diff --git "a/finegym/b_2/20250624_084254.log" "b/finegym/b_2/20250624_084254.log" new file mode 100644--- /dev/null +++ "b/finegym/b_2/20250624_084254.log" @@ -0,0 +1,3474 @@ +2025-06-24 08:42:54,192 - pyskl - INFO - Environment info: +------------------------------------------------------------ +sys.platform: linux +Python: 3.7.11 (default, Jul 27 2021, 14:32:16) [GCC 7.5.0] +CUDA available: True +GPU 0: Tesla V100-PCIE-32GB +CUDA_HOME: /usr/local/cuda-11.7 +NVCC: Cuda compilation tools, release 11.7, V11.7.64 +GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0 +PyTorch: 1.11.0 +PyTorch compiling details: PyTorch built with: + - GCC 7.3 + - C++ Version: 201402 + - Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications + - Intel(R) MKL-DNN v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e) + - OpenMP 201511 (a.k.a. OpenMP 4.5) + - LAPACK is enabled (usually provided by MKL) + - NNPACK is enabled + - CPU capability usage: AVX2 + - CUDA Runtime 11.3 + - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_37,code=compute_37 + - CuDNN 8.2 + - Magma 2.5.2 + - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, + +TorchVision: 0.12.0 +OpenCV: 4.8.0 +MMCV: 1.5.0 +MMCV Compiler: GCC 7.3 +MMCV CUDA Compiler: 11.3 +pyskl: 0.1.0+ +------------------------------------------------------------ + +2025-06-24 08:42:54,390 - pyskl - INFO - Config: modality = 'b' +graph = 'coco_new' +work_dir = './work_dirs/test_aclnet/finegym/b_2' +model = dict( + type='RecognizerGCN', + backbone=dict( + type='GCN_Module', + gcn_ratio=0.125, + gcn_ctr='T', + gcn_ada='T', + tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'], + graph_cfg=dict( + layout='coco_new', + mode='random', + num_filter=8, + init_off=0.04, + init_std=0.02)), + cls_head=dict(type='SimpleHead', data_cfg='finegym', num_classes=99, in_channels=384)) +dataset_type = 'PoseDataset' +ann_file = '/data/lhd/pyskl_data/gym/gym_hrnet.pkl' +left_kp = [1, 3, 5, 7, 9, 11, 13, 15] +right_kp = [2, 4, 6, 8, 10, 12, 14, 16] +train_pipeline = [ + dict(type='UniformSampleFrames', clip_len=100), + dict(type='PoseDecode'), + dict( + type='Flip', + flip_ratio=0.5, + left_kp=[1, 3, 5, 7, 9, 11, 13, 15], + right_kp=[2, 4, 6, 8, 10, 12, 14, 16]), + dict(type='Kinetics_Transform'), + dict(type='GenSkeFeat', dataset='coco_new', feats=['b']), + dict(type='FormatGCNInput', num_person=2), + dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]), + dict(type='ToTensor', keys=['keypoint']) +] +val_pipeline = [ + dict(type='UniformSampleFrames', clip_len=100, num_clips=1), + dict(type='PoseDecode'), + dict(type='Kinetics_Transform'), + dict(type='GenSkeFeat', dataset='coco_new', feats=['b']), + dict(type='FormatGCNInput', num_person=2), + dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]), + dict(type='ToTensor', keys=['keypoint']) +] +test_pipeline = [ + dict(type='UniformSampleFrames', clip_len=100, num_clips=10), + dict(type='PoseDecode'), + dict(type='Kinetics_Transform'), + dict(type='GenSkeFeat', dataset='coco_new', feats=['b']), + dict(type='FormatGCNInput', num_person=2), + dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]), + dict(type='ToTensor', keys=['keypoint']) +] +data = dict( + videos_per_gpu=16, + workers_per_gpu=4, + test_dataloader=dict(videos_per_gpu=1), + train=dict( + type='PoseDataset', + ann_file='/data/lhd/pyskl_data/gym/gym_hrnet.pkl', + pipeline=[ + dict(type='UniformSampleFrames', clip_len=100), + dict(type='PoseDecode'), + dict( + type='Flip', + flip_ratio=0.5, + left_kp=[1, 3, 5, 7, 9, 11, 13, 15], + right_kp=[2, 4, 6, 8, 10, 12, 14, 16]), + dict(type='Kinetics_Transform'), + dict(type='GenSkeFeat', dataset='coco_new', feats=['b']), + dict(type='FormatGCNInput', num_person=2), + dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]), + dict(type='ToTensor', keys=['keypoint']) + ], + split='train'), + val=dict( + type='PoseDataset', + ann_file='/data/lhd/pyskl_data/gym/gym_hrnet.pkl', + pipeline=[ + dict(type='UniformSampleFrames', clip_len=100, num_clips=1), + dict(type='PoseDecode'), + dict(type='Kinetics_Transform'), + dict(type='GenSkeFeat', dataset='coco_new', feats=['b']), + dict(type='FormatGCNInput', num_person=2), + dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]), + dict(type='ToTensor', keys=['keypoint']) + ], + split='val'), + test=dict( + type='PoseDataset', + ann_file='/data/lhd/pyskl_data/gym/gym_hrnet.pkl', + pipeline=[ + dict(type='UniformSampleFrames', clip_len=100, num_clips=10), + dict(type='PoseDecode'), + dict(type='Kinetics_Transform'), + dict(type='GenSkeFeat', dataset='coco_new', feats=['b']), + dict(type='FormatGCNInput', num_person=2), + dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]), + dict(type='ToTensor', keys=['keypoint']) + ], + split='val')) +optimizer = dict( + type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True) +optimizer_config = dict(grad_clip=None) +lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False) +total_epochs = 150 +checkpoint_config = dict(interval=1) +evaluation = dict( + interval=1, metrics=['top_k_accuracy', 'mean_class_accuracy'], topk=(1, 5)) +log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')]) +dist_params = dict(backend='nccl') +gpu_ids = range(0, 1) + +2025-06-24 08:42:54,391 - pyskl - INFO - Set random seed to 1488861688, deterministic: False +2025-06-24 08:42:55,815 - pyskl - INFO - 20484 videos remain after valid thresholding +2025-06-24 08:42:59,854 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-06-24 08:42:59,855 - pyskl - INFO - Start running, host: lhd@zkyd, work_dir: /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2 +2025-06-24 08:42:59,855 - pyskl - INFO - Hooks will be executed in the following order: +before_run: +(VERY_HIGH ) CosineAnnealingLrUpdaterHook +(NORMAL ) CustomCheckpointHook +(NORMAL ) DistEvalHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_train_epoch: +(VERY_HIGH ) CosineAnnealingLrUpdaterHook +(NORMAL ) DistSamplerSeedHook +(NORMAL ) DistEvalHook +(LOW ) IterTimerHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_train_iter: +(VERY_HIGH ) CosineAnnealingLrUpdaterHook +(NORMAL ) DistEvalHook +(LOW ) IterTimerHook + -------------------- +after_train_iter: +(ABOVE_NORMAL) OptimizerHook +(NORMAL ) CustomCheckpointHook +(NORMAL ) DistEvalHook +(LOW ) IterTimerHook +(VERY_LOW ) TextLoggerHook + -------------------- +after_train_epoch: +(NORMAL ) CustomCheckpointHook +(NORMAL ) DistEvalHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_val_epoch: +(NORMAL ) DistSamplerSeedHook +(LOW ) IterTimerHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_val_iter: +(LOW ) IterTimerHook + -------------------- +after_val_iter: +(LOW ) IterTimerHook + -------------------- +after_val_epoch: +(VERY_LOW ) TextLoggerHook + -------------------- +after_run: +(VERY_LOW ) TextLoggerHook + -------------------- +2025-06-24 08:42:59,855 - pyskl - INFO - workflow: [('train', 1)], max: 150 epochs +2025-06-24 08:42:59,856 - pyskl - INFO - Checkpoints will be saved to /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2 by HardDiskBackend. +2025-06-24 08:43:38,804 - pyskl - INFO - Epoch [1][100/1281] lr: 2.500e-02, eta: 20:46:34, time: 0.389, data_time: 0.175, memory: 4082, top1_acc: 0.0681, top5_acc: 0.2437, loss_cls: 4.5232, loss: 4.5232 +2025-06-24 08:44:00,066 - pyskl - INFO - Epoch [1][200/1281] lr: 2.500e-02, eta: 16:03:02, time: 0.213, data_time: 0.000, memory: 4082, top1_acc: 0.0938, top5_acc: 0.3544, loss_cls: 4.4434, loss: 4.4434 +2025-06-24 08:44:21,627 - pyskl - INFO - Epoch [1][300/1281] lr: 2.500e-02, eta: 14:31:29, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.0875, top5_acc: 0.3812, loss_cls: 4.2217, loss: 4.2217 +2025-06-24 08:44:43,275 - pyskl - INFO - Epoch [1][400/1281] lr: 2.500e-02, eta: 13:46:13, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.1256, top5_acc: 0.4300, loss_cls: 4.0282, loss: 4.0282 +2025-06-24 08:45:04,499 - pyskl - INFO - Epoch [1][500/1281] lr: 2.500e-02, eta: 13:16:13, time: 0.212, data_time: 0.000, memory: 4082, top1_acc: 0.1500, top5_acc: 0.4844, loss_cls: 3.8271, loss: 3.8271 +2025-06-24 08:45:25,883 - pyskl - INFO - Epoch [1][600/1281] lr: 2.500e-02, eta: 12:56:56, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.1862, top5_acc: 0.5144, loss_cls: 3.6721, loss: 3.6721 +2025-06-24 08:45:47,318 - pyskl - INFO - Epoch [1][700/1281] lr: 2.500e-02, eta: 12:43:18, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.2181, top5_acc: 0.5537, loss_cls: 3.5399, loss: 3.5399 +2025-06-24 08:46:08,673 - pyskl - INFO - Epoch [1][800/1281] lr: 2.500e-02, eta: 12:32:40, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.2612, top5_acc: 0.6131, loss_cls: 3.3254, loss: 3.3254 +2025-06-24 08:46:30,268 - pyskl - INFO - Epoch [1][900/1281] lr: 2.500e-02, eta: 12:25:10, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.2706, top5_acc: 0.6262, loss_cls: 3.2020, loss: 3.2020 +2025-06-24 08:46:51,892 - pyskl - INFO - Epoch [1][1000/1281] lr: 2.500e-02, eta: 12:19:11, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.2913, top5_acc: 0.6575, loss_cls: 3.0940, loss: 3.0940 +2025-06-24 08:47:13,536 - pyskl - INFO - Epoch [1][1100/1281] lr: 2.500e-02, eta: 12:14:17, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.3063, top5_acc: 0.6975, loss_cls: 2.9214, loss: 2.9214 +2025-06-24 08:47:35,230 - pyskl - INFO - Epoch [1][1200/1281] lr: 2.500e-02, eta: 12:10:16, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.3569, top5_acc: 0.7381, loss_cls: 2.7354, loss: 2.7354 +2025-06-24 08:47:53,473 - pyskl - INFO - Saving checkpoint at 1 epochs +2025-06-24 08:48:36,358 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 08:48:36,411 - pyskl - INFO - +top1_acc 0.3995 +top5_acc 0.7879 +2025-06-24 08:48:36,411 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 08:48:36,423 - pyskl - INFO - +mean_acc 0.2130 +2025-06-24 08:48:36,593 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_1.pth. +2025-06-24 08:48:36,593 - pyskl - INFO - Best top1_acc is 0.3995 at 1 epoch. +2025-06-24 08:48:36,596 - pyskl - INFO - Epoch(val) [1][533] top1_acc: 0.3995, top5_acc: 0.7879, mean_class_accuracy: 0.2130 +2025-06-24 08:49:16,602 - pyskl - INFO - Epoch [2][100/1281] lr: 2.500e-02, eta: 12:06:03, time: 0.400, data_time: 0.184, memory: 4082, top1_acc: 0.3919, top5_acc: 0.7994, loss_cls: 2.5334, loss: 2.5334 +2025-06-24 08:49:38,432 - pyskl - INFO - Epoch [2][200/1281] lr: 2.500e-02, eta: 12:03:31, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.3981, top5_acc: 0.8081, loss_cls: 2.5091, loss: 2.5091 +2025-06-24 08:50:00,107 - pyskl - INFO - Epoch [2][300/1281] lr: 2.500e-02, eta: 12:00:56, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.4369, top5_acc: 0.8269, loss_cls: 2.3453, loss: 2.3453 +2025-06-24 08:50:21,768 - pyskl - INFO - Epoch [2][400/1281] lr: 2.500e-02, eta: 11:58:36, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.4612, top5_acc: 0.8331, loss_cls: 2.3006, loss: 2.3006 +2025-06-24 08:50:43,557 - pyskl - INFO - Epoch [2][500/1281] lr: 2.499e-02, eta: 11:56:42, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.4512, top5_acc: 0.8488, loss_cls: 2.2694, loss: 2.2694 +2025-06-24 08:51:05,214 - pyskl - INFO - Epoch [2][600/1281] lr: 2.499e-02, eta: 11:54:45, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.4600, top5_acc: 0.8669, loss_cls: 2.1630, loss: 2.1630 +2025-06-24 08:51:26,819 - pyskl - INFO - Epoch [2][700/1281] lr: 2.499e-02, eta: 11:52:53, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.4806, top5_acc: 0.8725, loss_cls: 2.1396, loss: 2.1396 +2025-06-24 08:51:48,781 - pyskl - INFO - Epoch [2][800/1281] lr: 2.499e-02, eta: 11:51:42, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.5044, top5_acc: 0.8769, loss_cls: 2.0691, loss: 2.0691 +2025-06-24 08:52:10,462 - pyskl - INFO - Epoch [2][900/1281] lr: 2.499e-02, eta: 11:50:11, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.5094, top5_acc: 0.8812, loss_cls: 2.0220, loss: 2.0220 +2025-06-24 08:52:32,076 - pyskl - INFO - Epoch [2][1000/1281] lr: 2.499e-02, eta: 11:48:40, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.5112, top5_acc: 0.8912, loss_cls: 1.9777, loss: 1.9777 +2025-06-24 08:52:53,911 - pyskl - INFO - Epoch [2][1100/1281] lr: 2.499e-02, eta: 11:47:33, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.5275, top5_acc: 0.8869, loss_cls: 1.9321, loss: 1.9321 +2025-06-24 08:53:15,579 - pyskl - INFO - Epoch [2][1200/1281] lr: 2.499e-02, eta: 11:46:17, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.5494, top5_acc: 0.8938, loss_cls: 1.9134, loss: 1.9134 +2025-06-24 08:53:33,774 - pyskl - INFO - Saving checkpoint at 2 epochs +2025-06-24 08:54:16,866 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 08:54:16,923 - pyskl - INFO - +top1_acc 0.5394 +top5_acc 0.9010 +2025-06-24 08:54:16,923 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 08:54:16,929 - pyskl - INFO - +mean_acc 0.3727 +2025-06-24 08:54:16,935 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_1.pth was removed +2025-06-24 08:54:17,131 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_2.pth. +2025-06-24 08:54:17,131 - pyskl - INFO - Best top1_acc is 0.5394 at 2 epoch. +2025-06-24 08:54:17,134 - pyskl - INFO - Epoch(val) [2][533] top1_acc: 0.5394, top5_acc: 0.9010, mean_class_accuracy: 0.3727 +2025-06-24 08:54:57,211 - pyskl - INFO - Epoch [3][100/1281] lr: 2.499e-02, eta: 11:45:11, time: 0.401, data_time: 0.187, memory: 4082, top1_acc: 0.5675, top5_acc: 0.9150, loss_cls: 1.8082, loss: 1.8082 +2025-06-24 08:55:18,622 - pyskl - INFO - Epoch [3][200/1281] lr: 2.499e-02, eta: 11:43:45, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.5706, top5_acc: 0.9150, loss_cls: 1.7889, loss: 1.7889 +2025-06-24 08:55:40,164 - pyskl - INFO - Epoch [3][300/1281] lr: 2.499e-02, eta: 11:42:33, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.5813, top5_acc: 0.9281, loss_cls: 1.7373, loss: 1.7373 +2025-06-24 08:56:01,911 - pyskl - INFO - Epoch [3][400/1281] lr: 2.499e-02, eta: 11:41:37, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.5875, top5_acc: 0.9294, loss_cls: 1.7159, loss: 1.7159 +2025-06-24 08:56:23,286 - pyskl - INFO - Epoch [3][500/1281] lr: 2.498e-02, eta: 11:40:21, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.5713, top5_acc: 0.9200, loss_cls: 1.7391, loss: 1.7391 +2025-06-24 08:56:44,526 - pyskl - INFO - Epoch [3][600/1281] lr: 2.498e-02, eta: 11:39:00, time: 0.212, data_time: 0.000, memory: 4082, top1_acc: 0.6044, top5_acc: 0.9256, loss_cls: 1.6852, loss: 1.6852 +2025-06-24 08:57:06,017 - pyskl - INFO - Epoch [3][700/1281] lr: 2.498e-02, eta: 11:37:57, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.5994, top5_acc: 0.9437, loss_cls: 1.6409, loss: 1.6409 +2025-06-24 08:57:27,723 - pyskl - INFO - Epoch [3][800/1281] lr: 2.498e-02, eta: 11:37:09, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6062, top5_acc: 0.9450, loss_cls: 1.6154, loss: 1.6154 +2025-06-24 08:57:49,208 - pyskl - INFO - Epoch [3][900/1281] lr: 2.498e-02, eta: 11:36:10, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.6319, top5_acc: 0.9444, loss_cls: 1.5595, loss: 1.5595 +2025-06-24 08:58:10,644 - pyskl - INFO - Epoch [3][1000/1281] lr: 2.498e-02, eta: 11:35:10, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.6425, top5_acc: 0.9519, loss_cls: 1.4973, loss: 1.4973 +2025-06-24 08:58:32,104 - pyskl - INFO - Epoch [3][1100/1281] lr: 2.498e-02, eta: 11:34:14, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.6150, top5_acc: 0.9425, loss_cls: 1.6283, loss: 1.6283 +2025-06-24 08:58:53,702 - pyskl - INFO - Epoch [3][1200/1281] lr: 2.498e-02, eta: 11:33:27, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.6275, top5_acc: 0.9500, loss_cls: 1.5224, loss: 1.5224 +2025-06-24 08:59:11,785 - pyskl - INFO - Saving checkpoint at 3 epochs +2025-06-24 08:59:55,508 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 08:59:55,564 - pyskl - INFO - +top1_acc 0.5991 +top5_acc 0.9347 +2025-06-24 08:59:55,564 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 08:59:55,571 - pyskl - INFO - +mean_acc 0.4454 +2025-06-24 08:59:55,575 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_2.pth was removed +2025-06-24 08:59:55,762 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_3.pth. +2025-06-24 08:59:55,762 - pyskl - INFO - Best top1_acc is 0.5991 at 3 epoch. +2025-06-24 08:59:55,765 - pyskl - INFO - Epoch(val) [3][533] top1_acc: 0.5991, top5_acc: 0.9347, mean_class_accuracy: 0.4454 +2025-06-24 09:00:35,736 - pyskl - INFO - Epoch [4][100/1281] lr: 2.497e-02, eta: 11:32:47, time: 0.400, data_time: 0.182, memory: 4082, top1_acc: 0.6456, top5_acc: 0.9537, loss_cls: 1.4666, loss: 1.4666 +2025-06-24 09:00:57,506 - pyskl - INFO - Epoch [4][200/1281] lr: 2.497e-02, eta: 11:32:10, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.6506, top5_acc: 0.9563, loss_cls: 1.4189, loss: 1.4189 +2025-06-24 09:01:19,208 - pyskl - INFO - Epoch [4][300/1281] lr: 2.497e-02, eta: 11:31:31, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6606, top5_acc: 0.9550, loss_cls: 1.4052, loss: 1.4052 +2025-06-24 09:01:40,732 - pyskl - INFO - Epoch [4][400/1281] lr: 2.497e-02, eta: 11:30:44, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.6450, top5_acc: 0.9506, loss_cls: 1.5064, loss: 1.5064 +2025-06-24 09:02:02,799 - pyskl - INFO - Epoch [4][500/1281] lr: 2.497e-02, eta: 11:30:23, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.6231, top5_acc: 0.9544, loss_cls: 1.4858, loss: 1.4858 +2025-06-24 09:02:24,227 - pyskl - INFO - Epoch [4][600/1281] lr: 2.497e-02, eta: 11:29:34, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.6506, top5_acc: 0.9525, loss_cls: 1.4200, loss: 1.4200 +2025-06-24 09:02:45,782 - pyskl - INFO - Epoch [4][700/1281] lr: 2.497e-02, eta: 11:28:52, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.6763, top5_acc: 0.9650, loss_cls: 1.3261, loss: 1.3261 +2025-06-24 09:03:07,536 - pyskl - INFO - Epoch [4][800/1281] lr: 2.496e-02, eta: 11:28:19, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.6881, top5_acc: 0.9656, loss_cls: 1.3615, loss: 1.3615 +2025-06-24 09:03:29,397 - pyskl - INFO - Epoch [4][900/1281] lr: 2.496e-02, eta: 11:27:50, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.6806, top5_acc: 0.9619, loss_cls: 1.3752, loss: 1.3752 +2025-06-24 09:03:51,128 - pyskl - INFO - Epoch [4][1000/1281] lr: 2.496e-02, eta: 11:27:17, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6875, top5_acc: 0.9625, loss_cls: 1.3213, loss: 1.3213 +2025-06-24 09:04:12,849 - pyskl - INFO - Epoch [4][1100/1281] lr: 2.496e-02, eta: 11:26:44, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.6894, top5_acc: 0.9587, loss_cls: 1.3502, loss: 1.3502 +2025-06-24 09:04:34,442 - pyskl - INFO - Epoch [4][1200/1281] lr: 2.496e-02, eta: 11:26:06, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.6900, top5_acc: 0.9594, loss_cls: 1.2917, loss: 1.2917 +2025-06-24 09:04:52,379 - pyskl - INFO - Saving checkpoint at 4 epochs +2025-06-24 09:05:36,039 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:05:36,093 - pyskl - INFO - +top1_acc 0.6840 +top5_acc 0.9596 +2025-06-24 09:05:36,094 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:05:36,101 - pyskl - INFO - +mean_acc 0.5586 +2025-06-24 09:05:36,105 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_3.pth was removed +2025-06-24 09:05:36,283 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_4.pth. +2025-06-24 09:05:36,284 - pyskl - INFO - Best top1_acc is 0.6840 at 4 epoch. +2025-06-24 09:05:36,287 - pyskl - INFO - Epoch(val) [4][533] top1_acc: 0.6840, top5_acc: 0.9596, mean_class_accuracy: 0.5586 +2025-06-24 09:06:16,191 - pyskl - INFO - Epoch [5][100/1281] lr: 2.495e-02, eta: 11:25:29, time: 0.399, data_time: 0.182, memory: 4082, top1_acc: 0.6906, top5_acc: 0.9663, loss_cls: 1.2890, loss: 1.2890 +2025-06-24 09:06:38,145 - pyskl - INFO - Epoch [5][200/1281] lr: 2.495e-02, eta: 11:25:05, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.6787, top5_acc: 0.9719, loss_cls: 1.2767, loss: 1.2767 +2025-06-24 09:06:59,679 - pyskl - INFO - Epoch [5][300/1281] lr: 2.495e-02, eta: 11:24:27, time: 0.215, data_time: 0.001, memory: 4082, top1_acc: 0.6769, top5_acc: 0.9675, loss_cls: 1.2991, loss: 1.2991 +2025-06-24 09:07:21,330 - pyskl - INFO - Epoch [5][400/1281] lr: 2.495e-02, eta: 11:23:54, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7019, top5_acc: 0.9663, loss_cls: 1.2722, loss: 1.2722 +2025-06-24 09:07:42,886 - pyskl - INFO - Epoch [5][500/1281] lr: 2.495e-02, eta: 11:23:17, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7031, top5_acc: 0.9725, loss_cls: 1.2429, loss: 1.2429 +2025-06-24 09:08:04,403 - pyskl - INFO - Epoch [5][600/1281] lr: 2.495e-02, eta: 11:22:40, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7113, top5_acc: 0.9762, loss_cls: 1.2054, loss: 1.2054 +2025-06-24 09:08:26,125 - pyskl - INFO - Epoch [5][700/1281] lr: 2.494e-02, eta: 11:22:10, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7087, top5_acc: 0.9712, loss_cls: 1.2324, loss: 1.2324 +2025-06-24 09:08:47,806 - pyskl - INFO - Epoch [5][800/1281] lr: 2.494e-02, eta: 11:21:39, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7087, top5_acc: 0.9650, loss_cls: 1.2261, loss: 1.2261 +2025-06-24 09:09:09,316 - pyskl - INFO - Epoch [5][900/1281] lr: 2.494e-02, eta: 11:21:03, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.6969, top5_acc: 0.9719, loss_cls: 1.2182, loss: 1.2182 +2025-06-24 09:09:30,656 - pyskl - INFO - Epoch [5][1000/1281] lr: 2.494e-02, eta: 11:20:23, time: 0.213, data_time: 0.000, memory: 4082, top1_acc: 0.7169, top5_acc: 0.9750, loss_cls: 1.2064, loss: 1.2064 +2025-06-24 09:09:51,993 - pyskl - INFO - Epoch [5][1100/1281] lr: 2.494e-02, eta: 11:19:42, time: 0.213, data_time: 0.000, memory: 4082, top1_acc: 0.7100, top5_acc: 0.9663, loss_cls: 1.2030, loss: 1.2030 +2025-06-24 09:10:13,311 - pyskl - INFO - Epoch [5][1200/1281] lr: 2.493e-02, eta: 11:19:02, time: 0.213, data_time: 0.000, memory: 4082, top1_acc: 0.7200, top5_acc: 0.9744, loss_cls: 1.1516, loss: 1.1516 +2025-06-24 09:10:31,367 - pyskl - INFO - Saving checkpoint at 5 epochs +2025-06-24 09:11:14,819 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:11:14,874 - pyskl - INFO - +top1_acc 0.7080 +top5_acc 0.9666 +2025-06-24 09:11:14,874 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:11:14,881 - pyskl - INFO - +mean_acc 0.5733 +2025-06-24 09:11:14,885 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_4.pth was removed +2025-06-24 09:11:15,067 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_5.pth. +2025-06-24 09:11:15,067 - pyskl - INFO - Best top1_acc is 0.7080 at 5 epoch. +2025-06-24 09:11:15,070 - pyskl - INFO - Epoch(val) [5][533] top1_acc: 0.7080, top5_acc: 0.9666, mean_class_accuracy: 0.5733 +2025-06-24 09:11:55,537 - pyskl - INFO - Epoch [6][100/1281] lr: 2.493e-02, eta: 11:18:45, time: 0.405, data_time: 0.189, memory: 4082, top1_acc: 0.7200, top5_acc: 0.9700, loss_cls: 1.1732, loss: 1.1732 +2025-06-24 09:12:17,217 - pyskl - INFO - Epoch [6][200/1281] lr: 2.493e-02, eta: 11:18:16, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7331, top5_acc: 0.9750, loss_cls: 1.1663, loss: 1.1663 +2025-06-24 09:12:38,826 - pyskl - INFO - Epoch [6][300/1281] lr: 2.492e-02, eta: 11:17:45, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7319, top5_acc: 0.9794, loss_cls: 1.1330, loss: 1.1330 +2025-06-24 09:13:00,051 - pyskl - INFO - Epoch [6][400/1281] lr: 2.492e-02, eta: 11:17:04, time: 0.212, data_time: 0.000, memory: 4082, top1_acc: 0.7231, top5_acc: 0.9762, loss_cls: 1.1295, loss: 1.1295 +2025-06-24 09:13:21,934 - pyskl - INFO - Epoch [6][500/1281] lr: 2.492e-02, eta: 11:16:41, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7431, top5_acc: 0.9788, loss_cls: 1.1148, loss: 1.1148 +2025-06-24 09:13:43,739 - pyskl - INFO - Epoch [6][600/1281] lr: 2.492e-02, eta: 11:16:16, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7419, top5_acc: 0.9775, loss_cls: 1.1084, loss: 1.1084 +2025-06-24 09:14:05,571 - pyskl - INFO - Epoch [6][700/1281] lr: 2.492e-02, eta: 11:15:52, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7312, top5_acc: 0.9719, loss_cls: 1.1711, loss: 1.1711 +2025-06-24 09:14:27,200 - pyskl - INFO - Epoch [6][800/1281] lr: 2.491e-02, eta: 11:15:22, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7488, top5_acc: 0.9781, loss_cls: 1.0753, loss: 1.0753 +2025-06-24 09:14:48,656 - pyskl - INFO - Epoch [6][900/1281] lr: 2.491e-02, eta: 11:14:49, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7412, top5_acc: 0.9744, loss_cls: 1.0961, loss: 1.0961 +2025-06-24 09:15:10,502 - pyskl - INFO - Epoch [6][1000/1281] lr: 2.491e-02, eta: 11:14:26, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7188, top5_acc: 0.9681, loss_cls: 1.1981, loss: 1.1981 +2025-06-24 09:15:31,921 - pyskl - INFO - Epoch [6][1100/1281] lr: 2.491e-02, eta: 11:13:52, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7475, top5_acc: 0.9819, loss_cls: 1.0751, loss: 1.0751 +2025-06-24 09:15:53,582 - pyskl - INFO - Epoch [6][1200/1281] lr: 2.490e-02, eta: 11:13:24, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7450, top5_acc: 0.9769, loss_cls: 1.1060, loss: 1.1060 +2025-06-24 09:16:11,977 - pyskl - INFO - Saving checkpoint at 6 epochs +2025-06-24 09:16:55,602 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:16:55,676 - pyskl - INFO - +top1_acc 0.7098 +top5_acc 0.9668 +2025-06-24 09:16:55,676 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:16:55,685 - pyskl - INFO - +mean_acc 0.5972 +2025-06-24 09:16:55,690 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_5.pth was removed +2025-06-24 09:16:55,871 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_6.pth. +2025-06-24 09:16:55,872 - pyskl - INFO - Best top1_acc is 0.7098 at 6 epoch. +2025-06-24 09:16:55,874 - pyskl - INFO - Epoch(val) [6][533] top1_acc: 0.7098, top5_acc: 0.9668, mean_class_accuracy: 0.5972 +2025-06-24 09:17:35,979 - pyskl - INFO - Epoch [7][100/1281] lr: 2.490e-02, eta: 11:12:56, time: 0.401, data_time: 0.183, memory: 4082, top1_acc: 0.7412, top5_acc: 0.9744, loss_cls: 1.1101, loss: 1.1101 +2025-06-24 09:17:57,496 - pyskl - INFO - Epoch [7][200/1281] lr: 2.490e-02, eta: 11:12:25, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7469, top5_acc: 0.9788, loss_cls: 1.0499, loss: 1.0499 +2025-06-24 09:18:19,281 - pyskl - INFO - Epoch [7][300/1281] lr: 2.489e-02, eta: 11:12:00, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7631, top5_acc: 0.9869, loss_cls: 1.0021, loss: 1.0021 +2025-06-24 09:18:40,812 - pyskl - INFO - Epoch [7][400/1281] lr: 2.489e-02, eta: 11:11:30, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7500, top5_acc: 0.9831, loss_cls: 1.0753, loss: 1.0753 +2025-06-24 09:19:02,398 - pyskl - INFO - Epoch [7][500/1281] lr: 2.489e-02, eta: 11:11:01, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7531, top5_acc: 0.9812, loss_cls: 1.0612, loss: 1.0612 +2025-06-24 09:19:23,928 - pyskl - INFO - Epoch [7][600/1281] lr: 2.489e-02, eta: 11:10:32, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7431, top5_acc: 0.9819, loss_cls: 1.0841, loss: 1.0841 +2025-06-24 09:19:45,370 - pyskl - INFO - Epoch [7][700/1281] lr: 2.488e-02, eta: 11:10:00, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7544, top5_acc: 0.9750, loss_cls: 1.0587, loss: 1.0587 +2025-06-24 09:20:07,081 - pyskl - INFO - Epoch [7][800/1281] lr: 2.488e-02, eta: 11:09:35, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7494, top5_acc: 0.9762, loss_cls: 1.0687, loss: 1.0687 +2025-06-24 09:20:28,483 - pyskl - INFO - Epoch [7][900/1281] lr: 2.488e-02, eta: 11:09:03, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7462, top5_acc: 0.9788, loss_cls: 1.0368, loss: 1.0368 +2025-06-24 09:20:50,069 - pyskl - INFO - Epoch [7][1000/1281] lr: 2.487e-02, eta: 11:08:35, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7600, top5_acc: 0.9794, loss_cls: 1.0615, loss: 1.0615 +2025-06-24 09:21:11,774 - pyskl - INFO - Epoch [7][1100/1281] lr: 2.487e-02, eta: 11:08:09, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7519, top5_acc: 0.9812, loss_cls: 1.0599, loss: 1.0599 +2025-06-24 09:21:33,578 - pyskl - INFO - Epoch [7][1200/1281] lr: 2.487e-02, eta: 11:07:46, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7538, top5_acc: 0.9762, loss_cls: 1.0639, loss: 1.0639 +2025-06-24 09:21:51,783 - pyskl - INFO - Saving checkpoint at 7 epochs +2025-06-24 09:22:35,523 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:22:35,580 - pyskl - INFO - +top1_acc 0.7171 +top5_acc 0.9716 +2025-06-24 09:22:35,580 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:22:35,587 - pyskl - INFO - +mean_acc 0.6211 +2025-06-24 09:22:35,591 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_6.pth was removed +2025-06-24 09:22:35,775 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_7.pth. +2025-06-24 09:22:35,776 - pyskl - INFO - Best top1_acc is 0.7171 at 7 epoch. +2025-06-24 09:22:35,778 - pyskl - INFO - Epoch(val) [7][533] top1_acc: 0.7171, top5_acc: 0.9716, mean_class_accuracy: 0.6211 +2025-06-24 09:23:16,076 - pyskl - INFO - Epoch [8][100/1281] lr: 2.486e-02, eta: 11:07:21, time: 0.403, data_time: 0.186, memory: 4082, top1_acc: 0.7837, top5_acc: 0.9862, loss_cls: 0.9567, loss: 0.9567 +2025-06-24 09:23:37,542 - pyskl - INFO - Epoch [8][200/1281] lr: 2.486e-02, eta: 11:06:51, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7675, top5_acc: 0.9819, loss_cls: 0.9809, loss: 0.9809 +2025-06-24 09:23:59,191 - pyskl - INFO - Epoch [8][300/1281] lr: 2.486e-02, eta: 11:06:25, time: 0.216, data_time: 0.001, memory: 4082, top1_acc: 0.7588, top5_acc: 0.9825, loss_cls: 1.0359, loss: 1.0359 +2025-06-24 09:24:20,746 - pyskl - INFO - Epoch [8][400/1281] lr: 2.485e-02, eta: 11:05:57, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7500, top5_acc: 0.9812, loss_cls: 1.0395, loss: 1.0395 +2025-06-24 09:24:42,504 - pyskl - INFO - Epoch [8][500/1281] lr: 2.485e-02, eta: 11:05:33, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7481, top5_acc: 0.9806, loss_cls: 1.0499, loss: 1.0499 +2025-06-24 09:25:04,041 - pyskl - INFO - Epoch [8][600/1281] lr: 2.485e-02, eta: 11:05:05, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7544, top5_acc: 0.9838, loss_cls: 1.0043, loss: 1.0043 +2025-06-24 09:25:25,258 - pyskl - INFO - Epoch [8][700/1281] lr: 2.484e-02, eta: 11:04:31, time: 0.212, data_time: 0.000, memory: 4082, top1_acc: 0.7681, top5_acc: 0.9844, loss_cls: 0.9884, loss: 0.9884 +2025-06-24 09:25:46,696 - pyskl - INFO - Epoch [8][800/1281] lr: 2.484e-02, eta: 11:04:02, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7644, top5_acc: 0.9781, loss_cls: 1.0216, loss: 1.0216 +2025-06-24 09:26:08,158 - pyskl - INFO - Epoch [8][900/1281] lr: 2.484e-02, eta: 11:03:33, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7338, top5_acc: 0.9744, loss_cls: 1.0668, loss: 1.0668 +2025-06-24 09:26:29,632 - pyskl - INFO - Epoch [8][1000/1281] lr: 2.483e-02, eta: 11:03:04, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7725, top5_acc: 0.9831, loss_cls: 0.9610, loss: 0.9610 +2025-06-24 09:26:51,318 - pyskl - INFO - Epoch [8][1100/1281] lr: 2.483e-02, eta: 11:02:40, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7894, top5_acc: 0.9850, loss_cls: 0.9393, loss: 0.9393 +2025-06-24 09:27:12,991 - pyskl - INFO - Epoch [8][1200/1281] lr: 2.483e-02, eta: 11:02:15, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7538, top5_acc: 0.9819, loss_cls: 1.0015, loss: 1.0015 +2025-06-24 09:27:30,849 - pyskl - INFO - Saving checkpoint at 8 epochs +2025-06-24 09:28:14,126 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:28:14,178 - pyskl - INFO - +top1_acc 0.7205 +top5_acc 0.9752 +2025-06-24 09:28:14,178 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:28:14,184 - pyskl - INFO - +mean_acc 0.6372 +2025-06-24 09:28:14,188 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_7.pth was removed +2025-06-24 09:28:14,358 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_8.pth. +2025-06-24 09:28:14,359 - pyskl - INFO - Best top1_acc is 0.7205 at 8 epoch. +2025-06-24 09:28:14,361 - pyskl - INFO - Epoch(val) [8][533] top1_acc: 0.7205, top5_acc: 0.9752, mean_class_accuracy: 0.6372 +2025-06-24 09:28:54,550 - pyskl - INFO - Epoch [9][100/1281] lr: 2.482e-02, eta: 11:01:47, time: 0.402, data_time: 0.186, memory: 4082, top1_acc: 0.7850, top5_acc: 0.9875, loss_cls: 0.9338, loss: 0.9338 +2025-06-24 09:29:16,217 - pyskl - INFO - Epoch [9][200/1281] lr: 2.482e-02, eta: 11:01:22, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7794, top5_acc: 0.9831, loss_cls: 0.9758, loss: 0.9758 +2025-06-24 09:29:37,769 - pyskl - INFO - Epoch [9][300/1281] lr: 2.481e-02, eta: 11:00:55, time: 0.216, data_time: 0.001, memory: 4082, top1_acc: 0.7806, top5_acc: 0.9806, loss_cls: 0.9632, loss: 0.9632 +2025-06-24 09:29:59,152 - pyskl - INFO - Epoch [9][400/1281] lr: 2.481e-02, eta: 11:00:26, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7738, top5_acc: 0.9806, loss_cls: 1.0012, loss: 1.0012 +2025-06-24 09:30:20,584 - pyskl - INFO - Epoch [9][500/1281] lr: 2.481e-02, eta: 10:59:57, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7700, top5_acc: 0.9850, loss_cls: 0.9535, loss: 0.9535 +2025-06-24 09:30:42,134 - pyskl - INFO - Epoch [9][600/1281] lr: 2.480e-02, eta: 10:59:31, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7694, top5_acc: 0.9838, loss_cls: 0.9643, loss: 0.9643 +2025-06-24 09:31:03,866 - pyskl - INFO - Epoch [9][700/1281] lr: 2.480e-02, eta: 10:59:07, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7875, top5_acc: 0.9869, loss_cls: 0.9062, loss: 0.9062 +2025-06-24 09:31:25,349 - pyskl - INFO - Epoch [9][800/1281] lr: 2.480e-02, eta: 10:58:40, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7887, top5_acc: 0.9831, loss_cls: 0.9796, loss: 0.9796 +2025-06-24 09:31:46,936 - pyskl - INFO - Epoch [9][900/1281] lr: 2.479e-02, eta: 10:58:14, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7625, top5_acc: 0.9762, loss_cls: 1.0202, loss: 1.0202 +2025-06-24 09:32:08,540 - pyskl - INFO - Epoch [9][1000/1281] lr: 2.479e-02, eta: 10:57:49, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7700, top5_acc: 0.9838, loss_cls: 0.9804, loss: 0.9804 +2025-06-24 09:32:30,658 - pyskl - INFO - Epoch [9][1100/1281] lr: 2.479e-02, eta: 10:57:32, time: 0.221, data_time: 0.000, memory: 4082, top1_acc: 0.7825, top5_acc: 0.9812, loss_cls: 0.9392, loss: 0.9392 +2025-06-24 09:32:52,158 - pyskl - INFO - Epoch [9][1200/1281] lr: 2.478e-02, eta: 10:57:05, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7812, top5_acc: 0.9825, loss_cls: 0.9306, loss: 0.9306 +2025-06-24 09:33:10,246 - pyskl - INFO - Saving checkpoint at 9 epochs +2025-06-24 09:33:53,340 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:33:53,395 - pyskl - INFO - +top1_acc 0.7322 +top5_acc 0.9730 +2025-06-24 09:33:53,395 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:33:53,403 - pyskl - INFO - +mean_acc 0.6264 +2025-06-24 09:33:53,407 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_8.pth was removed +2025-06-24 09:33:53,586 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_9.pth. +2025-06-24 09:33:53,587 - pyskl - INFO - Best top1_acc is 0.7322 at 9 epoch. +2025-06-24 09:33:53,590 - pyskl - INFO - Epoch(val) [9][533] top1_acc: 0.7322, top5_acc: 0.9730, mean_class_accuracy: 0.6264 +2025-06-24 09:34:33,825 - pyskl - INFO - Epoch [10][100/1281] lr: 2.477e-02, eta: 10:56:37, time: 0.402, data_time: 0.188, memory: 4082, top1_acc: 0.7850, top5_acc: 0.9844, loss_cls: 0.9468, loss: 0.9468 +2025-06-24 09:34:55,361 - pyskl - INFO - Epoch [10][200/1281] lr: 2.477e-02, eta: 10:56:11, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7650, top5_acc: 0.9862, loss_cls: 0.9616, loss: 0.9616 +2025-06-24 09:35:17,022 - pyskl - INFO - Epoch [10][300/1281] lr: 2.477e-02, eta: 10:55:46, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7887, top5_acc: 0.9912, loss_cls: 0.9072, loss: 0.9072 +2025-06-24 09:35:38,423 - pyskl - INFO - Epoch [10][400/1281] lr: 2.476e-02, eta: 10:55:18, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7825, top5_acc: 0.9819, loss_cls: 0.9256, loss: 0.9256 +2025-06-24 09:36:00,226 - pyskl - INFO - Epoch [10][500/1281] lr: 2.476e-02, eta: 10:54:56, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7744, top5_acc: 0.9819, loss_cls: 0.9381, loss: 0.9381 +2025-06-24 09:36:21,644 - pyskl - INFO - Epoch [10][600/1281] lr: 2.476e-02, eta: 10:54:28, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7800, top5_acc: 0.9788, loss_cls: 0.9664, loss: 0.9664 +2025-06-24 09:36:43,017 - pyskl - INFO - Epoch [10][700/1281] lr: 2.475e-02, eta: 10:54:00, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7819, top5_acc: 0.9869, loss_cls: 0.9443, loss: 0.9443 +2025-06-24 09:37:04,502 - pyskl - INFO - Epoch [10][800/1281] lr: 2.475e-02, eta: 10:53:34, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7725, top5_acc: 0.9856, loss_cls: 0.9665, loss: 0.9665 +2025-06-24 09:37:26,257 - pyskl - INFO - Epoch [10][900/1281] lr: 2.474e-02, eta: 10:53:11, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7781, top5_acc: 0.9806, loss_cls: 0.9589, loss: 0.9589 +2025-06-24 09:37:47,831 - pyskl - INFO - Epoch [10][1000/1281] lr: 2.474e-02, eta: 10:52:46, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7837, top5_acc: 0.9888, loss_cls: 0.9278, loss: 0.9278 +2025-06-24 09:38:09,412 - pyskl - INFO - Epoch [10][1100/1281] lr: 2.473e-02, eta: 10:52:21, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7781, top5_acc: 0.9869, loss_cls: 0.9228, loss: 0.9228 +2025-06-24 09:38:31,352 - pyskl - INFO - Epoch [10][1200/1281] lr: 2.473e-02, eta: 10:52:01, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7956, top5_acc: 0.9838, loss_cls: 0.9183, loss: 0.9183 +2025-06-24 09:38:49,533 - pyskl - INFO - Saving checkpoint at 10 epochs +2025-06-24 09:39:32,456 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:39:32,511 - pyskl - INFO - +top1_acc 0.7073 +top5_acc 0.9653 +2025-06-24 09:39:32,511 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:39:32,518 - pyskl - INFO - +mean_acc 0.6302 +2025-06-24 09:39:32,520 - pyskl - INFO - Epoch(val) [10][533] top1_acc: 0.7073, top5_acc: 0.9653, mean_class_accuracy: 0.6302 +2025-06-24 09:40:12,542 - pyskl - INFO - Epoch [11][100/1281] lr: 2.472e-02, eta: 10:51:29, time: 0.400, data_time: 0.184, memory: 4082, top1_acc: 0.7819, top5_acc: 0.9831, loss_cls: 0.9141, loss: 0.9141 +2025-06-24 09:40:34,224 - pyskl - INFO - Epoch [11][200/1281] lr: 2.472e-02, eta: 10:51:06, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7762, top5_acc: 0.9881, loss_cls: 0.9217, loss: 0.9217 +2025-06-24 09:40:55,855 - pyskl - INFO - Epoch [11][300/1281] lr: 2.471e-02, eta: 10:50:41, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7925, top5_acc: 0.9919, loss_cls: 0.8724, loss: 0.8724 +2025-06-24 09:41:17,685 - pyskl - INFO - Epoch [11][400/1281] lr: 2.471e-02, eta: 10:50:20, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7869, top5_acc: 0.9869, loss_cls: 0.9278, loss: 0.9278 +2025-06-24 09:41:39,569 - pyskl - INFO - Epoch [11][500/1281] lr: 2.471e-02, eta: 10:49:59, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7700, top5_acc: 0.9831, loss_cls: 0.9673, loss: 0.9673 +2025-06-24 09:42:01,198 - pyskl - INFO - Epoch [11][600/1281] lr: 2.470e-02, eta: 10:49:35, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7906, top5_acc: 0.9856, loss_cls: 0.8905, loss: 0.8905 +2025-06-24 09:42:23,217 - pyskl - INFO - Epoch [11][700/1281] lr: 2.470e-02, eta: 10:49:16, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8163, top5_acc: 0.9856, loss_cls: 0.8371, loss: 0.8371 +2025-06-24 09:42:45,235 - pyskl - INFO - Epoch [11][800/1281] lr: 2.469e-02, eta: 10:48:57, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.7806, top5_acc: 0.9850, loss_cls: 0.9076, loss: 0.9076 +2025-06-24 09:43:06,875 - pyskl - INFO - Epoch [11][900/1281] lr: 2.469e-02, eta: 10:48:33, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7844, top5_acc: 0.9875, loss_cls: 0.9062, loss: 0.9062 +2025-06-24 09:43:28,276 - pyskl - INFO - Epoch [11][1000/1281] lr: 2.468e-02, eta: 10:48:06, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7788, top5_acc: 0.9838, loss_cls: 0.9471, loss: 0.9471 +2025-06-24 09:43:49,924 - pyskl - INFO - Epoch [11][1100/1281] lr: 2.468e-02, eta: 10:47:42, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7956, top5_acc: 0.9888, loss_cls: 0.8771, loss: 0.8771 +2025-06-24 09:44:11,724 - pyskl - INFO - Epoch [11][1200/1281] lr: 2.467e-02, eta: 10:47:20, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7887, top5_acc: 0.9869, loss_cls: 0.9170, loss: 0.9170 +2025-06-24 09:44:29,894 - pyskl - INFO - Saving checkpoint at 11 epochs +2025-06-24 09:45:13,709 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:45:13,778 - pyskl - INFO - +top1_acc 0.7604 +top5_acc 0.9798 +2025-06-24 09:45:13,778 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:45:13,787 - pyskl - INFO - +mean_acc 0.6611 +2025-06-24 09:45:13,792 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_9.pth was removed +2025-06-24 09:45:13,992 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_11.pth. +2025-06-24 09:45:13,993 - pyskl - INFO - Best top1_acc is 0.7604 at 11 epoch. +2025-06-24 09:45:13,996 - pyskl - INFO - Epoch(val) [11][533] top1_acc: 0.7604, top5_acc: 0.9798, mean_class_accuracy: 0.6611 +2025-06-24 09:45:54,642 - pyskl - INFO - Epoch [12][100/1281] lr: 2.467e-02, eta: 10:46:55, time: 0.406, data_time: 0.189, memory: 4082, top1_acc: 0.7850, top5_acc: 0.9888, loss_cls: 0.8763, loss: 0.8763 +2025-06-24 09:46:16,503 - pyskl - INFO - Epoch [12][200/1281] lr: 2.466e-02, eta: 10:46:34, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.8006, top5_acc: 0.9894, loss_cls: 0.8674, loss: 0.8674 +2025-06-24 09:46:38,108 - pyskl - INFO - Epoch [12][300/1281] lr: 2.466e-02, eta: 10:46:10, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7850, top5_acc: 0.9881, loss_cls: 0.9117, loss: 0.9117 +2025-06-24 09:46:59,919 - pyskl - INFO - Epoch [12][400/1281] lr: 2.465e-02, eta: 10:45:48, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7969, top5_acc: 0.9869, loss_cls: 0.8774, loss: 0.8774 +2025-06-24 09:47:21,913 - pyskl - INFO - Epoch [12][500/1281] lr: 2.465e-02, eta: 10:45:28, time: 0.220, data_time: 0.000, memory: 4082, top1_acc: 0.8013, top5_acc: 0.9875, loss_cls: 0.8485, loss: 0.8485 +2025-06-24 09:47:43,441 - pyskl - INFO - Epoch [12][600/1281] lr: 2.464e-02, eta: 10:45:03, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8044, top5_acc: 0.9856, loss_cls: 0.8802, loss: 0.8802 +2025-06-24 09:48:05,111 - pyskl - INFO - Epoch [12][700/1281] lr: 2.464e-02, eta: 10:44:40, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.7937, top5_acc: 0.9894, loss_cls: 0.9182, loss: 0.9182 +2025-06-24 09:48:26,644 - pyskl - INFO - Epoch [12][800/1281] lr: 2.463e-02, eta: 10:44:14, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8000, top5_acc: 0.9869, loss_cls: 0.8584, loss: 0.8584 +2025-06-24 09:48:47,937 - pyskl - INFO - Epoch [12][900/1281] lr: 2.463e-02, eta: 10:43:47, time: 0.213, data_time: 0.000, memory: 4082, top1_acc: 0.8025, top5_acc: 0.9894, loss_cls: 0.8528, loss: 0.8528 +2025-06-24 09:49:09,465 - pyskl - INFO - Epoch [12][1000/1281] lr: 2.462e-02, eta: 10:43:22, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7981, top5_acc: 0.9819, loss_cls: 0.9199, loss: 0.9199 +2025-06-24 09:49:31,040 - pyskl - INFO - Epoch [12][1100/1281] lr: 2.462e-02, eta: 10:42:57, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7894, top5_acc: 0.9862, loss_cls: 0.9041, loss: 0.9041 +2025-06-24 09:49:52,482 - pyskl - INFO - Epoch [12][1200/1281] lr: 2.461e-02, eta: 10:42:31, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7950, top5_acc: 0.9850, loss_cls: 0.8949, loss: 0.8949 +2025-06-24 09:50:10,397 - pyskl - INFO - Saving checkpoint at 12 epochs +2025-06-24 09:50:53,335 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:50:53,391 - pyskl - INFO - +top1_acc 0.7910 +top5_acc 0.9832 +2025-06-24 09:50:53,391 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:50:53,398 - pyskl - INFO - +mean_acc 0.6991 +2025-06-24 09:50:53,402 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_11.pth was removed +2025-06-24 09:50:53,585 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_12.pth. +2025-06-24 09:50:53,585 - pyskl - INFO - Best top1_acc is 0.7910 at 12 epoch. +2025-06-24 09:50:53,589 - pyskl - INFO - Epoch(val) [12][533] top1_acc: 0.7910, top5_acc: 0.9832, mean_class_accuracy: 0.6991 +2025-06-24 09:51:33,706 - pyskl - INFO - Epoch [13][100/1281] lr: 2.460e-02, eta: 10:41:59, time: 0.401, data_time: 0.183, memory: 4082, top1_acc: 0.8063, top5_acc: 0.9925, loss_cls: 0.8186, loss: 0.8186 +2025-06-24 09:51:55,235 - pyskl - INFO - Epoch [13][200/1281] lr: 2.460e-02, eta: 10:41:34, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8050, top5_acc: 0.9919, loss_cls: 0.8391, loss: 0.8391 +2025-06-24 09:52:16,990 - pyskl - INFO - Epoch [13][300/1281] lr: 2.459e-02, eta: 10:41:12, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.7900, top5_acc: 0.9869, loss_cls: 0.8978, loss: 0.8978 +2025-06-24 09:52:38,359 - pyskl - INFO - Epoch [13][400/1281] lr: 2.459e-02, eta: 10:40:45, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7906, top5_acc: 0.9900, loss_cls: 0.8617, loss: 0.8617 +2025-06-24 09:53:00,089 - pyskl - INFO - Epoch [13][500/1281] lr: 2.458e-02, eta: 10:40:23, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8000, top5_acc: 0.9919, loss_cls: 0.8409, loss: 0.8409 +2025-06-24 09:53:21,564 - pyskl - INFO - Epoch [13][600/1281] lr: 2.458e-02, eta: 10:39:57, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8125, top5_acc: 0.9912, loss_cls: 0.7970, loss: 0.7970 +2025-06-24 09:53:43,237 - pyskl - INFO - Epoch [13][700/1281] lr: 2.457e-02, eta: 10:39:34, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8119, top5_acc: 0.9869, loss_cls: 0.8326, loss: 0.8326 +2025-06-24 09:54:04,653 - pyskl - INFO - Epoch [13][800/1281] lr: 2.457e-02, eta: 10:39:08, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.8200, top5_acc: 0.9900, loss_cls: 0.8209, loss: 0.8209 +2025-06-24 09:54:26,069 - pyskl - INFO - Epoch [13][900/1281] lr: 2.456e-02, eta: 10:38:42, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7900, top5_acc: 0.9875, loss_cls: 0.8923, loss: 0.8923 +2025-06-24 09:54:47,610 - pyskl - INFO - Epoch [13][1000/1281] lr: 2.455e-02, eta: 10:38:18, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.7919, top5_acc: 0.9838, loss_cls: 0.9135, loss: 0.9135 +2025-06-24 09:55:09,021 - pyskl - INFO - Epoch [13][1100/1281] lr: 2.455e-02, eta: 10:37:52, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.8163, top5_acc: 0.9900, loss_cls: 0.8199, loss: 0.8199 +2025-06-24 09:55:30,794 - pyskl - INFO - Epoch [13][1200/1281] lr: 2.454e-02, eta: 10:37:30, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8187, top5_acc: 0.9888, loss_cls: 0.8179, loss: 0.8179 +2025-06-24 09:55:48,646 - pyskl - INFO - Saving checkpoint at 13 epochs +2025-06-24 09:56:31,838 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 09:56:31,899 - pyskl - INFO - +top1_acc 0.7942 +top5_acc 0.9857 +2025-06-24 09:56:31,899 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 09:56:31,906 - pyskl - INFO - +mean_acc 0.6852 +2025-06-24 09:56:31,910 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_12.pth was removed +2025-06-24 09:56:32,149 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_13.pth. +2025-06-24 09:56:32,150 - pyskl - INFO - Best top1_acc is 0.7942 at 13 epoch. +2025-06-24 09:56:32,152 - pyskl - INFO - Epoch(val) [13][533] top1_acc: 0.7942, top5_acc: 0.9857, mean_class_accuracy: 0.6852 +2025-06-24 09:57:12,473 - pyskl - INFO - Epoch [14][100/1281] lr: 2.453e-02, eta: 10:37:00, time: 0.403, data_time: 0.186, memory: 4082, top1_acc: 0.8119, top5_acc: 0.9931, loss_cls: 0.8133, loss: 0.8133 +2025-06-24 09:57:34,262 - pyskl - INFO - Epoch [14][200/1281] lr: 2.453e-02, eta: 10:36:38, time: 0.218, data_time: 0.000, memory: 4082, top1_acc: 0.8250, top5_acc: 0.9912, loss_cls: 0.7782, loss: 0.7782 +2025-06-24 09:57:55,814 - pyskl - INFO - Epoch [14][300/1281] lr: 2.452e-02, eta: 10:36:14, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7750, top5_acc: 0.9850, loss_cls: 0.9755, loss: 0.9755 +2025-06-24 09:58:17,259 - pyskl - INFO - Epoch [14][400/1281] lr: 2.452e-02, eta: 10:35:49, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7906, top5_acc: 0.9888, loss_cls: 0.9002, loss: 0.9002 +2025-06-24 09:58:38,744 - pyskl - INFO - Epoch [14][500/1281] lr: 2.451e-02, eta: 10:35:24, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8156, top5_acc: 0.9938, loss_cls: 0.7888, loss: 0.7888 +2025-06-24 09:59:00,136 - pyskl - INFO - Epoch [14][600/1281] lr: 2.451e-02, eta: 10:34:58, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.7925, top5_acc: 0.9888, loss_cls: 0.8609, loss: 0.8609 +2025-06-24 09:59:21,397 - pyskl - INFO - Epoch [14][700/1281] lr: 2.450e-02, eta: 10:34:31, time: 0.213, data_time: 0.000, memory: 4082, top1_acc: 0.8181, top5_acc: 0.9894, loss_cls: 0.8156, loss: 0.8156 +2025-06-24 09:59:42,970 - pyskl - INFO - Epoch [14][800/1281] lr: 2.449e-02, eta: 10:34:07, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.7800, top5_acc: 0.9856, loss_cls: 0.9355, loss: 0.9355 +2025-06-24 10:00:04,486 - pyskl - INFO - Epoch [14][900/1281] lr: 2.449e-02, eta: 10:33:43, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8194, top5_acc: 0.9888, loss_cls: 0.8149, loss: 0.8149 +2025-06-24 10:00:26,055 - pyskl - INFO - Epoch [14][1000/1281] lr: 2.448e-02, eta: 10:33:19, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8237, top5_acc: 0.9900, loss_cls: 0.7914, loss: 0.7914 +2025-06-24 10:00:47,446 - pyskl - INFO - Epoch [14][1100/1281] lr: 2.448e-02, eta: 10:32:53, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.8113, top5_acc: 0.9862, loss_cls: 0.8414, loss: 0.8414 +2025-06-24 10:01:09,344 - pyskl - INFO - Epoch [14][1200/1281] lr: 2.447e-02, eta: 10:32:33, time: 0.219, data_time: 0.000, memory: 4082, top1_acc: 0.7906, top5_acc: 0.9856, loss_cls: 0.9067, loss: 0.9067 +2025-06-24 10:01:27,428 - pyskl - INFO - Saving checkpoint at 14 epochs +2025-06-24 10:02:10,486 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:02:10,541 - pyskl - INFO - +top1_acc 0.7844 +top5_acc 0.9826 +2025-06-24 10:02:10,541 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:02:10,548 - pyskl - INFO - +mean_acc 0.6842 +2025-06-24 10:02:10,549 - pyskl - INFO - Epoch(val) [14][533] top1_acc: 0.7844, top5_acc: 0.9826, mean_class_accuracy: 0.6842 +2025-06-24 10:02:50,690 - pyskl - INFO - Epoch [15][100/1281] lr: 2.446e-02, eta: 10:32:00, time: 0.401, data_time: 0.185, memory: 4082, top1_acc: 0.8250, top5_acc: 0.9919, loss_cls: 0.8046, loss: 0.8046 +2025-06-24 10:03:12,523 - pyskl - INFO - Epoch [15][200/1281] lr: 2.445e-02, eta: 10:31:39, time: 0.218, data_time: 0.001, memory: 4082, top1_acc: 0.8156, top5_acc: 0.9912, loss_cls: 0.8106, loss: 0.8106 +2025-06-24 10:03:34,028 - pyskl - INFO - Epoch [15][300/1281] lr: 2.445e-02, eta: 10:31:15, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8131, top5_acc: 0.9906, loss_cls: 0.8308, loss: 0.8308 +2025-06-24 10:03:55,585 - pyskl - INFO - Epoch [15][400/1281] lr: 2.444e-02, eta: 10:30:51, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8369, top5_acc: 0.9875, loss_cls: 0.7640, loss: 0.7640 +2025-06-24 10:04:16,861 - pyskl - INFO - Epoch [15][500/1281] lr: 2.444e-02, eta: 10:30:24, time: 0.213, data_time: 0.000, memory: 4082, top1_acc: 0.8231, top5_acc: 0.9919, loss_cls: 0.7779, loss: 0.7779 +2025-06-24 10:04:38,366 - pyskl - INFO - Epoch [15][600/1281] lr: 2.443e-02, eta: 10:30:00, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8156, top5_acc: 0.9850, loss_cls: 0.8389, loss: 0.8389 +2025-06-24 10:04:59,959 - pyskl - INFO - Epoch [15][700/1281] lr: 2.442e-02, eta: 10:29:36, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8337, top5_acc: 0.9906, loss_cls: 0.8027, loss: 0.8027 +2025-06-24 10:05:21,473 - pyskl - INFO - Epoch [15][800/1281] lr: 2.442e-02, eta: 10:29:12, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8100, top5_acc: 0.9881, loss_cls: 0.8344, loss: 0.8344 +2025-06-24 10:05:42,996 - pyskl - INFO - Epoch [15][900/1281] lr: 2.441e-02, eta: 10:28:48, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8037, top5_acc: 0.9862, loss_cls: 0.8623, loss: 0.8623 +2025-06-24 10:06:04,532 - pyskl - INFO - Epoch [15][1000/1281] lr: 2.441e-02, eta: 10:28:24, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8156, top5_acc: 0.9919, loss_cls: 0.7874, loss: 0.7874 +2025-06-24 10:06:26,000 - pyskl - INFO - Epoch [15][1100/1281] lr: 2.440e-02, eta: 10:28:00, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8163, top5_acc: 0.9888, loss_cls: 0.8220, loss: 0.8220 +2025-06-24 10:06:47,679 - pyskl - INFO - Epoch [15][1200/1281] lr: 2.439e-02, eta: 10:27:37, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8113, top5_acc: 0.9919, loss_cls: 0.8163, loss: 0.8163 +2025-06-24 10:07:05,818 - pyskl - INFO - Saving checkpoint at 15 epochs +2025-06-24 10:07:49,303 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:07:49,370 - pyskl - INFO - +top1_acc 0.7766 +top5_acc 0.9791 +2025-06-24 10:07:49,370 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:07:49,379 - pyskl - INFO - +mean_acc 0.6900 +2025-06-24 10:07:49,381 - pyskl - INFO - Epoch(val) [15][533] top1_acc: 0.7766, top5_acc: 0.9791, mean_class_accuracy: 0.6900 +2025-06-24 10:08:28,861 - pyskl - INFO - Epoch [16][100/1281] lr: 2.438e-02, eta: 10:26:59, time: 0.395, data_time: 0.178, memory: 4082, top1_acc: 0.8063, top5_acc: 0.9888, loss_cls: 0.8615, loss: 0.8615 +2025-06-24 10:08:50,474 - pyskl - INFO - Epoch [16][200/1281] lr: 2.438e-02, eta: 10:26:35, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9894, loss_cls: 0.7867, loss: 0.7867 +2025-06-24 10:09:12,073 - pyskl - INFO - Epoch [16][300/1281] lr: 2.437e-02, eta: 10:26:12, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8156, top5_acc: 0.9925, loss_cls: 0.8034, loss: 0.8034 +2025-06-24 10:09:33,707 - pyskl - INFO - Epoch [16][400/1281] lr: 2.436e-02, eta: 10:25:49, time: 0.216, data_time: 0.000, memory: 4082, top1_acc: 0.8275, top5_acc: 0.9938, loss_cls: 0.7920, loss: 0.7920 +2025-06-24 10:09:54,952 - pyskl - INFO - Epoch [16][500/1281] lr: 2.436e-02, eta: 10:25:23, time: 0.212, data_time: 0.000, memory: 4082, top1_acc: 0.8225, top5_acc: 0.9875, loss_cls: 0.7881, loss: 0.7881 +2025-06-24 10:10:16,436 - pyskl - INFO - Epoch [16][600/1281] lr: 2.435e-02, eta: 10:24:59, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8219, top5_acc: 0.9944, loss_cls: 0.7747, loss: 0.7747 +2025-06-24 10:10:38,145 - pyskl - INFO - Epoch [16][700/1281] lr: 2.434e-02, eta: 10:24:37, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9931, loss_cls: 0.7637, loss: 0.7637 +2025-06-24 10:10:59,519 - pyskl - INFO - Epoch [16][800/1281] lr: 2.434e-02, eta: 10:24:11, time: 0.214, data_time: 0.000, memory: 4082, top1_acc: 0.8125, top5_acc: 0.9862, loss_cls: 0.8075, loss: 0.8075 +2025-06-24 10:11:21,248 - pyskl - INFO - Epoch [16][900/1281] lr: 2.433e-02, eta: 10:23:49, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8394, top5_acc: 0.9906, loss_cls: 0.7383, loss: 0.7383 +2025-06-24 10:11:42,770 - pyskl - INFO - Epoch [16][1000/1281] lr: 2.432e-02, eta: 10:23:26, time: 0.215, data_time: 0.000, memory: 4082, top1_acc: 0.8231, top5_acc: 0.9912, loss_cls: 0.7649, loss: 0.7649 +2025-06-24 10:12:04,485 - pyskl - INFO - Epoch [16][1100/1281] lr: 2.432e-02, eta: 10:23:04, time: 0.217, data_time: 0.000, memory: 4082, top1_acc: 0.8150, top5_acc: 0.9906, loss_cls: 0.8393, loss: 0.8393 +2025-06-24 10:12:26,123 - pyskl - INFO - Epoch [16][1200/1281] lr: 2.431e-02, eta: 10:22:41, time: 0.216, data_time: 0.001, memory: 4082, top1_acc: 0.8119, top5_acc: 0.9900, loss_cls: 0.8393, loss: 0.8393 +2025-06-24 10:12:44,713 - pyskl - INFO - Saving checkpoint at 16 epochs +2025-06-24 10:13:28,882 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:13:28,968 - pyskl - INFO - +top1_acc 0.7800 +top5_acc 0.9816 +2025-06-24 10:13:28,968 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:13:28,978 - pyskl - INFO - +mean_acc 0.7087 +2025-06-24 10:13:28,980 - pyskl - INFO - Epoch(val) [16][533] top1_acc: 0.7800, top5_acc: 0.9816, mean_class_accuracy: 0.7087 +2025-06-24 10:14:10,349 - pyskl - INFO - Epoch [17][100/1281] lr: 2.430e-02, eta: 10:22:18, time: 0.414, data_time: 0.196, memory: 4082, top1_acc: 0.8331, top5_acc: 0.9912, loss_cls: 0.7598, loss: 0.7598 +2025-06-24 10:14:32,876 - pyskl - INFO - Epoch [17][200/1281] lr: 2.429e-02, eta: 10:22:03, time: 0.225, data_time: 0.001, memory: 4082, top1_acc: 0.8488, top5_acc: 0.9888, loss_cls: 0.7321, loss: 0.7321 +2025-06-24 10:15:09,576 - pyskl - INFO - Epoch [17][300/1281] lr: 2.428e-02, eta: 10:23:44, time: 0.367, data_time: 0.000, memory: 4082, top1_acc: 0.8363, top5_acc: 0.9906, loss_cls: 0.7813, loss: 0.7813 +2025-06-24 10:15:51,121 - pyskl - INFO - Epoch [17][400/1281] lr: 2.428e-02, eta: 10:26:03, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8381, top5_acc: 0.9912, loss_cls: 0.7594, loss: 0.7594 +2025-06-24 10:16:32,612 - pyskl - INFO - Epoch [17][500/1281] lr: 2.427e-02, eta: 10:28:21, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9900, loss_cls: 0.7895, loss: 0.7895 +2025-06-24 10:17:14,362 - pyskl - INFO - Epoch [17][600/1281] lr: 2.426e-02, eta: 10:30:39, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9925, loss_cls: 0.7801, loss: 0.7801 +2025-06-24 10:17:56,041 - pyskl - INFO - Epoch [17][700/1281] lr: 2.426e-02, eta: 10:32:54, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8431, top5_acc: 0.9919, loss_cls: 0.7276, loss: 0.7276 +2025-06-24 10:18:37,612 - pyskl - INFO - Epoch [17][800/1281] lr: 2.425e-02, eta: 10:35:07, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8400, top5_acc: 0.9944, loss_cls: 0.7387, loss: 0.7387 +2025-06-24 10:19:18,868 - pyskl - INFO - Epoch [17][900/1281] lr: 2.424e-02, eta: 10:37:16, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9906, loss_cls: 0.8178, loss: 0.8178 +2025-06-24 10:20:00,475 - pyskl - INFO - Epoch [17][1000/1281] lr: 2.424e-02, eta: 10:39:27, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9894, loss_cls: 0.7725, loss: 0.7725 +2025-06-24 10:20:41,895 - pyskl - INFO - Epoch [17][1100/1281] lr: 2.423e-02, eta: 10:41:34, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8181, top5_acc: 0.9875, loss_cls: 0.8073, loss: 0.8073 +2025-06-24 10:21:23,447 - pyskl - INFO - Epoch [17][1200/1281] lr: 2.422e-02, eta: 10:43:40, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8187, top5_acc: 0.9925, loss_cls: 0.7782, loss: 0.7782 +2025-06-24 10:21:57,677 - pyskl - INFO - Saving checkpoint at 17 epochs +2025-06-24 10:23:09,276 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:23:09,332 - pyskl - INFO - +top1_acc 0.8026 +top5_acc 0.9857 +2025-06-24 10:23:09,332 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:23:09,339 - pyskl - INFO - +mean_acc 0.7239 +2025-06-24 10:23:09,344 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_13.pth was removed +2025-06-24 10:23:09,558 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_17.pth. +2025-06-24 10:23:09,558 - pyskl - INFO - Best top1_acc is 0.8026 at 17 epoch. +2025-06-24 10:23:09,561 - pyskl - INFO - Epoch(val) [17][533] top1_acc: 0.8026, top5_acc: 0.9857, mean_class_accuracy: 0.7239 +2025-06-24 10:24:10,550 - pyskl - INFO - Epoch [18][100/1281] lr: 2.421e-02, eta: 10:45:35, time: 0.610, data_time: 0.193, memory: 4082, top1_acc: 0.8287, top5_acc: 0.9919, loss_cls: 0.7594, loss: 0.7594 +2025-06-24 10:24:39,943 - pyskl - INFO - Epoch [18][200/1281] lr: 2.420e-02, eta: 10:46:03, time: 0.294, data_time: 0.001, memory: 4082, top1_acc: 0.8500, top5_acc: 0.9931, loss_cls: 0.6933, loss: 0.6933 +2025-06-24 10:25:16,289 - pyskl - INFO - Epoch [18][300/1281] lr: 2.419e-02, eta: 10:47:25, time: 0.363, data_time: 0.000, memory: 4082, top1_acc: 0.8462, top5_acc: 0.9912, loss_cls: 0.7262, loss: 0.7262 +2025-06-24 10:25:57,826 - pyskl - INFO - Epoch [18][400/1281] lr: 2.419e-02, eta: 10:49:25, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8425, top5_acc: 0.9944, loss_cls: 0.7326, loss: 0.7326 +2025-06-24 10:26:39,210 - pyskl - INFO - Epoch [18][500/1281] lr: 2.418e-02, eta: 10:51:23, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9938, loss_cls: 0.7431, loss: 0.7431 +2025-06-24 10:27:20,749 - pyskl - INFO - Epoch [18][600/1281] lr: 2.417e-02, eta: 10:53:21, time: 0.415, data_time: 0.001, memory: 4082, top1_acc: 0.8344, top5_acc: 0.9856, loss_cls: 0.7706, loss: 0.7706 +2025-06-24 10:28:02,152 - pyskl - INFO - Epoch [18][700/1281] lr: 2.417e-02, eta: 10:55:16, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8250, top5_acc: 0.9906, loss_cls: 0.8091, loss: 0.8091 +2025-06-24 10:28:43,744 - pyskl - INFO - Epoch [18][800/1281] lr: 2.416e-02, eta: 10:57:11, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8294, top5_acc: 0.9900, loss_cls: 0.7564, loss: 0.7564 +2025-06-24 10:29:25,243 - pyskl - INFO - Epoch [18][900/1281] lr: 2.415e-02, eta: 10:59:04, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8137, top5_acc: 0.9931, loss_cls: 0.8196, loss: 0.8196 +2025-06-24 10:30:06,709 - pyskl - INFO - Epoch [18][1000/1281] lr: 2.414e-02, eta: 11:00:56, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8438, top5_acc: 0.9912, loss_cls: 0.7338, loss: 0.7338 +2025-06-24 10:30:48,209 - pyskl - INFO - Epoch [18][1100/1281] lr: 2.414e-02, eta: 11:02:46, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8431, top5_acc: 0.9906, loss_cls: 0.7063, loss: 0.7063 +2025-06-24 10:31:29,635 - pyskl - INFO - Epoch [18][1200/1281] lr: 2.413e-02, eta: 11:04:35, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8344, top5_acc: 0.9906, loss_cls: 0.7677, loss: 0.7677 +2025-06-24 10:32:03,813 - pyskl - INFO - Saving checkpoint at 18 epochs +2025-06-24 10:33:15,295 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:33:15,351 - pyskl - INFO - +top1_acc 0.7850 +top5_acc 0.9798 +2025-06-24 10:33:15,352 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:33:15,360 - pyskl - INFO - +mean_acc 0.6993 +2025-06-24 10:33:15,362 - pyskl - INFO - Epoch(val) [18][533] top1_acc: 0.7850, top5_acc: 0.9798, mean_class_accuracy: 0.6993 +2025-06-24 10:34:15,921 - pyskl - INFO - Epoch [19][100/1281] lr: 2.411e-02, eta: 11:06:03, time: 0.606, data_time: 0.193, memory: 4082, top1_acc: 0.8512, top5_acc: 0.9931, loss_cls: 0.7129, loss: 0.7129 +2025-06-24 10:34:45,668 - pyskl - INFO - Epoch [19][200/1281] lr: 2.411e-02, eta: 11:06:23, time: 0.297, data_time: 0.000, memory: 4082, top1_acc: 0.8519, top5_acc: 0.9894, loss_cls: 0.6981, loss: 0.6981 +2025-06-24 10:35:21,389 - pyskl - INFO - Epoch [19][300/1281] lr: 2.410e-02, eta: 11:07:27, time: 0.357, data_time: 0.000, memory: 4082, top1_acc: 0.8481, top5_acc: 0.9925, loss_cls: 0.6926, loss: 0.6926 +2025-06-24 10:36:02,877 - pyskl - INFO - Epoch [19][400/1281] lr: 2.409e-02, eta: 11:09:11, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8519, top5_acc: 0.9944, loss_cls: 0.7087, loss: 0.7087 +2025-06-24 10:36:44,257 - pyskl - INFO - Epoch [19][500/1281] lr: 2.408e-02, eta: 11:10:53, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8319, top5_acc: 0.9969, loss_cls: 0.7275, loss: 0.7275 +2025-06-24 10:37:25,673 - pyskl - INFO - Epoch [19][600/1281] lr: 2.408e-02, eta: 11:12:34, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9925, loss_cls: 0.7512, loss: 0.7512 +2025-06-24 10:38:07,030 - pyskl - INFO - Epoch [19][700/1281] lr: 2.407e-02, eta: 11:14:13, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8438, top5_acc: 0.9938, loss_cls: 0.7260, loss: 0.7260 +2025-06-24 10:38:48,390 - pyskl - INFO - Epoch [19][800/1281] lr: 2.406e-02, eta: 11:15:51, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8356, top5_acc: 0.9906, loss_cls: 0.7430, loss: 0.7430 +2025-06-24 10:39:29,849 - pyskl - INFO - Epoch [19][900/1281] lr: 2.405e-02, eta: 11:17:29, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8400, top5_acc: 0.9919, loss_cls: 0.7437, loss: 0.7437 +2025-06-24 10:40:11,278 - pyskl - INFO - Epoch [19][1000/1281] lr: 2.405e-02, eta: 11:19:06, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8419, top5_acc: 0.9925, loss_cls: 0.7420, loss: 0.7420 +2025-06-24 10:40:52,689 - pyskl - INFO - Epoch [19][1100/1281] lr: 2.404e-02, eta: 11:20:41, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8344, top5_acc: 0.9844, loss_cls: 0.7798, loss: 0.7798 +2025-06-24 10:41:34,142 - pyskl - INFO - Epoch [19][1200/1281] lr: 2.403e-02, eta: 11:22:15, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8531, top5_acc: 0.9919, loss_cls: 0.7080, loss: 0.7080 +2025-06-24 10:42:08,648 - pyskl - INFO - Saving checkpoint at 19 epochs +2025-06-24 10:43:20,880 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:43:20,934 - pyskl - INFO - +top1_acc 0.7902 +top5_acc 0.9857 +2025-06-24 10:43:20,934 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:43:20,941 - pyskl - INFO - +mean_acc 0.7044 +2025-06-24 10:43:20,942 - pyskl - INFO - Epoch(val) [19][533] top1_acc: 0.7902, top5_acc: 0.9857, mean_class_accuracy: 0.7044 +2025-06-24 10:44:21,404 - pyskl - INFO - Epoch [20][100/1281] lr: 2.402e-02, eta: 11:23:23, time: 0.605, data_time: 0.194, memory: 4082, top1_acc: 0.8519, top5_acc: 0.9944, loss_cls: 0.6986, loss: 0.6986 +2025-06-24 10:44:51,358 - pyskl - INFO - Epoch [20][200/1281] lr: 2.401e-02, eta: 11:23:36, time: 0.300, data_time: 0.000, memory: 4082, top1_acc: 0.8306, top5_acc: 0.9925, loss_cls: 0.7520, loss: 0.7520 +2025-06-24 10:45:27,409 - pyskl - INFO - Epoch [20][300/1281] lr: 2.400e-02, eta: 11:24:30, time: 0.360, data_time: 0.000, memory: 4082, top1_acc: 0.8300, top5_acc: 0.9906, loss_cls: 0.7473, loss: 0.7473 +2025-06-24 10:46:08,846 - pyskl - INFO - Epoch [20][400/1281] lr: 2.399e-02, eta: 11:26:00, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8250, top5_acc: 0.9894, loss_cls: 0.7579, loss: 0.7579 +2025-06-24 10:46:50,469 - pyskl - INFO - Epoch [20][500/1281] lr: 2.398e-02, eta: 11:27:30, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8456, top5_acc: 0.9938, loss_cls: 0.7012, loss: 0.7012 +2025-06-24 10:47:32,033 - pyskl - INFO - Epoch [20][600/1281] lr: 2.398e-02, eta: 11:28:59, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8356, top5_acc: 0.9925, loss_cls: 0.7753, loss: 0.7753 +2025-06-24 10:48:13,620 - pyskl - INFO - Epoch [20][700/1281] lr: 2.397e-02, eta: 11:30:27, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8575, top5_acc: 0.9912, loss_cls: 0.6545, loss: 0.6545 +2025-06-24 10:48:55,174 - pyskl - INFO - Epoch [20][800/1281] lr: 2.396e-02, eta: 11:31:54, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8281, top5_acc: 0.9950, loss_cls: 0.7262, loss: 0.7262 +2025-06-24 10:49:36,574 - pyskl - INFO - Epoch [20][900/1281] lr: 2.395e-02, eta: 11:33:18, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8313, top5_acc: 0.9900, loss_cls: 0.7682, loss: 0.7682 +2025-06-24 10:50:18,088 - pyskl - INFO - Epoch [20][1000/1281] lr: 2.394e-02, eta: 11:34:42, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8438, top5_acc: 0.9900, loss_cls: 0.7344, loss: 0.7344 +2025-06-24 10:50:59,623 - pyskl - INFO - Epoch [20][1100/1281] lr: 2.393e-02, eta: 11:36:06, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8344, top5_acc: 0.9900, loss_cls: 0.7242, loss: 0.7242 +2025-06-24 10:51:41,143 - pyskl - INFO - Epoch [20][1200/1281] lr: 2.393e-02, eta: 11:37:28, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8444, top5_acc: 0.9919, loss_cls: 0.6968, loss: 0.6968 +2025-06-24 10:52:15,404 - pyskl - INFO - Saving checkpoint at 20 epochs +2025-06-24 10:53:26,597 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 10:53:26,656 - pyskl - INFO - +top1_acc 0.8194 +top5_acc 0.9887 +2025-06-24 10:53:26,656 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 10:53:26,666 - pyskl - INFO - +mean_acc 0.7431 +2025-06-24 10:53:26,671 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_17.pth was removed +2025-06-24 10:53:26,864 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_20.pth. +2025-06-24 10:53:26,864 - pyskl - INFO - Best top1_acc is 0.8194 at 20 epoch. +2025-06-24 10:53:26,867 - pyskl - INFO - Epoch(val) [20][533] top1_acc: 0.8194, top5_acc: 0.9887, mean_class_accuracy: 0.7431 +2025-06-24 10:54:26,424 - pyskl - INFO - Epoch [21][100/1281] lr: 2.391e-02, eta: 11:38:14, time: 0.596, data_time: 0.194, memory: 4082, top1_acc: 0.8525, top5_acc: 0.9925, loss_cls: 0.6959, loss: 0.6959 +2025-06-24 10:54:57,133 - pyskl - INFO - Epoch [21][200/1281] lr: 2.390e-02, eta: 11:38:24, time: 0.307, data_time: 0.000, memory: 4082, top1_acc: 0.8556, top5_acc: 0.9919, loss_cls: 0.6987, loss: 0.6987 +2025-06-24 10:55:31,954 - pyskl - INFO - Epoch [21][300/1281] lr: 2.389e-02, eta: 11:39:01, time: 0.348, data_time: 0.000, memory: 4082, top1_acc: 0.8525, top5_acc: 0.9906, loss_cls: 0.7090, loss: 0.7090 +2025-06-24 10:56:13,449 - pyskl - INFO - Epoch [21][400/1281] lr: 2.389e-02, eta: 11:40:20, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8281, top5_acc: 0.9931, loss_cls: 0.7487, loss: 0.7487 +2025-06-24 10:56:55,186 - pyskl - INFO - Epoch [21][500/1281] lr: 2.388e-02, eta: 11:41:39, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8600, top5_acc: 0.9975, loss_cls: 0.6702, loss: 0.6702 +2025-06-24 10:57:36,733 - pyskl - INFO - Epoch [21][600/1281] lr: 2.387e-02, eta: 11:42:56, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8194, top5_acc: 0.9944, loss_cls: 0.7627, loss: 0.7627 +2025-06-24 10:58:18,189 - pyskl - INFO - Epoch [21][700/1281] lr: 2.386e-02, eta: 11:44:11, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8394, top5_acc: 0.9956, loss_cls: 0.7064, loss: 0.7064 +2025-06-24 10:58:59,524 - pyskl - INFO - Epoch [21][800/1281] lr: 2.385e-02, eta: 11:45:25, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8444, top5_acc: 0.9931, loss_cls: 0.7158, loss: 0.7158 +2025-06-24 10:59:42,257 - pyskl - INFO - Epoch [21][900/1281] lr: 2.384e-02, eta: 11:46:47, time: 0.427, data_time: 0.000, memory: 4082, top1_acc: 0.8488, top5_acc: 0.9906, loss_cls: 0.7072, loss: 0.7072 +2025-06-24 11:00:23,594 - pyskl - INFO - Epoch [21][1000/1281] lr: 2.383e-02, eta: 11:47:59, time: 0.413, data_time: 0.000, memory: 4082, top1_acc: 0.8387, top5_acc: 0.9925, loss_cls: 0.7421, loss: 0.7421 +2025-06-24 11:01:05,065 - pyskl - INFO - Epoch [21][1100/1281] lr: 2.383e-02, eta: 11:49:12, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8331, top5_acc: 0.9931, loss_cls: 0.7300, loss: 0.7300 +2025-06-24 11:01:46,577 - pyskl - INFO - Epoch [21][1200/1281] lr: 2.382e-02, eta: 11:50:23, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8500, top5_acc: 0.9938, loss_cls: 0.7312, loss: 0.7312 +2025-06-24 11:02:20,909 - pyskl - INFO - Saving checkpoint at 21 epochs +2025-06-24 11:03:32,362 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:03:32,417 - pyskl - INFO - +top1_acc 0.8379 +top5_acc 0.9853 +2025-06-24 11:03:32,417 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:03:32,427 - pyskl - INFO - +mean_acc 0.7717 +2025-06-24 11:03:32,431 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_20.pth was removed +2025-06-24 11:03:32,606 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_21.pth. +2025-06-24 11:03:32,606 - pyskl - INFO - Best top1_acc is 0.8379 at 21 epoch. +2025-06-24 11:03:32,610 - pyskl - INFO - Epoch(val) [21][533] top1_acc: 0.8379, top5_acc: 0.9853, mean_class_accuracy: 0.7717 +2025-06-24 11:04:31,127 - pyskl - INFO - Epoch [22][100/1281] lr: 2.380e-02, eta: 11:50:49, time: 0.585, data_time: 0.197, memory: 4082, top1_acc: 0.8712, top5_acc: 0.9950, loss_cls: 0.6228, loss: 0.6228 +2025-06-24 11:05:03,230 - pyskl - INFO - Epoch [22][200/1281] lr: 2.379e-02, eta: 11:51:01, time: 0.321, data_time: 0.000, memory: 4082, top1_acc: 0.8538, top5_acc: 0.9925, loss_cls: 0.6726, loss: 0.6726 +2025-06-24 11:05:36,724 - pyskl - INFO - Epoch [22][300/1281] lr: 2.378e-02, eta: 11:51:22, time: 0.335, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9925, loss_cls: 0.6827, loss: 0.6827 +2025-06-24 11:06:18,455 - pyskl - INFO - Epoch [22][400/1281] lr: 2.378e-02, eta: 11:52:32, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8544, top5_acc: 0.9962, loss_cls: 0.6617, loss: 0.6617 +2025-06-24 11:07:00,047 - pyskl - INFO - Epoch [22][500/1281] lr: 2.377e-02, eta: 11:53:40, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8650, top5_acc: 0.9944, loss_cls: 0.6334, loss: 0.6334 +2025-06-24 11:07:41,457 - pyskl - INFO - Epoch [22][600/1281] lr: 2.376e-02, eta: 11:54:46, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8569, top5_acc: 0.9931, loss_cls: 0.6775, loss: 0.6775 +2025-06-24 11:08:22,977 - pyskl - INFO - Epoch [22][700/1281] lr: 2.375e-02, eta: 11:55:53, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8531, top5_acc: 0.9938, loss_cls: 0.6790, loss: 0.6790 +2025-06-24 11:09:04,372 - pyskl - INFO - Epoch [22][800/1281] lr: 2.374e-02, eta: 11:56:57, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8363, top5_acc: 0.9950, loss_cls: 0.6943, loss: 0.6943 +2025-06-24 11:09:46,020 - pyskl - INFO - Epoch [22][900/1281] lr: 2.373e-02, eta: 11:58:03, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8519, top5_acc: 0.9906, loss_cls: 0.6923, loss: 0.6923 +2025-06-24 11:10:27,516 - pyskl - INFO - Epoch [22][1000/1281] lr: 2.372e-02, eta: 11:59:06, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8306, top5_acc: 0.9944, loss_cls: 0.7533, loss: 0.7533 +2025-06-24 11:11:08,993 - pyskl - INFO - Epoch [22][1100/1281] lr: 2.371e-02, eta: 12:00:09, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8356, top5_acc: 0.9894, loss_cls: 0.7459, loss: 0.7459 +2025-06-24 11:11:50,664 - pyskl - INFO - Epoch [22][1200/1281] lr: 2.370e-02, eta: 12:01:13, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8194, top5_acc: 0.9925, loss_cls: 0.7852, loss: 0.7852 +2025-06-24 11:12:24,875 - pyskl - INFO - Saving checkpoint at 22 epochs +2025-06-24 11:13:36,123 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:13:36,200 - pyskl - INFO - +top1_acc 0.8089 +top5_acc 0.9859 +2025-06-24 11:13:36,200 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:13:36,212 - pyskl - INFO - +mean_acc 0.7425 +2025-06-24 11:13:36,216 - pyskl - INFO - Epoch(val) [22][533] top1_acc: 0.8089, top5_acc: 0.9859, mean_class_accuracy: 0.7425 +2025-06-24 11:14:33,070 - pyskl - INFO - Epoch [23][100/1281] lr: 2.369e-02, eta: 12:01:17, time: 0.568, data_time: 0.194, memory: 4082, top1_acc: 0.8656, top5_acc: 0.9994, loss_cls: 0.6107, loss: 0.6107 +2025-06-24 11:15:06,600 - pyskl - INFO - Epoch [23][200/1281] lr: 2.368e-02, eta: 12:01:32, time: 0.335, data_time: 0.000, memory: 4082, top1_acc: 0.8413, top5_acc: 0.9938, loss_cls: 0.7025, loss: 0.7025 +2025-06-24 11:15:39,434 - pyskl - INFO - Epoch [23][300/1281] lr: 2.367e-02, eta: 12:01:42, time: 0.328, data_time: 0.000, memory: 4082, top1_acc: 0.8494, top5_acc: 0.9944, loss_cls: 0.6578, loss: 0.6578 +2025-06-24 11:16:20,944 - pyskl - INFO - Epoch [23][400/1281] lr: 2.366e-02, eta: 12:02:42, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8538, top5_acc: 0.9925, loss_cls: 0.6598, loss: 0.6598 +2025-06-24 11:17:03,175 - pyskl - INFO - Epoch [23][500/1281] lr: 2.365e-02, eta: 12:03:45, time: 0.422, data_time: 0.000, memory: 4082, top1_acc: 0.8800, top5_acc: 0.9981, loss_cls: 0.5936, loss: 0.5936 +2025-06-24 11:17:45,705 - pyskl - INFO - Epoch [23][600/1281] lr: 2.364e-02, eta: 12:04:49, time: 0.425, data_time: 0.000, memory: 4082, top1_acc: 0.8606, top5_acc: 0.9975, loss_cls: 0.6398, loss: 0.6398 +2025-06-24 11:18:27,502 - pyskl - INFO - Epoch [23][700/1281] lr: 2.363e-02, eta: 12:05:48, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8444, top5_acc: 0.9938, loss_cls: 0.7073, loss: 0.7073 +2025-06-24 11:19:09,124 - pyskl - INFO - Epoch [23][800/1281] lr: 2.362e-02, eta: 12:06:46, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8506, top5_acc: 0.9894, loss_cls: 0.7091, loss: 0.7091 +2025-06-24 11:19:50,642 - pyskl - INFO - Epoch [23][900/1281] lr: 2.361e-02, eta: 12:07:42, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8462, top5_acc: 0.9938, loss_cls: 0.6936, loss: 0.6936 +2025-06-24 11:20:32,163 - pyskl - INFO - Epoch [23][1000/1281] lr: 2.360e-02, eta: 12:08:38, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8462, top5_acc: 0.9944, loss_cls: 0.6952, loss: 0.6952 +2025-06-24 11:21:13,720 - pyskl - INFO - Epoch [23][1100/1281] lr: 2.359e-02, eta: 12:09:33, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8569, top5_acc: 0.9912, loss_cls: 0.6739, loss: 0.6739 +2025-06-24 11:21:55,332 - pyskl - INFO - Epoch [23][1200/1281] lr: 2.359e-02, eta: 12:10:28, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8356, top5_acc: 0.9919, loss_cls: 0.7530, loss: 0.7530 +2025-06-24 11:22:29,771 - pyskl - INFO - Saving checkpoint at 23 epochs +2025-06-24 11:23:41,086 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:23:41,141 - pyskl - INFO - +top1_acc 0.8237 +top5_acc 0.9856 +2025-06-24 11:23:41,141 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:23:41,149 - pyskl - INFO - +mean_acc 0.7402 +2025-06-24 11:23:41,151 - pyskl - INFO - Epoch(val) [23][533] top1_acc: 0.8237, top5_acc: 0.9856, mean_class_accuracy: 0.7402 +2025-06-24 11:24:37,515 - pyskl - INFO - Epoch [24][100/1281] lr: 2.357e-02, eta: 12:10:21, time: 0.564, data_time: 0.200, memory: 4082, top1_acc: 0.8581, top5_acc: 0.9938, loss_cls: 0.6631, loss: 0.6631 +2025-06-24 11:25:12,099 - pyskl - INFO - Epoch [24][200/1281] lr: 2.356e-02, eta: 12:10:36, time: 0.346, data_time: 0.000, memory: 4082, top1_acc: 0.8444, top5_acc: 0.9950, loss_cls: 0.6790, loss: 0.6790 +2025-06-24 11:25:44,074 - pyskl - INFO - Epoch [24][300/1281] lr: 2.355e-02, eta: 12:10:36, time: 0.320, data_time: 0.000, memory: 4082, top1_acc: 0.8550, top5_acc: 0.9938, loss_cls: 0.6479, loss: 0.6479 +2025-06-24 11:26:25,662 - pyskl - INFO - Epoch [24][400/1281] lr: 2.354e-02, eta: 12:11:28, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8294, top5_acc: 0.9931, loss_cls: 0.7280, loss: 0.7280 +2025-06-24 11:27:07,346 - pyskl - INFO - Epoch [24][500/1281] lr: 2.353e-02, eta: 12:12:20, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8538, top5_acc: 0.9944, loss_cls: 0.6961, loss: 0.6961 +2025-06-24 11:27:49,017 - pyskl - INFO - Epoch [24][600/1281] lr: 2.352e-02, eta: 12:13:12, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8644, top5_acc: 0.9944, loss_cls: 0.6602, loss: 0.6602 +2025-06-24 11:28:30,510 - pyskl - INFO - Epoch [24][700/1281] lr: 2.351e-02, eta: 12:14:02, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8556, top5_acc: 0.9900, loss_cls: 0.6911, loss: 0.6911 +2025-06-24 11:29:11,964 - pyskl - INFO - Epoch [24][800/1281] lr: 2.350e-02, eta: 12:14:51, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8469, top5_acc: 0.9944, loss_cls: 0.6518, loss: 0.6518 +2025-06-24 11:29:53,340 - pyskl - INFO - Epoch [24][900/1281] lr: 2.349e-02, eta: 12:15:39, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8656, top5_acc: 0.9938, loss_cls: 0.6405, loss: 0.6405 +2025-06-24 11:30:35,050 - pyskl - INFO - Epoch [24][1000/1281] lr: 2.348e-02, eta: 12:16:28, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8444, top5_acc: 0.9944, loss_cls: 0.6935, loss: 0.6935 +2025-06-24 11:31:16,799 - pyskl - INFO - Epoch [24][1100/1281] lr: 2.347e-02, eta: 12:17:17, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8581, top5_acc: 0.9900, loss_cls: 0.6832, loss: 0.6832 +2025-06-24 11:31:58,472 - pyskl - INFO - Epoch [24][1200/1281] lr: 2.346e-02, eta: 12:18:05, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8519, top5_acc: 0.9881, loss_cls: 0.6733, loss: 0.6733 +2025-06-24 11:32:32,742 - pyskl - INFO - Saving checkpoint at 24 epochs +2025-06-24 11:33:44,076 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:33:44,132 - pyskl - INFO - +top1_acc 0.8148 +top5_acc 0.9866 +2025-06-24 11:33:44,132 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:33:44,140 - pyskl - INFO - +mean_acc 0.7443 +2025-06-24 11:33:44,143 - pyskl - INFO - Epoch(val) [24][533] top1_acc: 0.8148, top5_acc: 0.9866, mean_class_accuracy: 0.7443 +2025-06-24 11:34:39,208 - pyskl - INFO - Epoch [25][100/1281] lr: 2.344e-02, eta: 12:17:44, time: 0.551, data_time: 0.197, memory: 4082, top1_acc: 0.8675, top5_acc: 0.9962, loss_cls: 0.6394, loss: 0.6394 +2025-06-24 11:35:14,839 - pyskl - INFO - Epoch [25][200/1281] lr: 2.343e-02, eta: 12:17:59, time: 0.356, data_time: 0.001, memory: 4082, top1_acc: 0.8738, top5_acc: 0.9962, loss_cls: 0.5901, loss: 0.5901 +2025-06-24 11:35:46,029 - pyskl - INFO - Epoch [25][300/1281] lr: 2.342e-02, eta: 12:17:51, time: 0.312, data_time: 0.000, memory: 4082, top1_acc: 0.8650, top5_acc: 0.9956, loss_cls: 0.6193, loss: 0.6193 +2025-06-24 11:36:27,698 - pyskl - INFO - Epoch [25][400/1281] lr: 2.341e-02, eta: 12:18:37, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8538, top5_acc: 0.9919, loss_cls: 0.6621, loss: 0.6621 +2025-06-24 11:37:09,220 - pyskl - INFO - Epoch [25][500/1281] lr: 2.340e-02, eta: 12:19:21, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8662, top5_acc: 0.9931, loss_cls: 0.6488, loss: 0.6488 +2025-06-24 11:37:50,616 - pyskl - INFO - Epoch [25][600/1281] lr: 2.339e-02, eta: 12:20:05, time: 0.414, data_time: 0.001, memory: 4082, top1_acc: 0.8556, top5_acc: 0.9938, loss_cls: 0.6507, loss: 0.6507 +2025-06-24 11:38:32,301 - pyskl - INFO - Epoch [25][700/1281] lr: 2.338e-02, eta: 12:20:49, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8725, top5_acc: 0.9956, loss_cls: 0.6125, loss: 0.6125 +2025-06-24 11:39:13,856 - pyskl - INFO - Epoch [25][800/1281] lr: 2.337e-02, eta: 12:21:32, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8550, top5_acc: 0.9906, loss_cls: 0.6429, loss: 0.6429 +2025-06-24 11:39:55,409 - pyskl - INFO - Epoch [25][900/1281] lr: 2.336e-02, eta: 12:22:15, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8606, top5_acc: 0.9925, loss_cls: 0.6391, loss: 0.6391 +2025-06-24 11:40:36,829 - pyskl - INFO - Epoch [25][1000/1281] lr: 2.335e-02, eta: 12:22:56, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8519, top5_acc: 0.9925, loss_cls: 0.6579, loss: 0.6579 +2025-06-24 11:41:18,408 - pyskl - INFO - Epoch [25][1100/1281] lr: 2.334e-02, eta: 12:23:38, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8469, top5_acc: 0.9931, loss_cls: 0.7188, loss: 0.7188 +2025-06-24 11:41:59,865 - pyskl - INFO - Epoch [25][1200/1281] lr: 2.333e-02, eta: 12:24:18, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8456, top5_acc: 0.9919, loss_cls: 0.7268, loss: 0.7268 +2025-06-24 11:42:34,278 - pyskl - INFO - Saving checkpoint at 25 epochs +2025-06-24 11:43:46,346 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:43:46,401 - pyskl - INFO - +top1_acc 0.7979 +top5_acc 0.9845 +2025-06-24 11:43:46,401 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:43:46,408 - pyskl - INFO - +mean_acc 0.7238 +2025-06-24 11:43:46,410 - pyskl - INFO - Epoch(val) [25][533] top1_acc: 0.7979, top5_acc: 0.9845, mean_class_accuracy: 0.7238 +2025-06-24 11:44:42,597 - pyskl - INFO - Epoch [26][100/1281] lr: 2.332e-02, eta: 12:23:56, time: 0.562, data_time: 0.202, memory: 4082, top1_acc: 0.8725, top5_acc: 0.9956, loss_cls: 0.6530, loss: 0.6530 +2025-06-24 11:45:17,991 - pyskl - INFO - Epoch [26][200/1281] lr: 2.330e-02, eta: 12:24:05, time: 0.354, data_time: 0.000, memory: 4082, top1_acc: 0.8531, top5_acc: 0.9944, loss_cls: 0.6765, loss: 0.6765 +2025-06-24 11:45:51,427 - pyskl - INFO - Epoch [26][300/1281] lr: 2.329e-02, eta: 12:24:05, time: 0.334, data_time: 0.000, memory: 4082, top1_acc: 0.8594, top5_acc: 0.9944, loss_cls: 0.6453, loss: 0.6453 +2025-06-24 11:46:34,619 - pyskl - INFO - Epoch [26][400/1281] lr: 2.328e-02, eta: 12:24:52, time: 0.432, data_time: 0.001, memory: 4082, top1_acc: 0.8600, top5_acc: 0.9962, loss_cls: 0.6642, loss: 0.6642 +2025-06-24 11:47:16,132 - pyskl - INFO - Epoch [26][500/1281] lr: 2.327e-02, eta: 12:25:30, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8756, top5_acc: 0.9956, loss_cls: 0.6054, loss: 0.6054 +2025-06-24 11:47:57,771 - pyskl - INFO - Epoch [26][600/1281] lr: 2.326e-02, eta: 12:26:09, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8694, top5_acc: 0.9938, loss_cls: 0.6082, loss: 0.6082 +2025-06-24 11:48:39,262 - pyskl - INFO - Epoch [26][700/1281] lr: 2.325e-02, eta: 12:26:46, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8694, top5_acc: 0.9931, loss_cls: 0.6120, loss: 0.6120 +2025-06-24 11:49:20,634 - pyskl - INFO - Epoch [26][800/1281] lr: 2.324e-02, eta: 12:27:23, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8669, top5_acc: 0.9950, loss_cls: 0.6296, loss: 0.6296 +2025-06-24 11:50:02,155 - pyskl - INFO - Epoch [26][900/1281] lr: 2.323e-02, eta: 12:27:59, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8581, top5_acc: 0.9925, loss_cls: 0.6506, loss: 0.6506 +2025-06-24 11:50:43,815 - pyskl - INFO - Epoch [26][1000/1281] lr: 2.322e-02, eta: 12:28:36, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8475, top5_acc: 0.9969, loss_cls: 0.6962, loss: 0.6962 +2025-06-24 11:51:25,329 - pyskl - INFO - Epoch [26][1100/1281] lr: 2.321e-02, eta: 12:29:11, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8588, top5_acc: 0.9962, loss_cls: 0.6594, loss: 0.6594 +2025-06-24 11:52:06,831 - pyskl - INFO - Epoch [26][1200/1281] lr: 2.320e-02, eta: 12:29:46, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8525, top5_acc: 0.9900, loss_cls: 0.6988, loss: 0.6988 +2025-06-24 11:52:41,206 - pyskl - INFO - Saving checkpoint at 26 epochs +2025-06-24 11:53:53,035 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 11:53:53,090 - pyskl - INFO - +top1_acc 0.8228 +top5_acc 0.9863 +2025-06-24 11:53:53,090 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 11:53:53,097 - pyskl - INFO - +mean_acc 0.7602 +2025-06-24 11:53:53,099 - pyskl - INFO - Epoch(val) [26][533] top1_acc: 0.8228, top5_acc: 0.9863, mean_class_accuracy: 0.7602 +2025-06-24 11:54:49,651 - pyskl - INFO - Epoch [27][100/1281] lr: 2.318e-02, eta: 12:29:20, time: 0.565, data_time: 0.199, memory: 4082, top1_acc: 0.8769, top5_acc: 0.9962, loss_cls: 0.6082, loss: 0.6082 +2025-06-24 11:55:24,389 - pyskl - INFO - Epoch [27][200/1281] lr: 2.317e-02, eta: 12:29:23, time: 0.347, data_time: 0.000, memory: 4082, top1_acc: 0.8744, top5_acc: 0.9956, loss_cls: 0.5741, loss: 0.5741 +2025-06-24 11:55:56,970 - pyskl - INFO - Epoch [27][300/1281] lr: 2.316e-02, eta: 12:29:14, time: 0.326, data_time: 0.000, memory: 4082, top1_acc: 0.8612, top5_acc: 0.9962, loss_cls: 0.6193, loss: 0.6193 +2025-06-24 11:56:38,510 - pyskl - INFO - Epoch [27][400/1281] lr: 2.315e-02, eta: 12:29:48, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8656, top5_acc: 0.9931, loss_cls: 0.6400, loss: 0.6400 +2025-06-24 11:57:20,696 - pyskl - INFO - Epoch [27][500/1281] lr: 2.314e-02, eta: 12:30:24, time: 0.422, data_time: 0.000, memory: 4082, top1_acc: 0.8600, top5_acc: 0.9925, loss_cls: 0.6463, loss: 0.6463 +2025-06-24 11:58:03,597 - pyskl - INFO - Epoch [27][600/1281] lr: 2.313e-02, eta: 12:31:03, time: 0.429, data_time: 0.000, memory: 4082, top1_acc: 0.8856, top5_acc: 0.9956, loss_cls: 0.5718, loss: 0.5718 +2025-06-24 11:58:45,074 - pyskl - INFO - Epoch [27][700/1281] lr: 2.312e-02, eta: 12:31:35, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8525, top5_acc: 0.9938, loss_cls: 0.6706, loss: 0.6706 +2025-06-24 11:59:26,661 - pyskl - INFO - Epoch [27][800/1281] lr: 2.311e-02, eta: 12:32:07, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8644, top5_acc: 0.9888, loss_cls: 0.6528, loss: 0.6528 +2025-06-24 12:00:08,026 - pyskl - INFO - Epoch [27][900/1281] lr: 2.310e-02, eta: 12:32:38, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8625, top5_acc: 0.9950, loss_cls: 0.6533, loss: 0.6533 +2025-06-24 12:00:49,728 - pyskl - INFO - Epoch [27][1000/1281] lr: 2.308e-02, eta: 12:33:09, time: 0.417, data_time: 0.000, memory: 4082, top1_acc: 0.8469, top5_acc: 0.9900, loss_cls: 0.6787, loss: 0.6787 +2025-06-24 12:01:31,197 - pyskl - INFO - Epoch [27][1100/1281] lr: 2.307e-02, eta: 12:33:40, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8800, top5_acc: 0.9969, loss_cls: 0.5992, loss: 0.5992 +2025-06-24 12:02:12,827 - pyskl - INFO - Epoch [27][1200/1281] lr: 2.306e-02, eta: 12:34:10, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8488, top5_acc: 0.9956, loss_cls: 0.6830, loss: 0.6830 +2025-06-24 12:02:47,062 - pyskl - INFO - Saving checkpoint at 27 epochs +2025-06-24 12:03:57,807 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:03:57,871 - pyskl - INFO - +top1_acc 0.8242 +top5_acc 0.9813 +2025-06-24 12:03:57,871 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:03:57,880 - pyskl - INFO - +mean_acc 0.7548 +2025-06-24 12:03:57,883 - pyskl - INFO - Epoch(val) [27][533] top1_acc: 0.8242, top5_acc: 0.9813, mean_class_accuracy: 0.7548 +2025-06-24 12:04:52,708 - pyskl - INFO - Epoch [28][100/1281] lr: 2.304e-02, eta: 12:33:31, time: 0.548, data_time: 0.194, memory: 4082, top1_acc: 0.8612, top5_acc: 0.9950, loss_cls: 0.6404, loss: 0.6404 +2025-06-24 12:05:28,707 - pyskl - INFO - Epoch [28][200/1281] lr: 2.303e-02, eta: 12:33:36, time: 0.360, data_time: 0.000, memory: 4082, top1_acc: 0.8631, top5_acc: 0.9938, loss_cls: 0.6525, loss: 0.6525 +2025-06-24 12:05:59,912 - pyskl - INFO - Epoch [28][300/1281] lr: 2.302e-02, eta: 12:33:18, time: 0.312, data_time: 0.000, memory: 4082, top1_acc: 0.8725, top5_acc: 0.9956, loss_cls: 0.6071, loss: 0.6071 +2025-06-24 12:06:41,325 - pyskl - INFO - Epoch [28][400/1281] lr: 2.301e-02, eta: 12:33:46, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8606, top5_acc: 0.9938, loss_cls: 0.6688, loss: 0.6688 +2025-06-24 12:07:23,105 - pyskl - INFO - Epoch [28][500/1281] lr: 2.300e-02, eta: 12:34:16, time: 0.418, data_time: 0.000, memory: 4082, top1_acc: 0.8769, top5_acc: 0.9944, loss_cls: 0.5777, loss: 0.5777 +2025-06-24 12:08:04,534 - pyskl - INFO - Epoch [28][600/1281] lr: 2.299e-02, eta: 12:34:43, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8600, top5_acc: 0.9888, loss_cls: 0.6571, loss: 0.6571 +2025-06-24 12:08:45,985 - pyskl - INFO - Epoch [28][700/1281] lr: 2.298e-02, eta: 12:35:10, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8625, top5_acc: 0.9956, loss_cls: 0.6207, loss: 0.6207 +2025-06-24 12:09:27,584 - pyskl - INFO - Epoch [28][800/1281] lr: 2.297e-02, eta: 12:35:38, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8675, top5_acc: 0.9944, loss_cls: 0.6196, loss: 0.6196 +2025-06-24 12:10:09,152 - pyskl - INFO - Epoch [28][900/1281] lr: 2.295e-02, eta: 12:36:04, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8538, top5_acc: 0.9925, loss_cls: 0.6772, loss: 0.6772 +2025-06-24 12:10:50,519 - pyskl - INFO - Epoch [28][1000/1281] lr: 2.294e-02, eta: 12:36:30, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8669, top5_acc: 0.9925, loss_cls: 0.6298, loss: 0.6298 +2025-06-24 12:11:31,946 - pyskl - INFO - Epoch [28][1100/1281] lr: 2.293e-02, eta: 12:36:56, time: 0.414, data_time: 0.001, memory: 4082, top1_acc: 0.8569, top5_acc: 0.9919, loss_cls: 0.6542, loss: 0.6542 +2025-06-24 12:12:13,528 - pyskl - INFO - Epoch [28][1200/1281] lr: 2.292e-02, eta: 12:37:21, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8594, top5_acc: 0.9950, loss_cls: 0.6666, loss: 0.6666 +2025-06-24 12:12:47,949 - pyskl - INFO - Saving checkpoint at 28 epochs +2025-06-24 12:13:59,353 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:13:59,407 - pyskl - INFO - +top1_acc 0.8439 +top5_acc 0.9876 +2025-06-24 12:13:59,407 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:13:59,414 - pyskl - INFO - +mean_acc 0.7820 +2025-06-24 12:13:59,419 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_21.pth was removed +2025-06-24 12:13:59,609 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_28.pth. +2025-06-24 12:13:59,609 - pyskl - INFO - Best top1_acc is 0.8439 at 28 epoch. +2025-06-24 12:13:59,613 - pyskl - INFO - Epoch(val) [28][533] top1_acc: 0.8439, top5_acc: 0.9876, mean_class_accuracy: 0.7820 +2025-06-24 12:14:54,699 - pyskl - INFO - Epoch [29][100/1281] lr: 2.290e-02, eta: 12:36:40, time: 0.551, data_time: 0.197, memory: 4082, top1_acc: 0.8800, top5_acc: 0.9938, loss_cls: 0.5906, loss: 0.5906 +2025-06-24 12:15:30,410 - pyskl - INFO - Epoch [29][200/1281] lr: 2.289e-02, eta: 12:36:39, time: 0.357, data_time: 0.000, memory: 4082, top1_acc: 0.8638, top5_acc: 0.9950, loss_cls: 0.6421, loss: 0.6421 +2025-06-24 12:16:01,664 - pyskl - INFO - Epoch [29][300/1281] lr: 2.288e-02, eta: 12:36:20, time: 0.313, data_time: 0.001, memory: 4082, top1_acc: 0.8500, top5_acc: 0.9925, loss_cls: 0.6942, loss: 0.6942 +2025-06-24 12:16:43,230 - pyskl - INFO - Epoch [29][400/1281] lr: 2.287e-02, eta: 12:36:44, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8769, top5_acc: 0.9962, loss_cls: 0.5773, loss: 0.5773 +2025-06-24 12:17:24,703 - pyskl - INFO - Epoch [29][500/1281] lr: 2.285e-02, eta: 12:37:08, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8700, top5_acc: 0.9962, loss_cls: 0.6055, loss: 0.6055 +2025-06-24 12:18:06,178 - pyskl - INFO - Epoch [29][600/1281] lr: 2.284e-02, eta: 12:37:31, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8669, top5_acc: 0.9919, loss_cls: 0.6319, loss: 0.6319 +2025-06-24 12:18:47,575 - pyskl - INFO - Epoch [29][700/1281] lr: 2.283e-02, eta: 12:37:54, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8769, top5_acc: 0.9931, loss_cls: 0.6061, loss: 0.6061 +2025-06-24 12:19:29,048 - pyskl - INFO - Epoch [29][800/1281] lr: 2.282e-02, eta: 12:38:17, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8612, top5_acc: 0.9969, loss_cls: 0.6129, loss: 0.6129 +2025-06-24 12:20:10,633 - pyskl - INFO - Epoch [29][900/1281] lr: 2.281e-02, eta: 12:38:39, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8681, top5_acc: 0.9956, loss_cls: 0.6405, loss: 0.6405 +2025-06-24 12:20:52,159 - pyskl - INFO - Epoch [29][1000/1281] lr: 2.280e-02, eta: 12:39:02, time: 0.415, data_time: 0.000, memory: 4082, top1_acc: 0.8650, top5_acc: 0.9956, loss_cls: 0.6382, loss: 0.6382 +2025-06-24 12:21:33,559 - pyskl - INFO - Epoch [29][1100/1281] lr: 2.279e-02, eta: 12:39:23, time: 0.414, data_time: 0.000, memory: 4082, top1_acc: 0.8688, top5_acc: 0.9938, loss_cls: 0.6401, loss: 0.6401 +2025-06-24 12:22:15,125 - pyskl - INFO - Epoch [29][1200/1281] lr: 2.277e-02, eta: 12:39:45, time: 0.416, data_time: 0.000, memory: 4082, top1_acc: 0.8731, top5_acc: 0.9950, loss_cls: 0.6346, loss: 0.6346 +2025-06-24 12:22:49,575 - pyskl - INFO - Saving checkpoint at 29 epochs +2025-06-24 12:24:01,135 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:24:01,192 - pyskl - INFO - +top1_acc 0.8344 +top5_acc 0.9885 +2025-06-24 12:24:01,192 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:24:01,201 - pyskl - INFO - +mean_acc 0.7801 +2025-06-24 12:24:01,204 - pyskl - INFO - Epoch(val) [29][533] top1_acc: 0.8344, top5_acc: 0.9885, mean_class_accuracy: 0.7801 +2025-06-24 12:25:10,767 - pyskl - INFO - Epoch [30][100/1281] lr: 2.275e-02, eta: 12:39:59, time: 0.696, data_time: 0.195, memory: 4082, top1_acc: 0.8788, top5_acc: 0.9950, loss_cls: 0.5877, loss: 0.5877 +2025-06-24 12:25:36,001 - pyskl - INFO - Epoch [30][200/1281] lr: 2.274e-02, eta: 12:39:13, time: 0.252, data_time: 0.000, memory: 4082, top1_acc: 0.8862, top5_acc: 0.9975, loss_cls: 0.5511, loss: 0.5511 +2025-06-24 12:26:26,488 - pyskl - INFO - Epoch [30][300/1281] lr: 2.273e-02, eta: 12:40:10, time: 0.505, data_time: 0.001, memory: 4082, top1_acc: 0.8794, top5_acc: 0.9975, loss_cls: 0.5494, loss: 0.5494 +2025-06-24 12:27:15,947 - pyskl - INFO - Epoch [30][400/1281] lr: 2.272e-02, eta: 12:41:03, time: 0.495, data_time: 0.001, memory: 4082, top1_acc: 0.8562, top5_acc: 0.9888, loss_cls: 0.6518, loss: 0.6518 +2025-06-24 12:28:03,336 - pyskl - INFO - Epoch [30][500/1281] lr: 2.271e-02, eta: 12:41:47, time: 0.474, data_time: 0.000, memory: 4082, top1_acc: 0.8638, top5_acc: 0.9944, loss_cls: 0.6479, loss: 0.6479 +2025-06-24 12:28:52,640 - pyskl - INFO - Epoch [30][600/1281] lr: 2.269e-02, eta: 12:42:38, time: 0.493, data_time: 0.000, memory: 4082, top1_acc: 0.8762, top5_acc: 0.9950, loss_cls: 0.5989, loss: 0.5989 +2025-06-24 12:29:42,560 - pyskl - INFO - Epoch [30][700/1281] lr: 2.268e-02, eta: 12:43:31, time: 0.499, data_time: 0.000, memory: 4082, top1_acc: 0.8656, top5_acc: 0.9938, loss_cls: 0.6210, loss: 0.6210 +2025-06-24 12:30:31,790 - pyskl - INFO - Epoch [30][800/1281] lr: 2.267e-02, eta: 12:44:20, time: 0.492, data_time: 0.000, memory: 4082, top1_acc: 0.8712, top5_acc: 0.9944, loss_cls: 0.6469, loss: 0.6469 +2025-06-24 12:31:20,653 - pyskl - INFO - Epoch [30][900/1281] lr: 2.266e-02, eta: 12:45:08, time: 0.489, data_time: 0.000, memory: 4082, top1_acc: 0.8575, top5_acc: 0.9894, loss_cls: 0.6812, loss: 0.6812 +2025-06-24 12:32:10,668 - pyskl - INFO - Epoch [30][1000/1281] lr: 2.265e-02, eta: 12:46:00, time: 0.500, data_time: 0.000, memory: 4082, top1_acc: 0.8650, top5_acc: 0.9931, loss_cls: 0.6434, loss: 0.6434 +2025-06-24 12:32:59,982 - pyskl - INFO - Epoch [30][1100/1281] lr: 2.263e-02, eta: 12:46:49, time: 0.493, data_time: 0.000, memory: 4082, top1_acc: 0.8738, top5_acc: 0.9925, loss_cls: 0.6349, loss: 0.6349 +2025-06-24 12:33:48,781 - pyskl - INFO - Epoch [30][1200/1281] lr: 2.262e-02, eta: 12:47:34, time: 0.488, data_time: 0.000, memory: 4082, top1_acc: 0.8812, top5_acc: 0.9944, loss_cls: 0.5866, loss: 0.5866 +2025-06-24 12:34:15,566 - pyskl - INFO - Saving checkpoint at 30 epochs +2025-06-24 12:35:15,944 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:35:16,016 - pyskl - INFO - +top1_acc 0.8344 +top5_acc 0.9878 +2025-06-24 12:35:16,016 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:35:16,025 - pyskl - INFO - +mean_acc 0.7740 +2025-06-24 12:35:16,028 - pyskl - INFO - Epoch(val) [30][533] top1_acc: 0.8344, top5_acc: 0.9878, mean_class_accuracy: 0.7740 +2025-06-24 12:36:45,291 - pyskl - INFO - Epoch [31][100/1281] lr: 2.260e-02, eta: 12:49:00, time: 0.893, data_time: 0.194, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9981, loss_cls: 0.7241, loss: 0.7241 +2025-06-24 12:37:36,451 - pyskl - INFO - Epoch [31][200/1281] lr: 2.259e-02, eta: 12:49:54, time: 0.512, data_time: 0.001, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9956, loss_cls: 0.7471, loss: 0.7471 +2025-06-24 12:38:28,952 - pyskl - INFO - Epoch [31][300/1281] lr: 2.258e-02, eta: 12:50:53, time: 0.525, data_time: 0.000, memory: 4083, top1_acc: 0.8556, top5_acc: 0.9950, loss_cls: 0.7891, loss: 0.7891 +2025-06-24 12:39:20,139 - pyskl - INFO - Epoch [31][400/1281] lr: 2.256e-02, eta: 12:51:46, time: 0.512, data_time: 0.001, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9938, loss_cls: 0.7261, loss: 0.7261 +2025-06-24 12:40:12,169 - pyskl - INFO - Epoch [31][500/1281] lr: 2.255e-02, eta: 12:52:41, time: 0.520, data_time: 0.000, memory: 4083, top1_acc: 0.8694, top5_acc: 0.9950, loss_cls: 0.7509, loss: 0.7509 +2025-06-24 12:41:03,703 - pyskl - INFO - Epoch [31][600/1281] lr: 2.254e-02, eta: 12:53:34, time: 0.515, data_time: 0.000, memory: 4083, top1_acc: 0.8700, top5_acc: 0.9962, loss_cls: 0.7659, loss: 0.7659 +2025-06-24 12:41:53,570 - pyskl - INFO - Epoch [31][700/1281] lr: 2.253e-02, eta: 12:54:21, time: 0.499, data_time: 0.000, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9912, loss_cls: 0.8146, loss: 0.8146 +2025-06-24 12:42:44,886 - pyskl - INFO - Epoch [31][800/1281] lr: 2.252e-02, eta: 12:55:12, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9938, loss_cls: 0.7830, loss: 0.7830 +2025-06-24 12:43:25,331 - pyskl - INFO - Epoch [31][900/1281] lr: 2.250e-02, eta: 12:55:20, time: 0.404, data_time: 0.000, memory: 4083, top1_acc: 0.8644, top5_acc: 0.9944, loss_cls: 0.7881, loss: 0.7881 +2025-06-24 12:44:16,447 - pyskl - INFO - Epoch [31][1000/1281] lr: 2.249e-02, eta: 12:56:10, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9894, loss_cls: 0.8055, loss: 0.8055 +2025-06-24 12:44:42,735 - pyskl - INFO - Epoch [31][1100/1281] lr: 2.248e-02, eta: 12:55:23, time: 0.263, data_time: 0.000, memory: 4083, top1_acc: 0.8519, top5_acc: 0.9944, loss_cls: 0.8346, loss: 0.8346 +2025-06-24 12:45:34,251 - pyskl - INFO - Epoch [31][1200/1281] lr: 2.247e-02, eta: 12:56:14, time: 0.515, data_time: 0.000, memory: 4083, top1_acc: 0.8612, top5_acc: 0.9912, loss_cls: 0.8146, loss: 0.8146 +2025-06-24 12:46:16,352 - pyskl - INFO - Saving checkpoint at 31 epochs +2025-06-24 12:47:27,604 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:47:27,663 - pyskl - INFO - +top1_acc 0.8052 +top5_acc 0.9791 +2025-06-24 12:47:27,663 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:47:27,672 - pyskl - INFO - +mean_acc 0.7329 +2025-06-24 12:47:27,675 - pyskl - INFO - Epoch(val) [31][533] top1_acc: 0.8052, top5_acc: 0.9791, mean_class_accuracy: 0.7329 +2025-06-24 12:48:52,669 - pyskl - INFO - Epoch [32][100/1281] lr: 2.244e-02, eta: 12:57:12, time: 0.850, data_time: 0.199, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9925, loss_cls: 0.6506, loss: 0.6506 +2025-06-24 12:49:44,738 - pyskl - INFO - Epoch [32][200/1281] lr: 2.243e-02, eta: 12:58:03, time: 0.521, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9956, loss_cls: 0.6318, loss: 0.6318 +2025-06-24 12:50:37,304 - pyskl - INFO - Epoch [32][300/1281] lr: 2.242e-02, eta: 12:58:56, time: 0.526, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9938, loss_cls: 0.6757, loss: 0.6757 +2025-06-24 12:51:29,661 - pyskl - INFO - Epoch [32][400/1281] lr: 2.241e-02, eta: 12:59:47, time: 0.524, data_time: 0.000, memory: 4083, top1_acc: 0.8631, top5_acc: 0.9950, loss_cls: 0.7472, loss: 0.7472 +2025-06-24 12:52:19,096 - pyskl - INFO - Epoch [32][500/1281] lr: 2.239e-02, eta: 13:00:27, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8650, top5_acc: 0.9938, loss_cls: 0.7055, loss: 0.7055 +2025-06-24 12:52:51,062 - pyskl - INFO - Epoch [32][600/1281] lr: 2.238e-02, eta: 13:00:01, time: 0.320, data_time: 0.000, memory: 4083, top1_acc: 0.8638, top5_acc: 0.9944, loss_cls: 0.7420, loss: 0.7420 +2025-06-24 12:53:33,261 - pyskl - INFO - Epoch [32][700/1281] lr: 2.237e-02, eta: 13:00:12, time: 0.422, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9956, loss_cls: 0.6306, loss: 0.6306 +2025-06-24 12:54:17,455 - pyskl - INFO - Epoch [32][800/1281] lr: 2.236e-02, eta: 13:00:32, time: 0.442, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9956, loss_cls: 0.6222, loss: 0.6222 +2025-06-24 12:55:10,550 - pyskl - INFO - Epoch [32][900/1281] lr: 2.234e-02, eta: 13:01:24, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.8669, top5_acc: 0.9950, loss_cls: 0.7318, loss: 0.7318 +2025-06-24 12:56:03,375 - pyskl - INFO - Epoch [32][1000/1281] lr: 2.233e-02, eta: 13:02:14, time: 0.528, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9925, loss_cls: 0.6822, loss: 0.6822 +2025-06-24 12:56:56,609 - pyskl - INFO - Epoch [32][1100/1281] lr: 2.232e-02, eta: 13:03:06, time: 0.532, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9950, loss_cls: 0.6863, loss: 0.6863 +2025-06-24 12:57:49,090 - pyskl - INFO - Epoch [32][1200/1281] lr: 2.231e-02, eta: 13:03:54, time: 0.525, data_time: 0.000, memory: 4083, top1_acc: 0.8594, top5_acc: 0.9931, loss_cls: 0.6982, loss: 0.6982 +2025-06-24 12:58:31,367 - pyskl - INFO - Saving checkpoint at 32 epochs +2025-06-24 12:59:42,639 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 12:59:42,709 - pyskl - INFO - +top1_acc 0.7586 +top5_acc 0.9772 +2025-06-24 12:59:42,709 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 12:59:42,717 - pyskl - INFO - +mean_acc 0.7199 +2025-06-24 12:59:42,720 - pyskl - INFO - Epoch(val) [32][533] top1_acc: 0.7586, top5_acc: 0.9772, mean_class_accuracy: 0.7199 +2025-06-24 13:01:07,239 - pyskl - INFO - Epoch [33][100/1281] lr: 2.228e-02, eta: 13:04:41, time: 0.845, data_time: 0.199, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9981, loss_cls: 0.6469, loss: 0.6469 +2025-06-24 13:01:36,693 - pyskl - INFO - Epoch [33][200/1281] lr: 2.227e-02, eta: 13:04:04, time: 0.295, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9956, loss_cls: 0.6650, loss: 0.6650 +2025-06-24 13:02:28,144 - pyskl - INFO - Epoch [33][300/1281] lr: 2.226e-02, eta: 13:04:47, time: 0.514, data_time: 0.000, memory: 4083, top1_acc: 0.8581, top5_acc: 0.9956, loss_cls: 0.7144, loss: 0.7144 +2025-06-24 13:03:04,481 - pyskl - INFO - Epoch [33][400/1281] lr: 2.225e-02, eta: 13:04:34, time: 0.363, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9962, loss_cls: 0.6436, loss: 0.6436 +2025-06-24 13:03:56,678 - pyskl - INFO - Epoch [33][500/1281] lr: 2.223e-02, eta: 13:05:19, time: 0.522, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9931, loss_cls: 0.6776, loss: 0.6776 +2025-06-24 13:04:48,637 - pyskl - INFO - Epoch [33][600/1281] lr: 2.222e-02, eta: 13:06:03, time: 0.520, data_time: 0.000, memory: 4083, top1_acc: 0.8644, top5_acc: 0.9919, loss_cls: 0.7262, loss: 0.7262 +2025-06-24 13:05:40,426 - pyskl - INFO - Epoch [33][700/1281] lr: 2.221e-02, eta: 13:06:45, time: 0.518, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9956, loss_cls: 0.5991, loss: 0.5991 +2025-06-24 13:06:32,248 - pyskl - INFO - Epoch [33][800/1281] lr: 2.219e-02, eta: 13:07:27, time: 0.518, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9956, loss_cls: 0.6313, loss: 0.6313 +2025-06-24 13:07:23,749 - pyskl - INFO - Epoch [33][900/1281] lr: 2.218e-02, eta: 13:08:08, time: 0.515, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9938, loss_cls: 0.6485, loss: 0.6485 +2025-06-24 13:08:15,845 - pyskl - INFO - Epoch [33][1000/1281] lr: 2.217e-02, eta: 13:08:50, time: 0.521, data_time: 0.000, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9969, loss_cls: 0.6659, loss: 0.6659 +2025-06-24 13:09:07,457 - pyskl - INFO - Epoch [33][1100/1281] lr: 2.216e-02, eta: 13:09:30, time: 0.516, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9931, loss_cls: 0.6778, loss: 0.6778 +2025-06-24 13:09:57,811 - pyskl - INFO - Epoch [33][1200/1281] lr: 2.214e-02, eta: 13:10:05, time: 0.504, data_time: 0.000, memory: 4083, top1_acc: 0.8625, top5_acc: 0.9962, loss_cls: 0.6548, loss: 0.6548 +2025-06-24 13:10:40,333 - pyskl - INFO - Saving checkpoint at 33 epochs +2025-06-24 13:11:49,321 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:11:49,392 - pyskl - INFO - +top1_acc 0.7963 +top5_acc 0.9849 +2025-06-24 13:11:49,392 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:11:49,400 - pyskl - INFO - +mean_acc 0.7320 +2025-06-24 13:11:49,402 - pyskl - INFO - Epoch(val) [33][533] top1_acc: 0.7963, top5_acc: 0.9849, mean_class_accuracy: 0.7320 +2025-06-24 13:12:57,690 - pyskl - INFO - Epoch [34][100/1281] lr: 2.212e-02, eta: 13:09:47, time: 0.683, data_time: 0.199, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9981, loss_cls: 0.6189, loss: 0.6189 +2025-06-24 13:13:48,549 - pyskl - INFO - Epoch [34][200/1281] lr: 2.211e-02, eta: 13:10:23, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9956, loss_cls: 0.6540, loss: 0.6540 +2025-06-24 13:14:39,464 - pyskl - INFO - Epoch [34][300/1281] lr: 2.209e-02, eta: 13:10:59, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9969, loss_cls: 0.6114, loss: 0.6114 +2025-06-24 13:15:30,427 - pyskl - INFO - Epoch [34][400/1281] lr: 2.208e-02, eta: 13:11:35, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.8731, top5_acc: 0.9931, loss_cls: 0.6414, loss: 0.6414 +2025-06-24 13:16:22,747 - pyskl - INFO - Epoch [34][500/1281] lr: 2.207e-02, eta: 13:12:15, time: 0.523, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9956, loss_cls: 0.6054, loss: 0.6054 +2025-06-24 13:17:13,490 - pyskl - INFO - Epoch [34][600/1281] lr: 2.205e-02, eta: 13:12:49, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.8856, top5_acc: 0.9969, loss_cls: 0.5864, loss: 0.5864 +2025-06-24 13:18:06,438 - pyskl - INFO - Epoch [34][700/1281] lr: 2.204e-02, eta: 13:13:30, time: 0.529, data_time: 0.000, memory: 4083, top1_acc: 0.8512, top5_acc: 0.9956, loss_cls: 0.7012, loss: 0.7012 +2025-06-24 13:18:58,555 - pyskl - INFO - Epoch [34][800/1281] lr: 2.203e-02, eta: 13:14:08, time: 0.521, data_time: 0.000, memory: 4083, top1_acc: 0.8525, top5_acc: 0.9912, loss_cls: 0.7150, loss: 0.7150 +2025-06-24 13:19:50,429 - pyskl - INFO - Epoch [34][900/1281] lr: 2.201e-02, eta: 13:14:45, time: 0.519, data_time: 0.000, memory: 4083, top1_acc: 0.8531, top5_acc: 0.9969, loss_cls: 0.7438, loss: 0.7438 +2025-06-24 13:20:31,869 - pyskl - INFO - Epoch [34][1000/1281] lr: 2.200e-02, eta: 13:14:45, time: 0.414, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9969, loss_cls: 0.6193, loss: 0.6193 +2025-06-24 13:21:23,052 - pyskl - INFO - Epoch [34][1100/1281] lr: 2.199e-02, eta: 13:15:19, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9950, loss_cls: 0.6315, loss: 0.6315 +2025-06-24 13:21:50,294 - pyskl - INFO - Epoch [34][1200/1281] lr: 2.197e-02, eta: 13:14:31, time: 0.272, data_time: 0.000, memory: 4083, top1_acc: 0.8606, top5_acc: 0.9912, loss_cls: 0.7216, loss: 0.7216 +2025-06-24 13:22:33,621 - pyskl - INFO - Saving checkpoint at 34 epochs +2025-06-24 13:23:44,375 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:23:44,430 - pyskl - INFO - +top1_acc 0.8356 +top5_acc 0.9887 +2025-06-24 13:23:44,430 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:23:44,437 - pyskl - INFO - +mean_acc 0.7765 +2025-06-24 13:23:44,439 - pyskl - INFO - Epoch(val) [34][533] top1_acc: 0.8356, top5_acc: 0.9887, mean_class_accuracy: 0.7765 +2025-06-24 13:25:09,162 - pyskl - INFO - Epoch [35][100/1281] lr: 2.195e-02, eta: 13:15:03, time: 0.847, data_time: 0.194, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9938, loss_cls: 0.6321, loss: 0.6321 +2025-06-24 13:26:01,424 - pyskl - INFO - Epoch [35][200/1281] lr: 2.194e-02, eta: 13:15:39, time: 0.523, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9981, loss_cls: 0.6047, loss: 0.6047 +2025-06-24 13:26:54,233 - pyskl - INFO - Epoch [35][300/1281] lr: 2.192e-02, eta: 13:16:17, time: 0.528, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9925, loss_cls: 0.6333, loss: 0.6333 +2025-06-24 13:27:45,158 - pyskl - INFO - Epoch [35][400/1281] lr: 2.191e-02, eta: 13:16:48, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9956, loss_cls: 0.6147, loss: 0.6147 +2025-06-24 13:28:37,165 - pyskl - INFO - Epoch [35][500/1281] lr: 2.190e-02, eta: 13:17:22, time: 0.520, data_time: 0.000, memory: 4083, top1_acc: 0.8650, top5_acc: 0.9956, loss_cls: 0.6607, loss: 0.6607 +2025-06-24 13:29:25,578 - pyskl - INFO - Epoch [35][600/1281] lr: 2.188e-02, eta: 13:17:44, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9906, loss_cls: 0.6430, loss: 0.6430 +2025-06-24 13:30:04,562 - pyskl - INFO - Epoch [35][700/1281] lr: 2.187e-02, eta: 13:17:34, time: 0.390, data_time: 0.000, memory: 4083, top1_acc: 0.8669, top5_acc: 0.9950, loss_cls: 0.6443, loss: 0.6443 +2025-06-24 13:30:39,714 - pyskl - INFO - Epoch [35][800/1281] lr: 2.185e-02, eta: 13:17:11, time: 0.352, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9938, loss_cls: 0.6338, loss: 0.6338 +2025-06-24 13:31:27,990 - pyskl - INFO - Epoch [35][900/1281] lr: 2.184e-02, eta: 13:17:31, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9962, loss_cls: 0.6411, loss: 0.6411 +2025-06-24 13:32:19,843 - pyskl - INFO - Epoch [35][1000/1281] lr: 2.183e-02, eta: 13:18:03, time: 0.519, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9956, loss_cls: 0.6201, loss: 0.6201 +2025-06-24 13:33:11,658 - pyskl - INFO - Epoch [35][1100/1281] lr: 2.181e-02, eta: 13:18:35, time: 0.518, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9975, loss_cls: 0.6167, loss: 0.6167 +2025-06-24 13:34:04,141 - pyskl - INFO - Epoch [35][1200/1281] lr: 2.180e-02, eta: 13:19:08, time: 0.525, data_time: 0.000, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9969, loss_cls: 0.6146, loss: 0.6146 +2025-06-24 13:34:47,839 - pyskl - INFO - Saving checkpoint at 35 epochs +2025-06-24 13:35:58,794 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:35:58,852 - pyskl - INFO - +top1_acc 0.8375 +top5_acc 0.9891 +2025-06-24 13:35:58,852 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:35:58,859 - pyskl - INFO - +mean_acc 0.7717 +2025-06-24 13:35:58,862 - pyskl - INFO - Epoch(val) [35][533] top1_acc: 0.8375, top5_acc: 0.9891, mean_class_accuracy: 0.7717 +2025-06-24 13:37:23,340 - pyskl - INFO - Epoch [36][100/1281] lr: 2.178e-02, eta: 13:19:33, time: 0.845, data_time: 0.187, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9969, loss_cls: 0.6189, loss: 0.6189 +2025-06-24 13:38:14,938 - pyskl - INFO - Epoch [36][200/1281] lr: 2.176e-02, eta: 13:20:02, time: 0.516, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9956, loss_cls: 0.5856, loss: 0.5856 +2025-06-24 13:38:43,217 - pyskl - INFO - Epoch [36][300/1281] lr: 2.175e-02, eta: 13:19:16, time: 0.283, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9956, loss_cls: 0.6357, loss: 0.6357 +2025-06-24 13:39:33,710 - pyskl - INFO - Epoch [36][400/1281] lr: 2.173e-02, eta: 13:19:41, time: 0.505, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9975, loss_cls: 0.5810, loss: 0.5810 +2025-06-24 13:40:12,559 - pyskl - INFO - Epoch [36][500/1281] lr: 2.172e-02, eta: 13:19:28, time: 0.388, data_time: 0.001, memory: 4083, top1_acc: 0.8669, top5_acc: 0.9944, loss_cls: 0.6382, loss: 0.6382 +2025-06-24 13:41:04,624 - pyskl - INFO - Epoch [36][600/1281] lr: 2.171e-02, eta: 13:19:58, time: 0.521, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9975, loss_cls: 0.6228, loss: 0.6228 +2025-06-24 13:41:56,370 - pyskl - INFO - Epoch [36][700/1281] lr: 2.169e-02, eta: 13:20:27, time: 0.517, data_time: 0.000, memory: 4083, top1_acc: 0.8650, top5_acc: 0.9925, loss_cls: 0.7163, loss: 0.7163 +2025-06-24 13:42:48,617 - pyskl - INFO - Epoch [36][800/1281] lr: 2.168e-02, eta: 13:20:57, time: 0.522, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9931, loss_cls: 0.6409, loss: 0.6409 +2025-06-24 13:43:41,157 - pyskl - INFO - Epoch [36][900/1281] lr: 2.167e-02, eta: 13:21:27, time: 0.525, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9956, loss_cls: 0.5869, loss: 0.5869 +2025-06-24 13:44:32,746 - pyskl - INFO - Epoch [36][1000/1281] lr: 2.165e-02, eta: 13:21:54, time: 0.516, data_time: 0.000, memory: 4083, top1_acc: 0.8688, top5_acc: 0.9956, loss_cls: 0.6531, loss: 0.6531 +2025-06-24 13:45:25,187 - pyskl - INFO - Epoch [36][1100/1281] lr: 2.164e-02, eta: 13:22:24, time: 0.524, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9944, loss_cls: 0.6506, loss: 0.6506 +2025-06-24 13:46:16,252 - pyskl - INFO - Epoch [36][1200/1281] lr: 2.162e-02, eta: 13:22:48, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9944, loss_cls: 0.6061, loss: 0.6061 +2025-06-24 13:46:59,405 - pyskl - INFO - Saving checkpoint at 36 epochs +2025-06-24 13:47:56,811 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:47:56,869 - pyskl - INFO - +top1_acc 0.8047 +top5_acc 0.9840 +2025-06-24 13:47:56,869 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:47:56,876 - pyskl - INFO - +mean_acc 0.7259 +2025-06-24 13:47:56,878 - pyskl - INFO - Epoch(val) [36][533] top1_acc: 0.8047, top5_acc: 0.9840, mean_class_accuracy: 0.7259 +2025-06-24 13:48:54,357 - pyskl - INFO - Epoch [37][100/1281] lr: 2.160e-02, eta: 13:21:42, time: 0.575, data_time: 0.198, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9944, loss_cls: 0.6105, loss: 0.6105 +2025-06-24 13:49:45,864 - pyskl - INFO - Epoch [37][200/1281] lr: 2.158e-02, eta: 13:22:07, time: 0.515, data_time: 0.000, memory: 4083, top1_acc: 0.8706, top5_acc: 0.9931, loss_cls: 0.6733, loss: 0.6733 +2025-06-24 13:50:36,352 - pyskl - INFO - Epoch [37][300/1281] lr: 2.157e-02, eta: 13:22:29, time: 0.505, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9981, loss_cls: 0.5822, loss: 0.5822 +2025-06-24 13:51:28,590 - pyskl - INFO - Epoch [37][400/1281] lr: 2.156e-02, eta: 13:22:56, time: 0.522, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9969, loss_cls: 0.5692, loss: 0.5692 +2025-06-24 13:52:20,461 - pyskl - INFO - Epoch [37][500/1281] lr: 2.154e-02, eta: 13:23:22, time: 0.519, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9962, loss_cls: 0.6253, loss: 0.6253 +2025-06-24 13:53:12,326 - pyskl - INFO - Epoch [37][600/1281] lr: 2.153e-02, eta: 13:23:47, time: 0.519, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9950, loss_cls: 0.6323, loss: 0.6323 +2025-06-24 13:54:04,105 - pyskl - INFO - Epoch [37][700/1281] lr: 2.151e-02, eta: 13:24:11, time: 0.518, data_time: 0.000, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9956, loss_cls: 0.6516, loss: 0.6516 +2025-06-24 13:54:56,249 - pyskl - INFO - Epoch [37][800/1281] lr: 2.150e-02, eta: 13:24:37, time: 0.521, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9956, loss_cls: 0.5810, loss: 0.5810 +2025-06-24 13:55:47,327 - pyskl - INFO - Epoch [37][900/1281] lr: 2.149e-02, eta: 13:24:59, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9956, loss_cls: 0.5847, loss: 0.5847 +2025-06-24 13:56:38,595 - pyskl - INFO - Epoch [37][1000/1281] lr: 2.147e-02, eta: 13:25:21, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.8762, top5_acc: 0.9950, loss_cls: 0.6276, loss: 0.6276 +2025-06-24 13:57:13,173 - pyskl - INFO - Epoch [37][1100/1281] lr: 2.146e-02, eta: 13:24:51, time: 0.346, data_time: 0.000, memory: 4083, top1_acc: 0.8662, top5_acc: 0.9931, loss_cls: 0.6702, loss: 0.6702 +2025-06-24 13:58:04,318 - pyskl - INFO - Epoch [37][1200/1281] lr: 2.144e-02, eta: 13:25:13, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.8769, top5_acc: 0.9931, loss_cls: 0.6530, loss: 0.6530 +2025-06-24 13:58:27,574 - pyskl - INFO - Saving checkpoint at 37 epochs +2025-06-24 13:59:39,361 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 13:59:39,418 - pyskl - INFO - +top1_acc 0.8282 +top5_acc 0.9890 +2025-06-24 13:59:39,418 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 13:59:39,429 - pyskl - INFO - +mean_acc 0.7829 +2025-06-24 13:59:39,432 - pyskl - INFO - Epoch(val) [37][533] top1_acc: 0.8282, top5_acc: 0.9890, mean_class_accuracy: 0.7829 +2025-06-24 14:01:02,851 - pyskl - INFO - Epoch [38][100/1281] lr: 2.142e-02, eta: 13:25:22, time: 0.834, data_time: 0.198, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9944, loss_cls: 0.6174, loss: 0.6174 +2025-06-24 14:01:54,025 - pyskl - INFO - Epoch [38][200/1281] lr: 2.140e-02, eta: 13:25:43, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9956, loss_cls: 0.6038, loss: 0.6038 +2025-06-24 14:02:45,137 - pyskl - INFO - Epoch [38][300/1281] lr: 2.139e-02, eta: 13:26:03, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9944, loss_cls: 0.6418, loss: 0.6418 +2025-06-24 14:03:35,808 - pyskl - INFO - Epoch [38][400/1281] lr: 2.137e-02, eta: 13:26:21, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9981, loss_cls: 0.5834, loss: 0.5834 +2025-06-24 14:04:27,987 - pyskl - INFO - Epoch [38][500/1281] lr: 2.136e-02, eta: 13:26:44, time: 0.522, data_time: 0.000, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9956, loss_cls: 0.5920, loss: 0.5920 +2025-06-24 14:05:19,446 - pyskl - INFO - Epoch [38][600/1281] lr: 2.134e-02, eta: 13:27:04, time: 0.515, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9988, loss_cls: 0.5699, loss: 0.5699 +2025-06-24 14:06:07,487 - pyskl - INFO - Epoch [38][700/1281] lr: 2.133e-02, eta: 13:27:14, time: 0.480, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9944, loss_cls: 0.6458, loss: 0.6458 +2025-06-24 14:06:46,203 - pyskl - INFO - Epoch [38][800/1281] lr: 2.132e-02, eta: 13:26:56, time: 0.387, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9956, loss_cls: 0.6161, loss: 0.6161 +2025-06-24 14:07:21,630 - pyskl - INFO - Epoch [38][900/1281] lr: 2.130e-02, eta: 13:26:27, time: 0.354, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9925, loss_cls: 0.6156, loss: 0.6156 +2025-06-24 14:08:08,825 - pyskl - INFO - Epoch [38][1000/1281] lr: 2.129e-02, eta: 13:26:34, time: 0.472, data_time: 0.001, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9962, loss_cls: 0.6201, loss: 0.6201 +2025-06-24 14:09:00,400 - pyskl - INFO - Epoch [38][1100/1281] lr: 2.127e-02, eta: 13:26:53, time: 0.516, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9956, loss_cls: 0.6048, loss: 0.6048 +2025-06-24 14:09:53,518 - pyskl - INFO - Epoch [38][1200/1281] lr: 2.126e-02, eta: 13:27:17, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9938, loss_cls: 0.6810, loss: 0.6810 +2025-06-24 14:10:37,092 - pyskl - INFO - Saving checkpoint at 38 epochs +2025-06-24 14:11:48,577 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:11:48,638 - pyskl - INFO - +top1_acc 0.8520 +top5_acc 0.9901 +2025-06-24 14:11:48,639 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:11:48,648 - pyskl - INFO - +mean_acc 0.8026 +2025-06-24 14:11:48,653 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_28.pth was removed +2025-06-24 14:11:48,886 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_38.pth. +2025-06-24 14:11:48,887 - pyskl - INFO - Best top1_acc is 0.8520 at 38 epoch. +2025-06-24 14:11:48,890 - pyskl - INFO - Epoch(val) [38][533] top1_acc: 0.8520, top5_acc: 0.9901, mean_class_accuracy: 0.8026 +2025-06-24 14:13:12,539 - pyskl - INFO - Epoch [39][100/1281] lr: 2.123e-02, eta: 13:27:22, time: 0.836, data_time: 0.192, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9962, loss_cls: 0.5648, loss: 0.5648 +2025-06-24 14:14:04,667 - pyskl - INFO - Epoch [39][200/1281] lr: 2.122e-02, eta: 13:27:42, time: 0.521, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9962, loss_cls: 0.5862, loss: 0.5862 +2025-06-24 14:14:55,987 - pyskl - INFO - Epoch [39][300/1281] lr: 2.120e-02, eta: 13:27:59, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9938, loss_cls: 0.6330, loss: 0.6330 +2025-06-24 14:15:24,085 - pyskl - INFO - Epoch [39][400/1281] lr: 2.119e-02, eta: 13:27:09, time: 0.281, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9962, loss_cls: 0.6280, loss: 0.6280 +2025-06-24 14:16:15,288 - pyskl - INFO - Epoch [39][500/1281] lr: 2.117e-02, eta: 13:27:25, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9950, loss_cls: 0.5627, loss: 0.5627 +2025-06-24 14:16:53,878 - pyskl - INFO - Epoch [39][600/1281] lr: 2.116e-02, eta: 13:27:05, time: 0.386, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9925, loss_cls: 0.6000, loss: 0.6000 +2025-06-24 14:17:45,619 - pyskl - INFO - Epoch [39][700/1281] lr: 2.114e-02, eta: 13:27:23, time: 0.517, data_time: 0.000, memory: 4083, top1_acc: 0.8669, top5_acc: 0.9962, loss_cls: 0.6337, loss: 0.6337 +2025-06-24 14:18:37,134 - pyskl - INFO - Epoch [39][800/1281] lr: 2.113e-02, eta: 13:27:40, time: 0.515, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9975, loss_cls: 0.5567, loss: 0.5567 +2025-06-24 14:19:29,927 - pyskl - INFO - Epoch [39][900/1281] lr: 2.111e-02, eta: 13:28:00, time: 0.528, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9956, loss_cls: 0.5939, loss: 0.5939 +2025-06-24 14:20:21,753 - pyskl - INFO - Epoch [39][1000/1281] lr: 2.110e-02, eta: 13:28:17, time: 0.518, data_time: 0.000, memory: 4083, top1_acc: 0.8744, top5_acc: 0.9969, loss_cls: 0.6342, loss: 0.6342 +2025-06-24 14:21:14,128 - pyskl - INFO - Epoch [39][1100/1281] lr: 2.108e-02, eta: 13:28:35, time: 0.524, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9944, loss_cls: 0.5697, loss: 0.5697 +2025-06-24 14:22:04,732 - pyskl - INFO - Epoch [39][1200/1281] lr: 2.107e-02, eta: 13:28:48, time: 0.506, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9969, loss_cls: 0.5846, loss: 0.5846 +2025-06-24 14:22:46,354 - pyskl - INFO - Saving checkpoint at 39 epochs +2025-06-24 14:23:58,001 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:23:58,057 - pyskl - INFO - +top1_acc 0.8675 +top5_acc 0.9919 +2025-06-24 14:23:58,057 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:23:58,064 - pyskl - INFO - +mean_acc 0.8112 +2025-06-24 14:23:58,068 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_38.pth was removed +2025-06-24 14:23:58,242 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_39.pth. +2025-06-24 14:23:58,243 - pyskl - INFO - Best top1_acc is 0.8675 at 39 epoch. +2025-06-24 14:23:58,245 - pyskl - INFO - Epoch(val) [39][533] top1_acc: 0.8675, top5_acc: 0.9919, mean_class_accuracy: 0.8112 +2025-06-24 14:24:56,869 - pyskl - INFO - Epoch [40][100/1281] lr: 2.104e-02, eta: 13:27:38, time: 0.586, data_time: 0.195, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9962, loss_cls: 0.5272, loss: 0.5272 +2025-06-24 14:25:32,376 - pyskl - INFO - Epoch [40][200/1281] lr: 2.103e-02, eta: 13:27:08, time: 0.355, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9975, loss_cls: 0.5288, loss: 0.5288 +2025-06-24 14:26:18,703 - pyskl - INFO - Epoch [40][300/1281] lr: 2.101e-02, eta: 13:27:08, time: 0.463, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9988, loss_cls: 0.5527, loss: 0.5527 +2025-06-24 14:27:08,807 - pyskl - INFO - Epoch [40][400/1281] lr: 2.100e-02, eta: 13:27:19, time: 0.501, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9969, loss_cls: 0.5583, loss: 0.5583 +2025-06-24 14:27:59,248 - pyskl - INFO - Epoch [40][500/1281] lr: 2.098e-02, eta: 13:27:30, time: 0.504, data_time: 0.000, memory: 4083, top1_acc: 0.8719, top5_acc: 0.9925, loss_cls: 0.6444, loss: 0.6444 +2025-06-24 14:28:49,742 - pyskl - INFO - Epoch [40][600/1281] lr: 2.097e-02, eta: 13:27:42, time: 0.505, data_time: 0.000, memory: 4083, top1_acc: 0.8688, top5_acc: 0.9950, loss_cls: 0.6560, loss: 0.6560 +2025-06-24 14:29:41,475 - pyskl - INFO - Epoch [40][700/1281] lr: 2.095e-02, eta: 13:27:57, time: 0.517, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9938, loss_cls: 0.6342, loss: 0.6342 +2025-06-24 14:30:32,352 - pyskl - INFO - Epoch [40][800/1281] lr: 2.094e-02, eta: 13:28:09, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.8806, top5_acc: 0.9925, loss_cls: 0.6190, loss: 0.6190 +2025-06-24 14:31:24,007 - pyskl - INFO - Epoch [40][900/1281] lr: 2.092e-02, eta: 13:28:22, time: 0.517, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9969, loss_cls: 0.6177, loss: 0.6177 +2025-06-24 14:32:17,234 - pyskl - INFO - Epoch [40][1000/1281] lr: 2.091e-02, eta: 13:28:41, time: 0.532, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9962, loss_cls: 0.5626, loss: 0.5626 +2025-06-24 14:33:08,219 - pyskl - INFO - Epoch [40][1100/1281] lr: 2.089e-02, eta: 13:28:52, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9925, loss_cls: 0.6436, loss: 0.6436 +2025-06-24 14:33:54,341 - pyskl - INFO - Epoch [40][1200/1281] lr: 2.088e-02, eta: 13:28:50, time: 0.461, data_time: 0.000, memory: 4083, top1_acc: 0.8650, top5_acc: 0.9950, loss_cls: 0.6662, loss: 0.6662 +2025-06-24 14:34:20,955 - pyskl - INFO - Saving checkpoint at 40 epochs +2025-06-24 14:35:10,838 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:35:10,893 - pyskl - INFO - +top1_acc 0.8378 +top5_acc 0.9891 +2025-06-24 14:35:10,893 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:35:10,900 - pyskl - INFO - +mean_acc 0.7545 +2025-06-24 14:35:10,902 - pyskl - INFO - Epoch(val) [40][533] top1_acc: 0.8378, top5_acc: 0.9891, mean_class_accuracy: 0.7545 +2025-06-24 14:36:35,457 - pyskl - INFO - Epoch [41][100/1281] lr: 2.085e-02, eta: 13:28:49, time: 0.845, data_time: 0.198, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9888, loss_cls: 0.6599, loss: 0.6599 +2025-06-24 14:37:28,550 - pyskl - INFO - Epoch [41][200/1281] lr: 2.083e-02, eta: 13:29:05, time: 0.531, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9988, loss_cls: 0.5117, loss: 0.5117 +2025-06-24 14:38:20,556 - pyskl - INFO - Epoch [41][300/1281] lr: 2.082e-02, eta: 13:29:18, time: 0.520, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9988, loss_cls: 0.4982, loss: 0.4982 +2025-06-24 14:39:12,232 - pyskl - INFO - Epoch [41][400/1281] lr: 2.080e-02, eta: 13:29:31, time: 0.517, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9956, loss_cls: 0.5953, loss: 0.5953 +2025-06-24 14:40:01,813 - pyskl - INFO - Epoch [41][500/1281] lr: 2.079e-02, eta: 13:29:37, time: 0.496, data_time: 0.001, memory: 4083, top1_acc: 0.8750, top5_acc: 0.9962, loss_cls: 0.6356, loss: 0.6356 +2025-06-24 14:40:53,467 - pyskl - INFO - Epoch [41][600/1281] lr: 2.077e-02, eta: 13:29:48, time: 0.517, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9906, loss_cls: 0.6178, loss: 0.6178 +2025-06-24 14:41:44,279 - pyskl - INFO - Epoch [41][700/1281] lr: 2.076e-02, eta: 13:29:57, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9988, loss_cls: 0.5685, loss: 0.5685 +2025-06-24 14:42:38,093 - pyskl - INFO - Epoch [41][800/1281] lr: 2.074e-02, eta: 13:30:14, time: 0.538, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9931, loss_cls: 0.6905, loss: 0.6905 +2025-06-24 14:43:06,568 - pyskl - INFO - Epoch [41][900/1281] lr: 2.073e-02, eta: 13:29:23, time: 0.285, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9969, loss_cls: 0.5923, loss: 0.5923 +2025-06-24 14:43:57,747 - pyskl - INFO - Epoch [41][1000/1281] lr: 2.071e-02, eta: 13:29:32, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9950, loss_cls: 0.6142, loss: 0.6142 +2025-06-24 14:44:36,507 - pyskl - INFO - Epoch [41][1100/1281] lr: 2.070e-02, eta: 13:29:08, time: 0.388, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9962, loss_cls: 0.5558, loss: 0.5558 +2025-06-24 14:45:27,677 - pyskl - INFO - Epoch [41][1200/1281] lr: 2.068e-02, eta: 13:29:17, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9975, loss_cls: 0.5806, loss: 0.5806 +2025-06-24 14:46:09,487 - pyskl - INFO - Saving checkpoint at 41 epochs +2025-06-24 14:47:20,391 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:47:20,446 - pyskl - INFO - +top1_acc 0.8390 +top5_acc 0.9896 +2025-06-24 14:47:20,446 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:47:20,453 - pyskl - INFO - +mean_acc 0.7716 +2025-06-24 14:47:20,455 - pyskl - INFO - Epoch(val) [41][533] top1_acc: 0.8390, top5_acc: 0.9896, mean_class_accuracy: 0.7716 +2025-06-24 14:48:46,229 - pyskl - INFO - Epoch [42][100/1281] lr: 2.065e-02, eta: 13:29:15, time: 0.858, data_time: 0.194, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9956, loss_cls: 0.5821, loss: 0.5821 +2025-06-24 14:49:36,771 - pyskl - INFO - Epoch [42][200/1281] lr: 2.064e-02, eta: 13:29:22, time: 0.505, data_time: 0.000, memory: 4083, top1_acc: 0.8619, top5_acc: 0.9950, loss_cls: 0.6719, loss: 0.6719 +2025-06-24 14:50:28,990 - pyskl - INFO - Epoch [42][300/1281] lr: 2.062e-02, eta: 13:29:33, time: 0.522, data_time: 0.000, memory: 4083, top1_acc: 0.8625, top5_acc: 0.9956, loss_cls: 0.6694, loss: 0.6694 +2025-06-24 14:51:21,569 - pyskl - INFO - Epoch [42][400/1281] lr: 2.061e-02, eta: 13:29:45, time: 0.526, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9975, loss_cls: 0.6063, loss: 0.6063 +2025-06-24 14:51:59,694 - pyskl - INFO - Epoch [42][500/1281] lr: 2.059e-02, eta: 13:29:18, time: 0.381, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9944, loss_cls: 0.5689, loss: 0.5689 +2025-06-24 14:52:50,697 - pyskl - INFO - Epoch [42][600/1281] lr: 2.057e-02, eta: 13:29:26, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9925, loss_cls: 0.6194, loss: 0.6194 +2025-06-24 14:53:18,248 - pyskl - INFO - Epoch [42][700/1281] lr: 2.056e-02, eta: 13:28:31, time: 0.275, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9950, loss_cls: 0.5889, loss: 0.5889 +2025-06-24 14:54:06,586 - pyskl - INFO - Epoch [42][800/1281] lr: 2.054e-02, eta: 13:28:31, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9969, loss_cls: 0.5303, loss: 0.5303 +2025-06-24 14:54:54,868 - pyskl - INFO - Epoch [42][900/1281] lr: 2.053e-02, eta: 13:28:31, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9950, loss_cls: 0.5524, loss: 0.5524 +2025-06-24 14:55:43,142 - pyskl - INFO - Epoch [42][1000/1281] lr: 2.051e-02, eta: 13:28:31, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9962, loss_cls: 0.5632, loss: 0.5632 +2025-06-24 14:56:31,501 - pyskl - INFO - Epoch [42][1100/1281] lr: 2.050e-02, eta: 13:28:30, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9956, loss_cls: 0.5392, loss: 0.5392 +2025-06-24 14:57:19,770 - pyskl - INFO - Epoch [42][1200/1281] lr: 2.048e-02, eta: 13:28:29, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9962, loss_cls: 0.6016, loss: 0.6016 +2025-06-24 14:57:59,423 - pyskl - INFO - Saving checkpoint at 42 epochs +2025-06-24 14:59:00,007 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 14:59:00,074 - pyskl - INFO - +top1_acc 0.8150 +top5_acc 0.9879 +2025-06-24 14:59:00,074 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 14:59:00,082 - pyskl - INFO - +mean_acc 0.7686 +2025-06-24 14:59:00,084 - pyskl - INFO - Epoch(val) [42][533] top1_acc: 0.8150, top5_acc: 0.9879, mean_class_accuracy: 0.7686 +2025-06-24 15:00:19,793 - pyskl - INFO - Epoch [43][100/1281] lr: 2.045e-02, eta: 13:28:08, time: 0.797, data_time: 0.199, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9912, loss_cls: 0.6362, loss: 0.6362 +2025-06-24 15:01:08,031 - pyskl - INFO - Epoch [43][200/1281] lr: 2.044e-02, eta: 13:28:06, time: 0.482, data_time: 0.000, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9969, loss_cls: 0.5016, loss: 0.5016 +2025-06-24 15:01:56,557 - pyskl - INFO - Epoch [43][300/1281] lr: 2.042e-02, eta: 13:28:05, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9975, loss_cls: 0.5702, loss: 0.5702 +2025-06-24 15:02:44,891 - pyskl - INFO - Epoch [43][400/1281] lr: 2.040e-02, eta: 13:28:04, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9962, loss_cls: 0.5789, loss: 0.5789 +2025-06-24 15:03:15,841 - pyskl - INFO - Epoch [43][500/1281] lr: 2.039e-02, eta: 13:27:18, time: 0.309, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9981, loss_cls: 0.5864, loss: 0.5864 +2025-06-24 15:04:00,267 - pyskl - INFO - Epoch [43][600/1281] lr: 2.037e-02, eta: 13:27:06, time: 0.444, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9962, loss_cls: 0.5472, loss: 0.5472 +2025-06-24 15:04:30,028 - pyskl - INFO - Epoch [43][700/1281] lr: 2.036e-02, eta: 13:26:18, time: 0.298, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9975, loss_cls: 0.5667, loss: 0.5667 +2025-06-24 15:05:18,961 - pyskl - INFO - Epoch [43][800/1281] lr: 2.034e-02, eta: 13:26:17, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8775, top5_acc: 0.9975, loss_cls: 0.6000, loss: 0.6000 +2025-06-24 15:06:07,964 - pyskl - INFO - Epoch [43][900/1281] lr: 2.033e-02, eta: 13:26:17, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8800, top5_acc: 0.9931, loss_cls: 0.5859, loss: 0.5859 +2025-06-24 15:06:57,028 - pyskl - INFO - Epoch [43][1000/1281] lr: 2.031e-02, eta: 13:26:16, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9988, loss_cls: 0.5057, loss: 0.5057 +2025-06-24 15:07:46,156 - pyskl - INFO - Epoch [43][1100/1281] lr: 2.029e-02, eta: 13:26:16, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9988, loss_cls: 0.5231, loss: 0.5231 +2025-06-24 15:08:35,356 - pyskl - INFO - Epoch [43][1200/1281] lr: 2.028e-02, eta: 13:26:15, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9950, loss_cls: 0.6262, loss: 0.6262 +2025-06-24 15:09:15,827 - pyskl - INFO - Saving checkpoint at 43 epochs +2025-06-24 15:10:15,616 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:10:15,694 - pyskl - INFO - +top1_acc 0.8540 +top5_acc 0.9920 +2025-06-24 15:10:15,694 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:10:15,705 - pyskl - INFO - +mean_acc 0.7864 +2025-06-24 15:10:15,708 - pyskl - INFO - Epoch(val) [43][533] top1_acc: 0.8540, top5_acc: 0.9920, mean_class_accuracy: 0.7864 +2025-06-24 15:11:35,475 - pyskl - INFO - Epoch [44][100/1281] lr: 2.025e-02, eta: 13:25:51, time: 0.798, data_time: 0.194, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9988, loss_cls: 0.5380, loss: 0.5380 +2025-06-24 15:12:24,613 - pyskl - INFO - Epoch [44][200/1281] lr: 2.023e-02, eta: 13:25:50, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9969, loss_cls: 0.5227, loss: 0.5227 +2025-06-24 15:13:13,409 - pyskl - INFO - Epoch [44][300/1281] lr: 2.022e-02, eta: 13:25:48, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9956, loss_cls: 0.5763, loss: 0.5763 +2025-06-24 15:14:02,715 - pyskl - INFO - Epoch [44][400/1281] lr: 2.020e-02, eta: 13:25:47, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9950, loss_cls: 0.6128, loss: 0.6128 +2025-06-24 15:14:30,209 - pyskl - INFO - Epoch [44][500/1281] lr: 2.018e-02, eta: 13:24:52, time: 0.275, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9969, loss_cls: 0.5600, loss: 0.5600 +2025-06-24 15:15:21,558 - pyskl - INFO - Epoch [44][600/1281] lr: 2.017e-02, eta: 13:24:56, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9981, loss_cls: 0.5640, loss: 0.5640 +2025-06-24 15:15:51,766 - pyskl - INFO - Epoch [44][700/1281] lr: 2.015e-02, eta: 13:24:08, time: 0.302, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9956, loss_cls: 0.5366, loss: 0.5366 +2025-06-24 15:16:40,829 - pyskl - INFO - Epoch [44][800/1281] lr: 2.014e-02, eta: 13:24:06, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9988, loss_cls: 0.5169, loss: 0.5169 +2025-06-24 15:17:29,789 - pyskl - INFO - Epoch [44][900/1281] lr: 2.012e-02, eta: 13:24:04, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9969, loss_cls: 0.6436, loss: 0.6436 +2025-06-24 15:18:18,485 - pyskl - INFO - Epoch [44][1000/1281] lr: 2.010e-02, eta: 13:24:00, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9969, loss_cls: 0.5784, loss: 0.5784 +2025-06-24 15:19:07,708 - pyskl - INFO - Epoch [44][1100/1281] lr: 2.009e-02, eta: 13:23:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9956, loss_cls: 0.6455, loss: 0.6455 +2025-06-24 15:19:56,872 - pyskl - INFO - Epoch [44][1200/1281] lr: 2.007e-02, eta: 13:23:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9981, loss_cls: 0.5942, loss: 0.5942 +2025-06-24 15:20:37,232 - pyskl - INFO - Saving checkpoint at 44 epochs +2025-06-24 15:21:36,573 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:21:36,640 - pyskl - INFO - +top1_acc 0.8388 +top5_acc 0.9891 +2025-06-24 15:21:36,640 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:21:36,648 - pyskl - INFO - +mean_acc 0.7798 +2025-06-24 15:21:36,650 - pyskl - INFO - Epoch(val) [44][533] top1_acc: 0.8388, top5_acc: 0.9891, mean_class_accuracy: 0.7798 +2025-06-24 15:22:56,702 - pyskl - INFO - Epoch [45][100/1281] lr: 2.004e-02, eta: 13:23:29, time: 0.800, data_time: 0.190, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9975, loss_cls: 0.5907, loss: 0.5907 +2025-06-24 15:23:45,557 - pyskl - INFO - Epoch [45][200/1281] lr: 2.003e-02, eta: 13:23:26, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9969, loss_cls: 0.5367, loss: 0.5367 +2025-06-24 15:24:34,569 - pyskl - INFO - Epoch [45][300/1281] lr: 2.001e-02, eta: 13:23:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9956, loss_cls: 0.5580, loss: 0.5580 +2025-06-24 15:25:23,325 - pyskl - INFO - Epoch [45][400/1281] lr: 1.999e-02, eta: 13:23:18, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9912, loss_cls: 0.6062, loss: 0.6062 +2025-06-24 15:25:51,363 - pyskl - INFO - Epoch [45][500/1281] lr: 1.998e-02, eta: 13:22:25, time: 0.280, data_time: 0.000, memory: 4083, top1_acc: 0.8906, top5_acc: 0.9931, loss_cls: 0.5785, loss: 0.5785 +2025-06-24 15:26:42,545 - pyskl - INFO - Epoch [45][600/1281] lr: 1.996e-02, eta: 13:22:26, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8862, top5_acc: 0.9981, loss_cls: 0.5682, loss: 0.5682 +2025-06-24 15:27:13,019 - pyskl - INFO - Epoch [45][700/1281] lr: 1.994e-02, eta: 13:21:38, time: 0.305, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9969, loss_cls: 0.5602, loss: 0.5602 +2025-06-24 15:28:02,137 - pyskl - INFO - Epoch [45][800/1281] lr: 1.993e-02, eta: 13:21:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9981, loss_cls: 0.5240, loss: 0.5240 +2025-06-24 15:28:50,765 - pyskl - INFO - Epoch [45][900/1281] lr: 1.991e-02, eta: 13:21:30, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9962, loss_cls: 0.5881, loss: 0.5881 +2025-06-24 15:29:39,708 - pyskl - INFO - Epoch [45][1000/1281] lr: 1.989e-02, eta: 13:21:25, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9975, loss_cls: 0.5155, loss: 0.5155 +2025-06-24 15:30:28,830 - pyskl - INFO - Epoch [45][1100/1281] lr: 1.988e-02, eta: 13:21:21, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8888, top5_acc: 0.9969, loss_cls: 0.5912, loss: 0.5912 +2025-06-24 15:31:17,931 - pyskl - INFO - Epoch [45][1200/1281] lr: 1.986e-02, eta: 13:21:17, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9962, loss_cls: 0.5664, loss: 0.5664 +2025-06-24 15:31:58,359 - pyskl - INFO - Saving checkpoint at 45 epochs +2025-06-24 15:32:57,207 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:32:57,265 - pyskl - INFO - +top1_acc 0.8565 +top5_acc 0.9899 +2025-06-24 15:32:57,266 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:32:57,272 - pyskl - INFO - +mean_acc 0.8143 +2025-06-24 15:32:57,274 - pyskl - INFO - Epoch(val) [45][533] top1_acc: 0.8565, top5_acc: 0.9899, mean_class_accuracy: 0.8143 +2025-06-24 15:34:17,598 - pyskl - INFO - Epoch [46][100/1281] lr: 1.983e-02, eta: 13:20:48, time: 0.803, data_time: 0.198, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9962, loss_cls: 0.5401, loss: 0.5401 +2025-06-24 15:35:06,632 - pyskl - INFO - Epoch [46][200/1281] lr: 1.981e-02, eta: 13:20:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9981, loss_cls: 0.4932, loss: 0.4932 +2025-06-24 15:35:55,815 - pyskl - INFO - Epoch [46][300/1281] lr: 1.980e-02, eta: 13:20:39, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9969, loss_cls: 0.5358, loss: 0.5358 +2025-06-24 15:36:45,119 - pyskl - INFO - Epoch [46][400/1281] lr: 1.978e-02, eta: 13:20:34, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9956, loss_cls: 0.5420, loss: 0.5420 +2025-06-24 15:37:12,411 - pyskl - INFO - Epoch [46][500/1281] lr: 1.976e-02, eta: 13:19:39, time: 0.273, data_time: 0.001, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9962, loss_cls: 0.4972, loss: 0.4972 +2025-06-24 15:38:03,423 - pyskl - INFO - Epoch [46][600/1281] lr: 1.975e-02, eta: 13:19:38, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9975, loss_cls: 0.5026, loss: 0.5026 +2025-06-24 15:38:33,690 - pyskl - INFO - Epoch [46][700/1281] lr: 1.973e-02, eta: 13:18:49, time: 0.303, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9969, loss_cls: 0.5388, loss: 0.5388 +2025-06-24 15:39:22,673 - pyskl - INFO - Epoch [46][800/1281] lr: 1.971e-02, eta: 13:18:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8756, top5_acc: 0.9962, loss_cls: 0.6379, loss: 0.6379 +2025-06-24 15:40:11,498 - pyskl - INFO - Epoch [46][900/1281] lr: 1.970e-02, eta: 13:18:37, time: 0.488, data_time: 0.001, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9956, loss_cls: 0.6046, loss: 0.6046 +2025-06-24 15:41:00,453 - pyskl - INFO - Epoch [46][1000/1281] lr: 1.968e-02, eta: 13:18:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9969, loss_cls: 0.5137, loss: 0.5137 +2025-06-24 15:41:49,814 - pyskl - INFO - Epoch [46][1100/1281] lr: 1.966e-02, eta: 13:18:26, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9944, loss_cls: 0.5715, loss: 0.5715 +2025-06-24 15:42:39,472 - pyskl - INFO - Epoch [46][1200/1281] lr: 1.965e-02, eta: 13:18:21, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.8788, top5_acc: 0.9950, loss_cls: 0.6236, loss: 0.6236 +2025-06-24 15:43:19,842 - pyskl - INFO - Saving checkpoint at 46 epochs +2025-06-24 15:44:18,979 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:44:19,035 - pyskl - INFO - +top1_acc 0.8373 +top5_acc 0.9904 +2025-06-24 15:44:19,035 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:44:19,042 - pyskl - INFO - +mean_acc 0.7884 +2025-06-24 15:44:19,043 - pyskl - INFO - Epoch(val) [46][533] top1_acc: 0.8373, top5_acc: 0.9904, mean_class_accuracy: 0.7884 +2025-06-24 15:45:39,503 - pyskl - INFO - Epoch [47][100/1281] lr: 1.962e-02, eta: 13:17:51, time: 0.805, data_time: 0.200, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9962, loss_cls: 0.5483, loss: 0.5483 +2025-06-24 15:46:28,540 - pyskl - INFO - Epoch [47][200/1281] lr: 1.960e-02, eta: 13:17:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9956, loss_cls: 0.5313, loss: 0.5313 +2025-06-24 15:47:17,568 - pyskl - INFO - Epoch [47][300/1281] lr: 1.958e-02, eta: 13:17:38, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9962, loss_cls: 0.5526, loss: 0.5526 +2025-06-24 15:48:07,347 - pyskl - INFO - Epoch [47][400/1281] lr: 1.957e-02, eta: 13:17:33, time: 0.498, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9950, loss_cls: 0.5369, loss: 0.5369 +2025-06-24 15:48:34,812 - pyskl - INFO - Epoch [47][500/1281] lr: 1.955e-02, eta: 13:16:37, time: 0.275, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9956, loss_cls: 0.5637, loss: 0.5637 +2025-06-24 15:49:25,296 - pyskl - INFO - Epoch [47][600/1281] lr: 1.953e-02, eta: 13:16:34, time: 0.505, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9962, loss_cls: 0.5570, loss: 0.5570 +2025-06-24 15:49:55,437 - pyskl - INFO - Epoch [47][700/1281] lr: 1.952e-02, eta: 13:15:44, time: 0.301, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9969, loss_cls: 0.5217, loss: 0.5217 +2025-06-24 15:50:44,542 - pyskl - INFO - Epoch [47][800/1281] lr: 1.950e-02, eta: 13:15:37, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9969, loss_cls: 0.5871, loss: 0.5871 +2025-06-24 15:51:33,555 - pyskl - INFO - Epoch [47][900/1281] lr: 1.948e-02, eta: 13:15:30, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9925, loss_cls: 0.5522, loss: 0.5522 +2025-06-24 15:52:22,580 - pyskl - INFO - Epoch [47][1000/1281] lr: 1.947e-02, eta: 13:15:23, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8938, top5_acc: 0.9969, loss_cls: 0.5662, loss: 0.5662 +2025-06-24 15:53:11,286 - pyskl - INFO - Epoch [47][1100/1281] lr: 1.945e-02, eta: 13:15:14, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8831, top5_acc: 0.9931, loss_cls: 0.6077, loss: 0.6077 +2025-06-24 15:54:00,427 - pyskl - INFO - Epoch [47][1200/1281] lr: 1.943e-02, eta: 13:15:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8844, top5_acc: 0.9944, loss_cls: 0.5982, loss: 0.5982 +2025-06-24 15:54:40,882 - pyskl - INFO - Saving checkpoint at 47 epochs +2025-06-24 15:55:40,361 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 15:55:40,416 - pyskl - INFO - +top1_acc 0.8622 +top5_acc 0.9896 +2025-06-24 15:55:40,417 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 15:55:40,423 - pyskl - INFO - +mean_acc 0.8194 +2025-06-24 15:55:40,425 - pyskl - INFO - Epoch(val) [47][533] top1_acc: 0.8622, top5_acc: 0.9896, mean_class_accuracy: 0.8194 +2025-06-24 15:56:58,933 - pyskl - INFO - Epoch [48][100/1281] lr: 1.940e-02, eta: 13:14:30, time: 0.785, data_time: 0.188, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9962, loss_cls: 0.5167, loss: 0.5167 +2025-06-24 15:57:48,285 - pyskl - INFO - Epoch [48][200/1281] lr: 1.938e-02, eta: 13:14:23, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9969, loss_cls: 0.4800, loss: 0.4800 +2025-06-24 15:58:37,635 - pyskl - INFO - Epoch [48][300/1281] lr: 1.937e-02, eta: 13:14:15, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9988, loss_cls: 0.4969, loss: 0.4969 +2025-06-24 15:59:26,925 - pyskl - INFO - Epoch [48][400/1281] lr: 1.935e-02, eta: 13:14:07, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9962, loss_cls: 0.5085, loss: 0.5085 +2025-06-24 15:59:55,829 - pyskl - INFO - Epoch [48][500/1281] lr: 1.933e-02, eta: 13:13:15, time: 0.289, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9950, loss_cls: 0.5443, loss: 0.5443 +2025-06-24 16:00:47,017 - pyskl - INFO - Epoch [48][600/1281] lr: 1.932e-02, eta: 13:13:11, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9975, loss_cls: 0.5238, loss: 0.5238 +2025-06-24 16:01:15,237 - pyskl - INFO - Epoch [48][700/1281] lr: 1.930e-02, eta: 13:12:18, time: 0.282, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9962, loss_cls: 0.5568, loss: 0.5568 +2025-06-24 16:02:03,979 - pyskl - INFO - Epoch [48][800/1281] lr: 1.928e-02, eta: 13:12:09, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9931, loss_cls: 0.5883, loss: 0.5883 +2025-06-24 16:02:52,955 - pyskl - INFO - Epoch [48][900/1281] lr: 1.926e-02, eta: 13:12:00, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9975, loss_cls: 0.5437, loss: 0.5437 +2025-06-24 16:03:41,770 - pyskl - INFO - Epoch [48][1000/1281] lr: 1.925e-02, eta: 13:11:50, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9956, loss_cls: 0.5398, loss: 0.5398 +2025-06-24 16:04:30,810 - pyskl - INFO - Epoch [48][1100/1281] lr: 1.923e-02, eta: 13:11:41, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9975, loss_cls: 0.5643, loss: 0.5643 +2025-06-24 16:05:19,820 - pyskl - INFO - Epoch [48][1200/1281] lr: 1.921e-02, eta: 13:11:32, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9938, loss_cls: 0.6197, loss: 0.6197 +2025-06-24 16:05:59,830 - pyskl - INFO - Saving checkpoint at 48 epochs +2025-06-24 16:06:59,377 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:06:59,448 - pyskl - INFO - +top1_acc 0.8613 +top5_acc 0.9905 +2025-06-24 16:06:59,448 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:06:59,457 - pyskl - INFO - +mean_acc 0.8192 +2025-06-24 16:06:59,459 - pyskl - INFO - Epoch(val) [48][533] top1_acc: 0.8613, top5_acc: 0.9905, mean_class_accuracy: 0.8192 +2025-06-24 16:08:19,809 - pyskl - INFO - Epoch [49][100/1281] lr: 1.918e-02, eta: 13:10:57, time: 0.803, data_time: 0.194, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9975, loss_cls: 0.5225, loss: 0.5225 +2025-06-24 16:09:08,858 - pyskl - INFO - Epoch [49][200/1281] lr: 1.916e-02, eta: 13:10:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8850, top5_acc: 0.9962, loss_cls: 0.6019, loss: 0.6019 +2025-06-24 16:09:57,869 - pyskl - INFO - Epoch [49][300/1281] lr: 1.915e-02, eta: 13:10:38, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9981, loss_cls: 0.4695, loss: 0.4695 +2025-06-24 16:10:46,855 - pyskl - INFO - Epoch [49][400/1281] lr: 1.913e-02, eta: 13:10:28, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9962, loss_cls: 0.4914, loss: 0.4914 +2025-06-24 16:11:15,821 - pyskl - INFO - Epoch [49][500/1281] lr: 1.911e-02, eta: 13:09:36, time: 0.290, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9956, loss_cls: 0.5184, loss: 0.5184 +2025-06-24 16:12:07,017 - pyskl - INFO - Epoch [49][600/1281] lr: 1.909e-02, eta: 13:09:31, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9988, loss_cls: 0.5325, loss: 0.5325 +2025-06-24 16:12:35,670 - pyskl - INFO - Epoch [49][700/1281] lr: 1.908e-02, eta: 13:08:38, time: 0.287, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9950, loss_cls: 0.5677, loss: 0.5677 +2025-06-24 16:13:24,516 - pyskl - INFO - Epoch [49][800/1281] lr: 1.906e-02, eta: 13:08:27, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9938, loss_cls: 0.5419, loss: 0.5419 +2025-06-24 16:14:13,613 - pyskl - INFO - Epoch [49][900/1281] lr: 1.904e-02, eta: 13:08:17, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8925, top5_acc: 0.9975, loss_cls: 0.5573, loss: 0.5573 +2025-06-24 16:15:03,068 - pyskl - INFO - Epoch [49][1000/1281] lr: 1.902e-02, eta: 13:08:08, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9962, loss_cls: 0.5898, loss: 0.5898 +2025-06-24 16:15:52,239 - pyskl - INFO - Epoch [49][1100/1281] lr: 1.901e-02, eta: 13:07:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9962, loss_cls: 0.5169, loss: 0.5169 +2025-06-24 16:16:41,272 - pyskl - INFO - Epoch [49][1200/1281] lr: 1.899e-02, eta: 13:07:47, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8919, top5_acc: 0.9981, loss_cls: 0.5540, loss: 0.5540 +2025-06-24 16:17:21,628 - pyskl - INFO - Saving checkpoint at 49 epochs +2025-06-24 16:18:21,899 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:18:21,958 - pyskl - INFO - +top1_acc 0.8657 +top5_acc 0.9924 +2025-06-24 16:18:21,958 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:18:21,966 - pyskl - INFO - +mean_acc 0.8200 +2025-06-24 16:18:21,973 - pyskl - INFO - Epoch(val) [49][533] top1_acc: 0.8657, top5_acc: 0.9924, mean_class_accuracy: 0.8200 +2025-06-24 16:19:42,060 - pyskl - INFO - Epoch [50][100/1281] lr: 1.896e-02, eta: 13:07:10, time: 0.801, data_time: 0.195, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9969, loss_cls: 0.4624, loss: 0.4624 +2025-06-24 16:20:31,040 - pyskl - INFO - Epoch [50][200/1281] lr: 1.894e-02, eta: 13:06:59, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9962, loss_cls: 0.5189, loss: 0.5189 +2025-06-24 16:21:20,109 - pyskl - INFO - Epoch [50][300/1281] lr: 1.892e-02, eta: 13:06:48, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9975, loss_cls: 0.5232, loss: 0.5232 +2025-06-24 16:22:09,212 - pyskl - INFO - Epoch [50][400/1281] lr: 1.891e-02, eta: 13:06:37, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9969, loss_cls: 0.5458, loss: 0.5458 +2025-06-24 16:22:36,478 - pyskl - INFO - Epoch [50][500/1281] lr: 1.889e-02, eta: 13:05:41, time: 0.273, data_time: 0.000, memory: 4083, top1_acc: 0.8912, top5_acc: 0.9988, loss_cls: 0.5133, loss: 0.5133 +2025-06-24 16:23:27,549 - pyskl - INFO - Epoch [50][600/1281] lr: 1.887e-02, eta: 13:05:34, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9950, loss_cls: 0.5621, loss: 0.5621 +2025-06-24 16:23:58,977 - pyskl - INFO - Epoch [50][700/1281] lr: 1.885e-02, eta: 13:04:47, time: 0.314, data_time: 0.000, memory: 4083, top1_acc: 0.8838, top5_acc: 0.9969, loss_cls: 0.5993, loss: 0.5993 +2025-06-24 16:24:48,114 - pyskl - INFO - Epoch [50][800/1281] lr: 1.884e-02, eta: 13:04:36, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8812, top5_acc: 0.9956, loss_cls: 0.6166, loss: 0.6166 +2025-06-24 16:25:36,657 - pyskl - INFO - Epoch [50][900/1281] lr: 1.882e-02, eta: 13:04:23, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.8962, top5_acc: 0.9975, loss_cls: 0.5363, loss: 0.5363 +2025-06-24 16:26:25,473 - pyskl - INFO - Epoch [50][1000/1281] lr: 1.880e-02, eta: 13:04:11, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9950, loss_cls: 0.5372, loss: 0.5372 +2025-06-24 16:27:14,133 - pyskl - INFO - Epoch [50][1100/1281] lr: 1.878e-02, eta: 13:03:59, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9944, loss_cls: 0.5965, loss: 0.5965 +2025-06-24 16:28:03,090 - pyskl - INFO - Epoch [50][1200/1281] lr: 1.876e-02, eta: 13:03:47, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9962, loss_cls: 0.6104, loss: 0.6104 +2025-06-24 16:28:43,441 - pyskl - INFO - Saving checkpoint at 50 epochs +2025-06-24 16:29:42,564 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:29:42,622 - pyskl - INFO - +top1_acc 0.8451 +top5_acc 0.9916 +2025-06-24 16:29:42,622 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:29:42,629 - pyskl - INFO - +mean_acc 0.7959 +2025-06-24 16:29:42,632 - pyskl - INFO - Epoch(val) [50][533] top1_acc: 0.8451, top5_acc: 0.9916, mean_class_accuracy: 0.7959 +2025-06-24 16:31:03,827 - pyskl - INFO - Epoch [51][100/1281] lr: 1.873e-02, eta: 13:03:10, time: 0.812, data_time: 0.201, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9975, loss_cls: 0.4982, loss: 0.4982 +2025-06-24 16:31:53,012 - pyskl - INFO - Epoch [51][200/1281] lr: 1.871e-02, eta: 13:02:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9962, loss_cls: 0.4744, loss: 0.4744 +2025-06-24 16:32:41,840 - pyskl - INFO - Epoch [51][300/1281] lr: 1.870e-02, eta: 13:02:45, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9969, loss_cls: 0.4959, loss: 0.4959 +2025-06-24 16:33:31,114 - pyskl - INFO - Epoch [51][400/1281] lr: 1.868e-02, eta: 13:02:33, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9944, loss_cls: 0.4951, loss: 0.4951 +2025-06-24 16:33:58,410 - pyskl - INFO - Epoch [51][500/1281] lr: 1.866e-02, eta: 13:01:38, time: 0.273, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9962, loss_cls: 0.5399, loss: 0.5399 +2025-06-24 16:34:48,431 - pyskl - INFO - Epoch [51][600/1281] lr: 1.864e-02, eta: 13:01:27, time: 0.500, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9962, loss_cls: 0.5201, loss: 0.5201 +2025-06-24 16:35:20,187 - pyskl - INFO - Epoch [51][700/1281] lr: 1.863e-02, eta: 13:00:40, time: 0.318, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9962, loss_cls: 0.4796, loss: 0.4796 +2025-06-24 16:36:09,453 - pyskl - INFO - Epoch [51][800/1281] lr: 1.861e-02, eta: 13:00:28, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9969, loss_cls: 0.4827, loss: 0.4827 +2025-06-24 16:36:58,423 - pyskl - INFO - Epoch [51][900/1281] lr: 1.859e-02, eta: 13:00:15, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9962, loss_cls: 0.5352, loss: 0.5352 +2025-06-24 16:37:47,247 - pyskl - INFO - Epoch [51][1000/1281] lr: 1.857e-02, eta: 13:00:02, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9969, loss_cls: 0.4780, loss: 0.4780 +2025-06-24 16:38:36,107 - pyskl - INFO - Epoch [51][1100/1281] lr: 1.855e-02, eta: 12:59:49, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9988, loss_cls: 0.5551, loss: 0.5551 +2025-06-24 16:39:24,878 - pyskl - INFO - Epoch [51][1200/1281] lr: 1.854e-02, eta: 12:59:35, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9950, loss_cls: 0.5959, loss: 0.5959 +2025-06-24 16:40:05,437 - pyskl - INFO - Saving checkpoint at 51 epochs +2025-06-24 16:41:04,907 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:41:04,975 - pyskl - INFO - +top1_acc 0.8661 +top5_acc 0.9914 +2025-06-24 16:41:04,975 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:41:04,984 - pyskl - INFO - +mean_acc 0.8130 +2025-06-24 16:41:04,987 - pyskl - INFO - Epoch(val) [51][533] top1_acc: 0.8661, top5_acc: 0.9914, mean_class_accuracy: 0.8130 +2025-06-24 16:42:25,635 - pyskl - INFO - Epoch [52][100/1281] lr: 1.850e-02, eta: 12:58:55, time: 0.806, data_time: 0.200, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9956, loss_cls: 0.4953, loss: 0.4953 +2025-06-24 16:43:14,795 - pyskl - INFO - Epoch [52][200/1281] lr: 1.849e-02, eta: 12:58:42, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9988, loss_cls: 0.4640, loss: 0.4640 +2025-06-24 16:44:04,073 - pyskl - INFO - Epoch [52][300/1281] lr: 1.847e-02, eta: 12:58:29, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.8956, top5_acc: 0.9969, loss_cls: 0.5348, loss: 0.5348 +2025-06-24 16:44:52,912 - pyskl - INFO - Epoch [52][400/1281] lr: 1.845e-02, eta: 12:58:15, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9988, loss_cls: 0.4838, loss: 0.4838 +2025-06-24 16:45:21,898 - pyskl - INFO - Epoch [52][500/1281] lr: 1.843e-02, eta: 12:57:23, time: 0.290, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9962, loss_cls: 0.5105, loss: 0.5105 +2025-06-24 16:46:09,516 - pyskl - INFO - Epoch [52][600/1281] lr: 1.841e-02, eta: 12:57:06, time: 0.476, data_time: 0.000, memory: 4083, top1_acc: 0.8819, top5_acc: 0.9969, loss_cls: 0.6004, loss: 0.6004 +2025-06-24 16:46:40,944 - pyskl - INFO - Epoch [52][700/1281] lr: 1.840e-02, eta: 12:56:19, time: 0.314, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9950, loss_cls: 0.5345, loss: 0.5345 +2025-06-24 16:47:30,019 - pyskl - INFO - Epoch [52][800/1281] lr: 1.838e-02, eta: 12:56:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9962, loss_cls: 0.5352, loss: 0.5352 +2025-06-24 16:48:19,063 - pyskl - INFO - Epoch [52][900/1281] lr: 1.836e-02, eta: 12:55:51, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8881, top5_acc: 0.9950, loss_cls: 0.5664, loss: 0.5664 +2025-06-24 16:49:08,171 - pyskl - INFO - Epoch [52][1000/1281] lr: 1.834e-02, eta: 12:55:37, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8931, top5_acc: 0.9938, loss_cls: 0.5640, loss: 0.5640 +2025-06-24 16:49:57,200 - pyskl - INFO - Epoch [52][1100/1281] lr: 1.832e-02, eta: 12:55:23, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9962, loss_cls: 0.5322, loss: 0.5322 +2025-06-24 16:50:46,059 - pyskl - INFO - Epoch [52][1200/1281] lr: 1.831e-02, eta: 12:55:08, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8725, top5_acc: 0.9938, loss_cls: 0.5835, loss: 0.5835 +2025-06-24 16:51:26,451 - pyskl - INFO - Saving checkpoint at 52 epochs +2025-06-24 16:52:25,771 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 16:52:25,826 - pyskl - INFO - +top1_acc 0.8628 +top5_acc 0.9919 +2025-06-24 16:52:25,826 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 16:52:25,833 - pyskl - INFO - +mean_acc 0.8289 +2025-06-24 16:52:25,835 - pyskl - INFO - Epoch(val) [52][533] top1_acc: 0.8628, top5_acc: 0.9919, mean_class_accuracy: 0.8289 +2025-06-24 16:53:46,930 - pyskl - INFO - Epoch [53][100/1281] lr: 1.827e-02, eta: 12:54:28, time: 0.811, data_time: 0.193, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9962, loss_cls: 0.5376, loss: 0.5376 +2025-06-24 16:54:36,462 - pyskl - INFO - Epoch [53][200/1281] lr: 1.826e-02, eta: 12:54:14, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9019, top5_acc: 0.9962, loss_cls: 0.5125, loss: 0.5125 +2025-06-24 16:55:25,825 - pyskl - INFO - Epoch [53][300/1281] lr: 1.824e-02, eta: 12:54:00, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8894, top5_acc: 0.9950, loss_cls: 0.5378, loss: 0.5378 +2025-06-24 16:56:15,121 - pyskl - INFO - Epoch [53][400/1281] lr: 1.822e-02, eta: 12:53:46, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9969, loss_cls: 0.4978, loss: 0.4978 +2025-06-24 16:56:43,150 - pyskl - INFO - Epoch [53][500/1281] lr: 1.820e-02, eta: 12:52:52, time: 0.280, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9962, loss_cls: 0.4834, loss: 0.4834 +2025-06-24 16:57:32,574 - pyskl - INFO - Epoch [53][600/1281] lr: 1.818e-02, eta: 12:52:38, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9969, loss_cls: 0.4693, loss: 0.4693 +2025-06-24 16:58:04,460 - pyskl - INFO - Epoch [53][700/1281] lr: 1.816e-02, eta: 12:51:51, time: 0.319, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9981, loss_cls: 0.5167, loss: 0.5167 +2025-06-24 16:58:53,937 - pyskl - INFO - Epoch [53][800/1281] lr: 1.815e-02, eta: 12:51:37, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9969, loss_cls: 0.4883, loss: 0.4883 +2025-06-24 16:59:42,976 - pyskl - INFO - Epoch [53][900/1281] lr: 1.813e-02, eta: 12:51:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8781, top5_acc: 0.9975, loss_cls: 0.5987, loss: 0.5987 +2025-06-24 17:00:31,868 - pyskl - INFO - Epoch [53][1000/1281] lr: 1.811e-02, eta: 12:51:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9956, loss_cls: 0.5217, loss: 0.5217 +2025-06-24 17:01:20,947 - pyskl - INFO - Epoch [53][1100/1281] lr: 1.809e-02, eta: 12:50:51, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9981, loss_cls: 0.4956, loss: 0.4956 +2025-06-24 17:02:09,800 - pyskl - INFO - Epoch [53][1200/1281] lr: 1.807e-02, eta: 12:50:35, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9975, loss_cls: 0.5022, loss: 0.5022 +2025-06-24 17:02:49,844 - pyskl - INFO - Saving checkpoint at 53 epochs +2025-06-24 17:03:49,885 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:03:49,956 - pyskl - INFO - +top1_acc 0.8750 +top5_acc 0.9914 +2025-06-24 17:03:49,956 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:03:49,963 - pyskl - INFO - +mean_acc 0.8313 +2025-06-24 17:03:49,967 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_39.pth was removed +2025-06-24 17:03:50,155 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_53.pth. +2025-06-24 17:03:50,155 - pyskl - INFO - Best top1_acc is 0.8750 at 53 epoch. +2025-06-24 17:03:50,158 - pyskl - INFO - Epoch(val) [53][533] top1_acc: 0.8750, top5_acc: 0.9914, mean_class_accuracy: 0.8313 +2025-06-24 17:05:10,337 - pyskl - INFO - Epoch [54][100/1281] lr: 1.804e-02, eta: 12:49:51, time: 0.802, data_time: 0.193, memory: 4083, top1_acc: 0.8900, top5_acc: 0.9962, loss_cls: 0.5773, loss: 0.5773 +2025-06-24 17:05:59,339 - pyskl - INFO - Epoch [54][200/1281] lr: 1.802e-02, eta: 12:49:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9950, loss_cls: 0.4855, loss: 0.4855 +2025-06-24 17:06:48,814 - pyskl - INFO - Epoch [54][300/1281] lr: 1.800e-02, eta: 12:49:21, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9962, loss_cls: 0.4887, loss: 0.4887 +2025-06-24 17:07:38,002 - pyskl - INFO - Epoch [54][400/1281] lr: 1.798e-02, eta: 12:49:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9969, loss_cls: 0.4770, loss: 0.4770 +2025-06-24 17:08:08,562 - pyskl - INFO - Epoch [54][500/1281] lr: 1.797e-02, eta: 12:48:16, time: 0.306, data_time: 0.001, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9962, loss_cls: 0.4575, loss: 0.4575 +2025-06-24 17:08:54,012 - pyskl - INFO - Epoch [54][600/1281] lr: 1.795e-02, eta: 12:47:53, time: 0.454, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9975, loss_cls: 0.4843, loss: 0.4843 +2025-06-24 17:09:28,627 - pyskl - INFO - Epoch [54][700/1281] lr: 1.793e-02, eta: 12:47:11, time: 0.346, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9981, loss_cls: 0.5010, loss: 0.5010 +2025-06-24 17:10:17,820 - pyskl - INFO - Epoch [54][800/1281] lr: 1.791e-02, eta: 12:46:55, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9944, loss_cls: 0.4958, loss: 0.4958 +2025-06-24 17:11:06,901 - pyskl - INFO - Epoch [54][900/1281] lr: 1.789e-02, eta: 12:46:39, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9988, loss_cls: 0.4961, loss: 0.4961 +2025-06-24 17:11:55,911 - pyskl - INFO - Epoch [54][1000/1281] lr: 1.787e-02, eta: 12:46:23, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9988, loss_cls: 0.5080, loss: 0.5080 +2025-06-24 17:12:45,217 - pyskl - INFO - Epoch [54][1100/1281] lr: 1.786e-02, eta: 12:46:07, time: 0.493, data_time: 0.001, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9956, loss_cls: 0.5187, loss: 0.5187 +2025-06-24 17:13:34,019 - pyskl - INFO - Epoch [54][1200/1281] lr: 1.784e-02, eta: 12:45:50, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9975, loss_cls: 0.4404, loss: 0.4404 +2025-06-24 17:14:14,227 - pyskl - INFO - Saving checkpoint at 54 epochs +2025-06-24 17:15:14,110 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:15:14,177 - pyskl - INFO - +top1_acc 0.8532 +top5_acc 0.9903 +2025-06-24 17:15:14,177 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:15:14,185 - pyskl - INFO - +mean_acc 0.7894 +2025-06-24 17:15:14,188 - pyskl - INFO - Epoch(val) [54][533] top1_acc: 0.8532, top5_acc: 0.9903, mean_class_accuracy: 0.7894 +2025-06-24 17:16:34,702 - pyskl - INFO - Epoch [55][100/1281] lr: 1.780e-02, eta: 12:45:06, time: 0.805, data_time: 0.195, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9931, loss_cls: 0.5563, loss: 0.5563 +2025-06-24 17:17:23,826 - pyskl - INFO - Epoch [55][200/1281] lr: 1.779e-02, eta: 12:44:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9962, loss_cls: 0.5145, loss: 0.5145 +2025-06-24 17:18:12,962 - pyskl - INFO - Epoch [55][300/1281] lr: 1.777e-02, eta: 12:44:32, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9975, loss_cls: 0.4679, loss: 0.4679 +2025-06-24 17:19:02,099 - pyskl - INFO - Epoch [55][400/1281] lr: 1.775e-02, eta: 12:44:16, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9975, loss_cls: 0.4796, loss: 0.4796 +2025-06-24 17:19:34,467 - pyskl - INFO - Epoch [55][500/1281] lr: 1.773e-02, eta: 12:43:29, time: 0.324, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9975, loss_cls: 0.5041, loss: 0.5041 +2025-06-24 17:20:15,774 - pyskl - INFO - Epoch [55][600/1281] lr: 1.771e-02, eta: 12:42:59, time: 0.413, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9981, loss_cls: 0.5231, loss: 0.5231 +2025-06-24 17:20:52,221 - pyskl - INFO - Epoch [55][700/1281] lr: 1.769e-02, eta: 12:42:20, time: 0.364, data_time: 0.000, memory: 4083, top1_acc: 0.8944, top5_acc: 0.9950, loss_cls: 0.5309, loss: 0.5309 +2025-06-24 17:21:41,436 - pyskl - INFO - Epoch [55][800/1281] lr: 1.767e-02, eta: 12:42:03, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9944, loss_cls: 0.5479, loss: 0.5479 +2025-06-24 17:22:30,436 - pyskl - INFO - Epoch [55][900/1281] lr: 1.766e-02, eta: 12:41:46, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9981, loss_cls: 0.5320, loss: 0.5320 +2025-06-24 17:23:19,880 - pyskl - INFO - Epoch [55][1000/1281] lr: 1.764e-02, eta: 12:41:29, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9975, loss_cls: 0.4689, loss: 0.4689 +2025-06-24 17:24:09,532 - pyskl - INFO - Epoch [55][1100/1281] lr: 1.762e-02, eta: 12:41:13, time: 0.497, data_time: 0.000, memory: 4083, top1_acc: 0.8950, top5_acc: 0.9994, loss_cls: 0.5091, loss: 0.5091 +2025-06-24 17:24:58,901 - pyskl - INFO - Epoch [55][1200/1281] lr: 1.760e-02, eta: 12:40:56, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8869, top5_acc: 0.9956, loss_cls: 0.5849, loss: 0.5849 +2025-06-24 17:25:38,842 - pyskl - INFO - Saving checkpoint at 55 epochs +2025-06-24 17:26:38,171 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:26:38,228 - pyskl - INFO - +top1_acc 0.8653 +top5_acc 0.9914 +2025-06-24 17:26:38,228 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:26:38,235 - pyskl - INFO - +mean_acc 0.8143 +2025-06-24 17:26:38,237 - pyskl - INFO - Epoch(val) [55][533] top1_acc: 0.8653, top5_acc: 0.9914, mean_class_accuracy: 0.8143 +2025-06-24 17:27:58,201 - pyskl - INFO - Epoch [56][100/1281] lr: 1.757e-02, eta: 12:40:09, time: 0.800, data_time: 0.186, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9981, loss_cls: 0.4445, loss: 0.4445 +2025-06-24 17:28:47,068 - pyskl - INFO - Epoch [56][200/1281] lr: 1.755e-02, eta: 12:39:51, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9938, loss_cls: 0.5338, loss: 0.5338 +2025-06-24 17:29:35,927 - pyskl - INFO - Epoch [56][300/1281] lr: 1.753e-02, eta: 12:39:33, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9975, loss_cls: 0.4823, loss: 0.4823 +2025-06-24 17:30:23,682 - pyskl - INFO - Epoch [56][400/1281] lr: 1.751e-02, eta: 12:39:13, time: 0.478, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9981, loss_cls: 0.5101, loss: 0.5101 +2025-06-24 17:30:57,631 - pyskl - INFO - Epoch [56][500/1281] lr: 1.749e-02, eta: 12:38:29, time: 0.339, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9950, loss_cls: 0.4882, loss: 0.4882 +2025-06-24 17:31:37,351 - pyskl - INFO - Epoch [56][600/1281] lr: 1.747e-02, eta: 12:37:55, time: 0.397, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9969, loss_cls: 0.4524, loss: 0.4524 +2025-06-24 17:32:13,603 - pyskl - INFO - Epoch [56][700/1281] lr: 1.745e-02, eta: 12:37:16, time: 0.363, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9962, loss_cls: 0.4985, loss: 0.4985 +2025-06-24 17:33:02,931 - pyskl - INFO - Epoch [56][800/1281] lr: 1.743e-02, eta: 12:36:58, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 1.0000, loss_cls: 0.4919, loss: 0.4919 +2025-06-24 17:33:51,646 - pyskl - INFO - Epoch [56][900/1281] lr: 1.742e-02, eta: 12:36:39, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.8981, top5_acc: 0.9962, loss_cls: 0.5326, loss: 0.5326 +2025-06-24 17:34:40,633 - pyskl - INFO - Epoch [56][1000/1281] lr: 1.740e-02, eta: 12:36:21, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9969, loss_cls: 0.4988, loss: 0.4988 +2025-06-24 17:35:29,457 - pyskl - INFO - Epoch [56][1100/1281] lr: 1.738e-02, eta: 12:36:02, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9962, loss_cls: 0.5194, loss: 0.5194 +2025-06-24 17:36:18,750 - pyskl - INFO - Epoch [56][1200/1281] lr: 1.736e-02, eta: 12:35:44, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9969, loss_cls: 0.5201, loss: 0.5201 +2025-06-24 17:36:59,185 - pyskl - INFO - Saving checkpoint at 56 epochs +2025-06-24 17:37:57,803 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:37:57,891 - pyskl - INFO - +top1_acc 0.8566 +top5_acc 0.9899 +2025-06-24 17:37:57,891 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:37:57,898 - pyskl - INFO - +mean_acc 0.8088 +2025-06-24 17:37:57,900 - pyskl - INFO - Epoch(val) [56][533] top1_acc: 0.8566, top5_acc: 0.9899, mean_class_accuracy: 0.8088 +2025-06-24 17:39:17,482 - pyskl - INFO - Epoch [57][100/1281] lr: 1.733e-02, eta: 12:34:55, time: 0.796, data_time: 0.189, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9981, loss_cls: 0.4973, loss: 0.4973 +2025-06-24 17:40:06,195 - pyskl - INFO - Epoch [57][200/1281] lr: 1.731e-02, eta: 12:34:36, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9981, loss_cls: 0.4891, loss: 0.4891 +2025-06-24 17:40:55,269 - pyskl - INFO - Epoch [57][300/1281] lr: 1.729e-02, eta: 12:34:18, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9994, loss_cls: 0.4091, loss: 0.4091 +2025-06-24 17:41:44,359 - pyskl - INFO - Epoch [57][400/1281] lr: 1.727e-02, eta: 12:33:59, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9187, top5_acc: 0.9981, loss_cls: 0.4464, loss: 0.4464 +2025-06-24 17:42:15,957 - pyskl - INFO - Epoch [57][500/1281] lr: 1.725e-02, eta: 12:33:11, time: 0.316, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9969, loss_cls: 0.4484, loss: 0.4484 +2025-06-24 17:42:58,377 - pyskl - INFO - Epoch [57][600/1281] lr: 1.723e-02, eta: 12:32:41, time: 0.424, data_time: 0.000, memory: 4083, top1_acc: 0.8994, top5_acc: 0.9994, loss_cls: 0.5013, loss: 0.5013 +2025-06-24 17:43:33,135 - pyskl - INFO - Epoch [57][700/1281] lr: 1.721e-02, eta: 12:31:59, time: 0.348, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9962, loss_cls: 0.5247, loss: 0.5247 +2025-06-24 17:44:22,050 - pyskl - INFO - Epoch [57][800/1281] lr: 1.719e-02, eta: 12:31:39, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9956, loss_cls: 0.5164, loss: 0.5164 +2025-06-24 17:45:11,191 - pyskl - INFO - Epoch [57][900/1281] lr: 1.717e-02, eta: 12:31:21, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9956, loss_cls: 0.5207, loss: 0.5207 +2025-06-24 17:46:00,194 - pyskl - INFO - Epoch [57][1000/1281] lr: 1.716e-02, eta: 12:31:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9981, loss_cls: 0.4260, loss: 0.4260 +2025-06-24 17:46:49,173 - pyskl - INFO - Epoch [57][1100/1281] lr: 1.714e-02, eta: 12:30:42, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9975, loss_cls: 0.4719, loss: 0.4719 +2025-06-24 17:47:38,527 - pyskl - INFO - Epoch [57][1200/1281] lr: 1.712e-02, eta: 12:30:23, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.8825, top5_acc: 0.9956, loss_cls: 0.5667, loss: 0.5667 +2025-06-24 17:48:18,955 - pyskl - INFO - Saving checkpoint at 57 epochs +2025-06-24 17:49:17,800 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 17:49:17,857 - pyskl - INFO - +top1_acc 0.8803 +top5_acc 0.9898 +2025-06-24 17:49:17,857 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 17:49:17,865 - pyskl - INFO - +mean_acc 0.8337 +2025-06-24 17:49:17,869 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_53.pth was removed +2025-06-24 17:49:18,064 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_57.pth. +2025-06-24 17:49:18,064 - pyskl - INFO - Best top1_acc is 0.8803 at 57 epoch. +2025-06-24 17:49:18,067 - pyskl - INFO - Epoch(val) [57][533] top1_acc: 0.8803, top5_acc: 0.9898, mean_class_accuracy: 0.8337 +2025-06-24 17:50:39,242 - pyskl - INFO - Epoch [58][100/1281] lr: 1.708e-02, eta: 12:29:36, time: 0.812, data_time: 0.196, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9981, loss_cls: 0.4115, loss: 0.4115 +2025-06-24 17:51:28,513 - pyskl - INFO - Epoch [58][200/1281] lr: 1.706e-02, eta: 12:29:17, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9981, loss_cls: 0.4340, loss: 0.4340 +2025-06-24 17:52:17,702 - pyskl - INFO - Epoch [58][300/1281] lr: 1.704e-02, eta: 12:28:57, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9969, loss_cls: 0.4588, loss: 0.4588 +2025-06-24 17:53:06,352 - pyskl - INFO - Epoch [58][400/1281] lr: 1.703e-02, eta: 12:28:37, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9981, loss_cls: 0.4258, loss: 0.4258 +2025-06-24 17:53:38,866 - pyskl - INFO - Epoch [58][500/1281] lr: 1.701e-02, eta: 12:27:51, time: 0.325, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9975, loss_cls: 0.4523, loss: 0.4523 +2025-06-24 17:54:20,205 - pyskl - INFO - Epoch [58][600/1281] lr: 1.699e-02, eta: 12:27:18, time: 0.413, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9988, loss_cls: 0.4939, loss: 0.4939 +2025-06-24 17:54:55,739 - pyskl - INFO - Epoch [58][700/1281] lr: 1.697e-02, eta: 12:26:37, time: 0.355, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9975, loss_cls: 0.4649, loss: 0.4649 +2025-06-24 17:55:44,993 - pyskl - INFO - Epoch [58][800/1281] lr: 1.695e-02, eta: 12:26:17, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9975, loss_cls: 0.4741, loss: 0.4741 +2025-06-24 17:56:34,004 - pyskl - INFO - Epoch [58][900/1281] lr: 1.693e-02, eta: 12:25:57, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9950, loss_cls: 0.5117, loss: 0.5117 +2025-06-24 17:57:23,129 - pyskl - INFO - Epoch [58][1000/1281] lr: 1.691e-02, eta: 12:25:38, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9988, loss_cls: 0.5177, loss: 0.5177 +2025-06-24 17:58:12,338 - pyskl - INFO - Epoch [58][1100/1281] lr: 1.689e-02, eta: 12:25:18, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9956, loss_cls: 0.5060, loss: 0.5060 +2025-06-24 17:59:01,745 - pyskl - INFO - Epoch [58][1200/1281] lr: 1.687e-02, eta: 12:24:58, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9956, loss_cls: 0.5205, loss: 0.5205 +2025-06-24 17:59:42,192 - pyskl - INFO - Saving checkpoint at 58 epochs +2025-06-24 18:00:41,293 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:00:41,350 - pyskl - INFO - +top1_acc 0.8777 +top5_acc 0.9926 +2025-06-24 18:00:41,350 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:00:41,357 - pyskl - INFO - +mean_acc 0.8381 +2025-06-24 18:00:41,359 - pyskl - INFO - Epoch(val) [58][533] top1_acc: 0.8777, top5_acc: 0.9926, mean_class_accuracy: 0.8381 +2025-06-24 18:01:59,540 - pyskl - INFO - Epoch [59][100/1281] lr: 1.684e-02, eta: 12:24:05, time: 0.782, data_time: 0.194, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9962, loss_cls: 0.4529, loss: 0.4529 +2025-06-24 18:02:48,519 - pyskl - INFO - Epoch [59][200/1281] lr: 1.682e-02, eta: 12:23:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9956, loss_cls: 0.5018, loss: 0.5018 +2025-06-24 18:03:37,734 - pyskl - INFO - Epoch [59][300/1281] lr: 1.680e-02, eta: 12:23:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9956, loss_cls: 0.4666, loss: 0.4666 +2025-06-24 18:04:26,855 - pyskl - INFO - Epoch [59][400/1281] lr: 1.678e-02, eta: 12:23:04, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9981, loss_cls: 0.4391, loss: 0.4391 +2025-06-24 18:04:56,704 - pyskl - INFO - Epoch [59][500/1281] lr: 1.676e-02, eta: 12:22:13, time: 0.298, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9988, loss_cls: 0.4268, loss: 0.4268 +2025-06-24 18:05:41,696 - pyskl - INFO - Epoch [59][600/1281] lr: 1.674e-02, eta: 12:21:46, time: 0.450, data_time: 0.001, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9988, loss_cls: 0.4908, loss: 0.4908 +2025-06-24 18:06:15,416 - pyskl - INFO - Epoch [59][700/1281] lr: 1.672e-02, eta: 12:21:02, time: 0.337, data_time: 0.000, memory: 4083, top1_acc: 0.9087, top5_acc: 0.9969, loss_cls: 0.4891, loss: 0.4891 +2025-06-24 18:07:04,546 - pyskl - INFO - Epoch [59][800/1281] lr: 1.670e-02, eta: 12:20:41, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9962, loss_cls: 0.4944, loss: 0.4944 +2025-06-24 18:07:53,720 - pyskl - INFO - Epoch [59][900/1281] lr: 1.668e-02, eta: 12:20:20, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9956, loss_cls: 0.5086, loss: 0.5086 +2025-06-24 18:08:42,812 - pyskl - INFO - Epoch [59][1000/1281] lr: 1.667e-02, eta: 12:20:00, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9956, loss_cls: 0.5102, loss: 0.5102 +2025-06-24 18:09:31,845 - pyskl - INFO - Epoch [59][1100/1281] lr: 1.665e-02, eta: 12:19:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9994, loss_cls: 0.5390, loss: 0.5390 +2025-06-24 18:10:21,162 - pyskl - INFO - Epoch [59][1200/1281] lr: 1.663e-02, eta: 12:19:18, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9969, loss_cls: 0.4364, loss: 0.4364 +2025-06-24 18:11:01,484 - pyskl - INFO - Saving checkpoint at 59 epochs +2025-06-24 18:12:00,625 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:12:00,687 - pyskl - INFO - +top1_acc 0.8811 +top5_acc 0.9913 +2025-06-24 18:12:00,687 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:12:00,694 - pyskl - INFO - +mean_acc 0.8318 +2025-06-24 18:12:00,698 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_57.pth was removed +2025-06-24 18:12:00,868 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_59.pth. +2025-06-24 18:12:00,868 - pyskl - INFO - Best top1_acc is 0.8811 at 59 epoch. +2025-06-24 18:12:00,871 - pyskl - INFO - Epoch(val) [59][533] top1_acc: 0.8811, top5_acc: 0.9913, mean_class_accuracy: 0.8318 +2025-06-24 18:13:21,612 - pyskl - INFO - Epoch [60][100/1281] lr: 1.659e-02, eta: 12:18:28, time: 0.807, data_time: 0.194, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9994, loss_cls: 0.3914, loss: 0.3914 +2025-06-24 18:14:10,386 - pyskl - INFO - Epoch [60][200/1281] lr: 1.657e-02, eta: 12:18:06, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9969, loss_cls: 0.4203, loss: 0.4203 +2025-06-24 18:14:59,421 - pyskl - INFO - Epoch [60][300/1281] lr: 1.655e-02, eta: 12:17:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9981, loss_cls: 0.4859, loss: 0.4859 +2025-06-24 18:15:48,555 - pyskl - INFO - Epoch [60][400/1281] lr: 1.653e-02, eta: 12:17:24, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9988, loss_cls: 0.4896, loss: 0.4896 +2025-06-24 18:16:20,647 - pyskl - INFO - Epoch [60][500/1281] lr: 1.651e-02, eta: 12:16:37, time: 0.321, data_time: 0.001, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9969, loss_cls: 0.4880, loss: 0.4880 +2025-06-24 18:17:02,397 - pyskl - INFO - Epoch [60][600/1281] lr: 1.650e-02, eta: 12:16:04, time: 0.417, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9969, loss_cls: 0.4343, loss: 0.4343 +2025-06-24 18:17:38,444 - pyskl - INFO - Epoch [60][700/1281] lr: 1.648e-02, eta: 12:15:23, time: 0.360, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9988, loss_cls: 0.4831, loss: 0.4831 +2025-06-24 18:18:27,617 - pyskl - INFO - Epoch [60][800/1281] lr: 1.646e-02, eta: 12:15:02, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9981, loss_cls: 0.4414, loss: 0.4414 +2025-06-24 18:19:16,694 - pyskl - INFO - Epoch [60][900/1281] lr: 1.644e-02, eta: 12:14:40, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9225, top5_acc: 0.9975, loss_cls: 0.4492, loss: 0.4492 +2025-06-24 18:20:06,070 - pyskl - INFO - Epoch [60][1000/1281] lr: 1.642e-02, eta: 12:14:19, time: 0.494, data_time: 0.001, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9975, loss_cls: 0.4500, loss: 0.4500 +2025-06-24 18:20:54,977 - pyskl - INFO - Epoch [60][1100/1281] lr: 1.640e-02, eta: 12:13:57, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9006, top5_acc: 0.9944, loss_cls: 0.5225, loss: 0.5225 +2025-06-24 18:21:44,184 - pyskl - INFO - Epoch [60][1200/1281] lr: 1.638e-02, eta: 12:13:36, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9969, loss_cls: 0.4957, loss: 0.4957 +2025-06-24 18:22:24,506 - pyskl - INFO - Saving checkpoint at 60 epochs +2025-06-24 18:23:24,632 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:23:24,688 - pyskl - INFO - +top1_acc 0.8541 +top5_acc 0.9860 +2025-06-24 18:23:24,688 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:23:24,696 - pyskl - INFO - +mean_acc 0.8227 +2025-06-24 18:23:24,698 - pyskl - INFO - Epoch(val) [60][533] top1_acc: 0.8541, top5_acc: 0.9860, mean_class_accuracy: 0.8227 +2025-06-24 18:24:44,729 - pyskl - INFO - Epoch [61][100/1281] lr: 1.634e-02, eta: 12:12:43, time: 0.800, data_time: 0.196, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9981, loss_cls: 0.4693, loss: 0.4693 +2025-06-24 18:25:34,095 - pyskl - INFO - Epoch [61][200/1281] lr: 1.632e-02, eta: 12:12:22, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9975, loss_cls: 0.4159, loss: 0.4159 +2025-06-24 18:26:23,469 - pyskl - INFO - Epoch [61][300/1281] lr: 1.630e-02, eta: 12:12:00, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9969, loss_cls: 0.4543, loss: 0.4543 +2025-06-24 18:27:10,516 - pyskl - INFO - Epoch [61][400/1281] lr: 1.629e-02, eta: 12:11:35, time: 0.470, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9994, loss_cls: 0.4981, loss: 0.4981 +2025-06-24 18:27:46,693 - pyskl - INFO - Epoch [61][500/1281] lr: 1.627e-02, eta: 12:10:54, time: 0.362, data_time: 0.000, memory: 4083, top1_acc: 0.9000, top5_acc: 0.9988, loss_cls: 0.4966, loss: 0.4966 +2025-06-24 18:28:24,154 - pyskl - INFO - Epoch [61][600/1281] lr: 1.625e-02, eta: 12:10:15, time: 0.375, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9969, loss_cls: 0.5060, loss: 0.5060 +2025-06-24 18:29:02,515 - pyskl - INFO - Epoch [61][700/1281] lr: 1.623e-02, eta: 12:09:37, time: 0.384, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9969, loss_cls: 0.4886, loss: 0.4886 +2025-06-24 18:29:51,838 - pyskl - INFO - Epoch [61][800/1281] lr: 1.621e-02, eta: 12:09:15, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9062, top5_acc: 0.9981, loss_cls: 0.4910, loss: 0.4910 +2025-06-24 18:30:40,733 - pyskl - INFO - Epoch [61][900/1281] lr: 1.619e-02, eta: 12:08:52, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.8969, top5_acc: 0.9962, loss_cls: 0.5383, loss: 0.5383 +2025-06-24 18:31:29,688 - pyskl - INFO - Epoch [61][1000/1281] lr: 1.617e-02, eta: 12:08:30, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9962, loss_cls: 0.4553, loss: 0.4553 +2025-06-24 18:32:18,783 - pyskl - INFO - Epoch [61][1100/1281] lr: 1.615e-02, eta: 12:08:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9988, loss_cls: 0.4250, loss: 0.4250 +2025-06-24 18:33:08,001 - pyskl - INFO - Epoch [61][1200/1281] lr: 1.613e-02, eta: 12:07:45, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9969, loss_cls: 0.4953, loss: 0.4953 +2025-06-24 18:33:48,507 - pyskl - INFO - Saving checkpoint at 61 epochs +2025-06-24 18:34:48,084 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:34:48,141 - pyskl - INFO - +top1_acc 0.8392 +top5_acc 0.9867 +2025-06-24 18:34:48,142 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:34:48,150 - pyskl - INFO - +mean_acc 0.7928 +2025-06-24 18:34:48,153 - pyskl - INFO - Epoch(val) [61][533] top1_acc: 0.8392, top5_acc: 0.9867, mean_class_accuracy: 0.7928 +2025-06-24 18:36:07,228 - pyskl - INFO - Epoch [62][100/1281] lr: 1.609e-02, eta: 12:06:50, time: 0.791, data_time: 0.191, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9962, loss_cls: 0.5041, loss: 0.5041 +2025-06-24 18:36:56,271 - pyskl - INFO - Epoch [62][200/1281] lr: 1.607e-02, eta: 12:06:27, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9969, loss_cls: 0.4527, loss: 0.4527 +2025-06-24 18:37:45,466 - pyskl - INFO - Epoch [62][300/1281] lr: 1.605e-02, eta: 12:06:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9988, loss_cls: 0.4590, loss: 0.4590 +2025-06-24 18:38:32,089 - pyskl - INFO - Epoch [62][400/1281] lr: 1.603e-02, eta: 12:05:39, time: 0.466, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9969, loss_cls: 0.4671, loss: 0.4671 +2025-06-24 18:39:09,436 - pyskl - INFO - Epoch [62][500/1281] lr: 1.602e-02, eta: 12:04:59, time: 0.373, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9975, loss_cls: 0.4225, loss: 0.4225 +2025-06-24 18:39:45,578 - pyskl - INFO - Epoch [62][600/1281] lr: 1.600e-02, eta: 12:04:17, time: 0.361, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9969, loss_cls: 0.4113, loss: 0.4113 +2025-06-24 18:40:23,103 - pyskl - INFO - Epoch [62][700/1281] lr: 1.598e-02, eta: 12:03:38, time: 0.375, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9962, loss_cls: 0.4701, loss: 0.4701 +2025-06-24 18:41:11,738 - pyskl - INFO - Epoch [62][800/1281] lr: 1.596e-02, eta: 12:03:14, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9969, loss_cls: 0.4635, loss: 0.4635 +2025-06-24 18:42:00,774 - pyskl - INFO - Epoch [62][900/1281] lr: 1.594e-02, eta: 12:02:51, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9994, loss_cls: 0.4800, loss: 0.4800 +2025-06-24 18:42:49,700 - pyskl - INFO - Epoch [62][1000/1281] lr: 1.592e-02, eta: 12:02:28, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9938, loss_cls: 0.4937, loss: 0.4937 +2025-06-24 18:43:38,911 - pyskl - INFO - Epoch [62][1100/1281] lr: 1.590e-02, eta: 12:02:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9944, loss_cls: 0.4902, loss: 0.4902 +2025-06-24 18:44:28,036 - pyskl - INFO - Epoch [62][1200/1281] lr: 1.588e-02, eta: 12:01:42, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.8975, top5_acc: 0.9975, loss_cls: 0.4983, loss: 0.4983 +2025-06-24 18:45:08,255 - pyskl - INFO - Saving checkpoint at 62 epochs +2025-06-24 18:46:07,239 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:46:07,311 - pyskl - INFO - +top1_acc 0.8784 +top5_acc 0.9932 +2025-06-24 18:46:07,311 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:46:07,319 - pyskl - INFO - +mean_acc 0.8592 +2025-06-24 18:46:07,321 - pyskl - INFO - Epoch(val) [62][533] top1_acc: 0.8784, top5_acc: 0.9932, mean_class_accuracy: 0.8592 +2025-06-24 18:47:27,044 - pyskl - INFO - Epoch [63][100/1281] lr: 1.584e-02, eta: 12:00:47, time: 0.797, data_time: 0.194, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9975, loss_cls: 0.3970, loss: 0.3970 +2025-06-24 18:48:15,689 - pyskl - INFO - Epoch [63][200/1281] lr: 1.582e-02, eta: 12:00:23, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9981, loss_cls: 0.4340, loss: 0.4340 +2025-06-24 18:49:04,614 - pyskl - INFO - Epoch [63][300/1281] lr: 1.580e-02, eta: 12:00:00, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9994, loss_cls: 0.3979, loss: 0.3979 +2025-06-24 18:49:51,710 - pyskl - INFO - Epoch [63][400/1281] lr: 1.578e-02, eta: 11:59:34, time: 0.471, data_time: 0.000, memory: 4083, top1_acc: 0.9012, top5_acc: 0.9969, loss_cls: 0.4972, loss: 0.4972 +2025-06-24 18:50:26,147 - pyskl - INFO - Epoch [63][500/1281] lr: 1.576e-02, eta: 11:58:49, time: 0.344, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9981, loss_cls: 0.4531, loss: 0.4531 +2025-06-24 18:51:05,210 - pyskl - INFO - Epoch [63][600/1281] lr: 1.574e-02, eta: 11:58:12, time: 0.391, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9988, loss_cls: 0.4291, loss: 0.4291 +2025-06-24 18:51:41,912 - pyskl - INFO - Epoch [63][700/1281] lr: 1.572e-02, eta: 11:57:31, time: 0.367, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9981, loss_cls: 0.4216, loss: 0.4216 +2025-06-24 18:52:31,157 - pyskl - INFO - Epoch [63][800/1281] lr: 1.570e-02, eta: 11:57:08, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9981, loss_cls: 0.4651, loss: 0.4651 +2025-06-24 18:53:20,367 - pyskl - INFO - Epoch [63][900/1281] lr: 1.568e-02, eta: 11:56:44, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9025, top5_acc: 0.9988, loss_cls: 0.5086, loss: 0.5086 +2025-06-24 18:54:09,303 - pyskl - INFO - Epoch [63][1000/1281] lr: 1.566e-02, eta: 11:56:20, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9075, top5_acc: 0.9931, loss_cls: 0.5171, loss: 0.5171 +2025-06-24 18:54:58,451 - pyskl - INFO - Epoch [63][1100/1281] lr: 1.564e-02, eta: 11:55:57, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9031, top5_acc: 0.9956, loss_cls: 0.4826, loss: 0.4826 +2025-06-24 18:55:47,637 - pyskl - INFO - Epoch [63][1200/1281] lr: 1.562e-02, eta: 11:55:33, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9038, top5_acc: 0.9981, loss_cls: 0.4847, loss: 0.4847 +2025-06-24 18:56:28,203 - pyskl - INFO - Saving checkpoint at 63 epochs +2025-06-24 18:57:27,904 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 18:57:27,959 - pyskl - INFO - +top1_acc 0.8691 +top5_acc 0.9907 +2025-06-24 18:57:27,959 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 18:57:27,966 - pyskl - INFO - +mean_acc 0.8185 +2025-06-24 18:57:27,968 - pyskl - INFO - Epoch(val) [63][533] top1_acc: 0.8691, top5_acc: 0.9907, mean_class_accuracy: 0.8185 +2025-06-24 18:58:46,854 - pyskl - INFO - Epoch [64][100/1281] lr: 1.559e-02, eta: 11:54:36, time: 0.789, data_time: 0.199, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9988, loss_cls: 0.4053, loss: 0.4053 +2025-06-24 18:59:36,145 - pyskl - INFO - Epoch [64][200/1281] lr: 1.557e-02, eta: 11:54:12, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9956, loss_cls: 0.4451, loss: 0.4451 +2025-06-24 19:00:25,154 - pyskl - INFO - Epoch [64][300/1281] lr: 1.555e-02, eta: 11:53:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9988, loss_cls: 0.3849, loss: 0.3849 +2025-06-24 19:01:11,994 - pyskl - INFO - Epoch [64][400/1281] lr: 1.553e-02, eta: 11:53:21, time: 0.468, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9975, loss_cls: 0.4087, loss: 0.4087 +2025-06-24 19:01:47,174 - pyskl - INFO - Epoch [64][500/1281] lr: 1.551e-02, eta: 11:52:38, time: 0.352, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9988, loss_cls: 0.4551, loss: 0.4551 +2025-06-24 19:02:25,445 - pyskl - INFO - Epoch [64][600/1281] lr: 1.549e-02, eta: 11:51:59, time: 0.383, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9962, loss_cls: 0.4748, loss: 0.4748 +2025-06-24 19:03:03,015 - pyskl - INFO - Epoch [64][700/1281] lr: 1.547e-02, eta: 11:51:19, time: 0.376, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9962, loss_cls: 0.4055, loss: 0.4055 +2025-06-24 19:03:52,430 - pyskl - INFO - Epoch [64][800/1281] lr: 1.545e-02, eta: 11:50:55, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9956, loss_cls: 0.4634, loss: 0.4634 +2025-06-24 19:04:41,363 - pyskl - INFO - Epoch [64][900/1281] lr: 1.543e-02, eta: 11:50:31, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9981, loss_cls: 0.4612, loss: 0.4612 +2025-06-24 19:05:30,363 - pyskl - INFO - Epoch [64][1000/1281] lr: 1.541e-02, eta: 11:50:06, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9975, loss_cls: 0.4796, loss: 0.4796 +2025-06-24 19:06:19,562 - pyskl - INFO - Epoch [64][1100/1281] lr: 1.539e-02, eta: 11:49:42, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9106, top5_acc: 0.9956, loss_cls: 0.4702, loss: 0.4702 +2025-06-24 19:07:08,987 - pyskl - INFO - Epoch [64][1200/1281] lr: 1.537e-02, eta: 11:49:18, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9988, loss_cls: 0.4349, loss: 0.4349 +2025-06-24 19:07:49,593 - pyskl - INFO - Saving checkpoint at 64 epochs +2025-06-24 19:08:49,395 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:08:49,451 - pyskl - INFO - +top1_acc 0.8817 +top5_acc 0.9932 +2025-06-24 19:08:49,451 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:08:49,459 - pyskl - INFO - +mean_acc 0.8368 +2025-06-24 19:08:49,463 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_59.pth was removed +2025-06-24 19:08:49,712 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_64.pth. +2025-06-24 19:08:49,713 - pyskl - INFO - Best top1_acc is 0.8817 at 64 epoch. +2025-06-24 19:08:49,718 - pyskl - INFO - Epoch(val) [64][533] top1_acc: 0.8817, top5_acc: 0.9932, mean_class_accuracy: 0.8368 +2025-06-24 19:10:09,755 - pyskl - INFO - Epoch [65][100/1281] lr: 1.533e-02, eta: 11:48:22, time: 0.800, data_time: 0.193, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9981, loss_cls: 0.3819, loss: 0.3819 +2025-06-24 19:10:59,011 - pyskl - INFO - Epoch [65][200/1281] lr: 1.531e-02, eta: 11:47:58, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9994, loss_cls: 0.4650, loss: 0.4650 +2025-06-24 19:11:48,050 - pyskl - INFO - Epoch [65][300/1281] lr: 1.529e-02, eta: 11:47:33, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9988, loss_cls: 0.4505, loss: 0.4505 +2025-06-24 19:12:33,837 - pyskl - INFO - Epoch [65][400/1281] lr: 1.527e-02, eta: 11:47:04, time: 0.458, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9962, loss_cls: 0.3848, loss: 0.3848 +2025-06-24 19:13:14,303 - pyskl - INFO - Epoch [65][500/1281] lr: 1.526e-02, eta: 11:46:27, time: 0.405, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9988, loss_cls: 0.4190, loss: 0.4190 +2025-06-24 19:13:47,558 - pyskl - INFO - Epoch [65][600/1281] lr: 1.524e-02, eta: 11:45:42, time: 0.333, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9988, loss_cls: 0.4150, loss: 0.4150 +2025-06-24 19:14:28,281 - pyskl - INFO - Epoch [65][700/1281] lr: 1.522e-02, eta: 11:45:06, time: 0.407, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9994, loss_cls: 0.4292, loss: 0.4292 +2025-06-24 19:15:17,782 - pyskl - INFO - Epoch [65][800/1281] lr: 1.520e-02, eta: 11:44:41, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9962, loss_cls: 0.4515, loss: 0.4515 +2025-06-24 19:16:07,086 - pyskl - INFO - Epoch [65][900/1281] lr: 1.518e-02, eta: 11:44:17, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9988, loss_cls: 0.4709, loss: 0.4709 +2025-06-24 19:16:56,017 - pyskl - INFO - Epoch [65][1000/1281] lr: 1.516e-02, eta: 11:43:52, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 0.9100, top5_acc: 0.9962, loss_cls: 0.4587, loss: 0.4587 +2025-06-24 19:17:45,069 - pyskl - INFO - Epoch [65][1100/1281] lr: 1.514e-02, eta: 11:43:27, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9981, loss_cls: 0.4260, loss: 0.4260 +2025-06-24 19:18:33,837 - pyskl - INFO - Epoch [65][1200/1281] lr: 1.512e-02, eta: 11:43:01, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.8988, top5_acc: 0.9938, loss_cls: 0.5237, loss: 0.5237 +2025-06-24 19:19:14,214 - pyskl - INFO - Saving checkpoint at 65 epochs +2025-06-24 19:20:13,644 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:20:13,712 - pyskl - INFO - +top1_acc 0.8764 +top5_acc 0.9926 +2025-06-24 19:20:13,712 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:20:13,720 - pyskl - INFO - +mean_acc 0.8278 +2025-06-24 19:20:13,723 - pyskl - INFO - Epoch(val) [65][533] top1_acc: 0.8764, top5_acc: 0.9926, mean_class_accuracy: 0.8278 +2025-06-24 19:21:34,598 - pyskl - INFO - Epoch [66][100/1281] lr: 1.508e-02, eta: 11:42:05, time: 0.809, data_time: 0.197, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9988, loss_cls: 0.4144, loss: 0.4144 +2025-06-24 19:22:23,687 - pyskl - INFO - Epoch [66][200/1281] lr: 1.506e-02, eta: 11:41:40, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9988, loss_cls: 0.4258, loss: 0.4258 +2025-06-24 19:23:13,063 - pyskl - INFO - Epoch [66][300/1281] lr: 1.504e-02, eta: 11:41:15, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9975, loss_cls: 0.4363, loss: 0.4363 +2025-06-24 19:23:55,662 - pyskl - INFO - Epoch [66][400/1281] lr: 1.502e-02, eta: 11:40:41, time: 0.426, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9981, loss_cls: 0.4116, loss: 0.4116 +2025-06-24 19:24:40,032 - pyskl - INFO - Epoch [66][500/1281] lr: 1.500e-02, eta: 11:40:10, time: 0.444, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9988, loss_cls: 0.4247, loss: 0.4247 +2025-06-24 19:25:09,188 - pyskl - INFO - Epoch [66][600/1281] lr: 1.498e-02, eta: 11:39:19, time: 0.292, data_time: 0.000, memory: 4083, top1_acc: 0.9281, top5_acc: 0.9981, loss_cls: 0.3823, loss: 0.3823 +2025-06-24 19:25:50,395 - pyskl - INFO - Epoch [66][700/1281] lr: 1.496e-02, eta: 11:38:43, time: 0.412, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9981, loss_cls: 0.4517, loss: 0.4517 +2025-06-24 19:26:39,699 - pyskl - INFO - Epoch [66][800/1281] lr: 1.494e-02, eta: 11:38:18, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9994, loss_cls: 0.4239, loss: 0.4239 +2025-06-24 19:27:29,003 - pyskl - INFO - Epoch [66][900/1281] lr: 1.492e-02, eta: 11:37:53, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9988, loss_cls: 0.4669, loss: 0.4669 +2025-06-24 19:28:17,621 - pyskl - INFO - Epoch [66][1000/1281] lr: 1.490e-02, eta: 11:37:26, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9969, loss_cls: 0.4301, loss: 0.4301 +2025-06-24 19:29:06,574 - pyskl - INFO - Epoch [66][1100/1281] lr: 1.488e-02, eta: 11:37:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9994, loss_cls: 0.4098, loss: 0.4098 +2025-06-24 19:29:56,203 - pyskl - INFO - Epoch [66][1200/1281] lr: 1.486e-02, eta: 11:36:36, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9981, loss_cls: 0.4633, loss: 0.4633 +2025-06-24 19:30:36,584 - pyskl - INFO - Saving checkpoint at 66 epochs +2025-06-24 19:31:36,229 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:31:36,291 - pyskl - INFO - +top1_acc 0.8661 +top5_acc 0.9919 +2025-06-24 19:31:36,291 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:31:36,300 - pyskl - INFO - +mean_acc 0.8079 +2025-06-24 19:31:36,315 - pyskl - INFO - Epoch(val) [66][533] top1_acc: 0.8661, top5_acc: 0.9919, mean_class_accuracy: 0.8079 +2025-06-24 19:32:56,285 - pyskl - INFO - Epoch [67][100/1281] lr: 1.482e-02, eta: 11:35:38, time: 0.800, data_time: 0.198, memory: 4083, top1_acc: 0.9287, top5_acc: 1.0000, loss_cls: 0.3885, loss: 0.3885 +2025-06-24 19:33:45,775 - pyskl - INFO - Epoch [67][200/1281] lr: 1.480e-02, eta: 11:35:12, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9988, loss_cls: 0.4376, loss: 0.4376 +2025-06-24 19:34:34,775 - pyskl - INFO - Epoch [67][300/1281] lr: 1.478e-02, eta: 11:34:46, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9969, loss_cls: 0.4349, loss: 0.4349 +2025-06-24 19:35:16,206 - pyskl - INFO - Epoch [67][400/1281] lr: 1.476e-02, eta: 11:34:11, time: 0.414, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9994, loss_cls: 0.3715, loss: 0.3715 +2025-06-24 19:36:02,066 - pyskl - INFO - Epoch [67][500/1281] lr: 1.474e-02, eta: 11:33:41, time: 0.459, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9975, loss_cls: 0.3983, loss: 0.3983 +2025-06-24 19:36:29,761 - pyskl - INFO - Epoch [67][600/1281] lr: 1.472e-02, eta: 11:32:48, time: 0.277, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9988, loss_cls: 0.3950, loss: 0.3950 +2025-06-24 19:37:12,422 - pyskl - INFO - Epoch [67][700/1281] lr: 1.470e-02, eta: 11:32:14, time: 0.427, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9988, loss_cls: 0.4160, loss: 0.4160 +2025-06-24 19:38:01,442 - pyskl - INFO - Epoch [67][800/1281] lr: 1.468e-02, eta: 11:31:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9981, loss_cls: 0.4139, loss: 0.4139 +2025-06-24 19:38:50,521 - pyskl - INFO - Epoch [67][900/1281] lr: 1.466e-02, eta: 11:31:22, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9206, top5_acc: 0.9969, loss_cls: 0.3981, loss: 0.3981 +2025-06-24 19:39:39,479 - pyskl - INFO - Epoch [67][1000/1281] lr: 1.464e-02, eta: 11:30:55, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9044, top5_acc: 0.9975, loss_cls: 0.4630, loss: 0.4630 +2025-06-24 19:40:28,569 - pyskl - INFO - Epoch [67][1100/1281] lr: 1.462e-02, eta: 11:30:29, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9981, loss_cls: 0.4235, loss: 0.4235 +2025-06-24 19:41:17,854 - pyskl - INFO - Epoch [67][1200/1281] lr: 1.460e-02, eta: 11:30:03, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9975, loss_cls: 0.4379, loss: 0.4379 +2025-06-24 19:41:57,998 - pyskl - INFO - Saving checkpoint at 67 epochs +2025-06-24 19:42:56,597 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:42:56,665 - pyskl - INFO - +top1_acc 0.8726 +top5_acc 0.9932 +2025-06-24 19:42:56,665 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:42:56,672 - pyskl - INFO - +mean_acc 0.8462 +2025-06-24 19:42:56,674 - pyskl - INFO - Epoch(val) [67][533] top1_acc: 0.8726, top5_acc: 0.9932, mean_class_accuracy: 0.8462 +2025-06-24 19:44:17,267 - pyskl - INFO - Epoch [68][100/1281] lr: 1.456e-02, eta: 11:29:05, time: 0.806, data_time: 0.201, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9975, loss_cls: 0.4506, loss: 0.4506 +2025-06-24 19:45:06,279 - pyskl - INFO - Epoch [68][200/1281] lr: 1.454e-02, eta: 11:28:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9994, loss_cls: 0.3703, loss: 0.3703 +2025-06-24 19:45:55,970 - pyskl - INFO - Epoch [68][300/1281] lr: 1.452e-02, eta: 11:28:13, time: 0.497, data_time: 0.001, memory: 4083, top1_acc: 0.9163, top5_acc: 0.9988, loss_cls: 0.4287, loss: 0.4287 +2025-06-24 19:46:37,131 - pyskl - INFO - Epoch [68][400/1281] lr: 1.450e-02, eta: 11:27:37, time: 0.412, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9994, loss_cls: 0.3716, loss: 0.3716 +2025-06-24 19:47:24,501 - pyskl - INFO - Epoch [68][500/1281] lr: 1.448e-02, eta: 11:27:08, time: 0.474, data_time: 0.000, memory: 4083, top1_acc: 0.9094, top5_acc: 0.9975, loss_cls: 0.4494, loss: 0.4494 +2025-06-24 19:47:51,085 - pyskl - INFO - Epoch [68][600/1281] lr: 1.446e-02, eta: 11:26:14, time: 0.266, data_time: 0.000, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9994, loss_cls: 0.4415, loss: 0.4415 +2025-06-24 19:48:33,795 - pyskl - INFO - Epoch [68][700/1281] lr: 1.444e-02, eta: 11:25:40, time: 0.427, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9981, loss_cls: 0.4030, loss: 0.4030 +2025-06-24 19:49:22,937 - pyskl - INFO - Epoch [68][800/1281] lr: 1.442e-02, eta: 11:25:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9994, loss_cls: 0.3403, loss: 0.3403 +2025-06-24 19:50:12,073 - pyskl - INFO - Epoch [68][900/1281] lr: 1.440e-02, eta: 11:24:47, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9981, loss_cls: 0.4091, loss: 0.4091 +2025-06-24 19:51:01,379 - pyskl - INFO - Epoch [68][1000/1281] lr: 1.438e-02, eta: 11:24:20, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9131, top5_acc: 0.9975, loss_cls: 0.4247, loss: 0.4247 +2025-06-24 19:51:50,216 - pyskl - INFO - Epoch [68][1100/1281] lr: 1.436e-02, eta: 11:23:53, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9081, top5_acc: 0.9981, loss_cls: 0.4645, loss: 0.4645 +2025-06-24 19:52:39,251 - pyskl - INFO - Epoch [68][1200/1281] lr: 1.434e-02, eta: 11:23:26, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9988, loss_cls: 0.3946, loss: 0.3946 +2025-06-24 19:53:19,767 - pyskl - INFO - Saving checkpoint at 68 epochs +2025-06-24 19:54:18,397 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 19:54:18,466 - pyskl - INFO - +top1_acc 0.8742 +top5_acc 0.9926 +2025-06-24 19:54:18,466 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 19:54:18,474 - pyskl - INFO - +mean_acc 0.8324 +2025-06-24 19:54:18,476 - pyskl - INFO - Epoch(val) [68][533] top1_acc: 0.8742, top5_acc: 0.9926, mean_class_accuracy: 0.8324 +2025-06-24 19:55:38,336 - pyskl - INFO - Epoch [69][100/1281] lr: 1.431e-02, eta: 11:22:27, time: 0.799, data_time: 0.191, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9981, loss_cls: 0.3359, loss: 0.3359 +2025-06-24 19:56:27,272 - pyskl - INFO - Epoch [69][200/1281] lr: 1.429e-02, eta: 11:22:00, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9975, loss_cls: 0.4175, loss: 0.4175 +2025-06-24 19:57:16,393 - pyskl - INFO - Epoch [69][300/1281] lr: 1.427e-02, eta: 11:21:33, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9988, loss_cls: 0.3641, loss: 0.3641 +2025-06-24 19:57:57,612 - pyskl - INFO - Epoch [69][400/1281] lr: 1.425e-02, eta: 11:20:56, time: 0.412, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9994, loss_cls: 0.3765, loss: 0.3765 +2025-06-24 19:58:45,950 - pyskl - INFO - Epoch [69][500/1281] lr: 1.423e-02, eta: 11:20:28, time: 0.483, data_time: 0.001, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9988, loss_cls: 0.4339, loss: 0.4339 +2025-06-24 19:59:11,859 - pyskl - INFO - Epoch [69][600/1281] lr: 1.420e-02, eta: 11:19:34, time: 0.259, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9981, loss_cls: 0.3813, loss: 0.3813 +2025-06-24 19:59:53,894 - pyskl - INFO - Epoch [69][700/1281] lr: 1.418e-02, eta: 11:18:58, time: 0.420, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9975, loss_cls: 0.4112, loss: 0.4112 +2025-06-24 20:00:43,085 - pyskl - INFO - Epoch [69][800/1281] lr: 1.416e-02, eta: 11:18:31, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9969, loss_cls: 0.4115, loss: 0.4115 +2025-06-24 20:01:31,935 - pyskl - INFO - Epoch [69][900/1281] lr: 1.414e-02, eta: 11:18:04, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9969, loss_cls: 0.4566, loss: 0.4566 +2025-06-24 20:02:20,933 - pyskl - INFO - Epoch [69][1000/1281] lr: 1.412e-02, eta: 11:17:36, time: 0.490, data_time: 0.001, memory: 4083, top1_acc: 0.9125, top5_acc: 0.9956, loss_cls: 0.4652, loss: 0.4652 +2025-06-24 20:03:09,998 - pyskl - INFO - Epoch [69][1100/1281] lr: 1.410e-02, eta: 11:17:09, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9069, top5_acc: 0.9981, loss_cls: 0.4408, loss: 0.4408 +2025-06-24 20:03:59,105 - pyskl - INFO - Epoch [69][1200/1281] lr: 1.408e-02, eta: 11:16:42, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9975, loss_cls: 0.4362, loss: 0.4362 +2025-06-24 20:04:39,237 - pyskl - INFO - Saving checkpoint at 69 epochs +2025-06-24 20:05:38,707 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:05:38,766 - pyskl - INFO - +top1_acc 0.8756 +top5_acc 0.9890 +2025-06-24 20:05:38,766 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:05:38,776 - pyskl - INFO - +mean_acc 0.8340 +2025-06-24 20:05:38,779 - pyskl - INFO - Epoch(val) [69][533] top1_acc: 0.8756, top5_acc: 0.9890, mean_class_accuracy: 0.8340 +2025-06-24 20:06:59,509 - pyskl - INFO - Epoch [70][100/1281] lr: 1.405e-02, eta: 11:15:42, time: 0.807, data_time: 0.194, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9975, loss_cls: 0.4048, loss: 0.4048 +2025-06-24 20:07:48,696 - pyskl - INFO - Epoch [70][200/1281] lr: 1.403e-02, eta: 11:15:15, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9981, loss_cls: 0.3637, loss: 0.3637 +2025-06-24 20:08:37,637 - pyskl - INFO - Epoch [70][300/1281] lr: 1.401e-02, eta: 11:14:47, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9975, loss_cls: 0.3824, loss: 0.3824 +2025-06-24 20:09:17,554 - pyskl - INFO - Epoch [70][400/1281] lr: 1.399e-02, eta: 11:14:09, time: 0.399, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9975, loss_cls: 0.4000, loss: 0.4000 +2025-06-24 20:10:08,732 - pyskl - INFO - Epoch [70][500/1281] lr: 1.397e-02, eta: 11:13:44, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9988, loss_cls: 0.3551, loss: 0.3551 +2025-06-24 20:10:32,230 - pyskl - INFO - Epoch [70][600/1281] lr: 1.395e-02, eta: 11:12:47, time: 0.235, data_time: 0.000, memory: 4083, top1_acc: 0.9313, top5_acc: 0.9981, loss_cls: 0.3949, loss: 0.3949 +2025-06-24 20:11:15,464 - pyskl - INFO - Epoch [70][700/1281] lr: 1.392e-02, eta: 11:12:12, time: 0.432, data_time: 0.000, memory: 4083, top1_acc: 0.9181, top5_acc: 0.9988, loss_cls: 0.4231, loss: 0.4231 +2025-06-24 20:12:04,801 - pyskl - INFO - Epoch [70][800/1281] lr: 1.390e-02, eta: 11:11:45, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9962, loss_cls: 0.4348, loss: 0.4348 +2025-06-24 20:12:53,958 - pyskl - INFO - Epoch [70][900/1281] lr: 1.388e-02, eta: 11:11:17, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9137, top5_acc: 0.9988, loss_cls: 0.4352, loss: 0.4352 +2025-06-24 20:13:43,100 - pyskl - INFO - Epoch [70][1000/1281] lr: 1.386e-02, eta: 11:10:50, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9163, top5_acc: 1.0000, loss_cls: 0.4174, loss: 0.4174 +2025-06-24 20:14:32,251 - pyskl - INFO - Epoch [70][1100/1281] lr: 1.384e-02, eta: 11:10:22, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9050, top5_acc: 0.9962, loss_cls: 0.4787, loss: 0.4787 +2025-06-24 20:15:21,484 - pyskl - INFO - Epoch [70][1200/1281] lr: 1.382e-02, eta: 11:09:54, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 1.0000, loss_cls: 0.3962, loss: 0.3962 +2025-06-24 20:16:01,744 - pyskl - INFO - Saving checkpoint at 70 epochs +2025-06-24 20:17:01,625 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:17:01,682 - pyskl - INFO - +top1_acc 0.8713 +top5_acc 0.9918 +2025-06-24 20:17:01,682 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:17:01,689 - pyskl - INFO - +mean_acc 0.8298 +2025-06-24 20:17:01,691 - pyskl - INFO - Epoch(val) [70][533] top1_acc: 0.8713, top5_acc: 0.9918, mean_class_accuracy: 0.8298 +2025-06-24 20:18:21,887 - pyskl - INFO - Epoch [71][100/1281] lr: 1.379e-02, eta: 11:08:54, time: 0.802, data_time: 0.194, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3565, loss: 0.3565 +2025-06-24 20:19:11,000 - pyskl - INFO - Epoch [71][200/1281] lr: 1.377e-02, eta: 11:08:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9994, loss_cls: 0.3607, loss: 0.3607 +2025-06-24 20:20:00,211 - pyskl - INFO - Epoch [71][300/1281] lr: 1.375e-02, eta: 11:07:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9969, loss_cls: 0.3630, loss: 0.3630 +2025-06-24 20:20:39,553 - pyskl - INFO - Epoch [71][400/1281] lr: 1.373e-02, eta: 11:07:19, time: 0.393, data_time: 0.001, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9988, loss_cls: 0.3585, loss: 0.3585 +2025-06-24 20:21:30,717 - pyskl - INFO - Epoch [71][500/1281] lr: 1.371e-02, eta: 11:06:53, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.9213, top5_acc: 0.9975, loss_cls: 0.4311, loss: 0.4311 +2025-06-24 20:21:53,911 - pyskl - INFO - Epoch [71][600/1281] lr: 1.368e-02, eta: 11:05:56, time: 0.232, data_time: 0.000, memory: 4083, top1_acc: 0.9056, top5_acc: 0.9950, loss_cls: 0.4694, loss: 0.4694 +2025-06-24 20:22:37,774 - pyskl - INFO - Epoch [71][700/1281] lr: 1.366e-02, eta: 11:05:22, time: 0.439, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9975, loss_cls: 0.3853, loss: 0.3853 +2025-06-24 20:23:27,101 - pyskl - INFO - Epoch [71][800/1281] lr: 1.364e-02, eta: 11:04:54, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9256, top5_acc: 1.0000, loss_cls: 0.3943, loss: 0.3943 +2025-06-24 20:24:16,343 - pyskl - INFO - Epoch [71][900/1281] lr: 1.362e-02, eta: 11:04:26, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9156, top5_acc: 0.9969, loss_cls: 0.4287, loss: 0.4287 +2025-06-24 20:25:05,369 - pyskl - INFO - Epoch [71][1000/1281] lr: 1.360e-02, eta: 11:03:58, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9981, loss_cls: 0.4079, loss: 0.4079 +2025-06-24 20:25:54,335 - pyskl - INFO - Epoch [71][1100/1281] lr: 1.358e-02, eta: 11:03:29, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9200, top5_acc: 0.9981, loss_cls: 0.3915, loss: 0.3915 +2025-06-24 20:26:43,423 - pyskl - INFO - Epoch [71][1200/1281] lr: 1.356e-02, eta: 11:03:01, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9988, loss_cls: 0.3798, loss: 0.3798 +2025-06-24 20:27:23,729 - pyskl - INFO - Saving checkpoint at 71 epochs +2025-06-24 20:28:23,414 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:28:23,482 - pyskl - INFO - +top1_acc 0.8998 +top5_acc 0.9948 +2025-06-24 20:28:23,482 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:28:23,490 - pyskl - INFO - +mean_acc 0.8648 +2025-06-24 20:28:23,495 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_64.pth was removed +2025-06-24 20:28:23,673 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_71.pth. +2025-06-24 20:28:23,673 - pyskl - INFO - Best top1_acc is 0.8998 at 71 epoch. +2025-06-24 20:28:23,675 - pyskl - INFO - Epoch(val) [71][533] top1_acc: 0.8998, top5_acc: 0.9948, mean_class_accuracy: 0.8648 +2025-06-24 20:29:44,662 - pyskl - INFO - Epoch [72][100/1281] lr: 1.353e-02, eta: 11:02:01, time: 0.810, data_time: 0.200, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9994, loss_cls: 0.3835, loss: 0.3835 +2025-06-24 20:30:33,806 - pyskl - INFO - Epoch [72][200/1281] lr: 1.351e-02, eta: 11:01:33, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9981, loss_cls: 0.3407, loss: 0.3407 +2025-06-24 20:31:23,023 - pyskl - INFO - Epoch [72][300/1281] lr: 1.349e-02, eta: 11:01:04, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 0.2987, loss: 0.2987 +2025-06-24 20:32:00,210 - pyskl - INFO - Epoch [72][400/1281] lr: 1.346e-02, eta: 11:00:23, time: 0.372, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9981, loss_cls: 0.3659, loss: 0.3659 +2025-06-24 20:32:51,463 - pyskl - INFO - Epoch [72][500/1281] lr: 1.344e-02, eta: 10:59:57, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9981, loss_cls: 0.3695, loss: 0.3695 +2025-06-24 20:33:16,085 - pyskl - INFO - Epoch [72][600/1281] lr: 1.342e-02, eta: 10:59:01, time: 0.246, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9981, loss_cls: 0.3994, loss: 0.3994 +2025-06-24 20:34:01,521 - pyskl - INFO - Epoch [72][700/1281] lr: 1.340e-02, eta: 10:58:28, time: 0.454, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9969, loss_cls: 0.3912, loss: 0.3912 +2025-06-24 20:34:50,867 - pyskl - INFO - Epoch [72][800/1281] lr: 1.338e-02, eta: 10:58:00, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 0.9975, loss_cls: 0.3370, loss: 0.3370 +2025-06-24 20:35:39,894 - pyskl - INFO - Epoch [72][900/1281] lr: 1.336e-02, eta: 10:57:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9988, loss_cls: 0.3791, loss: 0.3791 +2025-06-24 20:36:28,911 - pyskl - INFO - Epoch [72][1000/1281] lr: 1.334e-02, eta: 10:57:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9975, loss_cls: 0.4707, loss: 0.4707 +2025-06-24 20:37:18,069 - pyskl - INFO - Epoch [72][1100/1281] lr: 1.332e-02, eta: 10:56:34, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9962, loss_cls: 0.4560, loss: 0.4560 +2025-06-24 20:38:07,373 - pyskl - INFO - Epoch [72][1200/1281] lr: 1.330e-02, eta: 10:56:05, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9113, top5_acc: 0.9956, loss_cls: 0.4643, loss: 0.4643 +2025-06-24 20:38:47,609 - pyskl - INFO - Saving checkpoint at 72 epochs +2025-06-24 20:39:46,374 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:39:46,455 - pyskl - INFO - +top1_acc 0.8825 +top5_acc 0.9920 +2025-06-24 20:39:46,455 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:39:46,463 - pyskl - INFO - +mean_acc 0.8366 +2025-06-24 20:39:46,465 - pyskl - INFO - Epoch(val) [72][533] top1_acc: 0.8825, top5_acc: 0.9920, mean_class_accuracy: 0.8366 +2025-06-24 20:41:07,805 - pyskl - INFO - Epoch [73][100/1281] lr: 1.326e-02, eta: 10:55:05, time: 0.813, data_time: 0.198, memory: 4083, top1_acc: 0.9250, top5_acc: 1.0000, loss_cls: 0.3839, loss: 0.3839 +2025-06-24 20:41:56,888 - pyskl - INFO - Epoch [73][200/1281] lr: 1.324e-02, eta: 10:54:36, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9981, loss_cls: 0.3857, loss: 0.3857 +2025-06-24 20:42:45,806 - pyskl - INFO - Epoch [73][300/1281] lr: 1.322e-02, eta: 10:54:07, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9975, loss_cls: 0.3760, loss: 0.3760 +2025-06-24 20:43:21,510 - pyskl - INFO - Epoch [73][400/1281] lr: 1.320e-02, eta: 10:53:24, time: 0.357, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9975, loss_cls: 0.3975, loss: 0.3975 +2025-06-24 20:44:12,433 - pyskl - INFO - Epoch [73][500/1281] lr: 1.318e-02, eta: 10:52:57, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9988, loss_cls: 0.3368, loss: 0.3368 +2025-06-24 20:44:37,032 - pyskl - INFO - Epoch [73][600/1281] lr: 1.316e-02, eta: 10:52:01, time: 0.246, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9981, loss_cls: 0.3546, loss: 0.3546 +2025-06-24 20:45:24,342 - pyskl - INFO - Epoch [73][700/1281] lr: 1.314e-02, eta: 10:51:30, time: 0.473, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9994, loss_cls: 0.3770, loss: 0.3770 +2025-06-24 20:46:13,228 - pyskl - INFO - Epoch [73][800/1281] lr: 1.312e-02, eta: 10:51:01, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9144, top5_acc: 0.9981, loss_cls: 0.4421, loss: 0.4421 +2025-06-24 20:47:02,064 - pyskl - INFO - Epoch [73][900/1281] lr: 1.310e-02, eta: 10:50:32, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9194, top5_acc: 0.9975, loss_cls: 0.4420, loss: 0.4420 +2025-06-24 20:47:51,069 - pyskl - INFO - Epoch [73][1000/1281] lr: 1.308e-02, eta: 10:50:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9975, loss_cls: 0.4099, loss: 0.4099 +2025-06-24 20:48:40,061 - pyskl - INFO - Epoch [73][1100/1281] lr: 1.306e-02, eta: 10:49:33, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9150, top5_acc: 0.9988, loss_cls: 0.4475, loss: 0.4475 +2025-06-24 20:49:29,060 - pyskl - INFO - Epoch [73][1200/1281] lr: 1.304e-02, eta: 10:49:04, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9994, loss_cls: 0.4013, loss: 0.4013 +2025-06-24 20:50:09,360 - pyskl - INFO - Saving checkpoint at 73 epochs +2025-06-24 20:51:08,403 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 20:51:08,474 - pyskl - INFO - +top1_acc 0.8726 +top5_acc 0.9910 +2025-06-24 20:51:08,474 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 20:51:08,482 - pyskl - INFO - +mean_acc 0.8435 +2025-06-24 20:51:08,484 - pyskl - INFO - Epoch(val) [73][533] top1_acc: 0.8726, top5_acc: 0.9910, mean_class_accuracy: 0.8435 +2025-06-24 20:52:28,973 - pyskl - INFO - Epoch [74][100/1281] lr: 1.300e-02, eta: 10:48:02, time: 0.805, data_time: 0.194, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9994, loss_cls: 0.3693, loss: 0.3693 +2025-06-24 20:53:17,992 - pyskl - INFO - Epoch [74][200/1281] lr: 1.298e-02, eta: 10:47:33, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9981, loss_cls: 0.3910, loss: 0.3910 +2025-06-24 20:54:07,108 - pyskl - INFO - Epoch [74][300/1281] lr: 1.296e-02, eta: 10:47:03, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9975, loss_cls: 0.4191, loss: 0.4191 +2025-06-24 20:54:40,644 - pyskl - INFO - Epoch [74][400/1281] lr: 1.294e-02, eta: 10:46:17, time: 0.335, data_time: 0.000, memory: 4083, top1_acc: 0.9294, top5_acc: 0.9969, loss_cls: 0.3723, loss: 0.3723 +2025-06-24 20:55:31,912 - pyskl - INFO - Epoch [74][500/1281] lr: 1.292e-02, eta: 10:45:50, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9994, loss_cls: 0.3399, loss: 0.3399 +2025-06-24 20:55:56,878 - pyskl - INFO - Epoch [74][600/1281] lr: 1.290e-02, eta: 10:44:56, time: 0.250, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 0.9969, loss_cls: 0.3542, loss: 0.3542 +2025-06-24 20:56:44,708 - pyskl - INFO - Epoch [74][700/1281] lr: 1.288e-02, eta: 10:44:25, time: 0.478, data_time: 0.000, memory: 4083, top1_acc: 0.9169, top5_acc: 0.9981, loss_cls: 0.4425, loss: 0.4425 +2025-06-24 20:57:33,753 - pyskl - INFO - Epoch [74][800/1281] lr: 1.286e-02, eta: 10:43:55, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9981, loss_cls: 0.3996, loss: 0.3996 +2025-06-24 20:58:22,836 - pyskl - INFO - Epoch [74][900/1281] lr: 1.284e-02, eta: 10:43:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 1.0000, loss_cls: 0.3667, loss: 0.3667 +2025-06-24 20:59:12,185 - pyskl - INFO - Epoch [74][1000/1281] lr: 1.282e-02, eta: 10:42:56, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9962, loss_cls: 0.3978, loss: 0.3978 +2025-06-24 21:00:01,492 - pyskl - INFO - Epoch [74][1100/1281] lr: 1.280e-02, eta: 10:42:27, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9994, loss_cls: 0.3627, loss: 0.3627 +2025-06-24 21:00:50,991 - pyskl - INFO - Epoch [74][1200/1281] lr: 1.278e-02, eta: 10:41:58, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9981, loss_cls: 0.3895, loss: 0.3895 +2025-06-24 21:01:31,500 - pyskl - INFO - Saving checkpoint at 74 epochs +2025-06-24 21:02:30,377 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:02:30,432 - pyskl - INFO - +top1_acc 0.8858 +top5_acc 0.9928 +2025-06-24 21:02:30,432 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:02:30,439 - pyskl - INFO - +mean_acc 0.8326 +2025-06-24 21:02:30,441 - pyskl - INFO - Epoch(val) [74][533] top1_acc: 0.8858, top5_acc: 0.9928, mean_class_accuracy: 0.8326 +2025-06-24 21:03:50,185 - pyskl - INFO - Epoch [75][100/1281] lr: 1.274e-02, eta: 10:40:55, time: 0.797, data_time: 0.197, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 0.2957, loss: 0.2957 +2025-06-24 21:04:39,351 - pyskl - INFO - Epoch [75][200/1281] lr: 1.272e-02, eta: 10:40:25, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9994, loss_cls: 0.3696, loss: 0.3696 +2025-06-24 21:05:28,534 - pyskl - INFO - Epoch [75][300/1281] lr: 1.270e-02, eta: 10:39:55, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9988, loss_cls: 0.3463, loss: 0.3463 +2025-06-24 21:06:02,759 - pyskl - INFO - Epoch [75][400/1281] lr: 1.268e-02, eta: 10:39:10, time: 0.342, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 1.0000, loss_cls: 0.3860, loss: 0.3860 +2025-06-24 21:06:53,813 - pyskl - INFO - Epoch [75][500/1281] lr: 1.266e-02, eta: 10:38:42, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9988, loss_cls: 0.4289, loss: 0.4289 +2025-06-24 21:07:19,670 - pyskl - INFO - Epoch [75][600/1281] lr: 1.264e-02, eta: 10:37:49, time: 0.259, data_time: 0.001, memory: 4083, top1_acc: 0.9256, top5_acc: 0.9994, loss_cls: 0.3756, loss: 0.3756 +2025-06-24 21:08:09,105 - pyskl - INFO - Epoch [75][700/1281] lr: 1.262e-02, eta: 10:37:19, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9219, top5_acc: 0.9962, loss_cls: 0.4317, loss: 0.4317 +2025-06-24 21:08:58,408 - pyskl - INFO - Epoch [75][800/1281] lr: 1.260e-02, eta: 10:36:50, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9988, loss_cls: 0.3720, loss: 0.3720 +2025-06-24 21:09:47,683 - pyskl - INFO - Epoch [75][900/1281] lr: 1.258e-02, eta: 10:36:20, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9994, loss_cls: 0.4011, loss: 0.4011 +2025-06-24 21:10:36,821 - pyskl - INFO - Epoch [75][1000/1281] lr: 1.256e-02, eta: 10:35:50, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9975, loss_cls: 0.4089, loss: 0.4089 +2025-06-24 21:11:26,060 - pyskl - INFO - Epoch [75][1100/1281] lr: 1.254e-02, eta: 10:35:20, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9988, loss_cls: 0.3567, loss: 0.3567 +2025-06-24 21:12:15,353 - pyskl - INFO - Epoch [75][1200/1281] lr: 1.252e-02, eta: 10:34:50, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9994, loss_cls: 0.3795, loss: 0.3795 +2025-06-24 21:12:55,474 - pyskl - INFO - Saving checkpoint at 75 epochs +2025-06-24 21:13:54,999 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:13:55,056 - pyskl - INFO - +top1_acc 0.8837 +top5_acc 0.9933 +2025-06-24 21:13:55,056 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:13:55,063 - pyskl - INFO - +mean_acc 0.8433 +2025-06-24 21:13:55,065 - pyskl - INFO - Epoch(val) [75][533] top1_acc: 0.8837, top5_acc: 0.9933, mean_class_accuracy: 0.8433 +2025-06-24 21:15:15,249 - pyskl - INFO - Epoch [76][100/1281] lr: 1.248e-02, eta: 10:33:47, time: 0.802, data_time: 0.194, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9975, loss_cls: 0.4071, loss: 0.4071 +2025-06-24 21:16:04,761 - pyskl - INFO - Epoch [76][200/1281] lr: 1.246e-02, eta: 10:33:17, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9988, loss_cls: 0.3812, loss: 0.3812 +2025-06-24 21:16:54,148 - pyskl - INFO - Epoch [76][300/1281] lr: 1.244e-02, eta: 10:32:47, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9994, loss_cls: 0.3290, loss: 0.3290 +2025-06-24 21:17:25,480 - pyskl - INFO - Epoch [76][400/1281] lr: 1.242e-02, eta: 10:31:59, time: 0.313, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 0.2919, loss: 0.2919 +2025-06-24 21:18:16,573 - pyskl - INFO - Epoch [76][500/1281] lr: 1.240e-02, eta: 10:31:31, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9325, top5_acc: 1.0000, loss_cls: 0.3793, loss: 0.3793 +2025-06-24 21:18:43,867 - pyskl - INFO - Epoch [76][600/1281] lr: 1.238e-02, eta: 10:30:39, time: 0.273, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 0.3462, loss: 0.3462 +2025-06-24 21:19:32,992 - pyskl - INFO - Epoch [76][700/1281] lr: 1.236e-02, eta: 10:30:09, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 0.3493, loss: 0.3493 +2025-06-24 21:20:22,879 - pyskl - INFO - Epoch [76][800/1281] lr: 1.234e-02, eta: 10:29:39, time: 0.499, data_time: 0.001, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9944, loss_cls: 0.4104, loss: 0.4104 +2025-06-24 21:21:11,993 - pyskl - INFO - Epoch [76][900/1281] lr: 1.232e-02, eta: 10:29:09, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9969, loss_cls: 0.3651, loss: 0.3651 +2025-06-24 21:22:01,529 - pyskl - INFO - Epoch [76][1000/1281] lr: 1.230e-02, eta: 10:28:39, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9306, top5_acc: 0.9994, loss_cls: 0.3494, loss: 0.3494 +2025-06-24 21:22:50,911 - pyskl - INFO - Epoch [76][1100/1281] lr: 1.228e-02, eta: 10:28:09, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9287, top5_acc: 0.9988, loss_cls: 0.4062, loss: 0.4062 +2025-06-24 21:23:40,051 - pyskl - INFO - Epoch [76][1200/1281] lr: 1.225e-02, eta: 10:27:38, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9981, loss_cls: 0.3996, loss: 0.3996 +2025-06-24 21:24:20,240 - pyskl - INFO - Saving checkpoint at 76 epochs +2025-06-24 21:25:19,694 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:25:19,762 - pyskl - INFO - +top1_acc 0.8850 +top5_acc 0.9919 +2025-06-24 21:25:19,762 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:25:19,771 - pyskl - INFO - +mean_acc 0.8523 +2025-06-24 21:25:19,773 - pyskl - INFO - Epoch(val) [76][533] top1_acc: 0.8850, top5_acc: 0.9919, mean_class_accuracy: 0.8523 +2025-06-24 21:26:39,392 - pyskl - INFO - Epoch [77][100/1281] lr: 1.222e-02, eta: 10:26:34, time: 0.796, data_time: 0.191, memory: 4083, top1_acc: 0.9331, top5_acc: 1.0000, loss_cls: 0.3450, loss: 0.3450 +2025-06-24 21:27:28,205 - pyskl - INFO - Epoch [77][200/1281] lr: 1.220e-02, eta: 10:26:03, time: 0.488, data_time: 0.001, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9994, loss_cls: 0.3655, loss: 0.3655 +2025-06-24 21:28:17,459 - pyskl - INFO - Epoch [77][300/1281] lr: 1.218e-02, eta: 10:25:33, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 1.0000, loss_cls: 0.3120, loss: 0.3120 +2025-06-24 21:28:47,005 - pyskl - INFO - Epoch [77][400/1281] lr: 1.216e-02, eta: 10:24:43, time: 0.295, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 1.0000, loss_cls: 0.3424, loss: 0.3424 +2025-06-24 21:29:38,210 - pyskl - INFO - Epoch [77][500/1281] lr: 1.214e-02, eta: 10:24:14, time: 0.512, data_time: 0.001, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9975, loss_cls: 0.3542, loss: 0.3542 +2025-06-24 21:30:05,596 - pyskl - INFO - Epoch [77][600/1281] lr: 1.212e-02, eta: 10:23:23, time: 0.274, data_time: 0.000, memory: 4083, top1_acc: 0.9231, top5_acc: 0.9994, loss_cls: 0.4025, loss: 0.4025 +2025-06-24 21:30:54,555 - pyskl - INFO - Epoch [77][700/1281] lr: 1.210e-02, eta: 10:22:52, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 0.9994, loss_cls: 0.3442, loss: 0.3442 +2025-06-24 21:31:43,544 - pyskl - INFO - Epoch [77][800/1281] lr: 1.207e-02, eta: 10:22:21, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9988, loss_cls: 0.3531, loss: 0.3531 +2025-06-24 21:32:32,751 - pyskl - INFO - Epoch [77][900/1281] lr: 1.205e-02, eta: 10:21:50, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9269, top5_acc: 0.9994, loss_cls: 0.3918, loss: 0.3918 +2025-06-24 21:33:21,728 - pyskl - INFO - Epoch [77][1000/1281] lr: 1.203e-02, eta: 10:21:20, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9981, loss_cls: 0.3671, loss: 0.3671 +2025-06-24 21:34:10,910 - pyskl - INFO - Epoch [77][1100/1281] lr: 1.201e-02, eta: 10:20:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9237, top5_acc: 0.9969, loss_cls: 0.4183, loss: 0.4183 +2025-06-24 21:35:00,409 - pyskl - INFO - Epoch [77][1200/1281] lr: 1.199e-02, eta: 10:20:18, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9981, loss_cls: 0.3532, loss: 0.3532 +2025-06-24 21:35:40,540 - pyskl - INFO - Saving checkpoint at 77 epochs +2025-06-24 21:36:40,950 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:36:41,011 - pyskl - INFO - +top1_acc 0.8975 +top5_acc 0.9925 +2025-06-24 21:36:41,011 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:36:41,019 - pyskl - INFO - +mean_acc 0.8696 +2025-06-24 21:36:41,021 - pyskl - INFO - Epoch(val) [77][533] top1_acc: 0.8975, top5_acc: 0.9925, mean_class_accuracy: 0.8696 +2025-06-24 21:38:01,542 - pyskl - INFO - Epoch [78][100/1281] lr: 1.196e-02, eta: 10:19:14, time: 0.805, data_time: 0.193, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 0.3276, loss: 0.3276 +2025-06-24 21:38:50,596 - pyskl - INFO - Epoch [78][200/1281] lr: 1.194e-02, eta: 10:18:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9319, top5_acc: 0.9988, loss_cls: 0.3571, loss: 0.3571 +2025-06-24 21:39:39,684 - pyskl - INFO - Epoch [78][300/1281] lr: 1.192e-02, eta: 10:18:12, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9994, loss_cls: 0.3167, loss: 0.3167 +2025-06-24 21:40:07,441 - pyskl - INFO - Epoch [78][400/1281] lr: 1.190e-02, eta: 10:17:21, time: 0.278, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9969, loss_cls: 0.3899, loss: 0.3899 +2025-06-24 21:40:58,469 - pyskl - INFO - Epoch [78][500/1281] lr: 1.187e-02, eta: 10:16:52, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9981, loss_cls: 0.3491, loss: 0.3491 +2025-06-24 21:41:29,673 - pyskl - INFO - Epoch [78][600/1281] lr: 1.185e-02, eta: 10:16:04, time: 0.312, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9975, loss_cls: 0.3983, loss: 0.3983 +2025-06-24 21:42:18,439 - pyskl - INFO - Epoch [78][700/1281] lr: 1.183e-02, eta: 10:15:33, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9119, top5_acc: 0.9981, loss_cls: 0.4630, loss: 0.4630 +2025-06-24 21:43:07,399 - pyskl - INFO - Epoch [78][800/1281] lr: 1.181e-02, eta: 10:15:02, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 0.9994, loss_cls: 0.3512, loss: 0.3512 +2025-06-24 21:43:56,323 - pyskl - INFO - Epoch [78][900/1281] lr: 1.179e-02, eta: 10:14:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9981, loss_cls: 0.4142, loss: 0.4142 +2025-06-24 21:44:45,592 - pyskl - INFO - Epoch [78][1000/1281] lr: 1.177e-02, eta: 10:13:59, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9969, loss_cls: 0.3755, loss: 0.3755 +2025-06-24 21:45:34,533 - pyskl - INFO - Epoch [78][1100/1281] lr: 1.175e-02, eta: 10:13:28, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9350, top5_acc: 1.0000, loss_cls: 0.3646, loss: 0.3646 +2025-06-24 21:46:23,638 - pyskl - INFO - Epoch [78][1200/1281] lr: 1.173e-02, eta: 10:12:57, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9175, top5_acc: 0.9975, loss_cls: 0.4092, loss: 0.4092 +2025-06-24 21:47:04,063 - pyskl - INFO - Saving checkpoint at 78 epochs +2025-06-24 21:48:03,031 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:48:03,088 - pyskl - INFO - +top1_acc 0.8801 +top5_acc 0.9910 +2025-06-24 21:48:03,088 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:48:03,095 - pyskl - INFO - +mean_acc 0.8479 +2025-06-24 21:48:03,097 - pyskl - INFO - Epoch(val) [78][533] top1_acc: 0.8801, top5_acc: 0.9910, mean_class_accuracy: 0.8479 +2025-06-24 21:49:22,183 - pyskl - INFO - Epoch [79][100/1281] lr: 1.169e-02, eta: 10:11:51, time: 0.791, data_time: 0.187, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9981, loss_cls: 0.3335, loss: 0.3335 +2025-06-24 21:50:11,474 - pyskl - INFO - Epoch [79][200/1281] lr: 1.167e-02, eta: 10:11:20, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9981, loss_cls: 0.3106, loss: 0.3106 +2025-06-24 21:51:00,769 - pyskl - INFO - Epoch [79][300/1281] lr: 1.165e-02, eta: 10:10:48, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9994, loss_cls: 0.3266, loss: 0.3266 +2025-06-24 21:51:29,135 - pyskl - INFO - Epoch [79][400/1281] lr: 1.163e-02, eta: 10:09:58, time: 0.284, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9994, loss_cls: 0.3060, loss: 0.3060 +2025-06-24 21:52:19,362 - pyskl - INFO - Epoch [79][500/1281] lr: 1.161e-02, eta: 10:09:28, time: 0.502, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9988, loss_cls: 0.3325, loss: 0.3325 +2025-06-24 21:52:50,896 - pyskl - INFO - Epoch [79][600/1281] lr: 1.159e-02, eta: 10:08:40, time: 0.315, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9988, loss_cls: 0.3989, loss: 0.3989 +2025-06-24 21:53:39,819 - pyskl - INFO - Epoch [79][700/1281] lr: 1.157e-02, eta: 10:08:09, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9250, top5_acc: 0.9994, loss_cls: 0.3607, loss: 0.3607 +2025-06-24 21:54:29,102 - pyskl - INFO - Epoch [79][800/1281] lr: 1.155e-02, eta: 10:07:37, time: 0.493, data_time: 0.001, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9981, loss_cls: 0.3109, loss: 0.3109 +2025-06-24 21:55:17,925 - pyskl - INFO - Epoch [79][900/1281] lr: 1.153e-02, eta: 10:07:06, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9981, loss_cls: 0.3277, loss: 0.3277 +2025-06-24 21:56:07,167 - pyskl - INFO - Epoch [79][1000/1281] lr: 1.151e-02, eta: 10:06:34, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9988, loss_cls: 0.3674, loss: 0.3674 +2025-06-24 21:56:56,318 - pyskl - INFO - Epoch [79][1100/1281] lr: 1.149e-02, eta: 10:06:03, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9244, top5_acc: 0.9981, loss_cls: 0.3888, loss: 0.3888 +2025-06-24 21:57:45,551 - pyskl - INFO - Epoch [79][1200/1281] lr: 1.147e-02, eta: 10:05:31, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9988, loss_cls: 0.3717, loss: 0.3717 +2025-06-24 21:58:25,754 - pyskl - INFO - Saving checkpoint at 79 epochs +2025-06-24 21:59:25,571 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 21:59:25,627 - pyskl - INFO - +top1_acc 0.8953 +top5_acc 0.9931 +2025-06-24 21:59:25,627 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 21:59:25,634 - pyskl - INFO - +mean_acc 0.8580 +2025-06-24 21:59:25,636 - pyskl - INFO - Epoch(val) [79][533] top1_acc: 0.8953, top5_acc: 0.9931, mean_class_accuracy: 0.8580 +2025-06-24 22:00:46,444 - pyskl - INFO - Epoch [80][100/1281] lr: 1.143e-02, eta: 10:04:27, time: 0.808, data_time: 0.197, memory: 4083, top1_acc: 0.9431, top5_acc: 1.0000, loss_cls: 0.3066, loss: 0.3066 +2025-06-24 22:01:35,360 - pyskl - INFO - Epoch [80][200/1281] lr: 1.141e-02, eta: 10:03:55, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9994, loss_cls: 0.3513, loss: 0.3513 +2025-06-24 22:02:24,627 - pyskl - INFO - Epoch [80][300/1281] lr: 1.139e-02, eta: 10:03:23, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.2944, loss: 0.2944 +2025-06-24 22:02:54,150 - pyskl - INFO - Epoch [80][400/1281] lr: 1.137e-02, eta: 10:02:34, time: 0.295, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 0.9988, loss_cls: 0.3882, loss: 0.3882 +2025-06-24 22:03:39,750 - pyskl - INFO - Epoch [80][500/1281] lr: 1.135e-02, eta: 10:01:59, time: 0.456, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 0.3610, loss: 0.3610 +2025-06-24 22:04:13,370 - pyskl - INFO - Epoch [80][600/1281] lr: 1.133e-02, eta: 10:01:13, time: 0.336, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9981, loss_cls: 0.3304, loss: 0.3304 +2025-06-24 22:05:02,549 - pyskl - INFO - Epoch [80][700/1281] lr: 1.131e-02, eta: 10:00:42, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9981, loss_cls: 0.2922, loss: 0.2922 +2025-06-24 22:05:51,834 - pyskl - INFO - Epoch [80][800/1281] lr: 1.129e-02, eta: 10:00:10, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.3028, loss: 0.3028 +2025-06-24 22:06:41,044 - pyskl - INFO - Epoch [80][900/1281] lr: 1.127e-02, eta: 9:59:38, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9988, loss_cls: 0.3194, loss: 0.3194 +2025-06-24 22:07:30,247 - pyskl - INFO - Epoch [80][1000/1281] lr: 1.125e-02, eta: 9:59:06, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9981, loss_cls: 0.3156, loss: 0.3156 +2025-06-24 22:08:18,900 - pyskl - INFO - Epoch [80][1100/1281] lr: 1.123e-02, eta: 9:58:34, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9981, loss_cls: 0.3442, loss: 0.3442 +2025-06-24 22:09:08,187 - pyskl - INFO - Epoch [80][1200/1281] lr: 1.121e-02, eta: 9:58:02, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9981, loss_cls: 0.3335, loss: 0.3335 +2025-06-24 22:09:48,456 - pyskl - INFO - Saving checkpoint at 80 epochs +2025-06-24 22:10:48,179 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:10:48,243 - pyskl - INFO - +top1_acc 0.8488 +top5_acc 0.9840 +2025-06-24 22:10:48,244 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:10:48,254 - pyskl - INFO - +mean_acc 0.7970 +2025-06-24 22:10:48,257 - pyskl - INFO - Epoch(val) [80][533] top1_acc: 0.8488, top5_acc: 0.9840, mean_class_accuracy: 0.7970 +2025-06-24 22:12:09,698 - pyskl - INFO - Epoch [81][100/1281] lr: 1.117e-02, eta: 9:56:58, time: 0.814, data_time: 0.199, memory: 4083, top1_acc: 0.9419, top5_acc: 1.0000, loss_cls: 0.3303, loss: 0.3303 +2025-06-24 22:12:58,785 - pyskl - INFO - Epoch [81][200/1281] lr: 1.115e-02, eta: 9:56:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9962, loss_cls: 0.3672, loss: 0.3672 +2025-06-24 22:13:47,153 - pyskl - INFO - Epoch [81][300/1281] lr: 1.113e-02, eta: 9:55:53, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9981, loss_cls: 0.3325, loss: 0.3325 +2025-06-24 22:14:20,726 - pyskl - INFO - Epoch [81][400/1281] lr: 1.111e-02, eta: 9:55:07, time: 0.336, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9981, loss_cls: 0.3463, loss: 0.3463 +2025-06-24 22:15:01,047 - pyskl - INFO - Epoch [81][500/1281] lr: 1.109e-02, eta: 9:54:28, time: 0.403, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 1.0000, loss_cls: 0.3698, loss: 0.3698 +2025-06-24 22:15:36,482 - pyskl - INFO - Epoch [81][600/1281] lr: 1.107e-02, eta: 9:53:44, time: 0.354, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9969, loss_cls: 0.3237, loss: 0.3237 +2025-06-24 22:16:25,836 - pyskl - INFO - Epoch [81][700/1281] lr: 1.105e-02, eta: 9:53:12, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9969, loss_cls: 0.3323, loss: 0.3323 +2025-06-24 22:17:14,920 - pyskl - INFO - Epoch [81][800/1281] lr: 1.103e-02, eta: 9:52:40, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 1.0000, loss_cls: 0.3140, loss: 0.3140 +2025-06-24 22:18:03,716 - pyskl - INFO - Epoch [81][900/1281] lr: 1.101e-02, eta: 9:52:07, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 1.0000, loss_cls: 0.3010, loss: 0.3010 +2025-06-24 22:18:53,059 - pyskl - INFO - Epoch [81][1000/1281] lr: 1.099e-02, eta: 9:51:35, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9988, loss_cls: 0.3021, loss: 0.3021 +2025-06-24 22:19:42,094 - pyskl - INFO - Epoch [81][1100/1281] lr: 1.097e-02, eta: 9:51:03, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9331, top5_acc: 1.0000, loss_cls: 0.3335, loss: 0.3335 +2025-06-24 22:20:31,238 - pyskl - INFO - Epoch [81][1200/1281] lr: 1.095e-02, eta: 9:50:31, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 0.3203, loss: 0.3203 +2025-06-24 22:21:11,568 - pyskl - INFO - Saving checkpoint at 81 epochs +2025-06-24 22:22:10,916 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:22:10,984 - pyskl - INFO - +top1_acc 0.8937 +top5_acc 0.9930 +2025-06-24 22:22:10,984 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:22:10,992 - pyskl - INFO - +mean_acc 0.8604 +2025-06-24 22:22:10,995 - pyskl - INFO - Epoch(val) [81][533] top1_acc: 0.8937, top5_acc: 0.9930, mean_class_accuracy: 0.8604 +2025-06-24 22:23:30,531 - pyskl - INFO - Epoch [82][100/1281] lr: 1.091e-02, eta: 9:49:24, time: 0.795, data_time: 0.199, memory: 4083, top1_acc: 0.9469, top5_acc: 1.0000, loss_cls: 0.3178, loss: 0.3178 +2025-06-24 22:24:19,850 - pyskl - INFO - Epoch [82][200/1281] lr: 1.089e-02, eta: 9:48:52, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9400, top5_acc: 0.9994, loss_cls: 0.3322, loss: 0.3322 +2025-06-24 22:25:08,071 - pyskl - INFO - Epoch [82][300/1281] lr: 1.087e-02, eta: 9:48:19, time: 0.482, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9988, loss_cls: 0.3270, loss: 0.3270 +2025-06-24 22:25:41,588 - pyskl - INFO - Epoch [82][400/1281] lr: 1.085e-02, eta: 9:47:33, time: 0.335, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.2989, loss: 0.2989 +2025-06-24 22:26:21,552 - pyskl - INFO - Epoch [82][500/1281] lr: 1.083e-02, eta: 9:46:53, time: 0.400, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9981, loss_cls: 0.3426, loss: 0.3426 +2025-06-24 22:26:57,078 - pyskl - INFO - Epoch [82][600/1281] lr: 1.081e-02, eta: 9:46:09, time: 0.355, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9988, loss_cls: 0.3233, loss: 0.3233 +2025-06-24 22:27:45,992 - pyskl - INFO - Epoch [82][700/1281] lr: 1.079e-02, eta: 9:45:36, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9981, loss_cls: 0.3440, loss: 0.3440 +2025-06-24 22:28:35,233 - pyskl - INFO - Epoch [82][800/1281] lr: 1.077e-02, eta: 9:45:04, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9962, loss_cls: 0.3805, loss: 0.3805 +2025-06-24 22:29:24,505 - pyskl - INFO - Epoch [82][900/1281] lr: 1.075e-02, eta: 9:44:32, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9406, top5_acc: 0.9988, loss_cls: 0.3181, loss: 0.3181 +2025-06-24 22:30:13,969 - pyskl - INFO - Epoch [82][1000/1281] lr: 1.073e-02, eta: 9:43:59, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9981, loss_cls: 0.3653, loss: 0.3653 +2025-06-24 22:31:02,862 - pyskl - INFO - Epoch [82][1100/1281] lr: 1.071e-02, eta: 9:43:27, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9994, loss_cls: 0.3201, loss: 0.3201 +2025-06-24 22:31:51,655 - pyskl - INFO - Epoch [82][1200/1281] lr: 1.069e-02, eta: 9:42:54, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9300, top5_acc: 0.9975, loss_cls: 0.3832, loss: 0.3832 +2025-06-24 22:32:31,840 - pyskl - INFO - Saving checkpoint at 82 epochs +2025-06-24 22:33:31,841 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:33:31,910 - pyskl - INFO - +top1_acc 0.8892 +top5_acc 0.9927 +2025-06-24 22:33:31,910 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:33:31,918 - pyskl - INFO - +mean_acc 0.8601 +2025-06-24 22:33:31,920 - pyskl - INFO - Epoch(val) [82][533] top1_acc: 0.8892, top5_acc: 0.9927, mean_class_accuracy: 0.8601 +2025-06-24 22:34:52,695 - pyskl - INFO - Epoch [83][100/1281] lr: 1.065e-02, eta: 9:41:48, time: 0.808, data_time: 0.198, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9994, loss_cls: 0.3566, loss: 0.3566 +2025-06-24 22:35:42,148 - pyskl - INFO - Epoch [83][200/1281] lr: 1.063e-02, eta: 9:41:15, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2743, loss: 0.2743 +2025-06-24 22:36:28,601 - pyskl - INFO - Epoch [83][300/1281] lr: 1.061e-02, eta: 9:40:41, time: 0.465, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9994, loss_cls: 0.2746, loss: 0.2746 +2025-06-24 22:37:07,122 - pyskl - INFO - Epoch [83][400/1281] lr: 1.059e-02, eta: 9:39:59, time: 0.385, data_time: 0.000, memory: 4083, top1_acc: 0.9456, top5_acc: 0.9988, loss_cls: 0.3200, loss: 0.3200 +2025-06-24 22:37:42,476 - pyskl - INFO - Epoch [83][500/1281] lr: 1.057e-02, eta: 9:39:15, time: 0.354, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 1.0000, loss_cls: 0.3020, loss: 0.3020 +2025-06-24 22:38:20,704 - pyskl - INFO - Epoch [83][600/1281] lr: 1.055e-02, eta: 9:38:33, time: 0.382, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 1.0000, loss_cls: 0.3323, loss: 0.3323 +2025-06-24 22:39:09,951 - pyskl - INFO - Epoch [83][700/1281] lr: 1.053e-02, eta: 9:38:01, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9975, loss_cls: 0.3228, loss: 0.3228 +2025-06-24 22:39:59,328 - pyskl - INFO - Epoch [83][800/1281] lr: 1.051e-02, eta: 9:37:28, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9988, loss_cls: 0.3101, loss: 0.3101 +2025-06-24 22:40:48,832 - pyskl - INFO - Epoch [83][900/1281] lr: 1.049e-02, eta: 9:36:56, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9337, top5_acc: 0.9981, loss_cls: 0.3313, loss: 0.3313 +2025-06-24 22:41:38,050 - pyskl - INFO - Epoch [83][1000/1281] lr: 1.047e-02, eta: 9:36:23, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9394, top5_acc: 1.0000, loss_cls: 0.3233, loss: 0.3233 +2025-06-24 22:42:27,059 - pyskl - INFO - Epoch [83][1100/1281] lr: 1.045e-02, eta: 9:35:50, time: 0.490, data_time: 0.001, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.3033, loss: 0.3033 +2025-06-24 22:43:16,026 - pyskl - INFO - Epoch [83][1200/1281] lr: 1.043e-02, eta: 9:35:17, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9981, loss_cls: 0.2742, loss: 0.2742 +2025-06-24 22:43:56,381 - pyskl - INFO - Saving checkpoint at 83 epochs +2025-06-24 22:44:56,293 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:44:56,361 - pyskl - INFO - +top1_acc 0.9007 +top5_acc 0.9947 +2025-06-24 22:44:56,361 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:44:56,369 - pyskl - INFO - +mean_acc 0.8589 +2025-06-24 22:44:56,373 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_71.pth was removed +2025-06-24 22:44:56,575 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_83.pth. +2025-06-24 22:44:56,575 - pyskl - INFO - Best top1_acc is 0.9007 at 83 epoch. +2025-06-24 22:44:56,578 - pyskl - INFO - Epoch(val) [83][533] top1_acc: 0.9007, top5_acc: 0.9947, mean_class_accuracy: 0.8589 +2025-06-24 22:46:16,267 - pyskl - INFO - Epoch [84][100/1281] lr: 1.040e-02, eta: 9:34:10, time: 0.797, data_time: 0.190, memory: 4083, top1_acc: 0.9656, top5_acc: 0.9988, loss_cls: 0.2786, loss: 0.2786 +2025-06-24 22:47:05,533 - pyskl - INFO - Epoch [84][200/1281] lr: 1.038e-02, eta: 9:33:37, time: 0.493, data_time: 0.001, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 0.2885, loss: 0.2885 +2025-06-24 22:47:50,769 - pyskl - INFO - Epoch [84][300/1281] lr: 1.036e-02, eta: 9:33:01, time: 0.452, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 0.2705, loss: 0.2705 +2025-06-24 22:48:31,705 - pyskl - INFO - Epoch [84][400/1281] lr: 1.034e-02, eta: 9:32:21, time: 0.409, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9994, loss_cls: 0.3077, loss: 0.3077 +2025-06-24 22:49:04,456 - pyskl - INFO - Epoch [84][500/1281] lr: 1.031e-02, eta: 9:31:35, time: 0.328, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9994, loss_cls: 0.3266, loss: 0.3266 +2025-06-24 22:49:43,975 - pyskl - INFO - Epoch [84][600/1281] lr: 1.029e-02, eta: 9:30:54, time: 0.395, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 0.2771, loss: 0.2771 +2025-06-24 22:50:33,013 - pyskl - INFO - Epoch [84][700/1281] lr: 1.027e-02, eta: 9:30:21, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9981, loss_cls: 0.3057, loss: 0.3057 +2025-06-24 22:51:22,295 - pyskl - INFO - Epoch [84][800/1281] lr: 1.025e-02, eta: 9:29:48, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9994, loss_cls: 0.3161, loss: 0.3161 +2025-06-24 22:52:11,081 - pyskl - INFO - Epoch [84][900/1281] lr: 1.023e-02, eta: 9:29:14, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9988, loss_cls: 0.3079, loss: 0.3079 +2025-06-24 22:53:00,549 - pyskl - INFO - Epoch [84][1000/1281] lr: 1.021e-02, eta: 9:28:42, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 0.2864, loss: 0.2864 +2025-06-24 22:53:49,587 - pyskl - INFO - Epoch [84][1100/1281] lr: 1.019e-02, eta: 9:28:08, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9988, loss_cls: 0.3102, loss: 0.3102 +2025-06-24 22:54:38,745 - pyskl - INFO - Epoch [84][1200/1281] lr: 1.017e-02, eta: 9:27:35, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 0.2932, loss: 0.2932 +2025-06-24 22:55:18,987 - pyskl - INFO - Saving checkpoint at 84 epochs +2025-06-24 22:56:18,251 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 22:56:18,307 - pyskl - INFO - +top1_acc 0.8875 +top5_acc 0.9938 +2025-06-24 22:56:18,307 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 22:56:18,314 - pyskl - INFO - +mean_acc 0.8450 +2025-06-24 22:56:18,316 - pyskl - INFO - Epoch(val) [84][533] top1_acc: 0.8875, top5_acc: 0.9938, mean_class_accuracy: 0.8450 +2025-06-24 22:57:38,357 - pyskl - INFO - Epoch [85][100/1281] lr: 1.014e-02, eta: 9:26:28, time: 0.800, data_time: 0.196, memory: 4083, top1_acc: 0.9581, top5_acc: 1.0000, loss_cls: 0.2658, loss: 0.2658 +2025-06-24 22:58:27,421 - pyskl - INFO - Epoch [85][200/1281] lr: 1.012e-02, eta: 9:25:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2455, loss: 0.2455 +2025-06-24 22:59:11,518 - pyskl - INFO - Epoch [85][300/1281] lr: 1.010e-02, eta: 9:25:17, time: 0.441, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9988, loss_cls: 0.2789, loss: 0.2789 +2025-06-24 22:59:55,262 - pyskl - INFO - Epoch [85][400/1281] lr: 1.008e-02, eta: 9:24:40, time: 0.437, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9981, loss_cls: 0.3244, loss: 0.3244 +2025-06-24 23:00:25,379 - pyskl - INFO - Epoch [85][500/1281] lr: 1.006e-02, eta: 9:23:52, time: 0.301, data_time: 0.000, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9994, loss_cls: 0.2850, loss: 0.2850 +2025-06-24 23:01:05,537 - pyskl - INFO - Epoch [85][600/1281] lr: 1.004e-02, eta: 9:23:11, time: 0.402, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 1.0000, loss_cls: 0.3181, loss: 0.3181 +2025-06-24 23:01:54,741 - pyskl - INFO - Epoch [85][700/1281] lr: 1.002e-02, eta: 9:22:38, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9988, loss_cls: 0.3060, loss: 0.3060 +2025-06-24 23:02:44,103 - pyskl - INFO - Epoch [85][800/1281] lr: 9.998e-03, eta: 9:22:05, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 0.3027, loss: 0.3027 +2025-06-24 23:03:33,277 - pyskl - INFO - Epoch [85][900/1281] lr: 9.978e-03, eta: 9:21:31, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9994, loss_cls: 0.3381, loss: 0.3381 +2025-06-24 23:04:22,560 - pyskl - INFO - Epoch [85][1000/1281] lr: 9.958e-03, eta: 9:20:58, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9363, top5_acc: 0.9981, loss_cls: 0.3644, loss: 0.3644 +2025-06-24 23:05:11,668 - pyskl - INFO - Epoch [85][1100/1281] lr: 9.937e-03, eta: 9:20:24, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9450, top5_acc: 0.9988, loss_cls: 0.3159, loss: 0.3159 +2025-06-24 23:06:00,594 - pyskl - INFO - Epoch [85][1200/1281] lr: 9.917e-03, eta: 9:19:51, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9988, loss_cls: 0.2793, loss: 0.2793 +2025-06-24 23:06:40,947 - pyskl - INFO - Saving checkpoint at 85 epochs +2025-06-24 23:07:40,910 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:07:40,977 - pyskl - INFO - +top1_acc 0.9049 +top5_acc 0.9923 +2025-06-24 23:07:40,977 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:07:40,985 - pyskl - INFO - +mean_acc 0.8724 +2025-06-24 23:07:40,989 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_83.pth was removed +2025-06-24 23:07:41,187 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_85.pth. +2025-06-24 23:07:41,187 - pyskl - INFO - Best top1_acc is 0.9049 at 85 epoch. +2025-06-24 23:07:41,190 - pyskl - INFO - Epoch(val) [85][533] top1_acc: 0.9049, top5_acc: 0.9923, mean_class_accuracy: 0.8724 +2025-06-24 23:09:00,901 - pyskl - INFO - Epoch [86][100/1281] lr: 9.881e-03, eta: 9:18:43, time: 0.797, data_time: 0.191, memory: 4083, top1_acc: 0.9437, top5_acc: 1.0000, loss_cls: 0.2981, loss: 0.2981 +2025-06-24 23:09:50,244 - pyskl - INFO - Epoch [86][200/1281] lr: 9.861e-03, eta: 9:18:10, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 0.2886, loss: 0.2886 +2025-06-24 23:10:33,110 - pyskl - INFO - Epoch [86][300/1281] lr: 9.841e-03, eta: 9:17:31, time: 0.429, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 0.9994, loss_cls: 0.2495, loss: 0.2495 +2025-06-24 23:11:19,238 - pyskl - INFO - Epoch [86][400/1281] lr: 9.821e-03, eta: 9:16:55, time: 0.461, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9994, loss_cls: 0.2667, loss: 0.2667 +2025-06-24 23:11:47,052 - pyskl - INFO - Epoch [86][500/1281] lr: 9.801e-03, eta: 9:16:05, time: 0.278, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 0.2634, loss: 0.2634 +2025-06-24 23:12:28,449 - pyskl - INFO - Epoch [86][600/1281] lr: 9.781e-03, eta: 9:15:26, time: 0.414, data_time: 0.000, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9994, loss_cls: 0.2988, loss: 0.2988 +2025-06-24 23:13:17,527 - pyskl - INFO - Epoch [86][700/1281] lr: 9.762e-03, eta: 9:14:52, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9344, top5_acc: 0.9981, loss_cls: 0.3410, loss: 0.3410 +2025-06-24 23:14:06,566 - pyskl - INFO - Epoch [86][800/1281] lr: 9.742e-03, eta: 9:14:18, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 1.0000, loss_cls: 0.3150, loss: 0.3150 +2025-06-24 23:14:55,607 - pyskl - INFO - Epoch [86][900/1281] lr: 9.722e-03, eta: 9:13:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9375, top5_acc: 0.9988, loss_cls: 0.3589, loss: 0.3589 +2025-06-24 23:15:44,727 - pyskl - INFO - Epoch [86][1000/1281] lr: 9.702e-03, eta: 9:13:11, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9263, top5_acc: 0.9994, loss_cls: 0.3882, loss: 0.3882 +2025-06-24 23:16:33,631 - pyskl - INFO - Epoch [86][1100/1281] lr: 9.682e-03, eta: 9:12:37, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9981, loss_cls: 0.3374, loss: 0.3374 +2025-06-24 23:17:22,509 - pyskl - INFO - Epoch [86][1200/1281] lr: 9.662e-03, eta: 9:12:03, time: 0.489, data_time: 0.001, memory: 4083, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 0.2928, loss: 0.2928 +2025-06-24 23:18:02,817 - pyskl - INFO - Saving checkpoint at 86 epochs +2025-06-24 23:19:01,919 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:19:01,976 - pyskl - INFO - +top1_acc 0.9006 +top5_acc 0.9928 +2025-06-24 23:19:01,976 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:19:01,983 - pyskl - INFO - +mean_acc 0.8635 +2025-06-24 23:19:01,985 - pyskl - INFO - Epoch(val) [86][533] top1_acc: 0.9006, top5_acc: 0.9928, mean_class_accuracy: 0.8635 +2025-06-24 23:20:22,103 - pyskl - INFO - Epoch [87][100/1281] lr: 9.626e-03, eta: 9:10:55, time: 0.801, data_time: 0.194, memory: 4083, top1_acc: 0.9506, top5_acc: 1.0000, loss_cls: 0.2929, loss: 0.2929 +2025-06-24 23:21:11,317 - pyskl - INFO - Epoch [87][200/1281] lr: 9.606e-03, eta: 9:10:21, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 0.2650, loss: 0.2650 +2025-06-24 23:21:53,576 - pyskl - INFO - Epoch [87][300/1281] lr: 9.586e-03, eta: 9:09:42, time: 0.423, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9994, loss_cls: 0.2769, loss: 0.2769 +2025-06-24 23:22:41,957 - pyskl - INFO - Epoch [87][400/1281] lr: 9.566e-03, eta: 9:09:08, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 1.0000, loss_cls: 0.2722, loss: 0.2722 +2025-06-24 23:23:07,966 - pyskl - INFO - Epoch [87][500/1281] lr: 9.546e-03, eta: 9:08:17, time: 0.260, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2431, loss: 0.2431 +2025-06-24 23:23:51,383 - pyskl - INFO - Epoch [87][600/1281] lr: 9.527e-03, eta: 9:07:39, time: 0.434, data_time: 0.001, memory: 4083, top1_acc: 0.9481, top5_acc: 0.9981, loss_cls: 0.3093, loss: 0.3093 +2025-06-24 23:24:41,031 - pyskl - INFO - Epoch [87][700/1281] lr: 9.507e-03, eta: 9:07:05, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9988, loss_cls: 0.3080, loss: 0.3080 +2025-06-24 23:25:30,466 - pyskl - INFO - Epoch [87][800/1281] lr: 9.487e-03, eta: 9:06:31, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9988, loss_cls: 0.2850, loss: 0.2850 +2025-06-24 23:26:19,627 - pyskl - INFO - Epoch [87][900/1281] lr: 9.467e-03, eta: 9:05:57, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9387, top5_acc: 0.9981, loss_cls: 0.3288, loss: 0.3288 +2025-06-24 23:27:08,999 - pyskl - INFO - Epoch [87][1000/1281] lr: 9.447e-03, eta: 9:05:24, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9444, top5_acc: 0.9988, loss_cls: 0.3206, loss: 0.3206 +2025-06-24 23:27:57,965 - pyskl - INFO - Epoch [87][1100/1281] lr: 9.427e-03, eta: 9:04:49, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9275, top5_acc: 0.9969, loss_cls: 0.3689, loss: 0.3689 +2025-06-24 23:28:46,997 - pyskl - INFO - Epoch [87][1200/1281] lr: 9.408e-03, eta: 9:04:15, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9381, top5_acc: 0.9988, loss_cls: 0.3261, loss: 0.3261 +2025-06-24 23:29:27,435 - pyskl - INFO - Saving checkpoint at 87 epochs +2025-06-24 23:30:27,095 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:30:27,151 - pyskl - INFO - +top1_acc 0.9061 +top5_acc 0.9931 +2025-06-24 23:30:27,151 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:30:27,158 - pyskl - INFO - +mean_acc 0.8772 +2025-06-24 23:30:27,162 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_85.pth was removed +2025-06-24 23:30:27,365 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_87.pth. +2025-06-24 23:30:27,365 - pyskl - INFO - Best top1_acc is 0.9061 at 87 epoch. +2025-06-24 23:30:27,369 - pyskl - INFO - Epoch(val) [87][533] top1_acc: 0.9061, top5_acc: 0.9931, mean_class_accuracy: 0.8772 +2025-06-24 23:31:47,922 - pyskl - INFO - Epoch [88][100/1281] lr: 9.372e-03, eta: 9:03:07, time: 0.805, data_time: 0.187, memory: 4083, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 0.2604, loss: 0.2604 +2025-06-24 23:32:37,321 - pyskl - INFO - Epoch [88][200/1281] lr: 9.352e-03, eta: 9:02:33, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 1.0000, loss_cls: 0.2723, loss: 0.2723 +2025-06-24 23:33:15,349 - pyskl - INFO - Epoch [88][300/1281] lr: 9.332e-03, eta: 9:01:51, time: 0.380, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 0.9994, loss_cls: 0.2824, loss: 0.2824 +2025-06-24 23:34:06,310 - pyskl - INFO - Epoch [88][400/1281] lr: 9.312e-03, eta: 9:01:18, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9988, loss_cls: 0.2721, loss: 0.2721 +2025-06-24 23:34:30,571 - pyskl - INFO - Epoch [88][500/1281] lr: 9.293e-03, eta: 9:00:26, time: 0.243, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9994, loss_cls: 0.3124, loss: 0.3124 +2025-06-24 23:35:15,310 - pyskl - INFO - Epoch [88][600/1281] lr: 9.273e-03, eta: 8:59:49, time: 0.447, data_time: 0.000, memory: 4083, top1_acc: 0.9437, top5_acc: 0.9994, loss_cls: 0.3383, loss: 0.3383 +2025-06-24 23:36:04,160 - pyskl - INFO - Epoch [88][700/1281] lr: 9.253e-03, eta: 8:59:14, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9413, top5_acc: 0.9994, loss_cls: 0.3222, loss: 0.3222 +2025-06-24 23:36:53,265 - pyskl - INFO - Epoch [88][800/1281] lr: 9.233e-03, eta: 8:58:40, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 1.0000, loss_cls: 0.3181, loss: 0.3181 +2025-06-24 23:37:42,592 - pyskl - INFO - Epoch [88][900/1281] lr: 9.214e-03, eta: 8:58:06, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9994, loss_cls: 0.3055, loss: 0.3055 +2025-06-24 23:38:32,186 - pyskl - INFO - Epoch [88][1000/1281] lr: 9.194e-03, eta: 8:57:32, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9525, top5_acc: 0.9988, loss_cls: 0.2717, loss: 0.2717 +2025-06-24 23:39:21,348 - pyskl - INFO - Epoch [88][1100/1281] lr: 9.174e-03, eta: 8:56:58, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.9500, top5_acc: 1.0000, loss_cls: 0.2998, loss: 0.2998 +2025-06-24 23:40:10,819 - pyskl - INFO - Epoch [88][1200/1281] lr: 9.155e-03, eta: 8:56:24, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 1.0000, loss_cls: 0.2895, loss: 0.2895 +2025-06-24 23:40:51,064 - pyskl - INFO - Saving checkpoint at 88 epochs +2025-06-24 23:41:49,874 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:41:49,931 - pyskl - INFO - +top1_acc 0.9036 +top5_acc 0.9937 +2025-06-24 23:41:49,931 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:41:49,938 - pyskl - INFO - +mean_acc 0.8735 +2025-06-24 23:41:49,941 - pyskl - INFO - Epoch(val) [88][533] top1_acc: 0.9036, top5_acc: 0.9937, mean_class_accuracy: 0.8735 +2025-06-24 23:43:10,390 - pyskl - INFO - Epoch [89][100/1281] lr: 9.119e-03, eta: 8:55:15, time: 0.804, data_time: 0.192, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.2226, loss: 0.2226 +2025-06-24 23:43:59,535 - pyskl - INFO - Epoch [89][200/1281] lr: 9.099e-03, eta: 8:54:41, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 1.0000, loss_cls: 0.2426, loss: 0.2426 +2025-06-24 23:44:36,543 - pyskl - INFO - Epoch [89][300/1281] lr: 9.080e-03, eta: 8:53:58, time: 0.370, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2362, loss: 0.2362 +2025-06-24 23:45:27,886 - pyskl - INFO - Epoch [89][400/1281] lr: 9.060e-03, eta: 8:53:25, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2123, loss: 0.2123 +2025-06-24 23:45:52,383 - pyskl - INFO - Epoch [89][500/1281] lr: 9.040e-03, eta: 8:52:33, time: 0.245, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 1.0000, loss_cls: 0.2678, loss: 0.2678 +2025-06-24 23:46:38,934 - pyskl - INFO - Epoch [89][600/1281] lr: 9.021e-03, eta: 8:51:57, time: 0.465, data_time: 0.000, memory: 4083, top1_acc: 0.9475, top5_acc: 0.9994, loss_cls: 0.2958, loss: 0.2958 +2025-06-24 23:47:28,131 - pyskl - INFO - Epoch [89][700/1281] lr: 9.001e-03, eta: 8:51:23, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9425, top5_acc: 0.9988, loss_cls: 0.3164, loss: 0.3164 +2025-06-24 23:48:17,346 - pyskl - INFO - Epoch [89][800/1281] lr: 8.982e-03, eta: 8:50:48, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2770, loss: 0.2770 +2025-06-24 23:49:06,452 - pyskl - INFO - Epoch [89][900/1281] lr: 8.962e-03, eta: 8:50:14, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2686, loss: 0.2686 +2025-06-24 23:49:55,513 - pyskl - INFO - Epoch [89][1000/1281] lr: 8.942e-03, eta: 8:49:39, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 1.0000, loss_cls: 0.2815, loss: 0.2815 +2025-06-24 23:50:44,671 - pyskl - INFO - Epoch [89][1100/1281] lr: 8.923e-03, eta: 8:49:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9419, top5_acc: 0.9988, loss_cls: 0.3200, loss: 0.3200 +2025-06-24 23:51:33,825 - pyskl - INFO - Epoch [89][1200/1281] lr: 8.903e-03, eta: 8:48:30, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 0.2762, loss: 0.2762 +2025-06-24 23:52:14,154 - pyskl - INFO - Saving checkpoint at 89 epochs +2025-06-24 23:53:13,119 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-24 23:53:13,184 - pyskl - INFO - +top1_acc 0.9026 +top5_acc 0.9934 +2025-06-24 23:53:13,184 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-24 23:53:13,191 - pyskl - INFO - +mean_acc 0.8732 +2025-06-24 23:53:13,193 - pyskl - INFO - Epoch(val) [89][533] top1_acc: 0.9026, top5_acc: 0.9934, mean_class_accuracy: 0.8732 +2025-06-24 23:54:33,163 - pyskl - INFO - Epoch [90][100/1281] lr: 8.868e-03, eta: 8:47:21, time: 0.800, data_time: 0.192, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2705, loss: 0.2705 +2025-06-24 23:55:22,960 - pyskl - INFO - Epoch [90][200/1281] lr: 8.848e-03, eta: 8:46:47, time: 0.498, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 1.0000, loss_cls: 0.2680, loss: 0.2680 +2025-06-24 23:55:57,971 - pyskl - INFO - Epoch [90][300/1281] lr: 8.829e-03, eta: 8:46:02, time: 0.350, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9994, loss_cls: 0.2467, loss: 0.2467 +2025-06-24 23:56:49,097 - pyskl - INFO - Epoch [90][400/1281] lr: 8.809e-03, eta: 8:45:29, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9988, loss_cls: 0.2854, loss: 0.2854 +2025-06-24 23:57:13,552 - pyskl - INFO - Epoch [90][500/1281] lr: 8.790e-03, eta: 8:44:38, time: 0.245, data_time: 0.001, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9981, loss_cls: 0.2457, loss: 0.2457 +2025-06-24 23:58:00,102 - pyskl - INFO - Epoch [90][600/1281] lr: 8.770e-03, eta: 8:44:01, time: 0.465, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 0.9994, loss_cls: 0.2780, loss: 0.2780 +2025-06-24 23:58:49,389 - pyskl - INFO - Epoch [90][700/1281] lr: 8.751e-03, eta: 8:43:27, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 0.2882, loss: 0.2882 +2025-06-24 23:59:38,692 - pyskl - INFO - Epoch [90][800/1281] lr: 8.731e-03, eta: 8:42:52, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9369, top5_acc: 0.9994, loss_cls: 0.3262, loss: 0.3262 +2025-06-25 00:00:27,654 - pyskl - INFO - Epoch [90][900/1281] lr: 8.712e-03, eta: 8:42:17, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 0.9994, loss_cls: 0.2803, loss: 0.2803 +2025-06-25 00:01:16,822 - pyskl - INFO - Epoch [90][1000/1281] lr: 8.692e-03, eta: 8:41:42, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9988, loss_cls: 0.2661, loss: 0.2661 +2025-06-25 00:02:06,053 - pyskl - INFO - Epoch [90][1100/1281] lr: 8.673e-03, eta: 8:41:07, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 0.9513, top5_acc: 0.9988, loss_cls: 0.2691, loss: 0.2691 +2025-06-25 00:02:55,346 - pyskl - INFO - Epoch [90][1200/1281] lr: 8.653e-03, eta: 8:40:33, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9994, loss_cls: 0.2616, loss: 0.2616 +2025-06-25 00:03:35,620 - pyskl - INFO - Saving checkpoint at 90 epochs +2025-06-25 00:04:34,035 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:04:34,096 - pyskl - INFO - +top1_acc 0.8904 +top5_acc 0.9939 +2025-06-25 00:04:34,096 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:04:34,103 - pyskl - INFO - +mean_acc 0.8517 +2025-06-25 00:04:34,104 - pyskl - INFO - Epoch(val) [90][533] top1_acc: 0.8904, top5_acc: 0.9939, mean_class_accuracy: 0.8517 +2025-06-25 00:05:54,376 - pyskl - INFO - Epoch [91][100/1281] lr: 8.618e-03, eta: 8:39:24, time: 0.803, data_time: 0.190, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9994, loss_cls: 0.2846, loss: 0.2846 +2025-06-25 00:06:43,427 - pyskl - INFO - Epoch [91][200/1281] lr: 8.599e-03, eta: 8:38:49, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 0.2301, loss: 0.2301 +2025-06-25 00:07:18,538 - pyskl - INFO - Epoch [91][300/1281] lr: 8.579e-03, eta: 8:38:04, time: 0.351, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 0.2301, loss: 0.2301 +2025-06-25 00:08:09,597 - pyskl - INFO - Epoch [91][400/1281] lr: 8.560e-03, eta: 8:37:31, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 0.2640, loss: 0.2640 +2025-06-25 00:08:34,576 - pyskl - INFO - Epoch [91][500/1281] lr: 8.540e-03, eta: 8:36:40, time: 0.250, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 1.0000, loss_cls: 0.2706, loss: 0.2706 +2025-06-25 00:09:22,039 - pyskl - INFO - Epoch [91][600/1281] lr: 8.521e-03, eta: 8:36:04, time: 0.475, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9988, loss_cls: 0.2850, loss: 0.2850 +2025-06-25 00:10:11,028 - pyskl - INFO - Epoch [91][700/1281] lr: 8.502e-03, eta: 8:35:29, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9988, loss_cls: 0.2872, loss: 0.2872 +2025-06-25 00:11:00,216 - pyskl - INFO - Epoch [91][800/1281] lr: 8.482e-03, eta: 8:34:54, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2516, loss: 0.2516 +2025-06-25 00:11:49,280 - pyskl - INFO - Epoch [91][900/1281] lr: 8.463e-03, eta: 8:34:18, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9994, loss_cls: 0.2575, loss: 0.2575 +2025-06-25 00:12:38,327 - pyskl - INFO - Epoch [91][1000/1281] lr: 8.444e-03, eta: 8:33:43, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2542, loss: 0.2542 +2025-06-25 00:13:27,254 - pyskl - INFO - Epoch [91][1100/1281] lr: 8.424e-03, eta: 8:33:08, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 1.0000, loss_cls: 0.2964, loss: 0.2964 +2025-06-25 00:14:16,249 - pyskl - INFO - Epoch [91][1200/1281] lr: 8.405e-03, eta: 8:32:33, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 0.9981, loss_cls: 0.2322, loss: 0.2322 +2025-06-25 00:14:56,276 - pyskl - INFO - Saving checkpoint at 91 epochs +2025-06-25 00:15:55,307 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:15:55,377 - pyskl - INFO - +top1_acc 0.9014 +top5_acc 0.9925 +2025-06-25 00:15:55,377 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:15:55,385 - pyskl - INFO - +mean_acc 0.8636 +2025-06-25 00:15:55,387 - pyskl - INFO - Epoch(val) [91][533] top1_acc: 0.9014, top5_acc: 0.9925, mean_class_accuracy: 0.8636 +2025-06-25 00:17:14,349 - pyskl - INFO - Epoch [92][100/1281] lr: 8.370e-03, eta: 8:31:23, time: 0.790, data_time: 0.186, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2725, loss: 0.2725 +2025-06-25 00:18:03,332 - pyskl - INFO - Epoch [92][200/1281] lr: 8.351e-03, eta: 8:30:48, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9537, top5_acc: 1.0000, loss_cls: 0.2499, loss: 0.2499 +2025-06-25 00:18:38,766 - pyskl - INFO - Epoch [92][300/1281] lr: 8.332e-03, eta: 8:30:04, time: 0.354, data_time: 0.000, memory: 4083, top1_acc: 0.9431, top5_acc: 0.9988, loss_cls: 0.3065, loss: 0.3065 +2025-06-25 00:19:29,850 - pyskl - INFO - Epoch [92][400/1281] lr: 8.312e-03, eta: 8:29:30, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9994, loss_cls: 0.2431, loss: 0.2431 +2025-06-25 00:19:54,425 - pyskl - INFO - Epoch [92][500/1281] lr: 8.293e-03, eta: 8:28:39, time: 0.246, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 1.0000, loss_cls: 0.2311, loss: 0.2311 +2025-06-25 00:20:41,271 - pyskl - INFO - Epoch [92][600/1281] lr: 8.274e-03, eta: 8:28:02, time: 0.468, data_time: 0.000, memory: 4083, top1_acc: 0.9469, top5_acc: 0.9981, loss_cls: 0.3027, loss: 0.3027 +2025-06-25 00:21:30,508 - pyskl - INFO - Epoch [92][700/1281] lr: 8.255e-03, eta: 8:27:27, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2503, loss: 0.2503 +2025-06-25 00:22:19,600 - pyskl - INFO - Epoch [92][800/1281] lr: 8.235e-03, eta: 8:26:51, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9981, loss_cls: 0.2998, loss: 0.2998 +2025-06-25 00:23:08,433 - pyskl - INFO - Epoch [92][900/1281] lr: 8.216e-03, eta: 8:26:16, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 1.0000, loss_cls: 0.2114, loss: 0.2114 +2025-06-25 00:23:57,637 - pyskl - INFO - Epoch [92][1000/1281] lr: 8.197e-03, eta: 8:25:41, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9569, top5_acc: 0.9988, loss_cls: 0.2523, loss: 0.2523 +2025-06-25 00:24:46,746 - pyskl - INFO - Epoch [92][1100/1281] lr: 8.178e-03, eta: 8:25:05, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 1.0000, loss_cls: 0.2469, loss: 0.2469 +2025-06-25 00:25:35,971 - pyskl - INFO - Epoch [92][1200/1281] lr: 8.159e-03, eta: 8:24:30, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9356, top5_acc: 0.9969, loss_cls: 0.3216, loss: 0.3216 +2025-06-25 00:26:16,455 - pyskl - INFO - Saving checkpoint at 92 epochs +2025-06-25 00:27:15,041 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:27:15,109 - pyskl - INFO - +top1_acc 0.9028 +top5_acc 0.9931 +2025-06-25 00:27:15,109 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:27:15,117 - pyskl - INFO - +mean_acc 0.8768 +2025-06-25 00:27:15,119 - pyskl - INFO - Epoch(val) [92][533] top1_acc: 0.9028, top5_acc: 0.9931, mean_class_accuracy: 0.8768 +2025-06-25 00:28:34,061 - pyskl - INFO - Epoch [93][100/1281] lr: 8.124e-03, eta: 8:23:20, time: 0.789, data_time: 0.190, memory: 4083, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 0.2186, loss: 0.2186 +2025-06-25 00:29:23,404 - pyskl - INFO - Epoch [93][200/1281] lr: 8.105e-03, eta: 8:22:44, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 0.2393, loss: 0.2393 +2025-06-25 00:29:59,918 - pyskl - INFO - Epoch [93][300/1281] lr: 8.086e-03, eta: 8:22:01, time: 0.365, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 0.9988, loss_cls: 0.2300, loss: 0.2300 +2025-06-25 00:30:51,147 - pyskl - INFO - Epoch [93][400/1281] lr: 8.067e-03, eta: 8:21:27, time: 0.512, data_time: 0.001, memory: 4083, top1_acc: 0.9637, top5_acc: 0.9994, loss_cls: 0.2384, loss: 0.2384 +2025-06-25 00:31:15,696 - pyskl - INFO - Epoch [93][500/1281] lr: 8.047e-03, eta: 8:20:36, time: 0.245, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 0.2637, loss: 0.2637 +2025-06-25 00:32:01,890 - pyskl - INFO - Epoch [93][600/1281] lr: 8.028e-03, eta: 8:19:59, time: 0.462, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2642, loss: 0.2642 +2025-06-25 00:32:51,192 - pyskl - INFO - Epoch [93][700/1281] lr: 8.009e-03, eta: 8:19:23, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9494, top5_acc: 0.9994, loss_cls: 0.2762, loss: 0.2762 +2025-06-25 00:33:39,942 - pyskl - INFO - Epoch [93][800/1281] lr: 7.990e-03, eta: 8:18:48, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9531, top5_acc: 0.9994, loss_cls: 0.2771, loss: 0.2771 +2025-06-25 00:34:28,755 - pyskl - INFO - Epoch [93][900/1281] lr: 7.971e-03, eta: 8:18:12, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9988, loss_cls: 0.2442, loss: 0.2442 +2025-06-25 00:35:17,843 - pyskl - INFO - Epoch [93][1000/1281] lr: 7.952e-03, eta: 8:17:36, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2340, loss: 0.2340 +2025-06-25 00:36:06,692 - pyskl - INFO - Epoch [93][1100/1281] lr: 7.933e-03, eta: 8:17:01, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9463, top5_acc: 0.9981, loss_cls: 0.3080, loss: 0.3080 +2025-06-25 00:36:55,541 - pyskl - INFO - Epoch [93][1200/1281] lr: 7.914e-03, eta: 8:16:25, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 0.2837, loss: 0.2837 +2025-06-25 00:37:35,498 - pyskl - INFO - Saving checkpoint at 93 epochs +2025-06-25 00:38:33,553 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:38:33,610 - pyskl - INFO - +top1_acc 0.9024 +top5_acc 0.9913 +2025-06-25 00:38:33,610 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:38:33,619 - pyskl - INFO - +mean_acc 0.8707 +2025-06-25 00:38:33,622 - pyskl - INFO - Epoch(val) [93][533] top1_acc: 0.9024, top5_acc: 0.9913, mean_class_accuracy: 0.8707 +2025-06-25 00:39:52,883 - pyskl - INFO - Epoch [94][100/1281] lr: 7.880e-03, eta: 8:15:15, time: 0.793, data_time: 0.186, memory: 4083, top1_acc: 0.9775, top5_acc: 0.9994, loss_cls: 0.1765, loss: 0.1765 +2025-06-25 00:40:41,880 - pyskl - INFO - Epoch [94][200/1281] lr: 7.861e-03, eta: 8:14:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 0.2259, loss: 0.2259 +2025-06-25 00:41:19,920 - pyskl - INFO - Epoch [94][300/1281] lr: 7.842e-03, eta: 8:13:56, time: 0.380, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 0.2124, loss: 0.2124 +2025-06-25 00:42:11,057 - pyskl - INFO - Epoch [94][400/1281] lr: 7.823e-03, eta: 8:13:22, time: 0.511, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1984, loss: 0.1984 +2025-06-25 00:42:35,228 - pyskl - INFO - Epoch [94][500/1281] lr: 7.804e-03, eta: 8:12:31, time: 0.242, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9981, loss_cls: 0.2252, loss: 0.2252 +2025-06-25 00:43:20,937 - pyskl - INFO - Epoch [94][600/1281] lr: 7.785e-03, eta: 8:11:53, time: 0.457, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9988, loss_cls: 0.2635, loss: 0.2635 +2025-06-25 00:44:09,885 - pyskl - INFO - Epoch [94][700/1281] lr: 7.766e-03, eta: 8:11:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9988, loss_cls: 0.2868, loss: 0.2868 +2025-06-25 00:44:58,906 - pyskl - INFO - Epoch [94][800/1281] lr: 7.747e-03, eta: 8:10:42, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9988, loss_cls: 0.2314, loss: 0.2314 +2025-06-25 00:45:48,050 - pyskl - INFO - Epoch [94][900/1281] lr: 7.728e-03, eta: 8:10:06, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 0.2180, loss: 0.2180 +2025-06-25 00:46:37,307 - pyskl - INFO - Epoch [94][1000/1281] lr: 7.709e-03, eta: 8:09:30, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9600, top5_acc: 0.9975, loss_cls: 0.2471, loss: 0.2471 +2025-06-25 00:47:26,219 - pyskl - INFO - Epoch [94][1100/1281] lr: 7.690e-03, eta: 8:08:54, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 0.9988, loss_cls: 0.2049, loss: 0.2049 +2025-06-25 00:48:15,310 - pyskl - INFO - Epoch [94][1200/1281] lr: 7.672e-03, eta: 8:08:19, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9487, top5_acc: 1.0000, loss_cls: 0.2707, loss: 0.2707 +2025-06-25 00:48:55,232 - pyskl - INFO - Saving checkpoint at 94 epochs +2025-06-25 00:49:54,557 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 00:49:54,626 - pyskl - INFO - +top1_acc 0.9155 +top5_acc 0.9950 +2025-06-25 00:49:54,626 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 00:49:54,635 - pyskl - INFO - +mean_acc 0.8824 +2025-06-25 00:49:54,640 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_87.pth was removed +2025-06-25 00:49:55,001 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_94.pth. +2025-06-25 00:49:55,002 - pyskl - INFO - Best top1_acc is 0.9155 at 94 epoch. +2025-06-25 00:49:55,004 - pyskl - INFO - Epoch(val) [94][533] top1_acc: 0.9155, top5_acc: 0.9950, mean_class_accuracy: 0.8824 +2025-06-25 00:51:13,318 - pyskl - INFO - Epoch [95][100/1281] lr: 7.637e-03, eta: 8:07:07, time: 0.783, data_time: 0.190, memory: 4083, top1_acc: 0.9613, top5_acc: 1.0000, loss_cls: 0.2447, loss: 0.2447 +2025-06-25 00:52:02,230 - pyskl - INFO - Epoch [95][200/1281] lr: 7.619e-03, eta: 8:06:31, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.2101, loss: 0.2101 +2025-06-25 00:52:39,181 - pyskl - INFO - Epoch [95][300/1281] lr: 7.600e-03, eta: 8:05:48, time: 0.370, data_time: 0.000, memory: 4083, top1_acc: 0.9519, top5_acc: 0.9988, loss_cls: 0.2750, loss: 0.2750 +2025-06-25 00:53:30,231 - pyskl - INFO - Epoch [95][400/1281] lr: 7.581e-03, eta: 8:05:14, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 0.9988, loss_cls: 0.2443, loss: 0.2443 +2025-06-25 00:53:54,932 - pyskl - INFO - Epoch [95][500/1281] lr: 7.562e-03, eta: 8:04:23, time: 0.247, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9994, loss_cls: 0.2316, loss: 0.2316 +2025-06-25 00:54:41,401 - pyskl - INFO - Epoch [95][600/1281] lr: 7.543e-03, eta: 8:03:46, time: 0.465, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 0.9994, loss_cls: 0.2453, loss: 0.2453 +2025-06-25 00:55:30,673 - pyskl - INFO - Epoch [95][700/1281] lr: 7.525e-03, eta: 8:03:10, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 1.0000, loss_cls: 0.2459, loss: 0.2459 +2025-06-25 00:56:20,041 - pyskl - INFO - Epoch [95][800/1281] lr: 7.506e-03, eta: 8:02:34, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9994, loss_cls: 0.2795, loss: 0.2795 +2025-06-25 00:57:08,984 - pyskl - INFO - Epoch [95][900/1281] lr: 7.487e-03, eta: 8:01:58, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2755, loss: 0.2755 +2025-06-25 00:57:58,627 - pyskl - INFO - Epoch [95][1000/1281] lr: 7.468e-03, eta: 8:01:22, time: 0.496, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2445, loss: 0.2445 +2025-06-25 00:58:47,686 - pyskl - INFO - Epoch [95][1100/1281] lr: 7.450e-03, eta: 8:00:46, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 1.0000, loss_cls: 0.2352, loss: 0.2352 +2025-06-25 00:59:36,820 - pyskl - INFO - Epoch [95][1200/1281] lr: 7.431e-03, eta: 8:00:10, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 0.2624, loss: 0.2624 +2025-06-25 01:00:17,245 - pyskl - INFO - Saving checkpoint at 95 epochs +2025-06-25 01:01:14,938 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:01:14,995 - pyskl - INFO - +top1_acc 0.9128 +top5_acc 0.9924 +2025-06-25 01:01:14,995 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:01:15,002 - pyskl - INFO - +mean_acc 0.8876 +2025-06-25 01:01:15,004 - pyskl - INFO - Epoch(val) [95][533] top1_acc: 0.9128, top5_acc: 0.9924, mean_class_accuracy: 0.8876 +2025-06-25 01:02:34,566 - pyskl - INFO - Epoch [96][100/1281] lr: 7.397e-03, eta: 7:59:00, time: 0.796, data_time: 0.186, memory: 4083, top1_acc: 0.9744, top5_acc: 0.9994, loss_cls: 0.2101, loss: 0.2101 +2025-06-25 01:03:23,551 - pyskl - INFO - Epoch [96][200/1281] lr: 7.379e-03, eta: 7:58:24, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.1847, loss: 0.1847 +2025-06-25 01:04:00,048 - pyskl - INFO - Epoch [96][300/1281] lr: 7.360e-03, eta: 7:57:40, time: 0.365, data_time: 0.000, memory: 4083, top1_acc: 0.9594, top5_acc: 1.0000, loss_cls: 0.2348, loss: 0.2348 +2025-06-25 01:04:51,211 - pyskl - INFO - Epoch [96][400/1281] lr: 7.341e-03, eta: 7:57:05, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 0.2041, loss: 0.2041 +2025-06-25 01:05:15,661 - pyskl - INFO - Epoch [96][500/1281] lr: 7.323e-03, eta: 7:56:15, time: 0.244, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 0.9994, loss_cls: 0.2044, loss: 0.2044 +2025-06-25 01:06:00,208 - pyskl - INFO - Epoch [96][600/1281] lr: 7.304e-03, eta: 7:55:36, time: 0.445, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 0.9994, loss_cls: 0.1806, loss: 0.1806 +2025-06-25 01:06:49,027 - pyskl - INFO - Epoch [96][700/1281] lr: 7.286e-03, eta: 7:55:00, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.2092, loss: 0.2092 +2025-06-25 01:07:37,558 - pyskl - INFO - Epoch [96][800/1281] lr: 7.267e-03, eta: 7:54:23, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9981, loss_cls: 0.2552, loss: 0.2552 +2025-06-25 01:08:26,441 - pyskl - INFO - Epoch [96][900/1281] lr: 7.249e-03, eta: 7:53:47, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9606, top5_acc: 0.9994, loss_cls: 0.2401, loss: 0.2401 +2025-06-25 01:09:15,045 - pyskl - INFO - Epoch [96][1000/1281] lr: 7.230e-03, eta: 7:53:11, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9994, loss_cls: 0.2435, loss: 0.2435 +2025-06-25 01:10:04,137 - pyskl - INFO - Epoch [96][1100/1281] lr: 7.211e-03, eta: 7:52:34, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 1.0000, loss_cls: 0.2928, loss: 0.2928 +2025-06-25 01:10:52,716 - pyskl - INFO - Epoch [96][1200/1281] lr: 7.193e-03, eta: 7:51:58, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 0.9994, loss_cls: 0.2332, loss: 0.2332 +2025-06-25 01:11:33,020 - pyskl - INFO - Saving checkpoint at 96 epochs +2025-06-25 01:12:30,654 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:12:30,714 - pyskl - INFO - +top1_acc 0.9075 +top5_acc 0.9945 +2025-06-25 01:12:30,714 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:12:30,721 - pyskl - INFO - +mean_acc 0.8730 +2025-06-25 01:12:30,723 - pyskl - INFO - Epoch(val) [96][533] top1_acc: 0.9075, top5_acc: 0.9945, mean_class_accuracy: 0.8730 +2025-06-25 01:13:50,206 - pyskl - INFO - Epoch [97][100/1281] lr: 7.159e-03, eta: 7:50:47, time: 0.795, data_time: 0.188, memory: 4083, top1_acc: 0.9650, top5_acc: 0.9981, loss_cls: 0.2174, loss: 0.2174 +2025-06-25 01:14:39,259 - pyskl - INFO - Epoch [97][200/1281] lr: 7.141e-03, eta: 7:50:11, time: 0.491, data_time: 0.001, memory: 4083, top1_acc: 0.9644, top5_acc: 1.0000, loss_cls: 0.2003, loss: 0.2003 +2025-06-25 01:15:18,559 - pyskl - INFO - Epoch [97][300/1281] lr: 7.123e-03, eta: 7:49:29, time: 0.393, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 1.0000, loss_cls: 0.1875, loss: 0.1875 +2025-06-25 01:16:09,836 - pyskl - INFO - Epoch [97][400/1281] lr: 7.104e-03, eta: 7:48:54, time: 0.513, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 0.9994, loss_cls: 0.1962, loss: 0.1962 +2025-06-25 01:16:33,631 - pyskl - INFO - Epoch [97][500/1281] lr: 7.086e-03, eta: 7:48:03, time: 0.238, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1941, loss: 0.1941 +2025-06-25 01:17:17,865 - pyskl - INFO - Epoch [97][600/1281] lr: 7.067e-03, eta: 7:47:24, time: 0.442, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 0.9994, loss_cls: 0.1747, loss: 0.1747 +2025-06-25 01:18:06,607 - pyskl - INFO - Epoch [97][700/1281] lr: 7.049e-03, eta: 7:46:48, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9563, top5_acc: 0.9994, loss_cls: 0.2175, loss: 0.2175 +2025-06-25 01:18:55,148 - pyskl - INFO - Epoch [97][800/1281] lr: 7.030e-03, eta: 7:46:11, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9981, loss_cls: 0.2233, loss: 0.2233 +2025-06-25 01:19:44,489 - pyskl - INFO - Epoch [97][900/1281] lr: 7.012e-03, eta: 7:45:35, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2277, loss: 0.2277 +2025-06-25 01:20:33,717 - pyskl - INFO - Epoch [97][1000/1281] lr: 6.994e-03, eta: 7:44:58, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9587, top5_acc: 1.0000, loss_cls: 0.2562, loss: 0.2562 +2025-06-25 01:21:23,054 - pyskl - INFO - Epoch [97][1100/1281] lr: 6.975e-03, eta: 7:44:22, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9575, top5_acc: 0.9994, loss_cls: 0.2669, loss: 0.2669 +2025-06-25 01:22:11,635 - pyskl - INFO - Epoch [97][1200/1281] lr: 6.957e-03, eta: 7:43:45, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9581, top5_acc: 0.9994, loss_cls: 0.2578, loss: 0.2578 +2025-06-25 01:22:51,850 - pyskl - INFO - Saving checkpoint at 97 epochs +2025-06-25 01:23:49,601 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:23:49,656 - pyskl - INFO - +top1_acc 0.9167 +top5_acc 0.9951 +2025-06-25 01:23:49,657 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:23:49,663 - pyskl - INFO - +mean_acc 0.8861 +2025-06-25 01:23:49,667 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_94.pth was removed +2025-06-25 01:23:49,850 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_97.pth. +2025-06-25 01:23:49,850 - pyskl - INFO - Best top1_acc is 0.9167 at 97 epoch. +2025-06-25 01:23:49,853 - pyskl - INFO - Epoch(val) [97][533] top1_acc: 0.9167, top5_acc: 0.9951, mean_class_accuracy: 0.8861 +2025-06-25 01:25:08,197 - pyskl - INFO - Epoch [98][100/1281] lr: 6.924e-03, eta: 7:42:33, time: 0.783, data_time: 0.183, memory: 4083, top1_acc: 0.9719, top5_acc: 0.9994, loss_cls: 0.1880, loss: 0.1880 +2025-06-25 01:25:57,020 - pyskl - INFO - Epoch [98][200/1281] lr: 6.906e-03, eta: 7:41:57, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 0.9994, loss_cls: 0.1952, loss: 0.1952 +2025-06-25 01:26:37,598 - pyskl - INFO - Epoch [98][300/1281] lr: 6.887e-03, eta: 7:41:16, time: 0.406, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 0.9994, loss_cls: 0.1795, loss: 0.1795 +2025-06-25 01:27:28,751 - pyskl - INFO - Epoch [98][400/1281] lr: 6.869e-03, eta: 7:40:40, time: 0.512, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1821, loss: 0.1821 +2025-06-25 01:27:52,199 - pyskl - INFO - Epoch [98][500/1281] lr: 6.851e-03, eta: 7:39:50, time: 0.234, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.2115, loss: 0.2115 +2025-06-25 01:28:35,735 - pyskl - INFO - Epoch [98][600/1281] lr: 6.833e-03, eta: 7:39:10, time: 0.435, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 0.9994, loss_cls: 0.2005, loss: 0.2005 +2025-06-25 01:29:24,444 - pyskl - INFO - Epoch [98][700/1281] lr: 6.814e-03, eta: 7:38:34, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.1991, loss: 0.1991 +2025-06-25 01:30:12,979 - pyskl - INFO - Epoch [98][800/1281] lr: 6.796e-03, eta: 7:37:57, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 1.0000, loss_cls: 0.2476, loss: 0.2476 +2025-06-25 01:31:02,053 - pyskl - INFO - Epoch [98][900/1281] lr: 6.778e-03, eta: 7:37:20, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 0.2095, loss: 0.2095 +2025-06-25 01:31:50,758 - pyskl - INFO - Epoch [98][1000/1281] lr: 6.760e-03, eta: 7:36:43, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 0.9994, loss_cls: 0.2751, loss: 0.2751 +2025-06-25 01:32:39,696 - pyskl - INFO - Epoch [98][1100/1281] lr: 6.742e-03, eta: 7:36:07, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 1.0000, loss_cls: 0.2516, loss: 0.2516 +2025-06-25 01:33:28,622 - pyskl - INFO - Epoch [98][1200/1281] lr: 6.724e-03, eta: 7:35:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 0.9994, loss_cls: 0.2334, loss: 0.2334 +2025-06-25 01:34:08,700 - pyskl - INFO - Saving checkpoint at 98 epochs +2025-06-25 01:35:07,473 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:35:07,545 - pyskl - INFO - +top1_acc 0.9147 +top5_acc 0.9961 +2025-06-25 01:35:07,545 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:35:07,553 - pyskl - INFO - +mean_acc 0.8769 +2025-06-25 01:35:07,555 - pyskl - INFO - Epoch(val) [98][533] top1_acc: 0.9147, top5_acc: 0.9961, mean_class_accuracy: 0.8769 +2025-06-25 01:36:27,876 - pyskl - INFO - Epoch [99][100/1281] lr: 6.691e-03, eta: 7:34:19, time: 0.803, data_time: 0.188, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9994, loss_cls: 0.2319, loss: 0.2319 +2025-06-25 01:37:16,940 - pyskl - INFO - Epoch [99][200/1281] lr: 6.673e-03, eta: 7:33:42, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 0.2125, loss: 0.2125 +2025-06-25 01:37:56,372 - pyskl - INFO - Epoch [99][300/1281] lr: 6.655e-03, eta: 7:33:00, time: 0.394, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 0.9994, loss_cls: 0.1776, loss: 0.1776 +2025-06-25 01:38:47,332 - pyskl - INFO - Epoch [99][400/1281] lr: 6.637e-03, eta: 7:32:25, time: 0.510, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2070, loss: 0.2070 +2025-06-25 01:39:11,062 - pyskl - INFO - Epoch [99][500/1281] lr: 6.619e-03, eta: 7:31:35, time: 0.237, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2027, loss: 0.2027 +2025-06-25 01:39:54,273 - pyskl - INFO - Epoch [99][600/1281] lr: 6.601e-03, eta: 7:30:55, time: 0.432, data_time: 0.000, memory: 4083, top1_acc: 0.9550, top5_acc: 0.9988, loss_cls: 0.2540, loss: 0.2540 +2025-06-25 01:40:43,447 - pyskl - INFO - Epoch [99][700/1281] lr: 6.583e-03, eta: 7:30:18, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 0.9988, loss_cls: 0.2267, loss: 0.2267 +2025-06-25 01:41:32,514 - pyskl - INFO - Epoch [99][800/1281] lr: 6.565e-03, eta: 7:29:41, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9619, top5_acc: 0.9988, loss_cls: 0.2198, loss: 0.2198 +2025-06-25 01:42:21,763 - pyskl - INFO - Epoch [99][900/1281] lr: 6.547e-03, eta: 7:29:05, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9544, top5_acc: 1.0000, loss_cls: 0.2585, loss: 0.2585 +2025-06-25 01:43:10,892 - pyskl - INFO - Epoch [99][1000/1281] lr: 6.529e-03, eta: 7:28:28, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9506, top5_acc: 1.0000, loss_cls: 0.2922, loss: 0.2922 +2025-06-25 01:43:59,893 - pyskl - INFO - Epoch [99][1100/1281] lr: 6.511e-03, eta: 7:27:51, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.2114, loss: 0.2114 +2025-06-25 01:44:48,790 - pyskl - INFO - Epoch [99][1200/1281] lr: 6.493e-03, eta: 7:27:14, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2049, loss: 0.2049 +2025-06-25 01:45:29,113 - pyskl - INFO - Saving checkpoint at 99 epochs +2025-06-25 01:46:27,022 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:46:27,078 - pyskl - INFO - +top1_acc 0.9015 +top5_acc 0.9926 +2025-06-25 01:46:27,078 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:46:27,085 - pyskl - INFO - +mean_acc 0.8712 +2025-06-25 01:46:27,087 - pyskl - INFO - Epoch(val) [99][533] top1_acc: 0.9015, top5_acc: 0.9926, mean_class_accuracy: 0.8712 +2025-06-25 01:47:45,693 - pyskl - INFO - Epoch [100][100/1281] lr: 6.460e-03, eta: 7:26:02, time: 0.786, data_time: 0.189, memory: 4083, top1_acc: 0.9663, top5_acc: 0.9988, loss_cls: 0.2110, loss: 0.2110 +2025-06-25 01:48:34,421 - pyskl - INFO - Epoch [100][200/1281] lr: 6.442e-03, eta: 7:25:25, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 0.9994, loss_cls: 0.2047, loss: 0.2047 +2025-06-25 01:49:16,418 - pyskl - INFO - Epoch [100][300/1281] lr: 6.425e-03, eta: 7:24:44, time: 0.420, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 0.9994, loss_cls: 0.1937, loss: 0.1937 +2025-06-25 01:50:05,916 - pyskl - INFO - Epoch [100][400/1281] lr: 6.407e-03, eta: 7:24:08, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.1947, loss: 0.1947 +2025-06-25 01:50:30,874 - pyskl - INFO - Epoch [100][500/1281] lr: 6.389e-03, eta: 7:23:18, time: 0.250, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 0.2215, loss: 0.2215 +2025-06-25 01:51:12,719 - pyskl - INFO - Epoch [100][600/1281] lr: 6.371e-03, eta: 7:22:38, time: 0.418, data_time: 0.000, memory: 4083, top1_acc: 0.9637, top5_acc: 1.0000, loss_cls: 0.2090, loss: 0.2090 +2025-06-25 01:52:01,526 - pyskl - INFO - Epoch [100][700/1281] lr: 6.353e-03, eta: 7:22:01, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 1.0000, loss_cls: 0.2207, loss: 0.2207 +2025-06-25 01:52:50,349 - pyskl - INFO - Epoch [100][800/1281] lr: 6.336e-03, eta: 7:21:23, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9500, top5_acc: 0.9981, loss_cls: 0.2791, loss: 0.2791 +2025-06-25 01:53:39,636 - pyskl - INFO - Epoch [100][900/1281] lr: 6.318e-03, eta: 7:20:47, time: 0.493, data_time: 0.001, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.2094, loss: 0.2094 +2025-06-25 01:54:29,006 - pyskl - INFO - Epoch [100][1000/1281] lr: 6.300e-03, eta: 7:20:10, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9556, top5_acc: 0.9988, loss_cls: 0.2485, loss: 0.2485 +2025-06-25 01:55:17,976 - pyskl - INFO - Epoch [100][1100/1281] lr: 6.282e-03, eta: 7:19:33, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.2076, loss: 0.2076 +2025-06-25 01:56:06,626 - pyskl - INFO - Epoch [100][1200/1281] lr: 6.265e-03, eta: 7:18:55, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 0.1903, loss: 0.1903 +2025-06-25 01:56:47,069 - pyskl - INFO - Saving checkpoint at 100 epochs +2025-06-25 01:57:45,389 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 01:57:45,445 - pyskl - INFO - +top1_acc 0.8948 +top5_acc 0.9920 +2025-06-25 01:57:45,445 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 01:57:45,452 - pyskl - INFO - +mean_acc 0.8598 +2025-06-25 01:57:45,453 - pyskl - INFO - Epoch(val) [100][533] top1_acc: 0.8948, top5_acc: 0.9920, mean_class_accuracy: 0.8598 +2025-06-25 01:59:04,711 - pyskl - INFO - Epoch [101][100/1281] lr: 6.232e-03, eta: 7:17:44, time: 0.793, data_time: 0.187, memory: 4083, top1_acc: 0.9688, top5_acc: 0.9981, loss_cls: 0.2336, loss: 0.2336 +2025-06-25 01:59:53,458 - pyskl - INFO - Epoch [101][200/1281] lr: 6.215e-03, eta: 7:17:06, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 0.9994, loss_cls: 0.1811, loss: 0.1811 +2025-06-25 02:00:35,763 - pyskl - INFO - Epoch [101][300/1281] lr: 6.197e-03, eta: 7:16:26, time: 0.423, data_time: 0.000, memory: 4083, top1_acc: 0.9625, top5_acc: 0.9994, loss_cls: 0.2115, loss: 0.2115 +2025-06-25 02:01:23,296 - pyskl - INFO - Epoch [101][400/1281] lr: 6.180e-03, eta: 7:15:48, time: 0.475, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 0.9994, loss_cls: 0.1851, loss: 0.1851 +2025-06-25 02:01:49,792 - pyskl - INFO - Epoch [101][500/1281] lr: 6.162e-03, eta: 7:15:00, time: 0.265, data_time: 0.000, memory: 4083, top1_acc: 0.9700, top5_acc: 1.0000, loss_cls: 0.1793, loss: 0.1793 +2025-06-25 02:02:31,447 - pyskl - INFO - Epoch [101][600/1281] lr: 6.144e-03, eta: 7:14:19, time: 0.417, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1648, loss: 0.1648 +2025-06-25 02:03:20,601 - pyskl - INFO - Epoch [101][700/1281] lr: 6.127e-03, eta: 7:13:42, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1835, loss: 0.1835 +2025-06-25 02:04:09,449 - pyskl - INFO - Epoch [101][800/1281] lr: 6.109e-03, eta: 7:13:05, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 1.0000, loss_cls: 0.1707, loss: 0.1707 +2025-06-25 02:04:58,641 - pyskl - INFO - Epoch [101][900/1281] lr: 6.092e-03, eta: 7:12:27, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 0.9994, loss_cls: 0.2009, loss: 0.2009 +2025-06-25 02:05:47,611 - pyskl - INFO - Epoch [101][1000/1281] lr: 6.074e-03, eta: 7:11:50, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.1984, loss: 0.1984 +2025-06-25 02:06:36,713 - pyskl - INFO - Epoch [101][1100/1281] lr: 6.057e-03, eta: 7:11:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.2099, loss: 0.2099 +2025-06-25 02:07:25,989 - pyskl - INFO - Epoch [101][1200/1281] lr: 6.039e-03, eta: 7:10:36, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 0.9994, loss_cls: 0.1824, loss: 0.1824 +2025-06-25 02:08:06,101 - pyskl - INFO - Saving checkpoint at 101 epochs +2025-06-25 02:09:04,425 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:09:04,480 - pyskl - INFO - +top1_acc 0.9141 +top5_acc 0.9942 +2025-06-25 02:09:04,480 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:09:04,486 - pyskl - INFO - +mean_acc 0.8878 +2025-06-25 02:09:04,488 - pyskl - INFO - Epoch(val) [101][533] top1_acc: 0.9141, top5_acc: 0.9942, mean_class_accuracy: 0.8878 +2025-06-25 02:10:22,863 - pyskl - INFO - Epoch [102][100/1281] lr: 6.007e-03, eta: 7:09:23, time: 0.784, data_time: 0.189, memory: 4083, top1_acc: 0.9569, top5_acc: 1.0000, loss_cls: 0.2599, loss: 0.2599 +2025-06-25 02:11:11,731 - pyskl - INFO - Epoch [102][200/1281] lr: 5.990e-03, eta: 7:08:46, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1610, loss: 0.1610 +2025-06-25 02:11:55,330 - pyskl - INFO - Epoch [102][300/1281] lr: 5.972e-03, eta: 7:08:06, time: 0.436, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 0.9994, loss_cls: 0.1648, loss: 0.1648 +2025-06-25 02:12:41,095 - pyskl - INFO - Epoch [102][400/1281] lr: 5.955e-03, eta: 7:07:27, time: 0.458, data_time: 0.000, memory: 4083, top1_acc: 0.9650, top5_acc: 0.9994, loss_cls: 0.1987, loss: 0.1987 +2025-06-25 02:13:08,757 - pyskl - INFO - Epoch [102][500/1281] lr: 5.938e-03, eta: 7:06:40, time: 0.277, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 0.9994, loss_cls: 0.2046, loss: 0.2046 +2025-06-25 02:13:50,981 - pyskl - INFO - Epoch [102][600/1281] lr: 5.920e-03, eta: 7:05:59, time: 0.422, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1490, loss: 0.1490 +2025-06-25 02:14:40,021 - pyskl - INFO - Epoch [102][700/1281] lr: 5.903e-03, eta: 7:05:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 0.9994, loss_cls: 0.1950, loss: 0.1950 +2025-06-25 02:15:28,910 - pyskl - INFO - Epoch [102][800/1281] lr: 5.886e-03, eta: 7:04:44, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 0.9988, loss_cls: 0.1907, loss: 0.1907 +2025-06-25 02:16:17,995 - pyskl - INFO - Epoch [102][900/1281] lr: 5.868e-03, eta: 7:04:07, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.2122, loss: 0.2122 +2025-06-25 02:17:06,956 - pyskl - INFO - Epoch [102][1000/1281] lr: 5.851e-03, eta: 7:03:30, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 0.9994, loss_cls: 0.2046, loss: 0.2046 +2025-06-25 02:17:55,713 - pyskl - INFO - Epoch [102][1100/1281] lr: 5.834e-03, eta: 7:02:52, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9688, top5_acc: 1.0000, loss_cls: 0.2058, loss: 0.2058 +2025-06-25 02:18:44,513 - pyskl - INFO - Epoch [102][1200/1281] lr: 5.816e-03, eta: 7:02:14, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9631, top5_acc: 1.0000, loss_cls: 0.2315, loss: 0.2315 +2025-06-25 02:19:24,378 - pyskl - INFO - Saving checkpoint at 102 epochs +2025-06-25 02:20:21,931 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:20:21,985 - pyskl - INFO - +top1_acc 0.9102 +top5_acc 0.9938 +2025-06-25 02:20:21,985 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:20:21,993 - pyskl - INFO - +mean_acc 0.8865 +2025-06-25 02:20:21,995 - pyskl - INFO - Epoch(val) [102][533] top1_acc: 0.9102, top5_acc: 0.9938, mean_class_accuracy: 0.8865 +2025-06-25 02:21:39,419 - pyskl - INFO - Epoch [103][100/1281] lr: 5.785e-03, eta: 7:01:01, time: 0.774, data_time: 0.190, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1840, loss: 0.1840 +2025-06-25 02:22:28,168 - pyskl - INFO - Epoch [103][200/1281] lr: 5.768e-03, eta: 7:00:24, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 0.9994, loss_cls: 0.1631, loss: 0.1631 +2025-06-25 02:23:12,591 - pyskl - INFO - Epoch [103][300/1281] lr: 5.751e-03, eta: 6:59:44, time: 0.444, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.1851, loss: 0.1851 +2025-06-25 02:23:54,238 - pyskl - INFO - Epoch [103][400/1281] lr: 5.733e-03, eta: 6:59:03, time: 0.416, data_time: 0.000, memory: 4083, top1_acc: 0.9613, top5_acc: 0.9994, loss_cls: 0.2290, loss: 0.2290 +2025-06-25 02:24:25,833 - pyskl - INFO - Epoch [103][500/1281] lr: 5.716e-03, eta: 6:58:18, time: 0.316, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1752, loss: 0.1752 +2025-06-25 02:25:05,709 - pyskl - INFO - Epoch [103][600/1281] lr: 5.699e-03, eta: 6:57:36, time: 0.399, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1502, loss: 0.1502 +2025-06-25 02:25:54,764 - pyskl - INFO - Epoch [103][700/1281] lr: 5.682e-03, eta: 6:56:58, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 0.9994, loss_cls: 0.1697, loss: 0.1697 +2025-06-25 02:26:43,654 - pyskl - INFO - Epoch [103][800/1281] lr: 5.665e-03, eta: 6:56:21, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9669, top5_acc: 1.0000, loss_cls: 0.1800, loss: 0.1800 +2025-06-25 02:27:32,326 - pyskl - INFO - Epoch [103][900/1281] lr: 5.648e-03, eta: 6:55:43, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 0.9994, loss_cls: 0.1595, loss: 0.1595 +2025-06-25 02:28:20,919 - pyskl - INFO - Epoch [103][1000/1281] lr: 5.631e-03, eta: 6:55:05, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 0.9988, loss_cls: 0.1985, loss: 0.1985 +2025-06-25 02:29:09,851 - pyskl - INFO - Epoch [103][1100/1281] lr: 5.614e-03, eta: 6:54:28, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1988, loss: 0.1988 +2025-06-25 02:29:58,904 - pyskl - INFO - Epoch [103][1200/1281] lr: 5.597e-03, eta: 6:53:50, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 0.9994, loss_cls: 0.1726, loss: 0.1726 +2025-06-25 02:30:38,810 - pyskl - INFO - Saving checkpoint at 103 epochs +2025-06-25 02:31:36,627 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:31:36,684 - pyskl - INFO - +top1_acc 0.9046 +top5_acc 0.9941 +2025-06-25 02:31:36,684 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:31:36,692 - pyskl - INFO - +mean_acc 0.8732 +2025-06-25 02:31:36,694 - pyskl - INFO - Epoch(val) [103][533] top1_acc: 0.9046, top5_acc: 0.9941, mean_class_accuracy: 0.8732 +2025-06-25 02:32:54,621 - pyskl - INFO - Epoch [104][100/1281] lr: 5.566e-03, eta: 6:52:37, time: 0.779, data_time: 0.182, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1711, loss: 0.1711 +2025-06-25 02:33:43,951 - pyskl - INFO - Epoch [104][200/1281] lr: 5.549e-03, eta: 6:52:00, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 0.9994, loss_cls: 0.1517, loss: 0.1517 +2025-06-25 02:34:31,470 - pyskl - INFO - Epoch [104][300/1281] lr: 5.532e-03, eta: 6:51:21, time: 0.475, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1310, loss: 0.1310 +2025-06-25 02:35:05,737 - pyskl - INFO - Epoch [104][400/1281] lr: 5.515e-03, eta: 6:50:37, time: 0.343, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1560, loss: 0.1560 +2025-06-25 02:35:44,494 - pyskl - INFO - Epoch [104][500/1281] lr: 5.498e-03, eta: 6:49:55, time: 0.388, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1537, loss: 0.1537 +2025-06-25 02:36:19,926 - pyskl - INFO - Epoch [104][600/1281] lr: 5.481e-03, eta: 6:49:11, time: 0.354, data_time: 0.000, memory: 4083, top1_acc: 0.9675, top5_acc: 1.0000, loss_cls: 0.2204, loss: 0.2204 +2025-06-25 02:37:08,689 - pyskl - INFO - Epoch [104][700/1281] lr: 5.464e-03, eta: 6:48:33, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 0.9994, loss_cls: 0.1789, loss: 0.1789 +2025-06-25 02:37:57,752 - pyskl - INFO - Epoch [104][800/1281] lr: 5.447e-03, eta: 6:47:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 0.1877, loss: 0.1877 +2025-06-25 02:38:46,603 - pyskl - INFO - Epoch [104][900/1281] lr: 5.430e-03, eta: 6:47:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9712, top5_acc: 1.0000, loss_cls: 0.1694, loss: 0.1694 +2025-06-25 02:39:35,168 - pyskl - INFO - Epoch [104][1000/1281] lr: 5.413e-03, eta: 6:46:40, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1605, loss: 0.1605 +2025-06-25 02:40:23,984 - pyskl - INFO - Epoch [104][1100/1281] lr: 5.397e-03, eta: 6:46:02, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1710, loss: 0.1710 +2025-06-25 02:41:13,102 - pyskl - INFO - Epoch [104][1200/1281] lr: 5.380e-03, eta: 6:45:24, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9794, top5_acc: 0.9994, loss_cls: 0.1476, loss: 0.1476 +2025-06-25 02:41:53,286 - pyskl - INFO - Saving checkpoint at 104 epochs +2025-06-25 02:42:51,398 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:42:51,463 - pyskl - INFO - +top1_acc 0.9137 +top5_acc 0.9940 +2025-06-25 02:42:51,464 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:42:51,471 - pyskl - INFO - +mean_acc 0.8847 +2025-06-25 02:42:51,472 - pyskl - INFO - Epoch(val) [104][533] top1_acc: 0.9137, top5_acc: 0.9940, mean_class_accuracy: 0.8847 +2025-06-25 02:44:09,982 - pyskl - INFO - Epoch [105][100/1281] lr: 5.349e-03, eta: 6:44:11, time: 0.785, data_time: 0.184, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1449, loss: 0.1449 +2025-06-25 02:44:59,426 - pyskl - INFO - Epoch [105][200/1281] lr: 5.333e-03, eta: 6:43:34, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1384, loss: 0.1384 +2025-06-25 02:45:48,562 - pyskl - INFO - Epoch [105][300/1281] lr: 5.316e-03, eta: 6:42:56, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1419, loss: 0.1419 +2025-06-25 02:46:19,022 - pyskl - INFO - Epoch [105][400/1281] lr: 5.299e-03, eta: 6:42:10, time: 0.305, data_time: 0.000, memory: 4083, top1_acc: 0.9656, top5_acc: 0.9988, loss_cls: 0.2091, loss: 0.2091 +2025-06-25 02:47:03,959 - pyskl - INFO - Epoch [105][500/1281] lr: 5.283e-03, eta: 6:41:30, time: 0.449, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1626, loss: 0.1626 +2025-06-25 02:47:36,933 - pyskl - INFO - Epoch [105][600/1281] lr: 5.266e-03, eta: 6:40:45, time: 0.330, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1405, loss: 0.1405 +2025-06-25 02:48:25,968 - pyskl - INFO - Epoch [105][700/1281] lr: 5.249e-03, eta: 6:40:08, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1557, loss: 0.1557 +2025-06-25 02:49:14,668 - pyskl - INFO - Epoch [105][800/1281] lr: 5.233e-03, eta: 6:39:30, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9725, top5_acc: 0.9994, loss_cls: 0.1867, loss: 0.1867 +2025-06-25 02:50:03,503 - pyskl - INFO - Epoch [105][900/1281] lr: 5.216e-03, eta: 6:38:52, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9719, top5_acc: 1.0000, loss_cls: 0.1594, loss: 0.1594 +2025-06-25 02:50:52,465 - pyskl - INFO - Epoch [105][1000/1281] lr: 5.199e-03, eta: 6:38:14, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 1.0000, loss_cls: 0.1560, loss: 0.1560 +2025-06-25 02:51:41,293 - pyskl - INFO - Epoch [105][1100/1281] lr: 5.183e-03, eta: 6:37:36, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 0.9994, loss_cls: 0.1938, loss: 0.1938 +2025-06-25 02:52:29,994 - pyskl - INFO - Epoch [105][1200/1281] lr: 5.166e-03, eta: 6:36:58, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1673, loss: 0.1673 +2025-06-25 02:53:10,117 - pyskl - INFO - Saving checkpoint at 105 epochs +2025-06-25 02:54:08,493 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 02:54:08,547 - pyskl - INFO - +top1_acc 0.9140 +top5_acc 0.9946 +2025-06-25 02:54:08,547 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 02:54:08,553 - pyskl - INFO - +mean_acc 0.8866 +2025-06-25 02:54:08,555 - pyskl - INFO - Epoch(val) [105][533] top1_acc: 0.9140, top5_acc: 0.9946, mean_class_accuracy: 0.8866 +2025-06-25 02:55:28,607 - pyskl - INFO - Epoch [106][100/1281] lr: 5.136e-03, eta: 6:35:45, time: 0.800, data_time: 0.187, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1558, loss: 0.1558 +2025-06-25 02:56:17,441 - pyskl - INFO - Epoch [106][200/1281] lr: 5.120e-03, eta: 6:35:07, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1341, loss: 0.1341 +2025-06-25 02:57:06,123 - pyskl - INFO - Epoch [106][300/1281] lr: 5.103e-03, eta: 6:34:29, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1132, loss: 0.1132 +2025-06-25 02:57:36,487 - pyskl - INFO - Epoch [106][400/1281] lr: 5.087e-03, eta: 6:33:43, time: 0.304, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1193, loss: 0.1193 +2025-06-25 02:58:21,796 - pyskl - INFO - Epoch [106][500/1281] lr: 5.070e-03, eta: 6:33:04, time: 0.453, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1120, loss: 0.1120 +2025-06-25 02:58:53,550 - pyskl - INFO - Epoch [106][600/1281] lr: 5.054e-03, eta: 6:32:18, time: 0.318, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1240, loss: 0.1240 +2025-06-25 02:59:42,396 - pyskl - INFO - Epoch [106][700/1281] lr: 5.038e-03, eta: 6:31:40, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9681, top5_acc: 1.0000, loss_cls: 0.1743, loss: 0.1743 +2025-06-25 03:00:31,767 - pyskl - INFO - Epoch [106][800/1281] lr: 5.021e-03, eta: 6:31:02, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 0.9994, loss_cls: 0.1551, loss: 0.1551 +2025-06-25 03:01:20,877 - pyskl - INFO - Epoch [106][900/1281] lr: 5.005e-03, eta: 6:30:24, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1252, loss: 0.1252 +2025-06-25 03:02:10,038 - pyskl - INFO - Epoch [106][1000/1281] lr: 4.988e-03, eta: 6:29:46, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9731, top5_acc: 0.9988, loss_cls: 0.1602, loss: 0.1602 +2025-06-25 03:02:59,308 - pyskl - INFO - Epoch [106][1100/1281] lr: 4.972e-03, eta: 6:29:09, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9706, top5_acc: 1.0000, loss_cls: 0.1869, loss: 0.1869 +2025-06-25 03:03:48,233 - pyskl - INFO - Epoch [106][1200/1281] lr: 4.956e-03, eta: 6:28:30, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9694, top5_acc: 1.0000, loss_cls: 0.1827, loss: 0.1827 +2025-06-25 03:04:28,436 - pyskl - INFO - Saving checkpoint at 106 epochs +2025-06-25 03:05:26,163 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:05:26,228 - pyskl - INFO - +top1_acc 0.9101 +top5_acc 0.9959 +2025-06-25 03:05:26,228 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:05:26,238 - pyskl - INFO - +mean_acc 0.8822 +2025-06-25 03:05:26,241 - pyskl - INFO - Epoch(val) [106][533] top1_acc: 0.9101, top5_acc: 0.9959, mean_class_accuracy: 0.8822 +2025-06-25 03:06:45,069 - pyskl - INFO - Epoch [107][100/1281] lr: 4.926e-03, eta: 6:27:17, time: 0.788, data_time: 0.188, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1482, loss: 0.1482 +2025-06-25 03:07:34,093 - pyskl - INFO - Epoch [107][200/1281] lr: 4.910e-03, eta: 6:26:39, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 0.9994, loss_cls: 0.1701, loss: 0.1701 +2025-06-25 03:08:23,479 - pyskl - INFO - Epoch [107][300/1281] lr: 4.894e-03, eta: 6:26:01, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 0.9994, loss_cls: 0.1525, loss: 0.1525 +2025-06-25 03:08:52,248 - pyskl - INFO - Epoch [107][400/1281] lr: 4.878e-03, eta: 6:25:15, time: 0.288, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 0.9994, loss_cls: 0.1447, loss: 0.1447 +2025-06-25 03:09:43,042 - pyskl - INFO - Epoch [107][500/1281] lr: 4.862e-03, eta: 6:24:37, time: 0.508, data_time: 0.001, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1562, loss: 0.1562 +2025-06-25 03:10:12,676 - pyskl - INFO - Epoch [107][600/1281] lr: 4.845e-03, eta: 6:23:51, time: 0.296, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1212, loss: 0.1212 +2025-06-25 03:11:01,268 - pyskl - INFO - Epoch [107][700/1281] lr: 4.829e-03, eta: 6:23:13, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1310, loss: 0.1310 +2025-06-25 03:11:50,350 - pyskl - INFO - Epoch [107][800/1281] lr: 4.813e-03, eta: 6:22:35, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1256, loss: 0.1256 +2025-06-25 03:12:38,775 - pyskl - INFO - Epoch [107][900/1281] lr: 4.797e-03, eta: 6:21:56, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1058, loss: 0.1058 +2025-06-25 03:13:27,708 - pyskl - INFO - Epoch [107][1000/1281] lr: 4.781e-03, eta: 6:21:18, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1373, loss: 0.1373 +2025-06-25 03:14:16,393 - pyskl - INFO - Epoch [107][1100/1281] lr: 4.765e-03, eta: 6:20:40, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1248, loss: 0.1248 +2025-06-25 03:15:05,040 - pyskl - INFO - Epoch [107][1200/1281] lr: 4.749e-03, eta: 6:20:01, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1292, loss: 0.1292 +2025-06-25 03:15:45,028 - pyskl - INFO - Saving checkpoint at 107 epochs +2025-06-25 03:16:43,105 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:16:43,159 - pyskl - INFO - +top1_acc 0.9248 +top5_acc 0.9959 +2025-06-25 03:16:43,159 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:16:43,165 - pyskl - INFO - +mean_acc 0.8960 +2025-06-25 03:16:43,170 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_97.pth was removed +2025-06-25 03:16:43,333 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_107.pth. +2025-06-25 03:16:43,333 - pyskl - INFO - Best top1_acc is 0.9248 at 107 epoch. +2025-06-25 03:16:43,336 - pyskl - INFO - Epoch(val) [107][533] top1_acc: 0.9248, top5_acc: 0.9959, mean_class_accuracy: 0.8960 +2025-06-25 03:18:01,934 - pyskl - INFO - Epoch [108][100/1281] lr: 4.720e-03, eta: 6:18:48, time: 0.786, data_time: 0.187, memory: 4083, top1_acc: 0.9731, top5_acc: 1.0000, loss_cls: 0.1532, loss: 0.1532 +2025-06-25 03:18:51,095 - pyskl - INFO - Epoch [108][200/1281] lr: 4.704e-03, eta: 6:18:10, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.1095, loss: 0.1095 +2025-06-25 03:19:39,804 - pyskl - INFO - Epoch [108][300/1281] lr: 4.688e-03, eta: 6:17:31, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 0.9994, loss_cls: 0.1170, loss: 0.1170 +2025-06-25 03:20:09,805 - pyskl - INFO - Epoch [108][400/1281] lr: 4.672e-03, eta: 6:16:46, time: 0.300, data_time: 0.001, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1519, loss: 0.1519 +2025-06-25 03:21:00,681 - pyskl - INFO - Epoch [108][500/1281] lr: 4.656e-03, eta: 6:16:08, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1575, loss: 0.1575 +2025-06-25 03:21:28,391 - pyskl - INFO - Epoch [108][600/1281] lr: 4.640e-03, eta: 6:15:21, time: 0.277, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1373, loss: 0.1373 +2025-06-25 03:22:17,296 - pyskl - INFO - Epoch [108][700/1281] lr: 4.624e-03, eta: 6:14:43, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1668, loss: 0.1668 +2025-06-25 03:23:05,970 - pyskl - INFO - Epoch [108][800/1281] lr: 4.608e-03, eta: 6:14:05, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 1.0000, loss_cls: 0.1457, loss: 0.1457 +2025-06-25 03:23:55,052 - pyskl - INFO - Epoch [108][900/1281] lr: 4.593e-03, eta: 6:13:26, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.1151, loss: 0.1151 +2025-06-25 03:24:44,113 - pyskl - INFO - Epoch [108][1000/1281] lr: 4.577e-03, eta: 6:12:48, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9663, top5_acc: 1.0000, loss_cls: 0.1919, loss: 0.1919 +2025-06-25 03:25:33,107 - pyskl - INFO - Epoch [108][1100/1281] lr: 4.561e-03, eta: 6:12:09, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1631, loss: 0.1631 +2025-06-25 03:26:22,088 - pyskl - INFO - Epoch [108][1200/1281] lr: 4.545e-03, eta: 6:11:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1340, loss: 0.1340 +2025-06-25 03:27:01,915 - pyskl - INFO - Saving checkpoint at 108 epochs +2025-06-25 03:28:00,598 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:28:00,669 - pyskl - INFO - +top1_acc 0.9079 +top5_acc 0.9955 +2025-06-25 03:28:00,669 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:28:00,676 - pyskl - INFO - +mean_acc 0.8656 +2025-06-25 03:28:00,678 - pyskl - INFO - Epoch(val) [108][533] top1_acc: 0.9079, top5_acc: 0.9955, mean_class_accuracy: 0.8656 +2025-06-25 03:29:20,129 - pyskl - INFO - Epoch [109][100/1281] lr: 4.517e-03, eta: 6:10:18, time: 0.794, data_time: 0.189, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1341, loss: 0.1341 +2025-06-25 03:30:08,802 - pyskl - INFO - Epoch [109][200/1281] lr: 4.501e-03, eta: 6:09:39, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1133, loss: 0.1133 +2025-06-25 03:30:57,636 - pyskl - INFO - Epoch [109][300/1281] lr: 4.485e-03, eta: 6:09:01, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.1087, loss: 0.1087 +2025-06-25 03:31:27,330 - pyskl - INFO - Epoch [109][400/1281] lr: 4.470e-03, eta: 6:08:15, time: 0.297, data_time: 0.000, memory: 4083, top1_acc: 0.9750, top5_acc: 1.0000, loss_cls: 0.1479, loss: 0.1479 +2025-06-25 03:32:18,218 - pyskl - INFO - Epoch [109][500/1281] lr: 4.454e-03, eta: 6:07:37, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1346, loss: 0.1346 +2025-06-25 03:32:46,517 - pyskl - INFO - Epoch [109][600/1281] lr: 4.438e-03, eta: 6:06:51, time: 0.283, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1325, loss: 0.1325 +2025-06-25 03:33:35,435 - pyskl - INFO - Epoch [109][700/1281] lr: 4.423e-03, eta: 6:06:12, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1185, loss: 0.1185 +2025-06-25 03:34:24,281 - pyskl - INFO - Epoch [109][800/1281] lr: 4.407e-03, eta: 6:05:34, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1200, loss: 0.1200 +2025-06-25 03:35:12,877 - pyskl - INFO - Epoch [109][900/1281] lr: 4.391e-03, eta: 6:04:55, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 0.9994, loss_cls: 0.1492, loss: 0.1492 +2025-06-25 03:36:01,787 - pyskl - INFO - Epoch [109][1000/1281] lr: 4.376e-03, eta: 6:04:17, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9744, top5_acc: 1.0000, loss_cls: 0.1493, loss: 0.1493 +2025-06-25 03:36:50,906 - pyskl - INFO - Epoch [109][1100/1281] lr: 4.360e-03, eta: 6:03:38, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.1061, loss: 0.1061 +2025-06-25 03:37:40,233 - pyskl - INFO - Epoch [109][1200/1281] lr: 4.345e-03, eta: 6:03:00, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1200, loss: 0.1200 +2025-06-25 03:38:20,122 - pyskl - INFO - Saving checkpoint at 109 epochs +2025-06-25 03:39:18,755 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:39:18,812 - pyskl - INFO - +top1_acc 0.9213 +top5_acc 0.9942 +2025-06-25 03:39:18,813 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:39:18,820 - pyskl - INFO - +mean_acc 0.8954 +2025-06-25 03:39:18,822 - pyskl - INFO - Epoch(val) [109][533] top1_acc: 0.9213, top5_acc: 0.9942, mean_class_accuracy: 0.8954 +2025-06-25 03:40:38,152 - pyskl - INFO - Epoch [110][100/1281] lr: 4.317e-03, eta: 6:01:47, time: 0.793, data_time: 0.189, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1290, loss: 0.1290 +2025-06-25 03:41:26,988 - pyskl - INFO - Epoch [110][200/1281] lr: 4.301e-03, eta: 6:01:08, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1168, loss: 0.1168 +2025-06-25 03:42:15,540 - pyskl - INFO - Epoch [110][300/1281] lr: 4.286e-03, eta: 6:00:29, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.1157, loss: 0.1157 +2025-06-25 03:42:45,128 - pyskl - INFO - Epoch [110][400/1281] lr: 4.271e-03, eta: 5:59:43, time: 0.296, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.0998, loss: 0.0998 +2025-06-25 03:43:35,727 - pyskl - INFO - Epoch [110][500/1281] lr: 4.255e-03, eta: 5:59:05, time: 0.506, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0908, loss: 0.0908 +2025-06-25 03:44:03,905 - pyskl - INFO - Epoch [110][600/1281] lr: 4.240e-03, eta: 5:58:19, time: 0.282, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1343, loss: 0.1343 +2025-06-25 03:44:52,874 - pyskl - INFO - Epoch [110][700/1281] lr: 4.225e-03, eta: 5:57:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1061, loss: 0.1061 +2025-06-25 03:45:41,814 - pyskl - INFO - Epoch [110][800/1281] lr: 4.209e-03, eta: 5:57:02, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1305, loss: 0.1305 +2025-06-25 03:46:30,685 - pyskl - INFO - Epoch [110][900/1281] lr: 4.194e-03, eta: 5:56:23, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1247, loss: 0.1247 +2025-06-25 03:47:19,725 - pyskl - INFO - Epoch [110][1000/1281] lr: 4.179e-03, eta: 5:55:44, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1151, loss: 0.1151 +2025-06-25 03:48:09,102 - pyskl - INFO - Epoch [110][1100/1281] lr: 4.164e-03, eta: 5:55:06, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.1085, loss: 0.1085 +2025-06-25 03:48:58,256 - pyskl - INFO - Epoch [110][1200/1281] lr: 4.148e-03, eta: 5:54:27, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9738, top5_acc: 0.9994, loss_cls: 0.1584, loss: 0.1584 +2025-06-25 03:49:38,489 - pyskl - INFO - Saving checkpoint at 110 epochs +2025-06-25 03:50:36,764 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 03:50:36,832 - pyskl - INFO - +top1_acc 0.9213 +top5_acc 0.9951 +2025-06-25 03:50:36,832 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 03:50:36,839 - pyskl - INFO - +mean_acc 0.8882 +2025-06-25 03:50:36,841 - pyskl - INFO - Epoch(val) [110][533] top1_acc: 0.9213, top5_acc: 0.9951, mean_class_accuracy: 0.8882 +2025-06-25 03:51:55,657 - pyskl - INFO - Epoch [111][100/1281] lr: 4.121e-03, eta: 5:53:14, time: 0.788, data_time: 0.187, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0930, loss: 0.0930 +2025-06-25 03:52:44,863 - pyskl - INFO - Epoch [111][200/1281] lr: 4.106e-03, eta: 5:52:35, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1044, loss: 0.1044 +2025-06-25 03:53:33,860 - pyskl - INFO - Epoch [111][300/1281] lr: 4.091e-03, eta: 5:51:56, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1028, loss: 0.1028 +2025-06-25 03:54:03,682 - pyskl - INFO - Epoch [111][400/1281] lr: 4.075e-03, eta: 5:51:11, time: 0.298, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 1.0000, loss_cls: 0.1192, loss: 0.1192 +2025-06-25 03:54:54,483 - pyskl - INFO - Epoch [111][500/1281] lr: 4.060e-03, eta: 5:50:33, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1187, loss: 0.1187 +2025-06-25 03:55:21,508 - pyskl - INFO - Epoch [111][600/1281] lr: 4.045e-03, eta: 5:49:46, time: 0.270, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0947, loss: 0.0947 +2025-06-25 03:56:09,979 - pyskl - INFO - Epoch [111][700/1281] lr: 4.030e-03, eta: 5:49:07, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9825, top5_acc: 1.0000, loss_cls: 0.1298, loss: 0.1298 +2025-06-25 03:56:58,618 - pyskl - INFO - Epoch [111][800/1281] lr: 4.015e-03, eta: 5:48:28, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9756, top5_acc: 0.9994, loss_cls: 0.1563, loss: 0.1563 +2025-06-25 03:57:47,328 - pyskl - INFO - Epoch [111][900/1281] lr: 4.000e-03, eta: 5:47:49, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9781, top5_acc: 1.0000, loss_cls: 0.1403, loss: 0.1403 +2025-06-25 03:58:36,501 - pyskl - INFO - Epoch [111][1000/1281] lr: 3.985e-03, eta: 5:47:11, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1498, loss: 0.1498 +2025-06-25 03:59:25,992 - pyskl - INFO - Epoch [111][1100/1281] lr: 3.970e-03, eta: 5:46:32, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1244, loss: 0.1244 +2025-06-25 04:00:14,762 - pyskl - INFO - Epoch [111][1200/1281] lr: 3.955e-03, eta: 5:45:53, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1386, loss: 0.1386 +2025-06-25 04:00:55,170 - pyskl - INFO - Saving checkpoint at 111 epochs +2025-06-25 04:01:53,881 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:01:53,938 - pyskl - INFO - +top1_acc 0.9139 +top5_acc 0.9925 +2025-06-25 04:01:53,938 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:01:53,945 - pyskl - INFO - +mean_acc 0.8878 +2025-06-25 04:01:53,947 - pyskl - INFO - Epoch(val) [111][533] top1_acc: 0.9139, top5_acc: 0.9925, mean_class_accuracy: 0.8878 +2025-06-25 04:03:15,036 - pyskl - INFO - Epoch [112][100/1281] lr: 3.928e-03, eta: 5:44:40, time: 0.811, data_time: 0.192, memory: 4083, top1_acc: 0.9769, top5_acc: 1.0000, loss_cls: 0.1409, loss: 0.1409 +2025-06-25 04:04:03,990 - pyskl - INFO - Epoch [112][200/1281] lr: 3.914e-03, eta: 5:44:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1107, loss: 0.1107 +2025-06-25 04:04:52,984 - pyskl - INFO - Epoch [112][300/1281] lr: 3.899e-03, eta: 5:43:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.1094, loss: 0.1094 +2025-06-25 04:05:22,025 - pyskl - INFO - Epoch [112][400/1281] lr: 3.884e-03, eta: 5:42:36, time: 0.290, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1143, loss: 0.1143 +2025-06-25 04:06:12,823 - pyskl - INFO - Epoch [112][500/1281] lr: 3.869e-03, eta: 5:41:58, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9762, top5_acc: 1.0000, loss_cls: 0.1550, loss: 0.1550 +2025-06-25 04:06:42,049 - pyskl - INFO - Epoch [112][600/1281] lr: 3.854e-03, eta: 5:41:13, time: 0.292, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.1197, loss: 0.1197 +2025-06-25 04:07:30,915 - pyskl - INFO - Epoch [112][700/1281] lr: 3.840e-03, eta: 5:40:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1055, loss: 0.1055 +2025-06-25 04:08:19,655 - pyskl - INFO - Epoch [112][800/1281] lr: 3.825e-03, eta: 5:39:55, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9862, top5_acc: 1.0000, loss_cls: 0.1139, loss: 0.1139 +2025-06-25 04:09:08,490 - pyskl - INFO - Epoch [112][900/1281] lr: 3.810e-03, eta: 5:39:16, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0863, loss: 0.0863 +2025-06-25 04:09:57,445 - pyskl - INFO - Epoch [112][1000/1281] lr: 3.795e-03, eta: 5:38:37, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1073, loss: 0.1073 +2025-06-25 04:10:46,502 - pyskl - INFO - Epoch [112][1100/1281] lr: 3.781e-03, eta: 5:37:58, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0880, loss: 0.0880 +2025-06-25 04:11:35,852 - pyskl - INFO - Epoch [112][1200/1281] lr: 3.766e-03, eta: 5:37:19, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9775, top5_acc: 1.0000, loss_cls: 0.1431, loss: 0.1431 +2025-06-25 04:12:16,091 - pyskl - INFO - Saving checkpoint at 112 epochs +2025-06-25 04:13:14,764 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:13:14,832 - pyskl - INFO - +top1_acc 0.9184 +top5_acc 0.9945 +2025-06-25 04:13:14,832 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:13:14,839 - pyskl - INFO - +mean_acc 0.9012 +2025-06-25 04:13:14,841 - pyskl - INFO - Epoch(val) [112][533] top1_acc: 0.9184, top5_acc: 0.9945, mean_class_accuracy: 0.9012 +2025-06-25 04:14:33,285 - pyskl - INFO - Epoch [113][100/1281] lr: 3.740e-03, eta: 5:36:05, time: 0.784, data_time: 0.185, memory: 4083, top1_acc: 0.9812, top5_acc: 1.0000, loss_cls: 0.1288, loss: 0.1288 +2025-06-25 04:15:22,054 - pyskl - INFO - Epoch [113][200/1281] lr: 3.725e-03, eta: 5:35:26, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9806, top5_acc: 0.9994, loss_cls: 0.1440, loss: 0.1440 +2025-06-25 04:16:10,979 - pyskl - INFO - Epoch [113][300/1281] lr: 3.711e-03, eta: 5:34:47, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1157, loss: 0.1157 +2025-06-25 04:16:40,227 - pyskl - INFO - Epoch [113][400/1281] lr: 3.696e-03, eta: 5:34:01, time: 0.292, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1123, loss: 0.1123 +2025-06-25 04:17:31,008 - pyskl - INFO - Epoch [113][500/1281] lr: 3.682e-03, eta: 5:33:23, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1068, loss: 0.1068 +2025-06-25 04:18:01,184 - pyskl - INFO - Epoch [113][600/1281] lr: 3.667e-03, eta: 5:32:37, time: 0.302, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0837, loss: 0.0837 +2025-06-25 04:18:49,840 - pyskl - INFO - Epoch [113][700/1281] lr: 3.653e-03, eta: 5:31:58, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0940, loss: 0.0940 +2025-06-25 04:19:38,683 - pyskl - INFO - Epoch [113][800/1281] lr: 3.638e-03, eta: 5:31:19, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1060, loss: 0.1060 +2025-06-25 04:20:27,851 - pyskl - INFO - Epoch [113][900/1281] lr: 3.624e-03, eta: 5:30:40, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0899, loss: 0.0899 +2025-06-25 04:21:16,937 - pyskl - INFO - Epoch [113][1000/1281] lr: 3.610e-03, eta: 5:30:01, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0773, loss: 0.0773 +2025-06-25 04:22:05,788 - pyskl - INFO - Epoch [113][1100/1281] lr: 3.595e-03, eta: 5:29:22, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9788, top5_acc: 1.0000, loss_cls: 0.1248, loss: 0.1248 +2025-06-25 04:22:54,784 - pyskl - INFO - Epoch [113][1200/1281] lr: 3.581e-03, eta: 5:28:43, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.1141, loss: 0.1141 +2025-06-25 04:23:35,048 - pyskl - INFO - Saving checkpoint at 113 epochs +2025-06-25 04:24:33,433 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:24:33,489 - pyskl - INFO - +top1_acc 0.9088 +top5_acc 0.9928 +2025-06-25 04:24:33,489 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:24:33,496 - pyskl - INFO - +mean_acc 0.8830 +2025-06-25 04:24:33,497 - pyskl - INFO - Epoch(val) [113][533] top1_acc: 0.9088, top5_acc: 0.9928, mean_class_accuracy: 0.8830 +2025-06-25 04:25:51,958 - pyskl - INFO - Epoch [114][100/1281] lr: 3.555e-03, eta: 5:27:29, time: 0.785, data_time: 0.187, memory: 4083, top1_acc: 0.9800, top5_acc: 1.0000, loss_cls: 0.1265, loss: 0.1265 +2025-06-25 04:26:40,755 - pyskl - INFO - Epoch [114][200/1281] lr: 3.541e-03, eta: 5:26:50, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0891, loss: 0.0891 +2025-06-25 04:27:29,889 - pyskl - INFO - Epoch [114][300/1281] lr: 3.526e-03, eta: 5:26:11, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.0897, loss: 0.0897 +2025-06-25 04:27:58,651 - pyskl - INFO - Epoch [114][400/1281] lr: 3.512e-03, eta: 5:25:25, time: 0.288, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0996, loss: 0.0996 +2025-06-25 04:28:49,427 - pyskl - INFO - Epoch [114][500/1281] lr: 3.498e-03, eta: 5:24:46, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.0949, loss: 0.0949 +2025-06-25 04:29:19,010 - pyskl - INFO - Epoch [114][600/1281] lr: 3.484e-03, eta: 5:24:01, time: 0.296, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0947, loss: 0.0947 +2025-06-25 04:30:07,919 - pyskl - INFO - Epoch [114][700/1281] lr: 3.470e-03, eta: 5:23:22, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0851, loss: 0.0851 +2025-06-25 04:30:56,726 - pyskl - INFO - Epoch [114][800/1281] lr: 3.456e-03, eta: 5:22:43, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.1070, loss: 0.1070 +2025-06-25 04:31:45,672 - pyskl - INFO - Epoch [114][900/1281] lr: 3.442e-03, eta: 5:22:03, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.1035, loss: 0.1035 +2025-06-25 04:32:34,411 - pyskl - INFO - Epoch [114][1000/1281] lr: 3.427e-03, eta: 5:21:24, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0740, loss: 0.0740 +2025-06-25 04:33:23,247 - pyskl - INFO - Epoch [114][1100/1281] lr: 3.413e-03, eta: 5:20:45, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9850, top5_acc: 1.0000, loss_cls: 0.0996, loss: 0.0996 +2025-06-25 04:34:12,338 - pyskl - INFO - Epoch [114][1200/1281] lr: 3.399e-03, eta: 5:20:06, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 1.0000, loss_cls: 0.1028, loss: 0.1028 +2025-06-25 04:34:52,837 - pyskl - INFO - Saving checkpoint at 114 epochs +2025-06-25 04:35:52,074 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:35:52,142 - pyskl - INFO - +top1_acc 0.9240 +top5_acc 0.9964 +2025-06-25 04:35:52,142 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:35:52,150 - pyskl - INFO - +mean_acc 0.8960 +2025-06-25 04:35:52,152 - pyskl - INFO - Epoch(val) [114][533] top1_acc: 0.9240, top5_acc: 0.9964, mean_class_accuracy: 0.8960 +2025-06-25 04:37:10,320 - pyskl - INFO - Epoch [115][100/1281] lr: 3.374e-03, eta: 5:18:51, time: 0.782, data_time: 0.186, memory: 4083, top1_acc: 0.9850, top5_acc: 0.9994, loss_cls: 0.1053, loss: 0.1053 +2025-06-25 04:37:59,282 - pyskl - INFO - Epoch [115][200/1281] lr: 3.360e-03, eta: 5:18:12, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0720, loss: 0.0720 +2025-06-25 04:38:48,741 - pyskl - INFO - Epoch [115][300/1281] lr: 3.346e-03, eta: 5:17:33, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0672, loss: 0.0672 +2025-06-25 04:39:17,386 - pyskl - INFO - Epoch [115][400/1281] lr: 3.332e-03, eta: 5:16:47, time: 0.286, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0757, loss: 0.0757 +2025-06-25 04:40:08,123 - pyskl - INFO - Epoch [115][500/1281] lr: 3.318e-03, eta: 5:16:09, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0635, loss: 0.0635 +2025-06-25 04:40:36,908 - pyskl - INFO - Epoch [115][600/1281] lr: 3.305e-03, eta: 5:15:23, time: 0.288, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0824, loss: 0.0824 +2025-06-25 04:41:25,757 - pyskl - INFO - Epoch [115][700/1281] lr: 3.291e-03, eta: 5:14:44, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0873, loss: 0.0873 +2025-06-25 04:42:14,678 - pyskl - INFO - Epoch [115][800/1281] lr: 3.277e-03, eta: 5:14:04, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0807, loss: 0.0807 +2025-06-25 04:43:03,479 - pyskl - INFO - Epoch [115][900/1281] lr: 3.263e-03, eta: 5:13:25, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0942, loss: 0.0942 +2025-06-25 04:43:52,613 - pyskl - INFO - Epoch [115][1000/1281] lr: 3.249e-03, eta: 5:12:46, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0950, loss: 0.0950 +2025-06-25 04:44:41,471 - pyskl - INFO - Epoch [115][1100/1281] lr: 3.236e-03, eta: 5:12:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0887, loss: 0.0887 +2025-06-25 04:45:30,907 - pyskl - INFO - Epoch [115][1200/1281] lr: 3.222e-03, eta: 5:11:27, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0888, loss: 0.0888 +2025-06-25 04:46:11,096 - pyskl - INFO - Saving checkpoint at 115 epochs +2025-06-25 04:47:09,499 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:47:09,555 - pyskl - INFO - +top1_acc 0.9242 +top5_acc 0.9951 +2025-06-25 04:47:09,556 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:47:09,562 - pyskl - INFO - +mean_acc 0.8920 +2025-06-25 04:47:09,564 - pyskl - INFO - Epoch(val) [115][533] top1_acc: 0.9242, top5_acc: 0.9951, mean_class_accuracy: 0.8920 +2025-06-25 04:48:27,798 - pyskl - INFO - Epoch [116][100/1281] lr: 3.197e-03, eta: 5:10:13, time: 0.782, data_time: 0.183, memory: 4083, top1_acc: 0.9831, top5_acc: 1.0000, loss_cls: 0.1135, loss: 0.1135 +2025-06-25 04:49:16,793 - pyskl - INFO - Epoch [116][200/1281] lr: 3.184e-03, eta: 5:09:33, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0892, loss: 0.0892 +2025-06-25 04:50:05,744 - pyskl - INFO - Epoch [116][300/1281] lr: 3.170e-03, eta: 5:08:54, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 0.9994, loss_cls: 0.0890, loss: 0.0890 +2025-06-25 04:50:34,978 - pyskl - INFO - Epoch [116][400/1281] lr: 3.156e-03, eta: 5:08:09, time: 0.292, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0854, loss: 0.0854 +2025-06-25 04:51:25,737 - pyskl - INFO - Epoch [116][500/1281] lr: 3.143e-03, eta: 5:07:30, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0676, loss: 0.0676 +2025-06-25 04:51:54,855 - pyskl - INFO - Epoch [116][600/1281] lr: 3.129e-03, eta: 5:06:44, time: 0.291, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0769, loss: 0.0769 +2025-06-25 04:52:43,640 - pyskl - INFO - Epoch [116][700/1281] lr: 3.116e-03, eta: 5:06:05, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 0.9994, loss_cls: 0.0894, loss: 0.0894 +2025-06-25 04:53:32,636 - pyskl - INFO - Epoch [116][800/1281] lr: 3.102e-03, eta: 5:05:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0881, loss: 0.0881 +2025-06-25 04:54:21,205 - pyskl - INFO - Epoch [116][900/1281] lr: 3.089e-03, eta: 5:04:46, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0836, loss: 0.0836 +2025-06-25 04:55:10,101 - pyskl - INFO - Epoch [116][1000/1281] lr: 3.075e-03, eta: 5:04:06, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0665, loss: 0.0665 +2025-06-25 04:55:59,013 - pyskl - INFO - Epoch [116][1100/1281] lr: 3.062e-03, eta: 5:03:27, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0782, loss: 0.0782 +2025-06-25 04:56:48,510 - pyskl - INFO - Epoch [116][1200/1281] lr: 3.049e-03, eta: 5:02:48, time: 0.495, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0750, loss: 0.0750 +2025-06-25 04:57:28,173 - pyskl - INFO - Saving checkpoint at 116 epochs +2025-06-25 04:58:26,095 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 04:58:26,165 - pyskl - INFO - +top1_acc 0.9328 +top5_acc 0.9965 +2025-06-25 04:58:26,165 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 04:58:26,173 - pyskl - INFO - +mean_acc 0.9114 +2025-06-25 04:58:26,178 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_107.pth was removed +2025-06-25 04:58:26,365 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_116.pth. +2025-06-25 04:58:26,365 - pyskl - INFO - Best top1_acc is 0.9328 at 116 epoch. +2025-06-25 04:58:26,368 - pyskl - INFO - Epoch(val) [116][533] top1_acc: 0.9328, top5_acc: 0.9965, mean_class_accuracy: 0.9114 +2025-06-25 04:59:45,546 - pyskl - INFO - Epoch [117][100/1281] lr: 3.024e-03, eta: 5:01:33, time: 0.792, data_time: 0.191, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0780, loss: 0.0780 +2025-06-25 05:00:34,087 - pyskl - INFO - Epoch [117][200/1281] lr: 3.011e-03, eta: 5:00:54, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9856, top5_acc: 1.0000, loss_cls: 0.0924, loss: 0.0924 +2025-06-25 05:01:22,982 - pyskl - INFO - Epoch [117][300/1281] lr: 2.998e-03, eta: 5:00:14, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9819, top5_acc: 1.0000, loss_cls: 0.1169, loss: 0.1169 +2025-06-25 05:01:51,469 - pyskl - INFO - Epoch [117][400/1281] lr: 2.984e-03, eta: 4:59:29, time: 0.285, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0942, loss: 0.0942 +2025-06-25 05:02:42,327 - pyskl - INFO - Epoch [117][500/1281] lr: 2.971e-03, eta: 4:58:50, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0826, loss: 0.0826 +2025-06-25 05:03:10,596 - pyskl - INFO - Epoch [117][600/1281] lr: 2.958e-03, eta: 4:58:04, time: 0.283, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0711, loss: 0.0711 +2025-06-25 05:03:59,430 - pyskl - INFO - Epoch [117][700/1281] lr: 2.945e-03, eta: 4:57:25, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0717, loss: 0.0717 +2025-06-25 05:04:48,354 - pyskl - INFO - Epoch [117][800/1281] lr: 2.932e-03, eta: 4:56:45, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0756, loss: 0.0756 +2025-06-25 05:05:37,455 - pyskl - INFO - Epoch [117][900/1281] lr: 2.919e-03, eta: 4:56:06, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9838, top5_acc: 0.9994, loss_cls: 0.1023, loss: 0.1023 +2025-06-25 05:06:26,280 - pyskl - INFO - Epoch [117][1000/1281] lr: 2.905e-03, eta: 4:55:26, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9869, top5_acc: 0.9994, loss_cls: 0.1052, loss: 0.1052 +2025-06-25 05:07:15,499 - pyskl - INFO - Epoch [117][1100/1281] lr: 2.892e-03, eta: 4:54:47, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9844, top5_acc: 1.0000, loss_cls: 0.0985, loss: 0.0985 +2025-06-25 05:08:04,162 - pyskl - INFO - Epoch [117][1200/1281] lr: 2.879e-03, eta: 4:54:07, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0862, loss: 0.0862 +2025-06-25 05:08:44,477 - pyskl - INFO - Saving checkpoint at 117 epochs +2025-06-25 05:09:42,724 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:09:42,779 - pyskl - INFO - +top1_acc 0.9283 +top5_acc 0.9947 +2025-06-25 05:09:42,780 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:09:42,787 - pyskl - INFO - +mean_acc 0.9022 +2025-06-25 05:09:42,788 - pyskl - INFO - Epoch(val) [117][533] top1_acc: 0.9283, top5_acc: 0.9947, mean_class_accuracy: 0.9022 +2025-06-25 05:11:02,252 - pyskl - INFO - Epoch [118][100/1281] lr: 2.856e-03, eta: 4:52:53, time: 0.795, data_time: 0.185, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0884, loss: 0.0884 +2025-06-25 05:11:51,228 - pyskl - INFO - Epoch [118][200/1281] lr: 2.843e-03, eta: 4:52:13, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0699, loss: 0.0699 +2025-06-25 05:12:40,274 - pyskl - INFO - Epoch [118][300/1281] lr: 2.830e-03, eta: 4:51:33, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0776, loss: 0.0776 +2025-06-25 05:13:09,742 - pyskl - INFO - Epoch [118][400/1281] lr: 2.817e-03, eta: 4:50:48, time: 0.295, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0866, loss: 0.0866 +2025-06-25 05:14:00,466 - pyskl - INFO - Epoch [118][500/1281] lr: 2.804e-03, eta: 4:50:09, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0637, loss: 0.0637 +2025-06-25 05:14:27,060 - pyskl - INFO - Epoch [118][600/1281] lr: 2.791e-03, eta: 4:49:23, time: 0.266, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0757, loss: 0.0757 +2025-06-25 05:15:15,799 - pyskl - INFO - Epoch [118][700/1281] lr: 2.778e-03, eta: 4:48:44, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0760, loss: 0.0760 +2025-06-25 05:16:04,520 - pyskl - INFO - Epoch [118][800/1281] lr: 2.765e-03, eta: 4:48:04, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9900, top5_acc: 1.0000, loss_cls: 0.0718, loss: 0.0718 +2025-06-25 05:16:53,405 - pyskl - INFO - Epoch [118][900/1281] lr: 2.753e-03, eta: 4:47:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0859, loss: 0.0859 +2025-06-25 05:17:42,583 - pyskl - INFO - Epoch [118][1000/1281] lr: 2.740e-03, eta: 4:46:44, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0566, loss: 0.0566 +2025-06-25 05:18:31,602 - pyskl - INFO - Epoch [118][1100/1281] lr: 2.727e-03, eta: 4:46:05, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0526, loss: 0.0526 +2025-06-25 05:19:20,459 - pyskl - INFO - Epoch [118][1200/1281] lr: 2.714e-03, eta: 4:45:25, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9881, top5_acc: 1.0000, loss_cls: 0.0763, loss: 0.0763 +2025-06-25 05:20:00,485 - pyskl - INFO - Saving checkpoint at 118 epochs +2025-06-25 05:20:58,641 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:20:58,697 - pyskl - INFO - +top1_acc 0.9276 +top5_acc 0.9955 +2025-06-25 05:20:58,697 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:20:58,704 - pyskl - INFO - +mean_acc 0.9008 +2025-06-25 05:20:58,706 - pyskl - INFO - Epoch(val) [118][533] top1_acc: 0.9276, top5_acc: 0.9955, mean_class_accuracy: 0.9008 +2025-06-25 05:22:18,786 - pyskl - INFO - Epoch [119][100/1281] lr: 2.691e-03, eta: 4:44:11, time: 0.801, data_time: 0.186, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0759, loss: 0.0759 +2025-06-25 05:23:07,391 - pyskl - INFO - Epoch [119][200/1281] lr: 2.679e-03, eta: 4:43:31, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0513, loss: 0.0513 +2025-06-25 05:23:56,266 - pyskl - INFO - Epoch [119][300/1281] lr: 2.666e-03, eta: 4:42:51, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0597, loss: 0.0597 +2025-06-25 05:24:27,676 - pyskl - INFO - Epoch [119][400/1281] lr: 2.653e-03, eta: 4:42:07, time: 0.314, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0657, loss: 0.0657 +2025-06-25 05:25:18,390 - pyskl - INFO - Epoch [119][500/1281] lr: 2.641e-03, eta: 4:41:27, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0579, loss: 0.0579 +2025-06-25 05:25:45,229 - pyskl - INFO - Epoch [119][600/1281] lr: 2.628e-03, eta: 4:40:42, time: 0.268, data_time: 0.000, memory: 4083, top1_acc: 0.9894, top5_acc: 1.0000, loss_cls: 0.0818, loss: 0.0818 +2025-06-25 05:26:34,447 - pyskl - INFO - Epoch [119][700/1281] lr: 2.616e-03, eta: 4:40:02, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0609, loss: 0.0609 +2025-06-25 05:27:22,791 - pyskl - INFO - Epoch [119][800/1281] lr: 2.603e-03, eta: 4:39:22, time: 0.483, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0511, loss: 0.0511 +2025-06-25 05:28:11,675 - pyskl - INFO - Epoch [119][900/1281] lr: 2.591e-03, eta: 4:38:42, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0604, loss: 0.0604 +2025-06-25 05:29:00,463 - pyskl - INFO - Epoch [119][1000/1281] lr: 2.578e-03, eta: 4:38:02, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0678, loss: 0.0678 +2025-06-25 05:29:49,364 - pyskl - INFO - Epoch [119][1100/1281] lr: 2.566e-03, eta: 4:37:23, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 0.9994, loss_cls: 0.0680, loss: 0.0680 +2025-06-25 05:30:38,252 - pyskl - INFO - Epoch [119][1200/1281] lr: 2.554e-03, eta: 4:36:43, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 0.9994, loss_cls: 0.0719, loss: 0.0719 +2025-06-25 05:31:18,485 - pyskl - INFO - Saving checkpoint at 119 epochs +2025-06-25 05:32:16,645 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:32:16,701 - pyskl - INFO - +top1_acc 0.9291 +top5_acc 0.9954 +2025-06-25 05:32:16,701 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:32:16,708 - pyskl - INFO - +mean_acc 0.9070 +2025-06-25 05:32:16,710 - pyskl - INFO - Epoch(val) [119][533] top1_acc: 0.9291, top5_acc: 0.9954, mean_class_accuracy: 0.9070 +2025-06-25 05:33:36,430 - pyskl - INFO - Epoch [120][100/1281] lr: 2.531e-03, eta: 4:35:28, time: 0.797, data_time: 0.186, memory: 4083, top1_acc: 0.9862, top5_acc: 0.9994, loss_cls: 0.1084, loss: 0.1084 +2025-06-25 05:34:25,215 - pyskl - INFO - Epoch [120][200/1281] lr: 2.519e-03, eta: 4:34:48, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0598, loss: 0.0598 +2025-06-25 05:35:14,001 - pyskl - INFO - Epoch [120][300/1281] lr: 2.507e-03, eta: 4:34:09, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0664, loss: 0.0664 +2025-06-25 05:35:45,229 - pyskl - INFO - Epoch [120][400/1281] lr: 2.494e-03, eta: 4:33:24, time: 0.312, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0535, loss: 0.0535 +2025-06-25 05:36:36,104 - pyskl - INFO - Epoch [120][500/1281] lr: 2.482e-03, eta: 4:32:45, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0580, loss: 0.0580 +2025-06-25 05:37:02,968 - pyskl - INFO - Epoch [120][600/1281] lr: 2.470e-03, eta: 4:31:59, time: 0.269, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0601, loss: 0.0601 +2025-06-25 05:37:51,831 - pyskl - INFO - Epoch [120][700/1281] lr: 2.458e-03, eta: 4:31:19, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0557, loss: 0.0557 +2025-06-25 05:38:40,302 - pyskl - INFO - Epoch [120][800/1281] lr: 2.446e-03, eta: 4:30:39, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0614, loss: 0.0614 +2025-06-25 05:39:29,594 - pyskl - INFO - Epoch [120][900/1281] lr: 2.433e-03, eta: 4:29:59, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9925, top5_acc: 1.0000, loss_cls: 0.0737, loss: 0.0737 +2025-06-25 05:40:18,474 - pyskl - INFO - Epoch [120][1000/1281] lr: 2.421e-03, eta: 4:29:19, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0544, loss: 0.0544 +2025-06-25 05:41:07,492 - pyskl - INFO - Epoch [120][1100/1281] lr: 2.409e-03, eta: 4:28:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9875, top5_acc: 1.0000, loss_cls: 0.0752, loss: 0.0752 +2025-06-25 05:41:55,961 - pyskl - INFO - Epoch [120][1200/1281] lr: 2.397e-03, eta: 4:28:00, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0542, loss: 0.0542 +2025-06-25 05:42:36,336 - pyskl - INFO - Saving checkpoint at 120 epochs +2025-06-25 05:43:34,263 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:43:34,322 - pyskl - INFO - +top1_acc 0.9319 +top5_acc 0.9957 +2025-06-25 05:43:34,322 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:43:34,330 - pyskl - INFO - +mean_acc 0.9072 +2025-06-25 05:43:34,331 - pyskl - INFO - Epoch(val) [120][533] top1_acc: 0.9319, top5_acc: 0.9957, mean_class_accuracy: 0.9072 +2025-06-25 05:44:55,566 - pyskl - INFO - Epoch [121][100/1281] lr: 2.375e-03, eta: 4:26:45, time: 0.812, data_time: 0.186, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0455, loss: 0.0455 +2025-06-25 05:45:44,443 - pyskl - INFO - Epoch [121][200/1281] lr: 2.363e-03, eta: 4:26:05, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0463, loss: 0.0463 +2025-06-25 05:46:33,144 - pyskl - INFO - Epoch [121][300/1281] lr: 2.351e-03, eta: 4:25:25, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0460, loss: 0.0460 +2025-06-25 05:47:03,703 - pyskl - INFO - Epoch [121][400/1281] lr: 2.340e-03, eta: 4:24:41, time: 0.306, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0473, loss: 0.0473 +2025-06-25 05:47:54,343 - pyskl - INFO - Epoch [121][500/1281] lr: 2.328e-03, eta: 4:24:01, time: 0.506, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0401, loss: 0.0401 +2025-06-25 05:48:21,511 - pyskl - INFO - Epoch [121][600/1281] lr: 2.316e-03, eta: 4:23:16, time: 0.272, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0393, loss: 0.0393 +2025-06-25 05:49:10,545 - pyskl - INFO - Epoch [121][700/1281] lr: 2.304e-03, eta: 4:22:36, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0569, loss: 0.0569 +2025-06-25 05:49:59,332 - pyskl - INFO - Epoch [121][800/1281] lr: 2.292e-03, eta: 4:21:56, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0629, loss: 0.0629 +2025-06-25 05:50:47,800 - pyskl - INFO - Epoch [121][900/1281] lr: 2.280e-03, eta: 4:21:16, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0425, loss: 0.0425 +2025-06-25 05:51:36,660 - pyskl - INFO - Epoch [121][1000/1281] lr: 2.269e-03, eta: 4:20:36, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0476, loss: 0.0476 +2025-06-25 05:52:25,708 - pyskl - INFO - Epoch [121][1100/1281] lr: 2.257e-03, eta: 4:19:56, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0533, loss: 0.0533 +2025-06-25 05:53:14,645 - pyskl - INFO - Epoch [121][1200/1281] lr: 2.245e-03, eta: 4:19:16, 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 05:53:54,856 - pyskl - INFO - Saving checkpoint at 121 epochs +2025-06-25 05:54:53,216 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 05:54:53,287 - pyskl - INFO - +top1_acc 0.9343 +top5_acc 0.9955 +2025-06-25 05:54:53,287 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 05:54:53,296 - pyskl - INFO - +mean_acc 0.9076 +2025-06-25 05:54:53,301 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_116.pth was removed +2025-06-25 05:54:53,490 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_121.pth. +2025-06-25 05:54:53,490 - pyskl - INFO - Best top1_acc is 0.9343 at 121 epoch. +2025-06-25 05:54:53,493 - pyskl - INFO - Epoch(val) [121][533] top1_acc: 0.9343, top5_acc: 0.9955, mean_class_accuracy: 0.9076 +2025-06-25 05:56:12,925 - pyskl - INFO - Epoch [122][100/1281] lr: 2.224e-03, eta: 4:18:01, time: 0.794, data_time: 0.186, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0401, loss: 0.0401 +2025-06-25 05:57:01,465 - pyskl - INFO - Epoch [122][200/1281] lr: 2.212e-03, eta: 4:17:21, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0445, loss: 0.0445 +2025-06-25 05:57:50,179 - pyskl - INFO - Epoch [122][300/1281] lr: 2.201e-03, eta: 4:16:41, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0461, loss: 0.0461 +2025-06-25 05:58:20,942 - pyskl - INFO - Epoch [122][400/1281] lr: 2.189e-03, eta: 4:15:56, time: 0.308, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0495, loss: 0.0495 +2025-06-25 05:59:11,869 - pyskl - INFO - Epoch [122][500/1281] lr: 2.178e-03, eta: 4:15:16, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 1.0000, loss_cls: 0.0710, loss: 0.0710 +2025-06-25 05:59:39,202 - pyskl - INFO - Epoch [122][600/1281] lr: 2.166e-03, eta: 4:14:31, time: 0.273, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0473, loss: 0.0473 +2025-06-25 06:00:27,949 - pyskl - INFO - Epoch [122][700/1281] lr: 2.155e-03, eta: 4:13:51, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0586, loss: 0.0586 +2025-06-25 06:01:17,261 - pyskl - INFO - Epoch [122][800/1281] lr: 2.143e-03, eta: 4:13:11, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9938, top5_acc: 1.0000, loss_cls: 0.0642, loss: 0.0642 +2025-06-25 06:02:05,979 - pyskl - INFO - Epoch [122][900/1281] lr: 2.132e-03, eta: 4:12:31, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9906, top5_acc: 0.9994, loss_cls: 0.0829, loss: 0.0829 +2025-06-25 06:02:55,103 - pyskl - INFO - Epoch [122][1000/1281] lr: 2.120e-03, eta: 4:11:51, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0534, loss: 0.0534 +2025-06-25 06:03:44,247 - pyskl - INFO - Epoch [122][1100/1281] lr: 2.109e-03, eta: 4:11:11, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0622, loss: 0.0622 +2025-06-25 06:04:33,199 - pyskl - INFO - Epoch [122][1200/1281] lr: 2.098e-03, eta: 4:10:31, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0545, loss: 0.0545 +2025-06-25 06:05:13,157 - pyskl - INFO - Saving checkpoint at 122 epochs +2025-06-25 06:06:11,173 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:06:11,235 - pyskl - INFO - +top1_acc 0.9343 +top5_acc 0.9965 +2025-06-25 06:06:11,235 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:06:11,242 - pyskl - INFO - +mean_acc 0.9103 +2025-06-25 06:06:11,244 - pyskl - INFO - Epoch(val) [122][533] top1_acc: 0.9343, top5_acc: 0.9965, mean_class_accuracy: 0.9103 +2025-06-25 06:07:30,369 - pyskl - INFO - Epoch [123][100/1281] lr: 2.077e-03, eta: 4:09:16, time: 0.791, data_time: 0.183, memory: 4083, top1_acc: 0.9919, top5_acc: 0.9994, loss_cls: 0.0604, loss: 0.0604 +2025-06-25 06:08:19,203 - pyskl - INFO - Epoch [123][200/1281] lr: 2.066e-03, eta: 4:08:35, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0412, loss: 0.0412 +2025-06-25 06:09:08,311 - pyskl - INFO - Epoch [123][300/1281] lr: 2.055e-03, eta: 4:07:55, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0445, loss: 0.0445 +2025-06-25 06:09:39,882 - pyskl - INFO - Epoch [123][400/1281] lr: 2.044e-03, eta: 4:07:11, time: 0.316, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0580, loss: 0.0580 +2025-06-25 06:10:30,679 - pyskl - INFO - Epoch [123][500/1281] lr: 2.032e-03, eta: 4:06:31, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0428, loss: 0.0428 +2025-06-25 06:10:55,772 - pyskl - INFO - Epoch [123][600/1281] lr: 2.021e-03, eta: 4:05:46, time: 0.251, data_time: 0.000, memory: 4083, top1_acc: 0.9931, top5_acc: 1.0000, loss_cls: 0.0576, loss: 0.0576 +2025-06-25 06:11:44,539 - pyskl - INFO - Epoch [123][700/1281] lr: 2.010e-03, eta: 4:05:05, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0546, loss: 0.0546 +2025-06-25 06:12:33,341 - pyskl - INFO - Epoch [123][800/1281] lr: 1.999e-03, eta: 4:04:25, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0509, loss: 0.0509 +2025-06-25 06:13:22,329 - pyskl - INFO - Epoch [123][900/1281] lr: 1.988e-03, eta: 4:03:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0497, loss: 0.0497 +2025-06-25 06:14:11,185 - pyskl - INFO - Epoch [123][1000/1281] lr: 1.977e-03, eta: 4:03:05, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0462, loss: 0.0462 +2025-06-25 06:15:00,150 - pyskl - INFO - Epoch [123][1100/1281] lr: 1.966e-03, eta: 4:02:24, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0463, loss: 0.0463 +2025-06-25 06:15:49,033 - pyskl - INFO - Epoch [123][1200/1281] lr: 1.955e-03, eta: 4:01:44, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0559, loss: 0.0559 +2025-06-25 06:16:29,226 - pyskl - INFO - Saving checkpoint at 123 epochs +2025-06-25 06:17:27,918 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:17:27,972 - pyskl - INFO - +top1_acc 0.9337 +top5_acc 0.9952 +2025-06-25 06:17:27,973 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:17:27,979 - pyskl - INFO - +mean_acc 0.9065 +2025-06-25 06:17:27,981 - pyskl - INFO - Epoch(val) [123][533] top1_acc: 0.9337, top5_acc: 0.9952, mean_class_accuracy: 0.9065 +2025-06-25 06:18:47,373 - pyskl - INFO - Epoch [124][100/1281] lr: 1.935e-03, eta: 4:00:29, time: 0.794, data_time: 0.184, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0473, loss: 0.0473 +2025-06-25 06:19:36,291 - pyskl - INFO - Epoch [124][200/1281] lr: 1.924e-03, eta: 3:59:49, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0518, loss: 0.0518 +2025-06-25 06:20:25,012 - pyskl - INFO - Epoch [124][300/1281] lr: 1.913e-03, eta: 3:59:09, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0482, loss: 0.0482 +2025-06-25 06:20:56,806 - pyskl - INFO - Epoch [124][400/1281] lr: 1.902e-03, eta: 3:58:25, time: 0.318, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0355, loss: 0.0355 +2025-06-25 06:21:47,620 - pyskl - INFO - Epoch [124][500/1281] lr: 1.892e-03, eta: 3:57:45, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0394, loss: 0.0394 +2025-06-25 06:22:13,018 - pyskl - INFO - Epoch [124][600/1281] lr: 1.881e-03, eta: 3:56:59, time: 0.254, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0441, loss: 0.0441 +2025-06-25 06:23:01,743 - pyskl - INFO - Epoch [124][700/1281] lr: 1.870e-03, eta: 3:56:19, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0382, loss: 0.0382 +2025-06-25 06:23:50,665 - pyskl - INFO - Epoch [124][800/1281] lr: 1.859e-03, eta: 3:55:39, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0532, loss: 0.0532 +2025-06-25 06:24:39,638 - pyskl - INFO - Epoch [124][900/1281] lr: 1.849e-03, eta: 3:54:58, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9912, top5_acc: 1.0000, loss_cls: 0.0634, loss: 0.0634 +2025-06-25 06:25:28,409 - pyskl - INFO - Epoch [124][1000/1281] lr: 1.838e-03, eta: 3:54:18, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9888, top5_acc: 1.0000, loss_cls: 0.0819, loss: 0.0819 +2025-06-25 06:26:17,720 - pyskl - INFO - Epoch [124][1100/1281] lr: 1.827e-03, eta: 3:53:38, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9919, top5_acc: 1.0000, loss_cls: 0.0754, loss: 0.0754 +2025-06-25 06:27:06,873 - pyskl - INFO - Epoch [124][1200/1281] lr: 1.817e-03, eta: 3:52:57, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0441, loss: 0.0441 +2025-06-25 06:27:47,207 - pyskl - INFO - Saving checkpoint at 124 epochs +2025-06-25 06:28:44,872 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:28:44,927 - pyskl - INFO - +top1_acc 0.9342 +top5_acc 0.9966 +2025-06-25 06:28:44,927 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:28:44,934 - pyskl - INFO - +mean_acc 0.9062 +2025-06-25 06:28:44,936 - pyskl - INFO - Epoch(val) [124][533] top1_acc: 0.9342, top5_acc: 0.9966, mean_class_accuracy: 0.9062 +2025-06-25 06:30:05,262 - pyskl - INFO - Epoch [125][100/1281] lr: 1.797e-03, eta: 3:51:42, time: 0.803, data_time: 0.188, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0397, loss: 0.0397 +2025-06-25 06:30:53,976 - pyskl - INFO - Epoch [125][200/1281] lr: 1.787e-03, eta: 3:51:02, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0347, loss: 0.0347 +2025-06-25 06:31:42,799 - pyskl - INFO - Epoch [125][300/1281] lr: 1.776e-03, eta: 3:50:22, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0349, loss: 0.0349 +2025-06-25 06:32:15,476 - pyskl - INFO - Epoch [125][400/1281] lr: 1.766e-03, eta: 3:49:38, time: 0.327, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0370, loss: 0.0370 +2025-06-25 06:33:06,315 - pyskl - INFO - Epoch [125][500/1281] lr: 1.755e-03, eta: 3:48:58, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0329, loss: 0.0329 +2025-06-25 06:33:31,666 - pyskl - INFO - Epoch [125][600/1281] lr: 1.745e-03, eta: 3:48:12, time: 0.254, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0293, loss: 0.0293 +2025-06-25 06:34:20,339 - pyskl - INFO - Epoch [125][700/1281] lr: 1.735e-03, eta: 3:47:32, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0390, loss: 0.0390 +2025-06-25 06:35:09,256 - pyskl - INFO - Epoch [125][800/1281] lr: 1.724e-03, eta: 3:46:52, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0474, loss: 0.0474 +2025-06-25 06:35:58,149 - pyskl - INFO - Epoch [125][900/1281] lr: 1.714e-03, eta: 3:46:11, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0431, loss: 0.0431 +2025-06-25 06:36:47,154 - pyskl - INFO - Epoch [125][1000/1281] lr: 1.704e-03, eta: 3:45:31, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0330, loss: 0.0330 +2025-06-25 06:37:36,459 - pyskl - INFO - Epoch [125][1100/1281] lr: 1.693e-03, eta: 3:44:50, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0415, loss: 0.0415 +2025-06-25 06:38:25,634 - pyskl - INFO - Epoch [125][1200/1281] lr: 1.683e-03, eta: 3:44:10, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0291, loss: 0.0291 +2025-06-25 06:39:05,618 - pyskl - INFO - Saving checkpoint at 125 epochs +2025-06-25 06:40:04,026 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:40:04,085 - pyskl - INFO - +top1_acc 0.9282 +top5_acc 0.9962 +2025-06-25 06:40:04,085 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:40:04,094 - pyskl - INFO - +mean_acc 0.9054 +2025-06-25 06:40:04,096 - pyskl - INFO - Epoch(val) [125][533] top1_acc: 0.9282, top5_acc: 0.9962, mean_class_accuracy: 0.9054 +2025-06-25 06:41:25,181 - pyskl - INFO - Epoch [126][100/1281] lr: 1.665e-03, eta: 3:42:55, time: 0.811, data_time: 0.192, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0392, loss: 0.0392 +2025-06-25 06:42:13,812 - pyskl - INFO - Epoch [126][200/1281] lr: 1.654e-03, eta: 3:42:15, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0386, loss: 0.0386 +2025-06-25 06:43:02,766 - pyskl - INFO - Epoch [126][300/1281] lr: 1.644e-03, eta: 3:41:34, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0343, loss: 0.0343 +2025-06-25 06:43:33,546 - pyskl - INFO - Epoch [126][400/1281] lr: 1.634e-03, eta: 3:40:50, time: 0.308, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0431, loss: 0.0431 +2025-06-25 06:44:24,406 - pyskl - INFO - Epoch [126][500/1281] lr: 1.624e-03, eta: 3:40:10, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0408, loss: 0.0408 +2025-06-25 06:44:51,658 - pyskl - INFO - Epoch [126][600/1281] lr: 1.614e-03, eta: 3:39:25, time: 0.273, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0315, loss: 0.0315 +2025-06-25 06:45:40,641 - pyskl - INFO - Epoch [126][700/1281] lr: 1.604e-03, eta: 3:38:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9950, top5_acc: 1.0000, loss_cls: 0.0461, loss: 0.0461 +2025-06-25 06:46:29,400 - pyskl - INFO - Epoch [126][800/1281] lr: 1.594e-03, eta: 3:38:04, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0339, loss: 0.0339 +2025-06-25 06:47:17,960 - pyskl - INFO - Epoch [126][900/1281] lr: 1.584e-03, eta: 3:37:23, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0375, loss: 0.0375 +2025-06-25 06:48:06,883 - pyskl - INFO - Epoch [126][1000/1281] lr: 1.574e-03, eta: 3:36:43, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0352, loss: 0.0352 +2025-06-25 06:48:55,947 - pyskl - INFO - Epoch [126][1100/1281] lr: 1.564e-03, eta: 3:36:02, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0333, loss: 0.0333 +2025-06-25 06:49:44,691 - pyskl - INFO - Epoch [126][1200/1281] lr: 1.554e-03, eta: 3:35:22, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0306, loss: 0.0306 +2025-06-25 06:50:24,848 - pyskl - INFO - Saving checkpoint at 126 epochs +2025-06-25 06:51:23,020 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 06:51:23,092 - pyskl - INFO - +top1_acc 0.9371 +top5_acc 0.9961 +2025-06-25 06:51:23,092 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 06:51:23,100 - pyskl - INFO - +mean_acc 0.9128 +2025-06-25 06:51:23,105 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_121.pth was removed +2025-06-25 06:51:23,443 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_126.pth. +2025-06-25 06:51:23,443 - pyskl - INFO - Best top1_acc is 0.9371 at 126 epoch. +2025-06-25 06:51:23,446 - pyskl - INFO - Epoch(val) [126][533] top1_acc: 0.9371, top5_acc: 0.9961, mean_class_accuracy: 0.9128 +2025-06-25 06:52:43,639 - pyskl - INFO - Epoch [127][100/1281] lr: 1.536e-03, eta: 3:34:07, time: 0.802, data_time: 0.193, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0295, loss: 0.0295 +2025-06-25 06:53:32,222 - pyskl - INFO - Epoch [127][200/1281] lr: 1.527e-03, eta: 3:33:26, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9956, top5_acc: 1.0000, loss_cls: 0.0441, loss: 0.0441 +2025-06-25 06:54:21,408 - pyskl - INFO - Epoch [127][300/1281] lr: 1.517e-03, eta: 3:32:45, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0318, loss: 0.0318 +2025-06-25 06:54:50,856 - pyskl - INFO - Epoch [127][400/1281] lr: 1.507e-03, eta: 3:32:01, time: 0.294, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0347, loss: 0.0347 +2025-06-25 06:55:41,761 - pyskl - INFO - Epoch [127][500/1281] lr: 1.497e-03, eta: 3:31:21, time: 0.509, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0356, loss: 0.0356 +2025-06-25 06:56:11,214 - pyskl - INFO - Epoch [127][600/1281] lr: 1.488e-03, eta: 3:30:37, time: 0.295, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0329, loss: 0.0329 +2025-06-25 06:56:59,939 - pyskl - INFO - Epoch [127][700/1281] lr: 1.478e-03, eta: 3:29:56, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0298, loss: 0.0298 +2025-06-25 06:57:48,632 - pyskl - INFO - Epoch [127][800/1281] lr: 1.468e-03, eta: 3:29:15, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0256, loss: 0.0256 +2025-06-25 06:58:37,681 - pyskl - INFO - Epoch [127][900/1281] lr: 1.459e-03, eta: 3:28:35, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9962, top5_acc: 1.0000, loss_cls: 0.0366, loss: 0.0366 +2025-06-25 06:59:26,655 - pyskl - INFO - Epoch [127][1000/1281] lr: 1.449e-03, eta: 3:27:54, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0382, loss: 0.0382 +2025-06-25 07:00:15,328 - pyskl - INFO - Epoch [127][1100/1281] lr: 1.440e-03, eta: 3:27:13, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9944, top5_acc: 1.0000, loss_cls: 0.0421, loss: 0.0421 +2025-06-25 07:01:04,504 - pyskl - INFO - Epoch [127][1200/1281] lr: 1.430e-03, eta: 3:26:33, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0406, loss: 0.0406 +2025-06-25 07:01:44,633 - pyskl - INFO - Saving checkpoint at 127 epochs +2025-06-25 07:02:42,820 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:02:42,877 - pyskl - INFO - +top1_acc 0.9376 +top5_acc 0.9964 +2025-06-25 07:02:42,877 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:02:42,887 - pyskl - INFO - +mean_acc 0.9135 +2025-06-25 07:02:42,904 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_126.pth was removed +2025-06-25 07:02:43,088 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_127.pth. +2025-06-25 07:02:43,088 - pyskl - INFO - Best top1_acc is 0.9376 at 127 epoch. +2025-06-25 07:02:43,091 - pyskl - INFO - Epoch(val) [127][533] top1_acc: 0.9376, top5_acc: 0.9964, mean_class_accuracy: 0.9135 +2025-06-25 07:04:02,252 - pyskl - INFO - Epoch [128][100/1281] lr: 1.413e-03, eta: 3:25:17, time: 0.792, data_time: 0.186, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0298, loss: 0.0298 +2025-06-25 07:04:50,779 - pyskl - INFO - Epoch [128][200/1281] lr: 1.404e-03, eta: 3:24:36, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0270, loss: 0.0270 +2025-06-25 07:05:39,400 - pyskl - INFO - Epoch [128][300/1281] lr: 1.394e-03, eta: 3:23:56, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0269, loss: 0.0269 +2025-06-25 07:06:07,821 - pyskl - INFO - Epoch [128][400/1281] lr: 1.385e-03, eta: 3:23:11, time: 0.284, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0285, loss: 0.0285 +2025-06-25 07:06:58,526 - pyskl - INFO - Epoch [128][500/1281] lr: 1.376e-03, eta: 3:22:31, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0282, loss: 0.0282 +2025-06-25 07:07:27,881 - pyskl - INFO - Epoch [128][600/1281] lr: 1.366e-03, eta: 3:21:47, time: 0.294, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0271, loss: 0.0271 +2025-06-25 07:08:16,602 - pyskl - INFO - Epoch [128][700/1281] lr: 1.357e-03, eta: 3:21:06, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0320, loss: 0.0320 +2025-06-25 07:09:05,605 - pyskl - INFO - Epoch [128][800/1281] lr: 1.348e-03, eta: 3:20:25, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0247, loss: 0.0247 +2025-06-25 07:09:54,625 - pyskl - INFO - Epoch [128][900/1281] lr: 1.339e-03, eta: 3:19:45, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0252, loss: 0.0252 +2025-06-25 07:10:43,821 - pyskl - INFO - Epoch [128][1000/1281] lr: 1.329e-03, eta: 3:19:04, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0228, loss: 0.0228 +2025-06-25 07:11:32,815 - pyskl - INFO - Epoch [128][1100/1281] lr: 1.320e-03, eta: 3:18:23, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0240, loss: 0.0240 +2025-06-25 07:12:21,687 - pyskl - INFO - Epoch [128][1200/1281] lr: 1.311e-03, eta: 3:17:42, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0246, loss: 0.0246 +2025-06-25 07:13:02,144 - pyskl - INFO - Saving checkpoint at 128 epochs +2025-06-25 07:14:00,417 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:14:00,473 - pyskl - INFO - +top1_acc 0.9409 +top5_acc 0.9973 +2025-06-25 07:14:00,474 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:14:00,481 - pyskl - INFO - +mean_acc 0.9172 +2025-06-25 07:14:00,485 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_127.pth was removed +2025-06-25 07:14:00,841 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_128.pth. +2025-06-25 07:14:00,841 - pyskl - INFO - Best top1_acc is 0.9409 at 128 epoch. +2025-06-25 07:14:00,844 - pyskl - INFO - Epoch(val) [128][533] top1_acc: 0.9409, top5_acc: 0.9973, mean_class_accuracy: 0.9172 +2025-06-25 07:15:19,222 - pyskl - INFO - Epoch [129][100/1281] lr: 1.295e-03, eta: 3:16:27, time: 0.784, data_time: 0.192, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-25 07:16:07,785 - pyskl - INFO - Epoch [129][200/1281] lr: 1.286e-03, eta: 3:15:46, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0200, loss: 0.0200 +2025-06-25 07:16:56,537 - pyskl - INFO - Epoch [129][300/1281] lr: 1.277e-03, eta: 3:15:05, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0231, loss: 0.0231 +2025-06-25 07:17:26,062 - pyskl - INFO - Epoch [129][400/1281] lr: 1.268e-03, eta: 3:14:21, time: 0.295, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0306, loss: 0.0306 +2025-06-25 07:18:16,731 - pyskl - INFO - Epoch [129][500/1281] lr: 1.259e-03, eta: 3:13:41, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0265, loss: 0.0265 +2025-06-25 07:18:43,833 - pyskl - INFO - Epoch [129][600/1281] lr: 1.250e-03, eta: 3:12:56, time: 0.271, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0251, loss: 0.0251 +2025-06-25 07:19:32,932 - pyskl - INFO - Epoch [129][700/1281] lr: 1.241e-03, eta: 3:12:15, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0238, loss: 0.0238 +2025-06-25 07:20:21,799 - pyskl - INFO - Epoch [129][800/1281] lr: 1.232e-03, eta: 3:11:34, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 0.9994, loss_cls: 0.0311, loss: 0.0311 +2025-06-25 07:21:10,849 - pyskl - INFO - Epoch [129][900/1281] lr: 1.223e-03, eta: 3:10:54, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0276, loss: 0.0276 +2025-06-25 07:21:59,826 - pyskl - INFO - Epoch [129][1000/1281] lr: 1.214e-03, eta: 3:10:13, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0242, loss: 0.0242 +2025-06-25 07:22:48,766 - pyskl - INFO - Epoch [129][1100/1281] lr: 1.206e-03, eta: 3:09:32, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-25 07:23:37,418 - pyskl - INFO - Epoch [129][1200/1281] lr: 1.197e-03, eta: 3:08:51, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0226, loss: 0.0226 +2025-06-25 07:24:17,619 - pyskl - INFO - Saving checkpoint at 129 epochs +2025-06-25 07:25:15,522 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:25:15,577 - pyskl - INFO - +top1_acc 0.9396 +top5_acc 0.9962 +2025-06-25 07:25:15,577 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:25:15,584 - pyskl - INFO - +mean_acc 0.9159 +2025-06-25 07:25:15,585 - pyskl - INFO - Epoch(val) [129][533] top1_acc: 0.9396, top5_acc: 0.9962, mean_class_accuracy: 0.9159 +2025-06-25 07:26:34,225 - pyskl - INFO - Epoch [130][100/1281] lr: 1.181e-03, eta: 3:07:35, time: 0.786, data_time: 0.192, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0239, loss: 0.0239 +2025-06-25 07:27:22,953 - pyskl - INFO - Epoch [130][200/1281] lr: 1.172e-03, eta: 3:06:55, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-25 07:28:11,823 - pyskl - INFO - Epoch [130][300/1281] lr: 1.164e-03, eta: 3:06:14, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0258, loss: 0.0258 +2025-06-25 07:28:44,160 - pyskl - INFO - Epoch [130][400/1281] lr: 1.155e-03, eta: 3:05:30, time: 0.323, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0235, loss: 0.0235 +2025-06-25 07:29:34,956 - pyskl - INFO - Epoch [130][500/1281] lr: 1.147e-03, eta: 3:04:49, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0236, loss: 0.0236 +2025-06-25 07:30:01,166 - pyskl - INFO - Epoch [130][600/1281] lr: 1.138e-03, eta: 3:04:05, time: 0.262, data_time: 0.000, memory: 4083, top1_acc: 0.9975, top5_acc: 1.0000, loss_cls: 0.0303, loss: 0.0303 +2025-06-25 07:30:50,075 - pyskl - INFO - Epoch [130][700/1281] lr: 1.130e-03, eta: 3:03:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0309, loss: 0.0309 +2025-06-25 07:31:38,805 - pyskl - INFO - Epoch [130][800/1281] lr: 1.121e-03, eta: 3:02:43, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0280, loss: 0.0280 +2025-06-25 07:32:27,914 - pyskl - INFO - Epoch [130][900/1281] lr: 1.113e-03, eta: 3:02:02, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0271, loss: 0.0271 +2025-06-25 07:33:16,926 - pyskl - INFO - Epoch [130][1000/1281] lr: 1.104e-03, eta: 3:01:21, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0242, loss: 0.0242 +2025-06-25 07:34:05,747 - pyskl - INFO - Epoch [130][1100/1281] lr: 1.096e-03, eta: 3:00:40, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0368, loss: 0.0368 +2025-06-25 07:34:54,393 - pyskl - INFO - Epoch [130][1200/1281] lr: 1.088e-03, eta: 2:59:59, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0217, loss: 0.0217 +2025-06-25 07:35:34,437 - pyskl - INFO - Saving checkpoint at 130 epochs +2025-06-25 07:36:32,771 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:36:32,826 - pyskl - INFO - +top1_acc 0.9405 +top5_acc 0.9966 +2025-06-25 07:36:32,827 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:36:32,833 - pyskl - INFO - +mean_acc 0.9164 +2025-06-25 07:36:32,835 - pyskl - INFO - Epoch(val) [130][533] top1_acc: 0.9405, top5_acc: 0.9966, mean_class_accuracy: 0.9164 +2025-06-25 07:37:52,236 - pyskl - INFO - Epoch [131][100/1281] lr: 1.072e-03, eta: 2:58:44, time: 0.794, data_time: 0.192, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0232, loss: 0.0232 +2025-06-25 07:38:41,127 - pyskl - INFO - Epoch [131][200/1281] lr: 1.064e-03, eta: 2:58:03, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0259, loss: 0.0259 +2025-06-25 07:39:29,799 - pyskl - INFO - Epoch [131][300/1281] lr: 1.056e-03, eta: 2:57:22, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-25 07:40:02,191 - pyskl - INFO - Epoch [131][400/1281] lr: 1.048e-03, eta: 2:56:38, time: 0.324, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-25 07:40:52,860 - pyskl - INFO - Epoch [131][500/1281] lr: 1.040e-03, eta: 2:55:58, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0228, loss: 0.0228 +2025-06-25 07:41:18,133 - pyskl - INFO - Epoch [131][600/1281] lr: 1.031e-03, eta: 2:55:13, time: 0.253, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0238, loss: 0.0238 +2025-06-25 07:42:06,621 - pyskl - INFO - Epoch [131][700/1281] lr: 1.023e-03, eta: 2:54:32, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 07:42:55,451 - pyskl - INFO - Epoch [131][800/1281] lr: 1.015e-03, eta: 2:53:51, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0293, loss: 0.0293 +2025-06-25 07:43:44,671 - pyskl - INFO - Epoch [131][900/1281] lr: 1.007e-03, eta: 2:53:10, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0221, loss: 0.0221 +2025-06-25 07:44:33,332 - pyskl - INFO - Epoch [131][1000/1281] lr: 9.992e-04, eta: 2:52:29, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0240, loss: 0.0240 +2025-06-25 07:45:21,950 - pyskl - INFO - Epoch [131][1100/1281] lr: 9.912e-04, eta: 2:51:48, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0235, loss: 0.0235 +2025-06-25 07:46:10,856 - pyskl - INFO - Epoch [131][1200/1281] lr: 9.832e-04, eta: 2:51:07, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0230, loss: 0.0230 +2025-06-25 07:46:51,353 - pyskl - INFO - Saving checkpoint at 131 epochs +2025-06-25 07:47:49,285 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:47:49,339 - pyskl - INFO - +top1_acc 0.9419 +top5_acc 0.9962 +2025-06-25 07:47:49,339 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:47:49,349 - pyskl - INFO - +mean_acc 0.9210 +2025-06-25 07:47:49,353 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_128.pth was removed +2025-06-25 07:47:49,521 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_131.pth. +2025-06-25 07:47:49,521 - pyskl - INFO - Best top1_acc is 0.9419 at 131 epoch. +2025-06-25 07:47:49,524 - pyskl - INFO - Epoch(val) [131][533] top1_acc: 0.9419, top5_acc: 0.9962, mean_class_accuracy: 0.9210 +2025-06-25 07:49:07,510 - pyskl - INFO - Epoch [132][100/1281] lr: 9.689e-04, eta: 2:49:51, time: 0.780, data_time: 0.189, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-25 07:49:56,201 - pyskl - INFO - Epoch [132][200/1281] lr: 9.610e-04, eta: 2:49:10, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0205, loss: 0.0205 +2025-06-25 07:50:45,119 - pyskl - INFO - Epoch [132][300/1281] lr: 9.532e-04, eta: 2:48:29, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0224, loss: 0.0224 +2025-06-25 07:51:19,760 - pyskl - INFO - Epoch [132][400/1281] lr: 9.454e-04, eta: 2:47:46, time: 0.346, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-25 07:52:10,376 - pyskl - INFO - Epoch [132][500/1281] lr: 9.376e-04, eta: 2:47:05, time: 0.506, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 07:52:35,044 - pyskl - INFO - Epoch [132][600/1281] lr: 9.298e-04, eta: 2:46:20, time: 0.247, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0218, loss: 0.0218 +2025-06-25 07:53:22,597 - pyskl - INFO - Epoch [132][700/1281] lr: 9.221e-04, eta: 2:45:39, time: 0.476, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0281, loss: 0.0281 +2025-06-25 07:54:11,893 - pyskl - INFO - Epoch [132][800/1281] lr: 9.144e-04, eta: 2:44:58, time: 0.493, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0226, loss: 0.0226 +2025-06-25 07:54:59,779 - pyskl - INFO - Epoch [132][900/1281] lr: 9.068e-04, eta: 2:44:17, time: 0.479, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-25 07:55:48,974 - pyskl - INFO - Epoch [132][1000/1281] lr: 8.991e-04, eta: 2:43:36, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9969, top5_acc: 1.0000, loss_cls: 0.0289, loss: 0.0289 +2025-06-25 07:56:38,017 - pyskl - INFO - Epoch [132][1100/1281] lr: 8.915e-04, eta: 2:42:55, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0291, loss: 0.0291 +2025-06-25 07:57:26,884 - pyskl - INFO - Epoch [132][1200/1281] lr: 8.840e-04, eta: 2:42:14, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0303, loss: 0.0303 +2025-06-25 07:58:07,216 - pyskl - INFO - Saving checkpoint at 132 epochs +2025-06-25 07:59:05,125 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 07:59:05,180 - pyskl - INFO - +top1_acc 0.9383 +top5_acc 0.9962 +2025-06-25 07:59:05,180 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 07:59:05,186 - pyskl - INFO - +mean_acc 0.9164 +2025-06-25 07:59:05,188 - pyskl - INFO - Epoch(val) [132][533] top1_acc: 0.9383, top5_acc: 0.9962, mean_class_accuracy: 0.9164 +2025-06-25 08:00:24,311 - pyskl - INFO - Epoch [133][100/1281] lr: 8.704e-04, eta: 2:40:58, time: 0.791, data_time: 0.187, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0240, loss: 0.0240 +2025-06-25 08:01:12,846 - pyskl - INFO - Epoch [133][200/1281] lr: 8.629e-04, eta: 2:40:17, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-25 08:02:01,984 - pyskl - INFO - Epoch [133][300/1281] lr: 8.554e-04, eta: 2:39:36, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0261, loss: 0.0261 +2025-06-25 08:02:38,162 - pyskl - INFO - Epoch [133][400/1281] lr: 8.480e-04, eta: 2:38:53, time: 0.362, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0229, loss: 0.0229 +2025-06-25 08:03:28,845 - pyskl - INFO - Epoch [133][500/1281] lr: 8.406e-04, eta: 2:38:12, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0217, loss: 0.0217 +2025-06-25 08:03:52,596 - pyskl - INFO - Epoch [133][600/1281] lr: 8.333e-04, eta: 2:37:27, time: 0.237, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0256, loss: 0.0256 +2025-06-25 08:04:37,401 - pyskl - INFO - Epoch [133][700/1281] lr: 8.260e-04, eta: 2:36:45, time: 0.448, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0235, loss: 0.0235 +2025-06-25 08:05:26,127 - pyskl - INFO - Epoch [133][800/1281] lr: 8.187e-04, eta: 2:36:04, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0277, loss: 0.0277 +2025-06-25 08:06:15,216 - pyskl - INFO - Epoch [133][900/1281] lr: 8.114e-04, eta: 2:35:23, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0222, loss: 0.0222 +2025-06-25 08:07:04,041 - pyskl - INFO - Epoch [133][1000/1281] lr: 8.042e-04, eta: 2:34:42, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0246, loss: 0.0246 +2025-06-25 08:07:52,818 - pyskl - INFO - Epoch [133][1100/1281] lr: 7.970e-04, eta: 2:34:01, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0292, loss: 0.0292 +2025-06-25 08:08:41,665 - pyskl - INFO - Epoch [133][1200/1281] lr: 7.898e-04, eta: 2:33:19, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0278, loss: 0.0278 +2025-06-25 08:09:21,911 - pyskl - INFO - Saving checkpoint at 133 epochs +2025-06-25 08:10:19,884 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:10:19,939 - pyskl - INFO - +top1_acc 0.9410 +top5_acc 0.9964 +2025-06-25 08:10:19,939 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:10:19,946 - pyskl - INFO - +mean_acc 0.9172 +2025-06-25 08:10:19,948 - pyskl - INFO - Epoch(val) [133][533] top1_acc: 0.9410, top5_acc: 0.9964, mean_class_accuracy: 0.9172 +2025-06-25 08:11:38,131 - pyskl - INFO - Epoch [134][100/1281] lr: 7.769e-04, eta: 2:32:04, time: 0.782, data_time: 0.189, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0276, loss: 0.0276 +2025-06-25 08:12:26,793 - pyskl - INFO - Epoch [134][200/1281] lr: 7.699e-04, eta: 2:31:22, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-25 08:13:15,756 - pyskl - INFO - Epoch [134][300/1281] lr: 7.628e-04, eta: 2:30:41, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0268, loss: 0.0268 +2025-06-25 08:13:54,896 - pyskl - INFO - Epoch [134][400/1281] lr: 7.558e-04, eta: 2:29:59, time: 0.391, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-25 08:14:45,192 - pyskl - INFO - Epoch [134][500/1281] lr: 7.488e-04, eta: 2:29:18, time: 0.503, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0220, loss: 0.0220 +2025-06-25 08:15:08,228 - pyskl - INFO - Epoch [134][600/1281] lr: 7.419e-04, eta: 2:28:33, time: 0.230, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0274, loss: 0.0274 +2025-06-25 08:15:51,324 - pyskl - INFO - Epoch [134][700/1281] lr: 7.349e-04, eta: 2:27:51, time: 0.431, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0254, loss: 0.0254 +2025-06-25 08:16:40,088 - pyskl - INFO - Epoch [134][800/1281] lr: 7.281e-04, eta: 2:27:10, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0239, loss: 0.0239 +2025-06-25 08:17:28,910 - pyskl - INFO - Epoch [134][900/1281] lr: 7.212e-04, eta: 2:26:29, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0222, loss: 0.0222 +2025-06-25 08:18:17,657 - pyskl - INFO - Epoch [134][1000/1281] lr: 7.144e-04, eta: 2:25:47, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0237, loss: 0.0237 +2025-06-25 08:19:06,465 - pyskl - INFO - Epoch [134][1100/1281] lr: 7.076e-04, eta: 2:25:06, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0221, loss: 0.0221 +2025-06-25 08:19:55,400 - pyskl - INFO - Epoch [134][1200/1281] lr: 7.008e-04, eta: 2:24:25, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0218, loss: 0.0218 +2025-06-25 08:20:35,402 - pyskl - INFO - Saving checkpoint at 134 epochs +2025-06-25 08:21:33,047 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:21:33,102 - pyskl - INFO - +top1_acc 0.9409 +top5_acc 0.9965 +2025-06-25 08:21:33,102 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:21:33,109 - pyskl - INFO - +mean_acc 0.9176 +2025-06-25 08:21:33,111 - pyskl - INFO - Epoch(val) [134][533] top1_acc: 0.9409, top5_acc: 0.9965, mean_class_accuracy: 0.9176 +2025-06-25 08:22:53,286 - pyskl - INFO - Epoch [135][100/1281] lr: 6.887e-04, eta: 2:23:09, time: 0.802, data_time: 0.187, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-25 08:23:42,254 - pyskl - INFO - Epoch [135][200/1281] lr: 6.820e-04, eta: 2:22:28, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0209, loss: 0.0209 +2025-06-25 08:24:31,036 - pyskl - INFO - Epoch [135][300/1281] lr: 6.753e-04, eta: 2:21:46, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0217, loss: 0.0217 +2025-06-25 08:25:11,563 - pyskl - INFO - Epoch [135][400/1281] lr: 6.687e-04, eta: 2:21:04, time: 0.405, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0217, loss: 0.0217 +2025-06-25 08:26:01,590 - pyskl - INFO - Epoch [135][500/1281] lr: 6.622e-04, eta: 2:20:23, time: 0.500, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-25 08:26:25,128 - pyskl - INFO - Epoch [135][600/1281] lr: 6.556e-04, eta: 2:19:39, time: 0.235, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0268, loss: 0.0268 +2025-06-25 08:27:08,300 - pyskl - INFO - Epoch [135][700/1281] lr: 6.491e-04, eta: 2:18:57, time: 0.432, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0240, loss: 0.0240 +2025-06-25 08:27:57,230 - pyskl - INFO - Epoch [135][800/1281] lr: 6.426e-04, eta: 2:18:15, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-25 08:28:46,316 - pyskl - INFO - Epoch [135][900/1281] lr: 6.362e-04, eta: 2:17:34, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0214, loss: 0.0214 +2025-06-25 08:29:34,982 - pyskl - INFO - Epoch [135][1000/1281] lr: 6.297e-04, eta: 2:16:52, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0233, loss: 0.0233 +2025-06-25 08:30:23,924 - pyskl - INFO - Epoch [135][1100/1281] lr: 6.233e-04, eta: 2:16:11, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0236, loss: 0.0236 +2025-06-25 08:31:13,068 - pyskl - INFO - Epoch [135][1200/1281] lr: 6.170e-04, eta: 2:15:30, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0229, loss: 0.0229 +2025-06-25 08:31:53,188 - pyskl - INFO - Saving checkpoint at 135 epochs +2025-06-25 08:32:51,092 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:32:51,159 - pyskl - INFO - +top1_acc 0.9425 +top5_acc 0.9966 +2025-06-25 08:32:51,159 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:32:51,166 - pyskl - INFO - +mean_acc 0.9184 +2025-06-25 08:32:51,172 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_131.pth was removed +2025-06-25 08:32:51,345 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_135.pth. +2025-06-25 08:32:51,345 - pyskl - INFO - Best top1_acc is 0.9425 at 135 epoch. +2025-06-25 08:32:51,348 - pyskl - INFO - Epoch(val) [135][533] top1_acc: 0.9425, top5_acc: 0.9966, mean_class_accuracy: 0.9184 +2025-06-25 08:34:10,860 - pyskl - INFO - Epoch [136][100/1281] lr: 6.056e-04, eta: 2:14:14, time: 0.795, data_time: 0.186, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0244, loss: 0.0244 +2025-06-25 08:34:59,395 - pyskl - INFO - Epoch [136][200/1281] lr: 5.993e-04, eta: 2:13:32, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-25 08:35:47,862 - pyskl - INFO - Epoch [136][300/1281] lr: 5.931e-04, eta: 2:12:51, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 08:36:28,311 - pyskl - INFO - Epoch [136][400/1281] lr: 5.868e-04, eta: 2:12:09, time: 0.404, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0232, loss: 0.0232 +2025-06-25 08:37:17,090 - pyskl - INFO - Epoch [136][500/1281] lr: 5.807e-04, eta: 2:11:27, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0235, loss: 0.0235 +2025-06-25 08:37:41,485 - pyskl - INFO - Epoch [136][600/1281] lr: 5.745e-04, eta: 2:10:43, time: 0.244, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0311, loss: 0.0311 +2025-06-25 08:38:24,116 - pyskl - INFO - Epoch [136][700/1281] lr: 5.684e-04, eta: 2:10:01, time: 0.426, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0234, loss: 0.0234 +2025-06-25 08:39:13,309 - pyskl - INFO - Epoch [136][800/1281] lr: 5.623e-04, eta: 2:09:20, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0218, loss: 0.0218 +2025-06-25 08:40:01,817 - pyskl - INFO - Epoch [136][900/1281] lr: 5.563e-04, eta: 2:08:38, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 08:40:50,712 - pyskl - INFO - Epoch [136][1000/1281] lr: 5.503e-04, eta: 2:07:57, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0205, loss: 0.0205 +2025-06-25 08:41:39,611 - pyskl - INFO - Epoch [136][1100/1281] lr: 5.443e-04, eta: 2:07:15, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0214, loss: 0.0214 +2025-06-25 08:42:28,293 - pyskl - INFO - Epoch [136][1200/1281] lr: 5.384e-04, eta: 2:06:34, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 08:43:08,145 - pyskl - INFO - Saving checkpoint at 136 epochs +2025-06-25 08:44:05,911 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:44:05,966 - pyskl - INFO - +top1_acc 0.9428 +top5_acc 0.9966 +2025-06-25 08:44:05,966 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:44:05,972 - pyskl - INFO - +mean_acc 0.9197 +2025-06-25 08:44:05,976 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_135.pth was removed +2025-06-25 08:44:06,147 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_136.pth. +2025-06-25 08:44:06,148 - pyskl - INFO - Best top1_acc is 0.9428 at 136 epoch. +2025-06-25 08:44:06,150 - pyskl - INFO - Epoch(val) [136][533] top1_acc: 0.9428, top5_acc: 0.9966, mean_class_accuracy: 0.9197 +2025-06-25 08:45:24,511 - pyskl - INFO - Epoch [137][100/1281] lr: 5.277e-04, eta: 2:05:18, time: 0.784, data_time: 0.185, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 08:46:13,517 - pyskl - INFO - Epoch [137][200/1281] lr: 5.218e-04, eta: 2:04:36, 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 08:47:02,404 - pyskl - INFO - Epoch [137][300/1281] lr: 5.160e-04, eta: 2:03:55, 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 08:47:45,436 - pyskl - INFO - Epoch [137][400/1281] lr: 5.102e-04, eta: 2:03:13, time: 0.430, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 08:48:32,211 - pyskl - INFO - Epoch [137][500/1281] lr: 5.044e-04, eta: 2:02:31, time: 0.468, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0224, loss: 0.0224 +2025-06-25 08:48:58,320 - pyskl - INFO - Epoch [137][600/1281] lr: 4.987e-04, eta: 2:01:47, time: 0.261, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0257, loss: 0.0257 +2025-06-25 08:49:39,712 - pyskl - INFO - Epoch [137][700/1281] lr: 4.930e-04, eta: 2:01:05, time: 0.414, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 08:50:28,872 - pyskl - INFO - Epoch [137][800/1281] lr: 4.873e-04, eta: 2:00:24, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 08:51:17,908 - pyskl - INFO - Epoch [137][900/1281] lr: 4.817e-04, eta: 1:59:42, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 08:52:06,899 - pyskl - INFO - Epoch [137][1000/1281] lr: 4.761e-04, eta: 1:59:01, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0225, loss: 0.0225 +2025-06-25 08:52:55,741 - pyskl - INFO - Epoch [137][1100/1281] lr: 4.705e-04, eta: 1:58:19, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 08:53:44,560 - pyskl - INFO - Epoch [137][1200/1281] lr: 4.650e-04, eta: 1:57:38, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0229, loss: 0.0229 +2025-06-25 08:54:24,843 - pyskl - INFO - Saving checkpoint at 137 epochs +2025-06-25 08:55:22,318 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 08:55:22,373 - pyskl - INFO - +top1_acc 0.9420 +top5_acc 0.9971 +2025-06-25 08:55:22,373 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 08:55:22,380 - pyskl - INFO - +mean_acc 0.9197 +2025-06-25 08:55:22,382 - pyskl - INFO - Epoch(val) [137][533] top1_acc: 0.9420, top5_acc: 0.9971, mean_class_accuracy: 0.9197 +2025-06-25 08:56:40,086 - pyskl - INFO - Epoch [138][100/1281] lr: 4.550e-04, eta: 1:56:21, time: 0.777, data_time: 0.184, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 08:57:28,861 - pyskl - INFO - Epoch [138][200/1281] lr: 4.496e-04, eta: 1:55:40, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 08:58:17,737 - pyskl - INFO - Epoch [138][300/1281] lr: 4.442e-04, eta: 1:54:58, 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 08:59:02,980 - pyskl - INFO - Epoch [138][400/1281] lr: 4.388e-04, eta: 1:54:16, time: 0.452, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-25 08:59:43,647 - pyskl - INFO - Epoch [138][500/1281] lr: 4.334e-04, eta: 1:53:34, time: 0.407, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0265, loss: 0.0265 +2025-06-25 09:00:15,949 - pyskl - INFO - Epoch [138][600/1281] lr: 4.281e-04, eta: 1:52:51, time: 0.323, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 09:00:53,801 - pyskl - INFO - Epoch [138][700/1281] lr: 4.228e-04, eta: 1:52:08, time: 0.379, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-25 09:01:42,566 - pyskl - INFO - Epoch [138][800/1281] lr: 4.176e-04, eta: 1:51:27, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0222, loss: 0.0222 +2025-06-25 09:02:31,368 - pyskl - INFO - Epoch [138][900/1281] lr: 4.124e-04, eta: 1:50:45, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 09:03:20,180 - pyskl - INFO - Epoch [138][1000/1281] lr: 4.072e-04, eta: 1:50:04, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0237, loss: 0.0237 +2025-06-25 09:04:08,907 - pyskl - INFO - Epoch [138][1100/1281] lr: 4.020e-04, eta: 1:49:22, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0234, loss: 0.0234 +2025-06-25 09:04:57,732 - pyskl - INFO - Epoch [138][1200/1281] lr: 3.969e-04, eta: 1:48:40, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0216, loss: 0.0216 +2025-06-25 09:05:37,831 - pyskl - INFO - Saving checkpoint at 138 epochs +2025-06-25 09:06:35,737 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:06:35,805 - pyskl - INFO - +top1_acc 0.9406 +top5_acc 0.9973 +2025-06-25 09:06:35,805 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:06:35,814 - pyskl - INFO - +mean_acc 0.9178 +2025-06-25 09:06:35,816 - pyskl - INFO - Epoch(val) [138][533] top1_acc: 0.9406, top5_acc: 0.9973, mean_class_accuracy: 0.9178 +2025-06-25 09:07:55,149 - pyskl - INFO - Epoch [139][100/1281] lr: 3.877e-04, eta: 1:47:24, time: 0.793, data_time: 0.188, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0234, loss: 0.0234 +2025-06-25 09:08:44,239 - pyskl - INFO - Epoch [139][200/1281] lr: 3.827e-04, eta: 1:46:43, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0255, loss: 0.0255 +2025-06-25 09:09:33,030 - pyskl - INFO - Epoch [139][300/1281] lr: 3.777e-04, eta: 1:46:01, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0236, loss: 0.0236 +2025-06-25 09:10:20,755 - pyskl - INFO - Epoch [139][400/1281] lr: 3.727e-04, eta: 1:45:19, time: 0.477, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0214, loss: 0.0214 +2025-06-25 09:10:56,752 - pyskl - INFO - Epoch [139][500/1281] lr: 3.678e-04, eta: 1:44:36, time: 0.360, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 09:11:33,674 - pyskl - INFO - Epoch [139][600/1281] lr: 3.628e-04, eta: 1:43:54, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 09:12:11,240 - pyskl - INFO - Epoch [139][700/1281] lr: 3.580e-04, eta: 1:43:11, time: 0.376, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 09:13:00,069 - pyskl - INFO - Epoch [139][800/1281] lr: 3.531e-04, eta: 1:42:30, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 09:13:48,945 - pyskl - INFO - Epoch [139][900/1281] lr: 3.483e-04, eta: 1:41:48, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 09:14:37,930 - pyskl - INFO - Epoch [139][1000/1281] lr: 3.436e-04, eta: 1:41:06, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 09:15:26,732 - pyskl - INFO - Epoch [139][1100/1281] lr: 3.388e-04, eta: 1:40:25, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0209, loss: 0.0209 +2025-06-25 09:16:15,898 - pyskl - INFO - Epoch [139][1200/1281] lr: 3.341e-04, eta: 1:39:43, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 09:16:56,216 - pyskl - INFO - Saving checkpoint at 139 epochs +2025-06-25 09:17:54,082 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:17:54,137 - pyskl - INFO - +top1_acc 0.9440 +top5_acc 0.9971 +2025-06-25 09:17:54,138 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:17:54,145 - pyskl - INFO - +mean_acc 0.9227 +2025-06-25 09:17:54,149 - pyskl - INFO - The previous best checkpoint /home/lhd/pyskl/work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_136.pth was removed +2025-06-25 09:17:54,312 - pyskl - INFO - Now best checkpoint is saved as best_top1_acc_epoch_139.pth. +2025-06-25 09:17:54,313 - pyskl - INFO - Best top1_acc is 0.9440 at 139 epoch. +2025-06-25 09:17:54,315 - pyskl - INFO - Epoch(val) [139][533] top1_acc: 0.9440, top5_acc: 0.9971, mean_class_accuracy: 0.9227 +2025-06-25 09:19:14,649 - pyskl - INFO - Epoch [140][100/1281] lr: 3.257e-04, eta: 1:38:27, time: 0.803, data_time: 0.192, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 09:20:03,844 - pyskl - INFO - Epoch [140][200/1281] lr: 3.210e-04, eta: 1:37:45, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0234, loss: 0.0234 +2025-06-25 09:20:52,571 - pyskl - INFO - Epoch [140][300/1281] lr: 3.165e-04, eta: 1:37:03, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-25 09:21:39,572 - pyskl - INFO - Epoch [140][400/1281] lr: 3.119e-04, eta: 1:36:21, time: 0.470, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 09:22:16,701 - pyskl - INFO - Epoch [140][500/1281] lr: 3.074e-04, eta: 1:35:39, time: 0.371, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 09:22:52,430 - pyskl - INFO - Epoch [140][600/1281] lr: 3.029e-04, eta: 1:34:56, time: 0.357, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0207, loss: 0.0207 +2025-06-25 09:23:30,489 - pyskl - INFO - Epoch [140][700/1281] lr: 2.984e-04, eta: 1:34:14, time: 0.381, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 09:24:19,722 - pyskl - INFO - Epoch [140][800/1281] lr: 2.940e-04, eta: 1:33:32, time: 0.492, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-25 09:25:08,144 - pyskl - INFO - Epoch [140][900/1281] lr: 2.896e-04, eta: 1:32:50, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 09:25:56,826 - pyskl - INFO - Epoch [140][1000/1281] lr: 2.853e-04, eta: 1:32:08, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 09:26:45,669 - pyskl - INFO - Epoch [140][1100/1281] lr: 2.809e-04, eta: 1:31:27, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 09:27:34,782 - pyskl - INFO - Epoch [140][1200/1281] lr: 2.767e-04, eta: 1:30:45, 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 09:28:15,559 - pyskl - INFO - Saving checkpoint at 140 epochs +2025-06-25 09:29:13,254 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:29:13,310 - pyskl - INFO - +top1_acc 0.9426 +top5_acc 0.9968 +2025-06-25 09:29:13,310 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:29:13,318 - pyskl - INFO - +mean_acc 0.9215 +2025-06-25 09:29:13,320 - pyskl - INFO - Epoch(val) [140][533] top1_acc: 0.9426, top5_acc: 0.9968, mean_class_accuracy: 0.9215 +2025-06-25 09:30:31,529 - pyskl - INFO - Epoch [141][100/1281] lr: 2.690e-04, eta: 1:29:29, time: 0.782, data_time: 0.189, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 09:31:20,476 - pyskl - INFO - Epoch [141][200/1281] lr: 2.648e-04, eta: 1:28:47, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0204, loss: 0.0204 +2025-06-25 09:32:09,261 - pyskl - INFO - Epoch [141][300/1281] lr: 2.606e-04, eta: 1:28:05, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-25 09:32:57,429 - pyskl - INFO - Epoch [141][400/1281] lr: 2.565e-04, eta: 1:27:23, time: 0.482, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0286, loss: 0.0286 +2025-06-25 09:33:31,481 - pyskl - INFO - Epoch [141][500/1281] lr: 2.524e-04, eta: 1:26:40, time: 0.340, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 09:34:10,395 - pyskl - INFO - Epoch [141][600/1281] lr: 2.483e-04, eta: 1:25:58, time: 0.389, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0205, loss: 0.0205 +2025-06-25 09:34:47,277 - pyskl - INFO - Epoch [141][700/1281] lr: 2.443e-04, eta: 1:25:15, time: 0.369, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 09:35:35,999 - pyskl - INFO - Epoch [141][800/1281] lr: 2.402e-04, eta: 1:24:33, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0209, loss: 0.0209 +2025-06-25 09:36:24,848 - pyskl - INFO - Epoch [141][900/1281] lr: 2.363e-04, eta: 1:23:52, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0214, loss: 0.0214 +2025-06-25 09:37:13,432 - pyskl - INFO - Epoch [141][1000/1281] lr: 2.323e-04, eta: 1:23:10, time: 0.486, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0185, loss: 0.0185 +2025-06-25 09:38:02,008 - pyskl - INFO - Epoch [141][1100/1281] lr: 2.284e-04, eta: 1:22:28, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 09:38:51,057 - pyskl - INFO - Epoch [141][1200/1281] lr: 2.246e-04, eta: 1:21:46, 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 09:39:31,320 - pyskl - INFO - Saving checkpoint at 141 epochs +2025-06-25 09:40:29,239 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:40:29,296 - pyskl - INFO - +top1_acc 0.9431 +top5_acc 0.9971 +2025-06-25 09:40:29,296 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:40:29,302 - pyskl - INFO - +mean_acc 0.9228 +2025-06-25 09:40:29,304 - pyskl - INFO - Epoch(val) [141][533] top1_acc: 0.9431, top5_acc: 0.9971, mean_class_accuracy: 0.9228 +2025-06-25 09:41:47,922 - pyskl - INFO - Epoch [142][100/1281] lr: 2.176e-04, eta: 1:20:30, time: 0.786, data_time: 0.191, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0218, loss: 0.0218 +2025-06-25 09:42:36,466 - pyskl - INFO - Epoch [142][200/1281] lr: 2.139e-04, eta: 1:19:48, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 09:43:25,545 - pyskl - INFO - Epoch [142][300/1281] lr: 2.101e-04, eta: 1:19:06, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 09:44:14,133 - pyskl - INFO - Epoch [142][400/1281] lr: 2.064e-04, eta: 1:18:24, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 09:44:45,778 - pyskl - INFO - Epoch [142][500/1281] lr: 2.027e-04, eta: 1:17:41, time: 0.316, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0209, loss: 0.0209 +2025-06-25 09:45:26,751 - pyskl - INFO - Epoch [142][600/1281] lr: 1.991e-04, eta: 1:16:59, time: 0.410, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0211, loss: 0.0211 +2025-06-25 09:46:02,163 - pyskl - INFO - Epoch [142][700/1281] lr: 1.954e-04, eta: 1:16:16, time: 0.354, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 09:46:50,682 - pyskl - INFO - Epoch [142][800/1281] lr: 1.919e-04, eta: 1:15:34, time: 0.485, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0215, loss: 0.0215 +2025-06-25 09:47:39,375 - pyskl - INFO - Epoch [142][900/1281] lr: 1.883e-04, eta: 1:14:52, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-25 09:48:28,341 - pyskl - INFO - Epoch [142][1000/1281] lr: 1.848e-04, eta: 1:14:11, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0204, loss: 0.0204 +2025-06-25 09:49:17,205 - pyskl - INFO - Epoch [142][1100/1281] lr: 1.813e-04, eta: 1:13:29, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 09:50:06,159 - pyskl - INFO - Epoch [142][1200/1281] lr: 1.779e-04, eta: 1:12:47, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 09:50:46,469 - pyskl - INFO - Saving checkpoint at 142 epochs +2025-06-25 09:51:43,958 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 09:51:44,013 - pyskl - INFO - +top1_acc 0.9407 +top5_acc 0.9971 +2025-06-25 09:51:44,013 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 09:51:44,019 - pyskl - INFO - +mean_acc 0.9190 +2025-06-25 09:51:44,021 - pyskl - INFO - Epoch(val) [142][533] top1_acc: 0.9407, top5_acc: 0.9971, mean_class_accuracy: 0.9190 +2025-06-25 09:53:01,565 - pyskl - INFO - Epoch [143][100/1281] lr: 1.717e-04, eta: 1:11:30, time: 0.775, data_time: 0.183, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 09:53:50,487 - pyskl - INFO - Epoch [143][200/1281] lr: 1.683e-04, eta: 1:10:48, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 09:54:39,730 - pyskl - INFO - Epoch [143][300/1281] lr: 1.650e-04, eta: 1:10:06, 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 09:55:28,619 - pyskl - INFO - Epoch [143][400/1281] lr: 1.617e-04, eta: 1:09:25, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 09:55:58,104 - pyskl - INFO - Epoch [143][500/1281] lr: 1.585e-04, eta: 1:08:42, time: 0.295, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0220, loss: 0.0220 +2025-06-25 09:56:45,009 - pyskl - INFO - Epoch [143][600/1281] lr: 1.552e-04, eta: 1:08:00, time: 0.469, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-25 09:57:17,609 - pyskl - INFO - Epoch [143][700/1281] lr: 1.520e-04, eta: 1:07:17, time: 0.326, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-25 09:58:07,034 - pyskl - INFO - Epoch [143][800/1281] lr: 1.489e-04, eta: 1:06:35, time: 0.494, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0207, loss: 0.0207 +2025-06-25 09:58:55,974 - pyskl - INFO - Epoch [143][900/1281] lr: 1.457e-04, eta: 1:05:53, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0209, loss: 0.0209 +2025-06-25 09:59:44,858 - pyskl - INFO - Epoch [143][1000/1281] lr: 1.426e-04, eta: 1:05:11, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 10:00:33,568 - pyskl - INFO - Epoch [143][1100/1281] lr: 1.396e-04, eta: 1:04:29, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 10:01:22,531 - pyskl - INFO - Epoch [143][1200/1281] lr: 1.366e-04, eta: 1:03:47, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0236, loss: 0.0236 +2025-06-25 10:02:02,913 - pyskl - INFO - Saving checkpoint at 143 epochs +2025-06-25 10:03:00,915 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:03:00,972 - pyskl - INFO - +top1_acc 0.9428 +top5_acc 0.9969 +2025-06-25 10:03:00,972 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:03:00,978 - pyskl - INFO - +mean_acc 0.9221 +2025-06-25 10:03:00,980 - pyskl - INFO - Epoch(val) [143][533] top1_acc: 0.9428, top5_acc: 0.9969, mean_class_accuracy: 0.9221 +2025-06-25 10:04:19,789 - pyskl - INFO - Epoch [144][100/1281] lr: 1.312e-04, eta: 1:02:30, time: 0.788, data_time: 0.187, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0251, loss: 0.0251 +2025-06-25 10:05:09,040 - pyskl - INFO - Epoch [144][200/1281] lr: 1.282e-04, eta: 1:01:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 10:05:57,985 - pyskl - INFO - Epoch [144][300/1281] lr: 1.253e-04, eta: 1:01:07, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 10:06:46,893 - pyskl - INFO - Epoch [144][400/1281] lr: 1.224e-04, eta: 1:00:25, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0197, loss: 0.0197 +2025-06-25 10:07:16,186 - pyskl - INFO - Epoch [144][500/1281] lr: 1.196e-04, eta: 0:59:42, time: 0.293, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0202, loss: 0.0202 +2025-06-25 10:08:03,587 - pyskl - INFO - Epoch [144][600/1281] lr: 1.168e-04, eta: 0:59:00, time: 0.474, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 10:08:36,151 - pyskl - INFO - Epoch [144][700/1281] lr: 1.140e-04, eta: 0:58:17, time: 0.326, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 10:09:25,114 - pyskl - INFO - Epoch [144][800/1281] lr: 1.113e-04, eta: 0:57:35, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 10:10:13,854 - pyskl - INFO - Epoch [144][900/1281] lr: 1.086e-04, eta: 0:56:53, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 10:11:02,899 - pyskl - INFO - Epoch [144][1000/1281] lr: 1.059e-04, eta: 0:56:11, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0215, loss: 0.0215 +2025-06-25 10:11:52,113 - pyskl - INFO - Epoch [144][1100/1281] lr: 1.033e-04, eta: 0:55:29, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0231, loss: 0.0231 +2025-06-25 10:12:41,131 - pyskl - INFO - Epoch [144][1200/1281] lr: 1.007e-04, eta: 0:54:47, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 10:13:21,313 - pyskl - INFO - Saving checkpoint at 144 epochs +2025-06-25 10:14:19,355 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:14:19,410 - pyskl - INFO - +top1_acc 0.9421 +top5_acc 0.9969 +2025-06-25 10:14:19,410 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:14:19,417 - pyskl - INFO - +mean_acc 0.9199 +2025-06-25 10:14:19,418 - pyskl - INFO - Epoch(val) [144][533] top1_acc: 0.9421, top5_acc: 0.9969, mean_class_accuracy: 0.9199 +2025-06-25 10:15:37,733 - pyskl - INFO - Epoch [145][100/1281] lr: 9.605e-05, eta: 0:53:30, time: 0.783, data_time: 0.185, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0186, loss: 0.0186 +2025-06-25 10:16:26,959 - pyskl - INFO - Epoch [145][200/1281] lr: 9.353e-05, eta: 0:52:48, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 10:17:15,617 - pyskl - INFO - Epoch [145][300/1281] lr: 9.106e-05, eta: 0:52:06, time: 0.487, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 10:18:04,480 - pyskl - INFO - Epoch [145][400/1281] lr: 8.861e-05, eta: 0:51:24, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9981, top5_acc: 1.0000, loss_cls: 0.0254, loss: 0.0254 +2025-06-25 10:18:31,638 - pyskl - INFO - Epoch [145][500/1281] lr: 8.620e-05, eta: 0:50:41, time: 0.272, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0205, loss: 0.0205 +2025-06-25 10:19:21,501 - pyskl - INFO - Epoch [145][600/1281] lr: 8.382e-05, eta: 0:49:59, time: 0.499, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0180, loss: 0.0180 +2025-06-25 10:19:52,222 - pyskl - INFO - Epoch [145][700/1281] lr: 8.147e-05, eta: 0:49:16, time: 0.307, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 10:20:41,218 - pyskl - INFO - Epoch [145][800/1281] lr: 7.916e-05, eta: 0:48:34, 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 10:21:30,205 - pyskl - INFO - Epoch [145][900/1281] lr: 7.688e-05, eta: 0:47:52, 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 10:22:19,059 - pyskl - INFO - Epoch [145][1000/1281] lr: 7.463e-05, eta: 0:47:10, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 10:23:08,223 - pyskl - INFO - Epoch [145][1100/1281] lr: 7.242e-05, eta: 0:46:28, 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 10:23:57,089 - pyskl - INFO - Epoch [145][1200/1281] lr: 7.024e-05, eta: 0:45:46, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0213, loss: 0.0213 +2025-06-25 10:24:37,284 - pyskl - INFO - Saving checkpoint at 145 epochs +2025-06-25 10:25:35,029 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:25:35,084 - pyskl - INFO - +top1_acc 0.9417 +top5_acc 0.9969 +2025-06-25 10:25:35,084 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:25:35,091 - pyskl - INFO - +mean_acc 0.9193 +2025-06-25 10:25:35,092 - pyskl - INFO - Epoch(val) [145][533] top1_acc: 0.9417, top5_acc: 0.9969, mean_class_accuracy: 0.9193 +2025-06-25 10:26:54,053 - pyskl - INFO - Epoch [146][100/1281] lr: 6.638e-05, eta: 0:44:29, time: 0.790, data_time: 0.188, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0200, loss: 0.0200 +2025-06-25 10:27:42,475 - pyskl - INFO - Epoch [146][200/1281] lr: 6.429e-05, eta: 0:43:47, time: 0.484, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0206, loss: 0.0206 +2025-06-25 10:28:31,243 - pyskl - INFO - Epoch [146][300/1281] lr: 6.224e-05, eta: 0:43:05, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-25 10:29:19,945 - pyskl - INFO - Epoch [146][400/1281] lr: 6.022e-05, eta: 0:42:23, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0196, loss: 0.0196 +2025-06-25 10:29:47,610 - pyskl - INFO - Epoch [146][500/1281] lr: 5.823e-05, eta: 0:41:40, time: 0.277, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0232, loss: 0.0232 +2025-06-25 10:30:38,303 - pyskl - INFO - Epoch [146][600/1281] lr: 5.628e-05, eta: 0:40:58, time: 0.507, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0194, loss: 0.0194 +2025-06-25 10:31:08,321 - pyskl - INFO - Epoch [146][700/1281] lr: 5.436e-05, eta: 0:40:15, time: 0.300, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0205, loss: 0.0205 +2025-06-25 10:31:57,381 - pyskl - INFO - Epoch [146][800/1281] lr: 5.247e-05, eta: 0:39:33, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 10:32:46,374 - pyskl - INFO - Epoch [146][900/1281] lr: 5.061e-05, eta: 0:38:51, 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 10:33:35,233 - pyskl - INFO - Epoch [146][1000/1281] lr: 4.879e-05, eta: 0:38:09, 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 10:34:24,432 - pyskl - INFO - Epoch [146][1100/1281] lr: 4.701e-05, eta: 0:37:27, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-25 10:35:13,335 - pyskl - INFO - Epoch [146][1200/1281] lr: 4.525e-05, eta: 0:36:44, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 10:35:53,743 - pyskl - INFO - Saving checkpoint at 146 epochs +2025-06-25 10:36:51,446 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:36:51,511 - pyskl - INFO - +top1_acc 0.9428 +top5_acc 0.9971 +2025-06-25 10:36:51,511 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:36:51,521 - pyskl - INFO - +mean_acc 0.9207 +2025-06-25 10:36:51,524 - pyskl - INFO - Epoch(val) [146][533] top1_acc: 0.9428, top5_acc: 0.9971, mean_class_accuracy: 0.9207 +2025-06-25 10:38:11,473 - pyskl - INFO - Epoch [147][100/1281] lr: 4.216e-05, eta: 0:35:28, time: 0.799, data_time: 0.186, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 10:39:00,495 - pyskl - INFO - Epoch [147][200/1281] lr: 4.050e-05, eta: 0:34:46, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0184, loss: 0.0184 +2025-06-25 10:39:49,168 - pyskl - INFO - Epoch [147][300/1281] lr: 3.887e-05, eta: 0:34:03, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 10:40:37,962 - pyskl - INFO - Epoch [147][400/1281] lr: 3.728e-05, eta: 0:33:21, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0204, loss: 0.0204 +2025-06-25 10:41:05,978 - pyskl - INFO - Epoch [147][500/1281] lr: 3.572e-05, eta: 0:32:38, time: 0.280, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0217, loss: 0.0217 +2025-06-25 10:41:56,791 - pyskl - INFO - Epoch [147][600/1281] lr: 3.419e-05, eta: 0:31:56, time: 0.508, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0192, loss: 0.0192 +2025-06-25 10:42:25,107 - pyskl - INFO - Epoch [147][700/1281] lr: 3.270e-05, eta: 0:31:14, time: 0.283, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 10:43:14,018 - pyskl - INFO - Epoch [147][800/1281] lr: 3.124e-05, eta: 0:30:31, 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 10:44:03,188 - pyskl - INFO - Epoch [147][900/1281] lr: 2.981e-05, eta: 0:29:49, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 0.9988, top5_acc: 1.0000, loss_cls: 0.0224, loss: 0.0224 +2025-06-25 10:44:52,002 - pyskl - INFO - Epoch [147][1000/1281] lr: 2.842e-05, eta: 0:29:07, time: 0.488, data_time: 0.001, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0250, loss: 0.0250 +2025-06-25 10:45:40,693 - pyskl - INFO - Epoch [147][1100/1281] lr: 2.706e-05, eta: 0:28:25, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0199, loss: 0.0199 +2025-06-25 10:46:30,106 - pyskl - INFO - Epoch [147][1200/1281] lr: 2.573e-05, eta: 0:27:42, 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 10:47:10,400 - pyskl - INFO - Saving checkpoint at 147 epochs +2025-06-25 10:48:08,376 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:48:08,431 - pyskl - INFO - +top1_acc 0.9413 +top5_acc 0.9967 +2025-06-25 10:48:08,431 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:48:08,438 - pyskl - INFO - +mean_acc 0.9201 +2025-06-25 10:48:08,439 - pyskl - INFO - Epoch(val) [147][533] top1_acc: 0.9413, top5_acc: 0.9967, mean_class_accuracy: 0.9201 +2025-06-25 10:49:26,201 - pyskl - INFO - Epoch [148][100/1281] lr: 2.341e-05, eta: 0:26:26, time: 0.778, data_time: 0.188, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 10:50:14,945 - pyskl - INFO - Epoch [148][200/1281] lr: 2.218e-05, eta: 0:25:44, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0268, loss: 0.0268 +2025-06-25 10:51:03,697 - pyskl - INFO - Epoch [148][300/1281] lr: 2.098e-05, eta: 0:25:01, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 10:51:52,574 - pyskl - INFO - Epoch [148][400/1281] lr: 1.981e-05, eta: 0:24:19, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0222, loss: 0.0222 +2025-06-25 10:52:22,993 - pyskl - INFO - Epoch [148][500/1281] lr: 1.868e-05, eta: 0:23:36, time: 0.304, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-25 10:53:13,601 - pyskl - INFO - Epoch [148][600/1281] lr: 1.758e-05, eta: 0:22:54, time: 0.506, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0203, loss: 0.0203 +2025-06-25 10:53:41,507 - pyskl - INFO - Epoch [148][700/1281] lr: 1.651e-05, eta: 0:22:12, time: 0.279, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0174, loss: 0.0174 +2025-06-25 10:54:30,489 - pyskl - INFO - Epoch [148][800/1281] lr: 1.548e-05, eta: 0:21:29, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 10:55:19,090 - pyskl - INFO - Epoch [148][900/1281] lr: 1.448e-05, eta: 0:20:47, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0187, loss: 0.0187 +2025-06-25 10:56:07,736 - pyskl - INFO - Epoch [148][1000/1281] lr: 1.351e-05, eta: 0:20:05, time: 0.486, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 10:56:56,746 - pyskl - INFO - Epoch [148][1100/1281] lr: 1.258e-05, eta: 0:19:22, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0209, loss: 0.0209 +2025-06-25 10:57:45,763 - pyskl - INFO - Epoch [148][1200/1281] lr: 1.168e-05, eta: 0:18:40, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 10:58:26,097 - pyskl - INFO - Saving checkpoint at 148 epochs +2025-06-25 10:59:24,043 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 10:59:24,098 - pyskl - INFO - +top1_acc 0.9433 +top5_acc 0.9967 +2025-06-25 10:59:24,099 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 10:59:24,105 - pyskl - INFO - +mean_acc 0.9214 +2025-06-25 10:59:24,107 - pyskl - INFO - Epoch(val) [148][533] top1_acc: 0.9433, top5_acc: 0.9967, mean_class_accuracy: 0.9214 +2025-06-25 11:00:44,143 - pyskl - INFO - Epoch [149][100/1281] lr: 1.013e-05, eta: 0:17:23, time: 0.800, data_time: 0.186, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 11:01:32,992 - pyskl - INFO - Epoch [149][200/1281] lr: 9.328e-06, eta: 0:16:41, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0208, loss: 0.0208 +2025-06-25 11:02:21,765 - pyskl - INFO - Epoch [149][300/1281] lr: 8.555e-06, eta: 0:15:59, time: 0.488, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0198, loss: 0.0198 +2025-06-25 11:03:10,842 - pyskl - INFO - Epoch [149][400/1281] lr: 7.816e-06, eta: 0:15:16, 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 11:03:40,868 - pyskl - INFO - Epoch [149][500/1281] lr: 7.110e-06, eta: 0:14:34, time: 0.300, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 11:04:31,631 - pyskl - INFO - Epoch [149][600/1281] lr: 6.437e-06, eta: 0:13:52, time: 0.508, data_time: 0.001, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0224, loss: 0.0224 +2025-06-25 11:05:00,055 - pyskl - INFO - Epoch [149][700/1281] lr: 5.798e-06, eta: 0:13:09, time: 0.284, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 11:05:48,787 - pyskl - INFO - Epoch [149][800/1281] lr: 5.192e-06, eta: 0:12:27, time: 0.487, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0190, loss: 0.0190 +2025-06-25 11:06:37,658 - pyskl - INFO - Epoch [149][900/1281] lr: 4.620e-06, eta: 0:11:44, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0215, loss: 0.0215 +2025-06-25 11:07:26,553 - pyskl - INFO - Epoch [149][1000/1281] lr: 4.081e-06, eta: 0:11:02, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0212, loss: 0.0212 +2025-06-25 11:08:15,771 - pyskl - INFO - Epoch [149][1100/1281] lr: 3.576e-06, eta: 0:10:20, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 11:09:04,848 - pyskl - INFO - Epoch [149][1200/1281] lr: 3.104e-06, eta: 0:09:37, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0217, loss: 0.0217 +2025-06-25 11:09:45,317 - pyskl - INFO - Saving checkpoint at 149 epochs +2025-06-25 11:10:43,541 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:10:43,597 - pyskl - INFO - +top1_acc 0.9421 +top5_acc 0.9966 +2025-06-25 11:10:43,597 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:10:43,603 - pyskl - INFO - +mean_acc 0.9212 +2025-06-25 11:10:43,605 - pyskl - INFO - Epoch(val) [149][533] top1_acc: 0.9421, top5_acc: 0.9966, mean_class_accuracy: 0.9212 +2025-06-25 11:12:01,595 - pyskl - INFO - Epoch [150][100/1281] lr: 2.334e-06, eta: 0:08:20, time: 0.780, data_time: 0.180, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0210, loss: 0.0210 +2025-06-25 11:12:50,618 - pyskl - INFO - Epoch [150][200/1281] lr: 1.956e-06, eta: 0:07:38, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0176, loss: 0.0176 +2025-06-25 11:13:39,830 - pyskl - INFO - Epoch [150][300/1281] lr: 1.611e-06, eta: 0:06:56, time: 0.492, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0189, loss: 0.0189 +2025-06-25 11:14:28,973 - pyskl - INFO - Epoch [150][400/1281] lr: 1.300e-06, eta: 0:06:13, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0179, loss: 0.0179 +2025-06-25 11:15:00,059 - pyskl - INFO - Epoch [150][500/1281] lr: 1.022e-06, eta: 0:05:31, time: 0.311, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0246, loss: 0.0246 +2025-06-25 11:15:50,658 - pyskl - INFO - Epoch [150][600/1281] lr: 7.771e-07, eta: 0:04:48, time: 0.506, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0201, loss: 0.0201 +2025-06-25 11:16:16,577 - pyskl - INFO - Epoch [150][700/1281] lr: 5.659e-07, eta: 0:04:06, time: 0.259, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0193, loss: 0.0193 +2025-06-25 11:17:05,600 - pyskl - INFO - Epoch [150][800/1281] lr: 3.881e-07, eta: 0:03:24, time: 0.490, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0191, loss: 0.0191 +2025-06-25 11:17:54,734 - pyskl - INFO - Epoch [150][900/1281] lr: 2.438e-07, eta: 0:02:41, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0195, loss: 0.0195 +2025-06-25 11:18:43,600 - pyskl - INFO - Epoch [150][1000/1281] lr: 1.329e-07, eta: 0:01:59, time: 0.489, data_time: 0.000, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0182, loss: 0.0182 +2025-06-25 11:19:32,437 - pyskl - INFO - Epoch [150][1100/1281] lr: 5.534e-08, eta: 0:01:16, time: 0.488, data_time: 0.001, memory: 4083, top1_acc: 1.0000, top5_acc: 1.0000, loss_cls: 0.0188, loss: 0.0188 +2025-06-25 11:20:21,573 - pyskl - INFO - Epoch [150][1200/1281] lr: 1.123e-08, eta: 0:00:34, time: 0.491, data_time: 0.000, memory: 4083, top1_acc: 0.9994, top5_acc: 1.0000, loss_cls: 0.0209, loss: 0.0209 +2025-06-25 11:21:01,685 - pyskl - INFO - Saving checkpoint at 150 epochs +2025-06-25 11:21:59,661 - pyskl - INFO - Evaluating top_k_accuracy ... +2025-06-25 11:21:59,731 - pyskl - INFO - +top1_acc 0.9431 +top5_acc 0.9965 +2025-06-25 11:21:59,731 - pyskl - INFO - Evaluating mean_class_accuracy ... +2025-06-25 11:21:59,740 - pyskl - INFO - +mean_acc 0.9212 +2025-06-25 11:21:59,743 - pyskl - INFO - Epoch(val) [150][533] top1_acc: 0.9431, top5_acc: 0.9965, mean_class_accuracy: 0.9212 +2025-06-25 11:22:04,281 - pyskl - INFO - 8521 videos remain after valid thresholding +2025-06-25 11:29:36,949 - pyskl - INFO - Testing results of the last checkpoint +2025-06-25 11:29:36,949 - pyskl - INFO - top1_acc: 0.9431 +2025-06-25 11:29:36,949 - pyskl - INFO - top5_acc: 0.9973 +2025-06-25 11:29:36,949 - pyskl - INFO - mean_class_accuracy: 0.9221 +2025-06-25 11:29:36,950 - pyskl - INFO - load checkpoint from local path: ./work_dirs/test_aclnet/finegym/b_2/best_top1_acc_epoch_139.pth +2025-06-25 11:37:19,917 - pyskl - INFO - Testing results of the best checkpoint +2025-06-25 11:37:19,918 - pyskl - INFO - top1_acc: 0.9457 +2025-06-25 11:37:19,918 - pyskl - INFO - top5_acc: 0.9974 +2025-06-25 11:37:19,918 - pyskl - INFO - mean_class_accuracy: 0.9259