diff --git "a/finegym/j_3/20250624_084345.log" "b/finegym/j_3/20250624_084345.log" new file mode 100644--- /dev/null +++ "b/finegym/j_3/20250624_084345.log" @@ -0,0 +1,3510 @@ +2025-06-24 08:43:45,978 - pyskl - INFO - Environment info: +------------------------------------------------------------ +sys.platform: linux +Python: 3.7.11 (default, Jul 27 2021, 14:32:16) [GCC 7.5.0] +CUDA available: True +GPU 0: Tesla V100-PCIE-32GB +CUDA_HOME: /usr/local/cuda-11.7 +NVCC: Cuda compilation tools, release 11.7, V11.7.64 +GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0 +PyTorch: 1.11.0 +PyTorch compiling details: PyTorch built with: + - GCC 7.3 + - C++ Version: 201402 + - Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications + - Intel(R) MKL-DNN v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e) + - OpenMP 201511 (a.k.a. OpenMP 4.5) + - LAPACK is enabled (usually provided by MKL) + - NNPACK is enabled + - CPU capability usage: AVX2 + - CUDA Runtime 11.3 + - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_37,code=compute_37 + - CuDNN 8.2 + - Magma 2.5.2 + - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, + +TorchVision: 0.12.0 +OpenCV: 4.8.0 +MMCV: 1.5.0 +MMCV Compiler: GCC 7.3 +MMCV CUDA Compiler: 11.3 +pyskl: 0.1.0+ +------------------------------------------------------------ + +2025-06-24 08:43:46,258 - pyskl - INFO - Config: modality = 'j' +graph = 'coco_new' +work_dir = './work_dirs/test_aclnet/finegym/j_3' +model = dict( + type='RecognizerGCN', + backbone=dict( + type='GCN_Module', + gcn_ratio=0.125, + gcn_ctr='T', + gcn_ada='T', + tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'], + graph_cfg=dict( + layout='coco_new', + mode='random', + num_filter=8, + init_off=0.04, + init_std=0.02)), + cls_head=dict(type='SimpleHead', data_cfg='finegym', num_classes=99, in_channels=384)) +dataset_type = 'PoseDataset' +ann_file = '/data/lhd/pyskl_data/gym/gym_hrnet.pkl' +left_kp = [1, 3, 5, 7, 9, 11, 13, 15] +right_kp = [2, 4, 6, 8, 10, 12, 14, 16] +train_pipeline = [ + dict(type='UniformSampleFrames', clip_len=100), + dict(type='PoseDecode'), + dict( + type='Flip', + flip_ratio=0.5, + left_kp=[1, 3, 5, 7, 9, 11, 13, 15], + right_kp=[2, 4, 6, 8, 10, 12, 14, 16]), + dict(type='Kinetics_Transform'), + dict(type='GenSkeFeat', dataset='coco_new', feats=['j']), + 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=['j']), + 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=['j']), + 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=['j']), + 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=['j']), + 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=['j']), + dict(type='FormatGCNInput', num_person=2), + dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]), + dict(type='ToTensor', keys=['keypoint']) + ], + split='val')) +optimizer = dict( + type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True) +optimizer_config = dict(grad_clip=None) +lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False) +total_epochs = 150 +checkpoint_config = dict(interval=1) +evaluation = dict( + interval=1, metrics=['top_k_accuracy', 'mean_class_accuracy'], topk=(1, 5)) +log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')]) +dist_params = dict(backend='nccl') +gpu_ids = range(0, 1) + +2025-06-24 08:43:46,259 - pyskl - INFO - Set random seed to 1562067252, deterministic: False +2025-06-24 08:43:47,751 - pyskl - INFO - 20484 videos remain after valid thresholding +2025-06-24 08:43:51,939 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-06-24 08:43:51,939 - pyskl - INFO - Start running, host: lhd@zkyd, work_dir: /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3 +2025-06-24 08:43:51,940 - pyskl - INFO - Hooks will be executed in the following order: +before_run: +(VERY_HIGH ) CosineAnnealingLrUpdaterHook +(NORMAL ) CustomCheckpointHook +(NORMAL ) DistEvalHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_train_epoch: +(VERY_HIGH ) CosineAnnealingLrUpdaterHook +(NORMAL ) DistSamplerSeedHook +(NORMAL ) DistEvalHook +(LOW ) IterTimerHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_train_iter: +(VERY_HIGH ) CosineAnnealingLrUpdaterHook +(NORMAL ) DistEvalHook +(LOW ) IterTimerHook + -------------------- +after_train_iter: +(ABOVE_NORMAL) OptimizerHook +(NORMAL ) CustomCheckpointHook +(NORMAL ) DistEvalHook +(LOW ) IterTimerHook +(VERY_LOW ) TextLoggerHook + -------------------- +after_train_epoch: +(NORMAL ) CustomCheckpointHook +(NORMAL ) DistEvalHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_val_epoch: +(NORMAL ) DistSamplerSeedHook +(LOW ) IterTimerHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_val_iter: +(LOW ) IterTimerHook + -------------------- +after_val_iter: +(LOW ) IterTimerHook + -------------------- +after_val_epoch: +(VERY_LOW ) TextLoggerHook + -------------------- +after_run: +(VERY_LOW ) TextLoggerHook + -------------------- +2025-06-24 08:43:51,940 - pyskl - INFO - workflow: [('train', 1)], max: 150 epochs +2025-06-24 08:43:51,940 - pyskl - INFO - Checkpoints will be saved to /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3 by HardDiskBackend. +2025-06-24 08:44:32,072 - pyskl - INFO - Epoch [1][100/1281] lr: 2.500e-02, eta: 21:24:25, time: 0.401, data_time: 0.184, memory: 4082, top1_acc: 0.0481, top5_acc: 0.2094, loss_cls: 4.5701, loss: 4.5701 +2025-06-24 08:44:53,589 - pyskl - INFO - Epoch [1][200/1281] lr: 2.500e-02, eta: 16:26:03, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.0750, top5_acc: 0.3081, loss_cls: 4.6447, loss: 4.6447 +2025-06-24 08:45:15,092 - pyskl - INFO - Epoch [1][300/1281] lr: 2.500e-02, eta: 14:46:12, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.1100, top5_acc: 0.3419, loss_cls: 4.4468, loss: 4.4468 +2025-06-24 08:45:37,003 - pyskl - INFO - Epoch [1][400/1281] lr: 2.500e-02, eta: 13:59:21, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.1212, top5_acc: 0.4100, loss_cls: 4.1699, loss: 4.1699 +2025-06-24 08:45:58,764 - pyskl - INFO - Epoch [1][500/1281] lr: 2.500e-02, eta: 13:30:08, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.1575, top5_acc: 0.5012, loss_cls: 3.8703, loss: 3.8703 +2025-06-24 08:46:20,716 - pyskl - INFO - Epoch [1][600/1281] lr: 2.500e-02, eta: 13:11:34, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.1913, top5_acc: 0.5687, loss_cls: 3.5739, loss: 3.5739 +2025-06-24 08:46:42,452 - pyskl - INFO - Epoch [1][700/1281] lr: 2.500e-02, eta: 12:57:12, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.2450, top5_acc: 0.5975, loss_cls: 3.3258, loss: 3.3258 +2025-06-24 08:47:04,369 - pyskl - INFO - Epoch [1][800/1281] lr: 2.500e-02, eta: 12:47:04, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.2737, top5_acc: 0.6412, loss_cls: 3.1596, loss: 3.1596 +2025-06-24 08:47:26,219 - pyskl - INFO - Epoch [1][900/1281] lr: 2.500e-02, eta: 12:38:52, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.3031, top5_acc: 0.6994, loss_cls: 2.9544, loss: 2.9544 +2025-06-24 08:47:47,880 - pyskl - INFO - Epoch [1][1000/1281] lr: 2.500e-02, eta: 12:31:37, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.3294, top5_acc: 0.7100, loss_cls: 2.8390, loss: 2.8390 +2025-06-24 08:48:09,647 - pyskl - INFO - Epoch [1][1100/1281] lr: 2.500e-02, eta: 12:25:56, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.3531, top5_acc: 0.7269, loss_cls: 2.8031, loss: 2.8031 +2025-06-24 08:48:31,510 - pyskl - INFO - Epoch [1][1200/1281] lr: 2.500e-02, eta: 12:21:24, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.3731, top5_acc: 0.7775, loss_cls: 2.6199, loss: 2.6199 +2025-06-24 08:48:50,017 - pyskl - INFO - Saving checkpoint at 1 epochs +2025-06-24 08:49:33,271 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 08:49:33,340 - pyskl - INFO - +top1_acc 0.4055 +top5_acc 0.7757 +2025-06-24 08:49:33,340 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 08:49:33,347 - pyskl - INFO - +mean_acc 0.2065 +2025-06-24 08:49:33,536 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_1.pth. +2025-06-24 08:49:33,536 - pyskl - INFO - Best top1_acc is 0.4055 at 1 epoch. +2025-06-24 08:49:33,539 - pyskl - INFO - Epoch(val) [1][533] top1_acc: 0.4055, top5_acc: 0.7757, mean_class_accuracy: 0.2065 +2025-06-24 08:50:13,836 - pyskl - INFO - Epoch [2][100/1281] lr: 2.500e-02, eta: 12:16:23, time: 0.403, data_time: 0.185, memory: 4082, top1_acc: 0.3762, top5_acc: 0.7781, loss_cls: 2.5608, loss: 2.5608 +2025-06-24 08:50:35,805 - pyskl - INFO - Epoch [2][200/1281] lr: 2.500e-02, eta: 12:13:26, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.4350, top5_acc: 0.8181, loss_cls: 2.4102, loss: 2.4102 +2025-06-24 08:50:57,851 - pyskl - INFO - Epoch [2][300/1281] lr: 2.500e-02, eta: 12:10:58, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.4425, top5_acc: 0.8219, loss_cls: 2.3340, loss: 2.3340 +2025-06-24 08:51:19,727 - pyskl - INFO - Epoch [2][400/1281] lr: 2.500e-02, eta: 12:08:26, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.4475, top5_acc: 0.8231, loss_cls: 2.2844, loss: 2.2844 +2025-06-24 08:51:41,610 - pyskl - INFO - Epoch [2][500/1281] lr: 2.499e-02, eta: 12:06:09, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.4725, top5_acc: 0.8469, loss_cls: 2.1704, loss: 2.1704 +2025-06-24 08:52:03,308 - pyskl - INFO - Epoch [2][600/1281] lr: 2.499e-02, eta: 12:03:46, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.4481, top5_acc: 0.8562, loss_cls: 2.1963, loss: 2.1963 +2025-06-24 08:52:25,063 - pyskl - INFO - Epoch [2][700/1281] lr: 2.499e-02, eta: 12:01:41, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.4738, top5_acc: 0.8562, loss_cls: 2.1393, loss: 2.1393 +2025-06-24 08:52:46,824 - pyskl - INFO - Epoch [2][800/1281] lr: 2.499e-02, eta: 11:59:46, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.4988, top5_acc: 0.8806, loss_cls: 2.0107, loss: 2.0107 +2025-06-24 08:53:08,616 - pyskl - INFO - Epoch [2][900/1281] lr: 2.499e-02, eta: 11:58:02, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.5025, top5_acc: 0.8638, loss_cls: 2.0205, loss: 2.0205 +2025-06-24 08:53:30,212 - pyskl - INFO - Epoch [2][1000/1281] lr: 2.499e-02, eta: 11:56:09, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.5181, top5_acc: 0.8775, loss_cls: 1.9561, loss: 1.9561 +2025-06-24 08:53:52,040 - pyskl - INFO - Epoch [2][1100/1281] lr: 2.499e-02, eta: 11:54:42, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.5144, top5_acc: 0.8950, loss_cls: 1.9483, loss: 1.9483 +2025-06-24 08:54:14,052 - pyskl - INFO - Epoch [2][1200/1281] lr: 2.499e-02, eta: 11:53:35, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5056, top5_acc: 0.8825, loss_cls: 1.9601, loss: 1.9601 +2025-06-24 08:54:32,513 - pyskl - INFO - Saving checkpoint at 2 epochs +2025-06-24 08:55:15,395 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 08:55:15,451 - pyskl - INFO - +top1_acc 0.5043 +top5_acc 0.8811 +2025-06-24 08:55:15,451 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 08:55:15,458 - pyskl - INFO - +mean_acc 0.2876 +2025-06-24 08:55:15,462 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_1.pth was removed +2025-06-24 08:55:15,649 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_2.pth. +2025-06-24 08:55:15,649 - pyskl - INFO - Best top1_acc is 0.5043 at 2 epoch. +2025-06-24 08:55:15,652 - pyskl - INFO - Epoch(val) [2][533] top1_acc: 0.5043, top5_acc: 0.8811, mean_class_accuracy: 0.2876 +2025-06-24 08:55:56,110 - pyskl - INFO - Epoch [3][100/1281] lr: 2.499e-02, eta: 11:52:25, time: 0.405, data_time: 0.184, memory: 4082, top1_acc: 0.5431, top5_acc: 0.9050, loss_cls: 1.7942, loss: 1.7942 +2025-06-24 08:56:18,063 - pyskl - INFO - Epoch [3][200/1281] lr: 2.499e-02, eta: 11:51:21, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5556, top5_acc: 0.8988, loss_cls: 1.8330, loss: 1.8330 +2025-06-24 08:56:40,025 - pyskl - INFO - Epoch [3][300/1281] lr: 2.499e-02, eta: 11:50:21, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5450, top5_acc: 0.9006, loss_cls: 1.8062, loss: 1.8062 +2025-06-24 08:57:01,778 - pyskl - INFO - Epoch [3][400/1281] lr: 2.499e-02, eta: 11:49:09, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.5575, top5_acc: 0.9113, loss_cls: 1.7391, loss: 1.7391 +2025-06-24 08:57:23,632 - pyskl - INFO - Epoch [3][500/1281] lr: 2.498e-02, eta: 11:48:07, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.5694, top5_acc: 0.9119, loss_cls: 1.7590, loss: 1.7590 +2025-06-24 08:57:45,647 - pyskl - INFO - Epoch [3][600/1281] lr: 2.498e-02, eta: 11:47:18, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5494, top5_acc: 0.9206, loss_cls: 1.7890, loss: 1.7890 +2025-06-24 08:58:07,650 - pyskl - INFO - Epoch [3][700/1281] lr: 2.498e-02, eta: 11:46:29, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5581, top5_acc: 0.9213, loss_cls: 1.7464, loss: 1.7464 +2025-06-24 08:58:29,362 - pyskl - INFO - Epoch [3][800/1281] lr: 2.498e-02, eta: 11:45:25, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.5519, top5_acc: 0.9275, loss_cls: 1.7218, loss: 1.7218 +2025-06-24 08:58:51,112 - pyskl - INFO - Epoch [3][900/1281] lr: 2.498e-02, eta: 11:44:26, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.5563, top5_acc: 0.9069, loss_cls: 1.7678, loss: 1.7678 +2025-06-24 08:59:12,819 - pyskl - INFO - Epoch [3][1000/1281] lr: 2.498e-02, eta: 11:43:27, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.5769, top5_acc: 0.9244, loss_cls: 1.6812, loss: 1.6812 +2025-06-24 08:59:34,725 - pyskl - INFO - Epoch [3][1100/1281] lr: 2.498e-02, eta: 11:42:40, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.5950, top5_acc: 0.9294, loss_cls: 1.6191, loss: 1.6191 +2025-06-24 08:59:56,856 - pyskl - INFO - Epoch [3][1200/1281] lr: 2.498e-02, eta: 11:42:06, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.5725, top5_acc: 0.9200, loss_cls: 1.6828, loss: 1.6828 +2025-06-24 09:00:15,176 - pyskl - INFO - Saving checkpoint at 3 epochs +2025-06-24 09:00:58,669 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:00:58,740 - pyskl - INFO - +top1_acc 0.5643 +top5_acc 0.9060 +2025-06-24 09:00:58,740 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:00:58,748 - pyskl - INFO - +mean_acc 0.3926 +2025-06-24 09:00:58,753 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_2.pth was removed +2025-06-24 09:00:59,047 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_3.pth. +2025-06-24 09:00:59,048 - pyskl - INFO - Best top1_acc is 0.5643 at 3 epoch. +2025-06-24 09:00:59,050 - pyskl - INFO - Epoch(val) [3][533] top1_acc: 0.5643, top5_acc: 0.9060, mean_class_accuracy: 0.3926 +2025-06-24 09:01:38,940 - pyskl - INFO - Epoch [4][100/1281] lr: 2.497e-02, eta: 11:40:58, time: 0.399, data_time: 0.182, memory: 4082, top1_acc: 0.5850, top5_acc: 0.9356, loss_cls: 1.5944, loss: 1.5944 +2025-06-24 09:02:00,550 - pyskl - INFO - Epoch [4][200/1281] lr: 2.497e-02, eta: 11:40:01, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.6150, top5_acc: 0.9350, loss_cls: 1.5410, loss: 1.5410 +2025-06-24 09:02:22,147 - pyskl - INFO - Epoch [4][300/1281] lr: 2.497e-02, eta: 11:39:05, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.5969, top5_acc: 0.9387, loss_cls: 1.5897, loss: 1.5897 +2025-06-24 09:02:43,941 - pyskl - INFO - Epoch [4][400/1281] lr: 2.497e-02, eta: 11:38:20, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.6069, top5_acc: 0.9337, loss_cls: 1.6188, loss: 1.6188 +2025-06-24 09:03:05,560 - pyskl - INFO - Epoch [4][500/1281] lr: 2.497e-02, eta: 11:37:28, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.6225, top5_acc: 0.9369, loss_cls: 1.5508, loss: 1.5508 +2025-06-24 09:03:27,046 - pyskl - INFO - Epoch [4][600/1281] lr: 2.497e-02, eta: 11:36:32, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.6156, top5_acc: 0.9469, loss_cls: 1.4946, loss: 1.4946 +2025-06-24 09:03:48,939 - pyskl - INFO - Epoch [4][700/1281] lr: 2.497e-02, eta: 11:35:55, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6100, top5_acc: 0.9394, loss_cls: 1.5414, loss: 1.5414 +2025-06-24 09:04:10,536 - pyskl - INFO - Epoch [4][800/1281] lr: 2.496e-02, eta: 11:35:06, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.6138, top5_acc: 0.9463, loss_cls: 1.4844, loss: 1.4844 +2025-06-24 09:04:32,119 - pyskl - INFO - Epoch [4][900/1281] lr: 2.496e-02, eta: 11:34:17, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.6131, top5_acc: 0.9425, loss_cls: 1.5241, loss: 1.5241 +2025-06-24 09:04:53,852 - pyskl - INFO - Epoch [4][1000/1281] lr: 2.496e-02, eta: 11:33:36, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6412, top5_acc: 0.9563, loss_cls: 1.4403, loss: 1.4403 +2025-06-24 09:05:15,708 - pyskl - INFO - Epoch [4][1100/1281] lr: 2.496e-02, eta: 11:33:00, time: 0.219, data_time: 0.001, memory: 4082, top1_acc: 0.6250, top5_acc: 0.9425, loss_cls: 1.5077, loss: 1.5077 +2025-06-24 09:05:37,144 - pyskl - INFO - Epoch [4][1200/1281] lr: 2.496e-02, eta: 11:32:09, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.6362, top5_acc: 0.9494, loss_cls: 1.5025, loss: 1.5025 +2025-06-24 09:05:55,737 - pyskl - INFO - Saving checkpoint at 4 epochs +2025-06-24 09:06:39,261 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:06:39,323 - pyskl - INFO - +top1_acc 0.6142 +top5_acc 0.9337 +2025-06-24 09:06:39,323 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:06:39,330 - pyskl - INFO - +mean_acc 0.4420 +2025-06-24 09:06:39,334 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_3.pth was removed +2025-06-24 09:06:39,514 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_4.pth. +2025-06-24 09:06:39,515 - pyskl - INFO - Best top1_acc is 0.6142 at 4 epoch. +2025-06-24 09:06:39,517 - pyskl - INFO - Epoch(val) [4][533] top1_acc: 0.6142, top5_acc: 0.9337, mean_class_accuracy: 0.4420 +2025-06-24 09:07:19,048 - pyskl - INFO - Epoch [5][100/1281] lr: 2.495e-02, eta: 11:31:06, time: 0.395, data_time: 0.178, memory: 4082, top1_acc: 0.6294, top5_acc: 0.9513, loss_cls: 1.4474, loss: 1.4474 +2025-06-24 09:07:41,097 - pyskl - INFO - Epoch [5][200/1281] lr: 2.495e-02, eta: 11:30:39, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.6400, top5_acc: 0.9513, loss_cls: 1.4097, loss: 1.4097 +2025-06-24 09:08:02,902 - pyskl - INFO - Epoch [5][300/1281] lr: 2.495e-02, eta: 11:30:04, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.6538, top5_acc: 0.9563, loss_cls: 1.3751, loss: 1.3751 +2025-06-24 09:08:24,635 - pyskl - INFO - Epoch [5][400/1281] lr: 2.495e-02, eta: 11:29:27, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6319, top5_acc: 0.9519, loss_cls: 1.4211, loss: 1.4211 +2025-06-24 09:08:46,291 - pyskl - INFO - Epoch [5][500/1281] lr: 2.495e-02, eta: 11:28:47, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6525, top5_acc: 0.9556, loss_cls: 1.3878, loss: 1.3878 +2025-06-24 09:09:07,830 - pyskl - INFO - Epoch [5][600/1281] lr: 2.495e-02, eta: 11:28:05, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.6581, top5_acc: 0.9513, loss_cls: 1.3689, loss: 1.3689 +2025-06-24 09:09:29,558 - pyskl - INFO - Epoch [5][700/1281] lr: 2.494e-02, eta: 11:27:30, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6619, top5_acc: 0.9525, loss_cls: 1.3966, loss: 1.3966 +2025-06-24 09:09:51,560 - pyskl - INFO - Epoch [5][800/1281] lr: 2.494e-02, eta: 11:27:03, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.6556, top5_acc: 0.9550, loss_cls: 1.4045, loss: 1.4045 +2025-06-24 09:10:13,420 - pyskl - INFO - Epoch [5][900/1281] lr: 2.494e-02, eta: 11:26:32, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6713, top5_acc: 0.9544, loss_cls: 1.3445, loss: 1.3445 +2025-06-24 09:10:35,405 - pyskl - INFO - Epoch [5][1000/1281] lr: 2.494e-02, eta: 11:26:06, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.6706, top5_acc: 0.9519, loss_cls: 1.3663, loss: 1.3663 +2025-06-24 09:10:57,401 - pyskl - INFO - Epoch [5][1100/1281] lr: 2.494e-02, eta: 11:25:40, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.6444, top5_acc: 0.9556, loss_cls: 1.4250, loss: 1.4250 +2025-06-24 09:11:19,417 - pyskl - INFO - Epoch [5][1200/1281] lr: 2.493e-02, eta: 11:25:14, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.6512, top5_acc: 0.9619, loss_cls: 1.4186, loss: 1.4186 +2025-06-24 09:11:37,998 - pyskl - INFO - Saving checkpoint at 5 epochs +2025-06-24 09:12:20,797 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:12:20,864 - pyskl - INFO - +top1_acc 0.6658 +top5_acc 0.9489 +2025-06-24 09:12:20,864 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:12:20,871 - pyskl - INFO - +mean_acc 0.5409 +2025-06-24 09:12:20,876 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_4.pth was removed +2025-06-24 09:12:21,070 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_5.pth. +2025-06-24 09:12:21,070 - pyskl - INFO - Best top1_acc is 0.6658 at 5 epoch. +2025-06-24 09:12:21,073 - pyskl - INFO - Epoch(val) [5][533] top1_acc: 0.6658, top5_acc: 0.9489, mean_class_accuracy: 0.5409 +2025-06-24 09:13:01,559 - pyskl - INFO - Epoch [6][100/1281] lr: 2.493e-02, eta: 11:24:47, time: 0.405, data_time: 0.188, memory: 4082, top1_acc: 0.6769, top5_acc: 0.9581, loss_cls: 1.2951, loss: 1.2951 +2025-06-24 09:13:23,435 - pyskl - INFO - Epoch [6][200/1281] lr: 2.493e-02, eta: 11:24:17, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6719, top5_acc: 0.9625, loss_cls: 1.3166, loss: 1.3166 +2025-06-24 09:13:45,009 - pyskl - INFO - Epoch [6][300/1281] lr: 2.492e-02, eta: 11:23:40, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.6700, top5_acc: 0.9556, loss_cls: 1.3587, loss: 1.3587 +2025-06-24 09:14:06,956 - pyskl - INFO - Epoch [6][400/1281] lr: 2.492e-02, eta: 11:23:13, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6744, top5_acc: 0.9613, loss_cls: 1.2863, loss: 1.2863 +2025-06-24 09:14:28,883 - pyskl - INFO - Epoch [6][500/1281] lr: 2.492e-02, eta: 11:22:46, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6606, top5_acc: 0.9606, loss_cls: 1.3772, loss: 1.3772 +2025-06-24 09:14:50,631 - pyskl - INFO - Epoch [6][600/1281] lr: 2.492e-02, eta: 11:22:14, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6444, top5_acc: 0.9581, loss_cls: 1.3702, loss: 1.3702 +2025-06-24 09:15:12,451 - pyskl - INFO - Epoch [6][700/1281] lr: 2.492e-02, eta: 11:21:44, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7037, top5_acc: 0.9712, loss_cls: 1.2067, loss: 1.2067 +2025-06-24 09:15:34,075 - pyskl - INFO - Epoch [6][800/1281] lr: 2.491e-02, eta: 11:21:10, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7050, top5_acc: 0.9681, loss_cls: 1.2496, loss: 1.2496 +2025-06-24 09:15:55,901 - pyskl - INFO - Epoch [6][900/1281] lr: 2.491e-02, eta: 11:20:41, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.6956, top5_acc: 0.9706, loss_cls: 1.2511, loss: 1.2511 +2025-06-24 09:16:17,542 - pyskl - INFO - Epoch [6][1000/1281] lr: 2.491e-02, eta: 11:20:07, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7163, top5_acc: 0.9681, loss_cls: 1.1860, loss: 1.1860 +2025-06-24 09:16:39,250 - pyskl - INFO - Epoch [6][1100/1281] lr: 2.491e-02, eta: 11:19:36, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6669, top5_acc: 0.9569, loss_cls: 1.3157, loss: 1.3157 +2025-06-24 09:17:01,175 - pyskl - INFO - Epoch [6][1200/1281] lr: 2.490e-02, eta: 11:19:10, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6931, top5_acc: 0.9644, loss_cls: 1.2684, loss: 1.2684 +2025-06-24 09:17:19,739 - pyskl - INFO - Saving checkpoint at 6 epochs +2025-06-24 09:18:03,551 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:18:03,625 - pyskl - INFO - +top1_acc 0.6794 +top5_acc 0.9626 +2025-06-24 09:18:03,626 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:18:03,634 - pyskl - INFO - +mean_acc 0.5321 +2025-06-24 09:18:03,639 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_5.pth was removed +2025-06-24 09:18:03,819 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_6.pth. +2025-06-24 09:18:03,820 - pyskl - INFO - Best top1_acc is 0.6794 at 6 epoch. +2025-06-24 09:18:03,823 - pyskl - INFO - Epoch(val) [6][533] top1_acc: 0.6794, top5_acc: 0.9626, mean_class_accuracy: 0.5321 +2025-06-24 09:18:44,182 - pyskl - INFO - Epoch [7][100/1281] lr: 2.490e-02, eta: 11:18:39, time: 0.404, data_time: 0.187, memory: 4082, top1_acc: 0.7175, top5_acc: 0.9738, loss_cls: 1.1671, loss: 1.1671 +2025-06-24 09:19:05,815 - pyskl - INFO - Epoch [7][200/1281] lr: 2.490e-02, eta: 11:18:06, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.6869, top5_acc: 0.9681, loss_cls: 1.2487, loss: 1.2487 +2025-06-24 09:19:27,779 - pyskl - INFO - Epoch [7][300/1281] lr: 2.489e-02, eta: 11:17:42, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.6887, top5_acc: 0.9675, loss_cls: 1.2553, loss: 1.2553 +2025-06-24 09:19:49,470 - pyskl - INFO - Epoch [7][400/1281] lr: 2.489e-02, eta: 11:17:11, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6863, top5_acc: 0.9750, loss_cls: 1.2195, loss: 1.2195 +2025-06-24 09:20:11,149 - pyskl - INFO - Epoch [7][500/1281] lr: 2.489e-02, eta: 11:16:40, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6994, top5_acc: 0.9663, loss_cls: 1.2224, loss: 1.2224 +2025-06-24 09:20:32,832 - pyskl - INFO - Epoch [7][600/1281] lr: 2.489e-02, eta: 11:16:09, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7050, top5_acc: 0.9719, loss_cls: 1.2054, loss: 1.2054 +2025-06-24 09:20:54,589 - pyskl - INFO - Epoch [7][700/1281] lr: 2.488e-02, eta: 11:15:40, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7019, top5_acc: 0.9706, loss_cls: 1.2379, loss: 1.2379 +2025-06-24 09:21:16,325 - pyskl - INFO - Epoch [7][800/1281] lr: 2.488e-02, eta: 11:15:11, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7106, top5_acc: 0.9706, loss_cls: 1.1706, loss: 1.1706 +2025-06-24 09:21:38,084 - pyskl - INFO - Epoch [7][900/1281] lr: 2.488e-02, eta: 11:14:43, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7006, top5_acc: 0.9625, loss_cls: 1.2394, loss: 1.2394 +2025-06-24 09:21:59,468 - pyskl - INFO - Epoch [7][1000/1281] lr: 2.487e-02, eta: 11:14:06, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7081, top5_acc: 0.9663, loss_cls: 1.1906, loss: 1.1906 +2025-06-24 09:22:21,251 - pyskl - INFO - Epoch [7][1100/1281] lr: 2.487e-02, eta: 11:13:39, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.6987, top5_acc: 0.9712, loss_cls: 1.1923, loss: 1.1923 +2025-06-24 09:22:43,281 - pyskl - INFO - Epoch [7][1200/1281] lr: 2.487e-02, eta: 11:13:16, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7225, top5_acc: 0.9681, loss_cls: 1.1873, loss: 1.1873 +2025-06-24 09:23:01,698 - pyskl - INFO - Saving checkpoint at 7 epochs +2025-06-24 09:23:45,127 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:23:45,180 - pyskl - INFO - +top1_acc 0.6468 +top5_acc 0.9495 +2025-06-24 09:23:45,181 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:23:45,187 - pyskl - INFO - +mean_acc 0.4955 +2025-06-24 09:23:45,188 - pyskl - INFO - Epoch(val) [7][533] top1_acc: 0.6468, top5_acc: 0.9495, mean_class_accuracy: 0.4955 +2025-06-24 09:24:25,757 - pyskl - INFO - Epoch [8][100/1281] lr: 2.486e-02, eta: 11:12:50, time: 0.406, data_time: 0.185, memory: 4082, top1_acc: 0.7250, top5_acc: 0.9694, loss_cls: 1.1535, loss: 1.1535 +2025-06-24 09:24:47,911 - pyskl - INFO - Epoch [8][200/1281] lr: 2.486e-02, eta: 11:12:30, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.7006, top5_acc: 0.9725, loss_cls: 1.1758, loss: 1.1758 +2025-06-24 09:25:09,524 - pyskl - INFO - Epoch [8][300/1281] lr: 2.486e-02, eta: 11:11:59, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7100, top5_acc: 0.9631, loss_cls: 1.2033, loss: 1.2033 +2025-06-24 09:25:31,292 - pyskl - INFO - Epoch [8][400/1281] lr: 2.485e-02, eta: 11:11:32, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7206, top5_acc: 0.9694, loss_cls: 1.1482, loss: 1.1482 +2025-06-24 09:25:52,994 - pyskl - INFO - Epoch [8][500/1281] lr: 2.485e-02, eta: 11:11:03, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7281, top5_acc: 0.9731, loss_cls: 1.1504, loss: 1.1504 +2025-06-24 09:26:14,896 - pyskl - INFO - Epoch [8][600/1281] lr: 2.485e-02, eta: 11:10:38, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7269, top5_acc: 0.9712, loss_cls: 1.1216, loss: 1.1216 +2025-06-24 09:26:36,580 - pyskl - INFO - Epoch [8][700/1281] lr: 2.484e-02, eta: 11:10:10, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6850, top5_acc: 0.9688, loss_cls: 1.2523, loss: 1.2523 +2025-06-24 09:26:58,578 - pyskl - INFO - Epoch [8][800/1281] lr: 2.484e-02, eta: 11:09:47, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7225, top5_acc: 0.9694, loss_cls: 1.1646, loss: 1.1646 +2025-06-24 09:27:20,312 - pyskl - INFO - Epoch [8][900/1281] lr: 2.484e-02, eta: 11:09:19, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7044, top5_acc: 0.9681, loss_cls: 1.1931, loss: 1.1931 +2025-06-24 09:27:42,145 - pyskl - INFO - Epoch [8][1000/1281] lr: 2.483e-02, eta: 11:08:54, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7450, top5_acc: 0.9775, loss_cls: 1.0770, loss: 1.0770 +2025-06-24 09:28:03,975 - pyskl - INFO - Epoch [8][1100/1281] lr: 2.483e-02, eta: 11:08:28, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7081, top5_acc: 0.9669, loss_cls: 1.1703, loss: 1.1703 +2025-06-24 09:28:25,709 - pyskl - INFO - Epoch [8][1200/1281] lr: 2.483e-02, eta: 11:08:01, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7194, top5_acc: 0.9750, loss_cls: 1.1460, loss: 1.1460 +2025-06-24 09:28:43,922 - pyskl - INFO - Saving checkpoint at 8 epochs +2025-06-24 09:29:26,962 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:29:27,018 - pyskl - INFO - +top1_acc 0.7047 +top5_acc 0.9723 +2025-06-24 09:29:27,018 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:29:27,024 - pyskl - INFO - +mean_acc 0.5743 +2025-06-24 09:29:27,028 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_6.pth was removed +2025-06-24 09:29:27,196 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_8.pth. +2025-06-24 09:29:27,196 - pyskl - INFO - Best top1_acc is 0.7047 at 8 epoch. +2025-06-24 09:29:27,199 - pyskl - INFO - Epoch(val) [8][533] top1_acc: 0.7047, top5_acc: 0.9723, mean_class_accuracy: 0.5743 +2025-06-24 09:30:06,856 - pyskl - INFO - Epoch [9][100/1281] lr: 2.482e-02, eta: 11:07:17, time: 0.397, data_time: 0.179, memory: 4082, top1_acc: 0.7525, top5_acc: 0.9775, loss_cls: 1.0806, loss: 1.0806 +2025-06-24 09:30:28,761 - pyskl - INFO - Epoch [9][200/1281] lr: 2.482e-02, eta: 11:06:53, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7212, top5_acc: 0.9637, loss_cls: 1.1540, loss: 1.1540 +2025-06-24 09:30:50,533 - pyskl - INFO - Epoch [9][300/1281] lr: 2.481e-02, eta: 11:06:27, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7262, top5_acc: 0.9781, loss_cls: 1.1044, loss: 1.1044 +2025-06-24 09:31:12,238 - pyskl - INFO - Epoch [9][400/1281] lr: 2.481e-02, eta: 11:05:59, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7275, top5_acc: 0.9637, loss_cls: 1.1552, loss: 1.1552 +2025-06-24 09:31:34,091 - pyskl - INFO - Epoch [9][500/1281] lr: 2.481e-02, eta: 11:05:34, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7312, top5_acc: 0.9725, loss_cls: 1.1681, loss: 1.1681 +2025-06-24 09:31:55,732 - pyskl - INFO - Epoch [9][600/1281] lr: 2.480e-02, eta: 11:05:06, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7188, top5_acc: 0.9706, loss_cls: 1.1658, loss: 1.1658 +2025-06-24 09:32:17,449 - pyskl - INFO - Epoch [9][700/1281] lr: 2.480e-02, eta: 11:04:39, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7356, top5_acc: 0.9744, loss_cls: 1.1048, loss: 1.1048 +2025-06-24 09:32:39,719 - pyskl - INFO - Epoch [9][800/1281] lr: 2.480e-02, eta: 11:04:22, time: 0.223, data_time: 0.000, memory: 4082, top1_acc: 0.7475, top5_acc: 0.9775, loss_cls: 1.0463, loss: 1.0463 +2025-06-24 09:33:01,279 - pyskl - INFO - Epoch [9][900/1281] lr: 2.479e-02, eta: 11:03:52, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7431, top5_acc: 0.9744, loss_cls: 1.0907, loss: 1.0907 +2025-06-24 09:33:23,172 - pyskl - INFO - Epoch [9][1000/1281] lr: 2.479e-02, eta: 11:03:28, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7075, top5_acc: 0.9675, loss_cls: 1.1593, loss: 1.1593 +2025-06-24 09:33:45,066 - pyskl - INFO - Epoch [9][1100/1281] lr: 2.479e-02, eta: 11:03:05, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7388, top5_acc: 0.9831, loss_cls: 1.0454, loss: 1.0454 +2025-06-24 09:34:06,991 - pyskl - INFO - Epoch [9][1200/1281] lr: 2.478e-02, eta: 11:02:41, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7300, top5_acc: 0.9775, loss_cls: 1.0892, loss: 1.0892 +2025-06-24 09:34:25,354 - pyskl - INFO - Saving checkpoint at 9 epochs +2025-06-24 09:35:09,011 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:35:09,069 - pyskl - INFO - +top1_acc 0.6818 +top5_acc 0.9528 +2025-06-24 09:35:09,069 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:35:09,077 - pyskl - INFO - +mean_acc 0.5434 +2025-06-24 09:35:09,079 - pyskl - INFO - Epoch(val) [9][533] top1_acc: 0.6818, top5_acc: 0.9528, mean_class_accuracy: 0.5434 +2025-06-24 09:35:49,213 - pyskl - INFO - Epoch [10][100/1281] lr: 2.477e-02, eta: 11:02:06, time: 0.401, data_time: 0.183, memory: 4082, top1_acc: 0.7300, top5_acc: 0.9688, loss_cls: 1.1078, loss: 1.1078 +2025-06-24 09:36:11,077 - pyskl - INFO - Epoch [10][200/1281] lr: 2.477e-02, eta: 11:01:42, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7456, top5_acc: 0.9744, loss_cls: 1.0688, loss: 1.0688 +2025-06-24 09:36:32,790 - pyskl - INFO - Epoch [10][300/1281] lr: 2.477e-02, eta: 11:01:15, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7612, top5_acc: 0.9775, loss_cls: 1.0216, loss: 1.0216 +2025-06-24 09:36:54,412 - pyskl - INFO - Epoch [10][400/1281] lr: 2.476e-02, eta: 11:00:48, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7238, top5_acc: 0.9788, loss_cls: 1.0817, loss: 1.0817 +2025-06-24 09:37:16,120 - pyskl - INFO - Epoch [10][500/1281] lr: 2.476e-02, eta: 11:00:21, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7375, top5_acc: 0.9731, loss_cls: 1.0972, loss: 1.0972 +2025-06-24 09:37:37,989 - pyskl - INFO - Epoch [10][600/1281] lr: 2.476e-02, eta: 10:59:57, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7438, top5_acc: 0.9781, loss_cls: 1.0728, loss: 1.0728 +2025-06-24 09:37:59,484 - pyskl - INFO - Epoch [10][700/1281] lr: 2.475e-02, eta: 10:59:28, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7481, top5_acc: 0.9794, loss_cls: 1.0548, loss: 1.0548 +2025-06-24 09:38:21,265 - pyskl - INFO - Epoch [10][800/1281] lr: 2.475e-02, eta: 10:59:03, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7194, top5_acc: 0.9719, loss_cls: 1.1362, loss: 1.1362 +2025-06-24 09:38:42,961 - pyskl - INFO - Epoch [10][900/1281] lr: 2.474e-02, eta: 10:58:37, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7606, top5_acc: 0.9800, loss_cls: 1.0242, loss: 1.0242 +2025-06-24 09:39:04,947 - pyskl - INFO - Epoch [10][1000/1281] lr: 2.474e-02, eta: 10:58:15, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7562, top5_acc: 0.9756, loss_cls: 1.0616, loss: 1.0616 +2025-06-24 09:39:26,933 - pyskl - INFO - Epoch [10][1100/1281] lr: 2.473e-02, eta: 10:57:53, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7425, top5_acc: 0.9769, loss_cls: 1.0899, loss: 1.0899 +2025-06-24 09:39:48,842 - pyskl - INFO - Epoch [10][1200/1281] lr: 2.473e-02, eta: 10:57:30, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7369, top5_acc: 0.9681, loss_cls: 1.1191, loss: 1.1191 +2025-06-24 09:40:07,048 - pyskl - INFO - Saving checkpoint at 10 epochs +2025-06-24 09:40:50,638 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:40:50,696 - pyskl - INFO - +top1_acc 0.7249 +top5_acc 0.9768 +2025-06-24 09:40:50,696 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:40:50,703 - pyskl - INFO - +mean_acc 0.5902 +2025-06-24 09:40:50,708 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_8.pth was removed +2025-06-24 09:40:50,878 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_10.pth. +2025-06-24 09:40:50,878 - pyskl - INFO - Best top1_acc is 0.7249 at 10 epoch. +2025-06-24 09:40:50,881 - pyskl - INFO - Epoch(val) [10][533] top1_acc: 0.7249, top5_acc: 0.9768, mean_class_accuracy: 0.5902 +2025-06-24 09:41:31,541 - pyskl - INFO - Epoch [11][100/1281] lr: 2.472e-02, eta: 10:57:02, time: 0.407, data_time: 0.187, memory: 4082, top1_acc: 0.7581, top5_acc: 0.9806, loss_cls: 1.0316, loss: 1.0316 +2025-06-24 09:41:53,380 - pyskl - INFO - Epoch [11][200/1281] lr: 2.472e-02, eta: 10:56:38, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7625, top5_acc: 0.9800, loss_cls: 1.0077, loss: 1.0077 +2025-06-24 09:42:15,140 - pyskl - INFO - Epoch [11][300/1281] lr: 2.471e-02, eta: 10:56:12, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7356, top5_acc: 0.9850, loss_cls: 1.0735, loss: 1.0735 +2025-06-24 09:42:36,691 - pyskl - INFO - Epoch [11][400/1281] lr: 2.471e-02, eta: 10:55:44, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7450, top5_acc: 0.9750, loss_cls: 1.0758, loss: 1.0758 +2025-06-24 09:42:58,609 - pyskl - INFO - Epoch [11][500/1281] lr: 2.471e-02, eta: 10:55:21, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7538, top5_acc: 0.9862, loss_cls: 1.0199, loss: 1.0199 +2025-06-24 09:43:20,339 - pyskl - INFO - Epoch [11][600/1281] lr: 2.470e-02, eta: 10:54:56, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7481, top5_acc: 0.9825, loss_cls: 1.0227, loss: 1.0227 +2025-06-24 09:43:42,024 - pyskl - INFO - Epoch [11][700/1281] lr: 2.470e-02, eta: 10:54:30, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7456, top5_acc: 0.9775, loss_cls: 1.0706, loss: 1.0706 +2025-06-24 09:44:03,891 - pyskl - INFO - Epoch [11][800/1281] lr: 2.469e-02, eta: 10:54:07, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7588, top5_acc: 0.9806, loss_cls: 1.0122, loss: 1.0122 +2025-06-24 09:44:25,576 - pyskl - INFO - Epoch [11][900/1281] lr: 2.469e-02, eta: 10:53:41, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7719, top5_acc: 0.9812, loss_cls: 0.9842, loss: 0.9842 +2025-06-24 09:44:47,399 - pyskl - INFO - Epoch [11][1000/1281] lr: 2.468e-02, eta: 10:53:17, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7462, top5_acc: 0.9800, loss_cls: 0.9956, loss: 0.9956 +2025-06-24 09:45:08,894 - pyskl - INFO - Epoch [11][1100/1281] lr: 2.468e-02, eta: 10:52:48, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7619, top5_acc: 0.9819, loss_cls: 1.0040, loss: 1.0040 +2025-06-24 09:45:30,787 - pyskl - INFO - Epoch [11][1200/1281] lr: 2.467e-02, eta: 10:52:25, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7381, top5_acc: 0.9700, loss_cls: 1.0759, loss: 1.0759 +2025-06-24 09:45:48,820 - pyskl - INFO - Saving checkpoint at 11 epochs +2025-06-24 09:46:31,818 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:46:31,884 - pyskl - INFO - +top1_acc 0.7208 +top5_acc 0.9745 +2025-06-24 09:46:31,884 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:46:31,891 - pyskl - INFO - +mean_acc 0.6022 +2025-06-24 09:46:31,893 - pyskl - INFO - Epoch(val) [11][533] top1_acc: 0.7208, top5_acc: 0.9745, mean_class_accuracy: 0.6022 +2025-06-24 09:47:12,080 - pyskl - INFO - Epoch [12][100/1281] lr: 2.467e-02, eta: 10:51:51, time: 0.402, data_time: 0.182, memory: 4082, top1_acc: 0.7812, top5_acc: 0.9819, loss_cls: 0.9888, loss: 0.9888 +2025-06-24 09:47:34,033 - pyskl - INFO - Epoch [12][200/1281] lr: 2.466e-02, eta: 10:51:28, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7406, top5_acc: 0.9825, loss_cls: 1.0297, loss: 1.0297 +2025-06-24 09:47:55,910 - pyskl - INFO - Epoch [12][300/1281] lr: 2.466e-02, eta: 10:51:05, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7350, top5_acc: 0.9725, loss_cls: 1.0946, loss: 1.0946 +2025-06-24 09:48:17,587 - pyskl - INFO - Epoch [12][400/1281] lr: 2.465e-02, eta: 10:50:40, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7662, top5_acc: 0.9831, loss_cls: 0.9653, loss: 0.9653 +2025-06-24 09:48:39,307 - pyskl - INFO - Epoch [12][500/1281] lr: 2.465e-02, eta: 10:50:14, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7594, top5_acc: 0.9812, loss_cls: 1.0174, loss: 1.0174 +2025-06-24 09:49:01,041 - pyskl - INFO - Epoch [12][600/1281] lr: 2.464e-02, eta: 10:49:50, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7506, top5_acc: 0.9775, loss_cls: 1.0404, loss: 1.0404 +2025-06-24 09:49:22,743 - pyskl - INFO - Epoch [12][700/1281] lr: 2.464e-02, eta: 10:49:24, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7531, top5_acc: 0.9762, loss_cls: 1.0049, loss: 1.0049 +2025-06-24 09:49:44,681 - pyskl - INFO - Epoch [12][800/1281] lr: 2.463e-02, eta: 10:49:02, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7275, top5_acc: 0.9794, loss_cls: 1.0937, loss: 1.0937 +2025-06-24 09:50:06,171 - pyskl - INFO - Epoch [12][900/1281] lr: 2.463e-02, eta: 10:48:34, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7619, top5_acc: 0.9800, loss_cls: 1.0220, loss: 1.0220 +2025-06-24 09:50:28,069 - pyskl - INFO - Epoch [12][1000/1281] lr: 2.462e-02, eta: 10:48:12, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7556, top5_acc: 0.9844, loss_cls: 1.0195, loss: 1.0195 +2025-06-24 09:50:49,786 - pyskl - INFO - Epoch [12][1100/1281] lr: 2.462e-02, eta: 10:47:47, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7538, top5_acc: 0.9825, loss_cls: 1.0044, loss: 1.0044 +2025-06-24 09:51:11,690 - pyskl - INFO - Epoch [12][1200/1281] lr: 2.461e-02, eta: 10:47:24, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7506, top5_acc: 0.9862, loss_cls: 0.9951, loss: 0.9951 +2025-06-24 09:51:30,303 - pyskl - INFO - Saving checkpoint at 12 epochs +2025-06-24 09:52:13,193 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:52:13,247 - pyskl - INFO - +top1_acc 0.6665 +top5_acc 0.9623 +2025-06-24 09:52:13,247 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:52:13,253 - pyskl - INFO - +mean_acc 0.5639 +2025-06-24 09:52:13,255 - pyskl - INFO - Epoch(val) [12][533] top1_acc: 0.6665, top5_acc: 0.9623, mean_class_accuracy: 0.5639 +2025-06-24 09:52:53,320 - pyskl - INFO - Epoch [13][100/1281] lr: 2.460e-02, eta: 10:46:48, time: 0.401, data_time: 0.183, memory: 4082, top1_acc: 0.7762, top5_acc: 0.9806, loss_cls: 0.9615, loss: 0.9615 +2025-06-24 09:53:15,053 - pyskl - INFO - Epoch [13][200/1281] lr: 2.460e-02, eta: 10:46:23, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7644, top5_acc: 0.9762, loss_cls: 1.0036, loss: 1.0036 +2025-06-24 09:53:37,073 - pyskl - INFO - Epoch [13][300/1281] lr: 2.459e-02, eta: 10:46:02, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7394, top5_acc: 0.9744, loss_cls: 1.0414, loss: 1.0414 +2025-06-24 09:53:58,668 - pyskl - INFO - Epoch [13][400/1281] lr: 2.459e-02, eta: 10:45:36, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7531, top5_acc: 0.9856, loss_cls: 0.9807, loss: 0.9807 +2025-06-24 09:54:20,581 - pyskl - INFO - Epoch [13][500/1281] lr: 2.458e-02, eta: 10:45:13, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7575, top5_acc: 0.9800, loss_cls: 1.0021, loss: 1.0021 +2025-06-24 09:54:42,508 - pyskl - INFO - Epoch [13][600/1281] lr: 2.458e-02, eta: 10:44:51, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7619, top5_acc: 0.9850, loss_cls: 0.9934, loss: 0.9934 +2025-06-24 09:55:04,303 - pyskl - INFO - Epoch [13][700/1281] lr: 2.457e-02, eta: 10:44:27, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7612, top5_acc: 0.9856, loss_cls: 0.9818, loss: 0.9818 +2025-06-24 09:55:26,179 - pyskl - INFO - Epoch [13][800/1281] lr: 2.457e-02, eta: 10:44:04, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7450, top5_acc: 0.9744, loss_cls: 1.0680, loss: 1.0680 +2025-06-24 09:55:48,055 - pyskl - INFO - Epoch [13][900/1281] lr: 2.456e-02, eta: 10:43:41, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7675, top5_acc: 0.9819, loss_cls: 0.9743, loss: 0.9743 +2025-06-24 09:56:09,605 - pyskl - INFO - Epoch [13][1000/1281] lr: 2.455e-02, eta: 10:43:15, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7400, top5_acc: 0.9800, loss_cls: 1.0403, loss: 1.0403 +2025-06-24 09:56:31,604 - pyskl - INFO - Epoch [13][1100/1281] lr: 2.455e-02, eta: 10:42:53, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7619, top5_acc: 0.9862, loss_cls: 0.9958, loss: 0.9958 +2025-06-24 09:56:53,464 - pyskl - INFO - Epoch [13][1200/1281] lr: 2.454e-02, eta: 10:42:30, time: 0.219, data_time: 0.001, memory: 4082, top1_acc: 0.7500, top5_acc: 0.9806, loss_cls: 1.0114, loss: 1.0114 +2025-06-24 09:57:11,624 - pyskl - INFO - Saving checkpoint at 13 epochs +2025-06-24 09:57:54,900 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:57:54,954 - pyskl - INFO - +top1_acc 0.7135 +top5_acc 0.9731 +2025-06-24 09:57:54,954 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:57:54,961 - pyskl - INFO - +mean_acc 0.6199 +2025-06-24 09:57:54,962 - pyskl - INFO - Epoch(val) [13][533] top1_acc: 0.7135, top5_acc: 0.9731, mean_class_accuracy: 0.6199 +2025-06-24 09:58:35,630 - pyskl - INFO - Epoch [14][100/1281] lr: 2.453e-02, eta: 10:42:00, time: 0.407, data_time: 0.187, memory: 4082, top1_acc: 0.7806, top5_acc: 0.9825, loss_cls: 0.9280, loss: 0.9280 +2025-06-24 09:58:57,554 - pyskl - INFO - Epoch [14][200/1281] lr: 2.453e-02, eta: 10:41:38, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7631, top5_acc: 0.9769, loss_cls: 1.0215, loss: 1.0215 +2025-06-24 09:59:19,173 - pyskl - INFO - Epoch [14][300/1281] lr: 2.452e-02, eta: 10:41:12, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7731, top5_acc: 0.9894, loss_cls: 0.9434, loss: 0.9434 +2025-06-24 09:59:40,999 - pyskl - INFO - Epoch [14][400/1281] lr: 2.452e-02, eta: 10:40:49, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7825, top5_acc: 0.9775, loss_cls: 0.9529, loss: 0.9529 +2025-06-24 10:00:02,878 - pyskl - INFO - Epoch [14][500/1281] lr: 2.451e-02, eta: 10:40:26, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7512, top5_acc: 0.9825, loss_cls: 1.0303, loss: 1.0303 +2025-06-24 10:00:24,678 - pyskl - INFO - Epoch [14][600/1281] lr: 2.451e-02, eta: 10:40:03, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7656, top5_acc: 0.9812, loss_cls: 0.9730, loss: 0.9730 +2025-06-24 10:00:46,714 - pyskl - INFO - Epoch [14][700/1281] lr: 2.450e-02, eta: 10:39:42, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7762, top5_acc: 0.9819, loss_cls: 0.9658, loss: 0.9658 +2025-06-24 10:01:08,673 - pyskl - INFO - Epoch [14][800/1281] lr: 2.449e-02, eta: 10:39:20, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7462, top5_acc: 0.9819, loss_cls: 0.9999, loss: 0.9999 +2025-06-24 10:01:30,372 - pyskl - INFO - Epoch [14][900/1281] lr: 2.449e-02, eta: 10:38:55, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7662, top5_acc: 0.9844, loss_cls: 0.9796, loss: 0.9796 +2025-06-24 10:01:52,229 - pyskl - INFO - Epoch [14][1000/1281] lr: 2.448e-02, eta: 10:38:32, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7538, top5_acc: 0.9844, loss_cls: 1.0340, loss: 1.0340 +2025-06-24 10:02:14,155 - pyskl - INFO - Epoch [14][1100/1281] lr: 2.448e-02, eta: 10:38:10, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7788, top5_acc: 0.9819, loss_cls: 0.9571, loss: 0.9571 +2025-06-24 10:02:35,782 - pyskl - INFO - Epoch [14][1200/1281] lr: 2.447e-02, eta: 10:37:45, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7662, top5_acc: 0.9881, loss_cls: 0.9343, loss: 0.9343 +2025-06-24 10:02:54,040 - pyskl - INFO - Saving checkpoint at 14 epochs +2025-06-24 10:03:37,307 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:03:37,376 - pyskl - INFO - +top1_acc 0.7304 +top5_acc 0.9736 +2025-06-24 10:03:37,376 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:03:37,384 - pyskl - INFO - +mean_acc 0.6129 +2025-06-24 10:03:37,388 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_10.pth was removed +2025-06-24 10:03:37,592 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_14.pth. +2025-06-24 10:03:37,592 - pyskl - INFO - Best top1_acc is 0.7304 at 14 epoch. +2025-06-24 10:03:37,594 - pyskl - INFO - Epoch(val) [14][533] top1_acc: 0.7304, top5_acc: 0.9736, mean_class_accuracy: 0.6129 +2025-06-24 10:04:18,512 - pyskl - INFO - Epoch [15][100/1281] lr: 2.446e-02, eta: 10:37:16, time: 0.409, data_time: 0.191, memory: 4082, top1_acc: 0.7681, top5_acc: 0.9794, loss_cls: 1.0094, loss: 1.0094 +2025-06-24 10:04:40,178 - pyskl - INFO - Epoch [15][200/1281] lr: 2.445e-02, eta: 10:36:52, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7606, top5_acc: 0.9862, loss_cls: 0.9574, loss: 0.9574 +2025-06-24 10:05:01,947 - pyskl - INFO - Epoch [15][300/1281] lr: 2.445e-02, eta: 10:36:28, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7575, top5_acc: 0.9781, loss_cls: 0.9881, loss: 0.9881 +2025-06-24 10:05:23,568 - pyskl - INFO - Epoch [15][400/1281] lr: 2.444e-02, eta: 10:36:03, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7937, top5_acc: 0.9862, loss_cls: 0.9176, loss: 0.9176 +2025-06-24 10:05:45,305 - pyskl - INFO - Epoch [15][500/1281] lr: 2.444e-02, eta: 10:35:39, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7488, top5_acc: 0.9756, loss_cls: 1.0340, loss: 1.0340 +2025-06-24 10:06:07,010 - pyskl - INFO - Epoch [15][600/1281] lr: 2.443e-02, eta: 10:35:14, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7869, top5_acc: 0.9844, loss_cls: 0.8784, loss: 0.8784 +2025-06-24 10:06:28,660 - pyskl - INFO - Epoch [15][700/1281] lr: 2.442e-02, eta: 10:34:49, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7794, top5_acc: 0.9831, loss_cls: 0.9416, loss: 0.9416 +2025-06-24 10:06:50,474 - pyskl - INFO - Epoch [15][800/1281] lr: 2.442e-02, eta: 10:34:26, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7481, top5_acc: 0.9819, loss_cls: 1.0205, loss: 1.0205 +2025-06-24 10:07:12,143 - pyskl - INFO - Epoch [15][900/1281] lr: 2.441e-02, eta: 10:34:02, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7800, top5_acc: 0.9850, loss_cls: 0.9154, loss: 0.9154 +2025-06-24 10:07:34,140 - pyskl - INFO - Epoch [15][1000/1281] lr: 2.441e-02, eta: 10:33:40, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7731, top5_acc: 0.9862, loss_cls: 0.9509, loss: 0.9509 +2025-06-24 10:07:55,991 - pyskl - INFO - Epoch [15][1100/1281] lr: 2.440e-02, eta: 10:33:17, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7700, top5_acc: 0.9800, loss_cls: 0.9338, loss: 0.9338 +2025-06-24 10:08:17,764 - pyskl - INFO - Epoch [15][1200/1281] lr: 2.439e-02, eta: 10:32:54, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7831, top5_acc: 0.9862, loss_cls: 0.9280, loss: 0.9280 +2025-06-24 10:08:36,220 - pyskl - INFO - Saving checkpoint at 15 epochs +2025-06-24 10:09:19,805 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:09:19,859 - pyskl - INFO - +top1_acc 0.7242 +top5_acc 0.9709 +2025-06-24 10:09:19,859 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:09:19,865 - pyskl - INFO - +mean_acc 0.6372 +2025-06-24 10:09:19,866 - pyskl - INFO - Epoch(val) [15][533] top1_acc: 0.7242, top5_acc: 0.9709, mean_class_accuracy: 0.6372 +2025-06-24 10:10:00,640 - pyskl - INFO - Epoch [16][100/1281] lr: 2.438e-02, eta: 10:32:23, time: 0.408, data_time: 0.189, memory: 4082, top1_acc: 0.7831, top5_acc: 0.9838, loss_cls: 0.9363, loss: 0.9363 +2025-06-24 10:10:22,321 - pyskl - INFO - Epoch [16][200/1281] lr: 2.438e-02, eta: 10:31:59, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7975, top5_acc: 0.9919, loss_cls: 0.8607, loss: 0.8607 +2025-06-24 10:10:44,175 - pyskl - INFO - Epoch [16][300/1281] lr: 2.437e-02, eta: 10:31:36, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7837, top5_acc: 0.9800, loss_cls: 0.9410, loss: 0.9410 +2025-06-24 10:11:05,727 - pyskl - INFO - Epoch [16][400/1281] lr: 2.436e-02, eta: 10:31:11, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7812, top5_acc: 0.9856, loss_cls: 0.9125, loss: 0.9125 +2025-06-24 10:11:27,663 - pyskl - INFO - Epoch [16][500/1281] lr: 2.436e-02, eta: 10:30:49, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7694, top5_acc: 0.9838, loss_cls: 0.9793, loss: 0.9793 +2025-06-24 10:11:49,151 - pyskl - INFO - Epoch [16][600/1281] lr: 2.435e-02, eta: 10:30:23, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7788, top5_acc: 0.9794, loss_cls: 0.9387, loss: 0.9387 +2025-06-24 10:12:11,004 - pyskl - INFO - Epoch [16][700/1281] lr: 2.434e-02, eta: 10:30:00, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7794, top5_acc: 0.9862, loss_cls: 0.9184, loss: 0.9184 +2025-06-24 10:12:33,014 - pyskl - INFO - Epoch [16][800/1281] lr: 2.434e-02, eta: 10:29:38, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7538, top5_acc: 0.9869, loss_cls: 1.0088, loss: 1.0088 +2025-06-24 10:12:54,952 - pyskl - INFO - Epoch [16][900/1281] lr: 2.433e-02, eta: 10:29:16, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7669, top5_acc: 0.9831, loss_cls: 0.9634, loss: 0.9634 +2025-06-24 10:13:17,241 - pyskl - INFO - Epoch [16][1000/1281] lr: 2.432e-02, eta: 10:28:57, time: 0.223, data_time: 0.000, memory: 4082, top1_acc: 0.7600, top5_acc: 0.9831, loss_cls: 0.9875, loss: 0.9875 +2025-06-24 10:13:39,420 - pyskl - INFO - Epoch [16][1100/1281] lr: 2.432e-02, eta: 10:28:37, time: 0.222, data_time: 0.000, memory: 4082, top1_acc: 0.7906, top5_acc: 0.9856, loss_cls: 0.9115, loss: 0.9115 +2025-06-24 10:14:01,404 - pyskl - INFO - Epoch [16][1200/1281] lr: 2.431e-02, eta: 10:28:16, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7662, top5_acc: 0.9831, loss_cls: 0.9420, loss: 0.9420 +2025-06-24 10:14:20,155 - pyskl - INFO - Saving checkpoint at 16 epochs +2025-06-24 10:15:04,588 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:15:04,643 - pyskl - INFO - +top1_acc 0.7313 +top5_acc 0.9738 +2025-06-24 10:15:04,643 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:15:04,650 - pyskl - INFO - +mean_acc 0.6078 +2025-06-24 10:15:04,654 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_14.pth was removed +2025-06-24 10:15:04,825 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_16.pth. +2025-06-24 10:15:04,825 - pyskl - INFO - Best top1_acc is 0.7313 at 16 epoch. +2025-06-24 10:15:04,828 - pyskl - INFO - Epoch(val) [16][533] top1_acc: 0.7313, top5_acc: 0.9738, mean_class_accuracy: 0.6078 +2025-06-24 10:16:00,979 - pyskl - INFO - Epoch [17][100/1281] lr: 2.430e-02, eta: 10:29:53, time: 0.561, data_time: 0.189, memory: 4082, top1_acc: 0.8006, top5_acc: 0.9888, loss_cls: 0.8509, loss: 0.8509 +2025-06-24 10:16:42,664 - pyskl - INFO - Epoch [17][200/1281] lr: 2.429e-02, eta: 10:32:13, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7825, top5_acc: 0.9825, loss_cls: 0.9163, loss: 0.9163 +2025-06-24 10:17:24,524 - pyskl - INFO - Epoch [17][300/1281] lr: 2.428e-02, eta: 10:34:34, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.7981, top5_acc: 0.9831, loss_cls: 0.8639, loss: 0.8639 +2025-06-24 10:18:06,166 - pyskl - INFO - Epoch [17][400/1281] lr: 2.428e-02, eta: 10:36:51, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7794, top5_acc: 0.9862, loss_cls: 0.8774, loss: 0.8774 +2025-06-24 10:18:48,059 - pyskl - INFO - Epoch [17][500/1281] lr: 2.427e-02, eta: 10:39:08, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.7731, top5_acc: 0.9838, loss_cls: 0.9487, loss: 0.9487 +2025-06-24 10:19:29,913 - pyskl - INFO - Epoch [17][600/1281] lr: 2.426e-02, eta: 10:41:23, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.7738, top5_acc: 0.9869, loss_cls: 0.9320, loss: 0.9320 +2025-06-24 10:20:11,488 - pyskl - INFO - Epoch [17][700/1281] lr: 2.426e-02, eta: 10:43:35, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7662, top5_acc: 0.9875, loss_cls: 0.9679, loss: 0.9679 +2025-06-24 10:20:53,540 - pyskl - INFO - Epoch [17][800/1281] lr: 2.425e-02, eta: 10:45:48, time: 0.421, data_time: 0.000, memory: 4082, top1_acc: 0.7919, top5_acc: 0.9794, loss_cls: 0.9421, loss: 0.9421 +2025-06-24 10:21:35,323 - pyskl - INFO - Epoch [17][900/1281] lr: 2.424e-02, eta: 10:47:58, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.7744, top5_acc: 0.9856, loss_cls: 0.9018, loss: 0.9018 +2025-06-24 10:22:17,128 - pyskl - INFO - Epoch [17][1000/1281] lr: 2.424e-02, eta: 10:50:06, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.7638, top5_acc: 0.9812, loss_cls: 0.9799, loss: 0.9799 +2025-06-24 10:22:58,923 - pyskl - INFO - Epoch [17][1100/1281] lr: 2.423e-02, eta: 10:52:13, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.7831, top5_acc: 0.9850, loss_cls: 0.9214, loss: 0.9214 +2025-06-24 10:23:41,948 - pyskl - INFO - Epoch [17][1200/1281] lr: 2.422e-02, eta: 10:54:28, time: 0.430, data_time: 0.001, memory: 4082, top1_acc: 0.7625, top5_acc: 0.9825, loss_cls: 0.9558, loss: 0.9558 +2025-06-24 10:24:17,006 - pyskl - INFO - Saving checkpoint at 17 epochs +2025-06-24 10:25:25,815 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:25:25,887 - pyskl - INFO - +top1_acc 0.7412 +top5_acc 0.9757 +2025-06-24 10:25:25,887 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:25:25,896 - pyskl - INFO - +mean_acc 0.6472 +2025-06-24 10:25:25,900 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_16.pth was removed +2025-06-24 10:25:26,098 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_17.pth. +2025-06-24 10:25:26,098 - pyskl - INFO - Best top1_acc is 0.7412 at 17 epoch. +2025-06-24 10:25:26,101 - pyskl - INFO - Epoch(val) [17][533] top1_acc: 0.7412, top5_acc: 0.9757, mean_class_accuracy: 0.6472 +2025-06-24 10:26:21,619 - pyskl - INFO - Epoch [18][100/1281] lr: 2.421e-02, eta: 10:55:34, time: 0.555, data_time: 0.191, memory: 4082, top1_acc: 0.7969, top5_acc: 0.9912, loss_cls: 0.8348, loss: 0.8348 +2025-06-24 10:27:04,532 - pyskl - INFO - Epoch [18][200/1281] lr: 2.420e-02, eta: 10:57:44, time: 0.429, data_time: 0.000, memory: 4082, top1_acc: 0.7881, top5_acc: 0.9831, loss_cls: 0.8765, loss: 0.8765 +2025-06-24 10:27:46,214 - pyskl - INFO - Epoch [18][300/1281] lr: 2.419e-02, eta: 10:59:43, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7963, top5_acc: 0.9856, loss_cls: 0.8832, loss: 0.8832 +2025-06-24 10:28:27,903 - pyskl - INFO - Epoch [18][400/1281] lr: 2.419e-02, eta: 11:01:41, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7869, top5_acc: 0.9875, loss_cls: 0.8729, loss: 0.8729 +2025-06-24 10:29:09,625 - pyskl - INFO - Epoch [18][500/1281] lr: 2.418e-02, eta: 11:03:38, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7994, top5_acc: 0.9881, loss_cls: 0.8677, loss: 0.8677 +2025-06-24 10:29:51,310 - pyskl - INFO - Epoch [18][600/1281] lr: 2.417e-02, eta: 11:05:33, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7644, top5_acc: 0.9862, loss_cls: 0.9251, loss: 0.9251 +2025-06-24 10:30:32,865 - pyskl - INFO - Epoch [18][700/1281] lr: 2.417e-02, eta: 11:07:25, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7869, top5_acc: 0.9825, loss_cls: 0.9262, loss: 0.9262 +2025-06-24 10:31:14,471 - pyskl - INFO - Epoch [18][800/1281] lr: 2.416e-02, eta: 11:09:17, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8044, top5_acc: 0.9844, loss_cls: 0.8887, loss: 0.8887 +2025-06-24 10:31:56,265 - pyskl - INFO - Epoch [18][900/1281] lr: 2.415e-02, eta: 11:11:09, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.7788, top5_acc: 0.9825, loss_cls: 0.9392, loss: 0.9392 +2025-06-24 10:32:37,981 - pyskl - INFO - Epoch [18][1000/1281] lr: 2.414e-02, eta: 11:12:59, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7956, top5_acc: 0.9856, loss_cls: 0.8727, loss: 0.8727 +2025-06-24 10:33:19,790 - pyskl - INFO - Epoch [18][1100/1281] lr: 2.414e-02, eta: 11:14:48, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.7863, top5_acc: 0.9838, loss_cls: 0.9103, loss: 0.9103 +2025-06-24 10:34:01,525 - pyskl - INFO - Epoch [18][1200/1281] lr: 2.413e-02, eta: 11:16:35, time: 0.417, data_time: 0.001, memory: 4082, top1_acc: 0.7825, top5_acc: 0.9881, loss_cls: 0.9693, loss: 0.9693 +2025-06-24 10:34:35,987 - pyskl - INFO - Saving checkpoint at 18 epochs +2025-06-24 10:35:42,597 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:35:42,665 - pyskl - INFO - +top1_acc 0.7287 +top5_acc 0.9742 +2025-06-24 10:35:42,665 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:35:42,673 - pyskl - INFO - +mean_acc 0.6340 +2025-06-24 10:35:42,675 - pyskl - INFO - Epoch(val) [18][533] top1_acc: 0.7287, top5_acc: 0.9742, mean_class_accuracy: 0.6340 +2025-06-24 10:36:37,703 - pyskl - INFO - Epoch [19][100/1281] lr: 2.411e-02, eta: 11:17:16, time: 0.550, data_time: 0.196, memory: 4082, top1_acc: 0.7881, top5_acc: 0.9919, loss_cls: 0.8641, loss: 0.8641 +2025-06-24 10:37:21,354 - pyskl - INFO - Epoch [19][200/1281] lr: 2.411e-02, eta: 11:19:14, time: 0.436, data_time: 0.000, memory: 4082, top1_acc: 0.7881, top5_acc: 0.9881, loss_cls: 0.8689, loss: 0.8689 +2025-06-24 10:38:03,016 - pyskl - INFO - Epoch [19][300/1281] lr: 2.410e-02, eta: 11:20:57, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7975, top5_acc: 0.9844, loss_cls: 0.8675, loss: 0.8675 +2025-06-24 10:38:44,738 - pyskl - INFO - Epoch [19][400/1281] lr: 2.409e-02, eta: 11:22:39, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7975, top5_acc: 0.9850, loss_cls: 0.8806, loss: 0.8806 +2025-06-24 10:39:26,512 - pyskl - INFO - Epoch [19][500/1281] lr: 2.408e-02, eta: 11:24:20, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8019, top5_acc: 0.9862, loss_cls: 0.8432, loss: 0.8432 +2025-06-24 10:40:08,209 - pyskl - INFO - Epoch [19][600/1281] lr: 2.408e-02, eta: 11:25:59, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8044, top5_acc: 0.9850, loss_cls: 0.8508, loss: 0.8508 +2025-06-24 10:40:50,089 - pyskl - INFO - Epoch [19][700/1281] lr: 2.407e-02, eta: 11:27:38, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.7844, top5_acc: 0.9831, loss_cls: 0.9206, loss: 0.9206 +2025-06-24 10:41:31,818 - pyskl - INFO - Epoch [19][800/1281] lr: 2.406e-02, eta: 11:29:15, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8013, top5_acc: 0.9825, loss_cls: 0.8903, loss: 0.8903 +2025-06-24 10:42:13,665 - pyskl - INFO - Epoch [19][900/1281] lr: 2.405e-02, eta: 11:30:52, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8000, top5_acc: 0.9850, loss_cls: 0.8730, loss: 0.8730 +2025-06-24 10:42:55,468 - pyskl - INFO - Epoch [19][1000/1281] lr: 2.405e-02, eta: 11:32:27, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.7875, top5_acc: 0.9912, loss_cls: 0.8816, loss: 0.8816 +2025-06-24 10:43:37,391 - pyskl - INFO - Epoch [19][1100/1281] lr: 2.404e-02, eta: 11:34:02, time: 0.419, data_time: 0.001, memory: 4082, top1_acc: 0.8031, top5_acc: 0.9900, loss_cls: 0.8453, loss: 0.8453 +2025-06-24 10:44:19,131 - pyskl - INFO - Epoch [19][1200/1281] lr: 2.403e-02, eta: 11:35:34, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7788, top5_acc: 0.9844, loss_cls: 0.9350, loss: 0.9350 +2025-06-24 10:44:53,899 - pyskl - INFO - Saving checkpoint at 19 epochs +2025-06-24 10:46:00,642 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:46:00,706 - pyskl - INFO - +top1_acc 0.7548 +top5_acc 0.9757 +2025-06-24 10:46:00,707 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:46:00,714 - pyskl - INFO - +mean_acc 0.6235 +2025-06-24 10:46:00,718 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_17.pth was removed +2025-06-24 10:46:00,893 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_19.pth. +2025-06-24 10:46:00,894 - pyskl - INFO - Best top1_acc is 0.7548 at 19 epoch. +2025-06-24 10:46:00,897 - pyskl - INFO - Epoch(val) [19][533] top1_acc: 0.7548, top5_acc: 0.9757, mean_class_accuracy: 0.6235 +2025-06-24 10:46:55,320 - pyskl - INFO - Epoch [20][100/1281] lr: 2.402e-02, eta: 11:35:54, time: 0.544, data_time: 0.193, memory: 4082, top1_acc: 0.7950, top5_acc: 0.9881, loss_cls: 0.8913, loss: 0.8913 +2025-06-24 10:47:36,955 - pyskl - INFO - Epoch [20][200/1281] lr: 2.401e-02, eta: 11:37:23, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8025, top5_acc: 0.9881, loss_cls: 0.8483, loss: 0.8483 +2025-06-24 10:48:18,704 - pyskl - INFO - Epoch [20][300/1281] lr: 2.400e-02, eta: 11:38:53, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8056, top5_acc: 0.9894, loss_cls: 0.8538, loss: 0.8538 +2025-06-24 10:49:00,733 - pyskl - INFO - Epoch [20][400/1281] lr: 2.399e-02, eta: 11:40:23, time: 0.420, data_time: 0.000, memory: 4082, top1_acc: 0.7913, top5_acc: 0.9869, loss_cls: 0.8903, loss: 0.8903 +2025-06-24 10:49:42,508 - pyskl - INFO - Epoch [20][500/1281] lr: 2.398e-02, eta: 11:41:50, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8013, top5_acc: 0.9888, loss_cls: 0.8409, loss: 0.8409 +2025-06-24 10:50:24,529 - pyskl - INFO - Epoch [20][600/1281] lr: 2.398e-02, eta: 11:43:18, time: 0.420, data_time: 0.000, memory: 4082, top1_acc: 0.8031, top5_acc: 0.9894, loss_cls: 0.8552, loss: 0.8552 +2025-06-24 10:51:06,344 - pyskl - INFO - Epoch [20][700/1281] lr: 2.397e-02, eta: 11:44:43, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8013, top5_acc: 0.9850, loss_cls: 0.8934, loss: 0.8934 +2025-06-24 10:51:48,242 - pyskl - INFO - Epoch [20][800/1281] lr: 2.396e-02, eta: 11:46:08, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.7844, top5_acc: 0.9869, loss_cls: 0.8840, loss: 0.8840 +2025-06-24 10:52:30,154 - pyskl - INFO - Epoch [20][900/1281] lr: 2.395e-02, eta: 11:47:32, time: 0.419, data_time: 0.001, memory: 4082, top1_acc: 0.8000, top5_acc: 0.9850, loss_cls: 0.8544, loss: 0.8544 +2025-06-24 10:53:11,984 - pyskl - INFO - Epoch [20][1000/1281] lr: 2.394e-02, eta: 11:48:54, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.7913, top5_acc: 0.9844, loss_cls: 0.8727, loss: 0.8727 +2025-06-24 10:53:53,789 - pyskl - INFO - Epoch [20][1100/1281] lr: 2.393e-02, eta: 11:50:16, time: 0.418, data_time: 0.001, memory: 4082, top1_acc: 0.7925, top5_acc: 0.9850, loss_cls: 0.8720, loss: 0.8720 +2025-06-24 10:54:35,621 - pyskl - INFO - Epoch [20][1200/1281] lr: 2.393e-02, eta: 11:51:36, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.7931, top5_acc: 0.9869, loss_cls: 0.8867, loss: 0.8867 +2025-06-24 10:55:10,781 - pyskl - INFO - Saving checkpoint at 20 epochs +2025-06-24 10:56:16,903 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:56:16,958 - pyskl - INFO - +top1_acc 0.7491 +top5_acc 0.9799 +2025-06-24 10:56:16,958 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:56:16,971 - pyskl - INFO - +mean_acc 0.6408 +2025-06-24 10:56:16,974 - pyskl - INFO - Epoch(val) [20][533] top1_acc: 0.7491, top5_acc: 0.9799, mean_class_accuracy: 0.6408 +2025-06-24 10:57:10,357 - pyskl - INFO - Epoch [21][100/1281] lr: 2.391e-02, eta: 11:51:35, time: 0.534, data_time: 0.196, memory: 4082, top1_acc: 0.7913, top5_acc: 0.9850, loss_cls: 0.8699, loss: 0.8699 +2025-06-24 10:57:51,863 - pyskl - INFO - Epoch [21][200/1281] lr: 2.390e-02, eta: 11:52:52, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.7975, top5_acc: 0.9900, loss_cls: 0.8140, loss: 0.8140 +2025-06-24 10:58:33,751 - pyskl - INFO - Epoch [21][300/1281] lr: 2.389e-02, eta: 11:54:10, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.7981, top5_acc: 0.9900, loss_cls: 0.8674, loss: 0.8674 +2025-06-24 10:59:15,733 - pyskl - INFO - Epoch [21][400/1281] lr: 2.389e-02, eta: 11:55:27, time: 0.420, data_time: 0.000, memory: 4082, top1_acc: 0.8056, top5_acc: 0.9906, loss_cls: 0.8336, loss: 0.8336 +2025-06-24 10:59:57,640 - pyskl - INFO - Epoch [21][500/1281] lr: 2.388e-02, eta: 11:56:44, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.8025, top5_acc: 0.9881, loss_cls: 0.8819, loss: 0.8819 +2025-06-24 11:00:39,271 - pyskl - INFO - Epoch [21][600/1281] lr: 2.387e-02, eta: 11:57:57, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8087, top5_acc: 0.9900, loss_cls: 0.8191, loss: 0.8191 +2025-06-24 11:01:21,093 - pyskl - INFO - Epoch [21][700/1281] lr: 2.386e-02, eta: 11:59:11, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8169, top5_acc: 0.9881, loss_cls: 0.7946, loss: 0.7946 +2025-06-24 11:02:02,915 - pyskl - INFO - Epoch [21][800/1281] lr: 2.385e-02, eta: 12:00:24, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8013, top5_acc: 0.9838, loss_cls: 0.8613, loss: 0.8613 +2025-06-24 11:02:44,856 - pyskl - INFO - Epoch [21][900/1281] lr: 2.384e-02, eta: 12:01:37, time: 0.419, data_time: 0.001, memory: 4082, top1_acc: 0.8000, top5_acc: 0.9875, loss_cls: 0.8858, loss: 0.8858 +2025-06-24 11:03:26,687 - pyskl - INFO - Epoch [21][1000/1281] lr: 2.383e-02, eta: 12:02:49, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8031, top5_acc: 0.9881, loss_cls: 0.8281, loss: 0.8281 +2025-06-24 11:04:10,606 - pyskl - INFO - Epoch [21][1100/1281] lr: 2.383e-02, eta: 12:04:12, time: 0.439, data_time: 0.000, memory: 4082, top1_acc: 0.8050, top5_acc: 0.9875, loss_cls: 0.8627, loss: 0.8627 +2025-06-24 11:04:54,493 - pyskl - INFO - Epoch [21][1200/1281] lr: 2.382e-02, eta: 12:05:35, time: 0.439, data_time: 0.000, memory: 4082, top1_acc: 0.7875, top5_acc: 0.9856, loss_cls: 0.9523, loss: 0.9523 +2025-06-24 11:05:29,636 - pyskl - INFO - Saving checkpoint at 21 epochs +2025-06-24 11:06:34,729 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:06:34,784 - pyskl - INFO - +top1_acc 0.7429 +top5_acc 0.9782 +2025-06-24 11:06:34,784 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:06:34,794 - pyskl - INFO - +mean_acc 0.6412 +2025-06-24 11:06:34,795 - pyskl - INFO - Epoch(val) [21][533] top1_acc: 0.7429, top5_acc: 0.9782, mean_class_accuracy: 0.6412 +2025-06-24 11:07:28,568 - pyskl - INFO - Epoch [22][100/1281] lr: 2.380e-02, eta: 12:05:24, time: 0.538, data_time: 0.194, memory: 4082, top1_acc: 0.7937, top5_acc: 0.9875, loss_cls: 0.8706, loss: 0.8706 +2025-06-24 11:08:10,286 - pyskl - INFO - Epoch [22][200/1281] lr: 2.379e-02, eta: 12:06:31, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8169, top5_acc: 0.9888, loss_cls: 0.7965, loss: 0.7965 +2025-06-24 11:08:52,130 - pyskl - INFO - Epoch [22][300/1281] lr: 2.378e-02, eta: 12:07:39, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8187, top5_acc: 0.9831, loss_cls: 0.8336, loss: 0.8336 +2025-06-24 11:09:33,782 - pyskl - INFO - Epoch [22][400/1281] lr: 2.378e-02, eta: 12:08:44, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8050, top5_acc: 0.9869, loss_cls: 0.8626, loss: 0.8626 +2025-06-24 11:10:15,688 - pyskl - INFO - Epoch [22][500/1281] lr: 2.377e-02, eta: 12:09:50, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.8213, top5_acc: 0.9906, loss_cls: 0.8119, loss: 0.8119 +2025-06-24 11:10:57,322 - pyskl - INFO - Epoch [22][600/1281] lr: 2.376e-02, eta: 12:10:53, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8087, top5_acc: 0.9850, loss_cls: 0.8276, loss: 0.8276 +2025-06-24 11:11:39,190 - pyskl - INFO - Epoch [22][700/1281] lr: 2.375e-02, eta: 12:11:57, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.8137, top5_acc: 0.9844, loss_cls: 0.8374, loss: 0.8374 +2025-06-24 11:12:21,044 - pyskl - INFO - Epoch [22][800/1281] lr: 2.374e-02, eta: 12:13:01, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.7987, top5_acc: 0.9875, loss_cls: 0.8566, loss: 0.8566 +2025-06-24 11:13:02,900 - pyskl - INFO - Epoch [22][900/1281] lr: 2.373e-02, eta: 12:14:03, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.8037, top5_acc: 0.9869, loss_cls: 0.8631, loss: 0.8631 +2025-06-24 11:13:44,715 - pyskl - INFO - Epoch [22][1000/1281] lr: 2.372e-02, eta: 12:15:05, time: 0.418, data_time: 0.001, memory: 4082, top1_acc: 0.8113, top5_acc: 0.9881, loss_cls: 0.8121, loss: 0.8121 +2025-06-24 11:14:27,627 - pyskl - INFO - Epoch [22][1100/1281] lr: 2.371e-02, eta: 12:16:12, time: 0.429, data_time: 0.001, memory: 4082, top1_acc: 0.8044, top5_acc: 0.9831, loss_cls: 0.8696, loss: 0.8696 +2025-06-24 11:15:11,551 - pyskl - INFO - Epoch [22][1200/1281] lr: 2.370e-02, eta: 12:17:25, time: 0.439, data_time: 0.000, memory: 4082, top1_acc: 0.8000, top5_acc: 0.9888, loss_cls: 0.8725, loss: 0.8725 +2025-06-24 11:15:46,392 - pyskl - INFO - Saving checkpoint at 22 epochs +2025-06-24 11:16:50,629 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:16:50,684 - pyskl - INFO - +top1_acc 0.7621 +top5_acc 0.9768 +2025-06-24 11:16:50,685 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:16:50,691 - pyskl - INFO - +mean_acc 0.6450 +2025-06-24 11:16:50,696 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_19.pth was removed +2025-06-24 11:16:50,877 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_22.pth. +2025-06-24 11:16:50,877 - pyskl - INFO - Best top1_acc is 0.7621 at 22 epoch. +2025-06-24 11:16:50,879 - pyskl - INFO - Epoch(val) [22][533] top1_acc: 0.7621, top5_acc: 0.9768, mean_class_accuracy: 0.6450 +2025-06-24 11:17:43,214 - pyskl - INFO - Epoch [23][100/1281] lr: 2.369e-02, eta: 12:16:56, time: 0.523, data_time: 0.196, memory: 4082, top1_acc: 0.8137, top5_acc: 0.9875, loss_cls: 0.8264, loss: 0.8264 +2025-06-24 11:18:24,987 - pyskl - INFO - Epoch [23][200/1281] lr: 2.368e-02, eta: 12:17:55, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8094, top5_acc: 0.9862, loss_cls: 0.7876, loss: 0.7876 +2025-06-24 11:19:07,488 - pyskl - INFO - Epoch [23][300/1281] lr: 2.367e-02, eta: 12:18:56, time: 0.425, data_time: 0.000, memory: 4082, top1_acc: 0.8175, top5_acc: 0.9894, loss_cls: 0.8081, loss: 0.8081 +2025-06-24 11:19:49,137 - pyskl - INFO - Epoch [23][400/1281] lr: 2.366e-02, eta: 12:19:53, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8006, top5_acc: 0.9856, loss_cls: 0.8554, loss: 0.8554 +2025-06-24 11:20:30,847 - pyskl - INFO - Epoch [23][500/1281] lr: 2.365e-02, eta: 12:20:48, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7987, top5_acc: 0.9875, loss_cls: 0.8439, loss: 0.8439 +2025-06-24 11:21:12,423 - pyskl - INFO - Epoch [23][600/1281] lr: 2.364e-02, eta: 12:21:43, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.7944, top5_acc: 0.9906, loss_cls: 0.8396, loss: 0.8396 +2025-06-24 11:21:54,086 - pyskl - INFO - Epoch [23][700/1281] lr: 2.363e-02, eta: 12:22:37, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8119, top5_acc: 0.9856, loss_cls: 0.8475, loss: 0.8475 +2025-06-24 11:22:35,859 - pyskl - INFO - Epoch [23][800/1281] lr: 2.362e-02, eta: 12:23:31, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8156, top5_acc: 0.9862, loss_cls: 0.8220, loss: 0.8220 +2025-06-24 11:23:17,866 - pyskl - INFO - Epoch [23][900/1281] lr: 2.361e-02, eta: 12:24:26, time: 0.420, data_time: 0.000, memory: 4082, top1_acc: 0.8069, top5_acc: 0.9869, loss_cls: 0.8537, loss: 0.8537 +2025-06-24 11:23:59,735 - pyskl - INFO - Epoch [23][1000/1281] lr: 2.360e-02, eta: 12:25:20, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.8137, top5_acc: 0.9875, loss_cls: 0.8036, loss: 0.8036 +2025-06-24 11:24:41,517 - pyskl - INFO - Epoch [23][1100/1281] lr: 2.359e-02, eta: 12:26:12, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8037, top5_acc: 0.9844, loss_cls: 0.8492, loss: 0.8492 +2025-06-24 11:25:23,412 - pyskl - INFO - Epoch [23][1200/1281] lr: 2.359e-02, eta: 12:27:04, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.7981, top5_acc: 0.9875, loss_cls: 0.8447, loss: 0.8447 +2025-06-24 11:25:57,887 - pyskl - INFO - Saving checkpoint at 23 epochs +2025-06-24 11:27:01,700 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:27:01,769 - pyskl - INFO - +top1_acc 0.7329 +top5_acc 0.9702 +2025-06-24 11:27:01,769 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:27:01,777 - pyskl - INFO - +mean_acc 0.6301 +2025-06-24 11:27:01,779 - pyskl - INFO - Epoch(val) [23][533] top1_acc: 0.7329, top5_acc: 0.9702, mean_class_accuracy: 0.6301 +2025-06-24 11:27:54,316 - pyskl - INFO - Epoch [24][100/1281] lr: 2.357e-02, eta: 12:26:29, time: 0.525, data_time: 0.200, memory: 4082, top1_acc: 0.8181, top5_acc: 0.9844, loss_cls: 0.8137, loss: 0.8137 +2025-06-24 11:28:36,103 - pyskl - INFO - Epoch [24][200/1281] lr: 2.356e-02, eta: 12:27:20, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8081, top5_acc: 0.9850, loss_cls: 0.8651, loss: 0.8651 +2025-06-24 11:29:17,770 - pyskl - INFO - Epoch [24][300/1281] lr: 2.355e-02, eta: 12:28:09, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8219, top5_acc: 0.9881, loss_cls: 0.7736, loss: 0.7736 +2025-06-24 11:29:59,554 - pyskl - INFO - Epoch [24][400/1281] lr: 2.354e-02, eta: 12:28:58, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.7981, top5_acc: 0.9825, loss_cls: 0.8365, loss: 0.8365 +2025-06-24 11:30:41,393 - pyskl - INFO - Epoch [24][500/1281] lr: 2.353e-02, eta: 12:29:47, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8106, top5_acc: 0.9869, loss_cls: 0.8216, loss: 0.8216 +2025-06-24 11:31:23,193 - pyskl - INFO - Epoch [24][600/1281] lr: 2.352e-02, eta: 12:30:35, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8225, top5_acc: 0.9875, loss_cls: 0.7859, loss: 0.7859 +2025-06-24 11:32:04,804 - pyskl - INFO - Epoch [24][700/1281] lr: 2.351e-02, eta: 12:31:22, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8037, top5_acc: 0.9850, loss_cls: 0.8448, loss: 0.8448 +2025-06-24 11:32:46,491 - pyskl - INFO - Epoch [24][800/1281] lr: 2.350e-02, eta: 12:32:08, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8187, top5_acc: 0.9894, loss_cls: 0.8247, loss: 0.8247 +2025-06-24 11:33:28,191 - pyskl - INFO - Epoch [24][900/1281] lr: 2.349e-02, eta: 12:32:54, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8125, top5_acc: 0.9919, loss_cls: 0.7858, loss: 0.7858 +2025-06-24 11:34:10,074 - pyskl - INFO - Epoch [24][1000/1281] lr: 2.348e-02, eta: 12:33:40, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.8087, top5_acc: 0.9900, loss_cls: 0.8174, loss: 0.8174 +2025-06-24 11:34:51,968 - pyskl - INFO - Epoch [24][1100/1281] lr: 2.347e-02, eta: 12:34:25, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.8294, top5_acc: 0.9925, loss_cls: 0.7547, loss: 0.7547 +2025-06-24 11:35:33,678 - pyskl - INFO - Epoch [24][1200/1281] lr: 2.346e-02, eta: 12:35:10, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8113, top5_acc: 0.9894, loss_cls: 0.8686, loss: 0.8686 +2025-06-24 11:36:08,388 - pyskl - INFO - Saving checkpoint at 24 epochs +2025-06-24 11:37:11,073 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:37:11,142 - pyskl - INFO - +top1_acc 0.7531 +top5_acc 0.9795 +2025-06-24 11:37:11,142 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:37:11,150 - pyskl - INFO - +mean_acc 0.6626 +2025-06-24 11:37:11,153 - pyskl - INFO - Epoch(val) [24][533] top1_acc: 0.7531, top5_acc: 0.9795, mean_class_accuracy: 0.6626 +2025-06-24 11:38:03,144 - pyskl - INFO - Epoch [25][100/1281] lr: 2.344e-02, eta: 12:34:25, time: 0.520, data_time: 0.201, memory: 4082, top1_acc: 0.7987, top5_acc: 0.9925, loss_cls: 0.8009, loss: 0.8009 +2025-06-24 11:38:44,900 - pyskl - INFO - Epoch [25][200/1281] lr: 2.343e-02, eta: 12:35:08, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8213, top5_acc: 0.9912, loss_cls: 0.7514, loss: 0.7514 +2025-06-24 11:39:26,604 - pyskl - INFO - Epoch [25][300/1281] lr: 2.342e-02, eta: 12:35:51, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8219, top5_acc: 0.9906, loss_cls: 0.7318, loss: 0.7318 +2025-06-24 11:40:08,349 - pyskl - INFO - Epoch [25][400/1281] lr: 2.341e-02, eta: 12:36:33, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8075, top5_acc: 0.9869, loss_cls: 0.7940, loss: 0.7940 +2025-06-24 11:40:49,969 - pyskl - INFO - Epoch [25][500/1281] lr: 2.340e-02, eta: 12:37:14, time: 0.416, data_time: 0.001, memory: 4082, top1_acc: 0.8131, top5_acc: 0.9912, loss_cls: 0.7886, loss: 0.7886 +2025-06-24 11:41:31,553 - pyskl - INFO - Epoch [25][600/1281] lr: 2.339e-02, eta: 12:37:54, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8363, top5_acc: 0.9906, loss_cls: 0.7457, loss: 0.7457 +2025-06-24 11:42:13,159 - pyskl - INFO - Epoch [25][700/1281] lr: 2.338e-02, eta: 12:38:34, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8156, top5_acc: 0.9875, loss_cls: 0.7844, loss: 0.7844 +2025-06-24 11:42:55,093 - pyskl - INFO - Epoch [25][800/1281] lr: 2.337e-02, eta: 12:39:15, time: 0.419, data_time: 0.001, memory: 4082, top1_acc: 0.7987, top5_acc: 0.9844, loss_cls: 0.8658, loss: 0.8658 +2025-06-24 11:43:36,742 - pyskl - INFO - Epoch [25][900/1281] lr: 2.336e-02, eta: 12:39:54, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8137, top5_acc: 0.9881, loss_cls: 0.8248, loss: 0.8248 +2025-06-24 11:44:18,404 - pyskl - INFO - Epoch [25][1000/1281] lr: 2.335e-02, eta: 12:40:32, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8106, top5_acc: 0.9819, loss_cls: 0.8412, loss: 0.8412 +2025-06-24 11:45:00,121 - pyskl - INFO - Epoch [25][1100/1281] lr: 2.334e-02, eta: 12:41:11, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8106, top5_acc: 0.9875, loss_cls: 0.8222, loss: 0.8222 +2025-06-24 11:45:41,967 - pyskl - INFO - Epoch [25][1200/1281] lr: 2.333e-02, eta: 12:41:49, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8094, top5_acc: 0.9869, loss_cls: 0.8484, loss: 0.8484 +2025-06-24 11:46:16,526 - pyskl - INFO - Saving checkpoint at 25 epochs +2025-06-24 11:47:18,180 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:47:18,234 - pyskl - INFO - +top1_acc 0.7741 +top5_acc 0.9837 +2025-06-24 11:47:18,234 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:47:18,241 - pyskl - INFO - +mean_acc 0.6618 +2025-06-24 11:47:18,245 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_22.pth was removed +2025-06-24 11:47:18,480 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_25.pth. +2025-06-24 11:47:18,481 - pyskl - INFO - Best top1_acc is 0.7741 at 25 epoch. +2025-06-24 11:47:18,484 - pyskl - INFO - Epoch(val) [25][533] top1_acc: 0.7741, top5_acc: 0.9837, mean_class_accuracy: 0.6618 +2025-06-24 11:48:10,454 - pyskl - INFO - Epoch [26][100/1281] lr: 2.332e-02, eta: 12:40:59, time: 0.520, data_time: 0.195, memory: 4082, top1_acc: 0.8250, top5_acc: 0.9906, loss_cls: 0.7379, loss: 0.7379 +2025-06-24 11:48:53,061 - pyskl - INFO - Epoch [26][200/1281] lr: 2.330e-02, eta: 12:41:41, time: 0.426, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9912, loss_cls: 0.7454, loss: 0.7454 +2025-06-24 11:49:34,734 - pyskl - INFO - Epoch [26][300/1281] lr: 2.329e-02, eta: 12:42:17, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9888, loss_cls: 0.7328, loss: 0.7328 +2025-06-24 11:50:16,359 - pyskl - INFO - Epoch [26][400/1281] lr: 2.328e-02, eta: 12:42:52, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9912, loss_cls: 0.7852, loss: 0.7852 +2025-06-24 11:50:58,022 - pyskl - INFO - Epoch [26][500/1281] lr: 2.327e-02, eta: 12:43:27, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8163, top5_acc: 0.9912, loss_cls: 0.7952, loss: 0.7952 +2025-06-24 11:51:39,847 - pyskl - INFO - Epoch [26][600/1281] lr: 2.326e-02, eta: 12:44:03, time: 0.418, data_time: 0.001, memory: 4082, top1_acc: 0.7944, top5_acc: 0.9850, loss_cls: 0.8554, loss: 0.8554 +2025-06-24 11:52:21,595 - pyskl - INFO - Epoch [26][700/1281] lr: 2.325e-02, eta: 12:44:37, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9931, loss_cls: 0.7538, loss: 0.7538 +2025-06-24 11:53:03,291 - pyskl - INFO - Epoch [26][800/1281] lr: 2.324e-02, eta: 12:45:11, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8025, top5_acc: 0.9912, loss_cls: 0.8257, loss: 0.8257 +2025-06-24 11:53:44,968 - pyskl - INFO - Epoch [26][900/1281] lr: 2.323e-02, eta: 12:45:45, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7937, top5_acc: 0.9850, loss_cls: 0.8865, loss: 0.8865 +2025-06-24 11:54:26,819 - pyskl - INFO - Epoch [26][1000/1281] lr: 2.322e-02, eta: 12:46:19, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8150, top5_acc: 0.9944, loss_cls: 0.7608, loss: 0.7608 +2025-06-24 11:55:08,648 - pyskl - INFO - Epoch [26][1100/1281] lr: 2.321e-02, eta: 12:46:52, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8181, top5_acc: 0.9875, loss_cls: 0.7751, loss: 0.7751 +2025-06-24 11:55:50,340 - pyskl - INFO - Epoch [26][1200/1281] lr: 2.320e-02, eta: 12:47:24, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8175, top5_acc: 0.9925, loss_cls: 0.7824, loss: 0.7824 +2025-06-24 11:56:24,572 - pyskl - INFO - Saving checkpoint at 26 epochs +2025-06-24 11:57:27,121 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:57:27,188 - pyskl - INFO - +top1_acc 0.7906 +top5_acc 0.9850 +2025-06-24 11:57:27,188 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:57:27,196 - pyskl - INFO - +mean_acc 0.7004 +2025-06-24 11:57:27,201 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_25.pth was removed +2025-06-24 11:57:27,392 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_26.pth. +2025-06-24 11:57:27,392 - pyskl - INFO - Best top1_acc is 0.7906 at 26 epoch. +2025-06-24 11:57:27,395 - pyskl - INFO - Epoch(val) [26][533] top1_acc: 0.7906, top5_acc: 0.9850, mean_class_accuracy: 0.7004 +2025-06-24 11:58:19,167 - pyskl - INFO - Epoch [27][100/1281] lr: 2.318e-02, eta: 12:46:28, time: 0.518, data_time: 0.198, memory: 4082, top1_acc: 0.8181, top5_acc: 0.9900, loss_cls: 0.7718, loss: 0.7718 +2025-06-24 11:59:02,206 - pyskl - INFO - Epoch [27][200/1281] lr: 2.317e-02, eta: 12:47:06, time: 0.430, data_time: 0.000, memory: 4082, top1_acc: 0.8506, top5_acc: 0.9906, loss_cls: 0.7000, loss: 0.7000 +2025-06-24 11:59:43,700 - pyskl - INFO - Epoch [27][300/1281] lr: 2.316e-02, eta: 12:47:36, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8244, top5_acc: 0.9938, loss_cls: 0.7685, loss: 0.7685 +2025-06-24 12:00:25,393 - pyskl - INFO - Epoch [27][400/1281] lr: 2.315e-02, eta: 12:48:06, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8175, top5_acc: 0.9881, loss_cls: 0.7921, loss: 0.7921 +2025-06-24 12:01:07,030 - pyskl - INFO - Epoch [27][500/1281] lr: 2.314e-02, eta: 12:48:36, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8325, top5_acc: 0.9906, loss_cls: 0.7198, loss: 0.7198 +2025-06-24 12:01:48,962 - pyskl - INFO - Epoch [27][600/1281] lr: 2.313e-02, eta: 12:49:06, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.8206, top5_acc: 0.9912, loss_cls: 0.7582, loss: 0.7582 +2025-06-24 12:02:30,620 - pyskl - INFO - Epoch [27][700/1281] lr: 2.312e-02, eta: 12:49:35, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8213, top5_acc: 0.9894, loss_cls: 0.7722, loss: 0.7722 +2025-06-24 12:03:12,402 - pyskl - INFO - Epoch [27][800/1281] lr: 2.311e-02, eta: 12:50:04, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8275, top5_acc: 0.9938, loss_cls: 0.7684, loss: 0.7684 +2025-06-24 12:03:54,157 - pyskl - INFO - Epoch [27][900/1281] lr: 2.310e-02, eta: 12:50:33, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.7950, top5_acc: 0.9888, loss_cls: 0.8390, loss: 0.8390 +2025-06-24 12:04:35,928 - pyskl - INFO - Epoch [27][1000/1281] lr: 2.308e-02, eta: 12:51:01, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8237, top5_acc: 0.9906, loss_cls: 0.8104, loss: 0.8104 +2025-06-24 12:05:17,546 - pyskl - INFO - Epoch [27][1100/1281] lr: 2.307e-02, eta: 12:51:28, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8269, top5_acc: 0.9900, loss_cls: 0.7508, loss: 0.7508 +2025-06-24 12:05:59,333 - pyskl - INFO - Epoch [27][1200/1281] lr: 2.306e-02, eta: 12:51:56, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8094, top5_acc: 0.9906, loss_cls: 0.7813, loss: 0.7813 +2025-06-24 12:06:33,969 - pyskl - INFO - Saving checkpoint at 27 epochs +2025-06-24 12:07:34,430 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:07:34,496 - pyskl - INFO - +top1_acc 0.7614 +top5_acc 0.9756 +2025-06-24 12:07:34,496 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:07:34,504 - pyskl - INFO - +mean_acc 0.6781 +2025-06-24 12:07:34,507 - pyskl - INFO - Epoch(val) [27][533] top1_acc: 0.7614, top5_acc: 0.9756, mean_class_accuracy: 0.6781 +2025-06-24 12:08:24,668 - pyskl - INFO - Epoch [28][100/1281] lr: 2.304e-02, eta: 12:50:49, time: 0.502, data_time: 0.191, memory: 4082, top1_acc: 0.8400, top5_acc: 0.9944, loss_cls: 0.7364, loss: 0.7364 +2025-06-24 12:09:08,608 - pyskl - INFO - Epoch [28][200/1281] lr: 2.303e-02, eta: 12:51:25, time: 0.439, data_time: 0.000, memory: 4082, top1_acc: 0.8219, top5_acc: 0.9906, loss_cls: 0.7725, loss: 0.7725 +2025-06-24 12:09:50,956 - pyskl - INFO - Epoch [28][300/1281] lr: 2.302e-02, eta: 12:51:54, time: 0.423, data_time: 0.000, memory: 4082, top1_acc: 0.8219, top5_acc: 0.9894, loss_cls: 0.7541, loss: 0.7541 +2025-06-24 12:10:32,521 - pyskl - INFO - Epoch [28][400/1281] lr: 2.301e-02, eta: 12:52:19, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9919, loss_cls: 0.7345, loss: 0.7345 +2025-06-24 12:11:14,189 - pyskl - INFO - Epoch [28][500/1281] lr: 2.300e-02, eta: 12:52:44, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8081, top5_acc: 0.9888, loss_cls: 0.8141, loss: 0.8141 +2025-06-24 12:11:55,967 - pyskl - INFO - Epoch [28][600/1281] lr: 2.299e-02, eta: 12:53:10, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8050, top5_acc: 0.9919, loss_cls: 0.8057, loss: 0.8057 +2025-06-24 12:12:38,991 - pyskl - INFO - Epoch [28][700/1281] lr: 2.298e-02, eta: 12:53:40, time: 0.430, data_time: 0.000, memory: 4082, top1_acc: 0.8237, top5_acc: 0.9888, loss_cls: 0.7809, loss: 0.7809 +2025-06-24 12:13:22,237 - pyskl - INFO - Epoch [28][800/1281] lr: 2.297e-02, eta: 12:54:11, time: 0.432, data_time: 0.000, memory: 4082, top1_acc: 0.8294, top5_acc: 0.9944, loss_cls: 0.7260, loss: 0.7260 +2025-06-24 12:14:03,844 - pyskl - INFO - Epoch [28][900/1281] lr: 2.295e-02, eta: 12:54:34, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8331, top5_acc: 0.9894, loss_cls: 0.7578, loss: 0.7578 +2025-06-24 12:14:45,648 - pyskl - INFO - Epoch [28][1000/1281] lr: 2.294e-02, eta: 12:54:58, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8250, top5_acc: 0.9888, loss_cls: 0.8067, loss: 0.8067 +2025-06-24 12:15:27,585 - pyskl - INFO - Epoch [28][1100/1281] lr: 2.293e-02, eta: 12:55:22, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.8256, top5_acc: 0.9881, loss_cls: 0.7447, loss: 0.7447 +2025-06-24 12:16:09,194 - pyskl - INFO - Epoch [28][1200/1281] lr: 2.292e-02, eta: 12:55:44, time: 0.416, data_time: 0.001, memory: 4082, top1_acc: 0.8119, top5_acc: 0.9894, loss_cls: 0.7957, loss: 0.7957 +2025-06-24 12:16:43,590 - pyskl - INFO - Saving checkpoint at 28 epochs +2025-06-24 12:17:44,095 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:17:44,150 - pyskl - INFO - +top1_acc 0.7611 +top5_acc 0.9758 +2025-06-24 12:17:44,151 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:17:44,157 - pyskl - INFO - +mean_acc 0.6660 +2025-06-24 12:17:44,159 - pyskl - INFO - Epoch(val) [28][533] top1_acc: 0.7611, top5_acc: 0.9758, mean_class_accuracy: 0.6660 +2025-06-24 12:18:34,462 - pyskl - INFO - Epoch [29][100/1281] lr: 2.290e-02, eta: 12:54:34, time: 0.503, data_time: 0.196, memory: 4082, top1_acc: 0.8250, top5_acc: 0.9925, loss_cls: 0.7449, loss: 0.7449 +2025-06-24 12:19:18,320 - pyskl - INFO - Epoch [29][200/1281] lr: 2.289e-02, eta: 12:55:06, time: 0.439, data_time: 0.000, memory: 4082, top1_acc: 0.8469, top5_acc: 0.9912, loss_cls: 0.7012, loss: 0.7012 +2025-06-24 12:20:02,016 - pyskl - INFO - Epoch [29][300/1281] lr: 2.288e-02, eta: 12:55:36, time: 0.437, data_time: 0.000, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9875, loss_cls: 0.7595, loss: 0.7595 +2025-06-24 12:20:45,708 - pyskl - INFO - Epoch [29][400/1281] lr: 2.287e-02, eta: 12:56:06, time: 0.437, data_time: 0.000, memory: 4082, top1_acc: 0.8269, top5_acc: 0.9881, loss_cls: 0.7575, loss: 0.7575 +2025-06-24 12:21:28,994 - pyskl - INFO - Epoch [29][500/1281] lr: 2.285e-02, eta: 12:56:33, time: 0.433, data_time: 0.000, memory: 4082, top1_acc: 0.8337, top5_acc: 0.9919, loss_cls: 0.7131, loss: 0.7131 +2025-06-24 12:22:12,822 - pyskl - INFO - Epoch [29][600/1281] lr: 2.284e-02, eta: 12:57:03, time: 0.438, data_time: 0.000, memory: 4082, top1_acc: 0.8263, top5_acc: 0.9875, loss_cls: 0.7863, loss: 0.7863 +2025-06-24 12:22:56,250 - pyskl - INFO - Epoch [29][700/1281] lr: 2.283e-02, eta: 12:57:30, time: 0.434, data_time: 0.000, memory: 4082, top1_acc: 0.8375, top5_acc: 0.9906, loss_cls: 0.7329, loss: 0.7329 +2025-06-24 12:23:39,896 - pyskl - INFO - Epoch [29][800/1281] lr: 2.282e-02, eta: 12:57:58, time: 0.436, data_time: 0.000, memory: 4082, top1_acc: 0.8169, top5_acc: 0.9881, loss_cls: 0.7867, loss: 0.7867 +2025-06-24 12:24:21,541 - pyskl - INFO - Epoch [29][900/1281] lr: 2.281e-02, eta: 12:58:17, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8281, top5_acc: 0.9912, loss_cls: 0.7564, loss: 0.7564 +2025-06-24 12:25:03,087 - pyskl - INFO - Epoch [29][1000/1281] lr: 2.280e-02, eta: 12:58:35, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8169, top5_acc: 0.9919, loss_cls: 0.7746, loss: 0.7746 +2025-06-24 12:25:44,950 - pyskl - INFO - Epoch [29][1100/1281] lr: 2.279e-02, eta: 12:58:55, time: 0.419, data_time: 0.000, memory: 4082, top1_acc: 0.8000, top5_acc: 0.9850, loss_cls: 0.8458, loss: 0.8458 +2025-06-24 12:26:26,671 - pyskl - INFO - Epoch [29][1200/1281] lr: 2.277e-02, eta: 12:59:13, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8394, top5_acc: 0.9894, loss_cls: 0.7208, loss: 0.7208 +2025-06-24 12:27:01,158 - pyskl - INFO - Saving checkpoint at 29 epochs +2025-06-24 12:27:59,086 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:27:59,141 - pyskl - INFO - +top1_acc 0.7519 +top5_acc 0.9770 +2025-06-24 12:27:59,141 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:27:59,148 - pyskl - INFO - +mean_acc 0.6696 +2025-06-24 12:27:59,150 - pyskl - INFO - Epoch(val) [29][533] top1_acc: 0.7519, top5_acc: 0.9770, mean_class_accuracy: 0.6696 +2025-06-24 12:28:51,169 - pyskl - INFO - Epoch [30][100/1281] lr: 2.275e-02, eta: 12:58:08, time: 0.520, data_time: 0.192, memory: 4082, top1_acc: 0.8400, top5_acc: 0.9894, loss_cls: 0.7024, loss: 0.7024 +2025-06-24 12:29:42,666 - pyskl - INFO - Epoch [30][200/1281] lr: 2.274e-02, eta: 12:59:06, time: 0.515, data_time: 0.000, memory: 4082, top1_acc: 0.8450, top5_acc: 0.9950, loss_cls: 0.7082, loss: 0.7082 +2025-06-24 12:30:35,213 - pyskl - INFO - Epoch [30][300/1281] lr: 2.273e-02, eta: 13:00:08, time: 0.525, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9950, loss_cls: 0.7071, loss: 0.7071 +2025-06-24 12:31:26,837 - pyskl - INFO - Epoch [30][400/1281] lr: 2.272e-02, eta: 13:01:06, time: 0.516, data_time: 0.000, memory: 4082, top1_acc: 0.8394, top5_acc: 0.9950, loss_cls: 0.7207, loss: 0.7207 +2025-06-24 12:32:18,754 - pyskl - INFO - Epoch [30][500/1281] lr: 2.271e-02, eta: 13:02:05, time: 0.519, data_time: 0.000, memory: 4082, top1_acc: 0.8337, top5_acc: 0.9862, loss_cls: 0.7353, loss: 0.7353 +2025-06-24 12:33:09,657 - pyskl - INFO - Epoch [30][600/1281] lr: 2.269e-02, eta: 13:02:58, time: 0.509, data_time: 0.000, memory: 4082, top1_acc: 0.8275, top5_acc: 0.9944, loss_cls: 0.7666, loss: 0.7666 +2025-06-24 12:34:00,475 - pyskl - INFO - Epoch [30][700/1281] lr: 2.268e-02, eta: 13:03:51, time: 0.508, data_time: 0.000, memory: 4082, top1_acc: 0.8356, top5_acc: 0.9900, loss_cls: 0.7269, loss: 0.7269 +2025-06-24 12:34:52,042 - pyskl - INFO - Epoch [30][800/1281] lr: 2.267e-02, eta: 13:04:46, time: 0.516, data_time: 0.000, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9900, loss_cls: 0.7255, loss: 0.7255 +2025-06-24 12:35:43,171 - pyskl - INFO - Epoch [30][900/1281] lr: 2.266e-02, eta: 13:05:39, time: 0.511, data_time: 0.000, memory: 4082, top1_acc: 0.8237, top5_acc: 0.9925, loss_cls: 0.7375, loss: 0.7375 +2025-06-24 12:36:34,219 - pyskl - INFO - Epoch [30][1000/1281] lr: 2.265e-02, eta: 13:06:31, time: 0.510, data_time: 0.000, memory: 4082, top1_acc: 0.8169, top5_acc: 0.9912, loss_cls: 0.8108, loss: 0.8108 +2025-06-24 12:37:05,103 - pyskl - INFO - Epoch [30][1100/1281] lr: 2.263e-02, eta: 13:06:01, time: 0.309, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9875, loss_cls: 0.7222, loss: 0.7222 +2025-06-24 12:37:56,332 - pyskl - INFO - Epoch [30][1200/1281] lr: 2.262e-02, eta: 13:06:53, time: 0.512, data_time: 0.000, memory: 4082, top1_acc: 0.8006, top5_acc: 0.9875, loss_cls: 0.8322, loss: 0.8322 +2025-06-24 12:38:23,006 - pyskl - INFO - Saving checkpoint at 30 epochs +2025-06-24 12:39:34,827 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:39:34,889 - pyskl - INFO - +top1_acc 0.7807 +top5_acc 0.9810 +2025-06-24 12:39:34,889 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:39:34,899 - pyskl - INFO - +mean_acc 0.6612 +2025-06-24 12:39:34,901 - pyskl - INFO - Epoch(val) [30][533] top1_acc: 0.7807, top5_acc: 0.9810, mean_class_accuracy: 0.6612 +2025-06-24 12:41:06,608 - pyskl - INFO - Epoch [31][100/1281] lr: 2.260e-02, eta: 13:08:22, time: 0.917, data_time: 0.198, memory: 4083, top1_acc: 0.8375, top5_acc: 0.9912, loss_cls: 0.8957, loss: 0.8957 +2025-06-24 12:42:00,566 - pyskl - INFO - Epoch [31][200/1281] lr: 2.259e-02, eta: 13:09:23, time: 0.540, data_time: 0.000, memory: 4083, top1_acc: 0.8256, top5_acc: 0.9912, loss_cls: 0.8750, loss: 0.8750 +2025-06-24 12:42:53,338 - pyskl - INFO - Epoch [31][300/1281] lr: 2.258e-02, eta: 13:10:19, time: 0.528, data_time: 0.000, memory: 4083, top1_acc: 0.8350, top5_acc: 0.9931, loss_cls: 0.8636, loss: 0.8636 +2025-06-24 12:43:46,597 - pyskl - INFO - Epoch [31][400/1281] lr: 2.256e-02, eta: 13:11:16, time: 0.533, data_time: 0.000, memory: 4083, top1_acc: 0.8287, top5_acc: 0.9881, loss_cls: 0.9070, loss: 0.9070 +2025-06-24 12:44:40,000 - pyskl - INFO - Epoch [31][500/1281] lr: 2.255e-02, eta: 13:12:14, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.8331, top5_acc: 0.9912, loss_cls: 0.8991, loss: 0.8991 +2025-06-24 12:45:34,423 - pyskl - INFO - Epoch [31][600/1281] lr: 2.254e-02, eta: 13:13:14, time: 0.544, data_time: 0.000, memory: 4083, top1_acc: 0.8438, top5_acc: 0.9919, loss_cls: 0.8910, loss: 0.8910 +2025-06-24 12:46:03,932 - pyskl - INFO - Epoch [31][700/1281] lr: 2.253e-02, eta: 13:12:37, time: 0.295, data_time: 0.000, memory: 4083, top1_acc: 0.8319, top5_acc: 0.9900, loss_cls: 0.8895, loss: 0.8895 +2025-06-24 12:46:55,139 - pyskl - INFO - Epoch [31][800/1281] lr: 2.252e-02, eta: 13:13:24, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8263, top5_acc: 0.9912, loss_cls: 0.8980, loss: 0.8980 +2025-06-24 12:47:32,688 - pyskl - INFO - Epoch [31][900/1281] lr: 2.250e-02, eta: 13:13:18, time: 0.375, data_time: 0.000, memory: 4083, top1_acc: 0.8425, top5_acc: 0.9944, loss_cls: 0.8390, loss: 0.8390 +2025-06-24 12:48:26,248 - pyskl - INFO - Epoch [31][1000/1281] lr: 2.249e-02, eta: 13:14:14, time: 0.536, data_time: 0.000, memory: 4083, top1_acc: 0.8387, top5_acc: 0.9950, loss_cls: 0.8435, loss: 0.8435 +2025-06-24 12:49:19,605 - pyskl - INFO - Epoch [31][1100/1281] lr: 2.248e-02, eta: 13:15:08, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.8294, top5_acc: 0.9888, loss_cls: 0.9496, loss: 0.9496 +2025-06-24 12:50:12,708 - pyskl - INFO - Epoch [31][1200/1281] lr: 2.247e-02, eta: 13:16:01, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.8325, top5_acc: 0.9912, loss_cls: 0.8907, loss: 0.8907 +2025-06-24 12:50:57,139 - pyskl - INFO - Saving checkpoint at 31 epochs +2025-06-24 12:52:08,663 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:52:08,730 - pyskl - INFO - +top1_acc 0.7731 +top5_acc 0.9811 +2025-06-24 12:52:08,730 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:52:08,738 - pyskl - INFO - +mean_acc 0.6971 +2025-06-24 12:52:08,740 - pyskl - INFO - Epoch(val) [31][533] top1_acc: 0.7731, top5_acc: 0.9811, mean_class_accuracy: 0.6971 +2025-06-24 12:53:37,930 - pyskl - INFO - Epoch [32][100/1281] lr: 2.244e-02, eta: 13:17:09, time: 0.892, data_time: 0.199, memory: 4083, top1_acc: 0.8450, top5_acc: 0.9925, loss_cls: 0.7922, loss: 0.7922 +2025-06-24 12:54:31,670 - pyskl - INFO - Epoch [32][200/1281] lr: 2.243e-02, eta: 13:18:03, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8194, top5_acc: 0.9912, loss_cls: 0.8518, loss: 0.8518 +2025-06-24 12:55:01,313 - pyskl - INFO - Epoch [32][300/1281] lr: 2.242e-02, eta: 13:17:24, time: 0.296, data_time: 0.000, memory: 4083, top1_acc: 0.8263, top5_acc: 0.9912, loss_cls: 0.8326, loss: 0.8326 +2025-06-24 12:55:52,450 - pyskl - INFO - Epoch [32][400/1281] lr: 2.241e-02, eta: 13:18:07, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.8263, top5_acc: 0.9906, loss_cls: 0.8626, loss: 0.8626 +2025-06-24 12:56:31,215 - pyskl - INFO - Epoch [32][500/1281] lr: 2.239e-02, eta: 13:18:03, time: 0.388, data_time: 0.001, memory: 4083, top1_acc: 0.8406, top5_acc: 0.9919, loss_cls: 0.7796, loss: 0.7796 +2025-06-24 12:57:24,227 - pyskl - INFO - Epoch [32][600/1281] lr: 2.238e-02, eta: 13:18:53, time: 0.530, data_time: 0.000, memory: 4083, top1_acc: 0.8056, top5_acc: 0.9888, loss_cls: 0.9166, loss: 0.9166 +2025-06-24 12:58:17,691 - pyskl - INFO - Epoch [32][700/1281] lr: 2.237e-02, eta: 13:19:43, time: 0.535, data_time: 0.000, memory: 4083, top1_acc: 0.8381, top5_acc: 0.9912, loss_cls: 0.8250, loss: 0.8250 +2025-06-24 12:59:09,822 - pyskl - INFO - Epoch [32][800/1281] lr: 2.236e-02, eta: 13:20:29, time: 0.521, data_time: 0.000, memory: 4083, top1_acc: 0.8325, top5_acc: 0.9912, loss_cls: 0.7912, loss: 0.7912 +2025-06-24 13:00:02,587 - pyskl - INFO - Epoch [32][900/1281] lr: 2.234e-02, eta: 13:21:16, time: 0.528, data_time: 0.000, memory: 4083, top1_acc: 0.8150, top5_acc: 0.9894, loss_cls: 0.8941, loss: 0.8941 +2025-06-24 13:00:55,080 - pyskl - INFO - Epoch [32][1000/1281] lr: 2.233e-02, eta: 13:22:01, time: 0.525, data_time: 0.001, memory: 4083, top1_acc: 0.8431, top5_acc: 0.9938, loss_cls: 0.8004, loss: 0.8004 +2025-06-24 13:01:49,558 - pyskl - INFO - Epoch [32][1100/1281] lr: 2.232e-02, eta: 13:22:54, time: 0.545, data_time: 0.001, memory: 4083, top1_acc: 0.8306, top5_acc: 0.9931, loss_cls: 0.8045, loss: 0.8045 +2025-06-24 13:02:44,069 - pyskl - INFO - Epoch [32][1200/1281] lr: 2.231e-02, eta: 13:23:46, time: 0.545, data_time: 0.000, memory: 4083, top1_acc: 0.8319, top5_acc: 0.9919, loss_cls: 0.8525, loss: 0.8525 +2025-06-24 13:03:28,270 - pyskl - INFO - Saving checkpoint at 32 epochs +2025-06-24 13:04:19,517 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:04:19,594 - pyskl - INFO - +top1_acc 0.7909 +top5_acc 0.9805 +2025-06-24 13:04:19,594 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:04:19,603 - pyskl - INFO - +mean_acc 0.6958 +2025-06-24 13:04:19,607 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_26.pth was removed +2025-06-24 13:04:19,781 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_32.pth. +2025-06-24 13:04:19,781 - pyskl - INFO - Best top1_acc is 0.7909 at 32 epoch. +2025-06-24 13:04:19,784 - pyskl - INFO - Epoch(val) [32][533] top1_acc: 0.7909, top5_acc: 0.9805, mean_class_accuracy: 0.6958 +2025-06-24 13:05:12,369 - pyskl - INFO - Epoch [33][100/1281] lr: 2.228e-02, eta: 13:22:29, time: 0.526, data_time: 0.190, memory: 4083, top1_acc: 0.8394, top5_acc: 0.9931, loss_cls: 0.7660, loss: 0.7660 +2025-06-24 13:06:04,802 - pyskl - INFO - Epoch [33][200/1281] lr: 2.227e-02, eta: 13:23:12, time: 0.524, data_time: 0.000, memory: 4083, top1_acc: 0.8425, top5_acc: 0.9950, loss_cls: 0.7504, loss: 0.7504 +2025-06-24 13:06:59,095 - pyskl - INFO - Epoch [33][300/1281] lr: 2.226e-02, eta: 13:24:02, time: 0.543, data_time: 0.000, memory: 4083, top1_acc: 0.8369, top5_acc: 0.9912, loss_cls: 0.7797, loss: 0.7797 +2025-06-24 13:07:53,873 - pyskl - INFO - Epoch [33][400/1281] lr: 2.225e-02, eta: 13:24:53, time: 0.548, data_time: 0.000, memory: 4083, top1_acc: 0.8431, top5_acc: 0.9919, loss_cls: 0.7728, loss: 0.7728 +2025-06-24 13:08:47,878 - pyskl - INFO - Epoch [33][500/1281] lr: 2.223e-02, eta: 13:25:41, time: 0.540, data_time: 0.000, memory: 4083, top1_acc: 0.8231, top5_acc: 0.9919, loss_cls: 0.8416, loss: 0.8416 +2025-06-24 13:09:40,601 - pyskl - INFO - Epoch [33][600/1281] lr: 2.222e-02, eta: 13:26:24, time: 0.527, data_time: 0.000, memory: 4083, top1_acc: 0.8206, top5_acc: 0.9900, loss_cls: 0.8222, loss: 0.8222 +2025-06-24 13:10:34,234 - pyskl - INFO - Epoch [33][700/1281] lr: 2.221e-02, eta: 13:27:09, time: 0.536, data_time: 0.000, memory: 4083, top1_acc: 0.8350, top5_acc: 0.9881, loss_cls: 0.7835, loss: 0.7835 +2025-06-24 13:11:28,249 - pyskl - INFO - Epoch [33][800/1281] lr: 2.219e-02, eta: 13:27:55, time: 0.540, data_time: 0.000, memory: 4083, top1_acc: 0.8244, top5_acc: 0.9956, loss_cls: 0.8287, loss: 0.8287 +2025-06-24 13:12:21,774 - pyskl - INFO - Epoch [33][900/1281] lr: 2.218e-02, eta: 13:28:39, time: 0.535, data_time: 0.000, memory: 4083, top1_acc: 0.8488, top5_acc: 0.9869, loss_cls: 0.7537, loss: 0.7537 +2025-06-24 13:13:11,468 - pyskl - INFO - Epoch [33][1000/1281] lr: 2.217e-02, eta: 13:29:09, time: 0.497, data_time: 0.001, memory: 4083, top1_acc: 0.8331, top5_acc: 0.9912, loss_cls: 0.7973, loss: 0.7973 +2025-06-24 13:13:50,550 - pyskl - INFO - Epoch [33][1100/1281] lr: 2.216e-02, eta: 13:29:01, time: 0.391, data_time: 0.000, memory: 4083, top1_acc: 0.8156, top5_acc: 0.9919, loss_cls: 0.8464, loss: 0.8464 +2025-06-24 13:14:25,293 - pyskl - INFO - Epoch [33][1200/1281] lr: 2.214e-02, eta: 13:28:37, time: 0.347, data_time: 0.001, memory: 4083, top1_acc: 0.8287, top5_acc: 0.9931, loss_cls: 0.7970, loss: 0.7970 +2025-06-24 13:15:05,685 - pyskl - INFO - Saving checkpoint at 33 epochs +2025-06-24 13:16:17,244 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:16:17,303 - pyskl - INFO - +top1_acc 0.7803 +top5_acc 0.9811 +2025-06-24 13:16:17,303 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:16:17,310 - pyskl - INFO - +mean_acc 0.6874 +2025-06-24 13:16:17,312 - pyskl - INFO - Epoch(val) [33][533] top1_acc: 0.7803, top5_acc: 0.9811, mean_class_accuracy: 0.6874 +2025-06-24 13:17:44,388 - pyskl - INFO - Epoch [34][100/1281] lr: 2.212e-02, eta: 13:29:20, time: 0.871, data_time: 0.196, memory: 4083, top1_acc: 0.8400, top5_acc: 0.9912, loss_cls: 0.7732, loss: 0.7732 +2025-06-24 13:18:38,734 - pyskl - INFO - Epoch [34][200/1281] lr: 2.211e-02, eta: 13:30:04, time: 0.543, data_time: 0.000, memory: 4083, top1_acc: 0.8306, top5_acc: 0.9931, loss_cls: 0.8003, loss: 0.8003 +2025-06-24 13:19:31,867 - pyskl - INFO - Epoch [34][300/1281] lr: 2.209e-02, eta: 13:30:44, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.8494, top5_acc: 0.9944, loss_cls: 0.7325, loss: 0.7325 +2025-06-24 13:20:26,027 - pyskl - INFO - Epoch [34][400/1281] lr: 2.208e-02, eta: 13:31:28, time: 0.542, data_time: 0.000, memory: 4083, top1_acc: 0.8475, top5_acc: 0.9956, loss_cls: 0.7474, loss: 0.7474 +2025-06-24 13:21:19,100 - pyskl - INFO - Epoch [34][500/1281] lr: 2.207e-02, eta: 13:32:07, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.8444, top5_acc: 0.9919, loss_cls: 0.7795, loss: 0.7795 +2025-06-24 13:22:08,835 - pyskl - INFO - Epoch [34][600/1281] lr: 2.205e-02, eta: 13:32:34, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.8413, top5_acc: 0.9931, loss_cls: 0.7727, loss: 0.7727 +2025-06-24 13:22:47,196 - pyskl - INFO - Epoch [34][700/1281] lr: 2.204e-02, eta: 13:32:21, time: 0.384, data_time: 0.000, memory: 4083, top1_acc: 0.8462, top5_acc: 0.9875, loss_cls: 0.7523, loss: 0.7523 +2025-06-24 13:23:22,981 - pyskl - INFO - Epoch [34][800/1281] lr: 2.203e-02, eta: 13:31:59, time: 0.358, data_time: 0.000, memory: 4083, top1_acc: 0.8331, top5_acc: 0.9919, loss_cls: 0.7686, loss: 0.7686 +2025-06-24 13:24:10,442 - pyskl - INFO - Epoch [34][900/1281] lr: 2.201e-02, eta: 13:32:17, time: 0.475, data_time: 0.000, memory: 4083, top1_acc: 0.8475, top5_acc: 0.9931, loss_cls: 0.7289, loss: 0.7289 +2025-06-24 13:25:04,114 - pyskl - INFO - Epoch [34][1000/1281] lr: 2.200e-02, eta: 13:32:57, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8144, top5_acc: 0.9938, loss_cls: 0.8607, loss: 0.8607 +2025-06-24 13:25:57,901 - pyskl - INFO - Epoch [34][1100/1281] lr: 2.199e-02, eta: 13:33:36, time: 0.538, data_time: 0.001, memory: 4083, top1_acc: 0.8113, top5_acc: 0.9900, loss_cls: 0.8358, loss: 0.8358 +2025-06-24 13:26:51,218 - pyskl - INFO - Epoch [34][1200/1281] lr: 2.197e-02, eta: 13:34:13, time: 0.533, data_time: 0.000, memory: 4083, top1_acc: 0.8425, top5_acc: 0.9925, loss_cls: 0.7853, loss: 0.7853 +2025-06-24 13:27:35,244 - pyskl - INFO - Saving checkpoint at 34 epochs +2025-06-24 13:28:46,489 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:28:46,545 - pyskl - INFO - +top1_acc 0.7827 +top5_acc 0.9852 +2025-06-24 13:28:46,545 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:28:46,552 - pyskl - INFO - +mean_acc 0.7081 +2025-06-24 13:28:46,553 - pyskl - INFO - Epoch(val) [34][533] top1_acc: 0.7827, top5_acc: 0.9852, mean_class_accuracy: 0.7081 +2025-06-24 13:30:14,158 - pyskl - INFO - Epoch [35][100/1281] lr: 2.195e-02, eta: 13:34:49, time: 0.876, data_time: 0.194, memory: 4083, top1_acc: 0.8369, top5_acc: 0.9894, loss_cls: 0.7934, loss: 0.7934 +2025-06-24 13:31:06,617 - pyskl - INFO - Epoch [35][200/1281] lr: 2.194e-02, eta: 13:35:23, time: 0.525, data_time: 0.000, memory: 4083, top1_acc: 0.8419, top5_acc: 0.9962, loss_cls: 0.7476, loss: 0.7476 +2025-06-24 13:31:41,398 - pyskl - INFO - Epoch [35][300/1281] lr: 2.192e-02, eta: 13:34:56, time: 0.348, data_time: 0.000, memory: 4083, top1_acc: 0.8494, top5_acc: 0.9906, loss_cls: 0.7301, loss: 0.7301 +2025-06-24 13:32:20,418 - pyskl - INFO - Epoch [35][400/1281] lr: 2.191e-02, eta: 13:34:43, time: 0.390, data_time: 0.000, memory: 4083, top1_acc: 0.8225, top5_acc: 0.9862, loss_cls: 0.8553, loss: 0.8553 +2025-06-24 13:33:05,642 - pyskl - INFO - Epoch [35][500/1281] lr: 2.190e-02, eta: 13:34:52, time: 0.452, data_time: 0.000, memory: 4083, top1_acc: 0.8425, top5_acc: 0.9925, loss_cls: 0.7741, loss: 0.7741 +2025-06-24 13:33:59,032 - pyskl - INFO - Epoch [35][600/1281] lr: 2.188e-02, eta: 13:35:27, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.8462, top5_acc: 0.9938, loss_cls: 0.7178, loss: 0.7178 +2025-06-24 13:34:52,548 - pyskl - INFO - Epoch [35][700/1281] lr: 2.187e-02, eta: 13:36:02, time: 0.535, data_time: 0.000, memory: 4083, top1_acc: 0.8450, top5_acc: 0.9912, loss_cls: 0.7413, loss: 0.7413 +2025-06-24 13:35:46,851 - pyskl - INFO - Epoch [35][800/1281] lr: 2.185e-02, eta: 13:36:40, time: 0.543, data_time: 0.000, memory: 4083, top1_acc: 0.8319, top5_acc: 0.9894, loss_cls: 0.7855, loss: 0.7855 +2025-06-24 13:36:40,688 - pyskl - INFO - Epoch [35][900/1281] lr: 2.184e-02, eta: 13:37:15, time: 0.538, data_time: 0.000, memory: 4083, top1_acc: 0.8413, top5_acc: 0.9938, loss_cls: 0.7858, loss: 0.7858 +2025-06-24 13:37:34,499 - pyskl - INFO - Epoch [35][1000/1281] lr: 2.183e-02, eta: 13:37:50, time: 0.538, data_time: 0.000, memory: 4083, top1_acc: 0.8394, top5_acc: 0.9906, loss_cls: 0.7578, loss: 0.7578 +2025-06-24 13:38:27,400 - pyskl - INFO - Epoch [35][1100/1281] lr: 2.181e-02, eta: 13:38:22, time: 0.529, data_time: 0.000, memory: 4083, top1_acc: 0.8475, top5_acc: 0.9912, loss_cls: 0.7411, loss: 0.7411 +2025-06-24 13:39:20,458 - pyskl - INFO - Epoch [35][1200/1281] lr: 2.180e-02, eta: 13:38:54, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.8488, top5_acc: 0.9944, loss_cls: 0.7466, loss: 0.7466 +2025-06-24 13:40:05,614 - pyskl - INFO - Saving checkpoint at 35 epochs +2025-06-24 13:41:04,784 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:41:04,852 - pyskl - INFO - +top1_acc 0.8086 +top5_acc 0.9871 +2025-06-24 13:41:04,853 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:41:04,861 - pyskl - INFO - +mean_acc 0.7238 +2025-06-24 13:41:04,866 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_32.pth was removed +2025-06-24 13:41:05,050 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_35.pth. +2025-06-24 13:41:05,050 - pyskl - INFO - Best top1_acc is 0.8086 at 35 epoch. +2025-06-24 13:41:05,053 - pyskl - INFO - Epoch(val) [35][533] top1_acc: 0.8086, top5_acc: 0.9871, mean_class_accuracy: 0.7238 +2025-06-24 13:42:02,011 - pyskl - INFO - Epoch [36][100/1281] lr: 2.178e-02, eta: 13:37:42, time: 0.570, data_time: 0.196, memory: 4083, top1_acc: 0.8419, top5_acc: 0.9944, loss_cls: 0.7643, loss: 0.7643 +2025-06-24 13:42:55,592 - pyskl - INFO - Epoch [36][200/1281] lr: 2.176e-02, eta: 13:38:15, time: 0.536, data_time: 0.000, memory: 4083, top1_acc: 0.8406, top5_acc: 0.9900, loss_cls: 0.7933, loss: 0.7933 +2025-06-24 13:43:48,428 - pyskl - INFO - Epoch [36][300/1281] lr: 2.175e-02, eta: 13:38:45, time: 0.528, data_time: 0.000, memory: 4083, top1_acc: 0.8569, top5_acc: 0.9925, loss_cls: 0.7040, loss: 0.7040 +2025-06-24 13:44:42,514 - pyskl - INFO - Epoch [36][400/1281] lr: 2.173e-02, eta: 13:39:19, time: 0.541, data_time: 0.000, memory: 4083, top1_acc: 0.8656, top5_acc: 0.9931, loss_cls: 0.7023, loss: 0.7023 +2025-06-24 13:45:36,634 - pyskl - INFO - Epoch [36][500/1281] lr: 2.172e-02, eta: 13:39:52, time: 0.541, data_time: 0.000, memory: 4083, top1_acc: 0.8531, top5_acc: 0.9925, loss_cls: 0.7039, loss: 0.7039 +2025-06-24 13:46:30,768 - pyskl - INFO - Epoch [36][600/1281] lr: 2.171e-02, eta: 13:40:25, time: 0.541, data_time: 0.000, memory: 4083, top1_acc: 0.8325, top5_acc: 0.9912, loss_cls: 0.7821, loss: 0.7821 +2025-06-24 13:47:24,002 - pyskl - INFO - Epoch [36][700/1281] lr: 2.169e-02, eta: 13:40:55, time: 0.532, data_time: 0.000, memory: 4083, top1_acc: 0.8488, top5_acc: 0.9925, loss_cls: 0.7687, loss: 0.7687 +2025-06-24 13:48:18,165 - pyskl - INFO - Epoch [36][800/1281] lr: 2.168e-02, eta: 13:41:28, time: 0.542, data_time: 0.000, memory: 4083, top1_acc: 0.8263, top5_acc: 0.9881, loss_cls: 0.8401, loss: 0.8401 +2025-06-24 13:49:11,871 - pyskl - INFO - Epoch [36][900/1281] lr: 2.167e-02, eta: 13:41:58, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8594, top5_acc: 0.9956, loss_cls: 0.6975, loss: 0.6975 +2025-06-24 13:49:51,867 - pyskl - INFO - Epoch [36][1000/1281] lr: 2.165e-02, eta: 13:41:45, time: 0.400, data_time: 0.000, memory: 4083, top1_acc: 0.8256, top5_acc: 0.9944, loss_cls: 0.8221, loss: 0.8221 +2025-06-24 13:50:43,207 - pyskl - INFO - Epoch [36][1100/1281] lr: 2.164e-02, eta: 13:42:07, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.8425, top5_acc: 0.9900, loss_cls: 0.7693, loss: 0.7693 +2025-06-24 13:51:11,624 - pyskl - INFO - Epoch [36][1200/1281] lr: 2.162e-02, eta: 13:41:17, time: 0.284, data_time: 0.000, memory: 4083, top1_acc: 0.8256, top5_acc: 0.9869, loss_cls: 0.8217, loss: 0.8217 +2025-06-24 13:51:55,985 - pyskl - INFO - Saving checkpoint at 36 epochs +2025-06-24 13:53:07,864 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:53:07,920 - pyskl - INFO - +top1_acc 0.7683 +top5_acc 0.9837 +2025-06-24 13:53:07,920 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:53:07,928 - pyskl - INFO - +mean_acc 0.6991 +2025-06-24 13:53:07,930 - pyskl - INFO - Epoch(val) [36][533] top1_acc: 0.7683, top5_acc: 0.9837, mean_class_accuracy: 0.6991 +2025-06-24 13:54:35,100 - pyskl - INFO - Epoch [37][100/1281] lr: 2.160e-02, eta: 13:41:38, time: 0.872, data_time: 0.201, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9950, loss_cls: 0.6259, loss: 0.6259 +2025-06-24 13:55:29,428 - pyskl - INFO - Epoch [37][200/1281] lr: 2.158e-02, eta: 13:42:09, time: 0.543, data_time: 0.000, memory: 4083, top1_acc: 0.8625, top5_acc: 0.9931, loss_cls: 0.6765, loss: 0.6765 +2025-06-24 13:56:24,359 - pyskl - INFO - Epoch [37][300/1281] lr: 2.157e-02, eta: 13:42:41, time: 0.549, data_time: 0.000, memory: 4083, top1_acc: 0.8325, top5_acc: 0.9919, loss_cls: 0.7858, loss: 0.7858 +2025-06-24 13:57:18,865 - pyskl - INFO - Epoch [37][400/1281] lr: 2.156e-02, eta: 13:43:12, time: 0.545, data_time: 0.000, memory: 4083, top1_acc: 0.8544, top5_acc: 0.9912, loss_cls: 0.7306, loss: 0.7306 +2025-06-24 13:58:13,268 - pyskl - INFO - Epoch [37][500/1281] lr: 2.154e-02, eta: 13:43:42, time: 0.544, data_time: 0.000, memory: 4083, top1_acc: 0.8225, top5_acc: 0.9888, loss_cls: 0.8144, loss: 0.8144 +2025-06-24 13:58:48,823 - pyskl - INFO - Epoch [37][600/1281] lr: 2.153e-02, eta: 13:43:13, time: 0.356, data_time: 0.000, memory: 4083, top1_acc: 0.8413, top5_acc: 0.9894, loss_cls: 0.7843, loss: 0.7843 +2025-06-24 13:59:40,046 - pyskl - INFO - Epoch [37][700/1281] lr: 2.151e-02, eta: 13:43:33, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8394, top5_acc: 0.9912, loss_cls: 0.7836, loss: 0.7836 +2025-06-24 14:00:13,004 - pyskl - INFO - Epoch [37][800/1281] lr: 2.150e-02, eta: 13:42:56, time: 0.330, data_time: 0.000, memory: 4083, top1_acc: 0.8631, top5_acc: 0.9944, loss_cls: 0.6849, loss: 0.6849 +2025-06-24 14:01:05,682 - pyskl - INFO - Epoch [37][900/1281] lr: 2.149e-02, eta: 13:43:19, time: 0.527, data_time: 0.000, memory: 4083, top1_acc: 0.8481, top5_acc: 0.9944, loss_cls: 0.7490, loss: 0.7490 +2025-06-24 14:01:58,777 - pyskl - INFO - Epoch [37][1000/1281] lr: 2.147e-02, eta: 13:43:44, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.8387, top5_acc: 0.9931, loss_cls: 0.7316, loss: 0.7316 +2025-06-24 14:02:52,525 - pyskl - INFO - Epoch [37][1100/1281] lr: 2.146e-02, eta: 13:44:10, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8444, top5_acc: 0.9906, loss_cls: 0.7584, loss: 0.7584 +2025-06-24 14:03:45,670 - pyskl - INFO - Epoch [37][1200/1281] lr: 2.144e-02, eta: 13:44:34, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.8431, top5_acc: 0.9912, loss_cls: 0.7872, loss: 0.7872 +2025-06-24 14:04:29,554 - pyskl - INFO - Saving checkpoint at 37 epochs +2025-06-24 14:05:41,458 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:05:41,526 - pyskl - INFO - +top1_acc 0.7818 +top5_acc 0.9839 +2025-06-24 14:05:41,526 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:05:41,534 - pyskl - INFO - +mean_acc 0.6998 +2025-06-24 14:05:41,537 - pyskl - INFO - Epoch(val) [37][533] top1_acc: 0.7818, top5_acc: 0.9839, mean_class_accuracy: 0.6998 +2025-06-24 14:07:06,261 - pyskl - INFO - Epoch [38][100/1281] lr: 2.142e-02, eta: 13:44:42, time: 0.847, data_time: 0.194, memory: 4083, top1_acc: 0.8631, top5_acc: 0.9931, loss_cls: 0.6765, loss: 0.6765 +2025-06-24 14:07:46,142 - pyskl - INFO - Epoch [38][200/1281] lr: 2.140e-02, eta: 13:44:25, time: 0.399, data_time: 0.000, memory: 4083, top1_acc: 0.8337, top5_acc: 0.9944, loss_cls: 0.7876, loss: 0.7876 +2025-06-24 14:08:37,538 - pyskl - INFO - Epoch [38][300/1281] lr: 2.139e-02, eta: 13:44:43, time: 0.514, data_time: 0.000, memory: 4083, top1_acc: 0.8556, top5_acc: 0.9931, loss_cls: 0.7299, loss: 0.7299 +2025-06-24 14:09:05,786 - pyskl - INFO - Epoch [38][400/1281] lr: 2.137e-02, eta: 13:43:51, time: 0.282, data_time: 0.000, memory: 4083, top1_acc: 0.8500, top5_acc: 0.9925, loss_cls: 0.7117, loss: 0.7117 +2025-06-24 14:09:59,589 - pyskl - INFO - Epoch [38][500/1281] lr: 2.136e-02, eta: 13:44:15, time: 0.538, data_time: 0.000, memory: 4083, top1_acc: 0.8325, top5_acc: 0.9912, loss_cls: 0.7598, loss: 0.7598 +2025-06-24 14:10:52,592 - pyskl - INFO - Epoch [38][600/1281] lr: 2.134e-02, eta: 13:44:37, time: 0.530, data_time: 0.000, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9919, loss_cls: 0.6867, loss: 0.6867 +2025-06-24 14:11:45,948 - pyskl - INFO - Epoch [38][700/1281] lr: 2.133e-02, eta: 13:45:00, time: 0.534, data_time: 0.001, memory: 4083, top1_acc: 0.8413, top5_acc: 0.9906, loss_cls: 0.7711, loss: 0.7711 +2025-06-24 14:12:39,692 - pyskl - INFO - Epoch [38][800/1281] lr: 2.132e-02, eta: 13:45:23, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8269, top5_acc: 0.9906, loss_cls: 0.8263, loss: 0.8263 +2025-06-24 14:13:33,075 - pyskl - INFO - Epoch [38][900/1281] lr: 2.130e-02, eta: 13:45:45, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.8419, top5_acc: 0.9912, loss_cls: 0.7719, loss: 0.7719 +2025-06-24 14:14:27,141 - pyskl - INFO - Epoch [38][1000/1281] lr: 2.129e-02, eta: 13:46:09, time: 0.541, data_time: 0.000, memory: 4083, top1_acc: 0.8425, top5_acc: 0.9912, loss_cls: 0.7919, loss: 0.7919 +2025-06-24 14:15:21,121 - pyskl - INFO - Epoch [38][1100/1281] lr: 2.127e-02, eta: 13:46:33, time: 0.540, data_time: 0.000, memory: 4083, top1_acc: 0.8469, top5_acc: 0.9912, loss_cls: 0.7316, loss: 0.7316 +2025-06-24 14:16:14,385 - pyskl - INFO - Epoch [38][1200/1281] lr: 2.126e-02, eta: 13:46:53, time: 0.533, data_time: 0.000, memory: 4083, top1_acc: 0.8544, top5_acc: 0.9944, loss_cls: 0.6800, loss: 0.6800 +2025-06-24 14:16:57,528 - pyskl - INFO - Saving checkpoint at 38 epochs +2025-06-24 14:18:11,235 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:18:11,291 - pyskl - INFO - +top1_acc 0.7998 +top5_acc 0.9853 +2025-06-24 14:18:11,291 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:18:11,298 - pyskl - INFO - +mean_acc 0.7164 +2025-06-24 14:18:11,299 - pyskl - INFO - Epoch(val) [38][533] top1_acc: 0.7998, top5_acc: 0.9853, mean_class_accuracy: 0.7164 +2025-06-24 14:19:23,945 - pyskl - INFO - Epoch [39][100/1281] lr: 2.123e-02, eta: 13:46:20, time: 0.726, data_time: 0.193, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9969, loss_cls: 0.6658, loss: 0.6658 +2025-06-24 14:20:17,893 - pyskl - INFO - Epoch [39][200/1281] lr: 2.122e-02, eta: 13:46:43, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9950, loss_cls: 0.6746, loss: 0.6746 +2025-06-24 14:21:11,608 - pyskl - INFO - Epoch [39][300/1281] lr: 2.120e-02, eta: 13:47:04, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8594, top5_acc: 0.9925, loss_cls: 0.7191, loss: 0.7191 +2025-06-24 14:22:06,241 - pyskl - INFO - Epoch [39][400/1281] lr: 2.119e-02, eta: 13:47:27, time: 0.546, data_time: 0.000, memory: 4083, top1_acc: 0.8375, top5_acc: 0.9944, loss_cls: 0.7752, loss: 0.7752 +2025-06-24 14:23:00,190 - pyskl - INFO - Epoch [39][500/1281] lr: 2.117e-02, eta: 13:47:49, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.8300, top5_acc: 0.9925, loss_cls: 0.7883, loss: 0.7883 +2025-06-24 14:23:53,788 - pyskl - INFO - Epoch [39][600/1281] lr: 2.116e-02, eta: 13:48:09, time: 0.536, data_time: 0.000, memory: 4083, top1_acc: 0.8456, top5_acc: 0.9938, loss_cls: 0.7438, loss: 0.7438 +2025-06-24 14:24:48,183 - pyskl - INFO - Epoch [39][700/1281] lr: 2.114e-02, eta: 13:48:31, time: 0.544, data_time: 0.000, memory: 4083, top1_acc: 0.8500, top5_acc: 0.9925, loss_cls: 0.7305, loss: 0.7305 +2025-06-24 14:25:42,055 - pyskl - INFO - Epoch [39][800/1281] lr: 2.113e-02, eta: 13:48:51, time: 0.539, data_time: 0.000, memory: 4083, top1_acc: 0.8456, top5_acc: 0.9938, loss_cls: 0.7317, loss: 0.7317 +2025-06-24 14:26:35,530 - pyskl - INFO - Epoch [39][900/1281] lr: 2.111e-02, eta: 13:49:09, time: 0.535, data_time: 0.000, memory: 4083, top1_acc: 0.8600, top5_acc: 0.9950, loss_cls: 0.6935, loss: 0.6935 +2025-06-24 14:27:07,425 - pyskl - INFO - Epoch [39][1000/1281] lr: 2.110e-02, eta: 13:48:26, time: 0.319, data_time: 0.001, memory: 4083, top1_acc: 0.8431, top5_acc: 0.9938, loss_cls: 0.7312, loss: 0.7312 +2025-06-24 14:27:49,348 - pyskl - INFO - Epoch [39][1100/1281] lr: 2.108e-02, eta: 13:48:11, time: 0.419, data_time: 0.000, memory: 4083, top1_acc: 0.8300, top5_acc: 0.9925, loss_cls: 0.8091, loss: 0.8091 +2025-06-24 14:28:35,280 - pyskl - INFO - Epoch [39][1200/1281] lr: 2.107e-02, eta: 13:48:08, time: 0.459, data_time: 0.000, memory: 4083, top1_acc: 0.8275, top5_acc: 0.9925, loss_cls: 0.8004, loss: 0.8004 +2025-06-24 14:29:20,117 - pyskl - INFO - Saving checkpoint at 39 epochs +2025-06-24 14:30:32,014 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:30:32,083 - pyskl - INFO - +top1_acc 0.8089 +top5_acc 0.9858 +2025-06-24 14:30:32,083 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:30:32,091 - pyskl - INFO - +mean_acc 0.7143 +2025-06-24 14:30:32,095 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_35.pth was removed +2025-06-24 14:30:32,292 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_39.pth. +2025-06-24 14:30:32,293 - pyskl - INFO - Best top1_acc is 0.8089 at 39 epoch. +2025-06-24 14:30:32,295 - pyskl - INFO - Epoch(val) [39][533] top1_acc: 0.8089, top5_acc: 0.9858, mean_class_accuracy: 0.7143 +2025-06-24 14:31:59,181 - pyskl - INFO - Epoch [40][100/1281] lr: 2.104e-02, eta: 13:48:12, time: 0.869, data_time: 0.193, memory: 4083, top1_acc: 0.8638, top5_acc: 0.9938, loss_cls: 0.6749, loss: 0.6749 +2025-06-24 14:32:52,911 - pyskl - INFO - Epoch [40][200/1281] lr: 2.103e-02, eta: 13:48:30, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8519, top5_acc: 0.9881, loss_cls: 0.7143, loss: 0.7143 +2025-06-24 14:33:46,614 - pyskl - INFO - Epoch [40][300/1281] lr: 2.101e-02, eta: 13:48:47, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8556, top5_acc: 0.9938, loss_cls: 0.6893, loss: 0.6893 +2025-06-24 14:34:40,020 - pyskl - INFO - Epoch [40][400/1281] lr: 2.100e-02, eta: 13:49:04, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9925, loss_cls: 0.6569, loss: 0.6569 +2025-06-24 14:35:33,435 - pyskl - INFO - Epoch [40][500/1281] lr: 2.098e-02, eta: 13:49:21, time: 0.534, data_time: 0.000, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9938, loss_cls: 0.6628, loss: 0.6628 +2025-06-24 14:36:05,833 - pyskl - INFO - Epoch [40][600/1281] lr: 2.097e-02, eta: 13:48:38, time: 0.324, data_time: 0.000, memory: 4083, top1_acc: 0.8519, top5_acc: 0.9931, loss_cls: 0.7290, loss: 0.7290 +2025-06-24 14:36:47,324 - pyskl - INFO - Epoch [40][700/1281] lr: 2.095e-02, eta: 13:48:20, time: 0.415, data_time: 0.001, memory: 4083, top1_acc: 0.8450, top5_acc: 0.9944, loss_cls: 0.7519, loss: 0.7519 +2025-06-24 14:37:31,755 - pyskl - INFO - Epoch [40][800/1281] lr: 2.094e-02, eta: 13:48:11, time: 0.444, data_time: 0.000, memory: 4083, top1_acc: 0.8394, top5_acc: 0.9906, loss_cls: 0.7305, loss: 0.7305 +2025-06-24 14:38:24,560 - pyskl - INFO - Epoch [40][900/1281] lr: 2.092e-02, eta: 13:48:25, time: 0.528, data_time: 0.000, memory: 4083, top1_acc: 0.8488, top5_acc: 0.9950, loss_cls: 0.7095, loss: 0.7095 +2025-06-24 14:39:19,339 - pyskl - INFO - Epoch [40][1000/1281] lr: 2.091e-02, eta: 13:48:44, time: 0.548, data_time: 0.000, memory: 4083, top1_acc: 0.8438, top5_acc: 0.9881, loss_cls: 0.7379, loss: 0.7379 +2025-06-24 14:40:13,140 - pyskl - INFO - Epoch [40][1100/1281] lr: 2.089e-02, eta: 13:49:00, time: 0.538, data_time: 0.001, memory: 4083, top1_acc: 0.8456, top5_acc: 0.9938, loss_cls: 0.7404, loss: 0.7404 +2025-06-24 14:41:06,004 - pyskl - INFO - Epoch [40][1200/1281] lr: 2.088e-02, eta: 13:49:14, time: 0.529, data_time: 0.000, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9931, loss_cls: 0.7196, loss: 0.7196 +2025-06-24 14:41:50,198 - pyskl - INFO - Saving checkpoint at 40 epochs +2025-06-24 14:43:02,047 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:43:02,105 - pyskl - INFO - +top1_acc 0.8165 +top5_acc 0.9883 +2025-06-24 14:43:02,105 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:43:02,112 - pyskl - INFO - +mean_acc 0.7303 +2025-06-24 14:43:02,116 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_39.pth was removed +2025-06-24 14:43:02,306 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_40.pth. +2025-06-24 14:43:02,307 - pyskl - INFO - Best top1_acc is 0.8165 at 40 epoch. +2025-06-24 14:43:02,310 - pyskl - INFO - Epoch(val) [40][533] top1_acc: 0.8165, top5_acc: 0.9883, mean_class_accuracy: 0.7303 +2025-06-24 14:44:29,009 - pyskl - INFO - Epoch [41][100/1281] lr: 2.085e-02, eta: 13:49:12, time: 0.867, data_time: 0.197, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9956, loss_cls: 0.6584, loss: 0.6584 +2025-06-24 14:44:59,283 - pyskl - INFO - Epoch [41][200/1281] lr: 2.083e-02, eta: 13:48:23, time: 0.303, data_time: 0.000, memory: 4083, top1_acc: 0.8475, top5_acc: 0.9906, loss_cls: 0.7045, loss: 0.7045 +2025-06-24 14:45:44,716 - pyskl - INFO - Epoch [41][300/1281] lr: 2.082e-02, eta: 13:48:15, time: 0.454, data_time: 0.000, memory: 4083, top1_acc: 0.8494, top5_acc: 0.9925, loss_cls: 0.6991, loss: 0.6991 +2025-06-24 14:46:28,157 - pyskl - INFO - Epoch [41][400/1281] lr: 2.080e-02, eta: 13:48:02, time: 0.434, data_time: 0.000, memory: 4083, top1_acc: 0.8550, top5_acc: 0.9888, loss_cls: 0.7186, loss: 0.7186 +2025-06-24 14:47:21,468 - pyskl - INFO - Epoch [41][500/1281] lr: 2.079e-02, eta: 13:48:16, time: 0.533, data_time: 0.000, memory: 4083, top1_acc: 0.8506, top5_acc: 0.9900, loss_cls: 0.7563, loss: 0.7563 +2025-06-24 14:48:14,465 - pyskl - INFO - Epoch [41][600/1281] lr: 2.077e-02, eta: 13:48:28, time: 0.530, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9962, loss_cls: 0.6614, loss: 0.6614 +2025-06-24 14:49:08,193 - pyskl - INFO - Epoch [41][700/1281] lr: 2.076e-02, eta: 13:48:42, time: 0.537, data_time: 0.000, memory: 4083, top1_acc: 0.8375, top5_acc: 0.9906, loss_cls: 0.7938, loss: 0.7938 +2025-06-24 14:50:02,275 - pyskl - INFO - Epoch [41][800/1281] lr: 2.074e-02, eta: 13:48:56, time: 0.541, data_time: 0.000, memory: 4083, top1_acc: 0.8581, top5_acc: 0.9950, loss_cls: 0.6814, loss: 0.6814 +2025-06-24 14:50:57,042 - pyskl - INFO - Epoch [41][900/1281] lr: 2.073e-02, eta: 13:49:13, time: 0.548, data_time: 0.000, memory: 4083, top1_acc: 0.8575, top5_acc: 0.9950, loss_cls: 0.6769, loss: 0.6769 +2025-06-24 14:51:50,048 - pyskl - INFO - Epoch [41][1000/1281] lr: 2.071e-02, eta: 13:49:24, time: 0.530, data_time: 0.000, memory: 4083, top1_acc: 0.8581, top5_acc: 0.9881, loss_cls: 0.7562, loss: 0.7562 +2025-06-24 14:52:43,175 - pyskl - INFO - Epoch [41][1100/1281] lr: 2.070e-02, eta: 13:49:35, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9956, loss_cls: 0.6699, loss: 0.6699 +2025-06-24 14:53:35,823 - pyskl - INFO - Epoch [41][1200/1281] lr: 2.068e-02, eta: 13:49:45, time: 0.526, data_time: 0.001, memory: 4083, top1_acc: 0.8594, top5_acc: 0.9938, loss_cls: 0.6753, loss: 0.6753 +2025-06-24 14:54:06,896 - pyskl - INFO - Saving checkpoint at 41 epochs +2025-06-24 14:55:12,745 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:55:12,799 - pyskl - INFO - +top1_acc 0.8007 +top5_acc 0.9832 +2025-06-24 14:55:12,800 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:55:12,806 - pyskl - INFO - +mean_acc 0.7029 +2025-06-24 14:55:12,807 - pyskl - INFO - Epoch(val) [41][533] top1_acc: 0.8007, top5_acc: 0.9832, mean_class_accuracy: 0.7029 +2025-06-24 14:56:30,229 - pyskl - INFO - Epoch [42][100/1281] lr: 2.065e-02, eta: 13:49:15, time: 0.774, data_time: 0.195, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9938, loss_cls: 0.6269, loss: 0.6269 +2025-06-24 14:57:18,170 - pyskl - INFO - Epoch [42][200/1281] lr: 2.064e-02, eta: 13:49:12, time: 0.479, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9950, loss_cls: 0.6192, loss: 0.6192 +2025-06-24 14:58:06,209 - pyskl - INFO - Epoch [42][300/1281] lr: 2.062e-02, eta: 13:49:09, time: 0.480, data_time: 0.000, memory: 4083, top1_acc: 0.8562, top5_acc: 0.9919, loss_cls: 0.6988, loss: 0.6988 +2025-06-24 14:58:54,321 - pyskl - INFO - Epoch [42][400/1281] lr: 2.061e-02, eta: 13:49:05, time: 0.481, data_time: 0.000, memory: 4083, top1_acc: 0.8550, top5_acc: 0.9931, loss_cls: 0.7039, loss: 0.7039 +2025-06-24 14:59:42,265 - pyskl - INFO - Epoch [42][500/1281] lr: 2.059e-02, eta: 13:49:02, time: 0.479, data_time: 0.000, memory: 4083, top1_acc: 0.8612, top5_acc: 0.9944, loss_cls: 0.6861, loss: 0.6861 +2025-06-24 15:00:30,477 - pyskl - INFO - Epoch [42][600/1281] lr: 2.057e-02, eta: 13:48:59, time: 0.482, data_time: 0.000, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9956, loss_cls: 0.6421, loss: 0.6421 +2025-06-24 15:01:18,778 - pyskl - INFO - Epoch [42][700/1281] lr: 2.056e-02, eta: 13:48:56, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.8544, top5_acc: 0.9912, loss_cls: 0.7376, loss: 0.7376 +2025-06-24 15:02:07,182 - pyskl - INFO - Epoch [42][800/1281] lr: 2.054e-02, eta: 13:48:53, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.8325, top5_acc: 0.9869, loss_cls: 0.7676, loss: 0.7676 +2025-06-24 15:02:55,410 - pyskl - INFO - Epoch [42][900/1281] lr: 2.053e-02, eta: 13:48:49, time: 0.482, data_time: 0.000, memory: 4083, top1_acc: 0.8488, top5_acc: 0.9925, loss_cls: 0.7536, loss: 0.7536 +2025-06-24 15:03:43,684 - pyskl - INFO - Epoch [42][1000/1281] lr: 2.051e-02, eta: 13:48:45, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.8325, top5_acc: 0.9912, loss_cls: 0.7903, loss: 0.7903 +2025-06-24 15:04:31,673 - pyskl - INFO - Epoch [42][1100/1281] lr: 2.050e-02, eta: 13:48:41, time: 0.480, data_time: 0.000, memory: 4083, top1_acc: 0.8550, top5_acc: 0.9938, loss_cls: 0.7115, loss: 0.7115 +2025-06-24 15:05:19,697 - pyskl - INFO - Epoch [42][1200/1281] lr: 2.048e-02, eta: 13:48:36, time: 0.480, data_time: 0.000, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9956, loss_cls: 0.7262, loss: 0.7262 +2025-06-24 15:05:41,572 - pyskl - INFO - Saving checkpoint at 42 epochs +2025-06-24 15:06:38,864 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:06:38,934 - pyskl - INFO - +top1_acc 0.8256 +top5_acc 0.9893 +2025-06-24 15:06:38,934 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:06:38,943 - pyskl - INFO - +mean_acc 0.7352 +2025-06-24 15:06:38,948 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_40.pth was removed +2025-06-24 15:06:39,153 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_42.pth. +2025-06-24 15:06:39,153 - pyskl - INFO - Best top1_acc is 0.8256 at 42 epoch. +2025-06-24 15:06:39,156 - pyskl - INFO - Epoch(val) [42][533] top1_acc: 0.8256, top5_acc: 0.9893, mean_class_accuracy: 0.7352 +2025-06-24 15:07:59,385 - pyskl - INFO - Epoch [43][100/1281] lr: 2.045e-02, eta: 13:48:10, time: 0.802, data_time: 0.194, memory: 4083, top1_acc: 0.8625, top5_acc: 0.9950, loss_cls: 0.6652, loss: 0.6652 +2025-06-24 15:08:48,645 - pyskl - INFO - Epoch [43][200/1281] lr: 2.044e-02, eta: 13:48:08, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9931, loss_cls: 0.6144, loss: 0.6144 +2025-06-24 15:09:37,687 - pyskl - INFO - Epoch [43][300/1281] lr: 2.042e-02, eta: 13:48:06, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8550, top5_acc: 0.9938, loss_cls: 0.6844, loss: 0.6844 +2025-06-24 15:10:26,516 - pyskl - INFO - Epoch [43][400/1281] lr: 2.040e-02, eta: 13:48:02, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8631, top5_acc: 0.9931, loss_cls: 0.7117, loss: 0.7117 +2025-06-24 15:11:15,197 - pyskl - INFO - Epoch [43][500/1281] lr: 2.039e-02, eta: 13:47:58, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8494, top5_acc: 0.9931, loss_cls: 0.6850, loss: 0.6850 +2025-06-24 15:12:04,439 - pyskl - INFO - Epoch [43][600/1281] lr: 2.037e-02, eta: 13:47:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8525, top5_acc: 0.9931, loss_cls: 0.7028, loss: 0.7028 +2025-06-24 15:12:53,502 - pyskl - INFO - Epoch [43][700/1281] lr: 2.036e-02, eta: 13:47:53, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9919, loss_cls: 0.6776, loss: 0.6776 +2025-06-24 15:13:42,716 - pyskl - INFO - Epoch [43][800/1281] lr: 2.034e-02, eta: 13:47:50, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8438, top5_acc: 0.9925, loss_cls: 0.7186, loss: 0.7186 +2025-06-24 15:14:31,934 - pyskl - INFO - Epoch [43][900/1281] lr: 2.033e-02, eta: 13:47:46, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8394, top5_acc: 0.9956, loss_cls: 0.7373, loss: 0.7373 +2025-06-24 15:15:21,071 - pyskl - INFO - Epoch [43][1000/1281] lr: 2.031e-02, eta: 13:47:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8419, top5_acc: 0.9938, loss_cls: 0.7341, loss: 0.7341 +2025-06-24 15:16:10,202 - pyskl - INFO - Epoch [43][1100/1281] lr: 2.029e-02, eta: 13:47:39, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8475, top5_acc: 0.9931, loss_cls: 0.7276, loss: 0.7276 +2025-06-24 15:16:53,331 - pyskl - INFO - Epoch [43][1200/1281] lr: 2.028e-02, eta: 13:47:20, time: 0.431, data_time: 0.000, memory: 4083, top1_acc: 0.8569, top5_acc: 0.9944, loss_cls: 0.6761, loss: 0.6761 +2025-06-24 15:17:21,849 - pyskl - INFO - Saving checkpoint at 43 epochs +2025-06-24 15:18:06,806 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:18:06,877 - pyskl - INFO - +top1_acc 0.7986 +top5_acc 0.9853 +2025-06-24 15:18:06,877 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:18:06,884 - pyskl - INFO - +mean_acc 0.7164 +2025-06-24 15:18:06,886 - pyskl - INFO - Epoch(val) [43][533] top1_acc: 0.7986, top5_acc: 0.9853, mean_class_accuracy: 0.7164 +2025-06-24 15:19:27,912 - pyskl - INFO - Epoch [44][100/1281] lr: 2.025e-02, eta: 13:46:53, time: 0.810, data_time: 0.195, memory: 4083, top1_acc: 0.8550, top5_acc: 0.9931, loss_cls: 0.7174, loss: 0.7174 +2025-06-24 15:20:16,972 - pyskl - INFO - Epoch [44][200/1281] lr: 2.023e-02, eta: 13:46:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9919, loss_cls: 0.6565, loss: 0.6565 +2025-06-24 15:21:06,234 - pyskl - INFO - Epoch [44][300/1281] lr: 2.022e-02, eta: 13:46:45, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8738, top5_acc: 0.9981, loss_cls: 0.6188, loss: 0.6188 +2025-06-24 15:21:55,258 - pyskl - INFO - Epoch [44][400/1281] lr: 2.020e-02, eta: 13:46:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9931, loss_cls: 0.6498, loss: 0.6498 +2025-06-24 15:22:44,380 - pyskl - INFO - Epoch [44][500/1281] lr: 2.018e-02, eta: 13:46:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8462, top5_acc: 0.9975, loss_cls: 0.7427, loss: 0.7427 +2025-06-24 15:23:33,487 - pyskl - INFO - Epoch [44][600/1281] lr: 2.017e-02, eta: 13:46:30, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8594, top5_acc: 0.9938, loss_cls: 0.6995, loss: 0.6995 +2025-06-24 15:24:22,665 - pyskl - INFO - Epoch [44][700/1281] lr: 2.015e-02, eta: 13:46:25, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8550, top5_acc: 0.9962, loss_cls: 0.7002, loss: 0.7002 +2025-06-24 15:25:11,996 - pyskl - INFO - Epoch [44][800/1281] lr: 2.014e-02, eta: 13:46:20, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8300, top5_acc: 0.9894, loss_cls: 0.7720, loss: 0.7720 +2025-06-24 15:26:01,117 - pyskl - INFO - Epoch [44][900/1281] lr: 2.012e-02, eta: 13:46:15, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8250, top5_acc: 0.9925, loss_cls: 0.7957, loss: 0.7957 +2025-06-24 15:26:50,079 - pyskl - INFO - Epoch [44][1000/1281] lr: 2.010e-02, eta: 13:46:09, time: 0.490, data_time: 0.001, memory: 4083, top1_acc: 0.8506, top5_acc: 0.9938, loss_cls: 0.6817, loss: 0.6817 +2025-06-24 15:27:39,562 - pyskl - INFO - Epoch [44][1100/1281] lr: 2.009e-02, eta: 13:46:04, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8438, top5_acc: 0.9925, loss_cls: 0.6810, loss: 0.6810 +2025-06-24 15:28:16,485 - pyskl - INFO - Epoch [44][1200/1281] lr: 2.007e-02, eta: 13:45:29, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 0.8456, top5_acc: 0.9944, loss_cls: 0.7274, loss: 0.7274 +2025-06-24 15:29:01,269 - pyskl - INFO - Saving checkpoint at 44 epochs +2025-06-24 15:29:49,762 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:29:49,820 - pyskl - INFO - +top1_acc 0.8120 +top5_acc 0.9856 +2025-06-24 15:29:49,820 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:29:49,831 - pyskl - INFO - +mean_acc 0.7308 +2025-06-24 15:29:49,834 - pyskl - INFO - Epoch(val) [44][533] top1_acc: 0.8120, top5_acc: 0.9856, mean_class_accuracy: 0.7308 +2025-06-24 15:31:09,729 - pyskl - INFO - Epoch [45][100/1281] lr: 2.004e-02, eta: 13:44:56, time: 0.799, data_time: 0.193, memory: 4083, top1_acc: 0.8669, top5_acc: 0.9969, loss_cls: 0.6681, loss: 0.6681 +2025-06-24 15:31:58,974 - pyskl - INFO - Epoch [45][200/1281] lr: 2.003e-02, eta: 13:44:50, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9931, loss_cls: 0.6572, loss: 0.6572 +2025-06-24 15:32:47,975 - pyskl - INFO - Epoch [45][300/1281] lr: 2.001e-02, eta: 13:44:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8681, top5_acc: 0.9981, loss_cls: 0.6090, loss: 0.6090 +2025-06-24 15:33:37,569 - pyskl - INFO - Epoch [45][400/1281] lr: 1.999e-02, eta: 13:44:38, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8656, top5_acc: 0.9950, loss_cls: 0.6634, loss: 0.6634 +2025-06-24 15:34:26,691 - pyskl - INFO - Epoch [45][500/1281] lr: 1.998e-02, eta: 13:44:32, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8681, top5_acc: 0.9956, loss_cls: 0.6494, loss: 0.6494 +2025-06-24 15:35:16,111 - pyskl - INFO - Epoch [45][600/1281] lr: 1.996e-02, eta: 13:44:26, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8506, top5_acc: 0.9862, loss_cls: 0.7062, loss: 0.7062 +2025-06-24 15:36:05,907 - pyskl - INFO - Epoch [45][700/1281] lr: 1.994e-02, eta: 13:44:20, time: 0.498, data_time: 0.000, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9925, loss_cls: 0.6671, loss: 0.6671 +2025-06-24 15:36:55,137 - pyskl - INFO - Epoch [45][800/1281] lr: 1.993e-02, eta: 13:44:14, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8569, top5_acc: 0.9944, loss_cls: 0.6996, loss: 0.6996 +2025-06-24 15:37:44,298 - pyskl - INFO - Epoch [45][900/1281] lr: 1.991e-02, eta: 13:44:06, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9962, loss_cls: 0.6026, loss: 0.6026 +2025-06-24 15:38:33,484 - pyskl - INFO - Epoch [45][1000/1281] lr: 1.989e-02, eta: 13:43:59, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8600, top5_acc: 0.9944, loss_cls: 0.6666, loss: 0.6666 +2025-06-24 15:39:22,680 - pyskl - INFO - Epoch [45][1100/1281] lr: 1.988e-02, eta: 13:43:52, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8500, top5_acc: 0.9931, loss_cls: 0.7402, loss: 0.7402 +2025-06-24 15:39:59,650 - pyskl - INFO - Epoch [45][1200/1281] lr: 1.986e-02, eta: 13:43:16, time: 0.370, data_time: 0.000, memory: 4083, top1_acc: 0.8562, top5_acc: 0.9900, loss_cls: 0.7232, loss: 0.7232 +2025-06-24 15:40:43,031 - pyskl - INFO - Saving checkpoint at 45 epochs +2025-06-24 15:41:31,645 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:41:31,699 - pyskl - INFO - +top1_acc 0.8075 +top5_acc 0.9833 +2025-06-24 15:41:31,700 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:41:31,707 - pyskl - INFO - +mean_acc 0.7296 +2025-06-24 15:41:31,709 - pyskl - INFO - Epoch(val) [45][533] top1_acc: 0.8075, top5_acc: 0.9833, mean_class_accuracy: 0.7296 +2025-06-24 15:42:51,349 - pyskl - INFO - Epoch [46][100/1281] lr: 1.983e-02, eta: 13:42:40, time: 0.796, data_time: 0.190, memory: 4083, top1_acc: 0.8569, top5_acc: 0.9925, loss_cls: 0.7165, loss: 0.7165 +2025-06-24 15:43:40,410 - pyskl - INFO - Epoch [46][200/1281] lr: 1.981e-02, eta: 13:42:32, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8600, top5_acc: 0.9944, loss_cls: 0.6864, loss: 0.6864 +2025-06-24 15:44:29,500 - pyskl - INFO - Epoch [46][300/1281] lr: 1.980e-02, eta: 13:42:24, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9944, loss_cls: 0.6745, loss: 0.6745 +2025-06-24 15:45:18,697 - pyskl - INFO - Epoch [46][400/1281] lr: 1.978e-02, eta: 13:42:16, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8387, top5_acc: 0.9906, loss_cls: 0.7462, loss: 0.7462 +2025-06-24 15:46:07,917 - pyskl - INFO - Epoch [46][500/1281] lr: 1.976e-02, eta: 13:42:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9956, loss_cls: 0.6144, loss: 0.6144 +2025-06-24 15:46:57,102 - pyskl - INFO - Epoch [46][600/1281] lr: 1.975e-02, eta: 13:41:59, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8506, top5_acc: 0.9975, loss_cls: 0.7075, loss: 0.7075 +2025-06-24 15:47:46,542 - pyskl - INFO - Epoch [46][700/1281] lr: 1.973e-02, eta: 13:41:51, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8531, top5_acc: 0.9956, loss_cls: 0.6728, loss: 0.6728 +2025-06-24 15:48:35,837 - pyskl - INFO - Epoch [46][800/1281] lr: 1.971e-02, eta: 13:41:43, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8681, top5_acc: 0.9956, loss_cls: 0.6722, loss: 0.6722 +2025-06-24 15:49:24,746 - pyskl - INFO - Epoch [46][900/1281] lr: 1.970e-02, eta: 13:41:34, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 0.8625, top5_acc: 0.9956, loss_cls: 0.6943, loss: 0.6943 +2025-06-24 15:50:14,197 - pyskl - INFO - Epoch [46][1000/1281] lr: 1.968e-02, eta: 13:41:25, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8681, top5_acc: 0.9944, loss_cls: 0.6447, loss: 0.6447 +2025-06-24 15:51:03,396 - pyskl - INFO - Epoch [46][1100/1281] lr: 1.966e-02, eta: 13:41:16, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8656, top5_acc: 0.9938, loss_cls: 0.6918, loss: 0.6918 +2025-06-24 15:51:41,470 - pyskl - INFO - Epoch [46][1200/1281] lr: 1.965e-02, eta: 13:40:42, time: 0.381, data_time: 0.000, memory: 4083, top1_acc: 0.8575, top5_acc: 0.9900, loss_cls: 0.7233, loss: 0.7233 +2025-06-24 15:52:22,578 - pyskl - INFO - Saving checkpoint at 46 epochs +2025-06-24 15:53:10,138 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:53:10,211 - pyskl - INFO - +top1_acc 0.8072 +top5_acc 0.9831 +2025-06-24 15:53:10,211 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:53:10,220 - pyskl - INFO - +mean_acc 0.7077 +2025-06-24 15:53:10,222 - pyskl - INFO - Epoch(val) [46][533] top1_acc: 0.8072, top5_acc: 0.9831, mean_class_accuracy: 0.7077 +2025-06-24 15:54:31,249 - pyskl - INFO - Epoch [47][100/1281] lr: 1.962e-02, eta: 13:40:07, time: 0.810, data_time: 0.195, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9944, loss_cls: 0.6295, loss: 0.6295 +2025-06-24 15:55:20,610 - pyskl - INFO - Epoch [47][200/1281] lr: 1.960e-02, eta: 13:39:58, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9931, loss_cls: 0.6091, loss: 0.6091 +2025-06-24 15:56:09,888 - pyskl - INFO - Epoch [47][300/1281] lr: 1.958e-02, eta: 13:39:48, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9969, loss_cls: 0.6000, loss: 0.6000 +2025-06-24 15:56:59,189 - pyskl - INFO - Epoch [47][400/1281] lr: 1.957e-02, eta: 13:39:39, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8556, top5_acc: 0.9931, loss_cls: 0.6718, loss: 0.6718 +2025-06-24 15:57:48,323 - pyskl - INFO - Epoch [47][500/1281] lr: 1.955e-02, eta: 13:39:29, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8550, top5_acc: 0.9925, loss_cls: 0.7120, loss: 0.7120 +2025-06-24 15:58:37,651 - pyskl - INFO - Epoch [47][600/1281] lr: 1.953e-02, eta: 13:39:19, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8681, top5_acc: 0.9931, loss_cls: 0.6587, loss: 0.6587 +2025-06-24 15:59:26,973 - pyskl - INFO - Epoch [47][700/1281] lr: 1.952e-02, eta: 13:39:09, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8531, top5_acc: 0.9931, loss_cls: 0.7054, loss: 0.7054 +2025-06-24 16:00:15,958 - pyskl - INFO - Epoch [47][800/1281] lr: 1.950e-02, eta: 13:38:59, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8625, top5_acc: 0.9912, loss_cls: 0.6947, loss: 0.6947 +2025-06-24 16:01:05,378 - pyskl - INFO - Epoch [47][900/1281] lr: 1.948e-02, eta: 13:38:49, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8538, top5_acc: 0.9950, loss_cls: 0.7086, loss: 0.7086 +2025-06-24 16:01:54,660 - pyskl - INFO - Epoch [47][1000/1281] lr: 1.947e-02, eta: 13:38:39, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9956, loss_cls: 0.6596, loss: 0.6596 +2025-06-24 16:02:43,597 - pyskl - INFO - Epoch [47][1100/1281] lr: 1.945e-02, eta: 13:38:27, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8638, top5_acc: 0.9938, loss_cls: 0.6866, loss: 0.6866 +2025-06-24 16:03:20,680 - pyskl - INFO - Epoch [47][1200/1281] lr: 1.943e-02, eta: 13:37:50, time: 0.371, data_time: 0.000, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9894, loss_cls: 0.6369, loss: 0.6369 +2025-06-24 16:04:03,501 - pyskl - INFO - Saving checkpoint at 47 epochs +2025-06-24 16:04:51,354 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:04:51,425 - pyskl - INFO - +top1_acc 0.8141 +top5_acc 0.9886 +2025-06-24 16:04:51,425 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:04:51,433 - pyskl - INFO - +mean_acc 0.7218 +2025-06-24 16:04:51,435 - pyskl - INFO - Epoch(val) [47][533] top1_acc: 0.8141, top5_acc: 0.9886, mean_class_accuracy: 0.7218 +2025-06-24 16:06:11,610 - pyskl - INFO - Epoch [48][100/1281] lr: 1.940e-02, eta: 13:37:11, time: 0.802, data_time: 0.192, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9919, loss_cls: 0.6223, loss: 0.6223 +2025-06-24 16:07:00,469 - pyskl - INFO - Epoch [48][200/1281] lr: 1.938e-02, eta: 13:36:59, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8562, top5_acc: 0.9931, loss_cls: 0.6632, loss: 0.6632 +2025-06-24 16:07:49,755 - pyskl - INFO - Epoch [48][300/1281] lr: 1.937e-02, eta: 13:36:48, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9969, loss_cls: 0.6393, loss: 0.6393 +2025-06-24 16:08:38,881 - pyskl - INFO - Epoch [48][400/1281] lr: 1.935e-02, eta: 13:36:37, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9925, loss_cls: 0.6455, loss: 0.6455 +2025-06-24 16:09:28,109 - pyskl - INFO - Epoch [48][500/1281] lr: 1.933e-02, eta: 13:36:26, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8594, top5_acc: 0.9938, loss_cls: 0.6956, loss: 0.6956 +2025-06-24 16:10:17,144 - pyskl - INFO - Epoch [48][600/1281] lr: 1.932e-02, eta: 13:36:14, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9919, loss_cls: 0.6513, loss: 0.6513 +2025-06-24 16:11:06,422 - pyskl - INFO - Epoch [48][700/1281] lr: 1.930e-02, eta: 13:36:02, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8600, top5_acc: 0.9919, loss_cls: 0.6998, loss: 0.6998 +2025-06-24 16:11:55,563 - pyskl - INFO - Epoch [48][800/1281] lr: 1.928e-02, eta: 13:35:50, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8538, top5_acc: 0.9931, loss_cls: 0.6841, loss: 0.6841 +2025-06-24 16:12:44,710 - pyskl - INFO - Epoch [48][900/1281] lr: 1.926e-02, eta: 13:35:38, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8556, top5_acc: 0.9944, loss_cls: 0.6880, loss: 0.6880 +2025-06-24 16:13:33,765 - pyskl - INFO - Epoch [48][1000/1281] lr: 1.925e-02, eta: 13:35:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9944, loss_cls: 0.6960, loss: 0.6960 +2025-06-24 16:14:23,044 - pyskl - INFO - Epoch [48][1100/1281] lr: 1.923e-02, eta: 13:35:14, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8612, top5_acc: 0.9938, loss_cls: 0.6948, loss: 0.6948 +2025-06-24 16:14:59,632 - pyskl - INFO - Epoch [48][1200/1281] lr: 1.921e-02, eta: 13:34:35, time: 0.366, data_time: 0.000, memory: 4083, top1_acc: 0.8669, top5_acc: 0.9981, loss_cls: 0.6493, loss: 0.6493 +2025-06-24 16:15:43,402 - pyskl - INFO - Saving checkpoint at 48 epochs +2025-06-24 16:16:31,662 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:16:31,733 - pyskl - INFO - +top1_acc 0.8371 +top5_acc 0.9898 +2025-06-24 16:16:31,733 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:16:31,740 - pyskl - INFO - +mean_acc 0.7534 +2025-06-24 16:16:31,744 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_42.pth was removed +2025-06-24 16:16:31,924 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_48.pth. +2025-06-24 16:16:31,924 - pyskl - INFO - Best top1_acc is 0.8371 at 48 epoch. +2025-06-24 16:16:31,927 - pyskl - INFO - Epoch(val) [48][533] top1_acc: 0.8371, top5_acc: 0.9898, mean_class_accuracy: 0.7534 +2025-06-24 16:17:51,755 - pyskl - INFO - Epoch [49][100/1281] lr: 1.918e-02, eta: 13:33:53, time: 0.798, data_time: 0.200, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9962, loss_cls: 0.6086, loss: 0.6086 +2025-06-24 16:18:41,096 - pyskl - INFO - Epoch [49][200/1281] lr: 1.916e-02, eta: 13:33:41, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9975, loss_cls: 0.5837, loss: 0.5837 +2025-06-24 16:19:30,132 - pyskl - INFO - Epoch [49][300/1281] lr: 1.915e-02, eta: 13:33:28, time: 0.490, data_time: 0.001, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9944, loss_cls: 0.6096, loss: 0.6096 +2025-06-24 16:20:19,345 - pyskl - INFO - Epoch [49][400/1281] lr: 1.913e-02, eta: 13:33:15, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8594, top5_acc: 0.9925, loss_cls: 0.6703, loss: 0.6703 +2025-06-24 16:21:08,468 - pyskl - INFO - Epoch [49][500/1281] lr: 1.911e-02, eta: 13:33:02, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8588, top5_acc: 0.9944, loss_cls: 0.6791, loss: 0.6791 +2025-06-24 16:21:57,709 - pyskl - INFO - Epoch [49][600/1281] lr: 1.909e-02, eta: 13:32:50, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9938, loss_cls: 0.6114, loss: 0.6114 +2025-06-24 16:22:47,010 - pyskl - INFO - Epoch [49][700/1281] lr: 1.908e-02, eta: 13:32:37, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9956, loss_cls: 0.6313, loss: 0.6313 +2025-06-24 16:23:36,394 - pyskl - INFO - Epoch [49][800/1281] lr: 1.906e-02, eta: 13:32:24, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9962, loss_cls: 0.6252, loss: 0.6252 +2025-06-24 16:24:25,713 - pyskl - INFO - Epoch [49][900/1281] lr: 1.904e-02, eta: 13:32:11, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8500, top5_acc: 0.9888, loss_cls: 0.7709, loss: 0.7709 +2025-06-24 16:25:14,693 - pyskl - INFO - Epoch [49][1000/1281] lr: 1.902e-02, eta: 13:31:57, time: 0.490, data_time: 0.001, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9925, loss_cls: 0.6947, loss: 0.6947 +2025-06-24 16:26:03,987 - pyskl - INFO - Epoch [49][1100/1281] lr: 1.901e-02, eta: 13:31:44, time: 0.493, data_time: 0.001, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9962, loss_cls: 0.6291, loss: 0.6291 +2025-06-24 16:26:40,781 - pyskl - INFO - Epoch [49][1200/1281] lr: 1.899e-02, eta: 13:31:05, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9925, loss_cls: 0.6399, loss: 0.6399 +2025-06-24 16:27:23,921 - pyskl - INFO - Saving checkpoint at 49 epochs +2025-06-24 16:28:12,265 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:28:12,319 - pyskl - INFO - +top1_acc 0.8010 +top5_acc 0.9883 +2025-06-24 16:28:12,320 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:28:12,326 - pyskl - INFO - +mean_acc 0.7182 +2025-06-24 16:28:12,328 - pyskl - INFO - Epoch(val) [49][533] top1_acc: 0.8010, top5_acc: 0.9883, mean_class_accuracy: 0.7182 +2025-06-24 16:29:32,766 - pyskl - INFO - Epoch [50][100/1281] lr: 1.896e-02, eta: 13:30:22, time: 0.804, data_time: 0.195, memory: 4083, top1_acc: 0.8656, top5_acc: 0.9919, loss_cls: 0.6528, loss: 0.6528 +2025-06-24 16:30:21,734 - pyskl - INFO - Epoch [50][200/1281] lr: 1.894e-02, eta: 13:30:08, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9969, loss_cls: 0.5509, loss: 0.5509 +2025-06-24 16:31:11,107 - pyskl - INFO - Epoch [50][300/1281] lr: 1.892e-02, eta: 13:29:54, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9981, loss_cls: 0.6027, loss: 0.6027 +2025-06-24 16:32:00,241 - pyskl - INFO - Epoch [50][400/1281] lr: 1.891e-02, eta: 13:29:40, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9962, loss_cls: 0.6155, loss: 0.6155 +2025-06-24 16:32:49,506 - pyskl - INFO - Epoch [50][500/1281] lr: 1.889e-02, eta: 13:29:26, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8562, top5_acc: 0.9950, loss_cls: 0.6550, loss: 0.6550 +2025-06-24 16:33:39,138 - pyskl - INFO - Epoch [50][600/1281] lr: 1.887e-02, eta: 13:29:12, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8631, top5_acc: 0.9950, loss_cls: 0.6531, loss: 0.6531 +2025-06-24 16:34:28,522 - pyskl - INFO - Epoch [50][700/1281] lr: 1.885e-02, eta: 13:28:58, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8600, top5_acc: 0.9950, loss_cls: 0.6703, loss: 0.6703 +2025-06-24 16:35:17,752 - pyskl - INFO - Epoch [50][800/1281] lr: 1.884e-02, eta: 13:28:44, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8656, top5_acc: 0.9956, loss_cls: 0.6553, loss: 0.6553 +2025-06-24 16:36:06,975 - pyskl - INFO - Epoch [50][900/1281] lr: 1.882e-02, eta: 13:28:29, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9956, loss_cls: 0.6291, loss: 0.6291 +2025-06-24 16:36:56,228 - pyskl - INFO - Epoch [50][1000/1281] lr: 1.880e-02, eta: 13:28:15, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8675, top5_acc: 0.9944, loss_cls: 0.6396, loss: 0.6396 +2025-06-24 16:37:44,824 - pyskl - INFO - Epoch [50][1100/1281] lr: 1.878e-02, eta: 13:27:59, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.8512, top5_acc: 0.9956, loss_cls: 0.6853, loss: 0.6853 +2025-06-24 16:38:21,419 - pyskl - INFO - Epoch [50][1200/1281] lr: 1.876e-02, eta: 13:27:19, time: 0.366, data_time: 0.000, memory: 4083, top1_acc: 0.8606, top5_acc: 0.9956, loss_cls: 0.6732, loss: 0.6732 +2025-06-24 16:39:05,006 - pyskl - INFO - Saving checkpoint at 50 epochs +2025-06-24 16:39:53,164 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:39:53,232 - pyskl - INFO - +top1_acc 0.7925 +top5_acc 0.9854 +2025-06-24 16:39:53,232 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:39:53,241 - pyskl - INFO - +mean_acc 0.7237 +2025-06-24 16:39:53,243 - pyskl - INFO - Epoch(val) [50][533] top1_acc: 0.7925, top5_acc: 0.9854, mean_class_accuracy: 0.7237 +2025-06-24 16:41:11,293 - pyskl - INFO - Epoch [51][100/1281] lr: 1.873e-02, eta: 13:26:29, time: 0.780, data_time: 0.196, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9975, loss_cls: 0.6024, loss: 0.6024 +2025-06-24 16:42:00,541 - pyskl - INFO - Epoch [51][200/1281] lr: 1.871e-02, eta: 13:26:14, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9956, loss_cls: 0.5624, loss: 0.5624 +2025-06-24 16:42:49,817 - pyskl - INFO - Epoch [51][300/1281] lr: 1.870e-02, eta: 13:25:59, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8738, top5_acc: 0.9944, loss_cls: 0.6304, loss: 0.6304 +2025-06-24 16:43:39,238 - pyskl - INFO - Epoch [51][400/1281] lr: 1.868e-02, eta: 13:25:44, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9906, loss_cls: 0.6316, loss: 0.6316 +2025-06-24 16:44:27,912 - pyskl - INFO - Epoch [51][500/1281] lr: 1.866e-02, eta: 13:25:28, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9912, loss_cls: 0.6411, loss: 0.6411 +2025-06-24 16:45:16,719 - pyskl - INFO - Epoch [51][600/1281] lr: 1.864e-02, eta: 13:25:12, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8650, top5_acc: 0.9956, loss_cls: 0.6540, loss: 0.6540 +2025-06-24 16:46:05,744 - pyskl - INFO - Epoch [51][700/1281] lr: 1.863e-02, eta: 13:24:56, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8594, top5_acc: 0.9938, loss_cls: 0.6650, loss: 0.6650 +2025-06-24 16:46:54,795 - pyskl - INFO - Epoch [51][800/1281] lr: 1.861e-02, eta: 13:24:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9969, loss_cls: 0.6181, loss: 0.6181 +2025-06-24 16:47:43,793 - pyskl - INFO - Epoch [51][900/1281] lr: 1.859e-02, eta: 13:24:23, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9919, loss_cls: 0.6592, loss: 0.6592 +2025-06-24 16:48:33,327 - pyskl - INFO - Epoch [51][1000/1281] lr: 1.857e-02, eta: 13:24:08, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8675, top5_acc: 0.9956, loss_cls: 0.6581, loss: 0.6581 +2025-06-24 16:49:22,518 - pyskl - INFO - Epoch [51][1100/1281] lr: 1.855e-02, eta: 13:23:52, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8594, top5_acc: 0.9938, loss_cls: 0.6786, loss: 0.6786 +2025-06-24 16:50:00,595 - pyskl - INFO - Epoch [51][1200/1281] lr: 1.854e-02, eta: 13:23:14, time: 0.381, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9912, loss_cls: 0.6236, loss: 0.6236 +2025-06-24 16:50:40,904 - pyskl - INFO - Saving checkpoint at 51 epochs +2025-06-24 16:51:28,663 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:51:28,719 - pyskl - INFO - +top1_acc 0.8322 +top5_acc 0.9865 +2025-06-24 16:51:28,719 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:51:28,727 - pyskl - INFO - +mean_acc 0.7351 +2025-06-24 16:51:28,729 - pyskl - INFO - Epoch(val) [51][533] top1_acc: 0.8322, top5_acc: 0.9865, mean_class_accuracy: 0.7351 +2025-06-24 16:52:50,124 - pyskl - INFO - Epoch [52][100/1281] lr: 1.850e-02, eta: 13:22:30, time: 0.814, data_time: 0.205, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9994, loss_cls: 0.6051, loss: 0.6051 +2025-06-24 16:53:39,613 - pyskl - INFO - Epoch [52][200/1281] lr: 1.849e-02, eta: 13:22:14, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9931, loss_cls: 0.5958, loss: 0.5958 +2025-06-24 16:54:29,197 - pyskl - INFO - Epoch [52][300/1281] lr: 1.847e-02, eta: 13:21:58, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8531, top5_acc: 0.9944, loss_cls: 0.6598, loss: 0.6598 +2025-06-24 16:55:18,557 - pyskl - INFO - Epoch [52][400/1281] lr: 1.845e-02, eta: 13:21:42, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9944, loss_cls: 0.6054, loss: 0.6054 +2025-06-24 16:56:07,638 - pyskl - INFO - Epoch [52][500/1281] lr: 1.843e-02, eta: 13:21:25, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9938, loss_cls: 0.5751, loss: 0.5751 +2025-06-24 16:56:56,743 - pyskl - INFO - Epoch [52][600/1281] lr: 1.841e-02, eta: 13:21:08, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8644, top5_acc: 0.9938, loss_cls: 0.6440, loss: 0.6440 +2025-06-24 16:57:45,729 - pyskl - INFO - Epoch [52][700/1281] lr: 1.840e-02, eta: 13:20:51, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9938, loss_cls: 0.6049, loss: 0.6049 +2025-06-24 16:58:35,099 - pyskl - INFO - Epoch [52][800/1281] lr: 1.838e-02, eta: 13:20:35, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8631, top5_acc: 0.9969, loss_cls: 0.6480, loss: 0.6480 +2025-06-24 16:59:24,468 - pyskl - INFO - Epoch [52][900/1281] lr: 1.836e-02, eta: 13:20:18, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9925, loss_cls: 0.6071, loss: 0.6071 +2025-06-24 17:00:13,506 - pyskl - INFO - Epoch [52][1000/1281] lr: 1.834e-02, eta: 13:20:00, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9906, loss_cls: 0.6308, loss: 0.6308 +2025-06-24 17:01:02,649 - pyskl - INFO - Epoch [52][1100/1281] lr: 1.832e-02, eta: 13:19:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8606, top5_acc: 0.9956, loss_cls: 0.6520, loss: 0.6520 +2025-06-24 17:01:38,592 - pyskl - INFO - Epoch [52][1200/1281] lr: 1.831e-02, eta: 13:19:01, time: 0.359, data_time: 0.000, memory: 4083, top1_acc: 0.8606, top5_acc: 0.9931, loss_cls: 0.6819, loss: 0.6819 +2025-06-24 17:02:25,131 - pyskl - INFO - Saving checkpoint at 52 epochs +2025-06-24 17:03:13,990 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:03:14,046 - pyskl - INFO - +top1_acc 0.8227 +top5_acc 0.9903 +2025-06-24 17:03:14,046 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:03:14,054 - pyskl - INFO - +mean_acc 0.7573 +2025-06-24 17:03:14,056 - pyskl - INFO - Epoch(val) [52][533] top1_acc: 0.8227, top5_acc: 0.9903, mean_class_accuracy: 0.7573 +2025-06-24 17:04:34,073 - pyskl - INFO - Epoch [53][100/1281] lr: 1.827e-02, eta: 13:18:12, time: 0.800, data_time: 0.196, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9944, loss_cls: 0.6065, loss: 0.6065 +2025-06-24 17:05:23,204 - pyskl - INFO - Epoch [53][200/1281] lr: 1.826e-02, eta: 13:17:54, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9956, loss_cls: 0.5762, loss: 0.5762 +2025-06-24 17:06:12,190 - pyskl - INFO - Epoch [53][300/1281] lr: 1.824e-02, eta: 13:17:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8656, top5_acc: 0.9931, loss_cls: 0.6568, loss: 0.6568 +2025-06-24 17:07:01,837 - pyskl - INFO - Epoch [53][400/1281] lr: 1.822e-02, eta: 13:17:20, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9962, loss_cls: 0.5733, loss: 0.5733 +2025-06-24 17:07:50,991 - pyskl - INFO - Epoch [53][500/1281] lr: 1.820e-02, eta: 13:17:02, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9975, loss_cls: 0.6110, loss: 0.6110 +2025-06-24 17:08:39,870 - pyskl - INFO - Epoch [53][600/1281] lr: 1.818e-02, eta: 13:16:43, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9931, loss_cls: 0.6354, loss: 0.6354 +2025-06-24 17:09:29,131 - pyskl - INFO - Epoch [53][700/1281] lr: 1.816e-02, eta: 13:16:25, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8650, top5_acc: 0.9931, loss_cls: 0.6655, loss: 0.6655 +2025-06-24 17:10:18,740 - pyskl - INFO - Epoch [53][800/1281] lr: 1.815e-02, eta: 13:16:08, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9944, loss_cls: 0.6088, loss: 0.6088 +2025-06-24 17:11:08,001 - pyskl - INFO - Epoch [53][900/1281] lr: 1.813e-02, eta: 13:15:50, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9938, loss_cls: 0.6449, loss: 0.6449 +2025-06-24 17:11:57,153 - pyskl - INFO - Epoch [53][1000/1281] lr: 1.811e-02, eta: 13:15:32, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.8688, top5_acc: 0.9944, loss_cls: 0.6200, loss: 0.6200 +2025-06-24 17:12:46,224 - pyskl - INFO - Epoch [53][1100/1281] lr: 1.809e-02, eta: 13:15:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9931, loss_cls: 0.6033, loss: 0.6033 +2025-06-24 17:13:22,360 - pyskl - INFO - Epoch [53][1200/1281] lr: 1.807e-02, eta: 13:14:31, time: 0.361, data_time: 0.000, memory: 4083, top1_acc: 0.8681, top5_acc: 0.9969, loss_cls: 0.6238, loss: 0.6238 +2025-06-24 17:14:07,929 - pyskl - INFO - Saving checkpoint at 53 epochs +2025-06-24 17:14:57,784 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:14:57,851 - pyskl - INFO - +top1_acc 0.8214 +top5_acc 0.9891 +2025-06-24 17:14:57,851 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:14:57,859 - pyskl - INFO - +mean_acc 0.7515 +2025-06-24 17:14:57,861 - pyskl - INFO - Epoch(val) [53][533] top1_acc: 0.8214, top5_acc: 0.9891, mean_class_accuracy: 0.7515 +2025-06-24 17:16:18,542 - pyskl - INFO - Epoch [54][100/1281] lr: 1.804e-02, eta: 13:13:42, time: 0.807, data_time: 0.201, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9938, loss_cls: 0.5883, loss: 0.5883 +2025-06-24 17:17:07,672 - pyskl - INFO - Epoch [54][200/1281] lr: 1.802e-02, eta: 13:13:23, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9988, loss_cls: 0.5468, loss: 0.5468 +2025-06-24 17:17:57,186 - pyskl - INFO - Epoch [54][300/1281] lr: 1.800e-02, eta: 13:13:05, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9938, loss_cls: 0.6077, loss: 0.6077 +2025-06-24 17:18:46,704 - pyskl - INFO - Epoch [54][400/1281] lr: 1.798e-02, eta: 13:12:47, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9969, loss_cls: 0.5664, loss: 0.5664 +2025-06-24 17:19:36,155 - pyskl - INFO - Epoch [54][500/1281] lr: 1.797e-02, eta: 13:12:28, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9956, loss_cls: 0.5685, loss: 0.5685 +2025-06-24 17:20:25,417 - pyskl - INFO - Epoch [54][600/1281] lr: 1.795e-02, eta: 13:12:10, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9956, loss_cls: 0.6138, loss: 0.6138 +2025-06-24 17:21:14,669 - pyskl - INFO - Epoch [54][700/1281] lr: 1.793e-02, eta: 13:11:51, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9956, loss_cls: 0.6006, loss: 0.6006 +2025-06-24 17:22:03,944 - pyskl - INFO - Epoch [54][800/1281] lr: 1.791e-02, eta: 13:11:32, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8581, top5_acc: 0.9962, loss_cls: 0.6652, loss: 0.6652 +2025-06-24 17:22:53,124 - pyskl - INFO - Epoch [54][900/1281] lr: 1.789e-02, eta: 13:11:12, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9938, loss_cls: 0.6470, loss: 0.6470 +2025-06-24 17:23:42,660 - pyskl - INFO - Epoch [54][1000/1281] lr: 1.787e-02, eta: 13:10:54, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8544, top5_acc: 0.9919, loss_cls: 0.7128, loss: 0.7128 +2025-06-24 17:24:32,420 - pyskl - INFO - Epoch [54][1100/1281] lr: 1.786e-02, eta: 13:10:35, time: 0.498, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9931, loss_cls: 0.5706, loss: 0.5706 +2025-06-24 17:25:08,421 - pyskl - INFO - Epoch [54][1200/1281] lr: 1.784e-02, eta: 13:09:52, time: 0.360, data_time: 0.000, memory: 4083, top1_acc: 0.8544, top5_acc: 0.9931, loss_cls: 0.7089, loss: 0.7089 +2025-06-24 17:25:52,704 - pyskl - INFO - Saving checkpoint at 54 epochs +2025-06-24 17:26:41,259 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:26:41,319 - pyskl - INFO - +top1_acc 0.8267 +top5_acc 0.9906 +2025-06-24 17:26:41,320 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:26:41,329 - pyskl - INFO - +mean_acc 0.7765 +2025-06-24 17:26:41,332 - pyskl - INFO - Epoch(val) [54][533] top1_acc: 0.8267, top5_acc: 0.9906, mean_class_accuracy: 0.7765 +2025-06-24 17:28:02,819 - pyskl - INFO - Epoch [55][100/1281] lr: 1.780e-02, eta: 13:09:03, time: 0.815, data_time: 0.203, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9938, loss_cls: 0.5450, loss: 0.5450 +2025-06-24 17:28:51,840 - pyskl - INFO - Epoch [55][200/1281] lr: 1.779e-02, eta: 13:08:43, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9969, loss_cls: 0.5531, loss: 0.5531 +2025-06-24 17:29:40,956 - pyskl - INFO - Epoch [55][300/1281] lr: 1.777e-02, eta: 13:08:24, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9981, loss_cls: 0.5908, loss: 0.5908 +2025-06-24 17:30:30,067 - pyskl - INFO - Epoch [55][400/1281] lr: 1.775e-02, eta: 13:08:04, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8638, top5_acc: 0.9944, loss_cls: 0.6580, loss: 0.6580 +2025-06-24 17:31:19,225 - pyskl - INFO - Epoch [55][500/1281] lr: 1.773e-02, eta: 13:07:44, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8669, top5_acc: 0.9919, loss_cls: 0.6799, loss: 0.6799 +2025-06-24 17:32:08,294 - pyskl - INFO - Epoch [55][600/1281] lr: 1.771e-02, eta: 13:07:23, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9956, loss_cls: 0.5666, loss: 0.5666 +2025-06-24 17:32:57,595 - pyskl - INFO - Epoch [55][700/1281] lr: 1.769e-02, eta: 13:07:03, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9938, loss_cls: 0.6069, loss: 0.6069 +2025-06-24 17:33:46,579 - pyskl - INFO - Epoch [55][800/1281] lr: 1.767e-02, eta: 13:06:43, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9962, loss_cls: 0.6157, loss: 0.6157 +2025-06-24 17:34:35,534 - pyskl - INFO - Epoch [55][900/1281] lr: 1.766e-02, eta: 13:06:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9962, loss_cls: 0.6157, loss: 0.6157 +2025-06-24 17:35:24,562 - pyskl - INFO - Epoch [55][1000/1281] lr: 1.764e-02, eta: 13:06:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9969, loss_cls: 0.5888, loss: 0.5888 +2025-06-24 17:36:13,892 - pyskl - INFO - Epoch [55][1100/1281] lr: 1.762e-02, eta: 13:05:42, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9931, loss_cls: 0.6091, loss: 0.6091 +2025-06-24 17:36:49,706 - pyskl - INFO - Epoch [55][1200/1281] lr: 1.760e-02, eta: 13:04:58, time: 0.358, data_time: 0.000, memory: 4083, top1_acc: 0.8612, top5_acc: 0.9962, loss_cls: 0.6655, loss: 0.6655 +2025-06-24 17:37:33,388 - pyskl - INFO - Saving checkpoint at 55 epochs +2025-06-24 17:38:21,830 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:38:21,891 - pyskl - INFO - +top1_acc 0.8296 +top5_acc 0.9897 +2025-06-24 17:38:21,892 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:38:21,898 - pyskl - INFO - +mean_acc 0.7554 +2025-06-24 17:38:21,900 - pyskl - INFO - Epoch(val) [55][533] top1_acc: 0.8296, top5_acc: 0.9897, mean_class_accuracy: 0.7554 +2025-06-24 17:39:41,829 - pyskl - INFO - Epoch [56][100/1281] lr: 1.757e-02, eta: 13:04:05, time: 0.799, data_time: 0.196, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9950, loss_cls: 0.5213, loss: 0.5213 +2025-06-24 17:40:31,040 - pyskl - INFO - Epoch [56][200/1281] lr: 1.755e-02, eta: 13:03:44, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9950, loss_cls: 0.6027, loss: 0.6027 +2025-06-24 17:41:20,526 - pyskl - INFO - Epoch [56][300/1281] lr: 1.753e-02, eta: 13:03:24, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9969, loss_cls: 0.5317, loss: 0.5317 +2025-06-24 17:42:10,297 - pyskl - INFO - Epoch [56][400/1281] lr: 1.751e-02, eta: 13:03:04, time: 0.498, data_time: 0.000, memory: 4083, top1_acc: 0.8631, top5_acc: 0.9938, loss_cls: 0.6828, loss: 0.6828 +2025-06-24 17:42:59,506 - pyskl - INFO - Epoch [56][500/1281] lr: 1.749e-02, eta: 13:02:43, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9956, loss_cls: 0.5462, loss: 0.5462 +2025-06-24 17:43:48,480 - pyskl - INFO - Epoch [56][600/1281] lr: 1.747e-02, eta: 13:02:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9950, loss_cls: 0.6309, loss: 0.6309 +2025-06-24 17:44:37,576 - pyskl - INFO - Epoch [56][700/1281] lr: 1.745e-02, eta: 13:02:01, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9962, loss_cls: 0.6537, loss: 0.6537 +2025-06-24 17:45:26,590 - pyskl - INFO - Epoch [56][800/1281] lr: 1.743e-02, eta: 13:01:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8631, top5_acc: 0.9919, loss_cls: 0.6904, loss: 0.6904 +2025-06-24 17:46:15,574 - pyskl - INFO - Epoch [56][900/1281] lr: 1.742e-02, eta: 13:01:18, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8669, top5_acc: 0.9912, loss_cls: 0.6637, loss: 0.6637 +2025-06-24 17:47:04,531 - pyskl - INFO - Epoch [56][1000/1281] lr: 1.740e-02, eta: 13:00:56, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9938, loss_cls: 0.6129, loss: 0.6129 +2025-06-24 17:47:53,936 - pyskl - INFO - Epoch [56][1100/1281] lr: 1.738e-02, eta: 13:00:35, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8669, top5_acc: 0.9975, loss_cls: 0.6240, loss: 0.6240 +2025-06-24 17:48:31,190 - pyskl - INFO - Epoch [56][1200/1281] lr: 1.736e-02, eta: 12:59:54, time: 0.373, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9956, loss_cls: 0.6343, loss: 0.6343 +2025-06-24 17:49:14,416 - pyskl - INFO - Saving checkpoint at 56 epochs +2025-06-24 17:50:02,569 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:50:02,626 - pyskl - INFO - +top1_acc 0.8361 +top5_acc 0.9889 +2025-06-24 17:50:02,627 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:50:02,635 - pyskl - INFO - +mean_acc 0.7687 +2025-06-24 17:50:02,637 - pyskl - INFO - Epoch(val) [56][533] top1_acc: 0.8361, top5_acc: 0.9889, mean_class_accuracy: 0.7687 +2025-06-24 17:51:23,747 - pyskl - INFO - Epoch [57][100/1281] lr: 1.733e-02, eta: 12:59:02, time: 0.811, data_time: 0.195, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9944, loss_cls: 0.5954, loss: 0.5954 +2025-06-24 17:52:13,312 - pyskl - INFO - Epoch [57][200/1281] lr: 1.731e-02, eta: 12:58:41, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9975, loss_cls: 0.5530, loss: 0.5530 +2025-06-24 17:53:02,686 - pyskl - INFO - Epoch [57][300/1281] lr: 1.729e-02, eta: 12:58:19, time: 0.494, data_time: 0.001, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9969, loss_cls: 0.5378, loss: 0.5378 +2025-06-24 17:53:51,953 - pyskl - INFO - Epoch [57][400/1281] lr: 1.727e-02, eta: 12:57:58, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9981, loss_cls: 0.5262, loss: 0.5262 +2025-06-24 17:54:41,136 - pyskl - INFO - Epoch [57][500/1281] lr: 1.725e-02, eta: 12:57:36, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9950, loss_cls: 0.5553, loss: 0.5553 +2025-06-24 17:55:30,169 - pyskl - INFO - Epoch [57][600/1281] lr: 1.723e-02, eta: 12:57:14, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8738, top5_acc: 0.9956, loss_cls: 0.6057, loss: 0.6057 +2025-06-24 17:56:19,516 - pyskl - INFO - Epoch [57][700/1281] lr: 1.721e-02, eta: 12:56:52, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9950, loss_cls: 0.5704, loss: 0.5704 +2025-06-24 17:57:08,367 - pyskl - INFO - Epoch [57][800/1281] lr: 1.719e-02, eta: 12:56:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9906, loss_cls: 0.6162, loss: 0.6162 +2025-06-24 17:57:57,509 - pyskl - INFO - Epoch [57][900/1281] lr: 1.717e-02, eta: 12:56:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9938, loss_cls: 0.5819, loss: 0.5819 +2025-06-24 17:58:46,912 - pyskl - INFO - Epoch [57][1000/1281] lr: 1.716e-02, eta: 12:55:46, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9931, loss_cls: 0.6332, loss: 0.6332 +2025-06-24 17:59:36,006 - pyskl - INFO - Epoch [57][1100/1281] lr: 1.714e-02, eta: 12:55:23, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9962, loss_cls: 0.5986, loss: 0.5986 +2025-06-24 18:00:11,897 - pyskl - INFO - Epoch [57][1200/1281] lr: 1.712e-02, eta: 12:54:39, time: 0.359, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9956, loss_cls: 0.5951, loss: 0.5951 +2025-06-24 18:00:55,868 - pyskl - INFO - Saving checkpoint at 57 epochs +2025-06-24 18:01:44,397 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:01:44,453 - pyskl - INFO - +top1_acc 0.8180 +top5_acc 0.9870 +2025-06-24 18:01:44,453 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:01:44,459 - pyskl - INFO - +mean_acc 0.7677 +2025-06-24 18:01:44,461 - pyskl - INFO - Epoch(val) [57][533] top1_acc: 0.8180, top5_acc: 0.9870, mean_class_accuracy: 0.7677 +2025-06-24 18:03:06,224 - pyskl - INFO - Epoch [58][100/1281] lr: 1.708e-02, eta: 12:53:47, time: 0.818, data_time: 0.202, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9975, loss_cls: 0.6774, loss: 0.6774 +2025-06-24 18:03:55,368 - pyskl - INFO - Epoch [58][200/1281] lr: 1.706e-02, eta: 12:53:24, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9962, loss_cls: 0.6227, loss: 0.6227 +2025-06-24 18:04:44,753 - pyskl - INFO - Epoch [58][300/1281] lr: 1.704e-02, eta: 12:53:02, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9994, loss_cls: 0.5037, loss: 0.5037 +2025-06-24 18:05:34,120 - pyskl - INFO - Epoch [58][400/1281] lr: 1.703e-02, eta: 12:52:40, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9969, loss_cls: 0.5911, loss: 0.5911 +2025-06-24 18:06:23,282 - pyskl - INFO - Epoch [58][500/1281] lr: 1.701e-02, eta: 12:52:17, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9969, loss_cls: 0.5946, loss: 0.5946 +2025-06-24 18:07:12,592 - pyskl - INFO - Epoch [58][600/1281] lr: 1.699e-02, eta: 12:51:54, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9962, loss_cls: 0.5553, loss: 0.5553 +2025-06-24 18:08:01,694 - pyskl - INFO - Epoch [58][700/1281] lr: 1.697e-02, eta: 12:51:31, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9988, loss_cls: 0.6125, loss: 0.6125 +2025-06-24 18:08:50,919 - pyskl - INFO - Epoch [58][800/1281] lr: 1.695e-02, eta: 12:51:09, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9944, loss_cls: 0.5833, loss: 0.5833 +2025-06-24 18:09:40,340 - pyskl - INFO - Epoch [58][900/1281] lr: 1.693e-02, eta: 12:50:46, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9944, loss_cls: 0.6236, loss: 0.6236 +2025-06-24 18:10:29,219 - pyskl - INFO - Epoch [58][1000/1281] lr: 1.691e-02, eta: 12:50:22, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9956, loss_cls: 0.5924, loss: 0.5924 +2025-06-24 18:11:18,523 - pyskl - INFO - Epoch [58][1100/1281] lr: 1.689e-02, eta: 12:49:59, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9988, loss_cls: 0.5419, loss: 0.5419 +2025-06-24 18:11:53,203 - pyskl - INFO - Epoch [58][1200/1281] lr: 1.687e-02, eta: 12:49:13, time: 0.347, data_time: 0.000, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9919, loss_cls: 0.6293, loss: 0.6293 +2025-06-24 18:12:40,950 - pyskl - INFO - Saving checkpoint at 58 epochs +2025-06-24 18:13:30,052 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:13:30,108 - pyskl - INFO - +top1_acc 0.8343 +top5_acc 0.9898 +2025-06-24 18:13:30,108 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:13:30,115 - pyskl - INFO - +mean_acc 0.7626 +2025-06-24 18:13:30,117 - pyskl - INFO - Epoch(val) [58][533] top1_acc: 0.8343, top5_acc: 0.9898, mean_class_accuracy: 0.7626 +2025-06-24 18:14:50,860 - pyskl - INFO - Epoch [59][100/1281] lr: 1.684e-02, eta: 12:48:18, time: 0.807, data_time: 0.196, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9962, loss_cls: 0.5781, loss: 0.5781 +2025-06-24 18:15:39,949 - pyskl - INFO - Epoch [59][200/1281] lr: 1.682e-02, eta: 12:47:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9969, loss_cls: 0.5244, loss: 0.5244 +2025-06-24 18:16:28,852 - pyskl - INFO - Epoch [59][300/1281] lr: 1.680e-02, eta: 12:47:31, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9981, loss_cls: 0.6318, loss: 0.6318 +2025-06-24 18:17:18,104 - pyskl - INFO - Epoch [59][400/1281] lr: 1.678e-02, eta: 12:47:08, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9962, loss_cls: 0.5290, loss: 0.5290 +2025-06-24 18:18:07,097 - pyskl - INFO - Epoch [59][500/1281] lr: 1.676e-02, eta: 12:46:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9931, loss_cls: 0.5951, loss: 0.5951 +2025-06-24 18:18:56,085 - pyskl - INFO - Epoch [59][600/1281] lr: 1.674e-02, eta: 12:46:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9956, loss_cls: 0.5750, loss: 0.5750 +2025-06-24 18:19:45,020 - pyskl - INFO - Epoch [59][700/1281] lr: 1.672e-02, eta: 12:45:56, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9956, loss_cls: 0.6068, loss: 0.6068 +2025-06-24 18:20:33,922 - pyskl - INFO - Epoch [59][800/1281] lr: 1.670e-02, eta: 12:45:32, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8794, top5_acc: 0.9962, loss_cls: 0.5954, loss: 0.5954 +2025-06-24 18:21:23,236 - pyskl - INFO - Epoch [59][900/1281] lr: 1.668e-02, eta: 12:45:08, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9944, loss_cls: 0.5911, loss: 0.5911 +2025-06-24 18:22:12,555 - pyskl - INFO - Epoch [59][1000/1281] lr: 1.667e-02, eta: 12:44:44, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9944, loss_cls: 0.6093, loss: 0.6093 +2025-06-24 18:23:01,603 - pyskl - INFO - Epoch [59][1100/1281] lr: 1.665e-02, eta: 12:44:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9950, loss_cls: 0.5846, loss: 0.5846 +2025-06-24 18:23:37,473 - pyskl - INFO - Epoch [59][1200/1281] lr: 1.663e-02, eta: 12:43:36, time: 0.359, data_time: 0.000, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9944, loss_cls: 0.6420, loss: 0.6420 +2025-06-24 18:24:21,397 - pyskl - INFO - Saving checkpoint at 59 epochs +2025-06-24 18:25:09,926 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:25:09,982 - pyskl - INFO - +top1_acc 0.8263 +top5_acc 0.9897 +2025-06-24 18:25:09,983 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:25:09,990 - pyskl - INFO - +mean_acc 0.7699 +2025-06-24 18:25:09,992 - pyskl - INFO - Epoch(val) [59][533] top1_acc: 0.8263, top5_acc: 0.9897, mean_class_accuracy: 0.7699 +2025-06-24 18:26:30,606 - pyskl - INFO - Epoch [60][100/1281] lr: 1.659e-02, eta: 12:42:39, time: 0.806, data_time: 0.197, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9994, loss_cls: 0.5283, loss: 0.5283 +2025-06-24 18:27:19,455 - pyskl - INFO - Epoch [60][200/1281] lr: 1.657e-02, eta: 12:42:15, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9988, loss_cls: 0.5211, loss: 0.5211 +2025-06-24 18:28:08,837 - pyskl - INFO - Epoch [60][300/1281] lr: 1.655e-02, eta: 12:41:51, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9950, loss_cls: 0.5913, loss: 0.5913 +2025-06-24 18:28:58,081 - pyskl - INFO - Epoch [60][400/1281] lr: 1.653e-02, eta: 12:41:27, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9962, loss_cls: 0.5390, loss: 0.5390 +2025-06-24 18:29:47,474 - pyskl - INFO - Epoch [60][500/1281] lr: 1.651e-02, eta: 12:41:03, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9981, loss_cls: 0.5924, loss: 0.5924 +2025-06-24 18:30:36,183 - pyskl - INFO - Epoch [60][600/1281] lr: 1.650e-02, eta: 12:40:38, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9962, loss_cls: 0.5736, loss: 0.5736 +2025-06-24 18:31:25,312 - pyskl - INFO - Epoch [60][700/1281] lr: 1.648e-02, eta: 12:40:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9931, loss_cls: 0.5982, loss: 0.5982 +2025-06-24 18:32:14,812 - pyskl - INFO - Epoch [60][800/1281] lr: 1.646e-02, eta: 12:39:49, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9988, loss_cls: 0.5541, loss: 0.5541 +2025-06-24 18:33:04,056 - pyskl - INFO - Epoch [60][900/1281] lr: 1.644e-02, eta: 12:39:25, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9950, loss_cls: 0.6152, loss: 0.6152 +2025-06-24 18:33:53,238 - pyskl - INFO - Epoch [60][1000/1281] lr: 1.642e-02, eta: 12:39:00, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9962, loss_cls: 0.5229, loss: 0.5229 +2025-06-24 18:34:42,242 - pyskl - INFO - Epoch [60][1100/1281] lr: 1.640e-02, eta: 12:38:35, time: 0.490, data_time: 0.001, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9975, loss_cls: 0.5535, loss: 0.5535 +2025-06-24 18:35:18,850 - pyskl - INFO - Epoch [60][1200/1281] lr: 1.638e-02, eta: 12:37:51, time: 0.366, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9944, loss_cls: 0.6303, loss: 0.6303 +2025-06-24 18:36:02,234 - pyskl - INFO - Saving checkpoint at 60 epochs +2025-06-24 18:36:50,194 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:36:50,250 - pyskl - INFO - +top1_acc 0.8476 +top5_acc 0.9906 +2025-06-24 18:36:50,250 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:36:50,257 - pyskl - INFO - +mean_acc 0.7846 +2025-06-24 18:36:50,261 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_48.pth was removed +2025-06-24 18:36:50,451 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_60.pth. +2025-06-24 18:36:50,452 - pyskl - INFO - Best top1_acc is 0.8476 at 60 epoch. +2025-06-24 18:36:50,455 - pyskl - INFO - Epoch(val) [60][533] top1_acc: 0.8476, top5_acc: 0.9906, mean_class_accuracy: 0.7846 +2025-06-24 18:38:11,513 - pyskl - INFO - Epoch [61][100/1281] lr: 1.634e-02, eta: 12:36:55, time: 0.811, data_time: 0.192, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9969, loss_cls: 0.5264, loss: 0.5264 +2025-06-24 18:39:00,712 - pyskl - INFO - Epoch [61][200/1281] lr: 1.632e-02, eta: 12:36:30, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9988, loss_cls: 0.4968, loss: 0.4968 +2025-06-24 18:39:49,811 - pyskl - INFO - Epoch [61][300/1281] lr: 1.630e-02, eta: 12:36:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9969, loss_cls: 0.5356, loss: 0.5356 +2025-06-24 18:40:38,964 - pyskl - INFO - Epoch [61][400/1281] lr: 1.629e-02, eta: 12:35:40, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9956, loss_cls: 0.5405, loss: 0.5405 +2025-06-24 18:41:28,049 - pyskl - INFO - Epoch [61][500/1281] lr: 1.627e-02, eta: 12:35:15, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9994, loss_cls: 0.4919, loss: 0.4919 +2025-06-24 18:42:16,923 - pyskl - INFO - Epoch [61][600/1281] lr: 1.625e-02, eta: 12:34:49, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9975, loss_cls: 0.6100, loss: 0.6100 +2025-06-24 18:43:06,025 - pyskl - INFO - Epoch [61][700/1281] lr: 1.623e-02, eta: 12:34:24, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9956, loss_cls: 0.5495, loss: 0.5495 +2025-06-24 18:43:55,381 - pyskl - INFO - Epoch [61][800/1281] lr: 1.621e-02, eta: 12:33:59, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9956, loss_cls: 0.5580, loss: 0.5580 +2025-06-24 18:44:44,725 - pyskl - INFO - Epoch [61][900/1281] lr: 1.619e-02, eta: 12:33:34, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9956, loss_cls: 0.6288, loss: 0.6288 +2025-06-24 18:45:33,896 - pyskl - INFO - Epoch [61][1000/1281] lr: 1.617e-02, eta: 12:33:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8712, top5_acc: 0.9925, loss_cls: 0.6156, loss: 0.6156 +2025-06-24 18:46:23,063 - pyskl - INFO - Epoch [61][1100/1281] lr: 1.615e-02, eta: 12:32:43, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8638, top5_acc: 0.9969, loss_cls: 0.6203, loss: 0.6203 +2025-06-24 18:46:59,676 - pyskl - INFO - Epoch [61][1200/1281] lr: 1.613e-02, eta: 12:31:59, time: 0.366, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9944, loss_cls: 0.5686, loss: 0.5686 +2025-06-24 18:47:45,605 - pyskl - INFO - Saving checkpoint at 61 epochs +2025-06-24 18:48:34,526 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:48:34,582 - pyskl - INFO - +top1_acc 0.8407 +top5_acc 0.9910 +2025-06-24 18:48:34,582 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:48:34,589 - pyskl - INFO - +mean_acc 0.7958 +2025-06-24 18:48:34,591 - pyskl - INFO - Epoch(val) [61][533] top1_acc: 0.8407, top5_acc: 0.9910, mean_class_accuracy: 0.7958 +2025-06-24 18:49:54,679 - pyskl - INFO - Epoch [62][100/1281] lr: 1.609e-02, eta: 12:31:00, time: 0.801, data_time: 0.196, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9969, loss_cls: 0.5072, loss: 0.5072 +2025-06-24 18:50:43,734 - pyskl - INFO - Epoch [62][200/1281] lr: 1.607e-02, eta: 12:30:34, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9981, loss_cls: 0.5200, loss: 0.5200 +2025-06-24 18:51:32,546 - pyskl - INFO - Epoch [62][300/1281] lr: 1.605e-02, eta: 12:30:08, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9988, loss_cls: 0.4724, loss: 0.4724 +2025-06-24 18:52:21,604 - pyskl - INFO - Epoch [62][400/1281] lr: 1.603e-02, eta: 12:29:42, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9981, loss_cls: 0.5167, loss: 0.5167 +2025-06-24 18:53:10,650 - pyskl - INFO - Epoch [62][500/1281] lr: 1.602e-02, eta: 12:29:16, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9988, loss_cls: 0.5141, loss: 0.5141 +2025-06-24 18:53:59,815 - pyskl - INFO - Epoch [62][600/1281] lr: 1.600e-02, eta: 12:28:50, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9975, loss_cls: 0.5275, loss: 0.5275 +2025-06-24 18:54:49,009 - pyskl - INFO - Epoch [62][700/1281] lr: 1.598e-02, eta: 12:28:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9962, loss_cls: 0.5344, loss: 0.5344 +2025-06-24 18:55:38,236 - pyskl - INFO - Epoch [62][800/1281] lr: 1.596e-02, eta: 12:27:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9975, loss_cls: 0.5650, loss: 0.5650 +2025-06-24 18:56:27,543 - pyskl - INFO - Epoch [62][900/1281] lr: 1.594e-02, eta: 12:27:33, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9950, loss_cls: 0.6005, loss: 0.6005 +2025-06-24 18:57:16,589 - pyskl - INFO - Epoch [62][1000/1281] lr: 1.592e-02, eta: 12:27:06, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9956, loss_cls: 0.5445, loss: 0.5445 +2025-06-24 18:58:06,009 - pyskl - INFO - Epoch [62][1100/1281] lr: 1.590e-02, eta: 12:26:41, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9969, loss_cls: 0.5987, loss: 0.5987 +2025-06-24 18:58:41,863 - pyskl - INFO - Epoch [62][1200/1281] lr: 1.588e-02, eta: 12:25:56, time: 0.359, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9969, loss_cls: 0.5396, loss: 0.5396 +2025-06-24 18:59:27,352 - pyskl - INFO - Saving checkpoint at 62 epochs +2025-06-24 19:00:16,342 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:00:16,397 - pyskl - INFO - +top1_acc 0.8511 +top5_acc 0.9901 +2025-06-24 19:00:16,397 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:00:16,404 - pyskl - INFO - +mean_acc 0.7790 +2025-06-24 19:00:16,408 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_60.pth was removed +2025-06-24 19:00:16,752 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_62.pth. +2025-06-24 19:00:16,753 - pyskl - INFO - Best top1_acc is 0.8511 at 62 epoch. +2025-06-24 19:00:16,756 - pyskl - INFO - Epoch(val) [62][533] top1_acc: 0.8511, top5_acc: 0.9901, mean_class_accuracy: 0.7790 +2025-06-24 19:01:36,441 - pyskl - INFO - Epoch [63][100/1281] lr: 1.584e-02, eta: 12:24:55, time: 0.797, data_time: 0.195, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9962, loss_cls: 0.5245, loss: 0.5245 +2025-06-24 19:02:25,585 - pyskl - INFO - Epoch [63][200/1281] lr: 1.582e-02, eta: 12:24:29, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9969, loss_cls: 0.5144, loss: 0.5144 +2025-06-24 19:03:14,838 - pyskl - INFO - Epoch [63][300/1281] lr: 1.580e-02, eta: 12:24:02, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9956, loss_cls: 0.5250, loss: 0.5250 +2025-06-24 19:04:04,300 - pyskl - INFO - Epoch [63][400/1281] lr: 1.578e-02, eta: 12:23:36, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9962, loss_cls: 0.5340, loss: 0.5340 +2025-06-24 19:04:53,633 - pyskl - INFO - Epoch [63][500/1281] lr: 1.576e-02, eta: 12:23:10, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9969, loss_cls: 0.5072, loss: 0.5072 +2025-06-24 19:05:42,686 - pyskl - INFO - Epoch [63][600/1281] lr: 1.574e-02, eta: 12:22:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9988, loss_cls: 0.4943, loss: 0.4943 +2025-06-24 19:06:32,001 - pyskl - INFO - Epoch [63][700/1281] lr: 1.572e-02, eta: 12:22:17, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9969, loss_cls: 0.5078, loss: 0.5078 +2025-06-24 19:07:20,982 - pyskl - INFO - Epoch [63][800/1281] lr: 1.570e-02, eta: 12:21:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9969, loss_cls: 0.5496, loss: 0.5496 +2025-06-24 19:08:10,258 - pyskl - INFO - Epoch [63][900/1281] lr: 1.568e-02, eta: 12:21:24, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9956, loss_cls: 0.5873, loss: 0.5873 +2025-06-24 19:08:59,248 - pyskl - INFO - Epoch [63][1000/1281] lr: 1.566e-02, eta: 12:20:57, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9962, loss_cls: 0.5263, loss: 0.5263 +2025-06-24 19:09:48,699 - pyskl - INFO - Epoch [63][1100/1281] lr: 1.564e-02, eta: 12:20:30, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9969, loss_cls: 0.5491, loss: 0.5491 +2025-06-24 19:10:25,879 - pyskl - INFO - Epoch [63][1200/1281] lr: 1.562e-02, eta: 12:19:47, time: 0.372, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9956, loss_cls: 0.6082, loss: 0.6082 +2025-06-24 19:11:08,965 - pyskl - INFO - Saving checkpoint at 63 epochs +2025-06-24 19:11:57,002 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:11:57,058 - pyskl - INFO - +top1_acc 0.8379 +top5_acc 0.9885 +2025-06-24 19:11:57,059 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:11:57,065 - pyskl - INFO - +mean_acc 0.7617 +2025-06-24 19:11:57,066 - pyskl - INFO - Epoch(val) [63][533] top1_acc: 0.8379, top5_acc: 0.9885, mean_class_accuracy: 0.7617 +2025-06-24 19:13:18,654 - pyskl - INFO - Epoch [64][100/1281] lr: 1.559e-02, eta: 12:18:48, time: 0.816, data_time: 0.195, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9975, loss_cls: 0.5251, loss: 0.5251 +2025-06-24 19:14:07,529 - pyskl - INFO - Epoch [64][200/1281] lr: 1.557e-02, eta: 12:18:21, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9981, loss_cls: 0.4776, loss: 0.4776 +2025-06-24 19:14:56,991 - pyskl - INFO - Epoch [64][300/1281] lr: 1.555e-02, eta: 12:17:54, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9956, loss_cls: 0.5469, loss: 0.5469 +2025-06-24 19:15:46,511 - pyskl - INFO - Epoch [64][400/1281] lr: 1.553e-02, eta: 12:17:27, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9975, loss_cls: 0.5398, loss: 0.5398 +2025-06-24 19:16:35,845 - pyskl - INFO - Epoch [64][500/1281] lr: 1.551e-02, eta: 12:17:01, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9950, loss_cls: 0.6028, loss: 0.6028 +2025-06-24 19:17:24,989 - pyskl - INFO - Epoch [64][600/1281] lr: 1.549e-02, eta: 12:16:33, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9969, loss_cls: 0.5375, loss: 0.5375 +2025-06-24 19:18:14,126 - pyskl - INFO - Epoch [64][700/1281] lr: 1.547e-02, eta: 12:16:06, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9906, loss_cls: 0.5492, loss: 0.5492 +2025-06-24 19:19:03,008 - pyskl - INFO - Epoch [64][800/1281] lr: 1.545e-02, eta: 12:15:38, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9962, loss_cls: 0.5673, loss: 0.5673 +2025-06-24 19:19:52,154 - pyskl - INFO - Epoch [64][900/1281] lr: 1.543e-02, eta: 12:15:11, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9931, loss_cls: 0.5564, loss: 0.5564 +2025-06-24 19:20:41,439 - pyskl - INFO - Epoch [64][1000/1281] lr: 1.541e-02, eta: 12:14:44, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9944, loss_cls: 0.5700, loss: 0.5700 +2025-06-24 19:21:30,677 - pyskl - INFO - Epoch [64][1100/1281] lr: 1.539e-02, eta: 12:14:17, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9962, loss_cls: 0.5732, loss: 0.5732 +2025-06-24 19:22:06,482 - pyskl - INFO - Epoch [64][1200/1281] lr: 1.537e-02, eta: 12:13:31, time: 0.358, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9956, loss_cls: 0.5579, loss: 0.5579 +2025-06-24 19:22:51,940 - pyskl - INFO - Saving checkpoint at 64 epochs +2025-06-24 19:23:40,723 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:23:40,781 - pyskl - INFO - +top1_acc 0.8438 +top5_acc 0.9903 +2025-06-24 19:23:40,781 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:23:40,789 - pyskl - INFO - +mean_acc 0.7733 +2025-06-24 19:23:40,791 - pyskl - INFO - Epoch(val) [64][533] top1_acc: 0.8438, top5_acc: 0.9903, mean_class_accuracy: 0.7733 +2025-06-24 19:25:01,947 - pyskl - INFO - Epoch [65][100/1281] lr: 1.533e-02, eta: 12:12:31, time: 0.812, data_time: 0.192, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9944, loss_cls: 0.4966, loss: 0.4966 +2025-06-24 19:25:51,394 - pyskl - INFO - Epoch [65][200/1281] lr: 1.531e-02, eta: 12:12:04, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9969, loss_cls: 0.4731, loss: 0.4731 +2025-06-24 19:26:40,713 - pyskl - INFO - Epoch [65][300/1281] lr: 1.529e-02, eta: 12:11:36, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9969, loss_cls: 0.5803, loss: 0.5803 +2025-06-24 19:27:30,066 - pyskl - INFO - Epoch [65][400/1281] lr: 1.527e-02, eta: 12:11:09, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9994, loss_cls: 0.4917, loss: 0.4917 +2025-06-24 19:28:18,805 - pyskl - INFO - Epoch [65][500/1281] lr: 1.526e-02, eta: 12:10:40, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9975, loss_cls: 0.5362, loss: 0.5362 +2025-06-24 19:29:08,155 - pyskl - INFO - Epoch [65][600/1281] lr: 1.524e-02, eta: 12:10:13, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9969, loss_cls: 0.5608, loss: 0.5608 +2025-06-24 19:29:57,703 - pyskl - INFO - Epoch [65][700/1281] lr: 1.522e-02, eta: 12:09:46, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9969, loss_cls: 0.5047, loss: 0.5047 +2025-06-24 19:30:47,004 - pyskl - INFO - Epoch [65][800/1281] lr: 1.520e-02, eta: 12:09:18, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9975, loss_cls: 0.4973, loss: 0.4973 +2025-06-24 19:31:36,216 - pyskl - INFO - Epoch [65][900/1281] lr: 1.518e-02, eta: 12:08:50, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9956, loss_cls: 0.5313, loss: 0.5313 +2025-06-24 19:32:25,329 - pyskl - INFO - Epoch [65][1000/1281] lr: 1.516e-02, eta: 12:08:22, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9950, loss_cls: 0.6109, loss: 0.6109 +2025-06-24 19:33:14,675 - pyskl - INFO - Epoch [65][1100/1281] lr: 1.514e-02, eta: 12:07:54, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9962, loss_cls: 0.4905, loss: 0.4905 +2025-06-24 19:33:50,984 - pyskl - INFO - Epoch [65][1200/1281] lr: 1.512e-02, eta: 12:07:09, time: 0.363, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9962, loss_cls: 0.5387, loss: 0.5387 +2025-06-24 19:34:35,906 - pyskl - INFO - Saving checkpoint at 65 epochs +2025-06-24 19:35:24,720 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:35:24,776 - pyskl - INFO - +top1_acc 0.8384 +top5_acc 0.9873 +2025-06-24 19:35:24,777 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:35:24,784 - pyskl - INFO - +mean_acc 0.7852 +2025-06-24 19:35:24,786 - pyskl - INFO - Epoch(val) [65][533] top1_acc: 0.8384, top5_acc: 0.9873, mean_class_accuracy: 0.7852 +2025-06-24 19:36:43,209 - pyskl - INFO - Epoch [66][100/1281] lr: 1.508e-02, eta: 12:06:04, time: 0.784, data_time: 0.192, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9969, loss_cls: 0.5048, loss: 0.5048 +2025-06-24 19:37:32,622 - pyskl - INFO - Epoch [66][200/1281] lr: 1.506e-02, eta: 12:05:37, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9988, loss_cls: 0.4132, loss: 0.4132 +2025-06-24 19:38:21,802 - pyskl - INFO - Epoch [66][300/1281] lr: 1.504e-02, eta: 12:05:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9962, loss_cls: 0.5466, loss: 0.5466 +2025-06-24 19:39:10,702 - pyskl - INFO - Epoch [66][400/1281] lr: 1.502e-02, eta: 12:04:40, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9975, loss_cls: 0.4961, loss: 0.4961 +2025-06-24 19:39:59,788 - pyskl - INFO - Epoch [66][500/1281] lr: 1.500e-02, eta: 12:04:11, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9962, loss_cls: 0.4503, loss: 0.4503 +2025-06-24 19:40:48,832 - pyskl - INFO - Epoch [66][600/1281] lr: 1.498e-02, eta: 12:03:43, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9950, loss_cls: 0.5542, loss: 0.5542 +2025-06-24 19:41:38,450 - pyskl - INFO - Epoch [66][700/1281] lr: 1.496e-02, eta: 12:03:15, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.8875, top5_acc: 0.9962, loss_cls: 0.5421, loss: 0.5421 +2025-06-24 19:42:27,599 - pyskl - INFO - Epoch [66][800/1281] lr: 1.494e-02, eta: 12:02:46, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9981, loss_cls: 0.5340, loss: 0.5340 +2025-06-24 19:43:16,657 - pyskl - INFO - Epoch [66][900/1281] lr: 1.492e-02, eta: 12:02:18, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9962, loss_cls: 0.5373, loss: 0.5373 +2025-06-24 19:44:06,142 - pyskl - INFO - Epoch [66][1000/1281] lr: 1.490e-02, eta: 12:01:50, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9975, loss_cls: 0.4507, loss: 0.4507 +2025-06-24 19:44:55,122 - pyskl - INFO - Epoch [66][1100/1281] lr: 1.488e-02, eta: 12:01:21, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9950, loss_cls: 0.5307, loss: 0.5307 +2025-06-24 19:45:33,134 - pyskl - INFO - Epoch [66][1200/1281] lr: 1.486e-02, eta: 12:00:38, time: 0.380, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9975, loss_cls: 0.5318, loss: 0.5318 +2025-06-24 19:46:12,395 - pyskl - INFO - Saving checkpoint at 66 epochs +2025-06-24 19:46:59,531 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:46:59,588 - pyskl - INFO - +top1_acc 0.8483 +top5_acc 0.9912 +2025-06-24 19:46:59,588 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:46:59,596 - pyskl - INFO - +mean_acc 0.7952 +2025-06-24 19:46:59,599 - pyskl - INFO - Epoch(val) [66][533] top1_acc: 0.8483, top5_acc: 0.9912, mean_class_accuracy: 0.7952 +2025-06-24 19:48:20,177 - pyskl - INFO - Epoch [67][100/1281] lr: 1.482e-02, eta: 11:59:35, time: 0.806, data_time: 0.190, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9969, loss_cls: 0.5038, loss: 0.5038 +2025-06-24 19:49:09,297 - pyskl - INFO - Epoch [67][200/1281] lr: 1.480e-02, eta: 11:59:06, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9975, loss_cls: 0.5139, loss: 0.5139 +2025-06-24 19:49:58,330 - pyskl - INFO - Epoch [67][300/1281] lr: 1.478e-02, eta: 11:58:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9981, loss_cls: 0.4975, loss: 0.4975 +2025-06-24 19:50:47,581 - pyskl - INFO - Epoch [67][400/1281] lr: 1.476e-02, eta: 11:58:09, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9956, loss_cls: 0.4915, loss: 0.4915 +2025-06-24 19:51:36,431 - pyskl - INFO - Epoch [67][500/1281] lr: 1.474e-02, eta: 11:57:39, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9969, loss_cls: 0.4918, loss: 0.4918 +2025-06-24 19:52:25,139 - pyskl - INFO - Epoch [67][600/1281] lr: 1.472e-02, eta: 11:57:10, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9981, loss_cls: 0.5423, loss: 0.5423 +2025-06-24 19:53:14,342 - pyskl - INFO - Epoch [67][700/1281] lr: 1.470e-02, eta: 11:56:41, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9962, loss_cls: 0.5448, loss: 0.5448 +2025-06-24 19:54:03,229 - pyskl - INFO - Epoch [67][800/1281] lr: 1.468e-02, eta: 11:56:12, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9956, loss_cls: 0.5161, loss: 0.5161 +2025-06-24 19:54:52,497 - pyskl - INFO - Epoch [67][900/1281] lr: 1.466e-02, eta: 11:55:43, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9938, loss_cls: 0.5272, loss: 0.5272 +2025-06-24 19:55:41,770 - pyskl - INFO - Epoch [67][1000/1281] lr: 1.464e-02, eta: 11:55:14, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9956, loss_cls: 0.5263, loss: 0.5263 +2025-06-24 19:56:31,269 - pyskl - INFO - Epoch [67][1100/1281] lr: 1.462e-02, eta: 11:54:45, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9962, loss_cls: 0.5116, loss: 0.5116 +2025-06-24 19:57:08,276 - pyskl - INFO - Epoch [67][1200/1281] lr: 1.460e-02, eta: 11:54:01, time: 0.370, data_time: 0.001, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9962, loss_cls: 0.5137, loss: 0.5137 +2025-06-24 19:57:50,973 - pyskl - INFO - Saving checkpoint at 67 epochs +2025-06-24 19:58:39,128 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:58:39,183 - pyskl - INFO - +top1_acc 0.8319 +top5_acc 0.9894 +2025-06-24 19:58:39,183 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:58:39,189 - pyskl - INFO - +mean_acc 0.7587 +2025-06-24 19:58:39,191 - pyskl - INFO - Epoch(val) [67][533] top1_acc: 0.8319, top5_acc: 0.9894, mean_class_accuracy: 0.7587 +2025-06-24 19:59:58,846 - pyskl - INFO - Epoch [68][100/1281] lr: 1.456e-02, eta: 11:52:56, time: 0.797, data_time: 0.197, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9975, loss_cls: 0.4780, loss: 0.4780 +2025-06-24 20:00:48,353 - pyskl - INFO - Epoch [68][200/1281] lr: 1.454e-02, eta: 11:52:27, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9944, loss_cls: 0.4949, loss: 0.4949 +2025-06-24 20:01:37,420 - pyskl - INFO - Epoch [68][300/1281] lr: 1.452e-02, eta: 11:51:58, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9988, loss_cls: 0.5107, loss: 0.5107 +2025-06-24 20:02:26,513 - pyskl - INFO - Epoch [68][400/1281] lr: 1.450e-02, eta: 11:51:28, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9962, loss_cls: 0.4719, loss: 0.4719 +2025-06-24 20:03:15,648 - pyskl - INFO - Epoch [68][500/1281] lr: 1.448e-02, eta: 11:50:59, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9962, loss_cls: 0.4849, loss: 0.4849 +2025-06-24 20:04:04,795 - pyskl - INFO - Epoch [68][600/1281] lr: 1.446e-02, eta: 11:50:29, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9994, loss_cls: 0.4545, loss: 0.4545 +2025-06-24 20:04:53,914 - pyskl - INFO - Epoch [68][700/1281] lr: 1.444e-02, eta: 11:50:00, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9962, loss_cls: 0.5120, loss: 0.5120 +2025-06-24 20:05:42,975 - pyskl - INFO - Epoch [68][800/1281] lr: 1.442e-02, eta: 11:49:30, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9956, loss_cls: 0.5082, loss: 0.5082 +2025-06-24 20:06:32,129 - pyskl - INFO - Epoch [68][900/1281] lr: 1.440e-02, eta: 11:49:00, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9962, loss_cls: 0.5214, loss: 0.5214 +2025-06-24 20:07:21,014 - pyskl - INFO - Epoch [68][1000/1281] lr: 1.438e-02, eta: 11:48:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9969, loss_cls: 0.4568, loss: 0.4568 +2025-06-24 20:08:10,280 - pyskl - INFO - Epoch [68][1100/1281] lr: 1.436e-02, eta: 11:48:01, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9981, loss_cls: 0.5022, loss: 0.5022 +2025-06-24 20:08:47,011 - pyskl - INFO - Epoch [68][1200/1281] lr: 1.434e-02, eta: 11:47:16, time: 0.367, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9975, loss_cls: 0.5093, loss: 0.5093 +2025-06-24 20:09:28,456 - pyskl - INFO - Saving checkpoint at 68 epochs +2025-06-24 20:10:16,437 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:10:16,494 - pyskl - INFO - +top1_acc 0.8373 +top5_acc 0.9832 +2025-06-24 20:10:16,494 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:10:16,501 - pyskl - INFO - +mean_acc 0.7831 +2025-06-24 20:10:16,504 - pyskl - INFO - Epoch(val) [68][533] top1_acc: 0.8373, top5_acc: 0.9832, mean_class_accuracy: 0.7831 +2025-06-24 20:11:35,146 - pyskl - INFO - Epoch [69][100/1281] lr: 1.431e-02, eta: 11:46:10, time: 0.786, data_time: 0.196, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9981, loss_cls: 0.4821, loss: 0.4821 +2025-06-24 20:12:24,333 - pyskl - INFO - Epoch [69][200/1281] lr: 1.429e-02, eta: 11:45:40, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9969, loss_cls: 0.4719, loss: 0.4719 +2025-06-24 20:13:13,756 - pyskl - INFO - Epoch [69][300/1281] lr: 1.427e-02, eta: 11:45:10, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9975, loss_cls: 0.4891, loss: 0.4891 +2025-06-24 20:14:02,544 - pyskl - INFO - Epoch [69][400/1281] lr: 1.425e-02, eta: 11:44:40, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9944, loss_cls: 0.5741, loss: 0.5741 +2025-06-24 20:14:51,636 - pyskl - INFO - Epoch [69][500/1281] lr: 1.423e-02, eta: 11:44:10, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9975, loss_cls: 0.5145, loss: 0.5145 +2025-06-24 20:15:40,599 - pyskl - INFO - Epoch [69][600/1281] lr: 1.420e-02, eta: 11:43:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9994, loss_cls: 0.5096, loss: 0.5096 +2025-06-24 20:16:29,763 - pyskl - INFO - Epoch [69][700/1281] lr: 1.418e-02, eta: 11:43:10, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9975, loss_cls: 0.5109, loss: 0.5109 +2025-06-24 20:17:19,019 - pyskl - INFO - Epoch [69][800/1281] lr: 1.416e-02, eta: 11:42:40, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9975, loss_cls: 0.5442, loss: 0.5442 +2025-06-24 20:18:08,194 - pyskl - INFO - Epoch [69][900/1281] lr: 1.414e-02, eta: 11:42:09, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9950, loss_cls: 0.5841, loss: 0.5841 +2025-06-24 20:18:57,312 - pyskl - INFO - Epoch [69][1000/1281] lr: 1.412e-02, eta: 11:41:39, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9981, loss_cls: 0.4739, loss: 0.4739 +2025-06-24 20:19:46,192 - pyskl - INFO - Epoch [69][1100/1281] lr: 1.410e-02, eta: 11:41:09, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9988, loss_cls: 0.4570, loss: 0.4570 +2025-06-24 20:20:24,782 - pyskl - INFO - Epoch [69][1200/1281] lr: 1.408e-02, eta: 11:40:26, time: 0.386, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9994, loss_cls: 0.4401, loss: 0.4401 +2025-06-24 20:21:03,568 - pyskl - INFO - Saving checkpoint at 69 epochs +2025-06-24 20:21:50,990 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:21:51,047 - pyskl - INFO - +top1_acc 0.8443 +top5_acc 0.9900 +2025-06-24 20:21:51,047 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:21:51,055 - pyskl - INFO - +mean_acc 0.7936 +2025-06-24 20:21:51,057 - pyskl - INFO - Epoch(val) [69][533] top1_acc: 0.8443, top5_acc: 0.9900, mean_class_accuracy: 0.7936 +2025-06-24 20:23:10,546 - pyskl - INFO - Epoch [70][100/1281] lr: 1.405e-02, eta: 11:39:20, time: 0.795, data_time: 0.193, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9962, loss_cls: 0.4357, loss: 0.4357 +2025-06-24 20:23:59,871 - pyskl - INFO - Epoch [70][200/1281] lr: 1.403e-02, eta: 11:38:50, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9988, loss_cls: 0.4665, loss: 0.4665 +2025-06-24 20:24:48,864 - pyskl - INFO - Epoch [70][300/1281] lr: 1.401e-02, eta: 11:38:19, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9988, loss_cls: 0.4503, loss: 0.4503 +2025-06-24 20:25:38,068 - pyskl - INFO - Epoch [70][400/1281] lr: 1.399e-02, eta: 11:37:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 1.0000, loss_cls: 0.4003, loss: 0.4003 +2025-06-24 20:26:27,441 - pyskl - INFO - Epoch [70][500/1281] lr: 1.397e-02, eta: 11:37:19, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9975, loss_cls: 0.4512, loss: 0.4512 +2025-06-24 20:27:16,638 - pyskl - INFO - Epoch [70][600/1281] lr: 1.395e-02, eta: 11:36:48, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9975, loss_cls: 0.4423, loss: 0.4423 +2025-06-24 20:28:05,814 - pyskl - INFO - Epoch [70][700/1281] lr: 1.392e-02, eta: 11:36:18, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9975, loss_cls: 0.4861, loss: 0.4861 +2025-06-24 20:28:55,174 - pyskl - INFO - Epoch [70][800/1281] lr: 1.390e-02, eta: 11:35:47, time: 0.494, data_time: 0.001, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9975, loss_cls: 0.4604, loss: 0.4604 +2025-06-24 20:29:44,517 - pyskl - INFO - Epoch [70][900/1281] lr: 1.388e-02, eta: 11:35:17, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9950, loss_cls: 0.4698, loss: 0.4698 +2025-06-24 20:30:33,623 - pyskl - INFO - Epoch [70][1000/1281] lr: 1.386e-02, eta: 11:34:46, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9969, loss_cls: 0.5603, loss: 0.5603 +2025-06-24 20:31:22,767 - pyskl - INFO - Epoch [70][1100/1281] lr: 1.384e-02, eta: 11:34:16, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9956, loss_cls: 0.5138, loss: 0.5138 +2025-06-24 20:31:59,819 - pyskl - INFO - Epoch [70][1200/1281] lr: 1.382e-02, eta: 11:33:31, time: 0.371, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9975, loss_cls: 0.4962, loss: 0.4962 +2025-06-24 20:32:41,076 - pyskl - INFO - Saving checkpoint at 70 epochs +2025-06-24 20:33:28,901 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:33:28,979 - pyskl - INFO - +top1_acc 0.8412 +top5_acc 0.9898 +2025-06-24 20:33:28,980 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:33:28,990 - pyskl - INFO - +mean_acc 0.7806 +2025-06-24 20:33:28,993 - pyskl - INFO - Epoch(val) [70][533] top1_acc: 0.8412, top5_acc: 0.9898, mean_class_accuracy: 0.7806 +2025-06-24 20:34:50,352 - pyskl - INFO - Epoch [71][100/1281] lr: 1.379e-02, eta: 11:32:27, time: 0.814, data_time: 0.195, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9981, loss_cls: 0.4572, loss: 0.4572 +2025-06-24 20:35:39,616 - pyskl - INFO - Epoch [71][200/1281] lr: 1.377e-02, eta: 11:31:56, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9994, loss_cls: 0.4293, loss: 0.4293 +2025-06-24 20:36:28,678 - pyskl - INFO - Epoch [71][300/1281] lr: 1.375e-02, eta: 11:31:25, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9969, loss_cls: 0.4964, loss: 0.4964 +2025-06-24 20:37:17,854 - pyskl - INFO - Epoch [71][400/1281] lr: 1.373e-02, eta: 11:30:54, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9969, loss_cls: 0.4564, loss: 0.4564 +2025-06-24 20:38:07,025 - pyskl - INFO - Epoch [71][500/1281] lr: 1.371e-02, eta: 11:30:23, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9981, loss_cls: 0.4550, loss: 0.4550 +2025-06-24 20:38:56,434 - pyskl - INFO - Epoch [71][600/1281] lr: 1.368e-02, eta: 11:29:52, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9988, loss_cls: 0.4900, loss: 0.4900 +2025-06-24 20:39:45,812 - pyskl - INFO - Epoch [71][700/1281] lr: 1.366e-02, eta: 11:29:22, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9969, loss_cls: 0.4539, loss: 0.4539 +2025-06-24 20:40:35,035 - pyskl - INFO - Epoch [71][800/1281] lr: 1.364e-02, eta: 11:28:51, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9988, loss_cls: 0.4760, loss: 0.4760 +2025-06-24 20:41:24,213 - pyskl - INFO - Epoch [71][900/1281] lr: 1.362e-02, eta: 11:28:19, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9950, loss_cls: 0.4645, loss: 0.4645 +2025-06-24 20:42:13,504 - pyskl - INFO - Epoch [71][1000/1281] lr: 1.360e-02, eta: 11:27:49, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9950, loss_cls: 0.4755, loss: 0.4755 +2025-06-24 20:43:02,953 - pyskl - INFO - Epoch [71][1100/1281] lr: 1.358e-02, eta: 11:27:18, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9988, loss_cls: 0.4656, loss: 0.4656 +2025-06-24 20:43:38,387 - pyskl - INFO - Epoch [71][1200/1281] lr: 1.356e-02, eta: 11:26:31, time: 0.354, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9975, loss_cls: 0.5064, loss: 0.5064 +2025-06-24 20:44:23,280 - pyskl - INFO - Saving checkpoint at 71 epochs +2025-06-24 20:45:11,416 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:45:11,471 - pyskl - INFO - +top1_acc 0.7773 +top5_acc 0.9788 +2025-06-24 20:45:11,471 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:45:11,479 - pyskl - INFO - +mean_acc 0.6912 +2025-06-24 20:45:11,481 - pyskl - INFO - Epoch(val) [71][533] top1_acc: 0.7773, top5_acc: 0.9788, mean_class_accuracy: 0.6912 +2025-06-24 20:46:30,952 - pyskl - INFO - Epoch [72][100/1281] lr: 1.353e-02, eta: 11:25:24, time: 0.795, data_time: 0.191, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9994, loss_cls: 0.4655, loss: 0.4655 +2025-06-24 20:47:20,021 - pyskl - INFO - Epoch [72][200/1281] lr: 1.351e-02, eta: 11:24:53, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9988, loss_cls: 0.4482, loss: 0.4482 +2025-06-24 20:48:08,967 - pyskl - INFO - Epoch [72][300/1281] lr: 1.349e-02, eta: 11:24:21, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9988, loss_cls: 0.4337, loss: 0.4337 +2025-06-24 20:48:57,747 - pyskl - INFO - Epoch [72][400/1281] lr: 1.346e-02, eta: 11:23:49, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9988, loss_cls: 0.4969, loss: 0.4969 +2025-06-24 20:49:46,942 - pyskl - INFO - Epoch [72][500/1281] lr: 1.344e-02, eta: 11:23:18, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9975, loss_cls: 0.4499, loss: 0.4499 +2025-06-24 20:50:36,109 - pyskl - INFO - Epoch [72][600/1281] lr: 1.342e-02, eta: 11:22:47, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9969, loss_cls: 0.5038, loss: 0.5038 +2025-06-24 20:51:25,000 - pyskl - INFO - Epoch [72][700/1281] lr: 1.340e-02, eta: 11:22:15, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9975, loss_cls: 0.4578, loss: 0.4578 +2025-06-24 20:52:13,781 - pyskl - INFO - Epoch [72][800/1281] lr: 1.338e-02, eta: 11:21:43, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9975, loss_cls: 0.4804, loss: 0.4804 +2025-06-24 20:53:02,794 - pyskl - INFO - Epoch [72][900/1281] lr: 1.336e-02, eta: 11:21:11, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9975, loss_cls: 0.5061, loss: 0.5061 +2025-06-24 20:53:51,831 - pyskl - INFO - Epoch [72][1000/1281] lr: 1.334e-02, eta: 11:20:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9969, loss_cls: 0.5463, loss: 0.5463 +2025-06-24 20:54:40,733 - pyskl - INFO - Epoch [72][1100/1281] lr: 1.332e-02, eta: 11:20:07, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9988, loss_cls: 0.4337, loss: 0.4337 +2025-06-24 20:55:18,255 - pyskl - INFO - Epoch [72][1200/1281] lr: 1.330e-02, eta: 11:19:23, time: 0.375, data_time: 0.001, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9956, loss_cls: 0.5117, loss: 0.5117 +2025-06-24 20:56:00,815 - pyskl - INFO - Saving checkpoint at 72 epochs +2025-06-24 20:56:48,921 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:56:48,977 - pyskl - INFO - +top1_acc 0.8494 +top5_acc 0.9911 +2025-06-24 20:56:48,978 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:56:48,984 - pyskl - INFO - +mean_acc 0.7925 +2025-06-24 20:56:48,986 - pyskl - INFO - Epoch(val) [72][533] top1_acc: 0.8494, top5_acc: 0.9911, mean_class_accuracy: 0.7925 +2025-06-24 20:58:08,847 - pyskl - INFO - Epoch [73][100/1281] lr: 1.326e-02, eta: 11:18:16, time: 0.799, data_time: 0.192, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9981, loss_cls: 0.4738, loss: 0.4738 +2025-06-24 20:58:58,101 - pyskl - INFO - Epoch [73][200/1281] lr: 1.324e-02, eta: 11:17:44, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9975, loss_cls: 0.4204, loss: 0.4204 +2025-06-24 20:59:47,324 - pyskl - INFO - Epoch [73][300/1281] lr: 1.322e-02, eta: 11:17:13, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9969, loss_cls: 0.4562, loss: 0.4562 +2025-06-24 21:00:36,085 - pyskl - INFO - Epoch [73][400/1281] lr: 1.320e-02, eta: 11:16:40, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9994, loss_cls: 0.3999, loss: 0.3999 +2025-06-24 21:01:25,604 - pyskl - INFO - Epoch [73][500/1281] lr: 1.318e-02, eta: 11:16:09, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9981, loss_cls: 0.4001, loss: 0.4001 +2025-06-24 21:02:14,739 - pyskl - INFO - Epoch [73][600/1281] lr: 1.316e-02, eta: 11:15:37, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9969, loss_cls: 0.4507, loss: 0.4507 +2025-06-24 21:03:04,098 - pyskl - INFO - Epoch [73][700/1281] lr: 1.314e-02, eta: 11:15:05, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9994, loss_cls: 0.4990, loss: 0.4990 +2025-06-24 21:03:53,383 - pyskl - INFO - Epoch [73][800/1281] lr: 1.312e-02, eta: 11:14:34, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9981, loss_cls: 0.4437, loss: 0.4437 +2025-06-24 21:04:42,624 - pyskl - INFO - Epoch [73][900/1281] lr: 1.310e-02, eta: 11:14:02, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9962, loss_cls: 0.4919, loss: 0.4919 +2025-06-24 21:05:31,983 - pyskl - INFO - Epoch [73][1000/1281] lr: 1.308e-02, eta: 11:13:30, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9956, loss_cls: 0.5050, loss: 0.5050 +2025-06-24 21:06:21,501 - pyskl - INFO - Epoch [73][1100/1281] lr: 1.306e-02, eta: 11:12:58, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9994, loss_cls: 0.4321, loss: 0.4321 +2025-06-24 21:06:58,535 - pyskl - INFO - Epoch [73][1200/1281] lr: 1.304e-02, eta: 11:12:13, time: 0.370, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9975, loss_cls: 0.4919, loss: 0.4919 +2025-06-24 21:07:41,090 - pyskl - INFO - Saving checkpoint at 73 epochs +2025-06-24 21:08:28,998 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:08:29,055 - pyskl - INFO - +top1_acc 0.8574 +top5_acc 0.9917 +2025-06-24 21:08:29,056 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:08:29,075 - pyskl - INFO - +mean_acc 0.8026 +2025-06-24 21:08:29,080 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_62.pth was removed +2025-06-24 21:08:29,278 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_73.pth. +2025-06-24 21:08:29,278 - pyskl - INFO - Best top1_acc is 0.8574 at 73 epoch. +2025-06-24 21:08:29,281 - pyskl - INFO - Epoch(val) [73][533] top1_acc: 0.8574, top5_acc: 0.9917, mean_class_accuracy: 0.8026 +2025-06-24 21:09:50,136 - pyskl - INFO - Epoch [74][100/1281] lr: 1.300e-02, eta: 11:11:07, time: 0.808, data_time: 0.196, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9994, loss_cls: 0.4191, loss: 0.4191 +2025-06-24 21:10:39,024 - pyskl - INFO - Epoch [74][200/1281] lr: 1.298e-02, eta: 11:10:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9975, loss_cls: 0.3763, loss: 0.3763 +2025-06-24 21:11:28,074 - pyskl - INFO - Epoch [74][300/1281] lr: 1.296e-02, eta: 11:10:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9994, loss_cls: 0.3860, loss: 0.3860 +2025-06-24 21:12:17,303 - pyskl - INFO - Epoch [74][400/1281] lr: 1.294e-02, eta: 11:09:30, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9969, loss_cls: 0.3968, loss: 0.3968 +2025-06-24 21:13:06,185 - pyskl - INFO - Epoch [74][500/1281] lr: 1.292e-02, eta: 11:08:57, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9962, loss_cls: 0.4516, loss: 0.4516 +2025-06-24 21:13:55,503 - pyskl - INFO - Epoch [74][600/1281] lr: 1.290e-02, eta: 11:08:25, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9975, loss_cls: 0.4480, loss: 0.4480 +2025-06-24 21:14:44,582 - pyskl - INFO - Epoch [74][700/1281] lr: 1.288e-02, eta: 11:07:53, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9981, loss_cls: 0.4831, loss: 0.4831 +2025-06-24 21:15:33,976 - pyskl - INFO - Epoch [74][800/1281] lr: 1.286e-02, eta: 11:07:20, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9956, loss_cls: 0.4401, loss: 0.4401 +2025-06-24 21:16:23,706 - pyskl - INFO - Epoch [74][900/1281] lr: 1.284e-02, eta: 11:06:49, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9994, loss_cls: 0.4214, loss: 0.4214 +2025-06-24 21:17:12,815 - pyskl - INFO - Epoch [74][1000/1281] lr: 1.282e-02, eta: 11:06:16, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9988, loss_cls: 0.4114, loss: 0.4114 +2025-06-24 21:18:02,142 - pyskl - INFO - Epoch [74][1100/1281] lr: 1.280e-02, eta: 11:05:44, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9994, loss_cls: 0.4698, loss: 0.4698 +2025-06-24 21:18:38,073 - pyskl - INFO - Epoch [74][1200/1281] lr: 1.278e-02, eta: 11:04:58, time: 0.359, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9988, loss_cls: 0.4415, loss: 0.4415 +2025-06-24 21:19:21,489 - pyskl - INFO - Saving checkpoint at 74 epochs +2025-06-24 21:20:09,385 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:20:09,442 - pyskl - INFO - +top1_acc 0.8459 +top5_acc 0.9932 +2025-06-24 21:20:09,442 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:20:09,449 - pyskl - INFO - +mean_acc 0.7929 +2025-06-24 21:20:09,451 - pyskl - INFO - Epoch(val) [74][533] top1_acc: 0.8459, top5_acc: 0.9932, mean_class_accuracy: 0.7929 +2025-06-24 21:21:29,814 - pyskl - INFO - Epoch [75][100/1281] lr: 1.274e-02, eta: 11:03:50, time: 0.804, data_time: 0.195, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9969, loss_cls: 0.4236, loss: 0.4236 +2025-06-24 21:22:19,409 - pyskl - INFO - Epoch [75][200/1281] lr: 1.272e-02, eta: 11:03:18, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9988, loss_cls: 0.3588, loss: 0.3588 +2025-06-24 21:23:08,623 - pyskl - INFO - Epoch [75][300/1281] lr: 1.270e-02, eta: 11:02:45, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9975, loss_cls: 0.3939, loss: 0.3939 +2025-06-24 21:23:57,832 - pyskl - INFO - Epoch [75][400/1281] lr: 1.268e-02, eta: 11:02:13, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 1.0000, loss_cls: 0.4001, loss: 0.4001 +2025-06-24 21:24:46,846 - pyskl - INFO - Epoch [75][500/1281] lr: 1.266e-02, eta: 11:01:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9988, loss_cls: 0.4298, loss: 0.4298 +2025-06-24 21:25:35,865 - pyskl - INFO - Epoch [75][600/1281] lr: 1.264e-02, eta: 11:01:07, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9988, loss_cls: 0.4931, loss: 0.4931 +2025-06-24 21:26:24,712 - pyskl - INFO - Epoch [75][700/1281] lr: 1.262e-02, eta: 11:00:34, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9988, loss_cls: 0.5116, loss: 0.5116 +2025-06-24 21:27:13,762 - pyskl - INFO - Epoch [75][800/1281] lr: 1.260e-02, eta: 11:00:01, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9944, loss_cls: 0.5269, loss: 0.5269 +2025-06-24 21:28:03,125 - pyskl - INFO - Epoch [75][900/1281] lr: 1.258e-02, eta: 10:59:29, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9969, loss_cls: 0.4539, loss: 0.4539 +2025-06-24 21:28:52,705 - pyskl - INFO - Epoch [75][1000/1281] lr: 1.256e-02, eta: 10:58:56, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9988, loss_cls: 0.4640, loss: 0.4640 +2025-06-24 21:29:41,642 - pyskl - INFO - Epoch [75][1100/1281] lr: 1.254e-02, eta: 10:58:23, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9988, loss_cls: 0.4232, loss: 0.4232 +2025-06-24 21:30:18,522 - pyskl - INFO - Epoch [75][1200/1281] lr: 1.252e-02, eta: 10:57:38, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9994, loss_cls: 0.4308, loss: 0.4308 +2025-06-24 21:31:00,330 - pyskl - INFO - Saving checkpoint at 75 epochs +2025-06-24 21:31:48,017 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:31:48,073 - pyskl - INFO - +top1_acc 0.8434 +top5_acc 0.9891 +2025-06-24 21:31:48,073 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:31:48,079 - pyskl - INFO - +mean_acc 0.7881 +2025-06-24 21:31:48,081 - pyskl - INFO - Epoch(val) [75][533] top1_acc: 0.8434, top5_acc: 0.9891, mean_class_accuracy: 0.7881 +2025-06-24 21:33:08,716 - pyskl - INFO - Epoch [76][100/1281] lr: 1.248e-02, eta: 10:56:30, time: 0.806, data_time: 0.193, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9994, loss_cls: 0.4478, loss: 0.4478 +2025-06-24 21:33:57,780 - pyskl - INFO - Epoch [76][200/1281] lr: 1.246e-02, eta: 10:55:57, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9994, loss_cls: 0.3677, loss: 0.3677 +2025-06-24 21:34:46,642 - pyskl - INFO - Epoch [76][300/1281] lr: 1.244e-02, eta: 10:55:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9981, loss_cls: 0.4273, loss: 0.4273 +2025-06-24 21:35:35,620 - pyskl - INFO - Epoch [76][400/1281] lr: 1.242e-02, eta: 10:54:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9969, loss_cls: 0.4393, loss: 0.4393 +2025-06-24 21:36:24,676 - pyskl - INFO - Epoch [76][500/1281] lr: 1.240e-02, eta: 10:54:17, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9981, loss_cls: 0.4173, loss: 0.4173 +2025-06-24 21:37:13,678 - pyskl - INFO - Epoch [76][600/1281] lr: 1.238e-02, eta: 10:53:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9994, loss_cls: 0.4213, loss: 0.4213 +2025-06-24 21:38:02,532 - pyskl - INFO - Epoch [76][700/1281] lr: 1.236e-02, eta: 10:53:11, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9981, loss_cls: 0.3736, loss: 0.3736 +2025-06-24 21:38:51,751 - pyskl - INFO - Epoch [76][800/1281] lr: 1.234e-02, eta: 10:52:37, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9988, loss_cls: 0.4513, loss: 0.4513 +2025-06-24 21:39:40,881 - pyskl - INFO - Epoch [76][900/1281] lr: 1.232e-02, eta: 10:52:04, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9975, loss_cls: 0.4535, loss: 0.4535 +2025-06-24 21:40:29,959 - pyskl - INFO - Epoch [76][1000/1281] lr: 1.230e-02, eta: 10:51:31, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9988, loss_cls: 0.4464, loss: 0.4464 +2025-06-24 21:41:19,116 - pyskl - INFO - Epoch [76][1100/1281] lr: 1.228e-02, eta: 10:50:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9975, loss_cls: 0.4978, loss: 0.4978 +2025-06-24 21:41:55,067 - pyskl - INFO - Epoch [76][1200/1281] lr: 1.225e-02, eta: 10:50:11, time: 0.360, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9981, loss_cls: 0.4579, loss: 0.4579 +2025-06-24 21:42:38,119 - pyskl - INFO - Saving checkpoint at 76 epochs +2025-06-24 21:43:26,018 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:43:26,076 - pyskl - INFO - +top1_acc 0.8694 +top5_acc 0.9903 +2025-06-24 21:43:26,076 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:43:26,085 - pyskl - INFO - +mean_acc 0.8137 +2025-06-24 21:43:26,090 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_73.pth was removed +2025-06-24 21:43:26,272 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_76.pth. +2025-06-24 21:43:26,272 - pyskl - INFO - Best top1_acc is 0.8694 at 76 epoch. +2025-06-24 21:43:26,274 - pyskl - INFO - Epoch(val) [76][533] top1_acc: 0.8694, top5_acc: 0.9903, mean_class_accuracy: 0.8137 +2025-06-24 21:44:46,688 - pyskl - INFO - Epoch [77][100/1281] lr: 1.222e-02, eta: 10:49:03, time: 0.804, data_time: 0.192, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 0.3501, loss: 0.3501 +2025-06-24 21:45:35,764 - pyskl - INFO - Epoch [77][200/1281] lr: 1.220e-02, eta: 10:48:29, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9988, loss_cls: 0.3090, loss: 0.3090 +2025-06-24 21:46:24,901 - pyskl - INFO - Epoch [77][300/1281] lr: 1.218e-02, eta: 10:47:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9975, loss_cls: 0.4426, loss: 0.4426 +2025-06-24 21:47:13,903 - pyskl - INFO - Epoch [77][400/1281] lr: 1.216e-02, eta: 10:47:23, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9988, loss_cls: 0.3972, loss: 0.3972 +2025-06-24 21:48:03,142 - pyskl - INFO - Epoch [77][500/1281] lr: 1.214e-02, eta: 10:46:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9994, loss_cls: 0.3701, loss: 0.3701 +2025-06-24 21:48:52,261 - pyskl - INFO - Epoch [77][600/1281] lr: 1.212e-02, eta: 10:46:16, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9956, loss_cls: 0.4662, loss: 0.4662 +2025-06-24 21:49:41,768 - pyskl - INFO - Epoch [77][700/1281] lr: 1.210e-02, eta: 10:45:42, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9956, loss_cls: 0.4487, loss: 0.4487 +2025-06-24 21:50:30,739 - pyskl - INFO - Epoch [77][800/1281] lr: 1.207e-02, eta: 10:45:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9981, loss_cls: 0.4417, loss: 0.4417 +2025-06-24 21:51:20,117 - pyskl - INFO - Epoch [77][900/1281] lr: 1.205e-02, eta: 10:44:35, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9962, loss_cls: 0.4665, loss: 0.4665 +2025-06-24 21:52:09,312 - pyskl - INFO - Epoch [77][1000/1281] lr: 1.203e-02, eta: 10:44:02, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9975, loss_cls: 0.5143, loss: 0.5143 +2025-06-24 21:52:58,485 - pyskl - INFO - Epoch [77][1100/1281] lr: 1.201e-02, eta: 10:43:28, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9975, loss_cls: 0.4350, loss: 0.4350 +2025-06-24 21:53:35,123 - pyskl - INFO - Epoch [77][1200/1281] lr: 1.199e-02, eta: 10:42:43, time: 0.366, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9988, loss_cls: 0.3916, loss: 0.3916 +2025-06-24 21:54:17,525 - pyskl - INFO - Saving checkpoint at 77 epochs +2025-06-24 21:55:05,264 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:55:05,334 - pyskl - INFO - +top1_acc 0.8747 +top5_acc 0.9928 +2025-06-24 21:55:05,334 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:55:05,342 - pyskl - INFO - +mean_acc 0.8302 +2025-06-24 21:55:05,346 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_76.pth was removed +2025-06-24 21:55:05,534 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_77.pth. +2025-06-24 21:55:05,535 - pyskl - INFO - Best top1_acc is 0.8747 at 77 epoch. +2025-06-24 21:55:05,537 - pyskl - INFO - Epoch(val) [77][533] top1_acc: 0.8747, top5_acc: 0.9928, mean_class_accuracy: 0.8302 +2025-06-24 21:56:25,601 - pyskl - INFO - Epoch [78][100/1281] lr: 1.196e-02, eta: 10:41:33, time: 0.801, data_time: 0.195, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3598, loss: 0.3598 +2025-06-24 21:57:14,918 - pyskl - INFO - Epoch [78][200/1281] lr: 1.194e-02, eta: 10:41:00, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 0.3374, loss: 0.3374 +2025-06-24 21:58:03,913 - pyskl - INFO - Epoch [78][300/1281] lr: 1.192e-02, eta: 10:40:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9988, loss_cls: 0.3209, loss: 0.3209 +2025-06-24 21:58:52,959 - pyskl - INFO - Epoch [78][400/1281] lr: 1.190e-02, eta: 10:39:52, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9981, loss_cls: 0.4088, loss: 0.4088 +2025-06-24 21:59:42,444 - pyskl - INFO - Epoch [78][500/1281] lr: 1.187e-02, eta: 10:39:19, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9975, loss_cls: 0.4040, loss: 0.4040 +2025-06-24 22:00:31,525 - pyskl - INFO - Epoch [78][600/1281] lr: 1.185e-02, eta: 10:38:45, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9975, loss_cls: 0.4330, loss: 0.4330 +2025-06-24 22:01:20,527 - pyskl - INFO - Epoch [78][700/1281] lr: 1.183e-02, eta: 10:38:11, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9981, loss_cls: 0.4123, loss: 0.4123 +2025-06-24 22:02:10,119 - pyskl - INFO - Epoch [78][800/1281] lr: 1.181e-02, eta: 10:37:37, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9988, loss_cls: 0.4141, loss: 0.4141 +2025-06-24 22:02:59,334 - pyskl - INFO - Epoch [78][900/1281] lr: 1.179e-02, eta: 10:37:03, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9956, loss_cls: 0.4642, loss: 0.4642 +2025-06-24 22:03:48,484 - pyskl - INFO - Epoch [78][1000/1281] lr: 1.177e-02, eta: 10:36:29, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9956, loss_cls: 0.4433, loss: 0.4433 +2025-06-24 22:04:37,498 - pyskl - INFO - Epoch [78][1100/1281] lr: 1.175e-02, eta: 10:35:55, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9994, loss_cls: 0.4219, loss: 0.4219 +2025-06-24 22:05:13,800 - pyskl - INFO - Epoch [78][1200/1281] lr: 1.173e-02, eta: 10:35:09, time: 0.363, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9981, loss_cls: 0.4178, loss: 0.4178 +2025-06-24 22:05:57,812 - pyskl - INFO - Saving checkpoint at 78 epochs +2025-06-24 22:06:45,949 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:06:46,011 - pyskl - INFO - +top1_acc 0.8619 +top5_acc 0.9928 +2025-06-24 22:06:46,011 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:06:46,019 - pyskl - INFO - +mean_acc 0.8152 +2025-06-24 22:06:46,021 - pyskl - INFO - Epoch(val) [78][533] top1_acc: 0.8619, top5_acc: 0.9928, mean_class_accuracy: 0.8152 +2025-06-24 22:08:06,241 - pyskl - INFO - Epoch [79][100/1281] lr: 1.169e-02, eta: 10:34:00, time: 0.802, data_time: 0.196, memory: 4083, top1_acc: 0.9294, top5_acc: 1.0000, loss_cls: 0.3551, loss: 0.3551 +2025-06-24 22:08:55,373 - pyskl - INFO - Epoch [79][200/1281] lr: 1.167e-02, eta: 10:33:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3460, loss: 0.3460 +2025-06-24 22:09:44,479 - pyskl - INFO - Epoch [79][300/1281] lr: 1.165e-02, eta: 10:32:51, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9975, loss_cls: 0.3965, loss: 0.3965 +2025-06-24 22:10:33,529 - pyskl - INFO - Epoch [79][400/1281] lr: 1.163e-02, eta: 10:32:17, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9969, loss_cls: 0.4292, loss: 0.4292 +2025-06-24 22:11:22,755 - pyskl - INFO - Epoch [79][500/1281] lr: 1.161e-02, eta: 10:31:43, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9975, loss_cls: 0.4316, loss: 0.4316 +2025-06-24 22:12:12,200 - pyskl - INFO - Epoch [79][600/1281] lr: 1.159e-02, eta: 10:31:09, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 1.0000, loss_cls: 0.3715, loss: 0.3715 +2025-06-24 22:13:01,553 - pyskl - INFO - Epoch [79][700/1281] lr: 1.157e-02, eta: 10:30:35, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 1.0000, loss_cls: 0.4275, loss: 0.4275 +2025-06-24 22:13:50,683 - pyskl - INFO - Epoch [79][800/1281] lr: 1.155e-02, eta: 10:30:01, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9956, loss_cls: 0.3742, loss: 0.3742 +2025-06-24 22:14:39,926 - pyskl - INFO - Epoch [79][900/1281] lr: 1.153e-02, eta: 10:29:27, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9994, loss_cls: 0.4251, loss: 0.4251 +2025-06-24 22:15:29,008 - pyskl - INFO - Epoch [79][1000/1281] lr: 1.151e-02, eta: 10:28:52, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9975, loss_cls: 0.4651, loss: 0.4651 +2025-06-24 22:16:18,587 - pyskl - INFO - Epoch [79][1100/1281] lr: 1.149e-02, eta: 10:28:18, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9994, loss_cls: 0.4745, loss: 0.4745 +2025-06-24 22:16:55,144 - pyskl - INFO - Epoch [79][1200/1281] lr: 1.147e-02, eta: 10:27:33, time: 0.366, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9988, loss_cls: 0.4672, loss: 0.4672 +2025-06-24 22:17:40,291 - pyskl - INFO - Saving checkpoint at 79 epochs +2025-06-24 22:18:28,669 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:18:28,737 - pyskl - INFO - +top1_acc 0.8464 +top5_acc 0.9899 +2025-06-24 22:18:28,737 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:18:28,745 - pyskl - INFO - +mean_acc 0.7915 +2025-06-24 22:18:28,747 - pyskl - INFO - Epoch(val) [79][533] top1_acc: 0.8464, top5_acc: 0.9899, mean_class_accuracy: 0.7915 +2025-06-24 22:19:48,985 - pyskl - INFO - Epoch [80][100/1281] lr: 1.143e-02, eta: 10:26:23, time: 0.802, data_time: 0.195, memory: 4083, top1_acc: 0.9406, top5_acc: 1.0000, loss_cls: 0.3391, loss: 0.3391 +2025-06-24 22:20:38,409 - pyskl - INFO - Epoch [80][200/1281] lr: 1.141e-02, eta: 10:25:49, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 1.0000, loss_cls: 0.3624, loss: 0.3624 +2025-06-24 22:21:27,446 - pyskl - INFO - Epoch [80][300/1281] lr: 1.139e-02, eta: 10:25:14, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9994, loss_cls: 0.3738, loss: 0.3738 +2025-06-24 22:22:16,783 - pyskl - INFO - Epoch [80][400/1281] lr: 1.137e-02, eta: 10:24:40, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9988, loss_cls: 0.3829, loss: 0.3829 +2025-06-24 22:23:05,668 - pyskl - INFO - Epoch [80][500/1281] lr: 1.135e-02, eta: 10:24:05, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 0.3268, loss: 0.3268 +2025-06-24 22:23:54,939 - pyskl - INFO - Epoch [80][600/1281] lr: 1.133e-02, eta: 10:23:31, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 1.0000, loss_cls: 0.3993, loss: 0.3993 +2025-06-24 22:24:43,894 - pyskl - INFO - Epoch [80][700/1281] lr: 1.131e-02, eta: 10:22:56, time: 0.490, data_time: 0.001, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9962, loss_cls: 0.4629, loss: 0.4629 +2025-06-24 22:25:33,218 - pyskl - INFO - Epoch [80][800/1281] lr: 1.129e-02, eta: 10:22:21, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9975, loss_cls: 0.4531, loss: 0.4531 +2025-06-24 22:26:22,254 - pyskl - INFO - Epoch [80][900/1281] lr: 1.127e-02, eta: 10:21:47, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9981, loss_cls: 0.3694, loss: 0.3694 +2025-06-24 22:27:11,291 - pyskl - INFO - Epoch [80][1000/1281] lr: 1.125e-02, eta: 10:21:12, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9962, loss_cls: 0.4835, loss: 0.4835 +2025-06-24 22:28:00,164 - pyskl - INFO - Epoch [80][1100/1281] lr: 1.123e-02, eta: 10:20:37, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9969, loss_cls: 0.4160, loss: 0.4160 +2025-06-24 22:28:36,243 - pyskl - INFO - Epoch [80][1200/1281] lr: 1.121e-02, eta: 10:19:51, time: 0.361, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9988, loss_cls: 0.3693, loss: 0.3693 +2025-06-24 22:29:19,300 - pyskl - INFO - Saving checkpoint at 80 epochs +2025-06-24 22:30:07,470 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:30:07,532 - pyskl - INFO - +top1_acc 0.8662 +top5_acc 0.9914 +2025-06-24 22:30:07,532 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:30:07,539 - pyskl - INFO - +mean_acc 0.8196 +2025-06-24 22:30:07,541 - pyskl - INFO - Epoch(val) [80][533] top1_acc: 0.8662, top5_acc: 0.9914, mean_class_accuracy: 0.8196 +2025-06-24 22:31:27,775 - pyskl - INFO - Epoch [81][100/1281] lr: 1.117e-02, eta: 10:18:40, time: 0.802, data_time: 0.197, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9988, loss_cls: 0.3426, loss: 0.3426 +2025-06-24 22:32:16,850 - pyskl - INFO - Epoch [81][200/1281] lr: 1.115e-02, eta: 10:18:06, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9981, loss_cls: 0.3290, loss: 0.3290 +2025-06-24 22:33:06,183 - pyskl - INFO - Epoch [81][300/1281] lr: 1.113e-02, eta: 10:17:31, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9969, loss_cls: 0.3311, loss: 0.3311 +2025-06-24 22:33:55,308 - pyskl - INFO - Epoch [81][400/1281] lr: 1.111e-02, eta: 10:16:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9956, loss_cls: 0.3637, loss: 0.3637 +2025-06-24 22:34:44,337 - pyskl - INFO - Epoch [81][500/1281] lr: 1.109e-02, eta: 10:16:21, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9988, loss_cls: 0.3646, loss: 0.3646 +2025-06-24 22:35:33,790 - pyskl - INFO - Epoch [81][600/1281] lr: 1.107e-02, eta: 10:15:47, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9969, loss_cls: 0.4020, loss: 0.4020 +2025-06-24 22:36:22,835 - pyskl - INFO - Epoch [81][700/1281] lr: 1.105e-02, eta: 10:15:12, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9975, loss_cls: 0.3940, loss: 0.3940 +2025-06-24 22:37:12,083 - pyskl - INFO - Epoch [81][800/1281] lr: 1.103e-02, eta: 10:14:37, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9994, loss_cls: 0.3528, loss: 0.3528 +2025-06-24 22:38:01,169 - pyskl - INFO - Epoch [81][900/1281] lr: 1.101e-02, eta: 10:14:02, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9975, loss_cls: 0.4674, loss: 0.4674 +2025-06-24 22:38:50,337 - pyskl - INFO - Epoch [81][1000/1281] lr: 1.099e-02, eta: 10:13:27, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9956, loss_cls: 0.3914, loss: 0.3914 +2025-06-24 22:39:39,733 - pyskl - INFO - Epoch [81][1100/1281] lr: 1.097e-02, eta: 10:12:52, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9988, loss_cls: 0.4147, loss: 0.4147 +2025-06-24 22:40:16,693 - pyskl - INFO - Epoch [81][1200/1281] lr: 1.095e-02, eta: 10:12:07, time: 0.370, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 0.3876, loss: 0.3876 +2025-06-24 22:40:58,913 - pyskl - INFO - Saving checkpoint at 81 epochs +2025-06-24 22:41:46,568 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:41:46,625 - pyskl - INFO - +top1_acc 0.8762 +top5_acc 0.9921 +2025-06-24 22:41:46,626 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:41:46,632 - pyskl - INFO - +mean_acc 0.8221 +2025-06-24 22:41:46,636 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_77.pth was removed +2025-06-24 22:41:46,815 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_81.pth. +2025-06-24 22:41:46,815 - pyskl - INFO - Best top1_acc is 0.8762 at 81 epoch. +2025-06-24 22:41:46,818 - pyskl - INFO - Epoch(val) [81][533] top1_acc: 0.8762, top5_acc: 0.9921, mean_class_accuracy: 0.8221 +2025-06-24 22:43:05,953 - pyskl - INFO - Epoch [82][100/1281] lr: 1.091e-02, eta: 10:10:55, time: 0.791, data_time: 0.191, memory: 4083, top1_acc: 0.9437, top5_acc: 1.0000, loss_cls: 0.3359, loss: 0.3359 +2025-06-24 22:43:54,908 - pyskl - INFO - Epoch [82][200/1281] lr: 1.089e-02, eta: 10:10:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9994, loss_cls: 0.3448, loss: 0.3448 +2025-06-24 22:44:44,004 - pyskl - INFO - Epoch [82][300/1281] lr: 1.087e-02, eta: 10:09:45, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9994, loss_cls: 0.3963, loss: 0.3963 +2025-06-24 22:45:33,167 - pyskl - INFO - Epoch [82][400/1281] lr: 1.085e-02, eta: 10:09:10, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9981, loss_cls: 0.3901, loss: 0.3901 +2025-06-24 22:46:22,725 - pyskl - INFO - Epoch [82][500/1281] lr: 1.083e-02, eta: 10:08:35, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9981, loss_cls: 0.3733, loss: 0.3733 +2025-06-24 22:47:12,001 - pyskl - INFO - Epoch [82][600/1281] lr: 1.081e-02, eta: 10:08:00, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.3054, loss: 0.3054 +2025-06-24 22:48:01,178 - pyskl - INFO - Epoch [82][700/1281] lr: 1.079e-02, eta: 10:07:25, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9981, loss_cls: 0.3736, loss: 0.3736 +2025-06-24 22:48:50,584 - pyskl - INFO - Epoch [82][800/1281] lr: 1.077e-02, eta: 10:06:50, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9988, loss_cls: 0.3335, loss: 0.3335 +2025-06-24 22:49:39,759 - pyskl - INFO - Epoch [82][900/1281] lr: 1.075e-02, eta: 10:06:15, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9988, loss_cls: 0.4021, loss: 0.4021 +2025-06-24 22:50:28,812 - pyskl - INFO - Epoch [82][1000/1281] lr: 1.073e-02, eta: 10:05:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9975, loss_cls: 0.4128, loss: 0.4128 +2025-06-24 22:51:17,942 - pyskl - INFO - Epoch [82][1100/1281] lr: 1.071e-02, eta: 10:05:04, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9988, loss_cls: 0.4148, loss: 0.4148 +2025-06-24 22:51:55,624 - pyskl - INFO - Epoch [82][1200/1281] lr: 1.069e-02, eta: 10:04:19, time: 0.377, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9975, loss_cls: 0.3948, loss: 0.3948 +2025-06-24 22:52:38,832 - pyskl - INFO - Saving checkpoint at 82 epochs +2025-06-24 22:53:26,812 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:53:26,867 - pyskl - INFO - +top1_acc 0.8540 +top5_acc 0.9897 +2025-06-24 22:53:26,868 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:53:26,874 - pyskl - INFO - +mean_acc 0.7924 +2025-06-24 22:53:26,876 - pyskl - INFO - Epoch(val) [82][533] top1_acc: 0.8540, top5_acc: 0.9897, mean_class_accuracy: 0.7924 +2025-06-24 22:54:46,787 - pyskl - INFO - Epoch [83][100/1281] lr: 1.065e-02, eta: 10:03:08, time: 0.799, data_time: 0.191, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 0.3081, loss: 0.3081 +2025-06-24 22:55:36,099 - pyskl - INFO - Epoch [83][200/1281] lr: 1.063e-02, eta: 10:02:32, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9981, loss_cls: 0.3475, loss: 0.3475 +2025-06-24 22:56:25,332 - pyskl - INFO - Epoch [83][300/1281] lr: 1.061e-02, eta: 10:01:57, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 1.0000, loss_cls: 0.3120, loss: 0.3120 +2025-06-24 22:57:14,482 - pyskl - INFO - Epoch [83][400/1281] lr: 1.059e-02, eta: 10:01:22, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9994, loss_cls: 0.3659, loss: 0.3659 +2025-06-24 22:58:03,758 - pyskl - INFO - Epoch [83][500/1281] lr: 1.057e-02, eta: 10:00:46, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9975, loss_cls: 0.3594, loss: 0.3594 +2025-06-24 22:58:53,034 - pyskl - INFO - Epoch [83][600/1281] lr: 1.055e-02, eta: 10:00:11, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9994, loss_cls: 0.3565, loss: 0.3565 +2025-06-24 22:59:42,172 - pyskl - INFO - Epoch [83][700/1281] lr: 1.053e-02, eta: 9:59:36, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9969, loss_cls: 0.3737, loss: 0.3737 +2025-06-24 23:00:31,303 - pyskl - INFO - Epoch [83][800/1281] lr: 1.051e-02, eta: 9:59:00, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9981, loss_cls: 0.4346, loss: 0.4346 +2025-06-24 23:01:20,513 - pyskl - INFO - Epoch [83][900/1281] lr: 1.049e-02, eta: 9:58:25, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9988, loss_cls: 0.4042, loss: 0.4042 +2025-06-24 23:02:09,820 - pyskl - INFO - Epoch [83][1000/1281] lr: 1.047e-02, eta: 9:57:49, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9975, loss_cls: 0.3550, loss: 0.3550 +2025-06-24 23:02:58,940 - pyskl - INFO - Epoch [83][1100/1281] lr: 1.045e-02, eta: 9:57:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 1.0000, loss_cls: 0.4074, loss: 0.4074 +2025-06-24 23:03:34,965 - pyskl - INFO - Epoch [83][1200/1281] lr: 1.043e-02, eta: 9:56:27, time: 0.360, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9981, loss_cls: 0.3561, loss: 0.3561 +2025-06-24 23:04:19,835 - pyskl - INFO - Saving checkpoint at 83 epochs +2025-06-24 23:05:08,047 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:05:08,101 - pyskl - INFO - +top1_acc 0.8754 +top5_acc 0.9939 +2025-06-24 23:05:08,101 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:05:08,108 - pyskl - INFO - +mean_acc 0.8281 +2025-06-24 23:05:08,109 - pyskl - INFO - Epoch(val) [83][533] top1_acc: 0.8754, top5_acc: 0.9939, mean_class_accuracy: 0.8281 +2025-06-24 23:06:27,249 - pyskl - INFO - Epoch [84][100/1281] lr: 1.040e-02, eta: 9:55:15, time: 0.791, data_time: 0.193, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9988, loss_cls: 0.3080, loss: 0.3080 +2025-06-24 23:07:16,262 - pyskl - INFO - Epoch [84][200/1281] lr: 1.038e-02, eta: 9:54:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9981, loss_cls: 0.3921, loss: 0.3921 +2025-06-24 23:08:05,480 - pyskl - INFO - Epoch [84][300/1281] lr: 1.036e-02, eta: 9:54:03, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9994, loss_cls: 0.3553, loss: 0.3553 +2025-06-24 23:08:54,474 - pyskl - INFO - Epoch [84][400/1281] lr: 1.034e-02, eta: 9:53:28, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9981, loss_cls: 0.4004, loss: 0.4004 +2025-06-24 23:09:43,921 - pyskl - INFO - Epoch [84][500/1281] lr: 1.031e-02, eta: 9:52:52, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9994, loss_cls: 0.3573, loss: 0.3573 +2025-06-24 23:10:33,292 - pyskl - INFO - Epoch [84][600/1281] lr: 1.029e-02, eta: 9:52:17, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9988, loss_cls: 0.3271, loss: 0.3271 +2025-06-24 23:11:22,621 - pyskl - INFO - Epoch [84][700/1281] lr: 1.027e-02, eta: 9:51:41, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9988, loss_cls: 0.3197, loss: 0.3197 +2025-06-24 23:12:11,736 - pyskl - INFO - Epoch [84][800/1281] lr: 1.025e-02, eta: 9:51:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9975, loss_cls: 0.4112, loss: 0.4112 +2025-06-24 23:13:00,955 - pyskl - INFO - Epoch [84][900/1281] lr: 1.023e-02, eta: 9:50:29, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9994, loss_cls: 0.4282, loss: 0.4282 +2025-06-24 23:13:50,125 - pyskl - INFO - Epoch [84][1000/1281] lr: 1.021e-02, eta: 9:49:54, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9988, loss_cls: 0.3947, loss: 0.3947 +2025-06-24 23:14:39,124 - pyskl - INFO - Epoch [84][1100/1281] lr: 1.019e-02, eta: 9:49:18, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9988, loss_cls: 0.3726, loss: 0.3726 +2025-06-24 23:15:17,003 - pyskl - INFO - Epoch [84][1200/1281] lr: 1.017e-02, eta: 9:48:33, time: 0.379, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 1.0000, loss_cls: 0.3440, loss: 0.3440 +2025-06-24 23:15:59,223 - pyskl - INFO - Saving checkpoint at 84 epochs +2025-06-24 23:16:47,126 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:16:47,195 - pyskl - INFO - +top1_acc 0.8709 +top5_acc 0.9921 +2025-06-24 23:16:47,195 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:16:47,202 - pyskl - INFO - +mean_acc 0.8288 +2025-06-24 23:16:47,204 - pyskl - INFO - Epoch(val) [84][533] top1_acc: 0.8709, top5_acc: 0.9921, mean_class_accuracy: 0.8288 +2025-06-24 23:18:08,077 - pyskl - INFO - Epoch [85][100/1281] lr: 1.014e-02, eta: 9:47:21, time: 0.809, data_time: 0.197, memory: 4083, top1_acc: 0.9456, top5_acc: 1.0000, loss_cls: 0.3175, loss: 0.3175 +2025-06-24 23:18:56,982 - pyskl - INFO - Epoch [85][200/1281] lr: 1.012e-02, eta: 9:46:45, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 0.2878, loss: 0.2878 +2025-06-24 23:19:46,160 - pyskl - INFO - Epoch [85][300/1281] lr: 1.010e-02, eta: 9:46:09, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 0.2951, loss: 0.2951 +2025-06-24 23:20:35,130 - pyskl - INFO - Epoch [85][400/1281] lr: 1.008e-02, eta: 9:45:33, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9988, loss_cls: 0.3193, loss: 0.3193 +2025-06-24 23:21:24,106 - pyskl - INFO - Epoch [85][500/1281] lr: 1.006e-02, eta: 9:44:57, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 1.0000, loss_cls: 0.2797, loss: 0.2797 +2025-06-24 23:22:13,301 - pyskl - INFO - Epoch [85][600/1281] lr: 1.004e-02, eta: 9:44:21, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9994, loss_cls: 0.3741, loss: 0.3741 +2025-06-24 23:23:02,413 - pyskl - INFO - Epoch [85][700/1281] lr: 1.002e-02, eta: 9:43:45, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9988, loss_cls: 0.3430, loss: 0.3430 +2025-06-24 23:23:51,395 - pyskl - INFO - Epoch [85][800/1281] lr: 9.998e-03, eta: 9:43:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 1.0000, loss_cls: 0.3190, loss: 0.3190 +2025-06-24 23:24:41,070 - pyskl - INFO - Epoch [85][900/1281] lr: 9.978e-03, eta: 9:42:33, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9988, loss_cls: 0.3781, loss: 0.3781 +2025-06-24 23:25:30,507 - pyskl - INFO - Epoch [85][1000/1281] lr: 9.958e-03, eta: 9:41:57, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9975, loss_cls: 0.4004, loss: 0.4004 +2025-06-24 23:26:19,795 - pyskl - INFO - Epoch [85][1100/1281] lr: 9.937e-03, eta: 9:41:21, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 1.0000, loss_cls: 0.3215, loss: 0.3215 +2025-06-24 23:26:55,820 - pyskl - INFO - Epoch [85][1200/1281] lr: 9.917e-03, eta: 9:40:35, time: 0.360, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9969, loss_cls: 0.4346, loss: 0.4346 +2025-06-24 23:27:42,148 - pyskl - INFO - Saving checkpoint at 85 epochs +2025-06-24 23:28:30,666 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:28:30,724 - pyskl - INFO - +top1_acc 0.8656 +top5_acc 0.9927 +2025-06-24 23:28:30,724 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:28:30,732 - pyskl - INFO - +mean_acc 0.8227 +2025-06-24 23:28:30,734 - pyskl - INFO - Epoch(val) [85][533] top1_acc: 0.8656, top5_acc: 0.9927, mean_class_accuracy: 0.8227 +2025-06-24 23:29:50,787 - pyskl - INFO - Epoch [86][100/1281] lr: 9.881e-03, eta: 9:39:23, time: 0.800, data_time: 0.196, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2693, loss: 0.2693 +2025-06-24 23:30:39,635 - pyskl - INFO - Epoch [86][200/1281] lr: 9.861e-03, eta: 9:38:46, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 0.3152, loss: 0.3152 +2025-06-24 23:31:28,684 - pyskl - INFO - Epoch [86][300/1281] lr: 9.841e-03, eta: 9:38:10, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2875, loss: 0.2875 +2025-06-24 23:32:18,042 - pyskl - INFO - Epoch [86][400/1281] lr: 9.821e-03, eta: 9:37:34, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 0.2900, loss: 0.2900 +2025-06-24 23:33:07,455 - pyskl - INFO - Epoch [86][500/1281] lr: 9.801e-03, eta: 9:36:58, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 0.2829, loss: 0.2829 +2025-06-24 23:33:56,680 - pyskl - INFO - Epoch [86][600/1281] lr: 9.781e-03, eta: 9:36:22, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9975, loss_cls: 0.3497, loss: 0.3497 +2025-06-24 23:34:45,903 - pyskl - INFO - Epoch [86][700/1281] lr: 9.762e-03, eta: 9:35:45, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 0.3342, loss: 0.3342 +2025-06-24 23:35:34,835 - pyskl - INFO - Epoch [86][800/1281] lr: 9.742e-03, eta: 9:35:09, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9994, loss_cls: 0.3229, loss: 0.3229 +2025-06-24 23:36:23,717 - pyskl - INFO - Epoch [86][900/1281] lr: 9.722e-03, eta: 9:34:32, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9975, loss_cls: 0.3910, loss: 0.3910 +2025-06-24 23:37:12,770 - pyskl - INFO - Epoch [86][1000/1281] lr: 9.702e-03, eta: 9:33:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9975, loss_cls: 0.3732, loss: 0.3732 +2025-06-24 23:38:02,061 - pyskl - INFO - Epoch [86][1100/1281] lr: 9.682e-03, eta: 9:33:19, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9988, loss_cls: 0.3859, loss: 0.3859 +2025-06-24 23:38:38,814 - pyskl - INFO - Epoch [86][1200/1281] lr: 9.662e-03, eta: 9:32:34, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9975, loss_cls: 0.4358, loss: 0.4358 +2025-06-24 23:39:23,940 - pyskl - INFO - Saving checkpoint at 86 epochs +2025-06-24 23:40:11,616 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:40:11,678 - pyskl - INFO - +top1_acc 0.8790 +top5_acc 0.9933 +2025-06-24 23:40:11,678 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:40:11,687 - pyskl - INFO - +mean_acc 0.8366 +2025-06-24 23:40:11,691 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_81.pth was removed +2025-06-24 23:40:11,876 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_86.pth. +2025-06-24 23:40:11,876 - pyskl - INFO - Best top1_acc is 0.8790 at 86 epoch. +2025-06-24 23:40:11,879 - pyskl - INFO - Epoch(val) [86][533] top1_acc: 0.8790, top5_acc: 0.9933, mean_class_accuracy: 0.8366 +2025-06-24 23:41:31,814 - pyskl - INFO - Epoch [87][100/1281] lr: 9.626e-03, eta: 9:31:21, time: 0.799, data_time: 0.196, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.2748, loss: 0.2748 +2025-06-24 23:42:20,871 - pyskl - INFO - Epoch [87][200/1281] lr: 9.606e-03, eta: 9:30:45, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 0.3273, loss: 0.3273 +2025-06-24 23:43:09,967 - pyskl - INFO - Epoch [87][300/1281] lr: 9.586e-03, eta: 9:30:08, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9988, loss_cls: 0.3384, loss: 0.3384 +2025-06-24 23:43:59,052 - pyskl - INFO - Epoch [87][400/1281] lr: 9.566e-03, eta: 9:29:31, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3194, loss: 0.3194 +2025-06-24 23:44:48,312 - pyskl - INFO - Epoch [87][500/1281] lr: 9.546e-03, eta: 9:28:55, time: 0.493, data_time: 0.001, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9994, loss_cls: 0.3256, loss: 0.3256 +2025-06-24 23:45:36,975 - pyskl - INFO - Epoch [87][600/1281] lr: 9.527e-03, eta: 9:28:18, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9988, loss_cls: 0.3157, loss: 0.3157 +2025-06-24 23:46:26,234 - pyskl - INFO - Epoch [87][700/1281] lr: 9.507e-03, eta: 9:27:42, time: 0.493, data_time: 0.001, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9981, loss_cls: 0.3719, loss: 0.3719 +2025-06-24 23:47:15,409 - pyskl - INFO - Epoch [87][800/1281] lr: 9.487e-03, eta: 9:27:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9994, loss_cls: 0.3417, loss: 0.3417 +2025-06-24 23:48:04,579 - pyskl - INFO - Epoch [87][900/1281] lr: 9.467e-03, eta: 9:26:28, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 0.2940, loss: 0.2940 +2025-06-24 23:48:53,731 - pyskl - INFO - Epoch [87][1000/1281] lr: 9.447e-03, eta: 9:25:52, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9994, loss_cls: 0.3210, loss: 0.3210 +2025-06-24 23:49:42,751 - pyskl - INFO - Epoch [87][1100/1281] lr: 9.427e-03, eta: 9:25:15, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9994, loss_cls: 0.3260, loss: 0.3260 +2025-06-24 23:50:19,797 - pyskl - INFO - Epoch [87][1200/1281] lr: 9.408e-03, eta: 9:24:29, time: 0.370, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 1.0000, loss_cls: 0.3341, loss: 0.3341 +2025-06-24 23:51:04,398 - pyskl - INFO - Saving checkpoint at 87 epochs +2025-06-24 23:51:52,639 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:51:52,697 - pyskl - INFO - +top1_acc 0.8649 +top5_acc 0.9914 +2025-06-24 23:51:52,697 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:51:52,705 - pyskl - INFO - +mean_acc 0.8219 +2025-06-24 23:51:52,707 - pyskl - INFO - Epoch(val) [87][533] top1_acc: 0.8649, top5_acc: 0.9914, mean_class_accuracy: 0.8219 +2025-06-24 23:53:12,125 - pyskl - INFO - Epoch [88][100/1281] lr: 9.372e-03, eta: 9:23:16, time: 0.794, data_time: 0.189, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9975, loss_cls: 0.2594, loss: 0.2594 +2025-06-24 23:54:01,080 - pyskl - INFO - Epoch [88][200/1281] lr: 9.352e-03, eta: 9:22:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 1.0000, loss_cls: 0.2999, loss: 0.2999 +2025-06-24 23:54:50,558 - pyskl - INFO - Epoch [88][300/1281] lr: 9.332e-03, eta: 9:22:03, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 1.0000, loss_cls: 0.3434, loss: 0.3434 +2025-06-24 23:55:39,939 - pyskl - INFO - Epoch [88][400/1281] lr: 9.312e-03, eta: 9:21:26, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9994, loss_cls: 0.3018, loss: 0.3018 +2025-06-24 23:56:29,152 - pyskl - INFO - Epoch [88][500/1281] lr: 9.293e-03, eta: 9:20:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 1.0000, loss_cls: 0.3104, loss: 0.3104 +2025-06-24 23:57:18,401 - pyskl - INFO - Epoch [88][600/1281] lr: 9.273e-03, eta: 9:20:13, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 1.0000, loss_cls: 0.3389, loss: 0.3389 +2025-06-24 23:58:07,305 - pyskl - INFO - Epoch [88][700/1281] lr: 9.253e-03, eta: 9:19:36, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9981, loss_cls: 0.3270, loss: 0.3270 +2025-06-24 23:58:56,802 - pyskl - INFO - Epoch [88][800/1281] lr: 9.233e-03, eta: 9:18:59, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9981, loss_cls: 0.3302, loss: 0.3302 +2025-06-24 23:59:46,058 - pyskl - INFO - Epoch [88][900/1281] lr: 9.214e-03, eta: 9:18:22, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 0.3203, loss: 0.3203 +2025-06-25 00:00:35,320 - pyskl - INFO - Epoch [88][1000/1281] lr: 9.194e-03, eta: 9:17:45, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9988, loss_cls: 0.3493, loss: 0.3493 +2025-06-25 00:01:24,481 - pyskl - INFO - Epoch [88][1100/1281] lr: 9.174e-03, eta: 9:17:09, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9994, loss_cls: 0.3817, loss: 0.3817 +2025-06-25 00:02:01,560 - pyskl - INFO - Epoch [88][1200/1281] lr: 9.155e-03, eta: 9:16:23, time: 0.371, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9988, loss_cls: 0.3489, loss: 0.3489 +2025-06-25 00:02:43,909 - pyskl - INFO - Saving checkpoint at 88 epochs +2025-06-25 00:03:32,065 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:03:32,121 - pyskl - INFO - +top1_acc 0.8722 +top5_acc 0.9912 +2025-06-25 00:03:32,122 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:03:32,128 - pyskl - INFO - +mean_acc 0.8331 +2025-06-25 00:03:32,130 - pyskl - INFO - Epoch(val) [88][533] top1_acc: 0.8722, top5_acc: 0.9912, mean_class_accuracy: 0.8331 +2025-06-25 00:04:51,186 - pyskl - INFO - Epoch [89][100/1281] lr: 9.119e-03, eta: 9:15:09, time: 0.791, data_time: 0.193, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2731, loss: 0.2731 +2025-06-25 00:05:40,426 - pyskl - INFO - Epoch [89][200/1281] lr: 9.099e-03, eta: 9:14:32, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 0.2637, loss: 0.2637 +2025-06-25 00:06:29,780 - pyskl - INFO - Epoch [89][300/1281] lr: 9.080e-03, eta: 9:13:55, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9969, loss_cls: 0.3190, loss: 0.3190 +2025-06-25 00:07:18,890 - pyskl - INFO - Epoch [89][400/1281] lr: 9.060e-03, eta: 9:13:18, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9981, loss_cls: 0.3787, loss: 0.3787 +2025-06-25 00:08:08,152 - pyskl - INFO - Epoch [89][500/1281] lr: 9.040e-03, eta: 9:12:41, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 1.0000, loss_cls: 0.3197, loss: 0.3197 +2025-06-25 00:08:57,061 - pyskl - INFO - Epoch [89][600/1281] lr: 9.021e-03, eta: 9:12:04, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9988, loss_cls: 0.3092, loss: 0.3092 +2025-06-25 00:09:46,063 - pyskl - INFO - Epoch [89][700/1281] lr: 9.001e-03, eta: 9:11:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3472, loss: 0.3472 +2025-06-25 00:10:35,146 - pyskl - INFO - Epoch [89][800/1281] lr: 8.982e-03, eta: 9:10:50, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9988, loss_cls: 0.3578, loss: 0.3578 +2025-06-25 00:11:24,324 - pyskl - INFO - Epoch [89][900/1281] lr: 8.962e-03, eta: 9:10:13, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9994, loss_cls: 0.3360, loss: 0.3360 +2025-06-25 00:12:13,258 - pyskl - INFO - Epoch [89][1000/1281] lr: 8.942e-03, eta: 9:09:35, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9981, loss_cls: 0.3780, loss: 0.3780 +2025-06-25 00:13:02,415 - pyskl - INFO - Epoch [89][1100/1281] lr: 8.923e-03, eta: 9:08:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9988, loss_cls: 0.3290, loss: 0.3290 +2025-06-25 00:13:39,815 - pyskl - INFO - Epoch [89][1200/1281] lr: 8.903e-03, eta: 9:08:13, time: 0.374, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9994, loss_cls: 0.3346, loss: 0.3346 +2025-06-25 00:14:19,012 - pyskl - INFO - Saving checkpoint at 89 epochs +2025-06-25 00:15:05,659 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:15:05,718 - pyskl - INFO - +top1_acc 0.8675 +top5_acc 0.9917 +2025-06-25 00:15:05,718 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:15:05,725 - pyskl - INFO - +mean_acc 0.8198 +2025-06-25 00:15:05,727 - pyskl - INFO - Epoch(val) [89][533] top1_acc: 0.8675, top5_acc: 0.9917, mean_class_accuracy: 0.8198 +2025-06-25 00:16:26,588 - pyskl - INFO - Epoch [90][100/1281] lr: 8.868e-03, eta: 9:07:00, time: 0.809, data_time: 0.195, memory: 4083, top1_acc: 0.9475, top5_acc: 1.0000, loss_cls: 0.3136, loss: 0.3136 +2025-06-25 00:17:15,346 - pyskl - INFO - Epoch [90][200/1281] lr: 8.848e-03, eta: 9:06:23, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9988, loss_cls: 0.3066, loss: 0.3066 +2025-06-25 00:18:04,359 - pyskl - INFO - Epoch [90][300/1281] lr: 8.829e-03, eta: 9:05:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.2855, loss: 0.2855 +2025-06-25 00:18:53,382 - pyskl - INFO - Epoch [90][400/1281] lr: 8.809e-03, eta: 9:05:08, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9981, loss_cls: 0.3279, loss: 0.3279 +2025-06-25 00:19:42,492 - pyskl - INFO - Epoch [90][500/1281] lr: 8.790e-03, eta: 9:04:31, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2457, loss: 0.2457 +2025-06-25 00:20:31,482 - pyskl - INFO - Epoch [90][600/1281] lr: 8.770e-03, eta: 9:03:53, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9988, loss_cls: 0.3487, loss: 0.3487 +2025-06-25 00:21:20,492 - pyskl - INFO - Epoch [90][700/1281] lr: 8.751e-03, eta: 9:03:16, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3457, loss: 0.3457 +2025-06-25 00:22:09,809 - pyskl - INFO - Epoch [90][800/1281] lr: 8.731e-03, eta: 9:02:39, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9981, loss_cls: 0.3008, loss: 0.3008 +2025-06-25 00:22:58,861 - pyskl - INFO - Epoch [90][900/1281] lr: 8.712e-03, eta: 9:02:01, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9994, loss_cls: 0.3275, loss: 0.3275 +2025-06-25 00:23:48,132 - pyskl - INFO - Epoch [90][1000/1281] lr: 8.692e-03, eta: 9:01:24, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 1.0000, loss_cls: 0.3245, loss: 0.3245 +2025-06-25 00:24:37,540 - pyskl - INFO - Epoch [90][1100/1281] lr: 8.673e-03, eta: 9:00:47, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 0.2845, loss: 0.2845 +2025-06-25 00:25:14,319 - pyskl - INFO - Epoch [90][1200/1281] lr: 8.653e-03, eta: 9:00:01, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9994, loss_cls: 0.3129, loss: 0.3129 +2025-06-25 00:25:57,225 - pyskl - INFO - Saving checkpoint at 90 epochs +2025-06-25 00:26:44,742 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:26:44,799 - pyskl - INFO - +top1_acc 0.8821 +top5_acc 0.9923 +2025-06-25 00:26:44,799 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:26:44,806 - pyskl - INFO - +mean_acc 0.8376 +2025-06-25 00:26:44,810 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_86.pth was removed +2025-06-25 00:26:44,980 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_90.pth. +2025-06-25 00:26:44,981 - pyskl - INFO - Best top1_acc is 0.8821 at 90 epoch. +2025-06-25 00:26:44,983 - pyskl - INFO - Epoch(val) [90][533] top1_acc: 0.8821, top5_acc: 0.9923, mean_class_accuracy: 0.8376 +2025-06-25 00:28:04,532 - pyskl - INFO - Epoch [91][100/1281] lr: 8.618e-03, eta: 8:58:47, time: 0.795, data_time: 0.192, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9981, loss_cls: 0.2772, loss: 0.2772 +2025-06-25 00:28:53,672 - pyskl - INFO - Epoch [91][200/1281] lr: 8.599e-03, eta: 8:58:10, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 0.2806, loss: 0.2806 +2025-06-25 00:29:43,077 - pyskl - INFO - Epoch [91][300/1281] lr: 8.579e-03, eta: 8:57:32, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 0.2428, loss: 0.2428 +2025-06-25 00:30:32,324 - pyskl - INFO - Epoch [91][400/1281] lr: 8.560e-03, eta: 8:56:55, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9988, loss_cls: 0.3355, loss: 0.3355 +2025-06-25 00:31:21,491 - pyskl - INFO - Epoch [91][500/1281] lr: 8.540e-03, eta: 8:56:17, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 1.0000, loss_cls: 0.2987, loss: 0.2987 +2025-06-25 00:32:10,368 - pyskl - INFO - Epoch [91][600/1281] lr: 8.521e-03, eta: 8:55:40, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.2986, loss: 0.2986 +2025-06-25 00:32:59,674 - pyskl - INFO - Epoch [91][700/1281] lr: 8.502e-03, eta: 8:55:02, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9988, loss_cls: 0.2666, loss: 0.2666 +2025-06-25 00:33:48,784 - pyskl - INFO - Epoch [91][800/1281] lr: 8.482e-03, eta: 8:54:25, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9994, loss_cls: 0.2951, loss: 0.2951 +2025-06-25 00:34:37,630 - pyskl - INFO - Epoch [91][900/1281] lr: 8.463e-03, eta: 8:53:47, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 0.3183, loss: 0.3183 +2025-06-25 00:35:26,619 - pyskl - INFO - Epoch [91][1000/1281] lr: 8.444e-03, eta: 8:53:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 1.0000, loss_cls: 0.2744, loss: 0.2744 +2025-06-25 00:36:15,536 - pyskl - INFO - Epoch [91][1100/1281] lr: 8.424e-03, eta: 8:52:31, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9988, loss_cls: 0.3168, loss: 0.3168 +2025-06-25 00:36:52,396 - pyskl - INFO - Epoch [91][1200/1281] lr: 8.405e-03, eta: 8:51:46, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9981, loss_cls: 0.2999, loss: 0.2999 +2025-06-25 00:37:33,399 - pyskl - INFO - Saving checkpoint at 91 epochs +2025-06-25 00:38:20,714 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:38:20,769 - pyskl - INFO - +top1_acc 0.8808 +top5_acc 0.9944 +2025-06-25 00:38:20,769 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:38:20,776 - pyskl - INFO - +mean_acc 0.8418 +2025-06-25 00:38:20,778 - pyskl - INFO - Epoch(val) [91][533] top1_acc: 0.8808, top5_acc: 0.9944, mean_class_accuracy: 0.8418 +2025-06-25 00:39:40,865 - pyskl - INFO - Epoch [92][100/1281] lr: 8.370e-03, eta: 8:50:32, time: 0.801, data_time: 0.192, memory: 4083, top1_acc: 0.9556, top5_acc: 1.0000, loss_cls: 0.2730, loss: 0.2730 +2025-06-25 00:40:29,859 - pyskl - INFO - Epoch [92][200/1281] lr: 8.351e-03, eta: 8:49:54, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 1.0000, loss_cls: 0.2989, loss: 0.2989 +2025-06-25 00:41:18,951 - pyskl - INFO - Epoch [92][300/1281] lr: 8.332e-03, eta: 8:49:16, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9988, loss_cls: 0.3032, loss: 0.3032 +2025-06-25 00:42:08,170 - pyskl - INFO - Epoch [92][400/1281] lr: 8.312e-03, eta: 8:48:39, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 0.2969, loss: 0.2969 +2025-06-25 00:42:57,272 - pyskl - INFO - Epoch [92][500/1281] lr: 8.293e-03, eta: 8:48:01, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9487, top5_acc: 1.0000, loss_cls: 0.2982, loss: 0.2982 +2025-06-25 00:43:46,470 - pyskl - INFO - Epoch [92][600/1281] lr: 8.274e-03, eta: 8:47:23, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9988, loss_cls: 0.2919, loss: 0.2919 +2025-06-25 00:44:35,434 - pyskl - INFO - Epoch [92][700/1281] lr: 8.255e-03, eta: 8:46:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9988, loss_cls: 0.2894, loss: 0.2894 +2025-06-25 00:45:24,544 - pyskl - INFO - Epoch [92][800/1281] lr: 8.235e-03, eta: 8:46:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.3074, loss: 0.3074 +2025-06-25 00:46:13,659 - pyskl - INFO - Epoch [92][900/1281] lr: 8.216e-03, eta: 8:45:30, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9988, loss_cls: 0.3265, loss: 0.3265 +2025-06-25 00:47:02,700 - pyskl - INFO - Epoch [92][1000/1281] lr: 8.197e-03, eta: 8:44:52, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 1.0000, loss_cls: 0.2814, loss: 0.2814 +2025-06-25 00:47:52,076 - pyskl - INFO - Epoch [92][1100/1281] lr: 8.178e-03, eta: 8:44:14, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 0.2680, loss: 0.2680 +2025-06-25 00:48:28,731 - pyskl - INFO - Epoch [92][1200/1281] lr: 8.159e-03, eta: 8:43:28, time: 0.367, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 1.0000, loss_cls: 0.3284, loss: 0.3284 +2025-06-25 00:49:12,360 - pyskl - INFO - Saving checkpoint at 92 epochs +2025-06-25 00:50:00,596 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:50:00,653 - pyskl - INFO - +top1_acc 0.8729 +top5_acc 0.9925 +2025-06-25 00:50:00,653 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:50:00,660 - pyskl - INFO - +mean_acc 0.8350 +2025-06-25 00:50:00,662 - pyskl - INFO - Epoch(val) [92][533] top1_acc: 0.8729, top5_acc: 0.9925, mean_class_accuracy: 0.8350 +2025-06-25 00:51:21,874 - pyskl - INFO - Epoch [93][100/1281] lr: 8.124e-03, eta: 8:42:15, time: 0.812, data_time: 0.193, memory: 4083, top1_acc: 0.9494, top5_acc: 1.0000, loss_cls: 0.2740, loss: 0.2740 +2025-06-25 00:52:10,900 - pyskl - INFO - Epoch [93][200/1281] lr: 8.105e-03, eta: 8:41:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 0.2463, loss: 0.2463 +2025-06-25 00:52:59,800 - pyskl - INFO - Epoch [93][300/1281] lr: 8.086e-03, eta: 8:40:59, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 0.2711, loss: 0.2711 +2025-06-25 00:53:48,855 - pyskl - INFO - Epoch [93][400/1281] lr: 8.067e-03, eta: 8:40:21, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 0.2604, loss: 0.2604 +2025-06-25 00:54:37,904 - pyskl - INFO - Epoch [93][500/1281] lr: 8.047e-03, eta: 8:39:43, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2559, loss: 0.2559 +2025-06-25 00:55:27,286 - pyskl - INFO - Epoch [93][600/1281] lr: 8.028e-03, eta: 8:39:05, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 0.2537, loss: 0.2537 +2025-06-25 00:56:16,566 - pyskl - INFO - Epoch [93][700/1281] lr: 8.009e-03, eta: 8:38:27, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 0.2835, loss: 0.2835 +2025-06-25 00:57:05,624 - pyskl - INFO - Epoch [93][800/1281] lr: 7.990e-03, eta: 8:37:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 0.2463, loss: 0.2463 +2025-06-25 00:57:55,193 - pyskl - INFO - Epoch [93][900/1281] lr: 7.971e-03, eta: 8:37:11, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 0.2707, loss: 0.2707 +2025-06-25 00:58:44,303 - pyskl - INFO - Epoch [93][1000/1281] lr: 7.952e-03, eta: 8:36:33, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9988, loss_cls: 0.3511, loss: 0.3511 +2025-06-25 00:59:33,398 - pyskl - INFO - Epoch [93][1100/1281] lr: 7.933e-03, eta: 8:35:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9988, loss_cls: 0.3189, loss: 0.3189 +2025-06-25 01:00:09,368 - pyskl - INFO - Epoch [93][1200/1281] lr: 7.914e-03, eta: 8:35:09, time: 0.360, data_time: 0.001, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3230, loss: 0.3230 +2025-06-25 01:00:55,350 - pyskl - INFO - Saving checkpoint at 93 epochs +2025-06-25 01:01:43,790 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:01:43,858 - pyskl - INFO - +top1_acc 0.8622 +top5_acc 0.9896 +2025-06-25 01:01:43,858 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:01:43,867 - pyskl - INFO - +mean_acc 0.8159 +2025-06-25 01:01:43,870 - pyskl - INFO - Epoch(val) [93][533] top1_acc: 0.8622, top5_acc: 0.9896, mean_class_accuracy: 0.8159 +2025-06-25 01:03:05,146 - pyskl - INFO - Epoch [94][100/1281] lr: 7.880e-03, eta: 8:33:55, time: 0.813, data_time: 0.192, memory: 4083, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 0.2639, loss: 0.2639 +2025-06-25 01:03:54,223 - pyskl - INFO - Epoch [94][200/1281] lr: 7.861e-03, eta: 8:33:17, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2453, loss: 0.2453 +2025-06-25 01:04:43,429 - pyskl - INFO - Epoch [94][300/1281] lr: 7.842e-03, eta: 8:32:39, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 0.2624, loss: 0.2624 +2025-06-25 01:05:32,465 - pyskl - INFO - Epoch [94][400/1281] lr: 7.823e-03, eta: 8:32:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9988, loss_cls: 0.2504, loss: 0.2504 +2025-06-25 01:06:21,411 - pyskl - INFO - Epoch [94][500/1281] lr: 7.804e-03, eta: 8:31:23, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2508, loss: 0.2508 +2025-06-25 01:07:10,294 - pyskl - INFO - Epoch [94][600/1281] lr: 7.785e-03, eta: 8:30:44, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9981, loss_cls: 0.2954, loss: 0.2954 +2025-06-25 01:07:59,087 - pyskl - INFO - Epoch [94][700/1281] lr: 7.766e-03, eta: 8:30:06, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9994, loss_cls: 0.2778, loss: 0.2778 +2025-06-25 01:08:48,109 - pyskl - INFO - Epoch [94][800/1281] lr: 7.747e-03, eta: 8:29:28, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 0.2703, loss: 0.2703 +2025-06-25 01:09:37,086 - pyskl - INFO - Epoch [94][900/1281] lr: 7.728e-03, eta: 8:28:49, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 0.2458, loss: 0.2458 +2025-06-25 01:10:26,336 - pyskl - INFO - Epoch [94][1000/1281] lr: 7.709e-03, eta: 8:28:11, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 0.2511, loss: 0.2511 +2025-06-25 01:11:15,514 - pyskl - INFO - Epoch [94][1100/1281] lr: 7.690e-03, eta: 8:27:33, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9994, loss_cls: 0.2551, loss: 0.2551 +2025-06-25 01:11:50,490 - pyskl - INFO - Epoch [94][1200/1281] lr: 7.672e-03, eta: 8:26:46, time: 0.350, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9981, loss_cls: 0.2685, loss: 0.2685 +2025-06-25 01:12:35,944 - pyskl - INFO - Saving checkpoint at 94 epochs +2025-06-25 01:13:23,777 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:13:23,832 - pyskl - INFO - +top1_acc 0.8853 +top5_acc 0.9933 +2025-06-25 01:13:23,832 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:13:23,839 - pyskl - INFO - +mean_acc 0.8442 +2025-06-25 01:13:23,843 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_90.pth was removed +2025-06-25 01:13:24,017 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_94.pth. +2025-06-25 01:13:24,017 - pyskl - INFO - Best top1_acc is 0.8853 at 94 epoch. +2025-06-25 01:13:24,020 - pyskl - INFO - Epoch(val) [94][533] top1_acc: 0.8853, top5_acc: 0.9933, mean_class_accuracy: 0.8442 +2025-06-25 01:14:44,150 - pyskl - INFO - Epoch [95][100/1281] lr: 7.637e-03, eta: 8:25:31, time: 0.801, data_time: 0.191, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 0.2319, loss: 0.2319 +2025-06-25 01:15:33,137 - pyskl - INFO - Epoch [95][200/1281] lr: 7.619e-03, eta: 8:24:53, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9994, loss_cls: 0.2502, loss: 0.2502 +2025-06-25 01:16:21,973 - pyskl - INFO - Epoch [95][300/1281] lr: 7.600e-03, eta: 8:24:15, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1998, loss: 0.1998 +2025-06-25 01:17:10,905 - pyskl - INFO - Epoch [95][400/1281] lr: 7.581e-03, eta: 8:23:36, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2328, loss: 0.2328 +2025-06-25 01:18:00,074 - pyskl - INFO - Epoch [95][500/1281] lr: 7.562e-03, eta: 8:22:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 0.9988, loss_cls: 0.2248, loss: 0.2248 +2025-06-25 01:18:48,878 - pyskl - INFO - Epoch [95][600/1281] lr: 7.543e-03, eta: 8:22:19, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 0.3211, loss: 0.3211 +2025-06-25 01:19:38,090 - pyskl - INFO - Epoch [95][700/1281] lr: 7.525e-03, eta: 8:21:41, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 0.2598, loss: 0.2598 +2025-06-25 01:20:27,346 - pyskl - INFO - Epoch [95][800/1281] lr: 7.506e-03, eta: 8:21:02, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 1.0000, loss_cls: 0.3003, loss: 0.3003 +2025-06-25 01:21:16,621 - pyskl - INFO - Epoch [95][900/1281] lr: 7.487e-03, eta: 8:20:24, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9988, loss_cls: 0.2679, loss: 0.2679 +2025-06-25 01:22:05,410 - pyskl - INFO - Epoch [95][1000/1281] lr: 7.468e-03, eta: 8:19:45, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2721, loss: 0.2721 +2025-06-25 01:22:54,531 - pyskl - INFO - Epoch [95][1100/1281] lr: 7.450e-03, eta: 8:19:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2438, loss: 0.2438 +2025-06-25 01:23:30,697 - pyskl - INFO - Epoch [95][1200/1281] lr: 7.431e-03, eta: 8:18:21, time: 0.362, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 0.2876, loss: 0.2876 +2025-06-25 01:24:15,116 - pyskl - INFO - Saving checkpoint at 95 epochs +2025-06-25 01:25:02,859 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:25:02,915 - pyskl - INFO - +top1_acc 0.8899 +top5_acc 0.9938 +2025-06-25 01:25:02,915 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:25:02,922 - pyskl - INFO - +mean_acc 0.8417 +2025-06-25 01:25:02,926 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_94.pth was removed +2025-06-25 01:25:03,105 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_95.pth. +2025-06-25 01:25:03,106 - pyskl - INFO - Best top1_acc is 0.8899 at 95 epoch. +2025-06-25 01:25:03,108 - pyskl - INFO - Epoch(val) [95][533] top1_acc: 0.8899, top5_acc: 0.9938, mean_class_accuracy: 0.8417 +2025-06-25 01:26:23,301 - pyskl - INFO - Epoch [96][100/1281] lr: 7.397e-03, eta: 8:17:06, time: 0.802, data_time: 0.193, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2230, loss: 0.2230 +2025-06-25 01:27:12,462 - pyskl - INFO - Epoch [96][200/1281] lr: 7.379e-03, eta: 8:16:28, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.1881, loss: 0.1881 +2025-06-25 01:28:01,271 - pyskl - INFO - Epoch [96][300/1281] lr: 7.360e-03, eta: 8:15:49, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 0.2275, loss: 0.2275 +2025-06-25 01:28:50,610 - pyskl - INFO - Epoch [96][400/1281] lr: 7.341e-03, eta: 8:15:11, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 0.9988, loss_cls: 0.2259, loss: 0.2259 +2025-06-25 01:29:39,750 - pyskl - INFO - Epoch [96][500/1281] lr: 7.323e-03, eta: 8:14:32, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 0.9981, loss_cls: 0.2461, loss: 0.2461 +2025-06-25 01:30:28,352 - pyskl - INFO - Epoch [96][600/1281] lr: 7.304e-03, eta: 8:13:53, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9994, loss_cls: 0.2380, loss: 0.2380 +2025-06-25 01:31:17,170 - pyskl - INFO - Epoch [96][700/1281] lr: 7.286e-03, eta: 8:13:14, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9994, loss_cls: 0.2801, loss: 0.2801 +2025-06-25 01:32:06,187 - pyskl - INFO - Epoch [96][800/1281] lr: 7.267e-03, eta: 8:12:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 0.9994, loss_cls: 0.2339, loss: 0.2339 +2025-06-25 01:32:55,414 - pyskl - INFO - Epoch [96][900/1281] lr: 7.249e-03, eta: 8:11:57, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2441, loss: 0.2441 +2025-06-25 01:33:44,271 - pyskl - INFO - Epoch [96][1000/1281] lr: 7.230e-03, eta: 8:11:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9988, loss_cls: 0.3077, loss: 0.3077 +2025-06-25 01:34:33,035 - pyskl - INFO - Epoch [96][1100/1281] lr: 7.211e-03, eta: 8:10:39, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9988, loss_cls: 0.3489, loss: 0.3489 +2025-06-25 01:35:09,106 - pyskl - INFO - Epoch [96][1200/1281] lr: 7.193e-03, eta: 8:09:53, time: 0.361, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 0.9994, loss_cls: 0.2905, loss: 0.2905 +2025-06-25 01:35:53,754 - pyskl - INFO - Saving checkpoint at 96 epochs +2025-06-25 01:36:41,225 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:36:41,281 - pyskl - INFO - +top1_acc 0.8825 +top5_acc 0.9913 +2025-06-25 01:36:41,282 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:36:41,288 - pyskl - INFO - +mean_acc 0.8429 +2025-06-25 01:36:41,290 - pyskl - INFO - Epoch(val) [96][533] top1_acc: 0.8825, top5_acc: 0.9913, mean_class_accuracy: 0.8429 +2025-06-25 01:38:00,550 - pyskl - INFO - Epoch [97][100/1281] lr: 7.159e-03, eta: 8:08:38, time: 0.793, data_time: 0.191, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.2367, loss: 0.2367 +2025-06-25 01:38:49,552 - pyskl - INFO - Epoch [97][200/1281] lr: 7.141e-03, eta: 8:07:59, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 0.2284, loss: 0.2284 +2025-06-25 01:39:38,539 - pyskl - INFO - Epoch [97][300/1281] lr: 7.123e-03, eta: 8:07:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9994, loss_cls: 0.2662, loss: 0.2662 +2025-06-25 01:40:27,731 - pyskl - INFO - Epoch [97][400/1281] lr: 7.104e-03, eta: 8:06:42, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9988, loss_cls: 0.2640, loss: 0.2640 +2025-06-25 01:41:16,813 - pyskl - INFO - Epoch [97][500/1281] lr: 7.086e-03, eta: 8:06:03, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1963, loss: 0.1963 +2025-06-25 01:42:05,492 - pyskl - INFO - Epoch [97][600/1281] lr: 7.067e-03, eta: 8:05:24, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.2123, loss: 0.2123 +2025-06-25 01:42:54,570 - pyskl - INFO - Epoch [97][700/1281] lr: 7.049e-03, eta: 8:04:45, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2376, loss: 0.2376 +2025-06-25 01:43:43,800 - pyskl - INFO - Epoch [97][800/1281] lr: 7.030e-03, eta: 8:04:06, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 1.0000, loss_cls: 0.2726, loss: 0.2726 +2025-06-25 01:44:32,745 - pyskl - INFO - Epoch [97][900/1281] lr: 7.012e-03, eta: 8:03:27, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9988, loss_cls: 0.2535, loss: 0.2535 +2025-06-25 01:45:21,713 - pyskl - INFO - Epoch [97][1000/1281] lr: 6.994e-03, eta: 8:02:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 1.0000, loss_cls: 0.2925, loss: 0.2925 +2025-06-25 01:46:10,831 - pyskl - INFO - Epoch [97][1100/1281] lr: 6.975e-03, eta: 8:02:10, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 0.2687, loss: 0.2687 +2025-06-25 01:46:48,325 - pyskl - INFO - Epoch [97][1200/1281] lr: 6.957e-03, eta: 8:01:24, time: 0.375, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9975, loss_cls: 0.2882, loss: 0.2882 +2025-06-25 01:47:30,178 - pyskl - INFO - Saving checkpoint at 97 epochs +2025-06-25 01:48:17,534 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:48:17,604 - pyskl - INFO - +top1_acc 0.8730 +top5_acc 0.9900 +2025-06-25 01:48:17,604 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:48:17,612 - pyskl - INFO - +mean_acc 0.8386 +2025-06-25 01:48:17,614 - pyskl - INFO - Epoch(val) [97][533] top1_acc: 0.8730, top5_acc: 0.9900, mean_class_accuracy: 0.8386 +2025-06-25 01:49:37,126 - pyskl - INFO - Epoch [98][100/1281] lr: 6.924e-03, eta: 8:00:09, time: 0.795, data_time: 0.190, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 0.2460, loss: 0.2460 +2025-06-25 01:50:26,111 - pyskl - INFO - Epoch [98][200/1281] lr: 6.906e-03, eta: 7:59:30, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2372, loss: 0.2372 +2025-06-25 01:51:14,851 - pyskl - INFO - Epoch [98][300/1281] lr: 6.887e-03, eta: 7:58:51, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 0.2483, loss: 0.2483 +2025-06-25 01:52:03,698 - pyskl - INFO - Epoch [98][400/1281] lr: 6.869e-03, eta: 7:58:12, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.2230, loss: 0.2230 +2025-06-25 01:52:52,817 - pyskl - INFO - Epoch [98][500/1281] lr: 6.851e-03, eta: 7:57:33, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.2011, loss: 0.2011 +2025-06-25 01:53:42,083 - pyskl - INFO - Epoch [98][600/1281] lr: 6.833e-03, eta: 7:56:54, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.2264, loss: 0.2264 +2025-06-25 01:54:31,503 - pyskl - INFO - Epoch [98][700/1281] lr: 6.814e-03, eta: 7:56:15, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2225, loss: 0.2225 +2025-06-25 01:55:20,473 - pyskl - INFO - Epoch [98][800/1281] lr: 6.796e-03, eta: 7:55:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 0.2367, loss: 0.2367 +2025-06-25 01:56:09,231 - pyskl - INFO - Epoch [98][900/1281] lr: 6.778e-03, eta: 7:54:57, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 0.9994, loss_cls: 0.2455, loss: 0.2455 +2025-06-25 01:56:58,124 - pyskl - INFO - Epoch [98][1000/1281] lr: 6.760e-03, eta: 7:54:18, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2026, loss: 0.2026 +2025-06-25 01:57:46,813 - pyskl - INFO - Epoch [98][1100/1281] lr: 6.742e-03, eta: 7:53:38, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2285, loss: 0.2285 +2025-06-25 01:58:24,018 - pyskl - INFO - Epoch [98][1200/1281] lr: 6.724e-03, eta: 7:52:53, time: 0.372, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2359, loss: 0.2359 +2025-06-25 01:59:06,279 - pyskl - INFO - Saving checkpoint at 98 epochs +2025-06-25 01:59:53,702 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:59:53,778 - pyskl - INFO - +top1_acc 0.8849 +top5_acc 0.9926 +2025-06-25 01:59:53,778 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:59:53,787 - pyskl - INFO - +mean_acc 0.8372 +2025-06-25 01:59:53,789 - pyskl - INFO - Epoch(val) [98][533] top1_acc: 0.8849, top5_acc: 0.9926, mean_class_accuracy: 0.8372 +2025-06-25 02:01:13,793 - pyskl - INFO - Epoch [99][100/1281] lr: 6.691e-03, eta: 7:51:38, time: 0.800, data_time: 0.188, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1929, loss: 0.1929 +2025-06-25 02:02:02,528 - pyskl - INFO - Epoch [99][200/1281] lr: 6.673e-03, eta: 7:50:58, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1629, loss: 0.1629 +2025-06-25 02:02:51,517 - pyskl - INFO - Epoch [99][300/1281] lr: 6.655e-03, eta: 7:50:19, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 0.9994, loss_cls: 0.1595, loss: 0.1595 +2025-06-25 02:03:40,537 - pyskl - INFO - Epoch [99][400/1281] lr: 6.637e-03, eta: 7:49:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 0.9994, loss_cls: 0.1774, loss: 0.1774 +2025-06-25 02:04:29,540 - pyskl - INFO - Epoch [99][500/1281] lr: 6.619e-03, eta: 7:49:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1630, loss: 0.1630 +2025-06-25 02:05:18,709 - pyskl - INFO - Epoch [99][600/1281] lr: 6.601e-03, eta: 7:48:22, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 0.2241, loss: 0.2241 +2025-06-25 02:06:08,053 - pyskl - INFO - Epoch [99][700/1281] lr: 6.583e-03, eta: 7:47:43, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.2041, loss: 0.2041 +2025-06-25 02:06:56,904 - pyskl - INFO - Epoch [99][800/1281] lr: 6.565e-03, eta: 7:47:03, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1802, loss: 0.1802 +2025-06-25 02:07:46,137 - pyskl - INFO - Epoch [99][900/1281] lr: 6.547e-03, eta: 7:46:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9994, loss_cls: 0.2405, loss: 0.2405 +2025-06-25 02:08:34,869 - pyskl - INFO - Epoch [99][1000/1281] lr: 6.529e-03, eta: 7:45:45, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2186, loss: 0.2186 +2025-06-25 02:09:24,031 - pyskl - INFO - Epoch [99][1100/1281] lr: 6.511e-03, eta: 7:45:06, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2192, loss: 0.2192 +2025-06-25 02:10:00,351 - pyskl - INFO - Epoch [99][1200/1281] lr: 6.493e-03, eta: 7:44:20, time: 0.363, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 0.2523, loss: 0.2523 +2025-06-25 02:10:45,631 - pyskl - INFO - Saving checkpoint at 99 epochs +2025-06-25 02:11:34,167 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:11:34,234 - pyskl - INFO - +top1_acc 0.8662 +top5_acc 0.9883 +2025-06-25 02:11:34,234 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:11:34,242 - pyskl - INFO - +mean_acc 0.8321 +2025-06-25 02:11:34,244 - pyskl - INFO - Epoch(val) [99][533] top1_acc: 0.8662, top5_acc: 0.9883, mean_class_accuracy: 0.8321 +2025-06-25 02:12:52,550 - pyskl - INFO - Epoch [100][100/1281] lr: 6.460e-03, eta: 7:43:03, time: 0.783, data_time: 0.193, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1702, loss: 0.1702 +2025-06-25 02:13:41,534 - pyskl - INFO - Epoch [100][200/1281] lr: 6.442e-03, eta: 7:42:24, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 0.2035, loss: 0.2035 +2025-06-25 02:14:30,740 - pyskl - INFO - Epoch [100][300/1281] lr: 6.425e-03, eta: 7:41:45, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2132, loss: 0.2132 +2025-06-25 02:15:19,693 - pyskl - INFO - Epoch [100][400/1281] lr: 6.407e-03, eta: 7:41:05, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 0.9994, loss_cls: 0.2198, loss: 0.2198 +2025-06-25 02:16:08,688 - pyskl - INFO - Epoch [100][500/1281] lr: 6.389e-03, eta: 7:40:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9994, loss_cls: 0.2422, loss: 0.2422 +2025-06-25 02:16:57,877 - pyskl - INFO - Epoch [100][600/1281] lr: 6.371e-03, eta: 7:39:47, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 0.9994, loss_cls: 0.2316, loss: 0.2316 +2025-06-25 02:17:47,223 - pyskl - INFO - Epoch [100][700/1281] lr: 6.353e-03, eta: 7:39:08, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9988, loss_cls: 0.2424, loss: 0.2424 +2025-06-25 02:18:36,385 - pyskl - INFO - Epoch [100][800/1281] lr: 6.336e-03, eta: 7:38:28, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 0.1978, loss: 0.1978 +2025-06-25 02:19:25,649 - pyskl - INFO - Epoch [100][900/1281] lr: 6.318e-03, eta: 7:37:49, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1993, loss: 0.1993 +2025-06-25 02:20:15,051 - pyskl - INFO - Epoch [100][1000/1281] lr: 6.300e-03, eta: 7:37:10, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9994, loss_cls: 0.2399, loss: 0.2399 +2025-06-25 02:21:04,066 - pyskl - INFO - Epoch [100][1100/1281] lr: 6.282e-03, eta: 7:36:30, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 0.9994, loss_cls: 0.2379, loss: 0.2379 +2025-06-25 02:21:42,129 - pyskl - INFO - Epoch [100][1200/1281] lr: 6.265e-03, eta: 7:35:45, time: 0.381, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.2666, loss: 0.2666 +2025-06-25 02:22:23,571 - pyskl - INFO - Saving checkpoint at 100 epochs +2025-06-25 02:23:10,729 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:23:10,786 - pyskl - INFO - +top1_acc 0.8852 +top5_acc 0.9935 +2025-06-25 02:23:10,786 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:23:10,793 - pyskl - INFO - +mean_acc 0.8541 +2025-06-25 02:23:10,795 - pyskl - INFO - Epoch(val) [100][533] top1_acc: 0.8852, top5_acc: 0.9935, mean_class_accuracy: 0.8541 +2025-06-25 02:24:30,449 - pyskl - INFO - Epoch [101][100/1281] lr: 6.232e-03, eta: 7:34:29, time: 0.796, data_time: 0.192, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.2186, loss: 0.2186 +2025-06-25 02:25:19,700 - pyskl - INFO - Epoch [101][200/1281] lr: 6.215e-03, eta: 7:33:50, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.2106, loss: 0.2106 +2025-06-25 02:26:09,006 - pyskl - INFO - Epoch [101][300/1281] lr: 6.197e-03, eta: 7:33:11, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1983, loss: 0.1983 +2025-06-25 02:26:58,004 - pyskl - INFO - Epoch [101][400/1281] lr: 6.180e-03, eta: 7:32:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 0.2087, loss: 0.2087 +2025-06-25 02:27:47,218 - pyskl - INFO - Epoch [101][500/1281] lr: 6.162e-03, eta: 7:31:52, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1432, loss: 0.1432 +2025-06-25 02:28:36,062 - pyskl - INFO - Epoch [101][600/1281] lr: 6.144e-03, eta: 7:31:12, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1919, loss: 0.1919 +2025-06-25 02:29:25,314 - pyskl - INFO - Epoch [101][700/1281] lr: 6.127e-03, eta: 7:30:33, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9994, loss_cls: 0.2735, loss: 0.2735 +2025-06-25 02:30:14,457 - pyskl - INFO - Epoch [101][800/1281] lr: 6.109e-03, eta: 7:29:53, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 0.9994, loss_cls: 0.2113, loss: 0.2113 +2025-06-25 02:31:03,514 - pyskl - INFO - Epoch [101][900/1281] lr: 6.092e-03, eta: 7:29:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.2697, loss: 0.2697 +2025-06-25 02:31:52,523 - pyskl - INFO - Epoch [101][1000/1281] lr: 6.074e-03, eta: 7:28:34, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.2141, loss: 0.2141 +2025-06-25 02:32:41,687 - pyskl - INFO - Epoch [101][1100/1281] lr: 6.057e-03, eta: 7:27:55, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2168, loss: 0.2168 +2025-06-25 02:33:18,619 - pyskl - INFO - Epoch [101][1200/1281] lr: 6.039e-03, eta: 7:27:09, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 0.2897, loss: 0.2897 +2025-06-25 02:34:01,530 - pyskl - INFO - Saving checkpoint at 101 epochs +2025-06-25 02:34:49,092 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:34:49,147 - pyskl - INFO - +top1_acc 0.8823 +top5_acc 0.9918 +2025-06-25 02:34:49,147 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:34:49,153 - pyskl - INFO - +mean_acc 0.8324 +2025-06-25 02:34:49,155 - pyskl - INFO - Epoch(val) [101][533] top1_acc: 0.8823, top5_acc: 0.9918, mean_class_accuracy: 0.8324 +2025-06-25 02:36:08,282 - pyskl - INFO - Epoch [102][100/1281] lr: 6.007e-03, eta: 7:25:53, time: 0.791, data_time: 0.183, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1888, loss: 0.1888 +2025-06-25 02:36:57,290 - pyskl - INFO - Epoch [102][200/1281] lr: 5.990e-03, eta: 7:25:13, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1876, loss: 0.1876 +2025-06-25 02:37:46,312 - pyskl - INFO - Epoch [102][300/1281] lr: 5.972e-03, eta: 7:24:33, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1912, loss: 0.1912 +2025-06-25 02:38:35,514 - pyskl - INFO - Epoch [102][400/1281] lr: 5.955e-03, eta: 7:23:54, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 0.9988, loss_cls: 0.2125, loss: 0.2125 +2025-06-25 02:39:24,538 - pyskl - INFO - Epoch [102][500/1281] lr: 5.938e-03, eta: 7:23:14, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 0.9994, loss_cls: 0.2050, loss: 0.2050 +2025-06-25 02:40:13,645 - pyskl - INFO - Epoch [102][600/1281] lr: 5.920e-03, eta: 7:22:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 0.9994, loss_cls: 0.2324, loss: 0.2324 +2025-06-25 02:41:02,755 - pyskl - INFO - Epoch [102][700/1281] lr: 5.903e-03, eta: 7:21:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 0.9994, loss_cls: 0.2121, loss: 0.2121 +2025-06-25 02:41:51,867 - pyskl - INFO - Epoch [102][800/1281] lr: 5.886e-03, eta: 7:21:15, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 0.2132, loss: 0.2132 +2025-06-25 02:42:40,855 - pyskl - INFO - Epoch [102][900/1281] lr: 5.868e-03, eta: 7:20:35, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2577, loss: 0.2577 +2025-06-25 02:43:30,097 - pyskl - INFO - Epoch [102][1000/1281] lr: 5.851e-03, eta: 7:19:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 0.2353, loss: 0.2353 +2025-06-25 02:44:19,462 - pyskl - INFO - Epoch [102][1100/1281] lr: 5.834e-03, eta: 7:19:16, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 0.9988, loss_cls: 0.1957, loss: 0.1957 +2025-06-25 02:44:57,483 - pyskl - INFO - Epoch [102][1200/1281] lr: 5.816e-03, eta: 7:18:31, time: 0.380, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1913, loss: 0.1913 +2025-06-25 02:45:41,221 - pyskl - INFO - Saving checkpoint at 102 epochs +2025-06-25 02:46:29,036 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:46:29,097 - pyskl - INFO - +top1_acc 0.8925 +top5_acc 0.9933 +2025-06-25 02:46:29,097 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:46:29,103 - pyskl - INFO - +mean_acc 0.8512 +2025-06-25 02:46:29,108 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_95.pth was removed +2025-06-25 02:46:29,274 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_102.pth. +2025-06-25 02:46:29,274 - pyskl - INFO - Best top1_acc is 0.8925 at 102 epoch. +2025-06-25 02:46:29,277 - pyskl - INFO - Epoch(val) [102][533] top1_acc: 0.8925, top5_acc: 0.9933, mean_class_accuracy: 0.8512 +2025-06-25 02:47:48,323 - pyskl - INFO - Epoch [103][100/1281] lr: 5.785e-03, eta: 7:17:15, time: 0.790, data_time: 0.182, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1996, loss: 0.1996 +2025-06-25 02:48:37,247 - pyskl - INFO - Epoch [103][200/1281] lr: 5.768e-03, eta: 7:16:35, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1571, loss: 0.1571 +2025-06-25 02:49:26,483 - pyskl - INFO - Epoch [103][300/1281] lr: 5.751e-03, eta: 7:15:55, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 0.9994, loss_cls: 0.1839, loss: 0.1839 +2025-06-25 02:50:15,337 - pyskl - INFO - Epoch [103][400/1281] lr: 5.733e-03, eta: 7:15:15, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 0.1749, loss: 0.1749 +2025-06-25 02:51:04,705 - pyskl - INFO - Epoch [103][500/1281] lr: 5.716e-03, eta: 7:14:36, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1390, loss: 0.1390 +2025-06-25 02:51:53,833 - pyskl - INFO - Epoch [103][600/1281] lr: 5.699e-03, eta: 7:13:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1819, loss: 0.1819 +2025-06-25 02:52:42,783 - pyskl - INFO - Epoch [103][700/1281] lr: 5.682e-03, eta: 7:13:16, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 0.9988, loss_cls: 0.1771, loss: 0.1771 +2025-06-25 02:53:31,754 - pyskl - INFO - Epoch [103][800/1281] lr: 5.665e-03, eta: 7:12:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.1830, loss: 0.1830 +2025-06-25 02:54:20,929 - pyskl - INFO - Epoch [103][900/1281] lr: 5.648e-03, eta: 7:11:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 0.9981, loss_cls: 0.1995, loss: 0.1995 +2025-06-25 02:55:10,188 - pyskl - INFO - Epoch [103][1000/1281] lr: 5.631e-03, eta: 7:11:16, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2082, loss: 0.2082 +2025-06-25 02:55:59,435 - pyskl - INFO - Epoch [103][1100/1281] lr: 5.614e-03, eta: 7:10:37, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1719, loss: 0.1719 +2025-06-25 02:56:36,876 - pyskl - INFO - Epoch [103][1200/1281] lr: 5.597e-03, eta: 7:09:51, time: 0.374, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1741, loss: 0.1741 +2025-06-25 02:57:20,315 - pyskl - INFO - Saving checkpoint at 103 epochs +2025-06-25 02:58:07,451 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:58:07,511 - pyskl - INFO - +top1_acc 0.8883 +top5_acc 0.9931 +2025-06-25 02:58:07,511 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:58:07,518 - pyskl - INFO - +mean_acc 0.8584 +2025-06-25 02:58:07,521 - pyskl - INFO - Epoch(val) [103][533] top1_acc: 0.8883, top5_acc: 0.9931, mean_class_accuracy: 0.8584 +2025-06-25 02:59:28,359 - pyskl - INFO - Epoch [104][100/1281] lr: 5.566e-03, eta: 7:08:35, time: 0.808, data_time: 0.195, memory: 4083, top1_acc: 0.9694, top5_acc: 0.9994, loss_cls: 0.1843, loss: 0.1843 +2025-06-25 03:00:17,831 - pyskl - INFO - Epoch [104][200/1281] lr: 5.549e-03, eta: 7:07:56, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1712, loss: 0.1712 +2025-06-25 03:01:06,951 - pyskl - INFO - Epoch [104][300/1281] lr: 5.532e-03, eta: 7:07:16, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1770, loss: 0.1770 +2025-06-25 03:01:56,479 - pyskl - INFO - Epoch [104][400/1281] lr: 5.515e-03, eta: 7:06:36, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1373, loss: 0.1373 +2025-06-25 03:02:46,033 - pyskl - INFO - Epoch [104][500/1281] lr: 5.498e-03, eta: 7:05:56, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.1739, loss: 0.1739 +2025-06-25 03:03:35,200 - pyskl - INFO - Epoch [104][600/1281] lr: 5.481e-03, eta: 7:05:16, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.1827, loss: 0.1827 +2025-06-25 03:04:24,161 - pyskl - INFO - Epoch [104][700/1281] lr: 5.464e-03, eta: 7:04:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1626, loss: 0.1626 +2025-06-25 03:05:13,373 - pyskl - INFO - Epoch [104][800/1281] lr: 5.447e-03, eta: 7:03:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9988, loss_cls: 0.2164, loss: 0.2164 +2025-06-25 03:06:02,225 - pyskl - INFO - Epoch [104][900/1281] lr: 5.430e-03, eta: 7:03:16, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 0.2444, loss: 0.2444 +2025-06-25 03:06:51,483 - pyskl - INFO - Epoch [104][1000/1281] lr: 5.413e-03, eta: 7:02:36, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9994, loss_cls: 0.2237, loss: 0.2237 +2025-06-25 03:07:40,490 - pyskl - INFO - Epoch [104][1100/1281] lr: 5.397e-03, eta: 7:01:56, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1620, loss: 0.1620 +2025-06-25 03:08:16,753 - pyskl - INFO - Epoch [104][1200/1281] lr: 5.380e-03, eta: 7:01:10, time: 0.363, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 0.9988, loss_cls: 0.1793, loss: 0.1793 +2025-06-25 03:09:03,826 - pyskl - INFO - Saving checkpoint at 104 epochs +2025-06-25 03:09:51,948 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:09:52,017 - pyskl - INFO - +top1_acc 0.8939 +top5_acc 0.9930 +2025-06-25 03:09:52,017 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:09:52,025 - pyskl - INFO - +mean_acc 0.8533 +2025-06-25 03:09:52,029 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_102.pth was removed +2025-06-25 03:09:52,197 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_104.pth. +2025-06-25 03:09:52,197 - pyskl - INFO - Best top1_acc is 0.8939 at 104 epoch. +2025-06-25 03:09:52,199 - pyskl - INFO - Epoch(val) [104][533] top1_acc: 0.8939, top5_acc: 0.9930, mean_class_accuracy: 0.8533 +2025-06-25 03:11:12,560 - pyskl - INFO - Epoch [105][100/1281] lr: 5.349e-03, eta: 6:59:54, time: 0.804, data_time: 0.183, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1207, loss: 0.1207 +2025-06-25 03:12:01,622 - pyskl - INFO - Epoch [105][200/1281] lr: 5.333e-03, eta: 6:59:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1618, loss: 0.1618 +2025-06-25 03:12:50,579 - pyskl - INFO - Epoch [105][300/1281] lr: 5.316e-03, eta: 6:58:34, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1340, loss: 0.1340 +2025-06-25 03:13:39,652 - pyskl - INFO - Epoch [105][400/1281] lr: 5.299e-03, eta: 6:57:54, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1349, loss: 0.1349 +2025-06-25 03:14:28,758 - pyskl - INFO - Epoch [105][500/1281] lr: 5.283e-03, eta: 6:57:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1684, loss: 0.1684 +2025-06-25 03:15:17,908 - pyskl - INFO - Epoch [105][600/1281] lr: 5.266e-03, eta: 6:56:34, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 0.9994, loss_cls: 0.1703, loss: 0.1703 +2025-06-25 03:16:06,879 - pyskl - INFO - Epoch [105][700/1281] lr: 5.249e-03, eta: 6:55:53, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1625, loss: 0.1625 +2025-06-25 03:16:56,066 - pyskl - INFO - Epoch [105][800/1281] lr: 5.233e-03, eta: 6:55:13, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.2104, loss: 0.2104 +2025-06-25 03:17:45,439 - pyskl - INFO - Epoch [105][900/1281] lr: 5.216e-03, eta: 6:54:33, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1518, loss: 0.1518 +2025-06-25 03:18:34,914 - pyskl - INFO - Epoch [105][1000/1281] lr: 5.199e-03, eta: 6:53:53, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.1978, loss: 0.1978 +2025-06-25 03:19:24,317 - pyskl - INFO - Epoch [105][1100/1281] lr: 5.183e-03, eta: 6:53:13, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1773, loss: 0.1773 +2025-06-25 03:20:00,441 - pyskl - INFO - Epoch [105][1200/1281] lr: 5.166e-03, eta: 6:52:27, time: 0.361, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 0.9994, loss_cls: 0.1640, loss: 0.1640 +2025-06-25 03:20:46,368 - pyskl - INFO - Saving checkpoint at 105 epochs +2025-06-25 03:21:34,172 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:21:34,227 - pyskl - INFO - +top1_acc 0.9000 +top5_acc 0.9926 +2025-06-25 03:21:34,227 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:21:34,233 - pyskl - INFO - +mean_acc 0.8728 +2025-06-25 03:21:34,237 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_104.pth was removed +2025-06-25 03:21:34,425 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_105.pth. +2025-06-25 03:21:34,425 - pyskl - INFO - Best top1_acc is 0.9000 at 105 epoch. +2025-06-25 03:21:34,428 - pyskl - INFO - Epoch(val) [105][533] top1_acc: 0.9000, top5_acc: 0.9926, mean_class_accuracy: 0.8728 +2025-06-25 03:22:53,447 - pyskl - INFO - Epoch [106][100/1281] lr: 5.136e-03, eta: 6:51:10, time: 0.790, data_time: 0.186, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1503, loss: 0.1503 +2025-06-25 03:23:42,562 - pyskl - INFO - Epoch [106][200/1281] lr: 5.120e-03, eta: 6:50:30, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 0.9994, loss_cls: 0.1522, loss: 0.1522 +2025-06-25 03:24:32,250 - pyskl - INFO - Epoch [106][300/1281] lr: 5.103e-03, eta: 6:49:50, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1421, loss: 0.1421 +2025-06-25 03:25:21,480 - pyskl - INFO - Epoch [106][400/1281] lr: 5.087e-03, eta: 6:49:10, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1569, loss: 0.1569 +2025-06-25 03:26:10,279 - pyskl - INFO - Epoch [106][500/1281] lr: 5.070e-03, eta: 6:48:30, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1054, loss: 0.1054 +2025-06-25 03:26:59,419 - pyskl - INFO - Epoch [106][600/1281] lr: 5.054e-03, eta: 6:47:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 0.1639, loss: 0.1639 +2025-06-25 03:27:48,628 - pyskl - INFO - Epoch [106][700/1281] lr: 5.038e-03, eta: 6:47:09, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1429, loss: 0.1429 +2025-06-25 03:28:37,929 - pyskl - INFO - Epoch [106][800/1281] lr: 5.021e-03, eta: 6:46:29, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.1833, loss: 0.1833 +2025-06-25 03:29:27,055 - pyskl - INFO - Epoch [106][900/1281] lr: 5.005e-03, eta: 6:45:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1622, loss: 0.1622 +2025-06-25 03:30:16,285 - pyskl - INFO - Epoch [106][1000/1281] lr: 4.988e-03, eta: 6:45:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1964, loss: 0.1964 +2025-06-25 03:31:05,433 - pyskl - INFO - Epoch [106][1100/1281] lr: 4.972e-03, eta: 6:44:28, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1528, loss: 0.1528 +2025-06-25 03:31:42,555 - pyskl - INFO - Epoch [106][1200/1281] lr: 4.956e-03, eta: 6:43:43, time: 0.371, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1731, loss: 0.1731 +2025-06-25 03:32:26,493 - pyskl - INFO - Saving checkpoint at 106 epochs +2025-06-25 03:33:13,867 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:33:13,922 - pyskl - INFO - +top1_acc 0.8900 +top5_acc 0.9937 +2025-06-25 03:33:13,922 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:33:13,928 - pyskl - INFO - +mean_acc 0.8456 +2025-06-25 03:33:13,930 - pyskl - INFO - Epoch(val) [106][533] top1_acc: 0.8900, top5_acc: 0.9937, mean_class_accuracy: 0.8456 +2025-06-25 03:34:34,498 - pyskl - INFO - Epoch [107][100/1281] lr: 4.926e-03, eta: 6:42:26, time: 0.806, data_time: 0.188, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1293, loss: 0.1293 +2025-06-25 03:35:23,689 - pyskl - INFO - Epoch [107][200/1281] lr: 4.910e-03, eta: 6:41:46, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1337, loss: 0.1337 +2025-06-25 03:36:13,056 - pyskl - INFO - Epoch [107][300/1281] lr: 4.894e-03, eta: 6:41:06, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1257, loss: 0.1257 +2025-06-25 03:37:02,294 - pyskl - INFO - Epoch [107][400/1281] lr: 4.878e-03, eta: 6:40:25, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1362, loss: 0.1362 +2025-06-25 03:37:51,518 - pyskl - INFO - Epoch [107][500/1281] lr: 4.862e-03, eta: 6:39:45, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1360, loss: 0.1360 +2025-06-25 03:38:40,625 - pyskl - INFO - Epoch [107][600/1281] lr: 4.845e-03, eta: 6:39:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1664, loss: 0.1664 +2025-06-25 03:39:30,127 - pyskl - INFO - Epoch [107][700/1281] lr: 4.829e-03, eta: 6:38:24, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1478, loss: 0.1478 +2025-06-25 03:40:19,235 - pyskl - INFO - Epoch [107][800/1281] lr: 4.813e-03, eta: 6:37:44, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1772, loss: 0.1772 +2025-06-25 03:41:08,154 - pyskl - INFO - Epoch [107][900/1281] lr: 4.797e-03, eta: 6:37:03, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 0.9994, loss_cls: 0.1843, loss: 0.1843 +2025-06-25 03:41:57,399 - pyskl - INFO - Epoch [107][1000/1281] lr: 4.781e-03, eta: 6:36:23, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1467, loss: 0.1467 +2025-06-25 03:42:46,345 - pyskl - INFO - Epoch [107][1100/1281] lr: 4.765e-03, eta: 6:35:42, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1521, loss: 0.1521 +2025-06-25 03:43:22,381 - pyskl - INFO - Epoch [107][1200/1281] lr: 4.749e-03, eta: 6:34:57, time: 0.360, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 0.9994, loss_cls: 0.1739, loss: 0.1739 +2025-06-25 03:44:08,384 - pyskl - INFO - Saving checkpoint at 107 epochs +2025-06-25 03:44:55,978 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:44:56,047 - pyskl - INFO - +top1_acc 0.9007 +top5_acc 0.9933 +2025-06-25 03:44:56,048 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:44:56,059 - pyskl - INFO - +mean_acc 0.8607 +2025-06-25 03:44:56,064 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_105.pth was removed +2025-06-25 03:44:56,242 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_107.pth. +2025-06-25 03:44:56,242 - pyskl - INFO - Best top1_acc is 0.9007 at 107 epoch. +2025-06-25 03:44:56,245 - pyskl - INFO - Epoch(val) [107][533] top1_acc: 0.9007, top5_acc: 0.9933, mean_class_accuracy: 0.8607 +2025-06-25 03:46:14,889 - pyskl - INFO - Epoch [108][100/1281] lr: 4.720e-03, eta: 6:33:39, time: 0.786, data_time: 0.180, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1209, loss: 0.1209 +2025-06-25 03:47:04,335 - pyskl - INFO - Epoch [108][200/1281] lr: 4.704e-03, eta: 6:32:59, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.1034, loss: 0.1034 +2025-06-25 03:47:53,361 - pyskl - INFO - Epoch [108][300/1281] lr: 4.688e-03, eta: 6:32:18, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 0.9994, loss_cls: 0.1236, loss: 0.1236 +2025-06-25 03:48:42,311 - pyskl - INFO - Epoch [108][400/1281] lr: 4.672e-03, eta: 6:31:38, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0922, loss: 0.0922 +2025-06-25 03:49:31,555 - pyskl - INFO - Epoch [108][500/1281] lr: 4.656e-03, eta: 6:30:57, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1536, loss: 0.1536 +2025-06-25 03:50:20,736 - pyskl - INFO - Epoch [108][600/1281] lr: 4.640e-03, eta: 6:30:17, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.1096, loss: 0.1096 +2025-06-25 03:51:09,729 - pyskl - INFO - Epoch [108][700/1281] lr: 4.624e-03, eta: 6:29:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1138, loss: 0.1138 +2025-06-25 03:51:59,098 - pyskl - INFO - Epoch [108][800/1281] lr: 4.608e-03, eta: 6:28:56, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0957, loss: 0.0957 +2025-06-25 03:52:48,304 - pyskl - INFO - Epoch [108][900/1281] lr: 4.593e-03, eta: 6:28:15, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 0.9994, loss_cls: 0.1588, loss: 0.1588 +2025-06-25 03:53:37,552 - pyskl - INFO - Epoch [108][1000/1281] lr: 4.577e-03, eta: 6:27:35, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1405, loss: 0.1405 +2025-06-25 03:54:27,007 - pyskl - INFO - Epoch [108][1100/1281] lr: 4.561e-03, eta: 6:26:54, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1227, loss: 0.1227 +2025-06-25 03:55:04,988 - pyskl - INFO - Epoch [108][1200/1281] lr: 4.545e-03, eta: 6:26:09, time: 0.380, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 0.9988, loss_cls: 0.1905, loss: 0.1905 +2025-06-25 03:55:47,059 - pyskl - INFO - Saving checkpoint at 108 epochs +2025-06-25 03:56:35,279 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:56:35,334 - pyskl - INFO - +top1_acc 0.9000 +top5_acc 0.9934 +2025-06-25 03:56:35,334 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:56:35,341 - pyskl - INFO - +mean_acc 0.8679 +2025-06-25 03:56:35,343 - pyskl - INFO - Epoch(val) [108][533] top1_acc: 0.9000, top5_acc: 0.9934, mean_class_accuracy: 0.8679 +2025-06-25 03:57:54,215 - pyskl - INFO - Epoch [109][100/1281] lr: 4.517e-03, eta: 6:24:52, time: 0.789, data_time: 0.188, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1256, loss: 0.1256 +2025-06-25 03:58:43,505 - pyskl - INFO - Epoch [109][200/1281] lr: 4.501e-03, eta: 6:24:11, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1017, loss: 0.1017 +2025-06-25 03:59:33,127 - pyskl - INFO - Epoch [109][300/1281] lr: 4.485e-03, eta: 6:23:31, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0995, loss: 0.0995 +2025-06-25 04:00:22,656 - pyskl - INFO - Epoch [109][400/1281] lr: 4.470e-03, eta: 6:22:50, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.1075, loss: 0.1075 +2025-06-25 04:01:11,757 - pyskl - INFO - Epoch [109][500/1281] lr: 4.454e-03, eta: 6:22:09, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0861, loss: 0.0861 +2025-06-25 04:02:00,654 - pyskl - INFO - Epoch [109][600/1281] lr: 4.438e-03, eta: 6:21:29, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0970, loss: 0.0970 +2025-06-25 04:02:49,657 - pyskl - INFO - Epoch [109][700/1281] lr: 4.423e-03, eta: 6:20:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 0.9994, loss_cls: 0.1356, loss: 0.1356 +2025-06-25 04:03:38,510 - pyskl - INFO - Epoch [109][800/1281] lr: 4.407e-03, eta: 6:20:07, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1339, loss: 0.1339 +2025-06-25 04:04:27,360 - pyskl - INFO - Epoch [109][900/1281] lr: 4.391e-03, eta: 6:19:26, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1320, loss: 0.1320 +2025-06-25 04:05:16,498 - pyskl - INFO - Epoch [109][1000/1281] lr: 4.376e-03, eta: 6:18:46, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1720, loss: 0.1720 +2025-06-25 04:06:05,888 - pyskl - INFO - Epoch [109][1100/1281] lr: 4.360e-03, eta: 6:18:05, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1225, loss: 0.1225 +2025-06-25 04:06:43,696 - pyskl - INFO - Epoch [109][1200/1281] lr: 4.345e-03, eta: 6:17:20, time: 0.378, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1393, loss: 0.1393 +2025-06-25 04:07:24,993 - pyskl - INFO - Saving checkpoint at 109 epochs +2025-06-25 04:08:12,335 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:08:12,403 - pyskl - INFO - +top1_acc 0.9005 +top5_acc 0.9933 +2025-06-25 04:08:12,403 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:08:12,410 - pyskl - INFO - +mean_acc 0.8661 +2025-06-25 04:08:12,411 - pyskl - INFO - Epoch(val) [109][533] top1_acc: 0.9005, top5_acc: 0.9933, mean_class_accuracy: 0.8661 +2025-06-25 04:09:32,237 - pyskl - INFO - Epoch [110][100/1281] lr: 4.317e-03, eta: 6:16:03, time: 0.798, data_time: 0.189, memory: 4083, top1_acc: 0.9869, top5_acc: 0.9994, loss_cls: 0.1089, loss: 0.1089 +2025-06-25 04:10:21,307 - pyskl - INFO - Epoch [110][200/1281] lr: 4.301e-03, eta: 6:15:22, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 0.9994, loss_cls: 0.1240, loss: 0.1240 +2025-06-25 04:11:10,523 - pyskl - INFO - Epoch [110][300/1281] lr: 4.286e-03, eta: 6:14:41, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1356, loss: 0.1356 +2025-06-25 04:11:59,815 - pyskl - INFO - Epoch [110][400/1281] lr: 4.271e-03, eta: 6:14:01, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 0.9994, loss_cls: 0.1469, loss: 0.1469 +2025-06-25 04:12:48,507 - pyskl - INFO - Epoch [110][500/1281] lr: 4.255e-03, eta: 6:13:20, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1266, loss: 0.1266 +2025-06-25 04:13:37,708 - pyskl - INFO - Epoch [110][600/1281] lr: 4.240e-03, eta: 6:12:39, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1385, loss: 0.1385 +2025-06-25 04:14:26,938 - pyskl - INFO - Epoch [110][700/1281] lr: 4.225e-03, eta: 6:11:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 0.9994, loss_cls: 0.1861, loss: 0.1861 +2025-06-25 04:15:15,945 - pyskl - INFO - Epoch [110][800/1281] lr: 4.209e-03, eta: 6:11:17, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1379, loss: 0.1379 +2025-06-25 04:16:05,023 - pyskl - INFO - Epoch [110][900/1281] lr: 4.194e-03, eta: 6:10:36, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1153, loss: 0.1153 +2025-06-25 04:16:54,340 - pyskl - INFO - Epoch [110][1000/1281] lr: 4.179e-03, eta: 6:09:55, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1134, loss: 0.1134 +2025-06-25 04:17:43,681 - pyskl - INFO - Epoch [110][1100/1281] lr: 4.164e-03, eta: 6:09:15, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 0.9994, loss_cls: 0.1203, loss: 0.1203 +2025-06-25 04:18:20,575 - pyskl - INFO - Epoch [110][1200/1281] lr: 4.148e-03, eta: 6:08:29, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1139, loss: 0.1139 +2025-06-25 04:19:04,251 - pyskl - INFO - Saving checkpoint at 110 epochs +2025-06-25 04:19:51,605 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:19:51,661 - pyskl - INFO - +top1_acc 0.9040 +top5_acc 0.9945 +2025-06-25 04:19:51,661 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:19:51,668 - pyskl - INFO - +mean_acc 0.8719 +2025-06-25 04:19:51,672 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_107.pth was removed +2025-06-25 04:19:51,992 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_110.pth. +2025-06-25 04:19:51,992 - pyskl - INFO - Best top1_acc is 0.9040 at 110 epoch. +2025-06-25 04:19:51,995 - pyskl - INFO - Epoch(val) [110][533] top1_acc: 0.9040, top5_acc: 0.9945, mean_class_accuracy: 0.8719 +2025-06-25 04:21:10,792 - pyskl - INFO - Epoch [111][100/1281] lr: 4.121e-03, eta: 6:07:12, time: 0.788, data_time: 0.179, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0753, loss: 0.0753 +2025-06-25 04:21:59,910 - pyskl - INFO - Epoch [111][200/1281] lr: 4.106e-03, eta: 6:06:31, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.1009, loss: 0.1009 +2025-06-25 04:22:48,659 - pyskl - INFO - Epoch [111][300/1281] lr: 4.091e-03, eta: 6:05:50, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1145, loss: 0.1145 +2025-06-25 04:23:37,568 - pyskl - INFO - Epoch [111][400/1281] lr: 4.075e-03, eta: 6:05:09, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1187, loss: 0.1187 +2025-06-25 04:24:26,574 - pyskl - INFO - Epoch [111][500/1281] lr: 4.060e-03, eta: 6:04:28, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1294, loss: 0.1294 +2025-06-25 04:25:15,641 - pyskl - INFO - Epoch [111][600/1281] lr: 4.045e-03, eta: 6:03:47, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 0.9994, loss_cls: 0.1138, loss: 0.1138 +2025-06-25 04:26:04,653 - pyskl - INFO - Epoch [111][700/1281] lr: 4.030e-03, eta: 6:03:06, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 0.9994, loss_cls: 0.1124, loss: 0.1124 +2025-06-25 04:26:54,034 - pyskl - INFO - Epoch [111][800/1281] lr: 4.015e-03, eta: 6:02:25, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.1056, loss: 0.1056 +2025-06-25 04:27:43,150 - pyskl - INFO - Epoch [111][900/1281] lr: 4.000e-03, eta: 6:01:44, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1622, loss: 0.1622 +2025-06-25 04:28:32,193 - pyskl - INFO - Epoch [111][1000/1281] lr: 3.985e-03, eta: 6:01:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1317, loss: 0.1317 +2025-06-25 04:29:21,499 - pyskl - INFO - Epoch [111][1100/1281] lr: 3.970e-03, eta: 6:00:22, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1138, loss: 0.1138 +2025-06-25 04:29:59,396 - pyskl - INFO - Epoch [111][1200/1281] lr: 3.955e-03, eta: 5:59:37, time: 0.379, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1099, loss: 0.1099 +2025-06-25 04:30:41,579 - pyskl - INFO - Saving checkpoint at 111 epochs +2025-06-25 04:31:28,545 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:31:28,600 - pyskl - INFO - +top1_acc 0.9045 +top5_acc 0.9935 +2025-06-25 04:31:28,600 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:31:28,607 - pyskl - INFO - +mean_acc 0.8735 +2025-06-25 04:31:28,610 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_110.pth was removed +2025-06-25 04:31:28,782 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_111.pth. +2025-06-25 04:31:28,782 - pyskl - INFO - Best top1_acc is 0.9045 at 111 epoch. +2025-06-25 04:31:28,785 - pyskl - INFO - Epoch(val) [111][533] top1_acc: 0.9045, top5_acc: 0.9935, mean_class_accuracy: 0.8735 +2025-06-25 04:32:48,994 - pyskl - INFO - Epoch [112][100/1281] lr: 3.928e-03, eta: 5:58:20, time: 0.802, data_time: 0.186, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0882, loss: 0.0882 +2025-06-25 04:33:38,243 - pyskl - INFO - Epoch [112][200/1281] lr: 3.914e-03, eta: 5:57:39, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.0935, loss: 0.0935 +2025-06-25 04:34:27,498 - pyskl - INFO - Epoch [112][300/1281] lr: 3.899e-03, eta: 5:56:58, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 0.9994, loss_cls: 0.1590, loss: 0.1590 +2025-06-25 04:35:16,783 - pyskl - INFO - Epoch [112][400/1281] lr: 3.884e-03, eta: 5:56:17, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1536, loss: 0.1536 +2025-06-25 04:36:05,837 - pyskl - INFO - Epoch [112][500/1281] lr: 3.869e-03, eta: 5:55:36, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1193, loss: 0.1193 +2025-06-25 04:36:54,613 - pyskl - INFO - Epoch [112][600/1281] lr: 3.854e-03, eta: 5:54:54, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1130, loss: 0.1130 +2025-06-25 04:37:43,683 - pyskl - INFO - Epoch [112][700/1281] lr: 3.840e-03, eta: 5:54:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1334, loss: 0.1334 +2025-06-25 04:38:33,091 - pyskl - INFO - Epoch [112][800/1281] lr: 3.825e-03, eta: 5:53:32, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1319, loss: 0.1319 +2025-06-25 04:39:22,496 - pyskl - INFO - Epoch [112][900/1281] lr: 3.810e-03, eta: 5:52:51, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1098, loss: 0.1098 +2025-06-25 04:40:11,568 - pyskl - INFO - Epoch [112][1000/1281] lr: 3.795e-03, eta: 5:52:10, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 1.0000, loss_cls: 0.1286, loss: 0.1286 +2025-06-25 04:41:00,850 - pyskl - INFO - Epoch [112][1100/1281] lr: 3.781e-03, eta: 5:51:29, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1316, loss: 0.1316 +2025-06-25 04:41:36,982 - pyskl - INFO - Epoch [112][1200/1281] lr: 3.766e-03, eta: 5:50:44, time: 0.361, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0965, loss: 0.0965 +2025-06-25 04:42:24,168 - pyskl - INFO - Saving checkpoint at 112 epochs +2025-06-25 04:43:12,166 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:43:12,220 - pyskl - INFO - +top1_acc 0.9082 +top5_acc 0.9937 +2025-06-25 04:43:12,220 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:43:12,226 - pyskl - INFO - +mean_acc 0.8763 +2025-06-25 04:43:12,230 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_111.pth was removed +2025-06-25 04:43:12,402 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_112.pth. +2025-06-25 04:43:12,402 - pyskl - INFO - Best top1_acc is 0.9082 at 112 epoch. +2025-06-25 04:43:12,405 - pyskl - INFO - Epoch(val) [112][533] top1_acc: 0.9082, top5_acc: 0.9937, mean_class_accuracy: 0.8763 +2025-06-25 04:44:32,111 - pyskl - INFO - Epoch [113][100/1281] lr: 3.740e-03, eta: 5:49:26, time: 0.797, data_time: 0.186, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0842, loss: 0.0842 +2025-06-25 04:45:21,703 - pyskl - INFO - Epoch [113][200/1281] lr: 3.725e-03, eta: 5:48:45, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0732, loss: 0.0732 +2025-06-25 04:46:10,783 - pyskl - INFO - Epoch [113][300/1281] lr: 3.711e-03, eta: 5:48:04, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.1058, loss: 0.1058 +2025-06-25 04:46:59,506 - pyskl - INFO - Epoch [113][400/1281] lr: 3.696e-03, eta: 5:47:23, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 0.9994, loss_cls: 0.0949, loss: 0.0949 +2025-06-25 04:47:48,630 - pyskl - INFO - Epoch [113][500/1281] lr: 3.682e-03, eta: 5:46:41, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0761, loss: 0.0761 +2025-06-25 04:48:37,975 - pyskl - INFO - Epoch [113][600/1281] lr: 3.667e-03, eta: 5:46:00, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0607, loss: 0.0607 +2025-06-25 04:49:26,863 - pyskl - INFO - Epoch [113][700/1281] lr: 3.653e-03, eta: 5:45:19, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0788, loss: 0.0788 +2025-06-25 04:50:15,889 - pyskl - INFO - Epoch [113][800/1281] lr: 3.638e-03, eta: 5:44:38, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0869, loss: 0.0869 +2025-06-25 04:51:04,780 - pyskl - INFO - Epoch [113][900/1281] lr: 3.624e-03, eta: 5:43:56, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0767, loss: 0.0767 +2025-06-25 04:51:53,924 - pyskl - INFO - Epoch [113][1000/1281] lr: 3.610e-03, eta: 5:43:15, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0653, loss: 0.0653 +2025-06-25 04:52:43,086 - pyskl - INFO - Epoch [113][1100/1281] lr: 3.595e-03, eta: 5:42:34, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0598, loss: 0.0598 +2025-06-25 04:53:19,814 - pyskl - INFO - Epoch [113][1200/1281] lr: 3.581e-03, eta: 5:41:49, time: 0.367, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1147, loss: 0.1147 +2025-06-25 04:54:05,096 - pyskl - INFO - Saving checkpoint at 113 epochs +2025-06-25 04:54:52,764 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:54:52,826 - pyskl - INFO - +top1_acc 0.9085 +top5_acc 0.9951 +2025-06-25 04:54:52,826 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:54:52,832 - pyskl - INFO - +mean_acc 0.8704 +2025-06-25 04:54:52,836 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_112.pth was removed +2025-06-25 04:54:53,000 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_113.pth. +2025-06-25 04:54:53,001 - pyskl - INFO - Best top1_acc is 0.9085 at 113 epoch. +2025-06-25 04:54:53,004 - pyskl - INFO - Epoch(val) [113][533] top1_acc: 0.9085, top5_acc: 0.9951, mean_class_accuracy: 0.8704 +2025-06-25 04:56:12,899 - pyskl - INFO - Epoch [114][100/1281] lr: 3.555e-03, eta: 5:40:31, time: 0.799, data_time: 0.183, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0938, loss: 0.0938 +2025-06-25 04:57:02,422 - pyskl - INFO - Epoch [114][200/1281] lr: 3.541e-03, eta: 5:39:50, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.1023, loss: 0.1023 +2025-06-25 04:57:51,467 - pyskl - INFO - Epoch [114][300/1281] lr: 3.526e-03, eta: 5:39:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0685, loss: 0.0685 +2025-06-25 04:58:40,704 - pyskl - INFO - Epoch [114][400/1281] lr: 3.512e-03, eta: 5:38:27, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0732, loss: 0.0732 +2025-06-25 04:59:29,629 - pyskl - INFO - Epoch [114][500/1281] lr: 3.498e-03, eta: 5:37:46, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1203, loss: 0.1203 +2025-06-25 05:00:18,744 - pyskl - INFO - Epoch [114][600/1281] lr: 3.484e-03, eta: 5:37:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1314, loss: 0.1314 +2025-06-25 05:01:07,855 - pyskl - INFO - Epoch [114][700/1281] lr: 3.470e-03, eta: 5:36:23, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1225, loss: 0.1225 +2025-06-25 05:01:56,270 - pyskl - INFO - Epoch [114][800/1281] lr: 3.456e-03, eta: 5:35:42, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.0919, loss: 0.0919 +2025-06-25 05:02:45,265 - pyskl - INFO - Epoch [114][900/1281] lr: 3.442e-03, eta: 5:35:00, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0650, loss: 0.0650 +2025-06-25 05:03:34,303 - pyskl - INFO - Epoch [114][1000/1281] lr: 3.427e-03, eta: 5:34:19, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0814, loss: 0.0814 +2025-06-25 05:04:23,478 - pyskl - INFO - Epoch [114][1100/1281] lr: 3.413e-03, eta: 5:33:38, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 0.9994, loss_cls: 0.1184, loss: 0.1184 +2025-06-25 05:05:00,259 - pyskl - INFO - Epoch [114][1200/1281] lr: 3.399e-03, eta: 5:32:52, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1083, loss: 0.1083 +2025-06-25 05:05:44,831 - pyskl - INFO - Saving checkpoint at 114 epochs +2025-06-25 05:06:32,080 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:06:32,134 - pyskl - INFO - +top1_acc 0.9114 +top5_acc 0.9957 +2025-06-25 05:06:32,134 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:06:32,140 - pyskl - INFO - +mean_acc 0.8763 +2025-06-25 05:06:32,144 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_113.pth was removed +2025-06-25 05:06:32,315 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_114.pth. +2025-06-25 05:06:32,315 - pyskl - INFO - Best top1_acc is 0.9114 at 114 epoch. +2025-06-25 05:06:32,318 - pyskl - INFO - Epoch(val) [114][533] top1_acc: 0.9114, top5_acc: 0.9957, mean_class_accuracy: 0.8763 +2025-06-25 05:07:53,552 - pyskl - INFO - Epoch [115][100/1281] lr: 3.374e-03, eta: 5:31:35, time: 0.812, data_time: 0.188, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0754, loss: 0.0754 +2025-06-25 05:08:42,975 - pyskl - INFO - Epoch [115][200/1281] lr: 3.360e-03, eta: 5:30:54, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0603, loss: 0.0603 +2025-06-25 05:09:32,211 - pyskl - INFO - Epoch [115][300/1281] lr: 3.346e-03, eta: 5:30:12, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0755, loss: 0.0755 +2025-06-25 05:10:21,475 - pyskl - INFO - Epoch [115][400/1281] lr: 3.332e-03, eta: 5:29:31, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0780, loss: 0.0780 +2025-06-25 05:11:10,829 - pyskl - INFO - Epoch [115][500/1281] lr: 3.318e-03, eta: 5:28:50, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0773, loss: 0.0773 +2025-06-25 05:12:00,025 - pyskl - INFO - Epoch [115][600/1281] lr: 3.305e-03, eta: 5:28:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0745, loss: 0.0745 +2025-06-25 05:12:49,030 - pyskl - INFO - Epoch [115][700/1281] lr: 3.291e-03, eta: 5:27:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1126, loss: 0.1126 +2025-06-25 05:13:38,526 - pyskl - INFO - Epoch [115][800/1281] lr: 3.277e-03, eta: 5:26:45, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0755, loss: 0.0755 +2025-06-25 05:14:27,666 - pyskl - INFO - Epoch [115][900/1281] lr: 3.263e-03, eta: 5:26:04, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0754, loss: 0.0754 +2025-06-25 05:15:16,696 - pyskl - INFO - Epoch [115][1000/1281] lr: 3.249e-03, eta: 5:25:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0914, loss: 0.0914 +2025-06-25 05:16:06,054 - pyskl - INFO - Epoch [115][1100/1281] lr: 3.236e-03, eta: 5:24:41, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1198, loss: 0.1198 +2025-06-25 05:16:40,768 - pyskl - INFO - Epoch [115][1200/1281] lr: 3.222e-03, eta: 5:23:55, time: 0.347, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0890, loss: 0.0890 +2025-06-25 05:17:28,438 - pyskl - INFO - Saving checkpoint at 115 epochs +2025-06-25 05:18:16,701 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:18:16,756 - pyskl - INFO - +top1_acc 0.9066 +top5_acc 0.9948 +2025-06-25 05:18:16,756 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:18:16,763 - pyskl - INFO - +mean_acc 0.8791 +2025-06-25 05:18:16,765 - pyskl - INFO - Epoch(val) [115][533] top1_acc: 0.9066, top5_acc: 0.9948, mean_class_accuracy: 0.8791 +2025-06-25 05:19:37,164 - pyskl - INFO - Epoch [116][100/1281] lr: 3.197e-03, eta: 5:22:37, time: 0.804, data_time: 0.186, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0768, loss: 0.0768 +2025-06-25 05:20:26,214 - pyskl - INFO - Epoch [116][200/1281] lr: 3.184e-03, eta: 5:21:56, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0585, loss: 0.0585 +2025-06-25 05:21:15,437 - pyskl - INFO - Epoch [116][300/1281] lr: 3.170e-03, eta: 5:21:14, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0623, loss: 0.0623 +2025-06-25 05:22:04,331 - pyskl - INFO - Epoch [116][400/1281] lr: 3.156e-03, eta: 5:20:33, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0640, loss: 0.0640 +2025-06-25 05:22:53,142 - pyskl - INFO - Epoch [116][500/1281] lr: 3.143e-03, eta: 5:19:51, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0648, loss: 0.0648 +2025-06-25 05:23:42,192 - pyskl - INFO - Epoch [116][600/1281] lr: 3.129e-03, eta: 5:19:10, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0671, loss: 0.0671 +2025-06-25 05:24:30,770 - pyskl - INFO - Epoch [116][700/1281] lr: 3.116e-03, eta: 5:18:28, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0547, loss: 0.0547 +2025-06-25 05:25:19,993 - pyskl - INFO - Epoch [116][800/1281] lr: 3.102e-03, eta: 5:17:46, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0517, loss: 0.0517 +2025-06-25 05:26:09,097 - pyskl - INFO - Epoch [116][900/1281] lr: 3.089e-03, eta: 5:17:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.0887, loss: 0.0887 +2025-06-25 05:26:58,177 - pyskl - INFO - Epoch [116][1000/1281] lr: 3.075e-03, eta: 5:16:23, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0779, loss: 0.0779 +2025-06-25 05:27:47,057 - pyskl - INFO - Epoch [116][1100/1281] lr: 3.062e-03, eta: 5:15:42, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0836, loss: 0.0836 +2025-06-25 05:28:23,650 - pyskl - INFO - Epoch [116][1200/1281] lr: 3.049e-03, eta: 5:14:56, time: 0.366, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0770, loss: 0.0770 +2025-06-25 05:29:08,609 - pyskl - INFO - Saving checkpoint at 116 epochs +2025-06-25 05:29:56,146 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:29:56,205 - pyskl - INFO - +top1_acc 0.9027 +top5_acc 0.9923 +2025-06-25 05:29:56,205 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:29:56,212 - pyskl - INFO - +mean_acc 0.8628 +2025-06-25 05:29:56,214 - pyskl - INFO - Epoch(val) [116][533] top1_acc: 0.9027, top5_acc: 0.9923, mean_class_accuracy: 0.8628 +2025-06-25 05:31:16,031 - pyskl - INFO - Epoch [117][100/1281] lr: 3.024e-03, eta: 5:13:38, time: 0.798, data_time: 0.191, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0820, loss: 0.0820 +2025-06-25 05:32:05,189 - pyskl - INFO - Epoch [117][200/1281] lr: 3.011e-03, eta: 5:12:57, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.0941, loss: 0.0941 +2025-06-25 05:32:53,973 - pyskl - INFO - Epoch [117][300/1281] lr: 2.998e-03, eta: 5:12:15, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0663, loss: 0.0663 +2025-06-25 05:33:43,328 - pyskl - INFO - Epoch [117][400/1281] lr: 2.984e-03, eta: 5:11:33, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0722, loss: 0.0722 +2025-06-25 05:34:32,566 - pyskl - INFO - Epoch [117][500/1281] lr: 2.971e-03, eta: 5:10:52, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 0.9994, loss_cls: 0.0615, loss: 0.0615 +2025-06-25 05:35:21,418 - pyskl - INFO - Epoch [117][600/1281] lr: 2.958e-03, eta: 5:10:10, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0779, loss: 0.0779 +2025-06-25 05:36:10,404 - pyskl - INFO - Epoch [117][700/1281] lr: 2.945e-03, eta: 5:09:28, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0799, loss: 0.0799 +2025-06-25 05:36:59,756 - pyskl - INFO - Epoch [117][800/1281] lr: 2.932e-03, eta: 5:08:47, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0582, loss: 0.0582 +2025-06-25 05:37:48,833 - pyskl - INFO - Epoch [117][900/1281] lr: 2.919e-03, eta: 5:08:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0577, loss: 0.0577 +2025-06-25 05:38:37,913 - pyskl - INFO - Epoch [117][1000/1281] lr: 2.905e-03, eta: 5:07:23, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.0916, loss: 0.0916 +2025-06-25 05:39:27,201 - pyskl - INFO - Epoch [117][1100/1281] lr: 2.892e-03, eta: 5:06:42, time: 0.493, data_time: 0.001, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0611, loss: 0.0611 +2025-06-25 05:40:03,970 - pyskl - INFO - Epoch [117][1200/1281] lr: 2.879e-03, eta: 5:05:56, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0583, loss: 0.0583 +2025-06-25 05:40:49,166 - pyskl - INFO - Saving checkpoint at 117 epochs +2025-06-25 05:41:36,164 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:41:36,221 - pyskl - INFO - +top1_acc 0.9147 +top5_acc 0.9937 +2025-06-25 05:41:36,221 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:41:36,227 - pyskl - INFO - +mean_acc 0.8818 +2025-06-25 05:41:36,232 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_114.pth was removed +2025-06-25 05:41:36,407 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_117.pth. +2025-06-25 05:41:36,407 - pyskl - INFO - Best top1_acc is 0.9147 at 117 epoch. +2025-06-25 05:41:36,410 - pyskl - INFO - Epoch(val) [117][533] top1_acc: 0.9147, top5_acc: 0.9937, mean_class_accuracy: 0.8818 +2025-06-25 05:42:56,107 - pyskl - INFO - Epoch [118][100/1281] lr: 2.856e-03, eta: 5:04:38, time: 0.797, data_time: 0.183, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0560, loss: 0.0560 +2025-06-25 05:43:45,466 - pyskl - INFO - Epoch [118][200/1281] lr: 2.843e-03, eta: 5:03:57, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0546, loss: 0.0546 +2025-06-25 05:44:34,386 - pyskl - INFO - Epoch [118][300/1281] lr: 2.830e-03, eta: 5:03:15, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0638, loss: 0.0638 +2025-06-25 05:45:23,745 - pyskl - INFO - Epoch [118][400/1281] lr: 2.817e-03, eta: 5:02:33, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0569, loss: 0.0569 +2025-06-25 05:46:12,783 - pyskl - INFO - Epoch [118][500/1281] lr: 2.804e-03, eta: 5:01:52, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0458, loss: 0.0458 +2025-06-25 05:47:01,776 - pyskl - INFO - Epoch [118][600/1281] lr: 2.791e-03, eta: 5:01:10, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0510, loss: 0.0510 +2025-06-25 05:47:50,672 - pyskl - INFO - Epoch [118][700/1281] lr: 2.778e-03, eta: 5:00:28, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0423, loss: 0.0423 +2025-06-25 05:48:39,865 - pyskl - INFO - Epoch [118][800/1281] lr: 2.765e-03, eta: 4:59:46, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0575, loss: 0.0575 +2025-06-25 05:49:29,253 - pyskl - INFO - Epoch [118][900/1281] lr: 2.753e-03, eta: 4:59:04, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0515, loss: 0.0515 +2025-06-25 05:50:18,271 - pyskl - INFO - Epoch [118][1000/1281] lr: 2.740e-03, eta: 4:58:23, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0691, loss: 0.0691 +2025-06-25 05:51:07,758 - pyskl - INFO - Epoch [118][1100/1281] lr: 2.727e-03, eta: 4:57:41, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0529, loss: 0.0529 +2025-06-25 05:51:44,137 - pyskl - INFO - Epoch [118][1200/1281] lr: 2.714e-03, eta: 4:56:56, time: 0.364, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0626, loss: 0.0626 +2025-06-25 05:52:29,479 - pyskl - INFO - Saving checkpoint at 118 epochs +2025-06-25 05:53:17,150 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:53:17,217 - pyskl - INFO - +top1_acc 0.9143 +top5_acc 0.9954 +2025-06-25 05:53:17,217 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:53:17,225 - pyskl - INFO - +mean_acc 0.8793 +2025-06-25 05:53:17,227 - pyskl - INFO - Epoch(val) [118][533] top1_acc: 0.9143, top5_acc: 0.9954, mean_class_accuracy: 0.8793 +2025-06-25 05:54:36,536 - pyskl - INFO - Epoch [119][100/1281] lr: 2.691e-03, eta: 4:55:37, time: 0.793, data_time: 0.187, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0470, loss: 0.0470 +2025-06-25 05:55:25,866 - pyskl - INFO - Epoch [119][200/1281] lr: 2.679e-03, eta: 4:54:55, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0392, loss: 0.0392 +2025-06-25 05:56:15,146 - pyskl - INFO - Epoch [119][300/1281] lr: 2.666e-03, eta: 4:54:14, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0588, loss: 0.0588 +2025-06-25 05:57:04,107 - pyskl - INFO - Epoch [119][400/1281] lr: 2.653e-03, eta: 4:53:32, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0435, loss: 0.0435 +2025-06-25 05:57:53,197 - pyskl - INFO - Epoch [119][500/1281] lr: 2.641e-03, eta: 4:52:50, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0429, loss: 0.0429 +2025-06-25 05:58:42,479 - pyskl - INFO - Epoch [119][600/1281] lr: 2.628e-03, eta: 4:52:08, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0307, loss: 0.0307 +2025-06-25 05:59:31,377 - pyskl - INFO - Epoch [119][700/1281] lr: 2.616e-03, eta: 4:51:26, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0304, loss: 0.0304 +2025-06-25 06:00:20,531 - pyskl - INFO - Epoch [119][800/1281] lr: 2.603e-03, eta: 4:50:44, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0375, loss: 0.0375 +2025-06-25 06:01:09,859 - pyskl - INFO - Epoch [119][900/1281] lr: 2.591e-03, eta: 4:50:02, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0444, loss: 0.0444 +2025-06-25 06:01:58,833 - pyskl - INFO - Epoch [119][1000/1281] lr: 2.578e-03, eta: 4:49:21, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0502, loss: 0.0502 +2025-06-25 06:02:48,400 - pyskl - INFO - Epoch [119][1100/1281] lr: 2.566e-03, eta: 4:48:39, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0487, loss: 0.0487 +2025-06-25 06:03:25,597 - pyskl - INFO - Epoch [119][1200/1281] lr: 2.554e-03, eta: 4:47:54, time: 0.372, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0496, loss: 0.0496 +2025-06-25 06:04:08,955 - pyskl - INFO - Saving checkpoint at 119 epochs +2025-06-25 06:04:56,572 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:04:56,627 - pyskl - INFO - +top1_acc 0.9195 +top5_acc 0.9947 +2025-06-25 06:04:56,627 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:04:56,634 - pyskl - INFO - +mean_acc 0.8877 +2025-06-25 06:04:56,638 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_117.pth was removed +2025-06-25 06:04:56,869 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_119.pth. +2025-06-25 06:04:56,869 - pyskl - INFO - Best top1_acc is 0.9195 at 119 epoch. +2025-06-25 06:04:56,872 - pyskl - INFO - Epoch(val) [119][533] top1_acc: 0.9195, top5_acc: 0.9947, mean_class_accuracy: 0.8877 +2025-06-25 06:06:16,857 - pyskl - INFO - Epoch [120][100/1281] lr: 2.531e-03, eta: 4:46:35, time: 0.800, data_time: 0.192, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0399, loss: 0.0399 +2025-06-25 06:07:05,867 - pyskl - INFO - Epoch [120][200/1281] lr: 2.519e-03, eta: 4:45:54, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0283, loss: 0.0283 +2025-06-25 06:07:55,223 - pyskl - INFO - Epoch [120][300/1281] lr: 2.507e-03, eta: 4:45:12, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0314, loss: 0.0314 +2025-06-25 06:08:44,289 - pyskl - INFO - Epoch [120][400/1281] lr: 2.494e-03, eta: 4:44:30, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0345, loss: 0.0345 +2025-06-25 06:09:33,843 - pyskl - INFO - Epoch [120][500/1281] lr: 2.482e-03, eta: 4:43:48, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0599, loss: 0.0599 +2025-06-25 06:10:23,021 - pyskl - INFO - Epoch [120][600/1281] lr: 2.470e-03, eta: 4:43:06, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0563, loss: 0.0563 +2025-06-25 06:11:12,003 - pyskl - INFO - Epoch [120][700/1281] lr: 2.458e-03, eta: 4:42:24, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0564, loss: 0.0564 +2025-06-25 06:12:01,477 - pyskl - INFO - Epoch [120][800/1281] lr: 2.446e-03, eta: 4:41:42, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0539, loss: 0.0539 +2025-06-25 06:12:50,622 - pyskl - INFO - Epoch [120][900/1281] lr: 2.433e-03, eta: 4:41:00, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0496, loss: 0.0496 +2025-06-25 06:13:39,504 - pyskl - INFO - Epoch [120][1000/1281] lr: 2.421e-03, eta: 4:40:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0508, loss: 0.0508 +2025-06-25 06:14:28,945 - pyskl - INFO - Epoch [120][1100/1281] lr: 2.409e-03, eta: 4:39:36, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0390, loss: 0.0390 +2025-06-25 06:15:04,488 - pyskl - INFO - Epoch [120][1200/1281] lr: 2.397e-03, eta: 4:38:50, time: 0.355, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0376, loss: 0.0376 +2025-06-25 06:15:51,847 - pyskl - INFO - Saving checkpoint at 120 epochs +2025-06-25 06:16:39,912 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:16:39,973 - pyskl - INFO - +top1_acc 0.9201 +top5_acc 0.9951 +2025-06-25 06:16:39,974 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:16:39,981 - pyskl - INFO - +mean_acc 0.8893 +2025-06-25 06:16:39,985 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_119.pth was removed +2025-06-25 06:16:40,156 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_120.pth. +2025-06-25 06:16:40,156 - pyskl - INFO - Best top1_acc is 0.9201 at 120 epoch. +2025-06-25 06:16:40,159 - pyskl - INFO - Epoch(val) [120][533] top1_acc: 0.9201, top5_acc: 0.9951, mean_class_accuracy: 0.8893 +2025-06-25 06:17:59,495 - pyskl - INFO - Epoch [121][100/1281] lr: 2.375e-03, eta: 4:37:32, time: 0.793, data_time: 0.187, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0345, loss: 0.0345 +2025-06-25 06:18:48,481 - pyskl - INFO - Epoch [121][200/1281] lr: 2.363e-03, eta: 4:36:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0390, loss: 0.0390 +2025-06-25 06:19:37,824 - pyskl - INFO - Epoch [121][300/1281] lr: 2.351e-03, eta: 4:36:08, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0327, loss: 0.0327 +2025-06-25 06:20:26,843 - pyskl - INFO - Epoch [121][400/1281] lr: 2.340e-03, eta: 4:35:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0326, loss: 0.0326 +2025-06-25 06:21:15,984 - pyskl - INFO - Epoch [121][500/1281] lr: 2.328e-03, eta: 4:34:44, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0434, loss: 0.0434 +2025-06-25 06:22:05,281 - pyskl - INFO - Epoch [121][600/1281] lr: 2.316e-03, eta: 4:34:02, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0365, loss: 0.0365 +2025-06-25 06:22:54,369 - pyskl - INFO - Epoch [121][700/1281] lr: 2.304e-03, eta: 4:33:20, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0355, loss: 0.0355 +2025-06-25 06:23:43,347 - pyskl - INFO - Epoch [121][800/1281] lr: 2.292e-03, eta: 4:32:38, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0352, loss: 0.0352 +2025-06-25 06:24:32,367 - pyskl - INFO - Epoch [121][900/1281] lr: 2.280e-03, eta: 4:31:55, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0449, loss: 0.0449 +2025-06-25 06:25:21,710 - pyskl - INFO - Epoch [121][1000/1281] lr: 2.269e-03, eta: 4:31:13, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0510, loss: 0.0510 +2025-06-25 06:26:10,824 - pyskl - INFO - Epoch [121][1100/1281] lr: 2.257e-03, eta: 4:30:31, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0364, loss: 0.0364 +2025-06-25 06:26:47,388 - pyskl - INFO - Epoch [121][1200/1281] lr: 2.245e-03, eta: 4:29:46, time: 0.366, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0467, loss: 0.0467 +2025-06-25 06:27:31,310 - pyskl - INFO - Saving checkpoint at 121 epochs +2025-06-25 06:28:19,120 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:28:19,175 - pyskl - INFO - +top1_acc 0.9166 +top5_acc 0.9953 +2025-06-25 06:28:19,175 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:28:19,181 - pyskl - INFO - +mean_acc 0.8817 +2025-06-25 06:28:19,183 - pyskl - INFO - Epoch(val) [121][533] top1_acc: 0.9166, top5_acc: 0.9953, mean_class_accuracy: 0.8817 +2025-06-25 06:29:37,552 - pyskl - INFO - Epoch [122][100/1281] lr: 2.224e-03, eta: 4:28:27, time: 0.784, data_time: 0.188, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0476, loss: 0.0476 +2025-06-25 06:30:26,611 - pyskl - INFO - Epoch [122][200/1281] lr: 2.212e-03, eta: 4:27:45, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0402, loss: 0.0402 +2025-06-25 06:31:15,650 - pyskl - INFO - Epoch [122][300/1281] lr: 2.201e-03, eta: 4:27:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0397, loss: 0.0397 +2025-06-25 06:32:04,914 - pyskl - INFO - Epoch [122][400/1281] lr: 2.189e-03, eta: 4:26:21, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0369, loss: 0.0369 +2025-06-25 06:32:54,375 - pyskl - INFO - Epoch [122][500/1281] lr: 2.178e-03, eta: 4:25:39, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0270, loss: 0.0270 +2025-06-25 06:33:43,651 - pyskl - INFO - Epoch [122][600/1281] lr: 2.166e-03, eta: 4:24:57, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0396, loss: 0.0396 +2025-06-25 06:34:32,731 - pyskl - INFO - Epoch [122][700/1281] lr: 2.155e-03, eta: 4:24:15, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0302, loss: 0.0302 +2025-06-25 06:35:21,808 - pyskl - INFO - Epoch [122][800/1281] lr: 2.143e-03, eta: 4:23:32, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0308, loss: 0.0308 +2025-06-25 06:36:10,765 - pyskl - INFO - Epoch [122][900/1281] lr: 2.132e-03, eta: 4:22:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0318, loss: 0.0318 +2025-06-25 06:37:00,083 - pyskl - INFO - Epoch [122][1000/1281] lr: 2.120e-03, eta: 4:22:08, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0306, loss: 0.0306 +2025-06-25 06:37:49,586 - pyskl - INFO - Epoch [122][1100/1281] lr: 2.109e-03, eta: 4:21:26, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0467, loss: 0.0467 +2025-06-25 06:38:28,118 - pyskl - INFO - Epoch [122][1200/1281] lr: 2.098e-03, eta: 4:20:41, time: 0.385, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0493, loss: 0.0493 +2025-06-25 06:39:09,534 - pyskl - INFO - Saving checkpoint at 122 epochs +2025-06-25 06:39:56,083 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:39:56,139 - pyskl - INFO - +top1_acc 0.9162 +top5_acc 0.9957 +2025-06-25 06:39:56,139 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:39:56,147 - pyskl - INFO - +mean_acc 0.8839 +2025-06-25 06:39:56,149 - pyskl - INFO - Epoch(val) [122][533] top1_acc: 0.9162, top5_acc: 0.9957, mean_class_accuracy: 0.8839 +2025-06-25 06:41:15,877 - pyskl - INFO - Epoch [123][100/1281] lr: 2.077e-03, eta: 4:19:23, time: 0.797, data_time: 0.190, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0309, loss: 0.0309 +2025-06-25 06:42:05,309 - pyskl - INFO - Epoch [123][200/1281] lr: 2.066e-03, eta: 4:18:40, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0317, loss: 0.0317 +2025-06-25 06:42:54,464 - pyskl - INFO - Epoch [123][300/1281] lr: 2.055e-03, eta: 4:17:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0497, loss: 0.0497 +2025-06-25 06:43:43,654 - pyskl - INFO - Epoch [123][400/1281] lr: 2.044e-03, eta: 4:17:16, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0392, loss: 0.0392 +2025-06-25 06:44:33,033 - pyskl - INFO - Epoch [123][500/1281] lr: 2.032e-03, eta: 4:16:34, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0264, loss: 0.0264 +2025-06-25 06:45:22,151 - pyskl - INFO - Epoch [123][600/1281] lr: 2.021e-03, eta: 4:15:52, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0246, loss: 0.0246 +2025-06-25 06:46:11,115 - pyskl - INFO - Epoch [123][700/1281] lr: 2.010e-03, eta: 4:15:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0251, loss: 0.0251 +2025-06-25 06:47:00,128 - pyskl - INFO - Epoch [123][800/1281] lr: 1.999e-03, eta: 4:14:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0258, loss: 0.0258 +2025-06-25 06:47:49,083 - pyskl - INFO - Epoch [123][900/1281] lr: 1.988e-03, eta: 4:13:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0293, loss: 0.0293 +2025-06-25 06:48:38,445 - pyskl - INFO - Epoch [123][1000/1281] lr: 1.977e-03, eta: 4:13:02, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0247, loss: 0.0247 +2025-06-25 06:49:27,602 - pyskl - INFO - Epoch [123][1100/1281] lr: 1.966e-03, eta: 4:12:20, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0289, loss: 0.0289 +2025-06-25 06:50:04,976 - pyskl - INFO - Epoch [123][1200/1281] lr: 1.955e-03, eta: 4:11:35, time: 0.374, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0351, loss: 0.0351 +2025-06-25 06:50:47,226 - pyskl - INFO - Saving checkpoint at 123 epochs +2025-06-25 06:51:33,541 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:51:33,596 - pyskl - INFO - +top1_acc 0.9148 +top5_acc 0.9940 +2025-06-25 06:51:33,596 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:51:33,602 - pyskl - INFO - +mean_acc 0.8831 +2025-06-25 06:51:33,603 - pyskl - INFO - Epoch(val) [123][533] top1_acc: 0.9148, top5_acc: 0.9940, mean_class_accuracy: 0.8831 +2025-06-25 06:52:52,448 - pyskl - INFO - Epoch [124][100/1281] lr: 1.935e-03, eta: 4:10:16, time: 0.788, data_time: 0.181, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0323, loss: 0.0323 +2025-06-25 06:53:41,382 - pyskl - INFO - Epoch [124][200/1281] lr: 1.924e-03, eta: 4:09:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0538, loss: 0.0538 +2025-06-25 06:54:30,512 - pyskl - INFO - Epoch [124][300/1281] lr: 1.913e-03, eta: 4:08:52, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0548, loss: 0.0548 +2025-06-25 06:55:19,749 - pyskl - INFO - Epoch [124][400/1281] lr: 1.902e-03, eta: 4:08:09, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0502, loss: 0.0502 +2025-06-25 06:56:08,830 - pyskl - INFO - Epoch [124][500/1281] lr: 1.892e-03, eta: 4:07:27, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0448, loss: 0.0448 +2025-06-25 06:56:57,959 - pyskl - INFO - Epoch [124][600/1281] lr: 1.881e-03, eta: 4:06:45, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0434, loss: 0.0434 +2025-06-25 06:57:47,160 - pyskl - INFO - Epoch [124][700/1281] lr: 1.870e-03, eta: 4:06:02, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0414, loss: 0.0414 +2025-06-25 06:58:36,252 - pyskl - INFO - Epoch [124][800/1281] lr: 1.859e-03, eta: 4:05:20, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0280, loss: 0.0280 +2025-06-25 06:59:25,218 - pyskl - INFO - Epoch [124][900/1281] lr: 1.849e-03, eta: 4:04:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0307, loss: 0.0307 +2025-06-25 07:00:14,396 - pyskl - INFO - Epoch [124][1000/1281] lr: 1.838e-03, eta: 4:03:55, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0321, loss: 0.0321 +2025-06-25 07:01:03,605 - pyskl - INFO - Epoch [124][1100/1281] lr: 1.827e-03, eta: 4:03:13, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0425, loss: 0.0425 +2025-06-25 07:01:41,033 - pyskl - INFO - Epoch [124][1200/1281] lr: 1.817e-03, eta: 4:02:28, time: 0.374, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0328, loss: 0.0328 +2025-06-25 07:02:21,718 - pyskl - INFO - Saving checkpoint at 124 epochs +2025-06-25 07:03:08,440 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:03:08,508 - pyskl - INFO - +top1_acc 0.9162 +top5_acc 0.9948 +2025-06-25 07:03:08,509 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:03:08,516 - pyskl - INFO - +mean_acc 0.8858 +2025-06-25 07:03:08,518 - pyskl - INFO - Epoch(val) [124][533] top1_acc: 0.9162, top5_acc: 0.9948, mean_class_accuracy: 0.8858 +2025-06-25 07:04:27,636 - pyskl - INFO - Epoch [125][100/1281] lr: 1.797e-03, eta: 4:01:09, time: 0.791, data_time: 0.185, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0320, loss: 0.0320 +2025-06-25 07:05:16,452 - pyskl - INFO - Epoch [125][200/1281] lr: 1.787e-03, eta: 4:00:26, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0324, loss: 0.0324 +2025-06-25 07:06:06,001 - pyskl - INFO - Epoch [125][300/1281] lr: 1.776e-03, eta: 3:59:44, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0412, loss: 0.0412 +2025-06-25 07:06:54,855 - pyskl - INFO - Epoch [125][400/1281] lr: 1.766e-03, eta: 3:59:02, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0344, loss: 0.0344 +2025-06-25 07:07:43,859 - pyskl - INFO - Epoch [125][500/1281] lr: 1.755e-03, eta: 3:58:19, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0249, loss: 0.0249 +2025-06-25 07:08:32,819 - pyskl - INFO - Epoch [125][600/1281] lr: 1.745e-03, eta: 3:57:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0315, loss: 0.0315 +2025-06-25 07:09:21,786 - pyskl - INFO - Epoch [125][700/1281] lr: 1.735e-03, eta: 3:56:54, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0264, loss: 0.0264 +2025-06-25 07:10:10,760 - pyskl - INFO - Epoch [125][800/1281] lr: 1.724e-03, eta: 3:56:12, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0321, loss: 0.0321 +2025-06-25 07:10:59,960 - pyskl - INFO - Epoch [125][900/1281] lr: 1.714e-03, eta: 3:55:29, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0522, loss: 0.0522 +2025-06-25 07:11:49,268 - pyskl - INFO - Epoch [125][1000/1281] lr: 1.704e-03, eta: 3:54:47, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0339, loss: 0.0339 +2025-06-25 07:12:38,047 - pyskl - INFO - Epoch [125][1100/1281] lr: 1.693e-03, eta: 3:54:04, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0364, loss: 0.0364 +2025-06-25 07:13:15,712 - pyskl - INFO - Epoch [125][1200/1281] lr: 1.683e-03, eta: 3:53:19, time: 0.377, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0508, loss: 0.0508 +2025-06-25 07:13:58,234 - pyskl - INFO - Saving checkpoint at 125 epochs +2025-06-25 07:14:46,626 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:14:46,682 - pyskl - INFO - +top1_acc 0.9144 +top5_acc 0.9954 +2025-06-25 07:14:46,682 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:14:46,689 - pyskl - INFO - +mean_acc 0.8842 +2025-06-25 07:14:46,691 - pyskl - INFO - Epoch(val) [125][533] top1_acc: 0.9144, top5_acc: 0.9954, mean_class_accuracy: 0.8842 +2025-06-25 07:16:05,935 - pyskl - INFO - Epoch [126][100/1281] lr: 1.665e-03, eta: 3:52:01, time: 0.792, data_time: 0.186, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0328, loss: 0.0328 +2025-06-25 07:16:54,927 - pyskl - INFO - Epoch [126][200/1281] lr: 1.654e-03, eta: 3:51:18, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0331, loss: 0.0331 +2025-06-25 07:17:44,014 - pyskl - INFO - Epoch [126][300/1281] lr: 1.644e-03, eta: 3:50:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0289, loss: 0.0289 +2025-06-25 07:18:33,248 - pyskl - INFO - Epoch [126][400/1281] lr: 1.634e-03, eta: 3:49:53, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0317, loss: 0.0317 +2025-06-25 07:19:22,161 - pyskl - INFO - Epoch [126][500/1281] lr: 1.624e-03, eta: 3:49:10, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0432, loss: 0.0432 +2025-06-25 07:20:11,066 - pyskl - INFO - Epoch [126][600/1281] lr: 1.614e-03, eta: 3:48:28, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0335, loss: 0.0335 +2025-06-25 07:21:00,031 - pyskl - INFO - Epoch [126][700/1281] lr: 1.604e-03, eta: 3:47:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0307, loss: 0.0307 +2025-06-25 07:21:49,110 - pyskl - INFO - Epoch [126][800/1281] lr: 1.594e-03, eta: 3:47:03, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0296, loss: 0.0296 +2025-06-25 07:22:38,431 - pyskl - INFO - Epoch [126][900/1281] lr: 1.584e-03, eta: 3:46:20, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0331, loss: 0.0331 +2025-06-25 07:23:27,550 - pyskl - INFO - Epoch [126][1000/1281] lr: 1.574e-03, eta: 3:45:38, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-25 07:24:16,524 - pyskl - INFO - Epoch [126][1100/1281] lr: 1.564e-03, eta: 3:44:55, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0247, loss: 0.0247 +2025-06-25 07:24:54,087 - pyskl - INFO - Epoch [126][1200/1281] lr: 1.554e-03, eta: 3:44:10, time: 0.376, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0411, loss: 0.0411 +2025-06-25 07:25:37,046 - pyskl - INFO - Saving checkpoint at 126 epochs +2025-06-25 07:26:23,804 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:26:23,861 - pyskl - INFO - +top1_acc 0.9125 +top5_acc 0.9952 +2025-06-25 07:26:23,861 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:26:23,869 - pyskl - INFO - +mean_acc 0.8764 +2025-06-25 07:26:23,871 - pyskl - INFO - Epoch(val) [126][533] top1_acc: 0.9125, top5_acc: 0.9952, mean_class_accuracy: 0.8764 +2025-06-25 07:27:44,560 - pyskl - INFO - Epoch [127][100/1281] lr: 1.536e-03, eta: 3:42:51, time: 0.807, data_time: 0.194, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0328, loss: 0.0328 +2025-06-25 07:28:33,843 - pyskl - INFO - Epoch [127][200/1281] lr: 1.527e-03, eta: 3:42:09, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0282, loss: 0.0282 +2025-06-25 07:29:23,195 - pyskl - INFO - Epoch [127][300/1281] lr: 1.517e-03, eta: 3:41:26, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0269, loss: 0.0269 +2025-06-25 07:30:12,312 - pyskl - INFO - Epoch [127][400/1281] lr: 1.507e-03, eta: 3:40:44, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0266, loss: 0.0266 +2025-06-25 07:31:01,663 - pyskl - INFO - Epoch [127][500/1281] lr: 1.497e-03, eta: 3:40:01, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0243, loss: 0.0243 +2025-06-25 07:31:50,602 - pyskl - INFO - Epoch [127][600/1281] lr: 1.488e-03, eta: 3:39:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0261, loss: 0.0261 +2025-06-25 07:32:39,658 - pyskl - INFO - Epoch [127][700/1281] lr: 1.478e-03, eta: 3:38:36, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0292, loss: 0.0292 +2025-06-25 07:33:28,818 - pyskl - INFO - Epoch [127][800/1281] lr: 1.468e-03, eta: 3:37:53, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0294, loss: 0.0294 +2025-06-25 07:34:18,037 - pyskl - INFO - Epoch [127][900/1281] lr: 1.459e-03, eta: 3:37:11, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0286, loss: 0.0286 +2025-06-25 07:35:07,138 - pyskl - INFO - Epoch [127][1000/1281] lr: 1.449e-03, eta: 3:36:28, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0271, loss: 0.0271 +2025-06-25 07:35:56,074 - pyskl - INFO - Epoch [127][1100/1281] lr: 1.440e-03, eta: 3:35:45, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0357, loss: 0.0357 +2025-06-25 07:36:31,959 - pyskl - INFO - Epoch [127][1200/1281] lr: 1.430e-03, eta: 3:35:00, time: 0.359, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0297, loss: 0.0297 +2025-06-25 07:37:17,833 - pyskl - INFO - Saving checkpoint at 127 epochs +2025-06-25 07:38:06,438 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:38:06,493 - pyskl - INFO - +top1_acc 0.9177 +top5_acc 0.9957 +2025-06-25 07:38:06,493 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:38:06,500 - pyskl - INFO - +mean_acc 0.8869 +2025-06-25 07:38:06,502 - pyskl - INFO - Epoch(val) [127][533] top1_acc: 0.9177, top5_acc: 0.9957, mean_class_accuracy: 0.8869 +2025-06-25 07:39:25,713 - pyskl - INFO - Epoch [128][100/1281] lr: 1.413e-03, eta: 3:33:41, time: 0.792, data_time: 0.186, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0264, loss: 0.0264 +2025-06-25 07:40:15,163 - pyskl - INFO - Epoch [128][200/1281] lr: 1.404e-03, eta: 3:32:58, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0356, loss: 0.0356 +2025-06-25 07:41:04,275 - pyskl - INFO - Epoch [128][300/1281] lr: 1.394e-03, eta: 3:32:16, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0274, loss: 0.0274 +2025-06-25 07:41:53,099 - pyskl - INFO - Epoch [128][400/1281] lr: 1.385e-03, eta: 3:31:33, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0257, loss: 0.0257 +2025-06-25 07:42:41,710 - pyskl - INFO - Epoch [128][500/1281] lr: 1.376e-03, eta: 3:30:50, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0256, loss: 0.0256 +2025-06-25 07:43:30,979 - pyskl - INFO - Epoch [128][600/1281] lr: 1.366e-03, eta: 3:30:08, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0238, loss: 0.0238 +2025-06-25 07:44:20,153 - pyskl - INFO - Epoch [128][700/1281] lr: 1.357e-03, eta: 3:29:25, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0275, loss: 0.0275 +2025-06-25 07:45:09,162 - pyskl - INFO - Epoch [128][800/1281] lr: 1.348e-03, eta: 3:28:42, 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 07:45:58,013 - pyskl - INFO - Epoch [128][900/1281] lr: 1.339e-03, eta: 3:27:59, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0263, loss: 0.0263 +2025-06-25 07:46:47,393 - pyskl - INFO - Epoch [128][1000/1281] lr: 1.329e-03, eta: 3:27:17, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0218, loss: 0.0218 +2025-06-25 07:47:36,710 - pyskl - INFO - Epoch [128][1100/1281] lr: 1.320e-03, eta: 3:26:34, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 07:48:15,149 - pyskl - INFO - Epoch [128][1200/1281] lr: 1.311e-03, eta: 3:25:49, time: 0.384, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0221, loss: 0.0221 +2025-06-25 07:48:58,053 - pyskl - INFO - Saving checkpoint at 128 epochs +2025-06-25 07:49:46,032 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:49:46,087 - pyskl - INFO - +top1_acc 0.9220 +top5_acc 0.9961 +2025-06-25 07:49:46,087 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:49:46,094 - pyskl - INFO - +mean_acc 0.8920 +2025-06-25 07:49:46,098 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_120.pth was removed +2025-06-25 07:49:46,286 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_128.pth. +2025-06-25 07:49:46,286 - pyskl - INFO - Best top1_acc is 0.9220 at 128 epoch. +2025-06-25 07:49:46,289 - pyskl - INFO - Epoch(val) [128][533] top1_acc: 0.9220, top5_acc: 0.9961, mean_class_accuracy: 0.8920 +2025-06-25 07:51:06,285 - pyskl - INFO - Epoch [129][100/1281] lr: 1.295e-03, eta: 3:24:30, time: 0.800, data_time: 0.185, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 07:51:55,591 - pyskl - INFO - Epoch [129][200/1281] lr: 1.286e-03, eta: 3:23:48, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-25 07:52:44,805 - pyskl - INFO - Epoch [129][300/1281] lr: 1.277e-03, eta: 3:23:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 07:53:33,938 - pyskl - INFO - Epoch [129][400/1281] lr: 1.268e-03, eta: 3:22:22, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 07:54:22,784 - pyskl - INFO - Epoch [129][500/1281] lr: 1.259e-03, eta: 3:21:39, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0237, loss: 0.0237 +2025-06-25 07:55:11,701 - pyskl - INFO - Epoch [129][600/1281] lr: 1.250e-03, eta: 3:20:56, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0238, loss: 0.0238 +2025-06-25 07:56:00,740 - pyskl - INFO - Epoch [129][700/1281] lr: 1.241e-03, eta: 3:20:14, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 07:56:49,761 - pyskl - INFO - Epoch [129][800/1281] lr: 1.232e-03, eta: 3:19:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0277, loss: 0.0277 +2025-06-25 07:57:38,650 - pyskl - INFO - Epoch [129][900/1281] lr: 1.223e-03, eta: 3:18:48, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0226, loss: 0.0226 +2025-06-25 07:58:27,873 - pyskl - INFO - Epoch [129][1000/1281] lr: 1.214e-03, eta: 3:18:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0229, loss: 0.0229 +2025-06-25 07:59:17,091 - pyskl - INFO - Epoch [129][1100/1281] lr: 1.206e-03, eta: 3:17:22, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0240, loss: 0.0240 +2025-06-25 07:59:53,890 - pyskl - INFO - Epoch [129][1200/1281] lr: 1.197e-03, eta: 3:16:37, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-25 08:00:37,048 - pyskl - INFO - Saving checkpoint at 129 epochs +2025-06-25 08:01:24,504 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:01:24,561 - pyskl - INFO - +top1_acc 0.9224 +top5_acc 0.9958 +2025-06-25 08:01:24,561 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:01:24,569 - pyskl - INFO - +mean_acc 0.8959 +2025-06-25 08:01:24,573 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_128.pth was removed +2025-06-25 08:01:24,749 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_129.pth. +2025-06-25 08:01:24,749 - pyskl - INFO - Best top1_acc is 0.9224 at 129 epoch. +2025-06-25 08:01:24,752 - pyskl - INFO - Epoch(val) [129][533] top1_acc: 0.9224, top5_acc: 0.9958, mean_class_accuracy: 0.8959 +2025-06-25 08:02:43,691 - pyskl - INFO - Epoch [130][100/1281] lr: 1.181e-03, eta: 3:15:18, time: 0.789, data_time: 0.188, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 08:03:33,156 - pyskl - INFO - Epoch [130][200/1281] lr: 1.172e-03, eta: 3:14:35, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-25 08:04:22,378 - pyskl - INFO - Epoch [130][300/1281] lr: 1.164e-03, eta: 3:13:52, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0249, loss: 0.0249 +2025-06-25 08:05:11,693 - pyskl - INFO - Epoch [130][400/1281] lr: 1.155e-03, eta: 3:13:10, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0233, loss: 0.0233 +2025-06-25 08:06:00,742 - pyskl - INFO - Epoch [130][500/1281] lr: 1.147e-03, eta: 3:12:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0226, loss: 0.0226 +2025-06-25 08:06:49,965 - pyskl - INFO - Epoch [130][600/1281] lr: 1.138e-03, eta: 3:11:44, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0224, loss: 0.0224 +2025-06-25 08:07:38,977 - pyskl - INFO - Epoch [130][700/1281] lr: 1.130e-03, eta: 3:11:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0222, loss: 0.0222 +2025-06-25 08:08:27,864 - pyskl - INFO - Epoch [130][800/1281] lr: 1.121e-03, eta: 3:10:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0215, loss: 0.0215 +2025-06-25 08:09:16,886 - pyskl - INFO - Epoch [130][900/1281] lr: 1.113e-03, eta: 3:09:35, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-25 08:10:05,901 - pyskl - INFO - Epoch [130][1000/1281] lr: 1.104e-03, eta: 3:08:52, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 08:10:54,792 - pyskl - INFO - Epoch [130][1100/1281] lr: 1.096e-03, eta: 3:08:09, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 08:11:32,633 - pyskl - INFO - Epoch [130][1200/1281] lr: 1.088e-03, eta: 3:07:25, time: 0.378, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 08:12:14,243 - pyskl - INFO - Saving checkpoint at 130 epochs +2025-06-25 08:13:01,618 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:13:01,672 - pyskl - INFO - +top1_acc 0.9237 +top5_acc 0.9953 +2025-06-25 08:13:01,672 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:13:01,678 - pyskl - INFO - +mean_acc 0.8939 +2025-06-25 08:13:01,683 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_129.pth was removed +2025-06-25 08:13:01,858 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_130.pth. +2025-06-25 08:13:01,858 - pyskl - INFO - Best top1_acc is 0.9237 at 130 epoch. +2025-06-25 08:13:01,860 - pyskl - INFO - Epoch(val) [130][533] top1_acc: 0.9237, top5_acc: 0.9953, mean_class_accuracy: 0.8939 +2025-06-25 08:14:22,323 - pyskl - INFO - Epoch [131][100/1281] lr: 1.072e-03, eta: 3:06:06, time: 0.805, data_time: 0.190, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 08:15:11,470 - pyskl - INFO - Epoch [131][200/1281] lr: 1.064e-03, eta: 3:05:23, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 08:16:00,516 - pyskl - INFO - Epoch [131][300/1281] lr: 1.056e-03, eta: 3:04:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 08:16:49,642 - pyskl - INFO - Epoch [131][400/1281] lr: 1.048e-03, eta: 3:03:57, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 08:17:38,719 - pyskl - INFO - Epoch [131][500/1281] lr: 1.040e-03, eta: 3:03:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0204, loss: 0.0204 +2025-06-25 08:18:27,464 - pyskl - INFO - Epoch [131][600/1281] lr: 1.031e-03, eta: 3:02:31, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0217, loss: 0.0217 +2025-06-25 08:19:16,036 - pyskl - INFO - Epoch [131][700/1281] lr: 1.023e-03, eta: 3:01:48, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-25 08:20:04,973 - pyskl - INFO - Epoch [131][800/1281] lr: 1.015e-03, eta: 3:01:05, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0219, loss: 0.0219 +2025-06-25 08:20:54,015 - pyskl - INFO - Epoch [131][900/1281] lr: 1.007e-03, eta: 3:00:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 08:21:43,088 - pyskl - INFO - Epoch [131][1000/1281] lr: 9.992e-04, eta: 2:59:39, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 08:22:32,244 - pyskl - INFO - Epoch [131][1100/1281] lr: 9.912e-04, eta: 2:58:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0234, loss: 0.0234 +2025-06-25 08:23:09,839 - pyskl - INFO - Epoch [131][1200/1281] lr: 9.832e-04, eta: 2:58:11, time: 0.376, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 08:23:52,769 - pyskl - INFO - Saving checkpoint at 131 epochs +2025-06-25 08:24:40,457 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:24:40,515 - pyskl - INFO - +top1_acc 0.9232 +top5_acc 0.9961 +2025-06-25 08:24:40,515 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:24:40,523 - pyskl - INFO - +mean_acc 0.8918 +2025-06-25 08:24:40,525 - pyskl - INFO - Epoch(val) [131][533] top1_acc: 0.9232, top5_acc: 0.9961, mean_class_accuracy: 0.8918 +2025-06-25 08:26:00,246 - pyskl - INFO - Epoch [132][100/1281] lr: 9.689e-04, eta: 2:56:52, time: 0.797, data_time: 0.185, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 08:26:49,344 - pyskl - INFO - Epoch [132][200/1281] lr: 9.610e-04, eta: 2:56:09, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 08:27:38,222 - pyskl - INFO - Epoch [132][300/1281] lr: 9.532e-04, eta: 2:55:26, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-25 08:28:27,138 - pyskl - INFO - Epoch [132][400/1281] lr: 9.454e-04, eta: 2:54:43, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 08:29:16,081 - pyskl - INFO - Epoch [132][500/1281] lr: 9.376e-04, eta: 2:54:00, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0200, loss: 0.0200 +2025-06-25 08:30:04,891 - pyskl - INFO - Epoch [132][600/1281] lr: 9.298e-04, eta: 2:53:17, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 08:30:54,129 - pyskl - INFO - Epoch [132][700/1281] lr: 9.221e-04, eta: 2:52:33, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0214, loss: 0.0214 +2025-06-25 08:31:43,355 - pyskl - INFO - Epoch [132][800/1281] lr: 9.144e-04, eta: 2:51:50, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 08:32:32,415 - pyskl - INFO - Epoch [132][900/1281] lr: 9.068e-04, eta: 2:51:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 08:33:21,246 - pyskl - INFO - Epoch [132][1000/1281] lr: 8.991e-04, eta: 2:50:24, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 08:34:09,943 - pyskl - INFO - Epoch [132][1100/1281] lr: 8.915e-04, eta: 2:49:41, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-25 08:34:47,035 - pyskl - INFO - Epoch [132][1200/1281] lr: 8.840e-04, eta: 2:48:56, time: 0.371, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0207, loss: 0.0207 +2025-06-25 08:35:31,672 - pyskl - INFO - Saving checkpoint at 132 epochs +2025-06-25 08:36:19,999 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:36:20,055 - pyskl - INFO - +top1_acc 0.9227 +top5_acc 0.9965 +2025-06-25 08:36:20,055 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:36:20,061 - pyskl - INFO - +mean_acc 0.8933 +2025-06-25 08:36:20,063 - pyskl - INFO - Epoch(val) [132][533] top1_acc: 0.9227, top5_acc: 0.9965, mean_class_accuracy: 0.8933 +2025-06-25 08:37:39,872 - pyskl - INFO - Epoch [133][100/1281] lr: 8.704e-04, eta: 2:47:37, time: 0.798, data_time: 0.189, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 08:38:28,580 - pyskl - INFO - Epoch [133][200/1281] lr: 8.629e-04, eta: 2:46:54, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 08:39:17,456 - pyskl - INFO - Epoch [133][300/1281] lr: 8.554e-04, eta: 2:46:11, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0207, loss: 0.0207 +2025-06-25 08:40:06,211 - pyskl - INFO - Epoch [133][400/1281] lr: 8.480e-04, eta: 2:45:28, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 08:40:55,472 - pyskl - INFO - Epoch [133][500/1281] lr: 8.406e-04, eta: 2:44:45, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-25 08:41:44,507 - pyskl - INFO - Epoch [133][600/1281] lr: 8.333e-04, eta: 2:44:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 08:42:33,737 - pyskl - INFO - Epoch [133][700/1281] lr: 8.260e-04, eta: 2:43:18, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 08:43:22,853 - pyskl - INFO - Epoch [133][800/1281] lr: 8.187e-04, eta: 2:42:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0236, loss: 0.0236 +2025-06-25 08:44:12,263 - pyskl - INFO - Epoch [133][900/1281] lr: 8.114e-04, eta: 2:41:52, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0209, loss: 0.0209 +2025-06-25 08:45:01,021 - pyskl - INFO - Epoch [133][1000/1281] lr: 8.042e-04, eta: 2:41:09, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 08:45:49,864 - pyskl - INFO - Epoch [133][1100/1281] lr: 7.970e-04, eta: 2:40:26, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 08:46:27,754 - pyskl - INFO - Epoch [133][1200/1281] lr: 7.898e-04, eta: 2:39:41, time: 0.379, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 08:47:10,277 - pyskl - INFO - Saving checkpoint at 133 epochs +2025-06-25 08:47:58,000 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:47:58,055 - pyskl - INFO - +top1_acc 0.9252 +top5_acc 0.9958 +2025-06-25 08:47:58,055 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:47:58,062 - pyskl - INFO - +mean_acc 0.8954 +2025-06-25 08:47:58,067 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_130.pth was removed +2025-06-25 08:47:58,249 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_133.pth. +2025-06-25 08:47:58,249 - pyskl - INFO - Best top1_acc is 0.9252 at 133 epoch. +2025-06-25 08:47:58,252 - pyskl - INFO - Epoch(val) [133][533] top1_acc: 0.9252, top5_acc: 0.9958, mean_class_accuracy: 0.8954 +2025-06-25 08:49:19,731 - pyskl - INFO - Epoch [134][100/1281] lr: 7.769e-04, eta: 2:38:22, time: 0.815, data_time: 0.193, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 08:50:08,890 - pyskl - INFO - Epoch [134][200/1281] lr: 7.699e-04, eta: 2:37:39, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 08:50:57,969 - pyskl - INFO - Epoch [134][300/1281] lr: 7.628e-04, eta: 2:36:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 08:51:47,202 - pyskl - INFO - Epoch [134][400/1281] lr: 7.558e-04, eta: 2:36:13, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-25 08:52:36,509 - pyskl - INFO - Epoch [134][500/1281] lr: 7.488e-04, eta: 2:35:29, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 08:53:25,546 - pyskl - INFO - Epoch [134][600/1281] lr: 7.419e-04, eta: 2:34:46, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 08:54:14,686 - pyskl - INFO - Epoch [134][700/1281] lr: 7.349e-04, eta: 2:34:03, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-25 08:55:04,253 - pyskl - INFO - Epoch [134][800/1281] lr: 7.281e-04, eta: 2:33:20, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 08:55:53,288 - pyskl - INFO - Epoch [134][900/1281] lr: 7.212e-04, eta: 2:32:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 08:56:42,458 - pyskl - INFO - Epoch [134][1000/1281] lr: 7.144e-04, eta: 2:31:53, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 08:57:31,367 - pyskl - INFO - Epoch [134][1100/1281] lr: 7.076e-04, eta: 2:31:10, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 08:58:06,928 - pyskl - INFO - Epoch [134][1200/1281] lr: 7.008e-04, eta: 2:30:25, time: 0.356, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 08:58:54,524 - pyskl - INFO - Saving checkpoint at 134 epochs +2025-06-25 08:59:43,157 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:59:43,213 - pyskl - INFO - +top1_acc 0.9243 +top5_acc 0.9958 +2025-06-25 08:59:43,214 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:59:43,220 - pyskl - INFO - +mean_acc 0.8954 +2025-06-25 08:59:43,222 - pyskl - INFO - Epoch(val) [134][533] top1_acc: 0.9243, top5_acc: 0.9958, mean_class_accuracy: 0.8954 +2025-06-25 09:01:01,187 - pyskl - INFO - Epoch [135][100/1281] lr: 6.887e-04, eta: 2:29:06, time: 0.780, data_time: 0.182, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 09:01:50,209 - pyskl - INFO - Epoch [135][200/1281] lr: 6.820e-04, eta: 2:28:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 09:02:39,156 - pyskl - INFO - Epoch [135][300/1281] lr: 6.753e-04, eta: 2:27:39, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 09:03:28,164 - pyskl - INFO - Epoch [135][400/1281] lr: 6.687e-04, eta: 2:26:56, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 09:04:17,186 - pyskl - INFO - Epoch [135][500/1281] lr: 6.622e-04, eta: 2:26:13, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 09:05:06,065 - pyskl - INFO - Epoch [135][600/1281] lr: 6.556e-04, eta: 2:25:29, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 09:05:55,315 - pyskl - INFO - Epoch [135][700/1281] lr: 6.491e-04, eta: 2:24:46, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 09:06:44,407 - pyskl - INFO - Epoch [135][800/1281] lr: 6.426e-04, eta: 2:24:03, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 09:07:33,443 - pyskl - INFO - Epoch [135][900/1281] lr: 6.362e-04, eta: 2:23:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0172, loss: 0.0172 +2025-06-25 09:08:22,619 - pyskl - INFO - Epoch [135][1000/1281] lr: 6.297e-04, eta: 2:22:36, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 09:09:11,661 - pyskl - INFO - Epoch [135][1100/1281] lr: 6.233e-04, eta: 2:21:53, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 09:09:50,385 - pyskl - INFO - Epoch [135][1200/1281] lr: 6.170e-04, eta: 2:21:08, time: 0.387, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 09:10:30,526 - pyskl - INFO - Saving checkpoint at 135 epochs +2025-06-25 09:11:17,252 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:11:17,326 - pyskl - INFO - +top1_acc 0.9247 +top5_acc 0.9961 +2025-06-25 09:11:17,327 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:11:17,335 - pyskl - INFO - +mean_acc 0.8936 +2025-06-25 09:11:17,339 - pyskl - INFO - Epoch(val) [135][533] top1_acc: 0.9247, top5_acc: 0.9961, mean_class_accuracy: 0.8936 +2025-06-25 09:12:37,787 - pyskl - INFO - Epoch [136][100/1281] lr: 6.056e-04, eta: 2:19:49, time: 0.804, data_time: 0.196, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 09:13:26,622 - pyskl - INFO - Epoch [136][200/1281] lr: 5.993e-04, eta: 2:19:06, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 09:14:15,981 - pyskl - INFO - Epoch [136][300/1281] lr: 5.931e-04, eta: 2:18:22, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0170, loss: 0.0170 +2025-06-25 09:15:05,136 - pyskl - INFO - Epoch [136][400/1281] lr: 5.868e-04, eta: 2:17:39, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 09:15:54,434 - pyskl - INFO - Epoch [136][500/1281] lr: 5.807e-04, eta: 2:16:56, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 09:16:43,581 - pyskl - INFO - Epoch [136][600/1281] lr: 5.745e-04, eta: 2:16:12, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 09:17:32,486 - pyskl - INFO - Epoch [136][700/1281] lr: 5.684e-04, eta: 2:15:29, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 09:18:21,631 - pyskl - INFO - Epoch [136][800/1281] lr: 5.623e-04, eta: 2:14:46, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-25 09:19:10,260 - pyskl - INFO - Epoch [136][900/1281] lr: 5.563e-04, eta: 2:14:02, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-25 09:19:59,341 - pyskl - INFO - Epoch [136][1000/1281] lr: 5.503e-04, eta: 2:13:19, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 09:20:48,723 - pyskl - INFO - Epoch [136][1100/1281] lr: 5.443e-04, eta: 2:12:36, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 09:21:25,528 - pyskl - INFO - Epoch [136][1200/1281] lr: 5.384e-04, eta: 2:11:51, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 09:22:07,980 - pyskl - INFO - Saving checkpoint at 136 epochs +2025-06-25 09:22:55,040 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:22:55,097 - pyskl - INFO - +top1_acc 0.9249 +top5_acc 0.9964 +2025-06-25 09:22:55,097 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:22:55,105 - pyskl - INFO - +mean_acc 0.8949 +2025-06-25 09:22:55,107 - pyskl - INFO - Epoch(val) [136][533] top1_acc: 0.9249, top5_acc: 0.9964, mean_class_accuracy: 0.8949 +2025-06-25 09:24:14,569 - pyskl - INFO - Epoch [137][100/1281] lr: 5.277e-04, eta: 2:10:31, time: 0.795, data_time: 0.189, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 09:25:03,602 - pyskl - INFO - Epoch [137][200/1281] lr: 5.218e-04, eta: 2:09:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 09:25:52,656 - pyskl - INFO - Epoch [137][300/1281] lr: 5.160e-04, eta: 2:09:05, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 09:26:41,341 - pyskl - INFO - Epoch [137][400/1281] lr: 5.102e-04, eta: 2:08:21, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0169, loss: 0.0169 +2025-06-25 09:27:30,893 - pyskl - INFO - Epoch [137][500/1281] lr: 5.044e-04, eta: 2:07:38, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0170, loss: 0.0170 +2025-06-25 09:28:20,283 - pyskl - INFO - Epoch [137][600/1281] lr: 4.987e-04, eta: 2:06:54, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 09:29:09,337 - pyskl - INFO - Epoch [137][700/1281] lr: 4.930e-04, eta: 2:06:11, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 09:29:58,761 - pyskl - INFO - Epoch [137][800/1281] lr: 4.873e-04, eta: 2:05:28, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 09:30:47,705 - pyskl - INFO - Epoch [137][900/1281] lr: 4.817e-04, eta: 2:04:44, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 09:31:36,829 - pyskl - INFO - Epoch [137][1000/1281] lr: 4.761e-04, eta: 2:04:01, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0215, loss: 0.0215 +2025-06-25 09:32:25,975 - pyskl - INFO - Epoch [137][1100/1281] lr: 4.705e-04, eta: 2:03:17, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 09:33:03,775 - pyskl - INFO - Epoch [137][1200/1281] lr: 4.650e-04, eta: 2:02:33, time: 0.378, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 09:33:47,270 - pyskl - INFO - Saving checkpoint at 137 epochs +2025-06-25 09:34:34,783 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:34:34,850 - pyskl - INFO - +top1_acc 0.9240 +top5_acc 0.9964 +2025-06-25 09:34:34,850 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:34:34,857 - pyskl - INFO - +mean_acc 0.8952 +2025-06-25 09:34:34,858 - pyskl - INFO - Epoch(val) [137][533] top1_acc: 0.9240, top5_acc: 0.9964, mean_class_accuracy: 0.8952 +2025-06-25 09:35:53,543 - pyskl - INFO - Epoch [138][100/1281] lr: 4.550e-04, eta: 2:01:13, time: 0.787, data_time: 0.185, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 09:36:42,437 - pyskl - INFO - Epoch [138][200/1281] lr: 4.496e-04, eta: 2:00:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 09:37:31,254 - pyskl - INFO - Epoch [138][300/1281] lr: 4.442e-04, eta: 1:59:46, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 09:38:20,423 - pyskl - INFO - Epoch [138][400/1281] lr: 4.388e-04, eta: 1:59:03, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 09:39:09,709 - pyskl - INFO - Epoch [138][500/1281] lr: 4.334e-04, eta: 1:58:19, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-25 09:39:59,021 - pyskl - INFO - Epoch [138][600/1281] lr: 4.281e-04, eta: 1:57:36, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 09:40:47,938 - pyskl - INFO - Epoch [138][700/1281] lr: 4.228e-04, eta: 1:56:52, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 09:41:37,298 - pyskl - INFO - Epoch [138][800/1281] lr: 4.176e-04, eta: 1:56:09, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0172, loss: 0.0172 +2025-06-25 09:42:26,255 - pyskl - INFO - Epoch [138][900/1281] lr: 4.124e-04, eta: 1:55:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0183, loss: 0.0183 +2025-06-25 09:43:15,397 - pyskl - INFO - Epoch [138][1000/1281] lr: 4.072e-04, eta: 1:54:42, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 09:44:04,432 - pyskl - INFO - Epoch [138][1100/1281] lr: 4.020e-04, eta: 1:53:58, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-25 09:44:41,916 - pyskl - INFO - Epoch [138][1200/1281] lr: 3.969e-04, eta: 1:53:14, time: 0.375, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 09:45:23,886 - pyskl - INFO - Saving checkpoint at 138 epochs +2025-06-25 09:46:11,077 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:46:11,143 - pyskl - INFO - +top1_acc 0.9245 +top5_acc 0.9962 +2025-06-25 09:46:11,143 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:46:11,150 - pyskl - INFO - +mean_acc 0.8959 +2025-06-25 09:46:11,152 - pyskl - INFO - Epoch(val) [138][533] top1_acc: 0.9245, top5_acc: 0.9962, mean_class_accuracy: 0.8959 +2025-06-25 09:47:30,697 - pyskl - INFO - Epoch [139][100/1281] lr: 3.877e-04, eta: 1:51:54, time: 0.795, data_time: 0.185, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 09:48:19,539 - pyskl - INFO - Epoch [139][200/1281] lr: 3.827e-04, eta: 1:51:11, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 09:49:08,492 - pyskl - INFO - Epoch [139][300/1281] lr: 3.777e-04, eta: 1:50:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0156, loss: 0.0156 +2025-06-25 09:49:57,565 - pyskl - INFO - Epoch [139][400/1281] lr: 3.727e-04, eta: 1:49:44, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 09:50:46,967 - pyskl - INFO - Epoch [139][500/1281] lr: 3.678e-04, eta: 1:49:00, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 09:51:36,258 - pyskl - INFO - Epoch [139][600/1281] lr: 3.628e-04, eta: 1:48:16, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 09:52:25,606 - pyskl - INFO - Epoch [139][700/1281] lr: 3.580e-04, eta: 1:47:33, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 09:53:14,350 - pyskl - INFO - Epoch [139][800/1281] lr: 3.531e-04, eta: 1:46:49, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 09:54:03,262 - pyskl - INFO - Epoch [139][900/1281] lr: 3.483e-04, eta: 1:46:06, 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 09:54:52,425 - pyskl - INFO - Epoch [139][1000/1281] lr: 3.436e-04, eta: 1:45:22, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 09:55:41,796 - pyskl - INFO - Epoch [139][1100/1281] lr: 3.388e-04, eta: 1:44:39, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 09:56:19,214 - pyskl - INFO - Epoch [139][1200/1281] lr: 3.341e-04, eta: 1:43:54, time: 0.374, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0172, loss: 0.0172 +2025-06-25 09:57:02,321 - pyskl - INFO - Saving checkpoint at 139 epochs +2025-06-25 09:57:49,726 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:57:49,782 - pyskl - INFO - +top1_acc 0.9227 +top5_acc 0.9961 +2025-06-25 09:57:49,782 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:57:49,788 - pyskl - INFO - +mean_acc 0.8923 +2025-06-25 09:57:49,790 - pyskl - INFO - Epoch(val) [139][533] top1_acc: 0.9227, top5_acc: 0.9961, mean_class_accuracy: 0.8923 +2025-06-25 09:59:08,676 - pyskl - INFO - Epoch [140][100/1281] lr: 3.257e-04, eta: 1:42:34, time: 0.789, data_time: 0.188, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 09:59:57,835 - pyskl - INFO - Epoch [140][200/1281] lr: 3.210e-04, eta: 1:41:51, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 10:00:46,774 - pyskl - INFO - Epoch [140][300/1281] lr: 3.165e-04, eta: 1:41:07, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 10:01:35,957 - pyskl - INFO - Epoch [140][400/1281] lr: 3.119e-04, eta: 1:40:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 10:02:24,924 - pyskl - INFO - Epoch [140][500/1281] lr: 3.074e-04, eta: 1:39:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 10:03:13,936 - pyskl - INFO - Epoch [140][600/1281] lr: 3.029e-04, eta: 1:38:56, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 10:04:03,070 - pyskl - INFO - Epoch [140][700/1281] lr: 2.984e-04, eta: 1:38:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0169, loss: 0.0169 +2025-06-25 10:04:52,316 - pyskl - INFO - Epoch [140][800/1281] lr: 2.940e-04, eta: 1:37:29, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 10:05:41,452 - pyskl - INFO - Epoch [140][900/1281] lr: 2.896e-04, eta: 1:36:46, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 10:06:30,654 - pyskl - INFO - Epoch [140][1000/1281] lr: 2.853e-04, eta: 1:36:02, 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 10:07:19,871 - pyskl - INFO - Epoch [140][1100/1281] lr: 2.809e-04, eta: 1:35:18, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 10:07:58,121 - pyskl - INFO - Epoch [140][1200/1281] lr: 2.767e-04, eta: 1:34:34, time: 0.383, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 10:08:39,465 - pyskl - INFO - Saving checkpoint at 140 epochs +2025-06-25 10:09:26,664 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:09:26,722 - pyskl - INFO - +top1_acc 0.9236 +top5_acc 0.9967 +2025-06-25 10:09:26,722 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:09:26,729 - pyskl - INFO - +mean_acc 0.8932 +2025-06-25 10:09:26,731 - pyskl - INFO - Epoch(val) [140][533] top1_acc: 0.9236, top5_acc: 0.9967, mean_class_accuracy: 0.8932 +2025-06-25 10:10:46,521 - pyskl - INFO - Epoch [141][100/1281] lr: 2.690e-04, eta: 1:33:14, time: 0.798, data_time: 0.186, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 10:11:35,699 - pyskl - INFO - Epoch [141][200/1281] lr: 2.648e-04, eta: 1:32:30, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 10:12:25,211 - pyskl - INFO - Epoch [141][300/1281] lr: 2.606e-04, eta: 1:31:47, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 10:13:14,528 - pyskl - INFO - Epoch [141][400/1281] lr: 2.565e-04, eta: 1:31:03, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 10:14:03,748 - pyskl - INFO - Epoch [141][500/1281] lr: 2.524e-04, eta: 1:30:20, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 10:14:52,980 - pyskl - INFO - Epoch [141][600/1281] lr: 2.483e-04, eta: 1:29:36, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-25 10:15:42,255 - pyskl - INFO - Epoch [141][700/1281] lr: 2.443e-04, eta: 1:28:52, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 10:16:31,330 - pyskl - INFO - Epoch [141][800/1281] lr: 2.402e-04, eta: 1:28:08, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 10:17:20,424 - pyskl - INFO - Epoch [141][900/1281] lr: 2.363e-04, eta: 1:27:25, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 10:18:09,416 - pyskl - INFO - Epoch [141][1000/1281] lr: 2.323e-04, eta: 1:26:41, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0172, loss: 0.0172 +2025-06-25 10:18:58,379 - pyskl - INFO - Epoch [141][1100/1281] lr: 2.284e-04, eta: 1:25:57, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 10:19:35,730 - pyskl - INFO - Epoch [141][1200/1281] lr: 2.246e-04, eta: 1:25:13, time: 0.373, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 10:20:20,751 - pyskl - INFO - Saving checkpoint at 141 epochs +2025-06-25 10:21:09,307 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:21:09,366 - pyskl - INFO - +top1_acc 0.9229 +top5_acc 0.9969 +2025-06-25 10:21:09,366 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:21:09,374 - pyskl - INFO - +mean_acc 0.8943 +2025-06-25 10:21:09,377 - pyskl - INFO - Epoch(val) [141][533] top1_acc: 0.9229, top5_acc: 0.9969, mean_class_accuracy: 0.8943 +2025-06-25 10:22:27,855 - pyskl - INFO - Epoch [142][100/1281] lr: 2.176e-04, eta: 1:23:53, time: 0.785, data_time: 0.182, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0229, loss: 0.0229 +2025-06-25 10:23:17,296 - pyskl - INFO - Epoch [142][200/1281] lr: 2.139e-04, eta: 1:23:09, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 10:24:06,603 - pyskl - INFO - Epoch [142][300/1281] lr: 2.101e-04, eta: 1:22:26, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 10:24:55,856 - pyskl - INFO - Epoch [142][400/1281] lr: 2.064e-04, eta: 1:21:42, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0172, loss: 0.0172 +2025-06-25 10:25:45,106 - pyskl - INFO - Epoch [142][500/1281] lr: 2.027e-04, eta: 1:20:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0153, loss: 0.0153 +2025-06-25 10:26:34,268 - pyskl - INFO - Epoch [142][600/1281] lr: 1.991e-04, eta: 1:20:14, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 10:27:22,818 - pyskl - INFO - Epoch [142][700/1281] lr: 1.954e-04, eta: 1:19:31, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 10:28:11,879 - pyskl - INFO - Epoch [142][800/1281] lr: 1.919e-04, eta: 1:18:47, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-25 10:29:01,073 - pyskl - INFO - Epoch [142][900/1281] lr: 1.883e-04, eta: 1:18:03, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 10:29:50,249 - pyskl - INFO - Epoch [142][1000/1281] lr: 1.848e-04, eta: 1:17:19, 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 10:30:39,360 - pyskl - INFO - Epoch [142][1100/1281] lr: 1.813e-04, eta: 1:16:36, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 10:31:17,507 - pyskl - INFO - Epoch [142][1200/1281] lr: 1.779e-04, eta: 1:15:51, time: 0.381, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0172, loss: 0.0172 +2025-06-25 10:31:58,142 - pyskl - INFO - Saving checkpoint at 142 epochs +2025-06-25 10:32:45,322 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:32:45,378 - pyskl - INFO - +top1_acc 0.9235 +top5_acc 0.9967 +2025-06-25 10:32:45,378 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:32:45,385 - pyskl - INFO - +mean_acc 0.8945 +2025-06-25 10:32:45,387 - pyskl - INFO - Epoch(val) [142][533] top1_acc: 0.9235, top5_acc: 0.9967, mean_class_accuracy: 0.8945 +2025-06-25 10:34:05,960 - pyskl - INFO - Epoch [143][100/1281] lr: 1.717e-04, eta: 1:14:31, time: 0.806, data_time: 0.188, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 10:34:55,507 - pyskl - INFO - Epoch [143][200/1281] lr: 1.683e-04, eta: 1:13:48, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0172, loss: 0.0172 +2025-06-25 10:35:44,721 - pyskl - INFO - Epoch [143][300/1281] lr: 1.650e-04, eta: 1:13:04, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0169, loss: 0.0169 +2025-06-25 10:36:34,078 - pyskl - INFO - Epoch [143][400/1281] lr: 1.617e-04, eta: 1:12:20, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 10:37:23,138 - pyskl - INFO - Epoch [143][500/1281] lr: 1.585e-04, eta: 1:11:36, 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 10:38:12,254 - pyskl - INFO - Epoch [143][600/1281] lr: 1.552e-04, eta: 1:10:52, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 10:39:01,517 - pyskl - INFO - Epoch [143][700/1281] lr: 1.520e-04, eta: 1:10:09, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 10:39:50,419 - pyskl - INFO - Epoch [143][800/1281] lr: 1.489e-04, eta: 1:09:25, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 10:40:39,629 - pyskl - INFO - Epoch [143][900/1281] lr: 1.457e-04, eta: 1:08:41, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 10:41:28,387 - pyskl - INFO - Epoch [143][1000/1281] lr: 1.426e-04, eta: 1:07:57, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-25 10:42:17,499 - pyskl - INFO - Epoch [143][1100/1281] lr: 1.396e-04, eta: 1:07:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0167, loss: 0.0167 +2025-06-25 10:42:54,334 - pyskl - INFO - Epoch [143][1200/1281] lr: 1.366e-04, eta: 1:06:29, time: 0.368, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 10:43:38,321 - pyskl - INFO - Saving checkpoint at 143 epochs +2025-06-25 10:44:26,178 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:44:26,233 - pyskl - INFO - +top1_acc 0.9254 +top5_acc 0.9967 +2025-06-25 10:44:26,233 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:44:26,240 - pyskl - INFO - +mean_acc 0.8958 +2025-06-25 10:44:26,244 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_133.pth was removed +2025-06-25 10:44:26,418 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_143.pth. +2025-06-25 10:44:26,418 - pyskl - INFO - Best top1_acc is 0.9254 at 143 epoch. +2025-06-25 10:44:26,421 - pyskl - INFO - Epoch(val) [143][533] top1_acc: 0.9254, top5_acc: 0.9967, mean_class_accuracy: 0.8958 +2025-06-25 10:45:46,667 - pyskl - INFO - Epoch [144][100/1281] lr: 1.312e-04, eta: 1:05:09, time: 0.802, data_time: 0.193, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 10:46:36,167 - pyskl - INFO - Epoch [144][200/1281] lr: 1.282e-04, eta: 1:04:25, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0183, loss: 0.0183 +2025-06-25 10:47:25,503 - pyskl - INFO - Epoch [144][300/1281] lr: 1.253e-04, eta: 1:03:41, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0168, loss: 0.0168 +2025-06-25 10:48:14,437 - pyskl - INFO - Epoch [144][400/1281] lr: 1.224e-04, eta: 1:02:58, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 10:49:03,658 - pyskl - INFO - Epoch [144][500/1281] lr: 1.196e-04, eta: 1:02:14, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 10:49:52,729 - pyskl - INFO - Epoch [144][600/1281] lr: 1.168e-04, eta: 1:01:30, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 10:50:42,029 - pyskl - INFO - Epoch [144][700/1281] lr: 1.140e-04, eta: 1:00:46, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0171, loss: 0.0171 +2025-06-25 10:51:31,083 - pyskl - INFO - Epoch [144][800/1281] lr: 1.113e-04, eta: 1:00:02, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 10:52:20,208 - pyskl - INFO - Epoch [144][900/1281] lr: 1.086e-04, eta: 0:59:18, 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 10:53:09,512 - pyskl - INFO - Epoch [144][1000/1281] lr: 1.059e-04, eta: 0:58:34, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 10:53:58,347 - pyskl - INFO - Epoch [144][1100/1281] lr: 1.033e-04, eta: 0:57:50, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0183, loss: 0.0183 +2025-06-25 10:54:34,580 - pyskl - INFO - Epoch [144][1200/1281] lr: 1.007e-04, eta: 0:57:06, time: 0.362, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 10:55:19,696 - pyskl - INFO - Saving checkpoint at 144 epochs +2025-06-25 10:56:07,451 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:56:07,533 - pyskl - INFO - +top1_acc 0.9241 +top5_acc 0.9961 +2025-06-25 10:56:07,533 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:56:07,546 - pyskl - INFO - +mean_acc 0.8946 +2025-06-25 10:56:07,549 - pyskl - INFO - Epoch(val) [144][533] top1_acc: 0.9241, top5_acc: 0.9961, mean_class_accuracy: 0.8946 +2025-06-25 10:57:27,456 - pyskl - INFO - Epoch [145][100/1281] lr: 9.605e-05, eta: 0:55:46, time: 0.799, data_time: 0.189, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 10:58:16,806 - pyskl - INFO - Epoch [145][200/1281] lr: 9.353e-05, eta: 0:55:02, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0155, loss: 0.0155 +2025-06-25 10:59:05,883 - pyskl - INFO - Epoch [145][300/1281] lr: 9.106e-05, eta: 0:54:18, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0183, loss: 0.0183 +2025-06-25 10:59:54,888 - pyskl - INFO - Epoch [145][400/1281] lr: 8.861e-05, eta: 0:53:34, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0169, loss: 0.0169 +2025-06-25 11:00:43,997 - pyskl - INFO - Epoch [145][500/1281] lr: 8.620e-05, eta: 0:52:50, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 11:01:33,378 - pyskl - INFO - Epoch [145][600/1281] lr: 8.382e-05, eta: 0:52:06, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 11:02:22,496 - pyskl - INFO - Epoch [145][700/1281] lr: 8.147e-05, eta: 0:51:22, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0163, loss: 0.0163 +2025-06-25 11:03:11,364 - pyskl - INFO - Epoch [145][800/1281] lr: 7.916e-05, eta: 0:50:39, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 11:04:00,588 - pyskl - INFO - Epoch [145][900/1281] lr: 7.688e-05, eta: 0:49:55, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 11:04:50,280 - pyskl - INFO - Epoch [145][1000/1281] lr: 7.463e-05, eta: 0:49:11, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 11:05:39,229 - pyskl - INFO - Epoch [145][1100/1281] lr: 7.242e-05, eta: 0:48:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0172, loss: 0.0172 +2025-06-25 11:06:16,531 - pyskl - INFO - Epoch [145][1200/1281] lr: 7.024e-05, eta: 0:47:42, time: 0.373, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 11:06:59,114 - pyskl - INFO - Saving checkpoint at 145 epochs +2025-06-25 11:07:46,468 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:07:46,535 - pyskl - INFO - +top1_acc 0.9255 +top5_acc 0.9959 +2025-06-25 11:07:46,536 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:07:46,543 - pyskl - INFO - +mean_acc 0.8964 +2025-06-25 11:07:46,547 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_143.pth was removed +2025-06-25 11:07:46,733 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_145.pth. +2025-06-25 11:07:46,734 - pyskl - INFO - Best top1_acc is 0.9255 at 145 epoch. +2025-06-25 11:07:46,736 - pyskl - INFO - Epoch(val) [145][533] top1_acc: 0.9255, top5_acc: 0.9959, mean_class_accuracy: 0.8964 +2025-06-25 11:09:05,867 - pyskl - INFO - Epoch [146][100/1281] lr: 6.638e-05, eta: 0:46:22, time: 0.791, data_time: 0.185, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 11:09:55,414 - pyskl - INFO - Epoch [146][200/1281] lr: 6.429e-05, eta: 0:45:38, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 11:10:44,289 - pyskl - INFO - Epoch [146][300/1281] lr: 6.224e-05, eta: 0:44:54, 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 11:11:33,523 - pyskl - INFO - Epoch [146][400/1281] lr: 6.022e-05, eta: 0:44:10, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0171, loss: 0.0171 +2025-06-25 11:12:22,807 - pyskl - INFO - Epoch [146][500/1281] lr: 5.823e-05, eta: 0:43:26, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 11:13:11,787 - pyskl - INFO - Epoch [146][600/1281] lr: 5.628e-05, eta: 0:42:42, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0171, loss: 0.0171 +2025-06-25 11:14:00,889 - pyskl - INFO - Epoch [146][700/1281] lr: 5.436e-05, eta: 0:41:58, 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 11:14:50,314 - pyskl - INFO - Epoch [146][800/1281] lr: 5.247e-05, eta: 0:41:14, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0162, loss: 0.0162 +2025-06-25 11:15:39,780 - pyskl - INFO - Epoch [146][900/1281] lr: 5.061e-05, eta: 0:40:30, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0166, loss: 0.0166 +2025-06-25 11:16:29,092 - pyskl - INFO - Epoch [146][1000/1281] lr: 4.879e-05, eta: 0:39:46, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 11:17:18,147 - pyskl - INFO - Epoch [146][1100/1281] lr: 4.701e-05, eta: 0:39:02, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 11:17:56,168 - pyskl - INFO - Epoch [146][1200/1281] lr: 4.525e-05, eta: 0:38:18, time: 0.380, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 11:18:38,858 - pyskl - INFO - Saving checkpoint at 146 epochs +2025-06-25 11:19:26,513 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:19:26,573 - pyskl - INFO - +top1_acc 0.9256 +top5_acc 0.9957 +2025-06-25 11:19:26,573 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:19:26,580 - pyskl - INFO - +mean_acc 0.8962 +2025-06-25 11:19:26,584 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_145.pth was removed +2025-06-25 11:19:26,772 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_146.pth. +2025-06-25 11:19:26,772 - pyskl - INFO - Best top1_acc is 0.9256 at 146 epoch. +2025-06-25 11:19:26,776 - pyskl - INFO - Epoch(val) [146][533] top1_acc: 0.9256, top5_acc: 0.9957, mean_class_accuracy: 0.8962 +2025-06-25 11:20:45,633 - pyskl - INFO - Epoch [147][100/1281] lr: 4.216e-05, eta: 0:36:58, time: 0.789, data_time: 0.187, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 11:21:35,045 - pyskl - INFO - Epoch [147][200/1281] lr: 4.050e-05, eta: 0:36:14, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0171, loss: 0.0171 +2025-06-25 11:22:24,356 - pyskl - INFO - Epoch [147][300/1281] lr: 3.887e-05, eta: 0:35:30, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 11:23:13,263 - pyskl - INFO - Epoch [147][400/1281] lr: 3.728e-05, eta: 0:34:46, 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 11:24:02,408 - pyskl - INFO - Epoch [147][500/1281] lr: 3.572e-05, eta: 0:34:02, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 11:24:51,461 - pyskl - INFO - Epoch [147][600/1281] lr: 3.419e-05, eta: 0:33:18, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0172, loss: 0.0172 +2025-06-25 11:25:40,608 - pyskl - INFO - Epoch [147][700/1281] lr: 3.270e-05, eta: 0:32:34, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0167, loss: 0.0167 +2025-06-25 11:26:29,884 - pyskl - INFO - Epoch [147][800/1281] lr: 3.124e-05, eta: 0:31:50, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0173, loss: 0.0173 +2025-06-25 11:27:18,914 - pyskl - INFO - Epoch [147][900/1281] lr: 2.981e-05, eta: 0:31:06, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 11:28:07,987 - pyskl - INFO - Epoch [147][1000/1281] lr: 2.842e-05, eta: 0:30:22, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0172, loss: 0.0172 +2025-06-25 11:28:57,376 - pyskl - INFO - Epoch [147][1100/1281] lr: 2.706e-05, eta: 0:29:38, 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 11:29:34,857 - pyskl - INFO - Epoch [147][1200/1281] lr: 2.573e-05, eta: 0:28:53, time: 0.375, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0171, loss: 0.0171 +2025-06-25 11:30:19,319 - pyskl - INFO - Saving checkpoint at 147 epochs +2025-06-25 11:31:06,433 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:31:06,502 - pyskl - INFO - +top1_acc 0.9240 +top5_acc 0.9964 +2025-06-25 11:31:06,502 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:31:06,510 - pyskl - INFO - +mean_acc 0.8938 +2025-06-25 11:31:06,512 - pyskl - INFO - Epoch(val) [147][533] top1_acc: 0.9240, top5_acc: 0.9964, mean_class_accuracy: 0.8938 +2025-06-25 11:32:26,922 - pyskl - INFO - Epoch [148][100/1281] lr: 2.341e-05, eta: 0:27:33, time: 0.804, data_time: 0.184, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 11:33:15,834 - pyskl - INFO - Epoch [148][200/1281] lr: 2.218e-05, eta: 0:26:49, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 11:34:04,970 - pyskl - INFO - Epoch [148][300/1281] lr: 2.098e-05, eta: 0:26:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0161, loss: 0.0161 +2025-06-25 11:34:53,946 - pyskl - INFO - Epoch [148][400/1281] lr: 1.981e-05, eta: 0:25:21, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 11:35:43,198 - pyskl - INFO - Epoch [148][500/1281] lr: 1.868e-05, eta: 0:24:37, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 11:36:32,190 - pyskl - INFO - Epoch [148][600/1281] lr: 1.758e-05, eta: 0:23:53, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0164, loss: 0.0164 +2025-06-25 11:37:21,019 - pyskl - INFO - Epoch [148][700/1281] lr: 1.651e-05, eta: 0:23:09, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0170, loss: 0.0170 +2025-06-25 11:38:09,942 - pyskl - INFO - Epoch [148][800/1281] lr: 1.548e-05, eta: 0:22:25, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 11:38:58,804 - pyskl - INFO - Epoch [148][900/1281] lr: 1.448e-05, eta: 0:21:40, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 11:39:47,861 - pyskl - INFO - Epoch [148][1000/1281] lr: 1.351e-05, eta: 0:20:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0207, loss: 0.0207 +2025-06-25 11:40:36,978 - pyskl - INFO - Epoch [148][1100/1281] lr: 1.258e-05, eta: 0:20:12, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 11:41:12,406 - pyskl - INFO - Epoch [148][1200/1281] lr: 1.168e-05, eta: 0:19:28, time: 0.354, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 11:42:00,096 - pyskl - INFO - Saving checkpoint at 148 epochs +2025-06-25 11:42:48,031 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:42:48,085 - pyskl - INFO - +top1_acc 0.9241 +top5_acc 0.9959 +2025-06-25 11:42:48,085 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:42:48,091 - pyskl - INFO - +mean_acc 0.8949 +2025-06-25 11:42:48,093 - pyskl - INFO - Epoch(val) [148][533] top1_acc: 0.9241, top5_acc: 0.9959, mean_class_accuracy: 0.8949 +2025-06-25 11:44:07,809 - pyskl - INFO - Epoch [149][100/1281] lr: 1.013e-05, eta: 0:18:08, time: 0.797, data_time: 0.185, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0165, loss: 0.0165 +2025-06-25 11:44:56,791 - pyskl - INFO - Epoch [149][200/1281] lr: 9.328e-06, eta: 0:17:24, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0166, loss: 0.0166 +2025-06-25 11:45:45,740 - pyskl - INFO - Epoch [149][300/1281] lr: 8.555e-06, eta: 0:16:40, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 11:46:34,367 - pyskl - INFO - Epoch [149][400/1281] lr: 7.816e-06, eta: 0:15:55, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0181, loss: 0.0181 +2025-06-25 11:47:22,957 - pyskl - INFO - Epoch [149][500/1281] lr: 7.110e-06, eta: 0:15:11, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 11:48:11,805 - pyskl - INFO - Epoch [149][600/1281] lr: 6.437e-06, eta: 0:14:27, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 11:49:00,508 - pyskl - INFO - Epoch [149][700/1281] lr: 5.798e-06, eta: 0:13:43, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 11:49:49,500 - pyskl - INFO - Epoch [149][800/1281] lr: 5.192e-06, eta: 0:12:59, 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 11:50:38,408 - pyskl - INFO - Epoch [149][900/1281] lr: 4.620e-06, eta: 0:12:15, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0175, loss: 0.0175 +2025-06-25 11:51:27,264 - pyskl - INFO - Epoch [149][1000/1281] lr: 4.081e-06, eta: 0:11:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0166, loss: 0.0166 +2025-06-25 11:52:16,092 - pyskl - INFO - Epoch [149][1100/1281] lr: 3.576e-06, eta: 0:10:46, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0177, loss: 0.0177 +2025-06-25 11:52:53,409 - pyskl - INFO - Epoch [149][1200/1281] lr: 3.104e-06, eta: 0:10:02, time: 0.373, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0161, loss: 0.0161 +2025-06-25 11:53:38,897 - pyskl - INFO - Saving checkpoint at 149 epochs +2025-06-25 11:54:26,344 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:54:26,412 - pyskl - INFO - +top1_acc 0.9251 +top5_acc 0.9965 +2025-06-25 11:54:26,413 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:54:26,421 - pyskl - INFO - +mean_acc 0.8953 +2025-06-25 11:54:26,422 - pyskl - INFO - Epoch(val) [149][533] top1_acc: 0.9251, top5_acc: 0.9965, mean_class_accuracy: 0.8953 +2025-06-25 11:55:46,019 - pyskl - INFO - Epoch [150][100/1281] lr: 2.334e-06, eta: 0:08:42, time: 0.796, data_time: 0.190, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 11:56:35,115 - pyskl - INFO - Epoch [150][200/1281] lr: 1.956e-06, eta: 0:07:58, 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 11:57:23,866 - pyskl - INFO - Epoch [150][300/1281] lr: 1.611e-06, eta: 0:07:13, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0178, loss: 0.0178 +2025-06-25 11:58:12,868 - pyskl - INFO - Epoch [150][400/1281] lr: 1.300e-06, eta: 0:06:29, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 11:59:01,695 - pyskl - INFO - Epoch [150][500/1281] lr: 1.022e-06, eta: 0:05:45, 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 11:59:50,612 - pyskl - INFO - Epoch [150][600/1281] lr: 7.771e-07, eta: 0:05:01, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 12:00:39,508 - pyskl - INFO - Epoch [150][700/1281] lr: 5.659e-07, eta: 0:04:17, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 12:01:28,487 - pyskl - INFO - Epoch [150][800/1281] lr: 3.881e-07, eta: 0:03:32, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 12:02:17,434 - pyskl - INFO - Epoch [150][900/1281] lr: 2.438e-07, eta: 0:02:48, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 12:03:06,398 - pyskl - INFO - Epoch [150][1000/1281] lr: 1.329e-07, eta: 0:02:04, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0169, loss: 0.0169 +2025-06-25 12:03:55,404 - pyskl - INFO - Epoch [150][1100/1281] lr: 5.534e-08, eta: 0:01:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0169, loss: 0.0169 +2025-06-25 12:04:32,255 - pyskl - INFO - Epoch [150][1200/1281] lr: 1.123e-08, eta: 0:00:35, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0159, loss: 0.0159 +2025-06-25 12:05:16,602 - pyskl - INFO - Saving checkpoint at 150 epochs +2025-06-25 12:06:04,129 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 12:06:04,196 - pyskl - INFO - +top1_acc 0.9237 +top5_acc 0.9964 +2025-06-25 12:06:04,197 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 12:06:04,204 - pyskl - INFO - +mean_acc 0.8932 +2025-06-25 12:06:04,206 - pyskl - INFO - Epoch(val) [150][533] top1_acc: 0.9237, top5_acc: 0.9964, mean_class_accuracy: 0.8932 +2025-06-25 12:06:08,676 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-06-25 12:13:45,791 - pyskl - INFO - Testing results of the last checkpoint +2025-06-25 12:13:45,792 - pyskl - INFO - top1_acc: 0.9289 +2025-06-25 12:13:45,792 - pyskl - INFO - top5_acc: 0.9969 +2025-06-25 12:13:45,792 - pyskl - INFO - mean_class_accuracy: 0.8982 +2025-06-25 12:13:45,792 - pyskl - INFO - load checkpoint from local path: ./work_dirs/test_aclnet/finegym/j_3/best_top1_acc_epoch_146.pth +2025-06-25 12:21:27,191 - pyskl - INFO - Testing results of the best checkpoint +2025-06-25 12:21:27,192 - pyskl - INFO - top1_acc: 0.9283 +2025-06-25 12:21:27,192 - pyskl - INFO - top5_acc: 0.9971 +2025-06-25 12:21:27,192 - pyskl - INFO - mean_class_accuracy: 0.8998