diff --git "a/finegym/bm/20250624_101409.log" "b/finegym/bm/20250624_101409.log" new file mode 100644--- /dev/null +++ "b/finegym/bm/20250624_101409.log" @@ -0,0 +1,3489 @@ +2025-06-24 10:14:09,119 - pyskl - INFO - Environment info: +------------------------------------------------------------ +sys.platform: linux +Python: 3.7.11 (default, Jul 27 2021, 14:32:16) [GCC 7.5.0] +CUDA available: True +GPU 0: Tesla V100-PCIE-32GB +CUDA_HOME: /usr/local/cuda-11.7 +NVCC: Cuda compilation tools, release 11.7, V11.7.64 +GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0 +PyTorch: 1.11.0 +PyTorch compiling details: PyTorch built with: + - GCC 7.3 + - C++ Version: 201402 + - Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications + - Intel(R) MKL-DNN v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e) + - OpenMP 201511 (a.k.a. OpenMP 4.5) + - LAPACK is enabled (usually provided by MKL) + - NNPACK is enabled + - CPU capability usage: AVX2 + - CUDA Runtime 11.3 + - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_37,code=compute_37 + - CuDNN 8.2 + - Magma 2.5.2 + - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, + +TorchVision: 0.12.0 +OpenCV: 4.8.0 +MMCV: 1.5.0 +MMCV Compiler: GCC 7.3 +MMCV CUDA Compiler: 11.3 +pyskl: 0.1.0+ +------------------------------------------------------------ + +2025-06-24 10:14:09,373 - pyskl - INFO - Config: modality = 'bm' +graph = 'coco_new' +work_dir = './work_dirs/test_aclnet/finegym/bm' +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=['bm']), + 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=['bm']), + 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=['bm']), + 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=['bm']), + 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=['bm']), + 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=['bm']), + dict(type='FormatGCNInput', num_person=2), + dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]), + dict(type='ToTensor', keys=['keypoint']) + ], + split='val')) +optimizer = dict( + type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True) +optimizer_config = dict(grad_clip=None) +lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False) +total_epochs = 150 +checkpoint_config = dict(interval=1) +evaluation = dict( + interval=1, metrics=['top_k_accuracy', 'mean_class_accuracy'], topk=(1, 5)) +log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')]) +dist_params = dict(backend='nccl') +gpu_ids = range(0, 1) + +2025-06-24 10:14:09,374 - pyskl - INFO - Set random seed to 1645946785, deterministic: False +2025-06-24 10:14:11,003 - pyskl - INFO - 20484 videos remain after valid thresholding +2025-06-24 10:14:17,191 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-06-24 10:14:17,192 - pyskl - INFO - Start running, host: lhd@zkyd, work_dir: /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm +2025-06-24 10:14:17,192 - pyskl - INFO - Hooks will be executed in the following order: +before_run: +(VERY_HIGH ) CosineAnnealingLrUpdaterHook +(NORMAL ) CustomCheckpointHook +(NORMAL ) DistEvalHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_train_epoch: +(VERY_HIGH ) CosineAnnealingLrUpdaterHook +(NORMAL ) DistSamplerSeedHook +(NORMAL ) DistEvalHook +(LOW ) IterTimerHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_train_iter: +(VERY_HIGH ) CosineAnnealingLrUpdaterHook +(NORMAL ) DistEvalHook +(LOW ) IterTimerHook + -------------------- +after_train_iter: +(ABOVE_NORMAL) OptimizerHook +(NORMAL ) CustomCheckpointHook +(NORMAL ) DistEvalHook +(LOW ) IterTimerHook +(VERY_LOW ) TextLoggerHook + -------------------- +after_train_epoch: +(NORMAL ) CustomCheckpointHook +(NORMAL ) DistEvalHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_val_epoch: +(NORMAL ) DistSamplerSeedHook +(LOW ) IterTimerHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_val_iter: +(LOW ) IterTimerHook + -------------------- +after_val_iter: +(LOW ) IterTimerHook + -------------------- +after_val_epoch: +(VERY_LOW ) TextLoggerHook + -------------------- +after_run: +(VERY_LOW ) TextLoggerHook + -------------------- +2025-06-24 10:14:17,192 - pyskl - INFO - workflow: [('train', 1)], max: 150 epochs +2025-06-24 10:14:17,192 - pyskl - INFO - Checkpoints will be saved to /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm by HardDiskBackend. +2025-06-24 10:15:19,744 - pyskl - INFO - Epoch [1][100/1281] lr: 2.500e-02, eta: 1 day, 9:22:01, time: 0.625, data_time: 0.203, memory: 4082, top1_acc: 0.0669, top5_acc: 0.2487, loss_cls: 4.5240, loss: 4.5240 +2025-06-24 10:16:01,247 - pyskl - INFO - Epoch [1][200/1281] lr: 2.500e-02, eta: 1 day, 3:44:17, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.0794, top5_acc: 0.3038, loss_cls: 4.5996, loss: 4.5996 +2025-06-24 10:16:42,927 - pyskl - INFO - Epoch [1][300/1281] lr: 2.500e-02, eta: 1 day, 1:53:11, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.1000, top5_acc: 0.3331, loss_cls: 4.4750, loss: 4.4750 +2025-06-24 10:17:24,639 - pyskl - INFO - Epoch [1][400/1281] lr: 2.500e-02, eta: 1 day, 0:57:32, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.1100, top5_acc: 0.3625, loss_cls: 4.3255, loss: 4.3255 +2025-06-24 10:18:06,262 - pyskl - INFO - Epoch [1][500/1281] lr: 2.500e-02, eta: 1 day, 0:23:18, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.1219, top5_acc: 0.3906, loss_cls: 4.1821, loss: 4.1821 +2025-06-24 10:18:47,693 - pyskl - INFO - Epoch [1][600/1281] lr: 2.500e-02, eta: 23:59:13, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.1300, top5_acc: 0.4219, loss_cls: 4.0994, loss: 4.0994 +2025-06-24 10:19:29,002 - pyskl - INFO - Epoch [1][700/1281] lr: 2.500e-02, eta: 23:41:16, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.1506, top5_acc: 0.4688, loss_cls: 3.8900, loss: 3.8900 +2025-06-24 10:20:10,657 - pyskl - INFO - Epoch [1][800/1281] lr: 2.500e-02, eta: 23:29:01, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.1900, top5_acc: 0.5244, loss_cls: 3.6852, loss: 3.6852 +2025-06-24 10:20:52,065 - pyskl - INFO - Epoch [1][900/1281] lr: 2.500e-02, eta: 23:18:27, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.2150, top5_acc: 0.5769, loss_cls: 3.4612, loss: 3.4612 +2025-06-24 10:21:33,553 - pyskl - INFO - Epoch [1][1000/1281] lr: 2.500e-02, eta: 23:10:07, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.2662, top5_acc: 0.6200, loss_cls: 3.3059, loss: 3.3059 +2025-06-24 10:22:06,568 - pyskl - INFO - Epoch [1][1100/1281] lr: 2.500e-02, eta: 22:38:39, time: 0.330, data_time: 0.000, memory: 4082, top1_acc: 0.2619, top5_acc: 0.6344, loss_cls: 3.2041, loss: 3.2041 +2025-06-24 10:22:41,935 - pyskl - INFO - Epoch [1][1200/1281] lr: 2.500e-02, eta: 22:18:34, time: 0.354, data_time: 0.000, memory: 4082, top1_acc: 0.3131, top5_acc: 0.6900, loss_cls: 2.9680, loss: 2.9680 +2025-06-24 10:23:14,095 - pyskl - INFO - Saving checkpoint at 1 epochs +2025-06-24 10:24:25,722 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:24:25,784 - pyskl - INFO - +top1_acc 0.2892 +top5_acc 0.6709 +2025-06-24 10:24:25,784 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:24:25,791 - pyskl - INFO - +mean_acc 0.1463 +2025-06-24 10:24:25,975 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_1.pth. +2025-06-24 10:24:25,976 - pyskl - INFO - Best top1_acc is 0.2892 at 1 epoch. +2025-06-24 10:24:25,979 - pyskl - INFO - Epoch(val) [1][533] top1_acc: 0.2892, top5_acc: 0.6709, mean_class_accuracy: 0.1463 +2025-06-24 10:25:27,776 - pyskl - INFO - Epoch [2][100/1281] lr: 2.500e-02, eta: 21:44:17, time: 0.618, data_time: 0.199, memory: 4082, top1_acc: 0.3294, top5_acc: 0.7456, loss_cls: 2.8346, loss: 2.8346 +2025-06-24 10:26:09,180 - pyskl - INFO - Epoch [2][200/1281] lr: 2.500e-02, eta: 21:44:25, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.3319, top5_acc: 0.7431, loss_cls: 2.7833, loss: 2.7833 +2025-06-24 10:26:50,683 - pyskl - INFO - Epoch [2][300/1281] lr: 2.500e-02, eta: 21:44:38, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.3794, top5_acc: 0.7869, loss_cls: 2.6001, loss: 2.6001 +2025-06-24 10:27:32,159 - pyskl - INFO - Epoch [2][400/1281] lr: 2.500e-02, eta: 21:44:43, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.3937, top5_acc: 0.7900, loss_cls: 2.5469, loss: 2.5469 +2025-06-24 10:28:13,579 - pyskl - INFO - Epoch [2][500/1281] lr: 2.499e-02, eta: 21:44:35, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.3931, top5_acc: 0.7937, loss_cls: 2.4895, loss: 2.4895 +2025-06-24 10:28:55,224 - pyskl - INFO - Epoch [2][600/1281] lr: 2.499e-02, eta: 21:44:48, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.4100, top5_acc: 0.8094, loss_cls: 2.4359, loss: 2.4359 +2025-06-24 10:29:36,641 - pyskl - INFO - Epoch [2][700/1281] lr: 2.499e-02, eta: 21:44:32, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.4031, top5_acc: 0.8169, loss_cls: 2.3992, loss: 2.3992 +2025-06-24 10:30:18,137 - pyskl - INFO - Epoch [2][800/1281] lr: 2.499e-02, eta: 21:44:22, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.4163, top5_acc: 0.8275, loss_cls: 2.3293, loss: 2.3293 +2025-06-24 10:30:59,582 - pyskl - INFO - Epoch [2][900/1281] lr: 2.499e-02, eta: 21:44:04, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.4625, top5_acc: 0.8644, loss_cls: 2.1930, loss: 2.1930 +2025-06-24 10:31:41,029 - pyskl - INFO - Epoch [2][1000/1281] lr: 2.499e-02, eta: 21:43:44, time: 0.414, data_time: 0.001, memory: 4082, top1_acc: 0.4244, top5_acc: 0.8413, loss_cls: 2.2607, loss: 2.2607 +2025-06-24 10:32:13,483 - pyskl - INFO - Epoch [2][1100/1281] lr: 2.499e-02, eta: 21:31:26, time: 0.325, data_time: 0.001, memory: 4082, top1_acc: 0.4612, top5_acc: 0.8650, loss_cls: 2.1832, loss: 2.1832 +2025-06-24 10:32:49,504 - pyskl - INFO - Epoch [2][1200/1281] lr: 2.499e-02, eta: 21:24:37, time: 0.360, data_time: 0.000, memory: 4082, top1_acc: 0.4919, top5_acc: 0.8650, loss_cls: 2.1198, loss: 2.1198 +2025-06-24 10:33:20,938 - pyskl - INFO - Saving checkpoint at 2 epochs +2025-06-24 10:34:31,930 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:34:31,985 - pyskl - INFO - +top1_acc 0.4627 +top5_acc 0.8528 +2025-06-24 10:34:31,985 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:34:31,993 - pyskl - INFO - +mean_acc 0.2624 +2025-06-24 10:34:31,999 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_1.pth was removed +2025-06-24 10:34:32,231 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_2.pth. +2025-06-24 10:34:32,231 - pyskl - INFO - Best top1_acc is 0.4627 at 2 epoch. +2025-06-24 10:34:32,235 - pyskl - INFO - Epoch(val) [2][533] top1_acc: 0.4627, top5_acc: 0.8528, mean_class_accuracy: 0.2624 +2025-06-24 10:35:33,610 - pyskl - INFO - Epoch [3][100/1281] lr: 2.499e-02, eta: 21:08:56, time: 0.614, data_time: 0.200, memory: 4082, top1_acc: 0.5044, top5_acc: 0.8806, loss_cls: 2.0531, loss: 2.0531 +2025-06-24 10:36:15,118 - pyskl - INFO - Epoch [3][200/1281] lr: 2.499e-02, eta: 21:09:47, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.4994, top5_acc: 0.8756, loss_cls: 2.0645, loss: 2.0645 +2025-06-24 10:36:56,525 - pyskl - INFO - Epoch [3][300/1281] lr: 2.499e-02, eta: 21:10:25, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.5012, top5_acc: 0.8919, loss_cls: 1.9961, loss: 1.9961 +2025-06-24 10:37:37,866 - pyskl - INFO - Epoch [3][400/1281] lr: 2.499e-02, eta: 21:10:53, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.4969, top5_acc: 0.9094, loss_cls: 1.9395, loss: 1.9395 +2025-06-24 10:38:19,239 - pyskl - INFO - Epoch [3][500/1281] lr: 2.498e-02, eta: 21:11:18, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.5425, top5_acc: 0.9062, loss_cls: 1.9004, loss: 1.9004 +2025-06-24 10:39:00,604 - pyskl - INFO - Epoch [3][600/1281] lr: 2.498e-02, eta: 21:11:39, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.5181, top5_acc: 0.9056, loss_cls: 1.9077, loss: 1.9077 +2025-06-24 10:39:42,063 - pyskl - INFO - Epoch [3][700/1281] lr: 2.498e-02, eta: 21:12:02, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.5344, top5_acc: 0.9094, loss_cls: 1.8703, loss: 1.8703 +2025-06-24 10:40:23,484 - pyskl - INFO - Epoch [3][800/1281] lr: 2.498e-02, eta: 21:12:18, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.5350, top5_acc: 0.9144, loss_cls: 1.8478, loss: 1.8478 +2025-06-24 10:41:04,896 - pyskl - INFO - Epoch [3][900/1281] lr: 2.498e-02, eta: 21:12:31, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.5500, top5_acc: 0.9113, loss_cls: 1.8127, loss: 1.8127 +2025-06-24 10:41:46,404 - pyskl - INFO - Epoch [3][1000/1281] lr: 2.498e-02, eta: 21:12:46, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.5537, top5_acc: 0.9113, loss_cls: 1.8322, loss: 1.8322 +2025-06-24 10:42:18,168 - pyskl - INFO - Epoch [3][1100/1281] lr: 2.498e-02, eta: 21:04:36, time: 0.318, data_time: 0.000, memory: 4082, top1_acc: 0.5469, top5_acc: 0.9169, loss_cls: 1.8100, loss: 1.8100 +2025-06-24 10:42:54,266 - pyskl - INFO - Epoch [3][1200/1281] lr: 2.498e-02, eta: 21:00:27, time: 0.361, data_time: 0.000, memory: 4082, top1_acc: 0.5425, top5_acc: 0.9200, loss_cls: 1.8006, loss: 1.8006 +2025-06-24 10:43:26,004 - pyskl - INFO - Saving checkpoint at 3 epochs +2025-06-24 10:44:37,860 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:44:37,919 - pyskl - INFO - +top1_acc 0.3984 +top5_acc 0.7809 +2025-06-24 10:44:37,919 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:44:37,930 - pyskl - INFO - +mean_acc 0.2448 +2025-06-24 10:44:37,933 - pyskl - INFO - Epoch(val) [3][533] top1_acc: 0.3984, top5_acc: 0.7809, mean_class_accuracy: 0.2448 +2025-06-24 10:45:39,218 - pyskl - INFO - Epoch [4][100/1281] lr: 2.497e-02, eta: 20:50:11, time: 0.613, data_time: 0.197, memory: 4082, top1_acc: 0.6100, top5_acc: 0.9325, loss_cls: 1.6559, loss: 1.6559 +2025-06-24 10:46:20,812 - pyskl - INFO - Epoch [4][200/1281] lr: 2.497e-02, eta: 20:50:52, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.5863, top5_acc: 0.9444, loss_cls: 1.6397, loss: 1.6397 +2025-06-24 10:47:02,260 - pyskl - INFO - Epoch [4][300/1281] lr: 2.497e-02, eta: 20:51:23, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.5981, top5_acc: 0.9431, loss_cls: 1.6487, loss: 1.6487 +2025-06-24 10:47:43,940 - pyskl - INFO - Epoch [4][400/1281] lr: 2.497e-02, eta: 20:52:00, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.5837, top5_acc: 0.9400, loss_cls: 1.6731, loss: 1.6731 +2025-06-24 10:48:25,497 - pyskl - INFO - Epoch [4][500/1281] lr: 2.497e-02, eta: 20:52:28, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.5763, top5_acc: 0.9313, loss_cls: 1.7002, loss: 1.7002 +2025-06-24 10:49:06,919 - pyskl - INFO - Epoch [4][600/1281] lr: 2.497e-02, eta: 20:52:48, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.6144, top5_acc: 0.9431, loss_cls: 1.5949, loss: 1.5949 +2025-06-24 10:49:48,356 - pyskl - INFO - Epoch [4][700/1281] lr: 2.497e-02, eta: 20:53:05, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.6175, top5_acc: 0.9463, loss_cls: 1.5439, loss: 1.5439 +2025-06-24 10:50:30,029 - pyskl - INFO - Epoch [4][800/1281] lr: 2.496e-02, eta: 20:53:29, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.6012, top5_acc: 0.9519, loss_cls: 1.5947, loss: 1.5947 +2025-06-24 10:51:11,462 - pyskl - INFO - Epoch [4][900/1281] lr: 2.496e-02, eta: 20:53:42, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.6462, top5_acc: 0.9581, loss_cls: 1.4411, loss: 1.4411 +2025-06-24 10:51:53,071 - pyskl - INFO - Epoch [4][1000/1281] lr: 2.496e-02, eta: 20:53:58, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.6294, top5_acc: 0.9369, loss_cls: 1.5424, loss: 1.5424 +2025-06-24 10:52:25,170 - pyskl - INFO - Epoch [4][1100/1281] lr: 2.496e-02, eta: 20:48:12, time: 0.321, data_time: 0.001, memory: 4082, top1_acc: 0.6312, top5_acc: 0.9525, loss_cls: 1.4917, loss: 1.4917 +2025-06-24 10:53:02,271 - pyskl - INFO - Epoch [4][1200/1281] lr: 2.496e-02, eta: 20:45:45, time: 0.371, data_time: 0.000, memory: 4082, top1_acc: 0.6375, top5_acc: 0.9563, loss_cls: 1.4911, loss: 1.4911 +2025-06-24 10:53:33,316 - pyskl - INFO - Saving checkpoint at 4 epochs +2025-06-24 10:54:44,659 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:54:44,717 - pyskl - INFO - +top1_acc 0.5659 +top5_acc 0.9296 +2025-06-24 10:54:44,717 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:54:44,725 - pyskl - INFO - +mean_acc 0.4331 +2025-06-24 10:54:44,729 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_2.pth was removed +2025-06-24 10:54:45,123 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_4.pth. +2025-06-24 10:54:45,123 - pyskl - INFO - Best top1_acc is 0.5659 at 4 epoch. +2025-06-24 10:54:45,126 - pyskl - INFO - Epoch(val) [4][533] top1_acc: 0.5659, top5_acc: 0.9296, mean_class_accuracy: 0.4331 +2025-06-24 10:55:46,717 - pyskl - INFO - Epoch [5][100/1281] lr: 2.495e-02, eta: 20:38:09, time: 0.616, data_time: 0.196, memory: 4082, top1_acc: 0.6356, top5_acc: 0.9613, loss_cls: 1.4645, loss: 1.4645 +2025-06-24 10:56:28,186 - pyskl - INFO - Epoch [5][200/1281] lr: 2.495e-02, eta: 20:38:29, time: 0.415, data_time: 0.001, memory: 4082, top1_acc: 0.6631, top5_acc: 0.9644, loss_cls: 1.3958, loss: 1.3958 +2025-06-24 10:57:10,029 - pyskl - INFO - Epoch [5][300/1281] lr: 2.495e-02, eta: 20:39:01, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.6669, top5_acc: 0.9500, loss_cls: 1.4111, loss: 1.4111 +2025-06-24 10:57:51,496 - pyskl - INFO - Epoch [5][400/1281] lr: 2.495e-02, eta: 20:39:17, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6569, top5_acc: 0.9625, loss_cls: 1.4161, loss: 1.4161 +2025-06-24 10:58:32,968 - pyskl - INFO - Epoch [5][500/1281] lr: 2.495e-02, eta: 20:39:31, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6488, top5_acc: 0.9581, loss_cls: 1.4256, loss: 1.4256 +2025-06-24 10:59:14,796 - pyskl - INFO - Epoch [5][600/1281] lr: 2.495e-02, eta: 20:39:55, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.6600, top5_acc: 0.9631, loss_cls: 1.3890, loss: 1.3890 +2025-06-24 10:59:57,366 - pyskl - INFO - Epoch [5][700/1281] lr: 2.494e-02, eta: 20:40:40, time: 0.426, data_time: 0.000, memory: 4082, top1_acc: 0.6656, top5_acc: 0.9644, loss_cls: 1.3567, loss: 1.3567 +2025-06-24 11:00:38,752 - pyskl - INFO - Epoch [5][800/1281] lr: 2.494e-02, eta: 20:40:45, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.6863, top5_acc: 0.9719, loss_cls: 1.2916, loss: 1.2916 +2025-06-24 11:01:20,204 - pyskl - INFO - Epoch [5][900/1281] lr: 2.494e-02, eta: 20:40:51, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.6644, top5_acc: 0.9587, loss_cls: 1.3865, loss: 1.3865 +2025-06-24 11:02:01,736 - pyskl - INFO - Epoch [5][1000/1281] lr: 2.494e-02, eta: 20:40:57, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6837, top5_acc: 0.9631, loss_cls: 1.3559, loss: 1.3559 +2025-06-24 11:02:32,447 - pyskl - INFO - Epoch [5][1100/1281] lr: 2.494e-02, eta: 20:35:39, time: 0.307, data_time: 0.000, memory: 4082, top1_acc: 0.6756, top5_acc: 0.9587, loss_cls: 1.3653, loss: 1.3653 +2025-06-24 11:03:11,347 - pyskl - INFO - Epoch [5][1200/1281] lr: 2.493e-02, eta: 20:34:30, time: 0.389, data_time: 0.000, memory: 4082, top1_acc: 0.6844, top5_acc: 0.9650, loss_cls: 1.3359, loss: 1.3359 +2025-06-24 11:03:40,310 - pyskl - INFO - Saving checkpoint at 5 epochs +2025-06-24 11:04:52,074 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:04:52,142 - pyskl - INFO - +top1_acc 0.6475 +top5_acc 0.9529 +2025-06-24 11:04:52,142 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:04:52,150 - pyskl - INFO - +mean_acc 0.5230 +2025-06-24 11:04:52,155 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_4.pth was removed +2025-06-24 11:04:52,357 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_5.pth. +2025-06-24 11:04:52,358 - pyskl - INFO - Best top1_acc is 0.6475 at 5 epoch. +2025-06-24 11:04:52,360 - pyskl - INFO - Epoch(val) [5][533] top1_acc: 0.6475, top5_acc: 0.9529, mean_class_accuracy: 0.5230 +2025-06-24 11:05:54,056 - pyskl - INFO - Epoch [6][100/1281] lr: 2.493e-02, eta: 20:28:20, time: 0.617, data_time: 0.200, memory: 4082, top1_acc: 0.7125, top5_acc: 0.9694, loss_cls: 1.2313, loss: 1.2313 +2025-06-24 11:06:35,747 - pyskl - INFO - Epoch [6][200/1281] lr: 2.493e-02, eta: 20:28:36, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7137, top5_acc: 0.9637, loss_cls: 1.2448, loss: 1.2448 +2025-06-24 11:07:17,291 - pyskl - INFO - Epoch [6][300/1281] lr: 2.492e-02, eta: 20:28:47, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6863, top5_acc: 0.9756, loss_cls: 1.2903, loss: 1.2903 +2025-06-24 11:07:58,789 - pyskl - INFO - Epoch [6][400/1281] lr: 2.492e-02, eta: 20:28:54, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6800, top5_acc: 0.9694, loss_cls: 1.2868, loss: 1.2868 +2025-06-24 11:08:40,185 - pyskl - INFO - Epoch [6][500/1281] lr: 2.492e-02, eta: 20:28:58, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.6931, top5_acc: 0.9762, loss_cls: 1.2651, loss: 1.2651 +2025-06-24 11:09:21,716 - pyskl - INFO - Epoch [6][600/1281] lr: 2.492e-02, eta: 20:29:03, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6987, top5_acc: 0.9681, loss_cls: 1.2753, loss: 1.2753 +2025-06-24 11:10:03,300 - pyskl - INFO - Epoch [6][700/1281] lr: 2.492e-02, eta: 20:29:09, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.6981, top5_acc: 0.9663, loss_cls: 1.2790, loss: 1.2790 +2025-06-24 11:10:44,740 - pyskl - INFO - Epoch [6][800/1281] lr: 2.491e-02, eta: 20:29:10, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7031, top5_acc: 0.9688, loss_cls: 1.2444, loss: 1.2444 +2025-06-24 11:11:26,373 - pyskl - INFO - Epoch [6][900/1281] lr: 2.491e-02, eta: 20:29:15, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.6925, top5_acc: 0.9750, loss_cls: 1.2526, loss: 1.2526 +2025-06-24 11:12:07,837 - pyskl - INFO - Epoch [6][1000/1281] lr: 2.491e-02, eta: 20:29:14, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.6987, top5_acc: 0.9637, loss_cls: 1.2544, loss: 1.2544 +2025-06-24 11:12:37,636 - pyskl - INFO - Epoch [6][1100/1281] lr: 2.491e-02, eta: 20:24:25, time: 0.298, data_time: 0.000, memory: 4082, top1_acc: 0.6769, top5_acc: 0.9650, loss_cls: 1.2922, loss: 1.2922 +2025-06-24 11:13:17,967 - pyskl - INFO - Epoch [6][1200/1281] lr: 2.490e-02, eta: 20:23:58, time: 0.403, data_time: 0.000, memory: 4082, top1_acc: 0.7019, top5_acc: 0.9688, loss_cls: 1.2509, loss: 1.2509 +2025-06-24 11:13:45,488 - pyskl - INFO - Saving checkpoint at 6 epochs +2025-06-24 11:14:56,463 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:14:56,527 - pyskl - INFO - +top1_acc 0.6774 +top5_acc 0.9680 +2025-06-24 11:14:56,527 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:14:56,534 - pyskl - INFO - +mean_acc 0.5539 +2025-06-24 11:14:56,538 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_5.pth was removed +2025-06-24 11:14:56,714 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_6.pth. +2025-06-24 11:14:56,714 - pyskl - INFO - Best top1_acc is 0.6774 at 6 epoch. +2025-06-24 11:14:56,717 - pyskl - INFO - Epoch(val) [6][533] top1_acc: 0.6774, top5_acc: 0.9680, mean_class_accuracy: 0.5539 +2025-06-24 11:15:58,759 - pyskl - INFO - Epoch [7][100/1281] lr: 2.490e-02, eta: 20:18:49, time: 0.620, data_time: 0.199, memory: 4082, top1_acc: 0.7206, top5_acc: 0.9775, loss_cls: 1.1744, loss: 1.1744 +2025-06-24 11:16:40,277 - pyskl - INFO - Epoch [7][200/1281] lr: 2.490e-02, eta: 20:18:53, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7238, top5_acc: 0.9725, loss_cls: 1.1469, loss: 1.1469 +2025-06-24 11:17:23,570 - pyskl - INFO - Epoch [7][300/1281] lr: 2.489e-02, eta: 20:19:36, time: 0.433, data_time: 0.000, memory: 4082, top1_acc: 0.7231, top5_acc: 0.9812, loss_cls: 1.1621, loss: 1.1621 +2025-06-24 11:18:05,568 - pyskl - INFO - Epoch [7][400/1281] lr: 2.489e-02, eta: 20:19:48, time: 0.420, data_time: 0.000, memory: 4082, top1_acc: 0.7288, top5_acc: 0.9725, loss_cls: 1.1506, loss: 1.1506 +2025-06-24 11:18:47,251 - pyskl - INFO - Epoch [7][500/1281] lr: 2.489e-02, eta: 20:19:51, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7056, top5_acc: 0.9719, loss_cls: 1.1979, loss: 1.1979 +2025-06-24 11:19:28,859 - pyskl - INFO - Epoch [7][600/1281] lr: 2.489e-02, eta: 20:19:52, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7106, top5_acc: 0.9725, loss_cls: 1.1959, loss: 1.1959 +2025-06-24 11:20:10,451 - pyskl - INFO - Epoch [7][700/1281] lr: 2.488e-02, eta: 20:19:51, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7144, top5_acc: 0.9750, loss_cls: 1.2031, loss: 1.2031 +2025-06-24 11:20:51,948 - pyskl - INFO - Epoch [7][800/1281] lr: 2.488e-02, eta: 20:19:48, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7031, top5_acc: 0.9731, loss_cls: 1.2427, loss: 1.2427 +2025-06-24 11:21:33,596 - pyskl - INFO - Epoch [7][900/1281] lr: 2.488e-02, eta: 20:19:46, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7400, top5_acc: 0.9781, loss_cls: 1.1270, loss: 1.1270 +2025-06-24 11:22:15,224 - pyskl - INFO - Epoch [7][1000/1281] lr: 2.487e-02, eta: 20:19:43, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7250, top5_acc: 0.9706, loss_cls: 1.1622, loss: 1.1622 +2025-06-24 11:22:43,681 - pyskl - INFO - Epoch [7][1100/1281] lr: 2.487e-02, eta: 20:15:05, time: 0.285, data_time: 0.000, memory: 4082, top1_acc: 0.7275, top5_acc: 0.9738, loss_cls: 1.1473, loss: 1.1473 +2025-06-24 11:23:24,809 - pyskl - INFO - Epoch [7][1200/1281] lr: 2.487e-02, eta: 20:14:53, time: 0.411, data_time: 0.000, memory: 4082, top1_acc: 0.7306, top5_acc: 0.9775, loss_cls: 1.1541, loss: 1.1541 +2025-06-24 11:23:51,495 - pyskl - INFO - Saving checkpoint at 7 epochs +2025-06-24 11:25:03,059 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:25:03,117 - pyskl - INFO - +top1_acc 0.6870 +top5_acc 0.9646 +2025-06-24 11:25:03,117 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:25:03,124 - pyskl - INFO - +mean_acc 0.5604 +2025-06-24 11:25:03,129 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_6.pth was removed +2025-06-24 11:25:03,327 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_7.pth. +2025-06-24 11:25:03,328 - pyskl - INFO - Best top1_acc is 0.6870 at 7 epoch. +2025-06-24 11:25:03,332 - pyskl - INFO - Epoch(val) [7][533] top1_acc: 0.6870, top5_acc: 0.9646, mean_class_accuracy: 0.5604 +2025-06-24 11:26:05,010 - pyskl - INFO - Epoch [8][100/1281] lr: 2.486e-02, eta: 20:10:13, time: 0.617, data_time: 0.200, memory: 4082, top1_acc: 0.7412, top5_acc: 0.9838, loss_cls: 1.0727, loss: 1.0727 +2025-06-24 11:26:46,801 - pyskl - INFO - Epoch [8][200/1281] lr: 2.486e-02, eta: 20:10:16, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.7212, top5_acc: 0.9775, loss_cls: 1.1676, loss: 1.1676 +2025-06-24 11:27:28,462 - pyskl - INFO - Epoch [8][300/1281] lr: 2.486e-02, eta: 20:10:15, time: 0.417, data_time: 0.001, memory: 4082, top1_acc: 0.7344, top5_acc: 0.9712, loss_cls: 1.1336, loss: 1.1336 +2025-06-24 11:28:09,998 - pyskl - INFO - Epoch [8][400/1281] lr: 2.485e-02, eta: 20:10:11, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7431, top5_acc: 0.9812, loss_cls: 1.1128, loss: 1.1128 +2025-06-24 11:28:51,413 - pyskl - INFO - Epoch [8][500/1281] lr: 2.485e-02, eta: 20:10:04, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7144, top5_acc: 0.9800, loss_cls: 1.1640, loss: 1.1640 +2025-06-24 11:29:32,904 - pyskl - INFO - Epoch [8][600/1281] lr: 2.485e-02, eta: 20:09:57, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7488, top5_acc: 0.9806, loss_cls: 1.0809, loss: 1.0809 +2025-06-24 11:30:14,505 - pyskl - INFO - Epoch [8][700/1281] lr: 2.484e-02, eta: 20:09:52, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7338, top5_acc: 0.9738, loss_cls: 1.1126, loss: 1.1126 +2025-06-24 11:30:56,300 - pyskl - INFO - Epoch [8][800/1281] lr: 2.484e-02, eta: 20:09:50, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.7512, top5_acc: 0.9825, loss_cls: 1.0830, loss: 1.0830 +2025-06-24 11:31:37,839 - pyskl - INFO - Epoch [8][900/1281] lr: 2.484e-02, eta: 20:09:43, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7350, top5_acc: 0.9775, loss_cls: 1.1407, loss: 1.1407 +2025-06-24 11:32:19,435 - pyskl - INFO - Epoch [8][1000/1281] lr: 2.483e-02, eta: 20:09:35, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7462, top5_acc: 0.9775, loss_cls: 1.0856, loss: 1.0856 +2025-06-24 11:32:47,564 - pyskl - INFO - Epoch [8][1100/1281] lr: 2.483e-02, eta: 20:05:24, time: 0.281, data_time: 0.000, memory: 4082, top1_acc: 0.7381, top5_acc: 0.9844, loss_cls: 1.1041, loss: 1.1041 +2025-06-24 11:33:29,669 - pyskl - INFO - Epoch [8][1200/1281] lr: 2.483e-02, eta: 20:05:27, time: 0.421, data_time: 0.000, memory: 4082, top1_acc: 0.7400, top5_acc: 0.9725, loss_cls: 1.1115, loss: 1.1115 +2025-06-24 11:33:55,538 - pyskl - INFO - Saving checkpoint at 8 epochs +2025-06-24 11:35:06,450 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:35:06,515 - pyskl - INFO - +top1_acc 0.6835 +top5_acc 0.9650 +2025-06-24 11:35:06,515 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:35:06,523 - pyskl - INFO - +mean_acc 0.5895 +2025-06-24 11:35:06,529 - pyskl - INFO - Epoch(val) [8][533] top1_acc: 0.6835, top5_acc: 0.9650, mean_class_accuracy: 0.5895 +2025-06-24 11:36:07,870 - pyskl - INFO - Epoch [9][100/1281] lr: 2.482e-02, eta: 20:01:08, time: 0.613, data_time: 0.198, memory: 4082, top1_acc: 0.7481, top5_acc: 0.9856, loss_cls: 1.0415, loss: 1.0415 +2025-06-24 11:36:49,519 - pyskl - INFO - Epoch [9][200/1281] lr: 2.482e-02, eta: 20:01:04, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7531, top5_acc: 0.9831, loss_cls: 1.0570, loss: 1.0570 +2025-06-24 11:37:30,996 - pyskl - INFO - Epoch [9][300/1281] lr: 2.481e-02, eta: 20:00:55, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7569, top5_acc: 0.9750, loss_cls: 1.0887, loss: 1.0887 +2025-06-24 11:38:12,562 - pyskl - INFO - Epoch [9][400/1281] lr: 2.481e-02, eta: 20:00:48, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7400, top5_acc: 0.9806, loss_cls: 1.0792, loss: 1.0792 +2025-06-24 11:38:54,137 - pyskl - INFO - Epoch [9][500/1281] lr: 2.481e-02, eta: 20:00:40, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7475, top5_acc: 0.9850, loss_cls: 1.0579, loss: 1.0579 +2025-06-24 11:39:35,646 - pyskl - INFO - Epoch [9][600/1281] lr: 2.480e-02, eta: 20:00:30, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7444, top5_acc: 0.9844, loss_cls: 1.0797, loss: 1.0797 +2025-06-24 11:40:17,156 - pyskl - INFO - Epoch [9][700/1281] lr: 2.480e-02, eta: 20:00:20, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7612, top5_acc: 0.9794, loss_cls: 1.0512, loss: 1.0512 +2025-06-24 11:40:58,613 - pyskl - INFO - Epoch [9][800/1281] lr: 2.480e-02, eta: 20:00:08, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7331, top5_acc: 0.9806, loss_cls: 1.1137, loss: 1.1137 +2025-06-24 11:41:40,089 - pyskl - INFO - Epoch [9][900/1281] lr: 2.479e-02, eta: 19:59:56, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7506, top5_acc: 0.9800, loss_cls: 1.0526, loss: 1.0526 +2025-06-24 11:42:21,703 - pyskl - INFO - Epoch [9][1000/1281] lr: 2.479e-02, eta: 19:59:46, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7394, top5_acc: 0.9794, loss_cls: 1.1119, loss: 1.1119 +2025-06-24 11:42:49,383 - pyskl - INFO - Epoch [9][1100/1281] lr: 2.479e-02, eta: 19:55:53, time: 0.277, data_time: 0.000, memory: 4082, top1_acc: 0.7319, top5_acc: 0.9788, loss_cls: 1.1110, loss: 1.1110 +2025-06-24 11:43:30,798 - pyskl - INFO - Epoch [9][1200/1281] lr: 2.478e-02, eta: 19:55:41, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7188, top5_acc: 0.9706, loss_cls: 1.1642, loss: 1.1642 +2025-06-24 11:43:57,164 - pyskl - INFO - Saving checkpoint at 9 epochs +2025-06-24 11:45:08,657 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:45:08,713 - pyskl - INFO - +top1_acc 0.6958 +top5_acc 0.9674 +2025-06-24 11:45:08,713 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:45:08,721 - pyskl - INFO - +mean_acc 0.5641 +2025-06-24 11:45:08,725 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_7.pth was removed +2025-06-24 11:45:08,908 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_9.pth. +2025-06-24 11:45:08,909 - pyskl - INFO - Best top1_acc is 0.6958 at 9 epoch. +2025-06-24 11:45:08,912 - pyskl - INFO - Epoch(val) [9][533] top1_acc: 0.6958, top5_acc: 0.9674, mean_class_accuracy: 0.5641 +2025-06-24 11:46:12,436 - pyskl - INFO - Epoch [10][100/1281] lr: 2.477e-02, eta: 19:52:19, time: 0.635, data_time: 0.198, memory: 4082, top1_acc: 0.7475, top5_acc: 0.9794, loss_cls: 1.0833, loss: 1.0833 +2025-06-24 11:46:54,315 - pyskl - INFO - Epoch [10][200/1281] lr: 2.477e-02, eta: 19:52:14, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.7488, top5_acc: 0.9844, loss_cls: 1.0795, loss: 1.0795 +2025-06-24 11:47:35,959 - pyskl - INFO - Epoch [10][300/1281] lr: 2.477e-02, eta: 19:52:05, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7644, top5_acc: 0.9819, loss_cls: 1.0385, loss: 1.0385 +2025-06-24 11:48:17,445 - pyskl - INFO - Epoch [10][400/1281] lr: 2.476e-02, eta: 19:51:53, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7556, top5_acc: 0.9812, loss_cls: 1.0602, loss: 1.0602 +2025-06-24 11:48:58,932 - pyskl - INFO - Epoch [10][500/1281] lr: 2.476e-02, eta: 19:51:40, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7575, top5_acc: 0.9794, loss_cls: 1.0381, loss: 1.0381 +2025-06-24 11:49:40,305 - pyskl - INFO - Epoch [10][600/1281] lr: 2.476e-02, eta: 19:51:25, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7525, top5_acc: 0.9800, loss_cls: 1.0947, loss: 1.0947 +2025-06-24 11:50:21,937 - pyskl - INFO - Epoch [10][700/1281] lr: 2.475e-02, eta: 19:51:14, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7562, top5_acc: 0.9850, loss_cls: 0.9992, loss: 0.9992 +2025-06-24 11:51:03,612 - pyskl - INFO - Epoch [10][800/1281] lr: 2.475e-02, eta: 19:51:03, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7694, top5_acc: 0.9850, loss_cls: 0.9984, loss: 0.9984 +2025-06-24 11:51:45,005 - pyskl - INFO - Epoch [10][900/1281] lr: 2.474e-02, eta: 19:50:47, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7344, top5_acc: 0.9788, loss_cls: 1.0948, loss: 1.0948 +2025-06-24 11:52:26,686 - pyskl - INFO - Epoch [10][1000/1281] lr: 2.474e-02, eta: 19:50:35, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7556, top5_acc: 0.9869, loss_cls: 1.0480, loss: 1.0480 +2025-06-24 11:52:55,266 - pyskl - INFO - Epoch [10][1100/1281] lr: 2.473e-02, eta: 19:47:16, time: 0.286, data_time: 0.000, memory: 4082, top1_acc: 0.7544, top5_acc: 0.9769, loss_cls: 1.0436, loss: 1.0436 +2025-06-24 11:53:36,170 - pyskl - INFO - Epoch [10][1200/1281] lr: 2.473e-02, eta: 19:46:53, time: 0.409, data_time: 0.000, memory: 4082, top1_acc: 0.7475, top5_acc: 0.9781, loss_cls: 1.0723, loss: 1.0723 +2025-06-24 11:54:03,080 - pyskl - INFO - Saving checkpoint at 10 epochs +2025-06-24 11:55:14,680 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:55:14,738 - pyskl - INFO - +top1_acc 0.7347 +top5_acc 0.9727 +2025-06-24 11:55:14,738 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:55:14,747 - pyskl - INFO - +mean_acc 0.6396 +2025-06-24 11:55:14,752 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_9.pth was removed +2025-06-24 11:55:14,940 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_10.pth. +2025-06-24 11:55:14,940 - pyskl - INFO - Best top1_acc is 0.7347 at 10 epoch. +2025-06-24 11:55:14,943 - pyskl - INFO - Epoch(val) [10][533] top1_acc: 0.7347, top5_acc: 0.9727, mean_class_accuracy: 0.6396 +2025-06-24 11:56:16,660 - pyskl - INFO - Epoch [11][100/1281] lr: 2.472e-02, eta: 19:43:21, time: 0.617, data_time: 0.202, memory: 4082, top1_acc: 0.7675, top5_acc: 0.9812, loss_cls: 1.0251, loss: 1.0251 +2025-06-24 11:56:58,340 - pyskl - INFO - Epoch [11][200/1281] lr: 2.472e-02, eta: 19:43:10, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7531, top5_acc: 0.9838, loss_cls: 1.0031, loss: 1.0031 +2025-06-24 11:57:41,529 - pyskl - INFO - Epoch [11][300/1281] lr: 2.471e-02, eta: 19:43:19, time: 0.432, data_time: 0.000, memory: 4082, top1_acc: 0.7788, top5_acc: 0.9825, loss_cls: 0.9614, loss: 0.9614 +2025-06-24 11:58:23,718 - pyskl - INFO - Epoch [11][400/1281] lr: 2.471e-02, eta: 19:43:13, time: 0.422, data_time: 0.000, memory: 4082, top1_acc: 0.7550, top5_acc: 0.9875, loss_cls: 1.0246, loss: 1.0246 +2025-06-24 11:59:05,328 - pyskl - INFO - Epoch [11][500/1281] lr: 2.471e-02, eta: 19:43:00, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7594, top5_acc: 0.9806, loss_cls: 1.0024, loss: 1.0024 +2025-06-24 11:59:46,752 - pyskl - INFO - Epoch [11][600/1281] lr: 2.470e-02, eta: 19:42:43, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7812, top5_acc: 0.9806, loss_cls: 1.0060, loss: 1.0060 +2025-06-24 12:00:28,215 - pyskl - INFO - Epoch [11][700/1281] lr: 2.470e-02, eta: 19:42:27, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7469, top5_acc: 0.9875, loss_cls: 1.0297, loss: 1.0297 +2025-06-24 12:01:09,864 - pyskl - INFO - Epoch [11][800/1281] lr: 2.469e-02, eta: 19:42:12, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7875, top5_acc: 0.9881, loss_cls: 0.9479, loss: 0.9479 +2025-06-24 12:01:51,425 - pyskl - INFO - Epoch [11][900/1281] lr: 2.469e-02, eta: 19:41:56, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7438, top5_acc: 0.9831, loss_cls: 1.0802, loss: 1.0802 +2025-06-24 12:02:32,915 - pyskl - INFO - Epoch [11][1000/1281] lr: 2.468e-02, eta: 19:41:39, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7738, top5_acc: 0.9800, loss_cls: 0.9994, loss: 0.9994 +2025-06-24 12:03:01,217 - pyskl - INFO - Epoch [11][1100/1281] lr: 2.468e-02, eta: 19:38:33, time: 0.283, data_time: 0.001, memory: 4082, top1_acc: 0.7669, top5_acc: 0.9825, loss_cls: 1.0027, loss: 1.0027 +2025-06-24 12:03:43,035 - pyskl - INFO - Epoch [11][1200/1281] lr: 2.467e-02, eta: 19:38:20, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.7488, top5_acc: 0.9794, loss_cls: 1.0649, loss: 1.0649 +2025-06-24 12:04:08,761 - pyskl - INFO - Saving checkpoint at 11 epochs +2025-06-24 12:05:20,813 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:05:20,877 - pyskl - INFO - +top1_acc 0.7467 +top5_acc 0.9720 +2025-06-24 12:05:20,877 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:05:20,884 - pyskl - INFO - +mean_acc 0.6624 +2025-06-24 12:05:20,888 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_10.pth was removed +2025-06-24 12:05:21,071 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_11.pth. +2025-06-24 12:05:21,072 - pyskl - INFO - Best top1_acc is 0.7467 at 11 epoch. +2025-06-24 12:05:21,074 - pyskl - INFO - Epoch(val) [11][533] top1_acc: 0.7467, top5_acc: 0.9720, mean_class_accuracy: 0.6624 +2025-06-24 12:06:22,454 - pyskl - INFO - Epoch [12][100/1281] lr: 2.467e-02, eta: 19:34:57, time: 0.614, data_time: 0.200, memory: 4082, top1_acc: 0.8019, top5_acc: 0.9844, loss_cls: 0.9181, loss: 0.9181 +2025-06-24 12:07:04,191 - pyskl - INFO - Epoch [12][200/1281] lr: 2.466e-02, eta: 19:34:44, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8006, top5_acc: 0.9875, loss_cls: 0.8955, loss: 0.8955 +2025-06-24 12:07:45,689 - pyskl - INFO - Epoch [12][300/1281] lr: 2.466e-02, eta: 19:34:27, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7844, top5_acc: 0.9844, loss_cls: 0.9872, loss: 0.9872 +2025-06-24 12:08:27,171 - pyskl - INFO - Epoch [12][400/1281] lr: 2.465e-02, eta: 19:34:10, time: 0.415, data_time: 0.001, memory: 4082, top1_acc: 0.7775, top5_acc: 0.9906, loss_cls: 0.9647, loss: 0.9647 +2025-06-24 12:09:08,655 - pyskl - INFO - Epoch [12][500/1281] lr: 2.465e-02, eta: 19:33:53, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7688, top5_acc: 0.9825, loss_cls: 0.9623, loss: 0.9623 +2025-06-24 12:09:50,359 - pyskl - INFO - Epoch [12][600/1281] lr: 2.464e-02, eta: 19:33:38, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7725, top5_acc: 0.9812, loss_cls: 0.9716, loss: 0.9716 +2025-06-24 12:10:31,678 - pyskl - INFO - Epoch [12][700/1281] lr: 2.464e-02, eta: 19:33:18, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.7650, top5_acc: 0.9750, loss_cls: 1.0028, loss: 1.0028 +2025-06-24 12:11:13,054 - pyskl - INFO - Epoch [12][800/1281] lr: 2.463e-02, eta: 19:32:58, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7738, top5_acc: 0.9812, loss_cls: 1.0118, loss: 1.0118 +2025-06-24 12:11:54,589 - pyskl - INFO - Epoch [12][900/1281] lr: 2.463e-02, eta: 19:32:40, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7656, top5_acc: 0.9825, loss_cls: 1.0257, loss: 1.0257 +2025-06-24 12:12:36,098 - pyskl - INFO - Epoch [12][1000/1281] lr: 2.462e-02, eta: 19:32:21, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7512, top5_acc: 0.9844, loss_cls: 1.0303, loss: 1.0303 +2025-06-24 12:13:03,290 - pyskl - INFO - Epoch [12][1100/1281] lr: 2.462e-02, eta: 19:29:15, time: 0.272, data_time: 0.000, memory: 4082, top1_acc: 0.7612, top5_acc: 0.9831, loss_cls: 1.0217, loss: 1.0217 +2025-06-24 12:13:45,650 - pyskl - INFO - Epoch [12][1200/1281] lr: 2.461e-02, eta: 19:29:07, time: 0.424, data_time: 0.000, memory: 4082, top1_acc: 0.7700, top5_acc: 0.9819, loss_cls: 0.9577, loss: 0.9577 +2025-06-24 12:14:11,065 - pyskl - INFO - Saving checkpoint at 12 epochs +2025-06-24 12:15:22,506 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:15:22,563 - pyskl - INFO - +top1_acc 0.7384 +top5_acc 0.9688 +2025-06-24 12:15:22,563 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:15:22,572 - pyskl - INFO - +mean_acc 0.6478 +2025-06-24 12:15:22,574 - pyskl - INFO - Epoch(val) [12][533] top1_acc: 0.7384, top5_acc: 0.9688, mean_class_accuracy: 0.6478 +2025-06-24 12:16:23,548 - pyskl - INFO - Epoch [13][100/1281] lr: 2.460e-02, eta: 19:25:52, time: 0.610, data_time: 0.194, memory: 4082, top1_acc: 0.7894, top5_acc: 0.9862, loss_cls: 0.8966, loss: 0.8966 +2025-06-24 12:17:04,948 - pyskl - INFO - Epoch [13][200/1281] lr: 2.460e-02, eta: 19:25:33, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7900, top5_acc: 0.9850, loss_cls: 0.9389, loss: 0.9389 +2025-06-24 12:17:46,522 - pyskl - INFO - Epoch [13][300/1281] lr: 2.459e-02, eta: 19:25:15, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7894, top5_acc: 0.9900, loss_cls: 0.8594, loss: 0.8594 +2025-06-24 12:18:27,887 - pyskl - INFO - Epoch [13][400/1281] lr: 2.459e-02, eta: 19:24:55, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7706, top5_acc: 0.9756, loss_cls: 0.9722, loss: 0.9722 +2025-06-24 12:19:09,310 - pyskl - INFO - Epoch [13][500/1281] lr: 2.458e-02, eta: 19:24:35, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.7719, top5_acc: 0.9825, loss_cls: 0.9725, loss: 0.9725 +2025-06-24 12:19:50,919 - pyskl - INFO - Epoch [13][600/1281] lr: 2.458e-02, eta: 19:24:18, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7738, top5_acc: 0.9800, loss_cls: 1.0039, loss: 1.0039 +2025-06-24 12:20:32,448 - pyskl - INFO - Epoch [13][700/1281] lr: 2.457e-02, eta: 19:23:58, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7531, top5_acc: 0.9850, loss_cls: 1.0109, loss: 1.0109 +2025-06-24 12:21:13,926 - pyskl - INFO - Epoch [13][800/1281] lr: 2.457e-02, eta: 19:23:39, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7831, top5_acc: 0.9862, loss_cls: 0.9719, loss: 0.9719 +2025-06-24 12:21:55,495 - pyskl - INFO - Epoch [13][900/1281] lr: 2.456e-02, eta: 19:23:19, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7731, top5_acc: 0.9838, loss_cls: 0.9377, loss: 0.9377 +2025-06-24 12:22:36,829 - pyskl - INFO - Epoch [13][1000/1281] lr: 2.455e-02, eta: 19:22:57, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.7569, top5_acc: 0.9838, loss_cls: 1.0063, loss: 1.0063 +2025-06-24 12:23:04,735 - pyskl - INFO - Epoch [13][1100/1281] lr: 2.455e-02, eta: 19:20:12, time: 0.279, data_time: 0.000, memory: 4082, top1_acc: 0.7819, top5_acc: 0.9844, loss_cls: 0.9602, loss: 0.9602 +2025-06-24 12:23:46,900 - pyskl - INFO - Epoch [13][1200/1281] lr: 2.454e-02, eta: 19:19:59, time: 0.422, data_time: 0.000, memory: 4082, top1_acc: 0.7719, top5_acc: 0.9850, loss_cls: 0.9474, loss: 0.9474 +2025-06-24 12:24:12,394 - pyskl - INFO - Saving checkpoint at 13 epochs +2025-06-24 12:25:13,721 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:25:13,787 - pyskl - INFO - +top1_acc 0.7509 +top5_acc 0.9783 +2025-06-24 12:25:13,788 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:25:13,798 - pyskl - INFO - +mean_acc 0.6598 +2025-06-24 12:25:13,804 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_11.pth was removed +2025-06-24 12:25:14,011 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_13.pth. +2025-06-24 12:25:14,011 - pyskl - INFO - Best top1_acc is 0.7509 at 13 epoch. +2025-06-24 12:25:14,015 - pyskl - INFO - Epoch(val) [13][533] top1_acc: 0.7509, top5_acc: 0.9783, mean_class_accuracy: 0.6598 +2025-06-24 12:26:13,329 - pyskl - INFO - Epoch [14][100/1281] lr: 2.453e-02, eta: 19:16:37, time: 0.593, data_time: 0.203, memory: 4082, top1_acc: 0.7894, top5_acc: 0.9881, loss_cls: 0.9041, loss: 0.9041 +2025-06-24 12:26:52,446 - pyskl - INFO - Epoch [14][200/1281] lr: 2.453e-02, eta: 19:15:53, time: 0.391, data_time: 0.000, memory: 4082, top1_acc: 0.8000, top5_acc: 0.9869, loss_cls: 0.8832, loss: 0.8832 +2025-06-24 12:27:33,004 - pyskl - INFO - Epoch [14][300/1281] lr: 2.452e-02, eta: 19:15:24, time: 0.406, data_time: 0.000, memory: 4082, top1_acc: 0.7856, top5_acc: 0.9844, loss_cls: 0.9245, loss: 0.9245 +2025-06-24 12:28:13,797 - pyskl - INFO - Epoch [14][400/1281] lr: 2.452e-02, eta: 19:14:57, time: 0.408, data_time: 0.000, memory: 4082, top1_acc: 0.7588, top5_acc: 0.9900, loss_cls: 0.9529, loss: 0.9529 +2025-06-24 12:28:52,941 - pyskl - INFO - Epoch [14][500/1281] lr: 2.451e-02, eta: 19:14:13, time: 0.391, data_time: 0.000, memory: 4082, top1_acc: 0.7762, top5_acc: 0.9825, loss_cls: 0.9808, loss: 0.9808 +2025-06-24 12:29:32,291 - pyskl - INFO - Epoch [14][600/1281] lr: 2.451e-02, eta: 19:13:31, time: 0.394, data_time: 0.000, memory: 4082, top1_acc: 0.7831, top5_acc: 0.9819, loss_cls: 0.9663, loss: 0.9663 +2025-06-24 12:30:12,074 - pyskl - INFO - Epoch [14][700/1281] lr: 2.450e-02, eta: 19:12:53, time: 0.398, data_time: 0.000, memory: 4082, top1_acc: 0.7963, top5_acc: 0.9838, loss_cls: 0.9097, loss: 0.9097 +2025-06-24 12:30:51,435 - pyskl - INFO - Epoch [14][800/1281] lr: 2.449e-02, eta: 19:12:12, time: 0.394, data_time: 0.000, memory: 4082, top1_acc: 0.7881, top5_acc: 0.9888, loss_cls: 0.9141, loss: 0.9141 +2025-06-24 12:31:31,412 - pyskl - INFO - Epoch [14][900/1281] lr: 2.449e-02, eta: 19:11:36, time: 0.400, data_time: 0.000, memory: 4082, top1_acc: 0.7944, top5_acc: 0.9862, loss_cls: 0.9132, loss: 0.9132 +2025-06-24 12:32:10,666 - pyskl - INFO - Epoch [14][1000/1281] lr: 2.448e-02, eta: 19:10:53, time: 0.393, data_time: 0.000, memory: 4082, top1_acc: 0.7812, top5_acc: 0.9819, loss_cls: 0.9396, loss: 0.9396 +2025-06-24 12:32:50,232 - pyskl - INFO - Epoch [14][1100/1281] lr: 2.448e-02, eta: 19:10:14, time: 0.396, data_time: 0.000, memory: 4082, top1_acc: 0.7869, top5_acc: 0.9819, loss_cls: 0.9036, loss: 0.9036 +2025-06-24 12:33:30,583 - pyskl - INFO - Epoch [14][1200/1281] lr: 2.447e-02, eta: 19:09:42, time: 0.403, data_time: 0.000, memory: 4082, top1_acc: 0.7738, top5_acc: 0.9844, loss_cls: 0.9279, loss: 0.9279 +2025-06-24 12:34:02,662 - pyskl - INFO - Saving checkpoint at 14 epochs +2025-06-24 12:35:03,192 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:35:03,258 - pyskl - INFO - +top1_acc 0.7302 +top5_acc 0.9620 +2025-06-24 12:35:03,258 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:35:03,270 - pyskl - INFO - +mean_acc 0.6531 +2025-06-24 12:35:03,274 - pyskl - INFO - Epoch(val) [14][533] top1_acc: 0.7302, top5_acc: 0.9620, mean_class_accuracy: 0.6531 +2025-06-24 12:35:46,357 - pyskl - INFO - Epoch [15][100/1281] lr: 2.446e-02, eta: 19:03:54, time: 0.431, data_time: 0.196, memory: 4082, top1_acc: 0.8025, top5_acc: 0.9900, loss_cls: 0.8604, loss: 0.8604 +2025-06-24 12:36:20,423 - pyskl - INFO - Epoch [15][200/1281] lr: 2.445e-02, eta: 19:02:23, time: 0.341, data_time: 0.000, memory: 4082, top1_acc: 0.8100, top5_acc: 0.9894, loss_cls: 0.8451, loss: 0.8451 +2025-06-24 12:36:59,160 - pyskl - INFO - Epoch [15][300/1281] lr: 2.445e-02, eta: 19:01:38, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.7919, top5_acc: 0.9881, loss_cls: 0.9019, loss: 0.9019 +2025-06-24 12:37:37,761 - pyskl - INFO - Epoch [15][400/1281] lr: 2.444e-02, eta: 19:00:51, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8087, top5_acc: 0.9869, loss_cls: 0.8470, loss: 0.8470 +2025-06-24 12:38:15,510 - pyskl - INFO - Epoch [15][500/1281] lr: 2.444e-02, eta: 18:59:56, time: 0.377, data_time: 0.000, memory: 4082, top1_acc: 0.7944, top5_acc: 0.9850, loss_cls: 0.8992, loss: 0.8992 +2025-06-24 12:38:54,731 - pyskl - INFO - Epoch [15][600/1281] lr: 2.443e-02, eta: 18:59:15, time: 0.392, data_time: 0.000, memory: 4082, top1_acc: 0.7844, top5_acc: 0.9819, loss_cls: 0.9645, loss: 0.9645 +2025-06-24 12:39:32,848 - pyskl - INFO - Epoch [15][700/1281] lr: 2.442e-02, eta: 18:58:24, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.7837, top5_acc: 0.9881, loss_cls: 0.9255, loss: 0.9255 +2025-06-24 12:40:11,486 - pyskl - INFO - Epoch [15][800/1281] lr: 2.442e-02, eta: 18:57:38, time: 0.386, data_time: 0.001, memory: 4082, top1_acc: 0.7850, top5_acc: 0.9875, loss_cls: 0.9399, loss: 0.9399 +2025-06-24 12:40:49,842 - pyskl - INFO - Epoch [15][900/1281] lr: 2.441e-02, eta: 18:56:50, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.7812, top5_acc: 0.9825, loss_cls: 0.9560, loss: 0.9560 +2025-06-24 12:41:28,566 - pyskl - INFO - Epoch [15][1000/1281] lr: 2.441e-02, eta: 18:56:04, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.7881, top5_acc: 0.9825, loss_cls: 0.9193, loss: 0.9193 +2025-06-24 12:42:07,002 - pyskl - INFO - Epoch [15][1100/1281] lr: 2.440e-02, eta: 18:55:17, time: 0.384, data_time: 0.001, memory: 4082, top1_acc: 0.7925, top5_acc: 0.9831, loss_cls: 0.9119, loss: 0.9119 +2025-06-24 12:42:45,783 - pyskl - INFO - Epoch [15][1200/1281] lr: 2.439e-02, eta: 18:54:32, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.7956, top5_acc: 0.9856, loss_cls: 0.8973, loss: 0.8973 +2025-06-24 12:43:18,234 - pyskl - INFO - Saving checkpoint at 15 epochs +2025-06-24 12:44:16,959 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:44:17,032 - pyskl - INFO - +top1_acc 0.7483 +top5_acc 0.9763 +2025-06-24 12:44:17,033 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:44:17,041 - pyskl - INFO - +mean_acc 0.6682 +2025-06-24 12:44:17,043 - pyskl - INFO - Epoch(val) [15][533] top1_acc: 0.7483, top5_acc: 0.9763, mean_class_accuracy: 0.6682 +2025-06-24 12:45:14,775 - pyskl - INFO - Epoch [16][100/1281] lr: 2.438e-02, eta: 18:51:20, time: 0.577, data_time: 0.193, memory: 4082, top1_acc: 0.8200, top5_acc: 0.9950, loss_cls: 0.7925, loss: 0.7925 +2025-06-24 12:45:52,803 - pyskl - INFO - Epoch [16][200/1281] lr: 2.438e-02, eta: 18:50:30, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.7913, top5_acc: 0.9869, loss_cls: 0.8889, loss: 0.8889 +2025-06-24 12:46:24,565 - pyskl - INFO - Epoch [16][300/1281] lr: 2.437e-02, eta: 18:48:44, time: 0.318, data_time: 0.000, memory: 4082, top1_acc: 0.7906, top5_acc: 0.9831, loss_cls: 0.9445, loss: 0.9445 +2025-06-24 12:47:00,111 - pyskl - INFO - Epoch [16][400/1281] lr: 2.436e-02, eta: 18:47:33, time: 0.355, data_time: 0.000, memory: 4082, top1_acc: 0.8087, top5_acc: 0.9869, loss_cls: 0.8760, loss: 0.8760 +2025-06-24 12:47:35,646 - pyskl - INFO - Epoch [16][500/1281] lr: 2.436e-02, eta: 18:46:21, time: 0.355, data_time: 0.000, memory: 4082, top1_acc: 0.7994, top5_acc: 0.9862, loss_cls: 0.8401, loss: 0.8401 +2025-06-24 12:47:59,207 - pyskl - INFO - Epoch [16][600/1281] lr: 2.435e-02, eta: 18:43:26, time: 0.236, data_time: 0.000, memory: 4082, top1_acc: 0.7956, top5_acc: 0.9881, loss_cls: 0.8887, loss: 0.8887 +2025-06-24 12:48:36,852 - pyskl - INFO - Epoch [16][700/1281] lr: 2.434e-02, eta: 18:42:34, time: 0.376, data_time: 0.000, memory: 4082, top1_acc: 0.7931, top5_acc: 0.9869, loss_cls: 0.8798, loss: 0.8798 +2025-06-24 12:49:14,722 - pyskl - INFO - Epoch [16][800/1281] lr: 2.434e-02, eta: 18:41:45, time: 0.379, data_time: 0.000, memory: 4082, top1_acc: 0.7812, top5_acc: 0.9875, loss_cls: 0.9171, loss: 0.9171 +2025-06-24 12:49:52,742 - pyskl - INFO - Epoch [16][900/1281] lr: 2.433e-02, eta: 18:40:56, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.7906, top5_acc: 0.9875, loss_cls: 0.8787, loss: 0.8787 +2025-06-24 12:50:30,749 - pyskl - INFO - Epoch [16][1000/1281] lr: 2.432e-02, eta: 18:40:08, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.7806, top5_acc: 0.9875, loss_cls: 0.9016, loss: 0.9016 +2025-06-24 12:51:09,162 - pyskl - INFO - Epoch [16][1100/1281] lr: 2.432e-02, eta: 18:39:23, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.7863, top5_acc: 0.9862, loss_cls: 0.9237, loss: 0.9237 +2025-06-24 12:51:47,367 - pyskl - INFO - Epoch [16][1200/1281] lr: 2.431e-02, eta: 18:38:37, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.7819, top5_acc: 0.9806, loss_cls: 0.9229, loss: 0.9229 +2025-06-24 12:52:19,452 - pyskl - INFO - Saving checkpoint at 16 epochs +2025-06-24 12:53:18,750 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:53:18,804 - pyskl - INFO - +top1_acc 0.7646 +top5_acc 0.9806 +2025-06-24 12:53:18,805 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:53:18,811 - pyskl - INFO - +mean_acc 0.6761 +2025-06-24 12:53:18,816 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_13.pth was removed +2025-06-24 12:53:19,022 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_16.pth. +2025-06-24 12:53:19,022 - pyskl - INFO - Best top1_acc is 0.7646 at 16 epoch. +2025-06-24 12:53:19,025 - pyskl - INFO - Epoch(val) [16][533] top1_acc: 0.7646, top5_acc: 0.9806, mean_class_accuracy: 0.6761 +2025-06-24 12:54:17,470 - pyskl - INFO - Epoch [17][100/1281] lr: 2.430e-02, eta: 18:35:43, time: 0.584, data_time: 0.197, memory: 4082, top1_acc: 0.8019, top5_acc: 0.9919, loss_cls: 0.8524, loss: 0.8524 +2025-06-24 12:54:55,173 - pyskl - INFO - Epoch [17][200/1281] lr: 2.429e-02, eta: 18:34:53, time: 0.377, data_time: 0.000, memory: 4082, top1_acc: 0.8025, top5_acc: 0.9856, loss_cls: 0.8598, loss: 0.8598 +2025-06-24 12:55:32,902 - pyskl - INFO - Epoch [17][300/1281] lr: 2.428e-02, eta: 18:34:04, time: 0.377, data_time: 0.001, memory: 4082, top1_acc: 0.7894, top5_acc: 0.9888, loss_cls: 0.9025, loss: 0.9025 +2025-06-24 12:56:10,731 - pyskl - INFO - Epoch [17][400/1281] lr: 2.428e-02, eta: 18:33:15, time: 0.378, data_time: 0.000, memory: 4082, top1_acc: 0.7894, top5_acc: 0.9875, loss_cls: 0.8966, loss: 0.8966 +2025-06-24 12:56:48,480 - pyskl - INFO - Epoch [17][500/1281] lr: 2.427e-02, eta: 18:32:26, time: 0.377, data_time: 0.000, memory: 4082, top1_acc: 0.7981, top5_acc: 0.9875, loss_cls: 0.8961, loss: 0.8961 +2025-06-24 12:57:26,130 - pyskl - INFO - Epoch [17][600/1281] lr: 2.426e-02, eta: 18:31:36, time: 0.376, data_time: 0.000, memory: 4082, top1_acc: 0.8150, top5_acc: 0.9844, loss_cls: 0.8666, loss: 0.8666 +2025-06-24 12:58:04,068 - pyskl - INFO - Epoch [17][700/1281] lr: 2.426e-02, eta: 18:30:48, time: 0.379, data_time: 0.000, memory: 4082, top1_acc: 0.7969, top5_acc: 0.9888, loss_cls: 0.8976, loss: 0.8976 +2025-06-24 12:58:37,502 - pyskl - INFO - Epoch [17][800/1281] lr: 2.425e-02, eta: 18:29:25, time: 0.334, data_time: 0.000, memory: 4082, top1_acc: 0.7994, top5_acc: 0.9844, loss_cls: 0.9083, loss: 0.9083 +2025-06-24 12:59:10,649 - pyskl - INFO - Epoch [17][900/1281] lr: 2.424e-02, eta: 18:28:00, time: 0.331, data_time: 0.000, memory: 4082, top1_acc: 0.7913, top5_acc: 0.9838, loss_cls: 0.8982, loss: 0.8982 +2025-06-24 12:59:48,447 - pyskl - INFO - Epoch [17][1000/1281] lr: 2.424e-02, eta: 18:27:12, time: 0.378, data_time: 0.000, memory: 4082, top1_acc: 0.8037, top5_acc: 0.9906, loss_cls: 0.8699, loss: 0.8699 +2025-06-24 13:00:12,002 - pyskl - INFO - Epoch [17][1100/1281] lr: 2.423e-02, eta: 18:24:31, time: 0.236, data_time: 0.000, memory: 4082, top1_acc: 0.7975, top5_acc: 0.9938, loss_cls: 0.8577, loss: 0.8577 +2025-06-24 13:00:48,207 - pyskl - INFO - Epoch [17][1200/1281] lr: 2.422e-02, eta: 18:23:32, time: 0.362, data_time: 0.000, memory: 4082, top1_acc: 0.7894, top5_acc: 0.9844, loss_cls: 0.9311, loss: 0.9311 +2025-06-24 13:01:19,971 - pyskl - INFO - Saving checkpoint at 17 epochs +2025-06-24 13:02:19,530 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:02:19,597 - pyskl - INFO - +top1_acc 0.7800 +top5_acc 0.9806 +2025-06-24 13:02:19,598 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:02:19,606 - pyskl - INFO - +mean_acc 0.7213 +2025-06-24 13:02:19,610 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_16.pth was removed +2025-06-24 13:02:19,787 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_17.pth. +2025-06-24 13:02:19,787 - pyskl - INFO - Best top1_acc is 0.7800 at 17 epoch. +2025-06-24 13:02:19,790 - pyskl - INFO - Epoch(val) [17][533] top1_acc: 0.7800, top5_acc: 0.9806, mean_class_accuracy: 0.7213 +2025-06-24 13:03:17,983 - pyskl - INFO - Epoch [18][100/1281] lr: 2.421e-02, eta: 18:20:47, time: 0.582, data_time: 0.200, memory: 4082, top1_acc: 0.8337, top5_acc: 0.9912, loss_cls: 0.7547, loss: 0.7547 +2025-06-24 13:03:56,235 - pyskl - INFO - Epoch [18][200/1281] lr: 2.420e-02, eta: 18:20:04, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.8137, top5_acc: 0.9906, loss_cls: 0.7947, loss: 0.7947 +2025-06-24 13:04:34,857 - pyskl - INFO - Epoch [18][300/1281] lr: 2.419e-02, eta: 18:19:24, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8013, top5_acc: 0.9875, loss_cls: 0.8773, loss: 0.8773 +2025-06-24 13:05:12,803 - pyskl - INFO - Epoch [18][400/1281] lr: 2.419e-02, eta: 18:18:39, time: 0.379, data_time: 0.000, memory: 4082, top1_acc: 0.7975, top5_acc: 0.9838, loss_cls: 0.9037, loss: 0.9037 +2025-06-24 13:05:50,937 - pyskl - INFO - Epoch [18][500/1281] lr: 2.418e-02, eta: 18:17:55, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8044, top5_acc: 0.9906, loss_cls: 0.8502, loss: 0.8502 +2025-06-24 13:06:28,810 - pyskl - INFO - Epoch [18][600/1281] lr: 2.417e-02, eta: 18:17:09, time: 0.379, data_time: 0.000, memory: 4082, top1_acc: 0.8019, top5_acc: 0.9862, loss_cls: 0.8839, loss: 0.8839 +2025-06-24 13:07:07,141 - pyskl - INFO - Epoch [18][700/1281] lr: 2.417e-02, eta: 18:16:27, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.8131, top5_acc: 0.9894, loss_cls: 0.8472, loss: 0.8472 +2025-06-24 13:07:44,752 - pyskl - INFO - Epoch [18][800/1281] lr: 2.416e-02, eta: 18:15:40, time: 0.376, data_time: 0.000, memory: 4082, top1_acc: 0.8137, top5_acc: 0.9881, loss_cls: 0.8435, loss: 0.8435 +2025-06-24 13:08:23,242 - pyskl - INFO - Epoch [18][900/1281] lr: 2.415e-02, eta: 18:14:59, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.7937, top5_acc: 0.9862, loss_cls: 0.9132, loss: 0.9132 +2025-06-24 13:09:01,496 - pyskl - INFO - Epoch [18][1000/1281] lr: 2.414e-02, eta: 18:14:16, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.8394, top5_acc: 0.9925, loss_cls: 0.7578, loss: 0.7578 +2025-06-24 13:09:40,443 - pyskl - INFO - Epoch [18][1100/1281] lr: 2.414e-02, eta: 18:13:39, time: 0.389, data_time: 0.000, memory: 4082, top1_acc: 0.8106, top5_acc: 0.9888, loss_cls: 0.8641, loss: 0.8641 +2025-06-24 13:10:19,195 - pyskl - INFO - Epoch [18][1200/1281] lr: 2.413e-02, eta: 18:13:00, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8094, top5_acc: 0.9894, loss_cls: 0.8419, loss: 0.8419 +2025-06-24 13:10:46,414 - pyskl - INFO - Saving checkpoint at 18 epochs +2025-06-24 13:11:54,998 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:11:55,068 - pyskl - INFO - +top1_acc 0.7473 +top5_acc 0.9654 +2025-06-24 13:11:55,068 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:11:55,078 - pyskl - INFO - +mean_acc 0.6660 +2025-06-24 13:11:55,081 - pyskl - INFO - Epoch(val) [18][533] top1_acc: 0.7473, top5_acc: 0.9654, mean_class_accuracy: 0.6660 +2025-06-24 13:12:52,289 - pyskl - INFO - Epoch [19][100/1281] lr: 2.411e-02, eta: 18:10:15, time: 0.572, data_time: 0.194, memory: 4082, top1_acc: 0.8331, top5_acc: 0.9919, loss_cls: 0.7668, loss: 0.7668 +2025-06-24 13:13:30,854 - pyskl - INFO - Epoch [19][200/1281] lr: 2.411e-02, eta: 18:09:35, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.7869, top5_acc: 0.9900, loss_cls: 0.9133, loss: 0.9133 +2025-06-24 13:14:09,590 - pyskl - INFO - Epoch [19][300/1281] lr: 2.410e-02, eta: 18:08:57, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.8081, top5_acc: 0.9875, loss_cls: 0.8487, loss: 0.8487 +2025-06-24 13:14:48,225 - pyskl - INFO - Epoch [19][400/1281] lr: 2.409e-02, eta: 18:08:18, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8094, top5_acc: 0.9869, loss_cls: 0.8658, loss: 0.8658 +2025-06-24 13:15:26,706 - pyskl - INFO - Epoch [19][500/1281] lr: 2.408e-02, eta: 18:07:37, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.8013, top5_acc: 0.9850, loss_cls: 0.9043, loss: 0.9043 +2025-06-24 13:16:04,800 - pyskl - INFO - Epoch [19][600/1281] lr: 2.408e-02, eta: 18:06:54, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8294, top5_acc: 0.9894, loss_cls: 0.7983, loss: 0.7983 +2025-06-24 13:16:43,338 - pyskl - INFO - Epoch [19][700/1281] lr: 2.407e-02, eta: 18:06:14, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.8081, top5_acc: 0.9825, loss_cls: 0.8372, loss: 0.8372 +2025-06-24 13:17:21,433 - pyskl - INFO - Epoch [19][800/1281] lr: 2.406e-02, eta: 18:05:31, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.7975, top5_acc: 0.9900, loss_cls: 0.8636, loss: 0.8636 +2025-06-24 13:17:59,090 - pyskl - INFO - Epoch [19][900/1281] lr: 2.405e-02, eta: 18:04:45, time: 0.377, data_time: 0.000, memory: 4082, top1_acc: 0.8031, top5_acc: 0.9856, loss_cls: 0.8575, loss: 0.8575 +2025-06-24 13:18:37,118 - pyskl - INFO - Epoch [19][1000/1281] lr: 2.405e-02, eta: 18:04:02, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8325, top5_acc: 0.9900, loss_cls: 0.7744, loss: 0.7744 +2025-06-24 13:19:15,103 - pyskl - INFO - Epoch [19][1100/1281] lr: 2.404e-02, eta: 18:03:18, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8244, top5_acc: 0.9894, loss_cls: 0.8072, loss: 0.8072 +2025-06-24 13:19:52,977 - pyskl - INFO - Epoch [19][1200/1281] lr: 2.403e-02, eta: 18:02:34, time: 0.379, data_time: 0.000, memory: 4082, top1_acc: 0.7975, top5_acc: 0.9888, loss_cls: 0.8854, loss: 0.8854 +2025-06-24 13:20:23,945 - pyskl - INFO - Saving checkpoint at 19 epochs +2025-06-24 13:21:22,870 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:21:22,927 - pyskl - INFO - +top1_acc 0.7808 +top5_acc 0.9791 +2025-06-24 13:21:22,927 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:21:22,934 - pyskl - INFO - +mean_acc 0.7036 +2025-06-24 13:21:22,938 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_17.pth was removed +2025-06-24 13:21:23,116 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_19.pth. +2025-06-24 13:21:23,116 - pyskl - INFO - Best top1_acc is 0.7808 at 19 epoch. +2025-06-24 13:21:23,119 - pyskl - INFO - Epoch(val) [19][533] top1_acc: 0.7808, top5_acc: 0.9791, mean_class_accuracy: 0.7036 +2025-06-24 13:22:20,187 - pyskl - INFO - Epoch [20][100/1281] lr: 2.402e-02, eta: 17:59:55, time: 0.571, data_time: 0.191, memory: 4082, top1_acc: 0.8244, top5_acc: 0.9894, loss_cls: 0.8015, loss: 0.8015 +2025-06-24 13:22:47,313 - pyskl - INFO - Epoch [20][200/1281] lr: 2.401e-02, eta: 17:57:58, time: 0.271, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9925, loss_cls: 0.7618, loss: 0.7618 +2025-06-24 13:23:28,727 - pyskl - INFO - Epoch [20][300/1281] lr: 2.400e-02, eta: 17:57:38, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8063, top5_acc: 0.9850, loss_cls: 0.8419, loss: 0.8419 +2025-06-24 13:23:58,207 - pyskl - INFO - Epoch [20][400/1281] lr: 2.399e-02, eta: 17:55:58, time: 0.295, data_time: 0.000, memory: 4082, top1_acc: 0.8194, top5_acc: 0.9938, loss_cls: 0.7968, loss: 0.7968 +2025-06-24 13:24:25,598 - pyskl - INFO - Epoch [20][500/1281] lr: 2.398e-02, eta: 17:54:04, time: 0.274, data_time: 0.000, memory: 4082, top1_acc: 0.8413, top5_acc: 0.9881, loss_cls: 0.7485, loss: 0.7485 +2025-06-24 13:25:03,545 - pyskl - INFO - Epoch [20][600/1281] lr: 2.398e-02, eta: 17:53:22, time: 0.379, data_time: 0.000, memory: 4082, top1_acc: 0.8063, top5_acc: 0.9806, loss_cls: 0.8756, loss: 0.8756 +2025-06-24 13:25:41,308 - pyskl - INFO - Epoch [20][700/1281] lr: 2.397e-02, eta: 17:52:38, time: 0.378, data_time: 0.000, memory: 4082, top1_acc: 0.8225, top5_acc: 0.9838, loss_cls: 0.8137, loss: 0.8137 +2025-06-24 13:26:19,679 - pyskl - INFO - Epoch [20][800/1281] lr: 2.396e-02, eta: 17:51:59, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8006, top5_acc: 0.9862, loss_cls: 0.8628, loss: 0.8628 +2025-06-24 13:26:57,339 - pyskl - INFO - Epoch [20][900/1281] lr: 2.395e-02, eta: 17:51:15, time: 0.377, data_time: 0.000, memory: 4082, top1_acc: 0.8094, top5_acc: 0.9894, loss_cls: 0.8336, loss: 0.8336 +2025-06-24 13:27:36,024 - pyskl - INFO - Epoch [20][1000/1281] lr: 2.394e-02, eta: 17:50:37, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.8488, top5_acc: 0.9919, loss_cls: 0.7587, loss: 0.7587 +2025-06-24 13:28:14,000 - pyskl - INFO - Epoch [20][1100/1281] lr: 2.393e-02, eta: 17:49:55, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8200, top5_acc: 0.9894, loss_cls: 0.8194, loss: 0.8194 +2025-06-24 13:28:52,553 - pyskl - INFO - Epoch [20][1200/1281] lr: 2.393e-02, eta: 17:49:17, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8181, top5_acc: 0.9888, loss_cls: 0.8039, loss: 0.8039 +2025-06-24 13:29:23,535 - pyskl - INFO - Saving checkpoint at 20 epochs +2025-06-24 13:30:22,798 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:30:22,872 - pyskl - INFO - +top1_acc 0.7618 +top5_acc 0.9786 +2025-06-24 13:30:22,872 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:30:22,879 - pyskl - INFO - +mean_acc 0.6520 +2025-06-24 13:30:22,882 - pyskl - INFO - Epoch(val) [20][533] top1_acc: 0.7618, top5_acc: 0.9786, mean_class_accuracy: 0.6520 +2025-06-24 13:31:20,586 - pyskl - INFO - Epoch [21][100/1281] lr: 2.391e-02, eta: 17:46:50, time: 0.577, data_time: 0.192, memory: 4082, top1_acc: 0.8150, top5_acc: 0.9900, loss_cls: 0.8140, loss: 0.8140 +2025-06-24 13:31:58,759 - pyskl - INFO - Epoch [21][200/1281] lr: 2.390e-02, eta: 17:46:09, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8306, top5_acc: 0.9938, loss_cls: 0.7087, loss: 0.7087 +2025-06-24 13:32:36,930 - pyskl - INFO - Epoch [21][300/1281] lr: 2.389e-02, eta: 17:45:29, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9862, loss_cls: 0.8044, loss: 0.8044 +2025-06-24 13:33:15,295 - pyskl - INFO - Epoch [21][400/1281] lr: 2.389e-02, eta: 17:44:50, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8244, top5_acc: 0.9844, loss_cls: 0.7843, loss: 0.7843 +2025-06-24 13:33:52,823 - pyskl - INFO - Epoch [21][500/1281] lr: 2.388e-02, eta: 17:44:06, time: 0.375, data_time: 0.000, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9906, loss_cls: 0.7499, loss: 0.7499 +2025-06-24 13:34:30,585 - pyskl - INFO - Epoch [21][600/1281] lr: 2.387e-02, eta: 17:43:23, time: 0.378, data_time: 0.000, memory: 4082, top1_acc: 0.8187, top5_acc: 0.9850, loss_cls: 0.8096, loss: 0.8096 +2025-06-24 13:34:59,372 - pyskl - INFO - Epoch [21][700/1281] lr: 2.386e-02, eta: 17:41:43, time: 0.288, data_time: 0.000, memory: 4082, top1_acc: 0.8200, top5_acc: 0.9894, loss_cls: 0.7911, loss: 0.7911 +2025-06-24 13:35:38,625 - pyskl - INFO - Epoch [21][800/1281] lr: 2.385e-02, eta: 17:41:10, time: 0.393, data_time: 0.000, memory: 4082, top1_acc: 0.8137, top5_acc: 0.9875, loss_cls: 0.8509, loss: 0.8509 +2025-06-24 13:36:10,430 - pyskl - INFO - Epoch [21][900/1281] lr: 2.384e-02, eta: 17:39:50, time: 0.318, data_time: 0.000, memory: 4082, top1_acc: 0.8137, top5_acc: 0.9912, loss_cls: 0.8341, loss: 0.8341 +2025-06-24 13:36:36,749 - pyskl - INFO - Epoch [21][1000/1281] lr: 2.383e-02, eta: 17:37:57, time: 0.263, data_time: 0.000, memory: 4082, top1_acc: 0.8213, top5_acc: 0.9875, loss_cls: 0.8248, loss: 0.8248 +2025-06-24 13:37:14,248 - pyskl - INFO - Epoch [21][1100/1281] lr: 2.383e-02, eta: 17:37:13, time: 0.375, data_time: 0.000, memory: 4082, top1_acc: 0.8381, top5_acc: 0.9931, loss_cls: 0.7402, loss: 0.7402 +2025-06-24 13:37:52,820 - pyskl - INFO - Epoch [21][1200/1281] lr: 2.382e-02, eta: 17:36:36, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.7931, top5_acc: 0.9850, loss_cls: 0.9086, loss: 0.9086 +2025-06-24 13:38:24,232 - pyskl - INFO - Saving checkpoint at 21 epochs +2025-06-24 13:39:23,807 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:39:23,875 - pyskl - INFO - +top1_acc 0.7963 +top5_acc 0.9850 +2025-06-24 13:39:23,875 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:39:23,883 - pyskl - INFO - +mean_acc 0.7199 +2025-06-24 13:39:23,888 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_19.pth was removed +2025-06-24 13:39:24,066 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_21.pth. +2025-06-24 13:39:24,066 - pyskl - INFO - Best top1_acc is 0.7963 at 21 epoch. +2025-06-24 13:39:24,069 - pyskl - INFO - Epoch(val) [21][533] top1_acc: 0.7963, top5_acc: 0.9850, mean_class_accuracy: 0.7199 +2025-06-24 13:40:21,666 - pyskl - INFO - Epoch [22][100/1281] lr: 2.380e-02, eta: 17:34:15, time: 0.576, data_time: 0.199, memory: 4082, top1_acc: 0.8244, top5_acc: 0.9912, loss_cls: 0.7681, loss: 0.7681 +2025-06-24 13:41:00,428 - pyskl - INFO - Epoch [22][200/1281] lr: 2.379e-02, eta: 17:33:39, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8406, top5_acc: 0.9875, loss_cls: 0.7867, loss: 0.7867 +2025-06-24 13:41:38,810 - pyskl - INFO - Epoch [22][300/1281] lr: 2.378e-02, eta: 17:33:01, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8219, top5_acc: 0.9875, loss_cls: 0.8066, loss: 0.8066 +2025-06-24 13:42:16,769 - pyskl - INFO - Epoch [22][400/1281] lr: 2.378e-02, eta: 17:32:21, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8337, top5_acc: 0.9912, loss_cls: 0.7559, loss: 0.7559 +2025-06-24 13:42:54,318 - pyskl - INFO - Epoch [22][500/1281] lr: 2.377e-02, eta: 17:31:38, time: 0.375, data_time: 0.000, memory: 4082, top1_acc: 0.8144, top5_acc: 0.9900, loss_cls: 0.8158, loss: 0.8158 +2025-06-24 13:43:32,326 - pyskl - INFO - Epoch [22][600/1281] lr: 2.376e-02, eta: 17:30:58, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8244, top5_acc: 0.9900, loss_cls: 0.7828, loss: 0.7828 +2025-06-24 13:44:11,411 - pyskl - INFO - Epoch [22][700/1281] lr: 2.375e-02, eta: 17:30:25, time: 0.391, data_time: 0.000, memory: 4082, top1_acc: 0.8500, top5_acc: 0.9900, loss_cls: 0.7016, loss: 0.7016 +2025-06-24 13:44:49,010 - pyskl - INFO - Epoch [22][800/1281] lr: 2.374e-02, eta: 17:29:42, time: 0.376, data_time: 0.000, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9844, loss_cls: 0.7912, loss: 0.7912 +2025-06-24 13:45:27,067 - pyskl - INFO - Epoch [22][900/1281] lr: 2.373e-02, eta: 17:29:02, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8037, top5_acc: 0.9862, loss_cls: 0.8570, loss: 0.8570 +2025-06-24 13:46:05,336 - pyskl - INFO - Epoch [22][1000/1281] lr: 2.372e-02, eta: 17:28:24, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.8100, top5_acc: 0.9912, loss_cls: 0.8127, loss: 0.8127 +2025-06-24 13:46:43,796 - pyskl - INFO - Epoch [22][1100/1281] lr: 2.371e-02, eta: 17:27:46, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.8250, top5_acc: 0.9912, loss_cls: 0.7974, loss: 0.7974 +2025-06-24 13:47:11,929 - pyskl - INFO - Epoch [22][1200/1281] lr: 2.370e-02, eta: 17:26:09, time: 0.281, data_time: 0.001, memory: 4082, top1_acc: 0.8256, top5_acc: 0.9844, loss_cls: 0.8119, loss: 0.8119 +2025-06-24 13:47:43,138 - pyskl - INFO - Saving checkpoint at 22 epochs +2025-06-24 13:48:29,323 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:48:29,384 - pyskl - INFO - +top1_acc 0.7734 +top5_acc 0.9790 +2025-06-24 13:48:29,385 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:48:29,391 - pyskl - INFO - +mean_acc 0.7033 +2025-06-24 13:48:29,393 - pyskl - INFO - Epoch(val) [22][533] top1_acc: 0.7734, top5_acc: 0.9790, mean_class_accuracy: 0.7033 +2025-06-24 13:49:27,884 - pyskl - INFO - Epoch [23][100/1281] lr: 2.369e-02, eta: 17:23:57, time: 0.585, data_time: 0.199, memory: 4082, top1_acc: 0.8100, top5_acc: 0.9869, loss_cls: 0.8359, loss: 0.8359 +2025-06-24 13:50:06,623 - pyskl - INFO - Epoch [23][200/1281] lr: 2.368e-02, eta: 17:23:22, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.8313, top5_acc: 0.9906, loss_cls: 0.7462, loss: 0.7462 +2025-06-24 13:50:45,229 - pyskl - INFO - Epoch [23][300/1281] lr: 2.367e-02, eta: 17:22:46, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9906, loss_cls: 0.7437, loss: 0.7437 +2025-06-24 13:51:23,150 - pyskl - INFO - Epoch [23][400/1281] lr: 2.366e-02, eta: 17:22:06, time: 0.379, data_time: 0.000, memory: 4082, top1_acc: 0.8281, top5_acc: 0.9894, loss_cls: 0.7471, loss: 0.7471 +2025-06-24 13:52:00,790 - pyskl - INFO - Epoch [23][500/1281] lr: 2.365e-02, eta: 17:21:24, time: 0.376, data_time: 0.000, memory: 4082, top1_acc: 0.8294, top5_acc: 0.9912, loss_cls: 0.7455, loss: 0.7455 +2025-06-24 13:52:39,167 - pyskl - INFO - Epoch [23][600/1281] lr: 2.364e-02, eta: 17:20:47, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8337, top5_acc: 0.9906, loss_cls: 0.7505, loss: 0.7505 +2025-06-24 13:53:17,423 - pyskl - INFO - Epoch [23][700/1281] lr: 2.363e-02, eta: 17:20:09, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.8325, top5_acc: 0.9894, loss_cls: 0.7628, loss: 0.7628 +2025-06-24 13:53:55,763 - pyskl - INFO - Epoch [23][800/1281] lr: 2.362e-02, eta: 17:19:31, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.8094, top5_acc: 0.9906, loss_cls: 0.8383, loss: 0.8383 +2025-06-24 13:54:33,281 - pyskl - INFO - Epoch [23][900/1281] lr: 2.361e-02, eta: 17:18:49, time: 0.375, data_time: 0.000, memory: 4082, top1_acc: 0.8200, top5_acc: 0.9869, loss_cls: 0.8106, loss: 0.8106 +2025-06-24 13:55:11,704 - pyskl - INFO - Epoch [23][1000/1281] lr: 2.360e-02, eta: 17:18:12, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8462, top5_acc: 0.9906, loss_cls: 0.7132, loss: 0.7132 +2025-06-24 13:55:50,472 - pyskl - INFO - Epoch [23][1100/1281] lr: 2.359e-02, eta: 17:17:37, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9875, loss_cls: 0.7750, loss: 0.7750 +2025-06-24 13:56:29,172 - pyskl - INFO - Epoch [23][1200/1281] lr: 2.359e-02, eta: 17:17:01, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.8263, top5_acc: 0.9894, loss_cls: 0.7770, loss: 0.7770 +2025-06-24 13:57:00,536 - pyskl - INFO - Saving checkpoint at 23 epochs +2025-06-24 13:57:59,572 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:57:59,641 - pyskl - INFO - +top1_acc 0.7984 +top5_acc 0.9830 +2025-06-24 13:57:59,641 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:57:59,649 - pyskl - INFO - +mean_acc 0.7314 +2025-06-24 13:57:59,653 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_21.pth was removed +2025-06-24 13:57:59,864 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_23.pth. +2025-06-24 13:57:59,865 - pyskl - INFO - Best top1_acc is 0.7984 at 23 epoch. +2025-06-24 13:57:59,867 - pyskl - INFO - Epoch(val) [23][533] top1_acc: 0.7984, top5_acc: 0.9830, mean_class_accuracy: 0.7314 +2025-06-24 13:58:44,913 - pyskl - INFO - Epoch [24][100/1281] lr: 2.357e-02, eta: 17:13:39, time: 0.450, data_time: 0.196, memory: 4082, top1_acc: 0.8431, top5_acc: 0.9944, loss_cls: 0.7287, loss: 0.7287 +2025-06-24 13:59:29,363 - pyskl - INFO - Epoch [24][200/1281] lr: 2.356e-02, eta: 17:13:36, time: 0.444, data_time: 0.000, memory: 4082, top1_acc: 0.8331, top5_acc: 0.9938, loss_cls: 0.7284, loss: 0.7284 +2025-06-24 13:59:56,220 - pyskl - INFO - Epoch [24][300/1281] lr: 2.355e-02, eta: 17:11:56, time: 0.269, data_time: 0.000, memory: 4082, top1_acc: 0.8250, top5_acc: 0.9962, loss_cls: 0.7724, loss: 0.7724 +2025-06-24 14:00:26,562 - pyskl - INFO - Epoch [24][400/1281] lr: 2.354e-02, eta: 17:10:35, time: 0.303, data_time: 0.000, memory: 4082, top1_acc: 0.8400, top5_acc: 0.9875, loss_cls: 0.7358, loss: 0.7358 +2025-06-24 14:01:04,738 - pyskl - INFO - Epoch [24][500/1281] lr: 2.353e-02, eta: 17:09:57, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8344, top5_acc: 0.9856, loss_cls: 0.7661, loss: 0.7661 +2025-06-24 14:01:43,032 - pyskl - INFO - Epoch [24][600/1281] lr: 2.352e-02, eta: 17:09:20, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.8169, top5_acc: 0.9906, loss_cls: 0.8078, loss: 0.8078 +2025-06-24 14:02:21,765 - pyskl - INFO - Epoch [24][700/1281] lr: 2.351e-02, eta: 17:08:46, time: 0.387, data_time: 0.000, memory: 4082, top1_acc: 0.8250, top5_acc: 0.9931, loss_cls: 0.7666, loss: 0.7666 +2025-06-24 14:03:00,373 - pyskl - INFO - Epoch [24][800/1281] lr: 2.350e-02, eta: 17:08:10, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8169, top5_acc: 0.9862, loss_cls: 0.8097, loss: 0.8097 +2025-06-24 14:03:39,182 - pyskl - INFO - Epoch [24][900/1281] lr: 2.349e-02, eta: 17:07:36, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8256, top5_acc: 0.9906, loss_cls: 0.7638, loss: 0.7638 +2025-06-24 14:04:17,344 - pyskl - INFO - Epoch [24][1000/1281] lr: 2.348e-02, eta: 17:06:58, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8231, top5_acc: 0.9856, loss_cls: 0.7750, loss: 0.7750 +2025-06-24 14:04:55,724 - pyskl - INFO - Epoch [24][1100/1281] lr: 2.347e-02, eta: 17:06:21, time: 0.384, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9869, loss_cls: 0.7895, loss: 0.7895 +2025-06-24 14:05:33,805 - pyskl - INFO - Epoch [24][1200/1281] lr: 2.346e-02, eta: 17:05:43, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8337, top5_acc: 0.9900, loss_cls: 0.7938, loss: 0.7938 +2025-06-24 14:06:05,677 - pyskl - INFO - Saving checkpoint at 24 epochs +2025-06-24 14:07:05,098 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:07:05,158 - pyskl - INFO - +top1_acc 0.7761 +top5_acc 0.9781 +2025-06-24 14:07:05,158 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:07:05,165 - pyskl - INFO - +mean_acc 0.7098 +2025-06-24 14:07:05,167 - pyskl - INFO - Epoch(val) [24][533] top1_acc: 0.7761, top5_acc: 0.9781, mean_class_accuracy: 0.7098 +2025-06-24 14:08:03,202 - pyskl - INFO - Epoch [25][100/1281] lr: 2.344e-02, eta: 17:03:37, time: 0.580, data_time: 0.195, memory: 4082, top1_acc: 0.8413, top5_acc: 0.9869, loss_cls: 0.7307, loss: 0.7307 +2025-06-24 14:08:41,822 - pyskl - INFO - Epoch [25][200/1281] lr: 2.343e-02, eta: 17:03:02, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8306, top5_acc: 0.9894, loss_cls: 0.7442, loss: 0.7442 +2025-06-24 14:09:19,361 - pyskl - INFO - Epoch [25][300/1281] lr: 2.342e-02, eta: 17:02:21, time: 0.375, data_time: 0.000, memory: 4082, top1_acc: 0.8381, top5_acc: 0.9900, loss_cls: 0.7179, loss: 0.7179 +2025-06-24 14:09:57,425 - pyskl - INFO - Epoch [25][400/1281] lr: 2.341e-02, eta: 17:01:43, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8413, top5_acc: 0.9956, loss_cls: 0.6769, loss: 0.6769 +2025-06-24 14:10:34,998 - pyskl - INFO - Epoch [25][500/1281] lr: 2.340e-02, eta: 17:01:02, time: 0.376, data_time: 0.000, memory: 4082, top1_acc: 0.8356, top5_acc: 0.9900, loss_cls: 0.7694, loss: 0.7694 +2025-06-24 14:10:59,770 - pyskl - INFO - Epoch [25][600/1281] lr: 2.339e-02, eta: 16:59:16, time: 0.248, data_time: 0.000, memory: 4082, top1_acc: 0.8425, top5_acc: 0.9925, loss_cls: 0.7340, loss: 0.7340 +2025-06-24 14:11:45,211 - pyskl - INFO - Epoch [25][700/1281] lr: 2.338e-02, eta: 16:59:15, time: 0.454, data_time: 0.000, memory: 4082, top1_acc: 0.8400, top5_acc: 0.9944, loss_cls: 0.7336, loss: 0.7336 +2025-06-24 14:12:08,377 - pyskl - INFO - Epoch [25][800/1281] lr: 2.337e-02, eta: 16:57:22, time: 0.232, data_time: 0.000, memory: 4082, top1_acc: 0.8169, top5_acc: 0.9875, loss_cls: 0.7912, loss: 0.7912 +2025-06-24 14:12:40,224 - pyskl - INFO - Epoch [25][900/1281] lr: 2.336e-02, eta: 16:56:12, time: 0.318, data_time: 0.000, memory: 4082, top1_acc: 0.8175, top5_acc: 0.9862, loss_cls: 0.7991, loss: 0.7991 +2025-06-24 14:13:18,232 - pyskl - INFO - Epoch [25][1000/1281] lr: 2.335e-02, eta: 16:55:34, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8256, top5_acc: 0.9919, loss_cls: 0.7658, loss: 0.7658 +2025-06-24 14:13:56,265 - pyskl - INFO - Epoch [25][1100/1281] lr: 2.334e-02, eta: 16:54:57, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8506, top5_acc: 0.9894, loss_cls: 0.6909, loss: 0.6909 +2025-06-24 14:14:34,891 - pyskl - INFO - Epoch [25][1200/1281] lr: 2.333e-02, eta: 16:54:22, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8181, top5_acc: 0.9900, loss_cls: 0.7739, loss: 0.7739 +2025-06-24 14:15:06,623 - pyskl - INFO - Saving checkpoint at 25 epochs +2025-06-24 14:16:05,636 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:16:05,690 - pyskl - INFO - +top1_acc 0.7877 +top5_acc 0.9847 +2025-06-24 14:16:05,691 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:16:05,697 - pyskl - INFO - +mean_acc 0.7187 +2025-06-24 14:16:05,698 - pyskl - INFO - Epoch(val) [25][533] top1_acc: 0.7877, top5_acc: 0.9847, mean_class_accuracy: 0.7187 +2025-06-24 14:17:03,553 - pyskl - INFO - Epoch [26][100/1281] lr: 2.332e-02, eta: 16:52:19, time: 0.579, data_time: 0.199, memory: 4082, top1_acc: 0.8450, top5_acc: 0.9906, loss_cls: 0.7282, loss: 0.7282 +2025-06-24 14:17:41,804 - pyskl - INFO - Epoch [26][200/1281] lr: 2.330e-02, eta: 16:51:42, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8512, top5_acc: 0.9900, loss_cls: 0.6602, loss: 0.6602 +2025-06-24 14:18:20,381 - pyskl - INFO - Epoch [26][300/1281] lr: 2.329e-02, eta: 16:51:07, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8500, top5_acc: 0.9912, loss_cls: 0.7089, loss: 0.7089 +2025-06-24 14:18:58,437 - pyskl - INFO - Epoch [26][400/1281] lr: 2.328e-02, eta: 16:50:30, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8263, top5_acc: 0.9875, loss_cls: 0.7751, loss: 0.7751 +2025-06-24 14:19:35,996 - pyskl - INFO - Epoch [26][500/1281] lr: 2.327e-02, eta: 16:49:50, time: 0.376, data_time: 0.000, memory: 4082, top1_acc: 0.8219, top5_acc: 0.9881, loss_cls: 0.7948, loss: 0.7948 +2025-06-24 14:20:14,190 - pyskl - INFO - Epoch [26][600/1281] lr: 2.326e-02, eta: 16:49:13, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8256, top5_acc: 0.9906, loss_cls: 0.7580, loss: 0.7580 +2025-06-24 14:20:52,053 - pyskl - INFO - Epoch [26][700/1281] lr: 2.325e-02, eta: 16:48:35, time: 0.379, data_time: 0.000, memory: 4082, top1_acc: 0.8325, top5_acc: 0.9944, loss_cls: 0.7535, loss: 0.7535 +2025-06-24 14:21:30,335 - pyskl - INFO - Epoch [26][800/1281] lr: 2.324e-02, eta: 16:47:58, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.8081, top5_acc: 0.9912, loss_cls: 0.8213, loss: 0.8213 +2025-06-24 14:22:09,139 - pyskl - INFO - Epoch [26][900/1281] lr: 2.323e-02, eta: 16:47:24, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8150, top5_acc: 0.9888, loss_cls: 0.8330, loss: 0.8330 +2025-06-24 14:22:46,826 - pyskl - INFO - Epoch [26][1000/1281] lr: 2.322e-02, eta: 16:46:45, time: 0.377, data_time: 0.000, memory: 4082, top1_acc: 0.8494, top5_acc: 0.9944, loss_cls: 0.6876, loss: 0.6876 +2025-06-24 14:23:13,488 - pyskl - INFO - Epoch [26][1100/1281] lr: 2.321e-02, eta: 16:45:13, time: 0.267, data_time: 0.000, memory: 4082, top1_acc: 0.8550, top5_acc: 0.9969, loss_cls: 0.6806, loss: 0.6806 +2025-06-24 14:23:57,869 - pyskl - INFO - Epoch [26][1200/1281] lr: 2.320e-02, eta: 16:45:06, time: 0.444, data_time: 0.000, memory: 4082, top1_acc: 0.8294, top5_acc: 0.9938, loss_cls: 0.7155, loss: 0.7155 +2025-06-24 14:24:16,658 - pyskl - INFO - Saving checkpoint at 26 epochs +2025-06-24 14:25:16,305 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:25:16,376 - pyskl - INFO - +top1_acc 0.7988 +top5_acc 0.9832 +2025-06-24 14:25:16,376 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:25:16,383 - pyskl - INFO - +mean_acc 0.7320 +2025-06-24 14:25:16,388 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_23.pth was removed +2025-06-24 14:25:16,598 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_26.pth. +2025-06-24 14:25:16,599 - pyskl - INFO - Best top1_acc is 0.7988 at 26 epoch. +2025-06-24 14:25:16,603 - pyskl - INFO - Epoch(val) [26][533] top1_acc: 0.7988, top5_acc: 0.9832, mean_class_accuracy: 0.7320 +2025-06-24 14:26:15,244 - pyskl - INFO - Epoch [27][100/1281] lr: 2.318e-02, eta: 16:43:09, time: 0.586, data_time: 0.198, memory: 4082, top1_acc: 0.8512, top5_acc: 0.9956, loss_cls: 0.6912, loss: 0.6912 +2025-06-24 14:26:54,111 - pyskl - INFO - Epoch [27][200/1281] lr: 2.317e-02, eta: 16:42:36, time: 0.389, data_time: 0.000, memory: 4082, top1_acc: 0.8488, top5_acc: 0.9925, loss_cls: 0.6607, loss: 0.6607 +2025-06-24 14:27:33,579 - pyskl - INFO - Epoch [27][300/1281] lr: 2.316e-02, eta: 16:42:05, time: 0.395, data_time: 0.000, memory: 4082, top1_acc: 0.8462, top5_acc: 0.9919, loss_cls: 0.6987, loss: 0.6987 +2025-06-24 14:28:12,429 - pyskl - INFO - Epoch [27][400/1281] lr: 2.315e-02, eta: 16:41:32, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8406, top5_acc: 0.9950, loss_cls: 0.7058, loss: 0.7058 +2025-06-24 14:28:51,219 - pyskl - INFO - Epoch [27][500/1281] lr: 2.314e-02, eta: 16:40:58, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8450, top5_acc: 0.9912, loss_cls: 0.7450, loss: 0.7450 +2025-06-24 14:29:29,315 - pyskl - INFO - Epoch [27][600/1281] lr: 2.313e-02, eta: 16:40:21, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8131, top5_acc: 0.9869, loss_cls: 0.8082, loss: 0.8082 +2025-06-24 14:30:07,842 - pyskl - INFO - Epoch [27][700/1281] lr: 2.312e-02, eta: 16:39:46, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9912, loss_cls: 0.8029, loss: 0.8029 +2025-06-24 14:30:46,996 - pyskl - INFO - Epoch [27][800/1281] lr: 2.311e-02, eta: 16:39:13, time: 0.392, data_time: 0.000, memory: 4082, top1_acc: 0.8375, top5_acc: 0.9894, loss_cls: 0.7510, loss: 0.7510 +2025-06-24 14:31:25,121 - pyskl - INFO - Epoch [27][900/1281] lr: 2.310e-02, eta: 16:38:36, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9950, loss_cls: 0.7024, loss: 0.7024 +2025-06-24 14:32:02,405 - pyskl - INFO - Epoch [27][1000/1281] lr: 2.308e-02, eta: 16:37:55, time: 0.373, data_time: 0.000, memory: 4082, top1_acc: 0.8400, top5_acc: 0.9925, loss_cls: 0.7444, loss: 0.7444 +2025-06-24 14:32:40,635 - pyskl - INFO - Epoch [27][1100/1281] lr: 2.307e-02, eta: 16:37:19, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8369, top5_acc: 0.9900, loss_cls: 0.7346, loss: 0.7346 +2025-06-24 14:33:19,200 - pyskl - INFO - Epoch [27][1200/1281] lr: 2.306e-02, eta: 16:36:44, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9894, loss_cls: 0.7398, loss: 0.7398 +2025-06-24 14:33:50,944 - pyskl - INFO - Saving checkpoint at 27 epochs +2025-06-24 14:34:39,516 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:34:39,570 - pyskl - INFO - +top1_acc 0.6599 +top5_acc 0.9428 +2025-06-24 14:34:39,570 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:34:39,577 - pyskl - INFO - +mean_acc 0.5887 +2025-06-24 14:34:39,578 - pyskl - INFO - Epoch(val) [27][533] top1_acc: 0.6599, top5_acc: 0.9428, mean_class_accuracy: 0.5887 +2025-06-24 14:35:26,847 - pyskl - INFO - Epoch [28][100/1281] lr: 2.304e-02, eta: 16:33:58, time: 0.473, data_time: 0.195, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9912, loss_cls: 0.7604, loss: 0.7604 +2025-06-24 14:35:55,426 - pyskl - INFO - Epoch [28][200/1281] lr: 2.303e-02, eta: 16:32:38, time: 0.286, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9944, loss_cls: 0.6956, loss: 0.6956 +2025-06-24 14:36:33,773 - pyskl - INFO - Epoch [28][300/1281] lr: 2.302e-02, eta: 16:32:02, time: 0.383, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9900, loss_cls: 0.7150, loss: 0.7150 +2025-06-24 14:37:11,658 - pyskl - INFO - Epoch [28][400/1281] lr: 2.301e-02, eta: 16:31:25, time: 0.379, data_time: 0.000, memory: 4082, top1_acc: 0.8400, top5_acc: 0.9925, loss_cls: 0.7030, loss: 0.7030 +2025-06-24 14:37:49,673 - pyskl - INFO - Epoch [28][500/1281] lr: 2.300e-02, eta: 16:30:48, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8394, top5_acc: 0.9925, loss_cls: 0.7593, loss: 0.7593 +2025-06-24 14:38:27,443 - pyskl - INFO - Epoch [28][600/1281] lr: 2.299e-02, eta: 16:30:09, time: 0.378, data_time: 0.000, memory: 4082, top1_acc: 0.8219, top5_acc: 0.9894, loss_cls: 0.7652, loss: 0.7652 +2025-06-24 14:39:05,645 - pyskl - INFO - Epoch [28][700/1281] lr: 2.298e-02, eta: 16:29:33, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8675, top5_acc: 0.9900, loss_cls: 0.6783, loss: 0.6783 +2025-06-24 14:39:45,396 - pyskl - INFO - Epoch [28][800/1281] lr: 2.297e-02, eta: 16:29:04, time: 0.397, data_time: 0.000, memory: 4082, top1_acc: 0.8237, top5_acc: 0.9919, loss_cls: 0.7802, loss: 0.7802 +2025-06-24 14:40:23,389 - pyskl - INFO - Epoch [28][900/1281] lr: 2.295e-02, eta: 16:28:26, time: 0.380, data_time: 0.000, memory: 4082, top1_acc: 0.8431, top5_acc: 0.9894, loss_cls: 0.7327, loss: 0.7327 +2025-06-24 14:41:02,301 - pyskl - INFO - Epoch [28][1000/1281] lr: 2.294e-02, eta: 16:27:53, time: 0.389, data_time: 0.000, memory: 4082, top1_acc: 0.8281, top5_acc: 0.9894, loss_cls: 0.7669, loss: 0.7669 +2025-06-24 14:41:40,823 - pyskl - INFO - Epoch [28][1100/1281] lr: 2.293e-02, eta: 16:27:18, time: 0.385, data_time: 0.000, memory: 4082, top1_acc: 0.8475, top5_acc: 0.9912, loss_cls: 0.7023, loss: 0.7023 +2025-06-24 14:42:18,375 - pyskl - INFO - Epoch [28][1200/1281] lr: 2.292e-02, eta: 16:26:39, time: 0.376, data_time: 0.000, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9875, loss_cls: 0.7626, loss: 0.7626 +2025-06-24 14:42:48,922 - pyskl - INFO - Saving checkpoint at 28 epochs +2025-06-24 14:43:48,099 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:43:48,157 - pyskl - INFO - +top1_acc 0.8113 +top5_acc 0.9836 +2025-06-24 14:43:48,157 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:43:48,164 - pyskl - INFO - +mean_acc 0.7589 +2025-06-24 14:43:48,169 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_26.pth was removed +2025-06-24 14:43:48,369 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_28.pth. +2025-06-24 14:43:48,370 - pyskl - INFO - Best top1_acc is 0.8113 at 28 epoch. +2025-06-24 14:43:48,372 - pyskl - INFO - Epoch(val) [28][533] top1_acc: 0.8113, top5_acc: 0.9836, mean_class_accuracy: 0.7589 +2025-06-24 14:44:46,077 - pyskl - INFO - Epoch [29][100/1281] lr: 2.290e-02, eta: 16:24:43, time: 0.577, data_time: 0.192, memory: 4082, top1_acc: 0.8625, top5_acc: 0.9931, loss_cls: 0.6577, loss: 0.6577 +2025-06-24 14:45:24,175 - pyskl - INFO - Epoch [29][200/1281] lr: 2.289e-02, eta: 16:24:07, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8431, top5_acc: 0.9950, loss_cls: 0.6844, loss: 0.6844 +2025-06-24 14:46:02,807 - pyskl - INFO - Epoch [29][300/1281] lr: 2.288e-02, eta: 16:23:32, time: 0.386, data_time: 0.000, memory: 4082, top1_acc: 0.8369, top5_acc: 0.9862, loss_cls: 0.7304, loss: 0.7304 +2025-06-24 14:46:28,178 - pyskl - INFO - Epoch [29][400/1281] lr: 2.287e-02, eta: 16:22:01, time: 0.254, data_time: 0.000, memory: 4082, top1_acc: 0.8181, top5_acc: 0.9894, loss_cls: 0.8028, loss: 0.8028 +2025-06-24 14:47:13,322 - pyskl - INFO - Epoch [29][500/1281] lr: 2.285e-02, eta: 16:21:55, time: 0.451, data_time: 0.000, memory: 4082, top1_acc: 0.8456, top5_acc: 0.9944, loss_cls: 0.7131, loss: 0.7131 +2025-06-24 14:47:38,571 - pyskl - INFO - Epoch [29][600/1281] lr: 2.284e-02, eta: 16:20:23, time: 0.252, data_time: 0.000, memory: 4082, top1_acc: 0.8569, top5_acc: 0.9912, loss_cls: 0.6852, loss: 0.6852 +2025-06-24 14:48:07,998 - pyskl - INFO - Epoch [29][700/1281] lr: 2.283e-02, eta: 16:19:10, time: 0.294, data_time: 0.000, memory: 4082, top1_acc: 0.8575, top5_acc: 0.9906, loss_cls: 0.7032, loss: 0.7032 +2025-06-24 14:48:46,247 - pyskl - INFO - Epoch [29][800/1281] lr: 2.282e-02, eta: 16:18:34, time: 0.382, data_time: 0.000, memory: 4082, top1_acc: 0.8469, top5_acc: 0.9931, loss_cls: 0.6814, loss: 0.6814 +2025-06-24 14:49:25,018 - pyskl - INFO - Epoch [29][900/1281] lr: 2.281e-02, eta: 16:18:01, time: 0.388, data_time: 0.000, memory: 4082, top1_acc: 0.8400, top5_acc: 0.9906, loss_cls: 0.6996, loss: 0.6996 +2025-06-24 14:50:03,120 - pyskl - INFO - Epoch [29][1000/1281] lr: 2.280e-02, eta: 16:17:24, time: 0.381, data_time: 0.000, memory: 4082, top1_acc: 0.8331, top5_acc: 0.9881, loss_cls: 0.7786, loss: 0.7786 +2025-06-24 14:50:40,496 - pyskl - INFO - Epoch [29][1100/1281] lr: 2.279e-02, eta: 16:16:45, time: 0.374, data_time: 0.000, memory: 4082, top1_acc: 0.8431, top5_acc: 0.9850, loss_cls: 0.7502, loss: 0.7502 +2025-06-24 14:51:18,345 - pyskl - INFO - Epoch [29][1200/1281] lr: 2.277e-02, eta: 16:16:07, time: 0.378, data_time: 0.000, memory: 4082, top1_acc: 0.8562, top5_acc: 0.9912, loss_cls: 0.6822, loss: 0.6822 +2025-06-24 14:51:50,017 - pyskl - INFO - Saving checkpoint at 29 epochs +2025-06-24 14:52:49,026 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:52:49,081 - pyskl - INFO - +top1_acc 0.7996 +top5_acc 0.9820 +2025-06-24 14:52:49,081 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:52:49,089 - pyskl - INFO - +mean_acc 0.7465 +2025-06-24 14:52:49,091 - pyskl - INFO - Epoch(val) [29][533] top1_acc: 0.7996, top5_acc: 0.9820, mean_class_accuracy: 0.7465 +2025-06-24 14:53:57,425 - pyskl - INFO - Epoch [30][100/1281] lr: 2.275e-02, eta: 16:14:59, time: 0.683, data_time: 0.199, memory: 4082, top1_acc: 0.8488, top5_acc: 0.9912, loss_cls: 0.6817, loss: 0.6817 +2025-06-24 14:54:45,753 - pyskl - INFO - Epoch [30][200/1281] lr: 2.274e-02, eta: 16:15:05, time: 0.483, data_time: 0.001, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9894, loss_cls: 0.7331, loss: 0.7331 +2025-06-24 14:55:33,928 - pyskl - INFO - Epoch [30][300/1281] lr: 2.273e-02, eta: 16:15:10, time: 0.482, data_time: 0.000, memory: 4082, top1_acc: 0.8494, top5_acc: 0.9912, loss_cls: 0.6897, loss: 0.6897 +2025-06-24 14:56:22,261 - pyskl - INFO - Epoch [30][400/1281] lr: 2.272e-02, eta: 16:15:16, time: 0.483, data_time: 0.000, memory: 4082, top1_acc: 0.8675, top5_acc: 0.9944, loss_cls: 0.6402, loss: 0.6402 +2025-06-24 14:57:10,627 - pyskl - INFO - Epoch [30][500/1281] lr: 2.271e-02, eta: 16:15:21, time: 0.484, data_time: 0.000, memory: 4082, top1_acc: 0.8337, top5_acc: 0.9938, loss_cls: 0.7017, loss: 0.7017 +2025-06-24 14:57:58,708 - pyskl - INFO - Epoch [30][600/1281] lr: 2.269e-02, eta: 16:15:25, time: 0.481, data_time: 0.000, memory: 4082, top1_acc: 0.8500, top5_acc: 0.9944, loss_cls: 0.6731, loss: 0.6731 +2025-06-24 14:58:30,197 - pyskl - INFO - Epoch [30][700/1281] lr: 2.268e-02, eta: 16:14:21, time: 0.315, data_time: 0.000, memory: 4082, top1_acc: 0.8625, top5_acc: 0.9925, loss_cls: 0.6559, loss: 0.6559 +2025-06-24 14:59:12,126 - pyskl - INFO - Epoch [30][800/1281] lr: 2.267e-02, eta: 16:13:59, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.8462, top5_acc: 0.9875, loss_cls: 0.7065, loss: 0.7065 +2025-06-24 14:59:44,374 - pyskl - INFO - Epoch [30][900/1281] lr: 2.266e-02, eta: 16:12:58, time: 0.322, data_time: 0.000, memory: 4082, top1_acc: 0.8450, top5_acc: 0.9819, loss_cls: 0.7532, loss: 0.7532 +2025-06-24 15:00:32,929 - pyskl - INFO - Epoch [30][1000/1281] lr: 2.265e-02, eta: 16:13:04, time: 0.486, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9925, loss_cls: 0.7494, loss: 0.7494 +2025-06-24 15:01:21,201 - pyskl - INFO - Epoch [30][1100/1281] lr: 2.263e-02, eta: 16:13:07, time: 0.483, data_time: 0.000, memory: 4082, top1_acc: 0.8225, top5_acc: 0.9919, loss_cls: 0.7518, loss: 0.7518 +2025-06-24 15:02:09,570 - pyskl - INFO - Epoch [30][1200/1281] lr: 2.262e-02, eta: 16:13:11, time: 0.484, data_time: 0.000, memory: 4082, top1_acc: 0.8481, top5_acc: 0.9894, loss_cls: 0.6805, loss: 0.6805 +2025-06-24 15:02:48,884 - pyskl - INFO - Saving checkpoint at 30 epochs +2025-06-24 15:03:47,367 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:03:47,424 - pyskl - INFO - +top1_acc 0.7815 +top5_acc 0.9815 +2025-06-24 15:03:47,424 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:03:47,431 - pyskl - INFO - +mean_acc 0.7117 +2025-06-24 15:03:47,433 - pyskl - INFO - Epoch(val) [30][533] top1_acc: 0.7815, top5_acc: 0.9815, mean_class_accuracy: 0.7117 +2025-06-24 15:05:13,055 - pyskl - INFO - Epoch [31][100/1281] lr: 2.260e-02, eta: 16:13:10, time: 0.856, data_time: 0.198, memory: 4083, top1_acc: 0.8575, top5_acc: 0.9944, loss_cls: 0.8132, loss: 0.8132 +2025-06-24 15:06:02,068 - pyskl - INFO - Epoch [31][200/1281] lr: 2.259e-02, eta: 16:13:16, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8381, top5_acc: 0.9912, loss_cls: 0.8458, loss: 0.8458 +2025-06-24 15:06:51,110 - pyskl - INFO - Epoch [31][300/1281] lr: 2.258e-02, eta: 16:13:21, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8625, top5_acc: 0.9938, loss_cls: 0.7964, loss: 0.7964 +2025-06-24 15:07:40,084 - pyskl - INFO - Epoch [31][400/1281] lr: 2.256e-02, eta: 16:13:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8556, top5_acc: 0.9938, loss_cls: 0.7957, loss: 0.7957 +2025-06-24 15:08:29,407 - pyskl - INFO - Epoch [31][500/1281] lr: 2.255e-02, eta: 16:13:32, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8569, top5_acc: 0.9931, loss_cls: 0.7905, loss: 0.7905 +2025-06-24 15:09:16,563 - pyskl - INFO - Epoch [31][600/1281] lr: 2.254e-02, eta: 16:13:30, time: 0.472, data_time: 0.000, memory: 4083, top1_acc: 0.8375, top5_acc: 0.9912, loss_cls: 0.8453, loss: 0.8453 +2025-06-24 15:09:50,808 - pyskl - INFO - Epoch [31][700/1281] lr: 2.253e-02, eta: 16:12:36, time: 0.342, data_time: 0.000, memory: 4083, top1_acc: 0.8506, top5_acc: 0.9906, loss_cls: 0.8391, loss: 0.8391 +2025-06-24 15:10:29,864 - pyskl - INFO - Epoch [31][800/1281] lr: 2.252e-02, eta: 16:12:02, time: 0.391, data_time: 0.000, memory: 4083, top1_acc: 0.8506, top5_acc: 0.9919, loss_cls: 0.8102, loss: 0.8102 +2025-06-24 15:11:05,623 - pyskl - INFO - Epoch [31][900/1281] lr: 2.250e-02, eta: 16:11:14, time: 0.358, data_time: 0.000, memory: 4083, top1_acc: 0.8444, top5_acc: 0.9925, loss_cls: 0.8776, loss: 0.8776 +2025-06-24 15:11:54,610 - pyskl - INFO - Epoch [31][1000/1281] lr: 2.249e-02, eta: 16:11:18, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8425, top5_acc: 0.9975, loss_cls: 0.8381, loss: 0.8381 +2025-06-24 15:12:43,739 - pyskl - INFO - Epoch [31][1100/1281] lr: 2.248e-02, eta: 16:11:22, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8313, top5_acc: 0.9875, loss_cls: 0.8864, loss: 0.8864 +2025-06-24 15:13:32,815 - pyskl - INFO - Epoch [31][1200/1281] lr: 2.247e-02, eta: 16:11:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8675, top5_acc: 0.9931, loss_cls: 0.7729, loss: 0.7729 +2025-06-24 15:14:13,007 - pyskl - INFO - Saving checkpoint at 31 epochs +2025-06-24 15:15:11,598 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:15:11,653 - pyskl - INFO - +top1_acc 0.8111 +top5_acc 0.9815 +2025-06-24 15:15:11,653 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:15:11,660 - pyskl - INFO - +mean_acc 0.7461 +2025-06-24 15:15:11,662 - pyskl - INFO - Epoch(val) [31][533] top1_acc: 0.8111, top5_acc: 0.9815, mean_class_accuracy: 0.7461 +2025-06-24 15:16:32,435 - pyskl - INFO - Epoch [32][100/1281] lr: 2.244e-02, eta: 16:11:01, time: 0.808, data_time: 0.192, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9944, loss_cls: 0.6873, loss: 0.6873 +2025-06-24 15:17:21,415 - pyskl - INFO - Epoch [32][200/1281] lr: 2.243e-02, eta: 16:11:04, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8325, top5_acc: 0.9919, loss_cls: 0.7922, loss: 0.7922 +2025-06-24 15:18:10,474 - pyskl - INFO - Epoch [32][300/1281] lr: 2.242e-02, eta: 16:11:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8494, top5_acc: 0.9894, loss_cls: 0.7452, loss: 0.7452 +2025-06-24 15:18:59,920 - pyskl - INFO - Epoch [32][400/1281] lr: 2.241e-02, eta: 16:11:11, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8431, top5_acc: 0.9938, loss_cls: 0.7845, loss: 0.7845 +2025-06-24 15:19:48,981 - pyskl - INFO - Epoch [32][500/1281] lr: 2.239e-02, eta: 16:11:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9919, loss_cls: 0.7351, loss: 0.7351 +2025-06-24 15:20:37,222 - pyskl - INFO - Epoch [32][600/1281] lr: 2.238e-02, eta: 16:11:12, time: 0.482, data_time: 0.000, memory: 4083, top1_acc: 0.8425, top5_acc: 0.9906, loss_cls: 0.7938, loss: 0.7938 +2025-06-24 15:21:12,067 - pyskl - INFO - Epoch [32][700/1281] lr: 2.237e-02, eta: 16:10:20, time: 0.348, data_time: 0.000, memory: 4083, top1_acc: 0.8531, top5_acc: 0.9931, loss_cls: 0.7683, loss: 0.7683 +2025-06-24 15:21:50,990 - pyskl - INFO - Epoch [32][800/1281] lr: 2.236e-02, eta: 16:09:44, time: 0.389, data_time: 0.000, memory: 4083, top1_acc: 0.8519, top5_acc: 0.9912, loss_cls: 0.7362, loss: 0.7362 +2025-06-24 15:22:27,050 - pyskl - INFO - Epoch [32][900/1281] lr: 2.234e-02, eta: 16:08:57, time: 0.361, data_time: 0.000, memory: 4083, top1_acc: 0.8550, top5_acc: 0.9956, loss_cls: 0.7501, loss: 0.7501 +2025-06-24 15:23:15,782 - pyskl - INFO - Epoch [32][1000/1281] lr: 2.233e-02, eta: 16:08:57, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8569, top5_acc: 0.9938, loss_cls: 0.7552, loss: 0.7552 +2025-06-24 15:24:04,626 - pyskl - INFO - Epoch [32][1100/1281] lr: 2.232e-02, eta: 16:08:57, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8625, top5_acc: 0.9900, loss_cls: 0.7656, loss: 0.7656 +2025-06-24 15:24:53,595 - pyskl - INFO - Epoch [32][1200/1281] lr: 2.231e-02, eta: 16:08:58, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8488, top5_acc: 0.9931, loss_cls: 0.7414, loss: 0.7414 +2025-06-24 15:25:33,734 - pyskl - INFO - Saving checkpoint at 32 epochs +2025-06-24 15:26:32,458 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:26:32,527 - pyskl - INFO - +top1_acc 0.7891 +top5_acc 0.9826 +2025-06-24 15:26:32,527 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:26:32,534 - pyskl - INFO - +mean_acc 0.7306 +2025-06-24 15:26:32,536 - pyskl - INFO - Epoch(val) [32][533] top1_acc: 0.7891, top5_acc: 0.9826, mean_class_accuracy: 0.7306 +2025-06-24 15:27:52,325 - pyskl - INFO - Epoch [33][100/1281] lr: 2.228e-02, eta: 16:08:26, time: 0.798, data_time: 0.197, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9962, loss_cls: 0.6343, loss: 0.6343 +2025-06-24 15:28:41,477 - pyskl - INFO - Epoch [33][200/1281] lr: 2.227e-02, eta: 16:08:27, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9931, loss_cls: 0.7035, loss: 0.7035 +2025-06-24 15:29:30,476 - pyskl - INFO - Epoch [33][300/1281] lr: 2.226e-02, eta: 16:08:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9938, loss_cls: 0.6792, loss: 0.6792 +2025-06-24 15:30:19,491 - pyskl - INFO - Epoch [33][400/1281] lr: 2.225e-02, eta: 16:08:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8344, top5_acc: 0.9894, loss_cls: 0.8087, loss: 0.8087 +2025-06-24 15:31:08,621 - pyskl - INFO - Epoch [33][500/1281] lr: 2.223e-02, eta: 16:08:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8512, top5_acc: 0.9912, loss_cls: 0.7198, loss: 0.7198 +2025-06-24 15:31:57,571 - pyskl - INFO - Epoch [33][600/1281] lr: 2.222e-02, eta: 16:08:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8387, top5_acc: 0.9894, loss_cls: 0.7883, loss: 0.7883 +2025-06-24 15:32:29,872 - pyskl - INFO - Epoch [33][700/1281] lr: 2.221e-02, eta: 16:07:24, time: 0.323, data_time: 0.000, memory: 4083, top1_acc: 0.8469, top5_acc: 0.9925, loss_cls: 0.7633, loss: 0.7633 +2025-06-24 15:33:11,353 - pyskl - INFO - Epoch [33][800/1281] lr: 2.219e-02, eta: 16:06:56, time: 0.415, data_time: 0.000, memory: 4083, top1_acc: 0.8644, top5_acc: 0.9944, loss_cls: 0.7057, loss: 0.7057 +2025-06-24 15:33:46,754 - pyskl - INFO - Epoch [33][900/1281] lr: 2.218e-02, eta: 16:06:06, time: 0.354, data_time: 0.000, memory: 4083, top1_acc: 0.8425, top5_acc: 0.9906, loss_cls: 0.7565, loss: 0.7565 +2025-06-24 15:34:35,774 - pyskl - INFO - Epoch [33][1000/1281] lr: 2.217e-02, eta: 16:06:04, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8319, top5_acc: 0.9925, loss_cls: 0.8009, loss: 0.8009 +2025-06-24 15:35:24,710 - pyskl - INFO - Epoch [33][1100/1281] lr: 2.216e-02, eta: 16:06:03, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8450, top5_acc: 0.9912, loss_cls: 0.7577, loss: 0.7577 +2025-06-24 15:36:14,330 - pyskl - INFO - Epoch [33][1200/1281] lr: 2.214e-02, eta: 16:06:03, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8381, top5_acc: 0.9931, loss_cls: 0.7706, loss: 0.7706 +2025-06-24 15:36:54,392 - pyskl - INFO - Saving checkpoint at 33 epochs +2025-06-24 15:37:53,566 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:37:53,621 - pyskl - INFO - +top1_acc 0.7938 +top5_acc 0.9835 +2025-06-24 15:37:53,621 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:37:53,627 - pyskl - INFO - +mean_acc 0.7276 +2025-06-24 15:37:53,629 - pyskl - INFO - Epoch(val) [33][533] top1_acc: 0.7938, top5_acc: 0.9835, mean_class_accuracy: 0.7276 +2025-06-24 15:39:13,838 - pyskl - INFO - Epoch [34][100/1281] lr: 2.212e-02, eta: 16:05:29, time: 0.802, data_time: 0.198, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9931, loss_cls: 0.6919, loss: 0.6919 +2025-06-24 15:40:02,625 - pyskl - INFO - Epoch [34][200/1281] lr: 2.211e-02, eta: 16:05:26, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9912, loss_cls: 0.6935, loss: 0.6935 +2025-06-24 15:40:51,539 - pyskl - INFO - Epoch [34][300/1281] lr: 2.209e-02, eta: 16:05:23, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 0.8681, top5_acc: 0.9956, loss_cls: 0.6912, loss: 0.6912 +2025-06-24 15:41:40,936 - pyskl - INFO - Epoch [34][400/1281] lr: 2.208e-02, eta: 16:05:22, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8600, top5_acc: 0.9956, loss_cls: 0.6740, loss: 0.6740 +2025-06-24 15:42:30,522 - pyskl - INFO - Epoch [34][500/1281] lr: 2.207e-02, eta: 16:05:21, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9944, loss_cls: 0.6449, loss: 0.6449 +2025-06-24 15:43:19,197 - pyskl - INFO - Epoch [34][600/1281] lr: 2.205e-02, eta: 16:05:17, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8481, top5_acc: 0.9931, loss_cls: 0.7296, loss: 0.7296 +2025-06-24 15:43:51,715 - pyskl - INFO - Epoch [34][700/1281] lr: 2.204e-02, eta: 16:04:16, time: 0.325, data_time: 0.000, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9931, loss_cls: 0.6890, loss: 0.6890 +2025-06-24 15:44:32,850 - pyskl - INFO - Epoch [34][800/1281] lr: 2.203e-02, eta: 16:03:46, time: 0.411, data_time: 0.000, memory: 4083, top1_acc: 0.8475, top5_acc: 0.9931, loss_cls: 0.7407, loss: 0.7407 +2025-06-24 15:45:07,717 - pyskl - INFO - Epoch [34][900/1281] lr: 2.201e-02, eta: 16:02:53, time: 0.349, data_time: 0.000, memory: 4083, top1_acc: 0.8650, top5_acc: 0.9919, loss_cls: 0.6834, loss: 0.6834 +2025-06-24 15:45:56,537 - pyskl - INFO - Epoch [34][1000/1281] lr: 2.200e-02, eta: 16:02:49, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8481, top5_acc: 0.9912, loss_cls: 0.7527, loss: 0.7527 +2025-06-24 15:46:45,714 - pyskl - INFO - Epoch [34][1100/1281] lr: 2.199e-02, eta: 16:02:46, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8562, top5_acc: 0.9950, loss_cls: 0.7046, loss: 0.7046 +2025-06-24 15:47:35,096 - pyskl - INFO - Epoch [34][1200/1281] lr: 2.197e-02, eta: 16:02:43, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8531, top5_acc: 0.9888, loss_cls: 0.7492, loss: 0.7492 +2025-06-24 15:48:15,863 - pyskl - INFO - Saving checkpoint at 34 epochs +2025-06-24 15:49:15,226 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:49:15,303 - pyskl - INFO - +top1_acc 0.8008 +top5_acc 0.9826 +2025-06-24 15:49:15,303 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:49:15,314 - pyskl - INFO - +mean_acc 0.7554 +2025-06-24 15:49:15,318 - pyskl - INFO - Epoch(val) [34][533] top1_acc: 0.8008, top5_acc: 0.9826, mean_class_accuracy: 0.7554 +2025-06-24 15:50:36,770 - pyskl - INFO - Epoch [35][100/1281] lr: 2.195e-02, eta: 16:02:11, time: 0.814, data_time: 0.196, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9925, loss_cls: 0.7201, loss: 0.7201 +2025-06-24 15:51:25,723 - pyskl - INFO - Epoch [35][200/1281] lr: 2.194e-02, eta: 16:02:06, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8600, top5_acc: 0.9962, loss_cls: 0.6738, loss: 0.6738 +2025-06-24 15:52:14,700 - pyskl - INFO - Epoch [35][300/1281] lr: 2.192e-02, eta: 16:02:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8512, top5_acc: 0.9931, loss_cls: 0.7161, loss: 0.7161 +2025-06-24 15:53:03,907 - pyskl - INFO - Epoch [35][400/1281] lr: 2.191e-02, eta: 16:01:57, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9975, loss_cls: 0.6027, loss: 0.6027 +2025-06-24 15:53:53,072 - pyskl - INFO - Epoch [35][500/1281] lr: 2.190e-02, eta: 16:01:52, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8650, top5_acc: 0.9919, loss_cls: 0.7236, loss: 0.7236 +2025-06-24 15:54:40,953 - pyskl - INFO - Epoch [35][600/1281] lr: 2.188e-02, eta: 16:01:43, time: 0.479, data_time: 0.000, memory: 4083, top1_acc: 0.8394, top5_acc: 0.9912, loss_cls: 0.7826, loss: 0.7826 +2025-06-24 15:55:14,416 - pyskl - INFO - Epoch [35][700/1281] lr: 2.187e-02, eta: 16:00:46, time: 0.335, data_time: 0.000, memory: 4083, top1_acc: 0.8469, top5_acc: 0.9944, loss_cls: 0.7274, loss: 0.7274 +2025-06-24 15:55:54,609 - pyskl - INFO - Epoch [35][800/1281] lr: 2.185e-02, eta: 16:00:11, time: 0.402, data_time: 0.000, memory: 4083, top1_acc: 0.8581, top5_acc: 0.9962, loss_cls: 0.6978, loss: 0.6978 +2025-06-24 15:56:31,890 - pyskl - INFO - Epoch [35][900/1281] lr: 2.184e-02, eta: 15:59:26, time: 0.373, data_time: 0.000, memory: 4083, top1_acc: 0.8538, top5_acc: 0.9900, loss_cls: 0.7393, loss: 0.7393 +2025-06-24 15:57:21,152 - pyskl - INFO - Epoch [35][1000/1281] lr: 2.183e-02, eta: 15:59:21, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8575, top5_acc: 0.9888, loss_cls: 0.7573, loss: 0.7573 +2025-06-24 15:58:10,508 - pyskl - INFO - Epoch [35][1100/1281] lr: 2.181e-02, eta: 15:59:16, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9906, loss_cls: 0.6766, loss: 0.6766 +2025-06-24 15:58:59,705 - pyskl - INFO - Epoch [35][1200/1281] lr: 2.180e-02, eta: 15:59:11, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8425, top5_acc: 0.9938, loss_cls: 0.7776, loss: 0.7776 +2025-06-24 15:59:40,202 - pyskl - INFO - Saving checkpoint at 35 epochs +2025-06-24 16:00:38,928 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:00:39,001 - pyskl - INFO - +top1_acc 0.8041 +top5_acc 0.9854 +2025-06-24 16:00:39,001 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:00:39,009 - pyskl - INFO - +mean_acc 0.7434 +2025-06-24 16:00:39,012 - pyskl - INFO - Epoch(val) [35][533] top1_acc: 0.8041, top5_acc: 0.9854, mean_class_accuracy: 0.7434 +2025-06-24 16:01:59,572 - pyskl - INFO - Epoch [36][100/1281] lr: 2.178e-02, eta: 15:58:33, time: 0.806, data_time: 0.194, memory: 4083, top1_acc: 0.8738, top5_acc: 0.9956, loss_cls: 0.6402, loss: 0.6402 +2025-06-24 16:02:48,524 - pyskl - INFO - Epoch [36][200/1281] lr: 2.176e-02, eta: 15:58:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8606, top5_acc: 0.9956, loss_cls: 0.6951, loss: 0.6951 +2025-06-24 16:03:37,421 - pyskl - INFO - Epoch [36][300/1281] lr: 2.175e-02, eta: 15:58:19, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8738, top5_acc: 0.9938, loss_cls: 0.6423, loss: 0.6423 +2025-06-24 16:04:26,386 - pyskl - INFO - Epoch [36][400/1281] lr: 2.173e-02, eta: 15:58:11, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9938, loss_cls: 0.6233, loss: 0.6233 +2025-06-24 16:05:15,418 - pyskl - INFO - Epoch [36][500/1281] lr: 2.172e-02, eta: 15:58:04, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8456, top5_acc: 0.9925, loss_cls: 0.7273, loss: 0.7273 +2025-06-24 16:06:01,369 - pyskl - INFO - Epoch [36][600/1281] lr: 2.171e-02, eta: 15:57:47, time: 0.460, data_time: 0.000, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9931, loss_cls: 0.6646, loss: 0.6646 +2025-06-24 16:06:37,884 - pyskl - INFO - Epoch [36][700/1281] lr: 2.169e-02, eta: 15:56:59, time: 0.365, data_time: 0.000, memory: 4083, top1_acc: 0.8475, top5_acc: 0.9944, loss_cls: 0.7309, loss: 0.7309 +2025-06-24 16:07:15,041 - pyskl - INFO - Epoch [36][800/1281] lr: 2.168e-02, eta: 15:56:14, time: 0.372, data_time: 0.000, memory: 4083, top1_acc: 0.8638, top5_acc: 0.9944, loss_cls: 0.7153, loss: 0.7153 +2025-06-24 16:07:52,167 - pyskl - INFO - Epoch [36][900/1281] lr: 2.167e-02, eta: 15:55:28, time: 0.371, data_time: 0.000, memory: 4083, top1_acc: 0.8494, top5_acc: 0.9919, loss_cls: 0.7320, loss: 0.7320 +2025-06-24 16:08:41,380 - pyskl - INFO - Epoch [36][1000/1281] lr: 2.165e-02, eta: 15:55:21, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8438, top5_acc: 0.9925, loss_cls: 0.7588, loss: 0.7588 +2025-06-24 16:09:30,468 - pyskl - INFO - Epoch [36][1100/1281] lr: 2.164e-02, eta: 15:55:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9919, loss_cls: 0.6953, loss: 0.6953 +2025-06-24 16:10:19,348 - pyskl - INFO - Epoch [36][1200/1281] lr: 2.162e-02, eta: 15:55:05, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8519, top5_acc: 0.9888, loss_cls: 0.7349, loss: 0.7349 +2025-06-24 16:10:59,580 - pyskl - INFO - Saving checkpoint at 36 epochs +2025-06-24 16:11:58,472 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:11:58,546 - pyskl - INFO - +top1_acc 0.8363 +top5_acc 0.9878 +2025-06-24 16:11:58,547 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:11:58,556 - pyskl - INFO - +mean_acc 0.7763 +2025-06-24 16:11:58,562 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_28.pth was removed +2025-06-24 16:11:58,742 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_36.pth. +2025-06-24 16:11:58,742 - pyskl - INFO - Best top1_acc is 0.8363 at 36 epoch. +2025-06-24 16:11:58,745 - pyskl - INFO - Epoch(val) [36][533] top1_acc: 0.8363, top5_acc: 0.9878, mean_class_accuracy: 0.7763 +2025-06-24 16:13:18,605 - pyskl - INFO - Epoch [37][100/1281] lr: 2.160e-02, eta: 15:54:22, time: 0.799, data_time: 0.198, memory: 4083, top1_acc: 0.8500, top5_acc: 0.9950, loss_cls: 0.7179, loss: 0.7179 +2025-06-24 16:14:07,742 - pyskl - INFO - Epoch [37][200/1281] lr: 2.158e-02, eta: 15:54:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9944, loss_cls: 0.6858, loss: 0.6858 +2025-06-24 16:14:57,140 - pyskl - INFO - Epoch [37][300/1281] lr: 2.157e-02, eta: 15:54:07, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9956, loss_cls: 0.6294, loss: 0.6294 +2025-06-24 16:15:46,325 - pyskl - INFO - Epoch [37][400/1281] lr: 2.156e-02, eta: 15:53:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9950, loss_cls: 0.6875, loss: 0.6875 +2025-06-24 16:16:35,382 - pyskl - INFO - Epoch [37][500/1281] lr: 2.154e-02, eta: 15:53:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9919, loss_cls: 0.6990, loss: 0.6990 +2025-06-24 16:17:22,446 - pyskl - INFO - Epoch [37][600/1281] lr: 2.153e-02, eta: 15:53:34, time: 0.471, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9938, loss_cls: 0.6566, loss: 0.6566 +2025-06-24 16:17:55,287 - pyskl - INFO - Epoch [37][700/1281] lr: 2.151e-02, eta: 15:52:35, time: 0.328, data_time: 0.000, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9950, loss_cls: 0.6933, loss: 0.6933 +2025-06-24 16:18:36,010 - pyskl - INFO - Epoch [37][800/1281] lr: 2.150e-02, eta: 15:52:00, time: 0.407, data_time: 0.001, memory: 4083, top1_acc: 0.8644, top5_acc: 0.9931, loss_cls: 0.6922, loss: 0.6922 +2025-06-24 16:19:11,282 - pyskl - INFO - Epoch [37][900/1281] lr: 2.149e-02, eta: 15:51:08, time: 0.353, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9919, loss_cls: 0.6331, loss: 0.6331 +2025-06-24 16:20:00,119 - pyskl - INFO - Epoch [37][1000/1281] lr: 2.147e-02, eta: 15:50:58, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8500, top5_acc: 0.9925, loss_cls: 0.7476, loss: 0.7476 +2025-06-24 16:20:49,311 - pyskl - INFO - Epoch [37][1100/1281] lr: 2.146e-02, eta: 15:50:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8394, top5_acc: 0.9906, loss_cls: 0.7608, loss: 0.7608 +2025-06-24 16:21:38,250 - pyskl - INFO - Epoch [37][1200/1281] lr: 2.144e-02, eta: 15:50:39, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9962, loss_cls: 0.6180, loss: 0.6180 +2025-06-24 16:22:18,446 - pyskl - INFO - Saving checkpoint at 37 epochs +2025-06-24 16:23:17,407 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:23:17,462 - pyskl - INFO - +top1_acc 0.7770 +top5_acc 0.9762 +2025-06-24 16:23:17,462 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:23:17,469 - pyskl - INFO - +mean_acc 0.7224 +2025-06-24 16:23:17,470 - pyskl - INFO - Epoch(val) [37][533] top1_acc: 0.7770, top5_acc: 0.9762, mean_class_accuracy: 0.7224 +2025-06-24 16:24:37,379 - pyskl - INFO - Epoch [38][100/1281] lr: 2.142e-02, eta: 15:49:54, time: 0.799, data_time: 0.194, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9956, loss_cls: 0.6496, loss: 0.6496 +2025-06-24 16:25:26,501 - pyskl - INFO - Epoch [38][200/1281] lr: 2.140e-02, eta: 15:49:44, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9969, loss_cls: 0.6283, loss: 0.6283 +2025-06-24 16:26:15,181 - pyskl - INFO - Epoch [38][300/1281] lr: 2.139e-02, eta: 15:49:32, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9925, loss_cls: 0.6024, loss: 0.6024 +2025-06-24 16:27:04,300 - pyskl - INFO - Epoch [38][400/1281] lr: 2.137e-02, eta: 15:49:22, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8688, top5_acc: 0.9950, loss_cls: 0.6753, loss: 0.6753 +2025-06-24 16:27:53,379 - pyskl - INFO - Epoch [38][500/1281] lr: 2.136e-02, eta: 15:49:12, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8644, top5_acc: 0.9950, loss_cls: 0.6629, loss: 0.6629 +2025-06-24 16:28:42,285 - pyskl - INFO - Epoch [38][600/1281] lr: 2.134e-02, eta: 15:49:00, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9881, loss_cls: 0.6777, loss: 0.6777 +2025-06-24 16:29:13,804 - pyskl - INFO - Epoch [38][700/1281] lr: 2.133e-02, eta: 15:47:57, time: 0.315, data_time: 0.000, memory: 4083, top1_acc: 0.8506, top5_acc: 0.9950, loss_cls: 0.7226, loss: 0.7226 +2025-06-24 16:29:56,179 - pyskl - INFO - Epoch [38][800/1281] lr: 2.132e-02, eta: 15:47:26, time: 0.424, data_time: 0.000, memory: 4083, top1_acc: 0.8550, top5_acc: 0.9944, loss_cls: 0.7202, loss: 0.7202 +2025-06-24 16:30:30,333 - pyskl - INFO - Epoch [38][900/1281] lr: 2.130e-02, eta: 15:46:31, time: 0.342, data_time: 0.000, memory: 4083, top1_acc: 0.8644, top5_acc: 0.9912, loss_cls: 0.7302, loss: 0.7302 +2025-06-24 16:31:19,619 - pyskl - INFO - Epoch [38][1000/1281] lr: 2.129e-02, eta: 15:46:20, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8738, top5_acc: 0.9962, loss_cls: 0.6070, loss: 0.6070 +2025-06-24 16:32:08,665 - pyskl - INFO - Epoch [38][1100/1281] lr: 2.127e-02, eta: 15:46:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8500, top5_acc: 0.9931, loss_cls: 0.7237, loss: 0.7237 +2025-06-24 16:32:57,442 - pyskl - INFO - Epoch [38][1200/1281] lr: 2.126e-02, eta: 15:45:57, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8675, top5_acc: 0.9900, loss_cls: 0.7126, loss: 0.7126 +2025-06-24 16:33:38,192 - pyskl - INFO - Saving checkpoint at 38 epochs +2025-06-24 16:34:37,934 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:34:37,995 - pyskl - INFO - +top1_acc 0.8412 +top5_acc 0.9840 +2025-06-24 16:34:37,995 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:34:38,003 - pyskl - INFO - +mean_acc 0.7850 +2025-06-24 16:34:38,008 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_36.pth was removed +2025-06-24 16:34:38,182 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_38.pth. +2025-06-24 16:34:38,183 - pyskl - INFO - Best top1_acc is 0.8412 at 38 epoch. +2025-06-24 16:34:38,186 - pyskl - INFO - Epoch(val) [38][533] top1_acc: 0.8412, top5_acc: 0.9840, mean_class_accuracy: 0.7850 +2025-06-24 16:35:57,515 - pyskl - INFO - Epoch [39][100/1281] lr: 2.123e-02, eta: 15:45:08, time: 0.793, data_time: 0.193, memory: 4083, top1_acc: 0.8681, top5_acc: 0.9938, loss_cls: 0.6444, loss: 0.6444 +2025-06-24 16:36:46,627 - pyskl - INFO - Epoch [39][200/1281] lr: 2.122e-02, eta: 15:44:57, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9956, loss_cls: 0.5751, loss: 0.5751 +2025-06-24 16:37:35,559 - pyskl - INFO - Epoch [39][300/1281] lr: 2.120e-02, eta: 15:44:45, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9925, loss_cls: 0.6649, loss: 0.6649 +2025-06-24 16:38:24,427 - pyskl - INFO - Epoch [39][400/1281] lr: 2.119e-02, eta: 15:44:32, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8638, top5_acc: 0.9919, loss_cls: 0.6886, loss: 0.6886 +2025-06-24 16:39:13,653 - pyskl - INFO - Epoch [39][500/1281] lr: 2.117e-02, eta: 15:44:20, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9919, loss_cls: 0.6972, loss: 0.6972 +2025-06-24 16:40:02,896 - pyskl - INFO - Epoch [39][600/1281] lr: 2.116e-02, eta: 15:44:09, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9969, loss_cls: 0.6083, loss: 0.6083 +2025-06-24 16:40:33,775 - pyskl - INFO - Epoch [39][700/1281] lr: 2.114e-02, eta: 15:43:04, time: 0.309, data_time: 0.001, memory: 4083, top1_acc: 0.8494, top5_acc: 0.9906, loss_cls: 0.7167, loss: 0.7167 +2025-06-24 16:41:17,749 - pyskl - INFO - Epoch [39][800/1281] lr: 2.113e-02, eta: 15:42:36, time: 0.440, data_time: 0.000, memory: 4083, top1_acc: 0.8600, top5_acc: 0.9944, loss_cls: 0.6829, loss: 0.6829 +2025-06-24 16:41:50,897 - pyskl - INFO - Epoch [39][900/1281] lr: 2.111e-02, eta: 15:41:38, time: 0.331, data_time: 0.000, memory: 4083, top1_acc: 0.8512, top5_acc: 0.9938, loss_cls: 0.7024, loss: 0.7024 +2025-06-24 16:42:39,885 - pyskl - INFO - Epoch [39][1000/1281] lr: 2.110e-02, eta: 15:41:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9919, loss_cls: 0.6636, loss: 0.6636 +2025-06-24 16:43:29,128 - pyskl - INFO - Epoch [39][1100/1281] lr: 2.108e-02, eta: 15:41:13, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9919, loss_cls: 0.6749, loss: 0.6749 +2025-06-24 16:44:18,265 - pyskl - INFO - Epoch [39][1200/1281] lr: 2.107e-02, eta: 15:41:00, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9950, loss_cls: 0.6628, loss: 0.6628 +2025-06-24 16:44:58,326 - pyskl - INFO - Saving checkpoint at 39 epochs +2025-06-24 16:45:58,124 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:45:58,210 - pyskl - INFO - +top1_acc 0.8152 +top5_acc 0.9833 +2025-06-24 16:45:58,211 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:45:58,219 - pyskl - INFO - +mean_acc 0.7758 +2025-06-24 16:45:58,221 - pyskl - INFO - Epoch(val) [39][533] top1_acc: 0.8152, top5_acc: 0.9833, mean_class_accuracy: 0.7758 +2025-06-24 16:47:19,738 - pyskl - INFO - Epoch [40][100/1281] lr: 2.104e-02, eta: 15:40:16, time: 0.815, data_time: 0.199, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9938, loss_cls: 0.5744, loss: 0.5744 +2025-06-24 16:48:08,364 - pyskl - INFO - Epoch [40][200/1281] lr: 2.103e-02, eta: 15:40:02, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9969, loss_cls: 0.5167, loss: 0.5167 +2025-06-24 16:48:57,377 - pyskl - INFO - Epoch [40][300/1281] lr: 2.101e-02, eta: 15:39:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8681, top5_acc: 0.9931, loss_cls: 0.6659, loss: 0.6659 +2025-06-24 16:49:46,381 - pyskl - INFO - Epoch [40][400/1281] lr: 2.100e-02, eta: 15:39:35, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8675, top5_acc: 0.9944, loss_cls: 0.6685, loss: 0.6685 +2025-06-24 16:50:35,688 - pyskl - INFO - Epoch [40][500/1281] lr: 2.098e-02, eta: 15:39:22, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9950, loss_cls: 0.6654, loss: 0.6654 +2025-06-24 16:51:24,912 - pyskl - INFO - Epoch [40][600/1281] lr: 2.097e-02, eta: 15:39:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9938, loss_cls: 0.6035, loss: 0.6035 +2025-06-24 16:51:56,220 - pyskl - INFO - Epoch [40][700/1281] lr: 2.095e-02, eta: 15:38:05, time: 0.313, data_time: 0.000, memory: 4083, top1_acc: 0.8581, top5_acc: 0.9919, loss_cls: 0.6730, loss: 0.6730 +2025-06-24 16:52:39,166 - pyskl - INFO - Epoch [40][800/1281] lr: 2.094e-02, eta: 15:37:34, time: 0.429, data_time: 0.000, memory: 4083, top1_acc: 0.8575, top5_acc: 0.9975, loss_cls: 0.7000, loss: 0.7000 +2025-06-24 16:53:13,940 - pyskl - INFO - Epoch [40][900/1281] lr: 2.092e-02, eta: 15:36:40, time: 0.348, data_time: 0.000, memory: 4083, top1_acc: 0.8569, top5_acc: 0.9950, loss_cls: 0.6644, loss: 0.6644 +2025-06-24 16:54:03,448 - pyskl - INFO - Epoch [40][1000/1281] lr: 2.091e-02, eta: 15:36:27, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9944, loss_cls: 0.6733, loss: 0.6733 +2025-06-24 16:54:52,805 - pyskl - INFO - Epoch [40][1100/1281] lr: 2.089e-02, eta: 15:36:14, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8625, top5_acc: 0.9938, loss_cls: 0.6821, loss: 0.6821 +2025-06-24 16:55:42,288 - pyskl - INFO - Epoch [40][1200/1281] lr: 2.088e-02, eta: 15:36:01, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8681, top5_acc: 0.9931, loss_cls: 0.6808, loss: 0.6808 +2025-06-24 16:56:22,572 - pyskl - INFO - Saving checkpoint at 40 epochs +2025-06-24 16:57:21,865 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:57:21,922 - pyskl - INFO - +top1_acc 0.8141 +top5_acc 0.9845 +2025-06-24 16:57:21,922 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:57:21,929 - pyskl - INFO - +mean_acc 0.7564 +2025-06-24 16:57:21,931 - pyskl - INFO - Epoch(val) [40][533] top1_acc: 0.8141, top5_acc: 0.9845, mean_class_accuracy: 0.7564 +2025-06-24 16:58:42,505 - pyskl - INFO - Epoch [41][100/1281] lr: 2.085e-02, eta: 15:35:12, time: 0.806, data_time: 0.196, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9950, loss_cls: 0.5741, loss: 0.5741 +2025-06-24 16:59:31,739 - pyskl - INFO - Epoch [41][200/1281] lr: 2.083e-02, eta: 15:34:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8638, top5_acc: 0.9938, loss_cls: 0.6774, loss: 0.6774 +2025-06-24 17:00:20,613 - pyskl - INFO - Epoch [41][300/1281] lr: 2.082e-02, eta: 15:34:42, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8569, top5_acc: 0.9906, loss_cls: 0.6977, loss: 0.6977 +2025-06-24 17:01:09,572 - pyskl - INFO - Epoch [41][400/1281] lr: 2.080e-02, eta: 15:34:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9950, loss_cls: 0.6654, loss: 0.6654 +2025-06-24 17:01:58,600 - pyskl - INFO - Epoch [41][500/1281] lr: 2.079e-02, eta: 15:34:12, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8688, top5_acc: 0.9931, loss_cls: 0.6664, loss: 0.6664 +2025-06-24 17:02:47,393 - pyskl - INFO - Epoch [41][600/1281] lr: 2.077e-02, eta: 15:33:56, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8625, top5_acc: 0.9919, loss_cls: 0.7172, loss: 0.7172 +2025-06-24 17:03:17,065 - pyskl - INFO - Epoch [41][700/1281] lr: 2.076e-02, eta: 15:32:48, time: 0.297, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9900, loss_cls: 0.6640, loss: 0.6640 +2025-06-24 17:04:01,953 - pyskl - INFO - Epoch [41][800/1281] lr: 2.074e-02, eta: 15:32:22, time: 0.449, data_time: 0.000, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9944, loss_cls: 0.6527, loss: 0.6527 +2025-06-24 17:04:34,560 - pyskl - INFO - Epoch [41][900/1281] lr: 2.073e-02, eta: 15:31:22, time: 0.326, data_time: 0.000, memory: 4083, top1_acc: 0.8612, top5_acc: 0.9962, loss_cls: 0.6574, loss: 0.6574 +2025-06-24 17:05:23,481 - pyskl - INFO - Epoch [41][1000/1281] lr: 2.071e-02, eta: 15:31:07, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8681, top5_acc: 0.9975, loss_cls: 0.6669, loss: 0.6669 +2025-06-24 17:06:12,683 - pyskl - INFO - Epoch [41][1100/1281] lr: 2.070e-02, eta: 15:30:51, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8581, top5_acc: 0.9938, loss_cls: 0.6760, loss: 0.6760 +2025-06-24 17:07:02,295 - pyskl - INFO - Epoch [41][1200/1281] lr: 2.068e-02, eta: 15:30:37, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9944, loss_cls: 0.6818, loss: 0.6818 +2025-06-24 17:07:42,433 - pyskl - INFO - Saving checkpoint at 41 epochs +2025-06-24 17:08:41,374 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:08:41,433 - pyskl - INFO - +top1_acc 0.8216 +top5_acc 0.9827 +2025-06-24 17:08:41,433 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:08:41,440 - pyskl - INFO - +mean_acc 0.7863 +2025-06-24 17:08:41,442 - pyskl - INFO - Epoch(val) [41][533] top1_acc: 0.8216, top5_acc: 0.9827, mean_class_accuracy: 0.7863 +2025-06-24 17:10:01,391 - pyskl - INFO - Epoch [42][100/1281] lr: 2.065e-02, eta: 15:29:45, time: 0.799, data_time: 0.194, memory: 4083, top1_acc: 0.8656, top5_acc: 0.9944, loss_cls: 0.7154, loss: 0.7154 +2025-06-24 17:10:50,269 - pyskl - INFO - Epoch [42][200/1281] lr: 2.064e-02, eta: 15:29:29, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8738, top5_acc: 0.9944, loss_cls: 0.6575, loss: 0.6575 +2025-06-24 17:11:39,256 - pyskl - INFO - Epoch [42][300/1281] lr: 2.062e-02, eta: 15:29:12, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9938, loss_cls: 0.6136, loss: 0.6136 +2025-06-24 17:12:28,355 - pyskl - INFO - Epoch [42][400/1281] lr: 2.061e-02, eta: 15:28:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8612, top5_acc: 0.9944, loss_cls: 0.6796, loss: 0.6796 +2025-06-24 17:13:17,525 - pyskl - INFO - Epoch [42][500/1281] lr: 2.059e-02, eta: 15:28:40, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9938, loss_cls: 0.6229, loss: 0.6229 +2025-06-24 17:14:06,298 - pyskl - INFO - Epoch [42][600/1281] lr: 2.057e-02, eta: 15:28:23, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9925, loss_cls: 0.6496, loss: 0.6496 +2025-06-24 17:14:32,890 - pyskl - INFO - Epoch [42][700/1281] lr: 2.056e-02, eta: 15:27:08, time: 0.266, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9956, loss_cls: 0.6243, loss: 0.6243 +2025-06-24 17:15:24,104 - pyskl - INFO - Epoch [42][800/1281] lr: 2.054e-02, eta: 15:26:57, time: 0.512, data_time: 0.001, memory: 4083, top1_acc: 0.8581, top5_acc: 0.9919, loss_cls: 0.7025, loss: 0.7025 +2025-06-24 17:15:54,506 - pyskl - INFO - Epoch [42][900/1281] lr: 2.053e-02, eta: 15:25:51, time: 0.304, data_time: 0.000, memory: 4083, top1_acc: 0.8669, top5_acc: 0.9912, loss_cls: 0.6873, loss: 0.6873 +2025-06-24 17:16:43,556 - pyskl - INFO - Epoch [42][1000/1281] lr: 2.051e-02, eta: 15:25:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9938, loss_cls: 0.6806, loss: 0.6806 +2025-06-24 17:17:32,639 - pyskl - INFO - Epoch [42][1100/1281] lr: 2.050e-02, eta: 15:25:18, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9944, loss_cls: 0.6258, loss: 0.6258 +2025-06-24 17:18:21,928 - pyskl - INFO - Epoch [42][1200/1281] lr: 2.048e-02, eta: 15:25:02, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9900, loss_cls: 0.6381, loss: 0.6381 +2025-06-24 17:19:02,639 - pyskl - INFO - Saving checkpoint at 42 epochs +2025-06-24 17:20:01,997 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:20:02,052 - pyskl - INFO - +top1_acc 0.8261 +top5_acc 0.9790 +2025-06-24 17:20:02,052 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:20:02,059 - pyskl - INFO - +mean_acc 0.7918 +2025-06-24 17:20:02,061 - pyskl - INFO - Epoch(val) [42][533] top1_acc: 0.8261, top5_acc: 0.9790, mean_class_accuracy: 0.7918 +2025-06-24 17:21:21,311 - pyskl - INFO - Epoch [43][100/1281] lr: 2.045e-02, eta: 15:24:06, time: 0.792, data_time: 0.190, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9919, loss_cls: 0.6296, loss: 0.6296 +2025-06-24 17:22:10,336 - pyskl - INFO - Epoch [43][200/1281] lr: 2.044e-02, eta: 15:23:49, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9962, loss_cls: 0.6278, loss: 0.6278 +2025-06-24 17:22:59,620 - pyskl - INFO - Epoch [43][300/1281] lr: 2.042e-02, eta: 15:23:32, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9956, loss_cls: 0.6523, loss: 0.6523 +2025-06-24 17:23:49,195 - pyskl - INFO - Epoch [43][400/1281] lr: 2.040e-02, eta: 15:23:16, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9981, loss_cls: 0.5887, loss: 0.5887 +2025-06-24 17:24:38,684 - pyskl - INFO - Epoch [43][500/1281] lr: 2.039e-02, eta: 15:23:00, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8600, top5_acc: 0.9931, loss_cls: 0.6607, loss: 0.6607 +2025-06-24 17:25:27,575 - pyskl - INFO - Epoch [43][600/1281] lr: 2.037e-02, eta: 15:22:41, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9969, loss_cls: 0.6365, loss: 0.6365 +2025-06-24 17:25:55,451 - pyskl - INFO - Epoch [43][700/1281] lr: 2.036e-02, eta: 15:21:30, time: 0.279, data_time: 0.000, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9912, loss_cls: 0.7120, loss: 0.7120 +2025-06-24 17:26:46,561 - pyskl - INFO - Epoch [43][800/1281] lr: 2.034e-02, eta: 15:21:18, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9944, loss_cls: 0.6315, loss: 0.6315 +2025-06-24 17:27:16,224 - pyskl - INFO - Epoch [43][900/1281] lr: 2.033e-02, eta: 15:20:11, time: 0.297, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9950, loss_cls: 0.5835, loss: 0.5835 +2025-06-24 17:28:04,984 - pyskl - INFO - Epoch [43][1000/1281] lr: 2.031e-02, eta: 15:19:52, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9956, loss_cls: 0.6133, loss: 0.6133 +2025-06-24 17:28:53,909 - pyskl - INFO - Epoch [43][1100/1281] lr: 2.029e-02, eta: 15:19:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9944, loss_cls: 0.6317, loss: 0.6317 +2025-06-24 17:29:42,714 - pyskl - INFO - Epoch [43][1200/1281] lr: 2.028e-02, eta: 15:19:15, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9950, loss_cls: 0.5414, loss: 0.5414 +2025-06-24 17:30:23,613 - pyskl - INFO - Saving checkpoint at 43 epochs +2025-06-24 17:31:22,449 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:31:22,504 - pyskl - INFO - +top1_acc 0.8155 +top5_acc 0.9812 +2025-06-24 17:31:22,504 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:31:22,511 - pyskl - INFO - +mean_acc 0.7441 +2025-06-24 17:31:22,513 - pyskl - INFO - Epoch(val) [43][533] top1_acc: 0.8155, top5_acc: 0.9812, mean_class_accuracy: 0.7441 +2025-06-24 17:32:42,767 - pyskl - INFO - Epoch [44][100/1281] lr: 2.025e-02, eta: 15:18:21, time: 0.802, data_time: 0.193, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9969, loss_cls: 0.5758, loss: 0.5758 +2025-06-24 17:33:31,843 - pyskl - INFO - Epoch [44][200/1281] lr: 2.023e-02, eta: 15:18:03, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8656, top5_acc: 0.9919, loss_cls: 0.6534, loss: 0.6534 +2025-06-24 17:34:20,984 - pyskl - INFO - Epoch [44][300/1281] lr: 2.022e-02, eta: 15:17:44, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8681, top5_acc: 0.9931, loss_cls: 0.6582, loss: 0.6582 +2025-06-24 17:35:09,895 - pyskl - INFO - Epoch [44][400/1281] lr: 2.020e-02, eta: 15:17:25, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8669, top5_acc: 0.9938, loss_cls: 0.6762, loss: 0.6762 +2025-06-24 17:35:59,171 - pyskl - INFO - Epoch [44][500/1281] lr: 2.018e-02, eta: 15:17:07, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9969, loss_cls: 0.5563, loss: 0.5563 +2025-06-24 17:36:48,293 - pyskl - INFO - Epoch [44][600/1281] lr: 2.017e-02, eta: 15:16:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9962, loss_cls: 0.6497, loss: 0.6497 +2025-06-24 17:37:16,211 - pyskl - INFO - Epoch [44][700/1281] lr: 2.015e-02, eta: 15:15:38, time: 0.279, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9925, loss_cls: 0.5918, loss: 0.5918 +2025-06-24 17:38:07,330 - pyskl - INFO - Epoch [44][800/1281] lr: 2.014e-02, eta: 15:15:24, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9938, loss_cls: 0.6642, loss: 0.6642 +2025-06-24 17:38:37,899 - pyskl - INFO - Epoch [44][900/1281] lr: 2.012e-02, eta: 15:14:20, time: 0.306, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9956, loss_cls: 0.6038, loss: 0.6038 +2025-06-24 17:39:26,763 - pyskl - INFO - Epoch [44][1000/1281] lr: 2.010e-02, eta: 15:14:01, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9919, loss_cls: 0.6146, loss: 0.6146 +2025-06-24 17:40:15,486 - pyskl - INFO - Epoch [44][1100/1281] lr: 2.009e-02, eta: 15:13:41, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8562, top5_acc: 0.9919, loss_cls: 0.6475, loss: 0.6475 +2025-06-24 17:41:04,748 - pyskl - INFO - Epoch [44][1200/1281] lr: 2.007e-02, eta: 15:13:22, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9975, loss_cls: 0.6515, loss: 0.6515 +2025-06-24 17:41:45,437 - pyskl - INFO - Saving checkpoint at 44 epochs +2025-06-24 17:42:44,749 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:42:44,820 - pyskl - INFO - +top1_acc 0.8459 +top5_acc 0.9906 +2025-06-24 17:42:44,821 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:42:44,829 - pyskl - INFO - +mean_acc 0.8050 +2025-06-24 17:42:44,834 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_38.pth was removed +2025-06-24 17:42:45,060 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_44.pth. +2025-06-24 17:42:45,060 - pyskl - INFO - Best top1_acc is 0.8459 at 44 epoch. +2025-06-24 17:42:45,063 - pyskl - INFO - Epoch(val) [44][533] top1_acc: 0.8459, top5_acc: 0.9906, mean_class_accuracy: 0.8050 +2025-06-24 17:44:05,348 - pyskl - INFO - Epoch [45][100/1281] lr: 2.004e-02, eta: 15:12:26, time: 0.803, data_time: 0.196, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9956, loss_cls: 0.5963, loss: 0.5963 +2025-06-24 17:44:54,561 - pyskl - INFO - Epoch [45][200/1281] lr: 2.003e-02, eta: 15:12:07, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9956, loss_cls: 0.5867, loss: 0.5867 +2025-06-24 17:45:43,645 - pyskl - INFO - Epoch [45][300/1281] lr: 2.001e-02, eta: 15:11:48, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9925, loss_cls: 0.6508, loss: 0.6508 +2025-06-24 17:46:32,570 - pyskl - INFO - Epoch [45][400/1281] lr: 1.999e-02, eta: 15:11:28, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9925, loss_cls: 0.6015, loss: 0.6015 +2025-06-24 17:47:21,773 - pyskl - INFO - Epoch [45][500/1281] lr: 1.998e-02, eta: 15:11:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9981, loss_cls: 0.5960, loss: 0.5960 +2025-06-24 17:48:11,009 - pyskl - INFO - Epoch [45][600/1281] lr: 1.996e-02, eta: 15:10:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8644, top5_acc: 0.9931, loss_cls: 0.6839, loss: 0.6839 +2025-06-24 17:48:39,647 - pyskl - INFO - Epoch [45][700/1281] lr: 1.994e-02, eta: 15:09:40, time: 0.286, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9938, loss_cls: 0.6263, loss: 0.6263 +2025-06-24 17:49:28,774 - pyskl - INFO - Epoch [45][800/1281] lr: 1.993e-02, eta: 15:09:21, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9950, loss_cls: 0.6613, loss: 0.6613 +2025-06-24 17:49:59,519 - pyskl - INFO - Epoch [45][900/1281] lr: 1.991e-02, eta: 15:08:17, time: 0.307, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9938, loss_cls: 0.6269, loss: 0.6269 +2025-06-24 17:50:48,567 - pyskl - INFO - Epoch [45][1000/1281] lr: 1.989e-02, eta: 15:07:57, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9925, loss_cls: 0.6397, loss: 0.6397 +2025-06-24 17:51:37,964 - pyskl - INFO - Epoch [45][1100/1281] lr: 1.988e-02, eta: 15:07:38, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9912, loss_cls: 0.6457, loss: 0.6457 +2025-06-24 17:52:27,034 - pyskl - INFO - Epoch [45][1200/1281] lr: 1.986e-02, eta: 15:07:18, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9931, loss_cls: 0.6574, loss: 0.6574 +2025-06-24 17:53:07,108 - pyskl - INFO - Saving checkpoint at 45 epochs +2025-06-24 17:54:06,562 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:54:06,620 - pyskl - INFO - +top1_acc 0.8524 +top5_acc 0.9897 +2025-06-24 17:54:06,620 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:54:06,627 - pyskl - INFO - +mean_acc 0.8083 +2025-06-24 17:54:06,631 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_44.pth was removed +2025-06-24 17:54:06,798 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_45.pth. +2025-06-24 17:54:06,798 - pyskl - INFO - Best top1_acc is 0.8524 at 45 epoch. +2025-06-24 17:54:06,801 - pyskl - INFO - Epoch(val) [45][533] top1_acc: 0.8524, top5_acc: 0.9897, mean_class_accuracy: 0.8083 +2025-06-24 17:55:25,728 - pyskl - INFO - Epoch [46][100/1281] lr: 1.983e-02, eta: 15:06:18, time: 0.789, data_time: 0.194, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9975, loss_cls: 0.5396, loss: 0.5396 +2025-06-24 17:56:14,809 - pyskl - INFO - Epoch [46][200/1281] lr: 1.981e-02, eta: 15:05:57, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9950, loss_cls: 0.5765, loss: 0.5765 +2025-06-24 17:57:03,956 - pyskl - INFO - Epoch [46][300/1281] lr: 1.980e-02, eta: 15:05:37, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9962, loss_cls: 0.6001, loss: 0.6001 +2025-06-24 17:57:53,001 - pyskl - INFO - Epoch [46][400/1281] lr: 1.978e-02, eta: 15:05:16, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9919, loss_cls: 0.6455, loss: 0.6455 +2025-06-24 17:58:42,338 - pyskl - INFO - Epoch [46][500/1281] lr: 1.976e-02, eta: 15:04:56, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8675, top5_acc: 0.9906, loss_cls: 0.6323, loss: 0.6323 +2025-06-24 17:59:31,818 - pyskl - INFO - Epoch [46][600/1281] lr: 1.975e-02, eta: 15:04:36, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9950, loss_cls: 0.5902, loss: 0.5902 +2025-06-24 17:59:59,376 - pyskl - INFO - Epoch [46][700/1281] lr: 1.973e-02, eta: 15:03:26, time: 0.276, data_time: 0.000, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9962, loss_cls: 0.6340, loss: 0.6340 +2025-06-24 18:00:50,518 - pyskl - INFO - Epoch [46][800/1281] lr: 1.971e-02, eta: 15:03:10, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9950, loss_cls: 0.5886, loss: 0.5886 +2025-06-24 18:01:22,253 - pyskl - INFO - Epoch [46][900/1281] lr: 1.970e-02, eta: 15:02:09, time: 0.317, data_time: 0.000, memory: 4083, top1_acc: 0.8688, top5_acc: 0.9944, loss_cls: 0.6315, loss: 0.6315 +2025-06-24 18:02:11,315 - pyskl - INFO - Epoch [46][1000/1281] lr: 1.968e-02, eta: 15:01:48, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9931, loss_cls: 0.6074, loss: 0.6074 +2025-06-24 18:03:00,308 - pyskl - INFO - Epoch [46][1100/1281] lr: 1.966e-02, eta: 15:01:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8612, top5_acc: 0.9931, loss_cls: 0.6573, loss: 0.6573 +2025-06-24 18:03:49,498 - pyskl - INFO - Epoch [46][1200/1281] lr: 1.965e-02, eta: 15:01:06, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9925, loss_cls: 0.6296, loss: 0.6296 +2025-06-24 18:04:29,839 - pyskl - INFO - Saving checkpoint at 46 epochs +2025-06-24 18:05:29,400 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:05:29,476 - pyskl - INFO - +top1_acc 0.8264 +top5_acc 0.9862 +2025-06-24 18:05:29,476 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:05:29,486 - pyskl - INFO - +mean_acc 0.7719 +2025-06-24 18:05:29,489 - pyskl - INFO - Epoch(val) [46][533] top1_acc: 0.8264, top5_acc: 0.9862, mean_class_accuracy: 0.7719 +2025-06-24 18:06:48,942 - pyskl - INFO - Epoch [47][100/1281] lr: 1.962e-02, eta: 15:00:06, time: 0.794, data_time: 0.193, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9944, loss_cls: 0.5362, loss: 0.5362 +2025-06-24 18:07:37,820 - pyskl - INFO - Epoch [47][200/1281] lr: 1.960e-02, eta: 14:59:44, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9969, loss_cls: 0.5138, loss: 0.5138 +2025-06-24 18:08:26,583 - pyskl - INFO - Epoch [47][300/1281] lr: 1.958e-02, eta: 14:59:22, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9912, loss_cls: 0.6470, loss: 0.6470 +2025-06-24 18:09:15,512 - pyskl - INFO - Epoch [47][400/1281] lr: 1.957e-02, eta: 14:59:00, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9969, loss_cls: 0.5992, loss: 0.5992 +2025-06-24 18:10:04,810 - pyskl - INFO - Epoch [47][500/1281] lr: 1.955e-02, eta: 14:58:39, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9950, loss_cls: 0.6121, loss: 0.6121 +2025-06-24 18:10:54,092 - pyskl - INFO - Epoch [47][600/1281] lr: 1.953e-02, eta: 14:58:17, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9944, loss_cls: 0.5656, loss: 0.5656 +2025-06-24 18:11:23,187 - pyskl - INFO - Epoch [47][700/1281] lr: 1.952e-02, eta: 14:57:11, time: 0.291, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9975, loss_cls: 0.5333, loss: 0.5333 +2025-06-24 18:12:11,343 - pyskl - INFO - Epoch [47][800/1281] lr: 1.950e-02, eta: 14:56:47, time: 0.482, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9944, loss_cls: 0.6136, loss: 0.6136 +2025-06-24 18:12:42,201 - pyskl - INFO - Epoch [47][900/1281] lr: 1.948e-02, eta: 14:55:45, time: 0.309, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9950, loss_cls: 0.6619, loss: 0.6619 +2025-06-24 18:13:31,321 - pyskl - INFO - Epoch [47][1000/1281] lr: 1.947e-02, eta: 14:55:23, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9950, loss_cls: 0.6361, loss: 0.6361 +2025-06-24 18:14:20,163 - pyskl - INFO - Epoch [47][1100/1281] lr: 1.945e-02, eta: 14:55:01, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9975, loss_cls: 0.6270, loss: 0.6270 +2025-06-24 18:15:09,250 - pyskl - INFO - Epoch [47][1200/1281] lr: 1.943e-02, eta: 14:54:38, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9956, loss_cls: 0.5621, loss: 0.5621 +2025-06-24 18:15:49,588 - pyskl - INFO - Saving checkpoint at 47 epochs +2025-06-24 18:16:48,791 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:16:48,854 - pyskl - INFO - +top1_acc 0.8490 +top5_acc 0.9883 +2025-06-24 18:16:48,854 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:16:48,862 - pyskl - INFO - +mean_acc 0.7949 +2025-06-24 18:16:48,864 - pyskl - INFO - Epoch(val) [47][533] top1_acc: 0.8490, top5_acc: 0.9883, mean_class_accuracy: 0.7949 +2025-06-24 18:18:07,977 - pyskl - INFO - Epoch [48][100/1281] lr: 1.940e-02, eta: 14:53:37, time: 0.791, data_time: 0.195, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9988, loss_cls: 0.5184, loss: 0.5184 +2025-06-24 18:18:57,113 - pyskl - INFO - Epoch [48][200/1281] lr: 1.938e-02, eta: 14:53:15, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9962, loss_cls: 0.5426, loss: 0.5426 +2025-06-24 18:19:46,408 - pyskl - INFO - Epoch [48][300/1281] lr: 1.937e-02, eta: 14:52:53, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9950, loss_cls: 0.5817, loss: 0.5817 +2025-06-24 18:20:35,358 - pyskl - INFO - Epoch [48][400/1281] lr: 1.935e-02, eta: 14:52:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9956, loss_cls: 0.5589, loss: 0.5589 +2025-06-24 18:21:24,490 - pyskl - INFO - Epoch [48][500/1281] lr: 1.933e-02, eta: 14:52:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9944, loss_cls: 0.5952, loss: 0.5952 +2025-06-24 18:22:13,687 - pyskl - INFO - Epoch [48][600/1281] lr: 1.932e-02, eta: 14:51:45, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9931, loss_cls: 0.6615, loss: 0.6615 +2025-06-24 18:22:41,799 - pyskl - INFO - Epoch [48][700/1281] lr: 1.930e-02, eta: 14:50:37, time: 0.281, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9975, loss_cls: 0.5700, loss: 0.5700 +2025-06-24 18:23:32,981 - pyskl - INFO - Epoch [48][800/1281] lr: 1.928e-02, eta: 14:50:19, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9956, loss_cls: 0.5699, loss: 0.5699 +2025-06-24 18:24:01,529 - pyskl - INFO - Epoch [48][900/1281] lr: 1.926e-02, eta: 14:49:12, time: 0.285, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9969, loss_cls: 0.5941, loss: 0.5941 +2025-06-24 18:24:50,701 - pyskl - INFO - Epoch [48][1000/1281] lr: 1.925e-02, eta: 14:48:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9969, loss_cls: 0.5775, loss: 0.5775 +2025-06-24 18:25:40,036 - pyskl - INFO - Epoch [48][1100/1281] lr: 1.923e-02, eta: 14:48:27, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9938, loss_cls: 0.6410, loss: 0.6410 +2025-06-24 18:26:29,384 - pyskl - INFO - Epoch [48][1200/1281] lr: 1.921e-02, eta: 14:48:05, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9919, loss_cls: 0.6374, loss: 0.6374 +2025-06-24 18:27:09,648 - pyskl - INFO - Saving checkpoint at 48 epochs +2025-06-24 18:28:08,726 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:28:08,784 - pyskl - INFO - +top1_acc 0.8339 +top5_acc 0.9842 +2025-06-24 18:28:08,784 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:28:08,791 - pyskl - INFO - +mean_acc 0.7760 +2025-06-24 18:28:08,793 - pyskl - INFO - Epoch(val) [48][533] top1_acc: 0.8339, top5_acc: 0.9842, mean_class_accuracy: 0.7760 +2025-06-24 18:29:28,251 - pyskl - INFO - Epoch [49][100/1281] lr: 1.918e-02, eta: 14:47:03, time: 0.795, data_time: 0.192, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9931, loss_cls: 0.5494, loss: 0.5494 +2025-06-24 18:30:17,234 - pyskl - INFO - Epoch [49][200/1281] lr: 1.916e-02, eta: 14:46:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9950, loss_cls: 0.5263, loss: 0.5263 +2025-06-24 18:31:06,133 - pyskl - INFO - Epoch [49][300/1281] lr: 1.915e-02, eta: 14:46:16, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9944, loss_cls: 0.5677, loss: 0.5677 +2025-06-24 18:31:55,235 - pyskl - INFO - Epoch [49][400/1281] lr: 1.913e-02, eta: 14:45:53, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9975, loss_cls: 0.5528, loss: 0.5528 +2025-06-24 18:32:44,367 - pyskl - INFO - Epoch [49][500/1281] lr: 1.911e-02, eta: 14:45:29, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9938, loss_cls: 0.5764, loss: 0.5764 +2025-06-24 18:33:33,604 - pyskl - INFO - Epoch [49][600/1281] lr: 1.909e-02, eta: 14:45:06, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9981, loss_cls: 0.5538, loss: 0.5538 +2025-06-24 18:34:03,797 - pyskl - INFO - Epoch [49][700/1281] lr: 1.908e-02, eta: 14:44:03, time: 0.302, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9962, loss_cls: 0.5957, loss: 0.5957 +2025-06-24 18:34:54,861 - pyskl - INFO - Epoch [49][800/1281] lr: 1.906e-02, eta: 14:43:44, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9931, loss_cls: 0.6203, loss: 0.6203 +2025-06-24 18:35:22,889 - pyskl - INFO - Epoch [49][900/1281] lr: 1.904e-02, eta: 14:42:36, time: 0.280, data_time: 0.000, memory: 4083, top1_acc: 0.8612, top5_acc: 0.9912, loss_cls: 0.6943, loss: 0.6943 +2025-06-24 18:36:12,154 - pyskl - INFO - Epoch [49][1000/1281] lr: 1.902e-02, eta: 14:42:13, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9962, loss_cls: 0.5891, loss: 0.5891 +2025-06-24 18:37:01,201 - pyskl - INFO - Epoch [49][1100/1281] lr: 1.901e-02, eta: 14:41:49, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9962, loss_cls: 0.5926, loss: 0.5926 +2025-06-24 18:37:50,367 - pyskl - INFO - Epoch [49][1200/1281] lr: 1.899e-02, eta: 14:41:25, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9919, loss_cls: 0.5884, loss: 0.5884 +2025-06-24 18:38:30,708 - pyskl - INFO - Saving checkpoint at 49 epochs +2025-06-24 18:39:29,720 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:39:29,789 - pyskl - INFO - +top1_acc 0.8290 +top5_acc 0.9835 +2025-06-24 18:39:29,789 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:39:29,797 - pyskl - INFO - +mean_acc 0.7731 +2025-06-24 18:39:29,799 - pyskl - INFO - Epoch(val) [49][533] top1_acc: 0.8290, top5_acc: 0.9835, mean_class_accuracy: 0.7731 +2025-06-24 18:40:49,745 - pyskl - INFO - Epoch [50][100/1281] lr: 1.896e-02, eta: 14:40:24, time: 0.799, data_time: 0.195, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9944, loss_cls: 0.5927, loss: 0.5927 +2025-06-24 18:41:38,738 - pyskl - INFO - Epoch [50][200/1281] lr: 1.894e-02, eta: 14:40:00, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9975, loss_cls: 0.5435, loss: 0.5435 +2025-06-24 18:42:27,765 - pyskl - INFO - Epoch [50][300/1281] lr: 1.892e-02, eta: 14:39:35, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9938, loss_cls: 0.5756, loss: 0.5756 +2025-06-24 18:43:16,722 - pyskl - INFO - Epoch [50][400/1281] lr: 1.891e-02, eta: 14:39:11, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9988, loss_cls: 0.5338, loss: 0.5338 +2025-06-24 18:44:05,997 - pyskl - INFO - Epoch [50][500/1281] lr: 1.889e-02, eta: 14:38:47, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9938, loss_cls: 0.5218, loss: 0.5218 +2025-06-24 18:44:54,989 - pyskl - INFO - Epoch [50][600/1281] lr: 1.887e-02, eta: 14:38:23, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9975, loss_cls: 0.5398, loss: 0.5398 +2025-06-24 18:45:23,898 - pyskl - INFO - Epoch [50][700/1281] lr: 1.885e-02, eta: 14:37:17, time: 0.289, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9956, loss_cls: 0.5628, loss: 0.5628 +2025-06-24 18:46:14,746 - pyskl - INFO - Epoch [50][800/1281] lr: 1.884e-02, eta: 14:36:57, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9950, loss_cls: 0.5835, loss: 0.5835 +2025-06-24 18:46:42,807 - pyskl - INFO - Epoch [50][900/1281] lr: 1.882e-02, eta: 14:35:50, time: 0.281, data_time: 0.001, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9950, loss_cls: 0.6000, loss: 0.6000 +2025-06-24 18:47:32,012 - pyskl - INFO - Epoch [50][1000/1281] lr: 1.880e-02, eta: 14:35:26, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8650, top5_acc: 0.9938, loss_cls: 0.6666, loss: 0.6666 +2025-06-24 18:48:21,069 - pyskl - INFO - Epoch [50][1100/1281] lr: 1.878e-02, eta: 14:35:01, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9950, loss_cls: 0.6236, loss: 0.6236 +2025-06-24 18:49:10,023 - pyskl - INFO - Epoch [50][1200/1281] lr: 1.876e-02, eta: 14:34:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9944, loss_cls: 0.6193, loss: 0.6193 +2025-06-24 18:49:50,563 - pyskl - INFO - Saving checkpoint at 50 epochs +2025-06-24 18:50:50,554 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:50:50,610 - pyskl - INFO - +top1_acc 0.8345 +top5_acc 0.9843 +2025-06-24 18:50:50,610 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:50:50,617 - pyskl - INFO - +mean_acc 0.7970 +2025-06-24 18:50:50,619 - pyskl - INFO - Epoch(val) [50][533] top1_acc: 0.8345, top5_acc: 0.9843, mean_class_accuracy: 0.7970 +2025-06-24 18:52:09,867 - pyskl - INFO - Epoch [51][100/1281] lr: 1.873e-02, eta: 14:33:32, time: 0.792, data_time: 0.193, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9950, loss_cls: 0.5828, loss: 0.5828 +2025-06-24 18:52:58,576 - pyskl - INFO - Epoch [51][200/1281] lr: 1.871e-02, eta: 14:33:07, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9975, loss_cls: 0.5933, loss: 0.5933 +2025-06-24 18:53:47,108 - pyskl - INFO - Epoch [51][300/1281] lr: 1.870e-02, eta: 14:32:41, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9981, loss_cls: 0.5452, loss: 0.5452 +2025-06-24 18:54:36,340 - pyskl - INFO - Epoch [51][400/1281] lr: 1.868e-02, eta: 14:32:16, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9944, loss_cls: 0.5395, loss: 0.5395 +2025-06-24 18:55:25,458 - pyskl - INFO - Epoch [51][500/1281] lr: 1.866e-02, eta: 14:31:51, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9975, loss_cls: 0.5787, loss: 0.5787 +2025-06-24 18:56:14,633 - pyskl - INFO - Epoch [51][600/1281] lr: 1.864e-02, eta: 14:31:27, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9975, loss_cls: 0.6139, loss: 0.6139 +2025-06-24 18:56:44,057 - pyskl - INFO - Epoch [51][700/1281] lr: 1.863e-02, eta: 14:30:23, time: 0.294, data_time: 0.001, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9938, loss_cls: 0.5914, loss: 0.5914 +2025-06-24 18:57:35,034 - pyskl - INFO - Epoch [51][800/1281] lr: 1.861e-02, eta: 14:30:01, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9944, loss_cls: 0.5483, loss: 0.5483 +2025-06-24 18:58:03,039 - pyskl - INFO - Epoch [51][900/1281] lr: 1.859e-02, eta: 14:28:55, time: 0.280, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9969, loss_cls: 0.5191, loss: 0.5191 +2025-06-24 18:58:52,305 - pyskl - INFO - Epoch [51][1000/1281] lr: 1.857e-02, eta: 14:28:30, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9962, loss_cls: 0.5483, loss: 0.5483 +2025-06-24 18:59:41,544 - pyskl - INFO - Epoch [51][1100/1281] lr: 1.855e-02, eta: 14:28:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9912, loss_cls: 0.6123, loss: 0.6123 +2025-06-24 19:00:30,997 - pyskl - INFO - Epoch [51][1200/1281] lr: 1.854e-02, eta: 14:27:40, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9975, loss_cls: 0.5479, loss: 0.5479 +2025-06-24 19:01:11,154 - pyskl - INFO - Saving checkpoint at 51 epochs +2025-06-24 19:02:10,396 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:02:10,463 - pyskl - INFO - +top1_acc 0.8325 +top5_acc 0.9891 +2025-06-24 19:02:10,463 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:02:10,471 - pyskl - INFO - +mean_acc 0.8085 +2025-06-24 19:02:10,473 - pyskl - INFO - Epoch(val) [51][533] top1_acc: 0.8325, top5_acc: 0.9891, mean_class_accuracy: 0.8085 +2025-06-24 19:03:30,769 - pyskl - INFO - Epoch [52][100/1281] lr: 1.850e-02, eta: 14:26:38, time: 0.803, data_time: 0.190, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9969, loss_cls: 0.5657, loss: 0.5657 +2025-06-24 19:04:19,785 - pyskl - INFO - Epoch [52][200/1281] lr: 1.849e-02, eta: 14:26:12, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9981, loss_cls: 0.5430, loss: 0.5430 +2025-06-24 19:05:08,797 - pyskl - INFO - Epoch [52][300/1281] lr: 1.847e-02, eta: 14:25:47, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9956, loss_cls: 0.5124, loss: 0.5124 +2025-06-24 19:05:57,871 - pyskl - INFO - Epoch [52][400/1281] lr: 1.845e-02, eta: 14:25:21, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9956, loss_cls: 0.5916, loss: 0.5916 +2025-06-24 19:06:47,384 - pyskl - INFO - Epoch [52][500/1281] lr: 1.843e-02, eta: 14:24:56, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9969, loss_cls: 0.5396, loss: 0.5396 +2025-06-24 19:07:36,679 - pyskl - INFO - Epoch [52][600/1281] lr: 1.841e-02, eta: 14:24:31, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9919, loss_cls: 0.6305, loss: 0.6305 +2025-06-24 19:08:05,660 - pyskl - INFO - Epoch [52][700/1281] lr: 1.840e-02, eta: 14:23:26, time: 0.290, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9931, loss_cls: 0.5997, loss: 0.5997 +2025-06-24 19:08:56,640 - pyskl - INFO - Epoch [52][800/1281] lr: 1.838e-02, eta: 14:23:04, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9969, loss_cls: 0.5167, loss: 0.5167 +2025-06-24 19:09:23,591 - pyskl - INFO - Epoch [52][900/1281] lr: 1.836e-02, eta: 14:21:56, time: 0.269, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9931, loss_cls: 0.6149, loss: 0.6149 +2025-06-24 19:10:12,716 - pyskl - INFO - Epoch [52][1000/1281] lr: 1.834e-02, eta: 14:21:30, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8738, top5_acc: 0.9931, loss_cls: 0.6271, loss: 0.6271 +2025-06-24 19:11:01,994 - pyskl - INFO - Epoch [52][1100/1281] lr: 1.832e-02, eta: 14:21:05, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9938, loss_cls: 0.5916, loss: 0.5916 +2025-06-24 19:11:51,515 - pyskl - INFO - Epoch [52][1200/1281] lr: 1.831e-02, eta: 14:20:40, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8675, top5_acc: 0.9894, loss_cls: 0.6727, loss: 0.6727 +2025-06-24 19:12:31,798 - pyskl - INFO - Saving checkpoint at 52 epochs +2025-06-24 19:13:30,089 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:13:30,147 - pyskl - INFO - +top1_acc 0.8388 +top5_acc 0.9872 +2025-06-24 19:13:30,147 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:13:30,154 - pyskl - INFO - +mean_acc 0.7815 +2025-06-24 19:13:30,155 - pyskl - INFO - Epoch(val) [52][533] top1_acc: 0.8388, top5_acc: 0.9872, mean_class_accuracy: 0.7815 +2025-06-24 19:14:49,641 - pyskl - INFO - Epoch [53][100/1281] lr: 1.827e-02, eta: 14:19:35, time: 0.795, data_time: 0.189, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9950, loss_cls: 0.5528, loss: 0.5528 +2025-06-24 19:15:39,044 - pyskl - INFO - Epoch [53][200/1281] lr: 1.826e-02, eta: 14:19:09, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9956, loss_cls: 0.5356, loss: 0.5356 +2025-06-24 19:16:28,120 - pyskl - INFO - Epoch [53][300/1281] lr: 1.824e-02, eta: 14:18:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9962, loss_cls: 0.5013, loss: 0.5013 +2025-06-24 19:17:17,173 - pyskl - INFO - Epoch [53][400/1281] lr: 1.822e-02, eta: 14:18:17, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9981, loss_cls: 0.5397, loss: 0.5397 +2025-06-24 19:18:06,300 - pyskl - INFO - Epoch [53][500/1281] lr: 1.820e-02, eta: 14:17:50, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9962, loss_cls: 0.5480, loss: 0.5480 +2025-06-24 19:18:55,508 - pyskl - INFO - Epoch [53][600/1281] lr: 1.818e-02, eta: 14:17:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9962, loss_cls: 0.5484, loss: 0.5484 +2025-06-24 19:19:27,653 - pyskl - INFO - Epoch [53][700/1281] lr: 1.816e-02, eta: 14:16:26, time: 0.321, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9975, loss_cls: 0.5755, loss: 0.5755 +2025-06-24 19:20:18,631 - pyskl - INFO - Epoch [53][800/1281] lr: 1.815e-02, eta: 14:16:03, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9969, loss_cls: 0.6134, loss: 0.6134 +2025-06-24 19:20:43,891 - pyskl - INFO - Epoch [53][900/1281] lr: 1.813e-02, eta: 14:14:53, time: 0.253, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9944, loss_cls: 0.6180, loss: 0.6180 +2025-06-24 19:21:31,619 - pyskl - INFO - Epoch [53][1000/1281] lr: 1.811e-02, eta: 14:14:24, time: 0.477, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9944, loss_cls: 0.6031, loss: 0.6031 +2025-06-24 19:22:20,702 - pyskl - INFO - Epoch [53][1100/1281] lr: 1.809e-02, eta: 14:13:57, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9988, loss_cls: 0.5435, loss: 0.5435 +2025-06-24 19:23:10,110 - pyskl - INFO - Epoch [53][1200/1281] lr: 1.807e-02, eta: 14:13:31, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9944, loss_cls: 0.5918, loss: 0.5918 +2025-06-24 19:23:50,922 - pyskl - INFO - Saving checkpoint at 53 epochs +2025-06-24 19:24:50,233 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:24:50,289 - pyskl - INFO - +top1_acc 0.8271 +top5_acc 0.9857 +2025-06-24 19:24:50,289 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:24:50,297 - pyskl - INFO - +mean_acc 0.7827 +2025-06-24 19:24:50,299 - pyskl - INFO - Epoch(val) [53][533] top1_acc: 0.8271, top5_acc: 0.9857, mean_class_accuracy: 0.7827 +2025-06-24 19:26:11,211 - pyskl - INFO - Epoch [54][100/1281] lr: 1.804e-02, eta: 14:12:28, time: 0.809, data_time: 0.197, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9944, loss_cls: 0.5949, loss: 0.5949 +2025-06-24 19:27:00,350 - pyskl - INFO - Epoch [54][200/1281] lr: 1.802e-02, eta: 14:12:01, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9975, loss_cls: 0.4757, loss: 0.4757 +2025-06-24 19:27:49,509 - pyskl - INFO - Epoch [54][300/1281] lr: 1.800e-02, eta: 14:11:35, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9969, loss_cls: 0.5047, loss: 0.5047 +2025-06-24 19:28:38,680 - pyskl - INFO - Epoch [54][400/1281] lr: 1.798e-02, eta: 14:11:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9956, loss_cls: 0.5211, loss: 0.5211 +2025-06-24 19:29:28,057 - pyskl - INFO - Epoch [54][500/1281] lr: 1.797e-02, eta: 14:10:41, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9950, loss_cls: 0.5221, loss: 0.5221 +2025-06-24 19:30:17,364 - pyskl - INFO - Epoch [54][600/1281] lr: 1.795e-02, eta: 14:10:15, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9956, loss_cls: 0.5561, loss: 0.5561 +2025-06-24 19:30:49,693 - pyskl - INFO - Epoch [54][700/1281] lr: 1.793e-02, eta: 14:09:17, time: 0.323, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9944, loss_cls: 0.5905, loss: 0.5905 +2025-06-24 19:31:40,639 - pyskl - INFO - Epoch [54][800/1281] lr: 1.791e-02, eta: 14:08:53, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9962, loss_cls: 0.5094, loss: 0.5094 +2025-06-24 19:32:05,512 - pyskl - INFO - Epoch [54][900/1281] lr: 1.789e-02, eta: 14:07:43, time: 0.249, data_time: 0.000, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9956, loss_cls: 0.6694, loss: 0.6694 +2025-06-24 19:32:52,860 - pyskl - INFO - Epoch [54][1000/1281] lr: 1.787e-02, eta: 14:07:12, time: 0.473, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9969, loss_cls: 0.5563, loss: 0.5563 +2025-06-24 19:33:41,841 - pyskl - INFO - Epoch [54][1100/1281] lr: 1.786e-02, eta: 14:06:45, time: 0.490, data_time: 0.001, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9944, loss_cls: 0.5665, loss: 0.5665 +2025-06-24 19:34:30,825 - pyskl - INFO - Epoch [54][1200/1281] lr: 1.784e-02, eta: 14:06:18, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9956, loss_cls: 0.5794, loss: 0.5794 +2025-06-24 19:35:10,860 - pyskl - INFO - Saving checkpoint at 54 epochs +2025-06-24 19:36:10,326 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:36:10,380 - pyskl - INFO - +top1_acc 0.8157 +top5_acc 0.9864 +2025-06-24 19:36:10,380 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:36:10,388 - pyskl - INFO - +mean_acc 0.7609 +2025-06-24 19:36:10,390 - pyskl - INFO - Epoch(val) [54][533] top1_acc: 0.8157, top5_acc: 0.9864, mean_class_accuracy: 0.7609 +2025-06-24 19:37:29,943 - pyskl - INFO - Epoch [55][100/1281] lr: 1.780e-02, eta: 14:05:11, time: 0.795, data_time: 0.192, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9956, loss_cls: 0.4853, loss: 0.4853 +2025-06-24 19:38:19,150 - pyskl - INFO - Epoch [55][200/1281] lr: 1.779e-02, eta: 14:04:44, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9969, loss_cls: 0.5183, loss: 0.5183 +2025-06-24 19:39:08,131 - pyskl - INFO - Epoch [55][300/1281] lr: 1.777e-02, eta: 14:04:17, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9931, loss_cls: 0.6075, loss: 0.6075 +2025-06-24 19:39:57,020 - pyskl - INFO - Epoch [55][400/1281] lr: 1.775e-02, eta: 14:03:49, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9950, loss_cls: 0.5375, loss: 0.5375 +2025-06-24 19:40:45,709 - pyskl - INFO - Epoch [55][500/1281] lr: 1.773e-02, eta: 14:03:20, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9962, loss_cls: 0.5352, loss: 0.5352 +2025-06-24 19:41:35,028 - pyskl - INFO - Epoch [55][600/1281] lr: 1.771e-02, eta: 14:02:53, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9925, loss_cls: 0.5892, loss: 0.5892 +2025-06-24 19:42:09,245 - pyskl - INFO - Epoch [55][700/1281] lr: 1.769e-02, eta: 14:01:59, time: 0.342, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9975, loss_cls: 0.5812, loss: 0.5812 +2025-06-24 19:43:00,332 - pyskl - INFO - Epoch [55][800/1281] lr: 1.767e-02, eta: 14:01:35, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9969, loss_cls: 0.5796, loss: 0.5796 +2025-06-24 19:43:24,715 - pyskl - INFO - Epoch [55][900/1281] lr: 1.766e-02, eta: 14:00:24, time: 0.244, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9925, loss_cls: 0.5848, loss: 0.5848 +2025-06-24 19:44:11,873 - pyskl - INFO - Epoch [55][1000/1281] lr: 1.764e-02, eta: 13:59:53, time: 0.472, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9956, loss_cls: 0.5167, loss: 0.5167 +2025-06-24 19:45:00,836 - pyskl - INFO - Epoch [55][1100/1281] lr: 1.762e-02, eta: 13:59:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9950, loss_cls: 0.5394, loss: 0.5394 +2025-06-24 19:45:50,515 - pyskl - INFO - Epoch [55][1200/1281] lr: 1.760e-02, eta: 13:58:58, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9969, loss_cls: 0.5503, loss: 0.5503 +2025-06-24 19:46:31,023 - pyskl - INFO - Saving checkpoint at 55 epochs +2025-06-24 19:47:30,878 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:47:30,939 - pyskl - INFO - +top1_acc 0.8427 +top5_acc 0.9878 +2025-06-24 19:47:30,939 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:47:30,946 - pyskl - INFO - +mean_acc 0.7919 +2025-06-24 19:47:30,947 - pyskl - INFO - Epoch(val) [55][533] top1_acc: 0.8427, top5_acc: 0.9878, mean_class_accuracy: 0.7919 +2025-06-24 19:48:50,586 - pyskl - INFO - Epoch [56][100/1281] lr: 1.757e-02, eta: 13:57:52, time: 0.796, data_time: 0.193, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9981, loss_cls: 0.4768, loss: 0.4768 +2025-06-24 19:49:39,657 - pyskl - INFO - Epoch [56][200/1281] lr: 1.755e-02, eta: 13:57:24, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9969, loss_cls: 0.5370, loss: 0.5370 +2025-06-24 19:50:28,775 - pyskl - INFO - Epoch [56][300/1281] lr: 1.753e-02, eta: 13:56:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9981, loss_cls: 0.5286, loss: 0.5286 +2025-06-24 19:51:17,777 - pyskl - INFO - Epoch [56][400/1281] lr: 1.751e-02, eta: 13:56:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9938, loss_cls: 0.5940, loss: 0.5940 +2025-06-24 19:52:06,464 - pyskl - INFO - Epoch [56][500/1281] lr: 1.749e-02, eta: 13:55:58, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9975, loss_cls: 0.5477, loss: 0.5477 +2025-06-24 19:52:55,490 - pyskl - INFO - Epoch [56][600/1281] lr: 1.747e-02, eta: 13:55:30, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9956, loss_cls: 0.5295, loss: 0.5295 +2025-06-24 19:53:30,867 - pyskl - INFO - Epoch [56][700/1281] lr: 1.745e-02, eta: 13:54:38, time: 0.354, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9975, loss_cls: 0.5095, loss: 0.5095 +2025-06-24 19:54:21,816 - pyskl - INFO - Epoch [56][800/1281] lr: 1.743e-02, eta: 13:54:13, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9950, loss_cls: 0.5930, loss: 0.5930 +2025-06-24 19:54:46,734 - pyskl - INFO - Epoch [56][900/1281] lr: 1.742e-02, eta: 13:53:04, time: 0.249, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9956, loss_cls: 0.5390, loss: 0.5390 +2025-06-24 19:55:33,449 - pyskl - INFO - Epoch [56][1000/1281] lr: 1.740e-02, eta: 13:52:31, time: 0.467, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9956, loss_cls: 0.5627, loss: 0.5627 +2025-06-24 19:56:22,414 - pyskl - INFO - Epoch [56][1100/1281] lr: 1.738e-02, eta: 13:52:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9969, loss_cls: 0.5847, loss: 0.5847 +2025-06-24 19:57:11,508 - pyskl - INFO - Epoch [56][1200/1281] lr: 1.736e-02, eta: 13:51:34, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9956, loss_cls: 0.5255, loss: 0.5255 +2025-06-24 19:57:51,698 - pyskl - INFO - Saving checkpoint at 56 epochs +2025-06-24 19:58:51,007 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:58:51,068 - pyskl - INFO - +top1_acc 0.8579 +top5_acc 0.9899 +2025-06-24 19:58:51,068 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:58:51,077 - pyskl - INFO - +mean_acc 0.8194 +2025-06-24 19:58:51,082 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_45.pth was removed +2025-06-24 19:58:51,280 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_56.pth. +2025-06-24 19:58:51,281 - pyskl - INFO - Best top1_acc is 0.8579 at 56 epoch. +2025-06-24 19:58:51,284 - pyskl - INFO - Epoch(val) [56][533] top1_acc: 0.8579, top5_acc: 0.9899, mean_class_accuracy: 0.8194 +2025-06-24 20:00:11,787 - pyskl - INFO - Epoch [57][100/1281] lr: 1.733e-02, eta: 13:50:29, time: 0.805, data_time: 0.190, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9969, loss_cls: 0.5345, loss: 0.5345 +2025-06-24 20:01:00,558 - pyskl - INFO - Epoch [57][200/1281] lr: 1.731e-02, eta: 13:50:00, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9956, loss_cls: 0.5056, loss: 0.5056 +2025-06-24 20:01:49,596 - pyskl - INFO - Epoch [57][300/1281] lr: 1.729e-02, eta: 13:49:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9962, loss_cls: 0.5298, loss: 0.5298 +2025-06-24 20:02:38,534 - pyskl - INFO - Epoch [57][400/1281] lr: 1.727e-02, eta: 13:49:02, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9956, loss_cls: 0.4843, loss: 0.4843 +2025-06-24 20:03:27,899 - pyskl - INFO - Epoch [57][500/1281] lr: 1.725e-02, eta: 13:48:34, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9962, loss_cls: 0.5657, loss: 0.5657 +2025-06-24 20:04:16,644 - pyskl - INFO - Epoch [57][600/1281] lr: 1.723e-02, eta: 13:48:04, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9925, loss_cls: 0.5520, loss: 0.5520 +2025-06-24 20:04:50,852 - pyskl - INFO - Epoch [57][700/1281] lr: 1.721e-02, eta: 13:47:11, time: 0.342, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9950, loss_cls: 0.5336, loss: 0.5336 +2025-06-24 20:05:41,728 - pyskl - INFO - Epoch [57][800/1281] lr: 1.719e-02, eta: 13:46:45, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9944, loss_cls: 0.5170, loss: 0.5170 +2025-06-24 20:06:06,357 - pyskl - INFO - Epoch [57][900/1281] lr: 1.717e-02, eta: 13:45:36, time: 0.246, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9938, loss_cls: 0.5697, loss: 0.5697 +2025-06-24 20:06:52,198 - pyskl - INFO - Epoch [57][1000/1281] lr: 1.716e-02, eta: 13:45:01, time: 0.458, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9962, loss_cls: 0.5543, loss: 0.5543 +2025-06-24 20:07:41,336 - pyskl - INFO - Epoch [57][1100/1281] lr: 1.714e-02, eta: 13:44:33, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9956, loss_cls: 0.5301, loss: 0.5301 +2025-06-24 20:08:30,369 - pyskl - INFO - Epoch [57][1200/1281] lr: 1.712e-02, eta: 13:44:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9950, loss_cls: 0.5328, loss: 0.5328 +2025-06-24 20:09:10,420 - pyskl - INFO - Saving checkpoint at 57 epochs +2025-06-24 20:10:09,650 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:10:09,705 - pyskl - INFO - +top1_acc 0.8490 +top5_acc 0.9879 +2025-06-24 20:10:09,706 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:10:09,713 - pyskl - INFO - +mean_acc 0.7968 +2025-06-24 20:10:09,715 - pyskl - INFO - Epoch(val) [57][533] top1_acc: 0.8490, top5_acc: 0.9879, mean_class_accuracy: 0.7968 +2025-06-24 20:11:30,046 - pyskl - INFO - Epoch [58][100/1281] lr: 1.708e-02, eta: 13:42:57, time: 0.803, data_time: 0.192, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9962, loss_cls: 0.5500, loss: 0.5500 +2025-06-24 20:12:19,391 - pyskl - INFO - Epoch [58][200/1281] lr: 1.706e-02, eta: 13:42:28, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9981, loss_cls: 0.5142, loss: 0.5142 +2025-06-24 20:13:08,573 - pyskl - INFO - Epoch [58][300/1281] lr: 1.704e-02, eta: 13:41:59, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9962, loss_cls: 0.4922, loss: 0.4922 +2025-06-24 20:13:57,877 - pyskl - INFO - Epoch [58][400/1281] lr: 1.703e-02, eta: 13:41:30, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9969, loss_cls: 0.4628, loss: 0.4628 +2025-06-24 20:14:47,126 - pyskl - INFO - Epoch [58][500/1281] lr: 1.701e-02, eta: 13:41:01, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9988, loss_cls: 0.4891, loss: 0.4891 +2025-06-24 20:15:36,199 - pyskl - INFO - Epoch [58][600/1281] lr: 1.699e-02, eta: 13:40:32, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9956, loss_cls: 0.5243, loss: 0.5243 +2025-06-24 20:16:12,144 - pyskl - INFO - Epoch [58][700/1281] lr: 1.697e-02, eta: 13:39:41, time: 0.359, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9950, loss_cls: 0.5518, loss: 0.5518 +2025-06-24 20:17:03,087 - pyskl - INFO - Epoch [58][800/1281] lr: 1.695e-02, eta: 13:39:15, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9944, loss_cls: 0.5121, loss: 0.5121 +2025-06-24 20:17:27,380 - pyskl - INFO - Epoch [58][900/1281] lr: 1.693e-02, eta: 13:38:06, time: 0.243, data_time: 0.001, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9919, loss_cls: 0.5879, loss: 0.5879 +2025-06-24 20:18:13,458 - pyskl - INFO - Epoch [58][1000/1281] lr: 1.691e-02, eta: 13:37:32, time: 0.461, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9988, loss_cls: 0.5145, loss: 0.5145 +2025-06-24 20:19:02,686 - pyskl - INFO - Epoch [58][1100/1281] lr: 1.689e-02, eta: 13:37:02, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9969, loss_cls: 0.5499, loss: 0.5499 +2025-06-24 20:19:51,786 - pyskl - INFO - Epoch [58][1200/1281] lr: 1.687e-02, eta: 13:36:33, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9969, loss_cls: 0.5190, loss: 0.5190 +2025-06-24 20:20:32,073 - pyskl - INFO - Saving checkpoint at 58 epochs +2025-06-24 20:21:31,500 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:21:31,556 - pyskl - INFO - +top1_acc 0.8583 +top5_acc 0.9877 +2025-06-24 20:21:31,556 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:21:31,563 - pyskl - INFO - +mean_acc 0.8218 +2025-06-24 20:21:31,567 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_56.pth was removed +2025-06-24 20:21:31,739 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_58.pth. +2025-06-24 20:21:31,739 - pyskl - INFO - Best top1_acc is 0.8583 at 58 epoch. +2025-06-24 20:21:31,741 - pyskl - INFO - Epoch(val) [58][533] top1_acc: 0.8583, top5_acc: 0.9877, mean_class_accuracy: 0.8218 +2025-06-24 20:22:51,132 - pyskl - INFO - Epoch [59][100/1281] lr: 1.684e-02, eta: 13:35:24, time: 0.794, data_time: 0.195, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9988, loss_cls: 0.4481, loss: 0.4481 +2025-06-24 20:23:40,336 - pyskl - INFO - Epoch [59][200/1281] lr: 1.682e-02, eta: 13:34:55, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9981, loss_cls: 0.5078, loss: 0.5078 +2025-06-24 20:24:29,475 - pyskl - INFO - Epoch [59][300/1281] lr: 1.680e-02, eta: 13:34:25, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9988, loss_cls: 0.4723, loss: 0.4723 +2025-06-24 20:25:18,613 - pyskl - INFO - Epoch [59][400/1281] lr: 1.678e-02, eta: 13:33:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9975, loss_cls: 0.5013, loss: 0.5013 +2025-06-24 20:26:07,574 - pyskl - INFO - Epoch [59][500/1281] lr: 1.676e-02, eta: 13:33:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9981, loss_cls: 0.5335, loss: 0.5335 +2025-06-24 20:26:56,612 - pyskl - INFO - Epoch [59][600/1281] lr: 1.674e-02, eta: 13:32:56, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9944, loss_cls: 0.5323, loss: 0.5323 +2025-06-24 20:27:33,279 - pyskl - INFO - Epoch [59][700/1281] lr: 1.672e-02, eta: 13:32:06, time: 0.367, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9962, loss_cls: 0.5484, loss: 0.5484 +2025-06-24 20:28:24,369 - pyskl - INFO - Epoch [59][800/1281] lr: 1.670e-02, eta: 13:31:39, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9969, loss_cls: 0.5786, loss: 0.5786 +2025-06-24 20:28:47,842 - pyskl - INFO - Epoch [59][900/1281] lr: 1.668e-02, eta: 13:30:30, time: 0.235, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9956, loss_cls: 0.4933, loss: 0.4933 +2025-06-24 20:29:31,931 - pyskl - INFO - Epoch [59][1000/1281] lr: 1.667e-02, eta: 13:29:52, time: 0.441, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9919, loss_cls: 0.6106, loss: 0.6106 +2025-06-24 20:30:21,130 - pyskl - INFO - Epoch [59][1100/1281] lr: 1.665e-02, eta: 13:29:22, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9962, loss_cls: 0.5480, loss: 0.5480 +2025-06-24 20:31:09,681 - pyskl - INFO - Epoch [59][1200/1281] lr: 1.663e-02, eta: 13:28:51, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9969, loss_cls: 0.5701, loss: 0.5701 +2025-06-24 20:31:50,440 - pyskl - INFO - Saving checkpoint at 59 epochs +2025-06-24 20:32:50,089 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:32:50,149 - pyskl - INFO - +top1_acc 0.8386 +top5_acc 0.9858 +2025-06-24 20:32:50,149 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:32:50,156 - pyskl - INFO - +mean_acc 0.8095 +2025-06-24 20:32:50,158 - pyskl - INFO - Epoch(val) [59][533] top1_acc: 0.8386, top5_acc: 0.9858, mean_class_accuracy: 0.8095 +2025-06-24 20:34:11,410 - pyskl - INFO - Epoch [60][100/1281] lr: 1.659e-02, eta: 13:27:45, time: 0.812, data_time: 0.193, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9988, loss_cls: 0.4896, loss: 0.4896 +2025-06-24 20:35:00,670 - pyskl - INFO - Epoch [60][200/1281] lr: 1.657e-02, eta: 13:27:15, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9931, loss_cls: 0.5044, loss: 0.5044 +2025-06-24 20:35:49,711 - pyskl - INFO - Epoch [60][300/1281] lr: 1.655e-02, eta: 13:26:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9956, loss_cls: 0.4988, loss: 0.4988 +2025-06-24 20:36:38,830 - pyskl - INFO - Epoch [60][400/1281] lr: 1.653e-02, eta: 13:26:15, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9981, loss_cls: 0.5035, loss: 0.5035 +2025-06-24 20:37:27,559 - pyskl - INFO - Epoch [60][500/1281] lr: 1.651e-02, eta: 13:25:44, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9962, loss_cls: 0.4818, loss: 0.4818 +2025-06-24 20:38:16,704 - pyskl - INFO - Epoch [60][600/1281] lr: 1.650e-02, eta: 13:25:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9975, loss_cls: 0.4522, loss: 0.4522 +2025-06-24 20:38:55,250 - pyskl - INFO - Epoch [60][700/1281] lr: 1.648e-02, eta: 13:24:27, time: 0.385, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9969, loss_cls: 0.5028, loss: 0.5028 +2025-06-24 20:39:46,403 - pyskl - INFO - Epoch [60][800/1281] lr: 1.646e-02, eta: 13:24:00, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9956, loss_cls: 0.5161, loss: 0.5161 +2025-06-24 20:40:09,809 - pyskl - INFO - Epoch [60][900/1281] lr: 1.644e-02, eta: 13:22:51, time: 0.234, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9944, loss_cls: 0.5111, loss: 0.5111 +2025-06-24 20:40:53,068 - pyskl - INFO - Epoch [60][1000/1281] lr: 1.642e-02, eta: 13:22:12, time: 0.433, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9981, loss_cls: 0.5132, loss: 0.5132 +2025-06-24 20:41:42,079 - pyskl - INFO - Epoch [60][1100/1281] lr: 1.640e-02, eta: 13:21:41, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9950, loss_cls: 0.5091, loss: 0.5091 +2025-06-24 20:42:31,112 - pyskl - INFO - Epoch [60][1200/1281] lr: 1.638e-02, eta: 13:21:10, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9956, loss_cls: 0.5485, loss: 0.5485 +2025-06-24 20:43:11,248 - pyskl - INFO - Saving checkpoint at 60 epochs +2025-06-24 20:44:10,472 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:44:10,530 - pyskl - INFO - +top1_acc 0.8537 +top5_acc 0.9865 +2025-06-24 20:44:10,530 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:44:10,538 - pyskl - INFO - +mean_acc 0.7989 +2025-06-24 20:44:10,540 - pyskl - INFO - Epoch(val) [60][533] top1_acc: 0.8537, top5_acc: 0.9865, mean_class_accuracy: 0.7989 +2025-06-24 20:45:28,781 - pyskl - INFO - Epoch [61][100/1281] lr: 1.634e-02, eta: 13:19:59, time: 0.782, data_time: 0.193, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9969, loss_cls: 0.5074, loss: 0.5074 +2025-06-24 20:46:17,623 - pyskl - INFO - Epoch [61][200/1281] lr: 1.632e-02, eta: 13:19:28, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9981, loss_cls: 0.4980, loss: 0.4980 +2025-06-24 20:47:06,552 - pyskl - INFO - Epoch [61][300/1281] lr: 1.630e-02, eta: 13:18:57, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9988, loss_cls: 0.4599, loss: 0.4599 +2025-06-24 20:47:55,490 - pyskl - INFO - Epoch [61][400/1281] lr: 1.629e-02, eta: 13:18:27, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9981, loss_cls: 0.4577, loss: 0.4577 +2025-06-24 20:48:44,517 - pyskl - INFO - Epoch [61][500/1281] lr: 1.627e-02, eta: 13:17:56, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9912, loss_cls: 0.5301, loss: 0.5301 +2025-06-24 20:49:33,369 - pyskl - INFO - Epoch [61][600/1281] lr: 1.625e-02, eta: 13:17:25, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9988, loss_cls: 0.5182, loss: 0.5182 +2025-06-24 20:50:14,916 - pyskl - INFO - Epoch [61][700/1281] lr: 1.623e-02, eta: 13:16:43, time: 0.415, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9962, loss_cls: 0.5057, loss: 0.5057 +2025-06-24 20:51:01,610 - pyskl - INFO - Epoch [61][800/1281] lr: 1.621e-02, eta: 13:16:08, time: 0.467, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9975, loss_cls: 0.4894, loss: 0.4894 +2025-06-24 20:51:28,365 - pyskl - INFO - Epoch [61][900/1281] lr: 1.619e-02, eta: 13:15:04, time: 0.268, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9944, loss_cls: 0.5564, loss: 0.5564 +2025-06-24 20:52:09,842 - pyskl - INFO - Epoch [61][1000/1281] lr: 1.617e-02, eta: 13:14:22, time: 0.415, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9969, loss_cls: 0.4997, loss: 0.4997 +2025-06-24 20:52:58,923 - pyskl - INFO - Epoch [61][1100/1281] lr: 1.615e-02, eta: 13:13:52, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9969, loss_cls: 0.5158, loss: 0.5158 +2025-06-24 20:53:47,906 - pyskl - INFO - Epoch [61][1200/1281] lr: 1.613e-02, eta: 13:13:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9975, loss_cls: 0.5299, loss: 0.5299 +2025-06-24 20:54:28,444 - pyskl - INFO - Saving checkpoint at 61 epochs +2025-06-24 20:55:28,250 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:55:28,307 - pyskl - INFO - +top1_acc 0.8406 +top5_acc 0.9857 +2025-06-24 20:55:28,307 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:55:28,314 - pyskl - INFO - +mean_acc 0.7917 +2025-06-24 20:55:28,317 - pyskl - INFO - Epoch(val) [61][533] top1_acc: 0.8406, top5_acc: 0.9857, mean_class_accuracy: 0.7917 +2025-06-24 20:56:48,152 - pyskl - INFO - Epoch [62][100/1281] lr: 1.609e-02, eta: 13:12:11, time: 0.798, data_time: 0.187, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9962, loss_cls: 0.5362, loss: 0.5362 +2025-06-24 20:57:37,156 - pyskl - INFO - Epoch [62][200/1281] lr: 1.607e-02, eta: 13:11:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9988, loss_cls: 0.4974, loss: 0.4974 +2025-06-24 20:58:26,282 - pyskl - INFO - Epoch [62][300/1281] lr: 1.605e-02, eta: 13:11:09, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9988, loss_cls: 0.4613, loss: 0.4613 +2025-06-24 20:59:15,708 - pyskl - INFO - Epoch [62][400/1281] lr: 1.603e-02, eta: 13:10:38, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9969, loss_cls: 0.5053, loss: 0.5053 +2025-06-24 21:00:04,914 - pyskl - INFO - Epoch [62][500/1281] lr: 1.602e-02, eta: 13:10:07, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9969, loss_cls: 0.4779, loss: 0.4779 +2025-06-24 21:00:54,384 - pyskl - INFO - Epoch [62][600/1281] lr: 1.600e-02, eta: 13:09:37, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9969, loss_cls: 0.4210, loss: 0.4210 +2025-06-24 21:01:36,484 - pyskl - INFO - Epoch [62][700/1281] lr: 1.598e-02, eta: 13:08:55, time: 0.421, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9969, loss_cls: 0.4551, loss: 0.4551 +2025-06-24 21:02:22,364 - pyskl - INFO - Epoch [62][800/1281] lr: 1.596e-02, eta: 13:08:20, time: 0.459, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9975, loss_cls: 0.5065, loss: 0.5065 +2025-06-24 21:02:49,815 - pyskl - INFO - Epoch [62][900/1281] lr: 1.594e-02, eta: 13:07:17, time: 0.275, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9975, loss_cls: 0.4515, loss: 0.4515 +2025-06-24 21:03:32,019 - pyskl - INFO - Epoch [62][1000/1281] lr: 1.592e-02, eta: 13:06:36, time: 0.422, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9969, loss_cls: 0.4845, loss: 0.4845 +2025-06-24 21:04:21,243 - pyskl - INFO - Epoch [62][1100/1281] lr: 1.590e-02, eta: 13:06:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9962, loss_cls: 0.5078, loss: 0.5078 +2025-06-24 21:05:10,271 - pyskl - INFO - Epoch [62][1200/1281] lr: 1.588e-02, eta: 13:05:33, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9988, loss_cls: 0.4760, loss: 0.4760 +2025-06-24 21:05:50,829 - pyskl - INFO - Saving checkpoint at 62 epochs +2025-06-24 21:06:49,083 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:06:49,140 - pyskl - INFO - +top1_acc 0.8366 +top5_acc 0.9844 +2025-06-24 21:06:49,140 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:06:49,147 - pyskl - INFO - +mean_acc 0.7957 +2025-06-24 21:06:49,150 - pyskl - INFO - Epoch(val) [62][533] top1_acc: 0.8366, top5_acc: 0.9844, mean_class_accuracy: 0.7957 +2025-06-24 21:08:08,599 - pyskl - INFO - Epoch [63][100/1281] lr: 1.584e-02, eta: 13:04:23, time: 0.794, data_time: 0.188, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9956, loss_cls: 0.4971, loss: 0.4971 +2025-06-24 21:08:57,886 - pyskl - INFO - Epoch [63][200/1281] lr: 1.582e-02, eta: 13:03:52, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9950, loss_cls: 0.4834, loss: 0.4834 +2025-06-24 21:09:47,185 - pyskl - INFO - Epoch [63][300/1281] lr: 1.580e-02, eta: 13:03:21, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9988, loss_cls: 0.4580, loss: 0.4580 +2025-06-24 21:10:36,320 - pyskl - INFO - Epoch [63][400/1281] lr: 1.578e-02, eta: 13:02:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9988, loss_cls: 0.4186, loss: 0.4186 +2025-06-24 21:11:25,587 - pyskl - INFO - Epoch [63][500/1281] lr: 1.576e-02, eta: 13:02:18, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9981, loss_cls: 0.4813, loss: 0.4813 +2025-06-24 21:12:14,879 - pyskl - INFO - Epoch [63][600/1281] lr: 1.574e-02, eta: 13:01:47, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9950, loss_cls: 0.5388, loss: 0.5388 +2025-06-24 21:12:58,739 - pyskl - INFO - Epoch [63][700/1281] lr: 1.572e-02, eta: 13:01:08, time: 0.439, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9969, loss_cls: 0.4978, loss: 0.4978 +2025-06-24 21:13:39,701 - pyskl - INFO - Epoch [63][800/1281] lr: 1.570e-02, eta: 13:00:25, time: 0.410, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9956, loss_cls: 0.5200, loss: 0.5200 +2025-06-24 21:14:12,369 - pyskl - INFO - Epoch [63][900/1281] lr: 1.568e-02, eta: 12:59:30, time: 0.327, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9956, loss_cls: 0.5246, loss: 0.5246 +2025-06-24 21:14:52,078 - pyskl - INFO - Epoch [63][1000/1281] lr: 1.566e-02, eta: 12:58:45, time: 0.397, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9969, loss_cls: 0.5091, loss: 0.5091 +2025-06-24 21:15:41,409 - pyskl - INFO - Epoch [63][1100/1281] lr: 1.564e-02, eta: 12:58:14, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9969, loss_cls: 0.5107, loss: 0.5107 +2025-06-24 21:16:30,913 - pyskl - INFO - Epoch [63][1200/1281] lr: 1.562e-02, eta: 12:57:43, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9969, loss_cls: 0.4916, loss: 0.4916 +2025-06-24 21:17:11,367 - pyskl - INFO - Saving checkpoint at 63 epochs +2025-06-24 21:18:10,292 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:18:10,360 - pyskl - INFO - +top1_acc 0.8511 +top5_acc 0.9896 +2025-06-24 21:18:10,360 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:18:10,368 - pyskl - INFO - +mean_acc 0.8234 +2025-06-24 21:18:10,370 - pyskl - INFO - Epoch(val) [63][533] top1_acc: 0.8511, top5_acc: 0.9896, mean_class_accuracy: 0.8234 +2025-06-24 21:19:29,562 - pyskl - INFO - Epoch [64][100/1281] lr: 1.559e-02, eta: 12:56:32, time: 0.792, data_time: 0.196, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9994, loss_cls: 0.4598, loss: 0.4598 +2025-06-24 21:20:18,939 - pyskl - INFO - Epoch [64][200/1281] lr: 1.557e-02, eta: 12:56:00, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9988, loss_cls: 0.4693, loss: 0.4693 +2025-06-24 21:21:08,130 - pyskl - INFO - Epoch [64][300/1281] lr: 1.555e-02, eta: 12:55:28, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9975, loss_cls: 0.4609, loss: 0.4609 +2025-06-24 21:21:57,566 - pyskl - INFO - Epoch [64][400/1281] lr: 1.553e-02, eta: 12:54:57, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9981, loss_cls: 0.4399, loss: 0.4399 +2025-06-24 21:22:46,994 - pyskl - INFO - Epoch [64][500/1281] lr: 1.551e-02, eta: 12:54:25, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9988, loss_cls: 0.4201, loss: 0.4201 +2025-06-24 21:23:36,136 - pyskl - INFO - Epoch [64][600/1281] lr: 1.549e-02, eta: 12:53:53, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9969, loss_cls: 0.5178, loss: 0.5178 +2025-06-24 21:24:21,974 - pyskl - INFO - Epoch [64][700/1281] lr: 1.547e-02, eta: 12:53:17, time: 0.458, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9969, loss_cls: 0.5001, loss: 0.5001 +2025-06-24 21:24:59,494 - pyskl - INFO - Epoch [64][800/1281] lr: 1.545e-02, eta: 12:52:29, time: 0.375, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9975, loss_cls: 0.5764, loss: 0.5764 +2025-06-24 21:25:35,606 - pyskl - INFO - Epoch [64][900/1281] lr: 1.543e-02, eta: 12:51:39, time: 0.361, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9962, loss_cls: 0.5572, loss: 0.5572 +2025-06-24 21:26:13,446 - pyskl - INFO - Epoch [64][1000/1281] lr: 1.541e-02, eta: 12:50:52, time: 0.378, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9912, loss_cls: 0.5697, loss: 0.5697 +2025-06-24 21:27:02,188 - pyskl - INFO - Epoch [64][1100/1281] lr: 1.539e-02, eta: 12:50:19, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9969, loss_cls: 0.5401, loss: 0.5401 +2025-06-24 21:27:51,449 - pyskl - INFO - Epoch [64][1200/1281] lr: 1.537e-02, eta: 12:49:47, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9975, loss_cls: 0.4437, loss: 0.4437 +2025-06-24 21:28:31,702 - pyskl - INFO - Saving checkpoint at 64 epochs +2025-06-24 21:29:30,467 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:29:30,540 - pyskl - INFO - +top1_acc 0.8578 +top5_acc 0.9900 +2025-06-24 21:29:30,540 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:29:30,552 - pyskl - INFO - +mean_acc 0.8192 +2025-06-24 21:29:30,554 - pyskl - INFO - Epoch(val) [64][533] top1_acc: 0.8578, top5_acc: 0.9900, mean_class_accuracy: 0.8192 +2025-06-24 21:30:51,114 - pyskl - INFO - Epoch [65][100/1281] lr: 1.533e-02, eta: 12:48:38, time: 0.806, data_time: 0.189, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9975, loss_cls: 0.4173, loss: 0.4173 +2025-06-24 21:31:40,095 - pyskl - INFO - Epoch [65][200/1281] lr: 1.531e-02, eta: 12:48:05, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9956, loss_cls: 0.5102, loss: 0.5102 +2025-06-24 21:32:29,300 - pyskl - INFO - Epoch [65][300/1281] lr: 1.529e-02, eta: 12:47:33, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9988, loss_cls: 0.4519, loss: 0.4519 +2025-06-24 21:33:18,256 - pyskl - INFO - Epoch [65][400/1281] lr: 1.527e-02, eta: 12:47:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9969, loss_cls: 0.5459, loss: 0.5459 +2025-06-24 21:34:07,490 - pyskl - INFO - Epoch [65][500/1281] lr: 1.526e-02, eta: 12:46:28, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9981, loss_cls: 0.4965, loss: 0.4965 +2025-06-24 21:34:56,882 - pyskl - INFO - Epoch [65][600/1281] lr: 1.524e-02, eta: 12:45:56, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9981, loss_cls: 0.4448, loss: 0.4448 +2025-06-24 21:35:42,498 - pyskl - INFO - Epoch [65][700/1281] lr: 1.522e-02, eta: 12:45:19, time: 0.456, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9956, loss_cls: 0.4499, loss: 0.4499 +2025-06-24 21:36:19,582 - pyskl - INFO - Epoch [65][800/1281] lr: 1.520e-02, eta: 12:44:31, time: 0.371, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9981, loss_cls: 0.4382, loss: 0.4382 +2025-06-24 21:36:55,879 - pyskl - INFO - Epoch [65][900/1281] lr: 1.518e-02, eta: 12:43:42, time: 0.363, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9975, loss_cls: 0.5187, loss: 0.5187 +2025-06-24 21:37:31,639 - pyskl - INFO - Epoch [65][1000/1281] lr: 1.516e-02, eta: 12:42:52, time: 0.358, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9988, loss_cls: 0.5312, loss: 0.5312 +2025-06-24 21:38:20,692 - pyskl - INFO - Epoch [65][1100/1281] lr: 1.514e-02, eta: 12:42:19, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9962, loss_cls: 0.5317, loss: 0.5317 +2025-06-24 21:39:09,818 - pyskl - INFO - Epoch [65][1200/1281] lr: 1.512e-02, eta: 12:41:46, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9950, loss_cls: 0.5280, loss: 0.5280 +2025-06-24 21:39:50,063 - pyskl - INFO - Saving checkpoint at 65 epochs +2025-06-24 21:40:48,406 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:40:48,461 - pyskl - INFO - +top1_acc 0.8781 +top5_acc 0.9916 +2025-06-24 21:40:48,461 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:40:48,468 - pyskl - INFO - +mean_acc 0.8381 +2025-06-24 21:40:48,472 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_58.pth was removed +2025-06-24 21:40:48,676 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_65.pth. +2025-06-24 21:40:48,676 - pyskl - INFO - Best top1_acc is 0.8781 at 65 epoch. +2025-06-24 21:40:48,678 - pyskl - INFO - Epoch(val) [65][533] top1_acc: 0.8781, top5_acc: 0.9916, mean_class_accuracy: 0.8381 +2025-06-24 21:42:08,598 - pyskl - INFO - Epoch [66][100/1281] lr: 1.508e-02, eta: 12:40:36, time: 0.799, data_time: 0.187, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9975, loss_cls: 0.4815, loss: 0.4815 +2025-06-24 21:42:57,619 - pyskl - INFO - Epoch [66][200/1281] lr: 1.506e-02, eta: 12:40:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9981, loss_cls: 0.4946, loss: 0.4946 +2025-06-24 21:43:46,568 - pyskl - INFO - Epoch [66][300/1281] lr: 1.504e-02, eta: 12:39:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9975, loss_cls: 0.4118, loss: 0.4118 +2025-06-24 21:44:35,788 - pyskl - INFO - Epoch [66][400/1281] lr: 1.502e-02, eta: 12:38:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9969, loss_cls: 0.4686, loss: 0.4686 +2025-06-24 21:45:24,767 - pyskl - INFO - Epoch [66][500/1281] lr: 1.500e-02, eta: 12:38:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9975, loss_cls: 0.4667, loss: 0.4667 +2025-06-24 21:46:13,781 - pyskl - INFO - Epoch [66][600/1281] lr: 1.498e-02, eta: 12:37:52, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9956, loss_cls: 0.4818, loss: 0.4818 +2025-06-24 21:47:02,605 - pyskl - INFO - Epoch [66][700/1281] lr: 1.496e-02, eta: 12:37:19, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9975, loss_cls: 0.4519, loss: 0.4519 +2025-06-24 21:47:33,875 - pyskl - INFO - Epoch [66][800/1281] lr: 1.494e-02, eta: 12:36:23, time: 0.313, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9975, loss_cls: 0.4982, loss: 0.4982 +2025-06-24 21:48:16,292 - pyskl - INFO - Epoch [66][900/1281] lr: 1.492e-02, eta: 12:35:41, time: 0.424, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9988, loss_cls: 0.4755, loss: 0.4755 +2025-06-24 21:48:51,357 - pyskl - INFO - Epoch [66][1000/1281] lr: 1.490e-02, eta: 12:34:50, time: 0.351, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9938, loss_cls: 0.5087, loss: 0.5087 +2025-06-24 21:49:40,491 - pyskl - INFO - Epoch [66][1100/1281] lr: 1.488e-02, eta: 12:34:18, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9931, loss_cls: 0.5924, loss: 0.5924 +2025-06-24 21:50:29,768 - pyskl - INFO - Epoch [66][1200/1281] lr: 1.486e-02, eta: 12:33:45, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9969, loss_cls: 0.5197, loss: 0.5197 +2025-06-24 21:51:10,162 - pyskl - INFO - Saving checkpoint at 66 epochs +2025-06-24 21:52:09,288 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:52:09,359 - pyskl - INFO - +top1_acc 0.8603 +top5_acc 0.9918 +2025-06-24 21:52:09,359 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:52:09,367 - pyskl - INFO - +mean_acc 0.8175 +2025-06-24 21:52:09,369 - pyskl - INFO - Epoch(val) [66][533] top1_acc: 0.8603, top5_acc: 0.9918, mean_class_accuracy: 0.8175 +2025-06-24 21:53:28,531 - pyskl - INFO - Epoch [67][100/1281] lr: 1.482e-02, eta: 12:32:33, time: 0.792, data_time: 0.190, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9981, loss_cls: 0.4033, loss: 0.4033 +2025-06-24 21:54:17,783 - pyskl - INFO - Epoch [67][200/1281] lr: 1.480e-02, eta: 12:32:00, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9994, loss_cls: 0.4274, loss: 0.4274 +2025-06-24 21:55:06,600 - pyskl - INFO - Epoch [67][300/1281] lr: 1.478e-02, eta: 12:31:27, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9988, loss_cls: 0.4644, loss: 0.4644 +2025-06-24 21:55:55,818 - pyskl - INFO - Epoch [67][400/1281] lr: 1.476e-02, eta: 12:30:54, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9981, loss_cls: 0.4181, loss: 0.4181 +2025-06-24 21:56:45,013 - pyskl - INFO - Epoch [67][500/1281] lr: 1.474e-02, eta: 12:30:21, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9969, loss_cls: 0.4943, loss: 0.4943 +2025-06-24 21:57:34,284 - pyskl - INFO - Epoch [67][600/1281] lr: 1.472e-02, eta: 12:29:48, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9969, loss_cls: 0.4776, loss: 0.4776 +2025-06-24 21:58:23,287 - pyskl - INFO - Epoch [67][700/1281] lr: 1.470e-02, eta: 12:29:14, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9962, loss_cls: 0.4813, loss: 0.4813 +2025-06-24 21:58:53,188 - pyskl - INFO - Epoch [67][800/1281] lr: 1.468e-02, eta: 12:28:17, time: 0.299, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9975, loss_cls: 0.4377, loss: 0.4377 +2025-06-24 21:59:37,419 - pyskl - INFO - Epoch [67][900/1281] lr: 1.466e-02, eta: 12:27:38, time: 0.442, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9975, loss_cls: 0.4331, loss: 0.4331 +2025-06-24 22:00:09,722 - pyskl - INFO - Epoch [67][1000/1281] lr: 1.464e-02, eta: 12:26:44, time: 0.323, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9969, loss_cls: 0.5369, loss: 0.5369 +2025-06-24 22:00:58,159 - pyskl - INFO - Epoch [67][1100/1281] lr: 1.462e-02, eta: 12:26:10, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9931, loss_cls: 0.5454, loss: 0.5454 +2025-06-24 22:01:47,778 - pyskl - INFO - Epoch [67][1200/1281] lr: 1.460e-02, eta: 12:25:37, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9969, loss_cls: 0.5589, loss: 0.5589 +2025-06-24 22:02:28,076 - pyskl - INFO - Saving checkpoint at 67 epochs +2025-06-24 22:03:27,560 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:03:27,618 - pyskl - INFO - +top1_acc 0.8670 +top5_acc 0.9893 +2025-06-24 22:03:27,618 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:03:27,625 - pyskl - INFO - +mean_acc 0.8168 +2025-06-24 22:03:27,628 - pyskl - INFO - Epoch(val) [67][533] top1_acc: 0.8670, top5_acc: 0.9893, mean_class_accuracy: 0.8168 +2025-06-24 22:04:47,539 - pyskl - INFO - Epoch [68][100/1281] lr: 1.456e-02, eta: 12:24:26, time: 0.799, data_time: 0.193, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9981, loss_cls: 0.4325, loss: 0.4325 +2025-06-24 22:05:37,036 - pyskl - INFO - Epoch [68][200/1281] lr: 1.454e-02, eta: 12:23:53, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9981, loss_cls: 0.4329, loss: 0.4329 +2025-06-24 22:06:26,699 - pyskl - INFO - Epoch [68][300/1281] lr: 1.452e-02, eta: 12:23:20, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9994, loss_cls: 0.3633, loss: 0.3633 +2025-06-24 22:07:15,997 - pyskl - INFO - Epoch [68][400/1281] lr: 1.450e-02, eta: 12:22:47, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9956, loss_cls: 0.4167, loss: 0.4167 +2025-06-24 22:08:04,711 - pyskl - INFO - Epoch [68][500/1281] lr: 1.448e-02, eta: 12:22:13, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9988, loss_cls: 0.4354, loss: 0.4354 +2025-06-24 22:08:53,951 - pyskl - INFO - Epoch [68][600/1281] lr: 1.446e-02, eta: 12:21:40, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9969, loss_cls: 0.4456, loss: 0.4456 +2025-06-24 22:09:43,013 - pyskl - INFO - Epoch [68][700/1281] lr: 1.444e-02, eta: 12:21:06, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9962, loss_cls: 0.4762, loss: 0.4762 +2025-06-24 22:10:11,335 - pyskl - INFO - Epoch [68][800/1281] lr: 1.442e-02, eta: 12:20:07, time: 0.283, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9975, loss_cls: 0.4342, loss: 0.4342 +2025-06-24 22:10:58,976 - pyskl - INFO - Epoch [68][900/1281] lr: 1.440e-02, eta: 12:19:32, time: 0.476, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9981, loss_cls: 0.4527, loss: 0.4527 +2025-06-24 22:11:29,411 - pyskl - INFO - Epoch [68][1000/1281] lr: 1.438e-02, eta: 12:18:36, time: 0.304, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9969, loss_cls: 0.4898, loss: 0.4898 +2025-06-24 22:12:18,172 - pyskl - INFO - Epoch [68][1100/1281] lr: 1.436e-02, eta: 12:18:02, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9975, loss_cls: 0.4966, loss: 0.4966 +2025-06-24 22:13:07,182 - pyskl - INFO - Epoch [68][1200/1281] lr: 1.434e-02, eta: 12:17:28, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9956, loss_cls: 0.4927, loss: 0.4927 +2025-06-24 22:13:47,372 - pyskl - INFO - Saving checkpoint at 68 epochs +2025-06-24 22:14:46,522 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:14:46,584 - pyskl - INFO - +top1_acc 0.8328 +top5_acc 0.9846 +2025-06-24 22:14:46,584 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:14:46,592 - pyskl - INFO - +mean_acc 0.7822 +2025-06-24 22:14:46,594 - pyskl - INFO - Epoch(val) [68][533] top1_acc: 0.8328, top5_acc: 0.9846, mean_class_accuracy: 0.7822 +2025-06-24 22:16:07,572 - pyskl - INFO - Epoch [69][100/1281] lr: 1.431e-02, eta: 12:16:17, time: 0.810, data_time: 0.199, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9975, loss_cls: 0.4074, loss: 0.4074 +2025-06-24 22:16:56,770 - pyskl - INFO - Epoch [69][200/1281] lr: 1.429e-02, eta: 12:15:44, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9938, loss_cls: 0.4352, loss: 0.4352 +2025-06-24 22:17:45,690 - pyskl - INFO - Epoch [69][300/1281] lr: 1.427e-02, eta: 12:15:10, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9969, loss_cls: 0.4485, loss: 0.4485 +2025-06-24 22:18:34,920 - pyskl - INFO - Epoch [69][400/1281] lr: 1.425e-02, eta: 12:14:36, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9988, loss_cls: 0.4480, loss: 0.4480 +2025-06-24 22:19:23,950 - pyskl - INFO - Epoch [69][500/1281] lr: 1.423e-02, eta: 12:14:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9981, loss_cls: 0.4243, loss: 0.4243 +2025-06-24 22:20:13,019 - pyskl - INFO - Epoch [69][600/1281] lr: 1.420e-02, eta: 12:13:29, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9988, loss_cls: 0.4152, loss: 0.4152 +2025-06-24 22:21:02,090 - pyskl - INFO - Epoch [69][700/1281] lr: 1.418e-02, eta: 12:12:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9981, loss_cls: 0.4382, loss: 0.4382 +2025-06-24 22:21:29,107 - pyskl - INFO - Epoch [69][800/1281] lr: 1.416e-02, eta: 12:11:55, time: 0.270, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9944, loss_cls: 0.5022, loss: 0.5022 +2025-06-24 22:22:20,015 - pyskl - INFO - Epoch [69][900/1281] lr: 1.414e-02, eta: 12:11:23, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9981, loss_cls: 0.4535, loss: 0.4535 +2025-06-24 22:22:49,535 - pyskl - INFO - Epoch [69][1000/1281] lr: 1.412e-02, eta: 12:10:26, time: 0.295, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9975, loss_cls: 0.5059, loss: 0.5059 +2025-06-24 22:23:38,459 - pyskl - INFO - Epoch [69][1100/1281] lr: 1.410e-02, eta: 12:09:52, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9944, loss_cls: 0.5034, loss: 0.5034 +2025-06-24 22:24:27,734 - pyskl - INFO - Epoch [69][1200/1281] lr: 1.408e-02, eta: 12:09:18, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9988, loss_cls: 0.4350, loss: 0.4350 +2025-06-24 22:25:08,104 - pyskl - INFO - Saving checkpoint at 69 epochs +2025-06-24 22:26:07,568 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:26:07,625 - pyskl - INFO - +top1_acc 0.8522 +top5_acc 0.9894 +2025-06-24 22:26:07,625 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:26:07,632 - pyskl - INFO - +mean_acc 0.8025 +2025-06-24 22:26:07,634 - pyskl - INFO - Epoch(val) [69][533] top1_acc: 0.8522, top5_acc: 0.9894, mean_class_accuracy: 0.8025 +2025-06-24 22:27:28,364 - pyskl - INFO - Epoch [70][100/1281] lr: 1.405e-02, eta: 12:08:07, time: 0.807, data_time: 0.195, memory: 4083, top1_acc: 0.9325, top5_acc: 1.0000, loss_cls: 0.3892, loss: 0.3892 +2025-06-24 22:28:17,084 - pyskl - INFO - Epoch [70][200/1281] lr: 1.403e-02, eta: 12:07:32, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9981, loss_cls: 0.4275, loss: 0.4275 +2025-06-24 22:29:05,756 - pyskl - INFO - Epoch [70][300/1281] lr: 1.401e-02, eta: 12:06:58, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9981, loss_cls: 0.4398, loss: 0.4398 +2025-06-24 22:29:55,232 - pyskl - INFO - Epoch [70][400/1281] lr: 1.399e-02, eta: 12:06:24, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9981, loss_cls: 0.4257, loss: 0.4257 +2025-06-24 22:30:44,377 - pyskl - INFO - Epoch [70][500/1281] lr: 1.397e-02, eta: 12:05:50, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9981, loss_cls: 0.3469, loss: 0.3469 +2025-06-24 22:31:33,063 - pyskl - INFO - Epoch [70][600/1281] lr: 1.395e-02, eta: 12:05:16, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9969, loss_cls: 0.4353, loss: 0.4353 +2025-06-24 22:32:22,497 - pyskl - INFO - Epoch [70][700/1281] lr: 1.392e-02, eta: 12:04:42, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9962, loss_cls: 0.4787, loss: 0.4787 +2025-06-24 22:32:49,489 - pyskl - INFO - Epoch [70][800/1281] lr: 1.390e-02, eta: 12:03:42, time: 0.270, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9988, loss_cls: 0.3970, loss: 0.3970 +2025-06-24 22:33:40,491 - pyskl - INFO - Epoch [70][900/1281] lr: 1.388e-02, eta: 12:03:10, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9981, loss_cls: 0.4574, loss: 0.4574 +2025-06-24 22:34:08,689 - pyskl - INFO - Epoch [70][1000/1281] lr: 1.386e-02, eta: 12:02:12, time: 0.282, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9994, loss_cls: 0.4652, loss: 0.4652 +2025-06-24 22:34:57,577 - pyskl - INFO - Epoch [70][1100/1281] lr: 1.384e-02, eta: 12:01:37, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9969, loss_cls: 0.4363, loss: 0.4363 +2025-06-24 22:35:46,530 - pyskl - INFO - Epoch [70][1200/1281] lr: 1.382e-02, eta: 12:01:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9969, loss_cls: 0.4544, loss: 0.4544 +2025-06-24 22:36:27,154 - pyskl - INFO - Saving checkpoint at 70 epochs +2025-06-24 22:37:25,957 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:37:26,013 - pyskl - INFO - +top1_acc 0.8572 +top5_acc 0.9887 +2025-06-24 22:37:26,013 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:37:26,020 - pyskl - INFO - +mean_acc 0.8226 +2025-06-24 22:37:26,021 - pyskl - INFO - Epoch(val) [70][533] top1_acc: 0.8572, top5_acc: 0.9887, mean_class_accuracy: 0.8226 +2025-06-24 22:38:46,222 - pyskl - INFO - Epoch [71][100/1281] lr: 1.379e-02, eta: 11:59:51, time: 0.802, data_time: 0.191, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9975, loss_cls: 0.4223, loss: 0.4223 +2025-06-24 22:39:35,716 - pyskl - INFO - Epoch [71][200/1281] lr: 1.377e-02, eta: 11:59:17, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9988, loss_cls: 0.3524, loss: 0.3524 +2025-06-24 22:40:25,020 - pyskl - INFO - Epoch [71][300/1281] lr: 1.375e-02, eta: 11:58:43, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9988, loss_cls: 0.3893, loss: 0.3893 +2025-06-24 22:41:14,501 - pyskl - INFO - Epoch [71][400/1281] lr: 1.373e-02, eta: 11:58:09, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9969, loss_cls: 0.3868, loss: 0.3868 +2025-06-24 22:42:03,384 - pyskl - INFO - Epoch [71][500/1281] lr: 1.371e-02, eta: 11:57:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9969, loss_cls: 0.4132, loss: 0.4132 +2025-06-24 22:42:52,469 - pyskl - INFO - Epoch [71][600/1281] lr: 1.368e-02, eta: 11:57:00, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9938, loss_cls: 0.4484, loss: 0.4484 +2025-06-24 22:43:41,557 - pyskl - INFO - Epoch [71][700/1281] lr: 1.366e-02, eta: 11:56:25, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9988, loss_cls: 0.4947, loss: 0.4947 +2025-06-24 22:44:11,469 - pyskl - INFO - Epoch [71][800/1281] lr: 1.364e-02, eta: 11:55:29, time: 0.299, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9969, loss_cls: 0.4464, loss: 0.4464 +2025-06-24 22:45:02,641 - pyskl - INFO - Epoch [71][900/1281] lr: 1.362e-02, eta: 11:54:57, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9981, loss_cls: 0.4377, loss: 0.4377 +2025-06-24 22:45:29,262 - pyskl - INFO - Epoch [71][1000/1281] lr: 1.360e-02, eta: 11:53:57, time: 0.266, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9969, loss_cls: 0.4084, loss: 0.4084 +2025-06-24 22:46:18,799 - pyskl - INFO - Epoch [71][1100/1281] lr: 1.358e-02, eta: 11:53:23, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9988, loss_cls: 0.4185, loss: 0.4185 +2025-06-24 22:47:07,989 - pyskl - INFO - Epoch [71][1200/1281] lr: 1.356e-02, eta: 11:52:49, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9975, loss_cls: 0.4810, loss: 0.4810 +2025-06-24 22:47:48,354 - pyskl - INFO - Saving checkpoint at 71 epochs +2025-06-24 22:48:47,320 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:48:47,379 - pyskl - INFO - +top1_acc 0.8662 +top5_acc 0.9873 +2025-06-24 22:48:47,379 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:48:47,386 - pyskl - INFO - +mean_acc 0.8284 +2025-06-24 22:48:47,388 - pyskl - INFO - Epoch(val) [71][533] top1_acc: 0.8662, top5_acc: 0.9873, mean_class_accuracy: 0.8284 +2025-06-24 22:50:07,500 - pyskl - INFO - Epoch [72][100/1281] lr: 1.353e-02, eta: 11:51:37, time: 0.801, data_time: 0.192, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9969, loss_cls: 0.3654, loss: 0.3654 +2025-06-24 22:50:56,167 - pyskl - INFO - Epoch [72][200/1281] lr: 1.351e-02, eta: 11:51:01, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9975, loss_cls: 0.3909, loss: 0.3909 +2025-06-24 22:51:45,467 - pyskl - INFO - Epoch [72][300/1281] lr: 1.349e-02, eta: 11:50:27, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9988, loss_cls: 0.4438, loss: 0.4438 +2025-06-24 22:52:34,787 - pyskl - INFO - Epoch [72][400/1281] lr: 1.346e-02, eta: 11:49:53, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9962, loss_cls: 0.4688, loss: 0.4688 +2025-06-24 22:53:24,102 - pyskl - INFO - Epoch [72][500/1281] lr: 1.344e-02, eta: 11:49:18, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 0.3980, loss: 0.3980 +2025-06-24 22:54:13,108 - pyskl - INFO - Epoch [72][600/1281] lr: 1.342e-02, eta: 11:48:43, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9988, loss_cls: 0.3747, loss: 0.3747 +2025-06-24 22:55:02,277 - pyskl - INFO - Epoch [72][700/1281] lr: 1.340e-02, eta: 11:48:09, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9962, loss_cls: 0.4067, loss: 0.4067 +2025-06-24 22:55:33,220 - pyskl - INFO - Epoch [72][800/1281] lr: 1.338e-02, eta: 11:47:14, time: 0.309, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9981, loss_cls: 0.4425, loss: 0.4425 +2025-06-24 22:56:24,231 - pyskl - INFO - Epoch [72][900/1281] lr: 1.336e-02, eta: 11:46:41, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9988, loss_cls: 0.4352, loss: 0.4352 +2025-06-24 22:56:50,298 - pyskl - INFO - Epoch [72][1000/1281] lr: 1.334e-02, eta: 11:45:41, time: 0.261, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9969, loss_cls: 0.4060, loss: 0.4060 +2025-06-24 22:57:39,346 - pyskl - INFO - Epoch [72][1100/1281] lr: 1.332e-02, eta: 11:45:06, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9981, loss_cls: 0.4232, loss: 0.4232 +2025-06-24 22:58:28,365 - pyskl - INFO - Epoch [72][1200/1281] lr: 1.330e-02, eta: 11:44:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9994, loss_cls: 0.4837, loss: 0.4837 +2025-06-24 22:59:08,363 - pyskl - INFO - Saving checkpoint at 72 epochs +2025-06-24 23:00:06,961 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:00:07,029 - pyskl - INFO - +top1_acc 0.8581 +top5_acc 0.9890 +2025-06-24 23:00:07,030 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:00:07,053 - pyskl - INFO - +mean_acc 0.8026 +2025-06-24 23:00:07,056 - pyskl - INFO - Epoch(val) [72][533] top1_acc: 0.8581, top5_acc: 0.9890, mean_class_accuracy: 0.8026 +2025-06-24 23:01:27,994 - pyskl - INFO - Epoch [73][100/1281] lr: 1.326e-02, eta: 11:43:20, time: 0.809, data_time: 0.194, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9988, loss_cls: 0.3831, loss: 0.3831 +2025-06-24 23:02:17,479 - pyskl - INFO - Epoch [73][200/1281] lr: 1.324e-02, eta: 11:42:45, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9994, loss_cls: 0.4136, loss: 0.4136 +2025-06-24 23:03:06,668 - pyskl - INFO - Epoch [73][300/1281] lr: 1.322e-02, eta: 11:42:10, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9994, loss_cls: 0.3756, loss: 0.3756 +2025-06-24 23:03:55,582 - pyskl - INFO - Epoch [73][400/1281] lr: 1.320e-02, eta: 11:41:35, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9969, loss_cls: 0.4090, loss: 0.4090 +2025-06-24 23:04:44,686 - pyskl - INFO - Epoch [73][500/1281] lr: 1.318e-02, eta: 11:41:00, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9994, loss_cls: 0.3626, loss: 0.3626 +2025-06-24 23:05:33,738 - pyskl - INFO - Epoch [73][600/1281] lr: 1.316e-02, eta: 11:40:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9981, loss_cls: 0.3662, loss: 0.3662 +2025-06-24 23:06:22,883 - pyskl - INFO - Epoch [73][700/1281] lr: 1.314e-02, eta: 11:39:50, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9294, top5_acc: 1.0000, loss_cls: 0.3943, loss: 0.3943 +2025-06-24 23:06:54,493 - pyskl - INFO - Epoch [73][800/1281] lr: 1.312e-02, eta: 11:38:56, time: 0.316, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9944, loss_cls: 0.5273, loss: 0.5273 +2025-06-24 23:07:45,517 - pyskl - INFO - Epoch [73][900/1281] lr: 1.310e-02, eta: 11:38:23, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9981, loss_cls: 0.4329, loss: 0.4329 +2025-06-24 23:08:10,608 - pyskl - INFO - Epoch [73][1000/1281] lr: 1.308e-02, eta: 11:37:23, time: 0.251, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9962, loss_cls: 0.4031, loss: 0.4031 +2025-06-24 23:08:58,454 - pyskl - INFO - Epoch [73][1100/1281] lr: 1.306e-02, eta: 11:36:46, time: 0.478, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9969, loss_cls: 0.4276, loss: 0.4276 +2025-06-24 23:09:47,781 - pyskl - INFO - Epoch [73][1200/1281] lr: 1.304e-02, eta: 11:36:11, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9956, loss_cls: 0.4805, loss: 0.4805 +2025-06-24 23:10:28,400 - pyskl - INFO - Saving checkpoint at 73 epochs +2025-06-24 23:11:27,253 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:11:27,316 - pyskl - INFO - +top1_acc 0.8645 +top5_acc 0.9870 +2025-06-24 23:11:27,316 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:11:27,324 - pyskl - INFO - +mean_acc 0.8358 +2025-06-24 23:11:27,327 - pyskl - INFO - Epoch(val) [73][533] top1_acc: 0.8645, top5_acc: 0.9870, mean_class_accuracy: 0.8358 +2025-06-24 23:12:48,128 - pyskl - INFO - Epoch [74][100/1281] lr: 1.300e-02, eta: 11:34:59, time: 0.808, data_time: 0.194, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9994, loss_cls: 0.3526, loss: 0.3526 +2025-06-24 23:13:37,077 - pyskl - INFO - Epoch [74][200/1281] lr: 1.298e-02, eta: 11:34:24, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9988, loss_cls: 0.3730, loss: 0.3730 +2025-06-24 23:14:26,171 - pyskl - INFO - Epoch [74][300/1281] lr: 1.296e-02, eta: 11:33:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9994, loss_cls: 0.4213, loss: 0.4213 +2025-06-24 23:15:15,266 - pyskl - INFO - Epoch [74][400/1281] lr: 1.294e-02, eta: 11:33:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9969, loss_cls: 0.4675, loss: 0.4675 +2025-06-24 23:16:04,210 - pyskl - INFO - Epoch [74][500/1281] lr: 1.292e-02, eta: 11:32:38, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9969, loss_cls: 0.3978, loss: 0.3978 +2025-06-24 23:16:53,148 - pyskl - INFO - Epoch [74][600/1281] lr: 1.290e-02, eta: 11:32:02, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9988, loss_cls: 0.4184, loss: 0.4184 +2025-06-24 23:17:42,144 - pyskl - INFO - Epoch [74][700/1281] lr: 1.288e-02, eta: 11:31:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9962, loss_cls: 0.4492, loss: 0.4492 +2025-06-24 23:18:15,315 - pyskl - INFO - Epoch [74][800/1281] lr: 1.286e-02, eta: 11:30:35, time: 0.332, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9994, loss_cls: 0.3739, loss: 0.3739 +2025-06-24 23:19:06,397 - pyskl - INFO - Epoch [74][900/1281] lr: 1.284e-02, eta: 11:30:02, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9988, loss_cls: 0.4115, loss: 0.4115 +2025-06-24 23:19:31,453 - pyskl - INFO - Epoch [74][1000/1281] lr: 1.282e-02, eta: 11:29:01, time: 0.251, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9988, loss_cls: 0.4333, loss: 0.4333 +2025-06-24 23:20:19,171 - pyskl - INFO - Epoch [74][1100/1281] lr: 1.280e-02, eta: 11:28:25, time: 0.477, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9975, loss_cls: 0.4116, loss: 0.4116 +2025-06-24 23:21:08,424 - pyskl - INFO - Epoch [74][1200/1281] lr: 1.278e-02, eta: 11:27:49, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9969, loss_cls: 0.4537, loss: 0.4537 +2025-06-24 23:21:48,608 - pyskl - INFO - Saving checkpoint at 74 epochs +2025-06-24 23:22:46,753 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:22:46,808 - pyskl - INFO - +top1_acc 0.8776 +top5_acc 0.9907 +2025-06-24 23:22:46,808 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:22:46,815 - pyskl - INFO - +mean_acc 0.8356 +2025-06-24 23:22:46,816 - pyskl - INFO - Epoch(val) [74][533] top1_acc: 0.8776, top5_acc: 0.9907, mean_class_accuracy: 0.8356 +2025-06-24 23:24:06,306 - pyskl - INFO - Epoch [75][100/1281] lr: 1.274e-02, eta: 11:26:36, time: 0.795, data_time: 0.192, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9988, loss_cls: 0.3782, loss: 0.3782 +2025-06-24 23:24:55,876 - pyskl - INFO - Epoch [75][200/1281] lr: 1.272e-02, eta: 11:26:01, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9988, loss_cls: 0.3472, loss: 0.3472 +2025-06-24 23:25:45,388 - pyskl - INFO - Epoch [75][300/1281] lr: 1.270e-02, eta: 11:25:26, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9988, loss_cls: 0.3474, loss: 0.3474 +2025-06-24 23:26:34,508 - pyskl - INFO - Epoch [75][400/1281] lr: 1.268e-02, eta: 11:24:50, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 1.0000, loss_cls: 0.4047, loss: 0.4047 +2025-06-24 23:27:23,651 - pyskl - INFO - Epoch [75][500/1281] lr: 1.266e-02, eta: 11:24:15, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9975, loss_cls: 0.4348, loss: 0.4348 +2025-06-24 23:28:12,783 - pyskl - INFO - Epoch [75][600/1281] lr: 1.264e-02, eta: 11:23:39, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9981, loss_cls: 0.4375, loss: 0.4375 +2025-06-24 23:29:01,709 - pyskl - INFO - Epoch [75][700/1281] lr: 1.262e-02, eta: 11:23:03, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9988, loss_cls: 0.4316, loss: 0.4316 +2025-06-24 23:29:37,573 - pyskl - INFO - Epoch [75][800/1281] lr: 1.260e-02, eta: 11:22:14, time: 0.359, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9981, loss_cls: 0.4221, loss: 0.4221 +2025-06-24 23:30:28,523 - pyskl - INFO - Epoch [75][900/1281] lr: 1.258e-02, eta: 11:21:40, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9975, loss_cls: 0.3775, loss: 0.3775 +2025-06-24 23:30:52,430 - pyskl - INFO - Epoch [75][1000/1281] lr: 1.256e-02, eta: 11:20:39, time: 0.239, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9944, loss_cls: 0.4566, loss: 0.4566 +2025-06-24 23:31:36,972 - pyskl - INFO - Epoch [75][1100/1281] lr: 1.254e-02, eta: 11:19:59, time: 0.445, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9981, loss_cls: 0.4091, loss: 0.4091 +2025-06-24 23:32:26,494 - pyskl - INFO - Epoch [75][1200/1281] lr: 1.252e-02, eta: 11:19:24, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9975, loss_cls: 0.3592, loss: 0.3592 +2025-06-24 23:33:06,861 - pyskl - INFO - Saving checkpoint at 75 epochs +2025-06-24 23:34:05,752 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:34:05,811 - pyskl - INFO - +top1_acc 0.7935 +top5_acc 0.9824 +2025-06-24 23:34:05,811 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:34:05,819 - pyskl - INFO - +mean_acc 0.7593 +2025-06-24 23:34:05,821 - pyskl - INFO - Epoch(val) [75][533] top1_acc: 0.7935, top5_acc: 0.9824, mean_class_accuracy: 0.7593 +2025-06-24 23:35:26,040 - pyskl - INFO - Epoch [76][100/1281] lr: 1.248e-02, eta: 11:18:11, time: 0.802, data_time: 0.194, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9981, loss_cls: 0.3547, loss: 0.3547 +2025-06-24 23:36:14,574 - pyskl - INFO - Epoch [76][200/1281] lr: 1.246e-02, eta: 11:17:34, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 1.0000, loss_cls: 0.3474, loss: 0.3474 +2025-06-24 23:37:03,593 - pyskl - INFO - Epoch [76][300/1281] lr: 1.244e-02, eta: 11:16:59, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9975, loss_cls: 0.4195, loss: 0.4195 +2025-06-24 23:37:53,019 - pyskl - INFO - Epoch [76][400/1281] lr: 1.242e-02, eta: 11:16:23, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9969, loss_cls: 0.3425, loss: 0.3425 +2025-06-24 23:38:42,439 - pyskl - INFO - Epoch [76][500/1281] lr: 1.240e-02, eta: 11:15:48, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9994, loss_cls: 0.3537, loss: 0.3537 +2025-06-24 23:39:31,742 - pyskl - INFO - Epoch [76][600/1281] lr: 1.238e-02, eta: 11:15:12, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9988, loss_cls: 0.3947, loss: 0.3947 +2025-06-24 23:40:21,093 - pyskl - INFO - Epoch [76][700/1281] lr: 1.236e-02, eta: 11:14:36, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 1.0000, loss_cls: 0.4069, loss: 0.4069 +2025-06-24 23:40:59,287 - pyskl - INFO - Epoch [76][800/1281] lr: 1.234e-02, eta: 11:13:50, time: 0.382, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9969, loss_cls: 0.4217, loss: 0.4217 +2025-06-24 23:41:50,302 - pyskl - INFO - Epoch [76][900/1281] lr: 1.232e-02, eta: 11:13:16, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9988, loss_cls: 0.3755, loss: 0.3755 +2025-06-24 23:42:13,669 - pyskl - INFO - Epoch [76][1000/1281] lr: 1.230e-02, eta: 11:12:15, time: 0.234, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9988, loss_cls: 0.3911, loss: 0.3911 +2025-06-24 23:42:57,677 - pyskl - INFO - Epoch [76][1100/1281] lr: 1.228e-02, eta: 11:11:34, time: 0.440, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9981, loss_cls: 0.3983, loss: 0.3983 +2025-06-24 23:43:46,692 - pyskl - INFO - Epoch [76][1200/1281] lr: 1.225e-02, eta: 11:10:58, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9981, loss_cls: 0.3987, loss: 0.3987 +2025-06-24 23:44:27,341 - pyskl - INFO - Saving checkpoint at 76 epochs +2025-06-24 23:45:25,478 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:45:25,539 - pyskl - INFO - +top1_acc 0.8572 +top5_acc 0.9911 +2025-06-24 23:45:25,539 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:45:25,547 - pyskl - INFO - +mean_acc 0.8244 +2025-06-24 23:45:25,549 - pyskl - INFO - Epoch(val) [76][533] top1_acc: 0.8572, top5_acc: 0.9911, mean_class_accuracy: 0.8244 +2025-06-24 23:46:45,413 - pyskl - INFO - Epoch [77][100/1281] lr: 1.222e-02, eta: 11:09:44, time: 0.799, data_time: 0.188, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9981, loss_cls: 0.3759, loss: 0.3759 +2025-06-24 23:47:34,546 - pyskl - INFO - Epoch [77][200/1281] lr: 1.220e-02, eta: 11:09:08, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9981, loss_cls: 0.3770, loss: 0.3770 +2025-06-24 23:48:23,714 - pyskl - INFO - Epoch [77][300/1281] lr: 1.218e-02, eta: 11:08:32, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 1.0000, loss_cls: 0.3506, loss: 0.3506 +2025-06-24 23:49:12,774 - pyskl - INFO - Epoch [77][400/1281] lr: 1.216e-02, eta: 11:07:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9975, loss_cls: 0.4137, loss: 0.4137 +2025-06-24 23:50:01,870 - pyskl - INFO - Epoch [77][500/1281] lr: 1.214e-02, eta: 11:07:20, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9988, loss_cls: 0.3908, loss: 0.3908 +2025-06-24 23:50:50,581 - pyskl - INFO - Epoch [77][600/1281] lr: 1.212e-02, eta: 11:06:43, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9975, loss_cls: 0.3485, loss: 0.3485 +2025-06-24 23:51:39,682 - pyskl - INFO - Epoch [77][700/1281] lr: 1.210e-02, eta: 11:06:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9956, loss_cls: 0.4217, loss: 0.4217 +2025-06-24 23:52:20,291 - pyskl - INFO - Epoch [77][800/1281] lr: 1.207e-02, eta: 11:05:23, time: 0.406, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9988, loss_cls: 0.4215, loss: 0.4215 +2025-06-24 23:53:10,208 - pyskl - INFO - Epoch [77][900/1281] lr: 1.205e-02, eta: 11:04:48, time: 0.499, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9981, loss_cls: 0.4232, loss: 0.4232 +2025-06-24 23:53:34,132 - pyskl - INFO - Epoch [77][1000/1281] lr: 1.203e-02, eta: 11:03:48, time: 0.239, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9988, loss_cls: 0.3937, loss: 0.3937 +2025-06-24 23:54:17,034 - pyskl - INFO - Epoch [77][1100/1281] lr: 1.201e-02, eta: 11:03:05, time: 0.429, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9969, loss_cls: 0.3997, loss: 0.3997 +2025-06-24 23:55:06,621 - pyskl - INFO - Epoch [77][1200/1281] lr: 1.199e-02, eta: 11:02:30, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9975, loss_cls: 0.4356, loss: 0.4356 +2025-06-24 23:55:46,999 - pyskl - INFO - Saving checkpoint at 77 epochs +2025-06-24 23:56:46,142 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:56:46,210 - pyskl - INFO - +top1_acc 0.8670 +top5_acc 0.9894 +2025-06-24 23:56:46,210 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:56:46,219 - pyskl - INFO - +mean_acc 0.8310 +2025-06-24 23:56:46,222 - pyskl - INFO - Epoch(val) [77][533] top1_acc: 0.8670, top5_acc: 0.9894, mean_class_accuracy: 0.8310 +2025-06-24 23:58:05,994 - pyskl - INFO - Epoch [78][100/1281] lr: 1.196e-02, eta: 11:01:16, time: 0.798, data_time: 0.191, memory: 4083, top1_acc: 0.9356, top5_acc: 1.0000, loss_cls: 0.3704, loss: 0.3704 +2025-06-24 23:58:55,335 - pyskl - INFO - Epoch [78][200/1281] lr: 1.194e-02, eta: 11:00:40, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9981, loss_cls: 0.3770, loss: 0.3770 +2025-06-24 23:59:44,576 - pyskl - INFO - Epoch [78][300/1281] lr: 1.192e-02, eta: 11:00:04, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9988, loss_cls: 0.3651, loss: 0.3651 +2025-06-25 00:00:33,570 - pyskl - INFO - Epoch [78][400/1281] lr: 1.190e-02, eta: 10:59:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9994, loss_cls: 0.3278, loss: 0.3278 +2025-06-25 00:01:22,775 - pyskl - INFO - Epoch [78][500/1281] lr: 1.187e-02, eta: 10:58:51, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9975, loss_cls: 0.3791, loss: 0.3791 +2025-06-25 00:02:12,026 - pyskl - INFO - Epoch [78][600/1281] lr: 1.185e-02, eta: 10:58:15, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9988, loss_cls: 0.3747, loss: 0.3747 +2025-06-25 00:03:01,152 - pyskl - INFO - Epoch [78][700/1281] lr: 1.183e-02, eta: 10:57:38, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9988, loss_cls: 0.3640, loss: 0.3640 +2025-06-25 00:03:41,683 - pyskl - INFO - Epoch [78][800/1281] lr: 1.181e-02, eta: 10:56:54, time: 0.405, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9975, loss_cls: 0.4367, loss: 0.4367 +2025-06-25 00:04:31,964 - pyskl - INFO - Epoch [78][900/1281] lr: 1.179e-02, eta: 10:56:19, time: 0.503, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9969, loss_cls: 0.4080, loss: 0.4080 +2025-06-25 00:04:55,554 - pyskl - INFO - Epoch [78][1000/1281] lr: 1.177e-02, eta: 10:55:19, time: 0.236, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9962, loss_cls: 0.4143, loss: 0.4143 +2025-06-25 00:05:38,160 - pyskl - INFO - Epoch [78][1100/1281] lr: 1.175e-02, eta: 10:54:36, time: 0.426, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9962, loss_cls: 0.4118, loss: 0.4118 +2025-06-25 00:06:27,318 - pyskl - INFO - Epoch [78][1200/1281] lr: 1.173e-02, eta: 10:54:00, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9981, loss_cls: 0.3875, loss: 0.3875 +2025-06-25 00:07:07,541 - pyskl - INFO - Saving checkpoint at 78 epochs +2025-06-25 00:08:06,545 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:08:06,601 - pyskl - INFO - +top1_acc 0.8760 +top5_acc 0.9879 +2025-06-25 00:08:06,601 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:08:06,607 - pyskl - INFO - +mean_acc 0.8448 +2025-06-25 00:08:06,608 - pyskl - INFO - Epoch(val) [78][533] top1_acc: 0.8760, top5_acc: 0.9879, mean_class_accuracy: 0.8448 +2025-06-25 00:09:25,910 - pyskl - INFO - Epoch [79][100/1281] lr: 1.169e-02, eta: 10:52:45, time: 0.793, data_time: 0.194, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9988, loss_cls: 0.3344, loss: 0.3344 +2025-06-25 00:10:14,876 - pyskl - INFO - Epoch [79][200/1281] lr: 1.167e-02, eta: 10:52:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3014, loss: 0.3014 +2025-06-25 00:11:04,075 - pyskl - INFO - Epoch [79][300/1281] lr: 1.165e-02, eta: 10:51:32, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9975, loss_cls: 0.3836, loss: 0.3836 +2025-06-25 00:11:53,188 - pyskl - INFO - Epoch [79][400/1281] lr: 1.163e-02, eta: 10:50:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9981, loss_cls: 0.3291, loss: 0.3291 +2025-06-25 00:12:42,223 - pyskl - INFO - Epoch [79][500/1281] lr: 1.161e-02, eta: 10:50:19, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9975, loss_cls: 0.3634, loss: 0.3634 +2025-06-25 00:13:31,148 - pyskl - INFO - Epoch [79][600/1281] lr: 1.159e-02, eta: 10:49:42, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9994, loss_cls: 0.4013, loss: 0.4013 +2025-06-25 00:14:20,408 - pyskl - INFO - Epoch [79][700/1281] lr: 1.157e-02, eta: 10:49:06, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9994, loss_cls: 0.3688, loss: 0.3688 +2025-06-25 00:15:01,835 - pyskl - INFO - Epoch [79][800/1281] lr: 1.155e-02, eta: 10:48:22, time: 0.414, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 1.0000, loss_cls: 0.3297, loss: 0.3297 +2025-06-25 00:15:49,550 - pyskl - INFO - Epoch [79][900/1281] lr: 1.153e-02, eta: 10:47:45, time: 0.477, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9981, loss_cls: 0.4291, loss: 0.4291 +2025-06-25 00:16:15,908 - pyskl - INFO - Epoch [79][1000/1281] lr: 1.151e-02, eta: 10:46:47, time: 0.264, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9994, loss_cls: 0.3818, loss: 0.3818 +2025-06-25 00:16:59,162 - pyskl - INFO - Epoch [79][1100/1281] lr: 1.149e-02, eta: 10:46:05, time: 0.433, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9981, loss_cls: 0.3656, loss: 0.3656 +2025-06-25 00:17:48,264 - pyskl - INFO - Epoch [79][1200/1281] lr: 1.147e-02, eta: 10:45:29, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9981, loss_cls: 0.3720, loss: 0.3720 +2025-06-25 00:18:28,356 - pyskl - INFO - Saving checkpoint at 79 epochs +2025-06-25 00:19:26,606 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:19:26,661 - pyskl - INFO - +top1_acc 0.8627 +top5_acc 0.9886 +2025-06-25 00:19:26,661 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:19:26,668 - pyskl - INFO - +mean_acc 0.8323 +2025-06-25 00:19:26,670 - pyskl - INFO - Epoch(val) [79][533] top1_acc: 0.8627, top5_acc: 0.9886, mean_class_accuracy: 0.8323 +2025-06-25 00:20:47,222 - pyskl - INFO - Epoch [80][100/1281] lr: 1.143e-02, eta: 10:44:15, time: 0.805, data_time: 0.194, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 0.3845, loss: 0.3845 +2025-06-25 00:21:36,368 - pyskl - INFO - Epoch [80][200/1281] lr: 1.141e-02, eta: 10:43:38, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 1.0000, loss_cls: 0.3586, loss: 0.3586 +2025-06-25 00:22:25,382 - pyskl - INFO - Epoch [80][300/1281] lr: 1.139e-02, eta: 10:43:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9981, loss_cls: 0.3412, loss: 0.3412 +2025-06-25 00:23:14,375 - pyskl - INFO - Epoch [80][400/1281] lr: 1.137e-02, eta: 10:42:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9988, loss_cls: 0.4066, loss: 0.4066 +2025-06-25 00:24:03,522 - pyskl - INFO - Epoch [80][500/1281] lr: 1.135e-02, eta: 10:41:48, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9981, loss_cls: 0.3166, loss: 0.3166 +2025-06-25 00:24:52,734 - pyskl - INFO - Epoch [80][600/1281] lr: 1.133e-02, eta: 10:41:11, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9975, loss_cls: 0.3063, loss: 0.3063 +2025-06-25 00:25:41,859 - pyskl - INFO - Epoch [80][700/1281] lr: 1.131e-02, eta: 10:40:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 0.9994, loss_cls: 0.3008, loss: 0.3008 +2025-06-25 00:26:22,593 - pyskl - INFO - Epoch [80][800/1281] lr: 1.129e-02, eta: 10:39:50, time: 0.407, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9994, loss_cls: 0.3376, loss: 0.3376 +2025-06-25 00:27:11,283 - pyskl - INFO - Epoch [80][900/1281] lr: 1.127e-02, eta: 10:39:13, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9975, loss_cls: 0.4101, loss: 0.4101 +2025-06-25 00:27:36,318 - pyskl - INFO - Epoch [80][1000/1281] lr: 1.125e-02, eta: 10:38:15, time: 0.250, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 1.0000, loss_cls: 0.3197, loss: 0.3197 +2025-06-25 00:28:20,187 - pyskl - INFO - Epoch [80][1100/1281] lr: 1.123e-02, eta: 10:37:34, time: 0.439, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9981, loss_cls: 0.3279, loss: 0.3279 +2025-06-25 00:29:09,499 - pyskl - INFO - Epoch [80][1200/1281] lr: 1.121e-02, eta: 10:36:57, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9975, loss_cls: 0.3846, loss: 0.3846 +2025-06-25 00:29:50,163 - pyskl - INFO - Saving checkpoint at 80 epochs +2025-06-25 00:30:48,575 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:30:48,631 - pyskl - INFO - +top1_acc 0.8774 +top5_acc 0.9900 +2025-06-25 00:30:48,632 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:30:48,639 - pyskl - INFO - +mean_acc 0.8417 +2025-06-25 00:30:48,641 - pyskl - INFO - Epoch(val) [80][533] top1_acc: 0.8774, top5_acc: 0.9900, mean_class_accuracy: 0.8417 +2025-06-25 00:32:09,333 - pyskl - INFO - Epoch [81][100/1281] lr: 1.117e-02, eta: 10:35:43, time: 0.807, data_time: 0.191, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9988, loss_cls: 0.2957, loss: 0.2957 +2025-06-25 00:32:58,526 - pyskl - INFO - Epoch [81][200/1281] lr: 1.115e-02, eta: 10:35:06, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 1.0000, loss_cls: 0.3337, loss: 0.3337 +2025-06-25 00:33:47,275 - pyskl - INFO - Epoch [81][300/1281] lr: 1.113e-02, eta: 10:34:29, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9988, loss_cls: 0.3164, loss: 0.3164 +2025-06-25 00:34:36,143 - pyskl - INFO - Epoch [81][400/1281] lr: 1.111e-02, eta: 10:33:52, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9981, loss_cls: 0.3560, loss: 0.3560 +2025-06-25 00:35:25,149 - pyskl - INFO - Epoch [81][500/1281] lr: 1.109e-02, eta: 10:33:15, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 1.0000, loss_cls: 0.3253, loss: 0.3253 +2025-06-25 00:36:13,966 - pyskl - INFO - Epoch [81][600/1281] lr: 1.107e-02, eta: 10:32:38, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 1.0000, loss_cls: 0.3897, loss: 0.3897 +2025-06-25 00:37:02,863 - pyskl - INFO - Epoch [81][700/1281] lr: 1.105e-02, eta: 10:32:00, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9981, loss_cls: 0.3567, loss: 0.3567 +2025-06-25 00:37:42,481 - pyskl - INFO - Epoch [81][800/1281] lr: 1.103e-02, eta: 10:31:15, time: 0.396, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9975, loss_cls: 0.3746, loss: 0.3746 +2025-06-25 00:38:33,496 - pyskl - INFO - Epoch [81][900/1281] lr: 1.101e-02, eta: 10:30:40, time: 0.510, data_time: 0.001, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9981, loss_cls: 0.3839, loss: 0.3839 +2025-06-25 00:38:57,677 - pyskl - INFO - Epoch [81][1000/1281] lr: 1.099e-02, eta: 10:29:41, time: 0.242, data_time: 0.001, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9981, loss_cls: 0.4216, loss: 0.4216 +2025-06-25 00:39:42,704 - pyskl - INFO - Epoch [81][1100/1281] lr: 1.097e-02, eta: 10:29:01, time: 0.450, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9988, loss_cls: 0.3941, loss: 0.3941 +2025-06-25 00:40:31,615 - pyskl - INFO - Epoch [81][1200/1281] lr: 1.095e-02, eta: 10:28:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9981, loss_cls: 0.3531, loss: 0.3531 +2025-06-25 00:41:11,565 - pyskl - INFO - Saving checkpoint at 81 epochs +2025-06-25 00:42:10,073 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:42:10,151 - pyskl - INFO - +top1_acc 0.8749 +top5_acc 0.9910 +2025-06-25 00:42:10,152 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:42:10,160 - pyskl - INFO - +mean_acc 0.8319 +2025-06-25 00:42:10,163 - pyskl - INFO - Epoch(val) [81][533] top1_acc: 0.8749, top5_acc: 0.9910, mean_class_accuracy: 0.8319 +2025-06-25 00:43:29,255 - pyskl - INFO - Epoch [82][100/1281] lr: 1.091e-02, eta: 10:27:08, time: 0.791, data_time: 0.189, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9981, loss_cls: 0.3509, loss: 0.3509 +2025-06-25 00:44:18,166 - pyskl - INFO - Epoch [82][200/1281] lr: 1.089e-02, eta: 10:26:31, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9994, loss_cls: 0.3593, loss: 0.3593 +2025-06-25 00:45:07,147 - pyskl - INFO - Epoch [82][300/1281] lr: 1.087e-02, eta: 10:25:53, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9975, loss_cls: 0.3840, loss: 0.3840 +2025-06-25 00:45:56,343 - pyskl - INFO - Epoch [82][400/1281] lr: 1.085e-02, eta: 10:25:16, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 0.3141, loss: 0.3141 +2025-06-25 00:46:45,652 - pyskl - INFO - Epoch [82][500/1281] lr: 1.083e-02, eta: 10:24:39, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9988, loss_cls: 0.2967, loss: 0.2967 +2025-06-25 00:47:34,618 - pyskl - INFO - Epoch [82][600/1281] lr: 1.081e-02, eta: 10:24:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9994, loss_cls: 0.3521, loss: 0.3521 +2025-06-25 00:48:23,542 - pyskl - INFO - Epoch [82][700/1281] lr: 1.079e-02, eta: 10:23:25, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9975, loss_cls: 0.3293, loss: 0.3293 +2025-06-25 00:49:02,721 - pyskl - INFO - Epoch [82][800/1281] lr: 1.077e-02, eta: 10:22:39, time: 0.392, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9988, loss_cls: 0.3590, loss: 0.3590 +2025-06-25 00:49:53,683 - pyskl - INFO - Epoch [82][900/1281] lr: 1.075e-02, eta: 10:22:03, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9988, loss_cls: 0.3531, loss: 0.3531 +2025-06-25 00:50:16,712 - pyskl - INFO - Epoch [82][1000/1281] lr: 1.073e-02, eta: 10:21:04, time: 0.230, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9994, loss_cls: 0.3543, loss: 0.3543 +2025-06-25 00:51:01,006 - pyskl - INFO - Epoch [82][1100/1281] lr: 1.071e-02, eta: 10:20:23, time: 0.443, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9988, loss_cls: 0.4042, loss: 0.4042 +2025-06-25 00:51:49,959 - pyskl - INFO - Epoch [82][1200/1281] lr: 1.069e-02, eta: 10:19:46, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 1.0000, loss_cls: 0.3774, loss: 0.3774 +2025-06-25 00:52:29,920 - pyskl - INFO - Saving checkpoint at 82 epochs +2025-06-25 00:53:28,283 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:53:28,338 - pyskl - INFO - +top1_acc 0.8708 +top5_acc 0.9885 +2025-06-25 00:53:28,339 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:53:28,346 - pyskl - INFO - +mean_acc 0.8236 +2025-06-25 00:53:28,348 - pyskl - INFO - Epoch(val) [82][533] top1_acc: 0.8708, top5_acc: 0.9885, mean_class_accuracy: 0.8236 +2025-06-25 00:54:48,231 - pyskl - INFO - Epoch [83][100/1281] lr: 1.065e-02, eta: 10:18:31, time: 0.799, data_time: 0.186, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9975, loss_cls: 0.3693, loss: 0.3693 +2025-06-25 00:55:37,520 - pyskl - INFO - Epoch [83][200/1281] lr: 1.063e-02, eta: 10:17:54, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9988, loss_cls: 0.3233, loss: 0.3233 +2025-06-25 00:56:26,874 - pyskl - INFO - Epoch [83][300/1281] lr: 1.061e-02, eta: 10:17:16, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9988, loss_cls: 0.3242, loss: 0.3242 +2025-06-25 00:57:15,994 - pyskl - INFO - Epoch [83][400/1281] lr: 1.059e-02, eta: 10:16:39, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9994, loss_cls: 0.3705, loss: 0.3705 +2025-06-25 00:58:05,511 - pyskl - INFO - Epoch [83][500/1281] lr: 1.057e-02, eta: 10:16:02, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9981, loss_cls: 0.3407, loss: 0.3407 +2025-06-25 00:58:54,661 - pyskl - INFO - Epoch [83][600/1281] lr: 1.055e-02, eta: 10:15:25, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9994, loss_cls: 0.3259, loss: 0.3259 +2025-06-25 00:59:43,723 - pyskl - INFO - Epoch [83][700/1281] lr: 1.053e-02, eta: 10:14:47, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9975, loss_cls: 0.3375, loss: 0.3375 +2025-06-25 01:00:23,790 - pyskl - INFO - Epoch [83][800/1281] lr: 1.051e-02, eta: 10:14:02, time: 0.401, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9994, loss_cls: 0.3255, loss: 0.3255 +2025-06-25 01:01:14,743 - pyskl - INFO - Epoch [83][900/1281] lr: 1.049e-02, eta: 10:13:26, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9969, loss_cls: 0.3318, loss: 0.3318 +2025-06-25 01:01:37,992 - pyskl - INFO - Epoch [83][1000/1281] lr: 1.047e-02, eta: 10:12:28, time: 0.232, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9988, loss_cls: 0.3880, loss: 0.3880 +2025-06-25 01:02:21,942 - pyskl - INFO - Epoch [83][1100/1281] lr: 1.045e-02, eta: 10:11:46, time: 0.439, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9994, loss_cls: 0.3959, loss: 0.3959 +2025-06-25 01:03:10,786 - pyskl - INFO - Epoch [83][1200/1281] lr: 1.043e-02, eta: 10:11:09, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9994, loss_cls: 0.3851, loss: 0.3851 +2025-06-25 01:03:50,792 - pyskl - INFO - Saving checkpoint at 83 epochs +2025-06-25 01:04:49,602 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:04:49,658 - pyskl - INFO - +top1_acc 0.8743 +top5_acc 0.9896 +2025-06-25 01:04:49,658 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:04:49,666 - pyskl - INFO - +mean_acc 0.8454 +2025-06-25 01:04:49,668 - pyskl - INFO - Epoch(val) [83][533] top1_acc: 0.8743, top5_acc: 0.9896, mean_class_accuracy: 0.8454 +2025-06-25 01:06:10,925 - pyskl - INFO - Epoch [84][100/1281] lr: 1.040e-02, eta: 10:09:54, time: 0.812, data_time: 0.190, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.2876, loss: 0.2876 +2025-06-25 01:06:59,699 - pyskl - INFO - Epoch [84][200/1281] lr: 1.038e-02, eta: 10:09:17, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 0.2773, loss: 0.2773 +2025-06-25 01:07:48,351 - pyskl - INFO - Epoch [84][300/1281] lr: 1.036e-02, eta: 10:08:39, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9994, loss_cls: 0.2613, loss: 0.2613 +2025-06-25 01:08:37,121 - pyskl - INFO - Epoch [84][400/1281] lr: 1.034e-02, eta: 10:08:01, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9988, loss_cls: 0.2957, loss: 0.2957 +2025-06-25 01:09:25,960 - pyskl - INFO - Epoch [84][500/1281] lr: 1.031e-02, eta: 10:07:23, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 0.2905, loss: 0.2905 +2025-06-25 01:10:14,754 - pyskl - INFO - Epoch [84][600/1281] lr: 1.029e-02, eta: 10:06:45, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9988, loss_cls: 0.2908, loss: 0.2908 +2025-06-25 01:11:03,592 - pyskl - INFO - Epoch [84][700/1281] lr: 1.027e-02, eta: 10:06:07, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9988, loss_cls: 0.3264, loss: 0.3264 +2025-06-25 01:11:41,374 - pyskl - INFO - Epoch [84][800/1281] lr: 1.025e-02, eta: 10:05:21, time: 0.378, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9988, loss_cls: 0.3214, loss: 0.3214 +2025-06-25 01:12:32,308 - pyskl - INFO - Epoch [84][900/1281] lr: 1.023e-02, eta: 10:04:45, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9981, loss_cls: 0.3405, loss: 0.3405 +2025-06-25 01:12:56,714 - pyskl - INFO - Epoch [84][1000/1281] lr: 1.021e-02, eta: 10:03:47, time: 0.244, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9994, loss_cls: 0.3625, loss: 0.3625 +2025-06-25 01:13:42,417 - pyskl - INFO - Epoch [84][1100/1281] lr: 1.019e-02, eta: 10:03:07, time: 0.457, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9981, loss_cls: 0.3167, loss: 0.3167 +2025-06-25 01:14:31,403 - pyskl - INFO - Epoch [84][1200/1281] lr: 1.017e-02, eta: 10:02:29, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9981, loss_cls: 0.3434, loss: 0.3434 +2025-06-25 01:15:11,645 - pyskl - INFO - Saving checkpoint at 84 epochs +2025-06-25 01:16:10,143 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:16:10,210 - pyskl - INFO - +top1_acc 0.8825 +top5_acc 0.9908 +2025-06-25 01:16:10,210 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:16:10,218 - pyskl - INFO - +mean_acc 0.8418 +2025-06-25 01:16:10,223 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_65.pth was removed +2025-06-25 01:16:10,418 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_84.pth. +2025-06-25 01:16:10,418 - pyskl - INFO - Best top1_acc is 0.8825 at 84 epoch. +2025-06-25 01:16:10,421 - pyskl - INFO - Epoch(val) [84][533] top1_acc: 0.8825, top5_acc: 0.9908, mean_class_accuracy: 0.8418 +2025-06-25 01:17:30,612 - pyskl - INFO - Epoch [85][100/1281] lr: 1.014e-02, eta: 10:01:14, time: 0.802, data_time: 0.185, memory: 4083, top1_acc: 0.9425, top5_acc: 1.0000, loss_cls: 0.3137, loss: 0.3137 +2025-06-25 01:18:19,193 - pyskl - INFO - Epoch [85][200/1281] lr: 1.012e-02, eta: 10:00:36, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 1.0000, loss_cls: 0.3064, loss: 0.3064 +2025-06-25 01:19:08,018 - pyskl - INFO - Epoch [85][300/1281] lr: 1.010e-02, eta: 9:59:58, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9981, loss_cls: 0.3014, loss: 0.3014 +2025-06-25 01:19:57,341 - pyskl - INFO - Epoch [85][400/1281] lr: 1.008e-02, eta: 9:59:20, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.2827, loss: 0.2827 +2025-06-25 01:20:46,682 - pyskl - INFO - Epoch [85][500/1281] lr: 1.006e-02, eta: 9:58:43, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9975, loss_cls: 0.3351, loss: 0.3351 +2025-06-25 01:21:35,701 - pyskl - INFO - Epoch [85][600/1281] lr: 1.004e-02, eta: 9:58:05, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 1.0000, loss_cls: 0.3302, loss: 0.3302 +2025-06-25 01:22:24,356 - pyskl - INFO - Epoch [85][700/1281] lr: 1.002e-02, eta: 9:57:27, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9994, loss_cls: 0.3104, loss: 0.3104 +2025-06-25 01:23:01,230 - pyskl - INFO - Epoch [85][800/1281] lr: 9.998e-03, eta: 9:56:40, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9994, loss_cls: 0.3282, loss: 0.3282 +2025-06-25 01:23:52,114 - pyskl - INFO - Epoch [85][900/1281] lr: 9.978e-03, eta: 9:56:03, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 1.0000, loss_cls: 0.2785, loss: 0.2785 +2025-06-25 01:24:16,719 - pyskl - INFO - Epoch [85][1000/1281] lr: 9.958e-03, eta: 9:55:06, time: 0.246, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9981, loss_cls: 0.3058, loss: 0.3058 +2025-06-25 01:25:03,313 - pyskl - INFO - Epoch [85][1100/1281] lr: 9.937e-03, eta: 9:54:27, time: 0.466, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9981, loss_cls: 0.3691, loss: 0.3691 +2025-06-25 01:25:52,127 - pyskl - INFO - Epoch [85][1200/1281] lr: 9.917e-03, eta: 9:53:48, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9975, loss_cls: 0.4000, loss: 0.4000 +2025-06-25 01:26:31,702 - pyskl - INFO - Saving checkpoint at 85 epochs +2025-06-25 01:27:29,608 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:27:29,676 - pyskl - INFO - +top1_acc 0.8742 +top5_acc 0.9901 +2025-06-25 01:27:29,676 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:27:29,685 - pyskl - INFO - +mean_acc 0.8304 +2025-06-25 01:27:29,687 - pyskl - INFO - Epoch(val) [85][533] top1_acc: 0.8742, top5_acc: 0.9901, mean_class_accuracy: 0.8304 +2025-06-25 01:28:49,862 - pyskl - INFO - Epoch [86][100/1281] lr: 9.881e-03, eta: 9:52:33, time: 0.802, data_time: 0.189, memory: 4083, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 0.2886, loss: 0.2886 +2025-06-25 01:29:38,520 - pyskl - INFO - Epoch [86][200/1281] lr: 9.861e-03, eta: 9:51:55, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 1.0000, loss_cls: 0.3104, loss: 0.3104 +2025-06-25 01:30:27,155 - pyskl - INFO - Epoch [86][300/1281] lr: 9.841e-03, eta: 9:51:17, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9994, loss_cls: 0.3154, loss: 0.3154 +2025-06-25 01:31:16,109 - pyskl - INFO - Epoch [86][400/1281] lr: 9.821e-03, eta: 9:50:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9994, loss_cls: 0.2719, loss: 0.2719 +2025-06-25 01:32:04,774 - pyskl - INFO - Epoch [86][500/1281] lr: 9.801e-03, eta: 9:50:00, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9981, loss_cls: 0.3269, loss: 0.3269 +2025-06-25 01:32:53,950 - pyskl - INFO - Epoch [86][600/1281] lr: 9.781e-03, eta: 9:49:22, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9994, loss_cls: 0.3460, loss: 0.3460 +2025-06-25 01:33:42,777 - pyskl - INFO - Epoch [86][700/1281] lr: 9.762e-03, eta: 9:48:44, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9994, loss_cls: 0.3611, loss: 0.3611 +2025-06-25 01:34:18,679 - pyskl - INFO - Epoch [86][800/1281] lr: 9.742e-03, eta: 9:47:56, time: 0.359, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.2916, loss: 0.2916 +2025-06-25 01:35:09,691 - pyskl - INFO - Epoch [86][900/1281] lr: 9.722e-03, eta: 9:47:20, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9975, loss_cls: 0.3583, loss: 0.3583 +2025-06-25 01:35:34,219 - pyskl - INFO - Epoch [86][1000/1281] lr: 9.702e-03, eta: 9:46:23, time: 0.245, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9994, loss_cls: 0.3636, loss: 0.3636 +2025-06-25 01:36:20,459 - pyskl - INFO - Epoch [86][1100/1281] lr: 9.682e-03, eta: 9:45:43, time: 0.462, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9981, loss_cls: 0.3805, loss: 0.3805 +2025-06-25 01:37:09,616 - pyskl - INFO - Epoch [86][1200/1281] lr: 9.662e-03, eta: 9:45:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9988, loss_cls: 0.3581, loss: 0.3581 +2025-06-25 01:37:49,481 - pyskl - INFO - Saving checkpoint at 86 epochs +2025-06-25 01:38:47,936 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:38:47,991 - pyskl - INFO - +top1_acc 0.8770 +top5_acc 0.9911 +2025-06-25 01:38:47,991 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:38:47,998 - pyskl - INFO - +mean_acc 0.8318 +2025-06-25 01:38:48,000 - pyskl - INFO - Epoch(val) [86][533] top1_acc: 0.8770, top5_acc: 0.9911, mean_class_accuracy: 0.8318 +2025-06-25 01:40:08,580 - pyskl - INFO - Epoch [87][100/1281] lr: 9.626e-03, eta: 9:43:50, time: 0.806, data_time: 0.188, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9981, loss_cls: 0.3256, loss: 0.3256 +2025-06-25 01:40:57,210 - pyskl - INFO - Epoch [87][200/1281] lr: 9.606e-03, eta: 9:43:11, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2279, loss: 0.2279 +2025-06-25 01:41:46,203 - pyskl - INFO - Epoch [87][300/1281] lr: 9.586e-03, eta: 9:42:33, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.2781, loss: 0.2781 +2025-06-25 01:42:35,314 - pyskl - INFO - Epoch [87][400/1281] lr: 9.566e-03, eta: 9:41:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 0.9994, loss_cls: 0.2491, loss: 0.2491 +2025-06-25 01:43:24,844 - pyskl - INFO - Epoch [87][500/1281] lr: 9.546e-03, eta: 9:41:17, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2432, loss: 0.2432 +2025-06-25 01:44:13,632 - pyskl - INFO - Epoch [87][600/1281] lr: 9.527e-03, eta: 9:40:39, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9988, loss_cls: 0.2706, loss: 0.2706 +2025-06-25 01:45:02,543 - pyskl - INFO - Epoch [87][700/1281] lr: 9.507e-03, eta: 9:40:00, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9969, loss_cls: 0.3032, loss: 0.3032 +2025-06-25 01:45:38,926 - pyskl - INFO - Epoch [87][800/1281] lr: 9.487e-03, eta: 9:39:13, time: 0.364, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 0.2982, loss: 0.2982 +2025-06-25 01:46:30,060 - pyskl - INFO - Epoch [87][900/1281] lr: 9.467e-03, eta: 9:38:36, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9994, loss_cls: 0.2745, loss: 0.2745 +2025-06-25 01:46:55,001 - pyskl - INFO - Epoch [87][1000/1281] lr: 9.447e-03, eta: 9:37:40, time: 0.249, data_time: 0.001, memory: 4083, top1_acc: 0.9481, top5_acc: 1.0000, loss_cls: 0.3172, loss: 0.3172 +2025-06-25 01:47:42,303 - pyskl - INFO - Epoch [87][1100/1281] lr: 9.427e-03, eta: 9:37:01, time: 0.473, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3132, loss: 0.3132 +2025-06-25 01:48:31,002 - pyskl - INFO - Epoch [87][1200/1281] lr: 9.408e-03, eta: 9:36:22, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 1.0000, loss_cls: 0.3754, loss: 0.3754 +2025-06-25 01:49:11,095 - pyskl - INFO - Saving checkpoint at 87 epochs +2025-06-25 01:50:09,459 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:50:09,527 - pyskl - INFO - +top1_acc 0.8865 +top5_acc 0.9925 +2025-06-25 01:50:09,528 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:50:09,535 - pyskl - INFO - +mean_acc 0.8514 +2025-06-25 01:50:09,540 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_84.pth was removed +2025-06-25 01:50:09,735 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_87.pth. +2025-06-25 01:50:09,736 - pyskl - INFO - Best top1_acc is 0.8865 at 87 epoch. +2025-06-25 01:50:09,738 - pyskl - INFO - Epoch(val) [87][533] top1_acc: 0.8865, top5_acc: 0.9925, mean_class_accuracy: 0.8514 +2025-06-25 01:51:30,326 - pyskl - INFO - Epoch [88][100/1281] lr: 9.372e-03, eta: 9:35:07, time: 0.806, data_time: 0.188, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 0.2978, loss: 0.2978 +2025-06-25 01:52:19,023 - pyskl - INFO - Epoch [88][200/1281] lr: 9.352e-03, eta: 9:34:29, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 0.2571, loss: 0.2571 +2025-06-25 01:53:08,182 - pyskl - INFO - Epoch [88][300/1281] lr: 9.332e-03, eta: 9:33:50, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 0.9988, loss_cls: 0.2398, loss: 0.2398 +2025-06-25 01:53:57,192 - pyskl - INFO - Epoch [88][400/1281] lr: 9.312e-03, eta: 9:33:12, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9994, loss_cls: 0.2751, loss: 0.2751 +2025-06-25 01:54:46,591 - pyskl - INFO - Epoch [88][500/1281] lr: 9.293e-03, eta: 9:32:34, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9994, loss_cls: 0.2934, loss: 0.2934 +2025-06-25 01:55:35,379 - pyskl - INFO - Epoch [88][600/1281] lr: 9.273e-03, eta: 9:31:55, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9981, loss_cls: 0.2883, loss: 0.2883 +2025-06-25 01:56:24,115 - pyskl - INFO - Epoch [88][700/1281] lr: 9.253e-03, eta: 9:31:17, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 0.2987, loss: 0.2987 +2025-06-25 01:56:58,270 - pyskl - INFO - Epoch [88][800/1281] lr: 9.233e-03, eta: 9:30:28, time: 0.342, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 1.0000, loss_cls: 0.3022, loss: 0.3022 +2025-06-25 01:57:49,229 - pyskl - INFO - Epoch [88][900/1281] lr: 9.214e-03, eta: 9:29:50, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2585, loss: 0.2585 +2025-06-25 01:58:14,187 - pyskl - INFO - Epoch [88][1000/1281] lr: 9.194e-03, eta: 9:28:55, time: 0.250, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9994, loss_cls: 0.3464, loss: 0.3464 +2025-06-25 01:59:01,797 - pyskl - INFO - Epoch [88][1100/1281] lr: 9.174e-03, eta: 9:28:15, time: 0.476, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9969, loss_cls: 0.3668, loss: 0.3668 +2025-06-25 01:59:50,986 - pyskl - INFO - Epoch [88][1200/1281] lr: 9.155e-03, eta: 9:27:37, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9994, loss_cls: 0.3070, loss: 0.3070 +2025-06-25 02:00:31,162 - pyskl - INFO - Saving checkpoint at 88 epochs +2025-06-25 02:01:29,290 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:01:29,357 - pyskl - INFO - +top1_acc 0.8790 +top5_acc 0.9887 +2025-06-25 02:01:29,358 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:01:29,366 - pyskl - INFO - +mean_acc 0.8449 +2025-06-25 02:01:29,368 - pyskl - INFO - Epoch(val) [88][533] top1_acc: 0.8790, top5_acc: 0.9887, mean_class_accuracy: 0.8449 +2025-06-25 02:02:50,183 - pyskl - INFO - Epoch [89][100/1281] lr: 9.119e-03, eta: 9:26:22, time: 0.808, data_time: 0.185, memory: 4083, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 0.2486, loss: 0.2486 +2025-06-25 02:03:39,040 - pyskl - INFO - Epoch [89][200/1281] lr: 9.099e-03, eta: 9:25:43, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 0.2666, loss: 0.2666 +2025-06-25 02:04:28,049 - pyskl - INFO - Epoch [89][300/1281] lr: 9.080e-03, eta: 9:25:05, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2557, loss: 0.2557 +2025-06-25 02:05:17,109 - pyskl - INFO - Epoch [89][400/1281] lr: 9.060e-03, eta: 9:24:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 0.3162, loss: 0.3162 +2025-06-25 02:06:06,561 - pyskl - INFO - Epoch [89][500/1281] lr: 9.040e-03, eta: 9:23:48, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.2891, loss: 0.2891 +2025-06-25 02:06:55,419 - pyskl - INFO - Epoch [89][600/1281] lr: 9.021e-03, eta: 9:23:09, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 0.2926, loss: 0.2926 +2025-06-25 02:07:44,592 - pyskl - INFO - Epoch [89][700/1281] lr: 9.001e-03, eta: 9:22:31, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 0.9981, loss_cls: 0.2914, loss: 0.2914 +2025-06-25 02:08:18,068 - pyskl - INFO - Epoch [89][800/1281] lr: 8.982e-03, eta: 9:21:41, time: 0.335, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9981, loss_cls: 0.2864, loss: 0.2864 +2025-06-25 02:09:08,809 - pyskl - INFO - Epoch [89][900/1281] lr: 8.962e-03, eta: 9:21:04, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 1.0000, loss_cls: 0.2999, loss: 0.2999 +2025-06-25 02:09:33,873 - pyskl - INFO - Epoch [89][1000/1281] lr: 8.942e-03, eta: 9:20:09, time: 0.251, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 0.2679, loss: 0.2679 +2025-06-25 02:10:22,381 - pyskl - INFO - Epoch [89][1100/1281] lr: 8.923e-03, eta: 9:19:30, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9994, loss_cls: 0.3080, loss: 0.3080 +2025-06-25 02:11:11,238 - pyskl - INFO - Epoch [89][1200/1281] lr: 8.903e-03, eta: 9:18:51, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9988, loss_cls: 0.2572, loss: 0.2572 +2025-06-25 02:11:51,498 - pyskl - INFO - Saving checkpoint at 89 epochs +2025-06-25 02:12:49,177 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:12:49,233 - pyskl - INFO - +top1_acc 0.8799 +top5_acc 0.9890 +2025-06-25 02:12:49,233 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:12:49,240 - pyskl - INFO - +mean_acc 0.8400 +2025-06-25 02:12:49,242 - pyskl - INFO - Epoch(val) [89][533] top1_acc: 0.8799, top5_acc: 0.9890, mean_class_accuracy: 0.8400 +2025-06-25 02:14:08,559 - pyskl - INFO - Epoch [90][100/1281] lr: 8.868e-03, eta: 9:17:35, time: 0.793, data_time: 0.185, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 0.2992, loss: 0.2992 +2025-06-25 02:14:57,676 - pyskl - INFO - Epoch [90][200/1281] lr: 8.848e-03, eta: 9:16:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 0.2840, loss: 0.2840 +2025-06-25 02:15:46,623 - pyskl - INFO - Epoch [90][300/1281] lr: 8.829e-03, eta: 9:16:17, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9994, loss_cls: 0.2651, loss: 0.2651 +2025-06-25 02:16:35,657 - pyskl - INFO - Epoch [90][400/1281] lr: 8.809e-03, eta: 9:15:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 0.9994, loss_cls: 0.2396, loss: 0.2396 +2025-06-25 02:17:24,497 - pyskl - INFO - Epoch [90][500/1281] lr: 8.790e-03, eta: 9:15:00, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 0.9994, loss_cls: 0.2102, loss: 0.2102 +2025-06-25 02:18:13,280 - pyskl - INFO - Epoch [90][600/1281] lr: 8.770e-03, eta: 9:14:21, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2426, loss: 0.2426 +2025-06-25 02:19:02,279 - pyskl - INFO - Epoch [90][700/1281] lr: 8.751e-03, eta: 9:13:42, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 1.0000, loss_cls: 0.3182, loss: 0.3182 +2025-06-25 02:19:36,112 - pyskl - INFO - Epoch [90][800/1281] lr: 8.731e-03, eta: 9:12:53, time: 0.338, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9981, loss_cls: 0.2894, loss: 0.2894 +2025-06-25 02:20:26,922 - pyskl - INFO - Epoch [90][900/1281] lr: 8.712e-03, eta: 9:12:16, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9981, loss_cls: 0.2795, loss: 0.2795 +2025-06-25 02:20:52,980 - pyskl - INFO - Epoch [90][1000/1281] lr: 8.692e-03, eta: 9:11:21, time: 0.261, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 0.3180, loss: 0.3180 +2025-06-25 02:21:41,383 - pyskl - INFO - Epoch [90][1100/1281] lr: 8.673e-03, eta: 9:10:42, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9988, loss_cls: 0.3868, loss: 0.3868 +2025-06-25 02:22:30,161 - pyskl - INFO - Epoch [90][1200/1281] lr: 8.653e-03, eta: 9:10:03, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9994, loss_cls: 0.3010, loss: 0.3010 +2025-06-25 02:23:10,036 - pyskl - INFO - Saving checkpoint at 90 epochs +2025-06-25 02:24:08,269 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:24:08,324 - pyskl - INFO - +top1_acc 0.8802 +top5_acc 0.9897 +2025-06-25 02:24:08,324 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:24:08,331 - pyskl - INFO - +mean_acc 0.8612 +2025-06-25 02:24:08,333 - pyskl - INFO - Epoch(val) [90][533] top1_acc: 0.8802, top5_acc: 0.9897, mean_class_accuracy: 0.8612 +2025-06-25 02:25:27,686 - pyskl - INFO - Epoch [91][100/1281] lr: 8.618e-03, eta: 9:08:47, time: 0.793, data_time: 0.190, memory: 4083, top1_acc: 0.9469, top5_acc: 1.0000, loss_cls: 0.2884, loss: 0.2884 +2025-06-25 02:26:16,857 - pyskl - INFO - Epoch [91][200/1281] lr: 8.599e-03, eta: 9:08:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 0.3051, loss: 0.3051 +2025-06-25 02:27:05,582 - pyskl - INFO - Epoch [91][300/1281] lr: 8.579e-03, eta: 9:07:29, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 0.2551, loss: 0.2551 +2025-06-25 02:27:54,237 - pyskl - INFO - Epoch [91][400/1281] lr: 8.560e-03, eta: 9:06:50, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9975, loss_cls: 0.2839, loss: 0.2839 +2025-06-25 02:28:42,996 - pyskl - INFO - Epoch [91][500/1281] lr: 8.540e-03, eta: 9:06:11, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 0.2838, loss: 0.2838 +2025-06-25 02:29:32,009 - pyskl - INFO - Epoch [91][600/1281] lr: 8.521e-03, eta: 9:05:32, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9988, loss_cls: 0.3169, loss: 0.3169 +2025-06-25 02:30:20,895 - pyskl - INFO - Epoch [91][700/1281] lr: 8.502e-03, eta: 9:04:53, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2434, loss: 0.2434 +2025-06-25 02:30:52,660 - pyskl - INFO - Epoch [91][800/1281] lr: 8.482e-03, eta: 9:04:03, time: 0.318, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2368, loss: 0.2368 +2025-06-25 02:31:43,787 - pyskl - INFO - Epoch [91][900/1281] lr: 8.463e-03, eta: 9:03:25, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9988, loss_cls: 0.2891, loss: 0.2891 +2025-06-25 02:32:13,054 - pyskl - INFO - Epoch [91][1000/1281] lr: 8.444e-03, eta: 9:02:33, time: 0.293, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 0.2784, loss: 0.2784 +2025-06-25 02:33:01,973 - pyskl - INFO - Epoch [91][1100/1281] lr: 8.424e-03, eta: 9:01:54, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.2845, loss: 0.2845 +2025-06-25 02:33:51,314 - pyskl - INFO - Epoch [91][1200/1281] lr: 8.405e-03, eta: 9:01:15, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 1.0000, loss_cls: 0.3289, loss: 0.3289 +2025-06-25 02:34:31,239 - pyskl - INFO - Saving checkpoint at 91 epochs +2025-06-25 02:35:29,524 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:35:29,592 - pyskl - INFO - +top1_acc 0.8748 +top5_acc 0.9876 +2025-06-25 02:35:29,593 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:35:29,600 - pyskl - INFO - +mean_acc 0.8431 +2025-06-25 02:35:29,602 - pyskl - INFO - Epoch(val) [91][533] top1_acc: 0.8748, top5_acc: 0.9876, mean_class_accuracy: 0.8431 +2025-06-25 02:36:50,294 - pyskl - INFO - Epoch [92][100/1281] lr: 8.370e-03, eta: 9:00:00, time: 0.807, data_time: 0.190, memory: 4083, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 0.2573, loss: 0.2573 +2025-06-25 02:37:39,149 - pyskl - INFO - Epoch [92][200/1281] lr: 8.351e-03, eta: 8:59:21, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 0.9994, loss_cls: 0.2257, loss: 0.2257 +2025-06-25 02:38:28,105 - pyskl - INFO - Epoch [92][300/1281] lr: 8.332e-03, eta: 8:58:42, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 0.2668, loss: 0.2668 +2025-06-25 02:39:16,717 - pyskl - INFO - Epoch [92][400/1281] lr: 8.312e-03, eta: 8:58:02, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9988, loss_cls: 0.2983, loss: 0.2983 +2025-06-25 02:40:05,478 - pyskl - INFO - Epoch [92][500/1281] lr: 8.293e-03, eta: 8:57:23, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 0.2222, loss: 0.2222 +2025-06-25 02:40:54,305 - pyskl - INFO - Epoch [92][600/1281] lr: 8.274e-03, eta: 8:56:44, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2556, loss: 0.2556 +2025-06-25 02:41:43,615 - pyskl - INFO - Epoch [92][700/1281] lr: 8.255e-03, eta: 8:56:05, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.2890, loss: 0.2890 +2025-06-25 02:42:11,156 - pyskl - INFO - Epoch [92][800/1281] lr: 8.235e-03, eta: 8:55:12, time: 0.275, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9994, loss_cls: 0.2802, loss: 0.2802 +2025-06-25 02:43:01,819 - pyskl - INFO - Epoch [92][900/1281] lr: 8.216e-03, eta: 8:54:34, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 0.2748, loss: 0.2748 +2025-06-25 02:43:34,295 - pyskl - INFO - Epoch [92][1000/1281] lr: 8.197e-03, eta: 8:53:45, time: 0.325, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2386, loss: 0.2386 +2025-06-25 02:44:23,455 - pyskl - INFO - Epoch [92][1100/1281] lr: 8.178e-03, eta: 8:53:06, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 0.2583, loss: 0.2583 +2025-06-25 02:45:12,648 - pyskl - INFO - Epoch [92][1200/1281] lr: 8.159e-03, eta: 8:52:27, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2156, loss: 0.2156 +2025-06-25 02:45:53,064 - pyskl - INFO - Saving checkpoint at 92 epochs +2025-06-25 02:46:51,756 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:46:51,812 - pyskl - INFO - +top1_acc 0.8863 +top5_acc 0.9911 +2025-06-25 02:46:51,812 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:46:51,818 - pyskl - INFO - +mean_acc 0.8531 +2025-06-25 02:46:51,820 - pyskl - INFO - Epoch(val) [92][533] top1_acc: 0.8863, top5_acc: 0.9911, mean_class_accuracy: 0.8531 +2025-06-25 02:48:11,707 - pyskl - INFO - Epoch [93][100/1281] lr: 8.124e-03, eta: 8:51:10, time: 0.799, data_time: 0.189, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9994, loss_cls: 0.2733, loss: 0.2733 +2025-06-25 02:49:00,439 - pyskl - INFO - Epoch [93][200/1281] lr: 8.105e-03, eta: 8:50:31, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.2080, loss: 0.2080 +2025-06-25 02:49:49,324 - pyskl - INFO - Epoch [93][300/1281] lr: 8.086e-03, eta: 8:49:52, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9994, loss_cls: 0.2782, loss: 0.2782 +2025-06-25 02:50:38,280 - pyskl - INFO - Epoch [93][400/1281] lr: 8.067e-03, eta: 8:49:12, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 0.2787, loss: 0.2787 +2025-06-25 02:51:26,962 - pyskl - INFO - Epoch [93][500/1281] lr: 8.047e-03, eta: 8:48:33, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 0.9994, loss_cls: 0.2363, loss: 0.2363 +2025-06-25 02:52:15,905 - pyskl - INFO - Epoch [93][600/1281] lr: 8.028e-03, eta: 8:47:54, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 0.9988, loss_cls: 0.2448, loss: 0.2448 +2025-06-25 02:53:04,552 - pyskl - INFO - Epoch [93][700/1281] lr: 8.009e-03, eta: 8:47:14, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9994, loss_cls: 0.2562, loss: 0.2562 +2025-06-25 02:53:33,556 - pyskl - INFO - Epoch [93][800/1281] lr: 7.990e-03, eta: 8:46:23, time: 0.290, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2470, loss: 0.2470 +2025-06-25 02:54:20,660 - pyskl - INFO - Epoch [93][900/1281] lr: 7.971e-03, eta: 8:45:42, time: 0.471, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.2708, loss: 0.2708 +2025-06-25 02:54:53,896 - pyskl - INFO - Epoch [93][1000/1281] lr: 7.952e-03, eta: 8:44:53, time: 0.332, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 0.2675, loss: 0.2675 +2025-06-25 02:55:42,726 - pyskl - INFO - Epoch [93][1100/1281] lr: 7.933e-03, eta: 8:44:14, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9994, loss_cls: 0.2665, loss: 0.2665 +2025-06-25 02:56:31,506 - pyskl - INFO - Epoch [93][1200/1281] lr: 7.914e-03, eta: 8:43:34, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.2673, loss: 0.2673 +2025-06-25 02:57:11,472 - pyskl - INFO - Saving checkpoint at 93 epochs +2025-06-25 02:58:10,356 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:58:10,412 - pyskl - INFO - +top1_acc 0.8857 +top5_acc 0.9923 +2025-06-25 02:58:10,412 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:58:10,419 - pyskl - INFO - +mean_acc 0.8609 +2025-06-25 02:58:10,421 - pyskl - INFO - Epoch(val) [93][533] top1_acc: 0.8857, top5_acc: 0.9923, mean_class_accuracy: 0.8609 +2025-06-25 02:59:31,099 - pyskl - INFO - Epoch [94][100/1281] lr: 7.880e-03, eta: 8:42:18, time: 0.807, data_time: 0.191, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 0.2226, loss: 0.2226 +2025-06-25 03:00:20,309 - pyskl - INFO - Epoch [94][200/1281] lr: 7.861e-03, eta: 8:41:39, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2205, loss: 0.2205 +2025-06-25 03:01:09,450 - pyskl - INFO - Epoch [94][300/1281] lr: 7.842e-03, eta: 8:41:00, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9988, loss_cls: 0.2457, loss: 0.2457 +2025-06-25 03:01:58,889 - pyskl - INFO - Epoch [94][400/1281] lr: 7.823e-03, eta: 8:40:21, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 0.2134, loss: 0.2134 +2025-06-25 03:02:47,988 - pyskl - INFO - Epoch [94][500/1281] lr: 7.804e-03, eta: 8:39:42, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9988, loss_cls: 0.2815, loss: 0.2815 +2025-06-25 03:03:37,049 - pyskl - INFO - Epoch [94][600/1281] lr: 7.785e-03, eta: 8:39:02, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9994, loss_cls: 0.3037, loss: 0.3037 +2025-06-25 03:04:25,991 - pyskl - INFO - Epoch [94][700/1281] lr: 7.766e-03, eta: 8:38:23, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9994, loss_cls: 0.2454, loss: 0.2454 +2025-06-25 03:04:58,799 - pyskl - INFO - Epoch [94][800/1281] lr: 7.747e-03, eta: 8:37:34, time: 0.328, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2138, loss: 0.2138 +2025-06-25 03:05:40,477 - pyskl - INFO - Epoch [94][900/1281] lr: 7.728e-03, eta: 8:36:50, time: 0.417, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9994, loss_cls: 0.2431, loss: 0.2431 +2025-06-25 03:06:17,298 - pyskl - INFO - Epoch [94][1000/1281] lr: 7.709e-03, eta: 8:36:03, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 0.2634, loss: 0.2634 +2025-06-25 03:07:06,143 - pyskl - INFO - Epoch [94][1100/1281] lr: 7.690e-03, eta: 8:35:24, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 0.2662, loss: 0.2662 +2025-06-25 03:07:55,341 - pyskl - INFO - Epoch [94][1200/1281] lr: 7.672e-03, eta: 8:34:44, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 0.2353, loss: 0.2353 +2025-06-25 03:08:35,741 - pyskl - INFO - Saving checkpoint at 94 epochs +2025-06-25 03:09:34,255 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:09:34,315 - pyskl - INFO - +top1_acc 0.8911 +top5_acc 0.9911 +2025-06-25 03:09:34,315 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:09:34,322 - pyskl - INFO - +mean_acc 0.8594 +2025-06-25 03:09:34,326 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_87.pth was removed +2025-06-25 03:09:34,540 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_94.pth. +2025-06-25 03:09:34,540 - pyskl - INFO - Best top1_acc is 0.8911 at 94 epoch. +2025-06-25 03:09:34,543 - pyskl - INFO - Epoch(val) [94][533] top1_acc: 0.8911, top5_acc: 0.9911, mean_class_accuracy: 0.8594 +2025-06-25 03:10:53,059 - pyskl - INFO - Epoch [95][100/1281] lr: 7.637e-03, eta: 8:33:27, time: 0.785, data_time: 0.187, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.2217, loss: 0.2217 +2025-06-25 03:11:41,964 - pyskl - INFO - Epoch [95][200/1281] lr: 7.619e-03, eta: 8:32:47, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 0.9988, loss_cls: 0.2026, loss: 0.2026 +2025-06-25 03:12:30,944 - pyskl - INFO - Epoch [95][300/1281] lr: 7.600e-03, eta: 8:32:08, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 0.9994, loss_cls: 0.2141, loss: 0.2141 +2025-06-25 03:13:19,847 - pyskl - INFO - Epoch [95][400/1281] lr: 7.581e-03, eta: 8:31:28, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2309, loss: 0.2309 +2025-06-25 03:14:08,610 - pyskl - INFO - Epoch [95][500/1281] lr: 7.562e-03, eta: 8:30:49, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2560, loss: 0.2560 +2025-06-25 03:14:57,283 - pyskl - INFO - Epoch [95][600/1281] lr: 7.543e-03, eta: 8:30:09, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 1.0000, loss_cls: 0.2400, loss: 0.2400 +2025-06-25 03:15:44,998 - pyskl - INFO - Epoch [95][700/1281] lr: 7.525e-03, eta: 8:29:29, time: 0.477, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 0.2197, loss: 0.2197 +2025-06-25 03:16:20,589 - pyskl - INFO - Epoch [95][800/1281] lr: 7.506e-03, eta: 8:28:41, time: 0.356, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 0.2438, loss: 0.2438 +2025-06-25 03:16:58,471 - pyskl - INFO - Epoch [95][900/1281] lr: 7.487e-03, eta: 8:27:55, time: 0.379, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9981, loss_cls: 0.2484, loss: 0.2484 +2025-06-25 03:17:36,546 - pyskl - INFO - Epoch [95][1000/1281] lr: 7.468e-03, eta: 8:27:10, time: 0.381, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.2893, loss: 0.2893 +2025-06-25 03:18:25,517 - pyskl - INFO - Epoch [95][1100/1281] lr: 7.450e-03, eta: 8:26:30, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9994, loss_cls: 0.2991, loss: 0.2991 +2025-06-25 03:19:14,500 - pyskl - INFO - Epoch [95][1200/1281] lr: 7.431e-03, eta: 8:25:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 0.2430, loss: 0.2430 +2025-06-25 03:19:54,522 - pyskl - INFO - Saving checkpoint at 95 epochs +2025-06-25 03:20:53,280 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:20:53,348 - pyskl - INFO - +top1_acc 0.8700 +top5_acc 0.9878 +2025-06-25 03:20:53,349 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:20:53,357 - pyskl - INFO - +mean_acc 0.8414 +2025-06-25 03:20:53,359 - pyskl - INFO - Epoch(val) [95][533] top1_acc: 0.8700, top5_acc: 0.9878, mean_class_accuracy: 0.8414 +2025-06-25 03:22:12,419 - pyskl - INFO - Epoch [96][100/1281] lr: 7.397e-03, eta: 8:24:33, time: 0.791, data_time: 0.190, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2403, loss: 0.2403 +2025-06-25 03:23:01,101 - pyskl - INFO - Epoch [96][200/1281] lr: 7.379e-03, eta: 8:23:53, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.1720, loss: 0.1720 +2025-06-25 03:23:50,221 - pyskl - INFO - Epoch [96][300/1281] lr: 7.360e-03, eta: 8:23:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 0.1729, loss: 0.1729 +2025-06-25 03:24:39,204 - pyskl - INFO - Epoch [96][400/1281] lr: 7.341e-03, eta: 8:22:34, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 0.9994, loss_cls: 0.1689, loss: 0.1689 +2025-06-25 03:25:28,277 - pyskl - INFO - Epoch [96][500/1281] lr: 7.323e-03, eta: 8:21:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2087, loss: 0.2087 +2025-06-25 03:26:17,179 - pyskl - INFO - Epoch [96][600/1281] lr: 7.304e-03, eta: 8:21:15, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 0.2029, loss: 0.2029 +2025-06-25 03:27:03,304 - pyskl - INFO - Epoch [96][700/1281] lr: 7.286e-03, eta: 8:20:34, time: 0.461, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1712, loss: 0.1712 +2025-06-25 03:27:41,149 - pyskl - INFO - Epoch [96][800/1281] lr: 7.267e-03, eta: 8:19:48, time: 0.378, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2123, loss: 0.2123 +2025-06-25 03:28:16,731 - pyskl - INFO - Epoch [96][900/1281] lr: 7.249e-03, eta: 8:19:00, time: 0.356, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 0.2600, loss: 0.2600 +2025-06-25 03:28:55,177 - pyskl - INFO - Epoch [96][1000/1281] lr: 7.230e-03, eta: 8:18:15, time: 0.384, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2143, loss: 0.2143 +2025-06-25 03:29:44,187 - pyskl - INFO - Epoch [96][1100/1281] lr: 7.211e-03, eta: 8:17:35, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 0.9994, loss_cls: 0.2307, loss: 0.2307 +2025-06-25 03:30:32,706 - pyskl - INFO - Epoch [96][1200/1281] lr: 7.193e-03, eta: 8:16:55, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2642, loss: 0.2642 +2025-06-25 03:31:12,838 - pyskl - INFO - Saving checkpoint at 96 epochs +2025-06-25 03:32:11,199 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:32:11,255 - pyskl - INFO - +top1_acc 0.8740 +top5_acc 0.9891 +2025-06-25 03:32:11,255 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:32:11,261 - pyskl - INFO - +mean_acc 0.8416 +2025-06-25 03:32:11,262 - pyskl - INFO - Epoch(val) [96][533] top1_acc: 0.8740, top5_acc: 0.9891, mean_class_accuracy: 0.8416 +2025-06-25 03:33:29,607 - pyskl - INFO - Epoch [97][100/1281] lr: 7.159e-03, eta: 8:15:37, time: 0.783, data_time: 0.186, memory: 4083, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 0.2498, loss: 0.2498 +2025-06-25 03:34:18,426 - pyskl - INFO - Epoch [97][200/1281] lr: 7.141e-03, eta: 8:14:58, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.2006, loss: 0.2006 +2025-06-25 03:35:07,514 - pyskl - INFO - Epoch [97][300/1281] lr: 7.123e-03, eta: 8:14:18, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2388, loss: 0.2388 +2025-06-25 03:35:56,374 - pyskl - INFO - Epoch [97][400/1281] lr: 7.104e-03, eta: 8:13:38, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1914, loss: 0.1914 +2025-06-25 03:36:45,302 - pyskl - INFO - Epoch [97][500/1281] lr: 7.086e-03, eta: 8:12:58, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.1982, loss: 0.1982 +2025-06-25 03:37:34,805 - pyskl - INFO - Epoch [97][600/1281] lr: 7.067e-03, eta: 8:12:19, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.1873, loss: 0.1873 +2025-06-25 03:38:21,183 - pyskl - INFO - Epoch [97][700/1281] lr: 7.049e-03, eta: 8:11:37, time: 0.464, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1818, loss: 0.1818 +2025-06-25 03:38:58,598 - pyskl - INFO - Epoch [97][800/1281] lr: 7.030e-03, eta: 8:10:51, time: 0.374, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.2030, loss: 0.2030 +2025-06-25 03:39:34,597 - pyskl - INFO - Epoch [97][900/1281] lr: 7.012e-03, eta: 8:10:04, time: 0.360, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.1966, loss: 0.1966 +2025-06-25 03:40:12,841 - pyskl - INFO - Epoch [97][1000/1281] lr: 6.994e-03, eta: 8:09:19, time: 0.382, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1982, loss: 0.1982 +2025-06-25 03:41:01,600 - pyskl - INFO - Epoch [97][1100/1281] lr: 6.975e-03, eta: 8:08:39, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9975, loss_cls: 0.2332, loss: 0.2332 +2025-06-25 03:41:50,276 - pyskl - INFO - Epoch [97][1200/1281] lr: 6.957e-03, eta: 8:07:59, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2114, loss: 0.2114 +2025-06-25 03:42:30,292 - pyskl - INFO - Saving checkpoint at 97 epochs +2025-06-25 03:43:28,991 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:43:29,046 - pyskl - INFO - +top1_acc 0.8880 +top5_acc 0.9900 +2025-06-25 03:43:29,046 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:43:29,053 - pyskl - INFO - +mean_acc 0.8637 +2025-06-25 03:43:29,054 - pyskl - INFO - Epoch(val) [97][533] top1_acc: 0.8880, top5_acc: 0.9900, mean_class_accuracy: 0.8637 +2025-06-25 03:44:47,014 - pyskl - INFO - Epoch [98][100/1281] lr: 6.924e-03, eta: 8:06:41, time: 0.780, data_time: 0.184, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2229, loss: 0.2229 +2025-06-25 03:45:36,012 - pyskl - INFO - Epoch [98][200/1281] lr: 6.906e-03, eta: 8:06:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1782, loss: 0.1782 +2025-06-25 03:46:24,868 - pyskl - INFO - Epoch [98][300/1281] lr: 6.887e-03, eta: 8:05:21, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1554, loss: 0.1554 +2025-06-25 03:47:13,885 - pyskl - INFO - Epoch [98][400/1281] lr: 6.869e-03, eta: 8:04:41, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1648, loss: 0.1648 +2025-06-25 03:48:03,152 - pyskl - INFO - Epoch [98][500/1281] lr: 6.851e-03, eta: 8:04:01, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1771, loss: 0.1771 +2025-06-25 03:48:52,391 - pyskl - INFO - Epoch [98][600/1281] lr: 6.833e-03, eta: 8:03:21, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1605, loss: 0.1605 +2025-06-25 03:49:39,320 - pyskl - INFO - Epoch [98][700/1281] lr: 6.814e-03, eta: 8:02:40, time: 0.469, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2259, loss: 0.2259 +2025-06-25 03:50:15,467 - pyskl - INFO - Epoch [98][800/1281] lr: 6.796e-03, eta: 8:01:54, time: 0.361, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 0.9994, loss_cls: 0.2380, loss: 0.2380 +2025-06-25 03:50:52,471 - pyskl - INFO - Epoch [98][900/1281] lr: 6.778e-03, eta: 8:01:07, time: 0.370, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 0.2155, loss: 0.2155 +2025-06-25 03:51:30,324 - pyskl - INFO - Epoch [98][1000/1281] lr: 6.760e-03, eta: 8:00:21, time: 0.379, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 0.9988, loss_cls: 0.1821, loss: 0.1821 +2025-06-25 03:52:19,450 - pyskl - INFO - Epoch [98][1100/1281] lr: 6.742e-03, eta: 7:59:41, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 0.2331, loss: 0.2331 +2025-06-25 03:53:08,517 - pyskl - INFO - Epoch [98][1200/1281] lr: 6.724e-03, eta: 7:59:02, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2427, loss: 0.2427 +2025-06-25 03:53:48,802 - pyskl - INFO - Saving checkpoint at 98 epochs +2025-06-25 03:54:47,404 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:54:47,460 - pyskl - INFO - +top1_acc 0.8991 +top5_acc 0.9935 +2025-06-25 03:54:47,460 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:54:47,466 - pyskl - INFO - +mean_acc 0.8655 +2025-06-25 03:54:47,470 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_94.pth was removed +2025-06-25 03:54:47,643 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_98.pth. +2025-06-25 03:54:47,644 - pyskl - INFO - Best top1_acc is 0.8991 at 98 epoch. +2025-06-25 03:54:47,647 - pyskl - INFO - Epoch(val) [98][533] top1_acc: 0.8991, top5_acc: 0.9935, mean_class_accuracy: 0.8655 +2025-06-25 03:56:06,613 - pyskl - INFO - Epoch [99][100/1281] lr: 6.691e-03, eta: 7:57:44, time: 0.790, data_time: 0.190, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1821, loss: 0.1821 +2025-06-25 03:56:55,199 - pyskl - INFO - Epoch [99][200/1281] lr: 6.673e-03, eta: 7:57:04, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 0.1783, loss: 0.1783 +2025-06-25 03:57:43,883 - pyskl - INFO - Epoch [99][300/1281] lr: 6.655e-03, eta: 7:56:24, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.1846, loss: 0.1846 +2025-06-25 03:58:33,047 - pyskl - INFO - Epoch [99][400/1281] lr: 6.637e-03, eta: 7:55:44, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 0.2234, loss: 0.2234 +2025-06-25 03:59:22,479 - pyskl - INFO - Epoch [99][500/1281] lr: 6.619e-03, eta: 7:55:04, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1872, loss: 0.1872 +2025-06-25 04:00:11,345 - pyskl - INFO - Epoch [99][600/1281] lr: 6.601e-03, eta: 7:54:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1883, loss: 0.1883 +2025-06-25 04:00:57,054 - pyskl - INFO - Epoch [99][700/1281] lr: 6.583e-03, eta: 7:53:42, time: 0.457, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1689, loss: 0.1689 +2025-06-25 04:01:36,474 - pyskl - INFO - Epoch [99][800/1281] lr: 6.565e-03, eta: 7:52:57, time: 0.394, data_time: 0.001, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2353, loss: 0.2353 +2025-06-25 04:02:10,356 - pyskl - INFO - Epoch [99][900/1281] lr: 6.547e-03, eta: 7:52:09, time: 0.339, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.2348, loss: 0.2348 +2025-06-25 04:02:47,983 - pyskl - INFO - Epoch [99][1000/1281] lr: 6.529e-03, eta: 7:51:23, time: 0.376, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2142, loss: 0.2142 +2025-06-25 04:03:37,045 - pyskl - INFO - Epoch [99][1100/1281] lr: 6.511e-03, eta: 7:50:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1951, loss: 0.1951 +2025-06-25 04:04:26,103 - pyskl - INFO - Epoch [99][1200/1281] lr: 6.493e-03, eta: 7:50:03, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9988, loss_cls: 0.2071, loss: 0.2071 +2025-06-25 04:05:06,244 - pyskl - INFO - Saving checkpoint at 99 epochs +2025-06-25 04:06:04,781 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:06:04,849 - pyskl - INFO - +top1_acc 0.8931 +top5_acc 0.9928 +2025-06-25 04:06:04,849 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:06:04,857 - pyskl - INFO - +mean_acc 0.8606 +2025-06-25 04:06:04,859 - pyskl - INFO - Epoch(val) [99][533] top1_acc: 0.8931, top5_acc: 0.9928, mean_class_accuracy: 0.8606 +2025-06-25 04:07:23,074 - pyskl - INFO - Epoch [100][100/1281] lr: 6.460e-03, eta: 7:48:45, time: 0.782, data_time: 0.185, memory: 4083, top1_acc: 0.9675, top5_acc: 0.9994, loss_cls: 0.1914, loss: 0.1914 +2025-06-25 04:08:11,791 - pyskl - INFO - Epoch [100][200/1281] lr: 6.442e-03, eta: 7:48:05, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 0.9994, loss_cls: 0.1933, loss: 0.1933 +2025-06-25 04:09:00,712 - pyskl - INFO - Epoch [100][300/1281] lr: 6.425e-03, eta: 7:47:25, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1564, loss: 0.1564 +2025-06-25 04:09:49,671 - pyskl - INFO - Epoch [100][400/1281] lr: 6.407e-03, eta: 7:46:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1611, loss: 0.1611 +2025-06-25 04:10:38,620 - pyskl - INFO - Epoch [100][500/1281] lr: 6.389e-03, eta: 7:46:04, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1739, loss: 0.1739 +2025-06-25 04:11:27,871 - pyskl - INFO - Epoch [100][600/1281] lr: 6.371e-03, eta: 7:45:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1740, loss: 0.1740 +2025-06-25 04:12:15,996 - pyskl - INFO - Epoch [100][700/1281] lr: 6.353e-03, eta: 7:44:44, time: 0.481, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 0.2120, loss: 0.2120 +2025-06-25 04:12:50,311 - pyskl - INFO - Epoch [100][800/1281] lr: 6.336e-03, eta: 7:43:56, time: 0.343, data_time: 0.001, memory: 4083, top1_acc: 0.9669, top5_acc: 0.9994, loss_cls: 0.2082, loss: 0.2082 +2025-06-25 04:13:29,370 - pyskl - INFO - Epoch [100][900/1281] lr: 6.318e-03, eta: 7:43:11, time: 0.391, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2434, loss: 0.2434 +2025-06-25 04:14:06,797 - pyskl - INFO - Epoch [100][1000/1281] lr: 6.300e-03, eta: 7:42:25, time: 0.374, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1847, loss: 0.1847 +2025-06-25 04:14:55,820 - pyskl - INFO - Epoch [100][1100/1281] lr: 6.282e-03, eta: 7:41:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1722, loss: 0.1722 +2025-06-25 04:15:44,478 - pyskl - INFO - Epoch [100][1200/1281] lr: 6.265e-03, eta: 7:41:04, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9994, loss_cls: 0.2260, loss: 0.2260 +2025-06-25 04:16:24,613 - pyskl - INFO - Saving checkpoint at 100 epochs +2025-06-25 04:17:22,706 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:17:22,784 - pyskl - INFO - +top1_acc 0.8885 +top5_acc 0.9918 +2025-06-25 04:17:22,784 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:17:22,791 - pyskl - INFO - +mean_acc 0.8519 +2025-06-25 04:17:22,792 - pyskl - INFO - Epoch(val) [100][533] top1_acc: 0.8885, top5_acc: 0.9918, mean_class_accuracy: 0.8519 +2025-06-25 04:18:40,583 - pyskl - INFO - Epoch [101][100/1281] lr: 6.232e-03, eta: 7:39:46, time: 0.778, data_time: 0.186, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1807, loss: 0.1807 +2025-06-25 04:19:29,458 - pyskl - INFO - Epoch [101][200/1281] lr: 6.215e-03, eta: 7:39:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1667, loss: 0.1667 +2025-06-25 04:20:18,411 - pyskl - INFO - Epoch [101][300/1281] lr: 6.197e-03, eta: 7:38:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2099, loss: 0.2099 +2025-06-25 04:21:07,767 - pyskl - INFO - Epoch [101][400/1281] lr: 6.180e-03, eta: 7:37:46, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1553, loss: 0.1553 +2025-06-25 04:21:56,487 - pyskl - INFO - Epoch [101][500/1281] lr: 6.162e-03, eta: 7:37:05, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 0.9988, loss_cls: 0.1539, loss: 0.1539 +2025-06-25 04:22:45,419 - pyskl - INFO - Epoch [101][600/1281] lr: 6.144e-03, eta: 7:36:25, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.2057, loss: 0.2057 +2025-06-25 04:23:34,443 - pyskl - INFO - Epoch [101][700/1281] lr: 6.127e-03, eta: 7:35:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 0.2080, loss: 0.2080 +2025-06-25 04:24:07,363 - pyskl - INFO - Epoch [101][800/1281] lr: 6.109e-03, eta: 7:34:56, time: 0.329, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9988, loss_cls: 0.2472, loss: 0.2472 +2025-06-25 04:24:47,852 - pyskl - INFO - Epoch [101][900/1281] lr: 6.092e-03, eta: 7:34:12, time: 0.405, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.2025, loss: 0.2025 +2025-06-25 04:25:24,793 - pyskl - INFO - Epoch [101][1000/1281] lr: 6.074e-03, eta: 7:33:26, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1702, loss: 0.1702 +2025-06-25 04:26:13,458 - pyskl - INFO - Epoch [101][1100/1281] lr: 6.057e-03, eta: 7:32:45, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2007, loss: 0.2007 +2025-06-25 04:27:02,396 - pyskl - INFO - Epoch [101][1200/1281] lr: 6.039e-03, eta: 7:32:05, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9988, loss_cls: 0.2700, loss: 0.2700 +2025-06-25 04:27:42,570 - pyskl - INFO - Saving checkpoint at 101 epochs +2025-06-25 04:28:40,667 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:28:40,727 - pyskl - INFO - +top1_acc 0.8957 +top5_acc 0.9931 +2025-06-25 04:28:40,728 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:28:40,735 - pyskl - INFO - +mean_acc 0.8684 +2025-06-25 04:28:40,737 - pyskl - INFO - Epoch(val) [101][533] top1_acc: 0.8957, top5_acc: 0.9931, mean_class_accuracy: 0.8684 +2025-06-25 04:30:00,513 - pyskl - INFO - Epoch [102][100/1281] lr: 6.007e-03, eta: 7:30:48, time: 0.798, data_time: 0.185, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1475, loss: 0.1475 +2025-06-25 04:30:48,931 - pyskl - INFO - Epoch [102][200/1281] lr: 5.990e-03, eta: 7:30:07, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1711, loss: 0.1711 +2025-06-25 04:31:37,820 - pyskl - INFO - Epoch [102][300/1281] lr: 5.972e-03, eta: 7:29:27, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1544, loss: 0.1544 +2025-06-25 04:32:26,691 - pyskl - INFO - Epoch [102][400/1281] lr: 5.955e-03, eta: 7:28:46, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 0.1838, loss: 0.1838 +2025-06-25 04:33:15,482 - pyskl - INFO - Epoch [102][500/1281] lr: 5.938e-03, eta: 7:28:06, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1749, loss: 0.1749 +2025-06-25 04:34:04,561 - pyskl - INFO - Epoch [102][600/1281] lr: 5.920e-03, eta: 7:27:25, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 0.2131, loss: 0.2131 +2025-06-25 04:34:52,718 - pyskl - INFO - Epoch [102][700/1281] lr: 5.903e-03, eta: 7:26:45, time: 0.482, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2178, loss: 0.2178 +2025-06-25 04:35:25,751 - pyskl - INFO - Epoch [102][800/1281] lr: 5.886e-03, eta: 7:25:57, time: 0.330, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1957, loss: 0.1957 +2025-06-25 04:36:06,076 - pyskl - INFO - Epoch [102][900/1281] lr: 5.868e-03, eta: 7:25:12, time: 0.403, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 0.9994, loss_cls: 0.1938, loss: 0.1938 +2025-06-25 04:36:43,155 - pyskl - INFO - Epoch [102][1000/1281] lr: 5.851e-03, eta: 7:24:26, time: 0.371, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 0.9994, loss_cls: 0.1848, loss: 0.1848 +2025-06-25 04:37:31,814 - pyskl - INFO - Epoch [102][1100/1281] lr: 5.834e-03, eta: 7:23:45, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9994, loss_cls: 0.2275, loss: 0.2275 +2025-06-25 04:38:21,079 - pyskl - INFO - Epoch [102][1200/1281] lr: 5.816e-03, eta: 7:23:05, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1975, loss: 0.1975 +2025-06-25 04:39:01,418 - pyskl - INFO - Saving checkpoint at 102 epochs +2025-06-25 04:39:59,536 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:39:59,592 - pyskl - INFO - +top1_acc 0.8857 +top5_acc 0.9893 +2025-06-25 04:39:59,592 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:39:59,599 - pyskl - INFO - +mean_acc 0.8608 +2025-06-25 04:39:59,600 - pyskl - INFO - Epoch(val) [102][533] top1_acc: 0.8857, top5_acc: 0.9893, mean_class_accuracy: 0.8608 +2025-06-25 04:41:18,971 - pyskl - INFO - Epoch [103][100/1281] lr: 5.785e-03, eta: 7:21:47, time: 0.794, data_time: 0.180, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1803, loss: 0.1803 +2025-06-25 04:42:07,808 - pyskl - INFO - Epoch [103][200/1281] lr: 5.768e-03, eta: 7:21:07, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1391, loss: 0.1391 +2025-06-25 04:42:56,814 - pyskl - INFO - Epoch [103][300/1281] lr: 5.751e-03, eta: 7:20:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1452, loss: 0.1452 +2025-06-25 04:43:45,792 - pyskl - INFO - Epoch [103][400/1281] lr: 5.733e-03, eta: 7:19:46, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1515, loss: 0.1515 +2025-06-25 04:44:34,631 - pyskl - INFO - Epoch [103][500/1281] lr: 5.716e-03, eta: 7:19:05, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1626, loss: 0.1626 +2025-06-25 04:45:23,990 - pyskl - INFO - Epoch [103][600/1281] lr: 5.699e-03, eta: 7:18:25, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1426, loss: 0.1426 +2025-06-25 04:46:11,544 - pyskl - INFO - Epoch [103][700/1281] lr: 5.682e-03, eta: 7:17:44, time: 0.476, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1707, loss: 0.1707 +2025-06-25 04:46:46,781 - pyskl - INFO - Epoch [103][800/1281] lr: 5.665e-03, eta: 7:16:57, time: 0.352, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1835, loss: 0.1835 +2025-06-25 04:47:24,599 - pyskl - INFO - Epoch [103][900/1281] lr: 5.648e-03, eta: 7:16:11, time: 0.378, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1686, loss: 0.1686 +2025-06-25 04:48:02,168 - pyskl - INFO - Epoch [103][1000/1281] lr: 5.631e-03, eta: 7:15:25, time: 0.376, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.1757, loss: 0.1757 +2025-06-25 04:48:50,688 - pyskl - INFO - Epoch [103][1100/1281] lr: 5.614e-03, eta: 7:14:45, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.1896, loss: 0.1896 +2025-06-25 04:49:39,383 - pyskl - INFO - Epoch [103][1200/1281] lr: 5.597e-03, eta: 7:14:04, time: 0.487, data_time: 0.001, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1604, loss: 0.1604 +2025-06-25 04:50:19,479 - pyskl - INFO - Saving checkpoint at 103 epochs +2025-06-25 04:51:18,361 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:51:18,415 - pyskl - INFO - +top1_acc 0.8948 +top5_acc 0.9921 +2025-06-25 04:51:18,415 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:51:18,421 - pyskl - INFO - +mean_acc 0.8716 +2025-06-25 04:51:18,423 - pyskl - INFO - Epoch(val) [103][533] top1_acc: 0.8948, top5_acc: 0.9921, mean_class_accuracy: 0.8716 +2025-06-25 04:52:36,309 - pyskl - INFO - Epoch [104][100/1281] lr: 5.566e-03, eta: 7:12:46, time: 0.779, data_time: 0.183, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1517, loss: 0.1517 +2025-06-25 04:53:24,833 - pyskl - INFO - Epoch [104][200/1281] lr: 5.549e-03, eta: 7:12:05, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2083, loss: 0.2083 +2025-06-25 04:54:13,895 - pyskl - INFO - Epoch [104][300/1281] lr: 5.532e-03, eta: 7:11:24, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1809, loss: 0.1809 +2025-06-25 04:55:02,606 - pyskl - INFO - Epoch [104][400/1281] lr: 5.515e-03, eta: 7:10:44, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1718, loss: 0.1718 +2025-06-25 04:55:51,632 - pyskl - INFO - Epoch [104][500/1281] lr: 5.498e-03, eta: 7:10:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1399, loss: 0.1399 +2025-06-25 04:56:41,135 - pyskl - INFO - Epoch [104][600/1281] lr: 5.481e-03, eta: 7:09:23, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1765, loss: 0.1765 +2025-06-25 04:57:28,381 - pyskl - INFO - Epoch [104][700/1281] lr: 5.464e-03, eta: 7:08:41, time: 0.472, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 0.9994, loss_cls: 0.1695, loss: 0.1695 +2025-06-25 04:58:04,268 - pyskl - INFO - Epoch [104][800/1281] lr: 5.447e-03, eta: 7:07:55, time: 0.359, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1159, loss: 0.1159 +2025-06-25 04:58:41,634 - pyskl - INFO - Epoch [104][900/1281] lr: 5.430e-03, eta: 7:07:09, time: 0.374, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 0.9994, loss_cls: 0.1650, loss: 0.1650 +2025-06-25 04:59:18,718 - pyskl - INFO - Epoch [104][1000/1281] lr: 5.413e-03, eta: 7:06:23, time: 0.371, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1781, loss: 0.1781 +2025-06-25 05:00:07,379 - pyskl - INFO - Epoch [104][1100/1281] lr: 5.397e-03, eta: 7:05:42, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 0.9994, loss_cls: 0.1412, loss: 0.1412 +2025-06-25 05:00:55,647 - pyskl - INFO - Epoch [104][1200/1281] lr: 5.380e-03, eta: 7:05:01, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1662, loss: 0.1662 +2025-06-25 05:01:35,641 - pyskl - INFO - Saving checkpoint at 104 epochs +2025-06-25 05:02:34,167 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:02:34,231 - pyskl - INFO - +top1_acc 0.8967 +top5_acc 0.9907 +2025-06-25 05:02:34,231 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:02:34,238 - pyskl - INFO - +mean_acc 0.8642 +2025-06-25 05:02:34,239 - pyskl - INFO - Epoch(val) [104][533] top1_acc: 0.8967, top5_acc: 0.9907, mean_class_accuracy: 0.8642 +2025-06-25 05:03:53,494 - pyskl - INFO - Epoch [105][100/1281] lr: 5.349e-03, eta: 7:03:43, time: 0.792, data_time: 0.188, memory: 4083, top1_acc: 0.9725, top5_acc: 0.9994, loss_cls: 0.1595, loss: 0.1595 +2025-06-25 05:04:42,505 - pyskl - INFO - Epoch [105][200/1281] lr: 5.333e-03, eta: 7:03:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1548, loss: 0.1548 +2025-06-25 05:05:31,138 - pyskl - INFO - Epoch [105][300/1281] lr: 5.316e-03, eta: 7:02:22, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1364, loss: 0.1364 +2025-06-25 05:06:19,806 - pyskl - INFO - Epoch [105][400/1281] lr: 5.299e-03, eta: 7:01:41, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1555, loss: 0.1555 +2025-06-25 05:07:09,108 - pyskl - INFO - Epoch [105][500/1281] lr: 5.283e-03, eta: 7:01:01, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1522, loss: 0.1522 +2025-06-25 05:07:57,778 - pyskl - INFO - Epoch [105][600/1281] lr: 5.266e-03, eta: 7:00:20, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 0.9994, loss_cls: 0.1685, loss: 0.1685 +2025-06-25 05:08:45,097 - pyskl - INFO - Epoch [105][700/1281] lr: 5.249e-03, eta: 6:59:38, time: 0.473, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1416, loss: 0.1416 +2025-06-25 05:09:22,660 - pyskl - INFO - Epoch [105][800/1281] lr: 5.233e-03, eta: 6:58:52, time: 0.376, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 0.9994, loss_cls: 0.1986, loss: 0.1986 +2025-06-25 05:09:58,416 - pyskl - INFO - Epoch [105][900/1281] lr: 5.216e-03, eta: 6:58:06, time: 0.358, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1788, loss: 0.1788 +2025-06-25 05:10:36,328 - pyskl - INFO - Epoch [105][1000/1281] lr: 5.199e-03, eta: 6:57:20, time: 0.379, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1771, loss: 0.1771 +2025-06-25 05:11:25,239 - pyskl - INFO - Epoch [105][1100/1281] lr: 5.183e-03, eta: 6:56:40, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1549, loss: 0.1549 +2025-06-25 05:12:14,340 - pyskl - INFO - Epoch [105][1200/1281] lr: 5.166e-03, eta: 6:55:59, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1581, loss: 0.1581 +2025-06-25 05:12:54,450 - pyskl - INFO - Saving checkpoint at 105 epochs +2025-06-25 05:13:52,854 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:13:52,909 - pyskl - INFO - +top1_acc 0.9026 +top5_acc 0.9931 +2025-06-25 05:13:52,909 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:13:52,916 - pyskl - INFO - +mean_acc 0.8773 +2025-06-25 05:13:52,920 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_98.pth was removed +2025-06-25 05:13:53,094 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_105.pth. +2025-06-25 05:13:53,095 - pyskl - INFO - Best top1_acc is 0.9026 at 105 epoch. +2025-06-25 05:13:53,097 - pyskl - INFO - Epoch(val) [105][533] top1_acc: 0.9026, top5_acc: 0.9931, mean_class_accuracy: 0.8773 +2025-06-25 05:15:13,390 - pyskl - INFO - Epoch [106][100/1281] lr: 5.136e-03, eta: 6:54:42, time: 0.803, data_time: 0.188, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1214, loss: 0.1214 +2025-06-25 05:16:02,507 - pyskl - INFO - Epoch [106][200/1281] lr: 5.120e-03, eta: 6:54:01, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 0.9994, loss_cls: 0.1296, loss: 0.1296 +2025-06-25 05:16:51,460 - pyskl - INFO - Epoch [106][300/1281] lr: 5.103e-03, eta: 6:53:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1484, loss: 0.1484 +2025-06-25 05:17:40,625 - pyskl - INFO - Epoch [106][400/1281] lr: 5.087e-03, eta: 6:52:39, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1619, loss: 0.1619 +2025-06-25 05:18:29,626 - pyskl - INFO - Epoch [106][500/1281] lr: 5.070e-03, eta: 6:51:58, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1439, loss: 0.1439 +2025-06-25 05:19:18,458 - pyskl - INFO - Epoch [106][600/1281] lr: 5.054e-03, eta: 6:51:18, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1304, loss: 0.1304 +2025-06-25 05:20:03,193 - pyskl - INFO - Epoch [106][700/1281] lr: 5.038e-03, eta: 6:50:35, time: 0.447, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1126, loss: 0.1126 +2025-06-25 05:20:44,258 - pyskl - INFO - Epoch [106][800/1281] lr: 5.021e-03, eta: 6:49:51, time: 0.411, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 0.9994, loss_cls: 0.1681, loss: 0.1681 +2025-06-25 05:21:16,296 - pyskl - INFO - Epoch [106][900/1281] lr: 5.005e-03, eta: 6:49:03, time: 0.320, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1488, loss: 0.1488 +2025-06-25 05:21:56,007 - pyskl - INFO - Epoch [106][1000/1281] lr: 4.988e-03, eta: 6:48:18, time: 0.397, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1466, loss: 0.1466 +2025-06-25 05:22:44,648 - pyskl - INFO - Epoch [106][1100/1281] lr: 4.972e-03, eta: 6:47:37, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1628, loss: 0.1628 +2025-06-25 05:23:33,724 - pyskl - INFO - Epoch [106][1200/1281] lr: 4.956e-03, eta: 6:46:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1525, loss: 0.1525 +2025-06-25 05:24:13,890 - pyskl - INFO - Saving checkpoint at 106 epochs +2025-06-25 05:25:11,812 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:25:11,867 - pyskl - INFO - +top1_acc 0.9120 +top5_acc 0.9939 +2025-06-25 05:25:11,867 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:25:11,874 - pyskl - INFO - +mean_acc 0.8787 +2025-06-25 05:25:11,879 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_105.pth was removed +2025-06-25 05:25:12,057 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_106.pth. +2025-06-25 05:25:12,057 - pyskl - INFO - Best top1_acc is 0.9120 at 106 epoch. +2025-06-25 05:25:12,059 - pyskl - INFO - Epoch(val) [106][533] top1_acc: 0.9120, top5_acc: 0.9939, mean_class_accuracy: 0.8787 +2025-06-25 05:26:32,047 - pyskl - INFO - Epoch [107][100/1281] lr: 4.926e-03, eta: 6:45:39, time: 0.800, data_time: 0.183, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1495, loss: 0.1495 +2025-06-25 05:27:20,830 - pyskl - INFO - Epoch [107][200/1281] lr: 4.910e-03, eta: 6:44:58, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1064, loss: 0.1064 +2025-06-25 05:28:09,254 - pyskl - INFO - Epoch [107][300/1281] lr: 4.894e-03, eta: 6:44:16, time: 0.484, data_time: 0.001, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1065, loss: 0.1065 +2025-06-25 05:28:58,000 - pyskl - INFO - Epoch [107][400/1281] lr: 4.878e-03, eta: 6:43:35, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1006, loss: 0.1006 +2025-06-25 05:29:46,934 - pyskl - INFO - Epoch [107][500/1281] lr: 4.862e-03, eta: 6:42:55, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1147, loss: 0.1147 +2025-06-25 05:30:35,815 - pyskl - INFO - Epoch [107][600/1281] lr: 4.845e-03, eta: 6:42:14, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1347, loss: 0.1347 +2025-06-25 05:31:20,813 - pyskl - INFO - Epoch [107][700/1281] lr: 4.829e-03, eta: 6:41:31, time: 0.450, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1056, loss: 0.1056 +2025-06-25 05:32:02,261 - pyskl - INFO - Epoch [107][800/1281] lr: 4.813e-03, eta: 6:40:47, time: 0.414, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1579, loss: 0.1579 +2025-06-25 05:32:33,975 - pyskl - INFO - Epoch [107][900/1281] lr: 4.797e-03, eta: 6:39:59, time: 0.317, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1731, loss: 0.1731 +2025-06-25 05:33:13,713 - pyskl - INFO - Epoch [107][1000/1281] lr: 4.781e-03, eta: 6:39:14, time: 0.397, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1431, loss: 0.1431 +2025-06-25 05:34:02,814 - pyskl - INFO - Epoch [107][1100/1281] lr: 4.765e-03, eta: 6:38:33, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 0.1544, loss: 0.1544 +2025-06-25 05:34:51,482 - pyskl - INFO - Epoch [107][1200/1281] lr: 4.749e-03, eta: 6:37:52, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1186, loss: 0.1186 +2025-06-25 05:35:31,611 - pyskl - INFO - Saving checkpoint at 107 epochs +2025-06-25 05:36:29,970 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:36:30,025 - pyskl - INFO - +top1_acc 0.8923 +top5_acc 0.9899 +2025-06-25 05:36:30,025 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:36:30,031 - pyskl - INFO - +mean_acc 0.8603 +2025-06-25 05:36:30,033 - pyskl - INFO - Epoch(val) [107][533] top1_acc: 0.8923, top5_acc: 0.9899, mean_class_accuracy: 0.8603 +2025-06-25 05:37:48,836 - pyskl - INFO - Epoch [108][100/1281] lr: 4.720e-03, eta: 6:36:34, time: 0.788, data_time: 0.183, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1285, loss: 0.1285 +2025-06-25 05:38:37,875 - pyskl - INFO - Epoch [108][200/1281] lr: 4.704e-03, eta: 6:35:53, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.1018, loss: 0.1018 +2025-06-25 05:39:27,146 - pyskl - INFO - Epoch [108][300/1281] lr: 4.688e-03, eta: 6:35:12, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1398, loss: 0.1398 +2025-06-25 05:40:16,032 - pyskl - INFO - Epoch [108][400/1281] lr: 4.672e-03, eta: 6:34:31, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1341, loss: 0.1341 +2025-06-25 05:41:04,983 - pyskl - INFO - Epoch [108][500/1281] lr: 4.656e-03, eta: 6:33:50, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1459, loss: 0.1459 +2025-06-25 05:41:53,993 - pyskl - INFO - Epoch [108][600/1281] lr: 4.640e-03, eta: 6:33:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1371, loss: 0.1371 +2025-06-25 05:42:38,844 - pyskl - INFO - Epoch [108][700/1281] lr: 4.624e-03, eta: 6:32:26, time: 0.449, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1050, loss: 0.1050 +2025-06-25 05:43:21,199 - pyskl - INFO - Epoch [108][800/1281] lr: 4.608e-03, eta: 6:31:43, time: 0.424, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1318, loss: 0.1318 +2025-06-25 05:43:51,791 - pyskl - INFO - Epoch [108][900/1281] lr: 4.593e-03, eta: 6:30:54, time: 0.306, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1111, loss: 0.1111 +2025-06-25 05:44:30,255 - pyskl - INFO - Epoch [108][1000/1281] lr: 4.577e-03, eta: 6:30:09, time: 0.385, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1495, loss: 0.1495 +2025-06-25 05:45:19,237 - pyskl - INFO - Epoch [108][1100/1281] lr: 4.561e-03, eta: 6:29:28, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1635, loss: 0.1635 +2025-06-25 05:46:08,630 - pyskl - INFO - Epoch [108][1200/1281] lr: 4.545e-03, eta: 6:28:47, time: 0.494, data_time: 0.001, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1394, loss: 0.1394 +2025-06-25 05:46:48,851 - pyskl - INFO - Saving checkpoint at 108 epochs +2025-06-25 05:47:47,099 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:47:47,172 - pyskl - INFO - +top1_acc 0.8992 +top5_acc 0.9930 +2025-06-25 05:47:47,172 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:47:47,180 - pyskl - INFO - +mean_acc 0.8713 +2025-06-25 05:47:47,182 - pyskl - INFO - Epoch(val) [108][533] top1_acc: 0.8992, top5_acc: 0.9930, mean_class_accuracy: 0.8713 +2025-06-25 05:49:07,000 - pyskl - INFO - Epoch [109][100/1281] lr: 4.517e-03, eta: 6:27:30, time: 0.798, data_time: 0.182, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1343, loss: 0.1343 +2025-06-25 05:49:55,969 - pyskl - INFO - Epoch [109][200/1281] lr: 4.501e-03, eta: 6:26:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1506, loss: 0.1506 +2025-06-25 05:50:44,881 - pyskl - INFO - Epoch [109][300/1281] lr: 4.485e-03, eta: 6:26:07, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1323, loss: 0.1323 +2025-06-25 05:51:33,751 - pyskl - INFO - Epoch [109][400/1281] lr: 4.470e-03, eta: 6:25:26, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1437, loss: 0.1437 +2025-06-25 05:52:22,751 - pyskl - INFO - Epoch [109][500/1281] lr: 4.454e-03, eta: 6:24:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1196, loss: 0.1196 +2025-06-25 05:53:11,775 - pyskl - INFO - Epoch [109][600/1281] lr: 4.438e-03, eta: 6:24:04, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 0.9994, loss_cls: 0.1274, loss: 0.1274 +2025-06-25 05:53:57,081 - pyskl - INFO - Epoch [109][700/1281] lr: 4.423e-03, eta: 6:23:21, time: 0.453, data_time: 0.001, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1088, loss: 0.1088 +2025-06-25 05:54:37,193 - pyskl - INFO - Epoch [109][800/1281] lr: 4.407e-03, eta: 6:22:37, time: 0.401, data_time: 0.001, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1612, loss: 0.1612 +2025-06-25 05:55:10,166 - pyskl - INFO - Epoch [109][900/1281] lr: 4.391e-03, eta: 6:21:50, time: 0.330, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 0.1440, loss: 0.1440 +2025-06-25 05:55:48,859 - pyskl - INFO - Epoch [109][1000/1281] lr: 4.376e-03, eta: 6:21:05, time: 0.387, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 0.9994, loss_cls: 0.1310, loss: 0.1310 +2025-06-25 05:56:37,762 - pyskl - INFO - Epoch [109][1100/1281] lr: 4.360e-03, eta: 6:20:23, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1086, loss: 0.1086 +2025-06-25 05:57:26,835 - pyskl - INFO - Epoch [109][1200/1281] lr: 4.345e-03, eta: 6:19:42, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1080, loss: 0.1080 +2025-06-25 05:58:06,825 - pyskl - INFO - Saving checkpoint at 109 epochs +2025-06-25 05:59:04,085 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:59:04,139 - pyskl - INFO - +top1_acc 0.9042 +top5_acc 0.9928 +2025-06-25 05:59:04,139 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:59:04,145 - pyskl - INFO - +mean_acc 0.8757 +2025-06-25 05:59:04,147 - pyskl - INFO - Epoch(val) [109][533] top1_acc: 0.9042, top5_acc: 0.9928, mean_class_accuracy: 0.8757 +2025-06-25 06:00:24,541 - pyskl - INFO - Epoch [110][100/1281] lr: 4.317e-03, eta: 6:18:25, time: 0.804, data_time: 0.188, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0819, loss: 0.0819 +2025-06-25 06:01:13,782 - pyskl - INFO - Epoch [110][200/1281] lr: 4.301e-03, eta: 6:17:43, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0798, loss: 0.0798 +2025-06-25 06:02:02,564 - pyskl - INFO - Epoch [110][300/1281] lr: 4.286e-03, eta: 6:17:02, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1016, loss: 0.1016 +2025-06-25 06:02:51,730 - pyskl - INFO - Epoch [110][400/1281] lr: 4.271e-03, eta: 6:16:21, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1518, loss: 0.1518 +2025-06-25 06:03:40,783 - pyskl - INFO - Epoch [110][500/1281] lr: 4.255e-03, eta: 6:15:40, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.1060, loss: 0.1060 +2025-06-25 06:04:29,755 - pyskl - INFO - Epoch [110][600/1281] lr: 4.240e-03, eta: 6:14:59, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 0.9994, loss_cls: 0.1588, loss: 0.1588 +2025-06-25 06:05:15,049 - pyskl - INFO - Epoch [110][700/1281] lr: 4.225e-03, eta: 6:14:16, time: 0.453, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1276, loss: 0.1276 +2025-06-25 06:05:55,376 - pyskl - INFO - Epoch [110][800/1281] lr: 4.209e-03, eta: 6:13:32, time: 0.403, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1279, loss: 0.1279 +2025-06-25 06:06:28,112 - pyskl - INFO - Epoch [110][900/1281] lr: 4.194e-03, eta: 6:12:44, time: 0.327, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1340, loss: 0.1340 +2025-06-25 06:07:08,008 - pyskl - INFO - Epoch [110][1000/1281] lr: 4.179e-03, eta: 6:12:00, time: 0.399, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 0.1349, loss: 0.1349 +2025-06-25 06:07:56,663 - pyskl - INFO - Epoch [110][1100/1281] lr: 4.164e-03, eta: 6:11:18, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1659, loss: 0.1659 +2025-06-25 06:08:45,769 - pyskl - INFO - Epoch [110][1200/1281] lr: 4.148e-03, eta: 6:10:37, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 0.1307, loss: 0.1307 +2025-06-25 06:09:26,187 - pyskl - INFO - Saving checkpoint at 110 epochs +2025-06-25 06:10:24,846 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:10:24,901 - pyskl - INFO - +top1_acc 0.9044 +top5_acc 0.9932 +2025-06-25 06:10:24,901 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:10:24,908 - pyskl - INFO - +mean_acc 0.8815 +2025-06-25 06:10:24,909 - pyskl - INFO - Epoch(val) [110][533] top1_acc: 0.9044, top5_acc: 0.9932, mean_class_accuracy: 0.8815 +2025-06-25 06:11:44,556 - pyskl - INFO - Epoch [111][100/1281] lr: 4.121e-03, eta: 6:09:19, time: 0.796, data_time: 0.189, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1037, loss: 0.1037 +2025-06-25 06:12:33,351 - pyskl - INFO - Epoch [111][200/1281] lr: 4.106e-03, eta: 6:08:38, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0858, loss: 0.0858 +2025-06-25 06:13:22,312 - pyskl - INFO - Epoch [111][300/1281] lr: 4.091e-03, eta: 6:07:56, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.0970, loss: 0.0970 +2025-06-25 06:14:11,215 - pyskl - INFO - Epoch [111][400/1281] lr: 4.075e-03, eta: 6:07:15, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.0895, loss: 0.0895 +2025-06-25 06:15:00,166 - pyskl - INFO - Epoch [111][500/1281] lr: 4.060e-03, eta: 6:06:34, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.0819, loss: 0.0819 +2025-06-25 06:15:49,044 - pyskl - INFO - Epoch [111][600/1281] lr: 4.045e-03, eta: 6:05:52, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1074, loss: 0.1074 +2025-06-25 06:16:32,461 - pyskl - INFO - Epoch [111][700/1281] lr: 4.030e-03, eta: 6:05:09, time: 0.434, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.0960, loss: 0.0960 +2025-06-25 06:17:14,594 - pyskl - INFO - Epoch [111][800/1281] lr: 4.015e-03, eta: 6:04:25, time: 0.421, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1051, loss: 0.1051 +2025-06-25 06:17:45,655 - pyskl - INFO - Epoch [111][900/1281] lr: 4.000e-03, eta: 6:03:38, time: 0.311, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1145, loss: 0.1145 +2025-06-25 06:18:25,966 - pyskl - INFO - Epoch [111][1000/1281] lr: 3.985e-03, eta: 6:02:53, time: 0.403, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 0.9994, loss_cls: 0.1032, loss: 0.1032 +2025-06-25 06:19:14,636 - pyskl - INFO - Epoch [111][1100/1281] lr: 3.970e-03, eta: 6:02:12, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0949, loss: 0.0949 +2025-06-25 06:20:03,521 - pyskl - INFO - Epoch [111][1200/1281] lr: 3.955e-03, eta: 6:01:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.0983, loss: 0.0983 +2025-06-25 06:20:43,797 - pyskl - INFO - Saving checkpoint at 111 epochs +2025-06-25 06:21:41,935 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:21:41,990 - pyskl - INFO - +top1_acc 0.8954 +top5_acc 0.9913 +2025-06-25 06:21:41,990 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:21:41,996 - pyskl - INFO - +mean_acc 0.8612 +2025-06-25 06:21:41,998 - pyskl - INFO - Epoch(val) [111][533] top1_acc: 0.8954, top5_acc: 0.9913, mean_class_accuracy: 0.8612 +2025-06-25 06:23:01,253 - pyskl - INFO - Epoch [112][100/1281] lr: 3.928e-03, eta: 6:00:12, time: 0.793, data_time: 0.183, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1265, loss: 0.1265 +2025-06-25 06:23:50,203 - pyskl - INFO - Epoch [112][200/1281] lr: 3.914e-03, eta: 5:59:31, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1109, loss: 0.1109 +2025-06-25 06:24:39,166 - pyskl - INFO - Epoch [112][300/1281] lr: 3.899e-03, eta: 5:58:49, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1047, loss: 0.1047 +2025-06-25 06:25:27,926 - pyskl - INFO - Epoch [112][400/1281] lr: 3.884e-03, eta: 5:58:08, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1222, loss: 0.1222 +2025-06-25 06:26:17,240 - pyskl - INFO - Epoch [112][500/1281] lr: 3.869e-03, eta: 5:57:27, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0882, loss: 0.0882 +2025-06-25 06:27:06,387 - pyskl - INFO - Epoch [112][600/1281] lr: 3.854e-03, eta: 5:56:45, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1082, loss: 0.1082 +2025-06-25 06:27:50,569 - pyskl - INFO - Epoch [112][700/1281] lr: 3.840e-03, eta: 5:56:02, time: 0.442, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1103, loss: 0.1103 +2025-06-25 06:28:35,804 - pyskl - INFO - Epoch [112][800/1281] lr: 3.825e-03, eta: 5:55:19, time: 0.452, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1333, loss: 0.1333 +2025-06-25 06:29:04,239 - pyskl - INFO - Epoch [112][900/1281] lr: 3.810e-03, eta: 5:54:31, time: 0.284, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0886, loss: 0.0886 +2025-06-25 06:29:45,670 - pyskl - INFO - Epoch [112][1000/1281] lr: 3.795e-03, eta: 5:53:47, time: 0.414, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 0.9994, loss_cls: 0.1133, loss: 0.1133 +2025-06-25 06:30:34,484 - pyskl - INFO - Epoch [112][1100/1281] lr: 3.781e-03, eta: 5:53:05, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1132, loss: 0.1132 +2025-06-25 06:31:23,147 - pyskl - INFO - Epoch [112][1200/1281] lr: 3.766e-03, eta: 5:52:24, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0995, loss: 0.0995 +2025-06-25 06:32:03,192 - pyskl - INFO - Saving checkpoint at 112 epochs +2025-06-25 06:33:00,967 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:33:01,022 - pyskl - INFO - +top1_acc 0.9033 +top5_acc 0.9916 +2025-06-25 06:33:01,022 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:33:01,028 - pyskl - INFO - +mean_acc 0.8716 +2025-06-25 06:33:01,030 - pyskl - INFO - Epoch(val) [112][533] top1_acc: 0.9033, top5_acc: 0.9916, mean_class_accuracy: 0.8716 +2025-06-25 06:34:20,332 - pyskl - INFO - Epoch [113][100/1281] lr: 3.740e-03, eta: 5:51:06, time: 0.793, data_time: 0.184, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1111, loss: 0.1111 +2025-06-25 06:35:09,232 - pyskl - INFO - Epoch [113][200/1281] lr: 3.725e-03, eta: 5:50:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1294, loss: 0.1294 +2025-06-25 06:35:58,146 - pyskl - INFO - Epoch [113][300/1281] lr: 3.711e-03, eta: 5:49:43, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0819, loss: 0.0819 +2025-06-25 06:36:47,142 - pyskl - INFO - Epoch [113][400/1281] lr: 3.696e-03, eta: 5:49:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.1064, loss: 0.1064 +2025-06-25 06:37:36,460 - pyskl - INFO - Epoch [113][500/1281] lr: 3.682e-03, eta: 5:48:20, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1391, loss: 0.1391 +2025-06-25 06:38:25,640 - pyskl - INFO - Epoch [113][600/1281] lr: 3.667e-03, eta: 5:47:38, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.1055, loss: 0.1055 +2025-06-25 06:39:09,232 - pyskl - INFO - Epoch [113][700/1281] lr: 3.653e-03, eta: 5:46:55, time: 0.436, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0885, loss: 0.0885 +2025-06-25 06:39:52,638 - pyskl - INFO - Epoch [113][800/1281] lr: 3.638e-03, eta: 5:46:12, time: 0.434, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0813, loss: 0.0813 +2025-06-25 06:40:22,423 - pyskl - INFO - Epoch [113][900/1281] lr: 3.624e-03, eta: 5:45:24, time: 0.298, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0909, loss: 0.0909 +2025-06-25 06:41:01,814 - pyskl - INFO - Epoch [113][1000/1281] lr: 3.610e-03, eta: 5:44:39, time: 0.394, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1148, loss: 0.1148 +2025-06-25 06:41:50,481 - pyskl - INFO - Epoch [113][1100/1281] lr: 3.595e-03, eta: 5:43:57, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 0.9994, loss_cls: 0.1078, loss: 0.1078 +2025-06-25 06:42:39,296 - pyskl - INFO - Epoch [113][1200/1281] lr: 3.581e-03, eta: 5:43:16, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 0.1242, loss: 0.1242 +2025-06-25 06:43:19,317 - pyskl - INFO - Saving checkpoint at 113 epochs +2025-06-25 06:44:17,934 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:44:17,989 - pyskl - INFO - +top1_acc 0.9061 +top5_acc 0.9923 +2025-06-25 06:44:17,989 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:44:17,995 - pyskl - INFO - +mean_acc 0.8799 +2025-06-25 06:44:17,997 - pyskl - INFO - Epoch(val) [113][533] top1_acc: 0.9061, top5_acc: 0.9923, mean_class_accuracy: 0.8799 +2025-06-25 06:45:37,224 - pyskl - INFO - Epoch [114][100/1281] lr: 3.555e-03, eta: 5:41:58, time: 0.792, data_time: 0.183, memory: 4083, top1_acc: 0.9844, top5_acc: 0.9994, loss_cls: 0.1100, loss: 0.1100 +2025-06-25 06:46:26,015 - pyskl - INFO - Epoch [114][200/1281] lr: 3.541e-03, eta: 5:41:16, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0843, loss: 0.0843 +2025-06-25 06:47:15,032 - pyskl - INFO - Epoch [114][300/1281] lr: 3.526e-03, eta: 5:40:34, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1276, loss: 0.1276 +2025-06-25 06:48:03,889 - pyskl - INFO - Epoch [114][400/1281] lr: 3.512e-03, eta: 5:39:53, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0940, loss: 0.0940 +2025-06-25 06:48:53,024 - pyskl - INFO - Epoch [114][500/1281] lr: 3.498e-03, eta: 5:39:11, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0784, loss: 0.0784 +2025-06-25 06:49:41,808 - pyskl - INFO - Epoch [114][600/1281] lr: 3.484e-03, eta: 5:38:30, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0822, loss: 0.0822 +2025-06-25 06:50:27,019 - pyskl - INFO - Epoch [114][700/1281] lr: 3.470e-03, eta: 5:37:47, time: 0.452, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0905, loss: 0.0905 +2025-06-25 06:51:06,718 - pyskl - INFO - Epoch [114][800/1281] lr: 3.456e-03, eta: 5:37:02, time: 0.397, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0785, loss: 0.0785 +2025-06-25 06:51:40,249 - pyskl - INFO - Epoch [114][900/1281] lr: 3.442e-03, eta: 5:36:16, time: 0.335, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0764, loss: 0.0764 +2025-06-25 06:52:18,358 - pyskl - INFO - Epoch [114][1000/1281] lr: 3.427e-03, eta: 5:35:31, time: 0.381, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0897, loss: 0.0897 +2025-06-25 06:53:06,965 - pyskl - INFO - Epoch [114][1100/1281] lr: 3.413e-03, eta: 5:34:49, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0884, loss: 0.0884 +2025-06-25 06:53:55,670 - pyskl - INFO - Epoch [114][1200/1281] lr: 3.399e-03, eta: 5:34:07, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.0886, loss: 0.0886 +2025-06-25 06:54:35,657 - pyskl - INFO - Saving checkpoint at 114 epochs +2025-06-25 06:55:33,447 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:55:33,522 - pyskl - INFO - +top1_acc 0.9096 +top5_acc 0.9919 +2025-06-25 06:55:33,522 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:55:33,530 - pyskl - INFO - +mean_acc 0.8849 +2025-06-25 06:55:33,532 - pyskl - INFO - Epoch(val) [114][533] top1_acc: 0.9096, top5_acc: 0.9919, mean_class_accuracy: 0.8849 +2025-06-25 06:56:51,663 - pyskl - INFO - Epoch [115][100/1281] lr: 3.374e-03, eta: 5:32:48, time: 0.781, data_time: 0.183, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0702, loss: 0.0702 +2025-06-25 06:57:40,286 - pyskl - INFO - Epoch [115][200/1281] lr: 3.360e-03, eta: 5:32:07, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0744, loss: 0.0744 +2025-06-25 06:58:29,382 - pyskl - INFO - Epoch [115][300/1281] lr: 3.346e-03, eta: 5:31:25, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.0865, loss: 0.0865 +2025-06-25 06:59:18,223 - pyskl - INFO - Epoch [115][400/1281] lr: 3.332e-03, eta: 5:30:43, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0737, loss: 0.0737 +2025-06-25 07:00:06,999 - pyskl - INFO - Epoch [115][500/1281] lr: 3.318e-03, eta: 5:30:02, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0642, loss: 0.0642 +2025-06-25 07:00:56,145 - pyskl - INFO - Epoch [115][600/1281] lr: 3.305e-03, eta: 5:29:20, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0724, loss: 0.0724 +2025-06-25 07:01:44,243 - pyskl - INFO - Epoch [115][700/1281] lr: 3.291e-03, eta: 5:28:38, time: 0.481, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0830, loss: 0.0830 +2025-06-25 07:02:18,426 - pyskl - INFO - Epoch [115][800/1281] lr: 3.277e-03, eta: 5:27:52, time: 0.342, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1007, loss: 0.1007 +2025-06-25 07:02:57,711 - pyskl - INFO - Epoch [115][900/1281] lr: 3.263e-03, eta: 5:27:07, time: 0.393, data_time: 0.001, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1022, loss: 0.1022 +2025-06-25 07:03:34,068 - pyskl - INFO - Epoch [115][1000/1281] lr: 3.249e-03, eta: 5:26:21, time: 0.364, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.0949, loss: 0.0949 +2025-06-25 07:04:22,632 - pyskl - INFO - Epoch [115][1100/1281] lr: 3.236e-03, eta: 5:25:40, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0877, loss: 0.0877 +2025-06-25 07:05:11,431 - pyskl - INFO - Epoch [115][1200/1281] lr: 3.222e-03, eta: 5:24:58, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.0925, loss: 0.0925 +2025-06-25 07:05:51,755 - pyskl - INFO - Saving checkpoint at 115 epochs +2025-06-25 07:06:50,007 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:06:50,063 - pyskl - INFO - +top1_acc 0.9099 +top5_acc 0.9925 +2025-06-25 07:06:50,063 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:06:50,070 - pyskl - INFO - +mean_acc 0.8890 +2025-06-25 07:06:50,072 - pyskl - INFO - Epoch(val) [115][533] top1_acc: 0.9099, top5_acc: 0.9925, mean_class_accuracy: 0.8890 +2025-06-25 07:08:08,817 - pyskl - INFO - Epoch [116][100/1281] lr: 3.197e-03, eta: 5:23:39, time: 0.787, data_time: 0.187, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0682, loss: 0.0682 +2025-06-25 07:08:57,754 - pyskl - INFO - Epoch [116][200/1281] lr: 3.184e-03, eta: 5:22:58, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0505, loss: 0.0505 +2025-06-25 07:09:46,790 - pyskl - INFO - Epoch [116][300/1281] lr: 3.170e-03, eta: 5:22:16, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0464, loss: 0.0464 +2025-06-25 07:10:36,055 - pyskl - INFO - Epoch [116][400/1281] lr: 3.156e-03, eta: 5:21:34, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0492, loss: 0.0492 +2025-06-25 07:11:24,934 - pyskl - INFO - Epoch [116][500/1281] lr: 3.143e-03, eta: 5:20:52, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0577, loss: 0.0577 +2025-06-25 07:12:13,872 - pyskl - INFO - Epoch [116][600/1281] lr: 3.129e-03, eta: 5:20:11, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0706, loss: 0.0706 +2025-06-25 07:13:01,951 - pyskl - INFO - Epoch [116][700/1281] lr: 3.116e-03, eta: 5:19:29, time: 0.481, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0627, loss: 0.0627 +2025-06-25 07:13:37,057 - pyskl - INFO - Epoch [116][800/1281] lr: 3.102e-03, eta: 5:18:43, time: 0.351, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0851, loss: 0.0851 +2025-06-25 07:14:16,032 - pyskl - INFO - Epoch [116][900/1281] lr: 3.089e-03, eta: 5:17:58, time: 0.390, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0740, loss: 0.0740 +2025-06-25 07:14:53,883 - pyskl - INFO - Epoch [116][1000/1281] lr: 3.075e-03, eta: 5:17:13, time: 0.378, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0694, loss: 0.0694 +2025-06-25 07:15:42,667 - pyskl - INFO - Epoch [116][1100/1281] lr: 3.062e-03, eta: 5:16:31, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0769, loss: 0.0769 +2025-06-25 07:16:31,243 - pyskl - INFO - Epoch [116][1200/1281] lr: 3.049e-03, eta: 5:15:49, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0827, loss: 0.0827 +2025-06-25 07:17:11,152 - pyskl - INFO - Saving checkpoint at 116 epochs +2025-06-25 07:18:09,182 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:18:09,248 - pyskl - INFO - +top1_acc 0.9127 +top5_acc 0.9923 +2025-06-25 07:18:09,248 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:18:09,256 - pyskl - INFO - +mean_acc 0.8842 +2025-06-25 07:18:09,261 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_106.pth was removed +2025-06-25 07:18:09,426 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_116.pth. +2025-06-25 07:18:09,426 - pyskl - INFO - Best top1_acc is 0.9127 at 116 epoch. +2025-06-25 07:18:09,429 - pyskl - INFO - Epoch(val) [116][533] top1_acc: 0.9127, top5_acc: 0.9923, mean_class_accuracy: 0.8842 +2025-06-25 07:19:28,959 - pyskl - INFO - Epoch [117][100/1281] lr: 3.024e-03, eta: 5:14:31, time: 0.795, data_time: 0.186, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0609, loss: 0.0609 +2025-06-25 07:20:17,842 - pyskl - INFO - Epoch [117][200/1281] lr: 3.011e-03, eta: 5:13:49, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.0839, loss: 0.0839 +2025-06-25 07:21:06,917 - pyskl - INFO - Epoch [117][300/1281] lr: 2.998e-03, eta: 5:13:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0718, loss: 0.0718 +2025-06-25 07:21:55,962 - pyskl - INFO - Epoch [117][400/1281] lr: 2.984e-03, eta: 5:12:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 0.9994, loss_cls: 0.0881, loss: 0.0881 +2025-06-25 07:22:44,791 - pyskl - INFO - Epoch [117][500/1281] lr: 2.971e-03, eta: 5:11:43, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0627, loss: 0.0627 +2025-06-25 07:23:33,538 - pyskl - INFO - Epoch [117][600/1281] lr: 2.958e-03, eta: 5:11:02, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0509, loss: 0.0509 +2025-06-25 07:24:19,445 - pyskl - INFO - Epoch [117][700/1281] lr: 2.945e-03, eta: 5:10:19, time: 0.459, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 0.9994, loss_cls: 0.0673, loss: 0.0673 +2025-06-25 07:25:01,105 - pyskl - INFO - Epoch [117][800/1281] lr: 2.932e-03, eta: 5:09:35, time: 0.417, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0601, loss: 0.0601 +2025-06-25 07:25:33,247 - pyskl - INFO - Epoch [117][900/1281] lr: 2.919e-03, eta: 5:08:48, time: 0.321, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0772, loss: 0.0772 +2025-06-25 07:26:13,815 - pyskl - INFO - Epoch [117][1000/1281] lr: 2.905e-03, eta: 5:08:04, time: 0.406, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0585, loss: 0.0585 +2025-06-25 07:27:02,524 - pyskl - INFO - Epoch [117][1100/1281] lr: 2.892e-03, eta: 5:07:22, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0434, loss: 0.0434 +2025-06-25 07:27:50,928 - pyskl - INFO - Epoch [117][1200/1281] lr: 2.879e-03, eta: 5:06:40, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.0932, loss: 0.0932 +2025-06-25 07:28:31,266 - pyskl - INFO - Saving checkpoint at 117 epochs +2025-06-25 07:29:29,811 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:29:29,866 - pyskl - INFO - +top1_acc 0.9123 +top5_acc 0.9926 +2025-06-25 07:29:29,866 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:29:29,872 - pyskl - INFO - +mean_acc 0.8771 +2025-06-25 07:29:29,874 - pyskl - INFO - Epoch(val) [117][533] top1_acc: 0.9123, top5_acc: 0.9926, mean_class_accuracy: 0.8771 +2025-06-25 07:30:48,128 - pyskl - INFO - Epoch [118][100/1281] lr: 2.856e-03, eta: 5:05:21, time: 0.782, data_time: 0.178, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0683, loss: 0.0683 +2025-06-25 07:31:36,826 - pyskl - INFO - Epoch [118][200/1281] lr: 2.843e-03, eta: 5:04:39, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0509, loss: 0.0509 +2025-06-25 07:32:25,924 - pyskl - INFO - Epoch [118][300/1281] lr: 2.830e-03, eta: 5:03:57, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0541, loss: 0.0541 +2025-06-25 07:33:14,971 - pyskl - INFO - Epoch [118][400/1281] lr: 2.817e-03, eta: 5:03:15, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0555, loss: 0.0555 +2025-06-25 07:34:03,794 - pyskl - INFO - Epoch [118][500/1281] lr: 2.804e-03, eta: 5:02:34, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0731, loss: 0.0731 +2025-06-25 07:34:52,433 - pyskl - INFO - Epoch [118][600/1281] lr: 2.791e-03, eta: 5:01:51, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0570, loss: 0.0570 +2025-06-25 07:35:36,849 - pyskl - INFO - Epoch [118][700/1281] lr: 2.778e-03, eta: 5:01:08, time: 0.444, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0540, loss: 0.0540 +2025-06-25 07:36:17,957 - pyskl - INFO - Epoch [118][800/1281] lr: 2.765e-03, eta: 5:00:24, time: 0.411, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0610, loss: 0.0610 +2025-06-25 07:36:50,886 - pyskl - INFO - Epoch [118][900/1281] lr: 2.753e-03, eta: 4:59:38, time: 0.329, data_time: 0.001, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0617, loss: 0.0617 +2025-06-25 07:37:31,631 - pyskl - INFO - Epoch [118][1000/1281] lr: 2.740e-03, eta: 4:58:54, time: 0.407, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 0.9994, loss_cls: 0.0669, loss: 0.0669 +2025-06-25 07:38:20,684 - pyskl - INFO - Epoch [118][1100/1281] lr: 2.727e-03, eta: 4:58:12, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0687, loss: 0.0687 +2025-06-25 07:39:09,269 - pyskl - INFO - Epoch [118][1200/1281] lr: 2.714e-03, eta: 4:57:30, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0590, loss: 0.0590 +2025-06-25 07:39:49,516 - pyskl - INFO - Saving checkpoint at 118 epochs +2025-06-25 07:40:47,152 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:40:47,209 - pyskl - INFO - +top1_acc 0.9152 +top5_acc 0.9926 +2025-06-25 07:40:47,209 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:40:47,216 - pyskl - INFO - +mean_acc 0.8862 +2025-06-25 07:40:47,220 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_116.pth was removed +2025-06-25 07:40:47,384 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_118.pth. +2025-06-25 07:40:47,384 - pyskl - INFO - Best top1_acc is 0.9152 at 118 epoch. +2025-06-25 07:40:47,387 - pyskl - INFO - Epoch(val) [118][533] top1_acc: 0.9152, top5_acc: 0.9926, mean_class_accuracy: 0.8862 +2025-06-25 07:42:07,109 - pyskl - INFO - Epoch [119][100/1281] lr: 2.691e-03, eta: 4:56:11, time: 0.797, data_time: 0.184, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0502, loss: 0.0502 +2025-06-25 07:42:55,962 - pyskl - INFO - Epoch [119][200/1281] lr: 2.679e-03, eta: 4:55:29, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0553, loss: 0.0553 +2025-06-25 07:43:45,162 - pyskl - INFO - Epoch [119][300/1281] lr: 2.666e-03, eta: 4:54:47, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0459, loss: 0.0459 +2025-06-25 07:44:33,788 - pyskl - INFO - Epoch [119][400/1281] lr: 2.653e-03, eta: 4:54:05, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0431, loss: 0.0431 +2025-06-25 07:45:22,451 - pyskl - INFO - Epoch [119][500/1281] lr: 2.641e-03, eta: 4:53:23, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0384, loss: 0.0384 +2025-06-25 07:46:11,337 - pyskl - INFO - Epoch [119][600/1281] lr: 2.628e-03, eta: 4:52:41, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0769, loss: 0.0769 +2025-06-25 07:46:55,177 - pyskl - INFO - Epoch [119][700/1281] lr: 2.616e-03, eta: 4:51:58, time: 0.438, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0761, loss: 0.0761 +2025-06-25 07:47:38,731 - pyskl - INFO - Epoch [119][800/1281] lr: 2.603e-03, eta: 4:51:14, time: 0.436, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0695, loss: 0.0695 +2025-06-25 07:48:08,096 - pyskl - INFO - Epoch [119][900/1281] lr: 2.591e-03, eta: 4:50:27, time: 0.294, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0812, loss: 0.0812 +2025-06-25 07:48:50,991 - pyskl - INFO - Epoch [119][1000/1281] lr: 2.578e-03, eta: 4:49:43, time: 0.429, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0521, loss: 0.0521 +2025-06-25 07:49:39,720 - pyskl - INFO - Epoch [119][1100/1281] lr: 2.566e-03, eta: 4:49:01, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0740, loss: 0.0740 +2025-06-25 07:50:28,417 - pyskl - INFO - Epoch [119][1200/1281] lr: 2.554e-03, eta: 4:48:19, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0695, loss: 0.0695 +2025-06-25 07:51:08,809 - pyskl - INFO - Saving checkpoint at 119 epochs +2025-06-25 07:52:06,301 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:52:06,361 - pyskl - INFO - +top1_acc 0.9098 +top5_acc 0.9928 +2025-06-25 07:52:06,361 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:52:06,367 - pyskl - INFO - +mean_acc 0.8808 +2025-06-25 07:52:06,369 - pyskl - INFO - Epoch(val) [119][533] top1_acc: 0.9098, top5_acc: 0.9928, mean_class_accuracy: 0.8808 +2025-06-25 07:53:26,500 - pyskl - INFO - Epoch [120][100/1281] lr: 2.531e-03, eta: 4:47:01, time: 0.801, data_time: 0.186, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0702, loss: 0.0702 +2025-06-25 07:54:15,748 - pyskl - INFO - Epoch [120][200/1281] lr: 2.519e-03, eta: 4:46:19, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0519, loss: 0.0519 +2025-06-25 07:55:04,624 - pyskl - INFO - Epoch [120][300/1281] lr: 2.507e-03, eta: 4:45:37, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0485, loss: 0.0485 +2025-06-25 07:55:53,879 - pyskl - INFO - Epoch [120][400/1281] lr: 2.494e-03, eta: 4:44:55, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0614, loss: 0.0614 +2025-06-25 07:56:42,902 - pyskl - INFO - Epoch [120][500/1281] lr: 2.482e-03, eta: 4:44:13, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0411, loss: 0.0411 +2025-06-25 07:57:31,775 - pyskl - INFO - Epoch [120][600/1281] lr: 2.470e-03, eta: 4:43:31, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0453, loss: 0.0453 +2025-06-25 07:58:12,867 - pyskl - INFO - Epoch [120][700/1281] lr: 2.458e-03, eta: 4:42:47, time: 0.411, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0633, loss: 0.0633 +2025-06-25 07:59:03,205 - pyskl - INFO - Epoch [120][800/1281] lr: 2.446e-03, eta: 4:42:05, time: 0.503, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0473, loss: 0.0473 +2025-06-25 07:59:26,862 - pyskl - INFO - Epoch [120][900/1281] lr: 2.433e-03, eta: 4:41:16, time: 0.237, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0415, loss: 0.0415 +2025-06-25 08:00:10,582 - pyskl - INFO - Epoch [120][1000/1281] lr: 2.421e-03, eta: 4:40:33, time: 0.437, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0509, loss: 0.0509 +2025-06-25 08:00:59,303 - pyskl - INFO - Epoch [120][1100/1281] lr: 2.409e-03, eta: 4:39:51, time: 0.487, data_time: 0.001, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0565, loss: 0.0565 +2025-06-25 08:01:48,141 - pyskl - INFO - Epoch [120][1200/1281] lr: 2.397e-03, eta: 4:39:09, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0408, loss: 0.0408 +2025-06-25 08:02:28,410 - pyskl - INFO - Saving checkpoint at 120 epochs +2025-06-25 08:03:26,574 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:03:26,641 - pyskl - INFO - +top1_acc 0.9187 +top5_acc 0.9934 +2025-06-25 08:03:26,641 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:03:26,648 - pyskl - INFO - +mean_acc 0.8934 +2025-06-25 08:03:26,653 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_118.pth was removed +2025-06-25 08:03:26,866 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_120.pth. +2025-06-25 08:03:26,867 - pyskl - INFO - Best top1_acc is 0.9187 at 120 epoch. +2025-06-25 08:03:26,869 - pyskl - INFO - Epoch(val) [120][533] top1_acc: 0.9187, top5_acc: 0.9934, mean_class_accuracy: 0.8934 +2025-06-25 08:04:47,652 - pyskl - INFO - Epoch [121][100/1281] lr: 2.375e-03, eta: 4:37:50, time: 0.808, data_time: 0.185, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0533, loss: 0.0533 +2025-06-25 08:05:36,409 - pyskl - INFO - Epoch [121][200/1281] lr: 2.363e-03, eta: 4:37:08, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0344, loss: 0.0344 +2025-06-25 08:06:25,529 - pyskl - INFO - Epoch [121][300/1281] lr: 2.351e-03, eta: 4:36:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0431, loss: 0.0431 +2025-06-25 08:07:14,341 - pyskl - INFO - Epoch [121][400/1281] lr: 2.340e-03, eta: 4:35:44, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0505, loss: 0.0505 +2025-06-25 08:08:03,085 - pyskl - INFO - Epoch [121][500/1281] lr: 2.328e-03, eta: 4:35:02, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0413, loss: 0.0413 +2025-06-25 08:08:51,964 - pyskl - INFO - Epoch [121][600/1281] lr: 2.316e-03, eta: 4:34:19, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0414, loss: 0.0414 +2025-06-25 08:09:29,889 - pyskl - INFO - Epoch [121][700/1281] lr: 2.304e-03, eta: 4:33:35, time: 0.379, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0485, loss: 0.0485 +2025-06-25 08:10:20,775 - pyskl - INFO - Epoch [121][800/1281] lr: 2.292e-03, eta: 4:32:53, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0361, loss: 0.0361 +2025-06-25 08:10:44,788 - pyskl - INFO - Epoch [121][900/1281] lr: 2.280e-03, eta: 4:32:05, time: 0.240, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0393, loss: 0.0393 +2025-06-25 08:11:30,617 - pyskl - INFO - Epoch [121][1000/1281] lr: 2.269e-03, eta: 4:31:22, time: 0.458, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0524, loss: 0.0524 +2025-06-25 08:12:19,522 - pyskl - INFO - Epoch [121][1100/1281] lr: 2.257e-03, eta: 4:30:40, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0589, loss: 0.0589 +2025-06-25 08:13:08,360 - pyskl - INFO - Epoch [121][1200/1281] lr: 2.245e-03, eta: 4:29:57, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0611, loss: 0.0611 +2025-06-25 08:13:48,472 - pyskl - INFO - Saving checkpoint at 121 epochs +2025-06-25 08:14:46,670 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:14:46,726 - pyskl - INFO - +top1_acc 0.9223 +top5_acc 0.9941 +2025-06-25 08:14:46,726 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:14:46,733 - pyskl - INFO - +mean_acc 0.8979 +2025-06-25 08:14:46,737 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_120.pth was removed +2025-06-25 08:14:46,904 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_121.pth. +2025-06-25 08:14:46,905 - pyskl - INFO - Best top1_acc is 0.9223 at 121 epoch. +2025-06-25 08:14:46,907 - pyskl - INFO - Epoch(val) [121][533] top1_acc: 0.9223, top5_acc: 0.9941, mean_class_accuracy: 0.8979 +2025-06-25 08:16:05,912 - pyskl - INFO - Epoch [122][100/1281] lr: 2.224e-03, eta: 4:28:39, time: 0.790, data_time: 0.182, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0375, loss: 0.0375 +2025-06-25 08:16:54,774 - pyskl - INFO - Epoch [122][200/1281] lr: 2.212e-03, eta: 4:27:56, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0466, loss: 0.0466 +2025-06-25 08:17:43,610 - pyskl - INFO - Epoch [122][300/1281] lr: 2.201e-03, eta: 4:27:14, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0310, loss: 0.0310 +2025-06-25 08:18:32,295 - pyskl - INFO - Epoch [122][400/1281] lr: 2.189e-03, eta: 4:26:32, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0467, loss: 0.0467 +2025-06-25 08:19:21,160 - pyskl - INFO - Epoch [122][500/1281] lr: 2.178e-03, eta: 4:25:50, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0515, loss: 0.0515 +2025-06-25 08:20:10,103 - pyskl - INFO - Epoch [122][600/1281] lr: 2.166e-03, eta: 4:25:07, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0364, loss: 0.0364 +2025-06-25 08:20:45,587 - pyskl - INFO - Epoch [122][700/1281] lr: 2.155e-03, eta: 4:24:22, time: 0.355, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0287, loss: 0.0287 +2025-06-25 08:21:36,545 - pyskl - INFO - Epoch [122][800/1281] lr: 2.143e-03, eta: 4:23:40, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0297, loss: 0.0297 +2025-06-25 08:22:01,185 - pyskl - INFO - Epoch [122][900/1281] lr: 2.132e-03, eta: 4:22:52, time: 0.246, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0293, loss: 0.0293 +2025-06-25 08:22:47,900 - pyskl - INFO - Epoch [122][1000/1281] lr: 2.120e-03, eta: 4:22:09, time: 0.467, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0377, loss: 0.0377 +2025-06-25 08:23:36,421 - pyskl - INFO - Epoch [122][1100/1281] lr: 2.109e-03, eta: 4:21:27, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0332, loss: 0.0332 +2025-06-25 08:24:25,240 - pyskl - INFO - Epoch [122][1200/1281] lr: 2.098e-03, eta: 4:20:45, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0389, loss: 0.0389 +2025-06-25 08:25:05,425 - pyskl - INFO - Saving checkpoint at 122 epochs +2025-06-25 08:26:03,760 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:26:03,815 - pyskl - INFO - +top1_acc 0.9200 +top5_acc 0.9941 +2025-06-25 08:26:03,816 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:26:03,822 - pyskl - INFO - +mean_acc 0.8966 +2025-06-25 08:26:03,823 - pyskl - INFO - Epoch(val) [122][533] top1_acc: 0.9200, top5_acc: 0.9941, mean_class_accuracy: 0.8966 +2025-06-25 08:27:23,036 - pyskl - INFO - Epoch [123][100/1281] lr: 2.077e-03, eta: 4:19:26, time: 0.792, data_time: 0.185, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0314, loss: 0.0314 +2025-06-25 08:28:11,821 - pyskl - INFO - Epoch [123][200/1281] lr: 2.066e-03, eta: 4:18:44, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0351, loss: 0.0351 +2025-06-25 08:29:00,848 - pyskl - INFO - Epoch [123][300/1281] lr: 2.055e-03, eta: 4:18:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0330, loss: 0.0330 +2025-06-25 08:29:49,702 - pyskl - INFO - Epoch [123][400/1281] lr: 2.044e-03, eta: 4:17:19, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0293, loss: 0.0293 +2025-06-25 08:30:38,783 - pyskl - INFO - Epoch [123][500/1281] lr: 2.032e-03, eta: 4:16:37, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0412, loss: 0.0412 +2025-06-25 08:31:27,769 - pyskl - INFO - Epoch [123][600/1281] lr: 2.021e-03, eta: 4:15:55, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0300, loss: 0.0300 +2025-06-25 08:32:03,422 - pyskl - INFO - Epoch [123][700/1281] lr: 2.010e-03, eta: 4:15:09, time: 0.357, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0416, loss: 0.0416 +2025-06-25 08:32:54,279 - pyskl - INFO - Epoch [123][800/1281] lr: 1.999e-03, eta: 4:14:27, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0406, loss: 0.0406 +2025-06-25 08:33:18,933 - pyskl - INFO - Epoch [123][900/1281] lr: 1.988e-03, eta: 4:13:40, time: 0.247, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0634, loss: 0.0634 +2025-06-25 08:34:05,539 - pyskl - INFO - Epoch [123][1000/1281] lr: 1.977e-03, eta: 4:12:57, time: 0.466, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0440, loss: 0.0440 +2025-06-25 08:34:54,115 - pyskl - INFO - Epoch [123][1100/1281] lr: 1.966e-03, eta: 4:12:14, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0421, loss: 0.0421 +2025-06-25 08:35:42,560 - pyskl - INFO - Epoch [123][1200/1281] lr: 1.955e-03, eta: 4:11:32, time: 0.484, data_time: 0.001, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0312, loss: 0.0312 +2025-06-25 08:36:22,428 - pyskl - INFO - Saving checkpoint at 123 epochs +2025-06-25 08:37:20,861 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:37:20,918 - pyskl - INFO - +top1_acc 0.9198 +top5_acc 0.9927 +2025-06-25 08:37:20,919 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:37:20,925 - pyskl - INFO - +mean_acc 0.8947 +2025-06-25 08:37:20,927 - pyskl - INFO - Epoch(val) [123][533] top1_acc: 0.9198, top5_acc: 0.9927, mean_class_accuracy: 0.8947 +2025-06-25 08:38:40,221 - pyskl - INFO - Epoch [124][100/1281] lr: 1.935e-03, eta: 4:10:13, time: 0.793, data_time: 0.187, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0330, loss: 0.0330 +2025-06-25 08:39:28,925 - pyskl - INFO - Epoch [124][200/1281] lr: 1.924e-03, eta: 4:09:31, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0402, loss: 0.0402 +2025-06-25 08:40:17,823 - pyskl - INFO - Epoch [124][300/1281] lr: 1.913e-03, eta: 4:08:48, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0286, loss: 0.0286 +2025-06-25 08:41:06,875 - pyskl - INFO - Epoch [124][400/1281] lr: 1.902e-03, eta: 4:08:06, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0402, loss: 0.0402 +2025-06-25 08:41:55,770 - pyskl - INFO - Epoch [124][500/1281] lr: 1.892e-03, eta: 4:07:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0292, loss: 0.0292 +2025-06-25 08:42:44,345 - pyskl - INFO - Epoch [124][600/1281] lr: 1.881e-03, eta: 4:06:41, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0336, loss: 0.0336 +2025-06-25 08:43:18,968 - pyskl - INFO - Epoch [124][700/1281] lr: 1.870e-03, eta: 4:05:56, time: 0.346, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0355, loss: 0.0355 +2025-06-25 08:44:09,950 - pyskl - INFO - Epoch [124][800/1281] lr: 1.859e-03, eta: 4:05:14, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0238, loss: 0.0238 +2025-06-25 08:44:34,983 - pyskl - INFO - Epoch [124][900/1281] lr: 1.849e-03, eta: 4:04:26, time: 0.250, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0236, loss: 0.0236 +2025-06-25 08:45:23,103 - pyskl - INFO - Epoch [124][1000/1281] lr: 1.838e-03, eta: 4:03:44, time: 0.481, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0312, loss: 0.0312 +2025-06-25 08:46:12,055 - pyskl - INFO - Epoch [124][1100/1281] lr: 1.827e-03, eta: 4:03:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0291, loss: 0.0291 +2025-06-25 08:47:00,928 - pyskl - INFO - Epoch [124][1200/1281] lr: 1.817e-03, eta: 4:02:19, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0302, loss: 0.0302 +2025-06-25 08:47:41,256 - pyskl - INFO - Saving checkpoint at 124 epochs +2025-06-25 08:48:38,774 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:48:38,829 - pyskl - INFO - +top1_acc 0.9223 +top5_acc 0.9950 +2025-06-25 08:48:38,829 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:48:38,836 - pyskl - INFO - +mean_acc 0.8959 +2025-06-25 08:48:38,837 - pyskl - INFO - Epoch(val) [124][533] top1_acc: 0.9223, top5_acc: 0.9950, mean_class_accuracy: 0.8959 +2025-06-25 08:49:58,542 - pyskl - INFO - Epoch [125][100/1281] lr: 1.797e-03, eta: 4:01:00, time: 0.797, data_time: 0.185, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0253, loss: 0.0253 +2025-06-25 08:50:47,561 - pyskl - INFO - Epoch [125][200/1281] lr: 1.787e-03, eta: 4:00:18, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0292, loss: 0.0292 +2025-06-25 08:51:36,496 - pyskl - INFO - Epoch [125][300/1281] lr: 1.776e-03, eta: 3:59:36, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0246, loss: 0.0246 +2025-06-25 08:52:25,598 - pyskl - INFO - Epoch [125][400/1281] lr: 1.766e-03, eta: 3:58:53, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0388, loss: 0.0388 +2025-06-25 08:53:14,329 - pyskl - INFO - Epoch [125][500/1281] lr: 1.755e-03, eta: 3:58:11, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0254, loss: 0.0254 +2025-06-25 08:54:03,168 - pyskl - INFO - Epoch [125][600/1281] lr: 1.745e-03, eta: 3:57:28, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0251, loss: 0.0251 +2025-06-25 08:54:36,887 - pyskl - INFO - Epoch [125][700/1281] lr: 1.735e-03, eta: 3:56:43, time: 0.337, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0271, loss: 0.0271 +2025-06-25 08:55:27,691 - pyskl - INFO - Epoch [125][800/1281] lr: 1.724e-03, eta: 3:56:00, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0247, loss: 0.0247 +2025-06-25 08:55:54,289 - pyskl - INFO - Epoch [125][900/1281] lr: 1.714e-03, eta: 3:55:13, time: 0.266, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0241, loss: 0.0241 +2025-06-25 08:56:42,996 - pyskl - INFO - Epoch [125][1000/1281] lr: 1.704e-03, eta: 3:54:31, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0235, loss: 0.0235 +2025-06-25 08:57:31,803 - pyskl - INFO - Epoch [125][1100/1281] lr: 1.693e-03, eta: 3:53:48, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 08:58:20,676 - pyskl - INFO - Epoch [125][1200/1281] lr: 1.683e-03, eta: 3:53:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0248, loss: 0.0248 +2025-06-25 08:59:00,762 - pyskl - INFO - Saving checkpoint at 125 epochs +2025-06-25 08:59:58,895 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:59:58,953 - pyskl - INFO - +top1_acc 0.9245 +top5_acc 0.9948 +2025-06-25 08:59:58,954 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:59:58,960 - pyskl - INFO - +mean_acc 0.9000 +2025-06-25 08:59:58,964 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_121.pth was removed +2025-06-25 08:59:59,137 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_125.pth. +2025-06-25 08:59:59,137 - pyskl - INFO - Best top1_acc is 0.9245 at 125 epoch. +2025-06-25 08:59:59,139 - pyskl - INFO - Epoch(val) [125][533] top1_acc: 0.9245, top5_acc: 0.9948, mean_class_accuracy: 0.9000 +2025-06-25 09:01:19,522 - pyskl - INFO - Epoch [126][100/1281] lr: 1.665e-03, eta: 3:51:47, time: 0.804, data_time: 0.188, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0276, loss: 0.0276 +2025-06-25 09:02:08,436 - pyskl - INFO - Epoch [126][200/1281] lr: 1.654e-03, eta: 3:51:05, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-25 09:02:57,146 - pyskl - INFO - Epoch [126][300/1281] lr: 1.644e-03, eta: 3:50:22, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0207, loss: 0.0207 +2025-06-25 09:03:45,920 - pyskl - INFO - Epoch [126][400/1281] lr: 1.634e-03, eta: 3:49:40, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0207, loss: 0.0207 +2025-06-25 09:04:34,931 - pyskl - INFO - Epoch [126][500/1281] lr: 1.624e-03, eta: 3:48:57, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0294, loss: 0.0294 +2025-06-25 09:05:23,684 - pyskl - INFO - Epoch [126][600/1281] lr: 1.614e-03, eta: 3:48:15, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-25 09:05:53,407 - pyskl - INFO - Epoch [126][700/1281] lr: 1.604e-03, eta: 3:47:28, time: 0.297, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0264, loss: 0.0264 +2025-06-25 09:06:44,392 - pyskl - INFO - Epoch [126][800/1281] lr: 1.594e-03, eta: 3:46:46, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0220, loss: 0.0220 +2025-06-25 09:07:13,896 - pyskl - INFO - Epoch [126][900/1281] lr: 1.584e-03, eta: 3:46:00, time: 0.295, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0331, loss: 0.0331 +2025-06-25 09:08:02,440 - pyskl - INFO - Epoch [126][1000/1281] lr: 1.574e-03, eta: 3:45:17, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0290, loss: 0.0290 +2025-06-25 09:08:51,587 - pyskl - INFO - Epoch [126][1100/1281] lr: 1.564e-03, eta: 3:44:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0314, loss: 0.0314 +2025-06-25 09:09:40,301 - pyskl - INFO - Epoch [126][1200/1281] lr: 1.554e-03, eta: 3:43:52, 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 09:10:20,584 - pyskl - INFO - Saving checkpoint at 126 epochs +2025-06-25 09:11:18,267 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:11:18,332 - pyskl - INFO - +top1_acc 0.9242 +top5_acc 0.9939 +2025-06-25 09:11:18,332 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:11:18,339 - pyskl - INFO - +mean_acc 0.9003 +2025-06-25 09:11:18,342 - pyskl - INFO - Epoch(val) [126][533] top1_acc: 0.9242, top5_acc: 0.9939, mean_class_accuracy: 0.9003 +2025-06-25 09:12:38,149 - pyskl - INFO - Epoch [127][100/1281] lr: 1.536e-03, eta: 3:42:34, time: 0.798, data_time: 0.187, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0263, loss: 0.0263 +2025-06-25 09:13:26,854 - pyskl - INFO - Epoch [127][200/1281] lr: 1.527e-03, eta: 3:41:51, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 09:14:15,895 - pyskl - INFO - Epoch [127][300/1281] lr: 1.517e-03, eta: 3:41:08, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0226, loss: 0.0226 +2025-06-25 09:15:04,783 - pyskl - INFO - Epoch [127][400/1281] lr: 1.507e-03, eta: 3:40:26, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0218, loss: 0.0218 +2025-06-25 09:15:53,912 - pyskl - INFO - Epoch [127][500/1281] lr: 1.497e-03, eta: 3:39:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 09:16:42,927 - pyskl - INFO - Epoch [127][600/1281] lr: 1.488e-03, eta: 3:39:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0170, loss: 0.0170 +2025-06-25 09:17:12,000 - pyskl - INFO - Epoch [127][700/1281] lr: 1.478e-03, eta: 3:38:14, time: 0.291, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0215, loss: 0.0215 +2025-06-25 09:18:02,871 - pyskl - INFO - Epoch [127][800/1281] lr: 1.468e-03, eta: 3:37:32, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-25 09:18:31,693 - pyskl - INFO - Epoch [127][900/1281] lr: 1.459e-03, eta: 3:36:46, time: 0.288, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0236, loss: 0.0236 +2025-06-25 09:19:20,477 - pyskl - INFO - Epoch [127][1000/1281] lr: 1.449e-03, eta: 3:36:03, time: 0.488, data_time: 0.001, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0241, loss: 0.0241 +2025-06-25 09:20:09,783 - pyskl - INFO - Epoch [127][1100/1281] lr: 1.440e-03, eta: 3:35:21, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0260, loss: 0.0260 +2025-06-25 09:20:58,491 - pyskl - INFO - Epoch [127][1200/1281] lr: 1.430e-03, eta: 3:34:38, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0245, loss: 0.0245 +2025-06-25 09:21:38,691 - pyskl - INFO - Saving checkpoint at 127 epochs +2025-06-25 09:22:37,073 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:22:37,140 - pyskl - INFO - +top1_acc 0.9229 +top5_acc 0.9945 +2025-06-25 09:22:37,140 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:22:37,147 - pyskl - INFO - +mean_acc 0.9019 +2025-06-25 09:22:37,149 - pyskl - INFO - Epoch(val) [127][533] top1_acc: 0.9229, top5_acc: 0.9945, mean_class_accuracy: 0.9019 +2025-06-25 09:23:55,805 - pyskl - INFO - Epoch [128][100/1281] lr: 1.413e-03, eta: 3:33:19, time: 0.787, data_time: 0.182, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 09:24:45,056 - pyskl - INFO - Epoch [128][200/1281] lr: 1.404e-03, eta: 3:32:37, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0250, loss: 0.0250 +2025-06-25 09:25:33,839 - pyskl - INFO - Epoch [128][300/1281] lr: 1.394e-03, eta: 3:31:54, time: 0.488, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-25 09:26:22,690 - pyskl - INFO - Epoch [128][400/1281] lr: 1.385e-03, eta: 3:31:11, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 09:27:11,897 - pyskl - INFO - Epoch [128][500/1281] lr: 1.376e-03, eta: 3:30:29, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 09:28:01,011 - pyskl - INFO - Epoch [128][600/1281] lr: 1.366e-03, eta: 3:29:46, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 09:28:30,624 - pyskl - INFO - Epoch [128][700/1281] lr: 1.357e-03, eta: 3:29:00, time: 0.296, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0209, loss: 0.0209 +2025-06-25 09:29:21,333 - pyskl - INFO - Epoch [128][800/1281] lr: 1.348e-03, eta: 3:28:18, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0234, loss: 0.0234 +2025-06-25 09:29:51,307 - pyskl - INFO - Epoch [128][900/1281] lr: 1.339e-03, eta: 3:27:32, time: 0.300, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 09:30:40,298 - pyskl - INFO - Epoch [128][1000/1281] lr: 1.329e-03, eta: 3:26:49, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0296, loss: 0.0296 +2025-06-25 09:31:29,209 - pyskl - INFO - Epoch [128][1100/1281] lr: 1.320e-03, eta: 3:26:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0217, loss: 0.0217 +2025-06-25 09:32:17,964 - pyskl - INFO - Epoch [128][1200/1281] lr: 1.311e-03, eta: 3:25:24, time: 0.488, data_time: 0.001, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0222, loss: 0.0222 +2025-06-25 09:32:57,913 - pyskl - INFO - Saving checkpoint at 128 epochs +2025-06-25 09:33:55,817 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:33:55,873 - pyskl - INFO - +top1_acc 0.9250 +top5_acc 0.9944 +2025-06-25 09:33:55,873 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:33:55,880 - pyskl - INFO - +mean_acc 0.9014 +2025-06-25 09:33:55,884 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_125.pth was removed +2025-06-25 09:33:56,059 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_128.pth. +2025-06-25 09:33:56,059 - pyskl - INFO - Best top1_acc is 0.9250 at 128 epoch. +2025-06-25 09:33:56,062 - pyskl - INFO - Epoch(val) [128][533] top1_acc: 0.9250, top5_acc: 0.9944, mean_class_accuracy: 0.9014 +2025-06-25 09:35:14,510 - pyskl - INFO - Epoch [129][100/1281] lr: 1.295e-03, eta: 3:24:05, time: 0.784, data_time: 0.184, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0218, loss: 0.0218 +2025-06-25 09:36:03,277 - pyskl - INFO - Epoch [129][200/1281] lr: 1.286e-03, eta: 3:23:22, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0241, loss: 0.0241 +2025-06-25 09:36:52,397 - pyskl - INFO - Epoch [129][300/1281] lr: 1.277e-03, eta: 3:22:39, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9988, top5_acc: 0.9994, loss_cls: 0.0321, loss: 0.0321 +2025-06-25 09:37:41,152 - pyskl - INFO - Epoch [129][400/1281] lr: 1.268e-03, eta: 3:21:56, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0230, loss: 0.0230 +2025-06-25 09:38:29,962 - pyskl - INFO - Epoch [129][500/1281] lr: 1.259e-03, eta: 3:21:14, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0276, loss: 0.0276 +2025-06-25 09:39:18,988 - pyskl - INFO - Epoch [129][600/1281] lr: 1.250e-03, eta: 3:20:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0241, loss: 0.0241 +2025-06-25 09:39:47,611 - pyskl - INFO - Epoch [129][700/1281] lr: 1.241e-03, eta: 3:19:45, time: 0.286, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0277, loss: 0.0277 +2025-06-25 09:40:38,344 - pyskl - INFO - Epoch [129][800/1281] lr: 1.232e-03, eta: 3:19:02, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0226, loss: 0.0226 +2025-06-25 09:41:09,007 - pyskl - INFO - Epoch [129][900/1281] lr: 1.223e-03, eta: 3:18:17, time: 0.307, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0220, loss: 0.0220 +2025-06-25 09:41:57,634 - pyskl - INFO - Epoch [129][1000/1281] lr: 1.214e-03, eta: 3:17:34, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0243, loss: 0.0243 +2025-06-25 09:42:46,294 - pyskl - INFO - Epoch [129][1100/1281] lr: 1.206e-03, eta: 3:16:51, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0279, loss: 0.0279 +2025-06-25 09:43:35,277 - pyskl - INFO - Epoch [129][1200/1281] lr: 1.197e-03, eta: 3:16:08, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-25 09:44:15,079 - pyskl - INFO - Saving checkpoint at 129 epochs +2025-06-25 09:45:13,164 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:45:13,226 - pyskl - INFO - +top1_acc 0.9241 +top5_acc 0.9944 +2025-06-25 09:45:13,226 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:45:13,233 - pyskl - INFO - +mean_acc 0.8982 +2025-06-25 09:45:13,235 - pyskl - INFO - Epoch(val) [129][533] top1_acc: 0.9241, top5_acc: 0.9944, mean_class_accuracy: 0.8982 +2025-06-25 09:46:32,010 - pyskl - INFO - Epoch [130][100/1281] lr: 1.181e-03, eta: 3:14:49, time: 0.788, data_time: 0.190, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 09:47:20,837 - pyskl - INFO - Epoch [130][200/1281] lr: 1.172e-03, eta: 3:14:07, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0256, loss: 0.0256 +2025-06-25 09:48:09,780 - pyskl - INFO - Epoch [130][300/1281] lr: 1.164e-03, eta: 3:13:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0221, loss: 0.0221 +2025-06-25 09:48:58,681 - pyskl - INFO - Epoch [130][400/1281] lr: 1.155e-03, eta: 3:12:41, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 09:49:47,504 - pyskl - INFO - Epoch [130][500/1281] lr: 1.147e-03, eta: 3:11:58, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-25 09:50:36,710 - pyskl - INFO - Epoch [130][600/1281] lr: 1.138e-03, eta: 3:11:15, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-25 09:51:04,900 - pyskl - INFO - Epoch [130][700/1281] lr: 1.130e-03, eta: 3:10:29, time: 0.282, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0205, loss: 0.0205 +2025-06-25 09:51:54,854 - pyskl - INFO - Epoch [130][800/1281] lr: 1.121e-03, eta: 3:09:47, time: 0.500, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0249, loss: 0.0249 +2025-06-25 09:52:28,831 - pyskl - INFO - Epoch [130][900/1281] lr: 1.113e-03, eta: 3:09:02, time: 0.340, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 09:53:17,658 - pyskl - INFO - Epoch [130][1000/1281] lr: 1.104e-03, eta: 3:08:19, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 09:54:06,654 - pyskl - INFO - Epoch [130][1100/1281] lr: 1.096e-03, eta: 3:07:36, time: 0.490, data_time: 0.001, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0221, loss: 0.0221 +2025-06-25 09:54:55,839 - pyskl - INFO - Epoch [130][1200/1281] lr: 1.088e-03, eta: 3:06:53, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0214, loss: 0.0214 +2025-06-25 09:55:35,876 - pyskl - INFO - Saving checkpoint at 130 epochs +2025-06-25 09:56:34,028 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:56:34,084 - pyskl - INFO - +top1_acc 0.9252 +top5_acc 0.9952 +2025-06-25 09:56:34,084 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:56:34,091 - pyskl - INFO - +mean_acc 0.9016 +2025-06-25 09:56:34,095 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_128.pth was removed +2025-06-25 09:56:34,315 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_130.pth. +2025-06-25 09:56:34,315 - pyskl - INFO - Best top1_acc is 0.9252 at 130 epoch. +2025-06-25 09:56:34,318 - pyskl - INFO - Epoch(val) [130][533] top1_acc: 0.9252, top5_acc: 0.9952, mean_class_accuracy: 0.9016 +2025-06-25 09:57:53,117 - pyskl - INFO - Epoch [131][100/1281] lr: 1.072e-03, eta: 3:05:34, time: 0.788, data_time: 0.184, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0207, loss: 0.0207 +2025-06-25 09:58:41,359 - pyskl - INFO - Epoch [131][200/1281] lr: 1.064e-03, eta: 3:04:51, time: 0.482, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 09:59:30,242 - pyskl - INFO - Epoch [131][300/1281] lr: 1.056e-03, eta: 3:04:08, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 10:00:19,013 - pyskl - INFO - Epoch [131][400/1281] lr: 1.048e-03, eta: 3:03:26, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0309, loss: 0.0309 +2025-06-25 10:01:07,933 - pyskl - INFO - Epoch [131][500/1281] lr: 1.040e-03, eta: 3:02:43, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0243, loss: 0.0243 +2025-06-25 10:01:57,089 - pyskl - INFO - Epoch [131][600/1281] lr: 1.031e-03, eta: 3:02:00, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0233, loss: 0.0233 +2025-06-25 10:02:26,642 - pyskl - INFO - Epoch [131][700/1281] lr: 1.023e-03, eta: 3:01:14, time: 0.296, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-25 10:03:12,859 - pyskl - INFO - Epoch [131][800/1281] lr: 1.015e-03, eta: 3:00:31, time: 0.462, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0200, loss: 0.0200 +2025-06-25 10:03:47,064 - pyskl - INFO - Epoch [131][900/1281] lr: 1.007e-03, eta: 2:59:46, time: 0.342, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0280, loss: 0.0280 +2025-06-25 10:04:36,067 - pyskl - INFO - Epoch [131][1000/1281] lr: 9.992e-04, eta: 2:59:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 10:05:25,266 - pyskl - INFO - Epoch [131][1100/1281] lr: 9.912e-04, eta: 2:58:20, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 10:06:14,097 - pyskl - INFO - Epoch [131][1200/1281] lr: 9.832e-04, eta: 2:57:37, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 10:06:54,228 - pyskl - INFO - Saving checkpoint at 131 epochs +2025-06-25 10:07:52,324 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:07:52,381 - pyskl - INFO - +top1_acc 0.9263 +top5_acc 0.9954 +2025-06-25 10:07:52,381 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:07:52,388 - pyskl - INFO - +mean_acc 0.9043 +2025-06-25 10:07:52,392 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_130.pth was removed +2025-06-25 10:07:52,593 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_131.pth. +2025-06-25 10:07:52,594 - pyskl - INFO - Best top1_acc is 0.9263 at 131 epoch. +2025-06-25 10:07:52,596 - pyskl - INFO - Epoch(val) [131][533] top1_acc: 0.9263, top5_acc: 0.9954, mean_class_accuracy: 0.9043 +2025-06-25 10:09:11,303 - pyskl - INFO - Epoch [132][100/1281] lr: 9.689e-04, eta: 2:56:18, time: 0.787, data_time: 0.185, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 10:10:00,186 - pyskl - INFO - Epoch [132][200/1281] lr: 9.610e-04, eta: 2:55:35, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0209, loss: 0.0209 +2025-06-25 10:10:49,250 - pyskl - INFO - Epoch [132][300/1281] lr: 9.532e-04, eta: 2:54:53, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 10:11:38,228 - pyskl - INFO - Epoch [132][400/1281] lr: 9.454e-04, eta: 2:54:10, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0217, loss: 0.0217 +2025-06-25 10:12:27,489 - pyskl - INFO - Epoch [132][500/1281] lr: 9.376e-04, eta: 2:53:27, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-25 10:13:16,453 - pyskl - INFO - Epoch [132][600/1281] lr: 9.298e-04, eta: 2:52:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 10:13:47,570 - pyskl - INFO - Epoch [132][700/1281] lr: 9.221e-04, eta: 2:51:58, time: 0.311, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 10:14:31,824 - pyskl - INFO - Epoch [132][800/1281] lr: 9.144e-04, eta: 2:51:15, time: 0.443, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0161, loss: 0.0161 +2025-06-25 10:15:06,910 - pyskl - INFO - Epoch [132][900/1281] lr: 9.068e-04, eta: 2:50:30, time: 0.351, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0205, loss: 0.0205 +2025-06-25 10:15:55,910 - pyskl - INFO - Epoch [132][1000/1281] lr: 8.991e-04, eta: 2:49:47, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 10:16:44,963 - pyskl - INFO - Epoch [132][1100/1281] lr: 8.915e-04, eta: 2:49:04, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 10:17:33,659 - pyskl - INFO - Epoch [132][1200/1281] lr: 8.840e-04, eta: 2:48:21, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 10:18:13,726 - pyskl - INFO - Saving checkpoint at 132 epochs +2025-06-25 10:19:11,798 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:19:11,859 - pyskl - INFO - +top1_acc 0.9263 +top5_acc 0.9947 +2025-06-25 10:19:11,859 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:19:11,867 - pyskl - INFO - +mean_acc 0.9053 +2025-06-25 10:19:11,869 - pyskl - INFO - Epoch(val) [132][533] top1_acc: 0.9263, top5_acc: 0.9947, mean_class_accuracy: 0.9053 +2025-06-25 10:20:31,005 - pyskl - INFO - Epoch [133][100/1281] lr: 8.704e-04, eta: 2:47:02, time: 0.791, data_time: 0.182, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 10:21:19,907 - pyskl - INFO - Epoch [133][200/1281] lr: 8.629e-04, eta: 2:46:19, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 10:22:08,781 - pyskl - INFO - Epoch [133][300/1281] lr: 8.554e-04, eta: 2:45:36, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 10:22:57,903 - pyskl - INFO - Epoch [133][400/1281] lr: 8.480e-04, eta: 2:44:53, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0183, loss: 0.0183 +2025-06-25 10:23:46,806 - pyskl - INFO - Epoch [133][500/1281] lr: 8.406e-04, eta: 2:44:10, 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 10:24:35,840 - pyskl - INFO - Epoch [133][600/1281] lr: 8.333e-04, eta: 2:43:28, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 10:25:07,892 - pyskl - INFO - Epoch [133][700/1281] lr: 8.260e-04, eta: 2:42:42, time: 0.321, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 10:25:49,112 - pyskl - INFO - Epoch [133][800/1281] lr: 8.187e-04, eta: 2:41:58, time: 0.412, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-25 10:26:25,008 - pyskl - INFO - Epoch [133][900/1281] lr: 8.114e-04, eta: 2:41:14, time: 0.359, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 10:27:13,635 - pyskl - INFO - Epoch [133][1000/1281] lr: 8.042e-04, eta: 2:40:31, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 10:28:02,503 - pyskl - INFO - Epoch [133][1100/1281] lr: 7.970e-04, eta: 2:39:48, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0151, loss: 0.0151 +2025-06-25 10:28:51,211 - pyskl - INFO - Epoch [133][1200/1281] lr: 7.898e-04, eta: 2:39:05, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0224, loss: 0.0224 +2025-06-25 10:29:31,188 - pyskl - INFO - Saving checkpoint at 133 epochs +2025-06-25 10:30:29,373 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:30:29,428 - pyskl - INFO - +top1_acc 0.9271 +top5_acc 0.9947 +2025-06-25 10:30:29,429 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:30:29,435 - pyskl - INFO - +mean_acc 0.9056 +2025-06-25 10:30:29,439 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_131.pth was removed +2025-06-25 10:30:29,607 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_133.pth. +2025-06-25 10:30:29,608 - pyskl - INFO - Best top1_acc is 0.9271 at 133 epoch. +2025-06-25 10:30:29,610 - pyskl - INFO - Epoch(val) [133][533] top1_acc: 0.9271, top5_acc: 0.9947, mean_class_accuracy: 0.9056 +2025-06-25 10:31:48,548 - pyskl - INFO - Epoch [134][100/1281] lr: 7.769e-04, eta: 2:37:46, time: 0.789, data_time: 0.186, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0214, loss: 0.0214 +2025-06-25 10:32:37,517 - pyskl - INFO - Epoch [134][200/1281] lr: 7.699e-04, eta: 2:37:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 10:33:26,523 - pyskl - INFO - Epoch [134][300/1281] lr: 7.628e-04, eta: 2:36:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0219, loss: 0.0219 +2025-06-25 10:34:15,562 - pyskl - INFO - Epoch [134][400/1281] lr: 7.558e-04, eta: 2:35:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 10:35:04,524 - pyskl - INFO - Epoch [134][500/1281] lr: 7.488e-04, eta: 2:34:54, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0238, loss: 0.0238 +2025-06-25 10:35:53,279 - pyskl - INFO - Epoch [134][600/1281] lr: 7.419e-04, eta: 2:34:10, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0200, loss: 0.0200 +2025-06-25 10:36:28,007 - pyskl - INFO - Epoch [134][700/1281] lr: 7.349e-04, eta: 2:33:26, time: 0.347, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 10:37:06,231 - pyskl - INFO - Epoch [134][800/1281] lr: 7.281e-04, eta: 2:32:41, time: 0.382, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 10:37:43,020 - pyskl - INFO - Epoch [134][900/1281] lr: 7.212e-04, eta: 2:31:57, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0170, loss: 0.0170 +2025-06-25 10:38:31,919 - pyskl - INFO - Epoch [134][1000/1281] lr: 7.144e-04, eta: 2:31:14, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 10:39:21,055 - pyskl - INFO - Epoch [134][1100/1281] lr: 7.076e-04, eta: 2:30:31, 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 10:40:09,629 - pyskl - INFO - Epoch [134][1200/1281] lr: 7.008e-04, eta: 2:29:48, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 10:40:49,755 - pyskl - INFO - Saving checkpoint at 134 epochs +2025-06-25 10:41:47,997 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:41:48,053 - pyskl - INFO - +top1_acc 0.9279 +top5_acc 0.9950 +2025-06-25 10:41:48,054 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:41:48,061 - pyskl - INFO - +mean_acc 0.9040 +2025-06-25 10:41:48,065 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_133.pth was removed +2025-06-25 10:41:48,232 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_134.pth. +2025-06-25 10:41:48,232 - pyskl - INFO - Best top1_acc is 0.9279 at 134 epoch. +2025-06-25 10:41:48,235 - pyskl - INFO - Epoch(val) [134][533] top1_acc: 0.9279, top5_acc: 0.9950, mean_class_accuracy: 0.9040 +2025-06-25 10:43:08,146 - pyskl - INFO - Epoch [135][100/1281] lr: 6.887e-04, eta: 2:28:29, time: 0.799, data_time: 0.190, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 10:43:56,802 - pyskl - INFO - Epoch [135][200/1281] lr: 6.820e-04, eta: 2:27:46, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 10:44:45,683 - pyskl - INFO - Epoch [135][300/1281] lr: 6.753e-04, eta: 2:27:03, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 10:45:34,456 - pyskl - INFO - Epoch [135][400/1281] lr: 6.687e-04, eta: 2:26:19, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 10:46:23,809 - pyskl - INFO - Epoch [135][500/1281] lr: 6.622e-04, eta: 2:25:36, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 10:47:11,067 - pyskl - INFO - Epoch [135][600/1281] lr: 6.556e-04, eta: 2:24:53, time: 0.473, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 10:47:47,154 - pyskl - INFO - Epoch [135][700/1281] lr: 6.491e-04, eta: 2:24:09, time: 0.361, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 10:48:24,090 - pyskl - INFO - Epoch [135][800/1281] lr: 6.426e-04, eta: 2:23:24, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 10:49:02,750 - pyskl - INFO - Epoch [135][900/1281] lr: 6.362e-04, eta: 2:22:40, time: 0.387, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 10:49:51,520 - pyskl - INFO - Epoch [135][1000/1281] lr: 6.297e-04, eta: 2:21:57, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0259, loss: 0.0259 +2025-06-25 10:50:40,251 - pyskl - INFO - Epoch [135][1100/1281] lr: 6.233e-04, eta: 2:21:14, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0171, loss: 0.0171 +2025-06-25 10:51:28,954 - pyskl - INFO - Epoch [135][1200/1281] lr: 6.170e-04, eta: 2:20:31, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0167, loss: 0.0167 +2025-06-25 10:52:09,202 - pyskl - INFO - Saving checkpoint at 135 epochs +2025-06-25 10:53:06,864 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:53:06,919 - pyskl - INFO - +top1_acc 0.9252 +top5_acc 0.9945 +2025-06-25 10:53:06,920 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:53:06,927 - pyskl - INFO - +mean_acc 0.9017 +2025-06-25 10:53:06,929 - pyskl - INFO - Epoch(val) [135][533] top1_acc: 0.9252, top5_acc: 0.9945, mean_class_accuracy: 0.9017 +2025-06-25 10:54:25,155 - pyskl - INFO - Epoch [136][100/1281] lr: 6.056e-04, eta: 2:19:11, time: 0.782, data_time: 0.183, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-25 10:55:13,761 - pyskl - INFO - Epoch [136][200/1281] lr: 5.993e-04, eta: 2:18:28, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 10:56:02,853 - pyskl - INFO - Epoch [136][300/1281] lr: 5.931e-04, eta: 2:17:45, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0231, loss: 0.0231 +2025-06-25 10:56:51,866 - pyskl - INFO - Epoch [136][400/1281] lr: 5.868e-04, eta: 2:17:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 10:57:40,763 - pyskl - INFO - Epoch [136][500/1281] lr: 5.807e-04, eta: 2:16:19, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 10:58:27,404 - pyskl - INFO - Epoch [136][600/1281] lr: 5.745e-04, eta: 2:15:35, time: 0.466, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 10:59:05,123 - pyskl - INFO - Epoch [136][700/1281] lr: 5.684e-04, eta: 2:14:51, time: 0.377, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 10:59:40,462 - pyskl - INFO - Epoch [136][800/1281] lr: 5.623e-04, eta: 2:14:06, time: 0.353, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 11:00:19,119 - pyskl - INFO - Epoch [136][900/1281] lr: 5.563e-04, eta: 2:13:22, time: 0.387, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0183, loss: 0.0183 +2025-06-25 11:01:08,175 - pyskl - INFO - Epoch [136][1000/1281] lr: 5.503e-04, eta: 2:12:39, 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 11:01:56,801 - pyskl - INFO - Epoch [136][1100/1281] lr: 5.443e-04, eta: 2:11:56, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0167, loss: 0.0167 +2025-06-25 11:02:45,828 - pyskl - INFO - Epoch [136][1200/1281] lr: 5.384e-04, eta: 2:11:13, 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 11:03:26,020 - pyskl - INFO - Saving checkpoint at 136 epochs +2025-06-25 11:04:24,066 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:04:24,134 - pyskl - INFO - +top1_acc 0.9259 +top5_acc 0.9945 +2025-06-25 11:04:24,135 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:04:24,142 - pyskl - INFO - +mean_acc 0.9038 +2025-06-25 11:04:24,144 - pyskl - INFO - Epoch(val) [136][533] top1_acc: 0.9259, top5_acc: 0.9945, mean_class_accuracy: 0.9038 +2025-06-25 11:05:43,472 - pyskl - INFO - Epoch [137][100/1281] lr: 5.277e-04, eta: 2:09:54, time: 0.793, data_time: 0.181, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0161, loss: 0.0161 +2025-06-25 11:06:32,231 - pyskl - INFO - Epoch [137][200/1281] lr: 5.218e-04, eta: 2:09:11, time: 0.488, data_time: 0.001, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 11:07:21,083 - pyskl - INFO - Epoch [137][300/1281] lr: 5.160e-04, eta: 2:08:27, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 11:08:10,380 - pyskl - INFO - Epoch [137][400/1281] lr: 5.102e-04, eta: 2:07:44, 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 11:08:59,429 - pyskl - INFO - Epoch [137][500/1281] lr: 5.044e-04, eta: 2:07:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-25 11:09:46,396 - pyskl - INFO - Epoch [137][600/1281] lr: 4.987e-04, eta: 2:06:18, time: 0.470, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 11:10:22,741 - pyskl - INFO - Epoch [137][700/1281] lr: 4.930e-04, eta: 2:05:33, time: 0.363, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 11:10:59,156 - pyskl - INFO - Epoch [137][800/1281] lr: 4.873e-04, eta: 2:04:49, time: 0.364, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0169, loss: 0.0169 +2025-06-25 11:11:38,547 - pyskl - INFO - Epoch [137][900/1281] lr: 4.817e-04, eta: 2:04:05, time: 0.394, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 11:12:27,717 - pyskl - INFO - Epoch [137][1000/1281] lr: 4.761e-04, eta: 2:03:21, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0171, loss: 0.0171 +2025-06-25 11:13:16,615 - pyskl - INFO - Epoch [137][1100/1281] lr: 4.705e-04, eta: 2:02:38, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 11:14:05,918 - pyskl - INFO - Epoch [137][1200/1281] lr: 4.650e-04, eta: 2:01:55, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 11:14:46,209 - pyskl - INFO - Saving checkpoint at 137 epochs +2025-06-25 11:15:44,602 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:15:44,666 - pyskl - INFO - +top1_acc 0.9288 +top5_acc 0.9944 +2025-06-25 11:15:44,666 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:15:44,675 - pyskl - INFO - +mean_acc 0.9064 +2025-06-25 11:15:44,681 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_134.pth was removed +2025-06-25 11:15:44,865 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_137.pth. +2025-06-25 11:15:44,865 - pyskl - INFO - Best top1_acc is 0.9288 at 137 epoch. +2025-06-25 11:15:44,868 - pyskl - INFO - Epoch(val) [137][533] top1_acc: 0.9288, top5_acc: 0.9944, mean_class_accuracy: 0.9064 +2025-06-25 11:17:04,147 - pyskl - INFO - Epoch [138][100/1281] lr: 4.550e-04, eta: 2:00:36, time: 0.793, data_time: 0.186, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 11:17:53,260 - pyskl - INFO - Epoch [138][200/1281] lr: 4.496e-04, eta: 1:59:53, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 11:18:42,147 - pyskl - INFO - Epoch [138][300/1281] lr: 4.442e-04, eta: 1:59:09, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0167, loss: 0.0167 +2025-06-25 11:19:30,993 - pyskl - INFO - Epoch [138][400/1281] lr: 4.388e-04, eta: 1:58:26, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 11:20:20,123 - pyskl - INFO - Epoch [138][500/1281] lr: 4.334e-04, eta: 1:57:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 11:21:04,490 - pyskl - INFO - Epoch [138][600/1281] lr: 4.281e-04, eta: 1:56:59, time: 0.444, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 11:21:47,315 - pyskl - INFO - Epoch [138][700/1281] lr: 4.228e-04, eta: 1:56:16, time: 0.428, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 11:22:17,705 - pyskl - INFO - Epoch [138][800/1281] lr: 4.176e-04, eta: 1:55:31, time: 0.304, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0171, loss: 0.0171 +2025-06-25 11:23:19,691 - pyskl - INFO - Epoch [138][900/1281] lr: 4.124e-04, eta: 1:54:48, time: 0.620, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0215, loss: 0.0215 +2025-06-25 11:24:28,955 - pyskl - INFO - Epoch [138][1000/1281] lr: 4.072e-04, eta: 1:54:07, time: 0.693, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0170, loss: 0.0170 +2025-06-25 11:25:40,308 - pyskl - INFO - Epoch [138][1100/1281] lr: 4.020e-04, eta: 1:53:26, time: 0.714, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 11:26:50,410 - pyskl - INFO - Epoch [138][1200/1281] lr: 3.969e-04, eta: 1:52:44, time: 0.701, data_time: 0.001, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-25 11:27:48,183 - pyskl - INFO - Saving checkpoint at 138 epochs +2025-06-25 11:29:02,174 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:29:02,241 - pyskl - INFO - +top1_acc 0.9303 +top5_acc 0.9948 +2025-06-25 11:29:02,241 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:29:02,249 - pyskl - INFO - +mean_acc 0.9075 +2025-06-25 11:29:02,254 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_137.pth was removed +2025-06-25 11:29:02,430 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_138.pth. +2025-06-25 11:29:02,431 - pyskl - INFO - Best top1_acc is 0.9303 at 138 epoch. +2025-06-25 11:29:02,433 - pyskl - INFO - Epoch(val) [138][533] top1_acc: 0.9303, top5_acc: 0.9948, mean_class_accuracy: 0.9075 +2025-06-25 11:30:06,767 - pyskl - INFO - Epoch [139][100/1281] lr: 3.877e-04, eta: 1:51:24, time: 0.643, data_time: 0.185, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 11:31:14,866 - pyskl - INFO - Epoch [139][200/1281] lr: 3.827e-04, eta: 1:50:42, time: 0.681, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 11:32:23,939 - pyskl - INFO - Epoch [139][300/1281] lr: 3.777e-04, eta: 1:50:00, time: 0.691, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0167, loss: 0.0167 +2025-06-25 11:33:34,136 - pyskl - INFO - Epoch [139][400/1281] lr: 3.727e-04, eta: 1:49:19, time: 0.702, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0149, loss: 0.0149 +2025-06-25 11:34:43,981 - pyskl - INFO - Epoch [139][500/1281] lr: 3.678e-04, eta: 1:48:37, time: 0.698, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 11:35:55,215 - pyskl - INFO - Epoch [139][600/1281] lr: 3.628e-04, eta: 1:47:56, time: 0.712, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0166, loss: 0.0166 +2025-06-25 11:37:05,817 - pyskl - INFO - Epoch [139][700/1281] lr: 3.580e-04, eta: 1:47:14, time: 0.706, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 11:37:36,545 - pyskl - INFO - Epoch [139][800/1281] lr: 3.531e-04, eta: 1:46:29, time: 0.307, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 11:37:58,402 - pyskl - INFO - Epoch [139][900/1281] lr: 3.483e-04, eta: 1:45:43, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 11:38:20,374 - pyskl - INFO - Epoch [139][1000/1281] lr: 3.436e-04, eta: 1:44:58, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 11:38:42,717 - pyskl - INFO - Epoch [139][1100/1281] lr: 3.388e-04, eta: 1:44:12, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 11:39:04,514 - pyskl - INFO - Epoch [139][1200/1281] lr: 3.341e-04, eta: 1:43:27, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0149, loss: 0.0149 +2025-06-25 11:39:22,980 - pyskl - INFO - Saving checkpoint at 139 epochs +2025-06-25 11:40:05,480 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:40:05,534 - pyskl - INFO - +top1_acc 0.9297 +top5_acc 0.9953 +2025-06-25 11:40:05,534 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:40:05,541 - pyskl - INFO - +mean_acc 0.9074 +2025-06-25 11:40:05,542 - pyskl - INFO - Epoch(val) [139][533] top1_acc: 0.9297, top5_acc: 0.9953, mean_class_accuracy: 0.9074 +2025-06-25 11:40:46,795 - pyskl - INFO - Epoch [140][100/1281] lr: 3.257e-04, eta: 1:42:04, time: 0.412, data_time: 0.182, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 11:41:08,863 - pyskl - INFO - Epoch [140][200/1281] lr: 3.210e-04, eta: 1:41:19, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 11:41:30,911 - pyskl - INFO - Epoch [140][300/1281] lr: 3.165e-04, eta: 1:40:34, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 11:41:52,786 - pyskl - INFO - Epoch [140][400/1281] lr: 3.119e-04, eta: 1:39:48, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 11:42:15,139 - pyskl - INFO - Epoch [140][500/1281] lr: 3.074e-04, eta: 1:39:03, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 11:42:36,935 - pyskl - INFO - Epoch [140][600/1281] lr: 3.029e-04, eta: 1:38:17, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0144, loss: 0.0144 +2025-06-25 11:42:59,157 - pyskl - INFO - Epoch [140][700/1281] lr: 2.984e-04, eta: 1:37:32, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 11:43:21,741 - pyskl - INFO - Epoch [140][800/1281] lr: 2.940e-04, eta: 1:36:47, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 11:43:43,633 - pyskl - INFO - Epoch [140][900/1281] lr: 2.896e-04, eta: 1:36:01, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 11:44:05,520 - pyskl - INFO - Epoch [140][1000/1281] lr: 2.853e-04, eta: 1:35:16, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 11:44:27,344 - pyskl - INFO - Epoch [140][1100/1281] lr: 2.809e-04, eta: 1:34:31, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0161, loss: 0.0161 +2025-06-25 11:44:49,276 - pyskl - INFO - Epoch [140][1200/1281] lr: 2.767e-04, eta: 1:33:46, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 11:45:07,607 - pyskl - INFO - Saving checkpoint at 140 epochs +2025-06-25 11:45:50,442 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:45:50,497 - pyskl - INFO - +top1_acc 0.9286 +top5_acc 0.9953 +2025-06-25 11:45:50,498 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:45:50,504 - pyskl - INFO - +mean_acc 0.9049 +2025-06-25 11:45:50,506 - pyskl - INFO - Epoch(val) [140][533] top1_acc: 0.9286, top5_acc: 0.9953, mean_class_accuracy: 0.9049 +2025-06-25 11:46:31,234 - pyskl - INFO - Epoch [141][100/1281] lr: 2.690e-04, eta: 1:32:24, time: 0.407, data_time: 0.177, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0150, loss: 0.0150 +2025-06-25 11:46:53,220 - pyskl - INFO - Epoch [141][200/1281] lr: 2.648e-04, eta: 1:31:39, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0146, loss: 0.0146 +2025-06-25 11:47:15,243 - pyskl - INFO - Epoch [141][300/1281] lr: 2.606e-04, eta: 1:30:54, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 11:47:37,314 - pyskl - INFO - Epoch [141][400/1281] lr: 2.565e-04, eta: 1:30:09, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 11:47:59,425 - pyskl - INFO - Epoch [141][500/1281] lr: 2.524e-04, eta: 1:29:24, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 11:48:21,482 - pyskl - INFO - Epoch [141][600/1281] lr: 2.483e-04, eta: 1:28:39, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 11:48:43,458 - pyskl - INFO - Epoch [141][700/1281] lr: 2.443e-04, eta: 1:27:54, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 11:49:05,363 - pyskl - INFO - Epoch [141][800/1281] lr: 2.402e-04, eta: 1:27:09, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0145, loss: 0.0145 +2025-06-25 11:49:27,281 - pyskl - INFO - Epoch [141][900/1281] lr: 2.363e-04, eta: 1:26:24, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0161, loss: 0.0161 +2025-06-25 11:49:49,212 - pyskl - INFO - Epoch [141][1000/1281] lr: 2.323e-04, eta: 1:25:39, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 11:50:11,181 - pyskl - INFO - Epoch [141][1100/1281] lr: 2.284e-04, eta: 1:24:54, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 11:50:33,191 - pyskl - INFO - Epoch [141][1200/1281] lr: 2.246e-04, eta: 1:24:09, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0169, loss: 0.0169 +2025-06-25 11:50:51,809 - pyskl - INFO - Saving checkpoint at 141 epochs +2025-06-25 11:51:34,495 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:51:34,549 - pyskl - INFO - +top1_acc 0.9276 +top5_acc 0.9950 +2025-06-25 11:51:34,549 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:51:34,556 - pyskl - INFO - +mean_acc 0.9051 +2025-06-25 11:51:34,557 - pyskl - INFO - Epoch(val) [141][533] top1_acc: 0.9276, top5_acc: 0.9950, mean_class_accuracy: 0.9051 +2025-06-25 11:52:15,707 - pyskl - INFO - Epoch [142][100/1281] lr: 2.176e-04, eta: 1:22:48, time: 0.411, data_time: 0.181, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 11:52:37,762 - pyskl - INFO - Epoch [142][200/1281] lr: 2.139e-04, eta: 1:22:03, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 11:53:00,515 - pyskl - INFO - Epoch [142][300/1281] lr: 2.101e-04, eta: 1:21:18, time: 0.228, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0167, loss: 0.0167 +2025-06-25 11:53:22,743 - pyskl - INFO - Epoch [142][400/1281] lr: 2.064e-04, eta: 1:20:33, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 11:53:44,662 - pyskl - INFO - Epoch [142][500/1281] lr: 2.027e-04, eta: 1:19:49, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 11:54:06,982 - pyskl - INFO - Epoch [142][600/1281] lr: 1.991e-04, eta: 1:19:04, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 11:54:29,172 - pyskl - INFO - Epoch [142][700/1281] lr: 1.954e-04, eta: 1:18:19, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 11:54:51,417 - pyskl - INFO - Epoch [142][800/1281] lr: 1.919e-04, eta: 1:17:35, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 11:55:13,548 - pyskl - INFO - Epoch [142][900/1281] lr: 1.883e-04, eta: 1:16:50, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 11:55:35,512 - pyskl - INFO - Epoch [142][1000/1281] lr: 1.848e-04, eta: 1:16:05, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0148, loss: 0.0148 +2025-06-25 11:55:57,514 - pyskl - INFO - Epoch [142][1100/1281] lr: 1.813e-04, eta: 1:15:21, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 11:56:19,342 - pyskl - INFO - Epoch [142][1200/1281] lr: 1.779e-04, eta: 1:14:36, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 11:56:38,292 - pyskl - INFO - Saving checkpoint at 142 epochs +2025-06-25 11:57:20,593 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:57:20,647 - pyskl - INFO - +top1_acc 0.9284 +top5_acc 0.9952 +2025-06-25 11:57:20,647 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:57:20,653 - pyskl - INFO - +mean_acc 0.9058 +2025-06-25 11:57:20,655 - pyskl - INFO - Epoch(val) [142][533] top1_acc: 0.9284, top5_acc: 0.9952, mean_class_accuracy: 0.9058 +2025-06-25 11:58:02,167 - pyskl - INFO - Epoch [143][100/1281] lr: 1.717e-04, eta: 1:13:16, time: 0.415, data_time: 0.182, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 11:58:24,031 - pyskl - INFO - Epoch [143][200/1281] lr: 1.683e-04, eta: 1:12:31, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 11:58:45,939 - pyskl - INFO - Epoch [143][300/1281] lr: 1.650e-04, eta: 1:11:47, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 11:59:08,317 - pyskl - INFO - Epoch [143][400/1281] lr: 1.617e-04, eta: 1:11:02, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0169, loss: 0.0169 +2025-06-25 11:59:30,229 - pyskl - INFO - Epoch [143][500/1281] lr: 1.585e-04, eta: 1:10:18, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 11:59:52,205 - pyskl - INFO - Epoch [143][600/1281] lr: 1.552e-04, eta: 1:09:34, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 12:00:14,436 - pyskl - INFO - Epoch [143][700/1281] lr: 1.520e-04, eta: 1:08:49, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 12:00:36,794 - pyskl - INFO - Epoch [143][800/1281] lr: 1.489e-04, eta: 1:08:05, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 12:00:59,000 - pyskl - INFO - Epoch [143][900/1281] lr: 1.457e-04, eta: 1:07:21, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 12:01:20,967 - pyskl - INFO - Epoch [143][1000/1281] lr: 1.426e-04, eta: 1:06:36, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 12:01:43,112 - pyskl - INFO - Epoch [143][1100/1281] lr: 1.396e-04, eta: 1:05:52, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0170, loss: 0.0170 +2025-06-25 12:02:05,002 - pyskl - INFO - Epoch [143][1200/1281] lr: 1.366e-04, eta: 1:05:08, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 12:02:23,490 - pyskl - INFO - Saving checkpoint at 143 epochs +2025-06-25 12:03:05,418 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:03:05,489 - pyskl - INFO - +top1_acc 0.9291 +top5_acc 0.9950 +2025-06-25 12:03:05,490 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:03:05,500 - pyskl - INFO - +mean_acc 0.9090 +2025-06-25 12:03:05,503 - pyskl - INFO - Epoch(val) [143][533] top1_acc: 0.9291, top5_acc: 0.9950, mean_class_accuracy: 0.9090 +2025-06-25 12:03:46,441 - pyskl - INFO - Epoch [144][100/1281] lr: 1.312e-04, eta: 1:03:48, time: 0.409, data_time: 0.175, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0151, loss: 0.0151 +2025-06-25 12:04:08,243 - pyskl - INFO - Epoch [144][200/1281] lr: 1.282e-04, eta: 1:03:04, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0151, loss: 0.0151 +2025-06-25 12:04:30,365 - pyskl - INFO - Epoch [144][300/1281] lr: 1.253e-04, eta: 1:02:19, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0143, loss: 0.0143 +2025-06-25 12:04:52,497 - pyskl - INFO - Epoch [144][400/1281] lr: 1.224e-04, eta: 1:01:35, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 12:05:14,574 - pyskl - INFO - Epoch [144][500/1281] lr: 1.196e-04, eta: 1:00:51, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 12:05:36,667 - pyskl - INFO - Epoch [144][600/1281] lr: 1.168e-04, eta: 1:00:07, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 12:05:58,566 - pyskl - INFO - Epoch [144][700/1281] lr: 1.140e-04, eta: 0:59:23, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 12:06:21,029 - pyskl - INFO - Epoch [144][800/1281] lr: 1.113e-04, eta: 0:58:39, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0151, loss: 0.0151 +2025-06-25 12:06:43,028 - pyskl - INFO - Epoch [144][900/1281] lr: 1.086e-04, eta: 0:57:55, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 12:07:04,895 - pyskl - INFO - Epoch [144][1000/1281] lr: 1.059e-04, eta: 0:57:11, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 12:07:26,674 - pyskl - INFO - Epoch [144][1100/1281] lr: 1.033e-04, eta: 0:56:27, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 12:07:48,630 - pyskl - INFO - Epoch [144][1200/1281] lr: 1.007e-04, eta: 0:55:43, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0183, loss: 0.0183 +2025-06-25 12:08:06,863 - pyskl - INFO - Saving checkpoint at 144 epochs +2025-06-25 12:08:48,821 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:08:48,888 - pyskl - INFO - +top1_acc 0.9279 +top5_acc 0.9952 +2025-06-25 12:08:48,888 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:08:48,895 - pyskl - INFO - +mean_acc 0.9071 +2025-06-25 12:08:48,897 - pyskl - INFO - Epoch(val) [144][533] top1_acc: 0.9279, top5_acc: 0.9952, mean_class_accuracy: 0.9071 +2025-06-25 12:09:29,839 - pyskl - INFO - Epoch [145][100/1281] lr: 9.605e-05, eta: 0:54:24, time: 0.409, data_time: 0.178, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 12:09:51,521 - pyskl - INFO - Epoch [145][200/1281] lr: 9.353e-05, eta: 0:53:40, time: 0.217, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 12:10:13,476 - pyskl - INFO - Epoch [145][300/1281] lr: 9.106e-05, eta: 0:52:56, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 12:10:35,592 - pyskl - INFO - Epoch [145][400/1281] lr: 8.861e-05, eta: 0:52:12, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0150, loss: 0.0150 +2025-06-25 12:10:57,684 - pyskl - INFO - Epoch [145][500/1281] lr: 8.620e-05, eta: 0:51:28, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 12:11:19,722 - pyskl - INFO - Epoch [145][600/1281] lr: 8.382e-05, eta: 0:50:44, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 12:11:41,609 - pyskl - INFO - Epoch [145][700/1281] lr: 8.147e-05, eta: 0:50:01, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 12:12:03,495 - pyskl - INFO - Epoch [145][800/1281] lr: 7.916e-05, eta: 0:49:17, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 12:12:25,261 - pyskl - INFO - Epoch [145][900/1281] lr: 7.688e-05, eta: 0:48:33, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 12:12:47,362 - pyskl - INFO - Epoch [145][1000/1281] lr: 7.463e-05, eta: 0:47:49, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 12:13:09,148 - pyskl - INFO - Epoch [145][1100/1281] lr: 7.242e-05, eta: 0:47:06, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 12:13:31,226 - pyskl - INFO - Epoch [145][1200/1281] lr: 7.024e-05, eta: 0:46:22, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 12:13:49,916 - pyskl - INFO - Saving checkpoint at 145 epochs +2025-06-25 12:14:33,270 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:14:33,324 - pyskl - INFO - +top1_acc 0.9283 +top5_acc 0.9948 +2025-06-25 12:14:33,324 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:14:33,331 - pyskl - INFO - +mean_acc 0.9063 +2025-06-25 12:14:33,332 - pyskl - INFO - Epoch(val) [145][533] top1_acc: 0.9283, top5_acc: 0.9948, mean_class_accuracy: 0.9063 +2025-06-25 12:15:13,712 - pyskl - INFO - Epoch [146][100/1281] lr: 6.638e-05, eta: 0:45:03, time: 0.404, data_time: 0.176, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 12:15:35,519 - pyskl - INFO - Epoch [146][200/1281] lr: 6.429e-05, eta: 0:44:20, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 12:15:57,472 - pyskl - INFO - Epoch [146][300/1281] lr: 6.224e-05, eta: 0:43:36, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0149, loss: 0.0149 +2025-06-25 12:16:19,223 - pyskl - INFO - Epoch [146][400/1281] lr: 6.022e-05, eta: 0:42:53, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 12:16:41,258 - pyskl - INFO - Epoch [146][500/1281] lr: 5.823e-05, eta: 0:42:09, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0151, loss: 0.0151 +2025-06-25 12:17:03,335 - pyskl - INFO - Epoch [146][600/1281] lr: 5.628e-05, eta: 0:41:26, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0149, loss: 0.0149 +2025-06-25 12:17:25,543 - pyskl - INFO - Epoch [146][700/1281] lr: 5.436e-05, eta: 0:40:42, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 12:17:47,522 - pyskl - INFO - Epoch [146][800/1281] lr: 5.247e-05, eta: 0:39:59, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0169, loss: 0.0169 +2025-06-25 12:18:09,246 - pyskl - INFO - Epoch [146][900/1281] lr: 5.061e-05, eta: 0:39:15, time: 0.217, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0171, loss: 0.0171 +2025-06-25 12:18:31,180 - pyskl - INFO - Epoch [146][1000/1281] lr: 4.879e-05, eta: 0:38:32, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 12:18:52,956 - pyskl - INFO - Epoch [146][1100/1281] lr: 4.701e-05, eta: 0:37:48, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 12:19:14,501 - pyskl - INFO - Epoch [146][1200/1281] lr: 4.525e-05, eta: 0:37:05, time: 0.215, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 12:19:32,673 - pyskl - INFO - Saving checkpoint at 146 epochs +2025-06-25 12:20:15,269 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:20:15,335 - pyskl - INFO - +top1_acc 0.9274 +top5_acc 0.9952 +2025-06-25 12:20:15,335 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:20:15,343 - pyskl - INFO - +mean_acc 0.9039 +2025-06-25 12:20:15,345 - pyskl - INFO - Epoch(val) [146][533] top1_acc: 0.9274, top5_acc: 0.9952, mean_class_accuracy: 0.9039 +2025-06-25 12:20:56,459 - pyskl - INFO - Epoch [147][100/1281] lr: 4.216e-05, eta: 0:35:47, time: 0.411, data_time: 0.177, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-25 12:21:18,147 - pyskl - INFO - Epoch [147][200/1281] lr: 4.050e-05, eta: 0:35:03, time: 0.217, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 12:21:40,207 - pyskl - INFO - Epoch [147][300/1281] lr: 3.887e-05, eta: 0:34:20, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0146, loss: 0.0146 +2025-06-25 12:22:02,394 - pyskl - INFO - Epoch [147][400/1281] lr: 3.728e-05, eta: 0:33:37, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 12:22:24,288 - pyskl - INFO - Epoch [147][500/1281] lr: 3.572e-05, eta: 0:32:54, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0217, loss: 0.0217 +2025-06-25 12:22:46,223 - pyskl - INFO - Epoch [147][600/1281] lr: 3.419e-05, eta: 0:32:11, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 12:23:08,288 - pyskl - INFO - Epoch [147][700/1281] lr: 3.270e-05, eta: 0:31:27, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 12:23:30,289 - pyskl - INFO - Epoch [147][800/1281] lr: 3.124e-05, eta: 0:30:44, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 12:23:52,466 - pyskl - INFO - Epoch [147][900/1281] lr: 2.981e-05, eta: 0:30:01, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0152, loss: 0.0152 +2025-06-25 12:24:14,667 - pyskl - INFO - Epoch [147][1000/1281] lr: 2.842e-05, eta: 0:29:18, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0161, loss: 0.0161 +2025-06-25 12:24:36,530 - pyskl - INFO - Epoch [147][1100/1281] lr: 2.706e-05, eta: 0:28:35, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 12:24:58,348 - pyskl - INFO - Epoch [147][1200/1281] lr: 2.573e-05, eta: 0:27:52, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0150, loss: 0.0150 +2025-06-25 12:25:16,730 - pyskl - INFO - Saving checkpoint at 147 epochs +2025-06-25 12:25:58,772 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:25:58,824 - pyskl - INFO - +top1_acc 0.9290 +top5_acc 0.9951 +2025-06-25 12:25:58,824 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:25:58,830 - pyskl - INFO - +mean_acc 0.9064 +2025-06-25 12:25:58,831 - pyskl - INFO - Epoch(val) [147][533] top1_acc: 0.9290, top5_acc: 0.9951, mean_class_accuracy: 0.9064 +2025-06-25 12:26:39,492 - pyskl - INFO - Epoch [148][100/1281] lr: 2.341e-05, eta: 0:26:34, time: 0.407, data_time: 0.174, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 12:27:01,258 - pyskl - INFO - Epoch [148][200/1281] lr: 2.218e-05, eta: 0:25:51, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 12:27:23,456 - pyskl - INFO - Epoch [148][300/1281] lr: 2.098e-05, eta: 0:25:08, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0158, loss: 0.0158 +2025-06-25 12:27:45,595 - pyskl - INFO - Epoch [148][400/1281] lr: 1.981e-05, eta: 0:24:25, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 12:28:08,086 - pyskl - INFO - Epoch [148][500/1281] lr: 1.868e-05, eta: 0:23:42, time: 0.225, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 12:28:30,254 - pyskl - INFO - Epoch [148][600/1281] lr: 1.758e-05, eta: 0:22:59, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0148, loss: 0.0148 +2025-06-25 12:28:52,594 - pyskl - INFO - Epoch [148][700/1281] lr: 1.651e-05, eta: 0:22:16, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0137, loss: 0.0137 +2025-06-25 12:29:14,375 - pyskl - INFO - Epoch [148][800/1281] lr: 1.548e-05, eta: 0:21:33, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 12:29:36,123 - pyskl - INFO - Epoch [148][900/1281] lr: 1.448e-05, eta: 0:20:51, time: 0.217, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0169, loss: 0.0169 +2025-06-25 12:29:57,849 - pyskl - INFO - Epoch [148][1000/1281] lr: 1.351e-05, eta: 0:20:08, time: 0.217, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 12:30:19,719 - pyskl - INFO - Epoch [148][1100/1281] lr: 1.258e-05, eta: 0:19:25, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 12:30:41,606 - pyskl - INFO - Epoch [148][1200/1281] lr: 1.168e-05, eta: 0:18:42, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 12:31:00,086 - pyskl - INFO - Saving checkpoint at 148 epochs +2025-06-25 12:31:42,346 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:31:42,400 - pyskl - INFO - +top1_acc 0.9306 +top5_acc 0.9950 +2025-06-25 12:31:42,400 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:31:42,406 - pyskl - INFO - +mean_acc 0.9085 +2025-06-25 12:31:42,410 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_138.pth was removed +2025-06-25 12:31:42,568 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_148.pth. +2025-06-25 12:31:42,569 - pyskl - INFO - Best top1_acc is 0.9306 at 148 epoch. +2025-06-25 12:31:42,571 - pyskl - INFO - Epoch(val) [148][533] top1_acc: 0.9306, top5_acc: 0.9950, mean_class_accuracy: 0.9085 +2025-06-25 12:32:23,800 - pyskl - INFO - Epoch [149][100/1281] lr: 1.013e-05, eta: 0:17:25, time: 0.412, data_time: 0.177, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 12:32:46,056 - pyskl - INFO - Epoch [149][200/1281] lr: 9.328e-06, eta: 0:16:42, time: 0.223, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0139, loss: 0.0139 +2025-06-25 12:33:08,243 - pyskl - INFO - Epoch [149][300/1281] lr: 8.555e-06, eta: 0:15:59, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 12:33:30,853 - pyskl - INFO - Epoch [149][400/1281] lr: 7.816e-06, eta: 0:15:17, time: 0.226, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0150, loss: 0.0150 +2025-06-25 12:33:52,954 - pyskl - INFO - Epoch [149][500/1281] lr: 7.110e-06, eta: 0:14:34, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 12:34:14,720 - pyskl - INFO - Epoch [149][600/1281] lr: 6.437e-06, eta: 0:13:52, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 12:34:36,903 - pyskl - INFO - Epoch [149][700/1281] lr: 5.798e-06, eta: 0:13:09, time: 0.222, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 12:34:58,833 - pyskl - INFO - Epoch [149][800/1281] lr: 5.192e-06, eta: 0:12:26, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 12:35:20,689 - pyskl - INFO - Epoch [149][900/1281] lr: 4.620e-06, eta: 0:11:44, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 12:35:42,694 - pyskl - INFO - Epoch [149][1000/1281] lr: 4.081e-06, eta: 0:11:01, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0172, loss: 0.0172 +2025-06-25 12:36:04,355 - pyskl - INFO - Epoch [149][1100/1281] lr: 3.576e-06, eta: 0:10:19, time: 0.217, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0160, loss: 0.0160 +2025-06-25 12:36:26,296 - pyskl - INFO - Epoch [149][1200/1281] lr: 3.104e-06, eta: 0:09:36, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0170, loss: 0.0170 +2025-06-25 12:36:44,943 - pyskl - INFO - Saving checkpoint at 149 epochs +2025-06-25 12:37:27,339 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:37:27,397 - pyskl - INFO - +top1_acc 0.9279 +top5_acc 0.9951 +2025-06-25 12:37:27,397 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:37:27,404 - pyskl - INFO - +mean_acc 0.9044 +2025-06-25 12:37:27,405 - pyskl - INFO - Epoch(val) [149][533] top1_acc: 0.9279, top5_acc: 0.9951, mean_class_accuracy: 0.9044 +2025-06-25 12:38:08,385 - pyskl - INFO - Epoch [150][100/1281] lr: 2.334e-06, eta: 0:08:19, time: 0.410, data_time: 0.177, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0147, loss: 0.0147 +2025-06-25 12:38:30,262 - pyskl - INFO - Epoch [150][200/1281] lr: 1.956e-06, eta: 0:07:37, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 12:38:52,302 - pyskl - INFO - Epoch [150][300/1281] lr: 1.611e-06, eta: 0:06:54, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0147, loss: 0.0147 +2025-06-25 12:39:14,228 - pyskl - INFO - Epoch [150][400/1281] lr: 1.300e-06, eta: 0:06:12, time: 0.219, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 12:39:36,368 - pyskl - INFO - Epoch [150][500/1281] lr: 1.022e-06, eta: 0:05:30, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 12:39:58,204 - pyskl - INFO - Epoch [150][600/1281] lr: 7.771e-07, eta: 0:04:47, time: 0.218, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 12:40:20,568 - pyskl - INFO - Epoch [150][700/1281] lr: 5.659e-07, eta: 0:04:05, time: 0.224, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0157, loss: 0.0157 +2025-06-25 12:40:42,611 - pyskl - INFO - Epoch [150][800/1281] lr: 3.881e-07, eta: 0:03:23, time: 0.220, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0148, loss: 0.0148 +2025-06-25 12:41:04,742 - pyskl - INFO - Epoch [150][900/1281] lr: 2.438e-07, eta: 0:02:40, time: 0.221, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0149, loss: 0.0149 +2025-06-25 12:41:26,483 - pyskl - INFO - Epoch [150][1000/1281] lr: 1.329e-07, eta: 0:01:58, time: 0.217, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 12:41:48,098 - pyskl - INFO - Epoch [150][1100/1281] lr: 5.534e-08, eta: 0:01:16, time: 0.216, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 12:42:10,012 - pyskl - INFO - Epoch [150][1200/1281] lr: 1.123e-08, eta: 0:00:34, time: 0.219, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0154, loss: 0.0154 +2025-06-25 12:42:28,759 - pyskl - INFO - Saving checkpoint at 150 epochs +2025-06-25 12:43:11,531 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:43:11,586 - pyskl - INFO - +top1_acc 0.9281 +top5_acc 0.9952 +2025-06-25 12:43:11,586 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:43:11,592 - pyskl - INFO - +mean_acc 0.9057 +2025-06-25 12:43:11,594 - pyskl - INFO - Epoch(val) [150][533] top1_acc: 0.9281, top5_acc: 0.9952, mean_class_accuracy: 0.9057 +2025-06-25 12:43:15,928 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-06-25 12:48:21,455 - pyskl - INFO - Testing results of the last checkpoint +2025-06-25 12:48:21,455 - pyskl - INFO - top1_acc: 0.9330 +2025-06-25 12:48:21,455 - pyskl - INFO - top5_acc: 0.9955 +2025-06-25 12:48:21,455 - pyskl - INFO - mean_class_accuracy: 0.9113 +2025-06-25 12:48:21,456 - pyskl - INFO - load checkpoint from local path: ./work_dirs/test_aclnet/finegym/bm/best_top1_acc_epoch_148.pth +2025-06-25 12:53:27,897 - pyskl - INFO - Testing results of the best checkpoint +2025-06-25 12:53:27,897 - pyskl - INFO - top1_acc: 0.9352 +2025-06-25 12:53:27,897 - pyskl - INFO - top5_acc: 0.9951 +2025-06-25 12:53:27,897 - pyskl - INFO - mean_class_accuracy: 0.9137