochs +2025-06-24 17:54:19,138 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:54:19,212 - pyskl - INFO - +top1_acc 0.8912 +top5_acc 0.9916 +2025-06-24 17:54:19,212 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:54:19,223 - pyskl - INFO - +mean_acc 0.8589 +2025-06-24 17:54:19,226 - pyskl - INFO - Epoch(val) [79][533] top1_acc: 0.8912, top5_acc: 0.9916, mean_class_accuracy: 0.8589 +2025-06-24 17:55:02,652 - pyskl - INFO - Epoch [80][100/1281] lr: 1.143e-02, eta: 5:39:37, time: 0.434, data_time: 0.196, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9994, loss_cls: 0.3183, loss: 0.3183 +2025-06-24 17:55:24,892 - pyskl - INFO - Epoch [80][200/1281] lr: 1.141e-02, eta: 5:39:14, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 0.3234, loss: 0.3234 +2025-06-24 17:55:47,400 - pyskl - INFO - Epoch [80][300/1281] lr: 1.139e-02, eta: 5:38:52, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9981, loss_cls: 0.3664, loss: 0.3664 +2025-06-24 17:56:09,750 - pyskl - INFO - Epoch [80][400/1281] lr: 1.137e-02, eta: 5:38:29, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9994, loss_cls: 0.3682, loss: 0.3682 +2025-06-24 17:56:32,301 - pyskl - INFO - Epoch [80][500/1281] lr: 1.135e-02, eta: 5:38:07, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9988, loss_cls: 0.3668, loss: 0.3668 +2025-06-24 17:56:54,723 - pyskl - INFO - Epoch [80][600/1281] lr: 1.133e-02, eta: 5:37:44, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 0.3486, loss: 0.3486 +2025-06-24 17:57:16,912 - pyskl - INFO - Epoch [80][700/1281] lr: 1.131e-02, eta: 5:37:22, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9981, loss_cls: 0.3782, loss: 0.3782 +2025-06-24 17:57:39,495 - pyskl - INFO - Epoch [80][800/1281] lr: 1.129e-02, eta: 5:36:59, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9994, loss_cls: 0.3739, loss: 0.3739 +2025-06-24 17:58:01,773 - pyskl - INFO - Epoch [80][900/1281] lr: 1.127e-02, eta: 5:36:37, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9988, loss_cls: 0.3520, loss: 0.3520 +2025-06-24 17:58:24,134 - pyskl - INFO - Epoch [80][1000/1281] lr: 1.125e-02, eta: 5:36:14, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9975, loss_cls: 0.3469, loss: 0.3469 +2025-06-24 17:58:46,281 - pyskl - INFO - Epoch [80][1100/1281] lr: 1.123e-02, eta: 5:35:52, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9981, loss_cls: 0.3705, loss: 0.3705 +2025-06-24 17:59:08,613 - pyskl - INFO - Epoch [80][1200/1281] lr: 1.121e-02, eta: 5:35:29, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9956, loss_cls: 0.3650, loss: 0.3650 +2025-06-24 17:59:27,319 - pyskl - INFO - Saving checkpoint at 80 epochs +2025-06-24 18:00:11,702 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:00:11,770 - pyskl - INFO - +top1_acc 0.8998 +top5_acc 0.9926 +2025-06-24 18:00:11,770 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:00:11,781 - pyskl - INFO - +mean_acc 0.8686 +2025-06-24 18:00:11,787 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_69.pth was removed +2025-06-24 18:00:11,986 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_80.pth. +2025-06-24 18:00:11,986 - pyskl - INFO - Best top1_acc is 0.8998 at 80 epoch. +2025-06-24 18:00:11,990 - pyskl - INFO - Epoch(val) [80][533] top1_acc: 0.8998, top5_acc: 0.9926, mean_class_accuracy: 0.8686 +2025-06-24 18:00:54,109 - pyskl - INFO - Epoch [81][100/1281] lr: 1.117e-02, eta: 5:34:50, time: 0.421, data_time: 0.185, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.2864, loss: 0.2864 +2025-06-24 18:01:16,886 - pyskl - INFO - Epoch [81][200/1281] lr: 1.115e-02, eta: 5:34:28, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.2966, loss: 0.2966 +2025-06-24 18:01:39,016 - pyskl - INFO - Epoch [81][300/1281] lr: 1.113e-02, eta: 5:34:05, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9988, loss_cls: 0.3102, loss: 0.3102 +2025-06-24 18:02:01,342 - pyskl - INFO - Epoch [81][400/1281] lr: 1.111e-02, eta: 5:33:43, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9975, loss_cls: 0.3579, loss: 0.3579 +2025-06-24 18:02:23,981 - pyskl - INFO - Epoch [81][500/1281] lr: 1.109e-02, eta: 5:33:20, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9988, loss_cls: 0.3394, loss: 0.3394 +2025-06-24 18:02:46,762 - pyskl - INFO - Epoch [81][600/1281] lr: 1.107e-02, eta: 5:32:58, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9994, loss_cls: 0.3486, loss: 0.3486 +2025-06-24 18:03:09,262 - pyskl - INFO - Epoch [81][700/1281] lr: 1.105e-02, eta: 5:32:36, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9988, loss_cls: 0.3477, loss: 0.3477 +2025-06-24 18:03:31,539 - pyskl - INFO - Epoch [81][800/1281] lr: 1.103e-02, eta: 5:32:13, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9994, loss_cls: 0.3141, loss: 0.3141 +2025-06-24 18:03:54,326 - pyskl - INFO - Epoch [81][900/1281] lr: 1.101e-02, eta: 5:31:51, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9975, loss_cls: 0.3452, loss: 0.3452 +2025-06-24 18:04:16,791 - pyskl - INFO - Epoch [81][1000/1281] lr: 1.099e-02, eta: 5:31:29, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9988, loss_cls: 0.4084, loss: 0.4084 +2025-06-24 18:04:39,208 - pyskl - INFO - Epoch [81][1100/1281] lr: 1.097e-02, eta: 5:31:06, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9969, loss_cls: 0.3882, loss: 0.3882 +2025-06-24 18:05:01,853 - pyskl - INFO - Epoch [81][1200/1281] lr: 1.095e-02, eta: 5:30:44, time: 0.226, data_time: 0.001, memory: 4083, top1_acc: 0.9456, top5_acc: 1.0000, loss_cls: 0.3311, loss: 0.3311 +2025-06-24 18:05:20,530 - pyskl - INFO - Saving checkpoint at 81 epochs +2025-06-24 18:06:04,120 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:06:04,175 - pyskl - INFO - +top1_acc 0.8826 +top5_acc 0.9919 +2025-06-24 18:06:04,175 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:06:04,181 - pyskl - INFO - +mean_acc 0.8606 +2025-06-24 18:06:04,183 - pyskl - INFO - Epoch(val) [81][533] top1_acc: 0.8826, top5_acc: 0.9919, mean_class_accuracy: 0.8606 +2025-06-24 18:06:47,048 - pyskl - INFO - Epoch [82][100/1281] lr: 1.091e-02, eta: 5:30:05, time: 0.429, data_time: 0.194, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9981, loss_cls: 0.3232, loss: 0.3232 +2025-06-24 18:07:09,577 - pyskl - INFO - Epoch [82][200/1281] lr: 1.089e-02, eta: 5:29:43, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9981, loss_cls: 0.2790, loss: 0.2790 +2025-06-24 18:07:31,813 - pyskl - INFO - Epoch [82][300/1281] lr: 1.087e-02, eta: 5:29:20, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9988, loss_cls: 0.3027, loss: 0.3027 +2025-06-24 18:07:54,147 - pyskl - INFO - Epoch [82][400/1281] lr: 1.085e-02, eta: 5:28:58, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9994, loss_cls: 0.3383, loss: 0.3383 +2025-06-24 18:08:16,495 - pyskl - INFO - Epoch [82][500/1281] lr: 1.083e-02, eta: 5:28:35, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9975, loss_cls: 0.3694, loss: 0.3694 +2025-06-24 18:08:38,470 - pyskl - INFO - Epoch [82][600/1281] lr: 1.081e-02, eta: 5:28:13, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9988, loss_cls: 0.3274, loss: 0.3274 +2025-06-24 18:09:00,891 - pyskl - INFO - Epoch [82][700/1281] lr: 1.079e-02, eta: 5:27:50, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 0.3069, loss: 0.3069 +2025-06-24 18:09:22,937 - pyskl - INFO - Epoch [82][800/1281] lr: 1.077e-02, eta: 5:27:27, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9956, loss_cls: 0.3970, loss: 0.3970 +2025-06-24 18:09:44,896 - pyskl - INFO - Epoch [82][900/1281] lr: 1.075e-02, eta: 5:27:05, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9981, loss_cls: 0.3519, loss: 0.3519 +2025-06-24 18:10:06,872 - pyskl - INFO - Epoch [82][1000/1281] lr: 1.073e-02, eta: 5:26:42, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9988, loss_cls: 0.3319, loss: 0.3319 +2025-06-24 18:10:29,274 - pyskl - INFO - Epoch [82][1100/1281] lr: 1.071e-02, eta: 5:26:19, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 1.0000, loss_cls: 0.3901, loss: 0.3901 +2025-06-24 18:10:51,678 - pyskl - INFO - Epoch [82][1200/1281] lr: 1.069e-02, eta: 5:25:57, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9994, loss_cls: 0.3825, loss: 0.3825 +2025-06-24 18:11:10,743 - pyskl - INFO - Saving checkpoint at 82 epochs +2025-06-24 18:11:54,524 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:11:54,599 - pyskl - INFO - +top1_acc 0.8886 +top5_acc 0.9932 +2025-06-24 18:11:54,600 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:11:54,609 - pyskl - INFO - +mean_acc 0.8553 +2025-06-24 18:11:54,611 - pyskl - INFO - Epoch(val) [82][533] top1_acc: 0.8886, top5_acc: 0.9932, mean_class_accuracy: 0.8553 +2025-06-24 18:12:37,705 - pyskl - INFO - Epoch [83][100/1281] lr: 1.065e-02, eta: 5:25:18, time: 0.431, data_time: 0.194, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9981, loss_cls: 0.3169, loss: 0.3169 +2025-06-24 18:13:00,161 - pyskl - INFO - Epoch [83][200/1281] lr: 1.063e-02, eta: 5:24:56, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9988, loss_cls: 0.3034, loss: 0.3034 +2025-06-24 18:13:22,205 - pyskl - INFO - Epoch [83][300/1281] lr: 1.061e-02, eta: 5:24:33, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9988, loss_cls: 0.2868, loss: 0.2868 +2025-06-24 18:13:44,514 - pyskl - INFO - Epoch [83][400/1281] lr: 1.059e-02, eta: 5:24:11, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 1.0000, loss_cls: 0.3052, loss: 0.3052 +2025-06-24 18:14:07,092 - pyskl - INFO - Epoch [83][500/1281] lr: 1.057e-02, eta: 5:23:48, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 1.0000, loss_cls: 0.2996, loss: 0.2996 +2025-06-24 18:14:29,251 - pyskl - INFO - Epoch [83][600/1281] lr: 1.055e-02, eta: 5:23:26, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9988, loss_cls: 0.3539, loss: 0.3539 +2025-06-24 18:14:51,706 - pyskl - INFO - Epoch [83][700/1281] lr: 1.053e-02, eta: 5:23:03, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9975, loss_cls: 0.3405, loss: 0.3405 +2025-06-24 18:15:14,015 - pyskl - INFO - Epoch [83][800/1281] lr: 1.051e-02, eta: 5:22:41, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9988, loss_cls: 0.3373, loss: 0.3373 +2025-06-24 18:15:36,154 - pyskl - INFO - Epoch [83][900/1281] lr: 1.049e-02, eta: 5:22:18, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 0.9975, loss_cls: 0.3206, loss: 0.3206 +2025-06-24 18:15:58,465 - pyskl - INFO - Epoch [83][1000/1281] lr: 1.047e-02, eta: 5:21:55, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9994, loss_cls: 0.3630, loss: 0.3630 +2025-06-24 18:16:20,960 - pyskl - INFO - Epoch [83][1100/1281] lr: 1.045e-02, eta: 5:21:33, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 1.0000, loss_cls: 0.3402, loss: 0.3402 +2025-06-24 18:16:43,188 - pyskl - INFO - Epoch [83][1200/1281] lr: 1.043e-02, eta: 5:21:10, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3209, loss: 0.3209 +2025-06-24 18:17:02,086 - pyskl - INFO - Saving checkpoint at 83 epochs +2025-06-24 18:17:46,518 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:17:46,590 - pyskl - INFO - +top1_acc 0.8943 +top5_acc 0.9940 +2025-06-24 18:17:46,590 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:17:46,598 - pyskl - INFO - +mean_acc 0.8474 +2025-06-24 18:17:46,600 - pyskl - INFO - Epoch(val) [83][533] top1_acc: 0.8943, top5_acc: 0.9940, mean_class_accuracy: 0.8474 +2025-06-24 18:18:29,231 - pyskl - INFO - Epoch [84][100/1281] lr: 1.040e-02, eta: 5:20:31, time: 0.426, data_time: 0.190, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9994, loss_cls: 0.3155, loss: 0.3155 +2025-06-24 18:18:51,493 - pyskl - INFO - Epoch [84][200/1281] lr: 1.038e-02, eta: 5:20:09, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9988, loss_cls: 0.2970, loss: 0.2970 +2025-06-24 18:19:14,285 - pyskl - INFO - Epoch [84][300/1281] lr: 1.036e-02, eta: 5:19:47, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 0.3233, loss: 0.3233 +2025-06-24 18:19:36,799 - pyskl - INFO - Epoch [84][400/1281] lr: 1.034e-02, eta: 5:19:24, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 0.3056, loss: 0.3056 +2025-06-24 18:19:59,150 - pyskl - INFO - Epoch [84][500/1281] lr: 1.031e-02, eta: 5:19:02, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9962, loss_cls: 0.3484, loss: 0.3484 +2025-06-24 18:20:21,512 - pyskl - INFO - Epoch [84][600/1281] lr: 1.029e-02, eta: 5:18:39, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9994, loss_cls: 0.3475, loss: 0.3475 +2025-06-24 18:20:44,026 - pyskl - INFO - Epoch [84][700/1281] lr: 1.027e-02, eta: 5:18:17, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9994, loss_cls: 0.3345, loss: 0.3345 +2025-06-24 18:21:06,201 - pyskl - INFO - Epoch [84][800/1281] lr: 1.025e-02, eta: 5:17:54, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9994, loss_cls: 0.3324, loss: 0.3324 +2025-06-24 18:21:28,406 - pyskl - INFO - Epoch [84][900/1281] lr: 1.023e-02, eta: 5:17:32, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9981, loss_cls: 0.3727, loss: 0.3727 +2025-06-24 18:21:50,697 - pyskl - INFO - Epoch [84][1000/1281] lr: 1.021e-02, eta: 5:17:09, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 1.0000, loss_cls: 0.3219, loss: 0.3219 +2025-06-24 18:22:12,996 - pyskl - INFO - Epoch [84][1100/1281] lr: 1.019e-02, eta: 5:16:47, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9988, loss_cls: 0.3534, loss: 0.3534 +2025-06-24 18:22:35,508 - pyskl - INFO - Epoch [84][1200/1281] lr: 1.017e-02, eta: 5:16:24, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9994, loss_cls: 0.3409, loss: 0.3409 +2025-06-24 18:22:53,947 - pyskl - INFO - Saving checkpoint at 84 epochs +2025-06-24 18:23:37,678 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:23:37,747 - pyskl - INFO - +top1_acc 0.8606 +top5_acc 0.9885 +2025-06-24 18:23:37,748 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:23:37,758 - pyskl - INFO - +mean_acc 0.8305 +2025-06-24 18:23:37,760 - pyskl - INFO - Epoch(val) [84][533] top1_acc: 0.8606, top5_acc: 0.9885, mean_class_accuracy: 0.8305 +2025-06-24 18:24:19,848 - pyskl - INFO - Epoch [85][100/1281] lr: 1.014e-02, eta: 5:15:45, time: 0.421, data_time: 0.185, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9994, loss_cls: 0.3385, loss: 0.3385 +2025-06-24 18:24:42,493 - pyskl - INFO - Epoch [85][200/1281] lr: 1.012e-02, eta: 5:15:23, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9975, loss_cls: 0.3044, loss: 0.3044 +2025-06-24 18:25:04,606 - pyskl - INFO - Epoch [85][300/1281] lr: 1.010e-02, eta: 5:15:00, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 0.2778, loss: 0.2778 +2025-06-24 18:25:26,961 - pyskl - INFO - Epoch [85][400/1281] lr: 1.008e-02, eta: 5:14:37, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 1.0000, loss_cls: 0.3066, loss: 0.3066 +2025-06-24 18:25:49,309 - pyskl - INFO - Epoch [85][500/1281] lr: 1.006e-02, eta: 5:14:15, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.2795, loss: 0.2795 +2025-06-24 18:26:11,299 - pyskl - INFO - Epoch [85][600/1281] lr: 1.004e-02, eta: 5:13:52, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 0.3111, loss: 0.3111 +2025-06-24 18:26:33,675 - pyskl - INFO - Epoch [85][700/1281] lr: 1.002e-02, eta: 5:13:30, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9988, loss_cls: 0.3000, loss: 0.3000 +2025-06-24 18:26:55,853 - pyskl - INFO - Epoch [85][800/1281] lr: 9.998e-03, eta: 5:13:07, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 1.0000, loss_cls: 0.3192, loss: 0.3192 +2025-06-24 18:27:17,945 - pyskl - INFO - Epoch [85][900/1281] lr: 9.978e-03, eta: 5:12:44, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 1.0000, loss_cls: 0.3450, loss: 0.3450 +2025-06-24 18:27:40,440 - pyskl - INFO - Epoch [85][1000/1281] lr: 9.958e-03, eta: 5:12:22, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 1.0000, loss_cls: 0.2972, loss: 0.2972 +2025-06-24 18:28:02,868 - pyskl - INFO - Epoch [85][1100/1281] lr: 9.937e-03, eta: 5:11:59, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 1.0000, loss_cls: 0.3361, loss: 0.3361 +2025-06-24 18:28:25,223 - pyskl - INFO - Epoch [85][1200/1281] lr: 9.917e-03, eta: 5:11:37, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9988, loss_cls: 0.3076, loss: 0.3076 +2025-06-24 18:28:44,301 - pyskl - INFO - Saving checkpoint at 85 epochs +2025-06-24 18:29:28,291 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:29:28,346 - pyskl - INFO - +top1_acc 0.8795 +top5_acc 0.9920 +2025-06-24 18:29:28,346 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:29:28,353 - pyskl - INFO - +mean_acc 0.8530 +2025-06-24 18:29:28,355 - pyskl - INFO - Epoch(val) [85][533] top1_acc: 0.8795, top5_acc: 0.9920, mean_class_accuracy: 0.8530 +2025-06-24 18:30:10,435 - pyskl - INFO - Epoch [86][100/1281] lr: 9.881e-03, eta: 5:10:57, time: 0.421, data_time: 0.187, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9988, loss_cls: 0.2935, loss: 0.2935 +2025-06-24 18:30:32,847 - pyskl - INFO - Epoch [86][200/1281] lr: 9.861e-03, eta: 5:10:35, time: 0.224, data_time: 0.001, memory: 4083, top1_acc: 0.9556, top5_acc: 1.0000, loss_cls: 0.2643, loss: 0.2643 +2025-06-24 18:30:55,358 - pyskl - INFO - Epoch [86][300/1281] lr: 9.841e-03, eta: 5:10:13, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 0.2398, loss: 0.2398 +2025-06-24 18:31:17,650 - pyskl - INFO - Epoch [86][400/1281] lr: 9.821e-03, eta: 5:09:50, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9988, loss_cls: 0.2459, loss: 0.2459 +2025-06-24 18:31:39,958 - pyskl - INFO - Epoch [86][500/1281] lr: 9.801e-03, eta: 5:09:28, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 0.3012, loss: 0.3012 +2025-06-24 18:32:02,095 - pyskl - INFO - Epoch [86][600/1281] lr: 9.781e-03, eta: 5:09:05, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 0.9994, loss_cls: 0.2719, loss: 0.2719 +2025-06-24 18:32:24,246 - pyskl - INFO - Epoch [86][700/1281] lr: 9.762e-03, eta: 5:08:42, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9994, loss_cls: 0.3146, loss: 0.3146 +2025-06-24 18:32:46,526 - pyskl - INFO - Epoch [86][800/1281] lr: 9.742e-03, eta: 5:08:20, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 0.3127, loss: 0.3127 +2025-06-24 18:33:08,964 - pyskl - INFO - Epoch [86][900/1281] lr: 9.722e-03, eta: 5:07:57, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 0.3007, loss: 0.3007 +2025-06-24 18:33:31,341 - pyskl - INFO - Epoch [86][1000/1281] lr: 9.702e-03, eta: 5:07:35, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9994, loss_cls: 0.3360, loss: 0.3360 +2025-06-24 18:33:53,828 - pyskl - INFO - Epoch [86][1100/1281] lr: 9.682e-03, eta: 5:07:12, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9988, loss_cls: 0.2930, loss: 0.2930 +2025-06-24 18:34:16,363 - pyskl - INFO - Epoch [86][1200/1281] lr: 9.662e-03, eta: 5:06:50, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9975, loss_cls: 0.3329, loss: 0.3329 +2025-06-24 18:34:35,100 - pyskl - INFO - Saving checkpoint at 86 epochs +2025-06-24 18:35:19,202 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:35:19,260 - pyskl - INFO - +top1_acc 0.8943 +top5_acc 0.9950 +2025-06-24 18:35:19,260 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:35:19,269 - pyskl - INFO - +mean_acc 0.8524 +2025-06-24 18:35:19,271 - pyskl - INFO - Epoch(val) [86][533] top1_acc: 0.8943, top5_acc: 0.9950, mean_class_accuracy: 0.8524 +2025-06-24 18:36:02,466 - pyskl - INFO - Epoch [87][100/1281] lr: 9.626e-03, eta: 5:06:11, time: 0.432, data_time: 0.195, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2601, loss: 0.2601 +2025-06-24 18:36:25,202 - pyskl - INFO - Epoch [87][200/1281] lr: 9.606e-03, eta: 5:05:49, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2548, loss: 0.2548 +2025-06-24 18:36:47,364 - pyskl - INFO - Epoch [87][300/1281] lr: 9.586e-03, eta: 5:05:27, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 0.2188, loss: 0.2188 +2025-06-24 18:37:09,702 - pyskl - INFO - Epoch [87][400/1281] lr: 9.566e-03, eta: 5:05:04, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 0.9994, loss_cls: 0.2312, loss: 0.2312 +2025-06-24 18:37:31,783 - pyskl - INFO - Epoch [87][500/1281] lr: 9.546e-03, eta: 5:04:41, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9988, loss_cls: 0.3089, loss: 0.3089 +2025-06-24 18:37:54,021 - pyskl - INFO - Epoch [87][600/1281] lr: 9.527e-03, eta: 5:04:19, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9981, loss_cls: 0.2813, loss: 0.2813 +2025-06-24 18:38:16,536 - pyskl - INFO - Epoch [87][700/1281] lr: 9.507e-03, eta: 5:03:56, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9994, loss_cls: 0.3110, loss: 0.3110 +2025-06-24 18:38:38,811 - pyskl - INFO - Epoch [87][800/1281] lr: 9.487e-03, eta: 5:03:34, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 0.2982, loss: 0.2982 +2025-06-24 18:39:01,156 - pyskl - INFO - Epoch [87][900/1281] lr: 9.467e-03, eta: 5:03:11, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 1.0000, loss_cls: 0.3627, loss: 0.3627 +2025-06-24 18:39:23,588 - pyskl - INFO - Epoch [87][1000/1281] lr: 9.447e-03, eta: 5:02:49, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9988, loss_cls: 0.3044, loss: 0.3044 +2025-06-24 18:39:45,876 - pyskl - INFO - Epoch [87][1100/1281] lr: 9.427e-03, eta: 5:02:26, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 0.2917, loss: 0.2917 +2025-06-24 18:40:08,373 - pyskl - INFO - Epoch [87][1200/1281] lr: 9.408e-03, eta: 5:02:04, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 1.0000, loss_cls: 0.3389, loss: 0.3389 +2025-06-24 18:40:27,362 - pyskl - INFO - Saving checkpoint at 87 epochs +2025-06-24 18:41:11,513 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:41:11,570 - pyskl - INFO - +top1_acc 0.9022 +top5_acc 0.9946 +2025-06-24 18:41:11,571 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:41:11,577 - pyskl - INFO - +mean_acc 0.8732 +2025-06-24 18:41:11,581 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_80.pth was removed +2025-06-24 18:41:11,748 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_87.pth. +2025-06-24 18:41:11,749 - pyskl - INFO - Best top1_acc is 0.9022 at 87 epoch. +2025-06-24 18:41:11,751 - pyskl - INFO - Epoch(val) [87][533] top1_acc: 0.9022, top5_acc: 0.9946, mean_class_accuracy: 0.8732 +2025-06-24 18:41:53,996 - pyskl - INFO - Epoch [88][100/1281] lr: 9.372e-03, eta: 5:01:24, time: 0.422, data_time: 0.187, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9994, loss_cls: 0.2401, loss: 0.2401 +2025-06-24 18:42:17,013 - pyskl - INFO - Epoch [88][200/1281] lr: 9.352e-03, eta: 5:01:02, time: 0.230, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9981, loss_cls: 0.2940, loss: 0.2940 +2025-06-24 18:42:39,193 - pyskl - INFO - Epoch [88][300/1281] lr: 9.332e-03, eta: 5:00:40, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9981, loss_cls: 0.2724, loss: 0.2724 +2025-06-24 18:43:01,459 - pyskl - INFO - Epoch [88][400/1281] lr: 9.312e-03, eta: 5:00:17, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9988, loss_cls: 0.3087, loss: 0.3087 +2025-06-24 18:43:23,796 - pyskl - INFO - Epoch [88][500/1281] lr: 9.293e-03, eta: 4:59:55, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 0.2706, loss: 0.2706 +2025-06-24 18:43:45,895 - pyskl - INFO - Epoch [88][600/1281] lr: 9.273e-03, eta: 4:59:32, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 0.2591, loss: 0.2591 +2025-06-24 18:44:07,885 - pyskl - INFO - Epoch [88][700/1281] lr: 9.253e-03, eta: 4:59:09, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9981, loss_cls: 0.2688, loss: 0.2688 +2025-06-24 18:44:30,359 - pyskl - INFO - Epoch [88][800/1281] lr: 9.233e-03, eta: 4:58:47, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2826, loss: 0.2826 +2025-06-24 18:44:52,505 - pyskl - INFO - Epoch [88][900/1281] lr: 9.214e-03, eta: 4:58:24, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9988, loss_cls: 0.2712, loss: 0.2712 +2025-06-24 18:45:14,934 - pyskl - INFO - Epoch [88][1000/1281] lr: 9.194e-03, eta: 4:58:02, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9988, loss_cls: 0.3316, loss: 0.3316 +2025-06-24 18:45:37,233 - pyskl - INFO - Epoch [88][1100/1281] lr: 9.174e-03, eta: 4:57:39, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9988, loss_cls: 0.2834, loss: 0.2834 +2025-06-24 18:45:59,478 - pyskl - INFO - Epoch [88][1200/1281] lr: 9.155e-03, eta: 4:57:17, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9994, loss_cls: 0.3364, loss: 0.3364 +2025-06-24 18:46:18,486 - pyskl - INFO - Saving checkpoint at 88 epochs +2025-06-24 18:47:02,261 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:47:02,317 - pyskl - INFO - +top1_acc 0.8760 +top5_acc 0.9891 +2025-06-24 18:47:02,317 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:47:02,324 - pyskl - INFO - +mean_acc 0.8528 +2025-06-24 18:47:02,326 - pyskl - INFO - Epoch(val) [88][533] top1_acc: 0.8760, top5_acc: 0.9891, mean_class_accuracy: 0.8528 +2025-06-24 18:47:44,073 - pyskl - INFO - Epoch [89][100/1281] lr: 9.119e-03, eta: 4:56:37, time: 0.417, data_time: 0.184, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2428, loss: 0.2428 +2025-06-24 18:48:06,857 - pyskl - INFO - Epoch [89][200/1281] lr: 9.099e-03, eta: 4:56:15, time: 0.228, data_time: 0.001, memory: 4083, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 0.2213, loss: 0.2213 +2025-06-24 18:48:28,958 - pyskl - INFO - Epoch [89][300/1281] lr: 9.080e-03, eta: 4:55:52, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.2829, loss: 0.2829 +2025-06-24 18:48:51,314 - pyskl - INFO - Epoch [89][400/1281] lr: 9.060e-03, eta: 4:55:30, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9988, loss_cls: 0.2846, loss: 0.2846 +2025-06-24 18:49:13,595 - pyskl - INFO - Epoch [89][500/1281] lr: 9.040e-03, eta: 4:55:07, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2674, loss: 0.2674 +2025-06-24 18:49:36,032 - pyskl - INFO - Epoch [89][600/1281] lr: 9.021e-03, eta: 4:54:45, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 0.3016, loss: 0.3016 +2025-06-24 18:49:58,384 - pyskl - INFO - Epoch [89][700/1281] lr: 9.001e-03, eta: 4:54:22, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9988, loss_cls: 0.3380, loss: 0.3380 +2025-06-24 18:50:20,741 - pyskl - INFO - Epoch [89][800/1281] lr: 8.982e-03, eta: 4:54:00, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9988, loss_cls: 0.3364, loss: 0.3364 +2025-06-24 18:50:43,249 - pyskl - INFO - Epoch [89][900/1281] lr: 8.962e-03, eta: 4:53:37, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9994, loss_cls: 0.3221, loss: 0.3221 +2025-06-24 18:51:05,333 - pyskl - INFO - Epoch [89][1000/1281] lr: 8.942e-03, eta: 4:53:15, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 1.0000, loss_cls: 0.3098, loss: 0.3098 +2025-06-24 18:51:27,743 - pyskl - INFO - Epoch [89][1100/1281] lr: 8.923e-03, eta: 4:52:52, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 1.0000, loss_cls: 0.3161, loss: 0.3161 +2025-06-24 18:51:50,070 - pyskl - INFO - Epoch [89][1200/1281] lr: 8.903e-03, eta: 4:52:30, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9988, loss_cls: 0.3126, loss: 0.3126 +2025-06-24 18:52:08,954 - pyskl - INFO - Saving checkpoint at 89 epochs +2025-06-24 18:52:52,771 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:52:52,826 - pyskl - INFO - +top1_acc 0.8749 +top5_acc 0.9920 +2025-06-24 18:52:52,826 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:52:52,833 - pyskl - INFO - +mean_acc 0.8486 +2025-06-24 18:52:52,835 - pyskl - INFO - Epoch(val) [89][533] top1_acc: 0.8749, top5_acc: 0.9920, mean_class_accuracy: 0.8486 +2025-06-24 18:53:35,265 - pyskl - INFO - Epoch [90][100/1281] lr: 8.868e-03, eta: 4:51:50, time: 0.424, data_time: 0.186, memory: 4083, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 0.2415, loss: 0.2415 +2025-06-24 18:53:57,774 - pyskl - INFO - Epoch [90][200/1281] lr: 8.848e-03, eta: 4:51:28, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9988, loss_cls: 0.2665, loss: 0.2665 +2025-06-24 18:54:20,034 - pyskl - INFO - Epoch [90][300/1281] lr: 8.829e-03, eta: 4:51:05, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 1.0000, loss_cls: 0.3152, loss: 0.3152 +2025-06-24 18:54:42,533 - pyskl - INFO - Epoch [90][400/1281] lr: 8.809e-03, eta: 4:50:43, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9981, loss_cls: 0.3267, loss: 0.3267 +2025-06-24 18:55:04,800 - pyskl - INFO - Epoch [90][500/1281] lr: 8.790e-03, eta: 4:50:20, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9988, loss_cls: 0.2843, loss: 0.2843 +2025-06-24 18:55:27,271 - pyskl - INFO - Epoch [90][600/1281] lr: 8.770e-03, eta: 4:49:58, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.2785, loss: 0.2785 +2025-06-24 18:55:49,570 - pyskl - INFO - Epoch [90][700/1281] lr: 8.751e-03, eta: 4:49:35, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2701, loss: 0.2701 +2025-06-24 18:56:11,980 - pyskl - INFO - Epoch [90][800/1281] lr: 8.731e-03, eta: 4:49:13, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 1.0000, loss_cls: 0.3259, loss: 0.3259 +2025-06-24 18:56:34,623 - pyskl - INFO - Epoch [90][900/1281] lr: 8.712e-03, eta: 4:48:51, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 1.0000, loss_cls: 0.2937, loss: 0.2937 +2025-06-24 18:56:56,908 - pyskl - INFO - Epoch [90][1000/1281] lr: 8.692e-03, eta: 4:48:28, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2616, loss: 0.2616 +2025-06-24 18:57:19,185 - pyskl - INFO - Epoch [90][1100/1281] lr: 8.673e-03, eta: 4:48:05, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9988, loss_cls: 0.2808, loss: 0.2808 +2025-06-24 18:57:41,706 - pyskl - INFO - Epoch [90][1200/1281] lr: 8.653e-03, eta: 4:47:43, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9994, loss_cls: 0.2583, loss: 0.2583 +2025-06-24 18:58:00,792 - pyskl - INFO - Saving checkpoint at 90 epochs +2025-06-24 18:58:44,500 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:58:44,567 - pyskl - INFO - +top1_acc 0.8958 +top5_acc 0.9933 +2025-06-24 18:58:44,568 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:58:44,582 - pyskl - INFO - +mean_acc 0.8621 +2025-06-24 18:58:44,585 - pyskl - INFO - Epoch(val) [90][533] top1_acc: 0.8958, top5_acc: 0.9933, mean_class_accuracy: 0.8621 +2025-06-24 18:59:27,083 - pyskl - INFO - Epoch [91][100/1281] lr: 8.618e-03, eta: 4:47:04, time: 0.425, data_time: 0.191, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2545, loss: 0.2545 +2025-06-24 18:59:49,483 - pyskl - INFO - Epoch [91][200/1281] lr: 8.599e-03, eta: 4:46:41, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 0.2459, loss: 0.2459 +2025-06-24 19:00:11,586 - pyskl - INFO - Epoch [91][300/1281] lr: 8.579e-03, eta: 4:46:19, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 0.9994, loss_cls: 0.2654, loss: 0.2654 +2025-06-24 19:00:34,048 - pyskl - INFO - Epoch [91][400/1281] lr: 8.560e-03, eta: 4:45:56, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 0.2385, loss: 0.2385 +2025-06-24 19:00:56,438 - pyskl - INFO - Epoch [91][500/1281] lr: 8.540e-03, eta: 4:45:34, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2274, loss: 0.2274 +2025-06-24 19:01:18,494 - pyskl - INFO - Epoch [91][600/1281] lr: 8.521e-03, eta: 4:45:11, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2782, loss: 0.2782 +2025-06-24 19:01:40,816 - pyskl - INFO - Epoch [91][700/1281] lr: 8.502e-03, eta: 4:44:49, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 1.0000, loss_cls: 0.2945, loss: 0.2945 +2025-06-24 19:02:03,261 - pyskl - INFO - Epoch [91][800/1281] lr: 8.482e-03, eta: 4:44:26, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 1.0000, loss_cls: 0.3003, loss: 0.3003 +2025-06-24 19:02:25,890 - pyskl - INFO - Epoch [91][900/1281] lr: 8.463e-03, eta: 4:44:04, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9981, loss_cls: 0.3041, loss: 0.3041 +2025-06-24 19:02:48,626 - pyskl - INFO - Epoch [91][1000/1281] lr: 8.444e-03, eta: 4:43:42, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.2830, loss: 0.2830 +2025-06-24 19:03:11,039 - pyskl - INFO - Epoch [91][1100/1281] lr: 8.424e-03, eta: 4:43:19, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 1.0000, loss_cls: 0.2659, loss: 0.2659 +2025-06-24 19:03:33,261 - pyskl - INFO - Epoch [91][1200/1281] lr: 8.405e-03, eta: 4:42:56, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9988, loss_cls: 0.2800, loss: 0.2800 +2025-06-24 19:03:52,535 - pyskl - INFO - Saving checkpoint at 91 epochs +2025-06-24 19:04:36,460 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:04:36,519 - pyskl - INFO - +top1_acc 0.8947 +top5_acc 0.9926 +2025-06-24 19:04:36,519 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:04:36,526 - pyskl - INFO - +mean_acc 0.8674 +2025-06-24 19:04:36,528 - pyskl - INFO - Epoch(val) [91][533] top1_acc: 0.8947, top5_acc: 0.9926, mean_class_accuracy: 0.8674 +2025-06-24 19:05:19,170 - pyskl - INFO - Epoch [92][100/1281] lr: 8.370e-03, eta: 4:42:17, time: 0.426, data_time: 0.191, memory: 4083, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 0.2614, loss: 0.2614 +2025-06-24 19:05:41,587 - pyskl - INFO - Epoch [92][200/1281] lr: 8.351e-03, eta: 4:41:55, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2132, loss: 0.2132 +2025-06-24 19:06:04,173 - pyskl - INFO - Epoch [92][300/1281] lr: 8.332e-03, eta: 4:41:32, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 0.2425, loss: 0.2425 +2025-06-24 19:06:26,407 - pyskl - INFO - Epoch [92][400/1281] lr: 8.312e-03, eta: 4:41:10, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.2823, loss: 0.2823 +2025-06-24 19:06:49,108 - pyskl - INFO - Epoch [92][500/1281] lr: 8.293e-03, eta: 4:40:48, time: 0.227, data_time: 0.001, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9988, loss_cls: 0.2808, loss: 0.2808 +2025-06-24 19:07:11,654 - pyskl - INFO - Epoch [92][600/1281] lr: 8.274e-03, eta: 4:40:25, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9988, loss_cls: 0.2798, loss: 0.2798 +2025-06-24 19:07:34,018 - pyskl - INFO - Epoch [92][700/1281] lr: 8.255e-03, eta: 4:40:03, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2556, loss: 0.2556 +2025-06-24 19:07:56,505 - pyskl - INFO - Epoch [92][800/1281] lr: 8.235e-03, eta: 4:39:40, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 0.2207, loss: 0.2207 +2025-06-24 19:08:18,984 - pyskl - INFO - Epoch [92][900/1281] lr: 8.216e-03, eta: 4:39:18, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2439, loss: 0.2439 +2025-06-24 19:08:41,300 - pyskl - INFO - Epoch [92][1000/1281] lr: 8.197e-03, eta: 4:38:55, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 0.2742, loss: 0.2742 +2025-06-24 19:09:03,839 - pyskl - INFO - Epoch [92][1100/1281] lr: 8.178e-03, eta: 4:38:33, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2747, loss: 0.2747 +2025-06-24 19:09:26,290 - pyskl - INFO - Epoch [92][1200/1281] lr: 8.159e-03, eta: 4:38:11, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2748, loss: 0.2748 +2025-06-24 19:09:45,329 - pyskl - INFO - Saving checkpoint at 92 epochs +2025-06-24 19:10:28,590 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:10:28,645 - pyskl - INFO - +top1_acc 0.8979 +top5_acc 0.9938 +2025-06-24 19:10:28,645 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:10:28,652 - pyskl - INFO - +mean_acc 0.8622 +2025-06-24 19:10:28,653 - pyskl - INFO - Epoch(val) [92][533] top1_acc: 0.8979, top5_acc: 0.9938, mean_class_accuracy: 0.8622 +2025-06-24 19:11:11,701 - pyskl - INFO - Epoch [93][100/1281] lr: 8.124e-03, eta: 4:37:31, time: 0.430, data_time: 0.191, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9975, loss_cls: 0.2921, loss: 0.2921 +2025-06-24 19:11:34,306 - pyskl - INFO - Epoch [93][200/1281] lr: 8.105e-03, eta: 4:37:09, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 0.2180, loss: 0.2180 +2025-06-24 19:11:56,524 - pyskl - INFO - Epoch [93][300/1281] lr: 8.086e-03, eta: 4:36:46, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 0.9988, loss_cls: 0.2376, loss: 0.2376 +2025-06-24 19:12:18,951 - pyskl - INFO - Epoch [93][400/1281] lr: 8.067e-03, eta: 4:36:24, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2450, loss: 0.2450 +2025-06-24 19:12:41,110 - pyskl - INFO - Epoch [93][500/1281] lr: 8.047e-03, eta: 4:36:01, time: 0.222, data_time: 0.001, memory: 4083, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 0.2317, loss: 0.2317 +2025-06-24 19:13:03,494 - pyskl - INFO - Epoch [93][600/1281] lr: 8.028e-03, eta: 4:35:39, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 1.0000, loss_cls: 0.2589, loss: 0.2589 +2025-06-24 19:13:25,838 - pyskl - INFO - Epoch [93][700/1281] lr: 8.009e-03, eta: 4:35:16, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9988, loss_cls: 0.2475, loss: 0.2475 +2025-06-24 19:13:48,113 - pyskl - INFO - Epoch [93][800/1281] lr: 7.990e-03, eta: 4:34:54, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9994, loss_cls: 0.3119, loss: 0.3119 +2025-06-24 19:14:10,471 - pyskl - INFO - Epoch [93][900/1281] lr: 7.971e-03, eta: 4:34:31, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 0.3091, loss: 0.3091 +2025-06-24 19:14:32,853 - pyskl - INFO - Epoch [93][1000/1281] lr: 7.952e-03, eta: 4:34:09, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9994, loss_cls: 0.3010, loss: 0.3010 +2025-06-24 19:14:55,109 - pyskl - INFO - Epoch [93][1100/1281] lr: 7.933e-03, eta: 4:33:46, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9975, loss_cls: 0.3025, loss: 0.3025 +2025-06-24 19:15:17,606 - pyskl - INFO - Epoch [93][1200/1281] lr: 7.914e-03, eta: 4:33:24, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9981, loss_cls: 0.2743, loss: 0.2743 +2025-06-24 19:15:36,517 - pyskl - INFO - Saving checkpoint at 93 epochs +2025-06-24 19:16:19,903 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:16:19,966 - pyskl - INFO - +top1_acc 0.8871 +top5_acc 0.9933 +2025-06-24 19:16:19,966 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:16:19,974 - pyskl - INFO - +mean_acc 0.8465 +2025-06-24 19:16:19,976 - pyskl - INFO - Epoch(val) [93][533] top1_acc: 0.8871, top5_acc: 0.9933, mean_class_accuracy: 0.8465 +2025-06-24 19:17:01,780 - pyskl - INFO - Epoch [94][100/1281] lr: 7.880e-03, eta: 4:32:44, time: 0.418, data_time: 0.186, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 0.2565, loss: 0.2565 +2025-06-24 19:17:24,456 - pyskl - INFO - Epoch [94][200/1281] lr: 7.861e-03, eta: 4:32:22, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.2256, loss: 0.2256 +2025-06-24 19:17:46,814 - pyskl - INFO - Epoch [94][300/1281] lr: 7.842e-03, eta: 4:31:59, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 0.9994, loss_cls: 0.2211, loss: 0.2211 +2025-06-24 19:18:09,325 - pyskl - INFO - Epoch [94][400/1281] lr: 7.823e-03, eta: 4:31:37, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 0.2742, loss: 0.2742 +2025-06-24 19:18:31,604 - pyskl - INFO - Epoch [94][500/1281] lr: 7.804e-03, eta: 4:31:14, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 0.2667, loss: 0.2667 +2025-06-24 19:18:53,756 - pyskl - INFO - Epoch [94][600/1281] lr: 7.785e-03, eta: 4:30:52, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 0.2857, loss: 0.2857 +2025-06-24 19:19:16,163 - pyskl - INFO - Epoch [94][700/1281] lr: 7.766e-03, eta: 4:30:29, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.2733, loss: 0.2733 +2025-06-24 19:19:38,419 - pyskl - INFO - Epoch [94][800/1281] lr: 7.747e-03, eta: 4:30:07, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9988, loss_cls: 0.2730, loss: 0.2730 +2025-06-24 19:20:00,688 - pyskl - INFO - Epoch [94][900/1281] lr: 7.728e-03, eta: 4:29:44, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 1.0000, loss_cls: 0.2856, loss: 0.2856 +2025-06-24 19:20:23,122 - pyskl - INFO - Epoch [94][1000/1281] lr: 7.709e-03, eta: 4:29:22, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 1.0000, loss_cls: 0.3076, loss: 0.3076 +2025-06-24 19:20:45,537 - pyskl - INFO - Epoch [94][1100/1281] lr: 7.690e-03, eta: 4:28:59, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 0.9988, loss_cls: 0.2480, loss: 0.2480 +2025-06-24 19:21:08,274 - pyskl - INFO - Epoch [94][1200/1281] lr: 7.672e-03, eta: 4:28:37, time: 0.227, data_time: 0.001, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2469, loss: 0.2469 +2025-06-24 19:21:26,996 - pyskl - INFO - Saving checkpoint at 94 epochs +2025-06-24 19:22:10,691 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:22:10,748 - pyskl - INFO - +top1_acc 0.8978 +top5_acc 0.9957 +2025-06-24 19:22:10,748 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:22:10,755 - pyskl - INFO - +mean_acc 0.8610 +2025-06-24 19:22:10,757 - pyskl - INFO - Epoch(val) [94][533] top1_acc: 0.8978, top5_acc: 0.9957, mean_class_accuracy: 0.8610 +2025-06-24 19:22:52,647 - pyskl - INFO - Epoch [95][100/1281] lr: 7.637e-03, eta: 4:27:57, time: 0.419, data_time: 0.186, memory: 4083, top1_acc: 0.9500, top5_acc: 1.0000, loss_cls: 0.2776, loss: 0.2776 +2025-06-24 19:23:15,012 - pyskl - INFO - Epoch [95][200/1281] lr: 7.619e-03, eta: 4:27:35, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 0.9994, loss_cls: 0.2154, loss: 0.2154 +2025-06-24 19:23:37,343 - pyskl - INFO - Epoch [95][300/1281] lr: 7.600e-03, eta: 4:27:12, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 0.9994, loss_cls: 0.1974, loss: 0.1974 +2025-06-24 19:23:59,859 - pyskl - INFO - Epoch [95][400/1281] lr: 7.581e-03, eta: 4:26:50, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2311, loss: 0.2311 +2025-06-24 19:24:22,260 - pyskl - INFO - Epoch [95][500/1281] lr: 7.562e-03, eta: 4:26:27, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 0.2355, loss: 0.2355 +2025-06-24 19:24:44,626 - pyskl - INFO - Epoch [95][600/1281] lr: 7.543e-03, eta: 4:26:05, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9988, loss_cls: 0.2459, loss: 0.2459 +2025-06-24 19:25:06,942 - pyskl - INFO - Epoch [95][700/1281] lr: 7.525e-03, eta: 4:25:42, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 0.2320, loss: 0.2320 +2025-06-24 19:25:29,220 - pyskl - INFO - Epoch [95][800/1281] lr: 7.506e-03, eta: 4:25:20, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 0.2168, loss: 0.2168 +2025-06-24 19:25:51,859 - pyskl - INFO - Epoch [95][900/1281] lr: 7.487e-03, eta: 4:24:57, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2350, loss: 0.2350 +2025-06-24 19:26:14,588 - pyskl - INFO - Epoch [95][1000/1281] lr: 7.468e-03, eta: 4:24:35, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9988, loss_cls: 0.2770, loss: 0.2770 +2025-06-24 19:26:37,172 - pyskl - INFO - Epoch [95][1100/1281] lr: 7.450e-03, eta: 4:24:13, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.2813, loss: 0.2813 +2025-06-24 19:26:59,255 - pyskl - INFO - Epoch [95][1200/1281] lr: 7.431e-03, eta: 4:23:50, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 0.9994, loss_cls: 0.2202, loss: 0.2202 +2025-06-24 19:27:18,023 - pyskl - INFO - Saving checkpoint at 95 epochs +2025-06-24 19:28:02,064 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:28:02,145 - pyskl - INFO - +top1_acc 0.9114 +top5_acc 0.9946 +2025-06-24 19:28:02,145 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:28:02,153 - pyskl - INFO - +mean_acc 0.8755 +2025-06-24 19:28:02,157 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_87.pth was removed +2025-06-24 19:28:02,367 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_95.pth. +2025-06-24 19:28:02,368 - pyskl - INFO - Best top1_acc is 0.9114 at 95 epoch. +2025-06-24 19:28:02,370 - pyskl - INFO - Epoch(val) [95][533] top1_acc: 0.9114, top5_acc: 0.9946, mean_class_accuracy: 0.8755 +2025-06-24 19:28:44,604 - pyskl - INFO - Epoch [96][100/1281] lr: 7.397e-03, eta: 4:23:10, time: 0.422, data_time: 0.188, memory: 4083, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 0.2031, loss: 0.2031 +2025-06-24 19:29:06,921 - pyskl - INFO - Epoch [96][200/1281] lr: 7.379e-03, eta: 4:22:48, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 0.2430, loss: 0.2430 +2025-06-24 19:29:29,602 - pyskl - INFO - Epoch [96][300/1281] lr: 7.360e-03, eta: 4:22:26, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 0.2195, loss: 0.2195 +2025-06-24 19:29:51,953 - pyskl - INFO - Epoch [96][400/1281] lr: 7.341e-03, eta: 4:22:03, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 0.9988, loss_cls: 0.2345, loss: 0.2345 +2025-06-24 19:30:14,160 - pyskl - INFO - Epoch [96][500/1281] lr: 7.323e-03, eta: 4:21:40, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 0.2834, loss: 0.2834 +2025-06-24 19:30:36,713 - pyskl - INFO - Epoch [96][600/1281] lr: 7.304e-03, eta: 4:21:18, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 0.2421, loss: 0.2421 +2025-06-24 19:30:59,219 - pyskl - INFO - Epoch [96][700/1281] lr: 7.286e-03, eta: 4:20:56, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 0.2451, loss: 0.2451 +2025-06-24 19:31:21,312 - pyskl - INFO - Epoch [96][800/1281] lr: 7.267e-03, eta: 4:20:33, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 0.2262, loss: 0.2262 +2025-06-24 19:31:43,832 - pyskl - INFO - Epoch [96][900/1281] lr: 7.249e-03, eta: 4:20:11, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 0.9994, loss_cls: 0.2096, loss: 0.2096 +2025-06-24 19:32:06,150 - pyskl - INFO - Epoch [96][1000/1281] lr: 7.230e-03, eta: 4:19:48, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.1939, loss: 0.1939 +2025-06-24 19:32:28,707 - pyskl - INFO - Epoch [96][1100/1281] lr: 7.211e-03, eta: 4:19:26, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1939, loss: 0.1939 +2025-06-24 19:32:51,156 - pyskl - INFO - Epoch [96][1200/1281] lr: 7.193e-03, eta: 4:19:03, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9988, loss_cls: 0.2488, loss: 0.2488 +2025-06-24 19:33:10,161 - pyskl - INFO - Saving checkpoint at 96 epochs +2025-06-24 19:33:54,218 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:33:54,279 - pyskl - INFO - +top1_acc 0.9060 +top5_acc 0.9951 +2025-06-24 19:33:54,279 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:33:54,286 - pyskl - INFO - +mean_acc 0.8729 +2025-06-24 19:33:54,289 - pyskl - INFO - Epoch(val) [96][533] top1_acc: 0.9060, top5_acc: 0.9951, mean_class_accuracy: 0.8729 +2025-06-24 19:34:36,712 - pyskl - INFO - Epoch [97][100/1281] lr: 7.159e-03, eta: 4:18:24, time: 0.424, data_time: 0.192, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2068, loss: 0.2068 +2025-06-24 19:34:59,433 - pyskl - INFO - Epoch [97][200/1281] lr: 7.141e-03, eta: 4:18:01, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 0.9994, loss_cls: 0.1890, loss: 0.1890 +2025-06-24 19:35:21,653 - pyskl - INFO - Epoch [97][300/1281] lr: 7.123e-03, eta: 4:17:39, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2277, loss: 0.2277 +2025-06-24 19:35:44,268 - pyskl - INFO - Epoch [97][400/1281] lr: 7.104e-03, eta: 4:17:16, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.2217, loss: 0.2217 +2025-06-24 19:36:06,548 - pyskl - INFO - Epoch [97][500/1281] lr: 7.086e-03, eta: 4:16:54, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 0.2592, loss: 0.2592 +2025-06-24 19:36:28,799 - pyskl - INFO - Epoch [97][600/1281] lr: 7.067e-03, eta: 4:16:31, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 0.2197, loss: 0.2197 +2025-06-24 19:36:50,978 - pyskl - INFO - Epoch [97][700/1281] lr: 7.049e-03, eta: 4:16:09, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9994, loss_cls: 0.2340, loss: 0.2340 +2025-06-24 19:37:13,444 - pyskl - INFO - Epoch [97][800/1281] lr: 7.030e-03, eta: 4:15:46, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2287, loss: 0.2287 +2025-06-24 19:37:35,936 - pyskl - INFO - Epoch [97][900/1281] lr: 7.012e-03, eta: 4:15:24, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 0.2251, loss: 0.2251 +2025-06-24 19:37:58,306 - pyskl - INFO - Epoch [97][1000/1281] lr: 6.994e-03, eta: 4:15:01, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 0.2476, loss: 0.2476 +2025-06-24 19:38:20,336 - pyskl - INFO - Epoch [97][1100/1281] lr: 6.975e-03, eta: 4:14:39, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 0.2130, loss: 0.2130 +2025-06-24 19:38:42,537 - pyskl - INFO - Epoch [97][1200/1281] lr: 6.957e-03, eta: 4:14:16, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 1.0000, loss_cls: 0.2689, loss: 0.2689 +2025-06-24 19:39:01,394 - pyskl - INFO - Saving checkpoint at 97 epochs +2025-06-24 19:39:45,264 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:39:45,322 - pyskl - INFO - +top1_acc 0.9119 +top5_acc 0.9942 +2025-06-24 19:39:45,322 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:39:45,329 - pyskl - INFO - +mean_acc 0.8753 +2025-06-24 19:39:45,333 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_95.pth was removed +2025-06-24 19:39:45,514 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_97.pth. +2025-06-24 19:39:45,515 - pyskl - INFO - Best top1_acc is 0.9119 at 97 epoch. +2025-06-24 19:39:45,518 - pyskl - INFO - Epoch(val) [97][533] top1_acc: 0.9119, top5_acc: 0.9942, mean_class_accuracy: 0.8753 +2025-06-24 19:40:28,045 - pyskl - INFO - Epoch [98][100/1281] lr: 6.924e-03, eta: 4:13:37, time: 0.425, data_time: 0.186, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9994, loss_cls: 0.2329, loss: 0.2329 +2025-06-24 19:40:50,346 - pyskl - INFO - Epoch [98][200/1281] lr: 6.906e-03, eta: 4:13:14, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1562, loss: 0.1562 +2025-06-24 19:41:12,921 - pyskl - INFO - Epoch [98][300/1281] lr: 6.887e-03, eta: 4:12:52, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9994, loss_cls: 0.2369, loss: 0.2369 +2025-06-24 19:41:35,156 - pyskl - INFO - Epoch [98][400/1281] lr: 6.869e-03, eta: 4:12:29, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 0.1718, loss: 0.1718 +2025-06-24 19:41:57,844 - pyskl - INFO - Epoch [98][500/1281] lr: 6.851e-03, eta: 4:12:07, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 0.2454, loss: 0.2454 +2025-06-24 19:42:20,269 - pyskl - INFO - Epoch [98][600/1281] lr: 6.833e-03, eta: 4:11:44, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 1.0000, loss_cls: 0.2392, loss: 0.2392 +2025-06-24 19:42:42,568 - pyskl - INFO - Epoch [98][700/1281] lr: 6.814e-03, eta: 4:11:22, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 0.2220, loss: 0.2220 +2025-06-24 19:43:05,156 - pyskl - INFO - Epoch [98][800/1281] lr: 6.796e-03, eta: 4:10:59, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 0.2146, loss: 0.2146 +2025-06-24 19:43:27,591 - pyskl - INFO - Epoch [98][900/1281] lr: 6.778e-03, eta: 4:10:37, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 0.2704, loss: 0.2704 +2025-06-24 19:43:50,232 - pyskl - INFO - Epoch [98][1000/1281] lr: 6.760e-03, eta: 4:10:15, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1978, loss: 0.1978 +2025-06-24 19:44:12,468 - pyskl - INFO - Epoch [98][1100/1281] lr: 6.742e-03, eta: 4:09:52, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2284, loss: 0.2284 +2025-06-24 19:44:34,660 - pyskl - INFO - Epoch [98][1200/1281] lr: 6.724e-03, eta: 4:09:29, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 0.9988, loss_cls: 0.2053, loss: 0.2053 +2025-06-24 19:44:53,643 - pyskl - INFO - Saving checkpoint at 98 epochs +2025-06-24 19:45:37,490 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:45:37,546 - pyskl - INFO - +top1_acc 0.9078 +top5_acc 0.9924 +2025-06-24 19:45:37,547 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:45:37,553 - pyskl - INFO - +mean_acc 0.8861 +2025-06-24 19:45:37,555 - pyskl - INFO - Epoch(val) [98][533] top1_acc: 0.9078, top5_acc: 0.9924, mean_class_accuracy: 0.8861 +2025-06-24 19:46:19,608 - pyskl - INFO - Epoch [99][100/1281] lr: 6.691e-03, eta: 4:08:50, time: 0.420, data_time: 0.187, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1660, loss: 0.1660 +2025-06-24 19:46:42,226 - pyskl - INFO - Epoch [99][200/1281] lr: 6.673e-03, eta: 4:08:27, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2146, loss: 0.2146 +2025-06-24 19:47:04,734 - pyskl - INFO - Epoch [99][300/1281] lr: 6.655e-03, eta: 4:08:05, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 0.9994, loss_cls: 0.2221, loss: 0.2221 +2025-06-24 19:47:26,733 - pyskl - INFO - Epoch [99][400/1281] lr: 6.637e-03, eta: 4:07:42, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 0.2247, loss: 0.2247 +2025-06-24 19:47:49,249 - pyskl - INFO - Epoch [99][500/1281] lr: 6.619e-03, eta: 4:07:20, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2503, loss: 0.2503 +2025-06-24 19:48:11,606 - pyskl - INFO - Epoch [99][600/1281] lr: 6.601e-03, eta: 4:06:57, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.1995, loss: 0.1995 +2025-06-24 19:48:33,864 - pyskl - INFO - Epoch [99][700/1281] lr: 6.583e-03, eta: 4:06:35, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2393, loss: 0.2393 +2025-06-24 19:48:55,888 - pyskl - INFO - Epoch [99][800/1281] lr: 6.565e-03, eta: 4:06:12, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 0.9994, loss_cls: 0.1891, loss: 0.1891 +2025-06-24 19:49:18,206 - pyskl - INFO - Epoch [99][900/1281] lr: 6.547e-03, eta: 4:05:50, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 0.9988, loss_cls: 0.2025, loss: 0.2025 +2025-06-24 19:49:40,422 - pyskl - INFO - Epoch [99][1000/1281] lr: 6.529e-03, eta: 4:05:27, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.1914, loss: 0.1914 +2025-06-24 19:50:02,672 - pyskl - INFO - Epoch [99][1100/1281] lr: 6.511e-03, eta: 4:05:04, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9988, loss_cls: 0.2376, loss: 0.2376 +2025-06-24 19:50:25,035 - pyskl - INFO - Epoch [99][1200/1281] lr: 6.493e-03, eta: 4:04:42, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 0.2536, loss: 0.2536 +2025-06-24 19:50:43,893 - pyskl - INFO - Saving checkpoint at 99 epochs +2025-06-24 19:51:27,414 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:51:27,469 - pyskl - INFO - +top1_acc 0.9053 +top5_acc 0.9937 +2025-06-24 19:51:27,469 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:51:27,476 - pyskl - INFO - +mean_acc 0.8859 +2025-06-24 19:51:27,478 - pyskl - INFO - Epoch(val) [99][533] top1_acc: 0.9053, top5_acc: 0.9937, mean_class_accuracy: 0.8859 +2025-06-24 19:52:10,461 - pyskl - INFO - Epoch [100][100/1281] lr: 6.460e-03, eta: 4:04:02, time: 0.430, data_time: 0.191, memory: 4083, top1_acc: 0.9775, top5_acc: 0.9994, loss_cls: 0.1634, loss: 0.1634 +2025-06-24 19:52:32,870 - pyskl - INFO - Epoch [100][200/1281] lr: 6.442e-03, eta: 4:03:40, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 0.9994, loss_cls: 0.2060, loss: 0.2060 +2025-06-24 19:52:55,216 - pyskl - INFO - Epoch [100][300/1281] lr: 6.425e-03, eta: 4:03:18, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.1874, loss: 0.1874 +2025-06-24 19:53:17,939 - pyskl - INFO - Epoch [100][400/1281] lr: 6.407e-03, eta: 4:02:55, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.1933, loss: 0.1933 +2025-06-24 19:53:40,168 - pyskl - INFO - Epoch [100][500/1281] lr: 6.389e-03, eta: 4:02:33, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1688, loss: 0.1688 +2025-06-24 19:54:02,559 - pyskl - INFO - Epoch [100][600/1281] lr: 6.371e-03, eta: 4:02:10, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 0.2110, loss: 0.2110 +2025-06-24 19:54:25,098 - pyskl - INFO - Epoch [100][700/1281] lr: 6.353e-03, eta: 4:01:48, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9994, loss_cls: 0.2508, loss: 0.2508 +2025-06-24 19:54:47,680 - pyskl - INFO - Epoch [100][800/1281] lr: 6.336e-03, eta: 4:01:25, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 0.9994, loss_cls: 0.2550, loss: 0.2550 +2025-06-24 19:55:10,145 - pyskl - INFO - Epoch [100][900/1281] lr: 6.318e-03, eta: 4:01:03, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.2057, loss: 0.2057 +2025-06-24 19:55:32,241 - pyskl - INFO - Epoch [100][1000/1281] lr: 6.300e-03, eta: 4:00:40, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 0.2393, loss: 0.2393 +2025-06-24 19:55:54,348 - pyskl - INFO - Epoch [100][1100/1281] lr: 6.282e-03, eta: 4:00:18, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 0.2096, loss: 0.2096 +2025-06-24 19:56:16,930 - pyskl - INFO - Epoch [100][1200/1281] lr: 6.265e-03, eta: 3:59:55, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 0.9994, loss_cls: 0.2393, loss: 0.2393 +2025-06-24 19:56:35,908 - pyskl - INFO - Saving checkpoint at 100 epochs +2025-06-24 19:57:19,679 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:57:19,735 - pyskl - INFO - +top1_acc 0.9083 +top5_acc 0.9931 +2025-06-24 19:57:19,735 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:57:19,744 - pyskl - INFO - +mean_acc 0.8723 +2025-06-24 19:57:19,747 - pyskl - INFO - Epoch(val) [100][533] top1_acc: 0.9083, top5_acc: 0.9931, mean_class_accuracy: 0.8723 +2025-06-24 19:58:02,286 - pyskl - INFO - Epoch [101][100/1281] lr: 6.232e-03, eta: 3:59:16, time: 0.425, data_time: 0.190, memory: 4083, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 0.2408, loss: 0.2408 +2025-06-24 19:58:25,027 - pyskl - INFO - Epoch [101][200/1281] lr: 6.215e-03, eta: 3:58:53, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.1959, loss: 0.1959 +2025-06-24 19:58:47,363 - pyskl - INFO - Epoch [101][300/1281] lr: 6.197e-03, eta: 3:58:31, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 0.9988, loss_cls: 0.1853, loss: 0.1853 +2025-06-24 19:59:09,901 - pyskl - INFO - Epoch [101][400/1281] lr: 6.180e-03, eta: 3:58:08, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 0.9994, loss_cls: 0.1662, loss: 0.1662 +2025-06-24 19:59:32,393 - pyskl - INFO - Epoch [101][500/1281] lr: 6.162e-03, eta: 3:57:46, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2050, loss: 0.2050 +2025-06-24 19:59:54,709 - pyskl - INFO - Epoch [101][600/1281] lr: 6.144e-03, eta: 3:57:23, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 0.9988, loss_cls: 0.1710, loss: 0.1710 +2025-06-24 20:00:17,317 - pyskl - INFO - Epoch [101][700/1281] lr: 6.127e-03, eta: 3:57:01, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1811, loss: 0.1811 +2025-06-24 20:00:39,867 - pyskl - INFO - Epoch [101][800/1281] lr: 6.109e-03, eta: 3:56:39, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1930, loss: 0.1930 +2025-06-24 20:01:02,204 - pyskl - INFO - Epoch [101][900/1281] lr: 6.092e-03, eta: 3:56:16, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2134, loss: 0.2134 +2025-06-24 20:01:24,469 - pyskl - INFO - Epoch [101][1000/1281] lr: 6.074e-03, eta: 3:55:54, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1895, loss: 0.1895 +2025-06-24 20:01:46,938 - pyskl - INFO - Epoch [101][1100/1281] lr: 6.057e-03, eta: 3:55:31, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 0.2169, loss: 0.2169 +2025-06-24 20:02:09,317 - pyskl - INFO - Epoch [101][1200/1281] lr: 6.039e-03, eta: 3:55:09, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 0.9994, loss_cls: 0.2176, loss: 0.2176 +2025-06-24 20:02:28,218 - pyskl - INFO - Saving checkpoint at 101 epochs +2025-06-24 20:03:12,159 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:03:12,217 - pyskl - INFO - +top1_acc 0.9101 +top5_acc 0.9941 +2025-06-24 20:03:12,217 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:03:12,225 - pyskl - INFO - +mean_acc 0.8854 +2025-06-24 20:03:12,227 - pyskl - INFO - Epoch(val) [101][533] top1_acc: 0.9101, top5_acc: 0.9941, mean_class_accuracy: 0.8854 +2025-06-24 20:03:54,675 - pyskl - INFO - Epoch [102][100/1281] lr: 6.007e-03, eta: 3:54:29, time: 0.424, data_time: 0.189, memory: 4083, top1_acc: 0.9688, top5_acc: 0.9988, loss_cls: 0.2003, loss: 0.2003 +2025-06-24 20:04:17,069 - pyskl - INFO - Epoch [102][200/1281] lr: 5.990e-03, eta: 3:54:07, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1828, loss: 0.1828 +2025-06-24 20:04:39,559 - pyskl - INFO - Epoch [102][300/1281] lr: 5.972e-03, eta: 3:53:44, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.1882, loss: 0.1882 +2025-06-24 20:05:02,085 - pyskl - INFO - Epoch [102][400/1281] lr: 5.955e-03, eta: 3:53:22, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 0.2113, loss: 0.2113 +2025-06-24 20:05:24,180 - pyskl - INFO - Epoch [102][500/1281] lr: 5.938e-03, eta: 3:52:59, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1910, loss: 0.1910 +2025-06-24 20:05:46,663 - pyskl - INFO - Epoch [102][600/1281] lr: 5.920e-03, eta: 3:52:37, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1657, loss: 0.1657 +2025-06-24 20:06:08,983 - pyskl - INFO - Epoch [102][700/1281] lr: 5.903e-03, eta: 3:52:14, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1743, loss: 0.1743 +2025-06-24 20:06:31,380 - pyskl - INFO - Epoch [102][800/1281] lr: 5.886e-03, eta: 3:51:52, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1506, loss: 0.1506 +2025-06-24 20:06:53,629 - pyskl - INFO - Epoch [102][900/1281] lr: 5.868e-03, eta: 3:51:29, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1368, loss: 0.1368 +2025-06-24 20:07:15,862 - pyskl - INFO - Epoch [102][1000/1281] lr: 5.851e-03, eta: 3:51:07, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1736, loss: 0.1736 +2025-06-24 20:07:38,231 - pyskl - INFO - Epoch [102][1100/1281] lr: 5.834e-03, eta: 3:50:44, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.1882, loss: 0.1882 +2025-06-24 20:08:00,688 - pyskl - INFO - Epoch [102][1200/1281] lr: 5.816e-03, eta: 3:50:22, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 0.2276, loss: 0.2276 +2025-06-24 20:08:19,506 - pyskl - INFO - Saving checkpoint at 102 epochs +2025-06-24 20:09:03,108 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:09:03,177 - pyskl - INFO - +top1_acc 0.8934 +top5_acc 0.9911 +2025-06-24 20:09:03,178 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:09:03,188 - pyskl - INFO - +mean_acc 0.8597 +2025-06-24 20:09:03,191 - pyskl - INFO - Epoch(val) [102][533] top1_acc: 0.8934, top5_acc: 0.9911, mean_class_accuracy: 0.8597 +2025-06-24 20:09:45,854 - pyskl - INFO - Epoch [103][100/1281] lr: 5.785e-03, eta: 3:49:42, time: 0.427, data_time: 0.190, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1806, loss: 0.1806 +2025-06-24 20:10:08,100 - pyskl - INFO - Epoch [103][200/1281] lr: 5.768e-03, eta: 3:49:19, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1573, loss: 0.1573 +2025-06-24 20:10:30,544 - pyskl - INFO - Epoch [103][300/1281] lr: 5.751e-03, eta: 3:48:57, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.1864, loss: 0.1864 +2025-06-24 20:10:52,908 - pyskl - INFO - Epoch [103][400/1281] lr: 5.733e-03, eta: 3:48:34, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1663, loss: 0.1663 +2025-06-24 20:11:15,400 - pyskl - INFO - Epoch [103][500/1281] lr: 5.716e-03, eta: 3:48:12, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 0.9994, loss_cls: 0.1915, loss: 0.1915 +2025-06-24 20:11:37,858 - pyskl - INFO - Epoch [103][600/1281] lr: 5.699e-03, eta: 3:47:50, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1816, loss: 0.1816 +2025-06-24 20:12:00,402 - pyskl - INFO - Epoch [103][700/1281] lr: 5.682e-03, eta: 3:47:27, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1868, loss: 0.1868 +2025-06-24 20:12:22,713 - pyskl - INFO - Epoch [103][800/1281] lr: 5.665e-03, eta: 3:47:05, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 0.9994, loss_cls: 0.1807, loss: 0.1807 +2025-06-24 20:12:45,490 - pyskl - INFO - Epoch [103][900/1281] lr: 5.648e-03, eta: 3:46:42, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1737, loss: 0.1737 +2025-06-24 20:13:07,963 - pyskl - INFO - Epoch [103][1000/1281] lr: 5.631e-03, eta: 3:46:20, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.2052, loss: 0.2052 +2025-06-24 20:13:30,590 - pyskl - INFO - Epoch [103][1100/1281] lr: 5.614e-03, eta: 3:45:57, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 0.9994, loss_cls: 0.1856, loss: 0.1856 +2025-06-24 20:13:52,966 - pyskl - INFO - Epoch [103][1200/1281] lr: 5.597e-03, eta: 3:45:35, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 0.9988, loss_cls: 0.1837, loss: 0.1837 +2025-06-24 20:14:11,754 - pyskl - INFO - Saving checkpoint at 103 epochs +2025-06-24 20:14:55,113 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:14:55,171 - pyskl - INFO - +top1_acc 0.9065 +top5_acc 0.9948 +2025-06-24 20:14:55,171 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:14:55,177 - pyskl - INFO - +mean_acc 0.8738 +2025-06-24 20:14:55,179 - pyskl - INFO - Epoch(val) [103][533] top1_acc: 0.9065, top5_acc: 0.9948, mean_class_accuracy: 0.8738 +2025-06-24 20:15:37,770 - pyskl - INFO - Epoch [104][100/1281] lr: 5.566e-03, eta: 3:44:55, time: 0.426, data_time: 0.190, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1575, loss: 0.1575 +2025-06-24 20:16:00,156 - pyskl - INFO - Epoch [104][200/1281] lr: 5.549e-03, eta: 3:44:33, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1392, loss: 0.1392 +2025-06-24 20:16:22,534 - pyskl - INFO - Epoch [104][300/1281] lr: 5.532e-03, eta: 3:44:10, time: 0.224, data_time: 0.001, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1652, loss: 0.1652 +2025-06-24 20:16:44,957 - pyskl - INFO - Epoch [104][400/1281] lr: 5.515e-03, eta: 3:43:48, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 0.1971, loss: 0.1971 +2025-06-24 20:17:07,747 - pyskl - INFO - Epoch [104][500/1281] lr: 5.498e-03, eta: 3:43:26, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1452, loss: 0.1452 +2025-06-24 20:17:30,323 - pyskl - INFO - Epoch [104][600/1281] lr: 5.481e-03, eta: 3:43:03, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2060, loss: 0.2060 +2025-06-24 20:17:52,909 - pyskl - INFO - Epoch [104][700/1281] lr: 5.464e-03, eta: 3:42:41, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1706, loss: 0.1706 +2025-06-24 20:18:15,420 - pyskl - INFO - Epoch [104][800/1281] lr: 5.447e-03, eta: 3:42:18, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1810, loss: 0.1810 +2025-06-24 20:18:37,460 - pyskl - INFO - Epoch [104][900/1281] lr: 5.430e-03, eta: 3:41:56, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 0.1914, loss: 0.1914 +2025-06-24 20:19:00,182 - pyskl - INFO - Epoch [104][1000/1281] lr: 5.413e-03, eta: 3:41:33, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 0.9994, loss_cls: 0.1930, loss: 0.1930 +2025-06-24 20:19:22,644 - pyskl - INFO - Epoch [104][1100/1281] lr: 5.397e-03, eta: 3:41:11, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1804, loss: 0.1804 +2025-06-24 20:19:45,168 - pyskl - INFO - Epoch [104][1200/1281] lr: 5.380e-03, eta: 3:40:48, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.2018, loss: 0.2018 +2025-06-24 20:20:04,235 - pyskl - INFO - Saving checkpoint at 104 epochs +2025-06-24 20:20:47,583 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:20:47,638 - pyskl - INFO - +top1_acc 0.8995 +top5_acc 0.9931 +2025-06-24 20:20:47,638 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:20:47,645 - pyskl - INFO - +mean_acc 0.8618 +2025-06-24 20:20:47,648 - pyskl - INFO - Epoch(val) [104][533] top1_acc: 0.8995, top5_acc: 0.9931, mean_class_accuracy: 0.8618 +2025-06-24 20:21:30,645 - pyskl - INFO - Epoch [105][100/1281] lr: 5.349e-03, eta: 3:40:09, time: 0.430, data_time: 0.192, memory: 4083, top1_acc: 0.9756, top5_acc: 0.9994, loss_cls: 0.1789, loss: 0.1789 +2025-06-24 20:21:53,101 - pyskl - INFO - Epoch [105][200/1281] lr: 5.333e-03, eta: 3:39:46, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1767, loss: 0.1767 +2025-06-24 20:22:15,566 - pyskl - INFO - Epoch [105][300/1281] lr: 5.316e-03, eta: 3:39:24, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 0.9994, loss_cls: 0.1564, loss: 0.1564 +2025-06-24 20:22:37,902 - pyskl - INFO - Epoch [105][400/1281] lr: 5.299e-03, eta: 3:39:01, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1853, loss: 0.1853 +2025-06-24 20:23:00,318 - pyskl - INFO - Epoch [105][500/1281] lr: 5.283e-03, eta: 3:38:39, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 0.9994, loss_cls: 0.1842, loss: 0.1842 +2025-06-24 20:23:23,072 - pyskl - INFO - Epoch [105][600/1281] lr: 5.266e-03, eta: 3:38:17, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 0.9994, loss_cls: 0.1580, loss: 0.1580 +2025-06-24 20:23:45,210 - pyskl - INFO - Epoch [105][700/1281] lr: 5.249e-03, eta: 3:37:54, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1564, loss: 0.1564 +2025-06-24 20:24:07,489 - pyskl - INFO - Epoch [105][800/1281] lr: 5.233e-03, eta: 3:37:32, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.1781, loss: 0.1781 +2025-06-24 20:24:29,878 - pyskl - INFO - Epoch [105][900/1281] lr: 5.216e-03, eta: 3:37:09, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 0.9994, loss_cls: 0.2079, loss: 0.2079 +2025-06-24 20:24:52,291 - pyskl - INFO - Epoch [105][1000/1281] lr: 5.199e-03, eta: 3:36:47, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1903, loss: 0.1903 +2025-06-24 20:25:14,584 - pyskl - INFO - Epoch [105][1100/1281] lr: 5.183e-03, eta: 3:36:24, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1801, loss: 0.1801 +2025-06-24 20:25:36,840 - pyskl - INFO - Epoch [105][1200/1281] lr: 5.166e-03, eta: 3:36:01, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1537, loss: 0.1537 +2025-06-24 20:25:55,994 - pyskl - INFO - Saving checkpoint at 105 epochs +2025-06-24 20:26:39,705 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:26:39,774 - pyskl - INFO - +top1_acc 0.9143 +top5_acc 0.9960 +2025-06-24 20:26:39,774 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:26:39,782 - pyskl - INFO - +mean_acc 0.8903 +2025-06-24 20:26:39,786 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_97.pth was removed +2025-06-24 20:26:39,985 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_105.pth. +2025-06-24 20:26:39,986 - pyskl - INFO - Best top1_acc is 0.9143 at 105 epoch. +2025-06-24 20:26:39,989 - pyskl - INFO - Epoch(val) [105][533] top1_acc: 0.9143, top5_acc: 0.9960, mean_class_accuracy: 0.8903 +2025-06-24 20:27:22,443 - pyskl - INFO - Epoch [106][100/1281] lr: 5.136e-03, eta: 3:35:22, time: 0.424, data_time: 0.189, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.1876, loss: 0.1876 +2025-06-24 20:27:44,945 - pyskl - INFO - Epoch [106][200/1281] lr: 5.120e-03, eta: 3:34:59, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1601, loss: 0.1601 +2025-06-24 20:28:07,324 - pyskl - INFO - Epoch [106][300/1281] lr: 5.103e-03, eta: 3:34:37, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1608, loss: 0.1608 +2025-06-24 20:28:29,863 - pyskl - INFO - Epoch [106][400/1281] lr: 5.087e-03, eta: 3:34:14, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1381, loss: 0.1381 +2025-06-24 20:28:52,267 - pyskl - INFO - Epoch [106][500/1281] lr: 5.070e-03, eta: 3:33:52, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1476, loss: 0.1476 +2025-06-24 20:29:14,504 - pyskl - INFO - Epoch [106][600/1281] lr: 5.054e-03, eta: 3:33:29, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1767, loss: 0.1767 +2025-06-24 20:29:37,044 - pyskl - INFO - Epoch [106][700/1281] lr: 5.038e-03, eta: 3:33:07, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1414, loss: 0.1414 +2025-06-24 20:29:59,364 - pyskl - INFO - Epoch [106][800/1281] lr: 5.021e-03, eta: 3:32:44, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1468, loss: 0.1468 +2025-06-24 20:30:21,870 - pyskl - INFO - Epoch [106][900/1281] lr: 5.005e-03, eta: 3:32:22, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1554, loss: 0.1554 +2025-06-24 20:30:44,119 - pyskl - INFO - Epoch [106][1000/1281] lr: 4.988e-03, eta: 3:31:59, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.1770, loss: 0.1770 +2025-06-24 20:31:06,349 - pyskl - INFO - Epoch [106][1100/1281] lr: 4.972e-03, eta: 3:31:37, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 0.9994, loss_cls: 0.1606, loss: 0.1606 +2025-06-24 20:31:28,582 - pyskl - INFO - Epoch [106][1200/1281] lr: 4.956e-03, eta: 3:31:14, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1697, loss: 0.1697 +2025-06-24 20:31:47,384 - pyskl - INFO - Saving checkpoint at 106 epochs +2025-06-24 20:32:31,348 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:32:31,404 - pyskl - INFO - +top1_acc 0.9195 +top5_acc 0.9955 +2025-06-24 20:32:31,404 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:32:31,411 - pyskl - INFO - +mean_acc 0.8951 +2025-06-24 20:32:31,415 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_105.pth was removed +2025-06-24 20:32:31,599 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_106.pth. +2025-06-24 20:32:31,599 - pyskl - INFO - Best top1_acc is 0.9195 at 106 epoch. +2025-06-24 20:32:31,603 - pyskl - INFO - Epoch(val) [106][533] top1_acc: 0.9195, top5_acc: 0.9955, mean_class_accuracy: 0.8951 +2025-06-24 20:33:14,457 - pyskl - INFO - Epoch [107][100/1281] lr: 4.926e-03, eta: 3:30:35, time: 0.428, data_time: 0.190, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1388, loss: 0.1388 +2025-06-24 20:33:36,927 - pyskl - INFO - Epoch [107][200/1281] lr: 4.910e-03, eta: 3:30:12, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 0.9994, loss_cls: 0.1235, loss: 0.1235 +2025-06-24 20:33:59,512 - pyskl - INFO - Epoch [107][300/1281] lr: 4.894e-03, eta: 3:29:50, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1610, loss: 0.1610 +2025-06-24 20:34:21,790 - pyskl - INFO - Epoch [107][400/1281] lr: 4.878e-03, eta: 3:29:27, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 0.9994, loss_cls: 0.1692, loss: 0.1692 +2025-06-24 20:34:44,166 - pyskl - INFO - Epoch [107][500/1281] lr: 4.862e-03, eta: 3:29:05, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.1784, loss: 0.1784 +2025-06-24 20:35:06,332 - pyskl - INFO - Epoch [107][600/1281] lr: 4.845e-03, eta: 3:28:42, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1474, loss: 0.1474 +2025-06-24 20:35:28,562 - pyskl - INFO - Epoch [107][700/1281] lr: 4.829e-03, eta: 3:28:20, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1748, loss: 0.1748 +2025-06-24 20:35:50,829 - pyskl - INFO - Epoch [107][800/1281] lr: 4.813e-03, eta: 3:27:57, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1925, loss: 0.1925 +2025-06-24 20:36:13,052 - pyskl - INFO - Epoch [107][900/1281] lr: 4.797e-03, eta: 3:27:34, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1580, loss: 0.1580 +2025-06-24 20:36:35,395 - pyskl - INFO - Epoch [107][1000/1281] lr: 4.781e-03, eta: 3:27:12, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 0.1732, loss: 0.1732 +2025-06-24 20:36:57,594 - pyskl - INFO - Epoch [107][1100/1281] lr: 4.765e-03, eta: 3:26:49, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1608, loss: 0.1608 +2025-06-24 20:37:20,182 - pyskl - INFO - Epoch [107][1200/1281] lr: 4.749e-03, eta: 3:26:27, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1263, loss: 0.1263 +2025-06-24 20:37:39,152 - pyskl - INFO - Saving checkpoint at 107 epochs +2025-06-24 20:38:22,502 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:38:22,561 - pyskl - INFO - +top1_acc 0.9173 +top5_acc 0.9957 +2025-06-24 20:38:22,561 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:38:22,569 - pyskl - INFO - +mean_acc 0.8859 +2025-06-24 20:38:22,571 - pyskl - INFO - Epoch(val) [107][533] top1_acc: 0.9173, top5_acc: 0.9957, mean_class_accuracy: 0.8859 +2025-06-24 20:39:05,394 - pyskl - INFO - Epoch [108][100/1281] lr: 4.720e-03, eta: 3:25:47, time: 0.428, data_time: 0.192, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1385, loss: 0.1385 +2025-06-24 20:39:27,872 - pyskl - INFO - Epoch [108][200/1281] lr: 4.704e-03, eta: 3:25:25, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1168, loss: 0.1168 +2025-06-24 20:39:50,413 - pyskl - INFO - Epoch [108][300/1281] lr: 4.688e-03, eta: 3:25:02, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1317, loss: 0.1317 +2025-06-24 20:40:12,935 - pyskl - INFO - Epoch [108][400/1281] lr: 4.672e-03, eta: 3:24:40, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1336, loss: 0.1336 +2025-06-24 20:40:35,240 - pyskl - INFO - Epoch [108][500/1281] lr: 4.656e-03, eta: 3:24:17, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 0.1496, loss: 0.1496 +2025-06-24 20:40:57,483 - pyskl - INFO - Epoch [108][600/1281] lr: 4.640e-03, eta: 3:23:55, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1359, loss: 0.1359 +2025-06-24 20:41:19,796 - pyskl - INFO - Epoch [108][700/1281] lr: 4.624e-03, eta: 3:23:32, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 0.9994, loss_cls: 0.1486, loss: 0.1486 +2025-06-24 20:41:42,493 - pyskl - INFO - Epoch [108][800/1281] lr: 4.608e-03, eta: 3:23:10, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1629, loss: 0.1629 +2025-06-24 20:42:04,674 - pyskl - INFO - Epoch [108][900/1281] lr: 4.593e-03, eta: 3:22:47, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 0.9994, loss_cls: 0.1533, loss: 0.1533 +2025-06-24 20:42:26,902 - pyskl - INFO - Epoch [108][1000/1281] lr: 4.577e-03, eta: 3:22:25, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1442, loss: 0.1442 +2025-06-24 20:42:49,615 - pyskl - INFO - Epoch [108][1100/1281] lr: 4.561e-03, eta: 3:22:02, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1826, loss: 0.1826 +2025-06-24 20:43:11,800 - pyskl - INFO - Epoch [108][1200/1281] lr: 4.545e-03, eta: 3:21:40, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1548, loss: 0.1548 +2025-06-24 20:43:30,846 - pyskl - INFO - Saving checkpoint at 108 epochs +2025-06-24 20:44:14,474 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:44:14,542 - pyskl - INFO - +top1_acc 0.9218 +top5_acc 0.9957 +2025-06-24 20:44:14,542 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:44:14,550 - pyskl - INFO - +mean_acc 0.8881 +2025-06-24 20:44:14,555 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_106.pth was removed +2025-06-24 20:44:14,750 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_108.pth. +2025-06-24 20:44:14,751 - pyskl - INFO - Best top1_acc is 0.9218 at 108 epoch. +2025-06-24 20:44:14,754 - pyskl - INFO - Epoch(val) [108][533] top1_acc: 0.9218, top5_acc: 0.9957, mean_class_accuracy: 0.8881 +2025-06-24 20:44:58,059 - pyskl - INFO - Epoch [109][100/1281] lr: 4.517e-03, eta: 3:21:00, time: 0.433, data_time: 0.195, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1026, loss: 0.1026 +2025-06-24 20:45:20,873 - pyskl - INFO - Epoch [109][200/1281] lr: 4.501e-03, eta: 3:20:38, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0863, loss: 0.0863 +2025-06-24 20:45:43,473 - pyskl - INFO - Epoch [109][300/1281] lr: 4.485e-03, eta: 3:20:16, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1151, loss: 0.1151 +2025-06-24 20:46:06,185 - pyskl - INFO - Epoch [109][400/1281] lr: 4.470e-03, eta: 3:19:53, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1474, loss: 0.1474 +2025-06-24 20:46:28,445 - pyskl - INFO - Epoch [109][500/1281] lr: 4.454e-03, eta: 3:19:31, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1234, loss: 0.1234 +2025-06-24 20:46:50,966 - pyskl - INFO - Epoch [109][600/1281] lr: 4.438e-03, eta: 3:19:08, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1233, loss: 0.1233 +2025-06-24 20:47:13,596 - pyskl - INFO - Epoch [109][700/1281] lr: 4.423e-03, eta: 3:18:46, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1125, loss: 0.1125 +2025-06-24 20:47:36,030 - pyskl - INFO - Epoch [109][800/1281] lr: 4.407e-03, eta: 3:18:23, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1387, loss: 0.1387 +2025-06-24 20:47:58,362 - pyskl - INFO - Epoch [109][900/1281] lr: 4.391e-03, eta: 3:18:01, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1452, loss: 0.1452 +2025-06-24 20:48:20,529 - pyskl - INFO - Epoch [109][1000/1281] lr: 4.376e-03, eta: 3:17:38, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 0.9981, loss_cls: 0.1727, loss: 0.1727 +2025-06-24 20:48:42,781 - pyskl - INFO - Epoch [109][1100/1281] lr: 4.360e-03, eta: 3:17:16, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1555, loss: 0.1555 +2025-06-24 20:49:05,101 - pyskl - INFO - Epoch [109][1200/1281] lr: 4.345e-03, eta: 3:16:53, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1221, loss: 0.1221 +2025-06-24 20:49:24,201 - pyskl - INFO - Saving checkpoint at 109 epochs +2025-06-24 20:50:08,078 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:50:08,136 - pyskl - INFO - +top1_acc 0.9173 +top5_acc 0.9948 +2025-06-24 20:50:08,136 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:50:08,143 - pyskl - INFO - +mean_acc 0.8851 +2025-06-24 20:50:08,145 - pyskl - INFO - Epoch(val) [109][533] top1_acc: 0.9173, top5_acc: 0.9948, mean_class_accuracy: 0.8851 +2025-06-24 20:50:50,908 - pyskl - INFO - Epoch [110][100/1281] lr: 4.317e-03, eta: 3:16:13, time: 0.428, data_time: 0.192, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1219, loss: 0.1219 +2025-06-24 20:51:13,392 - pyskl - INFO - Epoch [110][200/1281] lr: 4.301e-03, eta: 3:15:51, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1069, loss: 0.1069 +2025-06-24 20:51:35,995 - pyskl - INFO - Epoch [110][300/1281] lr: 4.286e-03, eta: 3:15:29, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1001, loss: 0.1001 +2025-06-24 20:51:58,354 - pyskl - INFO - Epoch [110][400/1281] lr: 4.271e-03, eta: 3:15:06, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1467, loss: 0.1467 +2025-06-24 20:52:20,711 - pyskl - INFO - Epoch [110][500/1281] lr: 4.255e-03, eta: 3:14:44, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1376, loss: 0.1376 +2025-06-24 20:52:42,873 - pyskl - INFO - Epoch [110][600/1281] lr: 4.240e-03, eta: 3:14:21, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 0.1334, loss: 0.1334 +2025-06-24 20:53:05,426 - pyskl - INFO - Epoch [110][700/1281] lr: 4.225e-03, eta: 3:13:59, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1250, loss: 0.1250 +2025-06-24 20:53:27,793 - pyskl - INFO - Epoch [110][800/1281] lr: 4.209e-03, eta: 3:13:36, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1602, loss: 0.1602 +2025-06-24 20:53:50,477 - pyskl - INFO - Epoch [110][900/1281] lr: 4.194e-03, eta: 3:13:14, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1304, loss: 0.1304 +2025-06-24 20:54:12,859 - pyskl - INFO - Epoch [110][1000/1281] lr: 4.179e-03, eta: 3:12:51, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1537, loss: 0.1537 +2025-06-24 20:54:35,259 - pyskl - INFO - Epoch [110][1100/1281] lr: 4.164e-03, eta: 3:12:29, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 0.9994, loss_cls: 0.1265, loss: 0.1265 +2025-06-24 20:54:57,855 - pyskl - INFO - Epoch [110][1200/1281] lr: 4.148e-03, eta: 3:12:06, time: 0.226, data_time: 0.001, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1487, loss: 0.1487 +2025-06-24 20:55:16,641 - pyskl - INFO - Saving checkpoint at 110 epochs +2025-06-24 20:56:00,457 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:56:00,517 - pyskl - INFO - +top1_acc 0.9234 +top5_acc 0.9959 +2025-06-24 20:56:00,517 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:56:00,524 - pyskl - INFO - +mean_acc 0.8966 +2025-06-24 20:56:00,528 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_108.pth was removed +2025-06-24 20:56:00,700 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_110.pth. +2025-06-24 20:56:00,701 - pyskl - INFO - Best top1_acc is 0.9234 at 110 epoch. +2025-06-24 20:56:00,703 - pyskl - INFO - Epoch(val) [110][533] top1_acc: 0.9234, top5_acc: 0.9959, mean_class_accuracy: 0.8966 +2025-06-24 20:56:43,307 - pyskl - INFO - Epoch [111][100/1281] lr: 4.121e-03, eta: 3:11:26, time: 0.426, data_time: 0.192, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1109, loss: 0.1109 +2025-06-24 20:57:05,763 - pyskl - INFO - Epoch [111][200/1281] lr: 4.106e-03, eta: 3:11:04, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1083, loss: 0.1083 +2025-06-24 20:57:28,214 - pyskl - INFO - Epoch [111][300/1281] lr: 4.091e-03, eta: 3:10:41, time: 0.225, data_time: 0.001, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0901, loss: 0.0901 +2025-06-24 20:57:50,530 - pyskl - INFO - Epoch [111][400/1281] lr: 4.075e-03, eta: 3:10:19, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.1003, loss: 0.1003 +2025-06-24 20:58:12,529 - pyskl - INFO - Epoch [111][500/1281] lr: 4.060e-03, eta: 3:09:56, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0984, loss: 0.0984 +2025-06-24 20:58:34,856 - pyskl - INFO - Epoch [111][600/1281] lr: 4.045e-03, eta: 3:09:34, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1163, loss: 0.1163 +2025-06-24 20:58:57,064 - pyskl - INFO - Epoch [111][700/1281] lr: 4.030e-03, eta: 3:09:11, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1687, loss: 0.1687 +2025-06-24 20:59:19,683 - pyskl - INFO - Epoch [111][800/1281] lr: 4.015e-03, eta: 3:08:49, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1213, loss: 0.1213 +2025-06-24 20:59:42,093 - pyskl - INFO - Epoch [111][900/1281] lr: 4.000e-03, eta: 3:08:26, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1388, loss: 0.1388 +2025-06-24 21:00:04,653 - pyskl - INFO - Epoch [111][1000/1281] lr: 3.985e-03, eta: 3:08:04, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 0.9994, loss_cls: 0.1212, loss: 0.1212 +2025-06-24 21:00:27,267 - pyskl - INFO - Epoch [111][1100/1281] lr: 3.970e-03, eta: 3:07:41, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1324, loss: 0.1324 +2025-06-24 21:00:49,965 - pyskl - INFO - Epoch [111][1200/1281] lr: 3.955e-03, eta: 3:07:19, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 0.9994, loss_cls: 0.1190, loss: 0.1190 +2025-06-24 21:01:08,883 - pyskl - INFO - Saving checkpoint at 111 epochs +2025-06-24 21:01:52,060 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:01:52,117 - pyskl - INFO - +top1_acc 0.9231 +top5_acc 0.9942 +2025-06-24 21:01:52,117 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:01:52,124 - pyskl - INFO - +mean_acc 0.8982 +2025-06-24 21:01:52,126 - pyskl - INFO - Epoch(val) [111][533] top1_acc: 0.9231, top5_acc: 0.9942, mean_class_accuracy: 0.8982 +2025-06-24 21:02:34,223 - pyskl - INFO - Epoch [112][100/1281] lr: 3.928e-03, eta: 3:06:39, time: 0.421, data_time: 0.185, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1046, loss: 0.1046 +2025-06-24 21:02:56,607 - pyskl - INFO - Epoch [112][200/1281] lr: 3.914e-03, eta: 3:06:16, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 0.1284, loss: 0.1284 +2025-06-24 21:03:19,039 - pyskl - INFO - Epoch [112][300/1281] lr: 3.899e-03, eta: 3:05:54, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 0.9994, loss_cls: 0.1132, loss: 0.1132 +2025-06-24 21:03:41,526 - pyskl - INFO - Epoch [112][400/1281] lr: 3.884e-03, eta: 3:05:32, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1619, loss: 0.1619 +2025-06-24 21:04:03,935 - pyskl - INFO - Epoch [112][500/1281] lr: 3.869e-03, eta: 3:05:09, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1335, loss: 0.1335 +2025-06-24 21:04:26,300 - pyskl - INFO - Epoch [112][600/1281] lr: 3.854e-03, eta: 3:04:47, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1135, loss: 0.1135 +2025-06-24 21:04:48,736 - pyskl - INFO - Epoch [112][700/1281] lr: 3.840e-03, eta: 3:04:24, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1275, loss: 0.1275 +2025-06-24 21:05:11,100 - pyskl - INFO - Epoch [112][800/1281] lr: 3.825e-03, eta: 3:04:02, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 0.1325, loss: 0.1325 +2025-06-24 21:05:33,311 - pyskl - INFO - Epoch [112][900/1281] lr: 3.810e-03, eta: 3:03:39, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1398, loss: 0.1398 +2025-06-24 21:05:55,453 - pyskl - INFO - Epoch [112][1000/1281] lr: 3.795e-03, eta: 3:03:16, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1174, loss: 0.1174 +2025-06-24 21:06:17,853 - pyskl - INFO - Epoch [112][1100/1281] lr: 3.781e-03, eta: 3:02:54, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1235, loss: 0.1235 +2025-06-24 21:06:40,058 - pyskl - INFO - Epoch [112][1200/1281] lr: 3.766e-03, eta: 3:02:31, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1418, loss: 0.1418 +2025-06-24 21:06:58,795 - pyskl - INFO - Saving checkpoint at 112 epochs +2025-06-24 21:07:42,947 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:07:43,004 - pyskl - INFO - +top1_acc 0.9182 +top5_acc 0.9948 +2025-06-24 21:07:43,004 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:07:43,012 - pyskl - INFO - +mean_acc 0.8920 +2025-06-24 21:07:43,014 - pyskl - INFO - Epoch(val) [112][533] top1_acc: 0.9182, top5_acc: 0.9948, mean_class_accuracy: 0.8920 +2025-06-24 21:08:25,250 - pyskl - INFO - Epoch [113][100/1281] lr: 3.740e-03, eta: 3:01:51, time: 0.422, data_time: 0.189, memory: 4083, top1_acc: 0.9925, top5_acc: 0.9994, loss_cls: 0.0867, loss: 0.0867 +2025-06-24 21:08:47,814 - pyskl - INFO - Epoch [113][200/1281] lr: 3.725e-03, eta: 3:01:29, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0737, loss: 0.0737 +2025-06-24 21:09:10,262 - pyskl - INFO - Epoch [113][300/1281] lr: 3.711e-03, eta: 3:01:06, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0827, loss: 0.0827 +2025-06-24 21:09:32,831 - pyskl - INFO - Epoch [113][400/1281] lr: 3.696e-03, eta: 3:00:44, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1148, loss: 0.1148 +2025-06-24 21:09:55,447 - pyskl - INFO - Epoch [113][500/1281] lr: 3.682e-03, eta: 3:00:22, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0963, loss: 0.0963 +2025-06-24 21:10:17,841 - pyskl - INFO - Epoch [113][600/1281] lr: 3.667e-03, eta: 2:59:59, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0884, loss: 0.0884 +2025-06-24 21:10:40,538 - pyskl - INFO - Epoch [113][700/1281] lr: 3.653e-03, eta: 2:59:37, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1008, loss: 0.1008 +2025-06-24 21:11:02,987 - pyskl - INFO - Epoch [113][800/1281] lr: 3.638e-03, eta: 2:59:14, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 0.9994, loss_cls: 0.1056, loss: 0.1056 +2025-06-24 21:11:25,666 - pyskl - INFO - Epoch [113][900/1281] lr: 3.624e-03, eta: 2:58:52, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0823, loss: 0.0823 +2025-06-24 21:11:48,323 - pyskl - INFO - Epoch [113][1000/1281] lr: 3.610e-03, eta: 2:58:29, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0882, loss: 0.0882 +2025-06-24 21:12:10,653 - pyskl - INFO - Epoch [113][1100/1281] lr: 3.595e-03, eta: 2:58:07, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0844, loss: 0.0844 +2025-06-24 21:12:33,261 - pyskl - INFO - Epoch [113][1200/1281] lr: 3.581e-03, eta: 2:57:45, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0850, loss: 0.0850 +2025-06-24 21:12:51,946 - pyskl - INFO - Saving checkpoint at 113 epochs +2025-06-24 21:13:36,231 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:13:36,289 - pyskl - INFO - +top1_acc 0.9196 +top5_acc 0.9954 +2025-06-24 21:13:36,289 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:13:36,298 - pyskl - INFO - +mean_acc 0.8919 +2025-06-24 21:13:36,301 - pyskl - INFO - Epoch(val) [113][533] top1_acc: 0.9196, top5_acc: 0.9954, mean_class_accuracy: 0.8919 +2025-06-24 21:14:18,664 - pyskl - INFO - Epoch [114][100/1281] lr: 3.555e-03, eta: 2:57:04, time: 0.424, data_time: 0.187, memory: 4083, top1_acc: 0.9869, top5_acc: 0.9994, loss_cls: 0.1121, loss: 0.1121 +2025-06-24 21:14:41,115 - pyskl - INFO - Epoch [114][200/1281] lr: 3.541e-03, eta: 2:56:42, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0936, loss: 0.0936 +2025-06-24 21:15:03,304 - pyskl - INFO - Epoch [114][300/1281] lr: 3.526e-03, eta: 2:56:19, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0777, loss: 0.0777 +2025-06-24 21:15:25,867 - pyskl - INFO - Epoch [114][400/1281] lr: 3.512e-03, eta: 2:55:57, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1022, loss: 0.1022 +2025-06-24 21:15:48,217 - pyskl - INFO - Epoch [114][500/1281] lr: 3.498e-03, eta: 2:55:34, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 0.9994, loss_cls: 0.1073, loss: 0.1073 +2025-06-24 21:16:10,516 - pyskl - INFO - Epoch [114][600/1281] lr: 3.484e-03, eta: 2:55:12, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0826, loss: 0.0826 +2025-06-24 21:16:33,201 - pyskl - INFO - Epoch [114][700/1281] lr: 3.470e-03, eta: 2:54:50, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1072, loss: 0.1072 +2025-06-24 21:16:55,571 - pyskl - INFO - Epoch [114][800/1281] lr: 3.456e-03, eta: 2:54:27, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0935, loss: 0.0935 +2025-06-24 21:17:17,704 - pyskl - INFO - Epoch [114][900/1281] lr: 3.442e-03, eta: 2:54:04, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.0971, loss: 0.0971 +2025-06-24 21:17:40,181 - pyskl - INFO - Epoch [114][1000/1281] lr: 3.427e-03, eta: 2:53:42, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0998, loss: 0.0998 +2025-06-24 21:18:02,389 - pyskl - INFO - Epoch [114][1100/1281] lr: 3.413e-03, eta: 2:53:19, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0854, loss: 0.0854 +2025-06-24 21:18:24,628 - pyskl - INFO - Epoch [114][1200/1281] lr: 3.399e-03, eta: 2:52:57, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1072, loss: 0.1072 +2025-06-24 21:18:43,275 - pyskl - INFO - Saving checkpoint at 114 epochs +2025-06-24 21:19:27,244 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:19:27,305 - pyskl - INFO - +top1_acc 0.9168 +top5_acc 0.9939 +2025-06-24 21:19:27,305 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:19:27,312 - pyskl - INFO - +mean_acc 0.8802 +2025-06-24 21:19:27,314 - pyskl - INFO - Epoch(val) [114][533] top1_acc: 0.9168, top5_acc: 0.9939, mean_class_accuracy: 0.8802 +2025-06-24 21:20:09,570 - pyskl - INFO - Epoch [115][100/1281] lr: 3.374e-03, eta: 2:52:17, time: 0.423, data_time: 0.189, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1071, loss: 0.1071 +2025-06-24 21:20:31,866 - pyskl - INFO - Epoch [115][200/1281] lr: 3.360e-03, eta: 2:51:54, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1197, loss: 0.1197 +2025-06-24 21:20:53,909 - pyskl - INFO - Epoch [115][300/1281] lr: 3.346e-03, eta: 2:51:32, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1100, loss: 0.1100 +2025-06-24 21:21:16,365 - pyskl - INFO - Epoch [115][400/1281] lr: 3.332e-03, eta: 2:51:09, time: 0.225, data_time: 0.001, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.0841, loss: 0.0841 +2025-06-24 21:21:38,846 - pyskl - INFO - Epoch [115][500/1281] lr: 3.318e-03, eta: 2:50:47, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0831, loss: 0.0831 +2025-06-24 21:22:01,396 - pyskl - INFO - Epoch [115][600/1281] lr: 3.305e-03, eta: 2:50:24, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0626, loss: 0.0626 +2025-06-24 21:22:23,761 - pyskl - INFO - Epoch [115][700/1281] lr: 3.291e-03, eta: 2:50:02, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1049, loss: 0.1049 +2025-06-24 21:22:45,942 - pyskl - INFO - Epoch [115][800/1281] lr: 3.277e-03, eta: 2:49:39, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1063, loss: 0.1063 +2025-06-24 21:23:08,250 - pyskl - INFO - Epoch [115][900/1281] lr: 3.263e-03, eta: 2:49:17, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0781, loss: 0.0781 +2025-06-24 21:23:30,575 - pyskl - INFO - Epoch [115][1000/1281] lr: 3.249e-03, eta: 2:48:54, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 0.9994, loss_cls: 0.0817, loss: 0.0817 +2025-06-24 21:23:52,813 - pyskl - INFO - Epoch [115][1100/1281] lr: 3.236e-03, eta: 2:48:32, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1076, loss: 0.1076 +2025-06-24 21:24:15,147 - pyskl - INFO - Epoch [115][1200/1281] lr: 3.222e-03, eta: 2:48:09, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.1035, loss: 0.1035 +2025-06-24 21:24:34,150 - pyskl - INFO - Saving checkpoint at 115 epochs +2025-06-24 21:25:17,619 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:25:17,676 - pyskl - INFO - +top1_acc 0.9143 +top5_acc 0.9946 +2025-06-24 21:25:17,676 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:25:17,683 - pyskl - INFO - +mean_acc 0.8911 +2025-06-24 21:25:17,685 - pyskl - INFO - Epoch(val) [115][533] top1_acc: 0.9143, top5_acc: 0.9946, mean_class_accuracy: 0.8911 +2025-06-24 21:26:00,517 - pyskl - INFO - Epoch [116][100/1281] lr: 3.197e-03, eta: 2:47:29, time: 0.428, data_time: 0.191, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0827, loss: 0.0827 +2025-06-24 21:26:22,980 - pyskl - INFO - Epoch [116][200/1281] lr: 3.184e-03, eta: 2:47:07, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0734, loss: 0.0734 +2025-06-24 21:26:45,140 - pyskl - INFO - Epoch [116][300/1281] lr: 3.170e-03, eta: 2:46:44, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0765, loss: 0.0765 +2025-06-24 21:27:07,380 - pyskl - INFO - Epoch [116][400/1281] lr: 3.156e-03, eta: 2:46:22, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0817, loss: 0.0817 +2025-06-24 21:27:29,595 - pyskl - INFO - Epoch [116][500/1281] lr: 3.143e-03, eta: 2:45:59, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.0963, loss: 0.0963 +2025-06-24 21:27:51,998 - pyskl - INFO - Epoch [116][600/1281] lr: 3.129e-03, eta: 2:45:37, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.0935, loss: 0.0935 +2025-06-24 21:28:14,509 - pyskl - INFO - Epoch [116][700/1281] lr: 3.116e-03, eta: 2:45:14, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0964, loss: 0.0964 +2025-06-24 21:28:36,647 - pyskl - INFO - Epoch [116][800/1281] lr: 3.102e-03, eta: 2:44:52, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0687, loss: 0.0687 +2025-06-24 21:28:59,161 - pyskl - INFO - Epoch [116][900/1281] lr: 3.089e-03, eta: 2:44:29, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0618, loss: 0.0618 +2025-06-24 21:29:21,481 - pyskl - INFO - Epoch [116][1000/1281] lr: 3.075e-03, eta: 2:44:07, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0733, loss: 0.0733 +2025-06-24 21:29:43,850 - pyskl - INFO - Epoch [116][1100/1281] lr: 3.062e-03, eta: 2:43:44, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0845, loss: 0.0845 +2025-06-24 21:30:06,099 - pyskl - INFO - Epoch [116][1200/1281] lr: 3.049e-03, eta: 2:43:22, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.0872, loss: 0.0872 +2025-06-24 21:30:25,126 - pyskl - INFO - Saving checkpoint at 116 epochs +2025-06-24 21:31:08,849 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:31:08,903 - pyskl - INFO - +top1_acc 0.9229 +top5_acc 0.9953 +2025-06-24 21:31:08,904 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:31:08,910 - pyskl - INFO - +mean_acc 0.8995 +2025-06-24 21:31:08,912 - pyskl - INFO - Epoch(val) [116][533] top1_acc: 0.9229, top5_acc: 0.9953, mean_class_accuracy: 0.8995 +2025-06-24 21:31:51,669 - pyskl - INFO - Epoch [117][100/1281] lr: 3.024e-03, eta: 2:42:42, time: 0.427, data_time: 0.193, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0670, loss: 0.0670 +2025-06-24 21:32:14,071 - pyskl - INFO - Epoch [117][200/1281] lr: 3.011e-03, eta: 2:42:19, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0759, loss: 0.0759 +2025-06-24 21:32:36,602 - pyskl - INFO - Epoch [117][300/1281] lr: 2.998e-03, eta: 2:41:57, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0658, loss: 0.0658 +2025-06-24 21:32:58,994 - pyskl - INFO - Epoch [117][400/1281] lr: 2.984e-03, eta: 2:41:34, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0622, loss: 0.0622 +2025-06-24 21:33:21,344 - pyskl - INFO - Epoch [117][500/1281] lr: 2.971e-03, eta: 2:41:12, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0681, loss: 0.0681 +2025-06-24 21:33:43,781 - pyskl - INFO - Epoch [117][600/1281] lr: 2.958e-03, eta: 2:40:49, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0845, loss: 0.0845 +2025-06-24 21:34:05,888 - pyskl - INFO - Epoch [117][700/1281] lr: 2.945e-03, eta: 2:40:27, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0619, loss: 0.0619 +2025-06-24 21:34:28,325 - pyskl - INFO - Epoch [117][800/1281] lr: 2.932e-03, eta: 2:40:04, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0864, loss: 0.0864 +2025-06-24 21:34:50,726 - pyskl - INFO - Epoch [117][900/1281] lr: 2.919e-03, eta: 2:39:42, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0822, loss: 0.0822 +2025-06-24 21:35:13,077 - pyskl - INFO - Epoch [117][1000/1281] lr: 2.905e-03, eta: 2:39:19, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0766, loss: 0.0766 +2025-06-24 21:35:35,781 - pyskl - INFO - Epoch [117][1100/1281] lr: 2.892e-03, eta: 2:38:57, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0642, loss: 0.0642 +2025-06-24 21:35:58,058 - pyskl - INFO - Epoch [117][1200/1281] lr: 2.879e-03, eta: 2:38:34, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0702, loss: 0.0702 +2025-06-24 21:36:16,988 - pyskl - INFO - Saving checkpoint at 117 epochs +2025-06-24 21:37:01,416 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:37:01,477 - pyskl - INFO - +top1_acc 0.9275 +top5_acc 0.9958 +2025-06-24 21:37:01,477 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:37:01,483 - pyskl - INFO - +mean_acc 0.8993 +2025-06-24 21:37:01,487 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_110.pth was removed +2025-06-24 21:37:01,698 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_117.pth. +2025-06-24 21:37:01,698 - pyskl - INFO - Best top1_acc is 0.9275 at 117 epoch. +2025-06-24 21:37:01,700 - pyskl - INFO - Epoch(val) [117][533] top1_acc: 0.9275, top5_acc: 0.9958, mean_class_accuracy: 0.8993 +2025-06-24 21:37:44,145 - pyskl - INFO - Epoch [118][100/1281] lr: 2.856e-03, eta: 2:37:54, time: 0.424, data_time: 0.187, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0827, loss: 0.0827 +2025-06-24 21:38:06,403 - pyskl - INFO - Epoch [118][200/1281] lr: 2.843e-03, eta: 2:37:32, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0557, loss: 0.0557 +2025-06-24 21:38:28,569 - pyskl - INFO - Epoch [118][300/1281] lr: 2.830e-03, eta: 2:37:09, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0689, loss: 0.0689 +2025-06-24 21:38:50,781 - pyskl - INFO - Epoch [118][400/1281] lr: 2.817e-03, eta: 2:36:46, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0648, loss: 0.0648 +2025-06-24 21:39:13,195 - pyskl - INFO - Epoch [118][500/1281] lr: 2.804e-03, eta: 2:36:24, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0532, loss: 0.0532 +2025-06-24 21:39:35,619 - pyskl - INFO - Epoch [118][600/1281] lr: 2.791e-03, eta: 2:36:02, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0641, loss: 0.0641 +2025-06-24 21:39:57,981 - pyskl - INFO - Epoch [118][700/1281] lr: 2.778e-03, eta: 2:35:39, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0549, loss: 0.0549 +2025-06-24 21:40:20,665 - pyskl - INFO - Epoch [118][800/1281] lr: 2.765e-03, eta: 2:35:17, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0759, loss: 0.0759 +2025-06-24 21:40:43,105 - pyskl - INFO - Epoch [118][900/1281] lr: 2.753e-03, eta: 2:34:54, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0802, loss: 0.0802 +2025-06-24 21:41:05,670 - pyskl - INFO - Epoch [118][1000/1281] lr: 2.740e-03, eta: 2:34:32, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1028, loss: 0.1028 +2025-06-24 21:41:27,829 - pyskl - INFO - Epoch [118][1100/1281] lr: 2.727e-03, eta: 2:34:09, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 0.9994, loss_cls: 0.0979, loss: 0.0979 +2025-06-24 21:41:50,088 - pyskl - INFO - Epoch [118][1200/1281] lr: 2.714e-03, eta: 2:33:47, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.0876, loss: 0.0876 +2025-06-24 21:42:08,853 - pyskl - INFO - Saving checkpoint at 118 epochs +2025-06-24 21:42:52,550 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:42:52,608 - pyskl - INFO - +top1_acc 0.9270 +top5_acc 0.9946 +2025-06-24 21:42:52,608 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:42:52,616 - pyskl - INFO - +mean_acc 0.9010 +2025-06-24 21:42:52,618 - pyskl - INFO - Epoch(val) [118][533] top1_acc: 0.9270, top5_acc: 0.9946, mean_class_accuracy: 0.9010 +2025-06-24 21:43:34,482 - pyskl - INFO - Epoch [119][100/1281] lr: 2.691e-03, eta: 2:33:06, time: 0.419, data_time: 0.185, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0591, loss: 0.0591 +2025-06-24 21:43:57,190 - pyskl - INFO - Epoch [119][200/1281] lr: 2.679e-03, eta: 2:32:44, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0507, loss: 0.0507 +2025-06-24 21:44:19,606 - pyskl - INFO - Epoch [119][300/1281] lr: 2.666e-03, eta: 2:32:21, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0467, loss: 0.0467 +2025-06-24 21:44:41,869 - pyskl - INFO - Epoch [119][400/1281] lr: 2.653e-03, eta: 2:31:59, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 0.9994, loss_cls: 0.0746, loss: 0.0746 +2025-06-24 21:45:04,334 - pyskl - INFO - Epoch [119][500/1281] lr: 2.641e-03, eta: 2:31:36, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0641, loss: 0.0641 +2025-06-24 21:45:26,454 - pyskl - INFO - Epoch [119][600/1281] lr: 2.628e-03, eta: 2:31:14, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0581, loss: 0.0581 +2025-06-24 21:45:48,667 - pyskl - INFO - Epoch [119][700/1281] lr: 2.616e-03, eta: 2:30:51, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0544, loss: 0.0544 +2025-06-24 21:46:10,931 - pyskl - INFO - Epoch [119][800/1281] lr: 2.603e-03, eta: 2:30:29, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0582, loss: 0.0582 +2025-06-24 21:46:33,016 - pyskl - INFO - Epoch [119][900/1281] lr: 2.591e-03, eta: 2:30:06, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0591, loss: 0.0591 +2025-06-24 21:46:55,123 - pyskl - INFO - Epoch [119][1000/1281] lr: 2.578e-03, eta: 2:29:44, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.0785, loss: 0.0785 +2025-06-24 21:47:17,544 - pyskl - INFO - Epoch [119][1100/1281] lr: 2.566e-03, eta: 2:29:21, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0634, loss: 0.0634 +2025-06-24 21:47:39,943 - pyskl - INFO - Epoch [119][1200/1281] lr: 2.554e-03, eta: 2:28:59, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0771, loss: 0.0771 +2025-06-24 21:47:58,652 - pyskl - INFO - Saving checkpoint at 119 epochs +2025-06-24 21:48:42,842 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:48:42,910 - pyskl - INFO - +top1_acc 0.9312 +top5_acc 0.9950 +2025-06-24 21:48:42,910 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:48:42,919 - pyskl - INFO - +mean_acc 0.9033 +2025-06-24 21:48:42,923 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_117.pth was removed +2025-06-24 21:48:43,118 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_119.pth. +2025-06-24 21:48:43,118 - pyskl - INFO - Best top1_acc is 0.9312 at 119 epoch. +2025-06-24 21:48:43,124 - pyskl - INFO - Epoch(val) [119][533] top1_acc: 0.9312, top5_acc: 0.9950, mean_class_accuracy: 0.9033 +2025-06-24 21:49:25,077 - pyskl - INFO - Epoch [120][100/1281] lr: 2.531e-03, eta: 2:28:18, time: 0.419, data_time: 0.186, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0688, loss: 0.0688 +2025-06-24 21:49:47,581 - pyskl - INFO - Epoch [120][200/1281] lr: 2.519e-03, eta: 2:27:56, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 0.9994, loss_cls: 0.0604, loss: 0.0604 +2025-06-24 21:50:09,999 - pyskl - INFO - Epoch [120][300/1281] lr: 2.507e-03, eta: 2:27:33, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0546, loss: 0.0546 +2025-06-24 21:50:32,558 - pyskl - INFO - Epoch [120][400/1281] lr: 2.494e-03, eta: 2:27:11, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0605, loss: 0.0605 +2025-06-24 21:50:54,833 - pyskl - INFO - Epoch [120][500/1281] lr: 2.482e-03, eta: 2:26:49, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0544, loss: 0.0544 +2025-06-24 21:51:17,134 - pyskl - INFO - Epoch [120][600/1281] lr: 2.470e-03, eta: 2:26:26, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0558, loss: 0.0558 +2025-06-24 21:51:39,814 - pyskl - INFO - Epoch [120][700/1281] lr: 2.458e-03, eta: 2:26:04, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0722, loss: 0.0722 +2025-06-24 21:52:02,240 - pyskl - INFO - Epoch [120][800/1281] lr: 2.446e-03, eta: 2:25:41, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0537, loss: 0.0537 +2025-06-24 21:52:24,777 - pyskl - INFO - Epoch [120][900/1281] lr: 2.433e-03, eta: 2:25:19, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0707, loss: 0.0707 +2025-06-24 21:52:47,168 - pyskl - INFO - Epoch [120][1000/1281] lr: 2.421e-03, eta: 2:24:56, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0612, loss: 0.0612 +2025-06-24 21:53:10,068 - pyskl - INFO - Epoch [120][1100/1281] lr: 2.409e-03, eta: 2:24:34, time: 0.229, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0588, loss: 0.0588 +2025-06-24 21:53:32,456 - pyskl - INFO - Epoch [120][1200/1281] lr: 2.397e-03, eta: 2:24:11, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0512, loss: 0.0512 +2025-06-24 21:53:51,747 - pyskl - INFO - Saving checkpoint at 120 epochs +2025-06-24 21:54:35,850 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:54:35,922 - pyskl - INFO - +top1_acc 0.9279 +top5_acc 0.9954 +2025-06-24 21:54:35,922 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:54:35,932 - pyskl - INFO - +mean_acc 0.8957 +2025-06-24 21:54:35,936 - pyskl - INFO - Epoch(val) [120][533] top1_acc: 0.9279, top5_acc: 0.9954, mean_class_accuracy: 0.8957 +2025-06-24 21:55:17,985 - pyskl - INFO - Epoch [121][100/1281] lr: 2.375e-03, eta: 2:23:31, time: 0.420, data_time: 0.185, memory: 4083, top1_acc: 0.9931, top5_acc: 0.9994, loss_cls: 0.0612, loss: 0.0612 +2025-06-24 21:55:40,366 - pyskl - INFO - Epoch [121][200/1281] lr: 2.363e-03, eta: 2:23:09, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0604, loss: 0.0604 +2025-06-24 21:56:02,899 - pyskl - INFO - Epoch [121][300/1281] lr: 2.351e-03, eta: 2:22:46, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0443, loss: 0.0443 +2025-06-24 21:56:25,730 - pyskl - INFO - Epoch [121][400/1281] lr: 2.340e-03, eta: 2:22:24, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0455, loss: 0.0455 +2025-06-24 21:56:48,179 - pyskl - INFO - Epoch [121][500/1281] lr: 2.328e-03, eta: 2:22:01, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0637, loss: 0.0637 +2025-06-24 21:57:10,603 - pyskl - INFO - Epoch [121][600/1281] lr: 2.316e-03, eta: 2:21:39, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0682, loss: 0.0682 +2025-06-24 21:57:33,113 - pyskl - INFO - Epoch [121][700/1281] lr: 2.304e-03, eta: 2:21:16, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0779, loss: 0.0779 +2025-06-24 21:57:55,437 - pyskl - INFO - Epoch [121][800/1281] lr: 2.292e-03, eta: 2:20:54, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0718, loss: 0.0718 +2025-06-24 21:58:17,970 - pyskl - INFO - Epoch [121][900/1281] lr: 2.280e-03, eta: 2:20:31, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0649, loss: 0.0649 +2025-06-24 21:58:40,201 - pyskl - INFO - Epoch [121][1000/1281] lr: 2.269e-03, eta: 2:20:09, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.0836, loss: 0.0836 +2025-06-24 21:59:02,381 - pyskl - INFO - Epoch [121][1100/1281] lr: 2.257e-03, eta: 2:19:46, time: 0.222, data_time: 0.001, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0641, loss: 0.0641 +2025-06-24 21:59:24,603 - pyskl - INFO - Epoch [121][1200/1281] lr: 2.245e-03, eta: 2:19:24, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0496, loss: 0.0496 +2025-06-24 21:59:43,611 - pyskl - INFO - Saving checkpoint at 121 epochs +2025-06-24 22:00:27,521 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:00:27,576 - pyskl - INFO - +top1_acc 0.9283 +top5_acc 0.9955 +2025-06-24 22:00:27,576 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:00:27,583 - pyskl - INFO - +mean_acc 0.9015 +2025-06-24 22:00:27,585 - pyskl - INFO - Epoch(val) [121][533] top1_acc: 0.9283, top5_acc: 0.9955, mean_class_accuracy: 0.9015 +2025-06-24 22:01:09,608 - pyskl - INFO - Epoch [122][100/1281] lr: 2.224e-03, eta: 2:18:43, time: 0.420, data_time: 0.187, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0548, loss: 0.0548 +2025-06-24 22:01:32,021 - pyskl - INFO - Epoch [122][200/1281] lr: 2.212e-03, eta: 2:18:21, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0556, loss: 0.0556 +2025-06-24 22:01:54,558 - pyskl - INFO - Epoch [122][300/1281] lr: 2.201e-03, eta: 2:17:59, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0672, loss: 0.0672 +2025-06-24 22:02:17,025 - pyskl - INFO - Epoch [122][400/1281] lr: 2.189e-03, eta: 2:17:36, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0546, loss: 0.0546 +2025-06-24 22:02:39,302 - pyskl - INFO - Epoch [122][500/1281] lr: 2.178e-03, eta: 2:17:14, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0439, loss: 0.0439 +2025-06-24 22:03:01,651 - pyskl - INFO - Epoch [122][600/1281] lr: 2.166e-03, eta: 2:16:51, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0388, loss: 0.0388 +2025-06-24 22:03:23,848 - pyskl - INFO - Epoch [122][700/1281] lr: 2.155e-03, eta: 2:16:28, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0391, loss: 0.0391 +2025-06-24 22:03:46,075 - pyskl - INFO - Epoch [122][800/1281] lr: 2.143e-03, eta: 2:16:06, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0586, loss: 0.0586 +2025-06-24 22:04:08,407 - pyskl - INFO - Epoch [122][900/1281] lr: 2.132e-03, eta: 2:15:43, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0746, loss: 0.0746 +2025-06-24 22:04:30,827 - pyskl - INFO - Epoch [122][1000/1281] lr: 2.120e-03, eta: 2:15:21, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0563, loss: 0.0563 +2025-06-24 22:04:53,396 - pyskl - INFO - Epoch [122][1100/1281] lr: 2.109e-03, eta: 2:14:59, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0493, loss: 0.0493 +2025-06-24 22:05:15,938 - pyskl - INFO - Epoch [122][1200/1281] lr: 2.098e-03, eta: 2:14:36, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0610, loss: 0.0610 +2025-06-24 22:05:34,693 - pyskl - INFO - Saving checkpoint at 122 epochs +2025-06-24 22:06:18,101 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:06:18,162 - pyskl - INFO - +top1_acc 0.9288 +top5_acc 0.9952 +2025-06-24 22:06:18,162 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:06:18,169 - pyskl - INFO - +mean_acc 0.9050 +2025-06-24 22:06:18,171 - pyskl - INFO - Epoch(val) [122][533] top1_acc: 0.9288, top5_acc: 0.9952, mean_class_accuracy: 0.9050 +2025-06-24 22:07:00,221 - pyskl - INFO - Epoch [123][100/1281] lr: 2.077e-03, eta: 2:13:56, time: 0.420, data_time: 0.185, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0376, loss: 0.0376 +2025-06-24 22:07:22,418 - pyskl - INFO - Epoch [123][200/1281] lr: 2.066e-03, eta: 2:13:33, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0346, loss: 0.0346 +2025-06-24 22:07:44,771 - pyskl - INFO - Epoch [123][300/1281] lr: 2.055e-03, eta: 2:13:11, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0509, loss: 0.0509 +2025-06-24 22:08:07,144 - pyskl - INFO - Epoch [123][400/1281] lr: 2.044e-03, eta: 2:12:48, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0484, loss: 0.0484 +2025-06-24 22:08:29,591 - pyskl - INFO - Epoch [123][500/1281] lr: 2.032e-03, eta: 2:12:26, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0644, loss: 0.0644 +2025-06-24 22:08:52,004 - pyskl - INFO - Epoch [123][600/1281] lr: 2.021e-03, eta: 2:12:03, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0477, loss: 0.0477 +2025-06-24 22:09:14,479 - pyskl - INFO - Epoch [123][700/1281] lr: 2.010e-03, eta: 2:11:41, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 0.9994, loss_cls: 0.0459, loss: 0.0459 +2025-06-24 22:09:37,249 - pyskl - INFO - Epoch [123][800/1281] lr: 1.999e-03, eta: 2:11:18, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0538, loss: 0.0538 +2025-06-24 22:09:59,617 - pyskl - INFO - Epoch [123][900/1281] lr: 1.988e-03, eta: 2:10:56, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0545, loss: 0.0545 +2025-06-24 22:10:22,312 - pyskl - INFO - Epoch [123][1000/1281] lr: 1.977e-03, eta: 2:10:34, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0490, loss: 0.0490 +2025-06-24 22:10:44,632 - pyskl - INFO - Epoch [123][1100/1281] lr: 1.966e-03, eta: 2:10:11, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0333, loss: 0.0333 +2025-06-24 22:11:06,989 - pyskl - INFO - Epoch [123][1200/1281] lr: 1.955e-03, eta: 2:09:49, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0500, loss: 0.0500 +2025-06-24 22:11:25,908 - pyskl - INFO - Saving checkpoint at 123 epochs +2025-06-24 22:12:10,323 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:12:10,379 - pyskl - INFO - +top1_acc 0.9338 +top5_acc 0.9953 +2025-06-24 22:12:10,379 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:12:10,387 - pyskl - INFO - +mean_acc 0.9064 +2025-06-24 22:12:10,392 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_119.pth was removed +2025-06-24 22:12:10,638 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_123.pth. +2025-06-24 22:12:10,638 - pyskl - INFO - Best top1_acc is 0.9338 at 123 epoch. +2025-06-24 22:12:10,642 - pyskl - INFO - Epoch(val) [123][533] top1_acc: 0.9338, top5_acc: 0.9953, mean_class_accuracy: 0.9064 +2025-06-24 22:12:52,605 - pyskl - INFO - Epoch [124][100/1281] lr: 1.935e-03, eta: 2:09:08, time: 0.420, data_time: 0.183, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0372, loss: 0.0372 +2025-06-24 22:13:15,223 - pyskl - INFO - Epoch [124][200/1281] lr: 1.924e-03, eta: 2:08:46, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0348, loss: 0.0348 +2025-06-24 22:13:37,424 - pyskl - INFO - Epoch [124][300/1281] lr: 1.913e-03, eta: 2:08:23, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0395, loss: 0.0395 +2025-06-24 22:13:59,840 - pyskl - INFO - Epoch [124][400/1281] lr: 1.902e-03, eta: 2:08:01, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0447, loss: 0.0447 +2025-06-24 22:14:22,172 - pyskl - INFO - Epoch [124][500/1281] lr: 1.892e-03, eta: 2:07:38, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0472, loss: 0.0472 +2025-06-24 22:14:44,461 - pyskl - INFO - Epoch [124][600/1281] lr: 1.881e-03, eta: 2:07:16, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0545, loss: 0.0545 +2025-06-24 22:15:06,761 - pyskl - INFO - Epoch [124][700/1281] lr: 1.870e-03, eta: 2:06:53, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0558, loss: 0.0558 +2025-06-24 22:15:28,924 - pyskl - INFO - Epoch [124][800/1281] lr: 1.859e-03, eta: 2:06:31, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0543, loss: 0.0543 +2025-06-24 22:15:51,267 - pyskl - INFO - Epoch [124][900/1281] lr: 1.849e-03, eta: 2:06:08, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0745, loss: 0.0745 +2025-06-24 22:16:13,554 - pyskl - INFO - Epoch [124][1000/1281] lr: 1.838e-03, eta: 2:05:46, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0621, loss: 0.0621 +2025-06-24 22:16:36,112 - pyskl - INFO - Epoch [124][1100/1281] lr: 1.827e-03, eta: 2:05:23, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0414, loss: 0.0414 +2025-06-24 22:16:58,543 - pyskl - INFO - Epoch [124][1200/1281] lr: 1.817e-03, eta: 2:05:01, time: 0.224, data_time: 0.001, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0468, loss: 0.0468 +2025-06-24 22:17:17,521 - pyskl - INFO - Saving checkpoint at 124 epochs +2025-06-24 22:18:01,318 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:18:01,373 - pyskl - INFO - +top1_acc 0.9313 +top5_acc 0.9951 +2025-06-24 22:18:01,374 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:18:01,380 - pyskl - INFO - +mean_acc 0.9063 +2025-06-24 22:18:01,382 - pyskl - INFO - Epoch(val) [124][533] top1_acc: 0.9313, top5_acc: 0.9951, mean_class_accuracy: 0.9063 +2025-06-24 22:18:42,949 - pyskl - INFO - Epoch [125][100/1281] lr: 1.797e-03, eta: 2:04:20, time: 0.416, data_time: 0.183, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0358, loss: 0.0358 +2025-06-24 22:19:05,537 - pyskl - INFO - Epoch [125][200/1281] lr: 1.787e-03, eta: 2:03:58, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0306, loss: 0.0306 +2025-06-24 22:19:27,548 - pyskl - INFO - Epoch [125][300/1281] lr: 1.776e-03, eta: 2:03:35, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0283, loss: 0.0283 +2025-06-24 22:19:49,739 - pyskl - INFO - Epoch [125][400/1281] lr: 1.766e-03, eta: 2:03:13, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0414, loss: 0.0414 +2025-06-24 22:20:11,809 - pyskl - INFO - Epoch [125][500/1281] lr: 1.755e-03, eta: 2:02:50, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0333, loss: 0.0333 +2025-06-24 22:20:33,960 - pyskl - INFO - Epoch [125][600/1281] lr: 1.745e-03, eta: 2:02:28, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0327, loss: 0.0327 +2025-06-24 22:20:56,212 - pyskl - INFO - Epoch [125][700/1281] lr: 1.735e-03, eta: 2:02:05, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0319, loss: 0.0319 +2025-06-24 22:21:18,520 - pyskl - INFO - Epoch [125][800/1281] lr: 1.724e-03, eta: 2:01:43, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0323, loss: 0.0323 +2025-06-24 22:21:40,863 - pyskl - INFO - Epoch [125][900/1281] lr: 1.714e-03, eta: 2:01:20, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0371, loss: 0.0371 +2025-06-24 22:22:03,243 - pyskl - INFO - Epoch [125][1000/1281] lr: 1.704e-03, eta: 2:00:58, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0518, loss: 0.0518 +2025-06-24 22:22:25,558 - pyskl - INFO - Epoch [125][1100/1281] lr: 1.693e-03, eta: 2:00:35, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0363, loss: 0.0363 +2025-06-24 22:22:47,735 - pyskl - INFO - Epoch [125][1200/1281] lr: 1.683e-03, eta: 2:00:13, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0429, loss: 0.0429 +2025-06-24 22:23:06,414 - pyskl - INFO - Saving checkpoint at 125 epochs +2025-06-24 22:23:50,580 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:23:50,642 - pyskl - INFO - +top1_acc 0.9330 +top5_acc 0.9965 +2025-06-24 22:23:50,642 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:23:50,650 - pyskl - INFO - +mean_acc 0.9079 +2025-06-24 22:23:50,652 - pyskl - INFO - Epoch(val) [125][533] top1_acc: 0.9330, top5_acc: 0.9965, mean_class_accuracy: 0.9079 +2025-06-24 22:24:33,347 - pyskl - INFO - Epoch [126][100/1281] lr: 1.665e-03, eta: 1:59:32, time: 0.427, data_time: 0.189, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0320, loss: 0.0320 +2025-06-24 22:24:55,745 - pyskl - INFO - Epoch [126][200/1281] lr: 1.654e-03, eta: 1:59:10, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0387, loss: 0.0387 +2025-06-24 22:25:17,858 - pyskl - INFO - Epoch [126][300/1281] lr: 1.644e-03, eta: 1:58:47, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0358, loss: 0.0358 +2025-06-24 22:25:40,385 - pyskl - INFO - Epoch [126][400/1281] lr: 1.634e-03, eta: 1:58:25, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0369, loss: 0.0369 +2025-06-24 22:26:02,788 - pyskl - INFO - Epoch [126][500/1281] lr: 1.624e-03, eta: 1:58:02, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0403, loss: 0.0403 +2025-06-24 22:26:25,143 - pyskl - INFO - Epoch [126][600/1281] lr: 1.614e-03, eta: 1:57:40, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0343, loss: 0.0343 +2025-06-24 22:26:47,401 - pyskl - INFO - Epoch [126][700/1281] lr: 1.604e-03, eta: 1:57:17, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0407, loss: 0.0407 +2025-06-24 22:27:10,062 - pyskl - INFO - Epoch [126][800/1281] lr: 1.594e-03, eta: 1:56:55, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0398, loss: 0.0398 +2025-06-24 22:27:32,385 - pyskl - INFO - Epoch [126][900/1281] lr: 1.584e-03, eta: 1:56:32, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0456, loss: 0.0456 +2025-06-24 22:27:54,853 - pyskl - INFO - Epoch [126][1000/1281] lr: 1.574e-03, eta: 1:56:10, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0330, loss: 0.0330 +2025-06-24 22:28:17,027 - pyskl - INFO - Epoch [126][1100/1281] lr: 1.564e-03, eta: 1:55:47, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0357, loss: 0.0357 +2025-06-24 22:28:39,092 - pyskl - INFO - Epoch [126][1200/1281] lr: 1.554e-03, eta: 1:55:25, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0441, loss: 0.0441 +2025-06-24 22:28:57,646 - pyskl - INFO - Saving checkpoint at 126 epochs +2025-06-24 22:29:41,456 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:29:41,525 - pyskl - INFO - +top1_acc 0.9370 +top5_acc 0.9965 +2025-06-24 22:29:41,525 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:29:41,534 - pyskl - INFO - +mean_acc 0.9129 +2025-06-24 22:29:41,539 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_123.pth was removed +2025-06-24 22:29:41,731 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_126.pth. +2025-06-24 22:29:41,731 - pyskl - INFO - Best top1_acc is 0.9370 at 126 epoch. +2025-06-24 22:29:41,735 - pyskl - INFO - Epoch(val) [126][533] top1_acc: 0.9370, top5_acc: 0.9965, mean_class_accuracy: 0.9129 +2025-06-24 22:30:24,260 - pyskl - INFO - Epoch [127][100/1281] lr: 1.536e-03, eta: 1:54:45, time: 0.425, data_time: 0.186, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0401, loss: 0.0401 +2025-06-24 22:30:46,599 - pyskl - INFO - Epoch [127][200/1281] lr: 1.527e-03, eta: 1:54:22, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0281, loss: 0.0281 +2025-06-24 22:31:08,642 - pyskl - INFO - Epoch [127][300/1281] lr: 1.517e-03, eta: 1:54:00, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0377, loss: 0.0377 +2025-06-24 22:31:31,178 - pyskl - INFO - Epoch [127][400/1281] lr: 1.507e-03, eta: 1:53:37, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0385, loss: 0.0385 +2025-06-24 22:31:53,434 - pyskl - INFO - Epoch [127][500/1281] lr: 1.497e-03, eta: 1:53:15, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0285, loss: 0.0285 +2025-06-24 22:32:15,752 - pyskl - INFO - Epoch [127][600/1281] lr: 1.488e-03, eta: 1:52:52, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0283, loss: 0.0283 +2025-06-24 22:32:37,819 - pyskl - INFO - Epoch [127][700/1281] lr: 1.478e-03, eta: 1:52:30, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0389, loss: 0.0389 +2025-06-24 22:33:00,138 - pyskl - INFO - Epoch [127][800/1281] lr: 1.468e-03, eta: 1:52:07, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0282, loss: 0.0282 +2025-06-24 22:33:22,578 - pyskl - INFO - Epoch [127][900/1281] lr: 1.459e-03, eta: 1:51:45, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0269, loss: 0.0269 +2025-06-24 22:33:44,851 - pyskl - INFO - Epoch [127][1000/1281] lr: 1.449e-03, eta: 1:51:22, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0321, loss: 0.0321 +2025-06-24 22:34:07,077 - pyskl - INFO - Epoch [127][1100/1281] lr: 1.440e-03, eta: 1:51:00, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0284, loss: 0.0284 +2025-06-24 22:34:29,553 - pyskl - INFO - Epoch [127][1200/1281] lr: 1.430e-03, eta: 1:50:37, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0338, loss: 0.0338 +2025-06-24 22:34:48,351 - pyskl - INFO - Saving checkpoint at 127 epochs +2025-06-24 22:35:31,983 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:35:32,043 - pyskl - INFO - +top1_acc 0.9378 +top5_acc 0.9968 +2025-06-24 22:35:32,043 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:35:32,051 - pyskl - INFO - +mean_acc 0.9140 +2025-06-24 22:35:32,055 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_126.pth was removed +2025-06-24 22:35:32,220 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_127.pth. +2025-06-24 22:35:32,220 - pyskl - INFO - Best top1_acc is 0.9378 at 127 epoch. +2025-06-24 22:35:32,223 - pyskl - INFO - Epoch(val) [127][533] top1_acc: 0.9378, top5_acc: 0.9968, mean_class_accuracy: 0.9140 +2025-06-24 22:36:14,546 - pyskl - INFO - Epoch [128][100/1281] lr: 1.413e-03, eta: 1:49:57, time: 0.423, data_time: 0.191, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0332, loss: 0.0332 +2025-06-24 22:36:37,030 - pyskl - INFO - Epoch [128][200/1281] lr: 1.404e-03, eta: 1:49:34, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0280, loss: 0.0280 +2025-06-24 22:36:59,499 - pyskl - INFO - Epoch [128][300/1281] lr: 1.394e-03, eta: 1:49:12, time: 0.225, data_time: 0.001, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0242, loss: 0.0242 +2025-06-24 22:37:21,874 - pyskl - INFO - Epoch [128][400/1281] lr: 1.385e-03, eta: 1:48:49, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0279, loss: 0.0279 +2025-06-24 22:37:44,681 - pyskl - INFO - Epoch [128][500/1281] lr: 1.376e-03, eta: 1:48:27, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0292, loss: 0.0292 +2025-06-24 22:38:06,902 - pyskl - INFO - Epoch [128][600/1281] lr: 1.366e-03, eta: 1:48:04, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0250, loss: 0.0250 +2025-06-24 22:38:29,290 - pyskl - INFO - Epoch [128][700/1281] lr: 1.357e-03, eta: 1:47:42, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0271, loss: 0.0271 +2025-06-24 22:38:51,464 - pyskl - INFO - Epoch [128][800/1281] lr: 1.348e-03, eta: 1:47:19, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0279, loss: 0.0279 +2025-06-24 22:39:13,854 - pyskl - INFO - Epoch [128][900/1281] lr: 1.339e-03, eta: 1:46:57, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0372, loss: 0.0372 +2025-06-24 22:39:36,555 - pyskl - INFO - Epoch [128][1000/1281] lr: 1.329e-03, eta: 1:46:35, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0398, loss: 0.0398 +2025-06-24 22:39:58,549 - pyskl - INFO - Epoch [128][1100/1281] lr: 1.320e-03, eta: 1:46:12, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0260, loss: 0.0260 +2025-06-24 22:40:21,066 - pyskl - INFO - Epoch [128][1200/1281] lr: 1.311e-03, eta: 1:45:50, time: 0.225, data_time: 0.001, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0323, loss: 0.0323 +2025-06-24 22:40:40,203 - pyskl - INFO - Saving checkpoint at 128 epochs +2025-06-24 22:41:24,022 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:41:24,078 - pyskl - INFO - +top1_acc 0.9352 +top5_acc 0.9961 +2025-06-24 22:41:24,078 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:41:24,087 - pyskl - INFO - +mean_acc 0.9080 +2025-06-24 22:41:24,089 - pyskl - INFO - Epoch(val) [128][533] top1_acc: 0.9352, top5_acc: 0.9961, mean_class_accuracy: 0.9080 +2025-06-24 22:42:06,625 - pyskl - INFO - Epoch [129][100/1281] lr: 1.295e-03, eta: 1:45:09, time: 0.425, data_time: 0.187, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0233, loss: 0.0233 +2025-06-24 22:42:28,910 - pyskl - INFO - Epoch [129][200/1281] lr: 1.286e-03, eta: 1:44:47, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0236, loss: 0.0236 +2025-06-24 22:42:51,519 - pyskl - INFO - Epoch [129][300/1281] lr: 1.277e-03, eta: 1:44:24, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0389, loss: 0.0389 +2025-06-24 22:43:13,941 - pyskl - INFO - Epoch [129][400/1281] lr: 1.268e-03, eta: 1:44:02, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0294, loss: 0.0294 +2025-06-24 22:43:36,460 - pyskl - INFO - Epoch [129][500/1281] lr: 1.259e-03, eta: 1:43:39, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0332, loss: 0.0332 +2025-06-24 22:43:58,753 - pyskl - INFO - Epoch [129][600/1281] lr: 1.250e-03, eta: 1:43:17, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0255, loss: 0.0255 +2025-06-24 22:44:21,351 - pyskl - INFO - Epoch [129][700/1281] lr: 1.241e-03, eta: 1:42:54, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0328, loss: 0.0328 +2025-06-24 22:44:43,879 - pyskl - INFO - Epoch [129][800/1281] lr: 1.232e-03, eta: 1:42:32, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0314, loss: 0.0314 +2025-06-24 22:45:06,570 - pyskl - INFO - Epoch [129][900/1281] lr: 1.223e-03, eta: 1:42:09, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0340, loss: 0.0340 +2025-06-24 22:45:29,058 - pyskl - INFO - Epoch [129][1000/1281] lr: 1.214e-03, eta: 1:41:47, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0291, loss: 0.0291 +2025-06-24 22:45:51,635 - pyskl - INFO - Epoch [129][1100/1281] lr: 1.206e-03, eta: 1:41:25, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0236, loss: 0.0236 +2025-06-24 22:46:14,140 - pyskl - INFO - Epoch [129][1200/1281] lr: 1.197e-03, eta: 1:41:02, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0301, loss: 0.0301 +2025-06-24 22:46:33,328 - pyskl - INFO - Saving checkpoint at 129 epochs +2025-06-24 22:47:17,159 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:47:17,226 - pyskl - INFO - +top1_acc 0.9369 +top5_acc 0.9969 +2025-06-24 22:47:17,227 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:47:17,234 - pyskl - INFO - +mean_acc 0.9085 +2025-06-24 22:47:17,236 - pyskl - INFO - Epoch(val) [129][533] top1_acc: 0.9369, top5_acc: 0.9969, mean_class_accuracy: 0.9085 +2025-06-24 22:47:59,059 - pyskl - INFO - Epoch [130][100/1281] lr: 1.181e-03, eta: 1:40:22, time: 0.418, data_time: 0.182, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0405, loss: 0.0405 +2025-06-24 22:48:21,567 - pyskl - INFO - Epoch [130][200/1281] lr: 1.172e-03, eta: 1:39:59, time: 0.225, data_time: 0.001, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0338, loss: 0.0338 +2025-06-24 22:48:43,848 - pyskl - INFO - Epoch [130][300/1281] lr: 1.164e-03, eta: 1:39:37, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0248, loss: 0.0248 +2025-06-24 22:49:06,213 - pyskl - INFO - Epoch [130][400/1281] lr: 1.155e-03, eta: 1:39:14, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0231, loss: 0.0231 +2025-06-24 22:49:28,700 - pyskl - INFO - Epoch [130][500/1281] lr: 1.147e-03, eta: 1:38:52, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0238, loss: 0.0238 +2025-06-24 22:49:51,076 - pyskl - INFO - Epoch [130][600/1281] lr: 1.138e-03, eta: 1:38:29, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0238, loss: 0.0238 +2025-06-24 22:50:13,491 - pyskl - INFO - Epoch [130][700/1281] lr: 1.130e-03, eta: 1:38:07, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0292, loss: 0.0292 +2025-06-24 22:50:35,760 - pyskl - INFO - Epoch [130][800/1281] lr: 1.121e-03, eta: 1:37:44, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0280, loss: 0.0280 +2025-06-24 22:50:58,238 - pyskl - INFO - Epoch [130][900/1281] lr: 1.113e-03, eta: 1:37:22, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0350, loss: 0.0350 +2025-06-24 22:51:20,310 - pyskl - INFO - Epoch [130][1000/1281] lr: 1.104e-03, eta: 1:36:59, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0264, loss: 0.0264 +2025-06-24 22:51:42,578 - pyskl - INFO - Epoch [130][1100/1281] lr: 1.096e-03, eta: 1:36:37, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0260, loss: 0.0260 +2025-06-24 22:52:05,122 - pyskl - INFO - Epoch [130][1200/1281] lr: 1.088e-03, eta: 1:36:14, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0327, loss: 0.0327 +2025-06-24 22:52:23,869 - pyskl - INFO - Saving checkpoint at 130 epochs +2025-06-24 22:53:07,631 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:53:07,695 - pyskl - INFO - +top1_acc 0.9399 +top5_acc 0.9965 +2025-06-24 22:53:07,695 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:53:07,702 - pyskl - INFO - +mean_acc 0.9124 +2025-06-24 22:53:07,706 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_127.pth was removed +2025-06-24 22:53:07,868 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_130.pth. +2025-06-24 22:53:07,868 - pyskl - INFO - Best top1_acc is 0.9399 at 130 epoch. +2025-06-24 22:53:07,871 - pyskl - INFO - Epoch(val) [130][533] top1_acc: 0.9399, top5_acc: 0.9965, mean_class_accuracy: 0.9124 +2025-06-24 22:53:49,667 - pyskl - INFO - Epoch [131][100/1281] lr: 1.072e-03, eta: 1:35:34, time: 0.418, data_time: 0.183, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-24 22:54:12,309 - pyskl - INFO - Epoch [131][200/1281] lr: 1.064e-03, eta: 1:35:11, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0276, loss: 0.0276 +2025-06-24 22:54:34,549 - pyskl - INFO - Epoch [131][300/1281] lr: 1.056e-03, eta: 1:34:49, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0244, loss: 0.0244 +2025-06-24 22:54:56,962 - pyskl - INFO - Epoch [131][400/1281] lr: 1.048e-03, eta: 1:34:26, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0268, loss: 0.0268 +2025-06-24 22:55:19,041 - pyskl - INFO - Epoch [131][500/1281] lr: 1.040e-03, eta: 1:34:04, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0329, loss: 0.0329 +2025-06-24 22:55:41,187 - pyskl - INFO - Epoch [131][600/1281] lr: 1.031e-03, eta: 1:33:41, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0287, loss: 0.0287 +2025-06-24 22:56:03,578 - pyskl - INFO - Epoch [131][700/1281] lr: 1.023e-03, eta: 1:33:19, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0226, loss: 0.0226 +2025-06-24 22:56:26,078 - pyskl - INFO - Epoch [131][800/1281] lr: 1.015e-03, eta: 1:32:56, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0261, loss: 0.0261 +2025-06-24 22:56:48,485 - pyskl - INFO - Epoch [131][900/1281] lr: 1.007e-03, eta: 1:32:34, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0246, loss: 0.0246 +2025-06-24 22:57:11,016 - pyskl - INFO - Epoch [131][1000/1281] lr: 9.992e-04, eta: 1:32:11, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0323, loss: 0.0323 +2025-06-24 22:57:33,304 - pyskl - INFO - Epoch [131][1100/1281] lr: 9.912e-04, eta: 1:31:49, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0250, loss: 0.0250 +2025-06-24 22:57:55,671 - pyskl - INFO - Epoch [131][1200/1281] lr: 9.832e-04, eta: 1:31:26, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0229, loss: 0.0229 +2025-06-24 22:58:14,619 - pyskl - INFO - Saving checkpoint at 131 epochs +2025-06-24 22:58:58,647 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:58:58,743 - pyskl - INFO - +top1_acc 0.9367 +top5_acc 0.9966 +2025-06-24 22:58:58,743 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:58:58,755 - pyskl - INFO - +mean_acc 0.9112 +2025-06-24 22:58:58,757 - pyskl - INFO - Epoch(val) [131][533] top1_acc: 0.9367, top5_acc: 0.9966, mean_class_accuracy: 0.9112 +2025-06-24 22:59:41,002 - pyskl - INFO - Epoch [132][100/1281] lr: 9.689e-04, eta: 1:30:46, time: 0.422, data_time: 0.187, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0221, loss: 0.0221 +2025-06-24 23:00:03,529 - pyskl - INFO - Epoch [132][200/1281] lr: 9.610e-04, eta: 1:30:24, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-24 23:00:25,889 - pyskl - INFO - Epoch [132][300/1281] lr: 9.532e-04, eta: 1:30:01, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0236, loss: 0.0236 +2025-06-24 23:00:48,000 - pyskl - INFO - Epoch [132][400/1281] lr: 9.454e-04, eta: 1:29:39, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0228, loss: 0.0228 +2025-06-24 23:01:10,192 - pyskl - INFO - Epoch [132][500/1281] lr: 9.376e-04, eta: 1:29:16, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0251, loss: 0.0251 +2025-06-24 23:01:32,604 - pyskl - INFO - Epoch [132][600/1281] lr: 9.298e-04, eta: 1:28:54, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0253, loss: 0.0253 +2025-06-24 23:01:55,020 - pyskl - INFO - Epoch [132][700/1281] lr: 9.221e-04, eta: 1:28:31, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0219, loss: 0.0219 +2025-06-24 23:02:17,559 - pyskl - INFO - Epoch [132][800/1281] lr: 9.144e-04, eta: 1:28:09, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0261, loss: 0.0261 +2025-06-24 23:02:39,808 - pyskl - INFO - Epoch [132][900/1281] lr: 9.068e-04, eta: 1:27:46, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0214, loss: 0.0214 +2025-06-24 23:03:02,160 - pyskl - INFO - Epoch [132][1000/1281] lr: 8.991e-04, eta: 1:27:24, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-24 23:03:24,809 - pyskl - INFO - Epoch [132][1100/1281] lr: 8.915e-04, eta: 1:27:01, time: 0.226, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0228, loss: 0.0228 +2025-06-24 23:03:47,123 - pyskl - INFO - Epoch [132][1200/1281] lr: 8.840e-04, eta: 1:26:39, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0253, loss: 0.0253 +2025-06-24 23:04:05,668 - pyskl - INFO - Saving checkpoint at 132 epochs +2025-06-24 23:04:49,591 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:04:49,647 - pyskl - INFO - +top1_acc 0.9386 +top5_acc 0.9965 +2025-06-24 23:04:49,647 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:04:49,654 - pyskl - INFO - +mean_acc 0.9127 +2025-06-24 23:04:49,656 - pyskl - INFO - Epoch(val) [132][533] top1_acc: 0.9386, top5_acc: 0.9965, mean_class_accuracy: 0.9127 +2025-06-24 23:05:31,943 - pyskl - INFO - Epoch [133][100/1281] lr: 8.704e-04, eta: 1:25:58, time: 0.423, data_time: 0.190, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-24 23:05:54,490 - pyskl - INFO - Epoch [133][200/1281] lr: 8.629e-04, eta: 1:25:36, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-24 23:06:16,826 - pyskl - INFO - Epoch [133][300/1281] lr: 8.554e-04, eta: 1:25:13, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0218, loss: 0.0218 +2025-06-24 23:06:38,934 - pyskl - INFO - Epoch [133][400/1281] lr: 8.480e-04, eta: 1:24:51, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0252, loss: 0.0252 +2025-06-24 23:07:01,505 - pyskl - INFO - Epoch [133][500/1281] lr: 8.406e-04, eta: 1:24:28, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0254, loss: 0.0254 +2025-06-24 23:07:24,071 - pyskl - INFO - Epoch [133][600/1281] lr: 8.333e-04, eta: 1:24:06, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0270, loss: 0.0270 +2025-06-24 23:07:46,211 - pyskl - INFO - Epoch [133][700/1281] lr: 8.260e-04, eta: 1:23:43, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0236, loss: 0.0236 +2025-06-24 23:08:08,785 - pyskl - INFO - Epoch [133][800/1281] lr: 8.187e-04, eta: 1:23:21, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0291, loss: 0.0291 +2025-06-24 23:08:31,173 - pyskl - INFO - Epoch [133][900/1281] lr: 8.114e-04, eta: 1:22:58, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-24 23:08:53,241 - pyskl - INFO - Epoch [133][1000/1281] lr: 8.042e-04, eta: 1:22:36, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-24 23:09:15,545 - pyskl - INFO - Epoch [133][1100/1281] lr: 7.970e-04, eta: 1:22:13, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0236, loss: 0.0236 +2025-06-24 23:09:37,923 - pyskl - INFO - Epoch [133][1200/1281] lr: 7.898e-04, eta: 1:21:51, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0242, loss: 0.0242 +2025-06-24 23:09:56,633 - pyskl - INFO - Saving checkpoint at 133 epochs +2025-06-24 23:10:40,032 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:10:40,093 - pyskl - INFO - +top1_acc 0.9389 +top5_acc 0.9964 +2025-06-24 23:10:40,093 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:10:40,103 - pyskl - INFO - +mean_acc 0.9120 +2025-06-24 23:10:40,106 - pyskl - INFO - Epoch(val) [133][533] top1_acc: 0.9389, top5_acc: 0.9964, mean_class_accuracy: 0.9120 +2025-06-24 23:11:22,629 - pyskl - INFO - Epoch [134][100/1281] lr: 7.769e-04, eta: 1:21:10, time: 0.425, data_time: 0.191, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-24 23:11:45,259 - pyskl - INFO - Epoch [134][200/1281] lr: 7.699e-04, eta: 1:20:48, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0240, loss: 0.0240 +2025-06-24 23:12:07,607 - pyskl - INFO - Epoch [134][300/1281] lr: 7.628e-04, eta: 1:20:26, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0227, loss: 0.0227 +2025-06-24 23:12:30,000 - pyskl - INFO - Epoch [134][400/1281] lr: 7.558e-04, eta: 1:20:03, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0277, loss: 0.0277 +2025-06-24 23:12:52,375 - pyskl - INFO - Epoch [134][500/1281] lr: 7.488e-04, eta: 1:19:41, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0209, loss: 0.0209 +2025-06-24 23:13:14,474 - pyskl - INFO - Epoch [134][600/1281] lr: 7.419e-04, eta: 1:19:18, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-24 23:13:37,060 - pyskl - INFO - Epoch [134][700/1281] lr: 7.349e-04, eta: 1:18:56, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-24 23:13:59,291 - pyskl - INFO - Epoch [134][800/1281] lr: 7.281e-04, eta: 1:18:33, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-24 23:14:21,476 - pyskl - INFO - Epoch [134][900/1281] lr: 7.212e-04, eta: 1:18:11, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0232, loss: 0.0232 +2025-06-24 23:14:43,575 - pyskl - INFO - Epoch [134][1000/1281] lr: 7.144e-04, eta: 1:17:48, time: 0.221, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0200, loss: 0.0200 +2025-06-24 23:15:05,899 - pyskl - INFO - Epoch [134][1100/1281] lr: 7.076e-04, eta: 1:17:26, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0259, loss: 0.0259 +2025-06-24 23:15:28,679 - pyskl - INFO - Epoch [134][1200/1281] lr: 7.008e-04, eta: 1:17:03, time: 0.228, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-24 23:15:47,241 - pyskl - INFO - Saving checkpoint at 134 epochs +2025-06-24 23:16:31,105 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:16:31,163 - pyskl - INFO - +top1_acc 0.9390 +top5_acc 0.9969 +2025-06-24 23:16:31,163 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:16:31,170 - pyskl - INFO - +mean_acc 0.9145 +2025-06-24 23:16:31,172 - pyskl - INFO - Epoch(val) [134][533] top1_acc: 0.9390, top5_acc: 0.9969, mean_class_accuracy: 0.9145 +2025-06-24 23:17:14,191 - pyskl - INFO - Epoch [135][100/1281] lr: 6.887e-04, eta: 1:16:23, time: 0.430, data_time: 0.192, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0232, loss: 0.0232 +2025-06-24 23:17:36,765 - pyskl - INFO - Epoch [135][200/1281] lr: 6.820e-04, eta: 1:16:00, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-24 23:17:59,029 - pyskl - INFO - Epoch [135][300/1281] lr: 6.753e-04, eta: 1:15:38, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-24 23:18:21,371 - pyskl - INFO - Epoch [135][400/1281] lr: 6.687e-04, eta: 1:15:15, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-24 23:18:43,987 - pyskl - INFO - Epoch [135][500/1281] lr: 6.622e-04, eta: 1:14:53, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0223, loss: 0.0223 +2025-06-24 23:19:06,429 - pyskl - INFO - Epoch [135][600/1281] lr: 6.556e-04, eta: 1:14:30, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-24 23:19:28,806 - pyskl - INFO - Epoch [135][700/1281] lr: 6.491e-04, eta: 1:14:08, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-24 23:19:51,438 - pyskl - INFO - Epoch [135][800/1281] lr: 6.426e-04, eta: 1:13:45, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0279, loss: 0.0279 +2025-06-24 23:20:13,709 - pyskl - INFO - Epoch [135][900/1281] lr: 6.362e-04, eta: 1:13:23, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0228, loss: 0.0228 +2025-06-24 23:20:36,144 - pyskl - INFO - Epoch [135][1000/1281] lr: 6.297e-04, eta: 1:13:00, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0218, loss: 0.0218 +2025-06-24 23:20:58,670 - pyskl - INFO - Epoch [135][1100/1281] lr: 6.233e-04, eta: 1:12:38, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-24 23:21:21,355 - pyskl - INFO - Epoch [135][1200/1281] lr: 6.170e-04, eta: 1:12:16, time: 0.227, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-24 23:21:40,380 - pyskl - INFO - Saving checkpoint at 135 epochs +2025-06-24 23:22:24,407 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:22:24,462 - pyskl - INFO - +top1_acc 0.9384 +top5_acc 0.9964 +2025-06-24 23:22:24,462 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:22:24,469 - pyskl - INFO - +mean_acc 0.9131 +2025-06-24 23:22:24,470 - pyskl - INFO - Epoch(val) [135][533] top1_acc: 0.9384, top5_acc: 0.9964, mean_class_accuracy: 0.9131 +2025-06-24 23:23:07,386 - pyskl - INFO - Epoch [136][100/1281] lr: 6.056e-04, eta: 1:11:35, time: 0.429, data_time: 0.194, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-24 23:23:29,839 - pyskl - INFO - Epoch [136][200/1281] lr: 5.993e-04, eta: 1:11:13, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-24 23:23:52,040 - pyskl - INFO - Epoch [136][300/1281] lr: 5.931e-04, eta: 1:10:50, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-24 23:24:14,312 - pyskl - INFO - Epoch [136][400/1281] lr: 5.868e-04, eta: 1:10:28, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-24 23:24:36,486 - pyskl - INFO - Epoch [136][500/1281] lr: 5.807e-04, eta: 1:10:05, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-24 23:24:58,798 - pyskl - INFO - Epoch [136][600/1281] lr: 5.745e-04, eta: 1:09:43, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0217, loss: 0.0217 +2025-06-24 23:25:21,179 - pyskl - INFO - Epoch [136][700/1281] lr: 5.684e-04, eta: 1:09:20, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-24 23:25:43,530 - pyskl - INFO - Epoch [136][800/1281] lr: 5.623e-04, eta: 1:08:58, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-24 23:26:05,952 - pyskl - INFO - Epoch [136][900/1281] lr: 5.563e-04, eta: 1:08:35, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-24 23:26:27,936 - pyskl - INFO - Epoch [136][1000/1281] lr: 5.503e-04, eta: 1:08:13, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-24 23:26:50,195 - pyskl - INFO - Epoch [136][1100/1281] lr: 5.443e-04, eta: 1:07:50, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-24 23:27:12,615 - pyskl - INFO - Epoch [136][1200/1281] lr: 5.384e-04, eta: 1:07:28, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0240, loss: 0.0240 +2025-06-24 23:27:31,428 - pyskl - INFO - Saving checkpoint at 136 epochs +2025-06-24 23:28:14,887 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:28:14,962 - pyskl - INFO - +top1_acc 0.9390 +top5_acc 0.9962 +2025-06-24 23:28:14,962 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:28:14,974 - pyskl - INFO - +mean_acc 0.9123 +2025-06-24 23:28:14,978 - pyskl - INFO - Epoch(val) [136][533] top1_acc: 0.9390, top5_acc: 0.9962, mean_class_accuracy: 0.9123 +2025-06-24 23:28:58,047 - pyskl - INFO - Epoch [137][100/1281] lr: 5.277e-04, eta: 1:06:47, time: 0.431, data_time: 0.195, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0218, loss: 0.0218 +2025-06-24 23:29:20,439 - pyskl - INFO - Epoch [137][200/1281] lr: 5.218e-04, eta: 1:06:25, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-24 23:29:42,857 - pyskl - INFO - Epoch [137][300/1281] lr: 5.160e-04, eta: 1:06:02, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-24 23:30:05,112 - pyskl - INFO - Epoch [137][400/1281] lr: 5.102e-04, eta: 1:05:40, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0200, loss: 0.0200 +2025-06-24 23:30:27,429 - pyskl - INFO - Epoch [137][500/1281] lr: 5.044e-04, eta: 1:05:17, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0248, loss: 0.0248 +2025-06-24 23:30:50,131 - pyskl - INFO - Epoch [137][600/1281] lr: 4.987e-04, eta: 1:04:55, time: 0.227, data_time: 0.001, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0207, loss: 0.0207 +2025-06-24 23:31:12,549 - pyskl - INFO - Epoch [137][700/1281] lr: 4.930e-04, eta: 1:04:32, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0263, loss: 0.0263 +2025-06-24 23:31:34,848 - pyskl - INFO - Epoch [137][800/1281] lr: 4.873e-04, eta: 1:04:10, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-24 23:31:56,925 - pyskl - INFO - Epoch [137][900/1281] lr: 4.817e-04, eta: 1:03:47, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0204, loss: 0.0204 +2025-06-24 23:32:19,414 - pyskl - INFO - Epoch [137][1000/1281] lr: 4.761e-04, eta: 1:03:25, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0207, loss: 0.0207 +2025-06-24 23:32:41,881 - pyskl - INFO - Epoch [137][1100/1281] lr: 4.705e-04, eta: 1:03:02, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0223, loss: 0.0223 +2025-06-24 23:33:04,181 - pyskl - INFO - Epoch [137][1200/1281] lr: 4.650e-04, eta: 1:02:40, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-24 23:33:23,031 - pyskl - INFO - Saving checkpoint at 137 epochs +2025-06-24 23:34:07,155 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:34:07,215 - pyskl - INFO - +top1_acc 0.9414 +top5_acc 0.9967 +2025-06-24 23:34:07,215 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:34:07,223 - pyskl - INFO - +mean_acc 0.9182 +2025-06-24 23:34:07,227 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_130.pth was removed +2025-06-24 23:34:07,439 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_137.pth. +2025-06-24 23:34:07,439 - pyskl - INFO - Best top1_acc is 0.9414 at 137 epoch. +2025-06-24 23:34:07,443 - pyskl - INFO - Epoch(val) [137][533] top1_acc: 0.9414, top5_acc: 0.9967, mean_class_accuracy: 0.9182 +2025-06-24 23:34:49,350 - pyskl - INFO - Epoch [138][100/1281] lr: 4.550e-04, eta: 1:01:59, time: 0.419, data_time: 0.188, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0224, loss: 0.0224 +2025-06-24 23:35:11,708 - pyskl - INFO - Epoch [138][200/1281] lr: 4.496e-04, eta: 1:01:37, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-24 23:35:33,824 - pyskl - INFO - Epoch [138][300/1281] lr: 4.442e-04, eta: 1:01:14, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-24 23:35:56,139 - pyskl - INFO - Epoch [138][400/1281] lr: 4.388e-04, eta: 1:00:52, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-24 23:36:18,543 - pyskl - INFO - Epoch [138][500/1281] lr: 4.334e-04, eta: 1:00:29, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-24 23:36:40,617 - pyskl - INFO - Epoch [138][600/1281] lr: 4.281e-04, eta: 1:00:07, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-24 23:37:02,702 - pyskl - INFO - Epoch [138][700/1281] lr: 4.228e-04, eta: 0:59:44, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-24 23:37:25,373 - pyskl - INFO - Epoch [138][800/1281] lr: 4.176e-04, eta: 0:59:22, time: 0.227, data_time: 0.001, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0222, loss: 0.0222 +2025-06-24 23:37:47,255 - pyskl - INFO - Epoch [138][900/1281] lr: 4.124e-04, eta: 0:58:59, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-24 23:38:09,435 - pyskl - INFO - Epoch [138][1000/1281] lr: 4.072e-04, eta: 0:58:37, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-24 23:38:31,426 - pyskl - INFO - Epoch [138][1100/1281] lr: 4.020e-04, eta: 0:58:14, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-24 23:38:53,770 - pyskl - INFO - Epoch [138][1200/1281] lr: 3.969e-04, eta: 0:57:52, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-24 23:39:12,344 - pyskl - INFO - Saving checkpoint at 138 epochs +2025-06-24 23:39:55,180 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:39:55,235 - pyskl - INFO - +top1_acc 0.9392 +top5_acc 0.9965 +2025-06-24 23:39:55,235 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:39:55,242 - pyskl - INFO - +mean_acc 0.9146 +2025-06-24 23:39:55,244 - pyskl - INFO - Epoch(val) [138][533] top1_acc: 0.9392, top5_acc: 0.9965, mean_class_accuracy: 0.9146 +2025-06-24 23:40:36,915 - pyskl - INFO - Epoch [139][100/1281] lr: 3.877e-04, eta: 0:57:11, time: 0.417, data_time: 0.182, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0234, loss: 0.0234 +2025-06-24 23:40:58,914 - pyskl - INFO - Epoch [139][200/1281] lr: 3.827e-04, eta: 0:56:49, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0280, loss: 0.0280 +2025-06-24 23:41:21,245 - pyskl - INFO - Epoch [139][300/1281] lr: 3.777e-04, eta: 0:56:26, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-24 23:41:43,552 - pyskl - INFO - Epoch [139][400/1281] lr: 3.727e-04, eta: 0:56:04, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0231, loss: 0.0231 +2025-06-24 23:42:05,628 - pyskl - INFO - Epoch [139][500/1281] lr: 3.678e-04, eta: 0:55:41, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-24 23:42:27,856 - pyskl - INFO - Epoch [139][600/1281] lr: 3.628e-04, eta: 0:55:19, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0209, loss: 0.0209 +2025-06-24 23:42:49,929 - pyskl - INFO - Epoch [139][700/1281] lr: 3.580e-04, eta: 0:54:56, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-24 23:43:12,221 - pyskl - INFO - Epoch [139][800/1281] lr: 3.531e-04, eta: 0:54:34, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-24 23:43:34,604 - pyskl - INFO - Epoch [139][900/1281] lr: 3.483e-04, eta: 0:54:11, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0209, loss: 0.0209 +2025-06-24 23:43:57,302 - pyskl - INFO - Epoch [139][1000/1281] lr: 3.436e-04, eta: 0:53:49, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-24 23:44:19,519 - pyskl - INFO - Epoch [139][1100/1281] lr: 3.388e-04, eta: 0:53:27, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-24 23:44:41,812 - pyskl - INFO - Epoch [139][1200/1281] lr: 3.341e-04, eta: 0:53:04, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-24 23:45:00,806 - pyskl - INFO - Saving checkpoint at 139 epochs +2025-06-24 23:45:44,113 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:45:44,189 - pyskl - INFO - +top1_acc 0.9404 +top5_acc 0.9964 +2025-06-24 23:45:44,189 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:45:44,196 - pyskl - INFO - +mean_acc 0.9166 +2025-06-24 23:45:44,198 - pyskl - INFO - Epoch(val) [139][533] top1_acc: 0.9404, top5_acc: 0.9964, mean_class_accuracy: 0.9166 +2025-06-24 23:46:26,084 - pyskl - INFO - Epoch [140][100/1281] lr: 3.257e-04, eta: 0:52:23, time: 0.419, data_time: 0.184, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0240, loss: 0.0240 +2025-06-24 23:46:48,182 - pyskl - INFO - Epoch [140][200/1281] lr: 3.210e-04, eta: 0:52:01, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-24 23:47:10,401 - pyskl - INFO - Epoch [140][300/1281] lr: 3.165e-04, eta: 0:51:38, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-24 23:47:32,495 - pyskl - INFO - Epoch [140][400/1281] lr: 3.119e-04, eta: 0:51:16, time: 0.221, data_time: 0.001, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-24 23:47:55,052 - pyskl - INFO - Epoch [140][500/1281] lr: 3.074e-04, eta: 0:50:54, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0219, loss: 0.0219 +2025-06-24 23:48:17,268 - pyskl - INFO - Epoch [140][600/1281] lr: 3.029e-04, eta: 0:50:31, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-24 23:48:39,658 - pyskl - INFO - Epoch [140][700/1281] lr: 2.984e-04, eta: 0:50:09, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0166, loss: 0.0166 +2025-06-24 23:49:01,953 - pyskl - INFO - Epoch [140][800/1281] lr: 2.940e-04, eta: 0:49:46, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-24 23:49:24,111 - pyskl - INFO - Epoch [140][900/1281] lr: 2.896e-04, eta: 0:49:24, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0226, loss: 0.0226 +2025-06-24 23:49:46,349 - pyskl - INFO - Epoch [140][1000/1281] lr: 2.853e-04, eta: 0:49:01, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-24 23:50:08,352 - pyskl - INFO - Epoch [140][1100/1281] lr: 2.809e-04, eta: 0:48:39, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-24 23:50:31,215 - pyskl - INFO - Epoch [140][1200/1281] lr: 2.767e-04, eta: 0:48:16, time: 0.229, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-24 23:50:49,727 - pyskl - INFO - Saving checkpoint at 140 epochs +2025-06-24 23:51:32,961 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:51:33,037 - pyskl - INFO - +top1_acc 0.9393 +top5_acc 0.9965 +2025-06-24 23:51:33,037 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:51:33,045 - pyskl - INFO - +mean_acc 0.9155 +2025-06-24 23:51:33,047 - pyskl - INFO - Epoch(val) [140][533] top1_acc: 0.9393, top5_acc: 0.9965, mean_class_accuracy: 0.9155 +2025-06-24 23:52:14,875 - pyskl - INFO - Epoch [141][100/1281] lr: 2.690e-04, eta: 0:47:36, time: 0.418, data_time: 0.185, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-24 23:52:37,120 - pyskl - INFO - Epoch [141][200/1281] lr: 2.648e-04, eta: 0:47:13, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-24 23:52:59,229 - pyskl - INFO - Epoch [141][300/1281] lr: 2.606e-04, eta: 0:46:51, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-24 23:53:21,253 - pyskl - INFO - Epoch [141][400/1281] lr: 2.565e-04, eta: 0:46:28, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-24 23:53:43,618 - pyskl - INFO - Epoch [141][500/1281] lr: 2.524e-04, eta: 0:46:06, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-24 23:54:06,122 - pyskl - INFO - Epoch [141][600/1281] lr: 2.483e-04, eta: 0:45:43, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-24 23:54:28,287 - pyskl - INFO - Epoch [141][700/1281] lr: 2.443e-04, eta: 0:45:21, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0205, loss: 0.0205 +2025-06-24 23:54:50,775 - pyskl - INFO - Epoch [141][800/1281] lr: 2.402e-04, eta: 0:44:58, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0209, loss: 0.0209 +2025-06-24 23:55:13,235 - pyskl - INFO - Epoch [141][900/1281] lr: 2.363e-04, eta: 0:44:36, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-24 23:55:35,086 - pyskl - INFO - Epoch [141][1000/1281] lr: 2.323e-04, eta: 0:44:13, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0241, loss: 0.0241 +2025-06-24 23:55:57,099 - pyskl - INFO - Epoch [141][1100/1281] lr: 2.284e-04, eta: 0:43:51, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-24 23:56:19,578 - pyskl - INFO - Epoch [141][1200/1281] lr: 2.246e-04, eta: 0:43:28, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0167, loss: 0.0167 +2025-06-24 23:56:38,142 - pyskl - INFO - Saving checkpoint at 141 epochs +2025-06-24 23:57:22,078 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:57:22,133 - pyskl - INFO - +top1_acc 0.9413 +top5_acc 0.9969 +2025-06-24 23:57:22,133 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:57:22,139 - pyskl - INFO - +mean_acc 0.9166 +2025-06-24 23:57:22,140 - pyskl - INFO - Epoch(val) [141][533] top1_acc: 0.9413, top5_acc: 0.9969, mean_class_accuracy: 0.9166 +2025-06-24 23:58:04,593 - pyskl - INFO - Epoch [142][100/1281] lr: 2.176e-04, eta: 0:42:48, time: 0.424, data_time: 0.191, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-24 23:58:26,487 - pyskl - INFO - Epoch [142][200/1281] lr: 2.139e-04, eta: 0:42:25, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-24 23:58:48,380 - pyskl - INFO - Epoch [142][300/1281] lr: 2.101e-04, eta: 0:42:03, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-24 23:59:10,759 - pyskl - INFO - Epoch [142][400/1281] lr: 2.064e-04, eta: 0:41:40, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0221, loss: 0.0221 +2025-06-24 23:59:32,852 - pyskl - INFO - Epoch [142][500/1281] lr: 2.027e-04, eta: 0:41:18, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0275, loss: 0.0275 +2025-06-24 23:59:55,111 - pyskl - INFO - Epoch [142][600/1281] lr: 1.991e-04, eta: 0:40:55, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0205, loss: 0.0205 +2025-06-25 00:00:17,112 - pyskl - INFO - Epoch [142][700/1281] lr: 1.954e-04, eta: 0:40:33, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 00:00:39,071 - pyskl - INFO - Epoch [142][800/1281] lr: 1.919e-04, eta: 0:40:10, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 00:01:01,413 - pyskl - INFO - Epoch [142][900/1281] lr: 1.883e-04, eta: 0:39:48, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-25 00:01:23,703 - pyskl - INFO - Epoch [142][1000/1281] lr: 1.848e-04, eta: 0:39:25, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 00:01:45,807 - pyskl - INFO - Epoch [142][1100/1281] lr: 1.813e-04, eta: 0:39:03, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-25 00:02:08,025 - pyskl - INFO - Epoch [142][1200/1281] lr: 1.779e-04, eta: 0:38:40, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 00:02:26,859 - pyskl - INFO - Saving checkpoint at 142 epochs +2025-06-25 00:03:10,402 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:03:10,470 - pyskl - INFO - +top1_acc 0.9403 +top5_acc 0.9959 +2025-06-25 00:03:10,470 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:03:10,478 - pyskl - INFO - +mean_acc 0.9173 +2025-06-25 00:03:10,480 - pyskl - INFO - Epoch(val) [142][533] top1_acc: 0.9403, top5_acc: 0.9959, mean_class_accuracy: 0.9173 +2025-06-25 00:03:52,471 - pyskl - INFO - Epoch [143][100/1281] lr: 1.717e-04, eta: 0:38:00, time: 0.420, data_time: 0.184, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 00:04:15,054 - pyskl - INFO - Epoch [143][200/1281] lr: 1.683e-04, eta: 0:37:37, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 00:04:37,189 - pyskl - INFO - Epoch [143][300/1281] lr: 1.650e-04, eta: 0:37:15, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 00:04:59,516 - pyskl - INFO - Epoch [143][400/1281] lr: 1.617e-04, eta: 0:36:52, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 00:05:22,201 - pyskl - INFO - Epoch [143][500/1281] lr: 1.585e-04, eta: 0:36:30, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 00:05:44,533 - pyskl - INFO - Epoch [143][600/1281] lr: 1.552e-04, eta: 0:36:07, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0172, loss: 0.0172 +2025-06-25 00:06:07,009 - pyskl - INFO - Epoch [143][700/1281] lr: 1.520e-04, eta: 0:35:45, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 00:06:29,226 - pyskl - INFO - Epoch [143][800/1281] lr: 1.489e-04, eta: 0:35:22, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0230, loss: 0.0230 +2025-06-25 00:06:51,463 - pyskl - INFO - Epoch [143][900/1281] lr: 1.457e-04, eta: 0:35:00, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 00:07:13,422 - pyskl - INFO - Epoch [143][1000/1281] lr: 1.426e-04, eta: 0:34:37, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-25 00:07:36,004 - pyskl - INFO - Epoch [143][1100/1281] lr: 1.396e-04, eta: 0:34:15, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 00:07:57,969 - pyskl - INFO - Epoch [143][1200/1281] lr: 1.366e-04, eta: 0:33:52, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 00:08:16,847 - pyskl - INFO - Saving checkpoint at 143 epochs +2025-06-25 00:08:59,676 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:08:59,741 - pyskl - INFO - +top1_acc 0.9414 +top5_acc 0.9965 +2025-06-25 00:08:59,741 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:08:59,749 - pyskl - INFO - +mean_acc 0.9173 +2025-06-25 00:08:59,751 - pyskl - INFO - Epoch(val) [143][533] top1_acc: 0.9414, top5_acc: 0.9965, mean_class_accuracy: 0.9173 +2025-06-25 00:09:42,005 - pyskl - INFO - Epoch [144][100/1281] lr: 1.312e-04, eta: 0:33:12, time: 0.422, data_time: 0.188, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0220, loss: 0.0220 +2025-06-25 00:10:04,193 - pyskl - INFO - Epoch [144][200/1281] lr: 1.282e-04, eta: 0:32:49, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 00:10:26,324 - pyskl - INFO - Epoch [144][300/1281] lr: 1.253e-04, eta: 0:32:27, 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 00:10:48,584 - pyskl - INFO - Epoch [144][400/1281] lr: 1.224e-04, eta: 0:32:04, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 00:11:10,731 - pyskl - INFO - Epoch [144][500/1281] lr: 1.196e-04, eta: 0:31:42, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 00:11:32,891 - pyskl - INFO - Epoch [144][600/1281] lr: 1.168e-04, eta: 0:31:19, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0247, loss: 0.0247 +2025-06-25 00:11:55,113 - pyskl - INFO - Epoch [144][700/1281] lr: 1.140e-04, eta: 0:30:57, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0204, loss: 0.0204 +2025-06-25 00:12:17,233 - pyskl - INFO - Epoch [144][800/1281] lr: 1.113e-04, eta: 0:30:34, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 00:12:39,685 - pyskl - INFO - Epoch [144][900/1281] lr: 1.086e-04, eta: 0:30:12, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-25 00:13:02,067 - pyskl - INFO - Epoch [144][1000/1281] lr: 1.059e-04, eta: 0:29:50, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 00:13:24,099 - pyskl - INFO - Epoch [144][1100/1281] lr: 1.033e-04, eta: 0:29:27, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0227, loss: 0.0227 +2025-06-25 00:13:46,259 - pyskl - INFO - Epoch [144][1200/1281] lr: 1.007e-04, eta: 0:29:05, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 00:14:04,875 - pyskl - INFO - Saving checkpoint at 144 epochs +2025-06-25 00:14:48,376 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:14:48,432 - pyskl - INFO - +top1_acc 0.9411 +top5_acc 0.9964 +2025-06-25 00:14:48,432 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:14:48,438 - pyskl - INFO - +mean_acc 0.9177 +2025-06-25 00:14:48,440 - pyskl - INFO - Epoch(val) [144][533] top1_acc: 0.9411, top5_acc: 0.9964, mean_class_accuracy: 0.9177 +2025-06-25 00:15:30,767 - pyskl - INFO - Epoch [145][100/1281] lr: 9.605e-05, eta: 0:28:24, time: 0.423, data_time: 0.187, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 00:15:53,043 - pyskl - INFO - Epoch [145][200/1281] lr: 9.353e-05, eta: 0:28:01, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0221, loss: 0.0221 +2025-06-25 00:16:15,557 - pyskl - INFO - Epoch [145][300/1281] lr: 9.106e-05, eta: 0:27:39, time: 0.225, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 00:16:37,928 - pyskl - INFO - Epoch [145][400/1281] lr: 8.861e-05, eta: 0:27:17, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 00:16:59,952 - pyskl - INFO - Epoch [145][500/1281] lr: 8.620e-05, eta: 0:26:54, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 00:17:22,201 - pyskl - INFO - Epoch [145][600/1281] lr: 8.382e-05, eta: 0:26:32, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 00:17:44,328 - pyskl - INFO - Epoch [145][700/1281] lr: 8.147e-05, eta: 0:26:09, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0183, loss: 0.0183 +2025-06-25 00:18:06,629 - pyskl - INFO - Epoch [145][800/1281] lr: 7.916e-05, eta: 0:25:47, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 00:18:28,771 - pyskl - INFO - Epoch [145][900/1281] lr: 7.688e-05, eta: 0:25:24, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 00:18:51,094 - pyskl - INFO - Epoch [145][1000/1281] lr: 7.463e-05, eta: 0:25:02, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0169, loss: 0.0169 +2025-06-25 00:19:13,167 - pyskl - INFO - Epoch [145][1100/1281] lr: 7.242e-05, eta: 0:24:39, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 00:19:35,764 - pyskl - INFO - Epoch [145][1200/1281] lr: 7.024e-05, eta: 0:24:17, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 00:19:54,269 - pyskl - INFO - Saving checkpoint at 145 epochs +2025-06-25 00:20:37,216 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:20:37,270 - pyskl - INFO - +top1_acc 0.9407 +top5_acc 0.9968 +2025-06-25 00:20:37,270 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:20:37,277 - pyskl - INFO - +mean_acc 0.9161 +2025-06-25 00:20:37,279 - pyskl - INFO - Epoch(val) [145][533] top1_acc: 0.9407, top5_acc: 0.9968, mean_class_accuracy: 0.9161 +2025-06-25 00:21:19,001 - pyskl - INFO - Epoch [146][100/1281] lr: 6.638e-05, eta: 0:23:36, time: 0.417, data_time: 0.186, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 00:21:41,408 - pyskl - INFO - Epoch [146][200/1281] lr: 6.429e-05, eta: 0:23:14, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 00:22:03,574 - pyskl - INFO - Epoch [146][300/1281] lr: 6.224e-05, eta: 0:22:51, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 00:22:25,808 - pyskl - INFO - Epoch [146][400/1281] lr: 6.022e-05, eta: 0:22:29, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-25 00:22:48,105 - pyskl - INFO - Epoch [146][500/1281] lr: 5.823e-05, eta: 0:22:06, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0224, loss: 0.0224 +2025-06-25 00:23:09,967 - pyskl - INFO - Epoch [146][600/1281] lr: 5.628e-05, eta: 0:21:44, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 00:23:31,995 - pyskl - INFO - Epoch [146][700/1281] lr: 5.436e-05, eta: 0:21:21, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 00:23:54,036 - pyskl - INFO - Epoch [146][800/1281] lr: 5.247e-05, eta: 0:20:59, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0170, loss: 0.0170 +2025-06-25 00:24:16,230 - pyskl - INFO - Epoch [146][900/1281] lr: 5.061e-05, eta: 0:20:36, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 00:24:38,668 - pyskl - INFO - Epoch [146][1000/1281] lr: 4.879e-05, eta: 0:20:14, time: 0.224, data_time: 0.001, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-25 00:25:00,669 - pyskl - INFO - Epoch [146][1100/1281] lr: 4.701e-05, eta: 0:19:51, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 00:25:23,188 - pyskl - INFO - Epoch [146][1200/1281] lr: 4.525e-05, eta: 0:19:29, time: 0.225, data_time: 0.001, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 00:25:41,894 - pyskl - INFO - Saving checkpoint at 146 epochs +2025-06-25 00:26:25,470 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:26:25,525 - pyskl - INFO - +top1_acc 0.9412 +top5_acc 0.9967 +2025-06-25 00:26:25,526 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:26:25,533 - pyskl - INFO - +mean_acc 0.9166 +2025-06-25 00:26:25,535 - pyskl - INFO - Epoch(val) [146][533] top1_acc: 0.9412, top5_acc: 0.9967, mean_class_accuracy: 0.9166 +2025-06-25 00:27:07,453 - pyskl - INFO - Epoch [147][100/1281] lr: 4.216e-05, eta: 0:18:48, time: 0.419, data_time: 0.183, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 00:27:29,948 - pyskl - INFO - Epoch [147][200/1281] lr: 4.050e-05, eta: 0:18:26, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0220, loss: 0.0220 +2025-06-25 00:27:52,526 - pyskl - INFO - Epoch [147][300/1281] lr: 3.887e-05, eta: 0:18:03, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-25 00:28:14,718 - pyskl - INFO - Epoch [147][400/1281] lr: 3.728e-05, eta: 0:17:41, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 00:28:36,916 - pyskl - INFO - Epoch [147][500/1281] lr: 3.572e-05, eta: 0:17:18, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 00:28:59,309 - pyskl - INFO - Epoch [147][600/1281] lr: 3.419e-05, eta: 0:16:56, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-25 00:29:21,806 - pyskl - INFO - Epoch [147][700/1281] lr: 3.270e-05, eta: 0:16:33, time: 0.225, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0183, loss: 0.0183 +2025-06-25 00:29:43,871 - pyskl - INFO - Epoch [147][800/1281] lr: 3.124e-05, eta: 0:16:11, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 00:30:06,236 - pyskl - INFO - Epoch [147][900/1281] lr: 2.981e-05, eta: 0:15:48, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 00:30:28,533 - pyskl - INFO - Epoch [147][1000/1281] lr: 2.842e-05, eta: 0:15:26, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 00:30:50,888 - pyskl - INFO - Epoch [147][1100/1281] lr: 2.706e-05, eta: 0:15:04, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 00:31:13,286 - pyskl - INFO - Epoch [147][1200/1281] lr: 2.573e-05, eta: 0:14:41, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 00:31:31,854 - pyskl - INFO - Saving checkpoint at 147 epochs +2025-06-25 00:32:15,636 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:32:15,692 - pyskl - INFO - +top1_acc 0.9424 +top5_acc 0.9967 +2025-06-25 00:32:15,692 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:32:15,698 - pyskl - INFO - +mean_acc 0.9196 +2025-06-25 00:32:15,702 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_137.pth was removed +2025-06-25 00:32:15,875 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_147.pth. +2025-06-25 00:32:15,875 - pyskl - INFO - Best top1_acc is 0.9424 at 147 epoch. +2025-06-25 00:32:15,877 - pyskl - INFO - Epoch(val) [147][533] top1_acc: 0.9424, top5_acc: 0.9967, mean_class_accuracy: 0.9196 +2025-06-25 00:32:57,374 - pyskl - INFO - Epoch [148][100/1281] lr: 2.341e-05, eta: 0:14:00, time: 0.415, data_time: 0.183, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 00:33:19,472 - pyskl - INFO - Epoch [148][200/1281] lr: 2.218e-05, eta: 0:13:38, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-25 00:33:41,718 - pyskl - INFO - Epoch [148][300/1281] lr: 2.098e-05, eta: 0:13:15, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 00:34:03,931 - pyskl - INFO - Epoch [148][400/1281] lr: 1.981e-05, eta: 0:12:53, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 00:34:25,861 - pyskl - INFO - Epoch [148][500/1281] lr: 1.868e-05, eta: 0:12:31, 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 00:34:47,893 - pyskl - INFO - Epoch [148][600/1281] lr: 1.758e-05, eta: 0:12:08, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 00:35:09,778 - pyskl - INFO - Epoch [148][700/1281] lr: 1.651e-05, eta: 0:11:46, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 00:35:31,783 - pyskl - INFO - Epoch [148][800/1281] lr: 1.548e-05, eta: 0:11:23, 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 00:35:54,059 - pyskl - INFO - Epoch [148][900/1281] lr: 1.448e-05, eta: 0:11:01, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 00:36:16,143 - pyskl - INFO - Epoch [148][1000/1281] lr: 1.351e-05, eta: 0:10:38, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 00:36:38,271 - pyskl - INFO - Epoch [148][1100/1281] lr: 1.258e-05, eta: 0:10:16, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 00:37:00,882 - pyskl - INFO - Epoch [148][1200/1281] lr: 1.168e-05, eta: 0:09:53, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0233, loss: 0.0233 +2025-06-25 00:37:19,798 - pyskl - INFO - Saving checkpoint at 148 epochs +2025-06-25 00:38:02,882 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:38:02,938 - pyskl - INFO - +top1_acc 0.9425 +top5_acc 0.9967 +2025-06-25 00:38:02,938 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:38:02,945 - pyskl - INFO - +mean_acc 0.9189 +2025-06-25 00:38:02,950 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_147.pth was removed +2025-06-25 00:38:03,119 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_148.pth. +2025-06-25 00:38:03,119 - pyskl - INFO - Best top1_acc is 0.9425 at 148 epoch. +2025-06-25 00:38:03,122 - pyskl - INFO - Epoch(val) [148][533] top1_acc: 0.9425, top5_acc: 0.9967, mean_class_accuracy: 0.9189 +2025-06-25 00:38:45,406 - pyskl - INFO - Epoch [149][100/1281] lr: 1.013e-05, eta: 0:09:13, time: 0.423, data_time: 0.187, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 00:39:07,863 - pyskl - INFO - Epoch [149][200/1281] lr: 9.328e-06, eta: 0:08:50, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0207, loss: 0.0207 +2025-06-25 00:39:30,086 - pyskl - INFO - Epoch [149][300/1281] lr: 8.555e-06, eta: 0:08:28, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0183, loss: 0.0183 +2025-06-25 00:39:52,311 - pyskl - INFO - Epoch [149][400/1281] lr: 7.816e-06, eta: 0:08:05, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 00:40:14,696 - pyskl - INFO - Epoch [149][500/1281] lr: 7.110e-06, eta: 0:07:43, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 00:40:37,082 - pyskl - INFO - Epoch [149][600/1281] lr: 6.437e-06, eta: 0:07:20, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 00:40:59,255 - pyskl - INFO - Epoch [149][700/1281] lr: 5.798e-06, eta: 0:06:58, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0205, loss: 0.0205 +2025-06-25 00:41:21,394 - pyskl - INFO - Epoch [149][800/1281] lr: 5.192e-06, eta: 0:06:35, 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 00:41:43,754 - pyskl - INFO - Epoch [149][900/1281] lr: 4.620e-06, eta: 0:06:13, time: 0.224, data_time: 0.001, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-25 00:42:05,684 - pyskl - INFO - Epoch [149][1000/1281] lr: 4.081e-06, eta: 0:05:50, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 00:42:28,409 - pyskl - INFO - Epoch [149][1100/1281] lr: 3.576e-06, eta: 0:05:28, time: 0.227, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 00:42:50,460 - pyskl - INFO - Epoch [149][1200/1281] lr: 3.104e-06, eta: 0:05:05, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 00:43:09,140 - pyskl - INFO - Saving checkpoint at 149 epochs +2025-06-25 00:43:52,974 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:43:53,030 - pyskl - INFO - +top1_acc 0.9421 +top5_acc 0.9965 +2025-06-25 00:43:53,030 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:43:53,037 - pyskl - INFO - +mean_acc 0.9183 +2025-06-25 00:43:53,039 - pyskl - INFO - Epoch(val) [149][533] top1_acc: 0.9421, top5_acc: 0.9965, mean_class_accuracy: 0.9183 +2025-06-25 00:44:35,332 - pyskl - INFO - Epoch [150][100/1281] lr: 2.334e-06, eta: 0:04:25, time: 0.423, data_time: 0.190, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 00:44:57,529 - pyskl - INFO - Epoch [150][200/1281] lr: 1.956e-06, eta: 0:04:02, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0204, loss: 0.0204 +2025-06-25 00:45:19,884 - pyskl - INFO - Epoch [150][300/1281] lr: 1.611e-06, eta: 0:03:40, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 00:45:42,020 - pyskl - INFO - Epoch [150][400/1281] lr: 1.300e-06, eta: 0:03:17, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 00:46:04,368 - pyskl - INFO - Epoch [150][500/1281] lr: 1.022e-06, eta: 0:02:55, time: 0.223, data_time: 0.001, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0258, loss: 0.0258 +2025-06-25 00:46:26,424 - pyskl - INFO - Epoch [150][600/1281] lr: 7.771e-07, eta: 0:02:32, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0205, loss: 0.0205 +2025-06-25 00:46:48,371 - pyskl - INFO - Epoch [150][700/1281] lr: 5.659e-07, eta: 0:02:10, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0183, loss: 0.0183 +2025-06-25 00:47:10,784 - pyskl - INFO - Epoch [150][800/1281] lr: 3.881e-07, eta: 0:01:48, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 00:47:32,698 - pyskl - INFO - Epoch [150][900/1281] lr: 2.438e-07, eta: 0:01:25, 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 00:47:54,744 - pyskl - INFO - Epoch [150][1000/1281] lr: 1.329e-07, eta: 0:01:03, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 00:48:17,257 - pyskl - INFO - Epoch [150][1100/1281] lr: 5.534e-08, eta: 0:00:40, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0183, loss: 0.0183 +2025-06-25 00:48:39,690 - pyskl - INFO - Epoch [150][1200/1281] lr: 1.123e-08, eta: 0:00:18, time: 0.224, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 00:48:58,185 - pyskl - INFO - Saving checkpoint at 150 epochs +2025-06-25 00:49:41,397 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:49:41,452 - pyskl - INFO - +top1_acc 0.9426 +top5_acc 0.9966 +2025-06-25 00:49:41,452 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:49:41,459 - pyskl - INFO - +mean_acc 0.9193 +2025-06-25 00:49:41,463 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_148.pth was removed +2025-06-25 00:49:41,629 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_150.pth. +2025-06-25 00:49:41,629 - pyskl - INFO - Best top1_acc is 0.9426 at 150 epoch. +2025-06-25 00:49:41,632 - pyskl - INFO - Epoch(val) [150][533] top1_acc: 0.9426, top5_acc: 0.9966, mean_class_accuracy: 0.9193 +2025-06-25 00:49:46,044 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-06-25 00:55:01,544 - pyskl - INFO - Testing results of the last checkpoint +2025-06-25 00:55:01,545 - pyskl - INFO - top1_acc: 0.9444 +2025-06-25 00:55:01,545 - pyskl - INFO - top5_acc: 0.9969 +2025-06-25 00:55:01,545 - pyskl - INFO - mean_class_accuracy: 0.9227 +2025-06-25 00:55:01,545 - pyskl - INFO - load checkpoint from local path: ./work_dirs/test_aclnet/finegym/k_1/best_top1_acc_epoch_150.pth +2025-06-25 01:00:16,611 - pyskl - INFO - Testing results of the best checkpoint +2025-06-25 01:00:16,612 - pyskl - INFO - top1_acc: 0.9444 +2025-06-25 01:00:16,612 - pyskl - INFO - top5_acc: 0.9969 +2025-06-25 01:00:16,612 - pyskl - INFO - mean_class_accuracy: 0.9227