diff --git "a/finegym/k_2/20250528_104123.log" "b/finegym/k_2/20250528_104123.log" new file mode 100644--- /dev/null +++ "b/finegym/k_2/20250528_104123.log" @@ -0,0 +1,3461 @@ +2025-05-28 10:41:23,214 - 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+ +------------------------------------------------------------ + +2025-05-28 10:41:23,452 - pyskl - INFO - Config: modality = 'k' +graph = 'coco_new' +work_dir = './work_dirs/finegym/k_2' +model = dict( + type='RecognizerGCN', + backbone=dict( + type='GCN_Module_LLM', + llm_model='gpt4o', + llm_modality='k', + num_classes=99, + 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', + joint_cfg='coco_new', + num_classes=99, + in_channels=384, + work_dir='./work_dirs/finegym/k_2', + interval_epoch=5, + weight_1=0.05, + weight_2=0.1)) +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) + +2025-05-28 10:41:23,452 - pyskl - INFO - Set random seed to 763588011, deterministic: False +2025-05-28 10:41:31,010 - pyskl - INFO - 20484 videos remain after valid thresholding +2025-05-28 10:41:32,955 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-05-28 10:41:32,961 - pyskl - INFO - Start running, host: lhd@zkyd, work_dir: /home/lhd/pyskl/work_dirs/finegym/k_2 +2025-05-28 10:41:32,961 - 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 + -------------------- +2025-05-28 10:41:32,961 - pyskl - INFO - workflow: [('train', 1)], max: 150 epochs +2025-05-28 10:41:32,961 - pyskl - INFO - Checkpoints will be saved to /home/lhd/pyskl/work_dirs/finegym/k_2 by HardDiskBackend. +2025-05-28 10:42:33,369 - pyskl - INFO - Epoch [1][100/1281] lr: 2.500e-02, eta: 1 day, 8:13:23, time: 0.604, data_time: 0.180, memory: 8997, top1_acc: 0.0544, top5_acc: 0.2106, loss_cls: 9.2861, loss: 9.2861 +2025-05-28 10:43:15,036 - pyskl - INFO - Epoch [1][200/1281] lr: 2.500e-02, eta: 1 day, 3:12:40, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.0938, top5_acc: 0.3187, loss_cls: 8.4869, loss: 8.4869 +2025-05-28 10:43:56,714 - pyskl - INFO - Epoch [1][300/1281] lr: 2.500e-02, eta: 1 day, 1:32:05, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.1013, top5_acc: 0.3600, loss_cls: 8.1897, loss: 8.1897 +2025-05-28 10:44:38,288 - pyskl - INFO - Epoch [1][400/1281] lr: 2.500e-02, eta: 1 day, 0:40:37, time: 0.416, data_time: 0.000, memory: 8997, top1_acc: 0.1181, top5_acc: 0.4025, loss_cls: 8.0109, loss: 8.0109 +2025-05-28 10:45:19,950 - pyskl - INFO - Epoch [1][500/1281] lr: 2.500e-02, eta: 1 day, 0:10:01, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.1556, top5_acc: 0.4537, loss_cls: 7.7398, loss: 7.7398 +2025-05-28 10:46:01,770 - pyskl - INFO - Epoch [1][600/1281] lr: 2.500e-02, eta: 23:50:14, time: 0.418, data_time: 0.000, memory: 8997, top1_acc: 0.1775, top5_acc: 0.4963, loss_cls: 7.4315, loss: 7.4315 +2025-05-28 10:46:43,465 - pyskl - INFO - Epoch [1][700/1281] lr: 2.500e-02, eta: 23:35:20, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.2112, top5_acc: 0.5594, loss_cls: 7.1276, loss: 7.1276 +2025-05-28 10:47:25,083 - pyskl - INFO - Epoch [1][800/1281] lr: 2.500e-02, eta: 23:23:40, time: 0.416, data_time: 0.000, memory: 8997, top1_acc: 0.2412, top5_acc: 0.5750, loss_cls: 6.9353, loss: 6.9353 +2025-05-28 10:48:06,774 - pyskl - INFO - Epoch [1][900/1281] lr: 2.500e-02, eta: 23:14:42, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.2537, top5_acc: 0.5900, loss_cls: 6.9462, loss: 6.9462 +2025-05-28 10:48:48,452 - pyskl - INFO - Epoch [1][1000/1281] lr: 2.500e-02, eta: 23:07:21, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.2706, top5_acc: 0.6562, loss_cls: 6.5950, loss: 6.5950 +2025-05-28 10:49:30,079 - pyskl - INFO - Epoch [1][1100/1281] lr: 2.500e-02, eta: 23:01:04, time: 0.416, data_time: 0.000, memory: 8997, top1_acc: 0.3162, top5_acc: 0.6644, loss_cls: 6.3724, loss: 6.3724 +2025-05-28 10:50:11,850 - pyskl - INFO - Epoch [1][1200/1281] lr: 2.500e-02, eta: 22:56:05, time: 0.418, data_time: 0.000, memory: 8997, top1_acc: 0.3281, top5_acc: 0.7037, loss_cls: 6.1732, loss: 6.1732 +2025-05-28 10:50:46,270 - pyskl - INFO - Saving checkpoint at 1 epochs +2025-05-28 10:51:27,325 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 10:51:27,381 - pyskl - INFO - +top1_acc 0.2508 +top5_acc 0.5944 +2025-05-28 10:51:27,381 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 10:51:27,387 - pyskl - INFO - +mean_acc 0.1315 +2025-05-28 10:51:28,916 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_1.pth. +2025-05-28 10:51:28,917 - pyskl - INFO - Best top1_acc is 0.2508 at 1 epoch. +2025-05-28 10:51:28,924 - pyskl - INFO - Epoch(val) [1][533] top1_acc: 0.2508, top5_acc: 0.5944, mean_class_accuracy: 0.1315 +2025-05-28 10:52:28,401 - pyskl - INFO - Epoch [2][100/1281] lr: 2.500e-02, eta: 22:11:31, time: 0.595, data_time: 0.178, memory: 8997, top1_acc: 0.3563, top5_acc: 0.7375, loss_cls: 5.9245, loss: 5.9245 +2025-05-28 10:53:09,631 - pyskl - INFO - Epoch [2][200/1281] lr: 2.500e-02, eta: 22:09:26, time: 0.412, data_time: 0.000, memory: 8997, top1_acc: 0.3831, top5_acc: 0.7562, loss_cls: 5.8807, loss: 5.8807 +2025-05-28 10:53:51,187 - pyskl - INFO - Epoch [2][300/1281] lr: 2.500e-02, eta: 22:08:10, time: 0.416, data_time: 0.000, memory: 8997, top1_acc: 0.4037, top5_acc: 0.7856, loss_cls: 5.6306, loss: 5.6306 +2025-05-28 10:54:33,451 - pyskl - INFO - Epoch [2][400/1281] lr: 2.500e-02, eta: 22:08:19, time: 0.423, data_time: 0.000, memory: 8997, top1_acc: 0.4150, top5_acc: 0.8031, loss_cls: 5.5422, loss: 5.5422 +2025-05-28 10:55:15,316 - pyskl - INFO - Epoch [2][500/1281] lr: 2.499e-02, eta: 22:07:39, time: 0.419, data_time: 0.000, memory: 8997, top1_acc: 0.4338, top5_acc: 0.8056, loss_cls: 5.4500, loss: 5.4500 +2025-05-28 10:55:57,112 - pyskl - INFO - Epoch [2][600/1281] lr: 2.499e-02, eta: 22:06:52, time: 0.418, data_time: 0.000, memory: 8997, top1_acc: 0.4450, top5_acc: 0.8344, loss_cls: 5.2654, loss: 5.2654 +2025-05-28 10:56:38,848 - pyskl - INFO - Epoch [2][700/1281] lr: 2.499e-02, eta: 22:06:00, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.4756, top5_acc: 0.8550, loss_cls: 5.2138, loss: 5.2138 +2025-05-28 10:57:20,623 - pyskl - INFO - Epoch [2][800/1281] lr: 2.499e-02, eta: 22:05:13, time: 0.418, data_time: 0.000, memory: 8997, top1_acc: 0.4781, top5_acc: 0.8569, loss_cls: 4.9880, loss: 4.9880 +2025-05-28 10:58:02,251 - pyskl - INFO - Epoch [2][900/1281] lr: 2.499e-02, eta: 22:04:13, time: 0.416, data_time: 0.000, memory: 8997, top1_acc: 0.4738, top5_acc: 0.8681, loss_cls: 5.0496, loss: 5.0496 +2025-05-28 10:58:43,860 - pyskl - INFO - Epoch [2][1000/1281] lr: 2.499e-02, eta: 22:03:13, time: 0.416, data_time: 0.000, memory: 8997, top1_acc: 0.4925, top5_acc: 0.8700, loss_cls: 5.0470, loss: 5.0470 +2025-05-28 10:59:25,476 - pyskl - INFO - Epoch [2][1100/1281] lr: 2.499e-02, eta: 22:02:15, time: 0.416, data_time: 0.000, memory: 8997, top1_acc: 0.5300, top5_acc: 0.8919, loss_cls: 4.7819, loss: 4.7819 +2025-05-28 11:00:07,242 - pyskl - INFO - Epoch [2][1200/1281] lr: 2.499e-02, eta: 22:01:30, time: 0.418, data_time: 0.000, memory: 8997, top1_acc: 0.5613, top5_acc: 0.9056, loss_cls: 4.6021, loss: 4.6021 +2025-05-28 11:00:41,703 - pyskl - INFO - Saving checkpoint at 2 epochs +2025-05-28 11:01:22,970 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 11:01:23,027 - pyskl - INFO - +top1_acc 0.4834 +top5_acc 0.8162 +2025-05-28 11:01:23,027 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 11:01:23,035 - pyskl - INFO - +mean_acc 0.3120 +2025-05-28 11:01:23,087 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_1.pth was removed +2025-05-28 11:01:24,555 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_2.pth. +2025-05-28 11:01:24,556 - pyskl - INFO - Best top1_acc is 0.4834 at 2 epoch. +2025-05-28 11:01:24,559 - pyskl - INFO - Epoch(val) [2][533] top1_acc: 0.4834, top5_acc: 0.8162, mean_class_accuracy: 0.3120 +2025-05-28 11:02:24,191 - pyskl - INFO - Epoch [3][100/1281] lr: 2.499e-02, eta: 21:41:13, time: 0.596, data_time: 0.179, memory: 8997, top1_acc: 0.5569, top5_acc: 0.9225, loss_cls: 4.5937, loss: 4.5937 +2025-05-28 11:03:05,862 - pyskl - INFO - Epoch [3][200/1281] lr: 2.499e-02, eta: 21:41:04, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.5706, top5_acc: 0.9206, loss_cls: 4.6308, loss: 4.6308 +2025-05-28 11:03:47,544 - pyskl - INFO - Epoch [3][300/1281] lr: 2.499e-02, eta: 21:40:53, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.5900, top5_acc: 0.9250, loss_cls: 4.4436, loss: 4.4436 +2025-05-28 11:04:29,307 - pyskl - INFO - Epoch [3][400/1281] lr: 2.499e-02, eta: 21:40:45, time: 0.418, data_time: 0.000, memory: 8997, top1_acc: 0.5675, top5_acc: 0.9200, loss_cls: 4.5276, loss: 4.5276 +2025-05-28 11:05:10,989 - pyskl - INFO - Epoch [3][500/1281] lr: 2.498e-02, eta: 21:40:31, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.5825, top5_acc: 0.9306, loss_cls: 4.3766, loss: 4.3766 +2025-05-28 11:05:52,691 - pyskl - INFO - Epoch [3][600/1281] lr: 2.498e-02, eta: 21:40:15, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.6081, top5_acc: 0.9387, loss_cls: 4.1706, loss: 4.1706 +2025-05-28 11:06:34,479 - pyskl - INFO - Epoch [3][700/1281] lr: 2.498e-02, eta: 21:40:03, time: 0.418, data_time: 0.000, memory: 8997, top1_acc: 0.6125, top5_acc: 0.9437, loss_cls: 4.2791, loss: 4.2791 +2025-05-28 11:07:16,238 - pyskl - INFO - Epoch [3][800/1281] lr: 2.498e-02, eta: 21:39:48, time: 0.418, data_time: 0.000, memory: 8997, top1_acc: 0.6188, top5_acc: 0.9487, loss_cls: 4.1964, loss: 4.1964 +2025-05-28 11:07:57,986 - pyskl - INFO - Epoch [3][900/1281] lr: 2.498e-02, eta: 21:39:31, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.6131, top5_acc: 0.9500, loss_cls: 4.2399, loss: 4.2399 +2025-05-28 11:08:39,760 - pyskl - INFO - Epoch [3][1000/1281] lr: 2.498e-02, eta: 21:39:13, time: 0.418, data_time: 0.000, memory: 8997, top1_acc: 0.6175, top5_acc: 0.9450, loss_cls: 4.1735, loss: 4.1735 +2025-05-28 11:09:21,444 - pyskl - INFO - Epoch [3][1100/1281] lr: 2.498e-02, eta: 21:38:50, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.6269, top5_acc: 0.9406, loss_cls: 4.1626, loss: 4.1626 +2025-05-28 11:10:03,211 - pyskl - INFO - Epoch [3][1200/1281] lr: 2.498e-02, eta: 21:38:29, time: 0.418, data_time: 0.000, memory: 8997, top1_acc: 0.6238, top5_acc: 0.9456, loss_cls: 4.1065, loss: 4.1065 +2025-05-28 11:10:37,582 - pyskl - INFO - Saving checkpoint at 3 epochs +2025-05-28 11:11:18,942 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 11:11:18,998 - pyskl - INFO - +top1_acc 0.5824 +top5_acc 0.9396 +2025-05-28 11:11:18,998 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 11:11:19,006 - pyskl - INFO - +mean_acc 0.4339 +2025-05-28 11:11:19,059 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_2.pth was removed +2025-05-28 11:11:20,540 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_3.pth. +2025-05-28 11:11:20,541 - pyskl - INFO - Best top1_acc is 0.5824 at 3 epoch. +2025-05-28 11:11:20,545 - pyskl - INFO - Epoch(val) [3][533] top1_acc: 0.5824, top5_acc: 0.9396, mean_class_accuracy: 0.4339 +2025-05-28 11:12:20,344 - pyskl - INFO - Epoch [4][100/1281] lr: 2.497e-02, eta: 21:25:16, time: 0.598, data_time: 0.180, memory: 8997, top1_acc: 0.6375, top5_acc: 0.9625, loss_cls: 3.9745, loss: 3.9745 +2025-05-28 11:13:02,201 - pyskl - INFO - Epoch [4][200/1281] lr: 2.497e-02, eta: 21:25:16, time: 0.419, data_time: 0.000, memory: 8997, top1_acc: 0.6462, top5_acc: 0.9613, loss_cls: 4.0209, loss: 4.0209 +2025-05-28 11:13:43,899 - pyskl - INFO - Epoch [4][300/1281] lr: 2.497e-02, eta: 21:25:07, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.6594, top5_acc: 0.9631, loss_cls: 3.8859, loss: 3.8859 +2025-05-28 11:14:25,592 - pyskl - INFO - Epoch [4][400/1281] lr: 2.497e-02, eta: 21:24:56, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.6681, top5_acc: 0.9594, loss_cls: 3.8887, loss: 3.8887 +2025-05-28 11:15:07,281 - pyskl - INFO - Epoch [4][500/1281] lr: 2.497e-02, eta: 21:24:43, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.6681, top5_acc: 0.9600, loss_cls: 3.7719, loss: 3.7719 +2025-05-28 11:15:49,048 - pyskl - INFO - Epoch [4][600/1281] lr: 2.497e-02, eta: 21:24:33, time: 0.418, data_time: 0.000, memory: 8997, top1_acc: 0.6844, top5_acc: 0.9619, loss_cls: 3.7792, loss: 3.7792 +2025-05-28 11:16:31,527 - pyskl - INFO - Epoch [4][700/1281] lr: 2.497e-02, eta: 21:24:50, time: 0.425, data_time: 0.000, memory: 8997, top1_acc: 0.6687, top5_acc: 0.9613, loss_cls: 3.9117, loss: 3.9117 +2025-05-28 11:17:13,370 - pyskl - INFO - Epoch [4][800/1281] lr: 2.496e-02, eta: 21:24:39, time: 0.418, data_time: 0.000, memory: 8997, top1_acc: 0.7031, top5_acc: 0.9688, loss_cls: 3.7307, loss: 3.7307 +2025-05-28 11:17:55,056 - pyskl - INFO - Epoch [4][900/1281] lr: 2.496e-02, eta: 21:24:21, time: 0.417, data_time: 0.000, memory: 8997, top1_acc: 0.6644, top5_acc: 0.9644, loss_cls: 3.8645, loss: 3.8645 +2025-05-28 11:18:36,696 - pyskl - INFO - Epoch [4][1000/1281] lr: 2.496e-02, eta: 21:24:00, time: 0.416, data_time: 0.000, memory: 8997, top1_acc: 0.6806, top5_acc: 0.9631, loss_cls: 3.8653, loss: 3.8653 +2025-05-28 11:19:18,465 - pyskl - INFO - Epoch [4][1100/1281] lr: 2.496e-02, eta: 21:23:43, time: 0.418, data_time: 0.000, memory: 8997, top1_acc: 0.7006, top5_acc: 0.9606, loss_cls: 3.7939, loss: 3.7939 +2025-05-28 11:20:00,296 - pyskl - INFO - Epoch [4][1200/1281] lr: 2.496e-02, eta: 21:23:27, time: 0.418, data_time: 0.000, memory: 8997, top1_acc: 0.7000, top5_acc: 0.9706, loss_cls: 3.7847, loss: 3.7847 +2025-05-28 11:20:34,871 - pyskl - INFO - Saving checkpoint at 4 epochs +2025-05-28 11:21:16,093 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 11:21:16,148 - pyskl - INFO - +top1_acc 0.6452 +top5_acc 0.9566 +2025-05-28 11:21:16,149 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 11:21:16,155 - pyskl - INFO - +mean_acc 0.5062 +2025-05-28 11:21:16,208 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_3.pth was removed +2025-05-28 11:21:17,721 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_4.pth. +2025-05-28 11:21:17,722 - pyskl - INFO - Best top1_acc is 0.6452 at 4 epoch. +2025-05-28 11:21:17,726 - pyskl - INFO - Epoch(val) [4][533] top1_acc: 0.6452, top5_acc: 0.9566, mean_class_accuracy: 0.5062 +2025-05-28 11:22:17,091 - pyskl - INFO - Epoch [5][100/1281] lr: 2.495e-02, eta: 21:13:11, time: 0.594, data_time: 0.176, memory: 8999, top1_acc: 0.7013, top5_acc: 0.9700, loss_cls: 3.6699, loss: 3.6699 +2025-05-28 11:22:58,761 - pyskl - INFO - Epoch [5][200/1281] lr: 2.495e-02, eta: 21:12:59, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7331, top5_acc: 0.9788, loss_cls: 3.5272, loss: 3.5272 +2025-05-28 11:23:40,583 - pyskl - INFO - Epoch [5][300/1281] lr: 2.495e-02, eta: 21:12:50, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.7238, top5_acc: 0.9762, loss_cls: 3.6524, loss: 3.6524 +2025-05-28 11:24:22,297 - pyskl - INFO - Epoch [5][400/1281] lr: 2.495e-02, eta: 21:12:37, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7019, top5_acc: 0.9725, loss_cls: 3.5013, loss: 3.5013 +2025-05-28 11:25:03,981 - pyskl - INFO - Epoch [5][500/1281] lr: 2.495e-02, eta: 21:12:21, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7425, top5_acc: 0.9775, loss_cls: 3.4924, loss: 3.4924 +2025-05-28 11:25:45,619 - pyskl - INFO - Epoch [5][600/1281] lr: 2.495e-02, eta: 21:12:03, time: 0.416, data_time: 0.000, memory: 8999, top1_acc: 0.7306, top5_acc: 0.9769, loss_cls: 3.5988, loss: 3.5988 +2025-05-28 11:26:27,327 - pyskl - INFO - Epoch [5][700/1281] lr: 2.494e-02, eta: 21:11:47, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7462, top5_acc: 0.9756, loss_cls: 3.5218, loss: 3.5218 +2025-05-28 11:27:08,997 - pyskl - INFO - Epoch [5][800/1281] lr: 2.494e-02, eta: 21:11:28, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7506, top5_acc: 0.9794, loss_cls: 3.4239, loss: 3.4239 +2025-05-28 11:27:50,831 - pyskl - INFO - Epoch [5][900/1281] lr: 2.494e-02, eta: 21:11:14, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.7431, top5_acc: 0.9762, loss_cls: 3.4702, loss: 3.4702 +2025-05-28 11:28:32,562 - pyskl - INFO - Epoch [5][1000/1281] lr: 2.494e-02, eta: 21:10:56, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7388, top5_acc: 0.9825, loss_cls: 3.4141, loss: 3.4141 +2025-05-28 11:29:14,284 - pyskl - INFO - Epoch [5][1100/1281] lr: 2.494e-02, eta: 21:10:37, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7394, top5_acc: 0.9762, loss_cls: 3.4791, loss: 3.4791 +2025-05-28 11:29:56,073 - pyskl - INFO - Epoch [5][1200/1281] lr: 2.493e-02, eta: 21:10:19, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.7525, top5_acc: 0.9850, loss_cls: 3.3063, loss: 3.3063 +2025-05-28 11:30:30,443 - pyskl - INFO - Saving checkpoint at 5 epochs +2025-05-28 11:43:03,703 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 11:43:03,760 - pyskl - INFO - +top1_acc 0.6851 +top5_acc 0.9673 +2025-05-28 11:43:03,761 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 11:43:03,768 - pyskl - INFO - +mean_acc 0.6017 +2025-05-28 11:43:03,822 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_4.pth was removed +2025-05-28 11:43:05,341 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_5.pth. +2025-05-28 11:43:05,342 - pyskl - INFO - Best top1_acc is 0.6851 at 5 epoch. +2025-05-28 11:43:05,346 - pyskl - INFO - Epoch(val) [5][533] top1_acc: 0.6851, top5_acc: 0.9673, mean_class_accuracy: 0.6017 +2025-05-28 11:44:05,228 - pyskl - INFO - Epoch [6][100/1281] lr: 2.493e-02, eta: 21:02:15, time: 0.599, data_time: 0.180, memory: 8999, top1_acc: 0.7438, top5_acc: 0.9762, loss_cls: 3.4620, loss: 3.4620 +2025-05-28 11:44:46,928 - pyskl - INFO - Epoch [6][200/1281] lr: 2.493e-02, eta: 21:01:59, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7531, top5_acc: 0.9744, loss_cls: 3.4816, loss: 3.4816 +2025-05-28 11:45:28,629 - pyskl - INFO - Epoch [6][300/1281] lr: 2.492e-02, eta: 21:01:43, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7825, top5_acc: 0.9800, loss_cls: 3.2967, loss: 3.2967 +2025-05-28 11:46:10,301 - pyskl - INFO - Epoch [6][400/1281] lr: 2.492e-02, eta: 21:01:25, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7512, top5_acc: 0.9831, loss_cls: 3.3621, loss: 3.3621 +2025-05-28 11:46:51,972 - pyskl - INFO - Epoch [6][500/1281] lr: 2.492e-02, eta: 21:01:07, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7562, top5_acc: 0.9812, loss_cls: 3.3964, loss: 3.3964 +2025-05-28 11:47:33,720 - pyskl - INFO - Epoch [6][600/1281] lr: 2.492e-02, eta: 21:00:50, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7800, top5_acc: 0.9825, loss_cls: 3.3817, loss: 3.3817 +2025-05-28 11:48:15,443 - pyskl - INFO - Epoch [6][700/1281] lr: 2.492e-02, eta: 21:00:32, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7725, top5_acc: 0.9844, loss_cls: 3.2643, loss: 3.2643 +2025-05-28 11:48:57,098 - pyskl - INFO - Epoch [6][800/1281] lr: 2.491e-02, eta: 21:00:11, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7731, top5_acc: 0.9869, loss_cls: 3.2299, loss: 3.2299 +2025-05-28 11:49:38,709 - pyskl - INFO - Epoch [6][900/1281] lr: 2.491e-02, eta: 20:59:48, time: 0.416, data_time: 0.000, memory: 8999, top1_acc: 0.7812, top5_acc: 0.9856, loss_cls: 3.1703, loss: 3.1703 +2025-05-28 11:50:20,291 - pyskl - INFO - Epoch [6][1000/1281] lr: 2.491e-02, eta: 20:59:25, time: 0.416, data_time: 0.000, memory: 8999, top1_acc: 0.7956, top5_acc: 0.9869, loss_cls: 3.2079, loss: 3.2079 +2025-05-28 11:51:02,051 - pyskl - INFO - Epoch [6][1100/1281] lr: 2.491e-02, eta: 20:59:05, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.7681, top5_acc: 0.9856, loss_cls: 3.3336, loss: 3.3336 +2025-05-28 11:51:43,865 - pyskl - INFO - Epoch [6][1200/1281] lr: 2.490e-02, eta: 20:58:46, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.7694, top5_acc: 0.9819, loss_cls: 3.3423, loss: 3.3423 +2025-05-28 11:52:18,335 - pyskl - INFO - Saving checkpoint at 6 epochs +2025-05-28 11:52:59,650 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 11:52:59,707 - pyskl - INFO - +top1_acc 0.7531 +top5_acc 0.9768 +2025-05-28 11:52:59,707 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 11:52:59,714 - pyskl - INFO - +mean_acc 0.6418 +2025-05-28 11:52:59,767 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_5.pth was removed +2025-05-28 11:53:01,237 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_6.pth. +2025-05-28 11:53:01,238 - pyskl - INFO - Best top1_acc is 0.7531 at 6 epoch. +2025-05-28 11:53:01,242 - pyskl - INFO - Epoch(val) [6][533] top1_acc: 0.7531, top5_acc: 0.9768, mean_class_accuracy: 0.6418 +2025-05-28 11:54:01,182 - pyskl - INFO - Epoch [7][100/1281] lr: 2.490e-02, eta: 20:51:57, time: 0.599, data_time: 0.182, memory: 8999, top1_acc: 0.7963, top5_acc: 0.9919, loss_cls: 3.1905, loss: 3.1905 +2025-05-28 11:54:42,947 - pyskl - INFO - Epoch [7][200/1281] lr: 2.490e-02, eta: 20:51:40, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8100, top5_acc: 0.9906, loss_cls: 3.2108, loss: 3.2108 +2025-05-28 11:55:24,796 - pyskl - INFO - Epoch [7][300/1281] lr: 2.489e-02, eta: 20:51:24, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.7969, top5_acc: 0.9944, loss_cls: 3.2566, loss: 3.2566 +2025-05-28 11:56:06,661 - pyskl - INFO - Epoch [7][400/1281] lr: 2.489e-02, eta: 20:51:08, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8075, top5_acc: 0.9906, loss_cls: 3.1008, loss: 3.1008 +2025-05-28 11:56:48,418 - pyskl - INFO - Epoch [7][500/1281] lr: 2.489e-02, eta: 20:50:49, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.7781, top5_acc: 0.9862, loss_cls: 3.1705, loss: 3.1705 +2025-05-28 11:57:30,130 - pyskl - INFO - Epoch [7][600/1281] lr: 2.489e-02, eta: 20:50:29, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7975, top5_acc: 0.9869, loss_cls: 3.1210, loss: 3.1210 +2025-05-28 11:58:11,850 - pyskl - INFO - Epoch [7][700/1281] lr: 2.488e-02, eta: 20:50:08, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7913, top5_acc: 0.9888, loss_cls: 2.9866, loss: 2.9866 +2025-05-28 11:58:53,568 - pyskl - INFO - Epoch [7][800/1281] lr: 2.488e-02, eta: 20:49:47, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7919, top5_acc: 0.9856, loss_cls: 3.1676, loss: 3.1676 +2025-05-28 11:59:35,425 - pyskl - INFO - Epoch [7][900/1281] lr: 2.488e-02, eta: 20:49:28, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.7812, top5_acc: 0.9856, loss_cls: 3.0691, loss: 3.0691 +2025-05-28 12:00:17,938 - pyskl - INFO - Epoch [7][1000/1281] lr: 2.487e-02, eta: 20:49:22, time: 0.425, data_time: 0.000, memory: 8999, top1_acc: 0.7931, top5_acc: 0.9875, loss_cls: 3.0146, loss: 3.0146 +2025-05-28 12:00:59,948 - pyskl - INFO - Epoch [7][1100/1281] lr: 2.487e-02, eta: 20:49:06, time: 0.420, data_time: 0.000, memory: 8999, top1_acc: 0.8019, top5_acc: 0.9869, loss_cls: 3.0852, loss: 3.0852 +2025-05-28 12:01:41,896 - pyskl - INFO - Epoch [7][1200/1281] lr: 2.487e-02, eta: 20:48:47, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.7987, top5_acc: 0.9781, loss_cls: 3.1163, loss: 3.1163 +2025-05-28 12:02:16,423 - pyskl - INFO - Saving checkpoint at 7 epochs +2025-05-28 12:02:57,507 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 12:02:57,563 - pyskl - INFO - +top1_acc 0.7573 +top5_acc 0.9757 +2025-05-28 12:02:57,563 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 12:02:57,571 - pyskl - INFO - +mean_acc 0.6738 +2025-05-28 12:02:57,623 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_6.pth was removed +2025-05-28 12:02:59,097 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_7.pth. +2025-05-28 12:02:59,098 - pyskl - INFO - Best top1_acc is 0.7573 at 7 epoch. +2025-05-28 12:02:59,101 - pyskl - INFO - Epoch(val) [7][533] top1_acc: 0.7573, top5_acc: 0.9757, mean_class_accuracy: 0.6738 +2025-05-28 12:03:58,718 - pyskl - INFO - Epoch [8][100/1281] lr: 2.486e-02, eta: 20:42:42, time: 0.596, data_time: 0.178, memory: 8999, top1_acc: 0.8081, top5_acc: 0.9869, loss_cls: 3.0744, loss: 3.0744 +2025-05-28 12:04:40,378 - pyskl - INFO - Epoch [8][200/1281] lr: 2.486e-02, eta: 20:42:20, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8281, top5_acc: 0.9938, loss_cls: 2.9652, loss: 2.9652 +2025-05-28 12:05:22,031 - pyskl - INFO - Epoch [8][300/1281] lr: 2.486e-02, eta: 20:41:57, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8081, top5_acc: 0.9912, loss_cls: 3.0844, loss: 3.0844 +2025-05-28 12:06:03,732 - pyskl - INFO - Epoch [8][400/1281] lr: 2.485e-02, eta: 20:41:35, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8250, top5_acc: 0.9931, loss_cls: 2.8912, loss: 2.8912 +2025-05-28 12:06:45,406 - pyskl - INFO - Epoch [8][500/1281] lr: 2.485e-02, eta: 20:41:12, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.7863, top5_acc: 0.9894, loss_cls: 3.0276, loss: 3.0276 +2025-05-28 12:07:27,109 - pyskl - INFO - Epoch [8][600/1281] lr: 2.485e-02, eta: 20:40:49, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8231, top5_acc: 0.9894, loss_cls: 2.9284, loss: 2.9284 +2025-05-28 12:08:08,850 - pyskl - INFO - Epoch [8][700/1281] lr: 2.484e-02, eta: 20:40:27, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8119, top5_acc: 0.9906, loss_cls: 2.9979, loss: 2.9979 +2025-05-28 12:08:50,676 - pyskl - INFO - Epoch [8][800/1281] lr: 2.484e-02, eta: 20:40:05, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8125, top5_acc: 0.9956, loss_cls: 3.0099, loss: 3.0099 +2025-05-28 12:09:32,532 - pyskl - INFO - Epoch [8][900/1281] lr: 2.484e-02, eta: 20:39:44, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8037, top5_acc: 0.9856, loss_cls: 3.0141, loss: 3.0141 +2025-05-28 12:10:14,434 - pyskl - INFO - Epoch [8][1000/1281] lr: 2.483e-02, eta: 20:39:23, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8325, top5_acc: 0.9906, loss_cls: 2.8447, loss: 2.8447 +2025-05-28 12:10:56,360 - pyskl - INFO - Epoch [8][1100/1281] lr: 2.483e-02, eta: 20:39:03, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8137, top5_acc: 0.9900, loss_cls: 2.9533, loss: 2.9533 +2025-05-28 12:11:38,260 - pyskl - INFO - Epoch [8][1200/1281] lr: 2.483e-02, eta: 20:38:41, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8100, top5_acc: 0.9862, loss_cls: 2.9445, loss: 2.9445 +2025-05-28 12:12:12,750 - pyskl - INFO - Saving checkpoint at 8 epochs +2025-05-28 12:12:53,768 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 12:12:53,823 - pyskl - INFO - +top1_acc 0.7946 +top5_acc 0.9862 +2025-05-28 12:12:53,823 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 12:12:53,830 - pyskl - INFO - +mean_acc 0.7179 +2025-05-28 12:12:53,883 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_7.pth was removed +2025-05-28 12:12:55,376 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_8.pth. +2025-05-28 12:12:55,377 - pyskl - INFO - Best top1_acc is 0.7946 at 8 epoch. +2025-05-28 12:12:55,382 - pyskl - INFO - Epoch(val) [8][533] top1_acc: 0.7946, top5_acc: 0.9862, mean_class_accuracy: 0.7179 +2025-05-28 12:13:55,542 - pyskl - INFO - Epoch [9][100/1281] lr: 2.482e-02, eta: 20:33:25, time: 0.602, data_time: 0.183, memory: 8999, top1_acc: 0.8425, top5_acc: 0.9944, loss_cls: 2.8404, loss: 2.8404 +2025-05-28 12:14:37,286 - pyskl - INFO - Epoch [9][200/1281] lr: 2.482e-02, eta: 20:33:02, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8319, top5_acc: 0.9944, loss_cls: 2.7955, loss: 2.7955 +2025-05-28 12:15:19,008 - pyskl - INFO - Epoch [9][300/1281] lr: 2.481e-02, eta: 20:32:39, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8381, top5_acc: 0.9906, loss_cls: 2.7707, loss: 2.7707 +2025-05-28 12:16:00,669 - pyskl - INFO - Epoch [9][400/1281] lr: 2.481e-02, eta: 20:32:14, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8269, top5_acc: 0.9900, loss_cls: 2.9014, loss: 2.9014 +2025-05-28 12:16:42,324 - pyskl - INFO - Epoch [9][500/1281] lr: 2.481e-02, eta: 20:31:49, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8194, top5_acc: 0.9912, loss_cls: 2.9430, loss: 2.9430 +2025-05-28 12:17:23,993 - pyskl - INFO - Epoch [9][600/1281] lr: 2.480e-02, eta: 20:31:24, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8369, top5_acc: 0.9881, loss_cls: 2.8990, loss: 2.8990 +2025-05-28 12:18:05,687 - pyskl - INFO - Epoch [9][700/1281] lr: 2.480e-02, eta: 20:30:59, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8413, top5_acc: 0.9919, loss_cls: 2.8057, loss: 2.8057 +2025-05-28 12:18:47,322 - pyskl - INFO - Epoch [9][800/1281] lr: 2.480e-02, eta: 20:30:32, time: 0.416, data_time: 0.000, memory: 8999, top1_acc: 0.8413, top5_acc: 0.9906, loss_cls: 2.9379, loss: 2.9379 +2025-05-28 12:19:28,974 - pyskl - INFO - Epoch [9][900/1281] lr: 2.479e-02, eta: 20:30:06, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8287, top5_acc: 0.9900, loss_cls: 2.8400, loss: 2.8400 +2025-05-28 12:20:10,709 - pyskl - INFO - Epoch [9][1000/1281] lr: 2.479e-02, eta: 20:29:40, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8275, top5_acc: 0.9906, loss_cls: 2.9434, loss: 2.9434 +2025-05-28 12:20:52,400 - pyskl - INFO - Epoch [9][1100/1281] lr: 2.479e-02, eta: 20:29:14, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8156, top5_acc: 0.9938, loss_cls: 2.9201, loss: 2.9201 +2025-05-28 12:21:34,472 - pyskl - INFO - Epoch [9][1200/1281] lr: 2.478e-02, eta: 20:28:53, time: 0.421, data_time: 0.000, memory: 8999, top1_acc: 0.8063, top5_acc: 0.9894, loss_cls: 2.8662, loss: 2.8662 +2025-05-28 12:22:09,651 - pyskl - INFO - Saving checkpoint at 9 epochs +2025-05-28 12:22:50,615 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 12:22:50,670 - pyskl - INFO - +top1_acc 0.7825 +top5_acc 0.9827 +2025-05-28 12:22:50,670 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 12:22:50,677 - pyskl - INFO - +mean_acc 0.6761 +2025-05-28 12:22:50,679 - pyskl - INFO - Epoch(val) [9][533] top1_acc: 0.7825, top5_acc: 0.9827, mean_class_accuracy: 0.6761 +2025-05-28 12:23:50,438 - pyskl - INFO - Epoch [10][100/1281] lr: 2.477e-02, eta: 20:24:01, time: 0.598, data_time: 0.179, memory: 8999, top1_acc: 0.8462, top5_acc: 0.9894, loss_cls: 2.8438, loss: 2.8438 +2025-05-28 12:24:32,098 - pyskl - INFO - Epoch [10][200/1281] lr: 2.477e-02, eta: 20:23:35, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8369, top5_acc: 0.9925, loss_cls: 2.7987, loss: 2.7987 +2025-05-28 12:25:13,859 - pyskl - INFO - Epoch [10][300/1281] lr: 2.477e-02, eta: 20:23:11, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8250, top5_acc: 0.9956, loss_cls: 2.8323, loss: 2.8323 +2025-05-28 12:25:55,546 - pyskl - INFO - Epoch [10][400/1281] lr: 2.476e-02, eta: 20:22:45, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8469, top5_acc: 0.9944, loss_cls: 2.7146, loss: 2.7146 +2025-05-28 12:26:37,209 - pyskl - INFO - Epoch [10][500/1281] lr: 2.476e-02, eta: 20:22:18, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8394, top5_acc: 0.9950, loss_cls: 2.8474, loss: 2.8474 +2025-05-28 12:27:19,039 - pyskl - INFO - Epoch [10][600/1281] lr: 2.476e-02, eta: 20:21:54, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8387, top5_acc: 0.9956, loss_cls: 2.8100, loss: 2.8100 +2025-05-28 12:28:00,747 - pyskl - INFO - Epoch [10][700/1281] lr: 2.475e-02, eta: 20:21:28, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8350, top5_acc: 0.9894, loss_cls: 2.7884, loss: 2.7884 +2025-05-28 12:28:42,497 - pyskl - INFO - Epoch [10][800/1281] lr: 2.475e-02, eta: 20:21:02, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8356, top5_acc: 0.9931, loss_cls: 2.7224, loss: 2.7224 +2025-05-28 12:29:24,227 - pyskl - INFO - Epoch [10][900/1281] lr: 2.474e-02, eta: 20:20:35, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8419, top5_acc: 0.9950, loss_cls: 2.7054, loss: 2.7054 +2025-05-28 12:30:06,035 - pyskl - INFO - Epoch [10][1000/1281] lr: 2.474e-02, eta: 20:20:10, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8237, top5_acc: 0.9912, loss_cls: 2.8739, loss: 2.8739 +2025-05-28 12:30:47,753 - pyskl - INFO - Epoch [10][1100/1281] lr: 2.473e-02, eta: 20:19:43, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8394, top5_acc: 0.9944, loss_cls: 2.8184, loss: 2.8184 +2025-05-28 12:31:29,493 - pyskl - INFO - Epoch [10][1200/1281] lr: 2.473e-02, eta: 20:19:16, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8419, top5_acc: 0.9938, loss_cls: 2.7926, loss: 2.7926 +2025-05-28 12:32:03,874 - pyskl - INFO - Saving checkpoint at 10 epochs +2025-05-28 12:45:26,969 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 12:45:27,025 - pyskl - INFO - +top1_acc 0.8187 +top5_acc 0.9894 +2025-05-28 12:45:27,025 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 12:45:27,033 - pyskl - INFO - +mean_acc 0.7421 +2025-05-28 12:45:27,085 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_8.pth was removed +2025-05-28 12:45:28,576 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_10.pth. +2025-05-28 12:45:28,577 - pyskl - INFO - Best top1_acc is 0.8187 at 10 epoch. +2025-05-28 12:45:28,580 - pyskl - INFO - Epoch(val) [10][533] top1_acc: 0.8187, top5_acc: 0.9894, mean_class_accuracy: 0.7421 +2025-05-28 12:46:28,416 - pyskl - INFO - Epoch [11][100/1281] lr: 2.472e-02, eta: 20:14:48, time: 0.598, data_time: 0.180, memory: 8999, top1_acc: 0.8519, top5_acc: 0.9962, loss_cls: 2.6716, loss: 2.6716 +2025-05-28 12:47:10,209 - pyskl - INFO - Epoch [11][200/1281] lr: 2.472e-02, eta: 20:14:23, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8619, top5_acc: 0.9931, loss_cls: 2.6970, loss: 2.6970 +2025-05-28 12:47:52,075 - pyskl - INFO - Epoch [11][300/1281] lr: 2.471e-02, eta: 20:13:58, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8706, top5_acc: 0.9956, loss_cls: 2.5738, loss: 2.5738 +2025-05-28 12:48:33,784 - pyskl - INFO - Epoch [11][400/1281] lr: 2.471e-02, eta: 20:13:32, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8662, top5_acc: 0.9944, loss_cls: 2.6817, loss: 2.6817 +2025-05-28 12:49:15,490 - pyskl - INFO - Epoch [11][500/1281] lr: 2.471e-02, eta: 20:13:04, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8469, top5_acc: 0.9938, loss_cls: 2.6877, loss: 2.6877 +2025-05-28 12:49:57,247 - pyskl - INFO - Epoch [11][600/1281] lr: 2.470e-02, eta: 20:12:38, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8575, top5_acc: 0.9931, loss_cls: 2.7033, loss: 2.7033 +2025-05-28 12:50:39,006 - pyskl - INFO - Epoch [11][700/1281] lr: 2.470e-02, eta: 20:12:11, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8494, top5_acc: 0.9931, loss_cls: 2.7371, loss: 2.7371 +2025-05-28 12:51:20,741 - pyskl - INFO - Epoch [11][800/1281] lr: 2.469e-02, eta: 20:11:44, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8631, top5_acc: 0.9931, loss_cls: 2.7050, loss: 2.7050 +2025-05-28 12:52:02,565 - pyskl - INFO - Epoch [11][900/1281] lr: 2.469e-02, eta: 20:11:17, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8500, top5_acc: 0.9925, loss_cls: 2.7025, loss: 2.7025 +2025-05-28 12:52:44,278 - pyskl - INFO - Epoch [11][1000/1281] lr: 2.468e-02, eta: 20:10:49, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8369, top5_acc: 0.9938, loss_cls: 2.7687, loss: 2.7687 +2025-05-28 12:53:25,944 - pyskl - INFO - Epoch [11][1100/1281] lr: 2.468e-02, eta: 20:10:20, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8350, top5_acc: 0.9919, loss_cls: 2.6871, loss: 2.6871 +2025-05-28 12:54:07,896 - pyskl - INFO - Epoch [11][1200/1281] lr: 2.467e-02, eta: 20:09:55, time: 0.420, data_time: 0.000, memory: 8999, top1_acc: 0.8431, top5_acc: 0.9938, loss_cls: 2.7583, loss: 2.7583 +2025-05-28 12:54:42,322 - pyskl - INFO - Saving checkpoint at 11 epochs +2025-05-28 12:55:23,796 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 12:55:23,853 - pyskl - INFO - +top1_acc 0.8161 +top5_acc 0.9862 +2025-05-28 12:55:23,853 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 12:55:23,860 - pyskl - INFO - +mean_acc 0.7572 +2025-05-28 12:55:23,862 - pyskl - INFO - Epoch(val) [11][533] top1_acc: 0.8161, top5_acc: 0.9862, mean_class_accuracy: 0.7572 +2025-05-28 12:56:23,446 - pyskl - INFO - Epoch [12][100/1281] lr: 2.467e-02, eta: 20:05:43, time: 0.596, data_time: 0.177, memory: 8999, top1_acc: 0.8469, top5_acc: 0.9931, loss_cls: 2.6692, loss: 2.6692 +2025-05-28 12:57:05,176 - pyskl - INFO - Epoch [12][200/1281] lr: 2.466e-02, eta: 20:05:16, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8650, top5_acc: 0.9931, loss_cls: 2.7312, loss: 2.7312 +2025-05-28 12:57:46,954 - pyskl - INFO - Epoch [12][300/1281] lr: 2.466e-02, eta: 20:04:49, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8600, top5_acc: 0.9975, loss_cls: 2.6032, loss: 2.6032 +2025-05-28 12:58:28,248 - pyskl - INFO - Epoch [12][400/1281] lr: 2.465e-02, eta: 20:04:16, time: 0.413, data_time: 0.000, memory: 8999, top1_acc: 0.8600, top5_acc: 0.9938, loss_cls: 2.5772, loss: 2.5772 +2025-05-28 12:59:09,450 - pyskl - INFO - Epoch [12][500/1281] lr: 2.465e-02, eta: 20:03:42, time: 0.412, data_time: 0.000, memory: 8999, top1_acc: 0.8450, top5_acc: 0.9950, loss_cls: 2.6809, loss: 2.6809 +2025-05-28 12:59:50,830 - pyskl - INFO - Epoch [12][600/1281] lr: 2.464e-02, eta: 20:03:10, time: 0.414, data_time: 0.000, memory: 8999, top1_acc: 0.8556, top5_acc: 0.9950, loss_cls: 2.6595, loss: 2.6595 +2025-05-28 13:00:32,470 - pyskl - INFO - Epoch [12][700/1281] lr: 2.464e-02, eta: 20:02:41, time: 0.416, data_time: 0.000, memory: 8999, top1_acc: 0.8575, top5_acc: 0.9925, loss_cls: 2.6807, loss: 2.6807 +2025-05-28 13:01:14,151 - pyskl - INFO - Epoch [12][800/1281] lr: 2.463e-02, eta: 20:02:12, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8594, top5_acc: 0.9962, loss_cls: 2.4799, loss: 2.4799 +2025-05-28 13:01:56,030 - pyskl - INFO - Epoch [12][900/1281] lr: 2.463e-02, eta: 20:01:45, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8481, top5_acc: 0.9900, loss_cls: 2.7298, loss: 2.7298 +2025-05-28 13:02:37,739 - pyskl - INFO - Epoch [12][1000/1281] lr: 2.462e-02, eta: 20:01:16, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8369, top5_acc: 0.9931, loss_cls: 2.7481, loss: 2.7481 +2025-05-28 13:03:19,453 - pyskl - INFO - Epoch [12][1100/1281] lr: 2.462e-02, eta: 20:00:47, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8450, top5_acc: 0.9938, loss_cls: 2.7376, loss: 2.7376 +2025-05-28 13:04:01,321 - pyskl - INFO - Epoch [12][1200/1281] lr: 2.461e-02, eta: 20:00:20, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8681, top5_acc: 0.9944, loss_cls: 2.6088, loss: 2.6088 +2025-05-28 13:04:35,478 - pyskl - INFO - Saving checkpoint at 12 epochs +2025-05-28 13:05:16,508 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 13:05:16,563 - pyskl - INFO - +top1_acc 0.8204 +top5_acc 0.9860 +2025-05-28 13:05:16,563 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 13:05:16,569 - pyskl - INFO - +mean_acc 0.7492 +2025-05-28 13:05:16,623 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_10.pth was removed +2025-05-28 13:05:18,149 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_12.pth. +2025-05-28 13:05:18,150 - pyskl - INFO - Best top1_acc is 0.8204 at 12 epoch. +2025-05-28 13:05:18,155 - pyskl - INFO - Epoch(val) [12][533] top1_acc: 0.8204, top5_acc: 0.9860, mean_class_accuracy: 0.7492 +2025-05-28 13:06:19,075 - pyskl - INFO - Epoch [13][100/1281] lr: 2.460e-02, eta: 19:56:40, time: 0.609, data_time: 0.190, memory: 8999, top1_acc: 0.8556, top5_acc: 0.9925, loss_cls: 2.5884, loss: 2.5884 +2025-05-28 13:07:01,048 - pyskl - INFO - Epoch [13][200/1281] lr: 2.460e-02, eta: 19:56:15, time: 0.420, data_time: 0.000, memory: 8999, top1_acc: 0.8619, top5_acc: 0.9938, loss_cls: 2.5707, loss: 2.5707 +2025-05-28 13:07:42,899 - pyskl - INFO - Epoch [13][300/1281] lr: 2.459e-02, eta: 19:55:48, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8775, top5_acc: 0.9919, loss_cls: 2.5958, loss: 2.5958 +2025-05-28 13:08:24,610 - pyskl - INFO - Epoch [13][400/1281] lr: 2.459e-02, eta: 19:55:19, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8569, top5_acc: 0.9962, loss_cls: 2.5263, loss: 2.5263 +2025-05-28 13:09:06,272 - pyskl - INFO - Epoch [13][500/1281] lr: 2.458e-02, eta: 19:54:49, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8625, top5_acc: 0.9950, loss_cls: 2.6326, loss: 2.6326 +2025-05-28 13:09:47,975 - pyskl - INFO - Epoch [13][600/1281] lr: 2.458e-02, eta: 19:54:20, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8444, top5_acc: 0.9956, loss_cls: 2.7652, loss: 2.7652 +2025-05-28 13:10:29,792 - pyskl - INFO - Epoch [13][700/1281] lr: 2.457e-02, eta: 19:53:52, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8644, top5_acc: 0.9969, loss_cls: 2.5410, loss: 2.5410 +2025-05-28 13:11:11,627 - pyskl - INFO - Epoch [13][800/1281] lr: 2.457e-02, eta: 19:53:24, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8619, top5_acc: 0.9925, loss_cls: 2.5841, loss: 2.5841 +2025-05-28 13:11:53,376 - pyskl - INFO - Epoch [13][900/1281] lr: 2.456e-02, eta: 19:52:54, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8519, top5_acc: 0.9962, loss_cls: 2.6373, loss: 2.6373 +2025-05-28 13:12:35,243 - pyskl - INFO - Epoch [13][1000/1281] lr: 2.455e-02, eta: 19:52:26, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8550, top5_acc: 0.9931, loss_cls: 2.5927, loss: 2.5927 +2025-05-28 13:13:17,030 - pyskl - INFO - Epoch [13][1100/1281] lr: 2.455e-02, eta: 19:51:57, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8556, top5_acc: 0.9931, loss_cls: 2.7000, loss: 2.7000 +2025-05-28 13:13:58,796 - pyskl - INFO - Epoch [13][1200/1281] lr: 2.454e-02, eta: 19:51:28, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8694, top5_acc: 0.9950, loss_cls: 2.5000, loss: 2.5000 +2025-05-28 13:14:33,363 - pyskl - INFO - Saving checkpoint at 13 epochs +2025-05-28 13:15:14,595 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 13:15:14,651 - pyskl - INFO - +top1_acc 0.8564 +top5_acc 0.9896 +2025-05-28 13:15:14,651 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 13:15:14,658 - pyskl - INFO - +mean_acc 0.7948 +2025-05-28 13:15:14,718 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_12.pth was removed +2025-05-28 13:15:16,243 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_13.pth. +2025-05-28 13:15:16,243 - pyskl - INFO - Best top1_acc is 0.8564 at 13 epoch. +2025-05-28 13:15:16,247 - pyskl - INFO - Epoch(val) [13][533] top1_acc: 0.8564, top5_acc: 0.9896, mean_class_accuracy: 0.7948 +2025-05-28 13:16:16,295 - pyskl - INFO - Epoch [14][100/1281] lr: 2.453e-02, eta: 19:47:51, time: 0.600, data_time: 0.181, memory: 8999, top1_acc: 0.8656, top5_acc: 0.9950, loss_cls: 2.5415, loss: 2.5415 +2025-05-28 13:16:58,083 - pyskl - INFO - Epoch [14][200/1281] lr: 2.453e-02, eta: 19:47:22, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8788, top5_acc: 0.9938, loss_cls: 2.5119, loss: 2.5119 +2025-05-28 13:17:39,951 - pyskl - INFO - Epoch [14][300/1281] lr: 2.452e-02, eta: 19:46:54, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8706, top5_acc: 0.9925, loss_cls: 2.6471, loss: 2.6471 +2025-05-28 13:18:21,686 - pyskl - INFO - Epoch [14][400/1281] lr: 2.452e-02, eta: 19:46:25, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8756, top5_acc: 0.9938, loss_cls: 2.4818, loss: 2.4818 +2025-05-28 13:19:03,367 - pyskl - INFO - Epoch [14][500/1281] lr: 2.451e-02, eta: 19:45:55, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8688, top5_acc: 0.9950, loss_cls: 2.6001, loss: 2.6001 +2025-05-28 13:19:45,073 - pyskl - INFO - Epoch [14][600/1281] lr: 2.451e-02, eta: 19:45:25, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8688, top5_acc: 0.9956, loss_cls: 2.5147, loss: 2.5147 +2025-05-28 13:20:26,777 - pyskl - INFO - Epoch [14][700/1281] lr: 2.450e-02, eta: 19:44:54, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8769, top5_acc: 0.9944, loss_cls: 2.4976, loss: 2.4976 +2025-05-28 13:21:08,505 - pyskl - INFO - Epoch [14][800/1281] lr: 2.449e-02, eta: 19:44:24, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8881, top5_acc: 0.9950, loss_cls: 2.5623, loss: 2.5623 +2025-05-28 13:21:50,175 - pyskl - INFO - Epoch [14][900/1281] lr: 2.449e-02, eta: 19:43:53, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8575, top5_acc: 0.9944, loss_cls: 2.5655, loss: 2.5655 +2025-05-28 13:22:31,968 - pyskl - INFO - Epoch [14][1000/1281] lr: 2.448e-02, eta: 19:43:24, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8650, top5_acc: 0.9956, loss_cls: 2.4872, loss: 2.4872 +2025-05-28 13:23:13,684 - pyskl - INFO - Epoch [14][1100/1281] lr: 2.448e-02, eta: 19:42:53, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8544, top5_acc: 0.9950, loss_cls: 2.6125, loss: 2.6125 +2025-05-28 13:23:55,559 - pyskl - INFO - Epoch [14][1200/1281] lr: 2.447e-02, eta: 19:42:24, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8556, top5_acc: 0.9950, loss_cls: 2.6002, loss: 2.6002 +2025-05-28 13:24:30,037 - pyskl - INFO - Saving checkpoint at 14 epochs +2025-05-28 13:25:11,042 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 13:25:11,099 - pyskl - INFO - +top1_acc 0.8074 +top5_acc 0.9873 +2025-05-28 13:25:11,099 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 13:25:11,106 - pyskl - INFO - +mean_acc 0.7327 +2025-05-28 13:25:11,109 - pyskl - INFO - Epoch(val) [14][533] top1_acc: 0.8074, top5_acc: 0.9873, mean_class_accuracy: 0.7327 +2025-05-28 13:26:11,170 - pyskl - INFO - Epoch [15][100/1281] lr: 2.446e-02, eta: 19:38:59, time: 0.601, data_time: 0.182, memory: 8999, top1_acc: 0.8631, top5_acc: 0.9956, loss_cls: 2.5642, loss: 2.5642 +2025-05-28 13:26:52,834 - pyskl - INFO - Epoch [15][200/1281] lr: 2.445e-02, eta: 19:38:28, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8750, top5_acc: 0.9944, loss_cls: 2.6277, loss: 2.6277 +2025-05-28 13:27:35,213 - pyskl - INFO - Epoch [15][300/1281] lr: 2.445e-02, eta: 19:38:04, time: 0.424, data_time: 0.000, memory: 8999, top1_acc: 0.8888, top5_acc: 0.9975, loss_cls: 2.4411, loss: 2.4411 +2025-05-28 13:28:17,434 - pyskl - INFO - Epoch [15][400/1281] lr: 2.444e-02, eta: 19:37:38, time: 0.422, data_time: 0.000, memory: 8999, top1_acc: 0.8706, top5_acc: 0.9944, loss_cls: 2.5632, loss: 2.5632 +2025-05-28 13:28:59,256 - pyskl - INFO - Epoch [15][500/1281] lr: 2.444e-02, eta: 19:37:09, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8750, top5_acc: 0.9944, loss_cls: 2.4396, loss: 2.4396 +2025-05-28 13:29:41,085 - pyskl - INFO - Epoch [15][600/1281] lr: 2.443e-02, eta: 19:36:39, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8688, top5_acc: 0.9956, loss_cls: 2.4122, loss: 2.4122 +2025-05-28 13:30:22,751 - pyskl - INFO - Epoch [15][700/1281] lr: 2.442e-02, eta: 19:36:08, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8625, top5_acc: 0.9931, loss_cls: 2.6447, loss: 2.6447 +2025-05-28 13:31:04,493 - pyskl - INFO - Epoch [15][800/1281] lr: 2.442e-02, eta: 19:35:37, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8588, top5_acc: 0.9950, loss_cls: 2.5842, loss: 2.5842 +2025-05-28 13:31:46,114 - pyskl - INFO - Epoch [15][900/1281] lr: 2.441e-02, eta: 19:35:05, time: 0.416, data_time: 0.000, memory: 8999, top1_acc: 0.8712, top5_acc: 0.9925, loss_cls: 2.5110, loss: 2.5110 +2025-05-28 13:32:27,735 - pyskl - INFO - Epoch [15][1000/1281] lr: 2.441e-02, eta: 19:34:33, time: 0.416, data_time: 0.000, memory: 8999, top1_acc: 0.8794, top5_acc: 0.9962, loss_cls: 2.4921, loss: 2.4921 +2025-05-28 13:33:09,377 - pyskl - INFO - Epoch [15][1100/1281] lr: 2.440e-02, eta: 19:34:01, time: 0.416, data_time: 0.000, memory: 8999, top1_acc: 0.8700, top5_acc: 0.9950, loss_cls: 2.4386, loss: 2.4386 +2025-05-28 13:33:50,719 - pyskl - INFO - Epoch [15][1200/1281] lr: 2.439e-02, eta: 19:33:26, time: 0.413, data_time: 0.000, memory: 8999, top1_acc: 0.8869, top5_acc: 0.9956, loss_cls: 2.4470, loss: 2.4470 +2025-05-28 13:34:24,714 - pyskl - INFO - Saving checkpoint at 15 epochs +2025-05-28 13:48:01,892 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 13:48:01,950 - pyskl - INFO - +top1_acc 0.8138 +top5_acc 0.9851 +2025-05-28 13:48:01,950 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 13:48:01,956 - pyskl - INFO - +mean_acc 0.7487 +2025-05-28 13:48:01,958 - pyskl - INFO - Epoch(val) [15][533] top1_acc: 0.8138, top5_acc: 0.9851, mean_class_accuracy: 0.7487 +2025-05-28 13:49:01,789 - pyskl - INFO - Epoch [16][100/1281] lr: 2.438e-02, eta: 19:30:09, time: 0.598, data_time: 0.179, memory: 8999, top1_acc: 0.8838, top5_acc: 0.9950, loss_cls: 2.4957, loss: 2.4957 +2025-05-28 13:49:44,757 - pyskl - INFO - Epoch [16][200/1281] lr: 2.438e-02, eta: 19:29:49, time: 0.430, data_time: 0.000, memory: 8999, top1_acc: 0.8862, top5_acc: 0.9962, loss_cls: 2.4564, loss: 2.4564 +2025-05-28 13:50:26,675 - pyskl - INFO - Epoch [16][300/1281] lr: 2.437e-02, eta: 19:29:20, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8875, top5_acc: 0.9956, loss_cls: 2.4314, loss: 2.4314 +2025-05-28 13:51:08,399 - pyskl - INFO - Epoch [16][400/1281] lr: 2.436e-02, eta: 19:28:48, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8769, top5_acc: 0.9962, loss_cls: 2.4858, loss: 2.4858 +2025-05-28 13:51:50,297 - pyskl - INFO - Epoch [16][500/1281] lr: 2.436e-02, eta: 19:28:19, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8888, top5_acc: 0.9962, loss_cls: 2.4344, loss: 2.4344 +2025-05-28 13:52:32,148 - pyskl - INFO - Epoch [16][600/1281] lr: 2.435e-02, eta: 19:27:49, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8725, top5_acc: 0.9925, loss_cls: 2.5515, loss: 2.5515 +2025-05-28 13:53:13,971 - pyskl - INFO - Epoch [16][700/1281] lr: 2.434e-02, eta: 19:27:18, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8681, top5_acc: 0.9938, loss_cls: 2.5068, loss: 2.5068 +2025-05-28 13:53:55,777 - pyskl - INFO - Epoch [16][800/1281] lr: 2.434e-02, eta: 19:26:47, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8700, top5_acc: 0.9944, loss_cls: 2.5145, loss: 2.5145 +2025-05-28 13:54:37,472 - pyskl - INFO - Epoch [16][900/1281] lr: 2.433e-02, eta: 19:26:15, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8581, top5_acc: 0.9950, loss_cls: 2.5152, loss: 2.5152 +2025-05-28 13:55:19,170 - pyskl - INFO - Epoch [16][1000/1281] lr: 2.432e-02, eta: 19:25:43, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8812, top5_acc: 0.9950, loss_cls: 2.4359, loss: 2.4359 +2025-05-28 13:56:01,034 - pyskl - INFO - Epoch [16][1100/1281] lr: 2.432e-02, eta: 19:25:12, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8638, top5_acc: 0.9925, loss_cls: 2.5607, loss: 2.5607 +2025-05-28 13:56:42,672 - pyskl - INFO - Epoch [16][1200/1281] lr: 2.431e-02, eta: 19:24:40, time: 0.416, data_time: 0.000, memory: 8999, top1_acc: 0.8644, top5_acc: 0.9950, loss_cls: 2.5593, loss: 2.5593 +2025-05-28 13:57:16,941 - pyskl - INFO - Saving checkpoint at 16 epochs +2025-05-28 13:57:58,300 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 13:57:58,355 - pyskl - INFO - +top1_acc 0.8314 +top5_acc 0.9872 +2025-05-28 13:57:58,355 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 13:57:58,361 - pyskl - INFO - +mean_acc 0.7773 +2025-05-28 13:57:58,363 - pyskl - INFO - Epoch(val) [16][533] top1_acc: 0.8314, top5_acc: 0.9872, mean_class_accuracy: 0.7773 +2025-05-28 13:58:58,398 - pyskl - INFO - Epoch [17][100/1281] lr: 2.430e-02, eta: 19:21:33, time: 0.600, data_time: 0.180, memory: 8999, top1_acc: 0.8838, top5_acc: 0.9969, loss_cls: 2.4012, loss: 2.4012 +2025-05-28 13:59:40,181 - pyskl - INFO - Epoch [17][200/1281] lr: 2.429e-02, eta: 19:21:02, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8688, top5_acc: 0.9956, loss_cls: 2.4644, loss: 2.4644 +2025-05-28 14:00:21,846 - pyskl - INFO - Epoch [17][300/1281] lr: 2.428e-02, eta: 19:20:30, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8675, top5_acc: 0.9969, loss_cls: 2.4237, loss: 2.4237 +2025-05-28 14:01:03,504 - pyskl - INFO - Epoch [17][400/1281] lr: 2.428e-02, eta: 19:19:57, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8869, top5_acc: 0.9969, loss_cls: 2.4775, loss: 2.4775 +2025-05-28 14:01:45,171 - pyskl - INFO - Epoch [17][500/1281] lr: 2.427e-02, eta: 19:19:25, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8775, top5_acc: 0.9925, loss_cls: 2.5522, loss: 2.5522 +2025-05-28 14:02:26,836 - pyskl - INFO - Epoch [17][600/1281] lr: 2.426e-02, eta: 19:18:53, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8769, top5_acc: 0.9975, loss_cls: 2.4034, loss: 2.4034 +2025-05-28 14:03:08,541 - pyskl - INFO - Epoch [17][700/1281] lr: 2.426e-02, eta: 19:18:20, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8800, top5_acc: 0.9938, loss_cls: 2.4416, loss: 2.4416 +2025-05-28 14:03:50,203 - pyskl - INFO - Epoch [17][800/1281] lr: 2.425e-02, eta: 19:17:48, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8688, top5_acc: 0.9950, loss_cls: 2.4451, loss: 2.4451 +2025-05-28 14:04:31,870 - pyskl - INFO - Epoch [17][900/1281] lr: 2.424e-02, eta: 19:17:15, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8806, top5_acc: 0.9938, loss_cls: 2.4396, loss: 2.4396 +2025-05-28 14:05:13,761 - pyskl - INFO - Epoch [17][1000/1281] lr: 2.424e-02, eta: 19:16:44, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8850, top5_acc: 0.9944, loss_cls: 2.4784, loss: 2.4784 +2025-05-28 14:05:55,658 - pyskl - INFO - Epoch [17][1100/1281] lr: 2.423e-02, eta: 19:16:13, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8750, top5_acc: 0.9962, loss_cls: 2.4932, loss: 2.4932 +2025-05-28 14:06:37,318 - pyskl - INFO - Epoch [17][1200/1281] lr: 2.422e-02, eta: 19:15:40, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8900, top5_acc: 0.9962, loss_cls: 2.3478, loss: 2.3478 +2025-05-28 14:07:11,596 - pyskl - INFO - Saving checkpoint at 17 epochs +2025-05-28 14:07:52,655 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 14:07:52,711 - pyskl - INFO - +top1_acc 0.8177 +top5_acc 0.9822 +2025-05-28 14:07:52,711 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 14:07:52,718 - pyskl - INFO - +mean_acc 0.7781 +2025-05-28 14:07:52,720 - pyskl - INFO - Epoch(val) [17][533] top1_acc: 0.8177, top5_acc: 0.9822, mean_class_accuracy: 0.7781 +2025-05-28 14:08:52,580 - pyskl - INFO - Epoch [18][100/1281] lr: 2.421e-02, eta: 19:12:40, time: 0.599, data_time: 0.179, memory: 8999, top1_acc: 0.8888, top5_acc: 0.9975, loss_cls: 2.3315, loss: 2.3315 +2025-05-28 14:09:34,452 - pyskl - INFO - Epoch [18][200/1281] lr: 2.420e-02, eta: 19:12:09, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8825, top5_acc: 0.9969, loss_cls: 2.4110, loss: 2.4110 +2025-05-28 14:10:16,314 - pyskl - INFO - Epoch [18][300/1281] lr: 2.419e-02, eta: 19:11:38, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8812, top5_acc: 0.9956, loss_cls: 2.4245, loss: 2.4245 +2025-05-28 14:10:58,012 - pyskl - INFO - Epoch [18][400/1281] lr: 2.419e-02, eta: 19:11:05, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8912, top5_acc: 0.9950, loss_cls: 2.3088, loss: 2.3088 +2025-05-28 14:11:39,977 - pyskl - INFO - Epoch [18][500/1281] lr: 2.418e-02, eta: 19:10:35, time: 0.420, data_time: 0.000, memory: 8999, top1_acc: 0.8625, top5_acc: 0.9912, loss_cls: 2.4899, loss: 2.4899 +2025-05-28 14:12:21,764 - pyskl - INFO - Epoch [18][600/1281] lr: 2.417e-02, eta: 19:10:03, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8931, top5_acc: 0.9931, loss_cls: 2.3598, loss: 2.3598 +2025-05-28 14:13:03,663 - pyskl - INFO - Epoch [18][700/1281] lr: 2.417e-02, eta: 19:09:32, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8806, top5_acc: 0.9969, loss_cls: 2.4134, loss: 2.4134 +2025-05-28 14:13:45,470 - pyskl - INFO - Epoch [18][800/1281] lr: 2.416e-02, eta: 19:09:00, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8756, top5_acc: 0.9938, loss_cls: 2.5356, loss: 2.5356 +2025-05-28 14:14:27,054 - pyskl - INFO - Epoch [18][900/1281] lr: 2.415e-02, eta: 19:08:26, time: 0.416, data_time: 0.000, memory: 8999, top1_acc: 0.8706, top5_acc: 0.9925, loss_cls: 2.4107, loss: 2.4107 +2025-05-28 14:15:08,921 - pyskl - INFO - Epoch [18][1000/1281] lr: 2.414e-02, eta: 19:07:54, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8950, top5_acc: 0.9956, loss_cls: 2.3299, loss: 2.3299 +2025-05-28 14:15:50,750 - pyskl - INFO - Epoch [18][1100/1281] lr: 2.414e-02, eta: 19:07:22, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8812, top5_acc: 0.9950, loss_cls: 2.4173, loss: 2.4173 +2025-05-28 14:16:32,634 - pyskl - INFO - Epoch [18][1200/1281] lr: 2.413e-02, eta: 19:06:50, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8712, top5_acc: 0.9938, loss_cls: 2.4597, loss: 2.4597 +2025-05-28 14:17:07,046 - pyskl - INFO - Saving checkpoint at 18 epochs +2025-05-28 14:17:47,980 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 14:17:48,036 - pyskl - INFO - +top1_acc 0.8160 +top5_acc 0.9817 +2025-05-28 14:17:48,037 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 14:17:48,044 - pyskl - INFO - +mean_acc 0.7545 +2025-05-28 14:17:48,046 - pyskl - INFO - Epoch(val) [18][533] top1_acc: 0.8160, top5_acc: 0.9817, mean_class_accuracy: 0.7545 +2025-05-28 14:18:47,766 - pyskl - INFO - Epoch [19][100/1281] lr: 2.411e-02, eta: 19:03:55, time: 0.597, data_time: 0.179, memory: 8999, top1_acc: 0.8944, top5_acc: 0.9981, loss_cls: 2.3679, loss: 2.3679 +2025-05-28 14:19:29,377 - pyskl - INFO - Epoch [19][200/1281] lr: 2.411e-02, eta: 19:03:22, time: 0.416, data_time: 0.000, memory: 8999, top1_acc: 0.8888, top5_acc: 0.9938, loss_cls: 2.3522, loss: 2.3522 +2025-05-28 14:20:11,015 - pyskl - INFO - Epoch [19][300/1281] lr: 2.410e-02, eta: 19:02:49, time: 0.416, data_time: 0.000, memory: 8999, top1_acc: 0.8906, top5_acc: 0.9969, loss_cls: 2.3733, loss: 2.3733 +2025-05-28 14:20:52,648 - pyskl - INFO - Epoch [19][400/1281] lr: 2.409e-02, eta: 19:02:15, time: 0.416, data_time: 0.000, memory: 8999, top1_acc: 0.8969, top5_acc: 0.9969, loss_cls: 2.4403, loss: 2.4403 +2025-05-28 14:21:34,283 - pyskl - INFO - Epoch [19][500/1281] lr: 2.408e-02, eta: 19:01:42, time: 0.416, data_time: 0.000, memory: 8999, top1_acc: 0.8925, top5_acc: 0.9956, loss_cls: 2.3918, loss: 2.3918 +2025-05-28 14:22:15,986 - pyskl - INFO - Epoch [19][600/1281] lr: 2.408e-02, eta: 19:01:09, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8925, top5_acc: 0.9975, loss_cls: 2.3411, loss: 2.3411 +2025-05-28 14:22:57,792 - pyskl - INFO - Epoch [19][700/1281] lr: 2.407e-02, eta: 19:00:36, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8694, top5_acc: 0.9925, loss_cls: 2.5077, loss: 2.5077 +2025-05-28 14:23:39,448 - pyskl - INFO - Epoch [19][800/1281] lr: 2.406e-02, eta: 19:00:03, time: 0.417, data_time: 0.000, memory: 8999, top1_acc: 0.8869, top5_acc: 0.9944, loss_cls: 2.4201, loss: 2.4201 +2025-05-28 14:24:21,035 - pyskl - INFO - Epoch [19][900/1281] lr: 2.405e-02, eta: 18:59:29, time: 0.416, data_time: 0.000, memory: 8999, top1_acc: 0.8888, top5_acc: 0.9944, loss_cls: 2.3375, loss: 2.3375 +2025-05-28 14:25:02,627 - pyskl - INFO - Epoch [19][1000/1281] lr: 2.405e-02, eta: 18:58:55, time: 0.416, data_time: 0.000, memory: 8999, top1_acc: 0.8900, top5_acc: 0.9962, loss_cls: 2.2780, loss: 2.2780 +2025-05-28 14:25:44,485 - pyskl - INFO - Epoch [19][1100/1281] lr: 2.404e-02, eta: 18:58:23, time: 0.419, data_time: 0.000, memory: 8999, top1_acc: 0.8888, top5_acc: 0.9969, loss_cls: 2.4009, loss: 2.4009 +2025-05-28 14:26:26,312 - pyskl - INFO - Epoch [19][1200/1281] lr: 2.403e-02, eta: 18:57:50, time: 0.418, data_time: 0.000, memory: 8999, top1_acc: 0.8794, top5_acc: 0.9931, loss_cls: 2.3807, loss: 2.3807 +2025-05-28 14:27:00,908 - pyskl - INFO - Saving checkpoint at 19 epochs +2025-05-28 14:27:42,031 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 14:27:42,088 - pyskl - INFO - +top1_acc 0.8210 +top5_acc 0.9899 +2025-05-28 14:27:42,089 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 14:27:42,096 - pyskl - INFO - +mean_acc 0.7481 +2025-05-28 14:27:42,099 - pyskl - INFO - Epoch(val) [19][533] top1_acc: 0.8210, top5_acc: 0.9899, mean_class_accuracy: 0.7481 +2025-05-28 14:28:41,998 - pyskl - INFO - Epoch [20][100/1281] lr: 2.402e-02, eta: 18:55:02, time: 0.599, data_time: 0.181, memory: 9000, top1_acc: 0.8956, top5_acc: 1.0000, loss_cls: 2.2672, loss: 2.2672 +2025-05-28 14:29:23,695 - pyskl - INFO - Epoch [20][200/1281] lr: 2.401e-02, eta: 18:54:29, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9075, top5_acc: 0.9969, loss_cls: 2.2989, loss: 2.2989 +2025-05-28 14:30:05,335 - pyskl - INFO - Epoch [20][300/1281] lr: 2.400e-02, eta: 18:53:56, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.8744, top5_acc: 0.9950, loss_cls: 2.3581, loss: 2.3581 +2025-05-28 14:30:47,018 - pyskl - INFO - Epoch [20][400/1281] lr: 2.399e-02, eta: 18:53:22, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8844, top5_acc: 0.9969, loss_cls: 2.3294, loss: 2.3294 +2025-05-28 14:31:28,832 - pyskl - INFO - Epoch [20][500/1281] lr: 2.398e-02, eta: 18:52:50, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9100, top5_acc: 0.9969, loss_cls: 2.2356, loss: 2.2356 +2025-05-28 14:32:10,606 - pyskl - INFO - Epoch [20][600/1281] lr: 2.398e-02, eta: 18:52:17, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8781, top5_acc: 0.9956, loss_cls: 2.4464, loss: 2.4464 +2025-05-28 14:32:52,428 - pyskl - INFO - Epoch [20][700/1281] lr: 2.397e-02, eta: 18:51:44, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8994, top5_acc: 0.9931, loss_cls: 2.3545, loss: 2.3545 +2025-05-28 14:33:35,093 - pyskl - INFO - Epoch [20][800/1281] lr: 2.396e-02, eta: 18:51:17, time: 0.427, data_time: 0.000, memory: 9000, top1_acc: 0.8806, top5_acc: 0.9962, loss_cls: 2.4008, loss: 2.4008 +2025-05-28 14:34:17,083 - pyskl - INFO - Epoch [20][900/1281] lr: 2.395e-02, eta: 18:50:45, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.8675, top5_acc: 0.9944, loss_cls: 2.4718, loss: 2.4718 +2025-05-28 14:34:59,059 - pyskl - INFO - Epoch [20][1000/1281] lr: 2.394e-02, eta: 18:50:13, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.8788, top5_acc: 0.9956, loss_cls: 2.4147, loss: 2.4147 +2025-05-28 14:35:40,868 - pyskl - INFO - Epoch [20][1100/1281] lr: 2.393e-02, eta: 18:49:40, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8925, top5_acc: 0.9975, loss_cls: 2.3136, loss: 2.3136 +2025-05-28 14:36:22,607 - pyskl - INFO - Epoch [20][1200/1281] lr: 2.393e-02, eta: 18:49:06, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8856, top5_acc: 0.9981, loss_cls: 2.2892, loss: 2.2892 +2025-05-28 14:36:56,958 - pyskl - INFO - Saving checkpoint at 20 epochs +2025-05-28 14:50:03,019 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 14:50:03,077 - pyskl - INFO - +top1_acc 0.8100 +top5_acc 0.9765 +2025-05-28 14:50:03,077 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 14:50:03,083 - pyskl - INFO - +mean_acc 0.7640 +2025-05-28 14:50:03,085 - pyskl - INFO - Epoch(val) [20][533] top1_acc: 0.8100, top5_acc: 0.9765, mean_class_accuracy: 0.7640 +2025-05-28 14:51:02,755 - pyskl - INFO - Epoch [21][100/1281] lr: 2.391e-02, eta: 18:46:23, time: 0.597, data_time: 0.178, memory: 9000, top1_acc: 0.8981, top5_acc: 0.9956, loss_cls: 2.3067, loss: 2.3067 +2025-05-28 14:51:44,430 - pyskl - INFO - Epoch [21][200/1281] lr: 2.390e-02, eta: 18:45:49, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8906, top5_acc: 0.9962, loss_cls: 2.2814, loss: 2.2814 +2025-05-28 14:52:26,034 - pyskl - INFO - Epoch [21][300/1281] lr: 2.389e-02, eta: 18:45:15, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9019, top5_acc: 0.9975, loss_cls: 2.3017, loss: 2.3017 +2025-05-28 14:53:07,708 - pyskl - INFO - Epoch [21][400/1281] lr: 2.389e-02, eta: 18:44:41, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8962, top5_acc: 0.9975, loss_cls: 2.3291, loss: 2.3291 +2025-05-28 14:53:49,367 - pyskl - INFO - Epoch [21][500/1281] lr: 2.388e-02, eta: 18:44:07, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8825, top5_acc: 0.9981, loss_cls: 2.3018, loss: 2.3018 +2025-05-28 14:54:31,031 - pyskl - INFO - Epoch [21][600/1281] lr: 2.387e-02, eta: 18:43:33, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9044, top5_acc: 0.9962, loss_cls: 2.2989, loss: 2.2989 +2025-05-28 14:55:12,834 - pyskl - INFO - Epoch [21][700/1281] lr: 2.386e-02, eta: 18:43:00, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9012, top5_acc: 0.9944, loss_cls: 2.3118, loss: 2.3118 +2025-05-28 14:55:55,688 - pyskl - INFO - Epoch [21][800/1281] lr: 2.385e-02, eta: 18:42:33, time: 0.429, data_time: 0.000, memory: 9000, top1_acc: 0.8831, top5_acc: 0.9975, loss_cls: 2.2672, loss: 2.2672 +2025-05-28 14:56:37,353 - pyskl - INFO - Epoch [21][900/1281] lr: 2.384e-02, eta: 18:41:59, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8919, top5_acc: 0.9981, loss_cls: 2.3918, loss: 2.3918 +2025-05-28 14:57:19,150 - pyskl - INFO - Epoch [21][1000/1281] lr: 2.383e-02, eta: 18:41:25, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8869, top5_acc: 0.9962, loss_cls: 2.4192, loss: 2.4192 +2025-05-28 14:58:01,027 - pyskl - INFO - Epoch [21][1100/1281] lr: 2.383e-02, eta: 18:40:52, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.8969, top5_acc: 0.9981, loss_cls: 2.2509, loss: 2.2509 +2025-05-28 14:58:43,007 - pyskl - INFO - Epoch [21][1200/1281] lr: 2.382e-02, eta: 18:40:20, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9012, top5_acc: 0.9950, loss_cls: 2.3091, loss: 2.3091 +2025-05-28 14:59:17,576 - pyskl - INFO - Saving checkpoint at 21 epochs +2025-05-28 14:59:58,554 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 14:59:58,610 - pyskl - INFO - +top1_acc 0.8547 +top5_acc 0.9898 +2025-05-28 14:59:58,610 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 14:59:58,617 - pyskl - INFO - +mean_acc 0.8022 +2025-05-28 14:59:58,619 - pyskl - INFO - Epoch(val) [21][533] top1_acc: 0.8547, top5_acc: 0.9898, mean_class_accuracy: 0.8022 +2025-05-28 15:00:58,008 - pyskl - INFO - Epoch [22][100/1281] lr: 2.380e-02, eta: 18:37:39, time: 0.594, data_time: 0.176, memory: 9000, top1_acc: 0.8956, top5_acc: 0.9975, loss_cls: 2.2954, loss: 2.2954 +2025-05-28 15:01:39,657 - pyskl - INFO - Epoch [22][200/1281] lr: 2.379e-02, eta: 18:37:05, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9081, top5_acc: 0.9956, loss_cls: 2.3747, loss: 2.3747 +2025-05-28 15:02:21,253 - pyskl - INFO - Epoch [22][300/1281] lr: 2.378e-02, eta: 18:36:30, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9144, top5_acc: 0.9950, loss_cls: 2.2174, loss: 2.2174 +2025-05-28 15:03:02,990 - pyskl - INFO - Epoch [22][400/1281] lr: 2.378e-02, eta: 18:35:56, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8794, top5_acc: 0.9962, loss_cls: 2.3868, loss: 2.3868 +2025-05-28 15:03:44,686 - pyskl - INFO - Epoch [22][500/1281] lr: 2.377e-02, eta: 18:35:22, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9100, top5_acc: 0.9994, loss_cls: 2.2420, loss: 2.2420 +2025-05-28 15:04:26,461 - pyskl - INFO - Epoch [22][600/1281] lr: 2.376e-02, eta: 18:34:49, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8875, top5_acc: 0.9969, loss_cls: 2.4286, loss: 2.4286 +2025-05-28 15:05:08,042 - pyskl - INFO - Epoch [22][700/1281] lr: 2.375e-02, eta: 18:34:14, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.8731, top5_acc: 0.9950, loss_cls: 2.4255, loss: 2.4255 +2025-05-28 15:05:49,759 - pyskl - INFO - Epoch [22][800/1281] lr: 2.374e-02, eta: 18:33:39, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8962, top5_acc: 0.9994, loss_cls: 2.2688, loss: 2.2688 +2025-05-28 15:06:31,653 - pyskl - INFO - Epoch [22][900/1281] lr: 2.373e-02, eta: 18:33:06, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9081, top5_acc: 0.9956, loss_cls: 2.2479, loss: 2.2479 +2025-05-28 15:07:13,478 - pyskl - INFO - Epoch [22][1000/1281] lr: 2.372e-02, eta: 18:32:33, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8869, top5_acc: 0.9969, loss_cls: 2.3197, loss: 2.3197 +2025-05-28 15:07:55,366 - pyskl - INFO - Epoch [22][1100/1281] lr: 2.371e-02, eta: 18:31:59, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.8938, top5_acc: 0.9969, loss_cls: 2.4215, loss: 2.4215 +2025-05-28 15:08:37,125 - pyskl - INFO - Epoch [22][1200/1281] lr: 2.370e-02, eta: 18:31:25, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8806, top5_acc: 0.9944, loss_cls: 2.3544, loss: 2.3544 +2025-05-28 15:09:11,437 - pyskl - INFO - Saving checkpoint at 22 epochs +2025-05-28 15:09:52,990 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 15:09:53,046 - pyskl - INFO - +top1_acc 0.8304 +top5_acc 0.9883 +2025-05-28 15:09:53,046 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 15:09:53,054 - pyskl - INFO - +mean_acc 0.7800 +2025-05-28 15:09:53,056 - pyskl - INFO - Epoch(val) [22][533] top1_acc: 0.8304, top5_acc: 0.9883, mean_class_accuracy: 0.7800 +2025-05-28 15:10:52,740 - pyskl - INFO - Epoch [23][100/1281] lr: 2.369e-02, eta: 18:28:51, time: 0.597, data_time: 0.178, memory: 9000, top1_acc: 0.8988, top5_acc: 0.9981, loss_cls: 2.2275, loss: 2.2275 +2025-05-28 15:11:34,384 - pyskl - INFO - Epoch [23][200/1281] lr: 2.368e-02, eta: 18:28:16, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9050, top5_acc: 0.9981, loss_cls: 2.1584, loss: 2.1584 +2025-05-28 15:12:16,048 - pyskl - INFO - Epoch [23][300/1281] lr: 2.367e-02, eta: 18:27:42, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8975, top5_acc: 0.9969, loss_cls: 2.2218, loss: 2.2218 +2025-05-28 15:12:57,716 - pyskl - INFO - Epoch [23][400/1281] lr: 2.366e-02, eta: 18:27:07, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8919, top5_acc: 0.9969, loss_cls: 2.3391, loss: 2.3391 +2025-05-28 15:13:39,368 - pyskl - INFO - Epoch [23][500/1281] lr: 2.365e-02, eta: 18:26:33, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8881, top5_acc: 0.9962, loss_cls: 2.3452, loss: 2.3452 +2025-05-28 15:14:21,015 - pyskl - INFO - Epoch [23][600/1281] lr: 2.364e-02, eta: 18:25:58, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9025, top5_acc: 0.9981, loss_cls: 2.2095, loss: 2.2095 +2025-05-28 15:15:02,647 - pyskl - INFO - Epoch [23][700/1281] lr: 2.363e-02, eta: 18:25:23, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.8869, top5_acc: 0.9962, loss_cls: 2.2672, loss: 2.2672 +2025-05-28 15:15:44,293 - pyskl - INFO - Epoch [23][800/1281] lr: 2.362e-02, eta: 18:24:48, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.8800, top5_acc: 0.9925, loss_cls: 2.3667, loss: 2.3667 +2025-05-28 15:16:26,102 - pyskl - INFO - Epoch [23][900/1281] lr: 2.361e-02, eta: 18:24:14, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8969, top5_acc: 0.9981, loss_cls: 2.3442, loss: 2.3442 +2025-05-28 15:17:08,019 - pyskl - INFO - Epoch [23][1000/1281] lr: 2.360e-02, eta: 18:23:41, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9012, top5_acc: 0.9956, loss_cls: 2.3645, loss: 2.3645 +2025-05-28 15:17:50,698 - pyskl - INFO - Epoch [23][1100/1281] lr: 2.359e-02, eta: 18:23:11, time: 0.427, data_time: 0.000, memory: 9000, top1_acc: 0.8775, top5_acc: 0.9919, loss_cls: 2.3686, loss: 2.3686 +2025-05-28 15:18:32,630 - pyskl - INFO - Epoch [23][1200/1281] lr: 2.359e-02, eta: 18:22:38, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.8950, top5_acc: 0.9969, loss_cls: 2.1973, loss: 2.1973 +2025-05-28 15:19:07,102 - pyskl - INFO - Saving checkpoint at 23 epochs +2025-05-28 15:19:48,107 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 15:19:48,164 - pyskl - INFO - +top1_acc 0.8538 +top5_acc 0.9923 +2025-05-28 15:19:48,164 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 15:19:48,171 - pyskl - INFO - +mean_acc 0.8111 +2025-05-28 15:19:48,174 - pyskl - INFO - Epoch(val) [23][533] top1_acc: 0.8538, top5_acc: 0.9923, mean_class_accuracy: 0.8111 +2025-05-28 15:20:48,031 - pyskl - INFO - Epoch [24][100/1281] lr: 2.357e-02, eta: 18:20:09, time: 0.599, data_time: 0.181, memory: 9000, top1_acc: 0.9050, top5_acc: 0.9975, loss_cls: 2.2838, loss: 2.2838 +2025-05-28 15:21:29,752 - pyskl - INFO - Epoch [24][200/1281] lr: 2.356e-02, eta: 18:19:35, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9156, top5_acc: 0.9944, loss_cls: 2.1559, loss: 2.1559 +2025-05-28 15:22:11,570 - pyskl - INFO - Epoch [24][300/1281] lr: 2.355e-02, eta: 18:19:01, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9038, top5_acc: 0.9969, loss_cls: 2.3218, loss: 2.3218 +2025-05-28 15:22:53,367 - pyskl - INFO - Epoch [24][400/1281] lr: 2.354e-02, eta: 18:18:26, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8931, top5_acc: 0.9944, loss_cls: 2.2595, loss: 2.2595 +2025-05-28 15:23:35,159 - pyskl - INFO - Epoch [24][500/1281] lr: 2.353e-02, eta: 18:17:52, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8969, top5_acc: 0.9969, loss_cls: 2.3241, loss: 2.3241 +2025-05-28 15:24:16,986 - pyskl - INFO - Epoch [24][600/1281] lr: 2.352e-02, eta: 18:17:18, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8906, top5_acc: 0.9956, loss_cls: 2.3287, loss: 2.3287 +2025-05-28 15:24:58,864 - pyskl - INFO - Epoch [24][700/1281] lr: 2.351e-02, eta: 18:16:44, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.8844, top5_acc: 0.9944, loss_cls: 2.3059, loss: 2.3059 +2025-05-28 15:25:40,665 - pyskl - INFO - Epoch [24][800/1281] lr: 2.350e-02, eta: 18:16:10, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8950, top5_acc: 0.9962, loss_cls: 2.3298, loss: 2.3298 +2025-05-28 15:26:22,446 - pyskl - INFO - Epoch [24][900/1281] lr: 2.349e-02, eta: 18:15:35, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8962, top5_acc: 0.9944, loss_cls: 2.2139, loss: 2.2139 +2025-05-28 15:27:04,240 - pyskl - INFO - Epoch [24][1000/1281] lr: 2.348e-02, eta: 18:15:01, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9094, top5_acc: 0.9975, loss_cls: 2.2259, loss: 2.2259 +2025-05-28 15:27:46,045 - pyskl - INFO - Epoch [24][1100/1281] lr: 2.347e-02, eta: 18:14:26, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8956, top5_acc: 0.9981, loss_cls: 2.2840, loss: 2.2840 +2025-05-28 15:28:27,786 - pyskl - INFO - Epoch [24][1200/1281] lr: 2.346e-02, eta: 18:13:52, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8944, top5_acc: 0.9962, loss_cls: 2.2331, loss: 2.2331 +2025-05-28 15:29:02,213 - pyskl - INFO - Saving checkpoint at 24 epochs +2025-05-28 15:29:43,696 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 15:29:43,752 - pyskl - INFO - +top1_acc 0.8487 +top5_acc 0.9913 +2025-05-28 15:29:43,752 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 15:29:43,760 - pyskl - INFO - +mean_acc 0.7867 +2025-05-28 15:29:43,762 - pyskl - INFO - Epoch(val) [24][533] top1_acc: 0.8487, top5_acc: 0.9913, mean_class_accuracy: 0.7867 +2025-05-28 15:30:43,498 - pyskl - INFO - Epoch [25][100/1281] lr: 2.344e-02, eta: 18:11:26, time: 0.597, data_time: 0.180, memory: 9000, top1_acc: 0.8844, top5_acc: 0.9944, loss_cls: 2.3024, loss: 2.3024 +2025-05-28 15:31:25,167 - pyskl - INFO - Epoch [25][200/1281] lr: 2.343e-02, eta: 18:10:51, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9200, top5_acc: 0.9969, loss_cls: 2.1018, loss: 2.1018 +2025-05-28 15:32:06,792 - pyskl - INFO - Epoch [25][300/1281] lr: 2.342e-02, eta: 18:10:15, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.8962, top5_acc: 0.9956, loss_cls: 2.1880, loss: 2.1880 +2025-05-28 15:32:48,455 - pyskl - INFO - Epoch [25][400/1281] lr: 2.341e-02, eta: 18:09:40, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9094, top5_acc: 0.9975, loss_cls: 2.1846, loss: 2.1846 +2025-05-28 15:33:30,165 - pyskl - INFO - Epoch [25][500/1281] lr: 2.340e-02, eta: 18:09:05, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9087, top5_acc: 0.9969, loss_cls: 2.2413, loss: 2.2413 +2025-05-28 15:34:11,864 - pyskl - INFO - Epoch [25][600/1281] lr: 2.339e-02, eta: 18:08:30, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8919, top5_acc: 0.9938, loss_cls: 2.2480, loss: 2.2480 +2025-05-28 15:34:53,639 - pyskl - INFO - Epoch [25][700/1281] lr: 2.338e-02, eta: 18:07:56, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8962, top5_acc: 0.9969, loss_cls: 2.1793, loss: 2.1793 +2025-05-28 15:35:35,403 - pyskl - INFO - Epoch [25][800/1281] lr: 2.337e-02, eta: 18:07:21, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8981, top5_acc: 0.9969, loss_cls: 2.2402, loss: 2.2402 +2025-05-28 15:36:17,146 - pyskl - INFO - Epoch [25][900/1281] lr: 2.336e-02, eta: 18:06:46, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9069, top5_acc: 0.9988, loss_cls: 2.2455, loss: 2.2455 +2025-05-28 15:36:58,923 - pyskl - INFO - Epoch [25][1000/1281] lr: 2.335e-02, eta: 18:06:11, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9981, loss_cls: 2.1923, loss: 2.1923 +2025-05-28 15:37:40,699 - pyskl - INFO - Epoch [25][1100/1281] lr: 2.334e-02, eta: 18:05:36, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8869, top5_acc: 0.9944, loss_cls: 2.2792, loss: 2.2792 +2025-05-28 15:38:22,291 - pyskl - INFO - Epoch [25][1200/1281] lr: 2.333e-02, eta: 18:05:00, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9050, top5_acc: 0.9969, loss_cls: 2.2653, loss: 2.2653 +2025-05-28 15:38:56,511 - pyskl - INFO - Saving checkpoint at 25 epochs +2025-05-28 15:51:58,091 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 15:51:58,148 - pyskl - INFO - +top1_acc 0.8645 +top5_acc 0.9920 +2025-05-28 15:51:58,148 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 15:51:58,156 - pyskl - INFO - +mean_acc 0.8113 +2025-05-28 15:51:58,215 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_13.pth was removed +2025-05-28 15:51:59,736 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_25.pth. +2025-05-28 15:51:59,736 - pyskl - INFO - Best top1_acc is 0.8645 at 25 epoch. +2025-05-28 15:51:59,740 - pyskl - INFO - Epoch(val) [25][533] top1_acc: 0.8645, top5_acc: 0.9920, mean_class_accuracy: 0.8113 +2025-05-28 15:52:59,574 - pyskl - INFO - Epoch [26][100/1281] lr: 2.332e-02, eta: 18:02:39, time: 0.598, data_time: 0.179, memory: 9000, top1_acc: 0.9163, top5_acc: 0.9944, loss_cls: 2.1731, loss: 2.1731 +2025-05-28 15:53:41,295 - pyskl - INFO - Epoch [26][200/1281] lr: 2.330e-02, eta: 18:02:04, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9075, top5_acc: 0.9975, loss_cls: 2.2185, loss: 2.2185 +2025-05-28 15:54:22,999 - pyskl - INFO - Epoch [26][300/1281] lr: 2.329e-02, eta: 18:01:28, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9069, top5_acc: 0.9988, loss_cls: 2.1688, loss: 2.1688 +2025-05-28 15:55:04,643 - pyskl - INFO - Epoch [26][400/1281] lr: 2.328e-02, eta: 18:00:53, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9087, top5_acc: 0.9988, loss_cls: 2.2462, loss: 2.2462 +2025-05-28 15:55:46,336 - pyskl - INFO - Epoch [26][500/1281] lr: 2.327e-02, eta: 18:00:18, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9031, top5_acc: 0.9988, loss_cls: 2.2384, loss: 2.2384 +2025-05-28 15:56:28,174 - pyskl - INFO - Epoch [26][600/1281] lr: 2.326e-02, eta: 17:59:43, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8812, top5_acc: 0.9962, loss_cls: 2.3054, loss: 2.3054 +2025-05-28 15:57:09,863 - pyskl - INFO - Epoch [26][700/1281] lr: 2.325e-02, eta: 17:59:08, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8981, top5_acc: 0.9944, loss_cls: 2.2576, loss: 2.2576 +2025-05-28 15:57:51,491 - pyskl - INFO - Epoch [26][800/1281] lr: 2.324e-02, eta: 17:58:32, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9038, top5_acc: 0.9931, loss_cls: 2.2349, loss: 2.2349 +2025-05-28 15:58:32,681 - pyskl - INFO - Epoch [26][900/1281] lr: 2.323e-02, eta: 17:57:54, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.8919, top5_acc: 0.9981, loss_cls: 2.2783, loss: 2.2783 +2025-05-28 15:59:13,895 - pyskl - INFO - Epoch [26][1000/1281] lr: 2.322e-02, eta: 17:57:16, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9100, top5_acc: 0.9994, loss_cls: 2.2270, loss: 2.2270 +2025-05-28 15:59:55,215 - pyskl - INFO - Epoch [26][1100/1281] lr: 2.321e-02, eta: 17:56:39, time: 0.413, data_time: 0.000, memory: 9000, top1_acc: 0.9087, top5_acc: 0.9969, loss_cls: 2.1689, loss: 2.1689 +2025-05-28 16:00:37,208 - pyskl - INFO - Epoch [26][1200/1281] lr: 2.320e-02, eta: 17:56:05, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9025, top5_acc: 0.9950, loss_cls: 2.2338, loss: 2.2338 +2025-05-28 16:01:11,686 - pyskl - INFO - Saving checkpoint at 26 epochs +2025-05-28 16:01:54,336 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 16:01:54,407 - pyskl - INFO - +top1_acc 0.8377 +top5_acc 0.9900 +2025-05-28 16:01:54,407 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 16:01:54,417 - pyskl - INFO - +mean_acc 0.7873 +2025-05-28 16:01:54,421 - pyskl - INFO - Epoch(val) [26][533] top1_acc: 0.8377, top5_acc: 0.9900, mean_class_accuracy: 0.7873 +2025-05-28 16:02:53,908 - pyskl - INFO - Epoch [27][100/1281] lr: 2.318e-02, eta: 17:53:45, time: 0.595, data_time: 0.177, memory: 9000, top1_acc: 0.9106, top5_acc: 0.9981, loss_cls: 2.1666, loss: 2.1666 +2025-05-28 16:03:35,132 - pyskl - INFO - Epoch [27][200/1281] lr: 2.317e-02, eta: 17:53:07, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9087, top5_acc: 0.9950, loss_cls: 2.2051, loss: 2.2051 +2025-05-28 16:04:16,356 - pyskl - INFO - Epoch [27][300/1281] lr: 2.316e-02, eta: 17:52:30, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9106, top5_acc: 0.9988, loss_cls: 2.2407, loss: 2.2407 +2025-05-28 16:04:57,580 - pyskl - INFO - Epoch [27][400/1281] lr: 2.315e-02, eta: 17:51:52, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9069, top5_acc: 0.9956, loss_cls: 2.1706, loss: 2.1706 +2025-05-28 16:05:38,820 - pyskl - INFO - Epoch [27][500/1281] lr: 2.314e-02, eta: 17:51:14, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9100, top5_acc: 0.9994, loss_cls: 2.1939, loss: 2.1939 +2025-05-28 16:06:20,050 - pyskl - INFO - Epoch [27][600/1281] lr: 2.313e-02, eta: 17:50:37, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.8962, top5_acc: 0.9969, loss_cls: 2.2600, loss: 2.2600 +2025-05-28 16:07:01,272 - pyskl - INFO - Epoch [27][700/1281] lr: 2.312e-02, eta: 17:49:59, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.8969, top5_acc: 0.9981, loss_cls: 2.2261, loss: 2.2261 +2025-05-28 16:07:42,506 - pyskl - INFO - Epoch [27][800/1281] lr: 2.311e-02, eta: 17:49:22, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.8906, top5_acc: 0.9956, loss_cls: 2.3168, loss: 2.3168 +2025-05-28 16:08:23,739 - pyskl - INFO - Epoch [27][900/1281] lr: 2.310e-02, eta: 17:48:44, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.8900, top5_acc: 0.9956, loss_cls: 2.3020, loss: 2.3020 +2025-05-28 16:09:05,018 - pyskl - INFO - Epoch [27][1000/1281] lr: 2.308e-02, eta: 17:48:06, time: 0.413, data_time: 0.000, memory: 9000, top1_acc: 0.8888, top5_acc: 0.9956, loss_cls: 2.2817, loss: 2.2817 +2025-05-28 16:09:47,137 - pyskl - INFO - Epoch [27][1100/1281] lr: 2.307e-02, eta: 17:47:33, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9038, top5_acc: 0.9962, loss_cls: 2.2393, loss: 2.2393 +2025-05-28 16:10:28,845 - pyskl - INFO - Epoch [27][1200/1281] lr: 2.306e-02, eta: 17:46:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8956, top5_acc: 0.9950, loss_cls: 2.2796, loss: 2.2796 +2025-05-28 16:11:03,107 - pyskl - INFO - Saving checkpoint at 27 epochs +2025-05-28 16:11:44,362 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 16:11:44,421 - pyskl - INFO - +top1_acc 0.8452 +top5_acc 0.9874 +2025-05-28 16:11:44,421 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 16:11:44,429 - pyskl - INFO - +mean_acc 0.8031 +2025-05-28 16:11:44,431 - pyskl - INFO - Epoch(val) [27][533] top1_acc: 0.8452, top5_acc: 0.9874, mean_class_accuracy: 0.8031 +2025-05-28 16:12:44,174 - pyskl - INFO - Epoch [28][100/1281] lr: 2.304e-02, eta: 17:44:41, time: 0.597, data_time: 0.179, memory: 9000, top1_acc: 0.9200, top5_acc: 0.9975, loss_cls: 2.1994, loss: 2.1994 +2025-05-28 16:13:25,961 - pyskl - INFO - Epoch [28][200/1281] lr: 2.303e-02, eta: 17:44:06, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9050, top5_acc: 0.9969, loss_cls: 2.1545, loss: 2.1545 +2025-05-28 16:14:07,655 - pyskl - INFO - Epoch [28][300/1281] lr: 2.302e-02, eta: 17:43:31, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9225, top5_acc: 0.9975, loss_cls: 2.0764, loss: 2.0764 +2025-05-28 16:14:49,197 - pyskl - INFO - Epoch [28][400/1281] lr: 2.301e-02, eta: 17:42:54, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 0.9019, top5_acc: 0.9950, loss_cls: 2.1684, loss: 2.1684 +2025-05-28 16:15:30,768 - pyskl - INFO - Epoch [28][500/1281] lr: 2.300e-02, eta: 17:42:18, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.8862, top5_acc: 0.9969, loss_cls: 2.1734, loss: 2.1734 +2025-05-28 16:16:12,530 - pyskl - INFO - Epoch [28][600/1281] lr: 2.299e-02, eta: 17:41:43, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9025, top5_acc: 0.9969, loss_cls: 2.2350, loss: 2.2350 +2025-05-28 16:16:54,265 - pyskl - INFO - Epoch [28][700/1281] lr: 2.298e-02, eta: 17:41:07, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8994, top5_acc: 0.9994, loss_cls: 2.2184, loss: 2.2184 +2025-05-28 16:17:36,063 - pyskl - INFO - Epoch [28][800/1281] lr: 2.297e-02, eta: 17:40:32, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9081, top5_acc: 0.9988, loss_cls: 2.1814, loss: 2.1814 +2025-05-28 16:18:17,811 - pyskl - INFO - Epoch [28][900/1281] lr: 2.295e-02, eta: 17:39:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9050, top5_acc: 0.9975, loss_cls: 2.2124, loss: 2.2124 +2025-05-28 16:18:59,454 - pyskl - INFO - Epoch [28][1000/1281] lr: 2.294e-02, eta: 17:39:21, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9000, top5_acc: 0.9981, loss_cls: 2.2609, loss: 2.2609 +2025-05-28 16:19:41,360 - pyskl - INFO - Epoch [28][1100/1281] lr: 2.293e-02, eta: 17:38:46, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9062, top5_acc: 0.9981, loss_cls: 2.2259, loss: 2.2259 +2025-05-28 16:20:23,182 - pyskl - INFO - Epoch [28][1200/1281] lr: 2.292e-02, eta: 17:38:11, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8844, top5_acc: 0.9975, loss_cls: 2.3213, loss: 2.3213 +2025-05-28 16:20:57,549 - pyskl - INFO - Saving checkpoint at 28 epochs +2025-05-28 16:21:38,643 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 16:21:38,698 - pyskl - INFO - +top1_acc 0.8566 +top5_acc 0.9904 +2025-05-28 16:21:38,699 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 16:21:38,705 - pyskl - INFO - +mean_acc 0.8138 +2025-05-28 16:21:38,707 - pyskl - INFO - Epoch(val) [28][533] top1_acc: 0.8566, top5_acc: 0.9904, mean_class_accuracy: 0.8138 +2025-05-28 16:22:38,119 - pyskl - INFO - Epoch [29][100/1281] lr: 2.290e-02, eta: 17:35:56, time: 0.594, data_time: 0.177, memory: 9000, top1_acc: 0.9062, top5_acc: 0.9962, loss_cls: 2.2134, loss: 2.2134 +2025-05-28 16:23:20,546 - pyskl - INFO - Epoch [29][200/1281] lr: 2.289e-02, eta: 17:35:23, time: 0.424, data_time: 0.000, memory: 9000, top1_acc: 0.9156, top5_acc: 0.9950, loss_cls: 2.0534, loss: 2.0534 +2025-05-28 16:24:02,591 - pyskl - INFO - Epoch [29][300/1281] lr: 2.288e-02, eta: 17:34:49, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9144, top5_acc: 0.9962, loss_cls: 2.1175, loss: 2.1175 +2025-05-28 16:24:44,423 - pyskl - INFO - Epoch [29][400/1281] lr: 2.287e-02, eta: 17:34:14, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9131, top5_acc: 0.9969, loss_cls: 2.1611, loss: 2.1611 +2025-05-28 16:25:26,270 - pyskl - INFO - Epoch [29][500/1281] lr: 2.285e-02, eta: 17:33:39, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9056, top5_acc: 0.9975, loss_cls: 2.2044, loss: 2.2044 +2025-05-28 16:26:08,013 - pyskl - INFO - Epoch [29][600/1281] lr: 2.284e-02, eta: 17:33:03, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9025, top5_acc: 0.9975, loss_cls: 2.2394, loss: 2.2394 +2025-05-28 16:26:49,998 - pyskl - INFO - Epoch [29][700/1281] lr: 2.283e-02, eta: 17:32:29, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.8944, top5_acc: 0.9956, loss_cls: 2.2358, loss: 2.2358 +2025-05-28 16:27:31,809 - pyskl - INFO - Epoch [29][800/1281] lr: 2.282e-02, eta: 17:31:53, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8944, top5_acc: 0.9969, loss_cls: 2.1971, loss: 2.1971 +2025-05-28 16:28:13,550 - pyskl - INFO - Epoch [29][900/1281] lr: 2.281e-02, eta: 17:31:17, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8981, top5_acc: 0.9962, loss_cls: 2.2479, loss: 2.2479 +2025-05-28 16:28:55,442 - pyskl - INFO - Epoch [29][1000/1281] lr: 2.280e-02, eta: 17:30:42, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9975, loss_cls: 2.0939, loss: 2.0939 +2025-05-28 16:29:37,370 - pyskl - INFO - Epoch [29][1100/1281] lr: 2.279e-02, eta: 17:30:07, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9056, top5_acc: 0.9981, loss_cls: 2.1990, loss: 2.1990 +2025-05-28 16:30:19,421 - pyskl - INFO - Epoch [29][1200/1281] lr: 2.277e-02, eta: 17:29:33, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9181, top5_acc: 0.9975, loss_cls: 2.1633, loss: 2.1633 +2025-05-28 16:30:53,977 - pyskl - INFO - Saving checkpoint at 29 epochs +2025-05-28 16:31:35,479 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 16:31:35,541 - pyskl - INFO - +top1_acc 0.8527 +top5_acc 0.9896 +2025-05-28 16:31:35,541 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 16:31:35,549 - pyskl - INFO - +mean_acc 0.7996 +2025-05-28 16:31:35,552 - pyskl - INFO - Epoch(val) [29][533] top1_acc: 0.8527, top5_acc: 0.9896, mean_class_accuracy: 0.7996 +2025-05-28 16:32:35,669 - pyskl - INFO - Epoch [30][100/1281] lr: 2.275e-02, eta: 17:27:24, time: 0.601, data_time: 0.179, memory: 9000, top1_acc: 0.9131, top5_acc: 0.9994, loss_cls: 2.0573, loss: 2.0573 +2025-05-28 16:33:18,860 - pyskl - INFO - Epoch [30][200/1281] lr: 2.274e-02, eta: 17:26:54, time: 0.432, data_time: 0.000, memory: 9000, top1_acc: 0.9062, top5_acc: 1.0000, loss_cls: 2.1943, loss: 2.1943 +2025-05-28 16:34:00,881 - pyskl - INFO - Epoch [30][300/1281] lr: 2.273e-02, eta: 17:26:19, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9137, top5_acc: 0.9994, loss_cls: 2.1471, loss: 2.1471 +2025-05-28 16:34:42,633 - pyskl - INFO - Epoch [30][400/1281] lr: 2.272e-02, eta: 17:25:43, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9187, top5_acc: 0.9962, loss_cls: 2.1625, loss: 2.1625 +2025-05-28 16:35:24,313 - pyskl - INFO - Epoch [30][500/1281] lr: 2.271e-02, eta: 17:25:07, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8994, top5_acc: 0.9956, loss_cls: 2.1902, loss: 2.1902 +2025-05-28 16:36:06,035 - pyskl - INFO - Epoch [30][600/1281] lr: 2.269e-02, eta: 17:24:31, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.8925, top5_acc: 0.9981, loss_cls: 2.3140, loss: 2.3140 +2025-05-28 16:36:47,739 - pyskl - INFO - Epoch [30][700/1281] lr: 2.268e-02, eta: 17:23:55, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9206, top5_acc: 0.9975, loss_cls: 2.1791, loss: 2.1791 +2025-05-28 16:37:29,447 - pyskl - INFO - Epoch [30][800/1281] lr: 2.267e-02, eta: 17:23:19, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9012, top5_acc: 0.9975, loss_cls: 2.1908, loss: 2.1908 +2025-05-28 16:38:11,109 - pyskl - INFO - Epoch [30][900/1281] lr: 2.266e-02, eta: 17:22:43, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9200, top5_acc: 0.9975, loss_cls: 2.1211, loss: 2.1211 +2025-05-28 16:38:52,915 - pyskl - INFO - Epoch [30][1000/1281] lr: 2.265e-02, eta: 17:22:07, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9038, top5_acc: 0.9956, loss_cls: 2.1574, loss: 2.1574 +2025-05-28 16:39:34,879 - pyskl - INFO - Epoch [30][1100/1281] lr: 2.263e-02, eta: 17:21:32, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9131, top5_acc: 0.9975, loss_cls: 2.1140, loss: 2.1140 +2025-05-28 16:40:16,770 - pyskl - INFO - Epoch [30][1200/1281] lr: 2.262e-02, eta: 17:20:57, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.8806, top5_acc: 0.9962, loss_cls: 2.3113, loss: 2.3113 +2025-05-28 16:40:50,768 - pyskl - INFO - Saving checkpoint at 30 epochs +2025-05-28 16:54:01,497 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 16:54:01,554 - pyskl - INFO - +top1_acc 0.8752 +top5_acc 0.9924 +2025-05-28 16:54:01,554 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 16:54:01,561 - pyskl - INFO - +mean_acc 0.8239 +2025-05-28 16:54:01,628 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_25.pth was removed +2025-05-28 16:54:03,197 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_30.pth. +2025-05-28 16:54:03,198 - pyskl - INFO - Best top1_acc is 0.8752 at 30 epoch. +2025-05-28 16:54:03,201 - pyskl - INFO - Epoch(val) [30][533] top1_acc: 0.8752, top5_acc: 0.9924, mean_class_accuracy: 0.8239 +2025-05-28 16:55:02,839 - pyskl - INFO - Epoch [31][100/1281] lr: 2.260e-02, eta: 17:18:48, time: 0.596, data_time: 0.175, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9988, loss_cls: 2.1312, loss: 2.1312 +2025-05-28 16:55:46,229 - pyskl - INFO - Epoch [31][200/1281] lr: 2.259e-02, eta: 17:18:19, time: 0.434, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9969, loss_cls: 2.0839, loss: 2.0839 +2025-05-28 16:56:28,059 - pyskl - INFO - Epoch [31][300/1281] lr: 2.258e-02, eta: 17:17:43, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9044, top5_acc: 0.9969, loss_cls: 2.1304, loss: 2.1304 +2025-05-28 16:57:09,995 - pyskl - INFO - Epoch [31][400/1281] lr: 2.256e-02, eta: 17:17:08, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9169, top5_acc: 0.9975, loss_cls: 2.1009, loss: 2.1009 +2025-05-28 16:57:51,916 - pyskl - INFO - Epoch [31][500/1281] lr: 2.255e-02, eta: 17:16:32, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9106, top5_acc: 0.9975, loss_cls: 2.2271, loss: 2.2271 +2025-05-28 16:58:33,825 - pyskl - INFO - Epoch [31][600/1281] lr: 2.254e-02, eta: 17:15:57, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.8831, top5_acc: 0.9962, loss_cls: 2.2443, loss: 2.2443 +2025-05-28 16:59:15,761 - pyskl - INFO - Epoch [31][700/1281] lr: 2.253e-02, eta: 17:15:22, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9100, top5_acc: 0.9956, loss_cls: 2.1312, loss: 2.1312 +2025-05-28 16:59:57,624 - pyskl - INFO - Epoch [31][800/1281] lr: 2.252e-02, eta: 17:14:46, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9025, top5_acc: 0.9975, loss_cls: 2.2162, loss: 2.2162 +2025-05-28 17:00:39,901 - pyskl - INFO - Epoch [31][900/1281] lr: 2.250e-02, eta: 17:14:12, time: 0.423, data_time: 0.000, memory: 9000, top1_acc: 0.9000, top5_acc: 0.9981, loss_cls: 2.3390, loss: 2.3390 +2025-05-28 17:01:22,825 - pyskl - INFO - Epoch [31][1000/1281] lr: 2.249e-02, eta: 17:13:40, time: 0.429, data_time: 0.000, memory: 9000, top1_acc: 0.9094, top5_acc: 0.9956, loss_cls: 2.1072, loss: 2.1072 +2025-05-28 17:02:05,259 - pyskl - INFO - Epoch [31][1100/1281] lr: 2.248e-02, eta: 17:13:07, time: 0.424, data_time: 0.000, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9988, loss_cls: 2.1559, loss: 2.1559 +2025-05-28 17:02:47,155 - pyskl - INFO - Epoch [31][1200/1281] lr: 2.247e-02, eta: 17:12:31, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9100, top5_acc: 0.9969, loss_cls: 2.0630, loss: 2.0630 +2025-05-28 17:03:21,918 - pyskl - INFO - Saving checkpoint at 31 epochs +2025-05-28 17:04:03,469 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 17:04:03,524 - pyskl - INFO - +top1_acc 0.8406 +top5_acc 0.9873 +2025-05-28 17:04:03,524 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 17:04:03,532 - pyskl - INFO - +mean_acc 0.8154 +2025-05-28 17:04:03,534 - pyskl - INFO - Epoch(val) [31][533] top1_acc: 0.8406, top5_acc: 0.9873, mean_class_accuracy: 0.8154 +2025-05-28 17:05:03,189 - pyskl - INFO - Epoch [32][100/1281] lr: 2.244e-02, eta: 17:10:24, time: 0.596, data_time: 0.177, memory: 9000, top1_acc: 0.9094, top5_acc: 0.9981, loss_cls: 2.2499, loss: 2.2499 +2025-05-28 17:05:45,239 - pyskl - INFO - Epoch [32][200/1281] lr: 2.243e-02, eta: 17:09:49, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9306, top5_acc: 0.9975, loss_cls: 1.9825, loss: 1.9825 +2025-05-28 17:06:27,286 - pyskl - INFO - Epoch [32][300/1281] lr: 2.242e-02, eta: 17:09:14, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9144, top5_acc: 0.9981, loss_cls: 2.1062, loss: 2.1062 +2025-05-28 17:07:09,321 - pyskl - INFO - Epoch [32][400/1281] lr: 2.241e-02, eta: 17:08:39, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9044, top5_acc: 0.9975, loss_cls: 2.1984, loss: 2.1984 +2025-05-28 17:07:52,148 - pyskl - INFO - Epoch [32][500/1281] lr: 2.239e-02, eta: 17:08:07, time: 0.428, data_time: 0.000, memory: 9000, top1_acc: 0.9131, top5_acc: 0.9944, loss_cls: 2.1623, loss: 2.1623 +2025-05-28 17:08:34,164 - pyskl - INFO - Epoch [32][600/1281] lr: 2.238e-02, eta: 17:07:32, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9050, top5_acc: 0.9988, loss_cls: 2.1276, loss: 2.1276 +2025-05-28 17:09:15,871 - pyskl - INFO - Epoch [32][700/1281] lr: 2.237e-02, eta: 17:06:55, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9150, top5_acc: 0.9956, loss_cls: 2.1520, loss: 2.1520 +2025-05-28 17:09:57,541 - pyskl - INFO - Epoch [32][800/1281] lr: 2.236e-02, eta: 17:06:19, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9006, top5_acc: 0.9962, loss_cls: 2.1982, loss: 2.1982 +2025-05-28 17:10:39,418 - pyskl - INFO - Epoch [32][900/1281] lr: 2.234e-02, eta: 17:05:43, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9187, top5_acc: 0.9994, loss_cls: 2.1207, loss: 2.1207 +2025-05-28 17:11:21,594 - pyskl - INFO - Epoch [32][1000/1281] lr: 2.233e-02, eta: 17:05:08, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 0.9087, top5_acc: 0.9956, loss_cls: 2.1789, loss: 2.1789 +2025-05-28 17:12:03,419 - pyskl - INFO - Epoch [32][1100/1281] lr: 2.232e-02, eta: 17:04:32, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9031, top5_acc: 0.9981, loss_cls: 2.2133, loss: 2.2133 +2025-05-28 17:12:45,199 - pyskl - INFO - Epoch [32][1200/1281] lr: 2.231e-02, eta: 17:03:55, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9000, top5_acc: 0.9956, loss_cls: 2.2549, loss: 2.2549 +2025-05-28 17:13:19,953 - pyskl - INFO - Saving checkpoint at 32 epochs +2025-05-28 17:14:01,141 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 17:14:01,196 - pyskl - INFO - +top1_acc 0.8588 +top5_acc 0.9884 +2025-05-28 17:14:01,196 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 17:14:01,203 - pyskl - INFO - +mean_acc 0.7929 +2025-05-28 17:14:01,205 - pyskl - INFO - Epoch(val) [32][533] top1_acc: 0.8588, top5_acc: 0.9884, mean_class_accuracy: 0.7929 +2025-05-28 17:15:00,969 - pyskl - INFO - Epoch [33][100/1281] lr: 2.228e-02, eta: 17:01:51, time: 0.598, data_time: 0.175, memory: 9000, top1_acc: 0.9200, top5_acc: 0.9981, loss_cls: 2.1525, loss: 2.1525 +2025-05-28 17:15:42,818 - pyskl - INFO - Epoch [33][200/1281] lr: 2.227e-02, eta: 17:01:15, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9094, top5_acc: 0.9969, loss_cls: 2.1343, loss: 2.1343 +2025-05-28 17:16:24,644 - pyskl - INFO - Epoch [33][300/1281] lr: 2.226e-02, eta: 17:00:39, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9969, loss_cls: 2.0522, loss: 2.0522 +2025-05-28 17:17:06,416 - pyskl - INFO - Epoch [33][400/1281] lr: 2.225e-02, eta: 17:00:03, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.8962, top5_acc: 0.9956, loss_cls: 2.1553, loss: 2.1553 +2025-05-28 17:17:48,172 - pyskl - INFO - Epoch [33][500/1281] lr: 2.223e-02, eta: 16:59:27, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9156, top5_acc: 0.9988, loss_cls: 2.0124, loss: 2.0124 +2025-05-28 17:18:29,845 - pyskl - INFO - Epoch [33][600/1281] lr: 2.222e-02, eta: 16:58:50, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9106, top5_acc: 0.9988, loss_cls: 2.2001, loss: 2.2001 +2025-05-28 17:19:11,748 - pyskl - INFO - Epoch [33][700/1281] lr: 2.221e-02, eta: 16:58:14, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.8981, top5_acc: 0.9975, loss_cls: 2.1981, loss: 2.1981 +2025-05-28 17:19:53,552 - pyskl - INFO - Epoch [33][800/1281] lr: 2.219e-02, eta: 16:57:38, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9094, top5_acc: 0.9956, loss_cls: 2.1667, loss: 2.1667 +2025-05-28 17:20:35,436 - pyskl - INFO - Epoch [33][900/1281] lr: 2.218e-02, eta: 16:57:02, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9006, top5_acc: 0.9988, loss_cls: 2.1124, loss: 2.1124 +2025-05-28 17:21:17,612 - pyskl - INFO - Epoch [33][1000/1281] lr: 2.217e-02, eta: 16:56:27, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9938, loss_cls: 2.1184, loss: 2.1184 +2025-05-28 17:21:59,525 - pyskl - INFO - Epoch [33][1100/1281] lr: 2.216e-02, eta: 16:55:51, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.8981, top5_acc: 0.9981, loss_cls: 2.1803, loss: 2.1803 +2025-05-28 17:22:41,323 - pyskl - INFO - Epoch [33][1200/1281] lr: 2.214e-02, eta: 16:55:14, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9025, top5_acc: 0.9988, loss_cls: 2.1908, loss: 2.1908 +2025-05-28 17:23:15,944 - pyskl - INFO - Saving checkpoint at 33 epochs +2025-05-28 17:23:57,257 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 17:23:57,312 - pyskl - INFO - +top1_acc 0.8326 +top5_acc 0.9870 +2025-05-28 17:23:57,312 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 17:23:57,319 - pyskl - INFO - +mean_acc 0.7952 +2025-05-28 17:23:57,321 - pyskl - INFO - Epoch(val) [33][533] top1_acc: 0.8326, top5_acc: 0.9870, mean_class_accuracy: 0.7952 +2025-05-28 17:24:56,988 - pyskl - INFO - Epoch [34][100/1281] lr: 2.212e-02, eta: 16:53:12, time: 0.597, data_time: 0.175, memory: 9000, top1_acc: 0.9094, top5_acc: 0.9975, loss_cls: 2.1443, loss: 2.1443 +2025-05-28 17:25:39,286 - pyskl - INFO - Epoch [34][200/1281] lr: 2.211e-02, eta: 16:52:37, time: 0.423, data_time: 0.000, memory: 9000, top1_acc: 0.9181, top5_acc: 0.9988, loss_cls: 2.0118, loss: 2.0118 +2025-05-28 17:26:21,340 - pyskl - INFO - Epoch [34][300/1281] lr: 2.209e-02, eta: 16:52:02, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9187, top5_acc: 0.9981, loss_cls: 2.0865, loss: 2.0865 +2025-05-28 17:27:03,100 - pyskl - INFO - Epoch [34][400/1281] lr: 2.208e-02, eta: 16:51:25, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9113, top5_acc: 0.9956, loss_cls: 2.1265, loss: 2.1265 +2025-05-28 17:27:44,969 - pyskl - INFO - Epoch [34][500/1281] lr: 2.207e-02, eta: 16:50:49, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9100, top5_acc: 0.9975, loss_cls: 2.1174, loss: 2.1174 +2025-05-28 17:28:26,759 - pyskl - INFO - Epoch [34][600/1281] lr: 2.205e-02, eta: 16:50:12, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9213, top5_acc: 0.9975, loss_cls: 2.0751, loss: 2.0751 +2025-05-28 17:29:08,822 - pyskl - INFO - Epoch [34][700/1281] lr: 2.204e-02, eta: 16:49:37, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9069, top5_acc: 0.9981, loss_cls: 2.1919, loss: 2.1919 +2025-05-28 17:29:50,802 - pyskl - INFO - Epoch [34][800/1281] lr: 2.203e-02, eta: 16:49:01, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9225, top5_acc: 0.9981, loss_cls: 2.1514, loss: 2.1514 +2025-05-28 17:30:32,699 - pyskl - INFO - Epoch [34][900/1281] lr: 2.201e-02, eta: 16:48:25, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9256, top5_acc: 0.9969, loss_cls: 2.0054, loss: 2.0054 +2025-05-28 17:31:14,917 - pyskl - INFO - Epoch [34][1000/1281] lr: 2.200e-02, eta: 16:47:50, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 0.9038, top5_acc: 0.9962, loss_cls: 2.1674, loss: 2.1674 +2025-05-28 17:31:56,794 - pyskl - INFO - Epoch [34][1100/1281] lr: 2.199e-02, eta: 16:47:14, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.8938, top5_acc: 0.9956, loss_cls: 2.2133, loss: 2.2133 +2025-05-28 17:32:38,697 - pyskl - INFO - Epoch [34][1200/1281] lr: 2.197e-02, eta: 16:46:37, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9219, top5_acc: 0.9981, loss_cls: 2.1005, loss: 2.1005 +2025-05-28 17:33:13,181 - pyskl - INFO - Saving checkpoint at 34 epochs +2025-05-28 17:33:54,624 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 17:33:54,679 - pyskl - INFO - +top1_acc 0.8823 +top5_acc 0.9933 +2025-05-28 17:33:54,679 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 17:33:54,686 - pyskl - INFO - +mean_acc 0.8486 +2025-05-28 17:33:54,750 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_30.pth was removed +2025-05-28 17:33:56,278 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_34.pth. +2025-05-28 17:33:56,279 - pyskl - INFO - Best top1_acc is 0.8823 at 34 epoch. +2025-05-28 17:33:56,283 - pyskl - INFO - Epoch(val) [34][533] top1_acc: 0.8823, top5_acc: 0.9933, mean_class_accuracy: 0.8486 +2025-05-28 17:34:55,294 - pyskl - INFO - Epoch [35][100/1281] lr: 2.195e-02, eta: 16:44:34, time: 0.590, data_time: 0.175, memory: 9000, top1_acc: 0.9194, top5_acc: 0.9988, loss_cls: 2.0744, loss: 2.0744 +2025-05-28 17:35:37,014 - pyskl - INFO - Epoch [35][200/1281] lr: 2.194e-02, eta: 16:43:58, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9988, loss_cls: 2.0421, loss: 2.0421 +2025-05-28 17:36:18,769 - pyskl - INFO - Epoch [35][300/1281] lr: 2.192e-02, eta: 16:43:21, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9119, top5_acc: 0.9956, loss_cls: 2.2460, loss: 2.2460 +2025-05-28 17:37:00,582 - pyskl - INFO - Epoch [35][400/1281] lr: 2.191e-02, eta: 16:42:44, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9044, top5_acc: 0.9981, loss_cls: 2.2261, loss: 2.2261 +2025-05-28 17:37:42,384 - pyskl - INFO - Epoch [35][500/1281] lr: 2.190e-02, eta: 16:42:08, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9256, top5_acc: 0.9988, loss_cls: 2.0236, loss: 2.0236 +2025-05-28 17:38:24,198 - pyskl - INFO - Epoch [35][600/1281] lr: 2.188e-02, eta: 16:41:31, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9169, top5_acc: 0.9969, loss_cls: 2.0773, loss: 2.0773 +2025-05-28 17:39:06,058 - pyskl - INFO - Epoch [35][700/1281] lr: 2.187e-02, eta: 16:40:55, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9231, top5_acc: 0.9956, loss_cls: 1.9748, loss: 1.9748 +2025-05-28 17:39:47,927 - pyskl - INFO - Epoch [35][800/1281] lr: 2.185e-02, eta: 16:40:19, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9213, top5_acc: 0.9981, loss_cls: 2.0402, loss: 2.0402 +2025-05-28 17:40:30,044 - pyskl - INFO - Epoch [35][900/1281] lr: 2.184e-02, eta: 16:39:43, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9069, top5_acc: 0.9988, loss_cls: 2.1425, loss: 2.1425 +2025-05-28 17:41:13,818 - pyskl - INFO - Epoch [35][1000/1281] lr: 2.183e-02, eta: 16:39:13, time: 0.438, data_time: 0.000, memory: 9000, top1_acc: 0.8981, top5_acc: 0.9956, loss_cls: 2.1613, loss: 2.1613 +2025-05-28 17:41:57,588 - pyskl - INFO - Epoch [35][1100/1281] lr: 2.181e-02, eta: 16:38:43, time: 0.438, data_time: 0.000, memory: 9000, top1_acc: 0.8969, top5_acc: 0.9956, loss_cls: 2.2286, loss: 2.2286 +2025-05-28 17:42:40,712 - pyskl - INFO - Epoch [35][1200/1281] lr: 2.180e-02, eta: 16:38:10, time: 0.431, data_time: 0.000, memory: 9000, top1_acc: 0.9031, top5_acc: 0.9975, loss_cls: 2.1247, loss: 2.1247 +2025-05-28 17:43:14,911 - pyskl - INFO - Saving checkpoint at 35 epochs +2025-05-28 17:55:47,553 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 17:55:47,609 - pyskl - INFO - +top1_acc 0.8814 +top5_acc 0.9923 +2025-05-28 17:55:47,609 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 17:55:47,616 - pyskl - INFO - +mean_acc 0.8278 +2025-05-28 17:55:47,619 - pyskl - INFO - Epoch(val) [35][533] top1_acc: 0.8814, top5_acc: 0.9923, mean_class_accuracy: 0.8278 +2025-05-28 17:56:47,082 - pyskl - INFO - Epoch [36][100/1281] lr: 2.178e-02, eta: 16:36:10, time: 0.595, data_time: 0.175, memory: 9000, top1_acc: 0.9156, top5_acc: 0.9981, loss_cls: 2.0976, loss: 2.0976 +2025-05-28 17:57:28,970 - pyskl - INFO - Epoch [36][200/1281] lr: 2.176e-02, eta: 16:35:34, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9163, top5_acc: 0.9975, loss_cls: 2.1475, loss: 2.1475 +2025-05-28 17:58:10,919 - pyskl - INFO - Epoch [36][300/1281] lr: 2.175e-02, eta: 16:34:58, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9119, top5_acc: 0.9988, loss_cls: 2.0237, loss: 2.0237 +2025-05-28 17:58:52,792 - pyskl - INFO - Epoch [36][400/1281] lr: 2.173e-02, eta: 16:34:21, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9981, loss_cls: 2.1991, loss: 2.1991 +2025-05-28 17:59:34,747 - pyskl - INFO - Epoch [36][500/1281] lr: 2.172e-02, eta: 16:33:45, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9094, top5_acc: 0.9969, loss_cls: 2.1477, loss: 2.1477 +2025-05-28 18:00:16,637 - pyskl - INFO - Epoch [36][600/1281] lr: 2.171e-02, eta: 16:33:09, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9069, top5_acc: 0.9975, loss_cls: 2.1919, loss: 2.1919 +2025-05-28 18:00:58,542 - pyskl - INFO - Epoch [36][700/1281] lr: 2.169e-02, eta: 16:32:32, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9969, loss_cls: 2.0692, loss: 2.0692 +2025-05-28 18:01:40,508 - pyskl - INFO - Epoch [36][800/1281] lr: 2.168e-02, eta: 16:31:56, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9237, top5_acc: 0.9975, loss_cls: 1.9758, loss: 1.9758 +2025-05-28 18:02:22,468 - pyskl - INFO - Epoch [36][900/1281] lr: 2.167e-02, eta: 16:31:19, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9119, top5_acc: 0.9956, loss_cls: 2.2040, loss: 2.2040 +2025-05-28 18:03:04,340 - pyskl - INFO - Epoch [36][1000/1281] lr: 2.165e-02, eta: 16:30:43, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.8969, top5_acc: 0.9962, loss_cls: 2.1219, loss: 2.1219 +2025-05-28 18:03:45,776 - pyskl - INFO - Epoch [36][1100/1281] lr: 2.164e-02, eta: 16:30:05, time: 0.414, data_time: 0.000, memory: 9000, top1_acc: 0.9144, top5_acc: 0.9962, loss_cls: 2.1406, loss: 2.1406 +2025-05-28 18:04:28,180 - pyskl - INFO - Epoch [36][1200/1281] lr: 2.162e-02, eta: 16:29:30, time: 0.424, data_time: 0.000, memory: 9000, top1_acc: 0.9181, top5_acc: 0.9962, loss_cls: 2.1090, loss: 2.1090 +2025-05-28 18:05:02,759 - pyskl - INFO - Saving checkpoint at 36 epochs +2025-05-28 18:05:43,791 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 18:05:43,847 - pyskl - INFO - +top1_acc 0.8515 +top5_acc 0.9885 +2025-05-28 18:05:43,847 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 18:05:43,854 - pyskl - INFO - +mean_acc 0.7934 +2025-05-28 18:05:43,857 - pyskl - INFO - Epoch(val) [36][533] top1_acc: 0.8515, top5_acc: 0.9885, mean_class_accuracy: 0.7934 +2025-05-28 18:06:43,422 - pyskl - INFO - Epoch [37][100/1281] lr: 2.160e-02, eta: 16:27:32, time: 0.596, data_time: 0.178, memory: 9000, top1_acc: 0.9062, top5_acc: 0.9981, loss_cls: 2.1299, loss: 2.1299 +2025-05-28 18:07:25,553 - pyskl - INFO - Epoch [37][200/1281] lr: 2.158e-02, eta: 16:26:56, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9119, top5_acc: 0.9975, loss_cls: 2.0457, loss: 2.0457 +2025-05-28 18:08:07,403 - pyskl - INFO - Epoch [37][300/1281] lr: 2.157e-02, eta: 16:26:20, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9150, top5_acc: 1.0000, loss_cls: 2.0699, loss: 2.0699 +2025-05-28 18:08:49,345 - pyskl - INFO - Epoch [37][400/1281] lr: 2.156e-02, eta: 16:25:43, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9150, top5_acc: 0.9969, loss_cls: 2.0915, loss: 2.0915 +2025-05-28 18:09:31,274 - pyskl - INFO - Epoch [37][500/1281] lr: 2.154e-02, eta: 16:25:07, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9975, loss_cls: 2.0536, loss: 2.0536 +2025-05-28 18:10:13,217 - pyskl - INFO - Epoch [37][600/1281] lr: 2.153e-02, eta: 16:24:30, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9056, top5_acc: 0.9956, loss_cls: 2.0912, loss: 2.0912 +2025-05-28 18:10:55,044 - pyskl - INFO - Epoch [37][700/1281] lr: 2.151e-02, eta: 16:23:53, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9181, top5_acc: 0.9981, loss_cls: 2.0956, loss: 2.0956 +2025-05-28 18:11:37,038 - pyskl - INFO - Epoch [37][800/1281] lr: 2.150e-02, eta: 16:23:17, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9237, top5_acc: 0.9975, loss_cls: 2.0395, loss: 2.0395 +2025-05-28 18:12:19,155 - pyskl - INFO - Epoch [37][900/1281] lr: 2.149e-02, eta: 16:22:41, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9087, top5_acc: 0.9969, loss_cls: 2.0721, loss: 2.0721 +2025-05-28 18:13:01,491 - pyskl - INFO - Epoch [37][1000/1281] lr: 2.147e-02, eta: 16:22:06, time: 0.423, data_time: 0.000, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9975, loss_cls: 2.0489, loss: 2.0489 +2025-05-28 18:13:44,365 - pyskl - INFO - Epoch [37][1100/1281] lr: 2.146e-02, eta: 16:21:32, time: 0.429, data_time: 0.000, memory: 9000, top1_acc: 0.9219, top5_acc: 0.9975, loss_cls: 2.0516, loss: 2.0516 +2025-05-28 18:14:27,002 - pyskl - INFO - Epoch [37][1200/1281] lr: 2.144e-02, eta: 16:20:57, time: 0.426, data_time: 0.000, memory: 9000, top1_acc: 0.9087, top5_acc: 0.9956, loss_cls: 2.1371, loss: 2.1371 +2025-05-28 18:15:01,596 - pyskl - INFO - Saving checkpoint at 37 epochs +2025-05-28 18:15:42,458 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 18:15:42,513 - pyskl - INFO - +top1_acc 0.8667 +top5_acc 0.9944 +2025-05-28 18:15:42,514 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 18:15:42,520 - pyskl - INFO - +mean_acc 0.8238 +2025-05-28 18:15:42,523 - pyskl - INFO - Epoch(val) [37][533] top1_acc: 0.8667, top5_acc: 0.9944, mean_class_accuracy: 0.8238 +2025-05-28 18:16:42,228 - pyskl - INFO - Epoch [38][100/1281] lr: 2.142e-02, eta: 16:19:02, time: 0.597, data_time: 0.176, memory: 9000, top1_acc: 0.9263, top5_acc: 1.0000, loss_cls: 1.9947, loss: 1.9947 +2025-05-28 18:17:24,039 - pyskl - INFO - Epoch [38][200/1281] lr: 2.140e-02, eta: 16:18:25, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9250, top5_acc: 0.9988, loss_cls: 2.0401, loss: 2.0401 +2025-05-28 18:18:05,904 - pyskl - INFO - Epoch [38][300/1281] lr: 2.139e-02, eta: 16:17:48, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9350, top5_acc: 0.9994, loss_cls: 1.9831, loss: 1.9831 +2025-05-28 18:18:47,820 - pyskl - INFO - Epoch [38][400/1281] lr: 2.137e-02, eta: 16:17:11, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9950, loss_cls: 2.0227, loss: 2.0227 +2025-05-28 18:19:29,824 - pyskl - INFO - Epoch [38][500/1281] lr: 2.136e-02, eta: 16:16:35, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9019, top5_acc: 0.9969, loss_cls: 2.1766, loss: 2.1766 +2025-05-28 18:20:11,619 - pyskl - INFO - Epoch [38][600/1281] lr: 2.134e-02, eta: 16:15:58, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9131, top5_acc: 0.9988, loss_cls: 2.0212, loss: 2.0212 +2025-05-28 18:20:53,493 - pyskl - INFO - Epoch [38][700/1281] lr: 2.133e-02, eta: 16:15:21, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9962, loss_cls: 2.0986, loss: 2.0986 +2025-05-28 18:21:35,367 - pyskl - INFO - Epoch [38][800/1281] lr: 2.132e-02, eta: 16:14:44, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9163, top5_acc: 0.9969, loss_cls: 2.1002, loss: 2.1002 +2025-05-28 18:22:17,257 - pyskl - INFO - Epoch [38][900/1281] lr: 2.130e-02, eta: 16:14:07, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9200, top5_acc: 0.9988, loss_cls: 2.0474, loss: 2.0474 +2025-05-28 18:22:59,197 - pyskl - INFO - Epoch [38][1000/1281] lr: 2.129e-02, eta: 16:13:30, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.8994, top5_acc: 0.9969, loss_cls: 2.1195, loss: 2.1195 +2025-05-28 18:23:41,574 - pyskl - INFO - Epoch [38][1100/1281] lr: 2.127e-02, eta: 16:12:55, time: 0.424, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 1.0000, loss_cls: 2.0298, loss: 2.0298 +2025-05-28 18:24:23,716 - pyskl - INFO - Epoch [38][1200/1281] lr: 2.126e-02, eta: 16:12:19, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9094, top5_acc: 0.9981, loss_cls: 2.0763, loss: 2.0763 +2025-05-28 18:24:58,479 - pyskl - INFO - Saving checkpoint at 38 epochs +2025-05-28 18:25:39,330 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 18:25:39,385 - pyskl - INFO - +top1_acc 0.8865 +top5_acc 0.9933 +2025-05-28 18:25:39,385 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 18:25:39,392 - pyskl - INFO - +mean_acc 0.8376 +2025-05-28 18:25:39,453 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_34.pth was removed +2025-05-28 18:25:40,996 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_38.pth. +2025-05-28 18:25:40,996 - pyskl - INFO - Best top1_acc is 0.8865 at 38 epoch. +2025-05-28 18:25:41,000 - pyskl - INFO - Epoch(val) [38][533] top1_acc: 0.8865, top5_acc: 0.9933, mean_class_accuracy: 0.8376 +2025-05-28 18:26:42,393 - pyskl - INFO - Epoch [39][100/1281] lr: 2.123e-02, eta: 16:10:29, time: 0.614, data_time: 0.175, memory: 9000, top1_acc: 0.9213, top5_acc: 0.9975, loss_cls: 2.0092, loss: 2.0092 +2025-05-28 18:27:26,230 - pyskl - INFO - Epoch [39][200/1281] lr: 2.122e-02, eta: 16:09:58, time: 0.438, data_time: 0.000, memory: 9000, top1_acc: 0.9275, top5_acc: 0.9994, loss_cls: 1.9731, loss: 1.9731 +2025-05-28 18:28:10,198 - pyskl - INFO - Epoch [39][300/1281] lr: 2.120e-02, eta: 16:09:27, time: 0.440, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9988, loss_cls: 1.9775, loss: 1.9775 +2025-05-28 18:28:54,142 - pyskl - INFO - Epoch [39][400/1281] lr: 2.119e-02, eta: 16:08:56, time: 0.439, data_time: 0.000, memory: 9000, top1_acc: 0.9131, top5_acc: 0.9975, loss_cls: 2.0981, loss: 2.0981 +2025-05-28 18:29:38,001 - pyskl - INFO - Epoch [39][500/1281] lr: 2.117e-02, eta: 16:08:25, time: 0.439, data_time: 0.000, memory: 9000, top1_acc: 0.9363, top5_acc: 0.9988, loss_cls: 2.0186, loss: 2.0186 +2025-05-28 18:30:21,827 - pyskl - INFO - Epoch [39][600/1281] lr: 2.116e-02, eta: 16:07:54, time: 0.438, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9969, loss_cls: 2.0969, loss: 2.0969 +2025-05-28 18:31:03,903 - pyskl - INFO - Epoch [39][700/1281] lr: 2.114e-02, eta: 16:07:17, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9019, top5_acc: 0.9956, loss_cls: 2.1775, loss: 2.1775 +2025-05-28 18:31:45,774 - pyskl - INFO - Epoch [39][800/1281] lr: 2.113e-02, eta: 16:06:40, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9150, top5_acc: 0.9988, loss_cls: 2.0635, loss: 2.0635 +2025-05-28 18:32:27,519 - pyskl - INFO - Epoch [39][900/1281] lr: 2.111e-02, eta: 16:06:02, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9231, top5_acc: 0.9962, loss_cls: 2.0119, loss: 2.0119 +2025-05-28 18:33:09,638 - pyskl - INFO - Epoch [39][1000/1281] lr: 2.110e-02, eta: 16:05:26, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9113, top5_acc: 0.9988, loss_cls: 2.0074, loss: 2.0074 +2025-05-28 18:33:51,763 - pyskl - INFO - Epoch [39][1100/1281] lr: 2.108e-02, eta: 16:04:49, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9988, loss_cls: 2.0174, loss: 2.0174 +2025-05-28 18:34:33,782 - pyskl - INFO - Epoch [39][1200/1281] lr: 2.107e-02, eta: 16:04:13, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 2.0444, loss: 2.0444 +2025-05-28 18:35:08,752 - pyskl - INFO - Saving checkpoint at 39 epochs +2025-05-28 18:35:50,189 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 18:35:50,245 - pyskl - INFO - +top1_acc 0.8740 +top5_acc 0.9918 +2025-05-28 18:35:50,245 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 18:35:50,252 - pyskl - INFO - +mean_acc 0.8471 +2025-05-28 18:35:50,254 - pyskl - INFO - Epoch(val) [39][533] top1_acc: 0.8740, top5_acc: 0.9918, mean_class_accuracy: 0.8471 +2025-05-28 18:36:50,007 - pyskl - INFO - Epoch [40][100/1281] lr: 2.104e-02, eta: 16:02:20, time: 0.597, data_time: 0.179, memory: 9000, top1_acc: 0.9306, top5_acc: 0.9981, loss_cls: 2.0231, loss: 2.0231 +2025-05-28 18:37:31,728 - pyskl - INFO - Epoch [40][200/1281] lr: 2.103e-02, eta: 16:01:42, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9187, top5_acc: 0.9981, loss_cls: 2.0157, loss: 2.0157 +2025-05-28 18:38:13,435 - pyskl - INFO - Epoch [40][300/1281] lr: 2.101e-02, eta: 16:01:05, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9144, top5_acc: 0.9988, loss_cls: 2.0388, loss: 2.0388 +2025-05-28 18:38:55,188 - pyskl - INFO - Epoch [40][400/1281] lr: 2.100e-02, eta: 16:00:27, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9150, top5_acc: 0.9975, loss_cls: 2.0461, loss: 2.0461 +2025-05-28 18:39:36,919 - pyskl - INFO - Epoch [40][500/1281] lr: 2.098e-02, eta: 15:59:49, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9069, top5_acc: 0.9956, loss_cls: 2.1348, loss: 2.1348 +2025-05-28 18:40:18,625 - pyskl - INFO - Epoch [40][600/1281] lr: 2.097e-02, eta: 15:59:12, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9994, loss_cls: 2.0362, loss: 2.0362 +2025-05-28 18:41:00,364 - pyskl - INFO - Epoch [40][700/1281] lr: 2.095e-02, eta: 15:58:34, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9294, top5_acc: 0.9969, loss_cls: 2.0145, loss: 2.0145 +2025-05-28 18:41:42,146 - pyskl - INFO - Epoch [40][800/1281] lr: 2.094e-02, eta: 15:57:57, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9069, top5_acc: 0.9994, loss_cls: 2.0859, loss: 2.0859 +2025-05-28 18:42:23,913 - pyskl - INFO - Epoch [40][900/1281] lr: 2.092e-02, eta: 15:57:19, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9012, top5_acc: 0.9956, loss_cls: 2.1954, loss: 2.1954 +2025-05-28 18:43:06,055 - pyskl - INFO - Epoch [40][1000/1281] lr: 2.091e-02, eta: 15:56:43, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9131, top5_acc: 0.9975, loss_cls: 2.0955, loss: 2.0955 +2025-05-28 18:43:48,051 - pyskl - INFO - Epoch [40][1100/1281] lr: 2.089e-02, eta: 15:56:06, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9969, loss_cls: 1.9633, loss: 1.9633 +2025-05-28 18:44:29,527 - pyskl - INFO - Epoch [40][1200/1281] lr: 2.088e-02, eta: 15:55:27, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9994, loss_cls: 2.0371, loss: 2.0371 +2025-05-28 18:45:03,750 - pyskl - INFO - Saving checkpoint at 40 epochs +2025-05-28 18:57:41,238 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 18:57:41,294 - pyskl - INFO - +top1_acc 0.8809 +top5_acc 0.9944 +2025-05-28 18:57:41,294 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 18:57:41,301 - pyskl - INFO - +mean_acc 0.8332 +2025-05-28 18:57:41,304 - pyskl - INFO - Epoch(val) [40][533] top1_acc: 0.8809, top5_acc: 0.9944, mean_class_accuracy: 0.8332 +2025-05-28 18:58:40,737 - pyskl - INFO - Epoch [41][100/1281] lr: 2.085e-02, eta: 15:53:35, time: 0.594, data_time: 0.176, memory: 9000, top1_acc: 0.9194, top5_acc: 0.9969, loss_cls: 2.0536, loss: 2.0536 +2025-05-28 18:59:22,683 - pyskl - INFO - Epoch [41][200/1281] lr: 2.083e-02, eta: 15:52:58, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9181, top5_acc: 0.9975, loss_cls: 2.0246, loss: 2.0246 +2025-05-28 19:00:04,617 - pyskl - INFO - Epoch [41][300/1281] lr: 2.082e-02, eta: 15:52:21, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9237, top5_acc: 0.9962, loss_cls: 2.0135, loss: 2.0135 +2025-05-28 19:00:46,542 - pyskl - INFO - Epoch [41][400/1281] lr: 2.080e-02, eta: 15:51:44, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9119, top5_acc: 0.9988, loss_cls: 2.1064, loss: 2.1064 +2025-05-28 19:01:28,511 - pyskl - INFO - Epoch [41][500/1281] lr: 2.079e-02, eta: 15:51:06, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9150, top5_acc: 0.9956, loss_cls: 2.0430, loss: 2.0430 +2025-05-28 19:02:10,478 - pyskl - INFO - Epoch [41][600/1281] lr: 2.077e-02, eta: 15:50:29, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9200, top5_acc: 0.9981, loss_cls: 1.9930, loss: 1.9930 +2025-05-28 19:02:52,388 - pyskl - INFO - Epoch [41][700/1281] lr: 2.076e-02, eta: 15:49:52, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9969, loss_cls: 1.9846, loss: 1.9846 +2025-05-28 19:03:34,154 - pyskl - INFO - Epoch [41][800/1281] lr: 2.074e-02, eta: 15:49:15, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9163, top5_acc: 0.9981, loss_cls: 2.1351, loss: 2.1351 +2025-05-28 19:04:16,028 - pyskl - INFO - Epoch [41][900/1281] lr: 2.073e-02, eta: 15:48:37, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9113, top5_acc: 0.9975, loss_cls: 2.0591, loss: 2.0591 +2025-05-28 19:04:58,025 - pyskl - INFO - Epoch [41][1000/1281] lr: 2.071e-02, eta: 15:48:00, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9144, top5_acc: 0.9975, loss_cls: 2.1119, loss: 2.1119 +2025-05-28 19:05:40,227 - pyskl - INFO - Epoch [41][1100/1281] lr: 2.070e-02, eta: 15:47:24, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 0.9163, top5_acc: 0.9975, loss_cls: 2.0542, loss: 2.0542 +2025-05-28 19:06:23,602 - pyskl - INFO - Epoch [41][1200/1281] lr: 2.068e-02, eta: 15:46:50, time: 0.434, data_time: 0.000, memory: 9000, top1_acc: 0.9137, top5_acc: 0.9962, loss_cls: 2.1020, loss: 2.1020 +2025-05-28 19:06:58,759 - pyskl - INFO - Saving checkpoint at 41 epochs +2025-05-28 19:07:39,877 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 19:07:39,933 - pyskl - INFO - +top1_acc 0.8757 +top5_acc 0.9933 +2025-05-28 19:07:39,933 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 19:07:39,940 - pyskl - INFO - +mean_acc 0.8448 +2025-05-28 19:07:39,942 - pyskl - INFO - Epoch(val) [41][533] top1_acc: 0.8757, top5_acc: 0.9933, mean_class_accuracy: 0.8448 +2025-05-28 19:08:39,490 - pyskl - INFO - Epoch [42][100/1281] lr: 2.065e-02, eta: 15:44:59, time: 0.595, data_time: 0.177, memory: 9000, top1_acc: 0.9256, top5_acc: 0.9975, loss_cls: 1.9847, loss: 1.9847 +2025-05-28 19:09:21,299 - pyskl - INFO - Epoch [42][200/1281] lr: 2.064e-02, eta: 15:44:22, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9363, top5_acc: 0.9981, loss_cls: 1.9614, loss: 1.9614 +2025-05-28 19:10:03,111 - pyskl - INFO - Epoch [42][300/1281] lr: 2.062e-02, eta: 15:43:44, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9350, top5_acc: 0.9994, loss_cls: 1.9683, loss: 1.9683 +2025-05-28 19:10:44,903 - pyskl - INFO - Epoch [42][400/1281] lr: 2.061e-02, eta: 15:43:07, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9350, top5_acc: 0.9994, loss_cls: 1.9195, loss: 1.9195 +2025-05-28 19:11:26,789 - pyskl - INFO - Epoch [42][500/1281] lr: 2.059e-02, eta: 15:42:29, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9975, loss_cls: 1.9533, loss: 1.9533 +2025-05-28 19:12:08,772 - pyskl - INFO - Epoch [42][600/1281] lr: 2.057e-02, eta: 15:41:52, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9181, top5_acc: 0.9975, loss_cls: 2.0053, loss: 2.0053 +2025-05-28 19:12:50,864 - pyskl - INFO - Epoch [42][700/1281] lr: 2.056e-02, eta: 15:41:15, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9119, top5_acc: 0.9981, loss_cls: 2.1524, loss: 2.1524 +2025-05-28 19:13:32,938 - pyskl - INFO - Epoch [42][800/1281] lr: 2.054e-02, eta: 15:40:38, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.8981, top5_acc: 0.9962, loss_cls: 2.0739, loss: 2.0739 +2025-05-28 19:14:14,977 - pyskl - INFO - Epoch [42][900/1281] lr: 2.053e-02, eta: 15:40:01, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9137, top5_acc: 0.9969, loss_cls: 2.1441, loss: 2.1441 +2025-05-28 19:14:56,916 - pyskl - INFO - Epoch [42][1000/1281] lr: 2.051e-02, eta: 15:39:24, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9281, top5_acc: 0.9975, loss_cls: 2.1002, loss: 2.1002 +2025-05-28 19:15:40,261 - pyskl - INFO - Epoch [42][1100/1281] lr: 2.050e-02, eta: 15:38:50, time: 0.433, data_time: 0.000, memory: 9000, top1_acc: 0.9287, top5_acc: 0.9988, loss_cls: 1.9608, loss: 1.9608 +2025-05-28 19:16:22,981 - pyskl - INFO - Epoch [42][1200/1281] lr: 2.048e-02, eta: 15:38:15, time: 0.427, data_time: 0.000, memory: 9000, top1_acc: 0.9200, top5_acc: 0.9981, loss_cls: 2.1359, loss: 2.1359 +2025-05-28 19:16:57,842 - pyskl - INFO - Saving checkpoint at 42 epochs +2025-05-28 19:17:38,876 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 19:17:38,932 - pyskl - INFO - +top1_acc 0.8645 +top5_acc 0.9904 +2025-05-28 19:17:38,933 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 19:17:38,940 - pyskl - INFO - +mean_acc 0.8263 +2025-05-28 19:17:38,943 - pyskl - INFO - Epoch(val) [42][533] top1_acc: 0.8645, top5_acc: 0.9904, mean_class_accuracy: 0.8263 +2025-05-28 19:18:38,540 - pyskl - INFO - Epoch [43][100/1281] lr: 2.045e-02, eta: 15:36:25, time: 0.596, data_time: 0.173, memory: 9000, top1_acc: 0.9344, top5_acc: 0.9988, loss_cls: 1.9743, loss: 1.9743 +2025-05-28 19:19:20,817 - pyskl - INFO - Epoch [43][200/1281] lr: 2.044e-02, eta: 15:35:49, time: 0.423, data_time: 0.000, memory: 9000, top1_acc: 0.9294, top5_acc: 0.9988, loss_cls: 1.9945, loss: 1.9945 +2025-05-28 19:20:03,403 - pyskl - INFO - Epoch [43][300/1281] lr: 2.042e-02, eta: 15:35:13, time: 0.426, data_time: 0.000, memory: 9000, top1_acc: 0.9275, top5_acc: 0.9988, loss_cls: 1.9698, loss: 1.9698 +2025-05-28 19:20:45,198 - pyskl - INFO - Epoch [43][400/1281] lr: 2.040e-02, eta: 15:34:35, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9275, top5_acc: 0.9994, loss_cls: 2.0191, loss: 2.0191 +2025-05-28 19:21:26,899 - pyskl - INFO - Epoch [43][500/1281] lr: 2.039e-02, eta: 15:33:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9975, loss_cls: 2.0823, loss: 2.0823 +2025-05-28 19:22:08,565 - pyskl - INFO - Epoch [43][600/1281] lr: 2.037e-02, eta: 15:33:19, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9313, top5_acc: 0.9981, loss_cls: 1.9455, loss: 1.9455 +2025-05-28 19:22:50,328 - pyskl - INFO - Epoch [43][700/1281] lr: 2.036e-02, eta: 15:32:41, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9294, top5_acc: 0.9969, loss_cls: 1.9453, loss: 1.9453 +2025-05-28 19:23:31,978 - pyskl - INFO - Epoch [43][800/1281] lr: 2.034e-02, eta: 15:32:03, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 1.9932, loss: 1.9932 +2025-05-28 19:24:13,644 - pyskl - INFO - Epoch [43][900/1281] lr: 2.033e-02, eta: 15:31:25, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9337, top5_acc: 0.9988, loss_cls: 1.9535, loss: 1.9535 +2025-05-28 19:24:55,323 - pyskl - INFO - Epoch [43][1000/1281] lr: 2.031e-02, eta: 15:30:47, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9094, top5_acc: 0.9969, loss_cls: 2.1142, loss: 2.1142 +2025-05-28 19:25:37,118 - pyskl - INFO - Epoch [43][1100/1281] lr: 2.029e-02, eta: 15:30:09, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9169, top5_acc: 0.9962, loss_cls: 1.9818, loss: 1.9818 +2025-05-28 19:26:18,914 - pyskl - INFO - Epoch [43][1200/1281] lr: 2.028e-02, eta: 15:29:31, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9075, top5_acc: 0.9975, loss_cls: 2.0507, loss: 2.0507 +2025-05-28 19:26:53,381 - pyskl - INFO - Saving checkpoint at 43 epochs +2025-05-28 19:27:34,390 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 19:27:34,448 - pyskl - INFO - +top1_acc 0.8513 +top5_acc 0.9879 +2025-05-28 19:27:34,448 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 19:27:34,455 - pyskl - INFO - +mean_acc 0.8173 +2025-05-28 19:27:34,458 - pyskl - INFO - Epoch(val) [43][533] top1_acc: 0.8513, top5_acc: 0.9879, mean_class_accuracy: 0.8173 +2025-05-28 19:28:34,245 - pyskl - INFO - Epoch [44][100/1281] lr: 2.025e-02, eta: 15:27:43, time: 0.598, data_time: 0.179, memory: 9000, top1_acc: 0.9369, top5_acc: 0.9969, loss_cls: 1.9357, loss: 1.9357 +2025-05-28 19:29:15,946 - pyskl - INFO - Epoch [44][200/1281] lr: 2.023e-02, eta: 15:27:05, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9456, top5_acc: 0.9988, loss_cls: 1.8471, loss: 1.8471 +2025-05-28 19:29:57,662 - pyskl - INFO - Epoch [44][300/1281] lr: 2.022e-02, eta: 15:26:27, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9225, top5_acc: 0.9994, loss_cls: 2.0652, loss: 2.0652 +2025-05-28 19:30:39,318 - pyskl - INFO - Epoch [44][400/1281] lr: 2.020e-02, eta: 15:25:49, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9150, top5_acc: 0.9969, loss_cls: 2.0854, loss: 2.0854 +2025-05-28 19:31:21,042 - pyskl - INFO - Epoch [44][500/1281] lr: 2.018e-02, eta: 15:25:11, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9200, top5_acc: 0.9988, loss_cls: 2.0015, loss: 2.0015 +2025-05-28 19:32:02,662 - pyskl - INFO - Epoch [44][600/1281] lr: 2.017e-02, eta: 15:24:33, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9325, top5_acc: 0.9988, loss_cls: 1.9703, loss: 1.9703 +2025-05-28 19:32:44,374 - pyskl - INFO - Epoch [44][700/1281] lr: 2.015e-02, eta: 15:23:55, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9263, top5_acc: 0.9988, loss_cls: 2.0316, loss: 2.0316 +2025-05-28 19:33:26,087 - pyskl - INFO - Epoch [44][800/1281] lr: 2.014e-02, eta: 15:23:17, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9213, top5_acc: 0.9975, loss_cls: 1.9449, loss: 1.9449 +2025-05-28 19:34:07,375 - pyskl - INFO - Epoch [44][900/1281] lr: 2.012e-02, eta: 15:22:38, time: 0.413, data_time: 0.000, memory: 9000, top1_acc: 0.9144, top5_acc: 0.9975, loss_cls: 2.0336, loss: 2.0336 +2025-05-28 19:34:48,576 - pyskl - INFO - Epoch [44][1000/1281] lr: 2.010e-02, eta: 15:21:58, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9250, top5_acc: 0.9956, loss_cls: 2.0672, loss: 2.0672 +2025-05-28 19:35:30,388 - pyskl - INFO - Epoch [44][1100/1281] lr: 2.009e-02, eta: 15:21:21, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9113, top5_acc: 0.9956, loss_cls: 2.0448, loss: 2.0448 +2025-05-28 19:36:12,285 - pyskl - INFO - Epoch [44][1200/1281] lr: 2.007e-02, eta: 15:20:43, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9294, top5_acc: 0.9975, loss_cls: 2.0414, loss: 2.0414 +2025-05-28 19:36:46,640 - pyskl - INFO - Saving checkpoint at 44 epochs +2025-05-28 19:37:28,062 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 19:37:28,118 - pyskl - INFO - +top1_acc 0.8787 +top5_acc 0.9923 +2025-05-28 19:37:28,118 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 19:37:28,124 - pyskl - INFO - +mean_acc 0.8361 +2025-05-28 19:37:28,126 - pyskl - INFO - Epoch(val) [44][533] top1_acc: 0.8787, top5_acc: 0.9923, mean_class_accuracy: 0.8361 +2025-05-28 19:38:27,894 - pyskl - INFO - Epoch [45][100/1281] lr: 2.004e-02, eta: 15:18:56, time: 0.598, data_time: 0.179, memory: 9000, top1_acc: 0.9313, top5_acc: 0.9988, loss_cls: 1.9618, loss: 1.9618 +2025-05-28 19:39:09,576 - pyskl - INFO - Epoch [45][200/1281] lr: 2.003e-02, eta: 15:18:18, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9256, top5_acc: 0.9975, loss_cls: 1.9973, loss: 1.9973 +2025-05-28 19:39:51,241 - pyskl - INFO - Epoch [45][300/1281] lr: 2.001e-02, eta: 15:17:40, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9294, top5_acc: 0.9994, loss_cls: 1.9711, loss: 1.9711 +2025-05-28 19:40:33,090 - pyskl - INFO - Epoch [45][400/1281] lr: 1.999e-02, eta: 15:17:02, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9969, loss_cls: 1.9781, loss: 1.9781 +2025-05-28 19:41:15,211 - pyskl - INFO - Epoch [45][500/1281] lr: 1.998e-02, eta: 15:16:25, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9988, loss_cls: 2.0311, loss: 2.0311 +2025-05-28 19:41:56,977 - pyskl - INFO - Epoch [45][600/1281] lr: 1.996e-02, eta: 15:15:47, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9287, top5_acc: 0.9988, loss_cls: 2.0247, loss: 2.0247 +2025-05-28 19:42:38,824 - pyskl - INFO - Epoch [45][700/1281] lr: 1.994e-02, eta: 15:15:09, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9087, top5_acc: 0.9981, loss_cls: 2.0142, loss: 2.0142 +2025-05-28 19:43:20,588 - pyskl - INFO - Epoch [45][800/1281] lr: 1.993e-02, eta: 15:14:31, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9200, top5_acc: 1.0000, loss_cls: 1.9365, loss: 1.9365 +2025-05-28 19:44:02,340 - pyskl - INFO - Epoch [45][900/1281] lr: 1.991e-02, eta: 15:13:53, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9206, top5_acc: 0.9994, loss_cls: 2.0069, loss: 2.0069 +2025-05-28 19:44:44,111 - pyskl - INFO - Epoch [45][1000/1281] lr: 1.989e-02, eta: 15:13:15, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9350, top5_acc: 0.9981, loss_cls: 1.9274, loss: 1.9274 +2025-05-28 19:45:25,814 - pyskl - INFO - Epoch [45][1100/1281] lr: 1.988e-02, eta: 15:12:37, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9100, top5_acc: 0.9975, loss_cls: 1.9957, loss: 1.9957 +2025-05-28 19:46:07,637 - pyskl - INFO - Epoch [45][1200/1281] lr: 1.986e-02, eta: 15:11:59, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9038, top5_acc: 0.9969, loss_cls: 2.1687, loss: 2.1687 +2025-05-28 19:46:42,078 - pyskl - INFO - Saving checkpoint at 45 epochs +2025-05-28 19:59:46,883 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 19:59:46,938 - pyskl - INFO - +top1_acc 0.8715 +top5_acc 0.9919 +2025-05-28 19:59:46,938 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 19:59:46,945 - pyskl - INFO - +mean_acc 0.8316 +2025-05-28 19:59:46,947 - pyskl - INFO - Epoch(val) [45][533] top1_acc: 0.8715, top5_acc: 0.9919, mean_class_accuracy: 0.8316 +2025-05-28 20:00:46,453 - pyskl - INFO - Epoch [46][100/1281] lr: 1.983e-02, eta: 15:10:13, time: 0.595, data_time: 0.176, memory: 9000, top1_acc: 0.9325, top5_acc: 0.9994, loss_cls: 1.9318, loss: 1.9318 +2025-05-28 20:01:28,181 - pyskl - INFO - Epoch [46][200/1281] lr: 1.981e-02, eta: 15:09:34, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9363, top5_acc: 0.9988, loss_cls: 1.9420, loss: 1.9420 +2025-05-28 20:02:09,996 - pyskl - INFO - Epoch [46][300/1281] lr: 1.980e-02, eta: 15:08:57, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9244, top5_acc: 0.9975, loss_cls: 2.0006, loss: 2.0006 +2025-05-28 20:02:52,699 - pyskl - INFO - Epoch [46][400/1281] lr: 1.978e-02, eta: 15:08:21, time: 0.427, data_time: 0.000, memory: 9000, top1_acc: 0.9137, top5_acc: 0.9981, loss_cls: 2.0891, loss: 2.0891 +2025-05-28 20:03:34,647 - pyskl - INFO - Epoch [46][500/1281] lr: 1.976e-02, eta: 15:07:43, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9194, top5_acc: 0.9988, loss_cls: 1.9986, loss: 1.9986 +2025-05-28 20:04:16,497 - pyskl - INFO - Epoch [46][600/1281] lr: 1.975e-02, eta: 15:07:05, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9981, loss_cls: 2.0194, loss: 2.0194 +2025-05-28 20:04:58,150 - pyskl - INFO - Epoch [46][700/1281] lr: 1.973e-02, eta: 15:06:27, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9275, top5_acc: 0.9988, loss_cls: 2.0323, loss: 2.0323 +2025-05-28 20:05:39,812 - pyskl - INFO - Epoch [46][800/1281] lr: 1.971e-02, eta: 15:05:48, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9169, top5_acc: 0.9981, loss_cls: 1.9647, loss: 1.9647 +2025-05-28 20:06:21,526 - pyskl - INFO - Epoch [46][900/1281] lr: 1.970e-02, eta: 15:05:10, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9181, top5_acc: 0.9981, loss_cls: 2.0441, loss: 2.0441 +2025-05-28 20:07:03,513 - pyskl - INFO - Epoch [46][1000/1281] lr: 1.968e-02, eta: 15:04:33, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9225, top5_acc: 0.9988, loss_cls: 2.0130, loss: 2.0130 +2025-05-28 20:07:45,334 - pyskl - INFO - Epoch [46][1100/1281] lr: 1.966e-02, eta: 15:03:55, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9263, top5_acc: 0.9981, loss_cls: 2.0411, loss: 2.0411 +2025-05-28 20:08:27,042 - pyskl - INFO - Epoch [46][1200/1281] lr: 1.965e-02, eta: 15:03:16, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9237, top5_acc: 0.9969, loss_cls: 1.9739, loss: 1.9739 +2025-05-28 20:09:01,594 - pyskl - INFO - Saving checkpoint at 46 epochs +2025-05-28 20:09:42,884 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 20:09:42,939 - pyskl - INFO - +top1_acc 0.8933 +top5_acc 0.9935 +2025-05-28 20:09:42,939 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 20:09:42,946 - pyskl - INFO - +mean_acc 0.8415 +2025-05-28 20:09:43,018 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_38.pth was removed +2025-05-28 20:09:44,504 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_46.pth. +2025-05-28 20:09:44,504 - pyskl - INFO - Best top1_acc is 0.8933 at 46 epoch. +2025-05-28 20:09:44,508 - pyskl - INFO - Epoch(val) [46][533] top1_acc: 0.8933, top5_acc: 0.9935, mean_class_accuracy: 0.8415 +2025-05-28 20:10:44,150 - pyskl - INFO - Epoch [47][100/1281] lr: 1.962e-02, eta: 15:01:31, time: 0.596, data_time: 0.179, memory: 9000, top1_acc: 0.9194, top5_acc: 0.9981, loss_cls: 1.9902, loss: 1.9902 +2025-05-28 20:11:25,969 - pyskl - INFO - Epoch [47][200/1281] lr: 1.960e-02, eta: 15:00:53, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9363, top5_acc: 0.9975, loss_cls: 1.9435, loss: 1.9435 +2025-05-28 20:12:07,585 - pyskl - INFO - Epoch [47][300/1281] lr: 1.958e-02, eta: 15:00:15, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9375, top5_acc: 0.9975, loss_cls: 1.9179, loss: 1.9179 +2025-05-28 20:12:49,257 - pyskl - INFO - Epoch [47][400/1281] lr: 1.957e-02, eta: 14:59:37, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 0.9994, loss_cls: 1.9119, loss: 1.9119 +2025-05-28 20:13:30,929 - pyskl - INFO - Epoch [47][500/1281] lr: 1.955e-02, eta: 14:58:58, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9237, top5_acc: 0.9962, loss_cls: 1.9449, loss: 1.9449 +2025-05-28 20:14:12,617 - pyskl - INFO - Epoch [47][600/1281] lr: 1.953e-02, eta: 14:58:20, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9975, loss_cls: 1.8947, loss: 1.8947 +2025-05-28 20:14:54,360 - pyskl - INFO - Epoch [47][700/1281] lr: 1.952e-02, eta: 14:57:42, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9163, top5_acc: 0.9981, loss_cls: 2.1053, loss: 2.1053 +2025-05-28 20:15:36,042 - pyskl - INFO - Epoch [47][800/1281] lr: 1.950e-02, eta: 14:57:03, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9981, loss_cls: 2.0251, loss: 2.0251 +2025-05-28 20:16:17,776 - pyskl - INFO - Epoch [47][900/1281] lr: 1.948e-02, eta: 14:56:25, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9981, loss_cls: 2.0812, loss: 2.0812 +2025-05-28 20:16:59,609 - pyskl - INFO - Epoch [47][1000/1281] lr: 1.947e-02, eta: 14:55:47, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9187, top5_acc: 0.9938, loss_cls: 2.0502, loss: 2.0502 +2025-05-28 20:17:41,420 - pyskl - INFO - Epoch [47][1100/1281] lr: 1.945e-02, eta: 14:55:09, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9350, top5_acc: 0.9975, loss_cls: 1.9289, loss: 1.9289 +2025-05-28 20:18:23,131 - pyskl - INFO - Epoch [47][1200/1281] lr: 1.943e-02, eta: 14:54:31, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9144, top5_acc: 0.9969, loss_cls: 2.0362, loss: 2.0362 +2025-05-28 20:18:57,456 - pyskl - INFO - Saving checkpoint at 47 epochs +2025-05-28 20:19:38,779 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 20:19:38,834 - pyskl - INFO - +top1_acc 0.8814 +top5_acc 0.9925 +2025-05-28 20:19:38,834 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 20:19:38,841 - pyskl - INFO - +mean_acc 0.8472 +2025-05-28 20:19:38,843 - pyskl - INFO - Epoch(val) [47][533] top1_acc: 0.8814, top5_acc: 0.9925, mean_class_accuracy: 0.8472 +2025-05-28 20:20:38,266 - pyskl - INFO - Epoch [48][100/1281] lr: 1.940e-02, eta: 14:52:46, time: 0.594, data_time: 0.177, memory: 9000, top1_acc: 0.9231, top5_acc: 0.9988, loss_cls: 2.0216, loss: 2.0216 +2025-05-28 20:21:19,966 - pyskl - INFO - Epoch [48][200/1281] lr: 1.938e-02, eta: 14:52:08, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9500, top5_acc: 1.0000, loss_cls: 1.8588, loss: 1.8588 +2025-05-28 20:22:01,666 - pyskl - INFO - Epoch [48][300/1281] lr: 1.937e-02, eta: 14:51:30, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9456, top5_acc: 0.9981, loss_cls: 1.8817, loss: 1.8817 +2025-05-28 20:22:43,349 - pyskl - INFO - Epoch [48][400/1281] lr: 1.935e-02, eta: 14:50:51, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9369, top5_acc: 0.9988, loss_cls: 1.9592, loss: 1.9592 +2025-05-28 20:23:25,061 - pyskl - INFO - Epoch [48][500/1281] lr: 1.933e-02, eta: 14:50:13, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9213, top5_acc: 0.9969, loss_cls: 2.0427, loss: 2.0427 +2025-05-28 20:24:06,689 - pyskl - INFO - Epoch [48][600/1281] lr: 1.932e-02, eta: 14:49:34, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9387, top5_acc: 0.9981, loss_cls: 1.9119, loss: 1.9119 +2025-05-28 20:24:49,069 - pyskl - INFO - Epoch [48][700/1281] lr: 1.930e-02, eta: 14:48:58, time: 0.424, data_time: 0.000, memory: 9000, top1_acc: 0.9219, top5_acc: 0.9975, loss_cls: 2.0725, loss: 2.0725 +2025-05-28 20:25:30,960 - pyskl - INFO - Epoch [48][800/1281] lr: 1.928e-02, eta: 14:48:20, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9250, top5_acc: 0.9969, loss_cls: 1.9962, loss: 1.9962 +2025-05-28 20:26:12,757 - pyskl - INFO - Epoch [48][900/1281] lr: 1.926e-02, eta: 14:47:41, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9169, top5_acc: 0.9981, loss_cls: 1.9749, loss: 1.9749 +2025-05-28 20:26:54,587 - pyskl - INFO - Epoch [48][1000/1281] lr: 1.925e-02, eta: 14:47:03, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 1.9755, loss: 1.9755 +2025-05-28 20:27:36,336 - pyskl - INFO - Epoch [48][1100/1281] lr: 1.923e-02, eta: 14:46:25, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9250, top5_acc: 0.9994, loss_cls: 1.9911, loss: 1.9911 +2025-05-28 20:28:18,004 - pyskl - INFO - Epoch [48][1200/1281] lr: 1.921e-02, eta: 14:45:47, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9200, top5_acc: 0.9994, loss_cls: 1.9966, loss: 1.9966 +2025-05-28 20:28:52,397 - pyskl - INFO - Saving checkpoint at 48 epochs +2025-05-28 20:29:33,706 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 20:29:33,761 - pyskl - INFO - +top1_acc 0.8929 +top5_acc 0.9924 +2025-05-28 20:29:33,761 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 20:29:33,768 - pyskl - INFO - +mean_acc 0.8454 +2025-05-28 20:29:33,771 - pyskl - INFO - Epoch(val) [48][533] top1_acc: 0.8929, top5_acc: 0.9924, mean_class_accuracy: 0.8454 +2025-05-28 20:30:33,196 - pyskl - INFO - Epoch [49][100/1281] lr: 1.918e-02, eta: 14:44:03, time: 0.594, data_time: 0.177, memory: 9000, top1_acc: 0.9425, top5_acc: 1.0000, loss_cls: 1.8879, loss: 1.8879 +2025-05-28 20:31:14,788 - pyskl - INFO - Epoch [49][200/1281] lr: 1.916e-02, eta: 14:43:24, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 0.9994, loss_cls: 1.8741, loss: 1.8741 +2025-05-28 20:31:56,380 - pyskl - INFO - Epoch [49][300/1281] lr: 1.915e-02, eta: 14:42:46, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9219, top5_acc: 0.9975, loss_cls: 1.9327, loss: 1.9327 +2025-05-28 20:32:38,244 - pyskl - INFO - Epoch [49][400/1281] lr: 1.913e-02, eta: 14:42:08, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9356, top5_acc: 0.9994, loss_cls: 1.8419, loss: 1.8419 +2025-05-28 20:33:20,088 - pyskl - INFO - Epoch [49][500/1281] lr: 1.911e-02, eta: 14:41:30, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9325, top5_acc: 0.9988, loss_cls: 1.9215, loss: 1.9215 +2025-05-28 20:34:01,992 - pyskl - INFO - Epoch [49][600/1281] lr: 1.909e-02, eta: 14:40:52, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9213, top5_acc: 0.9988, loss_cls: 2.0599, loss: 2.0599 +2025-05-28 20:34:43,771 - pyskl - INFO - Epoch [49][700/1281] lr: 1.908e-02, eta: 14:40:13, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9194, top5_acc: 0.9988, loss_cls: 1.9459, loss: 1.9459 +2025-05-28 20:35:25,485 - pyskl - INFO - Epoch [49][800/1281] lr: 1.906e-02, eta: 14:39:35, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9200, top5_acc: 0.9988, loss_cls: 1.9813, loss: 1.9813 +2025-05-28 20:36:07,162 - pyskl - INFO - Epoch [49][900/1281] lr: 1.904e-02, eta: 14:38:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9213, top5_acc: 0.9988, loss_cls: 1.9942, loss: 1.9942 +2025-05-28 20:36:48,973 - pyskl - INFO - Epoch [49][1000/1281] lr: 1.902e-02, eta: 14:38:18, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9306, top5_acc: 0.9981, loss_cls: 1.9076, loss: 1.9076 +2025-05-28 20:37:30,852 - pyskl - INFO - Epoch [49][1100/1281] lr: 1.901e-02, eta: 14:37:40, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9056, top5_acc: 0.9988, loss_cls: 2.0775, loss: 2.0775 +2025-05-28 20:38:12,635 - pyskl - INFO - Epoch [49][1200/1281] lr: 1.899e-02, eta: 14:37:02, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9313, top5_acc: 0.9981, loss_cls: 1.8818, loss: 1.8818 +2025-05-28 20:38:47,198 - pyskl - INFO - Saving checkpoint at 49 epochs +2025-05-28 20:39:28,542 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 20:39:28,598 - pyskl - INFO - +top1_acc 0.8812 +top5_acc 0.9937 +2025-05-28 20:39:28,598 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 20:39:28,605 - pyskl - INFO - +mean_acc 0.8351 +2025-05-28 20:39:28,608 - pyskl - INFO - Epoch(val) [49][533] top1_acc: 0.8812, top5_acc: 0.9937, mean_class_accuracy: 0.8351 +2025-05-28 20:40:28,357 - pyskl - INFO - Epoch [50][100/1281] lr: 1.896e-02, eta: 14:35:20, time: 0.597, data_time: 0.179, memory: 9000, top1_acc: 0.9369, top5_acc: 0.9975, loss_cls: 1.9792, loss: 1.9792 +2025-05-28 20:41:10,081 - pyskl - INFO - Epoch [50][200/1281] lr: 1.894e-02, eta: 14:34:42, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9313, top5_acc: 0.9981, loss_cls: 1.8690, loss: 1.8690 +2025-05-28 20:41:51,794 - pyskl - INFO - Epoch [50][300/1281] lr: 1.892e-02, eta: 14:34:03, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9313, top5_acc: 0.9981, loss_cls: 1.9623, loss: 1.9623 +2025-05-28 20:42:33,560 - pyskl - INFO - Epoch [50][400/1281] lr: 1.891e-02, eta: 14:33:25, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9231, top5_acc: 0.9969, loss_cls: 1.9897, loss: 1.9897 +2025-05-28 20:43:14,896 - pyskl - INFO - Epoch [50][500/1281] lr: 1.889e-02, eta: 14:32:46, time: 0.413, data_time: 0.000, memory: 9000, top1_acc: 0.9350, top5_acc: 0.9988, loss_cls: 1.9430, loss: 1.9430 +2025-05-28 20:43:56,066 - pyskl - INFO - Epoch [50][600/1281] lr: 1.887e-02, eta: 14:32:06, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9319, top5_acc: 0.9981, loss_cls: 1.9639, loss: 1.9639 +2025-05-28 20:44:37,234 - pyskl - INFO - Epoch [50][700/1281] lr: 1.885e-02, eta: 14:31:27, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9519, top5_acc: 0.9988, loss_cls: 1.8591, loss: 1.8591 +2025-05-28 20:45:18,855 - pyskl - INFO - Epoch [50][800/1281] lr: 1.884e-02, eta: 14:30:48, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9319, top5_acc: 1.0000, loss_cls: 1.9897, loss: 1.9897 +2025-05-28 20:46:00,555 - pyskl - INFO - Epoch [50][900/1281] lr: 1.882e-02, eta: 14:30:09, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9975, loss_cls: 1.9627, loss: 1.9627 +2025-05-28 20:46:43,319 - pyskl - INFO - Epoch [50][1000/1281] lr: 1.880e-02, eta: 14:29:33, time: 0.428, data_time: 0.000, memory: 9000, top1_acc: 0.9213, top5_acc: 0.9988, loss_cls: 1.9047, loss: 1.9047 +2025-05-28 20:47:25,157 - pyskl - INFO - Epoch [50][1100/1281] lr: 1.878e-02, eta: 14:28:55, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9106, top5_acc: 0.9981, loss_cls: 2.0658, loss: 2.0658 +2025-05-28 20:48:06,942 - pyskl - INFO - Epoch [50][1200/1281] lr: 1.876e-02, eta: 14:28:17, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9256, top5_acc: 0.9988, loss_cls: 1.8979, loss: 1.8979 +2025-05-28 20:48:41,517 - pyskl - INFO - Saving checkpoint at 50 epochs +2025-05-28 21:02:27,577 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 21:02:27,633 - pyskl - INFO - +top1_acc 0.8765 +top5_acc 0.9940 +2025-05-28 21:02:27,634 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 21:02:27,640 - pyskl - INFO - +mean_acc 0.8495 +2025-05-28 21:02:27,643 - pyskl - INFO - Epoch(val) [50][533] top1_acc: 0.8765, top5_acc: 0.9940, mean_class_accuracy: 0.8495 +2025-05-28 21:03:27,089 - pyskl - INFO - Epoch [51][100/1281] lr: 1.873e-02, eta: 14:26:35, time: 0.594, data_time: 0.177, memory: 9000, top1_acc: 0.9344, top5_acc: 0.9981, loss_cls: 1.9264, loss: 1.9264 +2025-05-28 21:04:08,774 - pyskl - INFO - Epoch [51][200/1281] lr: 1.871e-02, eta: 14:25:56, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 1.8575, loss: 1.8575 +2025-05-28 21:04:50,541 - pyskl - INFO - Epoch [51][300/1281] lr: 1.870e-02, eta: 14:25:18, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9425, top5_acc: 0.9981, loss_cls: 1.8558, loss: 1.8558 +2025-05-28 21:05:32,123 - pyskl - INFO - Epoch [51][400/1281] lr: 1.868e-02, eta: 14:24:39, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9387, top5_acc: 0.9994, loss_cls: 1.8848, loss: 1.8848 +2025-05-28 21:06:13,727 - pyskl - INFO - Epoch [51][500/1281] lr: 1.866e-02, eta: 14:24:00, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9263, top5_acc: 0.9956, loss_cls: 1.9175, loss: 1.9175 +2025-05-28 21:06:55,346 - pyskl - INFO - Epoch [51][600/1281] lr: 1.864e-02, eta: 14:23:22, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9394, top5_acc: 0.9981, loss_cls: 1.8912, loss: 1.8912 +2025-05-28 21:07:36,980 - pyskl - INFO - Epoch [51][700/1281] lr: 1.863e-02, eta: 14:22:43, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 1.8772, loss: 1.8772 +2025-05-28 21:08:19,751 - pyskl - INFO - Epoch [51][800/1281] lr: 1.861e-02, eta: 14:22:07, time: 0.428, data_time: 0.000, memory: 9000, top1_acc: 0.9331, top5_acc: 0.9988, loss_cls: 1.8540, loss: 1.8540 +2025-05-28 21:09:01,822 - pyskl - INFO - Epoch [51][900/1281] lr: 1.859e-02, eta: 14:21:29, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9256, top5_acc: 0.9988, loss_cls: 1.9249, loss: 1.9249 +2025-05-28 21:09:43,652 - pyskl - INFO - Epoch [51][1000/1281] lr: 1.857e-02, eta: 14:20:51, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9144, top5_acc: 0.9981, loss_cls: 2.0421, loss: 2.0421 +2025-05-28 21:10:25,396 - pyskl - INFO - Epoch [51][1100/1281] lr: 1.855e-02, eta: 14:20:12, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9988, loss_cls: 1.9132, loss: 1.9132 +2025-05-28 21:11:07,239 - pyskl - INFO - Epoch [51][1200/1281] lr: 1.854e-02, eta: 14:19:34, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9194, top5_acc: 0.9956, loss_cls: 1.9984, loss: 1.9984 +2025-05-28 21:11:41,579 - pyskl - INFO - Saving checkpoint at 51 epochs +2025-05-28 21:12:22,579 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 21:12:22,636 - pyskl - INFO - +top1_acc 0.8757 +top5_acc 0.9919 +2025-05-28 21:12:22,636 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 21:12:22,642 - pyskl - INFO - +mean_acc 0.8499 +2025-05-28 21:12:22,644 - pyskl - INFO - Epoch(val) [51][533] top1_acc: 0.8757, top5_acc: 0.9919, mean_class_accuracy: 0.8499 +2025-05-28 21:13:22,086 - pyskl - INFO - Epoch [52][100/1281] lr: 1.850e-02, eta: 14:17:53, time: 0.594, data_time: 0.177, memory: 9000, top1_acc: 0.9356, top5_acc: 0.9988, loss_cls: 1.8986, loss: 1.8986 +2025-05-28 21:14:03,832 - pyskl - INFO - Epoch [52][200/1281] lr: 1.849e-02, eta: 14:17:14, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9344, top5_acc: 0.9981, loss_cls: 1.8856, loss: 1.8856 +2025-05-28 21:14:45,519 - pyskl - INFO - Epoch [52][300/1281] lr: 1.847e-02, eta: 14:16:36, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9988, loss_cls: 1.9582, loss: 1.9582 +2025-05-28 21:15:27,230 - pyskl - INFO - Epoch [52][400/1281] lr: 1.845e-02, eta: 14:15:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9244, top5_acc: 0.9975, loss_cls: 1.9859, loss: 1.9859 +2025-05-28 21:16:08,992 - pyskl - INFO - Epoch [52][500/1281] lr: 1.843e-02, eta: 14:15:19, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9206, top5_acc: 0.9994, loss_cls: 1.8898, loss: 1.8898 +2025-05-28 21:16:50,796 - pyskl - INFO - Epoch [52][600/1281] lr: 1.841e-02, eta: 14:14:41, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9969, loss_cls: 1.9555, loss: 1.9555 +2025-05-28 21:17:32,523 - pyskl - INFO - Epoch [52][700/1281] lr: 1.840e-02, eta: 14:14:02, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9256, top5_acc: 0.9975, loss_cls: 1.8551, loss: 1.8551 +2025-05-28 21:18:14,304 - pyskl - INFO - Epoch [52][800/1281] lr: 1.838e-02, eta: 14:13:24, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9187, top5_acc: 0.9981, loss_cls: 1.9153, loss: 1.9153 +2025-05-28 21:18:56,153 - pyskl - INFO - Epoch [52][900/1281] lr: 1.836e-02, eta: 14:12:45, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9381, top5_acc: 0.9962, loss_cls: 1.9840, loss: 1.9840 +2025-05-28 21:19:37,781 - pyskl - INFO - Epoch [52][1000/1281] lr: 1.834e-02, eta: 14:12:06, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9344, top5_acc: 0.9988, loss_cls: 1.8355, loss: 1.8355 +2025-05-28 21:20:19,402 - pyskl - INFO - Epoch [52][1100/1281] lr: 1.832e-02, eta: 14:11:28, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9394, top5_acc: 0.9981, loss_cls: 1.8908, loss: 1.8908 +2025-05-28 21:21:01,292 - pyskl - INFO - Epoch [52][1200/1281] lr: 1.831e-02, eta: 14:10:49, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9375, top5_acc: 0.9994, loss_cls: 1.9112, loss: 1.9112 +2025-05-28 21:21:35,629 - pyskl - INFO - Saving checkpoint at 52 epochs +2025-05-28 21:22:16,736 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 21:22:16,794 - pyskl - INFO - +top1_acc 0.8812 +top5_acc 0.9927 +2025-05-28 21:22:16,794 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 21:22:16,802 - pyskl - INFO - +mean_acc 0.8498 +2025-05-28 21:22:16,805 - pyskl - INFO - Epoch(val) [52][533] top1_acc: 0.8812, top5_acc: 0.9927, mean_class_accuracy: 0.8498 +2025-05-28 21:23:16,248 - pyskl - INFO - Epoch [53][100/1281] lr: 1.827e-02, eta: 14:09:09, time: 0.594, data_time: 0.176, memory: 9000, top1_acc: 0.9419, top5_acc: 0.9975, loss_cls: 1.8409, loss: 1.8409 +2025-05-28 21:23:58,072 - pyskl - INFO - Epoch [53][200/1281] lr: 1.826e-02, eta: 14:08:31, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 1.7828, loss: 1.7828 +2025-05-28 21:24:39,752 - pyskl - INFO - Epoch [53][300/1281] lr: 1.824e-02, eta: 14:07:52, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9231, top5_acc: 0.9975, loss_cls: 1.9740, loss: 1.9740 +2025-05-28 21:25:21,385 - pyskl - INFO - Epoch [53][400/1281] lr: 1.822e-02, eta: 14:07:14, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9337, top5_acc: 0.9975, loss_cls: 1.9609, loss: 1.9609 +2025-05-28 21:26:03,162 - pyskl - INFO - Epoch [53][500/1281] lr: 1.820e-02, eta: 14:06:35, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9456, top5_acc: 0.9981, loss_cls: 1.8869, loss: 1.8869 +2025-05-28 21:26:44,913 - pyskl - INFO - Epoch [53][600/1281] lr: 1.818e-02, eta: 14:05:57, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 0.9981, loss_cls: 1.8483, loss: 1.8483 +2025-05-28 21:27:26,667 - pyskl - INFO - Epoch [53][700/1281] lr: 1.816e-02, eta: 14:05:18, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9325, top5_acc: 0.9975, loss_cls: 1.9231, loss: 1.9231 +2025-05-28 21:28:08,470 - pyskl - INFO - Epoch [53][800/1281] lr: 1.815e-02, eta: 14:04:40, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9225, top5_acc: 0.9994, loss_cls: 1.9583, loss: 1.9583 +2025-05-28 21:28:50,304 - pyskl - INFO - Epoch [53][900/1281] lr: 1.813e-02, eta: 14:04:01, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 0.9981, loss_cls: 1.9273, loss: 1.9273 +2025-05-28 21:29:31,878 - pyskl - INFO - Epoch [53][1000/1281] lr: 1.811e-02, eta: 14:03:22, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9381, top5_acc: 0.9988, loss_cls: 1.8847, loss: 1.8847 +2025-05-28 21:30:14,261 - pyskl - INFO - Epoch [53][1100/1281] lr: 1.809e-02, eta: 14:02:45, time: 0.424, data_time: 0.000, memory: 9000, top1_acc: 0.9356, top5_acc: 0.9994, loss_cls: 1.8837, loss: 1.8837 +2025-05-28 21:30:56,379 - pyskl - INFO - Epoch [53][1200/1281] lr: 1.807e-02, eta: 14:02:07, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9313, top5_acc: 1.0000, loss_cls: 1.9533, loss: 1.9533 +2025-05-28 21:31:30,822 - pyskl - INFO - Saving checkpoint at 53 epochs +2025-05-28 21:32:11,491 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 21:32:11,549 - pyskl - INFO - +top1_acc 0.8748 +top5_acc 0.9937 +2025-05-28 21:32:11,549 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 21:32:11,556 - pyskl - INFO - +mean_acc 0.8538 +2025-05-28 21:32:11,563 - pyskl - INFO - Epoch(val) [53][533] top1_acc: 0.8748, top5_acc: 0.9937, mean_class_accuracy: 0.8538 +2025-05-28 21:33:10,896 - pyskl - INFO - Epoch [54][100/1281] lr: 1.804e-02, eta: 14:00:27, time: 0.593, data_time: 0.177, memory: 9000, top1_acc: 0.9381, top5_acc: 1.0000, loss_cls: 1.8982, loss: 1.8982 +2025-05-28 21:33:52,561 - pyskl - INFO - Epoch [54][200/1281] lr: 1.802e-02, eta: 13:59:49, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9475, top5_acc: 0.9988, loss_cls: 1.9140, loss: 1.9140 +2025-05-28 21:34:34,247 - pyskl - INFO - Epoch [54][300/1281] lr: 1.800e-02, eta: 13:59:10, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9381, top5_acc: 0.9988, loss_cls: 1.8862, loss: 1.8862 +2025-05-28 21:35:15,986 - pyskl - INFO - Epoch [54][400/1281] lr: 1.798e-02, eta: 13:58:31, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9256, top5_acc: 0.9988, loss_cls: 1.9193, loss: 1.9193 +2025-05-28 21:35:57,722 - pyskl - INFO - Epoch [54][500/1281] lr: 1.797e-02, eta: 13:57:53, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 0.9988, loss_cls: 1.8619, loss: 1.8619 +2025-05-28 21:36:39,467 - pyskl - INFO - Epoch [54][600/1281] lr: 1.795e-02, eta: 13:57:14, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9344, top5_acc: 0.9988, loss_cls: 1.8907, loss: 1.8907 +2025-05-28 21:37:21,181 - pyskl - INFO - Epoch [54][700/1281] lr: 1.793e-02, eta: 13:56:36, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9413, top5_acc: 0.9994, loss_cls: 1.8714, loss: 1.8714 +2025-05-28 21:38:03,101 - pyskl - INFO - Epoch [54][800/1281] lr: 1.791e-02, eta: 13:55:57, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9306, top5_acc: 1.0000, loss_cls: 1.9061, loss: 1.9061 +2025-05-28 21:38:45,076 - pyskl - INFO - Epoch [54][900/1281] lr: 1.789e-02, eta: 13:55:19, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9219, top5_acc: 0.9931, loss_cls: 2.0615, loss: 2.0615 +2025-05-28 21:39:26,759 - pyskl - INFO - Epoch [54][1000/1281] lr: 1.787e-02, eta: 13:54:40, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9244, top5_acc: 0.9994, loss_cls: 1.9401, loss: 1.9401 +2025-05-28 21:40:08,537 - pyskl - INFO - Epoch [54][1100/1281] lr: 1.786e-02, eta: 13:54:02, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9381, top5_acc: 0.9994, loss_cls: 1.8541, loss: 1.8541 +2025-05-28 21:40:50,342 - pyskl - INFO - Epoch [54][1200/1281] lr: 1.784e-02, eta: 13:53:23, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9988, loss_cls: 1.9816, loss: 1.9816 +2025-05-28 21:41:24,913 - pyskl - INFO - Saving checkpoint at 54 epochs +2025-05-28 21:42:06,193 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 21:42:06,249 - pyskl - INFO - +top1_acc 0.8860 +top5_acc 0.9916 +2025-05-28 21:42:06,249 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 21:42:06,255 - pyskl - INFO - +mean_acc 0.8550 +2025-05-28 21:42:06,258 - pyskl - INFO - Epoch(val) [54][533] top1_acc: 0.8860, top5_acc: 0.9916, mean_class_accuracy: 0.8550 +2025-05-28 21:43:05,896 - pyskl - INFO - Epoch [55][100/1281] lr: 1.780e-02, eta: 13:51:45, time: 0.596, data_time: 0.180, memory: 9000, top1_acc: 0.9369, top5_acc: 0.9988, loss_cls: 1.8202, loss: 1.8202 +2025-05-28 21:43:47,588 - pyskl - INFO - Epoch [55][200/1281] lr: 1.779e-02, eta: 13:51:06, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9456, top5_acc: 1.0000, loss_cls: 1.7473, loss: 1.7473 +2025-05-28 21:44:29,399 - pyskl - INFO - Epoch [55][300/1281] lr: 1.777e-02, eta: 13:50:28, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9994, loss_cls: 1.8438, loss: 1.8438 +2025-05-28 21:45:11,087 - pyskl - INFO - Epoch [55][400/1281] lr: 1.775e-02, eta: 13:49:49, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9213, top5_acc: 0.9981, loss_cls: 1.9110, loss: 1.9110 +2025-05-28 21:45:52,784 - pyskl - INFO - Epoch [55][500/1281] lr: 1.773e-02, eta: 13:49:10, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9281, top5_acc: 0.9988, loss_cls: 1.9315, loss: 1.9315 +2025-05-28 21:46:34,527 - pyskl - INFO - Epoch [55][600/1281] lr: 1.771e-02, eta: 13:48:32, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9150, top5_acc: 0.9994, loss_cls: 1.9452, loss: 1.9452 +2025-05-28 21:47:16,409 - pyskl - INFO - Epoch [55][700/1281] lr: 1.769e-02, eta: 13:47:53, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9381, top5_acc: 0.9981, loss_cls: 1.8443, loss: 1.8443 +2025-05-28 21:47:58,203 - pyskl - INFO - Epoch [55][800/1281] lr: 1.767e-02, eta: 13:47:15, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9337, top5_acc: 0.9975, loss_cls: 2.0015, loss: 2.0015 +2025-05-28 21:48:39,842 - pyskl - INFO - Epoch [55][900/1281] lr: 1.766e-02, eta: 13:46:36, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9375, top5_acc: 0.9969, loss_cls: 1.8062, loss: 1.8062 +2025-05-28 21:49:21,421 - pyskl - INFO - Epoch [55][1000/1281] lr: 1.764e-02, eta: 13:45:57, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9400, top5_acc: 0.9994, loss_cls: 1.9026, loss: 1.9026 +2025-05-28 21:50:03,013 - pyskl - INFO - Epoch [55][1100/1281] lr: 1.762e-02, eta: 13:45:18, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9981, loss_cls: 1.9463, loss: 1.9463 +2025-05-28 21:50:44,601 - pyskl - INFO - Epoch [55][1200/1281] lr: 1.760e-02, eta: 13:44:39, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9363, top5_acc: 1.0000, loss_cls: 1.8368, loss: 1.8368 +2025-05-28 21:51:18,995 - pyskl - INFO - Saving checkpoint at 55 epochs +2025-05-28 22:04:19,909 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 22:04:19,965 - pyskl - INFO - +top1_acc 0.8950 +top5_acc 0.9940 +2025-05-28 22:04:19,966 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 22:04:19,977 - pyskl - INFO - +mean_acc 0.8571 +2025-05-28 22:04:20,037 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_46.pth was removed +2025-05-28 22:04:21,512 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_55.pth. +2025-05-28 22:04:21,513 - pyskl - INFO - Best top1_acc is 0.8950 at 55 epoch. +2025-05-28 22:04:21,517 - pyskl - INFO - Epoch(val) [55][533] top1_acc: 0.8950, top5_acc: 0.9940, mean_class_accuracy: 0.8571 +2025-05-28 22:05:20,997 - pyskl - INFO - Epoch [56][100/1281] lr: 1.757e-02, eta: 13:43:01, time: 0.595, data_time: 0.177, memory: 9000, top1_acc: 0.9556, top5_acc: 0.9994, loss_cls: 1.7488, loss: 1.7488 +2025-05-28 22:06:02,675 - pyskl - INFO - Epoch [56][200/1281] lr: 1.755e-02, eta: 13:42:22, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9513, top5_acc: 0.9988, loss_cls: 1.8057, loss: 1.8057 +2025-05-28 22:06:44,331 - pyskl - INFO - Epoch [56][300/1281] lr: 1.753e-02, eta: 13:41:44, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9306, top5_acc: 0.9988, loss_cls: 1.9203, loss: 1.9203 +2025-05-28 22:07:26,044 - pyskl - INFO - Epoch [56][400/1281] lr: 1.751e-02, eta: 13:41:05, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9400, top5_acc: 0.9975, loss_cls: 1.8091, loss: 1.8091 +2025-05-28 22:08:07,794 - pyskl - INFO - Epoch [56][500/1281] lr: 1.749e-02, eta: 13:40:26, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 1.7574, loss: 1.7574 +2025-05-28 22:08:49,543 - pyskl - INFO - Epoch [56][600/1281] lr: 1.747e-02, eta: 13:39:47, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9475, top5_acc: 0.9988, loss_cls: 1.8239, loss: 1.8239 +2025-05-28 22:09:31,284 - pyskl - INFO - Epoch [56][700/1281] lr: 1.745e-02, eta: 13:39:09, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9219, top5_acc: 0.9981, loss_cls: 1.8940, loss: 1.8940 +2025-05-28 22:10:12,945 - pyskl - INFO - Epoch [56][800/1281] lr: 1.743e-02, eta: 13:38:30, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9181, top5_acc: 0.9988, loss_cls: 2.0351, loss: 2.0351 +2025-05-28 22:10:54,606 - pyskl - INFO - Epoch [56][900/1281] lr: 1.742e-02, eta: 13:37:51, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9381, top5_acc: 0.9975, loss_cls: 1.9103, loss: 1.9103 +2025-05-28 22:11:36,446 - pyskl - INFO - Epoch [56][1000/1281] lr: 1.740e-02, eta: 13:37:12, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9306, top5_acc: 0.9981, loss_cls: 1.8375, loss: 1.8375 +2025-05-28 22:12:18,349 - pyskl - INFO - Epoch [56][1100/1281] lr: 1.738e-02, eta: 13:36:34, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9975, loss_cls: 1.9080, loss: 1.9080 +2025-05-28 22:12:59,965 - pyskl - INFO - Epoch [56][1200/1281] lr: 1.736e-02, eta: 13:35:55, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9187, top5_acc: 0.9988, loss_cls: 2.0478, loss: 2.0478 +2025-05-28 22:13:34,321 - pyskl - INFO - Saving checkpoint at 56 epochs +2025-05-28 22:14:15,363 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 22:14:15,416 - pyskl - INFO - +top1_acc 0.8729 +top5_acc 0.9919 +2025-05-28 22:14:15,416 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 22:14:15,422 - pyskl - INFO - +mean_acc 0.8319 +2025-05-28 22:14:15,424 - pyskl - INFO - Epoch(val) [56][533] top1_acc: 0.8729, top5_acc: 0.9919, mean_class_accuracy: 0.8319 +2025-05-28 22:15:15,554 - pyskl - INFO - Epoch [57][100/1281] lr: 1.733e-02, eta: 13:34:19, time: 0.601, data_time: 0.183, memory: 9000, top1_acc: 0.9337, top5_acc: 0.9988, loss_cls: 1.8309, loss: 1.8309 +2025-05-28 22:15:57,438 - pyskl - INFO - Epoch [57][200/1281] lr: 1.731e-02, eta: 13:33:40, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9487, top5_acc: 0.9975, loss_cls: 1.8358, loss: 1.8358 +2025-05-28 22:16:39,191 - pyskl - INFO - Epoch [57][300/1281] lr: 1.729e-02, eta: 13:33:02, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9331, top5_acc: 0.9994, loss_cls: 1.8294, loss: 1.8294 +2025-05-28 22:17:20,818 - pyskl - INFO - Epoch [57][400/1281] lr: 1.727e-02, eta: 13:32:23, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 1.7516, loss: 1.7516 +2025-05-28 22:18:02,437 - pyskl - INFO - Epoch [57][500/1281] lr: 1.725e-02, eta: 13:31:44, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9331, top5_acc: 0.9994, loss_cls: 1.8550, loss: 1.8550 +2025-05-28 22:18:44,014 - pyskl - INFO - Epoch [57][600/1281] lr: 1.723e-02, eta: 13:31:05, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9450, top5_acc: 0.9981, loss_cls: 1.8946, loss: 1.8946 +2025-05-28 22:19:25,617 - pyskl - INFO - Epoch [57][700/1281] lr: 1.721e-02, eta: 13:30:26, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 0.9994, loss_cls: 1.8601, loss: 1.8601 +2025-05-28 22:20:07,235 - pyskl - INFO - Epoch [57][800/1281] lr: 1.719e-02, eta: 13:29:47, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9325, top5_acc: 1.0000, loss_cls: 1.9191, loss: 1.9191 +2025-05-28 22:20:48,926 - pyskl - INFO - Epoch [57][900/1281] lr: 1.717e-02, eta: 13:29:08, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 1.8437, loss: 1.8437 +2025-05-28 22:21:30,897 - pyskl - INFO - Epoch [57][1000/1281] lr: 1.716e-02, eta: 13:28:30, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 1.9534, loss: 1.9534 +2025-05-28 22:22:12,815 - pyskl - INFO - Epoch [57][1100/1281] lr: 1.714e-02, eta: 13:27:51, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9394, top5_acc: 0.9975, loss_cls: 1.9982, loss: 1.9982 +2025-05-28 22:22:54,557 - pyskl - INFO - Epoch [57][1200/1281] lr: 1.712e-02, eta: 13:27:12, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9225, top5_acc: 0.9969, loss_cls: 1.9321, loss: 1.9321 +2025-05-28 22:23:28,962 - pyskl - INFO - Saving checkpoint at 57 epochs +2025-05-28 22:24:09,889 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 22:24:09,946 - pyskl - INFO - +top1_acc 0.8891 +top5_acc 0.9916 +2025-05-28 22:24:09,946 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 22:24:09,953 - pyskl - INFO - +mean_acc 0.8569 +2025-05-28 22:24:09,955 - pyskl - INFO - Epoch(val) [57][533] top1_acc: 0.8891, top5_acc: 0.9916, mean_class_accuracy: 0.8569 +2025-05-28 22:25:10,010 - pyskl - INFO - Epoch [58][100/1281] lr: 1.708e-02, eta: 13:25:37, time: 0.601, data_time: 0.179, memory: 9000, top1_acc: 0.9494, top5_acc: 1.0000, loss_cls: 1.7877, loss: 1.7877 +2025-05-28 22:25:51,841 - pyskl - INFO - Epoch [58][200/1281] lr: 1.706e-02, eta: 13:24:58, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9550, top5_acc: 0.9994, loss_cls: 1.6863, loss: 1.6863 +2025-05-28 22:26:33,427 - pyskl - INFO - Epoch [58][300/1281] lr: 1.704e-02, eta: 13:24:19, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9325, top5_acc: 0.9981, loss_cls: 1.8479, loss: 1.8479 +2025-05-28 22:27:15,176 - pyskl - INFO - Epoch [58][400/1281] lr: 1.703e-02, eta: 13:23:40, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 0.9988, loss_cls: 1.8282, loss: 1.8282 +2025-05-28 22:27:56,828 - pyskl - INFO - Epoch [58][500/1281] lr: 1.701e-02, eta: 13:23:01, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9306, top5_acc: 0.9988, loss_cls: 1.9365, loss: 1.9365 +2025-05-28 22:28:38,485 - pyskl - INFO - Epoch [58][600/1281] lr: 1.699e-02, eta: 13:22:23, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9344, top5_acc: 0.9988, loss_cls: 1.9396, loss: 1.9396 +2025-05-28 22:29:20,135 - pyskl - INFO - Epoch [58][700/1281] lr: 1.697e-02, eta: 13:21:44, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9244, top5_acc: 0.9988, loss_cls: 1.9508, loss: 1.9508 +2025-05-28 22:30:01,414 - pyskl - INFO - Epoch [58][800/1281] lr: 1.695e-02, eta: 13:21:04, time: 0.413, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9988, loss_cls: 1.8713, loss: 1.8713 +2025-05-28 22:30:42,776 - pyskl - INFO - Epoch [58][900/1281] lr: 1.693e-02, eta: 13:20:25, time: 0.414, data_time: 0.000, memory: 9000, top1_acc: 0.9363, top5_acc: 0.9975, loss_cls: 1.8266, loss: 1.8266 +2025-05-28 22:31:24,779 - pyskl - INFO - Epoch [58][1000/1281] lr: 1.691e-02, eta: 13:19:46, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9275, top5_acc: 0.9981, loss_cls: 1.9570, loss: 1.9570 +2025-05-28 22:32:06,348 - pyskl - INFO - Epoch [58][1100/1281] lr: 1.689e-02, eta: 13:19:07, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9250, top5_acc: 0.9988, loss_cls: 2.0077, loss: 2.0077 +2025-05-28 22:32:47,493 - pyskl - INFO - Epoch [58][1200/1281] lr: 1.687e-02, eta: 13:18:27, time: 0.411, data_time: 0.000, memory: 9000, top1_acc: 0.9356, top5_acc: 0.9981, loss_cls: 1.8838, loss: 1.8838 +2025-05-28 22:33:21,332 - pyskl - INFO - Saving checkpoint at 58 epochs +2025-05-28 22:34:02,190 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 22:34:02,247 - pyskl - INFO - +top1_acc 0.8906 +top5_acc 0.9940 +2025-05-28 22:34:02,247 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 22:34:02,255 - pyskl - INFO - +mean_acc 0.8554 +2025-05-28 22:34:02,257 - pyskl - INFO - Epoch(val) [58][533] top1_acc: 0.8906, top5_acc: 0.9940, mean_class_accuracy: 0.8554 +2025-05-28 22:35:01,714 - pyskl - INFO - Epoch [59][100/1281] lr: 1.684e-02, eta: 13:16:51, time: 0.595, data_time: 0.178, memory: 9000, top1_acc: 0.9350, top5_acc: 0.9988, loss_cls: 1.8635, loss: 1.8635 +2025-05-28 22:35:43,387 - pyskl - INFO - Epoch [59][200/1281] lr: 1.682e-02, eta: 13:16:13, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9287, top5_acc: 1.0000, loss_cls: 1.8341, loss: 1.8341 +2025-05-28 22:36:26,102 - pyskl - INFO - Epoch [59][300/1281] lr: 1.680e-02, eta: 13:15:35, time: 0.427, data_time: 0.000, memory: 9000, top1_acc: 0.9369, top5_acc: 0.9981, loss_cls: 1.9299, loss: 1.9299 +2025-05-28 22:37:08,054 - pyskl - INFO - Epoch [59][400/1281] lr: 1.678e-02, eta: 13:14:57, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9281, top5_acc: 0.9981, loss_cls: 1.9303, loss: 1.9303 +2025-05-28 22:37:49,813 - pyskl - INFO - Epoch [59][500/1281] lr: 1.676e-02, eta: 13:14:18, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9356, top5_acc: 0.9988, loss_cls: 1.8820, loss: 1.8820 +2025-05-28 22:38:31,535 - pyskl - INFO - Epoch [59][600/1281] lr: 1.674e-02, eta: 13:13:39, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9425, top5_acc: 0.9981, loss_cls: 1.8998, loss: 1.8998 +2025-05-28 22:39:13,260 - pyskl - INFO - Epoch [59][700/1281] lr: 1.672e-02, eta: 13:13:00, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 1.7955, loss: 1.7955 +2025-05-28 22:39:54,986 - pyskl - INFO - Epoch [59][800/1281] lr: 1.670e-02, eta: 13:12:21, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9313, top5_acc: 0.9988, loss_cls: 1.8654, loss: 1.8654 +2025-05-28 22:40:36,837 - pyskl - INFO - Epoch [59][900/1281] lr: 1.668e-02, eta: 13:11:43, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9287, top5_acc: 0.9981, loss_cls: 1.8773, loss: 1.8773 +2025-05-28 22:41:18,688 - pyskl - INFO - Epoch [59][1000/1281] lr: 1.667e-02, eta: 13:11:04, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9413, top5_acc: 0.9981, loss_cls: 1.8652, loss: 1.8652 +2025-05-28 22:42:00,510 - pyskl - INFO - Epoch [59][1100/1281] lr: 1.665e-02, eta: 13:10:25, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9350, top5_acc: 0.9994, loss_cls: 1.8518, loss: 1.8518 +2025-05-28 22:42:42,323 - pyskl - INFO - Epoch [59][1200/1281] lr: 1.663e-02, eta: 13:09:46, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9231, top5_acc: 0.9969, loss_cls: 1.8399, loss: 1.8399 +2025-05-28 22:43:16,694 - pyskl - INFO - Saving checkpoint at 59 epochs +2025-05-28 22:43:57,738 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 22:43:57,795 - pyskl - INFO - +top1_acc 0.8871 +top5_acc 0.9933 +2025-05-28 22:43:57,795 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 22:43:57,803 - pyskl - INFO - +mean_acc 0.8431 +2025-05-28 22:43:57,805 - pyskl - INFO - Epoch(val) [59][533] top1_acc: 0.8871, top5_acc: 0.9933, mean_class_accuracy: 0.8431 +2025-05-28 22:44:57,246 - pyskl - INFO - Epoch [60][100/1281] lr: 1.659e-02, eta: 13:08:11, time: 0.594, data_time: 0.178, memory: 9000, top1_acc: 0.9500, top5_acc: 0.9981, loss_cls: 1.8351, loss: 1.8351 +2025-05-28 22:45:38,873 - pyskl - INFO - Epoch [60][200/1281] lr: 1.657e-02, eta: 13:07:32, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 1.7337, loss: 1.7337 +2025-05-28 22:46:20,521 - pyskl - INFO - Epoch [60][300/1281] lr: 1.655e-02, eta: 13:06:53, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9369, top5_acc: 0.9969, loss_cls: 1.8610, loss: 1.8610 +2025-05-28 22:47:02,346 - pyskl - INFO - Epoch [60][400/1281] lr: 1.653e-02, eta: 13:06:14, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9375, top5_acc: 0.9988, loss_cls: 1.8739, loss: 1.8739 +2025-05-28 22:47:44,207 - pyskl - INFO - Epoch [60][500/1281] lr: 1.651e-02, eta: 13:05:36, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9625, top5_acc: 0.9988, loss_cls: 1.7442, loss: 1.7442 +2025-05-28 22:48:25,932 - pyskl - INFO - Epoch [60][600/1281] lr: 1.650e-02, eta: 13:04:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9444, top5_acc: 0.9994, loss_cls: 1.8223, loss: 1.8223 +2025-05-28 22:49:07,518 - pyskl - INFO - Epoch [60][700/1281] lr: 1.648e-02, eta: 13:04:18, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9369, top5_acc: 0.9981, loss_cls: 1.7560, loss: 1.7560 +2025-05-28 22:49:48,711 - pyskl - INFO - Epoch [60][800/1281] lr: 1.646e-02, eta: 13:03:38, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9981, loss_cls: 1.8837, loss: 1.8837 +2025-05-28 22:50:29,882 - pyskl - INFO - Epoch [60][900/1281] lr: 1.644e-02, eta: 13:02:58, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9225, top5_acc: 0.9981, loss_cls: 1.9071, loss: 1.9071 +2025-05-28 22:51:11,562 - pyskl - INFO - Epoch [60][1000/1281] lr: 1.642e-02, eta: 13:02:19, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9163, top5_acc: 0.9975, loss_cls: 1.9352, loss: 1.9352 +2025-05-28 22:51:53,516 - pyskl - INFO - Epoch [60][1100/1281] lr: 1.640e-02, eta: 13:01:41, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9331, top5_acc: 0.9994, loss_cls: 1.9403, loss: 1.9403 +2025-05-28 22:52:35,322 - pyskl - INFO - Epoch [60][1200/1281] lr: 1.638e-02, eta: 13:01:02, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9263, top5_acc: 0.9994, loss_cls: 1.8226, loss: 1.8226 +2025-05-28 22:53:09,938 - pyskl - INFO - Saving checkpoint at 60 epochs +2025-05-28 23:06:16,958 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 23:06:17,013 - pyskl - INFO - +top1_acc 0.8837 +top5_acc 0.9935 +2025-05-28 23:06:17,013 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 23:06:17,020 - pyskl - INFO - +mean_acc 0.8372 +2025-05-28 23:06:17,022 - pyskl - INFO - Epoch(val) [60][533] top1_acc: 0.8837, top5_acc: 0.9935, mean_class_accuracy: 0.8372 +2025-05-28 23:07:16,491 - pyskl - INFO - Epoch [61][100/1281] lr: 1.634e-02, eta: 12:59:27, time: 0.595, data_time: 0.178, memory: 9000, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 1.8223, loss: 1.8223 +2025-05-28 23:07:58,129 - pyskl - INFO - Epoch [61][200/1281] lr: 1.632e-02, eta: 12:58:48, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 1.6835, loss: 1.6835 +2025-05-28 23:08:39,758 - pyskl - INFO - Epoch [61][300/1281] lr: 1.630e-02, eta: 12:58:09, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9425, top5_acc: 1.0000, loss_cls: 1.7759, loss: 1.7759 +2025-05-28 23:09:21,375 - pyskl - INFO - Epoch [61][400/1281] lr: 1.629e-02, eta: 12:57:30, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 0.9994, loss_cls: 1.8222, loss: 1.8222 +2025-05-28 23:10:03,017 - pyskl - INFO - Epoch [61][500/1281] lr: 1.627e-02, eta: 12:56:51, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9456, top5_acc: 0.9994, loss_cls: 1.7543, loss: 1.7543 +2025-05-28 23:10:44,771 - pyskl - INFO - Epoch [61][600/1281] lr: 1.625e-02, eta: 12:56:12, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 1.7671, loss: 1.7671 +2025-05-28 23:11:26,439 - pyskl - INFO - Epoch [61][700/1281] lr: 1.623e-02, eta: 12:55:33, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9256, top5_acc: 0.9981, loss_cls: 1.8785, loss: 1.8785 +2025-05-28 23:12:08,061 - pyskl - INFO - Epoch [61][800/1281] lr: 1.621e-02, eta: 12:54:54, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 1.8545, loss: 1.8545 +2025-05-28 23:12:49,830 - pyskl - INFO - Epoch [61][900/1281] lr: 1.619e-02, eta: 12:54:15, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 1.7294, loss: 1.7294 +2025-05-28 23:13:31,710 - pyskl - INFO - Epoch [61][1000/1281] lr: 1.617e-02, eta: 12:53:36, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9256, top5_acc: 0.9988, loss_cls: 1.8806, loss: 1.8806 +2025-05-28 23:14:13,421 - pyskl - INFO - Epoch [61][1100/1281] lr: 1.615e-02, eta: 12:52:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9256, top5_acc: 0.9981, loss_cls: 1.9258, loss: 1.9258 +2025-05-28 23:14:55,235 - pyskl - INFO - Epoch [61][1200/1281] lr: 1.613e-02, eta: 12:52:18, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9306, top5_acc: 0.9988, loss_cls: 1.8814, loss: 1.8814 +2025-05-28 23:15:29,559 - pyskl - INFO - Saving checkpoint at 61 epochs +2025-05-28 23:16:10,616 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 23:16:10,673 - pyskl - INFO - +top1_acc 0.9041 +top5_acc 0.9957 +2025-05-28 23:16:10,673 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 23:16:10,680 - pyskl - INFO - +mean_acc 0.8701 +2025-05-28 23:16:10,735 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_55.pth was removed +2025-05-28 23:16:12,226 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_61.pth. +2025-05-28 23:16:12,227 - pyskl - INFO - Best top1_acc is 0.9041 at 61 epoch. +2025-05-28 23:16:12,230 - pyskl - INFO - Epoch(val) [61][533] top1_acc: 0.9041, top5_acc: 0.9957, mean_class_accuracy: 0.8701 +2025-05-28 23:17:11,648 - pyskl - INFO - Epoch [62][100/1281] lr: 1.609e-02, eta: 12:50:44, time: 0.594, data_time: 0.178, memory: 9000, top1_acc: 0.9431, top5_acc: 0.9988, loss_cls: 1.7748, loss: 1.7748 +2025-05-28 23:17:53,218 - pyskl - INFO - Epoch [62][200/1281] lr: 1.607e-02, eta: 12:50:05, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9600, top5_acc: 0.9994, loss_cls: 1.7383, loss: 1.7383 +2025-05-28 23:18:34,838 - pyskl - INFO - Epoch [62][300/1281] lr: 1.605e-02, eta: 12:49:26, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9400, top5_acc: 0.9994, loss_cls: 1.8265, loss: 1.8265 +2025-05-28 23:19:16,596 - pyskl - INFO - Epoch [62][400/1281] lr: 1.603e-02, eta: 12:48:47, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9988, loss_cls: 1.8573, loss: 1.8573 +2025-05-28 23:19:58,885 - pyskl - INFO - Epoch [62][500/1281] lr: 1.602e-02, eta: 12:48:09, time: 0.423, data_time: 0.000, memory: 9000, top1_acc: 0.9400, top5_acc: 1.0000, loss_cls: 1.7701, loss: 1.7701 +2025-05-28 23:20:40,700 - pyskl - INFO - Epoch [62][600/1281] lr: 1.600e-02, eta: 12:47:30, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9375, top5_acc: 0.9994, loss_cls: 1.7584, loss: 1.7584 +2025-05-28 23:21:22,421 - pyskl - INFO - Epoch [62][700/1281] lr: 1.598e-02, eta: 12:46:51, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 1.8250, loss: 1.8250 +2025-05-28 23:22:04,318 - pyskl - INFO - Epoch [62][800/1281] lr: 1.596e-02, eta: 12:46:12, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9294, top5_acc: 0.9969, loss_cls: 1.8677, loss: 1.8677 +2025-05-28 23:22:46,195 - pyskl - INFO - Epoch [62][900/1281] lr: 1.594e-02, eta: 12:45:33, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9413, top5_acc: 0.9994, loss_cls: 1.8692, loss: 1.8692 +2025-05-28 23:23:28,091 - pyskl - INFO - Epoch [62][1000/1281] lr: 1.592e-02, eta: 12:44:55, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9337, top5_acc: 0.9988, loss_cls: 1.8797, loss: 1.8797 +2025-05-28 23:24:09,875 - pyskl - INFO - Epoch [62][1100/1281] lr: 1.590e-02, eta: 12:44:16, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9275, top5_acc: 0.9988, loss_cls: 1.8941, loss: 1.8941 +2025-05-28 23:24:51,508 - pyskl - INFO - Epoch [62][1200/1281] lr: 1.588e-02, eta: 12:43:37, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9975, loss_cls: 1.9449, loss: 1.9449 +2025-05-28 23:25:25,894 - pyskl - INFO - Saving checkpoint at 62 epochs +2025-05-28 23:26:06,814 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 23:26:06,870 - pyskl - INFO - +top1_acc 0.8852 +top5_acc 0.9940 +2025-05-28 23:26:06,870 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 23:26:06,877 - pyskl - INFO - +mean_acc 0.8620 +2025-05-28 23:26:06,878 - pyskl - INFO - Epoch(val) [62][533] top1_acc: 0.8852, top5_acc: 0.9940, mean_class_accuracy: 0.8620 +2025-05-28 23:27:06,487 - pyskl - INFO - Epoch [63][100/1281] lr: 1.584e-02, eta: 12:42:03, time: 0.596, data_time: 0.178, memory: 9000, top1_acc: 0.9475, top5_acc: 1.0000, loss_cls: 1.7808, loss: 1.7808 +2025-05-28 23:27:48,133 - pyskl - INFO - Epoch [63][200/1281] lr: 1.582e-02, eta: 12:41:24, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 1.7620, loss: 1.7620 +2025-05-28 23:28:29,798 - pyskl - INFO - Epoch [63][300/1281] lr: 1.580e-02, eta: 12:40:45, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9450, top5_acc: 0.9994, loss_cls: 1.8177, loss: 1.8177 +2025-05-28 23:29:11,535 - pyskl - INFO - Epoch [63][400/1281] lr: 1.578e-02, eta: 12:40:06, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9994, loss_cls: 1.9880, loss: 1.9880 +2025-05-28 23:29:53,279 - pyskl - INFO - Epoch [63][500/1281] lr: 1.576e-02, eta: 12:39:27, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9519, top5_acc: 1.0000, loss_cls: 1.7399, loss: 1.7399 +2025-05-28 23:30:34,970 - pyskl - INFO - Epoch [63][600/1281] lr: 1.574e-02, eta: 12:38:48, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9350, top5_acc: 0.9994, loss_cls: 1.7889, loss: 1.7889 +2025-05-28 23:31:16,641 - pyskl - INFO - Epoch [63][700/1281] lr: 1.572e-02, eta: 12:38:09, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9369, top5_acc: 0.9975, loss_cls: 1.8650, loss: 1.8650 +2025-05-28 23:31:58,250 - pyskl - INFO - Epoch [63][800/1281] lr: 1.570e-02, eta: 12:37:30, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 1.7681, loss: 1.7681 +2025-05-28 23:32:40,074 - pyskl - INFO - Epoch [63][900/1281] lr: 1.568e-02, eta: 12:36:51, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9437, top5_acc: 0.9994, loss_cls: 1.8501, loss: 1.8501 +2025-05-28 23:33:22,051 - pyskl - INFO - Epoch [63][1000/1281] lr: 1.566e-02, eta: 12:36:12, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 1.8219, loss: 1.8219 +2025-05-28 23:34:03,879 - pyskl - INFO - Epoch [63][1100/1281] lr: 1.564e-02, eta: 12:35:33, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9287, top5_acc: 0.9988, loss_cls: 1.9477, loss: 1.9477 +2025-05-28 23:34:45,710 - pyskl - INFO - Epoch [63][1200/1281] lr: 1.562e-02, eta: 12:34:54, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9344, top5_acc: 0.9981, loss_cls: 1.8835, loss: 1.8835 +2025-05-28 23:35:20,135 - pyskl - INFO - Saving checkpoint at 63 epochs +2025-05-28 23:36:01,074 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 23:36:01,131 - pyskl - INFO - +top1_acc 0.8871 +top5_acc 0.9907 +2025-05-28 23:36:01,131 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 23:36:01,139 - pyskl - INFO - +mean_acc 0.8509 +2025-05-28 23:36:01,141 - pyskl - INFO - Epoch(val) [63][533] top1_acc: 0.8871, top5_acc: 0.9907, mean_class_accuracy: 0.8509 +2025-05-28 23:37:00,772 - pyskl - INFO - Epoch [64][100/1281] lr: 1.559e-02, eta: 12:33:22, time: 0.596, data_time: 0.178, memory: 9000, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 1.7401, loss: 1.7401 +2025-05-28 23:37:42,540 - pyskl - INFO - Epoch [64][200/1281] lr: 1.557e-02, eta: 12:32:43, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9550, top5_acc: 0.9988, loss_cls: 1.6593, loss: 1.6593 +2025-05-28 23:38:24,330 - pyskl - INFO - Epoch [64][300/1281] lr: 1.555e-02, eta: 12:32:04, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9337, top5_acc: 0.9988, loss_cls: 1.8392, loss: 1.8392 +2025-05-28 23:39:05,989 - pyskl - INFO - Epoch [64][400/1281] lr: 1.553e-02, eta: 12:31:25, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 1.7482, loss: 1.7482 +2025-05-28 23:39:47,762 - pyskl - INFO - Epoch [64][500/1281] lr: 1.551e-02, eta: 12:30:46, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9463, top5_acc: 0.9988, loss_cls: 1.7916, loss: 1.7916 +2025-05-28 23:40:29,421 - pyskl - INFO - Epoch [64][600/1281] lr: 1.549e-02, eta: 12:30:06, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9363, top5_acc: 0.9981, loss_cls: 1.9046, loss: 1.9046 +2025-05-28 23:41:11,107 - pyskl - INFO - Epoch [64][700/1281] lr: 1.547e-02, eta: 12:29:27, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9981, loss_cls: 1.8249, loss: 1.8249 +2025-05-28 23:41:53,896 - pyskl - INFO - Epoch [64][800/1281] lr: 1.545e-02, eta: 12:28:50, time: 0.428, data_time: 0.000, memory: 9000, top1_acc: 0.9394, top5_acc: 0.9994, loss_cls: 1.8023, loss: 1.8023 +2025-05-28 23:42:35,860 - pyskl - INFO - Epoch [64][900/1281] lr: 1.543e-02, eta: 12:28:11, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9419, top5_acc: 0.9981, loss_cls: 1.7792, loss: 1.7792 +2025-05-28 23:43:17,809 - pyskl - INFO - Epoch [64][1000/1281] lr: 1.541e-02, eta: 12:27:32, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9544, top5_acc: 0.9988, loss_cls: 1.7885, loss: 1.7885 +2025-05-28 23:43:59,584 - pyskl - INFO - Epoch [64][1100/1281] lr: 1.539e-02, eta: 12:26:53, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9456, top5_acc: 0.9981, loss_cls: 1.6373, loss: 1.6373 +2025-05-28 23:44:41,304 - pyskl - INFO - Epoch [64][1200/1281] lr: 1.537e-02, eta: 12:26:14, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9325, top5_acc: 0.9981, loss_cls: 1.9818, loss: 1.9818 +2025-05-28 23:45:15,790 - pyskl - INFO - Saving checkpoint at 64 epochs +2025-05-28 23:45:57,088 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-28 23:45:57,144 - pyskl - INFO - +top1_acc 0.8892 +top5_acc 0.9944 +2025-05-28 23:45:57,144 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-28 23:45:57,152 - pyskl - INFO - +mean_acc 0.8551 +2025-05-28 23:45:57,156 - pyskl - INFO - Epoch(val) [64][533] top1_acc: 0.8892, top5_acc: 0.9944, mean_class_accuracy: 0.8551 +2025-05-28 23:46:56,930 - pyskl - INFO - Epoch [65][100/1281] lr: 1.533e-02, eta: 12:24:42, time: 0.598, data_time: 0.179, memory: 9000, top1_acc: 0.9400, top5_acc: 1.0000, loss_cls: 1.8316, loss: 1.8316 +2025-05-28 23:47:38,641 - pyskl - INFO - Epoch [65][200/1281] lr: 1.531e-02, eta: 12:24:03, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 1.7109, loss: 1.7109 +2025-05-28 23:48:20,382 - pyskl - INFO - Epoch [65][300/1281] lr: 1.529e-02, eta: 12:23:24, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 1.7505, loss: 1.7505 +2025-05-28 23:49:02,074 - pyskl - INFO - Epoch [65][400/1281] lr: 1.527e-02, eta: 12:22:45, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9475, top5_acc: 0.9981, loss_cls: 1.8169, loss: 1.8169 +2025-05-28 23:49:43,842 - pyskl - INFO - Epoch [65][500/1281] lr: 1.526e-02, eta: 12:22:06, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 1.7453, loss: 1.7453 +2025-05-28 23:50:25,711 - pyskl - INFO - Epoch [65][600/1281] lr: 1.524e-02, eta: 12:21:27, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9325, top5_acc: 1.0000, loss_cls: 1.8500, loss: 1.8500 +2025-05-28 23:51:07,526 - pyskl - INFO - Epoch [65][700/1281] lr: 1.522e-02, eta: 12:20:48, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9500, top5_acc: 1.0000, loss_cls: 1.6517, loss: 1.6517 +2025-05-28 23:51:49,439 - pyskl - INFO - Epoch [65][800/1281] lr: 1.520e-02, eta: 12:20:09, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9425, top5_acc: 0.9975, loss_cls: 1.8020, loss: 1.8020 +2025-05-28 23:52:31,273 - pyskl - INFO - Epoch [65][900/1281] lr: 1.518e-02, eta: 12:19:30, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9369, top5_acc: 0.9988, loss_cls: 1.8621, loss: 1.8621 +2025-05-28 23:53:13,025 - pyskl - INFO - Epoch [65][1000/1281] lr: 1.516e-02, eta: 12:18:51, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9219, top5_acc: 0.9975, loss_cls: 1.9237, loss: 1.9237 +2025-05-28 23:53:54,747 - pyskl - INFO - Epoch [65][1100/1281] lr: 1.514e-02, eta: 12:18:12, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9487, top5_acc: 0.9981, loss_cls: 1.7444, loss: 1.7444 +2025-05-28 23:54:36,832 - pyskl - INFO - Epoch [65][1200/1281] lr: 1.512e-02, eta: 12:17:33, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9444, top5_acc: 0.9988, loss_cls: 1.7648, loss: 1.7648 +2025-05-28 23:55:11,191 - pyskl - INFO - Saving checkpoint at 65 epochs +2025-05-29 00:07:59,162 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 00:07:59,218 - pyskl - INFO - +top1_acc 0.9029 +top5_acc 0.9952 +2025-05-29 00:07:59,218 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 00:07:59,225 - pyskl - INFO - +mean_acc 0.8790 +2025-05-29 00:07:59,227 - pyskl - INFO - Epoch(val) [65][533] top1_acc: 0.9029, top5_acc: 0.9952, mean_class_accuracy: 0.8790 +2025-05-29 00:08:58,682 - pyskl - INFO - Epoch [66][100/1281] lr: 1.508e-02, eta: 12:16:01, time: 0.595, data_time: 0.177, memory: 9000, top1_acc: 0.9431, top5_acc: 1.0000, loss_cls: 1.8289, loss: 1.8289 +2025-05-29 00:09:40,394 - pyskl - INFO - Epoch [66][200/1281] lr: 1.506e-02, eta: 12:15:22, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9400, top5_acc: 1.0000, loss_cls: 1.7746, loss: 1.7746 +2025-05-29 00:10:22,025 - pyskl - INFO - Epoch [66][300/1281] lr: 1.504e-02, eta: 12:14:43, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9413, top5_acc: 1.0000, loss_cls: 1.7644, loss: 1.7644 +2025-05-29 00:11:03,775 - pyskl - INFO - Epoch [66][400/1281] lr: 1.502e-02, eta: 12:14:03, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9575, top5_acc: 0.9994, loss_cls: 1.7468, loss: 1.7468 +2025-05-29 00:11:45,448 - pyskl - INFO - Epoch [66][500/1281] lr: 1.500e-02, eta: 12:13:24, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9544, top5_acc: 0.9994, loss_cls: 1.6803, loss: 1.6803 +2025-05-29 00:12:27,137 - pyskl - INFO - Epoch [66][600/1281] lr: 1.498e-02, eta: 12:12:45, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9419, top5_acc: 0.9994, loss_cls: 1.8142, loss: 1.8142 +2025-05-29 00:13:08,896 - pyskl - INFO - Epoch [66][700/1281] lr: 1.496e-02, eta: 12:12:06, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9450, top5_acc: 1.0000, loss_cls: 1.7779, loss: 1.7779 +2025-05-29 00:13:50,576 - pyskl - INFO - Epoch [66][800/1281] lr: 1.494e-02, eta: 12:11:27, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9444, top5_acc: 0.9981, loss_cls: 1.7723, loss: 1.7723 +2025-05-29 00:14:32,317 - pyskl - INFO - Epoch [66][900/1281] lr: 1.492e-02, eta: 12:10:48, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9350, top5_acc: 0.9975, loss_cls: 1.7338, loss: 1.7338 +2025-05-29 00:15:14,229 - pyskl - INFO - Epoch [66][1000/1281] lr: 1.490e-02, eta: 12:10:09, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9437, top5_acc: 0.9994, loss_cls: 1.8709, loss: 1.8709 +2025-05-29 00:15:56,170 - pyskl - INFO - Epoch [66][1100/1281] lr: 1.488e-02, eta: 12:09:30, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9444, top5_acc: 0.9975, loss_cls: 1.8436, loss: 1.8436 +2025-05-29 00:16:37,830 - pyskl - INFO - Epoch [66][1200/1281] lr: 1.486e-02, eta: 12:08:50, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9375, top5_acc: 0.9994, loss_cls: 1.8316, loss: 1.8316 +2025-05-29 00:17:11,881 - pyskl - INFO - Saving checkpoint at 66 epochs +2025-05-29 00:17:52,783 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 00:17:52,838 - pyskl - INFO - +top1_acc 0.8794 +top5_acc 0.9935 +2025-05-29 00:17:52,838 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 00:17:52,844 - pyskl - INFO - +mean_acc 0.8514 +2025-05-29 00:17:52,846 - pyskl - INFO - Epoch(val) [66][533] top1_acc: 0.8794, top5_acc: 0.9935, mean_class_accuracy: 0.8514 +2025-05-29 00:18:52,450 - pyskl - INFO - Epoch [67][100/1281] lr: 1.482e-02, eta: 12:07:19, time: 0.596, data_time: 0.177, memory: 9000, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 1.7616, loss: 1.7616 +2025-05-29 00:19:34,111 - pyskl - INFO - Epoch [67][200/1281] lr: 1.480e-02, eta: 12:06:40, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9587, top5_acc: 0.9988, loss_cls: 1.6906, loss: 1.6906 +2025-05-29 00:20:15,617 - pyskl - INFO - Epoch [67][300/1281] lr: 1.478e-02, eta: 12:06:01, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 1.7438, loss: 1.7438 +2025-05-29 00:20:56,789 - pyskl - INFO - Epoch [67][400/1281] lr: 1.476e-02, eta: 12:05:21, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 1.7670, loss: 1.7670 +2025-05-29 00:21:37,968 - pyskl - INFO - Epoch [67][500/1281] lr: 1.474e-02, eta: 12:04:41, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9444, top5_acc: 0.9988, loss_cls: 1.7852, loss: 1.7852 +2025-05-29 00:22:19,133 - pyskl - INFO - Epoch [67][600/1281] lr: 1.472e-02, eta: 12:04:01, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9394, top5_acc: 0.9994, loss_cls: 1.7638, loss: 1.7638 +2025-05-29 00:23:00,297 - pyskl - INFO - Epoch [67][700/1281] lr: 1.470e-02, eta: 12:03:21, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9550, top5_acc: 0.9994, loss_cls: 1.6642, loss: 1.6642 +2025-05-29 00:23:41,469 - pyskl - INFO - Epoch [67][800/1281] lr: 1.468e-02, eta: 12:02:41, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9500, top5_acc: 1.0000, loss_cls: 1.7114, loss: 1.7114 +2025-05-29 00:24:22,687 - pyskl - INFO - Epoch [67][900/1281] lr: 1.466e-02, eta: 12:02:01, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9506, top5_acc: 1.0000, loss_cls: 1.7465, loss: 1.7465 +2025-05-29 00:25:04,593 - pyskl - INFO - Epoch [67][1000/1281] lr: 1.464e-02, eta: 12:01:22, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9506, top5_acc: 0.9988, loss_cls: 1.6708, loss: 1.6708 +2025-05-29 00:25:47,014 - pyskl - INFO - Epoch [67][1100/1281] lr: 1.462e-02, eta: 12:00:44, time: 0.424, data_time: 0.000, memory: 9000, top1_acc: 0.9425, top5_acc: 0.9988, loss_cls: 1.7673, loss: 1.7673 +2025-05-29 00:26:29,310 - pyskl - INFO - Epoch [67][1200/1281] lr: 1.460e-02, eta: 12:00:06, time: 0.423, data_time: 0.000, memory: 9000, top1_acc: 0.9206, top5_acc: 0.9944, loss_cls: 1.9197, loss: 1.9197 +2025-05-29 00:27:03,573 - pyskl - INFO - Saving checkpoint at 67 epochs +2025-05-29 00:27:44,556 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 00:27:44,616 - pyskl - INFO - +top1_acc 0.8222 +top5_acc 0.9810 +2025-05-29 00:27:44,616 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 00:27:44,623 - pyskl - INFO - +mean_acc 0.7743 +2025-05-29 00:27:44,625 - pyskl - INFO - Epoch(val) [67][533] top1_acc: 0.8222, top5_acc: 0.9810, mean_class_accuracy: 0.7743 +2025-05-29 00:28:43,893 - pyskl - INFO - Epoch [68][100/1281] lr: 1.456e-02, eta: 11:58:35, time: 0.593, data_time: 0.175, memory: 9000, top1_acc: 0.9487, top5_acc: 0.9988, loss_cls: 1.7136, loss: 1.7136 +2025-05-29 00:29:25,585 - pyskl - INFO - Epoch [68][200/1281] lr: 1.454e-02, eta: 11:57:55, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9581, top5_acc: 0.9988, loss_cls: 1.7155, loss: 1.7155 +2025-05-29 00:30:07,252 - pyskl - INFO - Epoch [68][300/1281] lr: 1.452e-02, eta: 11:57:16, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 1.6644, loss: 1.6644 +2025-05-29 00:30:48,861 - pyskl - INFO - Epoch [68][400/1281] lr: 1.450e-02, eta: 11:56:37, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9450, top5_acc: 1.0000, loss_cls: 1.7287, loss: 1.7287 +2025-05-29 00:31:30,456 - pyskl - INFO - Epoch [68][500/1281] lr: 1.448e-02, eta: 11:55:57, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9475, top5_acc: 0.9981, loss_cls: 1.7158, loss: 1.7158 +2025-05-29 00:32:12,013 - pyskl - INFO - Epoch [68][600/1281] lr: 1.446e-02, eta: 11:55:18, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9500, top5_acc: 0.9988, loss_cls: 1.6536, loss: 1.6536 +2025-05-29 00:32:53,583 - pyskl - INFO - Epoch [68][700/1281] lr: 1.444e-02, eta: 11:54:38, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9437, top5_acc: 0.9975, loss_cls: 1.8017, loss: 1.8017 +2025-05-29 00:33:35,149 - pyskl - INFO - Epoch [68][800/1281] lr: 1.442e-02, eta: 11:53:59, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9444, top5_acc: 0.9975, loss_cls: 1.7568, loss: 1.7568 +2025-05-29 00:34:16,735 - pyskl - INFO - Epoch [68][900/1281] lr: 1.440e-02, eta: 11:53:20, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9381, top5_acc: 0.9988, loss_cls: 1.8281, loss: 1.8281 +2025-05-29 00:34:58,571 - pyskl - INFO - Epoch [68][1000/1281] lr: 1.438e-02, eta: 11:52:41, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9500, top5_acc: 0.9988, loss_cls: 1.8124, loss: 1.8124 +2025-05-29 00:35:40,605 - pyskl - INFO - Epoch [68][1100/1281] lr: 1.436e-02, eta: 11:52:02, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9519, top5_acc: 0.9988, loss_cls: 1.7003, loss: 1.7003 +2025-05-29 00:36:22,263 - pyskl - INFO - Epoch [68][1200/1281] lr: 1.434e-02, eta: 11:51:22, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9263, top5_acc: 0.9969, loss_cls: 1.8632, loss: 1.8632 +2025-05-29 00:36:56,271 - pyskl - INFO - Saving checkpoint at 68 epochs +2025-05-29 00:37:37,594 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 00:37:37,650 - pyskl - INFO - +top1_acc 0.8683 +top5_acc 0.9913 +2025-05-29 00:37:37,650 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 00:37:37,657 - pyskl - INFO - +mean_acc 0.8410 +2025-05-29 00:37:37,660 - pyskl - INFO - Epoch(val) [68][533] top1_acc: 0.8683, top5_acc: 0.9913, mean_class_accuracy: 0.8410 +2025-05-29 00:38:37,484 - pyskl - INFO - Epoch [69][100/1281] lr: 1.431e-02, eta: 11:49:52, time: 0.598, data_time: 0.180, memory: 9000, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 1.6891, loss: 1.6891 +2025-05-29 00:39:19,193 - pyskl - INFO - Epoch [69][200/1281] lr: 1.429e-02, eta: 11:49:13, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 1.6584, loss: 1.6584 +2025-05-29 00:40:00,890 - pyskl - INFO - Epoch [69][300/1281] lr: 1.427e-02, eta: 11:48:34, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 1.7171, loss: 1.7171 +2025-05-29 00:40:42,729 - pyskl - INFO - Epoch [69][400/1281] lr: 1.425e-02, eta: 11:47:55, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 1.6420, loss: 1.6420 +2025-05-29 00:41:24,444 - pyskl - INFO - Epoch [69][500/1281] lr: 1.423e-02, eta: 11:47:16, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9594, top5_acc: 0.9994, loss_cls: 1.6266, loss: 1.6266 +2025-05-29 00:42:06,108 - pyskl - INFO - Epoch [69][600/1281] lr: 1.420e-02, eta: 11:46:36, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 1.7057, loss: 1.7057 +2025-05-29 00:42:47,831 - pyskl - INFO - Epoch [69][700/1281] lr: 1.418e-02, eta: 11:45:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9506, top5_acc: 0.9988, loss_cls: 1.6520, loss: 1.6520 +2025-05-29 00:43:29,432 - pyskl - INFO - Epoch [69][800/1281] lr: 1.416e-02, eta: 11:45:18, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 1.7365, loss: 1.7365 +2025-05-29 00:44:11,226 - pyskl - INFO - Epoch [69][900/1281] lr: 1.414e-02, eta: 11:44:38, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9581, top5_acc: 0.9981, loss_cls: 1.7840, loss: 1.7840 +2025-05-29 00:44:53,005 - pyskl - INFO - Epoch [69][1000/1281] lr: 1.412e-02, eta: 11:43:59, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9513, top5_acc: 0.9981, loss_cls: 1.7079, loss: 1.7079 +2025-05-29 00:45:34,761 - pyskl - INFO - Epoch [69][1100/1281] lr: 1.410e-02, eta: 11:43:20, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9437, top5_acc: 0.9988, loss_cls: 1.7689, loss: 1.7689 +2025-05-29 00:46:16,522 - pyskl - INFO - Epoch [69][1200/1281] lr: 1.408e-02, eta: 11:42:41, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9287, top5_acc: 0.9994, loss_cls: 1.8363, loss: 1.8363 +2025-05-29 00:46:50,836 - pyskl - INFO - Saving checkpoint at 69 epochs +2025-05-29 00:47:32,010 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 00:47:32,068 - pyskl - INFO - +top1_acc 0.8749 +top5_acc 0.9904 +2025-05-29 00:47:32,068 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 00:47:32,077 - pyskl - INFO - +mean_acc 0.8429 +2025-05-29 00:47:32,080 - pyskl - INFO - Epoch(val) [69][533] top1_acc: 0.8749, top5_acc: 0.9904, mean_class_accuracy: 0.8429 +2025-05-29 00:48:33,063 - pyskl - INFO - Epoch [70][100/1281] lr: 1.405e-02, eta: 11:41:13, time: 0.610, data_time: 0.191, memory: 9000, top1_acc: 0.9406, top5_acc: 1.0000, loss_cls: 1.7795, loss: 1.7795 +2025-05-29 00:49:14,841 - pyskl - INFO - Epoch [70][200/1281] lr: 1.403e-02, eta: 11:40:33, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9556, top5_acc: 1.0000, loss_cls: 1.6770, loss: 1.6770 +2025-05-29 00:49:56,525 - pyskl - INFO - Epoch [70][300/1281] lr: 1.401e-02, eta: 11:39:54, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 1.6726, loss: 1.6726 +2025-05-29 00:50:38,276 - pyskl - INFO - Epoch [70][400/1281] lr: 1.399e-02, eta: 11:39:15, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 0.9994, loss_cls: 1.7735, loss: 1.7735 +2025-05-29 00:51:20,017 - pyskl - INFO - Epoch [70][500/1281] lr: 1.397e-02, eta: 11:38:36, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9450, top5_acc: 0.9994, loss_cls: 1.7301, loss: 1.7301 +2025-05-29 00:52:01,713 - pyskl - INFO - Epoch [70][600/1281] lr: 1.395e-02, eta: 11:37:56, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9394, top5_acc: 1.0000, loss_cls: 1.7591, loss: 1.7591 +2025-05-29 00:52:43,360 - pyskl - INFO - Epoch [70][700/1281] lr: 1.392e-02, eta: 11:37:17, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 1.8003, loss: 1.8003 +2025-05-29 00:53:25,031 - pyskl - INFO - Epoch [70][800/1281] lr: 1.390e-02, eta: 11:36:38, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 1.7587, loss: 1.7587 +2025-05-29 00:54:06,761 - pyskl - INFO - Epoch [70][900/1281] lr: 1.388e-02, eta: 11:35:58, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9444, top5_acc: 1.0000, loss_cls: 1.8014, loss: 1.8014 +2025-05-29 00:54:48,489 - pyskl - INFO - Epoch [70][1000/1281] lr: 1.386e-02, eta: 11:35:19, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 1.6132, loss: 1.6132 +2025-05-29 00:55:30,583 - pyskl - INFO - Epoch [70][1100/1281] lr: 1.384e-02, eta: 11:34:40, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9394, top5_acc: 0.9994, loss_cls: 1.8043, loss: 1.8043 +2025-05-29 00:56:12,384 - pyskl - INFO - Epoch [70][1200/1281] lr: 1.382e-02, eta: 11:34:01, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 1.0000, loss_cls: 1.7847, loss: 1.7847 +2025-05-29 00:56:46,760 - pyskl - INFO - Saving checkpoint at 70 epochs +2025-05-29 01:09:16,109 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 01:09:16,166 - pyskl - INFO - +top1_acc 0.8946 +top5_acc 0.9906 +2025-05-29 01:09:16,166 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 01:09:16,174 - pyskl - INFO - +mean_acc 0.8571 +2025-05-29 01:09:16,178 - pyskl - INFO - Epoch(val) [70][533] top1_acc: 0.8946, top5_acc: 0.9906, mean_class_accuracy: 0.8571 +2025-05-29 01:10:16,778 - pyskl - INFO - Epoch [71][100/1281] lr: 1.379e-02, eta: 11:32:33, time: 0.606, data_time: 0.184, memory: 9000, top1_acc: 0.9500, top5_acc: 0.9988, loss_cls: 1.7829, loss: 1.7829 +2025-05-29 01:10:58,760 - pyskl - INFO - Epoch [71][200/1281] lr: 1.377e-02, eta: 11:31:54, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 1.6343, loss: 1.6343 +2025-05-29 01:11:40,519 - pyskl - INFO - Epoch [71][300/1281] lr: 1.375e-02, eta: 11:31:14, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9537, top5_acc: 0.9988, loss_cls: 1.6978, loss: 1.6978 +2025-05-29 01:12:22,195 - pyskl - INFO - Epoch [71][400/1281] lr: 1.373e-02, eta: 11:30:35, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 1.7425, loss: 1.7425 +2025-05-29 01:13:03,898 - pyskl - INFO - Epoch [71][500/1281] lr: 1.371e-02, eta: 11:29:56, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9563, top5_acc: 0.9988, loss_cls: 1.7576, loss: 1.7576 +2025-05-29 01:13:45,649 - pyskl - INFO - Epoch [71][600/1281] lr: 1.368e-02, eta: 11:29:16, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 1.6886, loss: 1.6886 +2025-05-29 01:14:27,491 - pyskl - INFO - Epoch [71][700/1281] lr: 1.366e-02, eta: 11:28:37, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9531, top5_acc: 0.9988, loss_cls: 1.6521, loss: 1.6521 +2025-05-29 01:15:09,158 - pyskl - INFO - Epoch [71][800/1281] lr: 1.364e-02, eta: 11:27:58, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9369, top5_acc: 0.9981, loss_cls: 1.8713, loss: 1.8713 +2025-05-29 01:15:50,873 - pyskl - INFO - Epoch [71][900/1281] lr: 1.362e-02, eta: 11:27:19, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9450, top5_acc: 0.9994, loss_cls: 1.7243, loss: 1.7243 +2025-05-29 01:16:32,722 - pyskl - INFO - Epoch [71][1000/1281] lr: 1.360e-02, eta: 11:26:39, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9437, top5_acc: 1.0000, loss_cls: 1.7767, loss: 1.7767 +2025-05-29 01:17:14,709 - pyskl - INFO - Epoch [71][1100/1281] lr: 1.358e-02, eta: 11:26:00, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 1.7715, loss: 1.7715 +2025-05-29 01:17:56,406 - pyskl - INFO - Epoch [71][1200/1281] lr: 1.356e-02, eta: 11:25:21, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 1.7510, loss: 1.7510 +2025-05-29 01:18:30,715 - pyskl - INFO - Saving checkpoint at 71 epochs +2025-05-29 01:19:12,034 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 01:19:12,090 - pyskl - INFO - +top1_acc 0.8838 +top5_acc 0.9930 +2025-05-29 01:19:12,090 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 01:19:12,096 - pyskl - INFO - +mean_acc 0.8583 +2025-05-29 01:19:12,099 - pyskl - INFO - Epoch(val) [71][533] top1_acc: 0.8838, top5_acc: 0.9930, mean_class_accuracy: 0.8583 +2025-05-29 01:20:11,488 - pyskl - INFO - Epoch [72][100/1281] lr: 1.353e-02, eta: 11:23:52, time: 0.594, data_time: 0.177, memory: 9000, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 1.6601, loss: 1.6601 +2025-05-29 01:20:53,176 - pyskl - INFO - Epoch [72][200/1281] lr: 1.351e-02, eta: 11:23:12, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9519, top5_acc: 1.0000, loss_cls: 1.7132, loss: 1.7132 +2025-05-29 01:21:34,913 - pyskl - INFO - Epoch [72][300/1281] lr: 1.349e-02, eta: 11:22:33, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9444, top5_acc: 1.0000, loss_cls: 1.8267, loss: 1.8267 +2025-05-29 01:22:16,563 - pyskl - INFO - Epoch [72][400/1281] lr: 1.346e-02, eta: 11:21:54, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 1.7207, loss: 1.7207 +2025-05-29 01:22:58,254 - pyskl - INFO - Epoch [72][500/1281] lr: 1.344e-02, eta: 11:21:14, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 1.7308, loss: 1.7308 +2025-05-29 01:23:39,917 - pyskl - INFO - Epoch [72][600/1281] lr: 1.342e-02, eta: 11:20:35, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9469, top5_acc: 1.0000, loss_cls: 1.7550, loss: 1.7550 +2025-05-29 01:24:21,557 - pyskl - INFO - Epoch [72][700/1281] lr: 1.340e-02, eta: 11:19:55, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9481, top5_acc: 0.9988, loss_cls: 1.7678, loss: 1.7678 +2025-05-29 01:25:03,285 - pyskl - INFO - Epoch [72][800/1281] lr: 1.338e-02, eta: 11:19:16, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 0.9988, loss_cls: 1.7062, loss: 1.7062 +2025-05-29 01:25:45,005 - pyskl - INFO - Epoch [72][900/1281] lr: 1.336e-02, eta: 11:18:37, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9337, top5_acc: 0.9981, loss_cls: 1.8430, loss: 1.8430 +2025-05-29 01:26:26,871 - pyskl - INFO - Epoch [72][1000/1281] lr: 1.334e-02, eta: 11:17:57, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9400, top5_acc: 0.9988, loss_cls: 1.7872, loss: 1.7872 +2025-05-29 01:27:08,378 - pyskl - INFO - Epoch [72][1100/1281] lr: 1.332e-02, eta: 11:17:18, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 0.9419, top5_acc: 0.9994, loss_cls: 1.7177, loss: 1.7177 +2025-05-29 01:27:50,154 - pyskl - INFO - Epoch [72][1200/1281] lr: 1.330e-02, eta: 11:16:39, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9594, top5_acc: 0.9994, loss_cls: 1.6713, loss: 1.6713 +2025-05-29 01:28:24,619 - pyskl - INFO - Saving checkpoint at 72 epochs +2025-05-29 01:29:05,504 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 01:29:05,560 - pyskl - INFO - +top1_acc 0.9074 +top5_acc 0.9942 +2025-05-29 01:29:05,560 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 01:29:05,567 - pyskl - INFO - +mean_acc 0.8811 +2025-05-29 01:29:05,622 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_61.pth was removed +2025-05-29 01:29:07,107 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_72.pth. +2025-05-29 01:29:07,108 - pyskl - INFO - Best top1_acc is 0.9074 at 72 epoch. +2025-05-29 01:29:07,111 - pyskl - INFO - Epoch(val) [72][533] top1_acc: 0.9074, top5_acc: 0.9942, mean_class_accuracy: 0.8811 +2025-05-29 01:30:06,646 - pyskl - INFO - Epoch [73][100/1281] lr: 1.326e-02, eta: 11:15:10, time: 0.595, data_time: 0.178, memory: 9000, top1_acc: 0.9556, top5_acc: 1.0000, loss_cls: 1.6253, loss: 1.6253 +2025-05-29 01:30:48,309 - pyskl - INFO - Epoch [73][200/1281] lr: 1.324e-02, eta: 11:14:31, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 1.6459, loss: 1.6459 +2025-05-29 01:31:30,265 - pyskl - INFO - Epoch [73][300/1281] lr: 1.322e-02, eta: 11:13:51, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9569, top5_acc: 0.9994, loss_cls: 1.6972, loss: 1.6972 +2025-05-29 01:32:12,476 - pyskl - INFO - Epoch [73][400/1281] lr: 1.320e-02, eta: 11:13:13, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 0.9531, top5_acc: 0.9988, loss_cls: 1.7292, loss: 1.7292 +2025-05-29 01:32:54,244 - pyskl - INFO - Epoch [73][500/1281] lr: 1.318e-02, eta: 11:12:33, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9650, top5_acc: 0.9988, loss_cls: 1.6767, loss: 1.6767 +2025-05-29 01:33:35,972 - pyskl - INFO - Epoch [73][600/1281] lr: 1.316e-02, eta: 11:11:54, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 1.6819, loss: 1.6819 +2025-05-29 01:34:17,808 - pyskl - INFO - Epoch [73][700/1281] lr: 1.314e-02, eta: 11:11:15, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9381, top5_acc: 0.9988, loss_cls: 1.8592, loss: 1.8592 +2025-05-29 01:34:59,633 - pyskl - INFO - Epoch [73][800/1281] lr: 1.312e-02, eta: 11:10:35, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9444, top5_acc: 0.9994, loss_cls: 1.7744, loss: 1.7744 +2025-05-29 01:35:41,416 - pyskl - INFO - Epoch [73][900/1281] lr: 1.310e-02, eta: 11:09:56, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9413, top5_acc: 0.9969, loss_cls: 1.7918, loss: 1.7918 +2025-05-29 01:36:23,440 - pyskl - INFO - Epoch [73][1000/1281] lr: 1.308e-02, eta: 11:09:17, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 1.6303, loss: 1.6303 +2025-05-29 01:37:05,340 - pyskl - INFO - Epoch [73][1100/1281] lr: 1.306e-02, eta: 11:08:38, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9587, top5_acc: 0.9994, loss_cls: 1.7277, loss: 1.7277 +2025-05-29 01:37:47,161 - pyskl - INFO - Epoch [73][1200/1281] lr: 1.304e-02, eta: 11:07:58, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 1.6819, loss: 1.6819 +2025-05-29 01:38:21,629 - pyskl - INFO - Saving checkpoint at 73 epochs +2025-05-29 01:39:02,732 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 01:39:02,789 - pyskl - INFO - +top1_acc 0.9076 +top5_acc 0.9957 +2025-05-29 01:39:02,789 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 01:39:02,796 - pyskl - INFO - +mean_acc 0.8676 +2025-05-29 01:39:02,854 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_72.pth was removed +2025-05-29 01:39:04,363 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_73.pth. +2025-05-29 01:39:04,363 - pyskl - INFO - Best top1_acc is 0.9076 at 73 epoch. +2025-05-29 01:39:04,367 - pyskl - INFO - Epoch(val) [73][533] top1_acc: 0.9076, top5_acc: 0.9957, mean_class_accuracy: 0.8676 +2025-05-29 01:40:04,025 - pyskl - INFO - Epoch [74][100/1281] lr: 1.300e-02, eta: 11:06:30, time: 0.597, data_time: 0.179, memory: 9000, top1_acc: 0.9569, top5_acc: 0.9994, loss_cls: 1.6871, loss: 1.6871 +2025-05-29 01:40:45,690 - pyskl - INFO - Epoch [74][200/1281] lr: 1.298e-02, eta: 11:05:51, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 1.5984, loss: 1.5984 +2025-05-29 01:41:27,386 - pyskl - INFO - Epoch [74][300/1281] lr: 1.296e-02, eta: 11:05:11, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 1.6674, loss: 1.6674 +2025-05-29 01:42:09,053 - pyskl - INFO - Epoch [74][400/1281] lr: 1.294e-02, eta: 11:04:32, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9481, top5_acc: 1.0000, loss_cls: 1.6757, loss: 1.6757 +2025-05-29 01:42:50,679 - pyskl - INFO - Epoch [74][500/1281] lr: 1.292e-02, eta: 11:03:53, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 1.5782, loss: 1.5782 +2025-05-29 01:43:32,321 - pyskl - INFO - Epoch [74][600/1281] lr: 1.290e-02, eta: 11:03:13, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9544, top5_acc: 0.9988, loss_cls: 1.6396, loss: 1.6396 +2025-05-29 01:44:13,991 - pyskl - INFO - Epoch [74][700/1281] lr: 1.288e-02, eta: 11:02:34, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 1.6102, loss: 1.6102 +2025-05-29 01:44:55,724 - pyskl - INFO - Epoch [74][800/1281] lr: 1.286e-02, eta: 11:01:54, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9581, top5_acc: 0.9981, loss_cls: 1.7149, loss: 1.7149 +2025-05-29 01:45:37,402 - pyskl - INFO - Epoch [74][900/1281] lr: 1.284e-02, eta: 11:01:15, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 1.6116, loss: 1.6116 +2025-05-29 01:46:19,183 - pyskl - INFO - Epoch [74][1000/1281] lr: 1.282e-02, eta: 11:00:35, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 1.7003, loss: 1.7003 +2025-05-29 01:47:01,001 - pyskl - INFO - Epoch [74][1100/1281] lr: 1.280e-02, eta: 10:59:56, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9419, top5_acc: 0.9988, loss_cls: 1.7639, loss: 1.7639 +2025-05-29 01:47:42,616 - pyskl - INFO - Epoch [74][1200/1281] lr: 1.278e-02, eta: 10:59:16, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9375, top5_acc: 0.9994, loss_cls: 1.8039, loss: 1.8039 +2025-05-29 01:48:16,845 - pyskl - INFO - Saving checkpoint at 74 epochs +2025-05-29 01:48:58,012 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 01:48:58,068 - pyskl - INFO - +top1_acc 0.8953 +top5_acc 0.9923 +2025-05-29 01:48:58,068 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 01:48:58,076 - pyskl - INFO - +mean_acc 0.8746 +2025-05-29 01:48:58,078 - pyskl - INFO - Epoch(val) [74][533] top1_acc: 0.8953, top5_acc: 0.9923, mean_class_accuracy: 0.8746 +2025-05-29 01:49:57,612 - pyskl - INFO - Epoch [75][100/1281] lr: 1.274e-02, eta: 10:57:49, time: 0.595, data_time: 0.178, memory: 9000, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 1.6355, loss: 1.6355 +2025-05-29 01:50:39,317 - pyskl - INFO - Epoch [75][200/1281] lr: 1.272e-02, eta: 10:57:09, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 1.6938, loss: 1.6938 +2025-05-29 01:51:20,938 - pyskl - INFO - Epoch [75][300/1281] lr: 1.270e-02, eta: 10:56:30, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 1.6615, loss: 1.6615 +2025-05-29 01:52:02,624 - pyskl - INFO - Epoch [75][400/1281] lr: 1.268e-02, eta: 10:55:50, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 1.6253, loss: 1.6253 +2025-05-29 01:52:44,356 - pyskl - INFO - Epoch [75][500/1281] lr: 1.266e-02, eta: 10:55:11, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 1.6150, loss: 1.6150 +2025-05-29 01:53:25,825 - pyskl - INFO - Epoch [75][600/1281] lr: 1.264e-02, eta: 10:54:31, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 0.9613, top5_acc: 0.9994, loss_cls: 1.6242, loss: 1.6242 +2025-05-29 01:54:08,121 - pyskl - INFO - Epoch [75][700/1281] lr: 1.262e-02, eta: 10:53:52, time: 0.423, data_time: 0.000, memory: 9000, top1_acc: 0.9537, top5_acc: 0.9988, loss_cls: 1.6699, loss: 1.6699 +2025-05-29 01:54:50,054 - pyskl - INFO - Epoch [75][800/1281] lr: 1.260e-02, eta: 10:53:13, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9519, top5_acc: 1.0000, loss_cls: 1.6274, loss: 1.6274 +2025-05-29 01:55:31,756 - pyskl - INFO - Epoch [75][900/1281] lr: 1.258e-02, eta: 10:52:34, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9556, top5_acc: 1.0000, loss_cls: 1.6693, loss: 1.6693 +2025-05-29 01:56:13,514 - pyskl - INFO - Epoch [75][1000/1281] lr: 1.256e-02, eta: 10:51:54, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9519, top5_acc: 0.9994, loss_cls: 1.6758, loss: 1.6758 +2025-05-29 01:56:54,654 - pyskl - INFO - Epoch [75][1100/1281] lr: 1.254e-02, eta: 10:51:14, time: 0.411, data_time: 0.000, memory: 9000, top1_acc: 0.9481, top5_acc: 0.9988, loss_cls: 1.6968, loss: 1.6968 +2025-05-29 01:57:36,929 - pyskl - INFO - Epoch [75][1200/1281] lr: 1.252e-02, eta: 10:50:35, time: 0.423, data_time: 0.000, memory: 9000, top1_acc: 0.9369, top5_acc: 0.9994, loss_cls: 1.7592, loss: 1.7592 +2025-05-29 01:58:11,276 - pyskl - INFO - Saving checkpoint at 75 epochs +2025-05-29 02:11:18,054 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 02:11:18,110 - pyskl - INFO - +top1_acc 0.8808 +top5_acc 0.9926 +2025-05-29 02:11:18,110 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 02:11:18,117 - pyskl - INFO - +mean_acc 0.8466 +2025-05-29 02:11:18,119 - pyskl - INFO - Epoch(val) [75][533] top1_acc: 0.8808, top5_acc: 0.9926, mean_class_accuracy: 0.8466 +2025-05-29 02:12:17,548 - pyskl - INFO - Epoch [76][100/1281] lr: 1.248e-02, eta: 10:49:08, time: 0.594, data_time: 0.177, memory: 9000, top1_acc: 0.9606, top5_acc: 0.9988, loss_cls: 1.6819, loss: 1.6819 +2025-05-29 02:12:59,170 - pyskl - INFO - Epoch [76][200/1281] lr: 1.246e-02, eta: 10:48:28, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 1.7055, loss: 1.7055 +2025-05-29 02:13:40,795 - pyskl - INFO - Epoch [76][300/1281] lr: 1.244e-02, eta: 10:47:49, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9550, top5_acc: 0.9988, loss_cls: 1.6083, loss: 1.6083 +2025-05-29 02:14:22,425 - pyskl - INFO - Epoch [76][400/1281] lr: 1.242e-02, eta: 10:47:09, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 1.7032, loss: 1.7032 +2025-05-29 02:15:04,098 - pyskl - INFO - Epoch [76][500/1281] lr: 1.240e-02, eta: 10:46:30, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 1.7073, loss: 1.7073 +2025-05-29 02:15:46,159 - pyskl - INFO - Epoch [76][600/1281] lr: 1.238e-02, eta: 10:45:50, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 1.6264, loss: 1.6264 +2025-05-29 02:16:28,119 - pyskl - INFO - Epoch [76][700/1281] lr: 1.236e-02, eta: 10:45:11, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9506, top5_acc: 0.9988, loss_cls: 1.6239, loss: 1.6239 +2025-05-29 02:17:09,849 - pyskl - INFO - Epoch [76][800/1281] lr: 1.234e-02, eta: 10:44:32, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 1.6619, loss: 1.6619 +2025-05-29 02:17:51,598 - pyskl - INFO - Epoch [76][900/1281] lr: 1.232e-02, eta: 10:43:52, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 1.6378, loss: 1.6378 +2025-05-29 02:18:33,521 - pyskl - INFO - Epoch [76][1000/1281] lr: 1.230e-02, eta: 10:43:13, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 1.6488, loss: 1.6488 +2025-05-29 02:19:15,369 - pyskl - INFO - Epoch [76][1100/1281] lr: 1.228e-02, eta: 10:42:34, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 1.6658, loss: 1.6658 +2025-05-29 02:19:57,145 - pyskl - INFO - Epoch [76][1200/1281] lr: 1.225e-02, eta: 10:41:54, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9525, top5_acc: 0.9988, loss_cls: 1.6515, loss: 1.6515 +2025-05-29 02:20:31,620 - pyskl - INFO - Saving checkpoint at 76 epochs +2025-05-29 02:21:12,489 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 02:21:12,545 - pyskl - INFO - +top1_acc 0.9112 +top5_acc 0.9957 +2025-05-29 02:21:12,545 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 02:21:12,552 - pyskl - INFO - +mean_acc 0.8825 +2025-05-29 02:21:12,610 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_73.pth was removed +2025-05-29 02:21:14,244 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_76.pth. +2025-05-29 02:21:14,245 - pyskl - INFO - Best top1_acc is 0.9112 at 76 epoch. +2025-05-29 02:21:14,248 - pyskl - INFO - Epoch(val) [76][533] top1_acc: 0.9112, top5_acc: 0.9957, mean_class_accuracy: 0.8825 +2025-05-29 02:22:13,755 - pyskl - INFO - Epoch [77][100/1281] lr: 1.222e-02, eta: 10:40:27, time: 0.595, data_time: 0.179, memory: 9000, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 1.5660, loss: 1.5660 +2025-05-29 02:22:55,337 - pyskl - INFO - Epoch [77][200/1281] lr: 1.220e-02, eta: 10:39:47, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 0.9994, loss_cls: 1.5148, loss: 1.5148 +2025-05-29 02:23:36,888 - pyskl - INFO - Epoch [77][300/1281] lr: 1.218e-02, eta: 10:39:08, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9650, top5_acc: 0.9988, loss_cls: 1.6072, loss: 1.6072 +2025-05-29 02:24:18,508 - pyskl - INFO - Epoch [77][400/1281] lr: 1.216e-02, eta: 10:38:28, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 1.5812, loss: 1.5812 +2025-05-29 02:25:00,213 - pyskl - INFO - Epoch [77][500/1281] lr: 1.214e-02, eta: 10:37:49, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 1.6571, loss: 1.6571 +2025-05-29 02:25:41,929 - pyskl - INFO - Epoch [77][600/1281] lr: 1.212e-02, eta: 10:37:09, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 1.6616, loss: 1.6616 +2025-05-29 02:26:23,520 - pyskl - INFO - Epoch [77][700/1281] lr: 1.210e-02, eta: 10:36:30, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9563, top5_acc: 0.9981, loss_cls: 1.7149, loss: 1.7149 +2025-05-29 02:27:05,155 - pyskl - INFO - Epoch [77][800/1281] lr: 1.207e-02, eta: 10:35:50, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 1.6284, loss: 1.6284 +2025-05-29 02:27:46,894 - pyskl - INFO - Epoch [77][900/1281] lr: 1.205e-02, eta: 10:35:11, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 1.7746, loss: 1.7746 +2025-05-29 02:28:28,764 - pyskl - INFO - Epoch [77][1000/1281] lr: 1.203e-02, eta: 10:34:31, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 1.7485, loss: 1.7485 +2025-05-29 02:29:10,550 - pyskl - INFO - Epoch [77][1100/1281] lr: 1.201e-02, eta: 10:33:52, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 1.5423, loss: 1.5423 +2025-05-29 02:29:52,388 - pyskl - INFO - Epoch [77][1200/1281] lr: 1.199e-02, eta: 10:33:12, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 1.6056, loss: 1.6056 +2025-05-29 02:30:26,692 - pyskl - INFO - Saving checkpoint at 77 epochs +2025-05-29 02:31:07,631 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 02:31:07,687 - pyskl - INFO - +top1_acc 0.9046 +top5_acc 0.9946 +2025-05-29 02:31:07,687 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 02:31:07,695 - pyskl - INFO - +mean_acc 0.8692 +2025-05-29 02:31:07,698 - pyskl - INFO - Epoch(val) [77][533] top1_acc: 0.9046, top5_acc: 0.9946, mean_class_accuracy: 0.8692 +2025-05-29 02:32:06,989 - pyskl - INFO - Epoch [78][100/1281] lr: 1.196e-02, eta: 10:31:45, time: 0.593, data_time: 0.175, memory: 9000, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 1.5678, loss: 1.5678 +2025-05-29 02:32:48,694 - pyskl - INFO - Epoch [78][200/1281] lr: 1.194e-02, eta: 10:31:06, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 1.5734, loss: 1.5734 +2025-05-29 02:33:30,567 - pyskl - INFO - Epoch [78][300/1281] lr: 1.192e-02, eta: 10:30:27, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 1.6127, loss: 1.6127 +2025-05-29 02:34:12,315 - pyskl - INFO - Epoch [78][400/1281] lr: 1.190e-02, eta: 10:29:47, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 1.7002, loss: 1.7002 +2025-05-29 02:34:54,032 - pyskl - INFO - Epoch [78][500/1281] lr: 1.187e-02, eta: 10:29:08, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 1.5406, loss: 1.5406 +2025-05-29 02:35:35,713 - pyskl - INFO - Epoch [78][600/1281] lr: 1.185e-02, eta: 10:28:28, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 1.6160, loss: 1.6160 +2025-05-29 02:36:17,376 - pyskl - INFO - Epoch [78][700/1281] lr: 1.183e-02, eta: 10:27:48, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9544, top5_acc: 0.9988, loss_cls: 1.7108, loss: 1.7108 +2025-05-29 02:36:59,027 - pyskl - INFO - Epoch [78][800/1281] lr: 1.181e-02, eta: 10:27:09, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9463, top5_acc: 0.9981, loss_cls: 1.6826, loss: 1.6826 +2025-05-29 02:37:41,779 - pyskl - INFO - Epoch [78][900/1281] lr: 1.179e-02, eta: 10:26:30, time: 0.428, data_time: 0.000, memory: 9000, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 1.5851, loss: 1.5851 +2025-05-29 02:38:23,804 - pyskl - INFO - Epoch [78][1000/1281] lr: 1.177e-02, eta: 10:25:51, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9456, top5_acc: 0.9975, loss_cls: 1.6757, loss: 1.6757 +2025-05-29 02:39:05,837 - pyskl - INFO - Epoch [78][1100/1281] lr: 1.175e-02, eta: 10:25:12, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9394, top5_acc: 0.9981, loss_cls: 1.7912, loss: 1.7912 +2025-05-29 02:39:47,803 - pyskl - INFO - Epoch [78][1200/1281] lr: 1.173e-02, eta: 10:24:32, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 1.5893, loss: 1.5893 +2025-05-29 02:40:22,041 - pyskl - INFO - Saving checkpoint at 78 epochs +2025-05-29 02:41:03,037 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 02:41:03,092 - pyskl - INFO - +top1_acc 0.8822 +top5_acc 0.9923 +2025-05-29 02:41:03,093 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 02:41:03,099 - pyskl - INFO - +mean_acc 0.8424 +2025-05-29 02:41:03,101 - pyskl - INFO - Epoch(val) [78][533] top1_acc: 0.8822, top5_acc: 0.9923, mean_class_accuracy: 0.8424 +2025-05-29 02:42:02,578 - pyskl - INFO - Epoch [79][100/1281] lr: 1.169e-02, eta: 10:23:06, time: 0.595, data_time: 0.176, memory: 9000, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 1.6292, loss: 1.6292 +2025-05-29 02:42:44,214 - pyskl - INFO - Epoch [79][200/1281] lr: 1.167e-02, eta: 10:22:26, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9594, top5_acc: 0.9994, loss_cls: 1.5437, loss: 1.5437 +2025-05-29 02:43:25,910 - pyskl - INFO - Epoch [79][300/1281] lr: 1.165e-02, eta: 10:21:47, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9613, top5_acc: 0.9994, loss_cls: 1.6305, loss: 1.6305 +2025-05-29 02:44:07,700 - pyskl - INFO - Epoch [79][400/1281] lr: 1.163e-02, eta: 10:21:07, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 1.5641, loss: 1.5641 +2025-05-29 02:44:49,441 - pyskl - INFO - Epoch [79][500/1281] lr: 1.161e-02, eta: 10:20:28, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 1.5908, loss: 1.5908 +2025-05-29 02:45:31,230 - pyskl - INFO - Epoch [79][600/1281] lr: 1.159e-02, eta: 10:19:48, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9475, top5_acc: 1.0000, loss_cls: 1.6679, loss: 1.6679 +2025-05-29 02:46:13,057 - pyskl - INFO - Epoch [79][700/1281] lr: 1.157e-02, eta: 10:19:09, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 1.6293, loss: 1.6293 +2025-05-29 02:46:54,642 - pyskl - INFO - Epoch [79][800/1281] lr: 1.155e-02, eta: 10:18:29, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 1.6437, loss: 1.6437 +2025-05-29 02:47:36,357 - pyskl - INFO - Epoch [79][900/1281] lr: 1.153e-02, eta: 10:17:50, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9425, top5_acc: 0.9975, loss_cls: 1.6894, loss: 1.6894 +2025-05-29 02:48:18,218 - pyskl - INFO - Epoch [79][1000/1281] lr: 1.151e-02, eta: 10:17:10, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9694, top5_acc: 0.9994, loss_cls: 1.6061, loss: 1.6061 +2025-05-29 02:49:00,061 - pyskl - INFO - Epoch [79][1100/1281] lr: 1.149e-02, eta: 10:16:31, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9563, top5_acc: 0.9988, loss_cls: 1.6429, loss: 1.6429 +2025-05-29 02:49:41,811 - pyskl - INFO - Epoch [79][1200/1281] lr: 1.147e-02, eta: 10:15:51, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9506, top5_acc: 1.0000, loss_cls: 1.6580, loss: 1.6580 +2025-05-29 02:50:16,085 - pyskl - INFO - Saving checkpoint at 79 epochs +2025-05-29 02:50:57,074 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 02:50:57,130 - pyskl - INFO - +top1_acc 0.9061 +top5_acc 0.9941 +2025-05-29 02:50:57,130 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 02:50:57,136 - pyskl - INFO - +mean_acc 0.8724 +2025-05-29 02:50:57,138 - pyskl - INFO - Epoch(val) [79][533] top1_acc: 0.9061, top5_acc: 0.9941, mean_class_accuracy: 0.8724 +2025-05-29 02:51:56,617 - pyskl - INFO - Epoch [80][100/1281] lr: 1.143e-02, eta: 10:14:25, time: 0.595, data_time: 0.178, memory: 9000, top1_acc: 0.9669, top5_acc: 0.9994, loss_cls: 1.5708, loss: 1.5708 +2025-05-29 02:52:38,235 - pyskl - INFO - Epoch [80][200/1281] lr: 1.141e-02, eta: 10:13:46, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 1.6507, loss: 1.6507 +2025-05-29 02:53:19,847 - pyskl - INFO - Epoch [80][300/1281] lr: 1.139e-02, eta: 10:13:06, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 1.5780, loss: 1.5780 +2025-05-29 02:54:01,459 - pyskl - INFO - Epoch [80][400/1281] lr: 1.137e-02, eta: 10:12:26, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 1.6511, loss: 1.6511 +2025-05-29 02:54:43,065 - pyskl - INFO - Epoch [80][500/1281] lr: 1.135e-02, eta: 10:11:47, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 1.8173, loss: 1.8173 +2025-05-29 02:55:24,820 - pyskl - INFO - Epoch [80][600/1281] lr: 1.133e-02, eta: 10:11:07, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9613, top5_acc: 0.9981, loss_cls: 1.6281, loss: 1.6281 +2025-05-29 02:56:06,511 - pyskl - INFO - Epoch [80][700/1281] lr: 1.131e-02, eta: 10:10:27, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 1.5967, loss: 1.5967 +2025-05-29 02:56:48,278 - pyskl - INFO - Epoch [80][800/1281] lr: 1.129e-02, eta: 10:09:48, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 1.6820, loss: 1.6820 +2025-05-29 02:57:30,132 - pyskl - INFO - Epoch [80][900/1281] lr: 1.127e-02, eta: 10:09:08, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 1.5794, loss: 1.5794 +2025-05-29 02:58:11,793 - pyskl - INFO - Epoch [80][1000/1281] lr: 1.125e-02, eta: 10:08:29, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 1.6027, loss: 1.6027 +2025-05-29 02:58:53,618 - pyskl - INFO - Epoch [80][1100/1281] lr: 1.123e-02, eta: 10:07:49, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9575, top5_acc: 0.9988, loss_cls: 1.6460, loss: 1.6460 +2025-05-29 02:59:35,842 - pyskl - INFO - Epoch [80][1200/1281] lr: 1.121e-02, eta: 10:07:10, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 0.9544, top5_acc: 0.9988, loss_cls: 1.6887, loss: 1.6887 +2025-05-29 03:00:10,407 - pyskl - INFO - Saving checkpoint at 80 epochs +2025-05-29 03:13:06,759 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 03:13:06,816 - pyskl - INFO - +top1_acc 0.8878 +top5_acc 0.9941 +2025-05-29 03:13:06,816 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 03:13:06,824 - pyskl - INFO - +mean_acc 0.8490 +2025-05-29 03:13:06,826 - pyskl - INFO - Epoch(val) [80][533] top1_acc: 0.8878, top5_acc: 0.9941, mean_class_accuracy: 0.8490 +2025-05-29 03:14:06,119 - pyskl - INFO - Epoch [81][100/1281] lr: 1.117e-02, eta: 10:05:44, time: 0.593, data_time: 0.176, memory: 9000, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 1.5291, loss: 1.5291 +2025-05-29 03:14:47,751 - pyskl - INFO - Epoch [81][200/1281] lr: 1.115e-02, eta: 10:05:05, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9700, top5_acc: 0.9994, loss_cls: 1.5501, loss: 1.5501 +2025-05-29 03:15:29,541 - pyskl - INFO - Epoch [81][300/1281] lr: 1.113e-02, eta: 10:04:25, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 1.6522, loss: 1.6522 +2025-05-29 03:16:11,314 - pyskl - INFO - Epoch [81][400/1281] lr: 1.111e-02, eta: 10:03:46, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 1.5610, loss: 1.5610 +2025-05-29 03:16:52,960 - pyskl - INFO - Epoch [81][500/1281] lr: 1.109e-02, eta: 10:03:06, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 1.5429, loss: 1.5429 +2025-05-29 03:17:34,576 - pyskl - INFO - Epoch [81][600/1281] lr: 1.107e-02, eta: 10:02:26, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 1.5862, loss: 1.5862 +2025-05-29 03:18:16,139 - pyskl - INFO - Epoch [81][700/1281] lr: 1.105e-02, eta: 10:01:46, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 1.5600, loss: 1.5600 +2025-05-29 03:18:57,768 - pyskl - INFO - Epoch [81][800/1281] lr: 1.103e-02, eta: 10:01:07, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9500, top5_acc: 1.0000, loss_cls: 1.6089, loss: 1.6089 +2025-05-29 03:19:39,412 - pyskl - INFO - Epoch [81][900/1281] lr: 1.101e-02, eta: 10:00:27, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 1.6202, loss: 1.6202 +2025-05-29 03:20:21,244 - pyskl - INFO - Epoch [81][1000/1281] lr: 1.099e-02, eta: 9:59:48, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9550, top5_acc: 0.9994, loss_cls: 1.5937, loss: 1.5937 +2025-05-29 03:21:03,072 - pyskl - INFO - Epoch [81][1100/1281] lr: 1.097e-02, eta: 9:59:08, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9613, top5_acc: 0.9988, loss_cls: 1.5537, loss: 1.5537 +2025-05-29 03:21:45,446 - pyskl - INFO - Epoch [81][1200/1281] lr: 1.095e-02, eta: 9:58:29, time: 0.424, data_time: 0.000, memory: 9000, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 1.6513, loss: 1.6513 +2025-05-29 03:22:19,990 - pyskl - INFO - Saving checkpoint at 81 epochs +2025-05-29 03:23:00,556 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 03:23:00,612 - pyskl - INFO - +top1_acc 0.9011 +top5_acc 0.9957 +2025-05-29 03:23:00,612 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 03:23:00,620 - pyskl - INFO - +mean_acc 0.8794 +2025-05-29 03:23:00,623 - pyskl - INFO - Epoch(val) [81][533] top1_acc: 0.9011, top5_acc: 0.9957, mean_class_accuracy: 0.8794 +2025-05-29 03:23:59,956 - pyskl - INFO - Epoch [82][100/1281] lr: 1.091e-02, eta: 9:57:03, time: 0.593, data_time: 0.176, memory: 9000, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 1.5369, loss: 1.5369 +2025-05-29 03:24:41,559 - pyskl - INFO - Epoch [82][200/1281] lr: 1.089e-02, eta: 9:56:24, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 1.6254, loss: 1.6254 +2025-05-29 03:25:23,151 - pyskl - INFO - Epoch [82][300/1281] lr: 1.087e-02, eta: 9:55:44, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 1.5332, loss: 1.5332 +2025-05-29 03:26:04,883 - pyskl - INFO - Epoch [82][400/1281] lr: 1.085e-02, eta: 9:55:04, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9712, top5_acc: 0.9994, loss_cls: 1.5119, loss: 1.5119 +2025-05-29 03:26:46,706 - pyskl - INFO - Epoch [82][500/1281] lr: 1.083e-02, eta: 9:54:25, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9681, top5_acc: 0.9994, loss_cls: 1.5936, loss: 1.5936 +2025-05-29 03:27:28,358 - pyskl - INFO - Epoch [82][600/1281] lr: 1.081e-02, eta: 9:53:45, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 1.5291, loss: 1.5291 +2025-05-29 03:28:10,003 - pyskl - INFO - Epoch [82][700/1281] lr: 1.079e-02, eta: 9:53:06, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9613, top5_acc: 0.9994, loss_cls: 1.5250, loss: 1.5250 +2025-05-29 03:28:51,635 - pyskl - INFO - Epoch [82][800/1281] lr: 1.077e-02, eta: 9:52:26, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9725, top5_acc: 0.9994, loss_cls: 1.5419, loss: 1.5419 +2025-05-29 03:29:33,319 - pyskl - INFO - Epoch [82][900/1281] lr: 1.075e-02, eta: 9:51:46, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 1.5937, loss: 1.5937 +2025-05-29 03:30:15,322 - pyskl - INFO - Epoch [82][1000/1281] lr: 1.073e-02, eta: 9:51:07, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 1.5924, loss: 1.5924 +2025-05-29 03:30:57,054 - pyskl - INFO - Epoch [82][1100/1281] lr: 1.071e-02, eta: 9:50:27, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 1.5275, loss: 1.5275 +2025-05-29 03:31:38,453 - pyskl - INFO - Epoch [82][1200/1281] lr: 1.069e-02, eta: 9:49:47, time: 0.414, data_time: 0.000, memory: 9000, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 1.5462, loss: 1.5462 +2025-05-29 03:32:12,748 - pyskl - INFO - Saving checkpoint at 82 epochs +2025-05-29 03:32:53,953 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 03:32:54,009 - pyskl - INFO - +top1_acc 0.9081 +top5_acc 0.9944 +2025-05-29 03:32:54,009 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 03:32:54,016 - pyskl - INFO - +mean_acc 0.8751 +2025-05-29 03:32:54,018 - pyskl - INFO - Epoch(val) [82][533] top1_acc: 0.9081, top5_acc: 0.9944, mean_class_accuracy: 0.8751 +2025-05-29 03:33:53,341 - pyskl - INFO - Epoch [83][100/1281] lr: 1.065e-02, eta: 9:48:22, time: 0.593, data_time: 0.176, memory: 9000, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 1.5315, loss: 1.5315 +2025-05-29 03:34:34,994 - pyskl - INFO - Epoch [83][200/1281] lr: 1.063e-02, eta: 9:47:42, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 1.6289, loss: 1.6289 +2025-05-29 03:35:16,866 - pyskl - INFO - Epoch [83][300/1281] lr: 1.061e-02, eta: 9:47:03, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 1.5829, loss: 1.5829 +2025-05-29 03:35:58,636 - pyskl - INFO - Epoch [83][400/1281] lr: 1.059e-02, eta: 9:46:23, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9550, top5_acc: 0.9994, loss_cls: 1.6841, loss: 1.6841 +2025-05-29 03:36:40,357 - pyskl - INFO - Epoch [83][500/1281] lr: 1.057e-02, eta: 9:45:44, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 1.5710, loss: 1.5710 +2025-05-29 03:37:21,962 - pyskl - INFO - Epoch [83][600/1281] lr: 1.055e-02, eta: 9:45:04, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 1.5173, loss: 1.5173 +2025-05-29 03:38:03,660 - pyskl - INFO - Epoch [83][700/1281] lr: 1.053e-02, eta: 9:44:24, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9637, top5_acc: 0.9988, loss_cls: 1.5442, loss: 1.5442 +2025-05-29 03:38:45,480 - pyskl - INFO - Epoch [83][800/1281] lr: 1.051e-02, eta: 9:43:45, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9694, top5_acc: 0.9994, loss_cls: 1.6072, loss: 1.6072 +2025-05-29 03:39:27,207 - pyskl - INFO - Epoch [83][900/1281] lr: 1.049e-02, eta: 9:43:05, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 1.5152, loss: 1.5152 +2025-05-29 03:40:08,944 - pyskl - INFO - Epoch [83][1000/1281] lr: 1.047e-02, eta: 9:42:25, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9631, top5_acc: 0.9988, loss_cls: 1.5420, loss: 1.5420 +2025-05-29 03:40:50,714 - pyskl - INFO - Epoch [83][1100/1281] lr: 1.045e-02, eta: 9:41:46, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9569, top5_acc: 0.9994, loss_cls: 1.5465, loss: 1.5465 +2025-05-29 03:41:32,550 - pyskl - INFO - Epoch [83][1200/1281] lr: 1.043e-02, eta: 9:41:06, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9613, top5_acc: 0.9994, loss_cls: 1.6494, loss: 1.6494 +2025-05-29 03:42:07,040 - pyskl - INFO - Saving checkpoint at 83 epochs +2025-05-29 03:42:47,974 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 03:42:48,031 - pyskl - INFO - +top1_acc 0.8877 +top5_acc 0.9930 +2025-05-29 03:42:48,031 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 03:42:48,039 - pyskl - INFO - +mean_acc 0.8679 +2025-05-29 03:42:48,042 - pyskl - INFO - Epoch(val) [83][533] top1_acc: 0.8877, top5_acc: 0.9930, mean_class_accuracy: 0.8679 +2025-05-29 03:43:48,775 - pyskl - INFO - Epoch [84][100/1281] lr: 1.040e-02, eta: 9:39:42, time: 0.607, data_time: 0.188, memory: 9000, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 1.6347, loss: 1.6347 +2025-05-29 03:44:30,629 - pyskl - INFO - Epoch [84][200/1281] lr: 1.038e-02, eta: 9:39:03, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 1.6456, loss: 1.6456 +2025-05-29 03:45:12,247 - pyskl - INFO - Epoch [84][300/1281] lr: 1.036e-02, eta: 9:38:23, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 1.5121, loss: 1.5121 +2025-05-29 03:45:53,852 - pyskl - INFO - Epoch [84][400/1281] lr: 1.034e-02, eta: 9:37:43, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 1.4456, loss: 1.4456 +2025-05-29 03:46:35,492 - pyskl - INFO - Epoch [84][500/1281] lr: 1.031e-02, eta: 9:37:04, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 1.5288, loss: 1.5288 +2025-05-29 03:47:17,171 - pyskl - INFO - Epoch [84][600/1281] lr: 1.029e-02, eta: 9:36:24, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 1.5333, loss: 1.5333 +2025-05-29 03:47:58,750 - pyskl - INFO - Epoch [84][700/1281] lr: 1.027e-02, eta: 9:35:44, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9681, top5_acc: 0.9994, loss_cls: 1.5475, loss: 1.5475 +2025-05-29 03:48:40,404 - pyskl - INFO - Epoch [84][800/1281] lr: 1.025e-02, eta: 9:35:04, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 1.5737, loss: 1.5737 +2025-05-29 03:49:22,034 - pyskl - INFO - Epoch [84][900/1281] lr: 1.023e-02, eta: 9:34:25, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 1.6057, loss: 1.6057 +2025-05-29 03:50:03,858 - pyskl - INFO - Epoch [84][1000/1281] lr: 1.021e-02, eta: 9:33:45, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 1.5936, loss: 1.5936 +2025-05-29 03:50:45,798 - pyskl - INFO - Epoch [84][1100/1281] lr: 1.019e-02, eta: 9:33:06, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9556, top5_acc: 0.9994, loss_cls: 1.6239, loss: 1.6239 +2025-05-29 03:51:27,563 - pyskl - INFO - Epoch [84][1200/1281] lr: 1.017e-02, eta: 9:32:26, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 1.5386, loss: 1.5386 +2025-05-29 03:52:02,123 - pyskl - INFO - Saving checkpoint at 84 epochs +2025-05-29 03:52:43,515 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 03:52:43,571 - pyskl - INFO - +top1_acc 0.9110 +top5_acc 0.9942 +2025-05-29 03:52:43,571 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 03:52:43,578 - pyskl - INFO - +mean_acc 0.8748 +2025-05-29 03:52:43,581 - pyskl - INFO - Epoch(val) [84][533] top1_acc: 0.9110, top5_acc: 0.9942, mean_class_accuracy: 0.8748 +2025-05-29 03:53:43,272 - pyskl - INFO - Epoch [85][100/1281] lr: 1.014e-02, eta: 9:31:02, time: 0.597, data_time: 0.180, memory: 9000, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 1.4961, loss: 1.4961 +2025-05-29 03:54:24,909 - pyskl - INFO - Epoch [85][200/1281] lr: 1.012e-02, eta: 9:30:22, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 1.5414, loss: 1.5414 +2025-05-29 03:55:06,559 - pyskl - INFO - Epoch [85][300/1281] lr: 1.010e-02, eta: 9:29:42, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9663, top5_acc: 0.9988, loss_cls: 1.6207, loss: 1.6207 +2025-05-29 03:55:48,237 - pyskl - INFO - Epoch [85][400/1281] lr: 1.008e-02, eta: 9:29:03, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 1.5459, loss: 1.5459 +2025-05-29 03:56:29,907 - pyskl - INFO - Epoch [85][500/1281] lr: 1.006e-02, eta: 9:28:23, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 1.5823, loss: 1.5823 +2025-05-29 03:57:11,554 - pyskl - INFO - Epoch [85][600/1281] lr: 1.004e-02, eta: 9:27:43, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 1.5021, loss: 1.5021 +2025-05-29 03:57:53,229 - pyskl - INFO - Epoch [85][700/1281] lr: 1.002e-02, eta: 9:27:03, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 1.5910, loss: 1.5910 +2025-05-29 03:58:34,936 - pyskl - INFO - Epoch [85][800/1281] lr: 9.998e-03, eta: 9:26:24, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 1.5623, loss: 1.5623 +2025-05-29 03:59:16,672 - pyskl - INFO - Epoch [85][900/1281] lr: 9.978e-03, eta: 9:25:44, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 1.6115, loss: 1.6115 +2025-05-29 03:59:58,535 - pyskl - INFO - Epoch [85][1000/1281] lr: 9.958e-03, eta: 9:25:04, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 1.5631, loss: 1.5631 +2025-05-29 04:00:40,286 - pyskl - INFO - Epoch [85][1100/1281] lr: 9.937e-03, eta: 9:24:25, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 1.4843, loss: 1.4843 +2025-05-29 04:01:22,098 - pyskl - INFO - Epoch [85][1200/1281] lr: 9.917e-03, eta: 9:23:45, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9712, top5_acc: 0.9994, loss_cls: 1.4767, loss: 1.4767 +2025-05-29 04:01:56,817 - pyskl - INFO - Saving checkpoint at 85 epochs +2025-05-29 04:15:17,052 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 04:15:17,108 - pyskl - INFO - +top1_acc 0.9012 +top5_acc 0.9945 +2025-05-29 04:15:17,108 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 04:15:17,115 - pyskl - INFO - +mean_acc 0.8660 +2025-05-29 04:15:17,118 - pyskl - INFO - Epoch(val) [85][533] top1_acc: 0.9012, top5_acc: 0.9945, mean_class_accuracy: 0.8660 +2025-05-29 04:16:16,767 - pyskl - INFO - Epoch [86][100/1281] lr: 9.881e-03, eta: 9:22:21, time: 0.596, data_time: 0.177, memory: 9000, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 1.5373, loss: 1.5373 +2025-05-29 04:16:58,447 - pyskl - INFO - Epoch [86][200/1281] lr: 9.861e-03, eta: 9:21:41, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9762, top5_acc: 0.9994, loss_cls: 1.5194, loss: 1.5194 +2025-05-29 04:17:40,144 - pyskl - INFO - Epoch [86][300/1281] lr: 9.841e-03, eta: 9:21:02, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 1.5184, loss: 1.5184 +2025-05-29 04:18:21,803 - pyskl - INFO - Epoch [86][400/1281] lr: 9.821e-03, eta: 9:20:22, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 1.4670, loss: 1.4670 +2025-05-29 04:19:03,048 - pyskl - INFO - Epoch [86][500/1281] lr: 9.801e-03, eta: 9:19:42, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 1.4762, loss: 1.4762 +2025-05-29 04:19:44,220 - pyskl - INFO - Epoch [86][600/1281] lr: 9.781e-03, eta: 9:19:02, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 1.5345, loss: 1.5345 +2025-05-29 04:20:25,390 - pyskl - INFO - Epoch [86][700/1281] lr: 9.762e-03, eta: 9:18:21, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9631, top5_acc: 0.9994, loss_cls: 1.5939, loss: 1.5939 +2025-05-29 04:21:06,560 - pyskl - INFO - Epoch [86][800/1281] lr: 9.742e-03, eta: 9:17:41, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 1.5045, loss: 1.5045 +2025-05-29 04:21:47,727 - pyskl - INFO - Epoch [86][900/1281] lr: 9.722e-03, eta: 9:17:01, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 1.6310, loss: 1.6310 +2025-05-29 04:22:28,967 - pyskl - INFO - Epoch [86][1000/1281] lr: 9.702e-03, eta: 9:16:21, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9587, top5_acc: 0.9994, loss_cls: 1.5744, loss: 1.5744 +2025-05-29 04:23:11,040 - pyskl - INFO - Epoch [86][1100/1281] lr: 9.682e-03, eta: 9:15:42, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9587, top5_acc: 0.9994, loss_cls: 1.5676, loss: 1.5676 +2025-05-29 04:23:52,384 - pyskl - INFO - Epoch [86][1200/1281] lr: 9.662e-03, eta: 9:15:02, time: 0.413, data_time: 0.000, memory: 9000, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 1.5760, loss: 1.5760 +2025-05-29 04:24:26,899 - pyskl - INFO - Saving checkpoint at 86 epochs +2025-05-29 04:25:07,817 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 04:25:07,872 - pyskl - INFO - +top1_acc 0.8984 +top5_acc 0.9928 +2025-05-29 04:25:07,872 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 04:25:07,878 - pyskl - INFO - +mean_acc 0.8745 +2025-05-29 04:25:07,881 - pyskl - INFO - Epoch(val) [86][533] top1_acc: 0.8984, top5_acc: 0.9928, mean_class_accuracy: 0.8745 +2025-05-29 04:26:07,392 - pyskl - INFO - Epoch [87][100/1281] lr: 9.626e-03, eta: 9:13:38, time: 0.595, data_time: 0.179, memory: 9000, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 1.4933, loss: 1.4933 +2025-05-29 04:26:49,613 - pyskl - INFO - Epoch [87][200/1281] lr: 9.606e-03, eta: 9:12:58, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 1.5022, loss: 1.5022 +2025-05-29 04:27:31,662 - pyskl - INFO - Epoch [87][300/1281] lr: 9.586e-03, eta: 9:12:19, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9656, top5_acc: 0.9994, loss_cls: 1.5291, loss: 1.5291 +2025-05-29 04:28:13,508 - pyskl - INFO - Epoch [87][400/1281] lr: 9.566e-03, eta: 9:11:39, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 1.4577, loss: 1.4577 +2025-05-29 04:28:55,283 - pyskl - INFO - Epoch [87][500/1281] lr: 9.546e-03, eta: 9:11:00, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 1.4819, loss: 1.4819 +2025-05-29 04:29:37,083 - pyskl - INFO - Epoch [87][600/1281] lr: 9.527e-03, eta: 9:10:20, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9656, top5_acc: 0.9994, loss_cls: 1.5458, loss: 1.5458 +2025-05-29 04:30:18,815 - pyskl - INFO - Epoch [87][700/1281] lr: 9.507e-03, eta: 9:09:40, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 1.5422, loss: 1.5422 +2025-05-29 04:31:00,547 - pyskl - INFO - Epoch [87][800/1281] lr: 9.487e-03, eta: 9:09:01, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 1.4071, loss: 1.4071 +2025-05-29 04:31:42,288 - pyskl - INFO - Epoch [87][900/1281] lr: 9.467e-03, eta: 9:08:21, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9669, top5_acc: 0.9994, loss_cls: 1.5234, loss: 1.5234 +2025-05-29 04:32:24,088 - pyskl - INFO - Epoch [87][1000/1281] lr: 9.447e-03, eta: 9:07:41, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 1.5756, loss: 1.5756 +2025-05-29 04:33:05,946 - pyskl - INFO - Epoch [87][1100/1281] lr: 9.427e-03, eta: 9:07:02, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9669, top5_acc: 0.9994, loss_cls: 1.5078, loss: 1.5078 +2025-05-29 04:33:47,761 - pyskl - INFO - Epoch [87][1200/1281] lr: 9.408e-03, eta: 9:06:22, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 1.5986, loss: 1.5986 +2025-05-29 04:34:22,246 - pyskl - INFO - Saving checkpoint at 87 epochs +2025-05-29 04:35:03,129 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 04:35:03,185 - pyskl - INFO - +top1_acc 0.9042 +top5_acc 0.9938 +2025-05-29 04:35:03,185 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 04:35:03,191 - pyskl - INFO - +mean_acc 0.8785 +2025-05-29 04:35:03,194 - pyskl - INFO - Epoch(val) [87][533] top1_acc: 0.9042, top5_acc: 0.9938, mean_class_accuracy: 0.8785 +2025-05-29 04:36:02,617 - pyskl - INFO - Epoch [88][100/1281] lr: 9.372e-03, eta: 9:04:58, time: 0.594, data_time: 0.176, memory: 9000, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 1.4618, loss: 1.4618 +2025-05-29 04:36:44,376 - pyskl - INFO - Epoch [88][200/1281] lr: 9.352e-03, eta: 9:04:19, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9656, top5_acc: 0.9994, loss_cls: 1.5673, loss: 1.5673 +2025-05-29 04:37:26,200 - pyskl - INFO - Epoch [88][300/1281] lr: 9.332e-03, eta: 9:03:39, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 1.4556, loss: 1.4556 +2025-05-29 04:38:07,936 - pyskl - INFO - Epoch [88][400/1281] lr: 9.312e-03, eta: 9:02:59, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 1.4856, loss: 1.4856 +2025-05-29 04:38:49,722 - pyskl - INFO - Epoch [88][500/1281] lr: 9.293e-03, eta: 9:02:19, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 1.5082, loss: 1.5082 +2025-05-29 04:39:31,381 - pyskl - INFO - Epoch [88][600/1281] lr: 9.273e-03, eta: 9:01:40, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 1.4230, loss: 1.4230 +2025-05-29 04:40:12,978 - pyskl - INFO - Epoch [88][700/1281] lr: 9.253e-03, eta: 9:01:00, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 1.3757, loss: 1.3757 +2025-05-29 04:40:54,637 - pyskl - INFO - Epoch [88][800/1281] lr: 9.233e-03, eta: 9:00:20, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 1.5312, loss: 1.5312 +2025-05-29 04:41:36,021 - pyskl - INFO - Epoch [88][900/1281] lr: 9.214e-03, eta: 8:59:40, time: 0.414, data_time: 0.000, memory: 9000, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 1.4988, loss: 1.4988 +2025-05-29 04:42:17,530 - pyskl - INFO - Epoch [88][1000/1281] lr: 9.194e-03, eta: 8:59:00, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 1.5221, loss: 1.5221 +2025-05-29 04:42:59,334 - pyskl - INFO - Epoch [88][1100/1281] lr: 9.174e-03, eta: 8:58:20, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9700, top5_acc: 0.9994, loss_cls: 1.5337, loss: 1.5337 +2025-05-29 04:43:41,254 - pyskl - INFO - Epoch [88][1200/1281] lr: 9.155e-03, eta: 8:57:41, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9712, top5_acc: 0.9994, loss_cls: 1.4839, loss: 1.4839 +2025-05-29 04:44:15,550 - pyskl - INFO - Saving checkpoint at 88 epochs +2025-05-29 04:44:56,470 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 04:44:56,526 - pyskl - INFO - +top1_acc 0.9010 +top5_acc 0.9935 +2025-05-29 04:44:56,526 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 04:44:56,534 - pyskl - INFO - +mean_acc 0.8725 +2025-05-29 04:44:56,536 - pyskl - INFO - Epoch(val) [88][533] top1_acc: 0.9010, top5_acc: 0.9935, mean_class_accuracy: 0.8725 +2025-05-29 04:45:55,815 - pyskl - INFO - Epoch [89][100/1281] lr: 9.119e-03, eta: 8:56:17, time: 0.593, data_time: 0.176, memory: 9000, top1_acc: 0.9750, top5_acc: 0.9994, loss_cls: 1.5104, loss: 1.5104 +2025-05-29 04:46:37,583 - pyskl - INFO - Epoch [89][200/1281] lr: 9.099e-03, eta: 8:55:38, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 1.4401, loss: 1.4401 +2025-05-29 04:47:19,248 - pyskl - INFO - Epoch [89][300/1281] lr: 9.080e-03, eta: 8:54:58, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 1.4479, loss: 1.4479 +2025-05-29 04:48:00,846 - pyskl - INFO - Epoch [89][400/1281] lr: 9.060e-03, eta: 8:54:18, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 1.5695, loss: 1.5695 +2025-05-29 04:48:42,858 - pyskl - INFO - Epoch [89][500/1281] lr: 9.040e-03, eta: 8:53:38, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 1.4471, loss: 1.4471 +2025-05-29 04:49:25,111 - pyskl - INFO - Epoch [89][600/1281] lr: 9.021e-03, eta: 8:52:59, time: 0.423, data_time: 0.000, memory: 9000, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 1.5125, loss: 1.5125 +2025-05-29 04:50:06,924 - pyskl - INFO - Epoch [89][700/1281] lr: 9.001e-03, eta: 8:52:19, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9725, top5_acc: 0.9994, loss_cls: 1.5408, loss: 1.5408 +2025-05-29 04:50:48,638 - pyskl - INFO - Epoch [89][800/1281] lr: 8.982e-03, eta: 8:51:40, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 1.5319, loss: 1.5319 +2025-05-29 04:51:30,346 - pyskl - INFO - Epoch [89][900/1281] lr: 8.962e-03, eta: 8:51:00, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 1.5724, loss: 1.5724 +2025-05-29 04:52:12,064 - pyskl - INFO - Epoch [89][1000/1281] lr: 8.942e-03, eta: 8:50:20, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 1.5108, loss: 1.5108 +2025-05-29 04:52:53,972 - pyskl - INFO - Epoch [89][1100/1281] lr: 8.923e-03, eta: 8:49:40, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9719, top5_acc: 0.9994, loss_cls: 1.4470, loss: 1.4470 +2025-05-29 04:53:35,749 - pyskl - INFO - Epoch [89][1200/1281] lr: 8.903e-03, eta: 8:49:01, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9719, top5_acc: 0.9988, loss_cls: 1.4338, loss: 1.4338 +2025-05-29 04:54:10,204 - pyskl - INFO - Saving checkpoint at 89 epochs +2025-05-29 04:54:51,307 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 04:54:51,363 - pyskl - INFO - +top1_acc 0.9174 +top5_acc 0.9951 +2025-05-29 04:54:51,363 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 04:54:51,369 - pyskl - INFO - +mean_acc 0.8820 +2025-05-29 04:54:51,428 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_76.pth was removed +2025-05-29 04:54:52,914 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_89.pth. +2025-05-29 04:54:52,914 - pyskl - INFO - Best top1_acc is 0.9174 at 89 epoch. +2025-05-29 04:54:52,918 - pyskl - INFO - Epoch(val) [89][533] top1_acc: 0.9174, top5_acc: 0.9951, mean_class_accuracy: 0.8820 +2025-05-29 04:55:52,373 - pyskl - INFO - Epoch [90][100/1281] lr: 8.868e-03, eta: 8:47:37, time: 0.595, data_time: 0.177, memory: 9000, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 1.5044, loss: 1.5044 +2025-05-29 04:56:33,952 - pyskl - INFO - Epoch [90][200/1281] lr: 8.848e-03, eta: 8:46:58, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 1.4565, loss: 1.4565 +2025-05-29 04:57:15,652 - pyskl - INFO - Epoch [90][300/1281] lr: 8.829e-03, eta: 8:46:18, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 1.4120, loss: 1.4120 +2025-05-29 04:57:57,334 - pyskl - INFO - Epoch [90][400/1281] lr: 8.809e-03, eta: 8:45:38, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 1.4420, loss: 1.4420 +2025-05-29 04:58:39,037 - pyskl - INFO - Epoch [90][500/1281] lr: 8.790e-03, eta: 8:44:58, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 1.4655, loss: 1.4655 +2025-05-29 04:59:20,826 - pyskl - INFO - Epoch [90][600/1281] lr: 8.770e-03, eta: 8:44:18, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 1.4397, loss: 1.4397 +2025-05-29 05:00:02,547 - pyskl - INFO - Epoch [90][700/1281] lr: 8.751e-03, eta: 8:43:39, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 1.3483, loss: 1.3483 +2025-05-29 05:00:44,248 - pyskl - INFO - Epoch [90][800/1281] lr: 8.731e-03, eta: 8:42:59, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 1.4242, loss: 1.4242 +2025-05-29 05:01:25,998 - pyskl - INFO - Epoch [90][900/1281] lr: 8.712e-03, eta: 8:42:19, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9725, top5_acc: 0.9988, loss_cls: 1.4712, loss: 1.4712 +2025-05-29 05:02:07,832 - pyskl - INFO - Epoch [90][1000/1281] lr: 8.692e-03, eta: 8:41:39, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 1.5579, loss: 1.5579 +2025-05-29 05:02:49,597 - pyskl - INFO - Epoch [90][1100/1281] lr: 8.673e-03, eta: 8:41:00, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9600, top5_acc: 0.9994, loss_cls: 1.5803, loss: 1.5803 +2025-05-29 05:03:31,200 - pyskl - INFO - Epoch [90][1200/1281] lr: 8.653e-03, eta: 8:40:20, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 1.4829, loss: 1.4829 +2025-05-29 05:04:05,589 - pyskl - INFO - Saving checkpoint at 90 epochs +2025-05-29 05:16:47,476 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 05:16:47,533 - pyskl - INFO - +top1_acc 0.9049 +top5_acc 0.9938 +2025-05-29 05:16:47,533 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 05:16:47,541 - pyskl - INFO - +mean_acc 0.8744 +2025-05-29 05:16:47,543 - pyskl - INFO - Epoch(val) [90][533] top1_acc: 0.9049, top5_acc: 0.9938, mean_class_accuracy: 0.8744 +2025-05-29 05:17:47,060 - pyskl - INFO - Epoch [91][100/1281] lr: 8.618e-03, eta: 8:38:57, time: 0.595, data_time: 0.179, memory: 9000, top1_acc: 0.9744, top5_acc: 0.9994, loss_cls: 1.4561, loss: 1.4561 +2025-05-29 05:18:28,672 - pyskl - INFO - Epoch [91][200/1281] lr: 8.599e-03, eta: 8:38:17, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 1.4602, loss: 1.4602 +2025-05-29 05:19:10,251 - pyskl - INFO - Epoch [91][300/1281] lr: 8.579e-03, eta: 8:37:37, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 1.4686, loss: 1.4686 +2025-05-29 05:19:51,863 - pyskl - INFO - Epoch [91][400/1281] lr: 8.560e-03, eta: 8:36:57, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9681, top5_acc: 0.9994, loss_cls: 1.5192, loss: 1.5192 +2025-05-29 05:20:33,487 - pyskl - INFO - Epoch [91][500/1281] lr: 8.540e-03, eta: 8:36:17, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 1.5331, loss: 1.5331 +2025-05-29 05:21:15,203 - pyskl - INFO - Epoch [91][600/1281] lr: 8.521e-03, eta: 8:35:38, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 1.4201, loss: 1.4201 +2025-05-29 05:21:57,016 - pyskl - INFO - Epoch [91][700/1281] lr: 8.502e-03, eta: 8:34:58, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 1.4213, loss: 1.4213 +2025-05-29 05:22:38,828 - pyskl - INFO - Epoch [91][800/1281] lr: 8.482e-03, eta: 8:34:18, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 1.5389, loss: 1.5389 +2025-05-29 05:23:20,527 - pyskl - INFO - Epoch [91][900/1281] lr: 8.463e-03, eta: 8:33:38, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 1.4675, loss: 1.4675 +2025-05-29 05:24:02,285 - pyskl - INFO - Epoch [91][1000/1281] lr: 8.444e-03, eta: 8:32:58, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 1.4982, loss: 1.4982 +2025-05-29 05:24:44,099 - pyskl - INFO - Epoch [91][1100/1281] lr: 8.424e-03, eta: 8:32:19, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9631, top5_acc: 0.9994, loss_cls: 1.5222, loss: 1.5222 +2025-05-29 05:25:25,938 - pyskl - INFO - Epoch [91][1200/1281] lr: 8.405e-03, eta: 8:31:39, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 1.4592, loss: 1.4592 +2025-05-29 05:26:00,285 - pyskl - INFO - Saving checkpoint at 91 epochs +2025-05-29 05:26:41,310 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 05:26:41,367 - pyskl - INFO - +top1_acc 0.9089 +top5_acc 0.9942 +2025-05-29 05:26:41,367 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 05:26:41,374 - pyskl - INFO - +mean_acc 0.8846 +2025-05-29 05:26:41,377 - pyskl - INFO - Epoch(val) [91][533] top1_acc: 0.9089, top5_acc: 0.9942, mean_class_accuracy: 0.8846 +2025-05-29 05:27:40,759 - pyskl - INFO - Epoch [92][100/1281] lr: 8.370e-03, eta: 8:30:16, time: 0.594, data_time: 0.177, memory: 9000, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 1.4139, loss: 1.4139 +2025-05-29 05:28:22,397 - pyskl - INFO - Epoch [92][200/1281] lr: 8.351e-03, eta: 8:29:37, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 1.4761, loss: 1.4761 +2025-05-29 05:29:04,065 - pyskl - INFO - Epoch [92][300/1281] lr: 8.332e-03, eta: 8:28:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 1.4096, loss: 1.4096 +2025-05-29 05:29:45,646 - pyskl - INFO - Epoch [92][400/1281] lr: 8.312e-03, eta: 8:28:17, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 1.4821, loss: 1.4821 +2025-05-29 05:30:27,302 - pyskl - INFO - Epoch [92][500/1281] lr: 8.293e-03, eta: 8:27:37, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 1.4323, loss: 1.4323 +2025-05-29 05:31:09,002 - pyskl - INFO - Epoch [92][600/1281] lr: 8.274e-03, eta: 8:26:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 1.4544, loss: 1.4544 +2025-05-29 05:31:50,676 - pyskl - INFO - Epoch [92][700/1281] lr: 8.255e-03, eta: 8:26:17, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 1.4398, loss: 1.4398 +2025-05-29 05:32:32,676 - pyskl - INFO - Epoch [92][800/1281] lr: 8.235e-03, eta: 8:25:38, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 1.4402, loss: 1.4402 +2025-05-29 05:33:15,118 - pyskl - INFO - Epoch [92][900/1281] lr: 8.216e-03, eta: 8:24:58, time: 0.424, data_time: 0.000, memory: 9000, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 1.4778, loss: 1.4778 +2025-05-29 05:33:57,083 - pyskl - INFO - Epoch [92][1000/1281] lr: 8.197e-03, eta: 8:24:18, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 1.4173, loss: 1.4173 +2025-05-29 05:34:39,103 - pyskl - INFO - Epoch [92][1100/1281] lr: 8.178e-03, eta: 8:23:39, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 1.5373, loss: 1.5373 +2025-05-29 05:35:20,936 - pyskl - INFO - Epoch [92][1200/1281] lr: 8.159e-03, eta: 8:22:59, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 1.6139, loss: 1.6139 +2025-05-29 05:35:55,286 - pyskl - INFO - Saving checkpoint at 92 epochs +2025-05-29 05:36:36,221 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 05:36:36,275 - pyskl - INFO - +top1_acc 0.9081 +top5_acc 0.9945 +2025-05-29 05:36:36,275 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 05:36:36,282 - pyskl - INFO - +mean_acc 0.8890 +2025-05-29 05:36:36,284 - pyskl - INFO - Epoch(val) [92][533] top1_acc: 0.9081, top5_acc: 0.9945, mean_class_accuracy: 0.8890 +2025-05-29 05:37:35,951 - pyskl - INFO - Epoch [93][100/1281] lr: 8.124e-03, eta: 8:21:37, time: 0.597, data_time: 0.180, memory: 9000, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 1.4198, loss: 1.4198 +2025-05-29 05:38:17,705 - pyskl - INFO - Epoch [93][200/1281] lr: 8.105e-03, eta: 8:20:57, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9781, top5_acc: 0.9994, loss_cls: 1.3836, loss: 1.3836 +2025-05-29 05:38:59,503 - pyskl - INFO - Epoch [93][300/1281] lr: 8.086e-03, eta: 8:20:17, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 1.3944, loss: 1.3944 +2025-05-29 05:39:41,177 - pyskl - INFO - Epoch [93][400/1281] lr: 8.067e-03, eta: 8:19:37, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 1.5050, loss: 1.5050 +2025-05-29 05:40:22,854 - pyskl - INFO - Epoch [93][500/1281] lr: 8.047e-03, eta: 8:18:58, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 1.4233, loss: 1.4233 +2025-05-29 05:41:04,532 - pyskl - INFO - Epoch [93][600/1281] lr: 8.028e-03, eta: 8:18:18, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9850, top5_acc: 0.9988, loss_cls: 1.3718, loss: 1.3718 +2025-05-29 05:41:46,205 - pyskl - INFO - Epoch [93][700/1281] lr: 8.009e-03, eta: 8:17:38, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 1.3525, loss: 1.3525 +2025-05-29 05:42:27,849 - pyskl - INFO - Epoch [93][800/1281] lr: 7.990e-03, eta: 8:16:58, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 1.4653, loss: 1.4653 +2025-05-29 05:43:09,583 - pyskl - INFO - Epoch [93][900/1281] lr: 7.971e-03, eta: 8:16:18, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 1.4683, loss: 1.4683 +2025-05-29 05:43:51,389 - pyskl - INFO - Epoch [93][1000/1281] lr: 7.952e-03, eta: 8:15:38, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 0.9994, loss_cls: 1.4355, loss: 1.4355 +2025-05-29 05:44:33,100 - pyskl - INFO - Epoch [93][1100/1281] lr: 7.933e-03, eta: 8:14:58, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 0.9994, loss_cls: 1.4380, loss: 1.4380 +2025-05-29 05:45:14,912 - pyskl - INFO - Epoch [93][1200/1281] lr: 7.914e-03, eta: 8:14:19, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9681, top5_acc: 0.9994, loss_cls: 1.5434, loss: 1.5434 +2025-05-29 05:45:49,226 - pyskl - INFO - Saving checkpoint at 93 epochs +2025-05-29 05:46:30,342 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 05:46:30,400 - pyskl - INFO - +top1_acc 0.9087 +top5_acc 0.9958 +2025-05-29 05:46:30,400 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 05:46:30,407 - pyskl - INFO - +mean_acc 0.8857 +2025-05-29 05:46:30,409 - pyskl - INFO - Epoch(val) [93][533] top1_acc: 0.9087, top5_acc: 0.9958, mean_class_accuracy: 0.8857 +2025-05-29 05:47:30,020 - pyskl - INFO - Epoch [94][100/1281] lr: 7.880e-03, eta: 8:12:57, time: 0.596, data_time: 0.179, memory: 9000, top1_acc: 0.9750, top5_acc: 0.9994, loss_cls: 1.5115, loss: 1.5115 +2025-05-29 05:48:11,651 - pyskl - INFO - Epoch [94][200/1281] lr: 7.861e-03, eta: 8:12:17, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 1.2981, loss: 1.2981 +2025-05-29 05:48:53,247 - pyskl - INFO - Epoch [94][300/1281] lr: 7.842e-03, eta: 8:11:37, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 1.4316, loss: 1.4316 +2025-05-29 05:49:34,835 - pyskl - INFO - Epoch [94][400/1281] lr: 7.823e-03, eta: 8:10:57, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9700, top5_acc: 0.9994, loss_cls: 1.4592, loss: 1.4592 +2025-05-29 05:50:16,448 - pyskl - INFO - Epoch [94][500/1281] lr: 7.804e-03, eta: 8:10:17, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 1.3982, loss: 1.3982 +2025-05-29 05:50:58,124 - pyskl - INFO - Epoch [94][600/1281] lr: 7.785e-03, eta: 8:09:37, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 1.4937, loss: 1.4937 +2025-05-29 05:51:39,789 - pyskl - INFO - Epoch [94][700/1281] lr: 7.766e-03, eta: 8:08:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 1.4196, loss: 1.4196 +2025-05-29 05:52:21,444 - pyskl - INFO - Epoch [94][800/1281] lr: 7.747e-03, eta: 8:08:17, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 1.4228, loss: 1.4228 +2025-05-29 05:53:03,232 - pyskl - INFO - Epoch [94][900/1281] lr: 7.728e-03, eta: 8:07:37, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 1.4481, loss: 1.4481 +2025-05-29 05:53:45,109 - pyskl - INFO - Epoch [94][1000/1281] lr: 7.709e-03, eta: 8:06:58, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9750, top5_acc: 0.9994, loss_cls: 1.4347, loss: 1.4347 +2025-05-29 05:54:26,977 - pyskl - INFO - Epoch [94][1100/1281] lr: 7.690e-03, eta: 8:06:18, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 1.4577, loss: 1.4577 +2025-05-29 05:55:09,621 - pyskl - INFO - Epoch [94][1200/1281] lr: 7.672e-03, eta: 8:05:38, time: 0.426, data_time: 0.000, memory: 9000, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 1.4463, loss: 1.4463 +2025-05-29 05:55:44,104 - pyskl - INFO - Saving checkpoint at 94 epochs +2025-05-29 05:56:24,792 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 05:56:24,848 - pyskl - INFO - +top1_acc 0.9194 +top5_acc 0.9952 +2025-05-29 05:56:24,849 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 05:56:24,855 - pyskl - INFO - +mean_acc 0.8895 +2025-05-29 05:56:24,913 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_89.pth was removed +2025-05-29 05:56:26,400 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_94.pth. +2025-05-29 05:56:26,400 - pyskl - INFO - Best top1_acc is 0.9194 at 94 epoch. +2025-05-29 05:56:26,404 - pyskl - INFO - Epoch(val) [94][533] top1_acc: 0.9194, top5_acc: 0.9952, mean_class_accuracy: 0.8895 +2025-05-29 05:57:25,868 - pyskl - INFO - Epoch [95][100/1281] lr: 7.637e-03, eta: 8:04:17, time: 0.595, data_time: 0.176, memory: 9000, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 1.4050, loss: 1.4050 +2025-05-29 05:58:07,618 - pyskl - INFO - Epoch [95][200/1281] lr: 7.619e-03, eta: 8:03:37, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.3245, loss: 1.3245 +2025-05-29 05:58:49,394 - pyskl - INFO - Epoch [95][300/1281] lr: 7.600e-03, eta: 8:02:57, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 1.3660, loss: 1.3660 +2025-05-29 05:59:31,205 - pyskl - INFO - Epoch [95][400/1281] lr: 7.581e-03, eta: 8:02:17, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 1.3351, loss: 1.3351 +2025-05-29 06:00:12,946 - pyskl - INFO - Epoch [95][500/1281] lr: 7.562e-03, eta: 8:01:37, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 1.3457, loss: 1.3457 +2025-05-29 06:00:54,619 - pyskl - INFO - Epoch [95][600/1281] lr: 7.543e-03, eta: 8:00:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 1.3606, loss: 1.3606 +2025-05-29 06:01:36,360 - pyskl - INFO - Epoch [95][700/1281] lr: 7.525e-03, eta: 8:00:18, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 1.4870, loss: 1.4870 +2025-05-29 06:02:18,025 - pyskl - INFO - Epoch [95][800/1281] lr: 7.506e-03, eta: 7:59:38, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 1.3987, loss: 1.3987 +2025-05-29 06:02:59,728 - pyskl - INFO - Epoch [95][900/1281] lr: 7.487e-03, eta: 7:58:58, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9762, top5_acc: 0.9994, loss_cls: 1.4664, loss: 1.4664 +2025-05-29 06:03:41,423 - pyskl - INFO - Epoch [95][1000/1281] lr: 7.468e-03, eta: 7:58:18, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 1.4138, loss: 1.4138 +2025-05-29 06:04:23,248 - pyskl - INFO - Epoch [95][1100/1281] lr: 7.450e-03, eta: 7:57:38, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 1.4005, loss: 1.4005 +2025-05-29 06:05:05,353 - pyskl - INFO - Epoch [95][1200/1281] lr: 7.431e-03, eta: 7:56:58, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9706, top5_acc: 0.9994, loss_cls: 1.4916, loss: 1.4916 +2025-05-29 06:05:40,027 - pyskl - INFO - Saving checkpoint at 95 epochs +2025-05-29 06:19:20,158 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 06:19:20,215 - pyskl - INFO - +top1_acc 0.9107 +top5_acc 0.9958 +2025-05-29 06:19:20,216 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 06:19:20,223 - pyskl - INFO - +mean_acc 0.8903 +2025-05-29 06:19:20,226 - pyskl - INFO - Epoch(val) [95][533] top1_acc: 0.9107, top5_acc: 0.9958, mean_class_accuracy: 0.8903 +2025-05-29 06:20:19,802 - pyskl - INFO - Epoch [96][100/1281] lr: 7.397e-03, eta: 7:55:37, time: 0.596, data_time: 0.178, memory: 9000, top1_acc: 0.9775, top5_acc: 0.9994, loss_cls: 1.4679, loss: 1.4679 +2025-05-29 06:21:01,395 - pyskl - INFO - Epoch [96][200/1281] lr: 7.379e-03, eta: 7:54:57, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 1.4420, loss: 1.4420 +2025-05-29 06:21:42,985 - pyskl - INFO - Epoch [96][300/1281] lr: 7.360e-03, eta: 7:54:17, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.3792, loss: 1.3792 +2025-05-29 06:22:24,644 - pyskl - INFO - Epoch [96][400/1281] lr: 7.341e-03, eta: 7:53:37, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 1.3413, loss: 1.3413 +2025-05-29 06:23:06,335 - pyskl - INFO - Epoch [96][500/1281] lr: 7.323e-03, eta: 7:52:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 1.3813, loss: 1.3813 +2025-05-29 06:23:48,048 - pyskl - INFO - Epoch [96][600/1281] lr: 7.304e-03, eta: 7:52:17, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9850, top5_acc: 0.9994, loss_cls: 1.3163, loss: 1.3163 +2025-05-29 06:24:29,966 - pyskl - INFO - Epoch [96][700/1281] lr: 7.286e-03, eta: 7:51:37, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 1.4125, loss: 1.4125 +2025-05-29 06:25:11,784 - pyskl - INFO - Epoch [96][800/1281] lr: 7.267e-03, eta: 7:50:57, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 1.4211, loss: 1.4211 +2025-05-29 06:25:53,476 - pyskl - INFO - Epoch [96][900/1281] lr: 7.249e-03, eta: 7:50:18, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 1.4089, loss: 1.4089 +2025-05-29 06:26:35,115 - pyskl - INFO - Epoch [96][1000/1281] lr: 7.230e-03, eta: 7:49:38, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 1.4172, loss: 1.4172 +2025-05-29 06:27:16,994 - pyskl - INFO - Epoch [96][1100/1281] lr: 7.211e-03, eta: 7:48:58, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 1.4166, loss: 1.4166 +2025-05-29 06:27:58,766 - pyskl - INFO - Epoch [96][1200/1281] lr: 7.193e-03, eta: 7:48:18, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 1.4391, loss: 1.4391 +2025-05-29 06:28:32,994 - pyskl - INFO - Saving checkpoint at 96 epochs +2025-05-29 06:29:14,213 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 06:29:14,268 - pyskl - INFO - +top1_acc 0.9181 +top5_acc 0.9954 +2025-05-29 06:29:14,268 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 06:29:14,275 - pyskl - INFO - +mean_acc 0.8979 +2025-05-29 06:29:14,277 - pyskl - INFO - Epoch(val) [96][533] top1_acc: 0.9181, top5_acc: 0.9954, mean_class_accuracy: 0.8979 +2025-05-29 06:30:13,613 - pyskl - INFO - Epoch [97][100/1281] lr: 7.159e-03, eta: 7:46:56, time: 0.593, data_time: 0.177, memory: 9000, top1_acc: 0.9769, top5_acc: 0.9994, loss_cls: 1.4124, loss: 1.4124 +2025-05-29 06:30:55,199 - pyskl - INFO - Epoch [97][200/1281] lr: 7.141e-03, eta: 7:46:16, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 1.3820, loss: 1.3820 +2025-05-29 06:31:36,888 - pyskl - INFO - Epoch [97][300/1281] lr: 7.123e-03, eta: 7:45:37, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.3735, loss: 1.3735 +2025-05-29 06:32:18,574 - pyskl - INFO - Epoch [97][400/1281] lr: 7.104e-03, eta: 7:44:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 1.3236, loss: 1.3236 +2025-05-29 06:33:00,226 - pyskl - INFO - Epoch [97][500/1281] lr: 7.086e-03, eta: 7:44:17, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 1.4603, loss: 1.4603 +2025-05-29 06:33:41,853 - pyskl - INFO - Epoch [97][600/1281] lr: 7.067e-03, eta: 7:43:37, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 1.3831, loss: 1.3831 +2025-05-29 06:34:23,388 - pyskl - INFO - Epoch [97][700/1281] lr: 7.049e-03, eta: 7:42:57, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 1.4069, loss: 1.4069 +2025-05-29 06:35:04,971 - pyskl - INFO - Epoch [97][800/1281] lr: 7.030e-03, eta: 7:42:17, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 1.3855, loss: 1.3855 +2025-05-29 06:35:46,611 - pyskl - INFO - Epoch [97][900/1281] lr: 7.012e-03, eta: 7:41:37, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 1.3895, loss: 1.3895 +2025-05-29 06:36:28,304 - pyskl - INFO - Epoch [97][1000/1281] lr: 6.994e-03, eta: 7:40:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 1.3825, loss: 1.3825 +2025-05-29 06:37:10,205 - pyskl - INFO - Epoch [97][1100/1281] lr: 6.975e-03, eta: 7:40:17, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 1.4387, loss: 1.4387 +2025-05-29 06:37:52,084 - pyskl - INFO - Epoch [97][1200/1281] lr: 6.957e-03, eta: 7:39:37, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9744, top5_acc: 0.9994, loss_cls: 1.3795, loss: 1.3795 +2025-05-29 06:38:27,155 - pyskl - INFO - Saving checkpoint at 97 epochs +2025-05-29 06:39:08,336 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 06:39:08,392 - pyskl - INFO - +top1_acc 0.9200 +top5_acc 0.9946 +2025-05-29 06:39:08,393 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 06:39:08,400 - pyskl - INFO - +mean_acc 0.8886 +2025-05-29 06:39:08,457 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_94.pth was removed +2025-05-29 06:39:09,999 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_97.pth. +2025-05-29 06:39:10,000 - pyskl - INFO - Best top1_acc is 0.9200 at 97 epoch. +2025-05-29 06:39:10,006 - pyskl - INFO - Epoch(val) [97][533] top1_acc: 0.9200, top5_acc: 0.9946, mean_class_accuracy: 0.8886 +2025-05-29 06:40:09,072 - pyskl - INFO - Epoch [98][100/1281] lr: 6.924e-03, eta: 7:38:16, time: 0.591, data_time: 0.173, memory: 9000, top1_acc: 0.9812, top5_acc: 0.9994, loss_cls: 1.3550, loss: 1.3550 +2025-05-29 06:40:50,762 - pyskl - INFO - Epoch [98][200/1281] lr: 6.906e-03, eta: 7:37:36, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 1.3416, loss: 1.3416 +2025-05-29 06:41:32,399 - pyskl - INFO - Epoch [98][300/1281] lr: 6.887e-03, eta: 7:36:56, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 0.9994, loss_cls: 1.4217, loss: 1.4217 +2025-05-29 06:42:14,015 - pyskl - INFO - Epoch [98][400/1281] lr: 6.869e-03, eta: 7:36:16, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 1.3837, loss: 1.3837 +2025-05-29 06:42:55,662 - pyskl - INFO - Epoch [98][500/1281] lr: 6.851e-03, eta: 7:35:36, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 1.3686, loss: 1.3686 +2025-05-29 06:43:37,240 - pyskl - INFO - Epoch [98][600/1281] lr: 6.833e-03, eta: 7:34:56, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9862, top5_acc: 0.9994, loss_cls: 1.3157, loss: 1.3157 +2025-05-29 06:44:19,007 - pyskl - INFO - Epoch [98][700/1281] lr: 6.814e-03, eta: 7:34:16, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9844, top5_acc: 0.9994, loss_cls: 1.3447, loss: 1.3447 +2025-05-29 06:45:00,967 - pyskl - INFO - Epoch [98][800/1281] lr: 6.796e-03, eta: 7:33:36, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 1.2655, loss: 1.2655 +2025-05-29 06:45:42,633 - pyskl - INFO - Epoch [98][900/1281] lr: 6.778e-03, eta: 7:32:56, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 1.3347, loss: 1.3347 +2025-05-29 06:46:24,281 - pyskl - INFO - Epoch [98][1000/1281] lr: 6.760e-03, eta: 7:32:16, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 1.3823, loss: 1.3823 +2025-05-29 06:47:06,031 - pyskl - INFO - Epoch [98][1100/1281] lr: 6.742e-03, eta: 7:31:36, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 1.3791, loss: 1.3791 +2025-05-29 06:47:47,761 - pyskl - INFO - Epoch [98][1200/1281] lr: 6.724e-03, eta: 7:30:56, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 1.3175, loss: 1.3175 +2025-05-29 06:48:22,386 - pyskl - INFO - Saving checkpoint at 98 epochs +2025-05-29 06:49:03,214 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 06:49:03,270 - pyskl - INFO - +top1_acc 0.9136 +top5_acc 0.9962 +2025-05-29 06:49:03,270 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 06:49:03,277 - pyskl - INFO - +mean_acc 0.8938 +2025-05-29 06:49:03,279 - pyskl - INFO - Epoch(val) [98][533] top1_acc: 0.9136, top5_acc: 0.9962, mean_class_accuracy: 0.8938 +2025-05-29 06:50:02,807 - pyskl - INFO - Epoch [99][100/1281] lr: 6.691e-03, eta: 7:29:35, time: 0.595, data_time: 0.179, memory: 9000, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 1.3768, loss: 1.3768 +2025-05-29 06:50:44,437 - pyskl - INFO - Epoch [99][200/1281] lr: 6.673e-03, eta: 7:28:55, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 1.4020, loss: 1.4020 +2025-05-29 06:51:26,060 - pyskl - INFO - Epoch [99][300/1281] lr: 6.655e-03, eta: 7:28:15, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 1.4251, loss: 1.4251 +2025-05-29 06:52:07,633 - pyskl - INFO - Epoch [99][400/1281] lr: 6.637e-03, eta: 7:27:35, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 1.3922, loss: 1.3922 +2025-05-29 06:52:49,295 - pyskl - INFO - Epoch [99][500/1281] lr: 6.619e-03, eta: 7:26:55, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 1.2929, loss: 1.2929 +2025-05-29 06:53:30,861 - pyskl - INFO - Epoch [99][600/1281] lr: 6.601e-03, eta: 7:26:15, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 1.3296, loss: 1.3296 +2025-05-29 06:54:12,723 - pyskl - INFO - Epoch [99][700/1281] lr: 6.583e-03, eta: 7:25:36, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 1.3613, loss: 1.3613 +2025-05-29 06:54:54,480 - pyskl - INFO - Epoch [99][800/1281] lr: 6.565e-03, eta: 7:24:56, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 1.3429, loss: 1.3429 +2025-05-29 06:55:36,179 - pyskl - INFO - Epoch [99][900/1281] lr: 6.547e-03, eta: 7:24:16, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 1.3226, loss: 1.3226 +2025-05-29 06:56:17,857 - pyskl - INFO - Epoch [99][1000/1281] lr: 6.529e-03, eta: 7:23:36, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 1.3354, loss: 1.3354 +2025-05-29 06:56:59,625 - pyskl - INFO - Epoch [99][1100/1281] lr: 6.511e-03, eta: 7:22:56, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 1.3171, loss: 1.3171 +2025-05-29 06:57:41,328 - pyskl - INFO - Epoch [99][1200/1281] lr: 6.493e-03, eta: 7:22:16, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 1.4381, loss: 1.4381 +2025-05-29 06:58:15,570 - pyskl - INFO - Saving checkpoint at 99 epochs +2025-05-29 06:58:56,640 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 06:58:56,698 - pyskl - INFO - +top1_acc 0.9025 +top5_acc 0.9953 +2025-05-29 06:58:56,698 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 06:58:56,705 - pyskl - INFO - +mean_acc 0.8776 +2025-05-29 06:58:56,707 - pyskl - INFO - Epoch(val) [99][533] top1_acc: 0.9025, top5_acc: 0.9953, mean_class_accuracy: 0.8776 +2025-05-29 06:59:56,629 - pyskl - INFO - Epoch [100][100/1281] lr: 6.460e-03, eta: 7:20:55, time: 0.599, data_time: 0.181, memory: 9000, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 1.3411, loss: 1.3411 +2025-05-29 07:00:39,074 - pyskl - INFO - Epoch [100][200/1281] lr: 6.442e-03, eta: 7:20:16, time: 0.424, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 1.3604, loss: 1.3604 +2025-05-29 07:01:20,949 - pyskl - INFO - Epoch [100][300/1281] lr: 6.425e-03, eta: 7:19:36, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 1.2825, loss: 1.2825 +2025-05-29 07:02:02,763 - pyskl - INFO - Epoch [100][400/1281] lr: 6.407e-03, eta: 7:18:56, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.3513, loss: 1.3513 +2025-05-29 07:02:44,473 - pyskl - INFO - Epoch [100][500/1281] lr: 6.389e-03, eta: 7:18:16, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.2718, loss: 1.2718 +2025-05-29 07:03:26,173 - pyskl - INFO - Epoch [100][600/1281] lr: 6.371e-03, eta: 7:17:36, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.2874, loss: 1.2874 +2025-05-29 07:04:07,887 - pyskl - INFO - Epoch [100][700/1281] lr: 6.353e-03, eta: 7:16:56, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9825, top5_acc: 0.9994, loss_cls: 1.3588, loss: 1.3588 +2025-05-29 07:04:49,625 - pyskl - INFO - Epoch [100][800/1281] lr: 6.336e-03, eta: 7:16:16, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 1.3418, loss: 1.3418 +2025-05-29 07:05:31,309 - pyskl - INFO - Epoch [100][900/1281] lr: 6.318e-03, eta: 7:15:36, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 1.3292, loss: 1.3292 +2025-05-29 07:06:13,093 - pyskl - INFO - Epoch [100][1000/1281] lr: 6.300e-03, eta: 7:14:56, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 1.3759, loss: 1.3759 +2025-05-29 07:06:54,817 - pyskl - INFO - Epoch [100][1100/1281] lr: 6.282e-03, eta: 7:14:16, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 1.4164, loss: 1.4164 +2025-05-29 07:07:36,473 - pyskl - INFO - Epoch [100][1200/1281] lr: 6.265e-03, eta: 7:13:36, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 1.3943, loss: 1.3943 +2025-05-29 07:08:10,783 - pyskl - INFO - Saving checkpoint at 100 epochs +2025-05-29 07:20:53,740 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 07:20:53,797 - pyskl - INFO - +top1_acc 0.9018 +top5_acc 0.9955 +2025-05-29 07:20:53,797 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 07:20:53,805 - pyskl - INFO - +mean_acc 0.8801 +2025-05-29 07:20:53,807 - pyskl - INFO - Epoch(val) [100][533] top1_acc: 0.9018, top5_acc: 0.9955, mean_class_accuracy: 0.8801 +2025-05-29 07:21:53,370 - pyskl - INFO - Epoch [101][100/1281] lr: 6.232e-03, eta: 7:12:16, time: 0.596, data_time: 0.178, memory: 9000, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 1.3389, loss: 1.3389 +2025-05-29 07:22:36,187 - pyskl - INFO - Epoch [101][200/1281] lr: 6.215e-03, eta: 7:11:36, time: 0.428, data_time: 0.000, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.3031, loss: 1.3031 +2025-05-29 07:23:17,929 - pyskl - INFO - Epoch [101][300/1281] lr: 6.197e-03, eta: 7:10:56, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 1.2675, loss: 1.2675 +2025-05-29 07:23:59,599 - pyskl - INFO - Epoch [101][400/1281] lr: 6.180e-03, eta: 7:10:16, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.3322, loss: 1.3322 +2025-05-29 07:24:41,339 - pyskl - INFO - Epoch [101][500/1281] lr: 6.162e-03, eta: 7:09:36, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.2643, loss: 1.2643 +2025-05-29 07:25:23,107 - pyskl - INFO - Epoch [101][600/1281] lr: 6.144e-03, eta: 7:08:56, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 1.3436, loss: 1.3436 +2025-05-29 07:26:04,765 - pyskl - INFO - Epoch [101][700/1281] lr: 6.127e-03, eta: 7:08:16, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.3742, loss: 1.3742 +2025-05-29 07:26:46,512 - pyskl - INFO - Epoch [101][800/1281] lr: 6.109e-03, eta: 7:07:36, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 0.9994, loss_cls: 1.3687, loss: 1.3687 +2025-05-29 07:27:28,278 - pyskl - INFO - Epoch [101][900/1281] lr: 6.092e-03, eta: 7:06:56, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 1.3649, loss: 1.3649 +2025-05-29 07:28:09,883 - pyskl - INFO - Epoch [101][1000/1281] lr: 6.074e-03, eta: 7:06:16, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 1.3618, loss: 1.3618 +2025-05-29 07:28:51,638 - pyskl - INFO - Epoch [101][1100/1281] lr: 6.057e-03, eta: 7:05:36, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 1.3542, loss: 1.3542 +2025-05-29 07:29:33,406 - pyskl - INFO - Epoch [101][1200/1281] lr: 6.039e-03, eta: 7:04:56, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.3440, loss: 1.3440 +2025-05-29 07:30:07,825 - pyskl - INFO - Saving checkpoint at 101 epochs +2025-05-29 07:30:48,981 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 07:30:49,037 - pyskl - INFO - +top1_acc 0.9289 +top5_acc 0.9951 +2025-05-29 07:30:49,037 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 07:30:49,044 - pyskl - INFO - +mean_acc 0.9078 +2025-05-29 07:30:49,105 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_97.pth was removed +2025-05-29 07:30:50,820 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_101.pth. +2025-05-29 07:30:50,820 - pyskl - INFO - Best top1_acc is 0.9289 at 101 epoch. +2025-05-29 07:30:50,826 - pyskl - INFO - Epoch(val) [101][533] top1_acc: 0.9289, top5_acc: 0.9951, mean_class_accuracy: 0.9078 +2025-05-29 07:31:50,193 - pyskl - INFO - Epoch [102][100/1281] lr: 6.007e-03, eta: 7:03:36, time: 0.594, data_time: 0.177, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.3252, loss: 1.3252 +2025-05-29 07:32:31,933 - pyskl - INFO - Epoch [102][200/1281] lr: 5.990e-03, eta: 7:02:56, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.2440, loss: 1.2440 +2025-05-29 07:33:13,549 - pyskl - INFO - Epoch [102][300/1281] lr: 5.972e-03, eta: 7:02:16, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9844, top5_acc: 0.9994, loss_cls: 1.2404, loss: 1.2404 +2025-05-29 07:33:55,136 - pyskl - INFO - Epoch [102][400/1281] lr: 5.955e-03, eta: 7:01:36, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 1.2669, loss: 1.2669 +2025-05-29 07:34:36,796 - pyskl - INFO - Epoch [102][500/1281] lr: 5.938e-03, eta: 7:00:56, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.3070, loss: 1.3070 +2025-05-29 07:35:18,469 - pyskl - INFO - Epoch [102][600/1281] lr: 5.920e-03, eta: 7:00:16, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 1.3007, loss: 1.3007 +2025-05-29 07:36:00,147 - pyskl - INFO - Epoch [102][700/1281] lr: 5.903e-03, eta: 6:59:36, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 1.3158, loss: 1.3158 +2025-05-29 07:36:41,893 - pyskl - INFO - Epoch [102][800/1281] lr: 5.886e-03, eta: 6:58:56, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 1.3465, loss: 1.3465 +2025-05-29 07:37:23,644 - pyskl - INFO - Epoch [102][900/1281] lr: 5.868e-03, eta: 6:58:16, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 1.3590, loss: 1.3590 +2025-05-29 07:38:05,372 - pyskl - INFO - Epoch [102][1000/1281] lr: 5.851e-03, eta: 6:57:36, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.2983, loss: 1.2983 +2025-05-29 07:38:47,088 - pyskl - INFO - Epoch [102][1100/1281] lr: 5.834e-03, eta: 6:56:56, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 1.3179, loss: 1.3179 +2025-05-29 07:39:28,840 - pyskl - INFO - Epoch [102][1200/1281] lr: 5.816e-03, eta: 6:56:16, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.3892, loss: 1.3892 +2025-05-29 07:40:03,115 - pyskl - INFO - Saving checkpoint at 102 epochs +2025-05-29 07:40:44,290 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 07:40:44,345 - pyskl - INFO - +top1_acc 0.9167 +top5_acc 0.9958 +2025-05-29 07:40:44,345 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 07:40:44,351 - pyskl - INFO - +mean_acc 0.8952 +2025-05-29 07:40:44,353 - pyskl - INFO - Epoch(val) [102][533] top1_acc: 0.9167, top5_acc: 0.9958, mean_class_accuracy: 0.8952 +2025-05-29 07:41:44,172 - pyskl - INFO - Epoch [103][100/1281] lr: 5.785e-03, eta: 6:54:56, time: 0.598, data_time: 0.180, memory: 9000, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 1.2336, loss: 1.2336 +2025-05-29 07:42:26,037 - pyskl - INFO - Epoch [103][200/1281] lr: 5.768e-03, eta: 6:54:16, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 1.2681, loss: 1.2681 +2025-05-29 07:43:07,898 - pyskl - INFO - Epoch [103][300/1281] lr: 5.751e-03, eta: 6:53:36, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.2504, loss: 1.2504 +2025-05-29 07:43:49,594 - pyskl - INFO - Epoch [103][400/1281] lr: 5.733e-03, eta: 6:52:56, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 1.2893, loss: 1.2893 +2025-05-29 07:44:32,297 - pyskl - INFO - Epoch [103][500/1281] lr: 5.716e-03, eta: 6:52:17, time: 0.427, data_time: 0.000, memory: 9000, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 1.3232, loss: 1.3232 +2025-05-29 07:45:13,939 - pyskl - INFO - Epoch [103][600/1281] lr: 5.699e-03, eta: 6:51:37, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.3031, loss: 1.3031 +2025-05-29 07:45:55,687 - pyskl - INFO - Epoch [103][700/1281] lr: 5.682e-03, eta: 6:50:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 0.9994, loss_cls: 1.2783, loss: 1.2783 +2025-05-29 07:46:37,611 - pyskl - INFO - Epoch [103][800/1281] lr: 5.665e-03, eta: 6:50:17, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.3311, loss: 1.3311 +2025-05-29 07:47:19,678 - pyskl - INFO - Epoch [103][900/1281] lr: 5.648e-03, eta: 6:49:37, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.2522, loss: 1.2522 +2025-05-29 07:48:01,372 - pyskl - INFO - Epoch [103][1000/1281] lr: 5.631e-03, eta: 6:48:57, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.2510, loss: 1.2510 +2025-05-29 07:48:43,244 - pyskl - INFO - Epoch [103][1100/1281] lr: 5.614e-03, eta: 6:48:17, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.2958, loss: 1.2958 +2025-05-29 07:49:25,086 - pyskl - INFO - Epoch [103][1200/1281] lr: 5.597e-03, eta: 6:47:37, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.3560, loss: 1.3560 +2025-05-29 07:49:59,598 - pyskl - INFO - Saving checkpoint at 103 epochs +2025-05-29 07:50:40,726 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 07:50:40,782 - pyskl - INFO - +top1_acc 0.9092 +top5_acc 0.9941 +2025-05-29 07:50:40,782 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 07:50:40,789 - pyskl - INFO - +mean_acc 0.8928 +2025-05-29 07:50:40,792 - pyskl - INFO - Epoch(val) [103][533] top1_acc: 0.9092, top5_acc: 0.9941, mean_class_accuracy: 0.8928 +2025-05-29 07:51:40,501 - pyskl - INFO - Epoch [104][100/1281] lr: 5.566e-03, eta: 6:46:17, time: 0.597, data_time: 0.179, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.2723, loss: 1.2723 +2025-05-29 07:52:23,779 - pyskl - INFO - Epoch [104][200/1281] lr: 5.549e-03, eta: 6:45:38, time: 0.433, data_time: 0.000, memory: 9000, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 1.2553, loss: 1.2553 +2025-05-29 07:53:06,344 - pyskl - INFO - Epoch [104][300/1281] lr: 5.532e-03, eta: 6:44:58, time: 0.426, data_time: 0.000, memory: 9000, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 1.2312, loss: 1.2312 +2025-05-29 07:53:48,206 - pyskl - INFO - Epoch [104][400/1281] lr: 5.515e-03, eta: 6:44:18, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.2657, loss: 1.2657 +2025-05-29 07:54:29,992 - pyskl - INFO - Epoch [104][500/1281] lr: 5.498e-03, eta: 6:43:38, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.2642, loss: 1.2642 +2025-05-29 07:55:11,849 - pyskl - INFO - Epoch [104][600/1281] lr: 5.481e-03, eta: 6:42:58, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 1.2875, loss: 1.2875 +2025-05-29 07:55:53,656 - pyskl - INFO - Epoch [104][700/1281] lr: 5.464e-03, eta: 6:42:18, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 1.2982, loss: 1.2982 +2025-05-29 07:56:35,573 - pyskl - INFO - Epoch [104][800/1281] lr: 5.447e-03, eta: 6:41:38, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 1.2982, loss: 1.2982 +2025-05-29 07:57:18,528 - pyskl - INFO - Epoch [104][900/1281] lr: 5.430e-03, eta: 6:40:59, time: 0.430, data_time: 0.000, memory: 9000, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 1.2755, loss: 1.2755 +2025-05-29 07:58:01,773 - pyskl - INFO - Epoch [104][1000/1281] lr: 5.413e-03, eta: 6:40:19, time: 0.432, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.2922, loss: 1.2922 +2025-05-29 07:58:44,556 - pyskl - INFO - Epoch [104][1100/1281] lr: 5.397e-03, eta: 6:39:40, time: 0.428, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.2950, loss: 1.2950 +2025-05-29 07:59:26,693 - pyskl - INFO - Epoch [104][1200/1281] lr: 5.380e-03, eta: 6:39:00, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.3053, loss: 1.3053 +2025-05-29 08:00:01,216 - pyskl - INFO - Saving checkpoint at 104 epochs +2025-05-29 08:00:42,249 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 08:00:42,304 - pyskl - INFO - +top1_acc 0.9136 +top5_acc 0.9959 +2025-05-29 08:00:42,304 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 08:00:42,311 - pyskl - INFO - +mean_acc 0.9002 +2025-05-29 08:00:42,314 - pyskl - INFO - Epoch(val) [104][533] top1_acc: 0.9136, top5_acc: 0.9959, mean_class_accuracy: 0.9002 +2025-05-29 08:01:41,633 - pyskl - INFO - Epoch [105][100/1281] lr: 5.349e-03, eta: 6:37:40, time: 0.593, data_time: 0.174, memory: 9000, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 1.2088, loss: 1.2088 +2025-05-29 08:02:23,388 - pyskl - INFO - Epoch [105][200/1281] lr: 5.333e-03, eta: 6:37:00, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.2728, loss: 1.2728 +2025-05-29 08:03:05,098 - pyskl - INFO - Epoch [105][300/1281] lr: 5.316e-03, eta: 6:36:20, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 1.2167, loss: 1.2167 +2025-05-29 08:03:46,740 - pyskl - INFO - Epoch [105][400/1281] lr: 5.299e-03, eta: 6:35:40, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.2581, loss: 1.2581 +2025-05-29 08:04:28,386 - pyskl - INFO - Epoch [105][500/1281] lr: 5.283e-03, eta: 6:35:00, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.3344, loss: 1.3344 +2025-05-29 08:05:10,186 - pyskl - INFO - Epoch [105][600/1281] lr: 5.266e-03, eta: 6:34:20, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 1.2992, loss: 1.2992 +2025-05-29 08:05:52,251 - pyskl - INFO - Epoch [105][700/1281] lr: 5.249e-03, eta: 6:33:40, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.2309, loss: 1.2309 +2025-05-29 08:06:34,514 - pyskl - INFO - Epoch [105][800/1281] lr: 5.233e-03, eta: 6:33:00, time: 0.423, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.2671, loss: 1.2671 +2025-05-29 08:07:16,546 - pyskl - INFO - Epoch [105][900/1281] lr: 5.216e-03, eta: 6:32:20, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.2848, loss: 1.2848 +2025-05-29 08:07:58,223 - pyskl - INFO - Epoch [105][1000/1281] lr: 5.199e-03, eta: 6:31:40, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.2633, loss: 1.2633 +2025-05-29 08:08:39,997 - pyskl - INFO - Epoch [105][1100/1281] lr: 5.183e-03, eta: 6:31:00, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.2425, loss: 1.2425 +2025-05-29 08:09:20,904 - pyskl - INFO - Epoch [105][1200/1281] lr: 5.166e-03, eta: 6:30:20, time: 0.409, data_time: 0.000, memory: 9000, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 1.2998, loss: 1.2998 +2025-05-29 08:09:54,527 - pyskl - INFO - Saving checkpoint at 105 epochs +2025-05-29 08:22:31,987 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 08:22:32,043 - pyskl - INFO - +top1_acc 0.9281 +top5_acc 0.9951 +2025-05-29 08:22:32,043 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 08:22:32,050 - pyskl - INFO - +mean_acc 0.9042 +2025-05-29 08:22:32,052 - pyskl - INFO - Epoch(val) [105][533] top1_acc: 0.9281, top5_acc: 0.9951, mean_class_accuracy: 0.9042 +2025-05-29 08:23:31,507 - pyskl - INFO - Epoch [106][100/1281] lr: 5.136e-03, eta: 6:29:00, time: 0.595, data_time: 0.177, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.2307, loss: 1.2307 +2025-05-29 08:24:13,280 - pyskl - INFO - Epoch [106][200/1281] lr: 5.120e-03, eta: 6:28:20, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 1.2114, loss: 1.2114 +2025-05-29 08:24:55,067 - pyskl - INFO - Epoch [106][300/1281] lr: 5.103e-03, eta: 6:27:40, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.1947, loss: 1.1947 +2025-05-29 08:25:36,899 - pyskl - INFO - Epoch [106][400/1281] lr: 5.087e-03, eta: 6:27:00, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 0.9994, loss_cls: 1.2979, loss: 1.2979 +2025-05-29 08:26:18,754 - pyskl - INFO - Epoch [106][500/1281] lr: 5.070e-03, eta: 6:26:20, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.2038, loss: 1.2038 +2025-05-29 08:27:00,723 - pyskl - INFO - Epoch [106][600/1281] lr: 5.054e-03, eta: 6:25:40, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.2518, loss: 1.2518 +2025-05-29 08:27:42,734 - pyskl - INFO - Epoch [106][700/1281] lr: 5.038e-03, eta: 6:25:00, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 1.2629, loss: 1.2629 +2025-05-29 08:28:25,316 - pyskl - INFO - Epoch [106][800/1281] lr: 5.021e-03, eta: 6:24:20, time: 0.426, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.3404, loss: 1.3404 +2025-05-29 08:29:07,443 - pyskl - INFO - Epoch [106][900/1281] lr: 5.005e-03, eta: 6:23:41, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.2515, loss: 1.2515 +2025-05-29 08:29:49,246 - pyskl - INFO - Epoch [106][1000/1281] lr: 4.988e-03, eta: 6:23:00, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.2530, loss: 1.2530 +2025-05-29 08:30:30,997 - pyskl - INFO - Epoch [106][1100/1281] lr: 4.972e-03, eta: 6:22:20, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 1.1933, loss: 1.1933 +2025-05-29 08:31:12,859 - pyskl - INFO - Epoch [106][1200/1281] lr: 4.956e-03, eta: 6:21:40, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 1.3113, loss: 1.3113 +2025-05-29 08:31:47,398 - pyskl - INFO - Saving checkpoint at 106 epochs +2025-05-29 08:32:28,305 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 08:32:28,361 - pyskl - INFO - +top1_acc 0.9285 +top5_acc 0.9953 +2025-05-29 08:32:28,361 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 08:32:28,368 - pyskl - INFO - +mean_acc 0.8988 +2025-05-29 08:32:28,370 - pyskl - INFO - Epoch(val) [106][533] top1_acc: 0.9285, top5_acc: 0.9953, mean_class_accuracy: 0.8988 +2025-05-29 08:33:27,587 - pyskl - INFO - Epoch [107][100/1281] lr: 4.926e-03, eta: 6:20:21, time: 0.592, data_time: 0.173, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.2433, loss: 1.2433 +2025-05-29 08:34:09,340 - pyskl - INFO - Epoch [107][200/1281] lr: 4.910e-03, eta: 6:19:41, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.1876, loss: 1.1876 +2025-05-29 08:34:51,048 - pyskl - INFO - Epoch [107][300/1281] lr: 4.894e-03, eta: 6:19:01, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.2176, loss: 1.2176 +2025-05-29 08:35:32,847 - pyskl - INFO - Epoch [107][400/1281] lr: 4.878e-03, eta: 6:18:21, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.2537, loss: 1.2537 +2025-05-29 08:36:14,740 - pyskl - INFO - Epoch [107][500/1281] lr: 4.862e-03, eta: 6:17:41, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.2206, loss: 1.2206 +2025-05-29 08:36:56,670 - pyskl - INFO - Epoch [107][600/1281] lr: 4.845e-03, eta: 6:17:01, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.2567, loss: 1.2567 +2025-05-29 08:37:38,563 - pyskl - INFO - Epoch [107][700/1281] lr: 4.829e-03, eta: 6:16:21, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 1.2980, loss: 1.2980 +2025-05-29 08:38:21,201 - pyskl - INFO - Epoch [107][800/1281] lr: 4.813e-03, eta: 6:15:41, time: 0.426, data_time: 0.000, memory: 9000, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 1.3187, loss: 1.3187 +2025-05-29 08:39:03,349 - pyskl - INFO - Epoch [107][900/1281] lr: 4.797e-03, eta: 6:15:01, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.2962, loss: 1.2962 +2025-05-29 08:39:45,244 - pyskl - INFO - Epoch [107][1000/1281] lr: 4.781e-03, eta: 6:14:21, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 1.3323, loss: 1.3323 +2025-05-29 08:40:27,111 - pyskl - INFO - Epoch [107][1100/1281] lr: 4.765e-03, eta: 6:13:41, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 1.3231, loss: 1.3231 +2025-05-29 08:41:09,212 - pyskl - INFO - Epoch [107][1200/1281] lr: 4.749e-03, eta: 6:13:01, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.2904, loss: 1.2904 +2025-05-29 08:41:43,728 - pyskl - INFO - Saving checkpoint at 107 epochs +2025-05-29 08:42:25,025 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 08:42:25,082 - pyskl - INFO - +top1_acc 0.9125 +top5_acc 0.9960 +2025-05-29 08:42:25,082 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 08:42:25,089 - pyskl - INFO - +mean_acc 0.9045 +2025-05-29 08:42:25,092 - pyskl - INFO - Epoch(val) [107][533] top1_acc: 0.9125, top5_acc: 0.9960, mean_class_accuracy: 0.9045 +2025-05-29 08:43:24,422 - pyskl - INFO - Epoch [108][100/1281] lr: 4.720e-03, eta: 6:11:42, time: 0.593, data_time: 0.176, memory: 9000, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 1.3701, loss: 1.3701 +2025-05-29 08:44:06,124 - pyskl - INFO - Epoch [108][200/1281] lr: 4.704e-03, eta: 6:11:02, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.2385, loss: 1.2385 +2025-05-29 08:44:47,833 - pyskl - INFO - Epoch [108][300/1281] lr: 4.688e-03, eta: 6:10:22, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 1.2358, loss: 1.2358 +2025-05-29 08:45:29,523 - pyskl - INFO - Epoch [108][400/1281] lr: 4.672e-03, eta: 6:09:42, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.2314, loss: 1.2314 +2025-05-29 08:46:11,174 - pyskl - INFO - Epoch [108][500/1281] lr: 4.656e-03, eta: 6:09:02, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 1.2492, loss: 1.2492 +2025-05-29 08:46:52,833 - pyskl - INFO - Epoch [108][600/1281] lr: 4.640e-03, eta: 6:08:21, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.1949, loss: 1.1949 +2025-05-29 08:47:34,803 - pyskl - INFO - Epoch [108][700/1281] lr: 4.624e-03, eta: 6:07:41, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 1.2759, loss: 1.2759 +2025-05-29 08:48:16,842 - pyskl - INFO - Epoch [108][800/1281] lr: 4.608e-03, eta: 6:07:01, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.2370, loss: 1.2370 +2025-05-29 08:48:58,565 - pyskl - INFO - Epoch [108][900/1281] lr: 4.593e-03, eta: 6:06:21, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.1804, loss: 1.1804 +2025-05-29 08:49:40,400 - pyskl - INFO - Epoch [108][1000/1281] lr: 4.577e-03, eta: 6:05:41, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 1.1883, loss: 1.1883 +2025-05-29 08:50:22,465 - pyskl - INFO - Epoch [108][1100/1281] lr: 4.561e-03, eta: 6:05:01, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.2337, loss: 1.2337 +2025-05-29 08:51:04,578 - pyskl - INFO - Epoch [108][1200/1281] lr: 4.545e-03, eta: 6:04:21, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.2401, loss: 1.2401 +2025-05-29 08:51:39,017 - pyskl - INFO - Saving checkpoint at 108 epochs +2025-05-29 08:52:20,226 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 08:52:20,282 - pyskl - INFO - +top1_acc 0.9005 +top5_acc 0.9948 +2025-05-29 08:52:20,282 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 08:52:20,289 - pyskl - INFO - +mean_acc 0.8848 +2025-05-29 08:52:20,291 - pyskl - INFO - Epoch(val) [108][533] top1_acc: 0.9005, top5_acc: 0.9948, mean_class_accuracy: 0.8848 +2025-05-29 08:53:19,621 - pyskl - INFO - Epoch [109][100/1281] lr: 4.517e-03, eta: 6:03:02, time: 0.593, data_time: 0.176, memory: 9000, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 1.2297, loss: 1.2297 +2025-05-29 08:54:01,388 - pyskl - INFO - Epoch [109][200/1281] lr: 4.501e-03, eta: 6:02:22, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.2263, loss: 1.2263 +2025-05-29 08:54:43,041 - pyskl - INFO - Epoch [109][300/1281] lr: 4.485e-03, eta: 6:01:42, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.2419, loss: 1.2419 +2025-05-29 08:55:24,741 - pyskl - INFO - Epoch [109][400/1281] lr: 4.470e-03, eta: 6:01:02, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.2960, loss: 1.2960 +2025-05-29 08:56:06,500 - pyskl - INFO - Epoch [109][500/1281] lr: 4.454e-03, eta: 6:00:22, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.1669, loss: 1.1669 +2025-05-29 08:56:48,243 - pyskl - INFO - Epoch [109][600/1281] lr: 4.438e-03, eta: 5:59:42, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.2589, loss: 1.2589 +2025-05-29 08:57:30,306 - pyskl - INFO - Epoch [109][700/1281] lr: 4.423e-03, eta: 5:59:02, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.2565, loss: 1.2565 +2025-05-29 08:58:12,253 - pyskl - INFO - Epoch [109][800/1281] lr: 4.407e-03, eta: 5:58:22, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.1589, loss: 1.1589 +2025-05-29 08:58:54,160 - pyskl - INFO - Epoch [109][900/1281] lr: 4.391e-03, eta: 5:57:42, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.2503, loss: 1.2503 +2025-05-29 08:59:35,959 - pyskl - INFO - Epoch [109][1000/1281] lr: 4.376e-03, eta: 5:57:02, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.2286, loss: 1.2286 +2025-05-29 09:00:17,705 - pyskl - INFO - Epoch [109][1100/1281] lr: 4.360e-03, eta: 5:56:21, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.2553, loss: 1.2553 +2025-05-29 09:00:59,739 - pyskl - INFO - Epoch [109][1200/1281] lr: 4.345e-03, eta: 5:55:41, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.2673, loss: 1.2673 +2025-05-29 09:01:34,463 - pyskl - INFO - Saving checkpoint at 109 epochs +2025-05-29 09:02:15,665 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 09:02:15,722 - pyskl - INFO - +top1_acc 0.9290 +top5_acc 0.9960 +2025-05-29 09:02:15,722 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 09:02:15,729 - pyskl - INFO - +mean_acc 0.9006 +2025-05-29 09:02:15,795 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_101.pth was removed +2025-05-29 09:02:17,323 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_109.pth. +2025-05-29 09:02:17,324 - pyskl - INFO - Best top1_acc is 0.9290 at 109 epoch. +2025-05-29 09:02:17,327 - pyskl - INFO - Epoch(val) [109][533] top1_acc: 0.9290, top5_acc: 0.9960, mean_class_accuracy: 0.9006 +2025-05-29 09:03:16,885 - pyskl - INFO - Epoch [110][100/1281] lr: 4.317e-03, eta: 5:54:23, time: 0.596, data_time: 0.176, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.2456, loss: 1.2456 +2025-05-29 09:03:58,673 - pyskl - INFO - Epoch [110][200/1281] lr: 4.301e-03, eta: 5:53:43, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 1.1772, loss: 1.1772 +2025-05-29 09:04:40,484 - pyskl - INFO - Epoch [110][300/1281] lr: 4.286e-03, eta: 5:53:03, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 1.1854, loss: 1.1854 +2025-05-29 09:05:22,287 - pyskl - INFO - Epoch [110][400/1281] lr: 4.271e-03, eta: 5:52:22, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.2076, loss: 1.2076 +2025-05-29 09:06:04,008 - pyskl - INFO - Epoch [110][500/1281] lr: 4.255e-03, eta: 5:51:42, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.2155, loss: 1.2155 +2025-05-29 09:06:45,752 - pyskl - INFO - Epoch [110][600/1281] lr: 4.240e-03, eta: 5:51:02, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.1530, loss: 1.1530 +2025-05-29 09:07:27,673 - pyskl - INFO - Epoch [110][700/1281] lr: 4.225e-03, eta: 5:50:22, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.1705, loss: 1.1705 +2025-05-29 09:08:09,218 - pyskl - INFO - Epoch [110][800/1281] lr: 4.209e-03, eta: 5:49:42, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 1.2645, loss: 1.2645 +2025-05-29 09:08:50,781 - pyskl - INFO - Epoch [110][900/1281] lr: 4.194e-03, eta: 5:49:02, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.1711, loss: 1.1711 +2025-05-29 09:09:32,367 - pyskl - INFO - Epoch [110][1000/1281] lr: 4.179e-03, eta: 5:48:21, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.2132, loss: 1.2132 +2025-05-29 09:10:13,974 - pyskl - INFO - Epoch [110][1100/1281] lr: 4.164e-03, eta: 5:47:41, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.2548, loss: 1.2548 +2025-05-29 09:10:55,551 - pyskl - INFO - Epoch [110][1200/1281] lr: 4.148e-03, eta: 5:47:01, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9900, top5_acc: 0.9994, loss_cls: 1.1956, loss: 1.1956 +2025-05-29 09:11:30,278 - pyskl - INFO - Saving checkpoint at 110 epochs +2025-05-29 09:24:05,219 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 09:24:05,283 - pyskl - INFO - +top1_acc 0.9217 +top5_acc 0.9951 +2025-05-29 09:24:05,283 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 09:24:05,292 - pyskl - INFO - +mean_acc 0.9041 +2025-05-29 09:24:05,296 - pyskl - INFO - Epoch(val) [110][533] top1_acc: 0.9217, top5_acc: 0.9951, mean_class_accuracy: 0.9041 +2025-05-29 09:25:05,145 - pyskl - INFO - Epoch [111][100/1281] lr: 4.121e-03, eta: 5:45:43, time: 0.598, data_time: 0.182, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.2114, loss: 1.2114 +2025-05-29 09:25:46,807 - pyskl - INFO - Epoch [111][200/1281] lr: 4.106e-03, eta: 5:45:03, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 0.9994, loss_cls: 1.2824, loss: 1.2824 +2025-05-29 09:26:28,545 - pyskl - INFO - Epoch [111][300/1281] lr: 4.091e-03, eta: 5:44:22, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 1.1897, loss: 1.1897 +2025-05-29 09:27:10,274 - pyskl - INFO - Epoch [111][400/1281] lr: 4.075e-03, eta: 5:43:42, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.2279, loss: 1.2279 +2025-05-29 09:27:51,976 - pyskl - INFO - Epoch [111][500/1281] lr: 4.060e-03, eta: 5:43:02, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.1653, loss: 1.1653 +2025-05-29 09:28:33,665 - pyskl - INFO - Epoch [111][600/1281] lr: 4.045e-03, eta: 5:42:22, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.2463, loss: 1.2463 +2025-05-29 09:29:15,359 - pyskl - INFO - Epoch [111][700/1281] lr: 4.030e-03, eta: 5:41:42, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.2937, loss: 1.2937 +2025-05-29 09:29:57,104 - pyskl - INFO - Epoch [111][800/1281] lr: 4.015e-03, eta: 5:41:02, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 1.1874, loss: 1.1874 +2025-05-29 09:30:39,159 - pyskl - INFO - Epoch [111][900/1281] lr: 4.000e-03, eta: 5:40:22, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 1.2516, loss: 1.2516 +2025-05-29 09:31:21,346 - pyskl - INFO - Epoch [111][1000/1281] lr: 3.985e-03, eta: 5:39:42, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.1789, loss: 1.1789 +2025-05-29 09:32:03,131 - pyskl - INFO - Epoch [111][1100/1281] lr: 3.970e-03, eta: 5:39:01, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.1927, loss: 1.1927 +2025-05-29 09:32:44,910 - pyskl - INFO - Epoch [111][1200/1281] lr: 3.955e-03, eta: 5:38:21, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 1.2027, loss: 1.2027 +2025-05-29 09:33:19,354 - pyskl - INFO - Saving checkpoint at 111 epochs +2025-05-29 09:34:00,885 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 09:34:00,943 - pyskl - INFO - +top1_acc 0.9262 +top5_acc 0.9967 +2025-05-29 09:34:00,943 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 09:34:00,950 - pyskl - INFO - +mean_acc 0.9013 +2025-05-29 09:34:00,953 - pyskl - INFO - Epoch(val) [111][533] top1_acc: 0.9262, top5_acc: 0.9967, mean_class_accuracy: 0.9013 +2025-05-29 09:35:01,220 - pyskl - INFO - Epoch [112][100/1281] lr: 3.928e-03, eta: 5:37:03, time: 0.603, data_time: 0.182, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.1413, loss: 1.1413 +2025-05-29 09:35:43,160 - pyskl - INFO - Epoch [112][200/1281] lr: 3.914e-03, eta: 5:36:23, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.1076, loss: 1.1076 +2025-05-29 09:36:24,989 - pyskl - INFO - Epoch [112][300/1281] lr: 3.899e-03, eta: 5:35:43, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 1.1584, loss: 1.1584 +2025-05-29 09:37:06,689 - pyskl - INFO - Epoch [112][400/1281] lr: 3.884e-03, eta: 5:35:03, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.1863, loss: 1.1863 +2025-05-29 09:37:48,365 - pyskl - INFO - Epoch [112][500/1281] lr: 3.869e-03, eta: 5:34:23, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.1405, loss: 1.1405 +2025-05-29 09:38:30,039 - pyskl - INFO - Epoch [112][600/1281] lr: 3.854e-03, eta: 5:33:43, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.1458, loss: 1.1458 +2025-05-29 09:39:11,738 - pyskl - INFO - Epoch [112][700/1281] lr: 3.840e-03, eta: 5:33:02, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.1433, loss: 1.1433 +2025-05-29 09:39:53,485 - pyskl - INFO - Epoch [112][800/1281] lr: 3.825e-03, eta: 5:32:22, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.2014, loss: 1.2014 +2025-05-29 09:40:36,096 - pyskl - INFO - Epoch [112][900/1281] lr: 3.810e-03, eta: 5:31:42, time: 0.426, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.1787, loss: 1.1787 +2025-05-29 09:41:18,157 - pyskl - INFO - Epoch [112][1000/1281] lr: 3.795e-03, eta: 5:31:02, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.1430, loss: 1.1430 +2025-05-29 09:41:59,934 - pyskl - INFO - Epoch [112][1100/1281] lr: 3.781e-03, eta: 5:30:22, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.1743, loss: 1.1743 +2025-05-29 09:42:41,717 - pyskl - INFO - Epoch [112][1200/1281] lr: 3.766e-03, eta: 5:29:42, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.1595, loss: 1.1595 +2025-05-29 09:43:16,069 - pyskl - INFO - Saving checkpoint at 112 epochs +2025-05-29 09:43:57,012 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 09:43:57,068 - pyskl - INFO - +top1_acc 0.9385 +top5_acc 0.9966 +2025-05-29 09:43:57,068 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 09:43:57,074 - pyskl - INFO - +mean_acc 0.9171 +2025-05-29 09:43:57,138 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_109.pth was removed +2025-05-29 09:43:58,812 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_112.pth. +2025-05-29 09:43:58,813 - pyskl - INFO - Best top1_acc is 0.9385 at 112 epoch. +2025-05-29 09:43:58,816 - pyskl - INFO - Epoch(val) [112][533] top1_acc: 0.9385, top5_acc: 0.9966, mean_class_accuracy: 0.9171 +2025-05-29 09:44:58,787 - pyskl - INFO - Epoch [113][100/1281] lr: 3.740e-03, eta: 5:28:24, time: 0.600, data_time: 0.180, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.1016, loss: 1.1016 +2025-05-29 09:45:40,552 - pyskl - INFO - Epoch [113][200/1281] lr: 3.725e-03, eta: 5:27:44, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.0927, loss: 1.0927 +2025-05-29 09:46:22,316 - pyskl - INFO - Epoch [113][300/1281] lr: 3.711e-03, eta: 5:27:04, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.1139, loss: 1.1139 +2025-05-29 09:47:04,109 - pyskl - INFO - Epoch [113][400/1281] lr: 3.696e-03, eta: 5:26:24, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.1274, loss: 1.1274 +2025-05-29 09:47:45,908 - pyskl - INFO - Epoch [113][500/1281] lr: 3.682e-03, eta: 5:25:43, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.1624, loss: 1.1624 +2025-05-29 09:48:27,791 - pyskl - INFO - Epoch [113][600/1281] lr: 3.667e-03, eta: 5:25:03, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.1568, loss: 1.1568 +2025-05-29 09:49:09,544 - pyskl - INFO - Epoch [113][700/1281] lr: 3.653e-03, eta: 5:24:23, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.1513, loss: 1.1513 +2025-05-29 09:49:51,376 - pyskl - INFO - Epoch [113][800/1281] lr: 3.638e-03, eta: 5:23:43, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 1.1498, loss: 1.1498 +2025-05-29 09:50:33,541 - pyskl - INFO - Epoch [113][900/1281] lr: 3.624e-03, eta: 5:23:03, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.1178, loss: 1.1178 +2025-05-29 09:51:15,577 - pyskl - INFO - Epoch [113][1000/1281] lr: 3.610e-03, eta: 5:22:23, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.1564, loss: 1.1564 +2025-05-29 09:51:57,395 - pyskl - INFO - Epoch [113][1100/1281] lr: 3.595e-03, eta: 5:21:43, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 1.1631, loss: 1.1631 +2025-05-29 09:52:39,226 - pyskl - INFO - Epoch [113][1200/1281] lr: 3.581e-03, eta: 5:21:02, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 1.1873, loss: 1.1873 +2025-05-29 09:53:13,635 - pyskl - INFO - Saving checkpoint at 113 epochs +2025-05-29 09:53:54,362 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 09:53:54,418 - pyskl - INFO - +top1_acc 0.9279 +top5_acc 0.9957 +2025-05-29 09:53:54,418 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 09:53:54,425 - pyskl - INFO - +mean_acc 0.9051 +2025-05-29 09:53:54,427 - pyskl - INFO - Epoch(val) [113][533] top1_acc: 0.9279, top5_acc: 0.9957, mean_class_accuracy: 0.9051 +2025-05-29 09:54:53,871 - pyskl - INFO - Epoch [114][100/1281] lr: 3.555e-03, eta: 5:19:44, time: 0.594, data_time: 0.180, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.1740, loss: 1.1740 +2025-05-29 09:55:35,403 - pyskl - INFO - Epoch [114][200/1281] lr: 3.541e-03, eta: 5:19:04, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.1297, loss: 1.1297 +2025-05-29 09:56:17,508 - pyskl - INFO - Epoch [114][300/1281] lr: 3.526e-03, eta: 5:18:24, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.1226, loss: 1.1226 +2025-05-29 09:56:59,401 - pyskl - INFO - Epoch [114][400/1281] lr: 3.512e-03, eta: 5:17:44, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0593, loss: 1.0593 +2025-05-29 09:57:41,248 - pyskl - INFO - Epoch [114][500/1281] lr: 3.498e-03, eta: 5:17:04, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.1618, loss: 1.1618 +2025-05-29 09:58:23,081 - pyskl - INFO - Epoch [114][600/1281] lr: 3.484e-03, eta: 5:16:24, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.1595, loss: 1.1595 +2025-05-29 09:59:04,921 - pyskl - INFO - Epoch [114][700/1281] lr: 3.470e-03, eta: 5:15:44, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.1304, loss: 1.1304 +2025-05-29 09:59:47,163 - pyskl - INFO - Epoch [114][800/1281] lr: 3.456e-03, eta: 5:15:04, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 1.1891, loss: 1.1891 +2025-05-29 10:00:29,172 - pyskl - INFO - Epoch [114][900/1281] lr: 3.442e-03, eta: 5:14:23, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.2247, loss: 1.2247 +2025-05-29 10:01:10,967 - pyskl - INFO - Epoch [114][1000/1281] lr: 3.427e-03, eta: 5:13:43, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.1913, loss: 1.1913 +2025-05-29 10:01:52,654 - pyskl - INFO - Epoch [114][1100/1281] lr: 3.413e-03, eta: 5:13:03, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.1639, loss: 1.1639 +2025-05-29 10:02:34,337 - pyskl - INFO - Epoch [114][1200/1281] lr: 3.399e-03, eta: 5:12:23, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 1.1810, loss: 1.1810 +2025-05-29 10:03:08,619 - pyskl - INFO - Saving checkpoint at 114 epochs +2025-05-29 10:03:49,569 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 10:03:49,626 - pyskl - INFO - +top1_acc 0.9383 +top5_acc 0.9960 +2025-05-29 10:03:49,626 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 10:03:49,633 - pyskl - INFO - +mean_acc 0.9143 +2025-05-29 10:03:49,635 - pyskl - INFO - Epoch(val) [114][533] top1_acc: 0.9383, top5_acc: 0.9960, mean_class_accuracy: 0.9143 +2025-05-29 10:04:49,127 - pyskl - INFO - Epoch [115][100/1281] lr: 3.374e-03, eta: 5:11:05, time: 0.595, data_time: 0.176, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.1346, loss: 1.1346 +2025-05-29 10:05:30,754 - pyskl - INFO - Epoch [115][200/1281] lr: 3.360e-03, eta: 5:10:25, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0605, loss: 1.0605 +2025-05-29 10:06:12,394 - pyskl - INFO - Epoch [115][300/1281] lr: 3.346e-03, eta: 5:09:44, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.1356, loss: 1.1356 +2025-05-29 10:06:54,016 - pyskl - INFO - Epoch [115][400/1281] lr: 3.332e-03, eta: 5:09:04, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 1.1078, loss: 1.1078 +2025-05-29 10:07:35,749 - pyskl - INFO - Epoch [115][500/1281] lr: 3.318e-03, eta: 5:08:24, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.0965, loss: 1.0965 +2025-05-29 10:08:17,479 - pyskl - INFO - Epoch [115][600/1281] lr: 3.305e-03, eta: 5:07:44, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.1624, loss: 1.1624 +2025-05-29 10:08:59,288 - pyskl - INFO - Epoch [115][700/1281] lr: 3.291e-03, eta: 5:07:04, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.1707, loss: 1.1707 +2025-05-29 10:09:41,071 - pyskl - INFO - Epoch [115][800/1281] lr: 3.277e-03, eta: 5:06:23, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.1320, loss: 1.1320 +2025-05-29 10:10:22,721 - pyskl - INFO - Epoch [115][900/1281] lr: 3.263e-03, eta: 5:05:43, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 0.9994, loss_cls: 1.1828, loss: 1.1828 +2025-05-29 10:11:04,253 - pyskl - INFO - Epoch [115][1000/1281] lr: 3.249e-03, eta: 5:05:03, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.1518, loss: 1.1518 +2025-05-29 10:11:45,850 - pyskl - INFO - Epoch [115][1100/1281] lr: 3.236e-03, eta: 5:04:23, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.1169, loss: 1.1169 +2025-05-29 10:12:27,467 - pyskl - INFO - Epoch [115][1200/1281] lr: 3.222e-03, eta: 5:03:42, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.1000, loss: 1.1000 +2025-05-29 10:13:01,630 - pyskl - INFO - Saving checkpoint at 115 epochs +2025-05-29 10:25:46,176 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 10:25:46,233 - pyskl - INFO - +top1_acc 0.9404 +top5_acc 0.9966 +2025-05-29 10:25:46,233 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 10:25:46,240 - pyskl - INFO - +mean_acc 0.9150 +2025-05-29 10:25:46,305 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_112.pth was removed +2025-05-29 10:25:47,845 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_115.pth. +2025-05-29 10:25:47,846 - pyskl - INFO - Best top1_acc is 0.9404 at 115 epoch. +2025-05-29 10:25:47,850 - pyskl - INFO - Epoch(val) [115][533] top1_acc: 0.9404, top5_acc: 0.9966, mean_class_accuracy: 0.9150 +2025-05-29 10:26:47,109 - pyskl - INFO - Epoch [116][100/1281] lr: 3.197e-03, eta: 5:02:25, time: 0.593, data_time: 0.173, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.1329, loss: 1.1329 +2025-05-29 10:27:28,867 - pyskl - INFO - Epoch [116][200/1281] lr: 3.184e-03, eta: 5:01:45, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.0786, loss: 1.0786 +2025-05-29 10:28:10,681 - pyskl - INFO - Epoch [116][300/1281] lr: 3.170e-03, eta: 5:01:04, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.1082, loss: 1.1082 +2025-05-29 10:28:52,502 - pyskl - INFO - Epoch [116][400/1281] lr: 3.156e-03, eta: 5:00:24, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.0828, loss: 1.0828 +2025-05-29 10:29:34,251 - pyskl - INFO - Epoch [116][500/1281] lr: 3.143e-03, eta: 4:59:44, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0693, loss: 1.0693 +2025-05-29 10:30:16,194 - pyskl - INFO - Epoch [116][600/1281] lr: 3.129e-03, eta: 4:59:04, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.1013, loss: 1.1013 +2025-05-29 10:30:57,900 - pyskl - INFO - Epoch [116][700/1281] lr: 3.116e-03, eta: 4:58:24, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.1335, loss: 1.1335 +2025-05-29 10:31:40,085 - pyskl - INFO - Epoch [116][800/1281] lr: 3.102e-03, eta: 4:57:43, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.1056, loss: 1.1056 +2025-05-29 10:32:22,019 - pyskl - INFO - Epoch [116][900/1281] lr: 3.089e-03, eta: 4:57:03, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.1139, loss: 1.1139 +2025-05-29 10:33:03,856 - pyskl - INFO - Epoch [116][1000/1281] lr: 3.075e-03, eta: 4:56:23, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.1131, loss: 1.1131 +2025-05-29 10:33:45,554 - pyskl - INFO - Epoch [116][1100/1281] lr: 3.062e-03, eta: 4:55:43, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 1.1167, loss: 1.1167 +2025-05-29 10:34:27,267 - pyskl - INFO - Epoch [116][1200/1281] lr: 3.049e-03, eta: 4:55:03, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.0527, loss: 1.0527 +2025-05-29 10:35:01,595 - pyskl - INFO - Saving checkpoint at 116 epochs +2025-05-29 10:35:42,454 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 10:35:42,511 - pyskl - INFO - +top1_acc 0.9345 +top5_acc 0.9968 +2025-05-29 10:35:42,511 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 10:35:42,518 - pyskl - INFO - +mean_acc 0.9132 +2025-05-29 10:35:42,520 - pyskl - INFO - Epoch(val) [116][533] top1_acc: 0.9345, top5_acc: 0.9968, mean_class_accuracy: 0.9132 +2025-05-29 10:36:41,884 - pyskl - INFO - Epoch [117][100/1281] lr: 3.024e-03, eta: 4:53:45, time: 0.594, data_time: 0.175, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.0555, loss: 1.0555 +2025-05-29 10:37:23,809 - pyskl - INFO - Epoch [117][200/1281] lr: 3.011e-03, eta: 4:53:05, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0686, loss: 1.0686 +2025-05-29 10:38:05,495 - pyskl - INFO - Epoch [117][300/1281] lr: 2.998e-03, eta: 4:52:25, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.1043, loss: 1.1043 +2025-05-29 10:38:47,204 - pyskl - INFO - Epoch [117][400/1281] lr: 2.984e-03, eta: 4:51:44, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.0609, loss: 1.0609 +2025-05-29 10:39:29,193 - pyskl - INFO - Epoch [117][500/1281] lr: 2.971e-03, eta: 4:51:04, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.0822, loss: 1.0822 +2025-05-29 10:40:11,263 - pyskl - INFO - Epoch [117][600/1281] lr: 2.958e-03, eta: 4:50:24, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.0871, loss: 1.0871 +2025-05-29 10:40:52,997 - pyskl - INFO - Epoch [117][700/1281] lr: 2.945e-03, eta: 4:49:44, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.1049, loss: 1.1049 +2025-05-29 10:41:34,870 - pyskl - INFO - Epoch [117][800/1281] lr: 2.932e-03, eta: 4:49:04, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.0711, loss: 1.0711 +2025-05-29 10:42:16,915 - pyskl - INFO - Epoch [117][900/1281] lr: 2.919e-03, eta: 4:48:24, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 1.0906, loss: 1.0906 +2025-05-29 10:42:59,012 - pyskl - INFO - Epoch [117][1000/1281] lr: 2.905e-03, eta: 4:47:43, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.0904, loss: 1.0904 +2025-05-29 10:43:40,769 - pyskl - INFO - Epoch [117][1100/1281] lr: 2.892e-03, eta: 4:47:03, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.0758, loss: 1.0758 +2025-05-29 10:44:22,410 - pyskl - INFO - Epoch [117][1200/1281] lr: 2.879e-03, eta: 4:46:23, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.0605, loss: 1.0605 +2025-05-29 10:44:56,694 - pyskl - INFO - Saving checkpoint at 117 epochs +2025-05-29 10:45:37,456 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 10:45:37,511 - pyskl - INFO - +top1_acc 0.9315 +top5_acc 0.9961 +2025-05-29 10:45:37,511 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 10:45:37,518 - pyskl - INFO - +mean_acc 0.9123 +2025-05-29 10:45:37,520 - pyskl - INFO - Epoch(val) [117][533] top1_acc: 0.9315, top5_acc: 0.9961, mean_class_accuracy: 0.9123 +2025-05-29 10:46:36,481 - pyskl - INFO - Epoch [118][100/1281] lr: 2.856e-03, eta: 4:45:05, time: 0.590, data_time: 0.173, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.0827, loss: 1.0827 +2025-05-29 10:47:18,185 - pyskl - INFO - Epoch [118][200/1281] lr: 2.843e-03, eta: 4:44:25, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 1.1487, loss: 1.1487 +2025-05-29 10:47:59,900 - pyskl - INFO - Epoch [118][300/1281] lr: 2.830e-03, eta: 4:43:45, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.0935, loss: 1.0935 +2025-05-29 10:48:41,629 - pyskl - INFO - Epoch [118][400/1281] lr: 2.817e-03, eta: 4:43:05, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.0871, loss: 1.0871 +2025-05-29 10:49:23,372 - pyskl - INFO - Epoch [118][500/1281] lr: 2.804e-03, eta: 4:42:25, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.0684, loss: 1.0684 +2025-05-29 10:50:05,079 - pyskl - INFO - Epoch [118][600/1281] lr: 2.791e-03, eta: 4:41:44, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.0968, loss: 1.0968 +2025-05-29 10:50:46,789 - pyskl - INFO - Epoch [118][700/1281] lr: 2.778e-03, eta: 4:41:04, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.1829, loss: 1.1829 +2025-05-29 10:51:29,115 - pyskl - INFO - Epoch [118][800/1281] lr: 2.765e-03, eta: 4:40:24, time: 0.423, data_time: 0.000, memory: 9000, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 1.1769, loss: 1.1769 +2025-05-29 10:52:11,172 - pyskl - INFO - Epoch [118][900/1281] lr: 2.753e-03, eta: 4:39:44, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.1121, loss: 1.1121 +2025-05-29 10:52:52,896 - pyskl - INFO - Epoch [118][1000/1281] lr: 2.740e-03, eta: 4:39:04, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0876, loss: 1.0876 +2025-05-29 10:53:34,564 - pyskl - INFO - Epoch [118][1100/1281] lr: 2.727e-03, eta: 4:38:23, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.1257, loss: 1.1257 +2025-05-29 10:54:16,233 - pyskl - INFO - Epoch [118][1200/1281] lr: 2.714e-03, eta: 4:37:43, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.1096, loss: 1.1096 +2025-05-29 10:54:50,527 - pyskl - INFO - Saving checkpoint at 118 epochs +2025-05-29 10:55:31,181 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 10:55:31,237 - pyskl - INFO - +top1_acc 0.9428 +top5_acc 0.9966 +2025-05-29 10:55:31,237 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 10:55:31,244 - pyskl - INFO - +mean_acc 0.9198 +2025-05-29 10:55:31,305 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_115.pth was removed +2025-05-29 10:55:32,867 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_118.pth. +2025-05-29 10:55:32,868 - pyskl - INFO - Best top1_acc is 0.9428 at 118 epoch. +2025-05-29 10:55:32,873 - pyskl - INFO - Epoch(val) [118][533] top1_acc: 0.9428, top5_acc: 0.9966, mean_class_accuracy: 0.9198 +2025-05-29 10:56:32,510 - pyskl - INFO - Epoch [119][100/1281] lr: 2.691e-03, eta: 4:36:26, time: 0.596, data_time: 0.176, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.0931, loss: 1.0931 +2025-05-29 10:57:14,297 - pyskl - INFO - Epoch [119][200/1281] lr: 2.679e-03, eta: 4:35:46, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0717, loss: 1.0717 +2025-05-29 10:57:56,160 - pyskl - INFO - Epoch [119][300/1281] lr: 2.666e-03, eta: 4:35:05, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.1001, loss: 1.1001 +2025-05-29 10:58:38,048 - pyskl - INFO - Epoch [119][400/1281] lr: 2.653e-03, eta: 4:34:25, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.1353, loss: 1.1353 +2025-05-29 10:59:19,788 - pyskl - INFO - Epoch [119][500/1281] lr: 2.641e-03, eta: 4:33:45, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0765, loss: 1.0765 +2025-05-29 11:00:01,489 - pyskl - INFO - Epoch [119][600/1281] lr: 2.628e-03, eta: 4:33:05, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0776, loss: 1.0776 +2025-05-29 11:00:43,233 - pyskl - INFO - Epoch [119][700/1281] lr: 2.616e-03, eta: 4:32:24, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.0744, loss: 1.0744 +2025-05-29 11:01:25,206 - pyskl - INFO - Epoch [119][800/1281] lr: 2.603e-03, eta: 4:31:44, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.0825, loss: 1.0825 +2025-05-29 11:02:07,709 - pyskl - INFO - Epoch [119][900/1281] lr: 2.591e-03, eta: 4:31:04, time: 0.425, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.0649, loss: 1.0649 +2025-05-29 11:02:50,083 - pyskl - INFO - Epoch [119][1000/1281] lr: 2.578e-03, eta: 4:30:24, time: 0.424, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.1348, loss: 1.1348 +2025-05-29 11:03:31,981 - pyskl - INFO - Epoch [119][1100/1281] lr: 2.566e-03, eta: 4:29:44, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.1154, loss: 1.1154 +2025-05-29 11:04:13,677 - pyskl - INFO - Epoch [119][1200/1281] lr: 2.554e-03, eta: 4:29:04, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.1221, loss: 1.1221 +2025-05-29 11:04:47,969 - pyskl - INFO - Saving checkpoint at 119 epochs +2025-05-29 11:05:28,447 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 11:05:28,503 - pyskl - INFO - +top1_acc 0.9378 +top5_acc 0.9965 +2025-05-29 11:05:28,503 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 11:05:28,510 - pyskl - INFO - +mean_acc 0.9154 +2025-05-29 11:05:28,512 - pyskl - INFO - Epoch(val) [119][533] top1_acc: 0.9378, top5_acc: 0.9965, mean_class_accuracy: 0.9154 +2025-05-29 11:06:27,987 - pyskl - INFO - Epoch [120][100/1281] lr: 2.531e-03, eta: 4:27:47, time: 0.595, data_time: 0.176, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.0855, loss: 1.0855 +2025-05-29 11:07:09,718 - pyskl - INFO - Epoch [120][200/1281] lr: 2.519e-03, eta: 4:27:06, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.0404, loss: 1.0404 +2025-05-29 11:07:51,486 - pyskl - INFO - Epoch [120][300/1281] lr: 2.507e-03, eta: 4:26:26, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.1173, loss: 1.1173 +2025-05-29 11:08:33,266 - pyskl - INFO - Epoch [120][400/1281] lr: 2.494e-03, eta: 4:25:46, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.0325, loss: 1.0325 +2025-05-29 11:09:15,012 - pyskl - INFO - Epoch [120][500/1281] lr: 2.482e-03, eta: 4:25:05, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0362, loss: 1.0362 +2025-05-29 11:09:56,742 - pyskl - INFO - Epoch [120][600/1281] lr: 2.470e-03, eta: 4:24:25, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0276, loss: 1.0276 +2025-05-29 11:10:38,458 - pyskl - INFO - Epoch [120][700/1281] lr: 2.458e-03, eta: 4:23:45, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.0528, loss: 1.0528 +2025-05-29 11:11:20,722 - pyskl - INFO - Epoch [120][800/1281] lr: 2.446e-03, eta: 4:23:05, time: 0.423, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.0847, loss: 1.0847 +2025-05-29 11:12:02,580 - pyskl - INFO - Epoch [120][900/1281] lr: 2.433e-03, eta: 4:22:25, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.0511, loss: 1.0511 +2025-05-29 11:12:44,297 - pyskl - INFO - Epoch [120][1000/1281] lr: 2.421e-03, eta: 4:21:44, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.0702, loss: 1.0702 +2025-05-29 11:13:25,904 - pyskl - INFO - Epoch [120][1100/1281] lr: 2.409e-03, eta: 4:21:04, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.1054, loss: 1.1054 +2025-05-29 11:14:07,492 - pyskl - INFO - Epoch [120][1200/1281] lr: 2.397e-03, eta: 4:20:24, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.0704, loss: 1.0704 +2025-05-29 11:14:41,748 - pyskl - INFO - Saving checkpoint at 120 epochs +2025-05-29 11:27:47,228 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 11:27:47,284 - pyskl - INFO - +top1_acc 0.9225 +top5_acc 0.9957 +2025-05-29 11:27:47,284 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 11:27:47,292 - pyskl - INFO - +mean_acc 0.9041 +2025-05-29 11:27:47,294 - pyskl - INFO - Epoch(val) [120][533] top1_acc: 0.9225, top5_acc: 0.9957, mean_class_accuracy: 0.9041 +2025-05-29 11:28:46,764 - pyskl - INFO - Epoch [121][100/1281] lr: 2.375e-03, eta: 4:19:07, time: 0.595, data_time: 0.175, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0642, loss: 1.0642 +2025-05-29 11:29:28,497 - pyskl - INFO - Epoch [121][200/1281] lr: 2.363e-03, eta: 4:18:26, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.0758, loss: 1.0758 +2025-05-29 11:30:10,177 - pyskl - INFO - Epoch [121][300/1281] lr: 2.351e-03, eta: 4:17:46, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.0386, loss: 1.0386 +2025-05-29 11:30:51,992 - pyskl - INFO - Epoch [121][400/1281] lr: 2.340e-03, eta: 4:17:06, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.0252, loss: 1.0252 +2025-05-29 11:31:34,205 - pyskl - INFO - Epoch [121][500/1281] lr: 2.328e-03, eta: 4:16:26, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.0745, loss: 1.0745 +2025-05-29 11:32:15,915 - pyskl - INFO - Epoch [121][600/1281] lr: 2.316e-03, eta: 4:15:45, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0392, loss: 1.0392 +2025-05-29 11:32:57,504 - pyskl - INFO - Epoch [121][700/1281] lr: 2.304e-03, eta: 4:15:05, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.0554, loss: 1.0554 +2025-05-29 11:33:39,137 - pyskl - INFO - Epoch [121][800/1281] lr: 2.292e-03, eta: 4:14:25, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.0555, loss: 1.0555 +2025-05-29 11:34:21,034 - pyskl - INFO - Epoch [121][900/1281] lr: 2.280e-03, eta: 4:13:45, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0225, loss: 1.0225 +2025-05-29 11:35:03,009 - pyskl - INFO - Epoch [121][1000/1281] lr: 2.269e-03, eta: 4:13:04, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.0243, loss: 1.0243 +2025-05-29 11:35:44,717 - pyskl - INFO - Epoch [121][1100/1281] lr: 2.257e-03, eta: 4:12:24, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.0500, loss: 1.0500 +2025-05-29 11:36:26,391 - pyskl - INFO - Epoch [121][1200/1281] lr: 2.245e-03, eta: 4:11:44, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0044, loss: 1.0044 +2025-05-29 11:37:00,680 - pyskl - INFO - Saving checkpoint at 121 epochs +2025-05-29 11:37:41,307 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 11:37:41,362 - pyskl - INFO - +top1_acc 0.9390 +top5_acc 0.9958 +2025-05-29 11:37:41,363 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 11:37:41,369 - pyskl - INFO - +mean_acc 0.9218 +2025-05-29 11:37:41,371 - pyskl - INFO - Epoch(val) [121][533] top1_acc: 0.9390, top5_acc: 0.9958, mean_class_accuracy: 0.9218 +2025-05-29 11:38:40,975 - pyskl - INFO - Epoch [122][100/1281] lr: 2.224e-03, eta: 4:10:27, time: 0.596, data_time: 0.175, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.0788, loss: 1.0788 +2025-05-29 11:39:22,698 - pyskl - INFO - Epoch [122][200/1281] lr: 2.212e-03, eta: 4:09:47, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.0293, loss: 1.0293 +2025-05-29 11:40:04,557 - pyskl - INFO - Epoch [122][300/1281] lr: 2.201e-03, eta: 4:09:07, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0421, loss: 1.0421 +2025-05-29 11:40:46,372 - pyskl - INFO - Epoch [122][400/1281] lr: 2.189e-03, eta: 4:08:26, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0745, loss: 1.0745 +2025-05-29 11:41:28,167 - pyskl - INFO - Epoch [122][500/1281] lr: 2.178e-03, eta: 4:07:46, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0091, loss: 1.0091 +2025-05-29 11:42:09,892 - pyskl - INFO - Epoch [122][600/1281] lr: 2.166e-03, eta: 4:07:06, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.0483, loss: 1.0483 +2025-05-29 11:42:51,641 - pyskl - INFO - Epoch [122][700/1281] lr: 2.155e-03, eta: 4:06:25, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0216, loss: 1.0216 +2025-05-29 11:43:33,404 - pyskl - INFO - Epoch [122][800/1281] lr: 2.143e-03, eta: 4:05:45, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.0428, loss: 1.0428 +2025-05-29 11:44:15,482 - pyskl - INFO - Epoch [122][900/1281] lr: 2.132e-03, eta: 4:05:05, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.0717, loss: 1.0717 +2025-05-29 11:44:57,393 - pyskl - INFO - Epoch [122][1000/1281] lr: 2.120e-03, eta: 4:04:25, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.9958, loss: 0.9958 +2025-05-29 11:45:39,391 - pyskl - INFO - Epoch [122][1100/1281] lr: 2.109e-03, eta: 4:03:44, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.0297, loss: 1.0297 +2025-05-29 11:46:21,359 - pyskl - INFO - Epoch [122][1200/1281] lr: 2.098e-03, eta: 4:03:04, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0026, loss: 1.0026 +2025-05-29 11:46:55,634 - pyskl - INFO - Saving checkpoint at 122 epochs +2025-05-29 11:47:36,194 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 11:47:36,250 - pyskl - INFO - +top1_acc 0.9426 +top5_acc 0.9966 +2025-05-29 11:47:36,250 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 11:47:36,257 - pyskl - INFO - +mean_acc 0.9212 +2025-05-29 11:47:36,259 - pyskl - INFO - Epoch(val) [122][533] top1_acc: 0.9426, top5_acc: 0.9966, mean_class_accuracy: 0.9212 +2025-05-29 11:48:35,749 - pyskl - INFO - Epoch [123][100/1281] lr: 2.077e-03, eta: 4:01:48, time: 0.595, data_time: 0.177, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.0393, loss: 1.0393 +2025-05-29 11:49:17,372 - pyskl - INFO - Epoch [123][200/1281] lr: 2.066e-03, eta: 4:01:07, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.9967, loss: 0.9967 +2025-05-29 11:49:59,020 - pyskl - INFO - Epoch [123][300/1281] lr: 2.055e-03, eta: 4:00:27, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.0386, loss: 1.0386 +2025-05-29 11:50:40,580 - pyskl - INFO - Epoch [123][400/1281] lr: 2.044e-03, eta: 3:59:47, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0341, loss: 1.0341 +2025-05-29 11:51:22,162 - pyskl - INFO - Epoch [123][500/1281] lr: 2.032e-03, eta: 3:59:06, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0466, loss: 1.0466 +2025-05-29 11:52:03,726 - pyskl - INFO - Epoch [123][600/1281] lr: 2.021e-03, eta: 3:58:26, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.0036, loss: 1.0036 +2025-05-29 11:52:45,308 - pyskl - INFO - Epoch [123][700/1281] lr: 2.010e-03, eta: 3:57:46, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0018, loss: 1.0018 +2025-05-29 11:53:26,843 - pyskl - INFO - Epoch [123][800/1281] lr: 1.999e-03, eta: 3:57:05, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9723, loss: 0.9723 +2025-05-29 11:54:08,600 - pyskl - INFO - Epoch [123][900/1281] lr: 1.988e-03, eta: 3:56:25, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0265, loss: 1.0265 +2025-05-29 11:54:50,478 - pyskl - INFO - Epoch [123][1000/1281] lr: 1.977e-03, eta: 3:55:45, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0617, loss: 1.0617 +2025-05-29 11:55:32,051 - pyskl - INFO - Epoch [123][1100/1281] lr: 1.966e-03, eta: 3:55:04, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0067, loss: 1.0067 +2025-05-29 11:56:13,556 - pyskl - INFO - Epoch [123][1200/1281] lr: 1.955e-03, eta: 3:54:24, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0182, loss: 1.0182 +2025-05-29 11:56:47,756 - pyskl - INFO - Saving checkpoint at 123 epochs +2025-05-29 11:57:28,193 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 11:57:28,249 - pyskl - INFO - +top1_acc 0.9418 +top5_acc 0.9965 +2025-05-29 11:57:28,249 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 11:57:28,255 - pyskl - INFO - +mean_acc 0.9156 +2025-05-29 11:57:28,257 - pyskl - INFO - Epoch(val) [123][533] top1_acc: 0.9418, top5_acc: 0.9965, mean_class_accuracy: 0.9156 +2025-05-29 11:58:27,798 - pyskl - INFO - Epoch [124][100/1281] lr: 1.935e-03, eta: 3:53:07, time: 0.595, data_time: 0.178, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0177, loss: 1.0177 +2025-05-29 11:59:09,504 - pyskl - INFO - Epoch [124][200/1281] lr: 1.924e-03, eta: 3:52:27, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.0370, loss: 1.0370 +2025-05-29 11:59:51,301 - pyskl - INFO - Epoch [124][300/1281] lr: 1.913e-03, eta: 3:51:47, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0267, loss: 1.0267 +2025-05-29 12:00:33,106 - pyskl - INFO - Epoch [124][400/1281] lr: 1.902e-03, eta: 3:51:07, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0037, loss: 1.0037 +2025-05-29 12:01:14,919 - pyskl - INFO - Epoch [124][500/1281] lr: 1.892e-03, eta: 3:50:26, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9761, loss: 0.9761 +2025-05-29 12:01:56,740 - pyskl - INFO - Epoch [124][600/1281] lr: 1.881e-03, eta: 3:49:46, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0280, loss: 1.0280 +2025-05-29 12:02:38,591 - pyskl - INFO - Epoch [124][700/1281] lr: 1.870e-03, eta: 3:49:06, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.0267, loss: 1.0267 +2025-05-29 12:03:20,442 - pyskl - INFO - Epoch [124][800/1281] lr: 1.859e-03, eta: 3:48:25, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0320, loss: 1.0320 +2025-05-29 12:04:02,431 - pyskl - INFO - Epoch [124][900/1281] lr: 1.849e-03, eta: 3:47:45, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.0145, loss: 1.0145 +2025-05-29 12:04:44,417 - pyskl - INFO - Epoch [124][1000/1281] lr: 1.838e-03, eta: 3:47:05, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0161, loss: 1.0161 +2025-05-29 12:05:26,209 - pyskl - INFO - Epoch [124][1100/1281] lr: 1.827e-03, eta: 3:46:25, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.0301, loss: 1.0301 +2025-05-29 12:06:07,945 - pyskl - INFO - Epoch [124][1200/1281] lr: 1.817e-03, eta: 3:45:44, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0095, loss: 1.0095 +2025-05-29 12:06:42,249 - pyskl - INFO - Saving checkpoint at 124 epochs +2025-05-29 12:07:22,968 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 12:07:23,023 - pyskl - INFO - +top1_acc 0.9423 +top5_acc 0.9969 +2025-05-29 12:07:23,024 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 12:07:23,030 - pyskl - INFO - +mean_acc 0.9203 +2025-05-29 12:07:23,033 - pyskl - INFO - Epoch(val) [124][533] top1_acc: 0.9423, top5_acc: 0.9969, mean_class_accuracy: 0.9203 +2025-05-29 12:08:23,054 - pyskl - INFO - Epoch [125][100/1281] lr: 1.797e-03, eta: 3:44:28, time: 0.600, data_time: 0.178, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9927, loss: 0.9927 +2025-05-29 12:09:04,874 - pyskl - INFO - Epoch [125][200/1281] lr: 1.787e-03, eta: 3:43:48, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.0168, loss: 1.0168 +2025-05-29 12:09:46,651 - pyskl - INFO - Epoch [125][300/1281] lr: 1.776e-03, eta: 3:43:07, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.0255, loss: 1.0255 +2025-05-29 12:10:28,374 - pyskl - INFO - Epoch [125][400/1281] lr: 1.766e-03, eta: 3:42:27, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0374, loss: 1.0374 +2025-05-29 12:11:10,160 - pyskl - INFO - Epoch [125][500/1281] lr: 1.755e-03, eta: 3:41:47, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.0610, loss: 1.0610 +2025-05-29 12:11:51,860 - pyskl - INFO - Epoch [125][600/1281] lr: 1.745e-03, eta: 3:41:06, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.0419, loss: 1.0419 +2025-05-29 12:12:33,119 - pyskl - INFO - Epoch [125][700/1281] lr: 1.735e-03, eta: 3:40:26, time: 0.413, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.0041, loss: 1.0041 +2025-05-29 12:13:14,425 - pyskl - INFO - Epoch [125][800/1281] lr: 1.724e-03, eta: 3:39:46, time: 0.413, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9948, loss: 0.9948 +2025-05-29 12:13:56,284 - pyskl - INFO - Epoch [125][900/1281] lr: 1.714e-03, eta: 3:39:05, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9995, loss: 0.9995 +2025-05-29 12:14:37,786 - pyskl - INFO - Epoch [125][1000/1281] lr: 1.704e-03, eta: 3:38:25, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0435, loss: 1.0435 +2025-05-29 12:15:19,312 - pyskl - INFO - Epoch [125][1100/1281] lr: 1.693e-03, eta: 3:37:45, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0004, loss: 1.0004 +2025-05-29 12:16:00,814 - pyskl - INFO - Epoch [125][1200/1281] lr: 1.683e-03, eta: 3:37:04, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9965, loss: 0.9965 +2025-05-29 12:16:34,942 - pyskl - INFO - Saving checkpoint at 125 epochs +2025-05-29 12:29:06,412 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 12:29:06,470 - pyskl - INFO - +top1_acc 0.9423 +top5_acc 0.9961 +2025-05-29 12:29:06,471 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 12:29:06,478 - pyskl - INFO - +mean_acc 0.9201 +2025-05-29 12:29:06,480 - pyskl - INFO - Epoch(val) [125][533] top1_acc: 0.9423, top5_acc: 0.9961, mean_class_accuracy: 0.9201 +2025-05-29 12:30:06,728 - pyskl - INFO - Epoch [126][100/1281] lr: 1.665e-03, eta: 3:35:48, time: 0.602, data_time: 0.177, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9968, loss: 0.9968 +2025-05-29 12:30:48,480 - pyskl - INFO - Epoch [126][200/1281] lr: 1.654e-03, eta: 3:35:08, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9672, loss: 0.9672 +2025-05-29 12:31:30,334 - pyskl - INFO - Epoch [126][300/1281] lr: 1.644e-03, eta: 3:34:27, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.0035, loss: 1.0035 +2025-05-29 12:32:12,258 - pyskl - INFO - Epoch [126][400/1281] lr: 1.634e-03, eta: 3:33:47, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0120, loss: 1.0120 +2025-05-29 12:32:54,079 - pyskl - INFO - Epoch [126][500/1281] lr: 1.624e-03, eta: 3:33:07, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.9960, loss: 0.9960 +2025-05-29 12:33:35,936 - pyskl - INFO - Epoch [126][600/1281] lr: 1.614e-03, eta: 3:32:27, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.0015, loss: 1.0015 +2025-05-29 12:34:17,722 - pyskl - INFO - Epoch [126][700/1281] lr: 1.604e-03, eta: 3:31:46, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9939, loss: 0.9939 +2025-05-29 12:34:59,493 - pyskl - INFO - Epoch [126][800/1281] lr: 1.594e-03, eta: 3:31:06, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.0228, loss: 1.0228 +2025-05-29 12:35:41,256 - pyskl - INFO - Epoch [126][900/1281] lr: 1.584e-03, eta: 3:30:26, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9961, loss: 0.9961 +2025-05-29 12:36:22,875 - pyskl - INFO - Epoch [126][1000/1281] lr: 1.574e-03, eta: 3:29:45, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0116, loss: 1.0116 +2025-05-29 12:37:04,791 - pyskl - INFO - Epoch [126][1100/1281] lr: 1.564e-03, eta: 3:29:05, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.0327, loss: 1.0327 +2025-05-29 12:37:46,741 - pyskl - INFO - Epoch [126][1200/1281] lr: 1.554e-03, eta: 3:28:25, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9803, loss: 0.9803 +2025-05-29 12:38:21,001 - pyskl - INFO - Saving checkpoint at 126 epochs +2025-05-29 12:39:01,706 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 12:39:01,763 - pyskl - INFO - +top1_acc 0.9452 +top5_acc 0.9971 +2025-05-29 12:39:01,763 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 12:39:01,770 - pyskl - INFO - +mean_acc 0.9235 +2025-05-29 12:39:01,833 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_118.pth was removed +2025-05-29 12:39:03,374 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_126.pth. +2025-05-29 12:39:03,375 - pyskl - INFO - Best top1_acc is 0.9452 at 126 epoch. +2025-05-29 12:39:03,379 - pyskl - INFO - Epoch(val) [126][533] top1_acc: 0.9452, top5_acc: 0.9971, mean_class_accuracy: 0.9235 +2025-05-29 12:40:03,213 - pyskl - INFO - Epoch [127][100/1281] lr: 1.536e-03, eta: 3:27:09, time: 0.598, data_time: 0.175, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9730, loss: 0.9730 +2025-05-29 12:40:45,009 - pyskl - INFO - Epoch [127][200/1281] lr: 1.527e-03, eta: 3:26:28, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9872, loss: 0.9872 +2025-05-29 12:41:27,015 - pyskl - INFO - Epoch [127][300/1281] lr: 1.517e-03, eta: 3:25:48, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9883, loss: 0.9883 +2025-05-29 12:42:08,861 - pyskl - INFO - Epoch [127][400/1281] lr: 1.507e-03, eta: 3:25:08, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9682, loss: 0.9682 +2025-05-29 12:42:50,654 - pyskl - INFO - Epoch [127][500/1281] lr: 1.497e-03, eta: 3:24:27, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.0080, loss: 1.0080 +2025-05-29 12:43:32,323 - pyskl - INFO - Epoch [127][600/1281] lr: 1.488e-03, eta: 3:23:47, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9958, loss: 0.9958 +2025-05-29 12:44:14,019 - pyskl - INFO - Epoch [127][700/1281] lr: 1.478e-03, eta: 3:23:07, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9825, loss: 0.9825 +2025-05-29 12:44:55,683 - pyskl - INFO - Epoch [127][800/1281] lr: 1.468e-03, eta: 3:22:26, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9970, loss: 0.9970 +2025-05-29 12:45:37,293 - pyskl - INFO - Epoch [127][900/1281] lr: 1.459e-03, eta: 3:21:46, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9600, loss: 0.9600 +2025-05-29 12:46:18,931 - pyskl - INFO - Epoch [127][1000/1281] lr: 1.449e-03, eta: 3:21:06, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9733, loss: 0.9733 +2025-05-29 12:47:01,097 - pyskl - INFO - Epoch [127][1100/1281] lr: 1.440e-03, eta: 3:20:25, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.9793, loss: 0.9793 +2025-05-29 12:47:42,970 - pyskl - INFO - Epoch [127][1200/1281] lr: 1.430e-03, eta: 3:19:45, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0265, loss: 1.0265 +2025-05-29 12:48:17,315 - pyskl - INFO - Saving checkpoint at 127 epochs +2025-05-29 12:48:57,812 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 12:48:57,868 - pyskl - INFO - +top1_acc 0.9425 +top5_acc 0.9971 +2025-05-29 12:48:57,868 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 12:48:57,875 - pyskl - INFO - +mean_acc 0.9170 +2025-05-29 12:48:57,877 - pyskl - INFO - Epoch(val) [127][533] top1_acc: 0.9425, top5_acc: 0.9971, mean_class_accuracy: 0.9170 +2025-05-29 12:49:57,031 - pyskl - INFO - Epoch [128][100/1281] lr: 1.413e-03, eta: 3:18:29, time: 0.591, data_time: 0.173, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9782, loss: 0.9782 +2025-05-29 12:50:38,866 - pyskl - INFO - Epoch [128][200/1281] lr: 1.404e-03, eta: 3:17:49, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.0129, loss: 1.0129 +2025-05-29 12:51:21,325 - pyskl - INFO - Epoch [128][300/1281] lr: 1.394e-03, eta: 3:17:08, time: 0.425, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0267, loss: 1.0267 +2025-05-29 12:52:03,375 - pyskl - INFO - Epoch [128][400/1281] lr: 1.385e-03, eta: 3:16:28, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0145, loss: 1.0145 +2025-05-29 12:52:45,066 - pyskl - INFO - Epoch [128][500/1281] lr: 1.376e-03, eta: 3:15:48, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9570, loss: 0.9570 +2025-05-29 12:53:26,726 - pyskl - INFO - Epoch [128][600/1281] lr: 1.366e-03, eta: 3:15:07, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9588, loss: 0.9588 +2025-05-29 12:54:08,394 - pyskl - INFO - Epoch [128][700/1281] lr: 1.357e-03, eta: 3:14:27, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9987, loss: 0.9987 +2025-05-29 12:54:50,101 - pyskl - INFO - Epoch [128][800/1281] lr: 1.348e-03, eta: 3:13:47, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9669, loss: 0.9669 +2025-05-29 12:55:31,925 - pyskl - INFO - Epoch [128][900/1281] lr: 1.339e-03, eta: 3:13:06, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9812, loss: 0.9812 +2025-05-29 12:56:13,825 - pyskl - INFO - Epoch [128][1000/1281] lr: 1.329e-03, eta: 3:12:26, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0098, loss: 1.0098 +2025-05-29 12:56:55,998 - pyskl - INFO - Epoch [128][1100/1281] lr: 1.320e-03, eta: 3:11:46, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9544, loss: 0.9544 +2025-05-29 12:57:37,933 - pyskl - INFO - Epoch [128][1200/1281] lr: 1.311e-03, eta: 3:11:05, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9476, loss: 0.9476 +2025-05-29 12:58:12,526 - pyskl - INFO - Saving checkpoint at 128 epochs +2025-05-29 12:58:53,077 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 12:58:53,135 - pyskl - INFO - +top1_acc 0.9477 +top5_acc 0.9965 +2025-05-29 12:58:53,135 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 12:58:53,142 - pyskl - INFO - +mean_acc 0.9228 +2025-05-29 12:58:53,205 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/k_2/best_top1_acc_epoch_126.pth was removed +2025-05-29 12:58:54,758 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_128.pth. +2025-05-29 12:58:54,758 - pyskl - INFO - Best top1_acc is 0.9477 at 128 epoch. +2025-05-29 12:58:54,763 - pyskl - INFO - Epoch(val) [128][533] top1_acc: 0.9477, top5_acc: 0.9965, mean_class_accuracy: 0.9228 +2025-05-29 12:59:54,201 - pyskl - INFO - Epoch [129][100/1281] lr: 1.295e-03, eta: 3:09:49, time: 0.594, data_time: 0.177, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9593, loss: 0.9593 +2025-05-29 13:00:35,909 - pyskl - INFO - Epoch [129][200/1281] lr: 1.286e-03, eta: 3:09:09, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9596, loss: 0.9596 +2025-05-29 13:01:17,755 - pyskl - INFO - Epoch [129][300/1281] lr: 1.277e-03, eta: 3:08:29, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9926, loss: 0.9926 +2025-05-29 13:01:59,601 - pyskl - INFO - Epoch [129][400/1281] lr: 1.268e-03, eta: 3:07:48, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9620, loss: 0.9620 +2025-05-29 13:02:41,309 - pyskl - INFO - Epoch [129][500/1281] lr: 1.259e-03, eta: 3:07:08, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9852, loss: 0.9852 +2025-05-29 13:03:22,951 - pyskl - INFO - Epoch [129][600/1281] lr: 1.250e-03, eta: 3:06:28, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9843, loss: 0.9843 +2025-05-29 13:04:04,586 - pyskl - INFO - Epoch [129][700/1281] lr: 1.241e-03, eta: 3:05:47, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.9928, loss: 0.9928 +2025-05-29 13:04:46,259 - pyskl - INFO - Epoch [129][800/1281] lr: 1.232e-03, eta: 3:05:07, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0084, loss: 1.0084 +2025-05-29 13:05:27,990 - pyskl - INFO - Epoch [129][900/1281] lr: 1.223e-03, eta: 3:04:27, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9699, loss: 0.9699 +2025-05-29 13:06:09,847 - pyskl - INFO - Epoch [129][1000/1281] lr: 1.214e-03, eta: 3:03:46, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9924, loss: 0.9924 +2025-05-29 13:06:51,946 - pyskl - INFO - Epoch [129][1100/1281] lr: 1.206e-03, eta: 3:03:06, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9796, loss: 0.9796 +2025-05-29 13:07:33,853 - pyskl - INFO - Epoch [129][1200/1281] lr: 1.197e-03, eta: 3:02:26, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.9486, loss: 0.9486 +2025-05-29 13:08:08,258 - pyskl - INFO - Saving checkpoint at 129 epochs +2025-05-29 13:08:48,914 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 13:08:48,972 - pyskl - INFO - +top1_acc 0.9461 +top5_acc 0.9968 +2025-05-29 13:08:48,972 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 13:08:48,979 - pyskl - INFO - +mean_acc 0.9223 +2025-05-29 13:08:48,981 - pyskl - INFO - Epoch(val) [129][533] top1_acc: 0.9461, top5_acc: 0.9968, mean_class_accuracy: 0.9223 +2025-05-29 13:09:48,869 - pyskl - INFO - Epoch [130][100/1281] lr: 1.181e-03, eta: 3:01:10, time: 0.599, data_time: 0.176, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9541, loss: 0.9541 +2025-05-29 13:10:30,678 - pyskl - INFO - Epoch [130][200/1281] lr: 1.172e-03, eta: 3:00:30, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9490, loss: 0.9490 +2025-05-29 13:11:12,644 - pyskl - INFO - Epoch [130][300/1281] lr: 1.164e-03, eta: 2:59:49, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9751, loss: 0.9751 +2025-05-29 13:11:54,561 - pyskl - INFO - Epoch [130][400/1281] lr: 1.155e-03, eta: 2:59:09, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9786, loss: 0.9786 +2025-05-29 13:12:36,358 - pyskl - INFO - Epoch [130][500/1281] lr: 1.147e-03, eta: 2:58:28, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9797, loss: 0.9797 +2025-05-29 13:13:18,552 - pyskl - INFO - Epoch [130][600/1281] lr: 1.138e-03, eta: 2:57:48, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9622, loss: 0.9622 +2025-05-29 13:14:00,694 - pyskl - INFO - Epoch [130][700/1281] lr: 1.130e-03, eta: 2:57:08, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9306, loss: 0.9306 +2025-05-29 13:14:42,560 - pyskl - INFO - Epoch [130][800/1281] lr: 1.121e-03, eta: 2:56:28, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9624, loss: 0.9624 +2025-05-29 13:15:24,452 - pyskl - INFO - Epoch [130][900/1281] lr: 1.113e-03, eta: 2:55:47, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9549, loss: 0.9549 +2025-05-29 13:16:06,229 - pyskl - INFO - Epoch [130][1000/1281] lr: 1.104e-03, eta: 2:55:07, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9864, loss: 0.9864 +2025-05-29 13:16:47,812 - pyskl - INFO - Epoch [130][1100/1281] lr: 1.096e-03, eta: 2:54:26, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9694, loss: 0.9694 +2025-05-29 13:17:29,336 - pyskl - INFO - Epoch [130][1200/1281] lr: 1.088e-03, eta: 2:53:46, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9033, loss: 0.9033 +2025-05-29 13:18:03,448 - pyskl - INFO - Saving checkpoint at 130 epochs +2025-05-29 13:30:30,047 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 13:30:30,102 - pyskl - INFO - +top1_acc 0.9411 +top5_acc 0.9966 +2025-05-29 13:30:30,102 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 13:30:30,108 - pyskl - INFO - +mean_acc 0.9143 +2025-05-29 13:30:30,110 - pyskl - INFO - Epoch(val) [130][533] top1_acc: 0.9411, top5_acc: 0.9966, mean_class_accuracy: 0.9143 +2025-05-29 13:31:29,765 - pyskl - INFO - Epoch [131][100/1281] lr: 1.072e-03, eta: 2:52:30, time: 0.597, data_time: 0.178, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9911, loss: 0.9911 +2025-05-29 13:32:11,602 - pyskl - INFO - Epoch [131][200/1281] lr: 1.064e-03, eta: 2:51:50, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.9633, loss: 0.9633 +2025-05-29 13:32:53,425 - pyskl - INFO - Epoch [131][300/1281] lr: 1.056e-03, eta: 2:51:10, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9756, loss: 0.9756 +2025-05-29 13:33:35,210 - pyskl - INFO - Epoch [131][400/1281] lr: 1.048e-03, eta: 2:50:29, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9606, loss: 0.9606 +2025-05-29 13:34:16,987 - pyskl - INFO - Epoch [131][500/1281] lr: 1.040e-03, eta: 2:49:49, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9847, loss: 0.9847 +2025-05-29 13:34:58,965 - pyskl - INFO - Epoch [131][600/1281] lr: 1.031e-03, eta: 2:49:09, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9623, loss: 0.9623 +2025-05-29 13:35:41,017 - pyskl - INFO - Epoch [131][700/1281] lr: 1.023e-03, eta: 2:48:28, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9764, loss: 0.9764 +2025-05-29 13:36:24,506 - pyskl - INFO - Epoch [131][800/1281] lr: 1.015e-03, eta: 2:47:48, time: 0.435, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9468, loss: 0.9468 +2025-05-29 13:37:08,233 - pyskl - INFO - Epoch [131][900/1281] lr: 1.007e-03, eta: 2:47:08, time: 0.437, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9524, loss: 0.9524 +2025-05-29 13:37:50,223 - pyskl - INFO - Epoch [131][1000/1281] lr: 9.992e-04, eta: 2:46:28, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9278, loss: 0.9278 +2025-05-29 13:38:32,010 - pyskl - INFO - Epoch [131][1100/1281] lr: 9.912e-04, eta: 2:45:47, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.9796, loss: 0.9796 +2025-05-29 13:39:13,996 - pyskl - INFO - Epoch [131][1200/1281] lr: 9.832e-04, eta: 2:45:07, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.9872, loss: 0.9872 +2025-05-29 13:39:48,618 - pyskl - INFO - Saving checkpoint at 131 epochs +2025-05-29 13:40:29,569 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 13:40:29,625 - pyskl - INFO - +top1_acc 0.9459 +top5_acc 0.9968 +2025-05-29 13:40:29,625 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 13:40:29,631 - pyskl - INFO - +mean_acc 0.9251 +2025-05-29 13:40:29,633 - pyskl - INFO - Epoch(val) [131][533] top1_acc: 0.9459, top5_acc: 0.9968, mean_class_accuracy: 0.9251 +2025-05-29 13:41:28,880 - pyskl - INFO - Epoch [132][100/1281] lr: 9.689e-04, eta: 2:43:51, time: 0.592, data_time: 0.174, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9527, loss: 0.9527 +2025-05-29 13:42:10,660 - pyskl - INFO - Epoch [132][200/1281] lr: 9.610e-04, eta: 2:43:11, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9756, loss: 0.9756 +2025-05-29 13:42:52,528 - pyskl - INFO - Epoch [132][300/1281] lr: 9.532e-04, eta: 2:42:31, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9919, loss: 0.9919 +2025-05-29 13:43:34,358 - pyskl - INFO - Epoch [132][400/1281] lr: 9.454e-04, eta: 2:41:50, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9397, loss: 0.9397 +2025-05-29 13:44:16,253 - pyskl - INFO - Epoch [132][500/1281] lr: 9.376e-04, eta: 2:41:10, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.0053, loss: 1.0053 +2025-05-29 13:44:58,029 - pyskl - INFO - Epoch [132][600/1281] lr: 9.298e-04, eta: 2:40:29, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9754, loss: 0.9754 +2025-05-29 13:45:39,834 - pyskl - INFO - Epoch [132][700/1281] lr: 9.221e-04, eta: 2:39:49, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9532, loss: 0.9532 +2025-05-29 13:46:21,631 - pyskl - INFO - Epoch [132][800/1281] lr: 9.144e-04, eta: 2:39:09, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9403, loss: 0.9403 +2025-05-29 13:47:03,438 - pyskl - INFO - Epoch [132][900/1281] lr: 9.068e-04, eta: 2:38:28, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9650, loss: 0.9650 +2025-05-29 13:47:45,298 - pyskl - INFO - Epoch [132][1000/1281] lr: 8.991e-04, eta: 2:37:48, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9617, loss: 0.9617 +2025-05-29 13:48:27,116 - pyskl - INFO - Epoch [132][1100/1281] lr: 8.915e-04, eta: 2:37:07, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9494, loss: 0.9494 +2025-05-29 13:49:09,099 - pyskl - INFO - Epoch [132][1200/1281] lr: 8.840e-04, eta: 2:36:27, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9419, loss: 0.9419 +2025-05-29 13:49:43,400 - pyskl - INFO - Saving checkpoint at 132 epochs +2025-05-29 13:50:24,052 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 13:50:24,108 - pyskl - INFO - +top1_acc 0.9437 +top5_acc 0.9973 +2025-05-29 13:50:24,108 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 13:50:24,115 - pyskl - INFO - +mean_acc 0.9215 +2025-05-29 13:50:24,117 - pyskl - INFO - Epoch(val) [132][533] top1_acc: 0.9437, top5_acc: 0.9973, mean_class_accuracy: 0.9215 +2025-05-29 13:51:23,640 - pyskl - INFO - Epoch [133][100/1281] lr: 8.704e-04, eta: 2:35:12, time: 0.595, data_time: 0.174, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9220, loss: 0.9220 +2025-05-29 13:52:05,325 - pyskl - INFO - Epoch [133][200/1281] lr: 8.629e-04, eta: 2:34:31, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9335, loss: 0.9335 +2025-05-29 13:52:47,148 - pyskl - INFO - Epoch [133][300/1281] lr: 8.554e-04, eta: 2:33:51, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9895, loss: 0.9895 +2025-05-29 13:53:30,043 - pyskl - INFO - Epoch [133][400/1281] lr: 8.480e-04, eta: 2:33:11, time: 0.429, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9689, loss: 0.9689 +2025-05-29 13:54:11,875 - pyskl - INFO - Epoch [133][500/1281] lr: 8.406e-04, eta: 2:32:30, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.9679, loss: 0.9679 +2025-05-29 13:54:53,573 - pyskl - INFO - Epoch [133][600/1281] lr: 8.333e-04, eta: 2:31:50, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9473, loss: 0.9473 +2025-05-29 13:55:35,247 - pyskl - INFO - Epoch [133][700/1281] lr: 8.260e-04, eta: 2:31:10, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9439, loss: 0.9439 +2025-05-29 13:56:16,949 - pyskl - INFO - Epoch [133][800/1281] lr: 8.187e-04, eta: 2:30:29, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9009, loss: 0.9009 +2025-05-29 13:56:58,861 - pyskl - INFO - Epoch [133][900/1281] lr: 8.114e-04, eta: 2:29:49, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.9693, loss: 0.9693 +2025-05-29 13:57:41,057 - pyskl - INFO - Epoch [133][1000/1281] lr: 8.042e-04, eta: 2:29:08, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9344, loss: 0.9344 +2025-05-29 13:58:22,811 - pyskl - INFO - Epoch [133][1100/1281] lr: 7.970e-04, eta: 2:28:28, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9592, loss: 0.9592 +2025-05-29 13:59:04,705 - pyskl - INFO - Epoch [133][1200/1281] lr: 7.898e-04, eta: 2:27:48, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9420, loss: 0.9420 +2025-05-29 13:59:39,375 - pyskl - INFO - Saving checkpoint at 133 epochs +2025-05-29 14:00:20,073 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 14:00:20,129 - pyskl - INFO - +top1_acc 0.9459 +top5_acc 0.9959 +2025-05-29 14:00:20,129 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 14:00:20,136 - pyskl - INFO - +mean_acc 0.9255 +2025-05-29 14:00:20,138 - pyskl - INFO - Epoch(val) [133][533] top1_acc: 0.9459, top5_acc: 0.9959, mean_class_accuracy: 0.9255 +2025-05-29 14:01:19,406 - pyskl - INFO - Epoch [134][100/1281] lr: 7.769e-04, eta: 2:26:32, time: 0.593, data_time: 0.174, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9468, loss: 0.9468 +2025-05-29 14:02:01,278 - pyskl - INFO - Epoch [134][200/1281] lr: 7.699e-04, eta: 2:25:52, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8807, loss: 0.8807 +2025-05-29 14:02:43,120 - pyskl - INFO - Epoch [134][300/1281] lr: 7.628e-04, eta: 2:25:11, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9566, loss: 0.9566 +2025-05-29 14:03:25,083 - pyskl - INFO - Epoch [134][400/1281] lr: 7.558e-04, eta: 2:24:31, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9688, loss: 0.9688 +2025-05-29 14:04:06,955 - pyskl - INFO - Epoch [134][500/1281] lr: 7.488e-04, eta: 2:23:51, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9073, loss: 0.9073 +2025-05-29 14:04:48,674 - pyskl - INFO - Epoch [134][600/1281] lr: 7.419e-04, eta: 2:23:10, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9608, loss: 0.9608 +2025-05-29 14:05:30,364 - pyskl - INFO - Epoch [134][700/1281] lr: 7.349e-04, eta: 2:22:30, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9249, loss: 0.9249 +2025-05-29 14:06:12,075 - pyskl - INFO - Epoch [134][800/1281] lr: 7.281e-04, eta: 2:21:49, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9398, loss: 0.9398 +2025-05-29 14:06:53,785 - pyskl - INFO - Epoch [134][900/1281] lr: 7.212e-04, eta: 2:21:09, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9343, loss: 0.9343 +2025-05-29 14:07:35,549 - pyskl - INFO - Epoch [134][1000/1281] lr: 7.144e-04, eta: 2:20:29, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9748, loss: 0.9748 +2025-05-29 14:08:17,343 - pyskl - INFO - Epoch [134][1100/1281] lr: 7.076e-04, eta: 2:19:48, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9326, loss: 0.9326 +2025-05-29 14:08:59,280 - pyskl - INFO - Epoch [134][1200/1281] lr: 7.008e-04, eta: 2:19:08, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9227, loss: 0.9227 +2025-05-29 14:09:33,889 - pyskl - INFO - Saving checkpoint at 134 epochs +2025-05-29 14:10:14,590 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 14:10:14,645 - pyskl - INFO - +top1_acc 0.9440 +top5_acc 0.9968 +2025-05-29 14:10:14,645 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 14:10:14,652 - pyskl - INFO - +mean_acc 0.9213 +2025-05-29 14:10:14,654 - pyskl - INFO - Epoch(val) [134][533] top1_acc: 0.9440, top5_acc: 0.9968, mean_class_accuracy: 0.9213 +2025-05-29 14:11:13,519 - pyskl - INFO - Epoch [135][100/1281] lr: 6.887e-04, eta: 2:17:53, time: 0.589, data_time: 0.172, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.9399, loss: 0.9399 +2025-05-29 14:11:55,233 - pyskl - INFO - Epoch [135][200/1281] lr: 6.820e-04, eta: 2:17:12, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9490, loss: 0.9490 +2025-05-29 14:12:36,876 - pyskl - INFO - Epoch [135][300/1281] lr: 6.753e-04, eta: 2:16:32, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9377, loss: 0.9377 +2025-05-29 14:13:18,680 - pyskl - INFO - Epoch [135][400/1281] lr: 6.687e-04, eta: 2:15:51, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9594, loss: 0.9594 +2025-05-29 14:14:00,203 - pyskl - INFO - Epoch [135][500/1281] lr: 6.622e-04, eta: 2:15:11, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9365, loss: 0.9365 +2025-05-29 14:14:41,412 - pyskl - INFO - Epoch [135][600/1281] lr: 6.556e-04, eta: 2:14:30, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9070, loss: 0.9070 +2025-05-29 14:15:22,619 - pyskl - INFO - Epoch [135][700/1281] lr: 6.491e-04, eta: 2:13:50, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9299, loss: 0.9299 +2025-05-29 14:16:03,823 - pyskl - INFO - Epoch [135][800/1281] lr: 6.426e-04, eta: 2:13:09, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9153, loss: 0.9153 +2025-05-29 14:16:45,033 - pyskl - INFO - Epoch [135][900/1281] lr: 6.362e-04, eta: 2:12:29, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9287, loss: 0.9287 +2025-05-29 14:17:26,247 - pyskl - INFO - Epoch [135][1000/1281] lr: 6.297e-04, eta: 2:11:48, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9113, loss: 0.9113 +2025-05-29 14:18:07,471 - pyskl - INFO - Epoch [135][1100/1281] lr: 6.233e-04, eta: 2:11:08, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9032, loss: 0.9032 +2025-05-29 14:18:49,684 - pyskl - INFO - Epoch [135][1200/1281] lr: 6.170e-04, eta: 2:10:28, time: 0.422, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9284, loss: 0.9284 +2025-05-29 14:19:24,286 - pyskl - INFO - Saving checkpoint at 135 epochs +2025-05-29 14:32:31,661 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 14:32:31,718 - pyskl - INFO - +top1_acc 0.9365 +top5_acc 0.9962 +2025-05-29 14:32:31,718 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 14:32:31,726 - pyskl - INFO - +mean_acc 0.9084 +2025-05-29 14:32:31,730 - pyskl - INFO - Epoch(val) [135][533] top1_acc: 0.9365, top5_acc: 0.9962, mean_class_accuracy: 0.9084 +2025-05-29 14:33:32,841 - pyskl - INFO - Epoch [136][100/1281] lr: 6.056e-04, eta: 2:09:13, time: 0.611, data_time: 0.174, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9386, loss: 0.9386 +2025-05-29 14:34:16,584 - pyskl - INFO - Epoch [136][200/1281] lr: 5.993e-04, eta: 2:08:33, time: 0.437, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9472, loss: 0.9472 +2025-05-29 14:35:00,311 - pyskl - INFO - Epoch [136][300/1281] lr: 5.931e-04, eta: 2:07:52, time: 0.437, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9340, loss: 0.9340 +2025-05-29 14:35:43,969 - pyskl - INFO - Epoch [136][400/1281] lr: 5.868e-04, eta: 2:07:12, time: 0.437, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.9199, loss: 0.9199 +2025-05-29 14:36:25,765 - pyskl - INFO - Epoch [136][500/1281] lr: 5.807e-04, eta: 2:06:32, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9565, loss: 0.9565 +2025-05-29 14:37:07,422 - pyskl - INFO - Epoch [136][600/1281] lr: 5.745e-04, eta: 2:05:51, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9121, loss: 0.9121 +2025-05-29 14:37:49,074 - pyskl - INFO - Epoch [136][700/1281] lr: 5.684e-04, eta: 2:05:11, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9410, loss: 0.9410 +2025-05-29 14:38:30,712 - pyskl - INFO - Epoch [136][800/1281] lr: 5.623e-04, eta: 2:04:30, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9348, loss: 0.9348 +2025-05-29 14:39:12,326 - pyskl - INFO - Epoch [136][900/1281] lr: 5.563e-04, eta: 2:03:50, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9042, loss: 0.9042 +2025-05-29 14:39:53,997 - pyskl - INFO - Epoch [136][1000/1281] lr: 5.503e-04, eta: 2:03:09, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9408, loss: 0.9408 +2025-05-29 14:40:35,833 - pyskl - INFO - Epoch [136][1100/1281] lr: 5.443e-04, eta: 2:02:29, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9517, loss: 0.9517 +2025-05-29 14:41:18,147 - pyskl - INFO - Epoch [136][1200/1281] lr: 5.384e-04, eta: 2:01:49, time: 0.423, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9110, loss: 0.9110 +2025-05-29 14:41:52,770 - pyskl - INFO - Saving checkpoint at 136 epochs +2025-05-29 14:42:33,982 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 14:42:34,050 - pyskl - INFO - +top1_acc 0.9444 +top5_acc 0.9973 +2025-05-29 14:42:34,050 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 14:42:34,058 - pyskl - INFO - +mean_acc 0.9236 +2025-05-29 14:42:34,060 - pyskl - INFO - Epoch(val) [136][533] top1_acc: 0.9444, top5_acc: 0.9973, mean_class_accuracy: 0.9236 +2025-05-29 14:43:33,450 - pyskl - INFO - Epoch [137][100/1281] lr: 5.277e-04, eta: 2:00:34, time: 0.594, data_time: 0.176, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9111, loss: 0.9111 +2025-05-29 14:44:15,219 - pyskl - INFO - Epoch [137][200/1281] lr: 5.218e-04, eta: 1:59:53, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9528, loss: 0.9528 +2025-05-29 14:44:57,014 - pyskl - INFO - Epoch [137][300/1281] lr: 5.160e-04, eta: 1:59:13, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9320, loss: 0.9320 +2025-05-29 14:45:38,968 - pyskl - INFO - Epoch [137][400/1281] lr: 5.102e-04, eta: 1:58:32, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9301, loss: 0.9301 +2025-05-29 14:46:20,916 - pyskl - INFO - Epoch [137][500/1281] lr: 5.044e-04, eta: 1:57:52, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9171, loss: 0.9171 +2025-05-29 14:47:02,557 - pyskl - INFO - Epoch [137][600/1281] lr: 4.987e-04, eta: 1:57:11, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9067, loss: 0.9067 +2025-05-29 14:47:44,203 - pyskl - INFO - Epoch [137][700/1281] lr: 4.930e-04, eta: 1:56:31, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8925, loss: 0.8925 +2025-05-29 14:48:25,837 - pyskl - INFO - Epoch [137][800/1281] lr: 4.873e-04, eta: 1:55:51, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9384, loss: 0.9384 +2025-05-29 14:49:07,519 - pyskl - INFO - Epoch [137][900/1281] lr: 4.817e-04, eta: 1:55:10, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9140, loss: 0.9140 +2025-05-29 14:49:49,187 - pyskl - INFO - Epoch [137][1000/1281] lr: 4.761e-04, eta: 1:54:30, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9091, loss: 0.9091 +2025-05-29 14:50:30,936 - pyskl - INFO - Epoch [137][1100/1281] lr: 4.705e-04, eta: 1:53:49, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9158, loss: 0.9158 +2025-05-29 14:51:12,712 - pyskl - INFO - Epoch [137][1200/1281] lr: 4.650e-04, eta: 1:53:09, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9122, loss: 0.9122 +2025-05-29 14:51:47,289 - pyskl - INFO - Saving checkpoint at 137 epochs +2025-05-29 14:52:28,480 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 14:52:28,538 - pyskl - INFO - +top1_acc 0.9447 +top5_acc 0.9971 +2025-05-29 14:52:28,538 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 14:52:28,545 - pyskl - INFO - +mean_acc 0.9232 +2025-05-29 14:52:28,547 - pyskl - INFO - Epoch(val) [137][533] top1_acc: 0.9447, top5_acc: 0.9971, mean_class_accuracy: 0.9232 +2025-05-29 14:53:27,656 - pyskl - INFO - Epoch [138][100/1281] lr: 4.550e-04, eta: 1:51:54, time: 0.591, data_time: 0.173, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9249, loss: 0.9249 +2025-05-29 14:54:09,449 - pyskl - INFO - Epoch [138][200/1281] lr: 4.496e-04, eta: 1:51:13, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9319, loss: 0.9319 +2025-05-29 14:54:51,235 - pyskl - INFO - Epoch [138][300/1281] lr: 4.442e-04, eta: 1:50:33, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9418, loss: 0.9418 +2025-05-29 14:55:32,765 - pyskl - INFO - Epoch [138][400/1281] lr: 4.388e-04, eta: 1:49:53, time: 0.415, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9114, loss: 0.9114 +2025-05-29 14:56:14,572 - pyskl - INFO - Epoch [138][500/1281] lr: 4.334e-04, eta: 1:49:12, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9537, loss: 0.9537 +2025-05-29 14:56:56,233 - pyskl - INFO - Epoch [138][600/1281] lr: 4.281e-04, eta: 1:48:32, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9021, loss: 0.9021 +2025-05-29 14:57:37,929 - pyskl - INFO - Epoch [138][700/1281] lr: 4.228e-04, eta: 1:47:51, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9436, loss: 0.9436 +2025-05-29 14:58:19,619 - pyskl - INFO - Epoch [138][800/1281] lr: 4.176e-04, eta: 1:47:11, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9328, loss: 0.9328 +2025-05-29 14:59:01,365 - pyskl - INFO - Epoch [138][900/1281] lr: 4.124e-04, eta: 1:46:30, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9407, loss: 0.9407 +2025-05-29 14:59:43,077 - pyskl - INFO - Epoch [138][1000/1281] lr: 4.072e-04, eta: 1:45:50, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9606, loss: 0.9606 +2025-05-29 15:00:24,866 - pyskl - INFO - Epoch [138][1100/1281] lr: 4.020e-04, eta: 1:45:09, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9139, loss: 0.9139 +2025-05-29 15:01:06,775 - pyskl - INFO - Epoch [138][1200/1281] lr: 3.969e-04, eta: 1:44:29, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9387, loss: 0.9387 +2025-05-29 15:01:41,288 - pyskl - INFO - Saving checkpoint at 138 epochs +2025-05-29 15:02:22,123 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 15:02:22,185 - pyskl - INFO - +top1_acc 0.9377 +top5_acc 0.9962 +2025-05-29 15:02:22,185 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 15:02:22,195 - pyskl - INFO - +mean_acc 0.9094 +2025-05-29 15:02:22,199 - pyskl - INFO - Epoch(val) [138][533] top1_acc: 0.9377, top5_acc: 0.9962, mean_class_accuracy: 0.9094 +2025-05-29 15:03:22,962 - pyskl - INFO - Epoch [139][100/1281] lr: 3.877e-04, eta: 1:43:14, time: 0.608, data_time: 0.181, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9449, loss: 0.9449 +2025-05-29 15:04:04,952 - pyskl - INFO - Epoch [139][200/1281] lr: 3.827e-04, eta: 1:42:34, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9063, loss: 0.9063 +2025-05-29 15:04:46,642 - pyskl - INFO - Epoch [139][300/1281] lr: 3.777e-04, eta: 1:41:53, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9384, loss: 0.9384 +2025-05-29 15:05:28,567 - pyskl - INFO - Epoch [139][400/1281] lr: 3.727e-04, eta: 1:41:13, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9466, loss: 0.9466 +2025-05-29 15:06:10,477 - pyskl - INFO - Epoch [139][500/1281] lr: 3.678e-04, eta: 1:40:33, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9110, loss: 0.9110 +2025-05-29 15:06:52,362 - pyskl - INFO - Epoch [139][600/1281] lr: 3.628e-04, eta: 1:39:52, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9077, loss: 0.9077 +2025-05-29 15:07:34,270 - pyskl - INFO - Epoch [139][700/1281] lr: 3.580e-04, eta: 1:39:12, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8917, loss: 0.8917 +2025-05-29 15:08:16,129 - pyskl - INFO - Epoch [139][800/1281] lr: 3.531e-04, eta: 1:38:31, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9134, loss: 0.9134 +2025-05-29 15:08:58,022 - pyskl - INFO - Epoch [139][900/1281] lr: 3.483e-04, eta: 1:37:51, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9079, loss: 0.9079 +2025-05-29 15:09:39,834 - pyskl - INFO - Epoch [139][1000/1281] lr: 3.436e-04, eta: 1:37:10, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9274, loss: 0.9274 +2025-05-29 15:10:21,673 - pyskl - INFO - Epoch [139][1100/1281] lr: 3.388e-04, eta: 1:36:30, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9454, loss: 0.9454 +2025-05-29 15:11:03,460 - pyskl - INFO - Epoch [139][1200/1281] lr: 3.341e-04, eta: 1:35:49, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9492, loss: 0.9492 +2025-05-29 15:11:38,158 - pyskl - INFO - Saving checkpoint at 139 epochs +2025-05-29 15:12:19,558 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 15:12:19,614 - pyskl - INFO - +top1_acc 0.9455 +top5_acc 0.9971 +2025-05-29 15:12:19,614 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 15:12:19,621 - pyskl - INFO - +mean_acc 0.9222 +2025-05-29 15:12:19,623 - pyskl - INFO - Epoch(val) [139][533] top1_acc: 0.9455, top5_acc: 0.9971, mean_class_accuracy: 0.9222 +2025-05-29 15:13:18,670 - pyskl - INFO - Epoch [140][100/1281] lr: 3.257e-04, eta: 1:34:35, time: 0.590, data_time: 0.174, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9168, loss: 0.9168 +2025-05-29 15:14:00,332 - pyskl - INFO - Epoch [140][200/1281] lr: 3.210e-04, eta: 1:33:54, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9064, loss: 0.9064 +2025-05-29 15:14:42,060 - pyskl - INFO - Epoch [140][300/1281] lr: 3.165e-04, eta: 1:33:14, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9096, loss: 0.9096 +2025-05-29 15:15:24,014 - pyskl - INFO - Epoch [140][400/1281] lr: 3.119e-04, eta: 1:32:33, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9036, loss: 0.9036 +2025-05-29 15:16:05,956 - pyskl - INFO - Epoch [140][500/1281] lr: 3.074e-04, eta: 1:31:53, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9328, loss: 0.9328 +2025-05-29 15:16:47,609 - pyskl - INFO - Epoch [140][600/1281] lr: 3.029e-04, eta: 1:31:12, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.9287, loss: 0.9287 +2025-05-29 15:17:29,251 - pyskl - INFO - Epoch [140][700/1281] lr: 2.984e-04, eta: 1:30:32, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9117, loss: 0.9117 +2025-05-29 15:18:11,059 - pyskl - INFO - Epoch [140][800/1281] lr: 2.940e-04, eta: 1:29:51, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9541, loss: 0.9541 +2025-05-29 15:18:52,856 - pyskl - INFO - Epoch [140][900/1281] lr: 2.896e-04, eta: 1:29:11, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9108, loss: 0.9108 +2025-05-29 15:19:34,667 - pyskl - INFO - Epoch [140][1000/1281] lr: 2.853e-04, eta: 1:28:30, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9149, loss: 0.9149 +2025-05-29 15:20:16,599 - pyskl - INFO - Epoch [140][1100/1281] lr: 2.809e-04, eta: 1:27:50, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9470, loss: 0.9470 +2025-05-29 15:20:58,427 - pyskl - INFO - Epoch [140][1200/1281] lr: 2.767e-04, eta: 1:27:09, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9074, loss: 0.9074 +2025-05-29 15:21:32,895 - pyskl - INFO - Saving checkpoint at 140 epochs +2025-05-29 15:35:14,419 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 15:35:14,475 - pyskl - INFO - +top1_acc 0.9451 +top5_acc 0.9964 +2025-05-29 15:35:14,475 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 15:35:14,481 - pyskl - INFO - +mean_acc 0.9238 +2025-05-29 15:35:14,484 - pyskl - INFO - Epoch(val) [140][533] top1_acc: 0.9451, top5_acc: 0.9964, mean_class_accuracy: 0.9238 +2025-05-29 15:36:15,520 - pyskl - INFO - Epoch [141][100/1281] lr: 2.690e-04, eta: 1:25:55, time: 0.610, data_time: 0.173, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9091, loss: 0.9091 +2025-05-29 15:36:59,390 - pyskl - INFO - Epoch [141][200/1281] lr: 2.648e-04, eta: 1:25:15, time: 0.439, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9141, loss: 0.9141 +2025-05-29 15:37:41,719 - pyskl - INFO - Epoch [141][300/1281] lr: 2.606e-04, eta: 1:24:34, time: 0.423, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9369, loss: 0.9369 +2025-05-29 15:38:22,923 - pyskl - INFO - Epoch [141][400/1281] lr: 2.565e-04, eta: 1:23:54, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9275, loss: 0.9275 +2025-05-29 15:39:04,132 - pyskl - INFO - Epoch [141][500/1281] lr: 2.524e-04, eta: 1:23:13, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9545, loss: 0.9545 +2025-05-29 15:39:45,314 - pyskl - INFO - Epoch [141][600/1281] lr: 2.483e-04, eta: 1:22:33, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9542, loss: 0.9542 +2025-05-29 15:40:26,514 - pyskl - INFO - Epoch [141][700/1281] lr: 2.443e-04, eta: 1:21:52, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9329, loss: 0.9329 +2025-05-29 15:41:07,712 - pyskl - INFO - Epoch [141][800/1281] lr: 2.402e-04, eta: 1:21:12, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9288, loss: 0.9288 +2025-05-29 15:41:48,918 - pyskl - INFO - Epoch [141][900/1281] lr: 2.363e-04, eta: 1:20:31, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9410, loss: 0.9410 +2025-05-29 15:42:30,118 - pyskl - INFO - Epoch [141][1000/1281] lr: 2.323e-04, eta: 1:19:51, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8858, loss: 0.8858 +2025-05-29 15:43:11,316 - pyskl - INFO - Epoch [141][1100/1281] lr: 2.284e-04, eta: 1:19:10, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9032, loss: 0.9032 +2025-05-29 15:43:52,524 - pyskl - INFO - Epoch [141][1200/1281] lr: 2.246e-04, eta: 1:18:30, time: 0.412, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9099, loss: 0.9099 +2025-05-29 15:44:27,141 - pyskl - INFO - Saving checkpoint at 141 epochs +2025-05-29 15:45:07,984 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 15:45:08,039 - pyskl - INFO - +top1_acc 0.9452 +top5_acc 0.9966 +2025-05-29 15:45:08,039 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 15:45:08,046 - pyskl - INFO - +mean_acc 0.9235 +2025-05-29 15:45:08,049 - pyskl - INFO - Epoch(val) [141][533] top1_acc: 0.9452, top5_acc: 0.9966, mean_class_accuracy: 0.9235 +2025-05-29 15:46:07,120 - pyskl - INFO - Epoch [142][100/1281] lr: 2.176e-04, eta: 1:17:15, time: 0.591, data_time: 0.173, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9117, loss: 0.9117 +2025-05-29 15:46:49,068 - pyskl - INFO - Epoch [142][200/1281] lr: 2.139e-04, eta: 1:16:35, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8940, loss: 0.8940 +2025-05-29 15:47:31,457 - pyskl - INFO - Epoch [142][300/1281] lr: 2.101e-04, eta: 1:15:54, time: 0.424, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8976, loss: 0.8976 +2025-05-29 15:48:13,275 - pyskl - INFO - Epoch [142][400/1281] lr: 2.064e-04, eta: 1:15:14, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.9373, loss: 0.9373 +2025-05-29 15:48:54,932 - pyskl - INFO - Epoch [142][500/1281] lr: 2.027e-04, eta: 1:14:33, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9116, loss: 0.9116 +2025-05-29 15:49:36,634 - pyskl - INFO - Epoch [142][600/1281] lr: 1.991e-04, eta: 1:13:53, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9287, loss: 0.9287 +2025-05-29 15:50:18,517 - pyskl - INFO - Epoch [142][700/1281] lr: 1.954e-04, eta: 1:13:12, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9132, loss: 0.9132 +2025-05-29 15:51:00,263 - pyskl - INFO - Epoch [142][800/1281] lr: 1.919e-04, eta: 1:12:32, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9184, loss: 0.9184 +2025-05-29 15:51:42,051 - pyskl - INFO - Epoch [142][900/1281] lr: 1.883e-04, eta: 1:11:51, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9120, loss: 0.9120 +2025-05-29 15:52:23,741 - pyskl - INFO - Epoch [142][1000/1281] lr: 1.848e-04, eta: 1:11:11, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9190, loss: 0.9190 +2025-05-29 15:53:05,368 - pyskl - INFO - Epoch [142][1100/1281] lr: 1.813e-04, eta: 1:10:30, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9297, loss: 0.9297 +2025-05-29 15:53:46,986 - pyskl - INFO - Epoch [142][1200/1281] lr: 1.779e-04, eta: 1:09:50, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9150, loss: 0.9150 +2025-05-29 15:54:21,585 - pyskl - INFO - Saving checkpoint at 142 epochs +2025-05-29 15:55:02,485 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 15:55:02,542 - pyskl - INFO - +top1_acc 0.9398 +top5_acc 0.9968 +2025-05-29 15:55:02,542 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 15:55:02,549 - pyskl - INFO - +mean_acc 0.9130 +2025-05-29 15:55:02,551 - pyskl - INFO - Epoch(val) [142][533] top1_acc: 0.9398, top5_acc: 0.9968, mean_class_accuracy: 0.9130 +2025-05-29 15:56:01,691 - pyskl - INFO - Epoch [143][100/1281] lr: 1.717e-04, eta: 1:08:36, time: 0.591, data_time: 0.174, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9246, loss: 0.9246 +2025-05-29 15:56:43,435 - pyskl - INFO - Epoch [143][200/1281] lr: 1.683e-04, eta: 1:07:55, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9278, loss: 0.9278 +2025-05-29 15:57:25,320 - pyskl - INFO - Epoch [143][300/1281] lr: 1.650e-04, eta: 1:07:15, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9115, loss: 0.9115 +2025-05-29 15:58:07,138 - pyskl - INFO - Epoch [143][400/1281] lr: 1.617e-04, eta: 1:06:34, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8888, loss: 0.8888 +2025-05-29 15:58:48,793 - pyskl - INFO - Epoch [143][500/1281] lr: 1.585e-04, eta: 1:05:54, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9088, loss: 0.9088 +2025-05-29 15:59:30,425 - pyskl - INFO - Epoch [143][600/1281] lr: 1.552e-04, eta: 1:05:13, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8935, loss: 0.8935 +2025-05-29 16:00:12,148 - pyskl - INFO - Epoch [143][700/1281] lr: 1.520e-04, eta: 1:04:33, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8847, loss: 0.8847 +2025-05-29 16:00:53,898 - pyskl - INFO - Epoch [143][800/1281] lr: 1.489e-04, eta: 1:03:52, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9278, loss: 0.9278 +2025-05-29 16:01:35,617 - pyskl - INFO - Epoch [143][900/1281] lr: 1.457e-04, eta: 1:03:12, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8712, loss: 0.8712 +2025-05-29 16:02:17,385 - pyskl - INFO - Epoch [143][1000/1281] lr: 1.426e-04, eta: 1:02:31, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9272, loss: 0.9272 +2025-05-29 16:02:59,234 - pyskl - INFO - Epoch [143][1100/1281] lr: 1.396e-04, eta: 1:01:51, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9015, loss: 0.9015 +2025-05-29 16:03:41,081 - pyskl - INFO - Epoch [143][1200/1281] lr: 1.366e-04, eta: 1:01:10, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9451, loss: 0.9451 +2025-05-29 16:04:15,731 - pyskl - INFO - Saving checkpoint at 143 epochs +2025-05-29 16:04:56,709 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 16:04:56,765 - pyskl - INFO - +top1_acc 0.9452 +top5_acc 0.9969 +2025-05-29 16:04:56,765 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 16:04:56,772 - pyskl - INFO - +mean_acc 0.9220 +2025-05-29 16:04:56,774 - pyskl - INFO - Epoch(val) [143][533] top1_acc: 0.9452, top5_acc: 0.9969, mean_class_accuracy: 0.9220 +2025-05-29 16:05:56,324 - pyskl - INFO - Epoch [144][100/1281] lr: 1.312e-04, eta: 0:59:56, time: 0.595, data_time: 0.177, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8896, loss: 0.8896 +2025-05-29 16:06:38,000 - pyskl - INFO - Epoch [144][200/1281] lr: 1.282e-04, eta: 0:59:16, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9066, loss: 0.9066 +2025-05-29 16:07:19,785 - pyskl - INFO - Epoch [144][300/1281] lr: 1.253e-04, eta: 0:58:35, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9342, loss: 0.9342 +2025-05-29 16:08:01,691 - pyskl - INFO - Epoch [144][400/1281] lr: 1.224e-04, eta: 0:57:55, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9116, loss: 0.9116 +2025-05-29 16:08:43,668 - pyskl - INFO - Epoch [144][500/1281] lr: 1.196e-04, eta: 0:57:14, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8815, loss: 0.8815 +2025-05-29 16:09:26,130 - pyskl - INFO - Epoch [144][600/1281] lr: 1.168e-04, eta: 0:56:34, time: 0.425, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8924, loss: 0.8924 +2025-05-29 16:10:08,117 - pyskl - INFO - Epoch [144][700/1281] lr: 1.140e-04, eta: 0:55:53, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9217, loss: 0.9217 +2025-05-29 16:10:49,799 - pyskl - INFO - Epoch [144][800/1281] lr: 1.113e-04, eta: 0:55:13, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8870, loss: 0.8870 +2025-05-29 16:11:31,433 - pyskl - INFO - Epoch [144][900/1281] lr: 1.086e-04, eta: 0:54:32, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9156, loss: 0.9156 +2025-05-29 16:12:13,059 - pyskl - INFO - Epoch [144][1000/1281] lr: 1.059e-04, eta: 0:53:52, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8983, loss: 0.8983 +2025-05-29 16:12:54,658 - pyskl - INFO - Epoch [144][1100/1281] lr: 1.033e-04, eta: 0:53:11, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8937, loss: 0.8937 +2025-05-29 16:13:36,340 - pyskl - INFO - Epoch [144][1200/1281] lr: 1.007e-04, eta: 0:52:30, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8853, loss: 0.8853 +2025-05-29 16:14:10,988 - pyskl - INFO - Saving checkpoint at 144 epochs +2025-05-29 16:14:52,128 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 16:14:52,184 - pyskl - INFO - +top1_acc 0.9465 +top5_acc 0.9965 +2025-05-29 16:14:52,184 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 16:14:52,191 - pyskl - INFO - +mean_acc 0.9242 +2025-05-29 16:14:52,193 - pyskl - INFO - Epoch(val) [144][533] top1_acc: 0.9465, top5_acc: 0.9965, mean_class_accuracy: 0.9242 +2025-05-29 16:15:51,441 - pyskl - INFO - Epoch [145][100/1281] lr: 9.605e-05, eta: 0:51:16, time: 0.592, data_time: 0.173, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9175, loss: 0.9175 +2025-05-29 16:16:33,198 - pyskl - INFO - Epoch [145][200/1281] lr: 9.353e-05, eta: 0:50:36, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8945, loss: 0.8945 +2025-05-29 16:17:15,126 - pyskl - INFO - Epoch [145][300/1281] lr: 9.106e-05, eta: 0:49:55, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8915, loss: 0.8915 +2025-05-29 16:17:56,979 - pyskl - INFO - Epoch [145][400/1281] lr: 8.861e-05, eta: 0:49:15, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9381, loss: 0.9381 +2025-05-29 16:18:38,701 - pyskl - INFO - Epoch [145][500/1281] lr: 8.620e-05, eta: 0:48:34, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9445, loss: 0.9445 +2025-05-29 16:19:20,373 - pyskl - INFO - Epoch [145][600/1281] lr: 8.382e-05, eta: 0:47:54, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8784, loss: 0.8784 +2025-05-29 16:20:02,005 - pyskl - INFO - Epoch [145][700/1281] lr: 8.147e-05, eta: 0:47:13, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9123, loss: 0.9123 +2025-05-29 16:20:43,854 - pyskl - INFO - Epoch [145][800/1281] lr: 7.916e-05, eta: 0:46:33, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8978, loss: 0.8978 +2025-05-29 16:21:25,620 - pyskl - INFO - Epoch [145][900/1281] lr: 7.688e-05, eta: 0:45:52, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9193, loss: 0.9193 +2025-05-29 16:22:07,604 - pyskl - INFO - Epoch [145][1000/1281] lr: 7.463e-05, eta: 0:45:12, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9273, loss: 0.9273 +2025-05-29 16:22:49,382 - pyskl - INFO - Epoch [145][1100/1281] lr: 7.242e-05, eta: 0:44:31, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8934, loss: 0.8934 +2025-05-29 16:23:31,158 - pyskl - INFO - Epoch [145][1200/1281] lr: 7.024e-05, eta: 0:43:51, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8956, loss: 0.8956 +2025-05-29 16:24:05,597 - pyskl - INFO - Saving checkpoint at 145 epochs +2025-05-29 16:37:06,110 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 16:37:06,166 - pyskl - INFO - +top1_acc 0.9436 +top5_acc 0.9972 +2025-05-29 16:37:06,166 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 16:37:06,173 - pyskl - INFO - +mean_acc 0.9202 +2025-05-29 16:37:06,175 - pyskl - INFO - Epoch(val) [145][533] top1_acc: 0.9436, top5_acc: 0.9972, mean_class_accuracy: 0.9202 +2025-05-29 16:38:05,880 - pyskl - INFO - Epoch [146][100/1281] lr: 6.638e-05, eta: 0:42:37, time: 0.597, data_time: 0.178, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8913, loss: 0.8913 +2025-05-29 16:38:47,586 - pyskl - INFO - Epoch [146][200/1281] lr: 6.429e-05, eta: 0:41:56, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9189, loss: 0.9189 +2025-05-29 16:39:29,520 - pyskl - INFO - Epoch [146][300/1281] lr: 6.224e-05, eta: 0:41:16, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9219, loss: 0.9219 +2025-05-29 16:40:11,274 - pyskl - INFO - Epoch [146][400/1281] lr: 6.022e-05, eta: 0:40:35, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8888, loss: 0.8888 +2025-05-29 16:40:52,914 - pyskl - INFO - Epoch [146][500/1281] lr: 5.823e-05, eta: 0:39:55, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8831, loss: 0.8831 +2025-05-29 16:41:34,578 - pyskl - INFO - Epoch [146][600/1281] lr: 5.628e-05, eta: 0:39:14, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8937, loss: 0.8937 +2025-05-29 16:42:16,294 - pyskl - INFO - Epoch [146][700/1281] lr: 5.436e-05, eta: 0:38:34, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8806, loss: 0.8806 +2025-05-29 16:42:57,941 - pyskl - INFO - Epoch [146][800/1281] lr: 5.247e-05, eta: 0:37:53, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9136, loss: 0.9136 +2025-05-29 16:43:39,662 - pyskl - INFO - Epoch [146][900/1281] lr: 5.061e-05, eta: 0:37:13, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9162, loss: 0.9162 +2025-05-29 16:44:21,402 - pyskl - INFO - Epoch [146][1000/1281] lr: 4.879e-05, eta: 0:36:32, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8843, loss: 0.8843 +2025-05-29 16:45:03,294 - pyskl - INFO - Epoch [146][1100/1281] lr: 4.701e-05, eta: 0:35:52, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9040, loss: 0.9040 +2025-05-29 16:45:45,155 - pyskl - INFO - Epoch [146][1200/1281] lr: 4.525e-05, eta: 0:35:11, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8938, loss: 0.8938 +2025-05-29 16:46:19,607 - pyskl - INFO - Saving checkpoint at 146 epochs +2025-05-29 16:47:00,194 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 16:47:00,250 - pyskl - INFO - +top1_acc 0.9384 +top5_acc 0.9966 +2025-05-29 16:47:00,250 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 16:47:00,258 - pyskl - INFO - +mean_acc 0.9122 +2025-05-29 16:47:00,260 - pyskl - INFO - Epoch(val) [146][533] top1_acc: 0.9384, top5_acc: 0.9966, mean_class_accuracy: 0.9122 +2025-05-29 16:48:00,897 - pyskl - INFO - Epoch [147][100/1281] lr: 4.216e-05, eta: 0:33:57, time: 0.606, data_time: 0.174, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9046, loss: 0.9046 +2025-05-29 16:48:44,060 - pyskl - INFO - Epoch [147][200/1281] lr: 4.050e-05, eta: 0:33:17, time: 0.432, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9299, loss: 0.9299 +2025-05-29 16:49:26,042 - pyskl - INFO - Epoch [147][300/1281] lr: 3.887e-05, eta: 0:32:36, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8961, loss: 0.8961 +2025-05-29 16:50:08,065 - pyskl - INFO - Epoch [147][400/1281] lr: 3.728e-05, eta: 0:31:56, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9221, loss: 0.9221 +2025-05-29 16:50:49,875 - pyskl - INFO - Epoch [147][500/1281] lr: 3.572e-05, eta: 0:31:15, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8937, loss: 0.8937 +2025-05-29 16:51:31,674 - pyskl - INFO - Epoch [147][600/1281] lr: 3.419e-05, eta: 0:30:35, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8732, loss: 0.8732 +2025-05-29 16:52:13,624 - pyskl - INFO - Epoch [147][700/1281] lr: 3.270e-05, eta: 0:29:54, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9073, loss: 0.9073 +2025-05-29 16:52:55,549 - pyskl - INFO - Epoch [147][800/1281] lr: 3.124e-05, eta: 0:29:14, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8596, loss: 0.8596 +2025-05-29 16:53:37,952 - pyskl - INFO - Epoch [147][900/1281] lr: 2.981e-05, eta: 0:28:33, time: 0.424, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9071, loss: 0.9071 +2025-05-29 16:54:19,873 - pyskl - INFO - Epoch [147][1000/1281] lr: 2.842e-05, eta: 0:27:53, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8795, loss: 0.8795 +2025-05-29 16:55:01,918 - pyskl - INFO - Epoch [147][1100/1281] lr: 2.706e-05, eta: 0:27:12, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8927, loss: 0.8927 +2025-05-29 16:55:44,060 - pyskl - INFO - Epoch [147][1200/1281] lr: 2.573e-05, eta: 0:26:31, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9301, loss: 0.9301 +2025-05-29 16:56:18,492 - pyskl - INFO - Saving checkpoint at 147 epochs +2025-05-29 16:56:59,088 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 16:56:59,144 - pyskl - INFO - +top1_acc 0.9455 +top5_acc 0.9971 +2025-05-29 16:56:59,144 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 16:56:59,151 - pyskl - INFO - +mean_acc 0.9240 +2025-05-29 16:56:59,153 - pyskl - INFO - Epoch(val) [147][533] top1_acc: 0.9455, top5_acc: 0.9971, mean_class_accuracy: 0.9240 +2025-05-29 16:57:58,555 - pyskl - INFO - Epoch [148][100/1281] lr: 2.341e-05, eta: 0:25:18, time: 0.594, data_time: 0.175, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.8987, loss: 0.8987 +2025-05-29 16:58:40,535 - pyskl - INFO - Epoch [148][200/1281] lr: 2.218e-05, eta: 0:24:37, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9006, loss: 0.9006 +2025-05-29 16:59:22,577 - pyskl - INFO - Epoch [148][300/1281] lr: 2.098e-05, eta: 0:23:57, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9189, loss: 0.9189 +2025-05-29 17:00:04,475 - pyskl - INFO - Epoch [148][400/1281] lr: 1.981e-05, eta: 0:23:16, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9203, loss: 0.9203 +2025-05-29 17:00:46,214 - pyskl - INFO - Epoch [148][500/1281] lr: 1.868e-05, eta: 0:22:36, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9026, loss: 0.9026 +2025-05-29 17:01:27,946 - pyskl - INFO - Epoch [148][600/1281] lr: 1.758e-05, eta: 0:21:55, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.8685, loss: 0.8685 +2025-05-29 17:02:09,669 - pyskl - INFO - Epoch [148][700/1281] lr: 1.651e-05, eta: 0:21:15, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9128, loss: 0.9128 +2025-05-29 17:02:51,368 - pyskl - INFO - Epoch [148][800/1281] lr: 1.548e-05, eta: 0:20:34, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8922, loss: 0.8922 +2025-05-29 17:03:32,956 - pyskl - INFO - Epoch [148][900/1281] lr: 1.448e-05, eta: 0:19:53, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9000, loss: 0.9000 +2025-05-29 17:04:14,566 - pyskl - INFO - Epoch [148][1000/1281] lr: 1.351e-05, eta: 0:19:13, time: 0.416, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9109, loss: 0.9109 +2025-05-29 17:04:56,501 - pyskl - INFO - Epoch [148][1100/1281] lr: 1.258e-05, eta: 0:18:32, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9106, loss: 0.9106 +2025-05-29 17:05:38,639 - pyskl - INFO - Epoch [148][1200/1281] lr: 1.168e-05, eta: 0:17:52, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8990, loss: 0.8990 +2025-05-29 17:06:13,167 - pyskl - INFO - Saving checkpoint at 148 epochs +2025-05-29 17:06:53,670 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 17:06:53,727 - pyskl - INFO - +top1_acc 0.9426 +top5_acc 0.9967 +2025-05-29 17:06:53,727 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 17:06:53,734 - pyskl - INFO - +mean_acc 0.9180 +2025-05-29 17:06:53,736 - pyskl - INFO - Epoch(val) [148][533] top1_acc: 0.9426, top5_acc: 0.9967, mean_class_accuracy: 0.9180 +2025-05-29 17:07:53,171 - pyskl - INFO - Epoch [149][100/1281] lr: 1.013e-05, eta: 0:16:38, time: 0.594, data_time: 0.175, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9178, loss: 0.9178 +2025-05-29 17:08:34,902 - pyskl - INFO - Epoch [149][200/1281] lr: 9.328e-06, eta: 0:15:58, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9394, loss: 0.9394 +2025-05-29 17:09:16,865 - pyskl - INFO - Epoch [149][300/1281] lr: 8.555e-06, eta: 0:15:17, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9376, loss: 0.9376 +2025-05-29 17:09:58,705 - pyskl - INFO - Epoch [149][400/1281] lr: 7.816e-06, eta: 0:14:37, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9106, loss: 0.9106 +2025-05-29 17:10:40,399 - pyskl - INFO - Epoch [149][500/1281] lr: 7.110e-06, eta: 0:13:56, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9471, loss: 0.9471 +2025-05-29 17:11:22,124 - pyskl - INFO - Epoch [149][600/1281] lr: 6.437e-06, eta: 0:13:15, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9143, loss: 0.9143 +2025-05-29 17:12:03,817 - pyskl - INFO - Epoch [149][700/1281] lr: 5.798e-06, eta: 0:12:35, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8853, loss: 0.8853 +2025-05-29 17:12:45,641 - pyskl - INFO - Epoch [149][800/1281] lr: 5.192e-06, eta: 0:11:54, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9064, loss: 0.9064 +2025-05-29 17:13:27,372 - pyskl - INFO - Epoch [149][900/1281] lr: 4.620e-06, eta: 0:11:14, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9087, loss: 0.9087 +2025-05-29 17:14:09,247 - pyskl - INFO - Epoch [149][1000/1281] lr: 4.081e-06, eta: 0:10:33, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9222, loss: 0.9222 +2025-05-29 17:14:51,655 - pyskl - INFO - Epoch [149][1100/1281] lr: 3.576e-06, eta: 0:09:53, time: 0.424, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.8858, loss: 0.8858 +2025-05-29 17:15:33,584 - pyskl - INFO - Epoch [149][1200/1281] lr: 3.104e-06, eta: 0:09:12, time: 0.419, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9130, loss: 0.9130 +2025-05-29 17:16:07,878 - pyskl - INFO - Saving checkpoint at 149 epochs +2025-05-29 17:16:48,535 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 17:16:48,595 - pyskl - INFO - +top1_acc 0.9436 +top5_acc 0.9968 +2025-05-29 17:16:48,595 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 17:16:48,602 - pyskl - INFO - +mean_acc 0.9194 +2025-05-29 17:16:48,604 - pyskl - INFO - Epoch(val) [149][533] top1_acc: 0.9436, top5_acc: 0.9968, mean_class_accuracy: 0.9194 +2025-05-29 17:17:47,901 - pyskl - INFO - Epoch [150][100/1281] lr: 2.334e-06, eta: 0:07:59, time: 0.593, data_time: 0.176, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.9352, loss: 0.9352 +2025-05-29 17:18:29,586 - pyskl - INFO - Epoch [150][200/1281] lr: 1.956e-06, eta: 0:07:18, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8976, loss: 0.8976 +2025-05-29 17:19:11,413 - pyskl - INFO - Epoch [150][300/1281] lr: 1.611e-06, eta: 0:06:37, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9100, loss: 0.9100 +2025-05-29 17:19:53,232 - pyskl - INFO - Epoch [150][400/1281] lr: 1.300e-06, eta: 0:05:57, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9107, loss: 0.9107 +2025-05-29 17:20:34,934 - pyskl - INFO - Epoch [150][500/1281] lr: 1.022e-06, eta: 0:05:16, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9281, loss: 0.9281 +2025-05-29 17:21:16,756 - pyskl - INFO - Epoch [150][600/1281] lr: 7.771e-07, eta: 0:04:36, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8971, loss: 0.8971 +2025-05-29 17:21:58,594 - pyskl - INFO - Epoch [150][700/1281] lr: 5.659e-07, eta: 0:03:55, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9038, loss: 0.9038 +2025-05-29 17:22:40,369 - pyskl - INFO - Epoch [150][800/1281] lr: 3.881e-07, eta: 0:03:15, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9044, loss: 0.9044 +2025-05-29 17:23:22,162 - pyskl - INFO - Epoch [150][900/1281] lr: 2.438e-07, eta: 0:02:34, time: 0.418, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8974, loss: 0.8974 +2025-05-29 17:24:03,910 - pyskl - INFO - Epoch [150][1000/1281] lr: 1.329e-07, eta: 0:01:53, time: 0.417, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.8944, loss: 0.8944 +2025-05-29 17:24:45,954 - pyskl - INFO - Epoch [150][1100/1281] lr: 5.534e-08, eta: 0:01:13, time: 0.420, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9338, loss: 0.9338 +2025-05-29 17:25:28,077 - pyskl - INFO - Epoch [150][1200/1281] lr: 1.123e-08, eta: 0:00:32, time: 0.421, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.9246, loss: 0.9246 +2025-05-29 17:26:02,608 - pyskl - INFO - Saving checkpoint at 150 epochs +2025-05-29 17:26:43,591 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-29 17:26:43,648 - pyskl - INFO - +top1_acc 0.9386 +top5_acc 0.9966 +2025-05-29 17:26:43,648 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-29 17:26:43,656 - pyskl - INFO - +mean_acc 0.9092 +2025-05-29 17:26:43,658 - pyskl - INFO - Epoch(val) [150][533] top1_acc: 0.9386, top5_acc: 0.9966, mean_class_accuracy: 0.9092 +2025-05-29 17:26:48,138 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-05-29 17:31:34,795 - pyskl - INFO - Testing results of the last checkpoint +2025-05-29 17:31:34,795 - pyskl - INFO - top1_acc: 0.9410 +2025-05-29 17:31:34,795 - pyskl - INFO - top5_acc: 0.9974 +2025-05-29 17:31:34,795 - pyskl - INFO - mean_class_accuracy: 0.9140 +2025-05-29 17:31:34,796 - pyskl - INFO - load checkpoint from local path: ./work_dirs/finegym/k_2/best_top1_acc_epoch_128.pth +2025-05-29 17:36:23,284 - pyskl - INFO - Testing results of the best checkpoint +2025-05-29 17:36:23,284 - pyskl - INFO - top1_acc: 0.9500 +2025-05-29 17:36:23,284 - pyskl - INFO - top5_acc: 0.9968 +2025-05-29 17:36:23,284 - pyskl - INFO - mean_class_accuracy: 0.9275