diff --git "a/finegym/km/20250505_070600.log" "b/finegym/km/20250505_070600.log" new file mode 100644--- /dev/null +++ "b/finegym/km/20250505_070600.log" @@ -0,0 +1,3484 @@ +2025-05-05 07:06:00,356 - 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+ +------------------------------------------------------------ + +2025-05-05 07:06:00,595 - pyskl - INFO - Config: modality = 'km' +graph = 'coco_new' +work_dir = './work_dirs/finegym/km' +model = dict( + type='RecognizerGCN', + backbone=dict( + type='GCN_Module_LLM', + llm_model='gpt4o', + 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/km', + interval_epoch=10, + weight_1=0.2, + weight_2=0.5)) +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=['km']), + 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=['km']), + 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=['km']), + 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=['km']), + 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=['km']), + 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=['km']), + 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) + +2025-05-05 07:06:00,595 - pyskl - INFO - Set random seed to 786155011, deterministic: False +2025-05-05 07:06:08,287 - pyskl - INFO - 20484 videos remain after valid thresholding +2025-05-05 07:06:10,336 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-05-05 07:06:10,342 - pyskl - INFO - Start running, host: lhd@zkyd, work_dir: /home/lhd/pyskl/work_dirs/finegym/km +2025-05-05 07:06:10,342 - 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 + -------------------- +2025-05-05 07:06:10,342 - pyskl - INFO - workflow: [('train', 1)], max: 150 epochs +2025-05-05 07:06:10,342 - pyskl - INFO - Checkpoints will be saved to /home/lhd/pyskl/work_dirs/finegym/km by HardDiskBackend. +2025-05-05 07:07:10,727 - pyskl - INFO - Epoch [1][100/1281] lr: 2.500e-02, eta: 1 day, 8:12:41, time: 0.604, data_time: 0.185, memory: 8997, top1_acc: 0.0519, top5_acc: 0.2075, loss_cls: 10.9726, loss: 10.9726 +2025-05-05 07:07:51,677 - pyskl - INFO - Epoch [1][200/1281] lr: 2.500e-02, eta: 1 day, 3:00:51, time: 0.409, data_time: 0.000, memory: 8997, top1_acc: 0.0737, top5_acc: 0.2625, loss_cls: 10.3771, loss: 10.3771 +2025-05-05 07:08:32,556 - pyskl - INFO - Epoch [1][300/1281] lr: 2.500e-02, eta: 1 day, 1:15:41, time: 0.409, data_time: 0.000, memory: 8997, top1_acc: 0.0813, top5_acc: 0.3038, loss_cls: 10.1021, loss: 10.1021 +2025-05-05 07:09:20,907 - pyskl - INFO - Epoch [1][400/1281] lr: 2.500e-02, eta: 1 day, 1:22:28, time: 0.484, data_time: 0.000, memory: 8997, top1_acc: 0.0887, top5_acc: 0.3137, loss_cls: 9.8857, loss: 9.8857 +2025-05-05 07:10:17,731 - pyskl - INFO - Epoch [1][500/1281] lr: 2.500e-02, eta: 1 day, 2:20:20, time: 0.568, data_time: 0.000, memory: 8997, top1_acc: 0.1219, top5_acc: 0.3581, loss_cls: 9.6078, loss: 9.6078 +2025-05-05 07:11:17,373 - pyskl - INFO - Epoch [1][600/1281] lr: 2.500e-02, eta: 1 day, 3:13:36, time: 0.596, data_time: 0.000, memory: 8997, top1_acc: 0.1319, top5_acc: 0.4188, loss_cls: 9.2970, loss: 9.2970 +2025-05-05 07:12:17,685 - pyskl - INFO - Epoch [1][700/1281] lr: 2.500e-02, eta: 1 day, 3:54:25, time: 0.603, data_time: 0.000, memory: 8997, top1_acc: 0.1363, top5_acc: 0.4344, loss_cls: 9.0949, loss: 9.0949 +2025-05-05 07:13:17,222 - pyskl - INFO - Epoch [1][800/1281] lr: 2.500e-02, eta: 1 day, 4:21:41, time: 0.595, data_time: 0.000, memory: 8997, top1_acc: 0.1525, top5_acc: 0.4788, loss_cls: 8.8835, loss: 8.8835 +2025-05-05 07:14:18,118 - pyskl - INFO - Epoch [1][900/1281] lr: 2.500e-02, eta: 1 day, 4:47:29, time: 0.609, data_time: 0.000, memory: 8997, top1_acc: 0.2025, top5_acc: 0.5138, loss_cls: 8.5928, loss: 8.5928 +2025-05-05 07:15:20,212 - pyskl - INFO - Epoch [1][1000/1281] lr: 2.500e-02, eta: 1 day, 5:11:45, time: 0.621, data_time: 0.000, memory: 8997, top1_acc: 0.2238, top5_acc: 0.5600, loss_cls: 8.3360, loss: 8.3360 +2025-05-05 07:16:23,276 - pyskl - INFO - Epoch [1][1100/1281] lr: 2.500e-02, eta: 1 day, 5:34:13, time: 0.631, data_time: 0.000, memory: 8997, top1_acc: 0.2487, top5_acc: 0.5787, loss_cls: 8.0248, loss: 8.0248 +2025-05-05 07:17:23,396 - pyskl - INFO - Epoch [1][1200/1281] lr: 2.500e-02, eta: 1 day, 5:44:57, time: 0.601, data_time: 0.000, memory: 8997, top1_acc: 0.2550, top5_acc: 0.6025, loss_cls: 7.8326, loss: 7.8326 +2025-05-05 07:18:12,940 - pyskl - INFO - Saving checkpoint at 1 epochs +2025-05-05 07:19:04,996 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 07:19:05,049 - pyskl - INFO - +top1_acc 0.2835 +top5_acc 0.6417 +2025-05-05 07:19:05,049 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 07:19:05,056 - pyskl - INFO - +mean_acc 0.1252 +2025-05-05 07:19:06,755 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_1.pth. +2025-05-05 07:19:06,755 - pyskl - INFO - Best top1_acc is 0.2835 at 1 epoch. +2025-05-05 07:19:06,759 - pyskl - INFO - Epoch(val) [1][533] top1_acc: 0.2835, top5_acc: 0.6417, mean_class_accuracy: 0.1252 +2025-05-05 07:20:16,197 - pyskl - INFO - Epoch [2][100/1281] lr: 2.500e-02, eta: 1 day, 4:29:23, time: 0.694, data_time: 0.180, memory: 8997, top1_acc: 0.2994, top5_acc: 0.6825, loss_cls: 7.4584, loss: 7.4584 +2025-05-05 07:21:15,360 - pyskl - INFO - Epoch [2][200/1281] lr: 2.500e-02, eta: 1 day, 4:40:05, time: 0.592, data_time: 0.000, memory: 8997, top1_acc: 0.3556, top5_acc: 0.7519, loss_cls: 6.9087, loss: 6.9087 +2025-05-05 07:22:14,631 - pyskl - INFO - Epoch [2][300/1281] lr: 2.500e-02, eta: 1 day, 4:49:30, time: 0.593, data_time: 0.000, memory: 8997, top1_acc: 0.3806, top5_acc: 0.7662, loss_cls: 6.8252, loss: 6.8252 +2025-05-05 07:23:15,541 - pyskl - INFO - Epoch [2][400/1281] lr: 2.500e-02, eta: 1 day, 5:00:47, time: 0.609, data_time: 0.000, memory: 8997, top1_acc: 0.4031, top5_acc: 0.7975, loss_cls: 6.4246, loss: 6.4246 +2025-05-05 07:24:18,986 - pyskl - INFO - Epoch [2][500/1281] lr: 2.499e-02, eta: 1 day, 5:15:13, time: 0.634, data_time: 0.000, memory: 8997, top1_acc: 0.4356, top5_acc: 0.8287, loss_cls: 6.2306, loss: 6.2306 +2025-05-05 07:25:21,023 - pyskl - INFO - Epoch [2][600/1281] lr: 2.499e-02, eta: 1 day, 5:25:36, time: 0.620, data_time: 0.000, memory: 8997, top1_acc: 0.4594, top5_acc: 0.8187, loss_cls: 6.1119, loss: 6.1119 +2025-05-05 07:26:20,861 - pyskl - INFO - Epoch [2][700/1281] lr: 2.499e-02, eta: 1 day, 5:31:20, time: 0.598, data_time: 0.000, memory: 8997, top1_acc: 0.4669, top5_acc: 0.8269, loss_cls: 6.0535, loss: 6.0535 +2025-05-05 07:27:19,985 - pyskl - INFO - Epoch [2][800/1281] lr: 2.499e-02, eta: 1 day, 5:35:20, time: 0.591, data_time: 0.000, memory: 8997, top1_acc: 0.4725, top5_acc: 0.8588, loss_cls: 5.9444, loss: 5.9444 +2025-05-05 07:28:22,342 - pyskl - INFO - Epoch [2][900/1281] lr: 2.499e-02, eta: 1 day, 5:43:34, time: 0.624, data_time: 0.000, memory: 8997, top1_acc: 0.4875, top5_acc: 0.8644, loss_cls: 5.8259, loss: 5.8259 +2025-05-05 07:29:25,747 - pyskl - INFO - Epoch [2][1000/1281] lr: 2.499e-02, eta: 1 day, 5:52:26, time: 0.634, data_time: 0.000, memory: 8997, top1_acc: 0.5044, top5_acc: 0.8838, loss_cls: 5.6625, loss: 5.6625 +2025-05-05 07:30:26,954 - pyskl - INFO - Epoch [2][1100/1281] lr: 2.499e-02, eta: 1 day, 5:57:33, time: 0.612, data_time: 0.000, memory: 8997, top1_acc: 0.4819, top5_acc: 0.8838, loss_cls: 5.7528, loss: 5.7528 +2025-05-05 07:31:25,858 - pyskl - INFO - Epoch [2][1200/1281] lr: 2.499e-02, eta: 1 day, 5:59:14, time: 0.589, data_time: 0.000, memory: 8997, top1_acc: 0.5106, top5_acc: 0.8956, loss_cls: 5.6309, loss: 5.6309 +2025-05-05 07:32:14,799 - pyskl - INFO - Saving checkpoint at 2 epochs +2025-05-05 07:33:06,740 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 07:33:06,795 - pyskl - INFO - +top1_acc 0.4795 +top5_acc 0.8649 +2025-05-05 07:33:06,795 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 07:33:06,802 - pyskl - INFO - +mean_acc 0.2956 +2025-05-05 07:33:06,858 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_1.pth was removed +2025-05-05 07:33:08,432 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_2.pth. +2025-05-05 07:33:08,433 - pyskl - INFO - Best top1_acc is 0.4795 at 2 epoch. +2025-05-05 07:33:08,437 - pyskl - INFO - Epoch(val) [2][533] top1_acc: 0.4795, top5_acc: 0.8649, mean_class_accuracy: 0.2956 +2025-05-05 07:34:17,928 - pyskl - INFO - Epoch [3][100/1281] lr: 2.499e-02, eta: 1 day, 5:17:44, time: 0.695, data_time: 0.183, memory: 8997, top1_acc: 0.5369, top5_acc: 0.9175, loss_cls: 5.4334, loss: 5.4334 +2025-05-05 07:35:17,319 - pyskl - INFO - Epoch [3][200/1281] lr: 2.499e-02, eta: 1 day, 5:21:05, time: 0.594, data_time: 0.000, memory: 8997, top1_acc: 0.5406, top5_acc: 0.9125, loss_cls: 5.3533, loss: 5.3533 +2025-05-05 07:36:19,353 - pyskl - INFO - Epoch [3][300/1281] lr: 2.499e-02, eta: 1 day, 5:27:01, time: 0.620, data_time: 0.000, memory: 8997, top1_acc: 0.5619, top5_acc: 0.9263, loss_cls: 5.2875, loss: 5.2875 +2025-05-05 07:37:23,119 - pyskl - INFO - Epoch [3][400/1281] lr: 2.499e-02, eta: 1 day, 5:34:21, time: 0.638, data_time: 0.000, memory: 8997, top1_acc: 0.5600, top5_acc: 0.9225, loss_cls: 5.2708, loss: 5.2708 +2025-05-05 07:38:28,437 - pyskl - INFO - Epoch [3][500/1281] lr: 2.498e-02, eta: 1 day, 5:42:43, time: 0.653, data_time: 0.000, memory: 8997, top1_acc: 0.5875, top5_acc: 0.9356, loss_cls: 5.0555, loss: 5.0555 +2025-05-05 07:39:32,569 - pyskl - INFO - Epoch [3][600/1281] lr: 2.498e-02, eta: 1 day, 5:49:18, time: 0.641, data_time: 0.000, memory: 8997, top1_acc: 0.5613, top5_acc: 0.9356, loss_cls: 5.0482, loss: 5.0482 +2025-05-05 07:40:32,462 - pyskl - INFO - Epoch [3][700/1281] lr: 2.498e-02, eta: 1 day, 5:51:20, time: 0.599, data_time: 0.000, memory: 8997, top1_acc: 0.5906, top5_acc: 0.9456, loss_cls: 5.0843, loss: 5.0843 +2025-05-05 07:41:33,781 - pyskl - INFO - Epoch [3][800/1281] lr: 2.498e-02, eta: 1 day, 5:54:31, time: 0.613, data_time: 0.000, memory: 8997, top1_acc: 0.5881, top5_acc: 0.9406, loss_cls: 5.0420, loss: 5.0420 +2025-05-05 07:42:36,984 - pyskl - INFO - Epoch [3][900/1281] lr: 2.498e-02, eta: 1 day, 5:59:11, time: 0.632, data_time: 0.000, memory: 8997, top1_acc: 0.6000, top5_acc: 0.9331, loss_cls: 5.0189, loss: 5.0189 +2025-05-05 07:43:40,422 - pyskl - INFO - Epoch [3][1000/1281] lr: 2.498e-02, eta: 1 day, 6:03:43, time: 0.634, data_time: 0.000, memory: 8997, top1_acc: 0.5931, top5_acc: 0.9350, loss_cls: 5.0381, loss: 5.0381 +2025-05-05 07:44:44,131 - pyskl - INFO - Epoch [3][1100/1281] lr: 2.498e-02, eta: 1 day, 6:08:11, time: 0.637, data_time: 0.000, memory: 8997, top1_acc: 0.6106, top5_acc: 0.9419, loss_cls: 4.9119, loss: 4.9119 +2025-05-05 07:45:46,533 - pyskl - INFO - Epoch [3][1200/1281] lr: 2.498e-02, eta: 1 day, 6:11:16, time: 0.624, data_time: 0.000, memory: 8997, top1_acc: 0.6150, top5_acc: 0.9419, loss_cls: 4.8943, loss: 4.8943 +2025-05-05 07:46:38,382 - pyskl - INFO - Saving checkpoint at 3 epochs +2025-05-05 07:47:31,848 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 07:47:31,905 - pyskl - INFO - +top1_acc 0.5956 +top5_acc 0.9380 +2025-05-05 07:47:31,905 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 07:47:31,912 - pyskl - INFO - +mean_acc 0.4136 +2025-05-05 07:47:31,971 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_2.pth was removed +2025-05-05 07:47:33,539 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_3.pth. +2025-05-05 07:47:33,540 - pyskl - INFO - Best top1_acc is 0.5956 at 3 epoch. +2025-05-05 07:47:33,543 - pyskl - INFO - Epoch(val) [3][533] top1_acc: 0.5956, top5_acc: 0.9380, mean_class_accuracy: 0.4136 +2025-05-05 07:48:44,432 - pyskl - INFO - Epoch [4][100/1281] lr: 2.497e-02, eta: 1 day, 5:42:51, time: 0.709, data_time: 0.183, memory: 8997, top1_acc: 0.6356, top5_acc: 0.9537, loss_cls: 4.6942, loss: 4.6942 +2025-05-05 07:49:41,866 - pyskl - INFO - Epoch [4][200/1281] lr: 2.497e-02, eta: 1 day, 5:42:22, time: 0.574, data_time: 0.000, memory: 8997, top1_acc: 0.6375, top5_acc: 0.9594, loss_cls: 4.6549, loss: 4.6549 +2025-05-05 07:50:40,669 - pyskl - INFO - Epoch [4][300/1281] lr: 2.497e-02, eta: 1 day, 5:42:54, time: 0.588, data_time: 0.000, memory: 8997, top1_acc: 0.6600, top5_acc: 0.9650, loss_cls: 4.5986, loss: 4.5986 +2025-05-05 07:51:42,866 - pyskl - INFO - Epoch [4][400/1281] lr: 2.497e-02, eta: 1 day, 5:45:51, time: 0.622, data_time: 0.000, memory: 8997, top1_acc: 0.6494, top5_acc: 0.9537, loss_cls: 4.6703, loss: 4.6703 +2025-05-05 07:52:46,982 - pyskl - INFO - Epoch [4][500/1281] lr: 2.497e-02, eta: 1 day, 5:50:01, time: 0.641, data_time: 0.000, memory: 8997, top1_acc: 0.6256, top5_acc: 0.9631, loss_cls: 4.7257, loss: 4.7257 +2025-05-05 07:53:50,689 - pyskl - INFO - Epoch [4][600/1281] lr: 2.497e-02, eta: 1 day, 5:53:39, time: 0.637, data_time: 0.000, memory: 8997, top1_acc: 0.6362, top5_acc: 0.9594, loss_cls: 4.6555, loss: 4.6555 +2025-05-05 07:54:54,020 - pyskl - INFO - Epoch [4][700/1281] lr: 2.497e-02, eta: 1 day, 5:56:49, time: 0.633, data_time: 0.000, memory: 8997, top1_acc: 0.6544, top5_acc: 0.9631, loss_cls: 4.5786, loss: 4.5786 +2025-05-05 07:55:56,453 - pyskl - INFO - Epoch [4][800/1281] lr: 2.496e-02, eta: 1 day, 5:59:12, time: 0.624, data_time: 0.000, memory: 8997, top1_acc: 0.6488, top5_acc: 0.9581, loss_cls: 4.5803, loss: 4.5803 +2025-05-05 07:57:02,280 - pyskl - INFO - Epoch [4][900/1281] lr: 2.496e-02, eta: 1 day, 6:03:41, time: 0.658, data_time: 0.000, memory: 8997, top1_acc: 0.6813, top5_acc: 0.9706, loss_cls: 4.4010, loss: 4.4010 +2025-05-05 07:58:06,563 - pyskl - INFO - Epoch [4][1000/1281] lr: 2.496e-02, eta: 1 day, 6:06:56, time: 0.643, data_time: 0.000, memory: 8997, top1_acc: 0.6681, top5_acc: 0.9600, loss_cls: 4.5307, loss: 4.5307 +2025-05-05 07:59:07,383 - pyskl - INFO - Epoch [4][1100/1281] lr: 2.496e-02, eta: 1 day, 6:07:49, time: 0.608, data_time: 0.000, memory: 8997, top1_acc: 0.6719, top5_acc: 0.9575, loss_cls: 4.4443, loss: 4.4443 +2025-05-05 08:00:06,969 - pyskl - INFO - Epoch [4][1200/1281] lr: 2.496e-02, eta: 1 day, 6:07:52, time: 0.596, data_time: 0.000, memory: 8997, top1_acc: 0.6819, top5_acc: 0.9631, loss_cls: 4.4234, loss: 4.4234 +2025-05-05 08:00:57,817 - pyskl - INFO - Saving checkpoint at 4 epochs +2025-05-05 08:01:51,506 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 08:01:51,564 - pyskl - INFO - +top1_acc 0.6314 +top5_acc 0.9481 +2025-05-05 08:01:51,564 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 08:01:51,571 - pyskl - INFO - +mean_acc 0.4984 +2025-05-05 08:01:51,628 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_3.pth was removed +2025-05-05 08:01:53,186 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_4.pth. +2025-05-05 08:01:53,187 - pyskl - INFO - Best top1_acc is 0.6314 at 4 epoch. +2025-05-05 08:01:53,192 - pyskl - INFO - Epoch(val) [4][533] top1_acc: 0.6314, top5_acc: 0.9481, mean_class_accuracy: 0.4984 +2025-05-05 08:03:03,712 - pyskl - INFO - Epoch [5][100/1281] lr: 2.495e-02, eta: 1 day, 5:45:36, time: 0.705, data_time: 0.181, memory: 8999, top1_acc: 0.6856, top5_acc: 0.9706, loss_cls: 4.4516, loss: 4.4516 +2025-05-05 08:04:07,219 - pyskl - INFO - Epoch [5][200/1281] lr: 2.495e-02, eta: 1 day, 5:48:16, time: 0.635, data_time: 0.000, memory: 8999, top1_acc: 0.6675, top5_acc: 0.9725, loss_cls: 4.4483, loss: 4.4483 +2025-05-05 08:05:10,357 - pyskl - INFO - Epoch [5][300/1281] lr: 2.495e-02, eta: 1 day, 5:50:35, time: 0.631, data_time: 0.000, memory: 8999, top1_acc: 0.6713, top5_acc: 0.9644, loss_cls: 4.5288, loss: 4.5288 +2025-05-05 08:06:15,348 - pyskl - INFO - Epoch [5][400/1281] lr: 2.495e-02, eta: 1 day, 5:53:49, time: 0.650, data_time: 0.000, memory: 8999, top1_acc: 0.7019, top5_acc: 0.9663, loss_cls: 4.3529, loss: 4.3529 +2025-05-05 08:07:18,858 - pyskl - INFO - Epoch [5][500/1281] lr: 2.495e-02, eta: 1 day, 5:56:05, time: 0.635, data_time: 0.000, memory: 8999, top1_acc: 0.6969, top5_acc: 0.9700, loss_cls: 4.2272, loss: 4.2272 +2025-05-05 08:08:19,840 - pyskl - INFO - Epoch [5][600/1281] lr: 2.495e-02, eta: 1 day, 5:56:52, time: 0.610, data_time: 0.000, memory: 8999, top1_acc: 0.7006, top5_acc: 0.9569, loss_cls: 4.3695, loss: 4.3695 +2025-05-05 08:09:20,482 - pyskl - INFO - Epoch [5][700/1281] lr: 2.494e-02, eta: 1 day, 5:57:24, time: 0.606, data_time: 0.000, memory: 8999, top1_acc: 0.6931, top5_acc: 0.9706, loss_cls: 4.3757, loss: 4.3757 +2025-05-05 08:10:22,733 - pyskl - INFO - Epoch [5][800/1281] lr: 2.494e-02, eta: 1 day, 5:58:43, time: 0.623, data_time: 0.000, memory: 8999, top1_acc: 0.6913, top5_acc: 0.9744, loss_cls: 4.3101, loss: 4.3101 +2025-05-05 08:11:25,299 - pyskl - INFO - Epoch [5][900/1281] lr: 2.494e-02, eta: 1 day, 6:00:08, time: 0.626, data_time: 0.000, memory: 8999, top1_acc: 0.6994, top5_acc: 0.9769, loss_cls: 4.2398, loss: 4.2398 +2025-05-05 08:12:29,353 - pyskl - INFO - Epoch [5][1000/1281] lr: 2.494e-02, eta: 1 day, 6:02:13, time: 0.641, data_time: 0.000, memory: 8999, top1_acc: 0.7069, top5_acc: 0.9750, loss_cls: 4.1067, loss: 4.1067 +2025-05-05 08:13:38,275 - pyskl - INFO - Epoch [5][1100/1281] lr: 2.494e-02, eta: 1 day, 6:06:37, time: 0.689, data_time: 0.000, memory: 8999, top1_acc: 0.7037, top5_acc: 0.9700, loss_cls: 4.2806, loss: 4.2806 +2025-05-05 08:14:44,617 - pyskl - INFO - Epoch [5][1200/1281] lr: 2.493e-02, eta: 1 day, 6:09:35, time: 0.663, data_time: 0.000, memory: 8999, top1_acc: 0.7144, top5_acc: 0.9712, loss_cls: 4.2369, loss: 4.2369 +2025-05-05 08:15:38,505 - pyskl - INFO - Saving checkpoint at 5 epochs +2025-05-05 08:16:31,314 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 08:16:31,372 - pyskl - INFO - +top1_acc 0.6922 +top5_acc 0.9593 +2025-05-05 08:16:31,373 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 08:16:31,380 - pyskl - INFO - +mean_acc 0.5573 +2025-05-05 08:16:31,443 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_4.pth was removed +2025-05-05 08:16:33,039 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_5.pth. +2025-05-05 08:16:33,040 - pyskl - INFO - Best top1_acc is 0.6922 at 5 epoch. +2025-05-05 08:16:33,043 - pyskl - INFO - Epoch(val) [5][533] top1_acc: 0.6922, top5_acc: 0.9593, mean_class_accuracy: 0.5573 +2025-05-05 08:17:41,480 - pyskl - INFO - Epoch [6][100/1281] lr: 2.493e-02, eta: 1 day, 5:50:04, time: 0.684, data_time: 0.183, memory: 8999, top1_acc: 0.7312, top5_acc: 0.9762, loss_cls: 4.1465, loss: 4.1465 +2025-05-05 08:18:38,980 - pyskl - INFO - Epoch [6][200/1281] lr: 2.493e-02, eta: 1 day, 5:48:56, time: 0.575, data_time: 0.000, memory: 8999, top1_acc: 0.7444, top5_acc: 0.9762, loss_cls: 4.0849, loss: 4.0849 +2025-05-05 08:19:40,727 - pyskl - INFO - Epoch [6][300/1281] lr: 2.492e-02, eta: 1 day, 5:49:46, time: 0.617, data_time: 0.000, memory: 8999, top1_acc: 0.6950, top5_acc: 0.9750, loss_cls: 4.1888, loss: 4.1888 +2025-05-05 08:20:44,481 - pyskl - INFO - Epoch [6][400/1281] lr: 2.492e-02, eta: 1 day, 5:51:27, time: 0.638, data_time: 0.000, memory: 8999, top1_acc: 0.7356, top5_acc: 0.9812, loss_cls: 4.1969, loss: 4.1969 +2025-05-05 08:21:46,153 - pyskl - INFO - Epoch [6][500/1281] lr: 2.492e-02, eta: 1 day, 5:52:08, time: 0.617, data_time: 0.000, memory: 8999, top1_acc: 0.7362, top5_acc: 0.9738, loss_cls: 4.0828, loss: 4.0828 +2025-05-05 08:22:50,757 - pyskl - INFO - Epoch [6][600/1281] lr: 2.492e-02, eta: 1 day, 5:54:03, time: 0.646, data_time: 0.000, memory: 8999, top1_acc: 0.7438, top5_acc: 0.9812, loss_cls: 3.9564, loss: 3.9564 +2025-05-05 08:23:55,093 - pyskl - INFO - Epoch [6][700/1281] lr: 2.492e-02, eta: 1 day, 5:55:47, time: 0.643, data_time: 0.000, memory: 8999, top1_acc: 0.7306, top5_acc: 0.9831, loss_cls: 4.0223, loss: 4.0223 +2025-05-05 08:25:00,150 - pyskl - INFO - Epoch [6][800/1281] lr: 2.491e-02, eta: 1 day, 5:57:44, time: 0.651, data_time: 0.000, memory: 8999, top1_acc: 0.7288, top5_acc: 0.9769, loss_cls: 4.0199, loss: 4.0199 +2025-05-05 08:26:03,258 - pyskl - INFO - Epoch [6][900/1281] lr: 2.491e-02, eta: 1 day, 5:58:46, time: 0.631, data_time: 0.000, memory: 8999, top1_acc: 0.7362, top5_acc: 0.9731, loss_cls: 4.1608, loss: 4.1608 +2025-05-05 08:27:03,845 - pyskl - INFO - Epoch [6][1000/1281] lr: 2.491e-02, eta: 1 day, 5:58:43, time: 0.606, data_time: 0.000, memory: 8999, top1_acc: 0.7494, top5_acc: 0.9844, loss_cls: 3.9974, loss: 3.9974 +2025-05-05 08:28:03,789 - pyskl - INFO - Epoch [6][1100/1281] lr: 2.491e-02, eta: 1 day, 5:58:22, time: 0.599, data_time: 0.000, memory: 8999, top1_acc: 0.7362, top5_acc: 0.9775, loss_cls: 4.0515, loss: 4.0515 +2025-05-05 08:29:07,473 - pyskl - INFO - Epoch [6][1200/1281] lr: 2.490e-02, eta: 1 day, 5:59:31, time: 0.637, data_time: 0.000, memory: 8999, top1_acc: 0.7319, top5_acc: 0.9794, loss_cls: 4.0676, loss: 4.0676 +2025-05-05 08:30:00,369 - pyskl - INFO - Saving checkpoint at 6 epochs +2025-05-05 08:30:51,102 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 08:30:51,160 - pyskl - INFO - +top1_acc 0.6994 +top5_acc 0.9695 +2025-05-05 08:30:51,161 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 08:30:51,169 - pyskl - INFO - +mean_acc 0.5769 +2025-05-05 08:30:51,226 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_5.pth was removed +2025-05-05 08:30:52,787 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_6.pth. +2025-05-05 08:30:52,788 - pyskl - INFO - Best top1_acc is 0.6994 at 6 epoch. +2025-05-05 08:30:52,792 - pyskl - INFO - Epoch(val) [6][533] top1_acc: 0.6994, top5_acc: 0.9695, mean_class_accuracy: 0.5769 +2025-05-05 08:32:00,862 - pyskl - INFO - Epoch [7][100/1281] lr: 2.490e-02, eta: 1 day, 5:42:49, time: 0.681, data_time: 0.183, memory: 8999, top1_acc: 0.7531, top5_acc: 0.9806, loss_cls: 3.9098, loss: 3.9098 +2025-05-05 08:33:02,202 - pyskl - INFO - Epoch [7][200/1281] lr: 2.490e-02, eta: 1 day, 5:43:09, time: 0.613, data_time: 0.000, memory: 8999, top1_acc: 0.7512, top5_acc: 0.9806, loss_cls: 4.0104, loss: 4.0104 +2025-05-05 08:34:08,019 - pyskl - INFO - Epoch [7][300/1281] lr: 2.489e-02, eta: 1 day, 5:45:09, time: 0.658, data_time: 0.000, memory: 8999, top1_acc: 0.7500, top5_acc: 0.9800, loss_cls: 3.8653, loss: 3.8653 +2025-05-05 08:35:11,493 - pyskl - INFO - Epoch [7][400/1281] lr: 2.489e-02, eta: 1 day, 5:46:12, time: 0.635, data_time: 0.000, memory: 8999, top1_acc: 0.7631, top5_acc: 0.9794, loss_cls: 3.8410, loss: 3.8410 +2025-05-05 08:36:12,983 - pyskl - INFO - Epoch [7][500/1281] lr: 2.489e-02, eta: 1 day, 5:46:27, time: 0.615, data_time: 0.000, memory: 8999, top1_acc: 0.7638, top5_acc: 0.9856, loss_cls: 3.8353, loss: 3.8353 +2025-05-05 08:37:13,533 - pyskl - INFO - Epoch [7][600/1281] lr: 2.489e-02, eta: 1 day, 5:46:20, time: 0.605, data_time: 0.000, memory: 8999, top1_acc: 0.7531, top5_acc: 0.9794, loss_cls: 3.9174, loss: 3.9174 +2025-05-05 08:38:18,087 - pyskl - INFO - Epoch [7][700/1281] lr: 2.488e-02, eta: 1 day, 5:47:38, time: 0.646, data_time: 0.000, memory: 8999, top1_acc: 0.7588, top5_acc: 0.9844, loss_cls: 3.9084, loss: 3.9084 +2025-05-05 08:39:22,179 - pyskl - INFO - Epoch [7][800/1281] lr: 2.488e-02, eta: 1 day, 5:48:44, time: 0.641, data_time: 0.000, memory: 8999, top1_acc: 0.7575, top5_acc: 0.9825, loss_cls: 3.9126, loss: 3.9126 +2025-05-05 08:40:24,075 - pyskl - INFO - Epoch [7][900/1281] lr: 2.488e-02, eta: 1 day, 5:48:59, time: 0.619, data_time: 0.000, memory: 8999, top1_acc: 0.7550, top5_acc: 0.9744, loss_cls: 3.9361, loss: 3.9361 +2025-05-05 08:41:24,267 - pyskl - INFO - Epoch [7][1000/1281] lr: 2.487e-02, eta: 1 day, 5:48:37, time: 0.602, data_time: 0.000, memory: 8999, top1_acc: 0.7344, top5_acc: 0.9681, loss_cls: 4.0271, loss: 4.0271 +2025-05-05 08:42:27,767 - pyskl - INFO - Epoch [7][1100/1281] lr: 2.487e-02, eta: 1 day, 5:49:23, time: 0.635, data_time: 0.000, memory: 8999, top1_acc: 0.7550, top5_acc: 0.9831, loss_cls: 3.7814, loss: 3.7814 +2025-05-05 08:43:35,011 - pyskl - INFO - Epoch [7][1200/1281] lr: 2.487e-02, eta: 1 day, 5:51:24, time: 0.672, data_time: 0.000, memory: 8999, top1_acc: 0.7431, top5_acc: 0.9869, loss_cls: 3.8401, loss: 3.8401 +2025-05-05 08:44:26,552 - pyskl - INFO - Saving checkpoint at 7 epochs +2025-05-05 08:45:17,485 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 08:45:17,542 - pyskl - INFO - +top1_acc 0.7105 +top5_acc 0.9624 +2025-05-05 08:45:17,542 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 08:45:17,550 - pyskl - INFO - +mean_acc 0.5700 +2025-05-05 08:45:17,612 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_6.pth was removed +2025-05-05 08:45:19,143 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_7.pth. +2025-05-05 08:45:19,143 - pyskl - INFO - Best top1_acc is 0.7105 at 7 epoch. +2025-05-05 08:45:19,148 - pyskl - INFO - Epoch(val) [7][533] top1_acc: 0.7105, top5_acc: 0.9624, mean_class_accuracy: 0.5700 +2025-05-05 08:46:26,926 - pyskl - INFO - Epoch [8][100/1281] lr: 2.486e-02, eta: 1 day, 5:36:43, time: 0.678, data_time: 0.183, memory: 8999, top1_acc: 0.7975, top5_acc: 0.9919, loss_cls: 3.6976, loss: 3.6976 +2025-05-05 08:47:27,053 - pyskl - INFO - Epoch [8][200/1281] lr: 2.486e-02, eta: 1 day, 5:36:22, time: 0.601, data_time: 0.000, memory: 8999, top1_acc: 0.7650, top5_acc: 0.9838, loss_cls: 3.8355, loss: 3.8355 +2025-05-05 08:48:30,644 - pyskl - INFO - Epoch [8][300/1281] lr: 2.486e-02, eta: 1 day, 5:37:10, time: 0.636, data_time: 0.000, memory: 8999, top1_acc: 0.7706, top5_acc: 0.9825, loss_cls: 3.8475, loss: 3.8475 +2025-05-05 08:49:31,963 - pyskl - INFO - Epoch [8][400/1281] lr: 2.485e-02, eta: 1 day, 5:37:10, time: 0.613, data_time: 0.000, memory: 8999, top1_acc: 0.7669, top5_acc: 0.9819, loss_cls: 3.9117, loss: 3.9117 +2025-05-05 08:50:33,742 - pyskl - INFO - Epoch [8][500/1281] lr: 2.485e-02, eta: 1 day, 5:37:18, time: 0.618, data_time: 0.000, memory: 8999, top1_acc: 0.7562, top5_acc: 0.9831, loss_cls: 3.8740, loss: 3.8740 +2025-05-05 08:51:35,043 - pyskl - INFO - Epoch [8][600/1281] lr: 2.485e-02, eta: 1 day, 5:37:16, time: 0.613, data_time: 0.000, memory: 8999, top1_acc: 0.7562, top5_acc: 0.9869, loss_cls: 3.8236, loss: 3.8236 +2025-05-05 08:52:40,311 - pyskl - INFO - Epoch [8][700/1281] lr: 2.484e-02, eta: 1 day, 5:38:27, time: 0.653, data_time: 0.000, memory: 8999, top1_acc: 0.7806, top5_acc: 0.9812, loss_cls: 3.9031, loss: 3.9031 +2025-05-05 08:53:42,980 - pyskl - INFO - Epoch [8][800/1281] lr: 2.484e-02, eta: 1 day, 5:38:47, time: 0.627, data_time: 0.000, memory: 8999, top1_acc: 0.7769, top5_acc: 0.9850, loss_cls: 3.7357, loss: 3.7357 +2025-05-05 08:54:43,675 - pyskl - INFO - Epoch [8][900/1281] lr: 2.484e-02, eta: 1 day, 5:38:28, time: 0.607, data_time: 0.000, memory: 8999, top1_acc: 0.7931, top5_acc: 0.9856, loss_cls: 3.7045, loss: 3.7045 +2025-05-05 08:55:43,186 - pyskl - INFO - Epoch [8][1000/1281] lr: 2.483e-02, eta: 1 day, 5:37:47, time: 0.595, data_time: 0.000, memory: 8999, top1_acc: 0.7575, top5_acc: 0.9788, loss_cls: 3.9078, loss: 3.9078 +2025-05-05 08:56:46,697 - pyskl - INFO - Epoch [8][1100/1281] lr: 2.483e-02, eta: 1 day, 5:38:19, time: 0.635, data_time: 0.000, memory: 8999, top1_acc: 0.7731, top5_acc: 0.9838, loss_cls: 3.7572, loss: 3.7572 +2025-05-05 08:57:51,110 - pyskl - INFO - Epoch [8][1200/1281] lr: 2.483e-02, eta: 1 day, 5:39:04, time: 0.644, data_time: 0.000, memory: 8999, top1_acc: 0.7831, top5_acc: 0.9850, loss_cls: 3.6891, loss: 3.6891 +2025-05-05 08:58:41,948 - pyskl - INFO - Saving checkpoint at 8 epochs +2025-05-05 08:59:32,764 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 08:59:32,822 - pyskl - INFO - +top1_acc 0.7251 +top5_acc 0.9720 +2025-05-05 08:59:32,822 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 08:59:32,829 - pyskl - INFO - +mean_acc 0.6383 +2025-05-05 08:59:32,894 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_7.pth was removed +2025-05-05 08:59:34,593 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_8.pth. +2025-05-05 08:59:34,594 - pyskl - INFO - Best top1_acc is 0.7251 at 8 epoch. +2025-05-05 08:59:34,597 - pyskl - INFO - Epoch(val) [8][533] top1_acc: 0.7251, top5_acc: 0.9720, mean_class_accuracy: 0.6383 +2025-05-05 09:00:42,879 - pyskl - INFO - Epoch [9][100/1281] lr: 2.482e-02, eta: 1 day, 5:26:12, time: 0.683, data_time: 0.183, memory: 8999, top1_acc: 0.7606, top5_acc: 0.9850, loss_cls: 3.7824, loss: 3.7824 +2025-05-05 09:01:45,151 - pyskl - INFO - Epoch [9][200/1281] lr: 2.482e-02, eta: 1 day, 5:26:23, time: 0.623, data_time: 0.000, memory: 8999, top1_acc: 0.7875, top5_acc: 0.9838, loss_cls: 3.6926, loss: 3.6926 +2025-05-05 09:02:47,643 - pyskl - INFO - Epoch [9][300/1281] lr: 2.481e-02, eta: 1 day, 5:26:36, time: 0.625, data_time: 0.000, memory: 8999, top1_acc: 0.7831, top5_acc: 0.9844, loss_cls: 3.6605, loss: 3.6605 +2025-05-05 09:03:48,174 - pyskl - INFO - Epoch [9][400/1281] lr: 2.481e-02, eta: 1 day, 5:26:15, time: 0.605, data_time: 0.000, memory: 8999, top1_acc: 0.7963, top5_acc: 0.9856, loss_cls: 3.5956, loss: 3.5956 +2025-05-05 09:04:49,264 - pyskl - INFO - Epoch [9][500/1281] lr: 2.481e-02, eta: 1 day, 5:26:02, time: 0.611, data_time: 0.000, memory: 8999, top1_acc: 0.7788, top5_acc: 0.9838, loss_cls: 3.7106, loss: 3.7106 +2025-05-05 09:05:51,348 - pyskl - INFO - Epoch [9][600/1281] lr: 2.480e-02, eta: 1 day, 5:26:05, time: 0.621, data_time: 0.000, memory: 8999, top1_acc: 0.8087, top5_acc: 0.9881, loss_cls: 3.6256, loss: 3.6256 +2025-05-05 09:06:56,475 - pyskl - INFO - Epoch [9][700/1281] lr: 2.480e-02, eta: 1 day, 5:26:57, time: 0.651, data_time: 0.000, memory: 8999, top1_acc: 0.7681, top5_acc: 0.9869, loss_cls: 3.7004, loss: 3.7004 +2025-05-05 09:07:59,267 - pyskl - INFO - Epoch [9][800/1281] lr: 2.480e-02, eta: 1 day, 5:27:09, time: 0.628, data_time: 0.000, memory: 8999, top1_acc: 0.7825, top5_acc: 0.9875, loss_cls: 3.7297, loss: 3.7297 +2025-05-05 09:09:00,150 - pyskl - INFO - Epoch [9][900/1281] lr: 2.479e-02, eta: 1 day, 5:26:48, time: 0.609, data_time: 0.000, memory: 8999, top1_acc: 0.7963, top5_acc: 0.9819, loss_cls: 3.6940, loss: 3.6940 +2025-05-05 09:10:00,869 - pyskl - INFO - Epoch [9][1000/1281] lr: 2.479e-02, eta: 1 day, 5:26:24, time: 0.607, data_time: 0.000, memory: 8999, top1_acc: 0.7919, top5_acc: 0.9844, loss_cls: 3.5898, loss: 3.5898 +2025-05-05 09:11:05,822 - pyskl - INFO - Epoch [9][1100/1281] lr: 2.479e-02, eta: 1 day, 5:27:07, time: 0.650, data_time: 0.000, memory: 8999, top1_acc: 0.8013, top5_acc: 0.9844, loss_cls: 3.6285, loss: 3.6285 +2025-05-05 09:12:09,558 - pyskl - INFO - Epoch [9][1200/1281] lr: 2.478e-02, eta: 1 day, 5:27:29, time: 0.637, data_time: 0.000, memory: 8999, top1_acc: 0.7869, top5_acc: 0.9856, loss_cls: 3.6076, loss: 3.6076 +2025-05-05 09:12:59,102 - pyskl - INFO - Saving checkpoint at 9 epochs +2025-05-05 09:13:49,353 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 09:13:49,410 - pyskl - INFO - +top1_acc 0.7449 +top5_acc 0.9714 +2025-05-05 09:13:49,410 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 09:13:49,418 - pyskl - INFO - +mean_acc 0.6812 +2025-05-05 09:13:49,477 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_8.pth was removed +2025-05-05 09:13:51,055 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_9.pth. +2025-05-05 09:13:51,055 - pyskl - INFO - Best top1_acc is 0.7449 at 9 epoch. +2025-05-05 09:13:51,061 - pyskl - INFO - Epoch(val) [9][533] top1_acc: 0.7449, top5_acc: 0.9714, mean_class_accuracy: 0.6812 +2025-05-05 09:15:00,247 - pyskl - INFO - Epoch [10][100/1281] lr: 2.477e-02, eta: 1 day, 5:16:08, time: 0.692, data_time: 0.180, memory: 8999, top1_acc: 0.8006, top5_acc: 0.9931, loss_cls: 3.6005, loss: 3.6005 +2025-05-05 09:16:02,057 - pyskl - INFO - Epoch [10][200/1281] lr: 2.477e-02, eta: 1 day, 5:16:02, time: 0.618, data_time: 0.000, memory: 8999, top1_acc: 0.7944, top5_acc: 0.9881, loss_cls: 3.5608, loss: 3.5608 +2025-05-05 09:17:04,391 - pyskl - INFO - Epoch [10][300/1281] lr: 2.477e-02, eta: 1 day, 5:16:04, time: 0.623, data_time: 0.000, memory: 8999, top1_acc: 0.8106, top5_acc: 0.9875, loss_cls: 3.4419, loss: 3.4419 +2025-05-05 09:18:03,966 - pyskl - INFO - Epoch [10][400/1281] lr: 2.476e-02, eta: 1 day, 5:15:22, time: 0.596, data_time: 0.000, memory: 8999, top1_acc: 0.7963, top5_acc: 0.9912, loss_cls: 3.6136, loss: 3.6136 +2025-05-05 09:19:04,377 - pyskl - INFO - Epoch [10][500/1281] lr: 2.476e-02, eta: 1 day, 5:14:54, time: 0.604, data_time: 0.000, memory: 8999, top1_acc: 0.8050, top5_acc: 0.9844, loss_cls: 3.6363, loss: 3.6363 +2025-05-05 09:20:08,551 - pyskl - INFO - Epoch [10][600/1281] lr: 2.476e-02, eta: 1 day, 5:15:20, time: 0.642, data_time: 0.000, memory: 8999, top1_acc: 0.7775, top5_acc: 0.9812, loss_cls: 3.6847, loss: 3.6847 +2025-05-05 09:21:11,809 - pyskl - INFO - Epoch [10][700/1281] lr: 2.475e-02, eta: 1 day, 5:15:31, time: 0.633, data_time: 0.000, memory: 8999, top1_acc: 0.8006, top5_acc: 0.9875, loss_cls: 3.6259, loss: 3.6259 +2025-05-05 09:22:13,248 - pyskl - INFO - Epoch [10][800/1281] lr: 2.475e-02, eta: 1 day, 5:15:15, time: 0.614, data_time: 0.000, memory: 8999, top1_acc: 0.8081, top5_acc: 0.9844, loss_cls: 3.6111, loss: 3.6111 +2025-05-05 09:23:13,613 - pyskl - INFO - Epoch [10][900/1281] lr: 2.474e-02, eta: 1 day, 5:14:42, time: 0.604, data_time: 0.000, memory: 8999, top1_acc: 0.7975, top5_acc: 0.9844, loss_cls: 3.7475, loss: 3.7475 +2025-05-05 09:24:14,943 - pyskl - INFO - Epoch [10][1000/1281] lr: 2.474e-02, eta: 1 day, 5:14:23, time: 0.613, data_time: 0.000, memory: 8999, top1_acc: 0.7987, top5_acc: 0.9881, loss_cls: 3.4823, loss: 3.4823 +2025-05-05 09:25:20,636 - pyskl - INFO - Epoch [10][1100/1281] lr: 2.473e-02, eta: 1 day, 5:15:05, time: 0.657, data_time: 0.000, memory: 8999, top1_acc: 0.7994, top5_acc: 0.9900, loss_cls: 3.6419, loss: 3.6419 +2025-05-05 09:26:23,075 - pyskl - INFO - Epoch [10][1200/1281] lr: 2.473e-02, eta: 1 day, 5:15:00, time: 0.624, data_time: 0.000, memory: 8999, top1_acc: 0.7806, top5_acc: 0.9869, loss_cls: 3.6555, loss: 3.6555 +2025-05-05 09:27:12,367 - pyskl - INFO - Saving checkpoint at 10 epochs +2025-05-05 09:28:02,266 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 09:28:02,323 - pyskl - INFO - +top1_acc 0.7536 +top5_acc 0.9770 +2025-05-05 09:28:02,323 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 09:28:02,331 - pyskl - INFO - +mean_acc 0.6634 +2025-05-05 09:28:02,395 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_9.pth was removed +2025-05-05 09:28:03,974 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_10.pth. +2025-05-05 09:28:03,974 - pyskl - INFO - Best top1_acc is 0.7536 at 10 epoch. +2025-05-05 09:28:03,978 - pyskl - INFO - Epoch(val) [10][533] top1_acc: 0.7536, top5_acc: 0.9770, mean_class_accuracy: 0.6634 +2025-05-05 09:29:13,501 - pyskl - INFO - Epoch [11][100/1281] lr: 2.472e-02, eta: 1 day, 5:04:44, time: 0.695, data_time: 0.182, memory: 8999, top1_acc: 0.8137, top5_acc: 0.9931, loss_cls: 3.3698, loss: 3.3698 +2025-05-05 09:30:14,393 - pyskl - INFO - Epoch [11][200/1281] lr: 2.472e-02, eta: 1 day, 5:04:20, time: 0.609, data_time: 0.000, memory: 8999, top1_acc: 0.8000, top5_acc: 0.9894, loss_cls: 3.4820, loss: 3.4820 +2025-05-05 09:31:16,288 - pyskl - INFO - Epoch [11][300/1281] lr: 2.471e-02, eta: 1 day, 5:04:09, time: 0.619, data_time: 0.000, memory: 8999, top1_acc: 0.8013, top5_acc: 0.9831, loss_cls: 3.5495, loss: 3.5495 +2025-05-05 09:32:18,022 - pyskl - INFO - Epoch [11][400/1281] lr: 2.471e-02, eta: 1 day, 5:03:55, time: 0.617, data_time: 0.000, memory: 8999, top1_acc: 0.8000, top5_acc: 0.9875, loss_cls: 3.5559, loss: 3.5559 +2025-05-05 09:33:22,201 - pyskl - INFO - Epoch [11][500/1281] lr: 2.471e-02, eta: 1 day, 5:04:13, time: 0.642, data_time: 0.000, memory: 8999, top1_acc: 0.8125, top5_acc: 0.9875, loss_cls: 3.5098, loss: 3.5098 +2025-05-05 09:34:28,552 - pyskl - INFO - Epoch [11][600/1281] lr: 2.470e-02, eta: 1 day, 5:04:59, time: 0.664, data_time: 0.000, memory: 8999, top1_acc: 0.8013, top5_acc: 0.9875, loss_cls: 3.4943, loss: 3.4943 +2025-05-05 09:35:32,074 - pyskl - INFO - Epoch [11][700/1281] lr: 2.470e-02, eta: 1 day, 5:05:06, time: 0.635, data_time: 0.000, memory: 8999, top1_acc: 0.8075, top5_acc: 0.9888, loss_cls: 3.6207, loss: 3.6207 +2025-05-05 09:36:34,115 - pyskl - INFO - Epoch [11][800/1281] lr: 2.469e-02, eta: 1 day, 5:04:52, time: 0.620, data_time: 0.000, memory: 8999, top1_acc: 0.7825, top5_acc: 0.9900, loss_cls: 3.6330, loss: 3.6330 +2025-05-05 09:37:34,226 - pyskl - INFO - Epoch [11][900/1281] lr: 2.469e-02, eta: 1 day, 5:04:13, time: 0.601, data_time: 0.000, memory: 8999, top1_acc: 0.8250, top5_acc: 0.9906, loss_cls: 3.3687, loss: 3.3687 +2025-05-05 09:38:38,348 - pyskl - INFO - Epoch [11][1000/1281] lr: 2.468e-02, eta: 1 day, 5:04:25, time: 0.641, data_time: 0.000, memory: 8999, top1_acc: 0.7937, top5_acc: 0.9881, loss_cls: 3.5525, loss: 3.5525 +2025-05-05 09:39:42,741 - pyskl - INFO - Epoch [11][1100/1281] lr: 2.468e-02, eta: 1 day, 5:04:39, time: 0.644, data_time: 0.000, memory: 8999, top1_acc: 0.8019, top5_acc: 0.9906, loss_cls: 3.5068, loss: 3.5068 +2025-05-05 09:40:44,001 - pyskl - INFO - Epoch [11][1200/1281] lr: 2.467e-02, eta: 1 day, 5:04:13, time: 0.613, data_time: 0.000, memory: 8999, top1_acc: 0.8187, top5_acc: 0.9869, loss_cls: 3.6435, loss: 3.6435 +2025-05-05 09:41:33,288 - pyskl - INFO - Saving checkpoint at 11 epochs +2025-05-05 09:42:25,227 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 09:42:25,282 - pyskl - INFO - +top1_acc 0.7404 +top5_acc 0.9736 +2025-05-05 09:42:25,283 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 09:42:25,289 - pyskl - INFO - +mean_acc 0.6547 +2025-05-05 09:42:25,292 - pyskl - INFO - Epoch(val) [11][533] top1_acc: 0.7404, top5_acc: 0.9736, mean_class_accuracy: 0.6547 +2025-05-05 09:43:39,022 - pyskl - INFO - Epoch [12][100/1281] lr: 2.467e-02, eta: 1 day, 4:55:37, time: 0.737, data_time: 0.183, memory: 8999, top1_acc: 0.8137, top5_acc: 0.9831, loss_cls: 3.5191, loss: 3.5191 +2025-05-05 09:44:41,319 - pyskl - INFO - Epoch [12][200/1281] lr: 2.466e-02, eta: 1 day, 4:55:26, time: 0.623, data_time: 0.000, memory: 8999, top1_acc: 0.8094, top5_acc: 0.9894, loss_cls: 3.4798, loss: 3.4798 +2025-05-05 09:45:40,086 - pyskl - INFO - Epoch [12][300/1281] lr: 2.466e-02, eta: 1 day, 4:54:30, time: 0.588, data_time: 0.000, memory: 8999, top1_acc: 0.8056, top5_acc: 0.9900, loss_cls: 3.5741, loss: 3.5741 +2025-05-05 09:46:38,383 - pyskl - INFO - Epoch [12][400/1281] lr: 2.465e-02, eta: 1 day, 4:53:28, time: 0.583, data_time: 0.000, memory: 8999, top1_acc: 0.8125, top5_acc: 0.9900, loss_cls: 3.5167, loss: 3.5167 +2025-05-05 09:47:37,863 - pyskl - INFO - Epoch [12][500/1281] lr: 2.465e-02, eta: 1 day, 4:52:41, time: 0.595, data_time: 0.000, memory: 8999, top1_acc: 0.8131, top5_acc: 0.9919, loss_cls: 3.4467, loss: 3.4467 +2025-05-05 09:48:40,828 - pyskl - INFO - Epoch [12][600/1281] lr: 2.464e-02, eta: 1 day, 4:52:36, time: 0.630, data_time: 0.000, memory: 8999, top1_acc: 0.8025, top5_acc: 0.9906, loss_cls: 3.4378, loss: 3.4378 +2025-05-05 09:49:40,843 - pyskl - INFO - Epoch [12][700/1281] lr: 2.464e-02, eta: 1 day, 4:51:55, time: 0.600, data_time: 0.000, memory: 8999, top1_acc: 0.8100, top5_acc: 0.9906, loss_cls: 3.4970, loss: 3.4970 +2025-05-05 09:50:40,438 - pyskl - INFO - Epoch [12][800/1281] lr: 2.463e-02, eta: 1 day, 4:51:08, time: 0.596, data_time: 0.000, memory: 8999, top1_acc: 0.8163, top5_acc: 0.9888, loss_cls: 3.4541, loss: 3.4541 +2025-05-05 09:51:44,544 - pyskl - INFO - Epoch [12][900/1281] lr: 2.463e-02, eta: 1 day, 4:51:14, time: 0.641, data_time: 0.000, memory: 8999, top1_acc: 0.8044, top5_acc: 0.9900, loss_cls: 3.5222, loss: 3.5222 +2025-05-05 09:52:52,376 - pyskl - INFO - Epoch [12][1000/1281] lr: 2.462e-02, eta: 1 day, 4:52:04, time: 0.678, data_time: 0.000, memory: 8999, top1_acc: 0.8056, top5_acc: 0.9931, loss_cls: 3.4721, loss: 3.4721 +2025-05-05 09:53:56,434 - pyskl - INFO - Epoch [12][1100/1281] lr: 2.462e-02, eta: 1 day, 4:52:07, time: 0.641, data_time: 0.000, memory: 8999, top1_acc: 0.7994, top5_acc: 0.9881, loss_cls: 3.5164, loss: 3.5164 +2025-05-05 09:54:56,952 - pyskl - INFO - Epoch [12][1200/1281] lr: 2.461e-02, eta: 1 day, 4:51:29, time: 0.605, data_time: 0.000, memory: 8999, top1_acc: 0.8113, top5_acc: 0.9856, loss_cls: 3.4904, loss: 3.4904 +2025-05-05 09:55:45,523 - pyskl - INFO - Saving checkpoint at 12 epochs +2025-05-05 09:56:36,172 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 09:56:36,228 - pyskl - INFO - +top1_acc 0.7690 +top5_acc 0.9795 +2025-05-05 09:56:36,228 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 09:56:36,235 - pyskl - INFO - +mean_acc 0.6934 +2025-05-05 09:56:36,295 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_10.pth was removed +2025-05-05 09:56:37,852 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_12.pth. +2025-05-05 09:56:37,853 - pyskl - INFO - Best top1_acc is 0.7690 at 12 epoch. +2025-05-05 09:56:37,857 - pyskl - INFO - Epoch(val) [12][533] top1_acc: 0.7690, top5_acc: 0.9795, mean_class_accuracy: 0.6934 +2025-05-05 09:57:48,345 - pyskl - INFO - Epoch [13][100/1281] lr: 2.460e-02, eta: 1 day, 4:42:54, time: 0.705, data_time: 0.179, memory: 8999, top1_acc: 0.8369, top5_acc: 0.9912, loss_cls: 3.2402, loss: 3.2402 +2025-05-05 09:58:47,973 - pyskl - INFO - Epoch [13][200/1281] lr: 2.460e-02, eta: 1 day, 4:42:08, time: 0.596, data_time: 0.000, memory: 8999, top1_acc: 0.8306, top5_acc: 0.9906, loss_cls: 3.2961, loss: 3.2961 +2025-05-05 09:59:48,922 - pyskl - INFO - Epoch [13][300/1281] lr: 2.459e-02, eta: 1 day, 4:41:37, time: 0.609, data_time: 0.000, memory: 8999, top1_acc: 0.8169, top5_acc: 0.9906, loss_cls: 3.3948, loss: 3.3948 +2025-05-05 10:00:49,269 - pyskl - INFO - Epoch [13][400/1281] lr: 2.459e-02, eta: 1 day, 4:40:59, time: 0.603, data_time: 0.000, memory: 8999, top1_acc: 0.8294, top5_acc: 0.9925, loss_cls: 3.3513, loss: 3.3513 +2025-05-05 10:01:52,697 - pyskl - INFO - Epoch [13][500/1281] lr: 2.458e-02, eta: 1 day, 4:40:54, time: 0.634, data_time: 0.000, memory: 8999, top1_acc: 0.8106, top5_acc: 0.9912, loss_cls: 3.4333, loss: 3.4333 +2025-05-05 10:02:57,614 - pyskl - INFO - Epoch [13][600/1281] lr: 2.458e-02, eta: 1 day, 4:41:06, time: 0.649, data_time: 0.000, memory: 8999, top1_acc: 0.8319, top5_acc: 0.9912, loss_cls: 3.4199, loss: 3.4199 +2025-05-05 10:04:00,321 - pyskl - INFO - Epoch [13][700/1281] lr: 2.457e-02, eta: 1 day, 4:40:52, time: 0.627, data_time: 0.000, memory: 8999, top1_acc: 0.8094, top5_acc: 0.9912, loss_cls: 3.4433, loss: 3.4433 +2025-05-05 10:05:00,786 - pyskl - INFO - Epoch [13][800/1281] lr: 2.457e-02, eta: 1 day, 4:40:13, time: 0.605, data_time: 0.000, memory: 8999, top1_acc: 0.7981, top5_acc: 0.9875, loss_cls: 3.5053, loss: 3.5053 +2025-05-05 10:06:03,862 - pyskl - INFO - Epoch [13][900/1281] lr: 2.456e-02, eta: 1 day, 4:40:02, time: 0.631, data_time: 0.000, memory: 8999, top1_acc: 0.8119, top5_acc: 0.9881, loss_cls: 3.4209, loss: 3.4209 +2025-05-05 10:07:10,133 - pyskl - INFO - Epoch [13][1000/1281] lr: 2.455e-02, eta: 1 day, 4:40:25, time: 0.663, data_time: 0.000, memory: 8999, top1_acc: 0.8150, top5_acc: 0.9881, loss_cls: 3.3663, loss: 3.3663 +2025-05-05 10:08:13,467 - pyskl - INFO - Epoch [13][1100/1281] lr: 2.455e-02, eta: 1 day, 4:40:15, time: 0.633, data_time: 0.000, memory: 8999, top1_acc: 0.8087, top5_acc: 0.9900, loss_cls: 3.5212, loss: 3.5212 +2025-05-05 10:09:13,854 - pyskl - INFO - Epoch [13][1200/1281] lr: 2.454e-02, eta: 1 day, 4:39:34, time: 0.604, data_time: 0.000, memory: 8999, top1_acc: 0.8256, top5_acc: 0.9894, loss_cls: 3.2294, loss: 3.2294 +2025-05-05 10:10:03,385 - pyskl - INFO - Saving checkpoint at 13 epochs +2025-05-05 10:10:56,910 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 10:10:56,965 - pyskl - INFO - +top1_acc 0.7734 +top5_acc 0.9748 +2025-05-05 10:10:56,965 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 10:10:56,972 - pyskl - INFO - +mean_acc 0.6825 +2025-05-05 10:10:57,032 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_12.pth was removed +2025-05-05 10:10:58,564 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_13.pth. +2025-05-05 10:10:58,564 - pyskl - INFO - Best top1_acc is 0.7734 at 13 epoch. +2025-05-05 10:10:58,568 - pyskl - INFO - Epoch(val) [13][533] top1_acc: 0.7734, top5_acc: 0.9748, mean_class_accuracy: 0.6825 +2025-05-05 10:12:11,590 - pyskl - INFO - Epoch [14][100/1281] lr: 2.453e-02, eta: 1 day, 4:31:59, time: 0.730, data_time: 0.184, memory: 8999, top1_acc: 0.8275, top5_acc: 0.9944, loss_cls: 3.3057, loss: 3.3057 +2025-05-05 10:13:10,263 - pyskl - INFO - Epoch [14][200/1281] lr: 2.453e-02, eta: 1 day, 4:31:01, time: 0.587, data_time: 0.000, memory: 8999, top1_acc: 0.8444, top5_acc: 0.9925, loss_cls: 3.2546, loss: 3.2546 +2025-05-05 10:14:07,826 - pyskl - INFO - Epoch [14][300/1281] lr: 2.452e-02, eta: 1 day, 4:29:52, time: 0.576, data_time: 0.000, memory: 8999, top1_acc: 0.8419, top5_acc: 0.9950, loss_cls: 3.3559, loss: 3.3559 +2025-05-05 10:15:06,714 - pyskl - INFO - Epoch [14][400/1281] lr: 2.452e-02, eta: 1 day, 4:28:57, time: 0.589, data_time: 0.000, memory: 8999, top1_acc: 0.8169, top5_acc: 0.9925, loss_cls: 3.3689, loss: 3.3689 +2025-05-05 10:16:08,407 - pyskl - INFO - Epoch [14][500/1281] lr: 2.451e-02, eta: 1 day, 4:28:30, time: 0.617, data_time: 0.000, memory: 8999, top1_acc: 0.8187, top5_acc: 0.9950, loss_cls: 3.2763, loss: 3.2763 +2025-05-05 10:17:09,887 - pyskl - INFO - Epoch [14][600/1281] lr: 2.451e-02, eta: 1 day, 4:28:01, time: 0.615, data_time: 0.000, memory: 8999, top1_acc: 0.8213, top5_acc: 0.9950, loss_cls: 3.3642, loss: 3.3642 +2025-05-05 10:18:08,513 - pyskl - INFO - Epoch [14][700/1281] lr: 2.450e-02, eta: 1 day, 4:27:03, time: 0.586, data_time: 0.000, memory: 8999, top1_acc: 0.8194, top5_acc: 0.9931, loss_cls: 3.4401, loss: 3.4401 +2025-05-05 10:19:04,960 - pyskl - INFO - Epoch [14][800/1281] lr: 2.449e-02, eta: 1 day, 4:25:43, time: 0.564, data_time: 0.000, memory: 8999, top1_acc: 0.8300, top5_acc: 0.9881, loss_cls: 3.3304, loss: 3.3304 +2025-05-05 10:20:03,586 - pyskl - INFO - Epoch [14][900/1281] lr: 2.449e-02, eta: 1 day, 4:24:45, time: 0.586, data_time: 0.000, memory: 8999, top1_acc: 0.8313, top5_acc: 0.9931, loss_cls: 3.2880, loss: 3.2880 +2025-05-05 10:21:08,309 - pyskl - INFO - Epoch [14][1000/1281] lr: 2.448e-02, eta: 1 day, 4:24:47, time: 0.647, data_time: 0.000, memory: 8999, top1_acc: 0.8137, top5_acc: 0.9881, loss_cls: 3.3655, loss: 3.3655 +2025-05-05 10:22:10,631 - pyskl - INFO - Epoch [14][1100/1281] lr: 2.448e-02, eta: 1 day, 4:24:25, time: 0.623, data_time: 0.000, memory: 8999, top1_acc: 0.8294, top5_acc: 0.9950, loss_cls: 3.3022, loss: 3.3022 +2025-05-05 10:23:11,151 - pyskl - INFO - Epoch [14][1200/1281] lr: 2.447e-02, eta: 1 day, 4:23:44, time: 0.605, data_time: 0.000, memory: 8999, top1_acc: 0.8231, top5_acc: 0.9881, loss_cls: 3.2913, loss: 3.2913 +2025-05-05 10:23:59,856 - pyskl - INFO - Saving checkpoint at 14 epochs +2025-05-05 10:24:51,333 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 10:24:51,388 - pyskl - INFO - +top1_acc 0.7651 +top5_acc 0.9778 +2025-05-05 10:24:51,389 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 10:24:51,395 - pyskl - INFO - +mean_acc 0.6939 +2025-05-05 10:24:51,397 - pyskl - INFO - Epoch(val) [14][533] top1_acc: 0.7651, top5_acc: 0.9778, mean_class_accuracy: 0.6939 +2025-05-05 10:26:03,557 - pyskl - INFO - Epoch [15][100/1281] lr: 2.446e-02, eta: 1 day, 4:16:30, time: 0.722, data_time: 0.181, memory: 8999, top1_acc: 0.8275, top5_acc: 0.9950, loss_cls: 3.3395, loss: 3.3395 +2025-05-05 10:27:03,521 - pyskl - INFO - Epoch [15][200/1281] lr: 2.445e-02, eta: 1 day, 4:15:46, time: 0.600, data_time: 0.000, memory: 8999, top1_acc: 0.8419, top5_acc: 0.9881, loss_cls: 3.2878, loss: 3.2878 +2025-05-05 10:28:03,535 - pyskl - INFO - Epoch [15][300/1281] lr: 2.445e-02, eta: 1 day, 4:15:02, time: 0.600, data_time: 0.000, memory: 8999, top1_acc: 0.8244, top5_acc: 0.9906, loss_cls: 3.4260, loss: 3.4260 +2025-05-05 10:29:03,757 - pyskl - INFO - Epoch [15][400/1281] lr: 2.444e-02, eta: 1 day, 4:14:20, time: 0.602, data_time: 0.000, memory: 8999, top1_acc: 0.8294, top5_acc: 0.9894, loss_cls: 3.4185, loss: 3.4185 +2025-05-05 10:30:09,461 - pyskl - INFO - Epoch [15][500/1281] lr: 2.444e-02, eta: 1 day, 4:14:30, time: 0.657, data_time: 0.000, memory: 8999, top1_acc: 0.8300, top5_acc: 0.9906, loss_cls: 3.2787, loss: 3.2787 +2025-05-05 10:31:13,617 - pyskl - INFO - Epoch [15][600/1281] lr: 2.443e-02, eta: 1 day, 4:14:24, time: 0.642, data_time: 0.000, memory: 8999, top1_acc: 0.8356, top5_acc: 0.9912, loss_cls: 3.2912, loss: 3.2912 +2025-05-05 10:32:16,088 - pyskl - INFO - Epoch [15][700/1281] lr: 2.442e-02, eta: 1 day, 4:14:02, time: 0.625, data_time: 0.000, memory: 8999, top1_acc: 0.8275, top5_acc: 0.9856, loss_cls: 3.3894, loss: 3.3894 +2025-05-05 10:33:18,112 - pyskl - INFO - Epoch [15][800/1281] lr: 2.442e-02, eta: 1 day, 4:13:35, time: 0.620, data_time: 0.000, memory: 8999, top1_acc: 0.8275, top5_acc: 0.9869, loss_cls: 3.3443, loss: 3.3443 +2025-05-05 10:34:22,806 - pyskl - INFO - Epoch [15][900/1281] lr: 2.441e-02, eta: 1 day, 4:13:32, time: 0.647, data_time: 0.000, memory: 8999, top1_acc: 0.8381, top5_acc: 0.9956, loss_cls: 3.2529, loss: 3.2529 +2025-05-05 10:35:27,446 - pyskl - INFO - Epoch [15][1000/1281] lr: 2.441e-02, eta: 1 day, 4:13:29, time: 0.646, data_time: 0.000, memory: 8999, top1_acc: 0.8319, top5_acc: 0.9931, loss_cls: 3.3053, loss: 3.3053 +2025-05-05 10:36:29,150 - pyskl - INFO - Epoch [15][1100/1281] lr: 2.440e-02, eta: 1 day, 4:12:58, time: 0.617, data_time: 0.000, memory: 8999, top1_acc: 0.8400, top5_acc: 0.9931, loss_cls: 3.2356, loss: 3.2356 +2025-05-05 10:37:29,060 - pyskl - INFO - Epoch [15][1200/1281] lr: 2.439e-02, eta: 1 day, 4:12:10, time: 0.599, data_time: 0.000, memory: 8999, top1_acc: 0.8337, top5_acc: 0.9900, loss_cls: 3.3138, loss: 3.3138 +2025-05-05 10:38:18,077 - pyskl - INFO - Saving checkpoint at 15 epochs +2025-05-05 10:39:10,669 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 10:39:10,724 - pyskl - INFO - +top1_acc 0.8039 +top5_acc 0.9856 +2025-05-05 10:39:10,724 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 10:39:10,731 - pyskl - INFO - +mean_acc 0.7383 +2025-05-05 10:39:10,787 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_13.pth was removed +2025-05-05 10:39:12,329 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_15.pth. +2025-05-05 10:39:12,330 - pyskl - INFO - Best top1_acc is 0.8039 at 15 epoch. +2025-05-05 10:39:12,334 - pyskl - INFO - Epoch(val) [15][533] top1_acc: 0.8039, top5_acc: 0.9856, mean_class_accuracy: 0.7383 +2025-05-05 10:40:22,812 - pyskl - INFO - Epoch [16][100/1281] lr: 2.438e-02, eta: 1 day, 4:05:04, time: 0.705, data_time: 0.186, memory: 8999, top1_acc: 0.8481, top5_acc: 0.9925, loss_cls: 3.2249, loss: 3.2249 +2025-05-05 10:41:23,612 - pyskl - INFO - Epoch [16][200/1281] lr: 2.438e-02, eta: 1 day, 4:04:26, time: 0.608, data_time: 0.000, memory: 8999, top1_acc: 0.8512, top5_acc: 0.9938, loss_cls: 3.2494, loss: 3.2494 +2025-05-05 10:42:25,933 - pyskl - INFO - Epoch [16][300/1281] lr: 2.437e-02, eta: 1 day, 4:04:01, time: 0.623, data_time: 0.000, memory: 8999, top1_acc: 0.8375, top5_acc: 0.9931, loss_cls: 3.2279, loss: 3.2279 +2025-05-05 10:43:28,839 - pyskl - INFO - Epoch [16][400/1281] lr: 2.436e-02, eta: 1 day, 4:03:41, time: 0.629, data_time: 0.000, memory: 8999, top1_acc: 0.8525, top5_acc: 0.9912, loss_cls: 3.3016, loss: 3.3016 +2025-05-05 10:44:35,574 - pyskl - INFO - Epoch [16][500/1281] lr: 2.436e-02, eta: 1 day, 4:03:54, time: 0.667, data_time: 0.000, memory: 8999, top1_acc: 0.8294, top5_acc: 0.9944, loss_cls: 3.2966, loss: 3.2966 +2025-05-05 10:45:38,345 - pyskl - INFO - Epoch [16][600/1281] lr: 2.435e-02, eta: 1 day, 4:03:32, time: 0.628, data_time: 0.000, memory: 8999, top1_acc: 0.8519, top5_acc: 0.9919, loss_cls: 3.3303, loss: 3.3303 +2025-05-05 10:46:39,670 - pyskl - INFO - Epoch [16][700/1281] lr: 2.434e-02, eta: 1 day, 4:02:57, time: 0.613, data_time: 0.000, memory: 8999, top1_acc: 0.8562, top5_acc: 0.9962, loss_cls: 3.2087, loss: 3.2087 +2025-05-05 10:47:40,307 - pyskl - INFO - Epoch [16][800/1281] lr: 2.434e-02, eta: 1 day, 4:02:16, time: 0.606, data_time: 0.000, memory: 8999, top1_acc: 0.8381, top5_acc: 0.9919, loss_cls: 3.2743, loss: 3.2743 +2025-05-05 10:48:45,002 - pyskl - INFO - Epoch [16][900/1281] lr: 2.433e-02, eta: 1 day, 4:02:09, time: 0.647, data_time: 0.000, memory: 8999, top1_acc: 0.8175, top5_acc: 0.9931, loss_cls: 3.3795, loss: 3.3795 +2025-05-05 10:49:48,437 - pyskl - INFO - Epoch [16][1000/1281] lr: 2.432e-02, eta: 1 day, 4:01:51, time: 0.634, data_time: 0.000, memory: 8999, top1_acc: 0.8512, top5_acc: 0.9919, loss_cls: 3.2177, loss: 3.2177 +2025-05-05 10:50:51,680 - pyskl - INFO - Epoch [16][1100/1281] lr: 2.432e-02, eta: 1 day, 4:01:30, time: 0.632, data_time: 0.000, memory: 8999, top1_acc: 0.8313, top5_acc: 0.9938, loss_cls: 3.1801, loss: 3.1801 +2025-05-05 10:51:53,662 - pyskl - INFO - Epoch [16][1200/1281] lr: 2.431e-02, eta: 1 day, 4:00:59, time: 0.620, data_time: 0.000, memory: 8999, top1_acc: 0.8337, top5_acc: 0.9931, loss_cls: 3.2797, loss: 3.2797 +2025-05-05 10:52:46,502 - pyskl - INFO - Saving checkpoint at 16 epochs +2025-05-05 10:53:40,584 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 10:53:40,640 - pyskl - INFO - +top1_acc 0.7466 +top5_acc 0.9762 +2025-05-05 10:53:40,640 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 10:53:40,647 - pyskl - INFO - +mean_acc 0.6621 +2025-05-05 10:53:40,649 - pyskl - INFO - Epoch(val) [16][533] top1_acc: 0.7466, top5_acc: 0.9762, mean_class_accuracy: 0.6621 +2025-05-05 10:54:50,913 - pyskl - INFO - Epoch [17][100/1281] lr: 2.430e-02, eta: 1 day, 3:54:13, time: 0.703, data_time: 0.180, memory: 8999, top1_acc: 0.8494, top5_acc: 0.9962, loss_cls: 3.2295, loss: 3.2295 +2025-05-05 10:55:49,131 - pyskl - INFO - Epoch [17][200/1281] lr: 2.429e-02, eta: 1 day, 3:53:11, time: 0.582, data_time: 0.000, memory: 8999, top1_acc: 0.8488, top5_acc: 0.9925, loss_cls: 3.2211, loss: 3.2211 +2025-05-05 10:56:49,406 - pyskl - INFO - Epoch [17][300/1281] lr: 2.428e-02, eta: 1 day, 3:52:27, time: 0.603, data_time: 0.000, memory: 8999, top1_acc: 0.8406, top5_acc: 0.9925, loss_cls: 3.2885, loss: 3.2885 +2025-05-05 10:57:55,468 - pyskl - INFO - Epoch [17][400/1281] lr: 2.428e-02, eta: 1 day, 3:52:30, time: 0.661, data_time: 0.000, memory: 8999, top1_acc: 0.8387, top5_acc: 0.9938, loss_cls: 3.1776, loss: 3.1776 +2025-05-05 10:59:00,249 - pyskl - INFO - Epoch [17][500/1281] lr: 2.427e-02, eta: 1 day, 3:52:22, time: 0.648, data_time: 0.000, memory: 8999, top1_acc: 0.8450, top5_acc: 0.9956, loss_cls: 3.2631, loss: 3.2631 +2025-05-05 11:00:04,155 - pyskl - INFO - Epoch [17][600/1281] lr: 2.426e-02, eta: 1 day, 3:52:06, time: 0.639, data_time: 0.000, memory: 8999, top1_acc: 0.8500, top5_acc: 0.9944, loss_cls: 3.2632, loss: 3.2632 +2025-05-05 11:01:08,192 - pyskl - INFO - Epoch [17][700/1281] lr: 2.426e-02, eta: 1 day, 3:51:51, time: 0.640, data_time: 0.000, memory: 8999, top1_acc: 0.8450, top5_acc: 0.9888, loss_cls: 3.1576, loss: 3.1576 +2025-05-05 11:02:12,455 - pyskl - INFO - Epoch [17][800/1281] lr: 2.425e-02, eta: 1 day, 3:51:37, time: 0.643, data_time: 0.000, memory: 8999, top1_acc: 0.8281, top5_acc: 0.9919, loss_cls: 3.3712, loss: 3.3712 +2025-05-05 11:03:19,375 - pyskl - INFO - Epoch [17][900/1281] lr: 2.424e-02, eta: 1 day, 3:51:44, time: 0.669, data_time: 0.000, memory: 8999, top1_acc: 0.8419, top5_acc: 0.9875, loss_cls: 3.1790, loss: 3.1790 +2025-05-05 11:04:22,887 - pyskl - INFO - Epoch [17][1000/1281] lr: 2.424e-02, eta: 1 day, 3:51:23, time: 0.635, data_time: 0.000, memory: 8999, top1_acc: 0.8275, top5_acc: 0.9881, loss_cls: 3.3667, loss: 3.3667 +2025-05-05 11:05:23,620 - pyskl - INFO - Epoch [17][1100/1281] lr: 2.423e-02, eta: 1 day, 3:50:39, time: 0.607, data_time: 0.000, memory: 8999, top1_acc: 0.8462, top5_acc: 0.9931, loss_cls: 3.0768, loss: 3.0768 +2025-05-05 11:06:25,126 - pyskl - INFO - Epoch [17][1200/1281] lr: 2.422e-02, eta: 1 day, 3:50:02, time: 0.615, data_time: 0.000, memory: 8999, top1_acc: 0.8450, top5_acc: 0.9925, loss_cls: 3.1875, loss: 3.1875 +2025-05-05 11:07:18,311 - pyskl - INFO - Saving checkpoint at 17 epochs +2025-05-05 11:08:10,693 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 11:08:10,753 - pyskl - INFO - +top1_acc 0.7790 +top5_acc 0.9832 +2025-05-05 11:08:10,753 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 11:08:10,762 - pyskl - INFO - +mean_acc 0.6980 +2025-05-05 11:08:10,765 - pyskl - INFO - Epoch(val) [17][533] top1_acc: 0.7790, top5_acc: 0.9832, mean_class_accuracy: 0.6980 +2025-05-05 11:09:20,048 - pyskl - INFO - Epoch [18][100/1281] lr: 2.421e-02, eta: 1 day, 3:43:27, time: 0.693, data_time: 0.182, memory: 8999, top1_acc: 0.8588, top5_acc: 0.9969, loss_cls: 3.1271, loss: 3.1271 +2025-05-05 11:10:18,873 - pyskl - INFO - Epoch [18][200/1281] lr: 2.420e-02, eta: 1 day, 3:42:30, time: 0.588, data_time: 0.000, memory: 8999, top1_acc: 0.8544, top5_acc: 0.9969, loss_cls: 3.1899, loss: 3.1899 +2025-05-05 11:11:22,072 - pyskl - INFO - Epoch [18][300/1281] lr: 2.419e-02, eta: 1 day, 3:42:06, time: 0.632, data_time: 0.000, memory: 8999, top1_acc: 0.8387, top5_acc: 0.9969, loss_cls: 3.1209, loss: 3.1209 +2025-05-05 11:12:27,775 - pyskl - INFO - Epoch [18][400/1281] lr: 2.419e-02, eta: 1 day, 3:42:02, time: 0.657, data_time: 0.000, memory: 8999, top1_acc: 0.8494, top5_acc: 0.9931, loss_cls: 3.1989, loss: 3.1989 +2025-05-05 11:13:30,336 - pyskl - INFO - Epoch [18][500/1281] lr: 2.418e-02, eta: 1 day, 3:41:33, time: 0.626, data_time: 0.000, memory: 8999, top1_acc: 0.8512, top5_acc: 0.9906, loss_cls: 3.2047, loss: 3.2047 +2025-05-05 11:14:31,070 - pyskl - INFO - Epoch [18][600/1281] lr: 2.417e-02, eta: 1 day, 3:40:50, time: 0.607, data_time: 0.000, memory: 8999, top1_acc: 0.8406, top5_acc: 0.9919, loss_cls: 3.2312, loss: 3.2312 +2025-05-05 11:15:30,953 - pyskl - INFO - Epoch [18][700/1281] lr: 2.417e-02, eta: 1 day, 3:40:00, time: 0.599, data_time: 0.000, memory: 8999, top1_acc: 0.8525, top5_acc: 0.9938, loss_cls: 3.1535, loss: 3.1535 +2025-05-05 11:16:34,926 - pyskl - INFO - Epoch [18][800/1281] lr: 2.416e-02, eta: 1 day, 3:39:41, time: 0.640, data_time: 0.000, memory: 8999, top1_acc: 0.8544, top5_acc: 0.9938, loss_cls: 3.2470, loss: 3.2470 +2025-05-05 11:17:38,999 - pyskl - INFO - Epoch [18][900/1281] lr: 2.415e-02, eta: 1 day, 3:39:22, time: 0.641, data_time: 0.000, memory: 8999, top1_acc: 0.8531, top5_acc: 0.9925, loss_cls: 3.1930, loss: 3.1930 +2025-05-05 11:18:39,773 - pyskl - INFO - Epoch [18][1000/1281] lr: 2.414e-02, eta: 1 day, 3:38:39, time: 0.608, data_time: 0.000, memory: 8999, top1_acc: 0.8481, top5_acc: 0.9888, loss_cls: 3.2716, loss: 3.2716 +2025-05-05 11:19:41,422 - pyskl - INFO - Epoch [18][1100/1281] lr: 2.414e-02, eta: 1 day, 3:38:01, time: 0.616, data_time: 0.000, memory: 8999, top1_acc: 0.8419, top5_acc: 0.9925, loss_cls: 3.1521, loss: 3.1521 +2025-05-05 11:20:45,701 - pyskl - INFO - Epoch [18][1200/1281] lr: 2.413e-02, eta: 1 day, 3:37:43, time: 0.643, data_time: 0.000, memory: 8999, top1_acc: 0.8688, top5_acc: 0.9925, loss_cls: 3.1342, loss: 3.1342 +2025-05-05 11:21:40,164 - pyskl - INFO - Saving checkpoint at 18 epochs +2025-05-05 11:22:32,563 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 11:22:32,621 - pyskl - INFO - +top1_acc 0.7906 +top5_acc 0.9757 +2025-05-05 11:22:32,621 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 11:22:32,630 - pyskl - INFO - +mean_acc 0.7242 +2025-05-05 11:22:32,633 - pyskl - INFO - Epoch(val) [18][533] top1_acc: 0.7906, top5_acc: 0.9757, mean_class_accuracy: 0.7242 +2025-05-05 11:23:40,435 - pyskl - INFO - Epoch [19][100/1281] lr: 2.411e-02, eta: 1 day, 3:31:15, time: 0.678, data_time: 0.182, memory: 8999, top1_acc: 0.8600, top5_acc: 0.9938, loss_cls: 3.1277, loss: 3.1277 +2025-05-05 11:24:37,090 - pyskl - INFO - Epoch [19][200/1281] lr: 2.411e-02, eta: 1 day, 3:30:02, time: 0.567, data_time: 0.000, memory: 8999, top1_acc: 0.8569, top5_acc: 0.9956, loss_cls: 3.1315, loss: 3.1315 +2025-05-05 11:25:39,779 - pyskl - INFO - Epoch [19][300/1281] lr: 2.410e-02, eta: 1 day, 3:29:33, time: 0.627, data_time: 0.000, memory: 8999, top1_acc: 0.8494, top5_acc: 0.9919, loss_cls: 3.1714, loss: 3.1714 +2025-05-05 11:26:44,096 - pyskl - INFO - Epoch [19][400/1281] lr: 2.409e-02, eta: 1 day, 3:29:15, time: 0.643, data_time: 0.000, memory: 8999, top1_acc: 0.8612, top5_acc: 0.9931, loss_cls: 3.1798, loss: 3.1798 +2025-05-05 11:27:46,075 - pyskl - INFO - Epoch [19][500/1281] lr: 2.408e-02, eta: 1 day, 3:28:40, time: 0.620, data_time: 0.000, memory: 8999, top1_acc: 0.8450, top5_acc: 0.9919, loss_cls: 3.0491, loss: 3.0491 +2025-05-05 11:28:46,776 - pyskl - INFO - Epoch [19][600/1281] lr: 2.408e-02, eta: 1 day, 3:27:56, time: 0.607, data_time: 0.000, memory: 8999, top1_acc: 0.8375, top5_acc: 0.9950, loss_cls: 3.2439, loss: 3.2439 +2025-05-05 11:29:51,197 - pyskl - INFO - Epoch [19][700/1281] lr: 2.407e-02, eta: 1 day, 3:27:38, time: 0.644, data_time: 0.001, memory: 8999, top1_acc: 0.8469, top5_acc: 0.9919, loss_cls: 3.2097, loss: 3.2097 +2025-05-05 11:30:58,217 - pyskl - INFO - Epoch [19][800/1281] lr: 2.406e-02, eta: 1 day, 3:27:37, time: 0.670, data_time: 0.000, memory: 8999, top1_acc: 0.8650, top5_acc: 0.9931, loss_cls: 3.0753, loss: 3.0753 +2025-05-05 11:31:59,311 - pyskl - INFO - Epoch [19][900/1281] lr: 2.405e-02, eta: 1 day, 3:26:55, time: 0.611, data_time: 0.000, memory: 8999, top1_acc: 0.8469, top5_acc: 0.9875, loss_cls: 3.1846, loss: 3.1846 +2025-05-05 11:32:59,843 - pyskl - INFO - Epoch [19][1000/1281] lr: 2.405e-02, eta: 1 day, 3:26:09, time: 0.605, data_time: 0.000, memory: 8999, top1_acc: 0.8600, top5_acc: 0.9944, loss_cls: 3.1192, loss: 3.1192 +2025-05-05 11:33:57,901 - pyskl - INFO - Epoch [19][1100/1281] lr: 2.404e-02, eta: 1 day, 3:25:05, time: 0.581, data_time: 0.000, memory: 8999, top1_acc: 0.8350, top5_acc: 0.9881, loss_cls: 3.2779, loss: 3.2779 +2025-05-05 11:34:59,036 - pyskl - INFO - Epoch [19][1200/1281] lr: 2.403e-02, eta: 1 day, 3:24:23, time: 0.611, data_time: 0.000, memory: 8999, top1_acc: 0.8406, top5_acc: 0.9931, loss_cls: 3.1881, loss: 3.1881 +2025-05-05 11:35:51,054 - pyskl - INFO - Saving checkpoint at 19 epochs +2025-05-05 11:36:42,222 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 11:36:42,275 - pyskl - INFO - +top1_acc 0.8021 +top5_acc 0.9797 +2025-05-05 11:36:42,276 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 11:36:42,282 - pyskl - INFO - +mean_acc 0.7376 +2025-05-05 11:36:42,284 - pyskl - INFO - Epoch(val) [19][533] top1_acc: 0.8021, top5_acc: 0.9797, mean_class_accuracy: 0.7376 +2025-05-05 11:37:50,114 - pyskl - INFO - Epoch [20][100/1281] lr: 2.402e-02, eta: 1 day, 3:18:12, time: 0.678, data_time: 0.176, memory: 9000, top1_acc: 0.8562, top5_acc: 0.9944, loss_cls: 3.0924, loss: 3.0924 +2025-05-05 11:38:48,577 - pyskl - INFO - Epoch [20][200/1281] lr: 2.401e-02, eta: 1 day, 3:17:13, time: 0.585, data_time: 0.000, memory: 9000, top1_acc: 0.8512, top5_acc: 0.9944, loss_cls: 3.1078, loss: 3.1078 +2025-05-05 11:40:01,733 - pyskl - INFO - Epoch [20][300/1281] lr: 2.400e-02, eta: 1 day, 3:17:53, time: 0.732, data_time: 0.000, memory: 9000, top1_acc: 0.8619, top5_acc: 0.9950, loss_cls: 3.0741, loss: 3.0741 +2025-05-05 11:41:13,711 - pyskl - INFO - Epoch [20][400/1281] lr: 2.399e-02, eta: 1 day, 3:18:24, time: 0.720, data_time: 0.000, memory: 9000, top1_acc: 0.8438, top5_acc: 0.9912, loss_cls: 3.2062, loss: 3.2062 +2025-05-05 11:42:18,416 - pyskl - INFO - Epoch [20][500/1281] lr: 2.398e-02, eta: 1 day, 3:18:06, time: 0.647, data_time: 0.000, memory: 9000, top1_acc: 0.8469, top5_acc: 0.9975, loss_cls: 3.1943, loss: 3.1943 +2025-05-05 11:43:21,804 - pyskl - INFO - Epoch [20][600/1281] lr: 2.398e-02, eta: 1 day, 3:17:38, time: 0.634, data_time: 0.000, memory: 9000, top1_acc: 0.8475, top5_acc: 0.9950, loss_cls: 3.1967, loss: 3.1967 +2025-05-05 11:44:28,438 - pyskl - INFO - Epoch [20][700/1281] lr: 2.397e-02, eta: 1 day, 3:17:32, time: 0.666, data_time: 0.000, memory: 9000, top1_acc: 0.8325, top5_acc: 0.9931, loss_cls: 3.3401, loss: 3.3401 +2025-05-05 11:45:36,503 - pyskl - INFO - Epoch [20][800/1281] lr: 2.396e-02, eta: 1 day, 3:17:35, time: 0.681, data_time: 0.000, memory: 9000, top1_acc: 0.8550, top5_acc: 0.9938, loss_cls: 3.1702, loss: 3.1702 +2025-05-05 11:46:40,991 - pyskl - INFO - Epoch [20][900/1281] lr: 2.395e-02, eta: 1 day, 3:17:13, time: 0.645, data_time: 0.000, memory: 9000, top1_acc: 0.8481, top5_acc: 0.9944, loss_cls: 3.1324, loss: 3.1324 +2025-05-05 11:47:44,390 - pyskl - INFO - Epoch [20][1000/1281] lr: 2.394e-02, eta: 1 day, 3:16:44, time: 0.634, data_time: 0.000, memory: 9000, top1_acc: 0.8594, top5_acc: 0.9944, loss_cls: 3.1446, loss: 3.1446 +2025-05-05 11:48:58,519 - pyskl - INFO - Epoch [20][1100/1281] lr: 2.393e-02, eta: 1 day, 3:17:25, time: 0.741, data_time: 0.000, memory: 9000, top1_acc: 0.8769, top5_acc: 0.9944, loss_cls: 3.0504, loss: 3.0504 +2025-05-05 11:50:13,291 - pyskl - INFO - Epoch [20][1200/1281] lr: 2.393e-02, eta: 1 day, 3:18:10, time: 0.748, data_time: 0.000, memory: 9000, top1_acc: 0.8656, top5_acc: 0.9931, loss_cls: 2.9797, loss: 2.9797 +2025-05-05 11:51:06,166 - pyskl - INFO - Saving checkpoint at 20 epochs +2025-05-05 11:51:56,558 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 11:51:56,611 - pyskl - INFO - +top1_acc 0.7979 +top5_acc 0.9805 +2025-05-05 11:51:56,611 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 11:51:56,618 - pyskl - INFO - +mean_acc 0.7521 +2025-05-05 11:51:56,619 - pyskl - INFO - Epoch(val) [20][533] top1_acc: 0.7979, top5_acc: 0.9805, mean_class_accuracy: 0.7521 +2025-05-05 11:53:06,546 - pyskl - INFO - Epoch [21][100/1281] lr: 2.391e-02, eta: 1 day, 3:12:25, time: 0.699, data_time: 0.174, memory: 9000, top1_acc: 0.8794, top5_acc: 0.9962, loss_cls: 3.0489, loss: 3.0489 +2025-05-05 11:54:10,020 - pyskl - INFO - Epoch [21][200/1281] lr: 2.390e-02, eta: 1 day, 3:11:56, time: 0.635, data_time: 0.000, memory: 9000, top1_acc: 0.8444, top5_acc: 0.9956, loss_cls: 3.1708, loss: 3.1708 +2025-05-05 11:55:17,808 - pyskl - INFO - Epoch [21][300/1281] lr: 2.389e-02, eta: 1 day, 3:11:54, time: 0.678, data_time: 0.000, memory: 9000, top1_acc: 0.8675, top5_acc: 0.9944, loss_cls: 3.0159, loss: 3.0159 +2025-05-05 11:56:26,783 - pyskl - INFO - Epoch [21][400/1281] lr: 2.389e-02, eta: 1 day, 3:11:59, time: 0.690, data_time: 0.000, memory: 9000, top1_acc: 0.8619, top5_acc: 0.9950, loss_cls: 3.1433, loss: 3.1433 +2025-05-05 11:57:37,712 - pyskl - INFO - Epoch [21][500/1281] lr: 2.388e-02, eta: 1 day, 3:12:16, time: 0.709, data_time: 0.000, memory: 9000, top1_acc: 0.8775, top5_acc: 0.9919, loss_cls: 2.9944, loss: 2.9944 +2025-05-05 11:59:07,888 - pyskl - INFO - Epoch [21][600/1281] lr: 2.387e-02, eta: 1 day, 3:14:35, time: 0.902, data_time: 0.000, memory: 9000, top1_acc: 0.8581, top5_acc: 0.9950, loss_cls: 3.0096, loss: 3.0096 +2025-05-05 12:00:28,285 - pyskl - INFO - Epoch [21][700/1281] lr: 2.386e-02, eta: 1 day, 3:15:50, time: 0.804, data_time: 0.000, memory: 9000, top1_acc: 0.8606, top5_acc: 0.9962, loss_cls: 3.0463, loss: 3.0463 +2025-05-05 12:01:43,151 - pyskl - INFO - Epoch [21][800/1281] lr: 2.385e-02, eta: 1 day, 3:16:29, time: 0.749, data_time: 0.000, memory: 9000, top1_acc: 0.8506, top5_acc: 0.9944, loss_cls: 3.1642, loss: 3.1642 +2025-05-05 12:02:56,035 - pyskl - INFO - Epoch [21][900/1281] lr: 2.384e-02, eta: 1 day, 3:16:55, time: 0.729, data_time: 0.000, memory: 9000, top1_acc: 0.8700, top5_acc: 0.9900, loss_cls: 3.0971, loss: 3.0971 +2025-05-05 12:04:10,141 - pyskl - INFO - Epoch [21][1000/1281] lr: 2.383e-02, eta: 1 day, 3:17:28, time: 0.741, data_time: 0.000, memory: 9000, top1_acc: 0.8550, top5_acc: 0.9919, loss_cls: 3.1752, loss: 3.1752 +2025-05-05 12:05:24,257 - pyskl - INFO - Epoch [21][1100/1281] lr: 2.383e-02, eta: 1 day, 3:18:00, time: 0.741, data_time: 0.000, memory: 9000, top1_acc: 0.8650, top5_acc: 0.9950, loss_cls: 3.0444, loss: 3.0444 +2025-05-05 12:06:37,992 - pyskl - INFO - Epoch [21][1200/1281] lr: 2.382e-02, eta: 1 day, 3:18:29, time: 0.737, data_time: 0.000, memory: 9000, top1_acc: 0.8594, top5_acc: 0.9912, loss_cls: 3.0326, loss: 3.0326 +2025-05-05 12:07:43,977 - pyskl - INFO - Saving checkpoint at 21 epochs +2025-05-05 12:08:52,745 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 12:08:52,798 - pyskl - INFO - +top1_acc 0.8050 +top5_acc 0.9764 +2025-05-05 12:08:52,798 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 12:08:52,804 - pyskl - INFO - +mean_acc 0.7235 +2025-05-05 12:08:52,861 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_15.pth was removed +2025-05-05 12:08:54,341 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_21.pth. +2025-05-05 12:08:54,342 - pyskl - INFO - Best top1_acc is 0.8050 at 21 epoch. +2025-05-05 12:08:54,346 - pyskl - INFO - Epoch(val) [21][533] top1_acc: 0.8050, top5_acc: 0.9764, mean_class_accuracy: 0.7235 +2025-05-05 12:10:18,757 - pyskl - INFO - Epoch [22][100/1281] lr: 2.380e-02, eta: 1 day, 3:14:19, time: 0.844, data_time: 0.174, memory: 9000, top1_acc: 0.8644, top5_acc: 0.9956, loss_cls: 3.0177, loss: 3.0177 +2025-05-05 12:11:32,892 - pyskl - INFO - Epoch [22][200/1281] lr: 2.379e-02, eta: 1 day, 3:14:50, time: 0.741, data_time: 0.000, memory: 9000, top1_acc: 0.8769, top5_acc: 0.9988, loss_cls: 2.9307, loss: 2.9307 +2025-05-05 12:12:46,699 - pyskl - INFO - Epoch [22][300/1281] lr: 2.378e-02, eta: 1 day, 3:15:17, time: 0.738, data_time: 0.000, memory: 9000, top1_acc: 0.8538, top5_acc: 0.9912, loss_cls: 3.0418, loss: 3.0418 +2025-05-05 12:14:00,793 - pyskl - INFO - Epoch [22][400/1281] lr: 2.378e-02, eta: 1 day, 3:15:46, time: 0.741, data_time: 0.000, memory: 9000, top1_acc: 0.8688, top5_acc: 0.9944, loss_cls: 2.9797, loss: 2.9797 +2025-05-05 12:15:15,299 - pyskl - INFO - Epoch [22][500/1281] lr: 2.377e-02, eta: 1 day, 3:16:16, time: 0.745, data_time: 0.000, memory: 9000, top1_acc: 0.8731, top5_acc: 0.9956, loss_cls: 2.9883, loss: 2.9883 +2025-05-05 12:16:29,772 - pyskl - INFO - Epoch [22][600/1281] lr: 2.376e-02, eta: 1 day, 3:16:46, time: 0.745, data_time: 0.000, memory: 9000, top1_acc: 0.8525, top5_acc: 0.9919, loss_cls: 3.2135, loss: 3.2135 +2025-05-05 12:17:58,975 - pyskl - INFO - Epoch [22][700/1281] lr: 2.375e-02, eta: 1 day, 3:18:43, time: 0.892, data_time: 0.000, memory: 9000, top1_acc: 0.8606, top5_acc: 0.9938, loss_cls: 3.0698, loss: 3.0698 +2025-05-05 12:19:20,914 - pyskl - INFO - Epoch [22][800/1281] lr: 2.374e-02, eta: 1 day, 3:19:55, time: 0.819, data_time: 0.000, memory: 9000, top1_acc: 0.8506, top5_acc: 0.9919, loss_cls: 3.0359, loss: 3.0359 +2025-05-05 12:20:36,245 - pyskl - INFO - Epoch [22][900/1281] lr: 2.373e-02, eta: 1 day, 3:20:26, time: 0.753, data_time: 0.000, memory: 9000, top1_acc: 0.8544, top5_acc: 0.9931, loss_cls: 3.0660, loss: 3.0660 +2025-05-05 12:21:51,041 - pyskl - INFO - Epoch [22][1000/1281] lr: 2.372e-02, eta: 1 day, 3:20:54, time: 0.748, data_time: 0.000, memory: 9000, top1_acc: 0.8606, top5_acc: 0.9912, loss_cls: 3.0838, loss: 3.0838 +2025-05-05 12:23:04,793 - pyskl - INFO - Epoch [22][1100/1281] lr: 2.371e-02, eta: 1 day, 3:21:15, time: 0.737, data_time: 0.000, memory: 9000, top1_acc: 0.8500, top5_acc: 0.9931, loss_cls: 3.1690, loss: 3.1690 +2025-05-05 12:24:19,591 - pyskl - INFO - Epoch [22][1200/1281] lr: 2.370e-02, eta: 1 day, 3:21:42, time: 0.748, data_time: 0.000, memory: 9000, top1_acc: 0.8619, top5_acc: 0.9962, loss_cls: 3.0653, loss: 3.0653 +2025-05-05 12:25:20,204 - pyskl - INFO - Saving checkpoint at 22 epochs +2025-05-05 12:26:19,448 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 12:26:19,500 - pyskl - INFO - +top1_acc 0.7872 +top5_acc 0.9786 +2025-05-05 12:26:19,500 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 12:26:19,506 - pyskl - INFO - +mean_acc 0.7074 +2025-05-05 12:26:19,507 - pyskl - INFO - Epoch(val) [22][533] top1_acc: 0.7872, top5_acc: 0.9786, mean_class_accuracy: 0.7074 +2025-05-05 12:27:53,357 - pyskl - INFO - Epoch [23][100/1281] lr: 2.369e-02, eta: 1 day, 3:18:27, time: 0.938, data_time: 0.176, memory: 9000, top1_acc: 0.8656, top5_acc: 0.9962, loss_cls: 3.0700, loss: 3.0700 +2025-05-05 12:29:11,208 - pyskl - INFO - Epoch [23][200/1281] lr: 2.368e-02, eta: 1 day, 3:19:10, time: 0.778, data_time: 0.000, memory: 9000, top1_acc: 0.8612, top5_acc: 0.9944, loss_cls: 2.9480, loss: 2.9480 +2025-05-05 12:30:26,638 - pyskl - INFO - Epoch [23][300/1281] lr: 2.367e-02, eta: 1 day, 3:19:38, time: 0.754, data_time: 0.000, memory: 9000, top1_acc: 0.8588, top5_acc: 0.9944, loss_cls: 3.0855, loss: 3.0855 +2025-05-05 12:31:40,913 - pyskl - INFO - Epoch [23][400/1281] lr: 2.366e-02, eta: 1 day, 3:19:59, time: 0.743, data_time: 0.000, memory: 9000, top1_acc: 0.8806, top5_acc: 0.9925, loss_cls: 3.0265, loss: 3.0265 +2025-05-05 12:32:54,831 - pyskl - INFO - Epoch [23][500/1281] lr: 2.365e-02, eta: 1 day, 3:20:18, time: 0.739, data_time: 0.000, memory: 9000, top1_acc: 0.8600, top5_acc: 0.9950, loss_cls: 3.0913, loss: 3.0913 +2025-05-05 12:34:08,970 - pyskl - INFO - Epoch [23][600/1281] lr: 2.364e-02, eta: 1 day, 3:20:36, time: 0.741, data_time: 0.000, memory: 9000, top1_acc: 0.8631, top5_acc: 0.9956, loss_cls: 3.0594, loss: 3.0594 +2025-05-05 12:35:23,322 - pyskl - INFO - Epoch [23][700/1281] lr: 2.363e-02, eta: 1 day, 3:20:56, time: 0.744, data_time: 0.000, memory: 9000, top1_acc: 0.8681, top5_acc: 0.9956, loss_cls: 2.9599, loss: 2.9599 +2025-05-05 12:36:47,472 - pyskl - INFO - Epoch [23][800/1281] lr: 2.362e-02, eta: 1 day, 3:22:10, time: 0.841, data_time: 0.000, memory: 9000, top1_acc: 0.8387, top5_acc: 0.9931, loss_cls: 3.2020, loss: 3.2020 +2025-05-05 12:38:12,783 - pyskl - INFO - Epoch [23][900/1281] lr: 2.361e-02, eta: 1 day, 3:23:29, time: 0.853, data_time: 0.000, memory: 9000, top1_acc: 0.8462, top5_acc: 0.9925, loss_cls: 3.1905, loss: 3.1905 +2025-05-05 12:39:29,668 - pyskl - INFO - Epoch [23][1000/1281] lr: 2.360e-02, eta: 1 day, 3:24:00, time: 0.769, data_time: 0.000, memory: 9000, top1_acc: 0.8638, top5_acc: 0.9931, loss_cls: 3.0559, loss: 3.0559 +2025-05-05 12:40:42,302 - pyskl - INFO - Epoch [23][1100/1281] lr: 2.359e-02, eta: 1 day, 3:24:07, time: 0.726, data_time: 0.000, memory: 9000, top1_acc: 0.8594, top5_acc: 0.9912, loss_cls: 3.1217, loss: 3.1217 +2025-05-05 12:41:55,203 - pyskl - INFO - Epoch [23][1200/1281] lr: 2.359e-02, eta: 1 day, 3:24:15, time: 0.729, data_time: 0.000, memory: 9000, top1_acc: 0.8662, top5_acc: 0.9919, loss_cls: 3.0784, loss: 3.0784 +2025-05-05 12:42:55,514 - pyskl - INFO - Saving checkpoint at 23 epochs +2025-05-05 12:43:53,780 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 12:43:53,832 - pyskl - INFO - +top1_acc 0.8289 +top5_acc 0.9872 +2025-05-05 12:43:53,833 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 12:43:53,838 - pyskl - INFO - +mean_acc 0.7755 +2025-05-05 12:43:53,896 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_21.pth was removed +2025-05-05 12:43:55,383 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_23.pth. +2025-05-05 12:43:55,384 - pyskl - INFO - Best top1_acc is 0.8289 at 23 epoch. +2025-05-05 12:43:55,388 - pyskl - INFO - Epoch(val) [23][533] top1_acc: 0.8289, top5_acc: 0.9872, mean_class_accuracy: 0.7755 +2025-05-05 12:45:13,392 - pyskl - INFO - Epoch [24][100/1281] lr: 2.357e-02, eta: 1 day, 3:19:31, time: 0.780, data_time: 0.177, memory: 9000, top1_acc: 0.8906, top5_acc: 0.9956, loss_cls: 2.8828, loss: 2.8828 +2025-05-05 12:46:37,200 - pyskl - INFO - Epoch [24][200/1281] lr: 2.356e-02, eta: 1 day, 3:20:38, time: 0.838, data_time: 0.000, memory: 9000, top1_acc: 0.8688, top5_acc: 0.9931, loss_cls: 3.0300, loss: 3.0300 +2025-05-05 12:48:00,815 - pyskl - INFO - Epoch [24][300/1281] lr: 2.355e-02, eta: 1 day, 3:21:43, time: 0.836, data_time: 0.000, memory: 9000, top1_acc: 0.8681, top5_acc: 0.9956, loss_cls: 2.9956, loss: 2.9956 +2025-05-05 12:49:16,283 - pyskl - INFO - Epoch [24][400/1281] lr: 2.354e-02, eta: 1 day, 3:22:03, time: 0.755, data_time: 0.000, memory: 9000, top1_acc: 0.8850, top5_acc: 0.9950, loss_cls: 2.8987, loss: 2.8987 +2025-05-05 12:50:30,575 - pyskl - INFO - Epoch [24][500/1281] lr: 2.353e-02, eta: 1 day, 3:22:16, time: 0.743, data_time: 0.000, memory: 9000, top1_acc: 0.8619, top5_acc: 0.9931, loss_cls: 2.9981, loss: 2.9981 +2025-05-05 12:51:44,369 - pyskl - INFO - Epoch [24][600/1281] lr: 2.352e-02, eta: 1 day, 3:22:25, time: 0.738, data_time: 0.000, memory: 9000, top1_acc: 0.8712, top5_acc: 0.9975, loss_cls: 3.0620, loss: 3.0620 +2025-05-05 12:52:58,583 - pyskl - INFO - Epoch [24][700/1281] lr: 2.351e-02, eta: 1 day, 3:22:36, time: 0.742, data_time: 0.000, memory: 9000, top1_acc: 0.8562, top5_acc: 0.9944, loss_cls: 3.0293, loss: 3.0293 +2025-05-05 12:54:11,698 - pyskl - INFO - Epoch [24][800/1281] lr: 2.350e-02, eta: 1 day, 3:22:41, time: 0.731, data_time: 0.000, memory: 9000, top1_acc: 0.8744, top5_acc: 0.9944, loss_cls: 3.0198, loss: 3.0198 +2025-05-05 12:55:29,975 - pyskl - INFO - Epoch [24][900/1281] lr: 2.349e-02, eta: 1 day, 3:23:13, time: 0.783, data_time: 0.000, memory: 9000, top1_acc: 0.8594, top5_acc: 0.9950, loss_cls: 3.0442, loss: 3.0442 +2025-05-05 12:57:00,551 - pyskl - INFO - Epoch [24][1000/1281] lr: 2.348e-02, eta: 1 day, 3:24:49, time: 0.906, data_time: 0.000, memory: 9000, top1_acc: 0.8525, top5_acc: 0.9925, loss_cls: 3.1141, loss: 3.1141 +2025-05-05 12:58:17,439 - pyskl - INFO - Epoch [24][1100/1281] lr: 2.347e-02, eta: 1 day, 3:25:12, time: 0.769, data_time: 0.000, memory: 9000, top1_acc: 0.8806, top5_acc: 0.9962, loss_cls: 2.9609, loss: 2.9609 +2025-05-05 12:59:31,673 - pyskl - INFO - Epoch [24][1200/1281] lr: 2.346e-02, eta: 1 day, 3:25:20, time: 0.742, data_time: 0.000, memory: 9000, top1_acc: 0.8612, top5_acc: 0.9944, loss_cls: 3.0109, loss: 3.0109 +2025-05-05 13:00:32,584 - pyskl - INFO - Saving checkpoint at 24 epochs +2025-05-05 13:01:37,809 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 13:01:37,861 - pyskl - INFO - +top1_acc 0.8264 +top5_acc 0.9874 +2025-05-05 13:01:37,862 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 13:01:37,867 - pyskl - INFO - +mean_acc 0.7831 +2025-05-05 13:01:37,869 - pyskl - INFO - Epoch(val) [24][533] top1_acc: 0.8264, top5_acc: 0.9874, mean_class_accuracy: 0.7831 +2025-05-05 13:03:00,379 - pyskl - INFO - Epoch [25][100/1281] lr: 2.344e-02, eta: 1 day, 3:21:02, time: 0.825, data_time: 0.175, memory: 9000, top1_acc: 0.8788, top5_acc: 0.9962, loss_cls: 2.8847, loss: 2.8847 +2025-05-05 13:04:12,598 - pyskl - INFO - Epoch [25][200/1281] lr: 2.343e-02, eta: 1 day, 3:21:00, time: 0.722, data_time: 0.000, memory: 9000, top1_acc: 0.8719, top5_acc: 0.9950, loss_cls: 3.0143, loss: 3.0143 +2025-05-05 13:05:29,993 - pyskl - INFO - Epoch [25][300/1281] lr: 2.342e-02, eta: 1 day, 3:21:23, time: 0.774, data_time: 0.000, memory: 9000, top1_acc: 0.8894, top5_acc: 0.9981, loss_cls: 2.9447, loss: 2.9447 +2025-05-05 13:07:29,329 - pyskl - INFO - Epoch [25][400/1281] lr: 2.341e-02, eta: 1 day, 3:25:23, time: 1.193, data_time: 0.000, memory: 9000, top1_acc: 0.8688, top5_acc: 0.9938, loss_cls: 3.0036, loss: 3.0036 +2025-05-05 13:09:41,649 - pyskl - INFO - Epoch [25][500/1281] lr: 2.340e-02, eta: 1 day, 3:30:27, time: 1.323, data_time: 0.000, memory: 9000, top1_acc: 0.8744, top5_acc: 0.9950, loss_cls: 2.9695, loss: 2.9695 +2025-05-05 13:12:01,311 - pyskl - INFO - Epoch [25][600/1281] lr: 2.339e-02, eta: 1 day, 3:36:07, time: 1.397, data_time: 0.000, memory: 9000, top1_acc: 0.8806, top5_acc: 0.9975, loss_cls: 2.9364, loss: 2.9364 +2025-05-05 13:14:21,054 - pyskl - INFO - Epoch [25][700/1281] lr: 2.338e-02, eta: 1 day, 3:41:43, time: 1.397, data_time: 0.000, memory: 9000, top1_acc: 0.8494, top5_acc: 0.9912, loss_cls: 3.1126, loss: 3.1126 +2025-05-05 13:16:40,832 - pyskl - INFO - Epoch [25][800/1281] lr: 2.337e-02, eta: 1 day, 3:47:17, time: 1.398, data_time: 0.000, memory: 9000, top1_acc: 0.8794, top5_acc: 0.9962, loss_cls: 2.9888, loss: 2.9888 +2025-05-05 13:19:00,536 - pyskl - INFO - Epoch [25][900/1281] lr: 2.336e-02, eta: 1 day, 3:52:47, time: 1.397, data_time: 0.000, memory: 9000, top1_acc: 0.8669, top5_acc: 0.9962, loss_cls: 2.9279, loss: 2.9279 +2025-05-05 13:21:21,007 - pyskl - INFO - Epoch [25][1000/1281] lr: 2.335e-02, eta: 1 day, 3:58:19, time: 1.405, data_time: 0.000, memory: 9000, top1_acc: 0.8756, top5_acc: 0.9956, loss_cls: 2.9620, loss: 2.9620 +2025-05-05 13:23:41,730 - pyskl - INFO - Epoch [25][1100/1281] lr: 2.334e-02, eta: 1 day, 4:03:48, time: 1.407, data_time: 0.000, memory: 9000, top1_acc: 0.8638, top5_acc: 0.9938, loss_cls: 3.0415, loss: 3.0415 +2025-05-05 13:26:01,903 - pyskl - INFO - Epoch [25][1200/1281] lr: 2.333e-02, eta: 1 day, 4:09:12, time: 1.402, data_time: 0.000, memory: 9000, top1_acc: 0.8562, top5_acc: 0.9938, loss_cls: 3.0484, loss: 3.0484 +2025-05-05 13:27:56,608 - pyskl - INFO - Saving checkpoint at 25 epochs +2025-05-05 13:29:41,364 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 13:29:41,415 - pyskl - INFO - +top1_acc 0.8050 +top5_acc 0.9825 +2025-05-05 13:29:41,415 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 13:29:41,421 - pyskl - INFO - +mean_acc 0.7552 +2025-05-05 13:29:41,423 - pyskl - INFO - Epoch(val) [25][533] top1_acc: 0.8050, top5_acc: 0.9825, mean_class_accuracy: 0.7552 +2025-05-05 13:32:08,725 - pyskl - INFO - Epoch [26][100/1281] lr: 2.332e-02, eta: 1 day, 4:10:01, time: 1.473, data_time: 0.172, memory: 9000, top1_acc: 0.8781, top5_acc: 0.9950, loss_cls: 2.9174, loss: 2.9174 +2025-05-05 13:34:27,992 - pyskl - INFO - Epoch [26][200/1281] lr: 2.330e-02, eta: 1 day, 4:15:14, time: 1.393, data_time: 0.000, memory: 9000, top1_acc: 0.8788, top5_acc: 0.9944, loss_cls: 2.8672, loss: 2.8672 +2025-05-05 13:36:47,751 - pyskl - INFO - Epoch [26][300/1281] lr: 2.329e-02, eta: 1 day, 4:20:27, time: 1.398, data_time: 0.000, memory: 9000, top1_acc: 0.8806, top5_acc: 0.9962, loss_cls: 2.9753, loss: 2.9753 +2025-05-05 13:39:09,911 - pyskl - INFO - Epoch [26][400/1281] lr: 2.328e-02, eta: 1 day, 4:25:49, time: 1.422, data_time: 0.000, memory: 9000, top1_acc: 0.8625, top5_acc: 0.9956, loss_cls: 2.9792, loss: 2.9792 +2025-05-05 13:41:30,085 - pyskl - INFO - Epoch [26][500/1281] lr: 2.327e-02, eta: 1 day, 4:30:59, time: 1.402, data_time: 0.000, memory: 9000, top1_acc: 0.8788, top5_acc: 0.9938, loss_cls: 3.0158, loss: 3.0158 +2025-05-05 13:43:49,324 - pyskl - INFO - Epoch [26][600/1281] lr: 2.326e-02, eta: 1 day, 4:36:01, time: 1.392, data_time: 0.000, memory: 9000, top1_acc: 0.8644, top5_acc: 0.9956, loss_cls: 2.9110, loss: 2.9110 +2025-05-05 13:46:09,466 - pyskl - INFO - Epoch [26][700/1281] lr: 2.325e-02, eta: 1 day, 4:41:04, time: 1.401, data_time: 0.000, memory: 9000, top1_acc: 0.8762, top5_acc: 0.9962, loss_cls: 2.9634, loss: 2.9634 +2025-05-05 13:48:30,101 - pyskl - INFO - Epoch [26][800/1281] lr: 2.324e-02, eta: 1 day, 4:46:08, time: 1.406, data_time: 0.000, memory: 9000, top1_acc: 0.8806, top5_acc: 0.9962, loss_cls: 2.9083, loss: 2.9083 +2025-05-05 13:50:49,491 - pyskl - INFO - Epoch [26][900/1281] lr: 2.323e-02, eta: 1 day, 4:51:03, time: 1.394, data_time: 0.000, memory: 9000, top1_acc: 0.8819, top5_acc: 0.9931, loss_cls: 2.9730, loss: 2.9730 +2025-05-05 13:53:10,006 - pyskl - INFO - Epoch [26][1000/1281] lr: 2.322e-02, eta: 1 day, 4:56:00, time: 1.405, data_time: 0.000, memory: 9000, top1_acc: 0.8719, top5_acc: 0.9938, loss_cls: 2.9401, loss: 2.9401 +2025-05-05 13:55:32,758 - pyskl - INFO - Epoch [26][1100/1281] lr: 2.321e-02, eta: 1 day, 5:01:06, time: 1.428, data_time: 0.000, memory: 9000, top1_acc: 0.8675, top5_acc: 0.9938, loss_cls: 3.0322, loss: 3.0322 +2025-05-05 13:57:53,145 - pyskl - INFO - Epoch [26][1200/1281] lr: 2.320e-02, eta: 1 day, 5:05:57, time: 1.404, data_time: 0.000, memory: 9000, top1_acc: 0.8525, top5_acc: 0.9931, loss_cls: 3.0796, loss: 3.0796 +2025-05-05 13:59:48,416 - pyskl - INFO - Saving checkpoint at 26 epochs +2025-05-05 14:01:32,166 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 14:01:32,218 - pyskl - INFO - +top1_acc 0.8034 +top5_acc 0.9791 +2025-05-05 14:01:32,218 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 14:01:32,224 - pyskl - INFO - +mean_acc 0.7348 +2025-05-05 14:01:32,226 - pyskl - INFO - Epoch(val) [26][533] top1_acc: 0.8034, top5_acc: 0.9791, mean_class_accuracy: 0.7348 +2025-05-05 14:04:00,057 - pyskl - INFO - Epoch [27][100/1281] lr: 2.318e-02, eta: 1 day, 5:06:13, time: 1.478, data_time: 0.173, memory: 9000, top1_acc: 0.8838, top5_acc: 0.9981, loss_cls: 2.8830, loss: 2.8830 +2025-05-05 14:06:20,096 - pyskl - INFO - Epoch [27][200/1281] lr: 2.317e-02, eta: 1 day, 5:10:58, time: 1.400, data_time: 0.000, memory: 9000, top1_acc: 0.8644, top5_acc: 0.9975, loss_cls: 2.9308, loss: 2.9308 +2025-05-05 14:08:40,826 - pyskl - INFO - Epoch [27][300/1281] lr: 2.316e-02, eta: 1 day, 5:15:43, time: 1.407, data_time: 0.000, memory: 9000, top1_acc: 0.8956, top5_acc: 0.9975, loss_cls: 2.8108, loss: 2.8108 +2025-05-05 14:11:03,189 - pyskl - INFO - Epoch [27][400/1281] lr: 2.315e-02, eta: 1 day, 5:20:34, time: 1.424, data_time: 0.000, memory: 9000, top1_acc: 0.8794, top5_acc: 0.9931, loss_cls: 2.9691, loss: 2.9691 +2025-05-05 14:13:22,127 - pyskl - INFO - Epoch [27][500/1281] lr: 2.314e-02, eta: 1 day, 5:25:05, time: 1.389, data_time: 0.000, memory: 9000, top1_acc: 0.8688, top5_acc: 0.9950, loss_cls: 2.9784, loss: 2.9784 +2025-05-05 14:15:42,096 - pyskl - INFO - Epoch [27][600/1281] lr: 2.313e-02, eta: 1 day, 5:29:40, time: 1.400, data_time: 0.000, memory: 9000, top1_acc: 0.8662, top5_acc: 0.9944, loss_cls: 3.0258, loss: 3.0258 +2025-05-05 14:18:04,225 - pyskl - INFO - Epoch [27][700/1281] lr: 2.312e-02, eta: 1 day, 5:34:21, time: 1.421, data_time: 0.000, memory: 9000, top1_acc: 0.8700, top5_acc: 0.9956, loss_cls: 2.9932, loss: 2.9932 +2025-05-05 14:20:24,308 - pyskl - INFO - Epoch [27][800/1281] lr: 2.311e-02, eta: 1 day, 5:38:51, time: 1.401, data_time: 0.000, memory: 9000, top1_acc: 0.8812, top5_acc: 0.9969, loss_cls: 2.8480, loss: 2.8480 +2025-05-05 14:22:44,912 - pyskl - INFO - Epoch [27][900/1281] lr: 2.310e-02, eta: 1 day, 5:43:21, time: 1.406, data_time: 0.000, memory: 9000, top1_acc: 0.8769, top5_acc: 0.9962, loss_cls: 2.9891, loss: 2.9891 +2025-05-05 14:25:07,234 - pyskl - INFO - Epoch [27][1000/1281] lr: 2.308e-02, eta: 1 day, 5:47:57, time: 1.423, data_time: 0.000, memory: 9000, top1_acc: 0.8919, top5_acc: 0.9962, loss_cls: 2.8081, loss: 2.8081 +2025-05-05 14:27:25,438 - pyskl - INFO - Epoch [27][1100/1281] lr: 2.307e-02, eta: 1 day, 5:52:11, time: 1.382, data_time: 0.000, memory: 9000, top1_acc: 0.8806, top5_acc: 0.9950, loss_cls: 2.8846, loss: 2.8846 +2025-05-05 14:29:45,761 - pyskl - INFO - Epoch [27][1200/1281] lr: 2.306e-02, eta: 1 day, 5:56:32, time: 1.403, data_time: 0.000, memory: 9000, top1_acc: 0.8712, top5_acc: 0.9938, loss_cls: 2.9719, loss: 2.9719 +2025-05-05 14:31:38,773 - pyskl - INFO - Saving checkpoint at 27 epochs +2025-05-05 14:33:24,003 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 14:33:24,055 - pyskl - INFO - +top1_acc 0.7877 +top5_acc 0.9782 +2025-05-05 14:33:24,056 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 14:33:24,061 - pyskl - INFO - +mean_acc 0.7276 +2025-05-05 14:33:24,063 - pyskl - INFO - Epoch(val) [27][533] top1_acc: 0.7877, top5_acc: 0.9782, mean_class_accuracy: 0.7276 +2025-05-05 14:35:51,976 - pyskl - INFO - Epoch [28][100/1281] lr: 2.304e-02, eta: 1 day, 5:56:18, time: 1.479, data_time: 0.172, memory: 9000, top1_acc: 0.8912, top5_acc: 0.9962, loss_cls: 2.7569, loss: 2.7569 +2025-05-05 14:38:12,343 - pyskl - INFO - Epoch [28][200/1281] lr: 2.303e-02, eta: 1 day, 6:00:35, time: 1.404, data_time: 0.000, memory: 9000, top1_acc: 0.8831, top5_acc: 0.9938, loss_cls: 2.8317, loss: 2.8317 +2025-05-05 14:40:30,946 - pyskl - INFO - Epoch [28][300/1281] lr: 2.302e-02, eta: 1 day, 6:04:42, time: 1.386, data_time: 0.000, memory: 9000, top1_acc: 0.8706, top5_acc: 0.9956, loss_cls: 2.9241, loss: 2.9241 +2025-05-05 14:42:52,597 - pyskl - INFO - Epoch [28][400/1281] lr: 2.301e-02, eta: 1 day, 6:09:00, time: 1.417, data_time: 0.000, memory: 9000, top1_acc: 0.8738, top5_acc: 0.9925, loss_cls: 2.9032, loss: 2.9032 +2025-05-05 14:45:11,263 - pyskl - INFO - Epoch [28][500/1281] lr: 2.300e-02, eta: 1 day, 6:13:02, time: 1.387, data_time: 0.000, memory: 9000, top1_acc: 0.8731, top5_acc: 0.9962, loss_cls: 2.8893, loss: 2.8893 +2025-05-05 14:47:30,194 - pyskl - INFO - Epoch [28][600/1281] lr: 2.299e-02, eta: 1 day, 6:17:04, time: 1.389, data_time: 0.000, memory: 9000, top1_acc: 0.8750, top5_acc: 0.9975, loss_cls: 2.9466, loss: 2.9466 +2025-05-05 14:49:52,815 - pyskl - INFO - Epoch [28][700/1281] lr: 2.298e-02, eta: 1 day, 6:21:19, time: 1.426, data_time: 0.000, memory: 9000, top1_acc: 0.8738, top5_acc: 0.9962, loss_cls: 2.8573, loss: 2.8573 +2025-05-05 14:52:13,830 - pyskl - INFO - Epoch [28][800/1281] lr: 2.297e-02, eta: 1 day, 6:25:26, time: 1.410, data_time: 0.000, memory: 9000, top1_acc: 0.8869, top5_acc: 0.9962, loss_cls: 2.9216, loss: 2.9216 +2025-05-05 14:54:31,794 - pyskl - INFO - Epoch [28][900/1281] lr: 2.295e-02, eta: 1 day, 6:29:17, time: 1.380, data_time: 0.000, memory: 9000, top1_acc: 0.8731, top5_acc: 0.9925, loss_cls: 2.9344, loss: 2.9344 +2025-05-05 14:56:53,691 - pyskl - INFO - Epoch [28][1000/1281] lr: 2.294e-02, eta: 1 day, 6:33:23, time: 1.419, data_time: 0.000, memory: 9000, top1_acc: 0.8562, top5_acc: 0.9950, loss_cls: 3.0053, loss: 3.0053 +2025-05-05 14:59:11,869 - pyskl - INFO - Epoch [28][1100/1281] lr: 2.293e-02, eta: 1 day, 6:37:10, time: 1.382, data_time: 0.000, memory: 9000, top1_acc: 0.8875, top5_acc: 0.9962, loss_cls: 2.8325, loss: 2.8325 +2025-05-05 15:01:30,027 - pyskl - INFO - Epoch [28][1200/1281] lr: 2.292e-02, eta: 1 day, 6:40:55, time: 1.382, data_time: 0.000, memory: 9000, top1_acc: 0.8500, top5_acc: 0.9925, loss_cls: 2.9527, loss: 2.9527 +2025-05-05 15:02:56,295 - pyskl - INFO - Saving checkpoint at 28 epochs +2025-05-05 15:03:55,714 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 15:03:55,769 - pyskl - INFO - +top1_acc 0.7993 +top5_acc 0.9786 +2025-05-05 15:03:55,769 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 15:03:55,776 - pyskl - INFO - +mean_acc 0.7162 +2025-05-05 15:03:55,778 - pyskl - INFO - Epoch(val) [28][533] top1_acc: 0.7993, top5_acc: 0.9786, mean_class_accuracy: 0.7162 +2025-05-05 15:05:11,202 - pyskl - INFO - Epoch [29][100/1281] lr: 2.290e-02, eta: 1 day, 6:35:00, time: 0.754, data_time: 0.176, memory: 9000, top1_acc: 0.8869, top5_acc: 0.9969, loss_cls: 2.8816, loss: 2.8816 +2025-05-05 15:06:18,789 - pyskl - INFO - Epoch [29][200/1281] lr: 2.289e-02, eta: 1 day, 6:33:37, time: 0.676, data_time: 0.000, memory: 9000, top1_acc: 0.8875, top5_acc: 0.9975, loss_cls: 2.8314, loss: 2.8314 +2025-05-05 15:07:31,177 - pyskl - INFO - Epoch [29][300/1281] lr: 2.288e-02, eta: 1 day, 6:32:35, time: 0.724, data_time: 0.000, memory: 9000, top1_acc: 0.8794, top5_acc: 0.9962, loss_cls: 2.8903, loss: 2.8903 +2025-05-05 15:08:35,840 - pyskl - INFO - Epoch [29][400/1281] lr: 2.287e-02, eta: 1 day, 6:30:59, time: 0.647, data_time: 0.000, memory: 9000, top1_acc: 0.8769, top5_acc: 0.9994, loss_cls: 2.8223, loss: 2.8223 +2025-05-05 15:09:37,973 - pyskl - INFO - Epoch [29][500/1281] lr: 2.285e-02, eta: 1 day, 6:29:13, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.8738, top5_acc: 0.9969, loss_cls: 2.9242, loss: 2.9242 +2025-05-05 15:10:43,707 - pyskl - INFO - Epoch [29][600/1281] lr: 2.284e-02, eta: 1 day, 6:27:42, time: 0.657, data_time: 0.000, memory: 9000, top1_acc: 0.8831, top5_acc: 0.9956, loss_cls: 2.8965, loss: 2.8965 +2025-05-05 15:11:57,034 - pyskl - INFO - Epoch [29][700/1281] lr: 2.283e-02, eta: 1 day, 6:26:44, time: 0.733, data_time: 0.000, memory: 9000, top1_acc: 0.8812, top5_acc: 0.9925, loss_cls: 2.8684, loss: 2.8684 +2025-05-05 15:13:03,112 - pyskl - INFO - Epoch [29][800/1281] lr: 2.282e-02, eta: 1 day, 6:25:15, time: 0.661, data_time: 0.000, memory: 9000, top1_acc: 0.8844, top5_acc: 0.9981, loss_cls: 2.7918, loss: 2.7918 +2025-05-05 15:14:04,813 - pyskl - INFO - Epoch [29][900/1281] lr: 2.281e-02, eta: 1 day, 6:23:28, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.8844, top5_acc: 0.9956, loss_cls: 2.8856, loss: 2.8856 +2025-05-05 15:15:07,519 - pyskl - INFO - Epoch [29][1000/1281] lr: 2.280e-02, eta: 1 day, 6:21:45, time: 0.627, data_time: 0.000, memory: 9000, top1_acc: 0.8775, top5_acc: 0.9944, loss_cls: 2.9242, loss: 2.9242 +2025-05-05 15:16:19,187 - pyskl - INFO - Epoch [29][1100/1281] lr: 2.279e-02, eta: 1 day, 6:20:40, time: 0.717, data_time: 0.000, memory: 9000, top1_acc: 0.8638, top5_acc: 0.9962, loss_cls: 2.9428, loss: 2.9428 +2025-05-05 15:17:27,853 - pyskl - INFO - Epoch [29][1200/1281] lr: 2.277e-02, eta: 1 day, 6:19:22, time: 0.687, data_time: 0.000, memory: 9000, top1_acc: 0.8894, top5_acc: 0.9944, loss_cls: 2.8502, loss: 2.8502 +2025-05-05 15:18:18,566 - pyskl - INFO - Saving checkpoint at 29 epochs +2025-05-05 15:19:09,751 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 15:19:09,804 - pyskl - INFO - +top1_acc 0.8322 +top5_acc 0.9863 +2025-05-05 15:19:09,805 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 15:19:09,810 - pyskl - INFO - +mean_acc 0.7785 +2025-05-05 15:19:09,869 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_23.pth was removed +2025-05-05 15:19:11,372 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_29.pth. +2025-05-05 15:19:11,373 - pyskl - INFO - Best top1_acc is 0.8322 at 29 epoch. +2025-05-05 15:19:11,377 - pyskl - INFO - Epoch(val) [29][533] top1_acc: 0.8322, top5_acc: 0.9863, mean_class_accuracy: 0.7785 +2025-05-05 15:20:23,665 - pyskl - INFO - Epoch [30][100/1281] lr: 2.275e-02, eta: 1 day, 6:13:25, time: 0.723, data_time: 0.179, memory: 9000, top1_acc: 0.8962, top5_acc: 0.9931, loss_cls: 2.8769, loss: 2.8769 +2025-05-05 15:21:32,621 - pyskl - INFO - Epoch [30][200/1281] lr: 2.274e-02, eta: 1 day, 6:12:10, time: 0.690, data_time: 0.000, memory: 9000, top1_acc: 0.8800, top5_acc: 0.9975, loss_cls: 2.9337, loss: 2.9337 +2025-05-05 15:22:35,449 - pyskl - INFO - Epoch [30][300/1281] lr: 2.273e-02, eta: 1 day, 6:10:29, time: 0.628, data_time: 0.000, memory: 9000, top1_acc: 0.8925, top5_acc: 0.9969, loss_cls: 2.7435, loss: 2.7435 +2025-05-05 15:23:35,740 - pyskl - INFO - Epoch [30][400/1281] lr: 2.272e-02, eta: 1 day, 6:08:38, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.8738, top5_acc: 0.9906, loss_cls: 2.8571, loss: 2.8571 +2025-05-05 15:24:38,622 - pyskl - INFO - Epoch [30][500/1281] lr: 2.271e-02, eta: 1 day, 6:06:58, time: 0.629, data_time: 0.000, memory: 9000, top1_acc: 0.8675, top5_acc: 0.9956, loss_cls: 3.0149, loss: 3.0149 +2025-05-05 15:25:49,978 - pyskl - INFO - Epoch [30][600/1281] lr: 2.269e-02, eta: 1 day, 6:05:52, time: 0.714, data_time: 0.000, memory: 9000, top1_acc: 0.8738, top5_acc: 0.9969, loss_cls: 2.8836, loss: 2.8836 +2025-05-05 15:26:56,843 - pyskl - INFO - Epoch [30][700/1281] lr: 2.268e-02, eta: 1 day, 6:04:29, time: 0.669, data_time: 0.000, memory: 9000, top1_acc: 0.8681, top5_acc: 0.9950, loss_cls: 2.8629, loss: 2.8629 +2025-05-05 15:27:58,366 - pyskl - INFO - Epoch [30][800/1281] lr: 2.267e-02, eta: 1 day, 6:02:43, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 0.8794, top5_acc: 0.9981, loss_cls: 2.8731, loss: 2.8731 +2025-05-05 15:28:59,918 - pyskl - INFO - Epoch [30][900/1281] lr: 2.266e-02, eta: 1 day, 6:00:58, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.8844, top5_acc: 0.9981, loss_cls: 2.9155, loss: 2.9155 +2025-05-05 15:30:08,164 - pyskl - INFO - Epoch [30][1000/1281] lr: 2.265e-02, eta: 1 day, 5:59:41, time: 0.682, data_time: 0.000, memory: 9000, top1_acc: 0.9012, top5_acc: 0.9962, loss_cls: 2.7684, loss: 2.7684 +2025-05-05 15:31:19,133 - pyskl - INFO - Epoch [30][1100/1281] lr: 2.263e-02, eta: 1 day, 5:58:34, time: 0.710, data_time: 0.000, memory: 9000, top1_acc: 0.8844, top5_acc: 0.9956, loss_cls: 2.8038, loss: 2.8038 +2025-05-05 15:32:20,800 - pyskl - INFO - Epoch [30][1200/1281] lr: 2.262e-02, eta: 1 day, 5:56:50, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.8919, top5_acc: 0.9938, loss_cls: 2.8044, loss: 2.8044 +2025-05-05 15:33:11,603 - pyskl - INFO - Saving checkpoint at 30 epochs +2025-05-05 15:34:03,334 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 15:34:03,389 - pyskl - INFO - +top1_acc 0.8376 +top5_acc 0.9903 +2025-05-05 15:34:03,389 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 15:34:03,396 - pyskl - INFO - +mean_acc 0.8022 +2025-05-05 15:34:03,457 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_29.pth was removed +2025-05-05 15:34:04,991 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_30.pth. +2025-05-05 15:34:04,991 - pyskl - INFO - Best top1_acc is 0.8376 at 30 epoch. +2025-05-05 15:34:04,996 - pyskl - INFO - Epoch(val) [30][533] top1_acc: 0.8376, top5_acc: 0.9903, mean_class_accuracy: 0.8022 +2025-05-05 15:35:21,148 - pyskl - INFO - Epoch [31][100/1281] lr: 2.260e-02, eta: 1 day, 5:51:21, time: 0.761, data_time: 0.184, memory: 9000, top1_acc: 0.8925, top5_acc: 0.9975, loss_cls: 2.7112, loss: 2.7112 +2025-05-05 15:36:23,927 - pyskl - INFO - Epoch [31][200/1281] lr: 2.259e-02, eta: 1 day, 5:49:42, time: 0.628, data_time: 0.000, memory: 9000, top1_acc: 0.8956, top5_acc: 0.9969, loss_cls: 2.7321, loss: 2.7321 +2025-05-05 15:37:23,498 - pyskl - INFO - Epoch [31][300/1281] lr: 2.258e-02, eta: 1 day, 5:47:51, time: 0.596, data_time: 0.000, memory: 9000, top1_acc: 0.8906, top5_acc: 0.9956, loss_cls: 2.8606, loss: 2.8606 +2025-05-05 15:38:25,484 - pyskl - INFO - Epoch [31][400/1281] lr: 2.256e-02, eta: 1 day, 5:46:10, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.8819, top5_acc: 0.9938, loss_cls: 2.7886, loss: 2.7886 +2025-05-05 15:39:33,828 - pyskl - INFO - Epoch [31][500/1281] lr: 2.255e-02, eta: 1 day, 5:44:54, time: 0.683, data_time: 0.000, memory: 9000, top1_acc: 0.8756, top5_acc: 0.9956, loss_cls: 2.9133, loss: 2.9133 +2025-05-05 15:40:43,498 - pyskl - INFO - Epoch [31][600/1281] lr: 2.254e-02, eta: 1 day, 5:43:43, time: 0.697, data_time: 0.000, memory: 9000, top1_acc: 0.8938, top5_acc: 0.9981, loss_cls: 2.7251, loss: 2.7251 +2025-05-05 15:41:43,919 - pyskl - INFO - Epoch [31][700/1281] lr: 2.253e-02, eta: 1 day, 5:41:56, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.8894, top5_acc: 0.9994, loss_cls: 2.8601, loss: 2.8601 +2025-05-05 15:42:46,360 - pyskl - INFO - Epoch [31][800/1281] lr: 2.252e-02, eta: 1 day, 5:40:17, time: 0.624, data_time: 0.000, memory: 9000, top1_acc: 0.8869, top5_acc: 0.9975, loss_cls: 2.8531, loss: 2.8531 +2025-05-05 15:43:52,803 - pyskl - INFO - Epoch [31][900/1281] lr: 2.250e-02, eta: 1 day, 5:38:54, time: 0.664, data_time: 0.000, memory: 9000, top1_acc: 0.8844, top5_acc: 0.9956, loss_cls: 2.8854, loss: 2.8854 +2025-05-05 15:45:05,713 - pyskl - INFO - Epoch [31][1000/1281] lr: 2.249e-02, eta: 1 day, 5:37:56, time: 0.729, data_time: 0.000, memory: 9000, top1_acc: 0.8625, top5_acc: 0.9950, loss_cls: 2.9273, loss: 2.9273 +2025-05-05 15:46:08,859 - pyskl - INFO - Epoch [31][1100/1281] lr: 2.248e-02, eta: 1 day, 5:36:21, time: 0.631, data_time: 0.000, memory: 9000, top1_acc: 0.8881, top5_acc: 0.9950, loss_cls: 2.8584, loss: 2.8584 +2025-05-05 15:47:09,223 - pyskl - INFO - Epoch [31][1200/1281] lr: 2.247e-02, eta: 1 day, 5:34:34, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.8925, top5_acc: 0.9950, loss_cls: 2.7636, loss: 2.7636 +2025-05-05 15:48:01,675 - pyskl - INFO - Saving checkpoint at 31 epochs +2025-05-05 15:49:00,108 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 15:49:00,164 - pyskl - INFO - +top1_acc 0.8277 +top5_acc 0.9871 +2025-05-05 15:49:00,164 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 15:49:00,172 - pyskl - INFO - +mean_acc 0.7689 +2025-05-05 15:49:00,175 - pyskl - INFO - Epoch(val) [31][533] top1_acc: 0.8277, top5_acc: 0.9871, mean_class_accuracy: 0.7689 +2025-05-05 15:50:15,048 - pyskl - INFO - Epoch [32][100/1281] lr: 2.244e-02, eta: 1 day, 5:29:11, time: 0.749, data_time: 0.180, memory: 9000, top1_acc: 0.9069, top5_acc: 0.9988, loss_cls: 2.7508, loss: 2.7508 +2025-05-05 15:51:15,187 - pyskl - INFO - Epoch [32][200/1281] lr: 2.243e-02, eta: 1 day, 5:27:25, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.8988, top5_acc: 0.9969, loss_cls: 2.8287, loss: 2.8287 +2025-05-05 15:52:18,060 - pyskl - INFO - Epoch [32][300/1281] lr: 2.242e-02, eta: 1 day, 5:25:49, time: 0.629, data_time: 0.000, memory: 9000, top1_acc: 0.8794, top5_acc: 0.9975, loss_cls: 2.8577, loss: 2.8577 +2025-05-05 15:53:25,761 - pyskl - INFO - Epoch [32][400/1281] lr: 2.241e-02, eta: 1 day, 5:24:32, time: 0.677, data_time: 0.000, memory: 9000, top1_acc: 0.8788, top5_acc: 0.9925, loss_cls: 2.9195, loss: 2.9195 +2025-05-05 15:54:36,025 - pyskl - INFO - Epoch [32][500/1281] lr: 2.239e-02, eta: 1 day, 5:23:25, time: 0.703, data_time: 0.000, memory: 9000, top1_acc: 0.8844, top5_acc: 0.9969, loss_cls: 2.8836, loss: 2.8836 +2025-05-05 15:55:36,085 - pyskl - INFO - Epoch [32][600/1281] lr: 2.238e-02, eta: 1 day, 5:21:39, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.8856, top5_acc: 0.9994, loss_cls: 2.7785, loss: 2.7785 +2025-05-05 15:56:38,321 - pyskl - INFO - Epoch [32][700/1281] lr: 2.237e-02, eta: 1 day, 5:20:02, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.8825, top5_acc: 0.9962, loss_cls: 2.8609, loss: 2.8609 +2025-05-05 15:57:43,611 - pyskl - INFO - Epoch [32][800/1281] lr: 2.236e-02, eta: 1 day, 5:18:36, time: 0.653, data_time: 0.000, memory: 9000, top1_acc: 0.8894, top5_acc: 0.9969, loss_cls: 2.8198, loss: 2.8198 +2025-05-05 15:58:56,400 - pyskl - INFO - Epoch [32][900/1281] lr: 2.234e-02, eta: 1 day, 5:17:39, time: 0.728, data_time: 0.000, memory: 9000, top1_acc: 0.8844, top5_acc: 0.9944, loss_cls: 2.8958, loss: 2.8958 +2025-05-05 15:59:59,707 - pyskl - INFO - Epoch [32][1000/1281] lr: 2.233e-02, eta: 1 day, 5:16:06, time: 0.633, data_time: 0.000, memory: 9000, top1_acc: 0.8781, top5_acc: 0.9938, loss_cls: 2.8235, loss: 2.8235 +2025-05-05 16:00:58,908 - pyskl - INFO - Epoch [32][1100/1281] lr: 2.232e-02, eta: 1 day, 5:14:18, time: 0.592, data_time: 0.000, memory: 9000, top1_acc: 0.8800, top5_acc: 0.9944, loss_cls: 2.8477, loss: 2.8477 +2025-05-05 16:02:00,107 - pyskl - INFO - Epoch [32][1200/1281] lr: 2.231e-02, eta: 1 day, 5:12:37, time: 0.612, data_time: 0.000, memory: 9000, top1_acc: 0.8756, top5_acc: 0.9950, loss_cls: 2.8898, loss: 2.8898 +2025-05-05 16:02:57,377 - pyskl - INFO - Saving checkpoint at 32 epochs +2025-05-05 16:03:54,736 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 16:03:54,790 - pyskl - INFO - +top1_acc 0.8081 +top5_acc 0.9843 +2025-05-05 16:03:54,790 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 16:03:54,797 - pyskl - INFO - +mean_acc 0.7571 +2025-05-05 16:03:54,799 - pyskl - INFO - Epoch(val) [32][533] top1_acc: 0.8081, top5_acc: 0.9843, mean_class_accuracy: 0.7571 +2025-05-05 16:05:03,845 - pyskl - INFO - Epoch [33][100/1281] lr: 2.228e-02, eta: 1 day, 5:07:03, time: 0.690, data_time: 0.180, memory: 9000, top1_acc: 0.8975, top5_acc: 0.9962, loss_cls: 2.8220, loss: 2.8220 +2025-05-05 16:06:03,525 - pyskl - INFO - Epoch [33][200/1281] lr: 2.227e-02, eta: 1 day, 5:05:18, time: 0.597, data_time: 0.000, memory: 9000, top1_acc: 0.9025, top5_acc: 0.9981, loss_cls: 2.7332, loss: 2.7332 +2025-05-05 16:07:08,350 - pyskl - INFO - Epoch [33][300/1281] lr: 2.226e-02, eta: 1 day, 5:03:52, time: 0.648, data_time: 0.000, memory: 9000, top1_acc: 0.8994, top5_acc: 0.9975, loss_cls: 2.8016, loss: 2.8016 +2025-05-05 16:08:19,774 - pyskl - INFO - Epoch [33][400/1281] lr: 2.225e-02, eta: 1 day, 5:02:50, time: 0.714, data_time: 0.000, memory: 9000, top1_acc: 0.8819, top5_acc: 0.9981, loss_cls: 2.7940, loss: 2.7940 +2025-05-05 16:09:23,625 - pyskl - INFO - Epoch [33][500/1281] lr: 2.223e-02, eta: 1 day, 5:01:21, time: 0.639, data_time: 0.000, memory: 9000, top1_acc: 0.8706, top5_acc: 0.9950, loss_cls: 2.8491, loss: 2.8491 +2025-05-05 16:10:24,494 - pyskl - INFO - Epoch [33][600/1281] lr: 2.222e-02, eta: 1 day, 4:59:40, time: 0.609, data_time: 0.000, memory: 9000, top1_acc: 0.8938, top5_acc: 0.9988, loss_cls: 2.7073, loss: 2.7073 +2025-05-05 16:11:26,870 - pyskl - INFO - Epoch [33][700/1281] lr: 2.221e-02, eta: 1 day, 4:58:06, time: 0.624, data_time: 0.000, memory: 9000, top1_acc: 0.8731, top5_acc: 0.9969, loss_cls: 2.9524, loss: 2.9524 +2025-05-05 16:12:38,270 - pyskl - INFO - Epoch [33][800/1281] lr: 2.219e-02, eta: 1 day, 4:57:04, time: 0.714, data_time: 0.000, memory: 9000, top1_acc: 0.8700, top5_acc: 0.9962, loss_cls: 2.9046, loss: 2.9046 +2025-05-05 16:13:43,003 - pyskl - INFO - Epoch [33][900/1281] lr: 2.218e-02, eta: 1 day, 4:55:38, time: 0.647, data_time: 0.000, memory: 9000, top1_acc: 0.8825, top5_acc: 0.9931, loss_cls: 2.7621, loss: 2.7621 +2025-05-05 16:14:43,987 - pyskl - INFO - Epoch [33][1000/1281] lr: 2.217e-02, eta: 1 day, 4:53:59, time: 0.610, data_time: 0.000, memory: 9000, top1_acc: 0.8775, top5_acc: 0.9975, loss_cls: 2.8493, loss: 2.8493 +2025-05-05 16:15:47,208 - pyskl - INFO - Epoch [33][1100/1281] lr: 2.216e-02, eta: 1 day, 4:52:28, time: 0.632, data_time: 0.000, memory: 9000, top1_acc: 0.8850, top5_acc: 0.9919, loss_cls: 2.8722, loss: 2.8722 +2025-05-05 16:16:55,527 - pyskl - INFO - Epoch [33][1200/1281] lr: 2.214e-02, eta: 1 day, 4:51:16, time: 0.683, data_time: 0.000, memory: 9000, top1_acc: 0.8900, top5_acc: 0.9944, loss_cls: 2.7844, loss: 2.7844 +2025-05-05 16:17:52,841 - pyskl - INFO - Saving checkpoint at 33 epochs +2025-05-05 16:18:43,726 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 16:18:43,781 - pyskl - INFO - +top1_acc 0.8393 +top5_acc 0.9871 +2025-05-05 16:18:43,781 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 16:18:43,788 - pyskl - INFO - +mean_acc 0.7940 +2025-05-05 16:18:43,845 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_30.pth was removed +2025-05-05 16:18:45,373 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_33.pth. +2025-05-05 16:18:45,374 - pyskl - INFO - Best top1_acc is 0.8393 at 33 epoch. +2025-05-05 16:18:45,378 - pyskl - INFO - Epoch(val) [33][533] top1_acc: 0.8393, top5_acc: 0.9871, mean_class_accuracy: 0.7940 +2025-05-05 16:19:53,124 - pyskl - INFO - Epoch [34][100/1281] lr: 2.212e-02, eta: 1 day, 4:45:47, time: 0.677, data_time: 0.180, memory: 9000, top1_acc: 0.8894, top5_acc: 0.9962, loss_cls: 2.8347, loss: 2.8347 +2025-05-05 16:20:53,337 - pyskl - INFO - Epoch [34][200/1281] lr: 2.211e-02, eta: 1 day, 4:44:06, time: 0.602, data_time: 0.000, memory: 9000, top1_acc: 0.8844, top5_acc: 0.9944, loss_cls: 2.7924, loss: 2.7924 +2025-05-05 16:22:02,588 - pyskl - INFO - Epoch [34][300/1281] lr: 2.209e-02, eta: 1 day, 4:42:57, time: 0.692, data_time: 0.000, memory: 9000, top1_acc: 0.9062, top5_acc: 0.9994, loss_cls: 2.7512, loss: 2.7512 +2025-05-05 16:23:08,868 - pyskl - INFO - Epoch [34][400/1281] lr: 2.208e-02, eta: 1 day, 4:41:38, time: 0.663, data_time: 0.000, memory: 9000, top1_acc: 0.8925, top5_acc: 0.9962, loss_cls: 2.8060, loss: 2.8060 +2025-05-05 16:24:09,781 - pyskl - INFO - Epoch [34][500/1281] lr: 2.207e-02, eta: 1 day, 4:40:01, time: 0.609, data_time: 0.000, memory: 9000, top1_acc: 0.8875, top5_acc: 0.9981, loss_cls: 2.8245, loss: 2.8245 +2025-05-05 16:25:10,465 - pyskl - INFO - Epoch [34][600/1281] lr: 2.205e-02, eta: 1 day, 4:38:22, time: 0.607, data_time: 0.000, memory: 9000, top1_acc: 0.8894, top5_acc: 0.9956, loss_cls: 2.7909, loss: 2.7909 +2025-05-05 16:26:16,634 - pyskl - INFO - Epoch [34][700/1281] lr: 2.204e-02, eta: 1 day, 4:37:03, time: 0.662, data_time: 0.000, memory: 9000, top1_acc: 0.8931, top5_acc: 0.9981, loss_cls: 2.8199, loss: 2.8199 +2025-05-05 16:27:26,733 - pyskl - INFO - Epoch [34][800/1281] lr: 2.203e-02, eta: 1 day, 4:35:58, time: 0.701, data_time: 0.000, memory: 9000, top1_acc: 0.8831, top5_acc: 0.9981, loss_cls: 2.7590, loss: 2.7590 +2025-05-05 16:28:27,770 - pyskl - INFO - Epoch [34][900/1281] lr: 2.201e-02, eta: 1 day, 4:34:21, time: 0.610, data_time: 0.000, memory: 9000, top1_acc: 0.8950, top5_acc: 0.9969, loss_cls: 2.7586, loss: 2.7586 +2025-05-05 16:29:28,933 - pyskl - INFO - Epoch [34][1000/1281] lr: 2.200e-02, eta: 1 day, 4:32:45, time: 0.612, data_time: 0.000, memory: 9000, top1_acc: 0.8825, top5_acc: 0.9938, loss_cls: 2.8882, loss: 2.8882 +2025-05-05 16:30:31,058 - pyskl - INFO - Epoch [34][1100/1281] lr: 2.199e-02, eta: 1 day, 4:31:12, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.8956, top5_acc: 0.9975, loss_cls: 2.7366, loss: 2.7366 +2025-05-05 16:31:40,498 - pyskl - INFO - Epoch [34][1200/1281] lr: 2.197e-02, eta: 1 day, 4:30:05, time: 0.694, data_time: 0.000, memory: 9000, top1_acc: 0.8944, top5_acc: 0.9988, loss_cls: 2.8366, loss: 2.8366 +2025-05-05 16:32:33,199 - pyskl - INFO - Saving checkpoint at 34 epochs +2025-05-05 16:33:23,298 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 16:33:23,352 - pyskl - INFO - +top1_acc 0.8481 +top5_acc 0.9880 +2025-05-05 16:33:23,352 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 16:33:23,358 - pyskl - INFO - +mean_acc 0.7769 +2025-05-05 16:33:23,416 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_33.pth was removed +2025-05-05 16:33:24,948 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_34.pth. +2025-05-05 16:33:24,949 - pyskl - INFO - Best top1_acc is 0.8481 at 34 epoch. +2025-05-05 16:33:24,953 - pyskl - INFO - Epoch(val) [34][533] top1_acc: 0.8481, top5_acc: 0.9880, mean_class_accuracy: 0.7769 +2025-05-05 16:34:34,297 - pyskl - INFO - Epoch [35][100/1281] lr: 2.195e-02, eta: 1 day, 4:24:51, time: 0.693, data_time: 0.177, memory: 9000, top1_acc: 0.9038, top5_acc: 0.9975, loss_cls: 2.7451, loss: 2.7451 +2025-05-05 16:35:36,255 - pyskl - INFO - Epoch [35][200/1281] lr: 2.194e-02, eta: 1 day, 4:23:18, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.9044, top5_acc: 0.9981, loss_cls: 2.7628, loss: 2.7628 +2025-05-05 16:36:44,432 - pyskl - INFO - Epoch [35][300/1281] lr: 2.192e-02, eta: 1 day, 4:22:07, time: 0.682, data_time: 0.000, memory: 9000, top1_acc: 0.8994, top5_acc: 0.9969, loss_cls: 2.6980, loss: 2.6980 +2025-05-05 16:37:46,594 - pyskl - INFO - Epoch [35][400/1281] lr: 2.191e-02, eta: 1 day, 4:20:36, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.9000, top5_acc: 0.9981, loss_cls: 2.7057, loss: 2.7057 +2025-05-05 16:38:47,671 - pyskl - INFO - Epoch [35][500/1281] lr: 2.190e-02, eta: 1 day, 4:19:01, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.8994, top5_acc: 0.9975, loss_cls: 2.7195, loss: 2.7195 +2025-05-05 16:39:49,719 - pyskl - INFO - Epoch [35][600/1281] lr: 2.188e-02, eta: 1 day, 4:17:29, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.8762, top5_acc: 0.9919, loss_cls: 2.8639, loss: 2.8639 +2025-05-05 16:40:59,227 - pyskl - INFO - Epoch [35][700/1281] lr: 2.187e-02, eta: 1 day, 4:16:22, time: 0.695, data_time: 0.000, memory: 9000, top1_acc: 0.8819, top5_acc: 0.9950, loss_cls: 2.8201, loss: 2.8201 +2025-05-05 16:42:02,735 - pyskl - INFO - Epoch [35][800/1281] lr: 2.185e-02, eta: 1 day, 4:14:56, time: 0.635, data_time: 0.000, memory: 9000, top1_acc: 0.8875, top5_acc: 0.9969, loss_cls: 2.7730, loss: 2.7730 +2025-05-05 16:43:04,868 - pyskl - INFO - Epoch [35][900/1281] lr: 2.184e-02, eta: 1 day, 4:13:25, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.8844, top5_acc: 0.9969, loss_cls: 2.8515, loss: 2.8515 +2025-05-05 16:44:07,575 - pyskl - INFO - Epoch [35][1000/1281] lr: 2.183e-02, eta: 1 day, 4:11:56, time: 0.627, data_time: 0.000, memory: 9000, top1_acc: 0.9006, top5_acc: 0.9925, loss_cls: 2.8735, loss: 2.8735 +2025-05-05 16:45:14,038 - pyskl - INFO - Epoch [35][1100/1281] lr: 2.181e-02, eta: 1 day, 4:10:40, time: 0.665, data_time: 0.000, memory: 9000, top1_acc: 0.8844, top5_acc: 0.9975, loss_cls: 2.8700, loss: 2.8700 +2025-05-05 16:46:20,450 - pyskl - INFO - Epoch [35][1200/1281] lr: 2.180e-02, eta: 1 day, 4:09:23, time: 0.664, data_time: 0.000, memory: 9000, top1_acc: 0.8838, top5_acc: 0.9969, loss_cls: 2.8294, loss: 2.8294 +2025-05-05 16:47:10,613 - pyskl - INFO - Saving checkpoint at 35 epochs +2025-05-05 16:48:01,956 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 16:48:02,010 - pyskl - INFO - +top1_acc 0.8256 +top5_acc 0.9844 +2025-05-05 16:48:02,010 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 16:48:02,017 - pyskl - INFO - +mean_acc 0.7768 +2025-05-05 16:48:02,019 - pyskl - INFO - Epoch(val) [35][533] top1_acc: 0.8256, top5_acc: 0.9844, mean_class_accuracy: 0.7768 +2025-05-05 16:49:13,259 - pyskl - INFO - Epoch [36][100/1281] lr: 2.178e-02, eta: 1 day, 4:04:24, time: 0.712, data_time: 0.179, memory: 9000, top1_acc: 0.8806, top5_acc: 0.9975, loss_cls: 2.8396, loss: 2.8396 +2025-05-05 16:50:19,810 - pyskl - INFO - Epoch [36][200/1281] lr: 2.176e-02, eta: 1 day, 4:03:09, time: 0.666, data_time: 0.000, memory: 9000, top1_acc: 0.9031, top5_acc: 0.9969, loss_cls: 2.7206, loss: 2.7206 +2025-05-05 16:51:22,341 - pyskl - INFO - Epoch [36][300/1281] lr: 2.175e-02, eta: 1 day, 4:01:40, time: 0.625, data_time: 0.000, memory: 9000, top1_acc: 0.8938, top5_acc: 0.9969, loss_cls: 2.7717, loss: 2.7717 +2025-05-05 16:52:23,487 - pyskl - INFO - Epoch [36][400/1281] lr: 2.173e-02, eta: 1 day, 4:00:07, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.8981, top5_acc: 0.9994, loss_cls: 2.6904, loss: 2.6904 +2025-05-05 16:53:25,393 - pyskl - INFO - Epoch [36][500/1281] lr: 2.172e-02, eta: 1 day, 3:58:37, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9012, top5_acc: 0.9956, loss_cls: 2.6517, loss: 2.6517 +2025-05-05 16:54:33,416 - pyskl - INFO - Epoch [36][600/1281] lr: 2.171e-02, eta: 1 day, 3:57:26, time: 0.680, data_time: 0.000, memory: 9000, top1_acc: 0.9113, top5_acc: 0.9994, loss_cls: 2.7300, loss: 2.7300 +2025-05-05 16:55:40,285 - pyskl - INFO - Epoch [36][700/1281] lr: 2.169e-02, eta: 1 day, 3:56:12, time: 0.669, data_time: 0.000, memory: 9000, top1_acc: 0.8994, top5_acc: 0.9950, loss_cls: 2.6840, loss: 2.6840 +2025-05-05 16:56:41,479 - pyskl - INFO - Epoch [36][800/1281] lr: 2.168e-02, eta: 1 day, 3:54:40, time: 0.612, data_time: 0.000, memory: 9000, top1_acc: 0.8744, top5_acc: 0.9938, loss_cls: 2.8876, loss: 2.8876 +2025-05-05 16:57:43,550 - pyskl - INFO - Epoch [36][900/1281] lr: 2.167e-02, eta: 1 day, 3:53:10, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.8900, top5_acc: 0.9944, loss_cls: 2.8565, loss: 2.8565 +2025-05-05 16:58:46,778 - pyskl - INFO - Epoch [36][1000/1281] lr: 2.165e-02, eta: 1 day, 3:51:45, time: 0.632, data_time: 0.000, memory: 9000, top1_acc: 0.8888, top5_acc: 0.9981, loss_cls: 2.7991, loss: 2.7991 +2025-05-05 16:59:56,448 - pyskl - INFO - Epoch [36][1100/1281] lr: 2.164e-02, eta: 1 day, 3:50:40, time: 0.697, data_time: 0.000, memory: 9000, top1_acc: 0.8825, top5_acc: 0.9956, loss_cls: 2.7393, loss: 2.7393 +2025-05-05 17:00:58,223 - pyskl - INFO - Epoch [36][1200/1281] lr: 2.162e-02, eta: 1 day, 3:49:10, time: 0.618, data_time: 0.000, memory: 9000, top1_acc: 0.8881, top5_acc: 0.9938, loss_cls: 2.8321, loss: 2.8321 +2025-05-05 17:01:48,115 - pyskl - INFO - Saving checkpoint at 36 epochs +2025-05-05 17:02:39,847 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 17:02:39,902 - pyskl - INFO - +top1_acc 0.8438 +top5_acc 0.9876 +2025-05-05 17:02:39,903 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 17:02:39,911 - pyskl - INFO - +mean_acc 0.7895 +2025-05-05 17:02:39,914 - pyskl - INFO - Epoch(val) [36][533] top1_acc: 0.8438, top5_acc: 0.9876, mean_class_accuracy: 0.7895 +2025-05-05 17:03:50,878 - pyskl - INFO - Epoch [37][100/1281] lr: 2.160e-02, eta: 1 day, 3:44:18, time: 0.710, data_time: 0.182, memory: 9000, top1_acc: 0.8988, top5_acc: 0.9962, loss_cls: 2.7146, loss: 2.7146 +2025-05-05 17:04:55,152 - pyskl - INFO - Epoch [37][200/1281] lr: 2.158e-02, eta: 1 day, 3:42:56, time: 0.643, data_time: 0.000, memory: 9000, top1_acc: 0.8881, top5_acc: 0.9969, loss_cls: 2.7406, loss: 2.7406 +2025-05-05 17:05:55,634 - pyskl - INFO - Epoch [37][300/1281] lr: 2.157e-02, eta: 1 day, 3:41:23, time: 0.605, data_time: 0.000, memory: 9000, top1_acc: 0.9031, top5_acc: 0.9944, loss_cls: 2.7777, loss: 2.7777 +2025-05-05 17:06:58,797 - pyskl - INFO - Epoch [37][400/1281] lr: 2.156e-02, eta: 1 day, 3:39:58, time: 0.632, data_time: 0.000, memory: 9000, top1_acc: 0.8862, top5_acc: 0.9950, loss_cls: 2.8024, loss: 2.8024 +2025-05-05 17:08:02,526 - pyskl - INFO - Epoch [37][500/1281] lr: 2.154e-02, eta: 1 day, 3:38:35, time: 0.637, data_time: 0.000, memory: 9000, top1_acc: 0.8900, top5_acc: 0.9969, loss_cls: 2.8117, loss: 2.8117 +2025-05-05 17:09:10,319 - pyskl - INFO - Epoch [37][600/1281] lr: 2.153e-02, eta: 1 day, 3:37:25, time: 0.678, data_time: 0.000, memory: 9000, top1_acc: 0.9038, top5_acc: 0.9950, loss_cls: 2.7632, loss: 2.7632 +2025-05-05 17:10:12,888 - pyskl - INFO - Epoch [37][700/1281] lr: 2.151e-02, eta: 1 day, 3:35:59, time: 0.626, data_time: 0.000, memory: 9000, top1_acc: 0.9006, top5_acc: 0.9944, loss_cls: 2.7048, loss: 2.7048 +2025-05-05 17:11:14,301 - pyskl - INFO - Epoch [37][800/1281] lr: 2.150e-02, eta: 1 day, 3:34:29, time: 0.614, data_time: 0.000, memory: 9000, top1_acc: 0.8869, top5_acc: 0.9938, loss_cls: 2.7306, loss: 2.7306 +2025-05-05 17:12:17,704 - pyskl - INFO - Epoch [37][900/1281] lr: 2.149e-02, eta: 1 day, 3:33:05, time: 0.634, data_time: 0.000, memory: 9000, top1_acc: 0.8900, top5_acc: 0.9981, loss_cls: 2.7692, loss: 2.7692 +2025-05-05 17:13:22,766 - pyskl - INFO - Epoch [37][1000/1281] lr: 2.147e-02, eta: 1 day, 3:31:47, time: 0.651, data_time: 0.000, memory: 9000, top1_acc: 0.8981, top5_acc: 0.9969, loss_cls: 2.7220, loss: 2.7220 +2025-05-05 17:14:27,473 - pyskl - INFO - Epoch [37][1100/1281] lr: 2.146e-02, eta: 1 day, 3:30:27, time: 0.647, data_time: 0.000, memory: 9000, top1_acc: 0.8944, top5_acc: 0.9981, loss_cls: 2.8021, loss: 2.8021 +2025-05-05 17:15:28,145 - pyskl - INFO - Epoch [37][1200/1281] lr: 2.144e-02, eta: 1 day, 3:28:55, time: 0.607, data_time: 0.000, memory: 9000, top1_acc: 0.9062, top5_acc: 0.9975, loss_cls: 2.7489, loss: 2.7489 +2025-05-05 17:16:19,629 - pyskl - INFO - Saving checkpoint at 37 epochs +2025-05-05 17:17:12,445 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 17:17:12,502 - pyskl - INFO - +top1_acc 0.8138 +top5_acc 0.9790 +2025-05-05 17:17:12,502 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 17:17:12,510 - pyskl - INFO - +mean_acc 0.7741 +2025-05-05 17:17:12,513 - pyskl - INFO - Epoch(val) [37][533] top1_acc: 0.8138, top5_acc: 0.9790, mean_class_accuracy: 0.7741 +2025-05-05 17:18:24,959 - pyskl - INFO - Epoch [38][100/1281] lr: 2.142e-02, eta: 1 day, 3:24:16, time: 0.724, data_time: 0.180, memory: 9000, top1_acc: 0.9150, top5_acc: 0.9962, loss_cls: 2.6713, loss: 2.6713 +2025-05-05 17:19:25,526 - pyskl - INFO - Epoch [38][200/1281] lr: 2.140e-02, eta: 1 day, 3:22:44, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9113, top5_acc: 0.9962, loss_cls: 2.6214, loss: 2.6214 +2025-05-05 17:20:26,232 - pyskl - INFO - Epoch [38][300/1281] lr: 2.139e-02, eta: 1 day, 3:21:14, time: 0.607, data_time: 0.000, memory: 9000, top1_acc: 0.8912, top5_acc: 0.9975, loss_cls: 2.7970, loss: 2.7970 +2025-05-05 17:21:29,894 - pyskl - INFO - Epoch [38][400/1281] lr: 2.137e-02, eta: 1 day, 3:19:52, time: 0.637, data_time: 0.000, memory: 9000, top1_acc: 0.9150, top5_acc: 0.9962, loss_cls: 2.6722, loss: 2.6722 +2025-05-05 17:22:32,687 - pyskl - INFO - Epoch [38][500/1281] lr: 2.136e-02, eta: 1 day, 3:18:27, time: 0.628, data_time: 0.000, memory: 9000, top1_acc: 0.9019, top5_acc: 0.9969, loss_cls: 2.7048, loss: 2.7048 +2025-05-05 17:23:38,651 - pyskl - INFO - Epoch [38][600/1281] lr: 2.134e-02, eta: 1 day, 3:17:13, time: 0.660, data_time: 0.000, memory: 9000, top1_acc: 0.8762, top5_acc: 0.9975, loss_cls: 2.7928, loss: 2.7928 +2025-05-05 17:24:40,497 - pyskl - INFO - Epoch [38][700/1281] lr: 2.133e-02, eta: 1 day, 3:15:46, time: 0.618, data_time: 0.000, memory: 9000, top1_acc: 0.8994, top5_acc: 0.9988, loss_cls: 2.7109, loss: 2.7109 +2025-05-05 17:25:43,145 - pyskl - INFO - Epoch [38][800/1281] lr: 2.132e-02, eta: 1 day, 3:14:21, time: 0.626, data_time: 0.000, memory: 9000, top1_acc: 0.8888, top5_acc: 0.9988, loss_cls: 2.6997, loss: 2.6997 +2025-05-05 17:26:47,988 - pyskl - INFO - Epoch [38][900/1281] lr: 2.130e-02, eta: 1 day, 3:13:03, time: 0.648, data_time: 0.000, memory: 9000, top1_acc: 0.9031, top5_acc: 0.9962, loss_cls: 2.6182, loss: 2.6182 +2025-05-05 17:27:53,162 - pyskl - INFO - Epoch [38][1000/1281] lr: 2.129e-02, eta: 1 day, 3:11:47, time: 0.652, data_time: 0.000, memory: 9000, top1_acc: 0.9025, top5_acc: 0.9962, loss_cls: 2.6912, loss: 2.6912 +2025-05-05 17:28:55,319 - pyskl - INFO - Epoch [38][1100/1281] lr: 2.127e-02, eta: 1 day, 3:10:21, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.8912, top5_acc: 0.9975, loss_cls: 2.6673, loss: 2.6673 +2025-05-05 17:29:55,754 - pyskl - INFO - Epoch [38][1200/1281] lr: 2.126e-02, eta: 1 day, 3:08:50, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.8706, top5_acc: 0.9931, loss_cls: 2.9199, loss: 2.9199 +2025-05-05 17:30:47,575 - pyskl - INFO - Saving checkpoint at 38 epochs +2025-05-05 17:31:39,482 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 17:31:39,537 - pyskl - INFO - +top1_acc 0.8410 +top5_acc 0.9865 +2025-05-05 17:31:39,537 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 17:31:39,545 - pyskl - INFO - +mean_acc 0.7880 +2025-05-05 17:31:39,547 - pyskl - INFO - Epoch(val) [38][533] top1_acc: 0.8410, top5_acc: 0.9865, mean_class_accuracy: 0.7880 +2025-05-05 17:32:50,884 - pyskl - INFO - Epoch [39][100/1281] lr: 2.123e-02, eta: 1 day, 3:04:14, time: 0.713, data_time: 0.182, memory: 9000, top1_acc: 0.9144, top5_acc: 0.9975, loss_cls: 2.6800, loss: 2.6800 +2025-05-05 17:33:50,231 - pyskl - INFO - Epoch [39][200/1281] lr: 2.122e-02, eta: 1 day, 3:02:41, time: 0.593, data_time: 0.000, memory: 9000, top1_acc: 0.8944, top5_acc: 0.9988, loss_cls: 2.7451, loss: 2.7451 +2025-05-05 17:34:50,560 - pyskl - INFO - Epoch [39][300/1281] lr: 2.120e-02, eta: 1 day, 3:01:11, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9056, top5_acc: 0.9975, loss_cls: 2.7583, loss: 2.7583 +2025-05-05 17:35:51,792 - pyskl - INFO - Epoch [39][400/1281] lr: 2.119e-02, eta: 1 day, 2:59:43, time: 0.612, data_time: 0.000, memory: 9000, top1_acc: 0.9163, top5_acc: 0.9950, loss_cls: 2.6221, loss: 2.6221 +2025-05-05 17:36:54,573 - pyskl - INFO - Epoch [39][500/1281] lr: 2.117e-02, eta: 1 day, 2:58:20, time: 0.628, data_time: 0.000, memory: 9000, top1_acc: 0.8894, top5_acc: 0.9962, loss_cls: 2.8263, loss: 2.8263 +2025-05-05 17:37:58,362 - pyskl - INFO - Epoch [39][600/1281] lr: 2.116e-02, eta: 1 day, 2:57:01, time: 0.638, data_time: 0.000, memory: 9000, top1_acc: 0.9062, top5_acc: 0.9969, loss_cls: 2.7800, loss: 2.7800 +2025-05-05 17:38:59,412 - pyskl - INFO - Epoch [39][700/1281] lr: 2.114e-02, eta: 1 day, 2:55:33, time: 0.610, data_time: 0.000, memory: 9000, top1_acc: 0.8725, top5_acc: 0.9931, loss_cls: 2.8539, loss: 2.8539 +2025-05-05 17:40:01,977 - pyskl - INFO - Epoch [39][800/1281] lr: 2.113e-02, eta: 1 day, 2:54:10, time: 0.626, data_time: 0.000, memory: 9000, top1_acc: 0.8919, top5_acc: 0.9975, loss_cls: 2.7024, loss: 2.7024 +2025-05-05 17:41:04,129 - pyskl - INFO - Epoch [39][900/1281] lr: 2.111e-02, eta: 1 day, 2:52:45, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.8938, top5_acc: 0.9956, loss_cls: 2.7709, loss: 2.7709 +2025-05-05 17:42:07,099 - pyskl - INFO - Epoch [39][1000/1281] lr: 2.110e-02, eta: 1 day, 2:51:23, time: 0.630, data_time: 0.000, memory: 9000, top1_acc: 0.8969, top5_acc: 0.9981, loss_cls: 2.7191, loss: 2.7191 +2025-05-05 17:43:08,357 - pyskl - INFO - Epoch [39][1100/1281] lr: 2.108e-02, eta: 1 day, 2:49:56, time: 0.613, data_time: 0.000, memory: 9000, top1_acc: 0.9000, top5_acc: 0.9969, loss_cls: 2.7578, loss: 2.7578 +2025-05-05 17:44:10,607 - pyskl - INFO - Epoch [39][1200/1281] lr: 2.107e-02, eta: 1 day, 2:48:33, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.8981, top5_acc: 0.9969, loss_cls: 2.7747, loss: 2.7747 +2025-05-05 17:45:02,774 - pyskl - INFO - Saving checkpoint at 39 epochs +2025-05-05 17:45:55,726 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 17:45:55,782 - pyskl - INFO - +top1_acc 0.8341 +top5_acc 0.9866 +2025-05-05 17:45:55,782 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 17:45:55,789 - pyskl - INFO - +mean_acc 0.7748 +2025-05-05 17:45:55,791 - pyskl - INFO - Epoch(val) [39][533] top1_acc: 0.8341, top5_acc: 0.9866, mean_class_accuracy: 0.7748 +2025-05-05 17:47:06,507 - pyskl - INFO - Epoch [40][100/1281] lr: 2.104e-02, eta: 1 day, 2:44:02, time: 0.707, data_time: 0.183, memory: 9000, top1_acc: 0.9106, top5_acc: 0.9969, loss_cls: 2.6647, loss: 2.6647 +2025-05-05 17:48:04,485 - pyskl - INFO - Epoch [40][200/1281] lr: 2.103e-02, eta: 1 day, 2:42:27, time: 0.580, data_time: 0.000, memory: 9000, top1_acc: 0.9113, top5_acc: 0.9994, loss_cls: 2.6155, loss: 2.6155 +2025-05-05 17:49:06,143 - pyskl - INFO - Epoch [40][300/1281] lr: 2.101e-02, eta: 1 day, 2:41:02, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.9056, top5_acc: 0.9969, loss_cls: 2.6418, loss: 2.6418 +2025-05-05 17:50:08,018 - pyskl - INFO - Epoch [40][400/1281] lr: 2.100e-02, eta: 1 day, 2:39:38, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9062, top5_acc: 0.9988, loss_cls: 2.6265, loss: 2.6265 +2025-05-05 17:51:10,000 - pyskl - INFO - Epoch [40][500/1281] lr: 2.098e-02, eta: 1 day, 2:38:14, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.8981, top5_acc: 0.9975, loss_cls: 2.6403, loss: 2.6403 +2025-05-05 17:52:11,251 - pyskl - INFO - Epoch [40][600/1281] lr: 2.097e-02, eta: 1 day, 2:36:48, time: 0.612, data_time: 0.000, memory: 9000, top1_acc: 0.9025, top5_acc: 0.9969, loss_cls: 2.8189, loss: 2.8189 +2025-05-05 17:53:12,832 - pyskl - INFO - Epoch [40][700/1281] lr: 2.095e-02, eta: 1 day, 2:35:24, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.8925, top5_acc: 0.9950, loss_cls: 2.7387, loss: 2.7387 +2025-05-05 17:54:15,860 - pyskl - INFO - Epoch [40][800/1281] lr: 2.094e-02, eta: 1 day, 2:34:03, time: 0.630, data_time: 0.000, memory: 9000, top1_acc: 0.9012, top5_acc: 0.9962, loss_cls: 2.7426, loss: 2.7426 +2025-05-05 17:55:19,965 - pyskl - INFO - Epoch [40][900/1281] lr: 2.092e-02, eta: 1 day, 2:32:46, time: 0.641, data_time: 0.000, memory: 9000, top1_acc: 0.8844, top5_acc: 0.9975, loss_cls: 2.8126, loss: 2.8126 +2025-05-05 17:56:23,778 - pyskl - INFO - Epoch [40][1000/1281] lr: 2.091e-02, eta: 1 day, 2:31:27, time: 0.638, data_time: 0.000, memory: 9000, top1_acc: 0.8875, top5_acc: 0.9981, loss_cls: 2.7500, loss: 2.7500 +2025-05-05 17:57:25,215 - pyskl - INFO - Epoch [40][1100/1281] lr: 2.089e-02, eta: 1 day, 2:30:03, time: 0.614, data_time: 0.000, memory: 9000, top1_acc: 0.8950, top5_acc: 0.9950, loss_cls: 2.7103, loss: 2.7103 +2025-05-05 17:58:27,081 - pyskl - INFO - Epoch [40][1200/1281] lr: 2.088e-02, eta: 1 day, 2:28:39, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9006, top5_acc: 0.9956, loss_cls: 2.7243, loss: 2.7243 +2025-05-05 17:59:20,160 - pyskl - INFO - Saving checkpoint at 40 epochs +2025-05-05 18:00:12,459 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 18:00:12,520 - pyskl - INFO - +top1_acc 0.8439 +top5_acc 0.9859 +2025-05-05 18:00:12,520 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 18:00:12,528 - pyskl - INFO - +mean_acc 0.7964 +2025-05-05 18:00:12,531 - pyskl - INFO - Epoch(val) [40][533] top1_acc: 0.8439, top5_acc: 0.9859, mean_class_accuracy: 0.7964 +2025-05-05 18:01:22,525 - pyskl - INFO - Epoch [41][100/1281] lr: 2.085e-02, eta: 1 day, 2:24:13, time: 0.700, data_time: 0.181, memory: 9000, top1_acc: 0.9056, top5_acc: 0.9988, loss_cls: 2.7209, loss: 2.7209 +2025-05-05 18:02:22,031 - pyskl - INFO - Epoch [41][200/1281] lr: 2.083e-02, eta: 1 day, 2:22:44, time: 0.595, data_time: 0.000, memory: 9000, top1_acc: 0.9156, top5_acc: 0.9981, loss_cls: 2.6603, loss: 2.6603 +2025-05-05 18:03:25,209 - pyskl - INFO - Epoch [41][300/1281] lr: 2.082e-02, eta: 1 day, 2:21:25, time: 0.632, data_time: 0.000, memory: 9000, top1_acc: 0.8944, top5_acc: 0.9975, loss_cls: 2.7222, loss: 2.7222 +2025-05-05 18:04:29,414 - pyskl - INFO - Epoch [41][400/1281] lr: 2.080e-02, eta: 1 day, 2:20:08, time: 0.642, data_time: 0.000, memory: 9000, top1_acc: 0.8931, top5_acc: 0.9969, loss_cls: 2.7552, loss: 2.7552 +2025-05-05 18:05:31,625 - pyskl - INFO - Epoch [41][500/1281] lr: 2.079e-02, eta: 1 day, 2:18:46, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.8919, top5_acc: 0.9969, loss_cls: 2.7299, loss: 2.7299 +2025-05-05 18:06:33,129 - pyskl - INFO - Epoch [41][600/1281] lr: 2.077e-02, eta: 1 day, 2:17:23, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 0.9100, top5_acc: 0.9969, loss_cls: 2.5892, loss: 2.5892 +2025-05-05 18:07:36,294 - pyskl - INFO - Epoch [41][700/1281] lr: 2.076e-02, eta: 1 day, 2:16:04, time: 0.632, data_time: 0.000, memory: 9000, top1_acc: 0.9006, top5_acc: 0.9975, loss_cls: 2.6617, loss: 2.6617 +2025-05-05 18:08:39,737 - pyskl - INFO - Epoch [41][800/1281] lr: 2.074e-02, eta: 1 day, 2:14:46, time: 0.634, data_time: 0.000, memory: 9000, top1_acc: 0.9056, top5_acc: 0.9981, loss_cls: 2.7238, loss: 2.7238 +2025-05-05 18:09:41,064 - pyskl - INFO - Epoch [41][900/1281] lr: 2.073e-02, eta: 1 day, 2:13:22, time: 0.613, data_time: 0.000, memory: 9000, top1_acc: 0.8938, top5_acc: 0.9944, loss_cls: 2.7413, loss: 2.7413 +2025-05-05 18:10:39,917 - pyskl - INFO - Epoch [41][1000/1281] lr: 2.071e-02, eta: 1 day, 2:11:51, time: 0.589, data_time: 0.000, memory: 9000, top1_acc: 0.8938, top5_acc: 0.9975, loss_cls: 2.7322, loss: 2.7322 +2025-05-05 18:11:40,676 - pyskl - INFO - Epoch [41][1100/1281] lr: 2.070e-02, eta: 1 day, 2:10:26, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9019, top5_acc: 0.9962, loss_cls: 2.7544, loss: 2.7544 +2025-05-05 18:12:43,807 - pyskl - INFO - Epoch [41][1200/1281] lr: 2.068e-02, eta: 1 day, 2:09:07, time: 0.631, data_time: 0.000, memory: 9000, top1_acc: 0.9025, top5_acc: 0.9950, loss_cls: 2.7709, loss: 2.7709 +2025-05-05 18:13:35,659 - pyskl - INFO - Saving checkpoint at 41 epochs +2025-05-05 18:14:28,132 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 18:14:28,189 - pyskl - INFO - +top1_acc 0.8467 +top5_acc 0.9896 +2025-05-05 18:14:28,189 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 18:14:28,196 - pyskl - INFO - +mean_acc 0.7899 +2025-05-05 18:14:28,198 - pyskl - INFO - Epoch(val) [41][533] top1_acc: 0.8467, top5_acc: 0.9896, mean_class_accuracy: 0.7899 +2025-05-05 18:15:37,036 - pyskl - INFO - Epoch [42][100/1281] lr: 2.065e-02, eta: 1 day, 2:04:44, time: 0.688, data_time: 0.181, memory: 9000, top1_acc: 0.9019, top5_acc: 0.9969, loss_cls: 2.6791, loss: 2.6791 +2025-05-05 18:16:36,778 - pyskl - INFO - Epoch [42][200/1281] lr: 2.064e-02, eta: 1 day, 2:03:17, time: 0.597, data_time: 0.000, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9969, loss_cls: 2.5973, loss: 2.5973 +2025-05-05 18:17:39,899 - pyskl - INFO - Epoch [42][300/1281] lr: 2.062e-02, eta: 1 day, 2:01:59, time: 0.631, data_time: 0.000, memory: 9000, top1_acc: 0.9012, top5_acc: 0.9988, loss_cls: 2.6067, loss: 2.6067 +2025-05-05 18:18:41,510 - pyskl - INFO - Epoch [42][400/1281] lr: 2.061e-02, eta: 1 day, 2:00:37, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.9100, top5_acc: 0.9975, loss_cls: 2.6461, loss: 2.6461 +2025-05-05 18:19:42,859 - pyskl - INFO - Epoch [42][500/1281] lr: 2.059e-02, eta: 1 day, 1:59:14, time: 0.613, data_time: 0.000, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9975, loss_cls: 2.5457, loss: 2.5457 +2025-05-05 18:20:44,362 - pyskl - INFO - Epoch [42][600/1281] lr: 2.057e-02, eta: 1 day, 1:57:52, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 0.9087, top5_acc: 0.9975, loss_cls: 2.7275, loss: 2.7275 +2025-05-05 18:21:46,379 - pyskl - INFO - Epoch [42][700/1281] lr: 2.056e-02, eta: 1 day, 1:56:31, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.9062, top5_acc: 0.9962, loss_cls: 2.5649, loss: 2.5649 +2025-05-05 18:22:50,813 - pyskl - INFO - Epoch [42][800/1281] lr: 2.054e-02, eta: 1 day, 1:55:17, time: 0.644, data_time: 0.000, memory: 9000, top1_acc: 0.9000, top5_acc: 0.9969, loss_cls: 2.6772, loss: 2.6772 +2025-05-05 18:23:54,614 - pyskl - INFO - Epoch [42][900/1281] lr: 2.053e-02, eta: 1 day, 1:54:00, time: 0.638, data_time: 0.000, memory: 9000, top1_acc: 0.9087, top5_acc: 0.9950, loss_cls: 2.6285, loss: 2.6285 +2025-05-05 18:24:55,231 - pyskl - INFO - Epoch [42][1000/1281] lr: 2.051e-02, eta: 1 day, 1:52:36, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.8888, top5_acc: 0.9975, loss_cls: 2.7099, loss: 2.7099 +2025-05-05 18:25:56,982 - pyskl - INFO - Epoch [42][1100/1281] lr: 2.050e-02, eta: 1 day, 1:51:15, time: 0.618, data_time: 0.000, memory: 9000, top1_acc: 0.8856, top5_acc: 0.9981, loss_cls: 2.8056, loss: 2.8056 +2025-05-05 18:26:59,801 - pyskl - INFO - Epoch [42][1200/1281] lr: 2.048e-02, eta: 1 day, 1:49:56, time: 0.628, data_time: 0.000, memory: 9000, top1_acc: 0.8950, top5_acc: 0.9956, loss_cls: 2.7576, loss: 2.7576 +2025-05-05 18:27:50,406 - pyskl - INFO - Saving checkpoint at 42 epochs +2025-05-05 18:28:41,623 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 18:28:41,678 - pyskl - INFO - +top1_acc 0.8481 +top5_acc 0.9871 +2025-05-05 18:28:41,678 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 18:28:41,685 - pyskl - INFO - +mean_acc 0.8045 +2025-05-05 18:28:41,687 - pyskl - INFO - Epoch(val) [42][533] top1_acc: 0.8481, top5_acc: 0.9871, mean_class_accuracy: 0.8045 +2025-05-05 18:29:50,874 - pyskl - INFO - Epoch [43][100/1281] lr: 2.045e-02, eta: 1 day, 1:45:40, time: 0.692, data_time: 0.184, memory: 9000, top1_acc: 0.9131, top5_acc: 0.9975, loss_cls: 2.6379, loss: 2.6379 +2025-05-05 18:30:51,438 - pyskl - INFO - Epoch [43][200/1281] lr: 2.044e-02, eta: 1 day, 1:44:17, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9038, top5_acc: 0.9962, loss_cls: 2.7410, loss: 2.7410 +2025-05-05 18:31:54,590 - pyskl - INFO - Epoch [43][300/1281] lr: 2.042e-02, eta: 1 day, 1:43:00, time: 0.632, data_time: 0.000, memory: 9000, top1_acc: 0.9056, top5_acc: 0.9981, loss_cls: 2.5290, loss: 2.5290 +2025-05-05 18:32:57,960 - pyskl - INFO - Epoch [43][400/1281] lr: 2.040e-02, eta: 1 day, 1:41:43, time: 0.634, data_time: 0.000, memory: 9000, top1_acc: 0.9000, top5_acc: 0.9962, loss_cls: 2.6766, loss: 2.6766 +2025-05-05 18:33:59,979 - pyskl - INFO - Epoch [43][500/1281] lr: 2.039e-02, eta: 1 day, 1:40:23, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.8994, top5_acc: 0.9988, loss_cls: 2.6153, loss: 2.6153 +2025-05-05 18:35:02,744 - pyskl - INFO - Epoch [43][600/1281] lr: 2.037e-02, eta: 1 day, 1:39:05, time: 0.628, data_time: 0.000, memory: 9000, top1_acc: 0.9000, top5_acc: 0.9975, loss_cls: 2.7206, loss: 2.7206 +2025-05-05 18:36:07,473 - pyskl - INFO - Epoch [43][700/1281] lr: 2.036e-02, eta: 1 day, 1:37:52, time: 0.647, data_time: 0.000, memory: 9000, top1_acc: 0.8975, top5_acc: 0.9981, loss_cls: 2.6560, loss: 2.6560 +2025-05-05 18:37:10,127 - pyskl - INFO - Epoch [43][800/1281] lr: 2.034e-02, eta: 1 day, 1:36:34, time: 0.627, data_time: 0.000, memory: 9000, top1_acc: 0.9163, top5_acc: 0.9975, loss_cls: 2.6538, loss: 2.6538 +2025-05-05 18:38:12,095 - pyskl - INFO - Epoch [43][900/1281] lr: 2.033e-02, eta: 1 day, 1:35:15, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.8994, top5_acc: 0.9975, loss_cls: 2.6400, loss: 2.6400 +2025-05-05 18:39:13,487 - pyskl - INFO - Epoch [43][1000/1281] lr: 2.031e-02, eta: 1 day, 1:33:54, time: 0.614, data_time: 0.000, memory: 9000, top1_acc: 0.8919, top5_acc: 0.9975, loss_cls: 2.7553, loss: 2.7553 +2025-05-05 18:40:16,904 - pyskl - INFO - Epoch [43][1100/1281] lr: 2.029e-02, eta: 1 day, 1:32:38, time: 0.634, data_time: 0.000, memory: 9000, top1_acc: 0.8881, top5_acc: 0.9962, loss_cls: 2.7663, loss: 2.7663 +2025-05-05 18:41:22,154 - pyskl - INFO - Epoch [43][1200/1281] lr: 2.028e-02, eta: 1 day, 1:31:26, time: 0.652, data_time: 0.000, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9975, loss_cls: 2.5931, loss: 2.5931 +2025-05-05 18:42:14,163 - pyskl - INFO - Saving checkpoint at 43 epochs +2025-05-05 18:43:04,846 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 18:43:04,901 - pyskl - INFO - +top1_acc 0.8515 +top5_acc 0.9889 +2025-05-05 18:43:04,901 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 18:43:04,907 - pyskl - INFO - +mean_acc 0.7991 +2025-05-05 18:43:04,968 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_34.pth was removed +2025-05-05 18:43:06,493 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_43.pth. +2025-05-05 18:43:06,493 - pyskl - INFO - Best top1_acc is 0.8515 at 43 epoch. +2025-05-05 18:43:06,497 - pyskl - INFO - Epoch(val) [43][533] top1_acc: 0.8515, top5_acc: 0.9889, mean_class_accuracy: 0.7991 +2025-05-05 18:44:15,298 - pyskl - INFO - Epoch [44][100/1281] lr: 2.025e-02, eta: 1 day, 1:27:15, time: 0.688, data_time: 0.177, memory: 9000, top1_acc: 0.9225, top5_acc: 0.9988, loss_cls: 2.5791, loss: 2.5791 +2025-05-05 18:45:15,796 - pyskl - INFO - Epoch [44][200/1281] lr: 2.023e-02, eta: 1 day, 1:25:52, time: 0.605, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 1.0000, loss_cls: 2.6161, loss: 2.6161 +2025-05-05 18:46:17,880 - pyskl - INFO - Epoch [44][300/1281] lr: 2.022e-02, eta: 1 day, 1:24:33, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.8981, top5_acc: 0.9975, loss_cls: 2.6424, loss: 2.6424 +2025-05-05 18:47:19,282 - pyskl - INFO - Epoch [44][400/1281] lr: 2.020e-02, eta: 1 day, 1:23:13, time: 0.614, data_time: 0.000, memory: 9000, top1_acc: 0.9000, top5_acc: 0.9944, loss_cls: 2.7724, loss: 2.7724 +2025-05-05 18:48:20,597 - pyskl - INFO - Epoch [44][500/1281] lr: 2.018e-02, eta: 1 day, 1:21:52, time: 0.613, data_time: 0.000, memory: 9000, top1_acc: 0.8994, top5_acc: 0.9975, loss_cls: 2.6066, loss: 2.6066 +2025-05-05 18:49:22,906 - pyskl - INFO - Epoch [44][600/1281] lr: 2.017e-02, eta: 1 day, 1:20:34, time: 0.623, data_time: 0.000, memory: 9000, top1_acc: 0.8938, top5_acc: 0.9950, loss_cls: 2.7542, loss: 2.7542 +2025-05-05 18:50:26,398 - pyskl - INFO - Epoch [44][700/1281] lr: 2.015e-02, eta: 1 day, 1:19:19, time: 0.635, data_time: 0.000, memory: 9000, top1_acc: 0.9094, top5_acc: 0.9981, loss_cls: 2.5667, loss: 2.5667 +2025-05-05 18:51:28,834 - pyskl - INFO - Epoch [44][800/1281] lr: 2.014e-02, eta: 1 day, 1:18:02, time: 0.624, data_time: 0.000, memory: 9000, top1_acc: 0.8831, top5_acc: 0.9950, loss_cls: 2.7579, loss: 2.7579 +2025-05-05 18:52:30,861 - pyskl - INFO - Epoch [44][900/1281] lr: 2.012e-02, eta: 1 day, 1:16:43, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.8938, top5_acc: 0.9925, loss_cls: 2.7429, loss: 2.7429 +2025-05-05 18:53:32,226 - pyskl - INFO - Epoch [44][1000/1281] lr: 2.010e-02, eta: 1 day, 1:15:23, time: 0.614, data_time: 0.000, memory: 9000, top1_acc: 0.8956, top5_acc: 0.9975, loss_cls: 2.6412, loss: 2.6412 +2025-05-05 18:54:38,164 - pyskl - INFO - Epoch [44][1100/1281] lr: 2.009e-02, eta: 1 day, 1:14:14, time: 0.659, data_time: 0.000, memory: 9000, top1_acc: 0.9012, top5_acc: 0.9994, loss_cls: 2.5755, loss: 2.5755 +2025-05-05 18:55:45,512 - pyskl - INFO - Epoch [44][1200/1281] lr: 2.007e-02, eta: 1 day, 1:13:08, time: 0.673, data_time: 0.000, memory: 9000, top1_acc: 0.8938, top5_acc: 0.9975, loss_cls: 2.7278, loss: 2.7278 +2025-05-05 18:56:38,419 - pyskl - INFO - Saving checkpoint at 44 epochs +2025-05-05 18:57:29,251 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 18:57:29,306 - pyskl - INFO - +top1_acc 0.8702 +top5_acc 0.9910 +2025-05-05 18:57:29,307 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 18:57:29,314 - pyskl - INFO - +mean_acc 0.8150 +2025-05-05 18:57:29,377 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_43.pth was removed +2025-05-05 18:57:30,933 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_44.pth. +2025-05-05 18:57:30,933 - pyskl - INFO - Best top1_acc is 0.8702 at 44 epoch. +2025-05-05 18:57:30,938 - pyskl - INFO - Epoch(val) [44][533] top1_acc: 0.8702, top5_acc: 0.9910, mean_class_accuracy: 0.8150 +2025-05-05 18:58:40,457 - pyskl - INFO - Epoch [45][100/1281] lr: 2.004e-02, eta: 1 day, 1:09:04, time: 0.695, data_time: 0.180, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9981, loss_cls: 2.6044, loss: 2.6044 +2025-05-05 18:59:41,764 - pyskl - INFO - Epoch [45][200/1281] lr: 2.003e-02, eta: 1 day, 1:07:44, time: 0.613, data_time: 0.000, memory: 9000, top1_acc: 0.8981, top5_acc: 0.9956, loss_cls: 2.5905, loss: 2.5905 +2025-05-05 19:00:44,198 - pyskl - INFO - Epoch [45][300/1281] lr: 2.001e-02, eta: 1 day, 1:06:27, time: 0.624, data_time: 0.000, memory: 9000, top1_acc: 0.9069, top5_acc: 0.9981, loss_cls: 2.6186, loss: 2.6186 +2025-05-05 19:01:45,684 - pyskl - INFO - Epoch [45][400/1281] lr: 1.999e-02, eta: 1 day, 1:05:08, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 0.9069, top5_acc: 0.9975, loss_cls: 2.6063, loss: 2.6063 +2025-05-05 19:02:46,703 - pyskl - INFO - Epoch [45][500/1281] lr: 1.998e-02, eta: 1 day, 1:03:48, time: 0.610, data_time: 0.000, memory: 9000, top1_acc: 0.9062, top5_acc: 0.9975, loss_cls: 2.7121, loss: 2.7121 +2025-05-05 19:03:50,852 - pyskl - INFO - Epoch [45][600/1281] lr: 1.996e-02, eta: 1 day, 1:02:35, time: 0.641, data_time: 0.000, memory: 9000, top1_acc: 0.9087, top5_acc: 0.9975, loss_cls: 2.5805, loss: 2.5805 +2025-05-05 19:04:56,112 - pyskl - INFO - Epoch [45][700/1281] lr: 1.994e-02, eta: 1 day, 1:01:25, time: 0.653, data_time: 0.000, memory: 9000, top1_acc: 0.9038, top5_acc: 0.9975, loss_cls: 2.7106, loss: 2.7106 +2025-05-05 19:06:01,279 - pyskl - INFO - Epoch [45][800/1281] lr: 1.993e-02, eta: 1 day, 1:00:15, time: 0.652, data_time: 0.000, memory: 9000, top1_acc: 0.9056, top5_acc: 0.9981, loss_cls: 2.6269, loss: 2.6269 +2025-05-05 19:07:02,182 - pyskl - INFO - Epoch [45][900/1281] lr: 1.991e-02, eta: 1 day, 0:58:54, time: 0.609, data_time: 0.000, memory: 9000, top1_acc: 0.8900, top5_acc: 0.9956, loss_cls: 2.7270, loss: 2.7270 +2025-05-05 19:08:05,359 - pyskl - INFO - Epoch [45][1000/1281] lr: 1.989e-02, eta: 1 day, 0:57:39, time: 0.632, data_time: 0.000, memory: 9000, top1_acc: 0.9025, top5_acc: 0.9962, loss_cls: 2.7001, loss: 2.7001 +2025-05-05 19:09:11,330 - pyskl - INFO - Epoch [45][1100/1281] lr: 1.988e-02, eta: 1 day, 0:56:31, time: 0.660, data_time: 0.000, memory: 9000, top1_acc: 0.9050, top5_acc: 0.9969, loss_cls: 2.7371, loss: 2.7371 +2025-05-05 19:10:13,990 - pyskl - INFO - Epoch [45][1200/1281] lr: 1.986e-02, eta: 1 day, 0:55:15, time: 0.627, data_time: 0.000, memory: 9000, top1_acc: 0.9087, top5_acc: 0.9975, loss_cls: 2.6719, loss: 2.6719 +2025-05-05 19:11:05,597 - pyskl - INFO - Saving checkpoint at 45 epochs +2025-05-05 19:11:55,633 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 19:11:55,690 - pyskl - INFO - +top1_acc 0.8433 +top5_acc 0.9872 +2025-05-05 19:11:55,690 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 19:11:55,698 - pyskl - INFO - +mean_acc 0.7875 +2025-05-05 19:11:55,702 - pyskl - INFO - Epoch(val) [45][533] top1_acc: 0.8433, top5_acc: 0.9872, mean_class_accuracy: 0.7875 +2025-05-05 19:13:07,199 - pyskl - INFO - Epoch [46][100/1281] lr: 1.983e-02, eta: 1 day, 0:51:20, time: 0.715, data_time: 0.180, memory: 9000, top1_acc: 0.9163, top5_acc: 0.9969, loss_cls: 2.5981, loss: 2.5981 +2025-05-05 19:14:08,811 - pyskl - INFO - Epoch [46][200/1281] lr: 1.981e-02, eta: 1 day, 0:50:02, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.8981, top5_acc: 0.9975, loss_cls: 2.7089, loss: 2.7089 +2025-05-05 19:15:11,802 - pyskl - INFO - Epoch [46][300/1281] lr: 1.980e-02, eta: 1 day, 0:48:47, time: 0.630, data_time: 0.000, memory: 9000, top1_acc: 0.9150, top5_acc: 0.9956, loss_cls: 2.6252, loss: 2.6252 +2025-05-05 19:16:12,311 - pyskl - INFO - Epoch [46][400/1281] lr: 1.978e-02, eta: 1 day, 0:47:26, time: 0.605, data_time: 0.000, memory: 9000, top1_acc: 0.9194, top5_acc: 0.9956, loss_cls: 2.5000, loss: 2.5000 +2025-05-05 19:17:15,484 - pyskl - INFO - Epoch [46][500/1281] lr: 1.976e-02, eta: 1 day, 0:46:12, time: 0.632, data_time: 0.000, memory: 9000, top1_acc: 0.9200, top5_acc: 0.9994, loss_cls: 2.5324, loss: 2.5324 +2025-05-05 19:18:21,384 - pyskl - INFO - Epoch [46][600/1281] lr: 1.975e-02, eta: 1 day, 0:45:04, time: 0.659, data_time: 0.000, memory: 9000, top1_acc: 0.9031, top5_acc: 0.9950, loss_cls: 2.5647, loss: 2.5647 +2025-05-05 19:19:25,598 - pyskl - INFO - Epoch [46][700/1281] lr: 1.973e-02, eta: 1 day, 0:43:52, time: 0.642, data_time: 0.000, memory: 9000, top1_acc: 0.9044, top5_acc: 0.9981, loss_cls: 2.5667, loss: 2.5667 +2025-05-05 19:20:27,433 - pyskl - INFO - Epoch [46][800/1281] lr: 1.971e-02, eta: 1 day, 0:42:35, time: 0.618, data_time: 0.000, memory: 9000, top1_acc: 0.9038, top5_acc: 0.9950, loss_cls: 2.5698, loss: 2.5698 +2025-05-05 19:21:28,635 - pyskl - INFO - Epoch [46][900/1281] lr: 1.970e-02, eta: 1 day, 0:41:16, time: 0.612, data_time: 0.000, memory: 9000, top1_acc: 0.9100, top5_acc: 0.9962, loss_cls: 2.6299, loss: 2.6299 +2025-05-05 19:22:34,171 - pyskl - INFO - Epoch [46][1000/1281] lr: 1.968e-02, eta: 1 day, 0:40:07, time: 0.655, data_time: 0.000, memory: 9000, top1_acc: 0.9019, top5_acc: 0.9962, loss_cls: 2.7603, loss: 2.7603 +2025-05-05 19:23:41,431 - pyskl - INFO - Epoch [46][1100/1281] lr: 1.966e-02, eta: 1 day, 0:39:03, time: 0.673, data_time: 0.000, memory: 9000, top1_acc: 0.9106, top5_acc: 0.9981, loss_cls: 2.5295, loss: 2.5295 +2025-05-05 19:24:45,625 - pyskl - INFO - Epoch [46][1200/1281] lr: 1.965e-02, eta: 1 day, 0:37:51, time: 0.642, data_time: 0.000, memory: 9000, top1_acc: 0.9044, top5_acc: 0.9981, loss_cls: 2.6142, loss: 2.6142 +2025-05-05 19:25:35,533 - pyskl - INFO - Saving checkpoint at 46 epochs +2025-05-05 19:26:28,151 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 19:26:28,206 - pyskl - INFO - +top1_acc 0.8561 +top5_acc 0.9914 +2025-05-05 19:26:28,206 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 19:26:28,213 - pyskl - INFO - +mean_acc 0.8014 +2025-05-05 19:26:28,215 - pyskl - INFO - Epoch(val) [46][533] top1_acc: 0.8561, top5_acc: 0.9914, mean_class_accuracy: 0.8014 +2025-05-05 19:27:41,425 - pyskl - INFO - Epoch [47][100/1281] lr: 1.962e-02, eta: 1 day, 0:34:04, time: 0.732, data_time: 0.181, memory: 9000, top1_acc: 0.9131, top5_acc: 0.9969, loss_cls: 2.5973, loss: 2.5973 +2025-05-05 19:28:43,422 - pyskl - INFO - Epoch [47][200/1281] lr: 1.960e-02, eta: 1 day, 0:32:48, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.9100, top5_acc: 0.9988, loss_cls: 2.5268, loss: 2.5268 +2025-05-05 19:29:44,359 - pyskl - INFO - Epoch [47][300/1281] lr: 1.958e-02, eta: 1 day, 0:31:29, time: 0.609, data_time: 0.000, memory: 9000, top1_acc: 0.9081, top5_acc: 0.9975, loss_cls: 2.5665, loss: 2.5665 +2025-05-05 19:30:46,517 - pyskl - INFO - Epoch [47][400/1281] lr: 1.957e-02, eta: 1 day, 0:30:13, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.9081, top5_acc: 0.9981, loss_cls: 2.6101, loss: 2.6101 +2025-05-05 19:31:51,210 - pyskl - INFO - Epoch [47][500/1281] lr: 1.955e-02, eta: 1 day, 0:29:03, time: 0.647, data_time: 0.000, memory: 9000, top1_acc: 0.9156, top5_acc: 0.9988, loss_cls: 2.5830, loss: 2.5830 +2025-05-05 19:32:57,949 - pyskl - INFO - Epoch [47][600/1281] lr: 1.953e-02, eta: 1 day, 0:27:57, time: 0.667, data_time: 0.000, memory: 9000, top1_acc: 0.9025, top5_acc: 0.9981, loss_cls: 2.7107, loss: 2.7107 +2025-05-05 19:34:03,379 - pyskl - INFO - Epoch [47][700/1281] lr: 1.952e-02, eta: 1 day, 0:26:48, time: 0.654, data_time: 0.000, memory: 9000, top1_acc: 0.9137, top5_acc: 0.9975, loss_cls: 2.6236, loss: 2.6236 +2025-05-05 19:35:05,252 - pyskl - INFO - Epoch [47][800/1281] lr: 1.950e-02, eta: 1 day, 0:25:32, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9113, top5_acc: 0.9988, loss_cls: 2.5508, loss: 2.5508 +2025-05-05 19:36:09,316 - pyskl - INFO - Epoch [47][900/1281] lr: 1.948e-02, eta: 1 day, 0:24:20, time: 0.641, data_time: 0.000, memory: 9000, top1_acc: 0.8981, top5_acc: 0.9969, loss_cls: 2.6238, loss: 2.6238 +2025-05-05 19:37:15,932 - pyskl - INFO - Epoch [47][1000/1281] lr: 1.947e-02, eta: 1 day, 0:23:14, time: 0.666, data_time: 0.000, memory: 9000, top1_acc: 0.9019, top5_acc: 0.9975, loss_cls: 2.6542, loss: 2.6542 +2025-05-05 19:38:18,355 - pyskl - INFO - Epoch [47][1100/1281] lr: 1.945e-02, eta: 1 day, 0:21:59, time: 0.624, data_time: 0.000, memory: 9000, top1_acc: 0.9194, top5_acc: 0.9969, loss_cls: 2.6192, loss: 2.6192 +2025-05-05 19:39:19,038 - pyskl - INFO - Epoch [47][1200/1281] lr: 1.943e-02, eta: 1 day, 0:20:40, time: 0.607, data_time: 0.000, memory: 9000, top1_acc: 0.9012, top5_acc: 0.9981, loss_cls: 2.6805, loss: 2.6805 +2025-05-05 19:40:09,152 - pyskl - INFO - Saving checkpoint at 47 epochs +2025-05-05 19:41:02,676 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 19:41:02,732 - pyskl - INFO - +top1_acc 0.8253 +top5_acc 0.9862 +2025-05-05 19:41:02,732 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 19:41:02,739 - pyskl - INFO - +mean_acc 0.7875 +2025-05-05 19:41:02,741 - pyskl - INFO - Epoch(val) [47][533] top1_acc: 0.8253, top5_acc: 0.9862, mean_class_accuracy: 0.7875 +2025-05-05 19:42:16,038 - pyskl - INFO - Epoch [48][100/1281] lr: 1.940e-02, eta: 1 day, 0:16:58, time: 0.733, data_time: 0.183, memory: 9000, top1_acc: 0.9163, top5_acc: 0.9981, loss_cls: 2.4921, loss: 2.4921 +2025-05-05 19:43:17,748 - pyskl - INFO - Epoch [48][200/1281] lr: 1.938e-02, eta: 1 day, 0:15:41, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 2.5597, loss: 2.5597 +2025-05-05 19:44:17,785 - pyskl - INFO - Epoch [48][300/1281] lr: 1.937e-02, eta: 1 day, 0:14:21, time: 0.600, data_time: 0.000, memory: 9000, top1_acc: 0.9244, top5_acc: 0.9988, loss_cls: 2.4846, loss: 2.4846 +2025-05-05 19:45:19,416 - pyskl - INFO - Epoch [48][400/1281] lr: 1.935e-02, eta: 1 day, 0:13:05, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.9231, top5_acc: 0.9981, loss_cls: 2.6896, loss: 2.6896 +2025-05-05 19:46:26,202 - pyskl - INFO - Epoch [48][500/1281] lr: 1.933e-02, eta: 1 day, 0:12:00, time: 0.668, data_time: 0.000, memory: 9000, top1_acc: 0.9225, top5_acc: 0.9988, loss_cls: 2.5080, loss: 2.5080 +2025-05-05 19:47:31,813 - pyskl - INFO - Epoch [48][600/1281] lr: 1.932e-02, eta: 1 day, 0:10:52, time: 0.656, data_time: 0.000, memory: 9000, top1_acc: 0.9131, top5_acc: 0.9950, loss_cls: 2.6328, loss: 2.6328 +2025-05-05 19:48:34,935 - pyskl - INFO - Epoch [48][700/1281] lr: 1.930e-02, eta: 1 day, 0:09:39, time: 0.631, data_time: 0.000, memory: 9000, top1_acc: 0.9006, top5_acc: 0.9944, loss_cls: 2.7101, loss: 2.7101 +2025-05-05 19:49:36,764 - pyskl - INFO - Epoch [48][800/1281] lr: 1.928e-02, eta: 1 day, 0:08:23, time: 0.618, data_time: 0.000, memory: 9000, top1_acc: 0.9100, top5_acc: 0.9981, loss_cls: 2.5395, loss: 2.5395 +2025-05-05 19:50:43,013 - pyskl - INFO - Epoch [48][900/1281] lr: 1.926e-02, eta: 1 day, 0:07:17, time: 0.662, data_time: 0.000, memory: 9000, top1_acc: 0.9062, top5_acc: 0.9981, loss_cls: 2.5349, loss: 2.5349 +2025-05-05 19:51:50,451 - pyskl - INFO - Epoch [48][1000/1281] lr: 1.925e-02, eta: 1 day, 0:06:13, time: 0.674, data_time: 0.000, memory: 9000, top1_acc: 0.9113, top5_acc: 0.9988, loss_cls: 2.6480, loss: 2.6480 +2025-05-05 19:52:54,268 - pyskl - INFO - Epoch [48][1100/1281] lr: 1.923e-02, eta: 1 day, 0:05:02, time: 0.638, data_time: 0.000, memory: 9000, top1_acc: 0.8925, top5_acc: 0.9969, loss_cls: 2.7195, loss: 2.7195 +2025-05-05 19:53:54,400 - pyskl - INFO - Epoch [48][1200/1281] lr: 1.921e-02, eta: 1 day, 0:03:42, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9956, loss_cls: 2.6488, loss: 2.6488 +2025-05-05 19:54:46,572 - pyskl - INFO - Saving checkpoint at 48 epochs +2025-05-05 19:55:43,362 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 19:55:43,417 - pyskl - INFO - +top1_acc 0.8667 +top5_acc 0.9896 +2025-05-05 19:55:43,417 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 19:55:43,423 - pyskl - INFO - +mean_acc 0.8164 +2025-05-05 19:55:43,425 - pyskl - INFO - Epoch(val) [48][533] top1_acc: 0.8667, top5_acc: 0.9896, mean_class_accuracy: 0.8164 +2025-05-05 19:56:56,573 - pyskl - INFO - Epoch [49][100/1281] lr: 1.918e-02, eta: 1 day, 0:00:03, time: 0.731, data_time: 0.179, memory: 9000, top1_acc: 0.9275, top5_acc: 0.9981, loss_cls: 2.5699, loss: 2.5699 +2025-05-05 19:57:55,946 - pyskl - INFO - Epoch [49][200/1281] lr: 1.916e-02, eta: 23:58:43, time: 0.594, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9988, loss_cls: 2.4733, loss: 2.4733 +2025-05-05 19:58:56,201 - pyskl - INFO - Epoch [49][300/1281] lr: 1.915e-02, eta: 23:57:24, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9144, top5_acc: 0.9981, loss_cls: 2.5657, loss: 2.5657 +2025-05-05 20:00:02,814 - pyskl - INFO - Epoch [49][400/1281] lr: 1.913e-02, eta: 23:56:19, time: 0.666, data_time: 0.000, memory: 9000, top1_acc: 0.9194, top5_acc: 0.9994, loss_cls: 2.5470, loss: 2.5470 +2025-05-05 20:01:08,452 - pyskl - INFO - Epoch [49][500/1281] lr: 1.911e-02, eta: 23:55:12, time: 0.656, data_time: 0.000, memory: 9000, top1_acc: 0.9075, top5_acc: 0.9988, loss_cls: 2.5629, loss: 2.5629 +2025-05-05 20:02:10,709 - pyskl - INFO - Epoch [49][600/1281] lr: 1.909e-02, eta: 23:53:57, time: 0.623, data_time: 0.000, memory: 9000, top1_acc: 0.9069, top5_acc: 0.9956, loss_cls: 2.6075, loss: 2.6075 +2025-05-05 20:03:11,505 - pyskl - INFO - Epoch [49][700/1281] lr: 1.908e-02, eta: 23:52:40, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9019, top5_acc: 0.9981, loss_cls: 2.6083, loss: 2.6083 +2025-05-05 20:04:16,891 - pyskl - INFO - Epoch [49][800/1281] lr: 1.906e-02, eta: 23:51:32, time: 0.654, data_time: 0.000, memory: 9000, top1_acc: 0.9075, top5_acc: 0.9981, loss_cls: 2.6736, loss: 2.6736 +2025-05-05 20:05:25,870 - pyskl - INFO - Epoch [49][900/1281] lr: 1.904e-02, eta: 23:50:32, time: 0.690, data_time: 0.000, memory: 9000, top1_acc: 0.9056, top5_acc: 0.9988, loss_cls: 2.5997, loss: 2.5997 +2025-05-05 20:06:31,476 - pyskl - INFO - Epoch [49][1000/1281] lr: 1.902e-02, eta: 23:49:25, time: 0.656, data_time: 0.000, memory: 9000, top1_acc: 0.9012, top5_acc: 0.9950, loss_cls: 2.7047, loss: 2.7047 +2025-05-05 20:07:32,260 - pyskl - INFO - Epoch [49][1100/1281] lr: 1.901e-02, eta: 23:48:07, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9031, top5_acc: 0.9969, loss_cls: 2.6370, loss: 2.6370 +2025-05-05 20:08:33,185 - pyskl - INFO - Epoch [49][1200/1281] lr: 1.899e-02, eta: 23:46:50, time: 0.609, data_time: 0.000, memory: 9000, top1_acc: 0.9056, top5_acc: 0.9988, loss_cls: 2.5768, loss: 2.5768 +2025-05-05 20:09:30,207 - pyskl - INFO - Saving checkpoint at 49 epochs +2025-05-05 20:10:25,844 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 20:10:25,899 - pyskl - INFO - +top1_acc 0.8531 +top5_acc 0.9916 +2025-05-05 20:10:25,899 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 20:10:25,907 - pyskl - INFO - +mean_acc 0.8048 +2025-05-05 20:10:25,910 - pyskl - INFO - Epoch(val) [49][533] top1_acc: 0.8531, top5_acc: 0.9916, mean_class_accuracy: 0.8048 +2025-05-05 20:11:36,806 - pyskl - INFO - Epoch [50][100/1281] lr: 1.896e-02, eta: 23:43:10, time: 0.709, data_time: 0.181, memory: 9000, top1_acc: 0.9200, top5_acc: 0.9975, loss_cls: 2.5119, loss: 2.5119 +2025-05-05 20:12:35,455 - pyskl - INFO - Epoch [50][200/1281] lr: 1.894e-02, eta: 23:41:49, time: 0.586, data_time: 0.000, memory: 9000, top1_acc: 0.9225, top5_acc: 0.9994, loss_cls: 2.4762, loss: 2.4762 +2025-05-05 20:13:39,947 - pyskl - INFO - Epoch [50][300/1281] lr: 1.892e-02, eta: 23:40:40, time: 0.645, data_time: 0.000, memory: 9000, top1_acc: 0.9219, top5_acc: 0.9988, loss_cls: 2.5218, loss: 2.5218 +2025-05-05 20:14:48,621 - pyskl - INFO - Epoch [50][400/1281] lr: 1.891e-02, eta: 23:39:39, time: 0.687, data_time: 0.000, memory: 9000, top1_acc: 0.9181, top5_acc: 1.0000, loss_cls: 2.5560, loss: 2.5560 +2025-05-05 20:15:53,544 - pyskl - INFO - Epoch [50][500/1281] lr: 1.889e-02, eta: 23:38:31, time: 0.649, data_time: 0.000, memory: 9000, top1_acc: 0.9069, top5_acc: 0.9981, loss_cls: 2.5130, loss: 2.5130 +2025-05-05 20:16:54,056 - pyskl - INFO - Epoch [50][600/1281] lr: 1.887e-02, eta: 23:37:14, time: 0.605, data_time: 0.000, memory: 9000, top1_acc: 0.9200, top5_acc: 0.9969, loss_cls: 2.5484, loss: 2.5484 +2025-05-05 20:17:56,447 - pyskl - INFO - Epoch [50][700/1281] lr: 1.885e-02, eta: 23:36:00, time: 0.624, data_time: 0.000, memory: 9000, top1_acc: 0.9075, top5_acc: 0.9975, loss_cls: 2.6027, loss: 2.6027 +2025-05-05 20:19:07,608 - pyskl - INFO - Epoch [50][800/1281] lr: 1.884e-02, eta: 23:35:05, time: 0.712, data_time: 0.000, memory: 9000, top1_acc: 0.9019, top5_acc: 0.9988, loss_cls: 2.6596, loss: 2.6596 +2025-05-05 20:20:14,092 - pyskl - INFO - Epoch [50][900/1281] lr: 1.882e-02, eta: 23:34:00, time: 0.665, data_time: 0.000, memory: 9000, top1_acc: 0.9256, top5_acc: 0.9981, loss_cls: 2.5219, loss: 2.5219 +2025-05-05 20:21:14,174 - pyskl - INFO - Epoch [50][1000/1281] lr: 1.880e-02, eta: 23:32:42, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.8988, top5_acc: 0.9956, loss_cls: 2.5546, loss: 2.5546 +2025-05-05 20:22:13,511 - pyskl - INFO - Epoch [50][1100/1281] lr: 1.878e-02, eta: 23:31:22, time: 0.593, data_time: 0.000, memory: 9000, top1_acc: 0.9094, top5_acc: 0.9956, loss_cls: 2.6154, loss: 2.6154 +2025-05-05 20:23:23,865 - pyskl - INFO - Epoch [50][1200/1281] lr: 1.876e-02, eta: 23:30:25, time: 0.704, data_time: 0.000, memory: 9000, top1_acc: 0.9237, top5_acc: 0.9962, loss_cls: 2.5587, loss: 2.5587 +2025-05-05 20:24:20,667 - pyskl - INFO - Saving checkpoint at 50 epochs +2025-05-05 20:25:12,713 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 20:25:12,770 - pyskl - INFO - +top1_acc 0.8411 +top5_acc 0.9883 +2025-05-05 20:25:12,770 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 20:25:12,778 - pyskl - INFO - +mean_acc 0.7995 +2025-05-05 20:25:12,781 - pyskl - INFO - Epoch(val) [50][533] top1_acc: 0.8411, top5_acc: 0.9883, mean_class_accuracy: 0.7995 +2025-05-05 20:26:20,343 - pyskl - INFO - Epoch [51][100/1281] lr: 1.873e-02, eta: 23:26:42, time: 0.676, data_time: 0.178, memory: 9000, top1_acc: 0.9187, top5_acc: 0.9994, loss_cls: 2.4863, loss: 2.4863 +2025-05-05 20:27:20,843 - pyskl - INFO - Epoch [51][200/1281] lr: 1.871e-02, eta: 23:25:25, time: 0.605, data_time: 0.000, memory: 9000, top1_acc: 0.9163, top5_acc: 0.9988, loss_cls: 2.5997, loss: 2.5997 +2025-05-05 20:28:31,466 - pyskl - INFO - Epoch [51][300/1281] lr: 1.870e-02, eta: 23:24:28, time: 0.706, data_time: 0.000, memory: 9000, top1_acc: 0.9038, top5_acc: 0.9950, loss_cls: 2.6216, loss: 2.6216 +2025-05-05 20:29:38,215 - pyskl - INFO - Epoch [51][400/1281] lr: 1.868e-02, eta: 23:23:24, time: 0.667, data_time: 0.000, memory: 9000, top1_acc: 0.9094, top5_acc: 0.9994, loss_cls: 2.6197, loss: 2.6197 +2025-05-05 20:30:39,339 - pyskl - INFO - Epoch [51][500/1281] lr: 1.866e-02, eta: 23:22:08, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9994, loss_cls: 2.4939, loss: 2.4939 +2025-05-05 20:31:39,286 - pyskl - INFO - Epoch [51][600/1281] lr: 1.864e-02, eta: 23:20:51, time: 0.599, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 1.0000, loss_cls: 2.4950, loss: 2.4950 +2025-05-05 20:32:52,269 - pyskl - INFO - Epoch [51][700/1281] lr: 1.863e-02, eta: 23:19:59, time: 0.730, data_time: 0.000, memory: 9000, top1_acc: 0.9094, top5_acc: 0.9975, loss_cls: 2.4993, loss: 2.4993 +2025-05-05 20:34:01,405 - pyskl - INFO - Epoch [51][800/1281] lr: 1.861e-02, eta: 23:18:59, time: 0.691, data_time: 0.000, memory: 9000, top1_acc: 0.8975, top5_acc: 0.9981, loss_cls: 2.6689, loss: 2.6689 +2025-05-05 20:35:03,266 - pyskl - INFO - Epoch [51][900/1281] lr: 1.859e-02, eta: 23:17:45, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9137, top5_acc: 0.9962, loss_cls: 2.5686, loss: 2.5686 +2025-05-05 20:36:03,829 - pyskl - INFO - Epoch [51][1000/1281] lr: 1.857e-02, eta: 23:16:29, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9062, top5_acc: 0.9969, loss_cls: 2.6346, loss: 2.6346 +2025-05-05 20:37:12,482 - pyskl - INFO - Epoch [51][1100/1281] lr: 1.855e-02, eta: 23:15:28, time: 0.687, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9981, loss_cls: 2.4308, loss: 2.4308 +2025-05-05 20:38:25,590 - pyskl - INFO - Epoch [51][1200/1281] lr: 1.854e-02, eta: 23:14:36, time: 0.731, data_time: 0.000, memory: 9000, top1_acc: 0.9038, top5_acc: 0.9975, loss_cls: 2.5296, loss: 2.5296 +2025-05-05 20:39:17,314 - pyskl - INFO - Saving checkpoint at 51 epochs +2025-05-05 20:40:07,241 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 20:40:07,299 - pyskl - INFO - +top1_acc 0.8711 +top5_acc 0.9904 +2025-05-05 20:40:07,299 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 20:40:07,307 - pyskl - INFO - +mean_acc 0.8173 +2025-05-05 20:40:07,363 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_44.pth was removed +2025-05-05 20:40:08,883 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_51.pth. +2025-05-05 20:40:08,884 - pyskl - INFO - Best top1_acc is 0.8711 at 51 epoch. +2025-05-05 20:40:08,887 - pyskl - INFO - Epoch(val) [51][533] top1_acc: 0.8711, top5_acc: 0.9904, mean_class_accuracy: 0.8173 +2025-05-05 20:41:18,400 - pyskl - INFO - Epoch [52][100/1281] lr: 1.850e-02, eta: 23:11:00, time: 0.695, data_time: 0.181, memory: 9000, top1_acc: 0.9250, top5_acc: 0.9981, loss_cls: 2.4962, loss: 2.4962 +2025-05-05 20:42:28,180 - pyskl - INFO - Epoch [52][200/1281] lr: 1.849e-02, eta: 23:10:02, time: 0.698, data_time: 0.000, memory: 9000, top1_acc: 0.9275, top5_acc: 1.0000, loss_cls: 2.4903, loss: 2.4903 +2025-05-05 20:43:34,159 - pyskl - INFO - Epoch [52][300/1281] lr: 1.847e-02, eta: 23:08:56, time: 0.660, data_time: 0.000, memory: 9000, top1_acc: 0.9200, top5_acc: 0.9981, loss_cls: 2.5222, loss: 2.5222 +2025-05-05 20:44:34,976 - pyskl - INFO - Epoch [52][400/1281] lr: 1.845e-02, eta: 23:07:41, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9219, top5_acc: 0.9969, loss_cls: 2.5286, loss: 2.5286 +2025-05-05 20:45:35,291 - pyskl - INFO - Epoch [52][500/1281] lr: 1.843e-02, eta: 23:06:24, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9144, top5_acc: 0.9988, loss_cls: 2.4887, loss: 2.4887 +2025-05-05 20:46:47,864 - pyskl - INFO - Epoch [52][600/1281] lr: 1.841e-02, eta: 23:05:31, time: 0.726, data_time: 0.000, memory: 9000, top1_acc: 0.9187, top5_acc: 0.9981, loss_cls: 2.6354, loss: 2.6354 +2025-05-05 20:47:59,269 - pyskl - INFO - Epoch [52][700/1281] lr: 1.840e-02, eta: 23:04:36, time: 0.714, data_time: 0.000, memory: 9000, top1_acc: 0.9181, top5_acc: 0.9988, loss_cls: 2.4926, loss: 2.4926 +2025-05-05 20:49:01,836 - pyskl - INFO - Epoch [52][800/1281] lr: 1.838e-02, eta: 23:03:24, time: 0.626, data_time: 0.000, memory: 9000, top1_acc: 0.9137, top5_acc: 0.9962, loss_cls: 2.5610, loss: 2.5610 +2025-05-05 20:50:02,002 - pyskl - INFO - Epoch [52][900/1281] lr: 1.836e-02, eta: 23:02:07, time: 0.602, data_time: 0.000, memory: 9000, top1_acc: 0.9113, top5_acc: 0.9975, loss_cls: 2.5620, loss: 2.5620 +2025-05-05 20:51:10,102 - pyskl - INFO - Epoch [52][1000/1281] lr: 1.834e-02, eta: 23:01:05, time: 0.681, data_time: 0.000, memory: 9000, top1_acc: 0.9244, top5_acc: 0.9975, loss_cls: 2.5509, loss: 2.5509 +2025-05-05 20:52:24,657 - pyskl - INFO - Epoch [52][1100/1281] lr: 1.832e-02, eta: 23:00:16, time: 0.746, data_time: 0.000, memory: 9000, top1_acc: 0.9219, top5_acc: 0.9994, loss_cls: 2.5309, loss: 2.5309 +2025-05-05 20:53:27,763 - pyskl - INFO - Epoch [52][1200/1281] lr: 1.831e-02, eta: 22:59:05, time: 0.631, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9975, loss_cls: 2.5834, loss: 2.5834 +2025-05-05 20:54:17,531 - pyskl - INFO - Saving checkpoint at 52 epochs +2025-05-05 20:55:08,035 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 20:55:08,114 - pyskl - INFO - +top1_acc 0.8565 +top5_acc 0.9908 +2025-05-05 20:55:08,114 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 20:55:08,123 - pyskl - INFO - +mean_acc 0.8285 +2025-05-05 20:55:08,127 - pyskl - INFO - Epoch(val) [52][533] top1_acc: 0.8565, top5_acc: 0.9908, mean_class_accuracy: 0.8285 +2025-05-05 20:56:27,454 - pyskl - INFO - Epoch [53][100/1281] lr: 1.827e-02, eta: 22:55:51, time: 0.793, data_time: 0.186, memory: 9000, top1_acc: 0.9156, top5_acc: 0.9994, loss_cls: 2.5405, loss: 2.5405 +2025-05-05 20:57:32,399 - pyskl - INFO - Epoch [53][200/1281] lr: 1.826e-02, eta: 22:54:43, time: 0.649, data_time: 0.000, memory: 9000, top1_acc: 0.9237, top5_acc: 0.9981, loss_cls: 2.4837, loss: 2.4837 +2025-05-05 20:58:33,559 - pyskl - INFO - Epoch [53][300/1281] lr: 1.824e-02, eta: 22:53:29, time: 0.612, data_time: 0.000, memory: 9000, top1_acc: 0.9113, top5_acc: 0.9988, loss_cls: 2.4628, loss: 2.4628 +2025-05-05 20:59:33,545 - pyskl - INFO - Epoch [53][400/1281] lr: 1.822e-02, eta: 22:52:12, time: 0.600, data_time: 0.000, memory: 9000, top1_acc: 0.9094, top5_acc: 0.9988, loss_cls: 2.5346, loss: 2.5346 +2025-05-05 21:00:45,514 - pyskl - INFO - Epoch [53][500/1281] lr: 1.820e-02, eta: 22:51:18, time: 0.720, data_time: 0.000, memory: 9000, top1_acc: 0.9287, top5_acc: 0.9994, loss_cls: 2.5556, loss: 2.5556 +2025-05-05 21:01:56,999 - pyskl - INFO - Epoch [53][600/1281] lr: 1.818e-02, eta: 22:50:23, time: 0.715, data_time: 0.000, memory: 9000, top1_acc: 0.9231, top5_acc: 0.9988, loss_cls: 2.4608, loss: 2.4608 +2025-05-05 21:02:59,126 - pyskl - INFO - Epoch [53][700/1281] lr: 1.816e-02, eta: 22:49:10, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.9181, top5_acc: 0.9988, loss_cls: 2.5323, loss: 2.5323 +2025-05-05 21:03:59,004 - pyskl - INFO - Epoch [53][800/1281] lr: 1.815e-02, eta: 22:47:53, time: 0.599, data_time: 0.000, memory: 9000, top1_acc: 0.8994, top5_acc: 0.9975, loss_cls: 2.6517, loss: 2.6517 +2025-05-05 21:05:03,479 - pyskl - INFO - Epoch [53][900/1281] lr: 1.813e-02, eta: 22:46:45, time: 0.645, data_time: 0.000, memory: 9000, top1_acc: 0.9144, top5_acc: 0.9975, loss_cls: 2.4917, loss: 2.4917 +2025-05-05 21:06:18,038 - pyskl - INFO - Epoch [53][1000/1281] lr: 1.811e-02, eta: 22:45:55, time: 0.746, data_time: 0.000, memory: 9000, top1_acc: 0.9075, top5_acc: 0.9962, loss_cls: 2.6026, loss: 2.6026 +2025-05-05 21:07:20,686 - pyskl - INFO - Epoch [53][1100/1281] lr: 1.809e-02, eta: 22:44:44, time: 0.626, data_time: 0.000, memory: 9000, top1_acc: 0.9062, top5_acc: 0.9956, loss_cls: 2.6360, loss: 2.6360 +2025-05-05 21:08:19,860 - pyskl - INFO - Epoch [53][1200/1281] lr: 1.807e-02, eta: 22:43:26, time: 0.592, data_time: 0.000, memory: 9000, top1_acc: 0.9062, top5_acc: 0.9944, loss_cls: 2.5960, loss: 2.5960 +2025-05-05 21:09:09,549 - pyskl - INFO - Saving checkpoint at 53 epochs +2025-05-05 21:10:08,881 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 21:10:08,936 - pyskl - INFO - +top1_acc 0.8451 +top5_acc 0.9885 +2025-05-05 21:10:08,936 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 21:10:08,942 - pyskl - INFO - +mean_acc 0.8124 +2025-05-05 21:10:08,945 - pyskl - INFO - Epoch(val) [53][533] top1_acc: 0.8451, top5_acc: 0.9885, mean_class_accuracy: 0.8124 +2025-05-05 21:11:24,573 - pyskl - INFO - Epoch [54][100/1281] lr: 1.804e-02, eta: 22:40:07, time: 0.756, data_time: 0.180, memory: 9000, top1_acc: 0.9281, top5_acc: 0.9981, loss_cls: 2.4303, loss: 2.4303 +2025-05-05 21:12:23,963 - pyskl - INFO - Epoch [54][200/1281] lr: 1.802e-02, eta: 22:38:50, time: 0.594, data_time: 0.000, memory: 9000, top1_acc: 0.9287, top5_acc: 0.9981, loss_cls: 2.4315, loss: 2.4315 +2025-05-05 21:13:23,146 - pyskl - INFO - Epoch [54][300/1281] lr: 1.800e-02, eta: 22:37:32, time: 0.592, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9981, loss_cls: 2.4266, loss: 2.4266 +2025-05-05 21:14:30,321 - pyskl - INFO - Epoch [54][400/1281] lr: 1.798e-02, eta: 22:36:29, time: 0.672, data_time: 0.000, memory: 9000, top1_acc: 0.9187, top5_acc: 0.9988, loss_cls: 2.4942, loss: 2.4942 +2025-05-05 21:15:44,058 - pyskl - INFO - Epoch [54][500/1281] lr: 1.797e-02, eta: 22:35:38, time: 0.737, data_time: 0.000, memory: 9000, top1_acc: 0.9163, top5_acc: 0.9981, loss_cls: 2.5019, loss: 2.5019 +2025-05-05 21:16:47,964 - pyskl - INFO - Epoch [54][600/1281] lr: 1.795e-02, eta: 22:34:29, time: 0.639, data_time: 0.000, memory: 9000, top1_acc: 0.9237, top5_acc: 0.9962, loss_cls: 2.5193, loss: 2.5193 +2025-05-05 21:17:48,244 - pyskl - INFO - Epoch [54][700/1281] lr: 1.793e-02, eta: 22:33:14, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9050, top5_acc: 0.9956, loss_cls: 2.6249, loss: 2.6249 +2025-05-05 21:18:50,553 - pyskl - INFO - Epoch [54][800/1281] lr: 1.791e-02, eta: 22:32:02, time: 0.623, data_time: 0.000, memory: 9000, top1_acc: 0.9144, top5_acc: 0.9975, loss_cls: 2.5270, loss: 2.5270 +2025-05-05 21:20:07,681 - pyskl - INFO - Epoch [54][900/1281] lr: 1.789e-02, eta: 22:31:16, time: 0.771, data_time: 0.000, memory: 9000, top1_acc: 0.9113, top5_acc: 0.9988, loss_cls: 2.5260, loss: 2.5260 +2025-05-05 21:21:12,310 - pyskl - INFO - Epoch [54][1000/1281] lr: 1.787e-02, eta: 22:30:09, time: 0.646, data_time: 0.000, memory: 9000, top1_acc: 0.9137, top5_acc: 0.9988, loss_cls: 2.5270, loss: 2.5270 +2025-05-05 21:22:13,285 - pyskl - INFO - Epoch [54][1100/1281] lr: 1.786e-02, eta: 22:28:55, time: 0.610, data_time: 0.000, memory: 9000, top1_acc: 0.9275, top5_acc: 0.9988, loss_cls: 2.3939, loss: 2.3939 +2025-05-05 21:23:13,710 - pyskl - INFO - Epoch [54][1200/1281] lr: 1.784e-02, eta: 22:27:39, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9287, top5_acc: 0.9981, loss_cls: 2.4817, loss: 2.4817 +2025-05-05 21:24:14,065 - pyskl - INFO - Saving checkpoint at 54 epochs +2025-05-05 21:25:12,568 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 21:25:12,623 - pyskl - INFO - +top1_acc 0.8690 +top5_acc 0.9910 +2025-05-05 21:25:12,623 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 21:25:12,630 - pyskl - INFO - +mean_acc 0.8187 +2025-05-05 21:25:12,633 - pyskl - INFO - Epoch(val) [54][533] top1_acc: 0.8690, top5_acc: 0.9910, mean_class_accuracy: 0.8187 +2025-05-05 21:26:22,332 - pyskl - INFO - Epoch [55][100/1281] lr: 1.780e-02, eta: 22:24:13, time: 0.697, data_time: 0.181, memory: 9000, top1_acc: 0.9275, top5_acc: 0.9981, loss_cls: 2.4294, loss: 2.4294 +2025-05-05 21:27:19,753 - pyskl - INFO - Epoch [55][200/1281] lr: 1.779e-02, eta: 22:22:53, time: 0.574, data_time: 0.000, memory: 9000, top1_acc: 0.9044, top5_acc: 0.9969, loss_cls: 2.5420, loss: 2.5420 +2025-05-05 21:28:24,790 - pyskl - INFO - Epoch [55][300/1281] lr: 1.777e-02, eta: 22:21:46, time: 0.650, data_time: 0.000, memory: 9000, top1_acc: 0.9231, top5_acc: 0.9962, loss_cls: 2.4716, loss: 2.4716 +2025-05-05 21:29:39,561 - pyskl - INFO - Epoch [55][400/1281] lr: 1.775e-02, eta: 22:20:57, time: 0.748, data_time: 0.000, memory: 9000, top1_acc: 0.9181, top5_acc: 0.9994, loss_cls: 2.4994, loss: 2.4994 +2025-05-05 21:30:41,773 - pyskl - INFO - Epoch [55][500/1281] lr: 1.773e-02, eta: 22:19:45, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.9294, top5_acc: 0.9975, loss_cls: 2.5330, loss: 2.5330 +2025-05-05 21:31:41,211 - pyskl - INFO - Epoch [55][600/1281] lr: 1.771e-02, eta: 22:18:29, time: 0.594, data_time: 0.000, memory: 9000, top1_acc: 0.9237, top5_acc: 0.9981, loss_cls: 2.4018, loss: 2.4018 +2025-05-05 21:32:42,157 - pyskl - INFO - Epoch [55][700/1281] lr: 1.769e-02, eta: 22:17:15, time: 0.609, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9994, loss_cls: 2.5173, loss: 2.5173 +2025-05-05 21:33:59,752 - pyskl - INFO - Epoch [55][800/1281] lr: 1.767e-02, eta: 22:16:30, time: 0.776, data_time: 0.000, memory: 9000, top1_acc: 0.9169, top5_acc: 0.9981, loss_cls: 2.5140, loss: 2.5140 +2025-05-05 21:35:04,969 - pyskl - INFO - Epoch [55][900/1281] lr: 1.766e-02, eta: 22:15:24, time: 0.652, data_time: 0.000, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9962, loss_cls: 2.5583, loss: 2.5583 +2025-05-05 21:36:05,648 - pyskl - INFO - Epoch [55][1000/1281] lr: 1.764e-02, eta: 22:14:09, time: 0.607, data_time: 0.000, memory: 9000, top1_acc: 0.9213, top5_acc: 0.9981, loss_cls: 2.4515, loss: 2.4515 +2025-05-05 21:37:06,038 - pyskl - INFO - Epoch [55][1100/1281] lr: 1.762e-02, eta: 22:12:55, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9219, top5_acc: 0.9994, loss_cls: 2.5842, loss: 2.5842 +2025-05-05 21:38:18,430 - pyskl - INFO - Epoch [55][1200/1281] lr: 1.760e-02, eta: 22:12:01, time: 0.724, data_time: 0.000, memory: 9000, top1_acc: 0.9113, top5_acc: 0.9981, loss_cls: 2.5331, loss: 2.5331 +2025-05-05 21:39:17,447 - pyskl - INFO - Saving checkpoint at 55 epochs +2025-05-05 21:40:08,521 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 21:40:08,577 - pyskl - INFO - +top1_acc 0.8607 +top5_acc 0.9905 +2025-05-05 21:40:08,577 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 21:40:08,584 - pyskl - INFO - +mean_acc 0.8252 +2025-05-05 21:40:08,586 - pyskl - INFO - Epoch(val) [55][533] top1_acc: 0.8607, top5_acc: 0.9905, mean_class_accuracy: 0.8252 +2025-05-05 21:41:15,812 - pyskl - INFO - Epoch [56][100/1281] lr: 1.757e-02, eta: 22:08:33, time: 0.672, data_time: 0.182, memory: 9000, top1_acc: 0.9375, top5_acc: 1.0000, loss_cls: 2.4975, loss: 2.4975 +2025-05-05 21:42:16,400 - pyskl - INFO - Epoch [56][200/1281] lr: 1.755e-02, eta: 22:07:19, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9350, top5_acc: 0.9988, loss_cls: 2.3683, loss: 2.3683 +2025-05-05 21:43:31,181 - pyskl - INFO - Epoch [56][300/1281] lr: 1.753e-02, eta: 22:06:29, time: 0.748, data_time: 0.000, memory: 9000, top1_acc: 0.9250, top5_acc: 0.9969, loss_cls: 2.4790, loss: 2.4790 +2025-05-05 21:44:36,183 - pyskl - INFO - Epoch [56][400/1281] lr: 1.751e-02, eta: 22:05:23, time: 0.650, data_time: 0.000, memory: 9000, top1_acc: 0.9263, top5_acc: 0.9994, loss_cls: 2.4639, loss: 2.4639 +2025-05-05 21:45:36,282 - pyskl - INFO - Epoch [56][500/1281] lr: 1.749e-02, eta: 22:04:08, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.9225, top5_acc: 1.0000, loss_cls: 2.4698, loss: 2.4698 +2025-05-05 21:46:36,178 - pyskl - INFO - Epoch [56][600/1281] lr: 1.747e-02, eta: 22:02:53, time: 0.599, data_time: 0.000, memory: 9000, top1_acc: 0.9144, top5_acc: 0.9994, loss_cls: 2.4563, loss: 2.4563 +2025-05-05 21:47:50,153 - pyskl - INFO - Epoch [56][700/1281] lr: 1.745e-02, eta: 22:02:02, time: 0.740, data_time: 0.000, memory: 9000, top1_acc: 0.9137, top5_acc: 0.9962, loss_cls: 2.4645, loss: 2.4645 +2025-05-05 21:48:58,411 - pyskl - INFO - Epoch [56][800/1281] lr: 1.743e-02, eta: 22:01:01, time: 0.683, data_time: 0.000, memory: 9000, top1_acc: 0.9150, top5_acc: 0.9962, loss_cls: 2.5087, loss: 2.5087 +2025-05-05 21:49:59,059 - pyskl - INFO - Epoch [56][900/1281] lr: 1.742e-02, eta: 21:59:47, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9125, top5_acc: 0.9994, loss_cls: 2.5367, loss: 2.5367 +2025-05-05 21:50:59,907 - pyskl - INFO - Epoch [56][1000/1281] lr: 1.740e-02, eta: 21:58:33, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9350, top5_acc: 0.9981, loss_cls: 2.4389, loss: 2.4389 +2025-05-05 21:52:08,303 - pyskl - INFO - Epoch [56][1100/1281] lr: 1.738e-02, eta: 21:57:32, time: 0.684, data_time: 0.000, memory: 9000, top1_acc: 0.9250, top5_acc: 1.0000, loss_cls: 2.4222, loss: 2.4222 +2025-05-05 21:53:22,807 - pyskl - INFO - Epoch [56][1200/1281] lr: 1.736e-02, eta: 21:56:42, time: 0.745, data_time: 0.000, memory: 9000, top1_acc: 0.9225, top5_acc: 0.9988, loss_cls: 2.4575, loss: 2.4575 +2025-05-05 21:54:13,903 - pyskl - INFO - Saving checkpoint at 56 epochs +2025-05-05 21:55:03,580 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 21:55:03,646 - pyskl - INFO - +top1_acc 0.8348 +top5_acc 0.9870 +2025-05-05 21:55:03,647 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 21:55:03,658 - pyskl - INFO - +mean_acc 0.7846 +2025-05-05 21:55:03,662 - pyskl - INFO - Epoch(val) [56][533] top1_acc: 0.8348, top5_acc: 0.9870, mean_class_accuracy: 0.7846 +2025-05-05 21:56:12,144 - pyskl - INFO - Epoch [57][100/1281] lr: 1.733e-02, eta: 21:53:19, time: 0.685, data_time: 0.178, memory: 9000, top1_acc: 0.9225, top5_acc: 1.0000, loss_cls: 2.4701, loss: 2.4701 +2025-05-05 21:57:22,319 - pyskl - INFO - Epoch [57][200/1281] lr: 1.731e-02, eta: 21:52:22, time: 0.702, data_time: 0.000, memory: 9000, top1_acc: 0.9356, top5_acc: 0.9981, loss_cls: 2.3601, loss: 2.3601 +2025-05-05 21:58:28,288 - pyskl - INFO - Epoch [57][300/1281] lr: 1.729e-02, eta: 21:51:17, time: 0.660, data_time: 0.000, memory: 9000, top1_acc: 0.9256, top5_acc: 0.9994, loss_cls: 2.4755, loss: 2.4755 +2025-05-05 21:59:28,086 - pyskl - INFO - Epoch [57][400/1281] lr: 1.727e-02, eta: 21:50:02, time: 0.598, data_time: 0.000, memory: 9000, top1_acc: 0.9319, top5_acc: 0.9975, loss_cls: 2.4277, loss: 2.4277 +2025-05-05 22:00:24,871 - pyskl - INFO - Epoch [57][500/1281] lr: 1.725e-02, eta: 21:48:42, time: 0.568, data_time: 0.000, memory: 9000, top1_acc: 0.9256, top5_acc: 0.9994, loss_cls: 2.4545, loss: 2.4545 +2025-05-05 22:01:31,534 - pyskl - INFO - Epoch [57][600/1281] lr: 1.723e-02, eta: 21:47:38, time: 0.667, data_time: 0.000, memory: 9000, top1_acc: 0.9206, top5_acc: 0.9962, loss_cls: 2.5141, loss: 2.5141 +2025-05-05 22:02:44,228 - pyskl - INFO - Epoch [57][700/1281] lr: 1.721e-02, eta: 21:46:45, time: 0.727, data_time: 0.000, memory: 9000, top1_acc: 0.9225, top5_acc: 0.9962, loss_cls: 2.5066, loss: 2.5066 +2025-05-05 22:03:46,444 - pyskl - INFO - Epoch [57][800/1281] lr: 1.719e-02, eta: 21:45:34, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.8975, top5_acc: 0.9981, loss_cls: 2.5985, loss: 2.5985 +2025-05-05 22:04:45,418 - pyskl - INFO - Epoch [57][900/1281] lr: 1.717e-02, eta: 21:44:18, time: 0.590, data_time: 0.000, memory: 9000, top1_acc: 0.9113, top5_acc: 0.9988, loss_cls: 2.4849, loss: 2.4849 +2025-05-05 22:05:48,050 - pyskl - INFO - Epoch [57][1000/1281] lr: 1.716e-02, eta: 21:43:07, time: 0.626, data_time: 0.000, memory: 9000, top1_acc: 0.9156, top5_acc: 0.9988, loss_cls: 2.4979, loss: 2.4979 +2025-05-05 22:07:03,123 - pyskl - INFO - Epoch [57][1100/1281] lr: 1.714e-02, eta: 21:42:18, time: 0.751, data_time: 0.000, memory: 9000, top1_acc: 0.9206, top5_acc: 0.9981, loss_cls: 2.4172, loss: 2.4172 +2025-05-05 22:08:07,935 - pyskl - INFO - Epoch [57][1200/1281] lr: 1.712e-02, eta: 21:41:11, time: 0.648, data_time: 0.000, memory: 9000, top1_acc: 0.9163, top5_acc: 0.9975, loss_cls: 2.5665, loss: 2.5665 +2025-05-05 22:08:57,590 - pyskl - INFO - Saving checkpoint at 57 epochs +2025-05-05 22:09:47,535 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 22:09:47,592 - pyskl - INFO - +top1_acc 0.8596 +top5_acc 0.9896 +2025-05-05 22:09:47,593 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 22:09:47,601 - pyskl - INFO - +mean_acc 0.8085 +2025-05-05 22:09:47,604 - pyskl - INFO - Epoch(val) [57][533] top1_acc: 0.8596, top5_acc: 0.9896, mean_class_accuracy: 0.8085 +2025-05-05 22:11:03,086 - pyskl - INFO - Epoch [58][100/1281] lr: 1.708e-02, eta: 21:38:02, time: 0.755, data_time: 0.180, memory: 9000, top1_acc: 0.9313, top5_acc: 0.9994, loss_cls: 2.4070, loss: 2.4070 +2025-05-05 22:12:10,249 - pyskl - INFO - Epoch [58][200/1281] lr: 1.706e-02, eta: 21:37:00, time: 0.672, data_time: 0.000, memory: 9000, top1_acc: 0.9294, top5_acc: 0.9975, loss_cls: 2.4417, loss: 2.4417 +2025-05-05 22:13:11,324 - pyskl - INFO - Epoch [58][300/1281] lr: 1.704e-02, eta: 21:35:47, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9988, loss_cls: 2.3864, loss: 2.3864 +2025-05-05 22:14:11,567 - pyskl - INFO - Epoch [58][400/1281] lr: 1.703e-02, eta: 21:34:34, time: 0.602, data_time: 0.000, memory: 9000, top1_acc: 0.9275, top5_acc: 0.9994, loss_cls: 2.4047, loss: 2.4047 +2025-05-05 22:15:14,392 - pyskl - INFO - Epoch [58][500/1281] lr: 1.701e-02, eta: 21:33:24, time: 0.628, data_time: 0.000, memory: 9000, top1_acc: 0.9250, top5_acc: 0.9988, loss_cls: 2.4889, loss: 2.4889 +2025-05-05 22:16:28,844 - pyskl - INFO - Epoch [58][600/1281] lr: 1.699e-02, eta: 21:32:33, time: 0.745, data_time: 0.000, memory: 9000, top1_acc: 0.9231, top5_acc: 0.9975, loss_cls: 2.5189, loss: 2.5189 +2025-05-05 22:17:34,267 - pyskl - INFO - Epoch [58][700/1281] lr: 1.697e-02, eta: 21:31:28, time: 0.654, data_time: 0.000, memory: 9000, top1_acc: 0.9263, top5_acc: 0.9994, loss_cls: 2.3834, loss: 2.3834 +2025-05-05 22:18:34,160 - pyskl - INFO - Epoch [58][800/1281] lr: 1.695e-02, eta: 21:30:13, time: 0.599, data_time: 0.000, memory: 9000, top1_acc: 0.9175, top5_acc: 0.9988, loss_cls: 2.4791, loss: 2.4791 +2025-05-05 22:19:35,461 - pyskl - INFO - Epoch [58][900/1281] lr: 1.693e-02, eta: 21:29:01, time: 0.613, data_time: 0.000, memory: 9000, top1_acc: 0.9150, top5_acc: 0.9988, loss_cls: 2.4595, loss: 2.4595 +2025-05-05 22:20:47,725 - pyskl - INFO - Epoch [58][1000/1281] lr: 1.691e-02, eta: 21:28:07, time: 0.723, data_time: 0.000, memory: 9000, top1_acc: 0.9244, top5_acc: 0.9988, loss_cls: 2.5265, loss: 2.5265 +2025-05-05 22:21:53,326 - pyskl - INFO - Epoch [58][1100/1281] lr: 1.689e-02, eta: 21:27:02, time: 0.656, data_time: 0.000, memory: 9000, top1_acc: 0.9081, top5_acc: 0.9975, loss_cls: 2.5909, loss: 2.5909 +2025-05-05 22:22:53,543 - pyskl - INFO - Epoch [58][1200/1281] lr: 1.687e-02, eta: 21:25:48, time: 0.602, data_time: 0.000, memory: 9000, top1_acc: 0.9225, top5_acc: 0.9975, loss_cls: 2.4463, loss: 2.4463 +2025-05-05 22:23:42,765 - pyskl - INFO - Saving checkpoint at 58 epochs +2025-05-05 22:24:34,742 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 22:24:34,800 - pyskl - INFO - +top1_acc 0.8363 +top5_acc 0.9890 +2025-05-05 22:24:34,800 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 22:24:34,809 - pyskl - INFO - +mean_acc 0.7907 +2025-05-05 22:24:34,812 - pyskl - INFO - Epoch(val) [58][533] top1_acc: 0.8363, top5_acc: 0.9890, mean_class_accuracy: 0.7907 +2025-05-05 22:25:53,378 - pyskl - INFO - Epoch [59][100/1281] lr: 1.684e-02, eta: 21:22:47, time: 0.786, data_time: 0.184, memory: 9000, top1_acc: 0.9394, top5_acc: 1.0000, loss_cls: 2.4321, loss: 2.4321 +2025-05-05 22:26:55,082 - pyskl - INFO - Epoch [59][200/1281] lr: 1.682e-02, eta: 21:21:35, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.9319, top5_acc: 0.9994, loss_cls: 2.3931, loss: 2.3931 +2025-05-05 22:27:55,201 - pyskl - INFO - Epoch [59][300/1281] lr: 1.680e-02, eta: 21:20:22, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9981, loss_cls: 2.4480, loss: 2.4480 +2025-05-05 22:28:57,203 - pyskl - INFO - Epoch [59][400/1281] lr: 1.678e-02, eta: 21:19:11, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.9181, top5_acc: 0.9994, loss_cls: 2.5263, loss: 2.5263 +2025-05-05 22:30:08,791 - pyskl - INFO - Epoch [59][500/1281] lr: 1.676e-02, eta: 21:18:16, time: 0.716, data_time: 0.000, memory: 9000, top1_acc: 0.9213, top5_acc: 0.9988, loss_cls: 2.4986, loss: 2.4986 +2025-05-05 22:31:15,139 - pyskl - INFO - Epoch [59][600/1281] lr: 1.674e-02, eta: 21:17:12, time: 0.663, data_time: 0.000, memory: 9000, top1_acc: 0.9287, top5_acc: 0.9994, loss_cls: 2.4097, loss: 2.4097 +2025-05-05 22:32:15,855 - pyskl - INFO - Epoch [59][700/1281] lr: 1.672e-02, eta: 21:15:59, time: 0.607, data_time: 0.000, memory: 9000, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 2.4851, loss: 2.4851 +2025-05-05 22:33:17,555 - pyskl - INFO - Epoch [59][800/1281] lr: 1.670e-02, eta: 21:14:48, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.9137, top5_acc: 0.9975, loss_cls: 2.5493, loss: 2.5493 +2025-05-05 22:34:23,694 - pyskl - INFO - Epoch [59][900/1281] lr: 1.668e-02, eta: 21:13:44, time: 0.661, data_time: 0.000, memory: 9000, top1_acc: 0.9287, top5_acc: 0.9988, loss_cls: 2.5336, loss: 2.5336 +2025-05-05 22:35:34,964 - pyskl - INFO - Epoch [59][1000/1281] lr: 1.667e-02, eta: 21:12:48, time: 0.713, data_time: 0.000, memory: 9000, top1_acc: 0.9344, top5_acc: 0.9988, loss_cls: 2.4084, loss: 2.4084 +2025-05-05 22:36:36,698 - pyskl - INFO - Epoch [59][1100/1281] lr: 1.665e-02, eta: 21:11:37, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.9206, top5_acc: 0.9962, loss_cls: 2.4999, loss: 2.4999 +2025-05-05 22:37:36,410 - pyskl - INFO - Epoch [59][1200/1281] lr: 1.663e-02, eta: 21:10:23, time: 0.597, data_time: 0.000, memory: 9000, top1_acc: 0.9150, top5_acc: 0.9994, loss_cls: 2.4630, loss: 2.4630 +2025-05-05 22:38:28,360 - pyskl - INFO - Saving checkpoint at 59 epochs +2025-05-05 22:39:28,093 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 22:39:28,148 - pyskl - INFO - +top1_acc 0.8826 +top5_acc 0.9928 +2025-05-05 22:39:28,148 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 22:39:28,155 - pyskl - INFO - +mean_acc 0.8402 +2025-05-05 22:39:28,213 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_51.pth was removed +2025-05-05 22:39:29,735 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_59.pth. +2025-05-05 22:39:29,736 - pyskl - INFO - Best top1_acc is 0.8826 at 59 epoch. +2025-05-05 22:39:29,739 - pyskl - INFO - Epoch(val) [59][533] top1_acc: 0.8826, top5_acc: 0.9928, mean_class_accuracy: 0.8402 +2025-05-05 22:40:43,133 - pyskl - INFO - Epoch [60][100/1281] lr: 1.659e-02, eta: 21:07:16, time: 0.734, data_time: 0.179, memory: 9000, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 2.3690, loss: 2.3690 +2025-05-05 22:41:42,273 - pyskl - INFO - Epoch [60][200/1281] lr: 1.657e-02, eta: 21:06:01, time: 0.591, data_time: 0.000, memory: 9000, top1_acc: 0.9369, top5_acc: 0.9981, loss_cls: 2.4078, loss: 2.4078 +2025-05-05 22:42:43,106 - pyskl - INFO - Epoch [60][300/1281] lr: 1.655e-02, eta: 21:04:49, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9337, top5_acc: 1.0000, loss_cls: 2.4337, loss: 2.4337 +2025-05-05 22:43:49,306 - pyskl - INFO - Epoch [60][400/1281] lr: 1.653e-02, eta: 21:03:45, time: 0.662, data_time: 0.000, memory: 9000, top1_acc: 0.9344, top5_acc: 0.9994, loss_cls: 2.4063, loss: 2.4063 +2025-05-05 22:44:59,046 - pyskl - INFO - Epoch [60][500/1281] lr: 1.651e-02, eta: 21:02:46, time: 0.697, data_time: 0.000, memory: 9000, top1_acc: 0.9319, top5_acc: 0.9975, loss_cls: 2.4282, loss: 2.4282 +2025-05-05 22:45:59,915 - pyskl - INFO - Epoch [60][600/1281] lr: 1.650e-02, eta: 21:01:34, time: 0.609, data_time: 0.000, memory: 9000, top1_acc: 0.9187, top5_acc: 1.0000, loss_cls: 2.4534, loss: 2.4534 +2025-05-05 22:47:01,634 - pyskl - INFO - Epoch [60][700/1281] lr: 1.648e-02, eta: 21:00:24, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.9363, top5_acc: 0.9988, loss_cls: 2.3860, loss: 2.3860 +2025-05-05 22:48:04,367 - pyskl - INFO - Epoch [60][800/1281] lr: 1.646e-02, eta: 20:59:15, time: 0.627, data_time: 0.000, memory: 9000, top1_acc: 0.9356, top5_acc: 0.9981, loss_cls: 2.4196, loss: 2.4196 +2025-05-05 22:49:16,391 - pyskl - INFO - Epoch [60][900/1281] lr: 1.644e-02, eta: 20:58:20, time: 0.720, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9981, loss_cls: 2.3105, loss: 2.3105 +2025-05-05 22:50:19,151 - pyskl - INFO - Epoch [60][1000/1281] lr: 1.642e-02, eta: 20:57:11, time: 0.628, data_time: 0.000, memory: 9000, top1_acc: 0.9244, top5_acc: 1.0000, loss_cls: 2.4878, loss: 2.4878 +2025-05-05 22:51:19,193 - pyskl - INFO - Epoch [60][1100/1281] lr: 1.640e-02, eta: 20:55:57, time: 0.600, data_time: 0.000, memory: 9000, top1_acc: 0.9250, top5_acc: 0.9994, loss_cls: 2.4162, loss: 2.4162 +2025-05-05 22:52:21,167 - pyskl - INFO - Epoch [60][1200/1281] lr: 1.638e-02, eta: 20:54:47, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.9213, top5_acc: 0.9975, loss_cls: 2.4582, loss: 2.4582 +2025-05-05 22:53:17,017 - pyskl - INFO - Saving checkpoint at 60 epochs +2025-05-05 22:54:14,324 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 22:54:14,379 - pyskl - INFO - +top1_acc 0.8675 +top5_acc 0.9906 +2025-05-05 22:54:14,379 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 22:54:14,386 - pyskl - INFO - +mean_acc 0.8239 +2025-05-05 22:54:14,388 - pyskl - INFO - Epoch(val) [60][533] top1_acc: 0.8675, top5_acc: 0.9906, mean_class_accuracy: 0.8239 +2025-05-05 22:55:25,386 - pyskl - INFO - Epoch [61][100/1281] lr: 1.634e-02, eta: 20:51:39, time: 0.710, data_time: 0.182, memory: 9000, top1_acc: 0.9331, top5_acc: 0.9994, loss_cls: 2.3787, loss: 2.3787 +2025-05-05 22:56:23,907 - pyskl - INFO - Epoch [61][200/1281] lr: 1.632e-02, eta: 20:50:23, time: 0.585, data_time: 0.000, memory: 9000, top1_acc: 0.9350, top5_acc: 0.9988, loss_cls: 2.3750, loss: 2.3750 +2025-05-05 22:57:25,062 - pyskl - INFO - Epoch [61][300/1281] lr: 1.630e-02, eta: 20:49:12, time: 0.612, data_time: 0.000, memory: 9000, top1_acc: 0.9287, top5_acc: 0.9994, loss_cls: 2.4306, loss: 2.4306 +2025-05-05 22:58:36,177 - pyskl - INFO - Epoch [61][400/1281] lr: 1.629e-02, eta: 20:48:16, time: 0.711, data_time: 0.000, memory: 9000, top1_acc: 0.9375, top5_acc: 0.9988, loss_cls: 2.3832, loss: 2.3832 +2025-05-05 22:59:39,825 - pyskl - INFO - Epoch [61][500/1281] lr: 1.627e-02, eta: 20:47:08, time: 0.636, data_time: 0.000, memory: 9000, top1_acc: 0.9306, top5_acc: 0.9975, loss_cls: 2.3712, loss: 2.3712 +2025-05-05 23:00:39,620 - pyskl - INFO - Epoch [61][600/1281] lr: 1.625e-02, eta: 20:45:55, time: 0.598, data_time: 0.000, memory: 9000, top1_acc: 0.9394, top5_acc: 0.9981, loss_cls: 2.2985, loss: 2.2985 +2025-05-05 23:01:41,452 - pyskl - INFO - Epoch [61][700/1281] lr: 1.623e-02, eta: 20:44:45, time: 0.618, data_time: 0.000, memory: 9000, top1_acc: 0.9250, top5_acc: 0.9969, loss_cls: 2.4288, loss: 2.4288 +2025-05-05 23:02:47,959 - pyskl - INFO - Epoch [61][800/1281] lr: 1.621e-02, eta: 20:43:42, time: 0.665, data_time: 0.000, memory: 9000, top1_acc: 0.9219, top5_acc: 0.9975, loss_cls: 2.5539, loss: 2.5539 +2025-05-05 23:03:55,576 - pyskl - INFO - Epoch [61][900/1281] lr: 1.619e-02, eta: 20:42:40, time: 0.676, data_time: 0.000, memory: 9000, top1_acc: 0.9237, top5_acc: 1.0000, loss_cls: 2.4685, loss: 2.4685 +2025-05-05 23:04:57,285 - pyskl - INFO - Epoch [61][1000/1281] lr: 1.617e-02, eta: 20:41:30, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9981, loss_cls: 2.5015, loss: 2.5015 +2025-05-05 23:05:59,104 - pyskl - INFO - Epoch [61][1100/1281] lr: 1.615e-02, eta: 20:40:20, time: 0.618, data_time: 0.000, memory: 9000, top1_acc: 0.9094, top5_acc: 0.9969, loss_cls: 2.5172, loss: 2.5172 +2025-05-05 23:07:03,286 - pyskl - INFO - Epoch [61][1200/1281] lr: 1.613e-02, eta: 20:39:13, time: 0.642, data_time: 0.000, memory: 9000, top1_acc: 0.9263, top5_acc: 0.9994, loss_cls: 2.4154, loss: 2.4154 +2025-05-05 23:08:01,196 - pyskl - INFO - Saving checkpoint at 61 epochs +2025-05-05 23:08:52,987 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 23:08:53,042 - pyskl - INFO - +top1_acc 0.8686 +top5_acc 0.9912 +2025-05-05 23:08:53,042 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 23:08:53,048 - pyskl - INFO - +mean_acc 0.8159 +2025-05-05 23:08:53,050 - pyskl - INFO - Epoch(val) [61][533] top1_acc: 0.8686, top5_acc: 0.9912, mean_class_accuracy: 0.8159 +2025-05-05 23:10:00,863 - pyskl - INFO - Epoch [62][100/1281] lr: 1.609e-02, eta: 20:36:02, time: 0.678, data_time: 0.180, memory: 9000, top1_acc: 0.9231, top5_acc: 0.9969, loss_cls: 2.4282, loss: 2.4282 +2025-05-05 23:11:01,148 - pyskl - INFO - Epoch [62][200/1281] lr: 1.607e-02, eta: 20:34:50, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9487, top5_acc: 1.0000, loss_cls: 2.2978, loss: 2.2978 +2025-05-05 23:12:07,624 - pyskl - INFO - Epoch [62][300/1281] lr: 1.605e-02, eta: 20:33:47, time: 0.665, data_time: 0.000, memory: 9000, top1_acc: 0.9425, top5_acc: 1.0000, loss_cls: 2.3088, loss: 2.3088 +2025-05-05 23:13:15,341 - pyskl - INFO - Epoch [62][400/1281] lr: 1.603e-02, eta: 20:32:46, time: 0.677, data_time: 0.000, memory: 9000, top1_acc: 0.9331, top5_acc: 0.9988, loss_cls: 2.3972, loss: 2.3972 +2025-05-05 23:14:15,728 - pyskl - INFO - Epoch [62][500/1281] lr: 1.602e-02, eta: 20:31:34, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9294, top5_acc: 0.9975, loss_cls: 2.3808, loss: 2.3808 +2025-05-05 23:15:17,607 - pyskl - INFO - Epoch [62][600/1281] lr: 1.600e-02, eta: 20:30:24, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9331, top5_acc: 0.9994, loss_cls: 2.3268, loss: 2.3268 +2025-05-05 23:16:20,249 - pyskl - INFO - Epoch [62][700/1281] lr: 1.598e-02, eta: 20:29:15, time: 0.626, data_time: 0.000, memory: 9000, top1_acc: 0.9356, top5_acc: 0.9988, loss_cls: 2.4028, loss: 2.4028 +2025-05-05 23:17:30,840 - pyskl - INFO - Epoch [62][800/1281] lr: 1.596e-02, eta: 20:28:18, time: 0.706, data_time: 0.000, memory: 9000, top1_acc: 0.9275, top5_acc: 0.9975, loss_cls: 2.3950, loss: 2.3950 +2025-05-05 23:18:34,229 - pyskl - INFO - Epoch [62][900/1281] lr: 1.594e-02, eta: 20:27:11, time: 0.634, data_time: 0.000, memory: 9000, top1_acc: 0.9281, top5_acc: 0.9988, loss_cls: 2.3470, loss: 2.3470 +2025-05-05 23:19:35,440 - pyskl - INFO - Epoch [62][1000/1281] lr: 1.592e-02, eta: 20:26:00, time: 0.612, data_time: 0.000, memory: 9000, top1_acc: 0.9163, top5_acc: 1.0000, loss_cls: 2.4443, loss: 2.4443 +2025-05-05 23:20:37,051 - pyskl - INFO - Epoch [62][1100/1281] lr: 1.590e-02, eta: 20:24:50, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.9275, top5_acc: 0.9988, loss_cls: 2.3727, loss: 2.3727 +2025-05-05 23:21:44,543 - pyskl - INFO - Epoch [62][1200/1281] lr: 1.588e-02, eta: 20:23:48, time: 0.675, data_time: 0.000, memory: 9000, top1_acc: 0.9281, top5_acc: 1.0000, loss_cls: 2.4560, loss: 2.4560 +2025-05-05 23:22:38,864 - pyskl - INFO - Saving checkpoint at 62 epochs +2025-05-05 23:23:30,036 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 23:23:30,092 - pyskl - INFO - +top1_acc 0.8805 +top5_acc 0.9911 +2025-05-05 23:23:30,092 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 23:23:30,099 - pyskl - INFO - +mean_acc 0.8381 +2025-05-05 23:23:30,101 - pyskl - INFO - Epoch(val) [62][533] top1_acc: 0.8805, top5_acc: 0.9911, mean_class_accuracy: 0.8381 +2025-05-05 23:24:38,598 - pyskl - INFO - Epoch [63][100/1281] lr: 1.584e-02, eta: 20:20:41, time: 0.685, data_time: 0.181, memory: 9000, top1_acc: 0.9287, top5_acc: 0.9994, loss_cls: 2.4474, loss: 2.4474 +2025-05-05 23:25:37,942 - pyskl - INFO - Epoch [63][200/1281] lr: 1.582e-02, eta: 20:19:28, time: 0.593, data_time: 0.000, memory: 9000, top1_acc: 0.9444, top5_acc: 1.0000, loss_cls: 2.3075, loss: 2.3075 +2025-05-05 23:26:46,561 - pyskl - INFO - Epoch [63][300/1281] lr: 1.580e-02, eta: 20:18:28, time: 0.686, data_time: 0.000, memory: 9000, top1_acc: 0.9275, top5_acc: 0.9994, loss_cls: 2.3754, loss: 2.3754 +2025-05-05 23:27:50,379 - pyskl - INFO - Epoch [63][400/1281] lr: 1.578e-02, eta: 20:17:21, time: 0.638, data_time: 0.000, memory: 9000, top1_acc: 0.9169, top5_acc: 1.0000, loss_cls: 2.4335, loss: 2.4335 +2025-05-05 23:28:51,171 - pyskl - INFO - Epoch [63][500/1281] lr: 1.576e-02, eta: 20:16:10, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9263, top5_acc: 0.9975, loss_cls: 2.4108, loss: 2.4108 +2025-05-05 23:29:53,053 - pyskl - INFO - Epoch [63][600/1281] lr: 1.574e-02, eta: 20:15:01, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9425, top5_acc: 0.9981, loss_cls: 2.2719, loss: 2.2719 +2025-05-05 23:31:00,418 - pyskl - INFO - Epoch [63][700/1281] lr: 1.572e-02, eta: 20:13:59, time: 0.674, data_time: 0.000, memory: 9000, top1_acc: 0.9337, top5_acc: 0.9988, loss_cls: 2.2788, loss: 2.2788 +2025-05-05 23:32:07,848 - pyskl - INFO - Epoch [63][800/1281] lr: 1.570e-02, eta: 20:12:57, time: 0.674, data_time: 0.000, memory: 9000, top1_acc: 0.9337, top5_acc: 0.9981, loss_cls: 2.3426, loss: 2.3426 +2025-05-05 23:33:09,121 - pyskl - INFO - Epoch [63][900/1281] lr: 1.568e-02, eta: 20:11:47, time: 0.613, data_time: 0.000, memory: 9000, top1_acc: 0.9313, top5_acc: 0.9981, loss_cls: 2.3645, loss: 2.3645 +2025-05-05 23:34:11,254 - pyskl - INFO - Epoch [63][1000/1281] lr: 1.566e-02, eta: 20:10:38, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.9306, top5_acc: 0.9994, loss_cls: 2.3448, loss: 2.3448 +2025-05-05 23:35:15,573 - pyskl - INFO - Epoch [63][1100/1281] lr: 1.564e-02, eta: 20:09:32, time: 0.643, data_time: 0.000, memory: 9000, top1_acc: 0.9319, top5_acc: 0.9975, loss_cls: 2.3605, loss: 2.3605 +2025-05-05 23:36:24,130 - pyskl - INFO - Epoch [63][1200/1281] lr: 1.562e-02, eta: 20:08:32, time: 0.686, data_time: 0.000, memory: 9000, top1_acc: 0.9181, top5_acc: 0.9988, loss_cls: 2.5785, loss: 2.5785 +2025-05-05 23:37:15,216 - pyskl - INFO - Saving checkpoint at 63 epochs +2025-05-05 23:38:05,503 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 23:38:05,557 - pyskl - INFO - +top1_acc 0.8805 +top5_acc 0.9924 +2025-05-05 23:38:05,558 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 23:38:05,564 - pyskl - INFO - +mean_acc 0.8425 +2025-05-05 23:38:05,566 - pyskl - INFO - Epoch(val) [63][533] top1_acc: 0.8805, top5_acc: 0.9924, mean_class_accuracy: 0.8425 +2025-05-05 23:39:14,580 - pyskl - INFO - Epoch [64][100/1281] lr: 1.559e-02, eta: 20:05:27, time: 0.690, data_time: 0.182, memory: 9000, top1_acc: 0.9437, top5_acc: 0.9994, loss_cls: 2.2661, loss: 2.2661 +2025-05-05 23:40:15,417 - pyskl - INFO - Epoch [64][200/1281] lr: 1.557e-02, eta: 20:04:16, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9981, loss_cls: 2.3538, loss: 2.3538 +2025-05-05 23:41:22,202 - pyskl - INFO - Epoch [64][300/1281] lr: 1.555e-02, eta: 20:03:14, time: 0.668, data_time: 0.000, memory: 9000, top1_acc: 0.9294, top5_acc: 0.9981, loss_cls: 2.3941, loss: 2.3941 +2025-05-05 23:42:23,698 - pyskl - INFO - Epoch [64][400/1281] lr: 1.553e-02, eta: 20:02:04, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 0.9337, top5_acc: 1.0000, loss_cls: 2.4066, loss: 2.4066 +2025-05-05 23:43:25,585 - pyskl - INFO - Epoch [64][500/1281] lr: 1.551e-02, eta: 20:00:55, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9306, top5_acc: 0.9975, loss_cls: 2.4234, loss: 2.4234 +2025-05-05 23:44:28,720 - pyskl - INFO - Epoch [64][600/1281] lr: 1.549e-02, eta: 19:59:48, time: 0.631, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9975, loss_cls: 2.4708, loss: 2.4708 +2025-05-05 23:45:36,310 - pyskl - INFO - Epoch [64][700/1281] lr: 1.547e-02, eta: 19:58:46, time: 0.676, data_time: 0.000, memory: 9000, top1_acc: 0.9250, top5_acc: 0.9994, loss_cls: 2.4416, loss: 2.4416 +2025-05-05 23:46:40,059 - pyskl - INFO - Epoch [64][800/1281] lr: 1.545e-02, eta: 19:57:40, time: 0.637, data_time: 0.000, memory: 9000, top1_acc: 0.9463, top5_acc: 0.9988, loss_cls: 2.3522, loss: 2.3522 +2025-05-05 23:47:40,762 - pyskl - INFO - Epoch [64][900/1281] lr: 1.543e-02, eta: 19:56:29, time: 0.607, data_time: 0.000, memory: 9000, top1_acc: 0.9325, top5_acc: 0.9988, loss_cls: 2.3970, loss: 2.3970 +2025-05-05 23:48:43,095 - pyskl - INFO - Epoch [64][1000/1281] lr: 1.541e-02, eta: 19:55:21, time: 0.623, data_time: 0.000, memory: 9000, top1_acc: 0.9337, top5_acc: 0.9975, loss_cls: 2.4680, loss: 2.4680 +2025-05-05 23:49:47,511 - pyskl - INFO - Epoch [64][1100/1281] lr: 1.539e-02, eta: 19:54:15, time: 0.644, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 0.9994, loss_cls: 2.4122, loss: 2.4122 +2025-05-05 23:50:53,057 - pyskl - INFO - Epoch [64][1200/1281] lr: 1.537e-02, eta: 19:53:11, time: 0.655, data_time: 0.000, memory: 9000, top1_acc: 0.9306, top5_acc: 0.9988, loss_cls: 2.3462, loss: 2.3462 +2025-05-05 23:51:42,441 - pyskl - INFO - Saving checkpoint at 64 epochs +2025-05-05 23:52:33,325 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-05 23:52:33,380 - pyskl - INFO - +top1_acc 0.8700 +top5_acc 0.9908 +2025-05-05 23:52:33,380 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-05 23:52:33,386 - pyskl - INFO - +mean_acc 0.8271 +2025-05-05 23:52:33,388 - pyskl - INFO - Epoch(val) [64][533] top1_acc: 0.8700, top5_acc: 0.9908, mean_class_accuracy: 0.8271 +2025-05-05 23:53:43,453 - pyskl - INFO - Epoch [65][100/1281] lr: 1.533e-02, eta: 19:50:10, time: 0.701, data_time: 0.179, memory: 9000, top1_acc: 0.9131, top5_acc: 0.9994, loss_cls: 2.4442, loss: 2.4442 +2025-05-05 23:54:46,796 - pyskl - INFO - Epoch [65][200/1281] lr: 1.531e-02, eta: 19:49:03, time: 0.633, data_time: 0.000, memory: 9000, top1_acc: 0.9387, top5_acc: 1.0000, loss_cls: 2.3475, loss: 2.3475 +2025-05-05 23:55:51,183 - pyskl - INFO - Epoch [65][300/1281] lr: 1.529e-02, eta: 19:47:57, time: 0.644, data_time: 0.000, memory: 9000, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 2.2395, loss: 2.2395 +2025-05-05 23:56:52,265 - pyskl - INFO - Epoch [65][400/1281] lr: 1.527e-02, eta: 19:46:47, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9444, top5_acc: 0.9994, loss_cls: 2.1882, loss: 2.1882 +2025-05-05 23:57:56,577 - pyskl - INFO - Epoch [65][500/1281] lr: 1.526e-02, eta: 19:45:42, time: 0.643, data_time: 0.000, memory: 9000, top1_acc: 0.9256, top5_acc: 0.9988, loss_cls: 2.3888, loss: 2.3888 +2025-05-05 23:59:01,563 - pyskl - INFO - Epoch [65][600/1281] lr: 1.524e-02, eta: 19:44:37, time: 0.650, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9994, loss_cls: 2.3459, loss: 2.3459 +2025-05-06 00:00:07,263 - pyskl - INFO - Epoch [65][700/1281] lr: 1.522e-02, eta: 19:43:33, time: 0.657, data_time: 0.000, memory: 9000, top1_acc: 0.9344, top5_acc: 0.9994, loss_cls: 2.3455, loss: 2.3455 +2025-05-06 00:01:07,525 - pyskl - INFO - Epoch [65][800/1281] lr: 1.520e-02, eta: 19:42:22, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9344, top5_acc: 0.9981, loss_cls: 2.2149, loss: 2.2149 +2025-05-06 00:02:09,461 - pyskl - INFO - Epoch [65][900/1281] lr: 1.518e-02, eta: 19:41:13, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9237, top5_acc: 0.9981, loss_cls: 2.4204, loss: 2.4204 +2025-05-06 00:03:13,039 - pyskl - INFO - Epoch [65][1000/1281] lr: 1.516e-02, eta: 19:40:07, time: 0.636, data_time: 0.000, memory: 9000, top1_acc: 0.9269, top5_acc: 0.9981, loss_cls: 2.4179, loss: 2.4179 +2025-05-06 00:04:17,516 - pyskl - INFO - Epoch [65][1100/1281] lr: 1.514e-02, eta: 19:39:02, time: 0.645, data_time: 0.000, memory: 9000, top1_acc: 0.9250, top5_acc: 0.9969, loss_cls: 2.4188, loss: 2.4188 +2025-05-06 00:05:19,003 - pyskl - INFO - Epoch [65][1200/1281] lr: 1.512e-02, eta: 19:37:52, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 0.9994, loss_cls: 2.4168, loss: 2.4168 +2025-05-06 00:06:08,214 - pyskl - INFO - Saving checkpoint at 65 epochs +2025-05-06 00:06:58,780 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 00:06:58,837 - pyskl - INFO - +top1_acc 0.8729 +top5_acc 0.9900 +2025-05-06 00:06:58,837 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 00:06:58,845 - pyskl - INFO - +mean_acc 0.8200 +2025-05-06 00:06:58,848 - pyskl - INFO - Epoch(val) [65][533] top1_acc: 0.8729, top5_acc: 0.9900, mean_class_accuracy: 0.8200 +2025-05-06 00:08:09,905 - pyskl - INFO - Epoch [66][100/1281] lr: 1.508e-02, eta: 19:34:54, time: 0.711, data_time: 0.179, memory: 9000, top1_acc: 0.9369, top5_acc: 0.9994, loss_cls: 2.3120, loss: 2.3120 +2025-05-06 00:09:12,030 - pyskl - INFO - Epoch [66][200/1281] lr: 1.506e-02, eta: 19:33:46, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.9456, top5_acc: 0.9988, loss_cls: 2.2365, loss: 2.2365 +2025-05-06 00:10:12,096 - pyskl - INFO - Epoch [66][300/1281] lr: 1.504e-02, eta: 19:32:35, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.9437, top5_acc: 0.9994, loss_cls: 2.2606, loss: 2.2606 +2025-05-06 00:11:13,147 - pyskl - INFO - Epoch [66][400/1281] lr: 1.502e-02, eta: 19:31:26, time: 0.610, data_time: 0.000, memory: 9000, top1_acc: 0.9463, top5_acc: 0.9988, loss_cls: 2.2453, loss: 2.2453 +2025-05-06 00:12:15,734 - pyskl - INFO - Epoch [66][500/1281] lr: 1.500e-02, eta: 19:30:18, time: 0.626, data_time: 0.000, memory: 9000, top1_acc: 0.9394, top5_acc: 0.9994, loss_cls: 2.3157, loss: 2.3157 +2025-05-06 00:13:20,284 - pyskl - INFO - Epoch [66][600/1281] lr: 1.498e-02, eta: 19:29:13, time: 0.645, data_time: 0.000, memory: 9000, top1_acc: 0.9325, top5_acc: 0.9994, loss_cls: 2.3738, loss: 2.3738 +2025-05-06 00:14:22,268 - pyskl - INFO - Epoch [66][700/1281] lr: 1.496e-02, eta: 19:28:04, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 2.4165, loss: 2.4165 +2025-05-06 00:15:21,529 - pyskl - INFO - Epoch [66][800/1281] lr: 1.494e-02, eta: 19:26:52, time: 0.593, data_time: 0.000, memory: 9000, top1_acc: 0.9425, top5_acc: 0.9981, loss_cls: 2.3569, loss: 2.3569 +2025-05-06 00:16:24,111 - pyskl - INFO - Epoch [66][900/1281] lr: 1.492e-02, eta: 19:25:45, time: 0.626, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9981, loss_cls: 2.4121, loss: 2.4121 +2025-05-06 00:17:28,295 - pyskl - INFO - Epoch [66][1000/1281] lr: 1.490e-02, eta: 19:24:39, time: 0.642, data_time: 0.000, memory: 9000, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 2.3524, loss: 2.3524 +2025-05-06 00:18:30,879 - pyskl - INFO - Epoch [66][1100/1281] lr: 1.488e-02, eta: 19:23:32, time: 0.626, data_time: 0.000, memory: 9000, top1_acc: 0.9456, top5_acc: 1.0000, loss_cls: 2.3381, loss: 2.3381 +2025-05-06 00:19:31,523 - pyskl - INFO - Epoch [66][1200/1281] lr: 1.486e-02, eta: 19:22:22, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9200, top5_acc: 0.9988, loss_cls: 2.4165, loss: 2.4165 +2025-05-06 00:20:21,537 - pyskl - INFO - Saving checkpoint at 66 epochs +2025-05-06 00:21:13,423 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 00:21:13,479 - pyskl - INFO - +top1_acc 0.8642 +top5_acc 0.9897 +2025-05-06 00:21:13,479 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 00:21:13,488 - pyskl - INFO - +mean_acc 0.8342 +2025-05-06 00:21:13,491 - pyskl - INFO - Epoch(val) [66][533] top1_acc: 0.8642, top5_acc: 0.9897, mean_class_accuracy: 0.8342 +2025-05-06 00:22:23,730 - pyskl - INFO - Epoch [67][100/1281] lr: 1.482e-02, eta: 19:19:25, time: 0.702, data_time: 0.181, memory: 9000, top1_acc: 0.9400, top5_acc: 0.9994, loss_cls: 2.2971, loss: 2.2971 +2025-05-06 00:23:24,615 - pyskl - INFO - Epoch [67][200/1281] lr: 1.480e-02, eta: 19:18:15, time: 0.609, data_time: 0.000, memory: 9000, top1_acc: 0.9469, top5_acc: 0.9994, loss_cls: 2.1998, loss: 2.1998 +2025-05-06 00:24:24,995 - pyskl - INFO - Epoch [67][300/1281] lr: 1.478e-02, eta: 19:17:05, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9325, top5_acc: 0.9994, loss_cls: 2.3435, loss: 2.3435 +2025-05-06 00:25:27,046 - pyskl - INFO - Epoch [67][400/1281] lr: 1.476e-02, eta: 19:15:57, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 0.9988, loss_cls: 2.3165, loss: 2.3165 +2025-05-06 00:26:29,324 - pyskl - INFO - Epoch [67][500/1281] lr: 1.474e-02, eta: 19:14:49, time: 0.623, data_time: 0.000, memory: 9000, top1_acc: 0.9319, top5_acc: 0.9981, loss_cls: 2.3762, loss: 2.3762 +2025-05-06 00:27:32,702 - pyskl - INFO - Epoch [67][600/1281] lr: 1.472e-02, eta: 19:13:43, time: 0.634, data_time: 0.000, memory: 9000, top1_acc: 0.9200, top5_acc: 0.9994, loss_cls: 2.4427, loss: 2.4427 +2025-05-06 00:28:34,849 - pyskl - INFO - Epoch [67][700/1281] lr: 1.470e-02, eta: 19:12:35, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.9313, top5_acc: 0.9988, loss_cls: 2.3035, loss: 2.3035 +2025-05-06 00:29:35,526 - pyskl - INFO - Epoch [67][800/1281] lr: 1.468e-02, eta: 19:11:25, time: 0.607, data_time: 0.000, memory: 9000, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 2.3168, loss: 2.3168 +2025-05-06 00:30:39,366 - pyskl - INFO - Epoch [67][900/1281] lr: 1.466e-02, eta: 19:10:20, time: 0.638, data_time: 0.000, memory: 9000, top1_acc: 0.9350, top5_acc: 0.9981, loss_cls: 2.2242, loss: 2.2242 +2025-05-06 00:31:43,885 - pyskl - INFO - Epoch [67][1000/1281] lr: 1.464e-02, eta: 19:09:15, time: 0.645, data_time: 0.000, memory: 9000, top1_acc: 0.9294, top5_acc: 0.9981, loss_cls: 2.3857, loss: 2.3857 +2025-05-06 00:32:46,185 - pyskl - INFO - Epoch [67][1100/1281] lr: 1.462e-02, eta: 19:08:07, time: 0.623, data_time: 0.000, memory: 9000, top1_acc: 0.9231, top5_acc: 0.9975, loss_cls: 2.4156, loss: 2.4156 +2025-05-06 00:33:47,242 - pyskl - INFO - Epoch [67][1200/1281] lr: 1.460e-02, eta: 19:06:58, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9444, top5_acc: 0.9994, loss_cls: 2.3398, loss: 2.3398 +2025-05-06 00:34:37,770 - pyskl - INFO - Saving checkpoint at 67 epochs +2025-05-06 00:35:29,612 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 00:35:29,668 - pyskl - INFO - +top1_acc 0.8567 +top5_acc 0.9920 +2025-05-06 00:35:29,668 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 00:35:29,676 - pyskl - INFO - +mean_acc 0.8041 +2025-05-06 00:35:29,679 - pyskl - INFO - Epoch(val) [67][533] top1_acc: 0.8567, top5_acc: 0.9920, mean_class_accuracy: 0.8041 +2025-05-06 00:36:39,102 - pyskl - INFO - Epoch [68][100/1281] lr: 1.456e-02, eta: 19:04:02, time: 0.694, data_time: 0.179, memory: 9000, top1_acc: 0.9437, top5_acc: 0.9994, loss_cls: 2.2357, loss: 2.2357 +2025-05-06 00:37:38,500 - pyskl - INFO - Epoch [68][200/1281] lr: 1.454e-02, eta: 19:02:51, time: 0.594, data_time: 0.000, memory: 9000, top1_acc: 0.9456, top5_acc: 1.0000, loss_cls: 2.2952, loss: 2.2952 +2025-05-06 00:38:38,929 - pyskl - INFO - Epoch [68][300/1281] lr: 1.452e-02, eta: 19:01:41, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9431, top5_acc: 1.0000, loss_cls: 2.3038, loss: 2.3038 +2025-05-06 00:39:41,911 - pyskl - INFO - Epoch [68][400/1281] lr: 1.450e-02, eta: 19:00:35, time: 0.630, data_time: 0.000, memory: 9000, top1_acc: 0.9363, top5_acc: 0.9988, loss_cls: 2.4149, loss: 2.4149 +2025-05-06 00:40:47,928 - pyskl - INFO - Epoch [68][500/1281] lr: 1.448e-02, eta: 18:59:32, time: 0.660, data_time: 0.000, memory: 9000, top1_acc: 0.9475, top5_acc: 1.0000, loss_cls: 2.2527, loss: 2.2527 +2025-05-06 00:41:53,779 - pyskl - INFO - Epoch [68][600/1281] lr: 1.446e-02, eta: 18:58:29, time: 0.658, data_time: 0.000, memory: 9000, top1_acc: 0.9294, top5_acc: 0.9994, loss_cls: 2.3518, loss: 2.3518 +2025-05-06 00:42:54,428 - pyskl - INFO - Epoch [68][700/1281] lr: 1.444e-02, eta: 18:57:19, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9363, top5_acc: 0.9994, loss_cls: 2.3832, loss: 2.3832 +2025-05-06 00:43:55,860 - pyskl - INFO - Epoch [68][800/1281] lr: 1.442e-02, eta: 18:56:11, time: 0.614, data_time: 0.000, memory: 9000, top1_acc: 0.9275, top5_acc: 0.9994, loss_cls: 2.3606, loss: 2.3606 +2025-05-06 00:45:00,759 - pyskl - INFO - Epoch [68][900/1281] lr: 1.440e-02, eta: 18:55:06, time: 0.649, data_time: 0.000, memory: 9000, top1_acc: 0.9344, top5_acc: 0.9988, loss_cls: 2.3508, loss: 2.3508 +2025-05-06 00:46:03,749 - pyskl - INFO - Epoch [68][1000/1281] lr: 1.438e-02, eta: 18:54:00, time: 0.630, data_time: 0.000, memory: 9000, top1_acc: 0.9319, top5_acc: 0.9994, loss_cls: 2.3658, loss: 2.3658 +2025-05-06 00:47:05,999 - pyskl - INFO - Epoch [68][1100/1281] lr: 1.436e-02, eta: 18:52:52, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.9344, top5_acc: 0.9969, loss_cls: 2.4067, loss: 2.4067 +2025-05-06 00:48:06,425 - pyskl - INFO - Epoch [68][1200/1281] lr: 1.434e-02, eta: 18:51:43, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9313, top5_acc: 0.9981, loss_cls: 2.4063, loss: 2.4063 +2025-05-06 00:48:58,135 - pyskl - INFO - Saving checkpoint at 68 epochs +2025-05-06 00:49:52,013 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 00:49:52,068 - pyskl - INFO - +top1_acc 0.8728 +top5_acc 0.9903 +2025-05-06 00:49:52,068 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 00:49:52,075 - pyskl - INFO - +mean_acc 0.8421 +2025-05-06 00:49:52,077 - pyskl - INFO - Epoch(val) [68][533] top1_acc: 0.8728, top5_acc: 0.9903, mean_class_accuracy: 0.8421 +2025-05-06 00:51:01,784 - pyskl - INFO - Epoch [69][100/1281] lr: 1.431e-02, eta: 18:48:49, time: 0.697, data_time: 0.178, memory: 9000, top1_acc: 0.9575, top5_acc: 0.9994, loss_cls: 2.1482, loss: 2.1482 +2025-05-06 00:51:59,670 - pyskl - INFO - Epoch [69][200/1281] lr: 1.429e-02, eta: 18:47:36, time: 0.579, data_time: 0.000, memory: 9000, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 2.1909, loss: 2.1909 +2025-05-06 00:53:00,491 - pyskl - INFO - Epoch [69][300/1281] lr: 1.427e-02, eta: 18:46:27, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9481, top5_acc: 0.9981, loss_cls: 2.2962, loss: 2.2962 +2025-05-06 00:54:06,248 - pyskl - INFO - Epoch [69][400/1281] lr: 1.425e-02, eta: 18:45:24, time: 0.658, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9994, loss_cls: 2.3549, loss: 2.3549 +2025-05-06 00:55:12,518 - pyskl - INFO - Epoch [69][500/1281] lr: 1.423e-02, eta: 18:44:22, time: 0.663, data_time: 0.000, memory: 9000, top1_acc: 0.9394, top5_acc: 0.9975, loss_cls: 2.3484, loss: 2.3484 +2025-05-06 00:56:15,623 - pyskl - INFO - Epoch [69][600/1281] lr: 1.420e-02, eta: 18:43:16, time: 0.631, data_time: 0.000, memory: 9000, top1_acc: 0.9444, top5_acc: 0.9988, loss_cls: 2.3396, loss: 2.3396 +2025-05-06 00:57:14,469 - pyskl - INFO - Epoch [69][700/1281] lr: 1.418e-02, eta: 18:42:04, time: 0.588, data_time: 0.000, memory: 9000, top1_acc: 0.9437, top5_acc: 1.0000, loss_cls: 2.3506, loss: 2.3506 +2025-05-06 00:58:17,950 - pyskl - INFO - Epoch [69][800/1281] lr: 1.416e-02, eta: 18:40:59, time: 0.635, data_time: 0.000, memory: 9000, top1_acc: 0.9150, top5_acc: 0.9994, loss_cls: 2.3984, loss: 2.3984 +2025-05-06 00:59:23,756 - pyskl - INFO - Epoch [69][900/1281] lr: 1.414e-02, eta: 18:39:56, time: 0.658, data_time: 0.000, memory: 9000, top1_acc: 0.9275, top5_acc: 0.9988, loss_cls: 2.3682, loss: 2.3682 +2025-05-06 01:00:26,354 - pyskl - INFO - Epoch [69][1000/1281] lr: 1.412e-02, eta: 18:38:49, time: 0.626, data_time: 0.000, memory: 9000, top1_acc: 0.9394, top5_acc: 0.9994, loss_cls: 2.3553, loss: 2.3553 +2025-05-06 01:01:27,914 - pyskl - INFO - Epoch [69][1100/1281] lr: 1.410e-02, eta: 18:37:41, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.9350, top5_acc: 0.9994, loss_cls: 2.3214, loss: 2.3214 +2025-05-06 01:02:28,744 - pyskl - INFO - Epoch [69][1200/1281] lr: 1.408e-02, eta: 18:36:32, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 1.0000, loss_cls: 2.2862, loss: 2.2862 +2025-05-06 01:03:20,499 - pyskl - INFO - Saving checkpoint at 69 epochs +2025-05-06 01:04:12,548 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 01:04:12,603 - pyskl - INFO - +top1_acc 0.8771 +top5_acc 0.9917 +2025-05-06 01:04:12,603 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 01:04:12,609 - pyskl - INFO - +mean_acc 0.8321 +2025-05-06 01:04:12,611 - pyskl - INFO - Epoch(val) [69][533] top1_acc: 0.8771, top5_acc: 0.9917, mean_class_accuracy: 0.8321 +2025-05-06 01:05:23,119 - pyskl - INFO - Epoch [70][100/1281] lr: 1.405e-02, eta: 18:33:41, time: 0.705, data_time: 0.181, memory: 9000, top1_acc: 0.9375, top5_acc: 1.0000, loss_cls: 2.2304, loss: 2.2304 +2025-05-06 01:06:22,126 - pyskl - INFO - Epoch [70][200/1281] lr: 1.403e-02, eta: 18:32:30, time: 0.590, data_time: 0.000, memory: 9000, top1_acc: 0.9425, top5_acc: 0.9988, loss_cls: 2.2183, loss: 2.2183 +2025-05-06 01:07:24,541 - pyskl - INFO - Epoch [70][300/1281] lr: 1.401e-02, eta: 18:31:23, time: 0.624, data_time: 0.000, memory: 9000, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 2.2734, loss: 2.2734 +2025-05-06 01:08:27,560 - pyskl - INFO - Epoch [70][400/1281] lr: 1.399e-02, eta: 18:30:17, time: 0.630, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 0.9994, loss_cls: 2.3725, loss: 2.3725 +2025-05-06 01:09:27,299 - pyskl - INFO - Epoch [70][500/1281] lr: 1.397e-02, eta: 18:29:07, time: 0.597, data_time: 0.000, memory: 9000, top1_acc: 0.9419, top5_acc: 1.0000, loss_cls: 2.3134, loss: 2.3134 +2025-05-06 01:10:26,380 - pyskl - INFO - Epoch [70][600/1281] lr: 1.395e-02, eta: 18:27:57, time: 0.591, data_time: 0.000, memory: 9000, top1_acc: 0.9594, top5_acc: 0.9994, loss_cls: 2.2285, loss: 2.2285 +2025-05-06 01:11:26,734 - pyskl - INFO - Epoch [70][700/1281] lr: 1.392e-02, eta: 18:26:47, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9319, top5_acc: 0.9994, loss_cls: 2.4224, loss: 2.4224 +2025-05-06 01:12:31,961 - pyskl - INFO - Epoch [70][800/1281] lr: 1.390e-02, eta: 18:25:44, time: 0.652, data_time: 0.000, memory: 9000, top1_acc: 0.9287, top5_acc: 1.0000, loss_cls: 2.3323, loss: 2.3323 +2025-05-06 01:13:38,514 - pyskl - INFO - Epoch [70][900/1281] lr: 1.388e-02, eta: 18:24:42, time: 0.666, data_time: 0.000, memory: 9000, top1_acc: 0.9331, top5_acc: 0.9994, loss_cls: 2.2959, loss: 2.2959 +2025-05-06 01:14:42,715 - pyskl - INFO - Epoch [70][1000/1281] lr: 1.386e-02, eta: 18:23:37, time: 0.642, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9994, loss_cls: 2.3235, loss: 2.3235 +2025-05-06 01:15:42,400 - pyskl - INFO - Epoch [70][1100/1281] lr: 1.384e-02, eta: 18:22:27, time: 0.597, data_time: 0.000, memory: 9000, top1_acc: 0.9419, top5_acc: 0.9981, loss_cls: 2.3310, loss: 2.3310 +2025-05-06 01:16:45,463 - pyskl - INFO - Epoch [70][1200/1281] lr: 1.382e-02, eta: 18:21:21, time: 0.631, data_time: 0.000, memory: 9000, top1_acc: 0.9487, top5_acc: 1.0000, loss_cls: 2.2705, loss: 2.2705 +2025-05-06 01:17:39,069 - pyskl - INFO - Saving checkpoint at 70 epochs +2025-05-06 01:18:31,048 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 01:18:31,103 - pyskl - INFO - +top1_acc 0.8722 +top5_acc 0.9903 +2025-05-06 01:18:31,103 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 01:18:31,110 - pyskl - INFO - +mean_acc 0.8363 +2025-05-06 01:18:31,112 - pyskl - INFO - Epoch(val) [70][533] top1_acc: 0.8722, top5_acc: 0.9903, mean_class_accuracy: 0.8363 +2025-05-06 01:19:40,454 - pyskl - INFO - Epoch [71][100/1281] lr: 1.379e-02, eta: 18:18:31, time: 0.693, data_time: 0.181, memory: 9000, top1_acc: 0.9381, top5_acc: 0.9994, loss_cls: 2.2512, loss: 2.2512 +2025-05-06 01:20:37,971 - pyskl - INFO - Epoch [71][200/1281] lr: 1.377e-02, eta: 18:17:19, time: 0.575, data_time: 0.000, memory: 9000, top1_acc: 0.9431, top5_acc: 0.9988, loss_cls: 2.2932, loss: 2.2932 +2025-05-06 01:21:43,181 - pyskl - INFO - Epoch [71][300/1281] lr: 1.375e-02, eta: 18:16:15, time: 0.652, data_time: 0.000, memory: 9000, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 2.1954, loss: 2.1954 +2025-05-06 01:22:47,442 - pyskl - INFO - Epoch [71][400/1281] lr: 1.373e-02, eta: 18:15:11, time: 0.643, data_time: 0.000, memory: 9000, top1_acc: 0.9375, top5_acc: 0.9988, loss_cls: 2.2858, loss: 2.2858 +2025-05-06 01:23:49,385 - pyskl - INFO - Epoch [71][500/1281] lr: 1.371e-02, eta: 18:14:04, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9419, top5_acc: 0.9994, loss_cls: 2.2524, loss: 2.2524 +2025-05-06 01:24:49,856 - pyskl - INFO - Epoch [71][600/1281] lr: 1.368e-02, eta: 18:12:55, time: 0.605, data_time: 0.000, memory: 9000, top1_acc: 0.9363, top5_acc: 0.9988, loss_cls: 2.2764, loss: 2.2764 +2025-05-06 01:25:53,129 - pyskl - INFO - Epoch [71][700/1281] lr: 1.366e-02, eta: 18:11:49, time: 0.633, data_time: 0.000, memory: 9000, top1_acc: 0.9375, top5_acc: 1.0000, loss_cls: 2.3313, loss: 2.3313 +2025-05-06 01:26:59,892 - pyskl - INFO - Epoch [71][800/1281] lr: 1.364e-02, eta: 18:10:48, time: 0.668, data_time: 0.000, memory: 9000, top1_acc: 0.9494, top5_acc: 0.9988, loss_cls: 2.2554, loss: 2.2554 +2025-05-06 01:28:06,578 - pyskl - INFO - Epoch [71][900/1281] lr: 1.362e-02, eta: 18:09:46, time: 0.667, data_time: 0.000, memory: 9000, top1_acc: 0.9369, top5_acc: 0.9994, loss_cls: 2.3229, loss: 2.3229 +2025-05-06 01:29:08,341 - pyskl - INFO - Epoch [71][1000/1281] lr: 1.360e-02, eta: 18:08:38, time: 0.618, data_time: 0.000, memory: 9000, top1_acc: 0.9350, top5_acc: 0.9981, loss_cls: 2.3468, loss: 2.3468 +2025-05-06 01:30:10,483 - pyskl - INFO - Epoch [71][1100/1281] lr: 1.358e-02, eta: 18:07:32, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.9287, top5_acc: 1.0000, loss_cls: 2.3192, loss: 2.3192 +2025-05-06 01:31:16,001 - pyskl - INFO - Epoch [71][1200/1281] lr: 1.356e-02, eta: 18:06:29, time: 0.655, data_time: 0.000, memory: 9000, top1_acc: 0.9250, top5_acc: 1.0000, loss_cls: 2.3339, loss: 2.3339 +2025-05-06 01:32:07,824 - pyskl - INFO - Saving checkpoint at 71 epochs +2025-05-06 01:32:59,454 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 01:32:59,510 - pyskl - INFO - +top1_acc 0.8817 +top5_acc 0.9918 +2025-05-06 01:32:59,510 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 01:32:59,517 - pyskl - INFO - +mean_acc 0.8475 +2025-05-06 01:32:59,519 - pyskl - INFO - Epoch(val) [71][533] top1_acc: 0.8817, top5_acc: 0.9918, mean_class_accuracy: 0.8475 +2025-05-06 01:34:07,933 - pyskl - INFO - Epoch [72][100/1281] lr: 1.353e-02, eta: 18:03:39, time: 0.684, data_time: 0.182, memory: 9000, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 2.2764, loss: 2.2764 +2025-05-06 01:35:07,623 - pyskl - INFO - Epoch [72][200/1281] lr: 1.351e-02, eta: 18:02:29, time: 0.597, data_time: 0.000, memory: 9000, top1_acc: 0.9444, top5_acc: 1.0000, loss_cls: 2.1453, loss: 2.1453 +2025-05-06 01:36:13,063 - pyskl - INFO - Epoch [72][300/1281] lr: 1.349e-02, eta: 18:01:26, time: 0.654, data_time: 0.000, memory: 9000, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 2.1918, loss: 2.1918 +2025-05-06 01:37:18,919 - pyskl - INFO - Epoch [72][400/1281] lr: 1.346e-02, eta: 18:00:24, time: 0.659, data_time: 0.000, memory: 9000, top1_acc: 0.9387, top5_acc: 0.9994, loss_cls: 2.2761, loss: 2.2761 +2025-05-06 01:38:21,478 - pyskl - INFO - Epoch [72][500/1281] lr: 1.344e-02, eta: 17:59:17, time: 0.626, data_time: 0.000, memory: 9000, top1_acc: 0.9463, top5_acc: 0.9988, loss_cls: 2.2957, loss: 2.2957 +2025-05-06 01:39:20,877 - pyskl - INFO - Epoch [72][600/1281] lr: 1.342e-02, eta: 17:58:08, time: 0.594, data_time: 0.000, memory: 9000, top1_acc: 0.9413, top5_acc: 0.9994, loss_cls: 2.3442, loss: 2.3442 +2025-05-06 01:40:26,202 - pyskl - INFO - Epoch [72][700/1281] lr: 1.340e-02, eta: 17:57:04, time: 0.653, data_time: 0.000, memory: 9000, top1_acc: 0.9450, top5_acc: 0.9994, loss_cls: 2.3363, loss: 2.3363 +2025-05-06 01:41:32,844 - pyskl - INFO - Epoch [72][800/1281] lr: 1.338e-02, eta: 17:56:03, time: 0.666, data_time: 0.000, memory: 9000, top1_acc: 0.9513, top5_acc: 0.9988, loss_cls: 2.2179, loss: 2.2179 +2025-05-06 01:42:38,069 - pyskl - INFO - Epoch [72][900/1281] lr: 1.336e-02, eta: 17:54:59, time: 0.652, data_time: 0.000, memory: 9000, top1_acc: 0.9437, top5_acc: 0.9994, loss_cls: 2.2571, loss: 2.2571 +2025-05-06 01:43:39,100 - pyskl - INFO - Epoch [72][1000/1281] lr: 1.334e-02, eta: 17:53:52, time: 0.610, data_time: 0.000, memory: 9000, top1_acc: 0.9344, top5_acc: 0.9969, loss_cls: 2.3410, loss: 2.3410 +2025-05-06 01:44:43,439 - pyskl - INFO - Epoch [72][1100/1281] lr: 1.332e-02, eta: 17:52:47, time: 0.643, data_time: 0.000, memory: 9000, top1_acc: 0.9506, top5_acc: 0.9988, loss_cls: 2.2963, loss: 2.2963 +2025-05-06 01:45:49,995 - pyskl - INFO - Epoch [72][1200/1281] lr: 1.330e-02, eta: 17:51:45, time: 0.666, data_time: 0.000, memory: 9000, top1_acc: 0.9331, top5_acc: 0.9975, loss_cls: 2.3313, loss: 2.3313 +2025-05-06 01:46:43,877 - pyskl - INFO - Saving checkpoint at 72 epochs +2025-05-06 01:47:35,008 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 01:47:35,064 - pyskl - INFO - +top1_acc 0.8445 +top5_acc 0.9792 +2025-05-06 01:47:35,064 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 01:47:35,071 - pyskl - INFO - +mean_acc 0.8000 +2025-05-06 01:47:35,074 - pyskl - INFO - Epoch(val) [72][533] top1_acc: 0.8445, top5_acc: 0.9792, mean_class_accuracy: 0.8000 +2025-05-06 01:48:44,313 - pyskl - INFO - Epoch [73][100/1281] lr: 1.326e-02, eta: 17:48:58, time: 0.692, data_time: 0.181, memory: 9000, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 2.2337, loss: 2.2337 +2025-05-06 01:49:47,101 - pyskl - INFO - Epoch [73][200/1281] lr: 1.324e-02, eta: 17:47:52, time: 0.628, data_time: 0.000, memory: 9000, top1_acc: 0.9531, top5_acc: 0.9981, loss_cls: 2.1296, loss: 2.1296 +2025-05-06 01:50:53,005 - pyskl - INFO - Epoch [73][300/1281] lr: 1.322e-02, eta: 17:46:50, time: 0.659, data_time: 0.000, memory: 9000, top1_acc: 0.9456, top5_acc: 0.9988, loss_cls: 2.2748, loss: 2.2748 +2025-05-06 01:51:57,225 - pyskl - INFO - Epoch [73][400/1281] lr: 1.320e-02, eta: 17:45:45, time: 0.642, data_time: 0.000, memory: 9000, top1_acc: 0.9600, top5_acc: 0.9994, loss_cls: 2.1257, loss: 2.1257 +2025-05-06 01:52:57,834 - pyskl - INFO - Epoch [73][500/1281] lr: 1.318e-02, eta: 17:44:37, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9413, top5_acc: 0.9988, loss_cls: 2.1947, loss: 2.1947 +2025-05-06 01:54:01,989 - pyskl - INFO - Epoch [73][600/1281] lr: 1.316e-02, eta: 17:43:33, time: 0.642, data_time: 0.000, memory: 9000, top1_acc: 0.9500, top5_acc: 0.9981, loss_cls: 2.2342, loss: 2.2342 +2025-05-06 01:55:09,373 - pyskl - INFO - Epoch [73][700/1281] lr: 1.314e-02, eta: 17:42:32, time: 0.674, data_time: 0.000, memory: 9000, top1_acc: 0.9500, top5_acc: 0.9988, loss_cls: 2.3118, loss: 2.3118 +2025-05-06 01:56:13,744 - pyskl - INFO - Epoch [73][800/1281] lr: 1.312e-02, eta: 17:41:28, time: 0.644, data_time: 0.000, memory: 9000, top1_acc: 0.9387, top5_acc: 0.9994, loss_cls: 2.2967, loss: 2.2967 +2025-05-06 01:57:14,331 - pyskl - INFO - Epoch [73][900/1281] lr: 1.310e-02, eta: 17:40:20, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9437, top5_acc: 0.9988, loss_cls: 2.2417, loss: 2.2417 +2025-05-06 01:58:17,213 - pyskl - INFO - Epoch [73][1000/1281] lr: 1.308e-02, eta: 17:39:14, time: 0.629, data_time: 0.000, memory: 9000, top1_acc: 0.9363, top5_acc: 1.0000, loss_cls: 2.2825, loss: 2.2825 +2025-05-06 01:59:24,342 - pyskl - INFO - Epoch [73][1100/1281] lr: 1.306e-02, eta: 17:38:13, time: 0.671, data_time: 0.000, memory: 9000, top1_acc: 0.9300, top5_acc: 0.9994, loss_cls: 2.3423, loss: 2.3423 +2025-05-06 02:00:29,312 - pyskl - INFO - Epoch [73][1200/1281] lr: 1.304e-02, eta: 17:37:09, time: 0.650, data_time: 0.000, memory: 9000, top1_acc: 0.9294, top5_acc: 0.9975, loss_cls: 2.3746, loss: 2.3746 +2025-05-06 02:01:20,942 - pyskl - INFO - Saving checkpoint at 73 epochs +2025-05-06 02:02:10,446 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 02:02:10,504 - pyskl - INFO - +top1_acc 0.8882 +top5_acc 0.9928 +2025-05-06 02:02:10,505 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 02:02:10,514 - pyskl - INFO - +mean_acc 0.8547 +2025-05-06 02:02:10,572 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_59.pth was removed +2025-05-06 02:02:12,108 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_73.pth. +2025-05-06 02:02:12,108 - pyskl - INFO - Best top1_acc is 0.8882 at 73 epoch. +2025-05-06 02:02:12,112 - pyskl - INFO - Epoch(val) [73][533] top1_acc: 0.8882, top5_acc: 0.9928, mean_class_accuracy: 0.8547 +2025-05-06 02:03:23,598 - pyskl - INFO - Epoch [74][100/1281] lr: 1.300e-02, eta: 17:34:26, time: 0.715, data_time: 0.182, memory: 9000, top1_acc: 0.9544, top5_acc: 0.9981, loss_cls: 2.2135, loss: 2.2135 +2025-05-06 02:04:28,073 - pyskl - INFO - Epoch [74][200/1281] lr: 1.298e-02, eta: 17:33:22, time: 0.645, data_time: 0.000, memory: 9000, top1_acc: 0.9644, top5_acc: 0.9988, loss_cls: 2.0555, loss: 2.0555 +2025-05-06 02:05:32,070 - pyskl - INFO - Epoch [74][300/1281] lr: 1.296e-02, eta: 17:32:17, time: 0.640, data_time: 0.000, memory: 9000, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 2.1825, loss: 2.1825 +2025-05-06 02:06:33,087 - pyskl - INFO - Epoch [74][400/1281] lr: 1.294e-02, eta: 17:31:10, time: 0.610, data_time: 0.000, memory: 9000, top1_acc: 0.9413, top5_acc: 0.9994, loss_cls: 2.1644, loss: 2.1644 +2025-05-06 02:07:34,990 - pyskl - INFO - Epoch [74][500/1281] lr: 1.292e-02, eta: 17:30:03, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 2.2246, loss: 2.2246 +2025-05-06 02:08:42,343 - pyskl - INFO - Epoch [74][600/1281] lr: 1.290e-02, eta: 17:29:02, time: 0.674, data_time: 0.000, memory: 9000, top1_acc: 0.9356, top5_acc: 0.9981, loss_cls: 2.2229, loss: 2.2229 +2025-05-06 02:09:47,286 - pyskl - INFO - Epoch [74][700/1281] lr: 1.288e-02, eta: 17:27:59, time: 0.649, data_time: 0.000, memory: 9000, top1_acc: 0.9306, top5_acc: 0.9988, loss_cls: 2.4175, loss: 2.4175 +2025-05-06 02:10:48,169 - pyskl - INFO - Epoch [74][800/1281] lr: 1.286e-02, eta: 17:26:51, time: 0.609, data_time: 0.000, memory: 9000, top1_acc: 0.9306, top5_acc: 0.9956, loss_cls: 2.3186, loss: 2.3186 +2025-05-06 02:11:48,567 - pyskl - INFO - Epoch [74][900/1281] lr: 1.284e-02, eta: 17:25:43, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9344, top5_acc: 0.9994, loss_cls: 2.3025, loss: 2.3025 +2025-05-06 02:12:54,318 - pyskl - INFO - Epoch [74][1000/1281] lr: 1.282e-02, eta: 17:24:41, time: 0.658, data_time: 0.000, memory: 9000, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 2.2854, loss: 2.2854 +2025-05-06 02:14:01,593 - pyskl - INFO - Epoch [74][1100/1281] lr: 1.280e-02, eta: 17:23:40, time: 0.673, data_time: 0.000, memory: 9000, top1_acc: 0.9450, top5_acc: 0.9981, loss_cls: 2.3189, loss: 2.3189 +2025-05-06 02:15:05,920 - pyskl - INFO - Epoch [74][1200/1281] lr: 1.278e-02, eta: 17:22:35, time: 0.643, data_time: 0.000, memory: 9000, top1_acc: 0.9394, top5_acc: 1.0000, loss_cls: 2.2521, loss: 2.2521 +2025-05-06 02:15:56,560 - pyskl - INFO - Saving checkpoint at 74 epochs +2025-05-06 02:16:48,505 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 02:16:48,567 - pyskl - INFO - +top1_acc 0.8801 +top5_acc 0.9903 +2025-05-06 02:16:48,567 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 02:16:48,575 - pyskl - INFO - +mean_acc 0.8396 +2025-05-06 02:16:48,578 - pyskl - INFO - Epoch(val) [74][533] top1_acc: 0.8801, top5_acc: 0.9903, mean_class_accuracy: 0.8396 +2025-05-06 02:18:02,289 - pyskl - INFO - Epoch [75][100/1281] lr: 1.274e-02, eta: 17:19:56, time: 0.737, data_time: 0.179, memory: 9000, top1_acc: 0.9437, top5_acc: 1.0000, loss_cls: 2.3042, loss: 2.3042 +2025-05-06 02:19:06,252 - pyskl - INFO - Epoch [75][200/1281] lr: 1.272e-02, eta: 17:18:51, time: 0.640, data_time: 0.000, memory: 9000, top1_acc: 0.9575, top5_acc: 0.9994, loss_cls: 2.2228, loss: 2.2228 +2025-05-06 02:20:09,084 - pyskl - INFO - Epoch [75][300/1281] lr: 1.270e-02, eta: 17:17:46, time: 0.628, data_time: 0.000, memory: 9000, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 2.2509, loss: 2.2509 +2025-05-06 02:21:09,962 - pyskl - INFO - Epoch [75][400/1281] lr: 1.268e-02, eta: 17:16:38, time: 0.609, data_time: 0.000, memory: 9000, top1_acc: 0.9550, top5_acc: 0.9988, loss_cls: 2.1577, loss: 2.1577 +2025-05-06 02:22:16,398 - pyskl - INFO - Epoch [75][500/1281] lr: 1.266e-02, eta: 17:15:37, time: 0.664, data_time: 0.000, memory: 9000, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 2.2468, loss: 2.2468 +2025-05-06 02:23:22,681 - pyskl - INFO - Epoch [75][600/1281] lr: 1.264e-02, eta: 17:14:35, time: 0.663, data_time: 0.000, memory: 9000, top1_acc: 0.9450, top5_acc: 0.9981, loss_cls: 2.3175, loss: 2.3175 +2025-05-06 02:24:26,198 - pyskl - INFO - Epoch [75][700/1281] lr: 1.262e-02, eta: 17:13:30, time: 0.635, data_time: 0.000, memory: 9000, top1_acc: 0.9525, top5_acc: 0.9988, loss_cls: 2.1662, loss: 2.1662 +2025-05-06 02:25:26,093 - pyskl - INFO - Epoch [75][800/1281] lr: 1.260e-02, eta: 17:12:21, time: 0.599, data_time: 0.000, memory: 9000, top1_acc: 0.9431, top5_acc: 0.9981, loss_cls: 2.3048, loss: 2.3048 +2025-05-06 02:26:29,921 - pyskl - INFO - Epoch [75][900/1281] lr: 1.258e-02, eta: 17:11:17, time: 0.638, data_time: 0.000, memory: 9000, top1_acc: 0.9306, top5_acc: 0.9981, loss_cls: 2.3076, loss: 2.3076 +2025-05-06 02:27:38,885 - pyskl - INFO - Epoch [75][1000/1281] lr: 1.256e-02, eta: 17:10:17, time: 0.690, data_time: 0.000, memory: 9000, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 2.1960, loss: 2.1960 +2025-05-06 02:28:44,508 - pyskl - INFO - Epoch [75][1100/1281] lr: 1.254e-02, eta: 17:09:15, time: 0.656, data_time: 0.000, memory: 9000, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 2.1987, loss: 2.1987 +2025-05-06 02:29:46,798 - pyskl - INFO - Epoch [75][1200/1281] lr: 1.252e-02, eta: 17:08:09, time: 0.623, data_time: 0.000, memory: 9000, top1_acc: 0.9494, top5_acc: 1.0000, loss_cls: 2.2439, loss: 2.2439 +2025-05-06 02:30:36,861 - pyskl - INFO - Saving checkpoint at 75 epochs +2025-05-06 02:31:31,640 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 02:31:31,695 - pyskl - INFO - +top1_acc 0.8835 +top5_acc 0.9928 +2025-05-06 02:31:31,695 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 02:31:31,701 - pyskl - INFO - +mean_acc 0.8434 +2025-05-06 02:31:31,703 - pyskl - INFO - Epoch(val) [75][533] top1_acc: 0.8835, top5_acc: 0.9928, mean_class_accuracy: 0.8434 +2025-05-06 02:32:42,798 - pyskl - INFO - Epoch [76][100/1281] lr: 1.248e-02, eta: 17:05:28, time: 0.711, data_time: 0.181, memory: 9000, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 2.2363, loss: 2.2363 +2025-05-06 02:33:42,422 - pyskl - INFO - Epoch [76][200/1281] lr: 1.246e-02, eta: 17:04:19, time: 0.596, data_time: 0.000, memory: 9000, top1_acc: 0.9556, top5_acc: 0.9969, loss_cls: 2.1826, loss: 2.1826 +2025-05-06 02:34:42,643 - pyskl - INFO - Epoch [76][300/1281] lr: 1.244e-02, eta: 17:03:11, time: 0.602, data_time: 0.000, memory: 9000, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 2.1755, loss: 2.1755 +2025-05-06 02:35:44,576 - pyskl - INFO - Epoch [76][400/1281] lr: 1.242e-02, eta: 17:02:05, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 2.2122, loss: 2.2122 +2025-05-06 02:36:52,594 - pyskl - INFO - Epoch [76][500/1281] lr: 1.240e-02, eta: 17:01:05, time: 0.680, data_time: 0.000, memory: 9000, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 2.1279, loss: 2.1279 +2025-05-06 02:37:58,037 - pyskl - INFO - Epoch [76][600/1281] lr: 1.238e-02, eta: 17:00:02, time: 0.654, data_time: 0.000, memory: 9000, top1_acc: 0.9487, top5_acc: 0.9988, loss_cls: 2.1427, loss: 2.1427 +2025-05-06 02:39:00,099 - pyskl - INFO - Epoch [76][700/1281] lr: 1.236e-02, eta: 16:58:56, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.9500, top5_acc: 0.9988, loss_cls: 2.1603, loss: 2.1603 +2025-05-06 02:40:01,801 - pyskl - INFO - Epoch [76][800/1281] lr: 1.234e-02, eta: 16:57:49, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.9556, top5_acc: 0.9994, loss_cls: 2.1682, loss: 2.1682 +2025-05-06 02:41:09,907 - pyskl - INFO - Epoch [76][900/1281] lr: 1.232e-02, eta: 16:56:49, time: 0.681, data_time: 0.000, memory: 9000, top1_acc: 0.9469, top5_acc: 1.0000, loss_cls: 2.1856, loss: 2.1856 +2025-05-06 02:42:15,514 - pyskl - INFO - Epoch [76][1000/1281] lr: 1.230e-02, eta: 16:55:47, time: 0.656, data_time: 0.000, memory: 9000, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 2.1910, loss: 2.1910 +2025-05-06 02:43:19,602 - pyskl - INFO - Epoch [76][1100/1281] lr: 1.228e-02, eta: 16:54:42, time: 0.641, data_time: 0.000, memory: 9000, top1_acc: 0.9463, top5_acc: 0.9981, loss_cls: 2.2046, loss: 2.2046 +2025-05-06 02:44:20,891 - pyskl - INFO - Epoch [76][1200/1281] lr: 1.225e-02, eta: 16:53:36, time: 0.613, data_time: 0.000, memory: 9000, top1_acc: 0.9413, top5_acc: 0.9994, loss_cls: 2.2197, loss: 2.2197 +2025-05-06 02:45:12,701 - pyskl - INFO - Saving checkpoint at 76 epochs +2025-05-06 02:46:08,740 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 02:46:08,795 - pyskl - INFO - +top1_acc 0.8775 +top5_acc 0.9930 +2025-05-06 02:46:08,796 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 02:46:08,802 - pyskl - INFO - +mean_acc 0.8450 +2025-05-06 02:46:08,805 - pyskl - INFO - Epoch(val) [76][533] top1_acc: 0.8775, top5_acc: 0.9930, mean_class_accuracy: 0.8450 +2025-05-06 02:47:21,299 - pyskl - INFO - Epoch [77][100/1281] lr: 1.222e-02, eta: 16:50:57, time: 0.725, data_time: 0.178, memory: 9000, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 2.1842, loss: 2.1842 +2025-05-06 02:48:21,487 - pyskl - INFO - Epoch [77][200/1281] lr: 1.220e-02, eta: 16:49:49, time: 0.602, data_time: 0.000, memory: 9000, top1_acc: 0.9575, top5_acc: 0.9994, loss_cls: 2.1171, loss: 2.1171 +2025-05-06 02:49:22,510 - pyskl - INFO - Epoch [77][300/1281] lr: 1.218e-02, eta: 16:48:42, time: 0.610, data_time: 0.000, memory: 9000, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 2.0941, loss: 2.0941 +2025-05-06 02:50:30,164 - pyskl - INFO - Epoch [77][400/1281] lr: 1.216e-02, eta: 16:47:42, time: 0.677, data_time: 0.000, memory: 9000, top1_acc: 0.9556, top5_acc: 1.0000, loss_cls: 2.1543, loss: 2.1543 +2025-05-06 02:51:37,132 - pyskl - INFO - Epoch [77][500/1281] lr: 1.214e-02, eta: 16:46:41, time: 0.670, data_time: 0.000, memory: 9000, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 2.1208, loss: 2.1208 +2025-05-06 02:52:40,674 - pyskl - INFO - Epoch [77][600/1281] lr: 1.212e-02, eta: 16:45:36, time: 0.635, data_time: 0.000, memory: 9000, top1_acc: 0.9469, top5_acc: 0.9975, loss_cls: 2.2147, loss: 2.2147 +2025-05-06 02:53:41,363 - pyskl - INFO - Epoch [77][700/1281] lr: 1.210e-02, eta: 16:44:29, time: 0.607, data_time: 0.000, memory: 9000, top1_acc: 0.9469, top5_acc: 0.9988, loss_cls: 2.1635, loss: 2.1635 +2025-05-06 02:54:46,691 - pyskl - INFO - Epoch [77][800/1281] lr: 1.207e-02, eta: 16:43:26, time: 0.653, data_time: 0.000, memory: 9000, top1_acc: 0.9456, top5_acc: 0.9988, loss_cls: 2.2016, loss: 2.2016 +2025-05-06 02:55:55,592 - pyskl - INFO - Epoch [77][900/1281] lr: 1.205e-02, eta: 16:42:27, time: 0.689, data_time: 0.000, memory: 9000, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 2.1728, loss: 2.1728 +2025-05-06 02:57:00,252 - pyskl - INFO - Epoch [77][1000/1281] lr: 1.203e-02, eta: 16:41:23, time: 0.647, data_time: 0.000, memory: 9000, top1_acc: 0.9444, top5_acc: 1.0000, loss_cls: 2.2264, loss: 2.2264 +2025-05-06 02:58:01,273 - pyskl - INFO - Epoch [77][1100/1281] lr: 1.201e-02, eta: 16:40:16, time: 0.610, data_time: 0.000, memory: 9000, top1_acc: 0.9513, top5_acc: 0.9988, loss_cls: 2.1689, loss: 2.1689 +2025-05-06 02:59:03,524 - pyskl - INFO - Epoch [77][1200/1281] lr: 1.199e-02, eta: 16:39:10, time: 0.623, data_time: 0.000, memory: 9000, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 2.1836, loss: 2.1836 +2025-05-06 03:00:00,640 - pyskl - INFO - Saving checkpoint at 77 epochs +2025-05-06 03:00:54,785 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 03:00:54,841 - pyskl - INFO - +top1_acc 0.8742 +top5_acc 0.9892 +2025-05-06 03:00:54,841 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 03:00:54,849 - pyskl - INFO - +mean_acc 0.8361 +2025-05-06 03:00:54,852 - pyskl - INFO - Epoch(val) [77][533] top1_acc: 0.8742, top5_acc: 0.9892, mean_class_accuracy: 0.8361 +2025-05-06 03:02:04,917 - pyskl - INFO - Epoch [78][100/1281] lr: 1.196e-02, eta: 16:36:31, time: 0.701, data_time: 0.178, memory: 9000, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 2.1833, loss: 2.1833 +2025-05-06 03:03:02,231 - pyskl - INFO - Epoch [78][200/1281] lr: 1.194e-02, eta: 16:35:21, time: 0.573, data_time: 0.000, memory: 9000, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 2.2163, loss: 2.2163 +2025-05-06 03:04:07,492 - pyskl - INFO - Epoch [78][300/1281] lr: 1.192e-02, eta: 16:34:18, time: 0.653, data_time: 0.000, memory: 9000, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 2.0991, loss: 2.0991 +2025-05-06 03:05:20,128 - pyskl - INFO - Epoch [78][400/1281] lr: 1.190e-02, eta: 16:33:22, time: 0.726, data_time: 0.000, memory: 9000, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 2.1118, loss: 2.1118 +2025-05-06 03:06:24,099 - pyskl - INFO - Epoch [78][500/1281] lr: 1.187e-02, eta: 16:32:18, time: 0.640, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 1.0000, loss_cls: 2.1407, loss: 2.1407 +2025-05-06 03:07:24,752 - pyskl - INFO - Epoch [78][600/1281] lr: 1.185e-02, eta: 16:31:11, time: 0.607, data_time: 0.000, memory: 9000, top1_acc: 0.9469, top5_acc: 0.9994, loss_cls: 2.1752, loss: 2.1752 +2025-05-06 03:08:26,746 - pyskl - INFO - Epoch [78][700/1281] lr: 1.183e-02, eta: 16:30:05, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.9425, top5_acc: 1.0000, loss_cls: 2.2994, loss: 2.2994 +2025-05-06 03:09:39,622 - pyskl - INFO - Epoch [78][800/1281] lr: 1.181e-02, eta: 16:29:09, time: 0.729, data_time: 0.000, memory: 9000, top1_acc: 0.9525, top5_acc: 0.9988, loss_cls: 2.2171, loss: 2.2171 +2025-05-06 03:10:45,920 - pyskl - INFO - Epoch [78][900/1281] lr: 1.179e-02, eta: 16:28:07, time: 0.663, data_time: 0.000, memory: 9000, top1_acc: 0.9506, top5_acc: 1.0000, loss_cls: 2.1159, loss: 2.1159 +2025-05-06 03:11:46,894 - pyskl - INFO - Epoch [78][1000/1281] lr: 1.177e-02, eta: 16:27:00, time: 0.610, data_time: 0.000, memory: 9000, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 2.1918, loss: 2.1918 +2025-05-06 03:12:47,843 - pyskl - INFO - Epoch [78][1100/1281] lr: 1.175e-02, eta: 16:25:54, time: 0.609, data_time: 0.000, memory: 9000, top1_acc: 0.9400, top5_acc: 0.9994, loss_cls: 2.2596, loss: 2.2596 +2025-05-06 03:14:00,055 - pyskl - INFO - Epoch [78][1200/1281] lr: 1.173e-02, eta: 16:24:57, time: 0.722, data_time: 0.000, memory: 9000, top1_acc: 0.9394, top5_acc: 0.9981, loss_cls: 2.2312, loss: 2.2312 +2025-05-06 03:14:56,670 - pyskl - INFO - Saving checkpoint at 78 epochs +2025-05-06 03:15:48,594 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 03:15:48,648 - pyskl - INFO - +top1_acc 0.8825 +top5_acc 0.9920 +2025-05-06 03:15:48,649 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 03:15:48,655 - pyskl - INFO - +mean_acc 0.8415 +2025-05-06 03:15:48,658 - pyskl - INFO - Epoch(val) [78][533] top1_acc: 0.8825, top5_acc: 0.9920, mean_class_accuracy: 0.8415 +2025-05-06 03:16:55,689 - pyskl - INFO - Epoch [79][100/1281] lr: 1.169e-02, eta: 16:22:16, time: 0.670, data_time: 0.176, memory: 9000, top1_acc: 0.9544, top5_acc: 0.9975, loss_cls: 2.2331, loss: 2.2331 +2025-05-06 03:17:56,399 - pyskl - INFO - Epoch [79][200/1281] lr: 1.167e-02, eta: 16:21:09, time: 0.607, data_time: 0.000, memory: 9000, top1_acc: 0.9550, top5_acc: 0.9994, loss_cls: 2.1242, loss: 2.1242 +2025-05-06 03:19:10,335 - pyskl - INFO - Epoch [79][300/1281] lr: 1.165e-02, eta: 16:20:14, time: 0.739, data_time: 0.000, memory: 9000, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 2.1648, loss: 2.1648 +2025-05-06 03:20:14,646 - pyskl - INFO - Epoch [79][400/1281] lr: 1.163e-02, eta: 16:19:11, time: 0.643, data_time: 0.000, memory: 9000, top1_acc: 0.9600, top5_acc: 0.9994, loss_cls: 2.1351, loss: 2.1351 +2025-05-06 03:21:16,284 - pyskl - INFO - Epoch [79][500/1281] lr: 1.161e-02, eta: 16:18:05, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.9487, top5_acc: 0.9981, loss_cls: 2.2203, loss: 2.2203 +2025-05-06 03:22:18,264 - pyskl - INFO - Epoch [79][600/1281] lr: 1.159e-02, eta: 16:16:59, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.9494, top5_acc: 1.0000, loss_cls: 2.2068, loss: 2.2068 +2025-05-06 03:23:33,648 - pyskl - INFO - Epoch [79][700/1281] lr: 1.157e-02, eta: 16:16:05, time: 0.754, data_time: 0.000, memory: 9000, top1_acc: 0.9619, top5_acc: 0.9988, loss_cls: 2.1564, loss: 2.1564 +2025-05-06 03:24:39,211 - pyskl - INFO - Epoch [79][800/1281] lr: 1.155e-02, eta: 16:15:03, time: 0.656, data_time: 0.000, memory: 9000, top1_acc: 0.9637, top5_acc: 0.9994, loss_cls: 2.0720, loss: 2.0720 +2025-05-06 03:25:39,209 - pyskl - INFO - Epoch [79][900/1281] lr: 1.153e-02, eta: 16:13:55, time: 0.600, data_time: 0.000, memory: 9000, top1_acc: 0.9475, top5_acc: 0.9988, loss_cls: 2.1584, loss: 2.1584 +2025-05-06 03:26:39,052 - pyskl - INFO - Epoch [79][1000/1281] lr: 1.151e-02, eta: 16:12:47, time: 0.598, data_time: 0.000, memory: 9000, top1_acc: 0.9506, top5_acc: 1.0000, loss_cls: 2.1958, loss: 2.1958 +2025-05-06 03:27:50,382 - pyskl - INFO - Epoch [79][1100/1281] lr: 1.149e-02, eta: 16:11:50, time: 0.713, data_time: 0.000, memory: 9000, top1_acc: 0.9469, top5_acc: 0.9994, loss_cls: 2.2031, loss: 2.2031 +2025-05-06 03:29:00,567 - pyskl - INFO - Epoch [79][1200/1281] lr: 1.147e-02, eta: 16:10:52, time: 0.702, data_time: 0.000, memory: 9000, top1_acc: 0.9450, top5_acc: 1.0000, loss_cls: 2.2636, loss: 2.2636 +2025-05-06 03:29:50,839 - pyskl - INFO - Saving checkpoint at 79 epochs +2025-05-06 03:30:39,615 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 03:30:39,669 - pyskl - INFO - +top1_acc 0.8731 +top5_acc 0.9906 +2025-05-06 03:30:39,669 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 03:30:39,676 - pyskl - INFO - +mean_acc 0.8284 +2025-05-06 03:30:39,678 - pyskl - INFO - Epoch(val) [79][533] top1_acc: 0.8731, top5_acc: 0.9906, mean_class_accuracy: 0.8284 +2025-05-06 03:31:48,845 - pyskl - INFO - Epoch [80][100/1281] lr: 1.143e-02, eta: 16:08:14, time: 0.692, data_time: 0.178, memory: 9000, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 2.0691, loss: 2.0691 +2025-05-06 03:33:00,533 - pyskl - INFO - Epoch [80][200/1281] lr: 1.141e-02, eta: 16:07:17, time: 0.717, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 1.9763, loss: 1.9763 +2025-05-06 03:34:04,939 - pyskl - INFO - Epoch [80][300/1281] lr: 1.139e-02, eta: 16:06:13, time: 0.644, data_time: 0.000, memory: 9000, top1_acc: 0.9506, top5_acc: 1.0000, loss_cls: 2.1450, loss: 2.1450 +2025-05-06 03:35:05,089 - pyskl - INFO - Epoch [80][400/1281] lr: 1.137e-02, eta: 16:05:06, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.9544, top5_acc: 0.9988, loss_cls: 2.1414, loss: 2.1414 +2025-05-06 03:36:05,462 - pyskl - INFO - Epoch [80][500/1281] lr: 1.135e-02, eta: 16:03:59, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9494, top5_acc: 0.9988, loss_cls: 2.1543, loss: 2.1543 +2025-05-06 03:37:19,614 - pyskl - INFO - Epoch [80][600/1281] lr: 1.133e-02, eta: 16:03:04, time: 0.742, data_time: 0.000, memory: 9000, top1_acc: 0.9594, top5_acc: 0.9988, loss_cls: 2.1789, loss: 2.1789 +2025-05-06 03:38:28,635 - pyskl - INFO - Epoch [80][700/1281] lr: 1.131e-02, eta: 16:02:05, time: 0.690, data_time: 0.000, memory: 9000, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 2.1625, loss: 2.1625 +2025-05-06 03:39:29,753 - pyskl - INFO - Epoch [80][800/1281] lr: 1.129e-02, eta: 16:00:58, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9544, top5_acc: 0.9994, loss_cls: 2.0971, loss: 2.0971 +2025-05-06 03:40:30,030 - pyskl - INFO - Epoch [80][900/1281] lr: 1.127e-02, eta: 15:59:51, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 2.2337, loss: 2.2337 +2025-05-06 03:41:38,495 - pyskl - INFO - Epoch [80][1000/1281] lr: 1.125e-02, eta: 15:58:51, time: 0.685, data_time: 0.000, memory: 9000, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 2.1278, loss: 2.1278 +2025-05-06 03:42:51,939 - pyskl - INFO - Epoch [80][1100/1281] lr: 1.123e-02, eta: 15:57:55, time: 0.734, data_time: 0.000, memory: 9000, top1_acc: 0.9406, top5_acc: 0.9981, loss_cls: 2.2523, loss: 2.2523 +2025-05-06 03:43:53,271 - pyskl - INFO - Epoch [80][1200/1281] lr: 1.121e-02, eta: 15:56:49, time: 0.613, data_time: 0.000, memory: 9000, top1_acc: 0.9519, top5_acc: 1.0000, loss_cls: 2.1987, loss: 2.1987 +2025-05-06 03:44:42,892 - pyskl - INFO - Saving checkpoint at 80 epochs +2025-05-06 03:45:33,148 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 03:45:33,206 - pyskl - INFO - +top1_acc 0.8880 +top5_acc 0.9927 +2025-05-06 03:45:33,206 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 03:45:33,214 - pyskl - INFO - +mean_acc 0.8584 +2025-05-06 03:45:33,217 - pyskl - INFO - Epoch(val) [80][533] top1_acc: 0.8880, top5_acc: 0.9927, mean_class_accuracy: 0.8584 +2025-05-06 03:46:53,208 - pyskl - INFO - Epoch [81][100/1281] lr: 1.117e-02, eta: 15:54:22, time: 0.800, data_time: 0.181, memory: 9000, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 2.1485, loss: 2.1485 +2025-05-06 03:47:57,278 - pyskl - INFO - Epoch [81][200/1281] lr: 1.115e-02, eta: 15:53:18, time: 0.641, data_time: 0.000, memory: 9000, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 2.0107, loss: 2.0107 +2025-05-06 03:48:57,309 - pyskl - INFO - Epoch [81][300/1281] lr: 1.113e-02, eta: 15:52:11, time: 0.600, data_time: 0.000, memory: 9000, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 2.0227, loss: 2.0227 +2025-05-06 03:49:57,182 - pyskl - INFO - Epoch [81][400/1281] lr: 1.111e-02, eta: 15:51:03, time: 0.599, data_time: 0.000, memory: 9000, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 2.0842, loss: 2.0842 +2025-05-06 03:51:05,872 - pyskl - INFO - Epoch [81][500/1281] lr: 1.109e-02, eta: 15:50:04, time: 0.687, data_time: 0.000, memory: 9000, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 2.0013, loss: 2.0013 +2025-05-06 03:52:18,738 - pyskl - INFO - Epoch [81][600/1281] lr: 1.107e-02, eta: 15:49:07, time: 0.729, data_time: 0.000, memory: 9000, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 2.1313, loss: 2.1313 +2025-05-06 03:53:21,412 - pyskl - INFO - Epoch [81][700/1281] lr: 1.105e-02, eta: 15:48:02, time: 0.627, data_time: 0.000, memory: 9000, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 2.1406, loss: 2.1406 +2025-05-06 03:54:22,494 - pyskl - INFO - Epoch [81][800/1281] lr: 1.103e-02, eta: 15:46:56, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9463, top5_acc: 0.9988, loss_cls: 2.2437, loss: 2.2437 +2025-05-06 03:55:27,511 - pyskl - INFO - Epoch [81][900/1281] lr: 1.101e-02, eta: 15:45:53, time: 0.650, data_time: 0.000, memory: 9000, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 2.2474, loss: 2.2474 +2025-05-06 03:56:42,691 - pyskl - INFO - Epoch [81][1000/1281] lr: 1.099e-02, eta: 15:44:59, time: 0.752, data_time: 0.000, memory: 9000, top1_acc: 0.9594, top5_acc: 0.9994, loss_cls: 2.1558, loss: 2.1558 +2025-05-06 03:57:45,379 - pyskl - INFO - Epoch [81][1100/1281] lr: 1.097e-02, eta: 15:43:54, time: 0.627, data_time: 0.000, memory: 9000, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 2.0977, loss: 2.0977 +2025-05-06 03:58:45,816 - pyskl - INFO - Epoch [81][1200/1281] lr: 1.095e-02, eta: 15:42:47, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9381, top5_acc: 0.9994, loss_cls: 2.2489, loss: 2.2489 +2025-05-06 03:59:35,087 - pyskl - INFO - Saving checkpoint at 81 epochs +2025-05-06 04:00:32,354 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 04:00:32,409 - pyskl - INFO - +top1_acc 0.8625 +top5_acc 0.9908 +2025-05-06 04:00:32,410 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 04:00:32,416 - pyskl - INFO - +mean_acc 0.8304 +2025-05-06 04:00:32,419 - pyskl - INFO - Epoch(val) [81][533] top1_acc: 0.8625, top5_acc: 0.9908, mean_class_accuracy: 0.8304 +2025-05-06 04:01:49,368 - pyskl - INFO - Epoch [82][100/1281] lr: 1.091e-02, eta: 15:40:18, time: 0.769, data_time: 0.179, memory: 9000, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 2.1642, loss: 2.1642 +2025-05-06 04:02:50,033 - pyskl - INFO - Epoch [82][200/1281] lr: 1.089e-02, eta: 15:39:11, time: 0.607, data_time: 0.000, memory: 9000, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 2.0629, loss: 2.0629 +2025-05-06 04:03:49,268 - pyskl - INFO - Epoch [82][300/1281] lr: 1.087e-02, eta: 15:38:04, time: 0.592, data_time: 0.000, memory: 9000, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 2.1355, loss: 2.1355 +2025-05-06 04:04:54,186 - pyskl - INFO - Epoch [82][400/1281] lr: 1.085e-02, eta: 15:37:01, time: 0.649, data_time: 0.000, memory: 9000, top1_acc: 0.9475, top5_acc: 1.0000, loss_cls: 2.1968, loss: 2.1968 +2025-05-06 04:06:08,737 - pyskl - INFO - Epoch [82][500/1281] lr: 1.083e-02, eta: 15:36:06, time: 0.746, data_time: 0.000, memory: 9000, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 2.1210, loss: 2.1210 +2025-05-06 04:07:11,467 - pyskl - INFO - Epoch [82][600/1281] lr: 1.081e-02, eta: 15:35:01, time: 0.627, data_time: 0.000, memory: 9000, top1_acc: 0.9556, top5_acc: 1.0000, loss_cls: 2.0489, loss: 2.0489 +2025-05-06 04:08:10,842 - pyskl - INFO - Epoch [82][700/1281] lr: 1.079e-02, eta: 15:33:53, time: 0.594, data_time: 0.000, memory: 9000, top1_acc: 0.9550, top5_acc: 0.9988, loss_cls: 2.1712, loss: 2.1712 +2025-05-06 04:09:13,030 - pyskl - INFO - Epoch [82][800/1281] lr: 1.077e-02, eta: 15:32:48, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.9587, top5_acc: 0.9994, loss_cls: 2.0582, loss: 2.0582 +2025-05-06 04:10:26,854 - pyskl - INFO - Epoch [82][900/1281] lr: 1.075e-02, eta: 15:31:52, time: 0.738, data_time: 0.000, memory: 9000, top1_acc: 0.9613, top5_acc: 0.9994, loss_cls: 2.0130, loss: 2.0130 +2025-05-06 04:11:31,440 - pyskl - INFO - Epoch [82][1000/1281] lr: 1.073e-02, eta: 15:30:49, time: 0.646, data_time: 0.000, memory: 9000, top1_acc: 0.9519, top5_acc: 1.0000, loss_cls: 2.1702, loss: 2.1702 +2025-05-06 04:12:31,531 - pyskl - INFO - Epoch [82][1100/1281] lr: 1.071e-02, eta: 15:29:42, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 2.2358, loss: 2.2358 +2025-05-06 04:13:31,647 - pyskl - INFO - Epoch [82][1200/1281] lr: 1.069e-02, eta: 15:28:35, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 2.1658, loss: 2.1658 +2025-05-06 04:14:26,799 - pyskl - INFO - Saving checkpoint at 82 epochs +2025-05-06 04:15:25,218 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 04:15:25,273 - pyskl - INFO - +top1_acc 0.8801 +top5_acc 0.9912 +2025-05-06 04:15:25,273 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 04:15:25,279 - pyskl - INFO - +mean_acc 0.8500 +2025-05-06 04:15:25,282 - pyskl - INFO - Epoch(val) [82][533] top1_acc: 0.8801, top5_acc: 0.9912, mean_class_accuracy: 0.8500 +2025-05-06 04:16:34,967 - pyskl - INFO - Epoch [83][100/1281] lr: 1.065e-02, eta: 15:26:01, time: 0.697, data_time: 0.177, memory: 9000, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 2.1586, loss: 2.1586 +2025-05-06 04:17:33,320 - pyskl - INFO - Epoch [83][200/1281] lr: 1.063e-02, eta: 15:24:52, time: 0.584, data_time: 0.000, memory: 9000, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 2.0628, loss: 2.0628 +2025-05-06 04:18:33,894 - pyskl - INFO - Epoch [83][300/1281] lr: 1.061e-02, eta: 15:23:46, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 2.0058, loss: 2.0058 +2025-05-06 04:19:46,489 - pyskl - INFO - Epoch [83][400/1281] lr: 1.059e-02, eta: 15:22:49, time: 0.726, data_time: 0.000, memory: 9000, top1_acc: 0.9606, top5_acc: 0.9988, loss_cls: 2.1622, loss: 2.1622 +2025-05-06 04:20:51,352 - pyskl - INFO - Epoch [83][500/1281] lr: 1.057e-02, eta: 15:21:46, time: 0.649, data_time: 0.000, memory: 9000, top1_acc: 0.9456, top5_acc: 0.9981, loss_cls: 2.1844, loss: 2.1844 +2025-05-06 04:21:51,588 - pyskl - INFO - Epoch [83][600/1281] lr: 1.055e-02, eta: 15:20:39, time: 0.602, data_time: 0.000, memory: 9000, top1_acc: 0.9519, top5_acc: 0.9994, loss_cls: 2.1788, loss: 2.1788 +2025-05-06 04:22:51,396 - pyskl - INFO - Epoch [83][700/1281] lr: 1.053e-02, eta: 15:19:32, time: 0.598, data_time: 0.000, memory: 9000, top1_acc: 0.9613, top5_acc: 0.9994, loss_cls: 2.0777, loss: 2.0777 +2025-05-06 04:23:56,376 - pyskl - INFO - Epoch [83][800/1281] lr: 1.051e-02, eta: 15:18:29, time: 0.650, data_time: 0.000, memory: 9000, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 2.0737, loss: 2.0737 +2025-05-06 04:25:07,078 - pyskl - INFO - Epoch [83][900/1281] lr: 1.049e-02, eta: 15:17:31, time: 0.707, data_time: 0.000, memory: 9000, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 2.0663, loss: 2.0663 +2025-05-06 04:26:09,132 - pyskl - INFO - Epoch [83][1000/1281] lr: 1.047e-02, eta: 15:16:26, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 2.0811, loss: 2.0811 +2025-05-06 04:27:09,238 - pyskl - INFO - Epoch [83][1100/1281] lr: 1.045e-02, eta: 15:15:19, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 2.1471, loss: 2.1471 +2025-05-06 04:28:12,582 - pyskl - INFO - Epoch [83][1200/1281] lr: 1.043e-02, eta: 15:14:15, time: 0.633, data_time: 0.000, memory: 9000, top1_acc: 0.9519, top5_acc: 1.0000, loss_cls: 2.1850, loss: 2.1850 +2025-05-06 04:29:11,302 - pyskl - INFO - Saving checkpoint at 83 epochs +2025-05-06 04:30:04,172 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 04:30:04,227 - pyskl - INFO - +top1_acc 0.8868 +top5_acc 0.9925 +2025-05-06 04:30:04,227 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 04:30:04,234 - pyskl - INFO - +mean_acc 0.8592 +2025-05-06 04:30:04,236 - pyskl - INFO - Epoch(val) [83][533] top1_acc: 0.8868, top5_acc: 0.9925, mean_class_accuracy: 0.8592 +2025-05-06 04:31:12,696 - pyskl - INFO - Epoch [84][100/1281] lr: 1.040e-02, eta: 15:11:41, time: 0.685, data_time: 0.175, memory: 9000, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 2.1066, loss: 2.1066 +2025-05-06 04:32:11,692 - pyskl - INFO - Epoch [84][200/1281] lr: 1.038e-02, eta: 15:10:33, time: 0.590, data_time: 0.000, memory: 9000, top1_acc: 0.9475, top5_acc: 0.9988, loss_cls: 2.1364, loss: 2.1364 +2025-05-06 04:33:17,407 - pyskl - INFO - Epoch [84][300/1281] lr: 1.036e-02, eta: 15:09:31, time: 0.657, data_time: 0.000, memory: 9000, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 2.1711, loss: 2.1711 +2025-05-06 04:34:24,323 - pyskl - INFO - Epoch [84][400/1281] lr: 1.034e-02, eta: 15:08:30, time: 0.669, data_time: 0.000, memory: 9000, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 2.0482, loss: 2.0482 +2025-05-06 04:35:25,475 - pyskl - INFO - Epoch [84][500/1281] lr: 1.031e-02, eta: 15:07:24, time: 0.612, data_time: 0.000, memory: 9000, top1_acc: 0.9475, top5_acc: 1.0000, loss_cls: 2.1920, loss: 2.1920 +2025-05-06 04:36:26,617 - pyskl - INFO - Epoch [84][600/1281] lr: 1.029e-02, eta: 15:06:18, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9437, top5_acc: 1.0000, loss_cls: 2.3866, loss: 2.3866 +2025-05-06 04:37:29,151 - pyskl - INFO - Epoch [84][700/1281] lr: 1.027e-02, eta: 15:05:13, time: 0.625, data_time: 0.000, memory: 9000, top1_acc: 0.9531, top5_acc: 0.9981, loss_cls: 2.1587, loss: 2.1587 +2025-05-06 04:38:40,545 - pyskl - INFO - Epoch [84][800/1281] lr: 1.025e-02, eta: 15:04:15, time: 0.714, data_time: 0.000, memory: 9000, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 2.1728, loss: 2.1728 +2025-05-06 04:39:43,503 - pyskl - INFO - Epoch [84][900/1281] lr: 1.023e-02, eta: 15:03:11, time: 0.630, data_time: 0.000, memory: 9000, top1_acc: 0.9519, top5_acc: 0.9994, loss_cls: 2.1832, loss: 2.1832 +2025-05-06 04:40:42,650 - pyskl - INFO - Epoch [84][1000/1281] lr: 1.021e-02, eta: 15:02:03, time: 0.591, data_time: 0.000, memory: 9000, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 2.1871, loss: 2.1871 +2025-05-06 04:41:43,225 - pyskl - INFO - Epoch [84][1100/1281] lr: 1.019e-02, eta: 15:00:57, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 2.1564, loss: 2.1564 +2025-05-06 04:42:49,588 - pyskl - INFO - Epoch [84][1200/1281] lr: 1.017e-02, eta: 14:59:55, time: 0.664, data_time: 0.000, memory: 9000, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 2.0953, loss: 2.0953 +2025-05-06 04:43:44,854 - pyskl - INFO - Saving checkpoint at 84 epochs +2025-05-06 04:44:35,403 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 04:44:35,460 - pyskl - INFO - +top1_acc 0.8959 +top5_acc 0.9932 +2025-05-06 04:44:35,461 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 04:44:35,468 - pyskl - INFO - +mean_acc 0.8651 +2025-05-06 04:44:35,527 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_73.pth was removed +2025-05-06 04:44:37,046 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_84.pth. +2025-05-06 04:44:37,047 - pyskl - INFO - Best top1_acc is 0.8959 at 84 epoch. +2025-05-06 04:44:37,051 - pyskl - INFO - Epoch(val) [84][533] top1_acc: 0.8959, top5_acc: 0.9932, mean_class_accuracy: 0.8651 +2025-05-06 04:45:44,103 - pyskl - INFO - Epoch [85][100/1281] lr: 1.014e-02, eta: 14:57:22, time: 0.670, data_time: 0.180, memory: 9000, top1_acc: 0.9675, top5_acc: 0.9994, loss_cls: 2.1237, loss: 2.1237 +2025-05-06 04:46:43,238 - pyskl - INFO - Epoch [85][200/1281] lr: 1.012e-02, eta: 14:56:14, time: 0.591, data_time: 0.000, memory: 9000, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 2.0919, loss: 2.0919 +2025-05-06 04:47:48,874 - pyskl - INFO - Epoch [85][300/1281] lr: 1.010e-02, eta: 14:55:12, time: 0.656, data_time: 0.000, memory: 9000, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 2.0159, loss: 2.0159 +2025-05-06 04:48:52,421 - pyskl - INFO - Epoch [85][400/1281] lr: 1.008e-02, eta: 14:54:08, time: 0.635, data_time: 0.000, memory: 9000, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 2.0134, loss: 2.0134 +2025-05-06 04:49:52,669 - pyskl - INFO - Epoch [85][500/1281] lr: 1.006e-02, eta: 14:53:02, time: 0.602, data_time: 0.000, memory: 9000, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 2.0274, loss: 2.0274 +2025-05-06 04:50:53,475 - pyskl - INFO - Epoch [85][600/1281] lr: 1.004e-02, eta: 14:51:56, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 2.0328, loss: 2.0328 +2025-05-06 04:51:57,102 - pyskl - INFO - Epoch [85][700/1281] lr: 1.002e-02, eta: 14:50:52, time: 0.636, data_time: 0.000, memory: 9000, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 2.0492, loss: 2.0492 +2025-05-06 04:53:04,095 - pyskl - INFO - Epoch [85][800/1281] lr: 9.998e-03, eta: 14:49:50, time: 0.670, data_time: 0.000, memory: 9000, top1_acc: 0.9400, top5_acc: 0.9988, loss_cls: 2.1405, loss: 2.1405 +2025-05-06 04:54:05,175 - pyskl - INFO - Epoch [85][900/1281] lr: 9.978e-03, eta: 14:48:45, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 2.1587, loss: 2.1587 +2025-05-06 04:55:05,055 - pyskl - INFO - Epoch [85][1000/1281] lr: 9.958e-03, eta: 14:47:38, time: 0.599, data_time: 0.000, memory: 9000, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 2.1137, loss: 2.1137 +2025-05-06 04:56:08,121 - pyskl - INFO - Epoch [85][1100/1281] lr: 9.937e-03, eta: 14:46:34, time: 0.631, data_time: 0.000, memory: 9000, top1_acc: 0.9700, top5_acc: 0.9994, loss_cls: 2.0563, loss: 2.0563 +2025-05-06 04:57:15,939 - pyskl - INFO - Epoch [85][1200/1281] lr: 9.917e-03, eta: 14:45:33, time: 0.678, data_time: 0.000, memory: 9000, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 2.0441, loss: 2.0441 +2025-05-06 04:58:07,105 - pyskl - INFO - Saving checkpoint at 85 epochs +2025-05-06 04:58:56,310 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 04:58:56,364 - pyskl - INFO - +top1_acc 0.8889 +top5_acc 0.9925 +2025-05-06 04:58:56,365 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 04:58:56,371 - pyskl - INFO - +mean_acc 0.8579 +2025-05-06 04:58:56,373 - pyskl - INFO - Epoch(val) [85][533] top1_acc: 0.8889, top5_acc: 0.9925, mean_class_accuracy: 0.8579 +2025-05-06 05:00:04,631 - pyskl - INFO - Epoch [86][100/1281] lr: 9.881e-03, eta: 14:43:02, time: 0.683, data_time: 0.175, memory: 9000, top1_acc: 0.9469, top5_acc: 0.9994, loss_cls: 2.1308, loss: 2.1308 +2025-05-06 05:01:06,480 - pyskl - INFO - Epoch [86][200/1281] lr: 9.861e-03, eta: 14:41:57, time: 0.618, data_time: 0.000, memory: 9000, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 2.0377, loss: 2.0377 +2025-05-06 05:02:12,420 - pyskl - INFO - Epoch [86][300/1281] lr: 9.841e-03, eta: 14:40:55, time: 0.659, data_time: 0.000, memory: 9000, top1_acc: 0.9656, top5_acc: 0.9981, loss_cls: 2.0492, loss: 2.0492 +2025-05-06 05:03:14,355 - pyskl - INFO - Epoch [86][400/1281] lr: 9.821e-03, eta: 14:39:50, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 2.0352, loss: 2.0352 +2025-05-06 05:04:14,156 - pyskl - INFO - Epoch [86][500/1281] lr: 9.801e-03, eta: 14:38:43, time: 0.598, data_time: 0.000, memory: 9000, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 2.0845, loss: 2.0845 +2025-05-06 05:05:16,299 - pyskl - INFO - Epoch [86][600/1281] lr: 9.781e-03, eta: 14:37:38, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 1.9973, loss: 1.9973 +2025-05-06 05:06:20,240 - pyskl - INFO - Epoch [86][700/1281] lr: 9.762e-03, eta: 14:36:34, time: 0.639, data_time: 0.000, memory: 9000, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 2.0602, loss: 2.0602 +2025-05-06 05:07:25,574 - pyskl - INFO - Epoch [86][800/1281] lr: 9.742e-03, eta: 14:35:32, time: 0.653, data_time: 0.000, memory: 9000, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 2.0441, loss: 2.0441 +2025-05-06 05:08:25,870 - pyskl - INFO - Epoch [86][900/1281] lr: 9.722e-03, eta: 14:34:26, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 2.0064, loss: 2.0064 +2025-05-06 05:09:27,123 - pyskl - INFO - Epoch [86][1000/1281] lr: 9.702e-03, eta: 14:33:20, time: 0.613, data_time: 0.000, memory: 9000, top1_acc: 0.9581, top5_acc: 0.9981, loss_cls: 2.0499, loss: 2.0499 +2025-05-06 05:10:31,802 - pyskl - INFO - Epoch [86][1100/1281] lr: 9.682e-03, eta: 14:32:17, time: 0.647, data_time: 0.000, memory: 9000, top1_acc: 0.9537, top5_acc: 0.9975, loss_cls: 2.0868, loss: 2.0868 +2025-05-06 05:11:35,630 - pyskl - INFO - Epoch [86][1200/1281] lr: 9.662e-03, eta: 14:31:14, time: 0.638, data_time: 0.000, memory: 9000, top1_acc: 0.9525, top5_acc: 0.9988, loss_cls: 2.1168, loss: 2.1168 +2025-05-06 05:12:25,837 - pyskl - INFO - Saving checkpoint at 86 epochs +2025-05-06 05:13:15,284 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 05:13:15,339 - pyskl - INFO - +top1_acc 0.8868 +top5_acc 0.9933 +2025-05-06 05:13:15,339 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 05:13:15,345 - pyskl - INFO - +mean_acc 0.8536 +2025-05-06 05:13:15,347 - pyskl - INFO - Epoch(val) [86][533] top1_acc: 0.8868, top5_acc: 0.9933, mean_class_accuracy: 0.8536 +2025-05-06 05:14:24,694 - pyskl - INFO - Epoch [87][100/1281] lr: 9.626e-03, eta: 14:28:44, time: 0.693, data_time: 0.180, memory: 9000, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 2.0017, loss: 2.0017 +2025-05-06 05:15:26,864 - pyskl - INFO - Epoch [87][200/1281] lr: 9.606e-03, eta: 14:27:39, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.9712, top5_acc: 0.9994, loss_cls: 1.9889, loss: 1.9889 +2025-05-06 05:16:30,126 - pyskl - INFO - Epoch [87][300/1281] lr: 9.586e-03, eta: 14:26:35, time: 0.633, data_time: 0.000, memory: 9000, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 1.9586, loss: 1.9586 +2025-05-06 05:17:30,732 - pyskl - INFO - Epoch [87][400/1281] lr: 9.566e-03, eta: 14:25:30, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 2.1352, loss: 2.1352 +2025-05-06 05:18:30,746 - pyskl - INFO - Epoch [87][500/1281] lr: 9.546e-03, eta: 14:24:23, time: 0.600, data_time: 0.000, memory: 9000, top1_acc: 0.9688, top5_acc: 0.9994, loss_cls: 2.0707, loss: 2.0707 +2025-05-06 05:19:34,571 - pyskl - INFO - Epoch [87][600/1281] lr: 9.527e-03, eta: 14:23:20, time: 0.638, data_time: 0.000, memory: 9000, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 2.0218, loss: 2.0218 +2025-05-06 05:20:38,941 - pyskl - INFO - Epoch [87][700/1281] lr: 9.507e-03, eta: 14:22:17, time: 0.644, data_time: 0.000, memory: 9000, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 2.0237, loss: 2.0237 +2025-05-06 05:21:40,814 - pyskl - INFO - Epoch [87][800/1281] lr: 9.487e-03, eta: 14:21:12, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 1.9756, loss: 1.9756 +2025-05-06 05:22:40,325 - pyskl - INFO - Epoch [87][900/1281] lr: 9.467e-03, eta: 14:20:05, time: 0.595, data_time: 0.000, memory: 9000, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 2.0671, loss: 2.0671 +2025-05-06 05:23:42,829 - pyskl - INFO - Epoch [87][1000/1281] lr: 9.447e-03, eta: 14:19:01, time: 0.625, data_time: 0.000, memory: 9000, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 2.1888, loss: 2.1888 +2025-05-06 05:24:46,752 - pyskl - INFO - Epoch [87][1100/1281] lr: 9.427e-03, eta: 14:17:57, time: 0.639, data_time: 0.000, memory: 9000, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 2.1373, loss: 2.1373 +2025-05-06 05:25:49,846 - pyskl - INFO - Epoch [87][1200/1281] lr: 9.408e-03, eta: 14:16:53, time: 0.631, data_time: 0.000, memory: 9000, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 2.1476, loss: 2.1476 +2025-05-06 05:26:39,271 - pyskl - INFO - Saving checkpoint at 87 epochs +2025-05-06 05:27:28,306 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 05:27:28,359 - pyskl - INFO - +top1_acc 0.8951 +top5_acc 0.9913 +2025-05-06 05:27:28,359 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 05:27:28,365 - pyskl - INFO - +mean_acc 0.8670 +2025-05-06 05:27:28,367 - pyskl - INFO - Epoch(val) [87][533] top1_acc: 0.8951, top5_acc: 0.9913, mean_class_accuracy: 0.8670 +2025-05-06 05:28:38,805 - pyskl - INFO - Epoch [88][100/1281] lr: 9.372e-03, eta: 14:14:25, time: 0.704, data_time: 0.181, memory: 9000, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 2.0520, loss: 2.0520 +2025-05-06 05:29:42,014 - pyskl - INFO - Epoch [88][200/1281] lr: 9.352e-03, eta: 14:13:22, time: 0.632, data_time: 0.000, memory: 9000, top1_acc: 0.9744, top5_acc: 0.9994, loss_cls: 1.9778, loss: 1.9778 +2025-05-06 05:30:43,534 - pyskl - INFO - Epoch [88][300/1281] lr: 9.332e-03, eta: 14:12:16, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 1.9426, loss: 1.9426 +2025-05-06 05:31:43,220 - pyskl - INFO - Epoch [88][400/1281] lr: 9.312e-03, eta: 14:11:10, time: 0.597, data_time: 0.000, memory: 9000, top1_acc: 0.9769, top5_acc: 0.9994, loss_cls: 1.9879, loss: 1.9879 +2025-05-06 05:32:43,978 - pyskl - INFO - Epoch [88][500/1281] lr: 9.293e-03, eta: 14:10:04, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 2.0498, loss: 2.0498 +2025-05-06 05:33:51,457 - pyskl - INFO - Epoch [88][600/1281] lr: 9.273e-03, eta: 14:09:04, time: 0.675, data_time: 0.000, memory: 9000, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 2.0096, loss: 2.0096 +2025-05-06 05:34:57,711 - pyskl - INFO - Epoch [88][700/1281] lr: 9.253e-03, eta: 14:08:02, time: 0.663, data_time: 0.000, memory: 9000, top1_acc: 0.9637, top5_acc: 0.9994, loss_cls: 2.0161, loss: 2.0161 +2025-05-06 05:35:57,799 - pyskl - INFO - Epoch [88][800/1281] lr: 9.233e-03, eta: 14:06:56, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 2.0148, loss: 2.0148 +2025-05-06 05:36:58,145 - pyskl - INFO - Epoch [88][900/1281] lr: 9.214e-03, eta: 14:05:50, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 2.0052, loss: 2.0052 +2025-05-06 05:38:00,942 - pyskl - INFO - Epoch [88][1000/1281] lr: 9.194e-03, eta: 14:04:46, time: 0.628, data_time: 0.000, memory: 9000, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 2.1388, loss: 2.1388 +2025-05-06 05:39:03,363 - pyskl - INFO - Epoch [88][1100/1281] lr: 9.174e-03, eta: 14:03:41, time: 0.624, data_time: 0.000, memory: 9000, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 2.1155, loss: 2.1155 +2025-05-06 05:40:04,967 - pyskl - INFO - Epoch [88][1200/1281] lr: 9.155e-03, eta: 14:02:36, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 2.0739, loss: 2.0739 +2025-05-06 05:40:53,433 - pyskl - INFO - Saving checkpoint at 88 epochs +2025-05-06 05:41:44,351 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 05:41:44,410 - pyskl - INFO - +top1_acc 0.8885 +top5_acc 0.9938 +2025-05-06 05:41:44,411 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 05:41:44,419 - pyskl - INFO - +mean_acc 0.8602 +2025-05-06 05:41:44,422 - pyskl - INFO - Epoch(val) [88][533] top1_acc: 0.8885, top5_acc: 0.9938, mean_class_accuracy: 0.8602 +2025-05-06 05:42:56,281 - pyskl - INFO - Epoch [89][100/1281] lr: 9.119e-03, eta: 14:00:11, time: 0.719, data_time: 0.185, memory: 9000, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 1.9583, loss: 1.9583 +2025-05-06 05:43:56,758 - pyskl - INFO - Epoch [89][200/1281] lr: 9.099e-03, eta: 13:59:05, time: 0.605, data_time: 0.000, memory: 9000, top1_acc: 0.9637, top5_acc: 0.9994, loss_cls: 2.0170, loss: 2.0170 +2025-05-06 05:44:57,952 - pyskl - INFO - Epoch [89][300/1281] lr: 9.080e-03, eta: 13:58:00, time: 0.612, data_time: 0.000, memory: 9000, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 2.0039, loss: 2.0039 +2025-05-06 05:45:57,561 - pyskl - INFO - Epoch [89][400/1281] lr: 9.060e-03, eta: 13:56:54, time: 0.596, data_time: 0.000, memory: 9000, top1_acc: 0.9637, top5_acc: 0.9994, loss_cls: 2.0707, loss: 2.0707 +2025-05-06 05:47:00,396 - pyskl - INFO - Epoch [89][500/1281] lr: 9.040e-03, eta: 13:55:50, time: 0.628, data_time: 0.000, memory: 9000, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 1.9863, loss: 1.9863 +2025-05-06 05:48:05,963 - pyskl - INFO - Epoch [89][600/1281] lr: 9.021e-03, eta: 13:54:47, time: 0.656, data_time: 0.000, memory: 9000, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 1.9833, loss: 1.9833 +2025-05-06 05:49:09,413 - pyskl - INFO - Epoch [89][700/1281] lr: 9.001e-03, eta: 13:53:44, time: 0.634, data_time: 0.000, memory: 9000, top1_acc: 0.9656, top5_acc: 0.9994, loss_cls: 1.9017, loss: 1.9017 +2025-05-06 05:50:09,653 - pyskl - INFO - Epoch [89][800/1281] lr: 8.982e-03, eta: 13:52:38, time: 0.602, data_time: 0.000, memory: 9000, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 2.0150, loss: 2.0150 +2025-05-06 05:51:10,094 - pyskl - INFO - Epoch [89][900/1281] lr: 8.962e-03, eta: 13:51:32, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9656, top5_acc: 0.9994, loss_cls: 2.0587, loss: 2.0587 +2025-05-06 05:52:15,700 - pyskl - INFO - Epoch [89][1000/1281] lr: 8.942e-03, eta: 13:50:30, time: 0.656, data_time: 0.000, memory: 9000, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 2.0200, loss: 2.0200 +2025-05-06 05:53:19,851 - pyskl - INFO - Epoch [89][1100/1281] lr: 8.923e-03, eta: 13:49:27, time: 0.641, data_time: 0.000, memory: 9000, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 2.0122, loss: 2.0122 +2025-05-06 05:54:20,183 - pyskl - INFO - Epoch [89][1200/1281] lr: 8.903e-03, eta: 13:48:21, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 2.0600, loss: 2.0600 +2025-05-06 05:55:09,177 - pyskl - INFO - Saving checkpoint at 89 epochs +2025-05-06 05:56:00,791 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 05:56:00,848 - pyskl - INFO - +top1_acc 0.8879 +top5_acc 0.9916 +2025-05-06 05:56:00,848 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 05:56:00,856 - pyskl - INFO - +mean_acc 0.8610 +2025-05-06 05:56:00,860 - pyskl - INFO - Epoch(val) [89][533] top1_acc: 0.8879, top5_acc: 0.9916, mean_class_accuracy: 0.8610 +2025-05-06 05:57:12,321 - pyskl - INFO - Epoch [90][100/1281] lr: 8.868e-03, eta: 13:45:57, time: 0.715, data_time: 0.179, memory: 9000, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 2.0628, loss: 2.0628 +2025-05-06 05:58:14,530 - pyskl - INFO - Epoch [90][200/1281] lr: 8.848e-03, eta: 13:44:52, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 1.9141, loss: 1.9141 +2025-05-06 05:59:15,337 - pyskl - INFO - Epoch [90][300/1281] lr: 8.829e-03, eta: 13:43:47, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 1.9617, loss: 1.9617 +2025-05-06 06:00:16,697 - pyskl - INFO - Epoch [90][400/1281] lr: 8.809e-03, eta: 13:42:42, time: 0.614, data_time: 0.000, memory: 9000, top1_acc: 0.9756, top5_acc: 0.9994, loss_cls: 1.9691, loss: 1.9691 +2025-05-06 06:01:20,281 - pyskl - INFO - Epoch [90][500/1281] lr: 8.790e-03, eta: 13:41:38, time: 0.636, data_time: 0.000, memory: 9000, top1_acc: 0.9744, top5_acc: 0.9994, loss_cls: 1.8794, loss: 1.8794 +2025-05-06 06:02:24,025 - pyskl - INFO - Epoch [90][600/1281] lr: 8.770e-03, eta: 13:40:35, time: 0.637, data_time: 0.000, memory: 9000, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 1.8939, loss: 1.8939 +2025-05-06 06:03:26,242 - pyskl - INFO - Epoch [90][700/1281] lr: 8.751e-03, eta: 13:39:31, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 1.9963, loss: 1.9963 +2025-05-06 06:04:25,683 - pyskl - INFO - Epoch [90][800/1281] lr: 8.731e-03, eta: 13:38:25, time: 0.594, data_time: 0.000, memory: 9000, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 2.0025, loss: 2.0025 +2025-05-06 06:05:29,255 - pyskl - INFO - Epoch [90][900/1281] lr: 8.712e-03, eta: 13:37:21, time: 0.636, data_time: 0.000, memory: 9000, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 1.9844, loss: 1.9844 +2025-05-06 06:06:38,354 - pyskl - INFO - Epoch [90][1000/1281] lr: 8.692e-03, eta: 13:36:21, time: 0.691, data_time: 0.000, memory: 9000, top1_acc: 0.9681, top5_acc: 0.9994, loss_cls: 1.9946, loss: 1.9946 +2025-05-06 06:07:43,379 - pyskl - INFO - Epoch [90][1100/1281] lr: 8.673e-03, eta: 13:35:19, time: 0.650, data_time: 0.000, memory: 9000, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 1.9944, loss: 1.9944 +2025-05-06 06:08:43,368 - pyskl - INFO - Epoch [90][1200/1281] lr: 8.653e-03, eta: 13:34:13, time: 0.600, data_time: 0.000, memory: 9000, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 2.0885, loss: 2.0885 +2025-05-06 06:09:32,011 - pyskl - INFO - Saving checkpoint at 90 epochs +2025-05-06 06:10:26,152 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 06:10:26,207 - pyskl - INFO - +top1_acc 0.8858 +top5_acc 0.9910 +2025-05-06 06:10:26,207 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 06:10:26,214 - pyskl - INFO - +mean_acc 0.8552 +2025-05-06 06:10:26,216 - pyskl - INFO - Epoch(val) [90][533] top1_acc: 0.8858, top5_acc: 0.9910, mean_class_accuracy: 0.8552 +2025-05-06 06:11:39,682 - pyskl - INFO - Epoch [91][100/1281] lr: 8.618e-03, eta: 13:31:51, time: 0.735, data_time: 0.180, memory: 9000, top1_acc: 0.9738, top5_acc: 0.9994, loss_cls: 1.9918, loss: 1.9918 +2025-05-06 06:12:41,182 - pyskl - INFO - Epoch [91][200/1281] lr: 8.599e-03, eta: 13:30:46, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 2.0029, loss: 2.0029 +2025-05-06 06:13:40,851 - pyskl - INFO - Epoch [91][300/1281] lr: 8.579e-03, eta: 13:29:40, time: 0.597, data_time: 0.000, memory: 9000, top1_acc: 0.9750, top5_acc: 0.9994, loss_cls: 1.9460, loss: 1.9460 +2025-05-06 06:14:41,281 - pyskl - INFO - Epoch [91][400/1281] lr: 8.560e-03, eta: 13:28:34, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9669, top5_acc: 0.9988, loss_cls: 2.0088, loss: 2.0088 +2025-05-06 06:15:43,096 - pyskl - INFO - Epoch [91][500/1281] lr: 8.540e-03, eta: 13:27:30, time: 0.618, data_time: 0.000, memory: 9000, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 1.8958, loss: 1.8958 +2025-05-06 06:16:43,726 - pyskl - INFO - Epoch [91][600/1281] lr: 8.521e-03, eta: 13:26:25, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 2.0392, loss: 2.0392 +2025-05-06 06:17:42,197 - pyskl - INFO - Epoch [91][700/1281] lr: 8.502e-03, eta: 13:25:18, time: 0.585, data_time: 0.000, memory: 9000, top1_acc: 0.9637, top5_acc: 0.9994, loss_cls: 2.0150, loss: 2.0150 +2025-05-06 06:18:43,136 - pyskl - INFO - Epoch [91][800/1281] lr: 8.482e-03, eta: 13:24:13, time: 0.609, data_time: 0.000, memory: 9000, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 2.0693, loss: 2.0693 +2025-05-06 06:19:49,104 - pyskl - INFO - Epoch [91][900/1281] lr: 8.463e-03, eta: 13:23:11, time: 0.660, data_time: 0.000, memory: 9000, top1_acc: 0.9637, top5_acc: 0.9994, loss_cls: 2.0208, loss: 2.0208 +2025-05-06 06:20:55,748 - pyskl - INFO - Epoch [91][1000/1281] lr: 8.444e-03, eta: 13:22:10, time: 0.666, data_time: 0.000, memory: 9000, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 2.0615, loss: 2.0615 +2025-05-06 06:21:58,705 - pyskl - INFO - Epoch [91][1100/1281] lr: 8.424e-03, eta: 13:21:06, time: 0.630, data_time: 0.000, memory: 9000, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 2.0931, loss: 2.0931 +2025-05-06 06:22:59,178 - pyskl - INFO - Epoch [91][1200/1281] lr: 8.405e-03, eta: 13:20:00, time: 0.605, data_time: 0.000, memory: 9000, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 2.1190, loss: 2.1190 +2025-05-06 06:23:50,547 - pyskl - INFO - Saving checkpoint at 91 epochs +2025-05-06 06:24:46,154 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 06:24:46,209 - pyskl - INFO - +top1_acc 0.8863 +top5_acc 0.9914 +2025-05-06 06:24:46,209 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 06:24:46,215 - pyskl - INFO - +mean_acc 0.8547 +2025-05-06 06:24:46,218 - pyskl - INFO - Epoch(val) [91][533] top1_acc: 0.8863, top5_acc: 0.9914, mean_class_accuracy: 0.8547 +2025-05-06 06:25:59,497 - pyskl - INFO - Epoch [92][100/1281] lr: 8.370e-03, eta: 13:17:39, time: 0.733, data_time: 0.179, memory: 9000, top1_acc: 0.9712, top5_acc: 0.9994, loss_cls: 2.0567, loss: 2.0567 +2025-05-06 06:26:58,619 - pyskl - INFO - Epoch [92][200/1281] lr: 8.351e-03, eta: 13:16:33, time: 0.591, data_time: 0.000, memory: 9000, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 1.9457, loss: 1.9457 +2025-05-06 06:27:58,038 - pyskl - INFO - Epoch [92][300/1281] lr: 8.332e-03, eta: 13:15:27, time: 0.594, data_time: 0.000, memory: 9000, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 1.9377, loss: 1.9377 +2025-05-06 06:29:01,766 - pyskl - INFO - Epoch [92][400/1281] lr: 8.312e-03, eta: 13:14:23, time: 0.637, data_time: 0.000, memory: 9000, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 1.8786, loss: 1.8786 +2025-05-06 06:30:07,849 - pyskl - INFO - Epoch [92][500/1281] lr: 8.293e-03, eta: 13:13:22, time: 0.661, data_time: 0.000, memory: 9000, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 1.8861, loss: 1.8861 +2025-05-06 06:31:10,332 - pyskl - INFO - Epoch [92][600/1281] lr: 8.274e-03, eta: 13:12:18, time: 0.625, data_time: 0.000, memory: 9000, top1_acc: 0.9719, top5_acc: 0.9994, loss_cls: 1.8873, loss: 1.8873 +2025-05-06 06:32:09,423 - pyskl - INFO - Epoch [92][700/1281] lr: 8.255e-03, eta: 13:11:12, time: 0.591, data_time: 0.000, memory: 9000, top1_acc: 0.9706, top5_acc: 0.9994, loss_cls: 2.0418, loss: 2.0418 +2025-05-06 06:33:12,035 - pyskl - INFO - Epoch [92][800/1281] lr: 8.235e-03, eta: 13:10:08, time: 0.626, data_time: 0.000, memory: 9000, top1_acc: 0.9675, top5_acc: 0.9994, loss_cls: 1.9606, loss: 1.9606 +2025-05-06 06:34:21,011 - pyskl - INFO - Epoch [92][900/1281] lr: 8.216e-03, eta: 13:09:08, time: 0.690, data_time: 0.000, memory: 9000, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 2.0203, loss: 2.0203 +2025-05-06 06:35:25,826 - pyskl - INFO - Epoch [92][1000/1281] lr: 8.197e-03, eta: 13:08:05, time: 0.648, data_time: 0.000, memory: 9000, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 2.0084, loss: 2.0084 +2025-05-06 06:36:27,342 - pyskl - INFO - Epoch [92][1100/1281] lr: 8.178e-03, eta: 13:07:01, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 1.9836, loss: 1.9836 +2025-05-06 06:37:28,199 - pyskl - INFO - Epoch [92][1200/1281] lr: 8.159e-03, eta: 13:05:56, time: 0.609, data_time: 0.000, memory: 9000, top1_acc: 0.9781, top5_acc: 0.9994, loss_cls: 1.8882, loss: 1.8882 +2025-05-06 06:38:20,904 - pyskl - INFO - Saving checkpoint at 92 epochs +2025-05-06 06:39:14,226 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 06:39:14,282 - pyskl - INFO - +top1_acc 0.8945 +top5_acc 0.9925 +2025-05-06 06:39:14,282 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 06:39:14,289 - pyskl - INFO - +mean_acc 0.8601 +2025-05-06 06:39:14,291 - pyskl - INFO - Epoch(val) [92][533] top1_acc: 0.8945, top5_acc: 0.9925, mean_class_accuracy: 0.8601 +2025-05-06 06:40:24,197 - pyskl - INFO - Epoch [93][100/1281] lr: 8.124e-03, eta: 13:03:33, time: 0.699, data_time: 0.179, memory: 9000, top1_acc: 0.9731, top5_acc: 0.9994, loss_cls: 1.9331, loss: 1.9331 +2025-05-06 06:41:22,466 - pyskl - INFO - Epoch [93][200/1281] lr: 8.105e-03, eta: 13:02:26, time: 0.583, data_time: 0.000, memory: 9000, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 1.8875, loss: 1.8875 +2025-05-06 06:42:24,143 - pyskl - INFO - Epoch [93][300/1281] lr: 8.086e-03, eta: 13:01:22, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 1.9232, loss: 1.9232 +2025-05-06 06:43:31,074 - pyskl - INFO - Epoch [93][400/1281] lr: 8.067e-03, eta: 13:00:21, time: 0.669, data_time: 0.000, memory: 9000, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 1.8503, loss: 1.8503 +2025-05-06 06:44:37,144 - pyskl - INFO - Epoch [93][500/1281] lr: 8.047e-03, eta: 12:59:19, time: 0.661, data_time: 0.000, memory: 9000, top1_acc: 0.9694, top5_acc: 0.9994, loss_cls: 2.0480, loss: 2.0480 +2025-05-06 06:45:37,175 - pyskl - INFO - Epoch [93][600/1281] lr: 8.028e-03, eta: 12:58:14, time: 0.600, data_time: 0.000, memory: 9000, top1_acc: 0.9756, top5_acc: 0.9994, loss_cls: 1.9121, loss: 1.9121 +2025-05-06 06:46:37,260 - pyskl - INFO - Epoch [93][700/1281] lr: 8.009e-03, eta: 12:57:08, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 1.8880, loss: 1.8880 +2025-05-06 06:47:44,804 - pyskl - INFO - Epoch [93][800/1281] lr: 7.990e-03, eta: 12:56:07, time: 0.675, data_time: 0.000, memory: 9000, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 1.9403, loss: 1.9403 +2025-05-06 06:48:52,514 - pyskl - INFO - Epoch [93][900/1281] lr: 7.971e-03, eta: 12:55:07, time: 0.677, data_time: 0.000, memory: 9000, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 2.0106, loss: 2.0106 +2025-05-06 06:49:55,410 - pyskl - INFO - Epoch [93][1000/1281] lr: 7.952e-03, eta: 12:54:03, time: 0.629, data_time: 0.000, memory: 9000, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 1.9462, loss: 1.9462 +2025-05-06 06:50:54,611 - pyskl - INFO - Epoch [93][1100/1281] lr: 7.933e-03, eta: 12:52:57, time: 0.592, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 1.9370, loss: 1.9370 +2025-05-06 06:51:59,563 - pyskl - INFO - Epoch [93][1200/1281] lr: 7.914e-03, eta: 12:51:55, time: 0.650, data_time: 0.000, memory: 9000, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 2.0515, loss: 2.0515 +2025-05-06 06:52:56,116 - pyskl - INFO - Saving checkpoint at 93 epochs +2025-05-06 06:53:49,296 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 06:53:49,349 - pyskl - INFO - +top1_acc 0.9010 +top5_acc 0.9944 +2025-05-06 06:53:49,350 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 06:53:49,356 - pyskl - INFO - +mean_acc 0.8728 +2025-05-06 06:53:49,414 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_84.pth was removed +2025-05-06 06:53:50,953 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_93.pth. +2025-05-06 06:53:50,954 - pyskl - INFO - Best top1_acc is 0.9010 at 93 epoch. +2025-05-06 06:53:50,958 - pyskl - INFO - Epoch(val) [93][533] top1_acc: 0.9010, top5_acc: 0.9944, mean_class_accuracy: 0.8728 +2025-05-06 06:54:59,840 - pyskl - INFO - Epoch [94][100/1281] lr: 7.880e-03, eta: 12:49:32, time: 0.689, data_time: 0.181, memory: 9000, top1_acc: 0.9775, top5_acc: 0.9988, loss_cls: 1.9372, loss: 1.9372 +2025-05-06 06:55:58,113 - pyskl - INFO - Epoch [94][200/1281] lr: 7.861e-03, eta: 12:48:26, time: 0.583, data_time: 0.000, memory: 9000, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 1.9280, loss: 1.9280 +2025-05-06 06:57:04,946 - pyskl - INFO - Epoch [94][300/1281] lr: 7.842e-03, eta: 12:47:24, time: 0.668, data_time: 0.000, memory: 9000, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 1.8779, loss: 1.8779 +2025-05-06 06:58:11,800 - pyskl - INFO - Epoch [94][400/1281] lr: 7.823e-03, eta: 12:46:23, time: 0.669, data_time: 0.000, memory: 9000, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 1.8905, loss: 1.8905 +2025-05-06 06:59:15,656 - pyskl - INFO - Epoch [94][500/1281] lr: 7.804e-03, eta: 12:45:20, time: 0.639, data_time: 0.000, memory: 9000, top1_acc: 0.9744, top5_acc: 0.9994, loss_cls: 1.9927, loss: 1.9927 +2025-05-06 07:00:15,708 - pyskl - INFO - Epoch [94][600/1281] lr: 7.785e-03, eta: 12:44:15, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 2.0181, loss: 2.0181 +2025-05-06 07:01:19,942 - pyskl - INFO - Epoch [94][700/1281] lr: 7.766e-03, eta: 12:43:12, time: 0.642, data_time: 0.000, memory: 9000, top1_acc: 0.9637, top5_acc: 0.9994, loss_cls: 1.9884, loss: 1.9884 +2025-05-06 07:02:29,818 - pyskl - INFO - Epoch [94][800/1281] lr: 7.747e-03, eta: 12:42:13, time: 0.699, data_time: 0.000, memory: 9000, top1_acc: 0.9788, top5_acc: 0.9994, loss_cls: 1.9162, loss: 1.9162 +2025-05-06 07:03:33,850 - pyskl - INFO - Epoch [94][900/1281] lr: 7.728e-03, eta: 12:41:10, time: 0.640, data_time: 0.000, memory: 9000, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 1.9683, loss: 1.9683 +2025-05-06 07:04:33,990 - pyskl - INFO - Epoch [94][1000/1281] lr: 7.709e-03, eta: 12:40:05, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 2.0831, loss: 2.0831 +2025-05-06 07:05:37,185 - pyskl - INFO - Epoch [94][1100/1281] lr: 7.690e-03, eta: 12:39:01, time: 0.632, data_time: 0.000, memory: 9000, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 2.0104, loss: 2.0104 +2025-05-06 07:06:46,482 - pyskl - INFO - Epoch [94][1200/1281] lr: 7.672e-03, eta: 12:38:02, time: 0.693, data_time: 0.000, memory: 9000, top1_acc: 0.9675, top5_acc: 0.9994, loss_cls: 2.0399, loss: 2.0399 +2025-05-06 07:07:41,614 - pyskl - INFO - Saving checkpoint at 94 epochs +2025-05-06 07:08:32,654 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 07:08:32,710 - pyskl - INFO - +top1_acc 0.9083 +top5_acc 0.9941 +2025-05-06 07:08:32,710 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 07:08:32,718 - pyskl - INFO - +mean_acc 0.8788 +2025-05-06 07:08:32,775 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_93.pth was removed +2025-05-06 07:08:34,311 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_94.pth. +2025-05-06 07:08:34,312 - pyskl - INFO - Best top1_acc is 0.9083 at 94 epoch. +2025-05-06 07:08:34,316 - pyskl - INFO - Epoch(val) [94][533] top1_acc: 0.9083, top5_acc: 0.9941, mean_class_accuracy: 0.8788 +2025-05-06 07:09:40,607 - pyskl - INFO - Epoch [95][100/1281] lr: 7.637e-03, eta: 12:35:38, time: 0.663, data_time: 0.179, memory: 9000, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 1.9122, loss: 1.9122 +2025-05-06 07:10:41,783 - pyskl - INFO - Epoch [95][200/1281] lr: 7.619e-03, eta: 12:34:34, time: 0.612, data_time: 0.000, memory: 9000, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 1.8996, loss: 1.8996 +2025-05-06 07:11:49,553 - pyskl - INFO - Epoch [95][300/1281] lr: 7.600e-03, eta: 12:33:33, time: 0.678, data_time: 0.000, memory: 9000, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 1.9304, loss: 1.9304 +2025-05-06 07:12:52,301 - pyskl - INFO - Epoch [95][400/1281] lr: 7.581e-03, eta: 12:32:29, time: 0.627, data_time: 0.000, memory: 9000, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 1.9009, loss: 1.9009 +2025-05-06 07:13:51,628 - pyskl - INFO - Epoch [95][500/1281] lr: 7.562e-03, eta: 12:31:24, time: 0.593, data_time: 0.000, memory: 9000, top1_acc: 0.9762, top5_acc: 0.9994, loss_cls: 1.9067, loss: 1.9067 +2025-05-06 07:14:54,019 - pyskl - INFO - Epoch [95][600/1281] lr: 7.543e-03, eta: 12:30:20, time: 0.624, data_time: 0.000, memory: 9000, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 1.8171, loss: 1.8171 +2025-05-06 07:16:04,029 - pyskl - INFO - Epoch [95][700/1281] lr: 7.525e-03, eta: 12:29:21, time: 0.700, data_time: 0.000, memory: 9000, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 1.9292, loss: 1.9292 +2025-05-06 07:17:09,964 - pyskl - INFO - Epoch [95][800/1281] lr: 7.506e-03, eta: 12:28:19, time: 0.659, data_time: 0.000, memory: 9000, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 1.9193, loss: 1.9193 +2025-05-06 07:18:10,259 - pyskl - INFO - Epoch [95][900/1281] lr: 7.487e-03, eta: 12:27:14, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 1.9187, loss: 1.9187 +2025-05-06 07:19:09,878 - pyskl - INFO - Epoch [95][1000/1281] lr: 7.468e-03, eta: 12:26:08, time: 0.596, data_time: 0.000, memory: 9000, top1_acc: 0.9744, top5_acc: 0.9994, loss_cls: 1.9338, loss: 1.9338 +2025-05-06 07:20:16,337 - pyskl - INFO - Epoch [95][1100/1281] lr: 7.450e-03, eta: 12:25:07, time: 0.665, data_time: 0.000, memory: 9000, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 1.9037, loss: 1.9037 +2025-05-06 07:21:22,202 - pyskl - INFO - Epoch [95][1200/1281] lr: 7.431e-03, eta: 12:24:05, time: 0.659, data_time: 0.000, memory: 9000, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 1.8895, loss: 1.8895 +2025-05-06 07:22:13,542 - pyskl - INFO - Saving checkpoint at 95 epochs +2025-05-06 07:23:03,207 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 07:23:03,261 - pyskl - INFO - +top1_acc 0.8945 +top5_acc 0.9931 +2025-05-06 07:23:03,262 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 07:23:03,268 - pyskl - INFO - +mean_acc 0.8700 +2025-05-06 07:23:03,270 - pyskl - INFO - Epoch(val) [95][533] top1_acc: 0.8945, top5_acc: 0.9931, mean_class_accuracy: 0.8700 +2025-05-06 07:24:13,176 - pyskl - INFO - Epoch [96][100/1281] lr: 7.397e-03, eta: 12:21:45, time: 0.699, data_time: 0.180, memory: 9000, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 1.8611, loss: 1.8611 +2025-05-06 07:25:19,715 - pyskl - INFO - Epoch [96][200/1281] lr: 7.379e-03, eta: 12:20:43, time: 0.665, data_time: 0.000, memory: 9000, top1_acc: 0.9762, top5_acc: 0.9994, loss_cls: 1.9535, loss: 1.9535 +2025-05-06 07:26:25,495 - pyskl - INFO - Epoch [96][300/1281] lr: 7.360e-03, eta: 12:19:42, time: 0.658, data_time: 0.000, memory: 9000, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 1.8446, loss: 1.8446 +2025-05-06 07:27:27,141 - pyskl - INFO - Epoch [96][400/1281] lr: 7.341e-03, eta: 12:18:37, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 1.9002, loss: 1.9002 +2025-05-06 07:28:27,647 - pyskl - INFO - Epoch [96][500/1281] lr: 7.323e-03, eta: 12:17:33, time: 0.605, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 1.8612, loss: 1.8612 +2025-05-06 07:29:37,015 - pyskl - INFO - Epoch [96][600/1281] lr: 7.304e-03, eta: 12:16:33, time: 0.694, data_time: 0.000, memory: 9000, top1_acc: 0.9663, top5_acc: 0.9988, loss_cls: 2.0310, loss: 2.0310 +2025-05-06 07:30:45,753 - pyskl - INFO - Epoch [96][700/1281] lr: 7.286e-03, eta: 12:15:33, time: 0.687, data_time: 0.000, memory: 9000, top1_acc: 0.9744, top5_acc: 0.9994, loss_cls: 1.9235, loss: 1.9235 +2025-05-06 07:31:46,749 - pyskl - INFO - Epoch [96][800/1281] lr: 7.267e-03, eta: 12:14:28, time: 0.610, data_time: 0.000, memory: 9000, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 1.8288, loss: 1.8288 +2025-05-06 07:32:46,234 - pyskl - INFO - Epoch [96][900/1281] lr: 7.249e-03, eta: 12:13:23, time: 0.595, data_time: 0.000, memory: 9000, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 1.8949, loss: 1.8949 +2025-05-06 07:33:50,977 - pyskl - INFO - Epoch [96][1000/1281] lr: 7.230e-03, eta: 12:12:20, time: 0.647, data_time: 0.000, memory: 9000, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 1.9259, loss: 1.9259 +2025-05-06 07:34:59,598 - pyskl - INFO - Epoch [96][1100/1281] lr: 7.211e-03, eta: 12:11:20, time: 0.686, data_time: 0.000, memory: 9000, top1_acc: 0.9606, top5_acc: 0.9981, loss_cls: 2.0601, loss: 2.0601 +2025-05-06 07:36:03,743 - pyskl - INFO - Epoch [96][1200/1281] lr: 7.193e-03, eta: 12:10:17, time: 0.641, data_time: 0.000, memory: 9000, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 1.9428, loss: 1.9428 +2025-05-06 07:36:53,803 - pyskl - INFO - Saving checkpoint at 96 epochs +2025-05-06 07:37:43,545 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 07:37:43,602 - pyskl - INFO - +top1_acc 0.8907 +top5_acc 0.9932 +2025-05-06 07:37:43,602 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 07:37:43,609 - pyskl - INFO - +mean_acc 0.8582 +2025-05-06 07:37:43,612 - pyskl - INFO - Epoch(val) [96][533] top1_acc: 0.8907, top5_acc: 0.9932, mean_class_accuracy: 0.8582 +2025-05-06 07:38:55,901 - pyskl - INFO - Epoch [97][100/1281] lr: 7.159e-03, eta: 12:07:59, time: 0.723, data_time: 0.187, memory: 9000, top1_acc: 0.9744, top5_acc: 0.9994, loss_cls: 1.9001, loss: 1.9001 +2025-05-06 07:39:57,947 - pyskl - INFO - Epoch [97][200/1281] lr: 7.141e-03, eta: 12:06:55, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.9675, top5_acc: 0.9994, loss_cls: 1.9097, loss: 1.9097 +2025-05-06 07:40:59,775 - pyskl - INFO - Epoch [97][300/1281] lr: 7.123e-03, eta: 12:05:51, time: 0.618, data_time: 0.000, memory: 9000, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 1.8564, loss: 1.8564 +2025-05-06 07:41:59,348 - pyskl - INFO - Epoch [97][400/1281] lr: 7.104e-03, eta: 12:04:46, time: 0.596, data_time: 0.000, memory: 9000, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 1.9350, loss: 1.9350 +2025-05-06 07:43:04,021 - pyskl - INFO - Epoch [97][500/1281] lr: 7.086e-03, eta: 12:03:43, time: 0.647, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 1.9112, loss: 1.9112 +2025-05-06 07:44:10,094 - pyskl - INFO - Epoch [97][600/1281] lr: 7.067e-03, eta: 12:02:42, time: 0.661, data_time: 0.000, memory: 9000, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 1.8521, loss: 1.8521 +2025-05-06 07:45:13,532 - pyskl - INFO - Epoch [97][700/1281] lr: 7.049e-03, eta: 12:01:39, time: 0.634, data_time: 0.000, memory: 9000, top1_acc: 0.9819, top5_acc: 0.9994, loss_cls: 1.8301, loss: 1.8301 +2025-05-06 07:46:15,474 - pyskl - INFO - Epoch [97][800/1281] lr: 7.030e-03, eta: 12:00:35, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 1.8251, loss: 1.8251 +2025-05-06 07:47:17,880 - pyskl - INFO - Epoch [97][900/1281] lr: 7.012e-03, eta: 11:59:31, time: 0.624, data_time: 0.000, memory: 9000, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 1.9987, loss: 1.9987 +2025-05-06 07:48:26,444 - pyskl - INFO - Epoch [97][1000/1281] lr: 6.994e-03, eta: 11:58:31, time: 0.686, data_time: 0.000, memory: 9000, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 1.9342, loss: 1.9342 +2025-05-06 07:49:30,814 - pyskl - INFO - Epoch [97][1100/1281] lr: 6.975e-03, eta: 11:57:28, time: 0.644, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 1.8884, loss: 1.8884 +2025-05-06 07:50:32,343 - pyskl - INFO - Epoch [97][1200/1281] lr: 6.957e-03, eta: 11:56:24, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 1.9381, loss: 1.9381 +2025-05-06 07:51:20,985 - pyskl - INFO - Saving checkpoint at 97 epochs +2025-05-06 07:52:14,099 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 07:52:14,155 - pyskl - INFO - +top1_acc 0.9056 +top5_acc 0.9938 +2025-05-06 07:52:14,155 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 07:52:14,163 - pyskl - INFO - +mean_acc 0.8813 +2025-05-06 07:52:14,165 - pyskl - INFO - Epoch(val) [97][533] top1_acc: 0.9056, top5_acc: 0.9938, mean_class_accuracy: 0.8813 +2025-05-06 07:53:29,699 - pyskl - INFO - Epoch [98][100/1281] lr: 6.924e-03, eta: 11:54:08, time: 0.755, data_time: 0.180, memory: 9000, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 1.9706, loss: 1.9706 +2025-05-06 07:54:31,222 - pyskl - INFO - Epoch [98][200/1281] lr: 6.906e-03, eta: 11:53:04, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 0.9800, top5_acc: 0.9994, loss_cls: 1.8667, loss: 1.8667 +2025-05-06 07:55:31,436 - pyskl - INFO - Epoch [98][300/1281] lr: 6.887e-03, eta: 11:51:59, time: 0.602, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.8649, loss: 1.8649 +2025-05-06 07:56:33,283 - pyskl - INFO - Epoch [98][400/1281] lr: 6.869e-03, eta: 11:50:55, time: 0.618, data_time: 0.000, memory: 9000, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 1.8181, loss: 1.8181 +2025-05-06 07:57:40,856 - pyskl - INFO - Epoch [98][500/1281] lr: 6.851e-03, eta: 11:49:54, time: 0.676, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 1.8873, loss: 1.8873 +2025-05-06 07:58:46,293 - pyskl - INFO - Epoch [98][600/1281] lr: 6.833e-03, eta: 11:48:52, time: 0.654, data_time: 0.000, memory: 9000, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 1.8470, loss: 1.8470 +2025-05-06 07:59:47,751 - pyskl - INFO - Epoch [98][700/1281] lr: 6.814e-03, eta: 11:47:48, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 1.7862, loss: 1.7862 +2025-05-06 08:00:47,862 - pyskl - INFO - Epoch [98][800/1281] lr: 6.796e-03, eta: 11:46:43, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.8539, loss: 1.8539 +2025-05-06 08:01:56,187 - pyskl - INFO - Epoch [98][900/1281] lr: 6.778e-03, eta: 11:45:43, time: 0.683, data_time: 0.000, memory: 9000, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 1.8461, loss: 1.8461 +2025-05-06 08:03:06,195 - pyskl - INFO - Epoch [98][1000/1281] lr: 6.760e-03, eta: 11:44:43, time: 0.700, data_time: 0.000, memory: 9000, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 1.8892, loss: 1.8892 +2025-05-06 08:04:08,788 - pyskl - INFO - Epoch [98][1100/1281] lr: 6.742e-03, eta: 11:43:40, time: 0.626, data_time: 0.000, memory: 9000, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 1.9094, loss: 1.9094 +2025-05-06 08:05:09,852 - pyskl - INFO - Epoch [98][1200/1281] lr: 6.724e-03, eta: 11:42:35, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 1.9190, loss: 1.9190 +2025-05-06 08:06:01,227 - pyskl - INFO - Saving checkpoint at 98 epochs +2025-05-06 08:06:56,086 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 08:06:56,141 - pyskl - INFO - +top1_acc 0.9053 +top5_acc 0.9931 +2025-05-06 08:06:56,141 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 08:06:56,149 - pyskl - INFO - +mean_acc 0.8741 +2025-05-06 08:06:56,153 - pyskl - INFO - Epoch(val) [98][533] top1_acc: 0.9053, top5_acc: 0.9931, mean_class_accuracy: 0.8741 +2025-05-06 08:08:07,356 - pyskl - INFO - Epoch [99][100/1281] lr: 6.691e-03, eta: 11:40:18, time: 0.712, data_time: 0.182, memory: 9000, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 1.8428, loss: 1.8428 +2025-05-06 08:09:08,422 - pyskl - INFO - Epoch [99][200/1281] lr: 6.673e-03, eta: 11:39:14, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.8340, loss: 1.8340 +2025-05-06 08:10:07,188 - pyskl - INFO - Epoch [99][300/1281] lr: 6.655e-03, eta: 11:38:08, time: 0.588, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.8149, loss: 1.8149 +2025-05-06 08:11:14,039 - pyskl - INFO - Epoch [99][400/1281] lr: 6.637e-03, eta: 11:37:07, time: 0.669, data_time: 0.000, memory: 9000, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 1.9671, loss: 1.9671 +2025-05-06 08:12:23,231 - pyskl - INFO - Epoch [99][500/1281] lr: 6.619e-03, eta: 11:36:07, time: 0.692, data_time: 0.000, memory: 9000, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 1.8896, loss: 1.8896 +2025-05-06 08:13:25,831 - pyskl - INFO - Epoch [99][600/1281] lr: 6.601e-03, eta: 11:35:04, time: 0.626, data_time: 0.000, memory: 9000, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 1.9148, loss: 1.9148 +2025-05-06 08:14:26,233 - pyskl - INFO - Epoch [99][700/1281] lr: 6.583e-03, eta: 11:33:59, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 1.9620, loss: 1.9620 +2025-05-06 08:15:30,257 - pyskl - INFO - Epoch [99][800/1281] lr: 6.565e-03, eta: 11:32:56, time: 0.640, data_time: 0.000, memory: 9000, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 1.8541, loss: 1.8541 +2025-05-06 08:16:42,155 - pyskl - INFO - Epoch [99][900/1281] lr: 6.547e-03, eta: 11:31:58, time: 0.719, data_time: 0.000, memory: 9000, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 1.9302, loss: 1.9302 +2025-05-06 08:17:47,034 - pyskl - INFO - Epoch [99][1000/1281] lr: 6.529e-03, eta: 11:30:55, time: 0.649, data_time: 0.000, memory: 9000, top1_acc: 0.9794, top5_acc: 0.9994, loss_cls: 1.9012, loss: 1.9012 +2025-05-06 08:18:47,467 - pyskl - INFO - Epoch [99][1100/1281] lr: 6.511e-03, eta: 11:29:51, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9750, top5_acc: 0.9994, loss_cls: 1.9198, loss: 1.9198 +2025-05-06 08:19:49,795 - pyskl - INFO - Epoch [99][1200/1281] lr: 6.493e-03, eta: 11:28:47, time: 0.623, data_time: 0.000, memory: 9000, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 1.8593, loss: 1.8593 +2025-05-06 08:20:46,314 - pyskl - INFO - Saving checkpoint at 99 epochs +2025-05-06 08:21:42,639 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 08:21:42,694 - pyskl - INFO - +top1_acc 0.8934 +top5_acc 0.9916 +2025-05-06 08:21:42,694 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 08:21:42,701 - pyskl - INFO - +mean_acc 0.8657 +2025-05-06 08:21:42,703 - pyskl - INFO - Epoch(val) [99][533] top1_acc: 0.8934, top5_acc: 0.9916, mean_class_accuracy: 0.8657 +2025-05-06 08:22:52,833 - pyskl - INFO - Epoch [100][100/1281] lr: 6.460e-03, eta: 11:26:30, time: 0.701, data_time: 0.184, memory: 9000, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 1.9655, loss: 1.9655 +2025-05-06 08:23:49,516 - pyskl - INFO - Epoch [100][200/1281] lr: 6.442e-03, eta: 11:25:24, time: 0.567, data_time: 0.000, memory: 9000, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 1.8084, loss: 1.8084 +2025-05-06 08:24:53,955 - pyskl - INFO - Epoch [100][300/1281] lr: 6.425e-03, eta: 11:24:21, time: 0.644, data_time: 0.000, memory: 9000, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 1.8316, loss: 1.8316 +2025-05-06 08:26:05,878 - pyskl - INFO - Epoch [100][400/1281] lr: 6.407e-03, eta: 11:23:22, time: 0.719, data_time: 0.000, memory: 9000, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 1.7825, loss: 1.7825 +2025-05-06 08:27:08,296 - pyskl - INFO - Epoch [100][500/1281] lr: 6.389e-03, eta: 11:22:19, time: 0.624, data_time: 0.000, memory: 9000, top1_acc: 0.9862, top5_acc: 0.9994, loss_cls: 1.7991, loss: 1.7991 +2025-05-06 08:28:08,198 - pyskl - INFO - Epoch [100][600/1281] lr: 6.371e-03, eta: 11:21:14, time: 0.599, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.8144, loss: 1.8144 +2025-05-06 08:29:08,987 - pyskl - INFO - Epoch [100][700/1281] lr: 6.353e-03, eta: 11:20:10, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 1.8001, loss: 1.8001 +2025-05-06 08:30:22,542 - pyskl - INFO - Epoch [100][800/1281] lr: 6.336e-03, eta: 11:19:12, time: 0.736, data_time: 0.000, memory: 9000, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 1.7475, loss: 1.7475 +2025-05-06 08:31:30,307 - pyskl - INFO - Epoch [100][900/1281] lr: 6.318e-03, eta: 11:18:11, time: 0.678, data_time: 0.000, memory: 9000, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 1.7941, loss: 1.7941 +2025-05-06 08:32:31,173 - pyskl - INFO - Epoch [100][1000/1281] lr: 6.300e-03, eta: 11:17:07, time: 0.609, data_time: 0.000, memory: 9000, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 1.7723, loss: 1.7723 +2025-05-06 08:33:31,322 - pyskl - INFO - Epoch [100][1100/1281] lr: 6.282e-03, eta: 11:16:02, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 1.7669, loss: 1.7669 +2025-05-06 08:34:41,826 - pyskl - INFO - Epoch [100][1200/1281] lr: 6.265e-03, eta: 11:15:03, time: 0.705, data_time: 0.000, memory: 9000, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 1.8423, loss: 1.8423 +2025-05-06 08:35:40,389 - pyskl - INFO - Saving checkpoint at 100 epochs +2025-05-06 08:36:31,623 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 08:36:31,680 - pyskl - INFO - +top1_acc 0.9094 +top5_acc 0.9942 +2025-05-06 08:36:31,680 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 08:36:31,686 - pyskl - INFO - +mean_acc 0.8805 +2025-05-06 08:36:31,749 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_94.pth was removed +2025-05-06 08:36:33,291 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_100.pth. +2025-05-06 08:36:33,291 - pyskl - INFO - Best top1_acc is 0.9094 at 100 epoch. +2025-05-06 08:36:33,295 - pyskl - INFO - Epoch(val) [100][533] top1_acc: 0.9094, top5_acc: 0.9942, mean_class_accuracy: 0.8805 +2025-05-06 08:37:41,116 - pyskl - INFO - Epoch [101][100/1281] lr: 6.232e-03, eta: 11:12:45, time: 0.678, data_time: 0.180, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.7876, loss: 1.7876 +2025-05-06 08:38:41,448 - pyskl - INFO - Epoch [101][200/1281] lr: 6.215e-03, eta: 11:11:41, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 0.9994, loss_cls: 1.8457, loss: 1.8457 +2025-05-06 08:39:53,530 - pyskl - INFO - Epoch [101][300/1281] lr: 6.197e-03, eta: 11:10:42, time: 0.721, data_time: 0.000, memory: 9000, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 1.8574, loss: 1.8574 +2025-05-06 08:40:58,570 - pyskl - INFO - Epoch [101][400/1281] lr: 6.180e-03, eta: 11:09:40, time: 0.650, data_time: 0.000, memory: 9000, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 1.8721, loss: 1.8721 +2025-05-06 08:41:58,735 - pyskl - INFO - Epoch [101][500/1281] lr: 6.162e-03, eta: 11:08:35, time: 0.602, data_time: 0.000, memory: 9000, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 1.7550, loss: 1.7550 +2025-05-06 08:43:01,318 - pyskl - INFO - Epoch [101][600/1281] lr: 6.144e-03, eta: 11:07:32, time: 0.626, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.7399, loss: 1.7399 +2025-05-06 08:44:16,405 - pyskl - INFO - Epoch [101][700/1281] lr: 6.127e-03, eta: 11:06:35, time: 0.751, data_time: 0.000, memory: 9000, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 1.7944, loss: 1.7944 +2025-05-06 08:45:21,858 - pyskl - INFO - Epoch [101][800/1281] lr: 6.109e-03, eta: 11:05:33, time: 0.655, data_time: 0.000, memory: 9000, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 1.8874, loss: 1.8874 +2025-05-06 08:46:22,432 - pyskl - INFO - Epoch [101][900/1281] lr: 6.092e-03, eta: 11:04:28, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 1.8034, loss: 1.8034 +2025-05-06 08:47:22,050 - pyskl - INFO - Epoch [101][1000/1281] lr: 6.074e-03, eta: 11:03:23, time: 0.596, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.7448, loss: 1.7448 +2025-05-06 08:48:35,513 - pyskl - INFO - Epoch [101][1100/1281] lr: 6.057e-03, eta: 11:02:25, time: 0.735, data_time: 0.000, memory: 9000, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 1.8588, loss: 1.8588 +2025-05-06 08:49:46,025 - pyskl - INFO - Epoch [101][1200/1281] lr: 6.039e-03, eta: 11:01:26, time: 0.705, data_time: 0.000, memory: 9000, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 1.8837, loss: 1.8837 +2025-05-06 08:50:37,340 - pyskl - INFO - Saving checkpoint at 101 epochs +2025-05-06 08:51:27,434 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 08:51:27,504 - pyskl - INFO - +top1_acc 0.9008 +top5_acc 0.9911 +2025-05-06 08:51:27,504 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 08:51:27,513 - pyskl - INFO - +mean_acc 0.8599 +2025-05-06 08:51:27,516 - pyskl - INFO - Epoch(val) [101][533] top1_acc: 0.9008, top5_acc: 0.9911, mean_class_accuracy: 0.8599 +2025-05-06 08:52:40,181 - pyskl - INFO - Epoch [102][100/1281] lr: 6.007e-03, eta: 10:59:11, time: 0.727, data_time: 0.185, memory: 9000, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 1.7653, loss: 1.7653 +2025-05-06 08:53:51,540 - pyskl - INFO - Epoch [102][200/1281] lr: 5.990e-03, eta: 10:58:12, time: 0.714, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.7994, loss: 1.7994 +2025-05-06 08:54:55,369 - pyskl - INFO - Epoch [102][300/1281] lr: 5.972e-03, eta: 10:57:09, time: 0.638, data_time: 0.000, memory: 9000, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 1.8065, loss: 1.8065 +2025-05-06 08:55:55,680 - pyskl - INFO - Epoch [102][400/1281] lr: 5.955e-03, eta: 10:56:05, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 1.8007, loss: 1.8007 +2025-05-06 08:56:57,148 - pyskl - INFO - Epoch [102][500/1281] lr: 5.938e-03, eta: 10:55:01, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 1.7798, loss: 1.7798 +2025-05-06 08:58:12,632 - pyskl - INFO - Epoch [102][600/1281] lr: 5.920e-03, eta: 10:54:04, time: 0.755, data_time: 0.000, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.8199, loss: 1.8199 +2025-05-06 08:59:19,517 - pyskl - INFO - Epoch [102][700/1281] lr: 5.903e-03, eta: 10:53:02, time: 0.669, data_time: 0.000, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.7056, loss: 1.7056 +2025-05-06 09:00:21,083 - pyskl - INFO - Epoch [102][800/1281] lr: 5.886e-03, eta: 10:51:59, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 1.7853, loss: 1.7853 +2025-05-06 09:01:22,134 - pyskl - INFO - Epoch [102][900/1281] lr: 5.868e-03, eta: 10:50:54, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 1.7898, loss: 1.7898 +2025-05-06 09:02:36,736 - pyskl - INFO - Epoch [102][1000/1281] lr: 5.851e-03, eta: 10:49:57, time: 0.746, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.8203, loss: 1.8203 +2025-05-06 09:03:46,401 - pyskl - INFO - Epoch [102][1100/1281] lr: 5.834e-03, eta: 10:48:57, time: 0.697, data_time: 0.000, memory: 9000, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 1.7534, loss: 1.7534 +2025-05-06 09:04:46,934 - pyskl - INFO - Epoch [102][1200/1281] lr: 5.816e-03, eta: 10:47:52, time: 0.605, data_time: 0.000, memory: 9000, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 1.8111, loss: 1.8111 +2025-05-06 09:05:36,428 - pyskl - INFO - Saving checkpoint at 102 epochs +2025-05-06 09:06:30,901 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 09:06:30,958 - pyskl - INFO - +top1_acc 0.9154 +top5_acc 0.9938 +2025-05-06 09:06:30,958 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 09:06:30,966 - pyskl - INFO - +mean_acc 0.8846 +2025-05-06 09:06:31,027 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_100.pth was removed +2025-05-06 09:06:32,566 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_102.pth. +2025-05-06 09:06:32,567 - pyskl - INFO - Best top1_acc is 0.9154 at 102 epoch. +2025-05-06 09:06:32,570 - pyskl - INFO - Epoch(val) [102][533] top1_acc: 0.9154, top5_acc: 0.9938, mean_class_accuracy: 0.8846 +2025-05-06 09:07:51,564 - pyskl - INFO - Epoch [103][100/1281] lr: 5.785e-03, eta: 10:45:41, time: 0.790, data_time: 0.182, memory: 9000, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 1.7917, loss: 1.7917 +2025-05-06 09:08:53,231 - pyskl - INFO - Epoch [103][200/1281] lr: 5.768e-03, eta: 10:44:38, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 1.7569, loss: 1.7569 +2025-05-06 09:09:54,050 - pyskl - INFO - Epoch [103][300/1281] lr: 5.751e-03, eta: 10:43:34, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 1.7707, loss: 1.7707 +2025-05-06 09:10:55,808 - pyskl - INFO - Epoch [103][400/1281] lr: 5.733e-03, eta: 10:42:30, time: 0.618, data_time: 0.000, memory: 9000, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 1.7988, loss: 1.7988 +2025-05-06 09:12:10,611 - pyskl - INFO - Epoch [103][500/1281] lr: 5.716e-03, eta: 10:41:32, time: 0.748, data_time: 0.000, memory: 9000, top1_acc: 0.9675, top5_acc: 0.9994, loss_cls: 1.9181, loss: 1.9181 +2025-05-06 09:13:17,390 - pyskl - INFO - Epoch [103][600/1281] lr: 5.699e-03, eta: 10:40:31, time: 0.668, data_time: 0.000, memory: 9000, top1_acc: 0.9725, top5_acc: 0.9994, loss_cls: 1.8630, loss: 1.8630 +2025-05-06 09:14:19,583 - pyskl - INFO - Epoch [103][700/1281] lr: 5.682e-03, eta: 10:39:27, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.7751, loss: 1.7751 +2025-05-06 09:15:20,559 - pyskl - INFO - Epoch [103][800/1281] lr: 5.665e-03, eta: 10:38:23, time: 0.610, data_time: 0.000, memory: 9000, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 1.7397, loss: 1.7397 +2025-05-06 09:16:35,428 - pyskl - INFO - Epoch [103][900/1281] lr: 5.648e-03, eta: 10:37:25, time: 0.749, data_time: 0.000, memory: 9000, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 1.7747, loss: 1.7747 +2025-05-06 09:17:45,298 - pyskl - INFO - Epoch [103][1000/1281] lr: 5.631e-03, eta: 10:36:25, time: 0.699, data_time: 0.000, memory: 9000, top1_acc: 0.9862, top5_acc: 0.9994, loss_cls: 1.7708, loss: 1.7708 +2025-05-06 09:18:47,446 - pyskl - INFO - Epoch [103][1100/1281] lr: 5.614e-03, eta: 10:35:22, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.7671, loss: 1.7671 +2025-05-06 09:19:48,326 - pyskl - INFO - Epoch [103][1200/1281] lr: 5.597e-03, eta: 10:34:18, time: 0.609, data_time: 0.000, memory: 9000, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 1.8316, loss: 1.8316 +2025-05-06 09:20:42,513 - pyskl - INFO - Saving checkpoint at 103 epochs +2025-05-06 09:21:44,061 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 09:21:44,115 - pyskl - INFO - +top1_acc 0.9044 +top5_acc 0.9928 +2025-05-06 09:21:44,115 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 09:21:44,122 - pyskl - INFO - +mean_acc 0.8758 +2025-05-06 09:21:44,123 - pyskl - INFO - Epoch(val) [103][533] top1_acc: 0.9044, top5_acc: 0.9928, mean_class_accuracy: 0.8758 +2025-05-06 09:22:56,369 - pyskl - INFO - Epoch [104][100/1281] lr: 5.566e-03, eta: 10:32:04, time: 0.722, data_time: 0.179, memory: 9000, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 1.8407, loss: 1.8407 +2025-05-06 09:23:55,575 - pyskl - INFO - Epoch [104][200/1281] lr: 5.549e-03, eta: 10:30:59, time: 0.592, data_time: 0.000, memory: 9000, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 1.7139, loss: 1.7139 +2025-05-06 09:24:59,338 - pyskl - INFO - Epoch [104][300/1281] lr: 5.532e-03, eta: 10:29:57, time: 0.638, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.7219, loss: 1.7219 +2025-05-06 09:26:15,659 - pyskl - INFO - Epoch [104][400/1281] lr: 5.515e-03, eta: 10:28:59, time: 0.763, data_time: 0.000, memory: 9000, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 1.7556, loss: 1.7556 +2025-05-06 09:27:22,724 - pyskl - INFO - Epoch [104][500/1281] lr: 5.498e-03, eta: 10:27:58, time: 0.671, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 1.8174, loss: 1.8174 +2025-05-06 09:28:23,413 - pyskl - INFO - Epoch [104][600/1281] lr: 5.481e-03, eta: 10:26:54, time: 0.607, data_time: 0.000, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.8187, loss: 1.8187 +2025-05-06 09:29:24,506 - pyskl - INFO - Epoch [104][700/1281] lr: 5.464e-03, eta: 10:25:50, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 1.8306, loss: 1.8306 +2025-05-06 09:30:39,071 - pyskl - INFO - Epoch [104][800/1281] lr: 5.447e-03, eta: 10:24:52, time: 0.746, data_time: 0.000, memory: 9000, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 1.7521, loss: 1.7521 +2025-05-06 09:31:47,985 - pyskl - INFO - Epoch [104][900/1281] lr: 5.430e-03, eta: 10:23:51, time: 0.689, data_time: 0.000, memory: 9000, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 1.7663, loss: 1.7663 +2025-05-06 09:32:49,055 - pyskl - INFO - Epoch [104][1000/1281] lr: 5.413e-03, eta: 10:22:47, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 1.8009, loss: 1.8009 +2025-05-06 09:33:49,024 - pyskl - INFO - Epoch [104][1100/1281] lr: 5.397e-03, eta: 10:21:43, time: 0.600, data_time: 0.000, memory: 9000, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 1.7707, loss: 1.7707 +2025-05-06 09:35:01,210 - pyskl - INFO - Epoch [104][1200/1281] lr: 5.380e-03, eta: 10:20:44, time: 0.722, data_time: 0.000, memory: 9000, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 1.7824, loss: 1.7824 +2025-05-06 09:36:02,476 - pyskl - INFO - Saving checkpoint at 104 epochs +2025-05-06 09:36:55,130 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 09:36:55,185 - pyskl - INFO - +top1_acc 0.9089 +top5_acc 0.9931 +2025-05-06 09:36:55,185 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 09:36:55,192 - pyskl - INFO - +mean_acc 0.8772 +2025-05-06 09:36:55,195 - pyskl - INFO - Epoch(val) [104][533] top1_acc: 0.9089, top5_acc: 0.9931, mean_class_accuracy: 0.8772 +2025-05-06 09:38:03,126 - pyskl - INFO - Epoch [105][100/1281] lr: 5.349e-03, eta: 10:18:29, time: 0.679, data_time: 0.182, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.8012, loss: 1.8012 +2025-05-06 09:39:03,821 - pyskl - INFO - Epoch [105][200/1281] lr: 5.333e-03, eta: 10:17:25, time: 0.607, data_time: 0.000, memory: 9000, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 1.6990, loss: 1.6990 +2025-05-06 09:40:20,313 - pyskl - INFO - Epoch [105][300/1281] lr: 5.316e-03, eta: 10:16:28, time: 0.765, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.7553, loss: 1.7553 +2025-05-06 09:41:25,917 - pyskl - INFO - Epoch [105][400/1281] lr: 5.299e-03, eta: 10:15:26, time: 0.656, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.7169, loss: 1.7169 +2025-05-06 09:42:27,005 - pyskl - INFO - Epoch [105][500/1281] lr: 5.283e-03, eta: 10:14:22, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 1.7825, loss: 1.7825 +2025-05-06 09:43:29,026 - pyskl - INFO - Epoch [105][600/1281] lr: 5.266e-03, eta: 10:13:18, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 1.7810, loss: 1.7810 +2025-05-06 09:44:44,666 - pyskl - INFO - Epoch [105][700/1281] lr: 5.249e-03, eta: 10:12:21, time: 0.756, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.7969, loss: 1.7969 +2025-05-06 09:45:54,386 - pyskl - INFO - Epoch [105][800/1281] lr: 5.233e-03, eta: 10:11:20, time: 0.697, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.8033, loss: 1.8033 +2025-05-06 09:46:56,298 - pyskl - INFO - Epoch [105][900/1281] lr: 5.216e-03, eta: 10:10:17, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 1.7965, loss: 1.7965 +2025-05-06 09:47:57,375 - pyskl - INFO - Epoch [105][1000/1281] lr: 5.199e-03, eta: 10:09:13, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 1.8223, loss: 1.8223 +2025-05-06 09:49:09,471 - pyskl - INFO - Epoch [105][1100/1281] lr: 5.183e-03, eta: 10:08:14, time: 0.721, data_time: 0.000, memory: 9000, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 1.8641, loss: 1.8641 +2025-05-06 09:50:21,278 - pyskl - INFO - Epoch [105][1200/1281] lr: 5.166e-03, eta: 10:07:14, time: 0.718, data_time: 0.000, memory: 9000, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 1.7978, loss: 1.7978 +2025-05-06 09:51:13,261 - pyskl - INFO - Saving checkpoint at 105 epochs +2025-05-06 09:52:03,287 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 09:52:03,342 - pyskl - INFO - +top1_acc 0.9040 +top5_acc 0.9935 +2025-05-06 09:52:03,342 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 09:52:03,349 - pyskl - INFO - +mean_acc 0.8817 +2025-05-06 09:52:03,351 - pyskl - INFO - Epoch(val) [105][533] top1_acc: 0.9040, top5_acc: 0.9935, mean_class_accuracy: 0.8817 +2025-05-06 09:53:13,462 - pyskl - INFO - Epoch [106][100/1281] lr: 5.136e-03, eta: 10:05:01, time: 0.701, data_time: 0.179, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.7103, loss: 1.7103 +2025-05-06 09:54:25,559 - pyskl - INFO - Epoch [106][200/1281] lr: 5.120e-03, eta: 10:04:02, time: 0.721, data_time: 0.000, memory: 9000, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 1.6752, loss: 1.6752 +2025-05-06 09:55:30,147 - pyskl - INFO - Epoch [106][300/1281] lr: 5.103e-03, eta: 10:02:59, time: 0.646, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.7025, loss: 1.7025 +2025-05-06 09:56:31,076 - pyskl - INFO - Epoch [106][400/1281] lr: 5.087e-03, eta: 10:01:55, time: 0.609, data_time: 0.000, memory: 9000, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 1.7164, loss: 1.7164 +2025-05-06 09:57:31,405 - pyskl - INFO - Epoch [106][500/1281] lr: 5.070e-03, eta: 10:00:51, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.7458, loss: 1.7458 +2025-05-06 09:58:42,898 - pyskl - INFO - Epoch [106][600/1281] lr: 5.054e-03, eta: 9:59:52, time: 0.715, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.6544, loss: 1.6544 +2025-05-06 09:59:54,284 - pyskl - INFO - Epoch [106][700/1281] lr: 5.038e-03, eta: 9:58:52, time: 0.714, data_time: 0.000, memory: 9000, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 1.6262, loss: 1.6262 +2025-05-06 10:00:55,419 - pyskl - INFO - Epoch [106][800/1281] lr: 5.021e-03, eta: 9:57:48, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 1.6818, loss: 1.6818 +2025-05-06 10:01:55,980 - pyskl - INFO - Epoch [106][900/1281] lr: 5.005e-03, eta: 9:56:44, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.7101, loss: 1.7101 +2025-05-06 10:03:05,884 - pyskl - INFO - Epoch [106][1000/1281] lr: 4.988e-03, eta: 9:55:44, time: 0.699, data_time: 0.000, memory: 9000, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 1.7756, loss: 1.7756 +2025-05-06 10:04:19,323 - pyskl - INFO - Epoch [106][1100/1281] lr: 4.972e-03, eta: 9:54:45, time: 0.734, data_time: 0.000, memory: 9000, top1_acc: 0.9838, top5_acc: 0.9994, loss_cls: 1.7606, loss: 1.7606 +2025-05-06 10:05:21,818 - pyskl - INFO - Epoch [106][1200/1281] lr: 4.956e-03, eta: 9:53:41, time: 0.625, data_time: 0.000, memory: 9000, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 1.6569, loss: 1.6569 +2025-05-06 10:06:11,216 - pyskl - INFO - Saving checkpoint at 106 epochs +2025-05-06 10:07:01,817 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 10:07:01,874 - pyskl - INFO - +top1_acc 0.9080 +top5_acc 0.9939 +2025-05-06 10:07:01,874 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 10:07:01,882 - pyskl - INFO - +mean_acc 0.8757 +2025-05-06 10:07:01,886 - pyskl - INFO - Epoch(val) [106][533] top1_acc: 0.9080, top5_acc: 0.9939, mean_class_accuracy: 0.8757 +2025-05-06 10:08:19,736 - pyskl - INFO - Epoch [107][100/1281] lr: 4.926e-03, eta: 9:51:32, time: 0.778, data_time: 0.182, memory: 9000, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 1.7709, loss: 1.7709 +2025-05-06 10:09:24,100 - pyskl - INFO - Epoch [107][200/1281] lr: 4.910e-03, eta: 9:50:30, time: 0.644, data_time: 0.000, memory: 9000, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 1.7693, loss: 1.7693 +2025-05-06 10:10:24,717 - pyskl - INFO - Epoch [107][300/1281] lr: 4.894e-03, eta: 9:49:26, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.6736, loss: 1.6736 +2025-05-06 10:11:25,009 - pyskl - INFO - Epoch [107][400/1281] lr: 4.878e-03, eta: 9:48:21, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.7367, loss: 1.7367 +2025-05-06 10:12:32,400 - pyskl - INFO - Epoch [107][500/1281] lr: 4.862e-03, eta: 9:47:20, time: 0.674, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.6762, loss: 1.6762 +2025-05-06 10:13:44,456 - pyskl - INFO - Epoch [107][600/1281] lr: 4.845e-03, eta: 9:46:21, time: 0.721, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.6694, loss: 1.6694 +2025-05-06 10:14:46,599 - pyskl - INFO - Epoch [107][700/1281] lr: 4.829e-03, eta: 9:45:17, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 1.6928, loss: 1.6928 +2025-05-06 10:15:47,705 - pyskl - INFO - Epoch [107][800/1281] lr: 4.813e-03, eta: 9:44:13, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 1.6858, loss: 1.6858 +2025-05-06 10:16:50,133 - pyskl - INFO - Epoch [107][900/1281] lr: 4.797e-03, eta: 9:43:10, time: 0.624, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.6963, loss: 1.6963 +2025-05-06 10:18:03,934 - pyskl - INFO - Epoch [107][1000/1281] lr: 4.781e-03, eta: 9:42:11, time: 0.738, data_time: 0.000, memory: 9000, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 1.7132, loss: 1.7132 +2025-05-06 10:19:08,486 - pyskl - INFO - Epoch [107][1100/1281] lr: 4.765e-03, eta: 9:41:09, time: 0.646, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.7387, loss: 1.7387 +2025-05-06 10:20:10,047 - pyskl - INFO - Epoch [107][1200/1281] lr: 4.749e-03, eta: 9:40:05, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.7280, loss: 1.7280 +2025-05-06 10:21:00,036 - pyskl - INFO - Saving checkpoint at 107 epochs +2025-05-06 10:21:56,603 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 10:21:56,658 - pyskl - INFO - +top1_acc 0.9148 +top5_acc 0.9927 +2025-05-06 10:21:56,658 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 10:21:56,665 - pyskl - INFO - +mean_acc 0.8932 +2025-05-06 10:21:56,667 - pyskl - INFO - Epoch(val) [107][533] top1_acc: 0.9148, top5_acc: 0.9927, mean_class_accuracy: 0.8932 +2025-05-06 10:23:13,340 - pyskl - INFO - Epoch [108][100/1281] lr: 4.720e-03, eta: 9:37:56, time: 0.767, data_time: 0.180, memory: 9000, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 1.7020, loss: 1.7020 +2025-05-06 10:24:13,736 - pyskl - INFO - Epoch [108][200/1281] lr: 4.704e-03, eta: 9:36:51, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.7037, loss: 1.7037 +2025-05-06 10:25:13,083 - pyskl - INFO - Epoch [108][300/1281] lr: 4.688e-03, eta: 9:35:47, time: 0.593, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.7113, loss: 1.7113 +2025-05-06 10:26:15,158 - pyskl - INFO - Epoch [108][400/1281] lr: 4.672e-03, eta: 9:34:43, time: 0.621, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.6857, loss: 1.6857 +2025-05-06 10:27:27,699 - pyskl - INFO - Epoch [108][500/1281] lr: 4.656e-03, eta: 9:33:44, time: 0.725, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.7649, loss: 1.7649 +2025-05-06 10:28:30,394 - pyskl - INFO - Epoch [108][600/1281] lr: 4.640e-03, eta: 9:32:41, time: 0.627, data_time: 0.000, memory: 9000, top1_acc: 0.9825, top5_acc: 0.9994, loss_cls: 1.7418, loss: 1.7418 +2025-05-06 10:29:30,896 - pyskl - INFO - Epoch [108][700/1281] lr: 4.624e-03, eta: 9:31:37, time: 0.605, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.7170, loss: 1.7170 +2025-05-06 10:30:32,548 - pyskl - INFO - Epoch [108][800/1281] lr: 4.608e-03, eta: 9:30:33, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.6820, loss: 1.6820 +2025-05-06 10:31:45,010 - pyskl - INFO - Epoch [108][900/1281] lr: 4.593e-03, eta: 9:29:34, time: 0.725, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.6774, loss: 1.6774 +2025-05-06 10:32:50,220 - pyskl - INFO - Epoch [108][1000/1281] lr: 4.577e-03, eta: 9:28:32, time: 0.652, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.6779, loss: 1.6779 +2025-05-06 10:33:50,665 - pyskl - INFO - Epoch [108][1100/1281] lr: 4.561e-03, eta: 9:27:28, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.6495, loss: 1.6495 +2025-05-06 10:34:50,479 - pyskl - INFO - Epoch [108][1200/1281] lr: 4.545e-03, eta: 9:26:23, time: 0.598, data_time: 0.000, memory: 9000, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 1.7461, loss: 1.7461 +2025-05-06 10:35:43,627 - pyskl - INFO - Saving checkpoint at 108 epochs +2025-05-06 10:36:42,758 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 10:36:42,814 - pyskl - INFO - +top1_acc 0.9058 +top5_acc 0.9935 +2025-05-06 10:36:42,814 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 10:36:42,822 - pyskl - INFO - +mean_acc 0.8799 +2025-05-06 10:36:42,824 - pyskl - INFO - Epoch(val) [108][533] top1_acc: 0.9058, top5_acc: 0.9935, mean_class_accuracy: 0.8799 +2025-05-06 10:37:53,590 - pyskl - INFO - Epoch [109][100/1281] lr: 4.517e-03, eta: 9:24:12, time: 0.708, data_time: 0.179, memory: 9000, top1_acc: 0.9844, top5_acc: 0.9994, loss_cls: 1.7367, loss: 1.7367 +2025-05-06 10:38:51,494 - pyskl - INFO - Epoch [109][200/1281] lr: 4.501e-03, eta: 9:23:07, time: 0.579, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.7338, loss: 1.7338 +2025-05-06 10:39:50,510 - pyskl - INFO - Epoch [109][300/1281] lr: 4.485e-03, eta: 9:22:03, time: 0.590, data_time: 0.000, memory: 9000, top1_acc: 0.9806, top5_acc: 0.9994, loss_cls: 1.7815, loss: 1.7815 +2025-05-06 10:41:00,230 - pyskl - INFO - Epoch [109][400/1281] lr: 4.470e-03, eta: 9:21:02, time: 0.697, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.7038, loss: 1.7038 +2025-05-06 10:42:06,472 - pyskl - INFO - Epoch [109][500/1281] lr: 4.454e-03, eta: 9:20:00, time: 0.662, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.7238, loss: 1.7238 +2025-05-06 10:43:07,483 - pyskl - INFO - Epoch [109][600/1281] lr: 4.438e-03, eta: 9:18:57, time: 0.610, data_time: 0.000, memory: 9000, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 1.7191, loss: 1.7191 +2025-05-06 10:44:07,557 - pyskl - INFO - Epoch [109][700/1281] lr: 4.423e-03, eta: 9:17:52, time: 0.601, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.7923, loss: 1.7923 +2025-05-06 10:45:13,241 - pyskl - INFO - Epoch [109][800/1281] lr: 4.407e-03, eta: 9:16:50, time: 0.657, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.7031, loss: 1.7031 +2025-05-06 10:46:22,439 - pyskl - INFO - Epoch [109][900/1281] lr: 4.391e-03, eta: 9:15:50, time: 0.692, data_time: 0.000, memory: 9000, top1_acc: 0.9900, top5_acc: 0.9994, loss_cls: 1.6997, loss: 1.6997 +2025-05-06 10:47:25,121 - pyskl - INFO - Epoch [109][1000/1281] lr: 4.376e-03, eta: 9:14:46, time: 0.627, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.6658, loss: 1.6658 +2025-05-06 10:48:25,425 - pyskl - INFO - Epoch [109][1100/1281] lr: 4.360e-03, eta: 9:13:42, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.7141, loss: 1.7141 +2025-05-06 10:49:26,217 - pyskl - INFO - Epoch [109][1200/1281] lr: 4.345e-03, eta: 9:12:39, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.7147, loss: 1.7147 +2025-05-06 10:50:23,259 - pyskl - INFO - Saving checkpoint at 109 epochs +2025-05-06 10:51:18,592 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 10:51:18,649 - pyskl - INFO - +top1_acc 0.9167 +top5_acc 0.9944 +2025-05-06 10:51:18,649 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 10:51:18,656 - pyskl - INFO - +mean_acc 0.8867 +2025-05-06 10:51:18,712 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_102.pth was removed +2025-05-06 10:51:20,302 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_109.pth. +2025-05-06 10:51:20,302 - pyskl - INFO - Best top1_acc is 0.9167 at 109 epoch. +2025-05-06 10:51:20,308 - pyskl - INFO - Epoch(val) [109][533] top1_acc: 0.9167, top5_acc: 0.9944, mean_class_accuracy: 0.8867 +2025-05-06 10:52:28,819 - pyskl - INFO - Epoch [110][100/1281] lr: 4.317e-03, eta: 9:10:27, time: 0.685, data_time: 0.181, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.6579, loss: 1.6579 +2025-05-06 10:53:25,330 - pyskl - INFO - Epoch [110][200/1281] lr: 4.301e-03, eta: 9:09:22, time: 0.565, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.5910, loss: 1.5910 +2025-05-06 10:54:27,545 - pyskl - INFO - Epoch [110][300/1281] lr: 4.286e-03, eta: 9:08:19, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.6486, loss: 1.6486 +2025-05-06 10:55:37,934 - pyskl - INFO - Epoch [110][400/1281] lr: 4.271e-03, eta: 9:07:18, time: 0.704, data_time: 0.000, memory: 9000, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 1.7133, loss: 1.7133 +2025-05-06 10:56:42,437 - pyskl - INFO - Epoch [110][500/1281] lr: 4.255e-03, eta: 9:06:16, time: 0.645, data_time: 0.000, memory: 9000, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 1.6522, loss: 1.6522 +2025-05-06 10:57:42,632 - pyskl - INFO - Epoch [110][600/1281] lr: 4.240e-03, eta: 9:05:12, time: 0.602, data_time: 0.000, memory: 9000, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 1.7092, loss: 1.7092 +2025-05-06 10:58:43,862 - pyskl - INFO - Epoch [110][700/1281] lr: 4.225e-03, eta: 9:04:08, time: 0.612, data_time: 0.000, memory: 9000, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 1.6024, loss: 1.6024 +2025-05-06 10:59:50,424 - pyskl - INFO - Epoch [110][800/1281] lr: 4.209e-03, eta: 9:03:06, time: 0.666, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.6272, loss: 1.6272 +2025-05-06 11:00:58,926 - pyskl - INFO - Epoch [110][900/1281] lr: 4.194e-03, eta: 9:02:05, time: 0.685, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.5639, loss: 1.5639 +2025-05-06 11:02:00,378 - pyskl - INFO - Epoch [110][1000/1281] lr: 4.179e-03, eta: 9:01:02, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.5832, loss: 1.5832 +2025-05-06 11:03:01,430 - pyskl - INFO - Epoch [110][1100/1281] lr: 4.164e-03, eta: 8:59:58, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 1.6666, loss: 1.6666 +2025-05-06 11:04:04,959 - pyskl - INFO - Epoch [110][1200/1281] lr: 4.148e-03, eta: 8:58:55, time: 0.635, data_time: 0.000, memory: 9000, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 1.7086, loss: 1.7086 +2025-05-06 11:05:01,160 - pyskl - INFO - Saving checkpoint at 110 epochs +2025-05-06 11:05:53,509 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 11:05:53,565 - pyskl - INFO - +top1_acc 0.9222 +top5_acc 0.9928 +2025-05-06 11:05:53,565 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 11:05:53,572 - pyskl - INFO - +mean_acc 0.8950 +2025-05-06 11:05:53,629 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_109.pth was removed +2025-05-06 11:05:55,164 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_110.pth. +2025-05-06 11:05:55,165 - pyskl - INFO - Best top1_acc is 0.9222 at 110 epoch. +2025-05-06 11:05:55,169 - pyskl - INFO - Epoch(val) [110][533] top1_acc: 0.9222, top5_acc: 0.9928, mean_class_accuracy: 0.8950 +2025-05-06 11:07:03,525 - pyskl - INFO - Epoch [111][100/1281] lr: 4.121e-03, eta: 8:56:45, time: 0.684, data_time: 0.182, memory: 9000, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 1.6076, loss: 1.6076 +2025-05-06 11:08:01,968 - pyskl - INFO - Epoch [111][200/1281] lr: 4.106e-03, eta: 8:55:40, time: 0.584, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.6240, loss: 1.6240 +2025-05-06 11:09:06,192 - pyskl - INFO - Epoch [111][300/1281] lr: 4.091e-03, eta: 8:54:38, time: 0.642, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.6672, loss: 1.6672 +2025-05-06 11:10:12,851 - pyskl - INFO - Epoch [111][400/1281] lr: 4.075e-03, eta: 8:53:36, time: 0.667, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.6117, loss: 1.6117 +2025-05-06 11:11:14,129 - pyskl - INFO - Epoch [111][500/1281] lr: 4.060e-03, eta: 8:52:32, time: 0.613, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.5534, loss: 1.5534 +2025-05-06 11:12:14,564 - pyskl - INFO - Epoch [111][600/1281] lr: 4.045e-03, eta: 8:51:29, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 1.6249, loss: 1.6249 +2025-05-06 11:13:16,939 - pyskl - INFO - Epoch [111][700/1281] lr: 4.030e-03, eta: 8:50:25, time: 0.624, data_time: 0.000, memory: 9000, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 1.6450, loss: 1.6450 +2025-05-06 11:14:26,367 - pyskl - INFO - Epoch [111][800/1281] lr: 4.015e-03, eta: 8:49:25, time: 0.694, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.5832, loss: 1.5832 +2025-05-06 11:15:28,101 - pyskl - INFO - Epoch [111][900/1281] lr: 4.000e-03, eta: 8:48:21, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.6473, loss: 1.6473 +2025-05-06 11:16:28,438 - pyskl - INFO - Epoch [111][1000/1281] lr: 3.985e-03, eta: 8:47:17, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.5974, loss: 1.5974 +2025-05-06 11:17:28,760 - pyskl - INFO - Epoch [111][1100/1281] lr: 3.970e-03, eta: 8:46:13, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.6419, loss: 1.6419 +2025-05-06 11:18:34,349 - pyskl - INFO - Epoch [111][1200/1281] lr: 3.955e-03, eta: 8:45:11, time: 0.656, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.6450, loss: 1.6450 +2025-05-06 11:19:28,809 - pyskl - INFO - Saving checkpoint at 111 epochs +2025-05-06 11:20:20,216 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 11:20:20,269 - pyskl - INFO - +top1_acc 0.9156 +top5_acc 0.9925 +2025-05-06 11:20:20,269 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 11:20:20,275 - pyskl - INFO - +mean_acc 0.8896 +2025-05-06 11:20:20,277 - pyskl - INFO - Epoch(val) [111][533] top1_acc: 0.9156, top5_acc: 0.9925, mean_class_accuracy: 0.8896 +2025-05-06 11:21:28,514 - pyskl - INFO - Epoch [112][100/1281] lr: 3.928e-03, eta: 8:43:01, time: 0.682, data_time: 0.184, memory: 9000, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 1.6385, loss: 1.6385 +2025-05-06 11:22:27,329 - pyskl - INFO - Epoch [112][200/1281] lr: 3.914e-03, eta: 8:41:57, time: 0.588, data_time: 0.000, memory: 9000, top1_acc: 0.9825, top5_acc: 0.9994, loss_cls: 1.7390, loss: 1.7390 +2025-05-06 11:23:33,577 - pyskl - INFO - Epoch [112][300/1281] lr: 3.899e-03, eta: 8:40:55, time: 0.662, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.6689, loss: 1.6689 +2025-05-06 11:24:38,820 - pyskl - INFO - Epoch [112][400/1281] lr: 3.884e-03, eta: 8:39:53, time: 0.652, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.6236, loss: 1.6236 +2025-05-06 11:25:40,342 - pyskl - INFO - Epoch [112][500/1281] lr: 3.869e-03, eta: 8:38:50, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.6196, loss: 1.6196 +2025-05-06 11:26:41,945 - pyskl - INFO - Epoch [112][600/1281] lr: 3.854e-03, eta: 8:37:46, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.5941, loss: 1.5941 +2025-05-06 11:27:45,933 - pyskl - INFO - Epoch [112][700/1281] lr: 3.840e-03, eta: 8:36:44, time: 0.640, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.6276, loss: 1.6276 +2025-05-06 11:28:52,557 - pyskl - INFO - Epoch [112][800/1281] lr: 3.825e-03, eta: 8:35:42, time: 0.666, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.6355, loss: 1.6355 +2025-05-06 11:29:53,970 - pyskl - INFO - Epoch [112][900/1281] lr: 3.810e-03, eta: 8:34:38, time: 0.614, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.6344, loss: 1.6344 +2025-05-06 11:30:54,412 - pyskl - INFO - Epoch [112][1000/1281] lr: 3.795e-03, eta: 8:33:35, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 1.6501, loss: 1.6501 +2025-05-06 11:31:58,694 - pyskl - INFO - Epoch [112][1100/1281] lr: 3.781e-03, eta: 8:32:32, time: 0.643, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.6698, loss: 1.6698 +2025-05-06 11:33:08,473 - pyskl - INFO - Epoch [112][1200/1281] lr: 3.766e-03, eta: 8:31:32, time: 0.698, data_time: 0.000, memory: 9000, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 1.6678, loss: 1.6678 +2025-05-06 11:34:00,219 - pyskl - INFO - Saving checkpoint at 112 epochs +2025-05-06 11:34:51,175 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 11:34:51,231 - pyskl - INFO - +top1_acc 0.9159 +top5_acc 0.9939 +2025-05-06 11:34:51,231 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 11:34:51,239 - pyskl - INFO - +mean_acc 0.8853 +2025-05-06 11:34:51,242 - pyskl - INFO - Epoch(val) [112][533] top1_acc: 0.9159, top5_acc: 0.9939, mean_class_accuracy: 0.8853 +2025-05-06 11:35:59,763 - pyskl - INFO - Epoch [113][100/1281] lr: 3.740e-03, eta: 8:29:22, time: 0.685, data_time: 0.181, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.5962, loss: 1.5962 +2025-05-06 11:37:02,032 - pyskl - INFO - Epoch [113][200/1281] lr: 3.725e-03, eta: 8:28:19, time: 0.623, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.6246, loss: 1.6246 +2025-05-06 11:38:08,683 - pyskl - INFO - Epoch [113][300/1281] lr: 3.711e-03, eta: 8:27:17, time: 0.666, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.6425, loss: 1.6425 +2025-05-06 11:39:10,613 - pyskl - INFO - Epoch [113][400/1281] lr: 3.696e-03, eta: 8:26:14, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 1.6238, loss: 1.6238 +2025-05-06 11:40:11,051 - pyskl - INFO - Epoch [113][500/1281] lr: 3.682e-03, eta: 8:25:10, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 1.7164, loss: 1.7164 +2025-05-06 11:41:14,963 - pyskl - INFO - Epoch [113][600/1281] lr: 3.667e-03, eta: 8:24:08, time: 0.639, data_time: 0.000, memory: 9000, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 1.6040, loss: 1.6040 +2025-05-06 11:42:24,075 - pyskl - INFO - Epoch [113][700/1281] lr: 3.653e-03, eta: 8:23:07, time: 0.691, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.6048, loss: 1.6048 +2025-05-06 11:43:27,654 - pyskl - INFO - Epoch [113][800/1281] lr: 3.638e-03, eta: 8:22:04, time: 0.636, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.5907, loss: 1.5907 +2025-05-06 11:44:28,189 - pyskl - INFO - Epoch [113][900/1281] lr: 3.624e-03, eta: 8:21:01, time: 0.605, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.5928, loss: 1.5928 +2025-05-06 11:45:31,826 - pyskl - INFO - Epoch [113][1000/1281] lr: 3.610e-03, eta: 8:19:58, time: 0.636, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.5424, loss: 1.5424 +2025-05-06 11:46:38,499 - pyskl - INFO - Epoch [113][1100/1281] lr: 3.595e-03, eta: 8:18:56, time: 0.667, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.5858, loss: 1.5858 +2025-05-06 11:47:45,126 - pyskl - INFO - Epoch [113][1200/1281] lr: 3.581e-03, eta: 8:17:55, time: 0.666, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.6047, loss: 1.6047 +2025-05-06 11:48:35,482 - pyskl - INFO - Saving checkpoint at 113 epochs +2025-05-06 11:49:25,776 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 11:49:25,831 - pyskl - INFO - +top1_acc 0.9277 +top5_acc 0.9947 +2025-05-06 11:49:25,831 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 11:49:25,838 - pyskl - INFO - +mean_acc 0.9076 +2025-05-06 11:49:25,898 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_110.pth was removed +2025-05-06 11:49:27,437 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_113.pth. +2025-05-06 11:49:27,437 - pyskl - INFO - Best top1_acc is 0.9277 at 113 epoch. +2025-05-06 11:49:27,441 - pyskl - INFO - Epoch(val) [113][533] top1_acc: 0.9277, top5_acc: 0.9947, mean_class_accuracy: 0.9076 +2025-05-06 11:50:36,401 - pyskl - INFO - Epoch [114][100/1281] lr: 3.555e-03, eta: 8:15:46, time: 0.690, data_time: 0.178, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.5521, loss: 1.5521 +2025-05-06 11:51:39,503 - pyskl - INFO - Epoch [114][200/1281] lr: 3.541e-03, eta: 8:14:43, time: 0.631, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.5532, loss: 1.5532 +2025-05-06 11:52:43,367 - pyskl - INFO - Epoch [114][300/1281] lr: 3.526e-03, eta: 8:13:41, time: 0.639, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.5882, loss: 1.5882 +2025-05-06 11:53:43,755 - pyskl - INFO - Epoch [114][400/1281] lr: 3.512e-03, eta: 8:12:37, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.5347, loss: 1.5347 +2025-05-06 11:54:46,675 - pyskl - INFO - Epoch [114][500/1281] lr: 3.498e-03, eta: 8:11:34, time: 0.629, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.6217, loss: 1.6217 +2025-05-06 11:55:52,523 - pyskl - INFO - Epoch [114][600/1281] lr: 3.484e-03, eta: 8:10:32, time: 0.658, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.5750, loss: 1.5750 +2025-05-06 11:56:58,894 - pyskl - INFO - Epoch [114][700/1281] lr: 3.470e-03, eta: 8:09:30, time: 0.664, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.6030, loss: 1.6030 +2025-05-06 11:58:00,395 - pyskl - INFO - Epoch [114][800/1281] lr: 3.456e-03, eta: 8:08:27, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 1.6279, loss: 1.6279 +2025-05-06 11:59:02,206 - pyskl - INFO - Epoch [114][900/1281] lr: 3.442e-03, eta: 8:07:24, time: 0.618, data_time: 0.000, memory: 9000, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 1.6416, loss: 1.6416 +2025-05-06 12:00:03,899 - pyskl - INFO - Epoch [114][1000/1281] lr: 3.427e-03, eta: 8:06:20, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 1.6619, loss: 1.6619 +2025-05-06 12:01:10,723 - pyskl - INFO - Epoch [114][1100/1281] lr: 3.413e-03, eta: 8:05:19, time: 0.668, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.6427, loss: 1.6427 +2025-05-06 12:02:13,248 - pyskl - INFO - Epoch [114][1200/1281] lr: 3.399e-03, eta: 8:04:16, time: 0.625, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.5808, loss: 1.5808 +2025-05-06 12:03:02,961 - pyskl - INFO - Saving checkpoint at 114 epochs +2025-05-06 12:03:54,875 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 12:03:54,929 - pyskl - INFO - +top1_acc 0.9220 +top5_acc 0.9941 +2025-05-06 12:03:54,929 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 12:03:54,936 - pyskl - INFO - +mean_acc 0.8962 +2025-05-06 12:03:54,938 - pyskl - INFO - Epoch(val) [114][533] top1_acc: 0.9220, top5_acc: 0.9941, mean_class_accuracy: 0.8962 +2025-05-06 12:05:06,875 - pyskl - INFO - Epoch [115][100/1281] lr: 3.374e-03, eta: 8:02:09, time: 0.719, data_time: 0.178, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.5934, loss: 1.5934 +2025-05-06 12:06:10,981 - pyskl - INFO - Epoch [115][200/1281] lr: 3.360e-03, eta: 8:01:06, time: 0.641, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.5751, loss: 1.5751 +2025-05-06 12:07:12,346 - pyskl - INFO - Epoch [115][300/1281] lr: 3.346e-03, eta: 8:00:03, time: 0.614, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.5621, loss: 1.5621 +2025-05-06 12:08:13,411 - pyskl - INFO - Epoch [115][400/1281] lr: 3.332e-03, eta: 7:58:59, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.6148, loss: 1.6148 +2025-05-06 12:09:17,541 - pyskl - INFO - Epoch [115][500/1281] lr: 3.318e-03, eta: 7:57:57, time: 0.641, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.5619, loss: 1.5619 +2025-05-06 12:10:25,200 - pyskl - INFO - Epoch [115][600/1281] lr: 3.305e-03, eta: 7:56:56, time: 0.677, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.5598, loss: 1.5598 +2025-05-06 12:11:28,812 - pyskl - INFO - Epoch [115][700/1281] lr: 3.291e-03, eta: 7:55:53, time: 0.636, data_time: 0.000, memory: 9000, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 1.6245, loss: 1.6245 +2025-05-06 12:12:29,581 - pyskl - INFO - Epoch [115][800/1281] lr: 3.277e-03, eta: 7:54:49, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.6194, loss: 1.6194 +2025-05-06 12:13:34,045 - pyskl - INFO - Epoch [115][900/1281] lr: 3.263e-03, eta: 7:53:47, time: 0.645, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.6331, loss: 1.6331 +2025-05-06 12:14:40,955 - pyskl - INFO - Epoch [115][1000/1281] lr: 3.249e-03, eta: 7:52:45, time: 0.669, data_time: 0.000, memory: 9000, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 1.6017, loss: 1.6017 +2025-05-06 12:15:45,685 - pyskl - INFO - Epoch [115][1100/1281] lr: 3.236e-03, eta: 7:51:43, time: 0.647, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.5748, loss: 1.5748 +2025-05-06 12:16:46,050 - pyskl - INFO - Epoch [115][1200/1281] lr: 3.222e-03, eta: 7:50:40, time: 0.604, data_time: 0.000, memory: 9000, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 1.6124, loss: 1.6124 +2025-05-06 12:17:37,037 - pyskl - INFO - Saving checkpoint at 115 epochs +2025-05-06 12:18:29,141 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 12:18:29,196 - pyskl - INFO - +top1_acc 0.9208 +top5_acc 0.9946 +2025-05-06 12:18:29,196 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 12:18:29,203 - pyskl - INFO - +mean_acc 0.8942 +2025-05-06 12:18:29,205 - pyskl - INFO - Epoch(val) [115][533] top1_acc: 0.9208, top5_acc: 0.9946, mean_class_accuracy: 0.8942 +2025-05-06 12:19:42,826 - pyskl - INFO - Epoch [116][100/1281] lr: 3.197e-03, eta: 7:48:34, time: 0.736, data_time: 0.180, memory: 9000, top1_acc: 0.9944, top5_acc: 0.9994, loss_cls: 1.6544, loss: 1.6544 +2025-05-06 12:20:43,051 - pyskl - INFO - Epoch [116][200/1281] lr: 3.184e-03, eta: 7:47:30, time: 0.602, data_time: 0.000, memory: 9000, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 1.6095, loss: 1.6095 +2025-05-06 12:21:44,189 - pyskl - INFO - Epoch [116][300/1281] lr: 3.170e-03, eta: 7:46:27, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.5638, loss: 1.5638 +2025-05-06 12:22:48,817 - pyskl - INFO - Epoch [116][400/1281] lr: 3.156e-03, eta: 7:45:24, time: 0.646, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.6235, loss: 1.6235 +2025-05-06 12:23:54,160 - pyskl - INFO - Epoch [116][500/1281] lr: 3.143e-03, eta: 7:44:22, time: 0.653, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.5699, loss: 1.5699 +2025-05-06 12:24:59,134 - pyskl - INFO - Epoch [116][600/1281] lr: 3.129e-03, eta: 7:43:20, time: 0.650, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.5287, loss: 1.5287 +2025-05-06 12:25:59,915 - pyskl - INFO - Epoch [116][700/1281] lr: 3.116e-03, eta: 7:42:16, time: 0.608, data_time: 0.000, memory: 9000, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 1.5800, loss: 1.5800 +2025-05-06 12:27:01,952 - pyskl - INFO - Epoch [116][800/1281] lr: 3.102e-03, eta: 7:41:13, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.5913, loss: 1.5913 +2025-05-06 12:28:06,459 - pyskl - INFO - Epoch [116][900/1281] lr: 3.089e-03, eta: 7:40:11, time: 0.645, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.5855, loss: 1.5855 +2025-05-06 12:29:11,673 - pyskl - INFO - Epoch [116][1000/1281] lr: 3.075e-03, eta: 7:39:09, time: 0.652, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.6184, loss: 1.6184 +2025-05-06 12:30:14,054 - pyskl - INFO - Epoch [116][1100/1281] lr: 3.062e-03, eta: 7:38:06, time: 0.624, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.5581, loss: 1.5581 +2025-05-06 12:31:16,244 - pyskl - INFO - Epoch [116][1200/1281] lr: 3.049e-03, eta: 7:37:03, time: 0.622, data_time: 0.000, memory: 9000, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 1.5727, loss: 1.5727 +2025-05-06 12:32:08,031 - pyskl - INFO - Saving checkpoint at 116 epochs +2025-05-06 12:33:01,279 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 12:33:01,334 - pyskl - INFO - +top1_acc 0.9227 +top5_acc 0.9940 +2025-05-06 12:33:01,334 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 12:33:01,342 - pyskl - INFO - +mean_acc 0.8953 +2025-05-06 12:33:01,345 - pyskl - INFO - Epoch(val) [116][533] top1_acc: 0.9227, top5_acc: 0.9940, mean_class_accuracy: 0.8953 +2025-05-06 12:34:12,811 - pyskl - INFO - Epoch [117][100/1281] lr: 3.024e-03, eta: 7:34:57, time: 0.715, data_time: 0.180, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.5815, loss: 1.5815 +2025-05-06 12:35:12,459 - pyskl - INFO - Epoch [117][200/1281] lr: 3.011e-03, eta: 7:33:53, time: 0.596, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.5854, loss: 1.5854 +2025-05-06 12:36:15,283 - pyskl - INFO - Epoch [117][300/1281] lr: 2.998e-03, eta: 7:32:50, time: 0.628, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.5457, loss: 1.5457 +2025-05-06 12:37:20,578 - pyskl - INFO - Epoch [117][400/1281] lr: 2.984e-03, eta: 7:31:48, time: 0.653, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.5436, loss: 1.5436 +2025-05-06 12:38:26,611 - pyskl - INFO - Epoch [117][500/1281] lr: 2.971e-03, eta: 7:30:46, time: 0.660, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.5101, loss: 1.5101 +2025-05-06 12:39:28,220 - pyskl - INFO - Epoch [117][600/1281] lr: 2.958e-03, eta: 7:29:43, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.5721, loss: 1.5721 +2025-05-06 12:40:29,667 - pyskl - INFO - Epoch [117][700/1281] lr: 2.945e-03, eta: 7:28:40, time: 0.614, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.5140, loss: 1.5140 +2025-05-06 12:41:35,310 - pyskl - INFO - Epoch [117][800/1281] lr: 2.932e-03, eta: 7:27:38, time: 0.656, data_time: 0.000, memory: 9000, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 1.6164, loss: 1.6164 +2025-05-06 12:42:40,886 - pyskl - INFO - Epoch [117][900/1281] lr: 2.919e-03, eta: 7:26:36, time: 0.656, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.5686, loss: 1.5686 +2025-05-06 12:43:44,611 - pyskl - INFO - Epoch [117][1000/1281] lr: 2.905e-03, eta: 7:25:33, time: 0.637, data_time: 0.000, memory: 9000, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 1.5553, loss: 1.5553 +2025-05-06 12:44:45,272 - pyskl - INFO - Epoch [117][1100/1281] lr: 2.892e-03, eta: 7:24:30, time: 0.607, data_time: 0.000, memory: 9000, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 1.5552, loss: 1.5552 +2025-05-06 12:45:47,938 - pyskl - INFO - Epoch [117][1200/1281] lr: 2.879e-03, eta: 7:23:27, time: 0.627, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.5694, loss: 1.5694 +2025-05-06 12:46:38,899 - pyskl - INFO - Saving checkpoint at 117 epochs +2025-05-06 12:47:31,576 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 12:47:31,631 - pyskl - INFO - +top1_acc 0.9210 +top5_acc 0.9948 +2025-05-06 12:47:31,631 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 12:47:31,639 - pyskl - INFO - +mean_acc 0.8957 +2025-05-06 12:47:31,641 - pyskl - INFO - Epoch(val) [117][533] top1_acc: 0.9210, top5_acc: 0.9948, mean_class_accuracy: 0.8957 +2025-05-06 12:48:41,795 - pyskl - INFO - Epoch [118][100/1281] lr: 2.856e-03, eta: 7:21:21, time: 0.701, data_time: 0.179, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.5170, loss: 1.5170 +2025-05-06 12:49:39,672 - pyskl - INFO - Epoch [118][200/1281] lr: 2.843e-03, eta: 7:20:17, time: 0.579, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.5051, loss: 1.5051 +2025-05-06 12:50:42,677 - pyskl - INFO - Epoch [118][300/1281] lr: 2.830e-03, eta: 7:19:14, time: 0.630, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.5519, loss: 1.5519 +2025-05-06 12:51:48,484 - pyskl - INFO - Epoch [118][400/1281] lr: 2.817e-03, eta: 7:18:12, time: 0.658, data_time: 0.000, memory: 9000, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 1.5979, loss: 1.5979 +2025-05-06 12:52:53,412 - pyskl - INFO - Epoch [118][500/1281] lr: 2.804e-03, eta: 7:17:10, time: 0.649, data_time: 0.000, memory: 9000, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 1.5028, loss: 1.5028 +2025-05-06 12:53:54,400 - pyskl - INFO - Epoch [118][600/1281] lr: 2.791e-03, eta: 7:16:07, time: 0.610, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.4644, loss: 1.4644 +2025-05-06 12:54:56,692 - pyskl - INFO - Epoch [118][700/1281] lr: 2.778e-03, eta: 7:15:04, time: 0.623, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.5209, loss: 1.5209 +2025-05-06 12:55:59,049 - pyskl - INFO - Epoch [118][800/1281] lr: 2.765e-03, eta: 7:14:01, time: 0.624, data_time: 0.000, memory: 9000, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 1.5460, loss: 1.5460 +2025-05-06 12:57:03,655 - pyskl - INFO - Epoch [118][900/1281] lr: 2.753e-03, eta: 7:12:58, time: 0.646, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.5277, loss: 1.5277 +2025-05-06 12:58:06,336 - pyskl - INFO - Epoch [118][1000/1281] lr: 2.740e-03, eta: 7:11:56, time: 0.627, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.5130, loss: 1.5130 +2025-05-06 12:59:09,039 - pyskl - INFO - Epoch [118][1100/1281] lr: 2.727e-03, eta: 7:10:53, time: 0.627, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.4831, loss: 1.4831 +2025-05-06 13:00:11,801 - pyskl - INFO - Epoch [118][1200/1281] lr: 2.714e-03, eta: 7:09:50, time: 0.628, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.5320, loss: 1.5320 +2025-05-06 13:01:04,047 - pyskl - INFO - Saving checkpoint at 118 epochs +2025-05-06 13:01:56,328 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 13:01:56,383 - pyskl - INFO - +top1_acc 0.9224 +top5_acc 0.9935 +2025-05-06 13:01:56,383 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 13:01:56,389 - pyskl - INFO - +mean_acc 0.8987 +2025-05-06 13:01:56,391 - pyskl - INFO - Epoch(val) [118][533] top1_acc: 0.9224, top5_acc: 0.9935, mean_class_accuracy: 0.8987 +2025-05-06 13:03:05,893 - pyskl - INFO - Epoch [119][100/1281] lr: 2.691e-03, eta: 7:07:44, time: 0.695, data_time: 0.180, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.5114, loss: 1.5114 +2025-05-06 13:04:05,626 - pyskl - INFO - Epoch [119][200/1281] lr: 2.679e-03, eta: 7:06:41, time: 0.597, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.5326, loss: 1.5326 +2025-05-06 13:05:06,633 - pyskl - INFO - Epoch [119][300/1281] lr: 2.666e-03, eta: 7:05:38, time: 0.610, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4630, loss: 1.4630 +2025-05-06 13:06:10,150 - pyskl - INFO - Epoch [119][400/1281] lr: 2.653e-03, eta: 7:04:35, time: 0.635, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.5158, loss: 1.5158 +2025-05-06 13:07:13,395 - pyskl - INFO - Epoch [119][500/1281] lr: 2.641e-03, eta: 7:03:32, time: 0.632, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4567, loss: 1.4567 +2025-05-06 13:08:13,707 - pyskl - INFO - Epoch [119][600/1281] lr: 2.628e-03, eta: 7:02:29, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.5089, loss: 1.5089 +2025-05-06 13:09:17,122 - pyskl - INFO - Epoch [119][700/1281] lr: 2.616e-03, eta: 7:01:26, time: 0.634, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.4760, loss: 1.4760 +2025-05-06 13:10:23,434 - pyskl - INFO - Epoch [119][800/1281] lr: 2.603e-03, eta: 7:00:25, time: 0.663, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.5350, loss: 1.5350 +2025-05-06 13:11:29,250 - pyskl - INFO - Epoch [119][900/1281] lr: 2.591e-03, eta: 6:59:23, time: 0.658, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4721, loss: 1.4721 +2025-05-06 13:12:30,817 - pyskl - INFO - Epoch [119][1000/1281] lr: 2.578e-03, eta: 6:58:20, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.5023, loss: 1.5023 +2025-05-06 13:13:34,473 - pyskl - INFO - Epoch [119][1100/1281] lr: 2.566e-03, eta: 6:57:17, time: 0.637, data_time: 0.000, memory: 9000, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 1.5269, loss: 1.5269 +2025-05-06 13:14:40,161 - pyskl - INFO - Epoch [119][1200/1281] lr: 2.554e-03, eta: 6:56:15, time: 0.657, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.5100, loss: 1.5100 +2025-05-06 13:15:34,751 - pyskl - INFO - Saving checkpoint at 119 epochs +2025-05-06 13:16:26,978 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 13:16:27,033 - pyskl - INFO - +top1_acc 0.9259 +top5_acc 0.9954 +2025-05-06 13:16:27,033 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 13:16:27,039 - pyskl - INFO - +mean_acc 0.9026 +2025-05-06 13:16:27,041 - pyskl - INFO - Epoch(val) [119][533] top1_acc: 0.9259, top5_acc: 0.9954, mean_class_accuracy: 0.9026 +2025-05-06 13:17:36,522 - pyskl - INFO - Epoch [120][100/1281] lr: 2.531e-03, eta: 6:54:10, time: 0.695, data_time: 0.178, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4382, loss: 1.4382 +2025-05-06 13:18:36,140 - pyskl - INFO - Epoch [120][200/1281] lr: 2.519e-03, eta: 6:53:06, time: 0.596, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.5072, loss: 1.5072 +2025-05-06 13:19:38,523 - pyskl - INFO - Epoch [120][300/1281] lr: 2.507e-03, eta: 6:52:04, time: 0.624, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4314, loss: 1.4314 +2025-05-06 13:20:43,310 - pyskl - INFO - Epoch [120][400/1281] lr: 2.494e-03, eta: 6:51:01, time: 0.648, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4840, loss: 1.4840 +2025-05-06 13:21:45,211 - pyskl - INFO - Epoch [120][500/1281] lr: 2.482e-03, eta: 6:49:58, time: 0.619, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4789, loss: 1.4789 +2025-05-06 13:22:48,348 - pyskl - INFO - Epoch [120][600/1281] lr: 2.470e-03, eta: 6:48:56, time: 0.631, data_time: 0.000, memory: 9000, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 1.4679, loss: 1.4679 +2025-05-06 13:23:50,893 - pyskl - INFO - Epoch [120][700/1281] lr: 2.458e-03, eta: 6:47:53, time: 0.625, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.5055, loss: 1.5055 +2025-05-06 13:24:54,432 - pyskl - INFO - Epoch [120][800/1281] lr: 2.446e-03, eta: 6:46:51, time: 0.635, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.5401, loss: 1.5401 +2025-05-06 13:25:56,459 - pyskl - INFO - Epoch [120][900/1281] lr: 2.433e-03, eta: 6:45:48, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.5380, loss: 1.5380 +2025-05-06 13:26:58,774 - pyskl - INFO - Epoch [120][1000/1281] lr: 2.421e-03, eta: 6:44:45, time: 0.623, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4731, loss: 1.4731 +2025-05-06 13:28:03,230 - pyskl - INFO - Epoch [120][1100/1281] lr: 2.409e-03, eta: 6:43:42, time: 0.645, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.5124, loss: 1.5124 +2025-05-06 13:29:10,006 - pyskl - INFO - Epoch [120][1200/1281] lr: 2.397e-03, eta: 6:42:41, time: 0.668, data_time: 0.000, memory: 9000, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 1.4796, loss: 1.4796 +2025-05-06 13:30:02,840 - pyskl - INFO - Saving checkpoint at 120 epochs +2025-05-06 13:30:53,894 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 13:30:53,949 - pyskl - INFO - +top1_acc 0.9268 +top5_acc 0.9947 +2025-05-06 13:30:53,949 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 13:30:53,957 - pyskl - INFO - +mean_acc 0.9019 +2025-05-06 13:30:53,960 - pyskl - INFO - Epoch(val) [120][533] top1_acc: 0.9268, top5_acc: 0.9947, mean_class_accuracy: 0.9019 +2025-05-06 13:32:03,806 - pyskl - INFO - Epoch [121][100/1281] lr: 2.375e-03, eta: 6:40:36, time: 0.698, data_time: 0.176, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.5100, loss: 1.5100 +2025-05-06 13:33:04,509 - pyskl - INFO - Epoch [121][200/1281] lr: 2.363e-03, eta: 6:39:33, time: 0.607, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4530, loss: 1.4530 +2025-05-06 13:34:09,611 - pyskl - INFO - Epoch [121][300/1281] lr: 2.351e-03, eta: 6:38:31, time: 0.651, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4956, loss: 1.4956 +2025-05-06 13:35:14,150 - pyskl - INFO - Epoch [121][400/1281] lr: 2.340e-03, eta: 6:37:29, time: 0.645, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4456, loss: 1.4456 +2025-05-06 13:36:15,756 - pyskl - INFO - Epoch [121][500/1281] lr: 2.328e-03, eta: 6:36:26, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.4629, loss: 1.4629 +2025-05-06 13:37:19,105 - pyskl - INFO - Epoch [121][600/1281] lr: 2.316e-03, eta: 6:35:23, time: 0.633, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4440, loss: 1.4440 +2025-05-06 13:38:24,053 - pyskl - INFO - Epoch [121][700/1281] lr: 2.304e-03, eta: 6:34:21, time: 0.649, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.4719, loss: 1.4719 +2025-05-06 13:39:29,514 - pyskl - INFO - Epoch [121][800/1281] lr: 2.292e-03, eta: 6:33:19, time: 0.655, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4297, loss: 1.4297 +2025-05-06 13:40:30,971 - pyskl - INFO - Epoch [121][900/1281] lr: 2.280e-03, eta: 6:32:16, time: 0.615, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4650, loss: 1.4650 +2025-05-06 13:41:34,868 - pyskl - INFO - Epoch [121][1000/1281] lr: 2.269e-03, eta: 6:31:13, time: 0.639, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4863, loss: 1.4863 +2025-05-06 13:42:40,222 - pyskl - INFO - Epoch [121][1100/1281] lr: 2.257e-03, eta: 6:30:11, time: 0.654, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3977, loss: 1.3977 +2025-05-06 13:43:45,597 - pyskl - INFO - Epoch [121][1200/1281] lr: 2.245e-03, eta: 6:29:09, time: 0.654, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.4461, loss: 1.4461 +2025-05-06 13:44:37,500 - pyskl - INFO - Saving checkpoint at 121 epochs +2025-05-06 13:45:28,494 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 13:45:28,549 - pyskl - INFO - +top1_acc 0.9309 +top5_acc 0.9953 +2025-05-06 13:45:28,550 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 13:45:28,557 - pyskl - INFO - +mean_acc 0.9101 +2025-05-06 13:45:28,625 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_113.pth was removed +2025-05-06 13:45:30,173 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_121.pth. +2025-05-06 13:45:30,174 - pyskl - INFO - Best top1_acc is 0.9309 at 121 epoch. +2025-05-06 13:45:30,180 - pyskl - INFO - Epoch(val) [121][533] top1_acc: 0.9309, top5_acc: 0.9953, mean_class_accuracy: 0.9101 +2025-05-06 13:46:43,128 - pyskl - INFO - Epoch [122][100/1281] lr: 2.224e-03, eta: 6:27:06, time: 0.729, data_time: 0.184, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4910, loss: 1.4910 +2025-05-06 13:47:44,319 - pyskl - INFO - Epoch [122][200/1281] lr: 2.212e-03, eta: 6:26:03, time: 0.612, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4131, loss: 1.4131 +2025-05-06 13:48:43,908 - pyskl - INFO - Epoch [122][300/1281] lr: 2.201e-03, eta: 6:25:00, time: 0.596, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.5057, loss: 1.5057 +2025-05-06 13:49:45,013 - pyskl - INFO - Epoch [122][400/1281] lr: 2.189e-03, eta: 6:23:57, time: 0.611, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4744, loss: 1.4744 +2025-05-06 13:50:52,490 - pyskl - INFO - Epoch [122][500/1281] lr: 2.178e-03, eta: 6:22:55, time: 0.675, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.5001, loss: 1.5001 +2025-05-06 13:52:00,513 - pyskl - INFO - Epoch [122][600/1281] lr: 2.166e-03, eta: 6:21:54, time: 0.680, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.4794, loss: 1.4794 +2025-05-06 13:53:04,331 - pyskl - INFO - Epoch [122][700/1281] lr: 2.155e-03, eta: 6:20:51, time: 0.638, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4785, loss: 1.4785 +2025-05-06 13:54:06,008 - pyskl - INFO - Epoch [122][800/1281] lr: 2.143e-03, eta: 6:19:48, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.4946, loss: 1.4946 +2025-05-06 13:55:10,490 - pyskl - INFO - Epoch [122][900/1281] lr: 2.132e-03, eta: 6:18:46, time: 0.645, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.5162, loss: 1.5162 +2025-05-06 13:56:16,816 - pyskl - INFO - Epoch [122][1000/1281] lr: 2.120e-03, eta: 6:17:44, time: 0.663, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.4637, loss: 1.4637 +2025-05-06 13:57:21,505 - pyskl - INFO - Epoch [122][1100/1281] lr: 2.109e-03, eta: 6:16:42, time: 0.647, data_time: 0.000, memory: 9000, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 1.4660, loss: 1.4660 +2025-05-06 13:58:22,897 - pyskl - INFO - Epoch [122][1200/1281] lr: 2.098e-03, eta: 6:15:39, time: 0.614, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4024, loss: 1.4024 +2025-05-06 13:59:12,359 - pyskl - INFO - Saving checkpoint at 122 epochs +2025-05-06 14:00:06,321 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 14:00:06,377 - pyskl - INFO - +top1_acc 0.9166 +top5_acc 0.9933 +2025-05-06 14:00:06,377 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 14:00:06,385 - pyskl - INFO - +mean_acc 0.8972 +2025-05-06 14:00:06,387 - pyskl - INFO - Epoch(val) [122][533] top1_acc: 0.9166, top5_acc: 0.9933, mean_class_accuracy: 0.8972 +2025-05-06 14:01:19,604 - pyskl - INFO - Epoch [123][100/1281] lr: 2.077e-03, eta: 6:13:36, time: 0.732, data_time: 0.192, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.4744, loss: 1.4744 +2025-05-06 14:02:18,722 - pyskl - INFO - Epoch [123][200/1281] lr: 2.066e-03, eta: 6:12:33, time: 0.591, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.5079, loss: 1.5079 +2025-05-06 14:03:18,731 - pyskl - INFO - Epoch [123][300/1281] lr: 2.055e-03, eta: 6:11:29, time: 0.600, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.4773, loss: 1.4773 +2025-05-06 14:04:22,775 - pyskl - INFO - Epoch [123][400/1281] lr: 2.044e-03, eta: 6:10:27, time: 0.640, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4708, loss: 1.4708 +2025-05-06 14:05:33,221 - pyskl - INFO - Epoch [123][500/1281] lr: 2.032e-03, eta: 6:09:26, time: 0.704, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.4619, loss: 1.4619 +2025-05-06 14:06:37,460 - pyskl - INFO - Epoch [123][600/1281] lr: 2.021e-03, eta: 6:08:24, time: 0.642, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4751, loss: 1.4751 +2025-05-06 14:07:39,039 - pyskl - INFO - Epoch [123][700/1281] lr: 2.010e-03, eta: 6:07:21, time: 0.616, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4176, loss: 1.4176 +2025-05-06 14:08:40,439 - pyskl - INFO - Epoch [123][800/1281] lr: 1.999e-03, eta: 6:06:18, time: 0.614, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4233, loss: 1.4233 +2025-05-06 14:09:46,066 - pyskl - INFO - Epoch [123][900/1281] lr: 1.988e-03, eta: 6:05:16, time: 0.656, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.4785, loss: 1.4785 +2025-05-06 14:10:50,933 - pyskl - INFO - Epoch [123][1000/1281] lr: 1.977e-03, eta: 6:04:14, time: 0.649, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.4658, loss: 1.4658 +2025-05-06 14:11:52,607 - pyskl - INFO - Epoch [123][1100/1281] lr: 1.966e-03, eta: 6:03:11, time: 0.617, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4484, loss: 1.4484 +2025-05-06 14:12:52,942 - pyskl - INFO - Epoch [123][1200/1281] lr: 1.955e-03, eta: 6:02:08, time: 0.603, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4603, loss: 1.4603 +2025-05-06 14:13:44,010 - pyskl - INFO - Saving checkpoint at 123 epochs +2025-05-06 14:14:39,347 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 14:14:39,402 - pyskl - INFO - +top1_acc 0.9306 +top5_acc 0.9948 +2025-05-06 14:14:39,403 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 14:14:39,409 - pyskl - INFO - +mean_acc 0.9111 +2025-05-06 14:14:39,412 - pyskl - INFO - Epoch(val) [123][533] top1_acc: 0.9306, top5_acc: 0.9948, mean_class_accuracy: 0.9111 +2025-05-06 14:15:52,334 - pyskl - INFO - Epoch [124][100/1281] lr: 1.935e-03, eta: 6:00:05, time: 0.729, data_time: 0.186, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4410, loss: 1.4410 +2025-05-06 14:16:52,140 - pyskl - INFO - Epoch [124][200/1281] lr: 1.924e-03, eta: 5:59:02, time: 0.598, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4615, loss: 1.4615 +2025-05-06 14:17:52,783 - pyskl - INFO - Epoch [124][300/1281] lr: 1.913e-03, eta: 5:57:59, time: 0.606, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.4834, loss: 1.4834 +2025-05-06 14:19:01,447 - pyskl - INFO - Epoch [124][400/1281] lr: 1.902e-03, eta: 5:56:58, time: 0.687, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.4313, loss: 1.4313 +2025-05-06 14:20:03,479 - pyskl - INFO - Epoch [124][500/1281] lr: 1.892e-03, eta: 5:55:55, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.4932, loss: 1.4932 +2025-05-06 14:21:04,639 - pyskl - INFO - Epoch [124][600/1281] lr: 1.881e-03, eta: 5:54:52, time: 0.612, data_time: 0.000, memory: 9000, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 1.4888, loss: 1.4888 +2025-05-06 14:22:03,865 - pyskl - INFO - Epoch [124][700/1281] lr: 1.870e-03, eta: 5:53:48, time: 0.592, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.4734, loss: 1.4734 +2025-05-06 14:23:14,115 - pyskl - INFO - Epoch [124][800/1281] lr: 1.859e-03, eta: 5:52:47, time: 0.702, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.4868, loss: 1.4868 +2025-05-06 14:24:21,662 - pyskl - INFO - Epoch [124][900/1281] lr: 1.849e-03, eta: 5:51:46, time: 0.675, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4318, loss: 1.4318 +2025-05-06 14:25:23,675 - pyskl - INFO - Epoch [124][1000/1281] lr: 1.838e-03, eta: 5:50:43, time: 0.620, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4232, loss: 1.4232 +2025-05-06 14:26:30,666 - pyskl - INFO - Epoch [124][1100/1281] lr: 1.827e-03, eta: 5:49:41, time: 0.670, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4176, loss: 1.4176 +2025-05-06 14:27:49,369 - pyskl - INFO - Epoch [124][1200/1281] lr: 1.817e-03, eta: 5:48:42, time: 0.787, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4748, loss: 1.4748 +2025-05-06 14:28:46,041 - pyskl - INFO - Saving checkpoint at 124 epochs +2025-05-06 14:29:39,194 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 14:29:39,247 - pyskl - INFO - +top1_acc 0.9272 +top5_acc 0.9959 +2025-05-06 14:29:39,248 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 14:29:39,254 - pyskl - INFO - +mean_acc 0.9042 +2025-05-06 14:29:39,256 - pyskl - INFO - Epoch(val) [124][533] top1_acc: 0.9272, top5_acc: 0.9959, mean_class_accuracy: 0.9042 +2025-05-06 14:30:49,944 - pyskl - INFO - Epoch [125][100/1281] lr: 1.797e-03, eta: 5:46:40, time: 0.707, data_time: 0.177, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.3874, loss: 1.3874 +2025-05-06 14:32:04,142 - pyskl - INFO - Epoch [125][200/1281] lr: 1.787e-03, eta: 5:45:39, time: 0.742, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3904, loss: 1.3904 +2025-05-06 14:33:13,147 - pyskl - INFO - Epoch [125][300/1281] lr: 1.776e-03, eta: 5:44:38, time: 0.690, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4093, loss: 1.4093 +2025-05-06 14:34:16,143 - pyskl - INFO - Epoch [125][400/1281] lr: 1.766e-03, eta: 5:43:36, time: 0.630, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.5256, loss: 1.5256 +2025-05-06 14:35:17,922 - pyskl - INFO - Epoch [125][500/1281] lr: 1.755e-03, eta: 5:42:33, time: 0.618, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4159, loss: 1.4159 +2025-05-06 14:36:39,525 - pyskl - INFO - Epoch [125][600/1281] lr: 1.745e-03, eta: 5:41:34, time: 0.816, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4011, loss: 1.4011 +2025-05-06 14:37:47,917 - pyskl - INFO - Epoch [125][700/1281] lr: 1.735e-03, eta: 5:40:32, time: 0.684, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4323, loss: 1.4323 +2025-05-06 14:38:57,873 - pyskl - INFO - Epoch [125][800/1281] lr: 1.724e-03, eta: 5:39:31, time: 0.700, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3995, loss: 1.3995 +2025-05-06 14:40:03,927 - pyskl - INFO - Epoch [125][900/1281] lr: 1.714e-03, eta: 5:38:29, time: 0.661, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.4282, loss: 1.4282 +2025-05-06 14:41:52,589 - pyskl - INFO - Epoch [125][1000/1281] lr: 1.704e-03, eta: 5:37:36, time: 1.087, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4666, loss: 1.4666 +2025-05-06 14:43:58,177 - pyskl - INFO - Epoch [125][1100/1281] lr: 1.693e-03, eta: 5:36:46, time: 1.256, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4360, loss: 1.4360 +2025-05-06 14:46:11,389 - pyskl - INFO - Epoch [125][1200/1281] lr: 1.683e-03, eta: 5:35:57, time: 1.332, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4209, loss: 1.4209 +2025-05-06 14:48:00,850 - pyskl - INFO - Saving checkpoint at 125 epochs +2025-05-06 14:49:42,608 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 14:49:42,659 - pyskl - INFO - +top1_acc 0.9317 +top5_acc 0.9958 +2025-05-06 14:49:42,659 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 14:49:42,665 - pyskl - INFO - +mean_acc 0.9100 +2025-05-06 14:49:42,721 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_121.pth was removed +2025-05-06 14:49:44,193 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_125.pth. +2025-05-06 14:49:44,194 - pyskl - INFO - Best top1_acc is 0.9317 at 125 epoch. +2025-05-06 14:49:44,198 - pyskl - INFO - Epoch(val) [125][533] top1_acc: 0.9317, top5_acc: 0.9958, mean_class_accuracy: 0.9100 +2025-05-06 14:52:08,322 - pyskl - INFO - Epoch [126][100/1281] lr: 1.665e-03, eta: 5:34:10, time: 1.441, data_time: 0.172, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3926, loss: 1.3926 +2025-05-06 14:54:24,349 - pyskl - INFO - Epoch [126][200/1281] lr: 1.654e-03, eta: 5:33:21, time: 1.360, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4368, loss: 1.4368 +2025-05-06 14:56:39,909 - pyskl - INFO - Epoch [126][300/1281] lr: 1.644e-03, eta: 5:32:33, time: 1.356, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4359, loss: 1.4359 +2025-05-06 14:58:56,108 - pyskl - INFO - Epoch [126][400/1281] lr: 1.634e-03, eta: 5:31:45, time: 1.362, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4066, loss: 1.4066 +2025-05-06 15:01:13,464 - pyskl - INFO - Epoch [126][500/1281] lr: 1.624e-03, eta: 5:30:56, time: 1.374, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3786, loss: 1.3786 +2025-05-06 15:03:30,396 - pyskl - INFO - Epoch [126][600/1281] lr: 1.614e-03, eta: 5:30:08, time: 1.369, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4295, loss: 1.4295 +2025-05-06 15:05:49,112 - pyskl - INFO - Epoch [126][700/1281] lr: 1.604e-03, eta: 5:29:19, time: 1.387, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3964, loss: 1.3964 +2025-05-06 15:08:06,486 - pyskl - INFO - Epoch [126][800/1281] lr: 1.594e-03, eta: 5:28:31, time: 1.374, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4135, loss: 1.4135 +2025-05-06 15:10:23,595 - pyskl - INFO - Epoch [126][900/1281] lr: 1.584e-03, eta: 5:27:42, time: 1.371, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4049, loss: 1.4049 +2025-05-06 15:12:42,159 - pyskl - INFO - Epoch [126][1000/1281] lr: 1.574e-03, eta: 5:26:53, time: 1.386, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4491, loss: 1.4491 +2025-05-06 15:14:58,346 - pyskl - INFO - Epoch [126][1100/1281] lr: 1.564e-03, eta: 5:26:04, time: 1.362, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.4186, loss: 1.4186 +2025-05-06 15:17:16,391 - pyskl - INFO - Epoch [126][1200/1281] lr: 1.554e-03, eta: 5:25:15, time: 1.381, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4883, loss: 1.4883 +2025-05-06 15:19:06,417 - pyskl - INFO - Saving checkpoint at 126 epochs +2025-05-06 15:20:49,487 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 15:20:49,538 - pyskl - INFO - +top1_acc 0.9308 +top5_acc 0.9948 +2025-05-06 15:20:49,538 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 15:20:49,543 - pyskl - INFO - +mean_acc 0.9062 +2025-05-06 15:20:49,545 - pyskl - INFO - Epoch(val) [126][533] top1_acc: 0.9308, top5_acc: 0.9948, mean_class_accuracy: 0.9062 +2025-05-06 15:23:14,454 - pyskl - INFO - Epoch [127][100/1281] lr: 1.536e-03, eta: 5:23:26, time: 1.449, data_time: 0.172, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.4524, loss: 1.4524 +2025-05-06 15:25:30,432 - pyskl - INFO - Epoch [127][200/1281] lr: 1.527e-03, eta: 5:22:37, time: 1.360, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4149, loss: 1.4149 +2025-05-06 15:27:45,844 - pyskl - INFO - Epoch [127][300/1281] lr: 1.517e-03, eta: 5:21:47, time: 1.354, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4524, loss: 1.4524 +2025-05-06 15:30:03,685 - pyskl - INFO - Epoch [127][400/1281] lr: 1.507e-03, eta: 5:20:57, time: 1.378, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4458, loss: 1.4458 +2025-05-06 15:32:22,311 - pyskl - INFO - Epoch [127][500/1281] lr: 1.497e-03, eta: 5:20:08, time: 1.386, data_time: 0.000, memory: 9000, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 1.4205, loss: 1.4205 +2025-05-06 15:34:37,895 - pyskl - INFO - Epoch [127][600/1281] lr: 1.488e-03, eta: 5:19:18, time: 1.356, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.4638, loss: 1.4638 +2025-05-06 15:36:54,148 - pyskl - INFO - Epoch [127][700/1281] lr: 1.478e-03, eta: 5:18:28, time: 1.363, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4256, loss: 1.4256 +2025-05-06 15:39:10,895 - pyskl - INFO - Epoch [127][800/1281] lr: 1.468e-03, eta: 5:17:38, time: 1.367, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4589, loss: 1.4589 +2025-05-06 15:41:29,477 - pyskl - INFO - Epoch [127][900/1281] lr: 1.459e-03, eta: 5:16:48, time: 1.386, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4433, loss: 1.4433 +2025-05-06 15:43:46,203 - pyskl - INFO - Epoch [127][1000/1281] lr: 1.449e-03, eta: 5:15:57, time: 1.367, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3563, loss: 1.3563 +2025-05-06 15:46:03,507 - pyskl - INFO - Epoch [127][1100/1281] lr: 1.440e-03, eta: 5:15:07, time: 1.373, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.3641, loss: 1.3641 +2025-05-06 15:48:20,403 - pyskl - INFO - Epoch [127][1200/1281] lr: 1.430e-03, eta: 5:14:17, time: 1.369, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4082, loss: 1.4082 +2025-05-06 15:50:11,809 - pyskl - INFO - Saving checkpoint at 127 epochs +2025-05-06 15:51:54,827 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 15:51:54,881 - pyskl - INFO - +top1_acc 0.9306 +top5_acc 0.9952 +2025-05-06 15:51:54,881 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 15:51:54,887 - pyskl - INFO - +mean_acc 0.9082 +2025-05-06 15:51:54,888 - pyskl - INFO - Epoch(val) [127][533] top1_acc: 0.9306, top5_acc: 0.9952, mean_class_accuracy: 0.9082 +2025-05-06 15:54:21,535 - pyskl - INFO - Epoch [128][100/1281] lr: 1.413e-03, eta: 5:12:27, time: 1.466, data_time: 0.171, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3881, loss: 1.3881 +2025-05-06 15:56:38,129 - pyskl - INFO - Epoch [128][200/1281] lr: 1.404e-03, eta: 5:11:36, time: 1.366, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4440, loss: 1.4440 +2025-05-06 15:58:55,727 - pyskl - INFO - Epoch [128][300/1281] lr: 1.394e-03, eta: 5:10:45, time: 1.376, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3769, loss: 1.3769 +2025-05-06 16:01:12,791 - pyskl - INFO - Epoch [128][400/1281] lr: 1.385e-03, eta: 5:09:54, time: 1.371, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4124, loss: 1.4124 +2025-05-06 16:03:27,489 - pyskl - INFO - Epoch [128][500/1281] lr: 1.376e-03, eta: 5:09:03, time: 1.347, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4073, loss: 1.4073 +2025-05-06 16:05:43,856 - pyskl - INFO - Epoch [128][600/1281] lr: 1.366e-03, eta: 5:08:12, time: 1.364, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4261, loss: 1.4261 +2025-05-06 16:08:01,855 - pyskl - INFO - Epoch [128][700/1281] lr: 1.357e-03, eta: 5:07:21, time: 1.380, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3768, loss: 1.3768 +2025-05-06 16:10:19,090 - pyskl - INFO - Epoch [128][800/1281] lr: 1.348e-03, eta: 5:06:29, time: 1.372, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.4184, loss: 1.4184 +2025-05-06 16:12:34,002 - pyskl - INFO - Epoch [128][900/1281] lr: 1.339e-03, eta: 5:05:37, time: 1.349, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.3900, loss: 1.3900 +2025-05-06 16:14:53,048 - pyskl - INFO - Epoch [128][1000/1281] lr: 1.329e-03, eta: 5:04:46, time: 1.390, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4382, loss: 1.4382 +2025-05-06 16:17:08,737 - pyskl - INFO - Epoch [128][1100/1281] lr: 1.320e-03, eta: 5:03:54, time: 1.357, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.3662, loss: 1.3662 +2025-05-06 16:19:24,923 - pyskl - INFO - Epoch [128][1200/1281] lr: 1.311e-03, eta: 5:03:03, time: 1.362, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3563, loss: 1.3563 +2025-05-06 16:21:16,818 - pyskl - INFO - Saving checkpoint at 128 epochs +2025-05-06 16:23:00,105 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 16:23:00,156 - pyskl - INFO - +top1_acc 0.9313 +top5_acc 0.9965 +2025-05-06 16:23:00,156 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 16:23:00,162 - pyskl - INFO - +mean_acc 0.9100 +2025-05-06 16:23:00,164 - pyskl - INFO - Epoch(val) [128][533] top1_acc: 0.9313, top5_acc: 0.9965, mean_class_accuracy: 0.9100 +2025-05-06 16:25:25,460 - pyskl - INFO - Epoch [129][100/1281] lr: 1.295e-03, eta: 5:01:11, time: 1.453, data_time: 0.170, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4057, loss: 1.4057 +2025-05-06 16:27:42,183 - pyskl - INFO - Epoch [129][200/1281] lr: 1.286e-03, eta: 5:00:19, time: 1.367, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3769, loss: 1.3769 +2025-05-06 16:30:00,812 - pyskl - INFO - Epoch [129][300/1281] lr: 1.277e-03, eta: 4:59:27, time: 1.386, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3872, loss: 1.3872 +2025-05-06 16:32:17,583 - pyskl - INFO - Epoch [129][400/1281] lr: 1.268e-03, eta: 4:58:35, time: 1.368, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4224, loss: 1.4224 +2025-05-06 16:34:35,140 - pyskl - INFO - Epoch [129][500/1281] lr: 1.259e-03, eta: 4:57:43, time: 1.375, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.4103, loss: 1.4103 +2025-05-06 16:36:54,747 - pyskl - INFO - Epoch [129][600/1281] lr: 1.250e-03, eta: 4:56:51, time: 1.396, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4022, loss: 1.4022 +2025-05-06 16:39:12,289 - pyskl - INFO - Epoch [129][700/1281] lr: 1.241e-03, eta: 4:55:58, time: 1.375, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4275, loss: 1.4275 +2025-05-06 16:41:30,002 - pyskl - INFO - Epoch [129][800/1281] lr: 1.232e-03, eta: 4:55:06, time: 1.377, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3841, loss: 1.3841 +2025-05-06 16:43:48,036 - pyskl - INFO - Epoch [129][900/1281] lr: 1.223e-03, eta: 4:54:13, time: 1.380, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4356, loss: 1.4356 +2025-05-06 16:46:06,129 - pyskl - INFO - Epoch [129][1000/1281] lr: 1.214e-03, eta: 4:53:21, time: 1.381, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3902, loss: 1.3902 +2025-05-06 16:48:22,444 - pyskl - INFO - Epoch [129][1100/1281] lr: 1.206e-03, eta: 4:52:28, time: 1.363, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4193, loss: 1.4193 +2025-05-06 16:50:41,477 - pyskl - INFO - Epoch [129][1200/1281] lr: 1.197e-03, eta: 4:51:35, time: 1.390, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3785, loss: 1.3785 +2025-05-06 16:52:33,903 - pyskl - INFO - Saving checkpoint at 129 epochs +2025-05-06 16:54:17,107 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 16:54:17,159 - pyskl - INFO - +top1_acc 0.9316 +top5_acc 0.9948 +2025-05-06 16:54:17,159 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 16:54:17,164 - pyskl - INFO - +mean_acc 0.9101 +2025-05-06 16:54:17,166 - pyskl - INFO - Epoch(val) [129][533] top1_acc: 0.9316, top5_acc: 0.9948, mean_class_accuracy: 0.9101 +2025-05-06 16:56:44,234 - pyskl - INFO - Epoch [130][100/1281] lr: 1.181e-03, eta: 4:49:43, time: 1.471, data_time: 0.171, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4161, loss: 1.4161 +2025-05-06 16:59:00,992 - pyskl - INFO - Epoch [130][200/1281] lr: 1.172e-03, eta: 4:48:49, time: 1.368, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3834, loss: 1.3834 +2025-05-06 17:01:17,759 - pyskl - INFO - Epoch [130][300/1281] lr: 1.164e-03, eta: 4:47:56, time: 1.368, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3957, loss: 1.3957 +2025-05-06 17:03:35,714 - pyskl - INFO - Epoch [130][400/1281] lr: 1.155e-03, eta: 4:47:03, time: 1.380, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3766, loss: 1.3766 +2025-05-06 17:05:53,298 - pyskl - INFO - Epoch [130][500/1281] lr: 1.147e-03, eta: 4:46:09, time: 1.376, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4325, loss: 1.4325 +2025-05-06 17:08:11,154 - pyskl - INFO - Epoch [130][600/1281] lr: 1.138e-03, eta: 4:45:16, time: 1.379, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3503, loss: 1.3503 +2025-05-06 17:10:28,197 - pyskl - INFO - Epoch [130][700/1281] lr: 1.130e-03, eta: 4:44:22, time: 1.370, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3455, loss: 1.3455 +2025-05-06 17:12:44,623 - pyskl - INFO - Epoch [130][800/1281] lr: 1.121e-03, eta: 4:43:28, time: 1.364, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.4261, loss: 1.4261 +2025-05-06 17:15:01,324 - pyskl - INFO - Epoch [130][900/1281] lr: 1.113e-03, eta: 4:42:34, time: 1.367, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4050, loss: 1.4050 +2025-05-06 17:17:20,521 - pyskl - INFO - Epoch [130][1000/1281] lr: 1.104e-03, eta: 4:41:41, time: 1.392, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3510, loss: 1.3510 +2025-05-06 17:19:38,428 - pyskl - INFO - Epoch [130][1100/1281] lr: 1.096e-03, eta: 4:40:47, time: 1.379, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4102, loss: 1.4102 +2025-05-06 17:21:55,265 - pyskl - INFO - Epoch [130][1200/1281] lr: 1.088e-03, eta: 4:39:52, time: 1.368, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3457, loss: 1.3457 +2025-05-06 17:23:44,805 - pyskl - INFO - Saving checkpoint at 130 epochs +2025-05-06 17:25:27,654 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 17:25:27,706 - pyskl - INFO - +top1_acc 0.9332 +top5_acc 0.9954 +2025-05-06 17:25:27,706 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 17:25:27,711 - pyskl - INFO - +mean_acc 0.9102 +2025-05-06 17:25:27,767 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_125.pth was removed +2025-05-06 17:25:29,236 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_130.pth. +2025-05-06 17:25:29,237 - pyskl - INFO - Best top1_acc is 0.9332 at 130 epoch. +2025-05-06 17:25:29,241 - pyskl - INFO - Epoch(val) [130][533] top1_acc: 0.9332, top5_acc: 0.9954, mean_class_accuracy: 0.9102 +2025-05-06 17:27:56,256 - pyskl - INFO - Epoch [131][100/1281] lr: 1.072e-03, eta: 4:37:58, time: 1.470, data_time: 0.170, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3681, loss: 1.3681 +2025-05-06 17:30:11,086 - pyskl - INFO - Epoch [131][200/1281] lr: 1.064e-03, eta: 4:37:04, time: 1.348, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3552, loss: 1.3552 +2025-05-06 17:32:27,394 - pyskl - INFO - Epoch [131][300/1281] lr: 1.056e-03, eta: 4:36:09, time: 1.363, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3834, loss: 1.3834 +2025-05-06 17:34:44,497 - pyskl - INFO - Epoch [131][400/1281] lr: 1.048e-03, eta: 4:35:14, time: 1.371, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3672, loss: 1.3672 +2025-05-06 17:37:01,715 - pyskl - INFO - Epoch [131][500/1281] lr: 1.040e-03, eta: 4:34:20, time: 1.372, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3618, loss: 1.3618 +2025-05-06 17:39:20,021 - pyskl - INFO - Epoch [131][600/1281] lr: 1.031e-03, eta: 4:33:25, time: 1.383, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4132, loss: 1.4132 +2025-05-06 17:41:37,276 - pyskl - INFO - Epoch [131][700/1281] lr: 1.023e-03, eta: 4:32:30, time: 1.373, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3458, loss: 1.3458 +2025-05-06 17:43:54,792 - pyskl - INFO - Epoch [131][800/1281] lr: 1.015e-03, eta: 4:31:35, time: 1.375, data_time: 0.000, memory: 9000, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 1.4068, loss: 1.4068 +2025-05-06 17:46:12,431 - pyskl - INFO - Epoch [131][900/1281] lr: 1.007e-03, eta: 4:30:40, time: 1.376, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4037, loss: 1.4037 +2025-05-06 17:48:29,098 - pyskl - INFO - Epoch [131][1000/1281] lr: 9.992e-04, eta: 4:29:45, time: 1.367, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4308, loss: 1.4308 +2025-05-06 17:50:45,155 - pyskl - INFO - Epoch [131][1100/1281] lr: 9.912e-04, eta: 4:28:49, time: 1.361, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3760, loss: 1.3760 +2025-05-06 17:53:04,159 - pyskl - INFO - Epoch [131][1200/1281] lr: 9.832e-04, eta: 4:27:54, time: 1.390, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3822, loss: 1.3822 +2025-05-06 17:54:54,832 - pyskl - INFO - Saving checkpoint at 131 epochs +2025-05-06 17:56:38,772 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 17:56:38,823 - pyskl - INFO - +top1_acc 0.9309 +top5_acc 0.9948 +2025-05-06 17:56:38,824 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 17:56:38,829 - pyskl - INFO - +mean_acc 0.9074 +2025-05-06 17:56:38,831 - pyskl - INFO - Epoch(val) [131][533] top1_acc: 0.9309, top5_acc: 0.9948, mean_class_accuracy: 0.9074 +2025-05-06 17:59:06,957 - pyskl - INFO - Epoch [132][100/1281] lr: 9.689e-04, eta: 4:25:59, time: 1.481, data_time: 0.172, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3259, loss: 1.3259 +2025-05-06 18:01:24,523 - pyskl - INFO - Epoch [132][200/1281] lr: 9.610e-04, eta: 4:25:04, time: 1.376, data_time: 0.000, memory: 9000, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 1.3697, loss: 1.3697 +2025-05-06 18:03:41,953 - pyskl - INFO - Epoch [132][300/1281] lr: 9.532e-04, eta: 4:24:08, time: 1.374, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3484, loss: 1.3484 +2025-05-06 18:05:58,623 - pyskl - INFO - Epoch [132][400/1281] lr: 9.454e-04, eta: 4:23:12, time: 1.367, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3989, loss: 1.3989 +2025-05-06 18:08:17,366 - pyskl - INFO - Epoch [132][500/1281] lr: 9.376e-04, eta: 4:22:17, time: 1.387, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3923, loss: 1.3923 +2025-05-06 18:10:32,649 - pyskl - INFO - Epoch [132][600/1281] lr: 9.298e-04, eta: 4:21:20, time: 1.353, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3511, loss: 1.3511 +2025-05-06 18:12:51,171 - pyskl - INFO - Epoch [132][700/1281] lr: 9.221e-04, eta: 4:20:25, time: 1.385, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4096, loss: 1.4096 +2025-05-06 18:15:07,842 - pyskl - INFO - Epoch [132][800/1281] lr: 9.144e-04, eta: 4:19:28, time: 1.367, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.3528, loss: 1.3528 +2025-05-06 18:17:24,360 - pyskl - INFO - Epoch [132][900/1281] lr: 9.068e-04, eta: 4:18:32, time: 1.365, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3846, loss: 1.3846 +2025-05-06 18:19:40,328 - pyskl - INFO - Epoch [132][1000/1281] lr: 8.991e-04, eta: 4:17:35, time: 1.360, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3607, loss: 1.3607 +2025-05-06 18:21:57,143 - pyskl - INFO - Epoch [132][1100/1281] lr: 8.915e-04, eta: 4:16:39, time: 1.368, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3582, loss: 1.3582 +2025-05-06 18:24:15,256 - pyskl - INFO - Epoch [132][1200/1281] lr: 8.840e-04, eta: 4:15:42, time: 1.381, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3895, loss: 1.3895 +2025-05-06 18:26:06,172 - pyskl - INFO - Saving checkpoint at 132 epochs +2025-05-06 18:27:48,865 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 18:27:48,916 - pyskl - INFO - +top1_acc 0.9323 +top5_acc 0.9958 +2025-05-06 18:27:48,916 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 18:27:48,922 - pyskl - INFO - +mean_acc 0.9112 +2025-05-06 18:27:48,924 - pyskl - INFO - Epoch(val) [132][533] top1_acc: 0.9323, top5_acc: 0.9958, mean_class_accuracy: 0.9112 +2025-05-06 18:30:16,412 - pyskl - INFO - Epoch [133][100/1281] lr: 8.704e-04, eta: 4:13:46, time: 1.475, data_time: 0.172, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3472, loss: 1.3472 +2025-05-06 18:32:32,488 - pyskl - INFO - Epoch [133][200/1281] lr: 8.629e-04, eta: 4:12:49, time: 1.361, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3464, loss: 1.3464 +2025-05-06 18:34:48,413 - pyskl - INFO - Epoch [133][300/1281] lr: 8.554e-04, eta: 4:11:52, time: 1.359, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3729, loss: 1.3729 +2025-05-06 18:37:06,451 - pyskl - INFO - Epoch [133][400/1281] lr: 8.480e-04, eta: 4:10:55, time: 1.380, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3605, loss: 1.3605 +2025-05-06 18:39:24,389 - pyskl - INFO - Epoch [133][500/1281] lr: 8.406e-04, eta: 4:09:58, time: 1.379, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3581, loss: 1.3581 +2025-05-06 18:41:39,571 - pyskl - INFO - Epoch [133][600/1281] lr: 8.333e-04, eta: 4:09:01, time: 1.352, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3963, loss: 1.3963 +2025-05-06 18:43:56,783 - pyskl - INFO - Epoch [133][700/1281] lr: 8.260e-04, eta: 4:08:04, time: 1.372, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3474, loss: 1.3474 +2025-05-06 18:46:13,849 - pyskl - INFO - Epoch [133][800/1281] lr: 8.187e-04, eta: 4:07:07, time: 1.371, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3600, loss: 1.3600 +2025-05-06 18:48:32,033 - pyskl - INFO - Epoch [133][900/1281] lr: 8.114e-04, eta: 4:06:09, time: 1.382, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3565, loss: 1.3565 +2025-05-06 18:50:49,200 - pyskl - INFO - Epoch [133][1000/1281] lr: 8.042e-04, eta: 4:05:12, time: 1.372, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3570, loss: 1.3570 +2025-05-06 18:53:05,536 - pyskl - INFO - Epoch [133][1100/1281] lr: 7.970e-04, eta: 4:04:14, time: 1.363, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3853, loss: 1.3853 +2025-05-06 18:55:23,285 - pyskl - INFO - Epoch [133][1200/1281] lr: 7.898e-04, eta: 4:03:16, time: 1.377, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3434, loss: 1.3434 +2025-05-06 18:57:15,682 - pyskl - INFO - Saving checkpoint at 133 epochs +2025-05-06 18:58:58,311 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 18:58:58,363 - pyskl - INFO - +top1_acc 0.9328 +top5_acc 0.9960 +2025-05-06 18:58:58,363 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 18:58:58,368 - pyskl - INFO - +mean_acc 0.9125 +2025-05-06 18:58:58,370 - pyskl - INFO - Epoch(val) [133][533] top1_acc: 0.9328, top5_acc: 0.9960, mean_class_accuracy: 0.9125 +2025-05-06 19:01:22,744 - pyskl - INFO - Epoch [134][100/1281] lr: 7.769e-04, eta: 4:01:18, time: 1.444, data_time: 0.170, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3932, loss: 1.3932 +2025-05-06 19:03:40,434 - pyskl - INFO - Epoch [134][200/1281] lr: 7.699e-04, eta: 4:00:21, time: 1.377, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3998, loss: 1.3998 +2025-05-06 19:05:56,558 - pyskl - INFO - Epoch [134][300/1281] lr: 7.628e-04, eta: 3:59:23, time: 1.361, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3623, loss: 1.3623 +2025-05-06 19:08:14,060 - pyskl - INFO - Epoch [134][400/1281] lr: 7.558e-04, eta: 3:58:25, time: 1.375, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3780, loss: 1.3780 +2025-05-06 19:10:29,541 - pyskl - INFO - Epoch [134][500/1281] lr: 7.488e-04, eta: 3:57:26, time: 1.355, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.4027, loss: 1.4027 +2025-05-06 19:12:45,929 - pyskl - INFO - Epoch [134][600/1281] lr: 7.419e-04, eta: 3:56:28, time: 1.364, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3518, loss: 1.3518 +2025-05-06 19:15:02,220 - pyskl - INFO - Epoch [134][700/1281] lr: 7.349e-04, eta: 3:55:29, time: 1.363, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3312, loss: 1.3312 +2025-05-06 19:17:17,426 - pyskl - INFO - Epoch [134][800/1281] lr: 7.281e-04, eta: 3:54:31, time: 1.352, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3614, loss: 1.3614 +2025-05-06 19:19:32,607 - pyskl - INFO - Epoch [134][900/1281] lr: 7.212e-04, eta: 3:53:32, time: 1.352, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3414, loss: 1.3414 +2025-05-06 19:21:49,665 - pyskl - INFO - Epoch [134][1000/1281] lr: 7.144e-04, eta: 3:52:33, time: 1.371, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3793, loss: 1.3793 +2025-05-06 19:24:06,659 - pyskl - INFO - Epoch [134][1100/1281] lr: 7.076e-04, eta: 3:51:34, time: 1.370, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3786, loss: 1.3786 +2025-05-06 19:26:22,348 - pyskl - INFO - Epoch [134][1200/1281] lr: 7.008e-04, eta: 3:50:35, time: 1.357, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3790, loss: 1.3790 +2025-05-06 19:28:13,316 - pyskl - INFO - Saving checkpoint at 134 epochs +2025-05-06 19:29:56,572 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 19:29:56,623 - pyskl - INFO - +top1_acc 0.9344 +top5_acc 0.9960 +2025-05-06 19:29:56,623 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 19:29:56,629 - pyskl - INFO - +mean_acc 0.9115 +2025-05-06 19:29:56,686 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_130.pth was removed +2025-05-06 19:29:58,290 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_134.pth. +2025-05-06 19:29:58,291 - pyskl - INFO - Best top1_acc is 0.9344 at 134 epoch. +2025-05-06 19:29:58,294 - pyskl - INFO - Epoch(val) [134][533] top1_acc: 0.9344, top5_acc: 0.9960, mean_class_accuracy: 0.9115 +2025-05-06 19:32:22,897 - pyskl - INFO - Epoch [135][100/1281] lr: 6.887e-04, eta: 3:48:37, time: 1.446, data_time: 0.171, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3436, loss: 1.3436 +2025-05-06 19:34:39,179 - pyskl - INFO - Epoch [135][200/1281] lr: 6.820e-04, eta: 3:47:37, time: 1.363, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3413, loss: 1.3413 +2025-05-06 19:36:55,763 - pyskl - INFO - Epoch [135][300/1281] lr: 6.753e-04, eta: 3:46:38, time: 1.366, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3334, loss: 1.3334 +2025-05-06 19:39:11,965 - pyskl - INFO - Epoch [135][400/1281] lr: 6.687e-04, eta: 3:45:39, time: 1.362, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3456, loss: 1.3456 +2025-05-06 19:41:29,316 - pyskl - INFO - Epoch [135][500/1281] lr: 6.622e-04, eta: 3:44:40, time: 1.374, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3511, loss: 1.3511 +2025-05-06 19:43:45,850 - pyskl - INFO - Epoch [135][600/1281] lr: 6.556e-04, eta: 3:43:40, time: 1.365, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3736, loss: 1.3736 +2025-05-06 19:46:03,575 - pyskl - INFO - Epoch [135][700/1281] lr: 6.491e-04, eta: 3:42:41, time: 1.377, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4174, loss: 1.4174 +2025-05-06 19:48:19,003 - pyskl - INFO - Epoch [135][800/1281] lr: 6.426e-04, eta: 3:41:41, time: 1.354, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3522, loss: 1.3522 +2025-05-06 19:50:36,071 - pyskl - INFO - Epoch [135][900/1281] lr: 6.362e-04, eta: 3:40:42, time: 1.371, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3771, loss: 1.3771 +2025-05-06 19:52:53,307 - pyskl - INFO - Epoch [135][1000/1281] lr: 6.297e-04, eta: 3:39:42, time: 1.372, data_time: 0.000, memory: 9000, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 1.3606, loss: 1.3606 +2025-05-06 19:55:11,751 - pyskl - INFO - Epoch [135][1100/1281] lr: 6.233e-04, eta: 3:38:42, time: 1.384, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3703, loss: 1.3703 +2025-05-06 19:57:28,616 - pyskl - INFO - Epoch [135][1200/1281] lr: 6.170e-04, eta: 3:37:42, time: 1.369, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3376, loss: 1.3376 +2025-05-06 19:59:18,346 - pyskl - INFO - Saving checkpoint at 135 epochs +2025-05-06 20:01:00,790 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 20:01:00,841 - pyskl - INFO - +top1_acc 0.9324 +top5_acc 0.9952 +2025-05-06 20:01:00,841 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 20:01:00,847 - pyskl - INFO - +mean_acc 0.9100 +2025-05-06 20:01:00,849 - pyskl - INFO - Epoch(val) [135][533] top1_acc: 0.9324, top5_acc: 0.9952, mean_class_accuracy: 0.9100 +2025-05-06 20:03:24,954 - pyskl - INFO - Epoch [136][100/1281] lr: 6.056e-04, eta: 3:35:42, time: 1.441, data_time: 0.171, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3388, loss: 1.3388 +2025-05-06 20:05:41,669 - pyskl - INFO - Epoch [136][200/1281] lr: 5.993e-04, eta: 3:34:42, time: 1.367, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3181, loss: 1.3181 +2025-05-06 20:07:57,950 - pyskl - INFO - Epoch [136][300/1281] lr: 5.931e-04, eta: 3:33:42, time: 1.363, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3715, loss: 1.3715 +2025-05-06 20:10:15,653 - pyskl - INFO - Epoch [136][400/1281] lr: 5.868e-04, eta: 3:32:41, time: 1.377, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3706, loss: 1.3706 +2025-05-06 20:12:30,500 - pyskl - INFO - Epoch [136][500/1281] lr: 5.807e-04, eta: 3:31:41, time: 1.349, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3476, loss: 1.3476 +2025-05-06 20:14:46,803 - pyskl - INFO - Epoch [136][600/1281] lr: 5.745e-04, eta: 3:30:40, time: 1.363, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3387, loss: 1.3387 +2025-05-06 20:17:03,417 - pyskl - INFO - Epoch [136][700/1281] lr: 5.684e-04, eta: 3:29:40, time: 1.366, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3690, loss: 1.3690 +2025-05-06 20:19:20,052 - pyskl - INFO - Epoch [136][800/1281] lr: 5.623e-04, eta: 3:28:39, time: 1.366, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3745, loss: 1.3745 +2025-05-06 20:21:35,510 - pyskl - INFO - Epoch [136][900/1281] lr: 5.563e-04, eta: 3:27:38, time: 1.355, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3913, loss: 1.3913 +2025-05-06 20:23:52,155 - pyskl - INFO - Epoch [136][1000/1281] lr: 5.503e-04, eta: 3:26:37, time: 1.366, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3493, loss: 1.3493 +2025-05-06 20:26:08,501 - pyskl - INFO - Epoch [136][1100/1281] lr: 5.443e-04, eta: 3:25:36, time: 1.363, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3402, loss: 1.3402 +2025-05-06 20:28:23,704 - pyskl - INFO - Epoch [136][1200/1281] lr: 5.384e-04, eta: 3:24:35, time: 1.352, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3066, loss: 1.3066 +2025-05-06 20:30:14,964 - pyskl - INFO - Saving checkpoint at 136 epochs +2025-05-06 20:31:56,716 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 20:31:56,767 - pyskl - INFO - +top1_acc 0.9351 +top5_acc 0.9953 +2025-05-06 20:31:56,767 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 20:31:56,772 - pyskl - INFO - +mean_acc 0.9117 +2025-05-06 20:31:56,828 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_134.pth was removed +2025-05-06 20:31:58,290 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_136.pth. +2025-05-06 20:31:58,291 - pyskl - INFO - Best top1_acc is 0.9351 at 136 epoch. +2025-05-06 20:31:58,294 - pyskl - INFO - Epoch(val) [136][533] top1_acc: 0.9351, top5_acc: 0.9953, mean_class_accuracy: 0.9117 +2025-05-06 20:34:23,825 - pyskl - INFO - Epoch [137][100/1281] lr: 5.277e-04, eta: 3:22:34, time: 1.455, data_time: 0.171, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3432, loss: 1.3432 +2025-05-06 20:36:39,808 - pyskl - INFO - Epoch [137][200/1281] lr: 5.218e-04, eta: 3:21:33, time: 1.360, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3418, loss: 1.3418 +2025-05-06 20:38:53,955 - pyskl - INFO - Epoch [137][300/1281] lr: 5.160e-04, eta: 3:20:31, time: 1.341, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3478, loss: 1.3478 +2025-05-06 20:41:11,061 - pyskl - INFO - Epoch [137][400/1281] lr: 5.102e-04, eta: 3:19:30, time: 1.371, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3511, loss: 1.3511 +2025-05-06 20:43:28,030 - pyskl - INFO - Epoch [137][500/1281] lr: 5.044e-04, eta: 3:18:29, time: 1.370, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3251, loss: 1.3251 +2025-05-06 20:45:43,868 - pyskl - INFO - Epoch [137][600/1281] lr: 4.987e-04, eta: 3:17:27, time: 1.358, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3361, loss: 1.3361 +2025-05-06 20:48:01,103 - pyskl - INFO - Epoch [137][700/1281] lr: 4.930e-04, eta: 3:16:26, time: 1.372, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3615, loss: 1.3615 +2025-05-06 20:50:18,780 - pyskl - INFO - Epoch [137][800/1281] lr: 4.873e-04, eta: 3:15:24, time: 1.377, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3533, loss: 1.3533 +2025-05-06 20:52:33,294 - pyskl - INFO - Epoch [137][900/1281] lr: 4.817e-04, eta: 3:14:22, time: 1.345, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.4045, loss: 1.4045 +2025-05-06 20:54:51,925 - pyskl - INFO - Epoch [137][1000/1281] lr: 4.761e-04, eta: 3:13:20, time: 1.386, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3581, loss: 1.3581 +2025-05-06 20:57:07,301 - pyskl - INFO - Epoch [137][1100/1281] lr: 4.705e-04, eta: 3:12:18, time: 1.354, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3434, loss: 1.3434 +2025-05-06 20:59:25,571 - pyskl - INFO - Epoch [137][1200/1281] lr: 4.650e-04, eta: 3:11:16, time: 1.383, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3282, loss: 1.3282 +2025-05-06 21:01:14,967 - pyskl - INFO - Saving checkpoint at 137 epochs +2025-05-06 21:02:57,416 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 21:02:57,470 - pyskl - INFO - +top1_acc 0.9339 +top5_acc 0.9957 +2025-05-06 21:02:57,470 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 21:02:57,476 - pyskl - INFO - +mean_acc 0.9116 +2025-05-06 21:02:57,478 - pyskl - INFO - Epoch(val) [137][533] top1_acc: 0.9339, top5_acc: 0.9957, mean_class_accuracy: 0.9116 +2025-05-06 21:05:22,036 - pyskl - INFO - Epoch [138][100/1281] lr: 4.550e-04, eta: 3:09:14, time: 1.446, data_time: 0.169, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3804, loss: 1.3804 +2025-05-06 21:07:38,712 - pyskl - INFO - Epoch [138][200/1281] lr: 4.496e-04, eta: 3:08:12, time: 1.367, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3144, loss: 1.3144 +2025-05-06 21:09:54,428 - pyskl - INFO - Epoch [138][300/1281] lr: 4.442e-04, eta: 3:07:09, time: 1.357, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3764, loss: 1.3764 +2025-05-06 21:12:09,381 - pyskl - INFO - Epoch [138][400/1281] lr: 4.388e-04, eta: 3:06:07, time: 1.350, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3256, loss: 1.3256 +2025-05-06 21:14:27,098 - pyskl - INFO - Epoch [138][500/1281] lr: 4.334e-04, eta: 3:05:04, time: 1.377, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3383, loss: 1.3383 +2025-05-06 21:16:42,466 - pyskl - INFO - Epoch [138][600/1281] lr: 4.281e-04, eta: 3:04:02, time: 1.354, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3219, loss: 1.3219 +2025-05-06 21:18:59,909 - pyskl - INFO - Epoch [138][700/1281] lr: 4.228e-04, eta: 3:02:59, time: 1.374, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3527, loss: 1.3527 +2025-05-06 21:21:14,032 - pyskl - INFO - Epoch [138][800/1281] lr: 4.176e-04, eta: 3:01:56, time: 1.341, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3533, loss: 1.3533 +2025-05-06 21:23:30,296 - pyskl - INFO - Epoch [138][900/1281] lr: 4.124e-04, eta: 3:00:53, time: 1.363, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3370, loss: 1.3370 +2025-05-06 21:25:47,284 - pyskl - INFO - Epoch [138][1000/1281] lr: 4.072e-04, eta: 2:59:51, time: 1.370, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3439, loss: 1.3439 +2025-05-06 21:28:02,860 - pyskl - INFO - Epoch [138][1100/1281] lr: 4.020e-04, eta: 2:58:48, time: 1.356, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3524, loss: 1.3524 +2025-05-06 21:30:19,049 - pyskl - INFO - Epoch [138][1200/1281] lr: 3.969e-04, eta: 2:57:44, time: 1.362, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2922, loss: 1.2922 +2025-05-06 21:32:09,181 - pyskl - INFO - Saving checkpoint at 138 epochs +2025-05-06 21:33:50,508 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 21:33:50,558 - pyskl - INFO - +top1_acc 0.9346 +top5_acc 0.9958 +2025-05-06 21:33:50,558 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 21:33:50,564 - pyskl - INFO - +mean_acc 0.9120 +2025-05-06 21:33:50,566 - pyskl - INFO - Epoch(val) [138][533] top1_acc: 0.9346, top5_acc: 0.9958, mean_class_accuracy: 0.9120 +2025-05-06 21:36:13,394 - pyskl - INFO - Epoch [139][100/1281] lr: 3.877e-04, eta: 2:55:41, time: 1.428, data_time: 0.169, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3596, loss: 1.3596 +2025-05-06 21:38:28,571 - pyskl - INFO - Epoch [139][200/1281] lr: 3.827e-04, eta: 2:54:38, time: 1.352, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3551, loss: 1.3551 +2025-05-06 21:40:44,882 - pyskl - INFO - Epoch [139][300/1281] lr: 3.777e-04, eta: 2:53:34, time: 1.363, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3273, loss: 1.3273 +2025-05-06 21:42:59,848 - pyskl - INFO - Epoch [139][400/1281] lr: 3.727e-04, eta: 2:52:31, time: 1.350, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3491, loss: 1.3491 +2025-05-06 21:45:14,745 - pyskl - INFO - Epoch [139][500/1281] lr: 3.678e-04, eta: 2:51:27, time: 1.349, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3376, loss: 1.3376 +2025-05-06 21:47:30,960 - pyskl - INFO - Epoch [139][600/1281] lr: 3.628e-04, eta: 2:50:24, time: 1.362, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2998, loss: 1.2998 +2025-05-06 21:49:46,846 - pyskl - INFO - Epoch [139][700/1281] lr: 3.580e-04, eta: 2:49:20, time: 1.359, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3194, loss: 1.3194 +2025-05-06 21:52:03,595 - pyskl - INFO - Epoch [139][800/1281] lr: 3.531e-04, eta: 2:48:16, time: 1.368, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3233, loss: 1.3233 +2025-05-06 21:54:19,611 - pyskl - INFO - Epoch [139][900/1281] lr: 3.483e-04, eta: 2:47:12, time: 1.360, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3312, loss: 1.3312 +2025-05-06 21:56:34,865 - pyskl - INFO - Epoch [139][1000/1281] lr: 3.436e-04, eta: 2:46:08, time: 1.353, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3429, loss: 1.3429 +2025-05-06 21:58:50,850 - pyskl - INFO - Epoch [139][1100/1281] lr: 3.388e-04, eta: 2:45:04, time: 1.360, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3528, loss: 1.3528 +2025-05-06 22:01:05,939 - pyskl - INFO - Epoch [139][1200/1281] lr: 3.341e-04, eta: 2:44:00, time: 1.351, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3063, loss: 1.3063 +2025-05-06 22:02:55,504 - pyskl - INFO - Saving checkpoint at 139 epochs +2025-05-06 22:04:38,215 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 22:04:38,266 - pyskl - INFO - +top1_acc 0.9339 +top5_acc 0.9958 +2025-05-06 22:04:38,266 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 22:04:38,272 - pyskl - INFO - +mean_acc 0.9104 +2025-05-06 22:04:38,274 - pyskl - INFO - Epoch(val) [139][533] top1_acc: 0.9339, top5_acc: 0.9958, mean_class_accuracy: 0.9104 +2025-05-06 22:07:01,892 - pyskl - INFO - Epoch [140][100/1281] lr: 3.257e-04, eta: 2:41:56, time: 1.436, data_time: 0.172, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3201, loss: 1.3201 +2025-05-06 22:09:17,170 - pyskl - INFO - Epoch [140][200/1281] lr: 3.210e-04, eta: 2:40:52, time: 1.353, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3275, loss: 1.3275 +2025-05-06 22:11:32,463 - pyskl - INFO - Epoch [140][300/1281] lr: 3.165e-04, eta: 2:39:47, time: 1.353, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3141, loss: 1.3141 +2025-05-06 22:13:47,260 - pyskl - INFO - Epoch [140][400/1281] lr: 3.119e-04, eta: 2:38:43, time: 1.348, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3609, loss: 1.3609 +2025-05-06 22:16:02,973 - pyskl - INFO - Epoch [140][500/1281] lr: 3.074e-04, eta: 2:37:38, time: 1.357, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3142, loss: 1.3142 +2025-05-06 22:18:19,172 - pyskl - INFO - Epoch [140][600/1281] lr: 3.029e-04, eta: 2:36:34, time: 1.362, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3410, loss: 1.3410 +2025-05-06 22:20:33,791 - pyskl - INFO - Epoch [140][700/1281] lr: 2.984e-04, eta: 2:35:29, time: 1.346, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3115, loss: 1.3115 +2025-05-06 22:22:47,696 - pyskl - INFO - Epoch [140][800/1281] lr: 2.940e-04, eta: 2:34:24, time: 1.339, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3215, loss: 1.3215 +2025-05-06 22:25:02,642 - pyskl - INFO - Epoch [140][900/1281] lr: 2.896e-04, eta: 2:33:19, time: 1.349, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3503, loss: 1.3503 +2025-05-06 22:27:17,982 - pyskl - INFO - Epoch [140][1000/1281] lr: 2.853e-04, eta: 2:32:14, time: 1.353, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3419, loss: 1.3419 +2025-05-06 22:29:32,933 - pyskl - INFO - Epoch [140][1100/1281] lr: 2.809e-04, eta: 2:31:09, time: 1.350, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3477, loss: 1.3477 +2025-05-06 22:31:47,685 - pyskl - INFO - Epoch [140][1200/1281] lr: 2.767e-04, eta: 2:30:04, time: 1.348, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3328, loss: 1.3328 +2025-05-06 22:33:36,781 - pyskl - INFO - Saving checkpoint at 140 epochs +2025-05-06 22:35:17,922 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 22:35:17,973 - pyskl - INFO - +top1_acc 0.9345 +top5_acc 0.9957 +2025-05-06 22:35:17,973 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 22:35:17,979 - pyskl - INFO - +mean_acc 0.9127 +2025-05-06 22:35:17,980 - pyskl - INFO - Epoch(val) [140][533] top1_acc: 0.9345, top5_acc: 0.9957, mean_class_accuracy: 0.9127 +2025-05-06 22:37:41,272 - pyskl - INFO - Epoch [141][100/1281] lr: 2.690e-04, eta: 2:27:59, time: 1.433, data_time: 0.172, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3151, loss: 1.3151 +2025-05-06 22:39:55,081 - pyskl - INFO - Epoch [141][200/1281] lr: 2.648e-04, eta: 2:26:53, time: 1.338, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3517, loss: 1.3517 +2025-05-06 22:42:10,695 - pyskl - INFO - Epoch [141][300/1281] lr: 2.606e-04, eta: 2:25:48, time: 1.356, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3363, loss: 1.3363 +2025-05-06 22:44:25,329 - pyskl - INFO - Epoch [141][400/1281] lr: 2.565e-04, eta: 2:24:42, time: 1.346, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3197, loss: 1.3197 +2025-05-06 22:46:41,906 - pyskl - INFO - Epoch [141][500/1281] lr: 2.524e-04, eta: 2:23:37, time: 1.366, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2933, loss: 1.2933 +2025-05-06 22:48:57,755 - pyskl - INFO - Epoch [141][600/1281] lr: 2.483e-04, eta: 2:22:32, time: 1.358, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3126, loss: 1.3126 +2025-05-06 22:51:13,711 - pyskl - INFO - Epoch [141][700/1281] lr: 2.443e-04, eta: 2:21:26, time: 1.360, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3228, loss: 1.3228 +2025-05-06 22:53:27,446 - pyskl - INFO - Epoch [141][800/1281] lr: 2.402e-04, eta: 2:20:20, time: 1.337, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3773, loss: 1.3773 +2025-05-06 22:55:41,756 - pyskl - INFO - Epoch [141][900/1281] lr: 2.363e-04, eta: 2:19:14, time: 1.343, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2990, loss: 1.2990 +2025-05-06 22:57:56,421 - pyskl - INFO - Epoch [141][1000/1281] lr: 2.323e-04, eta: 2:18:08, time: 1.347, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3096, loss: 1.3096 +2025-05-06 23:00:12,731 - pyskl - INFO - Epoch [141][1100/1281] lr: 2.284e-04, eta: 2:17:02, time: 1.363, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3371, loss: 1.3371 +2025-05-06 23:02:26,240 - pyskl - INFO - Epoch [141][1200/1281] lr: 2.246e-04, eta: 2:15:56, time: 1.335, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3694, loss: 1.3694 +2025-05-06 23:04:16,243 - pyskl - INFO - Saving checkpoint at 141 epochs +2025-05-06 23:05:56,718 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 23:05:56,770 - pyskl - INFO - +top1_acc 0.9358 +top5_acc 0.9954 +2025-05-06 23:05:56,770 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 23:05:56,776 - pyskl - INFO - +mean_acc 0.9132 +2025-05-06 23:05:56,831 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_136.pth was removed +2025-05-06 23:05:58,300 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_141.pth. +2025-05-06 23:05:58,301 - pyskl - INFO - Best top1_acc is 0.9358 at 141 epoch. +2025-05-06 23:05:58,304 - pyskl - INFO - Epoch(val) [141][533] top1_acc: 0.9358, top5_acc: 0.9954, mean_class_accuracy: 0.9132 +2025-05-06 23:08:21,462 - pyskl - INFO - Epoch [142][100/1281] lr: 2.176e-04, eta: 2:13:50, time: 1.432, data_time: 0.170, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3124, loss: 1.3124 +2025-05-06 23:10:34,601 - pyskl - INFO - Epoch [142][200/1281] lr: 2.139e-04, eta: 2:12:44, time: 1.331, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3468, loss: 1.3468 +2025-05-06 23:12:50,660 - pyskl - INFO - Epoch [142][300/1281] lr: 2.101e-04, eta: 2:11:38, time: 1.361, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3474, loss: 1.3474 +2025-05-06 23:15:06,190 - pyskl - INFO - Epoch [142][400/1281] lr: 2.064e-04, eta: 2:10:31, time: 1.355, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3525, loss: 1.3525 +2025-05-06 23:17:20,026 - pyskl - INFO - Epoch [142][500/1281] lr: 2.027e-04, eta: 2:09:25, time: 1.338, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3070, loss: 1.3070 +2025-05-06 23:19:35,067 - pyskl - INFO - Epoch [142][600/1281] lr: 1.991e-04, eta: 2:08:18, time: 1.351, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3633, loss: 1.3633 +2025-05-06 23:21:49,502 - pyskl - INFO - Epoch [142][700/1281] lr: 1.954e-04, eta: 2:07:12, time: 1.344, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3475, loss: 1.3475 +2025-05-06 23:24:06,356 - pyskl - INFO - Epoch [142][800/1281] lr: 1.919e-04, eta: 2:06:05, time: 1.369, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3280, loss: 1.3280 +2025-05-06 23:26:21,607 - pyskl - INFO - Epoch [142][900/1281] lr: 1.883e-04, eta: 2:04:58, time: 1.353, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3428, loss: 1.3428 +2025-05-06 23:28:35,338 - pyskl - INFO - Epoch [142][1000/1281] lr: 1.848e-04, eta: 2:03:51, time: 1.337, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3222, loss: 1.3222 +2025-05-06 23:30:50,139 - pyskl - INFO - Epoch [142][1100/1281] lr: 1.813e-04, eta: 2:02:45, time: 1.348, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3067, loss: 1.3067 +2025-05-06 23:33:03,997 - pyskl - INFO - Epoch [142][1200/1281] lr: 1.779e-04, eta: 2:01:38, time: 1.339, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3195, loss: 1.3195 +2025-05-06 23:34:54,315 - pyskl - INFO - Saving checkpoint at 142 epochs +2025-05-06 23:36:37,254 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-06 23:36:37,305 - pyskl - INFO - +top1_acc 0.9355 +top5_acc 0.9954 +2025-05-06 23:36:37,305 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-06 23:36:37,311 - pyskl - INFO - +mean_acc 0.9145 +2025-05-06 23:36:37,312 - pyskl - INFO - Epoch(val) [142][533] top1_acc: 0.9355, top5_acc: 0.9954, mean_class_accuracy: 0.9145 +2025-05-06 23:39:01,371 - pyskl - INFO - Epoch [143][100/1281] lr: 1.717e-04, eta: 1:59:31, time: 1.441, data_time: 0.169, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3079, loss: 1.3079 +2025-05-06 23:41:16,531 - pyskl - INFO - Epoch [143][200/1281] lr: 1.683e-04, eta: 1:58:23, time: 1.352, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3311, loss: 1.3311 +2025-05-06 23:43:30,194 - pyskl - INFO - Epoch [143][300/1281] lr: 1.650e-04, eta: 1:57:16, time: 1.337, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3406, loss: 1.3406 +2025-05-06 23:45:46,603 - pyskl - INFO - Epoch [143][400/1281] lr: 1.617e-04, eta: 1:56:09, time: 1.364, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3209, loss: 1.3209 +2025-05-06 23:48:01,713 - pyskl - INFO - Epoch [143][500/1281] lr: 1.585e-04, eta: 1:55:02, time: 1.351, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3203, loss: 1.3203 +2025-05-06 23:50:16,908 - pyskl - INFO - Epoch [143][600/1281] lr: 1.552e-04, eta: 1:53:54, time: 1.352, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3297, loss: 1.3297 +2025-05-06 23:52:32,668 - pyskl - INFO - Epoch [143][700/1281] lr: 1.520e-04, eta: 1:52:47, time: 1.358, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3188, loss: 1.3188 +2025-05-06 23:54:47,942 - pyskl - INFO - Epoch [143][800/1281] lr: 1.489e-04, eta: 1:51:39, time: 1.353, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2879, loss: 1.2879 +2025-05-06 23:57:02,920 - pyskl - INFO - Epoch [143][900/1281] lr: 1.457e-04, eta: 1:50:32, time: 1.350, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3338, loss: 1.3338 +2025-05-06 23:59:18,831 - pyskl - INFO - Epoch [143][1000/1281] lr: 1.426e-04, eta: 1:49:24, time: 1.359, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3304, loss: 1.3304 +2025-05-07 00:01:34,025 - pyskl - INFO - Epoch [143][1100/1281] lr: 1.396e-04, eta: 1:48:16, time: 1.352, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2733, loss: 1.2733 +2025-05-07 00:03:49,796 - pyskl - INFO - Epoch [143][1200/1281] lr: 1.366e-04, eta: 1:47:08, time: 1.358, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3401, loss: 1.3401 +2025-05-07 00:05:37,271 - pyskl - INFO - Saving checkpoint at 143 epochs +2025-05-07 00:07:20,141 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-07 00:07:20,192 - pyskl - INFO - +top1_acc 0.9353 +top5_acc 0.9957 +2025-05-07 00:07:20,192 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-07 00:07:20,197 - pyskl - INFO - +mean_acc 0.9136 +2025-05-07 00:07:20,199 - pyskl - INFO - Epoch(val) [143][533] top1_acc: 0.9353, top5_acc: 0.9957, mean_class_accuracy: 0.9136 +2025-05-07 00:09:46,348 - pyskl - INFO - Epoch [144][100/1281] lr: 1.312e-04, eta: 1:45:01, time: 1.461, data_time: 0.170, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2860, loss: 1.2860 +2025-05-07 00:12:00,829 - pyskl - INFO - Epoch [144][200/1281] lr: 1.282e-04, eta: 1:43:53, time: 1.345, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3106, loss: 1.3106 +2025-05-07 00:14:16,026 - pyskl - INFO - Epoch [144][300/1281] lr: 1.253e-04, eta: 1:42:44, time: 1.352, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2921, loss: 1.2921 +2025-05-07 00:16:30,471 - pyskl - INFO - Epoch [144][400/1281] lr: 1.224e-04, eta: 1:41:36, time: 1.344, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3444, loss: 1.3444 +2025-05-07 00:18:47,939 - pyskl - INFO - Epoch [144][500/1281] lr: 1.196e-04, eta: 1:40:28, time: 1.375, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3230, loss: 1.3230 +2025-05-07 00:21:03,142 - pyskl - INFO - Epoch [144][600/1281] lr: 1.168e-04, eta: 1:39:20, time: 1.352, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3086, loss: 1.3086 +2025-05-07 00:23:17,216 - pyskl - INFO - Epoch [144][700/1281] lr: 1.140e-04, eta: 1:38:12, time: 1.341, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3219, loss: 1.3219 +2025-05-07 00:25:33,430 - pyskl - INFO - Epoch [144][800/1281] lr: 1.113e-04, eta: 1:37:03, time: 1.362, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3221, loss: 1.3221 +2025-05-07 00:27:47,149 - pyskl - INFO - Epoch [144][900/1281] lr: 1.086e-04, eta: 1:35:55, time: 1.337, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3331, loss: 1.3331 +2025-05-07 00:30:01,541 - pyskl - INFO - Epoch [144][1000/1281] lr: 1.059e-04, eta: 1:34:46, time: 1.344, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3497, loss: 1.3497 +2025-05-07 00:32:16,878 - pyskl - INFO - Epoch [144][1100/1281] lr: 1.033e-04, eta: 1:33:37, time: 1.353, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3093, loss: 1.3093 +2025-05-07 00:34:32,494 - pyskl - INFO - Epoch [144][1200/1281] lr: 1.007e-04, eta: 1:32:29, time: 1.356, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3159, loss: 1.3159 +2025-05-07 00:36:21,873 - pyskl - INFO - Saving checkpoint at 144 epochs +2025-05-07 00:38:05,298 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-07 00:38:05,349 - pyskl - INFO - +top1_acc 0.9355 +top5_acc 0.9959 +2025-05-07 00:38:05,349 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-07 00:38:05,354 - pyskl - INFO - +mean_acc 0.9121 +2025-05-07 00:38:05,356 - pyskl - INFO - Epoch(val) [144][533] top1_acc: 0.9355, top5_acc: 0.9959, mean_class_accuracy: 0.9121 +2025-05-07 00:40:28,381 - pyskl - INFO - Epoch [145][100/1281] lr: 9.605e-05, eta: 1:30:20, time: 1.430, data_time: 0.171, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3146, loss: 1.3146 +2025-05-07 00:42:44,386 - pyskl - INFO - Epoch [145][200/1281] lr: 9.353e-05, eta: 1:29:11, time: 1.360, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2982, loss: 1.2982 +2025-05-07 00:44:59,063 - pyskl - INFO - Epoch [145][300/1281] lr: 9.106e-05, eta: 1:28:02, time: 1.347, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3063, loss: 1.3063 +2025-05-07 00:47:13,154 - pyskl - INFO - Epoch [145][400/1281] lr: 8.861e-05, eta: 1:26:53, time: 1.341, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3276, loss: 1.3276 +2025-05-07 00:49:30,679 - pyskl - INFO - Epoch [145][500/1281] lr: 8.620e-05, eta: 1:25:44, time: 1.375, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3316, loss: 1.3316 +2025-05-07 00:51:45,516 - pyskl - INFO - Epoch [145][600/1281] lr: 8.382e-05, eta: 1:24:35, time: 1.348, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3064, loss: 1.3064 +2025-05-07 00:54:00,738 - pyskl - INFO - Epoch [145][700/1281] lr: 8.147e-05, eta: 1:23:26, time: 1.352, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3382, loss: 1.3382 +2025-05-07 00:56:16,305 - pyskl - INFO - Epoch [145][800/1281] lr: 7.916e-05, eta: 1:22:16, time: 1.356, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3101, loss: 1.3101 +2025-05-07 00:58:31,462 - pyskl - INFO - Epoch [145][900/1281] lr: 7.688e-05, eta: 1:21:07, time: 1.352, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.2964, loss: 1.2964 +2025-05-07 01:00:47,647 - pyskl - INFO - Epoch [145][1000/1281] lr: 7.463e-05, eta: 1:19:58, time: 1.362, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3448, loss: 1.3448 +2025-05-07 01:03:02,767 - pyskl - INFO - Epoch [145][1100/1281] lr: 7.242e-05, eta: 1:18:48, time: 1.351, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3322, loss: 1.3322 +2025-05-07 01:05:16,736 - pyskl - INFO - Epoch [145][1200/1281] lr: 7.024e-05, eta: 1:17:38, time: 1.340, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3368, loss: 1.3368 +2025-05-07 01:07:07,544 - pyskl - INFO - Saving checkpoint at 145 epochs +2025-05-07 01:08:48,811 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-07 01:08:48,862 - pyskl - INFO - +top1_acc 0.9356 +top5_acc 0.9951 +2025-05-07 01:08:48,862 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-07 01:08:48,868 - pyskl - INFO - +mean_acc 0.9127 +2025-05-07 01:08:48,870 - pyskl - INFO - Epoch(val) [145][533] top1_acc: 0.9356, top5_acc: 0.9951, mean_class_accuracy: 0.9127 +2025-05-07 01:11:12,802 - pyskl - INFO - Epoch [146][100/1281] lr: 6.638e-05, eta: 1:15:29, time: 1.439, data_time: 0.170, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3196, loss: 1.3196 +2025-05-07 01:13:28,799 - pyskl - INFO - Epoch [146][200/1281] lr: 6.429e-05, eta: 1:14:19, time: 1.360, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3124, loss: 1.3124 +2025-05-07 01:15:43,959 - pyskl - INFO - Epoch [146][300/1281] lr: 6.224e-05, eta: 1:13:09, time: 1.352, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3185, loss: 1.3185 +2025-05-07 01:18:01,130 - pyskl - INFO - Epoch [146][400/1281] lr: 6.022e-05, eta: 1:12:00, time: 1.372, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3128, loss: 1.3128 +2025-05-07 01:20:15,064 - pyskl - INFO - Epoch [146][500/1281] lr: 5.823e-05, eta: 1:10:50, time: 1.339, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3279, loss: 1.3279 +2025-05-07 01:22:31,315 - pyskl - INFO - Epoch [146][600/1281] lr: 5.628e-05, eta: 1:09:40, time: 1.363, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2743, loss: 1.2743 +2025-05-07 01:24:48,169 - pyskl - INFO - Epoch [146][700/1281] lr: 5.436e-05, eta: 1:08:30, time: 1.368, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2799, loss: 1.2799 +2025-05-07 01:27:04,809 - pyskl - INFO - Epoch [146][800/1281] lr: 5.247e-05, eta: 1:07:19, time: 1.366, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3057, loss: 1.3057 +2025-05-07 01:29:21,429 - pyskl - INFO - Epoch [146][900/1281] lr: 5.061e-05, eta: 1:06:09, time: 1.366, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2833, loss: 1.2833 +2025-05-07 01:31:38,072 - pyskl - INFO - Epoch [146][1000/1281] lr: 4.879e-05, eta: 1:04:59, time: 1.367, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3288, loss: 1.3288 +2025-05-07 01:33:54,722 - pyskl - INFO - Epoch [146][1100/1281] lr: 4.701e-05, eta: 1:03:49, time: 1.366, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3117, loss: 1.3117 +2025-05-07 01:36:11,070 - pyskl - INFO - Epoch [146][1200/1281] lr: 4.525e-05, eta: 1:02:38, time: 1.363, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.2731, loss: 1.2731 +2025-05-07 01:38:02,592 - pyskl - INFO - Saving checkpoint at 146 epochs +2025-05-07 01:39:44,369 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-07 01:39:44,420 - pyskl - INFO - +top1_acc 0.9349 +top5_acc 0.9960 +2025-05-07 01:39:44,420 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-07 01:39:44,426 - pyskl - INFO - +mean_acc 0.9125 +2025-05-07 01:39:44,428 - pyskl - INFO - Epoch(val) [146][533] top1_acc: 0.9349, top5_acc: 0.9960, mean_class_accuracy: 0.9125 +2025-05-07 01:42:10,633 - pyskl - INFO - Epoch [147][100/1281] lr: 4.216e-05, eta: 1:00:28, time: 1.462, data_time: 0.170, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3326, loss: 1.3326 +2025-05-07 01:44:25,634 - pyskl - INFO - Epoch [147][200/1281] lr: 4.050e-05, eta: 0:59:17, time: 1.350, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3027, loss: 1.3027 +2025-05-07 01:46:40,769 - pyskl - INFO - Epoch [147][300/1281] lr: 3.887e-05, eta: 0:58:07, time: 1.351, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3502, loss: 1.3502 +2025-05-07 01:48:57,761 - pyskl - INFO - Epoch [147][400/1281] lr: 3.728e-05, eta: 0:56:56, time: 1.370, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3365, loss: 1.3365 +2025-05-07 01:51:14,772 - pyskl - INFO - Epoch [147][500/1281] lr: 3.572e-05, eta: 0:55:45, time: 1.370, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3233, loss: 1.3233 +2025-05-07 01:53:30,026 - pyskl - INFO - Epoch [147][600/1281] lr: 3.419e-05, eta: 0:54:35, time: 1.353, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2882, loss: 1.2882 +2025-05-07 01:55:47,092 - pyskl - INFO - Epoch [147][700/1281] lr: 3.270e-05, eta: 0:53:24, time: 1.371, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3072, loss: 1.3072 +2025-05-07 01:58:03,905 - pyskl - INFO - Epoch [147][800/1281] lr: 3.124e-05, eta: 0:52:13, time: 1.368, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3268, loss: 1.3268 +2025-05-07 02:00:21,055 - pyskl - INFO - Epoch [147][900/1281] lr: 2.981e-05, eta: 0:51:02, time: 1.372, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3402, loss: 1.3402 +2025-05-07 02:02:37,093 - pyskl - INFO - Epoch [147][1000/1281] lr: 2.842e-05, eta: 0:49:51, time: 1.360, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2756, loss: 1.2756 +2025-05-07 02:04:53,661 - pyskl - INFO - Epoch [147][1100/1281] lr: 2.706e-05, eta: 0:48:40, time: 1.366, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3050, loss: 1.3050 +2025-05-07 02:07:09,782 - pyskl - INFO - Epoch [147][1200/1281] lr: 2.573e-05, eta: 0:47:28, time: 1.361, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3093, loss: 1.3093 +2025-05-07 02:09:00,206 - pyskl - INFO - Saving checkpoint at 147 epochs +2025-05-07 02:10:43,741 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-07 02:10:43,793 - pyskl - INFO - +top1_acc 0.9351 +top5_acc 0.9954 +2025-05-07 02:10:43,793 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-07 02:10:43,799 - pyskl - INFO - +mean_acc 0.9121 +2025-05-07 02:10:43,800 - pyskl - INFO - Epoch(val) [147][533] top1_acc: 0.9351, top5_acc: 0.9954, mean_class_accuracy: 0.9121 +2025-05-07 02:13:09,445 - pyskl - INFO - Epoch [148][100/1281] lr: 2.341e-05, eta: 0:45:17, time: 1.456, data_time: 0.172, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3188, loss: 1.3188 +2025-05-07 02:15:25,638 - pyskl - INFO - Epoch [148][200/1281] lr: 2.218e-05, eta: 0:44:06, time: 1.362, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3325, loss: 1.3325 +2025-05-07 02:17:42,063 - pyskl - INFO - Epoch [148][300/1281] lr: 2.098e-05, eta: 0:42:54, time: 1.364, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3456, loss: 1.3456 +2025-05-07 02:19:58,612 - pyskl - INFO - Epoch [148][400/1281] lr: 1.981e-05, eta: 0:41:43, time: 1.365, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3360, loss: 1.3360 +2025-05-07 02:22:16,187 - pyskl - INFO - Epoch [148][500/1281] lr: 1.868e-05, eta: 0:40:31, time: 1.376, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2797, loss: 1.2797 +2025-05-07 02:24:32,053 - pyskl - INFO - Epoch [148][600/1281] lr: 1.758e-05, eta: 0:39:20, time: 1.359, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3075, loss: 1.3075 +2025-05-07 02:26:48,403 - pyskl - INFO - Epoch [148][700/1281] lr: 1.651e-05, eta: 0:38:08, time: 1.364, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3124, loss: 1.3124 +2025-05-07 02:29:05,320 - pyskl - INFO - Epoch [148][800/1281] lr: 1.548e-05, eta: 0:36:56, time: 1.369, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3229, loss: 1.3229 +2025-05-07 02:31:21,644 - pyskl - INFO - Epoch [148][900/1281] lr: 1.448e-05, eta: 0:35:44, time: 1.363, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3019, loss: 1.3019 +2025-05-07 02:33:36,900 - pyskl - INFO - Epoch [148][1000/1281] lr: 1.351e-05, eta: 0:34:32, time: 1.353, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3041, loss: 1.3041 +2025-05-07 02:35:53,537 - pyskl - INFO - Epoch [148][1100/1281] lr: 1.258e-05, eta: 0:33:20, time: 1.366, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2730, loss: 1.2730 +2025-05-07 02:38:09,189 - pyskl - INFO - Epoch [148][1200/1281] lr: 1.168e-05, eta: 0:32:08, time: 1.357, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2993, loss: 1.2993 +2025-05-07 02:40:00,686 - pyskl - INFO - Saving checkpoint at 148 epochs +2025-05-07 02:41:44,013 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-07 02:41:44,064 - pyskl - INFO - +top1_acc 0.9347 +top5_acc 0.9959 +2025-05-07 02:41:44,065 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-07 02:41:44,070 - pyskl - INFO - +mean_acc 0.9112 +2025-05-07 02:41:44,072 - pyskl - INFO - Epoch(val) [148][533] top1_acc: 0.9347, top5_acc: 0.9959, mean_class_accuracy: 0.9112 +2025-05-07 02:44:08,774 - pyskl - INFO - Epoch [149][100/1281] lr: 1.013e-05, eta: 0:29:56, time: 1.447, data_time: 0.170, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3363, loss: 1.3363 +2025-05-07 02:46:24,617 - pyskl - INFO - Epoch [149][200/1281] lr: 9.328e-06, eta: 0:28:44, time: 1.358, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3240, loss: 1.3240 +2025-05-07 02:48:39,631 - pyskl - INFO - Epoch [149][300/1281] lr: 8.555e-06, eta: 0:27:32, time: 1.350, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3370, loss: 1.3370 +2025-05-07 02:50:55,225 - pyskl - INFO - Epoch [149][400/1281] lr: 7.816e-06, eta: 0:26:20, time: 1.356, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3198, loss: 1.3198 +2025-05-07 02:53:12,250 - pyskl - INFO - Epoch [149][500/1281] lr: 7.110e-06, eta: 0:25:07, time: 1.370, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.2969, loss: 1.2969 +2025-05-07 02:55:29,400 - pyskl - INFO - Epoch [149][600/1281] lr: 6.437e-06, eta: 0:23:55, time: 1.371, data_time: 0.000, memory: 9000, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 1.3063, loss: 1.3063 +2025-05-07 02:57:45,318 - pyskl - INFO - Epoch [149][700/1281] lr: 5.798e-06, eta: 0:22:42, time: 1.359, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3007, loss: 1.3007 +2025-05-07 03:00:00,481 - pyskl - INFO - Epoch [149][800/1281] lr: 5.192e-06, eta: 0:21:30, time: 1.352, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3507, loss: 1.3507 +2025-05-07 03:02:16,627 - pyskl - INFO - Epoch [149][900/1281] lr: 4.620e-06, eta: 0:20:17, time: 1.361, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3127, loss: 1.3127 +2025-05-07 03:04:32,419 - pyskl - INFO - Epoch [149][1000/1281] lr: 4.081e-06, eta: 0:19:04, time: 1.358, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3175, loss: 1.3175 +2025-05-07 03:06:48,487 - pyskl - INFO - Epoch [149][1100/1281] lr: 3.576e-06, eta: 0:17:51, time: 1.361, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3188, loss: 1.3188 +2025-05-07 03:09:02,385 - pyskl - INFO - Epoch [149][1200/1281] lr: 3.104e-06, eta: 0:16:38, time: 1.339, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2980, loss: 1.2980 +2025-05-07 03:10:52,250 - pyskl - INFO - Saving checkpoint at 149 epochs +2025-05-07 03:12:35,101 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-07 03:12:35,152 - pyskl - INFO - +top1_acc 0.9338 +top5_acc 0.9959 +2025-05-07 03:12:35,152 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-07 03:12:35,158 - pyskl - INFO - +mean_acc 0.9102 +2025-05-07 03:12:35,159 - pyskl - INFO - Epoch(val) [149][533] top1_acc: 0.9338, top5_acc: 0.9959, mean_class_accuracy: 0.9102 +2025-05-07 03:14:58,685 - pyskl - INFO - Epoch [150][100/1281] lr: 2.334e-06, eta: 0:14:26, time: 1.435, data_time: 0.171, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2683, loss: 1.2683 +2025-05-07 03:17:14,770 - pyskl - INFO - Epoch [150][200/1281] lr: 1.956e-06, eta: 0:13:13, time: 1.361, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3298, loss: 1.3298 +2025-05-07 03:19:29,271 - pyskl - INFO - Epoch [150][300/1281] lr: 1.611e-06, eta: 0:12:00, time: 1.345, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3360, loss: 1.3360 +2025-05-07 03:21:45,729 - pyskl - INFO - Epoch [150][400/1281] lr: 1.300e-06, eta: 0:10:47, time: 1.365, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3399, loss: 1.3399 +2025-05-07 03:23:58,709 - pyskl - INFO - Epoch [150][500/1281] lr: 1.022e-06, eta: 0:09:33, time: 1.330, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3250, loss: 1.3250 +2025-05-07 03:26:15,725 - pyskl - INFO - Epoch [150][600/1281] lr: 7.771e-07, eta: 0:08:20, time: 1.370, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2957, loss: 1.2957 +2025-05-07 03:28:32,374 - pyskl - INFO - Epoch [150][700/1281] lr: 5.659e-07, eta: 0:07:07, time: 1.367, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3174, loss: 1.3174 +2025-05-07 03:30:47,047 - pyskl - INFO - Epoch [150][800/1281] lr: 3.881e-07, eta: 0:05:53, time: 1.347, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.2756, loss: 1.2756 +2025-05-07 03:33:03,308 - pyskl - INFO - Epoch [150][900/1281] lr: 2.438e-07, eta: 0:04:40, time: 1.363, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3287, loss: 1.3287 +2025-05-07 03:35:17,186 - pyskl - INFO - Epoch [150][1000/1281] lr: 1.329e-07, eta: 0:03:26, time: 1.339, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3078, loss: 1.3078 +2025-05-07 03:37:34,704 - pyskl - INFO - Epoch [150][1100/1281] lr: 5.534e-08, eta: 0:02:13, time: 1.375, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3369, loss: 1.3369 +2025-05-07 03:39:50,022 - pyskl - INFO - Epoch [150][1200/1281] lr: 1.123e-08, eta: 0:00:59, time: 1.353, data_time: 0.000, memory: 9000, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 1.3185, loss: 1.3185 +2025-05-07 03:41:40,048 - pyskl - INFO - Saving checkpoint at 150 epochs +2025-05-07 03:43:21,689 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-05-07 03:43:21,740 - pyskl - INFO - +top1_acc 0.9359 +top5_acc 0.9954 +2025-05-07 03:43:21,740 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-05-07 03:43:21,746 - pyskl - INFO - +mean_acc 0.9132 +2025-05-07 03:43:21,805 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/finegym/km/best_top1_acc_epoch_141.pth was removed +2025-05-07 03:43:23,256 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_150.pth. +2025-05-07 03:43:23,257 - pyskl - INFO - Best top1_acc is 0.9359 at 150 epoch. +2025-05-07 03:43:23,260 - pyskl - INFO - Epoch(val) [150][533] top1_acc: 0.9359, top5_acc: 0.9954, mean_class_accuracy: 0.9132 +2025-05-07 03:43:27,645 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-05-07 03:58:33,976 - pyskl - INFO - Testing results of the last checkpoint +2025-05-07 03:58:33,976 - pyskl - INFO - top1_acc: 0.9398 +2025-05-07 03:58:33,976 - pyskl - INFO - top5_acc: 0.9960 +2025-05-07 03:58:33,976 - pyskl - INFO - mean_class_accuracy: 0.9167 +2025-05-07 03:58:33,977 - pyskl - INFO - load checkpoint from local path: ./work_dirs/finegym/km/best_top1_acc_epoch_150.pth +2025-05-07 04:13:51,735 - pyskl - INFO - Testing results of the best checkpoint +2025-05-07 04:13:51,735 - pyskl - INFO - top1_acc: 0.9398 +2025-05-07 04:13:51,735 - pyskl - INFO - top5_acc: 0.9960 +2025-05-07 04:13:51,735 - pyskl - INFO - mean_class_accuracy: 0.9167