diff --git "a/finegym/b_1/20250624_084232.log" "b/finegym/b_1/20250624_084232.log" new file mode 100644--- /dev/null +++ "b/finegym/b_1/20250624_084232.log" @@ -0,0 +1,3471 @@ +2025-06-24 08:42:32,290 - 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 08:42:32,498 - pyskl - INFO - Config: modality = 'b' +graph = 'coco_new' +work_dir = './work_dirs/test_aclnet/finegym/b_1' +model = dict( + type='RecognizerGCN', + backbone=dict( + type='GCN_Module', + gcn_ratio=0.125, + gcn_ctr='T', + gcn_ada='T', + tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'], + graph_cfg=dict( + layout='coco_new', + mode='random', + num_filter=8, + init_off=0.04, + init_std=0.02)), + cls_head=dict(type='SimpleHead', data_cfg='finegym', num_classes=99, in_channels=384)) +dataset_type = 'PoseDataset' +ann_file = '/data/lhd/pyskl_data/gym/gym_hrnet.pkl' +left_kp = [1, 3, 5, 7, 9, 11, 13, 15] +right_kp = [2, 4, 6, 8, 10, 12, 14, 16] +train_pipeline = [ + dict(type='UniformSampleFrames', clip_len=100), + dict(type='PoseDecode'), + dict( + type='Flip', + flip_ratio=0.5, + left_kp=[1, 3, 5, 7, 9, 11, 13, 15], + right_kp=[2, 4, 6, 8, 10, 12, 14, 16]), + dict(type='Kinetics_Transform'), + dict(type='GenSkeFeat', dataset='coco_new', feats=['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 08:42:32,498 - pyskl - INFO - Set random seed to 135571342, deterministic: False +2025-06-24 08:42:33,954 - pyskl - INFO - 20484 videos remain after valid thresholding +2025-06-24 08:42:37,991 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-06-24 08:42:37,992 - pyskl - INFO - Start running, host: lhd@zkyd, work_dir: /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1 +2025-06-24 08:42:37,992 - 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 08:42:37,992 - pyskl - INFO - workflow: [('train', 1)], max: 150 epochs +2025-06-24 08:42:37,993 - pyskl - INFO - Checkpoints will be saved to /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1 by HardDiskBackend. +2025-06-24 08:43:15,924 - pyskl - INFO - Epoch [1][100/1281] lr: 2.500e-02, eta: 20:14:00, time: 0.379, data_time: 0.168, memory: 4082, top1_acc: 0.0775, top5_acc: 0.2494, loss_cls: 4.4720, loss: 4.4720 +2025-06-24 08:43:37,848 - pyskl - INFO - Epoch [1][200/1281] lr: 2.500e-02, eta: 15:57:21, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.0756, top5_acc: 0.3475, loss_cls: 4.4392, loss: 4.4392 +2025-06-24 08:43:59,621 - pyskl - INFO - Epoch [1][300/1281] lr: 2.500e-02, eta: 14:29:57, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.1288, top5_acc: 0.3869, loss_cls: 4.2202, loss: 4.2202 +2025-06-24 08:44:21,534 - pyskl - INFO - Epoch [1][400/1281] lr: 2.500e-02, eta: 13:47:12, time: 0.219, data_time: 0.001, memory: 4082, top1_acc: 0.1100, top5_acc: 0.4031, loss_cls: 4.2550, loss: 4.2550 +2025-06-24 08:44:43,609 - pyskl - INFO - Epoch [1][500/1281] lr: 2.500e-02, eta: 13:22:25, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.1206, top5_acc: 0.4431, loss_cls: 4.0044, loss: 4.0044 +2025-06-24 08:45:05,668 - pyskl - INFO - Epoch [1][600/1281] lr: 2.500e-02, eta: 13:05:42, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.1619, top5_acc: 0.4781, loss_cls: 3.7852, loss: 3.7852 +2025-06-24 08:45:27,314 - pyskl - INFO - Epoch [1][700/1281] lr: 2.500e-02, eta: 12:51:46, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.2087, top5_acc: 0.5425, loss_cls: 3.5211, loss: 3.5211 +2025-06-24 08:45:49,014 - pyskl - INFO - Epoch [1][800/1281] lr: 2.500e-02, eta: 12:41:27, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.2362, top5_acc: 0.6138, loss_cls: 3.3370, loss: 3.3370 +2025-06-24 08:46:10,826 - pyskl - INFO - Epoch [1][900/1281] lr: 2.500e-02, eta: 12:33:44, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.2669, top5_acc: 0.6406, loss_cls: 3.1559, loss: 3.1559 +2025-06-24 08:46:32,585 - pyskl - INFO - Epoch [1][1000/1281] lr: 2.500e-02, eta: 12:27:20, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.3144, top5_acc: 0.6813, loss_cls: 2.9708, loss: 2.9708 +2025-06-24 08:46:54,246 - pyskl - INFO - Epoch [1][1100/1281] lr: 2.500e-02, eta: 12:21:44, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.3144, top5_acc: 0.6906, loss_cls: 2.9437, loss: 2.9437 +2025-06-24 08:47:16,057 - pyskl - INFO - Epoch [1][1200/1281] lr: 2.500e-02, eta: 12:17:24, time: 0.218, data_time: 0.001, memory: 4082, top1_acc: 0.3400, top5_acc: 0.7094, loss_cls: 2.8599, loss: 2.8599 +2025-06-24 08:47:34,419 - pyskl - INFO - Saving checkpoint at 1 epochs +2025-06-24 08:48:17,427 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 08:48:17,479 - pyskl - INFO - +top1_acc 0.3090 +top5_acc 0.7075 +2025-06-24 08:48:17,479 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 08:48:17,484 - pyskl - INFO - +mean_acc 0.1655 +2025-06-24 08:48:17,651 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_1.pth. +2025-06-24 08:48:17,651 - pyskl - INFO - Best top1_acc is 0.3090 at 1 epoch. +2025-06-24 08:48:17,654 - pyskl - INFO - Epoch(val) [1][533] top1_acc: 0.3090, top5_acc: 0.7075, mean_class_accuracy: 0.1655 +2025-06-24 08:48:57,792 - pyskl - INFO - Epoch [2][100/1281] lr: 2.500e-02, eta: 12:12:33, time: 0.401, data_time: 0.183, memory: 4082, top1_acc: 0.3481, top5_acc: 0.7488, loss_cls: 2.6659, loss: 2.6659 +2025-06-24 08:49:19,836 - pyskl - INFO - Epoch [2][200/1281] lr: 2.500e-02, eta: 12:10:02, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.4037, top5_acc: 0.7925, loss_cls: 2.5267, loss: 2.5267 +2025-06-24 08:49:41,937 - pyskl - INFO - Epoch [2][300/1281] lr: 2.500e-02, eta: 12:07:52, time: 0.221, data_time: 0.001, memory: 4082, top1_acc: 0.4269, top5_acc: 0.8150, loss_cls: 2.3842, loss: 2.3842 +2025-06-24 08:50:03,886 - pyskl - INFO - Epoch [2][400/1281] lr: 2.500e-02, eta: 12:05:40, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.4425, top5_acc: 0.8231, loss_cls: 2.3297, loss: 2.3297 +2025-06-24 08:50:25,946 - pyskl - INFO - Epoch [2][500/1281] lr: 2.499e-02, eta: 12:03:51, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.4587, top5_acc: 0.8500, loss_cls: 2.2463, loss: 2.2463 +2025-06-24 08:50:47,633 - pyskl - INFO - Epoch [2][600/1281] lr: 2.499e-02, eta: 12:01:34, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.5062, top5_acc: 0.8750, loss_cls: 2.0824, loss: 2.0824 +2025-06-24 08:51:09,387 - pyskl - INFO - Epoch [2][700/1281] lr: 2.499e-02, eta: 11:59:35, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.4856, top5_acc: 0.8662, loss_cls: 2.1354, loss: 2.1354 +2025-06-24 08:51:31,516 - pyskl - INFO - Epoch [2][800/1281] lr: 2.499e-02, eta: 11:58:20, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.4919, top5_acc: 0.8556, loss_cls: 2.1117, loss: 2.1117 +2025-06-24 08:51:53,561 - pyskl - INFO - Epoch [2][900/1281] lr: 2.499e-02, eta: 11:57:02, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5150, top5_acc: 0.8962, loss_cls: 1.9696, loss: 1.9696 +2025-06-24 08:52:15,285 - pyskl - INFO - Epoch [2][1000/1281] lr: 2.499e-02, eta: 11:55:23, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.5188, top5_acc: 0.8969, loss_cls: 1.9813, loss: 1.9813 +2025-06-24 08:52:36,844 - pyskl - INFO - Epoch [2][1100/1281] lr: 2.499e-02, eta: 11:53:37, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.5606, top5_acc: 0.9038, loss_cls: 1.8661, loss: 1.8661 +2025-06-24 08:52:58,838 - pyskl - INFO - Epoch [2][1200/1281] lr: 2.499e-02, eta: 11:52:31, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5406, top5_acc: 0.9006, loss_cls: 1.9230, loss: 1.9230 +2025-06-24 08:53:16,898 - pyskl - INFO - Saving checkpoint at 2 epochs +2025-06-24 08:54:00,061 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 08:54:00,135 - pyskl - INFO - +top1_acc 0.4744 +top5_acc 0.8495 +2025-06-24 08:54:00,135 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 08:54:00,144 - pyskl - INFO - +mean_acc 0.3156 +2025-06-24 08:54:00,149 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_1.pth was removed +2025-06-24 08:54:00,348 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_2.pth. +2025-06-24 08:54:00,349 - pyskl - INFO - Best top1_acc is 0.4744 at 2 epoch. +2025-06-24 08:54:00,352 - pyskl - INFO - Epoch(val) [2][533] top1_acc: 0.4744, top5_acc: 0.8495, mean_class_accuracy: 0.3156 +2025-06-24 08:54:40,675 - pyskl - INFO - Epoch [3][100/1281] lr: 2.499e-02, eta: 11:51:16, time: 0.403, data_time: 0.185, memory: 4082, top1_acc: 0.5700, top5_acc: 0.9181, loss_cls: 1.7820, loss: 1.7820 +2025-06-24 08:55:02,647 - pyskl - INFO - Epoch [3][200/1281] lr: 2.499e-02, eta: 11:50:15, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5800, top5_acc: 0.9256, loss_cls: 1.7001, loss: 1.7001 +2025-06-24 08:55:24,675 - pyskl - INFO - Epoch [3][300/1281] lr: 2.499e-02, eta: 11:49:21, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5794, top5_acc: 0.9187, loss_cls: 1.7817, loss: 1.7817 +2025-06-24 08:55:46,657 - pyskl - INFO - Epoch [3][400/1281] lr: 2.499e-02, eta: 11:48:27, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.6225, top5_acc: 0.9244, loss_cls: 1.6474, loss: 1.6474 +2025-06-24 08:56:08,639 - pyskl - INFO - Epoch [3][500/1281] lr: 2.498e-02, eta: 11:47:34, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5894, top5_acc: 0.9400, loss_cls: 1.6743, loss: 1.6743 +2025-06-24 08:56:30,408 - pyskl - INFO - Epoch [3][600/1281] lr: 2.498e-02, eta: 11:46:31, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.5994, top5_acc: 0.9319, loss_cls: 1.6707, loss: 1.6707 +2025-06-24 08:56:52,338 - pyskl - INFO - Epoch [3][700/1281] lr: 2.498e-02, eta: 11:45:39, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6069, top5_acc: 0.9437, loss_cls: 1.6371, loss: 1.6371 +2025-06-24 08:57:14,213 - pyskl - INFO - Epoch [3][800/1281] lr: 2.498e-02, eta: 11:44:47, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6225, top5_acc: 0.9325, loss_cls: 1.6222, loss: 1.6222 +2025-06-24 08:57:35,974 - pyskl - INFO - Epoch [3][900/1281] lr: 2.498e-02, eta: 11:43:49, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.6369, top5_acc: 0.9387, loss_cls: 1.5260, loss: 1.5260 +2025-06-24 08:57:57,601 - pyskl - INFO - Epoch [3][1000/1281] lr: 2.498e-02, eta: 11:42:47, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.6144, top5_acc: 0.9413, loss_cls: 1.6061, loss: 1.6061 +2025-06-24 08:58:19,325 - pyskl - INFO - Epoch [3][1100/1281] lr: 2.498e-02, eta: 11:41:52, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6281, top5_acc: 0.9563, loss_cls: 1.5082, loss: 1.5082 +2025-06-24 08:58:41,146 - pyskl - INFO - Epoch [3][1200/1281] lr: 2.498e-02, eta: 11:41:03, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.6412, top5_acc: 0.9481, loss_cls: 1.4948, loss: 1.4948 +2025-06-24 08:58:59,496 - pyskl - INFO - Saving checkpoint at 3 epochs +2025-06-24 08:59:42,397 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 08:59:42,468 - pyskl - INFO - +top1_acc 0.6337 +top5_acc 0.9418 +2025-06-24 08:59:42,468 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 08:59:42,475 - pyskl - INFO - +mean_acc 0.4855 +2025-06-24 08:59:42,480 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_2.pth was removed +2025-06-24 08:59:42,668 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_3.pth. +2025-06-24 08:59:42,668 - pyskl - INFO - Best top1_acc is 0.6337 at 3 epoch. +2025-06-24 08:59:42,671 - pyskl - INFO - Epoch(val) [3][533] top1_acc: 0.6337, top5_acc: 0.9418, mean_class_accuracy: 0.4855 +2025-06-24 09:00:22,640 - pyskl - INFO - Epoch [4][100/1281] lr: 2.497e-02, eta: 11:40:01, time: 0.400, data_time: 0.180, memory: 4082, top1_acc: 0.6469, top5_acc: 0.9494, loss_cls: 1.4387, loss: 1.4387 +2025-06-24 09:00:44,701 - pyskl - INFO - Epoch [4][200/1281] lr: 2.497e-02, eta: 11:39:27, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.6619, top5_acc: 0.9600, loss_cls: 1.4074, loss: 1.4074 +2025-06-24 09:01:06,598 - pyskl - INFO - Epoch [4][300/1281] lr: 2.497e-02, eta: 11:38:46, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6525, top5_acc: 0.9550, loss_cls: 1.4718, loss: 1.4718 +2025-06-24 09:01:28,594 - pyskl - INFO - Epoch [4][400/1281] lr: 2.497e-02, eta: 11:38:10, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.6575, top5_acc: 0.9556, loss_cls: 1.3940, loss: 1.3940 +2025-06-24 09:01:50,454 - pyskl - INFO - Epoch [4][500/1281] lr: 2.497e-02, eta: 11:37:29, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6681, top5_acc: 0.9600, loss_cls: 1.3750, loss: 1.3750 +2025-06-24 09:02:11,814 - pyskl - INFO - Epoch [4][600/1281] lr: 2.497e-02, eta: 11:36:28, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.6719, top5_acc: 0.9656, loss_cls: 1.3838, loss: 1.3838 +2025-06-24 09:02:33,559 - pyskl - INFO - Epoch [4][700/1281] lr: 2.497e-02, eta: 11:35:44, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6794, top5_acc: 0.9725, loss_cls: 1.3110, loss: 1.3110 +2025-06-24 09:02:54,907 - pyskl - INFO - Epoch [4][800/1281] lr: 2.496e-02, eta: 11:34:45, time: 0.213, data_time: 0.000, memory: 4082, top1_acc: 0.6675, top5_acc: 0.9650, loss_cls: 1.3982, loss: 1.3982 +2025-06-24 09:03:16,257 - pyskl - INFO - Epoch [4][900/1281] lr: 2.496e-02, eta: 11:33:48, time: 0.213, data_time: 0.000, memory: 4082, top1_acc: 0.6819, top5_acc: 0.9606, loss_cls: 1.3404, loss: 1.3404 +2025-06-24 09:03:37,828 - pyskl - INFO - Epoch [4][1000/1281] lr: 2.496e-02, eta: 11:33:01, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.6831, top5_acc: 0.9644, loss_cls: 1.3256, loss: 1.3256 +2025-06-24 09:03:59,716 - pyskl - INFO - Epoch [4][1100/1281] lr: 2.496e-02, eta: 11:32:27, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6775, top5_acc: 0.9600, loss_cls: 1.3376, loss: 1.3376 +2025-06-24 09:04:21,302 - pyskl - INFO - Epoch [4][1200/1281] lr: 2.496e-02, eta: 11:31:42, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.6813, top5_acc: 0.9625, loss_cls: 1.3270, loss: 1.3270 +2025-06-24 09:04:39,162 - pyskl - INFO - Saving checkpoint at 4 epochs +2025-06-24 09:05:22,483 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:05:22,539 - pyskl - INFO - +top1_acc 0.6836 +top5_acc 0.9647 +2025-06-24 09:05:22,539 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:05:22,545 - pyskl - INFO - +mean_acc 0.5472 +2025-06-24 09:05:22,549 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_3.pth was removed +2025-06-24 09:05:22,775 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_4.pth. +2025-06-24 09:05:22,776 - pyskl - INFO - Best top1_acc is 0.6836 at 4 epoch. +2025-06-24 09:05:22,780 - pyskl - INFO - Epoch(val) [4][533] top1_acc: 0.6836, top5_acc: 0.9647, mean_class_accuracy: 0.5472 +2025-06-24 09:06:02,791 - pyskl - INFO - Epoch [5][100/1281] lr: 2.495e-02, eta: 11:30:57, time: 0.400, data_time: 0.185, memory: 4082, top1_acc: 0.7063, top5_acc: 0.9762, loss_cls: 1.2301, loss: 1.2301 +2025-06-24 09:06:24,573 - pyskl - INFO - Epoch [5][200/1281] lr: 2.495e-02, eta: 11:30:21, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7137, top5_acc: 0.9675, loss_cls: 1.2396, loss: 1.2396 +2025-06-24 09:06:46,442 - pyskl - INFO - Epoch [5][300/1281] lr: 2.495e-02, eta: 11:29:48, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7037, top5_acc: 0.9769, loss_cls: 1.2525, loss: 1.2525 +2025-06-24 09:07:07,928 - pyskl - INFO - Epoch [5][400/1281] lr: 2.495e-02, eta: 11:29:03, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7181, top5_acc: 0.9750, loss_cls: 1.2050, loss: 1.2050 +2025-06-24 09:07:29,516 - pyskl - INFO - Epoch [5][500/1281] lr: 2.495e-02, eta: 11:28:22, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.6875, top5_acc: 0.9675, loss_cls: 1.2522, loss: 1.2522 +2025-06-24 09:07:51,340 - pyskl - INFO - Epoch [5][600/1281] lr: 2.495e-02, eta: 11:27:50, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7156, top5_acc: 0.9719, loss_cls: 1.2288, loss: 1.2288 +2025-06-24 09:08:12,961 - pyskl - INFO - Epoch [5][700/1281] lr: 2.494e-02, eta: 11:27:11, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7131, top5_acc: 0.9744, loss_cls: 1.2239, loss: 1.2239 +2025-06-24 09:08:34,700 - pyskl - INFO - Epoch [5][800/1281] lr: 2.494e-02, eta: 11:26:37, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6956, top5_acc: 0.9731, loss_cls: 1.1946, loss: 1.1946 +2025-06-24 09:08:56,580 - pyskl - INFO - Epoch [5][900/1281] lr: 2.494e-02, eta: 11:26:07, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7031, top5_acc: 0.9706, loss_cls: 1.2332, loss: 1.2332 +2025-06-24 09:09:18,376 - pyskl - INFO - Epoch [5][1000/1281] lr: 2.494e-02, eta: 11:25:35, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7013, top5_acc: 0.9756, loss_cls: 1.2008, loss: 1.2008 +2025-06-24 09:09:39,845 - pyskl - INFO - Epoch [5][1100/1281] lr: 2.494e-02, eta: 11:24:54, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7344, top5_acc: 0.9706, loss_cls: 1.1585, loss: 1.1585 +2025-06-24 09:10:01,497 - pyskl - INFO - Epoch [5][1200/1281] lr: 2.493e-02, eta: 11:24:18, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7300, top5_acc: 0.9794, loss_cls: 1.1368, loss: 1.1368 +2025-06-24 09:10:19,435 - pyskl - INFO - Saving checkpoint at 5 epochs +2025-06-24 09:11:02,413 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:11:02,467 - pyskl - INFO - +top1_acc 0.7058 +top5_acc 0.9689 +2025-06-24 09:11:02,468 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:11:02,476 - pyskl - INFO - +mean_acc 0.5528 +2025-06-24 09:11:02,481 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_4.pth was removed +2025-06-24 09:11:02,662 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_5.pth. +2025-06-24 09:11:02,662 - pyskl - INFO - Best top1_acc is 0.7058 at 5 epoch. +2025-06-24 09:11:02,665 - pyskl - INFO - Epoch(val) [5][533] top1_acc: 0.7058, top5_acc: 0.9689, mean_class_accuracy: 0.5528 +2025-06-24 09:11:42,715 - pyskl - INFO - Epoch [6][100/1281] lr: 2.493e-02, eta: 11:23:40, time: 0.400, data_time: 0.186, memory: 4082, top1_acc: 0.7425, top5_acc: 0.9806, loss_cls: 1.0997, loss: 1.0997 +2025-06-24 09:12:04,577 - pyskl - INFO - Epoch [6][200/1281] lr: 2.493e-02, eta: 11:23:11, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7550, top5_acc: 0.9781, loss_cls: 1.0613, loss: 1.0613 +2025-06-24 09:12:26,082 - pyskl - INFO - Epoch [6][300/1281] lr: 2.492e-02, eta: 11:22:33, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7406, top5_acc: 0.9825, loss_cls: 1.1061, loss: 1.1061 +2025-06-24 09:12:47,845 - pyskl - INFO - Epoch [6][400/1281] lr: 2.492e-02, eta: 11:22:02, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7156, top5_acc: 0.9700, loss_cls: 1.1735, loss: 1.1735 +2025-06-24 09:13:09,626 - pyskl - INFO - Epoch [6][500/1281] lr: 2.492e-02, eta: 11:21:32, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7362, top5_acc: 0.9825, loss_cls: 1.1185, loss: 1.1185 +2025-06-24 09:13:31,328 - pyskl - INFO - Epoch [6][600/1281] lr: 2.492e-02, eta: 11:21:00, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7394, top5_acc: 0.9738, loss_cls: 1.1057, loss: 1.1057 +2025-06-24 09:13:52,805 - pyskl - INFO - Epoch [6][700/1281] lr: 2.492e-02, eta: 11:20:22, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7488, top5_acc: 0.9831, loss_cls: 1.0801, loss: 1.0801 +2025-06-24 09:14:14,250 - pyskl - INFO - Epoch [6][800/1281] lr: 2.491e-02, eta: 11:19:45, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7575, top5_acc: 0.9831, loss_cls: 1.0538, loss: 1.0538 +2025-06-24 09:14:35,935 - pyskl - INFO - Epoch [6][900/1281] lr: 2.491e-02, eta: 11:19:13, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7419, top5_acc: 0.9781, loss_cls: 1.0851, loss: 1.0851 +2025-06-24 09:14:57,517 - pyskl - INFO - Epoch [6][1000/1281] lr: 2.491e-02, eta: 11:18:40, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7562, top5_acc: 0.9838, loss_cls: 1.0526, loss: 1.0526 +2025-06-24 09:15:19,252 - pyskl - INFO - Epoch [6][1100/1281] lr: 2.491e-02, eta: 11:18:10, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7462, top5_acc: 0.9825, loss_cls: 1.0751, loss: 1.0751 +2025-06-24 09:15:41,307 - pyskl - INFO - Epoch [6][1200/1281] lr: 2.490e-02, eta: 11:17:48, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7456, top5_acc: 0.9731, loss_cls: 1.1109, loss: 1.1109 +2025-06-24 09:15:59,960 - pyskl - INFO - Saving checkpoint at 6 epochs +2025-06-24 09:16:43,076 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:16:43,143 - pyskl - INFO - +top1_acc 0.7145 +top5_acc 0.9683 +2025-06-24 09:16:43,143 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:16:43,150 - pyskl - INFO - +mean_acc 0.6276 +2025-06-24 09:16:43,154 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_5.pth was removed +2025-06-24 09:16:43,346 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_6.pth. +2025-06-24 09:16:43,346 - pyskl - INFO - Best top1_acc is 0.7145 at 6 epoch. +2025-06-24 09:16:43,349 - pyskl - INFO - Epoch(val) [6][533] top1_acc: 0.7145, top5_acc: 0.9683, mean_class_accuracy: 0.6276 +2025-06-24 09:17:23,325 - pyskl - INFO - Epoch [7][100/1281] lr: 2.490e-02, eta: 11:17:10, time: 0.400, data_time: 0.181, memory: 4082, top1_acc: 0.7412, top5_acc: 0.9819, loss_cls: 1.0699, loss: 1.0699 +2025-06-24 09:17:45,417 - pyskl - INFO - Epoch [7][200/1281] lr: 2.490e-02, eta: 11:16:50, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7606, top5_acc: 0.9831, loss_cls: 1.0106, loss: 1.0106 +2025-06-24 09:18:07,100 - pyskl - INFO - Epoch [7][300/1281] lr: 2.489e-02, eta: 11:16:19, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7781, top5_acc: 0.9825, loss_cls: 0.9704, loss: 0.9704 +2025-06-24 09:18:28,928 - pyskl - INFO - Epoch [7][400/1281] lr: 2.489e-02, eta: 11:15:53, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7481, top5_acc: 0.9781, loss_cls: 1.0800, loss: 1.0800 +2025-06-24 09:18:50,691 - pyskl - INFO - Epoch [7][500/1281] lr: 2.489e-02, eta: 11:15:24, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7575, top5_acc: 0.9831, loss_cls: 1.0324, loss: 1.0324 +2025-06-24 09:19:12,344 - pyskl - INFO - Epoch [7][600/1281] lr: 2.489e-02, eta: 11:14:54, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7606, top5_acc: 0.9862, loss_cls: 1.0085, loss: 1.0085 +2025-06-24 09:19:34,328 - pyskl - INFO - Epoch [7][700/1281] lr: 2.488e-02, eta: 11:14:31, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7656, top5_acc: 0.9831, loss_cls: 1.0073, loss: 1.0073 +2025-06-24 09:19:56,258 - pyskl - INFO - Epoch [7][800/1281] lr: 2.488e-02, eta: 11:14:07, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7712, top5_acc: 0.9838, loss_cls: 0.9712, loss: 0.9712 +2025-06-24 09:20:18,050 - pyskl - INFO - Epoch [7][900/1281] lr: 2.488e-02, eta: 11:13:40, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7650, top5_acc: 0.9838, loss_cls: 1.0264, loss: 1.0264 +2025-06-24 09:20:39,706 - pyskl - INFO - Epoch [7][1000/1281] lr: 2.487e-02, eta: 11:13:10, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7812, top5_acc: 0.9819, loss_cls: 0.9843, loss: 0.9843 +2025-06-24 09:21:01,365 - pyskl - INFO - Epoch [7][1100/1281] lr: 2.487e-02, eta: 11:12:41, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7581, top5_acc: 0.9825, loss_cls: 1.0390, loss: 1.0390 +2025-06-24 09:21:23,152 - pyskl - INFO - Epoch [7][1200/1281] lr: 2.487e-02, eta: 11:12:14, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7631, top5_acc: 0.9850, loss_cls: 1.0219, loss: 1.0219 +2025-06-24 09:21:41,399 - pyskl - INFO - Saving checkpoint at 7 epochs +2025-06-24 09:22:23,879 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:22:23,932 - pyskl - INFO - +top1_acc 0.6940 +top5_acc 0.9605 +2025-06-24 09:22:23,932 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:22:23,939 - pyskl - INFO - +mean_acc 0.5809 +2025-06-24 09:22:23,940 - pyskl - INFO - Epoch(val) [7][533] top1_acc: 0.6940, top5_acc: 0.9605, mean_class_accuracy: 0.5809 +2025-06-24 09:23:04,018 - pyskl - INFO - Epoch [8][100/1281] lr: 2.486e-02, eta: 11:11:39, time: 0.401, data_time: 0.182, memory: 4082, top1_acc: 0.7825, top5_acc: 0.9875, loss_cls: 0.9629, loss: 0.9629 +2025-06-24 09:23:26,126 - pyskl - INFO - Epoch [8][200/1281] lr: 2.486e-02, eta: 11:11:19, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7887, top5_acc: 0.9869, loss_cls: 0.9329, loss: 0.9329 +2025-06-24 09:23:48,082 - pyskl - INFO - Epoch [8][300/1281] lr: 2.486e-02, eta: 11:10:56, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7581, top5_acc: 0.9831, loss_cls: 1.0092, loss: 1.0092 +2025-06-24 09:24:10,052 - pyskl - INFO - Epoch [8][400/1281] lr: 2.485e-02, eta: 11:10:33, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7856, top5_acc: 0.9875, loss_cls: 0.9465, loss: 0.9465 +2025-06-24 09:24:31,767 - pyskl - INFO - Epoch [8][500/1281] lr: 2.485e-02, eta: 11:10:05, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7819, top5_acc: 0.9850, loss_cls: 0.9167, loss: 0.9167 +2025-06-24 09:24:53,610 - pyskl - INFO - Epoch [8][600/1281] lr: 2.485e-02, eta: 11:09:40, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7850, top5_acc: 0.9850, loss_cls: 0.9611, loss: 0.9611 +2025-06-24 09:25:15,270 - pyskl - INFO - Epoch [8][700/1281] lr: 2.484e-02, eta: 11:09:12, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7812, top5_acc: 0.9825, loss_cls: 0.9800, loss: 0.9800 +2025-06-24 09:25:37,255 - pyskl - INFO - Epoch [8][800/1281] lr: 2.484e-02, eta: 11:08:49, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7719, top5_acc: 0.9831, loss_cls: 0.9726, loss: 0.9726 +2025-06-24 09:25:59,093 - pyskl - INFO - Epoch [8][900/1281] lr: 2.484e-02, eta: 11:08:24, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7744, top5_acc: 0.9856, loss_cls: 0.9625, loss: 0.9625 +2025-06-24 09:26:20,936 - pyskl - INFO - Epoch [8][1000/1281] lr: 2.483e-02, eta: 11:07:59, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7900, top5_acc: 0.9812, loss_cls: 0.9683, loss: 0.9683 +2025-06-24 09:26:42,569 - pyskl - INFO - Epoch [8][1100/1281] lr: 2.483e-02, eta: 11:07:31, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7925, top5_acc: 0.9856, loss_cls: 0.9283, loss: 0.9283 +2025-06-24 09:27:04,439 - pyskl - INFO - Epoch [8][1200/1281] lr: 2.483e-02, eta: 11:07:06, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7987, top5_acc: 0.9844, loss_cls: 0.9274, loss: 0.9274 +2025-06-24 09:27:22,683 - pyskl - INFO - Saving checkpoint at 8 epochs +2025-06-24 09:28:06,300 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:28:06,358 - pyskl - INFO - +top1_acc 0.7877 +top5_acc 0.9811 +2025-06-24 09:28:06,359 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:28:06,365 - pyskl - INFO - +mean_acc 0.6924 +2025-06-24 09:28:06,370 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_6.pth was removed +2025-06-24 09:28:06,563 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_8.pth. +2025-06-24 09:28:06,564 - pyskl - INFO - Best top1_acc is 0.7877 at 8 epoch. +2025-06-24 09:28:06,566 - pyskl - INFO - Epoch(val) [8][533] top1_acc: 0.7877, top5_acc: 0.9811, mean_class_accuracy: 0.6924 +2025-06-24 09:28:46,859 - pyskl - INFO - Epoch [9][100/1281] lr: 2.482e-02, eta: 11:06:35, time: 0.403, data_time: 0.188, memory: 4082, top1_acc: 0.7875, top5_acc: 0.9906, loss_cls: 0.8897, loss: 0.8897 +2025-06-24 09:29:08,900 - pyskl - INFO - Epoch [9][200/1281] lr: 2.482e-02, eta: 11:06:14, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7831, top5_acc: 0.9856, loss_cls: 0.9139, loss: 0.9139 +2025-06-24 09:29:30,636 - pyskl - INFO - Epoch [9][300/1281] lr: 2.481e-02, eta: 11:05:47, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7800, top5_acc: 0.9912, loss_cls: 0.8921, loss: 0.8921 +2025-06-24 09:29:52,259 - pyskl - INFO - Epoch [9][400/1281] lr: 2.481e-02, eta: 11:05:19, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7725, top5_acc: 0.9844, loss_cls: 0.9620, loss: 0.9620 +2025-06-24 09:30:13,896 - pyskl - INFO - Epoch [9][500/1281] lr: 2.481e-02, eta: 11:04:51, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8100, top5_acc: 0.9919, loss_cls: 0.8425, loss: 0.8425 +2025-06-24 09:30:35,491 - pyskl - INFO - Epoch [9][600/1281] lr: 2.480e-02, eta: 11:04:22, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7844, top5_acc: 0.9881, loss_cls: 0.9328, loss: 0.9328 +2025-06-24 09:30:56,959 - pyskl - INFO - Epoch [9][700/1281] lr: 2.480e-02, eta: 11:03:51, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7512, top5_acc: 0.9781, loss_cls: 1.0349, loss: 1.0349 +2025-06-24 09:31:18,776 - pyskl - INFO - Epoch [9][800/1281] lr: 2.480e-02, eta: 11:03:27, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8106, top5_acc: 0.9856, loss_cls: 0.8764, loss: 0.8764 +2025-06-24 09:31:40,280 - pyskl - INFO - Epoch [9][900/1281] lr: 2.479e-02, eta: 11:02:57, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7756, top5_acc: 0.9838, loss_cls: 0.9636, loss: 0.9636 +2025-06-24 09:32:01,948 - pyskl - INFO - Epoch [9][1000/1281] lr: 2.479e-02, eta: 11:02:30, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7994, top5_acc: 0.9906, loss_cls: 0.8733, loss: 0.8733 +2025-06-24 09:32:23,370 - pyskl - INFO - Epoch [9][1100/1281] lr: 2.479e-02, eta: 11:01:59, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7831, top5_acc: 0.9856, loss_cls: 0.9363, loss: 0.9363 +2025-06-24 09:32:45,010 - pyskl - INFO - Epoch [9][1200/1281] lr: 2.478e-02, eta: 11:01:32, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7919, top5_acc: 0.9875, loss_cls: 0.9050, loss: 0.9050 +2025-06-24 09:33:03,147 - pyskl - INFO - Saving checkpoint at 9 epochs +2025-06-24 09:33:47,251 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:33:47,307 - pyskl - INFO - +top1_acc 0.7117 +top5_acc 0.9587 +2025-06-24 09:33:47,308 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:33:47,316 - pyskl - INFO - +mean_acc 0.6408 +2025-06-24 09:33:47,317 - pyskl - INFO - Epoch(val) [9][533] top1_acc: 0.7117, top5_acc: 0.9587, mean_class_accuracy: 0.6408 +2025-06-24 09:34:27,374 - pyskl - INFO - Epoch [10][100/1281] lr: 2.477e-02, eta: 11:00:57, time: 0.401, data_time: 0.184, memory: 4082, top1_acc: 0.8006, top5_acc: 0.9925, loss_cls: 0.8814, loss: 0.8814 +2025-06-24 09:34:49,276 - pyskl - INFO - Epoch [10][200/1281] lr: 2.477e-02, eta: 11:00:34, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8294, top5_acc: 0.9906, loss_cls: 0.7888, loss: 0.7888 +2025-06-24 09:35:11,159 - pyskl - INFO - Epoch [10][300/1281] lr: 2.477e-02, eta: 11:00:11, time: 0.219, data_time: 0.001, memory: 4082, top1_acc: 0.8144, top5_acc: 0.9844, loss_cls: 0.8686, loss: 0.8686 +2025-06-24 09:35:32,773 - pyskl - INFO - Epoch [10][400/1281] lr: 2.476e-02, eta: 10:59:43, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8069, top5_acc: 0.9912, loss_cls: 0.8641, loss: 0.8641 +2025-06-24 09:35:54,539 - pyskl - INFO - Epoch [10][500/1281] lr: 2.476e-02, eta: 10:59:18, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8119, top5_acc: 0.9881, loss_cls: 0.8825, loss: 0.8825 +2025-06-24 09:36:16,086 - pyskl - INFO - Epoch [10][600/1281] lr: 2.476e-02, eta: 10:58:50, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8013, top5_acc: 0.9888, loss_cls: 0.9134, loss: 0.9134 +2025-06-24 09:36:37,683 - pyskl - INFO - Epoch [10][700/1281] lr: 2.475e-02, eta: 10:58:23, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8100, top5_acc: 0.9862, loss_cls: 0.8857, loss: 0.8857 +2025-06-24 09:36:59,191 - pyskl - INFO - Epoch [10][800/1281] lr: 2.475e-02, eta: 10:57:54, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7781, top5_acc: 0.9862, loss_cls: 0.9145, loss: 0.9145 +2025-06-24 09:37:20,566 - pyskl - INFO - Epoch [10][900/1281] lr: 2.474e-02, eta: 10:57:24, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.8069, top5_acc: 0.9881, loss_cls: 0.8411, loss: 0.8411 +2025-06-24 09:37:42,414 - pyskl - INFO - Epoch [10][1000/1281] lr: 2.474e-02, eta: 10:57:01, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8031, top5_acc: 0.9875, loss_cls: 0.8910, loss: 0.8910 +2025-06-24 09:38:04,268 - pyskl - INFO - Epoch [10][1100/1281] lr: 2.473e-02, eta: 10:56:37, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8244, top5_acc: 0.9894, loss_cls: 0.8241, loss: 0.8241 +2025-06-24 09:38:26,045 - pyskl - INFO - Epoch [10][1200/1281] lr: 2.473e-02, eta: 10:56:13, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8087, top5_acc: 0.9881, loss_cls: 0.8683, loss: 0.8683 +2025-06-24 09:38:44,165 - pyskl - INFO - Saving checkpoint at 10 epochs +2025-06-24 09:39:27,079 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:39:27,146 - pyskl - INFO - +top1_acc 0.7025 +top5_acc 0.9693 +2025-06-24 09:39:27,146 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:39:27,154 - pyskl - INFO - +mean_acc 0.6068 +2025-06-24 09:39:27,156 - pyskl - INFO - Epoch(val) [10][533] top1_acc: 0.7025, top5_acc: 0.9693, mean_class_accuracy: 0.6068 +2025-06-24 09:40:07,662 - pyskl - INFO - Epoch [11][100/1281] lr: 2.472e-02, eta: 10:55:44, time: 0.405, data_time: 0.188, memory: 4082, top1_acc: 0.8019, top5_acc: 0.9912, loss_cls: 0.8472, loss: 0.8472 +2025-06-24 09:40:29,499 - pyskl - INFO - Epoch [11][200/1281] lr: 2.472e-02, eta: 10:55:21, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8213, top5_acc: 0.9825, loss_cls: 0.8400, loss: 0.8400 +2025-06-24 09:40:51,309 - pyskl - INFO - Epoch [11][300/1281] lr: 2.471e-02, eta: 10:54:57, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8206, top5_acc: 0.9881, loss_cls: 0.8003, loss: 0.8003 +2025-06-24 09:41:13,158 - pyskl - INFO - Epoch [11][400/1281] lr: 2.471e-02, eta: 10:54:34, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8150, top5_acc: 0.9912, loss_cls: 0.8178, loss: 0.8178 +2025-06-24 09:41:34,817 - pyskl - INFO - Epoch [11][500/1281] lr: 2.471e-02, eta: 10:54:08, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8000, top5_acc: 0.9875, loss_cls: 0.8542, loss: 0.8542 +2025-06-24 09:41:56,566 - pyskl - INFO - Epoch [11][600/1281] lr: 2.470e-02, eta: 10:53:43, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7987, top5_acc: 0.9881, loss_cls: 0.9016, loss: 0.9016 +2025-06-24 09:42:18,341 - pyskl - INFO - Epoch [11][700/1281] lr: 2.470e-02, eta: 10:53:19, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8206, top5_acc: 0.9944, loss_cls: 0.7949, loss: 0.7949 +2025-06-24 09:42:40,180 - pyskl - INFO - Epoch [11][800/1281] lr: 2.469e-02, eta: 10:52:56, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8281, top5_acc: 0.9919, loss_cls: 0.8004, loss: 0.8004 +2025-06-24 09:43:01,743 - pyskl - INFO - Epoch [11][900/1281] lr: 2.469e-02, eta: 10:52:29, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8150, top5_acc: 0.9906, loss_cls: 0.8238, loss: 0.8238 +2025-06-24 09:43:23,433 - pyskl - INFO - Epoch [11][1000/1281] lr: 2.468e-02, eta: 10:52:03, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8081, top5_acc: 0.9856, loss_cls: 0.8833, loss: 0.8833 +2025-06-24 09:43:45,057 - pyskl - INFO - Epoch [11][1100/1281] lr: 2.468e-02, eta: 10:51:38, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8075, top5_acc: 0.9925, loss_cls: 0.8634, loss: 0.8634 +2025-06-24 09:44:06,991 - pyskl - INFO - Epoch [11][1200/1281] lr: 2.467e-02, eta: 10:51:16, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8156, top5_acc: 0.9888, loss_cls: 0.8157, loss: 0.8157 +2025-06-24 09:44:25,158 - pyskl - INFO - Saving checkpoint at 11 epochs +2025-06-24 09:45:08,777 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:45:08,829 - pyskl - INFO - +top1_acc 0.7937 +top5_acc 0.9842 +2025-06-24 09:45:08,830 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:45:08,835 - pyskl - INFO - +mean_acc 0.7025 +2025-06-24 09:45:08,839 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_8.pth was removed +2025-06-24 09:45:09,006 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_11.pth. +2025-06-24 09:45:09,006 - pyskl - INFO - Best top1_acc is 0.7937 at 11 epoch. +2025-06-24 09:45:09,009 - pyskl - INFO - Epoch(val) [11][533] top1_acc: 0.7937, top5_acc: 0.9842, mean_class_accuracy: 0.7025 +2025-06-24 09:45:48,910 - pyskl - INFO - Epoch [12][100/1281] lr: 2.467e-02, eta: 10:50:38, time: 0.399, data_time: 0.184, memory: 4082, top1_acc: 0.8100, top5_acc: 0.9931, loss_cls: 0.8408, loss: 0.8408 +2025-06-24 09:46:10,845 - pyskl - INFO - Epoch [12][200/1281] lr: 2.466e-02, eta: 10:50:16, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8181, top5_acc: 0.9944, loss_cls: 0.7633, loss: 0.7633 +2025-06-24 09:46:32,585 - pyskl - INFO - Epoch [12][300/1281] lr: 2.466e-02, eta: 10:49:52, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8125, top5_acc: 0.9881, loss_cls: 0.7876, loss: 0.7876 +2025-06-24 09:46:54,593 - pyskl - INFO - Epoch [12][400/1281] lr: 2.465e-02, eta: 10:49:31, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8013, top5_acc: 0.9925, loss_cls: 0.8440, loss: 0.8440 +2025-06-24 09:47:16,339 - pyskl - INFO - Epoch [12][500/1281] lr: 2.465e-02, eta: 10:49:07, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8244, top5_acc: 0.9912, loss_cls: 0.8202, loss: 0.8202 +2025-06-24 09:47:38,052 - pyskl - INFO - Epoch [12][600/1281] lr: 2.464e-02, eta: 10:48:42, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8294, top5_acc: 0.9906, loss_cls: 0.8139, loss: 0.8139 +2025-06-24 09:47:59,804 - pyskl - INFO - Epoch [12][700/1281] lr: 2.464e-02, eta: 10:48:18, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8087, top5_acc: 0.9875, loss_cls: 0.8553, loss: 0.8553 +2025-06-24 09:48:21,440 - pyskl - INFO - Epoch [12][800/1281] lr: 2.463e-02, eta: 10:47:52, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8250, top5_acc: 0.9844, loss_cls: 0.8336, loss: 0.8336 +2025-06-24 09:48:42,994 - pyskl - INFO - Epoch [12][900/1281] lr: 2.463e-02, eta: 10:47:26, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8100, top5_acc: 0.9950, loss_cls: 0.8144, loss: 0.8144 +2025-06-24 09:49:04,635 - pyskl - INFO - Epoch [12][1000/1281] lr: 2.462e-02, eta: 10:47:01, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8219, top5_acc: 0.9912, loss_cls: 0.8156, loss: 0.8156 +2025-06-24 09:49:26,196 - pyskl - INFO - Epoch [12][1100/1281] lr: 2.462e-02, eta: 10:46:35, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8169, top5_acc: 0.9894, loss_cls: 0.8537, loss: 0.8537 +2025-06-24 09:49:47,809 - pyskl - INFO - Epoch [12][1200/1281] lr: 2.461e-02, eta: 10:46:09, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8256, top5_acc: 0.9919, loss_cls: 0.7849, loss: 0.7849 +2025-06-24 09:50:05,849 - pyskl - INFO - Saving checkpoint at 12 epochs +2025-06-24 09:50:49,308 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:50:49,362 - pyskl - INFO - +top1_acc 0.7784 +top5_acc 0.9779 +2025-06-24 09:50:49,362 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:50:49,369 - pyskl - INFO - +mean_acc 0.6862 +2025-06-24 09:50:49,371 - pyskl - INFO - Epoch(val) [12][533] top1_acc: 0.7784, top5_acc: 0.9779, mean_class_accuracy: 0.6862 +2025-06-24 09:51:29,394 - pyskl - INFO - Epoch [13][100/1281] lr: 2.460e-02, eta: 10:45:33, time: 0.400, data_time: 0.184, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9931, loss_cls: 0.7781, loss: 0.7781 +2025-06-24 09:51:51,318 - pyskl - INFO - Epoch [13][200/1281] lr: 2.460e-02, eta: 10:45:11, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8150, top5_acc: 0.9906, loss_cls: 0.8321, loss: 0.8321 +2025-06-24 09:52:12,930 - pyskl - INFO - Epoch [13][300/1281] lr: 2.459e-02, eta: 10:44:46, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9912, loss_cls: 0.7442, loss: 0.7442 +2025-06-24 09:52:34,580 - pyskl - INFO - Epoch [13][400/1281] lr: 2.459e-02, eta: 10:44:21, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8256, top5_acc: 0.9925, loss_cls: 0.7694, loss: 0.7694 +2025-06-24 09:52:56,241 - pyskl - INFO - Epoch [13][500/1281] lr: 2.458e-02, eta: 10:43:56, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8244, top5_acc: 0.9931, loss_cls: 0.7767, loss: 0.7767 +2025-06-24 09:53:17,853 - pyskl - INFO - Epoch [13][600/1281] lr: 2.458e-02, eta: 10:43:31, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8406, top5_acc: 0.9894, loss_cls: 0.7486, loss: 0.7486 +2025-06-24 09:53:39,559 - pyskl - INFO - Epoch [13][700/1281] lr: 2.457e-02, eta: 10:43:07, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8000, top5_acc: 0.9894, loss_cls: 0.8288, loss: 0.8288 +2025-06-24 09:54:01,173 - pyskl - INFO - Epoch [13][800/1281] lr: 2.457e-02, eta: 10:42:41, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8369, top5_acc: 0.9950, loss_cls: 0.7818, loss: 0.7818 +2025-06-24 09:54:22,857 - pyskl - INFO - Epoch [13][900/1281] lr: 2.456e-02, eta: 10:42:17, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8144, top5_acc: 0.9906, loss_cls: 0.8151, loss: 0.8151 +2025-06-24 09:54:44,282 - pyskl - INFO - Epoch [13][1000/1281] lr: 2.455e-02, eta: 10:41:50, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9906, loss_cls: 0.7655, loss: 0.7655 +2025-06-24 09:55:05,916 - pyskl - INFO - Epoch [13][1100/1281] lr: 2.455e-02, eta: 10:41:25, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8356, top5_acc: 0.9900, loss_cls: 0.7596, loss: 0.7596 +2025-06-24 09:55:27,757 - pyskl - INFO - Epoch [13][1200/1281] lr: 2.454e-02, eta: 10:41:02, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8019, top5_acc: 0.9900, loss_cls: 0.8458, loss: 0.8458 +2025-06-24 09:55:45,893 - pyskl - INFO - Saving checkpoint at 13 epochs +2025-06-24 09:56:29,146 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:56:29,202 - pyskl - INFO - +top1_acc 0.7393 +top5_acc 0.9783 +2025-06-24 09:56:29,202 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:56:29,209 - pyskl - INFO - +mean_acc 0.6651 +2025-06-24 09:56:29,211 - pyskl - INFO - Epoch(val) [13][533] top1_acc: 0.7393, top5_acc: 0.9783, mean_class_accuracy: 0.6651 +2025-06-24 09:57:09,327 - pyskl - INFO - Epoch [14][100/1281] lr: 2.453e-02, eta: 10:40:28, time: 0.401, data_time: 0.184, memory: 4082, top1_acc: 0.8306, top5_acc: 0.9888, loss_cls: 0.7756, loss: 0.7756 +2025-06-24 09:57:31,322 - pyskl - INFO - Epoch [14][200/1281] lr: 2.453e-02, eta: 10:40:07, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8394, top5_acc: 0.9956, loss_cls: 0.7225, loss: 0.7225 +2025-06-24 09:57:52,729 - pyskl - INFO - Epoch [14][300/1281] lr: 2.452e-02, eta: 10:39:39, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.8356, top5_acc: 0.9944, loss_cls: 0.7594, loss: 0.7594 +2025-06-24 09:58:14,746 - pyskl - INFO - Epoch [14][400/1281] lr: 2.452e-02, eta: 10:39:19, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8431, top5_acc: 0.9931, loss_cls: 0.7326, loss: 0.7326 +2025-06-24 09:58:36,431 - pyskl - INFO - Epoch [14][500/1281] lr: 2.451e-02, eta: 10:38:54, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9912, loss_cls: 0.7710, loss: 0.7710 +2025-06-24 09:58:58,032 - pyskl - INFO - Epoch [14][600/1281] lr: 2.451e-02, eta: 10:38:29, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8356, top5_acc: 0.9931, loss_cls: 0.7642, loss: 0.7642 +2025-06-24 09:59:19,463 - pyskl - INFO - Epoch [14][700/1281] lr: 2.450e-02, eta: 10:38:03, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9944, loss_cls: 0.7766, loss: 0.7766 +2025-06-24 09:59:41,077 - pyskl - INFO - Epoch [14][800/1281] lr: 2.449e-02, eta: 10:37:38, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8187, top5_acc: 0.9888, loss_cls: 0.7863, loss: 0.7863 +2025-06-24 10:00:02,733 - pyskl - INFO - Epoch [14][900/1281] lr: 2.449e-02, eta: 10:37:14, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8444, top5_acc: 0.9919, loss_cls: 0.7554, loss: 0.7554 +2025-06-24 10:00:24,401 - pyskl - INFO - Epoch [14][1000/1281] lr: 2.448e-02, eta: 10:36:49, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8269, top5_acc: 0.9919, loss_cls: 0.7995, loss: 0.7995 +2025-06-24 10:00:46,364 - pyskl - INFO - Epoch [14][1100/1281] lr: 2.448e-02, eta: 10:36:28, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8219, top5_acc: 0.9931, loss_cls: 0.8208, loss: 0.8208 +2025-06-24 10:01:08,537 - pyskl - INFO - Epoch [14][1200/1281] lr: 2.447e-02, eta: 10:36:09, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.8344, top5_acc: 0.9919, loss_cls: 0.7679, loss: 0.7679 +2025-06-24 10:01:26,859 - pyskl - INFO - Saving checkpoint at 14 epochs +2025-06-24 10:02:10,125 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:02:10,181 - pyskl - INFO - +top1_acc 0.8001 +top5_acc 0.9873 +2025-06-24 10:02:10,181 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:02:10,188 - pyskl - INFO - +mean_acc 0.7023 +2025-06-24 10:02:10,192 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_11.pth was removed +2025-06-24 10:02:10,357 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_14.pth. +2025-06-24 10:02:10,357 - pyskl - INFO - Best top1_acc is 0.8001 at 14 epoch. +2025-06-24 10:02:10,360 - pyskl - INFO - Epoch(val) [14][533] top1_acc: 0.8001, top5_acc: 0.9873, mean_class_accuracy: 0.7023 +2025-06-24 10:02:50,382 - pyskl - INFO - Epoch [15][100/1281] lr: 2.446e-02, eta: 10:35:33, time: 0.400, data_time: 0.184, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9919, loss_cls: 0.7635, loss: 0.7635 +2025-06-24 10:03:12,263 - pyskl - INFO - Epoch [15][200/1281] lr: 2.445e-02, eta: 10:35:11, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8237, top5_acc: 0.9919, loss_cls: 0.8123, loss: 0.8123 +2025-06-24 10:03:34,327 - pyskl - INFO - Epoch [15][300/1281] lr: 2.445e-02, eta: 10:34:50, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9925, loss_cls: 0.7360, loss: 0.7360 +2025-06-24 10:03:56,259 - pyskl - INFO - Epoch [15][400/1281] lr: 2.444e-02, eta: 10:34:29, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8175, top5_acc: 0.9831, loss_cls: 0.8006, loss: 0.8006 +2025-06-24 10:04:17,965 - pyskl - INFO - Epoch [15][500/1281] lr: 2.444e-02, eta: 10:34:05, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8356, top5_acc: 0.9944, loss_cls: 0.7308, loss: 0.7308 +2025-06-24 10:04:39,909 - pyskl - INFO - Epoch [15][600/1281] lr: 2.443e-02, eta: 10:33:44, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8413, top5_acc: 0.9938, loss_cls: 0.7367, loss: 0.7367 +2025-06-24 10:05:01,471 - pyskl - INFO - Epoch [15][700/1281] lr: 2.442e-02, eta: 10:33:19, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8381, top5_acc: 0.9962, loss_cls: 0.7211, loss: 0.7211 +2025-06-24 10:05:23,333 - pyskl - INFO - Epoch [15][800/1281] lr: 2.442e-02, eta: 10:32:56, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9931, loss_cls: 0.7416, loss: 0.7416 +2025-06-24 10:05:45,177 - pyskl - INFO - Epoch [15][900/1281] lr: 2.441e-02, eta: 10:32:34, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8538, top5_acc: 0.9962, loss_cls: 0.7047, loss: 0.7047 +2025-06-24 10:06:06,846 - pyskl - INFO - Epoch [15][1000/1281] lr: 2.441e-02, eta: 10:32:10, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8337, top5_acc: 0.9919, loss_cls: 0.7755, loss: 0.7755 +2025-06-24 10:06:28,493 - pyskl - INFO - Epoch [15][1100/1281] lr: 2.440e-02, eta: 10:31:46, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8119, top5_acc: 0.9869, loss_cls: 0.8444, loss: 0.8444 +2025-06-24 10:06:50,185 - pyskl - INFO - Epoch [15][1200/1281] lr: 2.439e-02, eta: 10:31:22, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8063, top5_acc: 0.9881, loss_cls: 0.8250, loss: 0.8250 +2025-06-24 10:07:08,576 - pyskl - INFO - Saving checkpoint at 15 epochs +2025-06-24 10:07:51,694 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:07:51,750 - pyskl - INFO - +top1_acc 0.8031 +top5_acc 0.9862 +2025-06-24 10:07:51,750 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:07:51,757 - pyskl - INFO - +mean_acc 0.7208 +2025-06-24 10:07:51,761 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_14.pth was removed +2025-06-24 10:07:51,934 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_15.pth. +2025-06-24 10:07:51,934 - pyskl - INFO - Best top1_acc is 0.8031 at 15 epoch. +2025-06-24 10:07:51,937 - pyskl - INFO - Epoch(val) [15][533] top1_acc: 0.8031, top5_acc: 0.9862, mean_class_accuracy: 0.7208 +2025-06-24 10:08:31,958 - pyskl - INFO - Epoch [16][100/1281] lr: 2.438e-02, eta: 10:30:46, time: 0.400, data_time: 0.182, memory: 4082, top1_acc: 0.8750, top5_acc: 0.9956, loss_cls: 0.6219, loss: 0.6219 +2025-06-24 10:08:53,911 - pyskl - INFO - Epoch [16][200/1281] lr: 2.438e-02, eta: 10:30:24, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8363, top5_acc: 0.9938, loss_cls: 0.7396, loss: 0.7396 +2025-06-24 10:09:15,574 - pyskl - INFO - Epoch [16][300/1281] lr: 2.437e-02, eta: 10:30:00, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8475, top5_acc: 0.9900, loss_cls: 0.7236, loss: 0.7236 +2025-06-24 10:09:37,276 - pyskl - INFO - Epoch [16][400/1281] lr: 2.436e-02, eta: 10:29:37, time: 0.217, data_time: 0.001, memory: 4082, top1_acc: 0.8550, top5_acc: 0.9900, loss_cls: 0.6828, loss: 0.6828 +2025-06-24 10:09:59,169 - pyskl - INFO - Epoch [16][500/1281] lr: 2.436e-02, eta: 10:29:15, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8337, top5_acc: 0.9919, loss_cls: 0.7313, loss: 0.7313 +2025-06-24 10:10:20,950 - pyskl - INFO - Epoch [16][600/1281] lr: 2.435e-02, eta: 10:28:52, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8244, top5_acc: 0.9938, loss_cls: 0.7849, loss: 0.7849 +2025-06-24 10:10:42,508 - pyskl - INFO - Epoch [16][700/1281] lr: 2.434e-02, eta: 10:28:27, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8488, top5_acc: 0.9925, loss_cls: 0.7270, loss: 0.7270 +2025-06-24 10:11:04,176 - pyskl - INFO - Epoch [16][800/1281] lr: 2.434e-02, eta: 10:28:03, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8294, top5_acc: 0.9875, loss_cls: 0.7770, loss: 0.7770 +2025-06-24 10:11:25,945 - pyskl - INFO - Epoch [16][900/1281] lr: 2.433e-02, eta: 10:27:40, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9894, loss_cls: 0.7715, loss: 0.7715 +2025-06-24 10:11:47,561 - pyskl - INFO - Epoch [16][1000/1281] lr: 2.432e-02, eta: 10:27:16, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8363, top5_acc: 0.9931, loss_cls: 0.7612, loss: 0.7612 +2025-06-24 10:12:09,222 - pyskl - INFO - Epoch [16][1100/1281] lr: 2.432e-02, eta: 10:26:52, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8462, top5_acc: 0.9925, loss_cls: 0.7064, loss: 0.7064 +2025-06-24 10:12:31,092 - pyskl - INFO - Epoch [16][1200/1281] lr: 2.431e-02, eta: 10:26:30, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8481, top5_acc: 0.9950, loss_cls: 0.7171, loss: 0.7171 +2025-06-24 10:12:49,965 - pyskl - INFO - Saving checkpoint at 16 epochs +2025-06-24 10:14:01,138 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:14:01,193 - pyskl - INFO - +top1_acc 0.7861 +top5_acc 0.9854 +2025-06-24 10:14:01,193 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:14:01,200 - pyskl - INFO - +mean_acc 0.7118 +2025-06-24 10:14:01,202 - pyskl - INFO - Epoch(val) [16][533] top1_acc: 0.7861, top5_acc: 0.9854, mean_class_accuracy: 0.7118 +2025-06-24 10:15:03,980 - pyskl - INFO - Epoch [17][100/1281] lr: 2.430e-02, eta: 10:29:03, time: 0.628, data_time: 0.194, memory: 4082, top1_acc: 0.8638, top5_acc: 0.9950, loss_cls: 0.6501, loss: 0.6501 +2025-06-24 10:15:45,683 - pyskl - INFO - Epoch [17][200/1281] lr: 2.429e-02, eta: 10:31:25, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8475, top5_acc: 0.9931, loss_cls: 0.7095, loss: 0.7095 +2025-06-24 10:16:27,224 - pyskl - INFO - Epoch [17][300/1281] lr: 2.428e-02, eta: 10:33:43, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8438, top5_acc: 0.9931, loss_cls: 0.7307, loss: 0.7307 +2025-06-24 10:17:08,586 - pyskl - INFO - Epoch [17][400/1281] lr: 2.428e-02, eta: 10:35:58, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8413, top5_acc: 0.9881, loss_cls: 0.7460, loss: 0.7460 +2025-06-24 10:17:50,004 - pyskl - INFO - Epoch [17][500/1281] lr: 2.427e-02, eta: 10:38:11, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9950, loss_cls: 0.7194, loss: 0.7194 +2025-06-24 10:18:31,475 - pyskl - INFO - Epoch [17][600/1281] lr: 2.426e-02, eta: 10:40:24, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9944, loss_cls: 0.7543, loss: 0.7543 +2025-06-24 10:19:12,979 - pyskl - INFO - Epoch [17][700/1281] lr: 2.426e-02, eta: 10:42:35, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9975, loss_cls: 0.7330, loss: 0.7330 +2025-06-24 10:19:54,552 - pyskl - INFO - Epoch [17][800/1281] lr: 2.425e-02, eta: 10:44:45, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8812, top5_acc: 0.9881, loss_cls: 0.6730, loss: 0.6730 +2025-06-24 10:20:36,153 - pyskl - INFO - Epoch [17][900/1281] lr: 2.424e-02, eta: 10:46:54, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8494, top5_acc: 0.9925, loss_cls: 0.7068, loss: 0.7068 +2025-06-24 10:21:17,654 - pyskl - INFO - Epoch [17][1000/1281] lr: 2.424e-02, eta: 10:49:00, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9906, loss_cls: 0.7484, loss: 0.7484 +2025-06-24 10:21:52,066 - pyskl - INFO - Epoch [17][1100/1281] lr: 2.423e-02, eta: 10:50:09, time: 0.344, data_time: 0.000, memory: 4082, top1_acc: 0.8438, top5_acc: 0.9931, loss_cls: 0.7081, loss: 0.7081 +2025-06-24 10:22:25,519 - pyskl - INFO - Epoch [17][1200/1281] lr: 2.422e-02, eta: 10:51:09, time: 0.334, data_time: 0.000, memory: 4082, top1_acc: 0.8394, top5_acc: 0.9900, loss_cls: 0.7711, loss: 0.7711 +2025-06-24 10:22:59,638 - pyskl - INFO - Saving checkpoint at 17 epochs +2025-06-24 10:24:11,287 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:24:11,355 - pyskl - INFO - +top1_acc 0.8160 +top5_acc 0.9858 +2025-06-24 10:24:11,355 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:24:11,363 - pyskl - INFO - +mean_acc 0.7463 +2025-06-24 10:24:11,368 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_15.pth was removed +2025-06-24 10:24:11,557 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_17.pth. +2025-06-24 10:24:11,557 - pyskl - INFO - Best top1_acc is 0.8160 at 17 epoch. +2025-06-24 10:24:11,560 - pyskl - INFO - Epoch(val) [17][533] top1_acc: 0.8160, top5_acc: 0.9858, mean_class_accuracy: 0.7463 +2025-06-24 10:25:12,963 - pyskl - INFO - Epoch [18][100/1281] lr: 2.421e-02, eta: 10:53:02, time: 0.614, data_time: 0.197, memory: 4082, top1_acc: 0.8525, top5_acc: 0.9944, loss_cls: 0.6603, loss: 0.6603 +2025-06-24 10:25:54,558 - pyskl - INFO - Epoch [18][200/1281] lr: 2.420e-02, eta: 10:55:03, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8569, top5_acc: 0.9906, loss_cls: 0.6448, loss: 0.6448 +2025-06-24 10:26:36,118 - pyskl - INFO - Epoch [18][300/1281] lr: 2.419e-02, eta: 10:57:02, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9944, loss_cls: 0.6632, loss: 0.6632 +2025-06-24 10:27:17,806 - pyskl - INFO - Epoch [18][400/1281] lr: 2.419e-02, eta: 10:59:01, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8281, top5_acc: 0.9931, loss_cls: 0.7458, loss: 0.7458 +2025-06-24 10:27:59,262 - pyskl - INFO - Epoch [18][500/1281] lr: 2.418e-02, eta: 11:00:56, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8712, top5_acc: 0.9925, loss_cls: 0.6162, loss: 0.6162 +2025-06-24 10:28:40,770 - pyskl - INFO - Epoch [18][600/1281] lr: 2.417e-02, eta: 11:02:51, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9944, loss_cls: 0.6589, loss: 0.6589 +2025-06-24 10:29:22,208 - pyskl - INFO - Epoch [18][700/1281] lr: 2.417e-02, eta: 11:04:43, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8431, top5_acc: 0.9925, loss_cls: 0.7121, loss: 0.7121 +2025-06-24 10:30:03,875 - pyskl - INFO - Epoch [18][800/1281] lr: 2.416e-02, eta: 11:06:36, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9931, loss_cls: 0.7059, loss: 0.7059 +2025-06-24 10:30:45,280 - pyskl - INFO - Epoch [18][900/1281] lr: 2.415e-02, eta: 11:08:26, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8425, top5_acc: 0.9912, loss_cls: 0.7450, loss: 0.7450 +2025-06-24 10:31:26,867 - pyskl - INFO - Epoch [18][1000/1281] lr: 2.414e-02, eta: 11:10:16, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8544, top5_acc: 0.9950, loss_cls: 0.6640, loss: 0.6640 +2025-06-24 10:32:02,314 - pyskl - INFO - Epoch [18][1100/1281] lr: 2.414e-02, eta: 11:11:18, time: 0.354, data_time: 0.000, memory: 4082, top1_acc: 0.8569, top5_acc: 0.9925, loss_cls: 0.6642, loss: 0.6642 +2025-06-24 10:32:35,216 - pyskl - INFO - Epoch [18][1200/1281] lr: 2.413e-02, eta: 11:12:02, time: 0.329, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9944, loss_cls: 0.7308, loss: 0.7308 +2025-06-24 10:33:10,035 - pyskl - INFO - Saving checkpoint at 18 epochs +2025-06-24 10:34:21,982 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:34:22,051 - pyskl - INFO - +top1_acc 0.8243 +top5_acc 0.9874 +2025-06-24 10:34:22,051 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:34:22,058 - pyskl - INFO - +mean_acc 0.7497 +2025-06-24 10:34:22,062 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_17.pth was removed +2025-06-24 10:34:22,235 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_18.pth. +2025-06-24 10:34:22,235 - pyskl - INFO - Best top1_acc is 0.8243 at 18 epoch. +2025-06-24 10:34:22,238 - pyskl - INFO - Epoch(val) [18][533] top1_acc: 0.8243, top5_acc: 0.9874, mean_class_accuracy: 0.7497 +2025-06-24 10:35:23,637 - pyskl - INFO - Epoch [19][100/1281] lr: 2.411e-02, eta: 11:13:32, time: 0.614, data_time: 0.199, memory: 4082, top1_acc: 0.8556, top5_acc: 0.9950, loss_cls: 0.6487, loss: 0.6487 +2025-06-24 10:36:05,160 - pyskl - INFO - Epoch [19][200/1281] lr: 2.411e-02, eta: 11:15:16, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9925, loss_cls: 0.6978, loss: 0.6978 +2025-06-24 10:36:46,825 - pyskl - INFO - Epoch [19][300/1281] lr: 2.410e-02, eta: 11:16:59, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8738, top5_acc: 0.9925, loss_cls: 0.6256, loss: 0.6256 +2025-06-24 10:37:28,661 - pyskl - INFO - Epoch [19][400/1281] lr: 2.409e-02, eta: 11:18:43, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8456, top5_acc: 0.9919, loss_cls: 0.7035, loss: 0.7035 +2025-06-24 10:38:10,315 - pyskl - INFO - Epoch [19][500/1281] lr: 2.408e-02, eta: 11:20:24, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8431, top5_acc: 0.9931, loss_cls: 0.6992, loss: 0.6992 +2025-06-24 10:38:52,090 - pyskl - INFO - Epoch [19][600/1281] lr: 2.408e-02, eta: 11:22:05, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8269, top5_acc: 0.9912, loss_cls: 0.7467, loss: 0.7467 +2025-06-24 10:39:35,393 - pyskl - INFO - Epoch [19][700/1281] lr: 2.407e-02, eta: 11:23:56, time: 0.433, data_time: 0.000, memory: 4082, top1_acc: 0.8512, top5_acc: 0.9912, loss_cls: 0.6918, loss: 0.6918 +2025-06-24 10:40:16,901 - pyskl - INFO - Epoch [19][800/1281] lr: 2.406e-02, eta: 11:25:32, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8469, top5_acc: 0.9956, loss_cls: 0.6741, loss: 0.6741 +2025-06-24 10:40:58,448 - pyskl - INFO - Epoch [19][900/1281] lr: 2.405e-02, eta: 11:27:08, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8413, top5_acc: 0.9931, loss_cls: 0.7510, loss: 0.7510 +2025-06-24 10:41:39,782 - pyskl - INFO - Epoch [19][1000/1281] lr: 2.405e-02, eta: 11:28:41, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8600, top5_acc: 0.9950, loss_cls: 0.6889, loss: 0.6889 +2025-06-24 10:42:15,105 - pyskl - INFO - Epoch [19][1100/1281] lr: 2.404e-02, eta: 11:29:31, time: 0.353, data_time: 0.000, memory: 4082, top1_acc: 0.8719, top5_acc: 0.9938, loss_cls: 0.6481, loss: 0.6481 +2025-06-24 10:42:47,811 - pyskl - INFO - Epoch [19][1200/1281] lr: 2.403e-02, eta: 11:30:02, time: 0.327, data_time: 0.000, memory: 4082, top1_acc: 0.8500, top5_acc: 0.9881, loss_cls: 0.7113, loss: 0.7113 +2025-06-24 10:43:22,911 - pyskl - INFO - Saving checkpoint at 19 epochs +2025-06-24 10:44:35,175 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:44:35,243 - pyskl - INFO - +top1_acc 0.8269 +top5_acc 0.9863 +2025-06-24 10:44:35,243 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:44:35,251 - pyskl - INFO - +mean_acc 0.7547 +2025-06-24 10:44:35,255 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_18.pth was removed +2025-06-24 10:44:35,469 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_19.pth. +2025-06-24 10:44:35,469 - pyskl - INFO - Best top1_acc is 0.8269 at 19 epoch. +2025-06-24 10:44:35,472 - pyskl - INFO - Epoch(val) [19][533] top1_acc: 0.8269, top5_acc: 0.9863, mean_class_accuracy: 0.7547 +2025-06-24 10:45:36,911 - pyskl - INFO - Epoch [20][100/1281] lr: 2.402e-02, eta: 11:31:13, time: 0.614, data_time: 0.199, memory: 4082, top1_acc: 0.8650, top5_acc: 0.9950, loss_cls: 0.6724, loss: 0.6724 +2025-06-24 10:46:18,442 - pyskl - INFO - Epoch [20][200/1281] lr: 2.401e-02, eta: 11:32:43, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8606, top5_acc: 0.9950, loss_cls: 0.6958, loss: 0.6958 +2025-06-24 10:47:00,042 - pyskl - INFO - Epoch [20][300/1281] lr: 2.400e-02, eta: 11:34:12, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8600, top5_acc: 0.9938, loss_cls: 0.6704, loss: 0.6704 +2025-06-24 10:47:41,575 - pyskl - INFO - Epoch [20][400/1281] lr: 2.399e-02, eta: 11:35:40, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8519, top5_acc: 0.9956, loss_cls: 0.6726, loss: 0.6726 +2025-06-24 10:48:23,200 - pyskl - INFO - Epoch [20][500/1281] lr: 2.398e-02, eta: 11:37:08, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8562, top5_acc: 0.9900, loss_cls: 0.7004, loss: 0.7004 +2025-06-24 10:49:04,740 - pyskl - INFO - Epoch [20][600/1281] lr: 2.398e-02, eta: 11:38:34, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9938, loss_cls: 0.6700, loss: 0.6700 +2025-06-24 10:49:46,241 - pyskl - INFO - Epoch [20][700/1281] lr: 2.397e-02, eta: 11:39:58, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8725, top5_acc: 0.9969, loss_cls: 0.6204, loss: 0.6204 +2025-06-24 10:50:27,922 - pyskl - INFO - Epoch [20][800/1281] lr: 2.396e-02, eta: 11:41:23, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8481, top5_acc: 0.9925, loss_cls: 0.6956, loss: 0.6956 +2025-06-24 10:51:09,541 - pyskl - INFO - Epoch [20][900/1281] lr: 2.395e-02, eta: 11:42:46, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8512, top5_acc: 0.9906, loss_cls: 0.6940, loss: 0.6940 +2025-06-24 10:51:51,220 - pyskl - INFO - Epoch [20][1000/1281] lr: 2.394e-02, eta: 11:44:09, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8475, top5_acc: 0.9975, loss_cls: 0.6721, loss: 0.6721 +2025-06-24 10:52:25,814 - pyskl - INFO - Epoch [20][1100/1281] lr: 2.393e-02, eta: 11:44:45, time: 0.346, data_time: 0.000, memory: 4082, top1_acc: 0.8550, top5_acc: 0.9919, loss_cls: 0.6911, loss: 0.6911 +2025-06-24 10:52:58,490 - pyskl - INFO - Epoch [20][1200/1281] lr: 2.393e-02, eta: 11:45:07, time: 0.327, data_time: 0.000, memory: 4082, top1_acc: 0.8556, top5_acc: 0.9969, loss_cls: 0.6538, loss: 0.6538 +2025-06-24 10:53:33,390 - pyskl - INFO - Saving checkpoint at 20 epochs +2025-06-24 10:54:45,112 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:54:45,167 - pyskl - INFO - +top1_acc 0.8319 +top5_acc 0.9870 +2025-06-24 10:54:45,167 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:54:45,173 - pyskl - INFO - +mean_acc 0.7765 +2025-06-24 10:54:45,177 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_19.pth was removed +2025-06-24 10:54:45,352 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_20.pth. +2025-06-24 10:54:45,353 - pyskl - INFO - Best top1_acc is 0.8319 at 20 epoch. +2025-06-24 10:54:45,355 - pyskl - INFO - Epoch(val) [20][533] top1_acc: 0.8319, top5_acc: 0.9870, mean_class_accuracy: 0.7765 +2025-06-24 10:55:47,305 - pyskl - INFO - Epoch [21][100/1281] lr: 2.391e-02, eta: 11:46:04, time: 0.619, data_time: 0.196, memory: 4082, top1_acc: 0.8788, top5_acc: 0.9950, loss_cls: 0.5920, loss: 0.5920 +2025-06-24 10:56:29,150 - pyskl - INFO - Epoch [21][200/1281] lr: 2.390e-02, eta: 11:47:24, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8794, top5_acc: 0.9956, loss_cls: 0.5994, loss: 0.5994 +2025-06-24 10:57:10,661 - pyskl - INFO - Epoch [21][300/1281] lr: 2.389e-02, eta: 11:48:41, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8756, top5_acc: 0.9944, loss_cls: 0.5931, loss: 0.5931 +2025-06-24 10:57:52,193 - pyskl - INFO - Epoch [21][400/1281] lr: 2.389e-02, eta: 11:49:58, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8700, top5_acc: 0.9925, loss_cls: 0.6120, loss: 0.6120 +2025-06-24 10:58:33,809 - pyskl - INFO - Epoch [21][500/1281] lr: 2.388e-02, eta: 11:51:14, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8669, top5_acc: 0.9931, loss_cls: 0.6302, loss: 0.6302 +2025-06-24 10:59:15,322 - pyskl - INFO - Epoch [21][600/1281] lr: 2.387e-02, eta: 11:52:28, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8662, top5_acc: 0.9900, loss_cls: 0.6729, loss: 0.6729 +2025-06-24 10:59:56,802 - pyskl - INFO - Epoch [21][700/1281] lr: 2.386e-02, eta: 11:53:41, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8800, top5_acc: 0.9950, loss_cls: 0.6082, loss: 0.6082 +2025-06-24 11:00:38,335 - pyskl - INFO - Epoch [21][800/1281] lr: 2.385e-02, eta: 11:54:54, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9956, loss_cls: 0.7651, loss: 0.7651 +2025-06-24 11:01:19,803 - pyskl - INFO - Epoch [21][900/1281] lr: 2.384e-02, eta: 11:56:05, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8506, top5_acc: 0.9944, loss_cls: 0.7038, loss: 0.7038 +2025-06-24 11:02:01,323 - pyskl - INFO - Epoch [21][1000/1281] lr: 2.383e-02, eta: 11:57:16, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8700, top5_acc: 0.9925, loss_cls: 0.6220, loss: 0.6220 +2025-06-24 11:02:37,512 - pyskl - INFO - Epoch [21][1100/1281] lr: 2.383e-02, eta: 11:57:53, time: 0.362, data_time: 0.000, memory: 4082, top1_acc: 0.8538, top5_acc: 0.9956, loss_cls: 0.6877, loss: 0.6877 +2025-06-24 11:03:09,867 - pyskl - INFO - Epoch [21][1200/1281] lr: 2.382e-02, eta: 11:58:06, time: 0.324, data_time: 0.000, memory: 4082, top1_acc: 0.8612, top5_acc: 0.9956, loss_cls: 0.6794, loss: 0.6794 +2025-06-24 11:03:45,365 - pyskl - INFO - Saving checkpoint at 21 epochs +2025-06-24 11:04:56,487 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:04:56,542 - pyskl - INFO - +top1_acc 0.8200 +top5_acc 0.9852 +2025-06-24 11:04:56,542 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:04:56,549 - pyskl - INFO - +mean_acc 0.7481 +2025-06-24 11:04:56,551 - pyskl - INFO - Epoch(val) [21][533] top1_acc: 0.8200, top5_acc: 0.9852, mean_class_accuracy: 0.7481 +2025-06-24 11:05:58,034 - pyskl - INFO - Epoch [22][100/1281] lr: 2.380e-02, eta: 11:58:47, time: 0.615, data_time: 0.200, memory: 4082, top1_acc: 0.8825, top5_acc: 0.9975, loss_cls: 0.5826, loss: 0.5826 +2025-06-24 11:06:39,572 - pyskl - INFO - Epoch [22][200/1281] lr: 2.379e-02, eta: 11:59:54, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8594, top5_acc: 0.9956, loss_cls: 0.6424, loss: 0.6424 +2025-06-24 11:07:21,131 - pyskl - INFO - Epoch [22][300/1281] lr: 2.378e-02, eta: 12:01:02, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8681, top5_acc: 0.9931, loss_cls: 0.6767, loss: 0.6767 +2025-06-24 11:08:02,519 - pyskl - INFO - Epoch [22][400/1281] lr: 2.378e-02, eta: 12:02:07, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8794, top5_acc: 0.9950, loss_cls: 0.6421, loss: 0.6421 +2025-06-24 11:08:43,898 - pyskl - INFO - Epoch [22][500/1281] lr: 2.377e-02, eta: 12:03:11, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8525, top5_acc: 0.9944, loss_cls: 0.6682, loss: 0.6682 +2025-06-24 11:09:25,222 - pyskl - INFO - Epoch [22][600/1281] lr: 2.376e-02, eta: 12:04:15, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8462, top5_acc: 0.9931, loss_cls: 0.6908, loss: 0.6908 +2025-06-24 11:10:06,820 - pyskl - INFO - Epoch [22][700/1281] lr: 2.375e-02, eta: 12:05:19, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8644, top5_acc: 0.9919, loss_cls: 0.6489, loss: 0.6489 +2025-06-24 11:10:48,349 - pyskl - INFO - Epoch [22][800/1281] lr: 2.374e-02, eta: 12:06:22, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8538, top5_acc: 0.9962, loss_cls: 0.6621, loss: 0.6621 +2025-06-24 11:11:29,764 - pyskl - INFO - Epoch [22][900/1281] lr: 2.373e-02, eta: 12:07:24, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8562, top5_acc: 0.9956, loss_cls: 0.6635, loss: 0.6635 +2025-06-24 11:12:11,314 - pyskl - INFO - Epoch [22][1000/1281] lr: 2.372e-02, eta: 12:08:25, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8631, top5_acc: 0.9944, loss_cls: 0.6774, loss: 0.6774 +2025-06-24 11:12:47,529 - pyskl - INFO - Epoch [22][1100/1281] lr: 2.371e-02, eta: 12:08:55, time: 0.362, data_time: 0.000, memory: 4082, top1_acc: 0.8500, top5_acc: 0.9950, loss_cls: 0.6966, loss: 0.6966 +2025-06-24 11:13:19,477 - pyskl - INFO - Epoch [22][1200/1281] lr: 2.370e-02, eta: 12:08:59, time: 0.319, data_time: 0.000, memory: 4082, top1_acc: 0.8638, top5_acc: 0.9938, loss_cls: 0.6352, loss: 0.6352 +2025-06-24 11:13:55,341 - pyskl - INFO - Saving checkpoint at 22 epochs +2025-06-24 11:15:05,942 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:15:06,005 - pyskl - INFO - +top1_acc 0.8109 +top5_acc 0.9853 +2025-06-24 11:15:06,005 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:15:06,013 - pyskl - INFO - +mean_acc 0.7364 +2025-06-24 11:15:06,016 - pyskl - INFO - Epoch(val) [22][533] top1_acc: 0.8109, top5_acc: 0.9853, mean_class_accuracy: 0.7364 +2025-06-24 11:16:07,543 - pyskl - INFO - Epoch [23][100/1281] lr: 2.369e-02, eta: 12:09:28, time: 0.615, data_time: 0.199, memory: 4082, top1_acc: 0.8438, top5_acc: 0.9962, loss_cls: 0.6887, loss: 0.6887 +2025-06-24 11:16:49,159 - pyskl - INFO - Epoch [23][200/1281] lr: 2.368e-02, eta: 12:10:27, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8631, top5_acc: 0.9944, loss_cls: 0.6227, loss: 0.6227 +2025-06-24 11:17:30,764 - pyskl - INFO - Epoch [23][300/1281] lr: 2.367e-02, eta: 12:11:26, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8806, top5_acc: 0.9944, loss_cls: 0.5861, loss: 0.5861 +2025-06-24 11:18:12,373 - pyskl - INFO - Epoch [23][400/1281] lr: 2.366e-02, eta: 12:12:24, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8881, top5_acc: 0.9981, loss_cls: 0.5801, loss: 0.5801 +2025-06-24 11:18:53,955 - pyskl - INFO - Epoch [23][500/1281] lr: 2.365e-02, eta: 12:13:21, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8681, top5_acc: 0.9938, loss_cls: 0.6333, loss: 0.6333 +2025-06-24 11:19:35,581 - pyskl - INFO - Epoch [23][600/1281] lr: 2.364e-02, eta: 12:14:17, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9956, loss_cls: 0.6426, loss: 0.6426 +2025-06-24 11:20:17,162 - pyskl - INFO - Epoch [23][700/1281] lr: 2.363e-02, eta: 12:15:13, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8869, top5_acc: 0.9969, loss_cls: 0.5765, loss: 0.5765 +2025-06-24 11:20:58,868 - pyskl - INFO - Epoch [23][800/1281] lr: 2.362e-02, eta: 12:16:09, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8681, top5_acc: 0.9956, loss_cls: 0.6239, loss: 0.6239 +2025-06-24 11:21:40,331 - pyskl - INFO - Epoch [23][900/1281] lr: 2.361e-02, eta: 12:17:02, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8594, top5_acc: 0.9931, loss_cls: 0.6534, loss: 0.6534 +2025-06-24 11:22:22,053 - pyskl - INFO - Epoch [23][1000/1281] lr: 2.360e-02, eta: 12:17:57, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8675, top5_acc: 0.9925, loss_cls: 0.6382, loss: 0.6382 +2025-06-24 11:22:58,590 - pyskl - INFO - Epoch [23][1100/1281] lr: 2.359e-02, eta: 12:18:22, time: 0.365, data_time: 0.000, memory: 4082, top1_acc: 0.8369, top5_acc: 0.9900, loss_cls: 0.7214, loss: 0.7214 +2025-06-24 11:23:30,486 - pyskl - INFO - Epoch [23][1200/1281] lr: 2.359e-02, eta: 12:18:20, time: 0.319, data_time: 0.000, memory: 4082, top1_acc: 0.8606, top5_acc: 0.9919, loss_cls: 0.6779, loss: 0.6779 +2025-06-24 11:24:06,449 - pyskl - INFO - Saving checkpoint at 23 epochs +2025-06-24 11:25:17,355 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:25:17,412 - pyskl - INFO - +top1_acc 0.8278 +top5_acc 0.9858 +2025-06-24 11:25:17,412 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:25:17,419 - pyskl - INFO - +mean_acc 0.7397 +2025-06-24 11:25:17,421 - pyskl - INFO - Epoch(val) [23][533] top1_acc: 0.8278, top5_acc: 0.9858, mean_class_accuracy: 0.7397 +2025-06-24 11:26:19,439 - pyskl - INFO - Epoch [24][100/1281] lr: 2.357e-02, eta: 12:18:41, time: 0.620, data_time: 0.201, memory: 4082, top1_acc: 0.8781, top5_acc: 0.9962, loss_cls: 0.5995, loss: 0.5995 +2025-06-24 11:27:01,042 - pyskl - INFO - Epoch [24][200/1281] lr: 2.356e-02, eta: 12:19:32, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8962, top5_acc: 0.9950, loss_cls: 0.5572, loss: 0.5572 +2025-06-24 11:27:42,666 - pyskl - INFO - Epoch [24][300/1281] lr: 2.355e-02, eta: 12:20:23, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8825, top5_acc: 0.9938, loss_cls: 0.5893, loss: 0.5893 +2025-06-24 11:28:24,279 - pyskl - INFO - Epoch [24][400/1281] lr: 2.354e-02, eta: 12:21:13, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8788, top5_acc: 0.9956, loss_cls: 0.6084, loss: 0.6084 +2025-06-24 11:29:05,826 - pyskl - INFO - Epoch [24][500/1281] lr: 2.353e-02, eta: 12:22:03, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8606, top5_acc: 0.9931, loss_cls: 0.6705, loss: 0.6705 +2025-06-24 11:29:47,517 - pyskl - INFO - Epoch [24][600/1281] lr: 2.352e-02, eta: 12:22:52, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8794, top5_acc: 0.9969, loss_cls: 0.5552, loss: 0.5552 +2025-06-24 11:30:29,219 - pyskl - INFO - Epoch [24][700/1281] lr: 2.351e-02, eta: 12:23:41, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8612, top5_acc: 0.9938, loss_cls: 0.6226, loss: 0.6226 +2025-06-24 11:31:10,816 - pyskl - INFO - Epoch [24][800/1281] lr: 2.350e-02, eta: 12:24:28, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8612, top5_acc: 0.9944, loss_cls: 0.6376, loss: 0.6376 +2025-06-24 11:31:52,467 - pyskl - INFO - Epoch [24][900/1281] lr: 2.349e-02, eta: 12:25:16, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8750, top5_acc: 0.9931, loss_cls: 0.6093, loss: 0.6093 +2025-06-24 11:32:34,162 - pyskl - INFO - Epoch [24][1000/1281] lr: 2.348e-02, eta: 12:26:02, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8731, top5_acc: 0.9944, loss_cls: 0.6093, loss: 0.6093 +2025-06-24 11:33:10,819 - pyskl - INFO - Epoch [24][1100/1281] lr: 2.347e-02, eta: 12:26:22, time: 0.367, data_time: 0.000, memory: 4082, top1_acc: 0.8712, top5_acc: 0.9900, loss_cls: 0.6568, loss: 0.6568 +2025-06-24 11:33:42,741 - pyskl - INFO - Epoch [24][1200/1281] lr: 2.346e-02, eta: 12:26:17, time: 0.319, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9950, loss_cls: 0.6601, loss: 0.6601 +2025-06-24 11:34:18,455 - pyskl - INFO - Saving checkpoint at 24 epochs +2025-06-24 11:35:29,603 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:35:29,669 - pyskl - INFO - +top1_acc 0.8258 +top5_acc 0.9896 +2025-06-24 11:35:29,669 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:35:29,678 - pyskl - INFO - +mean_acc 0.7551 +2025-06-24 11:35:29,681 - pyskl - INFO - Epoch(val) [24][533] top1_acc: 0.8258, top5_acc: 0.9896, mean_class_accuracy: 0.7551 +2025-06-24 11:36:30,629 - pyskl - INFO - Epoch [25][100/1281] lr: 2.344e-02, eta: 12:26:23, time: 0.609, data_time: 0.193, memory: 4082, top1_acc: 0.8669, top5_acc: 0.9969, loss_cls: 0.6137, loss: 0.6137 +2025-06-24 11:37:11,994 - pyskl - INFO - Epoch [25][200/1281] lr: 2.343e-02, eta: 12:27:06, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8794, top5_acc: 0.9912, loss_cls: 0.6034, loss: 0.6034 +2025-06-24 11:37:53,651 - pyskl - INFO - Epoch [25][300/1281] lr: 2.342e-02, eta: 12:27:50, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8781, top5_acc: 0.9969, loss_cls: 0.5871, loss: 0.5871 +2025-06-24 11:38:35,258 - pyskl - INFO - Epoch [25][400/1281] lr: 2.341e-02, eta: 12:28:33, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8725, top5_acc: 0.9969, loss_cls: 0.6190, loss: 0.6190 +2025-06-24 11:39:16,720 - pyskl - INFO - Epoch [25][500/1281] lr: 2.340e-02, eta: 12:29:15, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8456, top5_acc: 0.9894, loss_cls: 0.6985, loss: 0.6985 +2025-06-24 11:39:58,242 - pyskl - INFO - Epoch [25][600/1281] lr: 2.339e-02, eta: 12:29:57, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8525, top5_acc: 0.9919, loss_cls: 0.6666, loss: 0.6666 +2025-06-24 11:40:39,678 - pyskl - INFO - Epoch [25][700/1281] lr: 2.338e-02, eta: 12:30:38, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8675, top5_acc: 0.9938, loss_cls: 0.6225, loss: 0.6225 +2025-06-24 11:41:21,169 - pyskl - INFO - Epoch [25][800/1281] lr: 2.337e-02, eta: 12:31:18, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8825, top5_acc: 0.9975, loss_cls: 0.5771, loss: 0.5771 +2025-06-24 11:42:02,730 - pyskl - INFO - Epoch [25][900/1281] lr: 2.336e-02, eta: 12:31:59, time: 0.416, data_time: 0.001, memory: 4082, top1_acc: 0.8650, top5_acc: 0.9931, loss_cls: 0.6540, loss: 0.6540 +2025-06-24 11:42:44,259 - pyskl - INFO - Epoch [25][1000/1281] lr: 2.335e-02, eta: 12:32:38, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8612, top5_acc: 0.9969, loss_cls: 0.6360, loss: 0.6360 +2025-06-24 11:43:20,449 - pyskl - INFO - Epoch [25][1100/1281] lr: 2.334e-02, eta: 12:32:51, time: 0.362, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9938, loss_cls: 0.6487, loss: 0.6487 +2025-06-24 11:43:51,737 - pyskl - INFO - Epoch [25][1200/1281] lr: 2.333e-02, eta: 12:32:38, time: 0.313, data_time: 0.000, memory: 4082, top1_acc: 0.8744, top5_acc: 0.9938, loss_cls: 0.5948, loss: 0.5948 +2025-06-24 11:44:27,965 - pyskl - INFO - Saving checkpoint at 25 epochs +2025-06-24 11:45:37,596 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:45:37,650 - pyskl - INFO - +top1_acc 0.8102 +top5_acc 0.9874 +2025-06-24 11:45:37,651 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:45:37,657 - pyskl - INFO - +mean_acc 0.7361 +2025-06-24 11:45:37,659 - pyskl - INFO - Epoch(val) [25][533] top1_acc: 0.8102, top5_acc: 0.9874, mean_class_accuracy: 0.7361 +2025-06-24 11:46:40,053 - pyskl - INFO - Epoch [26][100/1281] lr: 2.332e-02, eta: 12:32:44, time: 0.624, data_time: 0.192, memory: 4082, top1_acc: 0.8581, top5_acc: 0.9938, loss_cls: 0.6422, loss: 0.6422 +2025-06-24 11:47:21,659 - pyskl - INFO - Epoch [26][200/1281] lr: 2.330e-02, eta: 12:33:22, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8812, top5_acc: 0.9956, loss_cls: 0.5968, loss: 0.5968 +2025-06-24 11:48:03,351 - pyskl - INFO - Epoch [26][300/1281] lr: 2.329e-02, eta: 12:34:00, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8800, top5_acc: 0.9981, loss_cls: 0.5463, loss: 0.5463 +2025-06-24 11:48:44,942 - pyskl - INFO - Epoch [26][400/1281] lr: 2.328e-02, eta: 12:34:37, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8781, top5_acc: 0.9931, loss_cls: 0.5995, loss: 0.5995 +2025-06-24 11:49:26,444 - pyskl - INFO - Epoch [26][500/1281] lr: 2.327e-02, eta: 12:35:13, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8781, top5_acc: 0.9950, loss_cls: 0.6032, loss: 0.6032 +2025-06-24 11:50:08,028 - pyskl - INFO - Epoch [26][600/1281] lr: 2.326e-02, eta: 12:35:49, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8662, top5_acc: 0.9962, loss_cls: 0.6490, loss: 0.6490 +2025-06-24 11:50:49,654 - pyskl - INFO - Epoch [26][700/1281] lr: 2.325e-02, eta: 12:36:25, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8725, top5_acc: 0.9944, loss_cls: 0.6260, loss: 0.6260 +2025-06-24 11:51:31,149 - pyskl - INFO - Epoch [26][800/1281] lr: 2.324e-02, eta: 12:37:00, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8706, top5_acc: 0.9969, loss_cls: 0.5634, loss: 0.5634 +2025-06-24 11:52:12,613 - pyskl - INFO - Epoch [26][900/1281] lr: 2.323e-02, eta: 12:37:34, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8744, top5_acc: 0.9956, loss_cls: 0.5939, loss: 0.5939 +2025-06-24 11:52:54,210 - pyskl - INFO - Epoch [26][1000/1281] lr: 2.322e-02, eta: 12:38:08, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8550, top5_acc: 0.9912, loss_cls: 0.6556, loss: 0.6556 +2025-06-24 11:53:31,886 - pyskl - INFO - Epoch [26][1100/1281] lr: 2.321e-02, eta: 12:38:23, time: 0.377, data_time: 0.000, memory: 4082, top1_acc: 0.8762, top5_acc: 0.9944, loss_cls: 0.6326, loss: 0.6326 +2025-06-24 11:54:02,772 - pyskl - INFO - Epoch [26][1200/1281] lr: 2.320e-02, eta: 12:38:06, time: 0.309, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9919, loss_cls: 0.6556, loss: 0.6556 +2025-06-24 11:54:39,821 - pyskl - INFO - Saving checkpoint at 26 epochs +2025-06-24 11:55:49,587 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:55:49,661 - pyskl - INFO - +top1_acc 0.8274 +top5_acc 0.9870 +2025-06-24 11:55:49,661 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:55:49,671 - pyskl - INFO - +mean_acc 0.7640 +2025-06-24 11:55:49,674 - pyskl - INFO - Epoch(val) [26][533] top1_acc: 0.8274, top5_acc: 0.9870, mean_class_accuracy: 0.7640 +2025-06-24 11:56:50,865 - pyskl - INFO - Epoch [27][100/1281] lr: 2.318e-02, eta: 12:37:58, time: 0.612, data_time: 0.196, memory: 4082, top1_acc: 0.8981, top5_acc: 0.9950, loss_cls: 0.5325, loss: 0.5325 +2025-06-24 11:57:32,301 - pyskl - INFO - Epoch [27][200/1281] lr: 2.317e-02, eta: 12:38:30, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8600, top5_acc: 0.9938, loss_cls: 0.6291, loss: 0.6291 +2025-06-24 11:58:13,887 - pyskl - INFO - Epoch [27][300/1281] lr: 2.316e-02, eta: 12:39:03, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8769, top5_acc: 0.9962, loss_cls: 0.5664, loss: 0.5664 +2025-06-24 11:58:55,440 - pyskl - INFO - Epoch [27][400/1281] lr: 2.315e-02, eta: 12:39:34, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8850, top5_acc: 0.9931, loss_cls: 0.5971, loss: 0.5971 +2025-06-24 11:59:37,015 - pyskl - INFO - Epoch [27][500/1281] lr: 2.314e-02, eta: 12:40:05, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8862, top5_acc: 0.9931, loss_cls: 0.5761, loss: 0.5761 +2025-06-24 12:00:18,504 - pyskl - INFO - Epoch [27][600/1281] lr: 2.313e-02, eta: 12:40:36, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8694, top5_acc: 0.9950, loss_cls: 0.6320, loss: 0.6320 +2025-06-24 12:01:01,218 - pyskl - INFO - Epoch [27][700/1281] lr: 2.312e-02, eta: 12:41:11, time: 0.427, data_time: 0.000, memory: 4082, top1_acc: 0.8819, top5_acc: 0.9962, loss_cls: 0.5785, loss: 0.5785 +2025-06-24 12:01:45,301 - pyskl - INFO - Epoch [27][800/1281] lr: 2.311e-02, eta: 12:41:53, time: 0.441, data_time: 0.000, memory: 4082, top1_acc: 0.8844, top5_acc: 0.9944, loss_cls: 0.5504, loss: 0.5504 +2025-06-24 12:02:27,858 - pyskl - INFO - Epoch [27][900/1281] lr: 2.310e-02, eta: 12:42:27, time: 0.426, data_time: 0.000, memory: 4082, top1_acc: 0.9025, top5_acc: 0.9981, loss_cls: 0.5167, loss: 0.5167 +2025-06-24 12:03:09,417 - pyskl - INFO - Epoch [27][1000/1281] lr: 2.308e-02, eta: 12:42:56, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8869, top5_acc: 0.9950, loss_cls: 0.5635, loss: 0.5635 +2025-06-24 12:03:47,871 - pyskl - INFO - Epoch [27][1100/1281] lr: 2.307e-02, eta: 12:43:10, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.8656, top5_acc: 0.9956, loss_cls: 0.6301, loss: 0.6301 +2025-06-24 12:04:16,821 - pyskl - INFO - Epoch [27][1200/1281] lr: 2.306e-02, eta: 12:42:41, time: 0.289, data_time: 0.000, memory: 4082, top1_acc: 0.8538, top5_acc: 0.9894, loss_cls: 0.7149, loss: 0.7149 +2025-06-24 12:04:54,428 - pyskl - INFO - Saving checkpoint at 27 epochs +2025-06-24 12:06:02,480 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:06:02,548 - pyskl - INFO - +top1_acc 0.8600 +top5_acc 0.9908 +2025-06-24 12:06:02,548 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:06:02,556 - pyskl - INFO - +mean_acc 0.7940 +2025-06-24 12:06:02,560 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_20.pth was removed +2025-06-24 12:06:02,760 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_27.pth. +2025-06-24 12:06:02,761 - pyskl - INFO - Best top1_acc is 0.8600 at 27 epoch. +2025-06-24 12:06:02,765 - pyskl - INFO - Epoch(val) [27][533] top1_acc: 0.8600, top5_acc: 0.9908, mean_class_accuracy: 0.7940 +2025-06-24 12:07:04,604 - pyskl - INFO - Epoch [28][100/1281] lr: 2.304e-02, eta: 12:42:31, time: 0.618, data_time: 0.200, memory: 4082, top1_acc: 0.8850, top5_acc: 0.9969, loss_cls: 0.5414, loss: 0.5414 +2025-06-24 12:07:46,106 - pyskl - INFO - Epoch [28][200/1281] lr: 2.303e-02, eta: 12:42:58, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8719, top5_acc: 0.9931, loss_cls: 0.5896, loss: 0.5896 +2025-06-24 12:08:27,744 - pyskl - INFO - Epoch [28][300/1281] lr: 2.302e-02, eta: 12:43:25, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8994, top5_acc: 0.9962, loss_cls: 0.5244, loss: 0.5244 +2025-06-24 12:09:09,353 - pyskl - INFO - Epoch [28][400/1281] lr: 2.301e-02, eta: 12:43:52, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8700, top5_acc: 0.9944, loss_cls: 0.5908, loss: 0.5908 +2025-06-24 12:09:50,941 - pyskl - INFO - Epoch [28][500/1281] lr: 2.300e-02, eta: 12:44:19, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8719, top5_acc: 0.9994, loss_cls: 0.5589, loss: 0.5589 +2025-06-24 12:10:32,322 - pyskl - INFO - Epoch [28][600/1281] lr: 2.299e-02, eta: 12:44:44, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8775, top5_acc: 0.9962, loss_cls: 0.5491, loss: 0.5491 +2025-06-24 12:11:13,800 - pyskl - INFO - Epoch [28][700/1281] lr: 2.298e-02, eta: 12:45:09, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8669, top5_acc: 0.9950, loss_cls: 0.6225, loss: 0.6225 +2025-06-24 12:11:55,376 - pyskl - INFO - Epoch [28][800/1281] lr: 2.297e-02, eta: 12:45:34, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8819, top5_acc: 0.9956, loss_cls: 0.5777, loss: 0.5777 +2025-06-24 12:12:36,943 - pyskl - INFO - Epoch [28][900/1281] lr: 2.295e-02, eta: 12:45:59, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8769, top5_acc: 0.9931, loss_cls: 0.5650, loss: 0.5650 +2025-06-24 12:13:18,594 - pyskl - INFO - Epoch [28][1000/1281] lr: 2.294e-02, eta: 12:46:24, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8838, top5_acc: 0.9938, loss_cls: 0.5514, loss: 0.5514 +2025-06-24 12:13:57,360 - pyskl - INFO - Epoch [28][1100/1281] lr: 2.293e-02, eta: 12:46:36, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8669, top5_acc: 0.9919, loss_cls: 0.6404, loss: 0.6404 +2025-06-24 12:14:26,910 - pyskl - INFO - Epoch [28][1200/1281] lr: 2.292e-02, eta: 12:46:07, time: 0.295, data_time: 0.000, memory: 4082, top1_acc: 0.8819, top5_acc: 0.9894, loss_cls: 0.6060, loss: 0.6060 +2025-06-24 12:15:04,383 - pyskl - INFO - Saving checkpoint at 28 epochs +2025-06-24 12:16:12,904 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:16:12,964 - pyskl - INFO - +top1_acc 0.8222 +top5_acc 0.9877 +2025-06-24 12:16:12,964 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:16:12,972 - pyskl - INFO - +mean_acc 0.7782 +2025-06-24 12:16:12,974 - pyskl - INFO - Epoch(val) [28][533] top1_acc: 0.8222, top5_acc: 0.9877, mean_class_accuracy: 0.7782 +2025-06-24 12:17:14,475 - pyskl - INFO - Epoch [29][100/1281] lr: 2.290e-02, eta: 12:45:50, time: 0.615, data_time: 0.200, memory: 4082, top1_acc: 0.8756, top5_acc: 0.9962, loss_cls: 0.5851, loss: 0.5851 +2025-06-24 12:17:56,449 - pyskl - INFO - Epoch [29][200/1281] lr: 2.289e-02, eta: 12:46:15, time: 0.420, data_time: 0.000, memory: 4082, top1_acc: 0.8806, top5_acc: 0.9962, loss_cls: 0.5841, loss: 0.5841 +2025-06-24 12:18:40,502 - pyskl - INFO - Epoch [29][300/1281] lr: 2.288e-02, eta: 12:46:48, time: 0.441, data_time: 0.000, memory: 4082, top1_acc: 0.8762, top5_acc: 0.9962, loss_cls: 0.5535, loss: 0.5535 +2025-06-24 12:19:24,238 - pyskl - INFO - Epoch [29][400/1281] lr: 2.287e-02, eta: 12:47:20, time: 0.437, data_time: 0.000, memory: 4082, top1_acc: 0.8775, top5_acc: 0.9906, loss_cls: 0.6168, loss: 0.6168 +2025-06-24 12:20:07,763 - pyskl - INFO - Epoch [29][500/1281] lr: 2.285e-02, eta: 12:47:50, time: 0.435, data_time: 0.000, memory: 4082, top1_acc: 0.8744, top5_acc: 0.9925, loss_cls: 0.5657, loss: 0.5657 +2025-06-24 12:20:50,056 - pyskl - INFO - Epoch [29][600/1281] lr: 2.284e-02, eta: 12:48:15, time: 0.423, data_time: 0.000, memory: 4082, top1_acc: 0.8812, top5_acc: 0.9919, loss_cls: 0.5541, loss: 0.5541 +2025-06-24 12:21:31,476 - pyskl - INFO - Epoch [29][700/1281] lr: 2.283e-02, eta: 12:48:36, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8619, top5_acc: 0.9931, loss_cls: 0.6224, loss: 0.6224 +2025-06-24 12:22:13,044 - pyskl - INFO - Epoch [29][800/1281] lr: 2.282e-02, eta: 12:48:57, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8694, top5_acc: 0.9944, loss_cls: 0.6251, loss: 0.6251 +2025-06-24 12:22:54,509 - pyskl - INFO - Epoch [29][900/1281] lr: 2.281e-02, eta: 12:49:17, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8662, top5_acc: 0.9956, loss_cls: 0.6102, loss: 0.6102 +2025-06-24 12:23:36,042 - pyskl - INFO - Epoch [29][1000/1281] lr: 2.280e-02, eta: 12:49:37, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8794, top5_acc: 0.9956, loss_cls: 0.5701, loss: 0.5701 +2025-06-24 12:24:14,337 - pyskl - INFO - Epoch [29][1100/1281] lr: 2.279e-02, eta: 12:49:43, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.8769, top5_acc: 0.9969, loss_cls: 0.5696, loss: 0.5696 +2025-06-24 12:24:43,725 - pyskl - INFO - Epoch [29][1200/1281] lr: 2.277e-02, eta: 12:49:12, time: 0.294, data_time: 0.000, memory: 4082, top1_acc: 0.8581, top5_acc: 0.9988, loss_cls: 0.6031, loss: 0.6031 +2025-06-24 12:25:21,355 - pyskl - INFO - Saving checkpoint at 29 epochs +2025-06-24 12:26:30,513 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:26:30,569 - pyskl - INFO - +top1_acc 0.8265 +top5_acc 0.9885 +2025-06-24 12:26:30,569 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:26:30,576 - pyskl - INFO - +mean_acc 0.7846 +2025-06-24 12:26:30,579 - pyskl - INFO - Epoch(val) [29][533] top1_acc: 0.8265, top5_acc: 0.9885, mean_class_accuracy: 0.7846 +2025-06-24 12:27:41,299 - pyskl - INFO - Epoch [30][100/1281] lr: 2.275e-02, eta: 12:49:28, time: 0.707, data_time: 0.197, memory: 4082, top1_acc: 0.8800, top5_acc: 0.9956, loss_cls: 0.6062, loss: 0.6062 +2025-06-24 12:28:31,459 - pyskl - INFO - Epoch [30][200/1281] lr: 2.274e-02, eta: 12:50:22, time: 0.502, data_time: 0.000, memory: 4082, top1_acc: 0.8719, top5_acc: 0.9938, loss_cls: 0.5864, loss: 0.5864 +2025-06-24 12:29:22,902 - pyskl - INFO - Epoch [30][300/1281] lr: 2.273e-02, eta: 12:51:22, time: 0.514, data_time: 0.000, memory: 4082, top1_acc: 0.8856, top5_acc: 0.9956, loss_cls: 0.5328, loss: 0.5328 +2025-06-24 12:30:14,119 - pyskl - INFO - Epoch [30][400/1281] lr: 2.272e-02, eta: 12:52:19, time: 0.512, data_time: 0.000, memory: 4082, top1_acc: 0.8794, top5_acc: 0.9988, loss_cls: 0.5581, loss: 0.5581 +2025-06-24 12:31:05,887 - pyskl - INFO - Epoch [30][500/1281] lr: 2.271e-02, eta: 12:53:19, time: 0.518, data_time: 0.000, memory: 4082, top1_acc: 0.9006, top5_acc: 0.9975, loss_cls: 0.5129, loss: 0.5129 +2025-06-24 12:31:56,913 - pyskl - INFO - Epoch [30][600/1281] lr: 2.269e-02, eta: 12:54:15, time: 0.510, data_time: 0.000, memory: 4082, top1_acc: 0.8875, top5_acc: 0.9950, loss_cls: 0.5616, loss: 0.5616 +2025-06-24 12:32:48,147 - pyskl - INFO - Epoch [30][700/1281] lr: 2.268e-02, eta: 12:55:11, time: 0.512, data_time: 0.000, memory: 4082, top1_acc: 0.8719, top5_acc: 0.9925, loss_cls: 0.6187, loss: 0.6187 +2025-06-24 12:33:40,278 - pyskl - INFO - Epoch [30][800/1281] lr: 2.267e-02, eta: 12:56:10, time: 0.521, data_time: 0.000, memory: 4082, top1_acc: 0.8831, top5_acc: 0.9962, loss_cls: 0.5696, loss: 0.5696 +2025-06-24 12:34:09,643 - pyskl - INFO - Epoch [30][900/1281] lr: 2.266e-02, eta: 12:55:36, time: 0.294, data_time: 0.000, memory: 4082, top1_acc: 0.8769, top5_acc: 0.9912, loss_cls: 0.5895, loss: 0.5895 +2025-06-24 12:35:00,763 - pyskl - INFO - Epoch [30][1000/1281] lr: 2.265e-02, eta: 12:56:31, time: 0.511, data_time: 0.000, memory: 4082, top1_acc: 0.8681, top5_acc: 0.9938, loss_cls: 0.6255, loss: 0.6255 +2025-06-24 12:35:35,810 - pyskl - INFO - Epoch [30][1100/1281] lr: 2.263e-02, eta: 12:56:20, time: 0.350, data_time: 0.001, memory: 4082, top1_acc: 0.8631, top5_acc: 0.9944, loss_cls: 0.6604, loss: 0.6604 +2025-06-24 12:36:26,666 - pyskl - INFO - Epoch [30][1200/1281] lr: 2.262e-02, eta: 12:57:12, time: 0.509, data_time: 0.000, memory: 4082, top1_acc: 0.8706, top5_acc: 0.9962, loss_cls: 0.5872, loss: 0.5872 +2025-06-24 12:37:08,791 - pyskl - INFO - Saving checkpoint at 30 epochs +2025-06-24 12:38:20,716 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:38:20,778 - pyskl - INFO - +top1_acc 0.8437 +top5_acc 0.9876 +2025-06-24 12:38:20,778 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:38:20,785 - pyskl - INFO - +mean_acc 0.7782 +2025-06-24 12:38:20,788 - pyskl - INFO - Epoch(val) [30][533] top1_acc: 0.8437, top5_acc: 0.9876, mean_class_accuracy: 0.7782 +2025-06-24 12:39:56,570 - pyskl - INFO - Epoch [31][100/1281] lr: 2.260e-02, eta: 12:59:00, time: 0.958, data_time: 0.202, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9975, loss_cls: 0.6818, loss: 0.6818 +2025-06-24 12:40:49,699 - pyskl - INFO - Epoch [31][200/1281] lr: 2.259e-02, eta: 13:00:00, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9956, loss_cls: 0.7064, loss: 0.7064 +2025-06-24 12:41:43,738 - pyskl - INFO - Epoch [31][300/1281] lr: 2.258e-02, eta: 13:01:03, time: 0.540, data_time: 0.000, memory: 4083, top1_acc: 0.8625, top5_acc: 0.9969, loss_cls: 0.7667, loss: 0.7667 +2025-06-24 12:42:36,820 - pyskl - INFO - Epoch [31][400/1281] lr: 2.256e-02, eta: 13:02:01, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9944, loss_cls: 0.6881, loss: 0.6881 +2025-06-24 12:43:08,973 - pyskl - INFO - Epoch [31][500/1281] lr: 2.255e-02, eta: 13:01:37, time: 0.322, data_time: 0.001, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9962, loss_cls: 0.6796, loss: 0.6796 +2025-06-24 12:44:00,388 - pyskl - INFO - Epoch [31][600/1281] lr: 2.254e-02, eta: 13:02:28, time: 0.514, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9969, loss_cls: 0.7064, loss: 0.7064 +2025-06-24 12:44:36,444 - pyskl - INFO - Epoch [31][700/1281] lr: 2.253e-02, eta: 13:02:18, time: 0.361, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9956, loss_cls: 0.7351, loss: 0.7351 +2025-06-24 12:45:29,720 - pyskl - INFO - Epoch [31][800/1281] lr: 2.252e-02, eta: 13:03:16, time: 0.533, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9938, loss_cls: 0.7337, loss: 0.7337 +2025-06-24 12:46:22,925 - pyskl - INFO - Epoch [31][900/1281] lr: 2.250e-02, eta: 13:04:12, time: 0.532, data_time: 0.000, memory: 4083, top1_acc: 0.8569, top5_acc: 0.9919, loss_cls: 0.8392, loss: 0.8392 +2025-06-24 12:47:16,439 - pyskl - INFO - Epoch [31][1000/1281] lr: 2.249e-02, eta: 13:05:09, time: 0.535, data_time: 0.000, memory: 4083, top1_acc: 0.8644, top5_acc: 0.9931, loss_cls: 0.8112, loss: 0.8112 +2025-06-24 12:48:10,241 - pyskl - INFO - Epoch [31][1100/1281] lr: 2.248e-02, eta: 13:06:07, time: 0.538, data_time: 0.001, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9944, loss_cls: 0.7345, loss: 0.7345 +2025-06-24 12:49:03,966 - pyskl - INFO - Epoch [31][1200/1281] lr: 2.247e-02, eta: 13:07:04, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9944, loss_cls: 0.7182, loss: 0.7182 +2025-06-24 12:49:48,644 - pyskl - INFO - Saving checkpoint at 31 epochs +2025-06-24 12:51:01,133 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:51:01,191 - pyskl - INFO - +top1_acc 0.8464 +top5_acc 0.9905 +2025-06-24 12:51:01,191 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:51:01,199 - pyskl - INFO - +mean_acc 0.7776 +2025-06-24 12:51:01,202 - pyskl - INFO - Epoch(val) [31][533] top1_acc: 0.8464, top5_acc: 0.9905, mean_class_accuracy: 0.7776 +2025-06-24 12:52:08,053 - pyskl - INFO - Epoch [32][100/1281] lr: 2.244e-02, eta: 13:06:49, time: 0.668, data_time: 0.193, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9931, loss_cls: 0.6431, loss: 0.6431 +2025-06-24 12:52:58,634 - pyskl - INFO - Epoch [32][200/1281] lr: 2.243e-02, eta: 13:07:33, time: 0.506, data_time: 0.000, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9981, loss_cls: 0.6661, loss: 0.6661 +2025-06-24 12:53:37,798 - pyskl - INFO - Epoch [32][300/1281] lr: 2.242e-02, eta: 13:07:33, time: 0.392, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9962, loss_cls: 0.7019, loss: 0.7019 +2025-06-24 12:54:30,794 - pyskl - INFO - Epoch [32][400/1281] lr: 2.241e-02, eta: 13:08:25, time: 0.530, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9969, loss_cls: 0.6521, loss: 0.6521 +2025-06-24 12:55:24,498 - pyskl - INFO - Epoch [32][500/1281] lr: 2.239e-02, eta: 13:09:19, time: 0.537, data_time: 0.001, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9925, loss_cls: 0.6609, loss: 0.6609 +2025-06-24 12:56:18,471 - pyskl - INFO - Epoch [32][600/1281] lr: 2.238e-02, eta: 13:10:14, time: 0.540, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9950, loss_cls: 0.6209, loss: 0.6209 +2025-06-24 12:57:12,647 - pyskl - INFO - Epoch [32][700/1281] lr: 2.237e-02, eta: 13:11:09, time: 0.542, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9925, loss_cls: 0.6782, loss: 0.6782 +2025-06-24 12:58:07,082 - pyskl - INFO - Epoch [32][800/1281] lr: 2.236e-02, eta: 13:12:04, time: 0.544, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9944, loss_cls: 0.6603, loss: 0.6603 +2025-06-24 12:59:01,014 - pyskl - INFO - Epoch [32][900/1281] lr: 2.234e-02, eta: 13:12:57, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9969, loss_cls: 0.6177, loss: 0.6177 +2025-06-24 12:59:54,254 - pyskl - INFO - Epoch [32][1000/1281] lr: 2.233e-02, eta: 13:13:47, time: 0.532, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9931, loss_cls: 0.6925, loss: 0.6925 +2025-06-24 13:00:49,241 - pyskl - INFO - Epoch [32][1100/1281] lr: 2.232e-02, eta: 13:14:43, time: 0.550, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9950, loss_cls: 0.6970, loss: 0.6970 +2025-06-24 13:01:24,934 - pyskl - INFO - Epoch [32][1200/1281] lr: 2.231e-02, eta: 13:14:27, time: 0.357, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9956, loss_cls: 0.7044, loss: 0.7044 +2025-06-24 13:02:12,681 - pyskl - INFO - Saving checkpoint at 32 epochs +2025-06-24 13:03:24,135 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:03:24,192 - pyskl - INFO - +top1_acc 0.8343 +top5_acc 0.9917 +2025-06-24 13:03:24,192 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:03:24,199 - pyskl - INFO - +mean_acc 0.7775 +2025-06-24 13:03:24,201 - pyskl - INFO - Epoch(val) [32][533] top1_acc: 0.8343, top5_acc: 0.9917, mean_class_accuracy: 0.7775 +2025-06-24 13:04:55,074 - pyskl - INFO - Epoch [33][100/1281] lr: 2.228e-02, eta: 13:15:34, time: 0.909, data_time: 0.193, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9962, loss_cls: 0.5908, loss: 0.5908 +2025-06-24 13:05:49,390 - pyskl - INFO - Epoch [33][200/1281] lr: 2.227e-02, eta: 13:16:26, time: 0.543, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9981, loss_cls: 0.6222, loss: 0.6222 +2025-06-24 13:06:43,113 - pyskl - INFO - Epoch [33][300/1281] lr: 2.226e-02, eta: 13:17:15, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9956, loss_cls: 0.6454, loss: 0.6454 +2025-06-24 13:07:37,718 - pyskl - INFO - Epoch [33][400/1281] lr: 2.225e-02, eta: 13:18:07, time: 0.546, data_time: 0.000, memory: 4083, top1_acc: 0.8675, top5_acc: 0.9944, loss_cls: 0.6950, loss: 0.6950 +2025-06-24 13:08:31,812 - pyskl - INFO - Epoch [33][500/1281] lr: 2.223e-02, eta: 13:18:56, time: 0.541, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9956, loss_cls: 0.5945, loss: 0.5945 +2025-06-24 13:09:26,312 - pyskl - INFO - Epoch [33][600/1281] lr: 2.222e-02, eta: 13:19:46, time: 0.545, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9956, loss_cls: 0.6530, loss: 0.6530 +2025-06-24 13:10:19,242 - pyskl - INFO - Epoch [33][700/1281] lr: 2.221e-02, eta: 13:20:30, time: 0.529, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9962, loss_cls: 0.6162, loss: 0.6162 +2025-06-24 13:10:52,964 - pyskl - INFO - Epoch [33][800/1281] lr: 2.219e-02, eta: 13:20:05, time: 0.337, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9975, loss_cls: 0.5917, loss: 0.5917 +2025-06-24 13:11:33,293 - pyskl - INFO - Epoch [33][900/1281] lr: 2.218e-02, eta: 13:20:03, time: 0.403, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9931, loss_cls: 0.5954, loss: 0.5954 +2025-06-24 13:12:20,332 - pyskl - INFO - Epoch [33][1000/1281] lr: 2.217e-02, eta: 13:20:25, time: 0.470, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9962, loss_cls: 0.5538, loss: 0.5538 +2025-06-24 13:13:15,088 - pyskl - INFO - Epoch [33][1100/1281] lr: 2.216e-02, eta: 13:21:14, time: 0.548, data_time: 0.000, memory: 4083, top1_acc: 0.8675, top5_acc: 0.9969, loss_cls: 0.6590, loss: 0.6590 +2025-06-24 13:14:08,764 - pyskl - INFO - Epoch [33][1200/1281] lr: 2.214e-02, eta: 13:21:59, time: 0.537, data_time: 0.001, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9956, loss_cls: 0.6068, loss: 0.6068 +2025-06-24 13:14:53,077 - pyskl - INFO - Saving checkpoint at 33 epochs +2025-06-24 13:16:05,180 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:16:05,235 - pyskl - INFO - +top1_acc 0.8533 +top5_acc 0.9923 +2025-06-24 13:16:05,236 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:16:05,243 - pyskl - INFO - +mean_acc 0.7888 +2025-06-24 13:16:05,245 - pyskl - INFO - Epoch(val) [33][533] top1_acc: 0.8533, top5_acc: 0.9923, mean_class_accuracy: 0.7888 +2025-06-24 13:17:32,415 - pyskl - INFO - Epoch [34][100/1281] lr: 2.212e-02, eta: 13:22:44, time: 0.872, data_time: 0.202, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9925, loss_cls: 0.6241, loss: 0.6241 +2025-06-24 13:18:25,706 - pyskl - INFO - Epoch [34][200/1281] lr: 2.211e-02, eta: 13:23:26, time: 0.533, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9975, loss_cls: 0.6073, loss: 0.6073 +2025-06-24 13:19:17,240 - pyskl - INFO - Epoch [34][300/1281] lr: 2.209e-02, eta: 13:24:02, time: 0.515, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9956, loss_cls: 0.6147, loss: 0.6147 +2025-06-24 13:19:52,567 - pyskl - INFO - Epoch [34][400/1281] lr: 2.208e-02, eta: 13:23:40, time: 0.353, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9962, loss_cls: 0.6094, loss: 0.6094 +2025-06-24 13:20:31,186 - pyskl - INFO - Epoch [34][500/1281] lr: 2.207e-02, eta: 13:23:30, time: 0.386, data_time: 0.000, memory: 4083, top1_acc: 0.8656, top5_acc: 0.9962, loss_cls: 0.6726, loss: 0.6726 +2025-06-24 13:21:17,879 - pyskl - INFO - Epoch [34][600/1281] lr: 2.205e-02, eta: 13:23:48, time: 0.467, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9969, loss_cls: 0.6165, loss: 0.6165 +2025-06-24 13:22:09,290 - pyskl - INFO - Epoch [34][700/1281] lr: 2.204e-02, eta: 13:24:22, time: 0.514, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9956, loss_cls: 0.5973, loss: 0.5973 +2025-06-24 13:23:03,434 - pyskl - INFO - Epoch [34][800/1281] lr: 2.203e-02, eta: 13:25:05, time: 0.541, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9944, loss_cls: 0.6105, loss: 0.6105 +2025-06-24 13:23:57,347 - pyskl - INFO - Epoch [34][900/1281] lr: 2.201e-02, eta: 13:25:47, time: 0.539, data_time: 0.001, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9962, loss_cls: 0.5803, loss: 0.5803 +2025-06-24 13:24:50,188 - pyskl - INFO - Epoch [34][1000/1281] lr: 2.200e-02, eta: 13:26:25, time: 0.528, data_time: 0.000, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9975, loss_cls: 0.5929, loss: 0.5929 +2025-06-24 13:25:44,350 - pyskl - INFO - Epoch [34][1100/1281] lr: 2.199e-02, eta: 13:27:07, time: 0.542, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9919, loss_cls: 0.6086, loss: 0.6086 +2025-06-24 13:26:38,245 - pyskl - INFO - Epoch [34][1200/1281] lr: 2.197e-02, eta: 13:27:47, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9969, loss_cls: 0.6019, loss: 0.6019 +2025-06-24 13:27:22,400 - pyskl - INFO - Saving checkpoint at 34 epochs +2025-06-24 13:28:34,184 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:28:34,241 - pyskl - INFO - +top1_acc 0.8305 +top5_acc 0.9874 +2025-06-24 13:28:34,241 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:28:34,248 - pyskl - INFO - +mean_acc 0.7680 +2025-06-24 13:28:34,251 - pyskl - INFO - Epoch(val) [34][533] top1_acc: 0.8305, top5_acc: 0.9874, mean_class_accuracy: 0.7680 +2025-06-24 13:29:50,125 - pyskl - INFO - Epoch [35][100/1281] lr: 2.195e-02, eta: 13:27:45, time: 0.759, data_time: 0.195, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9975, loss_cls: 0.6036, loss: 0.6036 +2025-06-24 13:30:43,613 - pyskl - INFO - Epoch [35][200/1281] lr: 2.194e-02, eta: 13:28:23, time: 0.535, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9969, loss_cls: 0.5932, loss: 0.5932 +2025-06-24 13:31:37,475 - pyskl - INFO - Epoch [35][300/1281] lr: 2.192e-02, eta: 13:29:02, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9950, loss_cls: 0.5638, loss: 0.5638 +2025-06-24 13:32:31,483 - pyskl - INFO - Epoch [35][400/1281] lr: 2.191e-02, eta: 13:29:41, time: 0.540, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9956, loss_cls: 0.5385, loss: 0.5385 +2025-06-24 13:33:25,386 - pyskl - INFO - Epoch [35][500/1281] lr: 2.190e-02, eta: 13:30:20, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9938, loss_cls: 0.5945, loss: 0.5945 +2025-06-24 13:34:20,151 - pyskl - INFO - Epoch [35][600/1281] lr: 2.188e-02, eta: 13:31:00, time: 0.548, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9981, loss_cls: 0.5363, loss: 0.5363 +2025-06-24 13:35:14,523 - pyskl - INFO - Epoch [35][700/1281] lr: 2.187e-02, eta: 13:31:39, time: 0.544, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9969, loss_cls: 0.6256, loss: 0.6256 +2025-06-24 13:36:08,304 - pyskl - INFO - Epoch [35][800/1281] lr: 2.185e-02, eta: 13:32:16, time: 0.538, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9950, loss_cls: 0.5486, loss: 0.5486 +2025-06-24 13:37:02,806 - pyskl - INFO - Epoch [35][900/1281] lr: 2.184e-02, eta: 13:32:54, time: 0.545, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9944, loss_cls: 0.5755, loss: 0.5755 +2025-06-24 13:37:50,747 - pyskl - INFO - Epoch [35][1000/1281] lr: 2.183e-02, eta: 13:33:11, time: 0.479, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9969, loss_cls: 0.5739, loss: 0.5739 +2025-06-24 13:38:33,050 - pyskl - INFO - Epoch [35][1100/1281] lr: 2.181e-02, eta: 13:33:08, time: 0.423, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9956, loss_cls: 0.5776, loss: 0.5776 +2025-06-24 13:39:04,732 - pyskl - INFO - Epoch [35][1200/1281] lr: 2.180e-02, eta: 13:32:30, time: 0.317, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9950, loss_cls: 0.5944, loss: 0.5944 +2025-06-24 13:39:45,290 - pyskl - INFO - Saving checkpoint at 35 epochs +2025-06-24 13:40:57,044 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:40:57,120 - pyskl - INFO - +top1_acc 0.8484 +top5_acc 0.9880 +2025-06-24 13:40:57,121 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:40:57,133 - pyskl - INFO - +mean_acc 0.8036 +2025-06-24 13:40:57,138 - pyskl - INFO - Epoch(val) [35][533] top1_acc: 0.8484, top5_acc: 0.9880, mean_class_accuracy: 0.8036 +2025-06-24 13:42:24,204 - pyskl - INFO - Epoch [36][100/1281] lr: 2.178e-02, eta: 13:33:00, time: 0.871, data_time: 0.204, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9919, loss_cls: 0.6076, loss: 0.6076 +2025-06-24 13:43:18,090 - pyskl - INFO - Epoch [36][200/1281] lr: 2.176e-02, eta: 13:33:34, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9938, loss_cls: 0.6151, loss: 0.6151 +2025-06-24 13:44:11,944 - pyskl - INFO - Epoch [36][300/1281] lr: 2.175e-02, eta: 13:34:09, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9969, loss_cls: 0.5487, loss: 0.5487 +2025-06-24 13:45:07,017 - pyskl - INFO - Epoch [36][400/1281] lr: 2.173e-02, eta: 13:34:46, time: 0.551, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9981, loss_cls: 0.5640, loss: 0.5640 +2025-06-24 13:46:00,596 - pyskl - INFO - Epoch [36][500/1281] lr: 2.172e-02, eta: 13:35:19, time: 0.536, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9944, loss_cls: 0.5691, loss: 0.5691 +2025-06-24 13:46:48,183 - pyskl - INFO - Epoch [36][600/1281] lr: 2.171e-02, eta: 13:35:31, time: 0.476, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9988, loss_cls: 0.5675, loss: 0.5675 +2025-06-24 13:47:30,158 - pyskl - INFO - Epoch [36][700/1281] lr: 2.169e-02, eta: 13:35:26, time: 0.420, data_time: 0.001, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9950, loss_cls: 0.6175, loss: 0.6175 +2025-06-24 13:48:02,210 - pyskl - INFO - Epoch [36][800/1281] lr: 2.168e-02, eta: 13:34:48, time: 0.321, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9975, loss_cls: 0.5445, loss: 0.5445 +2025-06-24 13:48:52,173 - pyskl - INFO - Epoch [36][900/1281] lr: 2.167e-02, eta: 13:35:08, time: 0.500, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9981, loss_cls: 0.5686, loss: 0.5686 +2025-06-24 13:49:47,223 - pyskl - INFO - Epoch [36][1000/1281] lr: 2.165e-02, eta: 13:35:44, time: 0.550, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9988, loss_cls: 0.5394, loss: 0.5394 +2025-06-24 13:50:40,342 - pyskl - INFO - Epoch [36][1100/1281] lr: 2.164e-02, eta: 13:36:13, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9975, loss_cls: 0.5550, loss: 0.5550 +2025-06-24 13:51:35,641 - pyskl - INFO - Epoch [36][1200/1281] lr: 2.162e-02, eta: 13:36:49, time: 0.553, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9969, loss_cls: 0.5514, loss: 0.5514 +2025-06-24 13:52:20,264 - pyskl - INFO - Saving checkpoint at 36 epochs +2025-06-24 13:53:31,500 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:53:31,556 - pyskl - INFO - +top1_acc 0.8667 +top5_acc 0.9903 +2025-06-24 13:53:31,557 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:53:31,563 - pyskl - INFO - +mean_acc 0.8060 +2025-06-24 13:53:31,568 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_27.pth was removed +2025-06-24 13:53:31,755 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_36.pth. +2025-06-24 13:53:31,756 - pyskl - INFO - Best top1_acc is 0.8667 at 36 epoch. +2025-06-24 13:53:31,758 - pyskl - INFO - Epoch(val) [36][533] top1_acc: 0.8667, top5_acc: 0.9903, mean_class_accuracy: 0.8060 +2025-06-24 13:55:01,182 - pyskl - INFO - Epoch [37][100/1281] lr: 2.160e-02, eta: 13:37:18, time: 0.894, data_time: 0.200, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9969, loss_cls: 0.5344, loss: 0.5344 +2025-06-24 13:55:46,113 - pyskl - INFO - Epoch [37][200/1281] lr: 2.158e-02, eta: 13:37:21, time: 0.449, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9956, loss_cls: 0.5669, loss: 0.5669 +2025-06-24 13:56:33,736 - pyskl - INFO - Epoch [37][300/1281] lr: 2.157e-02, eta: 13:37:31, time: 0.476, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9981, loss_cls: 0.5786, loss: 0.5786 +2025-06-24 13:56:59,924 - pyskl - INFO - Epoch [37][400/1281] lr: 2.156e-02, eta: 13:36:34, time: 0.262, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9962, loss_cls: 0.5548, loss: 0.5548 +2025-06-24 13:57:53,016 - pyskl - INFO - Epoch [37][500/1281] lr: 2.154e-02, eta: 13:37:01, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9969, loss_cls: 0.5369, loss: 0.5369 +2025-06-24 13:58:46,412 - pyskl - INFO - Epoch [37][600/1281] lr: 2.153e-02, eta: 13:37:29, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9944, loss_cls: 0.5533, loss: 0.5533 +2025-06-24 13:59:39,850 - pyskl - INFO - Epoch [37][700/1281] lr: 2.151e-02, eta: 13:37:56, time: 0.534, data_time: 0.001, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9988, loss_cls: 0.5512, loss: 0.5512 +2025-06-24 14:00:33,317 - pyskl - INFO - Epoch [37][800/1281] lr: 2.150e-02, eta: 13:38:23, time: 0.535, data_time: 0.001, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9962, loss_cls: 0.5555, loss: 0.5555 +2025-06-24 14:01:27,234 - pyskl - INFO - Epoch [37][900/1281] lr: 2.149e-02, eta: 13:38:51, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9944, loss_cls: 0.5849, loss: 0.5849 +2025-06-24 14:02:21,819 - pyskl - INFO - Epoch [37][1000/1281] lr: 2.147e-02, eta: 13:39:21, time: 0.546, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9956, loss_cls: 0.6375, loss: 0.6375 +2025-06-24 14:03:16,163 - pyskl - INFO - Epoch [37][1100/1281] lr: 2.146e-02, eta: 13:39:50, time: 0.543, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9944, loss_cls: 0.6325, loss: 0.6325 +2025-06-24 14:04:09,219 - pyskl - INFO - Epoch [37][1200/1281] lr: 2.144e-02, eta: 13:40:15, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9938, loss_cls: 0.6352, loss: 0.6352 +2025-06-24 14:04:53,561 - pyskl - INFO - Saving checkpoint at 37 epochs +2025-06-24 14:06:01,882 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:06:01,939 - pyskl - INFO - +top1_acc 0.8518 +top5_acc 0.9917 +2025-06-24 14:06:01,939 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:06:01,946 - pyskl - INFO - +mean_acc 0.7943 +2025-06-24 14:06:01,949 - pyskl - INFO - Epoch(val) [37][533] top1_acc: 0.8518, top5_acc: 0.9917, mean_class_accuracy: 0.7943 +2025-06-24 14:07:09,805 - pyskl - INFO - Epoch [38][100/1281] lr: 2.142e-02, eta: 13:39:33, time: 0.679, data_time: 0.198, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9969, loss_cls: 0.5618, loss: 0.5618 +2025-06-24 14:08:03,393 - pyskl - INFO - Epoch [38][200/1281] lr: 2.140e-02, eta: 13:39:58, time: 0.536, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9975, loss_cls: 0.5101, loss: 0.5101 +2025-06-24 14:08:58,175 - pyskl - INFO - Epoch [38][300/1281] lr: 2.139e-02, eta: 13:40:27, time: 0.548, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9956, loss_cls: 0.5180, loss: 0.5180 +2025-06-24 14:09:52,910 - pyskl - INFO - Epoch [38][400/1281] lr: 2.137e-02, eta: 13:40:55, time: 0.547, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9938, loss_cls: 0.5692, loss: 0.5692 +2025-06-24 14:10:46,839 - pyskl - INFO - Epoch [38][500/1281] lr: 2.136e-02, eta: 13:41:21, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9938, loss_cls: 0.5635, loss: 0.5635 +2025-06-24 14:11:40,843 - pyskl - INFO - Epoch [38][600/1281] lr: 2.134e-02, eta: 13:41:46, time: 0.540, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9988, loss_cls: 0.5694, loss: 0.5694 +2025-06-24 14:12:35,003 - pyskl - INFO - Epoch [38][700/1281] lr: 2.133e-02, eta: 13:42:12, time: 0.542, data_time: 0.001, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9956, loss_cls: 0.5430, loss: 0.5430 +2025-06-24 14:13:29,117 - pyskl - INFO - Epoch [38][800/1281] lr: 2.132e-02, eta: 13:42:37, time: 0.541, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9931, loss_cls: 0.5833, loss: 0.5833 +2025-06-24 14:14:23,921 - pyskl - INFO - Epoch [38][900/1281] lr: 2.130e-02, eta: 13:43:04, time: 0.548, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9950, loss_cls: 0.5850, loss: 0.5850 +2025-06-24 14:14:52,458 - pyskl - INFO - Epoch [38][1000/1281] lr: 2.129e-02, eta: 13:42:12, time: 0.285, data_time: 0.000, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9956, loss_cls: 0.5940, loss: 0.5940 +2025-06-24 14:15:40,069 - pyskl - INFO - Epoch [38][1100/1281] lr: 2.127e-02, eta: 13:42:17, time: 0.476, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9962, loss_cls: 0.6096, loss: 0.6096 +2025-06-24 14:16:22,959 - pyskl - INFO - Epoch [38][1200/1281] lr: 2.126e-02, eta: 13:42:08, time: 0.429, data_time: 0.001, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9950, loss_cls: 0.5800, loss: 0.5800 +2025-06-24 14:17:06,711 - pyskl - INFO - Saving checkpoint at 38 epochs +2025-06-24 14:18:18,744 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:18:18,799 - pyskl - INFO - +top1_acc 0.8520 +top5_acc 0.9907 +2025-06-24 14:18:18,799 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:18:18,806 - pyskl - INFO - +mean_acc 0.8119 +2025-06-24 14:18:18,808 - pyskl - INFO - Epoch(val) [38][533] top1_acc: 0.8520, top5_acc: 0.9907, mean_class_accuracy: 0.8119 +2025-06-24 14:19:46,715 - pyskl - INFO - Epoch [39][100/1281] lr: 2.123e-02, eta: 13:42:22, time: 0.879, data_time: 0.202, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9931, loss_cls: 0.5263, loss: 0.5263 +2025-06-24 14:20:40,205 - pyskl - INFO - Epoch [39][200/1281] lr: 2.122e-02, eta: 13:42:43, time: 0.535, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9956, loss_cls: 0.4948, loss: 0.4948 +2025-06-24 14:21:33,953 - pyskl - INFO - Epoch [39][300/1281] lr: 2.120e-02, eta: 13:43:05, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9962, loss_cls: 0.5701, loss: 0.5701 +2025-06-24 14:22:28,798 - pyskl - INFO - Epoch [39][400/1281] lr: 2.119e-02, eta: 13:43:30, time: 0.548, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9975, loss_cls: 0.5019, loss: 0.5019 +2025-06-24 14:23:21,420 - pyskl - INFO - Epoch [39][500/1281] lr: 2.117e-02, eta: 13:43:48, time: 0.526, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9956, loss_cls: 0.5771, loss: 0.5771 +2025-06-24 14:23:53,290 - pyskl - INFO - Epoch [39][600/1281] lr: 2.116e-02, eta: 13:43:05, time: 0.319, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9931, loss_cls: 0.5160, loss: 0.5160 +2025-06-24 14:24:38,362 - pyskl - INFO - Epoch [39][700/1281] lr: 2.114e-02, eta: 13:43:01, time: 0.451, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9938, loss_cls: 0.5362, loss: 0.5362 +2025-06-24 14:25:21,243 - pyskl - INFO - Epoch [39][800/1281] lr: 2.113e-02, eta: 13:42:51, time: 0.429, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9956, loss_cls: 0.5731, loss: 0.5731 +2025-06-24 14:26:15,084 - pyskl - INFO - Epoch [39][900/1281] lr: 2.111e-02, eta: 13:43:11, time: 0.538, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9950, loss_cls: 0.5794, loss: 0.5794 +2025-06-24 14:27:09,641 - pyskl - INFO - Epoch [39][1000/1281] lr: 2.110e-02, eta: 13:43:34, time: 0.546, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9962, loss_cls: 0.5598, loss: 0.5598 +2025-06-24 14:28:04,405 - pyskl - INFO - Epoch [39][1100/1281] lr: 2.108e-02, eta: 13:43:56, time: 0.548, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9956, loss_cls: 0.5525, loss: 0.5525 +2025-06-24 14:28:58,802 - pyskl - INFO - Epoch [39][1200/1281] lr: 2.107e-02, eta: 13:44:18, time: 0.544, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9975, loss_cls: 0.5316, loss: 0.5316 +2025-06-24 14:29:42,917 - pyskl - INFO - Saving checkpoint at 39 epochs +2025-06-24 14:30:54,409 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:30:54,467 - pyskl - INFO - +top1_acc 0.8629 +top5_acc 0.9905 +2025-06-24 14:30:54,467 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:30:54,473 - pyskl - INFO - +mean_acc 0.8105 +2025-06-24 14:30:54,475 - pyskl - INFO - Epoch(val) [39][533] top1_acc: 0.8629, top5_acc: 0.9905, mean_class_accuracy: 0.8105 +2025-06-24 14:32:19,012 - pyskl - INFO - Epoch [40][100/1281] lr: 2.104e-02, eta: 13:44:16, time: 0.845, data_time: 0.196, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9925, loss_cls: 0.5228, loss: 0.5228 +2025-06-24 14:32:47,122 - pyskl - INFO - Epoch [40][200/1281] lr: 2.103e-02, eta: 13:43:23, time: 0.281, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9975, loss_cls: 0.5571, loss: 0.5571 +2025-06-24 14:33:35,889 - pyskl - INFO - Epoch [40][300/1281] lr: 2.101e-02, eta: 13:43:27, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9994, loss_cls: 0.4904, loss: 0.4904 +2025-06-24 14:34:17,841 - pyskl - INFO - Epoch [40][400/1281] lr: 2.100e-02, eta: 13:43:12, time: 0.419, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9975, loss_cls: 0.5368, loss: 0.5368 +2025-06-24 14:35:12,809 - pyskl - INFO - Epoch [40][500/1281] lr: 2.098e-02, eta: 13:43:34, time: 0.550, data_time: 0.001, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9988, loss_cls: 0.5619, loss: 0.5619 +2025-06-24 14:36:06,489 - pyskl - INFO - Epoch [40][600/1281] lr: 2.097e-02, eta: 13:43:52, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9981, loss_cls: 0.5106, loss: 0.5106 +2025-06-24 14:37:00,687 - pyskl - INFO - Epoch [40][700/1281] lr: 2.095e-02, eta: 13:44:11, time: 0.542, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9919, loss_cls: 0.6434, loss: 0.6434 +2025-06-24 14:37:53,968 - pyskl - INFO - Epoch [40][800/1281] lr: 2.094e-02, eta: 13:44:27, time: 0.533, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9944, loss_cls: 0.6216, loss: 0.6216 +2025-06-24 14:38:47,705 - pyskl - INFO - Epoch [40][900/1281] lr: 2.092e-02, eta: 13:44:44, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9950, loss_cls: 0.5257, loss: 0.5257 +2025-06-24 14:39:42,153 - pyskl - INFO - Epoch [40][1000/1281] lr: 2.091e-02, eta: 13:45:03, time: 0.544, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9962, loss_cls: 0.5304, loss: 0.5304 +2025-06-24 14:40:36,028 - pyskl - INFO - Epoch [40][1100/1281] lr: 2.089e-02, eta: 13:45:20, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9975, loss_cls: 0.5039, loss: 0.5039 +2025-06-24 14:41:28,070 - pyskl - INFO - Epoch [40][1200/1281] lr: 2.088e-02, eta: 13:45:31, time: 0.520, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9969, loss_cls: 0.5543, loss: 0.5543 +2025-06-24 14:41:58,765 - pyskl - INFO - Saving checkpoint at 40 epochs +2025-06-24 14:43:03,392 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:43:03,448 - pyskl - INFO - +top1_acc 0.8756 +top5_acc 0.9904 +2025-06-24 14:43:03,448 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:43:03,455 - pyskl - INFO - +mean_acc 0.8238 +2025-06-24 14:43:03,459 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_36.pth was removed +2025-06-24 14:43:03,632 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_40.pth. +2025-06-24 14:43:03,632 - pyskl - INFO - Best top1_acc is 0.8756 at 40 epoch. +2025-06-24 14:43:03,635 - pyskl - INFO - Epoch(val) [40][533] top1_acc: 0.8756, top5_acc: 0.9904, mean_class_accuracy: 0.8238 +2025-06-24 14:44:30,464 - pyskl - INFO - Epoch [41][100/1281] lr: 2.085e-02, eta: 13:45:32, time: 0.868, data_time: 0.190, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9969, loss_cls: 0.5787, loss: 0.5787 +2025-06-24 14:45:23,724 - pyskl - INFO - Epoch [41][200/1281] lr: 2.083e-02, eta: 13:45:46, time: 0.533, data_time: 0.001, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9962, loss_cls: 0.5283, loss: 0.5283 +2025-06-24 14:46:17,158 - pyskl - INFO - Epoch [41][300/1281] lr: 2.082e-02, eta: 13:46:00, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9950, loss_cls: 0.4898, loss: 0.4898 +2025-06-24 14:47:11,743 - pyskl - INFO - Epoch [41][400/1281] lr: 2.080e-02, eta: 13:46:18, time: 0.546, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9969, loss_cls: 0.5009, loss: 0.5009 +2025-06-24 14:48:05,124 - pyskl - INFO - Epoch [41][500/1281] lr: 2.079e-02, eta: 13:46:32, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9969, loss_cls: 0.5121, loss: 0.5121 +2025-06-24 14:48:59,290 - pyskl - INFO - Epoch [41][600/1281] lr: 2.077e-02, eta: 13:46:47, time: 0.542, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9975, loss_cls: 0.5346, loss: 0.5346 +2025-06-24 14:49:53,841 - pyskl - INFO - Epoch [41][700/1281] lr: 2.076e-02, eta: 13:47:04, time: 0.546, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9981, loss_cls: 0.5276, loss: 0.5276 +2025-06-24 14:50:48,710 - pyskl - INFO - Epoch [41][800/1281] lr: 2.074e-02, eta: 13:47:21, time: 0.549, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9962, loss_cls: 0.5725, loss: 0.5725 +2025-06-24 14:51:20,749 - pyskl - INFO - Epoch [41][900/1281] lr: 2.073e-02, eta: 13:46:36, time: 0.320, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9950, loss_cls: 0.6470, loss: 0.6470 +2025-06-24 14:52:11,791 - pyskl - INFO - Epoch [41][1000/1281] lr: 2.071e-02, eta: 13:46:43, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9925, loss_cls: 0.5742, loss: 0.5742 +2025-06-24 14:52:44,594 - pyskl - INFO - Epoch [41][1100/1281] lr: 2.070e-02, eta: 13:46:00, time: 0.328, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9975, loss_cls: 0.5288, loss: 0.5288 +2025-06-24 14:53:32,640 - pyskl - INFO - Epoch [41][1200/1281] lr: 2.068e-02, eta: 13:45:58, time: 0.480, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9956, loss_cls: 0.5191, loss: 0.5191 +2025-06-24 14:54:12,502 - pyskl - INFO - Saving checkpoint at 41 epochs +2025-06-24 14:55:12,748 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:55:12,803 - pyskl - INFO - +top1_acc 0.8540 +top5_acc 0.9905 +2025-06-24 14:55:12,803 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:55:12,811 - pyskl - INFO - +mean_acc 0.8211 +2025-06-24 14:55:12,813 - pyskl - INFO - Epoch(val) [41][533] top1_acc: 0.8540, top5_acc: 0.9905, mean_class_accuracy: 0.8211 +2025-06-24 14:56:31,999 - pyskl - INFO - Epoch [42][100/1281] lr: 2.065e-02, eta: 13:45:34, time: 0.792, data_time: 0.201, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9988, loss_cls: 0.4543, loss: 0.4543 +2025-06-24 14:57:20,296 - pyskl - INFO - Epoch [42][200/1281] lr: 2.064e-02, eta: 13:45:32, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9981, loss_cls: 0.5117, loss: 0.5117 +2025-06-24 14:58:08,825 - pyskl - INFO - Epoch [42][300/1281] lr: 2.062e-02, eta: 13:45:31, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9975, loss_cls: 0.5477, loss: 0.5477 +2025-06-24 14:58:57,385 - pyskl - INFO - Epoch [42][400/1281] lr: 2.061e-02, eta: 13:45:29, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9975, loss_cls: 0.5244, loss: 0.5244 +2025-06-24 14:59:45,863 - pyskl - INFO - Epoch [42][500/1281] lr: 2.059e-02, eta: 13:45:28, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9981, loss_cls: 0.5030, loss: 0.5030 +2025-06-24 15:00:34,413 - pyskl - INFO - Epoch [42][600/1281] lr: 2.057e-02, eta: 13:45:26, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9975, loss_cls: 0.4885, loss: 0.4885 +2025-06-24 15:01:22,492 - pyskl - INFO - Epoch [42][700/1281] lr: 2.056e-02, eta: 13:45:23, time: 0.481, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9956, loss_cls: 0.5523, loss: 0.5523 +2025-06-24 15:02:08,940 - pyskl - INFO - Epoch [42][800/1281] lr: 2.054e-02, eta: 13:45:15, time: 0.464, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9975, loss_cls: 0.5138, loss: 0.5138 +2025-06-24 15:02:45,667 - pyskl - INFO - Epoch [42][900/1281] lr: 2.053e-02, eta: 13:44:42, time: 0.367, data_time: 0.001, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9969, loss_cls: 0.5188, loss: 0.5188 +2025-06-24 15:03:23,068 - pyskl - INFO - Epoch [42][1000/1281] lr: 2.051e-02, eta: 13:44:11, time: 0.374, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9950, loss_cls: 0.5678, loss: 0.5678 +2025-06-24 15:03:57,724 - pyskl - INFO - Epoch [42][1100/1281] lr: 2.050e-02, eta: 13:43:33, time: 0.347, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9975, loss_cls: 0.4997, loss: 0.4997 +2025-06-24 15:04:46,827 - pyskl - INFO - Epoch [42][1200/1281] lr: 2.048e-02, eta: 13:43:32, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9988, loss_cls: 0.5098, loss: 0.5098 +2025-06-24 15:05:27,254 - pyskl - INFO - Saving checkpoint at 42 epochs +2025-06-24 15:06:26,197 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:06:26,262 - pyskl - INFO - +top1_acc 0.8446 +top5_acc 0.9906 +2025-06-24 15:06:26,262 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:06:26,271 - pyskl - INFO - +mean_acc 0.7988 +2025-06-24 15:06:26,274 - pyskl - INFO - Epoch(val) [42][533] top1_acc: 0.8446, top5_acc: 0.9906, mean_class_accuracy: 0.7988 +2025-06-24 15:07:47,649 - pyskl - INFO - Epoch [43][100/1281] lr: 2.045e-02, eta: 13:43:10, time: 0.814, data_time: 0.198, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9969, loss_cls: 0.5795, loss: 0.5795 +2025-06-24 15:08:36,588 - pyskl - INFO - Epoch [43][200/1281] lr: 2.044e-02, eta: 13:43:08, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9981, loss_cls: 0.4851, loss: 0.4851 +2025-06-24 15:09:25,906 - pyskl - INFO - Epoch [43][300/1281] lr: 2.042e-02, eta: 13:43:07, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9969, loss_cls: 0.5163, loss: 0.5163 +2025-06-24 15:10:15,084 - pyskl - INFO - Epoch [43][400/1281] lr: 2.040e-02, eta: 13:43:06, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9956, loss_cls: 0.5233, loss: 0.5233 +2025-06-24 15:11:04,279 - pyskl - INFO - Epoch [43][500/1281] lr: 2.039e-02, eta: 13:43:04, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9969, loss_cls: 0.5230, loss: 0.5230 +2025-06-24 15:11:53,385 - pyskl - INFO - Epoch [43][600/1281] lr: 2.037e-02, eta: 13:43:02, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9969, loss_cls: 0.4870, loss: 0.4870 +2025-06-24 15:12:42,747 - pyskl - INFO - Epoch [43][700/1281] lr: 2.036e-02, eta: 13:43:00, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9988, loss_cls: 0.5078, loss: 0.5078 +2025-06-24 15:13:31,872 - pyskl - INFO - Epoch [43][800/1281] lr: 2.034e-02, eta: 13:42:57, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9956, loss_cls: 0.5513, loss: 0.5513 +2025-06-24 15:13:59,646 - pyskl - INFO - Epoch [43][900/1281] lr: 2.033e-02, eta: 13:42:01, time: 0.278, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9975, loss_cls: 0.5283, loss: 0.5283 +2025-06-24 15:14:48,070 - pyskl - INFO - Epoch [43][1000/1281] lr: 2.031e-02, eta: 13:41:57, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9975, loss_cls: 0.5192, loss: 0.5192 +2025-06-24 15:15:20,038 - pyskl - INFO - Epoch [43][1100/1281] lr: 2.029e-02, eta: 13:41:11, time: 0.320, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9962, loss_cls: 0.5206, loss: 0.5206 +2025-06-24 15:16:09,249 - pyskl - INFO - Epoch [43][1200/1281] lr: 2.028e-02, eta: 13:41:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9956, loss_cls: 0.5806, loss: 0.5806 +2025-06-24 15:16:49,503 - pyskl - INFO - Saving checkpoint at 43 epochs +2025-06-24 15:17:49,702 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:17:49,757 - pyskl - INFO - +top1_acc 0.8663 +top5_acc 0.9911 +2025-06-24 15:17:49,757 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:17:49,764 - pyskl - INFO - +mean_acc 0.7937 +2025-06-24 15:17:49,766 - pyskl - INFO - Epoch(val) [43][533] top1_acc: 0.8663, top5_acc: 0.9911, mean_class_accuracy: 0.7937 +2025-06-24 15:19:10,303 - pyskl - INFO - Epoch [44][100/1281] lr: 2.025e-02, eta: 13:40:42, time: 0.805, data_time: 0.197, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9988, loss_cls: 0.4204, loss: 0.4204 +2025-06-24 15:19:59,382 - pyskl - INFO - Epoch [44][200/1281] lr: 2.023e-02, eta: 13:40:38, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9962, loss_cls: 0.5297, loss: 0.5297 +2025-06-24 15:20:48,667 - pyskl - INFO - Epoch [44][300/1281] lr: 2.022e-02, eta: 13:40:35, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9981, loss_cls: 0.5096, loss: 0.5096 +2025-06-24 15:21:37,900 - pyskl - INFO - Epoch [44][400/1281] lr: 2.020e-02, eta: 13:40:32, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9956, loss_cls: 0.4986, loss: 0.4986 +2025-06-24 15:22:26,840 - pyskl - INFO - Epoch [44][500/1281] lr: 2.018e-02, eta: 13:40:27, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9969, loss_cls: 0.4784, loss: 0.4784 +2025-06-24 15:23:15,912 - pyskl - INFO - Epoch [44][600/1281] lr: 2.017e-02, eta: 13:40:23, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9962, loss_cls: 0.5056, loss: 0.5056 +2025-06-24 15:24:04,973 - pyskl - INFO - Epoch [44][700/1281] lr: 2.015e-02, eta: 13:40:19, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9981, loss_cls: 0.5379, loss: 0.5379 +2025-06-24 15:24:54,164 - pyskl - INFO - Epoch [44][800/1281] lr: 2.014e-02, eta: 13:40:15, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9962, loss_cls: 0.5296, loss: 0.5296 +2025-06-24 15:25:22,461 - pyskl - INFO - Epoch [44][900/1281] lr: 2.012e-02, eta: 13:39:20, time: 0.283, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9962, loss_cls: 0.5881, loss: 0.5881 +2025-06-24 15:26:10,797 - pyskl - INFO - Epoch [44][1000/1281] lr: 2.010e-02, eta: 13:39:13, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9919, loss_cls: 0.5824, loss: 0.5824 +2025-06-24 15:26:41,495 - pyskl - INFO - Epoch [44][1100/1281] lr: 2.009e-02, eta: 13:38:24, time: 0.307, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9975, loss_cls: 0.5204, loss: 0.5204 +2025-06-24 15:27:31,074 - pyskl - INFO - Epoch [44][1200/1281] lr: 2.007e-02, eta: 13:38:20, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9975, loss_cls: 0.5442, loss: 0.5442 +2025-06-24 15:28:11,936 - pyskl - INFO - Saving checkpoint at 44 epochs +2025-06-24 15:29:11,305 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:29:11,365 - pyskl - INFO - +top1_acc 0.8749 +top5_acc 0.9912 +2025-06-24 15:29:11,365 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:29:11,374 - pyskl - INFO - +mean_acc 0.8362 +2025-06-24 15:29:11,377 - pyskl - INFO - Epoch(val) [44][533] top1_acc: 0.8749, top5_acc: 0.9912, mean_class_accuracy: 0.8362 +2025-06-24 15:30:32,079 - pyskl - INFO - Epoch [45][100/1281] lr: 2.004e-02, eta: 13:37:52, time: 0.807, data_time: 0.194, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9975, loss_cls: 0.5469, loss: 0.5469 +2025-06-24 15:31:21,447 - pyskl - INFO - Epoch [45][200/1281] lr: 2.003e-02, eta: 13:37:47, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9962, loss_cls: 0.5444, loss: 0.5444 +2025-06-24 15:32:10,530 - pyskl - INFO - Epoch [45][300/1281] lr: 2.001e-02, eta: 13:37:42, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9944, loss_cls: 0.5528, loss: 0.5528 +2025-06-24 15:32:59,848 - pyskl - INFO - Epoch [45][400/1281] lr: 1.999e-02, eta: 13:37:37, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9950, loss_cls: 0.4560, loss: 0.4560 +2025-06-24 15:33:49,359 - pyskl - INFO - Epoch [45][500/1281] lr: 1.998e-02, eta: 13:37:32, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9962, loss_cls: 0.4804, loss: 0.4804 +2025-06-24 15:34:38,466 - pyskl - INFO - Epoch [45][600/1281] lr: 1.996e-02, eta: 13:37:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9956, loss_cls: 0.5891, loss: 0.5891 +2025-06-24 15:35:27,942 - pyskl - INFO - Epoch [45][700/1281] lr: 1.994e-02, eta: 13:37:21, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9962, loss_cls: 0.4930, loss: 0.4930 +2025-06-24 15:36:17,792 - pyskl - INFO - Epoch [45][800/1281] lr: 1.993e-02, eta: 13:37:17, time: 0.498, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9975, loss_cls: 0.4922, loss: 0.4922 +2025-06-24 15:36:45,943 - pyskl - INFO - Epoch [45][900/1281] lr: 1.991e-02, eta: 13:36:21, time: 0.282, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9950, loss_cls: 0.5382, loss: 0.5382 +2025-06-24 15:37:37,013 - pyskl - INFO - Epoch [45][1000/1281] lr: 1.989e-02, eta: 13:36:20, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9975, loss_cls: 0.4785, loss: 0.4785 +2025-06-24 15:38:06,688 - pyskl - INFO - Epoch [45][1100/1281] lr: 1.988e-02, eta: 13:35:28, time: 0.297, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9950, loss_cls: 0.4954, loss: 0.4954 +2025-06-24 15:38:56,023 - pyskl - INFO - Epoch [45][1200/1281] lr: 1.986e-02, eta: 13:35:22, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9969, loss_cls: 0.4990, loss: 0.4990 +2025-06-24 15:39:36,322 - pyskl - INFO - Saving checkpoint at 45 epochs +2025-06-24 15:40:35,757 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:40:35,813 - pyskl - INFO - +top1_acc 0.8676 +top5_acc 0.9919 +2025-06-24 15:40:35,814 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:40:35,822 - pyskl - INFO - +mean_acc 0.7991 +2025-06-24 15:40:35,824 - pyskl - INFO - Epoch(val) [45][533] top1_acc: 0.8676, top5_acc: 0.9919, mean_class_accuracy: 0.7991 +2025-06-24 15:41:56,369 - pyskl - INFO - Epoch [46][100/1281] lr: 1.983e-02, eta: 13:34:50, time: 0.805, data_time: 0.197, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9981, loss_cls: 0.4907, loss: 0.4907 +2025-06-24 15:42:45,957 - pyskl - INFO - Epoch [46][200/1281] lr: 1.981e-02, eta: 13:34:45, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9975, loss_cls: 0.4597, loss: 0.4597 +2025-06-24 15:43:34,907 - pyskl - INFO - Epoch [46][300/1281] lr: 1.980e-02, eta: 13:34:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9962, loss_cls: 0.5433, loss: 0.5433 +2025-06-24 15:44:24,324 - pyskl - INFO - Epoch [46][400/1281] lr: 1.978e-02, eta: 13:34:31, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9956, loss_cls: 0.4988, loss: 0.4988 +2025-06-24 15:45:13,529 - pyskl - INFO - Epoch [46][500/1281] lr: 1.976e-02, eta: 13:34:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9975, loss_cls: 0.4610, loss: 0.4610 +2025-06-24 15:46:02,498 - pyskl - INFO - Epoch [46][600/1281] lr: 1.975e-02, eta: 13:34:16, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9969, loss_cls: 0.5017, loss: 0.5017 +2025-06-24 15:46:51,661 - pyskl - INFO - Epoch [46][700/1281] lr: 1.973e-02, eta: 13:34:09, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9956, loss_cls: 0.4760, loss: 0.4760 +2025-06-24 15:47:41,028 - pyskl - INFO - Epoch [46][800/1281] lr: 1.971e-02, eta: 13:34:02, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9975, loss_cls: 0.5155, loss: 0.5155 +2025-06-24 15:48:10,601 - pyskl - INFO - Epoch [46][900/1281] lr: 1.970e-02, eta: 13:33:09, time: 0.296, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9962, loss_cls: 0.5184, loss: 0.5184 +2025-06-24 15:49:01,844 - pyskl - INFO - Epoch [46][1000/1281] lr: 1.968e-02, eta: 13:33:06, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9944, loss_cls: 0.5661, loss: 0.5661 +2025-06-24 15:49:32,036 - pyskl - INFO - Epoch [46][1100/1281] lr: 1.966e-02, eta: 13:32:15, time: 0.302, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9962, loss_cls: 0.5826, loss: 0.5826 +2025-06-24 15:50:21,307 - pyskl - INFO - Epoch [46][1200/1281] lr: 1.965e-02, eta: 13:32:08, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9956, loss_cls: 0.5238, loss: 0.5238 +2025-06-24 15:51:01,661 - pyskl - INFO - Saving checkpoint at 46 epochs +2025-06-24 15:52:00,911 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:52:00,967 - pyskl - INFO - +top1_acc 0.8378 +top5_acc 0.9838 +2025-06-24 15:52:00,967 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:52:00,974 - pyskl - INFO - +mean_acc 0.7875 +2025-06-24 15:52:00,976 - pyskl - INFO - Epoch(val) [46][533] top1_acc: 0.8378, top5_acc: 0.9838, mean_class_accuracy: 0.7875 +2025-06-24 15:53:20,876 - pyskl - INFO - Epoch [47][100/1281] lr: 1.962e-02, eta: 13:31:32, time: 0.799, data_time: 0.191, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9956, loss_cls: 0.5271, loss: 0.5271 +2025-06-24 15:54:09,976 - pyskl - INFO - Epoch [47][200/1281] lr: 1.960e-02, eta: 13:31:24, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9956, loss_cls: 0.4979, loss: 0.4979 +2025-06-24 15:54:59,465 - pyskl - INFO - Epoch [47][300/1281] lr: 1.958e-02, eta: 13:31:16, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9975, loss_cls: 0.4889, loss: 0.4889 +2025-06-24 15:55:48,674 - pyskl - INFO - Epoch [47][400/1281] lr: 1.957e-02, eta: 13:31:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9988, loss_cls: 0.5034, loss: 0.5034 +2025-06-24 15:56:38,187 - pyskl - INFO - Epoch [47][500/1281] lr: 1.955e-02, eta: 13:31:00, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9962, loss_cls: 0.5391, loss: 0.5391 +2025-06-24 15:57:27,590 - pyskl - INFO - Epoch [47][600/1281] lr: 1.953e-02, eta: 13:30:52, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9950, loss_cls: 0.4556, loss: 0.4556 +2025-06-24 15:58:16,942 - pyskl - INFO - Epoch [47][700/1281] lr: 1.952e-02, eta: 13:30:43, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9962, loss_cls: 0.5130, loss: 0.5130 +2025-06-24 15:59:06,083 - pyskl - INFO - Epoch [47][800/1281] lr: 1.950e-02, eta: 13:30:34, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9962, loss_cls: 0.5503, loss: 0.5503 +2025-06-24 15:59:35,766 - pyskl - INFO - Epoch [47][900/1281] lr: 1.948e-02, eta: 13:29:42, time: 0.297, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9962, loss_cls: 0.4909, loss: 0.4909 +2025-06-24 16:00:26,955 - pyskl - INFO - Epoch [47][1000/1281] lr: 1.947e-02, eta: 13:29:37, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9962, loss_cls: 0.5548, loss: 0.5548 +2025-06-24 16:00:55,220 - pyskl - INFO - Epoch [47][1100/1281] lr: 1.945e-02, eta: 13:28:42, time: 0.283, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9962, loss_cls: 0.4651, loss: 0.4651 +2025-06-24 16:01:44,180 - pyskl - INFO - Epoch [47][1200/1281] lr: 1.943e-02, eta: 13:28:32, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9981, loss_cls: 0.5397, loss: 0.5397 +2025-06-24 16:02:24,481 - pyskl - INFO - Saving checkpoint at 47 epochs +2025-06-24 16:03:23,451 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:03:23,516 - pyskl - INFO - +top1_acc 0.8796 +top5_acc 0.9930 +2025-06-24 16:03:23,516 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:03:23,526 - pyskl - INFO - +mean_acc 0.8340 +2025-06-24 16:03:23,532 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_40.pth was removed +2025-06-24 16:03:23,724 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_47.pth. +2025-06-24 16:03:23,725 - pyskl - INFO - Best top1_acc is 0.8796 at 47 epoch. +2025-06-24 16:03:23,727 - pyskl - INFO - Epoch(val) [47][533] top1_acc: 0.8796, top5_acc: 0.9930, mean_class_accuracy: 0.8340 +2025-06-24 16:04:44,833 - pyskl - INFO - Epoch [48][100/1281] lr: 1.940e-02, eta: 13:27:57, time: 0.811, data_time: 0.190, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9975, loss_cls: 0.4725, loss: 0.4725 +2025-06-24 16:05:33,871 - pyskl - INFO - Epoch [48][200/1281] lr: 1.938e-02, eta: 13:27:47, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9975, loss_cls: 0.4436, loss: 0.4436 +2025-06-24 16:06:22,896 - pyskl - INFO - Epoch [48][300/1281] lr: 1.937e-02, eta: 13:27:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9981, loss_cls: 0.4647, loss: 0.4647 +2025-06-24 16:07:12,247 - pyskl - INFO - Epoch [48][400/1281] lr: 1.935e-02, eta: 13:27:27, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9962, loss_cls: 0.5156, loss: 0.5156 +2025-06-24 16:08:01,368 - pyskl - INFO - Epoch [48][500/1281] lr: 1.933e-02, eta: 13:27:17, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9950, loss_cls: 0.5281, loss: 0.5281 +2025-06-24 16:08:50,427 - pyskl - INFO - Epoch [48][600/1281] lr: 1.932e-02, eta: 13:27:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9938, loss_cls: 0.5632, loss: 0.5632 +2025-06-24 16:09:39,587 - pyskl - INFO - Epoch [48][700/1281] lr: 1.930e-02, eta: 13:26:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9962, loss_cls: 0.5246, loss: 0.5246 +2025-06-24 16:10:28,776 - pyskl - INFO - Epoch [48][800/1281] lr: 1.928e-02, eta: 13:26:46, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9969, loss_cls: 0.4771, loss: 0.4771 +2025-06-24 16:10:59,111 - pyskl - INFO - Epoch [48][900/1281] lr: 1.926e-02, eta: 13:25:55, time: 0.303, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9981, loss_cls: 0.4847, loss: 0.4847 +2025-06-24 16:11:50,278 - pyskl - INFO - Epoch [48][1000/1281] lr: 1.925e-02, eta: 13:25:48, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9975, loss_cls: 0.4824, loss: 0.4824 +2025-06-24 16:12:17,501 - pyskl - INFO - Epoch [48][1100/1281] lr: 1.923e-02, eta: 13:24:51, time: 0.272, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9975, loss_cls: 0.5069, loss: 0.5069 +2025-06-24 16:13:06,909 - pyskl - INFO - Epoch [48][1200/1281] lr: 1.921e-02, eta: 13:24:40, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9981, loss_cls: 0.4945, loss: 0.4945 +2025-06-24 16:13:47,312 - pyskl - INFO - Saving checkpoint at 48 epochs +2025-06-24 16:14:47,189 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:14:47,246 - pyskl - INFO - +top1_acc 0.8640 +top5_acc 0.9897 +2025-06-24 16:14:47,246 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:14:47,253 - pyskl - INFO - +mean_acc 0.8160 +2025-06-24 16:14:47,255 - pyskl - INFO - Epoch(val) [48][533] top1_acc: 0.8640, top5_acc: 0.9897, mean_class_accuracy: 0.8160 +2025-06-24 16:16:06,046 - pyskl - INFO - Epoch [49][100/1281] lr: 1.918e-02, eta: 13:23:59, time: 0.788, data_time: 0.192, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9988, loss_cls: 0.4869, loss: 0.4869 +2025-06-24 16:16:54,978 - pyskl - INFO - Epoch [49][200/1281] lr: 1.916e-02, eta: 13:23:47, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9994, loss_cls: 0.3875, loss: 0.3875 +2025-06-24 16:17:44,368 - pyskl - INFO - Epoch [49][300/1281] lr: 1.915e-02, eta: 13:23:37, time: 0.494, data_time: 0.001, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9994, loss_cls: 0.4305, loss: 0.4305 +2025-06-24 16:18:33,705 - pyskl - INFO - Epoch [49][400/1281] lr: 1.913e-02, eta: 13:23:26, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9975, loss_cls: 0.5507, loss: 0.5507 +2025-06-24 16:19:22,850 - pyskl - INFO - Epoch [49][500/1281] lr: 1.911e-02, eta: 13:23:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9956, loss_cls: 0.5831, loss: 0.5831 +2025-06-24 16:20:11,765 - pyskl - INFO - Epoch [49][600/1281] lr: 1.909e-02, eta: 13:23:02, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9962, loss_cls: 0.4470, loss: 0.4470 +2025-06-24 16:21:01,177 - pyskl - INFO - Epoch [49][700/1281] lr: 1.908e-02, eta: 13:22:51, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9969, loss_cls: 0.5087, loss: 0.5087 +2025-06-24 16:21:50,172 - pyskl - INFO - Epoch [49][800/1281] lr: 1.906e-02, eta: 13:22:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9994, loss_cls: 0.4942, loss: 0.4942 +2025-06-24 16:22:23,109 - pyskl - INFO - Epoch [49][900/1281] lr: 1.904e-02, eta: 13:21:53, time: 0.329, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 1.0000, loss_cls: 0.5246, loss: 0.5246 +2025-06-24 16:23:14,319 - pyskl - INFO - Epoch [49][1000/1281] lr: 1.902e-02, eta: 13:21:45, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9944, loss_cls: 0.5197, loss: 0.5197 +2025-06-24 16:23:40,616 - pyskl - INFO - Epoch [49][1100/1281] lr: 1.901e-02, eta: 13:20:46, time: 0.263, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9975, loss_cls: 0.5053, loss: 0.5053 +2025-06-24 16:24:30,245 - pyskl - INFO - Epoch [49][1200/1281] lr: 1.899e-02, eta: 13:20:34, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9975, loss_cls: 0.5080, loss: 0.5080 +2025-06-24 16:25:10,420 - pyskl - INFO - Saving checkpoint at 49 epochs +2025-06-24 16:26:10,054 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:26:10,113 - pyskl - INFO - +top1_acc 0.8675 +top5_acc 0.9916 +2025-06-24 16:26:10,113 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:26:10,121 - pyskl - INFO - +mean_acc 0.8135 +2025-06-24 16:26:10,123 - pyskl - INFO - Epoch(val) [49][533] top1_acc: 0.8675, top5_acc: 0.9916, mean_class_accuracy: 0.8135 +2025-06-24 16:27:28,859 - pyskl - INFO - Epoch [50][100/1281] lr: 1.896e-02, eta: 13:19:51, time: 0.787, data_time: 0.189, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9981, loss_cls: 0.4648, loss: 0.4648 +2025-06-24 16:28:17,828 - pyskl - INFO - Epoch [50][200/1281] lr: 1.894e-02, eta: 13:19:38, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9962, loss_cls: 0.4624, loss: 0.4624 +2025-06-24 16:29:06,923 - pyskl - INFO - Epoch [50][300/1281] lr: 1.892e-02, eta: 13:19:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9956, loss_cls: 0.4676, loss: 0.4676 +2025-06-24 16:29:56,166 - pyskl - INFO - Epoch [50][400/1281] lr: 1.891e-02, eta: 13:19:13, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9969, loss_cls: 0.4845, loss: 0.4845 +2025-06-24 16:30:45,398 - pyskl - INFO - Epoch [50][500/1281] lr: 1.889e-02, eta: 13:19:00, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9988, loss_cls: 0.4725, loss: 0.4725 +2025-06-24 16:31:34,860 - pyskl - INFO - Epoch [50][600/1281] lr: 1.887e-02, eta: 13:18:48, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9969, loss_cls: 0.4969, loss: 0.4969 +2025-06-24 16:32:24,471 - pyskl - INFO - Epoch [50][700/1281] lr: 1.885e-02, eta: 13:18:36, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9988, loss_cls: 0.5252, loss: 0.5252 +2025-06-24 16:33:13,695 - pyskl - INFO - Epoch [50][800/1281] lr: 1.884e-02, eta: 13:18:23, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9956, loss_cls: 0.4956, loss: 0.4956 +2025-06-24 16:33:47,339 - pyskl - INFO - Epoch [50][900/1281] lr: 1.882e-02, eta: 13:17:39, time: 0.336, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9975, loss_cls: 0.4655, loss: 0.4655 +2025-06-24 16:34:38,673 - pyskl - INFO - Epoch [50][1000/1281] lr: 1.880e-02, eta: 13:17:30, time: 0.513, data_time: 0.001, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9981, loss_cls: 0.4548, loss: 0.4548 +2025-06-24 16:35:04,142 - pyskl - INFO - Epoch [50][1100/1281] lr: 1.878e-02, eta: 13:16:29, time: 0.255, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9962, loss_cls: 0.4799, loss: 0.4799 +2025-06-24 16:35:53,324 - pyskl - INFO - Epoch [50][1200/1281] lr: 1.876e-02, eta: 13:16:15, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9975, loss_cls: 0.4766, loss: 0.4766 +2025-06-24 16:36:33,767 - pyskl - INFO - Saving checkpoint at 50 epochs +2025-06-24 16:37:33,167 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:37:33,223 - pyskl - INFO - +top1_acc 0.8743 +top5_acc 0.9923 +2025-06-24 16:37:33,223 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:37:33,230 - pyskl - INFO - +mean_acc 0.8427 +2025-06-24 16:37:33,232 - pyskl - INFO - Epoch(val) [50][533] top1_acc: 0.8743, top5_acc: 0.9923, mean_class_accuracy: 0.8427 +2025-06-24 16:38:53,315 - pyskl - INFO - Epoch [51][100/1281] lr: 1.873e-02, eta: 13:15:33, time: 0.801, data_time: 0.190, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9975, loss_cls: 0.4459, loss: 0.4459 +2025-06-24 16:39:42,372 - pyskl - INFO - Epoch [51][200/1281] lr: 1.871e-02, eta: 13:15:19, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9994, loss_cls: 0.3715, loss: 0.3715 +2025-06-24 16:40:31,771 - pyskl - INFO - Epoch [51][300/1281] lr: 1.870e-02, eta: 13:15:06, time: 0.494, data_time: 0.001, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9969, loss_cls: 0.4586, loss: 0.4586 +2025-06-24 16:41:20,911 - pyskl - INFO - Epoch [51][400/1281] lr: 1.868e-02, eta: 13:14:52, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9962, loss_cls: 0.5128, loss: 0.5128 +2025-06-24 16:42:09,896 - pyskl - INFO - Epoch [51][500/1281] lr: 1.866e-02, eta: 13:14:38, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9975, loss_cls: 0.5233, loss: 0.5233 +2025-06-24 16:42:59,234 - pyskl - INFO - Epoch [51][600/1281] lr: 1.864e-02, eta: 13:14:24, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9969, loss_cls: 0.4933, loss: 0.4933 +2025-06-24 16:43:48,595 - pyskl - INFO - Epoch [51][700/1281] lr: 1.863e-02, eta: 13:14:10, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9994, loss_cls: 0.4913, loss: 0.4913 +2025-06-24 16:44:37,599 - pyskl - INFO - Epoch [51][800/1281] lr: 1.861e-02, eta: 13:13:55, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9956, loss_cls: 0.5305, loss: 0.5305 +2025-06-24 16:45:10,628 - pyskl - INFO - Epoch [51][900/1281] lr: 1.859e-02, eta: 13:13:09, time: 0.330, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9988, loss_cls: 0.5128, loss: 0.5128 +2025-06-24 16:46:01,850 - pyskl - INFO - Epoch [51][1000/1281] lr: 1.857e-02, eta: 13:12:59, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9981, loss_cls: 0.5086, loss: 0.5086 +2025-06-24 16:46:27,492 - pyskl - INFO - Epoch [51][1100/1281] lr: 1.855e-02, eta: 13:11:59, time: 0.256, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9950, loss_cls: 0.4917, loss: 0.4917 +2025-06-24 16:47:14,635 - pyskl - INFO - Epoch [51][1200/1281] lr: 1.854e-02, eta: 13:11:40, time: 0.471, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9975, loss_cls: 0.4489, loss: 0.4489 +2025-06-24 16:47:54,792 - pyskl - INFO - Saving checkpoint at 51 epochs +2025-06-24 16:48:54,808 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:48:54,866 - pyskl - INFO - +top1_acc 0.8900 +top5_acc 0.9940 +2025-06-24 16:48:54,867 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:48:54,876 - pyskl - INFO - +mean_acc 0.8453 +2025-06-24 16:48:54,882 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_47.pth was removed +2025-06-24 16:48:55,083 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_51.pth. +2025-06-24 16:48:55,083 - pyskl - INFO - Best top1_acc is 0.8900 at 51 epoch. +2025-06-24 16:48:55,086 - pyskl - INFO - Epoch(val) [51][533] top1_acc: 0.8900, top5_acc: 0.9940, mean_class_accuracy: 0.8453 +2025-06-24 16:50:15,079 - pyskl - INFO - Epoch [52][100/1281] lr: 1.850e-02, eta: 13:10:56, time: 0.800, data_time: 0.193, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9969, loss_cls: 0.4423, loss: 0.4423 +2025-06-24 16:51:04,248 - pyskl - INFO - Epoch [52][200/1281] lr: 1.849e-02, eta: 13:10:41, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9969, loss_cls: 0.4105, loss: 0.4105 +2025-06-24 16:51:53,559 - pyskl - INFO - Epoch [52][300/1281] lr: 1.847e-02, eta: 13:10:27, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9981, loss_cls: 0.4999, loss: 0.4999 +2025-06-24 16:52:42,783 - pyskl - INFO - Epoch [52][400/1281] lr: 1.845e-02, eta: 13:10:12, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9981, loss_cls: 0.4766, loss: 0.4766 +2025-06-24 16:53:32,318 - pyskl - INFO - Epoch [52][500/1281] lr: 1.843e-02, eta: 13:09:57, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9988, loss_cls: 0.4209, loss: 0.4209 +2025-06-24 16:54:21,823 - pyskl - INFO - Epoch [52][600/1281] lr: 1.841e-02, eta: 13:09:43, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9969, loss_cls: 0.5024, loss: 0.5024 +2025-06-24 16:55:11,075 - pyskl - INFO - Epoch [52][700/1281] lr: 1.840e-02, eta: 13:09:27, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9969, loss_cls: 0.4844, loss: 0.4844 +2025-06-24 16:56:00,610 - pyskl - INFO - Epoch [52][800/1281] lr: 1.838e-02, eta: 13:09:13, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9975, loss_cls: 0.4260, loss: 0.4260 +2025-06-24 16:56:35,112 - pyskl - INFO - Epoch [52][900/1281] lr: 1.836e-02, eta: 13:08:29, time: 0.345, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9956, loss_cls: 0.5283, loss: 0.5283 +2025-06-24 16:57:26,414 - pyskl - INFO - Epoch [52][1000/1281] lr: 1.834e-02, eta: 13:08:18, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9981, loss_cls: 0.3942, loss: 0.3942 +2025-06-24 16:57:51,319 - pyskl - INFO - Epoch [52][1100/1281] lr: 1.832e-02, eta: 13:07:16, time: 0.249, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9981, loss_cls: 0.4473, loss: 0.4473 +2025-06-24 16:58:37,559 - pyskl - INFO - Epoch [52][1200/1281] lr: 1.831e-02, eta: 13:06:55, time: 0.462, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9956, loss_cls: 0.4445, loss: 0.4445 +2025-06-24 16:59:18,187 - pyskl - INFO - Saving checkpoint at 52 epochs +2025-06-24 17:00:17,240 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:00:17,310 - pyskl - INFO - +top1_acc 0.8634 +top5_acc 0.9920 +2025-06-24 17:00:17,310 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:00:17,318 - pyskl - INFO - +mean_acc 0.8215 +2025-06-24 17:00:17,320 - pyskl - INFO - Epoch(val) [52][533] top1_acc: 0.8634, top5_acc: 0.9920, mean_class_accuracy: 0.8215 +2025-06-24 17:01:37,226 - pyskl - INFO - Epoch [53][100/1281] lr: 1.827e-02, eta: 13:06:09, time: 0.799, data_time: 0.188, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9956, loss_cls: 0.4792, loss: 0.4792 +2025-06-24 17:02:26,156 - pyskl - INFO - Epoch [53][200/1281] lr: 1.826e-02, eta: 13:05:53, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9981, loss_cls: 0.4832, loss: 0.4832 +2025-06-24 17:03:15,413 - pyskl - INFO - Epoch [53][300/1281] lr: 1.824e-02, eta: 13:05:37, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9969, loss_cls: 0.3857, loss: 0.3857 +2025-06-24 17:04:04,618 - pyskl - INFO - Epoch [53][400/1281] lr: 1.822e-02, eta: 13:05:21, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9975, loss_cls: 0.4690, loss: 0.4690 +2025-06-24 17:04:53,792 - pyskl - INFO - Epoch [53][500/1281] lr: 1.820e-02, eta: 13:05:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9988, loss_cls: 0.5043, loss: 0.5043 +2025-06-24 17:05:42,905 - pyskl - INFO - Epoch [53][600/1281] lr: 1.818e-02, eta: 13:04:48, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9969, loss_cls: 0.4913, loss: 0.4913 +2025-06-24 17:06:32,430 - pyskl - INFO - Epoch [53][700/1281] lr: 1.816e-02, eta: 13:04:33, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9969, loss_cls: 0.4437, loss: 0.4437 +2025-06-24 17:07:22,066 - pyskl - INFO - Epoch [53][800/1281] lr: 1.815e-02, eta: 13:04:17, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9988, loss_cls: 0.4469, loss: 0.4469 +2025-06-24 17:07:58,897 - pyskl - INFO - Epoch [53][900/1281] lr: 1.813e-02, eta: 13:03:38, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9950, loss_cls: 0.5234, loss: 0.5234 +2025-06-24 17:08:50,185 - pyskl - INFO - Epoch [53][1000/1281] lr: 1.811e-02, eta: 13:03:25, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9969, loss_cls: 0.4931, loss: 0.4931 +2025-06-24 17:09:14,513 - pyskl - INFO - Epoch [53][1100/1281] lr: 1.809e-02, eta: 13:02:22, time: 0.243, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9981, loss_cls: 0.4672, loss: 0.4672 +2025-06-24 17:09:59,930 - pyskl - INFO - Epoch [53][1200/1281] lr: 1.807e-02, eta: 13:01:59, time: 0.454, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9956, loss_cls: 0.5027, loss: 0.5027 +2025-06-24 17:10:40,613 - pyskl - INFO - Saving checkpoint at 53 epochs +2025-06-24 17:11:39,921 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:11:39,977 - pyskl - INFO - +top1_acc 0.8722 +top5_acc 0.9905 +2025-06-24 17:11:39,977 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:11:39,985 - pyskl - INFO - +mean_acc 0.8146 +2025-06-24 17:11:39,987 - pyskl - INFO - Epoch(val) [53][533] top1_acc: 0.8722, top5_acc: 0.9905, mean_class_accuracy: 0.8146 +2025-06-24 17:13:01,845 - pyskl - INFO - Epoch [54][100/1281] lr: 1.804e-02, eta: 13:01:15, time: 0.819, data_time: 0.199, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9981, loss_cls: 0.4534, loss: 0.4534 +2025-06-24 17:13:51,052 - pyskl - INFO - Epoch [54][200/1281] lr: 1.802e-02, eta: 13:00:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9975, loss_cls: 0.3977, loss: 0.3977 +2025-06-24 17:14:40,213 - pyskl - INFO - Epoch [54][300/1281] lr: 1.800e-02, eta: 13:00:41, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9994, loss_cls: 0.3856, loss: 0.3856 +2025-06-24 17:15:29,253 - pyskl - INFO - Epoch [54][400/1281] lr: 1.798e-02, eta: 13:00:24, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9981, loss_cls: 0.4506, loss: 0.4506 +2025-06-24 17:16:18,524 - pyskl - INFO - Epoch [54][500/1281] lr: 1.797e-02, eta: 13:00:07, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9988, loss_cls: 0.4593, loss: 0.4593 +2025-06-24 17:17:07,759 - pyskl - INFO - Epoch [54][600/1281] lr: 1.795e-02, eta: 12:59:50, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9981, loss_cls: 0.4114, loss: 0.4114 +2025-06-24 17:17:57,182 - pyskl - INFO - Epoch [54][700/1281] lr: 1.793e-02, eta: 12:59:33, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9981, loss_cls: 0.4883, loss: 0.4883 +2025-06-24 17:18:46,715 - pyskl - INFO - Epoch [54][800/1281] lr: 1.791e-02, eta: 12:59:16, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9975, loss_cls: 0.5068, loss: 0.5068 +2025-06-24 17:19:23,925 - pyskl - INFO - Epoch [54][900/1281] lr: 1.789e-02, eta: 12:58:37, time: 0.372, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9944, loss_cls: 0.5187, loss: 0.5187 +2025-06-24 17:20:15,002 - pyskl - INFO - Epoch [54][1000/1281] lr: 1.787e-02, eta: 12:58:22, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9956, loss_cls: 0.4728, loss: 0.4728 +2025-06-24 17:20:39,007 - pyskl - INFO - Epoch [54][1100/1281] lr: 1.786e-02, eta: 12:57:20, time: 0.240, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9981, loss_cls: 0.4608, loss: 0.4608 +2025-06-24 17:21:23,667 - pyskl - INFO - Epoch [54][1200/1281] lr: 1.784e-02, eta: 12:56:54, time: 0.447, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9962, loss_cls: 0.4563, loss: 0.4563 +2025-06-24 17:22:04,183 - pyskl - INFO - Saving checkpoint at 54 epochs +2025-06-24 17:23:03,573 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:23:03,644 - pyskl - INFO - +top1_acc 0.8571 +top5_acc 0.9894 +2025-06-24 17:23:03,644 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:23:03,654 - pyskl - INFO - +mean_acc 0.8258 +2025-06-24 17:23:03,657 - pyskl - INFO - Epoch(val) [54][533] top1_acc: 0.8571, top5_acc: 0.9894, mean_class_accuracy: 0.8258 +2025-06-24 17:24:25,025 - pyskl - INFO - Epoch [55][100/1281] lr: 1.780e-02, eta: 12:56:08, time: 0.814, data_time: 0.196, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9981, loss_cls: 0.4471, loss: 0.4471 +2025-06-24 17:25:14,485 - pyskl - INFO - Epoch [55][200/1281] lr: 1.779e-02, eta: 12:55:51, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9988, loss_cls: 0.4075, loss: 0.4075 +2025-06-24 17:26:03,593 - pyskl - INFO - Epoch [55][300/1281] lr: 1.777e-02, eta: 12:55:33, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9981, loss_cls: 0.4138, loss: 0.4138 +2025-06-24 17:26:52,655 - pyskl - INFO - Epoch [55][400/1281] lr: 1.775e-02, eta: 12:55:14, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9975, loss_cls: 0.4892, loss: 0.4892 +2025-06-24 17:27:41,723 - pyskl - INFO - Epoch [55][500/1281] lr: 1.773e-02, eta: 12:54:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9981, loss_cls: 0.3740, loss: 0.3740 +2025-06-24 17:28:30,536 - pyskl - INFO - Epoch [55][600/1281] lr: 1.771e-02, eta: 12:54:37, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9969, loss_cls: 0.4875, loss: 0.4875 +2025-06-24 17:29:19,677 - pyskl - INFO - Epoch [55][700/1281] lr: 1.769e-02, eta: 12:54:18, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9969, loss_cls: 0.4525, loss: 0.4525 +2025-06-24 17:30:08,930 - pyskl - INFO - Epoch [55][800/1281] lr: 1.767e-02, eta: 12:54:00, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9969, loss_cls: 0.4753, loss: 0.4753 +2025-06-24 17:30:47,970 - pyskl - INFO - Epoch [55][900/1281] lr: 1.766e-02, eta: 12:53:24, time: 0.390, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9988, loss_cls: 0.4632, loss: 0.4632 +2025-06-24 17:31:39,169 - pyskl - INFO - Epoch [55][1000/1281] lr: 1.764e-02, eta: 12:53:09, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9975, loss_cls: 0.4709, loss: 0.4709 +2025-06-24 17:32:02,639 - pyskl - INFO - Epoch [55][1100/1281] lr: 1.762e-02, eta: 12:52:06, time: 0.235, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9962, loss_cls: 0.4486, loss: 0.4486 +2025-06-24 17:32:47,706 - pyskl - INFO - Epoch [55][1200/1281] lr: 1.760e-02, eta: 12:51:40, time: 0.451, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9969, loss_cls: 0.4859, loss: 0.4859 +2025-06-24 17:33:28,286 - pyskl - INFO - Saving checkpoint at 55 epochs +2025-06-24 17:34:27,623 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:34:27,694 - pyskl - INFO - +top1_acc 0.8621 +top5_acc 0.9906 +2025-06-24 17:34:27,694 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:34:27,704 - pyskl - INFO - +mean_acc 0.8121 +2025-06-24 17:34:27,706 - pyskl - INFO - Epoch(val) [55][533] top1_acc: 0.8621, top5_acc: 0.9906, mean_class_accuracy: 0.8121 +2025-06-24 17:35:48,797 - pyskl - INFO - Epoch [56][100/1281] lr: 1.757e-02, eta: 12:50:52, time: 0.811, data_time: 0.194, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9969, loss_cls: 0.4426, loss: 0.4426 +2025-06-24 17:36:37,995 - pyskl - INFO - Epoch [56][200/1281] lr: 1.755e-02, eta: 12:50:33, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9975, loss_cls: 0.4422, loss: 0.4422 +2025-06-24 17:37:27,112 - pyskl - INFO - Epoch [56][300/1281] lr: 1.753e-02, eta: 12:50:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9969, loss_cls: 0.4371, loss: 0.4371 +2025-06-24 17:38:16,554 - pyskl - INFO - Epoch [56][400/1281] lr: 1.751e-02, eta: 12:49:56, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9981, loss_cls: 0.4269, loss: 0.4269 +2025-06-24 17:39:05,676 - pyskl - INFO - Epoch [56][500/1281] lr: 1.749e-02, eta: 12:49:36, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9969, loss_cls: 0.4017, loss: 0.4017 +2025-06-24 17:39:54,927 - pyskl - INFO - Epoch [56][600/1281] lr: 1.747e-02, eta: 12:49:17, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9988, loss_cls: 0.4302, loss: 0.4302 +2025-06-24 17:40:44,064 - pyskl - INFO - Epoch [56][700/1281] lr: 1.745e-02, eta: 12:48:58, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9981, loss_cls: 0.4388, loss: 0.4388 +2025-06-24 17:41:33,368 - pyskl - INFO - Epoch [56][800/1281] lr: 1.743e-02, eta: 12:48:39, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9956, loss_cls: 0.5378, loss: 0.5378 +2025-06-24 17:42:12,317 - pyskl - INFO - Epoch [56][900/1281] lr: 1.742e-02, eta: 12:48:02, time: 0.389, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9981, loss_cls: 0.4564, loss: 0.4564 +2025-06-24 17:43:03,650 - pyskl - INFO - Epoch [56][1000/1281] lr: 1.740e-02, eta: 12:47:46, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9938, loss_cls: 0.5514, loss: 0.5514 +2025-06-24 17:43:27,556 - pyskl - INFO - Epoch [56][1100/1281] lr: 1.738e-02, eta: 12:46:44, time: 0.239, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9981, loss_cls: 0.4558, loss: 0.4558 +2025-06-24 17:44:12,351 - pyskl - INFO - Epoch [56][1200/1281] lr: 1.736e-02, eta: 12:46:17, time: 0.448, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9962, loss_cls: 0.4223, loss: 0.4223 +2025-06-24 17:44:52,845 - pyskl - INFO - Saving checkpoint at 56 epochs +2025-06-24 17:45:52,212 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:45:52,267 - pyskl - INFO - +top1_acc 0.8747 +top5_acc 0.9917 +2025-06-24 17:45:52,268 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:45:52,275 - pyskl - INFO - +mean_acc 0.8414 +2025-06-24 17:45:52,277 - pyskl - INFO - Epoch(val) [56][533] top1_acc: 0.8747, top5_acc: 0.9917, mean_class_accuracy: 0.8414 +2025-06-24 17:47:13,848 - pyskl - INFO - Epoch [57][100/1281] lr: 1.733e-02, eta: 12:45:29, time: 0.816, data_time: 0.193, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9988, loss_cls: 0.4613, loss: 0.4613 +2025-06-24 17:48:03,282 - pyskl - INFO - Epoch [57][200/1281] lr: 1.731e-02, eta: 12:45:09, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9962, loss_cls: 0.4271, loss: 0.4271 +2025-06-24 17:48:52,474 - pyskl - INFO - Epoch [57][300/1281] lr: 1.729e-02, eta: 12:44:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9988, loss_cls: 0.3820, loss: 0.3820 +2025-06-24 17:49:41,361 - pyskl - INFO - Epoch [57][400/1281] lr: 1.727e-02, eta: 12:44:29, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9975, loss_cls: 0.3918, loss: 0.3918 +2025-06-24 17:50:30,504 - pyskl - INFO - Epoch [57][500/1281] lr: 1.725e-02, eta: 12:44:09, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9950, loss_cls: 0.4686, loss: 0.4686 +2025-06-24 17:51:19,564 - pyskl - INFO - Epoch [57][600/1281] lr: 1.723e-02, eta: 12:43:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9969, loss_cls: 0.4492, loss: 0.4492 +2025-06-24 17:52:09,387 - pyskl - INFO - Epoch [57][700/1281] lr: 1.721e-02, eta: 12:43:29, time: 0.498, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9975, loss_cls: 0.4385, loss: 0.4385 +2025-06-24 17:52:58,754 - pyskl - INFO - Epoch [57][800/1281] lr: 1.719e-02, eta: 12:43:09, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9981, loss_cls: 0.4560, loss: 0.4560 +2025-06-24 17:53:37,084 - pyskl - INFO - Epoch [57][900/1281] lr: 1.717e-02, eta: 12:42:31, time: 0.383, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9956, loss_cls: 0.5014, loss: 0.5014 +2025-06-24 17:54:28,441 - pyskl - INFO - Epoch [57][1000/1281] lr: 1.716e-02, eta: 12:42:14, time: 0.514, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9969, loss_cls: 0.4379, loss: 0.4379 +2025-06-24 17:54:52,454 - pyskl - INFO - Epoch [57][1100/1281] lr: 1.714e-02, eta: 12:41:13, time: 0.240, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9975, loss_cls: 0.4272, loss: 0.4272 +2025-06-24 17:55:36,736 - pyskl - INFO - Epoch [57][1200/1281] lr: 1.712e-02, eta: 12:40:44, time: 0.443, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9969, loss_cls: 0.4505, loss: 0.4505 +2025-06-24 17:56:17,380 - pyskl - INFO - Saving checkpoint at 57 epochs +2025-06-24 17:57:16,854 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:57:16,939 - pyskl - INFO - +top1_acc 0.8806 +top5_acc 0.9930 +2025-06-24 17:57:16,939 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:57:16,948 - pyskl - INFO - +mean_acc 0.8392 +2025-06-24 17:57:16,950 - pyskl - INFO - Epoch(val) [57][533] top1_acc: 0.8806, top5_acc: 0.9930, mean_class_accuracy: 0.8392 +2025-06-24 17:58:35,581 - pyskl - INFO - Epoch [58][100/1281] lr: 1.708e-02, eta: 12:39:50, time: 0.786, data_time: 0.185, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9988, loss_cls: 0.4100, loss: 0.4100 +2025-06-24 17:59:25,032 - pyskl - INFO - Epoch [58][200/1281] lr: 1.706e-02, eta: 12:39:30, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9988, loss_cls: 0.3543, loss: 0.3543 +2025-06-24 18:00:13,939 - pyskl - INFO - Epoch [58][300/1281] lr: 1.704e-02, eta: 12:39:09, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9988, loss_cls: 0.3588, loss: 0.3588 +2025-06-24 18:01:02,955 - pyskl - INFO - Epoch [58][400/1281] lr: 1.703e-02, eta: 12:38:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 1.0000, loss_cls: 0.3603, loss: 0.3603 +2025-06-24 18:01:52,213 - pyskl - INFO - Epoch [58][500/1281] lr: 1.701e-02, eta: 12:38:27, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 0.4071, loss: 0.4071 +2025-06-24 18:02:41,090 - pyskl - INFO - Epoch [58][600/1281] lr: 1.699e-02, eta: 12:38:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9962, loss_cls: 0.4200, loss: 0.4200 +2025-06-24 18:03:30,309 - pyskl - INFO - Epoch [58][700/1281] lr: 1.697e-02, eta: 12:37:45, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 0.4557, loss: 0.4557 +2025-06-24 18:04:19,481 - pyskl - INFO - Epoch [58][800/1281] lr: 1.695e-02, eta: 12:37:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9956, loss_cls: 0.5160, loss: 0.5160 +2025-06-24 18:04:59,964 - pyskl - INFO - Epoch [58][900/1281] lr: 1.693e-02, eta: 12:36:48, time: 0.405, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9981, loss_cls: 0.4487, loss: 0.4487 +2025-06-24 18:05:51,158 - pyskl - INFO - Epoch [58][1000/1281] lr: 1.691e-02, eta: 12:36:30, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9981, loss_cls: 0.4087, loss: 0.4087 +2025-06-24 18:06:14,401 - pyskl - INFO - Epoch [58][1100/1281] lr: 1.689e-02, eta: 12:35:28, time: 0.232, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9981, loss_cls: 0.4548, loss: 0.4548 +2025-06-24 18:06:58,320 - pyskl - INFO - Epoch [58][1200/1281] lr: 1.687e-02, eta: 12:34:58, time: 0.439, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9988, loss_cls: 0.4679, loss: 0.4679 +2025-06-24 18:07:38,800 - pyskl - INFO - Saving checkpoint at 58 epochs +2025-06-24 18:08:38,240 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:08:38,316 - pyskl - INFO - +top1_acc 0.8764 +top5_acc 0.9913 +2025-06-24 18:08:38,316 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:08:38,324 - pyskl - INFO - +mean_acc 0.8410 +2025-06-24 18:08:38,326 - pyskl - INFO - Epoch(val) [58][533] top1_acc: 0.8764, top5_acc: 0.9913, mean_class_accuracy: 0.8410 +2025-06-24 18:09:59,377 - pyskl - INFO - Epoch [59][100/1281] lr: 1.684e-02, eta: 12:34:07, time: 0.810, data_time: 0.193, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9975, loss_cls: 0.4691, loss: 0.4691 +2025-06-24 18:10:48,687 - pyskl - INFO - Epoch [59][200/1281] lr: 1.682e-02, eta: 12:33:46, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9988, loss_cls: 0.4208, loss: 0.4208 +2025-06-24 18:11:37,896 - pyskl - INFO - Epoch [59][300/1281] lr: 1.680e-02, eta: 12:33:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9994, loss_cls: 0.3958, loss: 0.3958 +2025-06-24 18:12:26,932 - pyskl - INFO - Epoch [59][400/1281] lr: 1.678e-02, eta: 12:33:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9950, loss_cls: 0.4287, loss: 0.4287 +2025-06-24 18:13:16,246 - pyskl - INFO - Epoch [59][500/1281] lr: 1.676e-02, eta: 12:32:41, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9969, loss_cls: 0.4424, loss: 0.4424 +2025-06-24 18:14:05,086 - pyskl - INFO - Epoch [59][600/1281] lr: 1.674e-02, eta: 12:32:19, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9988, loss_cls: 0.4264, loss: 0.4264 +2025-06-24 18:14:54,003 - pyskl - INFO - Epoch [59][700/1281] lr: 1.672e-02, eta: 12:31:56, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9994, loss_cls: 0.4355, loss: 0.4355 +2025-06-24 18:15:43,194 - pyskl - INFO - Epoch [59][800/1281] lr: 1.670e-02, eta: 12:31:35, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9994, loss_cls: 0.4210, loss: 0.4210 +2025-06-24 18:16:21,801 - pyskl - INFO - Epoch [59][900/1281] lr: 1.668e-02, eta: 12:30:56, time: 0.386, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9981, loss_cls: 0.4123, loss: 0.4123 +2025-06-24 18:17:12,951 - pyskl - INFO - Epoch [59][1000/1281] lr: 1.667e-02, eta: 12:30:37, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9975, loss_cls: 0.4422, loss: 0.4422 +2025-06-24 18:17:36,789 - pyskl - INFO - Epoch [59][1100/1281] lr: 1.665e-02, eta: 12:29:36, time: 0.238, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9975, loss_cls: 0.4344, loss: 0.4344 +2025-06-24 18:18:22,145 - pyskl - INFO - Epoch [59][1200/1281] lr: 1.663e-02, eta: 12:29:08, time: 0.454, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9969, loss_cls: 0.4765, loss: 0.4765 +2025-06-24 18:19:02,614 - pyskl - INFO - Saving checkpoint at 59 epochs +2025-06-24 18:20:01,710 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:20:01,765 - pyskl - INFO - +top1_acc 0.8729 +top5_acc 0.9914 +2025-06-24 18:20:01,765 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:20:01,771 - pyskl - INFO - +mean_acc 0.8256 +2025-06-24 18:20:01,773 - pyskl - INFO - Epoch(val) [59][533] top1_acc: 0.8729, top5_acc: 0.9914, mean_class_accuracy: 0.8256 +2025-06-24 18:21:22,725 - pyskl - INFO - Epoch [60][100/1281] lr: 1.659e-02, eta: 12:28:15, time: 0.809, data_time: 0.192, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9988, loss_cls: 0.4200, loss: 0.4200 +2025-06-24 18:22:12,045 - pyskl - INFO - Epoch [60][200/1281] lr: 1.657e-02, eta: 12:27:53, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 1.0000, loss_cls: 0.3767, loss: 0.3767 +2025-06-24 18:23:01,099 - pyskl - INFO - Epoch [60][300/1281] lr: 1.655e-02, eta: 12:27:31, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9975, loss_cls: 0.3979, loss: 0.3979 +2025-06-24 18:23:50,266 - pyskl - INFO - Epoch [60][400/1281] lr: 1.653e-02, eta: 12:27:09, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9994, loss_cls: 0.4194, loss: 0.4194 +2025-06-24 18:24:39,873 - pyskl - INFO - Epoch [60][500/1281] lr: 1.651e-02, eta: 12:26:47, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9981, loss_cls: 0.4209, loss: 0.4209 +2025-06-24 18:25:29,230 - pyskl - INFO - Epoch [60][600/1281] lr: 1.650e-02, eta: 12:26:25, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9988, loss_cls: 0.3798, loss: 0.3798 +2025-06-24 18:26:18,564 - pyskl - INFO - Epoch [60][700/1281] lr: 1.648e-02, eta: 12:26:02, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9950, loss_cls: 0.4227, loss: 0.4227 +2025-06-24 18:27:07,703 - pyskl - INFO - Epoch [60][800/1281] lr: 1.646e-02, eta: 12:25:40, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9975, loss_cls: 0.4729, loss: 0.4729 +2025-06-24 18:27:44,766 - pyskl - INFO - Epoch [60][900/1281] lr: 1.644e-02, eta: 12:24:59, time: 0.371, data_time: 0.001, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9969, loss_cls: 0.4177, loss: 0.4177 +2025-06-24 18:28:36,034 - pyskl - INFO - Epoch [60][1000/1281] lr: 1.642e-02, eta: 12:24:39, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9988, loss_cls: 0.4167, loss: 0.4167 +2025-06-24 18:29:00,818 - pyskl - INFO - Epoch [60][1100/1281] lr: 1.640e-02, eta: 12:23:39, time: 0.248, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9975, loss_cls: 0.4256, loss: 0.4256 +2025-06-24 18:29:48,856 - pyskl - INFO - Epoch [60][1200/1281] lr: 1.638e-02, eta: 12:23:15, time: 0.480, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9975, loss_cls: 0.4824, loss: 0.4824 +2025-06-24 18:30:29,040 - pyskl - INFO - Saving checkpoint at 60 epochs +2025-06-24 18:31:29,181 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:31:29,248 - pyskl - INFO - +top1_acc 0.8789 +top5_acc 0.9945 +2025-06-24 18:31:29,248 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:31:29,256 - pyskl - INFO - +mean_acc 0.8296 +2025-06-24 18:31:29,258 - pyskl - INFO - Epoch(val) [60][533] top1_acc: 0.8789, top5_acc: 0.9945, mean_class_accuracy: 0.8296 +2025-06-24 18:32:50,008 - pyskl - INFO - Epoch [61][100/1281] lr: 1.634e-02, eta: 12:22:21, time: 0.807, data_time: 0.195, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9962, loss_cls: 0.4364, loss: 0.4364 +2025-06-24 18:33:39,200 - pyskl - INFO - Epoch [61][200/1281] lr: 1.632e-02, eta: 12:21:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9988, loss_cls: 0.4209, loss: 0.4209 +2025-06-24 18:34:28,580 - pyskl - INFO - Epoch [61][300/1281] lr: 1.630e-02, eta: 12:21:35, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9988, loss_cls: 0.3763, loss: 0.3763 +2025-06-24 18:35:18,011 - pyskl - INFO - Epoch [61][400/1281] lr: 1.629e-02, eta: 12:21:13, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9975, loss_cls: 0.4088, loss: 0.4088 +2025-06-24 18:36:07,227 - pyskl - INFO - Epoch [61][500/1281] lr: 1.627e-02, eta: 12:20:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9969, loss_cls: 0.4224, loss: 0.4224 +2025-06-24 18:36:56,738 - pyskl - INFO - Epoch [61][600/1281] lr: 1.625e-02, eta: 12:20:27, time: 0.495, data_time: 0.001, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9975, loss_cls: 0.3876, loss: 0.3876 +2025-06-24 18:37:45,985 - pyskl - INFO - Epoch [61][700/1281] lr: 1.623e-02, eta: 12:20:04, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9988, loss_cls: 0.4104, loss: 0.4104 +2025-06-24 18:38:35,676 - pyskl - INFO - Epoch [61][800/1281] lr: 1.621e-02, eta: 12:19:41, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9988, loss_cls: 0.4293, loss: 0.4293 +2025-06-24 18:39:07,450 - pyskl - INFO - Epoch [61][900/1281] lr: 1.619e-02, eta: 12:18:52, time: 0.318, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9975, loss_cls: 0.4425, loss: 0.4425 +2025-06-24 18:39:58,719 - pyskl - INFO - Epoch [61][1000/1281] lr: 1.617e-02, eta: 12:18:31, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 0.4093, loss: 0.4093 +2025-06-24 18:40:25,115 - pyskl - INFO - Epoch [61][1100/1281] lr: 1.615e-02, eta: 12:17:35, time: 0.264, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9988, loss_cls: 0.4294, loss: 0.4294 +2025-06-24 18:41:14,777 - pyskl - INFO - Epoch [61][1200/1281] lr: 1.613e-02, eta: 12:17:12, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9981, loss_cls: 0.4186, loss: 0.4186 +2025-06-24 18:41:55,438 - pyskl - INFO - Saving checkpoint at 61 epochs +2025-06-24 18:42:54,817 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:42:54,893 - pyskl - INFO - +top1_acc 0.8680 +top5_acc 0.9899 +2025-06-24 18:42:54,893 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:42:54,901 - pyskl - INFO - +mean_acc 0.8159 +2025-06-24 18:42:54,903 - pyskl - INFO - Epoch(val) [61][533] top1_acc: 0.8680, top5_acc: 0.9899, mean_class_accuracy: 0.8159 +2025-06-24 18:44:14,575 - pyskl - INFO - Epoch [62][100/1281] lr: 1.609e-02, eta: 12:16:15, time: 0.797, data_time: 0.189, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9975, loss_cls: 0.4654, loss: 0.4654 +2025-06-24 18:45:04,186 - pyskl - INFO - Epoch [62][200/1281] lr: 1.607e-02, eta: 12:15:52, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9962, loss_cls: 0.4279, loss: 0.4279 +2025-06-24 18:45:53,317 - pyskl - INFO - Epoch [62][300/1281] lr: 1.605e-02, eta: 12:15:29, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9975, loss_cls: 0.4027, loss: 0.4027 +2025-06-24 18:46:42,339 - pyskl - INFO - Epoch [62][400/1281] lr: 1.603e-02, eta: 12:15:04, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9981, loss_cls: 0.4439, loss: 0.4439 +2025-06-24 18:47:32,005 - pyskl - INFO - Epoch [62][500/1281] lr: 1.602e-02, eta: 12:14:41, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9981, loss_cls: 0.4099, loss: 0.4099 +2025-06-24 18:48:21,057 - pyskl - INFO - Epoch [62][600/1281] lr: 1.600e-02, eta: 12:14:17, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3814, loss: 0.3814 +2025-06-24 18:49:10,003 - pyskl - INFO - Epoch [62][700/1281] lr: 1.598e-02, eta: 12:13:53, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9988, loss_cls: 0.4269, loss: 0.4269 +2025-06-24 18:49:59,445 - pyskl - INFO - Epoch [62][800/1281] lr: 1.596e-02, eta: 12:13:29, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9956, loss_cls: 0.4503, loss: 0.4503 +2025-06-24 18:50:30,757 - pyskl - INFO - Epoch [62][900/1281] lr: 1.594e-02, eta: 12:12:39, time: 0.313, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9981, loss_cls: 0.4103, loss: 0.4103 +2025-06-24 18:51:21,962 - pyskl - INFO - Epoch [62][1000/1281] lr: 1.592e-02, eta: 12:12:18, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9994, loss_cls: 0.4395, loss: 0.4395 +2025-06-24 18:51:48,092 - pyskl - INFO - Epoch [62][1100/1281] lr: 1.590e-02, eta: 12:11:21, time: 0.261, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9969, loss_cls: 0.4422, loss: 0.4422 +2025-06-24 18:52:37,087 - pyskl - INFO - Epoch [62][1200/1281] lr: 1.588e-02, eta: 12:10:57, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9962, loss_cls: 0.4393, loss: 0.4393 +2025-06-24 18:53:17,551 - pyskl - INFO - Saving checkpoint at 62 epochs +2025-06-24 18:54:17,065 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:54:17,139 - pyskl - INFO - +top1_acc 0.8860 +top5_acc 0.9920 +2025-06-24 18:54:17,139 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:54:17,154 - pyskl - INFO - +mean_acc 0.8510 +2025-06-24 18:54:17,157 - pyskl - INFO - Epoch(val) [62][533] top1_acc: 0.8860, top5_acc: 0.9920, mean_class_accuracy: 0.8510 +2025-06-24 18:55:38,069 - pyskl - INFO - Epoch [63][100/1281] lr: 1.584e-02, eta: 12:10:01, time: 0.809, data_time: 0.195, memory: 4083, top1_acc: 0.9181, top5_acc: 1.0000, loss_cls: 0.4000, loss: 0.4000 +2025-06-24 18:56:27,551 - pyskl - INFO - Epoch [63][200/1281] lr: 1.582e-02, eta: 12:09:37, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9969, loss_cls: 0.4009, loss: 0.4009 +2025-06-24 18:57:16,594 - pyskl - INFO - Epoch [63][300/1281] lr: 1.580e-02, eta: 12:09:13, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9981, loss_cls: 0.3685, loss: 0.3685 +2025-06-24 18:58:06,030 - pyskl - INFO - Epoch [63][400/1281] lr: 1.578e-02, eta: 12:08:49, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9975, loss_cls: 0.4118, loss: 0.4118 +2025-06-24 18:58:55,243 - pyskl - INFO - Epoch [63][500/1281] lr: 1.576e-02, eta: 12:08:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 0.3681, loss: 0.3681 +2025-06-24 18:59:44,527 - pyskl - INFO - Epoch [63][600/1281] lr: 1.574e-02, eta: 12:08:00, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 0.3074, loss: 0.3074 +2025-06-24 19:00:33,427 - pyskl - INFO - Epoch [63][700/1281] lr: 1.572e-02, eta: 12:07:35, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9994, loss_cls: 0.3763, loss: 0.3763 +2025-06-24 19:01:22,576 - pyskl - INFO - Epoch [63][800/1281] lr: 1.570e-02, eta: 12:07:10, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9994, loss_cls: 0.3771, loss: 0.3771 +2025-06-24 19:01:53,052 - pyskl - INFO - Epoch [63][900/1281] lr: 1.568e-02, eta: 12:06:19, time: 0.305, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9975, loss_cls: 0.4314, loss: 0.4314 +2025-06-24 19:02:44,138 - pyskl - INFO - Epoch [63][1000/1281] lr: 1.566e-02, eta: 12:05:57, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9962, loss_cls: 0.4909, loss: 0.4909 +2025-06-24 19:03:13,748 - pyskl - INFO - Epoch [63][1100/1281] lr: 1.564e-02, eta: 12:05:05, time: 0.296, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9988, loss_cls: 0.3877, loss: 0.3877 +2025-06-24 19:04:03,287 - pyskl - INFO - Epoch [63][1200/1281] lr: 1.562e-02, eta: 12:04:41, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9944, loss_cls: 0.4346, loss: 0.4346 +2025-06-24 19:04:43,825 - pyskl - INFO - Saving checkpoint at 63 epochs +2025-06-24 19:05:43,591 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:05:43,661 - pyskl - INFO - +top1_acc 0.9034 +top5_acc 0.9953 +2025-06-24 19:05:43,661 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:05:43,670 - pyskl - INFO - +mean_acc 0.8616 +2025-06-24 19:05:43,675 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_51.pth was removed +2025-06-24 19:05:44,159 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_63.pth. +2025-06-24 19:05:44,160 - pyskl - INFO - Best top1_acc is 0.9034 at 63 epoch. +2025-06-24 19:05:44,163 - pyskl - INFO - Epoch(val) [63][533] top1_acc: 0.9034, top5_acc: 0.9953, mean_class_accuracy: 0.8616 +2025-06-24 19:07:05,994 - pyskl - INFO - Epoch [64][100/1281] lr: 1.559e-02, eta: 12:03:46, time: 0.818, data_time: 0.197, memory: 4083, top1_acc: 0.9369, top5_acc: 1.0000, loss_cls: 0.3317, loss: 0.3317 +2025-06-24 19:07:55,446 - pyskl - INFO - Epoch [64][200/1281] lr: 1.557e-02, eta: 12:03:21, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9981, loss_cls: 0.4077, loss: 0.4077 +2025-06-24 19:08:44,564 - pyskl - INFO - Epoch [64][300/1281] lr: 1.555e-02, eta: 12:02:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9994, loss_cls: 0.3571, loss: 0.3571 +2025-06-24 19:09:33,776 - pyskl - INFO - Epoch [64][400/1281] lr: 1.553e-02, eta: 12:02:31, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9981, loss_cls: 0.3473, loss: 0.3473 +2025-06-24 19:10:23,347 - pyskl - INFO - Epoch [64][500/1281] lr: 1.551e-02, eta: 12:02:06, time: 0.496, data_time: 0.001, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9981, loss_cls: 0.4070, loss: 0.4070 +2025-06-24 19:11:12,947 - pyskl - INFO - Epoch [64][600/1281] lr: 1.549e-02, eta: 12:01:41, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9981, loss_cls: 0.3704, loss: 0.3704 +2025-06-24 19:12:02,065 - pyskl - INFO - Epoch [64][700/1281] lr: 1.547e-02, eta: 12:01:16, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9981, loss_cls: 0.4025, loss: 0.4025 +2025-06-24 19:12:51,575 - pyskl - INFO - Epoch [64][800/1281] lr: 1.545e-02, eta: 12:00:51, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9981, loss_cls: 0.4299, loss: 0.4299 +2025-06-24 19:13:20,358 - pyskl - INFO - Epoch [64][900/1281] lr: 1.543e-02, eta: 11:59:58, time: 0.288, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9962, loss_cls: 0.3988, loss: 0.3988 +2025-06-24 19:14:08,385 - pyskl - INFO - Epoch [64][1000/1281] lr: 1.541e-02, eta: 11:59:31, time: 0.480, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9956, loss_cls: 0.3657, loss: 0.3657 +2025-06-24 19:14:41,910 - pyskl - INFO - Epoch [64][1100/1281] lr: 1.539e-02, eta: 11:58:44, time: 0.335, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9981, loss_cls: 0.4554, loss: 0.4554 +2025-06-24 19:15:31,221 - pyskl - INFO - Epoch [64][1200/1281] lr: 1.537e-02, eta: 11:58:19, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9969, loss_cls: 0.4574, loss: 0.4574 +2025-06-24 19:16:11,519 - pyskl - INFO - Saving checkpoint at 64 epochs +2025-06-24 19:17:10,899 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:17:10,956 - pyskl - INFO - +top1_acc 0.8804 +top5_acc 0.9933 +2025-06-24 19:17:10,957 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:17:10,963 - pyskl - INFO - +mean_acc 0.8546 +2025-06-24 19:17:10,965 - pyskl - INFO - Epoch(val) [64][533] top1_acc: 0.8804, top5_acc: 0.9933, mean_class_accuracy: 0.8546 +2025-06-24 19:18:31,861 - pyskl - INFO - Epoch [65][100/1281] lr: 1.533e-02, eta: 11:57:22, time: 0.809, data_time: 0.192, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9988, loss_cls: 0.3494, loss: 0.3494 +2025-06-24 19:19:21,170 - pyskl - INFO - Epoch [65][200/1281] lr: 1.531e-02, eta: 11:56:56, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9994, loss_cls: 0.4057, loss: 0.4057 +2025-06-24 19:20:10,420 - pyskl - INFO - Epoch [65][300/1281] lr: 1.529e-02, eta: 11:56:31, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9994, loss_cls: 0.3658, loss: 0.3658 +2025-06-24 19:20:59,599 - pyskl - INFO - Epoch [65][400/1281] lr: 1.527e-02, eta: 11:56:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 1.0000, loss_cls: 0.3239, loss: 0.3239 +2025-06-24 19:21:48,799 - pyskl - INFO - Epoch [65][500/1281] lr: 1.526e-02, eta: 11:55:39, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9975, loss_cls: 0.3747, loss: 0.3747 +2025-06-24 19:22:37,875 - pyskl - INFO - Epoch [65][600/1281] lr: 1.524e-02, eta: 11:55:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9994, loss_cls: 0.3863, loss: 0.3863 +2025-06-24 19:23:27,394 - pyskl - INFO - Epoch [65][700/1281] lr: 1.522e-02, eta: 11:54:48, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9975, loss_cls: 0.4143, loss: 0.4143 +2025-06-24 19:24:16,373 - pyskl - INFO - Epoch [65][800/1281] lr: 1.520e-02, eta: 11:54:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9975, loss_cls: 0.4529, loss: 0.4529 +2025-06-24 19:24:48,246 - pyskl - INFO - Epoch [65][900/1281] lr: 1.518e-02, eta: 11:53:33, time: 0.319, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9981, loss_cls: 0.3744, loss: 0.3744 +2025-06-24 19:25:31,134 - pyskl - INFO - Epoch [65][1000/1281] lr: 1.516e-02, eta: 11:52:59, time: 0.429, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9981, loss_cls: 0.4212, loss: 0.4212 +2025-06-24 19:26:08,208 - pyskl - INFO - Epoch [65][1100/1281] lr: 1.514e-02, eta: 11:52:17, time: 0.371, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9981, loss_cls: 0.3853, loss: 0.3853 +2025-06-24 19:26:57,432 - pyskl - INFO - Epoch [65][1200/1281] lr: 1.512e-02, eta: 11:51:51, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9994, loss_cls: 0.3954, loss: 0.3954 +2025-06-24 19:27:38,125 - pyskl - INFO - Saving checkpoint at 65 epochs +2025-06-24 19:28:37,385 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:28:37,445 - pyskl - INFO - +top1_acc 0.8984 +top5_acc 0.9942 +2025-06-24 19:28:37,445 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:28:37,452 - pyskl - INFO - +mean_acc 0.8633 +2025-06-24 19:28:37,454 - pyskl - INFO - Epoch(val) [65][533] top1_acc: 0.8984, top5_acc: 0.9942, mean_class_accuracy: 0.8633 +2025-06-24 19:29:58,203 - pyskl - INFO - Epoch [66][100/1281] lr: 1.508e-02, eta: 11:50:52, time: 0.807, data_time: 0.198, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9994, loss_cls: 0.3540, loss: 0.3540 +2025-06-24 19:30:47,507 - pyskl - INFO - Epoch [66][200/1281] lr: 1.506e-02, eta: 11:50:26, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9988, loss_cls: 0.3489, loss: 0.3489 +2025-06-24 19:31:36,718 - pyskl - INFO - Epoch [66][300/1281] lr: 1.504e-02, eta: 11:50:00, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9988, loss_cls: 0.3377, loss: 0.3377 +2025-06-24 19:32:25,875 - pyskl - INFO - Epoch [66][400/1281] lr: 1.502e-02, eta: 11:49:34, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9988, loss_cls: 0.3825, loss: 0.3825 +2025-06-24 19:33:15,184 - pyskl - INFO - Epoch [66][500/1281] lr: 1.500e-02, eta: 11:49:07, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 1.0000, loss_cls: 0.4298, loss: 0.4298 +2025-06-24 19:34:04,326 - pyskl - INFO - Epoch [66][600/1281] lr: 1.498e-02, eta: 11:48:41, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 1.0000, loss_cls: 0.4075, loss: 0.4075 +2025-06-24 19:34:53,296 - pyskl - INFO - Epoch [66][700/1281] lr: 1.496e-02, eta: 11:48:14, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9988, loss_cls: 0.3834, loss: 0.3834 +2025-06-24 19:35:39,140 - pyskl - INFO - Epoch [66][800/1281] lr: 1.494e-02, eta: 11:47:43, time: 0.458, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9988, loss_cls: 0.4458, loss: 0.4458 +2025-06-24 19:36:19,285 - pyskl - INFO - Epoch [66][900/1281] lr: 1.492e-02, eta: 11:47:05, time: 0.401, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9969, loss_cls: 0.4053, loss: 0.4053 +2025-06-24 19:36:53,311 - pyskl - INFO - Epoch [66][1000/1281] lr: 1.490e-02, eta: 11:46:19, time: 0.340, data_time: 0.001, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9975, loss_cls: 0.4394, loss: 0.4394 +2025-06-24 19:37:33,331 - pyskl - INFO - Epoch [66][1100/1281] lr: 1.488e-02, eta: 11:45:41, time: 0.400, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9975, loss_cls: 0.4061, loss: 0.4061 +2025-06-24 19:38:22,621 - pyskl - INFO - Epoch [66][1200/1281] lr: 1.486e-02, eta: 11:45:14, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9981, loss_cls: 0.4053, loss: 0.4053 +2025-06-24 19:39:03,066 - pyskl - INFO - Saving checkpoint at 66 epochs +2025-06-24 19:40:02,169 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:40:02,284 - pyskl - INFO - +top1_acc 0.8751 +top5_acc 0.9918 +2025-06-24 19:40:02,284 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:40:02,293 - pyskl - INFO - +mean_acc 0.8305 +2025-06-24 19:40:02,295 - pyskl - INFO - Epoch(val) [66][533] top1_acc: 0.8751, top5_acc: 0.9918, mean_class_accuracy: 0.8305 +2025-06-24 19:41:23,660 - pyskl - INFO - Epoch [67][100/1281] lr: 1.482e-02, eta: 11:44:16, time: 0.814, data_time: 0.192, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9988, loss_cls: 0.4228, loss: 0.4228 +2025-06-24 19:42:12,777 - pyskl - INFO - Epoch [67][200/1281] lr: 1.480e-02, eta: 11:43:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 1.0000, loss_cls: 0.3530, loss: 0.3530 +2025-06-24 19:43:01,886 - pyskl - INFO - Epoch [67][300/1281] lr: 1.478e-02, eta: 11:43:22, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9994, loss_cls: 0.3476, loss: 0.3476 +2025-06-24 19:43:51,134 - pyskl - INFO - Epoch [67][400/1281] lr: 1.476e-02, eta: 11:42:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9981, loss_cls: 0.3614, loss: 0.3614 +2025-06-24 19:44:40,606 - pyskl - INFO - Epoch [67][500/1281] lr: 1.474e-02, eta: 11:42:29, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9981, loss_cls: 0.4123, loss: 0.4123 +2025-06-24 19:45:29,930 - pyskl - INFO - Epoch [67][600/1281] lr: 1.472e-02, eta: 11:42:02, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9975, loss_cls: 0.4219, loss: 0.4219 +2025-06-24 19:46:19,672 - pyskl - INFO - Epoch [67][700/1281] lr: 1.470e-02, eta: 11:41:36, time: 0.497, data_time: 0.001, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9975, loss_cls: 0.3795, loss: 0.3795 +2025-06-24 19:47:03,673 - pyskl - INFO - Epoch [67][800/1281] lr: 1.468e-02, eta: 11:41:02, time: 0.440, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 1.0000, loss_cls: 0.3995, loss: 0.3995 +2025-06-24 19:47:45,945 - pyskl - INFO - Epoch [67][900/1281] lr: 1.466e-02, eta: 11:40:26, time: 0.423, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9988, loss_cls: 0.3816, loss: 0.3816 +2025-06-24 19:48:17,400 - pyskl - INFO - Epoch [67][1000/1281] lr: 1.464e-02, eta: 11:39:37, time: 0.315, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9988, loss_cls: 0.4092, loss: 0.4092 +2025-06-24 19:48:58,457 - pyskl - INFO - Epoch [67][1100/1281] lr: 1.462e-02, eta: 11:39:00, time: 0.411, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9962, loss_cls: 0.4242, loss: 0.4242 +2025-06-24 19:49:47,355 - pyskl - INFO - Epoch [67][1200/1281] lr: 1.460e-02, eta: 11:38:32, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 1.0000, loss_cls: 0.4121, loss: 0.4121 +2025-06-24 19:50:27,639 - pyskl - INFO - Saving checkpoint at 67 epochs +2025-06-24 19:51:27,455 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:51:27,510 - pyskl - INFO - +top1_acc 0.8857 +top5_acc 0.9941 +2025-06-24 19:51:27,510 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:51:27,517 - pyskl - INFO - +mean_acc 0.8439 +2025-06-24 19:51:27,519 - pyskl - INFO - Epoch(val) [67][533] top1_acc: 0.8857, top5_acc: 0.9941, mean_class_accuracy: 0.8439 +2025-06-24 19:52:46,637 - pyskl - INFO - Epoch [68][100/1281] lr: 1.456e-02, eta: 11:37:31, time: 0.791, data_time: 0.184, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9994, loss_cls: 0.3461, loss: 0.3461 +2025-06-24 19:53:36,144 - pyskl - INFO - Epoch [68][200/1281] lr: 1.454e-02, eta: 11:37:04, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9969, loss_cls: 0.3445, loss: 0.3445 +2025-06-24 19:54:25,425 - pyskl - INFO - Epoch [68][300/1281] lr: 1.452e-02, eta: 11:36:36, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9994, loss_cls: 0.3646, loss: 0.3646 +2025-06-24 19:55:14,733 - pyskl - INFO - Epoch [68][400/1281] lr: 1.450e-02, eta: 11:36:09, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9981, loss_cls: 0.4177, loss: 0.4177 +2025-06-24 19:56:03,889 - pyskl - INFO - Epoch [68][500/1281] lr: 1.448e-02, eta: 11:35:42, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9950, loss_cls: 0.3681, loss: 0.3681 +2025-06-24 19:56:53,484 - pyskl - INFO - Epoch [68][600/1281] lr: 1.446e-02, eta: 11:35:15, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9994, loss_cls: 0.3546, loss: 0.3546 +2025-06-24 19:57:42,794 - pyskl - INFO - Epoch [68][700/1281] lr: 1.444e-02, eta: 11:34:47, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9981, loss_cls: 0.3559, loss: 0.3559 +2025-06-24 19:58:25,818 - pyskl - INFO - Epoch [68][800/1281] lr: 1.442e-02, eta: 11:34:12, time: 0.430, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9988, loss_cls: 0.3643, loss: 0.3643 +2025-06-24 19:59:11,643 - pyskl - INFO - Epoch [68][900/1281] lr: 1.440e-02, eta: 11:33:40, time: 0.458, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9988, loss_cls: 0.3738, loss: 0.3738 +2025-06-24 19:59:39,432 - pyskl - INFO - Epoch [68][1000/1281] lr: 1.438e-02, eta: 11:32:47, time: 0.278, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9981, loss_cls: 0.4244, loss: 0.4244 +2025-06-24 20:00:21,307 - pyskl - INFO - Epoch [68][1100/1281] lr: 1.436e-02, eta: 11:32:10, time: 0.419, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9994, loss_cls: 0.3720, loss: 0.3720 +2025-06-24 20:01:10,498 - pyskl - INFO - Epoch [68][1200/1281] lr: 1.434e-02, eta: 11:31:42, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9988, loss_cls: 0.3907, loss: 0.3907 +2025-06-24 20:01:51,052 - pyskl - INFO - Saving checkpoint at 68 epochs +2025-06-24 20:02:50,807 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:02:50,881 - pyskl - INFO - +top1_acc 0.8791 +top5_acc 0.9916 +2025-06-24 20:02:50,881 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:02:50,889 - pyskl - INFO - +mean_acc 0.8416 +2025-06-24 20:02:50,891 - pyskl - INFO - Epoch(val) [68][533] top1_acc: 0.8791, top5_acc: 0.9916, mean_class_accuracy: 0.8416 +2025-06-24 20:04:09,379 - pyskl - INFO - Epoch [69][100/1281] lr: 1.431e-02, eta: 11:30:39, time: 0.785, data_time: 0.187, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9994, loss_cls: 0.3781, loss: 0.3781 +2025-06-24 20:04:58,477 - pyskl - INFO - Epoch [69][200/1281] lr: 1.429e-02, eta: 11:30:11, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9994, loss_cls: 0.3415, loss: 0.3415 +2025-06-24 20:05:47,735 - pyskl - INFO - Epoch [69][300/1281] lr: 1.427e-02, eta: 11:29:44, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.2956, loss: 0.2956 +2025-06-24 20:06:36,752 - pyskl - INFO - Epoch [69][400/1281] lr: 1.425e-02, eta: 11:29:15, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9969, loss_cls: 0.4104, loss: 0.4104 +2025-06-24 20:07:25,931 - pyskl - INFO - Epoch [69][500/1281] lr: 1.423e-02, eta: 11:28:47, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9988, loss_cls: 0.3920, loss: 0.3920 +2025-06-24 20:08:15,503 - pyskl - INFO - Epoch [69][600/1281] lr: 1.420e-02, eta: 11:28:20, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9969, loss_cls: 0.4117, loss: 0.4117 +2025-06-24 20:09:04,964 - pyskl - INFO - Epoch [69][700/1281] lr: 1.418e-02, eta: 11:27:52, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9975, loss_cls: 0.3725, loss: 0.3725 +2025-06-24 20:09:48,111 - pyskl - INFO - Epoch [69][800/1281] lr: 1.416e-02, eta: 11:27:17, time: 0.431, data_time: 0.001, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9975, loss_cls: 0.3570, loss: 0.3570 +2025-06-24 20:10:33,283 - pyskl - INFO - Epoch [69][900/1281] lr: 1.414e-02, eta: 11:26:44, time: 0.452, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9988, loss_cls: 0.3715, loss: 0.3715 +2025-06-24 20:11:02,434 - pyskl - INFO - Epoch [69][1000/1281] lr: 1.412e-02, eta: 11:25:52, time: 0.292, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 0.3517, loss: 0.3517 +2025-06-24 20:11:46,472 - pyskl - INFO - Epoch [69][1100/1281] lr: 1.410e-02, eta: 11:25:18, time: 0.440, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9975, loss_cls: 0.3461, loss: 0.3461 +2025-06-24 20:12:35,611 - pyskl - INFO - Epoch [69][1200/1281] lr: 1.408e-02, eta: 11:24:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9988, loss_cls: 0.3865, loss: 0.3865 +2025-06-24 20:13:16,292 - pyskl - INFO - Saving checkpoint at 69 epochs +2025-06-24 20:14:15,783 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:14:15,852 - pyskl - INFO - +top1_acc 0.8933 +top5_acc 0.9939 +2025-06-24 20:14:15,852 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:14:15,859 - pyskl - INFO - +mean_acc 0.8548 +2025-06-24 20:14:15,861 - pyskl - INFO - Epoch(val) [69][533] top1_acc: 0.8933, top5_acc: 0.9939, mean_class_accuracy: 0.8548 +2025-06-24 20:15:35,204 - pyskl - INFO - Epoch [70][100/1281] lr: 1.405e-02, eta: 11:23:47, time: 0.793, data_time: 0.192, memory: 4083, top1_acc: 0.9381, top5_acc: 1.0000, loss_cls: 0.3518, loss: 0.3518 +2025-06-24 20:16:24,421 - pyskl - INFO - Epoch [70][200/1281] lr: 1.403e-02, eta: 11:23:19, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9975, loss_cls: 0.3435, loss: 0.3435 +2025-06-24 20:17:13,502 - pyskl - INFO - Epoch [70][300/1281] lr: 1.401e-02, eta: 11:22:50, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9962, loss_cls: 0.3921, loss: 0.3921 +2025-06-24 20:18:02,528 - pyskl - INFO - Epoch [70][400/1281] lr: 1.399e-02, eta: 11:22:21, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 1.0000, loss_cls: 0.3288, loss: 0.3288 +2025-06-24 20:18:51,862 - pyskl - INFO - Epoch [70][500/1281] lr: 1.397e-02, eta: 11:21:53, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 1.0000, loss_cls: 0.3127, loss: 0.3127 +2025-06-24 20:19:41,084 - pyskl - INFO - Epoch [70][600/1281] lr: 1.395e-02, eta: 11:21:25, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9981, loss_cls: 0.3912, loss: 0.3912 +2025-06-24 20:20:30,256 - pyskl - INFO - Epoch [70][700/1281] lr: 1.392e-02, eta: 11:20:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9962, loss_cls: 0.3799, loss: 0.3799 +2025-06-24 20:21:11,149 - pyskl - INFO - Epoch [70][800/1281] lr: 1.390e-02, eta: 11:20:18, time: 0.409, data_time: 0.001, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9981, loss_cls: 0.3843, loss: 0.3843 +2025-06-24 20:22:01,702 - pyskl - INFO - Epoch [70][900/1281] lr: 1.388e-02, eta: 11:19:51, time: 0.506, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9988, loss_cls: 0.4246, loss: 0.4246 +2025-06-24 20:22:25,895 - pyskl - INFO - Epoch [70][1000/1281] lr: 1.386e-02, eta: 11:18:53, time: 0.242, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9956, loss_cls: 0.4063, loss: 0.4063 +2025-06-24 20:23:09,106 - pyskl - INFO - Epoch [70][1100/1281] lr: 1.384e-02, eta: 11:18:18, time: 0.432, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9988, loss_cls: 0.4071, loss: 0.4071 +2025-06-24 20:23:58,401 - pyskl - INFO - Epoch [70][1200/1281] lr: 1.382e-02, eta: 11:17:49, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9988, loss_cls: 0.4413, loss: 0.4413 +2025-06-24 20:24:38,614 - pyskl - INFO - Saving checkpoint at 70 epochs +2025-06-24 20:25:38,018 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:25:38,078 - pyskl - INFO - +top1_acc 0.8973 +top5_acc 0.9951 +2025-06-24 20:25:38,078 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:25:38,085 - pyskl - INFO - +mean_acc 0.8663 +2025-06-24 20:25:38,087 - pyskl - INFO - Epoch(val) [70][533] top1_acc: 0.8973, top5_acc: 0.9951, mean_class_accuracy: 0.8663 +2025-06-24 20:26:58,922 - pyskl - INFO - Epoch [71][100/1281] lr: 1.379e-02, eta: 11:16:48, time: 0.808, data_time: 0.194, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9994, loss_cls: 0.2817, loss: 0.2817 +2025-06-24 20:27:48,216 - pyskl - INFO - Epoch [71][200/1281] lr: 1.377e-02, eta: 11:16:19, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 0.2896, loss: 0.2896 +2025-06-24 20:28:37,397 - pyskl - INFO - Epoch [71][300/1281] lr: 1.375e-02, eta: 11:15:50, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9981, loss_cls: 0.2882, loss: 0.2882 +2025-06-24 20:29:26,723 - pyskl - INFO - Epoch [71][400/1281] lr: 1.373e-02, eta: 11:15:21, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9988, loss_cls: 0.3402, loss: 0.3402 +2025-06-24 20:30:16,049 - pyskl - INFO - Epoch [71][500/1281] lr: 1.371e-02, eta: 11:14:53, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9994, loss_cls: 0.4087, loss: 0.4087 +2025-06-24 20:31:05,289 - pyskl - INFO - Epoch [71][600/1281] lr: 1.368e-02, eta: 11:14:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9988, loss_cls: 0.3625, loss: 0.3625 +2025-06-24 20:31:54,606 - pyskl - INFO - Epoch [71][700/1281] lr: 1.366e-02, eta: 11:13:55, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9988, loss_cls: 0.3604, loss: 0.3604 +2025-06-24 20:32:33,898 - pyskl - INFO - Epoch [71][800/1281] lr: 1.364e-02, eta: 11:13:14, time: 0.393, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 1.0000, loss_cls: 0.3506, loss: 0.3506 +2025-06-24 20:33:25,220 - pyskl - INFO - Epoch [71][900/1281] lr: 1.362e-02, eta: 11:12:48, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9994, loss_cls: 0.3587, loss: 0.3587 +2025-06-24 20:33:48,880 - pyskl - INFO - Epoch [71][1000/1281] lr: 1.360e-02, eta: 11:11:50, time: 0.237, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9994, loss_cls: 0.3554, loss: 0.3554 +2025-06-24 20:34:33,653 - pyskl - INFO - Epoch [71][1100/1281] lr: 1.358e-02, eta: 11:11:16, time: 0.448, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9981, loss_cls: 0.3434, loss: 0.3434 +2025-06-24 20:35:22,877 - pyskl - INFO - Epoch [71][1200/1281] lr: 1.356e-02, eta: 11:10:47, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9981, loss_cls: 0.3510, loss: 0.3510 +2025-06-24 20:36:03,273 - pyskl - INFO - Saving checkpoint at 71 epochs +2025-06-24 20:37:03,725 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:37:03,796 - pyskl - INFO - +top1_acc 0.8751 +top5_acc 0.9933 +2025-06-24 20:37:03,797 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:37:03,809 - pyskl - INFO - +mean_acc 0.8294 +2025-06-24 20:37:03,811 - pyskl - INFO - Epoch(val) [71][533] top1_acc: 0.8751, top5_acc: 0.9933, mean_class_accuracy: 0.8294 +2025-06-24 20:38:23,851 - pyskl - INFO - Epoch [72][100/1281] lr: 1.353e-02, eta: 11:09:44, time: 0.800, data_time: 0.195, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9981, loss_cls: 0.3348, loss: 0.3348 +2025-06-24 20:39:13,259 - pyskl - INFO - Epoch [72][200/1281] lr: 1.351e-02, eta: 11:09:15, time: 0.494, data_time: 0.001, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9988, loss_cls: 0.3023, loss: 0.3023 +2025-06-24 20:40:02,293 - pyskl - INFO - Epoch [72][300/1281] lr: 1.349e-02, eta: 11:08:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9975, loss_cls: 0.3242, loss: 0.3242 +2025-06-24 20:40:51,834 - pyskl - INFO - Epoch [72][400/1281] lr: 1.346e-02, eta: 11:08:16, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9956, loss_cls: 0.3019, loss: 0.3019 +2025-06-24 20:41:40,946 - pyskl - INFO - Epoch [72][500/1281] lr: 1.344e-02, eta: 11:07:47, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 1.0000, loss_cls: 0.3144, loss: 0.3144 +2025-06-24 20:42:30,342 - pyskl - INFO - Epoch [72][600/1281] lr: 1.342e-02, eta: 11:07:18, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9988, loss_cls: 0.4043, loss: 0.4043 +2025-06-24 20:43:19,595 - pyskl - INFO - Epoch [72][700/1281] lr: 1.340e-02, eta: 11:06:48, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9994, loss_cls: 0.3367, loss: 0.3367 +2025-06-24 20:43:56,833 - pyskl - INFO - Epoch [72][800/1281] lr: 1.338e-02, eta: 11:06:06, time: 0.372, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9969, loss_cls: 0.4090, loss: 0.4090 +2025-06-24 20:44:48,096 - pyskl - INFO - Epoch [72][900/1281] lr: 1.336e-02, eta: 11:05:38, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9988, loss_cls: 0.3626, loss: 0.3626 +2025-06-24 20:45:12,526 - pyskl - INFO - Epoch [72][1000/1281] lr: 1.334e-02, eta: 11:04:42, time: 0.244, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 1.0000, loss_cls: 0.3446, loss: 0.3446 +2025-06-24 20:45:59,002 - pyskl - INFO - Epoch [72][1100/1281] lr: 1.332e-02, eta: 11:04:09, time: 0.465, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9994, loss_cls: 0.3606, loss: 0.3606 +2025-06-24 20:46:48,196 - pyskl - INFO - Epoch [72][1200/1281] lr: 1.330e-02, eta: 11:03:39, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9975, loss_cls: 0.3836, loss: 0.3836 +2025-06-24 20:47:28,685 - pyskl - INFO - Saving checkpoint at 72 epochs +2025-06-24 20:48:28,037 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:48:28,098 - pyskl - INFO - +top1_acc 0.9039 +top5_acc 0.9958 +2025-06-24 20:48:28,098 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:48:28,106 - pyskl - INFO - +mean_acc 0.8683 +2025-06-24 20:48:28,110 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_63.pth was removed +2025-06-24 20:48:28,282 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_72.pth. +2025-06-24 20:48:28,283 - pyskl - INFO - Best top1_acc is 0.9039 at 72 epoch. +2025-06-24 20:48:28,286 - pyskl - INFO - Epoch(val) [72][533] top1_acc: 0.9039, top5_acc: 0.9958, mean_class_accuracy: 0.8683 +2025-06-24 20:49:48,780 - pyskl - INFO - Epoch [73][100/1281] lr: 1.326e-02, eta: 11:02:36, time: 0.805, data_time: 0.194, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 0.3295, loss: 0.3295 +2025-06-24 20:50:37,853 - pyskl - INFO - Epoch [73][200/1281] lr: 1.324e-02, eta: 11:02:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 0.2743, loss: 0.2743 +2025-06-24 20:51:27,093 - pyskl - INFO - Epoch [73][300/1281] lr: 1.322e-02, eta: 11:01:37, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 0.9981, loss_cls: 0.3372, loss: 0.3372 +2025-06-24 20:52:16,083 - pyskl - INFO - Epoch [73][400/1281] lr: 1.320e-02, eta: 11:01:07, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9981, loss_cls: 0.2732, loss: 0.2732 +2025-06-24 20:53:05,178 - pyskl - INFO - Epoch [73][500/1281] lr: 1.318e-02, eta: 11:00:37, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 0.3430, loss: 0.3430 +2025-06-24 20:53:54,266 - pyskl - INFO - Epoch [73][600/1281] lr: 1.316e-02, eta: 11:00:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 1.0000, loss_cls: 0.3251, loss: 0.3251 +2025-06-24 20:54:43,448 - pyskl - INFO - Epoch [73][700/1281] lr: 1.314e-02, eta: 10:59:37, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9981, loss_cls: 0.3349, loss: 0.3349 +2025-06-24 20:55:17,944 - pyskl - INFO - Epoch [73][800/1281] lr: 1.312e-02, eta: 10:58:51, time: 0.345, data_time: 0.001, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9988, loss_cls: 0.3759, loss: 0.3759 +2025-06-24 20:56:09,244 - pyskl - INFO - Epoch [73][900/1281] lr: 1.310e-02, eta: 10:58:24, time: 0.513, data_time: 0.001, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9981, loss_cls: 0.3665, loss: 0.3665 +2025-06-24 20:56:34,514 - pyskl - INFO - Epoch [73][1000/1281] lr: 1.308e-02, eta: 10:57:28, time: 0.253, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9981, loss_cls: 0.3650, loss: 0.3650 +2025-06-24 20:57:23,646 - pyskl - INFO - Epoch [73][1100/1281] lr: 1.306e-02, eta: 10:56:58, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9969, loss_cls: 0.3738, loss: 0.3738 +2025-06-24 20:58:12,741 - pyskl - INFO - Epoch [73][1200/1281] lr: 1.304e-02, eta: 10:56:28, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9975, loss_cls: 0.3863, loss: 0.3863 +2025-06-24 20:58:53,461 - pyskl - INFO - Saving checkpoint at 73 epochs +2025-06-24 20:59:53,006 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:59:53,061 - pyskl - INFO - +top1_acc 0.8953 +top5_acc 0.9946 +2025-06-24 20:59:53,062 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:59:53,068 - pyskl - INFO - +mean_acc 0.8689 +2025-06-24 20:59:53,070 - pyskl - INFO - Epoch(val) [73][533] top1_acc: 0.8953, top5_acc: 0.9946, mean_class_accuracy: 0.8689 +2025-06-24 21:01:13,108 - pyskl - INFO - Epoch [74][100/1281] lr: 1.300e-02, eta: 10:55:24, time: 0.800, data_time: 0.193, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9981, loss_cls: 0.2976, loss: 0.2976 +2025-06-24 21:02:02,522 - pyskl - INFO - Epoch [74][200/1281] lr: 1.298e-02, eta: 10:54:54, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9994, loss_cls: 0.3266, loss: 0.3266 +2025-06-24 21:02:51,730 - pyskl - INFO - Epoch [74][300/1281] lr: 1.296e-02, eta: 10:54:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 1.0000, loss_cls: 0.3123, loss: 0.3123 +2025-06-24 21:03:41,097 - pyskl - INFO - Epoch [74][400/1281] lr: 1.294e-02, eta: 10:53:54, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9988, loss_cls: 0.3056, loss: 0.3056 +2025-06-24 21:04:30,087 - pyskl - INFO - Epoch [74][500/1281] lr: 1.292e-02, eta: 10:53:23, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 0.9988, loss_cls: 0.2981, loss: 0.2981 +2025-06-24 21:05:19,081 - pyskl - INFO - Epoch [74][600/1281] lr: 1.290e-02, eta: 10:52:53, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 1.0000, loss_cls: 0.3113, loss: 0.3113 +2025-06-24 21:06:08,590 - pyskl - INFO - Epoch [74][700/1281] lr: 1.288e-02, eta: 10:52:23, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9988, loss_cls: 0.3663, loss: 0.3663 +2025-06-24 21:06:40,208 - pyskl - INFO - Epoch [74][800/1281] lr: 1.286e-02, eta: 10:51:34, time: 0.316, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9994, loss_cls: 0.3553, loss: 0.3553 +2025-06-24 21:07:31,436 - pyskl - INFO - Epoch [74][900/1281] lr: 1.284e-02, eta: 10:51:06, time: 0.512, data_time: 0.001, memory: 4083, top1_acc: 0.9225, top5_acc: 1.0000, loss_cls: 0.3984, loss: 0.3984 +2025-06-24 21:07:59,738 - pyskl - INFO - Epoch [74][1000/1281] lr: 1.282e-02, eta: 10:50:14, time: 0.283, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9994, loss_cls: 0.3416, loss: 0.3416 +2025-06-24 21:08:49,029 - pyskl - INFO - Epoch [74][1100/1281] lr: 1.280e-02, eta: 10:49:43, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9981, loss_cls: 0.3928, loss: 0.3928 +2025-06-24 21:09:38,600 - pyskl - INFO - Epoch [74][1200/1281] lr: 1.278e-02, eta: 10:49:13, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9975, loss_cls: 0.3437, loss: 0.3437 +2025-06-24 21:10:19,027 - pyskl - INFO - Saving checkpoint at 74 epochs +2025-06-24 21:11:18,117 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:11:18,185 - pyskl - INFO - +top1_acc 0.8903 +top5_acc 0.9937 +2025-06-24 21:11:18,185 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:11:18,195 - pyskl - INFO - +mean_acc 0.8461 +2025-06-24 21:11:18,197 - pyskl - INFO - Epoch(val) [74][533] top1_acc: 0.8903, top5_acc: 0.9937, mean_class_accuracy: 0.8461 +2025-06-24 21:12:36,912 - pyskl - INFO - Epoch [75][100/1281] lr: 1.274e-02, eta: 10:48:07, time: 0.787, data_time: 0.190, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9981, loss_cls: 0.3185, loss: 0.3185 +2025-06-24 21:13:25,874 - pyskl - INFO - Epoch [75][200/1281] lr: 1.272e-02, eta: 10:47:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2606, loss: 0.2606 +2025-06-24 21:14:15,197 - pyskl - INFO - Epoch [75][300/1281] lr: 1.270e-02, eta: 10:47:06, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3307, loss: 0.3307 +2025-06-24 21:15:04,385 - pyskl - INFO - Epoch [75][400/1281] lr: 1.268e-02, eta: 10:46:36, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9975, loss_cls: 0.3674, loss: 0.3674 +2025-06-24 21:15:53,740 - pyskl - INFO - Epoch [75][500/1281] lr: 1.266e-02, eta: 10:46:05, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9975, loss_cls: 0.3587, loss: 0.3587 +2025-06-24 21:16:43,260 - pyskl - INFO - Epoch [75][600/1281] lr: 1.264e-02, eta: 10:45:35, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9988, loss_cls: 0.3194, loss: 0.3194 +2025-06-24 21:17:32,511 - pyskl - INFO - Epoch [75][700/1281] lr: 1.262e-02, eta: 10:45:04, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 0.3205, loss: 0.3205 +2025-06-24 21:18:03,003 - pyskl - INFO - Epoch [75][800/1281] lr: 1.260e-02, eta: 10:44:14, time: 0.305, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 1.0000, loss_cls: 0.3290, loss: 0.3290 +2025-06-24 21:18:54,071 - pyskl - INFO - Epoch [75][900/1281] lr: 1.258e-02, eta: 10:43:45, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9975, loss_cls: 0.3729, loss: 0.3729 +2025-06-24 21:19:22,134 - pyskl - INFO - Epoch [75][1000/1281] lr: 1.256e-02, eta: 10:42:53, time: 0.281, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 1.0000, loss_cls: 0.3460, loss: 0.3460 +2025-06-24 21:20:11,964 - pyskl - INFO - Epoch [75][1100/1281] lr: 1.254e-02, eta: 10:42:23, time: 0.498, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9994, loss_cls: 0.4146, loss: 0.4146 +2025-06-24 21:21:01,238 - pyskl - INFO - Epoch [75][1200/1281] lr: 1.252e-02, eta: 10:41:52, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9994, loss_cls: 0.3725, loss: 0.3725 +2025-06-24 21:21:41,791 - pyskl - INFO - Saving checkpoint at 75 epochs +2025-06-24 21:22:41,561 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:22:41,622 - pyskl - INFO - +top1_acc 0.8910 +top5_acc 0.9945 +2025-06-24 21:22:41,622 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:22:41,637 - pyskl - INFO - +mean_acc 0.8606 +2025-06-24 21:22:41,641 - pyskl - INFO - Epoch(val) [75][533] top1_acc: 0.8910, top5_acc: 0.9945, mean_class_accuracy: 0.8606 +2025-06-24 21:24:01,875 - pyskl - INFO - Epoch [76][100/1281] lr: 1.248e-02, eta: 10:40:47, time: 0.802, data_time: 0.197, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9988, loss_cls: 0.3113, loss: 0.3113 +2025-06-24 21:24:50,740 - pyskl - INFO - Epoch [76][200/1281] lr: 1.246e-02, eta: 10:40:16, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9994, loss_cls: 0.3501, loss: 0.3501 +2025-06-24 21:25:39,788 - pyskl - INFO - Epoch [76][300/1281] lr: 1.244e-02, eta: 10:39:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 1.0000, loss_cls: 0.2936, loss: 0.2936 +2025-06-24 21:26:29,038 - pyskl - INFO - Epoch [76][400/1281] lr: 1.242e-02, eta: 10:39:14, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9988, loss_cls: 0.2941, loss: 0.2941 +2025-06-24 21:27:18,135 - pyskl - INFO - Epoch [76][500/1281] lr: 1.240e-02, eta: 10:38:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9988, loss_cls: 0.3786, loss: 0.3786 +2025-06-24 21:28:07,617 - pyskl - INFO - Epoch [76][600/1281] lr: 1.238e-02, eta: 10:38:12, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9981, loss_cls: 0.3251, loss: 0.3251 +2025-06-24 21:28:56,965 - pyskl - INFO - Epoch [76][700/1281] lr: 1.236e-02, eta: 10:37:41, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9994, loss_cls: 0.3384, loss: 0.3384 +2025-06-24 21:29:25,693 - pyskl - INFO - Epoch [76][800/1281] lr: 1.234e-02, eta: 10:36:50, time: 0.287, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9994, loss_cls: 0.3581, loss: 0.3581 +2025-06-24 21:30:16,821 - pyskl - INFO - Epoch [76][900/1281] lr: 1.232e-02, eta: 10:36:20, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9994, loss_cls: 0.3271, loss: 0.3271 +2025-06-24 21:30:46,485 - pyskl - INFO - Epoch [76][1000/1281] lr: 1.230e-02, eta: 10:35:30, time: 0.297, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 1.0000, loss_cls: 0.3504, loss: 0.3504 +2025-06-24 21:31:35,676 - pyskl - INFO - Epoch [76][1100/1281] lr: 1.228e-02, eta: 10:34:59, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 0.3095, loss: 0.3095 +2025-06-24 21:32:24,894 - pyskl - INFO - Epoch [76][1200/1281] lr: 1.225e-02, eta: 10:34:28, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9994, loss_cls: 0.3671, loss: 0.3671 +2025-06-24 21:33:05,378 - pyskl - INFO - Saving checkpoint at 76 epochs +2025-06-24 21:34:05,433 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:34:05,488 - pyskl - INFO - +top1_acc 0.9045 +top5_acc 0.9959 +2025-06-24 21:34:05,488 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:34:05,495 - pyskl - INFO - +mean_acc 0.8796 +2025-06-24 21:34:05,499 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_72.pth was removed +2025-06-24 21:34:05,673 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_76.pth. +2025-06-24 21:34:05,673 - pyskl - INFO - Best top1_acc is 0.9045 at 76 epoch. +2025-06-24 21:34:05,675 - pyskl - INFO - Epoch(val) [76][533] top1_acc: 0.9045, top5_acc: 0.9959, mean_class_accuracy: 0.8796 +2025-06-24 21:35:25,961 - pyskl - INFO - Epoch [77][100/1281] lr: 1.222e-02, eta: 10:33:22, time: 0.803, data_time: 0.197, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2484, loss: 0.2484 +2025-06-24 21:36:15,136 - pyskl - INFO - Epoch [77][200/1281] lr: 1.220e-02, eta: 10:32:51, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2652, loss: 0.2652 +2025-06-24 21:37:04,329 - pyskl - INFO - Epoch [77][300/1281] lr: 1.218e-02, eta: 10:32:20, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9994, loss_cls: 0.3319, loss: 0.3319 +2025-06-24 21:37:53,213 - pyskl - INFO - Epoch [77][400/1281] lr: 1.216e-02, eta: 10:31:48, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9981, loss_cls: 0.2772, loss: 0.2772 +2025-06-24 21:38:42,531 - pyskl - INFO - Epoch [77][500/1281] lr: 1.214e-02, eta: 10:31:17, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 1.0000, loss_cls: 0.3481, loss: 0.3481 +2025-06-24 21:39:31,773 - pyskl - INFO - Epoch [77][600/1281] lr: 1.212e-02, eta: 10:30:45, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 0.3101, loss: 0.3101 +2025-06-24 21:40:21,048 - pyskl - INFO - Epoch [77][700/1281] lr: 1.210e-02, eta: 10:30:14, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9981, loss_cls: 0.3129, loss: 0.3129 +2025-06-24 21:40:49,201 - pyskl - INFO - Epoch [77][800/1281] lr: 1.207e-02, eta: 10:29:22, time: 0.282, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9969, loss_cls: 0.4039, loss: 0.4039 +2025-06-24 21:41:38,176 - pyskl - INFO - Epoch [77][900/1281] lr: 1.205e-02, eta: 10:28:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9981, loss_cls: 0.3855, loss: 0.3855 +2025-06-24 21:42:10,628 - pyskl - INFO - Epoch [77][1000/1281] lr: 1.203e-02, eta: 10:28:03, time: 0.325, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 0.3776, loss: 0.3776 +2025-06-24 21:42:59,884 - pyskl - INFO - Epoch [77][1100/1281] lr: 1.201e-02, eta: 10:27:31, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9994, loss_cls: 0.3446, loss: 0.3446 +2025-06-24 21:43:49,001 - pyskl - INFO - Epoch [77][1200/1281] lr: 1.199e-02, eta: 10:26:59, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9975, loss_cls: 0.3809, loss: 0.3809 +2025-06-24 21:44:29,576 - pyskl - INFO - Saving checkpoint at 77 epochs +2025-06-24 21:45:29,086 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:45:29,143 - pyskl - INFO - +top1_acc 0.9013 +top5_acc 0.9953 +2025-06-24 21:45:29,144 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:45:29,151 - pyskl - INFO - +mean_acc 0.8595 +2025-06-24 21:45:29,153 - pyskl - INFO - Epoch(val) [77][533] top1_acc: 0.9013, top5_acc: 0.9953, mean_class_accuracy: 0.8595 +2025-06-24 21:46:49,209 - pyskl - INFO - Epoch [78][100/1281] lr: 1.196e-02, eta: 10:25:54, time: 0.801, data_time: 0.197, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9988, loss_cls: 0.2729, loss: 0.2729 +2025-06-24 21:47:38,553 - pyskl - INFO - Epoch [78][200/1281] lr: 1.194e-02, eta: 10:25:22, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9988, loss_cls: 0.3453, loss: 0.3453 +2025-06-24 21:48:27,639 - pyskl - INFO - Epoch [78][300/1281] lr: 1.192e-02, eta: 10:24:50, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9988, loss_cls: 0.3354, loss: 0.3354 +2025-06-24 21:49:17,079 - pyskl - INFO - Epoch [78][400/1281] lr: 1.190e-02, eta: 10:24:19, time: 0.494, data_time: 0.001, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9994, loss_cls: 0.2850, loss: 0.2850 +2025-06-24 21:50:06,294 - pyskl - INFO - Epoch [78][500/1281] lr: 1.187e-02, eta: 10:23:47, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9988, loss_cls: 0.3048, loss: 0.3048 +2025-06-24 21:50:55,441 - pyskl - INFO - Epoch [78][600/1281] lr: 1.185e-02, eta: 10:23:15, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.3060, loss: 0.3060 +2025-06-24 21:51:44,700 - pyskl - INFO - Epoch [78][700/1281] lr: 1.183e-02, eta: 10:22:43, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 1.0000, loss_cls: 0.2781, loss: 0.2781 +2025-06-24 21:52:15,430 - pyskl - INFO - Epoch [78][800/1281] lr: 1.181e-02, eta: 10:21:54, time: 0.307, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9988, loss_cls: 0.3375, loss: 0.3375 +2025-06-24 21:52:59,560 - pyskl - INFO - Epoch [78][900/1281] lr: 1.179e-02, eta: 10:21:17, time: 0.441, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9981, loss_cls: 0.3646, loss: 0.3646 +2025-06-24 21:53:35,174 - pyskl - INFO - Epoch [78][1000/1281] lr: 1.177e-02, eta: 10:20:33, time: 0.356, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9988, loss_cls: 0.2756, loss: 0.2756 +2025-06-24 21:54:24,130 - pyskl - INFO - Epoch [78][1100/1281] lr: 1.175e-02, eta: 10:20:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9981, loss_cls: 0.3079, loss: 0.3079 +2025-06-24 21:55:13,325 - pyskl - INFO - Epoch [78][1200/1281] lr: 1.173e-02, eta: 10:19:29, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9988, loss_cls: 0.3170, loss: 0.3170 +2025-06-24 21:55:53,687 - pyskl - INFO - Saving checkpoint at 78 epochs +2025-06-24 21:56:53,570 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:56:53,628 - pyskl - INFO - +top1_acc 0.9008 +top5_acc 0.9947 +2025-06-24 21:56:53,628 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:56:53,635 - pyskl - INFO - +mean_acc 0.8704 +2025-06-24 21:56:53,637 - pyskl - INFO - Epoch(val) [78][533] top1_acc: 0.9008, top5_acc: 0.9947, mean_class_accuracy: 0.8704 +2025-06-24 21:58:14,409 - pyskl - INFO - Epoch [79][100/1281] lr: 1.169e-02, eta: 10:18:23, time: 0.808, data_time: 0.193, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 0.3030, loss: 0.3030 +2025-06-24 21:59:03,750 - pyskl - INFO - Epoch [79][200/1281] lr: 1.167e-02, eta: 10:17:51, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2508, loss: 0.2508 +2025-06-24 21:59:53,129 - pyskl - INFO - Epoch [79][300/1281] lr: 1.165e-02, eta: 10:17:19, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9988, loss_cls: 0.2677, loss: 0.2677 +2025-06-24 22:00:42,337 - pyskl - INFO - Epoch [79][400/1281] lr: 1.163e-02, eta: 10:16:47, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9988, loss_cls: 0.2610, loss: 0.2610 +2025-06-24 22:01:31,391 - pyskl - INFO - Epoch [79][500/1281] lr: 1.161e-02, eta: 10:16:15, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9988, loss_cls: 0.2837, loss: 0.2837 +2025-06-24 22:02:20,964 - pyskl - INFO - Epoch [79][600/1281] lr: 1.159e-02, eta: 10:15:43, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 0.9994, loss_cls: 0.3192, loss: 0.3192 +2025-06-24 22:03:08,147 - pyskl - INFO - Epoch [79][700/1281] lr: 1.157e-02, eta: 10:15:09, time: 0.472, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 0.3416, loss: 0.3416 +2025-06-24 22:03:46,584 - pyskl - INFO - Epoch [79][800/1281] lr: 1.155e-02, eta: 10:14:27, time: 0.384, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 0.9988, loss_cls: 0.3174, loss: 0.3174 +2025-06-24 22:04:22,303 - pyskl - INFO - Epoch [79][900/1281] lr: 1.153e-02, eta: 10:13:42, time: 0.357, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 1.0000, loss_cls: 0.3155, loss: 0.3155 +2025-06-24 22:05:01,546 - pyskl - INFO - Epoch [79][1000/1281] lr: 1.151e-02, eta: 10:13:01, time: 0.392, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 0.2766, loss: 0.2766 +2025-06-24 22:05:50,831 - pyskl - INFO - Epoch [79][1100/1281] lr: 1.149e-02, eta: 10:12:29, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 1.0000, loss_cls: 0.3311, loss: 0.3311 +2025-06-24 22:06:40,566 - pyskl - INFO - Epoch [79][1200/1281] lr: 1.147e-02, eta: 10:11:57, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 0.3120, loss: 0.3120 +2025-06-24 22:07:20,910 - pyskl - INFO - Saving checkpoint at 79 epochs +2025-06-24 22:08:20,708 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:08:20,762 - pyskl - INFO - +top1_acc 0.8890 +top5_acc 0.9942 +2025-06-24 22:08:20,763 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:08:20,769 - pyskl - INFO - +mean_acc 0.8503 +2025-06-24 22:08:20,771 - pyskl - INFO - Epoch(val) [79][533] top1_acc: 0.8890, top5_acc: 0.9942, mean_class_accuracy: 0.8503 +2025-06-24 22:09:41,101 - pyskl - INFO - Epoch [80][100/1281] lr: 1.143e-02, eta: 10:10:50, time: 0.803, data_time: 0.192, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2693, loss: 0.2693 +2025-06-24 22:10:30,083 - pyskl - INFO - Epoch [80][200/1281] lr: 1.141e-02, eta: 10:10:18, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9988, loss_cls: 0.2329, loss: 0.2329 +2025-06-24 22:11:19,292 - pyskl - INFO - Epoch [80][300/1281] lr: 1.139e-02, eta: 10:09:45, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9988, loss_cls: 0.2734, loss: 0.2734 +2025-06-24 22:12:08,291 - pyskl - INFO - Epoch [80][400/1281] lr: 1.137e-02, eta: 10:09:13, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9981, loss_cls: 0.2778, loss: 0.2778 +2025-06-24 22:12:57,463 - pyskl - INFO - Epoch [80][500/1281] lr: 1.135e-02, eta: 10:08:40, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 0.2930, loss: 0.2930 +2025-06-24 22:13:46,638 - pyskl - INFO - Epoch [80][600/1281] lr: 1.133e-02, eta: 10:08:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9981, loss_cls: 0.2594, loss: 0.2594 +2025-06-24 22:14:31,349 - pyskl - INFO - Epoch [80][700/1281] lr: 1.131e-02, eta: 10:07:31, time: 0.447, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9981, loss_cls: 0.3466, loss: 0.3466 +2025-06-24 22:15:14,929 - pyskl - INFO - Epoch [80][800/1281] lr: 1.129e-02, eta: 10:06:53, time: 0.436, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 0.2994, loss: 0.2994 +2025-06-24 22:15:44,939 - pyskl - INFO - Epoch [80][900/1281] lr: 1.127e-02, eta: 10:06:04, time: 0.300, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9988, loss_cls: 0.3463, loss: 0.3463 +2025-06-24 22:16:26,999 - pyskl - INFO - Epoch [80][1000/1281] lr: 1.125e-02, eta: 10:05:25, time: 0.421, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9994, loss_cls: 0.3496, loss: 0.3496 +2025-06-24 22:17:16,188 - pyskl - INFO - Epoch [80][1100/1281] lr: 1.123e-02, eta: 10:04:52, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9988, loss_cls: 0.3720, loss: 0.3720 +2025-06-24 22:18:05,407 - pyskl - INFO - Epoch [80][1200/1281] lr: 1.121e-02, eta: 10:04:20, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9981, loss_cls: 0.3911, loss: 0.3911 +2025-06-24 22:18:45,782 - pyskl - INFO - Saving checkpoint at 80 epochs +2025-06-24 22:19:44,749 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:19:44,818 - pyskl - INFO - +top1_acc 0.8904 +top5_acc 0.9923 +2025-06-24 22:19:44,818 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:19:44,827 - pyskl - INFO - +mean_acc 0.8600 +2025-06-24 22:19:44,829 - pyskl - INFO - Epoch(val) [80][533] top1_acc: 0.8904, top5_acc: 0.9923, mean_class_accuracy: 0.8600 +2025-06-24 22:21:06,296 - pyskl - INFO - Epoch [81][100/1281] lr: 1.117e-02, eta: 10:03:14, time: 0.815, data_time: 0.196, memory: 4083, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 0.2279, loss: 0.2279 +2025-06-24 22:21:55,285 - pyskl - INFO - Epoch [81][200/1281] lr: 1.115e-02, eta: 10:02:41, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 0.2927, loss: 0.2927 +2025-06-24 22:22:44,643 - pyskl - INFO - Epoch [81][300/1281] lr: 1.113e-02, eta: 10:02:08, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9994, loss_cls: 0.3722, loss: 0.3722 +2025-06-24 22:23:33,800 - pyskl - INFO - Epoch [81][400/1281] lr: 1.111e-02, eta: 10:01:35, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9988, loss_cls: 0.3274, loss: 0.3274 +2025-06-24 22:24:23,050 - pyskl - INFO - Epoch [81][500/1281] lr: 1.109e-02, eta: 10:01:03, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2864, loss: 0.2864 +2025-06-24 22:25:12,430 - pyskl - INFO - Epoch [81][600/1281] lr: 1.107e-02, eta: 10:00:30, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 0.9994, loss_cls: 0.3002, loss: 0.3002 +2025-06-24 22:25:54,246 - pyskl - INFO - Epoch [81][700/1281] lr: 1.105e-02, eta: 9:59:51, time: 0.418, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9994, loss_cls: 0.3061, loss: 0.3061 +2025-06-24 22:26:40,878 - pyskl - INFO - Epoch [81][800/1281] lr: 1.103e-02, eta: 9:59:15, time: 0.466, data_time: 0.001, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9956, loss_cls: 0.3160, loss: 0.3160 +2025-06-24 22:27:08,187 - pyskl - INFO - Epoch [81][900/1281] lr: 1.101e-02, eta: 9:58:24, time: 0.273, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9981, loss_cls: 0.3561, loss: 0.3561 +2025-06-24 22:27:50,519 - pyskl - INFO - Epoch [81][1000/1281] lr: 1.099e-02, eta: 9:57:45, time: 0.423, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 1.0000, loss_cls: 0.2856, loss: 0.2856 +2025-06-24 22:28:39,745 - pyskl - INFO - Epoch [81][1100/1281] lr: 1.097e-02, eta: 9:57:12, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 0.2716, loss: 0.2716 +2025-06-24 22:29:28,974 - pyskl - INFO - Epoch [81][1200/1281] lr: 1.095e-02, eta: 9:56:39, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9981, loss_cls: 0.2680, loss: 0.2680 +2025-06-24 22:30:09,630 - pyskl - INFO - Saving checkpoint at 81 epochs +2025-06-24 22:31:09,388 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:31:09,461 - pyskl - INFO - +top1_acc 0.8951 +top5_acc 0.9957 +2025-06-24 22:31:09,461 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:31:09,468 - pyskl - INFO - +mean_acc 0.8680 +2025-06-24 22:31:09,470 - pyskl - INFO - Epoch(val) [81][533] top1_acc: 0.8951, top5_acc: 0.9957, mean_class_accuracy: 0.8680 +2025-06-24 22:32:29,623 - pyskl - INFO - Epoch [82][100/1281] lr: 1.091e-02, eta: 9:55:32, time: 0.801, data_time: 0.201, memory: 4083, top1_acc: 0.9437, top5_acc: 1.0000, loss_cls: 0.2954, loss: 0.2954 +2025-06-24 22:33:18,906 - pyskl - INFO - Epoch [82][200/1281] lr: 1.089e-02, eta: 9:54:59, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2280, loss: 0.2280 +2025-06-24 22:34:07,968 - pyskl - INFO - Epoch [82][300/1281] lr: 1.087e-02, eta: 9:54:25, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 1.0000, loss_cls: 0.2606, loss: 0.2606 +2025-06-24 22:34:57,144 - pyskl - INFO - Epoch [82][400/1281] lr: 1.085e-02, eta: 9:53:52, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 1.0000, loss_cls: 0.2897, loss: 0.2897 +2025-06-24 22:35:46,552 - pyskl - INFO - Epoch [82][500/1281] lr: 1.083e-02, eta: 9:53:19, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9981, loss_cls: 0.2919, loss: 0.2919 +2025-06-24 22:36:35,939 - pyskl - INFO - Epoch [82][600/1281] lr: 1.081e-02, eta: 9:52:46, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9962, loss_cls: 0.3408, loss: 0.3408 +2025-06-24 22:37:16,703 - pyskl - INFO - Epoch [82][700/1281] lr: 1.079e-02, eta: 9:52:06, time: 0.408, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 0.3032, loss: 0.3032 +2025-06-24 22:38:06,160 - pyskl - INFO - Epoch [82][800/1281] lr: 1.077e-02, eta: 9:51:33, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 0.9981, loss_cls: 0.2496, loss: 0.2496 +2025-06-24 22:38:31,172 - pyskl - INFO - Epoch [82][900/1281] lr: 1.075e-02, eta: 9:50:39, time: 0.250, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9981, loss_cls: 0.3115, loss: 0.3115 +2025-06-24 22:39:14,508 - pyskl - INFO - Epoch [82][1000/1281] lr: 1.073e-02, eta: 9:50:01, time: 0.433, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9994, loss_cls: 0.3245, loss: 0.3245 +2025-06-24 22:40:03,805 - pyskl - INFO - Epoch [82][1100/1281] lr: 1.071e-02, eta: 9:49:28, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2742, loss: 0.2742 +2025-06-24 22:40:53,364 - pyskl - INFO - Epoch [82][1200/1281] lr: 1.069e-02, eta: 9:48:55, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 0.2479, loss: 0.2479 +2025-06-24 22:41:33,540 - pyskl - INFO - Saving checkpoint at 82 epochs +2025-06-24 22:42:33,001 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:42:33,058 - pyskl - INFO - +top1_acc 0.8972 +top5_acc 0.9931 +2025-06-24 22:42:33,059 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:42:33,065 - pyskl - INFO - +mean_acc 0.8691 +2025-06-24 22:42:33,067 - pyskl - INFO - Epoch(val) [82][533] top1_acc: 0.8972, top5_acc: 0.9931, mean_class_accuracy: 0.8691 +2025-06-24 22:43:54,410 - pyskl - INFO - Epoch [83][100/1281] lr: 1.065e-02, eta: 9:47:48, time: 0.813, data_time: 0.199, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2511, loss: 0.2511 +2025-06-24 22:44:43,504 - pyskl - INFO - Epoch [83][200/1281] lr: 1.063e-02, eta: 9:47:15, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 0.2495, loss: 0.2495 +2025-06-24 22:45:32,729 - pyskl - INFO - Epoch [83][300/1281] lr: 1.061e-02, eta: 9:46:41, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 1.0000, loss_cls: 0.2795, loss: 0.2795 +2025-06-24 22:46:22,252 - pyskl - INFO - Epoch [83][400/1281] lr: 1.059e-02, eta: 9:46:08, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9981, loss_cls: 0.2644, loss: 0.2644 +2025-06-24 22:47:11,513 - pyskl - INFO - Epoch [83][500/1281] lr: 1.057e-02, eta: 9:45:35, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2788, loss: 0.2788 +2025-06-24 22:48:00,692 - pyskl - INFO - Epoch [83][600/1281] lr: 1.055e-02, eta: 9:45:01, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 1.0000, loss_cls: 0.2892, loss: 0.2892 +2025-06-24 22:48:39,756 - pyskl - INFO - Epoch [83][700/1281] lr: 1.053e-02, eta: 9:44:19, time: 0.391, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 0.2816, loss: 0.2816 +2025-06-24 22:49:30,867 - pyskl - INFO - Epoch [83][800/1281] lr: 1.051e-02, eta: 9:43:48, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9988, loss_cls: 0.2567, loss: 0.2567 +2025-06-24 22:49:54,861 - pyskl - INFO - Epoch [83][900/1281] lr: 1.049e-02, eta: 9:42:53, time: 0.240, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 1.0000, loss_cls: 0.2947, loss: 0.2947 +2025-06-24 22:50:40,406 - pyskl - INFO - Epoch [83][1000/1281] lr: 1.047e-02, eta: 9:42:17, time: 0.455, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9975, loss_cls: 0.2629, loss: 0.2629 +2025-06-24 22:51:29,437 - pyskl - INFO - Epoch [83][1100/1281] lr: 1.045e-02, eta: 9:41:43, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 0.2848, loss: 0.2848 +2025-06-24 22:52:18,656 - pyskl - INFO - Epoch [83][1200/1281] lr: 1.043e-02, eta: 9:41:10, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9988, loss_cls: 0.3111, loss: 0.3111 +2025-06-24 22:52:59,275 - pyskl - INFO - Saving checkpoint at 83 epochs +2025-06-24 22:53:58,667 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:53:58,722 - pyskl - INFO - +top1_acc 0.9004 +top5_acc 0.9940 +2025-06-24 22:53:58,722 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:53:58,728 - pyskl - INFO - +mean_acc 0.8597 +2025-06-24 22:53:58,730 - pyskl - INFO - Epoch(val) [83][533] top1_acc: 0.9004, top5_acc: 0.9940, mean_class_accuracy: 0.8597 +2025-06-24 22:55:20,258 - pyskl - INFO - Epoch [84][100/1281] lr: 1.040e-02, eta: 9:40:03, time: 0.815, data_time: 0.199, memory: 4083, top1_acc: 0.9494, top5_acc: 1.0000, loss_cls: 0.2871, loss: 0.2871 +2025-06-24 22:56:09,381 - pyskl - INFO - Epoch [84][200/1281] lr: 1.038e-02, eta: 9:39:29, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 1.0000, loss_cls: 0.2648, loss: 0.2648 +2025-06-24 22:56:58,500 - pyskl - INFO - Epoch [84][300/1281] lr: 1.036e-02, eta: 9:38:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 0.2543, loss: 0.2543 +2025-06-24 22:57:48,109 - pyskl - INFO - Epoch [84][400/1281] lr: 1.034e-02, eta: 9:38:22, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9975, loss_cls: 0.2681, loss: 0.2681 +2025-06-24 22:58:37,263 - pyskl - INFO - Epoch [84][500/1281] lr: 1.031e-02, eta: 9:37:48, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.2745, loss: 0.2745 +2025-06-24 22:59:26,398 - pyskl - INFO - Epoch [84][600/1281] lr: 1.029e-02, eta: 9:37:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 0.2870, loss: 0.2870 +2025-06-24 23:00:02,156 - pyskl - INFO - Epoch [84][700/1281] lr: 1.027e-02, eta: 9:36:29, time: 0.358, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9994, loss_cls: 0.3586, loss: 0.3586 +2025-06-24 23:00:53,331 - pyskl - INFO - Epoch [84][800/1281] lr: 1.025e-02, eta: 9:35:57, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9988, loss_cls: 0.3127, loss: 0.3127 +2025-06-24 23:01:18,602 - pyskl - INFO - Epoch [84][900/1281] lr: 1.023e-02, eta: 9:35:04, time: 0.253, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 0.3030, loss: 0.3030 +2025-06-24 23:02:06,651 - pyskl - INFO - Epoch [84][1000/1281] lr: 1.021e-02, eta: 9:34:30, time: 0.480, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 0.2209, loss: 0.2209 +2025-06-24 23:02:55,976 - pyskl - INFO - Epoch [84][1100/1281] lr: 1.019e-02, eta: 9:33:56, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 1.0000, loss_cls: 0.3375, loss: 0.3375 +2025-06-24 23:03:45,149 - pyskl - INFO - Epoch [84][1200/1281] lr: 1.017e-02, eta: 9:33:22, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2604, loss: 0.2604 +2025-06-24 23:04:25,937 - pyskl - INFO - Saving checkpoint at 84 epochs +2025-06-24 23:05:25,874 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:05:25,935 - pyskl - INFO - +top1_acc 0.8961 +top5_acc 0.9942 +2025-06-24 23:05:25,936 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:05:25,942 - pyskl - INFO - +mean_acc 0.8818 +2025-06-24 23:05:25,944 - pyskl - INFO - Epoch(val) [84][533] top1_acc: 0.8961, top5_acc: 0.9942, mean_class_accuracy: 0.8818 +2025-06-24 23:06:45,301 - pyskl - INFO - Epoch [85][100/1281] lr: 1.014e-02, eta: 9:32:13, time: 0.794, data_time: 0.188, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9988, loss_cls: 0.2854, loss: 0.2854 +2025-06-24 23:07:34,448 - pyskl - INFO - Epoch [85][200/1281] lr: 1.012e-02, eta: 9:31:39, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 0.9994, loss_cls: 0.2357, loss: 0.2357 +2025-06-24 23:08:23,670 - pyskl - INFO - Epoch [85][300/1281] lr: 1.010e-02, eta: 9:31:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2386, loss: 0.2386 +2025-06-24 23:09:12,679 - pyskl - INFO - Epoch [85][400/1281] lr: 1.008e-02, eta: 9:30:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2180, loss: 0.2180 +2025-06-24 23:10:02,090 - pyskl - INFO - Epoch [85][500/1281] lr: 1.006e-02, eta: 9:29:57, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9994, loss_cls: 0.2395, loss: 0.2395 +2025-06-24 23:10:51,625 - pyskl - INFO - Epoch [85][600/1281] lr: 1.004e-02, eta: 9:29:23, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 1.0000, loss_cls: 0.3047, loss: 0.3047 +2025-06-24 23:11:24,653 - pyskl - INFO - Epoch [85][700/1281] lr: 1.002e-02, eta: 9:28:36, time: 0.330, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 1.0000, loss_cls: 0.2959, loss: 0.2959 +2025-06-24 23:12:15,750 - pyskl - INFO - Epoch [85][800/1281] lr: 9.998e-03, eta: 9:28:04, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9981, loss_cls: 0.2748, loss: 0.2748 +2025-06-24 23:12:42,971 - pyskl - INFO - Epoch [85][900/1281] lr: 9.978e-03, eta: 9:27:13, time: 0.272, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 0.9994, loss_cls: 0.2182, loss: 0.2182 +2025-06-24 23:13:32,340 - pyskl - INFO - Epoch [85][1000/1281] lr: 9.958e-03, eta: 9:26:39, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 1.0000, loss_cls: 0.2446, loss: 0.2446 +2025-06-24 23:14:21,417 - pyskl - INFO - Epoch [85][1100/1281] lr: 9.937e-03, eta: 9:26:04, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9988, loss_cls: 0.2437, loss: 0.2437 +2025-06-24 23:15:10,818 - pyskl - INFO - Epoch [85][1200/1281] lr: 9.917e-03, eta: 9:25:30, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9994, loss_cls: 0.2762, loss: 0.2762 +2025-06-24 23:15:51,094 - pyskl - INFO - Saving checkpoint at 85 epochs +2025-06-24 23:16:50,807 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:16:50,879 - pyskl - INFO - +top1_acc 0.8983 +top5_acc 0.9953 +2025-06-24 23:16:50,879 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:16:50,888 - pyskl - INFO - +mean_acc 0.8726 +2025-06-24 23:16:50,891 - pyskl - INFO - Epoch(val) [85][533] top1_acc: 0.8983, top5_acc: 0.9953, mean_class_accuracy: 0.8726 +2025-06-24 23:18:11,624 - pyskl - INFO - Epoch [86][100/1281] lr: 9.881e-03, eta: 9:24:22, time: 0.807, data_time: 0.196, memory: 4083, top1_acc: 0.9650, top5_acc: 0.9975, loss_cls: 0.2351, loss: 0.2351 +2025-06-24 23:19:00,912 - pyskl - INFO - Epoch [86][200/1281] lr: 9.861e-03, eta: 9:23:48, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 0.2750, loss: 0.2750 +2025-06-24 23:19:50,147 - pyskl - INFO - Epoch [86][300/1281] lr: 9.841e-03, eta: 9:23:14, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9988, loss_cls: 0.2502, loss: 0.2502 +2025-06-24 23:20:39,355 - pyskl - INFO - Epoch [86][400/1281] lr: 9.821e-03, eta: 9:22:39, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9994, loss_cls: 0.2802, loss: 0.2802 +2025-06-24 23:21:28,458 - pyskl - INFO - Epoch [86][500/1281] lr: 9.801e-03, eta: 9:22:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 0.2808, loss: 0.2808 +2025-06-24 23:22:17,519 - pyskl - INFO - Epoch [86][600/1281] lr: 9.781e-03, eta: 9:21:30, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 0.2379, loss: 0.2379 +2025-06-24 23:22:47,178 - pyskl - INFO - Epoch [86][700/1281] lr: 9.762e-03, eta: 9:20:41, time: 0.297, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 0.9988, loss_cls: 0.2549, loss: 0.2549 +2025-06-24 23:23:38,396 - pyskl - INFO - Epoch [86][800/1281] lr: 9.742e-03, eta: 9:20:08, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9994, loss_cls: 0.2723, loss: 0.2723 +2025-06-24 23:24:07,797 - pyskl - INFO - Epoch [86][900/1281] lr: 9.722e-03, eta: 9:19:19, time: 0.294, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9988, loss_cls: 0.3056, loss: 0.3056 +2025-06-24 23:24:57,443 - pyskl - INFO - Epoch [86][1000/1281] lr: 9.702e-03, eta: 9:18:45, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 1.0000, loss_cls: 0.3222, loss: 0.3222 +2025-06-24 23:25:46,781 - pyskl - INFO - Epoch [86][1100/1281] lr: 9.682e-03, eta: 9:18:11, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 0.2426, loss: 0.2426 +2025-06-24 23:26:36,025 - pyskl - INFO - Epoch [86][1200/1281] lr: 9.662e-03, eta: 9:17:36, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 0.2629, loss: 0.2629 +2025-06-24 23:27:16,324 - pyskl - INFO - Saving checkpoint at 86 epochs +2025-06-24 23:28:15,492 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:28:15,547 - pyskl - INFO - +top1_acc 0.9049 +top5_acc 0.9946 +2025-06-24 23:28:15,547 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:28:15,554 - pyskl - INFO - +mean_acc 0.8759 +2025-06-24 23:28:15,558 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_76.pth was removed +2025-06-24 23:28:15,752 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_86.pth. +2025-06-24 23:28:15,752 - pyskl - INFO - Best top1_acc is 0.9049 at 86 epoch. +2025-06-24 23:28:15,756 - pyskl - INFO - Epoch(val) [86][533] top1_acc: 0.9049, top5_acc: 0.9946, mean_class_accuracy: 0.8759 +2025-06-24 23:29:34,837 - pyskl - INFO - Epoch [87][100/1281] lr: 9.626e-03, eta: 9:16:26, time: 0.791, data_time: 0.184, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9994, loss_cls: 0.2729, loss: 0.2729 +2025-06-24 23:30:24,113 - pyskl - INFO - Epoch [87][200/1281] lr: 9.606e-03, eta: 9:15:52, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 0.2301, loss: 0.2301 +2025-06-24 23:31:13,322 - pyskl - INFO - Epoch [87][300/1281] lr: 9.586e-03, eta: 9:15:17, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 1.0000, loss_cls: 0.2458, loss: 0.2458 +2025-06-24 23:32:02,744 - pyskl - INFO - Epoch [87][400/1281] lr: 9.566e-03, eta: 9:14:43, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2171, loss: 0.2171 +2025-06-24 23:32:52,233 - pyskl - INFO - Epoch [87][500/1281] lr: 9.546e-03, eta: 9:14:08, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9969, loss_cls: 0.3063, loss: 0.3063 +2025-06-24 23:33:41,583 - pyskl - INFO - Epoch [87][600/1281] lr: 9.527e-03, eta: 9:13:34, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.2448, loss: 0.2448 +2025-06-24 23:34:10,627 - pyskl - INFO - Epoch [87][700/1281] lr: 9.507e-03, eta: 9:12:45, time: 0.290, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 1.0000, loss_cls: 0.2851, loss: 0.2851 +2025-06-24 23:35:01,661 - pyskl - INFO - Epoch [87][800/1281] lr: 9.487e-03, eta: 9:12:11, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9988, loss_cls: 0.2798, loss: 0.2798 +2025-06-24 23:35:32,975 - pyskl - INFO - Epoch [87][900/1281] lr: 9.467e-03, eta: 9:11:23, time: 0.313, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 0.2509, loss: 0.2509 +2025-06-24 23:36:21,738 - pyskl - INFO - Epoch [87][1000/1281] lr: 9.447e-03, eta: 9:10:48, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 0.2092, loss: 0.2092 +2025-06-24 23:37:10,818 - pyskl - INFO - Epoch [87][1100/1281] lr: 9.427e-03, eta: 9:10:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 0.2655, loss: 0.2655 +2025-06-24 23:38:00,083 - pyskl - INFO - Epoch [87][1200/1281] lr: 9.408e-03, eta: 9:09:39, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9988, loss_cls: 0.2812, loss: 0.2812 +2025-06-24 23:38:40,807 - pyskl - INFO - Saving checkpoint at 87 epochs +2025-06-24 23:39:39,773 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:39:39,840 - pyskl - INFO - +top1_acc 0.8951 +top5_acc 0.9932 +2025-06-24 23:39:39,840 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:39:39,848 - pyskl - INFO - +mean_acc 0.8579 +2025-06-24 23:39:39,850 - pyskl - INFO - Epoch(val) [87][533] top1_acc: 0.8951, top5_acc: 0.9932, mean_class_accuracy: 0.8579 +2025-06-24 23:40:58,342 - pyskl - INFO - Epoch [88][100/1281] lr: 9.372e-03, eta: 9:08:28, time: 0.785, data_time: 0.184, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 0.2440, loss: 0.2440 +2025-06-24 23:41:47,497 - pyskl - INFO - Epoch [88][200/1281] lr: 9.352e-03, eta: 9:07:54, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2051, loss: 0.2051 +2025-06-24 23:42:36,745 - pyskl - INFO - Epoch [88][300/1281] lr: 9.332e-03, eta: 9:07:19, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1753, loss: 0.1753 +2025-06-24 23:43:25,599 - pyskl - INFO - Epoch [88][400/1281] lr: 9.312e-03, eta: 9:06:44, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1973, loss: 0.1973 +2025-06-24 23:44:14,757 - pyskl - INFO - Epoch [88][500/1281] lr: 9.293e-03, eta: 9:06:09, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.2041, loss: 0.2041 +2025-06-24 23:45:04,166 - pyskl - INFO - Epoch [88][600/1281] lr: 9.273e-03, eta: 9:05:34, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.2089, loss: 0.2089 +2025-06-24 23:45:32,414 - pyskl - INFO - Epoch [88][700/1281] lr: 9.253e-03, eta: 9:04:44, time: 0.282, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 0.2380, loss: 0.2380 +2025-06-24 23:46:23,532 - pyskl - INFO - Epoch [88][800/1281] lr: 9.233e-03, eta: 9:04:11, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 0.2383, loss: 0.2383 +2025-06-24 23:46:54,804 - pyskl - INFO - Epoch [88][900/1281] lr: 9.214e-03, eta: 9:03:23, time: 0.313, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9988, loss_cls: 0.2407, loss: 0.2407 +2025-06-24 23:47:43,960 - pyskl - INFO - Epoch [88][1000/1281] lr: 9.194e-03, eta: 9:02:48, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.2246, loss: 0.2246 +2025-06-24 23:48:33,135 - pyskl - INFO - Epoch [88][1100/1281] lr: 9.174e-03, eta: 9:02:13, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9981, loss_cls: 0.2590, loss: 0.2590 +2025-06-24 23:49:22,712 - pyskl - INFO - Epoch [88][1200/1281] lr: 9.155e-03, eta: 9:01:38, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9988, loss_cls: 0.2966, loss: 0.2966 +2025-06-24 23:50:02,861 - pyskl - INFO - Saving checkpoint at 88 epochs +2025-06-24 23:51:02,022 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:51:02,078 - pyskl - INFO - +top1_acc 0.9049 +top5_acc 0.9918 +2025-06-24 23:51:02,079 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:51:02,086 - pyskl - INFO - +mean_acc 0.8743 +2025-06-24 23:51:02,087 - pyskl - INFO - Epoch(val) [88][533] top1_acc: 0.9049, top5_acc: 0.9918, mean_class_accuracy: 0.8743 +2025-06-24 23:52:21,658 - pyskl - INFO - Epoch [89][100/1281] lr: 9.119e-03, eta: 9:00:28, time: 0.796, data_time: 0.185, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.2113, loss: 0.2113 +2025-06-24 23:53:10,748 - pyskl - INFO - Epoch [89][200/1281] lr: 9.099e-03, eta: 8:59:53, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 0.2101, loss: 0.2101 +2025-06-24 23:53:59,952 - pyskl - INFO - Epoch [89][300/1281] lr: 9.080e-03, eta: 8:59:18, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 0.2363, loss: 0.2363 +2025-06-24 23:54:49,579 - pyskl - INFO - Epoch [89][400/1281] lr: 9.060e-03, eta: 8:58:43, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9988, loss_cls: 0.2859, loss: 0.2859 +2025-06-24 23:55:38,960 - pyskl - INFO - Epoch [89][500/1281] lr: 9.040e-03, eta: 8:58:08, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9988, loss_cls: 0.2736, loss: 0.2736 +2025-06-24 23:56:28,196 - pyskl - INFO - Epoch [89][600/1281] lr: 9.021e-03, eta: 8:57:33, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9988, loss_cls: 0.2606, loss: 0.2606 +2025-06-24 23:56:57,295 - pyskl - INFO - Epoch [89][700/1281] lr: 9.001e-03, eta: 8:56:44, time: 0.291, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9988, loss_cls: 0.2697, loss: 0.2697 +2025-06-24 23:57:46,625 - pyskl - INFO - Epoch [89][800/1281] lr: 8.982e-03, eta: 8:56:09, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9994, loss_cls: 0.2508, loss: 0.2508 +2025-06-24 23:58:18,537 - pyskl - INFO - Epoch [89][900/1281] lr: 8.962e-03, eta: 8:55:22, time: 0.319, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 0.2774, loss: 0.2774 +2025-06-24 23:59:08,247 - pyskl - INFO - Epoch [89][1000/1281] lr: 8.942e-03, eta: 8:54:47, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 0.2626, loss: 0.2626 +2025-06-24 23:59:57,377 - pyskl - INFO - Epoch [89][1100/1281] lr: 8.923e-03, eta: 8:54:12, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 1.0000, loss_cls: 0.2719, loss: 0.2719 +2025-06-25 00:00:46,499 - pyskl - INFO - Epoch [89][1200/1281] lr: 8.903e-03, eta: 8:53:36, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 0.9994, loss_cls: 0.1985, loss: 0.1985 +2025-06-25 00:01:27,257 - pyskl - INFO - Saving checkpoint at 89 epochs +2025-06-25 00:02:26,633 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:02:26,702 - pyskl - INFO - +top1_acc 0.9089 +top5_acc 0.9951 +2025-06-25 00:02:26,703 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:02:26,711 - pyskl - INFO - +mean_acc 0.8877 +2025-06-25 00:02:26,716 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_86.pth was removed +2025-06-25 00:02:26,895 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_89.pth. +2025-06-25 00:02:26,895 - pyskl - INFO - Best top1_acc is 0.9089 at 89 epoch. +2025-06-25 00:02:26,898 - pyskl - INFO - Epoch(val) [89][533] top1_acc: 0.9089, top5_acc: 0.9951, mean_class_accuracy: 0.8877 +2025-06-25 00:03:46,199 - pyskl - INFO - Epoch [90][100/1281] lr: 8.868e-03, eta: 8:52:26, time: 0.793, data_time: 0.187, memory: 4083, top1_acc: 0.9613, top5_acc: 0.9988, loss_cls: 0.2224, loss: 0.2224 +2025-06-25 00:04:35,351 - pyskl - INFO - Epoch [90][200/1281] lr: 8.848e-03, eta: 8:51:50, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 0.2803, loss: 0.2803 +2025-06-25 00:05:24,626 - pyskl - INFO - Epoch [90][300/1281] lr: 8.829e-03, eta: 8:51:15, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 0.9994, loss_cls: 0.1910, loss: 0.1910 +2025-06-25 00:06:14,034 - pyskl - INFO - Epoch [90][400/1281] lr: 8.809e-03, eta: 8:50:40, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2715, loss: 0.2715 +2025-06-25 00:07:03,097 - pyskl - INFO - Epoch [90][500/1281] lr: 8.790e-03, eta: 8:50:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2314, loss: 0.2314 +2025-06-25 00:07:52,498 - pyskl - INFO - Epoch [90][600/1281] lr: 8.770e-03, eta: 8:49:29, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 0.2802, loss: 0.2802 +2025-06-25 00:08:21,060 - pyskl - INFO - Epoch [90][700/1281] lr: 8.751e-03, eta: 8:48:40, time: 0.285, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 0.2225, loss: 0.2225 +2025-06-25 00:09:09,314 - pyskl - INFO - Epoch [90][800/1281] lr: 8.731e-03, eta: 8:48:04, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2024, loss: 0.2024 +2025-06-25 00:09:43,577 - pyskl - INFO - Epoch [90][900/1281] lr: 8.712e-03, eta: 8:47:18, time: 0.343, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9988, loss_cls: 0.2557, loss: 0.2557 +2025-06-25 00:10:32,668 - pyskl - INFO - Epoch [90][1000/1281] lr: 8.692e-03, eta: 8:46:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 0.2189, loss: 0.2189 +2025-06-25 00:11:21,997 - pyskl - INFO - Epoch [90][1100/1281] lr: 8.673e-03, eta: 8:46:08, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 0.2908, loss: 0.2908 +2025-06-25 00:12:11,233 - pyskl - INFO - Epoch [90][1200/1281] lr: 8.653e-03, eta: 8:45:32, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9988, loss_cls: 0.2723, loss: 0.2723 +2025-06-25 00:12:51,602 - pyskl - INFO - Saving checkpoint at 90 epochs +2025-06-25 00:13:50,559 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:13:50,626 - pyskl - INFO - +top1_acc 0.9101 +top5_acc 0.9948 +2025-06-25 00:13:50,626 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:13:50,634 - pyskl - INFO - +mean_acc 0.8769 +2025-06-25 00:13:50,638 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_89.pth was removed +2025-06-25 00:13:50,847 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_90.pth. +2025-06-25 00:13:50,847 - pyskl - INFO - Best top1_acc is 0.9101 at 90 epoch. +2025-06-25 00:13:50,851 - pyskl - INFO - Epoch(val) [90][533] top1_acc: 0.9101, top5_acc: 0.9948, mean_class_accuracy: 0.8769 +2025-06-25 00:15:09,608 - pyskl - INFO - Epoch [91][100/1281] lr: 8.618e-03, eta: 8:44:21, time: 0.788, data_time: 0.189, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2363, loss: 0.2363 +2025-06-25 00:15:58,607 - pyskl - INFO - Epoch [91][200/1281] lr: 8.599e-03, eta: 8:43:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2043, loss: 0.2043 +2025-06-25 00:16:48,032 - pyskl - INFO - Epoch [91][300/1281] lr: 8.579e-03, eta: 8:43:10, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 0.2157, loss: 0.2157 +2025-06-25 00:17:37,286 - pyskl - INFO - Epoch [91][400/1281] lr: 8.560e-03, eta: 8:42:34, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 0.2516, loss: 0.2516 +2025-06-25 00:18:26,544 - pyskl - INFO - Epoch [91][500/1281] lr: 8.540e-03, eta: 8:41:59, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 0.2076, loss: 0.2076 +2025-06-25 00:19:15,795 - pyskl - INFO - Epoch [91][600/1281] lr: 8.521e-03, eta: 8:41:23, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2501, loss: 0.2501 +2025-06-25 00:19:47,998 - pyskl - INFO - Epoch [91][700/1281] lr: 8.502e-03, eta: 8:40:36, time: 0.322, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 0.2397, loss: 0.2397 +2025-06-25 00:20:30,658 - pyskl - INFO - Epoch [91][800/1281] lr: 8.482e-03, eta: 8:39:56, time: 0.427, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 0.2610, loss: 0.2610 +2025-06-25 00:21:08,154 - pyskl - INFO - Epoch [91][900/1281] lr: 8.463e-03, eta: 8:39:13, time: 0.375, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9988, loss_cls: 0.2644, loss: 0.2644 +2025-06-25 00:21:57,332 - pyskl - INFO - Epoch [91][1000/1281] lr: 8.444e-03, eta: 8:38:37, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 0.9994, loss_cls: 0.2178, loss: 0.2178 +2025-06-25 00:22:46,753 - pyskl - INFO - Epoch [91][1100/1281] lr: 8.424e-03, eta: 8:38:02, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 0.2352, loss: 0.2352 +2025-06-25 00:23:36,111 - pyskl - INFO - Epoch [91][1200/1281] lr: 8.405e-03, eta: 8:37:26, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 0.9994, loss_cls: 0.2194, loss: 0.2194 +2025-06-25 00:24:16,564 - pyskl - INFO - Saving checkpoint at 91 epochs +2025-06-25 00:25:15,092 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:25:15,150 - pyskl - INFO - +top1_acc 0.9066 +top5_acc 0.9945 +2025-06-25 00:25:15,151 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:25:15,157 - pyskl - INFO - +mean_acc 0.8769 +2025-06-25 00:25:15,159 - pyskl - INFO - Epoch(val) [91][533] top1_acc: 0.9066, top5_acc: 0.9945, mean_class_accuracy: 0.8769 +2025-06-25 00:26:33,069 - pyskl - INFO - Epoch [92][100/1281] lr: 8.370e-03, eta: 8:36:14, time: 0.779, data_time: 0.183, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9981, loss_cls: 0.2357, loss: 0.2357 +2025-06-25 00:27:22,252 - pyskl - INFO - Epoch [92][200/1281] lr: 8.351e-03, eta: 8:35:39, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.2012, loss: 0.2012 +2025-06-25 00:28:11,526 - pyskl - INFO - Epoch [92][300/1281] lr: 8.332e-03, eta: 8:35:03, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2137, loss: 0.2137 +2025-06-25 00:29:00,535 - pyskl - INFO - Epoch [92][400/1281] lr: 8.312e-03, eta: 8:34:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.2005, loss: 0.2005 +2025-06-25 00:29:49,960 - pyskl - INFO - Epoch [92][500/1281] lr: 8.293e-03, eta: 8:33:51, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 0.9994, loss_cls: 0.1815, loss: 0.1815 +2025-06-25 00:30:38,805 - pyskl - INFO - Epoch [92][600/1281] lr: 8.274e-03, eta: 8:33:15, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 0.9994, loss_cls: 0.1682, loss: 0.1682 +2025-06-25 00:31:12,223 - pyskl - INFO - Epoch [92][700/1281] lr: 8.255e-03, eta: 8:32:29, time: 0.334, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1877, loss: 0.1877 +2025-06-25 00:31:52,446 - pyskl - INFO - Epoch [92][800/1281] lr: 8.235e-03, eta: 8:31:47, time: 0.402, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 0.2201, loss: 0.2201 +2025-06-25 00:32:28,842 - pyskl - INFO - Epoch [92][900/1281] lr: 8.216e-03, eta: 8:31:03, time: 0.364, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9994, loss_cls: 0.2505, loss: 0.2505 +2025-06-25 00:33:17,929 - pyskl - INFO - Epoch [92][1000/1281] lr: 8.197e-03, eta: 8:30:27, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 0.9994, loss_cls: 0.2172, loss: 0.2172 +2025-06-25 00:34:06,957 - pyskl - INFO - Epoch [92][1100/1281] lr: 8.178e-03, eta: 8:29:51, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 0.2171, loss: 0.2171 +2025-06-25 00:34:55,977 - pyskl - INFO - Epoch [92][1200/1281] lr: 8.159e-03, eta: 8:29:15, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.2670, loss: 0.2670 +2025-06-25 00:35:36,407 - pyskl - INFO - Saving checkpoint at 92 epochs +2025-06-25 00:36:35,451 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:36:35,507 - pyskl - INFO - +top1_acc 0.9073 +top5_acc 0.9953 +2025-06-25 00:36:35,507 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:36:35,514 - pyskl - INFO - +mean_acc 0.8752 +2025-06-25 00:36:35,516 - pyskl - INFO - Epoch(val) [92][533] top1_acc: 0.9073, top5_acc: 0.9953, mean_class_accuracy: 0.8752 +2025-06-25 00:37:54,797 - pyskl - INFO - Epoch [93][100/1281] lr: 8.124e-03, eta: 8:28:04, time: 0.793, data_time: 0.194, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1917, loss: 0.1917 +2025-06-25 00:38:43,711 - pyskl - INFO - Epoch [93][200/1281] lr: 8.105e-03, eta: 8:27:28, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 0.9994, loss_cls: 0.1968, loss: 0.1968 +2025-06-25 00:39:32,921 - pyskl - INFO - Epoch [93][300/1281] lr: 8.086e-03, eta: 8:26:52, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 0.1997, loss: 0.1997 +2025-06-25 00:40:22,210 - pyskl - INFO - Epoch [93][400/1281] lr: 8.067e-03, eta: 8:26:16, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.1965, loss: 0.1965 +2025-06-25 00:41:11,309 - pyskl - INFO - Epoch [93][500/1281] lr: 8.047e-03, eta: 8:25:40, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 0.9994, loss_cls: 0.2170, loss: 0.2170 +2025-06-25 00:41:59,900 - pyskl - INFO - Epoch [93][600/1281] lr: 8.028e-03, eta: 8:25:03, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1950, loss: 0.1950 +2025-06-25 00:42:34,913 - pyskl - INFO - Epoch [93][700/1281] lr: 8.009e-03, eta: 8:24:18, time: 0.350, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1887, loss: 0.1887 +2025-06-25 00:43:13,662 - pyskl - INFO - Epoch [93][800/1281] lr: 7.990e-03, eta: 8:23:36, time: 0.387, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 0.9994, loss_cls: 0.1917, loss: 0.1917 +2025-06-25 00:43:51,772 - pyskl - INFO - Epoch [93][900/1281] lr: 7.971e-03, eta: 8:22:53, time: 0.381, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1975, loss: 0.1975 +2025-06-25 00:44:41,159 - pyskl - INFO - Epoch [93][1000/1281] lr: 7.952e-03, eta: 8:22:17, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 0.2233, loss: 0.2233 +2025-06-25 00:45:30,335 - pyskl - INFO - Epoch [93][1100/1281] lr: 7.933e-03, eta: 8:21:41, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.2622, loss: 0.2622 +2025-06-25 00:46:19,655 - pyskl - INFO - Epoch [93][1200/1281] lr: 7.914e-03, eta: 8:21:05, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 0.2199, loss: 0.2199 +2025-06-25 00:46:59,910 - pyskl - INFO - Saving checkpoint at 93 epochs +2025-06-25 00:47:58,437 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:47:58,492 - pyskl - INFO - +top1_acc 0.9150 +top5_acc 0.9950 +2025-06-25 00:47:58,492 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:47:58,498 - pyskl - INFO - +mean_acc 0.8846 +2025-06-25 00:47:58,502 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_90.pth was removed +2025-06-25 00:47:58,678 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_93.pth. +2025-06-25 00:47:58,678 - pyskl - INFO - Best top1_acc is 0.9150 at 93 epoch. +2025-06-25 00:47:58,682 - pyskl - INFO - Epoch(val) [93][533] top1_acc: 0.9150, top5_acc: 0.9950, mean_class_accuracy: 0.8846 +2025-06-25 00:49:17,220 - pyskl - INFO - Epoch [94][100/1281] lr: 7.880e-03, eta: 8:19:53, time: 0.785, data_time: 0.192, memory: 4083, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 0.2131, loss: 0.2131 +2025-06-25 00:50:06,389 - pyskl - INFO - Epoch [94][200/1281] lr: 7.861e-03, eta: 8:19:17, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1647, loss: 0.1647 +2025-06-25 00:50:55,513 - pyskl - INFO - Epoch [94][300/1281] lr: 7.842e-03, eta: 8:18:40, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.1902, loss: 0.1902 +2025-06-25 00:51:44,979 - pyskl - INFO - Epoch [94][400/1281] lr: 7.823e-03, eta: 8:18:04, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 0.2143, loss: 0.2143 +2025-06-25 00:52:34,129 - pyskl - INFO - Epoch [94][500/1281] lr: 7.804e-03, eta: 8:17:28, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 0.2060, loss: 0.2060 +2025-06-25 00:53:21,493 - pyskl - INFO - Epoch [94][600/1281] lr: 7.785e-03, eta: 8:16:50, time: 0.474, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 0.9994, loss_cls: 0.2403, loss: 0.2403 +2025-06-25 00:53:56,876 - pyskl - INFO - Epoch [94][700/1281] lr: 7.766e-03, eta: 8:16:06, time: 0.354, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 0.2056, loss: 0.2056 +2025-06-25 00:54:35,109 - pyskl - INFO - Epoch [94][800/1281] lr: 7.747e-03, eta: 8:15:23, time: 0.382, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 0.2305, loss: 0.2305 +2025-06-25 00:55:11,993 - pyskl - INFO - Epoch [94][900/1281] lr: 7.728e-03, eta: 8:14:39, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.2038, loss: 0.2038 +2025-06-25 00:56:01,147 - pyskl - INFO - Epoch [94][1000/1281] lr: 7.709e-03, eta: 8:14:03, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 0.9994, loss_cls: 0.2335, loss: 0.2335 +2025-06-25 00:56:50,355 - pyskl - INFO - Epoch [94][1100/1281] lr: 7.690e-03, eta: 8:13:26, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 0.2080, loss: 0.2080 +2025-06-25 00:57:39,781 - pyskl - INFO - Epoch [94][1200/1281] lr: 7.672e-03, eta: 8:12:50, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2145, loss: 0.2145 +2025-06-25 00:58:20,322 - pyskl - INFO - Saving checkpoint at 94 epochs +2025-06-25 00:59:19,352 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:59:19,420 - pyskl - INFO - +top1_acc 0.9180 +top5_acc 0.9939 +2025-06-25 00:59:19,420 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:59:19,428 - pyskl - INFO - +mean_acc 0.8950 +2025-06-25 00:59:19,432 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_93.pth was removed +2025-06-25 00:59:19,628 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_94.pth. +2025-06-25 00:59:19,629 - pyskl - INFO - Best top1_acc is 0.9180 at 94 epoch. +2025-06-25 00:59:19,631 - pyskl - INFO - Epoch(val) [94][533] top1_acc: 0.9180, top5_acc: 0.9939, mean_class_accuracy: 0.8950 +2025-06-25 01:00:39,653 - pyskl - INFO - Epoch [95][100/1281] lr: 7.637e-03, eta: 8:11:39, time: 0.800, data_time: 0.187, memory: 4083, top1_acc: 0.9669, top5_acc: 0.9994, loss_cls: 0.1958, loss: 0.1958 +2025-06-25 01:01:28,978 - pyskl - INFO - Epoch [95][200/1281] lr: 7.619e-03, eta: 8:11:03, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 0.1900, loss: 0.1900 +2025-06-25 01:02:17,799 - pyskl - INFO - Epoch [95][300/1281] lr: 7.600e-03, eta: 8:10:26, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 0.2500, loss: 0.2500 +2025-06-25 01:03:07,097 - pyskl - INFO - Epoch [95][400/1281] lr: 7.581e-03, eta: 8:09:49, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 1.0000, loss_cls: 0.2393, loss: 0.2393 +2025-06-25 01:03:56,223 - pyskl - INFO - Epoch [95][500/1281] lr: 7.562e-03, eta: 8:09:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1934, loss: 0.1934 +2025-06-25 01:04:43,299 - pyskl - INFO - Epoch [95][600/1281] lr: 7.543e-03, eta: 8:08:35, time: 0.471, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 0.9994, loss_cls: 0.1847, loss: 0.1847 +2025-06-25 01:05:20,904 - pyskl - INFO - Epoch [95][700/1281] lr: 7.525e-03, eta: 8:07:52, time: 0.376, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 0.9994, loss_cls: 0.2081, loss: 0.2081 +2025-06-25 01:05:56,548 - pyskl - INFO - Epoch [95][800/1281] lr: 7.506e-03, eta: 8:07:07, time: 0.356, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 0.9994, loss_cls: 0.1781, loss: 0.1781 +2025-06-25 01:06:34,510 - pyskl - INFO - Epoch [95][900/1281] lr: 7.487e-03, eta: 8:06:24, time: 0.380, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.1858, loss: 0.1858 +2025-06-25 01:07:23,613 - pyskl - INFO - Epoch [95][1000/1281] lr: 7.468e-03, eta: 8:05:48, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 0.2206, loss: 0.2206 +2025-06-25 01:08:12,650 - pyskl - INFO - Epoch [95][1100/1281] lr: 7.450e-03, eta: 8:05:11, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1962, loss: 0.1962 +2025-06-25 01:09:01,831 - pyskl - INFO - Epoch [95][1200/1281] lr: 7.431e-03, eta: 8:04:34, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 0.9994, loss_cls: 0.1917, loss: 0.1917 +2025-06-25 01:09:42,366 - pyskl - INFO - Saving checkpoint at 95 epochs +2025-06-25 01:10:40,119 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:10:40,183 - pyskl - INFO - +top1_acc 0.9099 +top5_acc 0.9940 +2025-06-25 01:10:40,183 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:10:40,193 - pyskl - INFO - +mean_acc 0.8889 +2025-06-25 01:10:40,197 - pyskl - INFO - Epoch(val) [95][533] top1_acc: 0.9099, top5_acc: 0.9940, mean_class_accuracy: 0.8889 +2025-06-25 01:11:58,183 - pyskl - INFO - Epoch [96][100/1281] lr: 7.397e-03, eta: 8:03:22, time: 0.780, data_time: 0.182, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1528, loss: 0.1528 +2025-06-25 01:12:47,202 - pyskl - INFO - Epoch [96][200/1281] lr: 7.379e-03, eta: 8:02:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1590, loss: 0.1590 +2025-06-25 01:13:36,518 - pyskl - INFO - Epoch [96][300/1281] lr: 7.360e-03, eta: 8:02:08, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1579, loss: 0.1579 +2025-06-25 01:14:25,492 - pyskl - INFO - Epoch [96][400/1281] lr: 7.341e-03, eta: 8:01:32, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 0.9994, loss_cls: 0.2131, loss: 0.2131 +2025-06-25 01:15:14,610 - pyskl - INFO - Epoch [96][500/1281] lr: 7.323e-03, eta: 8:00:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2109, loss: 0.2109 +2025-06-25 01:16:03,827 - pyskl - INFO - Epoch [96][600/1281] lr: 7.304e-03, eta: 8:00:18, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 0.1762, loss: 0.1762 +2025-06-25 01:16:37,156 - pyskl - INFO - Epoch [96][700/1281] lr: 7.286e-03, eta: 7:59:32, time: 0.333, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 0.2364, loss: 0.2364 +2025-06-25 01:17:17,414 - pyskl - INFO - Epoch [96][800/1281] lr: 7.267e-03, eta: 7:58:51, time: 0.403, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 0.2067, loss: 0.2067 +2025-06-25 01:17:54,678 - pyskl - INFO - Epoch [96][900/1281] lr: 7.249e-03, eta: 7:58:07, time: 0.373, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 0.9994, loss_cls: 0.2047, loss: 0.2047 +2025-06-25 01:18:43,853 - pyskl - INFO - Epoch [96][1000/1281] lr: 7.230e-03, eta: 7:57:30, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 0.9994, loss_cls: 0.2127, loss: 0.2127 +2025-06-25 01:19:33,202 - pyskl - INFO - Epoch [96][1100/1281] lr: 7.211e-03, eta: 7:56:54, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.2435, loss: 0.2435 +2025-06-25 01:20:22,293 - pyskl - INFO - Epoch [96][1200/1281] lr: 7.193e-03, eta: 7:56:17, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.2580, loss: 0.2580 +2025-06-25 01:21:02,813 - pyskl - INFO - Saving checkpoint at 96 epochs +2025-06-25 01:22:00,681 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:22:00,744 - pyskl - INFO - +top1_acc 0.9089 +top5_acc 0.9939 +2025-06-25 01:22:00,744 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:22:00,751 - pyskl - INFO - +mean_acc 0.8855 +2025-06-25 01:22:00,753 - pyskl - INFO - Epoch(val) [96][533] top1_acc: 0.9089, top5_acc: 0.9939, mean_class_accuracy: 0.8855 +2025-06-25 01:23:20,325 - pyskl - INFO - Epoch [97][100/1281] lr: 7.159e-03, eta: 7:55:05, time: 0.796, data_time: 0.181, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1547, loss: 0.1547 +2025-06-25 01:24:09,409 - pyskl - INFO - Epoch [97][200/1281] lr: 7.141e-03, eta: 7:54:28, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2038, loss: 0.2038 +2025-06-25 01:24:58,451 - pyskl - INFO - Epoch [97][300/1281] lr: 7.123e-03, eta: 7:53:51, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1691, loss: 0.1691 +2025-06-25 01:25:47,520 - pyskl - INFO - Epoch [97][400/1281] lr: 7.104e-03, eta: 7:53:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 0.1806, loss: 0.1806 +2025-06-25 01:26:36,598 - pyskl - INFO - Epoch [97][500/1281] lr: 7.086e-03, eta: 7:52:37, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 0.2377, loss: 0.2377 +2025-06-25 01:27:24,731 - pyskl - INFO - Epoch [97][600/1281] lr: 7.067e-03, eta: 7:52:00, time: 0.481, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.2135, loss: 0.2135 +2025-06-25 01:28:00,012 - pyskl - INFO - Epoch [97][700/1281] lr: 7.049e-03, eta: 7:51:15, time: 0.353, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1728, loss: 0.1728 +2025-06-25 01:28:38,299 - pyskl - INFO - Epoch [97][800/1281] lr: 7.030e-03, eta: 7:50:32, time: 0.383, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1760, loss: 0.1760 +2025-06-25 01:29:15,644 - pyskl - INFO - Epoch [97][900/1281] lr: 7.012e-03, eta: 7:49:49, time: 0.373, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 1.0000, loss_cls: 0.2421, loss: 0.2421 +2025-06-25 01:30:04,473 - pyskl - INFO - Epoch [97][1000/1281] lr: 6.994e-03, eta: 7:49:12, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 0.9988, loss_cls: 0.1962, loss: 0.1962 +2025-06-25 01:30:53,706 - pyskl - INFO - Epoch [97][1100/1281] lr: 6.975e-03, eta: 7:48:35, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 0.1991, loss: 0.1991 +2025-06-25 01:31:42,785 - pyskl - INFO - Epoch [97][1200/1281] lr: 6.957e-03, eta: 7:47:58, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2036, loss: 0.2036 +2025-06-25 01:32:22,854 - pyskl - INFO - Saving checkpoint at 97 epochs +2025-06-25 01:33:21,106 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:33:21,162 - pyskl - INFO - +top1_acc 0.9155 +top5_acc 0.9946 +2025-06-25 01:33:21,162 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:33:21,169 - pyskl - INFO - +mean_acc 0.8924 +2025-06-25 01:33:21,170 - pyskl - INFO - Epoch(val) [97][533] top1_acc: 0.9155, top5_acc: 0.9946, mean_class_accuracy: 0.8924 +2025-06-25 01:34:40,282 - pyskl - INFO - Epoch [98][100/1281] lr: 6.924e-03, eta: 7:46:45, time: 0.791, data_time: 0.180, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1494, loss: 0.1494 +2025-06-25 01:35:29,240 - pyskl - INFO - Epoch [98][200/1281] lr: 6.906e-03, eta: 7:46:08, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 0.9994, loss_cls: 0.1779, loss: 0.1779 +2025-06-25 01:36:18,477 - pyskl - INFO - Epoch [98][300/1281] lr: 6.887e-03, eta: 7:45:31, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1432, loss: 0.1432 +2025-06-25 01:37:07,686 - pyskl - INFO - Epoch [98][400/1281] lr: 6.869e-03, eta: 7:44:54, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1807, loss: 0.1807 +2025-06-25 01:37:56,666 - pyskl - INFO - Epoch [98][500/1281] lr: 6.851e-03, eta: 7:44:17, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 0.2017, loss: 0.2017 +2025-06-25 01:38:45,113 - pyskl - INFO - Epoch [98][600/1281] lr: 6.833e-03, eta: 7:43:39, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 0.2080, loss: 0.2080 +2025-06-25 01:39:21,832 - pyskl - INFO - Epoch [98][700/1281] lr: 6.814e-03, eta: 7:42:55, time: 0.367, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 0.9994, loss_cls: 0.1727, loss: 0.1727 +2025-06-25 01:39:58,666 - pyskl - INFO - Epoch [98][800/1281] lr: 6.796e-03, eta: 7:42:12, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1553, loss: 0.1553 +2025-06-25 01:40:37,220 - pyskl - INFO - Epoch [98][900/1281] lr: 6.778e-03, eta: 7:41:29, time: 0.386, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 0.9988, loss_cls: 0.1589, loss: 0.1589 +2025-06-25 01:41:26,183 - pyskl - INFO - Epoch [98][1000/1281] lr: 6.760e-03, eta: 7:40:52, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1541, loss: 0.1541 +2025-06-25 01:42:15,407 - pyskl - INFO - Epoch [98][1100/1281] lr: 6.742e-03, eta: 7:40:14, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2042, loss: 0.2042 +2025-06-25 01:43:04,423 - pyskl - INFO - Epoch [98][1200/1281] lr: 6.724e-03, eta: 7:39:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2310, loss: 0.2310 +2025-06-25 01:43:44,833 - pyskl - INFO - Saving checkpoint at 98 epochs +2025-06-25 01:44:42,658 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:44:42,712 - pyskl - INFO - +top1_acc 0.9046 +top5_acc 0.9935 +2025-06-25 01:44:42,713 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:44:42,719 - pyskl - INFO - +mean_acc 0.8808 +2025-06-25 01:44:42,721 - pyskl - INFO - Epoch(val) [98][533] top1_acc: 0.9046, top5_acc: 0.9935, mean_class_accuracy: 0.8808 +2025-06-25 01:46:02,040 - pyskl - INFO - Epoch [99][100/1281] lr: 6.691e-03, eta: 7:38:25, time: 0.793, data_time: 0.184, memory: 4083, top1_acc: 0.9738, top5_acc: 0.9994, loss_cls: 0.1782, loss: 0.1782 +2025-06-25 01:46:51,183 - pyskl - INFO - Epoch [99][200/1281] lr: 6.673e-03, eta: 7:37:47, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1289, loss: 0.1289 +2025-06-25 01:47:40,289 - pyskl - INFO - Epoch [99][300/1281] lr: 6.655e-03, eta: 7:37:10, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 0.1599, loss: 0.1599 +2025-06-25 01:48:29,472 - pyskl - INFO - Epoch [99][400/1281] lr: 6.637e-03, eta: 7:36:33, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 0.9994, loss_cls: 0.1603, loss: 0.1603 +2025-06-25 01:49:18,324 - pyskl - INFO - Epoch [99][500/1281] lr: 6.619e-03, eta: 7:35:55, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 0.9994, loss_cls: 0.1647, loss: 0.1647 +2025-06-25 01:50:05,295 - pyskl - INFO - Epoch [99][600/1281] lr: 6.601e-03, eta: 7:35:17, time: 0.470, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 0.9994, loss_cls: 0.1757, loss: 0.1757 +2025-06-25 01:50:43,279 - pyskl - INFO - Epoch [99][700/1281] lr: 6.583e-03, eta: 7:34:34, time: 0.380, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1830, loss: 0.1830 +2025-06-25 01:51:18,771 - pyskl - INFO - Epoch [99][800/1281] lr: 6.565e-03, eta: 7:33:49, time: 0.355, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 0.9994, loss_cls: 0.1863, loss: 0.1863 +2025-06-25 01:51:57,205 - pyskl - INFO - Epoch [99][900/1281] lr: 6.547e-03, eta: 7:33:06, time: 0.384, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1723, loss: 0.1723 +2025-06-25 01:52:46,415 - pyskl - INFO - Epoch [99][1000/1281] lr: 6.529e-03, eta: 7:32:29, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1713, loss: 0.1713 +2025-06-25 01:53:35,382 - pyskl - INFO - Epoch [99][1100/1281] lr: 6.511e-03, eta: 7:31:52, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.2149, loss: 0.2149 +2025-06-25 01:54:24,515 - pyskl - INFO - Epoch [99][1200/1281] lr: 6.493e-03, eta: 7:31:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2122, loss: 0.2122 +2025-06-25 01:55:04,815 - pyskl - INFO - Saving checkpoint at 99 epochs +2025-06-25 01:56:03,226 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:56:03,280 - pyskl - INFO - +top1_acc 0.9130 +top5_acc 0.9952 +2025-06-25 01:56:03,281 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:56:03,287 - pyskl - INFO - +mean_acc 0.8731 +2025-06-25 01:56:03,288 - pyskl - INFO - Epoch(val) [99][533] top1_acc: 0.9130, top5_acc: 0.9952, mean_class_accuracy: 0.8731 +2025-06-25 01:57:22,400 - pyskl - INFO - Epoch [100][100/1281] lr: 6.460e-03, eta: 7:30:02, time: 0.791, data_time: 0.183, memory: 4083, top1_acc: 0.9862, top5_acc: 0.9994, loss_cls: 0.1275, loss: 0.1275 +2025-06-25 01:58:11,346 - pyskl - INFO - Epoch [100][200/1281] lr: 6.442e-03, eta: 7:29:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1486, loss: 0.1486 +2025-06-25 01:59:00,369 - pyskl - INFO - Epoch [100][300/1281] lr: 6.425e-03, eta: 7:28:47, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1481, loss: 0.1481 +2025-06-25 01:59:49,308 - pyskl - INFO - Epoch [100][400/1281] lr: 6.407e-03, eta: 7:28:09, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1135, loss: 0.1135 +2025-06-25 02:00:38,299 - pyskl - INFO - Epoch [100][500/1281] lr: 6.389e-03, eta: 7:27:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1264, loss: 0.1264 +2025-06-25 02:01:25,596 - pyskl - INFO - Epoch [100][600/1281] lr: 6.371e-03, eta: 7:26:53, time: 0.473, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1902, loss: 0.1902 +2025-06-25 02:02:01,212 - pyskl - INFO - Epoch [100][700/1281] lr: 6.353e-03, eta: 7:26:09, time: 0.356, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1575, loss: 0.1575 +2025-06-25 02:02:39,102 - pyskl - INFO - Epoch [100][800/1281] lr: 6.336e-03, eta: 7:25:25, time: 0.379, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1620, loss: 0.1620 +2025-06-25 02:03:16,304 - pyskl - INFO - Epoch [100][900/1281] lr: 6.318e-03, eta: 7:24:42, time: 0.372, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9988, loss_cls: 0.2130, loss: 0.2130 +2025-06-25 02:04:05,531 - pyskl - INFO - Epoch [100][1000/1281] lr: 6.300e-03, eta: 7:24:04, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9988, loss_cls: 0.2733, loss: 0.2733 +2025-06-25 02:04:54,806 - pyskl - INFO - Epoch [100][1100/1281] lr: 6.282e-03, eta: 7:23:27, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 0.9994, loss_cls: 0.1738, loss: 0.1738 +2025-06-25 02:05:43,776 - pyskl - INFO - Epoch [100][1200/1281] lr: 6.265e-03, eta: 7:22:49, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 0.9994, loss_cls: 0.2106, loss: 0.2106 +2025-06-25 02:06:24,266 - pyskl - INFO - Saving checkpoint at 100 epochs +2025-06-25 02:07:21,968 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:07:22,022 - pyskl - INFO - +top1_acc 0.9164 +top5_acc 0.9946 +2025-06-25 02:07:22,022 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:07:22,029 - pyskl - INFO - +mean_acc 0.8953 +2025-06-25 02:07:22,031 - pyskl - INFO - Epoch(val) [100][533] top1_acc: 0.9164, top5_acc: 0.9946, mean_class_accuracy: 0.8953 +2025-06-25 02:08:41,702 - pyskl - INFO - Epoch [101][100/1281] lr: 6.232e-03, eta: 7:21:37, time: 0.797, data_time: 0.183, memory: 4083, top1_acc: 0.9844, top5_acc: 0.9994, loss_cls: 0.1484, loss: 0.1484 +2025-06-25 02:09:30,849 - pyskl - INFO - Epoch [101][200/1281] lr: 6.215e-03, eta: 7:20:59, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.1747, loss: 0.1747 +2025-06-25 02:10:19,891 - pyskl - INFO - Epoch [101][300/1281] lr: 6.197e-03, eta: 7:20:21, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1528, loss: 0.1528 +2025-06-25 02:11:09,300 - pyskl - INFO - Epoch [101][400/1281] lr: 6.180e-03, eta: 7:19:44, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.1123, loss: 0.1123 +2025-06-25 02:11:58,425 - pyskl - INFO - Epoch [101][500/1281] lr: 6.162e-03, eta: 7:19:06, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 0.9994, loss_cls: 0.0933, loss: 0.0933 +2025-06-25 02:12:47,060 - pyskl - INFO - Epoch [101][600/1281] lr: 6.144e-03, eta: 7:18:28, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1611, loss: 0.1611 +2025-06-25 02:13:22,289 - pyskl - INFO - Epoch [101][700/1281] lr: 6.127e-03, eta: 7:17:44, time: 0.352, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 0.9994, loss_cls: 0.1642, loss: 0.1642 +2025-06-25 02:14:00,522 - pyskl - INFO - Epoch [101][800/1281] lr: 6.109e-03, eta: 7:17:01, time: 0.382, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1535, loss: 0.1535 +2025-06-25 02:14:38,576 - pyskl - INFO - Epoch [101][900/1281] lr: 6.092e-03, eta: 7:16:18, time: 0.381, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1858, loss: 0.1858 +2025-06-25 02:15:27,526 - pyskl - INFO - Epoch [101][1000/1281] lr: 6.074e-03, eta: 7:15:40, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 0.9994, loss_cls: 0.1691, loss: 0.1691 +2025-06-25 02:16:16,579 - pyskl - INFO - Epoch [101][1100/1281] lr: 6.057e-03, eta: 7:15:02, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.2090, loss: 0.2090 +2025-06-25 02:17:05,764 - pyskl - INFO - Epoch [101][1200/1281] lr: 6.039e-03, eta: 7:14:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1756, loss: 0.1756 +2025-06-25 02:17:46,375 - pyskl - INFO - Saving checkpoint at 101 epochs +2025-06-25 02:18:44,334 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:18:44,390 - pyskl - INFO - +top1_acc 0.9173 +top5_acc 0.9938 +2025-06-25 02:18:44,390 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:18:44,396 - pyskl - INFO - +mean_acc 0.8887 +2025-06-25 02:18:44,398 - pyskl - INFO - Epoch(val) [101][533] top1_acc: 0.9173, top5_acc: 0.9938, mean_class_accuracy: 0.8887 +2025-06-25 02:20:03,700 - pyskl - INFO - Epoch [102][100/1281] lr: 6.007e-03, eta: 7:13:11, time: 0.793, data_time: 0.184, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1795, loss: 0.1795 +2025-06-25 02:20:52,539 - pyskl - INFO - Epoch [102][200/1281] lr: 5.990e-03, eta: 7:12:33, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 0.9994, loss_cls: 0.1848, loss: 0.1848 +2025-06-25 02:21:41,773 - pyskl - INFO - Epoch [102][300/1281] lr: 5.972e-03, eta: 7:11:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1594, loss: 0.1594 +2025-06-25 02:22:30,929 - pyskl - INFO - Epoch [102][400/1281] lr: 5.955e-03, eta: 7:11:18, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1158, loss: 0.1158 +2025-06-25 02:23:19,922 - pyskl - INFO - Epoch [102][500/1281] lr: 5.938e-03, eta: 7:10:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1542, loss: 0.1542 +2025-06-25 02:24:08,393 - pyskl - INFO - Epoch [102][600/1281] lr: 5.920e-03, eta: 7:10:02, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1547, loss: 0.1547 +2025-06-25 02:24:41,337 - pyskl - INFO - Epoch [102][700/1281] lr: 5.903e-03, eta: 7:09:16, time: 0.329, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 0.9994, loss_cls: 0.1572, loss: 0.1572 +2025-06-25 02:25:21,771 - pyskl - INFO - Epoch [102][800/1281] lr: 5.886e-03, eta: 7:08:34, time: 0.404, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1382, loss: 0.1382 +2025-06-25 02:25:58,760 - pyskl - INFO - Epoch [102][900/1281] lr: 5.868e-03, eta: 7:07:51, time: 0.370, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 0.9994, loss_cls: 0.1448, loss: 0.1448 +2025-06-25 02:26:47,591 - pyskl - INFO - Epoch [102][1000/1281] lr: 5.851e-03, eta: 7:07:13, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.1939, loss: 0.1939 +2025-06-25 02:27:36,519 - pyskl - INFO - Epoch [102][1100/1281] lr: 5.834e-03, eta: 7:06:35, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1474, loss: 0.1474 +2025-06-25 02:28:25,433 - pyskl - INFO - Epoch [102][1200/1281] lr: 5.816e-03, eta: 7:05:57, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1509, loss: 0.1509 +2025-06-25 02:29:05,656 - pyskl - INFO - Saving checkpoint at 102 epochs +2025-06-25 02:30:04,127 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:30:04,182 - pyskl - INFO - +top1_acc 0.9134 +top5_acc 0.9957 +2025-06-25 02:30:04,182 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:30:04,189 - pyskl - INFO - +mean_acc 0.8909 +2025-06-25 02:30:04,191 - pyskl - INFO - Epoch(val) [102][533] top1_acc: 0.9134, top5_acc: 0.9957, mean_class_accuracy: 0.8909 +2025-06-25 02:31:24,618 - pyskl - INFO - Epoch [103][100/1281] lr: 5.785e-03, eta: 7:04:44, time: 0.804, data_time: 0.185, memory: 4083, top1_acc: 0.9731, top5_acc: 0.9994, loss_cls: 0.1620, loss: 0.1620 +2025-06-25 02:32:13,715 - pyskl - INFO - Epoch [103][200/1281] lr: 5.768e-03, eta: 7:04:06, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1318, loss: 0.1318 +2025-06-25 02:33:02,958 - pyskl - INFO - Epoch [103][300/1281] lr: 5.751e-03, eta: 7:03:28, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1260, loss: 0.1260 +2025-06-25 02:33:52,256 - pyskl - INFO - Epoch [103][400/1281] lr: 5.733e-03, eta: 7:02:50, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1443, loss: 0.1443 +2025-06-25 02:34:41,517 - pyskl - INFO - Epoch [103][500/1281] lr: 5.716e-03, eta: 7:02:12, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1449, loss: 0.1449 +2025-06-25 02:35:28,115 - pyskl - INFO - Epoch [103][600/1281] lr: 5.699e-03, eta: 7:01:33, time: 0.466, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1158, loss: 0.1158 +2025-06-25 02:36:05,599 - pyskl - INFO - Epoch [103][700/1281] lr: 5.682e-03, eta: 7:00:50, time: 0.375, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1331, loss: 0.1331 +2025-06-25 02:36:41,163 - pyskl - INFO - Epoch [103][800/1281] lr: 5.665e-03, eta: 7:00:05, time: 0.356, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1600, loss: 0.1600 +2025-06-25 02:37:19,131 - pyskl - INFO - Epoch [103][900/1281] lr: 5.648e-03, eta: 6:59:22, time: 0.380, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1714, loss: 0.1714 +2025-06-25 02:38:08,165 - pyskl - INFO - Epoch [103][1000/1281] lr: 5.631e-03, eta: 6:58:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.1804, loss: 0.1804 +2025-06-25 02:38:57,213 - pyskl - INFO - Epoch [103][1100/1281] lr: 5.614e-03, eta: 6:58:06, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 0.9988, loss_cls: 0.1667, loss: 0.1667 +2025-06-25 02:39:45,954 - pyskl - INFO - Epoch [103][1200/1281] lr: 5.597e-03, eta: 6:57:28, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 0.9994, loss_cls: 0.1609, loss: 0.1609 +2025-06-25 02:40:26,561 - pyskl - INFO - Saving checkpoint at 103 epochs +2025-06-25 02:41:24,676 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:41:24,747 - pyskl - INFO - +top1_acc 0.9177 +top5_acc 0.9954 +2025-06-25 02:41:24,748 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:41:24,754 - pyskl - INFO - +mean_acc 0.8893 +2025-06-25 02:41:24,756 - pyskl - INFO - Epoch(val) [103][533] top1_acc: 0.9177, top5_acc: 0.9954, mean_class_accuracy: 0.8893 +2025-06-25 02:42:42,858 - pyskl - INFO - Epoch [104][100/1281] lr: 5.566e-03, eta: 6:56:14, time: 0.781, data_time: 0.187, memory: 4083, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 0.1881, loss: 0.1881 +2025-06-25 02:43:31,955 - pyskl - INFO - Epoch [104][200/1281] lr: 5.549e-03, eta: 6:55:36, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1417, loss: 0.1417 +2025-06-25 02:44:20,948 - pyskl - INFO - Epoch [104][300/1281] lr: 5.532e-03, eta: 6:54:57, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 0.9994, loss_cls: 0.1264, loss: 0.1264 +2025-06-25 02:45:10,192 - pyskl - INFO - Epoch [104][400/1281] lr: 5.515e-03, eta: 6:54:19, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1597, loss: 0.1597 +2025-06-25 02:45:59,241 - pyskl - INFO - Epoch [104][500/1281] lr: 5.498e-03, eta: 6:53:41, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1450, loss: 0.1450 +2025-06-25 02:46:47,749 - pyskl - INFO - Epoch [104][600/1281] lr: 5.481e-03, eta: 6:53:03, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1429, loss: 0.1429 +2025-06-25 02:47:21,994 - pyskl - INFO - Epoch [104][700/1281] lr: 5.464e-03, eta: 6:52:18, time: 0.342, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1629, loss: 0.1629 +2025-06-25 02:48:01,326 - pyskl - INFO - Epoch [104][800/1281] lr: 5.447e-03, eta: 6:51:35, time: 0.393, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 0.1560, loss: 0.1560 +2025-06-25 02:48:39,142 - pyskl - INFO - Epoch [104][900/1281] lr: 5.430e-03, eta: 6:50:52, time: 0.378, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1110, loss: 0.1110 +2025-06-25 02:49:28,430 - pyskl - INFO - Epoch [104][1000/1281] lr: 5.413e-03, eta: 6:50:14, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 0.9994, loss_cls: 0.1502, loss: 0.1502 +2025-06-25 02:50:17,377 - pyskl - INFO - Epoch [104][1100/1281] lr: 5.397e-03, eta: 6:49:36, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1487, loss: 0.1487 +2025-06-25 02:51:06,688 - pyskl - INFO - Epoch [104][1200/1281] lr: 5.380e-03, eta: 6:48:57, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 0.9994, loss_cls: 0.1431, loss: 0.1431 +2025-06-25 02:51:46,991 - pyskl - INFO - Saving checkpoint at 104 epochs +2025-06-25 02:52:44,538 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:52:44,593 - pyskl - INFO - +top1_acc 0.9135 +top5_acc 0.9941 +2025-06-25 02:52:44,594 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:52:44,600 - pyskl - INFO - +mean_acc 0.8799 +2025-06-25 02:52:44,602 - pyskl - INFO - Epoch(val) [104][533] top1_acc: 0.9135, top5_acc: 0.9941, mean_class_accuracy: 0.8799 +2025-06-25 02:54:04,042 - pyskl - INFO - Epoch [105][100/1281] lr: 5.349e-03, eta: 6:47:44, time: 0.794, data_time: 0.184, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1552, loss: 0.1552 +2025-06-25 02:54:52,897 - pyskl - INFO - Epoch [105][200/1281] lr: 5.333e-03, eta: 6:47:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.0982, loss: 0.0982 +2025-06-25 02:55:42,193 - pyskl - INFO - Epoch [105][300/1281] lr: 5.316e-03, eta: 6:46:27, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.0972, loss: 0.0972 +2025-06-25 02:56:31,354 - pyskl - INFO - Epoch [105][400/1281] lr: 5.299e-03, eta: 6:45:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1521, loss: 0.1521 +2025-06-25 02:57:20,604 - pyskl - INFO - Epoch [105][500/1281] lr: 5.283e-03, eta: 6:45:11, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1507, loss: 0.1507 +2025-06-25 02:58:08,574 - pyskl - INFO - Epoch [105][600/1281] lr: 5.266e-03, eta: 6:44:32, time: 0.480, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1245, loss: 0.1245 +2025-06-25 02:58:42,751 - pyskl - INFO - Epoch [105][700/1281] lr: 5.249e-03, eta: 6:43:47, time: 0.342, data_time: 0.001, memory: 4083, top1_acc: 0.9819, top5_acc: 0.9994, loss_cls: 0.1301, loss: 0.1301 +2025-06-25 02:59:22,105 - pyskl - INFO - Epoch [105][800/1281] lr: 5.233e-03, eta: 6:43:05, time: 0.394, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1000, loss: 0.1000 +2025-06-25 02:59:59,558 - pyskl - INFO - Epoch [105][900/1281] lr: 5.216e-03, eta: 6:42:21, time: 0.375, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 0.9994, loss_cls: 0.1507, loss: 0.1507 +2025-06-25 03:00:48,963 - pyskl - INFO - Epoch [105][1000/1281] lr: 5.199e-03, eta: 6:41:43, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1744, loss: 0.1744 +2025-06-25 03:01:38,203 - pyskl - INFO - Epoch [105][1100/1281] lr: 5.183e-03, eta: 6:41:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 0.9994, loss_cls: 0.1248, loss: 0.1248 +2025-06-25 03:02:27,637 - pyskl - INFO - Epoch [105][1200/1281] lr: 5.166e-03, eta: 6:40:26, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1578, loss: 0.1578 +2025-06-25 03:03:08,081 - pyskl - INFO - Saving checkpoint at 105 epochs +2025-06-25 03:04:05,937 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:04:05,992 - pyskl - INFO - +top1_acc 0.9150 +top5_acc 0.9953 +2025-06-25 03:04:05,992 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:04:05,999 - pyskl - INFO - +mean_acc 0.8780 +2025-06-25 03:04:06,001 - pyskl - INFO - Epoch(val) [105][533] top1_acc: 0.9150, top5_acc: 0.9953, mean_class_accuracy: 0.8780 +2025-06-25 03:05:25,126 - pyskl - INFO - Epoch [106][100/1281] lr: 5.136e-03, eta: 6:39:13, time: 0.791, data_time: 0.182, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1065, loss: 0.1065 +2025-06-25 03:06:13,834 - pyskl - INFO - Epoch [106][200/1281] lr: 5.120e-03, eta: 6:38:34, time: 0.487, data_time: 0.001, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1267, loss: 0.1267 +2025-06-25 03:07:03,052 - pyskl - INFO - Epoch [106][300/1281] lr: 5.103e-03, eta: 6:37:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1370, loss: 0.1370 +2025-06-25 03:07:52,403 - pyskl - INFO - Epoch [106][400/1281] lr: 5.087e-03, eta: 6:37:17, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.0999, loss: 0.0999 +2025-06-25 03:08:41,629 - pyskl - INFO - Epoch [106][500/1281] lr: 5.070e-03, eta: 6:36:39, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.0897, loss: 0.0897 +2025-06-25 03:09:30,734 - pyskl - INFO - Epoch [106][600/1281] lr: 5.054e-03, eta: 6:36:00, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0955, loss: 0.0955 +2025-06-25 03:10:03,500 - pyskl - INFO - Epoch [106][700/1281] lr: 5.038e-03, eta: 6:35:15, time: 0.328, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1085, loss: 0.1085 +2025-06-25 03:10:44,454 - pyskl - INFO - Epoch [106][800/1281] lr: 5.021e-03, eta: 6:34:33, time: 0.410, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1337, loss: 0.1337 +2025-06-25 03:11:21,268 - pyskl - INFO - Epoch [106][900/1281] lr: 5.005e-03, eta: 6:33:49, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1069, loss: 0.1069 +2025-06-25 03:12:10,398 - pyskl - INFO - Epoch [106][1000/1281] lr: 4.988e-03, eta: 6:33:11, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1096, loss: 0.1096 +2025-06-25 03:12:59,475 - pyskl - INFO - Epoch [106][1100/1281] lr: 4.972e-03, eta: 6:32:32, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1522, loss: 0.1522 +2025-06-25 03:13:48,742 - pyskl - INFO - Epoch [106][1200/1281] lr: 4.956e-03, eta: 6:31:54, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1322, loss: 0.1322 +2025-06-25 03:14:28,989 - pyskl - INFO - Saving checkpoint at 106 epochs +2025-06-25 03:15:27,300 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:15:27,364 - pyskl - INFO - +top1_acc 0.9117 +top5_acc 0.9951 +2025-06-25 03:15:27,364 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:15:27,370 - pyskl - INFO - +mean_acc 0.8802 +2025-06-25 03:15:27,372 - pyskl - INFO - Epoch(val) [106][533] top1_acc: 0.9117, top5_acc: 0.9951, mean_class_accuracy: 0.8802 +2025-06-25 03:16:45,277 - pyskl - INFO - Epoch [107][100/1281] lr: 4.926e-03, eta: 6:30:39, time: 0.779, data_time: 0.180, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1388, loss: 0.1388 +2025-06-25 03:17:34,533 - pyskl - INFO - Epoch [107][200/1281] lr: 4.910e-03, eta: 6:30:01, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1236, loss: 0.1236 +2025-06-25 03:18:23,981 - pyskl - INFO - Epoch [107][300/1281] lr: 4.894e-03, eta: 6:29:22, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 0.1266, loss: 0.1266 +2025-06-25 03:19:13,487 - pyskl - INFO - Epoch [107][400/1281] lr: 4.878e-03, eta: 6:28:44, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.1002, loss: 0.1002 +2025-06-25 03:20:02,690 - pyskl - INFO - Epoch [107][500/1281] lr: 4.862e-03, eta: 6:28:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1018, loss: 0.1018 +2025-06-25 03:20:51,786 - pyskl - INFO - Epoch [107][600/1281] lr: 4.845e-03, eta: 6:27:27, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1279, loss: 0.1279 +2025-06-25 03:21:23,252 - pyskl - INFO - Epoch [107][700/1281] lr: 4.829e-03, eta: 6:26:41, time: 0.315, data_time: 0.001, memory: 4083, top1_acc: 0.9700, top5_acc: 0.9994, loss_cls: 0.1532, loss: 0.1532 +2025-06-25 03:22:06,713 - pyskl - INFO - Epoch [107][800/1281] lr: 4.813e-03, eta: 6:26:00, time: 0.435, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1229, loss: 0.1229 +2025-06-25 03:22:43,033 - pyskl - INFO - Epoch [107][900/1281] lr: 4.797e-03, eta: 6:25:16, time: 0.363, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1159, loss: 0.1159 +2025-06-25 03:23:32,229 - pyskl - INFO - Epoch [107][1000/1281] lr: 4.781e-03, eta: 6:24:37, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1760, loss: 0.1760 +2025-06-25 03:24:21,836 - pyskl - INFO - Epoch [107][1100/1281] lr: 4.765e-03, eta: 6:23:59, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1278, loss: 0.1278 +2025-06-25 03:25:11,457 - pyskl - INFO - Epoch [107][1200/1281] lr: 4.749e-03, eta: 6:23:20, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1162, loss: 0.1162 +2025-06-25 03:25:51,626 - pyskl - INFO - Saving checkpoint at 107 epochs +2025-06-25 03:26:49,267 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:26:49,323 - pyskl - INFO - +top1_acc 0.9304 +top5_acc 0.9954 +2025-06-25 03:26:49,323 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:26:49,330 - pyskl - INFO - +mean_acc 0.9021 +2025-06-25 03:26:49,334 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_94.pth was removed +2025-06-25 03:26:49,658 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_107.pth. +2025-06-25 03:26:49,658 - pyskl - INFO - Best top1_acc is 0.9304 at 107 epoch. +2025-06-25 03:26:49,661 - pyskl - INFO - Epoch(val) [107][533] top1_acc: 0.9304, top5_acc: 0.9954, mean_class_accuracy: 0.9021 +2025-06-25 03:28:09,106 - pyskl - INFO - Epoch [108][100/1281] lr: 4.720e-03, eta: 6:22:07, time: 0.794, data_time: 0.184, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.0981, loss: 0.0981 +2025-06-25 03:28:58,371 - pyskl - INFO - Epoch [108][200/1281] lr: 4.704e-03, eta: 6:21:28, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1262, loss: 0.1262 +2025-06-25 03:29:47,594 - pyskl - INFO - Epoch [108][300/1281] lr: 4.688e-03, eta: 6:20:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0900, loss: 0.0900 +2025-06-25 03:30:36,631 - pyskl - INFO - Epoch [108][400/1281] lr: 4.672e-03, eta: 6:20:10, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1103, loss: 0.1103 +2025-06-25 03:31:25,748 - pyskl - INFO - Epoch [108][500/1281] lr: 4.656e-03, eta: 6:19:32, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 0.9994, loss_cls: 0.0905, loss: 0.0905 +2025-06-25 03:32:14,593 - pyskl - INFO - Epoch [108][600/1281] lr: 4.640e-03, eta: 6:18:53, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1015, loss: 0.1015 +2025-06-25 03:32:47,082 - pyskl - INFO - Epoch [108][700/1281] lr: 4.624e-03, eta: 6:18:07, time: 0.325, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1155, loss: 0.1155 +2025-06-25 03:33:27,831 - pyskl - INFO - Epoch [108][800/1281] lr: 4.608e-03, eta: 6:17:25, time: 0.407, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1415, loss: 0.1415 +2025-06-25 03:34:03,398 - pyskl - INFO - Epoch [108][900/1281] lr: 4.593e-03, eta: 6:16:41, time: 0.356, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1279, loss: 0.1279 +2025-06-25 03:34:52,459 - pyskl - INFO - Epoch [108][1000/1281] lr: 4.577e-03, eta: 6:16:02, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 0.9988, loss_cls: 0.1338, loss: 0.1338 +2025-06-25 03:35:41,855 - pyskl - INFO - Epoch [108][1100/1281] lr: 4.561e-03, eta: 6:15:24, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 0.9994, loss_cls: 0.1531, loss: 0.1531 +2025-06-25 03:36:31,152 - pyskl - INFO - Epoch [108][1200/1281] lr: 4.545e-03, eta: 6:14:45, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1307, loss: 0.1307 +2025-06-25 03:37:12,045 - pyskl - INFO - Saving checkpoint at 108 epochs +2025-06-25 03:38:10,795 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:38:10,875 - pyskl - INFO - +top1_acc 0.9202 +top5_acc 0.9951 +2025-06-25 03:38:10,875 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:38:10,883 - pyskl - INFO - +mean_acc 0.8948 +2025-06-25 03:38:10,885 - pyskl - INFO - Epoch(val) [108][533] top1_acc: 0.9202, top5_acc: 0.9951, mean_class_accuracy: 0.8948 +2025-06-25 03:39:29,904 - pyskl - INFO - Epoch [109][100/1281] lr: 4.517e-03, eta: 6:13:31, time: 0.790, data_time: 0.189, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1237, loss: 0.1237 +2025-06-25 03:40:19,189 - pyskl - INFO - Epoch [109][200/1281] lr: 4.501e-03, eta: 6:12:52, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1096, loss: 0.1096 +2025-06-25 03:41:08,271 - pyskl - INFO - Epoch [109][300/1281] lr: 4.485e-03, eta: 6:12:13, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1435, loss: 0.1435 +2025-06-25 03:41:57,043 - pyskl - INFO - Epoch [109][400/1281] lr: 4.470e-03, eta: 6:11:34, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1118, loss: 0.1118 +2025-06-25 03:42:46,097 - pyskl - INFO - Epoch [109][500/1281] lr: 4.454e-03, eta: 6:10:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0894, loss: 0.0894 +2025-06-25 03:43:34,886 - pyskl - INFO - Epoch [109][600/1281] lr: 4.438e-03, eta: 6:10:16, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1191, loss: 0.1191 +2025-06-25 03:44:07,281 - pyskl - INFO - Epoch [109][700/1281] lr: 4.423e-03, eta: 6:09:31, time: 0.324, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 0.9994, loss_cls: 0.1065, loss: 0.1065 +2025-06-25 03:44:49,325 - pyskl - INFO - Epoch [109][800/1281] lr: 4.407e-03, eta: 6:08:49, time: 0.420, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 0.9994, loss_cls: 0.1132, loss: 0.1132 +2025-06-25 03:45:26,224 - pyskl - INFO - Epoch [109][900/1281] lr: 4.391e-03, eta: 6:08:05, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1263, loss: 0.1263 +2025-06-25 03:46:15,357 - pyskl - INFO - Epoch [109][1000/1281] lr: 4.376e-03, eta: 6:07:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1259, loss: 0.1259 +2025-06-25 03:47:04,538 - pyskl - INFO - Epoch [109][1100/1281] lr: 4.360e-03, eta: 6:06:47, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1227, loss: 0.1227 +2025-06-25 03:47:53,833 - pyskl - INFO - Epoch [109][1200/1281] lr: 4.345e-03, eta: 6:06:08, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1348, loss: 0.1348 +2025-06-25 03:48:34,213 - pyskl - INFO - Saving checkpoint at 109 epochs +2025-06-25 03:49:31,974 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:49:32,030 - pyskl - INFO - +top1_acc 0.9251 +top5_acc 0.9952 +2025-06-25 03:49:32,030 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:49:32,037 - pyskl - INFO - +mean_acc 0.9014 +2025-06-25 03:49:32,039 - pyskl - INFO - Epoch(val) [109][533] top1_acc: 0.9251, top5_acc: 0.9952, mean_class_accuracy: 0.9014 +2025-06-25 03:50:50,853 - pyskl - INFO - Epoch [110][100/1281] lr: 4.317e-03, eta: 6:04:54, time: 0.788, data_time: 0.185, memory: 4083, top1_acc: 0.9875, top5_acc: 0.9994, loss_cls: 0.0966, loss: 0.0966 +2025-06-25 03:51:39,778 - pyskl - INFO - Epoch [110][200/1281] lr: 4.301e-03, eta: 6:04:15, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0873, loss: 0.0873 +2025-06-25 03:52:29,478 - pyskl - INFO - Epoch [110][300/1281] lr: 4.286e-03, eta: 6:03:36, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0846, loss: 0.0846 +2025-06-25 03:53:18,563 - pyskl - INFO - Epoch [110][400/1281] lr: 4.271e-03, eta: 6:02:57, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1074, loss: 0.1074 +2025-06-25 03:54:07,675 - pyskl - INFO - Epoch [110][500/1281] lr: 4.255e-03, eta: 6:02:18, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 0.9994, loss_cls: 0.1040, loss: 0.1040 +2025-06-25 03:54:57,075 - pyskl - INFO - Epoch [110][600/1281] lr: 4.240e-03, eta: 6:01:39, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0899, loss: 0.0899 +2025-06-25 03:55:30,720 - pyskl - INFO - Epoch [110][700/1281] lr: 4.225e-03, eta: 6:00:54, time: 0.336, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0730, loss: 0.0730 +2025-06-25 03:56:11,350 - pyskl - INFO - Epoch [110][800/1281] lr: 4.209e-03, eta: 6:00:12, time: 0.406, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 0.1159, loss: 0.1159 +2025-06-25 03:56:49,367 - pyskl - INFO - Epoch [110][900/1281] lr: 4.194e-03, eta: 5:59:29, time: 0.380, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 0.9994, loss_cls: 0.1119, loss: 0.1119 +2025-06-25 03:57:38,526 - pyskl - INFO - Epoch [110][1000/1281] lr: 4.179e-03, eta: 5:58:50, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1296, loss: 0.1296 +2025-06-25 03:58:27,743 - pyskl - INFO - Epoch [110][1100/1281] lr: 4.164e-03, eta: 5:58:11, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.0923, loss: 0.0923 +2025-06-25 03:59:17,260 - pyskl - INFO - Epoch [110][1200/1281] lr: 4.148e-03, eta: 5:57:32, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1300, loss: 0.1300 +2025-06-25 03:59:57,980 - pyskl - INFO - Saving checkpoint at 110 epochs +2025-06-25 04:00:55,893 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:00:55,947 - pyskl - INFO - +top1_acc 0.9203 +top5_acc 0.9962 +2025-06-25 04:00:55,947 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:00:55,954 - pyskl - INFO - +mean_acc 0.8963 +2025-06-25 04:00:55,955 - pyskl - INFO - Epoch(val) [110][533] top1_acc: 0.9203, top5_acc: 0.9962, mean_class_accuracy: 0.8963 +2025-06-25 04:02:15,335 - pyskl - INFO - Epoch [111][100/1281] lr: 4.121e-03, eta: 5:56:17, time: 0.794, data_time: 0.187, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0982, loss: 0.0982 +2025-06-25 04:03:04,674 - pyskl - INFO - Epoch [111][200/1281] lr: 4.106e-03, eta: 5:55:38, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0949, loss: 0.0949 +2025-06-25 04:03:53,718 - pyskl - INFO - Epoch [111][300/1281] lr: 4.091e-03, eta: 5:54:59, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0711, loss: 0.0711 +2025-06-25 04:04:42,579 - pyskl - INFO - Epoch [111][400/1281] lr: 4.075e-03, eta: 5:54:20, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0864, loss: 0.0864 +2025-06-25 04:05:31,752 - pyskl - INFO - Epoch [111][500/1281] lr: 4.060e-03, eta: 5:53:41, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0644, loss: 0.0644 +2025-06-25 04:06:20,322 - pyskl - INFO - Epoch [111][600/1281] lr: 4.045e-03, eta: 5:53:01, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0824, loss: 0.0824 +2025-06-25 04:06:54,896 - pyskl - INFO - Epoch [111][700/1281] lr: 4.030e-03, eta: 5:52:17, time: 0.346, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1007, loss: 0.1007 +2025-06-25 04:07:33,773 - pyskl - INFO - Epoch [111][800/1281] lr: 4.015e-03, eta: 5:51:34, time: 0.389, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.0906, loss: 0.0906 +2025-06-25 04:08:11,022 - pyskl - INFO - Epoch [111][900/1281] lr: 4.000e-03, eta: 5:50:51, time: 0.372, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1009, loss: 0.1009 +2025-06-25 04:08:59,692 - pyskl - INFO - Epoch [111][1000/1281] lr: 3.985e-03, eta: 5:50:11, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1018, loss: 0.1018 +2025-06-25 04:09:48,928 - pyskl - INFO - Epoch [111][1100/1281] lr: 3.970e-03, eta: 5:49:32, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.0930, loss: 0.0930 +2025-06-25 04:10:38,207 - pyskl - INFO - Epoch [111][1200/1281] lr: 3.955e-03, eta: 5:48:53, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.1003, loss: 0.1003 +2025-06-25 04:11:18,619 - pyskl - INFO - Saving checkpoint at 111 epochs +2025-06-25 04:12:16,947 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:12:17,003 - pyskl - INFO - +top1_acc 0.9316 +top5_acc 0.9962 +2025-06-25 04:12:17,003 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:12:17,010 - pyskl - INFO - +mean_acc 0.9107 +2025-06-25 04:12:17,014 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_107.pth was removed +2025-06-25 04:12:17,188 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_111.pth. +2025-06-25 04:12:17,189 - pyskl - INFO - Best top1_acc is 0.9316 at 111 epoch. +2025-06-25 04:12:17,192 - pyskl - INFO - Epoch(val) [111][533] top1_acc: 0.9316, top5_acc: 0.9962, mean_class_accuracy: 0.9107 +2025-06-25 04:13:38,245 - pyskl - INFO - Epoch [112][100/1281] lr: 3.928e-03, eta: 5:47:39, time: 0.810, data_time: 0.191, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0760, loss: 0.0760 +2025-06-25 04:14:27,360 - pyskl - INFO - Epoch [112][200/1281] lr: 3.914e-03, eta: 5:47:00, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0587, loss: 0.0587 +2025-06-25 04:15:16,457 - pyskl - INFO - Epoch [112][300/1281] lr: 3.899e-03, eta: 5:46:20, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0615, loss: 0.0615 +2025-06-25 04:16:05,722 - pyskl - INFO - Epoch [112][400/1281] lr: 3.884e-03, eta: 5:45:41, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0826, loss: 0.0826 +2025-06-25 04:16:54,848 - pyskl - INFO - Epoch [112][500/1281] lr: 3.869e-03, eta: 5:45:02, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0661, loss: 0.0661 +2025-06-25 04:17:41,329 - pyskl - INFO - Epoch [112][600/1281] lr: 3.854e-03, eta: 5:44:21, time: 0.465, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0657, loss: 0.0657 +2025-06-25 04:18:20,434 - pyskl - INFO - Epoch [112][700/1281] lr: 3.840e-03, eta: 5:43:39, time: 0.391, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0627, loss: 0.0627 +2025-06-25 04:18:55,196 - pyskl - INFO - Epoch [112][800/1281] lr: 3.825e-03, eta: 5:42:54, time: 0.348, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0714, loss: 0.0714 +2025-06-25 04:19:34,680 - pyskl - INFO - Epoch [112][900/1281] lr: 3.810e-03, eta: 5:42:12, time: 0.395, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0653, loss: 0.0653 +2025-06-25 04:20:23,968 - pyskl - INFO - Epoch [112][1000/1281] lr: 3.795e-03, eta: 5:41:32, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0782, loss: 0.0782 +2025-06-25 04:21:13,114 - pyskl - INFO - Epoch [112][1100/1281] lr: 3.781e-03, eta: 5:40:53, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0898, loss: 0.0898 +2025-06-25 04:22:02,042 - pyskl - INFO - Epoch [112][1200/1281] lr: 3.766e-03, eta: 5:40:14, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 0.9994, loss_cls: 0.0763, loss: 0.0763 +2025-06-25 04:22:42,499 - pyskl - INFO - Saving checkpoint at 112 epochs +2025-06-25 04:23:40,574 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:23:40,630 - pyskl - INFO - +top1_acc 0.9336 +top5_acc 0.9962 +2025-06-25 04:23:40,630 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:23:40,638 - pyskl - INFO - +mean_acc 0.9120 +2025-06-25 04:23:40,642 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_111.pth was removed +2025-06-25 04:23:40,830 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_112.pth. +2025-06-25 04:23:40,830 - pyskl - INFO - Best top1_acc is 0.9336 at 112 epoch. +2025-06-25 04:23:40,833 - pyskl - INFO - Epoch(val) [112][533] top1_acc: 0.9336, top5_acc: 0.9962, mean_class_accuracy: 0.9120 +2025-06-25 04:25:00,588 - pyskl - INFO - Epoch [113][100/1281] lr: 3.740e-03, eta: 5:38:59, time: 0.798, data_time: 0.191, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.0925, loss: 0.0925 +2025-06-25 04:25:49,545 - pyskl - INFO - Epoch [113][200/1281] lr: 3.725e-03, eta: 5:38:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 0.9994, loss_cls: 0.0975, loss: 0.0975 +2025-06-25 04:26:38,594 - pyskl - INFO - Epoch [113][300/1281] lr: 3.711e-03, eta: 5:37:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1013, loss: 0.1013 +2025-06-25 04:27:28,101 - pyskl - INFO - Epoch [113][400/1281] lr: 3.696e-03, eta: 5:37:01, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1198, loss: 0.1198 +2025-06-25 04:28:17,105 - pyskl - INFO - Epoch [113][500/1281] lr: 3.682e-03, eta: 5:36:21, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0755, loss: 0.0755 +2025-06-25 04:29:02,757 - pyskl - INFO - Epoch [113][600/1281] lr: 3.667e-03, eta: 5:35:41, time: 0.457, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0805, loss: 0.0805 +2025-06-25 04:29:43,641 - pyskl - INFO - Epoch [113][700/1281] lr: 3.653e-03, eta: 5:34:58, time: 0.409, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0740, loss: 0.0740 +2025-06-25 04:30:16,317 - pyskl - INFO - Epoch [113][800/1281] lr: 3.638e-03, eta: 5:34:14, time: 0.327, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0860, loss: 0.0860 +2025-06-25 04:30:56,013 - pyskl - INFO - Epoch [113][900/1281] lr: 3.624e-03, eta: 5:33:31, time: 0.397, data_time: 0.001, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0877, loss: 0.0877 +2025-06-25 04:31:45,162 - pyskl - INFO - Epoch [113][1000/1281] lr: 3.610e-03, eta: 5:32:51, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0843, loss: 0.0843 +2025-06-25 04:32:34,152 - pyskl - INFO - Epoch [113][1100/1281] lr: 3.595e-03, eta: 5:32:12, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1133, loss: 0.1133 +2025-06-25 04:33:23,490 - pyskl - INFO - Epoch [113][1200/1281] lr: 3.581e-03, eta: 5:31:32, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0792, loss: 0.0792 +2025-06-25 04:34:04,057 - pyskl - INFO - Saving checkpoint at 113 epochs +2025-06-25 04:35:02,052 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:35:02,121 - pyskl - INFO - +top1_acc 0.9251 +top5_acc 0.9959 +2025-06-25 04:35:02,121 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:35:02,128 - pyskl - INFO - +mean_acc 0.8963 +2025-06-25 04:35:02,130 - pyskl - INFO - Epoch(val) [113][533] top1_acc: 0.9251, top5_acc: 0.9959, mean_class_accuracy: 0.8963 +2025-06-25 04:36:21,578 - pyskl - INFO - Epoch [114][100/1281] lr: 3.555e-03, eta: 5:30:18, time: 0.794, data_time: 0.187, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0782, loss: 0.0782 +2025-06-25 04:37:10,338 - pyskl - INFO - Epoch [114][200/1281] lr: 3.541e-03, eta: 5:29:38, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0798, loss: 0.0798 +2025-06-25 04:37:59,538 - pyskl - INFO - Epoch [114][300/1281] lr: 3.526e-03, eta: 5:28:59, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0793, loss: 0.0793 +2025-06-25 04:38:48,905 - pyskl - INFO - Epoch [114][400/1281] lr: 3.512e-03, eta: 5:28:19, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0729, loss: 0.0729 +2025-06-25 04:39:38,177 - pyskl - INFO - Epoch [114][500/1281] lr: 3.498e-03, eta: 5:27:40, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0589, loss: 0.0589 +2025-06-25 04:40:24,012 - pyskl - INFO - Epoch [114][600/1281] lr: 3.484e-03, eta: 5:26:59, time: 0.458, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0614, loss: 0.0614 +2025-06-25 04:41:03,602 - pyskl - INFO - Epoch [114][700/1281] lr: 3.470e-03, eta: 5:26:16, time: 0.396, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0486, loss: 0.0486 +2025-06-25 04:41:37,690 - pyskl - INFO - Epoch [114][800/1281] lr: 3.456e-03, eta: 5:25:32, time: 0.341, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0738, loss: 0.0738 +2025-06-25 04:42:16,196 - pyskl - INFO - Epoch [114][900/1281] lr: 3.442e-03, eta: 5:24:49, time: 0.385, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0568, loss: 0.0568 +2025-06-25 04:43:05,072 - pyskl - INFO - Epoch [114][1000/1281] lr: 3.427e-03, eta: 5:24:09, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0737, loss: 0.0737 +2025-06-25 04:43:54,156 - pyskl - INFO - Epoch [114][1100/1281] lr: 3.413e-03, eta: 5:23:29, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0758, loss: 0.0758 +2025-06-25 04:44:42,982 - pyskl - INFO - Epoch [114][1200/1281] lr: 3.399e-03, eta: 5:22:50, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0817, loss: 0.0817 +2025-06-25 04:45:23,878 - pyskl - INFO - Saving checkpoint at 114 epochs +2025-06-25 04:46:22,666 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:46:22,724 - pyskl - INFO - +top1_acc 0.9310 +top5_acc 0.9966 +2025-06-25 04:46:22,724 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:46:22,732 - pyskl - INFO - +mean_acc 0.9056 +2025-06-25 04:46:22,734 - pyskl - INFO - Epoch(val) [114][533] top1_acc: 0.9310, top5_acc: 0.9966, mean_class_accuracy: 0.9056 +2025-06-25 04:47:43,013 - pyskl - INFO - Epoch [115][100/1281] lr: 3.374e-03, eta: 5:21:35, time: 0.803, data_time: 0.192, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0549, loss: 0.0549 +2025-06-25 04:48:31,989 - pyskl - INFO - Epoch [115][200/1281] lr: 3.360e-03, eta: 5:20:55, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0464, loss: 0.0464 +2025-06-25 04:49:21,234 - pyskl - INFO - Epoch [115][300/1281] lr: 3.346e-03, eta: 5:20:16, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0417, loss: 0.0417 +2025-06-25 04:50:10,279 - pyskl - INFO - Epoch [115][400/1281] lr: 3.332e-03, eta: 5:19:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0586, loss: 0.0586 +2025-06-25 04:50:59,354 - pyskl - INFO - Epoch [115][500/1281] lr: 3.318e-03, eta: 5:18:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0653, loss: 0.0653 +2025-06-25 04:51:44,993 - pyskl - INFO - Epoch [115][600/1281] lr: 3.305e-03, eta: 5:18:16, time: 0.456, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0776, loss: 0.0776 +2025-06-25 04:52:24,426 - pyskl - INFO - Epoch [115][700/1281] lr: 3.291e-03, eta: 5:17:33, time: 0.394, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0681, loss: 0.0681 +2025-06-25 04:52:58,337 - pyskl - INFO - Epoch [115][800/1281] lr: 3.277e-03, eta: 5:16:48, time: 0.339, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0417, loss: 0.0417 +2025-06-25 04:53:37,018 - pyskl - INFO - Epoch [115][900/1281] lr: 3.263e-03, eta: 5:16:05, time: 0.387, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0470, loss: 0.0470 +2025-06-25 04:54:26,165 - pyskl - INFO - Epoch [115][1000/1281] lr: 3.249e-03, eta: 5:15:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0829, loss: 0.0829 +2025-06-25 04:55:15,215 - pyskl - INFO - Epoch [115][1100/1281] lr: 3.236e-03, eta: 5:14:46, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0494, loss: 0.0494 +2025-06-25 04:56:04,217 - pyskl - INFO - Epoch [115][1200/1281] lr: 3.222e-03, eta: 5:14:06, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0718, loss: 0.0718 +2025-06-25 04:56:44,740 - pyskl - INFO - Saving checkpoint at 115 epochs +2025-06-25 04:57:42,678 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:57:42,746 - pyskl - INFO - +top1_acc 0.9331 +top5_acc 0.9962 +2025-06-25 04:57:42,746 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:57:42,755 - pyskl - INFO - +mean_acc 0.9080 +2025-06-25 04:57:42,757 - pyskl - INFO - Epoch(val) [115][533] top1_acc: 0.9331, top5_acc: 0.9962, mean_class_accuracy: 0.9080 +2025-06-25 04:59:00,986 - pyskl - INFO - Epoch [116][100/1281] lr: 3.197e-03, eta: 5:12:51, time: 0.782, data_time: 0.184, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0624, loss: 0.0624 +2025-06-25 04:59:50,118 - pyskl - INFO - Epoch [116][200/1281] lr: 3.184e-03, eta: 5:12:11, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0526, loss: 0.0526 +2025-06-25 05:00:38,965 - pyskl - INFO - Epoch [116][300/1281] lr: 3.170e-03, eta: 5:11:31, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0556, loss: 0.0556 +2025-06-25 05:01:28,200 - pyskl - INFO - Epoch [116][400/1281] lr: 3.156e-03, eta: 5:10:51, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0482, loss: 0.0482 +2025-06-25 05:02:17,298 - pyskl - INFO - Epoch [116][500/1281] lr: 3.143e-03, eta: 5:10:12, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0688, loss: 0.0688 +2025-06-25 05:03:05,694 - pyskl - INFO - Epoch [116][600/1281] lr: 3.129e-03, eta: 5:09:31, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.0888, loss: 0.0888 +2025-06-25 05:03:40,193 - pyskl - INFO - Epoch [116][700/1281] lr: 3.116e-03, eta: 5:08:47, time: 0.345, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0785, loss: 0.0785 +2025-06-25 05:04:19,353 - pyskl - INFO - Epoch [116][800/1281] lr: 3.102e-03, eta: 5:08:04, time: 0.392, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0778, loss: 0.0778 +2025-06-25 05:04:55,802 - pyskl - INFO - Epoch [116][900/1281] lr: 3.089e-03, eta: 5:07:21, time: 0.364, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0689, loss: 0.0689 +2025-06-25 05:05:44,885 - pyskl - INFO - Epoch [116][1000/1281] lr: 3.075e-03, eta: 5:06:41, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0690, loss: 0.0690 +2025-06-25 05:06:34,169 - pyskl - INFO - Epoch [116][1100/1281] lr: 3.062e-03, eta: 5:06:01, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0619, loss: 0.0619 +2025-06-25 05:07:23,351 - pyskl - INFO - Epoch [116][1200/1281] lr: 3.049e-03, eta: 5:05:21, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0527, loss: 0.0527 +2025-06-25 05:08:03,547 - pyskl - INFO - Saving checkpoint at 116 epochs +2025-06-25 05:09:01,958 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:09:02,013 - pyskl - INFO - +top1_acc 0.9301 +top5_acc 0.9964 +2025-06-25 05:09:02,013 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:09:02,019 - pyskl - INFO - +mean_acc 0.9070 +2025-06-25 05:09:02,021 - pyskl - INFO - Epoch(val) [116][533] top1_acc: 0.9301, top5_acc: 0.9964, mean_class_accuracy: 0.9070 +2025-06-25 05:10:21,448 - pyskl - INFO - Epoch [117][100/1281] lr: 3.024e-03, eta: 5:04:06, time: 0.794, data_time: 0.182, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0725, loss: 0.0725 +2025-06-25 05:11:10,720 - pyskl - INFO - Epoch [117][200/1281] lr: 3.011e-03, eta: 5:03:26, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0800, loss: 0.0800 +2025-06-25 05:11:59,805 - pyskl - INFO - Epoch [117][300/1281] lr: 2.998e-03, eta: 5:02:46, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0577, loss: 0.0577 +2025-06-25 05:12:48,533 - pyskl - INFO - Epoch [117][400/1281] lr: 2.984e-03, eta: 5:02:06, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0578, loss: 0.0578 +2025-06-25 05:13:37,994 - pyskl - INFO - Epoch [117][500/1281] lr: 2.971e-03, eta: 5:01:27, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0473, loss: 0.0473 +2025-06-25 05:14:27,203 - pyskl - INFO - Epoch [117][600/1281] lr: 2.958e-03, eta: 5:00:47, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0442, loss: 0.0442 +2025-06-25 05:14:59,873 - pyskl - INFO - Epoch [117][700/1281] lr: 2.945e-03, eta: 5:00:02, time: 0.327, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0404, loss: 0.0404 +2025-06-25 05:15:40,759 - pyskl - INFO - Epoch [117][800/1281] lr: 2.932e-03, eta: 4:59:20, time: 0.409, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0530, loss: 0.0530 +2025-06-25 05:16:16,799 - pyskl - INFO - Epoch [117][900/1281] lr: 2.919e-03, eta: 4:58:36, time: 0.360, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0353, loss: 0.0353 +2025-06-25 05:17:05,966 - pyskl - INFO - Epoch [117][1000/1281] lr: 2.905e-03, eta: 4:57:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0491, loss: 0.0491 +2025-06-25 05:17:55,159 - pyskl - INFO - Epoch [117][1100/1281] lr: 2.892e-03, eta: 4:57:16, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0479, loss: 0.0479 +2025-06-25 05:18:44,420 - pyskl - INFO - Epoch [117][1200/1281] lr: 2.879e-03, eta: 4:56:36, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0814, loss: 0.0814 +2025-06-25 05:19:24,905 - pyskl - INFO - Saving checkpoint at 117 epochs +2025-06-25 05:20:23,362 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:20:23,419 - pyskl - INFO - +top1_acc 0.9364 +top5_acc 0.9965 +2025-06-25 05:20:23,419 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:20:23,426 - pyskl - INFO - +mean_acc 0.9106 +2025-06-25 05:20:23,429 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_112.pth was removed +2025-06-25 05:20:23,599 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_117.pth. +2025-06-25 05:20:23,600 - pyskl - INFO - Best top1_acc is 0.9364 at 117 epoch. +2025-06-25 05:20:23,602 - pyskl - INFO - Epoch(val) [117][533] top1_acc: 0.9364, top5_acc: 0.9965, mean_class_accuracy: 0.9106 +2025-06-25 05:21:42,202 - pyskl - INFO - Epoch [118][100/1281] lr: 2.856e-03, eta: 4:55:21, time: 0.786, data_time: 0.186, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0365, loss: 0.0365 +2025-06-25 05:22:31,535 - pyskl - INFO - Epoch [118][200/1281] lr: 2.843e-03, eta: 4:54:41, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0470, loss: 0.0470 +2025-06-25 05:23:20,560 - pyskl - INFO - Epoch [118][300/1281] lr: 2.830e-03, eta: 4:54:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0447, loss: 0.0447 +2025-06-25 05:24:09,536 - pyskl - INFO - Epoch [118][400/1281] lr: 2.817e-03, eta: 4:53:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0463, loss: 0.0463 +2025-06-25 05:24:58,855 - pyskl - INFO - Epoch [118][500/1281] lr: 2.804e-03, eta: 4:52:40, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0482, loss: 0.0482 +2025-06-25 05:25:47,909 - pyskl - INFO - Epoch [118][600/1281] lr: 2.791e-03, eta: 4:52:00, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0422, loss: 0.0422 +2025-06-25 05:26:20,129 - pyskl - INFO - Epoch [118][700/1281] lr: 2.778e-03, eta: 4:51:16, time: 0.322, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0627, loss: 0.0627 +2025-06-25 05:27:01,269 - pyskl - INFO - Epoch [118][800/1281] lr: 2.765e-03, eta: 4:50:33, time: 0.411, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0476, loss: 0.0476 +2025-06-25 05:27:37,257 - pyskl - INFO - Epoch [118][900/1281] lr: 2.753e-03, eta: 4:49:50, time: 0.360, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0558, loss: 0.0558 +2025-06-25 05:28:26,248 - pyskl - INFO - Epoch [118][1000/1281] lr: 2.740e-03, eta: 4:49:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0396, loss: 0.0396 +2025-06-25 05:29:15,160 - pyskl - INFO - Epoch [118][1100/1281] lr: 2.727e-03, eta: 4:48:29, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0465, loss: 0.0465 +2025-06-25 05:30:04,315 - pyskl - INFO - Epoch [118][1200/1281] lr: 2.714e-03, eta: 4:47:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0386, loss: 0.0386 +2025-06-25 05:30:44,541 - pyskl - INFO - Saving checkpoint at 118 epochs +2025-06-25 05:31:43,388 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:31:43,448 - pyskl - INFO - +top1_acc 0.9397 +top5_acc 0.9967 +2025-06-25 05:31:43,448 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:31:43,455 - pyskl - INFO - +mean_acc 0.9173 +2025-06-25 05:31:43,459 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_117.pth was removed +2025-06-25 05:31:43,623 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_118.pth. +2025-06-25 05:31:43,623 - pyskl - INFO - Best top1_acc is 0.9397 at 118 epoch. +2025-06-25 05:31:43,626 - pyskl - INFO - Epoch(val) [118][533] top1_acc: 0.9397, top5_acc: 0.9967, mean_class_accuracy: 0.9173 +2025-06-25 05:33:03,805 - pyskl - INFO - Epoch [119][100/1281] lr: 2.691e-03, eta: 4:46:34, time: 0.802, data_time: 0.182, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0520, loss: 0.0520 +2025-06-25 05:33:53,142 - pyskl - INFO - Epoch [119][200/1281] lr: 2.679e-03, eta: 4:45:54, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0418, loss: 0.0418 +2025-06-25 05:34:42,294 - pyskl - INFO - Epoch [119][300/1281] lr: 2.666e-03, eta: 4:45:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0362, loss: 0.0362 +2025-06-25 05:35:31,756 - pyskl - INFO - Epoch [119][400/1281] lr: 2.653e-03, eta: 4:44:34, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0383, loss: 0.0383 +2025-06-25 05:36:20,747 - pyskl - INFO - Epoch [119][500/1281] lr: 2.641e-03, eta: 4:43:54, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0344, loss: 0.0344 +2025-06-25 05:37:09,354 - pyskl - INFO - Epoch [119][600/1281] lr: 2.628e-03, eta: 4:43:13, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0454, loss: 0.0454 +2025-06-25 05:37:44,033 - pyskl - INFO - Epoch [119][700/1281] lr: 2.616e-03, eta: 4:42:29, time: 0.347, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0326, loss: 0.0326 +2025-06-25 05:38:22,674 - pyskl - INFO - Epoch [119][800/1281] lr: 2.603e-03, eta: 4:41:46, time: 0.386, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0555, loss: 0.0555 +2025-06-25 05:39:00,432 - pyskl - INFO - Epoch [119][900/1281] lr: 2.591e-03, eta: 4:41:03, time: 0.378, data_time: 0.001, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0475, loss: 0.0475 +2025-06-25 05:39:49,755 - pyskl - INFO - Epoch [119][1000/1281] lr: 2.578e-03, eta: 4:40:23, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0810, loss: 0.0810 +2025-06-25 05:40:39,077 - pyskl - INFO - Epoch [119][1100/1281] lr: 2.566e-03, eta: 4:39:43, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0408, loss: 0.0408 +2025-06-25 05:41:27,917 - pyskl - INFO - Epoch [119][1200/1281] lr: 2.554e-03, eta: 4:39:03, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0478, loss: 0.0478 +2025-06-25 05:42:08,341 - pyskl - INFO - Saving checkpoint at 119 epochs +2025-06-25 05:43:06,162 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:43:06,221 - pyskl - INFO - +top1_acc 0.9299 +top5_acc 0.9974 +2025-06-25 05:43:06,221 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:43:06,228 - pyskl - INFO - +mean_acc 0.9066 +2025-06-25 05:43:06,229 - pyskl - INFO - Epoch(val) [119][533] top1_acc: 0.9299, top5_acc: 0.9974, mean_class_accuracy: 0.9066 +2025-06-25 05:44:25,639 - pyskl - INFO - Epoch [120][100/1281] lr: 2.531e-03, eta: 4:37:47, time: 0.794, data_time: 0.189, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0586, loss: 0.0586 +2025-06-25 05:45:14,756 - pyskl - INFO - Epoch [120][200/1281] lr: 2.519e-03, eta: 4:37:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0634, loss: 0.0634 +2025-06-25 05:46:04,183 - pyskl - INFO - Epoch [120][300/1281] lr: 2.507e-03, eta: 4:36:27, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0447, loss: 0.0447 +2025-06-25 05:46:53,229 - pyskl - INFO - Epoch [120][400/1281] lr: 2.494e-03, eta: 4:35:46, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0447, loss: 0.0447 +2025-06-25 05:47:42,294 - pyskl - INFO - Epoch [120][500/1281] lr: 2.482e-03, eta: 4:35:06, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0478, loss: 0.0478 +2025-06-25 05:48:30,257 - pyskl - INFO - Epoch [120][600/1281] lr: 2.470e-03, eta: 4:34:26, time: 0.480, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 0.9994, loss_cls: 0.0714, loss: 0.0714 +2025-06-25 05:49:04,073 - pyskl - INFO - Epoch [120][700/1281] lr: 2.458e-03, eta: 4:33:41, time: 0.338, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0445, loss: 0.0445 +2025-06-25 05:49:43,216 - pyskl - INFO - Epoch [120][800/1281] lr: 2.446e-03, eta: 4:32:59, time: 0.391, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0586, loss: 0.0586 +2025-06-25 05:50:20,265 - pyskl - INFO - Epoch [120][900/1281] lr: 2.433e-03, eta: 4:32:15, time: 0.370, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0599, loss: 0.0599 +2025-06-25 05:51:09,423 - pyskl - INFO - Epoch [120][1000/1281] lr: 2.421e-03, eta: 4:31:35, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0515, loss: 0.0515 +2025-06-25 05:51:58,473 - pyskl - INFO - Epoch [120][1100/1281] lr: 2.409e-03, eta: 4:30:54, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0407, loss: 0.0407 +2025-06-25 05:52:47,666 - pyskl - INFO - Epoch [120][1200/1281] lr: 2.397e-03, eta: 4:30:14, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0444, loss: 0.0444 +2025-06-25 05:53:28,072 - pyskl - INFO - Saving checkpoint at 120 epochs +2025-06-25 05:54:25,977 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:54:26,032 - pyskl - INFO - +top1_acc 0.9331 +top5_acc 0.9958 +2025-06-25 05:54:26,032 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:54:26,038 - pyskl - INFO - +mean_acc 0.9048 +2025-06-25 05:54:26,040 - pyskl - INFO - Epoch(val) [120][533] top1_acc: 0.9331, top5_acc: 0.9958, mean_class_accuracy: 0.9048 +2025-06-25 05:55:45,937 - pyskl - INFO - Epoch [121][100/1281] lr: 2.375e-03, eta: 4:28:59, time: 0.799, data_time: 0.185, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0572, loss: 0.0572 +2025-06-25 05:56:34,796 - pyskl - INFO - Epoch [121][200/1281] lr: 2.363e-03, eta: 4:28:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0462, loss: 0.0462 +2025-06-25 05:57:23,739 - pyskl - INFO - Epoch [121][300/1281] lr: 2.351e-03, eta: 4:27:38, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0386, loss: 0.0386 +2025-06-25 05:58:12,868 - pyskl - INFO - Epoch [121][400/1281] lr: 2.340e-03, eta: 4:26:58, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0459, loss: 0.0459 +2025-06-25 05:59:01,856 - pyskl - INFO - Epoch [121][500/1281] lr: 2.328e-03, eta: 4:26:17, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0433, loss: 0.0433 +2025-06-25 05:59:50,666 - pyskl - INFO - Epoch [121][600/1281] lr: 2.316e-03, eta: 4:25:37, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0282, loss: 0.0282 +2025-06-25 06:00:24,034 - pyskl - INFO - Epoch [121][700/1281] lr: 2.304e-03, eta: 4:24:52, time: 0.334, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0356, loss: 0.0356 +2025-06-25 06:01:04,419 - pyskl - INFO - Epoch [121][800/1281] lr: 2.292e-03, eta: 4:24:10, time: 0.404, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0303, loss: 0.0303 +2025-06-25 06:01:41,259 - pyskl - INFO - Epoch [121][900/1281] lr: 2.280e-03, eta: 4:23:27, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0501, loss: 0.0501 +2025-06-25 06:02:30,522 - pyskl - INFO - Epoch [121][1000/1281] lr: 2.269e-03, eta: 4:22:46, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0309, loss: 0.0309 +2025-06-25 06:03:19,912 - pyskl - INFO - Epoch [121][1100/1281] lr: 2.257e-03, eta: 4:22:06, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0343, loss: 0.0343 +2025-06-25 06:04:09,190 - pyskl - INFO - Epoch [121][1200/1281] lr: 2.245e-03, eta: 4:21:25, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0293, loss: 0.0293 +2025-06-25 06:04:49,307 - pyskl - INFO - Saving checkpoint at 121 epochs +2025-06-25 06:05:47,249 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:05:47,303 - pyskl - INFO - +top1_acc 0.9363 +top5_acc 0.9969 +2025-06-25 06:05:47,304 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:05:47,310 - pyskl - INFO - +mean_acc 0.9141 +2025-06-25 06:05:47,312 - pyskl - INFO - Epoch(val) [121][533] top1_acc: 0.9363, top5_acc: 0.9969, mean_class_accuracy: 0.9141 +2025-06-25 06:07:06,331 - pyskl - INFO - Epoch [122][100/1281] lr: 2.224e-03, eta: 4:20:10, time: 0.790, data_time: 0.182, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0365, loss: 0.0365 +2025-06-25 06:07:55,672 - pyskl - INFO - Epoch [122][200/1281] lr: 2.212e-03, eta: 4:19:29, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0296, loss: 0.0296 +2025-06-25 06:08:44,800 - pyskl - INFO - Epoch [122][300/1281] lr: 2.201e-03, eta: 4:18:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0238, loss: 0.0238 +2025-06-25 06:09:34,090 - pyskl - INFO - Epoch [122][400/1281] lr: 2.189e-03, eta: 4:18:08, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0261, loss: 0.0261 +2025-06-25 06:10:23,239 - pyskl - INFO - Epoch [122][500/1281] lr: 2.178e-03, eta: 4:17:28, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0261, loss: 0.0261 +2025-06-25 06:11:12,507 - pyskl - INFO - Epoch [122][600/1281] lr: 2.166e-03, eta: 4:16:47, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0303, loss: 0.0303 +2025-06-25 06:11:44,483 - pyskl - INFO - Epoch [122][700/1281] lr: 2.155e-03, eta: 4:16:03, time: 0.320, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0378, loss: 0.0378 +2025-06-25 06:12:26,328 - pyskl - INFO - Epoch [122][800/1281] lr: 2.143e-03, eta: 4:15:21, time: 0.418, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0389, loss: 0.0389 +2025-06-25 06:13:01,606 - pyskl - INFO - Epoch [122][900/1281] lr: 2.132e-03, eta: 4:14:37, time: 0.353, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0442, loss: 0.0442 +2025-06-25 06:13:50,868 - pyskl - INFO - Epoch [122][1000/1281] lr: 2.120e-03, eta: 4:13:56, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0299, loss: 0.0299 +2025-06-25 06:14:40,275 - pyskl - INFO - Epoch [122][1100/1281] lr: 2.109e-03, eta: 4:13:16, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0352, loss: 0.0352 +2025-06-25 06:15:29,798 - pyskl - INFO - Epoch [122][1200/1281] lr: 2.098e-03, eta: 4:12:35, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0416, loss: 0.0416 +2025-06-25 06:16:09,974 - pyskl - INFO - Saving checkpoint at 122 epochs +2025-06-25 06:17:08,345 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:17:08,400 - pyskl - INFO - +top1_acc 0.9374 +top5_acc 0.9965 +2025-06-25 06:17:08,400 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:17:08,407 - pyskl - INFO - +mean_acc 0.9107 +2025-06-25 06:17:08,408 - pyskl - INFO - Epoch(val) [122][533] top1_acc: 0.9374, top5_acc: 0.9965, mean_class_accuracy: 0.9107 +2025-06-25 06:18:27,424 - pyskl - INFO - Epoch [123][100/1281] lr: 2.077e-03, eta: 4:11:20, time: 0.790, data_time: 0.180, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0348, loss: 0.0348 +2025-06-25 06:19:16,469 - pyskl - INFO - Epoch [123][200/1281] lr: 2.066e-03, eta: 4:10:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0338, loss: 0.0338 +2025-06-25 06:20:05,730 - pyskl - INFO - Epoch [123][300/1281] lr: 2.055e-03, eta: 4:09:59, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0272, loss: 0.0272 +2025-06-25 06:20:54,976 - pyskl - INFO - Epoch [123][400/1281] lr: 2.044e-03, eta: 4:09:18, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0319, loss: 0.0319 +2025-06-25 06:21:44,093 - pyskl - INFO - Epoch [123][500/1281] lr: 2.032e-03, eta: 4:08:37, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0307, loss: 0.0307 +2025-06-25 06:22:33,058 - pyskl - INFO - Epoch [123][600/1281] lr: 2.021e-03, eta: 4:07:57, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0279, loss: 0.0279 +2025-06-25 06:23:02,973 - pyskl - INFO - Epoch [123][700/1281] lr: 2.010e-03, eta: 4:07:12, time: 0.299, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0250, loss: 0.0250 +2025-06-25 06:23:48,084 - pyskl - INFO - Epoch [123][800/1281] lr: 1.999e-03, eta: 4:06:30, time: 0.451, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0264, loss: 0.0264 +2025-06-25 06:24:21,656 - pyskl - INFO - Epoch [123][900/1281] lr: 1.988e-03, eta: 4:05:46, time: 0.336, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-25 06:25:11,000 - pyskl - INFO - Epoch [123][1000/1281] lr: 1.977e-03, eta: 4:05:06, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0263, loss: 0.0263 +2025-06-25 06:25:59,868 - pyskl - INFO - Epoch [123][1100/1281] lr: 1.966e-03, eta: 4:04:25, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0495, loss: 0.0495 +2025-06-25 06:26:48,900 - pyskl - INFO - Epoch [123][1200/1281] lr: 1.955e-03, eta: 4:03:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0443, loss: 0.0443 +2025-06-25 06:27:29,147 - pyskl - INFO - Saving checkpoint at 123 epochs +2025-06-25 06:28:28,117 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:28:28,172 - pyskl - INFO - +top1_acc 0.9340 +top5_acc 0.9967 +2025-06-25 06:28:28,173 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:28:28,179 - pyskl - INFO - +mean_acc 0.9089 +2025-06-25 06:28:28,180 - pyskl - INFO - Epoch(val) [123][533] top1_acc: 0.9340, top5_acc: 0.9967, mean_class_accuracy: 0.9089 +2025-06-25 06:29:47,170 - pyskl - INFO - Epoch [124][100/1281] lr: 1.935e-03, eta: 4:02:29, time: 0.790, data_time: 0.187, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0293, loss: 0.0293 +2025-06-25 06:30:36,142 - pyskl - INFO - Epoch [124][200/1281] lr: 1.924e-03, eta: 4:01:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0291, loss: 0.0291 +2025-06-25 06:31:25,110 - pyskl - INFO - Epoch [124][300/1281] lr: 1.913e-03, eta: 4:01:07, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0522, loss: 0.0522 +2025-06-25 06:32:14,258 - pyskl - INFO - Epoch [124][400/1281] lr: 1.902e-03, eta: 4:00:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0364, loss: 0.0364 +2025-06-25 06:33:03,660 - pyskl - INFO - Epoch [124][500/1281] lr: 1.892e-03, eta: 3:59:46, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0315, loss: 0.0315 +2025-06-25 06:33:53,100 - pyskl - INFO - Epoch [124][600/1281] lr: 1.881e-03, eta: 3:59:05, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 06:34:22,327 - pyskl - INFO - Epoch [124][700/1281] lr: 1.870e-03, eta: 3:58:20, time: 0.292, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0220, loss: 0.0220 +2025-06-25 06:35:09,464 - pyskl - INFO - Epoch [124][800/1281] lr: 1.859e-03, eta: 3:57:39, time: 0.471, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0265, loss: 0.0265 +2025-06-25 06:35:43,075 - pyskl - INFO - Epoch [124][900/1281] lr: 1.849e-03, eta: 3:56:55, time: 0.336, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0310, loss: 0.0310 +2025-06-25 06:36:31,904 - pyskl - INFO - Epoch [124][1000/1281] lr: 1.838e-03, eta: 3:56:14, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0327, loss: 0.0327 +2025-06-25 06:37:21,490 - pyskl - INFO - Epoch [124][1100/1281] lr: 1.827e-03, eta: 3:55:33, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0279, loss: 0.0279 +2025-06-25 06:38:11,053 - pyskl - INFO - Epoch [124][1200/1281] lr: 1.817e-03, eta: 3:54:53, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0283, loss: 0.0283 +2025-06-25 06:38:51,296 - pyskl - INFO - Saving checkpoint at 124 epochs +2025-06-25 06:39:49,739 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:39:49,805 - pyskl - INFO - +top1_acc 0.9372 +top5_acc 0.9972 +2025-06-25 06:39:49,806 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:39:49,812 - pyskl - INFO - +mean_acc 0.9161 +2025-06-25 06:39:49,814 - pyskl - INFO - Epoch(val) [124][533] top1_acc: 0.9372, top5_acc: 0.9972, mean_class_accuracy: 0.9161 +2025-06-25 06:41:08,545 - pyskl - INFO - Epoch [125][100/1281] lr: 1.797e-03, eta: 3:53:37, time: 0.787, data_time: 0.189, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0268, loss: 0.0268 +2025-06-25 06:41:57,881 - pyskl - INFO - Epoch [125][200/1281] lr: 1.787e-03, eta: 3:52:56, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0301, loss: 0.0301 +2025-06-25 06:42:47,073 - pyskl - INFO - Epoch [125][300/1281] lr: 1.776e-03, eta: 3:52:15, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0312, loss: 0.0312 +2025-06-25 06:43:36,179 - pyskl - INFO - Epoch [125][400/1281] lr: 1.766e-03, eta: 3:51:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0318, loss: 0.0318 +2025-06-25 06:44:25,502 - pyskl - INFO - Epoch [125][500/1281] lr: 1.755e-03, eta: 3:50:54, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0248, loss: 0.0248 +2025-06-25 06:45:14,822 - pyskl - INFO - Epoch [125][600/1281] lr: 1.745e-03, eta: 3:50:13, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0360, loss: 0.0360 +2025-06-25 06:45:42,797 - pyskl - INFO - Epoch [125][700/1281] lr: 1.735e-03, eta: 3:49:28, time: 0.280, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0423, loss: 0.0423 +2025-06-25 06:46:31,604 - pyskl - INFO - Epoch [125][800/1281] lr: 1.724e-03, eta: 3:48:47, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0383, loss: 0.0383 +2025-06-25 06:47:05,651 - pyskl - INFO - Epoch [125][900/1281] lr: 1.714e-03, eta: 3:48:03, time: 0.340, data_time: 0.001, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0479, loss: 0.0479 +2025-06-25 06:47:54,726 - pyskl - INFO - Epoch [125][1000/1281] lr: 1.704e-03, eta: 3:47:22, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0601, loss: 0.0601 +2025-06-25 06:48:44,127 - pyskl - INFO - Epoch [125][1100/1281] lr: 1.693e-03, eta: 3:46:42, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0404, loss: 0.0404 +2025-06-25 06:49:33,301 - pyskl - INFO - Epoch [125][1200/1281] lr: 1.683e-03, eta: 3:46:01, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0273, loss: 0.0273 +2025-06-25 06:50:13,478 - pyskl - INFO - Saving checkpoint at 125 epochs +2025-06-25 06:51:12,214 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:51:12,269 - pyskl - INFO - +top1_acc 0.9416 +top5_acc 0.9962 +2025-06-25 06:51:12,269 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:51:12,275 - pyskl - INFO - +mean_acc 0.9197 +2025-06-25 06:51:12,279 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_118.pth was removed +2025-06-25 06:51:12,458 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_125.pth. +2025-06-25 06:51:12,459 - pyskl - INFO - Best top1_acc is 0.9416 at 125 epoch. +2025-06-25 06:51:12,461 - pyskl - INFO - Epoch(val) [125][533] top1_acc: 0.9416, top5_acc: 0.9962, mean_class_accuracy: 0.9197 +2025-06-25 06:52:31,861 - pyskl - INFO - Epoch [126][100/1281] lr: 1.665e-03, eta: 3:44:45, time: 0.794, data_time: 0.189, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0309, loss: 0.0309 +2025-06-25 06:53:21,021 - pyskl - INFO - Epoch [126][200/1281] lr: 1.654e-03, eta: 3:44:04, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0297, loss: 0.0297 +2025-06-25 06:54:10,128 - pyskl - INFO - Epoch [126][300/1281] lr: 1.644e-03, eta: 3:43:23, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0330, loss: 0.0330 +2025-06-25 06:54:59,592 - pyskl - INFO - Epoch [126][400/1281] lr: 1.634e-03, eta: 3:42:42, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0323, loss: 0.0323 +2025-06-25 06:55:48,663 - pyskl - INFO - Epoch [126][500/1281] lr: 1.624e-03, eta: 3:42:01, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0263, loss: 0.0263 +2025-06-25 06:56:37,866 - pyskl - INFO - Epoch [126][600/1281] lr: 1.614e-03, eta: 3:41:20, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0251, loss: 0.0251 +2025-06-25 06:57:07,984 - pyskl - INFO - Epoch [126][700/1281] lr: 1.604e-03, eta: 3:40:36, time: 0.301, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-25 06:57:53,132 - pyskl - INFO - Epoch [126][800/1281] lr: 1.594e-03, eta: 3:39:54, time: 0.451, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0257, loss: 0.0257 +2025-06-25 06:58:27,595 - pyskl - INFO - Epoch [126][900/1281] lr: 1.584e-03, eta: 3:39:10, time: 0.345, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0257, loss: 0.0257 +2025-06-25 06:59:16,532 - pyskl - INFO - Epoch [126][1000/1281] lr: 1.574e-03, eta: 3:38:29, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0240, loss: 0.0240 +2025-06-25 07:00:05,590 - pyskl - INFO - Epoch [126][1100/1281] lr: 1.564e-03, eta: 3:37:48, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0338, loss: 0.0338 +2025-06-25 07:00:54,817 - pyskl - INFO - Epoch [126][1200/1281] lr: 1.554e-03, eta: 3:37:07, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0324, loss: 0.0324 +2025-06-25 07:01:34,709 - pyskl - INFO - Saving checkpoint at 126 epochs +2025-06-25 07:02:33,409 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:02:33,484 - pyskl - INFO - +top1_acc 0.9401 +top5_acc 0.9971 +2025-06-25 07:02:33,484 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:02:33,493 - pyskl - INFO - +mean_acc 0.9196 +2025-06-25 07:02:33,495 - pyskl - INFO - Epoch(val) [126][533] top1_acc: 0.9401, top5_acc: 0.9971, mean_class_accuracy: 0.9196 +2025-06-25 07:03:54,649 - pyskl - INFO - Epoch [127][100/1281] lr: 1.536e-03, eta: 3:35:52, time: 0.811, data_time: 0.189, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0227, loss: 0.0227 +2025-06-25 07:04:43,690 - pyskl - INFO - Epoch [127][200/1281] lr: 1.527e-03, eta: 3:35:11, 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 07:05:32,913 - pyskl - INFO - Epoch [127][300/1281] lr: 1.517e-03, eta: 3:34:30, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0296, loss: 0.0296 +2025-06-25 07:06:22,162 - pyskl - INFO - Epoch [127][400/1281] lr: 1.507e-03, eta: 3:33:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0307, loss: 0.0307 +2025-06-25 07:07:11,220 - pyskl - INFO - Epoch [127][500/1281] lr: 1.497e-03, eta: 3:33:08, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0215, loss: 0.0215 +2025-06-25 07:08:00,336 - pyskl - INFO - Epoch [127][600/1281] lr: 1.488e-03, eta: 3:32:27, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0217, loss: 0.0217 +2025-06-25 07:08:32,820 - pyskl - INFO - Epoch [127][700/1281] lr: 1.478e-03, eta: 3:31:43, time: 0.325, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0244, loss: 0.0244 +2025-06-25 07:09:14,104 - pyskl - INFO - Epoch [127][800/1281] lr: 1.468e-03, eta: 3:31:00, time: 0.413, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0279, loss: 0.0279 +2025-06-25 07:09:50,231 - pyskl - INFO - Epoch [127][900/1281] lr: 1.459e-03, eta: 3:30:17, time: 0.361, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0223, loss: 0.0223 +2025-06-25 07:10:39,446 - pyskl - INFO - Epoch [127][1000/1281] lr: 1.449e-03, eta: 3:29:36, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 07:11:28,482 - pyskl - INFO - Epoch [127][1100/1281] lr: 1.440e-03, eta: 3:28:55, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 07:12:17,436 - pyskl - INFO - Epoch [127][1200/1281] lr: 1.430e-03, eta: 3:28:14, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0254, loss: 0.0254 +2025-06-25 07:12:57,742 - pyskl - INFO - Saving checkpoint at 127 epochs +2025-06-25 07:13:56,666 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:13:56,734 - pyskl - INFO - +top1_acc 0.9390 +top5_acc 0.9966 +2025-06-25 07:13:56,734 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:13:56,742 - pyskl - INFO - +mean_acc 0.9184 +2025-06-25 07:13:56,743 - pyskl - INFO - Epoch(val) [127][533] top1_acc: 0.9390, top5_acc: 0.9966, mean_class_accuracy: 0.9184 +2025-06-25 07:15:17,192 - pyskl - INFO - Epoch [128][100/1281] lr: 1.413e-03, eta: 3:26:58, time: 0.804, data_time: 0.192, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-25 07:16:06,084 - pyskl - INFO - Epoch [128][200/1281] lr: 1.404e-03, eta: 3:26:17, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0256, loss: 0.0256 +2025-06-25 07:16:55,171 - pyskl - INFO - Epoch [128][300/1281] lr: 1.394e-03, eta: 3:25:36, 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 07:17:44,443 - pyskl - INFO - Epoch [128][400/1281] lr: 1.385e-03, eta: 3:24:55, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0220, loss: 0.0220 +2025-06-25 07:18:33,686 - pyskl - INFO - Epoch [128][500/1281] lr: 1.376e-03, eta: 3:24:14, 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 07:19:21,207 - pyskl - INFO - Epoch [128][600/1281] lr: 1.366e-03, eta: 3:23:32, time: 0.475, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 07:19:58,318 - pyskl - INFO - Epoch [128][700/1281] lr: 1.357e-03, eta: 3:22:49, time: 0.371, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 07:20:34,730 - pyskl - INFO - Epoch [128][800/1281] lr: 1.348e-03, eta: 3:22:06, time: 0.364, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 07:21:13,549 - pyskl - INFO - Epoch [128][900/1281] lr: 1.339e-03, eta: 3:21:23, time: 0.388, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0167, loss: 0.0167 +2025-06-25 07:22:02,379 - pyskl - INFO - Epoch [128][1000/1281] lr: 1.329e-03, eta: 3:20:42, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 07:22:51,442 - pyskl - INFO - Epoch [128][1100/1281] lr: 1.320e-03, eta: 3:20:00, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 07:23:40,593 - pyskl - INFO - Epoch [128][1200/1281] lr: 1.311e-03, eta: 3:19:19, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0293, loss: 0.0293 +2025-06-25 07:24:21,027 - pyskl - INFO - Saving checkpoint at 128 epochs +2025-06-25 07:25:19,267 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:25:19,351 - pyskl - INFO - +top1_acc 0.9364 +top5_acc 0.9967 +2025-06-25 07:25:19,358 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:25:19,368 - pyskl - INFO - +mean_acc 0.9117 +2025-06-25 07:25:19,381 - pyskl - INFO - Epoch(val) [128][533] top1_acc: 0.9364, top5_acc: 0.9967, mean_class_accuracy: 0.9117 +2025-06-25 07:26:38,574 - pyskl - INFO - Epoch [129][100/1281] lr: 1.295e-03, eta: 3:18:03, time: 0.792, data_time: 0.188, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0252, loss: 0.0252 +2025-06-25 07:27:27,287 - pyskl - INFO - Epoch [129][200/1281] lr: 1.286e-03, eta: 3:17:22, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0255, loss: 0.0255 +2025-06-25 07:28:16,188 - pyskl - INFO - Epoch [129][300/1281] lr: 1.277e-03, eta: 3:16:41, 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 07:29:05,123 - pyskl - INFO - Epoch [129][400/1281] lr: 1.268e-03, eta: 3:16:00, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 07:29:54,136 - pyskl - INFO - Epoch [129][500/1281] lr: 1.259e-03, eta: 3:15:18, 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 07:30:41,016 - pyskl - INFO - Epoch [129][600/1281] lr: 1.250e-03, eta: 3:14:37, time: 0.469, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0244, loss: 0.0244 +2025-06-25 07:31:18,474 - pyskl - INFO - Epoch [129][700/1281] lr: 1.241e-03, eta: 3:13:54, time: 0.375, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 07:31:54,591 - pyskl - INFO - Epoch [129][800/1281] lr: 1.232e-03, eta: 3:13:10, time: 0.361, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 07:32:34,105 - pyskl - INFO - Epoch [129][900/1281] lr: 1.223e-03, eta: 3:12:27, time: 0.395, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0200, loss: 0.0200 +2025-06-25 07:33:23,390 - pyskl - INFO - Epoch [129][1000/1281] lr: 1.214e-03, eta: 3:11:46, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0221, loss: 0.0221 +2025-06-25 07:34:12,602 - pyskl - INFO - Epoch [129][1100/1281] lr: 1.206e-03, eta: 3:11:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0241, loss: 0.0241 +2025-06-25 07:35:01,952 - pyskl - INFO - Epoch [129][1200/1281] lr: 1.197e-03, eta: 3:10:24, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0262, loss: 0.0262 +2025-06-25 07:35:42,327 - pyskl - INFO - Saving checkpoint at 129 epochs +2025-06-25 07:36:41,042 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:36:41,099 - pyskl - INFO - +top1_acc 0.9397 +top5_acc 0.9975 +2025-06-25 07:36:41,099 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:36:41,105 - pyskl - INFO - +mean_acc 0.9148 +2025-06-25 07:36:41,107 - pyskl - INFO - Epoch(val) [129][533] top1_acc: 0.9397, top5_acc: 0.9975, mean_class_accuracy: 0.9148 +2025-06-25 07:38:01,466 - pyskl - INFO - Epoch [130][100/1281] lr: 1.181e-03, eta: 3:09:08, time: 0.804, data_time: 0.191, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0200, loss: 0.0200 +2025-06-25 07:38:50,487 - pyskl - INFO - Epoch [130][200/1281] lr: 1.172e-03, eta: 3:08:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0214, loss: 0.0214 +2025-06-25 07:39:39,643 - pyskl - INFO - Epoch [130][300/1281] lr: 1.164e-03, eta: 3:07:45, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 07:40:28,906 - pyskl - INFO - Epoch [130][400/1281] lr: 1.155e-03, eta: 3:07:04, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0269, loss: 0.0269 +2025-06-25 07:41:17,847 - pyskl - INFO - Epoch [130][500/1281] lr: 1.147e-03, eta: 3:06:23, 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 07:42:01,899 - pyskl - INFO - Epoch [130][600/1281] lr: 1.138e-03, eta: 3:05:41, time: 0.441, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0166, loss: 0.0166 +2025-06-25 07:42:44,866 - pyskl - INFO - Epoch [130][700/1281] lr: 1.130e-03, eta: 3:04:58, time: 0.430, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0166, loss: 0.0166 +2025-06-25 07:43:15,326 - pyskl - INFO - Epoch [130][800/1281] lr: 1.121e-03, eta: 3:04:14, time: 0.305, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0219, loss: 0.0219 +2025-06-25 07:43:56,506 - pyskl - INFO - Epoch [130][900/1281] lr: 1.113e-03, eta: 3:03:32, time: 0.412, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 07:44:45,696 - pyskl - INFO - Epoch [130][1000/1281] lr: 1.104e-03, eta: 3:02:50, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-25 07:45:34,615 - pyskl - INFO - Epoch [130][1100/1281] lr: 1.096e-03, eta: 3:02:09, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0243, loss: 0.0243 +2025-06-25 07:46:23,674 - pyskl - INFO - Epoch [130][1200/1281] lr: 1.088e-03, eta: 3:01:28, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-25 07:47:04,351 - pyskl - INFO - Saving checkpoint at 130 epochs +2025-06-25 07:48:01,912 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:48:01,968 - pyskl - INFO - +top1_acc 0.9398 +top5_acc 0.9971 +2025-06-25 07:48:01,968 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:48:01,976 - pyskl - INFO - +mean_acc 0.9159 +2025-06-25 07:48:01,978 - pyskl - INFO - Epoch(val) [130][533] top1_acc: 0.9398, top5_acc: 0.9971, mean_class_accuracy: 0.9159 +2025-06-25 07:49:22,259 - pyskl - INFO - Epoch [131][100/1281] lr: 1.072e-03, eta: 3:00:12, time: 0.803, data_time: 0.183, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 07:50:11,177 - pyskl - INFO - Epoch [131][200/1281] lr: 1.064e-03, eta: 2:59:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 07:51:00,495 - pyskl - INFO - Epoch [131][300/1281] lr: 1.056e-03, eta: 2:58:49, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0222, loss: 0.0222 +2025-06-25 07:51:49,614 - pyskl - INFO - Epoch [131][400/1281] lr: 1.048e-03, eta: 2:58:08, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 07:52:38,630 - pyskl - INFO - Epoch [131][500/1281] lr: 1.040e-03, eta: 2:57:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0214, loss: 0.0214 +2025-06-25 07:53:23,484 - pyskl - INFO - Epoch [131][600/1281] lr: 1.031e-03, eta: 2:56:44, time: 0.449, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 07:54:06,067 - pyskl - INFO - Epoch [131][700/1281] lr: 1.023e-03, eta: 2:56:02, time: 0.426, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 07:54:37,196 - pyskl - INFO - Epoch [131][800/1281] lr: 1.015e-03, eta: 2:55:18, time: 0.311, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 07:55:19,454 - pyskl - INFO - Epoch [131][900/1281] lr: 1.007e-03, eta: 2:54:35, time: 0.423, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 07:56:08,501 - pyskl - INFO - Epoch [131][1000/1281] lr: 9.992e-04, eta: 2:53:54, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 07:56:57,643 - pyskl - INFO - Epoch [131][1100/1281] lr: 9.912e-04, eta: 2:53:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 07:57:46,416 - pyskl - INFO - Epoch [131][1200/1281] lr: 9.832e-04, eta: 2:52:31, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0218, loss: 0.0218 +2025-06-25 07:58:27,050 - pyskl - INFO - Saving checkpoint at 131 epochs +2025-06-25 07:59:24,895 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:59:24,951 - pyskl - INFO - +top1_acc 0.9427 +top5_acc 0.9969 +2025-06-25 07:59:24,951 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:59:24,958 - pyskl - INFO - +mean_acc 0.9203 +2025-06-25 07:59:24,962 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_125.pth was removed +2025-06-25 07:59:25,129 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_131.pth. +2025-06-25 07:59:25,129 - pyskl - INFO - Best top1_acc is 0.9427 at 131 epoch. +2025-06-25 07:59:25,132 - pyskl - INFO - Epoch(val) [131][533] top1_acc: 0.9427, top5_acc: 0.9969, mean_class_accuracy: 0.9203 +2025-06-25 08:00:44,458 - pyskl - INFO - Epoch [132][100/1281] lr: 9.689e-04, eta: 2:51:15, time: 0.793, data_time: 0.183, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 08:01:33,733 - pyskl - INFO - Epoch [132][200/1281] lr: 9.610e-04, eta: 2:50:33, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 08:02:23,045 - pyskl - INFO - Epoch [132][300/1281] lr: 9.532e-04, eta: 2:49:52, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-25 08:03:12,369 - pyskl - INFO - Epoch [132][400/1281] lr: 9.454e-04, eta: 2:49:10, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 08:04:01,636 - pyskl - INFO - Epoch [132][500/1281] lr: 9.376e-04, eta: 2:48:29, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 08:04:45,526 - pyskl - INFO - Epoch [132][600/1281] lr: 9.298e-04, eta: 2:47:47, time: 0.439, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-25 08:05:29,475 - pyskl - INFO - Epoch [132][700/1281] lr: 9.221e-04, eta: 2:47:05, time: 0.439, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 08:05:58,563 - pyskl - INFO - Epoch [132][800/1281] lr: 9.144e-04, eta: 2:46:20, time: 0.291, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 08:06:39,614 - pyskl - INFO - Epoch [132][900/1281] lr: 9.068e-04, eta: 2:45:38, time: 0.410, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 08:07:28,875 - pyskl - INFO - Epoch [132][1000/1281] lr: 8.991e-04, eta: 2:44:56, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0169, loss: 0.0169 +2025-06-25 08:08:17,775 - pyskl - INFO - Epoch [132][1100/1281] lr: 8.915e-04, eta: 2:44:15, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 08:09:06,819 - pyskl - INFO - Epoch [132][1200/1281] lr: 8.840e-04, eta: 2:43:33, 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 08:09:46,991 - pyskl - INFO - Saving checkpoint at 132 epochs +2025-06-25 08:10:45,204 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:10:45,260 - pyskl - INFO - +top1_acc 0.9426 +top5_acc 0.9975 +2025-06-25 08:10:45,261 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:10:45,268 - pyskl - INFO - +mean_acc 0.9215 +2025-06-25 08:10:45,270 - pyskl - INFO - Epoch(val) [132][533] top1_acc: 0.9426, top5_acc: 0.9975, mean_class_accuracy: 0.9215 +2025-06-25 08:12:05,029 - pyskl - INFO - Epoch [133][100/1281] lr: 8.704e-04, eta: 2:42:17, time: 0.798, data_time: 0.182, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 08:12:54,108 - pyskl - INFO - Epoch [133][200/1281] lr: 8.629e-04, eta: 2:41:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 08:13:43,026 - pyskl - INFO - Epoch [133][300/1281] lr: 8.554e-04, eta: 2:40:54, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0200, loss: 0.0200 +2025-06-25 08:14:32,155 - pyskl - INFO - Epoch [133][400/1281] lr: 8.480e-04, eta: 2:40:12, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0140, loss: 0.0140 +2025-06-25 08:15:21,502 - pyskl - INFO - Epoch [133][500/1281] lr: 8.406e-04, eta: 2:39:31, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 08:16:05,640 - pyskl - INFO - Epoch [133][600/1281] lr: 8.333e-04, eta: 2:38:49, time: 0.441, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0172, loss: 0.0172 +2025-06-25 08:16:47,883 - pyskl - INFO - Epoch [133][700/1281] lr: 8.260e-04, eta: 2:38:06, time: 0.422, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0166, loss: 0.0166 +2025-06-25 08:17:19,167 - pyskl - INFO - Epoch [133][800/1281] lr: 8.187e-04, eta: 2:37:22, time: 0.313, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 08:17:59,846 - pyskl - INFO - Epoch [133][900/1281] lr: 8.114e-04, eta: 2:36:40, time: 0.407, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0147, loss: 0.0147 +2025-06-25 08:18:48,777 - pyskl - INFO - Epoch [133][1000/1281] lr: 8.042e-04, eta: 2:35:58, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 08:19:37,793 - pyskl - INFO - Epoch [133][1100/1281] lr: 7.970e-04, eta: 2:35:17, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0161, loss: 0.0161 +2025-06-25 08:20:26,543 - pyskl - INFO - Epoch [133][1200/1281] lr: 7.898e-04, eta: 2:34:35, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 08:21:06,728 - pyskl - INFO - Saving checkpoint at 133 epochs +2025-06-25 08:22:04,596 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:22:04,663 - pyskl - INFO - +top1_acc 0.9423 +top5_acc 0.9975 +2025-06-25 08:22:04,663 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:22:04,672 - pyskl - INFO - +mean_acc 0.9203 +2025-06-25 08:22:04,674 - pyskl - INFO - Epoch(val) [133][533] top1_acc: 0.9423, top5_acc: 0.9975, mean_class_accuracy: 0.9203 +2025-06-25 08:23:23,822 - pyskl - INFO - Epoch [134][100/1281] lr: 7.769e-04, eta: 2:33:18, time: 0.791, data_time: 0.185, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 08:24:12,777 - pyskl - INFO - Epoch [134][200/1281] lr: 7.699e-04, eta: 2:32:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 08:25:02,054 - pyskl - INFO - Epoch [134][300/1281] lr: 7.628e-04, eta: 2:31:55, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 08:25:51,031 - pyskl - INFO - Epoch [134][400/1281] lr: 7.558e-04, eta: 2:31:14, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 08:26:39,888 - pyskl - INFO - Epoch [134][500/1281] lr: 7.488e-04, eta: 2:30:32, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 08:27:25,207 - pyskl - INFO - Epoch [134][600/1281] lr: 7.419e-04, eta: 2:29:50, time: 0.453, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0147, loss: 0.0147 +2025-06-25 08:28:05,043 - pyskl - INFO - Epoch [134][700/1281] lr: 7.349e-04, eta: 2:29:07, time: 0.398, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0231, loss: 0.0231 +2025-06-25 08:28:38,883 - pyskl - INFO - Epoch [134][800/1281] lr: 7.281e-04, eta: 2:28:24, time: 0.338, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 08:29:19,826 - pyskl - INFO - Epoch [134][900/1281] lr: 7.212e-04, eta: 2:27:41, time: 0.409, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0230, loss: 0.0230 +2025-06-25 08:30:08,786 - pyskl - INFO - Epoch [134][1000/1281] lr: 7.144e-04, eta: 2:26:59, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0161, loss: 0.0161 +2025-06-25 08:30:58,071 - pyskl - INFO - Epoch [134][1100/1281] lr: 7.076e-04, eta: 2:26:18, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 08:31:47,357 - pyskl - INFO - Epoch [134][1200/1281] lr: 7.008e-04, eta: 2:25:36, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0161, loss: 0.0161 +2025-06-25 08:32:27,549 - pyskl - INFO - Saving checkpoint at 134 epochs +2025-06-25 08:33:26,055 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:33:26,111 - pyskl - INFO - +top1_acc 0.9432 +top5_acc 0.9975 +2025-06-25 08:33:26,111 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:33:26,118 - pyskl - INFO - +mean_acc 0.9214 +2025-06-25 08:33:26,122 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_131.pth was removed +2025-06-25 08:33:26,301 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_134.pth. +2025-06-25 08:33:26,302 - pyskl - INFO - Best top1_acc is 0.9432 at 134 epoch. +2025-06-25 08:33:26,305 - pyskl - INFO - Epoch(val) [134][533] top1_acc: 0.9432, top5_acc: 0.9975, mean_class_accuracy: 0.9214 +2025-06-25 08:34:45,848 - pyskl - INFO - Epoch [135][100/1281] lr: 6.887e-04, eta: 2:24:19, time: 0.795, data_time: 0.180, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 08:35:34,846 - pyskl - INFO - Epoch [135][200/1281] lr: 6.820e-04, eta: 2:23:38, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 08:36:23,646 - pyskl - INFO - Epoch [135][300/1281] lr: 6.753e-04, eta: 2:22:56, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 08:37:12,661 - pyskl - INFO - Epoch [135][400/1281] lr: 6.687e-04, eta: 2:22:14, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 08:38:01,886 - pyskl - INFO - Epoch [135][500/1281] lr: 6.622e-04, eta: 2:21:33, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 08:38:46,424 - pyskl - INFO - Epoch [135][600/1281] lr: 6.556e-04, eta: 2:20:50, time: 0.445, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0171, loss: 0.0171 +2025-06-25 08:39:29,204 - pyskl - INFO - Epoch [135][700/1281] lr: 6.491e-04, eta: 2:20:08, time: 0.428, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 08:39:59,968 - pyskl - INFO - Epoch [135][800/1281] lr: 6.426e-04, eta: 2:19:24, time: 0.308, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-25 08:40:40,487 - pyskl - INFO - Epoch [135][900/1281] lr: 6.362e-04, eta: 2:18:41, time: 0.405, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 08:41:29,386 - pyskl - INFO - Epoch [135][1000/1281] lr: 6.297e-04, eta: 2:18:00, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 08:42:18,431 - pyskl - INFO - Epoch [135][1100/1281] lr: 6.233e-04, eta: 2:17:18, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 08:43:07,596 - pyskl - INFO - Epoch [135][1200/1281] lr: 6.170e-04, eta: 2:16:36, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 08:43:48,050 - pyskl - INFO - Saving checkpoint at 135 epochs +2025-06-25 08:44:45,701 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:44:45,779 - pyskl - INFO - +top1_acc 0.9459 +top5_acc 0.9978 +2025-06-25 08:44:45,779 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:44:45,787 - pyskl - INFO - +mean_acc 0.9260 +2025-06-25 08:44:45,792 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_134.pth was removed +2025-06-25 08:44:45,988 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_135.pth. +2025-06-25 08:44:45,988 - pyskl - INFO - Best top1_acc is 0.9459 at 135 epoch. +2025-06-25 08:44:45,991 - pyskl - INFO - Epoch(val) [135][533] top1_acc: 0.9459, top5_acc: 0.9978, mean_class_accuracy: 0.9260 +2025-06-25 08:46:05,676 - pyskl - INFO - Epoch [136][100/1281] lr: 6.056e-04, eta: 2:15:20, time: 0.797, data_time: 0.182, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 08:46:54,909 - pyskl - INFO - Epoch [136][200/1281] lr: 5.993e-04, eta: 2:14:38, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0169, loss: 0.0169 +2025-06-25 08:47:44,250 - pyskl - INFO - Epoch [136][300/1281] lr: 5.931e-04, eta: 2:13:56, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0137, loss: 0.0137 +2025-06-25 08:48:33,308 - pyskl - INFO - Epoch [136][400/1281] lr: 5.868e-04, eta: 2:13:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 08:49:22,438 - pyskl - INFO - Epoch [136][500/1281] lr: 5.807e-04, eta: 2:12:33, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 08:50:08,966 - pyskl - INFO - Epoch [136][600/1281] lr: 5.745e-04, eta: 2:11:51, time: 0.465, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0146, loss: 0.0146 +2025-06-25 08:50:47,970 - pyskl - INFO - Epoch [136][700/1281] lr: 5.684e-04, eta: 2:11:08, time: 0.390, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 08:51:22,543 - pyskl - INFO - Epoch [136][800/1281] lr: 5.623e-04, eta: 2:10:24, time: 0.346, data_time: 0.001, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0207, loss: 0.0207 +2025-06-25 08:52:01,697 - pyskl - INFO - Epoch [136][900/1281] lr: 5.563e-04, eta: 2:09:42, time: 0.392, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 08:52:51,003 - pyskl - INFO - Epoch [136][1000/1281] lr: 5.503e-04, eta: 2:09:00, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0148, loss: 0.0148 +2025-06-25 08:53:40,403 - pyskl - INFO - Epoch [136][1100/1281] lr: 5.443e-04, eta: 2:08:18, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 08:54:29,575 - pyskl - INFO - Epoch [136][1200/1281] lr: 5.384e-04, eta: 2:07:36, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0171, loss: 0.0171 +2025-06-25 08:55:10,098 - pyskl - INFO - Saving checkpoint at 136 epochs +2025-06-25 08:56:08,794 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:56:08,850 - pyskl - INFO - +top1_acc 0.9436 +top5_acc 0.9977 +2025-06-25 08:56:08,850 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:56:08,857 - pyskl - INFO - +mean_acc 0.9235 +2025-06-25 08:56:08,859 - pyskl - INFO - Epoch(val) [136][533] top1_acc: 0.9436, top5_acc: 0.9977, mean_class_accuracy: 0.9235 +2025-06-25 08:57:29,059 - pyskl - INFO - Epoch [137][100/1281] lr: 5.277e-04, eta: 2:06:20, time: 0.802, data_time: 0.185, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 08:58:18,041 - pyskl - INFO - Epoch [137][200/1281] lr: 5.218e-04, eta: 2:05:38, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0149, loss: 0.0149 +2025-06-25 08:59:07,238 - pyskl - INFO - Epoch [137][300/1281] lr: 5.160e-04, eta: 2:04:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0145, loss: 0.0145 +2025-06-25 08:59:56,495 - pyskl - INFO - Epoch [137][400/1281] lr: 5.102e-04, eta: 2:04:14, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0171, loss: 0.0171 +2025-06-25 09:00:45,647 - pyskl - INFO - Epoch [137][500/1281] lr: 5.044e-04, eta: 2:03:32, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 09:01:30,867 - pyskl - INFO - Epoch [137][600/1281] lr: 4.987e-04, eta: 2:02:50, time: 0.452, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0147, loss: 0.0147 +2025-06-25 09:02:12,717 - pyskl - INFO - Epoch [137][700/1281] lr: 4.930e-04, eta: 2:02:07, time: 0.418, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0139, loss: 0.0139 +2025-06-25 09:02:44,095 - pyskl - INFO - Epoch [137][800/1281] lr: 4.873e-04, eta: 2:01:24, time: 0.314, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 09:03:23,642 - pyskl - INFO - Epoch [137][900/1281] lr: 4.817e-04, eta: 2:00:41, time: 0.395, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 09:04:12,703 - pyskl - INFO - Epoch [137][1000/1281] lr: 4.761e-04, eta: 1:59:59, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 09:05:01,681 - pyskl - INFO - Epoch [137][1100/1281] lr: 4.705e-04, eta: 1:59:17, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 09:05:50,882 - pyskl - INFO - Epoch [137][1200/1281] lr: 4.650e-04, eta: 1:58:35, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0149, loss: 0.0149 +2025-06-25 09:06:31,267 - pyskl - INFO - Saving checkpoint at 137 epochs +2025-06-25 09:07:30,033 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:07:30,103 - pyskl - INFO - +top1_acc 0.9439 +top5_acc 0.9978 +2025-06-25 09:07:30,103 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:07:30,117 - pyskl - INFO - +mean_acc 0.9223 +2025-06-25 09:07:30,119 - pyskl - INFO - Epoch(val) [137][533] top1_acc: 0.9439, top5_acc: 0.9978, mean_class_accuracy: 0.9223 +2025-06-25 09:08:50,625 - pyskl - INFO - Epoch [138][100/1281] lr: 4.550e-04, eta: 1:57:19, time: 0.805, data_time: 0.186, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 09:09:39,791 - pyskl - INFO - Epoch [138][200/1281] lr: 4.496e-04, eta: 1:56:37, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0227, loss: 0.0227 +2025-06-25 09:10:28,866 - pyskl - INFO - Epoch [138][300/1281] lr: 4.442e-04, eta: 1:55:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 09:11:18,121 - pyskl - INFO - Epoch [138][400/1281] lr: 4.388e-04, eta: 1:55:13, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 09:12:07,338 - pyskl - INFO - Epoch [138][500/1281] lr: 4.334e-04, eta: 1:54:31, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 09:12:51,745 - pyskl - INFO - Epoch [138][600/1281] lr: 4.281e-04, eta: 1:53:49, time: 0.444, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 09:13:34,285 - pyskl - INFO - Epoch [138][700/1281] lr: 4.228e-04, eta: 1:53:06, time: 0.425, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0142, loss: 0.0142 +2025-06-25 09:14:04,962 - pyskl - INFO - Epoch [138][800/1281] lr: 4.176e-04, eta: 1:52:23, time: 0.307, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 09:14:46,370 - pyskl - INFO - Epoch [138][900/1281] lr: 4.124e-04, eta: 1:51:40, time: 0.414, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 09:15:35,665 - pyskl - INFO - Epoch [138][1000/1281] lr: 4.072e-04, eta: 1:50:58, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 09:16:24,963 - pyskl - INFO - Epoch [138][1100/1281] lr: 4.020e-04, eta: 1:50:16, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0161, loss: 0.0161 +2025-06-25 09:17:13,905 - pyskl - INFO - Epoch [138][1200/1281] lr: 3.969e-04, eta: 1:49:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 09:17:54,176 - pyskl - INFO - Saving checkpoint at 138 epochs +2025-06-25 09:18:52,751 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:18:52,806 - pyskl - INFO - +top1_acc 0.9465 +top5_acc 0.9977 +2025-06-25 09:18:52,807 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:18:52,813 - pyskl - INFO - +mean_acc 0.9249 +2025-06-25 09:18:52,817 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_135.pth was removed +2025-06-25 09:18:53,129 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_138.pth. +2025-06-25 09:18:53,129 - pyskl - INFO - Best top1_acc is 0.9465 at 138 epoch. +2025-06-25 09:18:53,132 - pyskl - INFO - Epoch(val) [138][533] top1_acc: 0.9465, top5_acc: 0.9977, mean_class_accuracy: 0.9249 +2025-06-25 09:20:14,677 - pyskl - INFO - Epoch [139][100/1281] lr: 3.877e-04, eta: 1:48:17, time: 0.815, data_time: 0.186, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0144, loss: 0.0144 +2025-06-25 09:21:04,001 - pyskl - INFO - Epoch [139][200/1281] lr: 3.827e-04, eta: 1:47:35, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 09:21:53,043 - pyskl - INFO - Epoch [139][300/1281] lr: 3.777e-04, eta: 1:46:53, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0145, loss: 0.0145 +2025-06-25 09:22:41,946 - pyskl - INFO - Epoch [139][400/1281] lr: 3.727e-04, eta: 1:46:11, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 09:23:31,144 - pyskl - INFO - Epoch [139][500/1281] lr: 3.678e-04, eta: 1:45:29, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0161, loss: 0.0161 +2025-06-25 09:24:12,643 - pyskl - INFO - Epoch [139][600/1281] lr: 3.628e-04, eta: 1:44:47, time: 0.415, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0142, loss: 0.0142 +2025-06-25 09:25:01,987 - pyskl - INFO - Epoch [139][700/1281] lr: 3.580e-04, eta: 1:44:05, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0141, loss: 0.0141 +2025-06-25 09:25:26,000 - pyskl - INFO - Epoch [139][800/1281] lr: 3.531e-04, eta: 1:43:21, time: 0.240, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 09:26:08,132 - pyskl - INFO - Epoch [139][900/1281] lr: 3.483e-04, eta: 1:42:38, time: 0.421, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0141, loss: 0.0141 +2025-06-25 09:26:57,752 - pyskl - INFO - Epoch [139][1000/1281] lr: 3.436e-04, eta: 1:41:56, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 09:27:47,085 - pyskl - INFO - Epoch [139][1100/1281] lr: 3.388e-04, eta: 1:41:14, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 09:28:36,620 - pyskl - INFO - Epoch [139][1200/1281] lr: 3.341e-04, eta: 1:40:32, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 09:29:17,227 - pyskl - INFO - Saving checkpoint at 139 epochs +2025-06-25 09:30:16,241 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:30:16,302 - pyskl - INFO - +top1_acc 0.9432 +top5_acc 0.9974 +2025-06-25 09:30:16,302 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:30:16,309 - pyskl - INFO - +mean_acc 0.9204 +2025-06-25 09:30:16,312 - pyskl - INFO - Epoch(val) [139][533] top1_acc: 0.9432, top5_acc: 0.9974, mean_class_accuracy: 0.9204 +2025-06-25 09:31:36,337 - pyskl - INFO - Epoch [140][100/1281] lr: 3.257e-04, eta: 1:39:15, time: 0.800, data_time: 0.188, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 09:32:24,993 - pyskl - INFO - Epoch [140][200/1281] lr: 3.210e-04, eta: 1:38:33, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0136, loss: 0.0136 +2025-06-25 09:33:14,123 - pyskl - INFO - Epoch [140][300/1281] lr: 3.165e-04, eta: 1:37:51, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0146, loss: 0.0146 +2025-06-25 09:34:02,936 - pyskl - INFO - Epoch [140][400/1281] lr: 3.119e-04, eta: 1:37:09, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 09:34:52,043 - pyskl - INFO - Epoch [140][500/1281] lr: 3.074e-04, eta: 1:36:27, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0161, loss: 0.0161 +2025-06-25 09:35:33,539 - pyskl - INFO - Epoch [140][600/1281] lr: 3.029e-04, eta: 1:35:44, time: 0.415, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0147, loss: 0.0147 +2025-06-25 09:36:22,789 - pyskl - INFO - Epoch [140][700/1281] lr: 2.984e-04, eta: 1:35:02, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0138, loss: 0.0138 +2025-06-25 09:36:47,984 - pyskl - INFO - Epoch [140][800/1281] lr: 2.940e-04, eta: 1:34:18, time: 0.252, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0146, loss: 0.0146 +2025-06-25 09:37:31,503 - pyskl - INFO - Epoch [140][900/1281] lr: 2.896e-04, eta: 1:33:36, time: 0.435, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0150, loss: 0.0150 +2025-06-25 09:38:20,435 - pyskl - INFO - Epoch [140][1000/1281] lr: 2.853e-04, eta: 1:32:54, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0145, loss: 0.0145 +2025-06-25 09:39:09,653 - pyskl - INFO - Epoch [140][1100/1281] lr: 2.809e-04, eta: 1:32:12, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0148, loss: 0.0148 +2025-06-25 09:39:59,008 - pyskl - INFO - Epoch [140][1200/1281] lr: 2.767e-04, eta: 1:31:29, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0151, loss: 0.0151 +2025-06-25 09:40:39,073 - pyskl - INFO - Saving checkpoint at 140 epochs +2025-06-25 09:41:37,719 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:41:37,777 - pyskl - INFO - +top1_acc 0.9437 +top5_acc 0.9975 +2025-06-25 09:41:37,777 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:41:37,785 - pyskl - INFO - +mean_acc 0.9222 +2025-06-25 09:41:37,787 - pyskl - INFO - Epoch(val) [140][533] top1_acc: 0.9437, top5_acc: 0.9975, mean_class_accuracy: 0.9222 +2025-06-25 09:42:56,591 - pyskl - INFO - Epoch [141][100/1281] lr: 2.690e-04, eta: 1:30:13, time: 0.788, data_time: 0.182, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0134, loss: 0.0134 +2025-06-25 09:43:45,521 - pyskl - INFO - Epoch [141][200/1281] lr: 2.648e-04, eta: 1:29:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 09:44:34,656 - pyskl - INFO - Epoch [141][300/1281] lr: 2.606e-04, eta: 1:28:48, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 09:45:23,789 - pyskl - INFO - Epoch [141][400/1281] lr: 2.565e-04, eta: 1:28:06, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 09:46:13,035 - pyskl - INFO - Epoch [141][500/1281] lr: 2.524e-04, eta: 1:27:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 09:46:54,263 - pyskl - INFO - Epoch [141][600/1281] lr: 2.483e-04, eta: 1:26:41, time: 0.412, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 09:47:42,540 - pyskl - INFO - Epoch [141][700/1281] lr: 2.443e-04, eta: 1:25:59, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 09:48:08,127 - pyskl - INFO - Epoch [141][800/1281] lr: 2.402e-04, eta: 1:25:15, time: 0.256, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0143, loss: 0.0143 +2025-06-25 09:48:50,150 - pyskl - INFO - Epoch [141][900/1281] lr: 2.363e-04, eta: 1:24:33, time: 0.420, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0132, loss: 0.0132 +2025-06-25 09:49:39,302 - pyskl - INFO - Epoch [141][1000/1281] lr: 2.323e-04, eta: 1:23:51, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0138, loss: 0.0138 +2025-06-25 09:50:28,759 - pyskl - INFO - Epoch [141][1100/1281] lr: 2.284e-04, eta: 1:23:08, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0141, loss: 0.0141 +2025-06-25 09:51:18,009 - pyskl - INFO - Epoch [141][1200/1281] lr: 2.246e-04, eta: 1:22:26, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 09:51:58,486 - pyskl - INFO - Saving checkpoint at 141 epochs +2025-06-25 09:52:57,102 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:52:57,157 - pyskl - INFO - +top1_acc 0.9441 +top5_acc 0.9979 +2025-06-25 09:52:57,157 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:52:57,164 - pyskl - INFO - +mean_acc 0.9221 +2025-06-25 09:52:57,166 - pyskl - INFO - Epoch(val) [141][533] top1_acc: 0.9441, top5_acc: 0.9979, mean_class_accuracy: 0.9221 +2025-06-25 09:54:17,505 - pyskl - INFO - Epoch [142][100/1281] lr: 2.176e-04, eta: 1:21:09, time: 0.803, data_time: 0.181, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 09:55:06,830 - pyskl - INFO - Epoch [142][200/1281] lr: 2.139e-04, eta: 1:20:27, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0142, loss: 0.0142 +2025-06-25 09:55:56,059 - pyskl - INFO - Epoch [142][300/1281] lr: 2.101e-04, eta: 1:19:45, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 09:56:45,286 - pyskl - INFO - Epoch [142][400/1281] lr: 2.064e-04, eta: 1:19:03, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0151, loss: 0.0151 +2025-06-25 09:57:34,432 - pyskl - INFO - Epoch [142][500/1281] lr: 2.027e-04, eta: 1:18:20, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0140, loss: 0.0140 +2025-06-25 09:58:16,192 - pyskl - INFO - Epoch [142][600/1281] lr: 1.991e-04, eta: 1:17:38, time: 0.418, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0143, loss: 0.0143 +2025-06-25 09:59:02,653 - pyskl - INFO - Epoch [142][700/1281] lr: 1.954e-04, eta: 1:16:55, time: 0.465, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0140, loss: 0.0140 +2025-06-25 09:59:29,746 - pyskl - INFO - Epoch [142][800/1281] lr: 1.919e-04, eta: 1:16:12, time: 0.271, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 10:00:11,610 - pyskl - INFO - Epoch [142][900/1281] lr: 1.883e-04, eta: 1:15:29, time: 0.419, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0144, loss: 0.0144 +2025-06-25 10:01:00,701 - pyskl - INFO - Epoch [142][1000/1281] lr: 1.848e-04, eta: 1:14:47, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0148, loss: 0.0148 +2025-06-25 10:01:49,751 - pyskl - INFO - Epoch [142][1100/1281] lr: 1.813e-04, eta: 1:14:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 10:02:38,779 - pyskl - INFO - Epoch [142][1200/1281] lr: 1.779e-04, eta: 1:13:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0148, loss: 0.0148 +2025-06-25 10:03:19,100 - pyskl - INFO - Saving checkpoint at 142 epochs +2025-06-25 10:04:17,078 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:04:17,134 - pyskl - INFO - +top1_acc 0.9457 +top5_acc 0.9975 +2025-06-25 10:04:17,134 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:04:17,141 - pyskl - INFO - +mean_acc 0.9232 +2025-06-25 10:04:17,143 - pyskl - INFO - Epoch(val) [142][533] top1_acc: 0.9457, top5_acc: 0.9975, mean_class_accuracy: 0.9232 +2025-06-25 10:05:36,680 - pyskl - INFO - Epoch [143][100/1281] lr: 1.717e-04, eta: 1:12:05, time: 0.795, data_time: 0.185, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 10:06:26,197 - pyskl - INFO - Epoch [143][200/1281] lr: 1.683e-04, eta: 1:11:23, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0139, loss: 0.0139 +2025-06-25 10:07:15,470 - pyskl - INFO - Epoch [143][300/1281] lr: 1.650e-04, eta: 1:10:41, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 10:08:04,551 - pyskl - INFO - Epoch [143][400/1281] lr: 1.617e-04, eta: 1:09:59, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0149, loss: 0.0149 +2025-06-25 10:08:53,744 - pyskl - INFO - Epoch [143][500/1281] lr: 1.585e-04, eta: 1:09:16, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0146, loss: 0.0146 +2025-06-25 10:09:36,395 - pyskl - INFO - Epoch [143][600/1281] lr: 1.552e-04, eta: 1:08:34, time: 0.427, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 10:10:23,192 - pyskl - INFO - Epoch [143][700/1281] lr: 1.520e-04, eta: 1:07:51, time: 0.468, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0137, loss: 0.0137 +2025-06-25 10:10:50,545 - pyskl - INFO - Epoch [143][800/1281] lr: 1.489e-04, eta: 1:07:08, time: 0.274, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0140, loss: 0.0140 +2025-06-25 10:11:33,019 - pyskl - INFO - Epoch [143][900/1281] lr: 1.457e-04, eta: 1:06:25, time: 0.425, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0138, loss: 0.0138 +2025-06-25 10:12:22,233 - pyskl - INFO - Epoch [143][1000/1281] lr: 1.426e-04, eta: 1:05:43, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0143, loss: 0.0143 +2025-06-25 10:13:11,530 - pyskl - INFO - Epoch [143][1100/1281] lr: 1.396e-04, eta: 1:05:01, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 10:14:00,697 - pyskl - INFO - Epoch [143][1200/1281] lr: 1.366e-04, eta: 1:04:18, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0148, loss: 0.0148 +2025-06-25 10:14:41,256 - pyskl - INFO - Saving checkpoint at 143 epochs +2025-06-25 10:15:39,761 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:15:39,817 - pyskl - INFO - +top1_acc 0.9463 +top5_acc 0.9979 +2025-06-25 10:15:39,817 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:15:39,824 - pyskl - INFO - +mean_acc 0.9243 +2025-06-25 10:15:39,826 - pyskl - INFO - Epoch(val) [143][533] top1_acc: 0.9463, top5_acc: 0.9979, mean_class_accuracy: 0.9243 +2025-06-25 10:16:59,490 - pyskl - INFO - Epoch [144][100/1281] lr: 1.312e-04, eta: 1:03:01, time: 0.797, data_time: 0.185, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 10:17:48,632 - pyskl - INFO - Epoch [144][200/1281] lr: 1.282e-04, eta: 1:02:19, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0143, loss: 0.0143 +2025-06-25 10:18:37,867 - pyskl - INFO - Epoch [144][300/1281] lr: 1.253e-04, eta: 1:01:36, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0150, loss: 0.0150 +2025-06-25 10:19:26,946 - pyskl - INFO - Epoch [144][400/1281] lr: 1.224e-04, eta: 1:00:54, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 10:20:16,015 - pyskl - INFO - Epoch [144][500/1281] lr: 1.196e-04, eta: 1:00:12, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0138, loss: 0.0138 +2025-06-25 10:20:57,979 - pyskl - INFO - Epoch [144][600/1281] lr: 1.168e-04, eta: 0:59:29, time: 0.420, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0151, loss: 0.0151 +2025-06-25 10:21:45,268 - pyskl - INFO - Epoch [144][700/1281] lr: 1.140e-04, eta: 0:58:47, time: 0.473, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0143, loss: 0.0143 +2025-06-25 10:22:11,308 - pyskl - INFO - Epoch [144][800/1281] lr: 1.113e-04, eta: 0:58:03, time: 0.260, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0144, loss: 0.0144 +2025-06-25 10:22:54,209 - pyskl - INFO - Epoch [144][900/1281] lr: 1.086e-04, eta: 0:57:21, time: 0.429, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0166, loss: 0.0166 +2025-06-25 10:23:43,471 - pyskl - INFO - Epoch [144][1000/1281] lr: 1.059e-04, eta: 0:56:38, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 10:24:32,657 - pyskl - INFO - Epoch [144][1100/1281] lr: 1.033e-04, eta: 0:55:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 10:25:21,840 - pyskl - INFO - Epoch [144][1200/1281] lr: 1.007e-04, eta: 0:55:13, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0134, loss: 0.0134 +2025-06-25 10:26:02,438 - pyskl - INFO - Saving checkpoint at 144 epochs +2025-06-25 10:27:00,505 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:27:00,561 - pyskl - INFO - +top1_acc 0.9447 +top5_acc 0.9975 +2025-06-25 10:27:00,561 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:27:00,568 - pyskl - INFO - +mean_acc 0.9227 +2025-06-25 10:27:00,570 - pyskl - INFO - Epoch(val) [144][533] top1_acc: 0.9447, top5_acc: 0.9975, mean_class_accuracy: 0.9227 +2025-06-25 10:28:19,509 - pyskl - INFO - Epoch [145][100/1281] lr: 9.605e-05, eta: 0:53:56, time: 0.789, data_time: 0.180, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0144, loss: 0.0144 +2025-06-25 10:29:08,099 - pyskl - INFO - Epoch [145][200/1281] lr: 9.353e-05, eta: 0:53:14, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 10:29:57,419 - pyskl - INFO - Epoch [145][300/1281] lr: 9.106e-05, eta: 0:52:31, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0142, loss: 0.0142 +2025-06-25 10:30:46,323 - pyskl - INFO - Epoch [145][400/1281] lr: 8.861e-05, eta: 0:51:49, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 10:31:35,527 - pyskl - INFO - Epoch [145][500/1281] lr: 8.620e-05, eta: 0:51:07, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 10:32:19,529 - pyskl - INFO - Epoch [145][600/1281] lr: 8.382e-05, eta: 0:50:24, time: 0.440, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 10:33:03,158 - pyskl - INFO - Epoch [145][700/1281] lr: 8.147e-05, eta: 0:49:41, time: 0.436, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0141, loss: 0.0141 +2025-06-25 10:33:32,589 - pyskl - INFO - Epoch [145][800/1281] lr: 7.916e-05, eta: 0:48:58, time: 0.294, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0147, loss: 0.0147 +2025-06-25 10:34:14,568 - pyskl - INFO - Epoch [145][900/1281] lr: 7.688e-05, eta: 0:48:15, time: 0.420, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 10:35:03,600 - pyskl - INFO - Epoch [145][1000/1281] lr: 7.463e-05, eta: 0:47:33, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0141, loss: 0.0141 +2025-06-25 10:35:52,691 - pyskl - INFO - Epoch [145][1100/1281] lr: 7.242e-05, eta: 0:46:51, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 10:36:41,866 - pyskl - INFO - Epoch [145][1200/1281] lr: 7.024e-05, eta: 0:46:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0133, loss: 0.0133 +2025-06-25 10:37:22,151 - pyskl - INFO - Saving checkpoint at 145 epochs +2025-06-25 10:38:20,169 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:38:20,224 - pyskl - INFO - +top1_acc 0.9445 +top5_acc 0.9978 +2025-06-25 10:38:20,224 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:38:20,231 - pyskl - INFO - +mean_acc 0.9226 +2025-06-25 10:38:20,233 - pyskl - INFO - Epoch(val) [145][533] top1_acc: 0.9445, top5_acc: 0.9978, mean_class_accuracy: 0.9226 +2025-06-25 10:39:39,089 - pyskl - INFO - Epoch [146][100/1281] lr: 6.638e-05, eta: 0:44:51, time: 0.789, data_time: 0.180, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 10:40:28,437 - pyskl - INFO - Epoch [146][200/1281] lr: 6.429e-05, eta: 0:44:08, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0137, loss: 0.0137 +2025-06-25 10:41:17,546 - pyskl - INFO - Epoch [146][300/1281] lr: 6.224e-05, eta: 0:43:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0143, loss: 0.0143 +2025-06-25 10:42:06,625 - pyskl - INFO - Epoch [146][400/1281] lr: 6.022e-05, eta: 0:42:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 10:42:55,814 - pyskl - INFO - Epoch [146][500/1281] lr: 5.823e-05, eta: 0:42:01, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0147, loss: 0.0147 +2025-06-25 10:43:40,367 - pyskl - INFO - Epoch [146][600/1281] lr: 5.628e-05, eta: 0:41:18, time: 0.446, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0141, loss: 0.0141 +2025-06-25 10:44:23,639 - pyskl - INFO - Epoch [146][700/1281] lr: 5.436e-05, eta: 0:40:36, time: 0.433, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0149, loss: 0.0149 +2025-06-25 10:44:54,080 - pyskl - INFO - Epoch [146][800/1281] lr: 5.247e-05, eta: 0:39:53, time: 0.304, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0161, loss: 0.0161 +2025-06-25 10:45:35,643 - pyskl - INFO - Epoch [146][900/1281] lr: 5.061e-05, eta: 0:39:10, time: 0.416, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 10:46:25,301 - pyskl - INFO - Epoch [146][1000/1281] lr: 4.879e-05, eta: 0:38:27, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 10:47:14,436 - pyskl - INFO - Epoch [146][1100/1281] lr: 4.701e-05, eta: 0:37:45, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0143, loss: 0.0143 +2025-06-25 10:48:03,663 - pyskl - INFO - Epoch [146][1200/1281] lr: 4.525e-05, eta: 0:37:02, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0134, loss: 0.0134 +2025-06-25 10:48:44,146 - pyskl - INFO - Saving checkpoint at 146 epochs +2025-06-25 10:49:42,229 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:49:42,284 - pyskl - INFO - +top1_acc 0.9434 +top5_acc 0.9980 +2025-06-25 10:49:42,285 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:49:42,292 - pyskl - INFO - +mean_acc 0.9214 +2025-06-25 10:49:42,294 - pyskl - INFO - Epoch(val) [146][533] top1_acc: 0.9434, top5_acc: 0.9980, mean_class_accuracy: 0.9214 +2025-06-25 10:51:01,205 - pyskl - INFO - Epoch [147][100/1281] lr: 4.216e-05, eta: 0:35:45, time: 0.789, data_time: 0.181, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0139, loss: 0.0139 +2025-06-25 10:51:50,105 - pyskl - INFO - Epoch [147][200/1281] lr: 4.050e-05, eta: 0:35:02, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 10:52:38,957 - pyskl - INFO - Epoch [147][300/1281] lr: 3.887e-05, eta: 0:34:20, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 10:53:28,221 - pyskl - INFO - Epoch [147][400/1281] lr: 3.728e-05, eta: 0:33:37, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 10:54:17,400 - pyskl - INFO - Epoch [147][500/1281] lr: 3.572e-05, eta: 0:32:55, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0136, loss: 0.0136 +2025-06-25 10:55:01,769 - pyskl - INFO - Epoch [147][600/1281] lr: 3.419e-05, eta: 0:32:12, time: 0.444, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0150, loss: 0.0150 +2025-06-25 10:55:42,541 - pyskl - INFO - Epoch [147][700/1281] lr: 3.270e-05, eta: 0:31:29, time: 0.408, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0138, loss: 0.0138 +2025-06-25 10:56:14,814 - pyskl - INFO - Epoch [147][800/1281] lr: 3.124e-05, eta: 0:30:46, time: 0.323, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 10:56:56,418 - pyskl - INFO - Epoch [147][900/1281] lr: 2.981e-05, eta: 0:30:04, time: 0.416, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0142, loss: 0.0142 +2025-06-25 10:57:45,785 - pyskl - INFO - Epoch [147][1000/1281] lr: 2.842e-05, eta: 0:29:21, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 10:58:35,037 - pyskl - INFO - Epoch [147][1100/1281] lr: 2.706e-05, eta: 0:28:39, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0134, loss: 0.0134 +2025-06-25 10:59:24,207 - pyskl - INFO - Epoch [147][1200/1281] lr: 2.573e-05, eta: 0:27:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0138, loss: 0.0138 +2025-06-25 11:00:04,402 - pyskl - INFO - Saving checkpoint at 147 epochs +2025-06-25 11:01:02,292 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:01:02,359 - pyskl - INFO - +top1_acc 0.9430 +top5_acc 0.9981 +2025-06-25 11:01:02,359 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:01:02,367 - pyskl - INFO - +mean_acc 0.9204 +2025-06-25 11:01:02,369 - pyskl - INFO - Epoch(val) [147][533] top1_acc: 0.9430, top5_acc: 0.9981, mean_class_accuracy: 0.9204 +2025-06-25 11:02:21,619 - pyskl - INFO - Epoch [148][100/1281] lr: 2.341e-05, eta: 0:26:39, time: 0.792, data_time: 0.182, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0149, loss: 0.0149 +2025-06-25 11:03:10,507 - pyskl - INFO - Epoch [148][200/1281] lr: 2.218e-05, eta: 0:25:56, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0145, loss: 0.0145 +2025-06-25 11:04:00,101 - pyskl - INFO - Epoch [148][300/1281] lr: 2.098e-05, eta: 0:25:13, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0132, loss: 0.0132 +2025-06-25 11:04:49,770 - pyskl - INFO - Epoch [148][400/1281] lr: 1.981e-05, eta: 0:24:31, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0151, loss: 0.0151 +2025-06-25 11:05:38,760 - pyskl - INFO - Epoch [148][500/1281] lr: 1.868e-05, eta: 0:23:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 11:06:23,095 - pyskl - INFO - Epoch [148][600/1281] lr: 1.758e-05, eta: 0:23:06, time: 0.443, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 11:07:07,519 - pyskl - INFO - Epoch [148][700/1281] lr: 1.651e-05, eta: 0:22:23, time: 0.444, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 11:07:36,378 - pyskl - INFO - Epoch [148][800/1281] lr: 1.548e-05, eta: 0:21:40, time: 0.289, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0148, loss: 0.0148 +2025-06-25 11:08:17,720 - pyskl - INFO - Epoch [148][900/1281] lr: 1.448e-05, eta: 0:20:57, time: 0.413, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0149, loss: 0.0149 +2025-06-25 11:09:06,814 - pyskl - INFO - Epoch [148][1000/1281] lr: 1.351e-05, eta: 0:20:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0132, loss: 0.0132 +2025-06-25 11:09:56,120 - pyskl - INFO - Epoch [148][1100/1281] lr: 1.258e-05, eta: 0:19:32, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0139, loss: 0.0139 +2025-06-25 11:10:45,290 - pyskl - INFO - Epoch [148][1200/1281] lr: 1.168e-05, eta: 0:18:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0135, loss: 0.0135 +2025-06-25 11:11:25,682 - pyskl - INFO - Saving checkpoint at 148 epochs +2025-06-25 11:12:23,692 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:12:23,759 - pyskl - INFO - +top1_acc 0.9441 +top5_acc 0.9975 +2025-06-25 11:12:23,759 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:12:23,767 - pyskl - INFO - +mean_acc 0.9215 +2025-06-25 11:12:23,769 - pyskl - INFO - Epoch(val) [148][533] top1_acc: 0.9441, top5_acc: 0.9975, mean_class_accuracy: 0.9215 +2025-06-25 11:13:43,314 - pyskl - INFO - Epoch [149][100/1281] lr: 1.013e-05, eta: 0:17:32, time: 0.795, data_time: 0.183, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0145, loss: 0.0145 +2025-06-25 11:14:32,515 - pyskl - INFO - Epoch [149][200/1281] lr: 9.328e-06, eta: 0:16:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 11:15:22,056 - pyskl - INFO - Epoch [149][300/1281] lr: 8.555e-06, eta: 0:16:07, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 11:16:11,217 - pyskl - INFO - Epoch [149][400/1281] lr: 7.816e-06, eta: 0:15:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0169, loss: 0.0169 +2025-06-25 11:17:00,743 - pyskl - INFO - Epoch [149][500/1281] lr: 7.110e-06, eta: 0:14:41, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0150, loss: 0.0150 +2025-06-25 11:17:46,059 - pyskl - INFO - Epoch [149][600/1281] lr: 6.437e-06, eta: 0:13:58, time: 0.453, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0140, loss: 0.0140 +2025-06-25 11:18:28,003 - pyskl - INFO - Epoch [149][700/1281] lr: 5.798e-06, eta: 0:13:16, time: 0.419, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0137, loss: 0.0137 +2025-06-25 11:18:59,660 - pyskl - INFO - Epoch [149][800/1281] lr: 5.192e-06, eta: 0:12:33, time: 0.317, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0150, loss: 0.0150 +2025-06-25 11:19:39,543 - pyskl - INFO - Epoch [149][900/1281] lr: 4.620e-06, eta: 0:11:50, time: 0.399, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0143, loss: 0.0143 +2025-06-25 11:20:28,431 - pyskl - INFO - Epoch [149][1000/1281] lr: 4.081e-06, eta: 0:11:07, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0145, loss: 0.0145 +2025-06-25 11:21:17,817 - pyskl - INFO - Epoch [149][1100/1281] lr: 3.576e-06, eta: 0:10:25, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0149, loss: 0.0149 +2025-06-25 11:22:07,167 - pyskl - INFO - Epoch [149][1200/1281] lr: 3.104e-06, eta: 0:09:42, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0135, loss: 0.0135 +2025-06-25 11:22:47,490 - pyskl - INFO - Saving checkpoint at 149 epochs +2025-06-25 11:23:45,638 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:23:45,706 - pyskl - INFO - +top1_acc 0.9440 +top5_acc 0.9975 +2025-06-25 11:23:45,706 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:23:45,714 - pyskl - INFO - +mean_acc 0.9228 +2025-06-25 11:23:45,717 - pyskl - INFO - Epoch(val) [149][533] top1_acc: 0.9440, top5_acc: 0.9975, mean_class_accuracy: 0.9228 +2025-06-25 11:25:03,706 - pyskl - INFO - Epoch [150][100/1281] lr: 2.334e-06, eta: 0:08:25, time: 0.780, data_time: 0.177, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0146, loss: 0.0146 +2025-06-25 11:25:52,834 - pyskl - INFO - Epoch [150][200/1281] lr: 1.956e-06, eta: 0:07:42, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 11:26:41,978 - pyskl - INFO - Epoch [150][300/1281] lr: 1.611e-06, eta: 0:06:59, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0146, loss: 0.0146 +2025-06-25 11:27:31,071 - pyskl - INFO - Epoch [150][400/1281] lr: 1.300e-06, eta: 0:06:16, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0135, loss: 0.0135 +2025-06-25 11:28:20,700 - pyskl - INFO - Epoch [150][500/1281] lr: 1.022e-06, eta: 0:05:34, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0147, loss: 0.0147 +2025-06-25 11:29:08,008 - pyskl - INFO - Epoch [150][600/1281] lr: 7.771e-07, eta: 0:04:51, time: 0.473, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 11:29:46,455 - pyskl - INFO - Epoch [150][700/1281] lr: 5.659e-07, eta: 0:04:08, time: 0.384, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 11:30:21,950 - pyskl - INFO - Epoch [150][800/1281] lr: 3.881e-07, eta: 0:03:25, time: 0.355, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 11:31:00,393 - pyskl - INFO - Epoch [150][900/1281] lr: 2.438e-07, eta: 0:02:42, time: 0.384, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0145, loss: 0.0145 +2025-06-25 11:31:49,555 - pyskl - INFO - Epoch [150][1000/1281] lr: 1.329e-07, eta: 0:02:00, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0149, loss: 0.0149 +2025-06-25 11:32:38,532 - pyskl - INFO - Epoch [150][1100/1281] lr: 5.534e-08, eta: 0:01:17, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0131, loss: 0.0131 +2025-06-25 11:33:27,553 - pyskl - INFO - Epoch [150][1200/1281] lr: 1.123e-08, eta: 0:00:34, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 11:34:07,966 - pyskl - INFO - Saving checkpoint at 150 epochs +2025-06-25 11:35:06,114 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:35:06,177 - pyskl - INFO - +top1_acc 0.9457 +top5_acc 0.9977 +2025-06-25 11:35:06,178 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:35:06,187 - pyskl - INFO - +mean_acc 0.9237 +2025-06-25 11:35:06,189 - pyskl - INFO - Epoch(val) [150][533] top1_acc: 0.9457, top5_acc: 0.9977, mean_class_accuracy: 0.9237 +2025-06-25 11:35:10,667 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-06-25 11:42:51,090 - pyskl - INFO - Testing results of the last checkpoint +2025-06-25 11:42:51,091 - pyskl - INFO - top1_acc: 0.9455 +2025-06-25 11:42:51,091 - pyskl - INFO - top5_acc: 0.9977 +2025-06-25 11:42:51,091 - pyskl - INFO - mean_class_accuracy: 0.9236 +2025-06-25 11:42:51,091 - pyskl - INFO - load checkpoint from local path: ./work_dirs/test_aclnet/finegym/b_1/best_top1_acc_epoch_138.pth +2025-06-25 11:50:26,448 - pyskl - INFO - Testing results of the best checkpoint +2025-06-25 11:50:26,448 - pyskl - INFO - top1_acc: 0.9481 +2025-06-25 11:50:26,448 - pyskl - INFO - top5_acc: 0.9977 +2025-06-25 11:50:26,448 - pyskl - INFO - mean_class_accuracy: 0.9274