diff --git "a/finegym/b_3/20250624_084158.log" "b/finegym/b_3/20250624_084158.log" new file mode 100644--- /dev/null +++ "b/finegym/b_3/20250624_084158.log" @@ -0,0 +1,3471 @@ +2025-06-24 08:41:58,353 - pyskl - INFO - Environment info: +------------------------------------------------------------ +sys.platform: linux +Python: 3.7.11 (default, Jul 27 2021, 14:32:16) [GCC 7.5.0] +CUDA available: True +GPU 0: Tesla V100-PCIE-32GB +CUDA_HOME: /usr/local/cuda-11.7 +NVCC: Cuda compilation tools, release 11.7, V11.7.64 +GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0 +PyTorch: 1.11.0 +PyTorch compiling details: PyTorch built with: + - GCC 7.3 + - C++ Version: 201402 + - Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications + - Intel(R) MKL-DNN v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e) + - OpenMP 201511 (a.k.a. OpenMP 4.5) + - LAPACK is enabled (usually provided by MKL) + - NNPACK is enabled + - CPU capability usage: AVX2 + - CUDA Runtime 11.3 + - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_37,code=compute_37 + - CuDNN 8.2 + - Magma 2.5.2 + - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, + +TorchVision: 0.12.0 +OpenCV: 4.8.0 +MMCV: 1.5.0 +MMCV Compiler: GCC 7.3 +MMCV CUDA Compiler: 11.3 +pyskl: 0.1.0+ +------------------------------------------------------------ + +2025-06-24 08:41:58,557 - pyskl - INFO - Config: modality = 'b' +graph = 'coco_new' +work_dir = './work_dirs/test_aclnet/finegym/b_3' +model = dict( + type='RecognizerGCN', + backbone=dict( + type='GCN_Module', + gcn_ratio=0.125, + gcn_ctr='T', + gcn_ada='T', + tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'], + graph_cfg=dict( + layout='coco_new', + mode='random', + num_filter=8, + init_off=0.04, + init_std=0.02)), + cls_head=dict(type='SimpleHead', data_cfg='finegym', num_classes=99, in_channels=384)) +dataset_type = 'PoseDataset' +ann_file = '/data/lhd/pyskl_data/gym/gym_hrnet.pkl' +left_kp = [1, 3, 5, 7, 9, 11, 13, 15] +right_kp = [2, 4, 6, 8, 10, 12, 14, 16] +train_pipeline = [ + dict(type='UniformSampleFrames', clip_len=100), + dict(type='PoseDecode'), + dict( + type='Flip', + flip_ratio=0.5, + left_kp=[1, 3, 5, 7, 9, 11, 13, 15], + right_kp=[2, 4, 6, 8, 10, 12, 14, 16]), + dict(type='Kinetics_Transform'), + dict(type='GenSkeFeat', dataset='coco_new', feats=['b']), + 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=['b']), + 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=['b']), + 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=['b']), + 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=['b']), + 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=['b']), + dict(type='FormatGCNInput', num_person=2), + dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]), + dict(type='ToTensor', keys=['keypoint']) + ], + split='val')) +optimizer = dict( + type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True) +optimizer_config = dict(grad_clip=None) +lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False) +total_epochs = 150 +checkpoint_config = dict(interval=1) +evaluation = dict( + interval=1, metrics=['top_k_accuracy', 'mean_class_accuracy'], topk=(1, 5)) +log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')]) +dist_params = dict(backend='nccl') +gpu_ids = range(0, 1) + +2025-06-24 08:41:58,557 - pyskl - INFO - Set random seed to 335308573, deterministic: False +2025-06-24 08:42:00,004 - pyskl - INFO - 20484 videos remain after valid thresholding +2025-06-24 08:42:04,097 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-06-24 08:42:04,098 - pyskl - INFO - Start running, host: lhd@zkyd, work_dir: /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3 +2025-06-24 08:42:04,098 - pyskl - INFO - Hooks will be executed in the following order: +before_run: +(VERY_HIGH ) CosineAnnealingLrUpdaterHook +(NORMAL ) CustomCheckpointHook +(NORMAL ) DistEvalHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_train_epoch: +(VERY_HIGH ) CosineAnnealingLrUpdaterHook +(NORMAL ) DistSamplerSeedHook +(NORMAL ) DistEvalHook +(LOW ) IterTimerHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_train_iter: +(VERY_HIGH ) CosineAnnealingLrUpdaterHook +(NORMAL ) DistEvalHook +(LOW ) IterTimerHook + -------------------- +after_train_iter: +(ABOVE_NORMAL) OptimizerHook +(NORMAL ) CustomCheckpointHook +(NORMAL ) DistEvalHook +(LOW ) IterTimerHook +(VERY_LOW ) TextLoggerHook + -------------------- +after_train_epoch: +(NORMAL ) CustomCheckpointHook +(NORMAL ) DistEvalHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_val_epoch: +(NORMAL ) DistSamplerSeedHook +(LOW ) IterTimerHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_val_iter: +(LOW ) IterTimerHook + -------------------- +after_val_iter: +(LOW ) IterTimerHook + -------------------- +after_val_epoch: +(VERY_LOW ) TextLoggerHook + -------------------- +after_run: +(VERY_LOW ) TextLoggerHook + -------------------- +2025-06-24 08:42:04,098 - pyskl - INFO - workflow: [('train', 1)], max: 150 epochs +2025-06-24 08:42:04,098 - pyskl - INFO - Checkpoints will be saved to /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3 by HardDiskBackend. +2025-06-24 08:42:41,473 - pyskl - INFO - Epoch [1][100/1281] lr: 2.500e-02, eta: 19:56:11, time: 0.374, data_time: 0.162, memory: 4082, top1_acc: 0.0612, top5_acc: 0.2419, loss_cls: 4.4726, loss: 4.4726 +2025-06-24 08:43:02,488 - pyskl - INFO - Epoch [1][200/1281] lr: 2.500e-02, eta: 15:33:55, time: 0.210, data_time: 0.000, memory: 4082, top1_acc: 0.1100, top5_acc: 0.3375, loss_cls: 4.5090, loss: 4.5090 +2025-06-24 08:43:23,867 - pyskl - INFO - Epoch [1][300/1281] lr: 2.500e-02, eta: 14:10:08, time: 0.214, data_time: 0.001, memory: 4082, top1_acc: 0.1019, top5_acc: 0.3713, loss_cls: 4.2762, loss: 4.2762 +2025-06-24 08:43:45,104 - pyskl - INFO - Epoch [1][400/1281] lr: 2.500e-02, eta: 13:26:56, time: 0.212, data_time: 0.000, memory: 4082, top1_acc: 0.1037, top5_acc: 0.4019, loss_cls: 4.1223, loss: 4.1223 +2025-06-24 08:44:06,679 - pyskl - INFO - Epoch [1][500/1281] lr: 2.500e-02, eta: 13:03:02, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.1481, top5_acc: 0.4631, loss_cls: 3.8994, loss: 3.8994 +2025-06-24 08:44:28,441 - pyskl - INFO - Epoch [1][600/1281] lr: 2.500e-02, eta: 12:47:58, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.1756, top5_acc: 0.5238, loss_cls: 3.6457, loss: 3.6457 +2025-06-24 08:44:50,038 - pyskl - INFO - Epoch [1][700/1281] lr: 2.500e-02, eta: 12:36:22, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.2019, top5_acc: 0.5306, loss_cls: 3.6087, loss: 3.6087 +2025-06-24 08:45:11,542 - pyskl - INFO - Epoch [1][800/1281] lr: 2.500e-02, eta: 12:27:11, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.2394, top5_acc: 0.5931, loss_cls: 3.3308, loss: 3.3308 +2025-06-24 08:45:33,111 - pyskl - INFO - Epoch [1][900/1281] lr: 2.500e-02, eta: 12:20:13, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.2612, top5_acc: 0.6181, loss_cls: 3.2159, loss: 3.2159 +2025-06-24 08:45:55,271 - pyskl - INFO - Epoch [1][1000/1281] lr: 2.500e-02, eta: 12:16:26, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.2981, top5_acc: 0.6875, loss_cls: 3.0353, loss: 3.0353 +2025-06-24 08:46:16,864 - pyskl - INFO - Epoch [1][1100/1281] lr: 2.500e-02, eta: 12:11:38, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.3306, top5_acc: 0.7087, loss_cls: 2.8867, loss: 2.8867 +2025-06-24 08:46:38,687 - pyskl - INFO - Epoch [1][1200/1281] lr: 2.500e-02, eta: 12:08:11, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.3344, top5_acc: 0.7319, loss_cls: 2.7906, loss: 2.7906 +2025-06-24 08:46:57,052 - pyskl - INFO - Saving checkpoint at 1 epochs +2025-06-24 08:47:39,817 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 08:47:39,872 - pyskl - INFO - +top1_acc 0.3713 +top5_acc 0.7521 +2025-06-24 08:47:39,873 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 08:47:39,880 - pyskl - INFO - +mean_acc 0.1741 +2025-06-24 08:47:40,047 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_1.pth. +2025-06-24 08:47:40,047 - pyskl - INFO - Best top1_acc is 0.3713 at 1 epoch. +2025-06-24 08:47:40,050 - pyskl - INFO - Epoch(val) [1][533] top1_acc: 0.3713, top5_acc: 0.7521, mean_class_accuracy: 0.1741 +2025-06-24 08:48:20,101 - pyskl - INFO - Epoch [2][100/1281] lr: 2.500e-02, eta: 12:04:21, time: 0.400, data_time: 0.185, memory: 4082, top1_acc: 0.3794, top5_acc: 0.7750, loss_cls: 2.5912, loss: 2.5912 +2025-06-24 08:48:41,741 - pyskl - INFO - Epoch [2][200/1281] lr: 2.500e-02, eta: 12:01:31, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.4219, top5_acc: 0.8037, loss_cls: 2.4540, loss: 2.4540 +2025-06-24 08:49:03,504 - pyskl - INFO - Epoch [2][300/1281] lr: 2.500e-02, eta: 11:59:15, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.4269, top5_acc: 0.8256, loss_cls: 2.3883, loss: 2.3883 +2025-06-24 08:49:25,314 - pyskl - INFO - Epoch [2][400/1281] lr: 2.500e-02, eta: 11:57:17, time: 0.218, data_time: 0.001, memory: 4082, top1_acc: 0.4219, top5_acc: 0.8219, loss_cls: 2.3825, loss: 2.3825 +2025-06-24 08:49:47,178 - pyskl - INFO - Epoch [2][500/1281] lr: 2.499e-02, eta: 11:55:36, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.4500, top5_acc: 0.8294, loss_cls: 2.2908, loss: 2.2908 +2025-06-24 08:50:08,898 - pyskl - INFO - Epoch [2][600/1281] lr: 2.499e-02, eta: 11:53:49, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.4544, top5_acc: 0.8569, loss_cls: 2.2045, loss: 2.2045 +2025-06-24 08:50:30,720 - pyskl - INFO - Epoch [2][700/1281] lr: 2.499e-02, eta: 11:52:21, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.4938, top5_acc: 0.8581, loss_cls: 2.1319, loss: 2.1319 +2025-06-24 08:50:52,616 - pyskl - INFO - Epoch [2][800/1281] lr: 2.499e-02, eta: 11:51:05, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.4994, top5_acc: 0.8644, loss_cls: 2.1104, loss: 2.1104 +2025-06-24 08:51:14,465 - pyskl - INFO - Epoch [2][900/1281] lr: 2.499e-02, eta: 11:49:51, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.4844, top5_acc: 0.8762, loss_cls: 2.0769, loss: 2.0769 +2025-06-24 08:51:36,045 - pyskl - INFO - Epoch [2][1000/1281] lr: 2.499e-02, eta: 11:48:18, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.5250, top5_acc: 0.8988, loss_cls: 1.9640, loss: 1.9640 +2025-06-24 08:51:57,769 - pyskl - INFO - Epoch [2][1100/1281] lr: 2.499e-02, eta: 11:47:03, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.5369, top5_acc: 0.9025, loss_cls: 1.9475, loss: 1.9475 +2025-06-24 08:52:19,753 - pyskl - INFO - Epoch [2][1200/1281] lr: 2.499e-02, eta: 11:46:12, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5238, top5_acc: 0.9038, loss_cls: 1.9329, loss: 1.9329 +2025-06-24 08:52:37,991 - pyskl - INFO - Saving checkpoint at 2 epochs +2025-06-24 08:53:21,279 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 08:53:21,332 - pyskl - INFO - +top1_acc 0.5258 +top5_acc 0.9012 +2025-06-24 08:53:21,332 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 08:53:21,338 - pyskl - INFO - +mean_acc 0.3436 +2025-06-24 08:53:21,342 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_1.pth was removed +2025-06-24 08:53:21,523 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_2.pth. +2025-06-24 08:53:21,523 - pyskl - INFO - Best top1_acc is 0.5258 at 2 epoch. +2025-06-24 08:53:21,526 - pyskl - INFO - Epoch(val) [2][533] top1_acc: 0.5258, top5_acc: 0.9012, mean_class_accuracy: 0.3436 +2025-06-24 08:54:01,638 - pyskl - INFO - Epoch [3][100/1281] lr: 2.499e-02, eta: 11:45:08, time: 0.401, data_time: 0.182, memory: 4082, top1_acc: 0.5381, top5_acc: 0.8975, loss_cls: 1.8894, loss: 1.8894 +2025-06-24 08:54:23,606 - pyskl - INFO - Epoch [3][200/1281] lr: 2.499e-02, eta: 11:44:21, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5450, top5_acc: 0.9263, loss_cls: 1.8151, loss: 1.8151 +2025-06-24 08:54:45,370 - pyskl - INFO - Epoch [3][300/1281] lr: 2.499e-02, eta: 11:43:23, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.5644, top5_acc: 0.9331, loss_cls: 1.7533, loss: 1.7533 +2025-06-24 08:55:07,179 - pyskl - INFO - Epoch [3][400/1281] lr: 2.499e-02, eta: 11:42:29, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.5700, top5_acc: 0.9225, loss_cls: 1.7419, loss: 1.7419 +2025-06-24 08:55:29,277 - pyskl - INFO - Epoch [3][500/1281] lr: 2.498e-02, eta: 11:41:56, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.6000, top5_acc: 0.9325, loss_cls: 1.6817, loss: 1.6817 +2025-06-24 08:55:51,071 - pyskl - INFO - Epoch [3][600/1281] lr: 2.498e-02, eta: 11:41:05, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.5613, top5_acc: 0.9219, loss_cls: 1.7374, loss: 1.7374 +2025-06-24 08:56:13,256 - pyskl - INFO - Epoch [3][700/1281] lr: 2.498e-02, eta: 11:40:38, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.5787, top5_acc: 0.9275, loss_cls: 1.7121, loss: 1.7121 +2025-06-24 08:56:35,146 - pyskl - INFO - Epoch [3][800/1281] lr: 2.498e-02, eta: 11:39:55, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.5887, top5_acc: 0.9469, loss_cls: 1.6447, loss: 1.6447 +2025-06-24 08:56:57,084 - pyskl - INFO - Epoch [3][900/1281] lr: 2.498e-02, eta: 11:39:16, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6238, top5_acc: 0.9406, loss_cls: 1.5952, loss: 1.5952 +2025-06-24 08:57:18,877 - pyskl - INFO - Epoch [3][1000/1281] lr: 2.498e-02, eta: 11:38:30, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.6150, top5_acc: 0.9394, loss_cls: 1.5650, loss: 1.5650 +2025-06-24 08:57:40,735 - pyskl - INFO - Epoch [3][1100/1281] lr: 2.498e-02, eta: 11:37:49, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6369, top5_acc: 0.9487, loss_cls: 1.5013, loss: 1.5013 +2025-06-24 08:58:02,528 - pyskl - INFO - Epoch [3][1200/1281] lr: 2.498e-02, eta: 11:37:06, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.6344, top5_acc: 0.9406, loss_cls: 1.5737, loss: 1.5737 +2025-06-24 08:58:20,855 - pyskl - INFO - Saving checkpoint at 3 epochs +2025-06-24 08:59:04,331 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 08:59:04,387 - pyskl - INFO - +top1_acc 0.6410 +top5_acc 0.9502 +2025-06-24 08:59:04,387 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 08:59:04,393 - pyskl - INFO - +mean_acc 0.4690 +2025-06-24 08:59:04,397 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_2.pth was removed +2025-06-24 08:59:04,583 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_3.pth. +2025-06-24 08:59:04,583 - pyskl - INFO - Best top1_acc is 0.6410 at 3 epoch. +2025-06-24 08:59:04,586 - pyskl - INFO - Epoch(val) [3][533] top1_acc: 0.6410, top5_acc: 0.9502, mean_class_accuracy: 0.4690 +2025-06-24 08:59:44,763 - pyskl - INFO - Epoch [4][100/1281] lr: 2.497e-02, eta: 11:36:25, time: 0.402, data_time: 0.182, memory: 4082, top1_acc: 0.6500, top5_acc: 0.9569, loss_cls: 1.4885, loss: 1.4885 +2025-06-24 09:00:06,425 - pyskl - INFO - Epoch [4][200/1281] lr: 2.497e-02, eta: 11:35:38, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6275, top5_acc: 0.9525, loss_cls: 1.5182, loss: 1.5182 +2025-06-24 09:00:28,230 - pyskl - INFO - Epoch [4][300/1281] lr: 2.497e-02, eta: 11:34:58, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.6575, top5_acc: 0.9575, loss_cls: 1.4487, loss: 1.4487 +2025-06-24 09:00:50,120 - pyskl - INFO - Epoch [4][400/1281] lr: 2.497e-02, eta: 11:34:23, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6469, top5_acc: 0.9525, loss_cls: 1.4495, loss: 1.4495 +2025-06-24 09:01:12,027 - pyskl - INFO - Epoch [4][500/1281] lr: 2.497e-02, eta: 11:33:49, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6781, top5_acc: 0.9481, loss_cls: 1.4115, loss: 1.4115 +2025-06-24 09:01:33,769 - pyskl - INFO - Epoch [4][600/1281] lr: 2.497e-02, eta: 11:33:09, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6713, top5_acc: 0.9581, loss_cls: 1.4014, loss: 1.4014 +2025-06-24 09:01:55,440 - pyskl - INFO - Epoch [4][700/1281] lr: 2.497e-02, eta: 11:32:27, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6687, top5_acc: 0.9600, loss_cls: 1.4084, loss: 1.4084 +2025-06-24 09:02:17,061 - pyskl - INFO - Epoch [4][800/1281] lr: 2.496e-02, eta: 11:31:44, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.6506, top5_acc: 0.9569, loss_cls: 1.4110, loss: 1.4110 +2025-06-24 09:02:38,563 - pyskl - INFO - Epoch [4][900/1281] lr: 2.496e-02, eta: 11:30:57, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.6775, top5_acc: 0.9550, loss_cls: 1.3629, loss: 1.3629 +2025-06-24 09:03:00,283 - pyskl - INFO - Epoch [4][1000/1281] lr: 2.496e-02, eta: 11:30:19, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6744, top5_acc: 0.9606, loss_cls: 1.3716, loss: 1.3716 +2025-06-24 09:03:21,862 - pyskl - INFO - Epoch [4][1100/1281] lr: 2.496e-02, eta: 11:29:37, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.6681, top5_acc: 0.9563, loss_cls: 1.3565, loss: 1.3565 +2025-06-24 09:03:43,777 - pyskl - INFO - Epoch [4][1200/1281] lr: 2.496e-02, eta: 11:29:07, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7025, top5_acc: 0.9656, loss_cls: 1.2617, loss: 1.2617 +2025-06-24 09:04:02,336 - pyskl - INFO - Saving checkpoint at 4 epochs +2025-06-24 09:04:45,327 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:04:45,380 - pyskl - INFO - +top1_acc 0.6728 +top5_acc 0.9605 +2025-06-24 09:04:45,381 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:04:45,387 - pyskl - INFO - +mean_acc 0.5369 +2025-06-24 09:04:45,391 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_3.pth was removed +2025-06-24 09:04:45,625 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_4.pth. +2025-06-24 09:04:45,626 - pyskl - INFO - Best top1_acc is 0.6728 at 4 epoch. +2025-06-24 09:04:45,628 - pyskl - INFO - Epoch(val) [4][533] top1_acc: 0.6728, top5_acc: 0.9605, mean_class_accuracy: 0.5369 +2025-06-24 09:05:25,446 - pyskl - INFO - Epoch [5][100/1281] lr: 2.495e-02, eta: 11:28:21, time: 0.398, data_time: 0.179, memory: 4082, top1_acc: 0.6806, top5_acc: 0.9650, loss_cls: 1.3018, loss: 1.3018 +2025-06-24 09:05:47,433 - pyskl - INFO - Epoch [5][200/1281] lr: 2.495e-02, eta: 11:27:55, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.6869, top5_acc: 0.9631, loss_cls: 1.2875, loss: 1.2875 +2025-06-24 09:06:09,249 - pyskl - INFO - Epoch [5][300/1281] lr: 2.495e-02, eta: 11:27:23, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7025, top5_acc: 0.9637, loss_cls: 1.2858, loss: 1.2858 +2025-06-24 09:06:31,049 - pyskl - INFO - Epoch [5][400/1281] lr: 2.495e-02, eta: 11:26:51, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7188, top5_acc: 0.9725, loss_cls: 1.2067, loss: 1.2067 +2025-06-24 09:06:53,075 - pyskl - INFO - Epoch [5][500/1281] lr: 2.495e-02, eta: 11:26:27, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7262, top5_acc: 0.9719, loss_cls: 1.2033, loss: 1.2033 +2025-06-24 09:07:15,092 - pyskl - INFO - Epoch [5][600/1281] lr: 2.495e-02, eta: 11:26:03, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7312, top5_acc: 0.9712, loss_cls: 1.2160, loss: 1.2160 +2025-06-24 09:07:37,154 - pyskl - INFO - Epoch [5][700/1281] lr: 2.494e-02, eta: 11:25:40, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7163, top5_acc: 0.9712, loss_cls: 1.1892, loss: 1.1892 +2025-06-24 09:07:58,849 - pyskl - INFO - Epoch [5][800/1281] lr: 2.494e-02, eta: 11:25:06, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7025, top5_acc: 0.9700, loss_cls: 1.2450, loss: 1.2450 +2025-06-24 09:08:20,324 - pyskl - INFO - Epoch [5][900/1281] lr: 2.494e-02, eta: 11:24:26, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7094, top5_acc: 0.9688, loss_cls: 1.2107, loss: 1.2107 +2025-06-24 09:08:41,935 - pyskl - INFO - Epoch [5][1000/1281] lr: 2.494e-02, eta: 11:23:50, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7169, top5_acc: 0.9700, loss_cls: 1.1996, loss: 1.1996 +2025-06-24 09:09:03,684 - pyskl - INFO - Epoch [5][1100/1281] lr: 2.494e-02, eta: 11:23:19, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7050, top5_acc: 0.9731, loss_cls: 1.2231, loss: 1.2231 +2025-06-24 09:09:25,351 - pyskl - INFO - Epoch [5][1200/1281] lr: 2.493e-02, eta: 11:22:45, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7312, top5_acc: 0.9762, loss_cls: 1.1563, loss: 1.1563 +2025-06-24 09:09:43,564 - pyskl - INFO - Saving checkpoint at 5 epochs +2025-06-24 09:10:26,368 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:10:26,424 - pyskl - INFO - +top1_acc 0.6924 +top5_acc 0.9671 +2025-06-24 09:10:26,424 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:10:26,430 - pyskl - INFO - +mean_acc 0.5494 +2025-06-24 09:10:26,434 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_4.pth was removed +2025-06-24 09:10:26,610 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_5.pth. +2025-06-24 09:10:26,610 - pyskl - INFO - Best top1_acc is 0.6924 at 5 epoch. +2025-06-24 09:10:26,613 - pyskl - INFO - Epoch(val) [5][533] top1_acc: 0.6924, top5_acc: 0.9671, mean_class_accuracy: 0.5494 +2025-06-24 09:11:06,667 - pyskl - INFO - Epoch [6][100/1281] lr: 2.493e-02, eta: 11:22:10, time: 0.400, data_time: 0.179, memory: 4082, top1_acc: 0.7269, top5_acc: 0.9738, loss_cls: 1.1695, loss: 1.1695 +2025-06-24 09:11:28,900 - pyskl - INFO - Epoch [6][200/1281] lr: 2.493e-02, eta: 11:21:53, time: 0.222, data_time: 0.001, memory: 4082, top1_acc: 0.7262, top5_acc: 0.9719, loss_cls: 1.1708, loss: 1.1708 +2025-06-24 09:11:50,854 - pyskl - INFO - Epoch [6][300/1281] lr: 2.492e-02, eta: 11:21:28, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7131, top5_acc: 0.9788, loss_cls: 1.1368, loss: 1.1368 +2025-06-24 09:12:12,531 - pyskl - INFO - Epoch [6][400/1281] lr: 2.492e-02, eta: 11:20:56, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7412, top5_acc: 0.9800, loss_cls: 1.1201, loss: 1.1201 +2025-06-24 09:12:34,732 - pyskl - INFO - Epoch [6][500/1281] lr: 2.492e-02, eta: 11:20:38, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.7469, top5_acc: 0.9806, loss_cls: 1.0919, loss: 1.0919 +2025-06-24 09:12:56,550 - pyskl - INFO - Epoch [6][600/1281] lr: 2.492e-02, eta: 11:20:10, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7319, top5_acc: 0.9725, loss_cls: 1.1229, loss: 1.1229 +2025-06-24 09:13:18,219 - pyskl - INFO - Epoch [6][700/1281] lr: 2.492e-02, eta: 11:19:38, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7356, top5_acc: 0.9812, loss_cls: 1.1129, loss: 1.1129 +2025-06-24 09:13:40,000 - pyskl - INFO - Epoch [6][800/1281] lr: 2.491e-02, eta: 11:19:09, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7175, top5_acc: 0.9812, loss_cls: 1.1928, loss: 1.1928 +2025-06-24 09:14:01,822 - pyskl - INFO - Epoch [6][900/1281] lr: 2.491e-02, eta: 11:18:42, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7350, top5_acc: 0.9694, loss_cls: 1.1657, loss: 1.1657 +2025-06-24 09:14:23,446 - pyskl - INFO - Epoch [6][1000/1281] lr: 2.491e-02, eta: 11:18:10, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7612, top5_acc: 0.9800, loss_cls: 1.0292, loss: 1.0292 +2025-06-24 09:14:45,443 - pyskl - INFO - Epoch [6][1100/1281] lr: 2.491e-02, eta: 11:17:47, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7475, top5_acc: 0.9731, loss_cls: 1.0815, loss: 1.0815 +2025-06-24 09:15:07,196 - pyskl - INFO - Epoch [6][1200/1281] lr: 2.490e-02, eta: 11:17:18, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7238, top5_acc: 0.9744, loss_cls: 1.1398, loss: 1.1398 +2025-06-24 09:15:25,391 - pyskl - INFO - Saving checkpoint at 6 epochs +2025-06-24 09:16:08,323 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:16:08,377 - pyskl - INFO - +top1_acc 0.6831 +top5_acc 0.9561 +2025-06-24 09:16:08,378 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:16:08,384 - pyskl - INFO - +mean_acc 0.5456 +2025-06-24 09:16:08,386 - pyskl - INFO - Epoch(val) [6][533] top1_acc: 0.6831, top5_acc: 0.9561, mean_class_accuracy: 0.5456 +2025-06-24 09:16:48,855 - pyskl - INFO - Epoch [7][100/1281] lr: 2.490e-02, eta: 11:16:53, time: 0.405, data_time: 0.184, memory: 4082, top1_acc: 0.7375, top5_acc: 0.9825, loss_cls: 1.0883, loss: 1.0883 +2025-06-24 09:17:10,680 - pyskl - INFO - Epoch [7][200/1281] lr: 2.490e-02, eta: 11:16:26, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7606, top5_acc: 0.9812, loss_cls: 1.0000, loss: 1.0000 +2025-06-24 09:17:32,250 - pyskl - INFO - Epoch [7][300/1281] lr: 2.489e-02, eta: 11:15:54, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7681, top5_acc: 0.9825, loss_cls: 0.9861, loss: 0.9861 +2025-06-24 09:17:53,724 - pyskl - INFO - Epoch [7][400/1281] lr: 2.489e-02, eta: 11:15:19, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7506, top5_acc: 0.9794, loss_cls: 1.0864, loss: 1.0864 +2025-06-24 09:18:15,454 - pyskl - INFO - Epoch [7][500/1281] lr: 2.489e-02, eta: 11:14:51, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7538, top5_acc: 0.9775, loss_cls: 1.0483, loss: 1.0483 +2025-06-24 09:18:36,766 - pyskl - INFO - Epoch [7][600/1281] lr: 2.489e-02, eta: 11:14:13, time: 0.213, data_time: 0.000, memory: 4082, top1_acc: 0.7612, top5_acc: 0.9812, loss_cls: 0.9947, loss: 0.9947 +2025-06-24 09:18:58,864 - pyskl - INFO - Epoch [7][700/1281] lr: 2.488e-02, eta: 11:13:53, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7538, top5_acc: 0.9869, loss_cls: 1.0268, loss: 1.0268 +2025-06-24 09:19:20,399 - pyskl - INFO - Epoch [7][800/1281] lr: 2.488e-02, eta: 11:13:21, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7594, top5_acc: 0.9819, loss_cls: 1.0243, loss: 1.0243 +2025-06-24 09:19:42,317 - pyskl - INFO - Epoch [7][900/1281] lr: 2.488e-02, eta: 11:12:57, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7512, top5_acc: 0.9794, loss_cls: 1.0556, loss: 1.0556 +2025-06-24 09:20:03,733 - pyskl - INFO - Epoch [7][1000/1281] lr: 2.487e-02, eta: 11:12:23, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7575, top5_acc: 0.9875, loss_cls: 1.0051, loss: 1.0051 +2025-06-24 09:20:25,314 - pyskl - INFO - Epoch [7][1100/1281] lr: 2.487e-02, eta: 11:11:53, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7600, top5_acc: 0.9825, loss_cls: 1.0222, loss: 1.0222 +2025-06-24 09:20:46,995 - pyskl - INFO - Epoch [7][1200/1281] lr: 2.487e-02, eta: 11:11:24, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7556, top5_acc: 0.9800, loss_cls: 1.0318, loss: 1.0318 +2025-06-24 09:21:05,135 - pyskl - INFO - Saving checkpoint at 7 epochs +2025-06-24 09:21:48,163 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:21:48,220 - pyskl - INFO - +top1_acc 0.7240 +top5_acc 0.9687 +2025-06-24 09:21:48,220 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:21:48,227 - pyskl - INFO - +mean_acc 0.5950 +2025-06-24 09:21:48,231 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_5.pth was removed +2025-06-24 09:21:48,404 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_7.pth. +2025-06-24 09:21:48,405 - pyskl - INFO - Best top1_acc is 0.7240 at 7 epoch. +2025-06-24 09:21:48,407 - pyskl - INFO - Epoch(val) [7][533] top1_acc: 0.7240, top5_acc: 0.9687, mean_class_accuracy: 0.5950 +2025-06-24 09:22:28,494 - pyskl - INFO - Epoch [8][100/1281] lr: 2.486e-02, eta: 11:10:50, time: 0.401, data_time: 0.182, memory: 4082, top1_acc: 0.7631, top5_acc: 0.9788, loss_cls: 1.0500, loss: 1.0500 +2025-06-24 09:22:50,541 - pyskl - INFO - Epoch [8][200/1281] lr: 2.486e-02, eta: 11:10:30, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7700, top5_acc: 0.9831, loss_cls: 1.0004, loss: 1.0004 +2025-06-24 09:23:12,333 - pyskl - INFO - Epoch [8][300/1281] lr: 2.486e-02, eta: 11:10:04, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7906, top5_acc: 0.9888, loss_cls: 0.9489, loss: 0.9489 +2025-06-24 09:23:34,084 - pyskl - INFO - Epoch [8][400/1281] lr: 2.485e-02, eta: 11:09:37, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7744, top5_acc: 0.9900, loss_cls: 0.9584, loss: 0.9584 +2025-06-24 09:23:55,719 - pyskl - INFO - Epoch [8][500/1281] lr: 2.485e-02, eta: 11:09:09, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7788, top5_acc: 0.9900, loss_cls: 0.9459, loss: 0.9459 +2025-06-24 09:24:17,599 - pyskl - INFO - Epoch [8][600/1281] lr: 2.485e-02, eta: 11:08:45, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7688, top5_acc: 0.9812, loss_cls: 0.9998, loss: 0.9998 +2025-06-24 09:24:39,325 - pyskl - INFO - Epoch [8][700/1281] lr: 2.484e-02, eta: 11:08:18, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7506, top5_acc: 0.9800, loss_cls: 1.0097, loss: 1.0097 +2025-06-24 09:25:00,970 - pyskl - INFO - Epoch [8][800/1281] lr: 2.484e-02, eta: 11:07:50, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8037, top5_acc: 0.9856, loss_cls: 0.9211, loss: 0.9211 +2025-06-24 09:25:23,072 - pyskl - INFO - Epoch [8][900/1281] lr: 2.484e-02, eta: 11:07:30, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7775, top5_acc: 0.9888, loss_cls: 0.9393, loss: 0.9393 +2025-06-24 09:25:44,853 - pyskl - INFO - Epoch [8][1000/1281] lr: 2.483e-02, eta: 11:07:05, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8006, top5_acc: 0.9856, loss_cls: 0.9036, loss: 0.9036 +2025-06-24 09:26:06,650 - pyskl - INFO - Epoch [8][1100/1281] lr: 2.483e-02, eta: 11:06:40, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7825, top5_acc: 0.9825, loss_cls: 0.9470, loss: 0.9470 +2025-06-24 09:26:28,523 - pyskl - INFO - Epoch [8][1200/1281] lr: 2.483e-02, eta: 11:06:16, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7725, top5_acc: 0.9856, loss_cls: 0.9767, loss: 0.9767 +2025-06-24 09:26:46,773 - pyskl - INFO - Saving checkpoint at 8 epochs +2025-06-24 09:27:30,137 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:27:30,195 - pyskl - INFO - +top1_acc 0.7836 +top5_acc 0.9798 +2025-06-24 09:27:30,195 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:27:30,203 - pyskl - INFO - +mean_acc 0.6870 +2025-06-24 09:27:30,207 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_7.pth was removed +2025-06-24 09:27:30,378 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_8.pth. +2025-06-24 09:27:30,378 - pyskl - INFO - Best top1_acc is 0.7836 at 8 epoch. +2025-06-24 09:27:30,381 - pyskl - INFO - Epoch(val) [8][533] top1_acc: 0.7836, top5_acc: 0.9798, mean_class_accuracy: 0.6870 +2025-06-24 09:28:10,243 - pyskl - INFO - Epoch [9][100/1281] lr: 2.482e-02, eta: 11:05:38, time: 0.399, data_time: 0.181, memory: 4082, top1_acc: 0.8037, top5_acc: 0.9881, loss_cls: 0.8610, loss: 0.8610 +2025-06-24 09:28:32,255 - pyskl - INFO - Epoch [9][200/1281] lr: 2.482e-02, eta: 11:05:17, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7863, top5_acc: 0.9888, loss_cls: 0.9166, loss: 0.9166 +2025-06-24 09:28:54,278 - pyskl - INFO - Epoch [9][300/1281] lr: 2.481e-02, eta: 11:04:56, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7750, top5_acc: 0.9838, loss_cls: 0.9574, loss: 0.9574 +2025-06-24 09:29:16,163 - pyskl - INFO - Epoch [9][400/1281] lr: 2.481e-02, eta: 11:04:32, time: 0.219, data_time: 0.001, memory: 4082, top1_acc: 0.7987, top5_acc: 0.9919, loss_cls: 0.8681, loss: 0.8681 +2025-06-24 09:29:38,231 - pyskl - INFO - Epoch [9][500/1281] lr: 2.481e-02, eta: 11:04:12, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7906, top5_acc: 0.9881, loss_cls: 0.9029, loss: 0.9029 +2025-06-24 09:29:59,905 - pyskl - INFO - Epoch [9][600/1281] lr: 2.480e-02, eta: 11:03:45, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7975, top5_acc: 0.9875, loss_cls: 0.9283, loss: 0.9283 +2025-06-24 09:30:21,458 - pyskl - INFO - Epoch [9][700/1281] lr: 2.480e-02, eta: 11:03:16, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7588, top5_acc: 0.9812, loss_cls: 0.9946, loss: 0.9946 +2025-06-24 09:30:43,591 - pyskl - INFO - Epoch [9][800/1281] lr: 2.480e-02, eta: 11:02:57, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7588, top5_acc: 0.9831, loss_cls: 0.9968, loss: 0.9968 +2025-06-24 09:31:05,580 - pyskl - INFO - Epoch [9][900/1281] lr: 2.479e-02, eta: 11:02:36, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7919, top5_acc: 0.9844, loss_cls: 0.9026, loss: 0.9026 +2025-06-24 09:31:27,167 - pyskl - INFO - Epoch [9][1000/1281] lr: 2.479e-02, eta: 11:02:08, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7863, top5_acc: 0.9862, loss_cls: 0.9290, loss: 0.9290 +2025-06-24 09:31:48,587 - pyskl - INFO - Epoch [9][1100/1281] lr: 2.479e-02, eta: 11:01:37, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.8006, top5_acc: 0.9838, loss_cls: 0.9051, loss: 0.9051 +2025-06-24 09:32:10,387 - pyskl - INFO - Epoch [9][1200/1281] lr: 2.478e-02, eta: 11:01:12, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7881, top5_acc: 0.9831, loss_cls: 0.9081, loss: 0.9081 +2025-06-24 09:32:28,645 - pyskl - INFO - Saving checkpoint at 9 epochs +2025-06-24 09:33:11,355 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:33:11,422 - pyskl - INFO - +top1_acc 0.7586 +top5_acc 0.9754 +2025-06-24 09:33:11,422 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:33:11,430 - pyskl - INFO - +mean_acc 0.6656 +2025-06-24 09:33:11,432 - pyskl - INFO - Epoch(val) [9][533] top1_acc: 0.7586, top5_acc: 0.9754, mean_class_accuracy: 0.6656 +2025-06-24 09:33:51,552 - pyskl - INFO - Epoch [10][100/1281] lr: 2.477e-02, eta: 11:00:39, time: 0.401, data_time: 0.183, memory: 4082, top1_acc: 0.8225, top5_acc: 0.9900, loss_cls: 0.8178, loss: 0.8178 +2025-06-24 09:34:13,653 - pyskl - INFO - Epoch [10][200/1281] lr: 2.477e-02, eta: 11:00:19, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7994, top5_acc: 0.9938, loss_cls: 0.8538, loss: 0.8538 +2025-06-24 09:34:35,807 - pyskl - INFO - Epoch [10][300/1281] lr: 2.477e-02, eta: 11:00:00, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.7987, top5_acc: 0.9875, loss_cls: 0.8692, loss: 0.8692 +2025-06-24 09:34:57,856 - pyskl - INFO - Epoch [10][400/1281] lr: 2.476e-02, eta: 10:59:39, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8031, top5_acc: 0.9844, loss_cls: 0.8752, loss: 0.8752 +2025-06-24 09:35:19,950 - pyskl - INFO - Epoch [10][500/1281] lr: 2.476e-02, eta: 10:59:19, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7869, top5_acc: 0.9856, loss_cls: 0.9395, loss: 0.9395 +2025-06-24 09:35:41,740 - pyskl - INFO - Epoch [10][600/1281] lr: 2.476e-02, eta: 10:58:55, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7894, top5_acc: 0.9844, loss_cls: 0.9020, loss: 0.9020 +2025-06-24 09:36:03,714 - pyskl - INFO - Epoch [10][700/1281] lr: 2.475e-02, eta: 10:58:33, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8031, top5_acc: 0.9912, loss_cls: 0.8157, loss: 0.8157 +2025-06-24 09:36:25,510 - pyskl - INFO - Epoch [10][800/1281] lr: 2.475e-02, eta: 10:58:08, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8006, top5_acc: 0.9881, loss_cls: 0.8781, loss: 0.8781 +2025-06-24 09:36:47,206 - pyskl - INFO - Epoch [10][900/1281] lr: 2.474e-02, eta: 10:57:43, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8131, top5_acc: 0.9894, loss_cls: 0.8407, loss: 0.8407 +2025-06-24 09:37:08,917 - pyskl - INFO - Epoch [10][1000/1281] lr: 2.474e-02, eta: 10:57:17, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7887, top5_acc: 0.9888, loss_cls: 0.8969, loss: 0.8969 +2025-06-24 09:37:31,041 - pyskl - INFO - Epoch [10][1100/1281] lr: 2.473e-02, eta: 10:56:58, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8025, top5_acc: 0.9869, loss_cls: 0.8643, loss: 0.8643 +2025-06-24 09:37:52,683 - pyskl - INFO - Epoch [10][1200/1281] lr: 2.473e-02, eta: 10:56:31, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8100, top5_acc: 0.9888, loss_cls: 0.8420, loss: 0.8420 +2025-06-24 09:38:11,537 - pyskl - INFO - Saving checkpoint at 10 epochs +2025-06-24 09:38:54,467 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:38:54,533 - pyskl - INFO - +top1_acc 0.7518 +top5_acc 0.9729 +2025-06-24 09:38:54,533 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:38:54,540 - pyskl - INFO - +mean_acc 0.6424 +2025-06-24 09:38:54,542 - pyskl - INFO - Epoch(val) [10][533] top1_acc: 0.7518, top5_acc: 0.9729, mean_class_accuracy: 0.6424 +2025-06-24 09:39:34,143 - pyskl - INFO - Epoch [11][100/1281] lr: 2.472e-02, eta: 10:55:49, time: 0.396, data_time: 0.176, memory: 4082, top1_acc: 0.8087, top5_acc: 0.9894, loss_cls: 0.8468, loss: 0.8468 +2025-06-24 09:39:56,002 - pyskl - INFO - Epoch [11][200/1281] lr: 2.472e-02, eta: 10:55:26, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8056, top5_acc: 0.9838, loss_cls: 0.8797, loss: 0.8797 +2025-06-24 09:40:17,639 - pyskl - INFO - Epoch [11][300/1281] lr: 2.471e-02, eta: 10:55:00, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8125, top5_acc: 0.9888, loss_cls: 0.8520, loss: 0.8520 +2025-06-24 09:40:39,280 - pyskl - INFO - Epoch [11][400/1281] lr: 2.471e-02, eta: 10:54:34, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7963, top5_acc: 0.9888, loss_cls: 0.8416, loss: 0.8416 +2025-06-24 09:41:01,216 - pyskl - INFO - Epoch [11][500/1281] lr: 2.471e-02, eta: 10:54:12, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8200, top5_acc: 0.9925, loss_cls: 0.7988, loss: 0.7988 +2025-06-24 09:41:22,859 - pyskl - INFO - Epoch [11][600/1281] lr: 2.470e-02, eta: 10:53:46, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8169, top5_acc: 0.9875, loss_cls: 0.8241, loss: 0.8241 +2025-06-24 09:41:44,665 - pyskl - INFO - Epoch [11][700/1281] lr: 2.470e-02, eta: 10:53:22, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8025, top5_acc: 0.9856, loss_cls: 0.8492, loss: 0.8492 +2025-06-24 09:42:06,226 - pyskl - INFO - Epoch [11][800/1281] lr: 2.469e-02, eta: 10:52:55, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8213, top5_acc: 0.9888, loss_cls: 0.7913, loss: 0.7913 +2025-06-24 09:42:28,069 - pyskl - INFO - Epoch [11][900/1281] lr: 2.469e-02, eta: 10:52:32, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8244, top5_acc: 0.9919, loss_cls: 0.7635, loss: 0.7635 +2025-06-24 09:42:49,778 - pyskl - INFO - Epoch [11][1000/1281] lr: 2.468e-02, eta: 10:52:07, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8194, top5_acc: 0.9862, loss_cls: 0.8339, loss: 0.8339 +2025-06-24 09:43:11,665 - pyskl - INFO - Epoch [11][1100/1281] lr: 2.468e-02, eta: 10:51:44, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8081, top5_acc: 0.9875, loss_cls: 0.8483, loss: 0.8483 +2025-06-24 09:43:33,171 - pyskl - INFO - Epoch [11][1200/1281] lr: 2.467e-02, eta: 10:51:16, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8363, top5_acc: 0.9912, loss_cls: 0.7391, loss: 0.7391 +2025-06-24 09:43:51,625 - pyskl - INFO - Saving checkpoint at 11 epochs +2025-06-24 09:44:35,621 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:44:35,679 - pyskl - INFO - +top1_acc 0.7321 +top5_acc 0.9702 +2025-06-24 09:44:35,679 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:44:35,687 - pyskl - INFO - +mean_acc 0.6185 +2025-06-24 09:44:35,689 - pyskl - INFO - Epoch(val) [11][533] top1_acc: 0.7321, top5_acc: 0.9702, mean_class_accuracy: 0.6185 +2025-06-24 09:45:16,451 - pyskl - INFO - Epoch [12][100/1281] lr: 2.467e-02, eta: 10:50:50, time: 0.408, data_time: 0.187, memory: 4082, top1_acc: 0.8206, top5_acc: 0.9938, loss_cls: 0.7728, loss: 0.7728 +2025-06-24 09:45:38,650 - pyskl - INFO - Epoch [12][200/1281] lr: 2.466e-02, eta: 10:50:31, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.8269, top5_acc: 0.9906, loss_cls: 0.7804, loss: 0.7804 +2025-06-24 09:46:00,786 - pyskl - INFO - Epoch [12][300/1281] lr: 2.466e-02, eta: 10:50:12, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9888, loss_cls: 0.7969, loss: 0.7969 +2025-06-24 09:46:22,747 - pyskl - INFO - Epoch [12][400/1281] lr: 2.465e-02, eta: 10:49:50, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8294, top5_acc: 0.9900, loss_cls: 0.8024, loss: 0.8024 +2025-06-24 09:46:44,586 - pyskl - INFO - Epoch [12][500/1281] lr: 2.465e-02, eta: 10:49:27, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8113, top5_acc: 0.9881, loss_cls: 0.8308, loss: 0.8308 +2025-06-24 09:47:06,187 - pyskl - INFO - Epoch [12][600/1281] lr: 2.464e-02, eta: 10:49:00, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8331, top5_acc: 0.9919, loss_cls: 0.7683, loss: 0.7683 +2025-06-24 09:47:28,227 - pyskl - INFO - Epoch [12][700/1281] lr: 2.464e-02, eta: 10:48:40, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8281, top5_acc: 0.9869, loss_cls: 0.7649, loss: 0.7649 +2025-06-24 09:47:49,963 - pyskl - INFO - Epoch [12][800/1281] lr: 2.463e-02, eta: 10:48:15, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8137, top5_acc: 0.9906, loss_cls: 0.7936, loss: 0.7936 +2025-06-24 09:48:11,965 - pyskl - INFO - Epoch [12][900/1281] lr: 2.463e-02, eta: 10:47:54, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8244, top5_acc: 0.9931, loss_cls: 0.7869, loss: 0.7869 +2025-06-24 09:48:33,606 - pyskl - INFO - Epoch [12][1000/1281] lr: 2.462e-02, eta: 10:47:28, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8187, top5_acc: 0.9894, loss_cls: 0.7984, loss: 0.7984 +2025-06-24 09:48:55,224 - pyskl - INFO - Epoch [12][1100/1281] lr: 2.462e-02, eta: 10:47:03, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8350, top5_acc: 0.9912, loss_cls: 0.7822, loss: 0.7822 +2025-06-24 09:49:17,165 - pyskl - INFO - Epoch [12][1200/1281] lr: 2.461e-02, eta: 10:46:41, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8119, top5_acc: 0.9900, loss_cls: 0.7976, loss: 0.7976 +2025-06-24 09:49:35,379 - pyskl - INFO - Saving checkpoint at 12 epochs +2025-06-24 09:50:17,818 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:50:17,873 - pyskl - INFO - +top1_acc 0.8013 +top5_acc 0.9857 +2025-06-24 09:50:17,873 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:50:17,880 - pyskl - INFO - +mean_acc 0.7040 +2025-06-24 09:50:17,884 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_8.pth was removed +2025-06-24 09:50:18,047 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_12.pth. +2025-06-24 09:50:18,047 - pyskl - INFO - Best top1_acc is 0.8013 at 12 epoch. +2025-06-24 09:50:18,050 - pyskl - INFO - Epoch(val) [12][533] top1_acc: 0.8013, top5_acc: 0.9857, mean_class_accuracy: 0.7040 +2025-06-24 09:50:57,817 - pyskl - INFO - Epoch [13][100/1281] lr: 2.460e-02, eta: 10:46:02, time: 0.398, data_time: 0.181, memory: 4082, top1_acc: 0.8331, top5_acc: 0.9919, loss_cls: 0.7700, loss: 0.7700 +2025-06-24 09:51:20,345 - pyskl - INFO - Epoch [13][200/1281] lr: 2.460e-02, eta: 10:45:46, time: 0.225, data_time: 0.000, memory: 4082, top1_acc: 0.8231, top5_acc: 0.9944, loss_cls: 0.7650, loss: 0.7650 +2025-06-24 09:51:42,190 - pyskl - INFO - Epoch [13][300/1281] lr: 2.459e-02, eta: 10:45:23, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8031, top5_acc: 0.9912, loss_cls: 0.8340, loss: 0.8340 +2025-06-24 09:52:03,727 - pyskl - INFO - Epoch [13][400/1281] lr: 2.459e-02, eta: 10:44:57, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8275, top5_acc: 0.9919, loss_cls: 0.7658, loss: 0.7658 +2025-06-24 09:52:25,411 - pyskl - INFO - Epoch [13][500/1281] lr: 2.458e-02, eta: 10:44:32, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9919, loss_cls: 0.7356, loss: 0.7356 +2025-06-24 09:52:47,128 - pyskl - INFO - Epoch [13][600/1281] lr: 2.458e-02, eta: 10:44:08, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8381, top5_acc: 0.9931, loss_cls: 0.7450, loss: 0.7450 +2025-06-24 09:53:08,859 - pyskl - INFO - Epoch [13][700/1281] lr: 2.457e-02, eta: 10:43:43, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8438, top5_acc: 0.9919, loss_cls: 0.7175, loss: 0.7175 +2025-06-24 09:53:30,747 - pyskl - INFO - Epoch [13][800/1281] lr: 2.457e-02, eta: 10:43:21, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8206, top5_acc: 0.9938, loss_cls: 0.7811, loss: 0.7811 +2025-06-24 09:53:52,317 - pyskl - INFO - Epoch [13][900/1281] lr: 2.456e-02, eta: 10:42:55, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8131, top5_acc: 0.9856, loss_cls: 0.8467, loss: 0.8467 +2025-06-24 09:54:13,938 - pyskl - INFO - Epoch [13][1000/1281] lr: 2.455e-02, eta: 10:42:30, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8094, top5_acc: 0.9925, loss_cls: 0.8224, loss: 0.8224 +2025-06-24 09:54:36,026 - pyskl - INFO - Epoch [13][1100/1281] lr: 2.455e-02, eta: 10:42:10, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8281, top5_acc: 0.9912, loss_cls: 0.7708, loss: 0.7708 +2025-06-24 09:54:57,619 - pyskl - INFO - Epoch [13][1200/1281] lr: 2.454e-02, eta: 10:41:44, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8350, top5_acc: 0.9919, loss_cls: 0.7597, loss: 0.7597 +2025-06-24 09:55:16,133 - pyskl - INFO - Saving checkpoint at 13 epochs +2025-06-24 09:55:58,922 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:55:58,976 - pyskl - INFO - +top1_acc 0.7985 +top5_acc 0.9809 +2025-06-24 09:55:58,976 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:55:58,982 - pyskl - INFO - +mean_acc 0.7333 +2025-06-24 09:55:58,984 - pyskl - INFO - Epoch(val) [13][533] top1_acc: 0.7985, top5_acc: 0.9809, mean_class_accuracy: 0.7333 +2025-06-24 09:56:39,069 - pyskl - INFO - Epoch [14][100/1281] lr: 2.453e-02, eta: 10:41:08, time: 0.401, data_time: 0.181, memory: 4082, top1_acc: 0.8281, top5_acc: 0.9925, loss_cls: 0.7564, loss: 0.7564 +2025-06-24 09:57:01,221 - pyskl - INFO - Epoch [14][200/1281] lr: 2.453e-02, eta: 10:40:49, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.8519, top5_acc: 0.9925, loss_cls: 0.7284, loss: 0.7284 +2025-06-24 09:57:23,075 - pyskl - INFO - Epoch [14][300/1281] lr: 2.452e-02, eta: 10:40:26, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8281, top5_acc: 0.9931, loss_cls: 0.7463, loss: 0.7463 +2025-06-24 09:57:45,048 - pyskl - INFO - Epoch [14][400/1281] lr: 2.452e-02, eta: 10:40:04, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8331, top5_acc: 0.9900, loss_cls: 0.7583, loss: 0.7583 +2025-06-24 09:58:07,378 - pyskl - INFO - Epoch [14][500/1281] lr: 2.451e-02, eta: 10:39:47, time: 0.223, data_time: 0.000, memory: 4082, top1_acc: 0.8394, top5_acc: 0.9912, loss_cls: 0.7263, loss: 0.7263 +2025-06-24 09:58:29,524 - pyskl - INFO - Epoch [14][600/1281] lr: 2.451e-02, eta: 10:39:27, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9862, loss_cls: 0.7573, loss: 0.7573 +2025-06-24 09:58:51,431 - pyskl - INFO - Epoch [14][700/1281] lr: 2.450e-02, eta: 10:39:04, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9900, loss_cls: 0.7489, loss: 0.7489 +2025-06-24 09:59:12,984 - pyskl - INFO - Epoch [14][800/1281] lr: 2.449e-02, eta: 10:38:39, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8325, top5_acc: 0.9894, loss_cls: 0.7612, loss: 0.7612 +2025-06-24 09:59:34,723 - pyskl - INFO - Epoch [14][900/1281] lr: 2.449e-02, eta: 10:38:15, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8256, top5_acc: 0.9931, loss_cls: 0.7695, loss: 0.7695 +2025-06-24 09:59:56,695 - pyskl - INFO - Epoch [14][1000/1281] lr: 2.448e-02, eta: 10:37:53, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8356, top5_acc: 0.9906, loss_cls: 0.7733, loss: 0.7733 +2025-06-24 10:00:18,314 - pyskl - INFO - Epoch [14][1100/1281] lr: 2.448e-02, eta: 10:37:28, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8144, top5_acc: 0.9919, loss_cls: 0.8028, loss: 0.8028 +2025-06-24 10:00:40,203 - pyskl - INFO - Epoch [14][1200/1281] lr: 2.447e-02, eta: 10:37:06, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8231, top5_acc: 0.9875, loss_cls: 0.7676, loss: 0.7676 +2025-06-24 10:00:58,530 - pyskl - INFO - Saving checkpoint at 14 epochs +2025-06-24 10:01:41,500 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:01:41,561 - pyskl - INFO - +top1_acc 0.7957 +top5_acc 0.9810 +2025-06-24 10:01:41,561 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:01:41,568 - pyskl - INFO - +mean_acc 0.7165 +2025-06-24 10:01:41,571 - pyskl - INFO - Epoch(val) [14][533] top1_acc: 0.7957, top5_acc: 0.9810, mean_class_accuracy: 0.7165 +2025-06-24 10:02:20,753 - pyskl - INFO - Epoch [15][100/1281] lr: 2.446e-02, eta: 10:36:21, time: 0.392, data_time: 0.169, memory: 4082, top1_acc: 0.8769, top5_acc: 0.9969, loss_cls: 0.6153, loss: 0.6153 +2025-06-24 10:02:42,596 - pyskl - INFO - Epoch [15][200/1281] lr: 2.445e-02, eta: 10:35:58, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8331, top5_acc: 0.9900, loss_cls: 0.7392, loss: 0.7392 +2025-06-24 10:03:04,688 - pyskl - INFO - Epoch [15][300/1281] lr: 2.445e-02, eta: 10:35:38, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9969, loss_cls: 0.6920, loss: 0.6920 +2025-06-24 10:03:26,325 - pyskl - INFO - Epoch [15][400/1281] lr: 2.444e-02, eta: 10:35:13, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8363, top5_acc: 0.9931, loss_cls: 0.7364, loss: 0.7364 +2025-06-24 10:03:47,782 - pyskl - INFO - Epoch [15][500/1281] lr: 2.444e-02, eta: 10:34:47, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8394, top5_acc: 0.9919, loss_cls: 0.7277, loss: 0.7277 +2025-06-24 10:04:09,802 - pyskl - INFO - Epoch [15][600/1281] lr: 2.443e-02, eta: 10:34:26, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8263, top5_acc: 0.9831, loss_cls: 0.8106, loss: 0.8106 +2025-06-24 10:04:31,679 - pyskl - INFO - Epoch [15][700/1281] lr: 2.442e-02, eta: 10:34:04, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8406, top5_acc: 0.9919, loss_cls: 0.7027, loss: 0.7027 +2025-06-24 10:04:53,648 - pyskl - INFO - Epoch [15][800/1281] lr: 2.442e-02, eta: 10:33:42, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8331, top5_acc: 0.9919, loss_cls: 0.7332, loss: 0.7332 +2025-06-24 10:05:15,051 - pyskl - INFO - Epoch [15][900/1281] lr: 2.441e-02, eta: 10:33:15, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.8356, top5_acc: 0.9931, loss_cls: 0.7148, loss: 0.7148 +2025-06-24 10:05:36,617 - pyskl - INFO - Epoch [15][1000/1281] lr: 2.441e-02, eta: 10:32:50, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8600, top5_acc: 0.9888, loss_cls: 0.6920, loss: 0.6920 +2025-06-24 10:05:58,389 - pyskl - INFO - Epoch [15][1100/1281] lr: 2.440e-02, eta: 10:32:27, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8475, top5_acc: 0.9900, loss_cls: 0.7229, loss: 0.7229 +2025-06-24 10:06:20,467 - pyskl - INFO - Epoch [15][1200/1281] lr: 2.439e-02, eta: 10:32:06, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8631, top5_acc: 0.9919, loss_cls: 0.6530, loss: 0.6530 +2025-06-24 10:06:38,618 - pyskl - INFO - Saving checkpoint at 15 epochs +2025-06-24 10:07:21,496 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:07:21,570 - pyskl - INFO - +top1_acc 0.7712 +top5_acc 0.9791 +2025-06-24 10:07:21,570 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:07:21,577 - pyskl - INFO - +mean_acc 0.7057 +2025-06-24 10:07:21,579 - pyskl - INFO - Epoch(val) [15][533] top1_acc: 0.7712, top5_acc: 0.9791, mean_class_accuracy: 0.7057 +2025-06-24 10:08:01,989 - pyskl - INFO - Epoch [16][100/1281] lr: 2.438e-02, eta: 10:31:33, time: 0.404, data_time: 0.182, memory: 4082, top1_acc: 0.8594, top5_acc: 0.9912, loss_cls: 0.6934, loss: 0.6934 +2025-06-24 10:08:23,911 - pyskl - INFO - Epoch [16][200/1281] lr: 2.438e-02, eta: 10:31:11, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8344, top5_acc: 0.9938, loss_cls: 0.6830, loss: 0.6830 +2025-06-24 10:08:45,990 - pyskl - INFO - Epoch [16][300/1281] lr: 2.437e-02, eta: 10:30:51, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8400, top5_acc: 0.9950, loss_cls: 0.7066, loss: 0.7066 +2025-06-24 10:09:07,766 - pyskl - INFO - Epoch [16][400/1281] lr: 2.436e-02, eta: 10:30:27, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8562, top5_acc: 0.9944, loss_cls: 0.6945, loss: 0.6945 +2025-06-24 10:09:29,497 - pyskl - INFO - Epoch [16][500/1281] lr: 2.436e-02, eta: 10:30:04, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8475, top5_acc: 0.9938, loss_cls: 0.7254, loss: 0.7254 +2025-06-24 10:09:51,645 - pyskl - INFO - Epoch [16][600/1281] lr: 2.435e-02, eta: 10:29:44, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8369, top5_acc: 0.9919, loss_cls: 0.7326, loss: 0.7326 +2025-06-24 10:10:13,300 - pyskl - INFO - Epoch [16][700/1281] lr: 2.434e-02, eta: 10:29:19, time: 0.217, data_time: 0.001, memory: 4082, top1_acc: 0.8431, top5_acc: 0.9925, loss_cls: 0.7079, loss: 0.7079 +2025-06-24 10:10:35,059 - pyskl - INFO - Epoch [16][800/1281] lr: 2.434e-02, eta: 10:28:56, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9938, loss_cls: 0.7072, loss: 0.7072 +2025-06-24 10:10:56,939 - pyskl - INFO - Epoch [16][900/1281] lr: 2.433e-02, eta: 10:28:34, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8462, top5_acc: 0.9900, loss_cls: 0.7080, loss: 0.7080 +2025-06-24 10:11:18,791 - pyskl - INFO - Epoch [16][1000/1281] lr: 2.432e-02, eta: 10:28:11, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8438, top5_acc: 0.9931, loss_cls: 0.7220, loss: 0.7220 +2025-06-24 10:11:40,411 - pyskl - INFO - Epoch [16][1100/1281] lr: 2.432e-02, eta: 10:27:47, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8337, top5_acc: 0.9900, loss_cls: 0.7717, loss: 0.7717 +2025-06-24 10:12:02,017 - pyskl - INFO - Epoch [16][1200/1281] lr: 2.431e-02, eta: 10:27:22, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9931, loss_cls: 0.7443, loss: 0.7443 +2025-06-24 10:12:20,614 - pyskl - INFO - Saving checkpoint at 16 epochs +2025-06-24 10:13:27,841 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:13:27,904 - pyskl - INFO - +top1_acc 0.8165 +top5_acc 0.9831 +2025-06-24 10:13:27,904 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:13:27,912 - pyskl - INFO - +mean_acc 0.7314 +2025-06-24 10:13:27,916 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_12.pth was removed +2025-06-24 10:13:28,095 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_16.pth. +2025-06-24 10:13:28,096 - pyskl - INFO - Best top1_acc is 0.8165 at 16 epoch. +2025-06-24 10:13:28,098 - pyskl - INFO - Epoch(val) [16][533] top1_acc: 0.8165, top5_acc: 0.9831, mean_class_accuracy: 0.7314 +2025-06-24 10:14:27,975 - pyskl - INFO - Epoch [17][100/1281] lr: 2.430e-02, eta: 10:29:31, time: 0.599, data_time: 0.184, memory: 4082, top1_acc: 0.8619, top5_acc: 0.9962, loss_cls: 0.6835, loss: 0.6835 +2025-06-24 10:15:09,300 - pyskl - INFO - Epoch [17][200/1281] lr: 2.429e-02, eta: 10:31:49, time: 0.413, data_time: 0.001, memory: 4082, top1_acc: 0.8488, top5_acc: 0.9906, loss_cls: 0.6953, loss: 0.6953 +2025-06-24 10:15:50,782 - pyskl - INFO - Epoch [17][300/1281] lr: 2.428e-02, eta: 10:34:06, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8488, top5_acc: 0.9956, loss_cls: 0.6910, loss: 0.6910 +2025-06-24 10:16:32,089 - pyskl - INFO - Epoch [17][400/1281] lr: 2.428e-02, eta: 10:36:21, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9944, loss_cls: 0.6700, loss: 0.6700 +2025-06-24 10:17:13,826 - pyskl - INFO - Epoch [17][500/1281] lr: 2.427e-02, eta: 10:38:37, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8450, top5_acc: 0.9938, loss_cls: 0.6844, loss: 0.6844 +2025-06-24 10:17:55,318 - pyskl - INFO - Epoch [17][600/1281] lr: 2.426e-02, eta: 10:40:49, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8425, top5_acc: 0.9906, loss_cls: 0.7121, loss: 0.7121 +2025-06-24 10:18:36,753 - pyskl - INFO - Epoch [17][700/1281] lr: 2.426e-02, eta: 10:43:00, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8469, top5_acc: 0.9938, loss_cls: 0.7094, loss: 0.7094 +2025-06-24 10:19:18,050 - pyskl - INFO - Epoch [17][800/1281] lr: 2.425e-02, eta: 10:45:07, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8438, top5_acc: 0.9938, loss_cls: 0.6774, loss: 0.6774 +2025-06-24 10:19:59,520 - pyskl - INFO - Epoch [17][900/1281] lr: 2.424e-02, eta: 10:47:15, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8512, top5_acc: 0.9931, loss_cls: 0.6980, loss: 0.6980 +2025-06-24 10:20:40,778 - pyskl - INFO - Epoch [17][1000/1281] lr: 2.424e-02, eta: 10:49:19, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8556, top5_acc: 0.9919, loss_cls: 0.6673, loss: 0.6673 +2025-06-24 10:21:21,843 - pyskl - INFO - Epoch [17][1100/1281] lr: 2.423e-02, eta: 10:51:20, time: 0.411, data_time: 0.000, memory: 4082, top1_acc: 0.8375, top5_acc: 0.9919, loss_cls: 0.7194, loss: 0.7194 +2025-06-24 10:21:50,146 - pyskl - INFO - Epoch [17][1200/1281] lr: 2.422e-02, eta: 10:51:40, time: 0.283, data_time: 0.000, memory: 4082, top1_acc: 0.8512, top5_acc: 0.9888, loss_cls: 0.7074, loss: 0.7074 +2025-06-24 10:22:27,588 - pyskl - INFO - Saving checkpoint at 17 epochs +2025-06-24 10:23:34,681 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:23:34,750 - pyskl - INFO - +top1_acc 0.8298 +top5_acc 0.9863 +2025-06-24 10:23:34,750 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:23:34,758 - pyskl - INFO - +mean_acc 0.7617 +2025-06-24 10:23:34,763 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_16.pth was removed +2025-06-24 10:23:34,955 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_17.pth. +2025-06-24 10:23:34,956 - pyskl - INFO - Best top1_acc is 0.8298 at 17 epoch. +2025-06-24 10:23:34,958 - pyskl - INFO - Epoch(val) [17][533] top1_acc: 0.8298, top5_acc: 0.9863, mean_class_accuracy: 0.7617 +2025-06-24 10:24:36,513 - pyskl - INFO - Epoch [18][100/1281] lr: 2.421e-02, eta: 10:53:34, time: 0.615, data_time: 0.197, memory: 4082, top1_acc: 0.8781, top5_acc: 0.9919, loss_cls: 0.6051, loss: 0.6051 +2025-06-24 10:25:18,153 - pyskl - INFO - Epoch [18][200/1281] lr: 2.420e-02, eta: 10:55:35, time: 0.416, data_time: 0.001, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9956, loss_cls: 0.6520, loss: 0.6520 +2025-06-24 10:25:59,427 - pyskl - INFO - Epoch [18][300/1281] lr: 2.419e-02, eta: 10:57:32, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8644, top5_acc: 0.9962, loss_cls: 0.6115, loss: 0.6115 +2025-06-24 10:26:40,893 - pyskl - INFO - Epoch [18][400/1281] lr: 2.419e-02, eta: 10:59:29, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8469, top5_acc: 0.9944, loss_cls: 0.6870, loss: 0.6870 +2025-06-24 10:27:22,231 - pyskl - INFO - Epoch [18][500/1281] lr: 2.418e-02, eta: 11:01:23, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8506, top5_acc: 0.9919, loss_cls: 0.7159, loss: 0.7159 +2025-06-24 10:28:05,828 - pyskl - INFO - Epoch [18][600/1281] lr: 2.417e-02, eta: 11:03:33, time: 0.436, data_time: 0.000, memory: 4082, top1_acc: 0.8581, top5_acc: 0.9962, loss_cls: 0.6563, loss: 0.6563 +2025-06-24 10:28:47,133 - pyskl - INFO - Epoch [18][700/1281] lr: 2.417e-02, eta: 11:05:25, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8450, top5_acc: 0.9894, loss_cls: 0.7361, loss: 0.7361 +2025-06-24 10:29:28,537 - pyskl - INFO - Epoch [18][800/1281] lr: 2.416e-02, eta: 11:07:15, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8450, top5_acc: 0.9925, loss_cls: 0.7165, loss: 0.7165 +2025-06-24 10:30:09,888 - pyskl - INFO - Epoch [18][900/1281] lr: 2.415e-02, eta: 11:09:04, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8638, top5_acc: 0.9944, loss_cls: 0.6707, loss: 0.6707 +2025-06-24 10:30:51,307 - pyskl - INFO - Epoch [18][1000/1281] lr: 2.414e-02, eta: 11:10:52, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8606, top5_acc: 0.9931, loss_cls: 0.6632, loss: 0.6632 +2025-06-24 10:31:30,149 - pyskl - INFO - Epoch [18][1100/1281] lr: 2.414e-02, eta: 11:12:20, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8594, top5_acc: 0.9956, loss_cls: 0.6640, loss: 0.6640 +2025-06-24 10:31:59,711 - pyskl - INFO - Epoch [18][1200/1281] lr: 2.413e-02, eta: 11:12:39, time: 0.296, data_time: 0.000, memory: 4082, top1_acc: 0.8556, top5_acc: 0.9938, loss_cls: 0.6874, loss: 0.6874 +2025-06-24 10:32:37,154 - pyskl - INFO - Saving checkpoint at 18 epochs +2025-06-24 10:33:47,499 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:33:47,556 - pyskl - INFO - +top1_acc 0.8501 +top5_acc 0.9876 +2025-06-24 10:33:47,556 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:33:47,564 - pyskl - INFO - +mean_acc 0.7818 +2025-06-24 10:33:47,568 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_17.pth was removed +2025-06-24 10:33:47,759 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_18.pth. +2025-06-24 10:33:47,759 - pyskl - INFO - Best top1_acc is 0.8501 at 18 epoch. +2025-06-24 10:33:47,763 - pyskl - INFO - Epoch(val) [18][533] top1_acc: 0.8501, top5_acc: 0.9876, mean_class_accuracy: 0.7818 +2025-06-24 10:34:48,467 - pyskl - INFO - Epoch [19][100/1281] lr: 2.411e-02, eta: 11:14:03, time: 0.607, data_time: 0.193, memory: 4082, top1_acc: 0.8712, top5_acc: 0.9950, loss_cls: 0.6127, loss: 0.6127 +2025-06-24 10:35:30,349 - pyskl - INFO - Epoch [19][200/1281] lr: 2.411e-02, eta: 11:15:50, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.8662, top5_acc: 0.9962, loss_cls: 0.6301, loss: 0.6301 +2025-06-24 10:36:11,809 - pyskl - INFO - Epoch [19][300/1281] lr: 2.410e-02, eta: 11:17:32, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8669, top5_acc: 0.9962, loss_cls: 0.6470, loss: 0.6470 +2025-06-24 10:36:53,240 - pyskl - INFO - Epoch [19][400/1281] lr: 2.409e-02, eta: 11:19:12, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8581, top5_acc: 0.9950, loss_cls: 0.6616, loss: 0.6616 +2025-06-24 10:37:34,766 - pyskl - INFO - Epoch [19][500/1281] lr: 2.408e-02, eta: 11:20:52, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8550, top5_acc: 0.9950, loss_cls: 0.6706, loss: 0.6706 +2025-06-24 10:38:16,047 - pyskl - INFO - Epoch [19][600/1281] lr: 2.408e-02, eta: 11:22:30, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8606, top5_acc: 0.9919, loss_cls: 0.6576, loss: 0.6576 +2025-06-24 10:38:57,499 - pyskl - INFO - Epoch [19][700/1281] lr: 2.407e-02, eta: 11:24:07, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8506, top5_acc: 0.9944, loss_cls: 0.6541, loss: 0.6541 +2025-06-24 10:39:38,978 - pyskl - INFO - Epoch [19][800/1281] lr: 2.406e-02, eta: 11:25:43, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8462, top5_acc: 0.9912, loss_cls: 0.7062, loss: 0.7062 +2025-06-24 10:40:20,551 - pyskl - INFO - Epoch [19][900/1281] lr: 2.405e-02, eta: 11:27:19, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8225, top5_acc: 0.9938, loss_cls: 0.7769, loss: 0.7769 +2025-06-24 10:41:01,959 - pyskl - INFO - Epoch [19][1000/1281] lr: 2.405e-02, eta: 11:28:52, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8638, top5_acc: 0.9956, loss_cls: 0.6374, loss: 0.6374 +2025-06-24 10:41:39,513 - pyskl - INFO - Epoch [19][1100/1281] lr: 2.404e-02, eta: 11:29:58, time: 0.376, data_time: 0.000, memory: 4082, top1_acc: 0.8638, top5_acc: 0.9925, loss_cls: 0.6803, loss: 0.6803 +2025-06-24 10:42:09,515 - pyskl - INFO - Epoch [19][1200/1281] lr: 2.403e-02, eta: 11:30:10, time: 0.300, data_time: 0.000, memory: 4082, top1_acc: 0.8512, top5_acc: 0.9944, loss_cls: 0.6810, loss: 0.6810 +2025-06-24 10:42:46,843 - pyskl - INFO - Saving checkpoint at 19 epochs +2025-06-24 10:43:56,236 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:43:56,292 - pyskl - INFO - +top1_acc 0.7895 +top5_acc 0.9838 +2025-06-24 10:43:56,293 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:43:56,299 - pyskl - INFO - +mean_acc 0.7170 +2025-06-24 10:43:56,301 - pyskl - INFO - Epoch(val) [19][533] top1_acc: 0.7895, top5_acc: 0.9838, mean_class_accuracy: 0.7170 +2025-06-24 10:44:56,574 - pyskl - INFO - Epoch [20][100/1281] lr: 2.402e-02, eta: 11:31:13, time: 0.603, data_time: 0.187, memory: 4082, top1_acc: 0.8719, top5_acc: 0.9950, loss_cls: 0.6116, loss: 0.6116 +2025-06-24 10:45:38,356 - pyskl - INFO - Epoch [20][200/1281] lr: 2.401e-02, eta: 11:32:45, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8856, top5_acc: 0.9975, loss_cls: 0.5462, loss: 0.5462 +2025-06-24 10:46:19,843 - pyskl - INFO - Epoch [20][300/1281] lr: 2.400e-02, eta: 11:34:13, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8656, top5_acc: 0.9919, loss_cls: 0.6243, loss: 0.6243 +2025-06-24 10:47:01,179 - pyskl - INFO - Epoch [20][400/1281] lr: 2.399e-02, eta: 11:35:40, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8781, top5_acc: 0.9962, loss_cls: 0.6156, loss: 0.6156 +2025-06-24 10:47:42,580 - pyskl - INFO - Epoch [20][500/1281] lr: 2.398e-02, eta: 11:37:06, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8594, top5_acc: 0.9944, loss_cls: 0.6538, loss: 0.6538 +2025-06-24 10:48:24,034 - pyskl - INFO - Epoch [20][600/1281] lr: 2.398e-02, eta: 11:38:31, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9938, loss_cls: 0.6677, loss: 0.6677 +2025-06-24 10:49:05,474 - pyskl - INFO - Epoch [20][700/1281] lr: 2.397e-02, eta: 11:39:55, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8500, top5_acc: 0.9931, loss_cls: 0.6921, loss: 0.6921 +2025-06-24 10:49:46,956 - pyskl - INFO - Epoch [20][800/1281] lr: 2.396e-02, eta: 11:41:19, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9938, loss_cls: 0.7158, loss: 0.7158 +2025-06-24 10:50:28,506 - pyskl - INFO - Epoch [20][900/1281] lr: 2.395e-02, eta: 11:42:42, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8569, top5_acc: 0.9925, loss_cls: 0.7068, loss: 0.7068 +2025-06-24 10:51:09,721 - pyskl - INFO - Epoch [20][1000/1281] lr: 2.394e-02, eta: 11:44:02, time: 0.412, data_time: 0.000, memory: 4082, top1_acc: 0.8488, top5_acc: 0.9938, loss_cls: 0.6855, loss: 0.6855 +2025-06-24 10:51:47,530 - pyskl - INFO - Epoch [20][1100/1281] lr: 2.393e-02, eta: 11:44:58, time: 0.378, data_time: 0.000, memory: 4082, top1_acc: 0.8625, top5_acc: 0.9906, loss_cls: 0.6387, loss: 0.6387 +2025-06-24 10:52:17,681 - pyskl - INFO - Epoch [20][1200/1281] lr: 2.393e-02, eta: 11:45:04, time: 0.301, data_time: 0.000, memory: 4082, top1_acc: 0.8600, top5_acc: 0.9938, loss_cls: 0.6335, loss: 0.6335 +2025-06-24 10:52:54,798 - pyskl - INFO - Saving checkpoint at 20 epochs +2025-06-24 10:54:04,283 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:54:04,340 - pyskl - INFO - +top1_acc 0.7498 +top5_acc 0.9738 +2025-06-24 10:54:04,341 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:54:04,348 - pyskl - INFO - +mean_acc 0.6397 +2025-06-24 10:54:04,350 - pyskl - INFO - Epoch(val) [20][533] top1_acc: 0.7498, top5_acc: 0.9738, mean_class_accuracy: 0.6397 +2025-06-24 10:55:07,469 - pyskl - INFO - Epoch [21][100/1281] lr: 2.391e-02, eta: 11:46:09, time: 0.631, data_time: 0.200, memory: 4082, top1_acc: 0.8644, top5_acc: 0.9975, loss_cls: 0.6068, loss: 0.6068 +2025-06-24 10:55:49,001 - pyskl - INFO - Epoch [21][200/1281] lr: 2.390e-02, eta: 11:47:27, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8669, top5_acc: 0.9912, loss_cls: 0.6260, loss: 0.6260 +2025-06-24 10:56:30,364 - pyskl - INFO - Epoch [21][300/1281] lr: 2.389e-02, eta: 11:48:43, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8725, top5_acc: 0.9938, loss_cls: 0.6195, loss: 0.6195 +2025-06-24 10:57:11,708 - pyskl - INFO - Epoch [21][400/1281] lr: 2.389e-02, eta: 11:49:58, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8512, top5_acc: 0.9938, loss_cls: 0.6451, loss: 0.6451 +2025-06-24 10:57:53,110 - pyskl - INFO - Epoch [21][500/1281] lr: 2.388e-02, eta: 11:51:13, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8712, top5_acc: 0.9938, loss_cls: 0.6512, loss: 0.6512 +2025-06-24 10:58:34,361 - pyskl - INFO - Epoch [21][600/1281] lr: 2.387e-02, eta: 11:52:25, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8712, top5_acc: 0.9938, loss_cls: 0.6424, loss: 0.6424 +2025-06-24 10:59:15,679 - pyskl - INFO - Epoch [21][700/1281] lr: 2.386e-02, eta: 11:53:38, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8731, top5_acc: 0.9950, loss_cls: 0.6188, loss: 0.6188 +2025-06-24 10:59:57,101 - pyskl - INFO - Epoch [21][800/1281] lr: 2.385e-02, eta: 11:54:50, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8700, top5_acc: 0.9944, loss_cls: 0.5953, loss: 0.5953 +2025-06-24 11:00:38,556 - pyskl - INFO - Epoch [21][900/1281] lr: 2.384e-02, eta: 11:56:01, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9931, loss_cls: 0.6614, loss: 0.6614 +2025-06-24 11:01:19,869 - pyskl - INFO - Epoch [21][1000/1281] lr: 2.383e-02, eta: 11:57:11, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8800, top5_acc: 0.9969, loss_cls: 0.5992, loss: 0.5992 +2025-06-24 11:01:57,331 - pyskl - INFO - Epoch [21][1100/1281] lr: 2.383e-02, eta: 11:57:56, time: 0.375, data_time: 0.000, memory: 4082, top1_acc: 0.8550, top5_acc: 0.9950, loss_cls: 0.6637, loss: 0.6637 +2025-06-24 11:02:28,105 - pyskl - INFO - Epoch [21][1200/1281] lr: 2.382e-02, eta: 11:57:59, time: 0.308, data_time: 0.000, memory: 4082, top1_acc: 0.8444, top5_acc: 0.9900, loss_cls: 0.7203, loss: 0.7203 +2025-06-24 11:03:05,059 - pyskl - INFO - Saving checkpoint at 21 epochs +2025-06-24 11:04:15,607 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:04:15,665 - pyskl - INFO - +top1_acc 0.8371 +top5_acc 0.9869 +2025-06-24 11:04:15,665 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:04:15,672 - pyskl - INFO - +mean_acc 0.7807 +2025-06-24 11:04:15,674 - pyskl - INFO - Epoch(val) [21][533] top1_acc: 0.8371, top5_acc: 0.9869, mean_class_accuracy: 0.7807 +2025-06-24 11:05:18,697 - pyskl - INFO - Epoch [22][100/1281] lr: 2.380e-02, eta: 11:58:49, time: 0.630, data_time: 0.197, memory: 4082, top1_acc: 0.8750, top5_acc: 0.9938, loss_cls: 0.6106, loss: 0.6106 +2025-06-24 11:06:00,972 - pyskl - INFO - Epoch [22][200/1281] lr: 2.379e-02, eta: 12:00:01, time: 0.423, data_time: 0.000, memory: 4082, top1_acc: 0.8675, top5_acc: 0.9938, loss_cls: 0.6098, loss: 0.6098 +2025-06-24 11:06:44,419 - pyskl - INFO - Epoch [22][300/1281] lr: 2.378e-02, eta: 12:01:20, time: 0.434, data_time: 0.000, memory: 4082, top1_acc: 0.8800, top5_acc: 0.9975, loss_cls: 0.5817, loss: 0.5817 +2025-06-24 11:07:28,050 - pyskl - INFO - Epoch [22][400/1281] lr: 2.378e-02, eta: 12:02:38, time: 0.436, data_time: 0.000, memory: 4082, top1_acc: 0.8625, top5_acc: 0.9981, loss_cls: 0.6290, loss: 0.6290 +2025-06-24 11:08:09,954 - pyskl - INFO - Epoch [22][500/1281] lr: 2.377e-02, eta: 12:03:46, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.8600, top5_acc: 0.9962, loss_cls: 0.6444, loss: 0.6444 +2025-06-24 11:08:51,194 - pyskl - INFO - Epoch [22][600/1281] lr: 2.376e-02, eta: 12:04:49, time: 0.412, data_time: 0.000, memory: 4082, top1_acc: 0.8794, top5_acc: 0.9931, loss_cls: 0.6244, loss: 0.6244 +2025-06-24 11:09:32,559 - pyskl - INFO - Epoch [22][700/1281] lr: 2.375e-02, eta: 12:05:51, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8644, top5_acc: 0.9944, loss_cls: 0.6308, loss: 0.6308 +2025-06-24 11:10:13,924 - pyskl - INFO - Epoch [22][800/1281] lr: 2.374e-02, eta: 12:06:53, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8725, top5_acc: 0.9931, loss_cls: 0.6634, loss: 0.6634 +2025-06-24 11:10:55,288 - pyskl - INFO - Epoch [22][900/1281] lr: 2.373e-02, eta: 12:07:54, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8481, top5_acc: 0.9894, loss_cls: 0.7179, loss: 0.7179 +2025-06-24 11:11:36,609 - pyskl - INFO - Epoch [22][1000/1281] lr: 2.372e-02, eta: 12:08:55, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8806, top5_acc: 0.9956, loss_cls: 0.5623, loss: 0.5623 +2025-06-24 11:12:12,539 - pyskl - INFO - Epoch [22][1100/1281] lr: 2.371e-02, eta: 12:09:23, time: 0.359, data_time: 0.001, memory: 4082, top1_acc: 0.8631, top5_acc: 0.9919, loss_cls: 0.6724, loss: 0.6724 +2025-06-24 11:12:43,279 - pyskl - INFO - Epoch [22][1200/1281] lr: 2.370e-02, eta: 12:09:20, time: 0.307, data_time: 0.000, memory: 4082, top1_acc: 0.8638, top5_acc: 0.9931, loss_cls: 0.6381, loss: 0.6381 +2025-06-24 11:13:20,075 - pyskl - INFO - Saving checkpoint at 22 epochs +2025-06-24 11:14:31,349 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:14:31,406 - pyskl - INFO - +top1_acc 0.8542 +top5_acc 0.9903 +2025-06-24 11:14:31,406 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:14:31,414 - pyskl - INFO - +mean_acc 0.7782 +2025-06-24 11:14:31,418 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_18.pth was removed +2025-06-24 11:14:31,606 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_22.pth. +2025-06-24 11:14:31,607 - pyskl - INFO - Best top1_acc is 0.8542 at 22 epoch. +2025-06-24 11:14:31,610 - pyskl - INFO - Epoch(val) [22][533] top1_acc: 0.8542, top5_acc: 0.9903, mean_class_accuracy: 0.7782 +2025-06-24 11:15:32,379 - pyskl - INFO - Epoch [23][100/1281] lr: 2.369e-02, eta: 12:09:44, time: 0.608, data_time: 0.193, memory: 4082, top1_acc: 0.8706, top5_acc: 0.9962, loss_cls: 0.5879, loss: 0.5879 +2025-06-24 11:16:13,879 - pyskl - INFO - Epoch [23][200/1281] lr: 2.368e-02, eta: 12:10:42, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8838, top5_acc: 0.9969, loss_cls: 0.5528, loss: 0.5528 +2025-06-24 11:16:55,418 - pyskl - INFO - Epoch [23][300/1281] lr: 2.367e-02, eta: 12:11:40, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8706, top5_acc: 0.9969, loss_cls: 0.5799, loss: 0.5799 +2025-06-24 11:17:36,967 - pyskl - INFO - Epoch [23][400/1281] lr: 2.366e-02, eta: 12:12:38, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8775, top5_acc: 0.9950, loss_cls: 0.6084, loss: 0.6084 +2025-06-24 11:18:18,261 - pyskl - INFO - Epoch [23][500/1281] lr: 2.365e-02, eta: 12:13:33, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8656, top5_acc: 0.9944, loss_cls: 0.6079, loss: 0.6079 +2025-06-24 11:18:59,845 - pyskl - INFO - Epoch [23][600/1281] lr: 2.364e-02, eta: 12:14:29, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8762, top5_acc: 0.9900, loss_cls: 0.6426, loss: 0.6426 +2025-06-24 11:19:41,136 - pyskl - INFO - Epoch [23][700/1281] lr: 2.363e-02, eta: 12:15:23, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8844, top5_acc: 0.9931, loss_cls: 0.6235, loss: 0.6235 +2025-06-24 11:20:22,680 - pyskl - INFO - Epoch [23][800/1281] lr: 2.362e-02, eta: 12:16:18, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8838, top5_acc: 0.9950, loss_cls: 0.5678, loss: 0.5678 +2025-06-24 11:21:04,091 - pyskl - INFO - Epoch [23][900/1281] lr: 2.361e-02, eta: 12:17:11, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8712, top5_acc: 0.9919, loss_cls: 0.6296, loss: 0.6296 +2025-06-24 11:21:45,271 - pyskl - INFO - Epoch [23][1000/1281] lr: 2.360e-02, eta: 12:18:03, time: 0.412, data_time: 0.000, memory: 4082, top1_acc: 0.8725, top5_acc: 0.9956, loss_cls: 0.6044, loss: 0.6044 +2025-06-24 11:22:22,041 - pyskl - INFO - Epoch [23][1100/1281] lr: 2.359e-02, eta: 12:18:29, time: 0.368, data_time: 0.000, memory: 4082, top1_acc: 0.8625, top5_acc: 0.9938, loss_cls: 0.6304, loss: 0.6304 +2025-06-24 11:22:53,533 - pyskl - INFO - Epoch [23][1200/1281] lr: 2.359e-02, eta: 12:18:26, time: 0.315, data_time: 0.000, memory: 4082, top1_acc: 0.8669, top5_acc: 0.9912, loss_cls: 0.6364, loss: 0.6364 +2025-06-24 11:23:29,773 - pyskl - INFO - Saving checkpoint at 23 epochs +2025-06-24 11:24:40,861 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:24:40,922 - pyskl - INFO - +top1_acc 0.8317 +top5_acc 0.9854 +2025-06-24 11:24:40,922 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:24:40,931 - pyskl - INFO - +mean_acc 0.7633 +2025-06-24 11:24:40,934 - pyskl - INFO - Epoch(val) [23][533] top1_acc: 0.8317, top5_acc: 0.9854, mean_class_accuracy: 0.7633 +2025-06-24 11:25:41,435 - pyskl - INFO - Epoch [24][100/1281] lr: 2.357e-02, eta: 12:18:38, time: 0.605, data_time: 0.191, memory: 4082, top1_acc: 0.8800, top5_acc: 0.9994, loss_cls: 0.5919, loss: 0.5919 +2025-06-24 11:26:22,952 - pyskl - INFO - Epoch [24][200/1281] lr: 2.356e-02, eta: 12:19:29, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8562, top5_acc: 0.9938, loss_cls: 0.6413, loss: 0.6413 +2025-06-24 11:27:04,365 - pyskl - INFO - Epoch [24][300/1281] lr: 2.355e-02, eta: 12:20:18, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8738, top5_acc: 0.9956, loss_cls: 0.6238, loss: 0.6238 +2025-06-24 11:27:45,921 - pyskl - INFO - Epoch [24][400/1281] lr: 2.354e-02, eta: 12:21:08, time: 0.416, data_time: 0.001, memory: 4082, top1_acc: 0.8638, top5_acc: 0.9956, loss_cls: 0.6375, loss: 0.6375 +2025-06-24 11:28:27,393 - pyskl - INFO - Epoch [24][500/1281] lr: 2.353e-02, eta: 12:21:57, time: 0.415, data_time: 0.001, memory: 4082, top1_acc: 0.8538, top5_acc: 0.9900, loss_cls: 0.6589, loss: 0.6589 +2025-06-24 11:29:08,872 - pyskl - INFO - Epoch [24][600/1281] lr: 2.352e-02, eta: 12:22:45, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8675, top5_acc: 0.9938, loss_cls: 0.6543, loss: 0.6543 +2025-06-24 11:29:50,151 - pyskl - INFO - Epoch [24][700/1281] lr: 2.351e-02, eta: 12:23:32, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8900, top5_acc: 0.9962, loss_cls: 0.5404, loss: 0.5404 +2025-06-24 11:30:31,535 - pyskl - INFO - Epoch [24][800/1281] lr: 2.350e-02, eta: 12:24:18, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8769, top5_acc: 0.9931, loss_cls: 0.6213, loss: 0.6213 +2025-06-24 11:31:13,052 - pyskl - INFO - Epoch [24][900/1281] lr: 2.349e-02, eta: 12:25:05, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8688, top5_acc: 0.9969, loss_cls: 0.5747, loss: 0.5747 +2025-06-24 11:31:54,444 - pyskl - INFO - Epoch [24][1000/1281] lr: 2.348e-02, eta: 12:25:50, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8631, top5_acc: 0.9906, loss_cls: 0.6475, loss: 0.6475 +2025-06-24 11:32:31,227 - pyskl - INFO - Epoch [24][1100/1281] lr: 2.347e-02, eta: 12:26:11, time: 0.368, data_time: 0.000, memory: 4082, top1_acc: 0.8794, top5_acc: 0.9938, loss_cls: 0.5917, loss: 0.5917 +2025-06-24 11:33:01,802 - pyskl - INFO - Epoch [24][1200/1281] lr: 2.346e-02, eta: 12:25:58, time: 0.306, data_time: 0.000, memory: 4082, top1_acc: 0.8606, top5_acc: 0.9962, loss_cls: 0.6330, loss: 0.6330 +2025-06-24 11:33:39,117 - pyskl - INFO - Saving checkpoint at 24 epochs +2025-06-24 11:34:49,446 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:34:49,502 - pyskl - INFO - +top1_acc 0.8403 +top5_acc 0.9896 +2025-06-24 11:34:49,502 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:34:49,510 - pyskl - INFO - +mean_acc 0.7694 +2025-06-24 11:34:49,512 - pyskl - INFO - Epoch(val) [24][533] top1_acc: 0.8403, top5_acc: 0.9896, mean_class_accuracy: 0.7694 +2025-06-24 11:35:50,555 - pyskl - INFO - Epoch [25][100/1281] lr: 2.344e-02, eta: 12:26:05, time: 0.610, data_time: 0.194, memory: 4082, top1_acc: 0.8944, top5_acc: 0.9962, loss_cls: 0.5158, loss: 0.5158 +2025-06-24 11:36:32,101 - pyskl - INFO - Epoch [25][200/1281] lr: 2.343e-02, eta: 12:26:49, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8806, top5_acc: 0.9956, loss_cls: 0.5417, loss: 0.5417 +2025-06-24 11:37:13,554 - pyskl - INFO - Epoch [25][300/1281] lr: 2.342e-02, eta: 12:27:32, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8738, top5_acc: 0.9962, loss_cls: 0.5874, loss: 0.5874 +2025-06-24 11:37:54,995 - pyskl - INFO - Epoch [25][400/1281] lr: 2.341e-02, eta: 12:28:15, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8938, top5_acc: 0.9975, loss_cls: 0.5205, loss: 0.5205 +2025-06-24 11:38:36,372 - pyskl - INFO - Epoch [25][500/1281] lr: 2.340e-02, eta: 12:28:56, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8850, top5_acc: 0.9919, loss_cls: 0.5789, loss: 0.5789 +2025-06-24 11:39:17,711 - pyskl - INFO - Epoch [25][600/1281] lr: 2.339e-02, eta: 12:29:37, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8738, top5_acc: 0.9925, loss_cls: 0.6243, loss: 0.6243 +2025-06-24 11:39:59,349 - pyskl - INFO - Epoch [25][700/1281] lr: 2.338e-02, eta: 12:30:19, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8725, top5_acc: 0.9919, loss_cls: 0.6059, loss: 0.6059 +2025-06-24 11:40:40,740 - pyskl - INFO - Epoch [25][800/1281] lr: 2.337e-02, eta: 12:30:59, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8788, top5_acc: 0.9981, loss_cls: 0.5945, loss: 0.5945 +2025-06-24 11:41:22,194 - pyskl - INFO - Epoch [25][900/1281] lr: 2.336e-02, eta: 12:31:39, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8594, top5_acc: 0.9969, loss_cls: 0.6705, loss: 0.6705 +2025-06-24 11:42:03,808 - pyskl - INFO - Epoch [25][1000/1281] lr: 2.335e-02, eta: 12:32:19, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8600, top5_acc: 0.9938, loss_cls: 0.6437, loss: 0.6437 +2025-06-24 11:42:41,383 - pyskl - INFO - Epoch [25][1100/1281] lr: 2.334e-02, eta: 12:32:38, time: 0.376, data_time: 0.000, memory: 4082, top1_acc: 0.8800, top5_acc: 0.9906, loss_cls: 0.6120, loss: 0.6120 +2025-06-24 11:43:10,904 - pyskl - INFO - Epoch [25][1200/1281] lr: 2.333e-02, eta: 12:32:17, time: 0.295, data_time: 0.000, memory: 4082, top1_acc: 0.8700, top5_acc: 0.9944, loss_cls: 0.5978, loss: 0.5978 +2025-06-24 11:43:48,339 - pyskl - INFO - Saving checkpoint at 25 epochs +2025-06-24 11:44:58,130 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:44:58,184 - pyskl - INFO - +top1_acc 0.8187 +top5_acc 0.9881 +2025-06-24 11:44:58,185 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:44:58,192 - pyskl - INFO - +mean_acc 0.7542 +2025-06-24 11:44:58,193 - pyskl - INFO - Epoch(val) [25][533] top1_acc: 0.8187, top5_acc: 0.9881, mean_class_accuracy: 0.7542 +2025-06-24 11:45:59,922 - pyskl - INFO - Epoch [26][100/1281] lr: 2.332e-02, eta: 12:32:19, time: 0.617, data_time: 0.203, memory: 4082, top1_acc: 0.8850, top5_acc: 0.9950, loss_cls: 0.5757, loss: 0.5757 +2025-06-24 11:46:41,305 - pyskl - INFO - Epoch [26][200/1281] lr: 2.330e-02, eta: 12:32:57, time: 0.414, data_time: 0.001, memory: 4082, top1_acc: 0.8694, top5_acc: 0.9950, loss_cls: 0.6063, loss: 0.6063 +2025-06-24 11:47:22,710 - pyskl - INFO - Epoch [26][300/1281] lr: 2.329e-02, eta: 12:33:33, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8650, top5_acc: 0.9969, loss_cls: 0.5988, loss: 0.5988 +2025-06-24 11:48:04,121 - pyskl - INFO - Epoch [26][400/1281] lr: 2.328e-02, eta: 12:34:10, time: 0.414, data_time: 0.001, memory: 4082, top1_acc: 0.8631, top5_acc: 0.9931, loss_cls: 0.6201, loss: 0.6201 +2025-06-24 11:48:45,470 - pyskl - INFO - Epoch [26][500/1281] lr: 2.327e-02, eta: 12:34:45, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8781, top5_acc: 0.9925, loss_cls: 0.6072, loss: 0.6072 +2025-06-24 11:49:26,785 - pyskl - INFO - Epoch [26][600/1281] lr: 2.326e-02, eta: 12:35:20, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8762, top5_acc: 0.9938, loss_cls: 0.5898, loss: 0.5898 +2025-06-24 11:50:08,113 - pyskl - INFO - Epoch [26][700/1281] lr: 2.325e-02, eta: 12:35:55, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8838, top5_acc: 0.9981, loss_cls: 0.5485, loss: 0.5485 +2025-06-24 11:50:49,472 - pyskl - INFO - Epoch [26][800/1281] lr: 2.324e-02, eta: 12:36:29, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8769, top5_acc: 0.9944, loss_cls: 0.5719, loss: 0.5719 +2025-06-24 11:51:30,777 - pyskl - INFO - Epoch [26][900/1281] lr: 2.323e-02, eta: 12:37:02, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8812, top5_acc: 0.9969, loss_cls: 0.5477, loss: 0.5477 +2025-06-24 11:52:12,133 - pyskl - INFO - Epoch [26][1000/1281] lr: 2.322e-02, eta: 12:37:36, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8744, top5_acc: 0.9969, loss_cls: 0.5728, loss: 0.5728 +2025-06-24 11:52:49,232 - pyskl - INFO - Epoch [26][1100/1281] lr: 2.321e-02, eta: 12:37:48, time: 0.371, data_time: 0.000, memory: 4082, top1_acc: 0.8525, top5_acc: 0.9925, loss_cls: 0.6811, loss: 0.6811 +2025-06-24 11:53:20,013 - pyskl - INFO - Epoch [26][1200/1281] lr: 2.320e-02, eta: 12:37:30, time: 0.308, data_time: 0.001, memory: 4082, top1_acc: 0.8769, top5_acc: 0.9925, loss_cls: 0.5801, loss: 0.5801 +2025-06-24 11:53:57,014 - pyskl - INFO - Saving checkpoint at 26 epochs +2025-06-24 11:55:08,062 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:55:08,132 - pyskl - INFO - +top1_acc 0.8487 +top5_acc 0.9891 +2025-06-24 11:55:08,132 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:55:08,141 - pyskl - INFO - +mean_acc 0.7743 +2025-06-24 11:55:08,143 - pyskl - INFO - Epoch(val) [26][533] top1_acc: 0.8487, top5_acc: 0.9891, mean_class_accuracy: 0.7743 +2025-06-24 11:56:10,689 - pyskl - INFO - Epoch [27][100/1281] lr: 2.318e-02, eta: 12:37:29, time: 0.625, data_time: 0.201, memory: 4082, top1_acc: 0.8875, top5_acc: 0.9938, loss_cls: 0.5667, loss: 0.5667 +2025-06-24 11:56:52,066 - pyskl - INFO - Epoch [27][200/1281] lr: 2.317e-02, eta: 12:38:01, time: 0.414, data_time: 0.001, memory: 4082, top1_acc: 0.8956, top5_acc: 0.9962, loss_cls: 0.5288, loss: 0.5288 +2025-06-24 11:57:33,547 - pyskl - INFO - Epoch [27][300/1281] lr: 2.316e-02, eta: 12:38:33, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8806, top5_acc: 0.9975, loss_cls: 0.5499, loss: 0.5499 +2025-06-24 11:58:14,964 - pyskl - INFO - Epoch [27][400/1281] lr: 2.315e-02, eta: 12:39:04, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8844, top5_acc: 0.9938, loss_cls: 0.5670, loss: 0.5670 +2025-06-24 11:58:56,405 - pyskl - INFO - Epoch [27][500/1281] lr: 2.314e-02, eta: 12:39:35, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8725, top5_acc: 0.9950, loss_cls: 0.5743, loss: 0.5743 +2025-06-24 11:59:37,891 - pyskl - INFO - Epoch [27][600/1281] lr: 2.313e-02, eta: 12:40:05, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8700, top5_acc: 0.9938, loss_cls: 0.6134, loss: 0.6134 +2025-06-24 12:00:19,337 - pyskl - INFO - Epoch [27][700/1281] lr: 2.312e-02, eta: 12:40:35, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8831, top5_acc: 0.9975, loss_cls: 0.5445, loss: 0.5445 +2025-06-24 12:01:00,700 - pyskl - INFO - Epoch [27][800/1281] lr: 2.311e-02, eta: 12:41:04, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8762, top5_acc: 0.9925, loss_cls: 0.5915, loss: 0.5915 +2025-06-24 12:01:42,134 - pyskl - INFO - Epoch [27][900/1281] lr: 2.310e-02, eta: 12:41:33, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8719, top5_acc: 0.9938, loss_cls: 0.6077, loss: 0.6077 +2025-06-24 12:02:23,545 - pyskl - INFO - Epoch [27][1000/1281] lr: 2.308e-02, eta: 12:42:02, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8662, top5_acc: 0.9925, loss_cls: 0.6205, loss: 0.6205 +2025-06-24 12:02:59,861 - pyskl - INFO - Epoch [27][1100/1281] lr: 2.307e-02, eta: 12:42:06, time: 0.363, data_time: 0.000, memory: 4082, top1_acc: 0.8900, top5_acc: 0.9956, loss_cls: 0.5079, loss: 0.5079 +2025-06-24 12:03:30,616 - pyskl - INFO - Epoch [27][1200/1281] lr: 2.306e-02, eta: 12:41:45, time: 0.308, data_time: 0.000, memory: 4082, top1_acc: 0.8606, top5_acc: 0.9944, loss_cls: 0.6321, loss: 0.6321 +2025-06-24 12:04:07,331 - pyskl - INFO - Saving checkpoint at 27 epochs +2025-06-24 12:05:18,313 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:05:18,391 - pyskl - INFO - +top1_acc 0.8341 +top5_acc 0.9878 +2025-06-24 12:05:18,391 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:05:18,403 - pyskl - INFO - +mean_acc 0.7584 +2025-06-24 12:05:18,407 - pyskl - INFO - Epoch(val) [27][533] top1_acc: 0.8341, top5_acc: 0.9878, mean_class_accuracy: 0.7584 +2025-06-24 12:06:20,187 - pyskl - INFO - Epoch [28][100/1281] lr: 2.304e-02, eta: 12:41:35, time: 0.618, data_time: 0.203, memory: 4082, top1_acc: 0.8856, top5_acc: 0.9969, loss_cls: 0.5381, loss: 0.5381 +2025-06-24 12:07:01,671 - pyskl - INFO - Epoch [28][200/1281] lr: 2.303e-02, eta: 12:42:03, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8894, top5_acc: 0.9925, loss_cls: 0.5486, loss: 0.5486 +2025-06-24 12:07:43,138 - pyskl - INFO - Epoch [28][300/1281] lr: 2.302e-02, eta: 12:42:29, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8631, top5_acc: 0.9956, loss_cls: 0.6031, loss: 0.6031 +2025-06-24 12:08:24,692 - pyskl - INFO - Epoch [28][400/1281] lr: 2.301e-02, eta: 12:42:56, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8856, top5_acc: 0.9969, loss_cls: 0.5478, loss: 0.5478 +2025-06-24 12:09:06,006 - pyskl - INFO - Epoch [28][500/1281] lr: 2.300e-02, eta: 12:43:22, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8850, top5_acc: 0.9931, loss_cls: 0.5498, loss: 0.5498 +2025-06-24 12:09:47,449 - pyskl - INFO - Epoch [28][600/1281] lr: 2.299e-02, eta: 12:43:47, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.9000, top5_acc: 0.9956, loss_cls: 0.5373, loss: 0.5373 +2025-06-24 12:10:28,829 - pyskl - INFO - Epoch [28][700/1281] lr: 2.298e-02, eta: 12:44:12, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8719, top5_acc: 0.9950, loss_cls: 0.6131, loss: 0.6131 +2025-06-24 12:11:10,248 - pyskl - INFO - Epoch [28][800/1281] lr: 2.297e-02, eta: 12:44:37, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8775, top5_acc: 0.9944, loss_cls: 0.5961, loss: 0.5961 +2025-06-24 12:11:51,646 - pyskl - INFO - Epoch [28][900/1281] lr: 2.295e-02, eta: 12:45:01, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8775, top5_acc: 0.9969, loss_cls: 0.5597, loss: 0.5597 +2025-06-24 12:12:32,976 - pyskl - INFO - Epoch [28][1000/1281] lr: 2.294e-02, eta: 12:45:25, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8812, top5_acc: 0.9944, loss_cls: 0.6017, loss: 0.6017 +2025-06-24 12:13:09,125 - pyskl - INFO - Epoch [28][1100/1281] lr: 2.293e-02, eta: 12:45:26, time: 0.361, data_time: 0.000, memory: 4082, top1_acc: 0.8712, top5_acc: 0.9962, loss_cls: 0.6116, loss: 0.6116 +2025-06-24 12:13:40,965 - pyskl - INFO - Epoch [28][1200/1281] lr: 2.292e-02, eta: 12:45:07, time: 0.318, data_time: 0.000, memory: 4082, top1_acc: 0.8656, top5_acc: 0.9925, loss_cls: 0.6184, loss: 0.6184 +2025-06-24 12:14:16,840 - pyskl - INFO - Saving checkpoint at 28 epochs +2025-06-24 12:15:28,320 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:15:28,377 - pyskl - INFO - +top1_acc 0.8433 +top5_acc 0.9890 +2025-06-24 12:15:28,377 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:15:28,386 - pyskl - INFO - +mean_acc 0.7635 +2025-06-24 12:15:28,388 - pyskl - INFO - Epoch(val) [28][533] top1_acc: 0.8433, top5_acc: 0.9890, mean_class_accuracy: 0.7635 +2025-06-24 12:16:29,859 - pyskl - INFO - Epoch [29][100/1281] lr: 2.290e-02, eta: 12:44:50, time: 0.615, data_time: 0.200, memory: 4082, top1_acc: 0.8838, top5_acc: 0.9956, loss_cls: 0.5460, loss: 0.5460 +2025-06-24 12:17:11,199 - pyskl - INFO - Epoch [29][200/1281] lr: 2.289e-02, eta: 12:45:12, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.9025, top5_acc: 0.9988, loss_cls: 0.5085, loss: 0.5085 +2025-06-24 12:17:52,760 - pyskl - INFO - Epoch [29][300/1281] lr: 2.288e-02, eta: 12:45:35, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8912, top5_acc: 0.9969, loss_cls: 0.5285, loss: 0.5285 +2025-06-24 12:18:34,090 - pyskl - INFO - Epoch [29][400/1281] lr: 2.287e-02, eta: 12:45:57, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8812, top5_acc: 0.9950, loss_cls: 0.5744, loss: 0.5744 +2025-06-24 12:19:15,473 - pyskl - INFO - Epoch [29][500/1281] lr: 2.285e-02, eta: 12:46:18, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8812, top5_acc: 0.9938, loss_cls: 0.6147, loss: 0.6147 +2025-06-24 12:19:56,951 - pyskl - INFO - Epoch [29][600/1281] lr: 2.284e-02, eta: 12:46:40, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.9056, top5_acc: 0.9988, loss_cls: 0.4897, loss: 0.4897 +2025-06-24 12:20:38,332 - pyskl - INFO - Epoch [29][700/1281] lr: 2.283e-02, eta: 12:47:01, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8862, top5_acc: 0.9950, loss_cls: 0.5274, loss: 0.5274 +2025-06-24 12:21:19,898 - pyskl - INFO - Epoch [29][800/1281] lr: 2.282e-02, eta: 12:47:22, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8925, top5_acc: 0.9938, loss_cls: 0.5566, loss: 0.5566 +2025-06-24 12:22:01,291 - pyskl - INFO - Epoch [29][900/1281] lr: 2.281e-02, eta: 12:47:42, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8788, top5_acc: 0.9931, loss_cls: 0.5855, loss: 0.5855 +2025-06-24 12:22:42,623 - pyskl - INFO - Epoch [29][1000/1281] lr: 2.280e-02, eta: 12:48:02, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8819, top5_acc: 0.9962, loss_cls: 0.5600, loss: 0.5600 +2025-06-24 12:23:18,584 - pyskl - INFO - Epoch [29][1100/1281] lr: 2.279e-02, eta: 12:47:58, time: 0.360, data_time: 0.000, memory: 4082, top1_acc: 0.8681, top5_acc: 0.9956, loss_cls: 0.6217, loss: 0.6217 +2025-06-24 12:23:50,592 - pyskl - INFO - Epoch [29][1200/1281] lr: 2.277e-02, eta: 12:47:38, time: 0.320, data_time: 0.000, memory: 4082, top1_acc: 0.8800, top5_acc: 0.9950, loss_cls: 0.5622, loss: 0.5622 +2025-06-24 12:24:26,138 - pyskl - INFO - Saving checkpoint at 29 epochs +2025-06-24 12:25:38,170 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:25:38,227 - pyskl - INFO - +top1_acc 0.8093 +top5_acc 0.9835 +2025-06-24 12:25:38,227 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:25:38,235 - pyskl - INFO - +mean_acc 0.7359 +2025-06-24 12:25:38,237 - pyskl - INFO - Epoch(val) [29][533] top1_acc: 0.8093, top5_acc: 0.9835, mean_class_accuracy: 0.7359 +2025-06-24 12:26:47,646 - pyskl - INFO - Epoch [30][100/1281] lr: 2.275e-02, eta: 12:47:50, time: 0.694, data_time: 0.197, memory: 4082, top1_acc: 0.8875, top5_acc: 0.9969, loss_cls: 0.5374, loss: 0.5374 +2025-06-24 12:27:37,321 - pyskl - INFO - Epoch [30][200/1281] lr: 2.274e-02, eta: 12:48:43, time: 0.497, data_time: 0.001, memory: 4082, top1_acc: 0.8862, top5_acc: 0.9938, loss_cls: 0.5678, loss: 0.5678 +2025-06-24 12:28:25,924 - pyskl - INFO - Epoch [30][300/1281] lr: 2.273e-02, eta: 12:49:31, time: 0.486, data_time: 0.000, memory: 4082, top1_acc: 0.8781, top5_acc: 0.9931, loss_cls: 0.5803, loss: 0.5803 +2025-06-24 12:29:16,616 - pyskl - INFO - Epoch [30][400/1281] lr: 2.272e-02, eta: 12:50:27, time: 0.507, data_time: 0.000, memory: 4082, top1_acc: 0.8988, top5_acc: 0.9956, loss_cls: 0.5142, loss: 0.5142 +2025-06-24 12:30:06,943 - pyskl - INFO - Epoch [30][500/1281] lr: 2.271e-02, eta: 12:51:20, time: 0.503, data_time: 0.000, memory: 4082, top1_acc: 0.8850, top5_acc: 0.9931, loss_cls: 0.5687, loss: 0.5687 +2025-06-24 12:30:57,343 - pyskl - INFO - Epoch [30][600/1281] lr: 2.269e-02, eta: 12:52:14, time: 0.504, data_time: 0.000, memory: 4082, top1_acc: 0.8894, top5_acc: 0.9975, loss_cls: 0.5388, loss: 0.5388 +2025-06-24 12:31:48,667 - pyskl - INFO - Epoch [30][700/1281] lr: 2.268e-02, eta: 12:53:11, time: 0.513, data_time: 0.000, memory: 4082, top1_acc: 0.8725, top5_acc: 0.9969, loss_cls: 0.5816, loss: 0.5816 +2025-06-24 12:32:40,033 - pyskl - INFO - Epoch [30][800/1281] lr: 2.267e-02, eta: 12:54:07, time: 0.514, data_time: 0.000, memory: 4082, top1_acc: 0.8950, top5_acc: 0.9931, loss_cls: 0.5358, loss: 0.5358 +2025-06-24 12:33:09,828 - pyskl - INFO - Epoch [30][900/1281] lr: 2.266e-02, eta: 12:53:36, time: 0.298, data_time: 0.000, memory: 4082, top1_acc: 0.8912, top5_acc: 0.9938, loss_cls: 0.5500, loss: 0.5500 +2025-06-24 12:34:00,747 - pyskl - INFO - Epoch [30][1000/1281] lr: 2.265e-02, eta: 12:54:30, time: 0.509, data_time: 0.000, memory: 4082, top1_acc: 0.8762, top5_acc: 0.9969, loss_cls: 0.5601, loss: 0.5601 +2025-06-24 12:34:33,399 - pyskl - INFO - Epoch [30][1100/1281] lr: 2.263e-02, eta: 12:54:10, time: 0.326, data_time: 0.000, memory: 4082, top1_acc: 0.8731, top5_acc: 0.9981, loss_cls: 0.5736, loss: 0.5736 +2025-06-24 12:35:24,222 - pyskl - INFO - Epoch [30][1200/1281] lr: 2.262e-02, eta: 12:55:02, time: 0.508, data_time: 0.000, memory: 4082, top1_acc: 0.8994, top5_acc: 0.9925, loss_cls: 0.5220, loss: 0.5220 +2025-06-24 12:36:06,016 - pyskl - INFO - Saving checkpoint at 30 epochs +2025-06-24 12:37:17,390 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:37:17,448 - pyskl - INFO - +top1_acc 0.8357 +top5_acc 0.9871 +2025-06-24 12:37:17,448 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:37:17,456 - pyskl - INFO - +mean_acc 0.7821 +2025-06-24 12:37:17,458 - pyskl - INFO - Epoch(val) [30][533] top1_acc: 0.8357, top5_acc: 0.9871, mean_class_accuracy: 0.7821 +2025-06-24 12:38:53,486 - pyskl - INFO - Epoch [31][100/1281] lr: 2.260e-02, eta: 12:56:52, time: 0.960, data_time: 0.195, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9969, loss_cls: 0.7596, loss: 0.7596 +2025-06-24 12:39:46,966 - pyskl - INFO - Epoch [31][200/1281] lr: 2.259e-02, eta: 12:57:54, time: 0.535, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9944, loss_cls: 0.7014, loss: 0.7014 +2025-06-24 12:40:40,176 - pyskl - INFO - Epoch [31][300/1281] lr: 2.258e-02, eta: 12:58:54, time: 0.532, data_time: 0.000, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9962, loss_cls: 0.7403, loss: 0.7403 +2025-06-24 12:41:32,248 - pyskl - INFO - Epoch [31][400/1281] lr: 2.256e-02, eta: 12:59:49, time: 0.521, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9969, loss_cls: 0.6760, loss: 0.6760 +2025-06-24 12:42:04,791 - pyskl - INFO - Epoch [31][500/1281] lr: 2.255e-02, eta: 12:59:26, time: 0.325, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9956, loss_cls: 0.7451, loss: 0.7451 +2025-06-24 12:42:55,767 - pyskl - INFO - Epoch [31][600/1281] lr: 2.254e-02, eta: 13:00:16, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9950, loss_cls: 0.7317, loss: 0.7317 +2025-06-24 12:43:29,522 - pyskl - INFO - Epoch [31][700/1281] lr: 2.253e-02, eta: 12:59:58, time: 0.338, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9950, loss_cls: 0.7527, loss: 0.7527 +2025-06-24 12:44:22,324 - pyskl - INFO - Epoch [31][800/1281] lr: 2.252e-02, eta: 13:00:54, time: 0.528, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9962, loss_cls: 0.8095, loss: 0.8095 +2025-06-24 12:45:14,760 - pyskl - INFO - Epoch [31][900/1281] lr: 2.250e-02, eta: 13:01:48, time: 0.524, data_time: 0.000, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9931, loss_cls: 0.7727, loss: 0.7727 +2025-06-24 12:46:07,397 - pyskl - INFO - Epoch [31][1000/1281] lr: 2.249e-02, eta: 13:02:42, time: 0.526, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9962, loss_cls: 0.7031, loss: 0.7031 +2025-06-24 12:46:58,071 - pyskl - INFO - Epoch [31][1100/1281] lr: 2.248e-02, eta: 13:03:28, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9931, loss_cls: 0.8338, loss: 0.8338 +2025-06-24 12:47:49,987 - pyskl - INFO - Epoch [31][1200/1281] lr: 2.247e-02, eta: 13:04:19, time: 0.519, data_time: 0.000, memory: 4083, top1_acc: 0.8656, top5_acc: 0.9925, loss_cls: 0.8099, loss: 0.8099 +2025-06-24 12:48:33,553 - pyskl - INFO - Saving checkpoint at 31 epochs +2025-06-24 12:49:45,232 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:49:45,287 - pyskl - INFO - +top1_acc 0.8410 +top5_acc 0.9892 +2025-06-24 12:49:45,287 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:49:45,294 - pyskl - INFO - +mean_acc 0.7870 +2025-06-24 12:49:45,296 - pyskl - INFO - Epoch(val) [31][533] top1_acc: 0.8410, top5_acc: 0.9892, mean_class_accuracy: 0.7870 +2025-06-24 12:50:59,003 - pyskl - INFO - Epoch [32][100/1281] lr: 2.244e-02, eta: 13:04:31, time: 0.737, data_time: 0.207, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9981, loss_cls: 0.6500, loss: 0.6500 +2025-06-24 12:51:50,212 - pyskl - INFO - Epoch [32][200/1281] lr: 2.243e-02, eta: 13:05:18, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9956, loss_cls: 0.6847, loss: 0.6847 +2025-06-24 12:52:20,929 - pyskl - INFO - Epoch [32][300/1281] lr: 2.242e-02, eta: 13:04:46, time: 0.307, data_time: 0.000, memory: 4083, top1_acc: 0.8638, top5_acc: 0.9925, loss_cls: 0.7106, loss: 0.7106 +2025-06-24 12:53:14,754 - pyskl - INFO - Epoch [32][400/1281] lr: 2.241e-02, eta: 13:05:42, time: 0.538, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9975, loss_cls: 0.6868, loss: 0.6868 +2025-06-24 12:54:07,843 - pyskl - INFO - Epoch [32][500/1281] lr: 2.239e-02, eta: 13:06:34, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9969, loss_cls: 0.6310, loss: 0.6310 +2025-06-24 12:55:01,660 - pyskl - INFO - Epoch [32][600/1281] lr: 2.238e-02, eta: 13:07:29, time: 0.538, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9931, loss_cls: 0.6195, loss: 0.6195 +2025-06-24 12:55:55,356 - pyskl - INFO - Epoch [32][700/1281] lr: 2.237e-02, eta: 13:08:22, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9969, loss_cls: 0.6806, loss: 0.6806 +2025-06-24 12:56:48,433 - pyskl - INFO - Epoch [32][800/1281] lr: 2.236e-02, eta: 13:09:13, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9981, loss_cls: 0.6215, loss: 0.6215 +2025-06-24 12:57:42,637 - pyskl - INFO - Epoch [32][900/1281] lr: 2.234e-02, eta: 13:10:08, time: 0.542, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9944, loss_cls: 0.6444, loss: 0.6444 +2025-06-24 12:58:35,997 - pyskl - INFO - Epoch [32][1000/1281] lr: 2.233e-02, eta: 13:10:58, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9956, loss_cls: 0.6922, loss: 0.6922 +2025-06-24 12:59:30,071 - pyskl - INFO - Epoch [32][1100/1281] lr: 2.232e-02, eta: 13:11:51, time: 0.541, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9938, loss_cls: 0.6454, loss: 0.6454 +2025-06-24 13:00:12,456 - pyskl - INFO - Epoch [32][1200/1281] lr: 2.231e-02, eta: 13:12:01, time: 0.424, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9962, loss_cls: 0.6020, loss: 0.6020 +2025-06-24 13:00:50,680 - pyskl - INFO - Saving checkpoint at 32 epochs +2025-06-24 13:01:51,626 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:01:51,700 - pyskl - INFO - +top1_acc 0.8359 +top5_acc 0.9859 +2025-06-24 13:01:51,701 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:01:51,712 - pyskl - INFO - +mean_acc 0.7698 +2025-06-24 13:01:51,715 - pyskl - INFO - Epoch(val) [32][533] top1_acc: 0.8359, top5_acc: 0.9859, mean_class_accuracy: 0.7698 +2025-06-24 13:03:19,132 - pyskl - INFO - Epoch [33][100/1281] lr: 2.228e-02, eta: 13:12:56, time: 0.874, data_time: 0.193, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9975, loss_cls: 0.5939, loss: 0.5939 +2025-06-24 13:04:13,055 - pyskl - INFO - Epoch [33][200/1281] lr: 2.227e-02, eta: 13:13:47, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9956, loss_cls: 0.6315, loss: 0.6315 +2025-06-24 13:05:06,788 - pyskl - INFO - Epoch [33][300/1281] lr: 2.226e-02, eta: 13:14:36, time: 0.537, data_time: 0.001, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9950, loss_cls: 0.5401, loss: 0.5401 +2025-06-24 13:05:59,557 - pyskl - INFO - Epoch [33][400/1281] lr: 2.225e-02, eta: 13:15:22, time: 0.528, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9962, loss_cls: 0.5529, loss: 0.5529 +2025-06-24 13:06:52,854 - pyskl - INFO - Epoch [33][500/1281] lr: 2.223e-02, eta: 13:16:09, time: 0.533, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9981, loss_cls: 0.6148, loss: 0.6148 +2025-06-24 13:07:47,228 - pyskl - INFO - Epoch [33][600/1281] lr: 2.222e-02, eta: 13:16:59, time: 0.544, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9944, loss_cls: 0.6388, loss: 0.6388 +2025-06-24 13:08:40,746 - pyskl - INFO - Epoch [33][700/1281] lr: 2.221e-02, eta: 13:17:46, time: 0.535, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9956, loss_cls: 0.5838, loss: 0.5838 +2025-06-24 13:09:14,316 - pyskl - INFO - Epoch [33][800/1281] lr: 2.219e-02, eta: 13:17:20, time: 0.336, data_time: 0.001, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9944, loss_cls: 0.5895, loss: 0.5895 +2025-06-24 13:10:05,277 - pyskl - INFO - Epoch [33][900/1281] lr: 2.218e-02, eta: 13:17:57, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9938, loss_cls: 0.6086, loss: 0.6086 +2025-06-24 13:10:40,107 - pyskl - INFO - Epoch [33][1000/1281] lr: 2.217e-02, eta: 13:17:36, time: 0.348, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9969, loss_cls: 0.5617, loss: 0.5617 +2025-06-24 13:11:34,467 - pyskl - INFO - Epoch [33][1100/1281] lr: 2.216e-02, eta: 13:18:24, time: 0.544, data_time: 0.000, memory: 4083, top1_acc: 0.8681, top5_acc: 0.9925, loss_cls: 0.6875, loss: 0.6875 +2025-06-24 13:12:28,221 - pyskl - INFO - Epoch [33][1200/1281] lr: 2.214e-02, eta: 13:19:10, time: 0.538, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9938, loss_cls: 0.5428, loss: 0.5428 +2025-06-24 13:13:11,739 - pyskl - INFO - Saving checkpoint at 33 epochs +2025-06-24 13:14:24,267 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:14:24,338 - pyskl - INFO - +top1_acc 0.8294 +top5_acc 0.9845 +2025-06-24 13:14:24,338 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:14:24,345 - pyskl - INFO - +mean_acc 0.7640 +2025-06-24 13:14:24,347 - pyskl - INFO - Epoch(val) [33][533] top1_acc: 0.8294, top5_acc: 0.9845, mean_class_accuracy: 0.7640 +2025-06-24 13:15:51,479 - pyskl - INFO - Epoch [34][100/1281] lr: 2.212e-02, eta: 13:19:55, time: 0.871, data_time: 0.195, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9988, loss_cls: 0.5538, loss: 0.5538 +2025-06-24 13:16:44,870 - pyskl - INFO - Epoch [34][200/1281] lr: 2.211e-02, eta: 13:20:38, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9938, loss_cls: 0.5447, loss: 0.5447 +2025-06-24 13:17:38,822 - pyskl - INFO - Epoch [34][300/1281] lr: 2.209e-02, eta: 13:21:23, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9975, loss_cls: 0.5912, loss: 0.5912 +2025-06-24 13:18:08,250 - pyskl - INFO - Epoch [34][400/1281] lr: 2.208e-02, eta: 13:20:41, time: 0.294, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9950, loss_cls: 0.6062, loss: 0.6062 +2025-06-24 13:18:59,334 - pyskl - INFO - Epoch [34][500/1281] lr: 2.207e-02, eta: 13:21:15, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9950, loss_cls: 0.5554, loss: 0.5554 +2025-06-24 13:19:36,118 - pyskl - INFO - Epoch [34][600/1281] lr: 2.205e-02, eta: 13:20:59, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9988, loss_cls: 0.5643, loss: 0.5643 +2025-06-24 13:20:30,165 - pyskl - INFO - Epoch [34][700/1281] lr: 2.204e-02, eta: 13:21:43, time: 0.540, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9950, loss_cls: 0.6534, loss: 0.6534 +2025-06-24 13:21:23,385 - pyskl - INFO - Epoch [34][800/1281] lr: 2.203e-02, eta: 13:22:23, time: 0.532, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9956, loss_cls: 0.6227, loss: 0.6227 +2025-06-24 13:22:17,566 - pyskl - INFO - Epoch [34][900/1281] lr: 2.201e-02, eta: 13:23:07, time: 0.542, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9950, loss_cls: 0.5543, loss: 0.5543 +2025-06-24 13:23:11,222 - pyskl - INFO - Epoch [34][1000/1281] lr: 2.200e-02, eta: 13:23:47, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9950, loss_cls: 0.6440, loss: 0.6440 +2025-06-24 13:24:05,170 - pyskl - INFO - Epoch [34][1100/1281] lr: 2.199e-02, eta: 13:24:29, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9950, loss_cls: 0.5738, loss: 0.5738 +2025-06-24 13:24:58,544 - pyskl - INFO - Epoch [34][1200/1281] lr: 2.197e-02, eta: 13:25:08, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9994, loss_cls: 0.5807, loss: 0.5807 +2025-06-24 13:25:41,377 - pyskl - INFO - Saving checkpoint at 34 epochs +2025-06-24 13:26:52,453 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:26:52,510 - pyskl - INFO - +top1_acc 0.8542 +top5_acc 0.9896 +2025-06-24 13:26:52,510 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:26:52,517 - pyskl - INFO - +mean_acc 0.7938 +2025-06-24 13:26:52,519 - pyskl - INFO - Epoch(val) [34][533] top1_acc: 0.8542, top5_acc: 0.9896, mean_class_accuracy: 0.7938 +2025-06-24 13:28:04,101 - pyskl - INFO - Epoch [35][100/1281] lr: 2.195e-02, eta: 13:24:53, time: 0.716, data_time: 0.194, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9944, loss_cls: 0.5693, loss: 0.5693 +2025-06-24 13:28:36,693 - pyskl - INFO - Epoch [35][200/1281] lr: 2.194e-02, eta: 13:24:20, time: 0.326, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9981, loss_cls: 0.6012, loss: 0.6012 +2025-06-24 13:29:30,318 - pyskl - INFO - Epoch [35][300/1281] lr: 2.192e-02, eta: 13:24:59, time: 0.536, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9988, loss_cls: 0.5536, loss: 0.5536 +2025-06-24 13:30:23,824 - pyskl - INFO - Epoch [35][400/1281] lr: 2.191e-02, eta: 13:25:37, time: 0.535, data_time: 0.001, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9931, loss_cls: 0.5939, loss: 0.5939 +2025-06-24 13:31:17,091 - pyskl - INFO - Epoch [35][500/1281] lr: 2.190e-02, eta: 13:26:14, time: 0.533, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9944, loss_cls: 0.5614, loss: 0.5614 +2025-06-24 13:32:10,658 - pyskl - INFO - Epoch [35][600/1281] lr: 2.188e-02, eta: 13:26:52, time: 0.536, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9944, loss_cls: 0.6210, loss: 0.6210 +2025-06-24 13:33:04,624 - pyskl - INFO - Epoch [35][700/1281] lr: 2.187e-02, eta: 13:27:30, time: 0.540, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9950, loss_cls: 0.5426, loss: 0.5426 +2025-06-24 13:33:58,376 - pyskl - INFO - Epoch [35][800/1281] lr: 2.185e-02, eta: 13:28:07, time: 0.538, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9981, loss_cls: 0.4814, loss: 0.4814 +2025-06-24 13:34:51,902 - pyskl - INFO - Epoch [35][900/1281] lr: 2.184e-02, eta: 13:28:43, time: 0.535, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9962, loss_cls: 0.5923, loss: 0.5923 +2025-06-24 13:35:45,458 - pyskl - INFO - Epoch [35][1000/1281] lr: 2.183e-02, eta: 13:29:19, time: 0.536, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9962, loss_cls: 0.5444, loss: 0.5444 +2025-06-24 13:36:26,192 - pyskl - INFO - Epoch [35][1100/1281] lr: 2.181e-02, eta: 13:29:12, time: 0.407, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9956, loss_cls: 0.6053, loss: 0.6053 +2025-06-24 13:37:17,196 - pyskl - INFO - Epoch [35][1200/1281] lr: 2.180e-02, eta: 13:29:38, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9956, loss_cls: 0.5796, loss: 0.5796 +2025-06-24 13:37:36,429 - pyskl - INFO - Saving checkpoint at 35 epochs +2025-06-24 13:38:48,338 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:38:48,402 - pyskl - INFO - +top1_acc 0.8365 +top5_acc 0.9889 +2025-06-24 13:38:48,403 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:38:48,409 - pyskl - INFO - +mean_acc 0.7997 +2025-06-24 13:38:48,411 - pyskl - INFO - Epoch(val) [35][533] top1_acc: 0.8365, top5_acc: 0.9889, mean_class_accuracy: 0.7997 +2025-06-24 13:40:12,921 - pyskl - INFO - Epoch [36][100/1281] lr: 2.178e-02, eta: 13:30:00, time: 0.845, data_time: 0.195, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9944, loss_cls: 0.5446, loss: 0.5446 +2025-06-24 13:41:06,583 - pyskl - INFO - Epoch [36][200/1281] lr: 2.176e-02, eta: 13:30:35, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9950, loss_cls: 0.5804, loss: 0.5804 +2025-06-24 13:41:59,788 - pyskl - INFO - Epoch [36][300/1281] lr: 2.175e-02, eta: 13:31:07, time: 0.532, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9981, loss_cls: 0.5673, loss: 0.5673 +2025-06-24 13:42:53,825 - pyskl - INFO - Epoch [36][400/1281] lr: 2.173e-02, eta: 13:31:42, time: 0.540, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9956, loss_cls: 0.5855, loss: 0.5855 +2025-06-24 13:43:47,268 - pyskl - INFO - Epoch [36][500/1281] lr: 2.172e-02, eta: 13:32:15, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9969, loss_cls: 0.5480, loss: 0.5480 +2025-06-24 13:44:41,154 - pyskl - INFO - Epoch [36][600/1281] lr: 2.171e-02, eta: 13:32:48, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9988, loss_cls: 0.5388, loss: 0.5388 +2025-06-24 13:45:21,189 - pyskl - INFO - Epoch [36][700/1281] lr: 2.169e-02, eta: 13:32:37, time: 0.400, data_time: 0.001, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9962, loss_cls: 0.5813, loss: 0.5813 +2025-06-24 13:46:12,184 - pyskl - INFO - Epoch [36][800/1281] lr: 2.168e-02, eta: 13:33:01, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9962, loss_cls: 0.5077, loss: 0.5077 +2025-06-24 13:46:39,639 - pyskl - INFO - Epoch [36][900/1281] lr: 2.167e-02, eta: 13:32:09, time: 0.275, data_time: 0.001, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9950, loss_cls: 0.6018, loss: 0.6018 +2025-06-24 13:47:33,046 - pyskl - INFO - Epoch [36][1000/1281] lr: 2.165e-02, eta: 13:32:40, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9975, loss_cls: 0.5961, loss: 0.5961 +2025-06-24 13:48:22,894 - pyskl - INFO - Epoch [36][1100/1281] lr: 2.164e-02, eta: 13:32:59, time: 0.498, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9962, loss_cls: 0.6079, loss: 0.6079 +2025-06-24 13:49:12,468 - pyskl - INFO - Epoch [36][1200/1281] lr: 2.162e-02, eta: 13:33:17, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9938, loss_cls: 0.5862, loss: 0.5862 +2025-06-24 13:49:56,457 - pyskl - INFO - Saving checkpoint at 36 epochs +2025-06-24 13:51:07,988 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:51:08,043 - pyskl - INFO - +top1_acc 0.8359 +top5_acc 0.9903 +2025-06-24 13:51:08,043 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:51:08,050 - pyskl - INFO - +mean_acc 0.7770 +2025-06-24 13:51:08,052 - pyskl - INFO - Epoch(val) [36][533] top1_acc: 0.8359, top5_acc: 0.9903, mean_class_accuracy: 0.7770 +2025-06-24 13:52:35,024 - pyskl - INFO - Epoch [37][100/1281] lr: 2.160e-02, eta: 13:33:40, time: 0.870, data_time: 0.201, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9962, loss_cls: 0.5571, loss: 0.5571 +2025-06-24 13:53:28,715 - pyskl - INFO - Epoch [37][200/1281] lr: 2.158e-02, eta: 13:34:10, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9962, loss_cls: 0.5680, loss: 0.5680 +2025-06-24 13:54:14,744 - pyskl - INFO - Epoch [37][300/1281] lr: 2.157e-02, eta: 13:34:16, time: 0.460, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9950, loss_cls: 0.6040, loss: 0.6040 +2025-06-24 13:55:00,826 - pyskl - INFO - Epoch [37][400/1281] lr: 2.156e-02, eta: 13:34:22, time: 0.461, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9969, loss_cls: 0.5396, loss: 0.5396 +2025-06-24 13:55:28,269 - pyskl - INFO - Epoch [37][500/1281] lr: 2.154e-02, eta: 13:33:29, time: 0.274, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9962, loss_cls: 0.4958, loss: 0.4958 +2025-06-24 13:56:21,012 - pyskl - INFO - Epoch [37][600/1281] lr: 2.153e-02, eta: 13:33:56, time: 0.527, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9969, loss_cls: 0.5150, loss: 0.5150 +2025-06-24 13:57:14,653 - pyskl - INFO - Epoch [37][700/1281] lr: 2.151e-02, eta: 13:34:24, time: 0.536, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9975, loss_cls: 0.5552, loss: 0.5552 +2025-06-24 13:58:07,793 - pyskl - INFO - Epoch [37][800/1281] lr: 2.150e-02, eta: 13:34:51, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9975, loss_cls: 0.5610, loss: 0.5610 +2025-06-24 13:59:01,297 - pyskl - INFO - Epoch [37][900/1281] lr: 2.149e-02, eta: 13:35:19, time: 0.535, data_time: 0.001, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9938, loss_cls: 0.5721, loss: 0.5721 +2025-06-24 13:59:55,683 - pyskl - INFO - Epoch [37][1000/1281] lr: 2.147e-02, eta: 13:35:49, time: 0.544, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9962, loss_cls: 0.6321, loss: 0.6321 +2025-06-24 14:00:49,882 - pyskl - INFO - Epoch [37][1100/1281] lr: 2.146e-02, eta: 13:36:18, time: 0.542, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9950, loss_cls: 0.5578, loss: 0.5578 +2025-06-24 14:01:44,098 - pyskl - INFO - Epoch [37][1200/1281] lr: 2.144e-02, eta: 13:36:46, time: 0.542, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9962, loss_cls: 0.5530, loss: 0.5530 +2025-06-24 14:02:27,730 - pyskl - INFO - Saving checkpoint at 37 epochs +2025-06-24 14:03:28,889 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:03:28,974 - pyskl - INFO - +top1_acc 0.8657 +top5_acc 0.9924 +2025-06-24 14:03:28,975 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:03:28,995 - pyskl - INFO - +mean_acc 0.8169 +2025-06-24 14:03:29,009 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_22.pth was removed +2025-06-24 14:03:29,199 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_37.pth. +2025-06-24 14:03:29,200 - pyskl - INFO - Best top1_acc is 0.8657 at 37 epoch. +2025-06-24 14:03:29,203 - pyskl - INFO - Epoch(val) [37][533] top1_acc: 0.8657, top5_acc: 0.9924, mean_class_accuracy: 0.8169 +2025-06-24 14:04:31,091 - pyskl - INFO - Epoch [38][100/1281] lr: 2.142e-02, eta: 13:35:47, time: 0.619, data_time: 0.196, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9994, loss_cls: 0.5109, loss: 0.5109 +2025-06-24 14:05:23,590 - pyskl - INFO - Epoch [38][200/1281] lr: 2.140e-02, eta: 13:36:10, time: 0.525, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9981, loss_cls: 0.4781, loss: 0.4781 +2025-06-24 14:06:16,854 - pyskl - INFO - Epoch [38][300/1281] lr: 2.139e-02, eta: 13:36:35, time: 0.533, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9969, loss_cls: 0.5423, loss: 0.5423 +2025-06-24 14:07:09,416 - pyskl - INFO - Epoch [38][400/1281] lr: 2.137e-02, eta: 13:36:57, time: 0.526, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9969, loss_cls: 0.5025, loss: 0.5025 +2025-06-24 14:08:03,725 - pyskl - INFO - Epoch [38][500/1281] lr: 2.136e-02, eta: 13:37:25, time: 0.543, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9969, loss_cls: 0.5449, loss: 0.5449 +2025-06-24 14:08:57,309 - pyskl - INFO - Epoch [38][600/1281] lr: 2.134e-02, eta: 13:37:49, time: 0.536, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9944, loss_cls: 0.5971, loss: 0.5971 +2025-06-24 14:09:50,109 - pyskl - INFO - Epoch [38][700/1281] lr: 2.133e-02, eta: 13:38:11, time: 0.528, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9969, loss_cls: 0.5296, loss: 0.5296 +2025-06-24 14:10:43,564 - pyskl - INFO - Epoch [38][800/1281] lr: 2.132e-02, eta: 13:38:35, time: 0.535, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9981, loss_cls: 0.5400, loss: 0.5400 +2025-06-24 14:11:36,950 - pyskl - INFO - Epoch [38][900/1281] lr: 2.130e-02, eta: 13:38:59, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9956, loss_cls: 0.5975, loss: 0.5975 +2025-06-24 14:12:27,177 - pyskl - INFO - Epoch [38][1000/1281] lr: 2.129e-02, eta: 13:39:12, time: 0.502, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9931, loss_cls: 0.5624, loss: 0.5624 +2025-06-24 14:13:06,312 - pyskl - INFO - Epoch [38][1100/1281] lr: 2.127e-02, eta: 13:38:53, time: 0.391, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9938, loss_cls: 0.6108, loss: 0.6108 +2025-06-24 14:13:40,976 - pyskl - INFO - Epoch [38][1200/1281] lr: 2.126e-02, eta: 13:38:20, time: 0.347, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9962, loss_cls: 0.5523, loss: 0.5523 +2025-06-24 14:14:22,468 - pyskl - INFO - Saving checkpoint at 38 epochs +2025-06-24 14:15:34,413 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:15:34,472 - pyskl - INFO - +top1_acc 0.8723 +top5_acc 0.9912 +2025-06-24 14:15:34,472 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:15:34,479 - pyskl - INFO - +mean_acc 0.8217 +2025-06-24 14:15:34,483 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_37.pth was removed +2025-06-24 14:15:34,809 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_38.pth. +2025-06-24 14:15:34,809 - pyskl - INFO - Best top1_acc is 0.8723 at 38 epoch. +2025-06-24 14:15:34,812 - pyskl - INFO - Epoch(val) [38][533] top1_acc: 0.8723, top5_acc: 0.9912, mean_class_accuracy: 0.8217 +2025-06-24 14:17:00,847 - pyskl - INFO - Epoch [39][100/1281] lr: 2.123e-02, eta: 13:38:29, time: 0.860, data_time: 0.203, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9981, loss_cls: 0.5088, loss: 0.5088 +2025-06-24 14:17:53,817 - pyskl - INFO - Epoch [39][200/1281] lr: 2.122e-02, eta: 13:38:49, time: 0.530, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9981, loss_cls: 0.4724, loss: 0.4724 +2025-06-24 14:18:46,506 - pyskl - INFO - Epoch [39][300/1281] lr: 2.120e-02, eta: 13:39:09, time: 0.527, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 1.0000, loss_cls: 0.4745, loss: 0.4745 +2025-06-24 14:19:40,141 - pyskl - INFO - Epoch [39][400/1281] lr: 2.119e-02, eta: 13:39:31, time: 0.536, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9975, loss_cls: 0.5278, loss: 0.5278 +2025-06-24 14:20:34,559 - pyskl - INFO - Epoch [39][500/1281] lr: 2.117e-02, eta: 13:39:55, time: 0.544, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9950, loss_cls: 0.5408, loss: 0.5408 +2025-06-24 14:21:21,114 - pyskl - INFO - Epoch [39][600/1281] lr: 2.116e-02, eta: 13:39:55, time: 0.466, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9988, loss_cls: 0.5344, loss: 0.5344 +2025-06-24 14:22:05,243 - pyskl - INFO - Epoch [39][700/1281] lr: 2.114e-02, eta: 13:39:49, time: 0.441, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9962, loss_cls: 0.4975, loss: 0.4975 +2025-06-24 14:22:34,429 - pyskl - INFO - Epoch [39][800/1281] lr: 2.113e-02, eta: 13:38:59, time: 0.292, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9950, loss_cls: 0.5186, loss: 0.5186 +2025-06-24 14:23:26,208 - pyskl - INFO - Epoch [39][900/1281] lr: 2.111e-02, eta: 13:39:15, time: 0.518, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9962, loss_cls: 0.5401, loss: 0.5401 +2025-06-24 14:24:18,995 - pyskl - INFO - Epoch [39][1000/1281] lr: 2.110e-02, eta: 13:39:33, time: 0.528, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9956, loss_cls: 0.5587, loss: 0.5587 +2025-06-24 14:25:11,625 - pyskl - INFO - Epoch [39][1100/1281] lr: 2.108e-02, eta: 13:39:50, time: 0.526, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9975, loss_cls: 0.4794, loss: 0.4794 +2025-06-24 14:26:04,853 - pyskl - INFO - Epoch [39][1200/1281] lr: 2.107e-02, eta: 13:40:09, time: 0.532, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9950, loss_cls: 0.5666, loss: 0.5666 +2025-06-24 14:26:48,656 - pyskl - INFO - Saving checkpoint at 39 epochs +2025-06-24 14:28:00,455 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:28:00,543 - pyskl - INFO - +top1_acc 0.8538 +top5_acc 0.9908 +2025-06-24 14:28:00,543 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:28:00,552 - pyskl - INFO - +mean_acc 0.8109 +2025-06-24 14:28:00,554 - pyskl - INFO - Epoch(val) [39][533] top1_acc: 0.8538, top5_acc: 0.9908, mean_class_accuracy: 0.8109 +2025-06-24 14:29:28,045 - pyskl - INFO - Epoch [40][100/1281] lr: 2.104e-02, eta: 13:40:17, time: 0.875, data_time: 0.201, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9969, loss_cls: 0.5726, loss: 0.5726 +2025-06-24 14:30:14,859 - pyskl - INFO - Epoch [40][200/1281] lr: 2.103e-02, eta: 13:40:17, time: 0.468, data_time: 0.001, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9994, loss_cls: 0.4890, loss: 0.4890 +2025-06-24 14:30:58,509 - pyskl - INFO - Epoch [40][300/1281] lr: 2.101e-02, eta: 13:40:07, time: 0.436, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9969, loss_cls: 0.4694, loss: 0.4694 +2025-06-24 14:31:28,192 - pyskl - INFO - Epoch [40][400/1281] lr: 2.100e-02, eta: 13:39:19, time: 0.297, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 1.0000, loss_cls: 0.5633, loss: 0.5633 +2025-06-24 14:32:19,165 - pyskl - INFO - Epoch [40][500/1281] lr: 2.098e-02, eta: 13:39:30, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9969, loss_cls: 0.5876, loss: 0.5876 +2025-06-24 14:33:12,394 - pyskl - INFO - Epoch [40][600/1281] lr: 2.097e-02, eta: 13:39:47, time: 0.532, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9975, loss_cls: 0.5187, loss: 0.5187 +2025-06-24 14:34:06,126 - pyskl - INFO - Epoch [40][700/1281] lr: 2.095e-02, eta: 13:40:05, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9950, loss_cls: 0.5369, loss: 0.5369 +2025-06-24 14:35:00,174 - pyskl - INFO - Epoch [40][800/1281] lr: 2.094e-02, eta: 13:40:24, time: 0.540, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9944, loss_cls: 0.5813, loss: 0.5813 +2025-06-24 14:35:53,558 - pyskl - INFO - Epoch [40][900/1281] lr: 2.092e-02, eta: 13:40:41, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9956, loss_cls: 0.5808, loss: 0.5808 +2025-06-24 14:36:47,575 - pyskl - INFO - Epoch [40][1000/1281] lr: 2.091e-02, eta: 13:40:59, time: 0.540, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9962, loss_cls: 0.5608, loss: 0.5608 +2025-06-24 14:37:42,133 - pyskl - INFO - Epoch [40][1100/1281] lr: 2.089e-02, eta: 13:41:19, time: 0.546, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9975, loss_cls: 0.5648, loss: 0.5648 +2025-06-24 14:38:36,723 - pyskl - INFO - Epoch [40][1200/1281] lr: 2.088e-02, eta: 13:41:38, time: 0.546, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9950, loss_cls: 0.6091, loss: 0.6091 +2025-06-24 14:39:21,157 - pyskl - INFO - Saving checkpoint at 40 epochs +2025-06-24 14:40:33,823 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:40:33,880 - pyskl - INFO - +top1_acc 0.8398 +top5_acc 0.9898 +2025-06-24 14:40:33,880 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:40:33,888 - pyskl - INFO - +mean_acc 0.7937 +2025-06-24 14:40:33,890 - pyskl - INFO - Epoch(val) [40][533] top1_acc: 0.8398, top5_acc: 0.9898, mean_class_accuracy: 0.7937 +2025-06-24 14:41:44,911 - pyskl - INFO - Epoch [41][100/1281] lr: 2.085e-02, eta: 13:40:56, time: 0.710, data_time: 0.194, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9956, loss_cls: 0.5376, loss: 0.5376 +2025-06-24 14:42:38,834 - pyskl - INFO - Epoch [41][200/1281] lr: 2.083e-02, eta: 13:41:13, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9975, loss_cls: 0.4754, loss: 0.4754 +2025-06-24 14:43:31,999 - pyskl - INFO - Epoch [41][300/1281] lr: 2.082e-02, eta: 13:41:27, time: 0.532, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9962, loss_cls: 0.5234, loss: 0.5234 +2025-06-24 14:44:25,221 - pyskl - INFO - Epoch [41][400/1281] lr: 2.080e-02, eta: 13:41:42, time: 0.532, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9981, loss_cls: 0.4982, loss: 0.4982 +2025-06-24 14:45:19,420 - pyskl - INFO - Epoch [41][500/1281] lr: 2.079e-02, eta: 13:41:58, time: 0.542, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9962, loss_cls: 0.5744, loss: 0.5744 +2025-06-24 14:46:12,877 - pyskl - INFO - Epoch [41][600/1281] lr: 2.077e-02, eta: 13:42:13, time: 0.535, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9944, loss_cls: 0.5059, loss: 0.5059 +2025-06-24 14:47:06,319 - pyskl - INFO - Epoch [41][700/1281] lr: 2.076e-02, eta: 13:42:27, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9931, loss_cls: 0.5115, loss: 0.5115 +2025-06-24 14:48:00,089 - pyskl - INFO - Epoch [41][800/1281] lr: 2.074e-02, eta: 13:42:42, time: 0.538, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9950, loss_cls: 0.5598, loss: 0.5598 +2025-06-24 14:48:53,987 - pyskl - INFO - Epoch [41][900/1281] lr: 2.073e-02, eta: 13:42:57, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9975, loss_cls: 0.5094, loss: 0.5094 +2025-06-24 14:49:24,275 - pyskl - INFO - Epoch [41][1000/1281] lr: 2.071e-02, eta: 13:42:08, time: 0.303, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9969, loss_cls: 0.5186, loss: 0.5186 +2025-06-24 14:50:07,584 - pyskl - INFO - Epoch [41][1100/1281] lr: 2.070e-02, eta: 13:41:54, time: 0.433, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9956, loss_cls: 0.5189, loss: 0.5189 +2025-06-24 14:50:47,827 - pyskl - INFO - Epoch [41][1200/1281] lr: 2.068e-02, eta: 13:41:32, time: 0.402, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9962, loss_cls: 0.5828, loss: 0.5828 +2025-06-24 14:51:26,966 - pyskl - INFO - Saving checkpoint at 41 epochs +2025-06-24 14:52:27,435 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:52:27,504 - pyskl - INFO - +top1_acc 0.8551 +top5_acc 0.9898 +2025-06-24 14:52:27,504 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:52:27,513 - pyskl - INFO - +mean_acc 0.8097 +2025-06-24 14:52:27,516 - pyskl - INFO - Epoch(val) [41][533] top1_acc: 0.8551, top5_acc: 0.9898, mean_class_accuracy: 0.8097 +2025-06-24 14:53:46,109 - pyskl - INFO - Epoch [42][100/1281] lr: 2.065e-02, eta: 13:41:07, time: 0.786, data_time: 0.198, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9981, loss_cls: 0.4485, loss: 0.4485 +2025-06-24 14:54:34,168 - pyskl - INFO - Epoch [42][200/1281] lr: 2.064e-02, eta: 13:41:06, time: 0.481, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9975, loss_cls: 0.4749, loss: 0.4749 +2025-06-24 14:55:22,006 - pyskl - INFO - Epoch [42][300/1281] lr: 2.062e-02, eta: 13:41:04, time: 0.478, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9944, loss_cls: 0.5380, loss: 0.5380 +2025-06-24 14:56:10,136 - pyskl - INFO - Epoch [42][400/1281] lr: 2.061e-02, eta: 13:41:02, time: 0.481, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9956, loss_cls: 0.4796, loss: 0.4796 +2025-06-24 14:56:57,936 - pyskl - INFO - Epoch [42][500/1281] lr: 2.059e-02, eta: 13:40:59, time: 0.478, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9969, loss_cls: 0.4689, loss: 0.4689 +2025-06-24 14:57:45,801 - pyskl - INFO - Epoch [42][600/1281] lr: 2.057e-02, eta: 13:40:56, time: 0.479, data_time: 0.000, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9944, loss_cls: 0.6305, loss: 0.6305 +2025-06-24 14:58:33,872 - pyskl - INFO - Epoch [42][700/1281] lr: 2.056e-02, eta: 13:40:54, time: 0.481, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9962, loss_cls: 0.5253, loss: 0.5253 +2025-06-24 14:59:21,789 - pyskl - INFO - Epoch [42][800/1281] lr: 2.054e-02, eta: 13:40:51, time: 0.479, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9969, loss_cls: 0.5406, loss: 0.5406 +2025-06-24 14:59:59,048 - pyskl - INFO - Epoch [42][900/1281] lr: 2.053e-02, eta: 13:40:20, time: 0.373, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9950, loss_cls: 0.5460, loss: 0.5460 +2025-06-24 15:00:50,144 - pyskl - INFO - Epoch [42][1000/1281] lr: 2.051e-02, eta: 13:40:25, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9969, loss_cls: 0.4951, loss: 0.4951 +2025-06-24 15:01:13,597 - pyskl - INFO - Epoch [42][1100/1281] lr: 2.050e-02, eta: 13:39:18, time: 0.235, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9944, loss_cls: 0.5303, loss: 0.5303 +2025-06-24 15:01:54,488 - pyskl - INFO - Epoch [42][1200/1281] lr: 2.048e-02, eta: 13:38:57, time: 0.409, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9956, loss_cls: 0.5866, loss: 0.5866 +2025-06-24 15:02:34,360 - pyskl - INFO - Saving checkpoint at 42 epochs +2025-06-24 15:03:33,925 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:03:33,981 - pyskl - INFO - +top1_acc 0.8467 +top5_acc 0.9872 +2025-06-24 15:03:33,981 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:03:33,989 - pyskl - INFO - +mean_acc 0.7845 +2025-06-24 15:03:33,991 - pyskl - INFO - Epoch(val) [42][533] top1_acc: 0.8467, top5_acc: 0.9872, mean_class_accuracy: 0.7845 +2025-06-24 15:04:54,279 - pyskl - INFO - Epoch [43][100/1281] lr: 2.045e-02, eta: 13:38:34, time: 0.803, data_time: 0.197, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9956, loss_cls: 0.5299, loss: 0.5299 +2025-06-24 15:05:43,160 - pyskl - INFO - Epoch [43][200/1281] lr: 2.044e-02, eta: 13:38:32, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9956, loss_cls: 0.4510, loss: 0.4510 +2025-06-24 15:06:32,024 - pyskl - INFO - Epoch [43][300/1281] lr: 2.042e-02, eta: 13:38:31, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9969, loss_cls: 0.4775, loss: 0.4775 +2025-06-24 15:07:20,932 - pyskl - INFO - Epoch [43][400/1281] lr: 2.040e-02, eta: 13:38:29, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 0.9106, top5_acc: 1.0000, loss_cls: 0.4775, loss: 0.4775 +2025-06-24 15:08:09,973 - pyskl - INFO - Epoch [43][500/1281] lr: 2.039e-02, eta: 13:38:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9956, loss_cls: 0.4556, loss: 0.4556 +2025-06-24 15:08:58,964 - pyskl - INFO - Epoch [43][600/1281] lr: 2.037e-02, eta: 13:38:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9981, loss_cls: 0.5479, loss: 0.5479 +2025-06-24 15:09:47,962 - pyskl - INFO - Epoch [43][700/1281] lr: 2.036e-02, eta: 13:38:24, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9975, loss_cls: 0.5116, loss: 0.5116 +2025-06-24 15:10:36,706 - pyskl - INFO - Epoch [43][800/1281] lr: 2.034e-02, eta: 13:38:21, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9950, loss_cls: 0.5567, loss: 0.5567 +2025-06-24 15:11:18,543 - pyskl - INFO - Epoch [43][900/1281] lr: 2.033e-02, eta: 13:38:01, time: 0.418, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9969, loss_cls: 0.5105, loss: 0.5105 +2025-06-24 15:12:02,330 - pyskl - INFO - Epoch [43][1000/1281] lr: 2.031e-02, eta: 13:37:45, time: 0.438, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9956, loss_cls: 0.4832, loss: 0.4832 +2025-06-24 15:12:31,920 - pyskl - INFO - Epoch [43][1100/1281] lr: 2.029e-02, eta: 13:36:54, time: 0.296, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9925, loss_cls: 0.5743, loss: 0.5743 +2025-06-24 15:13:11,556 - pyskl - INFO - Epoch [43][1200/1281] lr: 2.028e-02, eta: 13:36:28, time: 0.396, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9950, loss_cls: 0.5513, loss: 0.5513 +2025-06-24 15:13:52,037 - pyskl - INFO - Saving checkpoint at 43 epochs +2025-06-24 15:14:52,179 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:14:52,237 - pyskl - INFO - +top1_acc 0.8553 +top5_acc 0.9893 +2025-06-24 15:14:52,237 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:14:52,244 - pyskl - INFO - +mean_acc 0.7858 +2025-06-24 15:14:52,246 - pyskl - INFO - Epoch(val) [43][533] top1_acc: 0.8553, top5_acc: 0.9893, mean_class_accuracy: 0.7858 +2025-06-24 15:16:11,200 - pyskl - INFO - Epoch [44][100/1281] lr: 2.025e-02, eta: 13:35:59, time: 0.789, data_time: 0.193, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9962, loss_cls: 0.4987, loss: 0.4987 +2025-06-24 15:17:00,021 - pyskl - INFO - Epoch [44][200/1281] lr: 2.023e-02, eta: 13:35:56, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9988, loss_cls: 0.4740, loss: 0.4740 +2025-06-24 15:17:48,950 - pyskl - INFO - Epoch [44][300/1281] lr: 2.022e-02, eta: 13:35:52, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9969, loss_cls: 0.4632, loss: 0.4632 +2025-06-24 15:18:37,755 - pyskl - INFO - Epoch [44][400/1281] lr: 2.020e-02, eta: 13:35:49, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9975, loss_cls: 0.5251, loss: 0.5251 +2025-06-24 15:19:26,925 - pyskl - INFO - Epoch [44][500/1281] lr: 2.018e-02, eta: 13:35:46, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9969, loss_cls: 0.4830, loss: 0.4830 +2025-06-24 15:20:15,994 - pyskl - INFO - Epoch [44][600/1281] lr: 2.017e-02, eta: 13:35:42, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9988, loss_cls: 0.5296, loss: 0.5296 +2025-06-24 15:21:04,700 - pyskl - INFO - Epoch [44][700/1281] lr: 2.015e-02, eta: 13:35:38, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9938, loss_cls: 0.5861, loss: 0.5861 +2025-06-24 15:21:53,544 - pyskl - INFO - Epoch [44][800/1281] lr: 2.014e-02, eta: 13:35:33, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9962, loss_cls: 0.5078, loss: 0.5078 +2025-06-24 15:22:37,971 - pyskl - INFO - Epoch [44][900/1281] lr: 2.012e-02, eta: 13:35:18, time: 0.444, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9969, loss_cls: 0.5185, loss: 0.5185 +2025-06-24 15:23:19,162 - pyskl - INFO - Epoch [44][1000/1281] lr: 2.010e-02, eta: 13:34:55, time: 0.412, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9962, loss_cls: 0.4915, loss: 0.4915 +2025-06-24 15:23:51,708 - pyskl - INFO - Epoch [44][1100/1281] lr: 2.009e-02, eta: 13:34:11, time: 0.325, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9969, loss_cls: 0.5006, loss: 0.5006 +2025-06-24 15:24:31,134 - pyskl - INFO - Epoch [44][1200/1281] lr: 2.007e-02, eta: 13:33:43, time: 0.394, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9988, loss_cls: 0.4856, loss: 0.4856 +2025-06-24 15:25:11,584 - pyskl - INFO - Saving checkpoint at 44 epochs +2025-06-24 15:26:10,759 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:26:10,817 - pyskl - INFO - +top1_acc 0.8454 +top5_acc 0.9896 +2025-06-24 15:26:10,817 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:26:10,824 - pyskl - INFO - +mean_acc 0.7984 +2025-06-24 15:26:10,826 - pyskl - INFO - Epoch(val) [44][533] top1_acc: 0.8454, top5_acc: 0.9896, mean_class_accuracy: 0.7984 +2025-06-24 15:27:30,061 - pyskl - INFO - Epoch [45][100/1281] lr: 2.004e-02, eta: 13:33:13, time: 0.792, data_time: 0.197, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9981, loss_cls: 0.4721, loss: 0.4721 +2025-06-24 15:28:19,432 - pyskl - INFO - Epoch [45][200/1281] lr: 2.003e-02, eta: 13:33:09, time: 0.494, data_time: 0.001, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9975, loss_cls: 0.4943, loss: 0.4943 +2025-06-24 15:29:08,008 - pyskl - INFO - Epoch [45][300/1281] lr: 2.001e-02, eta: 13:33:03, time: 0.486, data_time: 0.001, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9969, loss_cls: 0.5108, loss: 0.5108 +2025-06-24 15:29:57,003 - pyskl - INFO - Epoch [45][400/1281] lr: 1.999e-02, eta: 13:32:58, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9981, loss_cls: 0.4676, loss: 0.4676 +2025-06-24 15:30:45,535 - pyskl - INFO - Epoch [45][500/1281] lr: 1.998e-02, eta: 13:32:52, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9962, loss_cls: 0.4533, loss: 0.4533 +2025-06-24 15:31:34,849 - pyskl - INFO - Epoch [45][600/1281] lr: 1.996e-02, eta: 13:32:47, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9981, loss_cls: 0.5140, loss: 0.5140 +2025-06-24 15:32:23,800 - pyskl - INFO - Epoch [45][700/1281] lr: 1.994e-02, eta: 13:32:41, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9950, loss_cls: 0.5370, loss: 0.5370 +2025-06-24 15:33:12,626 - pyskl - INFO - Epoch [45][800/1281] lr: 1.993e-02, eta: 13:32:35, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9956, loss_cls: 0.5274, loss: 0.5274 +2025-06-24 15:33:56,638 - pyskl - INFO - Epoch [45][900/1281] lr: 1.991e-02, eta: 13:32:18, time: 0.440, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9962, loss_cls: 0.5062, loss: 0.5062 +2025-06-24 15:34:40,031 - pyskl - INFO - Epoch [45][1000/1281] lr: 1.989e-02, eta: 13:31:59, time: 0.434, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9950, loss_cls: 0.5547, loss: 0.5547 +2025-06-24 15:35:10,235 - pyskl - INFO - Epoch [45][1100/1281] lr: 1.988e-02, eta: 13:31:09, time: 0.302, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9988, loss_cls: 0.5313, loss: 0.5313 +2025-06-24 15:35:50,070 - pyskl - INFO - Epoch [45][1200/1281] lr: 1.986e-02, eta: 13:30:41, time: 0.398, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9944, loss_cls: 0.5074, loss: 0.5074 +2025-06-24 15:36:30,511 - pyskl - INFO - Saving checkpoint at 45 epochs +2025-06-24 15:37:30,029 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:37:30,087 - pyskl - INFO - +top1_acc 0.8711 +top5_acc 0.9900 +2025-06-24 15:37:30,087 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:37:30,097 - pyskl - INFO - +mean_acc 0.8278 +2025-06-24 15:37:30,100 - pyskl - INFO - Epoch(val) [45][533] top1_acc: 0.8711, top5_acc: 0.9900, mean_class_accuracy: 0.8278 +2025-06-24 15:38:50,623 - pyskl - INFO - Epoch [46][100/1281] lr: 1.983e-02, eta: 13:30:11, time: 0.805, data_time: 0.197, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9962, loss_cls: 0.4812, loss: 0.4812 +2025-06-24 15:39:39,330 - pyskl - INFO - Epoch [46][200/1281] lr: 1.981e-02, eta: 13:30:04, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9988, loss_cls: 0.4605, loss: 0.4605 +2025-06-24 15:40:28,065 - pyskl - INFO - Epoch [46][300/1281] lr: 1.980e-02, eta: 13:29:57, time: 0.487, data_time: 0.001, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9969, loss_cls: 0.4778, loss: 0.4778 +2025-06-24 15:41:17,351 - pyskl - INFO - Epoch [46][400/1281] lr: 1.978e-02, eta: 13:29:51, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9956, loss_cls: 0.5154, loss: 0.5154 +2025-06-24 15:42:06,707 - pyskl - INFO - Epoch [46][500/1281] lr: 1.976e-02, eta: 13:29:45, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9956, loss_cls: 0.4910, loss: 0.4910 +2025-06-24 15:42:55,732 - pyskl - INFO - Epoch [46][600/1281] lr: 1.975e-02, eta: 13:29:38, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9969, loss_cls: 0.5486, loss: 0.5486 +2025-06-24 15:43:44,700 - pyskl - INFO - Epoch [46][700/1281] lr: 1.973e-02, eta: 13:29:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9969, loss_cls: 0.5568, loss: 0.5568 +2025-06-24 15:44:33,533 - pyskl - INFO - Epoch [46][800/1281] lr: 1.971e-02, eta: 13:29:23, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9988, loss_cls: 0.4654, loss: 0.4654 +2025-06-24 15:45:16,354 - pyskl - INFO - Epoch [46][900/1281] lr: 1.970e-02, eta: 13:29:01, time: 0.428, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9956, loss_cls: 0.4948, loss: 0.4948 +2025-06-24 15:45:59,856 - pyskl - INFO - Epoch [46][1000/1281] lr: 1.968e-02, eta: 13:28:41, time: 0.435, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9956, loss_cls: 0.5022, loss: 0.5022 +2025-06-24 15:46:29,781 - pyskl - INFO - Epoch [46][1100/1281] lr: 1.966e-02, eta: 13:27:51, time: 0.299, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9969, loss_cls: 0.5075, loss: 0.5075 +2025-06-24 15:47:10,755 - pyskl - INFO - Epoch [46][1200/1281] lr: 1.965e-02, eta: 13:27:25, time: 0.410, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9969, loss_cls: 0.5415, loss: 0.5415 +2025-06-24 15:47:51,618 - pyskl - INFO - Saving checkpoint at 46 epochs +2025-06-24 15:48:51,215 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:48:51,276 - pyskl - INFO - +top1_acc 0.8452 +top5_acc 0.9865 +2025-06-24 15:48:51,276 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:48:51,283 - pyskl - INFO - +mean_acc 0.8168 +2025-06-24 15:48:51,285 - pyskl - INFO - Epoch(val) [46][533] top1_acc: 0.8452, top5_acc: 0.9865, mean_class_accuracy: 0.8168 +2025-06-24 15:50:12,209 - pyskl - INFO - Epoch [47][100/1281] lr: 1.962e-02, eta: 13:26:53, time: 0.809, data_time: 0.200, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9956, loss_cls: 0.4643, loss: 0.4643 +2025-06-24 15:51:01,005 - pyskl - INFO - Epoch [47][200/1281] lr: 1.960e-02, eta: 13:26:45, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9981, loss_cls: 0.4513, loss: 0.4513 +2025-06-24 15:51:49,340 - pyskl - INFO - Epoch [47][300/1281] lr: 1.958e-02, eta: 13:26:35, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9962, loss_cls: 0.5022, loss: 0.5022 +2025-06-24 15:52:38,217 - pyskl - INFO - Epoch [47][400/1281] lr: 1.957e-02, eta: 13:26:27, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9988, loss_cls: 0.4600, loss: 0.4600 +2025-06-24 15:53:27,205 - pyskl - INFO - Epoch [47][500/1281] lr: 1.955e-02, eta: 13:26:18, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9975, loss_cls: 0.4636, loss: 0.4636 +2025-06-24 15:54:16,370 - pyskl - INFO - Epoch [47][600/1281] lr: 1.953e-02, eta: 13:26:10, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9981, loss_cls: 0.5315, loss: 0.5315 +2025-06-24 15:55:05,864 - pyskl - INFO - Epoch [47][700/1281] lr: 1.952e-02, eta: 13:26:03, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9975, loss_cls: 0.5566, loss: 0.5566 +2025-06-24 15:55:55,057 - pyskl - INFO - Epoch [47][800/1281] lr: 1.950e-02, eta: 13:25:54, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9956, loss_cls: 0.5162, loss: 0.5162 +2025-06-24 15:56:37,092 - pyskl - INFO - Epoch [47][900/1281] lr: 1.948e-02, eta: 13:25:30, time: 0.420, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9994, loss_cls: 0.4845, loss: 0.4845 +2025-06-24 15:57:21,298 - pyskl - INFO - Epoch [47][1000/1281] lr: 1.947e-02, eta: 13:25:10, time: 0.442, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9969, loss_cls: 0.4650, loss: 0.4650 +2025-06-24 15:57:50,475 - pyskl - INFO - Epoch [47][1100/1281] lr: 1.945e-02, eta: 13:24:18, time: 0.292, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9931, loss_cls: 0.5185, loss: 0.5185 +2025-06-24 15:58:30,303 - pyskl - INFO - Epoch [47][1200/1281] lr: 1.943e-02, eta: 13:23:48, time: 0.398, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9981, loss_cls: 0.5064, loss: 0.5064 +2025-06-24 15:59:10,766 - pyskl - INFO - Saving checkpoint at 47 epochs +2025-06-24 16:00:10,499 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:00:10,567 - pyskl - INFO - +top1_acc 0.8715 +top5_acc 0.9900 +2025-06-24 16:00:10,567 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:00:10,577 - pyskl - INFO - +mean_acc 0.8385 +2025-06-24 16:00:10,579 - pyskl - INFO - Epoch(val) [47][533] top1_acc: 0.8715, top5_acc: 0.9900, mean_class_accuracy: 0.8385 +2025-06-24 16:01:31,058 - pyskl - INFO - Epoch [48][100/1281] lr: 1.940e-02, eta: 13:23:14, time: 0.805, data_time: 0.193, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9994, loss_cls: 0.4389, loss: 0.4389 +2025-06-24 16:02:20,183 - pyskl - INFO - Epoch [48][200/1281] lr: 1.938e-02, eta: 13:23:04, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9969, loss_cls: 0.4548, loss: 0.4548 +2025-06-24 16:03:09,098 - pyskl - INFO - Epoch [48][300/1281] lr: 1.937e-02, eta: 13:22:55, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9981, loss_cls: 0.4921, loss: 0.4921 +2025-06-24 16:03:57,996 - pyskl - INFO - Epoch [48][400/1281] lr: 1.935e-02, eta: 13:22:45, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9969, loss_cls: 0.5152, loss: 0.5152 +2025-06-24 16:04:47,104 - pyskl - INFO - Epoch [48][500/1281] lr: 1.933e-02, eta: 13:22:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9962, loss_cls: 0.4797, loss: 0.4797 +2025-06-24 16:05:35,940 - pyskl - INFO - Epoch [48][600/1281] lr: 1.932e-02, eta: 13:22:25, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9969, loss_cls: 0.5024, loss: 0.5024 +2025-06-24 16:06:24,681 - pyskl - INFO - Epoch [48][700/1281] lr: 1.930e-02, eta: 13:22:14, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9994, loss_cls: 0.4655, loss: 0.4655 +2025-06-24 16:07:13,347 - pyskl - INFO - Epoch [48][800/1281] lr: 1.928e-02, eta: 13:22:03, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9956, loss_cls: 0.4993, loss: 0.4993 +2025-06-24 16:07:57,313 - pyskl - INFO - Epoch [48][900/1281] lr: 1.926e-02, eta: 13:21:42, time: 0.440, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9969, loss_cls: 0.4573, loss: 0.4573 +2025-06-24 16:08:38,072 - pyskl - INFO - Epoch [48][1000/1281] lr: 1.925e-02, eta: 13:21:14, time: 0.408, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9975, loss_cls: 0.5071, loss: 0.5071 +2025-06-24 16:09:10,532 - pyskl - INFO - Epoch [48][1100/1281] lr: 1.923e-02, eta: 13:20:29, time: 0.325, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9969, loss_cls: 0.4839, loss: 0.4839 +2025-06-24 16:09:48,539 - pyskl - INFO - Epoch [48][1200/1281] lr: 1.921e-02, eta: 13:19:55, time: 0.380, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9950, loss_cls: 0.5457, loss: 0.5457 +2025-06-24 16:10:28,790 - pyskl - INFO - Saving checkpoint at 48 epochs +2025-06-24 16:11:28,100 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:11:28,161 - pyskl - INFO - +top1_acc 0.8613 +top5_acc 0.9906 +2025-06-24 16:11:28,161 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:11:28,169 - pyskl - INFO - +mean_acc 0.8107 +2025-06-24 16:11:28,171 - pyskl - INFO - Epoch(val) [48][533] top1_acc: 0.8613, top5_acc: 0.9906, mean_class_accuracy: 0.8107 +2025-06-24 16:12:47,159 - pyskl - INFO - Epoch [49][100/1281] lr: 1.918e-02, eta: 13:19:15, time: 0.790, data_time: 0.191, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9988, loss_cls: 0.4526, loss: 0.4526 +2025-06-24 16:13:36,255 - pyskl - INFO - Epoch [49][200/1281] lr: 1.916e-02, eta: 13:19:04, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9975, loss_cls: 0.4691, loss: 0.4691 +2025-06-24 16:14:25,448 - pyskl - INFO - Epoch [49][300/1281] lr: 1.915e-02, eta: 13:18:54, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9981, loss_cls: 0.4408, loss: 0.4408 +2025-06-24 16:15:14,677 - pyskl - INFO - Epoch [49][400/1281] lr: 1.913e-02, eta: 13:18:43, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9944, loss_cls: 0.5145, loss: 0.5145 +2025-06-24 16:16:03,969 - pyskl - INFO - Epoch [49][500/1281] lr: 1.911e-02, eta: 13:18:33, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9962, loss_cls: 0.4835, loss: 0.4835 +2025-06-24 16:16:52,975 - pyskl - INFO - Epoch [49][600/1281] lr: 1.909e-02, eta: 13:18:21, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9981, loss_cls: 0.4729, loss: 0.4729 +2025-06-24 16:17:42,113 - pyskl - INFO - Epoch [49][700/1281] lr: 1.908e-02, eta: 13:18:10, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9944, loss_cls: 0.5066, loss: 0.5066 +2025-06-24 16:18:31,100 - pyskl - INFO - Epoch [49][800/1281] lr: 1.906e-02, eta: 13:17:59, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9969, loss_cls: 0.5362, loss: 0.5362 +2025-06-24 16:19:18,187 - pyskl - INFO - Epoch [49][900/1281] lr: 1.904e-02, eta: 13:17:43, time: 0.471, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9975, loss_cls: 0.4615, loss: 0.4615 +2025-06-24 16:19:52,679 - pyskl - INFO - Epoch [49][1000/1281] lr: 1.902e-02, eta: 13:17:01, time: 0.345, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9962, loss_cls: 0.4672, loss: 0.4672 +2025-06-24 16:20:31,628 - pyskl - INFO - Epoch [49][1100/1281] lr: 1.901e-02, eta: 13:16:29, time: 0.389, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9994, loss_cls: 0.5039, loss: 0.5039 +2025-06-24 16:21:08,084 - pyskl - INFO - Epoch [49][1200/1281] lr: 1.899e-02, eta: 13:15:51, time: 0.365, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9975, loss_cls: 0.4845, loss: 0.4845 +2025-06-24 16:21:48,341 - pyskl - INFO - Saving checkpoint at 49 epochs +2025-06-24 16:22:47,912 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:22:47,995 - pyskl - INFO - +top1_acc 0.8483 +top5_acc 0.9896 +2025-06-24 16:22:47,995 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:22:48,007 - pyskl - INFO - +mean_acc 0.8026 +2025-06-24 16:22:48,011 - pyskl - INFO - Epoch(val) [49][533] top1_acc: 0.8483, top5_acc: 0.9896, mean_class_accuracy: 0.8026 +2025-06-24 16:24:07,253 - pyskl - INFO - Epoch [50][100/1281] lr: 1.896e-02, eta: 13:15:10, time: 0.792, data_time: 0.195, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9969, loss_cls: 0.4953, loss: 0.4953 +2025-06-24 16:24:56,298 - pyskl - INFO - Epoch [50][200/1281] lr: 1.894e-02, eta: 13:14:58, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9956, loss_cls: 0.5398, loss: 0.5398 +2025-06-24 16:25:45,149 - pyskl - INFO - Epoch [50][300/1281] lr: 1.892e-02, eta: 13:14:45, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9950, loss_cls: 0.4519, loss: 0.4519 +2025-06-24 16:26:33,939 - pyskl - INFO - Epoch [50][400/1281] lr: 1.891e-02, eta: 13:14:32, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9975, loss_cls: 0.4344, loss: 0.4344 +2025-06-24 16:27:22,704 - pyskl - INFO - Epoch [50][500/1281] lr: 1.889e-02, eta: 13:14:19, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9969, loss_cls: 0.4715, loss: 0.4715 +2025-06-24 16:28:11,923 - pyskl - INFO - Epoch [50][600/1281] lr: 1.887e-02, eta: 13:14:07, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9962, loss_cls: 0.4706, loss: 0.4706 +2025-06-24 16:29:00,799 - pyskl - INFO - Epoch [50][700/1281] lr: 1.885e-02, eta: 13:13:54, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9981, loss_cls: 0.4248, loss: 0.4248 +2025-06-24 16:29:49,808 - pyskl - INFO - Epoch [50][800/1281] lr: 1.884e-02, eta: 13:13:42, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9975, loss_cls: 0.4611, loss: 0.4611 +2025-06-24 16:30:37,629 - pyskl - INFO - Epoch [50][900/1281] lr: 1.882e-02, eta: 13:13:26, time: 0.478, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9944, loss_cls: 0.5116, loss: 0.5116 +2025-06-24 16:31:11,668 - pyskl - INFO - Epoch [50][1000/1281] lr: 1.880e-02, eta: 13:12:43, time: 0.340, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9975, loss_cls: 0.4882, loss: 0.4882 +2025-06-24 16:31:50,813 - pyskl - INFO - Epoch [50][1100/1281] lr: 1.878e-02, eta: 13:12:10, time: 0.391, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9950, loss_cls: 0.5169, loss: 0.5169 +2025-06-24 16:32:25,897 - pyskl - INFO - Epoch [50][1200/1281] lr: 1.876e-02, eta: 13:11:29, time: 0.351, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9981, loss_cls: 0.4067, loss: 0.4067 +2025-06-24 16:33:06,122 - pyskl - INFO - Saving checkpoint at 50 epochs +2025-06-24 16:34:05,510 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:34:05,568 - pyskl - INFO - +top1_acc 0.8642 +top5_acc 0.9917 +2025-06-24 16:34:05,568 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:34:05,577 - pyskl - INFO - +mean_acc 0.8058 +2025-06-24 16:34:05,579 - pyskl - INFO - Epoch(val) [50][533] top1_acc: 0.8642, top5_acc: 0.9917, mean_class_accuracy: 0.8058 +2025-06-24 16:35:24,523 - pyskl - INFO - Epoch [51][100/1281] lr: 1.873e-02, eta: 13:10:46, time: 0.789, data_time: 0.187, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9962, loss_cls: 0.4952, loss: 0.4952 +2025-06-24 16:36:13,931 - pyskl - INFO - Epoch [51][200/1281] lr: 1.871e-02, eta: 13:10:34, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9962, loss_cls: 0.4257, loss: 0.4257 +2025-06-24 16:37:02,997 - pyskl - INFO - Epoch [51][300/1281] lr: 1.870e-02, eta: 13:10:20, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9969, loss_cls: 0.4009, loss: 0.4009 +2025-06-24 16:37:51,805 - pyskl - INFO - Epoch [51][400/1281] lr: 1.868e-02, eta: 13:10:06, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9988, loss_cls: 0.4250, loss: 0.4250 +2025-06-24 16:38:41,231 - pyskl - INFO - Epoch [51][500/1281] lr: 1.866e-02, eta: 13:09:54, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 1.0000, loss_cls: 0.4368, loss: 0.4368 +2025-06-24 16:39:30,248 - pyskl - INFO - Epoch [51][600/1281] lr: 1.864e-02, eta: 13:09:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9975, loss_cls: 0.4959, loss: 0.4959 +2025-06-24 16:40:19,962 - pyskl - INFO - Epoch [51][700/1281] lr: 1.863e-02, eta: 13:09:27, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9975, loss_cls: 0.4683, loss: 0.4683 +2025-06-24 16:41:08,869 - pyskl - INFO - Epoch [51][800/1281] lr: 1.861e-02, eta: 13:09:13, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9994, loss_cls: 0.4312, loss: 0.4312 +2025-06-24 16:41:58,030 - pyskl - INFO - Epoch [51][900/1281] lr: 1.859e-02, eta: 13:08:59, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9981, loss_cls: 0.4195, loss: 0.4195 +2025-06-24 16:42:27,540 - pyskl - INFO - Epoch [51][1000/1281] lr: 1.857e-02, eta: 13:08:07, time: 0.295, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9969, loss_cls: 0.5029, loss: 0.5029 +2025-06-24 16:43:11,739 - pyskl - INFO - Epoch [51][1100/1281] lr: 1.855e-02, eta: 13:07:44, time: 0.442, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9981, loss_cls: 0.5058, loss: 0.5058 +2025-06-24 16:43:45,870 - pyskl - INFO - Epoch [51][1200/1281] lr: 1.854e-02, eta: 13:07:00, time: 0.341, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9931, loss_cls: 0.4886, loss: 0.4886 +2025-06-24 16:44:26,233 - pyskl - INFO - Saving checkpoint at 51 epochs +2025-06-24 16:45:26,471 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:45:26,540 - pyskl - INFO - +top1_acc 0.8689 +top5_acc 0.9926 +2025-06-24 16:45:26,540 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:45:26,549 - pyskl - INFO - +mean_acc 0.8192 +2025-06-24 16:45:26,552 - pyskl - INFO - Epoch(val) [51][533] top1_acc: 0.8689, top5_acc: 0.9926, mean_class_accuracy: 0.8192 +2025-06-24 16:46:45,988 - pyskl - INFO - Epoch [52][100/1281] lr: 1.850e-02, eta: 13:06:16, time: 0.794, data_time: 0.192, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9988, loss_cls: 0.4428, loss: 0.4428 +2025-06-24 16:47:34,854 - pyskl - INFO - Epoch [52][200/1281] lr: 1.849e-02, eta: 13:06:02, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9981, loss_cls: 0.3861, loss: 0.3861 +2025-06-24 16:48:23,432 - pyskl - INFO - Epoch [52][300/1281] lr: 1.847e-02, eta: 13:05:46, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9988, loss_cls: 0.4441, loss: 0.4441 +2025-06-24 16:49:12,575 - pyskl - INFO - Epoch [52][400/1281] lr: 1.845e-02, eta: 13:05:32, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9975, loss_cls: 0.4554, loss: 0.4554 +2025-06-24 16:50:01,679 - pyskl - INFO - Epoch [52][500/1281] lr: 1.843e-02, eta: 13:05:17, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9981, loss_cls: 0.4122, loss: 0.4122 +2025-06-24 16:50:50,458 - pyskl - INFO - Epoch [52][600/1281] lr: 1.841e-02, eta: 13:05:02, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9981, loss_cls: 0.4001, loss: 0.4001 +2025-06-24 16:51:39,595 - pyskl - INFO - Epoch [52][700/1281] lr: 1.840e-02, eta: 13:04:47, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9988, loss_cls: 0.4657, loss: 0.4657 +2025-06-24 16:52:28,334 - pyskl - INFO - Epoch [52][800/1281] lr: 1.838e-02, eta: 13:04:32, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9962, loss_cls: 0.5522, loss: 0.5522 +2025-06-24 16:53:17,476 - pyskl - INFO - Epoch [52][900/1281] lr: 1.836e-02, eta: 13:04:17, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9981, loss_cls: 0.5186, loss: 0.5186 +2025-06-24 16:53:48,446 - pyskl - INFO - Epoch [52][1000/1281] lr: 1.834e-02, eta: 13:03:27, time: 0.310, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9962, loss_cls: 0.4436, loss: 0.4436 +2025-06-24 16:54:31,409 - pyskl - INFO - Epoch [52][1100/1281] lr: 1.832e-02, eta: 13:03:00, time: 0.430, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9988, loss_cls: 0.4386, loss: 0.4386 +2025-06-24 16:55:05,217 - pyskl - INFO - Epoch [52][1200/1281] lr: 1.831e-02, eta: 13:02:16, time: 0.338, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9975, loss_cls: 0.4574, loss: 0.4574 +2025-06-24 16:55:45,573 - pyskl - INFO - Saving checkpoint at 52 epochs +2025-06-24 16:56:44,936 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:56:45,006 - pyskl - INFO - +top1_acc 0.8510 +top5_acc 0.9885 +2025-06-24 16:56:45,006 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:56:45,015 - pyskl - INFO - +mean_acc 0.8254 +2025-06-24 16:56:45,017 - pyskl - INFO - Epoch(val) [52][533] top1_acc: 0.8510, top5_acc: 0.9885, mean_class_accuracy: 0.8254 +2025-06-24 16:58:03,915 - pyskl - INFO - Epoch [53][100/1281] lr: 1.827e-02, eta: 13:01:30, time: 0.789, data_time: 0.191, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9994, loss_cls: 0.4083, loss: 0.4083 +2025-06-24 16:58:52,926 - pyskl - INFO - Epoch [53][200/1281] lr: 1.826e-02, eta: 13:01:14, time: 0.490, data_time: 0.001, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9988, loss_cls: 0.4238, loss: 0.4238 +2025-06-24 16:59:42,229 - pyskl - INFO - Epoch [53][300/1281] lr: 1.824e-02, eta: 13:00:59, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9994, loss_cls: 0.4150, loss: 0.4150 +2025-06-24 17:00:31,172 - pyskl - INFO - Epoch [53][400/1281] lr: 1.822e-02, eta: 13:00:43, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9975, loss_cls: 0.4639, loss: 0.4639 +2025-06-24 17:01:20,129 - pyskl - INFO - Epoch [53][500/1281] lr: 1.820e-02, eta: 13:00:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9988, loss_cls: 0.4249, loss: 0.4249 +2025-06-24 17:02:09,007 - pyskl - INFO - Epoch [53][600/1281] lr: 1.818e-02, eta: 13:00:11, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9975, loss_cls: 0.4700, loss: 0.4700 +2025-06-24 17:02:57,947 - pyskl - INFO - Epoch [53][700/1281] lr: 1.816e-02, eta: 12:59:55, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9962, loss_cls: 0.5008, loss: 0.5008 +2025-06-24 17:03:46,962 - pyskl - INFO - Epoch [53][800/1281] lr: 1.815e-02, eta: 12:59:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9994, loss_cls: 0.3845, loss: 0.3845 +2025-06-24 17:04:35,974 - pyskl - INFO - Epoch [53][900/1281] lr: 1.813e-02, eta: 12:59:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9962, loss_cls: 0.4620, loss: 0.4620 +2025-06-24 17:05:05,077 - pyskl - INFO - Epoch [53][1000/1281] lr: 1.811e-02, eta: 12:58:29, time: 0.291, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9962, loss_cls: 0.4493, loss: 0.4493 +2025-06-24 17:05:51,662 - pyskl - INFO - Epoch [53][1100/1281] lr: 1.809e-02, eta: 12:58:09, time: 0.466, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9950, loss_cls: 0.4831, loss: 0.4831 +2025-06-24 17:06:25,201 - pyskl - INFO - Epoch [53][1200/1281] lr: 1.807e-02, eta: 12:57:24, time: 0.335, data_time: 0.001, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9981, loss_cls: 0.4676, loss: 0.4676 +2025-06-24 17:07:05,567 - pyskl - INFO - Saving checkpoint at 53 epochs +2025-06-24 17:08:04,849 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:08:04,904 - pyskl - INFO - +top1_acc 0.8683 +top5_acc 0.9910 +2025-06-24 17:08:04,904 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:08:04,911 - pyskl - INFO - +mean_acc 0.8266 +2025-06-24 17:08:04,913 - pyskl - INFO - Epoch(val) [53][533] top1_acc: 0.8683, top5_acc: 0.9910, mean_class_accuracy: 0.8266 +2025-06-24 17:09:25,670 - pyskl - INFO - Epoch [54][100/1281] lr: 1.804e-02, eta: 12:56:39, time: 0.808, data_time: 0.193, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9969, loss_cls: 0.4152, loss: 0.4152 +2025-06-24 17:10:15,228 - pyskl - INFO - Epoch [54][200/1281] lr: 1.802e-02, eta: 12:56:24, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9975, loss_cls: 0.4331, loss: 0.4331 +2025-06-24 17:11:04,319 - pyskl - INFO - Epoch [54][300/1281] lr: 1.800e-02, eta: 12:56:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 0.4173, loss: 0.4173 +2025-06-24 17:11:53,282 - pyskl - INFO - Epoch [54][400/1281] lr: 1.798e-02, eta: 12:55:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9975, loss_cls: 0.4340, loss: 0.4340 +2025-06-24 17:12:42,180 - pyskl - INFO - Epoch [54][500/1281] lr: 1.797e-02, eta: 12:55:33, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9994, loss_cls: 0.3940, loss: 0.3940 +2025-06-24 17:13:31,102 - pyskl - INFO - Epoch [54][600/1281] lr: 1.795e-02, eta: 12:55:16, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9969, loss_cls: 0.4363, loss: 0.4363 +2025-06-24 17:14:19,881 - pyskl - INFO - Epoch [54][700/1281] lr: 1.793e-02, eta: 12:54:58, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9956, loss_cls: 0.5253, loss: 0.5253 +2025-06-24 17:15:08,731 - pyskl - INFO - Epoch [54][800/1281] lr: 1.791e-02, eta: 12:54:41, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9969, loss_cls: 0.4689, loss: 0.4689 +2025-06-24 17:15:57,689 - pyskl - INFO - Epoch [54][900/1281] lr: 1.789e-02, eta: 12:54:24, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9975, loss_cls: 0.5240, loss: 0.5240 +2025-06-24 17:16:27,647 - pyskl - INFO - Epoch [54][1000/1281] lr: 1.787e-02, eta: 12:53:32, time: 0.300, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9975, loss_cls: 0.5073, loss: 0.5073 +2025-06-24 17:17:11,691 - pyskl - INFO - Epoch [54][1100/1281] lr: 1.786e-02, eta: 12:53:06, time: 0.440, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9969, loss_cls: 0.4296, loss: 0.4296 +2025-06-24 17:17:46,315 - pyskl - INFO - Epoch [54][1200/1281] lr: 1.784e-02, eta: 12:52:23, time: 0.346, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9950, loss_cls: 0.4896, loss: 0.4896 +2025-06-24 17:18:26,647 - pyskl - INFO - Saving checkpoint at 54 epochs +2025-06-24 17:19:25,653 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:19:25,708 - pyskl - INFO - +top1_acc 0.8755 +top5_acc 0.9919 +2025-06-24 17:19:25,708 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:19:25,715 - pyskl - INFO - +mean_acc 0.8199 +2025-06-24 17:19:25,719 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_38.pth was removed +2025-06-24 17:19:25,887 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_54.pth. +2025-06-24 17:19:25,888 - pyskl - INFO - Best top1_acc is 0.8755 at 54 epoch. +2025-06-24 17:19:25,890 - pyskl - INFO - Epoch(val) [54][533] top1_acc: 0.8755, top5_acc: 0.9919, mean_class_accuracy: 0.8199 +2025-06-24 17:20:45,757 - pyskl - INFO - Epoch [55][100/1281] lr: 1.780e-02, eta: 12:51:35, time: 0.799, data_time: 0.196, memory: 4083, top1_acc: 0.9169, top5_acc: 1.0000, loss_cls: 0.4372, loss: 0.4372 +2025-06-24 17:21:34,934 - pyskl - INFO - Epoch [55][200/1281] lr: 1.779e-02, eta: 12:51:18, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9988, loss_cls: 0.4217, loss: 0.4217 +2025-06-24 17:22:24,086 - pyskl - INFO - Epoch [55][300/1281] lr: 1.777e-02, eta: 12:51:01, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9981, loss_cls: 0.3978, loss: 0.3978 +2025-06-24 17:23:13,475 - pyskl - INFO - Epoch [55][400/1281] lr: 1.775e-02, eta: 12:50:43, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9988, loss_cls: 0.4395, loss: 0.4395 +2025-06-24 17:24:02,646 - pyskl - INFO - Epoch [55][500/1281] lr: 1.773e-02, eta: 12:50:26, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 0.3846, loss: 0.3846 +2025-06-24 17:24:52,342 - pyskl - INFO - Epoch [55][600/1281] lr: 1.771e-02, eta: 12:50:09, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9988, loss_cls: 0.4633, loss: 0.4633 +2025-06-24 17:25:41,407 - pyskl - INFO - Epoch [55][700/1281] lr: 1.769e-02, eta: 12:49:51, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9981, loss_cls: 0.4357, loss: 0.4357 +2025-06-24 17:26:30,378 - pyskl - INFO - Epoch [55][800/1281] lr: 1.767e-02, eta: 12:49:33, time: 0.490, data_time: 0.001, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9962, loss_cls: 0.4660, loss: 0.4660 +2025-06-24 17:27:19,386 - pyskl - INFO - Epoch [55][900/1281] lr: 1.766e-02, eta: 12:49:15, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9962, loss_cls: 0.4697, loss: 0.4697 +2025-06-24 17:27:50,333 - pyskl - INFO - Epoch [55][1000/1281] lr: 1.764e-02, eta: 12:48:25, time: 0.309, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9988, loss_cls: 0.4512, loss: 0.4512 +2025-06-24 17:28:33,328 - pyskl - INFO - Epoch [55][1100/1281] lr: 1.762e-02, eta: 12:47:56, time: 0.430, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9975, loss_cls: 0.4541, loss: 0.4541 +2025-06-24 17:29:07,261 - pyskl - INFO - Epoch [55][1200/1281] lr: 1.760e-02, eta: 12:47:12, time: 0.339, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9988, loss_cls: 0.4105, loss: 0.4105 +2025-06-24 17:29:47,293 - pyskl - INFO - Saving checkpoint at 55 epochs +2025-06-24 17:30:46,495 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:30:46,553 - pyskl - INFO - +top1_acc 0.8694 +top5_acc 0.9918 +2025-06-24 17:30:46,553 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:30:46,560 - pyskl - INFO - +mean_acc 0.8260 +2025-06-24 17:30:46,562 - pyskl - INFO - Epoch(val) [55][533] top1_acc: 0.8694, top5_acc: 0.9918, mean_class_accuracy: 0.8260 +2025-06-24 17:32:06,815 - pyskl - INFO - Epoch [56][100/1281] lr: 1.757e-02, eta: 12:46:24, time: 0.802, data_time: 0.193, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9969, loss_cls: 0.4261, loss: 0.4261 +2025-06-24 17:32:55,833 - pyskl - INFO - Epoch [56][200/1281] lr: 1.755e-02, eta: 12:46:05, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9975, loss_cls: 0.4294, loss: 0.4294 +2025-06-24 17:33:44,793 - pyskl - INFO - Epoch [56][300/1281] lr: 1.753e-02, eta: 12:45:46, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9988, loss_cls: 0.4184, loss: 0.4184 +2025-06-24 17:34:33,732 - pyskl - INFO - Epoch [56][400/1281] lr: 1.751e-02, eta: 12:45:27, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9975, loss_cls: 0.3876, loss: 0.3876 +2025-06-24 17:35:22,541 - pyskl - INFO - Epoch [56][500/1281] lr: 1.749e-02, eta: 12:45:08, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9975, loss_cls: 0.4091, loss: 0.4091 +2025-06-24 17:36:11,780 - pyskl - INFO - Epoch [56][600/1281] lr: 1.747e-02, eta: 12:44:50, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9981, loss_cls: 0.4312, loss: 0.4312 +2025-06-24 17:37:00,870 - pyskl - INFO - Epoch [56][700/1281] lr: 1.745e-02, eta: 12:44:31, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9975, loss_cls: 0.4389, loss: 0.4389 +2025-06-24 17:37:49,592 - pyskl - INFO - Epoch [56][800/1281] lr: 1.743e-02, eta: 12:44:11, time: 0.487, data_time: 0.001, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9981, loss_cls: 0.4572, loss: 0.4572 +2025-06-24 17:38:38,512 - pyskl - INFO - Epoch [56][900/1281] lr: 1.742e-02, eta: 12:43:52, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9962, loss_cls: 0.4263, loss: 0.4263 +2025-06-24 17:39:09,638 - pyskl - INFO - Epoch [56][1000/1281] lr: 1.740e-02, eta: 12:43:02, time: 0.311, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9988, loss_cls: 0.4574, loss: 0.4574 +2025-06-24 17:39:52,828 - pyskl - INFO - Epoch [56][1100/1281] lr: 1.738e-02, eta: 12:42:33, time: 0.432, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9969, loss_cls: 0.4413, loss: 0.4413 +2025-06-24 17:40:26,296 - pyskl - INFO - Epoch [56][1200/1281] lr: 1.736e-02, eta: 12:41:48, time: 0.335, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9981, loss_cls: 0.4015, loss: 0.4015 +2025-06-24 17:41:06,781 - pyskl - INFO - Saving checkpoint at 56 epochs +2025-06-24 17:42:06,812 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:42:06,872 - pyskl - INFO - +top1_acc 0.8789 +top5_acc 0.9931 +2025-06-24 17:42:06,872 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:42:06,880 - pyskl - INFO - +mean_acc 0.8402 +2025-06-24 17:42:06,884 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_54.pth was removed +2025-06-24 17:42:07,075 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_56.pth. +2025-06-24 17:42:07,076 - pyskl - INFO - Best top1_acc is 0.8789 at 56 epoch. +2025-06-24 17:42:07,080 - pyskl - INFO - Epoch(val) [56][533] top1_acc: 0.8789, top5_acc: 0.9931, mean_class_accuracy: 0.8402 +2025-06-24 17:43:26,860 - pyskl - INFO - Epoch [57][100/1281] lr: 1.733e-02, eta: 12:40:58, time: 0.798, data_time: 0.191, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9969, loss_cls: 0.4217, loss: 0.4217 +2025-06-24 17:44:15,817 - pyskl - INFO - Epoch [57][200/1281] lr: 1.731e-02, eta: 12:40:38, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9981, loss_cls: 0.4472, loss: 0.4472 +2025-06-24 17:45:04,850 - pyskl - INFO - Epoch [57][300/1281] lr: 1.729e-02, eta: 12:40:19, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9969, loss_cls: 0.4272, loss: 0.4272 +2025-06-24 17:45:53,905 - pyskl - INFO - Epoch [57][400/1281] lr: 1.727e-02, eta: 12:39:59, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9969, loss_cls: 0.4275, loss: 0.4275 +2025-06-24 17:46:42,808 - pyskl - INFO - Epoch [57][500/1281] lr: 1.725e-02, eta: 12:39:39, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9988, loss_cls: 0.4289, loss: 0.4289 +2025-06-24 17:47:32,117 - pyskl - INFO - Epoch [57][600/1281] lr: 1.723e-02, eta: 12:39:20, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9969, loss_cls: 0.4347, loss: 0.4347 +2025-06-24 17:48:21,580 - pyskl - INFO - Epoch [57][700/1281] lr: 1.721e-02, eta: 12:39:01, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9981, loss_cls: 0.4489, loss: 0.4489 +2025-06-24 17:49:10,168 - pyskl - INFO - Epoch [57][800/1281] lr: 1.719e-02, eta: 12:38:40, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9988, loss_cls: 0.4751, loss: 0.4751 +2025-06-24 17:49:58,945 - pyskl - INFO - Epoch [57][900/1281] lr: 1.717e-02, eta: 12:38:20, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9956, loss_cls: 0.4565, loss: 0.4565 +2025-06-24 17:50:27,775 - pyskl - INFO - Epoch [57][1000/1281] lr: 1.716e-02, eta: 12:37:27, time: 0.288, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9969, loss_cls: 0.4399, loss: 0.4399 +2025-06-24 17:51:13,778 - pyskl - INFO - Epoch [57][1100/1281] lr: 1.714e-02, eta: 12:37:02, time: 0.460, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9956, loss_cls: 0.5016, loss: 0.5016 +2025-06-24 17:51:46,494 - pyskl - INFO - Epoch [57][1200/1281] lr: 1.712e-02, eta: 12:36:15, time: 0.327, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9975, loss_cls: 0.4676, loss: 0.4676 +2025-06-24 17:52:26,817 - pyskl - INFO - Saving checkpoint at 57 epochs +2025-06-24 17:53:26,220 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:53:26,276 - pyskl - INFO - +top1_acc 0.8703 +top5_acc 0.9870 +2025-06-24 17:53:26,276 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:53:26,287 - pyskl - INFO - +mean_acc 0.8280 +2025-06-24 17:53:26,290 - pyskl - INFO - Epoch(val) [57][533] top1_acc: 0.8703, top5_acc: 0.9870, mean_class_accuracy: 0.8280 +2025-06-24 17:54:45,210 - pyskl - INFO - Epoch [58][100/1281] lr: 1.708e-02, eta: 12:35:22, time: 0.789, data_time: 0.192, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9981, loss_cls: 0.3863, loss: 0.3863 +2025-06-24 17:55:34,172 - pyskl - INFO - Epoch [58][200/1281] lr: 1.706e-02, eta: 12:35:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9981, loss_cls: 0.4204, loss: 0.4204 +2025-06-24 17:56:23,217 - pyskl - INFO - Epoch [58][300/1281] lr: 1.704e-02, eta: 12:34:41, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 1.0000, loss_cls: 0.4041, loss: 0.4041 +2025-06-24 17:57:12,099 - pyskl - INFO - Epoch [58][400/1281] lr: 1.703e-02, eta: 12:34:21, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9981, loss_cls: 0.4326, loss: 0.4326 +2025-06-24 17:58:00,933 - pyskl - INFO - Epoch [58][500/1281] lr: 1.701e-02, eta: 12:34:00, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9994, loss_cls: 0.3842, loss: 0.3842 +2025-06-24 17:58:50,031 - pyskl - INFO - Epoch [58][600/1281] lr: 1.699e-02, eta: 12:33:39, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9981, loss_cls: 0.3780, loss: 0.3780 +2025-06-24 17:59:39,206 - pyskl - INFO - Epoch [58][700/1281] lr: 1.697e-02, eta: 12:33:19, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9956, loss_cls: 0.4870, loss: 0.4870 +2025-06-24 18:00:28,217 - pyskl - INFO - Epoch [58][800/1281] lr: 1.695e-02, eta: 12:32:58, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9975, loss_cls: 0.4577, loss: 0.4577 +2025-06-24 18:01:17,253 - pyskl - INFO - Epoch [58][900/1281] lr: 1.693e-02, eta: 12:32:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9981, loss_cls: 0.4543, loss: 0.4543 +2025-06-24 18:01:44,721 - pyskl - INFO - Epoch [58][1000/1281] lr: 1.691e-02, eta: 12:31:42, time: 0.275, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9994, loss_cls: 0.4558, loss: 0.4558 +2025-06-24 18:02:33,913 - pyskl - INFO - Epoch [58][1100/1281] lr: 1.689e-02, eta: 12:31:21, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9950, loss_cls: 0.4342, loss: 0.4342 +2025-06-24 18:03:05,213 - pyskl - INFO - Epoch [58][1200/1281] lr: 1.687e-02, eta: 12:30:32, time: 0.313, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9981, loss_cls: 0.4238, loss: 0.4238 +2025-06-24 18:03:45,506 - pyskl - INFO - Saving checkpoint at 58 epochs +2025-06-24 18:04:44,918 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:04:44,976 - pyskl - INFO - +top1_acc 0.8826 +top5_acc 0.9910 +2025-06-24 18:04:44,976 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:04:44,983 - pyskl - INFO - +mean_acc 0.8344 +2025-06-24 18:04:44,987 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_56.pth was removed +2025-06-24 18:04:45,337 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_58.pth. +2025-06-24 18:04:45,338 - pyskl - INFO - Best top1_acc is 0.8826 at 58 epoch. +2025-06-24 18:04:45,340 - pyskl - INFO - Epoch(val) [58][533] top1_acc: 0.8826, top5_acc: 0.9910, mean_class_accuracy: 0.8344 +2025-06-24 18:06:04,825 - pyskl - INFO - Epoch [59][100/1281] lr: 1.684e-02, eta: 12:29:40, time: 0.795, data_time: 0.195, memory: 4083, top1_acc: 0.9400, top5_acc: 1.0000, loss_cls: 0.3662, loss: 0.3662 +2025-06-24 18:06:53,753 - pyskl - INFO - Epoch [59][200/1281] lr: 1.682e-02, eta: 12:29:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9981, loss_cls: 0.3847, loss: 0.3847 +2025-06-24 18:07:42,704 - pyskl - INFO - Epoch [59][300/1281] lr: 1.680e-02, eta: 12:28:57, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9981, loss_cls: 0.4284, loss: 0.4284 +2025-06-24 18:08:31,793 - pyskl - INFO - Epoch [59][400/1281] lr: 1.678e-02, eta: 12:28:36, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9956, loss_cls: 0.4111, loss: 0.4111 +2025-06-24 18:09:20,911 - pyskl - INFO - Epoch [59][500/1281] lr: 1.676e-02, eta: 12:28:15, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9975, loss_cls: 0.4490, loss: 0.4490 +2025-06-24 18:10:10,086 - pyskl - INFO - Epoch [59][600/1281] lr: 1.674e-02, eta: 12:27:54, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9981, loss_cls: 0.4084, loss: 0.4084 +2025-06-24 18:10:59,019 - pyskl - INFO - Epoch [59][700/1281] lr: 1.672e-02, eta: 12:27:32, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9981, loss_cls: 0.3962, loss: 0.3962 +2025-06-24 18:11:48,076 - pyskl - INFO - Epoch [59][800/1281] lr: 1.670e-02, eta: 12:27:10, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9981, loss_cls: 0.4331, loss: 0.4331 +2025-06-24 18:12:36,845 - pyskl - INFO - Epoch [59][900/1281] lr: 1.668e-02, eta: 12:26:48, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9975, loss_cls: 0.4671, loss: 0.4671 +2025-06-24 18:13:05,401 - pyskl - INFO - Epoch [59][1000/1281] lr: 1.667e-02, eta: 12:25:55, time: 0.286, data_time: 0.001, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9988, loss_cls: 0.4115, loss: 0.4115 +2025-06-24 18:13:54,179 - pyskl - INFO - Epoch [59][1100/1281] lr: 1.665e-02, eta: 12:25:33, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9962, loss_cls: 0.5067, loss: 0.5067 +2025-06-24 18:14:26,825 - pyskl - INFO - Epoch [59][1200/1281] lr: 1.663e-02, eta: 12:24:46, time: 0.326, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9962, loss_cls: 0.4299, loss: 0.4299 +2025-06-24 18:15:07,216 - pyskl - INFO - Saving checkpoint at 59 epochs +2025-06-24 18:16:06,070 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:16:06,125 - pyskl - INFO - +top1_acc 0.8812 +top5_acc 0.9918 +2025-06-24 18:16:06,126 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:16:06,133 - pyskl - INFO - +mean_acc 0.8406 +2025-06-24 18:16:06,135 - pyskl - INFO - Epoch(val) [59][533] top1_acc: 0.8812, top5_acc: 0.9918, mean_class_accuracy: 0.8406 +2025-06-24 18:17:25,106 - pyskl - INFO - Epoch [60][100/1281] lr: 1.659e-02, eta: 12:23:51, time: 0.790, data_time: 0.191, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 0.4102, loss: 0.4102 +2025-06-24 18:18:13,817 - pyskl - INFO - Epoch [60][200/1281] lr: 1.657e-02, eta: 12:23:29, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9994, loss_cls: 0.4002, loss: 0.4002 +2025-06-24 18:19:02,994 - pyskl - INFO - Epoch [60][300/1281] lr: 1.655e-02, eta: 12:23:07, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9969, loss_cls: 0.4009, loss: 0.4009 +2025-06-24 18:19:52,300 - pyskl - INFO - Epoch [60][400/1281] lr: 1.653e-02, eta: 12:22:46, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9994, loss_cls: 0.3527, loss: 0.3527 +2025-06-24 18:20:41,220 - pyskl - INFO - Epoch [60][500/1281] lr: 1.651e-02, eta: 12:22:23, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9981, loss_cls: 0.4042, loss: 0.4042 +2025-06-24 18:21:30,588 - pyskl - INFO - Epoch [60][600/1281] lr: 1.650e-02, eta: 12:22:02, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9981, loss_cls: 0.4067, loss: 0.4067 +2025-06-24 18:22:19,948 - pyskl - INFO - Epoch [60][700/1281] lr: 1.648e-02, eta: 12:21:40, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9975, loss_cls: 0.4200, loss: 0.4200 +2025-06-24 18:23:08,896 - pyskl - INFO - Epoch [60][800/1281] lr: 1.646e-02, eta: 12:21:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9950, loss_cls: 0.4822, loss: 0.4822 +2025-06-24 18:23:57,968 - pyskl - INFO - Epoch [60][900/1281] lr: 1.644e-02, eta: 12:20:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9975, loss_cls: 0.3871, loss: 0.3871 +2025-06-24 18:24:25,155 - pyskl - INFO - Epoch [60][1000/1281] lr: 1.642e-02, eta: 12:20:00, time: 0.272, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9994, loss_cls: 0.4285, loss: 0.4285 +2025-06-24 18:25:15,534 - pyskl - INFO - Epoch [60][1100/1281] lr: 1.640e-02, eta: 12:19:39, time: 0.504, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9994, loss_cls: 0.4053, loss: 0.4053 +2025-06-24 18:25:47,411 - pyskl - INFO - Epoch [60][1200/1281] lr: 1.638e-02, eta: 12:18:51, time: 0.319, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9988, loss_cls: 0.4008, loss: 0.4008 +2025-06-24 18:26:28,030 - pyskl - INFO - Saving checkpoint at 60 epochs +2025-06-24 18:27:27,233 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:27:27,293 - pyskl - INFO - +top1_acc 0.8857 +top5_acc 0.9919 +2025-06-24 18:27:27,293 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:27:27,300 - pyskl - INFO - +mean_acc 0.8508 +2025-06-24 18:27:27,304 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_58.pth was removed +2025-06-24 18:27:27,479 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_60.pth. +2025-06-24 18:27:27,480 - pyskl - INFO - Best top1_acc is 0.8857 at 60 epoch. +2025-06-24 18:27:27,483 - pyskl - INFO - Epoch(val) [60][533] top1_acc: 0.8857, top5_acc: 0.9919, mean_class_accuracy: 0.8508 +2025-06-24 18:28:48,611 - pyskl - INFO - Epoch [61][100/1281] lr: 1.634e-02, eta: 12:17:59, time: 0.811, data_time: 0.197, memory: 4083, top1_acc: 0.9287, top5_acc: 1.0000, loss_cls: 0.3930, loss: 0.3930 +2025-06-24 18:29:38,076 - pyskl - INFO - Epoch [61][200/1281] lr: 1.632e-02, eta: 12:17:37, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9975, loss_cls: 0.4050, loss: 0.4050 +2025-06-24 18:30:27,013 - pyskl - INFO - Epoch [61][300/1281] lr: 1.630e-02, eta: 12:17:14, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9975, loss_cls: 0.4076, loss: 0.4076 +2025-06-24 18:31:16,007 - pyskl - INFO - Epoch [61][400/1281] lr: 1.629e-02, eta: 12:16:51, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9962, loss_cls: 0.4428, loss: 0.4428 +2025-06-24 18:32:04,960 - pyskl - INFO - Epoch [61][500/1281] lr: 1.627e-02, eta: 12:16:28, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9988, loss_cls: 0.4033, loss: 0.4033 +2025-06-24 18:32:54,049 - pyskl - INFO - Epoch [61][600/1281] lr: 1.625e-02, eta: 12:16:06, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9969, loss_cls: 0.4296, loss: 0.4296 +2025-06-24 18:33:43,014 - pyskl - INFO - Epoch [61][700/1281] lr: 1.623e-02, eta: 12:15:42, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 0.4181, loss: 0.4181 +2025-06-24 18:34:31,887 - pyskl - INFO - Epoch [61][800/1281] lr: 1.621e-02, eta: 12:15:19, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9950, loss_cls: 0.4341, loss: 0.4341 +2025-06-24 18:35:21,069 - pyskl - INFO - Epoch [61][900/1281] lr: 1.619e-02, eta: 12:14:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9975, loss_cls: 0.4131, loss: 0.4131 +2025-06-24 18:35:50,138 - pyskl - INFO - Epoch [61][1000/1281] lr: 1.617e-02, eta: 12:14:04, time: 0.291, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9981, loss_cls: 0.4038, loss: 0.4038 +2025-06-24 18:36:36,416 - pyskl - INFO - Epoch [61][1100/1281] lr: 1.615e-02, eta: 12:13:37, time: 0.463, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9975, loss_cls: 0.4329, loss: 0.4329 +2025-06-24 18:37:09,341 - pyskl - INFO - Epoch [61][1200/1281] lr: 1.613e-02, eta: 12:12:50, time: 0.329, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9981, loss_cls: 0.4117, loss: 0.4117 +2025-06-24 18:37:49,904 - pyskl - INFO - Saving checkpoint at 61 epochs +2025-06-24 18:38:49,228 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:38:49,285 - pyskl - INFO - +top1_acc 0.8480 +top5_acc 0.9883 +2025-06-24 18:38:49,285 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:38:49,292 - pyskl - INFO - +mean_acc 0.8042 +2025-06-24 18:38:49,294 - pyskl - INFO - Epoch(val) [61][533] top1_acc: 0.8480, top5_acc: 0.9883, mean_class_accuracy: 0.8042 +2025-06-24 18:40:08,430 - pyskl - INFO - Epoch [62][100/1281] lr: 1.609e-02, eta: 12:11:54, time: 0.791, data_time: 0.193, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9988, loss_cls: 0.3908, loss: 0.3908 +2025-06-24 18:40:57,878 - pyskl - INFO - Epoch [62][200/1281] lr: 1.607e-02, eta: 12:11:31, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9994, loss_cls: 0.3532, loss: 0.3532 +2025-06-24 18:41:47,131 - pyskl - INFO - Epoch [62][300/1281] lr: 1.605e-02, eta: 12:11:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9988, loss_cls: 0.4179, loss: 0.4179 +2025-06-24 18:42:35,845 - pyskl - INFO - Epoch [62][400/1281] lr: 1.603e-02, eta: 12:10:44, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9988, loss_cls: 0.4272, loss: 0.4272 +2025-06-24 18:43:24,817 - pyskl - INFO - Epoch [62][500/1281] lr: 1.602e-02, eta: 12:10:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9988, loss_cls: 0.3882, loss: 0.3882 +2025-06-24 18:44:13,842 - pyskl - INFO - Epoch [62][600/1281] lr: 1.600e-02, eta: 12:09:57, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9962, loss_cls: 0.3732, loss: 0.3732 +2025-06-24 18:45:02,678 - pyskl - INFO - Epoch [62][700/1281] lr: 1.598e-02, eta: 12:09:33, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9962, loss_cls: 0.4480, loss: 0.4480 +2025-06-24 18:45:51,803 - pyskl - INFO - Epoch [62][800/1281] lr: 1.596e-02, eta: 12:09:09, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9988, loss_cls: 0.4151, loss: 0.4151 +2025-06-24 18:46:40,853 - pyskl - INFO - Epoch [62][900/1281] lr: 1.594e-02, eta: 12:08:46, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9969, loss_cls: 0.4247, loss: 0.4247 +2025-06-24 18:47:11,015 - pyskl - INFO - Epoch [62][1000/1281] lr: 1.592e-02, eta: 12:07:55, time: 0.302, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9981, loss_cls: 0.3765, loss: 0.3765 +2025-06-24 18:47:56,893 - pyskl - INFO - Epoch [62][1100/1281] lr: 1.590e-02, eta: 12:07:26, time: 0.459, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9981, loss_cls: 0.4638, loss: 0.4638 +2025-06-24 18:48:28,427 - pyskl - INFO - Epoch [62][1200/1281] lr: 1.588e-02, eta: 12:06:38, time: 0.315, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9981, loss_cls: 0.4317, loss: 0.4317 +2025-06-24 18:49:08,572 - pyskl - INFO - Saving checkpoint at 62 epochs +2025-06-24 18:50:08,079 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:50:08,135 - pyskl - INFO - +top1_acc 0.9032 +top5_acc 0.9945 +2025-06-24 18:50:08,135 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:50:08,142 - pyskl - INFO - +mean_acc 0.8766 +2025-06-24 18:50:08,146 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_60.pth was removed +2025-06-24 18:50:08,322 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_62.pth. +2025-06-24 18:50:08,322 - pyskl - INFO - Best top1_acc is 0.9032 at 62 epoch. +2025-06-24 18:50:08,325 - pyskl - INFO - Epoch(val) [62][533] top1_acc: 0.9032, top5_acc: 0.9945, mean_class_accuracy: 0.8766 +2025-06-24 18:51:28,968 - pyskl - INFO - Epoch [63][100/1281] lr: 1.584e-02, eta: 12:05:43, time: 0.806, data_time: 0.197, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9969, loss_cls: 0.3484, loss: 0.3484 +2025-06-24 18:52:17,817 - pyskl - INFO - Epoch [63][200/1281] lr: 1.582e-02, eta: 12:05:19, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9988, loss_cls: 0.3426, loss: 0.3426 +2025-06-24 18:53:07,020 - pyskl - INFO - Epoch [63][300/1281] lr: 1.580e-02, eta: 12:04:55, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9994, loss_cls: 0.3288, loss: 0.3288 +2025-06-24 18:53:55,834 - pyskl - INFO - Epoch [63][400/1281] lr: 1.578e-02, eta: 12:04:30, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9975, loss_cls: 0.4020, loss: 0.4020 +2025-06-24 18:54:44,759 - pyskl - INFO - Epoch [63][500/1281] lr: 1.576e-02, eta: 12:04:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9975, loss_cls: 0.4097, loss: 0.4097 +2025-06-24 18:55:33,801 - pyskl - INFO - Epoch [63][600/1281] lr: 1.574e-02, eta: 12:03:42, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9981, loss_cls: 0.3989, loss: 0.3989 +2025-06-24 18:56:22,716 - pyskl - INFO - Epoch [63][700/1281] lr: 1.572e-02, eta: 12:03:17, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 0.3984, loss: 0.3984 +2025-06-24 18:57:11,380 - pyskl - INFO - Epoch [63][800/1281] lr: 1.570e-02, eta: 12:02:52, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9994, loss_cls: 0.3656, loss: 0.3656 +2025-06-24 18:58:00,095 - pyskl - INFO - Epoch [63][900/1281] lr: 1.568e-02, eta: 12:02:27, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9981, loss_cls: 0.3735, loss: 0.3735 +2025-06-24 18:58:27,267 - pyskl - INFO - Epoch [63][1000/1281] lr: 1.566e-02, eta: 12:01:33, time: 0.272, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9975, loss_cls: 0.4127, loss: 0.4127 +2025-06-24 18:59:16,876 - pyskl - INFO - Epoch [63][1100/1281] lr: 1.564e-02, eta: 12:01:09, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9969, loss_cls: 0.4357, loss: 0.4357 +2025-06-24 18:59:48,287 - pyskl - INFO - Epoch [63][1200/1281] lr: 1.562e-02, eta: 12:00:20, time: 0.314, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9969, loss_cls: 0.4000, loss: 0.4000 +2025-06-24 19:00:28,627 - pyskl - INFO - Saving checkpoint at 63 epochs +2025-06-24 19:01:28,092 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:01:28,147 - pyskl - INFO - +top1_acc 0.8826 +top5_acc 0.9901 +2025-06-24 19:01:28,148 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:01:28,154 - pyskl - INFO - +mean_acc 0.8425 +2025-06-24 19:01:28,155 - pyskl - INFO - Epoch(val) [63][533] top1_acc: 0.8826, top5_acc: 0.9901, mean_class_accuracy: 0.8425 +2025-06-24 19:02:48,093 - pyskl - INFO - Epoch [64][100/1281] lr: 1.559e-02, eta: 11:59:23, time: 0.799, data_time: 0.195, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 0.3760, loss: 0.3760 +2025-06-24 19:03:37,548 - pyskl - INFO - Epoch [64][200/1281] lr: 1.557e-02, eta: 11:58:59, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9975, loss_cls: 0.3659, loss: 0.3659 +2025-06-24 19:04:27,002 - pyskl - INFO - Epoch [64][300/1281] lr: 1.555e-02, eta: 11:58:35, time: 0.495, data_time: 0.001, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9962, loss_cls: 0.3944, loss: 0.3944 +2025-06-24 19:05:16,098 - pyskl - INFO - Epoch [64][400/1281] lr: 1.553e-02, eta: 11:58:10, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9994, loss_cls: 0.3822, loss: 0.3822 +2025-06-24 19:06:05,146 - pyskl - INFO - Epoch [64][500/1281] lr: 1.551e-02, eta: 11:57:46, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9994, loss_cls: 0.3956, loss: 0.3956 +2025-06-24 19:06:54,290 - pyskl - INFO - Epoch [64][600/1281] lr: 1.549e-02, eta: 11:57:21, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9981, loss_cls: 0.3986, loss: 0.3986 +2025-06-24 19:07:43,496 - pyskl - INFO - Epoch [64][700/1281] lr: 1.547e-02, eta: 11:56:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9994, loss_cls: 0.3485, loss: 0.3485 +2025-06-24 19:08:32,301 - pyskl - INFO - Epoch [64][800/1281] lr: 1.545e-02, eta: 11:56:31, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9981, loss_cls: 0.3807, loss: 0.3807 +2025-06-24 19:09:21,488 - pyskl - INFO - Epoch [64][900/1281] lr: 1.543e-02, eta: 11:56:06, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9975, loss_cls: 0.3674, loss: 0.3674 +2025-06-24 19:09:49,592 - pyskl - INFO - Epoch [64][1000/1281] lr: 1.541e-02, eta: 11:55:13, time: 0.281, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9969, loss_cls: 0.4359, loss: 0.4359 +2025-06-24 19:10:38,021 - pyskl - INFO - Epoch [64][1100/1281] lr: 1.539e-02, eta: 11:54:47, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9956, loss_cls: 0.4338, loss: 0.4338 +2025-06-24 19:11:10,106 - pyskl - INFO - Epoch [64][1200/1281] lr: 1.537e-02, eta: 11:53:59, time: 0.321, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9988, loss_cls: 0.4145, loss: 0.4145 +2025-06-24 19:11:50,229 - pyskl - INFO - Saving checkpoint at 64 epochs +2025-06-24 19:12:49,819 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:12:49,877 - pyskl - INFO - +top1_acc 0.8521 +top5_acc 0.9866 +2025-06-24 19:12:49,877 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:12:49,884 - pyskl - INFO - +mean_acc 0.8065 +2025-06-24 19:12:49,885 - pyskl - INFO - Epoch(val) [64][533] top1_acc: 0.8521, top5_acc: 0.9866, mean_class_accuracy: 0.8065 +2025-06-24 19:14:10,018 - pyskl - INFO - Epoch [65][100/1281] lr: 1.533e-02, eta: 11:53:01, time: 0.801, data_time: 0.198, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9962, loss_cls: 0.4159, loss: 0.4159 +2025-06-24 19:14:59,467 - pyskl - INFO - Epoch [65][200/1281] lr: 1.531e-02, eta: 11:52:37, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9975, loss_cls: 0.4270, loss: 0.4270 +2025-06-24 19:15:48,882 - pyskl - INFO - Epoch [65][300/1281] lr: 1.529e-02, eta: 11:52:12, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9975, loss_cls: 0.3296, loss: 0.3296 +2025-06-24 19:16:38,312 - pyskl - INFO - Epoch [65][400/1281] lr: 1.527e-02, eta: 11:51:47, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 1.0000, loss_cls: 0.3677, loss: 0.3677 +2025-06-24 19:17:27,539 - pyskl - INFO - Epoch [65][500/1281] lr: 1.526e-02, eta: 11:51:22, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9975, loss_cls: 0.3507, loss: 0.3507 +2025-06-24 19:18:17,076 - pyskl - INFO - Epoch [65][600/1281] lr: 1.524e-02, eta: 11:50:57, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9994, loss_cls: 0.3691, loss: 0.3691 +2025-06-24 19:19:06,098 - pyskl - INFO - Epoch [65][700/1281] lr: 1.522e-02, eta: 11:50:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 1.0000, loss_cls: 0.4247, loss: 0.4247 +2025-06-24 19:19:55,017 - pyskl - INFO - Epoch [65][800/1281] lr: 1.520e-02, eta: 11:50:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9975, loss_cls: 0.4216, loss: 0.4216 +2025-06-24 19:20:44,182 - pyskl - INFO - Epoch [65][900/1281] lr: 1.518e-02, eta: 11:49:40, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9956, loss_cls: 0.4054, loss: 0.4054 +2025-06-24 19:21:12,649 - pyskl - INFO - Epoch [65][1000/1281] lr: 1.516e-02, eta: 11:48:47, time: 0.285, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9956, loss_cls: 0.4067, loss: 0.4067 +2025-06-24 19:21:59,644 - pyskl - INFO - Epoch [65][1100/1281] lr: 1.514e-02, eta: 11:48:19, time: 0.470, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9988, loss_cls: 0.3532, loss: 0.3532 +2025-06-24 19:22:32,034 - pyskl - INFO - Epoch [65][1200/1281] lr: 1.512e-02, eta: 11:47:31, time: 0.324, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9981, loss_cls: 0.3980, loss: 0.3980 +2025-06-24 19:23:12,102 - pyskl - INFO - Saving checkpoint at 65 epochs +2025-06-24 19:24:10,969 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:24:11,036 - pyskl - INFO - +top1_acc 0.8599 +top5_acc 0.9869 +2025-06-24 19:24:11,037 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:24:11,045 - pyskl - INFO - +mean_acc 0.8111 +2025-06-24 19:24:11,047 - pyskl - INFO - Epoch(val) [65][533] top1_acc: 0.8599, top5_acc: 0.9869, mean_class_accuracy: 0.8111 +2025-06-24 19:25:31,658 - pyskl - INFO - Epoch [66][100/1281] lr: 1.508e-02, eta: 11:46:34, time: 0.806, data_time: 0.203, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9994, loss_cls: 0.4200, loss: 0.4200 +2025-06-24 19:26:20,922 - pyskl - INFO - Epoch [66][200/1281] lr: 1.506e-02, eta: 11:46:08, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9981, loss_cls: 0.3840, loss: 0.3840 +2025-06-24 19:27:09,565 - pyskl - INFO - Epoch [66][300/1281] lr: 1.504e-02, eta: 11:45:42, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9981, loss_cls: 0.3373, loss: 0.3373 +2025-06-24 19:27:58,568 - pyskl - INFO - Epoch [66][400/1281] lr: 1.502e-02, eta: 11:45:16, time: 0.490, data_time: 0.001, memory: 4083, top1_acc: 0.9463, top5_acc: 1.0000, loss_cls: 0.3325, loss: 0.3325 +2025-06-24 19:28:47,443 - pyskl - INFO - Epoch [66][500/1281] lr: 1.500e-02, eta: 11:44:50, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9994, loss_cls: 0.3880, loss: 0.3880 +2025-06-24 19:29:36,937 - pyskl - INFO - Epoch [66][600/1281] lr: 1.498e-02, eta: 11:44:24, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9969, loss_cls: 0.3951, loss: 0.3951 +2025-06-24 19:30:26,015 - pyskl - INFO - Epoch [66][700/1281] lr: 1.496e-02, eta: 11:43:58, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9969, loss_cls: 0.3863, loss: 0.3863 +2025-06-24 19:31:15,261 - pyskl - INFO - Epoch [66][800/1281] lr: 1.494e-02, eta: 11:43:32, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9975, loss_cls: 0.3598, loss: 0.3598 +2025-06-24 19:32:04,190 - pyskl - INFO - Epoch [66][900/1281] lr: 1.492e-02, eta: 11:43:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9944, loss_cls: 0.4747, loss: 0.4747 +2025-06-24 19:32:32,350 - pyskl - INFO - Epoch [66][1000/1281] lr: 1.490e-02, eta: 11:42:13, time: 0.282, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9994, loss_cls: 0.3883, loss: 0.3883 +2025-06-24 19:33:20,704 - pyskl - INFO - Epoch [66][1100/1281] lr: 1.488e-02, eta: 11:41:46, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3207, loss: 0.3207 +2025-06-24 19:33:51,688 - pyskl - INFO - Epoch [66][1200/1281] lr: 1.486e-02, eta: 11:40:56, time: 0.310, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9994, loss_cls: 0.4249, loss: 0.4249 +2025-06-24 19:34:31,812 - pyskl - INFO - Saving checkpoint at 66 epochs +2025-06-24 19:35:31,148 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:35:31,216 - pyskl - INFO - +top1_acc 0.8957 +top5_acc 0.9917 +2025-06-24 19:35:31,216 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:35:31,227 - pyskl - INFO - +mean_acc 0.8653 +2025-06-24 19:35:31,230 - pyskl - INFO - Epoch(val) [66][533] top1_acc: 0.8957, top5_acc: 0.9917, mean_class_accuracy: 0.8653 +2025-06-24 19:36:50,306 - pyskl - INFO - Epoch [67][100/1281] lr: 1.482e-02, eta: 11:39:56, time: 0.791, data_time: 0.198, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 0.3765, loss: 0.3765 +2025-06-24 19:37:39,509 - pyskl - INFO - Epoch [67][200/1281] lr: 1.480e-02, eta: 11:39:30, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9988, loss_cls: 0.2847, loss: 0.2847 +2025-06-24 19:38:28,484 - pyskl - INFO - Epoch [67][300/1281] lr: 1.478e-02, eta: 11:39:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9981, loss_cls: 0.4145, loss: 0.4145 +2025-06-24 19:39:17,394 - pyskl - INFO - Epoch [67][400/1281] lr: 1.476e-02, eta: 11:38:37, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3650, loss: 0.3650 +2025-06-24 19:40:06,367 - pyskl - INFO - Epoch [67][500/1281] lr: 1.474e-02, eta: 11:38:10, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9988, loss_cls: 0.3628, loss: 0.3628 +2025-06-24 19:40:55,392 - pyskl - INFO - Epoch [67][600/1281] lr: 1.472e-02, eta: 11:37:43, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9975, loss_cls: 0.3712, loss: 0.3712 +2025-06-24 19:41:45,236 - pyskl - INFO - Epoch [67][700/1281] lr: 1.470e-02, eta: 11:37:18, time: 0.498, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 1.0000, loss_cls: 0.3732, loss: 0.3732 +2025-06-24 19:42:34,394 - pyskl - INFO - Epoch [67][800/1281] lr: 1.468e-02, eta: 11:36:51, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9988, loss_cls: 0.3705, loss: 0.3705 +2025-06-24 19:43:23,329 - pyskl - INFO - Epoch [67][900/1281] lr: 1.466e-02, eta: 11:36:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9962, loss_cls: 0.3641, loss: 0.3641 +2025-06-24 19:43:50,762 - pyskl - INFO - Epoch [67][1000/1281] lr: 1.464e-02, eta: 11:35:30, time: 0.274, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9981, loss_cls: 0.3739, loss: 0.3739 +2025-06-24 19:44:41,583 - pyskl - INFO - Epoch [67][1100/1281] lr: 1.462e-02, eta: 11:35:06, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 1.0000, loss_cls: 0.4400, loss: 0.4400 +2025-06-24 19:45:11,028 - pyskl - INFO - Epoch [67][1200/1281] lr: 1.460e-02, eta: 11:34:15, time: 0.294, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9975, loss_cls: 0.4336, loss: 0.4336 +2025-06-24 19:45:51,516 - pyskl - INFO - Saving checkpoint at 67 epochs +2025-06-24 19:46:50,434 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:46:50,493 - pyskl - INFO - +top1_acc 0.8902 +top5_acc 0.9938 +2025-06-24 19:46:50,493 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:46:50,500 - pyskl - INFO - +mean_acc 0.8458 +2025-06-24 19:46:50,503 - pyskl - INFO - Epoch(val) [67][533] top1_acc: 0.8902, top5_acc: 0.9938, mean_class_accuracy: 0.8458 +2025-06-24 19:48:10,743 - pyskl - INFO - Epoch [68][100/1281] lr: 1.456e-02, eta: 11:33:15, time: 0.802, data_time: 0.198, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9988, loss_cls: 0.3901, loss: 0.3901 +2025-06-24 19:48:59,722 - pyskl - INFO - Epoch [68][200/1281] lr: 1.454e-02, eta: 11:32:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9994, loss_cls: 0.3732, loss: 0.3732 +2025-06-24 19:49:48,475 - pyskl - INFO - Epoch [68][300/1281] lr: 1.452e-02, eta: 11:32:21, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9975, loss_cls: 0.3629, loss: 0.3629 +2025-06-24 19:50:37,586 - pyskl - INFO - Epoch [68][400/1281] lr: 1.450e-02, eta: 11:31:54, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9988, loss_cls: 0.3731, loss: 0.3731 +2025-06-24 19:51:26,569 - pyskl - INFO - Epoch [68][500/1281] lr: 1.448e-02, eta: 11:31:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.3241, loss: 0.3241 +2025-06-24 19:52:15,558 - pyskl - INFO - Epoch [68][600/1281] lr: 1.446e-02, eta: 11:31:00, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9988, loss_cls: 0.3944, loss: 0.3944 +2025-06-24 19:53:05,002 - pyskl - INFO - Epoch [68][700/1281] lr: 1.444e-02, eta: 11:30:33, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9975, loss_cls: 0.4169, loss: 0.4169 +2025-06-24 19:53:53,972 - pyskl - INFO - Epoch [68][800/1281] lr: 1.442e-02, eta: 11:30:05, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9988, loss_cls: 0.3841, loss: 0.3841 +2025-06-24 19:54:43,178 - pyskl - INFO - Epoch [68][900/1281] lr: 1.440e-02, eta: 11:29:38, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9981, loss_cls: 0.4119, loss: 0.4119 +2025-06-24 19:55:11,727 - pyskl - INFO - Epoch [68][1000/1281] lr: 1.438e-02, eta: 11:28:46, time: 0.285, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9975, loss_cls: 0.3801, loss: 0.3801 +2025-06-24 19:56:02,667 - pyskl - INFO - Epoch [68][1100/1281] lr: 1.436e-02, eta: 11:28:21, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9969, loss_cls: 0.4023, loss: 0.4023 +2025-06-24 19:56:30,220 - pyskl - INFO - Epoch [68][1200/1281] lr: 1.434e-02, eta: 11:27:28, time: 0.276, data_time: 0.001, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9981, loss_cls: 0.3717, loss: 0.3717 +2025-06-24 19:57:10,467 - pyskl - INFO - Saving checkpoint at 68 epochs +2025-06-24 19:58:10,686 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:58:10,745 - pyskl - INFO - +top1_acc 0.8938 +top5_acc 0.9930 +2025-06-24 19:58:10,745 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:58:10,753 - pyskl - INFO - +mean_acc 0.8628 +2025-06-24 19:58:10,755 - pyskl - INFO - Epoch(val) [68][533] top1_acc: 0.8938, top5_acc: 0.9930, mean_class_accuracy: 0.8628 +2025-06-24 19:59:30,589 - pyskl - INFO - Epoch [69][100/1281] lr: 1.431e-02, eta: 11:26:27, time: 0.798, data_time: 0.191, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9969, loss_cls: 0.3693, loss: 0.3693 +2025-06-24 20:00:19,567 - pyskl - INFO - Epoch [69][200/1281] lr: 1.429e-02, eta: 11:26:00, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9988, loss_cls: 0.3289, loss: 0.3289 +2025-06-24 20:01:08,470 - pyskl - INFO - Epoch [69][300/1281] lr: 1.427e-02, eta: 11:25:32, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9988, loss_cls: 0.3431, loss: 0.3431 +2025-06-24 20:01:57,425 - pyskl - INFO - Epoch [69][400/1281] lr: 1.425e-02, eta: 11:25:04, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 1.0000, loss_cls: 0.3067, loss: 0.3067 +2025-06-24 20:02:46,447 - pyskl - INFO - Epoch [69][500/1281] lr: 1.423e-02, eta: 11:24:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9981, loss_cls: 0.3248, loss: 0.3248 +2025-06-24 20:03:35,692 - pyskl - INFO - Epoch [69][600/1281] lr: 1.420e-02, eta: 11:24:09, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9988, loss_cls: 0.3152, loss: 0.3152 +2025-06-24 20:04:24,451 - pyskl - INFO - Epoch [69][700/1281] lr: 1.418e-02, eta: 11:23:41, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9962, loss_cls: 0.3550, loss: 0.3550 +2025-06-24 20:05:13,575 - pyskl - INFO - Epoch [69][800/1281] lr: 1.416e-02, eta: 11:23:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9988, loss_cls: 0.3042, loss: 0.3042 +2025-06-24 20:06:02,397 - pyskl - INFO - Epoch [69][900/1281] lr: 1.414e-02, eta: 11:22:45, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 1.0000, loss_cls: 0.3108, loss: 0.3108 +2025-06-24 20:06:31,574 - pyskl - INFO - Epoch [69][1000/1281] lr: 1.412e-02, eta: 11:21:54, time: 0.292, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9981, loss_cls: 0.3494, loss: 0.3494 +2025-06-24 20:07:22,591 - pyskl - INFO - Epoch [69][1100/1281] lr: 1.410e-02, eta: 11:21:28, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9994, loss_cls: 0.4168, loss: 0.4168 +2025-06-24 20:07:49,304 - pyskl - INFO - Epoch [69][1200/1281] lr: 1.408e-02, eta: 11:20:34, time: 0.267, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9975, loss_cls: 0.4427, loss: 0.4427 +2025-06-24 20:08:29,864 - pyskl - INFO - Saving checkpoint at 69 epochs +2025-06-24 20:09:29,123 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:09:29,192 - pyskl - INFO - +top1_acc 0.8918 +top5_acc 0.9925 +2025-06-24 20:09:29,193 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:09:29,201 - pyskl - INFO - +mean_acc 0.8516 +2025-06-24 20:09:29,203 - pyskl - INFO - Epoch(val) [69][533] top1_acc: 0.8918, top5_acc: 0.9925, mean_class_accuracy: 0.8516 +2025-06-24 20:10:47,499 - pyskl - INFO - Epoch [70][100/1281] lr: 1.405e-02, eta: 11:19:31, time: 0.783, data_time: 0.196, memory: 4083, top1_acc: 0.9344, top5_acc: 1.0000, loss_cls: 0.3444, loss: 0.3444 +2025-06-24 20:11:36,675 - pyskl - INFO - Epoch [70][200/1281] lr: 1.403e-02, eta: 11:19:04, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9988, loss_cls: 0.3489, loss: 0.3489 +2025-06-24 20:12:25,745 - pyskl - INFO - Epoch [70][300/1281] lr: 1.401e-02, eta: 11:18:36, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9981, loss_cls: 0.3326, loss: 0.3326 +2025-06-24 20:13:14,980 - pyskl - INFO - Epoch [70][400/1281] lr: 1.399e-02, eta: 11:18:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9981, loss_cls: 0.3304, loss: 0.3304 +2025-06-24 20:14:04,301 - pyskl - INFO - Epoch [70][500/1281] lr: 1.397e-02, eta: 11:17:40, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9969, loss_cls: 0.4136, loss: 0.4136 +2025-06-24 20:14:53,625 - pyskl - INFO - Epoch [70][600/1281] lr: 1.395e-02, eta: 11:17:12, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9994, loss_cls: 0.3530, loss: 0.3530 +2025-06-24 20:15:42,345 - pyskl - INFO - Epoch [70][700/1281] lr: 1.392e-02, eta: 11:16:43, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9988, loss_cls: 0.3356, loss: 0.3356 +2025-06-24 20:16:31,156 - pyskl - INFO - Epoch [70][800/1281] lr: 1.390e-02, eta: 11:16:15, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9994, loss_cls: 0.4058, loss: 0.4058 +2025-06-24 20:17:20,265 - pyskl - INFO - Epoch [70][900/1281] lr: 1.388e-02, eta: 11:15:47, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9981, loss_cls: 0.3663, loss: 0.3663 +2025-06-24 20:17:53,215 - pyskl - INFO - Epoch [70][1000/1281] lr: 1.386e-02, eta: 11:15:00, time: 0.329, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9988, loss_cls: 0.3565, loss: 0.3565 +2025-06-24 20:18:44,289 - pyskl - INFO - Epoch [70][1100/1281] lr: 1.384e-02, eta: 11:14:34, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 1.0000, loss_cls: 0.3734, loss: 0.3734 +2025-06-24 20:19:09,426 - pyskl - INFO - Epoch [70][1200/1281] lr: 1.382e-02, eta: 11:13:38, time: 0.251, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9994, loss_cls: 0.3535, loss: 0.3535 +2025-06-24 20:19:48,643 - pyskl - INFO - Saving checkpoint at 70 epochs +2025-06-24 20:20:48,164 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:20:48,221 - pyskl - INFO - +top1_acc 0.8849 +top5_acc 0.9916 +2025-06-24 20:20:48,221 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:20:48,228 - pyskl - INFO - +mean_acc 0.8343 +2025-06-24 20:20:48,231 - pyskl - INFO - Epoch(val) [70][533] top1_acc: 0.8849, top5_acc: 0.9916, mean_class_accuracy: 0.8343 +2025-06-24 20:22:06,714 - pyskl - INFO - Epoch [71][100/1281] lr: 1.379e-02, eta: 11:12:35, time: 0.785, data_time: 0.196, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9969, loss_cls: 0.3424, loss: 0.3424 +2025-06-24 20:22:55,893 - pyskl - INFO - Epoch [71][200/1281] lr: 1.377e-02, eta: 11:12:07, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 0.3337, loss: 0.3337 +2025-06-24 20:23:44,799 - pyskl - INFO - Epoch [71][300/1281] lr: 1.375e-02, eta: 11:11:38, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3572, loss: 0.3572 +2025-06-24 20:24:33,831 - pyskl - INFO - Epoch [71][400/1281] lr: 1.373e-02, eta: 11:11:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9994, loss_cls: 0.3083, loss: 0.3083 +2025-06-24 20:25:23,027 - pyskl - INFO - Epoch [71][500/1281] lr: 1.371e-02, eta: 11:10:41, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9988, loss_cls: 0.3541, loss: 0.3541 +2025-06-24 20:26:11,709 - pyskl - INFO - Epoch [71][600/1281] lr: 1.368e-02, eta: 11:10:12, time: 0.487, data_time: 0.001, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9988, loss_cls: 0.3080, loss: 0.3080 +2025-06-24 20:27:00,812 - pyskl - INFO - Epoch [71][700/1281] lr: 1.366e-02, eta: 11:09:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9994, loss_cls: 0.3704, loss: 0.3704 +2025-06-24 20:27:50,155 - pyskl - INFO - Epoch [71][800/1281] lr: 1.364e-02, eta: 11:09:15, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 1.0000, loss_cls: 0.3235, loss: 0.3235 +2025-06-24 20:28:39,331 - pyskl - INFO - Epoch [71][900/1281] lr: 1.362e-02, eta: 11:08:46, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 0.3196, loss: 0.3196 +2025-06-24 20:29:14,184 - pyskl - INFO - Epoch [71][1000/1281] lr: 1.360e-02, eta: 11:08:01, time: 0.349, data_time: 0.001, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9981, loss_cls: 0.3426, loss: 0.3426 +2025-06-24 20:30:04,997 - pyskl - INFO - Epoch [71][1100/1281] lr: 1.358e-02, eta: 11:07:35, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9988, loss_cls: 0.3616, loss: 0.3616 +2025-06-24 20:30:29,350 - pyskl - INFO - Epoch [71][1200/1281] lr: 1.356e-02, eta: 11:06:38, time: 0.244, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9962, loss_cls: 0.4241, loss: 0.4241 +2025-06-24 20:31:06,288 - pyskl - INFO - Saving checkpoint at 71 epochs +2025-06-24 20:32:05,505 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:32:05,562 - pyskl - INFO - +top1_acc 0.8838 +top5_acc 0.9925 +2025-06-24 20:32:05,562 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:32:05,571 - pyskl - INFO - +mean_acc 0.8411 +2025-06-24 20:32:05,574 - pyskl - INFO - Epoch(val) [71][533] top1_acc: 0.8838, top5_acc: 0.9925, mean_class_accuracy: 0.8411 +2025-06-24 20:33:24,796 - pyskl - INFO - Epoch [72][100/1281] lr: 1.353e-02, eta: 11:05:35, time: 0.792, data_time: 0.188, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9981, loss_cls: 0.3523, loss: 0.3523 +2025-06-24 20:34:13,973 - pyskl - INFO - Epoch [72][200/1281] lr: 1.351e-02, eta: 11:05:07, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9981, loss_cls: 0.3422, loss: 0.3422 +2025-06-24 20:35:02,936 - pyskl - INFO - Epoch [72][300/1281] lr: 1.349e-02, eta: 11:04:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9988, loss_cls: 0.3158, loss: 0.3158 +2025-06-24 20:35:51,627 - pyskl - INFO - Epoch [72][400/1281] lr: 1.346e-02, eta: 11:04:08, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 1.0000, loss_cls: 0.3513, loss: 0.3513 +2025-06-24 20:36:40,542 - pyskl - INFO - Epoch [72][500/1281] lr: 1.344e-02, eta: 11:03:39, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9994, loss_cls: 0.2928, loss: 0.2928 +2025-06-24 20:37:29,527 - pyskl - INFO - Epoch [72][600/1281] lr: 1.342e-02, eta: 11:03:10, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9988, loss_cls: 0.2970, loss: 0.2970 +2025-06-24 20:38:18,947 - pyskl - INFO - Epoch [72][700/1281] lr: 1.340e-02, eta: 11:02:41, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 1.0000, loss_cls: 0.3203, loss: 0.3203 +2025-06-24 20:39:07,953 - pyskl - INFO - Epoch [72][800/1281] lr: 1.338e-02, eta: 11:02:12, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9981, loss_cls: 0.3808, loss: 0.3808 +2025-06-24 20:39:56,803 - pyskl - INFO - Epoch [72][900/1281] lr: 1.336e-02, eta: 11:01:42, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9988, loss_cls: 0.3590, loss: 0.3590 +2025-06-24 20:40:34,107 - pyskl - INFO - Epoch [72][1000/1281] lr: 1.334e-02, eta: 11:01:00, time: 0.373, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9981, loss_cls: 0.3648, loss: 0.3648 +2025-06-24 20:41:24,995 - pyskl - INFO - Epoch [72][1100/1281] lr: 1.332e-02, eta: 11:00:33, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9988, loss_cls: 0.3712, loss: 0.3712 +2025-06-24 20:41:48,776 - pyskl - INFO - Epoch [72][1200/1281] lr: 1.330e-02, eta: 10:59:36, time: 0.238, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9969, loss_cls: 0.3588, loss: 0.3588 +2025-06-24 20:42:24,877 - pyskl - INFO - Saving checkpoint at 72 epochs +2025-06-24 20:43:23,755 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:43:23,814 - pyskl - INFO - +top1_acc 0.9060 +top5_acc 0.9934 +2025-06-24 20:43:23,815 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:43:23,822 - pyskl - INFO - +mean_acc 0.8784 +2025-06-24 20:43:23,826 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_62.pth was removed +2025-06-24 20:43:24,001 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_72.pth. +2025-06-24 20:43:24,001 - pyskl - INFO - Best top1_acc is 0.9060 at 72 epoch. +2025-06-24 20:43:24,005 - pyskl - INFO - Epoch(val) [72][533] top1_acc: 0.9060, top5_acc: 0.9934, mean_class_accuracy: 0.8784 +2025-06-24 20:44:42,961 - pyskl - INFO - Epoch [73][100/1281] lr: 1.326e-02, eta: 10:58:32, time: 0.790, data_time: 0.195, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9988, loss_cls: 0.3153, loss: 0.3153 +2025-06-24 20:45:31,994 - pyskl - INFO - Epoch [73][200/1281] lr: 1.324e-02, eta: 10:58:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9994, loss_cls: 0.3222, loss: 0.3222 +2025-06-24 20:46:20,943 - pyskl - INFO - Epoch [73][300/1281] lr: 1.322e-02, eta: 10:57:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9975, loss_cls: 0.3922, loss: 0.3922 +2025-06-24 20:47:09,973 - pyskl - INFO - Epoch [73][400/1281] lr: 1.320e-02, eta: 10:57:04, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9988, loss_cls: 0.3345, loss: 0.3345 +2025-06-24 20:47:58,915 - pyskl - INFO - Epoch [73][500/1281] lr: 1.318e-02, eta: 10:56:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9988, loss_cls: 0.3312, loss: 0.3312 +2025-06-24 20:48:47,890 - pyskl - INFO - Epoch [73][600/1281] lr: 1.316e-02, eta: 10:56:05, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9981, loss_cls: 0.3014, loss: 0.3014 +2025-06-24 20:49:36,880 - pyskl - INFO - Epoch [73][700/1281] lr: 1.314e-02, eta: 10:55:35, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9981, loss_cls: 0.3137, loss: 0.3137 +2025-06-24 20:50:26,069 - pyskl - INFO - Epoch [73][800/1281] lr: 1.312e-02, eta: 10:55:06, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9975, loss_cls: 0.3464, loss: 0.3464 +2025-06-24 20:51:15,075 - pyskl - INFO - Epoch [73][900/1281] lr: 1.310e-02, eta: 10:54:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 1.0000, loss_cls: 0.3119, loss: 0.3119 +2025-06-24 20:51:54,474 - pyskl - INFO - Epoch [73][1000/1281] lr: 1.308e-02, eta: 10:53:56, time: 0.394, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9969, loss_cls: 0.3439, loss: 0.3439 +2025-06-24 20:52:44,328 - pyskl - INFO - Epoch [73][1100/1281] lr: 1.306e-02, eta: 10:53:27, time: 0.499, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 0.3329, loss: 0.3329 +2025-06-24 20:53:08,064 - pyskl - INFO - Epoch [73][1200/1281] lr: 1.304e-02, eta: 10:52:31, time: 0.237, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.2921, loss: 0.2921 +2025-06-24 20:53:41,030 - pyskl - INFO - Saving checkpoint at 73 epochs +2025-06-24 20:54:39,828 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:54:39,885 - pyskl - INFO - +top1_acc 0.8924 +top5_acc 0.9935 +2025-06-24 20:54:39,885 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:54:39,892 - pyskl - INFO - +mean_acc 0.8500 +2025-06-24 20:54:39,894 - pyskl - INFO - Epoch(val) [73][533] top1_acc: 0.8924, top5_acc: 0.9935, mean_class_accuracy: 0.8500 +2025-06-24 20:56:00,767 - pyskl - INFO - Epoch [74][100/1281] lr: 1.300e-02, eta: 10:51:28, time: 0.809, data_time: 0.193, memory: 4083, top1_acc: 0.9556, top5_acc: 1.0000, loss_cls: 0.2824, loss: 0.2824 +2025-06-24 20:56:50,057 - pyskl - INFO - Epoch [74][200/1281] lr: 1.298e-02, eta: 10:50:59, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 0.3042, loss: 0.3042 +2025-06-24 20:57:39,094 - pyskl - INFO - Epoch [74][300/1281] lr: 1.296e-02, eta: 10:50:29, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9988, loss_cls: 0.3378, loss: 0.3378 +2025-06-24 20:58:28,257 - pyskl - INFO - Epoch [74][400/1281] lr: 1.294e-02, eta: 10:49:59, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9994, loss_cls: 0.3197, loss: 0.3197 +2025-06-24 20:59:17,692 - pyskl - INFO - Epoch [74][500/1281] lr: 1.292e-02, eta: 10:49:30, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9994, loss_cls: 0.3253, loss: 0.3253 +2025-06-24 21:00:06,970 - pyskl - INFO - Epoch [74][600/1281] lr: 1.290e-02, eta: 10:49:00, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 1.0000, loss_cls: 0.3819, loss: 0.3819 +2025-06-24 21:00:56,157 - pyskl - INFO - Epoch [74][700/1281] lr: 1.288e-02, eta: 10:48:30, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 1.0000, loss_cls: 0.3339, loss: 0.3339 +2025-06-24 21:01:44,592 - pyskl - INFO - Epoch [74][800/1281] lr: 1.286e-02, eta: 10:47:59, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 0.3059, loss: 0.3059 +2025-06-24 21:02:33,524 - pyskl - INFO - Epoch [74][900/1281] lr: 1.284e-02, eta: 10:47:29, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9981, loss_cls: 0.3729, loss: 0.3729 +2025-06-24 21:03:16,571 - pyskl - INFO - Epoch [74][1000/1281] lr: 1.282e-02, eta: 10:46:53, time: 0.430, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9988, loss_cls: 0.3395, loss: 0.3395 +2025-06-24 21:04:00,418 - pyskl - INFO - Epoch [74][1100/1281] lr: 1.280e-02, eta: 10:46:17, time: 0.438, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9981, loss_cls: 0.3824, loss: 0.3824 +2025-06-24 21:04:30,162 - pyskl - INFO - Epoch [74][1200/1281] lr: 1.278e-02, eta: 10:45:27, time: 0.297, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9975, loss_cls: 0.3845, loss: 0.3845 +2025-06-24 21:05:02,310 - pyskl - INFO - Saving checkpoint at 74 epochs +2025-06-24 21:06:00,974 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:06:01,039 - pyskl - INFO - +top1_acc 0.8943 +top5_acc 0.9920 +2025-06-24 21:06:01,039 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:06:01,050 - pyskl - INFO - +mean_acc 0.8601 +2025-06-24 21:06:01,052 - pyskl - INFO - Epoch(val) [74][533] top1_acc: 0.8943, top5_acc: 0.9920, mean_class_accuracy: 0.8601 +2025-06-24 21:07:22,299 - pyskl - INFO - Epoch [75][100/1281] lr: 1.274e-02, eta: 10:44:25, time: 0.812, data_time: 0.192, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9994, loss_cls: 0.3263, loss: 0.3263 +2025-06-24 21:08:11,485 - pyskl - INFO - Epoch [75][200/1281] lr: 1.272e-02, eta: 10:43:55, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9994, loss_cls: 0.3150, loss: 0.3150 +2025-06-24 21:09:00,382 - pyskl - INFO - Epoch [75][300/1281] lr: 1.270e-02, eta: 10:43:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9988, loss_cls: 0.3328, loss: 0.3328 +2025-06-24 21:09:49,625 - pyskl - INFO - Epoch [75][400/1281] lr: 1.268e-02, eta: 10:42:54, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9988, loss_cls: 0.2841, loss: 0.2841 +2025-06-24 21:10:38,800 - pyskl - INFO - Epoch [75][500/1281] lr: 1.266e-02, eta: 10:42:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 1.0000, loss_cls: 0.2974, loss: 0.2974 +2025-06-24 21:11:28,054 - pyskl - INFO - Epoch [75][600/1281] lr: 1.264e-02, eta: 10:41:54, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9981, loss_cls: 0.3242, loss: 0.3242 +2025-06-24 21:12:17,211 - pyskl - INFO - Epoch [75][700/1281] lr: 1.262e-02, eta: 10:41:23, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.2789, loss: 0.2789 +2025-06-24 21:13:06,248 - pyskl - INFO - Epoch [75][800/1281] lr: 1.260e-02, eta: 10:40:53, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 1.0000, loss_cls: 0.2968, loss: 0.2968 +2025-06-24 21:13:55,316 - pyskl - INFO - Epoch [75][900/1281] lr: 1.258e-02, eta: 10:40:22, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9994, loss_cls: 0.3410, loss: 0.3410 +2025-06-24 21:14:37,972 - pyskl - INFO - Epoch [75][1000/1281] lr: 1.256e-02, eta: 10:39:45, time: 0.427, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9988, loss_cls: 0.3229, loss: 0.3229 +2025-06-24 21:15:21,684 - pyskl - INFO - Epoch [75][1100/1281] lr: 1.254e-02, eta: 10:39:09, time: 0.437, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9994, loss_cls: 0.3481, loss: 0.3481 +2025-06-24 21:15:51,230 - pyskl - INFO - Epoch [75][1200/1281] lr: 1.252e-02, eta: 10:38:19, time: 0.295, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 1.0000, loss_cls: 0.3894, loss: 0.3894 +2025-06-24 21:16:23,229 - pyskl - INFO - Saving checkpoint at 75 epochs +2025-06-24 21:17:21,536 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:17:21,593 - pyskl - INFO - +top1_acc 0.9027 +top5_acc 0.9923 +2025-06-24 21:17:21,594 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:17:21,601 - pyskl - INFO - +mean_acc 0.8648 +2025-06-24 21:17:21,604 - pyskl - INFO - Epoch(val) [75][533] top1_acc: 0.9027, top5_acc: 0.9923, mean_class_accuracy: 0.8648 +2025-06-24 21:18:41,631 - pyskl - INFO - Epoch [76][100/1281] lr: 1.248e-02, eta: 10:37:15, time: 0.800, data_time: 0.193, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 0.3414, loss: 0.3414 +2025-06-24 21:19:30,979 - pyskl - INFO - Epoch [76][200/1281] lr: 1.246e-02, eta: 10:36:45, time: 0.493, data_time: 0.001, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9988, loss_cls: 0.3375, loss: 0.3375 +2025-06-24 21:20:20,680 - pyskl - INFO - Epoch [76][300/1281] lr: 1.244e-02, eta: 10:36:15, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9975, loss_cls: 0.3566, loss: 0.3566 +2025-06-24 21:21:09,553 - pyskl - INFO - Epoch [76][400/1281] lr: 1.242e-02, eta: 10:35:44, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9975, loss_cls: 0.3008, loss: 0.3008 +2025-06-24 21:21:59,066 - pyskl - INFO - Epoch [76][500/1281] lr: 1.240e-02, eta: 10:35:13, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9988, loss_cls: 0.3105, loss: 0.3105 +2025-06-24 21:22:48,213 - pyskl - INFO - Epoch [76][600/1281] lr: 1.238e-02, eta: 10:34:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2763, loss: 0.2763 +2025-06-24 21:23:37,086 - pyskl - INFO - Epoch [76][700/1281] lr: 1.236e-02, eta: 10:34:12, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9994, loss_cls: 0.3507, loss: 0.3507 +2025-06-24 21:24:26,206 - pyskl - INFO - Epoch [76][800/1281] lr: 1.234e-02, eta: 10:33:41, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9981, loss_cls: 0.2933, loss: 0.2933 +2025-06-24 21:25:14,958 - pyskl - INFO - Epoch [76][900/1281] lr: 1.232e-02, eta: 10:33:09, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9969, loss_cls: 0.3267, loss: 0.3267 +2025-06-24 21:25:58,926 - pyskl - INFO - Epoch [76][1000/1281] lr: 1.230e-02, eta: 10:32:34, time: 0.440, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9988, loss_cls: 0.3319, loss: 0.3319 +2025-06-24 21:26:40,616 - pyskl - INFO - Epoch [76][1100/1281] lr: 1.228e-02, eta: 10:31:55, time: 0.417, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9994, loss_cls: 0.3683, loss: 0.3683 +2025-06-24 21:27:12,637 - pyskl - INFO - Epoch [76][1200/1281] lr: 1.225e-02, eta: 10:31:08, time: 0.320, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9969, loss_cls: 0.3901, loss: 0.3901 +2025-06-24 21:27:43,264 - pyskl - INFO - Saving checkpoint at 76 epochs +2025-06-24 21:28:42,089 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:28:42,146 - pyskl - INFO - +top1_acc 0.8574 +top5_acc 0.9896 +2025-06-24 21:28:42,146 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:28:42,154 - pyskl - INFO - +mean_acc 0.8429 +2025-06-24 21:28:42,156 - pyskl - INFO - Epoch(val) [76][533] top1_acc: 0.8574, top5_acc: 0.9896, mean_class_accuracy: 0.8429 +2025-06-24 21:30:02,414 - pyskl - INFO - Epoch [77][100/1281] lr: 1.222e-02, eta: 10:30:03, time: 0.803, data_time: 0.193, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9981, loss_cls: 0.3483, loss: 0.3483 +2025-06-24 21:30:51,381 - pyskl - INFO - Epoch [77][200/1281] lr: 1.220e-02, eta: 10:29:32, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 0.2929, loss: 0.2929 +2025-06-24 21:31:40,086 - pyskl - INFO - Epoch [77][300/1281] lr: 1.218e-02, eta: 10:29:01, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9994, loss_cls: 0.3090, loss: 0.3090 +2025-06-24 21:32:29,152 - pyskl - INFO - Epoch [77][400/1281] lr: 1.216e-02, eta: 10:28:30, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 0.2916, loss: 0.2916 +2025-06-24 21:33:18,269 - pyskl - INFO - Epoch [77][500/1281] lr: 1.214e-02, eta: 10:27:58, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 1.0000, loss_cls: 0.3214, loss: 0.3214 +2025-06-24 21:34:07,494 - pyskl - INFO - Epoch [77][600/1281] lr: 1.212e-02, eta: 10:27:27, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 1.0000, loss_cls: 0.3082, loss: 0.3082 +2025-06-24 21:34:56,439 - pyskl - INFO - Epoch [77][700/1281] lr: 1.210e-02, eta: 10:26:56, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 1.0000, loss_cls: 0.2864, loss: 0.2864 +2025-06-24 21:35:45,440 - pyskl - INFO - Epoch [77][800/1281] lr: 1.207e-02, eta: 10:26:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 0.2744, loss: 0.2744 +2025-06-24 21:36:34,382 - pyskl - INFO - Epoch [77][900/1281] lr: 1.205e-02, eta: 10:25:53, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9988, loss_cls: 0.2888, loss: 0.2888 +2025-06-24 21:37:19,459 - pyskl - INFO - Epoch [77][1000/1281] lr: 1.203e-02, eta: 10:25:18, time: 0.451, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 0.2823, loss: 0.2823 +2025-06-24 21:37:59,735 - pyskl - INFO - Epoch [77][1100/1281] lr: 1.201e-02, eta: 10:24:38, time: 0.403, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2980, loss: 0.2980 +2025-06-24 21:38:32,642 - pyskl - INFO - Epoch [77][1200/1281] lr: 1.199e-02, eta: 10:23:52, time: 0.329, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.3069, loss: 0.3069 +2025-06-24 21:39:01,895 - pyskl - INFO - Saving checkpoint at 77 epochs +2025-06-24 21:40:00,928 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:40:00,985 - pyskl - INFO - +top1_acc 0.8967 +top5_acc 0.9919 +2025-06-24 21:40:00,985 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:40:00,993 - pyskl - INFO - +mean_acc 0.8660 +2025-06-24 21:40:00,996 - pyskl - INFO - Epoch(val) [77][533] top1_acc: 0.8967, top5_acc: 0.9919, mean_class_accuracy: 0.8660 +2025-06-24 21:41:21,039 - pyskl - INFO - Epoch [78][100/1281] lr: 1.196e-02, eta: 10:22:46, time: 0.800, data_time: 0.192, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2276, loss: 0.2276 +2025-06-24 21:42:10,114 - pyskl - INFO - Epoch [78][200/1281] lr: 1.194e-02, eta: 10:22:15, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 0.2510, loss: 0.2510 +2025-06-24 21:42:59,077 - pyskl - INFO - Epoch [78][300/1281] lr: 1.192e-02, eta: 10:21:43, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9994, loss_cls: 0.2417, loss: 0.2417 +2025-06-24 21:43:47,581 - pyskl - INFO - Epoch [78][400/1281] lr: 1.190e-02, eta: 10:21:11, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 0.3367, loss: 0.3367 +2025-06-24 21:44:36,734 - pyskl - INFO - Epoch [78][500/1281] lr: 1.187e-02, eta: 10:20:40, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 1.0000, loss_cls: 0.3153, loss: 0.3153 +2025-06-24 21:45:25,791 - pyskl - INFO - Epoch [78][600/1281] lr: 1.185e-02, eta: 10:20:08, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 1.0000, loss_cls: 0.3145, loss: 0.3145 +2025-06-24 21:46:15,010 - pyskl - INFO - Epoch [78][700/1281] lr: 1.183e-02, eta: 10:19:37, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 1.0000, loss_cls: 0.3103, loss: 0.3103 +2025-06-24 21:47:04,151 - pyskl - INFO - Epoch [78][800/1281] lr: 1.181e-02, eta: 10:19:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9988, loss_cls: 0.3492, loss: 0.3492 +2025-06-24 21:47:53,388 - pyskl - INFO - Epoch [78][900/1281] lr: 1.179e-02, eta: 10:18:34, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 0.3352, loss: 0.3352 +2025-06-24 21:48:40,848 - pyskl - INFO - Epoch [78][1000/1281] lr: 1.177e-02, eta: 10:18:01, time: 0.475, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 1.0000, loss_cls: 0.3400, loss: 0.3400 +2025-06-24 21:49:15,486 - pyskl - INFO - Epoch [78][1100/1281] lr: 1.175e-02, eta: 10:17:15, time: 0.346, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9975, loss_cls: 0.3024, loss: 0.3024 +2025-06-24 21:49:54,364 - pyskl - INFO - Epoch [78][1200/1281] lr: 1.173e-02, eta: 10:16:34, time: 0.389, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9975, loss_cls: 0.3439, loss: 0.3439 +2025-06-24 21:50:21,125 - pyskl - INFO - Saving checkpoint at 78 epochs +2025-06-24 21:51:20,132 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:51:20,205 - pyskl - INFO - +top1_acc 0.8859 +top5_acc 0.9927 +2025-06-24 21:51:20,205 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:51:20,214 - pyskl - INFO - +mean_acc 0.8453 +2025-06-24 21:51:20,216 - pyskl - INFO - Epoch(val) [78][533] top1_acc: 0.8859, top5_acc: 0.9927, mean_class_accuracy: 0.8453 +2025-06-24 21:52:40,132 - pyskl - INFO - Epoch [79][100/1281] lr: 1.169e-02, eta: 10:15:28, time: 0.799, data_time: 0.194, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.2554, loss: 0.2554 +2025-06-24 21:53:29,219 - pyskl - INFO - Epoch [79][200/1281] lr: 1.167e-02, eta: 10:14:57, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 0.2287, loss: 0.2287 +2025-06-24 21:54:18,275 - pyskl - INFO - Epoch [79][300/1281] lr: 1.165e-02, eta: 10:14:25, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9981, loss_cls: 0.2975, loss: 0.2975 +2025-06-24 21:55:06,548 - pyskl - INFO - Epoch [79][400/1281] lr: 1.163e-02, eta: 10:13:52, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9988, loss_cls: 0.3186, loss: 0.3186 +2025-06-24 21:55:55,662 - pyskl - INFO - Epoch [79][500/1281] lr: 1.161e-02, eta: 10:13:20, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 0.3185, loss: 0.3185 +2025-06-24 21:56:44,145 - pyskl - INFO - Epoch [79][600/1281] lr: 1.159e-02, eta: 10:12:48, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9988, loss_cls: 0.3068, loss: 0.3068 +2025-06-24 21:57:32,993 - pyskl - INFO - Epoch [79][700/1281] lr: 1.157e-02, eta: 10:12:16, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 0.3311, loss: 0.3311 +2025-06-24 21:58:21,933 - pyskl - INFO - Epoch [79][800/1281] lr: 1.155e-02, eta: 10:11:43, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9994, loss_cls: 0.3567, loss: 0.3567 +2025-06-24 21:59:11,154 - pyskl - INFO - Epoch [79][900/1281] lr: 1.153e-02, eta: 10:11:12, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 0.3431, loss: 0.3431 +2025-06-24 22:00:00,332 - pyskl - INFO - Epoch [79][1000/1281] lr: 1.151e-02, eta: 10:10:40, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9988, loss_cls: 0.3313, loss: 0.3313 +2025-06-24 22:00:30,616 - pyskl - INFO - Epoch [79][1100/1281] lr: 1.149e-02, eta: 10:09:50, time: 0.303, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9981, loss_cls: 0.3421, loss: 0.3421 +2025-06-24 22:01:14,277 - pyskl - INFO - Epoch [79][1200/1281] lr: 1.147e-02, eta: 10:09:13, time: 0.437, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 0.2638, loss: 0.2638 +2025-06-24 22:01:37,949 - pyskl - INFO - Saving checkpoint at 79 epochs +2025-06-24 22:02:36,159 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:02:36,245 - pyskl - INFO - +top1_acc 0.8999 +top5_acc 0.9935 +2025-06-24 22:02:36,245 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:02:36,257 - pyskl - INFO - +mean_acc 0.8539 +2025-06-24 22:02:36,259 - pyskl - INFO - Epoch(val) [79][533] top1_acc: 0.8999, top5_acc: 0.9935, mean_class_accuracy: 0.8539 +2025-06-24 22:03:55,500 - pyskl - INFO - Epoch [80][100/1281] lr: 1.143e-02, eta: 10:08:07, time: 0.792, data_time: 0.192, memory: 4083, top1_acc: 0.9656, top5_acc: 0.9962, loss_cls: 0.2377, loss: 0.2377 +2025-06-24 22:04:44,604 - pyskl - INFO - Epoch [80][200/1281] lr: 1.141e-02, eta: 10:07:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9981, loss_cls: 0.2611, loss: 0.2611 +2025-06-24 22:05:33,789 - pyskl - INFO - Epoch [80][300/1281] lr: 1.139e-02, eta: 10:07:02, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 0.9994, loss_cls: 0.2433, loss: 0.2433 +2025-06-24 22:06:22,738 - pyskl - INFO - Epoch [80][400/1281] lr: 1.137e-02, eta: 10:06:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 0.2478, loss: 0.2478 +2025-06-24 22:07:11,442 - pyskl - INFO - Epoch [80][500/1281] lr: 1.135e-02, eta: 10:05:57, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 0.9988, loss_cls: 0.3129, loss: 0.3129 +2025-06-24 22:08:00,329 - pyskl - INFO - Epoch [80][600/1281] lr: 1.133e-02, eta: 10:05:25, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9962, loss_cls: 0.3349, loss: 0.3349 +2025-06-24 22:08:49,479 - pyskl - INFO - Epoch [80][700/1281] lr: 1.131e-02, eta: 10:04:53, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9975, loss_cls: 0.3229, loss: 0.3229 +2025-06-24 22:09:38,530 - pyskl - INFO - Epoch [80][800/1281] lr: 1.129e-02, eta: 10:04:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9988, loss_cls: 0.3107, loss: 0.3107 +2025-06-24 22:10:27,576 - pyskl - INFO - Epoch [80][900/1281] lr: 1.127e-02, eta: 10:03:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9994, loss_cls: 0.3260, loss: 0.3260 +2025-06-24 22:11:16,731 - pyskl - INFO - Epoch [80][1000/1281] lr: 1.125e-02, eta: 10:03:15, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9994, loss_cls: 0.2724, loss: 0.2724 +2025-06-24 22:11:44,428 - pyskl - INFO - Epoch [80][1100/1281] lr: 1.123e-02, eta: 10:02:24, time: 0.277, data_time: 0.001, memory: 4083, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 0.2769, loss: 0.2769 +2025-06-24 22:12:35,273 - pyskl - INFO - Epoch [80][1200/1281] lr: 1.121e-02, eta: 10:01:53, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9994, loss_cls: 0.3242, loss: 0.3242 +2025-06-24 22:12:56,889 - pyskl - INFO - Saving checkpoint at 80 epochs +2025-06-24 22:13:55,554 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:13:55,610 - pyskl - INFO - +top1_acc 0.8869 +top5_acc 0.9908 +2025-06-24 22:13:55,610 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:13:55,616 - pyskl - INFO - +mean_acc 0.8586 +2025-06-24 22:13:55,618 - pyskl - INFO - Epoch(val) [80][533] top1_acc: 0.8869, top5_acc: 0.9908, mean_class_accuracy: 0.8586 +2025-06-24 22:15:16,666 - pyskl - INFO - Epoch [81][100/1281] lr: 1.117e-02, eta: 10:00:48, time: 0.810, data_time: 0.194, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9975, loss_cls: 0.3513, loss: 0.3513 +2025-06-24 22:16:05,642 - pyskl - INFO - Epoch [81][200/1281] lr: 1.115e-02, eta: 10:00:15, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9994, loss_cls: 0.2784, loss: 0.2784 +2025-06-24 22:16:54,563 - pyskl - INFO - Epoch [81][300/1281] lr: 1.113e-02, eta: 9:59:42, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2543, loss: 0.2543 +2025-06-24 22:17:43,592 - pyskl - INFO - Epoch [81][400/1281] lr: 1.111e-02, eta: 9:59:10, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 1.0000, loss_cls: 0.2833, loss: 0.2833 +2025-06-24 22:18:32,941 - pyskl - INFO - Epoch [81][500/1281] lr: 1.109e-02, eta: 9:58:37, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9994, loss_cls: 0.2673, loss: 0.2673 +2025-06-24 22:19:21,965 - pyskl - INFO - Epoch [81][600/1281] lr: 1.107e-02, eta: 9:58:04, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2902, loss: 0.2902 +2025-06-24 22:20:11,245 - pyskl - INFO - Epoch [81][700/1281] lr: 1.105e-02, eta: 9:57:32, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.2735, loss: 0.2735 +2025-06-24 22:21:00,424 - pyskl - INFO - Epoch [81][800/1281] lr: 1.103e-02, eta: 9:56:59, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2689, loss: 0.2689 +2025-06-24 22:21:49,541 - pyskl - INFO - Epoch [81][900/1281] lr: 1.101e-02, eta: 9:56:27, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9988, loss_cls: 0.3290, loss: 0.3290 +2025-06-24 22:22:38,592 - pyskl - INFO - Epoch [81][1000/1281] lr: 1.099e-02, eta: 9:55:54, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 0.3001, loss: 0.3001 +2025-06-24 22:23:05,403 - pyskl - INFO - Epoch [81][1100/1281] lr: 1.097e-02, eta: 9:55:02, time: 0.268, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9969, loss_cls: 0.3269, loss: 0.3269 +2025-06-24 22:23:56,313 - pyskl - INFO - Epoch [81][1200/1281] lr: 1.095e-02, eta: 9:54:31, time: 0.509, data_time: 0.001, memory: 4083, top1_acc: 0.9450, top5_acc: 1.0000, loss_cls: 0.3014, loss: 0.3014 +2025-06-24 22:24:18,110 - pyskl - INFO - Saving checkpoint at 81 epochs +2025-06-24 22:25:16,991 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:25:17,053 - pyskl - INFO - +top1_acc 0.9114 +top5_acc 0.9947 +2025-06-24 22:25:17,053 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:25:17,061 - pyskl - INFO - +mean_acc 0.8743 +2025-06-24 22:25:17,065 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_72.pth was removed +2025-06-24 22:25:17,239 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_81.pth. +2025-06-24 22:25:17,239 - pyskl - INFO - Best top1_acc is 0.9114 at 81 epoch. +2025-06-24 22:25:17,242 - pyskl - INFO - Epoch(val) [81][533] top1_acc: 0.9114, top5_acc: 0.9947, mean_class_accuracy: 0.8743 +2025-06-24 22:26:36,275 - pyskl - INFO - Epoch [82][100/1281] lr: 1.091e-02, eta: 9:53:23, time: 0.790, data_time: 0.188, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9994, loss_cls: 0.2397, loss: 0.2397 +2025-06-24 22:27:25,368 - pyskl - INFO - Epoch [82][200/1281] lr: 1.089e-02, eta: 9:52:50, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9988, loss_cls: 0.2914, loss: 0.2914 +2025-06-24 22:28:14,390 - pyskl - INFO - Epoch [82][300/1281] lr: 1.087e-02, eta: 9:52:17, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9994, loss_cls: 0.2791, loss: 0.2791 +2025-06-24 22:29:03,453 - pyskl - INFO - Epoch [82][400/1281] lr: 1.085e-02, eta: 9:51:44, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 0.2721, loss: 0.2721 +2025-06-24 22:29:52,638 - pyskl - INFO - Epoch [82][500/1281] lr: 1.083e-02, eta: 9:51:11, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 0.2596, loss: 0.2596 +2025-06-24 22:30:41,631 - pyskl - INFO - Epoch [82][600/1281] lr: 1.081e-02, eta: 9:50:38, time: 0.490, data_time: 0.001, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9994, loss_cls: 0.2722, loss: 0.2722 +2025-06-24 22:31:30,279 - pyskl - INFO - Epoch [82][700/1281] lr: 1.079e-02, eta: 9:50:04, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9994, loss_cls: 0.2838, loss: 0.2838 +2025-06-24 22:32:19,287 - pyskl - INFO - Epoch [82][800/1281] lr: 1.077e-02, eta: 9:49:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 0.9988, loss_cls: 0.2713, loss: 0.2713 +2025-06-24 22:33:08,473 - pyskl - INFO - Epoch [82][900/1281] lr: 1.075e-02, eta: 9:48:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 0.9994, loss_cls: 0.2582, loss: 0.2582 +2025-06-24 22:33:57,504 - pyskl - INFO - Epoch [82][1000/1281] lr: 1.073e-02, eta: 9:48:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.2801, loss: 0.2801 +2025-06-24 22:34:26,930 - pyskl - INFO - Epoch [82][1100/1281] lr: 1.071e-02, eta: 9:47:36, time: 0.294, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9988, loss_cls: 0.2927, loss: 0.2927 +2025-06-24 22:35:17,696 - pyskl - INFO - Epoch [82][1200/1281] lr: 1.069e-02, eta: 9:47:04, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 0.9981, loss_cls: 0.2973, loss: 0.2973 +2025-06-24 22:35:38,670 - pyskl - INFO - Saving checkpoint at 82 epochs +2025-06-24 22:36:37,002 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:36:37,070 - pyskl - INFO - +top1_acc 0.9153 +top5_acc 0.9934 +2025-06-24 22:36:37,070 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:36:37,079 - pyskl - INFO - +mean_acc 0.8916 +2025-06-24 22:36:37,084 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_81.pth was removed +2025-06-24 22:36:37,274 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_82.pth. +2025-06-24 22:36:37,275 - pyskl - INFO - Best top1_acc is 0.9153 at 82 epoch. +2025-06-24 22:36:37,278 - pyskl - INFO - Epoch(val) [82][533] top1_acc: 0.9153, top5_acc: 0.9934, mean_class_accuracy: 0.8916 +2025-06-24 22:37:56,747 - pyskl - INFO - Epoch [83][100/1281] lr: 1.065e-02, eta: 9:45:56, time: 0.795, data_time: 0.193, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9988, loss_cls: 0.2355, loss: 0.2355 +2025-06-24 22:38:45,728 - pyskl - INFO - Epoch [83][200/1281] lr: 1.063e-02, eta: 9:45:23, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 0.2340, loss: 0.2340 +2025-06-24 22:39:34,881 - pyskl - INFO - Epoch [83][300/1281] lr: 1.061e-02, eta: 9:44:49, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.2169, loss: 0.2169 +2025-06-24 22:40:24,069 - pyskl - INFO - Epoch [83][400/1281] lr: 1.059e-02, eta: 9:44:16, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9988, loss_cls: 0.2573, loss: 0.2573 +2025-06-24 22:41:13,584 - pyskl - INFO - Epoch [83][500/1281] lr: 1.057e-02, eta: 9:43:43, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 1.0000, loss_cls: 0.2927, loss: 0.2927 +2025-06-24 22:42:02,387 - pyskl - INFO - Epoch [83][600/1281] lr: 1.055e-02, eta: 9:43:10, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9981, loss_cls: 0.3016, loss: 0.3016 +2025-06-24 22:42:51,351 - pyskl - INFO - Epoch [83][700/1281] lr: 1.053e-02, eta: 9:42:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9988, loss_cls: 0.3150, loss: 0.3150 +2025-06-24 22:43:40,042 - pyskl - INFO - Epoch [83][800/1281] lr: 1.051e-02, eta: 9:42:02, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 1.0000, loss_cls: 0.3251, loss: 0.3251 +2025-06-24 22:44:29,091 - pyskl - INFO - Epoch [83][900/1281] lr: 1.049e-02, eta: 9:41:29, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9988, loss_cls: 0.2792, loss: 0.2792 +2025-06-24 22:45:18,235 - pyskl - INFO - Epoch [83][1000/1281] lr: 1.047e-02, eta: 9:40:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9988, loss_cls: 0.3138, loss: 0.3138 +2025-06-24 22:45:46,974 - pyskl - INFO - Epoch [83][1100/1281] lr: 1.045e-02, eta: 9:40:05, time: 0.287, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9994, loss_cls: 0.3047, loss: 0.3047 +2025-06-24 22:46:38,108 - pyskl - INFO - Epoch [83][1200/1281] lr: 1.043e-02, eta: 9:39:34, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9988, loss_cls: 0.2826, loss: 0.2826 +2025-06-24 22:46:59,419 - pyskl - INFO - Saving checkpoint at 83 epochs +2025-06-24 22:47:58,125 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:47:58,184 - pyskl - INFO - +top1_acc 0.9155 +top5_acc 0.9939 +2025-06-24 22:47:58,184 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:47:58,192 - pyskl - INFO - +mean_acc 0.8816 +2025-06-24 22:47:58,196 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_82.pth was removed +2025-06-24 22:47:58,375 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_83.pth. +2025-06-24 22:47:58,375 - pyskl - INFO - Best top1_acc is 0.9155 at 83 epoch. +2025-06-24 22:47:58,381 - pyskl - INFO - Epoch(val) [83][533] top1_acc: 0.9155, top5_acc: 0.9939, mean_class_accuracy: 0.8816 +2025-06-24 22:49:17,060 - pyskl - INFO - Epoch [84][100/1281] lr: 1.040e-02, eta: 9:38:25, time: 0.787, data_time: 0.190, memory: 4083, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 0.2511, loss: 0.2511 +2025-06-24 22:50:06,267 - pyskl - INFO - Epoch [84][200/1281] lr: 1.038e-02, eta: 9:37:51, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 0.2413, loss: 0.2413 +2025-06-24 22:50:55,202 - pyskl - INFO - Epoch [84][300/1281] lr: 1.036e-02, eta: 9:37:17, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9994, loss_cls: 0.2502, loss: 0.2502 +2025-06-24 22:51:44,485 - pyskl - INFO - Epoch [84][400/1281] lr: 1.034e-02, eta: 9:36:44, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 0.9988, loss_cls: 0.2016, loss: 0.2016 +2025-06-24 22:52:33,279 - pyskl - INFO - Epoch [84][500/1281] lr: 1.031e-02, eta: 9:36:10, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.2727, loss: 0.2727 +2025-06-24 22:53:22,645 - pyskl - INFO - Epoch [84][600/1281] lr: 1.029e-02, eta: 9:35:37, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9975, loss_cls: 0.3267, loss: 0.3267 +2025-06-24 22:54:11,466 - pyskl - INFO - Epoch [84][700/1281] lr: 1.027e-02, eta: 9:35:03, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 1.0000, loss_cls: 0.2893, loss: 0.2893 +2025-06-24 22:55:00,501 - pyskl - INFO - Epoch [84][800/1281] lr: 1.025e-02, eta: 9:34:29, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2629, loss: 0.2629 +2025-06-24 22:55:49,564 - pyskl - INFO - Epoch [84][900/1281] lr: 1.023e-02, eta: 9:33:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 0.2635, loss: 0.2635 +2025-06-24 22:56:38,411 - pyskl - INFO - Epoch [84][1000/1281] lr: 1.021e-02, eta: 9:33:21, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9994, loss_cls: 0.2704, loss: 0.2704 +2025-06-24 22:57:07,726 - pyskl - INFO - Epoch [84][1100/1281] lr: 1.019e-02, eta: 9:32:32, time: 0.293, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9994, loss_cls: 0.3179, loss: 0.3179 +2025-06-24 22:57:58,522 - pyskl - INFO - Epoch [84][1200/1281] lr: 1.017e-02, eta: 9:31:59, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9994, loss_cls: 0.3042, loss: 0.3042 +2025-06-24 22:58:19,660 - pyskl - INFO - Saving checkpoint at 84 epochs +2025-06-24 22:59:18,140 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:59:18,200 - pyskl - INFO - +top1_acc 0.8958 +top5_acc 0.9945 +2025-06-24 22:59:18,201 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:59:18,211 - pyskl - INFO - +mean_acc 0.8604 +2025-06-24 22:59:18,214 - pyskl - INFO - Epoch(val) [84][533] top1_acc: 0.8958, top5_acc: 0.9945, mean_class_accuracy: 0.8604 +2025-06-24 23:00:36,459 - pyskl - INFO - Epoch [85][100/1281] lr: 1.014e-02, eta: 9:30:50, time: 0.782, data_time: 0.190, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9981, loss_cls: 0.2654, loss: 0.2654 +2025-06-24 23:01:25,518 - pyskl - INFO - Epoch [85][200/1281] lr: 1.012e-02, eta: 9:30:16, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2126, loss: 0.2126 +2025-06-24 23:02:15,032 - pyskl - INFO - Epoch [85][300/1281] lr: 1.010e-02, eta: 9:29:42, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2506, loss: 0.2506 +2025-06-24 23:03:04,236 - pyskl - INFO - Epoch [85][400/1281] lr: 1.008e-02, eta: 9:29:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9994, loss_cls: 0.2711, loss: 0.2711 +2025-06-24 23:03:53,196 - pyskl - INFO - Epoch [85][500/1281] lr: 1.006e-02, eta: 9:28:34, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 0.2531, loss: 0.2531 +2025-06-24 23:04:42,510 - pyskl - INFO - Epoch [85][600/1281] lr: 1.004e-02, eta: 9:28:00, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9988, loss_cls: 0.2941, loss: 0.2941 +2025-06-24 23:05:31,248 - pyskl - INFO - Epoch [85][700/1281] lr: 1.002e-02, eta: 9:27:26, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2546, loss: 0.2546 +2025-06-24 23:06:20,054 - pyskl - INFO - Epoch [85][800/1281] lr: 9.998e-03, eta: 9:26:52, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 0.2488, loss: 0.2488 +2025-06-24 23:07:09,127 - pyskl - INFO - Epoch [85][900/1281] lr: 9.978e-03, eta: 9:26:18, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 1.0000, loss_cls: 0.3089, loss: 0.3089 +2025-06-24 23:07:58,254 - pyskl - INFO - Epoch [85][1000/1281] lr: 9.958e-03, eta: 9:25:44, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 1.0000, loss_cls: 0.2910, loss: 0.2910 +2025-06-24 23:08:28,088 - pyskl - INFO - Epoch [85][1100/1281] lr: 9.937e-03, eta: 9:24:55, time: 0.298, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 0.3009, loss: 0.3009 +2025-06-24 23:09:19,090 - pyskl - INFO - Epoch [85][1200/1281] lr: 9.917e-03, eta: 9:24:22, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9988, loss_cls: 0.2940, loss: 0.2940 +2025-06-24 23:09:39,970 - pyskl - INFO - Saving checkpoint at 85 epochs +2025-06-24 23:10:38,605 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:10:38,660 - pyskl - INFO - +top1_acc 0.8951 +top5_acc 0.9927 +2025-06-24 23:10:38,660 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:10:38,668 - pyskl - INFO - +mean_acc 0.8489 +2025-06-24 23:10:38,671 - pyskl - INFO - Epoch(val) [85][533] top1_acc: 0.8951, top5_acc: 0.9927, mean_class_accuracy: 0.8489 +2025-06-24 23:11:57,791 - pyskl - INFO - Epoch [86][100/1281] lr: 9.881e-03, eta: 9:23:13, time: 0.791, data_time: 0.198, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9994, loss_cls: 0.2643, loss: 0.2643 +2025-06-24 23:12:46,898 - pyskl - INFO - Epoch [86][200/1281] lr: 9.861e-03, eta: 9:22:39, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9994, loss_cls: 0.2236, loss: 0.2236 +2025-06-24 23:13:35,985 - pyskl - INFO - Epoch [86][300/1281] lr: 9.841e-03, eta: 9:22:04, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9994, loss_cls: 0.2489, loss: 0.2489 +2025-06-24 23:14:24,933 - pyskl - INFO - Epoch [86][400/1281] lr: 9.821e-03, eta: 9:21:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.2239, loss: 0.2239 +2025-06-24 23:15:14,027 - pyskl - INFO - Epoch [86][500/1281] lr: 9.801e-03, eta: 9:20:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2097, loss: 0.2097 +2025-06-24 23:16:02,980 - pyskl - INFO - Epoch [86][600/1281] lr: 9.781e-03, eta: 9:20:21, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2320, loss: 0.2320 +2025-06-24 23:16:51,700 - pyskl - INFO - Epoch [86][700/1281] lr: 9.762e-03, eta: 9:19:47, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 0.2578, loss: 0.2578 +2025-06-24 23:17:40,638 - pyskl - INFO - Epoch [86][800/1281] lr: 9.742e-03, eta: 9:19:12, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 0.2487, loss: 0.2487 +2025-06-24 23:18:29,563 - pyskl - INFO - Epoch [86][900/1281] lr: 9.722e-03, eta: 9:18:38, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9994, loss_cls: 0.2534, loss: 0.2534 +2025-06-24 23:19:18,596 - pyskl - INFO - Epoch [86][1000/1281] lr: 9.702e-03, eta: 9:18:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 0.2556, loss: 0.2556 +2025-06-24 23:19:48,242 - pyskl - INFO - Epoch [86][1100/1281] lr: 9.682e-03, eta: 9:17:14, time: 0.296, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9981, loss_cls: 0.2989, loss: 0.2989 +2025-06-24 23:20:39,215 - pyskl - INFO - Epoch [86][1200/1281] lr: 9.662e-03, eta: 9:16:41, time: 0.510, data_time: 0.001, memory: 4083, top1_acc: 0.9469, top5_acc: 0.9981, loss_cls: 0.2983, loss: 0.2983 +2025-06-24 23:20:59,907 - pyskl - INFO - Saving checkpoint at 86 epochs +2025-06-24 23:21:59,155 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:21:59,213 - pyskl - INFO - +top1_acc 0.9040 +top5_acc 0.9947 +2025-06-24 23:21:59,213 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:21:59,221 - pyskl - INFO - +mean_acc 0.8674 +2025-06-24 23:21:59,223 - pyskl - INFO - Epoch(val) [86][533] top1_acc: 0.9040, top5_acc: 0.9947, mean_class_accuracy: 0.8674 +2025-06-24 23:23:18,873 - pyskl - INFO - Epoch [87][100/1281] lr: 9.626e-03, eta: 9:15:32, time: 0.796, data_time: 0.189, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2363, loss: 0.2363 +2025-06-24 23:24:08,067 - pyskl - INFO - Epoch [87][200/1281] lr: 9.606e-03, eta: 9:14:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 0.9994, loss_cls: 0.1934, loss: 0.1934 +2025-06-24 23:24:57,438 - pyskl - INFO - Epoch [87][300/1281] lr: 9.586e-03, eta: 9:14:23, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 0.9994, loss_cls: 0.2165, loss: 0.2165 +2025-06-24 23:25:46,808 - pyskl - INFO - Epoch [87][400/1281] lr: 9.566e-03, eta: 9:13:49, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 0.9994, loss_cls: 0.1890, loss: 0.1890 +2025-06-24 23:26:36,013 - pyskl - INFO - Epoch [87][500/1281] lr: 9.546e-03, eta: 9:13:15, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2164, loss: 0.2164 +2025-06-24 23:27:25,087 - pyskl - INFO - Epoch [87][600/1281] lr: 9.527e-03, eta: 9:12:40, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 0.2309, loss: 0.2309 +2025-06-24 23:28:14,167 - pyskl - INFO - Epoch [87][700/1281] lr: 9.507e-03, eta: 9:12:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9988, loss_cls: 0.2523, loss: 0.2523 +2025-06-24 23:29:03,048 - pyskl - INFO - Epoch [87][800/1281] lr: 9.487e-03, eta: 9:11:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2747, loss: 0.2747 +2025-06-24 23:29:52,128 - pyskl - INFO - Epoch [87][900/1281] lr: 9.467e-03, eta: 9:10:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9988, loss_cls: 0.2682, loss: 0.2682 +2025-06-24 23:30:41,388 - pyskl - INFO - Epoch [87][1000/1281] lr: 9.447e-03, eta: 9:10:21, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 0.2635, loss: 0.2635 +2025-06-24 23:31:09,527 - pyskl - INFO - Epoch [87][1100/1281] lr: 9.427e-03, eta: 9:09:31, time: 0.281, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 0.2679, loss: 0.2679 +2025-06-24 23:32:00,316 - pyskl - INFO - Epoch [87][1200/1281] lr: 9.408e-03, eta: 9:08:58, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 0.9994, loss_cls: 0.2723, loss: 0.2723 +2025-06-24 23:32:22,057 - pyskl - INFO - Saving checkpoint at 87 epochs +2025-06-24 23:33:20,573 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:33:20,631 - pyskl - INFO - +top1_acc 0.9201 +top5_acc 0.9951 +2025-06-24 23:33:20,631 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:33:20,639 - pyskl - INFO - +mean_acc 0.8835 +2025-06-24 23:33:20,643 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_83.pth was removed +2025-06-24 23:33:20,827 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_87.pth. +2025-06-24 23:33:20,828 - pyskl - INFO - Best top1_acc is 0.9201 at 87 epoch. +2025-06-24 23:33:20,831 - pyskl - INFO - Epoch(val) [87][533] top1_acc: 0.9201, top5_acc: 0.9951, mean_class_accuracy: 0.8835 +2025-06-24 23:34:40,702 - pyskl - INFO - Epoch [88][100/1281] lr: 9.372e-03, eta: 9:07:48, time: 0.799, data_time: 0.193, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 0.2677, loss: 0.2677 +2025-06-24 23:35:29,492 - pyskl - INFO - Epoch [88][200/1281] lr: 9.352e-03, eta: 9:07:13, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.2217, loss: 0.2217 +2025-06-24 23:36:18,304 - pyskl - INFO - Epoch [88][300/1281] lr: 9.332e-03, eta: 9:06:38, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 0.2495, loss: 0.2495 +2025-06-24 23:37:06,921 - pyskl - INFO - Epoch [88][400/1281] lr: 9.312e-03, eta: 9:06:03, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 0.2327, loss: 0.2327 +2025-06-24 23:37:56,567 - pyskl - INFO - Epoch [88][500/1281] lr: 9.293e-03, eta: 9:05:29, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 0.9994, loss_cls: 0.2377, loss: 0.2377 +2025-06-24 23:38:45,388 - pyskl - INFO - Epoch [88][600/1281] lr: 9.273e-03, eta: 9:04:54, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9994, loss_cls: 0.2394, loss: 0.2394 +2025-06-24 23:39:34,673 - pyskl - INFO - Epoch [88][700/1281] lr: 9.253e-03, eta: 9:04:19, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2460, loss: 0.2460 +2025-06-24 23:40:23,640 - pyskl - INFO - Epoch [88][800/1281] lr: 9.233e-03, eta: 9:03:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2394, loss: 0.2394 +2025-06-24 23:41:12,438 - pyskl - INFO - Epoch [88][900/1281] lr: 9.214e-03, eta: 9:03:09, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9988, loss_cls: 0.2604, loss: 0.2604 +2025-06-24 23:42:01,066 - pyskl - INFO - Epoch [88][1000/1281] lr: 9.194e-03, eta: 9:02:33, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 0.2638, loss: 0.2638 +2025-06-24 23:42:29,002 - pyskl - INFO - Epoch [88][1100/1281] lr: 9.174e-03, eta: 9:01:43, time: 0.279, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 1.0000, loss_cls: 0.2662, loss: 0.2662 +2025-06-24 23:43:20,067 - pyskl - INFO - Epoch [88][1200/1281] lr: 9.155e-03, eta: 9:01:10, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9988, loss_cls: 0.2712, loss: 0.2712 +2025-06-24 23:43:42,882 - pyskl - INFO - Saving checkpoint at 88 epochs +2025-06-24 23:44:41,375 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:44:41,431 - pyskl - INFO - +top1_acc 0.9123 +top5_acc 0.9933 +2025-06-24 23:44:41,431 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:44:41,439 - pyskl - INFO - +mean_acc 0.8822 +2025-06-24 23:44:41,441 - pyskl - INFO - Epoch(val) [88][533] top1_acc: 0.9123, top5_acc: 0.9933, mean_class_accuracy: 0.8822 +2025-06-24 23:46:00,713 - pyskl - INFO - Epoch [89][100/1281] lr: 9.119e-03, eta: 9:00:00, time: 0.793, data_time: 0.191, memory: 4083, top1_acc: 0.9756, top5_acc: 0.9994, loss_cls: 0.1849, loss: 0.1849 +2025-06-24 23:46:49,810 - pyskl - INFO - Epoch [89][200/1281] lr: 9.099e-03, eta: 8:59:25, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9675, top5_acc: 0.9994, loss_cls: 0.1963, loss: 0.1963 +2025-06-24 23:47:38,619 - pyskl - INFO - Epoch [89][300/1281] lr: 9.080e-03, eta: 8:58:49, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 0.2145, loss: 0.2145 +2025-06-24 23:48:27,705 - pyskl - INFO - Epoch [89][400/1281] lr: 9.060e-03, eta: 8:58:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1692, loss: 0.1692 +2025-06-24 23:49:16,273 - pyskl - INFO - Epoch [89][500/1281] lr: 9.040e-03, eta: 8:57:39, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.1942, loss: 0.1942 +2025-06-24 23:50:05,153 - pyskl - INFO - Epoch [89][600/1281] lr: 9.021e-03, eta: 8:57:03, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9988, loss_cls: 0.2382, loss: 0.2382 +2025-06-24 23:50:54,019 - pyskl - INFO - Epoch [89][700/1281] lr: 9.001e-03, eta: 8:56:28, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2258, loss: 0.2258 +2025-06-24 23:51:43,115 - pyskl - INFO - Epoch [89][800/1281] lr: 8.982e-03, eta: 8:55:53, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 0.2681, loss: 0.2681 +2025-06-24 23:52:32,094 - pyskl - INFO - Epoch [89][900/1281] lr: 8.962e-03, eta: 8:55:17, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.2346, loss: 0.2346 +2025-06-24 23:53:21,010 - pyskl - INFO - Epoch [89][1000/1281] lr: 8.942e-03, eta: 8:54:42, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9994, loss_cls: 0.2757, loss: 0.2757 +2025-06-24 23:53:49,018 - pyskl - INFO - Epoch [89][1100/1281] lr: 8.923e-03, eta: 8:53:52, time: 0.280, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 0.2438, loss: 0.2438 +2025-06-24 23:54:39,853 - pyskl - INFO - Epoch [89][1200/1281] lr: 8.903e-03, eta: 8:53:18, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 0.2588, loss: 0.2588 +2025-06-24 23:55:01,504 - pyskl - INFO - Saving checkpoint at 89 epochs +2025-06-24 23:56:00,092 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:56:00,153 - pyskl - INFO - +top1_acc 0.8994 +top5_acc 0.9916 +2025-06-24 23:56:00,153 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:56:00,162 - pyskl - INFO - +mean_acc 0.8742 +2025-06-24 23:56:00,165 - pyskl - INFO - Epoch(val) [89][533] top1_acc: 0.8994, top5_acc: 0.9916, mean_class_accuracy: 0.8742 +2025-06-24 23:57:20,015 - pyskl - INFO - Epoch [90][100/1281] lr: 8.868e-03, eta: 8:52:08, time: 0.798, data_time: 0.192, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9981, loss_cls: 0.2756, loss: 0.2756 +2025-06-24 23:58:09,154 - pyskl - INFO - Epoch [90][200/1281] lr: 8.848e-03, eta: 8:51:33, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.2308, loss: 0.2308 +2025-06-24 23:58:58,802 - pyskl - INFO - Epoch [90][300/1281] lr: 8.829e-03, eta: 8:50:58, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1875, loss: 0.1875 +2025-06-24 23:59:47,776 - pyskl - INFO - Epoch [90][400/1281] lr: 8.809e-03, eta: 8:50:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 0.2292, loss: 0.2292 +2025-06-25 00:00:36,778 - pyskl - INFO - Epoch [90][500/1281] lr: 8.790e-03, eta: 8:49:47, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 0.2595, loss: 0.2595 +2025-06-25 00:01:26,263 - pyskl - INFO - Epoch [90][600/1281] lr: 8.770e-03, eta: 8:49:12, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9988, loss_cls: 0.3198, loss: 0.3198 +2025-06-25 00:02:15,489 - pyskl - INFO - Epoch [90][700/1281] lr: 8.751e-03, eta: 8:48:36, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2253, loss: 0.2253 +2025-06-25 00:03:04,572 - pyskl - INFO - Epoch [90][800/1281] lr: 8.731e-03, eta: 8:48:01, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 0.9994, loss_cls: 0.2553, loss: 0.2553 +2025-06-25 00:03:53,573 - pyskl - INFO - Epoch [90][900/1281] lr: 8.712e-03, eta: 8:47:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9988, loss_cls: 0.2911, loss: 0.2911 +2025-06-25 00:04:42,470 - pyskl - INFO - Epoch [90][1000/1281] lr: 8.692e-03, eta: 8:46:50, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 0.9988, loss_cls: 0.2408, loss: 0.2408 +2025-06-25 00:05:09,812 - pyskl - INFO - Epoch [90][1100/1281] lr: 8.673e-03, eta: 8:46:00, time: 0.273, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9994, loss_cls: 0.2514, loss: 0.2514 +2025-06-25 00:06:00,683 - pyskl - INFO - Epoch [90][1200/1281] lr: 8.653e-03, eta: 8:45:25, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2402, loss: 0.2402 +2025-06-25 00:06:22,319 - pyskl - INFO - Saving checkpoint at 90 epochs +2025-06-25 00:07:20,460 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:07:20,515 - pyskl - INFO - +top1_acc 0.8987 +top5_acc 0.9939 +2025-06-25 00:07:20,515 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:07:20,522 - pyskl - INFO - +mean_acc 0.8719 +2025-06-25 00:07:20,524 - pyskl - INFO - Epoch(val) [90][533] top1_acc: 0.8987, top5_acc: 0.9939, mean_class_accuracy: 0.8719 +2025-06-25 00:08:38,854 - pyskl - INFO - Epoch [91][100/1281] lr: 8.618e-03, eta: 8:44:14, time: 0.783, data_time: 0.190, memory: 4083, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 0.2157, loss: 0.2157 +2025-06-25 00:09:27,804 - pyskl - INFO - Epoch [91][200/1281] lr: 8.599e-03, eta: 8:43:38, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 0.2201, loss: 0.2201 +2025-06-25 00:10:16,825 - pyskl - INFO - Epoch [91][300/1281] lr: 8.579e-03, eta: 8:43:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2352, loss: 0.2352 +2025-06-25 00:11:05,643 - pyskl - INFO - Epoch [91][400/1281] lr: 8.560e-03, eta: 8:42:27, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 0.9994, loss_cls: 0.2147, loss: 0.2147 +2025-06-25 00:11:54,720 - pyskl - INFO - Epoch [91][500/1281] lr: 8.540e-03, eta: 8:41:51, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.2445, loss: 0.2445 +2025-06-25 00:12:43,166 - pyskl - INFO - Epoch [91][600/1281] lr: 8.521e-03, eta: 8:41:15, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 0.2311, loss: 0.2311 +2025-06-25 00:13:31,768 - pyskl - INFO - Epoch [91][700/1281] lr: 8.502e-03, eta: 8:40:39, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9994, loss_cls: 0.2355, loss: 0.2355 +2025-06-25 00:14:20,598 - pyskl - INFO - Epoch [91][800/1281] lr: 8.482e-03, eta: 8:40:03, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 0.2284, loss: 0.2284 +2025-06-25 00:15:09,632 - pyskl - INFO - Epoch [91][900/1281] lr: 8.463e-03, eta: 8:39:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.2153, loss: 0.2153 +2025-06-25 00:15:58,619 - pyskl - INFO - Epoch [91][1000/1281] lr: 8.444e-03, eta: 8:38:51, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9988, loss_cls: 0.2319, loss: 0.2319 +2025-06-25 00:16:28,874 - pyskl - INFO - Epoch [91][1100/1281] lr: 8.424e-03, eta: 8:38:03, time: 0.303, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9988, loss_cls: 0.2726, loss: 0.2726 +2025-06-25 00:17:19,824 - pyskl - INFO - Epoch [91][1200/1281] lr: 8.405e-03, eta: 8:37:29, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 0.2483, loss: 0.2483 +2025-06-25 00:17:41,073 - pyskl - INFO - Saving checkpoint at 91 epochs +2025-06-25 00:18:39,870 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:18:39,928 - pyskl - INFO - +top1_acc 0.9020 +top5_acc 0.9931 +2025-06-25 00:18:39,929 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:18:39,940 - pyskl - INFO - +mean_acc 0.8737 +2025-06-25 00:18:39,943 - pyskl - INFO - Epoch(val) [91][533] top1_acc: 0.9020, top5_acc: 0.9931, mean_class_accuracy: 0.8737 +2025-06-25 00:20:00,964 - pyskl - INFO - Epoch [92][100/1281] lr: 8.370e-03, eta: 8:36:19, time: 0.810, data_time: 0.196, memory: 4083, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 0.2402, loss: 0.2402 +2025-06-25 00:20:50,058 - pyskl - INFO - Epoch [92][200/1281] lr: 8.351e-03, eta: 8:35:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2126, loss: 0.2126 +2025-06-25 00:21:39,316 - pyskl - INFO - Epoch [92][300/1281] lr: 8.332e-03, eta: 8:35:07, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 0.2185, loss: 0.2185 +2025-06-25 00:22:28,337 - pyskl - INFO - Epoch [92][400/1281] lr: 8.312e-03, eta: 8:34:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1926, loss: 0.1926 +2025-06-25 00:23:17,026 - pyskl - INFO - Epoch [92][500/1281] lr: 8.293e-03, eta: 8:33:55, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2312, loss: 0.2312 +2025-06-25 00:24:06,301 - pyskl - INFO - Epoch [92][600/1281] lr: 8.274e-03, eta: 8:33:19, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1924, loss: 0.1924 +2025-06-25 00:24:55,103 - pyskl - INFO - Epoch [92][700/1281] lr: 8.255e-03, eta: 8:32:43, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 0.9994, loss_cls: 0.1723, loss: 0.1723 +2025-06-25 00:25:44,147 - pyskl - INFO - Epoch [92][800/1281] lr: 8.235e-03, eta: 8:32:07, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 0.2073, loss: 0.2073 +2025-06-25 00:26:32,394 - pyskl - INFO - Epoch [92][900/1281] lr: 8.216e-03, eta: 8:31:31, time: 0.482, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 0.2397, loss: 0.2397 +2025-06-25 00:27:21,001 - pyskl - INFO - Epoch [92][1000/1281] lr: 8.197e-03, eta: 8:30:54, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.2003, loss: 0.2003 +2025-06-25 00:27:48,357 - pyskl - INFO - Epoch [92][1100/1281] lr: 8.178e-03, eta: 8:30:04, time: 0.274, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 0.1593, loss: 0.1593 +2025-06-25 00:28:39,227 - pyskl - INFO - Epoch [92][1200/1281] lr: 8.159e-03, eta: 8:29:29, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 0.9994, loss_cls: 0.2589, loss: 0.2589 +2025-06-25 00:29:01,391 - pyskl - INFO - Saving checkpoint at 92 epochs +2025-06-25 00:29:59,991 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:30:00,061 - pyskl - INFO - +top1_acc 0.9060 +top5_acc 0.9924 +2025-06-25 00:30:00,061 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:30:00,069 - pyskl - INFO - +mean_acc 0.8796 +2025-06-25 00:30:00,072 - pyskl - INFO - Epoch(val) [92][533] top1_acc: 0.9060, top5_acc: 0.9924, mean_class_accuracy: 0.8796 +2025-06-25 00:31:20,489 - pyskl - INFO - Epoch [93][100/1281] lr: 8.124e-03, eta: 8:28:19, time: 0.804, data_time: 0.192, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1778, loss: 0.1778 +2025-06-25 00:32:09,356 - pyskl - INFO - Epoch [93][200/1281] lr: 8.105e-03, eta: 8:27:43, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 0.9994, loss_cls: 0.1855, loss: 0.1855 +2025-06-25 00:32:58,701 - pyskl - INFO - Epoch [93][300/1281] lr: 8.086e-03, eta: 8:27:07, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 0.9994, loss_cls: 0.1958, loss: 0.1958 +2025-06-25 00:33:47,814 - pyskl - INFO - Epoch [93][400/1281] lr: 8.067e-03, eta: 8:26:31, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.2112, loss: 0.2112 +2025-06-25 00:34:36,350 - pyskl - INFO - Epoch [93][500/1281] lr: 8.047e-03, eta: 8:25:54, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1922, loss: 0.1922 +2025-06-25 00:35:25,051 - pyskl - INFO - Epoch [93][600/1281] lr: 8.028e-03, eta: 8:25:18, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1947, loss: 0.1947 +2025-06-25 00:36:13,721 - pyskl - INFO - Epoch [93][700/1281] lr: 8.009e-03, eta: 8:24:41, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1860, loss: 0.1860 +2025-06-25 00:37:02,652 - pyskl - INFO - Epoch [93][800/1281] lr: 7.990e-03, eta: 8:24:05, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 0.9994, loss_cls: 0.2005, loss: 0.2005 +2025-06-25 00:37:51,519 - pyskl - INFO - Epoch [93][900/1281] lr: 7.971e-03, eta: 8:23:28, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2180, loss: 0.2180 +2025-06-25 00:38:40,272 - pyskl - INFO - Epoch [93][1000/1281] lr: 7.952e-03, eta: 8:22:52, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 0.2166, loss: 0.2166 +2025-06-25 00:39:07,359 - pyskl - INFO - Epoch [93][1100/1281] lr: 7.933e-03, eta: 8:22:02, time: 0.271, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1897, loss: 0.1897 +2025-06-25 00:39:58,188 - pyskl - INFO - Epoch [93][1200/1281] lr: 7.914e-03, eta: 8:21:27, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 0.2134, loss: 0.2134 +2025-06-25 00:40:20,003 - pyskl - INFO - Saving checkpoint at 93 epochs +2025-06-25 00:41:18,265 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:41:18,327 - pyskl - INFO - +top1_acc 0.8983 +top5_acc 0.9906 +2025-06-25 00:41:18,327 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:41:18,334 - pyskl - INFO - +mean_acc 0.8647 +2025-06-25 00:41:18,336 - pyskl - INFO - Epoch(val) [93][533] top1_acc: 0.8983, top5_acc: 0.9906, mean_class_accuracy: 0.8647 +2025-06-25 00:42:38,663 - pyskl - INFO - Epoch [94][100/1281] lr: 7.880e-03, eta: 8:20:16, time: 0.803, data_time: 0.195, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.2076, loss: 0.2076 +2025-06-25 00:43:27,757 - pyskl - INFO - Epoch [94][200/1281] lr: 7.861e-03, eta: 8:19:40, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2252, loss: 0.2252 +2025-06-25 00:44:16,572 - pyskl - INFO - Epoch [94][300/1281] lr: 7.842e-03, eta: 8:19:03, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.2375, loss: 0.2375 +2025-06-25 00:45:05,722 - pyskl - INFO - Epoch [94][400/1281] lr: 7.823e-03, eta: 8:18:27, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1794, loss: 0.1794 +2025-06-25 00:45:54,926 - pyskl - INFO - Epoch [94][500/1281] lr: 7.804e-03, eta: 8:17:51, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1550, loss: 0.1550 +2025-06-25 00:46:44,177 - pyskl - INFO - Epoch [94][600/1281] lr: 7.785e-03, eta: 8:17:14, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.1981, loss: 0.1981 +2025-06-25 00:47:33,338 - pyskl - INFO - Epoch [94][700/1281] lr: 7.766e-03, eta: 8:16:38, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9988, loss_cls: 0.2521, loss: 0.2521 +2025-06-25 00:48:22,094 - pyskl - INFO - Epoch [94][800/1281] lr: 7.747e-03, eta: 8:16:01, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 0.2251, loss: 0.2251 +2025-06-25 00:49:11,283 - pyskl - INFO - Epoch [94][900/1281] lr: 7.728e-03, eta: 8:15:25, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1946, loss: 0.1946 +2025-06-25 00:50:00,080 - pyskl - INFO - Epoch [94][1000/1281] lr: 7.709e-03, eta: 8:14:48, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1660, loss: 0.1660 +2025-06-25 00:50:28,449 - pyskl - INFO - Epoch [94][1100/1281] lr: 7.690e-03, eta: 8:13:59, time: 0.284, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.2029, loss: 0.2029 +2025-06-25 00:51:19,171 - pyskl - INFO - Epoch [94][1200/1281] lr: 7.672e-03, eta: 8:13:24, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2311, loss: 0.2311 +2025-06-25 00:51:40,741 - pyskl - INFO - Saving checkpoint at 94 epochs +2025-06-25 00:52:38,319 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:52:38,374 - pyskl - INFO - +top1_acc 0.9193 +top5_acc 0.9951 +2025-06-25 00:52:38,374 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:52:38,381 - pyskl - INFO - +mean_acc 0.8969 +2025-06-25 00:52:38,383 - pyskl - INFO - Epoch(val) [94][533] top1_acc: 0.9193, top5_acc: 0.9951, mean_class_accuracy: 0.8969 +2025-06-25 00:53:57,603 - pyskl - INFO - Epoch [95][100/1281] lr: 7.637e-03, eta: 8:12:12, time: 0.792, data_time: 0.187, memory: 4083, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 0.2151, loss: 0.2151 +2025-06-25 00:54:46,789 - pyskl - INFO - Epoch [95][200/1281] lr: 7.619e-03, eta: 8:11:35, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 0.9988, loss_cls: 0.1964, loss: 0.1964 +2025-06-25 00:55:36,020 - pyskl - INFO - Epoch [95][300/1281] lr: 7.600e-03, eta: 8:10:59, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1685, loss: 0.1685 +2025-06-25 00:56:25,336 - pyskl - INFO - Epoch [95][400/1281] lr: 7.581e-03, eta: 8:10:22, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1463, loss: 0.1463 +2025-06-25 00:57:14,469 - pyskl - INFO - Epoch [95][500/1281] lr: 7.562e-03, eta: 8:09:46, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 0.9994, loss_cls: 0.1690, loss: 0.1690 +2025-06-25 00:58:03,535 - pyskl - INFO - Epoch [95][600/1281] lr: 7.543e-03, eta: 8:09:09, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9994, loss_cls: 0.2337, loss: 0.2337 +2025-06-25 00:58:52,631 - pyskl - INFO - Epoch [95][700/1281] lr: 7.525e-03, eta: 8:08:32, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.2009, loss: 0.2009 +2025-06-25 00:59:41,415 - pyskl - INFO - Epoch [95][800/1281] lr: 7.506e-03, eta: 8:07:55, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9988, loss_cls: 0.2179, loss: 0.2179 +2025-06-25 01:00:30,296 - pyskl - INFO - Epoch [95][900/1281] lr: 7.487e-03, eta: 8:07:19, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2153, loss: 0.2153 +2025-06-25 01:01:19,160 - pyskl - INFO - Epoch [95][1000/1281] lr: 7.468e-03, eta: 8:06:42, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1955, loss: 0.1955 +2025-06-25 01:01:49,240 - pyskl - INFO - Epoch [95][1100/1281] lr: 7.450e-03, eta: 8:05:54, time: 0.301, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1767, loss: 0.1767 +2025-06-25 01:02:40,105 - pyskl - INFO - Epoch [95][1200/1281] lr: 7.431e-03, eta: 8:05:18, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2408, loss: 0.2408 +2025-06-25 01:03:01,439 - pyskl - INFO - Saving checkpoint at 95 epochs +2025-06-25 01:04:00,554 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:04:00,623 - pyskl - INFO - +top1_acc 0.9200 +top5_acc 0.9950 +2025-06-25 01:04:00,623 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:04:00,631 - pyskl - INFO - +mean_acc 0.8859 +2025-06-25 01:04:00,633 - pyskl - INFO - Epoch(val) [95][533] top1_acc: 0.9200, top5_acc: 0.9950, mean_class_accuracy: 0.8859 +2025-06-25 01:05:21,115 - pyskl - INFO - Epoch [96][100/1281] lr: 7.397e-03, eta: 8:04:07, time: 0.805, data_time: 0.187, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1668, loss: 0.1668 +2025-06-25 01:06:09,929 - pyskl - INFO - Epoch [96][200/1281] lr: 7.379e-03, eta: 8:03:30, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 0.9994, loss_cls: 0.1861, loss: 0.1861 +2025-06-25 01:06:58,716 - pyskl - INFO - Epoch [96][300/1281] lr: 7.360e-03, eta: 8:02:53, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 0.9994, loss_cls: 0.1952, loss: 0.1952 +2025-06-25 01:07:47,581 - pyskl - INFO - Epoch [96][400/1281] lr: 7.341e-03, eta: 8:02:16, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 0.9994, loss_cls: 0.1860, loss: 0.1860 +2025-06-25 01:08:36,431 - pyskl - INFO - Epoch [96][500/1281] lr: 7.323e-03, eta: 8:01:39, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1855, loss: 0.1855 +2025-06-25 01:09:25,443 - pyskl - INFO - Epoch [96][600/1281] lr: 7.304e-03, eta: 8:01:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 0.9994, loss_cls: 0.1872, loss: 0.1872 +2025-06-25 01:10:14,153 - pyskl - INFO - Epoch [96][700/1281] lr: 7.286e-03, eta: 8:00:25, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1779, loss: 0.1779 +2025-06-25 01:11:03,089 - pyskl - INFO - Epoch [96][800/1281] lr: 7.267e-03, eta: 7:59:48, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.2057, loss: 0.2057 +2025-06-25 01:11:52,061 - pyskl - INFO - Epoch [96][900/1281] lr: 7.249e-03, eta: 7:59:11, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 0.9988, loss_cls: 0.2154, loss: 0.2154 +2025-06-25 01:12:40,855 - pyskl - INFO - Epoch [96][1000/1281] lr: 7.230e-03, eta: 7:58:34, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 0.9988, loss_cls: 0.2209, loss: 0.2209 +2025-06-25 01:13:10,008 - pyskl - INFO - Epoch [96][1100/1281] lr: 7.211e-03, eta: 7:57:46, time: 0.292, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 0.9994, loss_cls: 0.1951, loss: 0.1951 +2025-06-25 01:13:58,199 - pyskl - INFO - Epoch [96][1200/1281] lr: 7.193e-03, eta: 7:57:08, time: 0.482, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 0.9994, loss_cls: 0.2161, loss: 0.2161 +2025-06-25 01:14:20,648 - pyskl - INFO - Saving checkpoint at 96 epochs +2025-06-25 01:15:18,957 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:15:19,013 - pyskl - INFO - +top1_acc 0.9105 +top5_acc 0.9941 +2025-06-25 01:15:19,013 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:15:19,021 - pyskl - INFO - +mean_acc 0.8836 +2025-06-25 01:15:19,023 - pyskl - INFO - Epoch(val) [96][533] top1_acc: 0.9105, top5_acc: 0.9941, mean_class_accuracy: 0.8836 +2025-06-25 01:16:37,116 - pyskl - INFO - Epoch [97][100/1281] lr: 7.159e-03, eta: 7:55:55, time: 0.781, data_time: 0.185, memory: 4083, top1_acc: 0.9738, top5_acc: 0.9994, loss_cls: 0.1617, loss: 0.1617 +2025-06-25 01:17:26,200 - pyskl - INFO - Epoch [97][200/1281] lr: 7.141e-03, eta: 7:55:18, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1732, loss: 0.1732 +2025-06-25 01:18:14,871 - pyskl - INFO - Epoch [97][300/1281] lr: 7.123e-03, eta: 7:54:41, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 0.1786, loss: 0.1786 +2025-06-25 01:19:03,669 - pyskl - INFO - Epoch [97][400/1281] lr: 7.104e-03, eta: 7:54:04, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.2073, loss: 0.2073 +2025-06-25 01:19:52,543 - pyskl - INFO - Epoch [97][500/1281] lr: 7.086e-03, eta: 7:53:27, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1792, loss: 0.1792 +2025-06-25 01:20:41,502 - pyskl - INFO - Epoch [97][600/1281] lr: 7.067e-03, eta: 7:52:49, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 0.9994, loss_cls: 0.1924, loss: 0.1924 +2025-06-25 01:21:30,254 - pyskl - INFO - Epoch [97][700/1281] lr: 7.049e-03, eta: 7:52:12, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 0.2219, loss: 0.2219 +2025-06-25 01:22:18,959 - pyskl - INFO - Epoch [97][800/1281] lr: 7.030e-03, eta: 7:51:35, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2441, loss: 0.2441 +2025-06-25 01:23:07,929 - pyskl - INFO - Epoch [97][900/1281] lr: 7.012e-03, eta: 7:50:58, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.2080, loss: 0.2080 +2025-06-25 01:23:57,115 - pyskl - INFO - Epoch [97][1000/1281] lr: 6.994e-03, eta: 7:50:20, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2103, loss: 0.2103 +2025-06-25 01:24:25,953 - pyskl - INFO - Epoch [97][1100/1281] lr: 6.975e-03, eta: 7:49:32, time: 0.288, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.2054, loss: 0.2054 +2025-06-25 01:25:16,791 - pyskl - INFO - Epoch [97][1200/1281] lr: 6.957e-03, eta: 7:48:56, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2074, loss: 0.2074 +2025-06-25 01:25:38,100 - pyskl - INFO - Saving checkpoint at 97 epochs +2025-06-25 01:26:36,720 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:26:36,774 - pyskl - INFO - +top1_acc 0.9142 +top5_acc 0.9939 +2025-06-25 01:26:36,774 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:26:36,780 - pyskl - INFO - +mean_acc 0.8861 +2025-06-25 01:26:36,782 - pyskl - INFO - Epoch(val) [97][533] top1_acc: 0.9142, top5_acc: 0.9939, mean_class_accuracy: 0.8861 +2025-06-25 01:27:57,791 - pyskl - INFO - Epoch [98][100/1281] lr: 6.924e-03, eta: 7:47:44, time: 0.810, data_time: 0.190, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1503, loss: 0.1503 +2025-06-25 01:28:46,963 - pyskl - INFO - Epoch [98][200/1281] lr: 6.906e-03, eta: 7:47:07, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1903, loss: 0.1903 +2025-06-25 01:29:35,942 - pyskl - INFO - Epoch [98][300/1281] lr: 6.887e-03, eta: 7:46:30, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1364, loss: 0.1364 +2025-06-25 01:30:24,594 - pyskl - INFO - Epoch [98][400/1281] lr: 6.869e-03, eta: 7:45:52, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1316, loss: 0.1316 +2025-06-25 01:31:13,319 - pyskl - INFO - Epoch [98][500/1281] lr: 6.851e-03, eta: 7:45:15, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1598, loss: 0.1598 +2025-06-25 01:32:02,277 - pyskl - INFO - Epoch [98][600/1281] lr: 6.833e-03, eta: 7:44:38, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 0.9994, loss_cls: 0.1630, loss: 0.1630 +2025-06-25 01:32:51,499 - pyskl - INFO - Epoch [98][700/1281] lr: 6.814e-03, eta: 7:44:00, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.1865, loss: 0.1865 +2025-06-25 01:33:40,315 - pyskl - INFO - Epoch [98][800/1281] lr: 6.796e-03, eta: 7:43:23, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1959, loss: 0.1959 +2025-06-25 01:34:29,043 - pyskl - INFO - Epoch [98][900/1281] lr: 6.778e-03, eta: 7:42:45, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 0.2180, loss: 0.2180 +2025-06-25 01:35:17,728 - pyskl - INFO - Epoch [98][1000/1281] lr: 6.760e-03, eta: 7:42:08, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1859, loss: 0.1859 +2025-06-25 01:35:46,612 - pyskl - INFO - Epoch [98][1100/1281] lr: 6.742e-03, eta: 7:41:20, time: 0.289, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1755, loss: 0.1755 +2025-06-25 01:36:34,709 - pyskl - INFO - Epoch [98][1200/1281] lr: 6.724e-03, eta: 7:40:42, time: 0.481, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1579, loss: 0.1579 +2025-06-25 01:37:00,587 - pyskl - INFO - Saving checkpoint at 98 epochs +2025-06-25 01:37:58,158 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:37:58,214 - pyskl - INFO - +top1_acc 0.9139 +top5_acc 0.9964 +2025-06-25 01:37:58,214 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:37:58,221 - pyskl - INFO - +mean_acc 0.8980 +2025-06-25 01:37:58,223 - pyskl - INFO - Epoch(val) [98][533] top1_acc: 0.9139, top5_acc: 0.9964, mean_class_accuracy: 0.8980 +2025-06-25 01:39:18,056 - pyskl - INFO - Epoch [99][100/1281] lr: 6.691e-03, eta: 7:39:29, time: 0.798, data_time: 0.188, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1512, loss: 0.1512 +2025-06-25 01:40:07,096 - pyskl - INFO - Epoch [99][200/1281] lr: 6.673e-03, eta: 7:38:52, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 0.9994, loss_cls: 0.1432, loss: 0.1432 +2025-06-25 01:40:55,693 - pyskl - INFO - Epoch [99][300/1281] lr: 6.655e-03, eta: 7:38:14, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1521, loss: 0.1521 +2025-06-25 01:41:44,227 - pyskl - INFO - Epoch [99][400/1281] lr: 6.637e-03, eta: 7:37:36, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 0.9994, loss_cls: 0.1822, loss: 0.1822 +2025-06-25 01:42:33,345 - pyskl - INFO - Epoch [99][500/1281] lr: 6.619e-03, eta: 7:36:59, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.1981, loss: 0.1981 +2025-06-25 01:43:22,759 - pyskl - INFO - Epoch [99][600/1281] lr: 6.601e-03, eta: 7:36:22, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1831, loss: 0.1831 +2025-06-25 01:44:11,552 - pyskl - INFO - Epoch [99][700/1281] lr: 6.583e-03, eta: 7:35:44, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1372, loss: 0.1372 +2025-06-25 01:45:00,467 - pyskl - INFO - Epoch [99][800/1281] lr: 6.565e-03, eta: 7:35:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1527, loss: 0.1527 +2025-06-25 01:45:49,180 - pyskl - INFO - Epoch [99][900/1281] lr: 6.547e-03, eta: 7:34:29, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 0.1955, loss: 0.1955 +2025-06-25 01:46:38,057 - pyskl - INFO - Epoch [99][1000/1281] lr: 6.529e-03, eta: 7:33:51, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1345, loss: 0.1345 +2025-06-25 01:47:08,895 - pyskl - INFO - Epoch [99][1100/1281] lr: 6.511e-03, eta: 7:33:04, time: 0.308, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1643, loss: 0.1643 +2025-06-25 01:47:54,654 - pyskl - INFO - Epoch [99][1200/1281] lr: 6.493e-03, eta: 7:32:25, time: 0.458, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1845, loss: 0.1845 +2025-06-25 01:48:20,575 - pyskl - INFO - Saving checkpoint at 99 epochs +2025-06-25 01:49:19,286 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:49:19,342 - pyskl - INFO - +top1_acc 0.9267 +top5_acc 0.9961 +2025-06-25 01:49:19,342 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:49:19,349 - pyskl - INFO - +mean_acc 0.9064 +2025-06-25 01:49:19,353 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_87.pth was removed +2025-06-25 01:49:19,540 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_99.pth. +2025-06-25 01:49:19,540 - pyskl - INFO - Best top1_acc is 0.9267 at 99 epoch. +2025-06-25 01:49:19,544 - pyskl - INFO - Epoch(val) [99][533] top1_acc: 0.9267, top5_acc: 0.9961, mean_class_accuracy: 0.9064 +2025-06-25 01:50:37,921 - pyskl - INFO - Epoch [100][100/1281] lr: 6.460e-03, eta: 7:31:11, time: 0.784, data_time: 0.190, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1365, loss: 0.1365 +2025-06-25 01:51:26,602 - pyskl - INFO - Epoch [100][200/1281] lr: 6.442e-03, eta: 7:30:33, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1533, loss: 0.1533 +2025-06-25 01:52:15,387 - pyskl - INFO - Epoch [100][300/1281] lr: 6.425e-03, eta: 7:29:56, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1874, loss: 0.1874 +2025-06-25 01:53:04,231 - pyskl - INFO - Epoch [100][400/1281] lr: 6.407e-03, eta: 7:29:18, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 0.9994, loss_cls: 0.1828, loss: 0.1828 +2025-06-25 01:53:53,126 - pyskl - INFO - Epoch [100][500/1281] lr: 6.389e-03, eta: 7:28:40, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1561, loss: 0.1561 +2025-06-25 01:54:41,992 - pyskl - INFO - Epoch [100][600/1281] lr: 6.371e-03, eta: 7:28:02, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1620, loss: 0.1620 +2025-06-25 01:55:30,833 - pyskl - INFO - Epoch [100][700/1281] lr: 6.353e-03, eta: 7:27:24, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1393, loss: 0.1393 +2025-06-25 01:56:19,303 - pyskl - INFO - Epoch [100][800/1281] lr: 6.336e-03, eta: 7:26:46, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1357, loss: 0.1357 +2025-06-25 01:57:08,144 - pyskl - INFO - Epoch [100][900/1281] lr: 6.318e-03, eta: 7:26:08, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1201, loss: 0.1201 +2025-06-25 01:57:57,076 - pyskl - INFO - Epoch [100][1000/1281] lr: 6.300e-03, eta: 7:25:31, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 0.9994, loss_cls: 0.1941, loss: 0.1941 +2025-06-25 01:58:27,067 - pyskl - INFO - Epoch [100][1100/1281] lr: 6.282e-03, eta: 7:24:43, time: 0.300, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.1944, loss: 0.1944 +2025-06-25 01:59:12,441 - pyskl - INFO - Epoch [100][1200/1281] lr: 6.265e-03, eta: 7:24:04, time: 0.454, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 0.9994, loss_cls: 0.1868, loss: 0.1868 +2025-06-25 01:59:38,264 - pyskl - INFO - Saving checkpoint at 100 epochs +2025-06-25 02:00:36,918 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:00:36,976 - pyskl - INFO - +top1_acc 0.9137 +top5_acc 0.9946 +2025-06-25 02:00:36,976 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:00:36,984 - pyskl - INFO - +mean_acc 0.8732 +2025-06-25 02:00:36,987 - pyskl - INFO - Epoch(val) [100][533] top1_acc: 0.9137, top5_acc: 0.9946, mean_class_accuracy: 0.8732 +2025-06-25 02:01:57,160 - pyskl - INFO - Epoch [101][100/1281] lr: 6.232e-03, eta: 7:22:51, time: 0.802, data_time: 0.191, memory: 4083, top1_acc: 0.9681, top5_acc: 0.9994, loss_cls: 0.1884, loss: 0.1884 +2025-06-25 02:02:46,223 - pyskl - INFO - Epoch [101][200/1281] lr: 6.215e-03, eta: 7:22:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1303, loss: 0.1303 +2025-06-25 02:03:34,987 - pyskl - INFO - Epoch [101][300/1281] lr: 6.197e-03, eta: 7:21:35, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 0.9994, loss_cls: 0.1451, loss: 0.1451 +2025-06-25 02:04:23,649 - pyskl - INFO - Epoch [101][400/1281] lr: 6.180e-03, eta: 7:20:57, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1558, loss: 0.1558 +2025-06-25 02:05:12,254 - pyskl - INFO - Epoch [101][500/1281] lr: 6.162e-03, eta: 7:20:19, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 0.9994, loss_cls: 0.2005, loss: 0.2005 +2025-06-25 02:06:01,286 - pyskl - INFO - Epoch [101][600/1281] lr: 6.144e-03, eta: 7:19:41, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 0.9994, loss_cls: 0.1624, loss: 0.1624 +2025-06-25 02:06:49,978 - pyskl - INFO - Epoch [101][700/1281] lr: 6.127e-03, eta: 7:19:03, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1647, loss: 0.1647 +2025-06-25 02:07:39,188 - pyskl - INFO - Epoch [101][800/1281] lr: 6.109e-03, eta: 7:18:25, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 0.9994, loss_cls: 0.1474, loss: 0.1474 +2025-06-25 02:08:27,929 - pyskl - INFO - Epoch [101][900/1281] lr: 6.092e-03, eta: 7:17:47, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.1956, loss: 0.1956 +2025-06-25 02:09:16,616 - pyskl - INFO - Epoch [101][1000/1281] lr: 6.074e-03, eta: 7:17:09, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1865, loss: 0.1865 +2025-06-25 02:09:48,839 - pyskl - INFO - Epoch [101][1100/1281] lr: 6.057e-03, eta: 7:16:23, time: 0.322, data_time: 0.001, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1869, loss: 0.1869 +2025-06-25 02:10:30,260 - pyskl - INFO - Epoch [101][1200/1281] lr: 6.039e-03, eta: 7:15:41, time: 0.414, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1479, loss: 0.1479 +2025-06-25 02:10:55,989 - pyskl - INFO - Saving checkpoint at 101 epochs +2025-06-25 02:11:54,829 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:11:54,910 - pyskl - INFO - +top1_acc 0.9272 +top5_acc 0.9968 +2025-06-25 02:11:54,911 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:11:54,922 - pyskl - INFO - +mean_acc 0.9043 +2025-06-25 02:11:54,926 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_99.pth was removed +2025-06-25 02:11:55,107 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_101.pth. +2025-06-25 02:11:55,107 - pyskl - INFO - Best top1_acc is 0.9272 at 101 epoch. +2025-06-25 02:11:55,110 - pyskl - INFO - Epoch(val) [101][533] top1_acc: 0.9272, top5_acc: 0.9968, mean_class_accuracy: 0.9043 +2025-06-25 02:13:15,143 - pyskl - INFO - Epoch [102][100/1281] lr: 6.007e-03, eta: 7:14:28, time: 0.800, data_time: 0.191, memory: 4083, top1_acc: 0.9825, top5_acc: 0.9994, loss_cls: 0.1336, loss: 0.1336 +2025-06-25 02:14:04,151 - pyskl - INFO - Epoch [102][200/1281] lr: 5.990e-03, eta: 7:13:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 0.9994, loss_cls: 0.1523, loss: 0.1523 +2025-06-25 02:14:53,229 - pyskl - INFO - Epoch [102][300/1281] lr: 5.972e-03, eta: 7:13:12, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1536, loss: 0.1536 +2025-06-25 02:15:42,272 - pyskl - INFO - Epoch [102][400/1281] lr: 5.955e-03, eta: 7:12:34, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1473, loss: 0.1473 +2025-06-25 02:16:30,982 - pyskl - INFO - Epoch [102][500/1281] lr: 5.938e-03, eta: 7:11:56, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1314, loss: 0.1314 +2025-06-25 02:17:19,839 - pyskl - INFO - Epoch [102][600/1281] lr: 5.920e-03, eta: 7:11:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 0.9994, loss_cls: 0.1610, loss: 0.1610 +2025-06-25 02:18:08,882 - pyskl - INFO - Epoch [102][700/1281] lr: 5.903e-03, eta: 7:10:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1657, loss: 0.1657 +2025-06-25 02:18:57,680 - pyskl - INFO - Epoch [102][800/1281] lr: 5.886e-03, eta: 7:10:01, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 0.9994, loss_cls: 0.1459, loss: 0.1459 +2025-06-25 02:19:46,997 - pyskl - INFO - Epoch [102][900/1281] lr: 5.868e-03, eta: 7:09:23, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1305, loss: 0.1305 +2025-06-25 02:20:35,611 - pyskl - INFO - Epoch [102][1000/1281] lr: 5.851e-03, eta: 7:08:45, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1317, loss: 0.1317 +2025-06-25 02:21:08,012 - pyskl - INFO - Epoch [102][1100/1281] lr: 5.834e-03, eta: 7:07:59, time: 0.324, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1539, loss: 0.1539 +2025-06-25 02:21:49,338 - pyskl - INFO - Epoch [102][1200/1281] lr: 5.816e-03, eta: 7:07:17, time: 0.413, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1586, loss: 0.1586 +2025-06-25 02:22:14,808 - pyskl - INFO - Saving checkpoint at 102 epochs +2025-06-25 02:23:13,264 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:23:13,346 - pyskl - INFO - +top1_acc 0.9122 +top5_acc 0.9942 +2025-06-25 02:23:13,346 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:23:13,354 - pyskl - INFO - +mean_acc 0.8799 +2025-06-25 02:23:13,356 - pyskl - INFO - Epoch(val) [102][533] top1_acc: 0.9122, top5_acc: 0.9942, mean_class_accuracy: 0.8799 +2025-06-25 02:24:32,963 - pyskl - INFO - Epoch [103][100/1281] lr: 5.785e-03, eta: 7:06:04, time: 0.796, data_time: 0.193, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1428, loss: 0.1428 +2025-06-25 02:25:22,179 - pyskl - INFO - Epoch [103][200/1281] lr: 5.768e-03, eta: 7:05:26, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1273, loss: 0.1273 +2025-06-25 02:26:11,437 - pyskl - INFO - Epoch [103][300/1281] lr: 5.751e-03, eta: 7:04:48, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1208, loss: 0.1208 +2025-06-25 02:27:00,412 - pyskl - INFO - Epoch [103][400/1281] lr: 5.733e-03, eta: 7:04:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1643, loss: 0.1643 +2025-06-25 02:27:49,141 - pyskl - INFO - Epoch [103][500/1281] lr: 5.716e-03, eta: 7:03:31, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1505, loss: 0.1505 +2025-06-25 02:28:37,955 - pyskl - INFO - Epoch [103][600/1281] lr: 5.699e-03, eta: 7:02:53, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1084, loss: 0.1084 +2025-06-25 02:29:27,111 - pyskl - INFO - Epoch [103][700/1281] lr: 5.682e-03, eta: 7:02:14, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0978, loss: 0.0978 +2025-06-25 02:30:15,865 - pyskl - INFO - Epoch [103][800/1281] lr: 5.665e-03, eta: 7:01:36, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 0.9994, loss_cls: 0.1522, loss: 0.1522 +2025-06-25 02:31:04,592 - pyskl - INFO - Epoch [103][900/1281] lr: 5.648e-03, eta: 7:00:58, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1166, loss: 0.1166 +2025-06-25 02:31:53,344 - pyskl - INFO - Epoch [103][1000/1281] lr: 5.631e-03, eta: 7:00:19, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1287, loss: 0.1287 +2025-06-25 02:32:23,197 - pyskl - INFO - Epoch [103][1100/1281] lr: 5.614e-03, eta: 6:59:32, time: 0.299, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1536, loss: 0.1536 +2025-06-25 02:33:08,992 - pyskl - INFO - Epoch [103][1200/1281] lr: 5.597e-03, eta: 6:58:52, time: 0.458, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1656, loss: 0.1656 +2025-06-25 02:33:35,160 - pyskl - INFO - Saving checkpoint at 103 epochs +2025-06-25 02:34:33,038 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:34:33,093 - pyskl - INFO - +top1_acc 0.9157 +top5_acc 0.9965 +2025-06-25 02:34:33,094 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:34:33,100 - pyskl - INFO - +mean_acc 0.8849 +2025-06-25 02:34:33,102 - pyskl - INFO - Epoch(val) [103][533] top1_acc: 0.9157, top5_acc: 0.9965, mean_class_accuracy: 0.8849 +2025-06-25 02:35:53,648 - pyskl - INFO - Epoch [104][100/1281] lr: 5.566e-03, eta: 6:57:39, time: 0.805, data_time: 0.195, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1336, loss: 0.1336 +2025-06-25 02:36:42,443 - pyskl - INFO - Epoch [104][200/1281] lr: 5.549e-03, eta: 6:57:01, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1202, loss: 0.1202 +2025-06-25 02:37:31,331 - pyskl - INFO - Epoch [104][300/1281] lr: 5.532e-03, eta: 6:56:22, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1297, loss: 0.1297 +2025-06-25 02:38:20,365 - pyskl - INFO - Epoch [104][400/1281] lr: 5.515e-03, eta: 6:55:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1307, loss: 0.1307 +2025-06-25 02:39:09,274 - pyskl - INFO - Epoch [104][500/1281] lr: 5.498e-03, eta: 6:55:05, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1358, loss: 0.1358 +2025-06-25 02:39:58,315 - pyskl - INFO - Epoch [104][600/1281] lr: 5.481e-03, eta: 6:54:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1115, loss: 0.1115 +2025-06-25 02:40:47,475 - pyskl - INFO - Epoch [104][700/1281] lr: 5.464e-03, eta: 6:53:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 0.1546, loss: 0.1546 +2025-06-25 02:41:36,725 - pyskl - INFO - Epoch [104][800/1281] lr: 5.447e-03, eta: 6:53:10, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1278, loss: 0.1278 +2025-06-25 02:42:25,609 - pyskl - INFO - Epoch [104][900/1281] lr: 5.430e-03, eta: 6:52:32, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1254, loss: 0.1254 +2025-06-25 02:43:14,362 - pyskl - INFO - Epoch [104][1000/1281] lr: 5.413e-03, eta: 6:51:53, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.1803, loss: 0.1803 +2025-06-25 02:43:46,453 - pyskl - INFO - Epoch [104][1100/1281] lr: 5.397e-03, eta: 6:51:07, time: 0.321, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1619, loss: 0.1619 +2025-06-25 02:44:28,172 - pyskl - INFO - Epoch [104][1200/1281] lr: 5.380e-03, eta: 6:50:25, time: 0.417, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1693, loss: 0.1693 +2025-06-25 02:44:54,464 - pyskl - INFO - Saving checkpoint at 104 epochs +2025-06-25 02:45:52,842 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:45:52,898 - pyskl - INFO - +top1_acc 0.9250 +top5_acc 0.9951 +2025-06-25 02:45:52,898 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:45:52,905 - pyskl - INFO - +mean_acc 0.8900 +2025-06-25 02:45:52,907 - pyskl - INFO - Epoch(val) [104][533] top1_acc: 0.9250, top5_acc: 0.9951, mean_class_accuracy: 0.8900 +2025-06-25 02:47:12,059 - pyskl - INFO - Epoch [105][100/1281] lr: 5.349e-03, eta: 6:49:11, time: 0.791, data_time: 0.197, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1155, loss: 0.1155 +2025-06-25 02:48:01,002 - pyskl - INFO - Epoch [105][200/1281] lr: 5.333e-03, eta: 6:48:33, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 0.9994, loss_cls: 0.1218, loss: 0.1218 +2025-06-25 02:48:49,944 - pyskl - INFO - Epoch [105][300/1281] lr: 5.316e-03, eta: 6:47:54, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 0.9994, loss_cls: 0.1371, loss: 0.1371 +2025-06-25 02:49:38,907 - pyskl - INFO - Epoch [105][400/1281] lr: 5.299e-03, eta: 6:47:16, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1138, loss: 0.1138 +2025-06-25 02:50:27,920 - pyskl - INFO - Epoch [105][500/1281] lr: 5.283e-03, eta: 6:46:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1515, loss: 0.1515 +2025-06-25 02:51:17,054 - pyskl - INFO - Epoch [105][600/1281] lr: 5.266e-03, eta: 6:45:58, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1515, loss: 0.1515 +2025-06-25 02:52:06,117 - pyskl - INFO - Epoch [105][700/1281] lr: 5.249e-03, eta: 6:45:20, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1248, loss: 0.1248 +2025-06-25 02:52:54,840 - pyskl - INFO - Epoch [105][800/1281] lr: 5.233e-03, eta: 6:44:41, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.1123, loss: 0.1123 +2025-06-25 02:53:43,728 - pyskl - INFO - Epoch [105][900/1281] lr: 5.216e-03, eta: 6:44:02, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1396, loss: 0.1396 +2025-06-25 02:54:32,689 - pyskl - INFO - Epoch [105][1000/1281] lr: 5.199e-03, eta: 6:43:24, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 0.9994, loss_cls: 0.1500, loss: 0.1500 +2025-06-25 02:55:04,855 - pyskl - INFO - Epoch [105][1100/1281] lr: 5.183e-03, eta: 6:42:38, time: 0.322, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1440, loss: 0.1440 +2025-06-25 02:55:47,839 - pyskl - INFO - Epoch [105][1200/1281] lr: 5.166e-03, eta: 6:41:57, time: 0.430, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1256, loss: 0.1256 +2025-06-25 02:56:14,465 - pyskl - INFO - Saving checkpoint at 105 epochs +2025-06-25 02:57:12,563 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:57:12,617 - pyskl - INFO - +top1_acc 0.9248 +top5_acc 0.9948 +2025-06-25 02:57:12,618 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:57:12,624 - pyskl - INFO - +mean_acc 0.9045 +2025-06-25 02:57:12,626 - pyskl - INFO - Epoch(val) [105][533] top1_acc: 0.9248, top5_acc: 0.9948, mean_class_accuracy: 0.9045 +2025-06-25 02:58:31,406 - pyskl - INFO - Epoch [106][100/1281] lr: 5.136e-03, eta: 6:40:42, time: 0.788, data_time: 0.185, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0988, loss: 0.0988 +2025-06-25 02:59:20,217 - pyskl - INFO - Epoch [106][200/1281] lr: 5.120e-03, eta: 6:40:04, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 0.9994, loss_cls: 0.1125, loss: 0.1125 +2025-06-25 03:00:09,417 - pyskl - INFO - Epoch [106][300/1281] lr: 5.103e-03, eta: 6:39:25, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0965, loss: 0.0965 +2025-06-25 03:00:58,825 - pyskl - INFO - Epoch [106][400/1281] lr: 5.087e-03, eta: 6:38:46, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1114, loss: 0.1114 +2025-06-25 03:01:47,839 - pyskl - INFO - Epoch [106][500/1281] lr: 5.070e-03, eta: 6:38:08, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1127, loss: 0.1127 +2025-06-25 03:02:36,831 - pyskl - INFO - Epoch [106][600/1281] lr: 5.054e-03, eta: 6:37:29, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1130, loss: 0.1130 +2025-06-25 03:03:25,719 - pyskl - INFO - Epoch [106][700/1281] lr: 5.038e-03, eta: 6:36:50, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1117, loss: 0.1117 +2025-06-25 03:04:14,821 - pyskl - INFO - Epoch [106][800/1281] lr: 5.021e-03, eta: 6:36:11, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0964, loss: 0.0964 +2025-06-25 03:05:04,003 - pyskl - INFO - Epoch [106][900/1281] lr: 5.005e-03, eta: 6:35:33, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.1007, loss: 0.1007 +2025-06-25 03:05:52,873 - pyskl - INFO - Epoch [106][1000/1281] lr: 4.988e-03, eta: 6:34:54, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 0.9994, loss_cls: 0.1004, loss: 0.1004 +2025-06-25 03:06:22,384 - pyskl - INFO - Epoch [106][1100/1281] lr: 4.972e-03, eta: 6:34:07, time: 0.295, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1520, loss: 0.1520 +2025-06-25 03:07:08,181 - pyskl - INFO - Epoch [106][1200/1281] lr: 4.956e-03, eta: 6:33:27, time: 0.458, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1456, loss: 0.1456 +2025-06-25 03:07:33,697 - pyskl - INFO - Saving checkpoint at 106 epochs +2025-06-25 03:08:32,042 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:08:32,110 - pyskl - INFO - +top1_acc 0.9257 +top5_acc 0.9957 +2025-06-25 03:08:32,110 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:08:32,117 - pyskl - INFO - +mean_acc 0.9055 +2025-06-25 03:08:32,119 - pyskl - INFO - Epoch(val) [106][533] top1_acc: 0.9257, top5_acc: 0.9957, mean_class_accuracy: 0.9055 +2025-06-25 03:09:51,844 - pyskl - INFO - Epoch [107][100/1281] lr: 4.926e-03, eta: 6:32:12, time: 0.797, data_time: 0.191, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1326, loss: 0.1326 +2025-06-25 03:10:40,767 - pyskl - INFO - Epoch [107][200/1281] lr: 4.910e-03, eta: 6:31:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1136, loss: 0.1136 +2025-06-25 03:11:29,837 - pyskl - INFO - Epoch [107][300/1281] lr: 4.894e-03, eta: 6:30:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1425, loss: 0.1425 +2025-06-25 03:12:18,726 - pyskl - INFO - Epoch [107][400/1281] lr: 4.878e-03, eta: 6:30:16, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1368, loss: 0.1368 +2025-06-25 03:13:07,320 - pyskl - INFO - Epoch [107][500/1281] lr: 4.862e-03, eta: 6:29:37, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1299, loss: 0.1299 +2025-06-25 03:13:56,560 - pyskl - INFO - Epoch [107][600/1281] lr: 4.845e-03, eta: 6:28:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 0.9994, loss_cls: 0.1404, loss: 0.1404 +2025-06-25 03:14:45,355 - pyskl - INFO - Epoch [107][700/1281] lr: 4.829e-03, eta: 6:28:19, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 0.9994, loss_cls: 0.1183, loss: 0.1183 +2025-06-25 03:15:34,295 - pyskl - INFO - Epoch [107][800/1281] lr: 4.813e-03, eta: 6:27:40, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 0.1463, loss: 0.1463 +2025-06-25 03:16:22,906 - pyskl - INFO - Epoch [107][900/1281] lr: 4.797e-03, eta: 6:27:01, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1295, loss: 0.1295 +2025-06-25 03:17:11,800 - pyskl - INFO - Epoch [107][1000/1281] lr: 4.781e-03, eta: 6:26:22, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1380, loss: 0.1380 +2025-06-25 03:17:40,391 - pyskl - INFO - Epoch [107][1100/1281] lr: 4.765e-03, eta: 6:25:35, time: 0.286, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1297, loss: 0.1297 +2025-06-25 03:18:26,488 - pyskl - INFO - Epoch [107][1200/1281] lr: 4.749e-03, eta: 6:24:54, time: 0.461, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1104, loss: 0.1104 +2025-06-25 03:18:51,087 - pyskl - INFO - Saving checkpoint at 107 epochs +2025-06-25 03:19:49,235 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:19:49,295 - pyskl - INFO - +top1_acc 0.9275 +top5_acc 0.9960 +2025-06-25 03:19:49,295 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:19:49,305 - pyskl - INFO - +mean_acc 0.8987 +2025-06-25 03:19:49,309 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_101.pth was removed +2025-06-25 03:19:49,486 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_107.pth. +2025-06-25 03:19:49,487 - pyskl - INFO - Best top1_acc is 0.9275 at 107 epoch. +2025-06-25 03:19:49,490 - pyskl - INFO - Epoch(val) [107][533] top1_acc: 0.9275, top5_acc: 0.9960, mean_class_accuracy: 0.8987 +2025-06-25 03:21:09,748 - pyskl - INFO - Epoch [108][100/1281] lr: 4.720e-03, eta: 6:23:40, time: 0.803, data_time: 0.194, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1174, loss: 0.1174 +2025-06-25 03:21:58,608 - pyskl - INFO - Epoch [108][200/1281] lr: 4.704e-03, eta: 6:23:01, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1306, loss: 0.1306 +2025-06-25 03:22:47,479 - pyskl - INFO - Epoch [108][300/1281] lr: 4.688e-03, eta: 6:22:22, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1038, loss: 0.1038 +2025-06-25 03:23:36,520 - pyskl - INFO - Epoch [108][400/1281] lr: 4.672e-03, eta: 6:21:43, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1027, loss: 0.1027 +2025-06-25 03:24:25,402 - pyskl - INFO - Epoch [108][500/1281] lr: 4.656e-03, eta: 6:21:04, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1484, loss: 0.1484 +2025-06-25 03:25:14,605 - pyskl - INFO - Epoch [108][600/1281] lr: 4.640e-03, eta: 6:20:25, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.1159, loss: 0.1159 +2025-06-25 03:26:03,355 - pyskl - INFO - Epoch [108][700/1281] lr: 4.624e-03, eta: 6:19:46, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0854, loss: 0.0854 +2025-06-25 03:26:52,380 - pyskl - INFO - Epoch [108][800/1281] lr: 4.608e-03, eta: 6:19:07, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1365, loss: 0.1365 +2025-06-25 03:27:41,320 - pyskl - INFO - Epoch [108][900/1281] lr: 4.593e-03, eta: 6:18:28, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0880, loss: 0.0880 +2025-06-25 03:28:30,387 - pyskl - INFO - Epoch [108][1000/1281] lr: 4.577e-03, eta: 6:17:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1102, loss: 0.1102 +2025-06-25 03:29:00,697 - pyskl - INFO - Epoch [108][1100/1281] lr: 4.561e-03, eta: 6:17:02, time: 0.303, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.0939, loss: 0.0939 +2025-06-25 03:29:45,706 - pyskl - INFO - Epoch [108][1200/1281] lr: 4.545e-03, eta: 6:16:21, time: 0.450, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1251, loss: 0.1251 +2025-06-25 03:30:10,239 - pyskl - INFO - Saving checkpoint at 108 epochs +2025-06-25 03:31:08,512 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:31:08,572 - pyskl - INFO - +top1_acc 0.9161 +top5_acc 0.9927 +2025-06-25 03:31:08,572 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:31:08,579 - pyskl - INFO - +mean_acc 0.8834 +2025-06-25 03:31:08,580 - pyskl - INFO - Epoch(val) [108][533] top1_acc: 0.9161, top5_acc: 0.9927, mean_class_accuracy: 0.8834 +2025-06-25 03:32:27,642 - pyskl - INFO - Epoch [109][100/1281] lr: 4.517e-03, eta: 6:15:07, time: 0.791, data_time: 0.193, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1210, loss: 0.1210 +2025-06-25 03:33:16,380 - pyskl - INFO - Epoch [109][200/1281] lr: 4.501e-03, eta: 6:14:28, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1186, loss: 0.1186 +2025-06-25 03:34:05,370 - pyskl - INFO - Epoch [109][300/1281] lr: 4.485e-03, eta: 6:13:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0942, loss: 0.0942 +2025-06-25 03:34:54,378 - pyskl - INFO - Epoch [109][400/1281] lr: 4.470e-03, eta: 6:13:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0884, loss: 0.0884 +2025-06-25 03:35:43,854 - pyskl - INFO - Epoch [109][500/1281] lr: 4.454e-03, eta: 6:12:30, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1055, loss: 0.1055 +2025-06-25 03:36:33,047 - pyskl - INFO - Epoch [109][600/1281] lr: 4.438e-03, eta: 6:11:51, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0889, loss: 0.0889 +2025-06-25 03:37:22,483 - pyskl - INFO - Epoch [109][700/1281] lr: 4.423e-03, eta: 6:11:12, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1306, loss: 0.1306 +2025-06-25 03:38:11,300 - pyskl - INFO - Epoch [109][800/1281] lr: 4.407e-03, eta: 6:10:33, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1361, loss: 0.1361 +2025-06-25 03:39:00,473 - pyskl - INFO - Epoch [109][900/1281] lr: 4.391e-03, eta: 6:09:53, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1216, loss: 0.1216 +2025-06-25 03:39:49,563 - pyskl - INFO - Epoch [109][1000/1281] lr: 4.376e-03, eta: 6:09:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.0912, loss: 0.0912 +2025-06-25 03:40:17,962 - pyskl - INFO - Epoch [109][1100/1281] lr: 4.360e-03, eta: 6:08:27, time: 0.284, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 0.9994, loss_cls: 0.1621, loss: 0.1621 +2025-06-25 03:41:05,680 - pyskl - INFO - Epoch [109][1200/1281] lr: 4.345e-03, eta: 6:07:47, time: 0.477, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 0.9994, loss_cls: 0.1286, loss: 0.1286 +2025-06-25 03:41:27,670 - pyskl - INFO - Saving checkpoint at 109 epochs +2025-06-25 03:42:25,926 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:42:25,987 - pyskl - INFO - +top1_acc 0.9276 +top5_acc 0.9953 +2025-06-25 03:42:25,987 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:42:25,994 - pyskl - INFO - +mean_acc 0.9106 +2025-06-25 03:42:25,998 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_107.pth was removed +2025-06-25 03:42:26,175 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_109.pth. +2025-06-25 03:42:26,175 - pyskl - INFO - Best top1_acc is 0.9276 at 109 epoch. +2025-06-25 03:42:26,178 - pyskl - INFO - Epoch(val) [109][533] top1_acc: 0.9276, top5_acc: 0.9953, mean_class_accuracy: 0.9106 +2025-06-25 03:43:46,618 - pyskl - INFO - Epoch [110][100/1281] lr: 4.317e-03, eta: 6:06:33, time: 0.804, data_time: 0.194, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1066, loss: 0.1066 +2025-06-25 03:44:35,740 - pyskl - INFO - Epoch [110][200/1281] lr: 4.301e-03, eta: 6:05:54, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0903, loss: 0.0903 +2025-06-25 03:45:24,729 - pyskl - INFO - Epoch [110][300/1281] lr: 4.286e-03, eta: 6:05:14, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1036, loss: 0.1036 +2025-06-25 03:46:13,671 - pyskl - INFO - Epoch [110][400/1281] lr: 4.271e-03, eta: 6:04:35, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0783, loss: 0.0783 +2025-06-25 03:47:02,849 - pyskl - INFO - Epoch [110][500/1281] lr: 4.255e-03, eta: 6:03:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0927, loss: 0.0927 +2025-06-25 03:47:51,885 - pyskl - INFO - Epoch [110][600/1281] lr: 4.240e-03, eta: 6:03:16, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1100, loss: 0.1100 +2025-06-25 03:48:40,812 - pyskl - INFO - Epoch [110][700/1281] lr: 4.225e-03, eta: 6:02:37, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1027, loss: 0.1027 +2025-06-25 03:49:30,077 - pyskl - INFO - Epoch [110][800/1281] lr: 4.209e-03, eta: 6:01:58, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0837, loss: 0.0837 +2025-06-25 03:50:19,175 - pyskl - INFO - Epoch [110][900/1281] lr: 4.194e-03, eta: 6:01:18, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 0.9994, loss_cls: 0.1148, loss: 0.1148 +2025-06-25 03:51:07,797 - pyskl - INFO - Epoch [110][1000/1281] lr: 4.179e-03, eta: 6:00:39, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.1010, loss: 0.1010 +2025-06-25 03:51:35,739 - pyskl - INFO - Epoch [110][1100/1281] lr: 4.164e-03, eta: 5:59:52, time: 0.279, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.0966, loss: 0.0966 +2025-06-25 03:52:25,493 - pyskl - INFO - Epoch [110][1200/1281] lr: 4.148e-03, eta: 5:59:12, time: 0.498, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0874, loss: 0.0874 +2025-06-25 03:52:47,483 - pyskl - INFO - Saving checkpoint at 110 epochs +2025-06-25 03:53:45,507 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:53:45,562 - pyskl - INFO - +top1_acc 0.9302 +top5_acc 0.9962 +2025-06-25 03:53:45,562 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:53:45,569 - pyskl - INFO - +mean_acc 0.9040 +2025-06-25 03:53:45,573 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_109.pth was removed +2025-06-25 03:53:45,748 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_110.pth. +2025-06-25 03:53:45,749 - pyskl - INFO - Best top1_acc is 0.9302 at 110 epoch. +2025-06-25 03:53:45,751 - pyskl - INFO - Epoch(val) [110][533] top1_acc: 0.9302, top5_acc: 0.9962, mean_class_accuracy: 0.9040 +2025-06-25 03:55:04,853 - pyskl - INFO - Epoch [111][100/1281] lr: 4.121e-03, eta: 5:57:57, time: 0.791, data_time: 0.192, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0713, loss: 0.0713 +2025-06-25 03:55:53,515 - pyskl - INFO - Epoch [111][200/1281] lr: 4.106e-03, eta: 5:57:18, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0820, loss: 0.0820 +2025-06-25 03:56:42,607 - pyskl - INFO - Epoch [111][300/1281] lr: 4.091e-03, eta: 5:56:38, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0777, loss: 0.0777 +2025-06-25 03:57:31,206 - pyskl - INFO - Epoch [111][400/1281] lr: 4.075e-03, eta: 5:55:59, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0997, loss: 0.0997 +2025-06-25 03:58:20,427 - pyskl - INFO - Epoch [111][500/1281] lr: 4.060e-03, eta: 5:55:19, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 0.9994, loss_cls: 0.1256, loss: 0.1256 +2025-06-25 03:59:09,778 - pyskl - INFO - Epoch [111][600/1281] lr: 4.045e-03, eta: 5:54:40, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1047, loss: 0.1047 +2025-06-25 03:59:59,380 - pyskl - INFO - Epoch [111][700/1281] lr: 4.030e-03, eta: 5:54:01, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.1014, loss: 0.1014 +2025-06-25 04:00:48,204 - pyskl - INFO - Epoch [111][800/1281] lr: 4.015e-03, eta: 5:53:21, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.0986, loss: 0.0986 +2025-06-25 04:01:36,869 - pyskl - INFO - Epoch [111][900/1281] lr: 4.000e-03, eta: 5:52:41, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1126, loss: 0.1126 +2025-06-25 04:02:25,943 - pyskl - INFO - Epoch [111][1000/1281] lr: 3.985e-03, eta: 5:52:02, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.1024, loss: 0.1024 +2025-06-25 04:02:53,821 - pyskl - INFO - Epoch [111][1100/1281] lr: 3.970e-03, eta: 5:51:15, time: 0.279, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1007, loss: 0.1007 +2025-06-25 04:03:44,504 - pyskl - INFO - Epoch [111][1200/1281] lr: 3.955e-03, eta: 5:50:36, time: 0.507, data_time: 0.001, memory: 4083, top1_acc: 0.9869, top5_acc: 0.9994, loss_cls: 0.1121, loss: 0.1121 +2025-06-25 04:04:06,253 - pyskl - INFO - Saving checkpoint at 111 epochs +2025-06-25 04:05:04,142 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:05:04,197 - pyskl - INFO - +top1_acc 0.9250 +top5_acc 0.9961 +2025-06-25 04:05:04,197 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:05:04,203 - pyskl - INFO - +mean_acc 0.8972 +2025-06-25 04:05:04,205 - pyskl - INFO - Epoch(val) [111][533] top1_acc: 0.9250, top5_acc: 0.9961, mean_class_accuracy: 0.8972 +2025-06-25 04:06:23,462 - pyskl - INFO - Epoch [112][100/1281] lr: 3.928e-03, eta: 5:49:21, time: 0.793, data_time: 0.191, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0868, loss: 0.0868 +2025-06-25 04:07:12,336 - pyskl - INFO - Epoch [112][200/1281] lr: 3.914e-03, eta: 5:48:41, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0885, loss: 0.0885 +2025-06-25 04:08:01,102 - pyskl - INFO - Epoch [112][300/1281] lr: 3.899e-03, eta: 5:48:01, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1170, loss: 0.1170 +2025-06-25 04:08:49,862 - pyskl - INFO - Epoch [112][400/1281] lr: 3.884e-03, eta: 5:47:22, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0902, loss: 0.0902 +2025-06-25 04:09:38,874 - pyskl - INFO - Epoch [112][500/1281] lr: 3.869e-03, eta: 5:46:42, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0738, loss: 0.0738 +2025-06-25 04:10:27,840 - pyskl - INFO - Epoch [112][600/1281] lr: 3.854e-03, eta: 5:46:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0891, loss: 0.0891 +2025-06-25 04:11:17,022 - pyskl - INFO - Epoch [112][700/1281] lr: 3.840e-03, eta: 5:45:23, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0990, loss: 0.0990 +2025-06-25 04:12:06,198 - pyskl - INFO - Epoch [112][800/1281] lr: 3.825e-03, eta: 5:44:43, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1016, loss: 0.1016 +2025-06-25 04:12:55,087 - pyskl - INFO - Epoch [112][900/1281] lr: 3.810e-03, eta: 5:44:03, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0788, loss: 0.0788 +2025-06-25 04:13:43,998 - pyskl - INFO - Epoch [112][1000/1281] lr: 3.795e-03, eta: 5:43:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0603, loss: 0.0603 +2025-06-25 04:14:12,842 - pyskl - INFO - Epoch [112][1100/1281] lr: 3.781e-03, eta: 5:42:37, time: 0.288, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0777, loss: 0.0777 +2025-06-25 04:15:03,547 - pyskl - INFO - Epoch [112][1200/1281] lr: 3.766e-03, eta: 5:41:58, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0812, loss: 0.0812 +2025-06-25 04:15:24,667 - pyskl - INFO - Saving checkpoint at 112 epochs +2025-06-25 04:16:22,964 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:16:23,027 - pyskl - INFO - +top1_acc 0.9306 +top5_acc 0.9973 +2025-06-25 04:16:23,027 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:16:23,033 - pyskl - INFO - +mean_acc 0.9042 +2025-06-25 04:16:23,037 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_110.pth was removed +2025-06-25 04:16:23,209 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_112.pth. +2025-06-25 04:16:23,209 - pyskl - INFO - Best top1_acc is 0.9306 at 112 epoch. +2025-06-25 04:16:23,212 - pyskl - INFO - Epoch(val) [112][533] top1_acc: 0.9306, top5_acc: 0.9973, mean_class_accuracy: 0.9042 +2025-06-25 04:17:42,682 - pyskl - INFO - Epoch [113][100/1281] lr: 3.740e-03, eta: 5:40:43, time: 0.795, data_time: 0.191, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0701, loss: 0.0701 +2025-06-25 04:18:31,480 - pyskl - INFO - Epoch [113][200/1281] lr: 3.725e-03, eta: 5:40:03, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1121, loss: 0.1121 +2025-06-25 04:19:20,112 - pyskl - INFO - Epoch [113][300/1281] lr: 3.711e-03, eta: 5:39:23, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0972, loss: 0.0972 +2025-06-25 04:20:08,999 - pyskl - INFO - Epoch [113][400/1281] lr: 3.696e-03, eta: 5:38:43, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0737, loss: 0.0737 +2025-06-25 04:20:58,525 - pyskl - INFO - Epoch [113][500/1281] lr: 3.682e-03, eta: 5:38:04, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0537, loss: 0.0537 +2025-06-25 04:21:47,395 - pyskl - INFO - Epoch [113][600/1281] lr: 3.667e-03, eta: 5:37:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0762, loss: 0.0762 +2025-06-25 04:22:36,533 - pyskl - INFO - Epoch [113][700/1281] lr: 3.653e-03, eta: 5:36:44, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0753, loss: 0.0753 +2025-06-25 04:23:25,305 - pyskl - INFO - Epoch [113][800/1281] lr: 3.638e-03, eta: 5:36:04, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 0.9994, loss_cls: 0.0975, loss: 0.0975 +2025-06-25 04:24:14,315 - pyskl - INFO - Epoch [113][900/1281] lr: 3.624e-03, eta: 5:35:24, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0835, loss: 0.0835 +2025-06-25 04:25:03,262 - pyskl - INFO - Epoch [113][1000/1281] lr: 3.610e-03, eta: 5:34:45, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0776, loss: 0.0776 +2025-06-25 04:25:31,428 - pyskl - INFO - Epoch [113][1100/1281] lr: 3.595e-03, eta: 5:33:58, time: 0.282, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0820, loss: 0.0820 +2025-06-25 04:26:22,199 - pyskl - INFO - Epoch [113][1200/1281] lr: 3.581e-03, eta: 5:33:19, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0902, loss: 0.0902 +2025-06-25 04:26:43,867 - pyskl - INFO - Saving checkpoint at 113 epochs +2025-06-25 04:27:42,072 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:27:42,129 - pyskl - INFO - +top1_acc 0.9390 +top5_acc 0.9957 +2025-06-25 04:27:42,129 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:27:42,137 - pyskl - INFO - +mean_acc 0.9180 +2025-06-25 04:27:42,141 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_112.pth was removed +2025-06-25 04:27:42,323 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_113.pth. +2025-06-25 04:27:42,324 - pyskl - INFO - Best top1_acc is 0.9390 at 113 epoch. +2025-06-25 04:27:42,327 - pyskl - INFO - Epoch(val) [113][533] top1_acc: 0.9390, top5_acc: 0.9957, mean_class_accuracy: 0.9180 +2025-06-25 04:29:01,771 - pyskl - INFO - Epoch [114][100/1281] lr: 3.555e-03, eta: 5:32:03, time: 0.794, data_time: 0.192, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0860, loss: 0.0860 +2025-06-25 04:29:50,986 - pyskl - INFO - Epoch [114][200/1281] lr: 3.541e-03, eta: 5:31:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0768, loss: 0.0768 +2025-06-25 04:30:39,753 - pyskl - INFO - Epoch [114][300/1281] lr: 3.526e-03, eta: 5:30:44, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0927, loss: 0.0927 +2025-06-25 04:31:28,278 - pyskl - INFO - Epoch [114][400/1281] lr: 3.512e-03, eta: 5:30:04, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0780, loss: 0.0780 +2025-06-25 04:32:17,209 - pyskl - INFO - Epoch [114][500/1281] lr: 3.498e-03, eta: 5:29:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0843, loss: 0.0843 +2025-06-25 04:33:06,168 - pyskl - INFO - Epoch [114][600/1281] lr: 3.484e-03, eta: 5:28:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0811, loss: 0.0811 +2025-06-25 04:33:55,048 - pyskl - INFO - Epoch [114][700/1281] lr: 3.470e-03, eta: 5:28:04, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0669, loss: 0.0669 +2025-06-25 04:34:44,311 - pyskl - INFO - Epoch [114][800/1281] lr: 3.456e-03, eta: 5:27:24, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0819, loss: 0.0819 +2025-06-25 04:35:33,003 - pyskl - INFO - Epoch [114][900/1281] lr: 3.442e-03, eta: 5:26:44, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0805, loss: 0.0805 +2025-06-25 04:36:21,922 - pyskl - INFO - Epoch [114][1000/1281] lr: 3.427e-03, eta: 5:26:04, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0686, loss: 0.0686 +2025-06-25 04:36:50,257 - pyskl - INFO - Epoch [114][1100/1281] lr: 3.413e-03, eta: 5:25:17, time: 0.283, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.0963, loss: 0.0963 +2025-06-25 04:37:41,111 - pyskl - INFO - Epoch [114][1200/1281] lr: 3.399e-03, eta: 5:24:38, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0765, loss: 0.0765 +2025-06-25 04:38:03,108 - pyskl - INFO - Saving checkpoint at 114 epochs +2025-06-25 04:39:00,956 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:39:01,011 - pyskl - INFO - +top1_acc 0.9342 +top5_acc 0.9968 +2025-06-25 04:39:01,012 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:39:01,018 - pyskl - INFO - +mean_acc 0.9101 +2025-06-25 04:39:01,020 - pyskl - INFO - Epoch(val) [114][533] top1_acc: 0.9342, top5_acc: 0.9968, mean_class_accuracy: 0.9101 +2025-06-25 04:40:19,982 - pyskl - INFO - Epoch [115][100/1281] lr: 3.374e-03, eta: 5:23:22, time: 0.790, data_time: 0.188, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0758, loss: 0.0758 +2025-06-25 04:41:09,189 - pyskl - INFO - Epoch [115][200/1281] lr: 3.360e-03, eta: 5:22:42, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0871, loss: 0.0871 +2025-06-25 04:41:57,958 - pyskl - INFO - Epoch [115][300/1281] lr: 3.346e-03, eta: 5:22:02, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 0.9994, loss_cls: 0.0935, loss: 0.0935 +2025-06-25 04:42:46,903 - pyskl - INFO - Epoch [115][400/1281] lr: 3.332e-03, eta: 5:21:22, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0624, loss: 0.0624 +2025-06-25 04:43:36,015 - pyskl - INFO - Epoch [115][500/1281] lr: 3.318e-03, eta: 5:20:42, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0590, loss: 0.0590 +2025-06-25 04:44:24,744 - pyskl - INFO - Epoch [115][600/1281] lr: 3.305e-03, eta: 5:20:02, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0622, loss: 0.0622 +2025-06-25 04:45:13,795 - pyskl - INFO - Epoch [115][700/1281] lr: 3.291e-03, eta: 5:19:22, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0816, loss: 0.0816 +2025-06-25 04:46:02,897 - pyskl - INFO - Epoch [115][800/1281] lr: 3.277e-03, eta: 5:18:42, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0819, loss: 0.0819 +2025-06-25 04:46:51,664 - pyskl - INFO - Epoch [115][900/1281] lr: 3.263e-03, eta: 5:18:02, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1333, loss: 0.1333 +2025-06-25 04:47:40,649 - pyskl - INFO - Epoch [115][1000/1281] lr: 3.249e-03, eta: 5:17:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0675, loss: 0.0675 +2025-06-25 04:48:09,216 - pyskl - INFO - Epoch [115][1100/1281] lr: 3.236e-03, eta: 5:16:35, time: 0.286, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 0.9994, loss_cls: 0.0891, loss: 0.0891 +2025-06-25 04:48:59,969 - pyskl - INFO - Epoch [115][1200/1281] lr: 3.222e-03, eta: 5:15:56, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0633, loss: 0.0633 +2025-06-25 04:49:21,691 - pyskl - INFO - Saving checkpoint at 115 epochs +2025-06-25 04:50:20,502 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:50:20,561 - pyskl - INFO - +top1_acc 0.9365 +top5_acc 0.9968 +2025-06-25 04:50:20,561 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:50:20,569 - pyskl - INFO - +mean_acc 0.9163 +2025-06-25 04:50:20,571 - pyskl - INFO - Epoch(val) [115][533] top1_acc: 0.9365, top5_acc: 0.9968, mean_class_accuracy: 0.9163 +2025-06-25 04:51:41,109 - pyskl - INFO - Epoch [116][100/1281] lr: 3.197e-03, eta: 5:14:40, time: 0.805, data_time: 0.191, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0605, loss: 0.0605 +2025-06-25 04:52:30,373 - pyskl - INFO - Epoch [116][200/1281] lr: 3.184e-03, eta: 5:14:00, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0554, loss: 0.0554 +2025-06-25 04:53:19,322 - pyskl - INFO - Epoch [116][300/1281] lr: 3.170e-03, eta: 5:13:20, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0548, loss: 0.0548 +2025-06-25 04:54:08,044 - pyskl - INFO - Epoch [116][400/1281] lr: 3.156e-03, eta: 5:12:40, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0557, loss: 0.0557 +2025-06-25 04:54:56,784 - pyskl - INFO - Epoch [116][500/1281] lr: 3.143e-03, eta: 5:12:00, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0593, loss: 0.0593 +2025-06-25 04:55:45,635 - pyskl - INFO - Epoch [116][600/1281] lr: 3.129e-03, eta: 5:11:19, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0435, loss: 0.0435 +2025-06-25 04:56:34,652 - pyskl - INFO - Epoch [116][700/1281] lr: 3.116e-03, eta: 5:10:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0615, loss: 0.0615 +2025-06-25 04:57:23,871 - pyskl - INFO - Epoch [116][800/1281] lr: 3.102e-03, eta: 5:09:59, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0777, loss: 0.0777 +2025-06-25 04:58:12,828 - pyskl - INFO - Epoch [116][900/1281] lr: 3.089e-03, eta: 5:09:19, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0503, loss: 0.0503 +2025-06-25 04:59:01,714 - pyskl - INFO - Epoch [116][1000/1281] lr: 3.075e-03, eta: 5:08:39, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0681, loss: 0.0681 +2025-06-25 04:59:30,085 - pyskl - INFO - Epoch [116][1100/1281] lr: 3.062e-03, eta: 5:07:52, time: 0.284, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0610, loss: 0.0610 +2025-06-25 05:00:18,891 - pyskl - INFO - Epoch [116][1200/1281] lr: 3.049e-03, eta: 5:07:12, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0801, loss: 0.0801 +2025-06-25 05:00:41,054 - pyskl - INFO - Saving checkpoint at 116 epochs +2025-06-25 05:01:39,266 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:01:39,321 - pyskl - INFO - +top1_acc 0.9291 +top5_acc 0.9953 +2025-06-25 05:01:39,321 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:01:39,327 - pyskl - INFO - +mean_acc 0.9086 +2025-06-25 05:01:39,329 - pyskl - INFO - Epoch(val) [116][533] top1_acc: 0.9291, top5_acc: 0.9953, mean_class_accuracy: 0.9086 +2025-06-25 05:02:59,069 - pyskl - INFO - Epoch [117][100/1281] lr: 3.024e-03, eta: 5:05:56, time: 0.797, data_time: 0.189, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0667, loss: 0.0667 +2025-06-25 05:03:48,025 - pyskl - INFO - Epoch [117][200/1281] lr: 3.011e-03, eta: 5:05:16, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0569, loss: 0.0569 +2025-06-25 05:04:37,122 - pyskl - INFO - Epoch [117][300/1281] lr: 2.998e-03, eta: 5:04:36, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0688, loss: 0.0688 +2025-06-25 05:05:26,139 - pyskl - INFO - Epoch [117][400/1281] lr: 2.984e-03, eta: 5:03:56, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0545, loss: 0.0545 +2025-06-25 05:06:15,034 - pyskl - INFO - Epoch [117][500/1281] lr: 2.971e-03, eta: 5:03:15, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0567, loss: 0.0567 +2025-06-25 05:07:04,047 - pyskl - INFO - Epoch [117][600/1281] lr: 2.958e-03, eta: 5:02:35, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0521, loss: 0.0521 +2025-06-25 05:07:53,125 - pyskl - INFO - Epoch [117][700/1281] lr: 2.945e-03, eta: 5:01:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0610, loss: 0.0610 +2025-06-25 05:08:42,198 - pyskl - INFO - Epoch [117][800/1281] lr: 2.932e-03, eta: 5:01:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0682, loss: 0.0682 +2025-06-25 05:09:30,974 - pyskl - INFO - Epoch [117][900/1281] lr: 2.919e-03, eta: 5:00:34, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0474, loss: 0.0474 +2025-06-25 05:10:19,968 - pyskl - INFO - Epoch [117][1000/1281] lr: 2.905e-03, eta: 4:59:53, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0533, loss: 0.0533 +2025-06-25 05:10:47,681 - pyskl - INFO - Epoch [117][1100/1281] lr: 2.892e-03, eta: 4:59:07, time: 0.277, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0585, loss: 0.0585 +2025-06-25 05:11:38,400 - pyskl - INFO - Epoch [117][1200/1281] lr: 2.879e-03, eta: 4:58:27, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0693, loss: 0.0693 +2025-06-25 05:12:00,212 - pyskl - INFO - Saving checkpoint at 117 epochs +2025-06-25 05:12:58,186 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:12:58,242 - pyskl - INFO - +top1_acc 0.9356 +top5_acc 0.9962 +2025-06-25 05:12:58,242 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:12:58,249 - pyskl - INFO - +mean_acc 0.9062 +2025-06-25 05:12:58,250 - pyskl - INFO - Epoch(val) [117][533] top1_acc: 0.9356, top5_acc: 0.9962, mean_class_accuracy: 0.9062 +2025-06-25 05:14:17,712 - pyskl - INFO - Epoch [118][100/1281] lr: 2.856e-03, eta: 4:57:11, time: 0.795, data_time: 0.190, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0410, loss: 0.0410 +2025-06-25 05:15:06,667 - pyskl - INFO - Epoch [118][200/1281] lr: 2.843e-03, eta: 4:56:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0430, loss: 0.0430 +2025-06-25 05:15:55,583 - pyskl - INFO - Epoch [118][300/1281] lr: 2.830e-03, eta: 4:55:51, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0482, loss: 0.0482 +2025-06-25 05:16:44,702 - pyskl - INFO - Epoch [118][400/1281] lr: 2.817e-03, eta: 4:55:10, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0652, loss: 0.0652 +2025-06-25 05:17:33,750 - pyskl - INFO - Epoch [118][500/1281] lr: 2.804e-03, eta: 4:54:30, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0481, loss: 0.0481 +2025-06-25 05:18:22,553 - pyskl - INFO - Epoch [118][600/1281] lr: 2.791e-03, eta: 4:53:49, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0613, loss: 0.0613 +2025-06-25 05:19:11,569 - pyskl - INFO - Epoch [118][700/1281] lr: 2.778e-03, eta: 4:53:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0488, loss: 0.0488 +2025-06-25 05:20:00,617 - pyskl - INFO - Epoch [118][800/1281] lr: 2.765e-03, eta: 4:52:28, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0513, loss: 0.0513 +2025-06-25 05:20:49,477 - pyskl - INFO - Epoch [118][900/1281] lr: 2.753e-03, eta: 4:51:48, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0608, loss: 0.0608 +2025-06-25 05:21:38,303 - pyskl - INFO - Epoch [118][1000/1281] lr: 2.740e-03, eta: 4:51:07, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0573, loss: 0.0573 +2025-06-25 05:22:06,410 - pyskl - INFO - Epoch [118][1100/1281] lr: 2.727e-03, eta: 4:50:21, time: 0.281, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0677, loss: 0.0677 +2025-06-25 05:22:57,116 - pyskl - INFO - Epoch [118][1200/1281] lr: 2.714e-03, eta: 4:49:41, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0692, loss: 0.0692 +2025-06-25 05:23:19,014 - pyskl - INFO - Saving checkpoint at 118 epochs +2025-06-25 05:24:16,975 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:24:17,043 - pyskl - INFO - +top1_acc 0.9409 +top5_acc 0.9967 +2025-06-25 05:24:17,043 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:24:17,051 - pyskl - INFO - +mean_acc 0.9240 +2025-06-25 05:24:17,056 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_113.pth was removed +2025-06-25 05:24:17,268 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_118.pth. +2025-06-25 05:24:17,268 - pyskl - INFO - Best top1_acc is 0.9409 at 118 epoch. +2025-06-25 05:24:17,271 - pyskl - INFO - Epoch(val) [118][533] top1_acc: 0.9409, top5_acc: 0.9967, mean_class_accuracy: 0.9240 +2025-06-25 05:25:37,410 - pyskl - INFO - Epoch [119][100/1281] lr: 2.691e-03, eta: 4:48:25, time: 0.801, data_time: 0.194, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0375, loss: 0.0375 +2025-06-25 05:26:26,537 - pyskl - INFO - Epoch [119][200/1281] lr: 2.679e-03, eta: 4:47:45, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0513, loss: 0.0513 +2025-06-25 05:27:15,365 - pyskl - INFO - Epoch [119][300/1281] lr: 2.666e-03, eta: 4:47:04, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0378, loss: 0.0378 +2025-06-25 05:28:04,233 - pyskl - INFO - Epoch [119][400/1281] lr: 2.653e-03, eta: 4:46:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0349, loss: 0.0349 +2025-06-25 05:28:52,887 - pyskl - INFO - Epoch [119][500/1281] lr: 2.641e-03, eta: 4:45:43, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0520, loss: 0.0520 +2025-06-25 05:29:42,051 - pyskl - INFO - Epoch [119][600/1281] lr: 2.628e-03, eta: 4:45:03, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0432, loss: 0.0432 +2025-06-25 05:30:31,011 - pyskl - INFO - Epoch [119][700/1281] lr: 2.616e-03, eta: 4:44:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0461, loss: 0.0461 +2025-06-25 05:31:19,940 - pyskl - INFO - Epoch [119][800/1281] lr: 2.603e-03, eta: 4:43:41, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0633, loss: 0.0633 +2025-06-25 05:32:09,014 - pyskl - INFO - Epoch [119][900/1281] lr: 2.591e-03, eta: 4:43:01, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0536, loss: 0.0536 +2025-06-25 05:32:57,451 - pyskl - INFO - Epoch [119][1000/1281] lr: 2.578e-03, eta: 4:42:20, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0526, loss: 0.0526 +2025-06-25 05:33:25,301 - pyskl - INFO - Epoch [119][1100/1281] lr: 2.566e-03, eta: 4:41:34, time: 0.278, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0499, loss: 0.0499 +2025-06-25 05:34:16,128 - pyskl - INFO - Epoch [119][1200/1281] lr: 2.554e-03, eta: 4:40:54, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0536, loss: 0.0536 +2025-06-25 05:34:38,214 - pyskl - INFO - Saving checkpoint at 119 epochs +2025-06-25 05:35:36,014 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:35:36,083 - pyskl - INFO - +top1_acc 0.9378 +top5_acc 0.9964 +2025-06-25 05:35:36,083 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:35:36,091 - pyskl - INFO - +mean_acc 0.9150 +2025-06-25 05:35:36,093 - pyskl - INFO - Epoch(val) [119][533] top1_acc: 0.9378, top5_acc: 0.9964, mean_class_accuracy: 0.9150 +2025-06-25 05:36:56,343 - pyskl - INFO - Epoch [120][100/1281] lr: 2.531e-03, eta: 4:39:38, time: 0.802, data_time: 0.194, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0430, loss: 0.0430 +2025-06-25 05:37:45,382 - pyskl - INFO - Epoch [120][200/1281] lr: 2.519e-03, eta: 4:38:57, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0335, loss: 0.0335 +2025-06-25 05:38:33,930 - pyskl - INFO - Epoch [120][300/1281] lr: 2.507e-03, eta: 4:38:17, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0459, loss: 0.0459 +2025-06-25 05:39:22,774 - pyskl - INFO - Epoch [120][400/1281] lr: 2.494e-03, eta: 4:37:36, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0374, loss: 0.0374 +2025-06-25 05:40:11,849 - pyskl - INFO - Epoch [120][500/1281] lr: 2.482e-03, eta: 4:36:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0486, loss: 0.0486 +2025-06-25 05:41:01,070 - pyskl - INFO - Epoch [120][600/1281] lr: 2.470e-03, eta: 4:36:15, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0674, loss: 0.0674 +2025-06-25 05:41:49,860 - pyskl - INFO - Epoch [120][700/1281] lr: 2.458e-03, eta: 4:35:34, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0743, loss: 0.0743 +2025-06-25 05:42:38,899 - pyskl - INFO - Epoch [120][800/1281] lr: 2.446e-03, eta: 4:34:53, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0553, loss: 0.0553 +2025-06-25 05:43:27,848 - pyskl - INFO - Epoch [120][900/1281] lr: 2.433e-03, eta: 4:34:13, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0693, loss: 0.0693 +2025-06-25 05:44:16,622 - pyskl - INFO - Epoch [120][1000/1281] lr: 2.421e-03, eta: 4:33:32, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0585, loss: 0.0585 +2025-06-25 05:44:44,542 - pyskl - INFO - Epoch [120][1100/1281] lr: 2.409e-03, eta: 4:32:46, time: 0.279, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0630, loss: 0.0630 +2025-06-25 05:45:35,359 - pyskl - INFO - Epoch [120][1200/1281] lr: 2.397e-03, eta: 4:32:05, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0620, loss: 0.0620 +2025-06-25 05:45:57,423 - pyskl - INFO - Saving checkpoint at 120 epochs +2025-06-25 05:46:55,332 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:46:55,388 - pyskl - INFO - +top1_acc 0.9357 +top5_acc 0.9958 +2025-06-25 05:46:55,388 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:46:55,396 - pyskl - INFO - +mean_acc 0.9157 +2025-06-25 05:46:55,398 - pyskl - INFO - Epoch(val) [120][533] top1_acc: 0.9357, top5_acc: 0.9958, mean_class_accuracy: 0.9157 +2025-06-25 05:48:15,231 - pyskl - INFO - Epoch [121][100/1281] lr: 2.375e-03, eta: 4:30:49, time: 0.798, data_time: 0.188, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0693, loss: 0.0693 +2025-06-25 05:49:04,541 - pyskl - INFO - Epoch [121][200/1281] lr: 2.363e-03, eta: 4:30:09, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0423, loss: 0.0423 +2025-06-25 05:49:53,512 - pyskl - INFO - Epoch [121][300/1281] lr: 2.351e-03, eta: 4:29:28, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0412, loss: 0.0412 +2025-06-25 05:50:42,415 - pyskl - INFO - Epoch [121][400/1281] lr: 2.340e-03, eta: 4:28:47, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0418, loss: 0.0418 +2025-06-25 05:51:31,314 - pyskl - INFO - Epoch [121][500/1281] lr: 2.328e-03, eta: 4:28:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0571, loss: 0.0571 +2025-06-25 05:52:20,330 - pyskl - INFO - Epoch [121][600/1281] lr: 2.316e-03, eta: 4:27:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0460, loss: 0.0460 +2025-06-25 05:53:09,313 - pyskl - INFO - Epoch [121][700/1281] lr: 2.304e-03, eta: 4:26:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0421, loss: 0.0421 +2025-06-25 05:53:58,256 - pyskl - INFO - Epoch [121][800/1281] lr: 2.292e-03, eta: 4:26:04, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0386, loss: 0.0386 +2025-06-25 05:54:46,823 - pyskl - INFO - Epoch [121][900/1281] lr: 2.280e-03, eta: 4:25:23, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0572, loss: 0.0572 +2025-06-25 05:55:36,085 - pyskl - INFO - Epoch [121][1000/1281] lr: 2.269e-03, eta: 4:24:42, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0530, loss: 0.0530 +2025-06-25 05:56:05,021 - pyskl - INFO - Epoch [121][1100/1281] lr: 2.257e-03, eta: 4:23:57, time: 0.289, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0457, loss: 0.0457 +2025-06-25 05:56:55,754 - pyskl - INFO - Epoch [121][1200/1281] lr: 2.245e-03, eta: 4:23:16, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0525, loss: 0.0525 +2025-06-25 05:57:17,367 - pyskl - INFO - Saving checkpoint at 121 epochs +2025-06-25 05:58:15,568 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:58:15,636 - pyskl - INFO - +top1_acc 0.9380 +top5_acc 0.9959 +2025-06-25 05:58:15,636 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:58:15,644 - pyskl - INFO - +mean_acc 0.9163 +2025-06-25 05:58:15,646 - pyskl - INFO - Epoch(val) [121][533] top1_acc: 0.9380, top5_acc: 0.9959, mean_class_accuracy: 0.9163 +2025-06-25 05:59:34,496 - pyskl - INFO - Epoch [122][100/1281] lr: 2.224e-03, eta: 4:22:00, time: 0.788, data_time: 0.191, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0372, loss: 0.0372 +2025-06-25 06:00:23,400 - pyskl - INFO - Epoch [122][200/1281] lr: 2.212e-03, eta: 4:21:19, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0416, loss: 0.0416 +2025-06-25 06:01:12,672 - pyskl - INFO - Epoch [122][300/1281] lr: 2.201e-03, eta: 4:20:38, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0401, loss: 0.0401 +2025-06-25 06:02:01,490 - pyskl - INFO - Epoch [122][400/1281] lr: 2.189e-03, eta: 4:19:57, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0323, loss: 0.0323 +2025-06-25 06:02:50,814 - pyskl - INFO - Epoch [122][500/1281] lr: 2.178e-03, eta: 4:19:16, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0428, loss: 0.0428 +2025-06-25 06:03:40,072 - pyskl - INFO - Epoch [122][600/1281] lr: 2.166e-03, eta: 4:18:36, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0403, loss: 0.0403 +2025-06-25 06:04:29,246 - pyskl - INFO - Epoch [122][700/1281] lr: 2.155e-03, eta: 4:17:55, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0435, loss: 0.0435 +2025-06-25 06:05:18,196 - pyskl - INFO - Epoch [122][800/1281] lr: 2.143e-03, eta: 4:17:14, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0453, loss: 0.0453 +2025-06-25 06:06:07,082 - pyskl - INFO - Epoch [122][900/1281] lr: 2.132e-03, eta: 4:16:33, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0445, loss: 0.0445 +2025-06-25 06:06:55,897 - pyskl - INFO - Epoch [122][1000/1281] lr: 2.120e-03, eta: 4:15:52, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0394, loss: 0.0394 +2025-06-25 06:07:24,132 - pyskl - INFO - Epoch [122][1100/1281] lr: 2.109e-03, eta: 4:15:06, time: 0.282, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0366, loss: 0.0366 +2025-06-25 06:08:14,853 - pyskl - INFO - Epoch [122][1200/1281] lr: 2.098e-03, eta: 4:14:25, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0401, loss: 0.0401 +2025-06-25 06:08:36,015 - pyskl - INFO - Saving checkpoint at 122 epochs +2025-06-25 06:09:34,073 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:09:34,141 - pyskl - INFO - +top1_acc 0.9370 +top5_acc 0.9960 +2025-06-25 06:09:34,141 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:09:34,151 - pyskl - INFO - +mean_acc 0.9203 +2025-06-25 06:09:34,153 - pyskl - INFO - Epoch(val) [122][533] top1_acc: 0.9370, top5_acc: 0.9960, mean_class_accuracy: 0.9203 +2025-06-25 06:10:53,842 - pyskl - INFO - Epoch [123][100/1281] lr: 2.077e-03, eta: 4:13:09, time: 0.797, data_time: 0.190, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0378, loss: 0.0378 +2025-06-25 06:11:42,837 - pyskl - INFO - Epoch [123][200/1281] lr: 2.066e-03, eta: 4:12:28, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0365, loss: 0.0365 +2025-06-25 06:12:31,895 - pyskl - INFO - Epoch [123][300/1281] lr: 2.055e-03, eta: 4:11:47, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0348, loss: 0.0348 +2025-06-25 06:13:20,895 - pyskl - INFO - Epoch [123][400/1281] lr: 2.044e-03, eta: 4:11:06, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0284, loss: 0.0284 +2025-06-25 06:14:09,927 - pyskl - INFO - Epoch [123][500/1281] lr: 2.032e-03, eta: 4:10:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0343, loss: 0.0343 +2025-06-25 06:14:59,124 - pyskl - INFO - Epoch [123][600/1281] lr: 2.021e-03, eta: 4:09:44, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0329, loss: 0.0329 +2025-06-25 06:15:48,019 - pyskl - INFO - Epoch [123][700/1281] lr: 2.010e-03, eta: 4:09:03, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 0.9994, loss_cls: 0.0479, loss: 0.0479 +2025-06-25 06:16:36,787 - pyskl - INFO - Epoch [123][800/1281] lr: 1.999e-03, eta: 4:08:22, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0384, loss: 0.0384 +2025-06-25 06:17:25,704 - pyskl - INFO - Epoch [123][900/1281] lr: 1.988e-03, eta: 4:07:41, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0319, loss: 0.0319 +2025-06-25 06:18:14,669 - pyskl - INFO - Epoch [123][1000/1281] lr: 1.977e-03, eta: 4:07:00, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0326, loss: 0.0326 +2025-06-25 06:18:43,024 - pyskl - INFO - Epoch [123][1100/1281] lr: 1.966e-03, eta: 4:06:14, time: 0.284, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0317, loss: 0.0317 +2025-06-25 06:19:33,873 - pyskl - INFO - Epoch [123][1200/1281] lr: 1.955e-03, eta: 4:05:34, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0327, loss: 0.0327 +2025-06-25 06:19:55,391 - pyskl - INFO - Saving checkpoint at 123 epochs +2025-06-25 06:20:53,292 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:20:53,349 - pyskl - INFO - +top1_acc 0.9391 +top5_acc 0.9965 +2025-06-25 06:20:53,349 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:20:53,356 - pyskl - INFO - +mean_acc 0.9217 +2025-06-25 06:20:53,358 - pyskl - INFO - Epoch(val) [123][533] top1_acc: 0.9391, top5_acc: 0.9965, mean_class_accuracy: 0.9217 +2025-06-25 06:22:11,782 - pyskl - INFO - Epoch [124][100/1281] lr: 1.935e-03, eta: 4:04:17, time: 0.784, data_time: 0.188, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0294, loss: 0.0294 +2025-06-25 06:23:00,784 - pyskl - INFO - Epoch [124][200/1281] lr: 1.924e-03, eta: 4:03:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0382, loss: 0.0382 +2025-06-25 06:23:49,721 - pyskl - INFO - Epoch [124][300/1281] lr: 1.913e-03, eta: 4:02:55, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0353, loss: 0.0353 +2025-06-25 06:24:38,609 - pyskl - INFO - Epoch [124][400/1281] lr: 1.902e-03, eta: 4:02:14, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0451, loss: 0.0451 +2025-06-25 06:25:27,529 - pyskl - INFO - Epoch [124][500/1281] lr: 1.892e-03, eta: 4:01:33, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0350, loss: 0.0350 +2025-06-25 06:26:16,408 - pyskl - INFO - Epoch [124][600/1281] lr: 1.881e-03, eta: 4:00:51, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0361, loss: 0.0361 +2025-06-25 06:27:05,385 - pyskl - INFO - Epoch [124][700/1281] lr: 1.870e-03, eta: 4:00:10, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 0.9994, loss_cls: 0.0426, loss: 0.0426 +2025-06-25 06:27:54,411 - pyskl - INFO - Epoch [124][800/1281] lr: 1.859e-03, eta: 3:59:29, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0272, loss: 0.0272 +2025-06-25 06:28:43,099 - pyskl - INFO - Epoch [124][900/1281] lr: 1.849e-03, eta: 3:58:48, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0259, loss: 0.0259 +2025-06-25 06:29:32,174 - pyskl - INFO - Epoch [124][1000/1281] lr: 1.838e-03, eta: 3:58:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0287, loss: 0.0287 +2025-06-25 06:30:02,038 - pyskl - INFO - Epoch [124][1100/1281] lr: 1.827e-03, eta: 3:57:22, time: 0.299, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0307, loss: 0.0307 +2025-06-25 06:30:52,794 - pyskl - INFO - Epoch [124][1200/1281] lr: 1.817e-03, eta: 3:56:41, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0255, loss: 0.0255 +2025-06-25 06:31:13,963 - pyskl - INFO - Saving checkpoint at 124 epochs +2025-06-25 06:32:12,041 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:32:12,096 - pyskl - INFO - +top1_acc 0.9437 +top5_acc 0.9967 +2025-06-25 06:32:12,096 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:32:12,103 - pyskl - INFO - +mean_acc 0.9247 +2025-06-25 06:32:12,107 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_118.pth was removed +2025-06-25 06:32:12,266 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_124.pth. +2025-06-25 06:32:12,266 - pyskl - INFO - Best top1_acc is 0.9437 at 124 epoch. +2025-06-25 06:32:12,269 - pyskl - INFO - Epoch(val) [124][533] top1_acc: 0.9437, top5_acc: 0.9967, mean_class_accuracy: 0.9247 +2025-06-25 06:33:30,842 - pyskl - INFO - Epoch [125][100/1281] lr: 1.797e-03, eta: 3:55:24, time: 0.786, data_time: 0.185, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0279, loss: 0.0279 +2025-06-25 06:34:19,971 - pyskl - INFO - Epoch [125][200/1281] lr: 1.787e-03, eta: 3:54:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0347, loss: 0.0347 +2025-06-25 06:35:08,788 - pyskl - INFO - Epoch [125][300/1281] lr: 1.776e-03, eta: 3:54:02, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0317, loss: 0.0317 +2025-06-25 06:35:57,517 - pyskl - INFO - Epoch [125][400/1281] lr: 1.766e-03, eta: 3:53:20, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0290, loss: 0.0290 +2025-06-25 06:36:46,634 - pyskl - INFO - Epoch [125][500/1281] lr: 1.755e-03, eta: 3:52:39, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0266, loss: 0.0266 +2025-06-25 06:37:36,181 - pyskl - INFO - Epoch [125][600/1281] lr: 1.745e-03, eta: 3:51:58, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0262, loss: 0.0262 +2025-06-25 06:38:25,369 - pyskl - INFO - Epoch [125][700/1281] lr: 1.735e-03, eta: 3:51:17, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0379, loss: 0.0379 +2025-06-25 06:39:14,331 - pyskl - INFO - Epoch [125][800/1281] lr: 1.724e-03, eta: 3:50:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0432, loss: 0.0432 +2025-06-25 06:40:02,602 - pyskl - INFO - Epoch [125][900/1281] lr: 1.714e-03, eta: 3:49:54, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0447, loss: 0.0447 +2025-06-25 06:40:51,428 - pyskl - INFO - Epoch [125][1000/1281] lr: 1.704e-03, eta: 3:49:13, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0401, loss: 0.0401 +2025-06-25 06:41:21,808 - pyskl - INFO - Epoch [125][1100/1281] lr: 1.693e-03, eta: 3:48:28, time: 0.304, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0308, loss: 0.0308 +2025-06-25 06:42:12,524 - pyskl - INFO - Epoch [125][1200/1281] lr: 1.683e-03, eta: 3:47:47, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0328, loss: 0.0328 +2025-06-25 06:42:33,151 - pyskl - INFO - Saving checkpoint at 125 epochs +2025-06-25 06:43:31,047 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:43:31,102 - pyskl - INFO - +top1_acc 0.9404 +top5_acc 0.9967 +2025-06-25 06:43:31,103 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:43:31,110 - pyskl - INFO - +mean_acc 0.9203 +2025-06-25 06:43:31,112 - pyskl - INFO - Epoch(val) [125][533] top1_acc: 0.9404, top5_acc: 0.9967, mean_class_accuracy: 0.9203 +2025-06-25 06:44:49,977 - pyskl - INFO - Epoch [126][100/1281] lr: 1.665e-03, eta: 3:46:30, time: 0.789, data_time: 0.186, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0286, loss: 0.0286 +2025-06-25 06:45:39,135 - pyskl - INFO - Epoch [126][200/1281] lr: 1.654e-03, eta: 3:45:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0280, loss: 0.0280 +2025-06-25 06:46:28,291 - pyskl - INFO - Epoch [126][300/1281] lr: 1.644e-03, eta: 3:45:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0293, loss: 0.0293 +2025-06-25 06:47:16,952 - pyskl - INFO - Epoch [126][400/1281] lr: 1.634e-03, eta: 3:44:26, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0327, loss: 0.0327 +2025-06-25 06:48:05,885 - pyskl - INFO - Epoch [126][500/1281] lr: 1.624e-03, eta: 3:43:45, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0307, loss: 0.0307 +2025-06-25 06:48:55,028 - pyskl - INFO - Epoch [126][600/1281] lr: 1.614e-03, eta: 3:43:04, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0250, loss: 0.0250 +2025-06-25 06:49:43,938 - pyskl - INFO - Epoch [126][700/1281] lr: 1.604e-03, eta: 3:42:22, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0251, loss: 0.0251 +2025-06-25 06:50:32,352 - pyskl - INFO - Epoch [126][800/1281] lr: 1.594e-03, eta: 3:41:41, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0220, loss: 0.0220 +2025-06-25 06:51:21,082 - pyskl - INFO - Epoch [126][900/1281] lr: 1.584e-03, eta: 3:41:00, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0268, loss: 0.0268 +2025-06-25 06:52:09,963 - pyskl - INFO - Epoch [126][1000/1281] lr: 1.574e-03, eta: 3:40:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0303, loss: 0.0303 +2025-06-25 06:52:39,739 - pyskl - INFO - Epoch [126][1100/1281] lr: 1.564e-03, eta: 3:39:33, time: 0.298, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0374, loss: 0.0374 +2025-06-25 06:53:30,376 - pyskl - INFO - Epoch [126][1200/1281] lr: 1.554e-03, eta: 3:38:52, time: 0.506, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0350, loss: 0.0350 +2025-06-25 06:53:51,527 - pyskl - INFO - Saving checkpoint at 126 epochs +2025-06-25 06:54:49,740 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:54:49,809 - pyskl - INFO - +top1_acc 0.9434 +top5_acc 0.9972 +2025-06-25 06:54:49,809 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:54:49,818 - pyskl - INFO - +mean_acc 0.9251 +2025-06-25 06:54:49,820 - pyskl - INFO - Epoch(val) [126][533] top1_acc: 0.9434, top5_acc: 0.9972, mean_class_accuracy: 0.9251 +2025-06-25 06:56:08,472 - pyskl - INFO - Epoch [127][100/1281] lr: 1.536e-03, eta: 3:37:35, time: 0.786, data_time: 0.184, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0285, loss: 0.0285 +2025-06-25 06:56:57,330 - pyskl - INFO - Epoch [127][200/1281] lr: 1.527e-03, eta: 3:36:54, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0375, loss: 0.0375 +2025-06-25 06:57:46,191 - pyskl - INFO - Epoch [127][300/1281] lr: 1.517e-03, eta: 3:36:12, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0369, loss: 0.0369 +2025-06-25 06:58:35,296 - pyskl - INFO - Epoch [127][400/1281] lr: 1.507e-03, eta: 3:35:31, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0329, loss: 0.0329 +2025-06-25 06:59:24,217 - pyskl - INFO - Epoch [127][500/1281] lr: 1.497e-03, eta: 3:34:50, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0250, loss: 0.0250 +2025-06-25 07:00:12,900 - pyskl - INFO - Epoch [127][600/1281] lr: 1.488e-03, eta: 3:34:08, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0257, loss: 0.0257 +2025-06-25 07:01:02,110 - pyskl - INFO - Epoch [127][700/1281] lr: 1.478e-03, eta: 3:33:27, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0256, loss: 0.0256 +2025-06-25 07:01:50,822 - pyskl - INFO - Epoch [127][800/1281] lr: 1.468e-03, eta: 3:32:45, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0331, loss: 0.0331 +2025-06-25 07:02:39,446 - pyskl - INFO - Epoch [127][900/1281] lr: 1.459e-03, eta: 3:32:04, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0283, loss: 0.0283 +2025-06-25 07:03:28,166 - pyskl - INFO - Epoch [127][1000/1281] lr: 1.449e-03, eta: 3:31:22, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0323, loss: 0.0323 +2025-06-25 07:03:57,345 - pyskl - INFO - Epoch [127][1100/1281] lr: 1.440e-03, eta: 3:30:37, time: 0.292, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0280, loss: 0.0280 +2025-06-25 07:04:48,159 - pyskl - INFO - Epoch [127][1200/1281] lr: 1.430e-03, eta: 3:29:56, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0224, loss: 0.0224 +2025-06-25 07:05:09,781 - pyskl - INFO - Saving checkpoint at 127 epochs +2025-06-25 07:06:07,865 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:06:07,922 - pyskl - INFO - +top1_acc 0.9419 +top5_acc 0.9967 +2025-06-25 07:06:07,922 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:06:07,929 - pyskl - INFO - +mean_acc 0.9223 +2025-06-25 07:06:07,930 - pyskl - INFO - Epoch(val) [127][533] top1_acc: 0.9419, top5_acc: 0.9967, mean_class_accuracy: 0.9223 +2025-06-25 07:07:27,376 - pyskl - INFO - Epoch [128][100/1281] lr: 1.413e-03, eta: 3:28:39, time: 0.794, data_time: 0.188, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0275, loss: 0.0275 +2025-06-25 07:08:16,102 - pyskl - INFO - Epoch [128][200/1281] lr: 1.404e-03, eta: 3:27:58, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0261, loss: 0.0261 +2025-06-25 07:09:04,857 - pyskl - INFO - Epoch [128][300/1281] lr: 1.394e-03, eta: 3:27:16, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0231, loss: 0.0231 +2025-06-25 07:09:53,628 - pyskl - INFO - Epoch [128][400/1281] lr: 1.385e-03, eta: 3:26:34, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0238, loss: 0.0238 +2025-06-25 07:10:42,811 - pyskl - INFO - Epoch [128][500/1281] lr: 1.376e-03, eta: 3:25:53, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0238, loss: 0.0238 +2025-06-25 07:11:31,872 - pyskl - INFO - Epoch [128][600/1281] lr: 1.366e-03, eta: 3:25:11, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0234, loss: 0.0234 +2025-06-25 07:12:20,741 - pyskl - INFO - Epoch [128][700/1281] lr: 1.357e-03, eta: 3:24:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0224, loss: 0.0224 +2025-06-25 07:13:09,557 - pyskl - INFO - Epoch [128][800/1281] lr: 1.348e-03, eta: 3:23:48, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0314, loss: 0.0314 +2025-06-25 07:13:58,274 - pyskl - INFO - Epoch [128][900/1281] lr: 1.339e-03, eta: 3:23:07, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0239, loss: 0.0239 +2025-06-25 07:14:47,166 - pyskl - INFO - Epoch [128][1000/1281] lr: 1.329e-03, eta: 3:22:25, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0245, loss: 0.0245 +2025-06-25 07:15:15,889 - pyskl - INFO - Epoch [128][1100/1281] lr: 1.320e-03, eta: 3:21:40, time: 0.287, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0307, loss: 0.0307 +2025-06-25 07:16:06,628 - pyskl - INFO - Epoch [128][1200/1281] lr: 1.311e-03, eta: 3:20:59, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0244, loss: 0.0244 +2025-06-25 07:16:29,065 - pyskl - INFO - Saving checkpoint at 128 epochs +2025-06-25 07:17:27,432 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:17:27,489 - pyskl - INFO - +top1_acc 0.9432 +top5_acc 0.9968 +2025-06-25 07:17:27,489 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:17:27,495 - pyskl - INFO - +mean_acc 0.9227 +2025-06-25 07:17:27,497 - pyskl - INFO - Epoch(val) [128][533] top1_acc: 0.9432, top5_acc: 0.9968, mean_class_accuracy: 0.9227 +2025-06-25 07:18:47,173 - pyskl - INFO - Epoch [129][100/1281] lr: 1.295e-03, eta: 3:19:42, time: 0.797, data_time: 0.189, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0227, loss: 0.0227 +2025-06-25 07:19:36,324 - pyskl - INFO - Epoch [129][200/1281] lr: 1.286e-03, eta: 3:19:00, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0334, loss: 0.0334 +2025-06-25 07:20:25,304 - pyskl - INFO - Epoch [129][300/1281] lr: 1.277e-03, eta: 3:18:19, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0246, loss: 0.0246 +2025-06-25 07:21:14,308 - pyskl - INFO - Epoch [129][400/1281] lr: 1.268e-03, eta: 3:17:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0232, loss: 0.0232 +2025-06-25 07:22:03,384 - pyskl - INFO - Epoch [129][500/1281] lr: 1.259e-03, eta: 3:16:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 07:22:52,683 - pyskl - INFO - Epoch [129][600/1281] lr: 1.250e-03, eta: 3:16:14, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0270, loss: 0.0270 +2025-06-25 07:23:41,670 - pyskl - INFO - Epoch [129][700/1281] lr: 1.241e-03, eta: 3:15:32, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0218, loss: 0.0218 +2025-06-25 07:24:30,813 - pyskl - INFO - Epoch [129][800/1281] lr: 1.232e-03, eta: 3:14:51, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0237, loss: 0.0237 +2025-06-25 07:25:19,506 - pyskl - INFO - Epoch [129][900/1281] lr: 1.223e-03, eta: 3:14:09, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0240, loss: 0.0240 +2025-06-25 07:26:08,350 - pyskl - INFO - Epoch [129][1000/1281] lr: 1.214e-03, eta: 3:13:27, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0260, loss: 0.0260 +2025-06-25 07:26:36,855 - pyskl - INFO - Epoch [129][1100/1281] lr: 1.206e-03, eta: 3:12:42, time: 0.285, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 07:27:26,681 - pyskl - INFO - Epoch [129][1200/1281] lr: 1.197e-03, eta: 3:12:01, time: 0.498, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0276, loss: 0.0276 +2025-06-25 07:27:49,121 - pyskl - INFO - Saving checkpoint at 129 epochs +2025-06-25 07:28:47,127 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:28:47,191 - pyskl - INFO - +top1_acc 0.9431 +top5_acc 0.9968 +2025-06-25 07:28:47,191 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:28:47,199 - pyskl - INFO - +mean_acc 0.9255 +2025-06-25 07:28:47,201 - pyskl - INFO - Epoch(val) [129][533] top1_acc: 0.9431, top5_acc: 0.9968, mean_class_accuracy: 0.9255 +2025-06-25 07:30:07,384 - pyskl - INFO - Epoch [130][100/1281] lr: 1.181e-03, eta: 3:10:44, time: 0.802, data_time: 0.189, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0257, loss: 0.0257 +2025-06-25 07:30:56,560 - pyskl - INFO - Epoch [130][200/1281] lr: 1.172e-03, eta: 3:10:02, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0230, loss: 0.0230 +2025-06-25 07:31:45,422 - pyskl - INFO - Epoch [130][300/1281] lr: 1.164e-03, eta: 3:09:21, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0276, loss: 0.0276 +2025-06-25 07:32:34,015 - pyskl - INFO - Epoch [130][400/1281] lr: 1.155e-03, eta: 3:08:39, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0282, loss: 0.0282 +2025-06-25 07:33:23,174 - pyskl - INFO - Epoch [130][500/1281] lr: 1.147e-03, eta: 3:07:57, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0228, loss: 0.0228 +2025-06-25 07:34:12,123 - pyskl - INFO - Epoch [130][600/1281] lr: 1.138e-03, eta: 3:07:15, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0228, loss: 0.0228 +2025-06-25 07:35:00,763 - pyskl - INFO - Epoch [130][700/1281] lr: 1.130e-03, eta: 3:06:34, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0227, loss: 0.0227 +2025-06-25 07:35:49,270 - pyskl - INFO - Epoch [130][800/1281] lr: 1.121e-03, eta: 3:05:52, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0275, loss: 0.0275 +2025-06-25 07:36:37,576 - pyskl - INFO - Epoch [130][900/1281] lr: 1.113e-03, eta: 3:05:10, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0287, loss: 0.0287 +2025-06-25 07:37:26,328 - pyskl - INFO - Epoch [130][1000/1281] lr: 1.104e-03, eta: 3:04:28, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0230, loss: 0.0230 +2025-06-25 07:37:54,643 - pyskl - INFO - Epoch [130][1100/1281] lr: 1.096e-03, eta: 3:03:43, time: 0.283, data_time: 0.001, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-25 07:38:45,047 - pyskl - INFO - Epoch [130][1200/1281] lr: 1.088e-03, eta: 3:03:02, time: 0.504, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 07:39:06,786 - pyskl - INFO - Saving checkpoint at 130 epochs +2025-06-25 07:40:04,976 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:40:05,035 - pyskl - INFO - +top1_acc 0.9454 +top5_acc 0.9971 +2025-06-25 07:40:05,035 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:40:05,041 - pyskl - INFO - +mean_acc 0.9283 +2025-06-25 07:40:05,045 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_124.pth was removed +2025-06-25 07:40:05,212 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_130.pth. +2025-06-25 07:40:05,212 - pyskl - INFO - Best top1_acc is 0.9454 at 130 epoch. +2025-06-25 07:40:05,215 - pyskl - INFO - Epoch(val) [130][533] top1_acc: 0.9454, top5_acc: 0.9971, mean_class_accuracy: 0.9283 +2025-06-25 07:41:24,025 - pyskl - INFO - Epoch [131][100/1281] lr: 1.072e-03, eta: 3:01:44, time: 0.788, data_time: 0.189, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0218, loss: 0.0218 +2025-06-25 07:42:12,825 - pyskl - INFO - Epoch [131][200/1281] lr: 1.064e-03, eta: 3:01:03, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0217, loss: 0.0217 +2025-06-25 07:43:01,833 - pyskl - INFO - Epoch [131][300/1281] lr: 1.056e-03, eta: 3:00:21, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 07:43:50,653 - pyskl - INFO - Epoch [131][400/1281] lr: 1.048e-03, eta: 2:59:39, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-25 07:44:39,785 - pyskl - INFO - Epoch [131][500/1281] lr: 1.040e-03, eta: 2:58:57, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-25 07:45:28,554 - pyskl - INFO - Epoch [131][600/1281] lr: 1.031e-03, eta: 2:58:15, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-25 07:46:17,555 - pyskl - INFO - Epoch [131][700/1281] lr: 1.023e-03, eta: 2:57:34, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 07:47:06,939 - pyskl - INFO - Epoch [131][800/1281] lr: 1.015e-03, eta: 2:56:52, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0260, loss: 0.0260 +2025-06-25 07:47:55,673 - pyskl - INFO - Epoch [131][900/1281] lr: 1.007e-03, eta: 2:56:10, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0245, loss: 0.0245 +2025-06-25 07:48:44,644 - pyskl - INFO - Epoch [131][1000/1281] lr: 9.992e-04, eta: 2:55:28, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-25 07:49:13,577 - pyskl - INFO - Epoch [131][1100/1281] lr: 9.912e-04, eta: 2:54:43, time: 0.289, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-25 07:50:04,532 - pyskl - INFO - Epoch [131][1200/1281] lr: 9.832e-04, eta: 2:54:02, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0215, loss: 0.0215 +2025-06-25 07:50:26,125 - pyskl - INFO - Saving checkpoint at 131 epochs +2025-06-25 07:51:24,272 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:51:24,333 - pyskl - INFO - +top1_acc 0.9453 +top5_acc 0.9966 +2025-06-25 07:51:24,333 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:51:24,340 - pyskl - INFO - +mean_acc 0.9262 +2025-06-25 07:51:24,341 - pyskl - INFO - Epoch(val) [131][533] top1_acc: 0.9453, top5_acc: 0.9966, mean_class_accuracy: 0.9262 +2025-06-25 07:52:44,518 - pyskl - INFO - Epoch [132][100/1281] lr: 9.689e-04, eta: 2:52:45, time: 0.802, data_time: 0.187, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 07:53:33,339 - pyskl - INFO - Epoch [132][200/1281] lr: 9.610e-04, eta: 2:52:03, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-25 07:54:22,624 - pyskl - INFO - Epoch [132][300/1281] lr: 9.532e-04, eta: 2:51:21, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 07:55:11,566 - pyskl - INFO - Epoch [132][400/1281] lr: 9.454e-04, eta: 2:50:39, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0242, loss: 0.0242 +2025-06-25 07:56:00,783 - pyskl - INFO - Epoch [132][500/1281] lr: 9.376e-04, eta: 2:49:57, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-25 07:56:49,621 - pyskl - INFO - Epoch [132][600/1281] lr: 9.298e-04, eta: 2:49:15, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0219, loss: 0.0219 +2025-06-25 07:57:38,636 - pyskl - INFO - Epoch [132][700/1281] lr: 9.221e-04, eta: 2:48:33, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 07:58:27,469 - pyskl - INFO - Epoch [132][800/1281] lr: 9.144e-04, eta: 2:47:52, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0223, loss: 0.0223 +2025-06-25 07:59:16,096 - pyskl - INFO - Epoch [132][900/1281] lr: 9.068e-04, eta: 2:47:10, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-25 08:00:04,460 - pyskl - INFO - Epoch [132][1000/1281] lr: 8.991e-04, eta: 2:46:28, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-25 08:00:32,422 - pyskl - INFO - Epoch [132][1100/1281] lr: 8.915e-04, eta: 2:45:43, time: 0.280, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0220, loss: 0.0220 +2025-06-25 08:01:23,102 - pyskl - INFO - Epoch [132][1200/1281] lr: 8.840e-04, eta: 2:45:01, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 08:01:44,551 - pyskl - INFO - Saving checkpoint at 132 epochs +2025-06-25 08:02:42,819 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:02:42,887 - pyskl - INFO - +top1_acc 0.9440 +top5_acc 0.9967 +2025-06-25 08:02:42,887 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:02:42,896 - pyskl - INFO - +mean_acc 0.9266 +2025-06-25 08:02:42,898 - pyskl - INFO - Epoch(val) [132][533] top1_acc: 0.9440, top5_acc: 0.9967, mean_class_accuracy: 0.9266 +2025-06-25 08:04:02,834 - pyskl - INFO - Epoch [133][100/1281] lr: 8.704e-04, eta: 2:43:44, time: 0.799, data_time: 0.186, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0246, loss: 0.0246 +2025-06-25 08:04:51,833 - pyskl - INFO - Epoch [133][200/1281] lr: 8.629e-04, eta: 2:43:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0233, loss: 0.0233 +2025-06-25 08:05:40,861 - pyskl - INFO - Epoch [133][300/1281] lr: 8.554e-04, eta: 2:42:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0230, loss: 0.0230 +2025-06-25 08:06:29,943 - pyskl - INFO - Epoch [133][400/1281] lr: 8.480e-04, eta: 2:41:38, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0219, loss: 0.0219 +2025-06-25 08:07:18,901 - pyskl - INFO - Epoch [133][500/1281] lr: 8.406e-04, eta: 2:40:56, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0223, loss: 0.0223 +2025-06-25 08:08:07,581 - pyskl - INFO - Epoch [133][600/1281] lr: 8.333e-04, eta: 2:40:14, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0278, loss: 0.0278 +2025-06-25 08:08:56,394 - pyskl - INFO - Epoch [133][700/1281] lr: 8.260e-04, eta: 2:39:32, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0209, loss: 0.0209 +2025-06-25 08:09:45,143 - pyskl - INFO - Epoch [133][800/1281] lr: 8.187e-04, eta: 2:38:50, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-25 08:10:34,061 - pyskl - INFO - Epoch [133][900/1281] lr: 8.114e-04, eta: 2:38:08, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0281, loss: 0.0281 +2025-06-25 08:11:22,653 - pyskl - INFO - Epoch [133][1000/1281] lr: 8.042e-04, eta: 2:37:26, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-25 08:11:50,592 - pyskl - INFO - Epoch [133][1100/1281] lr: 7.970e-04, eta: 2:36:41, time: 0.279, data_time: 0.001, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-25 08:12:41,432 - pyskl - INFO - Epoch [133][1200/1281] lr: 7.898e-04, eta: 2:35:59, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0220, loss: 0.0220 +2025-06-25 08:13:03,006 - pyskl - INFO - Saving checkpoint at 133 epochs +2025-06-25 08:14:01,036 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:14:01,104 - pyskl - INFO - +top1_acc 0.9431 +top5_acc 0.9969 +2025-06-25 08:14:01,105 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:14:01,112 - pyskl - INFO - +mean_acc 0.9242 +2025-06-25 08:14:01,114 - pyskl - INFO - Epoch(val) [133][533] top1_acc: 0.9431, top5_acc: 0.9969, mean_class_accuracy: 0.9242 +2025-06-25 08:15:19,938 - pyskl - INFO - Epoch [134][100/1281] lr: 7.769e-04, eta: 2:34:42, time: 0.788, data_time: 0.188, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 08:16:08,670 - pyskl - INFO - Epoch [134][200/1281] lr: 7.699e-04, eta: 2:34:00, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0242, loss: 0.0242 +2025-06-25 08:16:57,392 - pyskl - INFO - Epoch [134][300/1281] lr: 7.628e-04, eta: 2:33:18, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0214, loss: 0.0214 +2025-06-25 08:17:46,505 - pyskl - INFO - Epoch [134][400/1281] lr: 7.558e-04, eta: 2:32:36, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-25 08:18:35,279 - pyskl - INFO - Epoch [134][500/1281] lr: 7.488e-04, eta: 2:31:54, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0275, loss: 0.0275 +2025-06-25 08:19:24,105 - pyskl - INFO - Epoch [134][600/1281] lr: 7.419e-04, eta: 2:31:12, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 08:20:12,956 - pyskl - INFO - Epoch [134][700/1281] lr: 7.349e-04, eta: 2:30:29, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-25 08:21:01,898 - pyskl - INFO - Epoch [134][800/1281] lr: 7.281e-04, eta: 2:29:47, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 08:21:50,708 - pyskl - INFO - Epoch [134][900/1281] lr: 7.212e-04, eta: 2:29:05, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0234, loss: 0.0234 +2025-06-25 08:22:39,491 - pyskl - INFO - Epoch [134][1000/1281] lr: 7.144e-04, eta: 2:28:23, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0222, loss: 0.0222 +2025-06-25 08:23:09,147 - pyskl - INFO - Epoch [134][1100/1281] lr: 7.076e-04, eta: 2:27:39, time: 0.297, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 08:23:59,959 - pyskl - INFO - Epoch [134][1200/1281] lr: 7.008e-04, eta: 2:26:57, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 08:24:20,835 - pyskl - INFO - Saving checkpoint at 134 epochs +2025-06-25 08:25:18,701 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:25:18,759 - pyskl - INFO - +top1_acc 0.9458 +top5_acc 0.9971 +2025-06-25 08:25:18,759 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:25:18,765 - pyskl - INFO - +mean_acc 0.9286 +2025-06-25 08:25:18,770 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_130.pth was removed +2025-06-25 08:25:18,955 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_134.pth. +2025-06-25 08:25:18,955 - pyskl - INFO - Best top1_acc is 0.9458 at 134 epoch. +2025-06-25 08:25:18,959 - pyskl - INFO - Epoch(val) [134][533] top1_acc: 0.9458, top5_acc: 0.9971, mean_class_accuracy: 0.9286 +2025-06-25 08:26:38,479 - pyskl - INFO - Epoch [135][100/1281] lr: 6.887e-04, eta: 2:25:39, time: 0.795, data_time: 0.194, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0233, loss: 0.0233 +2025-06-25 08:27:27,417 - pyskl - INFO - Epoch [135][200/1281] lr: 6.820e-04, eta: 2:24:57, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0223, loss: 0.0223 +2025-06-25 08:28:16,222 - pyskl - INFO - Epoch [135][300/1281] lr: 6.753e-04, eta: 2:24:15, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0245, loss: 0.0245 +2025-06-25 08:29:05,350 - pyskl - INFO - Epoch [135][400/1281] lr: 6.687e-04, eta: 2:23:33, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 08:29:54,183 - pyskl - INFO - Epoch [135][500/1281] lr: 6.622e-04, eta: 2:22:51, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0236, loss: 0.0236 +2025-06-25 08:30:43,186 - pyskl - INFO - Epoch [135][600/1281] lr: 6.556e-04, eta: 2:22:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 08:31:32,185 - pyskl - INFO - Epoch [135][700/1281] lr: 6.491e-04, eta: 2:21:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0221, loss: 0.0221 +2025-06-25 08:32:21,051 - pyskl - INFO - Epoch [135][800/1281] lr: 6.426e-04, eta: 2:20:44, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 08:33:10,035 - pyskl - INFO - Epoch [135][900/1281] lr: 6.362e-04, eta: 2:20:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0204, loss: 0.0204 +2025-06-25 08:33:58,754 - pyskl - INFO - Epoch [135][1000/1281] lr: 6.297e-04, eta: 2:19:20, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-25 08:34:27,091 - pyskl - INFO - Epoch [135][1100/1281] lr: 6.233e-04, eta: 2:18:35, time: 0.283, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0204, loss: 0.0204 +2025-06-25 08:35:17,872 - pyskl - INFO - Epoch [135][1200/1281] lr: 6.170e-04, eta: 2:17:53, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 08:35:39,674 - pyskl - INFO - Saving checkpoint at 135 epochs +2025-06-25 08:36:37,577 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:36:37,633 - pyskl - INFO - +top1_acc 0.9454 +top5_acc 0.9971 +2025-06-25 08:36:37,633 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:36:37,641 - pyskl - INFO - +mean_acc 0.9261 +2025-06-25 08:36:37,643 - pyskl - INFO - Epoch(val) [135][533] top1_acc: 0.9454, top5_acc: 0.9971, mean_class_accuracy: 0.9261 +2025-06-25 08:37:57,471 - pyskl - INFO - Epoch [136][100/1281] lr: 6.056e-04, eta: 2:16:36, time: 0.798, data_time: 0.186, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-25 08:38:46,385 - pyskl - INFO - Epoch [136][200/1281] lr: 5.993e-04, eta: 2:15:54, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0241, loss: 0.0241 +2025-06-25 08:39:35,283 - pyskl - INFO - Epoch [136][300/1281] lr: 5.931e-04, eta: 2:15:12, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 08:40:24,229 - pyskl - INFO - Epoch [136][400/1281] lr: 5.868e-04, eta: 2:14:29, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-25 08:41:13,259 - pyskl - INFO - Epoch [136][500/1281] lr: 5.807e-04, eta: 2:13:47, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0220, loss: 0.0220 +2025-06-25 08:42:02,099 - pyskl - INFO - Epoch [136][600/1281] lr: 5.745e-04, eta: 2:13:05, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 08:42:50,798 - pyskl - INFO - Epoch [136][700/1281] lr: 5.684e-04, eta: 2:12:23, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 08:43:39,633 - pyskl - INFO - Epoch [136][800/1281] lr: 5.623e-04, eta: 2:11:40, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 08:44:28,600 - pyskl - INFO - Epoch [136][900/1281] lr: 5.563e-04, eta: 2:10:58, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0233, loss: 0.0233 +2025-06-25 08:45:17,707 - pyskl - INFO - Epoch [136][1000/1281] lr: 5.503e-04, eta: 2:10:16, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-25 08:45:46,523 - pyskl - INFO - Epoch [136][1100/1281] lr: 5.443e-04, eta: 2:09:31, time: 0.288, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0204, loss: 0.0204 +2025-06-25 08:46:37,451 - pyskl - INFO - Epoch [136][1200/1281] lr: 5.384e-04, eta: 2:08:49, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 08:46:58,758 - pyskl - INFO - Saving checkpoint at 136 epochs +2025-06-25 08:47:56,858 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:47:56,914 - pyskl - INFO - +top1_acc 0.9452 +top5_acc 0.9973 +2025-06-25 08:47:56,914 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:47:56,921 - pyskl - INFO - +mean_acc 0.9238 +2025-06-25 08:47:56,923 - pyskl - INFO - Epoch(val) [136][533] top1_acc: 0.9452, top5_acc: 0.9973, mean_class_accuracy: 0.9238 +2025-06-25 08:49:15,908 - pyskl - INFO - Epoch [137][100/1281] lr: 5.277e-04, eta: 2:07:32, time: 0.790, data_time: 0.185, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0221, loss: 0.0221 +2025-06-25 08:50:04,893 - pyskl - INFO - Epoch [137][200/1281] lr: 5.218e-04, eta: 2:06:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0214, loss: 0.0214 +2025-06-25 08:50:54,034 - pyskl - INFO - Epoch [137][300/1281] lr: 5.160e-04, eta: 2:06:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 08:51:42,707 - pyskl - INFO - Epoch [137][400/1281] lr: 5.102e-04, eta: 2:05:25, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0200, loss: 0.0200 +2025-06-25 08:52:32,066 - pyskl - INFO - Epoch [137][500/1281] lr: 5.044e-04, eta: 2:04:43, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 08:53:21,154 - pyskl - INFO - Epoch [137][600/1281] lr: 4.987e-04, eta: 2:04:00, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 08:54:09,820 - pyskl - INFO - Epoch [137][700/1281] lr: 4.930e-04, eta: 2:03:18, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0221, loss: 0.0221 +2025-06-25 08:54:58,847 - pyskl - INFO - Epoch [137][800/1281] lr: 4.873e-04, eta: 2:02:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0262, loss: 0.0262 +2025-06-25 08:55:47,776 - pyskl - INFO - Epoch [137][900/1281] lr: 4.817e-04, eta: 2:01:53, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0231, loss: 0.0231 +2025-06-25 08:56:37,030 - pyskl - INFO - Epoch [137][1000/1281] lr: 4.761e-04, eta: 2:01:11, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 08:57:06,457 - pyskl - INFO - Epoch [137][1100/1281] lr: 4.705e-04, eta: 2:00:27, time: 0.294, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 08:57:57,196 - pyskl - INFO - Epoch [137][1200/1281] lr: 4.650e-04, eta: 1:59:45, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 08:58:19,188 - pyskl - INFO - Saving checkpoint at 137 epochs +2025-06-25 08:59:17,365 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:59:17,423 - pyskl - INFO - +top1_acc 0.9451 +top5_acc 0.9973 +2025-06-25 08:59:17,423 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:59:17,430 - pyskl - INFO - +mean_acc 0.9239 +2025-06-25 08:59:17,432 - pyskl - INFO - Epoch(val) [137][533] top1_acc: 0.9451, top5_acc: 0.9973, mean_class_accuracy: 0.9239 +2025-06-25 09:00:36,145 - pyskl - INFO - Epoch [138][100/1281] lr: 4.550e-04, eta: 1:58:27, time: 0.787, data_time: 0.185, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-25 09:01:24,953 - pyskl - INFO - Epoch [138][200/1281] lr: 4.496e-04, eta: 1:57:45, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-25 09:02:13,860 - pyskl - INFO - Epoch [138][300/1281] lr: 4.442e-04, eta: 1:57:02, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 09:03:02,494 - pyskl - INFO - Epoch [138][400/1281] lr: 4.388e-04, eta: 1:56:20, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 09:03:51,514 - pyskl - INFO - Epoch [138][500/1281] lr: 4.334e-04, eta: 1:55:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 09:04:40,202 - pyskl - INFO - Epoch [138][600/1281] lr: 4.281e-04, eta: 1:54:55, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-25 09:05:29,167 - pyskl - INFO - Epoch [138][700/1281] lr: 4.228e-04, eta: 1:54:13, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-25 09:06:18,466 - pyskl - INFO - Epoch [138][800/1281] lr: 4.176e-04, eta: 1:53:30, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 09:07:07,263 - pyskl - INFO - Epoch [138][900/1281] lr: 4.124e-04, eta: 1:52:48, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-25 09:07:56,200 - pyskl - INFO - Epoch [138][1000/1281] lr: 4.072e-04, eta: 1:52:05, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0219, loss: 0.0219 +2025-06-25 09:08:24,957 - pyskl - INFO - Epoch [138][1100/1281] lr: 4.020e-04, eta: 1:51:21, time: 0.288, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0228, loss: 0.0228 +2025-06-25 09:09:15,663 - pyskl - INFO - Epoch [138][1200/1281] lr: 3.969e-04, eta: 1:50:39, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-25 09:09:37,092 - pyskl - INFO - Saving checkpoint at 138 epochs +2025-06-25 09:10:35,217 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:10:35,273 - pyskl - INFO - +top1_acc 0.9455 +top5_acc 0.9969 +2025-06-25 09:10:35,273 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:10:35,280 - pyskl - INFO - +mean_acc 0.9268 +2025-06-25 09:10:35,282 - pyskl - INFO - Epoch(val) [138][533] top1_acc: 0.9455, top5_acc: 0.9969, mean_class_accuracy: 0.9268 +2025-06-25 09:11:54,545 - pyskl - INFO - Epoch [139][100/1281] lr: 3.877e-04, eta: 1:49:21, time: 0.793, data_time: 0.190, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-25 09:12:43,633 - pyskl - INFO - Epoch [139][200/1281] lr: 3.827e-04, eta: 1:48:39, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 09:13:32,751 - pyskl - INFO - Epoch [139][300/1281] lr: 3.777e-04, eta: 1:47:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0230, loss: 0.0230 +2025-06-25 09:14:21,937 - pyskl - INFO - Epoch [139][400/1281] lr: 3.727e-04, eta: 1:47:14, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 09:15:10,769 - pyskl - INFO - Epoch [139][500/1281] lr: 3.678e-04, eta: 1:46:31, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-25 09:15:59,897 - pyskl - INFO - Epoch [139][600/1281] lr: 3.628e-04, eta: 1:45:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 09:16:48,920 - pyskl - INFO - Epoch [139][700/1281] lr: 3.580e-04, eta: 1:45:06, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 09:17:37,742 - pyskl - INFO - Epoch [139][800/1281] lr: 3.531e-04, eta: 1:44:24, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 09:18:26,667 - pyskl - INFO - Epoch [139][900/1281] lr: 3.483e-04, eta: 1:43:41, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 09:19:15,337 - pyskl - INFO - Epoch [139][1000/1281] lr: 3.436e-04, eta: 1:42:59, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 09:19:44,575 - pyskl - INFO - Epoch [139][1100/1281] lr: 3.388e-04, eta: 1:42:15, time: 0.292, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-25 09:20:35,352 - pyskl - INFO - Epoch [139][1200/1281] lr: 3.341e-04, eta: 1:41:32, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 09:20:56,845 - pyskl - INFO - Saving checkpoint at 139 epochs +2025-06-25 09:21:54,716 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:21:54,772 - pyskl - INFO - +top1_acc 0.9475 +top5_acc 0.9974 +2025-06-25 09:21:54,772 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:21:54,778 - pyskl - INFO - +mean_acc 0.9287 +2025-06-25 09:21:54,782 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_134.pth was removed +2025-06-25 09:21:54,951 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_139.pth. +2025-06-25 09:21:54,951 - pyskl - INFO - Best top1_acc is 0.9475 at 139 epoch. +2025-06-25 09:21:54,954 - pyskl - INFO - Epoch(val) [139][533] top1_acc: 0.9475, top5_acc: 0.9974, mean_class_accuracy: 0.9287 +2025-06-25 09:23:12,491 - pyskl - INFO - Epoch [140][100/1281] lr: 3.257e-04, eta: 1:40:15, time: 0.775, data_time: 0.183, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 09:24:01,332 - pyskl - INFO - Epoch [140][200/1281] lr: 3.210e-04, eta: 1:39:32, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 09:24:50,334 - pyskl - INFO - Epoch [140][300/1281] lr: 3.165e-04, eta: 1:38:49, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 09:25:38,951 - pyskl - INFO - Epoch [140][400/1281] lr: 3.119e-04, eta: 1:38:07, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 09:26:27,815 - pyskl - INFO - Epoch [140][500/1281] lr: 3.074e-04, eta: 1:37:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 09:27:17,413 - pyskl - INFO - Epoch [140][600/1281] lr: 3.029e-04, eta: 1:36:42, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 09:28:06,515 - pyskl - INFO - Epoch [140][700/1281] lr: 2.984e-04, eta: 1:35:59, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 09:28:55,675 - pyskl - INFO - Epoch [140][800/1281] lr: 2.940e-04, eta: 1:35:17, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 09:29:44,741 - pyskl - INFO - Epoch [140][900/1281] lr: 2.896e-04, eta: 1:34:34, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 09:30:33,955 - pyskl - INFO - Epoch [140][1000/1281] lr: 2.853e-04, eta: 1:33:52, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 09:31:04,871 - pyskl - INFO - Epoch [140][1100/1281] lr: 2.809e-04, eta: 1:33:08, time: 0.309, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 09:31:55,544 - pyskl - INFO - Epoch [140][1200/1281] lr: 2.767e-04, eta: 1:32:25, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-25 09:32:16,120 - pyskl - INFO - Saving checkpoint at 140 epochs +2025-06-25 09:33:14,388 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:33:14,443 - pyskl - INFO - +top1_acc 0.9472 +top5_acc 0.9969 +2025-06-25 09:33:14,443 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:33:14,451 - pyskl - INFO - +mean_acc 0.9291 +2025-06-25 09:33:14,453 - pyskl - INFO - Epoch(val) [140][533] top1_acc: 0.9472, top5_acc: 0.9969, mean_class_accuracy: 0.9291 +2025-06-25 09:34:34,556 - pyskl - INFO - Epoch [141][100/1281] lr: 2.690e-04, eta: 1:31:08, time: 0.801, data_time: 0.185, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 09:35:23,331 - pyskl - INFO - Epoch [141][200/1281] lr: 2.648e-04, eta: 1:30:25, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 09:36:12,131 - pyskl - INFO - Epoch [141][300/1281] lr: 2.606e-04, eta: 1:29:42, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 09:37:00,958 - pyskl - INFO - Epoch [141][400/1281] lr: 2.565e-04, eta: 1:29:00, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0222, loss: 0.0222 +2025-06-25 09:37:49,901 - pyskl - INFO - Epoch [141][500/1281] lr: 2.524e-04, eta: 1:28:17, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0207, loss: 0.0207 +2025-06-25 09:38:38,819 - pyskl - INFO - Epoch [141][600/1281] lr: 2.483e-04, eta: 1:27:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0200, loss: 0.0200 +2025-06-25 09:39:27,758 - pyskl - INFO - Epoch [141][700/1281] lr: 2.443e-04, eta: 1:26:52, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 09:40:16,470 - pyskl - INFO - Epoch [141][800/1281] lr: 2.402e-04, eta: 1:26:09, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 09:41:05,750 - pyskl - INFO - Epoch [141][900/1281] lr: 2.363e-04, eta: 1:25:26, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 09:41:54,597 - pyskl - INFO - Epoch [141][1000/1281] lr: 2.323e-04, eta: 1:24:44, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 09:42:22,519 - pyskl - INFO - Epoch [141][1100/1281] lr: 2.284e-04, eta: 1:24:00, time: 0.279, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 09:43:13,288 - pyskl - INFO - Epoch [141][1200/1281] lr: 2.246e-04, eta: 1:23:17, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 09:43:34,923 - pyskl - INFO - Saving checkpoint at 141 epochs +2025-06-25 09:44:33,184 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:44:33,254 - pyskl - INFO - +top1_acc 0.9464 +top5_acc 0.9974 +2025-06-25 09:44:33,254 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:44:33,262 - pyskl - INFO - +mean_acc 0.9264 +2025-06-25 09:44:33,265 - pyskl - INFO - Epoch(val) [141][533] top1_acc: 0.9464, top5_acc: 0.9974, mean_class_accuracy: 0.9264 +2025-06-25 09:45:53,055 - pyskl - INFO - Epoch [142][100/1281] lr: 2.176e-04, eta: 1:21:59, time: 0.798, data_time: 0.190, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 09:46:41,975 - pyskl - INFO - Epoch [142][200/1281] lr: 2.139e-04, eta: 1:21:17, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 09:47:30,923 - pyskl - INFO - Epoch [142][300/1281] lr: 2.101e-04, eta: 1:20:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-25 09:48:20,064 - pyskl - INFO - Epoch [142][400/1281] lr: 2.064e-04, eta: 1:19:51, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 09:49:08,975 - pyskl - INFO - Epoch [142][500/1281] lr: 2.027e-04, eta: 1:19:09, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-25 09:49:58,046 - pyskl - INFO - Epoch [142][600/1281] lr: 1.991e-04, eta: 1:18:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 09:50:47,427 - pyskl - INFO - Epoch [142][700/1281] lr: 1.954e-04, eta: 1:17:43, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0214, loss: 0.0214 +2025-06-25 09:51:36,452 - pyskl - INFO - Epoch [142][800/1281] lr: 1.919e-04, eta: 1:17:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 09:52:25,384 - pyskl - INFO - Epoch [142][900/1281] lr: 1.883e-04, eta: 1:16:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 09:53:14,232 - pyskl - INFO - Epoch [142][1000/1281] lr: 1.848e-04, eta: 1:15:35, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 09:53:41,154 - pyskl - INFO - Epoch [142][1100/1281] lr: 1.813e-04, eta: 1:14:51, time: 0.269, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 09:54:32,028 - pyskl - INFO - Epoch [142][1200/1281] lr: 1.779e-04, eta: 1:14:08, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 09:54:54,572 - pyskl - INFO - Saving checkpoint at 142 epochs +2025-06-25 09:55:52,564 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:55:52,639 - pyskl - INFO - +top1_acc 0.9473 +top5_acc 0.9973 +2025-06-25 09:55:52,639 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:55:52,647 - pyskl - INFO - +mean_acc 0.9265 +2025-06-25 09:55:52,649 - pyskl - INFO - Epoch(val) [142][533] top1_acc: 0.9473, top5_acc: 0.9973, mean_class_accuracy: 0.9265 +2025-06-25 09:57:10,855 - pyskl - INFO - Epoch [143][100/1281] lr: 1.717e-04, eta: 1:12:51, time: 0.782, data_time: 0.190, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 09:58:00,095 - pyskl - INFO - Epoch [143][200/1281] lr: 1.683e-04, eta: 1:12:08, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 09:58:49,155 - pyskl - INFO - Epoch [143][300/1281] lr: 1.650e-04, eta: 1:11:25, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 09:59:38,078 - pyskl - INFO - Epoch [143][400/1281] lr: 1.617e-04, eta: 1:10:42, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 10:00:27,171 - pyskl - INFO - Epoch [143][500/1281] lr: 1.585e-04, eta: 1:10:00, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 10:01:16,322 - pyskl - INFO - Epoch [143][600/1281] lr: 1.552e-04, eta: 1:09:17, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 10:02:05,403 - pyskl - INFO - Epoch [143][700/1281] lr: 1.520e-04, eta: 1:08:34, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 10:02:54,177 - pyskl - INFO - Epoch [143][800/1281] lr: 1.489e-04, eta: 1:07:51, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 10:03:42,918 - pyskl - INFO - Epoch [143][900/1281] lr: 1.457e-04, eta: 1:07:08, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 10:04:32,042 - pyskl - INFO - Epoch [143][1000/1281] lr: 1.426e-04, eta: 1:06:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-25 10:04:59,910 - pyskl - INFO - Epoch [143][1100/1281] lr: 1.396e-04, eta: 1:05:42, time: 0.279, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 10:05:50,771 - pyskl - INFO - Epoch [143][1200/1281] lr: 1.366e-04, eta: 1:04:59, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 10:06:12,853 - pyskl - INFO - Saving checkpoint at 143 epochs +2025-06-25 10:07:10,978 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:07:11,048 - pyskl - INFO - +top1_acc 0.9473 +top5_acc 0.9968 +2025-06-25 10:07:11,048 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:07:11,056 - pyskl - INFO - +mean_acc 0.9291 +2025-06-25 10:07:11,058 - pyskl - INFO - Epoch(val) [143][533] top1_acc: 0.9473, top5_acc: 0.9968, mean_class_accuracy: 0.9291 +2025-06-25 10:08:30,494 - pyskl - INFO - Epoch [144][100/1281] lr: 1.312e-04, eta: 1:03:41, time: 0.794, data_time: 0.192, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 10:09:19,194 - pyskl - INFO - Epoch [144][200/1281] lr: 1.282e-04, eta: 1:02:58, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 10:10:07,908 - pyskl - INFO - Epoch [144][300/1281] lr: 1.253e-04, eta: 1:02:15, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 10:10:57,006 - pyskl - INFO - Epoch [144][400/1281] lr: 1.224e-04, eta: 1:01:33, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 10:11:46,128 - pyskl - INFO - Epoch [144][500/1281] lr: 1.196e-04, eta: 1:00:50, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-25 10:12:35,629 - pyskl - INFO - Epoch [144][600/1281] lr: 1.168e-04, eta: 1:00:07, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 10:13:24,696 - pyskl - INFO - Epoch [144][700/1281] lr: 1.140e-04, eta: 0:59:24, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 10:14:14,131 - pyskl - INFO - Epoch [144][800/1281] lr: 1.113e-04, eta: 0:58:41, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0205, loss: 0.0205 +2025-06-25 10:15:03,234 - pyskl - INFO - Epoch [144][900/1281] lr: 1.086e-04, eta: 0:57:58, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 10:15:52,478 - pyskl - INFO - Epoch [144][1000/1281] lr: 1.059e-04, eta: 0:57:16, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 10:16:19,386 - pyskl - INFO - Epoch [144][1100/1281] lr: 1.033e-04, eta: 0:56:32, time: 0.269, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0207, loss: 0.0207 +2025-06-25 10:17:10,089 - pyskl - INFO - Epoch [144][1200/1281] lr: 1.007e-04, eta: 0:55:49, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-25 10:17:31,692 - pyskl - INFO - Saving checkpoint at 144 epochs +2025-06-25 10:18:29,783 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:18:29,839 - pyskl - INFO - +top1_acc 0.9466 +top5_acc 0.9971 +2025-06-25 10:18:29,839 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:18:29,846 - pyskl - INFO - +mean_acc 0.9274 +2025-06-25 10:18:29,847 - pyskl - INFO - Epoch(val) [144][533] top1_acc: 0.9466, top5_acc: 0.9971, mean_class_accuracy: 0.9274 +2025-06-25 10:19:48,089 - pyskl - INFO - Epoch [145][100/1281] lr: 9.605e-05, eta: 0:54:31, time: 0.782, data_time: 0.184, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 10:20:37,247 - pyskl - INFO - Epoch [145][200/1281] lr: 9.353e-05, eta: 0:53:48, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 10:21:26,260 - pyskl - INFO - Epoch [145][300/1281] lr: 9.106e-05, eta: 0:53:05, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 10:22:15,279 - pyskl - INFO - Epoch [145][400/1281] lr: 8.861e-05, eta: 0:52:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 10:23:04,380 - pyskl - INFO - Epoch [145][500/1281] lr: 8.620e-05, eta: 0:51:39, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 10:23:53,046 - pyskl - INFO - Epoch [145][600/1281] lr: 8.382e-05, eta: 0:50:56, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 10:24:41,987 - pyskl - INFO - Epoch [145][700/1281] lr: 8.147e-05, eta: 0:50:13, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 10:25:31,041 - pyskl - INFO - Epoch [145][800/1281] lr: 7.916e-05, eta: 0:49:31, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0205, loss: 0.0205 +2025-06-25 10:26:19,894 - pyskl - INFO - Epoch [145][900/1281] lr: 7.688e-05, eta: 0:48:48, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 10:27:08,559 - pyskl - INFO - Epoch [145][1000/1281] lr: 7.463e-05, eta: 0:48:05, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 10:27:38,263 - pyskl - INFO - Epoch [145][1100/1281] lr: 7.242e-05, eta: 0:47:21, time: 0.297, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 10:28:29,060 - pyskl - INFO - Epoch [145][1200/1281] lr: 7.024e-05, eta: 0:46:38, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 10:28:50,715 - pyskl - INFO - Saving checkpoint at 145 epochs +2025-06-25 10:29:48,815 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:29:48,870 - pyskl - INFO - +top1_acc 0.9460 +top5_acc 0.9972 +2025-06-25 10:29:48,870 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:29:48,877 - pyskl - INFO - +mean_acc 0.9264 +2025-06-25 10:29:48,878 - pyskl - INFO - Epoch(val) [145][533] top1_acc: 0.9460, top5_acc: 0.9972, mean_class_accuracy: 0.9264 +2025-06-25 10:31:07,702 - pyskl - INFO - Epoch [146][100/1281] lr: 6.638e-05, eta: 0:45:20, time: 0.788, data_time: 0.186, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 10:31:56,971 - pyskl - INFO - Epoch [146][200/1281] lr: 6.429e-05, eta: 0:44:37, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 10:32:45,880 - pyskl - INFO - Epoch [146][300/1281] lr: 6.224e-05, eta: 0:43:54, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0204, loss: 0.0204 +2025-06-25 10:33:34,886 - pyskl - INFO - Epoch [146][400/1281] lr: 6.022e-05, eta: 0:43:11, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 10:34:24,525 - pyskl - INFO - Epoch [146][500/1281] lr: 5.823e-05, eta: 0:42:28, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-25 10:35:13,314 - pyskl - INFO - Epoch [146][600/1281] lr: 5.628e-05, eta: 0:41:45, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 10:36:02,588 - pyskl - INFO - Epoch [146][700/1281] lr: 5.436e-05, eta: 0:41:02, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 10:36:51,494 - pyskl - INFO - Epoch [146][800/1281] lr: 5.247e-05, eta: 0:40:19, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 10:37:40,518 - pyskl - INFO - Epoch [146][900/1281] lr: 5.061e-05, eta: 0:39:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 10:38:29,538 - pyskl - INFO - Epoch [146][1000/1281] lr: 4.879e-05, eta: 0:38:53, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0200, loss: 0.0200 +2025-06-25 10:38:58,625 - pyskl - INFO - Epoch [146][1100/1281] lr: 4.701e-05, eta: 0:38:10, time: 0.291, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-25 10:39:49,464 - pyskl - INFO - Epoch [146][1200/1281] lr: 4.525e-05, eta: 0:37:27, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-25 10:40:10,702 - pyskl - INFO - Saving checkpoint at 146 epochs +2025-06-25 10:41:08,898 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:41:08,962 - pyskl - INFO - +top1_acc 0.9463 +top5_acc 0.9971 +2025-06-25 10:41:08,962 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:41:08,976 - pyskl - INFO - +mean_acc 0.9249 +2025-06-25 10:41:08,980 - pyskl - INFO - Epoch(val) [146][533] top1_acc: 0.9463, top5_acc: 0.9971, mean_class_accuracy: 0.9249 +2025-06-25 10:42:27,806 - pyskl - INFO - Epoch [147][100/1281] lr: 4.216e-05, eta: 0:36:09, time: 0.788, data_time: 0.189, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 10:43:16,642 - pyskl - INFO - Epoch [147][200/1281] lr: 4.050e-05, eta: 0:35:26, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 10:44:05,627 - pyskl - INFO - Epoch [147][300/1281] lr: 3.887e-05, eta: 0:34:43, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0214, loss: 0.0214 +2025-06-25 10:44:54,386 - pyskl - INFO - Epoch [147][400/1281] lr: 3.728e-05, eta: 0:33:59, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0205, loss: 0.0205 +2025-06-25 10:45:43,189 - pyskl - INFO - Epoch [147][500/1281] lr: 3.572e-05, eta: 0:33:16, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 10:46:32,688 - pyskl - INFO - Epoch [147][600/1281] lr: 3.419e-05, eta: 0:32:33, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-25 10:47:22,048 - pyskl - INFO - Epoch [147][700/1281] lr: 3.270e-05, eta: 0:31:50, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 10:48:11,065 - pyskl - INFO - Epoch [147][800/1281] lr: 3.124e-05, eta: 0:31:07, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 10:49:00,213 - pyskl - INFO - Epoch [147][900/1281] lr: 2.981e-05, eta: 0:30:24, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 10:49:49,149 - pyskl - INFO - Epoch [147][1000/1281] lr: 2.842e-05, eta: 0:29:41, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 10:50:17,459 - pyskl - INFO - Epoch [147][1100/1281] lr: 2.706e-05, eta: 0:28:58, time: 0.283, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 10:51:08,280 - pyskl - INFO - Epoch [147][1200/1281] lr: 2.573e-05, eta: 0:28:15, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 10:51:30,054 - pyskl - INFO - Saving checkpoint at 147 epochs +2025-06-25 10:52:28,202 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:52:28,264 - pyskl - INFO - +top1_acc 0.9468 +top5_acc 0.9973 +2025-06-25 10:52:28,264 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:52:28,271 - pyskl - INFO - +mean_acc 0.9274 +2025-06-25 10:52:28,273 - pyskl - INFO - Epoch(val) [147][533] top1_acc: 0.9468, top5_acc: 0.9973, mean_class_accuracy: 0.9274 +2025-06-25 10:53:46,871 - pyskl - INFO - Epoch [148][100/1281] lr: 2.341e-05, eta: 0:26:56, time: 0.786, data_time: 0.185, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 10:54:35,731 - pyskl - INFO - Epoch [148][200/1281] lr: 2.218e-05, eta: 0:26:13, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 10:55:24,529 - pyskl - INFO - Epoch [148][300/1281] lr: 2.098e-05, eta: 0:25:30, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 10:56:13,168 - pyskl - INFO - Epoch [148][400/1281] lr: 1.981e-05, eta: 0:24:47, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 10:57:02,148 - pyskl - INFO - Epoch [148][500/1281] lr: 1.868e-05, eta: 0:24:04, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 10:57:51,114 - pyskl - INFO - Epoch [148][600/1281] lr: 1.758e-05, eta: 0:23:21, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 10:58:40,168 - pyskl - INFO - Epoch [148][700/1281] lr: 1.651e-05, eta: 0:22:38, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 10:59:29,146 - pyskl - INFO - Epoch [148][800/1281] lr: 1.548e-05, eta: 0:21:55, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-25 11:00:18,176 - pyskl - INFO - Epoch [148][900/1281] lr: 1.448e-05, eta: 0:21:12, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0204, loss: 0.0204 +2025-06-25 11:01:07,257 - pyskl - INFO - Epoch [148][1000/1281] lr: 1.351e-05, eta: 0:20:28, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0219, loss: 0.0219 +2025-06-25 11:01:36,631 - pyskl - INFO - Epoch [148][1100/1281] lr: 1.258e-05, eta: 0:19:45, time: 0.294, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 11:02:27,363 - pyskl - INFO - Epoch [148][1200/1281] lr: 1.168e-05, eta: 0:19:02, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 11:02:48,678 - pyskl - INFO - Saving checkpoint at 148 epochs +2025-06-25 11:03:46,919 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:03:46,974 - pyskl - INFO - +top1_acc 0.9478 +top5_acc 0.9974 +2025-06-25 11:03:46,974 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:03:46,980 - pyskl - INFO - +mean_acc 0.9287 +2025-06-25 11:03:46,984 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_139.pth was removed +2025-06-25 11:03:47,150 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_148.pth. +2025-06-25 11:03:47,150 - pyskl - INFO - Best top1_acc is 0.9478 at 148 epoch. +2025-06-25 11:03:47,153 - pyskl - INFO - Epoch(val) [148][533] top1_acc: 0.9478, top5_acc: 0.9974, mean_class_accuracy: 0.9287 +2025-06-25 11:05:06,693 - pyskl - INFO - Epoch [149][100/1281] lr: 1.013e-05, eta: 0:17:44, time: 0.795, data_time: 0.185, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 11:05:55,530 - pyskl - INFO - Epoch [149][200/1281] lr: 9.328e-06, eta: 0:17:01, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 11:06:44,542 - pyskl - INFO - Epoch [149][300/1281] lr: 8.555e-06, eta: 0:16:17, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 11:07:33,512 - pyskl - INFO - Epoch [149][400/1281] lr: 7.816e-06, eta: 0:15:34, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 11:08:22,595 - pyskl - INFO - Epoch [149][500/1281] lr: 7.110e-06, eta: 0:14:51, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 11:09:11,823 - pyskl - INFO - Epoch [149][600/1281] lr: 6.437e-06, eta: 0:14:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 11:10:01,210 - pyskl - INFO - Epoch [149][700/1281] lr: 5.798e-06, eta: 0:13:25, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-25 11:10:50,126 - pyskl - INFO - Epoch [149][800/1281] lr: 5.192e-06, eta: 0:12:41, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 11:11:39,495 - pyskl - INFO - Epoch [149][900/1281] lr: 4.620e-06, eta: 0:11:58, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 11:12:28,682 - pyskl - INFO - Epoch [149][1000/1281] lr: 4.081e-06, eta: 0:11:15, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 11:12:57,101 - pyskl - INFO - Epoch [149][1100/1281] lr: 3.576e-06, eta: 0:10:32, time: 0.284, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 11:13:47,856 - pyskl - INFO - Epoch [149][1200/1281] lr: 3.104e-06, eta: 0:09:49, time: 0.508, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0215, loss: 0.0215 +2025-06-25 11:14:09,106 - pyskl - INFO - Saving checkpoint at 149 epochs +2025-06-25 11:15:07,192 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:15:07,248 - pyskl - INFO - +top1_acc 0.9477 +top5_acc 0.9974 +2025-06-25 11:15:07,248 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:15:07,256 - pyskl - INFO - +mean_acc 0.9282 +2025-06-25 11:15:07,258 - pyskl - INFO - Epoch(val) [149][533] top1_acc: 0.9477, top5_acc: 0.9974, mean_class_accuracy: 0.9282 +2025-06-25 11:16:27,405 - pyskl - INFO - Epoch [150][100/1281] lr: 2.334e-06, eta: 0:08:30, time: 0.801, data_time: 0.187, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0200, loss: 0.0200 +2025-06-25 11:17:16,259 - pyskl - INFO - Epoch [150][200/1281] lr: 1.956e-06, eta: 0:07:47, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 11:18:05,405 - pyskl - INFO - Epoch [150][300/1281] lr: 1.611e-06, eta: 0:07:04, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0200, loss: 0.0200 +2025-06-25 11:18:54,284 - pyskl - INFO - Epoch [150][400/1281] lr: 1.300e-06, eta: 0:06:21, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 11:19:43,278 - pyskl - INFO - Epoch [150][500/1281] lr: 1.022e-06, eta: 0:05:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 11:20:32,318 - pyskl - INFO - Epoch [150][600/1281] lr: 7.771e-07, eta: 0:04:54, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 11:21:21,493 - pyskl - INFO - Epoch [150][700/1281] lr: 5.659e-07, eta: 0:04:11, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 11:22:10,344 - pyskl - INFO - Epoch [150][800/1281] lr: 3.881e-07, eta: 0:03:28, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 11:22:59,377 - pyskl - INFO - Epoch [150][900/1281] lr: 2.438e-07, eta: 0:02:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 11:23:47,952 - pyskl - INFO - Epoch [150][1000/1281] lr: 1.329e-07, eta: 0:02:01, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 11:24:17,422 - pyskl - INFO - Epoch [150][1100/1281] lr: 5.534e-08, eta: 0:01:18, time: 0.295, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-25 11:25:06,483 - pyskl - INFO - Epoch [150][1200/1281] lr: 1.123e-08, eta: 0:00:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 11:25:28,898 - pyskl - INFO - Saving checkpoint at 150 epochs +2025-06-25 11:26:26,629 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:26:26,698 - pyskl - INFO - +top1_acc 0.9464 +top5_acc 0.9973 +2025-06-25 11:26:26,699 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:26:26,707 - pyskl - INFO - +mean_acc 0.9259 +2025-06-25 11:26:26,709 - pyskl - INFO - Epoch(val) [150][533] top1_acc: 0.9464, top5_acc: 0.9973, mean_class_accuracy: 0.9259 +2025-06-25 11:26:31,211 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-06-25 11:34:17,565 - pyskl - INFO - Testing results of the last checkpoint +2025-06-25 11:34:17,565 - pyskl - INFO - top1_acc: 0.9461 +2025-06-25 11:34:17,565 - pyskl - INFO - top5_acc: 0.9973 +2025-06-25 11:34:17,565 - pyskl - INFO - mean_class_accuracy: 0.9253 +2025-06-25 11:34:17,566 - pyskl - INFO - load checkpoint from local path: ./work_dirs/test_aclnet/finegym/b_3/best_top1_acc_epoch_148.pth +2025-06-25 11:41:44,850 - pyskl - INFO - Testing results of the best checkpoint +2025-06-25 11:41:44,850 - pyskl - INFO - top1_acc: 0.9470 +2025-06-25 11:41:44,851 - pyskl - INFO - top5_acc: 0.9975 +2025-06-25 11:41:44,851 - pyskl - INFO - mean_class_accuracy: 0.9292