2023/02/17 12:07:19 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.7.0 (default, Oct 9 2018, 10:31:47) [GCC 7.3.0] CUDA available: True numpy_random_seed: 443340459 GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/cache/share/cuda-11.1 NVCC: Cuda compilation tools, release 11.1, V11.1.74 GCC: gcc (GCC) 5.4.0 PyTorch: 1.9.0+cu111 PyTorch compiling details: PyTorch built with: - GCC 7.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.1.2 (Git Hash 98be7e8afa711dc9b66c8ff3504129cb82013cdb) - OpenMP 201511 (a.k.a. OpenMP 4.5) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.1 - 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_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 - CuDNN 8.0.5 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, 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 -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-variable -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=1.9.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, TorchVision: 0.10.0+cu111 OpenCV: 4.6.0 MMEngine: 0.5.0 Runtime environment: cudnn_benchmark: False mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: None diff_rank_seed: False deterministic: False Distributed launcher: pytorch Distributed training: True GPU number: 8 ------------------------------------------------------------ 2023/02/17 12:07:19 - mmengine - INFO - Config: model = dict( type='Recognizer2D', backbone=dict( type='ResNetTSM', pretrained='torchvision://resnet50', depth=50, out_indices=(2, 3), norm_eval=False, shift_div=8), neck=dict( type='TPN', in_channels=(1024, 2048), out_channels=1024, spatial_modulation_cfg=dict( in_channels=(1024, 2048), out_channels=2048), temporal_modulation_cfg=dict(downsample_scales=(8, 8)), upsample_cfg=dict(scale_factor=(1, 1, 1)), downsample_cfg=dict(downsample_scale=(1, 1, 1)), level_fusion_cfg=dict( in_channels=(1024, 1024), mid_channels=(1024, 1024), out_channels=2048, downsample_scales=((1, 1, 1), (1, 1, 1))), aux_head_cfg=dict(out_channels=174, loss_weight=0.5)), cls_head=dict( type='TPNHead', num_classes=174, in_channels=2048, spatial_type='avg', consensus=dict(type='AvgConsensus', dim=1), dropout_ratio=0.5, init_std=0.01, average_clips='prob'), data_preprocessor=dict( type='ActionDataPreprocessor', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], format_shape='NCHW'), train_cfg=None, test_cfg=dict(fcn_test=True)) default_scope = 'mmaction' default_hooks = dict( runtime_info=dict(type='RuntimeInfoHook'), timer=dict(type='IterTimerHook'), logger=dict(type='LoggerHook', interval=20, ignore_last=False), param_scheduler=dict(type='ParamSchedulerHook'), checkpoint=dict(type='CheckpointHook', interval=1, save_best='auto'), sampler_seed=dict(type='DistSamplerSeedHook'), sync_buffers=dict(type='SyncBuffersHook')) env_cfg = dict( cudnn_benchmark=False, mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), dist_cfg=dict(backend='nccl')) log_processor = dict(type='LogProcessor', window_size=20, by_epoch=True) vis_backends = [ dict(type='LocalVisBackend'), dict(type='TensorboardVisBackend') ] visualizer = dict( type='ActionVisualizer', vis_backends=[ dict(type='LocalVisBackend'), dict(type='TensorboardVisBackend') ]) log_level = 'INFO' load_from = None resume = False dataset_type = 'RawframeDataset' data_root = 'data/sthv1/rawframes' data_root_val = 'data/sthv1/rawframes' ann_file_train = 'data/sthv1/sthv1_train_list_rawframes.txt' ann_file_val = 'data/sthv1/sthv1_val_list_rawframes.txt' ann_file_test = 'data/sthv1/sthv1_val_list_rawframes.txt' file_client_args = dict( io_backend='petrel', path_mapping=dict( {'data/sthv1': 's204:s3://openmmlab/datasets/action/sthv1'})) sthv1_flip_label_map = dict({2: 4, 4: 2, 30: 41, 41: 30, 52: 66, 66: 52}) train_pipeline = [ dict(type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict( {'data/sthv1': 's204:s3://openmmlab/datasets/action/sthv1'})), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict( type='Flip', flip_ratio=0.5, flip_label_map=dict({ 2: 4, 4: 2, 30: 41, 41: 30, 52: 66, 66: 52 })), dict(type='ColorJitter'), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ] val_pipeline = [ dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8, test_mode=True), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict( {'data/sthv1': 's204:s3://openmmlab/datasets/action/sthv1'})), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ] test_pipeline = [ dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8, twice_sample=True, test_mode=True), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict( {'data/sthv1': 's204:s3://openmmlab/datasets/action/sthv1'})), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ] train_dataloader = dict( batch_size=8, num_workers=16, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='RawframeDataset', ann_file='data/sthv1/sthv1_train_list_rawframes.txt', data_prefix=dict(img='data/sthv1/rawframes'), filename_tmpl='{:05}.jpg', pipeline=[ dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict({ 'data/sthv1': 's204:s3://openmmlab/datasets/action/sthv1' })), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict( type='Flip', flip_ratio=0.5, flip_label_map=dict({ 2: 4, 4: 2, 30: 41, 41: 30, 52: 66, 66: 52 })), dict(type='ColorJitter'), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ])) val_dataloader = dict( batch_size=8, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='RawframeDataset', ann_file='data/sthv1/sthv1_val_list_rawframes.txt', data_prefix=dict(img='data/sthv1/rawframes'), filename_tmpl='{:05}.jpg', pipeline=[ dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8, test_mode=True), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict({ 'data/sthv1': 's204:s3://openmmlab/datasets/action/sthv1' })), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ], test_mode=True)) test_dataloader = dict( batch_size=1, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='RawframeDataset', ann_file='data/sthv1/sthv1_val_list_rawframes.txt', data_prefix=dict(img='data/sthv1/rawframes'), filename_tmpl='{:05}.jpg', pipeline=[ dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8, twice_sample=True, test_mode=True), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict({ 'data/sthv1': 's204:s3://openmmlab/datasets/action/sthv1' })), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ], test_mode=True)) val_evaluator = dict(type='AccMetric') test_evaluator = dict(type='AccMetric') train_cfg = dict( type='EpochBasedTrainLoop', max_epochs=150, val_begin=1, val_interval=5) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') param_scheduler = [ dict( type='MultiStepLR', begin=0, end=150, by_epoch=True, milestones=[75, 125], gamma=0.1) ] optim_wrapper = dict( optimizer=dict( type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005, nesterov=True), clip_grad=dict(max_norm=20, norm_type=2)) launcher = 'pytorch' work_dir = 'work_dirs/fix_flip/tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb' randomness = dict(seed=None, diff_rank_seed=False, deterministic=False) 2023/02/17 12:07:22 - mmengine - INFO - These parameters in pretrained checkpoint are not loaded: {'fc.bias', 'fc.weight'} 2023/02/17 12:07:23 - mmengine - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) RuntimeInfoHook (BELOW_NORMAL) LoggerHook -------------------- before_train: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (VERY_LOW ) CheckpointHook -------------------- before_train_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (NORMAL ) DistSamplerSeedHook -------------------- before_train_iter: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook -------------------- after_train_iter: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- after_train_epoch: (NORMAL ) IterTimerHook (NORMAL ) SyncBuffersHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- before_val_epoch: (NORMAL ) IterTimerHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_val_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- before_test_epoch: (NORMAL ) IterTimerHook -------------------- before_test_iter: (NORMAL ) IterTimerHook -------------------- after_test_iter: (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- Name of parameter - Initialization information backbone.conv1.conv.weight - torch.Size([64, 3, 7, 7]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.conv1.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.conv1.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.0.conv1.conv.net.weight - torch.Size([64, 64, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.0.conv1.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.0.conv1.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.0.conv2.conv.weight - torch.Size([64, 64, 3, 3]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.0.conv2.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.0.conv2.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.0.conv3.conv.weight - torch.Size([256, 64, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.0.conv3.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.0.conv3.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.0.downsample.conv.weight - torch.Size([256, 64, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.0.downsample.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.0.downsample.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.1.conv1.conv.net.weight - torch.Size([64, 256, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.1.conv1.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.1.conv1.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.1.conv2.conv.weight - torch.Size([64, 64, 3, 3]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.1.conv2.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.1.conv2.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.1.conv3.conv.weight - torch.Size([256, 64, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.1.conv3.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.1.conv3.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.2.conv1.conv.net.weight - torch.Size([64, 256, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.2.conv1.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.2.conv1.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.2.conv2.conv.weight - torch.Size([64, 64, 3, 3]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.2.conv2.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.2.conv2.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.2.conv3.conv.weight - torch.Size([256, 64, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.2.conv3.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer1.2.conv3.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.0.conv1.conv.net.weight - torch.Size([128, 256, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.0.conv1.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.0.conv1.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.0.conv2.conv.weight - torch.Size([128, 128, 3, 3]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.0.conv2.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.0.conv2.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.0.conv3.conv.weight - torch.Size([512, 128, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.0.conv3.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.0.conv3.bn.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.0.downsample.conv.weight - torch.Size([512, 256, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.0.downsample.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.0.downsample.bn.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.1.conv1.conv.net.weight - torch.Size([128, 512, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.1.conv1.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.1.conv1.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.1.conv2.conv.weight - torch.Size([128, 128, 3, 3]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.1.conv2.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.1.conv2.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.1.conv3.conv.weight - torch.Size([512, 128, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.1.conv3.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.1.conv3.bn.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.2.conv1.conv.net.weight - torch.Size([128, 512, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.2.conv1.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.2.conv1.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.2.conv2.conv.weight - torch.Size([128, 128, 3, 3]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.2.conv2.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.2.conv2.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.2.conv3.conv.weight - torch.Size([512, 128, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.2.conv3.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.2.conv3.bn.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.3.conv1.conv.net.weight - torch.Size([128, 512, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.3.conv1.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.3.conv1.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.3.conv2.conv.weight - torch.Size([128, 128, 3, 3]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.3.conv2.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.3.conv2.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.3.conv3.conv.weight - torch.Size([512, 128, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.3.conv3.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer2.3.conv3.bn.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.0.conv1.conv.net.weight - torch.Size([256, 512, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.0.conv1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.0.conv1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.0.conv2.conv.weight - torch.Size([256, 256, 3, 3]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.0.conv2.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.0.conv2.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.0.conv3.conv.weight - torch.Size([1024, 256, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.0.conv3.bn.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.0.conv3.bn.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.0.downsample.conv.weight - torch.Size([1024, 512, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.0.downsample.bn.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.0.downsample.bn.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.1.conv1.conv.net.weight - torch.Size([256, 1024, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.1.conv1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.1.conv1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.1.conv2.conv.weight - torch.Size([256, 256, 3, 3]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.1.conv2.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.1.conv2.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.1.conv3.conv.weight - torch.Size([1024, 256, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.1.conv3.bn.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.1.conv3.bn.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.2.conv1.conv.net.weight - torch.Size([256, 1024, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.2.conv1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.2.conv1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.2.conv2.conv.weight - torch.Size([256, 256, 3, 3]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.2.conv2.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.2.conv2.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.2.conv3.conv.weight - torch.Size([1024, 256, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.2.conv3.bn.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.2.conv3.bn.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.3.conv1.conv.net.weight - torch.Size([256, 1024, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.3.conv1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.3.conv1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.3.conv2.conv.weight - torch.Size([256, 256, 3, 3]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.3.conv2.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.3.conv2.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.3.conv3.conv.weight - torch.Size([1024, 256, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.3.conv3.bn.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.3.conv3.bn.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.4.conv1.conv.net.weight - torch.Size([256, 1024, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.4.conv1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.4.conv1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.4.conv2.conv.weight - torch.Size([256, 256, 3, 3]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.4.conv2.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.4.conv2.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.4.conv3.conv.weight - torch.Size([1024, 256, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.4.conv3.bn.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.4.conv3.bn.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.5.conv1.conv.net.weight - torch.Size([256, 1024, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.5.conv1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.5.conv1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.5.conv2.conv.weight - torch.Size([256, 256, 3, 3]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.5.conv2.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.5.conv2.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.5.conv3.conv.weight - torch.Size([1024, 256, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.5.conv3.bn.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer3.5.conv3.bn.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.0.conv1.conv.net.weight - torch.Size([512, 1024, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.0.conv1.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.0.conv1.bn.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.0.conv2.conv.weight - torch.Size([512, 512, 3, 3]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.0.conv2.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.0.conv2.bn.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.0.conv3.conv.weight - torch.Size([2048, 512, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.0.conv3.bn.weight - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.0.conv3.bn.bias - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.0.downsample.conv.weight - torch.Size([2048, 1024, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.0.downsample.bn.weight - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.0.downsample.bn.bias - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.1.conv1.conv.net.weight - torch.Size([512, 2048, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.1.conv1.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.1.conv1.bn.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.1.conv2.conv.weight - torch.Size([512, 512, 3, 3]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.1.conv2.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.1.conv2.bn.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.1.conv3.conv.weight - torch.Size([2048, 512, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.1.conv3.bn.weight - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.1.conv3.bn.bias - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.2.conv1.conv.net.weight - torch.Size([512, 2048, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.2.conv1.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.2.conv1.bn.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.2.conv2.conv.weight - torch.Size([512, 512, 3, 3]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.2.conv2.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.2.conv2.bn.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.2.conv3.conv.weight - torch.Size([2048, 512, 1, 1]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.2.conv3.bn.weight - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D backbone.layer4.2.conv3.bn.bias - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D neck.temporal_modulation_ops.0.conv.conv.weight - torch.Size([1024, 64, 3, 1, 1]): Initialized by user-defined `init_weights` in TPN neck.temporal_modulation_ops.1.conv.conv.weight - torch.Size([1024, 64, 3, 1, 1]): Initialized by user-defined `init_weights` in TPN neck.downsample_ops.0.conv.conv.weight - torch.Size([1024, 1024, 3, 1, 1]): Initialized by user-defined `init_weights` in TPN neck.level_fusion_1.downsamples.0.conv.conv.weight - torch.Size([1024, 32, 1, 1, 1]): Initialized by user-defined `init_weights` in TPN neck.level_fusion_1.downsamples.0.conv.bn.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D neck.level_fusion_1.downsamples.0.conv.bn.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D neck.level_fusion_1.downsamples.1.conv.conv.weight - torch.Size([1024, 32, 1, 1, 1]): Initialized by user-defined `init_weights` in TPN neck.level_fusion_1.downsamples.1.conv.bn.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D neck.level_fusion_1.downsamples.1.conv.bn.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D neck.level_fusion_1.fusion_conv.conv.weight - torch.Size([2048, 2048, 1, 1, 1]): Initialized by user-defined `init_weights` in TPN neck.level_fusion_1.fusion_conv.bn.weight - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D neck.level_fusion_1.fusion_conv.bn.bias - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D neck.spatial_modulation.spatial_modulation.0.0.conv.weight - torch.Size([2048, 1024, 1, 3, 3]): Initialized by user-defined `init_weights` in TPN neck.spatial_modulation.spatial_modulation.0.0.bn.weight - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D neck.spatial_modulation.spatial_modulation.0.0.bn.bias - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D neck.level_fusion_2.downsamples.0.conv.conv.weight - torch.Size([1024, 32, 1, 1, 1]): Initialized by user-defined `init_weights` in TPN neck.level_fusion_2.downsamples.0.conv.bn.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D neck.level_fusion_2.downsamples.0.conv.bn.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D neck.level_fusion_2.downsamples.1.conv.conv.weight - torch.Size([1024, 32, 1, 1, 1]): Initialized by user-defined `init_weights` in TPN neck.level_fusion_2.downsamples.1.conv.bn.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D neck.level_fusion_2.downsamples.1.conv.bn.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of Recognizer2D neck.level_fusion_2.fusion_conv.conv.weight - torch.Size([2048, 2048, 1, 1, 1]): Initialized by user-defined `init_weights` in TPN neck.level_fusion_2.fusion_conv.bn.weight - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D neck.level_fusion_2.fusion_conv.bn.bias - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D neck.pyramid_fusion.conv.weight - torch.Size([2048, 4096, 1, 1, 1]): Initialized by user-defined `init_weights` in TPN neck.pyramid_fusion.bn.weight - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D neck.pyramid_fusion.bn.bias - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D neck.aux_head.conv.conv.weight - torch.Size([2048, 1024, 1, 3, 3]): Initialized by user-defined `init_weights` in TPN neck.aux_head.conv.bn.weight - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D neck.aux_head.conv.bn.bias - torch.Size([2048]): The value is the same before and after calling `init_weights` of Recognizer2D neck.aux_head.fc.weight - torch.Size([174, 2048]): Initialized by user-defined `init_weights` in TPN neck.aux_head.fc.bias - torch.Size([174]): Initialized by user-defined `init_weights` in TPN cls_head.fc_cls.weight - torch.Size([174, 2048]): Initialized by user-defined `init_weights` in TPNHead cls_head.fc_cls.bias - torch.Size([174]): Initialized by user-defined `init_weights` in TPNHead 2023/02/17 12:07:25 - mmengine - INFO - Checkpoints will be saved to /mnt/petrelfs/lilin/Repos/mmact_dev/mmaction2/work_dirs/fix_flip/tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb. 2023/02/17 12:08:16 - mmengine - INFO - Epoch(train) [1][ 20/1345] lr: 1.0000e-02 eta: 6 days, 1:14:19 time: 2.5919 data_time: 2.3429 memory: 8326 grad_norm: 5.6361 loss: 7.7325 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 5.1664 loss_aux: 2.5661 2023/02/17 12:08:20 - mmengine - INFO - Epoch(train) [1][ 40/1345] lr: 1.0000e-02 eta: 3 days, 6:14:59 time: 0.2012 data_time: 0.0061 memory: 8326 grad_norm: 5.5182 loss: 7.9091 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.3081 loss_aux: 2.6009 2023/02/17 12:08:24 - mmengine - INFO - Epoch(train) [1][ 60/1345] lr: 1.0000e-02 eta: 2 days, 7:50:37 time: 0.1972 data_time: 0.0048 memory: 8326 grad_norm: 5.3804 loss: 7.7168 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 5.1730 loss_aux: 2.5437 2023/02/17 12:08:28 - mmengine - INFO - Epoch(train) [1][ 80/1345] lr: 1.0000e-02 eta: 1 day, 20:36:44 time: 0.1952 data_time: 0.0060 memory: 8326 grad_norm: 5.0954 loss: 7.6665 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 5.1189 loss_aux: 2.5476 2023/02/17 12:08:32 - mmengine - INFO - Epoch(train) [1][ 100/1345] lr: 1.0000e-02 eta: 1 day, 13:52:14 time: 0.1950 data_time: 0.0072 memory: 8326 grad_norm: 4.9998 loss: 7.6666 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 5.1094 loss_aux: 2.5572 2023/02/17 12:08:36 - mmengine - INFO - Epoch(train) [1][ 120/1345] lr: 1.0000e-02 eta: 1 day, 9:21:50 time: 0.1937 data_time: 0.0064 memory: 8326 grad_norm: 4.8075 loss: 7.5840 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 5.0428 loss_aux: 2.5411 2023/02/17 12:08:40 - mmengine - INFO - Epoch(train) [1][ 140/1345] lr: 1.0000e-02 eta: 1 day, 6:09:00 time: 0.1944 data_time: 0.0055 memory: 8326 grad_norm: 4.4949 loss: 7.5953 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 5.0436 loss_aux: 2.5518 2023/02/17 12:08:44 - mmengine - INFO - Epoch(train) [1][ 160/1345] lr: 1.0000e-02 eta: 1 day, 3:44:18 time: 0.1942 data_time: 0.0058 memory: 8326 grad_norm: 4.3322 loss: 7.4806 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 4.9600 loss_aux: 2.5206 2023/02/17 12:08:48 - mmengine - INFO - Epoch(train) [1][ 180/1345] lr: 1.0000e-02 eta: 1 day, 1:51:51 time: 0.1945 data_time: 0.0061 memory: 8326 grad_norm: 4.2034 loss: 7.5618 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 5.0200 loss_aux: 2.5418 2023/02/17 12:08:52 - mmengine - INFO - Epoch(train) [1][ 200/1345] lr: 1.0000e-02 eta: 1 day, 0:21:48 time: 0.1943 data_time: 0.0061 memory: 8326 grad_norm: 4.2150 loss: 7.6455 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.0784 loss_aux: 2.5672 2023/02/17 12:08:57 - mmengine - INFO - Epoch(train) [1][ 220/1345] lr: 1.0000e-02 eta: 23:31:21 time: 0.2705 data_time: 0.0067 memory: 8326 grad_norm: 4.1432 loss: 7.4205 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 4.8881 loss_aux: 2.5325 2023/02/17 12:09:01 - mmengine - INFO - Epoch(train) [1][ 240/1345] lr: 1.0000e-02 eta: 22:29:00 time: 0.1979 data_time: 0.0059 memory: 8326 grad_norm: 4.1430 loss: 7.4223 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.9106 loss_aux: 2.5117 2023/02/17 12:09:05 - mmengine - INFO - Epoch(train) [1][ 260/1345] lr: 1.0000e-02 eta: 21:38:13 time: 0.2056 data_time: 0.0162 memory: 8326 grad_norm: 4.1853 loss: 7.4596 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 4.9275 loss_aux: 2.5321 2023/02/17 12:09:09 - mmengine - INFO - Epoch(train) [1][ 280/1345] lr: 1.0000e-02 eta: 20:52:00 time: 0.1945 data_time: 0.0059 memory: 8326 grad_norm: 4.1809 loss: 7.3705 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.8537 loss_aux: 2.5169 2023/02/17 12:09:13 - mmengine - INFO - Epoch(train) [1][ 300/1345] lr: 1.0000e-02 eta: 20:12:00 time: 0.1947 data_time: 0.0060 memory: 8326 grad_norm: 4.1269 loss: 7.2757 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.7806 loss_aux: 2.4951 2023/02/17 12:09:17 - mmengine - INFO - Epoch(train) [1][ 320/1345] lr: 1.0000e-02 eta: 19:37:17 time: 0.1961 data_time: 0.0065 memory: 8326 grad_norm: 4.0674 loss: 7.5258 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.9763 loss_aux: 2.5495 2023/02/17 12:09:21 - mmengine - INFO - Epoch(train) [1][ 340/1345] lr: 1.0000e-02 eta: 19:06:12 time: 0.1939 data_time: 0.0055 memory: 8326 grad_norm: 4.0461 loss: 7.4071 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.8801 loss_aux: 2.5271 2023/02/17 12:09:24 - mmengine - INFO - Epoch(train) [1][ 360/1345] lr: 1.0000e-02 eta: 18:38:35 time: 0.1940 data_time: 0.0060 memory: 8326 grad_norm: 4.2463 loss: 7.4517 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 4.9253 loss_aux: 2.5264 2023/02/17 12:09:28 - mmengine - INFO - Epoch(train) [1][ 380/1345] lr: 1.0000e-02 eta: 18:14:07 time: 0.1953 data_time: 0.0059 memory: 8326 grad_norm: 4.2738 loss: 7.1505 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.6890 loss_aux: 2.4616 2023/02/17 12:09:32 - mmengine - INFO - Epoch(train) [1][ 400/1345] lr: 1.0000e-02 eta: 17:51:53 time: 0.1942 data_time: 0.0061 memory: 8326 grad_norm: 4.3048 loss: 7.3140 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.8407 loss_aux: 2.4734 2023/02/17 12:09:36 - mmengine - INFO - Epoch(train) [1][ 420/1345] lr: 1.0000e-02 eta: 17:31:49 time: 0.1944 data_time: 0.0061 memory: 8326 grad_norm: 4.3790 loss: 7.2299 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.7603 loss_aux: 2.4696 2023/02/17 12:09:40 - mmengine - INFO - Epoch(train) [1][ 440/1345] lr: 1.0000e-02 eta: 17:13:32 time: 0.1943 data_time: 0.0061 memory: 8326 grad_norm: 4.3046 loss: 7.0489 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 4.6276 loss_aux: 2.4213 2023/02/17 12:09:45 - mmengine - INFO - Epoch(train) [1][ 460/1345] lr: 1.0000e-02 eta: 17:06:59 time: 0.2639 data_time: 0.0058 memory: 8326 grad_norm: 4.4425 loss: 7.1939 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.7244 loss_aux: 2.4695 2023/02/17 12:09:49 - mmengine - INFO - Epoch(train) [1][ 480/1345] lr: 1.0000e-02 eta: 16:51:46 time: 0.1979 data_time: 0.0059 memory: 8326 grad_norm: 4.6625 loss: 7.0034 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.5926 loss_aux: 2.4108 2023/02/17 12:09:53 - mmengine - INFO - Epoch(train) [1][ 500/1345] lr: 1.0000e-02 eta: 16:37:35 time: 0.1967 data_time: 0.0062 memory: 8326 grad_norm: 4.4487 loss: 7.1542 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.7069 loss_aux: 2.4473 2023/02/17 12:09:57 - mmengine - INFO - Epoch(train) [1][ 520/1345] lr: 1.0000e-02 eta: 16:24:20 time: 0.1955 data_time: 0.0070 memory: 8326 grad_norm: 4.3988 loss: 7.1728 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.7226 loss_aux: 2.4503 2023/02/17 12:10:01 - mmengine - INFO - Epoch(train) [1][ 540/1345] lr: 1.0000e-02 eta: 16:11:57 time: 0.1946 data_time: 0.0063 memory: 8326 grad_norm: 4.4732 loss: 7.2004 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.7352 loss_aux: 2.4651 2023/02/17 12:10:05 - mmengine - INFO - Epoch(train) [1][ 560/1345] lr: 1.0000e-02 eta: 16:00:19 time: 0.1935 data_time: 0.0059 memory: 8326 grad_norm: 4.5638 loss: 7.2538 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.7783 loss_aux: 2.4755 2023/02/17 12:10:09 - mmengine - INFO - Epoch(train) [1][ 580/1345] lr: 1.0000e-02 eta: 15:49:35 time: 0.1944 data_time: 0.0060 memory: 8326 grad_norm: 4.4976 loss: 6.9771 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.5658 loss_aux: 2.4112 2023/02/17 12:10:13 - mmengine - INFO - Epoch(train) [1][ 600/1345] lr: 1.0000e-02 eta: 15:39:36 time: 0.1948 data_time: 0.0068 memory: 8326 grad_norm: 4.5933 loss: 7.1830 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 4.6899 loss_aux: 2.4931 2023/02/17 12:10:17 - mmengine - INFO - Epoch(train) [1][ 620/1345] lr: 1.0000e-02 eta: 15:30:15 time: 0.1947 data_time: 0.0060 memory: 8326 grad_norm: 4.6286 loss: 7.0741 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.6448 loss_aux: 2.4292 2023/02/17 12:10:20 - mmengine - INFO - Epoch(train) [1][ 640/1345] lr: 1.0000e-02 eta: 15:21:24 time: 0.1939 data_time: 0.0058 memory: 8326 grad_norm: 4.6707 loss: 6.9085 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.5335 loss_aux: 2.3750 2023/02/17 12:10:24 - mmengine - INFO - Epoch(train) [1][ 660/1345] lr: 1.0000e-02 eta: 15:13:00 time: 0.1931 data_time: 0.0058 memory: 8326 grad_norm: 4.7052 loss: 7.1685 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.7207 loss_aux: 2.4478 2023/02/17 12:10:30 - mmengine - INFO - Epoch(train) [1][ 680/1345] lr: 1.0000e-02 eta: 15:11:48 time: 0.2612 data_time: 0.0062 memory: 8326 grad_norm: 4.7967 loss: 6.9530 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 4.5644 loss_aux: 2.3887 2023/02/17 12:10:33 - mmengine - INFO - Epoch(train) [1][ 700/1345] lr: 1.0000e-02 eta: 15:04:24 time: 0.1956 data_time: 0.0062 memory: 8326 grad_norm: 4.8272 loss: 6.9955 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.6018 loss_aux: 2.3936 2023/02/17 12:10:37 - mmengine - INFO - Epoch(train) [1][ 720/1345] lr: 1.0000e-02 eta: 14:57:18 time: 0.1946 data_time: 0.0060 memory: 8326 grad_norm: 4.9359 loss: 7.1817 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.7310 loss_aux: 2.4507 2023/02/17 12:10:41 - mmengine - INFO - Epoch(train) [1][ 740/1345] lr: 1.0000e-02 eta: 14:50:30 time: 0.1937 data_time: 0.0059 memory: 8326 grad_norm: 4.6961 loss: 7.1149 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 4.6656 loss_aux: 2.4493 2023/02/17 12:10:46 - mmengine - INFO - Epoch(train) [1][ 760/1345] lr: 1.0000e-02 eta: 14:48:39 time: 0.2459 data_time: 0.0059 memory: 8326 grad_norm: 4.8052 loss: 7.0473 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.6293 loss_aux: 2.4180 2023/02/17 12:10:50 - mmengine - INFO - Epoch(train) [1][ 780/1345] lr: 1.0000e-02 eta: 14:42:33 time: 0.1952 data_time: 0.0070 memory: 8326 grad_norm: 4.7830 loss: 7.0305 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.6369 loss_aux: 2.3936 2023/02/17 12:10:54 - mmengine - INFO - Epoch(train) [1][ 800/1345] lr: 1.0000e-02 eta: 14:36:49 time: 0.1961 data_time: 0.0055 memory: 8326 grad_norm: 5.0203 loss: 7.0211 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.5816 loss_aux: 2.4395 2023/02/17 12:10:58 - mmengine - INFO - Epoch(train) [1][ 820/1345] lr: 1.0000e-02 eta: 14:31:11 time: 0.1939 data_time: 0.0056 memory: 8326 grad_norm: 5.0129 loss: 6.9980 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.5651 loss_aux: 2.4329 2023/02/17 12:11:02 - mmengine - INFO - Epoch(train) [1][ 840/1345] lr: 1.0000e-02 eta: 14:25:48 time: 0.1939 data_time: 0.0053 memory: 8326 grad_norm: 5.0019 loss: 6.8880 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.5087 loss_aux: 2.3793 2023/02/17 12:11:06 - mmengine - INFO - Epoch(train) [1][ 860/1345] lr: 1.0000e-02 eta: 14:20:45 time: 0.1948 data_time: 0.0055 memory: 8326 grad_norm: 5.1030 loss: 7.0063 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.5747 loss_aux: 2.4316 2023/02/17 12:11:09 - mmengine - INFO - Epoch(train) [1][ 880/1345] lr: 1.0000e-02 eta: 14:15:50 time: 0.1934 data_time: 0.0058 memory: 8326 grad_norm: 5.1598 loss: 6.8064 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.4514 loss_aux: 2.3550 2023/02/17 12:11:13 - mmengine - INFO - Epoch(train) [1][ 900/1345] lr: 1.0000e-02 eta: 14:11:17 time: 0.1956 data_time: 0.0050 memory: 8326 grad_norm: 5.1347 loss: 6.9433 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.5464 loss_aux: 2.3969 2023/02/17 12:11:17 - mmengine - INFO - Epoch(train) [1][ 920/1345] lr: 1.0000e-02 eta: 14:06:48 time: 0.1940 data_time: 0.0057 memory: 8326 grad_norm: 5.1201 loss: 6.9404 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.5550 loss_aux: 2.3854 2023/02/17 12:11:21 - mmengine - INFO - Epoch(train) [1][ 940/1345] lr: 1.0000e-02 eta: 14:02:23 time: 0.1922 data_time: 0.0055 memory: 8326 grad_norm: 5.1081 loss: 6.7366 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 4.3551 loss_aux: 2.3815 2023/02/17 12:11:26 - mmengine - INFO - Epoch(train) [1][ 960/1345] lr: 1.0000e-02 eta: 14:03:27 time: 0.2681 data_time: 0.0077 memory: 8326 grad_norm: 5.2454 loss: 6.8561 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 4.4696 loss_aux: 2.3865 2023/02/17 12:11:30 - mmengine - INFO - Epoch(train) [1][ 980/1345] lr: 1.0000e-02 eta: 13:59:19 time: 0.1926 data_time: 0.0055 memory: 8326 grad_norm: 5.3215 loss: 6.6742 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 4.2990 loss_aux: 2.3752 2023/02/17 12:11:34 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:11:34 - mmengine - INFO - Epoch(train) [1][1000/1345] lr: 1.0000e-02 eta: 13:55:31 time: 0.1955 data_time: 0.0052 memory: 8326 grad_norm: 5.2074 loss: 6.8933 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.4995 loss_aux: 2.3938 2023/02/17 12:11:38 - mmengine - INFO - Epoch(train) [1][1020/1345] lr: 1.0000e-02 eta: 13:51:47 time: 0.1939 data_time: 0.0049 memory: 8326 grad_norm: 5.4150 loss: 6.6512 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.3368 loss_aux: 2.3143 2023/02/17 12:11:43 - mmengine - INFO - Epoch(train) [1][1040/1345] lr: 1.0000e-02 eta: 13:51:56 time: 0.2523 data_time: 0.0054 memory: 8326 grad_norm: 5.5329 loss: 6.6718 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.3392 loss_aux: 2.3326 2023/02/17 12:11:47 - mmengine - INFO - Epoch(train) [1][1060/1345] lr: 1.0000e-02 eta: 13:48:22 time: 0.1935 data_time: 0.0050 memory: 8326 grad_norm: 5.5439 loss: 6.9326 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.5234 loss_aux: 2.4092 2023/02/17 12:11:51 - mmengine - INFO - Epoch(train) [1][1080/1345] lr: 1.0000e-02 eta: 13:44:54 time: 0.1931 data_time: 0.0056 memory: 8326 grad_norm: 5.3871 loss: 6.8383 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.4617 loss_aux: 2.3766 2023/02/17 12:11:55 - mmengine - INFO - Epoch(train) [1][1100/1345] lr: 1.0000e-02 eta: 13:41:35 time: 0.1935 data_time: 0.0048 memory: 8326 grad_norm: 5.4888 loss: 6.6432 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.3222 loss_aux: 2.3210 2023/02/17 12:11:59 - mmengine - INFO - Epoch(train) [1][1120/1345] lr: 1.0000e-02 eta: 13:38:23 time: 0.1935 data_time: 0.0053 memory: 8326 grad_norm: 5.6696 loss: 6.6391 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 4.3145 loss_aux: 2.3246 2023/02/17 12:12:02 - mmengine - INFO - Epoch(train) [1][1140/1345] lr: 1.0000e-02 eta: 13:35:15 time: 0.1926 data_time: 0.0053 memory: 8326 grad_norm: 5.5423 loss: 6.6724 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 4.3608 loss_aux: 2.3117 2023/02/17 12:12:06 - mmengine - INFO - Epoch(train) [1][1160/1345] lr: 1.0000e-02 eta: 13:32:14 time: 0.1928 data_time: 0.0053 memory: 8326 grad_norm: 5.5205 loss: 6.8104 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.4459 loss_aux: 2.3645 2023/02/17 12:12:11 - mmengine - INFO - Epoch(train) [1][1180/1345] lr: 1.0000e-02 eta: 13:32:23 time: 0.2470 data_time: 0.0053 memory: 8326 grad_norm: 5.6058 loss: 6.7419 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.3749 loss_aux: 2.3670 2023/02/17 12:12:15 - mmengine - INFO - Epoch(train) [1][1200/1345] lr: 1.0000e-02 eta: 13:29:42 time: 0.1966 data_time: 0.0054 memory: 8326 grad_norm: 5.6119 loss: 6.6180 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 4.3181 loss_aux: 2.3000 2023/02/17 12:12:19 - mmengine - INFO - Epoch(train) [1][1220/1345] lr: 1.0000e-02 eta: 13:27:26 time: 0.2024 data_time: 0.0054 memory: 8326 grad_norm: 5.7022 loss: 6.5966 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 4.3054 loss_aux: 2.2912 2023/02/17 12:12:23 - mmengine - INFO - Epoch(train) [1][1240/1345] lr: 1.0000e-02 eta: 13:25:18 time: 0.2035 data_time: 0.0063 memory: 8326 grad_norm: 5.6774 loss: 6.5027 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.2101 loss_aux: 2.2926 2023/02/17 12:12:27 - mmengine - INFO - Epoch(train) [1][1260/1345] lr: 1.0000e-02 eta: 13:23:03 time: 0.2000 data_time: 0.0054 memory: 8326 grad_norm: 5.7719 loss: 6.6475 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.3003 loss_aux: 2.3472 2023/02/17 12:12:31 - mmengine - INFO - Epoch(train) [1][1280/1345] lr: 1.0000e-02 eta: 13:20:49 time: 0.1989 data_time: 0.0050 memory: 8326 grad_norm: 5.8361 loss: 6.4793 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 4.1897 loss_aux: 2.2895 2023/02/17 12:12:36 - mmengine - INFO - Epoch(train) [1][1300/1345] lr: 1.0000e-02 eta: 13:21:22 time: 0.2519 data_time: 0.0053 memory: 8326 grad_norm: 5.6930 loss: 6.6384 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.3025 loss_aux: 2.3359 2023/02/17 12:12:40 - mmengine - INFO - Epoch(train) [1][1320/1345] lr: 1.0000e-02 eta: 13:18:51 time: 0.1920 data_time: 0.0056 memory: 8326 grad_norm: 5.8555 loss: 6.3904 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 4.1347 loss_aux: 2.2556 2023/02/17 12:12:44 - mmengine - INFO - Epoch(train) [1][1340/1345] lr: 1.0000e-02 eta: 13:16:26 time: 0.1921 data_time: 0.0053 memory: 8326 grad_norm: 6.0826 loss: 6.6938 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.3338 loss_aux: 2.3600 2023/02/17 12:12:45 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:12:45 - mmengine - INFO - Epoch(train) [1][1345/1345] lr: 1.0000e-02 eta: 13:15:33 time: 0.1846 data_time: 0.0051 memory: 8326 grad_norm: 6.3179 loss: 6.7642 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.3869 loss_aux: 2.3773 2023/02/17 12:12:45 - mmengine - INFO - Saving checkpoint at 1 epochs 2023/02/17 12:12:53 - mmengine - INFO - Epoch(train) [2][ 20/1345] lr: 1.0000e-02 eta: 13:17:49 time: 0.2863 data_time: 0.0972 memory: 8326 grad_norm: 5.9294 loss: 6.5528 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.2365 loss_aux: 2.3163 2023/02/17 12:12:57 - mmengine - INFO - Epoch(train) [2][ 40/1345] lr: 1.0000e-02 eta: 13:15:24 time: 0.1903 data_time: 0.0048 memory: 8326 grad_norm: 5.8775 loss: 6.5365 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 4.2255 loss_aux: 2.3110 2023/02/17 12:13:01 - mmengine - INFO - Epoch(train) [2][ 60/1345] lr: 1.0000e-02 eta: 13:13:09 time: 0.1926 data_time: 0.0051 memory: 8326 grad_norm: 6.0434 loss: 6.4481 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.1636 loss_aux: 2.2845 2023/02/17 12:13:05 - mmengine - INFO - Epoch(train) [2][ 80/1345] lr: 1.0000e-02 eta: 13:10:54 time: 0.1912 data_time: 0.0050 memory: 8326 grad_norm: 6.1152 loss: 6.3326 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.0514 loss_aux: 2.2812 2023/02/17 12:13:09 - mmengine - INFO - Epoch(train) [2][ 100/1345] lr: 1.0000e-02 eta: 13:10:19 time: 0.2258 data_time: 0.0387 memory: 8326 grad_norm: 6.1616 loss: 6.4222 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.1535 loss_aux: 2.2687 2023/02/17 12:13:13 - mmengine - INFO - Epoch(train) [2][ 120/1345] lr: 1.0000e-02 eta: 13:08:11 time: 0.1918 data_time: 0.0043 memory: 8326 grad_norm: 6.0930 loss: 6.4697 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 4.1730 loss_aux: 2.2966 2023/02/17 12:13:17 - mmengine - INFO - Epoch(train) [2][ 140/1345] lr: 1.0000e-02 eta: 13:06:03 time: 0.1905 data_time: 0.0047 memory: 8326 grad_norm: 6.0517 loss: 6.4554 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 4.1572 loss_aux: 2.2982 2023/02/17 12:13:21 - mmengine - INFO - Epoch(train) [2][ 160/1345] lr: 1.0000e-02 eta: 13:03:59 time: 0.1907 data_time: 0.0056 memory: 8326 grad_norm: 6.1729 loss: 6.2858 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 4.0542 loss_aux: 2.2316 2023/02/17 12:13:24 - mmengine - INFO - Epoch(train) [2][ 180/1345] lr: 1.0000e-02 eta: 13:01:57 time: 0.1900 data_time: 0.0053 memory: 8326 grad_norm: 6.1253 loss: 6.9064 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 4.5118 loss_aux: 2.3946 2023/02/17 12:13:28 - mmengine - INFO - Epoch(train) [2][ 200/1345] lr: 1.0000e-02 eta: 12:59:58 time: 0.1904 data_time: 0.0054 memory: 8326 grad_norm: 5.8847 loss: 6.3515 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 4.0744 loss_aux: 2.2771 2023/02/17 12:13:33 - mmengine - INFO - Epoch(train) [2][ 220/1345] lr: 1.0000e-02 eta: 12:59:55 time: 0.2341 data_time: 0.0067 memory: 8326 grad_norm: 5.9398 loss: 6.3912 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 4.1473 loss_aux: 2.2439 2023/02/17 12:13:37 - mmengine - INFO - Epoch(train) [2][ 240/1345] lr: 1.0000e-02 eta: 12:58:02 time: 0.1909 data_time: 0.0053 memory: 8326 grad_norm: 6.1156 loss: 6.3849 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 4.0483 loss_aux: 2.3366 2023/02/17 12:13:41 - mmengine - INFO - Epoch(train) [2][ 260/1345] lr: 1.0000e-02 eta: 12:56:14 time: 0.1919 data_time: 0.0055 memory: 8326 grad_norm: 6.0520 loss: 6.3693 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 4.0888 loss_aux: 2.2805 2023/02/17 12:13:44 - mmengine - INFO - Epoch(train) [2][ 280/1345] lr: 1.0000e-02 eta: 12:54:27 time: 0.1912 data_time: 0.0055 memory: 8326 grad_norm: 6.0536 loss: 6.2394 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.9930 loss_aux: 2.2465 2023/02/17 12:13:48 - mmengine - INFO - Epoch(train) [2][ 300/1345] lr: 1.0000e-02 eta: 12:52:47 time: 0.1928 data_time: 0.0072 memory: 8326 grad_norm: 6.1343 loss: 6.4160 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.1443 loss_aux: 2.2718 2023/02/17 12:13:52 - mmengine - INFO - Epoch(train) [2][ 320/1345] lr: 1.0000e-02 eta: 12:51:04 time: 0.1908 data_time: 0.0055 memory: 8326 grad_norm: 6.1371 loss: 6.2786 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 4.0196 loss_aux: 2.2590 2023/02/17 12:13:56 - mmengine - INFO - Epoch(train) [2][ 340/1345] lr: 1.0000e-02 eta: 12:49:26 time: 0.1920 data_time: 0.0059 memory: 8326 grad_norm: 6.1129 loss: 6.2896 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.0545 loss_aux: 2.2351 2023/02/17 12:14:00 - mmengine - INFO - Epoch(train) [2][ 360/1345] lr: 1.0000e-02 eta: 12:47:47 time: 0.1906 data_time: 0.0054 memory: 8326 grad_norm: 6.1595 loss: 5.9993 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.7853 loss_aux: 2.2140 2023/02/17 12:14:05 - mmengine - INFO - Epoch(train) [2][ 380/1345] lr: 1.0000e-02 eta: 12:48:32 time: 0.2518 data_time: 0.0654 memory: 8326 grad_norm: 6.3131 loss: 6.4270 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.0977 loss_aux: 2.3293 2023/02/17 12:14:09 - mmengine - INFO - Epoch(train) [2][ 400/1345] lr: 1.0000e-02 eta: 12:46:58 time: 0.1912 data_time: 0.0032 memory: 8326 grad_norm: 6.0387 loss: 6.2388 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.9988 loss_aux: 2.2400 2023/02/17 12:14:12 - mmengine - INFO - Epoch(train) [2][ 420/1345] lr: 1.0000e-02 eta: 12:45:27 time: 0.1922 data_time: 0.0057 memory: 8326 grad_norm: 6.2258 loss: 6.4792 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 4.1516 loss_aux: 2.3276 2023/02/17 12:14:16 - mmengine - INFO - Epoch(train) [2][ 440/1345] lr: 1.0000e-02 eta: 12:43:56 time: 0.1909 data_time: 0.0051 memory: 8326 grad_norm: 6.2868 loss: 6.3029 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 4.0489 loss_aux: 2.2540 2023/02/17 12:14:21 - mmengine - INFO - Epoch(train) [2][ 460/1345] lr: 1.0000e-02 eta: 12:43:35 time: 0.2219 data_time: 0.0058 memory: 8326 grad_norm: 6.2536 loss: 6.1300 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.9001 loss_aux: 2.2299 2023/02/17 12:14:25 - mmengine - INFO - Epoch(train) [2][ 480/1345] lr: 1.0000e-02 eta: 12:42:10 time: 0.1926 data_time: 0.0054 memory: 8326 grad_norm: 6.2965 loss: 6.3170 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 4.0794 loss_aux: 2.2376 2023/02/17 12:14:28 - mmengine - INFO - Epoch(train) [2][ 500/1345] lr: 1.0000e-02 eta: 12:40:48 time: 0.1929 data_time: 0.0054 memory: 8326 grad_norm: 6.2563 loss: 6.2242 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.9882 loss_aux: 2.2360 2023/02/17 12:14:32 - mmengine - INFO - Epoch(train) [2][ 520/1345] lr: 1.0000e-02 eta: 12:39:23 time: 0.1909 data_time: 0.0054 memory: 8326 grad_norm: 6.4016 loss: 6.3565 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.0865 loss_aux: 2.2700 2023/02/17 12:14:36 - mmengine - INFO - Epoch(train) [2][ 540/1345] lr: 1.0000e-02 eta: 12:38:01 time: 0.1916 data_time: 0.0055 memory: 8326 grad_norm: 6.2856 loss: 6.0530 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.8424 loss_aux: 2.2106 2023/02/17 12:14:40 - mmengine - INFO - Epoch(train) [2][ 560/1345] lr: 1.0000e-02 eta: 12:36:39 time: 0.1906 data_time: 0.0055 memory: 8326 grad_norm: 6.3230 loss: 6.2358 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.9853 loss_aux: 2.2505 2023/02/17 12:14:44 - mmengine - INFO - Epoch(train) [2][ 580/1345] lr: 1.0000e-02 eta: 12:35:20 time: 0.1910 data_time: 0.0053 memory: 8326 grad_norm: 6.2368 loss: 6.3919 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 4.0949 loss_aux: 2.2970 2023/02/17 12:14:47 - mmengine - INFO - Epoch(train) [2][ 600/1345] lr: 1.0000e-02 eta: 12:33:59 time: 0.1898 data_time: 0.0053 memory: 8326 grad_norm: 6.2730 loss: 6.0895 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.8883 loss_aux: 2.2013 2023/02/17 12:14:51 - mmengine - INFO - Epoch(train) [2][ 620/1345] lr: 1.0000e-02 eta: 12:32:42 time: 0.1906 data_time: 0.0055 memory: 8326 grad_norm: 6.1832 loss: 6.0857 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.8790 loss_aux: 2.2067 2023/02/17 12:14:56 - mmengine - INFO - Epoch(train) [2][ 640/1345] lr: 1.0000e-02 eta: 12:33:42 time: 0.2585 data_time: 0.0726 memory: 8326 grad_norm: 6.1156 loss: 6.2455 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 4.0150 loss_aux: 2.2304 2023/02/17 12:14:59 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:15:00 - mmengine - INFO - Epoch(train) [2][ 660/1345] lr: 1.0000e-02 eta: 12:32:25 time: 0.1900 data_time: 0.0030 memory: 8326 grad_norm: 6.2384 loss: 6.0562 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.8448 loss_aux: 2.2114 2023/02/17 12:15:04 - mmengine - INFO - Epoch(train) [2][ 680/1345] lr: 1.0000e-02 eta: 12:31:14 time: 0.1920 data_time: 0.0045 memory: 8326 grad_norm: 6.2728 loss: 6.1843 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.9760 loss_aux: 2.2083 2023/02/17 12:15:08 - mmengine - INFO - Epoch(train) [2][ 700/1345] lr: 1.0000e-02 eta: 12:30:01 time: 0.1906 data_time: 0.0056 memory: 8326 grad_norm: 6.2566 loss: 6.1473 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.9462 loss_aux: 2.2011 2023/02/17 12:15:12 - mmengine - INFO - Epoch(train) [2][ 720/1345] lr: 1.0000e-02 eta: 12:28:50 time: 0.1914 data_time: 0.0053 memory: 8326 grad_norm: 6.1566 loss: 5.9524 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.8108 loss_aux: 2.1416 2023/02/17 12:15:16 - mmengine - INFO - Epoch(train) [2][ 740/1345] lr: 1.0000e-02 eta: 12:27:39 time: 0.1900 data_time: 0.0054 memory: 8326 grad_norm: 6.4309 loss: 6.0200 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.8362 loss_aux: 2.1838 2023/02/17 12:15:19 - mmengine - INFO - Epoch(train) [2][ 760/1345] lr: 1.0000e-02 eta: 12:26:29 time: 0.1901 data_time: 0.0055 memory: 8326 grad_norm: 6.3076 loss: 5.9189 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.7227 loss_aux: 2.1962 2023/02/17 12:15:23 - mmengine - INFO - Epoch(train) [2][ 780/1345] lr: 1.0000e-02 eta: 12:25:25 time: 0.1928 data_time: 0.0054 memory: 8326 grad_norm: 6.2944 loss: 5.9004 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.7298 loss_aux: 2.1705 2023/02/17 12:15:28 - mmengine - INFO - Epoch(train) [2][ 800/1345] lr: 1.0000e-02 eta: 12:25:56 time: 0.2431 data_time: 0.0053 memory: 8326 grad_norm: 6.4341 loss: 5.9376 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.7831 loss_aux: 2.1545 2023/02/17 12:15:32 - mmengine - INFO - Epoch(train) [2][ 820/1345] lr: 1.0000e-02 eta: 12:24:52 time: 0.1917 data_time: 0.0057 memory: 8326 grad_norm: 6.2385 loss: 6.1378 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.8821 loss_aux: 2.2557 2023/02/17 12:15:36 - mmengine - INFO - Epoch(train) [2][ 840/1345] lr: 1.0000e-02 eta: 12:23:48 time: 0.1918 data_time: 0.0053 memory: 8326 grad_norm: 6.2545 loss: 5.8059 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.6700 loss_aux: 2.1359 2023/02/17 12:15:40 - mmengine - INFO - Epoch(train) [2][ 860/1345] lr: 1.0000e-02 eta: 12:22:45 time: 0.1909 data_time: 0.0056 memory: 8326 grad_norm: 6.4463 loss: 5.8511 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.7304 loss_aux: 2.1206 2023/02/17 12:15:43 - mmengine - INFO - Epoch(train) [2][ 880/1345] lr: 1.0000e-02 eta: 12:21:42 time: 0.1907 data_time: 0.0057 memory: 8326 grad_norm: 6.3736 loss: 5.7969 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.6539 loss_aux: 2.1431 2023/02/17 12:15:48 - mmengine - INFO - Epoch(train) [2][ 900/1345] lr: 1.0000e-02 eta: 12:21:50 time: 0.2305 data_time: 0.0048 memory: 8326 grad_norm: 6.4236 loss: 6.0740 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 3.8995 loss_aux: 2.1745 2023/02/17 12:15:52 - mmengine - INFO - Epoch(train) [2][ 920/1345] lr: 1.0000e-02 eta: 12:20:50 time: 0.1915 data_time: 0.0055 memory: 8326 grad_norm: 6.2934 loss: 5.8486 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 3.6938 loss_aux: 2.1549 2023/02/17 12:15:56 - mmengine - INFO - Epoch(train) [2][ 940/1345] lr: 1.0000e-02 eta: 12:19:49 time: 0.1903 data_time: 0.0055 memory: 8326 grad_norm: 6.4929 loss: 6.0291 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.8614 loss_aux: 2.1677 2023/02/17 12:15:59 - mmengine - INFO - Epoch(train) [2][ 960/1345] lr: 1.0000e-02 eta: 12:18:53 time: 0.1925 data_time: 0.0054 memory: 8326 grad_norm: 6.4329 loss: 5.9194 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.7969 loss_aux: 2.1224 2023/02/17 12:16:03 - mmengine - INFO - Epoch(train) [2][ 980/1345] lr: 1.0000e-02 eta: 12:17:55 time: 0.1910 data_time: 0.0054 memory: 8326 grad_norm: 6.2981 loss: 5.8698 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.7188 loss_aux: 2.1510 2023/02/17 12:16:07 - mmengine - INFO - Epoch(train) [2][1000/1345] lr: 1.0000e-02 eta: 12:16:56 time: 0.1904 data_time: 0.0055 memory: 8326 grad_norm: 6.1722 loss: 5.9680 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.7685 loss_aux: 2.1994 2023/02/17 12:16:11 - mmengine - INFO - Epoch(train) [2][1020/1345] lr: 1.0000e-02 eta: 12:15:59 time: 0.1906 data_time: 0.0056 memory: 8326 grad_norm: 6.2600 loss: 6.0835 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.8636 loss_aux: 2.2199 2023/02/17 12:16:15 - mmengine - INFO - Epoch(train) [2][1040/1345] lr: 1.0000e-02 eta: 12:15:04 time: 0.1909 data_time: 0.0054 memory: 8326 grad_norm: 6.5219 loss: 6.0171 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.8543 loss_aux: 2.1628 2023/02/17 12:16:18 - mmengine - INFO - Epoch(train) [2][1060/1345] lr: 1.0000e-02 eta: 12:14:08 time: 0.1903 data_time: 0.0055 memory: 8326 grad_norm: 6.2759 loss: 6.0504 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.8946 loss_aux: 2.1558 2023/02/17 12:16:22 - mmengine - INFO - Epoch(train) [2][1080/1345] lr: 1.0000e-02 eta: 12:13:15 time: 0.1913 data_time: 0.0054 memory: 8326 grad_norm: 6.4107 loss: 5.7683 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.6597 loss_aux: 2.1087 2023/02/17 12:16:26 - mmengine - INFO - Epoch(train) [2][1100/1345] lr: 1.0000e-02 eta: 12:12:22 time: 0.1913 data_time: 0.0054 memory: 8326 grad_norm: 6.4337 loss: 6.1769 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.9642 loss_aux: 2.2127 2023/02/17 12:16:30 - mmengine - INFO - Epoch(train) [2][1120/1345] lr: 1.0000e-02 eta: 12:11:30 time: 0.1910 data_time: 0.0060 memory: 8326 grad_norm: 6.5566 loss: 6.0490 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 3.8300 loss_aux: 2.2190 2023/02/17 12:16:34 - mmengine - INFO - Epoch(train) [2][1140/1345] lr: 1.0000e-02 eta: 12:10:38 time: 0.1906 data_time: 0.0055 memory: 8326 grad_norm: 6.3590 loss: 5.9246 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.7840 loss_aux: 2.1406 2023/02/17 12:16:39 - mmengine - INFO - Epoch(train) [2][1160/1345] lr: 1.0000e-02 eta: 12:11:26 time: 0.2528 data_time: 0.0056 memory: 8326 grad_norm: 6.3178 loss: 5.8072 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.7034 loss_aux: 2.1038 2023/02/17 12:16:43 - mmengine - INFO - Epoch(train) [2][1180/1345] lr: 1.0000e-02 eta: 12:10:40 time: 0.1940 data_time: 0.0053 memory: 8326 grad_norm: 6.5033 loss: 5.8518 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.7307 loss_aux: 2.1211 2023/02/17 12:16:47 - mmengine - INFO - Epoch(train) [2][1200/1345] lr: 1.0000e-02 eta: 12:09:54 time: 0.1930 data_time: 0.0057 memory: 8326 grad_norm: 6.8079 loss: 5.6923 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.6013 loss_aux: 2.0909 2023/02/17 12:16:50 - mmengine - INFO - Epoch(train) [2][1220/1345] lr: 1.0000e-02 eta: 12:09:03 time: 0.1901 data_time: 0.0056 memory: 8326 grad_norm: 6.5076 loss: 5.8084 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.6846 loss_aux: 2.1238 2023/02/17 12:16:54 - mmengine - INFO - Epoch(train) [2][1240/1345] lr: 1.0000e-02 eta: 12:08:18 time: 0.1934 data_time: 0.0073 memory: 8326 grad_norm: 6.3044 loss: 5.7745 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.6242 loss_aux: 2.1503 2023/02/17 12:16:58 - mmengine - INFO - Epoch(train) [2][1260/1345] lr: 1.0000e-02 eta: 12:07:30 time: 0.1909 data_time: 0.0054 memory: 8326 grad_norm: 6.3856 loss: 5.5416 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.5187 loss_aux: 2.0229 2023/02/17 12:17:02 - mmengine - INFO - Epoch(train) [2][1280/1345] lr: 1.0000e-02 eta: 12:06:42 time: 0.1904 data_time: 0.0055 memory: 8326 grad_norm: 6.7379 loss: 6.2244 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.9535 loss_aux: 2.2709 2023/02/17 12:17:06 - mmengine - INFO - Epoch(train) [2][1300/1345] lr: 1.0000e-02 eta: 12:05:58 time: 0.1926 data_time: 0.0061 memory: 8326 grad_norm: 6.4571 loss: 5.9909 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.7807 loss_aux: 2.2101 2023/02/17 12:17:10 - mmengine - INFO - Epoch(train) [2][1320/1345] lr: 1.0000e-02 eta: 12:05:11 time: 0.1903 data_time: 0.0058 memory: 8326 grad_norm: 6.3393 loss: 5.5522 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.4510 loss_aux: 2.1013 2023/02/17 12:17:13 - mmengine - INFO - Epoch(train) [2][1340/1345] lr: 1.0000e-02 eta: 12:04:26 time: 0.1911 data_time: 0.0055 memory: 8326 grad_norm: 6.5102 loss: 6.0376 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.8422 loss_aux: 2.1954 2023/02/17 12:17:14 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:17:14 - mmengine - INFO - Epoch(train) [2][1345/1345] lr: 1.0000e-02 eta: 12:04:05 time: 0.1839 data_time: 0.0052 memory: 8326 grad_norm: 6.6753 loss: 5.9412 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.7619 loss_aux: 2.1793 2023/02/17 12:17:14 - mmengine - INFO - Saving checkpoint at 2 epochs 2023/02/17 12:17:22 - mmengine - INFO - Epoch(train) [3][ 20/1345] lr: 1.0000e-02 eta: 12:05:44 time: 0.2889 data_time: 0.1003 memory: 8326 grad_norm: 6.5779 loss: 5.8698 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.7381 loss_aux: 2.1317 2023/02/17 12:17:26 - mmengine - INFO - Epoch(train) [3][ 40/1345] lr: 1.0000e-02 eta: 12:05:01 time: 0.1922 data_time: 0.0057 memory: 8326 grad_norm: 6.4478 loss: 5.8161 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.6600 loss_aux: 2.1561 2023/02/17 12:17:30 - mmengine - INFO - Epoch(train) [3][ 60/1345] lr: 1.0000e-02 eta: 12:04:16 time: 0.1902 data_time: 0.0052 memory: 8326 grad_norm: 6.4898 loss: 5.6527 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 3.5187 loss_aux: 2.1341 2023/02/17 12:17:34 - mmengine - INFO - Epoch(train) [3][ 80/1345] lr: 1.0000e-02 eta: 12:03:33 time: 0.1914 data_time: 0.0054 memory: 8326 grad_norm: 6.6086 loss: 5.7782 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.6964 loss_aux: 2.0818 2023/02/17 12:17:38 - mmengine - INFO - Epoch(train) [3][ 100/1345] lr: 1.0000e-02 eta: 12:03:25 time: 0.2161 data_time: 0.0055 memory: 8326 grad_norm: 6.5557 loss: 5.8145 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.6926 loss_aux: 2.1219 2023/02/17 12:17:42 - mmengine - INFO - Epoch(train) [3][ 120/1345] lr: 1.0000e-02 eta: 12:02:43 time: 0.1915 data_time: 0.0057 memory: 8326 grad_norm: 6.5346 loss: 5.7581 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.6467 loss_aux: 2.1114 2023/02/17 12:17:46 - mmengine - INFO - Epoch(train) [3][ 140/1345] lr: 1.0000e-02 eta: 12:02:44 time: 0.2215 data_time: 0.0063 memory: 8326 grad_norm: 6.4737 loss: 5.7559 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.6698 loss_aux: 2.0861 2023/02/17 12:17:50 - mmengine - INFO - Epoch(train) [3][ 160/1345] lr: 1.0000e-02 eta: 12:02:02 time: 0.1911 data_time: 0.0053 memory: 8326 grad_norm: 6.6250 loss: 5.6643 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.6118 loss_aux: 2.0526 2023/02/17 12:17:54 - mmengine - INFO - Epoch(train) [3][ 180/1345] lr: 1.0000e-02 eta: 12:01:21 time: 0.1913 data_time: 0.0054 memory: 8326 grad_norm: 6.4455 loss: 6.0341 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.8452 loss_aux: 2.1889 2023/02/17 12:17:58 - mmengine - INFO - Epoch(train) [3][ 200/1345] lr: 1.0000e-02 eta: 12:00:39 time: 0.1905 data_time: 0.0055 memory: 8326 grad_norm: 6.5734 loss: 5.3523 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.3040 loss_aux: 2.0483 2023/02/17 12:18:02 - mmengine - INFO - Epoch(train) [3][ 220/1345] lr: 1.0000e-02 eta: 11:59:59 time: 0.1913 data_time: 0.0057 memory: 8326 grad_norm: 6.5322 loss: 5.7684 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 3.6338 loss_aux: 2.1347 2023/02/17 12:18:06 - mmengine - INFO - Epoch(train) [3][ 240/1345] lr: 1.0000e-02 eta: 11:59:19 time: 0.1907 data_time: 0.0056 memory: 8326 grad_norm: 6.5539 loss: 5.7712 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.6698 loss_aux: 2.1014 2023/02/17 12:18:09 - mmengine - INFO - Epoch(train) [3][ 260/1345] lr: 1.0000e-02 eta: 11:58:38 time: 0.1898 data_time: 0.0048 memory: 8326 grad_norm: 6.6451 loss: 5.5932 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.5722 loss_aux: 2.0211 2023/02/17 12:18:13 - mmengine - INFO - Epoch(train) [3][ 280/1345] lr: 1.0000e-02 eta: 11:57:59 time: 0.1909 data_time: 0.0056 memory: 8326 grad_norm: 6.6820 loss: 5.9448 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.7863 loss_aux: 2.1585 2023/02/17 12:18:17 - mmengine - INFO - Epoch(train) [3][ 300/1345] lr: 1.0000e-02 eta: 11:57:20 time: 0.1907 data_time: 0.0057 memory: 8326 grad_norm: 6.8143 loss: 6.2211 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.9846 loss_aux: 2.2364 2023/02/17 12:18:19 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:18:21 - mmengine - INFO - Epoch(train) [3][ 320/1345] lr: 1.0000e-02 eta: 11:56:42 time: 0.1914 data_time: 0.0052 memory: 8326 grad_norm: 6.4808 loss: 5.5994 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.5407 loss_aux: 2.0587 2023/02/17 12:18:25 - mmengine - INFO - Epoch(train) [3][ 340/1345] lr: 1.0000e-02 eta: 11:56:04 time: 0.1909 data_time: 0.0055 memory: 8326 grad_norm: 6.4729 loss: 5.3117 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.2962 loss_aux: 2.0155 2023/02/17 12:18:28 - mmengine - INFO - Epoch(train) [3][ 360/1345] lr: 1.0000e-02 eta: 11:55:27 time: 0.1910 data_time: 0.0057 memory: 8326 grad_norm: 6.5037 loss: 5.6066 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.4818 loss_aux: 2.1248 2023/02/17 12:18:32 - mmengine - INFO - Epoch(train) [3][ 380/1345] lr: 1.0000e-02 eta: 11:54:50 time: 0.1906 data_time: 0.0053 memory: 8326 grad_norm: 6.4217 loss: 5.5953 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.4923 loss_aux: 2.1030 2023/02/17 12:18:36 - mmengine - INFO - Epoch(train) [3][ 400/1345] lr: 1.0000e-02 eta: 11:54:13 time: 0.1906 data_time: 0.0053 memory: 8326 grad_norm: 6.7079 loss: 5.7607 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.6566 loss_aux: 2.1041 2023/02/17 12:18:40 - mmengine - INFO - Epoch(train) [3][ 420/1345] lr: 1.0000e-02 eta: 11:53:39 time: 0.1922 data_time: 0.0062 memory: 8326 grad_norm: 6.6652 loss: 5.6596 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.5766 loss_aux: 2.0831 2023/02/17 12:18:44 - mmengine - INFO - Epoch(train) [3][ 440/1345] lr: 1.0000e-02 eta: 11:53:39 time: 0.2190 data_time: 0.0052 memory: 8326 grad_norm: 6.7269 loss: 5.8455 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.7219 loss_aux: 2.1236 2023/02/17 12:18:48 - mmengine - INFO - Epoch(train) [3][ 460/1345] lr: 1.0000e-02 eta: 11:53:04 time: 0.1911 data_time: 0.0057 memory: 8326 grad_norm: 6.7556 loss: 5.6238 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.5616 loss_aux: 2.0622 2023/02/17 12:18:52 - mmengine - INFO - Epoch(train) [3][ 480/1345] lr: 1.0000e-02 eta: 11:52:46 time: 0.2044 data_time: 0.0057 memory: 8326 grad_norm: 6.7233 loss: 5.2818 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2362 loss_aux: 2.0456 2023/02/17 12:18:56 - mmengine - INFO - Epoch(train) [3][ 500/1345] lr: 1.0000e-02 eta: 11:52:11 time: 0.1911 data_time: 0.0052 memory: 8326 grad_norm: 6.6688 loss: 5.3253 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.2923 loss_aux: 2.0329 2023/02/17 12:19:00 - mmengine - INFO - Epoch(train) [3][ 520/1345] lr: 1.0000e-02 eta: 11:51:36 time: 0.1905 data_time: 0.0055 memory: 8326 grad_norm: 6.5317 loss: 5.6040 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.5068 loss_aux: 2.0972 2023/02/17 12:19:04 - mmengine - INFO - Epoch(train) [3][ 540/1345] lr: 1.0000e-02 eta: 11:51:04 time: 0.1925 data_time: 0.0056 memory: 8326 grad_norm: 6.6888 loss: 5.7318 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.6285 loss_aux: 2.1033 2023/02/17 12:19:07 - mmengine - INFO - Epoch(train) [3][ 560/1345] lr: 1.0000e-02 eta: 11:50:30 time: 0.1906 data_time: 0.0057 memory: 8326 grad_norm: 6.6309 loss: 5.6250 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.5395 loss_aux: 2.0856 2023/02/17 12:19:11 - mmengine - INFO - Epoch(train) [3][ 580/1345] lr: 1.0000e-02 eta: 11:49:58 time: 0.1917 data_time: 0.0056 memory: 8326 grad_norm: 6.5436 loss: 5.6029 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.4593 loss_aux: 2.1436 2023/02/17 12:19:15 - mmengine - INFO - Epoch(train) [3][ 600/1345] lr: 1.0000e-02 eta: 11:49:25 time: 0.1909 data_time: 0.0055 memory: 8326 grad_norm: 6.5774 loss: 5.3074 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.3426 loss_aux: 1.9648 2023/02/17 12:19:19 - mmengine - INFO - Epoch(train) [3][ 620/1345] lr: 1.0000e-02 eta: 11:48:53 time: 0.1914 data_time: 0.0053 memory: 8326 grad_norm: 6.6144 loss: 5.5300 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.4700 loss_aux: 2.0599 2023/02/17 12:19:23 - mmengine - INFO - Epoch(train) [3][ 640/1345] lr: 1.0000e-02 eta: 11:48:21 time: 0.1910 data_time: 0.0057 memory: 8326 grad_norm: 6.4333 loss: 5.7404 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.6702 loss_aux: 2.0702 2023/02/17 12:19:27 - mmengine - INFO - Epoch(train) [3][ 660/1345] lr: 1.0000e-02 eta: 11:47:49 time: 0.1910 data_time: 0.0054 memory: 8326 grad_norm: 6.4441 loss: 5.6418 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.5373 loss_aux: 2.1045 2023/02/17 12:19:30 - mmengine - INFO - Epoch(train) [3][ 680/1345] lr: 1.0000e-02 eta: 11:47:18 time: 0.1914 data_time: 0.0055 memory: 8326 grad_norm: 6.5207 loss: 5.7579 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.6376 loss_aux: 2.1202 2023/02/17 12:19:34 - mmengine - INFO - Epoch(train) [3][ 700/1345] lr: 1.0000e-02 eta: 11:46:47 time: 0.1907 data_time: 0.0058 memory: 8326 grad_norm: 6.3992 loss: 5.2986 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.3415 loss_aux: 1.9571 2023/02/17 12:19:38 - mmengine - INFO - Epoch(train) [3][ 720/1345] lr: 1.0000e-02 eta: 11:46:16 time: 0.1906 data_time: 0.0051 memory: 8326 grad_norm: 6.5112 loss: 5.4845 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.4733 loss_aux: 2.0112 2023/02/17 12:19:42 - mmengine - INFO - Epoch(train) [3][ 740/1345] lr: 1.0000e-02 eta: 11:45:46 time: 0.1922 data_time: 0.0055 memory: 8326 grad_norm: 6.9237 loss: 5.5019 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.4322 loss_aux: 2.0697 2023/02/17 12:19:46 - mmengine - INFO - Epoch(train) [3][ 760/1345] lr: 1.0000e-02 eta: 11:45:18 time: 0.1928 data_time: 0.0074 memory: 8326 grad_norm: 6.6519 loss: 5.3085 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.2882 loss_aux: 2.0203 2023/02/17 12:19:50 - mmengine - INFO - Epoch(train) [3][ 780/1345] lr: 1.0000e-02 eta: 11:44:50 time: 0.1919 data_time: 0.0054 memory: 8326 grad_norm: 6.5633 loss: 5.4042 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 3.3729 loss_aux: 2.0313 2023/02/17 12:19:54 - mmengine - INFO - Epoch(train) [3][ 800/1345] lr: 1.0000e-02 eta: 11:45:11 time: 0.2356 data_time: 0.0491 memory: 8326 grad_norm: 6.4894 loss: 5.3694 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 3.3453 loss_aux: 2.0241 2023/02/17 12:19:58 - mmengine - INFO - Epoch(train) [3][ 820/1345] lr: 1.0000e-02 eta: 11:44:40 time: 0.1898 data_time: 0.0030 memory: 8326 grad_norm: 6.7078 loss: 5.7434 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.5953 loss_aux: 2.1481 2023/02/17 12:20:02 - mmengine - INFO - Epoch(train) [3][ 840/1345] lr: 1.0000e-02 eta: 11:44:10 time: 0.1907 data_time: 0.0054 memory: 8326 grad_norm: 6.7225 loss: 5.6014 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.5205 loss_aux: 2.0808 2023/02/17 12:20:06 - mmengine - INFO - Epoch(train) [3][ 860/1345] lr: 1.0000e-02 eta: 11:43:41 time: 0.1913 data_time: 0.0062 memory: 8326 grad_norm: 6.6303 loss: 5.7239 top1_acc: 0.0000 top5_acc: 0.7500 loss_cls: 3.6344 loss_aux: 2.0895 2023/02/17 12:20:10 - mmengine - INFO - Epoch(train) [3][ 880/1345] lr: 1.0000e-02 eta: 11:43:46 time: 0.2211 data_time: 0.0055 memory: 8326 grad_norm: 6.6085 loss: 5.4248 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.3863 loss_aux: 2.0385 2023/02/17 12:20:14 - mmengine - INFO - Epoch(train) [3][ 900/1345] lr: 1.0000e-02 eta: 11:43:17 time: 0.1907 data_time: 0.0059 memory: 8326 grad_norm: 6.6128 loss: 5.6283 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.5230 loss_aux: 2.1053 2023/02/17 12:20:18 - mmengine - INFO - Epoch(train) [3][ 920/1345] lr: 1.0000e-02 eta: 11:42:49 time: 0.1911 data_time: 0.0050 memory: 8326 grad_norm: 6.4672 loss: 5.5020 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.4810 loss_aux: 2.0210 2023/02/17 12:20:22 - mmengine - INFO - Epoch(train) [3][ 940/1345] lr: 1.0000e-02 eta: 11:42:21 time: 0.1915 data_time: 0.0058 memory: 8326 grad_norm: 6.6269 loss: 5.7189 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.6074 loss_aux: 2.1115 2023/02/17 12:20:25 - mmengine - INFO - Epoch(train) [3][ 960/1345] lr: 1.0000e-02 eta: 11:41:54 time: 0.1912 data_time: 0.0053 memory: 8326 grad_norm: 6.5932 loss: 5.3735 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.3752 loss_aux: 1.9983 2023/02/17 12:20:29 - mmengine - INFO - Epoch(train) [3][ 980/1345] lr: 1.0000e-02 eta: 11:41:26 time: 0.1911 data_time: 0.0055 memory: 8326 grad_norm: 6.6192 loss: 5.5795 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.5257 loss_aux: 2.0538 2023/02/17 12:20:33 - mmengine - INFO - Epoch(train) [3][1000/1345] lr: 1.0000e-02 eta: 11:41:00 time: 0.1922 data_time: 0.0059 memory: 8326 grad_norm: 6.8441 loss: 5.1376 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1830 loss_aux: 1.9546 2023/02/17 12:20:37 - mmengine - INFO - Epoch(train) [3][1020/1345] lr: 1.0000e-02 eta: 11:40:35 time: 0.1921 data_time: 0.0049 memory: 8326 grad_norm: 6.6297 loss: 5.7001 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.5700 loss_aux: 2.1301 2023/02/17 12:20:41 - mmengine - INFO - Epoch(train) [3][1040/1345] lr: 1.0000e-02 eta: 11:40:08 time: 0.1914 data_time: 0.0055 memory: 8326 grad_norm: 6.7555 loss: 5.6624 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.5601 loss_aux: 2.1023 2023/02/17 12:20:45 - mmengine - INFO - Epoch(train) [3][1060/1345] lr: 1.0000e-02 eta: 11:39:42 time: 0.1913 data_time: 0.0054 memory: 8326 grad_norm: 6.6117 loss: 5.3371 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.3413 loss_aux: 1.9958 2023/02/17 12:20:48 - mmengine - INFO - Epoch(train) [3][1080/1345] lr: 1.0000e-02 eta: 11:39:16 time: 0.1913 data_time: 0.0054 memory: 8326 grad_norm: 6.9176 loss: 5.6421 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.6091 loss_aux: 2.0330 2023/02/17 12:20:52 - mmengine - INFO - Epoch(train) [3][1100/1345] lr: 1.0000e-02 eta: 11:38:49 time: 0.1904 data_time: 0.0055 memory: 8326 grad_norm: 6.4946 loss: 5.7305 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.6896 loss_aux: 2.0408 2023/02/17 12:20:57 - mmengine - INFO - Epoch(train) [3][1120/1345] lr: 1.0000e-02 eta: 11:38:55 time: 0.2218 data_time: 0.0054 memory: 8326 grad_norm: 6.6352 loss: 5.0581 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.1317 loss_aux: 1.9265 2023/02/17 12:21:01 - mmengine - INFO - Epoch(train) [3][1140/1345] lr: 1.0000e-02 eta: 11:38:29 time: 0.1906 data_time: 0.0054 memory: 8326 grad_norm: 6.7838 loss: 5.6453 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.5263 loss_aux: 2.1190 2023/02/17 12:21:04 - mmengine - INFO - Epoch(train) [3][1160/1345] lr: 1.0000e-02 eta: 11:38:04 time: 0.1916 data_time: 0.0054 memory: 8326 grad_norm: 6.7268 loss: 5.2220 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.2597 loss_aux: 1.9623 2023/02/17 12:21:08 - mmengine - INFO - Epoch(train) [3][1180/1345] lr: 1.0000e-02 eta: 11:37:39 time: 0.1912 data_time: 0.0056 memory: 8326 grad_norm: 6.6274 loss: 5.7551 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.6705 loss_aux: 2.0845 2023/02/17 12:21:12 - mmengine - INFO - Epoch(train) [3][1200/1345] lr: 1.0000e-02 eta: 11:37:14 time: 0.1911 data_time: 0.0056 memory: 8326 grad_norm: 6.5783 loss: 5.4370 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.3475 loss_aux: 2.0895 2023/02/17 12:21:16 - mmengine - INFO - Epoch(train) [3][1220/1345] lr: 1.0000e-02 eta: 11:36:49 time: 0.1909 data_time: 0.0054 memory: 8326 grad_norm: 6.7092 loss: 5.2029 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.1940 loss_aux: 2.0090 2023/02/17 12:21:20 - mmengine - INFO - Epoch(train) [3][1240/1345] lr: 1.0000e-02 eta: 11:37:00 time: 0.2264 data_time: 0.0397 memory: 8326 grad_norm: 6.7921 loss: 5.6158 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.5336 loss_aux: 2.0822 2023/02/17 12:21:24 - mmengine - INFO - Epoch(train) [3][1260/1345] lr: 1.0000e-02 eta: 11:36:36 time: 0.1913 data_time: 0.0038 memory: 8326 grad_norm: 6.8119 loss: 5.3470 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.3396 loss_aux: 2.0074 2023/02/17 12:21:28 - mmengine - INFO - Epoch(train) [3][1280/1345] lr: 1.0000e-02 eta: 11:36:13 time: 0.1931 data_time: 0.0056 memory: 8326 grad_norm: 6.6169 loss: 5.4279 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.4173 loss_aux: 2.0107 2023/02/17 12:21:32 - mmengine - INFO - Epoch(train) [3][1300/1345] lr: 1.0000e-02 eta: 11:35:49 time: 0.1910 data_time: 0.0058 memory: 8326 grad_norm: 6.4661 loss: 5.3873 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.3800 loss_aux: 2.0073 2023/02/17 12:21:34 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:21:36 - mmengine - INFO - Epoch(train) [3][1320/1345] lr: 1.0000e-02 eta: 11:35:25 time: 0.1911 data_time: 0.0053 memory: 8326 grad_norm: 6.6051 loss: 5.5233 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.4756 loss_aux: 2.0477 2023/02/17 12:21:40 - mmengine - INFO - Epoch(train) [3][1340/1345] lr: 1.0000e-02 eta: 11:35:03 time: 0.1928 data_time: 0.0052 memory: 8326 grad_norm: 6.7010 loss: 5.7849 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.6717 loss_aux: 2.1131 2023/02/17 12:21:40 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:21:40 - mmengine - INFO - Epoch(train) [3][1345/1345] lr: 1.0000e-02 eta: 11:34:51 time: 0.1845 data_time: 0.0050 memory: 8326 grad_norm: 6.7203 loss: 5.7342 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.6663 loss_aux: 2.0680 2023/02/17 12:21:40 - mmengine - INFO - Saving checkpoint at 3 epochs 2023/02/17 12:21:48 - mmengine - INFO - Epoch(train) [4][ 20/1345] lr: 1.0000e-02 eta: 11:35:38 time: 0.2628 data_time: 0.0738 memory: 8326 grad_norm: 6.7185 loss: 5.3478 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.3928 loss_aux: 1.9551 2023/02/17 12:21:52 - mmengine - INFO - Epoch(train) [4][ 40/1345] lr: 1.0000e-02 eta: 11:35:12 time: 0.1893 data_time: 0.0046 memory: 8326 grad_norm: 6.3507 loss: 5.6050 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.5165 loss_aux: 2.0885 2023/02/17 12:21:55 - mmengine - INFO - Epoch(train) [4][ 60/1345] lr: 1.0000e-02 eta: 11:34:48 time: 0.1901 data_time: 0.0048 memory: 8326 grad_norm: 6.6917 loss: 5.3395 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.3865 loss_aux: 1.9530 2023/02/17 12:21:59 - mmengine - INFO - Epoch(train) [4][ 80/1345] lr: 1.0000e-02 eta: 11:34:33 time: 0.1994 data_time: 0.0073 memory: 8326 grad_norm: 6.7253 loss: 5.4990 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.4561 loss_aux: 2.0429 2023/02/17 12:22:03 - mmengine - INFO - Epoch(train) [4][ 100/1345] lr: 1.0000e-02 eta: 11:34:11 time: 0.1930 data_time: 0.0057 memory: 8326 grad_norm: 6.7289 loss: 5.1705 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1977 loss_aux: 1.9728 2023/02/17 12:22:07 - mmengine - INFO - Epoch(train) [4][ 120/1345] lr: 1.0000e-02 eta: 11:33:48 time: 0.1906 data_time: 0.0055 memory: 8326 grad_norm: 6.8675 loss: 5.3708 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 3.3562 loss_aux: 2.0146 2023/02/17 12:22:11 - mmengine - INFO - Epoch(train) [4][ 140/1345] lr: 1.0000e-02 eta: 11:33:24 time: 0.1904 data_time: 0.0051 memory: 8326 grad_norm: 6.6644 loss: 5.4588 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.4278 loss_aux: 2.0311 2023/02/17 12:22:15 - mmengine - INFO - Epoch(train) [4][ 160/1345] lr: 1.0000e-02 eta: 11:33:03 time: 0.1921 data_time: 0.0054 memory: 8326 grad_norm: 6.6213 loss: 5.1730 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.2296 loss_aux: 1.9434 2023/02/17 12:22:19 - mmengine - INFO - Epoch(train) [4][ 180/1345] lr: 1.0000e-02 eta: 11:32:49 time: 0.2001 data_time: 0.0060 memory: 8326 grad_norm: 6.5398 loss: 5.2032 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.2544 loss_aux: 1.9488 2023/02/17 12:22:23 - mmengine - INFO - Epoch(train) [4][ 200/1345] lr: 1.0000e-02 eta: 11:32:30 time: 0.1944 data_time: 0.0058 memory: 8326 grad_norm: 6.4749 loss: 5.2726 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.2917 loss_aux: 1.9809 2023/02/17 12:22:27 - mmengine - INFO - Epoch(train) [4][ 220/1345] lr: 1.0000e-02 eta: 11:32:09 time: 0.1925 data_time: 0.0045 memory: 8326 grad_norm: 6.7006 loss: 5.3540 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.3810 loss_aux: 1.9729 2023/02/17 12:22:30 - mmengine - INFO - Epoch(train) [4][ 240/1345] lr: 1.0000e-02 eta: 11:31:52 time: 0.1963 data_time: 0.0105 memory: 8326 grad_norm: 6.8670 loss: 5.2344 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.2598 loss_aux: 1.9746 2023/02/17 12:22:34 - mmengine - INFO - Epoch(train) [4][ 260/1345] lr: 1.0000e-02 eta: 11:31:30 time: 0.1911 data_time: 0.0036 memory: 8326 grad_norm: 6.8523 loss: 5.2835 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.3314 loss_aux: 1.9520 2023/02/17 12:22:38 - mmengine - INFO - Epoch(train) [4][ 280/1345] lr: 1.0000e-02 eta: 11:31:10 time: 0.1923 data_time: 0.0066 memory: 8326 grad_norm: 6.5562 loss: 5.2412 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.2471 loss_aux: 1.9942 2023/02/17 12:22:42 - mmengine - INFO - Epoch(train) [4][ 300/1345] lr: 1.0000e-02 eta: 11:30:49 time: 0.1917 data_time: 0.0059 memory: 8326 grad_norm: 6.8182 loss: 5.4241 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.4420 loss_aux: 1.9821 2023/02/17 12:22:46 - mmengine - INFO - Epoch(train) [4][ 320/1345] lr: 1.0000e-02 eta: 11:30:29 time: 0.1929 data_time: 0.0071 memory: 8326 grad_norm: 6.5596 loss: 5.1770 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.2506 loss_aux: 1.9264 2023/02/17 12:22:50 - mmengine - INFO - Epoch(train) [4][ 340/1345] lr: 1.0000e-02 eta: 11:30:07 time: 0.1900 data_time: 0.0058 memory: 8326 grad_norm: 6.4783 loss: 5.2870 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.3412 loss_aux: 1.9457 2023/02/17 12:22:53 - mmengine - INFO - Epoch(train) [4][ 360/1345] lr: 1.0000e-02 eta: 11:29:46 time: 0.1911 data_time: 0.0057 memory: 8326 grad_norm: 6.6360 loss: 5.1976 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.1858 loss_aux: 2.0118 2023/02/17 12:22:57 - mmengine - INFO - Epoch(train) [4][ 380/1345] lr: 1.0000e-02 eta: 11:29:25 time: 0.1916 data_time: 0.0063 memory: 8326 grad_norm: 6.7466 loss: 5.2745 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.3373 loss_aux: 1.9372 2023/02/17 12:23:01 - mmengine - INFO - Epoch(train) [4][ 400/1345] lr: 1.0000e-02 eta: 11:29:05 time: 0.1917 data_time: 0.0059 memory: 8326 grad_norm: 6.5227 loss: 5.0212 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.1224 loss_aux: 1.8988 2023/02/17 12:23:05 - mmengine - INFO - Epoch(train) [4][ 420/1345] lr: 1.0000e-02 eta: 11:29:07 time: 0.2167 data_time: 0.0296 memory: 8326 grad_norm: 6.4999 loss: 5.1480 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2043 loss_aux: 1.9437 2023/02/17 12:23:09 - mmengine - INFO - Epoch(train) [4][ 440/1345] lr: 1.0000e-02 eta: 11:28:47 time: 0.1917 data_time: 0.0035 memory: 8326 grad_norm: 6.7199 loss: 5.1380 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.1703 loss_aux: 1.9677 2023/02/17 12:23:13 - mmengine - INFO - Epoch(train) [4][ 460/1345] lr: 1.0000e-02 eta: 11:28:28 time: 0.1921 data_time: 0.0046 memory: 8326 grad_norm: 6.8996 loss: 5.2989 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.3139 loss_aux: 1.9850 2023/02/17 12:23:17 - mmengine - INFO - Epoch(train) [4][ 480/1345] lr: 1.0000e-02 eta: 11:28:08 time: 0.1913 data_time: 0.0055 memory: 8326 grad_norm: 6.7089 loss: 4.9587 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.0642 loss_aux: 1.8945 2023/02/17 12:23:21 - mmengine - INFO - Epoch(train) [4][ 500/1345] lr: 1.0000e-02 eta: 11:27:48 time: 0.1912 data_time: 0.0056 memory: 8326 grad_norm: 6.6876 loss: 5.4116 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.3914 loss_aux: 2.0201 2023/02/17 12:23:25 - mmengine - INFO - Epoch(train) [4][ 520/1345] lr: 1.0000e-02 eta: 11:27:28 time: 0.1906 data_time: 0.0053 memory: 8326 grad_norm: 6.6733 loss: 5.1618 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 3.2170 loss_aux: 1.9448 2023/02/17 12:23:28 - mmengine - INFO - Epoch(train) [4][ 540/1345] lr: 1.0000e-02 eta: 11:27:08 time: 0.1919 data_time: 0.0059 memory: 8326 grad_norm: 6.8421 loss: 5.1894 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.2232 loss_aux: 1.9663 2023/02/17 12:23:32 - mmengine - INFO - Epoch(train) [4][ 560/1345] lr: 1.0000e-02 eta: 11:26:48 time: 0.1902 data_time: 0.0052 memory: 8326 grad_norm: 6.6661 loss: 5.3005 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.2973 loss_aux: 2.0032 2023/02/17 12:23:36 - mmengine - INFO - Epoch(train) [4][ 580/1345] lr: 1.0000e-02 eta: 11:26:28 time: 0.1905 data_time: 0.0057 memory: 8326 grad_norm: 6.5931 loss: 5.3226 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.3259 loss_aux: 1.9967 2023/02/17 12:23:40 - mmengine - INFO - Epoch(train) [4][ 600/1345] lr: 1.0000e-02 eta: 11:26:09 time: 0.1909 data_time: 0.0054 memory: 8326 grad_norm: 6.8921 loss: 5.3984 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.3555 loss_aux: 2.0429 2023/02/17 12:23:44 - mmengine - INFO - Epoch(train) [4][ 620/1345] lr: 1.0000e-02 eta: 11:25:50 time: 0.1913 data_time: 0.0056 memory: 8326 grad_norm: 6.8379 loss: 5.2596 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2564 loss_aux: 2.0032 2023/02/17 12:23:48 - mmengine - INFO - Epoch(train) [4][ 640/1345] lr: 1.0000e-02 eta: 11:25:31 time: 0.1916 data_time: 0.0055 memory: 8326 grad_norm: 6.6376 loss: 5.2415 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.2647 loss_aux: 1.9768 2023/02/17 12:23:51 - mmengine - INFO - Epoch(train) [4][ 660/1345] lr: 1.0000e-02 eta: 11:25:11 time: 0.1906 data_time: 0.0054 memory: 8326 grad_norm: 6.6464 loss: 5.2553 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.2787 loss_aux: 1.9766 2023/02/17 12:23:55 - mmengine - INFO - Epoch(train) [4][ 680/1345] lr: 1.0000e-02 eta: 11:24:52 time: 0.1909 data_time: 0.0057 memory: 8326 grad_norm: 6.7458 loss: 5.0846 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 3.1391 loss_aux: 1.9456 2023/02/17 12:23:59 - mmengine - INFO - Epoch(train) [4][ 700/1345] lr: 1.0000e-02 eta: 11:24:34 time: 0.1914 data_time: 0.0055 memory: 8326 grad_norm: 6.8755 loss: 5.1289 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.2101 loss_aux: 1.9188 2023/02/17 12:24:03 - mmengine - INFO - Epoch(train) [4][ 720/1345] lr: 1.0000e-02 eta: 11:24:15 time: 0.1910 data_time: 0.0056 memory: 8326 grad_norm: 6.8692 loss: 5.1970 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2027 loss_aux: 1.9943 2023/02/17 12:24:07 - mmengine - INFO - Epoch(train) [4][ 740/1345] lr: 1.0000e-02 eta: 11:24:22 time: 0.2220 data_time: 0.0055 memory: 8326 grad_norm: 6.6686 loss: 5.3440 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.3560 loss_aux: 1.9880 2023/02/17 12:24:11 - mmengine - INFO - Epoch(train) [4][ 760/1345] lr: 1.0000e-02 eta: 11:24:07 time: 0.1953 data_time: 0.0057 memory: 8326 grad_norm: 6.6763 loss: 5.1022 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 3.1819 loss_aux: 1.9203 2023/02/17 12:24:15 - mmengine - INFO - Epoch(train) [4][ 780/1345] lr: 1.0000e-02 eta: 11:23:49 time: 0.1906 data_time: 0.0053 memory: 8326 grad_norm: 6.7107 loss: 5.3775 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.4358 loss_aux: 1.9417 2023/02/17 12:24:19 - mmengine - INFO - Epoch(train) [4][ 800/1345] lr: 1.0000e-02 eta: 11:23:30 time: 0.1903 data_time: 0.0056 memory: 8326 grad_norm: 6.6720 loss: 4.8581 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0057 loss_aux: 1.8524 2023/02/17 12:24:23 - mmengine - INFO - Epoch(train) [4][ 820/1345] lr: 1.0000e-02 eta: 11:23:11 time: 0.1905 data_time: 0.0055 memory: 8326 grad_norm: 6.7231 loss: 5.4154 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.3862 loss_aux: 2.0292 2023/02/17 12:24:26 - mmengine - INFO - Epoch(train) [4][ 840/1345] lr: 1.0000e-02 eta: 11:22:54 time: 0.1917 data_time: 0.0057 memory: 8326 grad_norm: 6.7314 loss: 5.2827 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.3317 loss_aux: 1.9510 2023/02/17 12:24:30 - mmengine - INFO - Epoch(train) [4][ 860/1345] lr: 1.0000e-02 eta: 11:22:36 time: 0.1911 data_time: 0.0058 memory: 8326 grad_norm: 6.5408 loss: 4.9597 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0320 loss_aux: 1.9276 2023/02/17 12:24:34 - mmengine - INFO - Epoch(train) [4][ 880/1345] lr: 1.0000e-02 eta: 11:22:23 time: 0.1975 data_time: 0.0053 memory: 8326 grad_norm: 6.7644 loss: 4.9297 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.0139 loss_aux: 1.9158 2023/02/17 12:24:38 - mmengine - INFO - Epoch(train) [4][ 900/1345] lr: 1.0000e-02 eta: 11:22:07 time: 0.1926 data_time: 0.0059 memory: 8326 grad_norm: 6.7296 loss: 5.2027 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.2442 loss_aux: 1.9585 2023/02/17 12:24:42 - mmengine - INFO - Epoch(train) [4][ 920/1345] lr: 1.0000e-02 eta: 11:21:49 time: 0.1907 data_time: 0.0056 memory: 8326 grad_norm: 6.6490 loss: 4.8499 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.9755 loss_aux: 1.8744 2023/02/17 12:24:46 - mmengine - INFO - Epoch(train) [4][ 940/1345] lr: 1.0000e-02 eta: 11:21:32 time: 0.1913 data_time: 0.0055 memory: 8326 grad_norm: 6.7557 loss: 4.9225 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0224 loss_aux: 1.9001 2023/02/17 12:24:50 - mmengine - INFO - Epoch(train) [4][ 960/1345] lr: 1.0000e-02 eta: 11:21:15 time: 0.1912 data_time: 0.0058 memory: 8326 grad_norm: 6.7468 loss: 5.0653 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.0940 loss_aux: 1.9713 2023/02/17 12:24:50 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:24:53 - mmengine - INFO - Epoch(train) [4][ 980/1345] lr: 1.0000e-02 eta: 11:20:58 time: 0.1917 data_time: 0.0060 memory: 8326 grad_norm: 6.5760 loss: 4.9744 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0258 loss_aux: 1.9487 2023/02/17 12:24:57 - mmengine - INFO - Epoch(train) [4][1000/1345] lr: 1.0000e-02 eta: 11:20:41 time: 0.1914 data_time: 0.0051 memory: 8326 grad_norm: 6.6180 loss: 5.2711 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.2955 loss_aux: 1.9757 2023/02/17 12:25:01 - mmengine - INFO - Epoch(train) [4][1020/1345] lr: 1.0000e-02 eta: 11:20:24 time: 0.1912 data_time: 0.0056 memory: 8326 grad_norm: 6.6167 loss: 5.0132 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.0556 loss_aux: 1.9576 2023/02/17 12:25:05 - mmengine - INFO - Epoch(train) [4][1040/1345] lr: 1.0000e-02 eta: 11:20:23 time: 0.2110 data_time: 0.0255 memory: 8326 grad_norm: 6.7381 loss: 5.2907 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.2960 loss_aux: 1.9947 2023/02/17 12:25:09 - mmengine - INFO - Epoch(train) [4][1060/1345] lr: 1.0000e-02 eta: 11:20:07 time: 0.1930 data_time: 0.0057 memory: 8326 grad_norm: 6.6401 loss: 5.0101 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0826 loss_aux: 1.9274 2023/02/17 12:25:13 - mmengine - INFO - Epoch(train) [4][1080/1345] lr: 1.0000e-02 eta: 11:19:50 time: 0.1905 data_time: 0.0055 memory: 8326 grad_norm: 6.5697 loss: 5.1272 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.1549 loss_aux: 1.9722 2023/02/17 12:25:17 - mmengine - INFO - Epoch(train) [4][1100/1345] lr: 1.0000e-02 eta: 11:19:34 time: 0.1919 data_time: 0.0059 memory: 8326 grad_norm: 6.4629 loss: 5.3309 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.3681 loss_aux: 1.9628 2023/02/17 12:25:21 - mmengine - INFO - Epoch(train) [4][1120/1345] lr: 1.0000e-02 eta: 11:19:18 time: 0.1917 data_time: 0.0052 memory: 8326 grad_norm: 6.7446 loss: 5.1391 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.1897 loss_aux: 1.9494 2023/02/17 12:25:24 - mmengine - INFO - Epoch(train) [4][1140/1345] lr: 1.0000e-02 eta: 11:19:05 time: 0.1956 data_time: 0.0055 memory: 8326 grad_norm: 6.6537 loss: 5.4631 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.4574 loss_aux: 2.0057 2023/02/17 12:25:28 - mmengine - INFO - Epoch(train) [4][1160/1345] lr: 1.0000e-02 eta: 11:18:49 time: 0.1923 data_time: 0.0056 memory: 8326 grad_norm: 6.6808 loss: 5.0783 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1896 loss_aux: 1.8888 2023/02/17 12:25:32 - mmengine - INFO - Epoch(train) [4][1180/1345] lr: 1.0000e-02 eta: 11:18:34 time: 0.1924 data_time: 0.0057 memory: 8326 grad_norm: 6.5269 loss: 4.9455 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0212 loss_aux: 1.9242 2023/02/17 12:25:36 - mmengine - INFO - Epoch(train) [4][1200/1345] lr: 1.0000e-02 eta: 11:18:19 time: 0.1924 data_time: 0.0054 memory: 8326 grad_norm: 6.6323 loss: 5.2794 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.3578 loss_aux: 1.9216 2023/02/17 12:25:40 - mmengine - INFO - Epoch(train) [4][1220/1345] lr: 1.0000e-02 eta: 11:18:02 time: 0.1909 data_time: 0.0058 memory: 8326 grad_norm: 6.6568 loss: 5.2528 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.3156 loss_aux: 1.9372 2023/02/17 12:25:44 - mmengine - INFO - Epoch(train) [4][1240/1345] lr: 1.0000e-02 eta: 11:17:49 time: 0.1946 data_time: 0.0056 memory: 8326 grad_norm: 6.7037 loss: 5.5970 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.5141 loss_aux: 2.0830 2023/02/17 12:25:48 - mmengine - INFO - Epoch(train) [4][1260/1345] lr: 1.0000e-02 eta: 11:17:33 time: 0.1916 data_time: 0.0056 memory: 8326 grad_norm: 6.7433 loss: 4.7755 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9356 loss_aux: 1.8399 2023/02/17 12:25:51 - mmengine - INFO - Epoch(train) [4][1280/1345] lr: 1.0000e-02 eta: 11:17:19 time: 0.1925 data_time: 0.0056 memory: 8326 grad_norm: 6.5910 loss: 5.5819 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.5345 loss_aux: 2.0474 2023/02/17 12:25:55 - mmengine - INFO - Epoch(train) [4][1300/1345] lr: 1.0000e-02 eta: 11:17:03 time: 0.1919 data_time: 0.0057 memory: 8326 grad_norm: 6.5212 loss: 5.0815 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1652 loss_aux: 1.9163 2023/02/17 12:25:59 - mmengine - INFO - Epoch(train) [4][1320/1345] lr: 1.0000e-02 eta: 11:16:48 time: 0.1910 data_time: 0.0051 memory: 8326 grad_norm: 6.5990 loss: 5.0869 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2023 loss_aux: 1.8846 2023/02/17 12:26:03 - mmengine - INFO - Epoch(train) [4][1340/1345] lr: 1.0000e-02 eta: 11:16:32 time: 0.1905 data_time: 0.0054 memory: 8326 grad_norm: 6.6998 loss: 4.9820 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.1076 loss_aux: 1.8744 2023/02/17 12:26:04 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:26:04 - mmengine - INFO - Epoch(train) [4][1345/1345] lr: 1.0000e-02 eta: 11:16:24 time: 0.1854 data_time: 0.0054 memory: 8326 grad_norm: 6.7536 loss: 5.2033 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.2831 loss_aux: 1.9202 2023/02/17 12:26:04 - mmengine - INFO - Saving checkpoint at 4 epochs 2023/02/17 12:26:12 - mmengine - INFO - Epoch(train) [5][ 20/1345] lr: 1.0000e-02 eta: 11:17:02 time: 0.2652 data_time: 0.0737 memory: 8326 grad_norm: 6.5745 loss: 5.0927 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.1598 loss_aux: 1.9329 2023/02/17 12:26:15 - mmengine - INFO - Epoch(train) [5][ 40/1345] lr: 1.0000e-02 eta: 11:16:46 time: 0.1898 data_time: 0.0047 memory: 8326 grad_norm: 6.6899 loss: 4.9369 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 3.0622 loss_aux: 1.8747 2023/02/17 12:26:19 - mmengine - INFO - Epoch(train) [5][ 60/1345] lr: 1.0000e-02 eta: 11:16:29 time: 0.1902 data_time: 0.0055 memory: 8326 grad_norm: 6.8980 loss: 5.1056 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.1448 loss_aux: 1.9608 2023/02/17 12:26:23 - mmengine - INFO - Epoch(train) [5][ 80/1345] lr: 1.0000e-02 eta: 11:16:14 time: 0.1911 data_time: 0.0056 memory: 8326 grad_norm: 6.8276 loss: 4.9890 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1168 loss_aux: 1.8723 2023/02/17 12:26:27 - mmengine - INFO - Epoch(train) [5][ 100/1345] lr: 1.0000e-02 eta: 11:15:58 time: 0.1907 data_time: 0.0052 memory: 8326 grad_norm: 6.5295 loss: 4.9589 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1332 loss_aux: 1.8258 2023/02/17 12:26:31 - mmengine - INFO - Epoch(train) [5][ 120/1345] lr: 1.0000e-02 eta: 11:15:44 time: 0.1921 data_time: 0.0055 memory: 8326 grad_norm: 6.6942 loss: 5.0356 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1456 loss_aux: 1.8900 2023/02/17 12:26:35 - mmengine - INFO - Epoch(train) [5][ 140/1345] lr: 1.0000e-02 eta: 11:15:29 time: 0.1913 data_time: 0.0055 memory: 8326 grad_norm: 6.6788 loss: 5.0672 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.1476 loss_aux: 1.9195 2023/02/17 12:26:38 - mmengine - INFO - Epoch(train) [5][ 160/1345] lr: 1.0000e-02 eta: 11:15:14 time: 0.1909 data_time: 0.0054 memory: 8326 grad_norm: 6.5746 loss: 4.8330 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9652 loss_aux: 1.8678 2023/02/17 12:26:42 - mmengine - INFO - Epoch(train) [5][ 180/1345] lr: 1.0000e-02 eta: 11:14:58 time: 0.1904 data_time: 0.0057 memory: 8326 grad_norm: 6.5916 loss: 4.7617 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9491 loss_aux: 1.8126 2023/02/17 12:26:46 - mmengine - INFO - Epoch(train) [5][ 200/1345] lr: 1.0000e-02 eta: 11:14:43 time: 0.1907 data_time: 0.0056 memory: 8326 grad_norm: 6.6242 loss: 5.0247 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.1233 loss_aux: 1.9014 2023/02/17 12:26:50 - mmengine - INFO - Epoch(train) [5][ 220/1345] lr: 1.0000e-02 eta: 11:14:29 time: 0.1921 data_time: 0.0069 memory: 8326 grad_norm: 6.6789 loss: 4.9112 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0337 loss_aux: 1.8775 2023/02/17 12:26:54 - mmengine - INFO - Epoch(train) [5][ 240/1345] lr: 1.0000e-02 eta: 11:14:13 time: 0.1898 data_time: 0.0056 memory: 8326 grad_norm: 6.6796 loss: 5.0140 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1088 loss_aux: 1.9053 2023/02/17 12:26:57 - mmengine - INFO - Epoch(train) [5][ 260/1345] lr: 1.0000e-02 eta: 11:13:58 time: 0.1905 data_time: 0.0053 memory: 8326 grad_norm: 6.8050 loss: 5.2488 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.2327 loss_aux: 2.0161 2023/02/17 12:27:01 - mmengine - INFO - Epoch(train) [5][ 280/1345] lr: 1.0000e-02 eta: 11:13:45 time: 0.1926 data_time: 0.0064 memory: 8326 grad_norm: 6.8090 loss: 5.0803 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.1423 loss_aux: 1.9380 2023/02/17 12:27:05 - mmengine - INFO - Epoch(train) [5][ 300/1345] lr: 1.0000e-02 eta: 11:13:41 time: 0.2070 data_time: 0.0055 memory: 8326 grad_norm: 6.5791 loss: 4.8466 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9862 loss_aux: 1.8604 2023/02/17 12:27:09 - mmengine - INFO - Epoch(train) [5][ 320/1345] lr: 1.0000e-02 eta: 11:13:27 time: 0.1915 data_time: 0.0055 memory: 8326 grad_norm: 6.5604 loss: 4.8733 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0058 loss_aux: 1.8675 2023/02/17 12:27:13 - mmengine - INFO - Epoch(train) [5][ 340/1345] lr: 1.0000e-02 eta: 11:13:12 time: 0.1906 data_time: 0.0058 memory: 8326 grad_norm: 6.6576 loss: 4.8866 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0464 loss_aux: 1.8401 2023/02/17 12:27:17 - mmengine - INFO - Epoch(train) [5][ 360/1345] lr: 1.0000e-02 eta: 11:13:02 time: 0.1971 data_time: 0.0055 memory: 8326 grad_norm: 6.6852 loss: 5.1407 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.2234 loss_aux: 1.9174 2023/02/17 12:27:21 - mmengine - INFO - Epoch(train) [5][ 380/1345] lr: 1.0000e-02 eta: 11:13:02 time: 0.2121 data_time: 0.0063 memory: 8326 grad_norm: 6.7278 loss: 5.0601 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.1880 loss_aux: 1.8721 2023/02/17 12:27:25 - mmengine - INFO - Epoch(train) [5][ 400/1345] lr: 1.0000e-02 eta: 11:12:47 time: 0.1906 data_time: 0.0056 memory: 8326 grad_norm: 6.7126 loss: 5.3219 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.3996 loss_aux: 1.9223 2023/02/17 12:27:29 - mmengine - INFO - Epoch(train) [5][ 420/1345] lr: 1.0000e-02 eta: 11:12:33 time: 0.1908 data_time: 0.0054 memory: 8326 grad_norm: 6.4979 loss: 5.0601 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.2504 loss_aux: 1.8096 2023/02/17 12:27:33 - mmengine - INFO - Epoch(train) [5][ 440/1345] lr: 1.0000e-02 eta: 11:12:19 time: 0.1909 data_time: 0.0056 memory: 8326 grad_norm: 6.7377 loss: 5.2770 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.3076 loss_aux: 1.9693 2023/02/17 12:27:37 - mmengine - INFO - Epoch(train) [5][ 460/1345] lr: 1.0000e-02 eta: 11:12:05 time: 0.1916 data_time: 0.0058 memory: 8326 grad_norm: 6.8201 loss: 5.2682 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 3.3172 loss_aux: 1.9511 2023/02/17 12:27:40 - mmengine - INFO - Epoch(train) [5][ 480/1345] lr: 1.0000e-02 eta: 11:11:52 time: 0.1920 data_time: 0.0070 memory: 8326 grad_norm: 6.7531 loss: 5.2456 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.3169 loss_aux: 1.9287 2023/02/17 12:27:44 - mmengine - INFO - Epoch(train) [5][ 500/1345] lr: 1.0000e-02 eta: 11:11:37 time: 0.1902 data_time: 0.0060 memory: 8326 grad_norm: 6.5956 loss: 5.0266 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.1477 loss_aux: 1.8789 2023/02/17 12:27:48 - mmengine - INFO - Epoch(train) [5][ 520/1345] lr: 1.0000e-02 eta: 11:11:23 time: 0.1908 data_time: 0.0051 memory: 8326 grad_norm: 6.8273 loss: 4.5803 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7872 loss_aux: 1.7931 2023/02/17 12:27:52 - mmengine - INFO - Epoch(train) [5][ 540/1345] lr: 1.0000e-02 eta: 11:11:09 time: 0.1911 data_time: 0.0056 memory: 8326 grad_norm: 6.7072 loss: 4.9952 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0989 loss_aux: 1.8964 2023/02/17 12:27:56 - mmengine - INFO - Epoch(train) [5][ 560/1345] lr: 1.0000e-02 eta: 11:10:56 time: 0.1909 data_time: 0.0055 memory: 8326 grad_norm: 6.5675 loss: 4.8900 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0819 loss_aux: 1.8081 2023/02/17 12:27:59 - mmengine - INFO - Epoch(train) [5][ 580/1345] lr: 1.0000e-02 eta: 11:10:41 time: 0.1901 data_time: 0.0055 memory: 8326 grad_norm: 6.7585 loss: 5.3594 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 3.3242 loss_aux: 2.0352 2023/02/17 12:28:03 - mmengine - INFO - Epoch(train) [5][ 600/1345] lr: 1.0000e-02 eta: 11:10:28 time: 0.1919 data_time: 0.0055 memory: 8326 grad_norm: 6.8481 loss: 4.6951 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9115 loss_aux: 1.7836 2023/02/17 12:28:07 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:28:07 - mmengine - INFO - Epoch(train) [5][ 620/1345] lr: 1.0000e-02 eta: 11:10:15 time: 0.1910 data_time: 0.0056 memory: 8326 grad_norm: 6.7650 loss: 5.2771 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.3556 loss_aux: 1.9215 2023/02/17 12:28:11 - mmengine - INFO - Epoch(train) [5][ 640/1345] lr: 1.0000e-02 eta: 11:10:01 time: 0.1909 data_time: 0.0054 memory: 8326 grad_norm: 6.9324 loss: 5.3104 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.3231 loss_aux: 1.9874 2023/02/17 12:28:15 - mmengine - INFO - Epoch(train) [5][ 660/1345] lr: 1.0000e-02 eta: 11:09:48 time: 0.1919 data_time: 0.0055 memory: 8326 grad_norm: 6.7846 loss: 4.9408 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.0459 loss_aux: 1.8949 2023/02/17 12:28:19 - mmengine - INFO - Epoch(train) [5][ 680/1345] lr: 1.0000e-02 eta: 11:09:35 time: 0.1916 data_time: 0.0057 memory: 8326 grad_norm: 6.8565 loss: 5.1205 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.1820 loss_aux: 1.9386 2023/02/17 12:28:22 - mmengine - INFO - Epoch(train) [5][ 700/1345] lr: 1.0000e-02 eta: 11:09:22 time: 0.1905 data_time: 0.0054 memory: 8326 grad_norm: 6.6562 loss: 5.6298 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.5818 loss_aux: 2.0480 2023/02/17 12:28:26 - mmengine - INFO - Epoch(train) [5][ 720/1345] lr: 1.0000e-02 eta: 11:09:09 time: 0.1929 data_time: 0.0057 memory: 8326 grad_norm: 6.8507 loss: 4.8384 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9901 loss_aux: 1.8483 2023/02/17 12:28:30 - mmengine - INFO - Epoch(train) [5][ 740/1345] lr: 1.0000e-02 eta: 11:08:56 time: 0.1911 data_time: 0.0053 memory: 8326 grad_norm: 6.9018 loss: 5.2067 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.2683 loss_aux: 1.9384 2023/02/17 12:28:34 - mmengine - INFO - Epoch(train) [5][ 760/1345] lr: 1.0000e-02 eta: 11:08:44 time: 0.1926 data_time: 0.0058 memory: 8326 grad_norm: 6.6284 loss: 5.1950 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.2188 loss_aux: 1.9762 2023/02/17 12:28:38 - mmengine - INFO - Epoch(train) [5][ 780/1345] lr: 1.0000e-02 eta: 11:08:31 time: 0.1910 data_time: 0.0054 memory: 8326 grad_norm: 6.7097 loss: 5.2182 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.2743 loss_aux: 1.9438 2023/02/17 12:28:42 - mmengine - INFO - Epoch(train) [5][ 800/1345] lr: 1.0000e-02 eta: 11:08:19 time: 0.1915 data_time: 0.0060 memory: 8326 grad_norm: 6.4398 loss: 5.1794 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 3.2788 loss_aux: 1.9005 2023/02/17 12:28:46 - mmengine - INFO - Epoch(train) [5][ 820/1345] lr: 1.0000e-02 eta: 11:08:09 time: 0.1964 data_time: 0.0076 memory: 8326 grad_norm: 6.4787 loss: 5.0313 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 3.0913 loss_aux: 1.9399 2023/02/17 12:28:49 - mmengine - INFO - Epoch(train) [5][ 840/1345] lr: 1.0000e-02 eta: 11:07:57 time: 0.1933 data_time: 0.0079 memory: 8326 grad_norm: 6.6690 loss: 5.0557 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0738 loss_aux: 1.9819 2023/02/17 12:28:53 - mmengine - INFO - Epoch(train) [5][ 860/1345] lr: 1.0000e-02 eta: 11:07:46 time: 0.1928 data_time: 0.0059 memory: 8326 grad_norm: 6.6051 loss: 4.7976 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9641 loss_aux: 1.8335 2023/02/17 12:28:57 - mmengine - INFO - Epoch(train) [5][ 880/1345] lr: 1.0000e-02 eta: 11:07:33 time: 0.1909 data_time: 0.0055 memory: 8326 grad_norm: 6.5150 loss: 4.7851 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9914 loss_aux: 1.7938 2023/02/17 12:29:01 - mmengine - INFO - Epoch(train) [5][ 900/1345] lr: 1.0000e-02 eta: 11:07:20 time: 0.1908 data_time: 0.0056 memory: 8326 grad_norm: 6.6375 loss: 5.1113 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.1878 loss_aux: 1.9234 2023/02/17 12:29:05 - mmengine - INFO - Epoch(train) [5][ 920/1345] lr: 1.0000e-02 eta: 11:07:07 time: 0.1911 data_time: 0.0059 memory: 8326 grad_norm: 6.7705 loss: 4.9791 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1307 loss_aux: 1.8484 2023/02/17 12:29:09 - mmengine - INFO - Epoch(train) [5][ 940/1345] lr: 1.0000e-02 eta: 11:06:54 time: 0.1905 data_time: 0.0056 memory: 8326 grad_norm: 6.7875 loss: 5.4689 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.4504 loss_aux: 2.0186 2023/02/17 12:29:12 - mmengine - INFO - Epoch(train) [5][ 960/1345] lr: 1.0000e-02 eta: 11:06:41 time: 0.1902 data_time: 0.0053 memory: 8326 grad_norm: 6.7357 loss: 4.9352 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1110 loss_aux: 1.8242 2023/02/17 12:29:16 - mmengine - INFO - Epoch(train) [5][ 980/1345] lr: 1.0000e-02 eta: 11:06:29 time: 0.1918 data_time: 0.0059 memory: 8326 grad_norm: 6.6870 loss: 4.8059 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0235 loss_aux: 1.7825 2023/02/17 12:29:20 - mmengine - INFO - Epoch(train) [5][1000/1345] lr: 1.0000e-02 eta: 11:06:17 time: 0.1911 data_time: 0.0054 memory: 8326 grad_norm: 6.6914 loss: 4.8830 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0089 loss_aux: 1.8741 2023/02/17 12:29:24 - mmengine - INFO - Epoch(train) [5][1020/1345] lr: 1.0000e-02 eta: 11:06:05 time: 0.1916 data_time: 0.0058 memory: 8326 grad_norm: 6.6023 loss: 5.2657 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.3195 loss_aux: 1.9462 2023/02/17 12:29:28 - mmengine - INFO - Epoch(train) [5][1040/1345] lr: 1.0000e-02 eta: 11:05:53 time: 0.1920 data_time: 0.0058 memory: 8326 grad_norm: 6.8216 loss: 5.1717 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 3.2594 loss_aux: 1.9123 2023/02/17 12:29:31 - mmengine - INFO - Epoch(train) [5][1060/1345] lr: 1.0000e-02 eta: 11:05:40 time: 0.1902 data_time: 0.0055 memory: 8326 grad_norm: 6.9215 loss: 4.8936 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0217 loss_aux: 1.8719 2023/02/17 12:29:35 - mmengine - INFO - Epoch(train) [5][1080/1345] lr: 1.0000e-02 eta: 11:05:28 time: 0.1914 data_time: 0.0059 memory: 8326 grad_norm: 6.8451 loss: 5.1114 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.1731 loss_aux: 1.9383 2023/02/17 12:29:39 - mmengine - INFO - Epoch(train) [5][1100/1345] lr: 1.0000e-02 eta: 11:05:16 time: 0.1911 data_time: 0.0055 memory: 8326 grad_norm: 6.6411 loss: 4.6379 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8370 loss_aux: 1.8009 2023/02/17 12:29:43 - mmengine - INFO - Epoch(train) [5][1120/1345] lr: 1.0000e-02 eta: 11:05:04 time: 0.1908 data_time: 0.0056 memory: 8326 grad_norm: 6.7059 loss: 4.9552 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.0860 loss_aux: 1.8692 2023/02/17 12:29:47 - mmengine - INFO - Epoch(train) [5][1140/1345] lr: 1.0000e-02 eta: 11:04:52 time: 0.1914 data_time: 0.0056 memory: 8326 grad_norm: 6.7869 loss: 5.1840 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2589 loss_aux: 1.9251 2023/02/17 12:29:51 - mmengine - INFO - Epoch(train) [5][1160/1345] lr: 1.0000e-02 eta: 11:04:48 time: 0.2043 data_time: 0.0054 memory: 8326 grad_norm: 6.7063 loss: 4.9188 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0389 loss_aux: 1.8799 2023/02/17 12:29:55 - mmengine - INFO - Epoch(train) [5][1180/1345] lr: 1.0000e-02 eta: 11:04:36 time: 0.1915 data_time: 0.0055 memory: 8326 grad_norm: 6.5004 loss: 5.0272 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.0958 loss_aux: 1.9314 2023/02/17 12:29:58 - mmengine - INFO - Epoch(train) [5][1200/1345] lr: 1.0000e-02 eta: 11:04:24 time: 0.1904 data_time: 0.0055 memory: 8326 grad_norm: 6.4184 loss: 4.8624 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.0256 loss_aux: 1.8368 2023/02/17 12:30:02 - mmengine - INFO - Epoch(train) [5][1220/1345] lr: 1.0000e-02 eta: 11:04:12 time: 0.1911 data_time: 0.0058 memory: 8326 grad_norm: 6.5285 loss: 5.0025 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.1475 loss_aux: 1.8550 2023/02/17 12:30:06 - mmengine - INFO - Epoch(train) [5][1240/1345] lr: 1.0000e-02 eta: 11:04:00 time: 0.1912 data_time: 0.0056 memory: 8326 grad_norm: 6.7183 loss: 5.1617 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.2278 loss_aux: 1.9340 2023/02/17 12:30:10 - mmengine - INFO - Epoch(train) [5][1260/1345] lr: 1.0000e-02 eta: 11:03:49 time: 0.1915 data_time: 0.0058 memory: 8326 grad_norm: 6.7699 loss: 4.8938 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.0618 loss_aux: 1.8320 2023/02/17 12:30:14 - mmengine - INFO - Epoch(train) [5][1280/1345] lr: 1.0000e-02 eta: 11:03:38 time: 0.1919 data_time: 0.0065 memory: 8326 grad_norm: 6.6140 loss: 5.2026 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2575 loss_aux: 1.9451 2023/02/17 12:30:18 - mmengine - INFO - Epoch(train) [5][1300/1345] lr: 1.0000e-02 eta: 11:03:27 time: 0.1930 data_time: 0.0057 memory: 8326 grad_norm: 6.5664 loss: 4.5980 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8321 loss_aux: 1.7658 2023/02/17 12:30:21 - mmengine - INFO - Epoch(train) [5][1320/1345] lr: 1.0000e-02 eta: 11:03:15 time: 0.1911 data_time: 0.0057 memory: 8326 grad_norm: 6.5832 loss: 4.9759 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.1036 loss_aux: 1.8724 2023/02/17 12:30:25 - mmengine - INFO - Epoch(train) [5][1340/1345] lr: 1.0000e-02 eta: 11:03:04 time: 0.1912 data_time: 0.0049 memory: 8326 grad_norm: 6.7964 loss: 4.8398 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.9527 loss_aux: 1.8871 2023/02/17 12:30:27 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:30:27 - mmengine - INFO - Epoch(train) [5][1345/1345] lr: 1.0000e-02 eta: 11:03:11 time: 0.2081 data_time: 0.0053 memory: 8326 grad_norm: 6.7100 loss: 4.9497 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.0600 loss_aux: 1.8897 2023/02/17 12:30:27 - mmengine - INFO - Saving checkpoint at 5 epochs 2023/02/17 12:31:03 - mmengine - INFO - Epoch(val) [5][ 20/181] eta: 0:04:30 time: 1.6789 data_time: 1.6270 memory: 1994 2023/02/17 12:31:09 - mmengine - INFO - Epoch(val) [5][ 40/181] eta: 0:02:18 time: 0.2918 data_time: 0.2397 memory: 1994 2023/02/17 12:31:16 - mmengine - INFO - Epoch(val) [5][ 60/181] eta: 0:01:35 time: 0.3891 data_time: 0.3388 memory: 1994 2023/02/17 12:31:22 - mmengine - INFO - Epoch(val) [5][ 80/181] eta: 0:01:06 time: 0.2725 data_time: 0.2231 memory: 1994 2023/02/17 12:31:30 - mmengine - INFO - Epoch(val) [5][100/181] eta: 0:00:49 time: 0.3925 data_time: 0.3429 memory: 1994 2023/02/17 12:31:36 - mmengine - INFO - Epoch(val) [5][120/181] eta: 0:00:33 time: 0.3002 data_time: 0.2525 memory: 1994 2023/02/17 12:31:43 - mmengine - INFO - Epoch(val) [5][140/181] eta: 0:00:21 time: 0.3493 data_time: 0.2980 memory: 1994 2023/02/17 12:31:49 - mmengine - INFO - Epoch(val) [5][160/181] eta: 0:00:10 time: 0.2971 data_time: 0.2477 memory: 1994 2023/02/17 12:31:57 - mmengine - INFO - Epoch(val) [5][180/181] eta: 0:00:00 time: 0.4027 data_time: 0.3525 memory: 1994 2023/02/17 12:32:01 - mmengine - INFO - Epoch(val) [5][181/181] acc/top1: 0.2826 acc/top5: 0.5649 acc/mean1: 0.2571 2023/02/17 12:32:02 - mmengine - INFO - The best checkpoint with 0.2826 acc/top1 at 5 epoch is saved to best_acc/top1_epoch_5.pth. 2023/02/17 12:32:07 - mmengine - INFO - Epoch(train) [6][ 20/1345] lr: 1.0000e-02 eta: 11:03:36 time: 0.2556 data_time: 0.0664 memory: 8327 grad_norm: 6.3840 loss: 4.9122 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0344 loss_aux: 1.8778 2023/02/17 12:32:11 - mmengine - INFO - Epoch(train) [6][ 40/1345] lr: 1.0000e-02 eta: 11:03:25 time: 0.1911 data_time: 0.0051 memory: 8327 grad_norm: 6.7333 loss: 4.8932 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0294 loss_aux: 1.8638 2023/02/17 12:32:15 - mmengine - INFO - Epoch(train) [6][ 60/1345] lr: 1.0000e-02 eta: 11:03:14 time: 0.1920 data_time: 0.0054 memory: 8327 grad_norm: 6.8486 loss: 4.8825 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0592 loss_aux: 1.8233 2023/02/17 12:32:19 - mmengine - INFO - Epoch(train) [6][ 80/1345] lr: 1.0000e-02 eta: 11:03:04 time: 0.1950 data_time: 0.0057 memory: 8327 grad_norm: 6.6799 loss: 5.0243 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0911 loss_aux: 1.9333 2023/02/17 12:32:23 - mmengine - INFO - Epoch(train) [6][ 100/1345] lr: 1.0000e-02 eta: 11:02:53 time: 0.1919 data_time: 0.0055 memory: 8327 grad_norm: 6.6737 loss: 5.0813 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.1955 loss_aux: 1.8857 2023/02/17 12:32:27 - mmengine - INFO - Epoch(train) [6][ 120/1345] lr: 1.0000e-02 eta: 11:02:44 time: 0.1944 data_time: 0.0053 memory: 8327 grad_norm: 6.5261 loss: 4.9233 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0864 loss_aux: 1.8368 2023/02/17 12:32:30 - mmengine - INFO - Epoch(train) [6][ 140/1345] lr: 1.0000e-02 eta: 11:02:33 time: 0.1922 data_time: 0.0058 memory: 8327 grad_norm: 6.5737 loss: 4.5417 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7849 loss_aux: 1.7568 2023/02/17 12:32:34 - mmengine - INFO - Epoch(train) [6][ 160/1345] lr: 1.0000e-02 eta: 11:02:21 time: 0.1905 data_time: 0.0053 memory: 8327 grad_norm: 6.7003 loss: 5.0757 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 3.2247 loss_aux: 1.8510 2023/02/17 12:32:38 - mmengine - INFO - Epoch(train) [6][ 180/1345] lr: 1.0000e-02 eta: 11:02:10 time: 0.1911 data_time: 0.0055 memory: 8327 grad_norm: 6.6735 loss: 4.9838 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 3.0880 loss_aux: 1.8958 2023/02/17 12:32:42 - mmengine - INFO - Epoch(train) [6][ 200/1345] lr: 1.0000e-02 eta: 11:01:58 time: 0.1900 data_time: 0.0054 memory: 8327 grad_norm: 6.6839 loss: 5.1085 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1775 loss_aux: 1.9311 2023/02/17 12:32:46 - mmengine - INFO - Epoch(train) [6][ 220/1345] lr: 1.0000e-02 eta: 11:01:46 time: 0.1896 data_time: 0.0053 memory: 8327 grad_norm: 6.7336 loss: 4.7509 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9482 loss_aux: 1.8027 2023/02/17 12:32:50 - mmengine - INFO - Epoch(train) [6][ 240/1345] lr: 1.0000e-02 eta: 11:01:34 time: 0.1905 data_time: 0.0054 memory: 8327 grad_norm: 6.7726 loss: 4.5625 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7918 loss_aux: 1.7707 2023/02/17 12:32:53 - mmengine - INFO - Epoch(train) [6][ 260/1345] lr: 1.0000e-02 eta: 11:01:23 time: 0.1904 data_time: 0.0054 memory: 8327 grad_norm: 6.6477 loss: 4.7839 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.9661 loss_aux: 1.8179 2023/02/17 12:32:56 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:32:57 - mmengine - INFO - Epoch(train) [6][ 280/1345] lr: 1.0000e-02 eta: 11:01:12 time: 0.1920 data_time: 0.0055 memory: 8327 grad_norm: 6.8121 loss: 4.7475 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9463 loss_aux: 1.8012 2023/02/17 12:33:01 - mmengine - INFO - Epoch(train) [6][ 300/1345] lr: 1.0000e-02 eta: 11:01:01 time: 0.1911 data_time: 0.0057 memory: 8327 grad_norm: 6.5943 loss: 4.6642 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8978 loss_aux: 1.7664 2023/02/17 12:33:05 - mmengine - INFO - Epoch(train) [6][ 320/1345] lr: 1.0000e-02 eta: 11:00:50 time: 0.1902 data_time: 0.0050 memory: 8327 grad_norm: 6.7652 loss: 5.0458 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1442 loss_aux: 1.9016 2023/02/17 12:33:09 - mmengine - INFO - Epoch(train) [6][ 340/1345] lr: 1.0000e-02 eta: 11:00:39 time: 0.1911 data_time: 0.0053 memory: 8327 grad_norm: 6.7152 loss: 4.7657 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8986 loss_aux: 1.8671 2023/02/17 12:33:12 - mmengine - INFO - Epoch(train) [6][ 360/1345] lr: 1.0000e-02 eta: 11:00:27 time: 0.1907 data_time: 0.0056 memory: 8327 grad_norm: 6.9340 loss: 4.9825 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.1158 loss_aux: 1.8667 2023/02/17 12:33:16 - mmengine - INFO - Epoch(train) [6][ 380/1345] lr: 1.0000e-02 eta: 11:00:16 time: 0.1910 data_time: 0.0053 memory: 8327 grad_norm: 6.4990 loss: 4.8832 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.0653 loss_aux: 1.8179 2023/02/17 12:33:20 - mmengine - INFO - Epoch(train) [6][ 400/1345] lr: 1.0000e-02 eta: 11:00:07 time: 0.1938 data_time: 0.0053 memory: 8327 grad_norm: 6.5276 loss: 4.5785 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7790 loss_aux: 1.7995 2023/02/17 12:33:24 - mmengine - INFO - Epoch(train) [6][ 420/1345] lr: 1.0000e-02 eta: 10:59:56 time: 0.1901 data_time: 0.0055 memory: 8327 grad_norm: 6.5382 loss: 4.8024 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9319 loss_aux: 1.8705 2023/02/17 12:33:28 - mmengine - INFO - Epoch(train) [6][ 440/1345] lr: 1.0000e-02 eta: 10:59:45 time: 0.1908 data_time: 0.0055 memory: 8327 grad_norm: 6.7339 loss: 4.5757 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.8025 loss_aux: 1.7732 2023/02/17 12:33:32 - mmengine - INFO - Epoch(train) [6][ 460/1345] lr: 1.0000e-02 eta: 10:59:34 time: 0.1906 data_time: 0.0054 memory: 8327 grad_norm: 6.5797 loss: 4.8227 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 3.0216 loss_aux: 1.8011 2023/02/17 12:33:35 - mmengine - INFO - Epoch(train) [6][ 480/1345] lr: 1.0000e-02 eta: 10:59:23 time: 0.1913 data_time: 0.0053 memory: 8327 grad_norm: 6.6818 loss: 5.0345 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.1521 loss_aux: 1.8824 2023/02/17 12:33:39 - mmengine - INFO - Epoch(train) [6][ 500/1345] lr: 1.0000e-02 eta: 10:59:13 time: 0.1914 data_time: 0.0054 memory: 8327 grad_norm: 6.7715 loss: 4.9263 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0582 loss_aux: 1.8681 2023/02/17 12:33:43 - mmengine - INFO - Epoch(train) [6][ 520/1345] lr: 1.0000e-02 eta: 10:59:02 time: 0.1914 data_time: 0.0057 memory: 8327 grad_norm: 6.6697 loss: 4.4585 top1_acc: 0.1250 top5_acc: 0.8750 loss_cls: 2.7184 loss_aux: 1.7400 2023/02/17 12:33:47 - mmengine - INFO - Epoch(train) [6][ 540/1345] lr: 1.0000e-02 eta: 10:58:51 time: 0.1904 data_time: 0.0053 memory: 8327 grad_norm: 6.5750 loss: 4.5450 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7642 loss_aux: 1.7808 2023/02/17 12:33:51 - mmengine - INFO - Epoch(train) [6][ 560/1345] lr: 1.0000e-02 eta: 10:58:40 time: 0.1905 data_time: 0.0055 memory: 8327 grad_norm: 6.7870 loss: 5.0592 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.1492 loss_aux: 1.9100 2023/02/17 12:33:54 - mmengine - INFO - Epoch(train) [6][ 580/1345] lr: 1.0000e-02 eta: 10:58:29 time: 0.1900 data_time: 0.0058 memory: 8327 grad_norm: 6.4568 loss: 4.7755 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9386 loss_aux: 1.8369 2023/02/17 12:33:58 - mmengine - INFO - Epoch(train) [6][ 600/1345] lr: 1.0000e-02 eta: 10:58:19 time: 0.1909 data_time: 0.0051 memory: 8327 grad_norm: 6.6175 loss: 4.8169 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9941 loss_aux: 1.8228 2023/02/17 12:34:02 - mmengine - INFO - Epoch(train) [6][ 620/1345] lr: 1.0000e-02 eta: 10:58:08 time: 0.1908 data_time: 0.0053 memory: 8327 grad_norm: 6.7073 loss: 4.7927 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9276 loss_aux: 1.8651 2023/02/17 12:34:06 - mmengine - INFO - Epoch(train) [6][ 640/1345] lr: 1.0000e-02 eta: 10:57:58 time: 0.1918 data_time: 0.0071 memory: 8327 grad_norm: 6.7003 loss: 4.9679 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0953 loss_aux: 1.8725 2023/02/17 12:34:10 - mmengine - INFO - Epoch(train) [6][ 660/1345] lr: 1.0000e-02 eta: 10:57:48 time: 0.1913 data_time: 0.0052 memory: 8327 grad_norm: 6.6624 loss: 4.8065 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.9549 loss_aux: 1.8515 2023/02/17 12:34:14 - mmengine - INFO - Epoch(train) [6][ 680/1345] lr: 1.0000e-02 eta: 10:57:37 time: 0.1910 data_time: 0.0054 memory: 8327 grad_norm: 6.5768 loss: 4.7949 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9909 loss_aux: 1.8040 2023/02/17 12:34:17 - mmengine - INFO - Epoch(train) [6][ 700/1345] lr: 1.0000e-02 eta: 10:57:27 time: 0.1903 data_time: 0.0055 memory: 8327 grad_norm: 6.5044 loss: 4.8101 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9969 loss_aux: 1.8131 2023/02/17 12:34:21 - mmengine - INFO - Epoch(train) [6][ 720/1345] lr: 1.0000e-02 eta: 10:57:17 time: 0.1918 data_time: 0.0064 memory: 8327 grad_norm: 6.7600 loss: 4.6949 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8840 loss_aux: 1.8109 2023/02/17 12:34:25 - mmengine - INFO - Epoch(train) [6][ 740/1345] lr: 1.0000e-02 eta: 10:57:06 time: 0.1902 data_time: 0.0052 memory: 8327 grad_norm: 6.6539 loss: 5.0322 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 3.1510 loss_aux: 1.8812 2023/02/17 12:34:29 - mmengine - INFO - Epoch(train) [6][ 760/1345] lr: 1.0000e-02 eta: 10:56:56 time: 0.1920 data_time: 0.0060 memory: 8327 grad_norm: 6.5008 loss: 5.2377 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.3171 loss_aux: 1.9205 2023/02/17 12:34:33 - mmengine - INFO - Epoch(train) [6][ 780/1345] lr: 1.0000e-02 eta: 10:56:45 time: 0.1900 data_time: 0.0052 memory: 8327 grad_norm: 6.5093 loss: 4.8978 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0589 loss_aux: 1.8389 2023/02/17 12:34:36 - mmengine - INFO - Epoch(train) [6][ 800/1345] lr: 1.0000e-02 eta: 10:56:35 time: 0.1913 data_time: 0.0058 memory: 8327 grad_norm: 6.7357 loss: 4.9477 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.0747 loss_aux: 1.8730 2023/02/17 12:34:40 - mmengine - INFO - Epoch(train) [6][ 820/1345] lr: 1.0000e-02 eta: 10:56:25 time: 0.1913 data_time: 0.0055 memory: 8327 grad_norm: 6.6009 loss: 4.7171 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9042 loss_aux: 1.8130 2023/02/17 12:34:44 - mmengine - INFO - Epoch(train) [6][ 840/1345] lr: 1.0000e-02 eta: 10:56:15 time: 0.1913 data_time: 0.0051 memory: 8327 grad_norm: 6.7916 loss: 5.0066 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.1039 loss_aux: 1.9027 2023/02/17 12:34:48 - mmengine - INFO - Epoch(train) [6][ 860/1345] lr: 1.0000e-02 eta: 10:56:05 time: 0.1906 data_time: 0.0053 memory: 8327 grad_norm: 6.5431 loss: 4.4912 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7364 loss_aux: 1.7548 2023/02/17 12:34:52 - mmengine - INFO - Epoch(train) [6][ 880/1345] lr: 1.0000e-02 eta: 10:55:55 time: 0.1916 data_time: 0.0058 memory: 8327 grad_norm: 6.6590 loss: 4.6908 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.9116 loss_aux: 1.7792 2023/02/17 12:34:56 - mmengine - INFO - Epoch(train) [6][ 900/1345] lr: 1.0000e-02 eta: 10:55:45 time: 0.1909 data_time: 0.0050 memory: 8327 grad_norm: 6.9364 loss: 5.4832 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.4594 loss_aux: 2.0237 2023/02/17 12:34:59 - mmengine - INFO - Epoch(train) [6][ 920/1345] lr: 1.0000e-02 eta: 10:55:35 time: 0.1907 data_time: 0.0055 memory: 8327 grad_norm: 6.7063 loss: 4.7031 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8926 loss_aux: 1.8105 2023/02/17 12:35:03 - mmengine - INFO - Epoch(train) [6][ 940/1345] lr: 1.0000e-02 eta: 10:55:25 time: 0.1907 data_time: 0.0055 memory: 8327 grad_norm: 6.6916 loss: 4.4938 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6897 loss_aux: 1.8041 2023/02/17 12:35:07 - mmengine - INFO - Epoch(train) [6][ 960/1345] lr: 1.0000e-02 eta: 10:55:15 time: 0.1910 data_time: 0.0054 memory: 8327 grad_norm: 6.8349 loss: 5.0491 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.1378 loss_aux: 1.9113 2023/02/17 12:35:11 - mmengine - INFO - Epoch(train) [6][ 980/1345] lr: 1.0000e-02 eta: 10:55:06 time: 0.1924 data_time: 0.0062 memory: 8327 grad_norm: 6.6651 loss: 4.7289 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.8991 loss_aux: 1.8298 2023/02/17 12:35:15 - mmengine - INFO - Epoch(train) [6][1000/1345] lr: 1.0000e-02 eta: 10:54:56 time: 0.1912 data_time: 0.0054 memory: 8327 grad_norm: 6.8723 loss: 4.8117 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9859 loss_aux: 1.8258 2023/02/17 12:35:19 - mmengine - INFO - Epoch(train) [6][1020/1345] lr: 1.0000e-02 eta: 10:54:46 time: 0.1901 data_time: 0.0055 memory: 8327 grad_norm: 6.7427 loss: 4.9596 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0884 loss_aux: 1.8712 2023/02/17 12:35:22 - mmengine - INFO - Epoch(train) [6][1040/1345] lr: 1.0000e-02 eta: 10:54:36 time: 0.1906 data_time: 0.0053 memory: 8327 grad_norm: 6.6828 loss: 4.3181 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6819 loss_aux: 1.6362 2023/02/17 12:35:26 - mmengine - INFO - Epoch(train) [6][1060/1345] lr: 1.0000e-02 eta: 10:54:26 time: 0.1916 data_time: 0.0057 memory: 8327 grad_norm: 6.7109 loss: 4.7584 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9388 loss_aux: 1.8196 2023/02/17 12:35:30 - mmengine - INFO - Epoch(train) [6][1080/1345] lr: 1.0000e-02 eta: 10:54:17 time: 0.1915 data_time: 0.0056 memory: 8327 grad_norm: 6.8374 loss: 4.7064 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8869 loss_aux: 1.8195 2023/02/17 12:35:34 - mmengine - INFO - Epoch(train) [6][1100/1345] lr: 1.0000e-02 eta: 10:54:07 time: 0.1909 data_time: 0.0054 memory: 8327 grad_norm: 6.7614 loss: 4.7328 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9398 loss_aux: 1.7930 2023/02/17 12:35:38 - mmengine - INFO - Epoch(train) [6][1120/1345] lr: 1.0000e-02 eta: 10:53:58 time: 0.1910 data_time: 0.0053 memory: 8327 grad_norm: 6.5964 loss: 4.8332 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.0364 loss_aux: 1.7969 2023/02/17 12:35:41 - mmengine - INFO - Epoch(train) [6][1140/1345] lr: 1.0000e-02 eta: 10:53:48 time: 0.1909 data_time: 0.0057 memory: 8327 grad_norm: 6.6972 loss: 4.9470 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1370 loss_aux: 1.8100 2023/02/17 12:35:45 - mmengine - INFO - Epoch(train) [6][1160/1345] lr: 1.0000e-02 eta: 10:53:40 time: 0.1936 data_time: 0.0054 memory: 8327 grad_norm: 6.6748 loss: 4.9227 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0448 loss_aux: 1.8779 2023/02/17 12:35:49 - mmengine - INFO - Epoch(train) [6][1180/1345] lr: 1.0000e-02 eta: 10:53:29 time: 0.1900 data_time: 0.0059 memory: 8327 grad_norm: 6.5924 loss: 4.7391 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9493 loss_aux: 1.7897 2023/02/17 12:35:53 - mmengine - INFO - Epoch(train) [6][1200/1345] lr: 1.0000e-02 eta: 10:53:20 time: 0.1909 data_time: 0.0062 memory: 8327 grad_norm: 6.6822 loss: 4.8804 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0720 loss_aux: 1.8085 2023/02/17 12:35:57 - mmengine - INFO - Epoch(train) [6][1220/1345] lr: 1.0000e-02 eta: 10:53:10 time: 0.1908 data_time: 0.0059 memory: 8327 grad_norm: 6.7776 loss: 4.6556 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8618 loss_aux: 1.7938 2023/02/17 12:36:01 - mmengine - INFO - Epoch(train) [6][1240/1345] lr: 1.0000e-02 eta: 10:53:01 time: 0.1908 data_time: 0.0053 memory: 8327 grad_norm: 6.5582 loss: 4.7500 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9404 loss_aux: 1.8095 2023/02/17 12:36:04 - mmengine - INFO - Epoch(train) [6][1260/1345] lr: 1.0000e-02 eta: 10:52:51 time: 0.1906 data_time: 0.0055 memory: 8327 grad_norm: 6.8207 loss: 4.5947 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8538 loss_aux: 1.7409 2023/02/17 12:36:07 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:36:08 - mmengine - INFO - Epoch(train) [6][1280/1345] lr: 1.0000e-02 eta: 10:52:42 time: 0.1917 data_time: 0.0059 memory: 8327 grad_norm: 6.7567 loss: 4.3845 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6686 loss_aux: 1.7159 2023/02/17 12:36:12 - mmengine - INFO - Epoch(train) [6][1300/1345] lr: 1.0000e-02 eta: 10:52:32 time: 0.1898 data_time: 0.0052 memory: 8327 grad_norm: 6.6717 loss: 4.3001 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6469 loss_aux: 1.6532 2023/02/17 12:36:16 - mmengine - INFO - Epoch(train) [6][1320/1345] lr: 1.0000e-02 eta: 10:52:23 time: 0.1924 data_time: 0.0079 memory: 8327 grad_norm: 6.6311 loss: 5.2165 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2643 loss_aux: 1.9521 2023/02/17 12:36:20 - mmengine - INFO - Epoch(train) [6][1340/1345] lr: 1.0000e-02 eta: 10:52:14 time: 0.1911 data_time: 0.0063 memory: 8327 grad_norm: 6.8631 loss: 4.7162 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.9558 loss_aux: 1.7604 2023/02/17 12:36:21 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:36:21 - mmengine - INFO - Epoch(train) [6][1345/1345] lr: 1.0000e-02 eta: 10:52:08 time: 0.1837 data_time: 0.0055 memory: 8327 grad_norm: 6.7080 loss: 4.7868 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 3.0075 loss_aux: 1.7793 2023/02/17 12:36:21 - mmengine - INFO - Saving checkpoint at 6 epochs 2023/02/17 12:36:28 - mmengine - INFO - Epoch(train) [7][ 20/1345] lr: 1.0000e-02 eta: 10:52:15 time: 0.2255 data_time: 0.0366 memory: 8327 grad_norm: 6.6524 loss: 4.4572 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7268 loss_aux: 1.7304 2023/02/17 12:36:31 - mmengine - INFO - Epoch(train) [7][ 40/1345] lr: 1.0000e-02 eta: 10:52:06 time: 0.1911 data_time: 0.0036 memory: 8327 grad_norm: 6.7464 loss: 4.9062 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.0663 loss_aux: 1.8399 2023/02/17 12:36:35 - mmengine - INFO - Epoch(train) [7][ 60/1345] lr: 1.0000e-02 eta: 10:51:56 time: 0.1900 data_time: 0.0049 memory: 8327 grad_norm: 6.6380 loss: 4.7084 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9402 loss_aux: 1.7683 2023/02/17 12:36:39 - mmengine - INFO - Epoch(train) [7][ 80/1345] lr: 1.0000e-02 eta: 10:51:47 time: 0.1903 data_time: 0.0054 memory: 8327 grad_norm: 6.6667 loss: 5.1263 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2034 loss_aux: 1.9229 2023/02/17 12:36:43 - mmengine - INFO - Epoch(train) [7][ 100/1345] lr: 1.0000e-02 eta: 10:51:37 time: 0.1908 data_time: 0.0053 memory: 8327 grad_norm: 6.5505 loss: 4.8096 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9162 loss_aux: 1.8935 2023/02/17 12:36:47 - mmengine - INFO - Epoch(train) [7][ 120/1345] lr: 1.0000e-02 eta: 10:51:28 time: 0.1911 data_time: 0.0055 memory: 8327 grad_norm: 6.5952 loss: 4.8997 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0452 loss_aux: 1.8544 2023/02/17 12:36:50 - mmengine - INFO - Epoch(train) [7][ 140/1345] lr: 1.0000e-02 eta: 10:51:19 time: 0.1909 data_time: 0.0053 memory: 8327 grad_norm: 6.6319 loss: 4.5909 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7777 loss_aux: 1.8133 2023/02/17 12:36:54 - mmengine - INFO - Epoch(train) [7][ 160/1345] lr: 1.0000e-02 eta: 10:51:09 time: 0.1901 data_time: 0.0054 memory: 8327 grad_norm: 6.6075 loss: 4.4229 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6953 loss_aux: 1.7277 2023/02/17 12:36:58 - mmengine - INFO - Epoch(train) [7][ 180/1345] lr: 1.0000e-02 eta: 10:51:00 time: 0.1903 data_time: 0.0053 memory: 8327 grad_norm: 6.7596 loss: 4.6669 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8589 loss_aux: 1.8080 2023/02/17 12:37:02 - mmengine - INFO - Epoch(train) [7][ 200/1345] lr: 1.0000e-02 eta: 10:51:00 time: 0.2101 data_time: 0.0254 memory: 8327 grad_norm: 6.6069 loss: 4.5092 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7817 loss_aux: 1.7275 2023/02/17 12:37:06 - mmengine - INFO - Epoch(train) [7][ 220/1345] lr: 1.0000e-02 eta: 10:50:50 time: 0.1905 data_time: 0.0055 memory: 8327 grad_norm: 6.8211 loss: 4.7755 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9544 loss_aux: 1.8211 2023/02/17 12:37:10 - mmengine - INFO - Epoch(train) [7][ 240/1345] lr: 1.0000e-02 eta: 10:50:41 time: 0.1917 data_time: 0.0055 memory: 8327 grad_norm: 6.6682 loss: 4.9694 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.1487 loss_aux: 1.8207 2023/02/17 12:37:14 - mmengine - INFO - Epoch(train) [7][ 260/1345] lr: 1.0000e-02 eta: 10:50:33 time: 0.1919 data_time: 0.0057 memory: 8327 grad_norm: 6.6627 loss: 4.8110 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9893 loss_aux: 1.8217 2023/02/17 12:37:18 - mmengine - INFO - Epoch(train) [7][ 280/1345] lr: 1.0000e-02 eta: 10:50:24 time: 0.1908 data_time: 0.0054 memory: 8327 grad_norm: 6.7200 loss: 4.3453 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6591 loss_aux: 1.6862 2023/02/17 12:37:21 - mmengine - INFO - Epoch(train) [7][ 300/1345] lr: 1.0000e-02 eta: 10:50:14 time: 0.1901 data_time: 0.0054 memory: 8327 grad_norm: 6.7660 loss: 4.9008 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.0909 loss_aux: 1.8099 2023/02/17 12:37:25 - mmengine - INFO - Epoch(train) [7][ 320/1345] lr: 1.0000e-02 eta: 10:50:05 time: 0.1905 data_time: 0.0056 memory: 8327 grad_norm: 6.7756 loss: 4.7731 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9879 loss_aux: 1.7852 2023/02/17 12:37:29 - mmengine - INFO - Epoch(train) [7][ 340/1345] lr: 1.0000e-02 eta: 10:49:55 time: 0.1894 data_time: 0.0054 memory: 8327 grad_norm: 6.6260 loss: 4.7814 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0171 loss_aux: 1.7643 2023/02/17 12:37:33 - mmengine - INFO - Epoch(train) [7][ 360/1345] lr: 1.0000e-02 eta: 10:49:46 time: 0.1909 data_time: 0.0060 memory: 8327 grad_norm: 6.6994 loss: 4.7314 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9869 loss_aux: 1.7444 2023/02/17 12:37:37 - mmengine - INFO - Epoch(train) [7][ 380/1345] lr: 1.0000e-02 eta: 10:49:37 time: 0.1900 data_time: 0.0048 memory: 8327 grad_norm: 6.6012 loss: 4.6831 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.9002 loss_aux: 1.7829 2023/02/17 12:37:40 - mmengine - INFO - Epoch(train) [7][ 400/1345] lr: 1.0000e-02 eta: 10:49:28 time: 0.1903 data_time: 0.0053 memory: 8327 grad_norm: 6.9170 loss: 4.9010 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.0310 loss_aux: 1.8700 2023/02/17 12:37:44 - mmengine - INFO - Epoch(train) [7][ 420/1345] lr: 1.0000e-02 eta: 10:49:20 time: 0.1940 data_time: 0.0056 memory: 8327 grad_norm: 6.7404 loss: 4.7365 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9914 loss_aux: 1.7451 2023/02/17 12:37:48 - mmengine - INFO - Epoch(train) [7][ 440/1345] lr: 1.0000e-02 eta: 10:49:11 time: 0.1911 data_time: 0.0053 memory: 8327 grad_norm: 6.7765 loss: 4.8642 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0183 loss_aux: 1.8459 2023/02/17 12:37:52 - mmengine - INFO - Epoch(train) [7][ 460/1345] lr: 1.0000e-02 eta: 10:49:03 time: 0.1910 data_time: 0.0055 memory: 8327 grad_norm: 6.6917 loss: 4.2555 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5852 loss_aux: 1.6703 2023/02/17 12:37:56 - mmengine - INFO - Epoch(train) [7][ 480/1345] lr: 1.0000e-02 eta: 10:48:55 time: 0.1925 data_time: 0.0058 memory: 8327 grad_norm: 6.6475 loss: 4.9255 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0910 loss_aux: 1.8345 2023/02/17 12:38:00 - mmengine - INFO - Epoch(train) [7][ 500/1345] lr: 1.0000e-02 eta: 10:48:45 time: 0.1901 data_time: 0.0052 memory: 8327 grad_norm: 6.5948 loss: 5.0773 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.1858 loss_aux: 1.8915 2023/02/17 12:38:03 - mmengine - INFO - Epoch(train) [7][ 520/1345] lr: 1.0000e-02 eta: 10:48:37 time: 0.1912 data_time: 0.0056 memory: 8327 grad_norm: 6.7430 loss: 4.8204 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0105 loss_aux: 1.8099 2023/02/17 12:38:07 - mmengine - INFO - Epoch(train) [7][ 540/1345] lr: 1.0000e-02 eta: 10:48:28 time: 0.1906 data_time: 0.0055 memory: 8327 grad_norm: 6.6108 loss: 4.6548 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8755 loss_aux: 1.7793 2023/02/17 12:38:11 - mmengine - INFO - Epoch(train) [7][ 560/1345] lr: 1.0000e-02 eta: 10:48:19 time: 0.1913 data_time: 0.0055 memory: 8327 grad_norm: 6.5884 loss: 4.6087 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8015 loss_aux: 1.8072 2023/02/17 12:38:15 - mmengine - INFO - Epoch(train) [7][ 580/1345] lr: 1.0000e-02 eta: 10:48:10 time: 0.1901 data_time: 0.0055 memory: 8327 grad_norm: 6.5646 loss: 4.7796 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9344 loss_aux: 1.8452 2023/02/17 12:38:19 - mmengine - INFO - Epoch(train) [7][ 600/1345] lr: 1.0000e-02 eta: 10:48:01 time: 0.1910 data_time: 0.0055 memory: 8327 grad_norm: 6.8345 loss: 4.7366 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9694 loss_aux: 1.7672 2023/02/17 12:38:22 - mmengine - INFO - Epoch(train) [7][ 620/1345] lr: 1.0000e-02 eta: 10:47:53 time: 0.1915 data_time: 0.0057 memory: 8327 grad_norm: 6.6784 loss: 4.7731 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9538 loss_aux: 1.8193 2023/02/17 12:38:26 - mmengine - INFO - Epoch(train) [7][ 640/1345] lr: 1.0000e-02 eta: 10:47:45 time: 0.1915 data_time: 0.0055 memory: 8327 grad_norm: 6.5077 loss: 4.6911 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8877 loss_aux: 1.8035 2023/02/17 12:38:30 - mmengine - INFO - Epoch(train) [7][ 660/1345] lr: 1.0000e-02 eta: 10:47:36 time: 0.1897 data_time: 0.0052 memory: 8327 grad_norm: 6.7552 loss: 4.6506 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.8849 loss_aux: 1.7657 2023/02/17 12:38:34 - mmengine - INFO - Epoch(train) [7][ 680/1345] lr: 1.0000e-02 eta: 10:47:27 time: 0.1912 data_time: 0.0058 memory: 8327 grad_norm: 6.7619 loss: 4.4686 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7012 loss_aux: 1.7674 2023/02/17 12:38:38 - mmengine - INFO - Epoch(train) [7][ 700/1345] lr: 1.0000e-02 eta: 10:47:18 time: 0.1904 data_time: 0.0054 memory: 8327 grad_norm: 6.7338 loss: 4.9135 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0525 loss_aux: 1.8609 2023/02/17 12:38:42 - mmengine - INFO - Epoch(train) [7][ 720/1345] lr: 1.0000e-02 eta: 10:47:10 time: 0.1911 data_time: 0.0056 memory: 8327 grad_norm: 6.6611 loss: 4.7114 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9187 loss_aux: 1.7928 2023/02/17 12:38:45 - mmengine - INFO - Epoch(train) [7][ 740/1345] lr: 1.0000e-02 eta: 10:47:01 time: 0.1909 data_time: 0.0059 memory: 8327 grad_norm: 6.8647 loss: 4.8722 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0241 loss_aux: 1.8481 2023/02/17 12:38:49 - mmengine - INFO - Epoch(train) [7][ 760/1345] lr: 1.0000e-02 eta: 10:46:52 time: 0.1906 data_time: 0.0055 memory: 8327 grad_norm: 6.7683 loss: 4.5010 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7561 loss_aux: 1.7449 2023/02/17 12:38:53 - mmengine - INFO - Epoch(train) [7][ 780/1345] lr: 1.0000e-02 eta: 10:46:44 time: 0.1906 data_time: 0.0054 memory: 8327 grad_norm: 6.6022 loss: 4.8238 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9640 loss_aux: 1.8597 2023/02/17 12:38:57 - mmengine - INFO - Epoch(train) [7][ 800/1345] lr: 1.0000e-02 eta: 10:46:35 time: 0.1904 data_time: 0.0055 memory: 8327 grad_norm: 6.8302 loss: 4.8939 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0218 loss_aux: 1.8721 2023/02/17 12:39:01 - mmengine - INFO - Epoch(train) [7][ 820/1345] lr: 1.0000e-02 eta: 10:46:27 time: 0.1910 data_time: 0.0053 memory: 8327 grad_norm: 6.7222 loss: 4.8016 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 3.0139 loss_aux: 1.7877 2023/02/17 12:39:04 - mmengine - INFO - Epoch(train) [7][ 840/1345] lr: 1.0000e-02 eta: 10:46:18 time: 0.1901 data_time: 0.0057 memory: 8327 grad_norm: 6.5288 loss: 4.7801 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.9439 loss_aux: 1.8363 2023/02/17 12:39:08 - mmengine - INFO - Epoch(train) [7][ 860/1345] lr: 1.0000e-02 eta: 10:46:09 time: 0.1903 data_time: 0.0055 memory: 8327 grad_norm: 6.6708 loss: 4.6178 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8774 loss_aux: 1.7404 2023/02/17 12:39:12 - mmengine - INFO - Epoch(train) [7][ 880/1345] lr: 1.0000e-02 eta: 10:46:01 time: 0.1922 data_time: 0.0068 memory: 8327 grad_norm: 6.6680 loss: 4.7168 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9470 loss_aux: 1.7698 2023/02/17 12:39:16 - mmengine - INFO - Epoch(train) [7][ 900/1345] lr: 1.0000e-02 eta: 10:45:53 time: 0.1904 data_time: 0.0051 memory: 8327 grad_norm: 6.6396 loss: 4.5656 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.8435 loss_aux: 1.7221 2023/02/17 12:39:20 - mmengine - INFO - Epoch(train) [7][ 920/1345] lr: 1.0000e-02 eta: 10:45:45 time: 0.1916 data_time: 0.0055 memory: 8327 grad_norm: 6.5482 loss: 4.3192 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.6636 loss_aux: 1.6556 2023/02/17 12:39:22 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:39:24 - mmengine - INFO - Epoch(train) [7][ 940/1345] lr: 1.0000e-02 eta: 10:45:37 time: 0.1914 data_time: 0.0057 memory: 8327 grad_norm: 6.3401 loss: 4.6633 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8426 loss_aux: 1.8207 2023/02/17 12:39:27 - mmengine - INFO - Epoch(train) [7][ 960/1345] lr: 1.0000e-02 eta: 10:45:28 time: 0.1909 data_time: 0.0059 memory: 8327 grad_norm: 6.6429 loss: 5.1044 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.2072 loss_aux: 1.8972 2023/02/17 12:39:31 - mmengine - INFO - Epoch(train) [7][ 980/1345] lr: 1.0000e-02 eta: 10:45:20 time: 0.1914 data_time: 0.0051 memory: 8327 grad_norm: 6.7114 loss: 4.5090 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7611 loss_aux: 1.7479 2023/02/17 12:39:35 - mmengine - INFO - Epoch(train) [7][1000/1345] lr: 1.0000e-02 eta: 10:45:12 time: 0.1905 data_time: 0.0055 memory: 8327 grad_norm: 6.6691 loss: 4.7475 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9918 loss_aux: 1.7557 2023/02/17 12:39:39 - mmengine - INFO - Epoch(train) [7][1020/1345] lr: 1.0000e-02 eta: 10:45:03 time: 0.1905 data_time: 0.0056 memory: 8327 grad_norm: 6.8235 loss: 4.5406 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7945 loss_aux: 1.7461 2023/02/17 12:39:43 - mmengine - INFO - Epoch(train) [7][1040/1345] lr: 1.0000e-02 eta: 10:44:55 time: 0.1905 data_time: 0.0055 memory: 8327 grad_norm: 6.7361 loss: 4.3075 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.5801 loss_aux: 1.7274 2023/02/17 12:39:46 - mmengine - INFO - Epoch(train) [7][1060/1345] lr: 1.0000e-02 eta: 10:44:46 time: 0.1903 data_time: 0.0056 memory: 8327 grad_norm: 6.6802 loss: 4.6417 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8587 loss_aux: 1.7830 2023/02/17 12:39:50 - mmengine - INFO - Epoch(train) [7][1080/1345] lr: 1.0000e-02 eta: 10:44:40 time: 0.1940 data_time: 0.0088 memory: 8327 grad_norm: 6.5583 loss: 4.4650 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7522 loss_aux: 1.7128 2023/02/17 12:39:54 - mmengine - INFO - Epoch(train) [7][1100/1345] lr: 1.0000e-02 eta: 10:44:31 time: 0.1911 data_time: 0.0033 memory: 8327 grad_norm: 6.6919 loss: 4.7983 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.9871 loss_aux: 1.8112 2023/02/17 12:39:58 - mmengine - INFO - Epoch(train) [7][1120/1345] lr: 1.0000e-02 eta: 10:44:23 time: 0.1904 data_time: 0.0039 memory: 8327 grad_norm: 6.6644 loss: 4.4548 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7709 loss_aux: 1.6839 2023/02/17 12:40:02 - mmengine - INFO - Epoch(train) [7][1140/1345] lr: 1.0000e-02 eta: 10:44:15 time: 0.1903 data_time: 0.0052 memory: 8327 grad_norm: 6.6922 loss: 4.6003 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8875 loss_aux: 1.7129 2023/02/17 12:40:06 - mmengine - INFO - Epoch(train) [7][1160/1345] lr: 1.0000e-02 eta: 10:44:07 time: 0.1916 data_time: 0.0058 memory: 8327 grad_norm: 6.5922 loss: 4.5228 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7429 loss_aux: 1.7799 2023/02/17 12:40:09 - mmengine - INFO - Epoch(train) [7][1180/1345] lr: 1.0000e-02 eta: 10:43:59 time: 0.1927 data_time: 0.0072 memory: 8327 grad_norm: 6.6697 loss: 5.2426 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.3664 loss_aux: 1.8761 2023/02/17 12:40:13 - mmengine - INFO - Epoch(train) [7][1200/1345] lr: 1.0000e-02 eta: 10:43:51 time: 0.1904 data_time: 0.0055 memory: 8327 grad_norm: 6.6568 loss: 4.6239 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8731 loss_aux: 1.7508 2023/02/17 12:40:17 - mmengine - INFO - Epoch(train) [7][1220/1345] lr: 1.0000e-02 eta: 10:43:43 time: 0.1916 data_time: 0.0059 memory: 8327 grad_norm: 6.6821 loss: 4.6558 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8698 loss_aux: 1.7860 2023/02/17 12:40:21 - mmengine - INFO - Epoch(train) [7][1240/1345] lr: 1.0000e-02 eta: 10:43:35 time: 0.1902 data_time: 0.0054 memory: 8327 grad_norm: 6.6005 loss: 4.4851 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7731 loss_aux: 1.7120 2023/02/17 12:40:25 - mmengine - INFO - Epoch(train) [7][1260/1345] lr: 1.0000e-02 eta: 10:43:27 time: 0.1919 data_time: 0.0053 memory: 8327 grad_norm: 6.6684 loss: 4.3068 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6585 loss_aux: 1.6483 2023/02/17 12:40:29 - mmengine - INFO - Epoch(train) [7][1280/1345] lr: 1.0000e-02 eta: 10:43:19 time: 0.1907 data_time: 0.0057 memory: 8327 grad_norm: 6.6720 loss: 4.6885 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8568 loss_aux: 1.8318 2023/02/17 12:40:32 - mmengine - INFO - Epoch(train) [7][1300/1345] lr: 1.0000e-02 eta: 10:43:11 time: 0.1906 data_time: 0.0052 memory: 8327 grad_norm: 6.6750 loss: 4.9216 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.0902 loss_aux: 1.8314 2023/02/17 12:40:36 - mmengine - INFO - Epoch(train) [7][1320/1345] lr: 1.0000e-02 eta: 10:43:03 time: 0.1907 data_time: 0.0059 memory: 8327 grad_norm: 6.5006 loss: 4.8000 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.9247 loss_aux: 1.8753 2023/02/17 12:40:40 - mmengine - INFO - Epoch(train) [7][1340/1345] lr: 1.0000e-02 eta: 10:42:55 time: 0.1896 data_time: 0.0054 memory: 8327 grad_norm: 6.6002 loss: 4.6116 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8508 loss_aux: 1.7609 2023/02/17 12:40:41 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:40:41 - mmengine - INFO - Epoch(train) [7][1345/1345] lr: 1.0000e-02 eta: 10:42:50 time: 0.1834 data_time: 0.0052 memory: 8327 grad_norm: 6.6289 loss: 4.6849 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.8760 loss_aux: 1.8089 2023/02/17 12:40:41 - mmengine - INFO - Saving checkpoint at 7 epochs 2023/02/17 12:40:48 - mmengine - INFO - Epoch(train) [8][ 20/1345] lr: 1.0000e-02 eta: 10:42:58 time: 0.2305 data_time: 0.0376 memory: 8327 grad_norm: 6.7308 loss: 4.8899 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 3.0592 loss_aux: 1.8308 2023/02/17 12:40:52 - mmengine - INFO - Epoch(train) [8][ 40/1345] lr: 1.0000e-02 eta: 10:42:50 time: 0.1907 data_time: 0.0048 memory: 8327 grad_norm: 6.6259 loss: 4.5353 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7931 loss_aux: 1.7422 2023/02/17 12:40:55 - mmengine - INFO - Epoch(train) [8][ 60/1345] lr: 1.0000e-02 eta: 10:42:42 time: 0.1905 data_time: 0.0058 memory: 8327 grad_norm: 6.6820 loss: 4.9726 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.1300 loss_aux: 1.8426 2023/02/17 12:40:59 - mmengine - INFO - Epoch(train) [8][ 80/1345] lr: 1.0000e-02 eta: 10:42:34 time: 0.1902 data_time: 0.0056 memory: 8327 grad_norm: 6.7677 loss: 4.8135 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.0191 loss_aux: 1.7944 2023/02/17 12:41:03 - mmengine - INFO - Epoch(train) [8][ 100/1345] lr: 1.0000e-02 eta: 10:42:25 time: 0.1898 data_time: 0.0053 memory: 8327 grad_norm: 6.6196 loss: 4.7247 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9326 loss_aux: 1.7921 2023/02/17 12:41:07 - mmengine - INFO - Epoch(train) [8][ 120/1345] lr: 1.0000e-02 eta: 10:42:18 time: 0.1914 data_time: 0.0056 memory: 8327 grad_norm: 6.8254 loss: 4.4511 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7211 loss_aux: 1.7300 2023/02/17 12:41:11 - mmengine - INFO - Epoch(train) [8][ 140/1345] lr: 1.0000e-02 eta: 10:42:10 time: 0.1903 data_time: 0.0055 memory: 8327 grad_norm: 6.6134 loss: 4.4244 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7280 loss_aux: 1.6964 2023/02/17 12:41:15 - mmengine - INFO - Epoch(train) [8][ 160/1345] lr: 1.0000e-02 eta: 10:42:02 time: 0.1908 data_time: 0.0052 memory: 8327 grad_norm: 6.6459 loss: 4.5220 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8356 loss_aux: 1.6864 2023/02/17 12:41:18 - mmengine - INFO - Epoch(train) [8][ 180/1345] lr: 1.0000e-02 eta: 10:41:54 time: 0.1907 data_time: 0.0057 memory: 8327 grad_norm: 6.8002 loss: 4.6635 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8761 loss_aux: 1.7874 2023/02/17 12:41:22 - mmengine - INFO - Epoch(train) [8][ 200/1345] lr: 1.0000e-02 eta: 10:41:46 time: 0.1899 data_time: 0.0055 memory: 8327 grad_norm: 6.7961 loss: 4.4193 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7565 loss_aux: 1.6627 2023/02/17 12:41:26 - mmengine - INFO - Epoch(train) [8][ 220/1345] lr: 1.0000e-02 eta: 10:41:38 time: 0.1917 data_time: 0.0052 memory: 8327 grad_norm: 6.6421 loss: 4.6597 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8968 loss_aux: 1.7629 2023/02/17 12:41:30 - mmengine - INFO - Epoch(train) [8][ 240/1345] lr: 1.0000e-02 eta: 10:41:31 time: 0.1920 data_time: 0.0055 memory: 8327 grad_norm: 6.5872 loss: 4.4789 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7263 loss_aux: 1.7526 2023/02/17 12:41:34 - mmengine - INFO - Epoch(train) [8][ 260/1345] lr: 1.0000e-02 eta: 10:41:23 time: 0.1900 data_time: 0.0053 memory: 8327 grad_norm: 6.6979 loss: 4.6442 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8199 loss_aux: 1.8243 2023/02/17 12:41:37 - mmengine - INFO - Epoch(train) [8][ 280/1345] lr: 1.0000e-02 eta: 10:41:15 time: 0.1911 data_time: 0.0055 memory: 8327 grad_norm: 6.6213 loss: 4.7315 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9024 loss_aux: 1.8291 2023/02/17 12:41:41 - mmengine - INFO - Epoch(train) [8][ 300/1345] lr: 1.0000e-02 eta: 10:41:07 time: 0.1900 data_time: 0.0054 memory: 8327 grad_norm: 6.6459 loss: 4.8492 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9928 loss_aux: 1.8564 2023/02/17 12:41:45 - mmengine - INFO - Epoch(train) [8][ 320/1345] lr: 1.0000e-02 eta: 10:40:59 time: 0.1903 data_time: 0.0055 memory: 8327 grad_norm: 6.7173 loss: 4.5798 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8242 loss_aux: 1.7556 2023/02/17 12:41:49 - mmengine - INFO - Epoch(train) [8][ 340/1345] lr: 1.0000e-02 eta: 10:40:51 time: 0.1913 data_time: 0.0066 memory: 8327 grad_norm: 6.7258 loss: 4.7779 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9587 loss_aux: 1.8191 2023/02/17 12:41:53 - mmengine - INFO - Epoch(train) [8][ 360/1345] lr: 1.0000e-02 eta: 10:40:44 time: 0.1906 data_time: 0.0058 memory: 8327 grad_norm: 6.7666 loss: 4.4286 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6651 loss_aux: 1.7635 2023/02/17 12:41:56 - mmengine - INFO - Epoch(train) [8][ 380/1345] lr: 1.0000e-02 eta: 10:40:36 time: 0.1908 data_time: 0.0053 memory: 8327 grad_norm: 6.7366 loss: 4.1470 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5328 loss_aux: 1.6142 2023/02/17 12:42:00 - mmengine - INFO - Epoch(train) [8][ 400/1345] lr: 1.0000e-02 eta: 10:40:28 time: 0.1902 data_time: 0.0054 memory: 8327 grad_norm: 6.6606 loss: 4.7007 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9017 loss_aux: 1.7990 2023/02/17 12:42:04 - mmengine - INFO - Epoch(train) [8][ 420/1345] lr: 1.0000e-02 eta: 10:40:20 time: 0.1910 data_time: 0.0056 memory: 8327 grad_norm: 6.6651 loss: 4.3869 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6916 loss_aux: 1.6952 2023/02/17 12:42:08 - mmengine - INFO - Epoch(train) [8][ 440/1345] lr: 1.0000e-02 eta: 10:40:13 time: 0.1918 data_time: 0.0056 memory: 8327 grad_norm: 6.6905 loss: 4.4035 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6913 loss_aux: 1.7123 2023/02/17 12:42:12 - mmengine - INFO - Epoch(train) [8][ 460/1345] lr: 1.0000e-02 eta: 10:40:05 time: 0.1909 data_time: 0.0054 memory: 8327 grad_norm: 6.7266 loss: 4.8999 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0978 loss_aux: 1.8021 2023/02/17 12:42:16 - mmengine - INFO - Epoch(train) [8][ 480/1345] lr: 1.0000e-02 eta: 10:39:58 time: 0.1906 data_time: 0.0055 memory: 8327 grad_norm: 6.5689 loss: 4.6273 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8596 loss_aux: 1.7677 2023/02/17 12:42:19 - mmengine - INFO - Epoch(train) [8][ 500/1345] lr: 1.0000e-02 eta: 10:39:51 time: 0.1939 data_time: 0.0059 memory: 8327 grad_norm: 6.7289 loss: 4.5180 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8343 loss_aux: 1.6837 2023/02/17 12:42:23 - mmengine - INFO - Epoch(train) [8][ 520/1345] lr: 1.0000e-02 eta: 10:39:45 time: 0.1941 data_time: 0.0072 memory: 8327 grad_norm: 6.7453 loss: 4.4475 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7055 loss_aux: 1.7420 2023/02/17 12:42:27 - mmengine - INFO - Epoch(train) [8][ 540/1345] lr: 1.0000e-02 eta: 10:39:37 time: 0.1908 data_time: 0.0053 memory: 8327 grad_norm: 6.5680 loss: 4.3832 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6975 loss_aux: 1.6857 2023/02/17 12:42:31 - mmengine - INFO - Epoch(train) [8][ 560/1345] lr: 1.0000e-02 eta: 10:39:30 time: 0.1903 data_time: 0.0054 memory: 8327 grad_norm: 6.7683 loss: 4.4533 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7488 loss_aux: 1.7045 2023/02/17 12:42:35 - mmengine - INFO - Epoch(train) [8][ 580/1345] lr: 1.0000e-02 eta: 10:39:22 time: 0.1909 data_time: 0.0057 memory: 8327 grad_norm: 6.6775 loss: 4.4577 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7685 loss_aux: 1.6892 2023/02/17 12:42:36 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:42:39 - mmengine - INFO - Epoch(train) [8][ 600/1345] lr: 1.0000e-02 eta: 10:39:15 time: 0.1914 data_time: 0.0053 memory: 8327 grad_norm: 6.6535 loss: 4.8357 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 3.0560 loss_aux: 1.7797 2023/02/17 12:42:42 - mmengine - INFO - Epoch(train) [8][ 620/1345] lr: 1.0000e-02 eta: 10:39:07 time: 0.1907 data_time: 0.0055 memory: 8327 grad_norm: 6.6672 loss: 4.5627 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8143 loss_aux: 1.7484 2023/02/17 12:42:46 - mmengine - INFO - Epoch(train) [8][ 640/1345] lr: 1.0000e-02 eta: 10:39:00 time: 0.1903 data_time: 0.0057 memory: 8327 grad_norm: 6.8171 loss: 4.3855 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6509 loss_aux: 1.7346 2023/02/17 12:42:50 - mmengine - INFO - Epoch(train) [8][ 660/1345] lr: 1.0000e-02 eta: 10:38:53 time: 0.1935 data_time: 0.0055 memory: 8327 grad_norm: 6.8086 loss: 4.6497 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9090 loss_aux: 1.7406 2023/02/17 12:42:54 - mmengine - INFO - Epoch(train) [8][ 680/1345] lr: 1.0000e-02 eta: 10:38:45 time: 0.1895 data_time: 0.0053 memory: 8327 grad_norm: 6.9424 loss: 4.5708 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8627 loss_aux: 1.7081 2023/02/17 12:42:58 - mmengine - INFO - Epoch(train) [8][ 700/1345] lr: 1.0000e-02 eta: 10:38:37 time: 0.1904 data_time: 0.0057 memory: 8327 grad_norm: 6.8971 loss: 4.5784 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7948 loss_aux: 1.7836 2023/02/17 12:43:02 - mmengine - INFO - Epoch(train) [8][ 720/1345] lr: 1.0000e-02 eta: 10:38:30 time: 0.1907 data_time: 0.0054 memory: 8327 grad_norm: 6.6814 loss: 4.4862 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7961 loss_aux: 1.6901 2023/02/17 12:43:05 - mmengine - INFO - Epoch(train) [8][ 740/1345] lr: 1.0000e-02 eta: 10:38:22 time: 0.1902 data_time: 0.0055 memory: 8327 grad_norm: 6.6323 loss: 4.5557 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7878 loss_aux: 1.7679 2023/02/17 12:43:09 - mmengine - INFO - Epoch(train) [8][ 760/1345] lr: 1.0000e-02 eta: 10:38:15 time: 0.1909 data_time: 0.0056 memory: 8327 grad_norm: 6.6932 loss: 4.5422 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8375 loss_aux: 1.7047 2023/02/17 12:43:13 - mmengine - INFO - Epoch(train) [8][ 780/1345] lr: 1.0000e-02 eta: 10:38:08 time: 0.1909 data_time: 0.0066 memory: 8327 grad_norm: 6.6210 loss: 4.4154 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7066 loss_aux: 1.7087 2023/02/17 12:43:17 - mmengine - INFO - Epoch(train) [8][ 800/1345] lr: 1.0000e-02 eta: 10:38:00 time: 0.1898 data_time: 0.0046 memory: 8327 grad_norm: 6.6705 loss: 4.5951 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8722 loss_aux: 1.7229 2023/02/17 12:43:21 - mmengine - INFO - Epoch(train) [8][ 820/1345] lr: 1.0000e-02 eta: 10:37:53 time: 0.1912 data_time: 0.0054 memory: 8327 grad_norm: 6.7609 loss: 4.4084 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6858 loss_aux: 1.7225 2023/02/17 12:43:24 - mmengine - INFO - Epoch(train) [8][ 840/1345] lr: 1.0000e-02 eta: 10:37:45 time: 0.1902 data_time: 0.0055 memory: 8327 grad_norm: 6.6745 loss: 4.2921 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6523 loss_aux: 1.6398 2023/02/17 12:43:28 - mmengine - INFO - Epoch(train) [8][ 860/1345] lr: 1.0000e-02 eta: 10:37:38 time: 0.1906 data_time: 0.0054 memory: 8327 grad_norm: 6.5510 loss: 4.9320 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.0931 loss_aux: 1.8388 2023/02/17 12:43:32 - mmengine - INFO - Epoch(train) [8][ 880/1345] lr: 1.0000e-02 eta: 10:37:30 time: 0.1901 data_time: 0.0057 memory: 8327 grad_norm: 6.6967 loss: 4.2133 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5766 loss_aux: 1.6366 2023/02/17 12:43:36 - mmengine - INFO - Epoch(train) [8][ 900/1345] lr: 1.0000e-02 eta: 10:37:23 time: 0.1910 data_time: 0.0051 memory: 8327 grad_norm: 6.6190 loss: 4.2564 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6065 loss_aux: 1.6499 2023/02/17 12:43:40 - mmengine - INFO - Epoch(train) [8][ 920/1345] lr: 1.0000e-02 eta: 10:37:15 time: 0.1907 data_time: 0.0054 memory: 8327 grad_norm: 6.9843 loss: 4.6739 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8915 loss_aux: 1.7824 2023/02/17 12:43:43 - mmengine - INFO - Epoch(train) [8][ 940/1345] lr: 1.0000e-02 eta: 10:37:08 time: 0.1907 data_time: 0.0057 memory: 8327 grad_norm: 6.7405 loss: 4.0740 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4659 loss_aux: 1.6082 2023/02/17 12:43:47 - mmengine - INFO - Epoch(train) [8][ 960/1345] lr: 1.0000e-02 eta: 10:37:00 time: 0.1903 data_time: 0.0053 memory: 8327 grad_norm: 6.8535 loss: 4.7330 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9523 loss_aux: 1.7806 2023/02/17 12:43:51 - mmengine - INFO - Epoch(train) [8][ 980/1345] lr: 1.0000e-02 eta: 10:36:53 time: 0.1908 data_time: 0.0054 memory: 8327 grad_norm: 6.6823 loss: 4.4676 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.7094 loss_aux: 1.7582 2023/02/17 12:43:55 - mmengine - INFO - Epoch(train) [8][1000/1345] lr: 1.0000e-02 eta: 10:36:46 time: 0.1905 data_time: 0.0056 memory: 8327 grad_norm: 6.8935 loss: 4.6629 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8149 loss_aux: 1.8480 2023/02/17 12:43:59 - mmengine - INFO - Epoch(train) [8][1020/1345] lr: 1.0000e-02 eta: 10:36:39 time: 0.1909 data_time: 0.0054 memory: 8327 grad_norm: 6.6583 loss: 4.3207 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.6984 loss_aux: 1.6223 2023/02/17 12:44:03 - mmengine - INFO - Epoch(train) [8][1040/1345] lr: 1.0000e-02 eta: 10:36:32 time: 0.1916 data_time: 0.0053 memory: 8327 grad_norm: 6.6702 loss: 4.6124 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8540 loss_aux: 1.7584 2023/02/17 12:44:06 - mmengine - INFO - Epoch(train) [8][1060/1345] lr: 1.0000e-02 eta: 10:36:24 time: 0.1897 data_time: 0.0054 memory: 8327 grad_norm: 6.5352 loss: 4.5077 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8366 loss_aux: 1.6711 2023/02/17 12:44:10 - mmengine - INFO - Epoch(train) [8][1080/1345] lr: 1.0000e-02 eta: 10:36:17 time: 0.1913 data_time: 0.0055 memory: 8327 grad_norm: 6.7247 loss: 4.4206 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7303 loss_aux: 1.6903 2023/02/17 12:44:14 - mmengine - INFO - Epoch(train) [8][1100/1345] lr: 1.0000e-02 eta: 10:36:10 time: 0.1908 data_time: 0.0055 memory: 8327 grad_norm: 6.5476 loss: 4.4918 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7669 loss_aux: 1.7249 2023/02/17 12:44:18 - mmengine - INFO - Epoch(train) [8][1120/1345] lr: 1.0000e-02 eta: 10:36:02 time: 0.1902 data_time: 0.0055 memory: 8327 grad_norm: 6.6854 loss: 4.5531 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8206 loss_aux: 1.7325 2023/02/17 12:44:22 - mmengine - INFO - Epoch(train) [8][1140/1345] lr: 1.0000e-02 eta: 10:35:55 time: 0.1915 data_time: 0.0055 memory: 8327 grad_norm: 6.6903 loss: 4.5338 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7680 loss_aux: 1.7658 2023/02/17 12:44:25 - mmengine - INFO - Epoch(train) [8][1160/1345] lr: 1.0000e-02 eta: 10:35:48 time: 0.1904 data_time: 0.0052 memory: 8327 grad_norm: 6.7383 loss: 4.2631 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5869 loss_aux: 1.6762 2023/02/17 12:44:29 - mmengine - INFO - Epoch(train) [8][1180/1345] lr: 1.0000e-02 eta: 10:35:41 time: 0.1909 data_time: 0.0055 memory: 8327 grad_norm: 6.8035 loss: 4.5337 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7649 loss_aux: 1.7689 2023/02/17 12:44:33 - mmengine - INFO - Epoch(train) [8][1200/1345] lr: 1.0000e-02 eta: 10:35:34 time: 0.1903 data_time: 0.0056 memory: 8327 grad_norm: 6.8914 loss: 4.3541 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7124 loss_aux: 1.6418 2023/02/17 12:44:37 - mmengine - INFO - Epoch(train) [8][1220/1345] lr: 1.0000e-02 eta: 10:35:26 time: 0.1898 data_time: 0.0052 memory: 8327 grad_norm: 6.7456 loss: 4.3524 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6355 loss_aux: 1.7168 2023/02/17 12:44:41 - mmengine - INFO - Epoch(train) [8][1240/1345] lr: 1.0000e-02 eta: 10:35:19 time: 0.1911 data_time: 0.0055 memory: 8327 grad_norm: 6.8733 loss: 4.5172 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8472 loss_aux: 1.6700 2023/02/17 12:44:44 - mmengine - INFO - Epoch(train) [8][1260/1345] lr: 1.0000e-02 eta: 10:35:12 time: 0.1902 data_time: 0.0060 memory: 8327 grad_norm: 6.5583 loss: 4.6831 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9136 loss_aux: 1.7695 2023/02/17 12:44:48 - mmengine - INFO - Epoch(train) [8][1280/1345] lr: 1.0000e-02 eta: 10:35:05 time: 0.1916 data_time: 0.0069 memory: 8327 grad_norm: 6.6028 loss: 4.6109 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8259 loss_aux: 1.7850 2023/02/17 12:44:52 - mmengine - INFO - Epoch(train) [8][1300/1345] lr: 1.0000e-02 eta: 10:34:58 time: 0.1904 data_time: 0.0054 memory: 8327 grad_norm: 6.6137 loss: 4.8002 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9981 loss_aux: 1.8020 2023/02/17 12:44:56 - mmengine - INFO - Epoch(train) [8][1320/1345] lr: 1.0000e-02 eta: 10:34:51 time: 0.1909 data_time: 0.0063 memory: 8327 grad_norm: 6.7154 loss: 4.5412 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.8116 loss_aux: 1.7296 2023/02/17 12:45:00 - mmengine - INFO - Epoch(train) [8][1340/1345] lr: 1.0000e-02 eta: 10:34:43 time: 0.1898 data_time: 0.0052 memory: 8327 grad_norm: 6.6612 loss: 4.5851 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8048 loss_aux: 1.7803 2023/02/17 12:45:01 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:45:01 - mmengine - INFO - Epoch(train) [8][1345/1345] lr: 1.0000e-02 eta: 10:34:39 time: 0.1836 data_time: 0.0054 memory: 8327 grad_norm: 6.6412 loss: 4.5944 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.7952 loss_aux: 1.7992 2023/02/17 12:45:01 - mmengine - INFO - Saving checkpoint at 8 epochs 2023/02/17 12:45:08 - mmengine - INFO - Epoch(train) [9][ 20/1345] lr: 1.0000e-02 eta: 10:34:47 time: 0.2329 data_time: 0.0404 memory: 8327 grad_norm: 6.6646 loss: 4.2178 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5271 loss_aux: 1.6907 2023/02/17 12:45:12 - mmengine - INFO - Epoch(train) [9][ 40/1345] lr: 1.0000e-02 eta: 10:34:41 time: 0.1922 data_time: 0.0044 memory: 8327 grad_norm: 6.5756 loss: 4.2266 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5484 loss_aux: 1.6782 2023/02/17 12:45:15 - mmengine - INFO - Epoch(train) [9][ 60/1345] lr: 1.0000e-02 eta: 10:34:34 time: 0.1909 data_time: 0.0056 memory: 8327 grad_norm: 6.6990 loss: 4.3798 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6749 loss_aux: 1.7049 2023/02/17 12:45:19 - mmengine - INFO - Epoch(train) [9][ 80/1345] lr: 1.0000e-02 eta: 10:34:27 time: 0.1906 data_time: 0.0054 memory: 8327 grad_norm: 6.7884 loss: 4.4603 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7428 loss_aux: 1.7175 2023/02/17 12:45:23 - mmengine - INFO - Epoch(train) [9][ 100/1345] lr: 1.0000e-02 eta: 10:34:20 time: 0.1914 data_time: 0.0067 memory: 8327 grad_norm: 6.7749 loss: 4.6509 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8513 loss_aux: 1.7996 2023/02/17 12:45:27 - mmengine - INFO - Epoch(train) [9][ 120/1345] lr: 1.0000e-02 eta: 10:34:12 time: 0.1897 data_time: 0.0054 memory: 8327 grad_norm: 6.5881 loss: 4.6887 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9290 loss_aux: 1.7597 2023/02/17 12:45:31 - mmengine - INFO - Epoch(train) [9][ 140/1345] lr: 1.0000e-02 eta: 10:34:06 time: 0.1911 data_time: 0.0057 memory: 8327 grad_norm: 6.8583 loss: 4.4095 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7406 loss_aux: 1.6689 2023/02/17 12:45:35 - mmengine - INFO - Epoch(train) [9][ 160/1345] lr: 1.0000e-02 eta: 10:33:58 time: 0.1902 data_time: 0.0053 memory: 8327 grad_norm: 6.6970 loss: 4.3422 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6714 loss_aux: 1.6708 2023/02/17 12:45:38 - mmengine - INFO - Epoch(train) [9][ 180/1345] lr: 1.0000e-02 eta: 10:33:52 time: 0.1912 data_time: 0.0058 memory: 8327 grad_norm: 6.8278 loss: 4.3246 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6095 loss_aux: 1.7151 2023/02/17 12:45:42 - mmengine - INFO - Epoch(train) [9][ 200/1345] lr: 1.0000e-02 eta: 10:33:44 time: 0.1903 data_time: 0.0052 memory: 8327 grad_norm: 6.6330 loss: 4.2777 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6286 loss_aux: 1.6492 2023/02/17 12:45:46 - mmengine - INFO - Epoch(train) [9][ 220/1345] lr: 1.0000e-02 eta: 10:33:37 time: 0.1904 data_time: 0.0052 memory: 8327 grad_norm: 6.5136 loss: 4.3714 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6868 loss_aux: 1.6846 2023/02/17 12:45:50 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:45:50 - mmengine - INFO - Epoch(train) [9][ 240/1345] lr: 1.0000e-02 eta: 10:33:30 time: 0.1899 data_time: 0.0057 memory: 8327 grad_norm: 6.6819 loss: 4.6642 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8663 loss_aux: 1.7979 2023/02/17 12:45:54 - mmengine - INFO - Epoch(train) [9][ 260/1345] lr: 1.0000e-02 eta: 10:33:23 time: 0.1897 data_time: 0.0054 memory: 8327 grad_norm: 7.0478 loss: 4.4685 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7469 loss_aux: 1.7216 2023/02/17 12:45:57 - mmengine - INFO - Epoch(train) [9][ 280/1345] lr: 1.0000e-02 eta: 10:33:16 time: 0.1905 data_time: 0.0055 memory: 8327 grad_norm: 6.9726 loss: 4.4088 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7397 loss_aux: 1.6691 2023/02/17 12:46:01 - mmengine - INFO - Epoch(train) [9][ 300/1345] lr: 1.0000e-02 eta: 10:33:09 time: 0.1909 data_time: 0.0063 memory: 8327 grad_norm: 6.7599 loss: 4.4998 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8198 loss_aux: 1.6800 2023/02/17 12:46:05 - mmengine - INFO - Epoch(train) [9][ 320/1345] lr: 1.0000e-02 eta: 10:33:02 time: 0.1913 data_time: 0.0053 memory: 8327 grad_norm: 6.7325 loss: 4.0417 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4838 loss_aux: 1.5579 2023/02/17 12:46:09 - mmengine - INFO - Epoch(train) [9][ 340/1345] lr: 1.0000e-02 eta: 10:32:55 time: 0.1907 data_time: 0.0060 memory: 8327 grad_norm: 6.5651 loss: 4.3338 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6699 loss_aux: 1.6639 2023/02/17 12:46:13 - mmengine - INFO - Epoch(train) [9][ 360/1345] lr: 1.0000e-02 eta: 10:32:48 time: 0.1910 data_time: 0.0056 memory: 8327 grad_norm: 6.7224 loss: 4.6858 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8898 loss_aux: 1.7960 2023/02/17 12:46:16 - mmengine - INFO - Epoch(train) [9][ 380/1345] lr: 1.0000e-02 eta: 10:32:41 time: 0.1903 data_time: 0.0056 memory: 8327 grad_norm: 6.5785 loss: 4.5074 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7857 loss_aux: 1.7217 2023/02/17 12:46:20 - mmengine - INFO - Epoch(train) [9][ 400/1345] lr: 1.0000e-02 eta: 10:32:34 time: 0.1904 data_time: 0.0055 memory: 8327 grad_norm: 6.6233 loss: 4.2579 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6192 loss_aux: 1.6387 2023/02/17 12:46:24 - mmengine - INFO - Epoch(train) [9][ 420/1345] lr: 1.0000e-02 eta: 10:32:28 time: 0.1916 data_time: 0.0057 memory: 8327 grad_norm: 6.8245 loss: 4.2999 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6552 loss_aux: 1.6447 2023/02/17 12:46:28 - mmengine - INFO - Epoch(train) [9][ 440/1345] lr: 1.0000e-02 eta: 10:32:21 time: 0.1903 data_time: 0.0053 memory: 8327 grad_norm: 6.5694 loss: 4.4885 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7210 loss_aux: 1.7675 2023/02/17 12:46:32 - mmengine - INFO - Epoch(train) [9][ 460/1345] lr: 1.0000e-02 eta: 10:32:14 time: 0.1902 data_time: 0.0057 memory: 8327 grad_norm: 6.5645 loss: 4.4901 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7917 loss_aux: 1.6984 2023/02/17 12:46:36 - mmengine - INFO - Epoch(train) [9][ 480/1345] lr: 1.0000e-02 eta: 10:32:07 time: 0.1904 data_time: 0.0052 memory: 8327 grad_norm: 6.6962 loss: 4.6595 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9430 loss_aux: 1.7165 2023/02/17 12:46:39 - mmengine - INFO - Epoch(train) [9][ 500/1345] lr: 1.0000e-02 eta: 10:32:00 time: 0.1912 data_time: 0.0054 memory: 8327 grad_norm: 6.6246 loss: 4.6282 top1_acc: 0.0000 top5_acc: 0.7500 loss_cls: 2.8928 loss_aux: 1.7355 2023/02/17 12:46:43 - mmengine - INFO - Epoch(train) [9][ 520/1345] lr: 1.0000e-02 eta: 10:31:54 time: 0.1913 data_time: 0.0057 memory: 8327 grad_norm: 6.5052 loss: 4.5930 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8593 loss_aux: 1.7337 2023/02/17 12:46:47 - mmengine - INFO - Epoch(train) [9][ 540/1345] lr: 1.0000e-02 eta: 10:31:47 time: 0.1900 data_time: 0.0052 memory: 8327 grad_norm: 6.5706 loss: 4.3952 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7470 loss_aux: 1.6481 2023/02/17 12:46:51 - mmengine - INFO - Epoch(train) [9][ 560/1345] lr: 1.0000e-02 eta: 10:31:40 time: 0.1906 data_time: 0.0055 memory: 8327 grad_norm: 6.6945 loss: 4.5918 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8783 loss_aux: 1.7135 2023/02/17 12:46:55 - mmengine - INFO - Epoch(train) [9][ 580/1345] lr: 1.0000e-02 eta: 10:31:33 time: 0.1909 data_time: 0.0061 memory: 8327 grad_norm: 6.6006 loss: 4.3280 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6516 loss_aux: 1.6764 2023/02/17 12:46:58 - mmengine - INFO - Epoch(train) [9][ 600/1345] lr: 1.0000e-02 eta: 10:31:26 time: 0.1906 data_time: 0.0057 memory: 8327 grad_norm: 6.9225 loss: 4.2852 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.6343 loss_aux: 1.6509 2023/02/17 12:47:02 - mmengine - INFO - Epoch(train) [9][ 620/1345] lr: 1.0000e-02 eta: 10:31:19 time: 0.1902 data_time: 0.0053 memory: 8327 grad_norm: 6.6632 loss: 4.1380 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5321 loss_aux: 1.6059 2023/02/17 12:47:06 - mmengine - INFO - Epoch(train) [9][ 640/1345] lr: 1.0000e-02 eta: 10:31:13 time: 0.1918 data_time: 0.0055 memory: 8327 grad_norm: 6.7836 loss: 4.1605 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5433 loss_aux: 1.6172 2023/02/17 12:47:10 - mmengine - INFO - Epoch(train) [9][ 660/1345] lr: 1.0000e-02 eta: 10:31:06 time: 0.1908 data_time: 0.0056 memory: 8327 grad_norm: 6.7975 loss: 4.6128 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8644 loss_aux: 1.7484 2023/02/17 12:47:14 - mmengine - INFO - Epoch(train) [9][ 680/1345] lr: 1.0000e-02 eta: 10:31:00 time: 0.1908 data_time: 0.0059 memory: 8327 grad_norm: 6.8560 loss: 4.5026 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7786 loss_aux: 1.7240 2023/02/17 12:47:18 - mmengine - INFO - Epoch(train) [9][ 700/1345] lr: 1.0000e-02 eta: 10:30:53 time: 0.1904 data_time: 0.0052 memory: 8327 grad_norm: 6.5710 loss: 4.5272 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8020 loss_aux: 1.7252 2023/02/17 12:47:21 - mmengine - INFO - Epoch(train) [9][ 720/1345] lr: 1.0000e-02 eta: 10:30:46 time: 0.1899 data_time: 0.0054 memory: 8327 grad_norm: 6.6981 loss: 4.4258 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7449 loss_aux: 1.6808 2023/02/17 12:47:25 - mmengine - INFO - Epoch(train) [9][ 740/1345] lr: 1.0000e-02 eta: 10:30:39 time: 0.1907 data_time: 0.0058 memory: 8327 grad_norm: 6.6268 loss: 4.5202 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7809 loss_aux: 1.7393 2023/02/17 12:47:29 - mmengine - INFO - Epoch(train) [9][ 760/1345] lr: 1.0000e-02 eta: 10:30:33 time: 0.1908 data_time: 0.0053 memory: 8327 grad_norm: 6.5382 loss: 4.6256 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8641 loss_aux: 1.7615 2023/02/17 12:47:37 - mmengine - INFO - Epoch(train) [9][ 780/1345] lr: 1.0000e-02 eta: 10:31:33 time: 0.3955 data_time: 0.0076 memory: 8327 grad_norm: 6.8834 loss: 4.3170 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6043 loss_aux: 1.7127 2023/02/17 12:47:41 - mmengine - INFO - Epoch(train) [9][ 800/1345] lr: 1.0000e-02 eta: 10:31:27 time: 0.1905 data_time: 0.0054 memory: 8327 grad_norm: 6.6808 loss: 4.0471 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4737 loss_aux: 1.5734 2023/02/17 12:47:44 - mmengine - INFO - Epoch(train) [9][ 820/1345] lr: 1.0000e-02 eta: 10:31:19 time: 0.1897 data_time: 0.0055 memory: 8327 grad_norm: 6.6973 loss: 4.5204 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7451 loss_aux: 1.7752 2023/02/17 12:47:48 - mmengine - INFO - Epoch(train) [9][ 840/1345] lr: 1.0000e-02 eta: 10:31:12 time: 0.1897 data_time: 0.0055 memory: 8327 grad_norm: 6.7501 loss: 4.4147 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6922 loss_aux: 1.7225 2023/02/17 12:47:52 - mmengine - INFO - Epoch(train) [9][ 860/1345] lr: 1.0000e-02 eta: 10:31:05 time: 0.1905 data_time: 0.0054 memory: 8327 grad_norm: 6.6514 loss: 4.3980 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6859 loss_aux: 1.7120 2023/02/17 12:47:56 - mmengine - INFO - Epoch(train) [9][ 880/1345] lr: 1.0000e-02 eta: 10:30:59 time: 0.1911 data_time: 0.0053 memory: 8327 grad_norm: 6.5687 loss: 4.7005 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9357 loss_aux: 1.7648 2023/02/17 12:48:00 - mmengine - INFO - Epoch(train) [9][ 900/1345] lr: 1.0000e-02 eta: 10:30:52 time: 0.1906 data_time: 0.0058 memory: 8327 grad_norm: 6.8049 loss: 4.5359 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8294 loss_aux: 1.7064 2023/02/17 12:48:04 - mmengine - INFO - Epoch(train) [9][ 920/1345] lr: 1.0000e-02 eta: 10:30:45 time: 0.1902 data_time: 0.0054 memory: 8327 grad_norm: 6.9496 loss: 4.6478 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8832 loss_aux: 1.7647 2023/02/17 12:48:07 - mmengine - INFO - Epoch(train) [9][ 940/1345] lr: 1.0000e-02 eta: 10:30:39 time: 0.1909 data_time: 0.0056 memory: 8327 grad_norm: 6.8767 loss: 4.7104 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9378 loss_aux: 1.7726 2023/02/17 12:48:11 - mmengine - INFO - Epoch(train) [9][ 960/1345] lr: 1.0000e-02 eta: 10:30:32 time: 0.1907 data_time: 0.0054 memory: 8327 grad_norm: 6.6685 loss: 4.7318 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9208 loss_aux: 1.8109 2023/02/17 12:48:15 - mmengine - INFO - Epoch(train) [9][ 980/1345] lr: 1.0000e-02 eta: 10:30:25 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 6.6687 loss: 4.1508 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5096 loss_aux: 1.6412 2023/02/17 12:48:19 - mmengine - INFO - Epoch(train) [9][1000/1345] lr: 1.0000e-02 eta: 10:30:18 time: 0.1904 data_time: 0.0055 memory: 8327 grad_norm: 6.7164 loss: 4.6353 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.9066 loss_aux: 1.7288 2023/02/17 12:48:23 - mmengine - INFO - Epoch(train) [9][1020/1345] lr: 1.0000e-02 eta: 10:30:11 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 6.7576 loss: 4.4280 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6737 loss_aux: 1.7543 2023/02/17 12:48:26 - mmengine - INFO - Epoch(train) [9][1040/1345] lr: 1.0000e-02 eta: 10:30:04 time: 0.1903 data_time: 0.0053 memory: 8327 grad_norm: 6.8354 loss: 4.2460 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6094 loss_aux: 1.6366 2023/02/17 12:48:30 - mmengine - INFO - Epoch(train) [9][1060/1345] lr: 1.0000e-02 eta: 10:29:57 time: 0.1895 data_time: 0.0054 memory: 8327 grad_norm: 6.5254 loss: 4.4338 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7793 loss_aux: 1.6544 2023/02/17 12:48:34 - mmengine - INFO - Epoch(train) [9][1080/1345] lr: 1.0000e-02 eta: 10:29:50 time: 0.1900 data_time: 0.0055 memory: 8327 grad_norm: 6.7707 loss: 4.4419 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.7427 loss_aux: 1.6993 2023/02/17 12:48:38 - mmengine - INFO - Epoch(train) [9][1100/1345] lr: 1.0000e-02 eta: 10:29:44 time: 0.1910 data_time: 0.0055 memory: 8327 grad_norm: 6.8257 loss: 4.7115 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9535 loss_aux: 1.7580 2023/02/17 12:48:42 - mmengine - INFO - Epoch(train) [9][1120/1345] lr: 1.0000e-02 eta: 10:29:37 time: 0.1913 data_time: 0.0061 memory: 8327 grad_norm: 6.7176 loss: 4.0603 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4530 loss_aux: 1.6073 2023/02/17 12:48:45 - mmengine - INFO - Epoch(train) [9][1140/1345] lr: 1.0000e-02 eta: 10:29:31 time: 0.1916 data_time: 0.0068 memory: 8327 grad_norm: 6.6056 loss: 4.1554 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5499 loss_aux: 1.6055 2023/02/17 12:48:49 - mmengine - INFO - Epoch(train) [9][1160/1345] lr: 1.0000e-02 eta: 10:29:24 time: 0.1904 data_time: 0.0054 memory: 8327 grad_norm: 6.5843 loss: 4.3093 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6963 loss_aux: 1.6129 2023/02/17 12:48:53 - mmengine - INFO - Epoch(train) [9][1180/1345] lr: 1.0000e-02 eta: 10:29:17 time: 0.1898 data_time: 0.0052 memory: 8327 grad_norm: 6.9050 loss: 4.3572 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7265 loss_aux: 1.6307 2023/02/17 12:48:57 - mmengine - INFO - Epoch(train) [9][1200/1345] lr: 1.0000e-02 eta: 10:29:11 time: 0.1907 data_time: 0.0059 memory: 8327 grad_norm: 6.8355 loss: 4.0425 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4686 loss_aux: 1.5739 2023/02/17 12:49:01 - mmengine - INFO - Epoch(train) [9][1220/1345] lr: 1.0000e-02 eta: 10:29:04 time: 0.1903 data_time: 0.0055 memory: 8327 grad_norm: 6.7854 loss: 4.3475 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6550 loss_aux: 1.6925 2023/02/17 12:49:04 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:49:04 - mmengine - INFO - Epoch(train) [9][1240/1345] lr: 1.0000e-02 eta: 10:28:57 time: 0.1889 data_time: 0.0053 memory: 8327 grad_norm: 6.6823 loss: 4.5505 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7978 loss_aux: 1.7527 2023/02/17 12:49:08 - mmengine - INFO - Epoch(train) [9][1260/1345] lr: 1.0000e-02 eta: 10:28:51 time: 0.1932 data_time: 0.0058 memory: 8327 grad_norm: 6.7667 loss: 4.2263 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6067 loss_aux: 1.6196 2023/02/17 12:49:12 - mmengine - INFO - Epoch(train) [9][1280/1345] lr: 1.0000e-02 eta: 10:28:44 time: 0.1902 data_time: 0.0050 memory: 8327 grad_norm: 6.6532 loss: 4.5945 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8744 loss_aux: 1.7201 2023/02/17 12:49:16 - mmengine - INFO - Epoch(train) [9][1300/1345] lr: 1.0000e-02 eta: 10:28:38 time: 0.1902 data_time: 0.0055 memory: 8327 grad_norm: 6.6364 loss: 4.1971 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5732 loss_aux: 1.6239 2023/02/17 12:49:20 - mmengine - INFO - Epoch(train) [9][1320/1345] lr: 1.0000e-02 eta: 10:28:31 time: 0.1900 data_time: 0.0054 memory: 8327 grad_norm: 6.5474 loss: 4.9069 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0817 loss_aux: 1.8252 2023/02/17 12:49:23 - mmengine - INFO - Epoch(train) [9][1340/1345] lr: 1.0000e-02 eta: 10:28:24 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 6.7755 loss: 4.2919 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6309 loss_aux: 1.6609 2023/02/17 12:49:24 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:49:24 - mmengine - INFO - Epoch(train) [9][1345/1345] lr: 1.0000e-02 eta: 10:28:20 time: 0.1832 data_time: 0.0053 memory: 8327 grad_norm: 6.7653 loss: 4.4104 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.7129 loss_aux: 1.6975 2023/02/17 12:49:24 - mmengine - INFO - Saving checkpoint at 9 epochs 2023/02/17 12:49:31 - mmengine - INFO - Epoch(train) [10][ 20/1345] lr: 1.0000e-02 eta: 10:28:24 time: 0.2246 data_time: 0.0341 memory: 8327 grad_norm: 6.5795 loss: 4.2751 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6066 loss_aux: 1.6684 2023/02/17 12:49:35 - mmengine - INFO - Epoch(train) [10][ 40/1345] lr: 1.0000e-02 eta: 10:28:18 time: 0.1907 data_time: 0.0049 memory: 8327 grad_norm: 6.6779 loss: 4.3419 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6963 loss_aux: 1.6456 2023/02/17 12:49:39 - mmengine - INFO - Epoch(train) [10][ 60/1345] lr: 1.0000e-02 eta: 10:28:11 time: 0.1906 data_time: 0.0065 memory: 8327 grad_norm: 6.6522 loss: 4.3753 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6650 loss_aux: 1.7103 2023/02/17 12:49:43 - mmengine - INFO - Epoch(train) [10][ 80/1345] lr: 1.0000e-02 eta: 10:28:05 time: 0.1907 data_time: 0.0057 memory: 8327 grad_norm: 6.5988 loss: 4.3214 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7008 loss_aux: 1.6206 2023/02/17 12:49:46 - mmengine - INFO - Epoch(train) [10][ 100/1345] lr: 1.0000e-02 eta: 10:27:58 time: 0.1908 data_time: 0.0056 memory: 8327 grad_norm: 6.6345 loss: 4.2178 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5530 loss_aux: 1.6648 2023/02/17 12:49:54 - mmengine - INFO - Epoch(train) [10][ 120/1345] lr: 1.0000e-02 eta: 10:28:47 time: 0.3681 data_time: 0.0054 memory: 8327 grad_norm: 6.8394 loss: 4.3408 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6793 loss_aux: 1.6615 2023/02/17 12:49:58 - mmengine - INFO - Epoch(train) [10][ 140/1345] lr: 1.0000e-02 eta: 10:28:40 time: 0.1899 data_time: 0.0055 memory: 8327 grad_norm: 6.9087 loss: 4.9386 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.1079 loss_aux: 1.8307 2023/02/17 12:50:01 - mmengine - INFO - Epoch(train) [10][ 160/1345] lr: 1.0000e-02 eta: 10:28:34 time: 0.1909 data_time: 0.0054 memory: 8327 grad_norm: 6.7552 loss: 4.3494 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7180 loss_aux: 1.6314 2023/02/17 12:50:05 - mmengine - INFO - Epoch(train) [10][ 180/1345] lr: 1.0000e-02 eta: 10:28:27 time: 0.1916 data_time: 0.0057 memory: 8327 grad_norm: 6.7569 loss: 4.1675 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5627 loss_aux: 1.6048 2023/02/17 12:50:09 - mmengine - INFO - Epoch(train) [10][ 200/1345] lr: 1.0000e-02 eta: 10:28:21 time: 0.1911 data_time: 0.0052 memory: 8327 grad_norm: 6.8065 loss: 4.6680 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.8580 loss_aux: 1.8100 2023/02/17 12:50:13 - mmengine - INFO - Epoch(train) [10][ 220/1345] lr: 1.0000e-02 eta: 10:28:14 time: 0.1905 data_time: 0.0053 memory: 8327 grad_norm: 6.7876 loss: 4.6591 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9298 loss_aux: 1.7294 2023/02/17 12:50:17 - mmengine - INFO - Epoch(train) [10][ 240/1345] lr: 1.0000e-02 eta: 10:28:08 time: 0.1905 data_time: 0.0054 memory: 8327 grad_norm: 6.8294 loss: 4.0931 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4656 loss_aux: 1.6275 2023/02/17 12:50:21 - mmengine - INFO - Epoch(train) [10][ 260/1345] lr: 1.0000e-02 eta: 10:28:01 time: 0.1903 data_time: 0.0056 memory: 8327 grad_norm: 6.9563 loss: 4.1950 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6218 loss_aux: 1.5732 2023/02/17 12:50:24 - mmengine - INFO - Epoch(train) [10][ 280/1345] lr: 1.0000e-02 eta: 10:27:54 time: 0.1897 data_time: 0.0055 memory: 8327 grad_norm: 6.6527 loss: 4.4367 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7353 loss_aux: 1.7014 2023/02/17 12:50:28 - mmengine - INFO - Epoch(train) [10][ 300/1345] lr: 1.0000e-02 eta: 10:27:48 time: 0.1914 data_time: 0.0054 memory: 8327 grad_norm: 6.7372 loss: 4.3217 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6059 loss_aux: 1.7158 2023/02/17 12:50:32 - mmengine - INFO - Epoch(train) [10][ 320/1345] lr: 1.0000e-02 eta: 10:27:42 time: 0.1915 data_time: 0.0054 memory: 8327 grad_norm: 6.5432 loss: 4.4887 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7247 loss_aux: 1.7640 2023/02/17 12:50:36 - mmengine - INFO - Epoch(train) [10][ 340/1345] lr: 1.0000e-02 eta: 10:27:35 time: 0.1909 data_time: 0.0057 memory: 8327 grad_norm: 6.5930 loss: 4.3118 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6063 loss_aux: 1.7055 2023/02/17 12:50:40 - mmengine - INFO - Epoch(train) [10][ 360/1345] lr: 1.0000e-02 eta: 10:27:29 time: 0.1912 data_time: 0.0062 memory: 8327 grad_norm: 6.5866 loss: 4.3893 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7330 loss_aux: 1.6564 2023/02/17 12:50:43 - mmengine - INFO - Epoch(train) [10][ 380/1345] lr: 1.0000e-02 eta: 10:27:23 time: 0.1907 data_time: 0.0054 memory: 8327 grad_norm: 6.5891 loss: 4.2718 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5973 loss_aux: 1.6745 2023/02/17 12:50:47 - mmengine - INFO - Epoch(train) [10][ 400/1345] lr: 1.0000e-02 eta: 10:27:16 time: 0.1901 data_time: 0.0057 memory: 8327 grad_norm: 6.8330 loss: 4.2312 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5515 loss_aux: 1.6796 2023/02/17 12:50:51 - mmengine - INFO - Epoch(train) [10][ 420/1345] lr: 1.0000e-02 eta: 10:27:09 time: 0.1900 data_time: 0.0055 memory: 8327 grad_norm: 6.6864 loss: 4.5002 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7688 loss_aux: 1.7314 2023/02/17 12:50:55 - mmengine - INFO - Epoch(train) [10][ 440/1345] lr: 1.0000e-02 eta: 10:27:09 time: 0.2128 data_time: 0.0055 memory: 8327 grad_norm: 6.6570 loss: 4.3674 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7043 loss_aux: 1.6631 2023/02/17 12:50:59 - mmengine - INFO - Epoch(train) [10][ 460/1345] lr: 1.0000e-02 eta: 10:27:04 time: 0.1933 data_time: 0.0052 memory: 8327 grad_norm: 6.5621 loss: 4.3920 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6918 loss_aux: 1.7002 2023/02/17 12:51:03 - mmengine - INFO - Epoch(train) [10][ 480/1345] lr: 1.0000e-02 eta: 10:26:58 time: 0.1922 data_time: 0.0054 memory: 8327 grad_norm: 6.6763 loss: 4.3289 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6599 loss_aux: 1.6690 2023/02/17 12:51:07 - mmengine - INFO - Epoch(train) [10][ 500/1345] lr: 1.0000e-02 eta: 10:26:51 time: 0.1905 data_time: 0.0054 memory: 8327 grad_norm: 6.7446 loss: 4.2578 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6021 loss_aux: 1.6557 2023/02/17 12:51:11 - mmengine - INFO - Epoch(train) [10][ 520/1345] lr: 1.0000e-02 eta: 10:26:45 time: 0.1903 data_time: 0.0056 memory: 8327 grad_norm: 6.7279 loss: 4.4431 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7379 loss_aux: 1.7052 2023/02/17 12:51:14 - mmengine - INFO - Epoch(train) [10][ 540/1345] lr: 1.0000e-02 eta: 10:26:39 time: 0.1916 data_time: 0.0058 memory: 8327 grad_norm: 6.8260 loss: 4.2899 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5821 loss_aux: 1.7078 2023/02/17 12:51:18 - mmengine - INFO - Epoch(train) [10][ 560/1345] lr: 1.0000e-02 eta: 10:26:32 time: 0.1904 data_time: 0.0049 memory: 8327 grad_norm: 6.6320 loss: 4.1408 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5241 loss_aux: 1.6167 2023/02/17 12:51:22 - mmengine - INFO - Epoch(train) [10][ 580/1345] lr: 1.0000e-02 eta: 10:26:26 time: 0.1898 data_time: 0.0054 memory: 8327 grad_norm: 6.5986 loss: 4.4295 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7847 loss_aux: 1.6447 2023/02/17 12:51:26 - mmengine - INFO - Epoch(train) [10][ 600/1345] lr: 1.0000e-02 eta: 10:26:19 time: 0.1903 data_time: 0.0056 memory: 8327 grad_norm: 6.6873 loss: 4.4232 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6920 loss_aux: 1.7312 2023/02/17 12:51:30 - mmengine - INFO - Epoch(train) [10][ 620/1345] lr: 1.0000e-02 eta: 10:26:13 time: 0.1908 data_time: 0.0056 memory: 8327 grad_norm: 6.8317 loss: 4.2669 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6317 loss_aux: 1.6353 2023/02/17 12:51:33 - mmengine - INFO - Epoch(train) [10][ 640/1345] lr: 1.0000e-02 eta: 10:26:06 time: 0.1897 data_time: 0.0052 memory: 8327 grad_norm: 6.6843 loss: 4.3305 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6871 loss_aux: 1.6434 2023/02/17 12:51:37 - mmengine - INFO - Epoch(train) [10][ 660/1345] lr: 1.0000e-02 eta: 10:26:00 time: 0.1906 data_time: 0.0055 memory: 8327 grad_norm: 6.7830 loss: 3.9241 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4115 loss_aux: 1.5126 2023/02/17 12:51:41 - mmengine - INFO - Epoch(train) [10][ 680/1345] lr: 1.0000e-02 eta: 10:25:53 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 6.8159 loss: 4.3724 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6881 loss_aux: 1.6843 2023/02/17 12:51:45 - mmengine - INFO - Epoch(train) [10][ 700/1345] lr: 1.0000e-02 eta: 10:25:47 time: 0.1903 data_time: 0.0054 memory: 8327 grad_norm: 6.8783 loss: 4.1974 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.5689 loss_aux: 1.6285 2023/02/17 12:51:49 - mmengine - INFO - Epoch(train) [10][ 720/1345] lr: 1.0000e-02 eta: 10:25:40 time: 0.1902 data_time: 0.0057 memory: 8327 grad_norm: 6.6702 loss: 4.3507 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6575 loss_aux: 1.6932 2023/02/17 12:51:53 - mmengine - INFO - Epoch(train) [10][ 740/1345] lr: 1.0000e-02 eta: 10:25:33 time: 0.1899 data_time: 0.0055 memory: 8327 grad_norm: 6.7113 loss: 4.0124 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4108 loss_aux: 1.6016 2023/02/17 12:51:56 - mmengine - INFO - Epoch(train) [10][ 760/1345] lr: 1.0000e-02 eta: 10:25:27 time: 0.1912 data_time: 0.0056 memory: 8327 grad_norm: 6.7870 loss: 4.5806 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8652 loss_aux: 1.7155 2023/02/17 12:52:00 - mmengine - INFO - Epoch(train) [10][ 780/1345] lr: 1.0000e-02 eta: 10:25:21 time: 0.1903 data_time: 0.0057 memory: 8327 grad_norm: 6.6767 loss: 4.2515 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6568 loss_aux: 1.5947 2023/02/17 12:52:04 - mmengine - INFO - Epoch(train) [10][ 800/1345] lr: 1.0000e-02 eta: 10:25:14 time: 0.1905 data_time: 0.0055 memory: 8327 grad_norm: 6.6993 loss: 4.7772 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0166 loss_aux: 1.7606 2023/02/17 12:52:08 - mmengine - INFO - Epoch(train) [10][ 820/1345] lr: 1.0000e-02 eta: 10:25:09 time: 0.1921 data_time: 0.0059 memory: 8327 grad_norm: 6.6962 loss: 4.4584 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7692 loss_aux: 1.6892 2023/02/17 12:52:12 - mmengine - INFO - Epoch(train) [10][ 840/1345] lr: 1.0000e-02 eta: 10:25:02 time: 0.1904 data_time: 0.0049 memory: 8327 grad_norm: 6.6681 loss: 4.9602 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.1134 loss_aux: 1.8468 2023/02/17 12:52:15 - mmengine - INFO - Epoch(train) [10][ 860/1345] lr: 1.0000e-02 eta: 10:24:56 time: 0.1924 data_time: 0.0055 memory: 8327 grad_norm: 6.8358 loss: 4.3016 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6282 loss_aux: 1.6734 2023/02/17 12:52:19 - mmengine - INFO - Epoch(train) [10][ 880/1345] lr: 1.0000e-02 eta: 10:24:51 time: 0.1936 data_time: 0.0053 memory: 8327 grad_norm: 6.7188 loss: 4.0790 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4336 loss_aux: 1.6454 2023/02/17 12:52:22 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:52:23 - mmengine - INFO - Epoch(train) [10][ 900/1345] lr: 1.0000e-02 eta: 10:24:45 time: 0.1924 data_time: 0.0053 memory: 8327 grad_norm: 6.8266 loss: 4.2101 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5982 loss_aux: 1.6119 2023/02/17 12:52:27 - mmengine - INFO - Epoch(train) [10][ 920/1345] lr: 1.0000e-02 eta: 10:24:39 time: 0.1916 data_time: 0.0057 memory: 8327 grad_norm: 6.7244 loss: 4.1804 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.5610 loss_aux: 1.6194 2023/02/17 12:52:31 - mmengine - INFO - Epoch(train) [10][ 940/1345] lr: 1.0000e-02 eta: 10:24:33 time: 0.1907 data_time: 0.0054 memory: 8327 grad_norm: 6.8647 loss: 4.3279 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7111 loss_aux: 1.6167 2023/02/17 12:52:35 - mmengine - INFO - Epoch(train) [10][ 960/1345] lr: 1.0000e-02 eta: 10:24:27 time: 0.1908 data_time: 0.0056 memory: 8327 grad_norm: 6.7043 loss: 4.5659 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8298 loss_aux: 1.7361 2023/02/17 12:52:38 - mmengine - INFO - Epoch(train) [10][ 980/1345] lr: 1.0000e-02 eta: 10:24:20 time: 0.1899 data_time: 0.0052 memory: 8327 grad_norm: 6.6128 loss: 4.4422 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7440 loss_aux: 1.6982 2023/02/17 12:52:42 - mmengine - INFO - Epoch(train) [10][1000/1345] lr: 1.0000e-02 eta: 10:24:14 time: 0.1913 data_time: 0.0054 memory: 8327 grad_norm: 6.7068 loss: 4.1014 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4697 loss_aux: 1.6317 2023/02/17 12:52:46 - mmengine - INFO - Epoch(train) [10][1020/1345] lr: 1.0000e-02 eta: 10:24:08 time: 0.1914 data_time: 0.0055 memory: 8327 grad_norm: 6.8150 loss: 4.4106 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6974 loss_aux: 1.7132 2023/02/17 12:52:50 - mmengine - INFO - Epoch(train) [10][1040/1345] lr: 1.0000e-02 eta: 10:24:02 time: 0.1898 data_time: 0.0054 memory: 8327 grad_norm: 6.7692 loss: 4.2631 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6143 loss_aux: 1.6488 2023/02/17 12:52:54 - mmengine - INFO - Epoch(train) [10][1060/1345] lr: 1.0000e-02 eta: 10:23:55 time: 0.1907 data_time: 0.0054 memory: 8327 grad_norm: 6.7782 loss: 4.3145 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.6724 loss_aux: 1.6421 2023/02/17 12:52:58 - mmengine - INFO - Epoch(train) [10][1080/1345] lr: 1.0000e-02 eta: 10:23:49 time: 0.1911 data_time: 0.0054 memory: 8327 grad_norm: 6.7484 loss: 4.5590 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8557 loss_aux: 1.7032 2023/02/17 12:53:01 - mmengine - INFO - Epoch(train) [10][1100/1345] lr: 1.0000e-02 eta: 10:23:43 time: 0.1898 data_time: 0.0054 memory: 8327 grad_norm: 6.8658 loss: 4.0611 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4404 loss_aux: 1.6207 2023/02/17 12:53:05 - mmengine - INFO - Epoch(train) [10][1120/1345] lr: 1.0000e-02 eta: 10:23:36 time: 0.1897 data_time: 0.0056 memory: 8327 grad_norm: 6.7669 loss: 4.5416 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.7712 loss_aux: 1.7704 2023/02/17 12:53:09 - mmengine - INFO - Epoch(train) [10][1140/1345] lr: 1.0000e-02 eta: 10:23:31 time: 0.1917 data_time: 0.0058 memory: 8327 grad_norm: 6.7256 loss: 4.2628 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6315 loss_aux: 1.6313 2023/02/17 12:53:13 - mmengine - INFO - Epoch(train) [10][1160/1345] lr: 1.0000e-02 eta: 10:23:24 time: 0.1902 data_time: 0.0055 memory: 8327 grad_norm: 6.7556 loss: 4.5017 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8560 loss_aux: 1.6456 2023/02/17 12:53:17 - mmengine - INFO - Epoch(train) [10][1180/1345] lr: 1.0000e-02 eta: 10:23:18 time: 0.1900 data_time: 0.0055 memory: 8327 grad_norm: 6.8268 loss: 3.7932 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3196 loss_aux: 1.4737 2023/02/17 12:53:20 - mmengine - INFO - Epoch(train) [10][1200/1345] lr: 1.0000e-02 eta: 10:23:12 time: 0.1901 data_time: 0.0057 memory: 8327 grad_norm: 6.6465 loss: 4.5805 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8388 loss_aux: 1.7418 2023/02/17 12:53:24 - mmengine - INFO - Epoch(train) [10][1220/1345] lr: 1.0000e-02 eta: 10:23:06 time: 0.1930 data_time: 0.0052 memory: 8327 grad_norm: 6.4652 loss: 4.3589 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7075 loss_aux: 1.6514 2023/02/17 12:53:28 - mmengine - INFO - Epoch(train) [10][1240/1345] lr: 1.0000e-02 eta: 10:23:00 time: 0.1902 data_time: 0.0055 memory: 8327 grad_norm: 6.6592 loss: 4.5086 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.7582 loss_aux: 1.7504 2023/02/17 12:53:32 - mmengine - INFO - Epoch(train) [10][1260/1345] lr: 1.0000e-02 eta: 10:22:54 time: 0.1906 data_time: 0.0055 memory: 8327 grad_norm: 6.7976 loss: 4.3935 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7505 loss_aux: 1.6430 2023/02/17 12:53:36 - mmengine - INFO - Epoch(train) [10][1280/1345] lr: 1.0000e-02 eta: 10:22:47 time: 0.1902 data_time: 0.0052 memory: 8327 grad_norm: 6.7055 loss: 4.0761 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5101 loss_aux: 1.5659 2023/02/17 12:53:40 - mmengine - INFO - Epoch(train) [10][1300/1345] lr: 1.0000e-02 eta: 10:22:42 time: 0.1926 data_time: 0.0071 memory: 8327 grad_norm: 6.6597 loss: 4.2535 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6536 loss_aux: 1.5999 2023/02/17 12:53:43 - mmengine - INFO - Epoch(train) [10][1320/1345] lr: 1.0000e-02 eta: 10:22:36 time: 0.1913 data_time: 0.0066 memory: 8327 grad_norm: 6.6730 loss: 4.4263 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7582 loss_aux: 1.6682 2023/02/17 12:53:47 - mmengine - INFO - Epoch(train) [10][1340/1345] lr: 1.0000e-02 eta: 10:22:29 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 6.7386 loss: 4.4073 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7394 loss_aux: 1.6679 2023/02/17 12:53:48 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:53:48 - mmengine - INFO - Epoch(train) [10][1345/1345] lr: 1.0000e-02 eta: 10:22:26 time: 0.1836 data_time: 0.0054 memory: 8327 grad_norm: 6.6745 loss: 4.4480 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.7392 loss_aux: 1.7088 2023/02/17 12:53:48 - mmengine - INFO - Saving checkpoint at 10 epochs 2023/02/17 12:53:52 - mmengine - INFO - Epoch(val) [10][ 20/181] eta: 0:00:09 time: 0.0606 data_time: 0.0084 memory: 1994 2023/02/17 12:53:53 - mmengine - INFO - Epoch(val) [10][ 40/181] eta: 0:00:07 time: 0.0528 data_time: 0.0047 memory: 1994 2023/02/17 12:53:54 - mmengine - INFO - Epoch(val) [10][ 60/181] eta: 0:00:06 time: 0.0525 data_time: 0.0046 memory: 1994 2023/02/17 12:53:55 - mmengine - INFO - Epoch(val) [10][ 80/181] eta: 0:00:05 time: 0.0522 data_time: 0.0045 memory: 1994 2023/02/17 12:53:56 - mmengine - INFO - Epoch(val) [10][100/181] eta: 0:00:04 time: 0.0524 data_time: 0.0045 memory: 1994 2023/02/17 12:53:57 - mmengine - INFO - Epoch(val) [10][120/181] eta: 0:00:03 time: 0.0548 data_time: 0.0049 memory: 1994 2023/02/17 12:53:58 - mmengine - INFO - Epoch(val) [10][140/181] eta: 0:00:02 time: 0.0519 data_time: 0.0044 memory: 1994 2023/02/17 12:53:59 - mmengine - INFO - Epoch(val) [10][160/181] eta: 0:00:01 time: 0.0520 data_time: 0.0044 memory: 1994 2023/02/17 12:54:00 - mmengine - INFO - Epoch(val) [10][180/181] eta: 0:00:00 time: 0.0517 data_time: 0.0042 memory: 1994 2023/02/17 12:54:00 - mmengine - INFO - Epoch(val) [10][181/181] acc/top1: 0.3262 acc/top5: 0.6137 acc/mean1: 0.2969 2023/02/17 12:54:00 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/lilin/Repos/mmact_dev/mmaction2/work_dirs/fix_flip/tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb/best_acc/top1_epoch_5.pth is removed 2023/02/17 12:54:02 - mmengine - INFO - The best checkpoint with 0.3262 acc/top1 at 10 epoch is saved to best_acc/top1_epoch_10.pth. 2023/02/17 12:54:07 - mmengine - INFO - Epoch(train) [11][ 20/1345] lr: 1.0000e-02 eta: 10:22:30 time: 0.2262 data_time: 0.0352 memory: 8327 grad_norm: 6.5021 loss: 4.2976 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6137 loss_aux: 1.6839 2023/02/17 12:54:10 - mmengine - INFO - Epoch(train) [11][ 40/1345] lr: 1.0000e-02 eta: 10:22:23 time: 0.1891 data_time: 0.0040 memory: 8327 grad_norm: 6.6489 loss: 4.3330 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6433 loss_aux: 1.6897 2023/02/17 12:54:14 - mmengine - INFO - Epoch(train) [11][ 60/1345] lr: 1.0000e-02 eta: 10:22:17 time: 0.1898 data_time: 0.0056 memory: 8327 grad_norm: 6.9259 loss: 4.1713 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4958 loss_aux: 1.6755 2023/02/17 12:54:18 - mmengine - INFO - Epoch(train) [11][ 80/1345] lr: 1.0000e-02 eta: 10:22:11 time: 0.1903 data_time: 0.0056 memory: 8327 grad_norm: 6.6732 loss: 4.0461 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5246 loss_aux: 1.5214 2023/02/17 12:54:22 - mmengine - INFO - Epoch(train) [11][ 100/1345] lr: 1.0000e-02 eta: 10:22:04 time: 0.1897 data_time: 0.0052 memory: 8327 grad_norm: 6.6530 loss: 4.3634 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6844 loss_aux: 1.6790 2023/02/17 12:54:26 - mmengine - INFO - Epoch(train) [11][ 120/1345] lr: 1.0000e-02 eta: 10:21:58 time: 0.1899 data_time: 0.0054 memory: 8327 grad_norm: 6.7170 loss: 4.0271 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4225 loss_aux: 1.6046 2023/02/17 12:54:29 - mmengine - INFO - Epoch(train) [11][ 140/1345] lr: 1.0000e-02 eta: 10:21:52 time: 0.1899 data_time: 0.0055 memory: 8327 grad_norm: 6.5903 loss: 4.1596 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5394 loss_aux: 1.6201 2023/02/17 12:54:33 - mmengine - INFO - Epoch(train) [11][ 160/1345] lr: 1.0000e-02 eta: 10:21:45 time: 0.1896 data_time: 0.0054 memory: 8327 grad_norm: 6.7542 loss: 4.4186 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7345 loss_aux: 1.6841 2023/02/17 12:54:37 - mmengine - INFO - Epoch(train) [11][ 180/1345] lr: 1.0000e-02 eta: 10:21:39 time: 0.1902 data_time: 0.0060 memory: 8327 grad_norm: 6.8017 loss: 4.2354 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6094 loss_aux: 1.6260 2023/02/17 12:54:41 - mmengine - INFO - Epoch(train) [11][ 200/1345] lr: 1.0000e-02 eta: 10:21:33 time: 0.1901 data_time: 0.0054 memory: 8327 grad_norm: 6.4701 loss: 4.2765 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6473 loss_aux: 1.6291 2023/02/17 12:54:45 - mmengine - INFO - Epoch(train) [11][ 220/1345] lr: 1.0000e-02 eta: 10:21:27 time: 0.1895 data_time: 0.0054 memory: 8327 grad_norm: 6.7537 loss: 4.1107 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5693 loss_aux: 1.5413 2023/02/17 12:54:48 - mmengine - INFO - Epoch(train) [11][ 240/1345] lr: 1.0000e-02 eta: 10:21:21 time: 0.1913 data_time: 0.0060 memory: 8327 grad_norm: 6.8867 loss: 4.0357 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4597 loss_aux: 1.5761 2023/02/17 12:54:52 - mmengine - INFO - Epoch(train) [11][ 260/1345] lr: 1.0000e-02 eta: 10:21:15 time: 0.1904 data_time: 0.0056 memory: 8327 grad_norm: 6.7211 loss: 4.0226 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4830 loss_aux: 1.5396 2023/02/17 12:54:56 - mmengine - INFO - Epoch(train) [11][ 280/1345] lr: 1.0000e-02 eta: 10:21:08 time: 0.1900 data_time: 0.0053 memory: 8327 grad_norm: 6.7696 loss: 4.3029 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6358 loss_aux: 1.6671 2023/02/17 12:55:00 - mmengine - INFO - Epoch(train) [11][ 300/1345] lr: 1.0000e-02 eta: 10:21:03 time: 0.1911 data_time: 0.0054 memory: 8327 grad_norm: 6.8358 loss: 4.3130 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6643 loss_aux: 1.6487 2023/02/17 12:55:04 - mmengine - INFO - Epoch(train) [11][ 320/1345] lr: 1.0000e-02 eta: 10:20:57 time: 0.1909 data_time: 0.0055 memory: 8327 grad_norm: 6.7180 loss: 4.1761 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5670 loss_aux: 1.6091 2023/02/17 12:55:07 - mmengine - INFO - Epoch(train) [11][ 340/1345] lr: 1.0000e-02 eta: 10:20:50 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 6.8154 loss: 4.3984 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7899 loss_aux: 1.6085 2023/02/17 12:55:11 - mmengine - INFO - Epoch(train) [11][ 360/1345] lr: 1.0000e-02 eta: 10:20:44 time: 0.1912 data_time: 0.0060 memory: 8327 grad_norm: 6.7973 loss: 4.4515 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7398 loss_aux: 1.7117 2023/02/17 12:55:15 - mmengine - INFO - Epoch(train) [11][ 380/1345] lr: 1.0000e-02 eta: 10:20:38 time: 0.1902 data_time: 0.0055 memory: 8327 grad_norm: 6.8727 loss: 4.7074 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.9718 loss_aux: 1.7356 2023/02/17 12:55:19 - mmengine - INFO - Epoch(train) [11][ 400/1345] lr: 1.0000e-02 eta: 10:20:32 time: 0.1904 data_time: 0.0052 memory: 8327 grad_norm: 6.7730 loss: 4.6877 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9152 loss_aux: 1.7724 2023/02/17 12:55:23 - mmengine - INFO - Epoch(train) [11][ 420/1345] lr: 1.0000e-02 eta: 10:20:26 time: 0.1901 data_time: 0.0053 memory: 8327 grad_norm: 6.6871 loss: 4.4019 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7146 loss_aux: 1.6873 2023/02/17 12:55:26 - mmengine - INFO - Epoch(train) [11][ 440/1345] lr: 1.0000e-02 eta: 10:20:20 time: 0.1901 data_time: 0.0054 memory: 8327 grad_norm: 6.7722 loss: 4.5250 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8139 loss_aux: 1.7111 2023/02/17 12:55:30 - mmengine - INFO - Epoch(train) [11][ 460/1345] lr: 1.0000e-02 eta: 10:20:14 time: 0.1897 data_time: 0.0055 memory: 8327 grad_norm: 6.9636 loss: 4.1713 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5590 loss_aux: 1.6123 2023/02/17 12:55:34 - mmengine - INFO - Epoch(train) [11][ 480/1345] lr: 1.0000e-02 eta: 10:20:07 time: 0.1895 data_time: 0.0056 memory: 8327 grad_norm: 6.7509 loss: 4.5972 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8684 loss_aux: 1.7288 2023/02/17 12:55:38 - mmengine - INFO - Epoch(train) [11][ 500/1345] lr: 1.0000e-02 eta: 10:20:01 time: 0.1900 data_time: 0.0052 memory: 8327 grad_norm: 6.7198 loss: 4.4231 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7502 loss_aux: 1.6730 2023/02/17 12:55:42 - mmengine - INFO - Epoch(train) [11][ 520/1345] lr: 1.0000e-02 eta: 10:19:55 time: 0.1900 data_time: 0.0055 memory: 8327 grad_norm: 6.8254 loss: 4.6245 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8695 loss_aux: 1.7550 2023/02/17 12:55:45 - mmengine - INFO - Epoch(train) [11][ 540/1345] lr: 1.0000e-02 eta: 10:19:49 time: 0.1904 data_time: 0.0069 memory: 8327 grad_norm: 6.7245 loss: 4.2546 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6318 loss_aux: 1.6228 2023/02/17 12:55:47 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:55:49 - mmengine - INFO - Epoch(train) [11][ 560/1345] lr: 1.0000e-02 eta: 10:19:43 time: 0.1905 data_time: 0.0054 memory: 8327 grad_norm: 6.8549 loss: 4.3749 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7060 loss_aux: 1.6688 2023/02/17 12:55:53 - mmengine - INFO - Epoch(train) [11][ 580/1345] lr: 1.0000e-02 eta: 10:19:37 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 6.7983 loss: 4.2824 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6228 loss_aux: 1.6597 2023/02/17 12:55:57 - mmengine - INFO - Epoch(train) [11][ 600/1345] lr: 1.0000e-02 eta: 10:19:30 time: 0.1891 data_time: 0.0055 memory: 8327 grad_norm: 6.9628 loss: 4.0671 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4677 loss_aux: 1.5993 2023/02/17 12:56:01 - mmengine - INFO - Epoch(train) [11][ 620/1345] lr: 1.0000e-02 eta: 10:19:24 time: 0.1904 data_time: 0.0058 memory: 8327 grad_norm: 6.8737 loss: 4.5309 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.8226 loss_aux: 1.7082 2023/02/17 12:56:04 - mmengine - INFO - Epoch(train) [11][ 640/1345] lr: 1.0000e-02 eta: 10:19:18 time: 0.1894 data_time: 0.0052 memory: 8327 grad_norm: 6.7972 loss: 4.1801 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5950 loss_aux: 1.5851 2023/02/17 12:56:08 - mmengine - INFO - Epoch(train) [11][ 660/1345] lr: 1.0000e-02 eta: 10:19:12 time: 0.1902 data_time: 0.0053 memory: 8327 grad_norm: 6.7223 loss: 4.5212 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7658 loss_aux: 1.7554 2023/02/17 12:56:12 - mmengine - INFO - Epoch(train) [11][ 680/1345] lr: 1.0000e-02 eta: 10:19:06 time: 0.1910 data_time: 0.0063 memory: 8327 grad_norm: 6.8221 loss: 4.3057 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.6247 loss_aux: 1.6810 2023/02/17 12:56:16 - mmengine - INFO - Epoch(train) [11][ 700/1345] lr: 1.0000e-02 eta: 10:19:00 time: 0.1906 data_time: 0.0055 memory: 8327 grad_norm: 6.5785 loss: 4.5476 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8100 loss_aux: 1.7376 2023/02/17 12:56:20 - mmengine - INFO - Epoch(train) [11][ 720/1345] lr: 1.0000e-02 eta: 10:18:54 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 6.7181 loss: 4.3852 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6941 loss_aux: 1.6911 2023/02/17 12:56:23 - mmengine - INFO - Epoch(train) [11][ 740/1345] lr: 1.0000e-02 eta: 10:18:48 time: 0.1900 data_time: 0.0055 memory: 8327 grad_norm: 6.6592 loss: 4.3108 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6485 loss_aux: 1.6623 2023/02/17 12:56:27 - mmengine - INFO - Epoch(train) [11][ 760/1345] lr: 1.0000e-02 eta: 10:18:42 time: 0.1901 data_time: 0.0053 memory: 8327 grad_norm: 6.6445 loss: 4.2903 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6491 loss_aux: 1.6412 2023/02/17 12:56:31 - mmengine - INFO - Epoch(train) [11][ 780/1345] lr: 1.0000e-02 eta: 10:18:36 time: 0.1908 data_time: 0.0054 memory: 8327 grad_norm: 6.6772 loss: 4.4362 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7530 loss_aux: 1.6832 2023/02/17 12:56:35 - mmengine - INFO - Epoch(train) [11][ 800/1345] lr: 1.0000e-02 eta: 10:18:30 time: 0.1894 data_time: 0.0052 memory: 8327 grad_norm: 6.7764 loss: 4.0016 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4525 loss_aux: 1.5491 2023/02/17 12:56:39 - mmengine - INFO - Epoch(train) [11][ 820/1345] lr: 1.0000e-02 eta: 10:18:24 time: 0.1890 data_time: 0.0053 memory: 8327 grad_norm: 6.8376 loss: 4.2778 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6616 loss_aux: 1.6162 2023/02/17 12:56:42 - mmengine - INFO - Epoch(train) [11][ 840/1345] lr: 1.0000e-02 eta: 10:18:18 time: 0.1905 data_time: 0.0056 memory: 8327 grad_norm: 6.8072 loss: 4.8270 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9991 loss_aux: 1.8279 2023/02/17 12:56:46 - mmengine - INFO - Epoch(train) [11][ 860/1345] lr: 1.0000e-02 eta: 10:18:13 time: 0.1930 data_time: 0.0052 memory: 8327 grad_norm: 6.8609 loss: 4.3680 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7125 loss_aux: 1.6555 2023/02/17 12:56:50 - mmengine - INFO - Epoch(train) [11][ 880/1345] lr: 1.0000e-02 eta: 10:18:06 time: 0.1895 data_time: 0.0054 memory: 8327 grad_norm: 6.7639 loss: 4.0943 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5430 loss_aux: 1.5513 2023/02/17 12:56:54 - mmengine - INFO - Epoch(train) [11][ 900/1345] lr: 1.0000e-02 eta: 10:18:00 time: 0.1901 data_time: 0.0054 memory: 8327 grad_norm: 6.7589 loss: 4.1304 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5535 loss_aux: 1.5769 2023/02/17 12:56:58 - mmengine - INFO - Epoch(train) [11][ 920/1345] lr: 1.0000e-02 eta: 10:17:54 time: 0.1891 data_time: 0.0054 memory: 8327 grad_norm: 6.7479 loss: 4.1419 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5326 loss_aux: 1.6092 2023/02/17 12:57:01 - mmengine - INFO - Epoch(train) [11][ 940/1345] lr: 1.0000e-02 eta: 10:17:48 time: 0.1898 data_time: 0.0054 memory: 8327 grad_norm: 6.7321 loss: 4.4173 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7960 loss_aux: 1.6212 2023/02/17 12:57:05 - mmengine - INFO - Epoch(train) [11][ 960/1345] lr: 1.0000e-02 eta: 10:17:42 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 6.6710 loss: 4.5017 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7816 loss_aux: 1.7201 2023/02/17 12:57:09 - mmengine - INFO - Epoch(train) [11][ 980/1345] lr: 1.0000e-02 eta: 10:17:36 time: 0.1903 data_time: 0.0054 memory: 8327 grad_norm: 6.4658 loss: 3.9984 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3779 loss_aux: 1.6205 2023/02/17 12:57:13 - mmengine - INFO - Epoch(train) [11][1000/1345] lr: 1.0000e-02 eta: 10:17:30 time: 0.1900 data_time: 0.0052 memory: 8327 grad_norm: 6.9841 loss: 4.5701 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.8310 loss_aux: 1.7391 2023/02/17 12:57:17 - mmengine - INFO - Epoch(train) [11][1020/1345] lr: 1.0000e-02 eta: 10:17:24 time: 0.1892 data_time: 0.0055 memory: 8327 grad_norm: 6.7070 loss: 4.2706 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5911 loss_aux: 1.6795 2023/02/17 12:57:20 - mmengine - INFO - Epoch(train) [11][1040/1345] lr: 1.0000e-02 eta: 10:17:18 time: 0.1910 data_time: 0.0059 memory: 8327 grad_norm: 6.6663 loss: 4.3042 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6697 loss_aux: 1.6345 2023/02/17 12:57:24 - mmengine - INFO - Epoch(train) [11][1060/1345] lr: 1.0000e-02 eta: 10:17:12 time: 0.1905 data_time: 0.0054 memory: 8327 grad_norm: 6.7728 loss: 4.3922 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6908 loss_aux: 1.7014 2023/02/17 12:57:28 - mmengine - INFO - Epoch(train) [11][1080/1345] lr: 1.0000e-02 eta: 10:17:06 time: 0.1898 data_time: 0.0063 memory: 8327 grad_norm: 6.9058 loss: 4.2062 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5858 loss_aux: 1.6204 2023/02/17 12:57:32 - mmengine - INFO - Epoch(train) [11][1100/1345] lr: 1.0000e-02 eta: 10:17:00 time: 0.1896 data_time: 0.0053 memory: 8327 grad_norm: 6.9397 loss: 4.3386 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6659 loss_aux: 1.6727 2023/02/17 12:57:36 - mmengine - INFO - Epoch(train) [11][1120/1345] lr: 1.0000e-02 eta: 10:16:54 time: 0.1895 data_time: 0.0054 memory: 8327 grad_norm: 6.7542 loss: 3.9425 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4241 loss_aux: 1.5184 2023/02/17 12:57:40 - mmengine - INFO - Epoch(train) [11][1140/1345] lr: 1.0000e-02 eta: 10:16:49 time: 0.1910 data_time: 0.0060 memory: 8327 grad_norm: 6.6934 loss: 4.3789 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6855 loss_aux: 1.6934 2023/02/17 12:57:43 - mmengine - INFO - Epoch(train) [11][1160/1345] lr: 1.0000e-02 eta: 10:16:43 time: 0.1916 data_time: 0.0071 memory: 8327 grad_norm: 6.6087 loss: 4.1013 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5244 loss_aux: 1.5769 2023/02/17 12:57:47 - mmengine - INFO - Epoch(train) [11][1180/1345] lr: 1.0000e-02 eta: 10:16:37 time: 0.1905 data_time: 0.0055 memory: 8327 grad_norm: 6.6389 loss: 3.8415 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3029 loss_aux: 1.5385 2023/02/17 12:57:51 - mmengine - INFO - Epoch(train) [11][1200/1345] lr: 1.0000e-02 eta: 10:16:31 time: 0.1905 data_time: 0.0055 memory: 8327 grad_norm: 6.6833 loss: 4.2228 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6146 loss_aux: 1.6081 2023/02/17 12:57:55 - mmengine - INFO - Epoch(train) [11][1220/1345] lr: 1.0000e-02 eta: 10:16:25 time: 0.1899 data_time: 0.0055 memory: 8327 grad_norm: 6.7007 loss: 3.9774 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4085 loss_aux: 1.5689 2023/02/17 12:57:59 - mmengine - INFO - Epoch(train) [11][1240/1345] lr: 1.0000e-02 eta: 10:16:20 time: 0.1904 data_time: 0.0051 memory: 8327 grad_norm: 6.8601 loss: 4.3184 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6797 loss_aux: 1.6387 2023/02/17 12:58:02 - mmengine - INFO - Epoch(train) [11][1260/1345] lr: 1.0000e-02 eta: 10:16:14 time: 0.1916 data_time: 0.0054 memory: 8327 grad_norm: 6.8620 loss: 4.4872 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7736 loss_aux: 1.7136 2023/02/17 12:58:06 - mmengine - INFO - Epoch(train) [11][1280/1345] lr: 1.0000e-02 eta: 10:16:09 time: 0.1909 data_time: 0.0054 memory: 8327 grad_norm: 6.9262 loss: 4.3970 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6751 loss_aux: 1.7220 2023/02/17 12:58:10 - mmengine - INFO - Epoch(train) [11][1300/1345] lr: 1.0000e-02 eta: 10:16:03 time: 0.1905 data_time: 0.0055 memory: 8327 grad_norm: 6.6821 loss: 4.2774 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6304 loss_aux: 1.6470 2023/02/17 12:58:14 - mmengine - INFO - Epoch(train) [11][1320/1345] lr: 1.0000e-02 eta: 10:15:58 time: 0.1936 data_time: 0.0054 memory: 8327 grad_norm: 6.5889 loss: 3.8308 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3612 loss_aux: 1.4696 2023/02/17 12:58:18 - mmengine - INFO - Epoch(train) [11][1340/1345] lr: 1.0000e-02 eta: 10:15:52 time: 0.1906 data_time: 0.0054 memory: 8327 grad_norm: 6.5370 loss: 4.3230 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6995 loss_aux: 1.6235 2023/02/17 12:58:19 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:58:19 - mmengine - INFO - Epoch(train) [11][1345/1345] lr: 1.0000e-02 eta: 10:15:49 time: 0.1844 data_time: 0.0053 memory: 8327 grad_norm: 6.4371 loss: 4.4243 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.7732 loss_aux: 1.6511 2023/02/17 12:58:19 - mmengine - INFO - Saving checkpoint at 11 epochs 2023/02/17 12:58:26 - mmengine - INFO - Epoch(train) [12][ 20/1345] lr: 1.0000e-02 eta: 10:15:53 time: 0.2294 data_time: 0.0389 memory: 8327 grad_norm: 6.6745 loss: 4.0849 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4251 loss_aux: 1.6598 2023/02/17 12:58:30 - mmengine - INFO - Epoch(train) [12][ 40/1345] lr: 1.0000e-02 eta: 10:15:48 time: 0.1925 data_time: 0.0062 memory: 8327 grad_norm: 6.8638 loss: 4.1383 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5691 loss_aux: 1.5692 2023/02/17 12:58:33 - mmengine - INFO - Epoch(train) [12][ 60/1345] lr: 1.0000e-02 eta: 10:15:42 time: 0.1898 data_time: 0.0054 memory: 8327 grad_norm: 6.5776 loss: 3.9930 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4814 loss_aux: 1.5116 2023/02/17 12:58:37 - mmengine - INFO - Epoch(train) [12][ 80/1345] lr: 1.0000e-02 eta: 10:15:36 time: 0.1897 data_time: 0.0055 memory: 8327 grad_norm: 6.6545 loss: 4.3346 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6089 loss_aux: 1.7257 2023/02/17 12:58:41 - mmengine - INFO - Epoch(train) [12][ 100/1345] lr: 1.0000e-02 eta: 10:15:30 time: 0.1917 data_time: 0.0069 memory: 8327 grad_norm: 6.6852 loss: 3.9832 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.3920 loss_aux: 1.5912 2023/02/17 12:58:45 - mmengine - INFO - Epoch(train) [12][ 120/1345] lr: 1.0000e-02 eta: 10:15:24 time: 0.1900 data_time: 0.0055 memory: 8327 grad_norm: 6.9517 loss: 4.1302 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5527 loss_aux: 1.5775 2023/02/17 12:58:49 - mmengine - INFO - Epoch(train) [12][ 140/1345] lr: 1.0000e-02 eta: 10:15:19 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 6.9672 loss: 4.1171 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4915 loss_aux: 1.6256 2023/02/17 12:58:52 - mmengine - INFO - Epoch(train) [12][ 160/1345] lr: 1.0000e-02 eta: 10:15:13 time: 0.1897 data_time: 0.0052 memory: 8327 grad_norm: 6.8982 loss: 4.4333 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.7484 loss_aux: 1.6849 2023/02/17 12:58:56 - mmengine - INFO - Epoch(train) [12][ 180/1345] lr: 1.0000e-02 eta: 10:15:07 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 6.9125 loss: 4.1131 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5061 loss_aux: 1.6070 2023/02/17 12:59:00 - mmengine - INFO - Epoch(train) [12][ 200/1345] lr: 1.0000e-02 eta: 10:15:01 time: 0.1896 data_time: 0.0052 memory: 8327 grad_norm: 6.6583 loss: 4.4080 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6783 loss_aux: 1.7297 2023/02/17 12:59:01 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 12:59:04 - mmengine - INFO - Epoch(train) [12][ 220/1345] lr: 1.0000e-02 eta: 10:14:55 time: 0.1909 data_time: 0.0055 memory: 8327 grad_norm: 6.7994 loss: 4.0469 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4710 loss_aux: 1.5759 2023/02/17 12:59:08 - mmengine - INFO - Epoch(train) [12][ 240/1345] lr: 1.0000e-02 eta: 10:14:49 time: 0.1903 data_time: 0.0055 memory: 8327 grad_norm: 6.8961 loss: 4.2342 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5871 loss_aux: 1.6471 2023/02/17 12:59:11 - mmengine - INFO - Epoch(train) [12][ 260/1345] lr: 1.0000e-02 eta: 10:14:44 time: 0.1900 data_time: 0.0058 memory: 8327 grad_norm: 6.6001 loss: 4.1618 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.5414 loss_aux: 1.6204 2023/02/17 12:59:15 - mmengine - INFO - Epoch(train) [12][ 280/1345] lr: 1.0000e-02 eta: 10:14:38 time: 0.1893 data_time: 0.0052 memory: 8327 grad_norm: 6.7335 loss: 4.0576 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4940 loss_aux: 1.5635 2023/02/17 12:59:19 - mmengine - INFO - Epoch(train) [12][ 300/1345] lr: 1.0000e-02 eta: 10:14:32 time: 0.1893 data_time: 0.0054 memory: 8327 grad_norm: 6.7906 loss: 4.3648 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6676 loss_aux: 1.6971 2023/02/17 12:59:23 - mmengine - INFO - Epoch(train) [12][ 320/1345] lr: 1.0000e-02 eta: 10:14:26 time: 0.1902 data_time: 0.0055 memory: 8327 grad_norm: 6.6336 loss: 4.4113 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7437 loss_aux: 1.6677 2023/02/17 12:59:27 - mmengine - INFO - Epoch(train) [12][ 340/1345] lr: 1.0000e-02 eta: 10:14:20 time: 0.1899 data_time: 0.0054 memory: 8327 grad_norm: 6.8471 loss: 3.9870 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4620 loss_aux: 1.5249 2023/02/17 12:59:30 - mmengine - INFO - Epoch(train) [12][ 360/1345] lr: 1.0000e-02 eta: 10:14:14 time: 0.1899 data_time: 0.0055 memory: 8327 grad_norm: 6.7888 loss: 4.5035 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8076 loss_aux: 1.6960 2023/02/17 12:59:34 - mmengine - INFO - Epoch(train) [12][ 380/1345] lr: 1.0000e-02 eta: 10:14:08 time: 0.1895 data_time: 0.0052 memory: 8327 grad_norm: 6.9427 loss: 4.0926 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4815 loss_aux: 1.6111 2023/02/17 12:59:38 - mmengine - INFO - Epoch(train) [12][ 400/1345] lr: 1.0000e-02 eta: 10:14:02 time: 0.1903 data_time: 0.0055 memory: 8327 grad_norm: 6.7550 loss: 4.0409 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4501 loss_aux: 1.5908 2023/02/17 12:59:42 - mmengine - INFO - Epoch(train) [12][ 420/1345] lr: 1.0000e-02 eta: 10:13:57 time: 0.1895 data_time: 0.0053 memory: 8327 grad_norm: 6.5610 loss: 4.5901 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8533 loss_aux: 1.7368 2023/02/17 12:59:45 - mmengine - INFO - Epoch(train) [12][ 440/1345] lr: 1.0000e-02 eta: 10:13:51 time: 0.1896 data_time: 0.0054 memory: 8327 grad_norm: 6.6855 loss: 4.2727 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6503 loss_aux: 1.6224 2023/02/17 12:59:49 - mmengine - INFO - Epoch(train) [12][ 460/1345] lr: 1.0000e-02 eta: 10:13:45 time: 0.1896 data_time: 0.0056 memory: 8327 grad_norm: 6.7182 loss: 4.1243 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5198 loss_aux: 1.6044 2023/02/17 12:59:53 - mmengine - INFO - Epoch(train) [12][ 480/1345] lr: 1.0000e-02 eta: 10:13:39 time: 0.1905 data_time: 0.0062 memory: 8327 grad_norm: 7.0082 loss: 4.5641 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8451 loss_aux: 1.7190 2023/02/17 12:59:57 - mmengine - INFO - Epoch(train) [12][ 500/1345] lr: 1.0000e-02 eta: 10:13:33 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 6.7211 loss: 4.4345 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.7304 loss_aux: 1.7041 2023/02/17 13:00:01 - mmengine - INFO - Epoch(train) [12][ 520/1345] lr: 1.0000e-02 eta: 10:13:28 time: 0.1904 data_time: 0.0053 memory: 8327 grad_norm: 6.6986 loss: 3.9775 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4135 loss_aux: 1.5640 2023/02/17 13:00:04 - mmengine - INFO - Epoch(train) [12][ 540/1345] lr: 1.0000e-02 eta: 10:13:22 time: 0.1894 data_time: 0.0053 memory: 8327 grad_norm: 6.9223 loss: 4.1839 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5445 loss_aux: 1.6394 2023/02/17 13:00:08 - mmengine - INFO - Epoch(train) [12][ 560/1345] lr: 1.0000e-02 eta: 10:13:16 time: 0.1898 data_time: 0.0055 memory: 8327 grad_norm: 6.7279 loss: 4.0633 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5033 loss_aux: 1.5600 2023/02/17 13:00:12 - mmengine - INFO - Epoch(train) [12][ 580/1345] lr: 1.0000e-02 eta: 10:13:10 time: 0.1900 data_time: 0.0055 memory: 8327 grad_norm: 6.8162 loss: 4.2517 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6122 loss_aux: 1.6395 2023/02/17 13:00:16 - mmengine - INFO - Epoch(train) [12][ 600/1345] lr: 1.0000e-02 eta: 10:13:04 time: 0.1901 data_time: 0.0053 memory: 8327 grad_norm: 6.8439 loss: 4.2398 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6304 loss_aux: 1.6094 2023/02/17 13:00:20 - mmengine - INFO - Epoch(train) [12][ 620/1345] lr: 1.0000e-02 eta: 10:12:59 time: 0.1901 data_time: 0.0055 memory: 8327 grad_norm: 6.9303 loss: 4.1910 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5810 loss_aux: 1.6100 2023/02/17 13:00:23 - mmengine - INFO - Epoch(train) [12][ 640/1345] lr: 1.0000e-02 eta: 10:12:53 time: 0.1895 data_time: 0.0054 memory: 8327 grad_norm: 6.6448 loss: 4.1204 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4635 loss_aux: 1.6569 2023/02/17 13:00:27 - mmengine - INFO - Epoch(train) [12][ 660/1345] lr: 1.0000e-02 eta: 10:12:47 time: 0.1897 data_time: 0.0055 memory: 8327 grad_norm: 6.7793 loss: 4.4694 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7743 loss_aux: 1.6951 2023/02/17 13:00:31 - mmengine - INFO - Epoch(train) [12][ 680/1345] lr: 1.0000e-02 eta: 10:12:41 time: 0.1897 data_time: 0.0052 memory: 8327 grad_norm: 6.7798 loss: 4.5059 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8604 loss_aux: 1.6455 2023/02/17 13:00:35 - mmengine - INFO - Epoch(train) [12][ 700/1345] lr: 1.0000e-02 eta: 10:12:36 time: 0.1898 data_time: 0.0056 memory: 8327 grad_norm: 6.9067 loss: 4.2739 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6150 loss_aux: 1.6589 2023/02/17 13:00:39 - mmengine - INFO - Epoch(train) [12][ 720/1345] lr: 1.0000e-02 eta: 10:12:30 time: 0.1900 data_time: 0.0054 memory: 8327 grad_norm: 6.9671 loss: 4.5293 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8293 loss_aux: 1.7000 2023/02/17 13:00:42 - mmengine - INFO - Epoch(train) [12][ 740/1345] lr: 1.0000e-02 eta: 10:12:24 time: 0.1905 data_time: 0.0051 memory: 8327 grad_norm: 6.6307 loss: 4.4422 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7241 loss_aux: 1.7181 2023/02/17 13:00:46 - mmengine - INFO - Epoch(train) [12][ 760/1345] lr: 1.0000e-02 eta: 10:12:18 time: 0.1891 data_time: 0.0054 memory: 8327 grad_norm: 6.7655 loss: 4.2636 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6170 loss_aux: 1.6466 2023/02/17 13:00:50 - mmengine - INFO - Epoch(train) [12][ 780/1345] lr: 1.0000e-02 eta: 10:12:13 time: 0.1901 data_time: 0.0055 memory: 8327 grad_norm: 6.9947 loss: 4.4952 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8054 loss_aux: 1.6898 2023/02/17 13:00:54 - mmengine - INFO - Epoch(train) [12][ 800/1345] lr: 1.0000e-02 eta: 10:12:07 time: 0.1902 data_time: 0.0059 memory: 8327 grad_norm: 6.9371 loss: 4.4518 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7497 loss_aux: 1.7021 2023/02/17 13:00:58 - mmengine - INFO - Epoch(train) [12][ 820/1345] lr: 1.0000e-02 eta: 10:12:01 time: 0.1897 data_time: 0.0054 memory: 8327 grad_norm: 7.0069 loss: 3.8806 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3800 loss_aux: 1.5005 2023/02/17 13:01:01 - mmengine - INFO - Epoch(train) [12][ 840/1345] lr: 1.0000e-02 eta: 10:11:56 time: 0.1905 data_time: 0.0060 memory: 8327 grad_norm: 6.8790 loss: 4.0631 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 2.4823 loss_aux: 1.5808 2023/02/17 13:01:05 - mmengine - INFO - Epoch(train) [12][ 860/1345] lr: 1.0000e-02 eta: 10:11:50 time: 0.1903 data_time: 0.0055 memory: 8327 grad_norm: 6.7178 loss: 3.5290 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1219 loss_aux: 1.4071 2023/02/17 13:01:09 - mmengine - INFO - Epoch(train) [12][ 880/1345] lr: 1.0000e-02 eta: 10:11:44 time: 0.1901 data_time: 0.0058 memory: 8327 grad_norm: 6.7937 loss: 4.1513 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5282 loss_aux: 1.6231 2023/02/17 13:01:13 - mmengine - INFO - Epoch(train) [12][ 900/1345] lr: 1.0000e-02 eta: 10:11:39 time: 0.1896 data_time: 0.0054 memory: 8327 grad_norm: 6.8609 loss: 4.3794 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.7023 loss_aux: 1.6772 2023/02/17 13:01:17 - mmengine - INFO - Epoch(train) [12][ 920/1345] lr: 1.0000e-02 eta: 10:11:33 time: 0.1896 data_time: 0.0054 memory: 8327 grad_norm: 6.8710 loss: 4.3801 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6685 loss_aux: 1.7116 2023/02/17 13:01:20 - mmengine - INFO - Epoch(train) [12][ 940/1345] lr: 1.0000e-02 eta: 10:11:27 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 6.7847 loss: 4.3041 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6689 loss_aux: 1.6352 2023/02/17 13:01:24 - mmengine - INFO - Epoch(train) [12][ 960/1345] lr: 1.0000e-02 eta: 10:11:21 time: 0.1900 data_time: 0.0055 memory: 8327 grad_norm: 6.9099 loss: 4.1290 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5568 loss_aux: 1.5722 2023/02/17 13:01:28 - mmengine - INFO - Epoch(train) [12][ 980/1345] lr: 1.0000e-02 eta: 10:11:16 time: 0.1895 data_time: 0.0053 memory: 8327 grad_norm: 6.9178 loss: 4.4579 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7830 loss_aux: 1.6748 2023/02/17 13:01:32 - mmengine - INFO - Epoch(train) [12][1000/1345] lr: 1.0000e-02 eta: 10:11:10 time: 0.1898 data_time: 0.0055 memory: 8327 grad_norm: 6.8182 loss: 4.0118 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4646 loss_aux: 1.5472 2023/02/17 13:01:36 - mmengine - INFO - Epoch(train) [12][1020/1345] lr: 1.0000e-02 eta: 10:11:04 time: 0.1893 data_time: 0.0054 memory: 8327 grad_norm: 6.8544 loss: 4.4813 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8125 loss_aux: 1.6688 2023/02/17 13:01:39 - mmengine - INFO - Epoch(train) [12][1040/1345] lr: 1.0000e-02 eta: 10:10:58 time: 0.1899 data_time: 0.0055 memory: 8327 grad_norm: 6.9492 loss: 4.2172 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6404 loss_aux: 1.5768 2023/02/17 13:01:43 - mmengine - INFO - Epoch(train) [12][1060/1345] lr: 1.0000e-02 eta: 10:10:53 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 6.7524 loss: 4.2848 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6408 loss_aux: 1.6440 2023/02/17 13:01:47 - mmengine - INFO - Epoch(train) [12][1080/1345] lr: 1.0000e-02 eta: 10:10:48 time: 0.1923 data_time: 0.0056 memory: 8327 grad_norm: 6.5829 loss: 4.2328 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6274 loss_aux: 1.6054 2023/02/17 13:01:51 - mmengine - INFO - Epoch(train) [12][1100/1345] lr: 1.0000e-02 eta: 10:10:42 time: 0.1908 data_time: 0.0053 memory: 8327 grad_norm: 6.8383 loss: 4.6671 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8701 loss_aux: 1.7970 2023/02/17 13:01:55 - mmengine - INFO - Epoch(train) [12][1120/1345] lr: 1.0000e-02 eta: 10:10:37 time: 0.1896 data_time: 0.0054 memory: 8327 grad_norm: 6.8414 loss: 4.3279 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6962 loss_aux: 1.6316 2023/02/17 13:01:58 - mmengine - INFO - Epoch(train) [12][1140/1345] lr: 1.0000e-02 eta: 10:10:31 time: 0.1899 data_time: 0.0055 memory: 8327 grad_norm: 6.8370 loss: 3.9216 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3728 loss_aux: 1.5487 2023/02/17 13:02:02 - mmengine - INFO - Epoch(train) [12][1160/1345] lr: 1.0000e-02 eta: 10:10:25 time: 0.1898 data_time: 0.0053 memory: 8327 grad_norm: 6.7504 loss: 4.3446 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7246 loss_aux: 1.6200 2023/02/17 13:02:06 - mmengine - INFO - Epoch(train) [12][1180/1345] lr: 1.0000e-02 eta: 10:10:20 time: 0.1895 data_time: 0.0054 memory: 8327 grad_norm: 6.6562 loss: 4.2639 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6540 loss_aux: 1.6100 2023/02/17 13:02:10 - mmengine - INFO - Epoch(train) [12][1200/1345] lr: 1.0000e-02 eta: 10:10:14 time: 0.1897 data_time: 0.0057 memory: 8327 grad_norm: 6.9585 loss: 4.4769 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7778 loss_aux: 1.6991 2023/02/17 13:02:11 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:02:14 - mmengine - INFO - Epoch(train) [12][1220/1345] lr: 1.0000e-02 eta: 10:10:08 time: 0.1896 data_time: 0.0052 memory: 8327 grad_norm: 6.7657 loss: 4.1692 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5684 loss_aux: 1.6008 2023/02/17 13:02:17 - mmengine - INFO - Epoch(train) [12][1240/1345] lr: 1.0000e-02 eta: 10:10:03 time: 0.1905 data_time: 0.0053 memory: 8327 grad_norm: 6.9273 loss: 4.2777 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6656 loss_aux: 1.6121 2023/02/17 13:02:21 - mmengine - INFO - Epoch(train) [12][1260/1345] lr: 1.0000e-02 eta: 10:09:57 time: 0.1915 data_time: 0.0055 memory: 8327 grad_norm: 6.7502 loss: 4.2987 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.6207 loss_aux: 1.6780 2023/02/17 13:02:25 - mmengine - INFO - Epoch(train) [12][1280/1345] lr: 1.0000e-02 eta: 10:09:52 time: 0.1926 data_time: 0.0056 memory: 8327 grad_norm: 6.7484 loss: 3.8709 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3610 loss_aux: 1.5099 2023/02/17 13:02:29 - mmengine - INFO - Epoch(train) [12][1300/1345] lr: 1.0000e-02 eta: 10:09:47 time: 0.1901 data_time: 0.0054 memory: 8327 grad_norm: 6.6623 loss: 4.0783 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5320 loss_aux: 1.5462 2023/02/17 13:02:33 - mmengine - INFO - Epoch(train) [12][1320/1345] lr: 1.0000e-02 eta: 10:09:41 time: 0.1896 data_time: 0.0054 memory: 8327 grad_norm: 6.7640 loss: 3.7989 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2935 loss_aux: 1.5054 2023/02/17 13:02:37 - mmengine - INFO - Epoch(train) [12][1340/1345] lr: 1.0000e-02 eta: 10:09:36 time: 0.1911 data_time: 0.0058 memory: 8327 grad_norm: 6.7856 loss: 4.4047 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7710 loss_aux: 1.6337 2023/02/17 13:02:37 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:02:37 - mmengine - INFO - Epoch(train) [12][1345/1345] lr: 1.0000e-02 eta: 10:09:33 time: 0.1859 data_time: 0.0056 memory: 8327 grad_norm: 6.6910 loss: 4.6900 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.9505 loss_aux: 1.7395 2023/02/17 13:02:37 - mmengine - INFO - Saving checkpoint at 12 epochs 2023/02/17 13:02:44 - mmengine - INFO - Epoch(train) [13][ 20/1345] lr: 1.0000e-02 eta: 10:09:35 time: 0.2199 data_time: 0.0295 memory: 8327 grad_norm: 6.7966 loss: 4.0790 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4874 loss_aux: 1.5916 2023/02/17 13:02:48 - mmengine - INFO - Epoch(train) [13][ 40/1345] lr: 1.0000e-02 eta: 10:09:29 time: 0.1901 data_time: 0.0038 memory: 8327 grad_norm: 6.5960 loss: 3.8728 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3591 loss_aux: 1.5137 2023/02/17 13:02:52 - mmengine - INFO - Epoch(train) [13][ 60/1345] lr: 1.0000e-02 eta: 10:09:23 time: 0.1893 data_time: 0.0056 memory: 8327 grad_norm: 6.8072 loss: 3.9422 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4593 loss_aux: 1.4829 2023/02/17 13:02:56 - mmengine - INFO - Epoch(train) [13][ 80/1345] lr: 1.0000e-02 eta: 10:09:18 time: 0.1906 data_time: 0.0054 memory: 8327 grad_norm: 6.8089 loss: 4.3773 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.6920 loss_aux: 1.6853 2023/02/17 13:02:59 - mmengine - INFO - Epoch(train) [13][ 100/1345] lr: 1.0000e-02 eta: 10:09:12 time: 0.1901 data_time: 0.0063 memory: 8327 grad_norm: 6.8688 loss: 4.4540 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7633 loss_aux: 1.6906 2023/02/17 13:03:03 - mmengine - INFO - Epoch(train) [13][ 120/1345] lr: 1.0000e-02 eta: 10:09:07 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 6.7760 loss: 4.3449 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6887 loss_aux: 1.6562 2023/02/17 13:03:07 - mmengine - INFO - Epoch(train) [13][ 140/1345] lr: 1.0000e-02 eta: 10:09:01 time: 0.1902 data_time: 0.0053 memory: 8327 grad_norm: 6.7079 loss: 4.1623 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5957 loss_aux: 1.5666 2023/02/17 13:03:11 - mmengine - INFO - Epoch(train) [13][ 160/1345] lr: 1.0000e-02 eta: 10:08:56 time: 0.1892 data_time: 0.0055 memory: 8327 grad_norm: 6.5682 loss: 4.1722 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5120 loss_aux: 1.6603 2023/02/17 13:03:15 - mmengine - INFO - Epoch(train) [13][ 180/1345] lr: 1.0000e-02 eta: 10:08:50 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 6.8187 loss: 3.4717 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0759 loss_aux: 1.3958 2023/02/17 13:03:18 - mmengine - INFO - Epoch(train) [13][ 200/1345] lr: 1.0000e-02 eta: 10:08:44 time: 0.1895 data_time: 0.0054 memory: 8327 grad_norm: 6.8544 loss: 4.4221 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6938 loss_aux: 1.7282 2023/02/17 13:03:22 - mmengine - INFO - Epoch(train) [13][ 220/1345] lr: 1.0000e-02 eta: 10:08:39 time: 0.1892 data_time: 0.0053 memory: 8327 grad_norm: 6.8308 loss: 4.0206 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4901 loss_aux: 1.5305 2023/02/17 13:03:26 - mmengine - INFO - Epoch(train) [13][ 240/1345] lr: 1.0000e-02 eta: 10:08:33 time: 0.1907 data_time: 0.0062 memory: 8327 grad_norm: 6.9144 loss: 4.2251 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5474 loss_aux: 1.6777 2023/02/17 13:03:30 - mmengine - INFO - Epoch(train) [13][ 260/1345] lr: 1.0000e-02 eta: 10:08:28 time: 0.1902 data_time: 0.0054 memory: 8327 grad_norm: 6.8748 loss: 4.3844 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7505 loss_aux: 1.6339 2023/02/17 13:03:34 - mmengine - INFO - Epoch(train) [13][ 280/1345] lr: 1.0000e-02 eta: 10:08:22 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 6.9547 loss: 4.2283 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5989 loss_aux: 1.6294 2023/02/17 13:03:37 - mmengine - INFO - Epoch(train) [13][ 300/1345] lr: 1.0000e-02 eta: 10:08:17 time: 0.1892 data_time: 0.0055 memory: 8327 grad_norm: 6.9158 loss: 4.3294 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7256 loss_aux: 1.6039 2023/02/17 13:03:41 - mmengine - INFO - Epoch(train) [13][ 320/1345] lr: 1.0000e-02 eta: 10:08:11 time: 0.1893 data_time: 0.0052 memory: 8327 grad_norm: 6.9968 loss: 4.2123 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6414 loss_aux: 1.5709 2023/02/17 13:03:45 - mmengine - INFO - Epoch(train) [13][ 340/1345] lr: 1.0000e-02 eta: 10:08:05 time: 0.1894 data_time: 0.0054 memory: 8327 grad_norm: 6.7765 loss: 4.1859 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5425 loss_aux: 1.6434 2023/02/17 13:03:49 - mmengine - INFO - Epoch(train) [13][ 360/1345] lr: 1.0000e-02 eta: 10:08:00 time: 0.1897 data_time: 0.0055 memory: 8327 grad_norm: 6.8331 loss: 3.7599 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2860 loss_aux: 1.4739 2023/02/17 13:03:52 - mmengine - INFO - Epoch(train) [13][ 380/1345] lr: 1.0000e-02 eta: 10:07:54 time: 0.1893 data_time: 0.0053 memory: 8327 grad_norm: 6.6687 loss: 3.7158 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2260 loss_aux: 1.4898 2023/02/17 13:03:57 - mmengine - INFO - Epoch(train) [13][ 400/1345] lr: 1.0000e-02 eta: 10:07:53 time: 0.2107 data_time: 0.0264 memory: 8327 grad_norm: 6.7801 loss: 4.0852 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5335 loss_aux: 1.5517 2023/02/17 13:04:00 - mmengine - INFO - Epoch(train) [13][ 420/1345] lr: 1.0000e-02 eta: 10:07:48 time: 0.1902 data_time: 0.0058 memory: 8327 grad_norm: 6.8994 loss: 4.1338 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5625 loss_aux: 1.5713 2023/02/17 13:04:04 - mmengine - INFO - Epoch(train) [13][ 440/1345] lr: 1.0000e-02 eta: 10:07:42 time: 0.1898 data_time: 0.0054 memory: 8327 grad_norm: 6.8038 loss: 4.0089 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4418 loss_aux: 1.5672 2023/02/17 13:04:08 - mmengine - INFO - Epoch(train) [13][ 460/1345] lr: 1.0000e-02 eta: 10:07:37 time: 0.1900 data_time: 0.0055 memory: 8327 grad_norm: 6.7315 loss: 4.5962 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8942 loss_aux: 1.7021 2023/02/17 13:04:12 - mmengine - INFO - Epoch(train) [13][ 480/1345] lr: 1.0000e-02 eta: 10:07:31 time: 0.1899 data_time: 0.0054 memory: 8327 grad_norm: 6.7408 loss: 4.2425 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6040 loss_aux: 1.6385 2023/02/17 13:04:16 - mmengine - INFO - Epoch(train) [13][ 500/1345] lr: 1.0000e-02 eta: 10:07:25 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 6.8463 loss: 4.4036 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7287 loss_aux: 1.6749 2023/02/17 13:04:19 - mmengine - INFO - Epoch(train) [13][ 520/1345] lr: 1.0000e-02 eta: 10:07:20 time: 0.1900 data_time: 0.0051 memory: 8327 grad_norm: 6.6944 loss: 4.0747 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4363 loss_aux: 1.6383 2023/02/17 13:04:23 - mmengine - INFO - Epoch(train) [13][ 540/1345] lr: 1.0000e-02 eta: 10:07:14 time: 0.1893 data_time: 0.0056 memory: 8327 grad_norm: 6.8780 loss: 4.1635 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5526 loss_aux: 1.6109 2023/02/17 13:04:27 - mmengine - INFO - Epoch(train) [13][ 560/1345] lr: 1.0000e-02 eta: 10:07:09 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 6.8632 loss: 4.2004 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6453 loss_aux: 1.5551 2023/02/17 13:04:31 - mmengine - INFO - Epoch(train) [13][ 580/1345] lr: 1.0000e-02 eta: 10:07:04 time: 0.1908 data_time: 0.0056 memory: 8327 grad_norm: 6.7172 loss: 3.8917 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3844 loss_aux: 1.5073 2023/02/17 13:04:35 - mmengine - INFO - Epoch(train) [13][ 600/1345] lr: 1.0000e-02 eta: 10:06:58 time: 0.1906 data_time: 0.0064 memory: 8327 grad_norm: 6.7136 loss: 4.0614 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4643 loss_aux: 1.5971 2023/02/17 13:04:38 - mmengine - INFO - Epoch(train) [13][ 620/1345] lr: 1.0000e-02 eta: 10:06:53 time: 0.1892 data_time: 0.0054 memory: 8327 grad_norm: 6.6319 loss: 4.5375 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8447 loss_aux: 1.6928 2023/02/17 13:04:42 - mmengine - INFO - Epoch(train) [13][ 640/1345] lr: 1.0000e-02 eta: 10:06:47 time: 0.1902 data_time: 0.0056 memory: 8327 grad_norm: 6.6233 loss: 3.9143 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4292 loss_aux: 1.4852 2023/02/17 13:04:46 - mmengine - INFO - Epoch(train) [13][ 660/1345] lr: 1.0000e-02 eta: 10:06:42 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 6.9219 loss: 4.1806 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5849 loss_aux: 1.5956 2023/02/17 13:04:50 - mmengine - INFO - Epoch(train) [13][ 680/1345] lr: 1.0000e-02 eta: 10:06:36 time: 0.1904 data_time: 0.0058 memory: 8327 grad_norm: 7.0297 loss: 4.0060 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4344 loss_aux: 1.5716 2023/02/17 13:04:54 - mmengine - INFO - Epoch(train) [13][ 700/1345] lr: 1.0000e-02 eta: 10:06:31 time: 0.1892 data_time: 0.0053 memory: 8327 grad_norm: 7.1107 loss: 4.1724 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5579 loss_aux: 1.6146 2023/02/17 13:04:57 - mmengine - INFO - Epoch(train) [13][ 720/1345] lr: 1.0000e-02 eta: 10:06:25 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 6.7865 loss: 3.9286 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3927 loss_aux: 1.5360 2023/02/17 13:05:01 - mmengine - INFO - Epoch(train) [13][ 740/1345] lr: 1.0000e-02 eta: 10:06:20 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 6.8702 loss: 4.5118 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.7822 loss_aux: 1.7297 2023/02/17 13:05:05 - mmengine - INFO - Epoch(train) [13][ 760/1345] lr: 1.0000e-02 eta: 10:06:14 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 6.8281 loss: 4.2344 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6070 loss_aux: 1.6275 2023/02/17 13:05:09 - mmengine - INFO - Epoch(train) [13][ 780/1345] lr: 1.0000e-02 eta: 10:06:09 time: 0.1902 data_time: 0.0053 memory: 8327 grad_norm: 6.8378 loss: 4.0943 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4704 loss_aux: 1.6239 2023/02/17 13:05:13 - mmengine - INFO - Epoch(train) [13][ 800/1345] lr: 1.0000e-02 eta: 10:06:03 time: 0.1893 data_time: 0.0053 memory: 8327 grad_norm: 6.8105 loss: 4.1496 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5647 loss_aux: 1.5849 2023/02/17 13:05:16 - mmengine - INFO - Epoch(train) [13][ 820/1345] lr: 1.0000e-02 eta: 10:05:58 time: 0.1899 data_time: 0.0054 memory: 8327 grad_norm: 6.8511 loss: 4.3087 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6991 loss_aux: 1.6096 2023/02/17 13:05:20 - mmengine - INFO - Epoch(train) [13][ 840/1345] lr: 1.0000e-02 eta: 10:05:53 time: 0.1902 data_time: 0.0054 memory: 8327 grad_norm: 7.0173 loss: 4.3602 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7267 loss_aux: 1.6335 2023/02/17 13:05:24 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:05:24 - mmengine - INFO - Epoch(train) [13][ 860/1345] lr: 1.0000e-02 eta: 10:05:47 time: 0.1907 data_time: 0.0055 memory: 8327 grad_norm: 6.9136 loss: 4.0025 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4462 loss_aux: 1.5563 2023/02/17 13:05:28 - mmengine - INFO - Epoch(train) [13][ 880/1345] lr: 1.0000e-02 eta: 10:05:42 time: 0.1899 data_time: 0.0055 memory: 8327 grad_norm: 6.7500 loss: 4.2131 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6398 loss_aux: 1.5733 2023/02/17 13:05:32 - mmengine - INFO - Epoch(train) [13][ 900/1345] lr: 1.0000e-02 eta: 10:05:41 time: 0.2099 data_time: 0.0256 memory: 8327 grad_norm: 6.6808 loss: 4.1568 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5567 loss_aux: 1.6002 2023/02/17 13:05:36 - mmengine - INFO - Epoch(train) [13][ 920/1345] lr: 1.0000e-02 eta: 10:05:35 time: 0.1893 data_time: 0.0055 memory: 8327 grad_norm: 6.9400 loss: 4.1783 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5924 loss_aux: 1.5859 2023/02/17 13:05:40 - mmengine - INFO - Epoch(train) [13][ 940/1345] lr: 1.0000e-02 eta: 10:05:30 time: 0.1902 data_time: 0.0060 memory: 8327 grad_norm: 6.9226 loss: 4.3505 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7191 loss_aux: 1.6314 2023/02/17 13:05:44 - mmengine - INFO - Epoch(train) [13][ 960/1345] lr: 1.0000e-02 eta: 10:05:29 time: 0.2093 data_time: 0.0255 memory: 8327 grad_norm: 6.9042 loss: 4.1294 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.5736 loss_aux: 1.5558 2023/02/17 13:05:48 - mmengine - INFO - Epoch(train) [13][ 980/1345] lr: 1.0000e-02 eta: 10:05:23 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 6.8626 loss: 3.9279 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3941 loss_aux: 1.5339 2023/02/17 13:05:51 - mmengine - INFO - Epoch(train) [13][1000/1345] lr: 1.0000e-02 eta: 10:05:18 time: 0.1899 data_time: 0.0052 memory: 8327 grad_norm: 6.7714 loss: 4.1195 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5480 loss_aux: 1.5715 2023/02/17 13:05:55 - mmengine - INFO - Epoch(train) [13][1020/1345] lr: 1.0000e-02 eta: 10:05:12 time: 0.1892 data_time: 0.0054 memory: 8327 grad_norm: 6.6295 loss: 4.1220 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5642 loss_aux: 1.5578 2023/02/17 13:05:59 - mmengine - INFO - Epoch(train) [13][1040/1345] lr: 1.0000e-02 eta: 10:05:07 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 6.6607 loss: 4.1330 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5514 loss_aux: 1.5816 2023/02/17 13:06:03 - mmengine - INFO - Epoch(train) [13][1060/1345] lr: 1.0000e-02 eta: 10:05:01 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 6.8491 loss: 4.1678 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5176 loss_aux: 1.6502 2023/02/17 13:06:07 - mmengine - INFO - Epoch(train) [13][1080/1345] lr: 1.0000e-02 eta: 10:04:56 time: 0.1893 data_time: 0.0053 memory: 8327 grad_norm: 6.8520 loss: 4.3698 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7104 loss_aux: 1.6594 2023/02/17 13:06:10 - mmengine - INFO - Epoch(train) [13][1100/1345] lr: 1.0000e-02 eta: 10:04:51 time: 0.1918 data_time: 0.0067 memory: 8327 grad_norm: 6.6377 loss: 3.8554 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3293 loss_aux: 1.5260 2023/02/17 13:06:14 - mmengine - INFO - Epoch(train) [13][1120/1345] lr: 1.0000e-02 eta: 10:04:45 time: 0.1901 data_time: 0.0054 memory: 8327 grad_norm: 6.6622 loss: 4.3073 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6671 loss_aux: 1.6402 2023/02/17 13:06:18 - mmengine - INFO - Epoch(train) [13][1140/1345] lr: 1.0000e-02 eta: 10:04:40 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 6.7619 loss: 4.2226 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6138 loss_aux: 1.6089 2023/02/17 13:06:22 - mmengine - INFO - Epoch(train) [13][1160/1345] lr: 1.0000e-02 eta: 10:04:34 time: 0.1888 data_time: 0.0052 memory: 8327 grad_norm: 6.8112 loss: 3.7216 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2521 loss_aux: 1.4695 2023/02/17 13:06:26 - mmengine - INFO - Epoch(train) [13][1180/1345] lr: 1.0000e-02 eta: 10:04:29 time: 0.1892 data_time: 0.0054 memory: 8327 grad_norm: 6.9032 loss: 4.3122 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6350 loss_aux: 1.6773 2023/02/17 13:06:29 - mmengine - INFO - Epoch(train) [13][1200/1345] lr: 1.0000e-02 eta: 10:04:23 time: 0.1898 data_time: 0.0056 memory: 8327 grad_norm: 6.8339 loss: 4.1482 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5788 loss_aux: 1.5695 2023/02/17 13:06:33 - mmengine - INFO - Epoch(train) [13][1220/1345] lr: 1.0000e-02 eta: 10:04:18 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 6.6252 loss: 4.0972 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5385 loss_aux: 1.5587 2023/02/17 13:06:37 - mmengine - INFO - Epoch(train) [13][1240/1345] lr: 1.0000e-02 eta: 10:04:12 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 6.7851 loss: 4.1358 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5653 loss_aux: 1.5705 2023/02/17 13:06:41 - mmengine - INFO - Epoch(train) [13][1260/1345] lr: 1.0000e-02 eta: 10:04:07 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 6.7489 loss: 3.8967 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4032 loss_aux: 1.4934 2023/02/17 13:06:45 - mmengine - INFO - Epoch(train) [13][1280/1345] lr: 1.0000e-02 eta: 10:04:02 time: 0.1904 data_time: 0.0059 memory: 8327 grad_norm: 6.6959 loss: 4.1798 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5984 loss_aux: 1.5814 2023/02/17 13:06:48 - mmengine - INFO - Epoch(train) [13][1300/1345] lr: 1.0000e-02 eta: 10:03:56 time: 0.1897 data_time: 0.0063 memory: 8327 grad_norm: 6.8321 loss: 4.1294 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5446 loss_aux: 1.5849 2023/02/17 13:06:52 - mmengine - INFO - Epoch(train) [13][1320/1345] lr: 1.0000e-02 eta: 10:03:51 time: 0.1895 data_time: 0.0054 memory: 8327 grad_norm: 6.8362 loss: 3.9292 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4070 loss_aux: 1.5222 2023/02/17 13:06:56 - mmengine - INFO - Epoch(train) [13][1340/1345] lr: 1.0000e-02 eta: 10:03:45 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 6.7436 loss: 3.6418 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2334 loss_aux: 1.4084 2023/02/17 13:06:57 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:06:57 - mmengine - INFO - Epoch(train) [13][1345/1345] lr: 1.0000e-02 eta: 10:03:43 time: 0.1829 data_time: 0.0057 memory: 8327 grad_norm: 6.6652 loss: 3.9171 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.4172 loss_aux: 1.4999 2023/02/17 13:06:57 - mmengine - INFO - Saving checkpoint at 13 epochs 2023/02/17 13:07:04 - mmengine - INFO - Epoch(train) [14][ 20/1345] lr: 1.0000e-02 eta: 10:03:43 time: 0.2179 data_time: 0.0283 memory: 8327 grad_norm: 6.6576 loss: 4.4866 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7673 loss_aux: 1.7193 2023/02/17 13:07:07 - mmengine - INFO - Epoch(train) [14][ 40/1345] lr: 1.0000e-02 eta: 10:03:38 time: 0.1893 data_time: 0.0041 memory: 8327 grad_norm: 6.7643 loss: 4.4225 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7192 loss_aux: 1.7033 2023/02/17 13:07:11 - mmengine - INFO - Epoch(train) [14][ 60/1345] lr: 1.0000e-02 eta: 10:03:33 time: 0.1903 data_time: 0.0056 memory: 8327 grad_norm: 6.7493 loss: 4.0554 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4922 loss_aux: 1.5632 2023/02/17 13:07:15 - mmengine - INFO - Epoch(train) [14][ 80/1345] lr: 1.0000e-02 eta: 10:03:27 time: 0.1896 data_time: 0.0056 memory: 8327 grad_norm: 6.7071 loss: 3.9033 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3795 loss_aux: 1.5238 2023/02/17 13:07:19 - mmengine - INFO - Epoch(train) [14][ 100/1345] lr: 1.0000e-02 eta: 10:03:22 time: 0.1895 data_time: 0.0056 memory: 8327 grad_norm: 6.7276 loss: 4.1046 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5820 loss_aux: 1.5227 2023/02/17 13:07:23 - mmengine - INFO - Epoch(train) [14][ 120/1345] lr: 1.0000e-02 eta: 10:03:16 time: 0.1894 data_time: 0.0053 memory: 8327 grad_norm: 6.9867 loss: 4.6018 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8276 loss_aux: 1.7742 2023/02/17 13:07:26 - mmengine - INFO - Epoch(train) [14][ 140/1345] lr: 1.0000e-02 eta: 10:03:11 time: 0.1903 data_time: 0.0066 memory: 8327 grad_norm: 6.8565 loss: 3.7009 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.2320 loss_aux: 1.4689 2023/02/17 13:07:30 - mmengine - INFO - Epoch(train) [14][ 160/1345] lr: 1.0000e-02 eta: 10:03:06 time: 0.1898 data_time: 0.0062 memory: 8327 grad_norm: 6.8412 loss: 4.4053 top1_acc: 0.1250 top5_acc: 0.8750 loss_cls: 2.7144 loss_aux: 1.6909 2023/02/17 13:07:34 - mmengine - INFO - Epoch(train) [14][ 180/1345] lr: 1.0000e-02 eta: 10:03:00 time: 0.1887 data_time: 0.0055 memory: 8327 grad_norm: 6.8840 loss: 4.0158 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4631 loss_aux: 1.5526 2023/02/17 13:07:38 - mmengine - INFO - Epoch(train) [14][ 200/1345] lr: 1.0000e-02 eta: 10:02:55 time: 0.1896 data_time: 0.0056 memory: 8327 grad_norm: 6.6409 loss: 3.9502 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4030 loss_aux: 1.5472 2023/02/17 13:07:42 - mmengine - INFO - Epoch(train) [14][ 220/1345] lr: 1.0000e-02 eta: 10:02:49 time: 0.1893 data_time: 0.0055 memory: 8327 grad_norm: 6.8739 loss: 3.9773 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3985 loss_aux: 1.5788 2023/02/17 13:07:45 - mmengine - INFO - Epoch(train) [14][ 240/1345] lr: 1.0000e-02 eta: 10:02:44 time: 0.1890 data_time: 0.0054 memory: 8327 grad_norm: 6.8896 loss: 4.2742 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6440 loss_aux: 1.6302 2023/02/17 13:07:49 - mmengine - INFO - Epoch(train) [14][ 260/1345] lr: 1.0000e-02 eta: 10:02:38 time: 0.1891 data_time: 0.0055 memory: 8327 grad_norm: 6.8640 loss: 4.0743 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4883 loss_aux: 1.5860 2023/02/17 13:07:53 - mmengine - INFO - Epoch(train) [14][ 280/1345] lr: 1.0000e-02 eta: 10:02:33 time: 0.1894 data_time: 0.0053 memory: 8327 grad_norm: 6.8507 loss: 3.9415 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3755 loss_aux: 1.5660 2023/02/17 13:07:57 - mmengine - INFO - Epoch(train) [14][ 300/1345] lr: 1.0000e-02 eta: 10:02:27 time: 0.1891 data_time: 0.0054 memory: 8327 grad_norm: 7.0159 loss: 4.3805 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7530 loss_aux: 1.6276 2023/02/17 13:08:00 - mmengine - INFO - Epoch(train) [14][ 320/1345] lr: 1.0000e-02 eta: 10:02:22 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 6.8486 loss: 3.9962 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4540 loss_aux: 1.5422 2023/02/17 13:08:04 - mmengine - INFO - Epoch(train) [14][ 340/1345] lr: 1.0000e-02 eta: 10:02:17 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 6.9827 loss: 4.3615 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6942 loss_aux: 1.6673 2023/02/17 13:08:08 - mmengine - INFO - Epoch(train) [14][ 360/1345] lr: 1.0000e-02 eta: 10:02:12 time: 0.1940 data_time: 0.0054 memory: 8327 grad_norm: 6.8791 loss: 4.3402 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6716 loss_aux: 1.6685 2023/02/17 13:08:12 - mmengine - INFO - Epoch(train) [14][ 380/1345] lr: 1.0000e-02 eta: 10:02:07 time: 0.1898 data_time: 0.0055 memory: 8327 grad_norm: 6.8179 loss: 4.4073 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7016 loss_aux: 1.7057 2023/02/17 13:08:16 - mmengine - INFO - Epoch(train) [14][ 400/1345] lr: 1.0000e-02 eta: 10:02:02 time: 0.1896 data_time: 0.0052 memory: 8327 grad_norm: 7.1417 loss: 4.0697 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4770 loss_aux: 1.5927 2023/02/17 13:08:20 - mmengine - INFO - Epoch(train) [14][ 420/1345] lr: 1.0000e-02 eta: 10:01:56 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 6.7966 loss: 4.2653 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6283 loss_aux: 1.6370 2023/02/17 13:08:23 - mmengine - INFO - Epoch(train) [14][ 440/1345] lr: 1.0000e-02 eta: 10:01:51 time: 0.1911 data_time: 0.0073 memory: 8327 grad_norm: 7.0120 loss: 4.4597 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7602 loss_aux: 1.6995 2023/02/17 13:08:27 - mmengine - INFO - Epoch(train) [14][ 460/1345] lr: 1.0000e-02 eta: 10:01:46 time: 0.1890 data_time: 0.0053 memory: 8327 grad_norm: 6.8429 loss: 4.3082 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6510 loss_aux: 1.6573 2023/02/17 13:08:31 - mmengine - INFO - Epoch(train) [14][ 480/1345] lr: 1.0000e-02 eta: 10:01:40 time: 0.1892 data_time: 0.0053 memory: 8327 grad_norm: 6.8447 loss: 4.2055 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5742 loss_aux: 1.6313 2023/02/17 13:08:35 - mmengine - INFO - Epoch(train) [14][ 500/1345] lr: 1.0000e-02 eta: 10:01:35 time: 0.1893 data_time: 0.0054 memory: 8327 grad_norm: 6.8575 loss: 4.1511 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5103 loss_aux: 1.6408 2023/02/17 13:08:38 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:08:38 - mmengine - INFO - Epoch(train) [14][ 520/1345] lr: 1.0000e-02 eta: 10:01:29 time: 0.1890 data_time: 0.0054 memory: 8327 grad_norm: 6.8212 loss: 4.2143 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5779 loss_aux: 1.6364 2023/02/17 13:08:42 - mmengine - INFO - Epoch(train) [14][ 540/1345] lr: 1.0000e-02 eta: 10:01:24 time: 0.1900 data_time: 0.0054 memory: 8327 grad_norm: 6.9318 loss: 4.1650 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6170 loss_aux: 1.5480 2023/02/17 13:08:46 - mmengine - INFO - Epoch(train) [14][ 560/1345] lr: 1.0000e-02 eta: 10:01:19 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 6.6682 loss: 3.8274 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3137 loss_aux: 1.5136 2023/02/17 13:08:50 - mmengine - INFO - Epoch(train) [14][ 580/1345] lr: 1.0000e-02 eta: 10:01:14 time: 0.1895 data_time: 0.0054 memory: 8327 grad_norm: 6.8458 loss: 4.1675 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5784 loss_aux: 1.5891 2023/02/17 13:08:54 - mmengine - INFO - Epoch(train) [14][ 600/1345] lr: 1.0000e-02 eta: 10:01:08 time: 0.1893 data_time: 0.0053 memory: 8327 grad_norm: 6.8245 loss: 4.4481 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7778 loss_aux: 1.6703 2023/02/17 13:08:57 - mmengine - INFO - Epoch(train) [14][ 620/1345] lr: 1.0000e-02 eta: 10:01:03 time: 0.1891 data_time: 0.0055 memory: 8327 grad_norm: 6.8417 loss: 3.5925 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2256 loss_aux: 1.3668 2023/02/17 13:09:01 - mmengine - INFO - Epoch(train) [14][ 640/1345] lr: 1.0000e-02 eta: 10:00:57 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 6.8217 loss: 3.7329 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2515 loss_aux: 1.4815 2023/02/17 13:09:05 - mmengine - INFO - Epoch(train) [14][ 660/1345] lr: 1.0000e-02 eta: 10:00:52 time: 0.1893 data_time: 0.0056 memory: 8327 grad_norm: 6.8019 loss: 4.3465 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.6952 loss_aux: 1.6513 2023/02/17 13:09:09 - mmengine - INFO - Epoch(train) [14][ 680/1345] lr: 1.0000e-02 eta: 10:00:47 time: 0.1898 data_time: 0.0054 memory: 8327 grad_norm: 6.8705 loss: 4.1265 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5214 loss_aux: 1.6051 2023/02/17 13:09:13 - mmengine - INFO - Epoch(train) [14][ 700/1345] lr: 1.0000e-02 eta: 10:00:41 time: 0.1895 data_time: 0.0054 memory: 8327 grad_norm: 6.8716 loss: 4.1094 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5512 loss_aux: 1.5581 2023/02/17 13:09:16 - mmengine - INFO - Epoch(train) [14][ 720/1345] lr: 1.0000e-02 eta: 10:00:36 time: 0.1914 data_time: 0.0071 memory: 8327 grad_norm: 6.9888 loss: 4.1196 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5740 loss_aux: 1.5456 2023/02/17 13:09:20 - mmengine - INFO - Epoch(train) [14][ 740/1345] lr: 1.0000e-02 eta: 10:00:31 time: 0.1903 data_time: 0.0054 memory: 8327 grad_norm: 6.8129 loss: 3.8483 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3455 loss_aux: 1.5028 2023/02/17 13:09:24 - mmengine - INFO - Epoch(train) [14][ 760/1345] lr: 1.0000e-02 eta: 10:00:26 time: 0.1893 data_time: 0.0054 memory: 8327 grad_norm: 6.7901 loss: 4.0487 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4811 loss_aux: 1.5676 2023/02/17 13:09:28 - mmengine - INFO - Epoch(train) [14][ 780/1345] lr: 1.0000e-02 eta: 10:00:21 time: 0.1897 data_time: 0.0054 memory: 8327 grad_norm: 7.0094 loss: 4.0281 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4801 loss_aux: 1.5480 2023/02/17 13:09:32 - mmengine - INFO - Epoch(train) [14][ 800/1345] lr: 1.0000e-02 eta: 10:00:15 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 6.9568 loss: 4.3526 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6867 loss_aux: 1.6659 2023/02/17 13:09:35 - mmengine - INFO - Epoch(train) [14][ 820/1345] lr: 1.0000e-02 eta: 10:00:10 time: 0.1903 data_time: 0.0058 memory: 8327 grad_norm: 6.8659 loss: 3.9616 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4170 loss_aux: 1.5446 2023/02/17 13:09:39 - mmengine - INFO - Epoch(train) [14][ 840/1345] lr: 1.0000e-02 eta: 10:00:05 time: 0.1901 data_time: 0.0054 memory: 8327 grad_norm: 6.6781 loss: 4.3558 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7212 loss_aux: 1.6346 2023/02/17 13:09:43 - mmengine - INFO - Epoch(train) [14][ 860/1345] lr: 1.0000e-02 eta: 10:00:00 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 6.6470 loss: 4.2692 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6479 loss_aux: 1.6212 2023/02/17 13:09:47 - mmengine - INFO - Epoch(train) [14][ 880/1345] lr: 1.0000e-02 eta: 9:59:54 time: 0.1892 data_time: 0.0055 memory: 8327 grad_norm: 6.8270 loss: 4.0950 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4931 loss_aux: 1.6018 2023/02/17 13:09:51 - mmengine - INFO - Epoch(train) [14][ 900/1345] lr: 1.0000e-02 eta: 9:59:49 time: 0.1900 data_time: 0.0055 memory: 8327 grad_norm: 6.9007 loss: 4.1494 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5949 loss_aux: 1.5546 2023/02/17 13:09:54 - mmengine - INFO - Epoch(train) [14][ 920/1345] lr: 1.0000e-02 eta: 9:59:44 time: 0.1901 data_time: 0.0056 memory: 8327 grad_norm: 6.9790 loss: 3.7856 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3575 loss_aux: 1.4281 2023/02/17 13:09:58 - mmengine - INFO - Epoch(train) [14][ 940/1345] lr: 1.0000e-02 eta: 9:59:39 time: 0.1891 data_time: 0.0054 memory: 8327 grad_norm: 6.7892 loss: 3.8178 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3502 loss_aux: 1.4677 2023/02/17 13:10:02 - mmengine - INFO - Epoch(train) [14][ 960/1345] lr: 1.0000e-02 eta: 9:59:34 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 6.7974 loss: 3.9093 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4277 loss_aux: 1.4817 2023/02/17 13:10:06 - mmengine - INFO - Epoch(train) [14][ 980/1345] lr: 1.0000e-02 eta: 9:59:29 time: 0.1912 data_time: 0.0067 memory: 8327 grad_norm: 6.7789 loss: 4.3741 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7730 loss_aux: 1.6010 2023/02/17 13:10:10 - mmengine - INFO - Epoch(train) [14][1000/1345] lr: 1.0000e-02 eta: 9:59:23 time: 0.1893 data_time: 0.0054 memory: 8327 grad_norm: 6.7542 loss: 4.2172 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6378 loss_aux: 1.5794 2023/02/17 13:10:13 - mmengine - INFO - Epoch(train) [14][1020/1345] lr: 1.0000e-02 eta: 9:59:18 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 6.7680 loss: 4.1466 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5342 loss_aux: 1.6124 2023/02/17 13:10:17 - mmengine - INFO - Epoch(train) [14][1040/1345] lr: 1.0000e-02 eta: 9:59:13 time: 0.1903 data_time: 0.0055 memory: 8327 grad_norm: 6.7412 loss: 4.1591 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5893 loss_aux: 1.5698 2023/02/17 13:10:21 - mmengine - INFO - Epoch(train) [14][1060/1345] lr: 1.0000e-02 eta: 9:59:08 time: 0.1897 data_time: 0.0054 memory: 8327 grad_norm: 6.8608 loss: 4.5049 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7763 loss_aux: 1.7286 2023/02/17 13:10:25 - mmengine - INFO - Epoch(train) [14][1080/1345] lr: 1.0000e-02 eta: 9:59:03 time: 0.1902 data_time: 0.0054 memory: 8327 grad_norm: 6.5668 loss: 3.5810 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1741 loss_aux: 1.4069 2023/02/17 13:10:29 - mmengine - INFO - Epoch(train) [14][1100/1345] lr: 1.0000e-02 eta: 9:58:57 time: 0.1899 data_time: 0.0054 memory: 8327 grad_norm: 6.7891 loss: 4.2187 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6525 loss_aux: 1.5662 2023/02/17 13:10:32 - mmengine - INFO - Epoch(train) [14][1120/1345] lr: 1.0000e-02 eta: 9:58:52 time: 0.1900 data_time: 0.0055 memory: 8327 grad_norm: 6.5811 loss: 3.6755 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2333 loss_aux: 1.4422 2023/02/17 13:10:36 - mmengine - INFO - Epoch(train) [14][1140/1345] lr: 1.0000e-02 eta: 9:58:47 time: 0.1910 data_time: 0.0067 memory: 8327 grad_norm: 6.7013 loss: 4.2970 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6950 loss_aux: 1.6020 2023/02/17 13:10:40 - mmengine - INFO - Epoch(train) [14][1160/1345] lr: 1.0000e-02 eta: 9:58:42 time: 0.1897 data_time: 0.0054 memory: 8327 grad_norm: 6.7706 loss: 4.0145 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4873 loss_aux: 1.5271 2023/02/17 13:10:44 - mmengine - INFO - Epoch(train) [14][1180/1345] lr: 1.0000e-02 eta: 9:58:37 time: 0.1889 data_time: 0.0054 memory: 8327 grad_norm: 6.7433 loss: 4.2341 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6146 loss_aux: 1.6195 2023/02/17 13:10:48 - mmengine - INFO - Epoch(train) [14][1200/1345] lr: 1.0000e-02 eta: 9:58:32 time: 0.1891 data_time: 0.0055 memory: 8327 grad_norm: 6.9050 loss: 3.9376 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4252 loss_aux: 1.5124 2023/02/17 13:10:51 - mmengine - INFO - Epoch(train) [14][1220/1345] lr: 1.0000e-02 eta: 9:58:26 time: 0.1894 data_time: 0.0054 memory: 8327 grad_norm: 6.9747 loss: 4.1954 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5683 loss_aux: 1.6271 2023/02/17 13:10:55 - mmengine - INFO - Epoch(train) [14][1240/1345] lr: 1.0000e-02 eta: 9:58:21 time: 0.1906 data_time: 0.0054 memory: 8327 grad_norm: 6.7458 loss: 4.0289 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4800 loss_aux: 1.5489 2023/02/17 13:10:59 - mmengine - INFO - Epoch(train) [14][1260/1345] lr: 1.0000e-02 eta: 9:58:16 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 6.8477 loss: 4.2938 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.7194 loss_aux: 1.5744 2023/02/17 13:11:03 - mmengine - INFO - Epoch(train) [14][1280/1345] lr: 1.0000e-02 eta: 9:58:11 time: 0.1902 data_time: 0.0055 memory: 8327 grad_norm: 6.9293 loss: 4.4884 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7911 loss_aux: 1.6974 2023/02/17 13:11:07 - mmengine - INFO - Epoch(train) [14][1300/1345] lr: 1.0000e-02 eta: 9:58:06 time: 0.1892 data_time: 0.0055 memory: 8327 grad_norm: 6.8037 loss: 3.9588 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4237 loss_aux: 1.5351 2023/02/17 13:11:10 - mmengine - INFO - Epoch(train) [14][1320/1345] lr: 1.0000e-02 eta: 9:58:00 time: 0.1886 data_time: 0.0052 memory: 8327 grad_norm: 6.7748 loss: 3.7342 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2268 loss_aux: 1.5074 2023/02/17 13:11:14 - mmengine - INFO - Epoch(train) [14][1340/1345] lr: 1.0000e-02 eta: 9:57:55 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.8766 loss: 4.2775 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6217 loss_aux: 1.6558 2023/02/17 13:11:15 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:11:15 - mmengine - INFO - Epoch(train) [14][1345/1345] lr: 1.0000e-02 eta: 9:57:52 time: 0.1824 data_time: 0.0054 memory: 8327 grad_norm: 6.7947 loss: 4.3631 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.6878 loss_aux: 1.6753 2023/02/17 13:11:15 - mmengine - INFO - Saving checkpoint at 14 epochs 2023/02/17 13:11:22 - mmengine - INFO - Epoch(train) [15][ 20/1345] lr: 1.0000e-02 eta: 9:57:51 time: 0.2105 data_time: 0.0204 memory: 8327 grad_norm: 7.1260 loss: 4.3579 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6749 loss_aux: 1.6830 2023/02/17 13:11:25 - mmengine - INFO - Epoch(train) [15][ 40/1345] lr: 1.0000e-02 eta: 9:57:46 time: 0.1899 data_time: 0.0040 memory: 8327 grad_norm: 6.7588 loss: 4.2260 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6066 loss_aux: 1.6194 2023/02/17 13:11:29 - mmengine - INFO - Epoch(train) [15][ 60/1345] lr: 1.0000e-02 eta: 9:57:41 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 6.9245 loss: 4.2875 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6629 loss_aux: 1.6245 2023/02/17 13:11:33 - mmengine - INFO - Epoch(train) [15][ 80/1345] lr: 1.0000e-02 eta: 9:57:36 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 6.9437 loss: 3.7205 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2376 loss_aux: 1.4829 2023/02/17 13:11:37 - mmengine - INFO - Epoch(train) [15][ 100/1345] lr: 1.0000e-02 eta: 9:57:31 time: 0.1893 data_time: 0.0054 memory: 8327 grad_norm: 6.9765 loss: 3.8140 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2902 loss_aux: 1.5238 2023/02/17 13:11:41 - mmengine - INFO - Epoch(train) [15][ 120/1345] lr: 1.0000e-02 eta: 9:57:25 time: 0.1896 data_time: 0.0056 memory: 8327 grad_norm: 6.8687 loss: 4.0497 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5381 loss_aux: 1.5116 2023/02/17 13:11:44 - mmengine - INFO - Epoch(train) [15][ 140/1345] lr: 1.0000e-02 eta: 9:57:20 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 6.9043 loss: 4.4252 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7513 loss_aux: 1.6739 2023/02/17 13:11:48 - mmengine - INFO - Epoch(train) [15][ 160/1345] lr: 1.0000e-02 eta: 9:57:15 time: 0.1902 data_time: 0.0057 memory: 8327 grad_norm: 6.7075 loss: 4.0540 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4632 loss_aux: 1.5907 2023/02/17 13:11:50 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:11:52 - mmengine - INFO - Epoch(train) [15][ 180/1345] lr: 1.0000e-02 eta: 9:57:10 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 6.9880 loss: 4.1942 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5726 loss_aux: 1.6216 2023/02/17 13:11:56 - mmengine - INFO - Epoch(train) [15][ 200/1345] lr: 1.0000e-02 eta: 9:57:05 time: 0.1902 data_time: 0.0068 memory: 8327 grad_norm: 6.6507 loss: 3.6640 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2258 loss_aux: 1.4382 2023/02/17 13:12:00 - mmengine - INFO - Epoch(train) [15][ 220/1345] lr: 1.0000e-02 eta: 9:57:00 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 6.8940 loss: 4.2069 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6212 loss_aux: 1.5858 2023/02/17 13:12:03 - mmengine - INFO - Epoch(train) [15][ 240/1345] lr: 1.0000e-02 eta: 9:56:54 time: 0.1890 data_time: 0.0053 memory: 8327 grad_norm: 7.0612 loss: 4.2180 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5729 loss_aux: 1.6451 2023/02/17 13:12:07 - mmengine - INFO - Epoch(train) [15][ 260/1345] lr: 1.0000e-02 eta: 9:56:49 time: 0.1894 data_time: 0.0054 memory: 8327 grad_norm: 6.8805 loss: 3.8911 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3484 loss_aux: 1.5427 2023/02/17 13:12:11 - mmengine - INFO - Epoch(train) [15][ 280/1345] lr: 1.0000e-02 eta: 9:56:44 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 6.8175 loss: 3.9119 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3703 loss_aux: 1.5416 2023/02/17 13:12:15 - mmengine - INFO - Epoch(train) [15][ 300/1345] lr: 1.0000e-02 eta: 9:56:39 time: 0.1888 data_time: 0.0055 memory: 8327 grad_norm: 6.7744 loss: 4.0058 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4535 loss_aux: 1.5522 2023/02/17 13:12:19 - mmengine - INFO - Epoch(train) [15][ 320/1345] lr: 1.0000e-02 eta: 9:56:34 time: 0.1928 data_time: 0.0054 memory: 8327 grad_norm: 6.8549 loss: 4.4508 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7307 loss_aux: 1.7201 2023/02/17 13:12:22 - mmengine - INFO - Epoch(train) [15][ 340/1345] lr: 1.0000e-02 eta: 9:56:29 time: 0.1916 data_time: 0.0053 memory: 8327 grad_norm: 6.8319 loss: 4.0289 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4578 loss_aux: 1.5711 2023/02/17 13:12:26 - mmengine - INFO - Epoch(train) [15][ 360/1345] lr: 1.0000e-02 eta: 9:56:24 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 7.0644 loss: 4.1776 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5606 loss_aux: 1.6170 2023/02/17 13:12:30 - mmengine - INFO - Epoch(train) [15][ 380/1345] lr: 1.0000e-02 eta: 9:56:19 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.0706 loss: 3.7705 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2740 loss_aux: 1.4965 2023/02/17 13:12:34 - mmengine - INFO - Epoch(train) [15][ 400/1345] lr: 1.0000e-02 eta: 9:56:14 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 6.8979 loss: 4.4930 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7909 loss_aux: 1.7021 2023/02/17 13:12:38 - mmengine - INFO - Epoch(train) [15][ 420/1345] lr: 1.0000e-02 eta: 9:56:09 time: 0.1902 data_time: 0.0053 memory: 8327 grad_norm: 6.9666 loss: 4.3960 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7230 loss_aux: 1.6730 2023/02/17 13:12:41 - mmengine - INFO - Epoch(train) [15][ 440/1345] lr: 1.0000e-02 eta: 9:56:04 time: 0.1897 data_time: 0.0054 memory: 8327 grad_norm: 6.9943 loss: 4.3731 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6555 loss_aux: 1.7177 2023/02/17 13:12:45 - mmengine - INFO - Epoch(train) [15][ 460/1345] lr: 1.0000e-02 eta: 9:55:59 time: 0.1900 data_time: 0.0054 memory: 8327 grad_norm: 6.8553 loss: 4.1061 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5398 loss_aux: 1.5663 2023/02/17 13:12:49 - mmengine - INFO - Epoch(train) [15][ 480/1345] lr: 1.0000e-02 eta: 9:55:54 time: 0.1896 data_time: 0.0054 memory: 8327 grad_norm: 6.7138 loss: 3.8443 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3629 loss_aux: 1.4814 2023/02/17 13:12:53 - mmengine - INFO - Epoch(train) [15][ 500/1345] lr: 1.0000e-02 eta: 9:55:48 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 6.9353 loss: 3.9935 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4482 loss_aux: 1.5454 2023/02/17 13:12:57 - mmengine - INFO - Epoch(train) [15][ 520/1345] lr: 1.0000e-02 eta: 9:55:43 time: 0.1899 data_time: 0.0054 memory: 8327 grad_norm: 6.9776 loss: 4.2175 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6350 loss_aux: 1.5824 2023/02/17 13:13:00 - mmengine - INFO - Epoch(train) [15][ 540/1345] lr: 1.0000e-02 eta: 9:55:38 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 6.8299 loss: 4.3660 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6989 loss_aux: 1.6671 2023/02/17 13:13:04 - mmengine - INFO - Epoch(train) [15][ 560/1345] lr: 1.0000e-02 eta: 9:55:33 time: 0.1892 data_time: 0.0055 memory: 8327 grad_norm: 6.8171 loss: 4.2794 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6484 loss_aux: 1.6309 2023/02/17 13:13:08 - mmengine - INFO - Epoch(train) [15][ 580/1345] lr: 1.0000e-02 eta: 9:55:28 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 6.6858 loss: 4.4185 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7376 loss_aux: 1.6809 2023/02/17 13:13:12 - mmengine - INFO - Epoch(train) [15][ 600/1345] lr: 1.0000e-02 eta: 9:55:23 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 6.8570 loss: 3.8902 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3742 loss_aux: 1.5160 2023/02/17 13:13:16 - mmengine - INFO - Epoch(train) [15][ 620/1345] lr: 1.0000e-02 eta: 9:55:18 time: 0.1903 data_time: 0.0055 memory: 8327 grad_norm: 6.9432 loss: 4.2759 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6535 loss_aux: 1.6224 2023/02/17 13:13:19 - mmengine - INFO - Epoch(train) [15][ 640/1345] lr: 1.0000e-02 eta: 9:55:13 time: 0.1908 data_time: 0.0054 memory: 8327 grad_norm: 6.9081 loss: 4.0004 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4287 loss_aux: 1.5717 2023/02/17 13:13:23 - mmengine - INFO - Epoch(train) [15][ 660/1345] lr: 1.0000e-02 eta: 9:55:08 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 6.8492 loss: 4.1271 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5184 loss_aux: 1.6087 2023/02/17 13:13:27 - mmengine - INFO - Epoch(train) [15][ 680/1345] lr: 1.0000e-02 eta: 9:55:03 time: 0.1891 data_time: 0.0055 memory: 8327 grad_norm: 6.9753 loss: 4.3561 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.7128 loss_aux: 1.6433 2023/02/17 13:13:31 - mmengine - INFO - Epoch(train) [15][ 700/1345] lr: 1.0000e-02 eta: 9:54:58 time: 0.1897 data_time: 0.0054 memory: 8327 grad_norm: 6.9269 loss: 3.9269 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3711 loss_aux: 1.5558 2023/02/17 13:13:35 - mmengine - INFO - Epoch(train) [15][ 720/1345] lr: 1.0000e-02 eta: 9:54:53 time: 0.1919 data_time: 0.0070 memory: 8327 grad_norm: 7.2359 loss: 4.3175 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6830 loss_aux: 1.6345 2023/02/17 13:13:38 - mmengine - INFO - Epoch(train) [15][ 740/1345] lr: 1.0000e-02 eta: 9:54:48 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 6.9637 loss: 3.9947 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4196 loss_aux: 1.5751 2023/02/17 13:13:42 - mmengine - INFO - Epoch(train) [15][ 760/1345] lr: 1.0000e-02 eta: 9:54:43 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 7.0406 loss: 3.8894 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3883 loss_aux: 1.5011 2023/02/17 13:13:46 - mmengine - INFO - Epoch(train) [15][ 780/1345] lr: 1.0000e-02 eta: 9:54:38 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 7.0254 loss: 3.6287 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1721 loss_aux: 1.4566 2023/02/17 13:13:50 - mmengine - INFO - Epoch(train) [15][ 800/1345] lr: 1.0000e-02 eta: 9:54:32 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.0733 loss: 4.2122 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6214 loss_aux: 1.5908 2023/02/17 13:13:53 - mmengine - INFO - Epoch(train) [15][ 820/1345] lr: 1.0000e-02 eta: 9:54:27 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 6.9629 loss: 4.2514 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6287 loss_aux: 1.6227 2023/02/17 13:13:57 - mmengine - INFO - Epoch(train) [15][ 840/1345] lr: 1.0000e-02 eta: 9:54:22 time: 0.1891 data_time: 0.0052 memory: 8327 grad_norm: 6.9529 loss: 4.0877 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5041 loss_aux: 1.5836 2023/02/17 13:14:01 - mmengine - INFO - Epoch(train) [15][ 860/1345] lr: 1.0000e-02 eta: 9:54:17 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 6.8639 loss: 4.5555 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8717 loss_aux: 1.6838 2023/02/17 13:14:05 - mmengine - INFO - Epoch(train) [15][ 880/1345] lr: 1.0000e-02 eta: 9:54:12 time: 0.1892 data_time: 0.0054 memory: 8327 grad_norm: 7.0238 loss: 4.1344 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4933 loss_aux: 1.6411 2023/02/17 13:14:09 - mmengine - INFO - Epoch(train) [15][ 900/1345] lr: 1.0000e-02 eta: 9:54:07 time: 0.1897 data_time: 0.0056 memory: 8327 grad_norm: 6.6514 loss: 4.3157 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7094 loss_aux: 1.6063 2023/02/17 13:14:12 - mmengine - INFO - Epoch(train) [15][ 920/1345] lr: 1.0000e-02 eta: 9:54:02 time: 0.1897 data_time: 0.0057 memory: 8327 grad_norm: 6.7669 loss: 3.8513 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3480 loss_aux: 1.5032 2023/02/17 13:14:16 - mmengine - INFO - Epoch(train) [15][ 940/1345] lr: 1.0000e-02 eta: 9:53:57 time: 0.1889 data_time: 0.0053 memory: 8327 grad_norm: 6.7985 loss: 4.0523 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5506 loss_aux: 1.5017 2023/02/17 13:14:20 - mmengine - INFO - Epoch(train) [15][ 960/1345] lr: 1.0000e-02 eta: 9:53:52 time: 0.1903 data_time: 0.0058 memory: 8327 grad_norm: 7.0744 loss: 4.4807 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.8148 loss_aux: 1.6659 2023/02/17 13:14:24 - mmengine - INFO - Epoch(train) [15][ 980/1345] lr: 1.0000e-02 eta: 9:53:46 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.8664 loss: 4.0514 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5033 loss_aux: 1.5481 2023/02/17 13:14:28 - mmengine - INFO - Epoch(train) [15][1000/1345] lr: 1.0000e-02 eta: 9:53:41 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 6.9959 loss: 4.0999 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5085 loss_aux: 1.5914 2023/02/17 13:14:31 - mmengine - INFO - Epoch(train) [15][1020/1345] lr: 1.0000e-02 eta: 9:53:37 time: 0.1913 data_time: 0.0071 memory: 8327 grad_norm: 7.0970 loss: 4.2641 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.6406 loss_aux: 1.6236 2023/02/17 13:14:35 - mmengine - INFO - Epoch(train) [15][1040/1345] lr: 1.0000e-02 eta: 9:53:32 time: 0.1893 data_time: 0.0054 memory: 8327 grad_norm: 6.7167 loss: 4.1684 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5690 loss_aux: 1.5994 2023/02/17 13:14:39 - mmengine - INFO - Epoch(train) [15][1060/1345] lr: 1.0000e-02 eta: 9:53:26 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 6.6680 loss: 4.1444 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5354 loss_aux: 1.6089 2023/02/17 13:14:43 - mmengine - INFO - Epoch(train) [15][1080/1345] lr: 1.0000e-02 eta: 9:53:21 time: 0.1897 data_time: 0.0055 memory: 8327 grad_norm: 6.8312 loss: 3.8852 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3421 loss_aux: 1.5431 2023/02/17 13:14:47 - mmengine - INFO - Epoch(train) [15][1100/1345] lr: 1.0000e-02 eta: 9:53:16 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 7.0163 loss: 3.9375 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4591 loss_aux: 1.4784 2023/02/17 13:14:50 - mmengine - INFO - Epoch(train) [15][1120/1345] lr: 1.0000e-02 eta: 9:53:12 time: 0.1909 data_time: 0.0070 memory: 8327 grad_norm: 6.8652 loss: 4.0782 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4699 loss_aux: 1.6084 2023/02/17 13:14:54 - mmengine - INFO - Epoch(train) [15][1140/1345] lr: 1.0000e-02 eta: 9:53:06 time: 0.1892 data_time: 0.0053 memory: 8327 grad_norm: 7.0426 loss: 4.1122 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5850 loss_aux: 1.5271 2023/02/17 13:14:58 - mmengine - INFO - Epoch(train) [15][1160/1345] lr: 1.0000e-02 eta: 9:53:01 time: 0.1899 data_time: 0.0054 memory: 8327 grad_norm: 7.1363 loss: 4.2224 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6269 loss_aux: 1.5955 2023/02/17 13:15:00 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:15:02 - mmengine - INFO - Epoch(train) [15][1180/1345] lr: 1.0000e-02 eta: 9:52:56 time: 0.1898 data_time: 0.0056 memory: 8327 grad_norm: 6.7922 loss: 3.7690 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2639 loss_aux: 1.5051 2023/02/17 13:15:06 - mmengine - INFO - Epoch(train) [15][1200/1345] lr: 1.0000e-02 eta: 9:52:51 time: 0.1896 data_time: 0.0053 memory: 8327 grad_norm: 6.7904 loss: 3.9502 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4298 loss_aux: 1.5204 2023/02/17 13:15:09 - mmengine - INFO - Epoch(train) [15][1220/1345] lr: 1.0000e-02 eta: 9:52:46 time: 0.1897 data_time: 0.0053 memory: 8327 grad_norm: 6.9549 loss: 4.1534 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5275 loss_aux: 1.6259 2023/02/17 13:15:13 - mmengine - INFO - Epoch(train) [15][1240/1345] lr: 1.0000e-02 eta: 9:52:41 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 6.9056 loss: 4.0414 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5044 loss_aux: 1.5370 2023/02/17 13:15:17 - mmengine - INFO - Epoch(train) [15][1260/1345] lr: 1.0000e-02 eta: 9:52:36 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 6.9413 loss: 4.1940 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6217 loss_aux: 1.5723 2023/02/17 13:15:21 - mmengine - INFO - Epoch(train) [15][1280/1345] lr: 1.0000e-02 eta: 9:52:31 time: 0.1906 data_time: 0.0070 memory: 8327 grad_norm: 7.1045 loss: 4.2672 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6770 loss_aux: 1.5902 2023/02/17 13:15:25 - mmengine - INFO - Epoch(train) [15][1300/1345] lr: 1.0000e-02 eta: 9:52:26 time: 0.1893 data_time: 0.0054 memory: 8327 grad_norm: 6.8359 loss: 4.3757 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7792 loss_aux: 1.5965 2023/02/17 13:15:28 - mmengine - INFO - Epoch(train) [15][1320/1345] lr: 1.0000e-02 eta: 9:52:21 time: 0.1898 data_time: 0.0055 memory: 8327 grad_norm: 6.7396 loss: 4.0210 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4451 loss_aux: 1.5758 2023/02/17 13:15:32 - mmengine - INFO - Epoch(train) [15][1340/1345] lr: 1.0000e-02 eta: 9:52:16 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 6.9323 loss: 4.3629 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7117 loss_aux: 1.6512 2023/02/17 13:15:33 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:15:33 - mmengine - INFO - Epoch(train) [15][1345/1345] lr: 1.0000e-02 eta: 9:52:14 time: 0.1826 data_time: 0.0055 memory: 8327 grad_norm: 6.8650 loss: 4.5934 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.8952 loss_aux: 1.6982 2023/02/17 13:15:33 - mmengine - INFO - Saving checkpoint at 15 epochs 2023/02/17 13:15:37 - mmengine - INFO - Epoch(val) [15][ 20/181] eta: 0:00:09 time: 0.0573 data_time: 0.0077 memory: 1994 2023/02/17 13:15:38 - mmengine - INFO - Epoch(val) [15][ 40/181] eta: 0:00:07 time: 0.0525 data_time: 0.0046 memory: 1994 2023/02/17 13:15:39 - mmengine - INFO - Epoch(val) [15][ 60/181] eta: 0:00:06 time: 0.0525 data_time: 0.0047 memory: 1994 2023/02/17 13:15:40 - mmengine - INFO - Epoch(val) [15][ 80/181] eta: 0:00:05 time: 0.0526 data_time: 0.0046 memory: 1994 2023/02/17 13:15:41 - mmengine - INFO - Epoch(val) [15][100/181] eta: 0:00:04 time: 0.0523 data_time: 0.0045 memory: 1994 2023/02/17 13:15:42 - mmengine - INFO - Epoch(val) [15][120/181] eta: 0:00:03 time: 0.0526 data_time: 0.0047 memory: 1994 2023/02/17 13:15:43 - mmengine - INFO - Epoch(val) [15][140/181] eta: 0:00:02 time: 0.0523 data_time: 0.0046 memory: 1994 2023/02/17 13:15:44 - mmengine - INFO - Epoch(val) [15][160/181] eta: 0:00:01 time: 0.0519 data_time: 0.0043 memory: 1994 2023/02/17 13:15:45 - mmengine - INFO - Epoch(val) [15][180/181] eta: 0:00:00 time: 0.0515 data_time: 0.0042 memory: 1994 2023/02/17 13:15:45 - mmengine - INFO - Epoch(val) [15][181/181] acc/top1: 0.3486 acc/top5: 0.6407 acc/mean1: 0.3114 2023/02/17 13:15:45 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/lilin/Repos/mmact_dev/mmaction2/work_dirs/fix_flip/tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb/best_acc/top1_epoch_10.pth is removed 2023/02/17 13:15:47 - mmengine - INFO - The best checkpoint with 0.3486 acc/top1 at 15 epoch is saved to best_acc/top1_epoch_15.pth. 2023/02/17 13:15:51 - mmengine - INFO - Epoch(train) [16][ 20/1345] lr: 1.0000e-02 eta: 9:52:11 time: 0.2029 data_time: 0.0144 memory: 8327 grad_norm: 6.7380 loss: 4.2572 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6597 loss_aux: 1.5975 2023/02/17 13:15:55 - mmengine - INFO - Epoch(train) [16][ 40/1345] lr: 1.0000e-02 eta: 9:52:07 time: 0.1907 data_time: 0.0046 memory: 8327 grad_norm: 6.7555 loss: 4.4726 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7576 loss_aux: 1.7150 2023/02/17 13:15:59 - mmengine - INFO - Epoch(train) [16][ 60/1345] lr: 1.0000e-02 eta: 9:52:02 time: 0.1897 data_time: 0.0056 memory: 8327 grad_norm: 6.7169 loss: 4.4005 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.7897 loss_aux: 1.6108 2023/02/17 13:16:02 - mmengine - INFO - Epoch(train) [16][ 80/1345] lr: 1.0000e-02 eta: 9:51:56 time: 0.1890 data_time: 0.0052 memory: 8327 grad_norm: 6.8673 loss: 3.9791 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4622 loss_aux: 1.5169 2023/02/17 13:16:06 - mmengine - INFO - Epoch(train) [16][ 100/1345] lr: 1.0000e-02 eta: 9:51:51 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 6.7204 loss: 4.0692 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4926 loss_aux: 1.5766 2023/02/17 13:16:10 - mmengine - INFO - Epoch(train) [16][ 120/1345] lr: 1.0000e-02 eta: 9:51:46 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 6.9287 loss: 3.7853 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.2856 loss_aux: 1.4997 2023/02/17 13:16:14 - mmengine - INFO - Epoch(train) [16][ 140/1345] lr: 1.0000e-02 eta: 9:51:41 time: 0.1888 data_time: 0.0052 memory: 8327 grad_norm: 6.9821 loss: 3.4394 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0829 loss_aux: 1.3565 2023/02/17 13:16:17 - mmengine - INFO - Epoch(train) [16][ 160/1345] lr: 1.0000e-02 eta: 9:51:36 time: 0.1888 data_time: 0.0053 memory: 8327 grad_norm: 6.9022 loss: 4.0911 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5023 loss_aux: 1.5887 2023/02/17 13:16:21 - mmengine - INFO - Epoch(train) [16][ 180/1345] lr: 1.0000e-02 eta: 9:51:31 time: 0.1892 data_time: 0.0055 memory: 8327 grad_norm: 6.8113 loss: 3.9622 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4188 loss_aux: 1.5434 2023/02/17 13:16:25 - mmengine - INFO - Epoch(train) [16][ 200/1345] lr: 1.0000e-02 eta: 9:51:26 time: 0.1893 data_time: 0.0053 memory: 8327 grad_norm: 6.7950 loss: 3.9199 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3906 loss_aux: 1.5292 2023/02/17 13:16:29 - mmengine - INFO - Epoch(train) [16][ 220/1345] lr: 1.0000e-02 eta: 9:51:21 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 6.9368 loss: 3.9217 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4101 loss_aux: 1.5116 2023/02/17 13:16:33 - mmengine - INFO - Epoch(train) [16][ 240/1345] lr: 1.0000e-02 eta: 9:51:16 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.8031 loss: 4.2473 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5790 loss_aux: 1.6684 2023/02/17 13:16:36 - mmengine - INFO - Epoch(train) [16][ 260/1345] lr: 1.0000e-02 eta: 9:51:11 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 6.9771 loss: 3.9013 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3649 loss_aux: 1.5364 2023/02/17 13:16:40 - mmengine - INFO - Epoch(train) [16][ 280/1345] lr: 1.0000e-02 eta: 9:51:06 time: 0.1895 data_time: 0.0056 memory: 8327 grad_norm: 6.9530 loss: 4.4257 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7087 loss_aux: 1.7170 2023/02/17 13:16:44 - mmengine - INFO - Epoch(train) [16][ 300/1345] lr: 1.0000e-02 eta: 9:51:01 time: 0.1886 data_time: 0.0054 memory: 8327 grad_norm: 6.9882 loss: 4.1543 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5616 loss_aux: 1.5927 2023/02/17 13:16:48 - mmengine - INFO - Epoch(train) [16][ 320/1345] lr: 1.0000e-02 eta: 9:50:55 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 6.8692 loss: 3.9417 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.4151 loss_aux: 1.5266 2023/02/17 13:16:52 - mmengine - INFO - Epoch(train) [16][ 340/1345] lr: 1.0000e-02 eta: 9:50:50 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 6.9040 loss: 3.9261 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4070 loss_aux: 1.5191 2023/02/17 13:16:55 - mmengine - INFO - Epoch(train) [16][ 360/1345] lr: 1.0000e-02 eta: 9:50:45 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 6.7470 loss: 4.0031 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4640 loss_aux: 1.5390 2023/02/17 13:16:59 - mmengine - INFO - Epoch(train) [16][ 380/1345] lr: 1.0000e-02 eta: 9:50:40 time: 0.1893 data_time: 0.0054 memory: 8327 grad_norm: 6.9175 loss: 4.1635 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5339 loss_aux: 1.6296 2023/02/17 13:17:03 - mmengine - INFO - Epoch(train) [16][ 400/1345] lr: 1.0000e-02 eta: 9:50:35 time: 0.1888 data_time: 0.0055 memory: 8327 grad_norm: 6.6785 loss: 3.9493 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4592 loss_aux: 1.4901 2023/02/17 13:17:07 - mmengine - INFO - Epoch(train) [16][ 420/1345] lr: 1.0000e-02 eta: 9:50:30 time: 0.1902 data_time: 0.0054 memory: 8327 grad_norm: 6.8375 loss: 4.1266 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5543 loss_aux: 1.5722 2023/02/17 13:17:11 - mmengine - INFO - Epoch(train) [16][ 440/1345] lr: 1.0000e-02 eta: 9:50:26 time: 0.1902 data_time: 0.0055 memory: 8327 grad_norm: 6.8659 loss: 4.1392 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5616 loss_aux: 1.5776 2023/02/17 13:17:14 - mmengine - INFO - Epoch(train) [16][ 460/1345] lr: 1.0000e-02 eta: 9:50:21 time: 0.1894 data_time: 0.0054 memory: 8327 grad_norm: 6.8773 loss: 4.1532 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5240 loss_aux: 1.6292 2023/02/17 13:17:18 - mmengine - INFO - Epoch(train) [16][ 480/1345] lr: 1.0000e-02 eta: 9:50:16 time: 0.1914 data_time: 0.0066 memory: 8327 grad_norm: 7.0868 loss: 4.2235 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5868 loss_aux: 1.6367 2023/02/17 13:17:22 - mmengine - INFO - Epoch(train) [16][ 500/1345] lr: 1.0000e-02 eta: 9:50:11 time: 0.1899 data_time: 0.0055 memory: 8327 grad_norm: 6.6797 loss: 4.0092 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4478 loss_aux: 1.5614 2023/02/17 13:17:26 - mmengine - INFO - Epoch(train) [16][ 520/1345] lr: 1.0000e-02 eta: 9:50:06 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 6.8132 loss: 4.0471 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4807 loss_aux: 1.5664 2023/02/17 13:17:30 - mmengine - INFO - Epoch(train) [16][ 540/1345] lr: 1.0000e-02 eta: 9:50:01 time: 0.1915 data_time: 0.0072 memory: 8327 grad_norm: 6.7675 loss: 4.3657 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6926 loss_aux: 1.6731 2023/02/17 13:17:33 - mmengine - INFO - Epoch(train) [16][ 560/1345] lr: 1.0000e-02 eta: 9:49:56 time: 0.1895 data_time: 0.0054 memory: 8327 grad_norm: 6.9170 loss: 4.0045 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4821 loss_aux: 1.5224 2023/02/17 13:17:37 - mmengine - INFO - Epoch(train) [16][ 580/1345] lr: 1.0000e-02 eta: 9:49:51 time: 0.1894 data_time: 0.0054 memory: 8327 grad_norm: 6.8850 loss: 3.8976 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3759 loss_aux: 1.5218 2023/02/17 13:17:41 - mmengine - INFO - Epoch(train) [16][ 600/1345] lr: 1.0000e-02 eta: 9:49:46 time: 0.1893 data_time: 0.0055 memory: 8327 grad_norm: 6.9199 loss: 3.9713 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4029 loss_aux: 1.5684 2023/02/17 13:17:45 - mmengine - INFO - Epoch(train) [16][ 620/1345] lr: 1.0000e-02 eta: 9:49:41 time: 0.1889 data_time: 0.0054 memory: 8327 grad_norm: 6.7841 loss: 4.0150 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4678 loss_aux: 1.5472 2023/02/17 13:17:48 - mmengine - INFO - Epoch(train) [16][ 640/1345] lr: 1.0000e-02 eta: 9:49:36 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 6.8718 loss: 4.1699 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5310 loss_aux: 1.6390 2023/02/17 13:17:52 - mmengine - INFO - Epoch(train) [16][ 660/1345] lr: 1.0000e-02 eta: 9:49:31 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 6.8822 loss: 4.0225 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4997 loss_aux: 1.5228 2023/02/17 13:17:56 - mmengine - INFO - Epoch(train) [16][ 680/1345] lr: 1.0000e-02 eta: 9:49:26 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 6.9966 loss: 4.1737 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5639 loss_aux: 1.6098 2023/02/17 13:18:00 - mmengine - INFO - Epoch(train) [16][ 700/1345] lr: 1.0000e-02 eta: 9:49:21 time: 0.1892 data_time: 0.0055 memory: 8327 grad_norm: 7.0214 loss: 3.8578 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4043 loss_aux: 1.4535 2023/02/17 13:18:04 - mmengine - INFO - Epoch(train) [16][ 720/1345] lr: 1.0000e-02 eta: 9:49:17 time: 0.1902 data_time: 0.0065 memory: 8327 grad_norm: 6.8441 loss: 4.1719 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5810 loss_aux: 1.5909 2023/02/17 13:18:07 - mmengine - INFO - Epoch(train) [16][ 740/1345] lr: 1.0000e-02 eta: 9:49:12 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.0461 loss: 3.8772 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3526 loss_aux: 1.5246 2023/02/17 13:18:11 - mmengine - INFO - Epoch(train) [16][ 760/1345] lr: 1.0000e-02 eta: 9:49:07 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 6.9183 loss: 4.3891 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7168 loss_aux: 1.6723 2023/02/17 13:18:15 - mmengine - INFO - Epoch(train) [16][ 780/1345] lr: 1.0000e-02 eta: 9:49:02 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.7829 loss: 3.7740 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2853 loss_aux: 1.4886 2023/02/17 13:18:19 - mmengine - INFO - Epoch(train) [16][ 800/1345] lr: 1.0000e-02 eta: 9:48:57 time: 0.1895 data_time: 0.0056 memory: 8327 grad_norm: 6.9830 loss: 4.3121 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7214 loss_aux: 1.5906 2023/02/17 13:18:23 - mmengine - INFO - Epoch(train) [16][ 820/1345] lr: 1.0000e-02 eta: 9:48:52 time: 0.1892 data_time: 0.0055 memory: 8327 grad_norm: 7.0000 loss: 4.4152 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7605 loss_aux: 1.6547 2023/02/17 13:18:24 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:18:26 - mmengine - INFO - Epoch(train) [16][ 840/1345] lr: 1.0000e-02 eta: 9:48:47 time: 0.1903 data_time: 0.0070 memory: 8327 grad_norm: 6.7346 loss: 3.8230 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3045 loss_aux: 1.5185 2023/02/17 13:18:30 - mmengine - INFO - Epoch(train) [16][ 860/1345] lr: 1.0000e-02 eta: 9:48:42 time: 0.1890 data_time: 0.0062 memory: 8327 grad_norm: 6.9441 loss: 3.9393 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4063 loss_aux: 1.5330 2023/02/17 13:18:34 - mmengine - INFO - Epoch(train) [16][ 880/1345] lr: 1.0000e-02 eta: 9:48:37 time: 0.1885 data_time: 0.0055 memory: 8327 grad_norm: 6.8204 loss: 4.2232 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6404 loss_aux: 1.5828 2023/02/17 13:18:38 - mmengine - INFO - Epoch(train) [16][ 900/1345] lr: 1.0000e-02 eta: 9:48:32 time: 0.1897 data_time: 0.0056 memory: 8327 grad_norm: 6.9193 loss: 4.1148 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5594 loss_aux: 1.5554 2023/02/17 13:18:42 - mmengine - INFO - Epoch(train) [16][ 920/1345] lr: 1.0000e-02 eta: 9:48:27 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.0818 loss: 4.2149 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6078 loss_aux: 1.6071 2023/02/17 13:18:45 - mmengine - INFO - Epoch(train) [16][ 940/1345] lr: 1.0000e-02 eta: 9:48:22 time: 0.1910 data_time: 0.0056 memory: 8327 grad_norm: 6.8408 loss: 4.1236 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5412 loss_aux: 1.5824 2023/02/17 13:18:49 - mmengine - INFO - Epoch(train) [16][ 960/1345] lr: 1.0000e-02 eta: 9:48:17 time: 0.1898 data_time: 0.0055 memory: 8327 grad_norm: 6.8820 loss: 3.8303 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3257 loss_aux: 1.5046 2023/02/17 13:18:53 - mmengine - INFO - Epoch(train) [16][ 980/1345] lr: 1.0000e-02 eta: 9:48:12 time: 0.1892 data_time: 0.0054 memory: 8327 grad_norm: 6.8526 loss: 3.7232 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.2653 loss_aux: 1.4580 2023/02/17 13:18:57 - mmengine - INFO - Epoch(train) [16][1000/1345] lr: 1.0000e-02 eta: 9:48:07 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 6.8124 loss: 3.9576 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3911 loss_aux: 1.5665 2023/02/17 13:19:00 - mmengine - INFO - Epoch(train) [16][1020/1345] lr: 1.0000e-02 eta: 9:48:02 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 6.8448 loss: 4.2928 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6930 loss_aux: 1.5998 2023/02/17 13:19:04 - mmengine - INFO - Epoch(train) [16][1040/1345] lr: 1.0000e-02 eta: 9:47:57 time: 0.1897 data_time: 0.0057 memory: 8327 grad_norm: 7.1414 loss: 4.0017 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5179 loss_aux: 1.4838 2023/02/17 13:19:08 - mmengine - INFO - Epoch(train) [16][1060/1345] lr: 1.0000e-02 eta: 9:47:53 time: 0.1906 data_time: 0.0064 memory: 8327 grad_norm: 6.8957 loss: 4.3743 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7135 loss_aux: 1.6607 2023/02/17 13:19:12 - mmengine - INFO - Epoch(train) [16][1080/1345] lr: 1.0000e-02 eta: 9:47:48 time: 0.1906 data_time: 0.0062 memory: 8327 grad_norm: 7.0886 loss: 3.9025 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4653 loss_aux: 1.4372 2023/02/17 13:19:16 - mmengine - INFO - Epoch(train) [16][1100/1345] lr: 1.0000e-02 eta: 9:47:43 time: 0.1893 data_time: 0.0056 memory: 8327 grad_norm: 6.7228 loss: 3.8741 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3854 loss_aux: 1.4888 2023/02/17 13:19:20 - mmengine - INFO - Epoch(train) [16][1120/1345] lr: 1.0000e-02 eta: 9:47:38 time: 0.1910 data_time: 0.0074 memory: 8327 grad_norm: 6.9772 loss: 3.8258 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.2942 loss_aux: 1.5315 2023/02/17 13:19:23 - mmengine - INFO - Epoch(train) [16][1140/1345] lr: 1.0000e-02 eta: 9:47:33 time: 0.1888 data_time: 0.0054 memory: 8327 grad_norm: 6.6457 loss: 3.8605 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3266 loss_aux: 1.5339 2023/02/17 13:19:27 - mmengine - INFO - Epoch(train) [16][1160/1345] lr: 1.0000e-02 eta: 9:47:28 time: 0.1890 data_time: 0.0054 memory: 8327 grad_norm: 7.1221 loss: 4.1084 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5114 loss_aux: 1.5969 2023/02/17 13:19:31 - mmengine - INFO - Epoch(train) [16][1180/1345] lr: 1.0000e-02 eta: 9:47:24 time: 0.1924 data_time: 0.0054 memory: 8327 grad_norm: 7.1469 loss: 4.3215 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6553 loss_aux: 1.6662 2023/02/17 13:19:35 - mmengine - INFO - Epoch(train) [16][1200/1345] lr: 1.0000e-02 eta: 9:47:19 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 6.8277 loss: 3.9875 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4918 loss_aux: 1.4957 2023/02/17 13:19:38 - mmengine - INFO - Epoch(train) [16][1220/1345] lr: 1.0000e-02 eta: 9:47:14 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.8880 loss: 4.0436 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5065 loss_aux: 1.5370 2023/02/17 13:19:42 - mmengine - INFO - Epoch(train) [16][1240/1345] lr: 1.0000e-02 eta: 9:47:10 time: 0.1926 data_time: 0.0054 memory: 8327 grad_norm: 6.9735 loss: 3.9628 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4392 loss_aux: 1.5237 2023/02/17 13:19:46 - mmengine - INFO - Epoch(train) [16][1260/1345] lr: 1.0000e-02 eta: 9:47:05 time: 0.1893 data_time: 0.0055 memory: 8327 grad_norm: 6.8195 loss: 4.1257 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5385 loss_aux: 1.5872 2023/02/17 13:19:50 - mmengine - INFO - Epoch(train) [16][1280/1345] lr: 1.0000e-02 eta: 9:47:00 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 6.8667 loss: 4.0332 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4603 loss_aux: 1.5729 2023/02/17 13:19:54 - mmengine - INFO - Epoch(train) [16][1300/1345] lr: 1.0000e-02 eta: 9:46:55 time: 0.1898 data_time: 0.0054 memory: 8327 grad_norm: 6.8899 loss: 4.0400 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4903 loss_aux: 1.5497 2023/02/17 13:19:58 - mmengine - INFO - Epoch(train) [16][1320/1345] lr: 1.0000e-02 eta: 9:46:50 time: 0.1900 data_time: 0.0055 memory: 8327 grad_norm: 6.9191 loss: 4.0350 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4574 loss_aux: 1.5776 2023/02/17 13:20:01 - mmengine - INFO - Epoch(train) [16][1340/1345] lr: 1.0000e-02 eta: 9:46:45 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.0931 loss: 3.8048 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2981 loss_aux: 1.5067 2023/02/17 13:20:02 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:20:02 - mmengine - INFO - Epoch(train) [16][1345/1345] lr: 1.0000e-02 eta: 9:46:43 time: 0.1823 data_time: 0.0056 memory: 8327 grad_norm: 7.0609 loss: 4.1131 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.4966 loss_aux: 1.6164 2023/02/17 13:20:02 - mmengine - INFO - Saving checkpoint at 16 epochs 2023/02/17 13:20:09 - mmengine - INFO - Epoch(train) [17][ 20/1345] lr: 1.0000e-02 eta: 9:46:41 time: 0.2082 data_time: 0.0163 memory: 8327 grad_norm: 6.8588 loss: 3.9955 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4102 loss_aux: 1.5854 2023/02/17 13:20:13 - mmengine - INFO - Epoch(train) [17][ 40/1345] lr: 1.0000e-02 eta: 9:46:36 time: 0.1908 data_time: 0.0056 memory: 8327 grad_norm: 6.7770 loss: 4.1106 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5180 loss_aux: 1.5925 2023/02/17 13:20:16 - mmengine - INFO - Epoch(train) [17][ 60/1345] lr: 1.0000e-02 eta: 9:46:32 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 6.8619 loss: 3.9659 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4153 loss_aux: 1.5506 2023/02/17 13:20:20 - mmengine - INFO - Epoch(train) [17][ 80/1345] lr: 1.0000e-02 eta: 9:46:27 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 6.8918 loss: 3.9764 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4460 loss_aux: 1.5304 2023/02/17 13:20:24 - mmengine - INFO - Epoch(train) [17][ 100/1345] lr: 1.0000e-02 eta: 9:46:22 time: 0.1898 data_time: 0.0062 memory: 8327 grad_norm: 6.8674 loss: 4.0853 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5177 loss_aux: 1.5676 2023/02/17 13:20:28 - mmengine - INFO - Epoch(train) [17][ 120/1345] lr: 1.0000e-02 eta: 9:46:17 time: 0.1899 data_time: 0.0057 memory: 8327 grad_norm: 6.9731 loss: 4.1657 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5705 loss_aux: 1.5952 2023/02/17 13:20:32 - mmengine - INFO - Epoch(train) [17][ 140/1345] lr: 1.0000e-02 eta: 9:46:12 time: 0.1893 data_time: 0.0055 memory: 8327 grad_norm: 6.9872 loss: 4.0189 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5079 loss_aux: 1.5110 2023/02/17 13:20:35 - mmengine - INFO - Epoch(train) [17][ 160/1345] lr: 1.0000e-02 eta: 9:46:07 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 6.9151 loss: 4.0963 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5483 loss_aux: 1.5481 2023/02/17 13:20:39 - mmengine - INFO - Epoch(train) [17][ 180/1345] lr: 1.0000e-02 eta: 9:46:02 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 6.8616 loss: 4.1458 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5562 loss_aux: 1.5896 2023/02/17 13:20:43 - mmengine - INFO - Epoch(train) [17][ 200/1345] lr: 1.0000e-02 eta: 9:45:57 time: 0.1890 data_time: 0.0053 memory: 8327 grad_norm: 6.8452 loss: 3.6811 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.2504 loss_aux: 1.4307 2023/02/17 13:20:47 - mmengine - INFO - Epoch(train) [17][ 220/1345] lr: 1.0000e-02 eta: 9:45:52 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 7.1662 loss: 3.7075 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.2789 loss_aux: 1.4286 2023/02/17 13:20:50 - mmengine - INFO - Epoch(train) [17][ 240/1345] lr: 1.0000e-02 eta: 9:45:47 time: 0.1892 data_time: 0.0054 memory: 8327 grad_norm: 6.8501 loss: 3.8692 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3497 loss_aux: 1.5195 2023/02/17 13:20:54 - mmengine - INFO - Epoch(train) [17][ 260/1345] lr: 1.0000e-02 eta: 9:45:43 time: 0.1892 data_time: 0.0055 memory: 8327 grad_norm: 6.9056 loss: 3.9297 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4071 loss_aux: 1.5226 2023/02/17 13:20:58 - mmengine - INFO - Epoch(train) [17][ 280/1345] lr: 1.0000e-02 eta: 9:45:38 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 6.8369 loss: 4.0949 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4992 loss_aux: 1.5957 2023/02/17 13:21:02 - mmengine - INFO - Epoch(train) [17][ 300/1345] lr: 1.0000e-02 eta: 9:45:33 time: 0.1894 data_time: 0.0054 memory: 8327 grad_norm: 7.0206 loss: 4.2422 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6532 loss_aux: 1.5890 2023/02/17 13:21:06 - mmengine - INFO - Epoch(train) [17][ 320/1345] lr: 1.0000e-02 eta: 9:45:28 time: 0.1900 data_time: 0.0055 memory: 8327 grad_norm: 6.9039 loss: 3.8468 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3604 loss_aux: 1.4864 2023/02/17 13:21:09 - mmengine - INFO - Epoch(train) [17][ 340/1345] lr: 1.0000e-02 eta: 9:45:23 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.0492 loss: 3.7933 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2798 loss_aux: 1.5134 2023/02/17 13:21:13 - mmengine - INFO - Epoch(train) [17][ 360/1345] lr: 1.0000e-02 eta: 9:45:18 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.0154 loss: 4.1449 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5544 loss_aux: 1.5905 2023/02/17 13:21:17 - mmengine - INFO - Epoch(train) [17][ 380/1345] lr: 1.0000e-02 eta: 9:45:13 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 6.8368 loss: 3.9509 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4239 loss_aux: 1.5269 2023/02/17 13:21:21 - mmengine - INFO - Epoch(train) [17][ 400/1345] lr: 1.0000e-02 eta: 9:45:08 time: 0.1902 data_time: 0.0071 memory: 8327 grad_norm: 6.8008 loss: 3.6588 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2019 loss_aux: 1.4569 2023/02/17 13:21:25 - mmengine - INFO - Epoch(train) [17][ 420/1345] lr: 1.0000e-02 eta: 9:45:04 time: 0.1900 data_time: 0.0060 memory: 8327 grad_norm: 6.8670 loss: 4.0710 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4676 loss_aux: 1.6034 2023/02/17 13:21:28 - mmengine - INFO - Epoch(train) [17][ 440/1345] lr: 1.0000e-02 eta: 9:44:59 time: 0.1900 data_time: 0.0067 memory: 8327 grad_norm: 6.8800 loss: 3.8894 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3571 loss_aux: 1.5324 2023/02/17 13:21:32 - mmengine - INFO - Epoch(train) [17][ 460/1345] lr: 1.0000e-02 eta: 9:44:54 time: 0.1884 data_time: 0.0055 memory: 8327 grad_norm: 6.9510 loss: 3.9548 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4092 loss_aux: 1.5456 2023/02/17 13:21:36 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:21:36 - mmengine - INFO - Epoch(train) [17][ 480/1345] lr: 1.0000e-02 eta: 9:44:49 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 6.9793 loss: 4.0621 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5097 loss_aux: 1.5524 2023/02/17 13:21:40 - mmengine - INFO - Epoch(train) [17][ 500/1345] lr: 1.0000e-02 eta: 9:44:44 time: 0.1893 data_time: 0.0056 memory: 8327 grad_norm: 6.9117 loss: 4.2959 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7233 loss_aux: 1.5726 2023/02/17 13:21:43 - mmengine - INFO - Epoch(train) [17][ 520/1345] lr: 1.0000e-02 eta: 9:44:39 time: 0.1892 data_time: 0.0054 memory: 8327 grad_norm: 6.8550 loss: 4.0240 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4461 loss_aux: 1.5779 2023/02/17 13:21:47 - mmengine - INFO - Epoch(train) [17][ 540/1345] lr: 1.0000e-02 eta: 9:44:34 time: 0.1884 data_time: 0.0056 memory: 8327 grad_norm: 6.7920 loss: 3.9477 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4384 loss_aux: 1.5094 2023/02/17 13:21:51 - mmengine - INFO - Epoch(train) [17][ 560/1345] lr: 1.0000e-02 eta: 9:44:29 time: 0.1889 data_time: 0.0051 memory: 8327 grad_norm: 7.1573 loss: 4.2808 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6573 loss_aux: 1.6234 2023/02/17 13:21:55 - mmengine - INFO - Epoch(train) [17][ 580/1345] lr: 1.0000e-02 eta: 9:44:24 time: 0.1900 data_time: 0.0055 memory: 8327 grad_norm: 6.9462 loss: 4.3182 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6780 loss_aux: 1.6402 2023/02/17 13:21:59 - mmengine - INFO - Epoch(train) [17][ 600/1345] lr: 1.0000e-02 eta: 9:44:20 time: 0.1897 data_time: 0.0054 memory: 8327 grad_norm: 6.8619 loss: 4.3852 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7318 loss_aux: 1.6533 2023/02/17 13:22:02 - mmengine - INFO - Epoch(train) [17][ 620/1345] lr: 1.0000e-02 eta: 9:44:15 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 6.7924 loss: 4.0813 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5722 loss_aux: 1.5091 2023/02/17 13:22:06 - mmengine - INFO - Epoch(train) [17][ 640/1345] lr: 1.0000e-02 eta: 9:44:10 time: 0.1892 data_time: 0.0053 memory: 8327 grad_norm: 6.8236 loss: 4.1762 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6402 loss_aux: 1.5360 2023/02/17 13:22:10 - mmengine - INFO - Epoch(train) [17][ 660/1345] lr: 1.0000e-02 eta: 9:44:05 time: 0.1896 data_time: 0.0056 memory: 8327 grad_norm: 6.9722 loss: 4.4570 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8188 loss_aux: 1.6382 2023/02/17 13:22:14 - mmengine - INFO - Epoch(train) [17][ 680/1345] lr: 1.0000e-02 eta: 9:44:00 time: 0.1892 data_time: 0.0055 memory: 8327 grad_norm: 6.7850 loss: 4.0897 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5237 loss_aux: 1.5659 2023/02/17 13:22:18 - mmengine - INFO - Epoch(train) [17][ 700/1345] lr: 1.0000e-02 eta: 9:43:55 time: 0.1904 data_time: 0.0057 memory: 8327 grad_norm: 7.0007 loss: 4.2571 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7142 loss_aux: 1.5429 2023/02/17 13:22:21 - mmengine - INFO - Epoch(train) [17][ 720/1345] lr: 1.0000e-02 eta: 9:43:51 time: 0.1924 data_time: 0.0069 memory: 8327 grad_norm: 6.8131 loss: 3.9853 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4611 loss_aux: 1.5242 2023/02/17 13:22:31 - mmengine - INFO - Epoch(train) [17][ 740/1345] lr: 1.0000e-02 eta: 9:44:35 time: 0.4906 data_time: 0.0056 memory: 8327 grad_norm: 6.6196 loss: 3.9606 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3978 loss_aux: 1.5629 2023/02/17 13:22:35 - mmengine - INFO - Epoch(train) [17][ 760/1345] lr: 1.0000e-02 eta: 9:44:30 time: 0.1895 data_time: 0.0052 memory: 8327 grad_norm: 6.9582 loss: 3.9651 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4174 loss_aux: 1.5476 2023/02/17 13:22:39 - mmengine - INFO - Epoch(train) [17][ 780/1345] lr: 1.0000e-02 eta: 9:44:25 time: 0.1898 data_time: 0.0054 memory: 8327 grad_norm: 7.0299 loss: 4.0945 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5379 loss_aux: 1.5567 2023/02/17 13:22:43 - mmengine - INFO - Epoch(train) [17][ 800/1345] lr: 1.0000e-02 eta: 9:44:20 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 6.8249 loss: 3.9807 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4412 loss_aux: 1.5395 2023/02/17 13:22:46 - mmengine - INFO - Epoch(train) [17][ 820/1345] lr: 1.0000e-02 eta: 9:44:15 time: 0.1893 data_time: 0.0054 memory: 8327 grad_norm: 6.8300 loss: 4.1060 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5295 loss_aux: 1.5765 2023/02/17 13:22:50 - mmengine - INFO - Epoch(train) [17][ 840/1345] lr: 1.0000e-02 eta: 9:44:11 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 6.8262 loss: 3.8385 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2926 loss_aux: 1.5459 2023/02/17 13:22:54 - mmengine - INFO - Epoch(train) [17][ 860/1345] lr: 1.0000e-02 eta: 9:44:06 time: 0.1901 data_time: 0.0054 memory: 8327 grad_norm: 6.7620 loss: 3.6096 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.2046 loss_aux: 1.4050 2023/02/17 13:22:58 - mmengine - INFO - Epoch(train) [17][ 880/1345] lr: 1.0000e-02 eta: 9:44:01 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 6.8549 loss: 3.9589 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3995 loss_aux: 1.5594 2023/02/17 13:23:02 - mmengine - INFO - Epoch(train) [17][ 900/1345] lr: 1.0000e-02 eta: 9:43:56 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 6.9472 loss: 3.8181 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2902 loss_aux: 1.5279 2023/02/17 13:23:05 - mmengine - INFO - Epoch(train) [17][ 920/1345] lr: 1.0000e-02 eta: 9:43:51 time: 0.1891 data_time: 0.0054 memory: 8327 grad_norm: 6.9194 loss: 4.1050 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5127 loss_aux: 1.5923 2023/02/17 13:23:09 - mmengine - INFO - Epoch(train) [17][ 940/1345] lr: 1.0000e-02 eta: 9:43:46 time: 0.1891 data_time: 0.0055 memory: 8327 grad_norm: 7.0120 loss: 4.0631 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4610 loss_aux: 1.6021 2023/02/17 13:23:13 - mmengine - INFO - Epoch(train) [17][ 960/1345] lr: 1.0000e-02 eta: 9:43:41 time: 0.1893 data_time: 0.0055 memory: 8327 grad_norm: 7.3912 loss: 4.1046 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5523 loss_aux: 1.5523 2023/02/17 13:23:17 - mmengine - INFO - Epoch(train) [17][ 980/1345] lr: 1.0000e-02 eta: 9:43:36 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 6.9154 loss: 3.9480 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4349 loss_aux: 1.5131 2023/02/17 13:23:20 - mmengine - INFO - Epoch(train) [17][1000/1345] lr: 1.0000e-02 eta: 9:43:31 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 6.9438 loss: 4.0891 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5210 loss_aux: 1.5681 2023/02/17 13:23:24 - mmengine - INFO - Epoch(train) [17][1020/1345] lr: 1.0000e-02 eta: 9:43:27 time: 0.1889 data_time: 0.0054 memory: 8327 grad_norm: 6.6665 loss: 4.0865 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5158 loss_aux: 1.5707 2023/02/17 13:23:28 - mmengine - INFO - Epoch(train) [17][1040/1345] lr: 1.0000e-02 eta: 9:43:22 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 6.9398 loss: 4.2059 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6117 loss_aux: 1.5942 2023/02/17 13:23:32 - mmengine - INFO - Epoch(train) [17][1060/1345] lr: 1.0000e-02 eta: 9:43:17 time: 0.1891 data_time: 0.0054 memory: 8327 grad_norm: 7.1010 loss: 4.0345 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4726 loss_aux: 1.5619 2023/02/17 13:23:36 - mmengine - INFO - Epoch(train) [17][1080/1345] lr: 1.0000e-02 eta: 9:43:12 time: 0.1895 data_time: 0.0056 memory: 8327 grad_norm: 6.9362 loss: 3.8310 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2999 loss_aux: 1.5311 2023/02/17 13:23:39 - mmengine - INFO - Epoch(train) [17][1100/1345] lr: 1.0000e-02 eta: 9:43:07 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 6.8743 loss: 4.0776 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4933 loss_aux: 1.5842 2023/02/17 13:23:43 - mmengine - INFO - Epoch(train) [17][1120/1345] lr: 1.0000e-02 eta: 9:43:02 time: 0.1893 data_time: 0.0056 memory: 8327 grad_norm: 7.0637 loss: 4.0802 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5135 loss_aux: 1.5666 2023/02/17 13:23:47 - mmengine - INFO - Epoch(train) [17][1140/1345] lr: 1.0000e-02 eta: 9:42:57 time: 0.1893 data_time: 0.0055 memory: 8327 grad_norm: 7.0127 loss: 3.7901 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3170 loss_aux: 1.4731 2023/02/17 13:23:51 - mmengine - INFO - Epoch(train) [17][1160/1345] lr: 1.0000e-02 eta: 9:42:52 time: 0.1893 data_time: 0.0054 memory: 8327 grad_norm: 6.9715 loss: 3.9862 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4109 loss_aux: 1.5753 2023/02/17 13:23:55 - mmengine - INFO - Epoch(train) [17][1180/1345] lr: 1.0000e-02 eta: 9:42:48 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.0244 loss: 3.6835 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2149 loss_aux: 1.4686 2023/02/17 13:23:58 - mmengine - INFO - Epoch(train) [17][1200/1345] lr: 1.0000e-02 eta: 9:42:43 time: 0.1906 data_time: 0.0073 memory: 8327 grad_norm: 6.8175 loss: 4.1082 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4780 loss_aux: 1.6303 2023/02/17 13:24:02 - mmengine - INFO - Epoch(train) [17][1220/1345] lr: 1.0000e-02 eta: 9:42:38 time: 0.1892 data_time: 0.0054 memory: 8327 grad_norm: 7.0594 loss: 3.6693 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2664 loss_aux: 1.4029 2023/02/17 13:24:06 - mmengine - INFO - Epoch(train) [17][1240/1345] lr: 1.0000e-02 eta: 9:42:33 time: 0.1893 data_time: 0.0054 memory: 8327 grad_norm: 7.1941 loss: 3.4438 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1178 loss_aux: 1.3260 2023/02/17 13:24:10 - mmengine - INFO - Epoch(train) [17][1260/1345] lr: 1.0000e-02 eta: 9:42:29 time: 0.1904 data_time: 0.0058 memory: 8327 grad_norm: 6.9931 loss: 4.0183 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5030 loss_aux: 1.5154 2023/02/17 13:24:14 - mmengine - INFO - Epoch(train) [17][1280/1345] lr: 1.0000e-02 eta: 9:42:24 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 6.8765 loss: 4.2351 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5626 loss_aux: 1.6725 2023/02/17 13:24:17 - mmengine - INFO - Epoch(train) [17][1300/1345] lr: 1.0000e-02 eta: 9:42:19 time: 0.1897 data_time: 0.0057 memory: 8327 grad_norm: 6.9081 loss: 3.6201 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2291 loss_aux: 1.3910 2023/02/17 13:24:21 - mmengine - INFO - Epoch(train) [17][1320/1345] lr: 1.0000e-02 eta: 9:42:14 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.0087 loss: 4.0579 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4950 loss_aux: 1.5629 2023/02/17 13:24:25 - mmengine - INFO - Epoch(train) [17][1340/1345] lr: 1.0000e-02 eta: 9:42:09 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 6.8853 loss: 4.0328 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4905 loss_aux: 1.5423 2023/02/17 13:24:26 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:24:26 - mmengine - INFO - Epoch(train) [17][1345/1345] lr: 1.0000e-02 eta: 9:42:07 time: 0.1840 data_time: 0.0058 memory: 8327 grad_norm: 6.8025 loss: 4.2426 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.6452 loss_aux: 1.5973 2023/02/17 13:24:26 - mmengine - INFO - Saving checkpoint at 17 epochs 2023/02/17 13:24:32 - mmengine - INFO - Epoch(train) [18][ 20/1345] lr: 1.0000e-02 eta: 9:42:05 time: 0.2077 data_time: 0.0165 memory: 8327 grad_norm: 6.8809 loss: 3.9413 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4429 loss_aux: 1.4984 2023/02/17 13:24:36 - mmengine - INFO - Epoch(train) [18][ 40/1345] lr: 1.0000e-02 eta: 9:42:01 time: 0.1926 data_time: 0.0043 memory: 8327 grad_norm: 6.7881 loss: 4.1305 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5299 loss_aux: 1.6007 2023/02/17 13:24:40 - mmengine - INFO - Epoch(train) [18][ 60/1345] lr: 1.0000e-02 eta: 9:41:56 time: 0.1890 data_time: 0.0054 memory: 8327 grad_norm: 7.0432 loss: 4.3579 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7289 loss_aux: 1.6290 2023/02/17 13:24:44 - mmengine - INFO - Epoch(train) [18][ 80/1345] lr: 1.0000e-02 eta: 9:41:51 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 6.8437 loss: 3.6898 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2053 loss_aux: 1.4844 2023/02/17 13:24:48 - mmengine - INFO - Epoch(train) [18][ 100/1345] lr: 1.0000e-02 eta: 9:41:46 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 6.8856 loss: 3.8774 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4275 loss_aux: 1.4499 2023/02/17 13:24:51 - mmengine - INFO - Epoch(train) [18][ 120/1345] lr: 1.0000e-02 eta: 9:41:41 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.8996 loss: 4.1888 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.5718 loss_aux: 1.6169 2023/02/17 13:24:54 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:24:55 - mmengine - INFO - Epoch(train) [18][ 140/1345] lr: 1.0000e-02 eta: 9:41:36 time: 0.1893 data_time: 0.0055 memory: 8327 grad_norm: 6.7773 loss: 3.9467 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3922 loss_aux: 1.5545 2023/02/17 13:24:59 - mmengine - INFO - Epoch(train) [18][ 160/1345] lr: 1.0000e-02 eta: 9:41:31 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 6.8934 loss: 3.8477 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4067 loss_aux: 1.4409 2023/02/17 13:25:03 - mmengine - INFO - Epoch(train) [18][ 180/1345] lr: 1.0000e-02 eta: 9:41:27 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 6.8129 loss: 3.6476 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2140 loss_aux: 1.4336 2023/02/17 13:25:07 - mmengine - INFO - Epoch(train) [18][ 200/1345] lr: 1.0000e-02 eta: 9:41:22 time: 0.1893 data_time: 0.0055 memory: 8327 grad_norm: 6.7892 loss: 4.1454 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5040 loss_aux: 1.6414 2023/02/17 13:25:10 - mmengine - INFO - Epoch(train) [18][ 220/1345] lr: 1.0000e-02 eta: 9:41:17 time: 0.1895 data_time: 0.0056 memory: 8327 grad_norm: 6.8482 loss: 4.0488 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4917 loss_aux: 1.5572 2023/02/17 13:25:14 - mmengine - INFO - Epoch(train) [18][ 240/1345] lr: 1.0000e-02 eta: 9:41:12 time: 0.1891 data_time: 0.0055 memory: 8327 grad_norm: 6.9363 loss: 3.7990 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.3188 loss_aux: 1.4802 2023/02/17 13:25:18 - mmengine - INFO - Epoch(train) [18][ 260/1345] lr: 1.0000e-02 eta: 9:41:07 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 6.8700 loss: 4.1987 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6122 loss_aux: 1.5865 2023/02/17 13:25:22 - mmengine - INFO - Epoch(train) [18][ 280/1345] lr: 1.0000e-02 eta: 9:41:02 time: 0.1893 data_time: 0.0055 memory: 8327 grad_norm: 6.9307 loss: 3.8048 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3316 loss_aux: 1.4732 2023/02/17 13:25:25 - mmengine - INFO - Epoch(train) [18][ 300/1345] lr: 1.0000e-02 eta: 9:40:58 time: 0.1888 data_time: 0.0055 memory: 8327 grad_norm: 6.9079 loss: 3.7839 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3002 loss_aux: 1.4836 2023/02/17 13:25:29 - mmengine - INFO - Epoch(train) [18][ 320/1345] lr: 1.0000e-02 eta: 9:40:53 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 6.7098 loss: 3.8690 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3018 loss_aux: 1.5673 2023/02/17 13:25:33 - mmengine - INFO - Epoch(train) [18][ 340/1345] lr: 1.0000e-02 eta: 9:40:48 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.8913 loss: 3.8624 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3911 loss_aux: 1.4713 2023/02/17 13:25:37 - mmengine - INFO - Epoch(train) [18][ 360/1345] lr: 1.0000e-02 eta: 9:40:43 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 6.9437 loss: 4.0381 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4955 loss_aux: 1.5426 2023/02/17 13:25:41 - mmengine - INFO - Epoch(train) [18][ 380/1345] lr: 1.0000e-02 eta: 9:40:38 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 7.0899 loss: 3.9865 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4030 loss_aux: 1.5835 2023/02/17 13:25:44 - mmengine - INFO - Epoch(train) [18][ 400/1345] lr: 1.0000e-02 eta: 9:40:33 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 6.9751 loss: 4.0382 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4603 loss_aux: 1.5780 2023/02/17 13:25:48 - mmengine - INFO - Epoch(train) [18][ 420/1345] lr: 1.0000e-02 eta: 9:40:29 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.3295 loss: 3.9833 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4281 loss_aux: 1.5552 2023/02/17 13:25:52 - mmengine - INFO - Epoch(train) [18][ 440/1345] lr: 1.0000e-02 eta: 9:40:24 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 6.9514 loss: 3.9905 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4618 loss_aux: 1.5287 2023/02/17 13:25:56 - mmengine - INFO - Epoch(train) [18][ 460/1345] lr: 1.0000e-02 eta: 9:40:19 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 6.9165 loss: 3.6709 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2563 loss_aux: 1.4146 2023/02/17 13:26:00 - mmengine - INFO - Epoch(train) [18][ 480/1345] lr: 1.0000e-02 eta: 9:40:14 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 6.8709 loss: 4.3542 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7386 loss_aux: 1.6156 2023/02/17 13:26:03 - mmengine - INFO - Epoch(train) [18][ 500/1345] lr: 1.0000e-02 eta: 9:40:09 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 7.0591 loss: 3.8480 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3584 loss_aux: 1.4896 2023/02/17 13:26:07 - mmengine - INFO - Epoch(train) [18][ 520/1345] lr: 1.0000e-02 eta: 9:40:04 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.1472 loss: 3.9620 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4696 loss_aux: 1.4924 2023/02/17 13:26:11 - mmengine - INFO - Epoch(train) [18][ 540/1345] lr: 1.0000e-02 eta: 9:40:00 time: 0.1902 data_time: 0.0066 memory: 8327 grad_norm: 6.9957 loss: 4.0496 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4662 loss_aux: 1.5835 2023/02/17 13:26:15 - mmengine - INFO - Epoch(train) [18][ 560/1345] lr: 1.0000e-02 eta: 9:39:55 time: 0.1885 data_time: 0.0052 memory: 8327 grad_norm: 6.8635 loss: 3.8065 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3347 loss_aux: 1.4718 2023/02/17 13:26:18 - mmengine - INFO - Epoch(train) [18][ 580/1345] lr: 1.0000e-02 eta: 9:39:50 time: 0.1886 data_time: 0.0055 memory: 8327 grad_norm: 6.7650 loss: 3.6023 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.1825 loss_aux: 1.4199 2023/02/17 13:26:22 - mmengine - INFO - Epoch(train) [18][ 600/1345] lr: 1.0000e-02 eta: 9:39:45 time: 0.1884 data_time: 0.0054 memory: 8327 grad_norm: 6.9473 loss: 3.8132 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2822 loss_aux: 1.5310 2023/02/17 13:26:26 - mmengine - INFO - Epoch(train) [18][ 620/1345] lr: 1.0000e-02 eta: 9:39:40 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.0121 loss: 4.3558 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.7160 loss_aux: 1.6398 2023/02/17 13:26:30 - mmengine - INFO - Epoch(train) [18][ 640/1345] lr: 1.0000e-02 eta: 9:39:37 time: 0.1990 data_time: 0.0155 memory: 8327 grad_norm: 7.0865 loss: 3.5925 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1356 loss_aux: 1.4569 2023/02/17 13:26:34 - mmengine - INFO - Epoch(train) [18][ 660/1345] lr: 1.0000e-02 eta: 9:39:32 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 6.9705 loss: 3.8366 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3764 loss_aux: 1.4603 2023/02/17 13:26:38 - mmengine - INFO - Epoch(train) [18][ 680/1345] lr: 1.0000e-02 eta: 9:39:27 time: 0.1885 data_time: 0.0055 memory: 8327 grad_norm: 6.9577 loss: 4.1183 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5768 loss_aux: 1.5415 2023/02/17 13:26:41 - mmengine - INFO - Epoch(train) [18][ 700/1345] lr: 1.0000e-02 eta: 9:39:22 time: 0.1893 data_time: 0.0055 memory: 8327 grad_norm: 7.0226 loss: 4.0025 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4933 loss_aux: 1.5093 2023/02/17 13:26:45 - mmengine - INFO - Epoch(train) [18][ 720/1345] lr: 1.0000e-02 eta: 9:39:18 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 6.9389 loss: 4.0580 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5308 loss_aux: 1.5272 2023/02/17 13:26:49 - mmengine - INFO - Epoch(train) [18][ 740/1345] lr: 1.0000e-02 eta: 9:39:13 time: 0.1890 data_time: 0.0059 memory: 8327 grad_norm: 7.0167 loss: 3.9457 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4547 loss_aux: 1.4910 2023/02/17 13:26:53 - mmengine - INFO - Epoch(train) [18][ 760/1345] lr: 1.0000e-02 eta: 9:39:08 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 7.0278 loss: 4.3741 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7362 loss_aux: 1.6379 2023/02/17 13:26:56 - mmengine - INFO - Epoch(train) [18][ 780/1345] lr: 1.0000e-02 eta: 9:39:03 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.1139 loss: 3.8134 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3518 loss_aux: 1.4616 2023/02/17 13:27:00 - mmengine - INFO - Epoch(train) [18][ 800/1345] lr: 1.0000e-02 eta: 9:38:58 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.9486 loss: 3.8414 top1_acc: 0.1250 top5_acc: 0.8750 loss_cls: 2.3495 loss_aux: 1.4920 2023/02/17 13:27:04 - mmengine - INFO - Epoch(train) [18][ 820/1345] lr: 1.0000e-02 eta: 9:38:53 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.9121 loss: 3.9458 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4123 loss_aux: 1.5335 2023/02/17 13:27:08 - mmengine - INFO - Epoch(train) [18][ 840/1345] lr: 1.0000e-02 eta: 9:38:49 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 6.8379 loss: 3.7506 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2880 loss_aux: 1.4626 2023/02/17 13:27:12 - mmengine - INFO - Epoch(train) [18][ 860/1345] lr: 1.0000e-02 eta: 9:38:44 time: 0.1891 data_time: 0.0055 memory: 8327 grad_norm: 7.0781 loss: 3.9679 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4364 loss_aux: 1.5315 2023/02/17 13:27:15 - mmengine - INFO - Epoch(train) [18][ 880/1345] lr: 1.0000e-02 eta: 9:38:39 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 6.9995 loss: 4.0628 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5425 loss_aux: 1.5202 2023/02/17 13:27:19 - mmengine - INFO - Epoch(train) [18][ 900/1345] lr: 1.0000e-02 eta: 9:38:34 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.9212 loss: 3.9988 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4556 loss_aux: 1.5432 2023/02/17 13:27:23 - mmengine - INFO - Epoch(train) [18][ 920/1345] lr: 1.0000e-02 eta: 9:38:29 time: 0.1888 data_time: 0.0055 memory: 8327 grad_norm: 7.1581 loss: 4.2698 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6367 loss_aux: 1.6331 2023/02/17 13:27:27 - mmengine - INFO - Epoch(train) [18][ 940/1345] lr: 1.0000e-02 eta: 9:38:24 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 6.9723 loss: 4.2302 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5708 loss_aux: 1.6594 2023/02/17 13:27:30 - mmengine - INFO - Epoch(train) [18][ 960/1345] lr: 1.0000e-02 eta: 9:38:20 time: 0.1902 data_time: 0.0063 memory: 8327 grad_norm: 6.9540 loss: 3.9358 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4437 loss_aux: 1.4921 2023/02/17 13:27:34 - mmengine - INFO - Epoch(train) [18][ 980/1345] lr: 1.0000e-02 eta: 9:38:15 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 6.8712 loss: 3.8757 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4047 loss_aux: 1.4710 2023/02/17 13:27:38 - mmengine - INFO - Epoch(train) [18][1000/1345] lr: 1.0000e-02 eta: 9:38:10 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 6.8727 loss: 4.6154 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.9209 loss_aux: 1.6945 2023/02/17 13:27:42 - mmengine - INFO - Epoch(train) [18][1020/1345] lr: 1.0000e-02 eta: 9:38:05 time: 0.1885 data_time: 0.0056 memory: 8327 grad_norm: 7.1204 loss: 4.2053 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6503 loss_aux: 1.5550 2023/02/17 13:27:46 - mmengine - INFO - Epoch(train) [18][1040/1345] lr: 1.0000e-02 eta: 9:38:01 time: 0.1892 data_time: 0.0054 memory: 8327 grad_norm: 6.8697 loss: 4.0131 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4747 loss_aux: 1.5384 2023/02/17 13:27:49 - mmengine - INFO - Epoch(train) [18][1060/1345] lr: 1.0000e-02 eta: 9:37:56 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 6.9685 loss: 4.0759 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5238 loss_aux: 1.5521 2023/02/17 13:27:53 - mmengine - INFO - Epoch(train) [18][1080/1345] lr: 1.0000e-02 eta: 9:37:51 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 6.8129 loss: 4.0303 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5324 loss_aux: 1.4979 2023/02/17 13:27:57 - mmengine - INFO - Epoch(train) [18][1100/1345] lr: 1.0000e-02 eta: 9:37:46 time: 0.1893 data_time: 0.0055 memory: 8327 grad_norm: 6.8817 loss: 4.0060 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4090 loss_aux: 1.5971 2023/02/17 13:28:01 - mmengine - INFO - Epoch(train) [18][1120/1345] lr: 1.0000e-02 eta: 9:37:42 time: 0.1905 data_time: 0.0070 memory: 8327 grad_norm: 6.7711 loss: 3.6569 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2192 loss_aux: 1.4377 2023/02/17 13:28:04 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:28:05 - mmengine - INFO - Epoch(train) [18][1140/1345] lr: 1.0000e-02 eta: 9:37:37 time: 0.1888 data_time: 0.0055 memory: 8327 grad_norm: 6.8836 loss: 3.8541 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.3472 loss_aux: 1.5069 2023/02/17 13:28:08 - mmengine - INFO - Epoch(train) [18][1160/1345] lr: 1.0000e-02 eta: 9:37:32 time: 0.1904 data_time: 0.0062 memory: 8327 grad_norm: 6.9240 loss: 4.1600 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5872 loss_aux: 1.5728 2023/02/17 13:28:12 - mmengine - INFO - Epoch(train) [18][1180/1345] lr: 1.0000e-02 eta: 9:37:27 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 6.8842 loss: 3.8333 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3195 loss_aux: 1.5138 2023/02/17 13:28:16 - mmengine - INFO - Epoch(train) [18][1200/1345] lr: 1.0000e-02 eta: 9:37:23 time: 0.1886 data_time: 0.0058 memory: 8327 grad_norm: 6.7818 loss: 4.2502 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6418 loss_aux: 1.6084 2023/02/17 13:28:20 - mmengine - INFO - Epoch(train) [18][1220/1345] lr: 1.0000e-02 eta: 9:37:18 time: 0.1889 data_time: 0.0053 memory: 8327 grad_norm: 6.7995 loss: 3.6229 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2243 loss_aux: 1.3986 2023/02/17 13:28:23 - mmengine - INFO - Epoch(train) [18][1240/1345] lr: 1.0000e-02 eta: 9:37:13 time: 0.1897 data_time: 0.0055 memory: 8327 grad_norm: 7.0697 loss: 3.9825 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4443 loss_aux: 1.5382 2023/02/17 13:28:27 - mmengine - INFO - Epoch(train) [18][1260/1345] lr: 1.0000e-02 eta: 9:37:08 time: 0.1888 data_time: 0.0055 memory: 8327 grad_norm: 7.0217 loss: 3.8311 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3315 loss_aux: 1.4996 2023/02/17 13:28:31 - mmengine - INFO - Epoch(train) [18][1280/1345] lr: 1.0000e-02 eta: 9:37:03 time: 0.1885 data_time: 0.0055 memory: 8327 grad_norm: 6.9147 loss: 4.2781 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6655 loss_aux: 1.6126 2023/02/17 13:28:35 - mmengine - INFO - Epoch(train) [18][1300/1345] lr: 1.0000e-02 eta: 9:36:59 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 6.8294 loss: 3.5608 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0999 loss_aux: 1.4609 2023/02/17 13:28:39 - mmengine - INFO - Epoch(train) [18][1320/1345] lr: 1.0000e-02 eta: 9:36:54 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.0682 loss: 3.6261 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2211 loss_aux: 1.4050 2023/02/17 13:28:42 - mmengine - INFO - Epoch(train) [18][1340/1345] lr: 1.0000e-02 eta: 9:36:49 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 7.0331 loss: 4.1499 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5687 loss_aux: 1.5812 2023/02/17 13:28:43 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:28:43 - mmengine - INFO - Epoch(train) [18][1345/1345] lr: 1.0000e-02 eta: 9:36:47 time: 0.1829 data_time: 0.0055 memory: 8327 grad_norm: 6.8829 loss: 4.3928 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.7266 loss_aux: 1.6662 2023/02/17 13:28:43 - mmengine - INFO - Saving checkpoint at 18 epochs 2023/02/17 13:28:50 - mmengine - INFO - Epoch(train) [19][ 20/1345] lr: 1.0000e-02 eta: 9:36:45 time: 0.2070 data_time: 0.0171 memory: 8327 grad_norm: 7.0398 loss: 3.7024 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2963 loss_aux: 1.4061 2023/02/17 13:28:54 - mmengine - INFO - Epoch(train) [19][ 40/1345] lr: 1.0000e-02 eta: 9:36:40 time: 0.1912 data_time: 0.0051 memory: 8327 grad_norm: 7.0701 loss: 3.9663 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4378 loss_aux: 1.5284 2023/02/17 13:28:57 - mmengine - INFO - Epoch(train) [19][ 60/1345] lr: 1.0000e-02 eta: 9:36:36 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 7.1046 loss: 3.5058 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.1221 loss_aux: 1.3837 2023/02/17 13:29:01 - mmengine - INFO - Epoch(train) [19][ 80/1345] lr: 1.0000e-02 eta: 9:36:31 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.0542 loss: 4.0162 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4636 loss_aux: 1.5526 2023/02/17 13:29:05 - mmengine - INFO - Epoch(train) [19][ 100/1345] lr: 1.0000e-02 eta: 9:36:26 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.0382 loss: 3.8924 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3789 loss_aux: 1.5135 2023/02/17 13:29:09 - mmengine - INFO - Epoch(train) [19][ 120/1345] lr: 1.0000e-02 eta: 9:36:22 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 6.9305 loss: 3.8030 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3017 loss_aux: 1.5013 2023/02/17 13:29:12 - mmengine - INFO - Epoch(train) [19][ 140/1345] lr: 1.0000e-02 eta: 9:36:17 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 6.9813 loss: 4.3342 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6545 loss_aux: 1.6797 2023/02/17 13:29:16 - mmengine - INFO - Epoch(train) [19][ 160/1345] lr: 1.0000e-02 eta: 9:36:12 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 6.9642 loss: 4.4049 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7551 loss_aux: 1.6499 2023/02/17 13:29:20 - mmengine - INFO - Epoch(train) [19][ 180/1345] lr: 1.0000e-02 eta: 9:36:07 time: 0.1892 data_time: 0.0054 memory: 8327 grad_norm: 7.0636 loss: 3.8551 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3743 loss_aux: 1.4808 2023/02/17 13:29:24 - mmengine - INFO - Epoch(train) [19][ 200/1345] lr: 1.0000e-02 eta: 9:36:03 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.2080 loss: 3.9534 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4050 loss_aux: 1.5484 2023/02/17 13:29:28 - mmengine - INFO - Epoch(train) [19][ 220/1345] lr: 1.0000e-02 eta: 9:35:58 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 6.9637 loss: 3.7512 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2674 loss_aux: 1.4838 2023/02/17 13:29:31 - mmengine - INFO - Epoch(train) [19][ 240/1345] lr: 1.0000e-02 eta: 9:35:53 time: 0.1892 data_time: 0.0061 memory: 8327 grad_norm: 6.9040 loss: 4.4832 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7430 loss_aux: 1.7401 2023/02/17 13:29:35 - mmengine - INFO - Epoch(train) [19][ 260/1345] lr: 1.0000e-02 eta: 9:35:48 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 6.9911 loss: 3.9918 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4438 loss_aux: 1.5480 2023/02/17 13:29:39 - mmengine - INFO - Epoch(train) [19][ 280/1345] lr: 1.0000e-02 eta: 9:35:44 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.0516 loss: 4.1560 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5671 loss_aux: 1.5889 2023/02/17 13:29:43 - mmengine - INFO - Epoch(train) [19][ 300/1345] lr: 1.0000e-02 eta: 9:35:39 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.9549 loss: 4.2226 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6532 loss_aux: 1.5694 2023/02/17 13:29:47 - mmengine - INFO - Epoch(train) [19][ 320/1345] lr: 1.0000e-02 eta: 9:35:34 time: 0.1888 data_time: 0.0055 memory: 8327 grad_norm: 6.7478 loss: 3.8432 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3508 loss_aux: 1.4924 2023/02/17 13:29:50 - mmengine - INFO - Epoch(train) [19][ 340/1345] lr: 1.0000e-02 eta: 9:35:29 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 6.8845 loss: 3.5704 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1378 loss_aux: 1.4327 2023/02/17 13:29:54 - mmengine - INFO - Epoch(train) [19][ 360/1345] lr: 1.0000e-02 eta: 9:35:25 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 6.9516 loss: 3.6027 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1477 loss_aux: 1.4550 2023/02/17 13:29:58 - mmengine - INFO - Epoch(train) [19][ 380/1345] lr: 1.0000e-02 eta: 9:35:20 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 6.8719 loss: 3.9872 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4363 loss_aux: 1.5509 2023/02/17 13:30:02 - mmengine - INFO - Epoch(train) [19][ 400/1345] lr: 1.0000e-02 eta: 9:35:15 time: 0.1889 data_time: 0.0054 memory: 8327 grad_norm: 7.1101 loss: 3.8892 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3622 loss_aux: 1.5271 2023/02/17 13:30:05 - mmengine - INFO - Epoch(train) [19][ 420/1345] lr: 1.0000e-02 eta: 9:35:11 time: 0.1908 data_time: 0.0071 memory: 8327 grad_norm: 7.0491 loss: 3.8540 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3836 loss_aux: 1.4704 2023/02/17 13:30:09 - mmengine - INFO - Epoch(train) [19][ 440/1345] lr: 1.0000e-02 eta: 9:35:06 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.1181 loss: 4.0791 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5070 loss_aux: 1.5721 2023/02/17 13:30:13 - mmengine - INFO - Epoch(train) [19][ 460/1345] lr: 1.0000e-02 eta: 9:35:01 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 6.9446 loss: 4.1007 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5488 loss_aux: 1.5520 2023/02/17 13:30:17 - mmengine - INFO - Epoch(train) [19][ 480/1345] lr: 1.0000e-02 eta: 9:34:56 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 6.9019 loss: 3.8734 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3944 loss_aux: 1.4790 2023/02/17 13:30:21 - mmengine - INFO - Epoch(train) [19][ 500/1345] lr: 1.0000e-02 eta: 9:34:52 time: 0.1890 data_time: 0.0054 memory: 8327 grad_norm: 6.9334 loss: 4.1185 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5368 loss_aux: 1.5818 2023/02/17 13:30:24 - mmengine - INFO - Epoch(train) [19][ 520/1345] lr: 1.0000e-02 eta: 9:34:47 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.9262 loss: 4.1433 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6047 loss_aux: 1.5386 2023/02/17 13:30:28 - mmengine - INFO - Epoch(train) [19][ 540/1345] lr: 1.0000e-02 eta: 9:34:42 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 6.8737 loss: 3.8954 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3103 loss_aux: 1.5851 2023/02/17 13:30:32 - mmengine - INFO - Epoch(train) [19][ 560/1345] lr: 1.0000e-02 eta: 9:34:37 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 6.9023 loss: 3.8617 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3573 loss_aux: 1.5044 2023/02/17 13:30:36 - mmengine - INFO - Epoch(train) [19][ 580/1345] lr: 1.0000e-02 eta: 9:34:33 time: 0.1897 data_time: 0.0055 memory: 8327 grad_norm: 7.1582 loss: 3.9259 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3827 loss_aux: 1.5431 2023/02/17 13:30:39 - mmengine - INFO - Epoch(train) [19][ 600/1345] lr: 1.0000e-02 eta: 9:34:28 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.1471 loss: 3.9682 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4788 loss_aux: 1.4894 2023/02/17 13:30:43 - mmengine - INFO - Epoch(train) [19][ 620/1345] lr: 1.0000e-02 eta: 9:34:23 time: 0.1891 data_time: 0.0055 memory: 8327 grad_norm: 6.9759 loss: 3.9470 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4572 loss_aux: 1.4899 2023/02/17 13:30:47 - mmengine - INFO - Epoch(train) [19][ 640/1345] lr: 1.0000e-02 eta: 9:34:19 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 6.9915 loss: 3.6882 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2167 loss_aux: 1.4714 2023/02/17 13:30:51 - mmengine - INFO - Epoch(train) [19][ 660/1345] lr: 1.0000e-02 eta: 9:34:14 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.0459 loss: 4.0667 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5013 loss_aux: 1.5654 2023/02/17 13:30:55 - mmengine - INFO - Epoch(train) [19][ 680/1345] lr: 1.0000e-02 eta: 9:34:09 time: 0.1904 data_time: 0.0073 memory: 8327 grad_norm: 7.3559 loss: 3.9338 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4347 loss_aux: 1.4991 2023/02/17 13:30:58 - mmengine - INFO - Epoch(train) [19][ 700/1345] lr: 1.0000e-02 eta: 9:34:04 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 7.1918 loss: 3.8022 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4150 loss_aux: 1.3872 2023/02/17 13:31:02 - mmengine - INFO - Epoch(train) [19][ 720/1345] lr: 1.0000e-02 eta: 9:34:00 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 6.8979 loss: 4.1696 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5816 loss_aux: 1.5879 2023/02/17 13:31:06 - mmengine - INFO - Epoch(train) [19][ 740/1345] lr: 1.0000e-02 eta: 9:33:55 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.1273 loss: 4.2192 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6057 loss_aux: 1.6135 2023/02/17 13:31:10 - mmengine - INFO - Epoch(train) [19][ 760/1345] lr: 1.0000e-02 eta: 9:33:50 time: 0.1896 data_time: 0.0064 memory: 8327 grad_norm: 6.8822 loss: 4.1355 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5580 loss_aux: 1.5775 2023/02/17 13:31:14 - mmengine - INFO - Epoch(train) [19][ 780/1345] lr: 1.0000e-02 eta: 9:33:46 time: 0.1893 data_time: 0.0055 memory: 8327 grad_norm: 7.0306 loss: 4.1767 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6383 loss_aux: 1.5384 2023/02/17 13:31:15 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:31:17 - mmengine - INFO - Epoch(train) [19][ 800/1345] lr: 1.0000e-02 eta: 9:33:41 time: 0.1898 data_time: 0.0055 memory: 8327 grad_norm: 6.8941 loss: 3.8820 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3644 loss_aux: 1.5177 2023/02/17 13:31:21 - mmengine - INFO - Epoch(train) [19][ 820/1345] lr: 1.0000e-02 eta: 9:33:36 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 6.8850 loss: 4.2563 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.6211 loss_aux: 1.6352 2023/02/17 13:31:25 - mmengine - INFO - Epoch(train) [19][ 840/1345] lr: 1.0000e-02 eta: 9:33:32 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 6.8583 loss: 4.2065 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5916 loss_aux: 1.6149 2023/02/17 13:31:29 - mmengine - INFO - Epoch(train) [19][ 860/1345] lr: 1.0000e-02 eta: 9:33:27 time: 0.1891 data_time: 0.0054 memory: 8327 grad_norm: 6.8779 loss: 3.9034 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3493 loss_aux: 1.5541 2023/02/17 13:31:32 - mmengine - INFO - Epoch(train) [19][ 880/1345] lr: 1.0000e-02 eta: 9:33:22 time: 0.1887 data_time: 0.0055 memory: 8327 grad_norm: 6.9806 loss: 4.0115 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5315 loss_aux: 1.4799 2023/02/17 13:31:36 - mmengine - INFO - Epoch(train) [19][ 900/1345] lr: 1.0000e-02 eta: 9:33:18 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.9913 loss: 3.8986 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4252 loss_aux: 1.4734 2023/02/17 13:31:40 - mmengine - INFO - Epoch(train) [19][ 920/1345] lr: 1.0000e-02 eta: 9:33:13 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 6.9851 loss: 3.7149 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2731 loss_aux: 1.4418 2023/02/17 13:31:44 - mmengine - INFO - Epoch(train) [19][ 940/1345] lr: 1.0000e-02 eta: 9:33:08 time: 0.1891 data_time: 0.0055 memory: 8327 grad_norm: 6.9015 loss: 3.6130 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2074 loss_aux: 1.4056 2023/02/17 13:31:48 - mmengine - INFO - Epoch(train) [19][ 960/1345] lr: 1.0000e-02 eta: 9:33:03 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 6.9753 loss: 4.0043 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4734 loss_aux: 1.5309 2023/02/17 13:31:51 - mmengine - INFO - Epoch(train) [19][ 980/1345] lr: 1.0000e-02 eta: 9:32:59 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 6.9387 loss: 3.6079 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2282 loss_aux: 1.3797 2023/02/17 13:31:55 - mmengine - INFO - Epoch(train) [19][1000/1345] lr: 1.0000e-02 eta: 9:32:54 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 6.9159 loss: 3.8059 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3316 loss_aux: 1.4743 2023/02/17 13:31:59 - mmengine - INFO - Epoch(train) [19][1020/1345] lr: 1.0000e-02 eta: 9:32:50 time: 0.1901 data_time: 0.0056 memory: 8327 grad_norm: 7.1958 loss: 3.9788 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4438 loss_aux: 1.5350 2023/02/17 13:32:03 - mmengine - INFO - Epoch(train) [19][1040/1345] lr: 1.0000e-02 eta: 9:32:45 time: 0.1888 data_time: 0.0055 memory: 8327 grad_norm: 7.0800 loss: 4.1411 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5720 loss_aux: 1.5690 2023/02/17 13:32:07 - mmengine - INFO - Epoch(train) [19][1060/1345] lr: 1.0000e-02 eta: 9:32:40 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.0445 loss: 4.1465 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5618 loss_aux: 1.5847 2023/02/17 13:32:10 - mmengine - INFO - Epoch(train) [19][1080/1345] lr: 1.0000e-02 eta: 9:32:36 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 6.8110 loss: 3.8577 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3675 loss_aux: 1.4902 2023/02/17 13:32:14 - mmengine - INFO - Epoch(train) [19][1100/1345] lr: 1.0000e-02 eta: 9:32:31 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.0000 loss: 3.9939 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4522 loss_aux: 1.5417 2023/02/17 13:32:18 - mmengine - INFO - Epoch(train) [19][1120/1345] lr: 1.0000e-02 eta: 9:32:26 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.0740 loss: 4.2393 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6132 loss_aux: 1.6261 2023/02/17 13:32:22 - mmengine - INFO - Epoch(train) [19][1140/1345] lr: 1.0000e-02 eta: 9:32:22 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.1061 loss: 4.0844 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5295 loss_aux: 1.5548 2023/02/17 13:32:25 - mmengine - INFO - Epoch(train) [19][1160/1345] lr: 1.0000e-02 eta: 9:32:17 time: 0.1903 data_time: 0.0068 memory: 8327 grad_norm: 7.1474 loss: 3.8111 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3335 loss_aux: 1.4775 2023/02/17 13:32:29 - mmengine - INFO - Epoch(train) [19][1180/1345] lr: 1.0000e-02 eta: 9:32:12 time: 0.1896 data_time: 0.0054 memory: 8327 grad_norm: 7.1627 loss: 3.9685 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4524 loss_aux: 1.5161 2023/02/17 13:32:33 - mmengine - INFO - Epoch(train) [19][1200/1345] lr: 1.0000e-02 eta: 9:32:08 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 6.9220 loss: 4.1996 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6098 loss_aux: 1.5898 2023/02/17 13:32:37 - mmengine - INFO - Epoch(train) [19][1220/1345] lr: 1.0000e-02 eta: 9:32:03 time: 0.1891 data_time: 0.0064 memory: 8327 grad_norm: 7.0751 loss: 4.0752 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5093 loss_aux: 1.5659 2023/02/17 13:32:41 - mmengine - INFO - Epoch(train) [19][1240/1345] lr: 1.0000e-02 eta: 9:31:58 time: 0.1886 data_time: 0.0059 memory: 8327 grad_norm: 7.1095 loss: 4.2517 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6714 loss_aux: 1.5803 2023/02/17 13:32:44 - mmengine - INFO - Epoch(train) [19][1260/1345] lr: 1.0000e-02 eta: 9:31:54 time: 0.1886 data_time: 0.0054 memory: 8327 grad_norm: 7.1854 loss: 4.0480 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4965 loss_aux: 1.5516 2023/02/17 13:32:48 - mmengine - INFO - Epoch(train) [19][1280/1345] lr: 1.0000e-02 eta: 9:31:49 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 7.0586 loss: 3.7548 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2967 loss_aux: 1.4582 2023/02/17 13:32:52 - mmengine - INFO - Epoch(train) [19][1300/1345] lr: 1.0000e-02 eta: 9:31:44 time: 0.1887 data_time: 0.0055 memory: 8327 grad_norm: 6.9747 loss: 3.7903 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3362 loss_aux: 1.4541 2023/02/17 13:32:56 - mmengine - INFO - Epoch(train) [19][1320/1345] lr: 1.0000e-02 eta: 9:31:39 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.1017 loss: 4.2409 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6154 loss_aux: 1.6255 2023/02/17 13:33:00 - mmengine - INFO - Epoch(train) [19][1340/1345] lr: 1.0000e-02 eta: 9:31:35 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 6.8875 loss: 3.7628 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3103 loss_aux: 1.4526 2023/02/17 13:33:00 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:33:00 - mmengine - INFO - Epoch(train) [19][1345/1345] lr: 1.0000e-02 eta: 9:31:33 time: 0.1831 data_time: 0.0059 memory: 8327 grad_norm: 6.8169 loss: 3.9072 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.4338 loss_aux: 1.4734 2023/02/17 13:33:00 - mmengine - INFO - Saving checkpoint at 19 epochs 2023/02/17 13:33:08 - mmengine - INFO - Epoch(train) [20][ 20/1345] lr: 1.0000e-02 eta: 9:31:31 time: 0.2059 data_time: 0.0148 memory: 8327 grad_norm: 6.9647 loss: 4.0544 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5296 loss_aux: 1.5248 2023/02/17 13:33:11 - mmengine - INFO - Epoch(train) [20][ 40/1345] lr: 1.0000e-02 eta: 9:31:26 time: 0.1888 data_time: 0.0045 memory: 8327 grad_norm: 6.9679 loss: 3.9769 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4263 loss_aux: 1.5507 2023/02/17 13:33:15 - mmengine - INFO - Epoch(train) [20][ 60/1345] lr: 1.0000e-02 eta: 9:31:21 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 6.8177 loss: 3.7260 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2755 loss_aux: 1.4506 2023/02/17 13:33:19 - mmengine - INFO - Epoch(train) [20][ 80/1345] lr: 1.0000e-02 eta: 9:31:16 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 6.9575 loss: 4.0203 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4887 loss_aux: 1.5317 2023/02/17 13:33:23 - mmengine - INFO - Epoch(train) [20][ 100/1345] lr: 1.0000e-02 eta: 9:31:12 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 6.8686 loss: 4.0615 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5216 loss_aux: 1.5399 2023/02/17 13:33:26 - mmengine - INFO - Epoch(train) [20][ 120/1345] lr: 1.0000e-02 eta: 9:31:07 time: 0.1903 data_time: 0.0057 memory: 8327 grad_norm: 7.0881 loss: 4.1142 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5501 loss_aux: 1.5641 2023/02/17 13:33:30 - mmengine - INFO - Epoch(train) [20][ 140/1345] lr: 1.0000e-02 eta: 9:31:03 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 7.0456 loss: 3.9285 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3946 loss_aux: 1.5339 2023/02/17 13:33:34 - mmengine - INFO - Epoch(train) [20][ 160/1345] lr: 1.0000e-02 eta: 9:30:58 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.2297 loss: 3.7298 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2406 loss_aux: 1.4892 2023/02/17 13:33:38 - mmengine - INFO - Epoch(train) [20][ 180/1345] lr: 1.0000e-02 eta: 9:30:53 time: 0.1887 data_time: 0.0055 memory: 8327 grad_norm: 6.9406 loss: 4.1740 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5736 loss_aux: 1.6004 2023/02/17 13:33:42 - mmengine - INFO - Epoch(train) [20][ 200/1345] lr: 1.0000e-02 eta: 9:30:49 time: 0.1888 data_time: 0.0055 memory: 8327 grad_norm: 7.0650 loss: 3.2359 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9230 loss_aux: 1.3129 2023/02/17 13:33:45 - mmengine - INFO - Epoch(train) [20][ 220/1345] lr: 1.0000e-02 eta: 9:30:44 time: 0.1907 data_time: 0.0076 memory: 8327 grad_norm: 7.1850 loss: 3.9415 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3754 loss_aux: 1.5661 2023/02/17 13:33:49 - mmengine - INFO - Epoch(train) [20][ 240/1345] lr: 1.0000e-02 eta: 9:30:39 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.0651 loss: 4.2613 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6663 loss_aux: 1.5951 2023/02/17 13:33:53 - mmengine - INFO - Epoch(train) [20][ 260/1345] lr: 1.0000e-02 eta: 9:30:35 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 6.9674 loss: 4.0563 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5060 loss_aux: 1.5503 2023/02/17 13:33:57 - mmengine - INFO - Epoch(train) [20][ 280/1345] lr: 1.0000e-02 eta: 9:30:30 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.6976 loss: 3.7782 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.3027 loss_aux: 1.4755 2023/02/17 13:34:00 - mmengine - INFO - Epoch(train) [20][ 300/1345] lr: 1.0000e-02 eta: 9:30:25 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.0761 loss: 4.1412 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5769 loss_aux: 1.5643 2023/02/17 13:34:04 - mmengine - INFO - Epoch(train) [20][ 320/1345] lr: 1.0000e-02 eta: 9:30:21 time: 0.1885 data_time: 0.0056 memory: 8327 grad_norm: 7.1817 loss: 3.5913 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1838 loss_aux: 1.4075 2023/02/17 13:34:08 - mmengine - INFO - Epoch(train) [20][ 340/1345] lr: 1.0000e-02 eta: 9:30:16 time: 0.1891 data_time: 0.0055 memory: 8327 grad_norm: 7.3108 loss: 3.8371 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3409 loss_aux: 1.4962 2023/02/17 13:34:12 - mmengine - INFO - Epoch(train) [20][ 360/1345] lr: 1.0000e-02 eta: 9:30:11 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.1972 loss: 3.6874 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2622 loss_aux: 1.4252 2023/02/17 13:34:16 - mmengine - INFO - Epoch(train) [20][ 380/1345] lr: 1.0000e-02 eta: 9:30:07 time: 0.1897 data_time: 0.0056 memory: 8327 grad_norm: 7.0841 loss: 3.9759 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4302 loss_aux: 1.5457 2023/02/17 13:34:19 - mmengine - INFO - Epoch(train) [20][ 400/1345] lr: 1.0000e-02 eta: 9:30:02 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 6.9673 loss: 4.1605 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5925 loss_aux: 1.5680 2023/02/17 13:34:23 - mmengine - INFO - Epoch(train) [20][ 420/1345] lr: 1.0000e-02 eta: 9:29:58 time: 0.1885 data_time: 0.0056 memory: 8327 grad_norm: 6.9319 loss: 4.1129 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6195 loss_aux: 1.4934 2023/02/17 13:34:27 - mmengine - INFO - Epoch(train) [20][ 440/1345] lr: 1.0000e-02 eta: 9:29:53 time: 0.1887 data_time: 0.0055 memory: 8327 grad_norm: 6.8315 loss: 3.7513 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2782 loss_aux: 1.4732 2023/02/17 13:34:28 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:34:31 - mmengine - INFO - Epoch(train) [20][ 460/1345] lr: 1.0000e-02 eta: 9:29:48 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 7.1582 loss: 3.7693 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3079 loss_aux: 1.4614 2023/02/17 13:34:35 - mmengine - INFO - Epoch(train) [20][ 480/1345] lr: 1.0000e-02 eta: 9:29:44 time: 0.1887 data_time: 0.0055 memory: 8327 grad_norm: 6.8801 loss: 3.9622 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4283 loss_aux: 1.5339 2023/02/17 13:34:38 - mmengine - INFO - Epoch(train) [20][ 500/1345] lr: 1.0000e-02 eta: 9:29:39 time: 0.1885 data_time: 0.0055 memory: 8327 grad_norm: 7.0489 loss: 3.7479 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2488 loss_aux: 1.4991 2023/02/17 13:34:42 - mmengine - INFO - Epoch(train) [20][ 520/1345] lr: 1.0000e-02 eta: 9:29:34 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 6.9901 loss: 3.5967 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1958 loss_aux: 1.4009 2023/02/17 13:34:46 - mmengine - INFO - Epoch(train) [20][ 540/1345] lr: 1.0000e-02 eta: 9:29:30 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 7.0823 loss: 4.1256 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.5152 loss_aux: 1.6103 2023/02/17 13:34:50 - mmengine - INFO - Epoch(train) [20][ 560/1345] lr: 1.0000e-02 eta: 9:29:25 time: 0.1904 data_time: 0.0073 memory: 8327 grad_norm: 6.9987 loss: 3.8841 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3844 loss_aux: 1.4997 2023/02/17 13:34:53 - mmengine - INFO - Epoch(train) [20][ 580/1345] lr: 1.0000e-02 eta: 9:29:21 time: 0.1896 data_time: 0.0061 memory: 8327 grad_norm: 7.1662 loss: 3.8108 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3913 loss_aux: 1.4195 2023/02/17 13:34:57 - mmengine - INFO - Epoch(train) [20][ 600/1345] lr: 1.0000e-02 eta: 9:29:16 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 6.9583 loss: 4.2010 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5990 loss_aux: 1.6019 2023/02/17 13:35:01 - mmengine - INFO - Epoch(train) [20][ 620/1345] lr: 1.0000e-02 eta: 9:29:11 time: 0.1886 data_time: 0.0054 memory: 8327 grad_norm: 7.1862 loss: 4.0596 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4885 loss_aux: 1.5711 2023/02/17 13:35:05 - mmengine - INFO - Epoch(train) [20][ 640/1345] lr: 1.0000e-02 eta: 9:29:07 time: 0.1894 data_time: 0.0063 memory: 8327 grad_norm: 7.2309 loss: 4.1558 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5742 loss_aux: 1.5816 2023/02/17 13:35:09 - mmengine - INFO - Epoch(train) [20][ 660/1345] lr: 1.0000e-02 eta: 9:29:02 time: 0.1892 data_time: 0.0054 memory: 8327 grad_norm: 7.1641 loss: 4.1947 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5565 loss_aux: 1.6383 2023/02/17 13:35:12 - mmengine - INFO - Epoch(train) [20][ 680/1345] lr: 1.0000e-02 eta: 9:28:58 time: 0.1923 data_time: 0.0055 memory: 8327 grad_norm: 7.1465 loss: 4.1414 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5331 loss_aux: 1.6083 2023/02/17 13:35:16 - mmengine - INFO - Epoch(train) [20][ 700/1345] lr: 1.0000e-02 eta: 9:28:53 time: 0.1894 data_time: 0.0067 memory: 8327 grad_norm: 7.0705 loss: 4.0239 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4619 loss_aux: 1.5620 2023/02/17 13:35:20 - mmengine - INFO - Epoch(train) [20][ 720/1345] lr: 1.0000e-02 eta: 9:28:49 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.1101 loss: 3.7302 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2131 loss_aux: 1.5171 2023/02/17 13:35:24 - mmengine - INFO - Epoch(train) [20][ 740/1345] lr: 1.0000e-02 eta: 9:28:44 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.1062 loss: 3.5319 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1377 loss_aux: 1.3942 2023/02/17 13:35:28 - mmengine - INFO - Epoch(train) [20][ 760/1345] lr: 1.0000e-02 eta: 9:28:39 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.2347 loss: 4.0713 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5157 loss_aux: 1.5556 2023/02/17 13:35:31 - mmengine - INFO - Epoch(train) [20][ 780/1345] lr: 1.0000e-02 eta: 9:28:35 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 6.9195 loss: 4.1397 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5783 loss_aux: 1.5614 2023/02/17 13:35:35 - mmengine - INFO - Epoch(train) [20][ 800/1345] lr: 1.0000e-02 eta: 9:28:30 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.1087 loss: 3.8531 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3673 loss_aux: 1.4858 2023/02/17 13:35:39 - mmengine - INFO - Epoch(train) [20][ 820/1345] lr: 1.0000e-02 eta: 9:28:26 time: 0.1898 data_time: 0.0068 memory: 8327 grad_norm: 7.1035 loss: 4.0509 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4920 loss_aux: 1.5589 2023/02/17 13:35:43 - mmengine - INFO - Epoch(train) [20][ 840/1345] lr: 1.0000e-02 eta: 9:28:21 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 6.8258 loss: 4.0270 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4978 loss_aux: 1.5293 2023/02/17 13:35:46 - mmengine - INFO - Epoch(train) [20][ 860/1345] lr: 1.0000e-02 eta: 9:28:16 time: 0.1891 data_time: 0.0060 memory: 8327 grad_norm: 6.9523 loss: 3.9947 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4251 loss_aux: 1.5696 2023/02/17 13:35:50 - mmengine - INFO - Epoch(train) [20][ 880/1345] lr: 1.0000e-02 eta: 9:28:12 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.1098 loss: 3.9471 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4279 loss_aux: 1.5192 2023/02/17 13:35:54 - mmengine - INFO - Epoch(train) [20][ 900/1345] lr: 1.0000e-02 eta: 9:28:07 time: 0.1896 data_time: 0.0056 memory: 8327 grad_norm: 7.2446 loss: 3.8601 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3973 loss_aux: 1.4628 2023/02/17 13:35:58 - mmengine - INFO - Epoch(train) [20][ 920/1345] lr: 1.0000e-02 eta: 9:28:03 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.1038 loss: 4.2086 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6458 loss_aux: 1.5628 2023/02/17 13:36:02 - mmengine - INFO - Epoch(train) [20][ 940/1345] lr: 1.0000e-02 eta: 9:27:58 time: 0.1887 data_time: 0.0054 memory: 8327 grad_norm: 6.8615 loss: 3.8855 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3827 loss_aux: 1.5027 2023/02/17 13:36:05 - mmengine - INFO - Epoch(train) [20][ 960/1345] lr: 1.0000e-02 eta: 9:27:53 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 6.8475 loss: 3.7220 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2999 loss_aux: 1.4221 2023/02/17 13:36:09 - mmengine - INFO - Epoch(train) [20][ 980/1345] lr: 1.0000e-02 eta: 9:27:49 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.1702 loss: 3.8348 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3370 loss_aux: 1.4979 2023/02/17 13:36:13 - mmengine - INFO - Epoch(train) [20][1000/1345] lr: 1.0000e-02 eta: 9:27:44 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.1445 loss: 3.6549 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2032 loss_aux: 1.4517 2023/02/17 13:36:17 - mmengine - INFO - Epoch(train) [20][1020/1345] lr: 1.0000e-02 eta: 9:27:40 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.1292 loss: 3.8393 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3274 loss_aux: 1.5120 2023/02/17 13:36:21 - mmengine - INFO - Epoch(train) [20][1040/1345] lr: 1.0000e-02 eta: 9:27:35 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 6.9176 loss: 3.9116 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4089 loss_aux: 1.5027 2023/02/17 13:36:24 - mmengine - INFO - Epoch(train) [20][1060/1345] lr: 1.0000e-02 eta: 9:27:30 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.1059 loss: 4.3773 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7312 loss_aux: 1.6461 2023/02/17 13:36:28 - mmengine - INFO - Epoch(train) [20][1080/1345] lr: 1.0000e-02 eta: 9:27:28 time: 0.2092 data_time: 0.0257 memory: 8327 grad_norm: 6.9113 loss: 4.1795 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5918 loss_aux: 1.5876 2023/02/17 13:36:32 - mmengine - INFO - Epoch(train) [20][1100/1345] lr: 1.0000e-02 eta: 9:27:24 time: 0.1885 data_time: 0.0057 memory: 8327 grad_norm: 6.9287 loss: 3.9170 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3984 loss_aux: 1.5187 2023/02/17 13:36:36 - mmengine - INFO - Epoch(train) [20][1120/1345] lr: 1.0000e-02 eta: 9:27:19 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.9776 loss: 3.8596 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3956 loss_aux: 1.4640 2023/02/17 13:36:40 - mmengine - INFO - Epoch(train) [20][1140/1345] lr: 1.0000e-02 eta: 9:27:15 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.0842 loss: 3.6999 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2284 loss_aux: 1.4715 2023/02/17 13:36:44 - mmengine - INFO - Epoch(train) [20][1160/1345] lr: 1.0000e-02 eta: 9:27:10 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.0676 loss: 3.7940 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3684 loss_aux: 1.4256 2023/02/17 13:36:47 - mmengine - INFO - Epoch(train) [20][1180/1345] lr: 1.0000e-02 eta: 9:27:05 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.9784 loss: 4.1152 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5432 loss_aux: 1.5721 2023/02/17 13:36:51 - mmengine - INFO - Epoch(train) [20][1200/1345] lr: 1.0000e-02 eta: 9:27:01 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.1182 loss: 3.9770 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4978 loss_aux: 1.4793 2023/02/17 13:36:55 - mmengine - INFO - Epoch(train) [20][1220/1345] lr: 1.0000e-02 eta: 9:26:56 time: 0.1893 data_time: 0.0054 memory: 8327 grad_norm: 7.1295 loss: 3.9197 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4142 loss_aux: 1.5055 2023/02/17 13:36:59 - mmengine - INFO - Epoch(train) [20][1240/1345] lr: 1.0000e-02 eta: 9:26:52 time: 0.1893 data_time: 0.0056 memory: 8327 grad_norm: 7.0433 loss: 3.6026 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1477 loss_aux: 1.4550 2023/02/17 13:37:03 - mmengine - INFO - Epoch(train) [20][1260/1345] lr: 1.0000e-02 eta: 9:26:47 time: 0.1893 data_time: 0.0054 memory: 8327 grad_norm: 7.0410 loss: 3.9690 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4647 loss_aux: 1.5043 2023/02/17 13:37:06 - mmengine - INFO - Epoch(train) [20][1280/1345] lr: 1.0000e-02 eta: 9:26:43 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 6.9505 loss: 3.8789 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3672 loss_aux: 1.5117 2023/02/17 13:37:10 - mmengine - INFO - Epoch(train) [20][1300/1345] lr: 1.0000e-02 eta: 9:26:38 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 7.0673 loss: 4.1146 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5187 loss_aux: 1.5959 2023/02/17 13:37:14 - mmengine - INFO - Epoch(train) [20][1320/1345] lr: 1.0000e-02 eta: 9:26:33 time: 0.1899 data_time: 0.0069 memory: 8327 grad_norm: 7.0558 loss: 3.9533 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4113 loss_aux: 1.5419 2023/02/17 13:37:18 - mmengine - INFO - Epoch(train) [20][1340/1345] lr: 1.0000e-02 eta: 9:26:29 time: 0.1894 data_time: 0.0070 memory: 8327 grad_norm: 7.0672 loss: 3.6398 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2047 loss_aux: 1.4351 2023/02/17 13:37:19 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:37:19 - mmengine - INFO - Epoch(train) [20][1345/1345] lr: 1.0000e-02 eta: 9:26:27 time: 0.1831 data_time: 0.0069 memory: 8327 grad_norm: 7.0728 loss: 4.1260 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.5451 loss_aux: 1.5809 2023/02/17 13:37:19 - mmengine - INFO - Saving checkpoint at 20 epochs 2023/02/17 13:37:22 - mmengine - INFO - Epoch(val) [20][ 20/181] eta: 0:00:09 time: 0.0570 data_time: 0.0076 memory: 1994 2023/02/17 13:37:23 - mmengine - INFO - Epoch(val) [20][ 40/181] eta: 0:00:07 time: 0.0523 data_time: 0.0046 memory: 1994 2023/02/17 13:37:24 - mmengine - INFO - Epoch(val) [20][ 60/181] eta: 0:00:06 time: 0.0523 data_time: 0.0046 memory: 1994 2023/02/17 13:37:25 - mmengine - INFO - Epoch(val) [20][ 80/181] eta: 0:00:05 time: 0.0522 data_time: 0.0046 memory: 1994 2023/02/17 13:37:26 - mmengine - INFO - Epoch(val) [20][100/181] eta: 0:00:04 time: 0.0525 data_time: 0.0046 memory: 1994 2023/02/17 13:37:27 - mmengine - INFO - Epoch(val) [20][120/181] eta: 0:00:03 time: 0.0523 data_time: 0.0045 memory: 1994 2023/02/17 13:37:28 - mmengine - INFO - Epoch(val) [20][140/181] eta: 0:00:02 time: 0.0524 data_time: 0.0046 memory: 1994 2023/02/17 13:37:29 - mmengine - INFO - Epoch(val) [20][160/181] eta: 0:00:01 time: 0.0518 data_time: 0.0043 memory: 1994 2023/02/17 13:37:30 - mmengine - INFO - Epoch(val) [20][180/181] eta: 0:00:00 time: 0.0516 data_time: 0.0043 memory: 1994 2023/02/17 13:37:31 - mmengine - INFO - Epoch(val) [20][181/181] acc/top1: 0.3542 acc/top5: 0.6461 acc/mean1: 0.3251 2023/02/17 13:37:31 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/lilin/Repos/mmact_dev/mmaction2/work_dirs/fix_flip/tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb/best_acc/top1_epoch_15.pth is removed 2023/02/17 13:37:33 - mmengine - INFO - The best checkpoint with 0.3542 acc/top1 at 20 epoch is saved to best_acc/top1_epoch_20.pth. 2023/02/17 13:37:38 - mmengine - INFO - Epoch(train) [21][ 20/1345] lr: 1.0000e-02 eta: 9:26:25 time: 0.2127 data_time: 0.0240 memory: 8327 grad_norm: 6.8435 loss: 3.2456 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9292 loss_aux: 1.3164 2023/02/17 13:37:41 - mmengine - INFO - Epoch(train) [21][ 40/1345] lr: 1.0000e-02 eta: 9:26:21 time: 0.1912 data_time: 0.0053 memory: 8327 grad_norm: 7.0371 loss: 3.6278 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2080 loss_aux: 1.4198 2023/02/17 13:37:45 - mmengine - INFO - Epoch(train) [21][ 60/1345] lr: 1.0000e-02 eta: 9:26:17 time: 0.1907 data_time: 0.0057 memory: 8327 grad_norm: 6.9689 loss: 3.9277 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.4472 loss_aux: 1.4805 2023/02/17 13:37:49 - mmengine - INFO - Epoch(train) [21][ 80/1345] lr: 1.0000e-02 eta: 9:26:12 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 6.9585 loss: 3.9209 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4304 loss_aux: 1.4905 2023/02/17 13:37:53 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:37:53 - mmengine - INFO - Epoch(train) [21][ 100/1345] lr: 1.0000e-02 eta: 9:26:08 time: 0.1887 data_time: 0.0055 memory: 8327 grad_norm: 7.0367 loss: 3.7467 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3039 loss_aux: 1.4429 2023/02/17 13:37:57 - mmengine - INFO - Epoch(train) [21][ 120/1345] lr: 1.0000e-02 eta: 9:26:03 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.1241 loss: 4.0838 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4764 loss_aux: 1.6073 2023/02/17 13:38:00 - mmengine - INFO - Epoch(train) [21][ 140/1345] lr: 1.0000e-02 eta: 9:25:58 time: 0.1892 data_time: 0.0063 memory: 8327 grad_norm: 7.0787 loss: 3.6763 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2260 loss_aux: 1.4503 2023/02/17 13:38:04 - mmengine - INFO - Epoch(train) [21][ 160/1345] lr: 1.0000e-02 eta: 9:25:54 time: 0.1893 data_time: 0.0056 memory: 8327 grad_norm: 7.0571 loss: 3.5832 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1505 loss_aux: 1.4327 2023/02/17 13:38:08 - mmengine - INFO - Epoch(train) [21][ 180/1345] lr: 1.0000e-02 eta: 9:25:49 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.0947 loss: 3.4198 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0152 loss_aux: 1.4046 2023/02/17 13:38:12 - mmengine - INFO - Epoch(train) [21][ 200/1345] lr: 1.0000e-02 eta: 9:25:45 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 6.8257 loss: 3.7103 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3204 loss_aux: 1.3898 2023/02/17 13:38:16 - mmengine - INFO - Epoch(train) [21][ 220/1345] lr: 1.0000e-02 eta: 9:25:40 time: 0.1888 data_time: 0.0059 memory: 8327 grad_norm: 6.8698 loss: 3.6978 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2199 loss_aux: 1.4779 2023/02/17 13:38:19 - mmengine - INFO - Epoch(train) [21][ 240/1345] lr: 1.0000e-02 eta: 9:25:35 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.2922 loss: 4.0318 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4897 loss_aux: 1.5421 2023/02/17 13:38:23 - mmengine - INFO - Epoch(train) [21][ 260/1345] lr: 1.0000e-02 eta: 9:25:31 time: 0.1890 data_time: 0.0054 memory: 8327 grad_norm: 7.1644 loss: 4.0232 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5114 loss_aux: 1.5118 2023/02/17 13:38:27 - mmengine - INFO - Epoch(train) [21][ 280/1345] lr: 1.0000e-02 eta: 9:25:26 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 7.1694 loss: 4.0023 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4384 loss_aux: 1.5639 2023/02/17 13:38:31 - mmengine - INFO - Epoch(train) [21][ 300/1345] lr: 1.0000e-02 eta: 9:25:22 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 7.0398 loss: 4.0009 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.4849 loss_aux: 1.5160 2023/02/17 13:38:34 - mmengine - INFO - Epoch(train) [21][ 320/1345] lr: 1.0000e-02 eta: 9:25:17 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 7.1431 loss: 4.1620 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5833 loss_aux: 1.5787 2023/02/17 13:38:38 - mmengine - INFO - Epoch(train) [21][ 340/1345] lr: 1.0000e-02 eta: 9:25:12 time: 0.1884 data_time: 0.0058 memory: 8327 grad_norm: 7.0509 loss: 3.9042 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4353 loss_aux: 1.4689 2023/02/17 13:38:42 - mmengine - INFO - Epoch(train) [21][ 360/1345] lr: 1.0000e-02 eta: 9:25:08 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.1130 loss: 4.0240 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4596 loss_aux: 1.5644 2023/02/17 13:38:46 - mmengine - INFO - Epoch(train) [21][ 380/1345] lr: 1.0000e-02 eta: 9:25:03 time: 0.1888 data_time: 0.0055 memory: 8327 grad_norm: 7.1270 loss: 4.2531 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6296 loss_aux: 1.6236 2023/02/17 13:38:50 - mmengine - INFO - Epoch(train) [21][ 400/1345] lr: 1.0000e-02 eta: 9:24:59 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 6.9541 loss: 4.2681 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6659 loss_aux: 1.6023 2023/02/17 13:38:53 - mmengine - INFO - Epoch(train) [21][ 420/1345] lr: 1.0000e-02 eta: 9:24:54 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.1235 loss: 3.9751 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4709 loss_aux: 1.5042 2023/02/17 13:38:57 - mmengine - INFO - Epoch(train) [21][ 440/1345] lr: 1.0000e-02 eta: 9:24:50 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.0684 loss: 3.9040 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4111 loss_aux: 1.4929 2023/02/17 13:39:01 - mmengine - INFO - Epoch(train) [21][ 460/1345] lr: 1.0000e-02 eta: 9:24:48 time: 0.2089 data_time: 0.0257 memory: 8327 grad_norm: 7.0054 loss: 3.8797 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3699 loss_aux: 1.5098 2023/02/17 13:39:05 - mmengine - INFO - Epoch(train) [21][ 480/1345] lr: 1.0000e-02 eta: 9:24:43 time: 0.1893 data_time: 0.0056 memory: 8327 grad_norm: 7.2668 loss: 3.6567 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1956 loss_aux: 1.4611 2023/02/17 13:39:09 - mmengine - INFO - Epoch(train) [21][ 500/1345] lr: 1.0000e-02 eta: 9:24:38 time: 0.1887 data_time: 0.0055 memory: 8327 grad_norm: 6.9545 loss: 3.9569 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4537 loss_aux: 1.5032 2023/02/17 13:39:13 - mmengine - INFO - Epoch(train) [21][ 520/1345] lr: 1.0000e-02 eta: 9:24:34 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.9761 loss: 4.0861 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5436 loss_aux: 1.5425 2023/02/17 13:39:16 - mmengine - INFO - Epoch(train) [21][ 540/1345] lr: 1.0000e-02 eta: 9:24:29 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.0167 loss: 3.5321 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1331 loss_aux: 1.3990 2023/02/17 13:39:20 - mmengine - INFO - Epoch(train) [21][ 560/1345] lr: 1.0000e-02 eta: 9:24:25 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.2916 loss: 3.9731 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4643 loss_aux: 1.5087 2023/02/17 13:39:24 - mmengine - INFO - Epoch(train) [21][ 580/1345] lr: 1.0000e-02 eta: 9:24:20 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 6.9891 loss: 3.6982 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2610 loss_aux: 1.4371 2023/02/17 13:39:28 - mmengine - INFO - Epoch(train) [21][ 600/1345] lr: 1.0000e-02 eta: 9:24:16 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 6.8377 loss: 3.7715 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2931 loss_aux: 1.4784 2023/02/17 13:39:32 - mmengine - INFO - Epoch(train) [21][ 620/1345] lr: 1.0000e-02 eta: 9:24:11 time: 0.1891 data_time: 0.0054 memory: 8327 grad_norm: 7.1462 loss: 3.7957 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2924 loss_aux: 1.5033 2023/02/17 13:39:35 - mmengine - INFO - Epoch(train) [21][ 640/1345] lr: 1.0000e-02 eta: 9:24:07 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 6.9481 loss: 3.9122 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3876 loss_aux: 1.5247 2023/02/17 13:39:39 - mmengine - INFO - Epoch(train) [21][ 660/1345] lr: 1.0000e-02 eta: 9:24:02 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 6.9173 loss: 3.6767 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2188 loss_aux: 1.4578 2023/02/17 13:39:43 - mmengine - INFO - Epoch(train) [21][ 680/1345] lr: 1.0000e-02 eta: 9:23:57 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.2258 loss: 4.1064 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5498 loss_aux: 1.5566 2023/02/17 13:39:47 - mmengine - INFO - Epoch(train) [21][ 700/1345] lr: 1.0000e-02 eta: 9:23:53 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.2928 loss: 3.8837 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4277 loss_aux: 1.4560 2023/02/17 13:39:50 - mmengine - INFO - Epoch(train) [21][ 720/1345] lr: 1.0000e-02 eta: 9:23:48 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.1354 loss: 3.9701 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4667 loss_aux: 1.5034 2023/02/17 13:39:54 - mmengine - INFO - Epoch(train) [21][ 740/1345] lr: 1.0000e-02 eta: 9:23:44 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 7.0466 loss: 4.2833 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6695 loss_aux: 1.6138 2023/02/17 13:39:58 - mmengine - INFO - Epoch(train) [21][ 760/1345] lr: 1.0000e-02 eta: 9:23:39 time: 0.1885 data_time: 0.0057 memory: 8327 grad_norm: 7.1224 loss: 3.7627 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2688 loss_aux: 1.4939 2023/02/17 13:40:02 - mmengine - INFO - Epoch(train) [21][ 780/1345] lr: 1.0000e-02 eta: 9:23:35 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.2905 loss: 3.8826 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3945 loss_aux: 1.4880 2023/02/17 13:40:06 - mmengine - INFO - Epoch(train) [21][ 800/1345] lr: 1.0000e-02 eta: 9:23:30 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.0857 loss: 4.2807 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6582 loss_aux: 1.6224 2023/02/17 13:40:09 - mmengine - INFO - Epoch(train) [21][ 820/1345] lr: 1.0000e-02 eta: 9:23:25 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.1430 loss: 4.0646 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5294 loss_aux: 1.5353 2023/02/17 13:40:13 - mmengine - INFO - Epoch(train) [21][ 840/1345] lr: 1.0000e-02 eta: 9:23:21 time: 0.1897 data_time: 0.0064 memory: 8327 grad_norm: 6.9337 loss: 3.8529 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3801 loss_aux: 1.4728 2023/02/17 13:40:17 - mmengine - INFO - Epoch(train) [21][ 860/1345] lr: 1.0000e-02 eta: 9:23:17 time: 0.1899 data_time: 0.0057 memory: 8327 grad_norm: 7.0089 loss: 3.8859 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4441 loss_aux: 1.4419 2023/02/17 13:40:21 - mmengine - INFO - Epoch(train) [21][ 880/1345] lr: 1.0000e-02 eta: 9:23:12 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.1064 loss: 3.9717 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4383 loss_aux: 1.5334 2023/02/17 13:40:25 - mmengine - INFO - Epoch(train) [21][ 900/1345] lr: 1.0000e-02 eta: 9:23:12 time: 0.2291 data_time: 0.0462 memory: 8327 grad_norm: 7.1369 loss: 4.1190 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5294 loss_aux: 1.5896 2023/02/17 13:40:29 - mmengine - INFO - Epoch(train) [21][ 920/1345] lr: 1.0000e-02 eta: 9:23:08 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 7.1544 loss: 3.8351 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3359 loss_aux: 1.4991 2023/02/17 13:40:33 - mmengine - INFO - Epoch(train) [21][ 940/1345] lr: 1.0000e-02 eta: 9:23:03 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 6.9441 loss: 3.7922 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3109 loss_aux: 1.4812 2023/02/17 13:40:37 - mmengine - INFO - Epoch(train) [21][ 960/1345] lr: 1.0000e-02 eta: 9:22:59 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.0896 loss: 3.9346 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4443 loss_aux: 1.4903 2023/02/17 13:40:40 - mmengine - INFO - Epoch(train) [21][ 980/1345] lr: 1.0000e-02 eta: 9:22:54 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.1038 loss: 4.0475 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4764 loss_aux: 1.5712 2023/02/17 13:40:44 - mmengine - INFO - Epoch(train) [21][1000/1345] lr: 1.0000e-02 eta: 9:22:50 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.3238 loss: 3.8729 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3631 loss_aux: 1.5098 2023/02/17 13:40:48 - mmengine - INFO - Epoch(train) [21][1020/1345] lr: 1.0000e-02 eta: 9:22:45 time: 0.1891 data_time: 0.0055 memory: 8327 grad_norm: 7.1559 loss: 4.1790 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6507 loss_aux: 1.5283 2023/02/17 13:40:52 - mmengine - INFO - Epoch(train) [21][1040/1345] lr: 1.0000e-02 eta: 9:22:41 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.0158 loss: 3.9769 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4240 loss_aux: 1.5529 2023/02/17 13:40:56 - mmengine - INFO - Epoch(train) [21][1060/1345] lr: 1.0000e-02 eta: 9:22:36 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.0561 loss: 4.0328 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4896 loss_aux: 1.5432 2023/02/17 13:40:59 - mmengine - INFO - Epoch(train) [21][1080/1345] lr: 1.0000e-02 eta: 9:22:32 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.0161 loss: 3.7098 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2729 loss_aux: 1.4369 2023/02/17 13:41:03 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:41:03 - mmengine - INFO - Epoch(train) [21][1100/1345] lr: 1.0000e-02 eta: 9:22:27 time: 0.1905 data_time: 0.0067 memory: 8327 grad_norm: 7.2249 loss: 3.8274 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2833 loss_aux: 1.5441 2023/02/17 13:41:07 - mmengine - INFO - Epoch(train) [21][1120/1345] lr: 1.0000e-02 eta: 9:22:23 time: 0.1899 data_time: 0.0056 memory: 8327 grad_norm: 7.1806 loss: 4.1817 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6217 loss_aux: 1.5600 2023/02/17 13:41:11 - mmengine - INFO - Epoch(train) [21][1140/1345] lr: 1.0000e-02 eta: 9:22:18 time: 0.1887 data_time: 0.0055 memory: 8327 grad_norm: 7.0475 loss: 3.7586 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3169 loss_aux: 1.4417 2023/02/17 13:41:14 - mmengine - INFO - Epoch(train) [21][1160/1345] lr: 1.0000e-02 eta: 9:22:14 time: 0.1884 data_time: 0.0055 memory: 8327 grad_norm: 7.0382 loss: 3.7566 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3351 loss_aux: 1.4215 2023/02/17 13:41:18 - mmengine - INFO - Epoch(train) [21][1180/1345] lr: 1.0000e-02 eta: 9:22:09 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.2926 loss: 4.1804 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5798 loss_aux: 1.6006 2023/02/17 13:41:22 - mmengine - INFO - Epoch(train) [21][1200/1345] lr: 1.0000e-02 eta: 9:22:05 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.0114 loss: 3.3385 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.0143 loss_aux: 1.3242 2023/02/17 13:41:26 - mmengine - INFO - Epoch(train) [21][1220/1345] lr: 1.0000e-02 eta: 9:22:00 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 7.1897 loss: 4.1861 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6109 loss_aux: 1.5752 2023/02/17 13:41:30 - mmengine - INFO - Epoch(train) [21][1240/1345] lr: 1.0000e-02 eta: 9:21:56 time: 0.1895 data_time: 0.0056 memory: 8327 grad_norm: 7.1102 loss: 3.8145 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3405 loss_aux: 1.4739 2023/02/17 13:41:33 - mmengine - INFO - Epoch(train) [21][1260/1345] lr: 1.0000e-02 eta: 9:21:51 time: 0.1888 data_time: 0.0054 memory: 8327 grad_norm: 6.9448 loss: 4.0064 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4683 loss_aux: 1.5381 2023/02/17 13:41:37 - mmengine - INFO - Epoch(train) [21][1280/1345] lr: 1.0000e-02 eta: 9:21:47 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 7.2251 loss: 4.0256 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4480 loss_aux: 1.5776 2023/02/17 13:41:41 - mmengine - INFO - Epoch(train) [21][1300/1345] lr: 1.0000e-02 eta: 9:21:42 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 7.0184 loss: 3.8239 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3321 loss_aux: 1.4919 2023/02/17 13:41:45 - mmengine - INFO - Epoch(train) [21][1320/1345] lr: 1.0000e-02 eta: 9:21:37 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 7.2413 loss: 4.6418 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9159 loss_aux: 1.7259 2023/02/17 13:41:49 - mmengine - INFO - Epoch(train) [21][1340/1345] lr: 1.0000e-02 eta: 9:21:33 time: 0.1908 data_time: 0.0060 memory: 8327 grad_norm: 7.3659 loss: 3.7366 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3224 loss_aux: 1.4143 2023/02/17 13:41:49 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:41:49 - mmengine - INFO - Epoch(train) [21][1345/1345] lr: 1.0000e-02 eta: 9:21:31 time: 0.1828 data_time: 0.0059 memory: 8327 grad_norm: 7.2333 loss: 3.9215 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.4666 loss_aux: 1.4550 2023/02/17 13:41:49 - mmengine - INFO - Saving checkpoint at 21 epochs 2023/02/17 13:41:56 - mmengine - INFO - Epoch(train) [22][ 20/1345] lr: 1.0000e-02 eta: 9:21:30 time: 0.2138 data_time: 0.0181 memory: 8327 grad_norm: 7.2748 loss: 4.2570 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6125 loss_aux: 1.6445 2023/02/17 13:42:00 - mmengine - INFO - Epoch(train) [22][ 40/1345] lr: 1.0000e-02 eta: 9:21:26 time: 0.1915 data_time: 0.0037 memory: 8327 grad_norm: 7.2234 loss: 3.9737 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4109 loss_aux: 1.5629 2023/02/17 13:42:04 - mmengine - INFO - Epoch(train) [22][ 60/1345] lr: 1.0000e-02 eta: 9:21:21 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 7.0645 loss: 3.9304 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3834 loss_aux: 1.5471 2023/02/17 13:42:08 - mmengine - INFO - Epoch(train) [22][ 80/1345] lr: 1.0000e-02 eta: 9:21:16 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 6.8788 loss: 4.0474 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5604 loss_aux: 1.4870 2023/02/17 13:42:12 - mmengine - INFO - Epoch(train) [22][ 100/1345] lr: 1.0000e-02 eta: 9:21:12 time: 0.1898 data_time: 0.0055 memory: 8327 grad_norm: 7.0750 loss: 3.9151 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4204 loss_aux: 1.4948 2023/02/17 13:42:15 - mmengine - INFO - Epoch(train) [22][ 120/1345] lr: 1.0000e-02 eta: 9:21:08 time: 0.1901 data_time: 0.0068 memory: 8327 grad_norm: 7.3357 loss: 3.8486 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2959 loss_aux: 1.5527 2023/02/17 13:42:19 - mmengine - INFO - Epoch(train) [22][ 140/1345] lr: 1.0000e-02 eta: 9:21:03 time: 0.1907 data_time: 0.0054 memory: 8327 grad_norm: 7.1726 loss: 3.7195 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2780 loss_aux: 1.4415 2023/02/17 13:42:23 - mmengine - INFO - Epoch(train) [22][ 160/1345] lr: 1.0000e-02 eta: 9:20:59 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 7.1942 loss: 3.5015 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1165 loss_aux: 1.3849 2023/02/17 13:42:27 - mmengine - INFO - Epoch(train) [22][ 180/1345] lr: 1.0000e-02 eta: 9:20:54 time: 0.1887 data_time: 0.0055 memory: 8327 grad_norm: 7.2171 loss: 3.9874 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4214 loss_aux: 1.5660 2023/02/17 13:42:31 - mmengine - INFO - Epoch(train) [22][ 200/1345] lr: 1.0000e-02 eta: 9:20:50 time: 0.1885 data_time: 0.0054 memory: 8327 grad_norm: 7.0205 loss: 3.9312 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3973 loss_aux: 1.5339 2023/02/17 13:42:34 - mmengine - INFO - Epoch(train) [22][ 220/1345] lr: 1.0000e-02 eta: 9:20:45 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 6.9941 loss: 3.6117 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1643 loss_aux: 1.4474 2023/02/17 13:42:38 - mmengine - INFO - Epoch(train) [22][ 240/1345] lr: 1.0000e-02 eta: 9:20:42 time: 0.1985 data_time: 0.0156 memory: 8327 grad_norm: 7.1329 loss: 4.1199 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5747 loss_aux: 1.5451 2023/02/17 13:42:42 - mmengine - INFO - Epoch(train) [22][ 260/1345] lr: 1.0000e-02 eta: 9:20:37 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.0609 loss: 3.6767 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2707 loss_aux: 1.4061 2023/02/17 13:42:46 - mmengine - INFO - Epoch(train) [22][ 280/1345] lr: 1.0000e-02 eta: 9:20:33 time: 0.1886 data_time: 0.0055 memory: 8327 grad_norm: 7.1202 loss: 3.7703 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3098 loss_aux: 1.4605 2023/02/17 13:42:50 - mmengine - INFO - Epoch(train) [22][ 300/1345] lr: 1.0000e-02 eta: 9:20:28 time: 0.1903 data_time: 0.0071 memory: 8327 grad_norm: 7.1124 loss: 4.0025 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4713 loss_aux: 1.5312 2023/02/17 13:42:53 - mmengine - INFO - Epoch(train) [22][ 320/1345] lr: 1.0000e-02 eta: 9:20:24 time: 0.1920 data_time: 0.0066 memory: 8327 grad_norm: 6.9111 loss: 3.7906 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3325 loss_aux: 1.4581 2023/02/17 13:42:57 - mmengine - INFO - Epoch(train) [22][ 340/1345] lr: 1.0000e-02 eta: 9:20:20 time: 0.1908 data_time: 0.0062 memory: 8327 grad_norm: 7.1644 loss: 4.2522 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6304 loss_aux: 1.6218 2023/02/17 13:43:01 - mmengine - INFO - Epoch(train) [22][ 360/1345] lr: 1.0000e-02 eta: 9:20:15 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.0801 loss: 3.9925 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.4470 loss_aux: 1.5454 2023/02/17 13:43:05 - mmengine - INFO - Epoch(train) [22][ 380/1345] lr: 1.0000e-02 eta: 9:20:11 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 7.0382 loss: 4.0615 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4813 loss_aux: 1.5802 2023/02/17 13:43:09 - mmengine - INFO - Epoch(train) [22][ 400/1345] lr: 1.0000e-02 eta: 9:20:06 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 6.9607 loss: 3.8148 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3275 loss_aux: 1.4874 2023/02/17 13:43:12 - mmengine - INFO - Epoch(train) [22][ 420/1345] lr: 1.0000e-02 eta: 9:20:02 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 7.0878 loss: 3.6302 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1843 loss_aux: 1.4459 2023/02/17 13:43:16 - mmengine - INFO - Epoch(train) [22][ 440/1345] lr: 1.0000e-02 eta: 9:19:58 time: 0.1894 data_time: 0.0062 memory: 8327 grad_norm: 7.4133 loss: 3.9204 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.3891 loss_aux: 1.5313 2023/02/17 13:43:20 - mmengine - INFO - Epoch(train) [22][ 460/1345] lr: 1.0000e-02 eta: 9:19:53 time: 0.1885 data_time: 0.0056 memory: 8327 grad_norm: 6.9878 loss: 3.5370 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1277 loss_aux: 1.4093 2023/02/17 13:43:24 - mmengine - INFO - Epoch(train) [22][ 480/1345] lr: 1.0000e-02 eta: 9:19:48 time: 0.1887 data_time: 0.0055 memory: 8327 grad_norm: 6.8813 loss: 3.6296 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2031 loss_aux: 1.4265 2023/02/17 13:43:28 - mmengine - INFO - Epoch(train) [22][ 500/1345] lr: 1.0000e-02 eta: 9:19:44 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 7.1044 loss: 3.5506 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1463 loss_aux: 1.4043 2023/02/17 13:43:31 - mmengine - INFO - Epoch(train) [22][ 520/1345] lr: 1.0000e-02 eta: 9:19:40 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 7.1715 loss: 3.7546 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2630 loss_aux: 1.4916 2023/02/17 13:43:35 - mmengine - INFO - Epoch(train) [22][ 540/1345] lr: 1.0000e-02 eta: 9:19:35 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.0126 loss: 3.3119 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9777 loss_aux: 1.3342 2023/02/17 13:43:39 - mmengine - INFO - Epoch(train) [22][ 560/1345] lr: 1.0000e-02 eta: 9:19:31 time: 0.1903 data_time: 0.0054 memory: 8327 grad_norm: 7.1400 loss: 3.9388 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4351 loss_aux: 1.5038 2023/02/17 13:43:43 - mmengine - INFO - Epoch(train) [22][ 580/1345] lr: 1.0000e-02 eta: 9:19:26 time: 0.1903 data_time: 0.0056 memory: 8327 grad_norm: 7.3810 loss: 3.8452 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3604 loss_aux: 1.4847 2023/02/17 13:43:47 - mmengine - INFO - Epoch(train) [22][ 600/1345] lr: 1.0000e-02 eta: 9:19:22 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.2860 loss: 4.0758 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5242 loss_aux: 1.5516 2023/02/17 13:43:50 - mmengine - INFO - Epoch(train) [22][ 620/1345] lr: 1.0000e-02 eta: 9:19:17 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 7.1058 loss: 3.9330 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3966 loss_aux: 1.5364 2023/02/17 13:43:54 - mmengine - INFO - Epoch(train) [22][ 640/1345] lr: 1.0000e-02 eta: 9:19:13 time: 0.1886 data_time: 0.0055 memory: 8327 grad_norm: 7.0118 loss: 3.7091 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2441 loss_aux: 1.4650 2023/02/17 13:43:58 - mmengine - INFO - Epoch(train) [22][ 660/1345] lr: 1.0000e-02 eta: 9:19:08 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 6.9509 loss: 3.9998 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4633 loss_aux: 1.5365 2023/02/17 13:44:02 - mmengine - INFO - Epoch(train) [22][ 680/1345] lr: 1.0000e-02 eta: 9:19:04 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 6.9153 loss: 3.7951 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3287 loss_aux: 1.4664 2023/02/17 13:44:05 - mmengine - INFO - Epoch(train) [22][ 700/1345] lr: 1.0000e-02 eta: 9:19:00 time: 0.1906 data_time: 0.0072 memory: 8327 grad_norm: 7.2439 loss: 4.0398 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5126 loss_aux: 1.5272 2023/02/17 13:44:09 - mmengine - INFO - Epoch(train) [22][ 720/1345] lr: 1.0000e-02 eta: 9:18:55 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.2032 loss: 3.6816 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.2021 loss_aux: 1.4795 2023/02/17 13:44:13 - mmengine - INFO - Epoch(train) [22][ 740/1345] lr: 1.0000e-02 eta: 9:18:51 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 6.9386 loss: 3.8868 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4020 loss_aux: 1.4848 2023/02/17 13:44:16 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:44:17 - mmengine - INFO - Epoch(train) [22][ 760/1345] lr: 1.0000e-02 eta: 9:18:46 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.2281 loss: 3.9365 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3704 loss_aux: 1.5661 2023/02/17 13:44:21 - mmengine - INFO - Epoch(train) [22][ 780/1345] lr: 1.0000e-02 eta: 9:18:42 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.0035 loss: 3.9758 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4504 loss_aux: 1.5254 2023/02/17 13:44:24 - mmengine - INFO - Epoch(train) [22][ 800/1345] lr: 1.0000e-02 eta: 9:18:37 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.2585 loss: 3.9400 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4678 loss_aux: 1.4722 2023/02/17 13:44:28 - mmengine - INFO - Epoch(train) [22][ 820/1345] lr: 1.0000e-02 eta: 9:18:33 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.0647 loss: 4.0318 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4781 loss_aux: 1.5537 2023/02/17 13:44:32 - mmengine - INFO - Epoch(train) [22][ 840/1345] lr: 1.0000e-02 eta: 9:18:28 time: 0.1888 data_time: 0.0053 memory: 8327 grad_norm: 7.0912 loss: 4.0768 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5319 loss_aux: 1.5449 2023/02/17 13:44:36 - mmengine - INFO - Epoch(train) [22][ 860/1345] lr: 1.0000e-02 eta: 9:18:24 time: 0.1909 data_time: 0.0078 memory: 8327 grad_norm: 7.0951 loss: 4.1306 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5391 loss_aux: 1.5915 2023/02/17 13:44:40 - mmengine - INFO - Epoch(train) [22][ 880/1345] lr: 1.0000e-02 eta: 9:18:19 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.2449 loss: 3.7311 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.2987 loss_aux: 1.4325 2023/02/17 13:44:43 - mmengine - INFO - Epoch(train) [22][ 900/1345] lr: 1.0000e-02 eta: 9:18:15 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.1575 loss: 4.0329 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5106 loss_aux: 1.5222 2023/02/17 13:44:47 - mmengine - INFO - Epoch(train) [22][ 920/1345] lr: 1.0000e-02 eta: 9:18:10 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 6.9639 loss: 3.8974 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3821 loss_aux: 1.5153 2023/02/17 13:44:51 - mmengine - INFO - Epoch(train) [22][ 940/1345] lr: 1.0000e-02 eta: 9:18:06 time: 0.1901 data_time: 0.0067 memory: 8327 grad_norm: 6.9548 loss: 3.6116 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1702 loss_aux: 1.4414 2023/02/17 13:44:55 - mmengine - INFO - Epoch(train) [22][ 960/1345] lr: 1.0000e-02 eta: 9:18:02 time: 0.1893 data_time: 0.0064 memory: 8327 grad_norm: 7.0930 loss: 4.1417 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5566 loss_aux: 1.5851 2023/02/17 13:44:58 - mmengine - INFO - Epoch(train) [22][ 980/1345] lr: 1.0000e-02 eta: 9:17:57 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.0471 loss: 3.6888 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2425 loss_aux: 1.4463 2023/02/17 13:45:02 - mmengine - INFO - Epoch(train) [22][1000/1345] lr: 1.0000e-02 eta: 9:17:53 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.1107 loss: 3.4871 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0978 loss_aux: 1.3893 2023/02/17 13:45:06 - mmengine - INFO - Epoch(train) [22][1020/1345] lr: 1.0000e-02 eta: 9:17:48 time: 0.1902 data_time: 0.0057 memory: 8327 grad_norm: 7.0278 loss: 3.8094 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3341 loss_aux: 1.4753 2023/02/17 13:45:10 - mmengine - INFO - Epoch(train) [22][1040/1345] lr: 1.0000e-02 eta: 9:17:44 time: 0.1896 data_time: 0.0062 memory: 8327 grad_norm: 6.9045 loss: 3.8513 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4127 loss_aux: 1.4386 2023/02/17 13:45:14 - mmengine - INFO - Epoch(train) [22][1060/1345] lr: 1.0000e-02 eta: 9:17:39 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.1488 loss: 3.8776 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4072 loss_aux: 1.4704 2023/02/17 13:45:17 - mmengine - INFO - Epoch(train) [22][1080/1345] lr: 1.0000e-02 eta: 9:17:35 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.1282 loss: 3.7705 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3423 loss_aux: 1.4282 2023/02/17 13:45:21 - mmengine - INFO - Epoch(train) [22][1100/1345] lr: 1.0000e-02 eta: 9:17:31 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 6.9430 loss: 4.1382 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5824 loss_aux: 1.5558 2023/02/17 13:45:25 - mmengine - INFO - Epoch(train) [22][1120/1345] lr: 1.0000e-02 eta: 9:17:26 time: 0.1906 data_time: 0.0056 memory: 8327 grad_norm: 7.0671 loss: 3.8368 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3325 loss_aux: 1.5043 2023/02/17 13:45:29 - mmengine - INFO - Epoch(train) [22][1140/1345] lr: 1.0000e-02 eta: 9:17:22 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.1565 loss: 4.1623 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5483 loss_aux: 1.6140 2023/02/17 13:45:33 - mmengine - INFO - Epoch(train) [22][1160/1345] lr: 1.0000e-02 eta: 9:17:17 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 7.0304 loss: 3.9006 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4065 loss_aux: 1.4942 2023/02/17 13:45:36 - mmengine - INFO - Epoch(train) [22][1180/1345] lr: 1.0000e-02 eta: 9:17:13 time: 0.1887 data_time: 0.0055 memory: 8327 grad_norm: 7.2867 loss: 3.5469 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1838 loss_aux: 1.3631 2023/02/17 13:45:40 - mmengine - INFO - Epoch(train) [22][1200/1345] lr: 1.0000e-02 eta: 9:17:08 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.2289 loss: 3.6678 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2171 loss_aux: 1.4507 2023/02/17 13:45:44 - mmengine - INFO - Epoch(train) [22][1220/1345] lr: 1.0000e-02 eta: 9:17:04 time: 0.1891 data_time: 0.0055 memory: 8327 grad_norm: 7.2151 loss: 4.0200 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5033 loss_aux: 1.5166 2023/02/17 13:45:48 - mmengine - INFO - Epoch(train) [22][1240/1345] lr: 1.0000e-02 eta: 9:16:59 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.1191 loss: 3.9851 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4304 loss_aux: 1.5548 2023/02/17 13:45:52 - mmengine - INFO - Epoch(train) [22][1260/1345] lr: 1.0000e-02 eta: 9:16:55 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 6.8296 loss: 4.0466 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5054 loss_aux: 1.5412 2023/02/17 13:45:55 - mmengine - INFO - Epoch(train) [22][1280/1345] lr: 1.0000e-02 eta: 9:16:51 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.0406 loss: 4.1115 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5556 loss_aux: 1.5559 2023/02/17 13:45:59 - mmengine - INFO - Epoch(train) [22][1300/1345] lr: 1.0000e-02 eta: 9:16:46 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 6.9704 loss: 3.7825 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3137 loss_aux: 1.4688 2023/02/17 13:46:03 - mmengine - INFO - Epoch(train) [22][1320/1345] lr: 1.0000e-02 eta: 9:16:42 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.4153 loss: 3.8452 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3389 loss_aux: 1.5063 2023/02/17 13:46:07 - mmengine - INFO - Epoch(train) [22][1340/1345] lr: 1.0000e-02 eta: 9:16:37 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.3365 loss: 4.0922 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5325 loss_aux: 1.5597 2023/02/17 13:46:07 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:46:07 - mmengine - INFO - Epoch(train) [22][1345/1345] lr: 1.0000e-02 eta: 9:16:35 time: 0.1828 data_time: 0.0056 memory: 8327 grad_norm: 7.2963 loss: 4.3977 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.7026 loss_aux: 1.6951 2023/02/17 13:46:07 - mmengine - INFO - Saving checkpoint at 22 epochs 2023/02/17 13:46:14 - mmengine - INFO - Epoch(train) [23][ 20/1345] lr: 1.0000e-02 eta: 9:16:33 time: 0.2079 data_time: 0.0177 memory: 8327 grad_norm: 7.1264 loss: 3.5581 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1682 loss_aux: 1.3898 2023/02/17 13:46:18 - mmengine - INFO - Epoch(train) [23][ 40/1345] lr: 1.0000e-02 eta: 9:16:29 time: 0.1889 data_time: 0.0040 memory: 8327 grad_norm: 7.1528 loss: 3.7940 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.3228 loss_aux: 1.4712 2023/02/17 13:46:22 - mmengine - INFO - Epoch(train) [23][ 60/1345] lr: 1.0000e-02 eta: 9:16:24 time: 0.1896 data_time: 0.0056 memory: 8327 grad_norm: 7.0500 loss: 3.6842 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2454 loss_aux: 1.4388 2023/02/17 13:46:26 - mmengine - INFO - Epoch(train) [23][ 80/1345] lr: 1.0000e-02 eta: 9:16:20 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 6.9644 loss: 4.1080 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5494 loss_aux: 1.5586 2023/02/17 13:46:29 - mmengine - INFO - Epoch(train) [23][ 100/1345] lr: 1.0000e-02 eta: 9:16:15 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 6.8957 loss: 3.3725 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0689 loss_aux: 1.3035 2023/02/17 13:46:33 - mmengine - INFO - Epoch(train) [23][ 120/1345] lr: 1.0000e-02 eta: 9:16:11 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.1020 loss: 3.8967 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4009 loss_aux: 1.4958 2023/02/17 13:46:37 - mmengine - INFO - Epoch(train) [23][ 140/1345] lr: 1.0000e-02 eta: 9:16:06 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 7.2076 loss: 3.8814 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4236 loss_aux: 1.4578 2023/02/17 13:46:41 - mmengine - INFO - Epoch(train) [23][ 160/1345] lr: 1.0000e-02 eta: 9:16:02 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.2473 loss: 4.2112 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6491 loss_aux: 1.5621 2023/02/17 13:46:44 - mmengine - INFO - Epoch(train) [23][ 180/1345] lr: 1.0000e-02 eta: 9:15:57 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 6.9424 loss: 3.8592 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3575 loss_aux: 1.5017 2023/02/17 13:46:48 - mmengine - INFO - Epoch(train) [23][ 200/1345] lr: 1.0000e-02 eta: 9:15:53 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.0540 loss: 3.3782 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0463 loss_aux: 1.3319 2023/02/17 13:46:52 - mmengine - INFO - Epoch(train) [23][ 220/1345] lr: 1.0000e-02 eta: 9:15:49 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.1273 loss: 3.5893 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1730 loss_aux: 1.4163 2023/02/17 13:46:56 - mmengine - INFO - Epoch(train) [23][ 240/1345] lr: 1.0000e-02 eta: 9:15:44 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.0205 loss: 4.0961 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5472 loss_aux: 1.5489 2023/02/17 13:47:00 - mmengine - INFO - Epoch(train) [23][ 260/1345] lr: 1.0000e-02 eta: 9:15:40 time: 0.1887 data_time: 0.0055 memory: 8327 grad_norm: 7.4285 loss: 4.0547 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4959 loss_aux: 1.5588 2023/02/17 13:47:03 - mmengine - INFO - Epoch(train) [23][ 280/1345] lr: 1.0000e-02 eta: 9:15:35 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.1294 loss: 3.9946 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4440 loss_aux: 1.5506 2023/02/17 13:47:07 - mmengine - INFO - Epoch(train) [23][ 300/1345] lr: 1.0000e-02 eta: 9:15:31 time: 0.1887 data_time: 0.0055 memory: 8327 grad_norm: 7.1209 loss: 3.9019 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3967 loss_aux: 1.5052 2023/02/17 13:47:11 - mmengine - INFO - Epoch(train) [23][ 320/1345] lr: 1.0000e-02 eta: 9:15:26 time: 0.1899 data_time: 0.0071 memory: 8327 grad_norm: 7.2953 loss: 3.9093 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4000 loss_aux: 1.5093 2023/02/17 13:47:15 - mmengine - INFO - Epoch(train) [23][ 340/1345] lr: 1.0000e-02 eta: 9:15:22 time: 0.1899 data_time: 0.0064 memory: 8327 grad_norm: 7.1418 loss: 3.8636 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4089 loss_aux: 1.4547 2023/02/17 13:47:18 - mmengine - INFO - Epoch(train) [23][ 360/1345] lr: 1.0000e-02 eta: 9:15:17 time: 0.1884 data_time: 0.0057 memory: 8327 grad_norm: 7.1018 loss: 3.9883 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4128 loss_aux: 1.5755 2023/02/17 13:47:22 - mmengine - INFO - Epoch(train) [23][ 380/1345] lr: 1.0000e-02 eta: 9:15:13 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.0508 loss: 3.9135 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4453 loss_aux: 1.4681 2023/02/17 13:47:26 - mmengine - INFO - Epoch(train) [23][ 400/1345] lr: 1.0000e-02 eta: 9:15:08 time: 0.1884 data_time: 0.0058 memory: 8327 grad_norm: 7.2286 loss: 3.9325 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4343 loss_aux: 1.4982 2023/02/17 13:47:28 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:47:30 - mmengine - INFO - Epoch(train) [23][ 420/1345] lr: 1.0000e-02 eta: 9:15:04 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 7.3071 loss: 4.0895 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5265 loss_aux: 1.5630 2023/02/17 13:47:34 - mmengine - INFO - Epoch(train) [23][ 440/1345] lr: 1.0000e-02 eta: 9:15:00 time: 0.1888 data_time: 0.0055 memory: 8327 grad_norm: 7.1336 loss: 3.8331 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3351 loss_aux: 1.4980 2023/02/17 13:47:37 - mmengine - INFO - Epoch(train) [23][ 460/1345] lr: 1.0000e-02 eta: 9:14:55 time: 0.1888 data_time: 0.0055 memory: 8327 grad_norm: 7.1431 loss: 3.7342 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2114 loss_aux: 1.5229 2023/02/17 13:47:41 - mmengine - INFO - Epoch(train) [23][ 480/1345] lr: 1.0000e-02 eta: 9:14:51 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.1297 loss: 3.8277 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3686 loss_aux: 1.4590 2023/02/17 13:47:45 - mmengine - INFO - Epoch(train) [23][ 500/1345] lr: 1.0000e-02 eta: 9:14:46 time: 0.1889 data_time: 0.0054 memory: 8327 grad_norm: 7.3547 loss: 4.0880 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5338 loss_aux: 1.5542 2023/02/17 13:47:49 - mmengine - INFO - Epoch(train) [23][ 520/1345] lr: 1.0000e-02 eta: 9:14:42 time: 0.1906 data_time: 0.0055 memory: 8327 grad_norm: 7.1079 loss: 3.3191 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9976 loss_aux: 1.3215 2023/02/17 13:47:53 - mmengine - INFO - Epoch(train) [23][ 540/1345] lr: 1.0000e-02 eta: 9:14:38 time: 0.1908 data_time: 0.0058 memory: 8327 grad_norm: 7.1455 loss: 4.1113 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5345 loss_aux: 1.5768 2023/02/17 13:47:56 - mmengine - INFO - Epoch(train) [23][ 560/1345] lr: 1.0000e-02 eta: 9:14:33 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 7.2341 loss: 4.0130 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5023 loss_aux: 1.5106 2023/02/17 13:48:00 - mmengine - INFO - Epoch(train) [23][ 580/1345] lr: 1.0000e-02 eta: 9:14:29 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.0847 loss: 3.9000 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4046 loss_aux: 1.4954 2023/02/17 13:48:04 - mmengine - INFO - Epoch(train) [23][ 600/1345] lr: 1.0000e-02 eta: 9:14:24 time: 0.1888 data_time: 0.0055 memory: 8327 grad_norm: 6.9735 loss: 3.9561 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4489 loss_aux: 1.5072 2023/02/17 13:48:08 - mmengine - INFO - Epoch(train) [23][ 620/1345] lr: 1.0000e-02 eta: 9:14:20 time: 0.1887 data_time: 0.0055 memory: 8327 grad_norm: 7.0854 loss: 3.3893 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0445 loss_aux: 1.3448 2023/02/17 13:48:11 - mmengine - INFO - Epoch(train) [23][ 640/1345] lr: 1.0000e-02 eta: 9:14:15 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 7.1036 loss: 3.5257 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1367 loss_aux: 1.3890 2023/02/17 13:48:15 - mmengine - INFO - Epoch(train) [23][ 660/1345] lr: 1.0000e-02 eta: 9:14:11 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.1561 loss: 3.7056 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2625 loss_aux: 1.4431 2023/02/17 13:48:19 - mmengine - INFO - Epoch(train) [23][ 680/1345] lr: 1.0000e-02 eta: 9:14:07 time: 0.1888 data_time: 0.0055 memory: 8327 grad_norm: 7.2101 loss: 4.1278 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5487 loss_aux: 1.5791 2023/02/17 13:48:23 - mmengine - INFO - Epoch(train) [23][ 700/1345] lr: 1.0000e-02 eta: 9:14:02 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.2305 loss: 4.0811 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4709 loss_aux: 1.6102 2023/02/17 13:48:27 - mmengine - INFO - Epoch(train) [23][ 720/1345] lr: 1.0000e-02 eta: 9:13:58 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 7.0391 loss: 3.8821 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3618 loss_aux: 1.5203 2023/02/17 13:48:30 - mmengine - INFO - Epoch(train) [23][ 740/1345] lr: 1.0000e-02 eta: 9:13:54 time: 0.1919 data_time: 0.0081 memory: 8327 grad_norm: 7.2828 loss: 3.9652 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4062 loss_aux: 1.5590 2023/02/17 13:48:34 - mmengine - INFO - Epoch(train) [23][ 760/1345] lr: 1.0000e-02 eta: 9:13:49 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 6.9357 loss: 3.9191 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4345 loss_aux: 1.4846 2023/02/17 13:48:38 - mmengine - INFO - Epoch(train) [23][ 780/1345] lr: 1.0000e-02 eta: 9:13:45 time: 0.1885 data_time: 0.0057 memory: 8327 grad_norm: 7.0014 loss: 4.1173 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5513 loss_aux: 1.5659 2023/02/17 13:48:42 - mmengine - INFO - Epoch(train) [23][ 800/1345] lr: 1.0000e-02 eta: 9:13:40 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.0084 loss: 3.7762 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3739 loss_aux: 1.4023 2023/02/17 13:48:46 - mmengine - INFO - Epoch(train) [23][ 820/1345] lr: 1.0000e-02 eta: 9:13:36 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.1426 loss: 3.4402 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0596 loss_aux: 1.3805 2023/02/17 13:48:49 - mmengine - INFO - Epoch(train) [23][ 840/1345] lr: 1.0000e-02 eta: 9:13:31 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.1949 loss: 4.0253 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4907 loss_aux: 1.5347 2023/02/17 13:48:53 - mmengine - INFO - Epoch(train) [23][ 860/1345] lr: 1.0000e-02 eta: 9:13:27 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 7.1184 loss: 3.4390 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0848 loss_aux: 1.3542 2023/02/17 13:48:57 - mmengine - INFO - Epoch(train) [23][ 880/1345] lr: 1.0000e-02 eta: 9:13:23 time: 0.1886 data_time: 0.0055 memory: 8327 grad_norm: 7.2366 loss: 3.6564 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2065 loss_aux: 1.4499 2023/02/17 13:49:01 - mmengine - INFO - Epoch(train) [23][ 900/1345] lr: 1.0000e-02 eta: 9:13:18 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.1063 loss: 3.9725 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4411 loss_aux: 1.5315 2023/02/17 13:49:04 - mmengine - INFO - Epoch(train) [23][ 920/1345] lr: 1.0000e-02 eta: 9:13:14 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.2099 loss: 4.0729 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5342 loss_aux: 1.5387 2023/02/17 13:49:08 - mmengine - INFO - Epoch(train) [23][ 940/1345] lr: 1.0000e-02 eta: 9:13:09 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.1736 loss: 3.7155 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2673 loss_aux: 1.4483 2023/02/17 13:49:12 - mmengine - INFO - Epoch(train) [23][ 960/1345] lr: 1.0000e-02 eta: 9:13:05 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.3418 loss: 3.7911 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3219 loss_aux: 1.4692 2023/02/17 13:49:16 - mmengine - INFO - Epoch(train) [23][ 980/1345] lr: 1.0000e-02 eta: 9:13:00 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.2734 loss: 3.9438 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4562 loss_aux: 1.4876 2023/02/17 13:49:20 - mmengine - INFO - Epoch(train) [23][1000/1345] lr: 1.0000e-02 eta: 9:12:56 time: 0.1891 data_time: 0.0062 memory: 8327 grad_norm: 7.1097 loss: 3.4606 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0801 loss_aux: 1.3805 2023/02/17 13:49:23 - mmengine - INFO - Epoch(train) [23][1020/1345] lr: 1.0000e-02 eta: 9:12:51 time: 0.1884 data_time: 0.0055 memory: 8327 grad_norm: 7.0812 loss: 4.1566 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5916 loss_aux: 1.5650 2023/02/17 13:49:27 - mmengine - INFO - Epoch(train) [23][1040/1345] lr: 1.0000e-02 eta: 9:12:47 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.1489 loss: 4.4341 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8226 loss_aux: 1.6115 2023/02/17 13:49:31 - mmengine - INFO - Epoch(train) [23][1060/1345] lr: 1.0000e-02 eta: 9:12:43 time: 0.1894 data_time: 0.0063 memory: 8327 grad_norm: 7.1920 loss: 3.5072 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1142 loss_aux: 1.3930 2023/02/17 13:49:35 - mmengine - INFO - Epoch(train) [23][1080/1345] lr: 1.0000e-02 eta: 9:12:38 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 7.3040 loss: 3.9131 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4511 loss_aux: 1.4620 2023/02/17 13:49:38 - mmengine - INFO - Epoch(train) [23][1100/1345] lr: 1.0000e-02 eta: 9:12:34 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 7.0421 loss: 3.9950 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4939 loss_aux: 1.5011 2023/02/17 13:49:42 - mmengine - INFO - Epoch(train) [23][1120/1345] lr: 1.0000e-02 eta: 9:12:30 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.1691 loss: 3.7628 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3178 loss_aux: 1.4450 2023/02/17 13:49:47 - mmengine - INFO - Epoch(train) [23][1140/1345] lr: 1.0000e-02 eta: 9:12:30 time: 0.2291 data_time: 0.0458 memory: 8327 grad_norm: 7.1434 loss: 3.7028 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.2943 loss_aux: 1.4086 2023/02/17 13:49:51 - mmengine - INFO - Epoch(train) [23][1160/1345] lr: 1.0000e-02 eta: 9:12:25 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.0343 loss: 3.4906 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0931 loss_aux: 1.3975 2023/02/17 13:49:54 - mmengine - INFO - Epoch(train) [23][1180/1345] lr: 1.0000e-02 eta: 9:12:21 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.1780 loss: 4.0427 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5711 loss_aux: 1.4716 2023/02/17 13:49:58 - mmengine - INFO - Epoch(train) [23][1200/1345] lr: 1.0000e-02 eta: 9:12:16 time: 0.1886 data_time: 0.0055 memory: 8327 grad_norm: 6.9266 loss: 3.9423 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4542 loss_aux: 1.4881 2023/02/17 13:50:02 - mmengine - INFO - Epoch(train) [23][1220/1345] lr: 1.0000e-02 eta: 9:12:12 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.0841 loss: 3.8556 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4051 loss_aux: 1.4505 2023/02/17 13:50:06 - mmengine - INFO - Epoch(train) [23][1240/1345] lr: 1.0000e-02 eta: 9:12:08 time: 0.1900 data_time: 0.0070 memory: 8327 grad_norm: 7.1338 loss: 4.0607 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4859 loss_aux: 1.5747 2023/02/17 13:50:10 - mmengine - INFO - Epoch(train) [23][1260/1345] lr: 1.0000e-02 eta: 9:12:03 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.2160 loss: 3.9368 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4397 loss_aux: 1.4970 2023/02/17 13:50:13 - mmengine - INFO - Epoch(train) [23][1280/1345] lr: 1.0000e-02 eta: 9:11:59 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 7.0475 loss: 3.8887 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4439 loss_aux: 1.4448 2023/02/17 13:50:17 - mmengine - INFO - Epoch(train) [23][1300/1345] lr: 1.0000e-02 eta: 9:11:54 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.2663 loss: 4.0270 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4857 loss_aux: 1.5413 2023/02/17 13:50:21 - mmengine - INFO - Epoch(train) [23][1320/1345] lr: 1.0000e-02 eta: 9:11:50 time: 0.1899 data_time: 0.0068 memory: 8327 grad_norm: 7.0768 loss: 3.8032 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3602 loss_aux: 1.4430 2023/02/17 13:50:25 - mmengine - INFO - Epoch(train) [23][1340/1345] lr: 1.0000e-02 eta: 9:11:46 time: 0.1899 data_time: 0.0072 memory: 8327 grad_norm: 7.0481 loss: 3.6442 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1952 loss_aux: 1.4490 2023/02/17 13:50:26 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:50:26 - mmengine - INFO - Epoch(train) [23][1345/1345] lr: 1.0000e-02 eta: 9:11:44 time: 0.1825 data_time: 0.0058 memory: 8327 grad_norm: 6.9674 loss: 3.9010 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.3806 loss_aux: 1.5204 2023/02/17 13:50:26 - mmengine - INFO - Saving checkpoint at 23 epochs 2023/02/17 13:50:32 - mmengine - INFO - Epoch(train) [24][ 20/1345] lr: 1.0000e-02 eta: 9:11:41 time: 0.2044 data_time: 0.0152 memory: 8327 grad_norm: 6.8060 loss: 4.1085 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5816 loss_aux: 1.5269 2023/02/17 13:50:36 - mmengine - INFO - Epoch(train) [24][ 40/1345] lr: 1.0000e-02 eta: 9:11:37 time: 0.1939 data_time: 0.0063 memory: 8327 grad_norm: 7.0645 loss: 3.5190 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.1137 loss_aux: 1.4053 2023/02/17 13:50:40 - mmengine - INFO - Epoch(train) [24][ 60/1345] lr: 1.0000e-02 eta: 9:11:33 time: 0.1899 data_time: 0.0044 memory: 8327 grad_norm: 7.2422 loss: 3.8284 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3677 loss_aux: 1.4608 2023/02/17 13:50:41 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:50:44 - mmengine - INFO - Epoch(train) [24][ 80/1345] lr: 1.0000e-02 eta: 9:11:29 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 7.1545 loss: 3.5512 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1513 loss_aux: 1.3999 2023/02/17 13:50:47 - mmengine - INFO - Epoch(train) [24][ 100/1345] lr: 1.0000e-02 eta: 9:11:24 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.0635 loss: 3.2232 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9090 loss_aux: 1.3142 2023/02/17 13:50:51 - mmengine - INFO - Epoch(train) [24][ 120/1345] lr: 1.0000e-02 eta: 9:11:20 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 6.9361 loss: 3.6781 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1973 loss_aux: 1.4808 2023/02/17 13:50:55 - mmengine - INFO - Epoch(train) [24][ 140/1345] lr: 1.0000e-02 eta: 9:11:15 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 7.2087 loss: 3.8111 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3487 loss_aux: 1.4624 2023/02/17 13:50:59 - mmengine - INFO - Epoch(train) [24][ 160/1345] lr: 1.0000e-02 eta: 9:11:11 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.2163 loss: 3.9636 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4485 loss_aux: 1.5151 2023/02/17 13:51:02 - mmengine - INFO - Epoch(train) [24][ 180/1345] lr: 1.0000e-02 eta: 9:11:06 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.0293 loss: 3.5000 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1002 loss_aux: 1.3998 2023/02/17 13:51:06 - mmengine - INFO - Epoch(train) [24][ 200/1345] lr: 1.0000e-02 eta: 9:11:02 time: 0.1885 data_time: 0.0057 memory: 8327 grad_norm: 7.0618 loss: 3.8834 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3832 loss_aux: 1.5002 2023/02/17 13:51:10 - mmengine - INFO - Epoch(train) [24][ 220/1345] lr: 1.0000e-02 eta: 9:10:58 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.3175 loss: 4.2852 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7139 loss_aux: 1.5713 2023/02/17 13:51:14 - mmengine - INFO - Epoch(train) [24][ 240/1345] lr: 1.0000e-02 eta: 9:10:53 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.1580 loss: 3.8725 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3998 loss_aux: 1.4727 2023/02/17 13:51:18 - mmengine - INFO - Epoch(train) [24][ 260/1345] lr: 1.0000e-02 eta: 9:10:49 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.0481 loss: 3.3673 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0330 loss_aux: 1.3342 2023/02/17 13:51:21 - mmengine - INFO - Epoch(train) [24][ 280/1345] lr: 1.0000e-02 eta: 9:10:44 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.1933 loss: 3.5343 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1538 loss_aux: 1.3805 2023/02/17 13:51:25 - mmengine - INFO - Epoch(train) [24][ 300/1345] lr: 1.0000e-02 eta: 9:10:40 time: 0.1892 data_time: 0.0060 memory: 8327 grad_norm: 7.1302 loss: 3.5497 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1573 loss_aux: 1.3925 2023/02/17 13:51:29 - mmengine - INFO - Epoch(train) [24][ 320/1345] lr: 1.0000e-02 eta: 9:10:36 time: 0.1896 data_time: 0.0065 memory: 8327 grad_norm: 6.8738 loss: 3.7241 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2442 loss_aux: 1.4798 2023/02/17 13:51:33 - mmengine - INFO - Epoch(train) [24][ 340/1345] lr: 1.0000e-02 eta: 9:10:31 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.1299 loss: 3.8095 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3472 loss_aux: 1.4622 2023/02/17 13:51:36 - mmengine - INFO - Epoch(train) [24][ 360/1345] lr: 1.0000e-02 eta: 9:10:27 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 6.9791 loss: 3.8458 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3727 loss_aux: 1.4731 2023/02/17 13:51:40 - mmengine - INFO - Epoch(train) [24][ 380/1345] lr: 1.0000e-02 eta: 9:10:22 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.2915 loss: 3.9347 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4242 loss_aux: 1.5105 2023/02/17 13:51:44 - mmengine - INFO - Epoch(train) [24][ 400/1345] lr: 1.0000e-02 eta: 9:10:18 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.2801 loss: 4.1079 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5493 loss_aux: 1.5587 2023/02/17 13:51:48 - mmengine - INFO - Epoch(train) [24][ 420/1345] lr: 1.0000e-02 eta: 9:10:14 time: 0.1902 data_time: 0.0057 memory: 8327 grad_norm: 7.1825 loss: 4.1514 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5334 loss_aux: 1.6179 2023/02/17 13:51:52 - mmengine - INFO - Epoch(train) [24][ 440/1345] lr: 1.0000e-02 eta: 9:10:09 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.1650 loss: 3.5512 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1556 loss_aux: 1.3956 2023/02/17 13:51:55 - mmengine - INFO - Epoch(train) [24][ 460/1345] lr: 1.0000e-02 eta: 9:10:05 time: 0.1895 data_time: 0.0064 memory: 8327 grad_norm: 6.8854 loss: 3.7051 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2526 loss_aux: 1.4525 2023/02/17 13:51:59 - mmengine - INFO - Epoch(train) [24][ 480/1345] lr: 1.0000e-02 eta: 9:10:01 time: 0.1893 data_time: 0.0056 memory: 8327 grad_norm: 7.0238 loss: 3.8782 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3793 loss_aux: 1.4989 2023/02/17 13:52:03 - mmengine - INFO - Epoch(train) [24][ 500/1345] lr: 1.0000e-02 eta: 9:09:56 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.0603 loss: 3.5749 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1832 loss_aux: 1.3917 2023/02/17 13:52:07 - mmengine - INFO - Epoch(train) [24][ 520/1345] lr: 1.0000e-02 eta: 9:09:52 time: 0.1900 data_time: 0.0056 memory: 8327 grad_norm: 7.2513 loss: 3.6087 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2353 loss_aux: 1.3734 2023/02/17 13:52:11 - mmengine - INFO - Epoch(train) [24][ 540/1345] lr: 1.0000e-02 eta: 9:09:48 time: 0.1887 data_time: 0.0055 memory: 8327 grad_norm: 7.0238 loss: 3.8090 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3476 loss_aux: 1.4614 2023/02/17 13:52:14 - mmengine - INFO - Epoch(train) [24][ 560/1345] lr: 1.0000e-02 eta: 9:09:43 time: 0.1893 data_time: 0.0056 memory: 8327 grad_norm: 6.9955 loss: 3.8043 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3575 loss_aux: 1.4468 2023/02/17 13:52:18 - mmengine - INFO - Epoch(train) [24][ 580/1345] lr: 1.0000e-02 eta: 9:09:39 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.1881 loss: 4.2746 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6686 loss_aux: 1.6060 2023/02/17 13:52:22 - mmengine - INFO - Epoch(train) [24][ 600/1345] lr: 1.0000e-02 eta: 9:09:34 time: 0.1893 data_time: 0.0056 memory: 8327 grad_norm: 7.2092 loss: 3.6479 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2642 loss_aux: 1.3837 2023/02/17 13:52:26 - mmengine - INFO - Epoch(train) [24][ 620/1345] lr: 1.0000e-02 eta: 9:09:30 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 7.3182 loss: 3.9280 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4396 loss_aux: 1.4884 2023/02/17 13:52:30 - mmengine - INFO - Epoch(train) [24][ 640/1345] lr: 1.0000e-02 eta: 9:09:26 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 6.9991 loss: 3.7213 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2394 loss_aux: 1.4819 2023/02/17 13:52:33 - mmengine - INFO - Epoch(train) [24][ 660/1345] lr: 1.0000e-02 eta: 9:09:21 time: 0.1901 data_time: 0.0071 memory: 8327 grad_norm: 7.1737 loss: 3.8725 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3780 loss_aux: 1.4945 2023/02/17 13:52:37 - mmengine - INFO - Epoch(train) [24][ 680/1345] lr: 1.0000e-02 eta: 9:09:17 time: 0.1900 data_time: 0.0057 memory: 8327 grad_norm: 7.0946 loss: 3.8858 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3465 loss_aux: 1.5394 2023/02/17 13:52:41 - mmengine - INFO - Epoch(train) [24][ 700/1345] lr: 1.0000e-02 eta: 9:09:13 time: 0.1906 data_time: 0.0069 memory: 8327 grad_norm: 7.1983 loss: 3.7214 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2411 loss_aux: 1.4803 2023/02/17 13:52:45 - mmengine - INFO - Epoch(train) [24][ 720/1345] lr: 1.0000e-02 eta: 9:09:09 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.4946 loss: 3.4225 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0590 loss_aux: 1.3634 2023/02/17 13:52:48 - mmengine - INFO - Epoch(train) [24][ 740/1345] lr: 1.0000e-02 eta: 9:09:04 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.2998 loss: 3.6651 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2304 loss_aux: 1.4347 2023/02/17 13:52:52 - mmengine - INFO - Epoch(train) [24][ 760/1345] lr: 1.0000e-02 eta: 9:09:00 time: 0.1888 data_time: 0.0060 memory: 8327 grad_norm: 7.3349 loss: 3.9928 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4367 loss_aux: 1.5561 2023/02/17 13:52:56 - mmengine - INFO - Epoch(train) [24][ 780/1345] lr: 1.0000e-02 eta: 9:08:55 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.1007 loss: 3.5985 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2296 loss_aux: 1.3689 2023/02/17 13:53:00 - mmengine - INFO - Epoch(train) [24][ 800/1345] lr: 1.0000e-02 eta: 9:08:51 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.0348 loss: 3.8703 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3795 loss_aux: 1.4908 2023/02/17 13:53:04 - mmengine - INFO - Epoch(train) [24][ 820/1345] lr: 1.0000e-02 eta: 9:08:47 time: 0.1886 data_time: 0.0058 memory: 8327 grad_norm: 7.0213 loss: 3.7025 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2694 loss_aux: 1.4331 2023/02/17 13:53:07 - mmengine - INFO - Epoch(train) [24][ 840/1345] lr: 1.0000e-02 eta: 9:08:42 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.3944 loss: 4.0780 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5373 loss_aux: 1.5408 2023/02/17 13:53:11 - mmengine - INFO - Epoch(train) [24][ 860/1345] lr: 1.0000e-02 eta: 9:08:38 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.2104 loss: 3.9549 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4199 loss_aux: 1.5350 2023/02/17 13:53:15 - mmengine - INFO - Epoch(train) [24][ 880/1345] lr: 1.0000e-02 eta: 9:08:33 time: 0.1886 data_time: 0.0058 memory: 8327 grad_norm: 7.1323 loss: 3.5163 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1057 loss_aux: 1.4106 2023/02/17 13:53:19 - mmengine - INFO - Epoch(train) [24][ 900/1345] lr: 1.0000e-02 eta: 9:08:29 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.0005 loss: 3.5400 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1633 loss_aux: 1.3767 2023/02/17 13:53:23 - mmengine - INFO - Epoch(train) [24][ 920/1345] lr: 1.0000e-02 eta: 9:08:25 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 7.1733 loss: 3.7909 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3065 loss_aux: 1.4844 2023/02/17 13:53:26 - mmengine - INFO - Epoch(train) [24][ 940/1345] lr: 1.0000e-02 eta: 9:08:20 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 7.0725 loss: 3.6442 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2086 loss_aux: 1.4355 2023/02/17 13:53:30 - mmengine - INFO - Epoch(train) [24][ 960/1345] lr: 1.0000e-02 eta: 9:08:16 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 6.9538 loss: 3.4732 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1120 loss_aux: 1.3613 2023/02/17 13:53:34 - mmengine - INFO - Epoch(train) [24][ 980/1345] lr: 1.0000e-02 eta: 9:08:12 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.0684 loss: 3.9001 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3776 loss_aux: 1.5224 2023/02/17 13:53:38 - mmengine - INFO - Epoch(train) [24][1000/1345] lr: 1.0000e-02 eta: 9:08:07 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 7.1892 loss: 3.6892 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2312 loss_aux: 1.4580 2023/02/17 13:53:41 - mmengine - INFO - Epoch(train) [24][1020/1345] lr: 1.0000e-02 eta: 9:08:03 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.0213 loss: 3.8273 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3655 loss_aux: 1.4618 2023/02/17 13:53:45 - mmengine - INFO - Epoch(train) [24][1040/1345] lr: 1.0000e-02 eta: 9:07:59 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.0307 loss: 3.8924 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4188 loss_aux: 1.4736 2023/02/17 13:53:49 - mmengine - INFO - Epoch(train) [24][1060/1345] lr: 1.0000e-02 eta: 9:07:54 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.2558 loss: 4.2877 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6812 loss_aux: 1.6065 2023/02/17 13:53:50 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:53:53 - mmengine - INFO - Epoch(train) [24][1080/1345] lr: 1.0000e-02 eta: 9:07:50 time: 0.1891 data_time: 0.0061 memory: 8327 grad_norm: 7.0256 loss: 3.5267 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1377 loss_aux: 1.3890 2023/02/17 13:53:57 - mmengine - INFO - Epoch(train) [24][1100/1345] lr: 1.0000e-02 eta: 9:07:45 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.2544 loss: 3.8100 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3249 loss_aux: 1.4850 2023/02/17 13:54:00 - mmengine - INFO - Epoch(train) [24][1120/1345] lr: 1.0000e-02 eta: 9:07:41 time: 0.1914 data_time: 0.0084 memory: 8327 grad_norm: 6.9624 loss: 3.6447 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1781 loss_aux: 1.4666 2023/02/17 13:54:04 - mmengine - INFO - Epoch(train) [24][1140/1345] lr: 1.0000e-02 eta: 9:07:37 time: 0.1885 data_time: 0.0056 memory: 8327 grad_norm: 7.0865 loss: 3.7890 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3439 loss_aux: 1.4451 2023/02/17 13:54:08 - mmengine - INFO - Epoch(train) [24][1160/1345] lr: 1.0000e-02 eta: 9:07:33 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 7.1550 loss: 3.7892 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3127 loss_aux: 1.4765 2023/02/17 13:54:12 - mmengine - INFO - Epoch(train) [24][1180/1345] lr: 1.0000e-02 eta: 9:07:28 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.3310 loss: 3.8730 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3980 loss_aux: 1.4749 2023/02/17 13:54:16 - mmengine - INFO - Epoch(train) [24][1200/1345] lr: 1.0000e-02 eta: 9:07:24 time: 0.1895 data_time: 0.0056 memory: 8327 grad_norm: 7.0587 loss: 3.7835 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3320 loss_aux: 1.4515 2023/02/17 13:54:19 - mmengine - INFO - Epoch(train) [24][1220/1345] lr: 1.0000e-02 eta: 9:07:20 time: 0.1885 data_time: 0.0056 memory: 8327 grad_norm: 7.3019 loss: 3.9116 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3987 loss_aux: 1.5128 2023/02/17 13:54:23 - mmengine - INFO - Epoch(train) [24][1240/1345] lr: 1.0000e-02 eta: 9:07:15 time: 0.1888 data_time: 0.0059 memory: 8327 grad_norm: 7.2805 loss: 3.8462 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3466 loss_aux: 1.4997 2023/02/17 13:54:27 - mmengine - INFO - Epoch(train) [24][1260/1345] lr: 1.0000e-02 eta: 9:07:11 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.1371 loss: 3.7424 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2582 loss_aux: 1.4842 2023/02/17 13:54:31 - mmengine - INFO - Epoch(train) [24][1280/1345] lr: 1.0000e-02 eta: 9:07:06 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.1492 loss: 3.4417 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0683 loss_aux: 1.3734 2023/02/17 13:54:34 - mmengine - INFO - Epoch(train) [24][1300/1345] lr: 1.0000e-02 eta: 9:07:02 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.0978 loss: 3.8510 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4081 loss_aux: 1.4429 2023/02/17 13:54:38 - mmengine - INFO - Epoch(train) [24][1320/1345] lr: 1.0000e-02 eta: 9:06:58 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 6.9702 loss: 3.6915 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2795 loss_aux: 1.4120 2023/02/17 13:54:42 - mmengine - INFO - Epoch(train) [24][1340/1345] lr: 1.0000e-02 eta: 9:06:53 time: 0.1903 data_time: 0.0057 memory: 8327 grad_norm: 7.1325 loss: 4.0211 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5021 loss_aux: 1.5190 2023/02/17 13:54:43 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:54:43 - mmengine - INFO - Epoch(train) [24][1345/1345] lr: 1.0000e-02 eta: 9:06:52 time: 0.1839 data_time: 0.0062 memory: 8327 grad_norm: 7.0696 loss: 3.9788 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.4544 loss_aux: 1.5244 2023/02/17 13:54:43 - mmengine - INFO - Saving checkpoint at 24 epochs 2023/02/17 13:54:50 - mmengine - INFO - Epoch(train) [25][ 20/1345] lr: 1.0000e-02 eta: 9:06:49 time: 0.2065 data_time: 0.0162 memory: 8327 grad_norm: 7.1042 loss: 3.5736 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2136 loss_aux: 1.3600 2023/02/17 13:54:53 - mmengine - INFO - Epoch(train) [25][ 40/1345] lr: 1.0000e-02 eta: 9:06:45 time: 0.1907 data_time: 0.0038 memory: 8327 grad_norm: 7.0402 loss: 3.7756 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2846 loss_aux: 1.4909 2023/02/17 13:54:57 - mmengine - INFO - Epoch(train) [25][ 60/1345] lr: 1.0000e-02 eta: 9:06:41 time: 0.1898 data_time: 0.0055 memory: 8327 grad_norm: 6.9918 loss: 3.8309 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3558 loss_aux: 1.4751 2023/02/17 13:55:01 - mmengine - INFO - Epoch(train) [25][ 80/1345] lr: 1.0000e-02 eta: 9:06:37 time: 0.1895 data_time: 0.0056 memory: 8327 grad_norm: 7.0379 loss: 3.4564 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0989 loss_aux: 1.3575 2023/02/17 13:55:05 - mmengine - INFO - Epoch(train) [25][ 100/1345] lr: 1.0000e-02 eta: 9:06:32 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.1437 loss: 3.9923 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5030 loss_aux: 1.4892 2023/02/17 13:55:09 - mmengine - INFO - Epoch(train) [25][ 120/1345] lr: 1.0000e-02 eta: 9:06:28 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.3825 loss: 3.8517 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3635 loss_aux: 1.4882 2023/02/17 13:55:12 - mmengine - INFO - Epoch(train) [25][ 140/1345] lr: 1.0000e-02 eta: 9:06:24 time: 0.1900 data_time: 0.0056 memory: 8327 grad_norm: 7.2194 loss: 3.6310 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1554 loss_aux: 1.4756 2023/02/17 13:55:16 - mmengine - INFO - Epoch(train) [25][ 160/1345] lr: 1.0000e-02 eta: 9:06:19 time: 0.1885 data_time: 0.0055 memory: 8327 grad_norm: 7.1627 loss: 3.5715 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1769 loss_aux: 1.3946 2023/02/17 13:55:20 - mmengine - INFO - Epoch(train) [25][ 180/1345] lr: 1.0000e-02 eta: 9:06:15 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.1477 loss: 3.6031 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1581 loss_aux: 1.4450 2023/02/17 13:55:24 - mmengine - INFO - Epoch(train) [25][ 200/1345] lr: 1.0000e-02 eta: 9:06:10 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.3203 loss: 3.9874 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4335 loss_aux: 1.5539 2023/02/17 13:55:27 - mmengine - INFO - Epoch(train) [25][ 220/1345] lr: 1.0000e-02 eta: 9:06:06 time: 0.1885 data_time: 0.0057 memory: 8327 grad_norm: 7.0929 loss: 3.6669 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2210 loss_aux: 1.4459 2023/02/17 13:55:31 - mmengine - INFO - Epoch(train) [25][ 240/1345] lr: 1.0000e-02 eta: 9:06:02 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.1423 loss: 3.8169 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3228 loss_aux: 1.4941 2023/02/17 13:55:35 - mmengine - INFO - Epoch(train) [25][ 260/1345] lr: 1.0000e-02 eta: 9:05:57 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.3655 loss: 3.6483 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2088 loss_aux: 1.4395 2023/02/17 13:55:39 - mmengine - INFO - Epoch(train) [25][ 280/1345] lr: 1.0000e-02 eta: 9:05:53 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.1511 loss: 3.6320 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2100 loss_aux: 1.4220 2023/02/17 13:55:43 - mmengine - INFO - Epoch(train) [25][ 300/1345] lr: 1.0000e-02 eta: 9:05:49 time: 0.1891 data_time: 0.0055 memory: 8327 grad_norm: 7.0434 loss: 3.5661 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2086 loss_aux: 1.3576 2023/02/17 13:55:46 - mmengine - INFO - Epoch(train) [25][ 320/1345] lr: 1.0000e-02 eta: 9:05:44 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.1602 loss: 3.8563 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3571 loss_aux: 1.4992 2023/02/17 13:55:50 - mmengine - INFO - Epoch(train) [25][ 340/1345] lr: 1.0000e-02 eta: 9:05:40 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.1535 loss: 3.7376 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2861 loss_aux: 1.4515 2023/02/17 13:55:54 - mmengine - INFO - Epoch(train) [25][ 360/1345] lr: 1.0000e-02 eta: 9:05:36 time: 0.1892 data_time: 0.0055 memory: 8327 grad_norm: 7.3393 loss: 4.1811 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5770 loss_aux: 1.6041 2023/02/17 13:55:58 - mmengine - INFO - Epoch(train) [25][ 380/1345] lr: 1.0000e-02 eta: 9:05:31 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.2261 loss: 4.0284 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4684 loss_aux: 1.5600 2023/02/17 13:56:02 - mmengine - INFO - Epoch(train) [25][ 400/1345] lr: 1.0000e-02 eta: 9:05:27 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.2773 loss: 3.4886 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0537 loss_aux: 1.4349 2023/02/17 13:56:05 - mmengine - INFO - Epoch(train) [25][ 420/1345] lr: 1.0000e-02 eta: 9:05:23 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.0724 loss: 3.7961 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3170 loss_aux: 1.4790 2023/02/17 13:56:09 - mmengine - INFO - Epoch(train) [25][ 440/1345] lr: 1.0000e-02 eta: 9:05:18 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.1422 loss: 3.8155 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2819 loss_aux: 1.5335 2023/02/17 13:56:13 - mmengine - INFO - Epoch(train) [25][ 460/1345] lr: 1.0000e-02 eta: 9:05:14 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.1114 loss: 3.6206 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2315 loss_aux: 1.3891 2023/02/17 13:56:17 - mmengine - INFO - Epoch(train) [25][ 480/1345] lr: 1.0000e-02 eta: 9:05:09 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.3648 loss: 3.5343 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.1616 loss_aux: 1.3727 2023/02/17 13:56:20 - mmengine - INFO - Epoch(train) [25][ 500/1345] lr: 1.0000e-02 eta: 9:05:05 time: 0.1888 data_time: 0.0059 memory: 8327 grad_norm: 7.2532 loss: 3.9657 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4223 loss_aux: 1.5434 2023/02/17 13:56:24 - mmengine - INFO - Epoch(train) [25][ 520/1345] lr: 1.0000e-02 eta: 9:05:01 time: 0.1895 data_time: 0.0056 memory: 8327 grad_norm: 7.3083 loss: 3.8268 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.3568 loss_aux: 1.4700 2023/02/17 13:56:28 - mmengine - INFO - Epoch(train) [25][ 540/1345] lr: 1.0000e-02 eta: 9:04:57 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.0484 loss: 3.5438 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1505 loss_aux: 1.3932 2023/02/17 13:56:32 - mmengine - INFO - Epoch(train) [25][ 560/1345] lr: 1.0000e-02 eta: 9:04:52 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 7.2105 loss: 3.5793 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1782 loss_aux: 1.4010 2023/02/17 13:56:36 - mmengine - INFO - Epoch(train) [25][ 580/1345] lr: 1.0000e-02 eta: 9:04:48 time: 0.1895 data_time: 0.0056 memory: 8327 grad_norm: 7.1402 loss: 3.8325 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3708 loss_aux: 1.4617 2023/02/17 13:56:39 - mmengine - INFO - Epoch(train) [25][ 600/1345] lr: 1.0000e-02 eta: 9:04:44 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.1028 loss: 3.5569 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1775 loss_aux: 1.3794 2023/02/17 13:56:43 - mmengine - INFO - Epoch(train) [25][ 620/1345] lr: 1.0000e-02 eta: 9:04:39 time: 0.1893 data_time: 0.0055 memory: 8327 grad_norm: 7.1100 loss: 3.6125 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.2229 loss_aux: 1.3896 2023/02/17 13:56:47 - mmengine - INFO - Epoch(train) [25][ 640/1345] lr: 1.0000e-02 eta: 9:04:35 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 7.2256 loss: 3.7253 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2051 loss_aux: 1.5202 2023/02/17 13:56:51 - mmengine - INFO - Epoch(train) [25][ 660/1345] lr: 1.0000e-02 eta: 9:04:31 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.4603 loss: 3.8025 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3510 loss_aux: 1.4516 2023/02/17 13:56:54 - mmengine - INFO - Epoch(train) [25][ 680/1345] lr: 1.0000e-02 eta: 9:04:26 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.0724 loss: 3.5908 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1511 loss_aux: 1.4397 2023/02/17 13:56:58 - mmengine - INFO - Epoch(train) [25][ 700/1345] lr: 1.0000e-02 eta: 9:04:22 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.2445 loss: 3.7975 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3180 loss_aux: 1.4794 2023/02/17 13:57:02 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:57:02 - mmengine - INFO - Epoch(train) [25][ 720/1345] lr: 1.0000e-02 eta: 9:04:18 time: 0.1911 data_time: 0.0077 memory: 8327 grad_norm: 6.9949 loss: 3.5933 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.2328 loss_aux: 1.3605 2023/02/17 13:57:06 - mmengine - INFO - Epoch(train) [25][ 740/1345] lr: 1.0000e-02 eta: 9:04:13 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.4853 loss: 3.6875 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2399 loss_aux: 1.4476 2023/02/17 13:57:10 - mmengine - INFO - Epoch(train) [25][ 760/1345] lr: 1.0000e-02 eta: 9:04:09 time: 0.1907 data_time: 0.0065 memory: 8327 grad_norm: 7.2622 loss: 3.6726 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3173 loss_aux: 1.3552 2023/02/17 13:57:13 - mmengine - INFO - Epoch(train) [25][ 780/1345] lr: 1.0000e-02 eta: 9:04:05 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.1802 loss: 3.7984 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3632 loss_aux: 1.4352 2023/02/17 13:57:17 - mmengine - INFO - Epoch(train) [25][ 800/1345] lr: 1.0000e-02 eta: 9:04:00 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.2317 loss: 3.6824 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2160 loss_aux: 1.4665 2023/02/17 13:57:21 - mmengine - INFO - Epoch(train) [25][ 820/1345] lr: 1.0000e-02 eta: 9:03:56 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.4391 loss: 3.9402 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4616 loss_aux: 1.4786 2023/02/17 13:57:25 - mmengine - INFO - Epoch(train) [25][ 840/1345] lr: 1.0000e-02 eta: 9:03:52 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.3292 loss: 3.5529 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.1189 loss_aux: 1.4339 2023/02/17 13:57:29 - mmengine - INFO - Epoch(train) [25][ 860/1345] lr: 1.0000e-02 eta: 9:03:47 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.2078 loss: 4.3497 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7345 loss_aux: 1.6152 2023/02/17 13:57:32 - mmengine - INFO - Epoch(train) [25][ 880/1345] lr: 1.0000e-02 eta: 9:03:43 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 6.9843 loss: 3.7071 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2613 loss_aux: 1.4459 2023/02/17 13:57:36 - mmengine - INFO - Epoch(train) [25][ 900/1345] lr: 1.0000e-02 eta: 9:03:39 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.0177 loss: 4.1010 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5071 loss_aux: 1.5940 2023/02/17 13:57:40 - mmengine - INFO - Epoch(train) [25][ 920/1345] lr: 1.0000e-02 eta: 9:03:34 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.3185 loss: 3.9582 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4748 loss_aux: 1.4834 2023/02/17 13:57:44 - mmengine - INFO - Epoch(train) [25][ 940/1345] lr: 1.0000e-02 eta: 9:03:30 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.2323 loss: 3.7634 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3000 loss_aux: 1.4634 2023/02/17 13:57:47 - mmengine - INFO - Epoch(train) [25][ 960/1345] lr: 1.0000e-02 eta: 9:03:26 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.2126 loss: 3.4405 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0914 loss_aux: 1.3490 2023/02/17 13:57:51 - mmengine - INFO - Epoch(train) [25][ 980/1345] lr: 1.0000e-02 eta: 9:03:22 time: 0.1988 data_time: 0.0158 memory: 8327 grad_norm: 7.0410 loss: 3.4678 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1133 loss_aux: 1.3546 2023/02/17 13:57:55 - mmengine - INFO - Epoch(train) [25][1000/1345] lr: 1.0000e-02 eta: 9:03:18 time: 0.1889 data_time: 0.0059 memory: 8327 grad_norm: 7.0142 loss: 3.9043 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4004 loss_aux: 1.5039 2023/02/17 13:57:59 - mmengine - INFO - Epoch(train) [25][1020/1345] lr: 1.0000e-02 eta: 9:03:14 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 7.3983 loss: 3.8635 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3419 loss_aux: 1.5216 2023/02/17 13:58:03 - mmengine - INFO - Epoch(train) [25][1040/1345] lr: 1.0000e-02 eta: 9:03:09 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.1693 loss: 3.4993 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.1373 loss_aux: 1.3620 2023/02/17 13:58:07 - mmengine - INFO - Epoch(train) [25][1060/1345] lr: 1.0000e-02 eta: 9:03:05 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 6.9753 loss: 3.7310 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2804 loss_aux: 1.4506 2023/02/17 13:58:10 - mmengine - INFO - Epoch(train) [25][1080/1345] lr: 1.0000e-02 eta: 9:03:01 time: 0.1904 data_time: 0.0071 memory: 8327 grad_norm: 7.4665 loss: 4.0554 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5282 loss_aux: 1.5272 2023/02/17 13:58:14 - mmengine - INFO - Epoch(train) [25][1100/1345] lr: 1.0000e-02 eta: 9:02:57 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.1631 loss: 3.9873 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5064 loss_aux: 1.4808 2023/02/17 13:58:18 - mmengine - INFO - Epoch(train) [25][1120/1345] lr: 1.0000e-02 eta: 9:02:52 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.0572 loss: 3.6798 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2504 loss_aux: 1.4294 2023/02/17 13:58:22 - mmengine - INFO - Epoch(train) [25][1140/1345] lr: 1.0000e-02 eta: 9:02:48 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.2966 loss: 4.3670 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7253 loss_aux: 1.6417 2023/02/17 13:58:26 - mmengine - INFO - Epoch(train) [25][1160/1345] lr: 1.0000e-02 eta: 9:02:44 time: 0.1907 data_time: 0.0074 memory: 8327 grad_norm: 7.1288 loss: 3.9391 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4088 loss_aux: 1.5303 2023/02/17 13:58:29 - mmengine - INFO - Epoch(train) [25][1180/1345] lr: 1.0000e-02 eta: 9:02:40 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 6.9429 loss: 4.0694 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5153 loss_aux: 1.5541 2023/02/17 13:58:33 - mmengine - INFO - Epoch(train) [25][1200/1345] lr: 1.0000e-02 eta: 9:02:35 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 6.9423 loss: 3.5970 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1369 loss_aux: 1.4601 2023/02/17 13:58:37 - mmengine - INFO - Epoch(train) [25][1220/1345] lr: 1.0000e-02 eta: 9:02:31 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.1192 loss: 3.3964 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0583 loss_aux: 1.3381 2023/02/17 13:58:41 - mmengine - INFO - Epoch(train) [25][1240/1345] lr: 1.0000e-02 eta: 9:02:27 time: 0.1897 data_time: 0.0056 memory: 8327 grad_norm: 7.2937 loss: 3.6976 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2011 loss_aux: 1.4965 2023/02/17 13:58:44 - mmengine - INFO - Epoch(train) [25][1260/1345] lr: 1.0000e-02 eta: 9:02:22 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 7.3259 loss: 4.1096 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5698 loss_aux: 1.5398 2023/02/17 13:58:48 - mmengine - INFO - Epoch(train) [25][1280/1345] lr: 1.0000e-02 eta: 9:02:18 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.2251 loss: 3.9152 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3923 loss_aux: 1.5230 2023/02/17 13:58:52 - mmengine - INFO - Epoch(train) [25][1300/1345] lr: 1.0000e-02 eta: 9:02:14 time: 0.1906 data_time: 0.0072 memory: 8327 grad_norm: 6.8918 loss: 3.6385 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2222 loss_aux: 1.4162 2023/02/17 13:58:56 - mmengine - INFO - Epoch(train) [25][1320/1345] lr: 1.0000e-02 eta: 9:02:09 time: 0.1885 data_time: 0.0056 memory: 8327 grad_norm: 7.2166 loss: 3.5771 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1475 loss_aux: 1.4297 2023/02/17 13:59:00 - mmengine - INFO - Epoch(train) [25][1340/1345] lr: 1.0000e-02 eta: 9:02:05 time: 0.1910 data_time: 0.0071 memory: 8327 grad_norm: 7.3494 loss: 3.3091 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9529 loss_aux: 1.3562 2023/02/17 13:59:00 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 13:59:00 - mmengine - INFO - Epoch(train) [25][1345/1345] lr: 1.0000e-02 eta: 9:02:04 time: 0.1829 data_time: 0.0060 memory: 8327 grad_norm: 7.3063 loss: 3.6487 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.2155 loss_aux: 1.4333 2023/02/17 13:59:01 - mmengine - INFO - Saving checkpoint at 25 epochs 2023/02/17 13:59:04 - mmengine - INFO - Epoch(val) [25][ 20/181] eta: 0:00:09 time: 0.0567 data_time: 0.0078 memory: 1994 2023/02/17 13:59:05 - mmengine - INFO - Epoch(val) [25][ 40/181] eta: 0:00:07 time: 0.0524 data_time: 0.0046 memory: 1994 2023/02/17 13:59:06 - mmengine - INFO - Epoch(val) [25][ 60/181] eta: 0:00:06 time: 0.0524 data_time: 0.0048 memory: 1994 2023/02/17 13:59:07 - mmengine - INFO - Epoch(val) [25][ 80/181] eta: 0:00:05 time: 0.0523 data_time: 0.0046 memory: 1994 2023/02/17 13:59:08 - mmengine - INFO - Epoch(val) [25][100/181] eta: 0:00:04 time: 0.0526 data_time: 0.0046 memory: 1994 2023/02/17 13:59:09 - mmengine - INFO - Epoch(val) [25][120/181] eta: 0:00:03 time: 0.0526 data_time: 0.0047 memory: 1994 2023/02/17 13:59:10 - mmengine - INFO - Epoch(val) [25][140/181] eta: 0:00:02 time: 0.0523 data_time: 0.0045 memory: 1994 2023/02/17 13:59:11 - mmengine - INFO - Epoch(val) [25][160/181] eta: 0:00:01 time: 0.0516 data_time: 0.0041 memory: 1994 2023/02/17 13:59:12 - mmengine - INFO - Epoch(val) [25][180/181] eta: 0:00:00 time: 0.0514 data_time: 0.0041 memory: 1994 2023/02/17 13:59:13 - mmengine - INFO - Epoch(val) [25][181/181] acc/top1: 0.3670 acc/top5: 0.6512 acc/mean1: 0.3279 2023/02/17 13:59:13 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/lilin/Repos/mmact_dev/mmaction2/work_dirs/fix_flip/tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb/best_acc/top1_epoch_20.pth is removed 2023/02/17 13:59:14 - mmengine - INFO - The best checkpoint with 0.3670 acc/top1 at 25 epoch is saved to best_acc/top1_epoch_25.pth. 2023/02/17 13:59:19 - mmengine - INFO - Epoch(train) [26][ 20/1345] lr: 1.0000e-02 eta: 9:02:02 time: 0.2109 data_time: 0.0162 memory: 8327 grad_norm: 7.3704 loss: 3.7997 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3279 loss_aux: 1.4718 2023/02/17 13:59:22 - mmengine - INFO - Epoch(train) [26][ 40/1345] lr: 1.0000e-02 eta: 9:01:57 time: 0.1912 data_time: 0.0039 memory: 8327 grad_norm: 7.0775 loss: 3.8121 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3318 loss_aux: 1.4803 2023/02/17 13:59:26 - mmengine - INFO - Epoch(train) [26][ 60/1345] lr: 1.0000e-02 eta: 9:01:53 time: 0.1896 data_time: 0.0055 memory: 8327 grad_norm: 7.0135 loss: 3.4260 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0660 loss_aux: 1.3600 2023/02/17 13:59:30 - mmengine - INFO - Epoch(train) [26][ 80/1345] lr: 1.0000e-02 eta: 9:01:49 time: 0.1899 data_time: 0.0057 memory: 8327 grad_norm: 6.9763 loss: 3.7808 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2709 loss_aux: 1.5098 2023/02/17 13:59:34 - mmengine - INFO - Epoch(train) [26][ 100/1345] lr: 1.0000e-02 eta: 9:01:45 time: 0.1889 data_time: 0.0059 memory: 8327 grad_norm: 6.9392 loss: 3.5823 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1360 loss_aux: 1.4463 2023/02/17 13:59:38 - mmengine - INFO - Epoch(train) [26][ 120/1345] lr: 1.0000e-02 eta: 9:01:40 time: 0.1900 data_time: 0.0057 memory: 8327 grad_norm: 7.2892 loss: 3.5976 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1867 loss_aux: 1.4109 2023/02/17 13:59:41 - mmengine - INFO - Epoch(train) [26][ 140/1345] lr: 1.0000e-02 eta: 9:01:36 time: 0.1894 data_time: 0.0064 memory: 8327 grad_norm: 7.4832 loss: 3.3650 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9983 loss_aux: 1.3667 2023/02/17 13:59:45 - mmengine - INFO - Epoch(train) [26][ 160/1345] lr: 1.0000e-02 eta: 9:01:32 time: 0.1885 data_time: 0.0056 memory: 8327 grad_norm: 7.0347 loss: 3.9818 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4670 loss_aux: 1.5148 2023/02/17 13:59:49 - mmengine - INFO - Epoch(train) [26][ 180/1345] lr: 1.0000e-02 eta: 9:01:28 time: 0.1888 data_time: 0.0055 memory: 8327 grad_norm: 7.2015 loss: 3.7011 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2504 loss_aux: 1.4507 2023/02/17 13:59:53 - mmengine - INFO - Epoch(train) [26][ 200/1345] lr: 1.0000e-02 eta: 9:01:23 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.0762 loss: 3.5923 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2246 loss_aux: 1.3677 2023/02/17 13:59:57 - mmengine - INFO - Epoch(train) [26][ 220/1345] lr: 1.0000e-02 eta: 9:01:19 time: 0.1885 data_time: 0.0055 memory: 8327 grad_norm: 7.2560 loss: 3.5058 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0985 loss_aux: 1.4073 2023/02/17 14:00:00 - mmengine - INFO - Epoch(train) [26][ 240/1345] lr: 1.0000e-02 eta: 9:01:14 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.3173 loss: 3.9128 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.4326 loss_aux: 1.4802 2023/02/17 14:00:04 - mmengine - INFO - Epoch(train) [26][ 260/1345] lr: 1.0000e-02 eta: 9:01:10 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.2871 loss: 3.5515 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.1379 loss_aux: 1.4136 2023/02/17 14:00:08 - mmengine - INFO - Epoch(train) [26][ 280/1345] lr: 1.0000e-02 eta: 9:01:06 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.1972 loss: 4.1048 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5945 loss_aux: 1.5102 2023/02/17 14:00:12 - mmengine - INFO - Epoch(train) [26][ 300/1345] lr: 1.0000e-02 eta: 9:01:02 time: 0.1894 data_time: 0.0055 memory: 8327 grad_norm: 7.2739 loss: 3.4784 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1357 loss_aux: 1.3427 2023/02/17 14:00:16 - mmengine - INFO - Epoch(train) [26][ 320/1345] lr: 1.0000e-02 eta: 9:01:00 time: 0.2193 data_time: 0.0356 memory: 8327 grad_norm: 7.3744 loss: 3.5464 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1118 loss_aux: 1.4346 2023/02/17 14:00:20 - mmengine - INFO - Epoch(train) [26][ 340/1345] lr: 1.0000e-02 eta: 9:00:56 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.4532 loss: 3.8808 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3603 loss_aux: 1.5205 2023/02/17 14:00:24 - mmengine - INFO - Epoch(train) [26][ 360/1345] lr: 1.0000e-02 eta: 9:00:52 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.1876 loss: 4.0224 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5054 loss_aux: 1.5170 2023/02/17 14:00:26 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:00:27 - mmengine - INFO - Epoch(train) [26][ 380/1345] lr: 1.0000e-02 eta: 9:00:47 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 7.0066 loss: 3.7952 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.3293 loss_aux: 1.4659 2023/02/17 14:00:31 - mmengine - INFO - Epoch(train) [26][ 400/1345] lr: 1.0000e-02 eta: 9:00:43 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.1913 loss: 3.8245 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3581 loss_aux: 1.4665 2023/02/17 14:00:35 - mmengine - INFO - Epoch(train) [26][ 420/1345] lr: 1.0000e-02 eta: 9:00:39 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.1166 loss: 3.5889 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1887 loss_aux: 1.4001 2023/02/17 14:00:39 - mmengine - INFO - Epoch(train) [26][ 440/1345] lr: 1.0000e-02 eta: 9:00:34 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.1583 loss: 4.0014 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4786 loss_aux: 1.5228 2023/02/17 14:00:42 - mmengine - INFO - Epoch(train) [26][ 460/1345] lr: 1.0000e-02 eta: 9:00:30 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 7.1748 loss: 3.6151 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2204 loss_aux: 1.3947 2023/02/17 14:00:46 - mmengine - INFO - Epoch(train) [26][ 480/1345] lr: 1.0000e-02 eta: 9:00:26 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.2880 loss: 3.9901 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4524 loss_aux: 1.5378 2023/02/17 14:00:50 - mmengine - INFO - Epoch(train) [26][ 500/1345] lr: 1.0000e-02 eta: 9:00:21 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.3619 loss: 3.6349 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2031 loss_aux: 1.4318 2023/02/17 14:00:54 - mmengine - INFO - Epoch(train) [26][ 520/1345] lr: 1.0000e-02 eta: 9:00:17 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.3466 loss: 3.5316 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1151 loss_aux: 1.4165 2023/02/17 14:00:58 - mmengine - INFO - Epoch(train) [26][ 540/1345] lr: 1.0000e-02 eta: 9:00:13 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.1681 loss: 4.1764 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5856 loss_aux: 1.5908 2023/02/17 14:01:01 - mmengine - INFO - Epoch(train) [26][ 560/1345] lr: 1.0000e-02 eta: 9:00:09 time: 0.1912 data_time: 0.0071 memory: 8327 grad_norm: 7.2235 loss: 3.8956 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4032 loss_aux: 1.4924 2023/02/17 14:01:05 - mmengine - INFO - Epoch(train) [26][ 580/1345] lr: 1.0000e-02 eta: 9:00:04 time: 0.1885 data_time: 0.0057 memory: 8327 grad_norm: 7.2569 loss: 3.9072 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4504 loss_aux: 1.4567 2023/02/17 14:01:09 - mmengine - INFO - Epoch(train) [26][ 600/1345] lr: 1.0000e-02 eta: 9:00:00 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.2972 loss: 3.8572 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3068 loss_aux: 1.5504 2023/02/17 14:01:13 - mmengine - INFO - Epoch(train) [26][ 620/1345] lr: 1.0000e-02 eta: 8:59:56 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.2557 loss: 4.1110 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5712 loss_aux: 1.5399 2023/02/17 14:01:17 - mmengine - INFO - Epoch(train) [26][ 640/1345] lr: 1.0000e-02 eta: 8:59:51 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.1880 loss: 3.9994 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4263 loss_aux: 1.5730 2023/02/17 14:01:20 - mmengine - INFO - Epoch(train) [26][ 660/1345] lr: 1.0000e-02 eta: 8:59:47 time: 0.1908 data_time: 0.0066 memory: 8327 grad_norm: 7.2329 loss: 3.8287 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3864 loss_aux: 1.4423 2023/02/17 14:01:24 - mmengine - INFO - Epoch(train) [26][ 680/1345] lr: 1.0000e-02 eta: 8:59:43 time: 0.1885 data_time: 0.0052 memory: 8327 grad_norm: 6.9443 loss: 3.8544 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3915 loss_aux: 1.4629 2023/02/17 14:01:28 - mmengine - INFO - Epoch(train) [26][ 700/1345] lr: 1.0000e-02 eta: 8:59:39 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.3975 loss: 3.9463 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4380 loss_aux: 1.5083 2023/02/17 14:01:32 - mmengine - INFO - Epoch(train) [26][ 720/1345] lr: 1.0000e-02 eta: 8:59:34 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.3195 loss: 3.9647 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4304 loss_aux: 1.5343 2023/02/17 14:01:35 - mmengine - INFO - Epoch(train) [26][ 740/1345] lr: 1.0000e-02 eta: 8:59:30 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.0402 loss: 3.5429 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1567 loss_aux: 1.3863 2023/02/17 14:01:39 - mmengine - INFO - Epoch(train) [26][ 760/1345] lr: 1.0000e-02 eta: 8:59:26 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.2622 loss: 3.7666 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3009 loss_aux: 1.4657 2023/02/17 14:01:43 - mmengine - INFO - Epoch(train) [26][ 780/1345] lr: 1.0000e-02 eta: 8:59:21 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.3725 loss: 3.9535 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4123 loss_aux: 1.5412 2023/02/17 14:01:47 - mmengine - INFO - Epoch(train) [26][ 800/1345] lr: 1.0000e-02 eta: 8:59:17 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.2386 loss: 3.9673 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4806 loss_aux: 1.4867 2023/02/17 14:01:51 - mmengine - INFO - Epoch(train) [26][ 820/1345] lr: 1.0000e-02 eta: 8:59:13 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 6.8606 loss: 3.7126 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2774 loss_aux: 1.4352 2023/02/17 14:01:54 - mmengine - INFO - Epoch(train) [26][ 840/1345] lr: 1.0000e-02 eta: 8:59:08 time: 0.1889 data_time: 0.0059 memory: 8327 grad_norm: 7.0390 loss: 3.6702 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.1920 loss_aux: 1.4782 2023/02/17 14:01:58 - mmengine - INFO - Epoch(train) [26][ 860/1345] lr: 1.0000e-02 eta: 8:59:04 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.2793 loss: 3.9075 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3924 loss_aux: 1.5151 2023/02/17 14:02:02 - mmengine - INFO - Epoch(train) [26][ 880/1345] lr: 1.0000e-02 eta: 8:59:00 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.1738 loss: 3.7854 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3570 loss_aux: 1.4284 2023/02/17 14:02:06 - mmengine - INFO - Epoch(train) [26][ 900/1345] lr: 1.0000e-02 eta: 8:58:55 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.0904 loss: 3.8497 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3698 loss_aux: 1.4800 2023/02/17 14:02:10 - mmengine - INFO - Epoch(train) [26][ 920/1345] lr: 1.0000e-02 eta: 8:58:51 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.2326 loss: 4.1482 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5884 loss_aux: 1.5598 2023/02/17 14:02:13 - mmengine - INFO - Epoch(train) [26][ 940/1345] lr: 1.0000e-02 eta: 8:58:47 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.1140 loss: 3.2357 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9359 loss_aux: 1.2998 2023/02/17 14:02:17 - mmengine - INFO - Epoch(train) [26][ 960/1345] lr: 1.0000e-02 eta: 8:58:43 time: 0.1898 data_time: 0.0054 memory: 8327 grad_norm: 7.1817 loss: 3.2378 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 1.9271 loss_aux: 1.3107 2023/02/17 14:02:21 - mmengine - INFO - Epoch(train) [26][ 980/1345] lr: 1.0000e-02 eta: 8:58:39 time: 0.1905 data_time: 0.0057 memory: 8327 grad_norm: 7.3876 loss: 3.6630 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2380 loss_aux: 1.4250 2023/02/17 14:02:25 - mmengine - INFO - Epoch(train) [26][1000/1345] lr: 1.0000e-02 eta: 8:58:34 time: 0.1894 data_time: 0.0063 memory: 8327 grad_norm: 7.3638 loss: 3.5254 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.1435 loss_aux: 1.3820 2023/02/17 14:02:28 - mmengine - INFO - Epoch(train) [26][1020/1345] lr: 1.0000e-02 eta: 8:58:30 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 7.1838 loss: 3.7002 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2729 loss_aux: 1.4273 2023/02/17 14:02:32 - mmengine - INFO - Epoch(train) [26][1040/1345] lr: 1.0000e-02 eta: 8:58:26 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.3018 loss: 3.8967 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4148 loss_aux: 1.4819 2023/02/17 14:02:36 - mmengine - INFO - Epoch(train) [26][1060/1345] lr: 1.0000e-02 eta: 8:58:21 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 7.1097 loss: 3.9604 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.4401 loss_aux: 1.5203 2023/02/17 14:02:40 - mmengine - INFO - Epoch(train) [26][1080/1345] lr: 1.0000e-02 eta: 8:58:17 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.0502 loss: 3.5753 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1760 loss_aux: 1.3993 2023/02/17 14:02:44 - mmengine - INFO - Epoch(train) [26][1100/1345] lr: 1.0000e-02 eta: 8:58:13 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.0379 loss: 3.6537 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2001 loss_aux: 1.4535 2023/02/17 14:02:47 - mmengine - INFO - Epoch(train) [26][1120/1345] lr: 1.0000e-02 eta: 8:58:09 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.0501 loss: 3.8360 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.3588 loss_aux: 1.4772 2023/02/17 14:02:51 - mmengine - INFO - Epoch(train) [26][1140/1345] lr: 1.0000e-02 eta: 8:58:04 time: 0.1898 data_time: 0.0066 memory: 8327 grad_norm: 7.2229 loss: 3.5349 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.1226 loss_aux: 1.4123 2023/02/17 14:02:55 - mmengine - INFO - Epoch(train) [26][1160/1345] lr: 1.0000e-02 eta: 8:58:00 time: 0.1890 data_time: 0.0060 memory: 8327 grad_norm: 7.1168 loss: 3.6656 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2008 loss_aux: 1.4649 2023/02/17 14:02:59 - mmengine - INFO - Epoch(train) [26][1180/1345] lr: 1.0000e-02 eta: 8:57:56 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.2671 loss: 3.8670 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3667 loss_aux: 1.5003 2023/02/17 14:03:03 - mmengine - INFO - Epoch(train) [26][1200/1345] lr: 1.0000e-02 eta: 8:57:52 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 7.0790 loss: 3.7473 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.2898 loss_aux: 1.4575 2023/02/17 14:03:06 - mmengine - INFO - Epoch(train) [26][1220/1345] lr: 1.0000e-02 eta: 8:57:47 time: 0.1893 data_time: 0.0056 memory: 8327 grad_norm: 7.2225 loss: 3.5706 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1611 loss_aux: 1.4095 2023/02/17 14:03:10 - mmengine - INFO - Epoch(train) [26][1240/1345] lr: 1.0000e-02 eta: 8:57:43 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.4487 loss: 3.4011 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0661 loss_aux: 1.3350 2023/02/17 14:03:14 - mmengine - INFO - Epoch(train) [26][1260/1345] lr: 1.0000e-02 eta: 8:57:39 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.1776 loss: 4.1629 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5351 loss_aux: 1.6278 2023/02/17 14:03:18 - mmengine - INFO - Epoch(train) [26][1280/1345] lr: 1.0000e-02 eta: 8:57:35 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.1379 loss: 3.9956 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5123 loss_aux: 1.4833 2023/02/17 14:03:21 - mmengine - INFO - Epoch(train) [26][1300/1345] lr: 1.0000e-02 eta: 8:57:30 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.2837 loss: 4.0435 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5143 loss_aux: 1.5292 2023/02/17 14:03:25 - mmengine - INFO - Epoch(train) [26][1320/1345] lr: 1.0000e-02 eta: 8:57:26 time: 0.1895 data_time: 0.0066 memory: 8327 grad_norm: 6.9632 loss: 3.8230 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3504 loss_aux: 1.4726 2023/02/17 14:03:29 - mmengine - INFO - Epoch(train) [26][1340/1345] lr: 1.0000e-02 eta: 8:57:22 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.1860 loss: 4.1495 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5719 loss_aux: 1.5775 2023/02/17 14:03:30 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:03:30 - mmengine - INFO - Epoch(train) [26][1345/1345] lr: 1.0000e-02 eta: 8:57:20 time: 0.1828 data_time: 0.0060 memory: 8327 grad_norm: 7.0674 loss: 4.3229 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.7013 loss_aux: 1.6216 2023/02/17 14:03:30 - mmengine - INFO - Saving checkpoint at 26 epochs 2023/02/17 14:03:37 - mmengine - INFO - Epoch(train) [27][ 20/1345] lr: 1.0000e-02 eta: 8:57:18 time: 0.2100 data_time: 0.0187 memory: 8327 grad_norm: 7.0736 loss: 4.0050 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4583 loss_aux: 1.5467 2023/02/17 14:03:39 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:03:41 - mmengine - INFO - Epoch(train) [27][ 40/1345] lr: 1.0000e-02 eta: 8:57:14 time: 0.1906 data_time: 0.0052 memory: 8327 grad_norm: 7.0543 loss: 3.7331 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2776 loss_aux: 1.4555 2023/02/17 14:03:44 - mmengine - INFO - Epoch(train) [27][ 60/1345] lr: 1.0000e-02 eta: 8:57:09 time: 0.1900 data_time: 0.0056 memory: 8327 grad_norm: 7.0679 loss: 3.8294 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3639 loss_aux: 1.4655 2023/02/17 14:03:48 - mmengine - INFO - Epoch(train) [27][ 80/1345] lr: 1.0000e-02 eta: 8:57:05 time: 0.1888 data_time: 0.0055 memory: 8327 grad_norm: 7.1202 loss: 3.9844 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4478 loss_aux: 1.5366 2023/02/17 14:03:52 - mmengine - INFO - Epoch(train) [27][ 100/1345] lr: 1.0000e-02 eta: 8:57:01 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 6.9475 loss: 3.3787 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0659 loss_aux: 1.3128 2023/02/17 14:03:56 - mmengine - INFO - Epoch(train) [27][ 120/1345] lr: 1.0000e-02 eta: 8:56:57 time: 0.1901 data_time: 0.0058 memory: 8327 grad_norm: 7.0024 loss: 3.6322 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1997 loss_aux: 1.4326 2023/02/17 14:04:00 - mmengine - INFO - Epoch(train) [27][ 140/1345] lr: 1.0000e-02 eta: 8:56:53 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.0987 loss: 3.6426 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2477 loss_aux: 1.3949 2023/02/17 14:04:03 - mmengine - INFO - Epoch(train) [27][ 160/1345] lr: 1.0000e-02 eta: 8:56:48 time: 0.1900 data_time: 0.0055 memory: 8327 grad_norm: 7.2442 loss: 4.1156 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5350 loss_aux: 1.5806 2023/02/17 14:04:07 - mmengine - INFO - Epoch(train) [27][ 180/1345] lr: 1.0000e-02 eta: 8:56:44 time: 0.1906 data_time: 0.0057 memory: 8327 grad_norm: 7.2254 loss: 4.0465 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4782 loss_aux: 1.5683 2023/02/17 14:04:11 - mmengine - INFO - Epoch(train) [27][ 200/1345] lr: 1.0000e-02 eta: 8:56:40 time: 0.1896 data_time: 0.0065 memory: 8327 grad_norm: 7.0339 loss: 3.7345 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2468 loss_aux: 1.4876 2023/02/17 14:04:15 - mmengine - INFO - Epoch(train) [27][ 220/1345] lr: 1.0000e-02 eta: 8:56:36 time: 0.1898 data_time: 0.0069 memory: 8327 grad_norm: 7.4715 loss: 3.8720 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3528 loss_aux: 1.5192 2023/02/17 14:04:18 - mmengine - INFO - Epoch(train) [27][ 240/1345] lr: 1.0000e-02 eta: 8:56:32 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.4190 loss: 3.9876 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5016 loss_aux: 1.4860 2023/02/17 14:04:22 - mmengine - INFO - Epoch(train) [27][ 260/1345] lr: 1.0000e-02 eta: 8:56:27 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 7.1284 loss: 3.8446 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3590 loss_aux: 1.4856 2023/02/17 14:04:26 - mmengine - INFO - Epoch(train) [27][ 280/1345] lr: 1.0000e-02 eta: 8:56:23 time: 0.1888 data_time: 0.0059 memory: 8327 grad_norm: 7.2029 loss: 3.6942 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2694 loss_aux: 1.4247 2023/02/17 14:04:30 - mmengine - INFO - Epoch(train) [27][ 300/1345] lr: 1.0000e-02 eta: 8:56:19 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.3513 loss: 3.2981 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9543 loss_aux: 1.3438 2023/02/17 14:04:34 - mmengine - INFO - Epoch(train) [27][ 320/1345] lr: 1.0000e-02 eta: 8:56:14 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.3039 loss: 3.7126 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2990 loss_aux: 1.4136 2023/02/17 14:04:37 - mmengine - INFO - Epoch(train) [27][ 340/1345] lr: 1.0000e-02 eta: 8:56:10 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.1146 loss: 3.5093 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0698 loss_aux: 1.4395 2023/02/17 14:04:41 - mmengine - INFO - Epoch(train) [27][ 360/1345] lr: 1.0000e-02 eta: 8:56:06 time: 0.1895 data_time: 0.0064 memory: 8327 grad_norm: 7.3667 loss: 3.4098 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.0338 loss_aux: 1.3760 2023/02/17 14:04:45 - mmengine - INFO - Epoch(train) [27][ 380/1345] lr: 1.0000e-02 eta: 8:56:02 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.3477 loss: 3.6598 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2184 loss_aux: 1.4414 2023/02/17 14:04:49 - mmengine - INFO - Epoch(train) [27][ 400/1345] lr: 1.0000e-02 eta: 8:55:57 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.5343 loss: 3.9565 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4519 loss_aux: 1.5045 2023/02/17 14:04:53 - mmengine - INFO - Epoch(train) [27][ 420/1345] lr: 1.0000e-02 eta: 8:55:53 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.2674 loss: 3.8428 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3130 loss_aux: 1.5298 2023/02/17 14:04:56 - mmengine - INFO - Epoch(train) [27][ 440/1345] lr: 1.0000e-02 eta: 8:55:49 time: 0.1885 data_time: 0.0056 memory: 8327 grad_norm: 7.3889 loss: 4.0907 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5697 loss_aux: 1.5210 2023/02/17 14:05:00 - mmengine - INFO - Epoch(train) [27][ 460/1345] lr: 1.0000e-02 eta: 8:55:45 time: 0.1888 data_time: 0.0059 memory: 8327 grad_norm: 7.4161 loss: 4.1840 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6089 loss_aux: 1.5752 2023/02/17 14:05:04 - mmengine - INFO - Epoch(train) [27][ 480/1345] lr: 1.0000e-02 eta: 8:55:40 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.2212 loss: 3.4448 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0844 loss_aux: 1.3604 2023/02/17 14:05:08 - mmengine - INFO - Epoch(train) [27][ 500/1345] lr: 1.0000e-02 eta: 8:55:36 time: 0.1885 data_time: 0.0056 memory: 8327 grad_norm: 7.3513 loss: 3.8952 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3829 loss_aux: 1.5124 2023/02/17 14:05:12 - mmengine - INFO - Epoch(train) [27][ 520/1345] lr: 1.0000e-02 eta: 8:55:33 time: 0.1990 data_time: 0.0156 memory: 8327 grad_norm: 7.3073 loss: 3.9129 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4484 loss_aux: 1.4645 2023/02/17 14:05:15 - mmengine - INFO - Epoch(train) [27][ 540/1345] lr: 1.0000e-02 eta: 8:55:28 time: 0.1886 data_time: 0.0058 memory: 8327 grad_norm: 7.3031 loss: 3.3778 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0402 loss_aux: 1.3376 2023/02/17 14:05:19 - mmengine - INFO - Epoch(train) [27][ 560/1345] lr: 1.0000e-02 eta: 8:55:24 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.0549 loss: 3.6758 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2048 loss_aux: 1.4710 2023/02/17 14:05:23 - mmengine - INFO - Epoch(train) [27][ 580/1345] lr: 1.0000e-02 eta: 8:55:20 time: 0.1885 data_time: 0.0058 memory: 8327 grad_norm: 7.2005 loss: 3.6708 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2488 loss_aux: 1.4220 2023/02/17 14:05:27 - mmengine - INFO - Epoch(train) [27][ 600/1345] lr: 1.0000e-02 eta: 8:55:15 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 6.9452 loss: 3.1820 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9191 loss_aux: 1.2630 2023/02/17 14:05:31 - mmengine - INFO - Epoch(train) [27][ 620/1345] lr: 1.0000e-02 eta: 8:55:11 time: 0.1890 data_time: 0.0060 memory: 8327 grad_norm: 7.1322 loss: 3.5037 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1335 loss_aux: 1.3702 2023/02/17 14:05:34 - mmengine - INFO - Epoch(train) [27][ 640/1345] lr: 1.0000e-02 eta: 8:55:07 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.2696 loss: 3.8105 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3862 loss_aux: 1.4243 2023/02/17 14:05:38 - mmengine - INFO - Epoch(train) [27][ 660/1345] lr: 1.0000e-02 eta: 8:55:03 time: 0.1893 data_time: 0.0064 memory: 8327 grad_norm: 7.4021 loss: 4.1146 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5516 loss_aux: 1.5630 2023/02/17 14:05:42 - mmengine - INFO - Epoch(train) [27][ 680/1345] lr: 1.0000e-02 eta: 8:54:58 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.4009 loss: 3.7316 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2538 loss_aux: 1.4778 2023/02/17 14:05:46 - mmengine - INFO - Epoch(train) [27][ 700/1345] lr: 1.0000e-02 eta: 8:54:54 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 7.2881 loss: 3.2889 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9569 loss_aux: 1.3320 2023/02/17 14:05:49 - mmengine - INFO - Epoch(train) [27][ 720/1345] lr: 1.0000e-02 eta: 8:54:50 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 7.2205 loss: 3.5909 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1694 loss_aux: 1.4215 2023/02/17 14:05:53 - mmengine - INFO - Epoch(train) [27][ 740/1345] lr: 1.0000e-02 eta: 8:54:46 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.1857 loss: 3.9627 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4501 loss_aux: 1.5126 2023/02/17 14:05:57 - mmengine - INFO - Epoch(train) [27][ 760/1345] lr: 1.0000e-02 eta: 8:54:41 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.1542 loss: 3.7833 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3821 loss_aux: 1.4012 2023/02/17 14:06:01 - mmengine - INFO - Epoch(train) [27][ 780/1345] lr: 1.0000e-02 eta: 8:54:37 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.2195 loss: 3.6410 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2756 loss_aux: 1.3654 2023/02/17 14:06:05 - mmengine - INFO - Epoch(train) [27][ 800/1345] lr: 1.0000e-02 eta: 8:54:33 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.3051 loss: 4.1495 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5089 loss_aux: 1.6407 2023/02/17 14:06:09 - mmengine - INFO - Epoch(train) [27][ 820/1345] lr: 1.0000e-02 eta: 8:54:30 time: 0.2090 data_time: 0.0258 memory: 8327 grad_norm: 7.2882 loss: 4.0525 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5008 loss_aux: 1.5516 2023/02/17 14:06:13 - mmengine - INFO - Epoch(train) [27][ 840/1345] lr: 1.0000e-02 eta: 8:54:26 time: 0.1902 data_time: 0.0056 memory: 8327 grad_norm: 7.1627 loss: 3.7223 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2796 loss_aux: 1.4427 2023/02/17 14:06:16 - mmengine - INFO - Epoch(train) [27][ 860/1345] lr: 1.0000e-02 eta: 8:54:22 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 7.4023 loss: 4.0258 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4721 loss_aux: 1.5538 2023/02/17 14:06:20 - mmengine - INFO - Epoch(train) [27][ 880/1345] lr: 1.0000e-02 eta: 8:54:18 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.1799 loss: 3.8092 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2782 loss_aux: 1.5311 2023/02/17 14:06:24 - mmengine - INFO - Epoch(train) [27][ 900/1345] lr: 1.0000e-02 eta: 8:54:13 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.2940 loss: 3.7129 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3060 loss_aux: 1.4070 2023/02/17 14:06:28 - mmengine - INFO - Epoch(train) [27][ 920/1345] lr: 1.0000e-02 eta: 8:54:09 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.1836 loss: 3.8391 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3606 loss_aux: 1.4785 2023/02/17 14:06:31 - mmengine - INFO - Epoch(train) [27][ 940/1345] lr: 1.0000e-02 eta: 8:54:05 time: 0.1890 data_time: 0.0059 memory: 8327 grad_norm: 7.3214 loss: 3.5514 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2096 loss_aux: 1.3418 2023/02/17 14:06:35 - mmengine - INFO - Epoch(train) [27][ 960/1345] lr: 1.0000e-02 eta: 8:54:01 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.2457 loss: 3.7065 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2275 loss_aux: 1.4790 2023/02/17 14:06:39 - mmengine - INFO - Epoch(train) [27][ 980/1345] lr: 1.0000e-02 eta: 8:53:57 time: 0.1904 data_time: 0.0066 memory: 8327 grad_norm: 7.2428 loss: 3.8858 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3860 loss_aux: 1.4998 2023/02/17 14:06:43 - mmengine - INFO - Epoch(train) [27][1000/1345] lr: 1.0000e-02 eta: 8:53:52 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.0385 loss: 3.5631 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1424 loss_aux: 1.4207 2023/02/17 14:06:47 - mmengine - INFO - Epoch(train) [27][1020/1345] lr: 1.0000e-02 eta: 8:53:48 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 7.0385 loss: 3.6507 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.2082 loss_aux: 1.4425 2023/02/17 14:06:49 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:06:50 - mmengine - INFO - Epoch(train) [27][1040/1345] lr: 1.0000e-02 eta: 8:53:44 time: 0.1904 data_time: 0.0071 memory: 8327 grad_norm: 7.3386 loss: 3.7700 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2990 loss_aux: 1.4710 2023/02/17 14:06:54 - mmengine - INFO - Epoch(train) [27][1060/1345] lr: 1.0000e-02 eta: 8:53:40 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.1396 loss: 3.3838 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0306 loss_aux: 1.3532 2023/02/17 14:06:58 - mmengine - INFO - Epoch(train) [27][1080/1345] lr: 1.0000e-02 eta: 8:53:35 time: 0.1889 data_time: 0.0059 memory: 8327 grad_norm: 7.1515 loss: 3.7710 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.2959 loss_aux: 1.4751 2023/02/17 14:07:02 - mmengine - INFO - Epoch(train) [27][1100/1345] lr: 1.0000e-02 eta: 8:53:31 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.2066 loss: 3.7336 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2637 loss_aux: 1.4700 2023/02/17 14:07:06 - mmengine - INFO - Epoch(train) [27][1120/1345] lr: 1.0000e-02 eta: 8:53:27 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.2450 loss: 3.8184 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3788 loss_aux: 1.4396 2023/02/17 14:07:09 - mmengine - INFO - Epoch(train) [27][1140/1345] lr: 1.0000e-02 eta: 8:53:23 time: 0.1895 data_time: 0.0056 memory: 8327 grad_norm: 7.3866 loss: 4.1618 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.6377 loss_aux: 1.5241 2023/02/17 14:07:13 - mmengine - INFO - Epoch(train) [27][1160/1345] lr: 1.0000e-02 eta: 8:53:19 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.2155 loss: 3.6355 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1927 loss_aux: 1.4428 2023/02/17 14:07:17 - mmengine - INFO - Epoch(train) [27][1180/1345] lr: 1.0000e-02 eta: 8:53:14 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.1296 loss: 3.9533 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4209 loss_aux: 1.5324 2023/02/17 14:07:21 - mmengine - INFO - Epoch(train) [27][1200/1345] lr: 1.0000e-02 eta: 8:53:10 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 7.2627 loss: 3.5718 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1955 loss_aux: 1.3763 2023/02/17 14:07:25 - mmengine - INFO - Epoch(train) [27][1220/1345] lr: 1.0000e-02 eta: 8:53:07 time: 0.1990 data_time: 0.0156 memory: 8327 grad_norm: 7.2821 loss: 3.5518 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1526 loss_aux: 1.3992 2023/02/17 14:07:28 - mmengine - INFO - Epoch(train) [27][1240/1345] lr: 1.0000e-02 eta: 8:53:02 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.0619 loss: 3.7334 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3539 loss_aux: 1.3795 2023/02/17 14:07:32 - mmengine - INFO - Epoch(train) [27][1260/1345] lr: 1.0000e-02 eta: 8:52:58 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.1669 loss: 4.2831 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6721 loss_aux: 1.6111 2023/02/17 14:07:36 - mmengine - INFO - Epoch(train) [27][1280/1345] lr: 1.0000e-02 eta: 8:52:54 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.2301 loss: 3.5570 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1365 loss_aux: 1.4206 2023/02/17 14:07:40 - mmengine - INFO - Epoch(train) [27][1300/1345] lr: 1.0000e-02 eta: 8:52:50 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.3234 loss: 3.7088 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.2501 loss_aux: 1.4588 2023/02/17 14:07:44 - mmengine - INFO - Epoch(train) [27][1320/1345] lr: 1.0000e-02 eta: 8:52:45 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.1604 loss: 3.8598 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3915 loss_aux: 1.4683 2023/02/17 14:07:47 - mmengine - INFO - Epoch(train) [27][1340/1345] lr: 1.0000e-02 eta: 8:52:41 time: 0.1888 data_time: 0.0060 memory: 8327 grad_norm: 7.4641 loss: 3.8245 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3282 loss_aux: 1.4963 2023/02/17 14:07:48 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:07:48 - mmengine - INFO - Epoch(train) [27][1345/1345] lr: 1.0000e-02 eta: 8:52:40 time: 0.1826 data_time: 0.0060 memory: 8327 grad_norm: 7.4700 loss: 3.9157 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.4217 loss_aux: 1.4939 2023/02/17 14:07:48 - mmengine - INFO - Saving checkpoint at 27 epochs 2023/02/17 14:07:55 - mmengine - INFO - Epoch(train) [28][ 20/1345] lr: 1.0000e-02 eta: 8:52:37 time: 0.2066 data_time: 0.0155 memory: 8327 grad_norm: 7.2749 loss: 3.9773 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4839 loss_aux: 1.4934 2023/02/17 14:07:59 - mmengine - INFO - Epoch(train) [28][ 40/1345] lr: 1.0000e-02 eta: 8:52:33 time: 0.1902 data_time: 0.0039 memory: 8327 grad_norm: 7.1238 loss: 3.2830 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9539 loss_aux: 1.3291 2023/02/17 14:08:02 - mmengine - INFO - Epoch(train) [28][ 60/1345] lr: 1.0000e-02 eta: 8:52:29 time: 0.1893 data_time: 0.0054 memory: 8327 grad_norm: 7.2865 loss: 4.1130 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5348 loss_aux: 1.5782 2023/02/17 14:08:06 - mmengine - INFO - Epoch(train) [28][ 80/1345] lr: 1.0000e-02 eta: 8:52:24 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.0678 loss: 3.7123 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3122 loss_aux: 1.4001 2023/02/17 14:08:10 - mmengine - INFO - Epoch(train) [28][ 100/1345] lr: 1.0000e-02 eta: 8:52:20 time: 0.1929 data_time: 0.0057 memory: 8327 grad_norm: 7.2558 loss: 3.9362 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4030 loss_aux: 1.5333 2023/02/17 14:08:14 - mmengine - INFO - Epoch(train) [28][ 120/1345] lr: 1.0000e-02 eta: 8:52:16 time: 0.1888 data_time: 0.0059 memory: 8327 grad_norm: 7.3297 loss: 3.6840 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2469 loss_aux: 1.4371 2023/02/17 14:08:18 - mmengine - INFO - Epoch(train) [28][ 140/1345] lr: 1.0000e-02 eta: 8:52:12 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.1061 loss: 3.6962 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2508 loss_aux: 1.4454 2023/02/17 14:08:21 - mmengine - INFO - Epoch(train) [28][ 160/1345] lr: 1.0000e-02 eta: 8:52:08 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.3367 loss: 3.5727 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1343 loss_aux: 1.4385 2023/02/17 14:08:25 - mmengine - INFO - Epoch(train) [28][ 180/1345] lr: 1.0000e-02 eta: 8:52:03 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 7.3955 loss: 3.6025 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1522 loss_aux: 1.4503 2023/02/17 14:08:29 - mmengine - INFO - Epoch(train) [28][ 200/1345] lr: 1.0000e-02 eta: 8:51:59 time: 0.1889 data_time: 0.0061 memory: 8327 grad_norm: 7.5461 loss: 3.7443 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2627 loss_aux: 1.4816 2023/02/17 14:08:33 - mmengine - INFO - Epoch(train) [28][ 220/1345] lr: 1.0000e-02 eta: 8:51:55 time: 0.1888 data_time: 0.0059 memory: 8327 grad_norm: 7.2248 loss: 3.8998 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4364 loss_aux: 1.4634 2023/02/17 14:08:37 - mmengine - INFO - Epoch(train) [28][ 240/1345] lr: 1.0000e-02 eta: 8:51:51 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.2577 loss: 3.7553 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3097 loss_aux: 1.4457 2023/02/17 14:08:40 - mmengine - INFO - Epoch(train) [28][ 260/1345] lr: 1.0000e-02 eta: 8:51:46 time: 0.1893 data_time: 0.0055 memory: 8327 grad_norm: 7.2050 loss: 3.9466 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4047 loss_aux: 1.5419 2023/02/17 14:08:44 - mmengine - INFO - Epoch(train) [28][ 280/1345] lr: 1.0000e-02 eta: 8:51:42 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.0680 loss: 3.8375 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3522 loss_aux: 1.4853 2023/02/17 14:08:48 - mmengine - INFO - Epoch(train) [28][ 300/1345] lr: 1.0000e-02 eta: 8:51:38 time: 0.1886 data_time: 0.0055 memory: 8327 grad_norm: 7.3881 loss: 3.7597 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3123 loss_aux: 1.4474 2023/02/17 14:08:52 - mmengine - INFO - Epoch(train) [28][ 320/1345] lr: 1.0000e-02 eta: 8:51:34 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.3252 loss: 3.5335 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1389 loss_aux: 1.3946 2023/02/17 14:08:55 - mmengine - INFO - Epoch(train) [28][ 340/1345] lr: 1.0000e-02 eta: 8:51:29 time: 0.1885 data_time: 0.0057 memory: 8327 grad_norm: 7.0588 loss: 3.5557 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1876 loss_aux: 1.3681 2023/02/17 14:08:59 - mmengine - INFO - Epoch(train) [28][ 360/1345] lr: 1.0000e-02 eta: 8:51:25 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.1327 loss: 3.6056 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2033 loss_aux: 1.4023 2023/02/17 14:09:03 - mmengine - INFO - Epoch(train) [28][ 380/1345] lr: 1.0000e-02 eta: 8:51:21 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.2667 loss: 3.7326 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2787 loss_aux: 1.4539 2023/02/17 14:09:07 - mmengine - INFO - Epoch(train) [28][ 400/1345] lr: 1.0000e-02 eta: 8:51:17 time: 0.1902 data_time: 0.0057 memory: 8327 grad_norm: 7.3166 loss: 4.0736 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5271 loss_aux: 1.5465 2023/02/17 14:09:11 - mmengine - INFO - Epoch(train) [28][ 420/1345] lr: 1.0000e-02 eta: 8:51:13 time: 0.1910 data_time: 0.0056 memory: 8327 grad_norm: 7.4072 loss: 3.7316 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2474 loss_aux: 1.4841 2023/02/17 14:09:14 - mmengine - INFO - Epoch(train) [28][ 440/1345] lr: 1.0000e-02 eta: 8:51:08 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.4413 loss: 3.9266 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4428 loss_aux: 1.4838 2023/02/17 14:09:18 - mmengine - INFO - Epoch(train) [28][ 460/1345] lr: 1.0000e-02 eta: 8:51:04 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.1273 loss: 3.5924 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1269 loss_aux: 1.4655 2023/02/17 14:09:22 - mmengine - INFO - Epoch(train) [28][ 480/1345] lr: 1.0000e-02 eta: 8:51:00 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.2914 loss: 3.4058 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0390 loss_aux: 1.3669 2023/02/17 14:09:26 - mmengine - INFO - Epoch(train) [28][ 500/1345] lr: 1.0000e-02 eta: 8:50:56 time: 0.1905 data_time: 0.0072 memory: 8327 grad_norm: 6.9999 loss: 3.8310 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3642 loss_aux: 1.4668 2023/02/17 14:09:30 - mmengine - INFO - Epoch(train) [28][ 520/1345] lr: 1.0000e-02 eta: 8:50:52 time: 0.1911 data_time: 0.0076 memory: 8327 grad_norm: 7.2189 loss: 3.7499 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3257 loss_aux: 1.4242 2023/02/17 14:09:33 - mmengine - INFO - Epoch(train) [28][ 540/1345] lr: 1.0000e-02 eta: 8:50:48 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 7.6146 loss: 4.0564 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4997 loss_aux: 1.5568 2023/02/17 14:09:37 - mmengine - INFO - Epoch(train) [28][ 560/1345] lr: 1.0000e-02 eta: 8:50:43 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.2809 loss: 3.8996 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.3827 loss_aux: 1.5169 2023/02/17 14:09:41 - mmengine - INFO - Epoch(train) [28][ 580/1345] lr: 1.0000e-02 eta: 8:50:39 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.1534 loss: 4.0372 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4875 loss_aux: 1.5497 2023/02/17 14:09:45 - mmengine - INFO - Epoch(train) [28][ 600/1345] lr: 1.0000e-02 eta: 8:50:35 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.1716 loss: 3.7227 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2593 loss_aux: 1.4634 2023/02/17 14:09:49 - mmengine - INFO - Epoch(train) [28][ 620/1345] lr: 1.0000e-02 eta: 8:50:31 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.5462 loss: 3.6824 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2796 loss_aux: 1.4028 2023/02/17 14:09:52 - mmengine - INFO - Epoch(train) [28][ 640/1345] lr: 1.0000e-02 eta: 8:50:26 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 7.3993 loss: 3.6793 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2666 loss_aux: 1.4127 2023/02/17 14:09:56 - mmengine - INFO - Epoch(train) [28][ 660/1345] lr: 1.0000e-02 eta: 8:50:22 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.3662 loss: 3.6433 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2329 loss_aux: 1.4104 2023/02/17 14:10:00 - mmengine - INFO - Epoch(train) [28][ 680/1345] lr: 1.0000e-02 eta: 8:50:18 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.2203 loss: 3.8137 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3554 loss_aux: 1.4582 2023/02/17 14:10:01 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:10:04 - mmengine - INFO - Epoch(train) [28][ 700/1345] lr: 1.0000e-02 eta: 8:50:14 time: 0.1906 data_time: 0.0057 memory: 8327 grad_norm: 7.1037 loss: 3.5761 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2022 loss_aux: 1.3739 2023/02/17 14:10:07 - mmengine - INFO - Epoch(train) [28][ 720/1345] lr: 1.0000e-02 eta: 8:50:10 time: 0.1888 data_time: 0.0060 memory: 8327 grad_norm: 7.1631 loss: 3.6579 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1976 loss_aux: 1.4603 2023/02/17 14:10:11 - mmengine - INFO - Epoch(train) [28][ 740/1345] lr: 1.0000e-02 eta: 8:50:05 time: 0.1898 data_time: 0.0061 memory: 8327 grad_norm: 7.2350 loss: 3.4396 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0886 loss_aux: 1.3510 2023/02/17 14:10:15 - mmengine - INFO - Epoch(train) [28][ 760/1345] lr: 1.0000e-02 eta: 8:50:01 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.2686 loss: 3.6400 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1958 loss_aux: 1.4442 2023/02/17 14:10:19 - mmengine - INFO - Epoch(train) [28][ 780/1345] lr: 1.0000e-02 eta: 8:49:57 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.2740 loss: 3.8297 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3938 loss_aux: 1.4360 2023/02/17 14:10:23 - mmengine - INFO - Epoch(train) [28][ 800/1345] lr: 1.0000e-02 eta: 8:49:56 time: 0.2292 data_time: 0.0460 memory: 8327 grad_norm: 7.2966 loss: 3.7492 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2794 loss_aux: 1.4698 2023/02/17 14:10:27 - mmengine - INFO - Epoch(train) [28][ 820/1345] lr: 1.0000e-02 eta: 8:49:52 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.4212 loss: 3.7035 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2508 loss_aux: 1.4527 2023/02/17 14:10:31 - mmengine - INFO - Epoch(train) [28][ 840/1345] lr: 1.0000e-02 eta: 8:49:48 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 7.0811 loss: 3.4532 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1274 loss_aux: 1.3257 2023/02/17 14:10:35 - mmengine - INFO - Epoch(train) [28][ 860/1345] lr: 1.0000e-02 eta: 8:49:44 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.4036 loss: 4.1063 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5309 loss_aux: 1.5754 2023/02/17 14:10:39 - mmengine - INFO - Epoch(train) [28][ 880/1345] lr: 1.0000e-02 eta: 8:49:39 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.2635 loss: 3.5039 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1274 loss_aux: 1.3764 2023/02/17 14:10:42 - mmengine - INFO - Epoch(train) [28][ 900/1345] lr: 1.0000e-02 eta: 8:49:35 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.4251 loss: 3.7489 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3460 loss_aux: 1.4029 2023/02/17 14:10:46 - mmengine - INFO - Epoch(train) [28][ 920/1345] lr: 1.0000e-02 eta: 8:49:31 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 7.2730 loss: 3.5192 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1127 loss_aux: 1.4064 2023/02/17 14:10:50 - mmengine - INFO - Epoch(train) [28][ 940/1345] lr: 1.0000e-02 eta: 8:49:27 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.2834 loss: 3.7452 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2718 loss_aux: 1.4734 2023/02/17 14:10:54 - mmengine - INFO - Epoch(train) [28][ 960/1345] lr: 1.0000e-02 eta: 8:49:22 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 7.3370 loss: 3.7859 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3582 loss_aux: 1.4278 2023/02/17 14:10:57 - mmengine - INFO - Epoch(train) [28][ 980/1345] lr: 1.0000e-02 eta: 8:49:18 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.4952 loss: 4.0984 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5593 loss_aux: 1.5391 2023/02/17 14:11:01 - mmengine - INFO - Epoch(train) [28][1000/1345] lr: 1.0000e-02 eta: 8:49:14 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.2571 loss: 3.7546 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2857 loss_aux: 1.4689 2023/02/17 14:11:05 - mmengine - INFO - Epoch(train) [28][1020/1345] lr: 1.0000e-02 eta: 8:49:10 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.2084 loss: 3.9542 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4597 loss_aux: 1.4945 2023/02/17 14:11:09 - mmengine - INFO - Epoch(train) [28][1040/1345] lr: 1.0000e-02 eta: 8:49:06 time: 0.1909 data_time: 0.0060 memory: 8327 grad_norm: 7.3142 loss: 3.7184 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2756 loss_aux: 1.4429 2023/02/17 14:11:13 - mmengine - INFO - Epoch(train) [28][1060/1345] lr: 1.0000e-02 eta: 8:49:02 time: 0.1907 data_time: 0.0057 memory: 8327 grad_norm: 7.2204 loss: 3.4071 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.0647 loss_aux: 1.3423 2023/02/17 14:11:16 - mmengine - INFO - Epoch(train) [28][1080/1345] lr: 1.0000e-02 eta: 8:48:57 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.4374 loss: 3.9027 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4562 loss_aux: 1.4465 2023/02/17 14:11:20 - mmengine - INFO - Epoch(train) [28][1100/1345] lr: 1.0000e-02 eta: 8:48:53 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.1786 loss: 3.6099 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1799 loss_aux: 1.4299 2023/02/17 14:11:24 - mmengine - INFO - Epoch(train) [28][1120/1345] lr: 1.0000e-02 eta: 8:48:49 time: 0.1897 data_time: 0.0064 memory: 8327 grad_norm: 7.2873 loss: 3.8456 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3585 loss_aux: 1.4872 2023/02/17 14:11:28 - mmengine - INFO - Epoch(train) [28][1140/1345] lr: 1.0000e-02 eta: 8:48:47 time: 0.2092 data_time: 0.0258 memory: 8327 grad_norm: 7.2625 loss: 3.4550 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0277 loss_aux: 1.4274 2023/02/17 14:11:32 - mmengine - INFO - Epoch(train) [28][1160/1345] lr: 1.0000e-02 eta: 8:48:42 time: 0.1888 data_time: 0.0059 memory: 8327 grad_norm: 7.1909 loss: 3.7915 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3708 loss_aux: 1.4206 2023/02/17 14:11:36 - mmengine - INFO - Epoch(train) [28][1180/1345] lr: 1.0000e-02 eta: 8:48:38 time: 0.1907 data_time: 0.0074 memory: 8327 grad_norm: 7.2308 loss: 3.8670 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3988 loss_aux: 1.4682 2023/02/17 14:11:40 - mmengine - INFO - Epoch(train) [28][1200/1345] lr: 1.0000e-02 eta: 8:48:34 time: 0.1912 data_time: 0.0076 memory: 8327 grad_norm: 7.3167 loss: 3.9468 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4822 loss_aux: 1.4646 2023/02/17 14:11:43 - mmengine - INFO - Epoch(train) [28][1220/1345] lr: 1.0000e-02 eta: 8:48:30 time: 0.1893 data_time: 0.0063 memory: 8327 grad_norm: 7.2178 loss: 3.5873 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2165 loss_aux: 1.3708 2023/02/17 14:11:47 - mmengine - INFO - Epoch(train) [28][1240/1345] lr: 1.0000e-02 eta: 8:48:26 time: 0.1886 data_time: 0.0058 memory: 8327 grad_norm: 7.1719 loss: 3.9496 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4230 loss_aux: 1.5266 2023/02/17 14:11:51 - mmengine - INFO - Epoch(train) [28][1260/1345] lr: 1.0000e-02 eta: 8:48:22 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.0655 loss: 3.6827 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2661 loss_aux: 1.4166 2023/02/17 14:11:55 - mmengine - INFO - Epoch(train) [28][1280/1345] lr: 1.0000e-02 eta: 8:48:17 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.3691 loss: 3.5798 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1656 loss_aux: 1.4142 2023/02/17 14:11:59 - mmengine - INFO - Epoch(train) [28][1300/1345] lr: 1.0000e-02 eta: 8:48:13 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.3008 loss: 3.6798 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2679 loss_aux: 1.4119 2023/02/17 14:12:02 - mmengine - INFO - Epoch(train) [28][1320/1345] lr: 1.0000e-02 eta: 8:48:09 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.3000 loss: 3.5754 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1850 loss_aux: 1.3904 2023/02/17 14:12:06 - mmengine - INFO - Epoch(train) [28][1340/1345] lr: 1.0000e-02 eta: 8:48:05 time: 0.1896 data_time: 0.0065 memory: 8327 grad_norm: 7.3826 loss: 3.7840 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.2908 loss_aux: 1.4933 2023/02/17 14:12:07 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:12:07 - mmengine - INFO - Epoch(train) [28][1345/1345] lr: 1.0000e-02 eta: 8:48:03 time: 0.1835 data_time: 0.0064 memory: 8327 grad_norm: 7.2818 loss: 3.9965 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 2.4410 loss_aux: 1.5554 2023/02/17 14:12:07 - mmengine - INFO - Saving checkpoint at 28 epochs 2023/02/17 14:12:14 - mmengine - INFO - Epoch(train) [29][ 20/1345] lr: 1.0000e-02 eta: 8:48:01 time: 0.2071 data_time: 0.0160 memory: 8327 grad_norm: 7.3602 loss: 3.7696 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2933 loss_aux: 1.4763 2023/02/17 14:12:18 - mmengine - INFO - Epoch(train) [29][ 40/1345] lr: 1.0000e-02 eta: 8:47:57 time: 0.1917 data_time: 0.0039 memory: 8327 grad_norm: 7.2464 loss: 3.5811 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1524 loss_aux: 1.4287 2023/02/17 14:12:21 - mmengine - INFO - Epoch(train) [29][ 60/1345] lr: 1.0000e-02 eta: 8:47:52 time: 0.1893 data_time: 0.0061 memory: 8327 grad_norm: 7.0746 loss: 3.1635 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9206 loss_aux: 1.2428 2023/02/17 14:12:25 - mmengine - INFO - Epoch(train) [29][ 80/1345] lr: 1.0000e-02 eta: 8:47:48 time: 0.1895 data_time: 0.0056 memory: 8327 grad_norm: 7.5596 loss: 3.6155 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1996 loss_aux: 1.4159 2023/02/17 14:12:29 - mmengine - INFO - Epoch(train) [29][ 100/1345] lr: 1.0000e-02 eta: 8:47:44 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 7.3942 loss: 3.5420 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1103 loss_aux: 1.4318 2023/02/17 14:12:33 - mmengine - INFO - Epoch(train) [29][ 120/1345] lr: 1.0000e-02 eta: 8:47:40 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.3240 loss: 3.5994 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2154 loss_aux: 1.3840 2023/02/17 14:12:37 - mmengine - INFO - Epoch(train) [29][ 140/1345] lr: 1.0000e-02 eta: 8:47:36 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 7.1001 loss: 3.5274 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1394 loss_aux: 1.3880 2023/02/17 14:12:40 - mmengine - INFO - Epoch(train) [29][ 160/1345] lr: 1.0000e-02 eta: 8:47:31 time: 0.1886 data_time: 0.0058 memory: 8327 grad_norm: 7.1132 loss: 3.8949 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4105 loss_aux: 1.4844 2023/02/17 14:12:44 - mmengine - INFO - Epoch(train) [29][ 180/1345] lr: 1.0000e-02 eta: 8:47:27 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.2913 loss: 4.0000 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4112 loss_aux: 1.5888 2023/02/17 14:12:48 - mmengine - INFO - Epoch(train) [29][ 200/1345] lr: 1.0000e-02 eta: 8:47:23 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.2378 loss: 3.6358 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2049 loss_aux: 1.4309 2023/02/17 14:12:52 - mmengine - INFO - Epoch(train) [29][ 220/1345] lr: 1.0000e-02 eta: 8:47:19 time: 0.1921 data_time: 0.0057 memory: 8327 grad_norm: 7.2098 loss: 4.0166 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5459 loss_aux: 1.4707 2023/02/17 14:12:55 - mmengine - INFO - Epoch(train) [29][ 240/1345] lr: 1.0000e-02 eta: 8:47:15 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 6.8231 loss: 3.6521 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2286 loss_aux: 1.4236 2023/02/17 14:12:59 - mmengine - INFO - Epoch(train) [29][ 260/1345] lr: 1.0000e-02 eta: 8:47:10 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.2992 loss: 3.4260 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1061 loss_aux: 1.3200 2023/02/17 14:13:03 - mmengine - INFO - Epoch(train) [29][ 280/1345] lr: 1.0000e-02 eta: 8:47:06 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.3684 loss: 3.6354 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1766 loss_aux: 1.4588 2023/02/17 14:13:07 - mmengine - INFO - Epoch(train) [29][ 300/1345] lr: 1.0000e-02 eta: 8:47:02 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.3758 loss: 3.7507 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3011 loss_aux: 1.4496 2023/02/17 14:13:11 - mmengine - INFO - Epoch(train) [29][ 320/1345] lr: 1.0000e-02 eta: 8:46:58 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.3465 loss: 3.9663 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4732 loss_aux: 1.4931 2023/02/17 14:13:14 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:13:14 - mmengine - INFO - Epoch(train) [29][ 340/1345] lr: 1.0000e-02 eta: 8:46:54 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.1616 loss: 3.5947 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1691 loss_aux: 1.4256 2023/02/17 14:13:18 - mmengine - INFO - Epoch(train) [29][ 360/1345] lr: 1.0000e-02 eta: 8:46:49 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.3471 loss: 3.8301 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3476 loss_aux: 1.4824 2023/02/17 14:13:22 - mmengine - INFO - Epoch(train) [29][ 380/1345] lr: 1.0000e-02 eta: 8:46:45 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.3745 loss: 3.6735 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2774 loss_aux: 1.3961 2023/02/17 14:13:26 - mmengine - INFO - Epoch(train) [29][ 400/1345] lr: 1.0000e-02 eta: 8:46:41 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.3100 loss: 3.5034 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0818 loss_aux: 1.4216 2023/02/17 14:13:29 - mmengine - INFO - Epoch(train) [29][ 420/1345] lr: 1.0000e-02 eta: 8:46:37 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.5915 loss: 4.0415 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4979 loss_aux: 1.5436 2023/02/17 14:13:33 - mmengine - INFO - Epoch(train) [29][ 440/1345] lr: 1.0000e-02 eta: 8:46:32 time: 0.1886 data_time: 0.0059 memory: 8327 grad_norm: 7.4317 loss: 3.8370 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.3310 loss_aux: 1.5060 2023/02/17 14:13:37 - mmengine - INFO - Epoch(train) [29][ 460/1345] lr: 1.0000e-02 eta: 8:46:28 time: 0.1892 data_time: 0.0064 memory: 8327 grad_norm: 7.3293 loss: 3.6899 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2358 loss_aux: 1.4542 2023/02/17 14:13:41 - mmengine - INFO - Epoch(train) [29][ 480/1345] lr: 1.0000e-02 eta: 8:46:24 time: 0.1889 data_time: 0.0060 memory: 8327 grad_norm: 7.2225 loss: 3.9200 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4403 loss_aux: 1.4797 2023/02/17 14:13:45 - mmengine - INFO - Epoch(train) [29][ 500/1345] lr: 1.0000e-02 eta: 8:46:20 time: 0.1894 data_time: 0.0063 memory: 8327 grad_norm: 7.2400 loss: 3.5478 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1501 loss_aux: 1.3977 2023/02/17 14:13:48 - mmengine - INFO - Epoch(train) [29][ 520/1345] lr: 1.0000e-02 eta: 8:46:16 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.0974 loss: 3.5018 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1198 loss_aux: 1.3820 2023/02/17 14:13:52 - mmengine - INFO - Epoch(train) [29][ 540/1345] lr: 1.0000e-02 eta: 8:46:11 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.3057 loss: 3.6762 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2870 loss_aux: 1.3891 2023/02/17 14:13:56 - mmengine - INFO - Epoch(train) [29][ 560/1345] lr: 1.0000e-02 eta: 8:46:07 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.3805 loss: 3.4023 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.0706 loss_aux: 1.3317 2023/02/17 14:14:00 - mmengine - INFO - Epoch(train) [29][ 580/1345] lr: 1.0000e-02 eta: 8:46:03 time: 0.1886 data_time: 0.0059 memory: 8327 grad_norm: 7.2291 loss: 3.5396 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1183 loss_aux: 1.4213 2023/02/17 14:14:04 - mmengine - INFO - Epoch(train) [29][ 600/1345] lr: 1.0000e-02 eta: 8:45:59 time: 0.1890 data_time: 0.0060 memory: 8327 grad_norm: 7.3476 loss: 3.8553 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3563 loss_aux: 1.4989 2023/02/17 14:14:07 - mmengine - INFO - Epoch(train) [29][ 620/1345] lr: 1.0000e-02 eta: 8:45:54 time: 0.1888 data_time: 0.0059 memory: 8327 grad_norm: 7.4492 loss: 3.8659 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3777 loss_aux: 1.4882 2023/02/17 14:14:11 - mmengine - INFO - Epoch(train) [29][ 640/1345] lr: 1.0000e-02 eta: 8:45:50 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5247 loss: 3.7072 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2341 loss_aux: 1.4731 2023/02/17 14:14:15 - mmengine - INFO - Epoch(train) [29][ 660/1345] lr: 1.0000e-02 eta: 8:45:46 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.4280 loss: 4.2181 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6499 loss_aux: 1.5681 2023/02/17 14:14:19 - mmengine - INFO - Epoch(train) [29][ 680/1345] lr: 1.0000e-02 eta: 8:45:42 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 7.4829 loss: 3.5977 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1977 loss_aux: 1.4001 2023/02/17 14:14:22 - mmengine - INFO - Epoch(train) [29][ 700/1345] lr: 1.0000e-02 eta: 8:45:38 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 7.2257 loss: 3.6932 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2484 loss_aux: 1.4448 2023/02/17 14:14:26 - mmengine - INFO - Epoch(train) [29][ 720/1345] lr: 1.0000e-02 eta: 8:45:33 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.4314 loss: 3.9037 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4196 loss_aux: 1.4841 2023/02/17 14:14:30 - mmengine - INFO - Epoch(train) [29][ 740/1345] lr: 1.0000e-02 eta: 8:45:29 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.1394 loss: 3.6274 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2000 loss_aux: 1.4273 2023/02/17 14:14:34 - mmengine - INFO - Epoch(train) [29][ 760/1345] lr: 1.0000e-02 eta: 8:45:25 time: 0.1889 data_time: 0.0055 memory: 8327 grad_norm: 7.2046 loss: 3.6476 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2095 loss_aux: 1.4381 2023/02/17 14:14:38 - mmengine - INFO - Epoch(train) [29][ 780/1345] lr: 1.0000e-02 eta: 8:45:21 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.1120 loss: 3.5006 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1771 loss_aux: 1.3236 2023/02/17 14:14:41 - mmengine - INFO - Epoch(train) [29][ 800/1345] lr: 1.0000e-02 eta: 8:45:17 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.0655 loss: 3.2053 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9336 loss_aux: 1.2716 2023/02/17 14:14:45 - mmengine - INFO - Epoch(train) [29][ 820/1345] lr: 1.0000e-02 eta: 8:45:13 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.4253 loss: 3.8469 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3909 loss_aux: 1.4560 2023/02/17 14:14:49 - mmengine - INFO - Epoch(train) [29][ 840/1345] lr: 1.0000e-02 eta: 8:45:08 time: 0.1892 data_time: 0.0060 memory: 8327 grad_norm: 7.3577 loss: 3.8276 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3635 loss_aux: 1.4641 2023/02/17 14:14:53 - mmengine - INFO - Epoch(train) [29][ 860/1345] lr: 1.0000e-02 eta: 8:45:04 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.0922 loss: 3.8234 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3558 loss_aux: 1.4676 2023/02/17 14:14:57 - mmengine - INFO - Epoch(train) [29][ 880/1345] lr: 1.0000e-02 eta: 8:45:00 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.3128 loss: 3.6697 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1998 loss_aux: 1.4699 2023/02/17 14:15:00 - mmengine - INFO - Epoch(train) [29][ 900/1345] lr: 1.0000e-02 eta: 8:44:56 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.3585 loss: 3.8039 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3585 loss_aux: 1.4454 2023/02/17 14:15:04 - mmengine - INFO - Epoch(train) [29][ 920/1345] lr: 1.0000e-02 eta: 8:44:52 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.1541 loss: 3.5124 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.0823 loss_aux: 1.4301 2023/02/17 14:15:08 - mmengine - INFO - Epoch(train) [29][ 940/1345] lr: 1.0000e-02 eta: 8:44:47 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.2652 loss: 3.7179 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2809 loss_aux: 1.4369 2023/02/17 14:15:12 - mmengine - INFO - Epoch(train) [29][ 960/1345] lr: 1.0000e-02 eta: 8:44:43 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 6.9681 loss: 3.4171 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0537 loss_aux: 1.3634 2023/02/17 14:15:15 - mmengine - INFO - Epoch(train) [29][ 980/1345] lr: 1.0000e-02 eta: 8:44:39 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.4045 loss: 3.6827 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2266 loss_aux: 1.4561 2023/02/17 14:15:19 - mmengine - INFO - Epoch(train) [29][1000/1345] lr: 1.0000e-02 eta: 8:44:35 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.2347 loss: 3.9840 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4896 loss_aux: 1.4944 2023/02/17 14:15:23 - mmengine - INFO - Epoch(train) [29][1020/1345] lr: 1.0000e-02 eta: 8:44:31 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.7005 loss: 3.5072 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1113 loss_aux: 1.3959 2023/02/17 14:15:27 - mmengine - INFO - Epoch(train) [29][1040/1345] lr: 1.0000e-02 eta: 8:44:26 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.6728 loss: 4.0352 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5090 loss_aux: 1.5262 2023/02/17 14:15:31 - mmengine - INFO - Epoch(train) [29][1060/1345] lr: 1.0000e-02 eta: 8:44:22 time: 0.1896 data_time: 0.0064 memory: 8327 grad_norm: 7.4591 loss: 3.6569 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1950 loss_aux: 1.4619 2023/02/17 14:15:34 - mmengine - INFO - Epoch(train) [29][1080/1345] lr: 1.0000e-02 eta: 8:44:18 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.2234 loss: 4.2192 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6140 loss_aux: 1.6052 2023/02/17 14:15:38 - mmengine - INFO - Epoch(train) [29][1100/1345] lr: 1.0000e-02 eta: 8:44:14 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.2184 loss: 3.6985 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.2781 loss_aux: 1.4204 2023/02/17 14:15:42 - mmengine - INFO - Epoch(train) [29][1120/1345] lr: 1.0000e-02 eta: 8:44:10 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.3525 loss: 3.6541 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2225 loss_aux: 1.4316 2023/02/17 14:15:46 - mmengine - INFO - Epoch(train) [29][1140/1345] lr: 1.0000e-02 eta: 8:44:05 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.3271 loss: 4.1126 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5596 loss_aux: 1.5531 2023/02/17 14:15:49 - mmengine - INFO - Epoch(train) [29][1160/1345] lr: 1.0000e-02 eta: 8:44:01 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.2113 loss: 3.4285 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1381 loss_aux: 1.2904 2023/02/17 14:15:53 - mmengine - INFO - Epoch(train) [29][1180/1345] lr: 1.0000e-02 eta: 8:43:57 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.4747 loss: 3.6374 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2252 loss_aux: 1.4122 2023/02/17 14:15:57 - mmengine - INFO - Epoch(train) [29][1200/1345] lr: 1.0000e-02 eta: 8:43:53 time: 0.1908 data_time: 0.0073 memory: 8327 grad_norm: 7.4313 loss: 3.9317 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4269 loss_aux: 1.5048 2023/02/17 14:16:01 - mmengine - INFO - Epoch(train) [29][1220/1345] lr: 1.0000e-02 eta: 8:43:49 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.2252 loss: 4.1221 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5262 loss_aux: 1.5959 2023/02/17 14:16:05 - mmengine - INFO - Epoch(train) [29][1240/1345] lr: 1.0000e-02 eta: 8:43:45 time: 0.1889 data_time: 0.0060 memory: 8327 grad_norm: 7.3827 loss: 3.6218 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1835 loss_aux: 1.4382 2023/02/17 14:16:08 - mmengine - INFO - Epoch(train) [29][1260/1345] lr: 1.0000e-02 eta: 8:43:41 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.3013 loss: 3.7144 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2494 loss_aux: 1.4650 2023/02/17 14:16:12 - mmengine - INFO - Epoch(train) [29][1280/1345] lr: 1.0000e-02 eta: 8:43:36 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.2543 loss: 3.8616 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3996 loss_aux: 1.4620 2023/02/17 14:16:16 - mmengine - INFO - Epoch(train) [29][1300/1345] lr: 1.0000e-02 eta: 8:43:32 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.1655 loss: 3.4639 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0347 loss_aux: 1.4292 2023/02/17 14:16:20 - mmengine - INFO - Epoch(train) [29][1320/1345] lr: 1.0000e-02 eta: 8:43:28 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.4000 loss: 3.6297 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2022 loss_aux: 1.4275 2023/02/17 14:16:24 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:16:24 - mmengine - INFO - Epoch(train) [29][1340/1345] lr: 1.0000e-02 eta: 8:43:24 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.3975 loss: 3.4607 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0842 loss_aux: 1.3764 2023/02/17 14:16:24 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:16:24 - mmengine - INFO - Epoch(train) [29][1345/1345] lr: 1.0000e-02 eta: 8:43:22 time: 0.1836 data_time: 0.0058 memory: 8327 grad_norm: 7.3882 loss: 3.6447 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.2111 loss_aux: 1.4337 2023/02/17 14:16:24 - mmengine - INFO - Saving checkpoint at 29 epochs 2023/02/17 14:16:31 - mmengine - INFO - Epoch(train) [30][ 20/1345] lr: 1.0000e-02 eta: 8:43:19 time: 0.2052 data_time: 0.0153 memory: 8327 grad_norm: 7.1989 loss: 3.6208 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2052 loss_aux: 1.4156 2023/02/17 14:16:35 - mmengine - INFO - Epoch(train) [30][ 40/1345] lr: 1.0000e-02 eta: 8:43:15 time: 0.1900 data_time: 0.0041 memory: 8327 grad_norm: 7.1632 loss: 3.6813 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2127 loss_aux: 1.4687 2023/02/17 14:16:39 - mmengine - INFO - Epoch(train) [30][ 60/1345] lr: 1.0000e-02 eta: 8:43:11 time: 0.1892 data_time: 0.0055 memory: 8327 grad_norm: 7.1405 loss: 3.2309 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9356 loss_aux: 1.2953 2023/02/17 14:16:42 - mmengine - INFO - Epoch(train) [30][ 80/1345] lr: 1.0000e-02 eta: 8:43:07 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 7.1727 loss: 3.5222 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.1497 loss_aux: 1.3725 2023/02/17 14:16:46 - mmengine - INFO - Epoch(train) [30][ 100/1345] lr: 1.0000e-02 eta: 8:43:03 time: 0.1886 data_time: 0.0057 memory: 8327 grad_norm: 7.0629 loss: 3.5188 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1484 loss_aux: 1.3704 2023/02/17 14:16:50 - mmengine - INFO - Epoch(train) [30][ 120/1345] lr: 1.0000e-02 eta: 8:42:59 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.6101 loss: 3.5560 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1754 loss_aux: 1.3806 2023/02/17 14:16:54 - mmengine - INFO - Epoch(train) [30][ 140/1345] lr: 1.0000e-02 eta: 8:42:54 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.5012 loss: 3.6267 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2484 loss_aux: 1.3783 2023/02/17 14:16:58 - mmengine - INFO - Epoch(train) [30][ 160/1345] lr: 1.0000e-02 eta: 8:42:50 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.4266 loss: 4.0050 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5184 loss_aux: 1.4866 2023/02/17 14:17:01 - mmengine - INFO - Epoch(train) [30][ 180/1345] lr: 1.0000e-02 eta: 8:42:46 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.2741 loss: 3.4005 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0373 loss_aux: 1.3632 2023/02/17 14:17:05 - mmengine - INFO - Epoch(train) [30][ 200/1345] lr: 1.0000e-02 eta: 8:42:42 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.2380 loss: 3.8070 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3466 loss_aux: 1.4603 2023/02/17 14:17:09 - mmengine - INFO - Epoch(train) [30][ 220/1345] lr: 1.0000e-02 eta: 8:42:38 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.1982 loss: 3.7543 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2807 loss_aux: 1.4736 2023/02/17 14:17:13 - mmengine - INFO - Epoch(train) [30][ 240/1345] lr: 1.0000e-02 eta: 8:42:33 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.3602 loss: 3.6481 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2571 loss_aux: 1.3910 2023/02/17 14:17:16 - mmengine - INFO - Epoch(train) [30][ 260/1345] lr: 1.0000e-02 eta: 8:42:29 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.2590 loss: 3.4241 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1058 loss_aux: 1.3183 2023/02/17 14:17:20 - mmengine - INFO - Epoch(train) [30][ 280/1345] lr: 1.0000e-02 eta: 8:42:25 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.2795 loss: 3.3211 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9843 loss_aux: 1.3367 2023/02/17 14:17:24 - mmengine - INFO - Epoch(train) [30][ 300/1345] lr: 1.0000e-02 eta: 8:42:21 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.2853 loss: 3.4955 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.0930 loss_aux: 1.4025 2023/02/17 14:17:28 - mmengine - INFO - Epoch(train) [30][ 320/1345] lr: 1.0000e-02 eta: 8:42:17 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.1951 loss: 3.8003 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3354 loss_aux: 1.4649 2023/02/17 14:17:32 - mmengine - INFO - Epoch(train) [30][ 340/1345] lr: 1.0000e-02 eta: 8:42:13 time: 0.1897 data_time: 0.0057 memory: 8327 grad_norm: 7.2630 loss: 3.2248 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9678 loss_aux: 1.2570 2023/02/17 14:17:35 - mmengine - INFO - Epoch(train) [30][ 360/1345] lr: 1.0000e-02 eta: 8:42:08 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.2358 loss: 3.5281 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1531 loss_aux: 1.3750 2023/02/17 14:17:39 - mmengine - INFO - Epoch(train) [30][ 380/1345] lr: 1.0000e-02 eta: 8:42:04 time: 0.1906 data_time: 0.0057 memory: 8327 grad_norm: 7.2854 loss: 3.6385 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2556 loss_aux: 1.3829 2023/02/17 14:17:43 - mmengine - INFO - Epoch(train) [30][ 400/1345] lr: 1.0000e-02 eta: 8:42:00 time: 0.1908 data_time: 0.0056 memory: 8327 grad_norm: 7.4483 loss: 3.7436 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2255 loss_aux: 1.5181 2023/02/17 14:17:47 - mmengine - INFO - Epoch(train) [30][ 420/1345] lr: 1.0000e-02 eta: 8:41:56 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.1863 loss: 3.8441 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3384 loss_aux: 1.5057 2023/02/17 14:17:51 - mmengine - INFO - Epoch(train) [30][ 440/1345] lr: 1.0000e-02 eta: 8:41:52 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.4703 loss: 4.0047 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4750 loss_aux: 1.5296 2023/02/17 14:17:54 - mmengine - INFO - Epoch(train) [30][ 460/1345] lr: 1.0000e-02 eta: 8:41:48 time: 0.1888 data_time: 0.0059 memory: 8327 grad_norm: 7.1434 loss: 3.9683 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4777 loss_aux: 1.4906 2023/02/17 14:17:58 - mmengine - INFO - Epoch(train) [30][ 480/1345] lr: 1.0000e-02 eta: 8:41:44 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.3904 loss: 3.8060 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3273 loss_aux: 1.4787 2023/02/17 14:18:02 - mmengine - INFO - Epoch(train) [30][ 500/1345] lr: 1.0000e-02 eta: 8:41:39 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.2540 loss: 3.5050 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1179 loss_aux: 1.3871 2023/02/17 14:18:06 - mmengine - INFO - Epoch(train) [30][ 520/1345] lr: 1.0000e-02 eta: 8:41:35 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.2350 loss: 3.7705 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3279 loss_aux: 1.4426 2023/02/17 14:18:09 - mmengine - INFO - Epoch(train) [30][ 540/1345] lr: 1.0000e-02 eta: 8:41:31 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.2588 loss: 3.9271 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4185 loss_aux: 1.5086 2023/02/17 14:18:13 - mmengine - INFO - Epoch(train) [30][ 560/1345] lr: 1.0000e-02 eta: 8:41:27 time: 0.1902 data_time: 0.0060 memory: 8327 grad_norm: 7.3113 loss: 3.8869 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3703 loss_aux: 1.5166 2023/02/17 14:18:17 - mmengine - INFO - Epoch(train) [30][ 580/1345] lr: 1.0000e-02 eta: 8:41:23 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.2392 loss: 3.5285 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1735 loss_aux: 1.3550 2023/02/17 14:18:21 - mmengine - INFO - Epoch(train) [30][ 600/1345] lr: 1.0000e-02 eta: 8:41:19 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.2645 loss: 3.7431 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3173 loss_aux: 1.4257 2023/02/17 14:18:25 - mmengine - INFO - Epoch(train) [30][ 620/1345] lr: 1.0000e-02 eta: 8:41:14 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.4026 loss: 3.9242 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4325 loss_aux: 1.4916 2023/02/17 14:18:28 - mmengine - INFO - Epoch(train) [30][ 640/1345] lr: 1.0000e-02 eta: 8:41:10 time: 0.1892 data_time: 0.0060 memory: 8327 grad_norm: 7.3565 loss: 3.5571 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1320 loss_aux: 1.4250 2023/02/17 14:18:32 - mmengine - INFO - Epoch(train) [30][ 660/1345] lr: 1.0000e-02 eta: 8:41:06 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.4105 loss: 3.7719 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3005 loss_aux: 1.4715 2023/02/17 14:18:36 - mmengine - INFO - Epoch(train) [30][ 680/1345] lr: 1.0000e-02 eta: 8:41:02 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.5058 loss: 3.6882 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.2617 loss_aux: 1.4266 2023/02/17 14:18:40 - mmengine - INFO - Epoch(train) [30][ 700/1345] lr: 1.0000e-02 eta: 8:40:58 time: 0.1905 data_time: 0.0058 memory: 8327 grad_norm: 7.3025 loss: 3.7154 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2898 loss_aux: 1.4256 2023/02/17 14:18:44 - mmengine - INFO - Epoch(train) [30][ 720/1345] lr: 1.0000e-02 eta: 8:40:54 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.3018 loss: 4.1370 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5414 loss_aux: 1.5955 2023/02/17 14:18:47 - mmengine - INFO - Epoch(train) [30][ 740/1345] lr: 1.0000e-02 eta: 8:40:50 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.1152 loss: 3.6493 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1882 loss_aux: 1.4610 2023/02/17 14:18:51 - mmengine - INFO - Epoch(train) [30][ 760/1345] lr: 1.0000e-02 eta: 8:40:45 time: 0.1891 data_time: 0.0060 memory: 8327 grad_norm: 7.4327 loss: 3.7297 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3034 loss_aux: 1.4263 2023/02/17 14:18:55 - mmengine - INFO - Epoch(train) [30][ 780/1345] lr: 1.0000e-02 eta: 8:40:41 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.3211 loss: 3.7373 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2811 loss_aux: 1.4562 2023/02/17 14:18:59 - mmengine - INFO - Epoch(train) [30][ 800/1345] lr: 1.0000e-02 eta: 8:40:37 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.0969 loss: 3.5907 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1865 loss_aux: 1.4042 2023/02/17 14:19:03 - mmengine - INFO - Epoch(train) [30][ 820/1345] lr: 1.0000e-02 eta: 8:40:33 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.3628 loss: 4.0166 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5550 loss_aux: 1.4616 2023/02/17 14:19:06 - mmengine - INFO - Epoch(train) [30][ 840/1345] lr: 1.0000e-02 eta: 8:40:29 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.4533 loss: 3.4760 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.1088 loss_aux: 1.3672 2023/02/17 14:19:10 - mmengine - INFO - Epoch(train) [30][ 860/1345] lr: 1.0000e-02 eta: 8:40:25 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.3009 loss: 3.8219 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3107 loss_aux: 1.5113 2023/02/17 14:19:14 - mmengine - INFO - Epoch(train) [30][ 880/1345] lr: 1.0000e-02 eta: 8:40:20 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.3547 loss: 3.4608 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0979 loss_aux: 1.3628 2023/02/17 14:19:18 - mmengine - INFO - Epoch(train) [30][ 900/1345] lr: 1.0000e-02 eta: 8:40:16 time: 0.1894 data_time: 0.0064 memory: 8327 grad_norm: 7.4486 loss: 3.7693 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3346 loss_aux: 1.4347 2023/02/17 14:19:21 - mmengine - INFO - Epoch(train) [30][ 920/1345] lr: 1.0000e-02 eta: 8:40:12 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.2307 loss: 3.7324 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2933 loss_aux: 1.4392 2023/02/17 14:19:25 - mmengine - INFO - Epoch(train) [30][ 940/1345] lr: 1.0000e-02 eta: 8:40:08 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.3948 loss: 3.5618 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1543 loss_aux: 1.4075 2023/02/17 14:19:29 - mmengine - INFO - Epoch(train) [30][ 960/1345] lr: 1.0000e-02 eta: 8:40:04 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.2529 loss: 3.5905 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2282 loss_aux: 1.3622 2023/02/17 14:19:33 - mmengine - INFO - Epoch(train) [30][ 980/1345] lr: 1.0000e-02 eta: 8:40:00 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.6435 loss: 3.6604 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2234 loss_aux: 1.4370 2023/02/17 14:19:36 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:19:37 - mmengine - INFO - Epoch(train) [30][1000/1345] lr: 1.0000e-02 eta: 8:39:55 time: 0.1886 data_time: 0.0058 memory: 8327 grad_norm: 7.3124 loss: 3.7134 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2898 loss_aux: 1.4236 2023/02/17 14:19:40 - mmengine - INFO - Epoch(train) [30][1020/1345] lr: 1.0000e-02 eta: 8:39:51 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.2838 loss: 3.8300 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3932 loss_aux: 1.4368 2023/02/17 14:19:44 - mmengine - INFO - Epoch(train) [30][1040/1345] lr: 1.0000e-02 eta: 8:39:47 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.3260 loss: 3.8870 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3800 loss_aux: 1.5069 2023/02/17 14:19:48 - mmengine - INFO - Epoch(train) [30][1060/1345] lr: 1.0000e-02 eta: 8:39:43 time: 0.1896 data_time: 0.0056 memory: 8327 grad_norm: 7.4632 loss: 4.1876 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6797 loss_aux: 1.5079 2023/02/17 14:19:52 - mmengine - INFO - Epoch(train) [30][1080/1345] lr: 1.0000e-02 eta: 8:39:39 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.6224 loss: 3.7695 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3447 loss_aux: 1.4248 2023/02/17 14:19:55 - mmengine - INFO - Epoch(train) [30][1100/1345] lr: 1.0000e-02 eta: 8:39:34 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.1431 loss: 3.6119 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2659 loss_aux: 1.3460 2023/02/17 14:19:59 - mmengine - INFO - Epoch(train) [30][1120/1345] lr: 1.0000e-02 eta: 8:39:30 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.4912 loss: 3.9029 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4374 loss_aux: 1.4655 2023/02/17 14:20:03 - mmengine - INFO - Epoch(train) [30][1140/1345] lr: 1.0000e-02 eta: 8:39:26 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.4793 loss: 3.9247 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4338 loss_aux: 1.4910 2023/02/17 14:20:07 - mmengine - INFO - Epoch(train) [30][1160/1345] lr: 1.0000e-02 eta: 8:39:22 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.2683 loss: 3.7847 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3138 loss_aux: 1.4709 2023/02/17 14:20:11 - mmengine - INFO - Epoch(train) [30][1180/1345] lr: 1.0000e-02 eta: 8:39:18 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.4527 loss: 3.8554 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3549 loss_aux: 1.5004 2023/02/17 14:20:14 - mmengine - INFO - Epoch(train) [30][1200/1345] lr: 1.0000e-02 eta: 8:39:14 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.2121 loss: 3.3913 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0821 loss_aux: 1.3092 2023/02/17 14:20:18 - mmengine - INFO - Epoch(train) [30][1220/1345] lr: 1.0000e-02 eta: 8:39:10 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.3389 loss: 3.5987 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2384 loss_aux: 1.3603 2023/02/17 14:20:22 - mmengine - INFO - Epoch(train) [30][1240/1345] lr: 1.0000e-02 eta: 8:39:05 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.4791 loss: 3.6853 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1993 loss_aux: 1.4860 2023/02/17 14:20:26 - mmengine - INFO - Epoch(train) [30][1260/1345] lr: 1.0000e-02 eta: 8:39:01 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.2913 loss: 3.4012 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0558 loss_aux: 1.3454 2023/02/17 14:20:30 - mmengine - INFO - Epoch(train) [30][1280/1345] lr: 1.0000e-02 eta: 8:38:57 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.2875 loss: 3.7422 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2504 loss_aux: 1.4919 2023/02/17 14:20:33 - mmengine - INFO - Epoch(train) [30][1300/1345] lr: 1.0000e-02 eta: 8:38:53 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.3627 loss: 3.6227 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2406 loss_aux: 1.3822 2023/02/17 14:20:37 - mmengine - INFO - Epoch(train) [30][1320/1345] lr: 1.0000e-02 eta: 8:38:49 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.1929 loss: 3.6976 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2551 loss_aux: 1.4425 2023/02/17 14:20:41 - mmengine - INFO - Epoch(train) [30][1340/1345] lr: 1.0000e-02 eta: 8:38:45 time: 0.1906 data_time: 0.0076 memory: 8327 grad_norm: 7.3893 loss: 3.8354 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3437 loss_aux: 1.4917 2023/02/17 14:20:42 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:20:42 - mmengine - INFO - Epoch(train) [30][1345/1345] lr: 1.0000e-02 eta: 8:38:43 time: 0.1836 data_time: 0.0061 memory: 8327 grad_norm: 7.3468 loss: 3.9551 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.4349 loss_aux: 1.5202 2023/02/17 14:20:42 - mmengine - INFO - Saving checkpoint at 30 epochs 2023/02/17 14:20:46 - mmengine - INFO - Epoch(val) [30][ 20/181] eta: 0:00:09 time: 0.0568 data_time: 0.0079 memory: 1994 2023/02/17 14:20:47 - mmengine - INFO - Epoch(val) [30][ 40/181] eta: 0:00:07 time: 0.0527 data_time: 0.0047 memory: 1994 2023/02/17 14:20:48 - mmengine - INFO - Epoch(val) [30][ 60/181] eta: 0:00:06 time: 0.0523 data_time: 0.0045 memory: 1994 2023/02/17 14:20:49 - mmengine - INFO - Epoch(val) [30][ 80/181] eta: 0:00:05 time: 0.0524 data_time: 0.0045 memory: 1994 2023/02/17 14:20:50 - mmengine - INFO - Epoch(val) [30][100/181] eta: 0:00:04 time: 0.0523 data_time: 0.0046 memory: 1994 2023/02/17 14:20:51 - mmengine - INFO - Epoch(val) [30][120/181] eta: 0:00:03 time: 0.0524 data_time: 0.0045 memory: 1994 2023/02/17 14:20:52 - mmengine - INFO - Epoch(val) [30][140/181] eta: 0:00:02 time: 0.0518 data_time: 0.0042 memory: 1994 2023/02/17 14:20:53 - mmengine - INFO - Epoch(val) [30][160/181] eta: 0:00:01 time: 0.0518 data_time: 0.0041 memory: 1994 2023/02/17 14:20:54 - mmengine - INFO - Epoch(val) [30][180/181] eta: 0:00:00 time: 0.0519 data_time: 0.0042 memory: 1994 2023/02/17 14:20:54 - mmengine - INFO - Epoch(val) [30][181/181] acc/top1: 0.3774 acc/top5: 0.6722 acc/mean1: 0.3410 2023/02/17 14:20:54 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/lilin/Repos/mmact_dev/mmaction2/work_dirs/fix_flip/tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb/best_acc/top1_epoch_25.pth is removed 2023/02/17 14:20:56 - mmengine - INFO - The best checkpoint with 0.3774 acc/top1 at 30 epoch is saved to best_acc/top1_epoch_30.pth. 2023/02/17 14:21:00 - mmengine - INFO - Epoch(train) [31][ 20/1345] lr: 1.0000e-02 eta: 8:38:41 time: 0.2087 data_time: 0.0174 memory: 8327 grad_norm: 7.4154 loss: 3.7951 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3224 loss_aux: 1.4727 2023/02/17 14:21:04 - mmengine - INFO - Epoch(train) [31][ 40/1345] lr: 1.0000e-02 eta: 8:38:37 time: 0.1906 data_time: 0.0040 memory: 8327 grad_norm: 7.1539 loss: 3.8285 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3440 loss_aux: 1.4845 2023/02/17 14:21:08 - mmengine - INFO - Epoch(train) [31][ 60/1345] lr: 1.0000e-02 eta: 8:38:32 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.3822 loss: 3.8674 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4003 loss_aux: 1.4671 2023/02/17 14:21:12 - mmengine - INFO - Epoch(train) [31][ 80/1345] lr: 1.0000e-02 eta: 8:38:28 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.3671 loss: 3.6403 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1802 loss_aux: 1.4600 2023/02/17 14:21:15 - mmengine - INFO - Epoch(train) [31][ 100/1345] lr: 1.0000e-02 eta: 8:38:24 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.3451 loss: 3.2001 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9495 loss_aux: 1.2506 2023/02/17 14:21:19 - mmengine - INFO - Epoch(train) [31][ 120/1345] lr: 1.0000e-02 eta: 8:38:20 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.3326 loss: 3.9041 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4143 loss_aux: 1.4898 2023/02/17 14:21:23 - mmengine - INFO - Epoch(train) [31][ 140/1345] lr: 1.0000e-02 eta: 8:38:16 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.4978 loss: 3.5075 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1660 loss_aux: 1.3415 2023/02/17 14:21:27 - mmengine - INFO - Epoch(train) [31][ 160/1345] lr: 1.0000e-02 eta: 8:38:12 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.2287 loss: 3.4598 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1199 loss_aux: 1.3399 2023/02/17 14:21:31 - mmengine - INFO - Epoch(train) [31][ 180/1345] lr: 1.0000e-02 eta: 8:38:07 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.2388 loss: 3.7915 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3280 loss_aux: 1.4635 2023/02/17 14:21:34 - mmengine - INFO - Epoch(train) [31][ 200/1345] lr: 1.0000e-02 eta: 8:38:03 time: 0.1894 data_time: 0.0063 memory: 8327 grad_norm: 7.3018 loss: 3.8163 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3560 loss_aux: 1.4603 2023/02/17 14:21:38 - mmengine - INFO - Epoch(train) [31][ 220/1345] lr: 1.0000e-02 eta: 8:37:59 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.3547 loss: 3.6914 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.2435 loss_aux: 1.4479 2023/02/17 14:21:42 - mmengine - INFO - Epoch(train) [31][ 240/1345] lr: 1.0000e-02 eta: 8:37:55 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.3430 loss: 3.6515 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2129 loss_aux: 1.4385 2023/02/17 14:21:46 - mmengine - INFO - Epoch(train) [31][ 260/1345] lr: 1.0000e-02 eta: 8:37:51 time: 0.1886 data_time: 0.0056 memory: 8327 grad_norm: 7.5240 loss: 3.9275 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4370 loss_aux: 1.4905 2023/02/17 14:21:50 - mmengine - INFO - Epoch(train) [31][ 280/1345] lr: 1.0000e-02 eta: 8:37:47 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.2644 loss: 3.9057 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4280 loss_aux: 1.4776 2023/02/17 14:21:53 - mmengine - INFO - Epoch(train) [31][ 300/1345] lr: 1.0000e-02 eta: 8:37:42 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.2220 loss: 3.4160 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1318 loss_aux: 1.2843 2023/02/17 14:21:57 - mmengine - INFO - Epoch(train) [31][ 320/1345] lr: 1.0000e-02 eta: 8:37:38 time: 0.1907 data_time: 0.0071 memory: 8327 grad_norm: 7.3982 loss: 3.4733 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1408 loss_aux: 1.3325 2023/02/17 14:22:01 - mmengine - INFO - Epoch(train) [31][ 340/1345] lr: 1.0000e-02 eta: 8:37:34 time: 0.1904 data_time: 0.0067 memory: 8327 grad_norm: 7.1503 loss: 4.0441 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5125 loss_aux: 1.5316 2023/02/17 14:22:05 - mmengine - INFO - Epoch(train) [31][ 360/1345] lr: 1.0000e-02 eta: 8:37:30 time: 0.1906 data_time: 0.0056 memory: 8327 grad_norm: 7.4275 loss: 3.8167 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3681 loss_aux: 1.4486 2023/02/17 14:22:09 - mmengine - INFO - Epoch(train) [31][ 380/1345] lr: 1.0000e-02 eta: 8:37:26 time: 0.1906 data_time: 0.0059 memory: 8327 grad_norm: 7.3290 loss: 3.5371 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.1492 loss_aux: 1.3879 2023/02/17 14:22:12 - mmengine - INFO - Epoch(train) [31][ 400/1345] lr: 1.0000e-02 eta: 8:37:22 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 7.1058 loss: 3.6672 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2258 loss_aux: 1.4414 2023/02/17 14:22:16 - mmengine - INFO - Epoch(train) [31][ 420/1345] lr: 1.0000e-02 eta: 8:37:18 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.0910 loss: 3.8753 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4150 loss_aux: 1.4603 2023/02/17 14:22:20 - mmengine - INFO - Epoch(train) [31][ 440/1345] lr: 1.0000e-02 eta: 8:37:14 time: 0.1885 data_time: 0.0057 memory: 8327 grad_norm: 7.3902 loss: 3.5258 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1715 loss_aux: 1.3543 2023/02/17 14:22:24 - mmengine - INFO - Epoch(train) [31][ 460/1345] lr: 1.0000e-02 eta: 8:37:10 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.2513 loss: 3.9154 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4030 loss_aux: 1.5124 2023/02/17 14:22:27 - mmengine - INFO - Epoch(train) [31][ 480/1345] lr: 1.0000e-02 eta: 8:37:05 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.1500 loss: 3.8909 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4276 loss_aux: 1.4634 2023/02/17 14:22:31 - mmengine - INFO - Epoch(train) [31][ 500/1345] lr: 1.0000e-02 eta: 8:37:01 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.2845 loss: 3.5553 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2018 loss_aux: 1.3535 2023/02/17 14:22:35 - mmengine - INFO - Epoch(train) [31][ 520/1345] lr: 1.0000e-02 eta: 8:36:57 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.3865 loss: 3.5230 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1746 loss_aux: 1.3484 2023/02/17 14:22:39 - mmengine - INFO - Epoch(train) [31][ 540/1345] lr: 1.0000e-02 eta: 8:36:53 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.4104 loss: 3.7700 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3102 loss_aux: 1.4598 2023/02/17 14:22:43 - mmengine - INFO - Epoch(train) [31][ 560/1345] lr: 1.0000e-02 eta: 8:36:49 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.4022 loss: 3.9024 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3803 loss_aux: 1.5221 2023/02/17 14:22:46 - mmengine - INFO - Epoch(train) [31][ 580/1345] lr: 1.0000e-02 eta: 8:36:45 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 7.2191 loss: 4.0152 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4722 loss_aux: 1.5429 2023/02/17 14:22:50 - mmengine - INFO - Epoch(train) [31][ 600/1345] lr: 1.0000e-02 eta: 8:36:41 time: 0.1887 data_time: 0.0056 memory: 8327 grad_norm: 7.4197 loss: 3.2998 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0067 loss_aux: 1.2931 2023/02/17 14:22:54 - mmengine - INFO - Epoch(train) [31][ 620/1345] lr: 1.0000e-02 eta: 8:36:36 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.2962 loss: 3.2625 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9227 loss_aux: 1.3397 2023/02/17 14:22:58 - mmengine - INFO - Epoch(train) [31][ 640/1345] lr: 1.0000e-02 eta: 8:36:32 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.4401 loss: 3.8479 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3439 loss_aux: 1.5040 2023/02/17 14:23:00 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:23:02 - mmengine - INFO - Epoch(train) [31][ 660/1345] lr: 1.0000e-02 eta: 8:36:28 time: 0.1897 data_time: 0.0057 memory: 8327 grad_norm: 7.3824 loss: 3.8600 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3543 loss_aux: 1.5057 2023/02/17 14:23:05 - mmengine - INFO - Epoch(train) [31][ 680/1345] lr: 1.0000e-02 eta: 8:36:24 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.2747 loss: 4.1382 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5716 loss_aux: 1.5665 2023/02/17 14:23:09 - mmengine - INFO - Epoch(train) [31][ 700/1345] lr: 1.0000e-02 eta: 8:36:20 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.2600 loss: 3.8186 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3632 loss_aux: 1.4554 2023/02/17 14:23:13 - mmengine - INFO - Epoch(train) [31][ 720/1345] lr: 1.0000e-02 eta: 8:36:16 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.3923 loss: 3.7265 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2503 loss_aux: 1.4762 2023/02/17 14:23:17 - mmengine - INFO - Epoch(train) [31][ 740/1345] lr: 1.0000e-02 eta: 8:36:11 time: 0.1888 data_time: 0.0059 memory: 8327 grad_norm: 7.3348 loss: 3.5921 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1906 loss_aux: 1.4015 2023/02/17 14:23:20 - mmengine - INFO - Epoch(train) [31][ 760/1345] lr: 1.0000e-02 eta: 8:36:07 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.3969 loss: 3.8741 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3513 loss_aux: 1.5229 2023/02/17 14:23:24 - mmengine - INFO - Epoch(train) [31][ 780/1345] lr: 1.0000e-02 eta: 8:36:03 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.4989 loss: 3.7503 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3002 loss_aux: 1.4502 2023/02/17 14:23:28 - mmengine - INFO - Epoch(train) [31][ 800/1345] lr: 1.0000e-02 eta: 8:35:59 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.2428 loss: 3.9716 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4802 loss_aux: 1.4914 2023/02/17 14:23:32 - mmengine - INFO - Epoch(train) [31][ 820/1345] lr: 1.0000e-02 eta: 8:35:55 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.5338 loss: 3.2270 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9378 loss_aux: 1.2892 2023/02/17 14:23:36 - mmengine - INFO - Epoch(train) [31][ 840/1345] lr: 1.0000e-02 eta: 8:35:51 time: 0.1901 data_time: 0.0070 memory: 8327 grad_norm: 7.3891 loss: 3.9726 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4169 loss_aux: 1.5558 2023/02/17 14:23:39 - mmengine - INFO - Epoch(train) [31][ 860/1345] lr: 1.0000e-02 eta: 8:35:47 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.2875 loss: 3.5647 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1917 loss_aux: 1.3729 2023/02/17 14:23:44 - mmengine - INFO - Epoch(train) [31][ 880/1345] lr: 1.0000e-02 eta: 8:35:44 time: 0.2091 data_time: 0.0259 memory: 8327 grad_norm: 7.0289 loss: 3.3417 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0304 loss_aux: 1.3112 2023/02/17 14:23:47 - mmengine - INFO - Epoch(train) [31][ 900/1345] lr: 1.0000e-02 eta: 8:35:40 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.4733 loss: 3.5438 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1777 loss_aux: 1.3661 2023/02/17 14:23:51 - mmengine - INFO - Epoch(train) [31][ 920/1345] lr: 1.0000e-02 eta: 8:35:36 time: 0.1887 data_time: 0.0059 memory: 8327 grad_norm: 7.4729 loss: 3.4320 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.0790 loss_aux: 1.3530 2023/02/17 14:23:55 - mmengine - INFO - Epoch(train) [31][ 940/1345] lr: 1.0000e-02 eta: 8:35:32 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.1087 loss: 3.6360 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2265 loss_aux: 1.4094 2023/02/17 14:23:59 - mmengine - INFO - Epoch(train) [31][ 960/1345] lr: 1.0000e-02 eta: 8:35:28 time: 0.1905 data_time: 0.0059 memory: 8327 grad_norm: 7.1972 loss: 3.7071 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2694 loss_aux: 1.4377 2023/02/17 14:24:03 - mmengine - INFO - Epoch(train) [31][ 980/1345] lr: 1.0000e-02 eta: 8:35:23 time: 0.1906 data_time: 0.0056 memory: 8327 grad_norm: 7.3759 loss: 3.7086 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3185 loss_aux: 1.3900 2023/02/17 14:24:06 - mmengine - INFO - Epoch(train) [31][1000/1345] lr: 1.0000e-02 eta: 8:35:19 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.3444 loss: 3.7092 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3117 loss_aux: 1.3975 2023/02/17 14:24:10 - mmengine - INFO - Epoch(train) [31][1020/1345] lr: 1.0000e-02 eta: 8:35:15 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.4511 loss: 3.3828 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0323 loss_aux: 1.3505 2023/02/17 14:24:14 - mmengine - INFO - Epoch(train) [31][1040/1345] lr: 1.0000e-02 eta: 8:35:11 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.2434 loss: 3.6868 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.2835 loss_aux: 1.4033 2023/02/17 14:24:18 - mmengine - INFO - Epoch(train) [31][1060/1345] lr: 1.0000e-02 eta: 8:35:07 time: 0.1907 data_time: 0.0058 memory: 8327 grad_norm: 7.4301 loss: 3.8258 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3558 loss_aux: 1.4700 2023/02/17 14:24:21 - mmengine - INFO - Epoch(train) [31][1080/1345] lr: 1.0000e-02 eta: 8:35:03 time: 0.1906 data_time: 0.0057 memory: 8327 grad_norm: 7.2921 loss: 3.7035 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2709 loss_aux: 1.4326 2023/02/17 14:24:25 - mmengine - INFO - Epoch(train) [31][1100/1345] lr: 1.0000e-02 eta: 8:34:59 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.2770 loss: 4.1189 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5766 loss_aux: 1.5423 2023/02/17 14:24:29 - mmengine - INFO - Epoch(train) [31][1120/1345] lr: 1.0000e-02 eta: 8:34:55 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.4528 loss: 3.4874 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1180 loss_aux: 1.3694 2023/02/17 14:24:33 - mmengine - INFO - Epoch(train) [31][1140/1345] lr: 1.0000e-02 eta: 8:34:51 time: 0.1890 data_time: 0.0055 memory: 8327 grad_norm: 7.4350 loss: 3.7647 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3558 loss_aux: 1.4089 2023/02/17 14:24:37 - mmengine - INFO - Epoch(train) [31][1160/1345] lr: 1.0000e-02 eta: 8:34:46 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.4466 loss: 3.5454 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1412 loss_aux: 1.4042 2023/02/17 14:24:40 - mmengine - INFO - Epoch(train) [31][1180/1345] lr: 1.0000e-02 eta: 8:34:42 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.5538 loss: 3.7374 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3124 loss_aux: 1.4251 2023/02/17 14:24:44 - mmengine - INFO - Epoch(train) [31][1200/1345] lr: 1.0000e-02 eta: 8:34:38 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.5807 loss: 4.1434 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.6025 loss_aux: 1.5409 2023/02/17 14:24:48 - mmengine - INFO - Epoch(train) [31][1220/1345] lr: 1.0000e-02 eta: 8:34:34 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.6596 loss: 3.9260 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4138 loss_aux: 1.5122 2023/02/17 14:24:52 - mmengine - INFO - Epoch(train) [31][1240/1345] lr: 1.0000e-02 eta: 8:34:30 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.1990 loss: 3.7255 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2942 loss_aux: 1.4312 2023/02/17 14:24:56 - mmengine - INFO - Epoch(train) [31][1260/1345] lr: 1.0000e-02 eta: 8:34:26 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.2494 loss: 3.8425 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3554 loss_aux: 1.4871 2023/02/17 14:24:59 - mmengine - INFO - Epoch(train) [31][1280/1345] lr: 1.0000e-02 eta: 8:34:22 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.5792 loss: 3.4218 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0736 loss_aux: 1.3483 2023/02/17 14:25:03 - mmengine - INFO - Epoch(train) [31][1300/1345] lr: 1.0000e-02 eta: 8:34:17 time: 0.1900 data_time: 0.0067 memory: 8327 grad_norm: 7.2981 loss: 3.5320 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1703 loss_aux: 1.3617 2023/02/17 14:25:07 - mmengine - INFO - Epoch(train) [31][1320/1345] lr: 1.0000e-02 eta: 8:34:13 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.6761 loss: 4.3056 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6800 loss_aux: 1.6257 2023/02/17 14:25:11 - mmengine - INFO - Epoch(train) [31][1340/1345] lr: 1.0000e-02 eta: 8:34:09 time: 0.1889 data_time: 0.0059 memory: 8327 grad_norm: 7.3820 loss: 3.7765 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3214 loss_aux: 1.4551 2023/02/17 14:25:12 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:25:12 - mmengine - INFO - Epoch(train) [31][1345/1345] lr: 1.0000e-02 eta: 8:34:08 time: 0.1843 data_time: 0.0074 memory: 8327 grad_norm: 7.3185 loss: 3.9472 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.4807 loss_aux: 1.4665 2023/02/17 14:25:12 - mmengine - INFO - Saving checkpoint at 31 epochs 2023/02/17 14:25:18 - mmengine - INFO - Epoch(train) [32][ 20/1345] lr: 1.0000e-02 eta: 8:34:05 time: 0.2068 data_time: 0.0159 memory: 8327 grad_norm: 7.2915 loss: 3.3832 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0253 loss_aux: 1.3579 2023/02/17 14:25:22 - mmengine - INFO - Epoch(train) [32][ 40/1345] lr: 1.0000e-02 eta: 8:34:01 time: 0.1915 data_time: 0.0048 memory: 8327 grad_norm: 7.2787 loss: 3.5076 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1362 loss_aux: 1.3714 2023/02/17 14:25:26 - mmengine - INFO - Epoch(train) [32][ 60/1345] lr: 1.0000e-02 eta: 8:33:57 time: 0.1889 data_time: 0.0059 memory: 8327 grad_norm: 7.0939 loss: 3.5125 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1165 loss_aux: 1.3960 2023/02/17 14:25:30 - mmengine - INFO - Epoch(train) [32][ 80/1345] lr: 1.0000e-02 eta: 8:33:53 time: 0.1911 data_time: 0.0082 memory: 8327 grad_norm: 7.0801 loss: 3.4886 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0431 loss_aux: 1.4455 2023/02/17 14:25:33 - mmengine - INFO - Epoch(train) [32][ 100/1345] lr: 1.0000e-02 eta: 8:33:49 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.2215 loss: 3.2750 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9712 loss_aux: 1.3039 2023/02/17 14:25:37 - mmengine - INFO - Epoch(train) [32][ 120/1345] lr: 1.0000e-02 eta: 8:33:45 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.1220 loss: 3.1829 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8544 loss_aux: 1.3285 2023/02/17 14:25:41 - mmengine - INFO - Epoch(train) [32][ 140/1345] lr: 1.0000e-02 eta: 8:33:41 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.4571 loss: 3.5507 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1595 loss_aux: 1.3912 2023/02/17 14:25:45 - mmengine - INFO - Epoch(train) [32][ 160/1345] lr: 1.0000e-02 eta: 8:33:36 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.4639 loss: 3.2161 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9101 loss_aux: 1.3060 2023/02/17 14:25:49 - mmengine - INFO - Epoch(train) [32][ 180/1345] lr: 1.0000e-02 eta: 8:33:32 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.2824 loss: 3.7415 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3114 loss_aux: 1.4301 2023/02/17 14:25:52 - mmengine - INFO - Epoch(train) [32][ 200/1345] lr: 1.0000e-02 eta: 8:33:28 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.3709 loss: 3.4356 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0264 loss_aux: 1.4091 2023/02/17 14:25:56 - mmengine - INFO - Epoch(train) [32][ 220/1345] lr: 1.0000e-02 eta: 8:33:24 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.3370 loss: 3.8257 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3434 loss_aux: 1.4823 2023/02/17 14:26:00 - mmengine - INFO - Epoch(train) [32][ 240/1345] lr: 1.0000e-02 eta: 8:33:20 time: 0.1892 data_time: 0.0064 memory: 8327 grad_norm: 7.1892 loss: 3.3500 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0401 loss_aux: 1.3099 2023/02/17 14:26:04 - mmengine - INFO - Epoch(train) [32][ 260/1345] lr: 1.0000e-02 eta: 8:33:16 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.1485 loss: 3.8571 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3912 loss_aux: 1.4660 2023/02/17 14:26:07 - mmengine - INFO - Epoch(train) [32][ 280/1345] lr: 1.0000e-02 eta: 8:33:12 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.3791 loss: 3.6586 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2907 loss_aux: 1.3679 2023/02/17 14:26:11 - mmengine - INFO - Epoch(train) [32][ 300/1345] lr: 1.0000e-02 eta: 8:33:07 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.3798 loss: 3.6787 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2557 loss_aux: 1.4230 2023/02/17 14:26:12 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:26:15 - mmengine - INFO - Epoch(train) [32][ 320/1345] lr: 1.0000e-02 eta: 8:33:03 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.3128 loss: 3.7703 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2441 loss_aux: 1.5262 2023/02/17 14:26:19 - mmengine - INFO - Epoch(train) [32][ 340/1345] lr: 1.0000e-02 eta: 8:32:59 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 7.1667 loss: 3.7522 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.2813 loss_aux: 1.4709 2023/02/17 14:26:23 - mmengine - INFO - Epoch(train) [32][ 360/1345] lr: 1.0000e-02 eta: 8:32:55 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.4609 loss: 4.2642 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6614 loss_aux: 1.6027 2023/02/17 14:26:26 - mmengine - INFO - Epoch(train) [32][ 380/1345] lr: 1.0000e-02 eta: 8:32:51 time: 0.1902 data_time: 0.0064 memory: 8327 grad_norm: 7.2665 loss: 3.8104 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3218 loss_aux: 1.4886 2023/02/17 14:26:30 - mmengine - INFO - Epoch(train) [32][ 400/1345] lr: 1.0000e-02 eta: 8:32:47 time: 0.1889 data_time: 0.0059 memory: 8327 grad_norm: 7.3000 loss: 3.3606 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0792 loss_aux: 1.2814 2023/02/17 14:26:34 - mmengine - INFO - Epoch(train) [32][ 420/1345] lr: 1.0000e-02 eta: 8:32:43 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.4837 loss: 3.8705 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3657 loss_aux: 1.5048 2023/02/17 14:26:38 - mmengine - INFO - Epoch(train) [32][ 440/1345] lr: 1.0000e-02 eta: 8:32:39 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.3081 loss: 3.7064 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2591 loss_aux: 1.4473 2023/02/17 14:26:42 - mmengine - INFO - Epoch(train) [32][ 460/1345] lr: 1.0000e-02 eta: 8:32:36 time: 0.2091 data_time: 0.0260 memory: 8327 grad_norm: 7.3789 loss: 3.7548 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3070 loss_aux: 1.4478 2023/02/17 14:26:46 - mmengine - INFO - Epoch(train) [32][ 480/1345] lr: 1.0000e-02 eta: 8:32:32 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.4797 loss: 3.9186 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3745 loss_aux: 1.5441 2023/02/17 14:26:50 - mmengine - INFO - Epoch(train) [32][ 500/1345] lr: 1.0000e-02 eta: 8:32:28 time: 0.1891 data_time: 0.0062 memory: 8327 grad_norm: 7.3132 loss: 3.7946 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3325 loss_aux: 1.4621 2023/02/17 14:26:53 - mmengine - INFO - Epoch(train) [32][ 520/1345] lr: 1.0000e-02 eta: 8:32:24 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.1674 loss: 3.5058 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1448 loss_aux: 1.3610 2023/02/17 14:26:57 - mmengine - INFO - Epoch(train) [32][ 540/1345] lr: 1.0000e-02 eta: 8:32:19 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.5392 loss: 3.7193 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2862 loss_aux: 1.4331 2023/02/17 14:27:01 - mmengine - INFO - Epoch(train) [32][ 560/1345] lr: 1.0000e-02 eta: 8:32:15 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.3397 loss: 3.7806 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3201 loss_aux: 1.4605 2023/02/17 14:27:05 - mmengine - INFO - Epoch(train) [32][ 580/1345] lr: 1.0000e-02 eta: 8:32:11 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.3391 loss: 3.5214 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1397 loss_aux: 1.3818 2023/02/17 14:27:08 - mmengine - INFO - Epoch(train) [32][ 600/1345] lr: 1.0000e-02 eta: 8:32:07 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.5260 loss: 3.7312 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2986 loss_aux: 1.4326 2023/02/17 14:27:12 - mmengine - INFO - Epoch(train) [32][ 620/1345] lr: 1.0000e-02 eta: 8:32:03 time: 0.1898 data_time: 0.0069 memory: 8327 grad_norm: 7.3645 loss: 3.6063 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2065 loss_aux: 1.3999 2023/02/17 14:27:16 - mmengine - INFO - Epoch(train) [32][ 640/1345] lr: 1.0000e-02 eta: 8:31:59 time: 0.1894 data_time: 0.0062 memory: 8327 grad_norm: 7.5505 loss: 3.6751 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1757 loss_aux: 1.4994 2023/02/17 14:27:20 - mmengine - INFO - Epoch(train) [32][ 660/1345] lr: 1.0000e-02 eta: 8:31:55 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.4998 loss: 3.5783 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1978 loss_aux: 1.3805 2023/02/17 14:27:24 - mmengine - INFO - Epoch(train) [32][ 680/1345] lr: 1.0000e-02 eta: 8:31:51 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.2308 loss: 3.1688 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8702 loss_aux: 1.2987 2023/02/17 14:27:27 - mmengine - INFO - Epoch(train) [32][ 700/1345] lr: 1.0000e-02 eta: 8:31:46 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.5120 loss: 3.5742 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1576 loss_aux: 1.4165 2023/02/17 14:27:31 - mmengine - INFO - Epoch(train) [32][ 720/1345] lr: 1.0000e-02 eta: 8:31:42 time: 0.1906 data_time: 0.0056 memory: 8327 grad_norm: 7.7944 loss: 3.9697 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4839 loss_aux: 1.4858 2023/02/17 14:27:35 - mmengine - INFO - Epoch(train) [32][ 740/1345] lr: 1.0000e-02 eta: 8:31:38 time: 0.1905 data_time: 0.0057 memory: 8327 grad_norm: 7.2847 loss: 3.6899 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2358 loss_aux: 1.4541 2023/02/17 14:27:39 - mmengine - INFO - Epoch(train) [32][ 760/1345] lr: 1.0000e-02 eta: 8:31:34 time: 0.1893 data_time: 0.0062 memory: 8327 grad_norm: 7.2455 loss: 4.0485 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5552 loss_aux: 1.4933 2023/02/17 14:27:43 - mmengine - INFO - Epoch(train) [32][ 780/1345] lr: 1.0000e-02 eta: 8:31:30 time: 0.1900 data_time: 0.0057 memory: 8327 grad_norm: 7.3453 loss: 4.0669 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5503 loss_aux: 1.5166 2023/02/17 14:27:46 - mmengine - INFO - Epoch(train) [32][ 800/1345] lr: 1.0000e-02 eta: 8:31:26 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.2879 loss: 3.5060 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1564 loss_aux: 1.3497 2023/02/17 14:27:50 - mmengine - INFO - Epoch(train) [32][ 820/1345] lr: 1.0000e-02 eta: 8:31:22 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.4034 loss: 4.0333 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5070 loss_aux: 1.5263 2023/02/17 14:27:54 - mmengine - INFO - Epoch(train) [32][ 840/1345] lr: 1.0000e-02 eta: 8:31:18 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.4027 loss: 3.6320 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1861 loss_aux: 1.4460 2023/02/17 14:27:58 - mmengine - INFO - Epoch(train) [32][ 860/1345] lr: 1.0000e-02 eta: 8:31:14 time: 0.1907 data_time: 0.0079 memory: 8327 grad_norm: 7.2230 loss: 3.5795 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1952 loss_aux: 1.3843 2023/02/17 14:28:02 - mmengine - INFO - Epoch(train) [32][ 880/1345] lr: 1.0000e-02 eta: 8:31:10 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.2535 loss: 3.7093 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2948 loss_aux: 1.4145 2023/02/17 14:28:05 - mmengine - INFO - Epoch(train) [32][ 900/1345] lr: 1.0000e-02 eta: 8:31:06 time: 0.1890 data_time: 0.0059 memory: 8327 grad_norm: 7.2794 loss: 3.5063 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1261 loss_aux: 1.3802 2023/02/17 14:28:09 - mmengine - INFO - Epoch(train) [32][ 920/1345] lr: 1.0000e-02 eta: 8:31:01 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.1753 loss: 3.5340 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1659 loss_aux: 1.3680 2023/02/17 14:28:13 - mmengine - INFO - Epoch(train) [32][ 940/1345] lr: 1.0000e-02 eta: 8:30:57 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.3210 loss: 3.4632 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0810 loss_aux: 1.3822 2023/02/17 14:28:17 - mmengine - INFO - Epoch(train) [32][ 960/1345] lr: 1.0000e-02 eta: 8:30:53 time: 0.1890 data_time: 0.0069 memory: 8327 grad_norm: 7.3156 loss: 3.5891 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1572 loss_aux: 1.4319 2023/02/17 14:28:20 - mmengine - INFO - Epoch(train) [32][ 980/1345] lr: 1.0000e-02 eta: 8:30:49 time: 0.1892 data_time: 0.0060 memory: 8327 grad_norm: 7.3692 loss: 3.4571 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1257 loss_aux: 1.3314 2023/02/17 14:28:24 - mmengine - INFO - Epoch(train) [32][1000/1345] lr: 1.0000e-02 eta: 8:30:45 time: 0.1889 data_time: 0.0060 memory: 8327 grad_norm: 7.3615 loss: 3.8576 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3870 loss_aux: 1.4705 2023/02/17 14:28:28 - mmengine - INFO - Epoch(train) [32][1020/1345] lr: 1.0000e-02 eta: 8:30:41 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.3102 loss: 3.4669 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.1098 loss_aux: 1.3570 2023/02/17 14:28:32 - mmengine - INFO - Epoch(train) [32][1040/1345] lr: 1.0000e-02 eta: 8:30:37 time: 0.1906 data_time: 0.0058 memory: 8327 grad_norm: 7.6843 loss: 3.7498 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3242 loss_aux: 1.4255 2023/02/17 14:28:36 - mmengine - INFO - Epoch(train) [32][1060/1345] lr: 1.0000e-02 eta: 8:30:34 time: 0.2007 data_time: 0.0158 memory: 8327 grad_norm: 7.2035 loss: 3.6102 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2131 loss_aux: 1.3970 2023/02/17 14:28:40 - mmengine - INFO - Epoch(train) [32][1080/1345] lr: 1.0000e-02 eta: 8:30:29 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.4084 loss: 3.8507 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3575 loss_aux: 1.4932 2023/02/17 14:28:43 - mmengine - INFO - Epoch(train) [32][1100/1345] lr: 1.0000e-02 eta: 8:30:25 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.3843 loss: 3.6091 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1781 loss_aux: 1.4310 2023/02/17 14:28:47 - mmengine - INFO - Epoch(train) [32][1120/1345] lr: 1.0000e-02 eta: 8:30:21 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.3074 loss: 3.6785 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2143 loss_aux: 1.4643 2023/02/17 14:28:51 - mmengine - INFO - Epoch(train) [32][1140/1345] lr: 1.0000e-02 eta: 8:30:17 time: 0.1896 data_time: 0.0061 memory: 8327 grad_norm: 7.4976 loss: 3.8735 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3906 loss_aux: 1.4829 2023/02/17 14:28:55 - mmengine - INFO - Epoch(train) [32][1160/1345] lr: 1.0000e-02 eta: 8:30:13 time: 0.1888 data_time: 0.0056 memory: 8327 grad_norm: 7.3298 loss: 3.6811 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2886 loss_aux: 1.3925 2023/02/17 14:28:59 - mmengine - INFO - Epoch(train) [32][1180/1345] lr: 1.0000e-02 eta: 8:30:09 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.4111 loss: 3.8472 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3631 loss_aux: 1.4841 2023/02/17 14:29:02 - mmengine - INFO - Epoch(train) [32][1200/1345] lr: 1.0000e-02 eta: 8:30:05 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.2772 loss: 4.1303 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6254 loss_aux: 1.5049 2023/02/17 14:29:06 - mmengine - INFO - Epoch(train) [32][1220/1345] lr: 1.0000e-02 eta: 8:30:01 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.2099 loss: 3.3542 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0670 loss_aux: 1.2872 2023/02/17 14:29:10 - mmengine - INFO - Epoch(train) [32][1240/1345] lr: 1.0000e-02 eta: 8:29:57 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.3500 loss: 3.9192 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3652 loss_aux: 1.5540 2023/02/17 14:29:14 - mmengine - INFO - Epoch(train) [32][1260/1345] lr: 1.0000e-02 eta: 8:29:52 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.6569 loss: 3.9195 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4009 loss_aux: 1.5186 2023/02/17 14:29:18 - mmengine - INFO - Epoch(train) [32][1280/1345] lr: 1.0000e-02 eta: 8:29:48 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.2114 loss: 3.5820 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1915 loss_aux: 1.3905 2023/02/17 14:29:21 - mmengine - INFO - Epoch(train) [32][1300/1345] lr: 1.0000e-02 eta: 8:29:44 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.5779 loss: 3.5224 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1213 loss_aux: 1.4011 2023/02/17 14:29:22 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:29:25 - mmengine - INFO - Epoch(train) [32][1320/1345] lr: 1.0000e-02 eta: 8:29:40 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.2748 loss: 3.5318 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1669 loss_aux: 1.3649 2023/02/17 14:29:29 - mmengine - INFO - Epoch(train) [32][1340/1345] lr: 1.0000e-02 eta: 8:29:36 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.4273 loss: 3.6261 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2326 loss_aux: 1.3934 2023/02/17 14:29:30 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:29:30 - mmengine - INFO - Epoch(train) [32][1345/1345] lr: 1.0000e-02 eta: 8:29:35 time: 0.1829 data_time: 0.0061 memory: 8327 grad_norm: 7.4588 loss: 4.0191 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.4762 loss_aux: 1.5429 2023/02/17 14:29:30 - mmengine - INFO - Saving checkpoint at 32 epochs 2023/02/17 14:29:36 - mmengine - INFO - Epoch(train) [33][ 20/1345] lr: 1.0000e-02 eta: 8:29:32 time: 0.2060 data_time: 0.0151 memory: 8327 grad_norm: 7.3507 loss: 3.4945 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1250 loss_aux: 1.3695 2023/02/17 14:29:40 - mmengine - INFO - Epoch(train) [33][ 40/1345] lr: 1.0000e-02 eta: 8:29:28 time: 0.1911 data_time: 0.0044 memory: 8327 grad_norm: 7.3690 loss: 3.7704 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3295 loss_aux: 1.4409 2023/02/17 14:29:44 - mmengine - INFO - Epoch(train) [33][ 60/1345] lr: 1.0000e-02 eta: 8:29:24 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.3165 loss: 3.4413 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0841 loss_aux: 1.3572 2023/02/17 14:29:48 - mmengine - INFO - Epoch(train) [33][ 80/1345] lr: 1.0000e-02 eta: 8:29:20 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.5928 loss: 3.6128 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1973 loss_aux: 1.4156 2023/02/17 14:29:52 - mmengine - INFO - Epoch(train) [33][ 100/1345] lr: 1.0000e-02 eta: 8:29:15 time: 0.1887 data_time: 0.0059 memory: 8327 grad_norm: 7.3688 loss: 3.4100 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0587 loss_aux: 1.3513 2023/02/17 14:29:55 - mmengine - INFO - Epoch(train) [33][ 120/1345] lr: 1.0000e-02 eta: 8:29:11 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.2305 loss: 3.5025 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1646 loss_aux: 1.3379 2023/02/17 14:29:59 - mmengine - INFO - Epoch(train) [33][ 140/1345] lr: 1.0000e-02 eta: 8:29:07 time: 0.1890 data_time: 0.0054 memory: 8327 grad_norm: 7.4401 loss: 3.6893 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2486 loss_aux: 1.4406 2023/02/17 14:30:03 - mmengine - INFO - Epoch(train) [33][ 160/1345] lr: 1.0000e-02 eta: 8:29:03 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.4808 loss: 3.7328 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3028 loss_aux: 1.4301 2023/02/17 14:30:07 - mmengine - INFO - Epoch(train) [33][ 180/1345] lr: 1.0000e-02 eta: 8:28:59 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.5327 loss: 3.5927 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1931 loss_aux: 1.3996 2023/02/17 14:30:11 - mmengine - INFO - Epoch(train) [33][ 200/1345] lr: 1.0000e-02 eta: 8:28:55 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.4542 loss: 3.7225 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2808 loss_aux: 1.4417 2023/02/17 14:30:14 - mmengine - INFO - Epoch(train) [33][ 220/1345] lr: 1.0000e-02 eta: 8:28:51 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.2907 loss: 3.6228 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1825 loss_aux: 1.4402 2023/02/17 14:30:18 - mmengine - INFO - Epoch(train) [33][ 240/1345] lr: 1.0000e-02 eta: 8:28:47 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.5068 loss: 3.5076 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1283 loss_aux: 1.3793 2023/02/17 14:30:22 - mmengine - INFO - Epoch(train) [33][ 260/1345] lr: 1.0000e-02 eta: 8:28:43 time: 0.1897 data_time: 0.0056 memory: 8327 grad_norm: 7.4215 loss: 3.8195 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3391 loss_aux: 1.4805 2023/02/17 14:30:26 - mmengine - INFO - Epoch(train) [33][ 280/1345] lr: 1.0000e-02 eta: 8:28:38 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.4753 loss: 3.6074 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1604 loss_aux: 1.4470 2023/02/17 14:30:29 - mmengine - INFO - Epoch(train) [33][ 300/1345] lr: 1.0000e-02 eta: 8:28:34 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.6182 loss: 3.7031 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3055 loss_aux: 1.3976 2023/02/17 14:30:33 - mmengine - INFO - Epoch(train) [33][ 320/1345] lr: 1.0000e-02 eta: 8:28:30 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.2987 loss: 3.7089 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2416 loss_aux: 1.4674 2023/02/17 14:30:37 - mmengine - INFO - Epoch(train) [33][ 340/1345] lr: 1.0000e-02 eta: 8:28:26 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.3053 loss: 3.5335 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1870 loss_aux: 1.3465 2023/02/17 14:30:41 - mmengine - INFO - Epoch(train) [33][ 360/1345] lr: 1.0000e-02 eta: 8:28:22 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.2790 loss: 3.4485 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0976 loss_aux: 1.3509 2023/02/17 14:30:45 - mmengine - INFO - Epoch(train) [33][ 380/1345] lr: 1.0000e-02 eta: 8:28:18 time: 0.1906 data_time: 0.0067 memory: 8327 grad_norm: 7.4124 loss: 3.4684 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0840 loss_aux: 1.3844 2023/02/17 14:30:48 - mmengine - INFO - Epoch(train) [33][ 400/1345] lr: 1.0000e-02 eta: 8:28:14 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.4103 loss: 4.2461 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5989 loss_aux: 1.6472 2023/02/17 14:30:52 - mmengine - INFO - Epoch(train) [33][ 420/1345] lr: 1.0000e-02 eta: 8:28:10 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.3546 loss: 3.8484 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3707 loss_aux: 1.4777 2023/02/17 14:30:56 - mmengine - INFO - Epoch(train) [33][ 440/1345] lr: 1.0000e-02 eta: 8:28:06 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.3912 loss: 3.4961 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1505 loss_aux: 1.3456 2023/02/17 14:31:00 - mmengine - INFO - Epoch(train) [33][ 460/1345] lr: 1.0000e-02 eta: 8:28:02 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.3247 loss: 4.1601 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5547 loss_aux: 1.6054 2023/02/17 14:31:04 - mmengine - INFO - Epoch(train) [33][ 480/1345] lr: 1.0000e-02 eta: 8:27:57 time: 0.1889 data_time: 0.0059 memory: 8327 grad_norm: 7.4595 loss: 3.6634 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2654 loss_aux: 1.3980 2023/02/17 14:31:07 - mmengine - INFO - Epoch(train) [33][ 500/1345] lr: 1.0000e-02 eta: 8:27:53 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.0209 loss: 3.5395 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1222 loss_aux: 1.4173 2023/02/17 14:31:11 - mmengine - INFO - Epoch(train) [33][ 520/1345] lr: 1.0000e-02 eta: 8:27:49 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.5248 loss: 3.3950 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0482 loss_aux: 1.3469 2023/02/17 14:31:15 - mmengine - INFO - Epoch(train) [33][ 540/1345] lr: 1.0000e-02 eta: 8:27:45 time: 0.1899 data_time: 0.0058 memory: 8327 grad_norm: 7.5426 loss: 3.9610 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4518 loss_aux: 1.5092 2023/02/17 14:31:19 - mmengine - INFO - Epoch(train) [33][ 560/1345] lr: 1.0000e-02 eta: 8:27:41 time: 0.1889 data_time: 0.0059 memory: 8327 grad_norm: 7.1833 loss: 4.1105 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6008 loss_aux: 1.5097 2023/02/17 14:31:23 - mmengine - INFO - Epoch(train) [33][ 580/1345] lr: 1.0000e-02 eta: 8:27:37 time: 0.1891 data_time: 0.0060 memory: 8327 grad_norm: 7.2703 loss: 3.5742 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1929 loss_aux: 1.3812 2023/02/17 14:31:26 - mmengine - INFO - Epoch(train) [33][ 600/1345] lr: 1.0000e-02 eta: 8:27:33 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.2434 loss: 3.6100 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1903 loss_aux: 1.4197 2023/02/17 14:31:30 - mmengine - INFO - Epoch(train) [33][ 620/1345] lr: 1.0000e-02 eta: 8:27:29 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.3527 loss: 3.3146 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9619 loss_aux: 1.3527 2023/02/17 14:31:34 - mmengine - INFO - Epoch(train) [33][ 640/1345] lr: 1.0000e-02 eta: 8:27:25 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.6094 loss: 3.5342 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1120 loss_aux: 1.4222 2023/02/17 14:31:38 - mmengine - INFO - Epoch(train) [33][ 660/1345] lr: 1.0000e-02 eta: 8:27:21 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.5449 loss: 3.8763 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3858 loss_aux: 1.4905 2023/02/17 14:31:41 - mmengine - INFO - Epoch(train) [33][ 680/1345] lr: 1.0000e-02 eta: 8:27:16 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.4801 loss: 3.7266 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3103 loss_aux: 1.4163 2023/02/17 14:31:45 - mmengine - INFO - Epoch(train) [33][ 700/1345] lr: 1.0000e-02 eta: 8:27:12 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.2419 loss: 3.6227 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2197 loss_aux: 1.4031 2023/02/17 14:31:49 - mmengine - INFO - Epoch(train) [33][ 720/1345] lr: 1.0000e-02 eta: 8:27:08 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.4629 loss: 3.7395 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2595 loss_aux: 1.4800 2023/02/17 14:31:53 - mmengine - INFO - Epoch(train) [33][ 740/1345] lr: 1.0000e-02 eta: 8:27:04 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.3016 loss: 3.9372 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4322 loss_aux: 1.5049 2023/02/17 14:31:57 - mmengine - INFO - Epoch(train) [33][ 760/1345] lr: 1.0000e-02 eta: 8:27:00 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.3602 loss: 3.7535 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2498 loss_aux: 1.5036 2023/02/17 14:32:00 - mmengine - INFO - Epoch(train) [33][ 780/1345] lr: 1.0000e-02 eta: 8:26:56 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.6273 loss: 3.8464 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3881 loss_aux: 1.4583 2023/02/17 14:32:04 - mmengine - INFO - Epoch(train) [33][ 800/1345] lr: 1.0000e-02 eta: 8:26:52 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.4046 loss: 3.5271 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1964 loss_aux: 1.3306 2023/02/17 14:32:08 - mmengine - INFO - Epoch(train) [33][ 820/1345] lr: 1.0000e-02 eta: 8:26:48 time: 0.1901 data_time: 0.0063 memory: 8327 grad_norm: 7.7086 loss: 3.6974 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.2403 loss_aux: 1.4571 2023/02/17 14:32:12 - mmengine - INFO - Epoch(train) [33][ 840/1345] lr: 1.0000e-02 eta: 8:26:44 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.4172 loss: 3.7177 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3479 loss_aux: 1.3698 2023/02/17 14:32:16 - mmengine - INFO - Epoch(train) [33][ 860/1345] lr: 1.0000e-02 eta: 8:26:40 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.3388 loss: 3.5018 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1181 loss_aux: 1.3838 2023/02/17 14:32:19 - mmengine - INFO - Epoch(train) [33][ 880/1345] lr: 1.0000e-02 eta: 8:26:36 time: 0.1900 data_time: 0.0057 memory: 8327 grad_norm: 7.3857 loss: 3.5097 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1287 loss_aux: 1.3810 2023/02/17 14:32:23 - mmengine - INFO - Epoch(train) [33][ 900/1345] lr: 1.0000e-02 eta: 8:26:31 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.5456 loss: 3.8868 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3634 loss_aux: 1.5234 2023/02/17 14:32:27 - mmengine - INFO - Epoch(train) [33][ 920/1345] lr: 1.0000e-02 eta: 8:26:27 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.3646 loss: 3.5558 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1728 loss_aux: 1.3830 2023/02/17 14:32:31 - mmengine - INFO - Epoch(train) [33][ 940/1345] lr: 1.0000e-02 eta: 8:26:23 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.2996 loss: 3.2677 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9819 loss_aux: 1.2858 2023/02/17 14:32:35 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:32:35 - mmengine - INFO - Epoch(train) [33][ 960/1345] lr: 1.0000e-02 eta: 8:26:19 time: 0.1904 data_time: 0.0073 memory: 8327 grad_norm: 7.4025 loss: 3.4365 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0966 loss_aux: 1.3399 2023/02/17 14:32:38 - mmengine - INFO - Epoch(train) [33][ 980/1345] lr: 1.0000e-02 eta: 8:26:15 time: 0.1888 data_time: 0.0059 memory: 8327 grad_norm: 7.5356 loss: 3.9139 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3657 loss_aux: 1.5482 2023/02/17 14:32:42 - mmengine - INFO - Epoch(train) [33][1000/1345] lr: 1.0000e-02 eta: 8:26:11 time: 0.1902 data_time: 0.0063 memory: 8327 grad_norm: 7.2827 loss: 3.9490 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4855 loss_aux: 1.4636 2023/02/17 14:32:46 - mmengine - INFO - Epoch(train) [33][1020/1345] lr: 1.0000e-02 eta: 8:26:07 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.4895 loss: 3.6778 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2736 loss_aux: 1.4042 2023/02/17 14:32:50 - mmengine - INFO - Epoch(train) [33][1040/1345] lr: 1.0000e-02 eta: 8:26:03 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.2783 loss: 3.3837 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0565 loss_aux: 1.3272 2023/02/17 14:32:53 - mmengine - INFO - Epoch(train) [33][1060/1345] lr: 1.0000e-02 eta: 8:25:59 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.2907 loss: 3.9135 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4468 loss_aux: 1.4667 2023/02/17 14:32:57 - mmengine - INFO - Epoch(train) [33][1080/1345] lr: 1.0000e-02 eta: 8:25:55 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.4298 loss: 3.4647 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0796 loss_aux: 1.3850 2023/02/17 14:33:01 - mmengine - INFO - Epoch(train) [33][1100/1345] lr: 1.0000e-02 eta: 8:25:51 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.6523 loss: 3.7105 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2387 loss_aux: 1.4717 2023/02/17 14:33:05 - mmengine - INFO - Epoch(train) [33][1120/1345] lr: 1.0000e-02 eta: 8:25:47 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.3150 loss: 3.2919 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9931 loss_aux: 1.2988 2023/02/17 14:33:09 - mmengine - INFO - Epoch(train) [33][1140/1345] lr: 1.0000e-02 eta: 8:25:42 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.5097 loss: 3.3263 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0062 loss_aux: 1.3200 2023/02/17 14:33:12 - mmengine - INFO - Epoch(train) [33][1160/1345] lr: 1.0000e-02 eta: 8:25:38 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.2385 loss: 3.8189 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3583 loss_aux: 1.4606 2023/02/17 14:33:16 - mmengine - INFO - Epoch(train) [33][1180/1345] lr: 1.0000e-02 eta: 8:25:34 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.1893 loss: 3.6921 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2046 loss_aux: 1.4875 2023/02/17 14:33:20 - mmengine - INFO - Epoch(train) [33][1200/1345] lr: 1.0000e-02 eta: 8:25:30 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.2778 loss: 3.6393 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2393 loss_aux: 1.4001 2023/02/17 14:33:24 - mmengine - INFO - Epoch(train) [33][1220/1345] lr: 1.0000e-02 eta: 8:25:26 time: 0.1889 data_time: 0.0060 memory: 8327 grad_norm: 6.9850 loss: 3.6389 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2367 loss_aux: 1.4022 2023/02/17 14:33:28 - mmengine - INFO - Epoch(train) [33][1240/1345] lr: 1.0000e-02 eta: 8:25:22 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.2426 loss: 3.0394 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8163 loss_aux: 1.2232 2023/02/17 14:33:31 - mmengine - INFO - Epoch(train) [33][1260/1345] lr: 1.0000e-02 eta: 8:25:18 time: 0.1889 data_time: 0.0056 memory: 8327 grad_norm: 7.4512 loss: 3.1591 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8946 loss_aux: 1.2645 2023/02/17 14:33:35 - mmengine - INFO - Epoch(train) [33][1280/1345] lr: 1.0000e-02 eta: 8:25:14 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.3421 loss: 3.8427 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3321 loss_aux: 1.5106 2023/02/17 14:33:39 - mmengine - INFO - Epoch(train) [33][1300/1345] lr: 1.0000e-02 eta: 8:25:10 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.5326 loss: 3.8909 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3684 loss_aux: 1.5225 2023/02/17 14:33:43 - mmengine - INFO - Epoch(train) [33][1320/1345] lr: 1.0000e-02 eta: 8:25:06 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.5964 loss: 3.9180 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4074 loss_aux: 1.5106 2023/02/17 14:33:46 - mmengine - INFO - Epoch(train) [33][1340/1345] lr: 1.0000e-02 eta: 8:25:01 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.3459 loss: 3.3936 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0753 loss_aux: 1.3184 2023/02/17 14:33:47 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:33:47 - mmengine - INFO - Epoch(train) [33][1345/1345] lr: 1.0000e-02 eta: 8:25:00 time: 0.1833 data_time: 0.0059 memory: 8327 grad_norm: 7.3841 loss: 3.7949 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.3508 loss_aux: 1.4441 2023/02/17 14:33:47 - mmengine - INFO - Saving checkpoint at 33 epochs 2023/02/17 14:33:54 - mmengine - INFO - Epoch(train) [34][ 20/1345] lr: 1.0000e-02 eta: 8:24:58 time: 0.2138 data_time: 0.0217 memory: 8327 grad_norm: 7.3620 loss: 3.9418 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4327 loss_aux: 1.5091 2023/02/17 14:33:58 - mmengine - INFO - Epoch(train) [34][ 40/1345] lr: 1.0000e-02 eta: 8:24:54 time: 0.1904 data_time: 0.0045 memory: 8327 grad_norm: 7.4566 loss: 3.6784 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2107 loss_aux: 1.4677 2023/02/17 14:34:02 - mmengine - INFO - Epoch(train) [34][ 60/1345] lr: 1.0000e-02 eta: 8:24:50 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.3670 loss: 3.0032 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7358 loss_aux: 1.2674 2023/02/17 14:34:06 - mmengine - INFO - Epoch(train) [34][ 80/1345] lr: 1.0000e-02 eta: 8:24:46 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.5956 loss: 3.3238 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0087 loss_aux: 1.3151 2023/02/17 14:34:09 - mmengine - INFO - Epoch(train) [34][ 100/1345] lr: 1.0000e-02 eta: 8:24:41 time: 0.1886 data_time: 0.0059 memory: 8327 grad_norm: 7.3568 loss: 3.4870 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0837 loss_aux: 1.4033 2023/02/17 14:34:13 - mmengine - INFO - Epoch(train) [34][ 120/1345] lr: 1.0000e-02 eta: 8:24:37 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.3012 loss: 3.3228 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0286 loss_aux: 1.2942 2023/02/17 14:34:17 - mmengine - INFO - Epoch(train) [34][ 140/1345] lr: 1.0000e-02 eta: 8:24:33 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.3480 loss: 3.1831 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9284 loss_aux: 1.2547 2023/02/17 14:34:21 - mmengine - INFO - Epoch(train) [34][ 160/1345] lr: 1.0000e-02 eta: 8:24:29 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.4730 loss: 3.7759 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3030 loss_aux: 1.4730 2023/02/17 14:34:25 - mmengine - INFO - Epoch(train) [34][ 180/1345] lr: 1.0000e-02 eta: 8:24:25 time: 0.1902 data_time: 0.0066 memory: 8327 grad_norm: 7.4778 loss: 3.7202 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2994 loss_aux: 1.4208 2023/02/17 14:34:28 - mmengine - INFO - Epoch(train) [34][ 200/1345] lr: 1.0000e-02 eta: 8:24:21 time: 0.1889 data_time: 0.0059 memory: 8327 grad_norm: 7.5418 loss: 3.5684 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1717 loss_aux: 1.3967 2023/02/17 14:34:32 - mmengine - INFO - Epoch(train) [34][ 220/1345] lr: 1.0000e-02 eta: 8:24:17 time: 0.1891 data_time: 0.0060 memory: 8327 grad_norm: 7.5990 loss: 3.4633 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.1181 loss_aux: 1.3453 2023/02/17 14:34:36 - mmengine - INFO - Epoch(train) [34][ 240/1345] lr: 1.0000e-02 eta: 8:24:13 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.4175 loss: 3.7131 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2597 loss_aux: 1.4534 2023/02/17 14:34:40 - mmengine - INFO - Epoch(train) [34][ 260/1345] lr: 1.0000e-02 eta: 8:24:09 time: 0.1911 data_time: 0.0059 memory: 8327 grad_norm: 7.3787 loss: 3.5672 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1341 loss_aux: 1.4331 2023/02/17 14:34:44 - mmengine - INFO - Epoch(train) [34][ 280/1345] lr: 1.0000e-02 eta: 8:24:05 time: 0.1904 data_time: 0.0057 memory: 8327 grad_norm: 7.5750 loss: 3.9685 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4363 loss_aux: 1.5322 2023/02/17 14:34:47 - mmengine - INFO - Epoch(train) [34][ 300/1345] lr: 1.0000e-02 eta: 8:24:01 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.4604 loss: 3.5030 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0981 loss_aux: 1.4049 2023/02/17 14:34:51 - mmengine - INFO - Epoch(train) [34][ 320/1345] lr: 1.0000e-02 eta: 8:23:57 time: 0.1903 data_time: 0.0058 memory: 8327 grad_norm: 7.3941 loss: 3.4845 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1191 loss_aux: 1.3654 2023/02/17 14:34:55 - mmengine - INFO - Epoch(train) [34][ 340/1345] lr: 1.0000e-02 eta: 8:23:53 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.4968 loss: 3.5461 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.1507 loss_aux: 1.3953 2023/02/17 14:34:59 - mmengine - INFO - Epoch(train) [34][ 360/1345] lr: 1.0000e-02 eta: 8:23:49 time: 0.1892 data_time: 0.0060 memory: 8327 grad_norm: 7.3219 loss: 3.5418 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1840 loss_aux: 1.3577 2023/02/17 14:35:02 - mmengine - INFO - Epoch(train) [34][ 380/1345] lr: 1.0000e-02 eta: 8:23:44 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.3643 loss: 3.7649 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3239 loss_aux: 1.4410 2023/02/17 14:35:06 - mmengine - INFO - Epoch(train) [34][ 400/1345] lr: 1.0000e-02 eta: 8:23:40 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.4373 loss: 3.8911 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3956 loss_aux: 1.4955 2023/02/17 14:35:10 - mmengine - INFO - Epoch(train) [34][ 420/1345] lr: 1.0000e-02 eta: 8:23:36 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.3183 loss: 3.6834 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2523 loss_aux: 1.4311 2023/02/17 14:35:14 - mmengine - INFO - Epoch(train) [34][ 440/1345] lr: 1.0000e-02 eta: 8:23:32 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.3934 loss: 3.3844 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0312 loss_aux: 1.3531 2023/02/17 14:35:18 - mmengine - INFO - Epoch(train) [34][ 460/1345] lr: 1.0000e-02 eta: 8:23:28 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.3491 loss: 3.6814 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2568 loss_aux: 1.4246 2023/02/17 14:35:21 - mmengine - INFO - Epoch(train) [34][ 480/1345] lr: 1.0000e-02 eta: 8:23:24 time: 0.1892 data_time: 0.0061 memory: 8327 grad_norm: 7.4106 loss: 3.7125 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.2568 loss_aux: 1.4557 2023/02/17 14:35:25 - mmengine - INFO - Epoch(train) [34][ 500/1345] lr: 1.0000e-02 eta: 8:23:20 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.4502 loss: 3.6617 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2329 loss_aux: 1.4288 2023/02/17 14:35:29 - mmengine - INFO - Epoch(train) [34][ 520/1345] lr: 1.0000e-02 eta: 8:23:16 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.4062 loss: 3.7378 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2647 loss_aux: 1.4731 2023/02/17 14:35:33 - mmengine - INFO - Epoch(train) [34][ 540/1345] lr: 1.0000e-02 eta: 8:23:12 time: 0.1891 data_time: 0.0060 memory: 8327 grad_norm: 7.3359 loss: 3.4565 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0872 loss_aux: 1.3692 2023/02/17 14:35:37 - mmengine - INFO - Epoch(train) [34][ 560/1345] lr: 1.0000e-02 eta: 8:23:08 time: 0.1889 data_time: 0.0059 memory: 8327 grad_norm: 7.3983 loss: 3.7685 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3295 loss_aux: 1.4389 2023/02/17 14:35:40 - mmengine - INFO - Epoch(train) [34][ 580/1345] lr: 1.0000e-02 eta: 8:23:04 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.6222 loss: 4.1362 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5795 loss_aux: 1.5567 2023/02/17 14:35:44 - mmengine - INFO - Epoch(train) [34][ 600/1345] lr: 1.0000e-02 eta: 8:23:00 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.4815 loss: 3.4458 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.0379 loss_aux: 1.4079 2023/02/17 14:35:47 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:35:48 - mmengine - INFO - Epoch(train) [34][ 620/1345] lr: 1.0000e-02 eta: 8:22:55 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.2304 loss: 3.7793 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3841 loss_aux: 1.3952 2023/02/17 14:35:52 - mmengine - INFO - Epoch(train) [34][ 640/1345] lr: 1.0000e-02 eta: 8:22:51 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.2652 loss: 3.6559 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2652 loss_aux: 1.3907 2023/02/17 14:35:55 - mmengine - INFO - Epoch(train) [34][ 660/1345] lr: 1.0000e-02 eta: 8:22:47 time: 0.1904 data_time: 0.0066 memory: 8327 grad_norm: 7.1227 loss: 3.5489 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1601 loss_aux: 1.3888 2023/02/17 14:35:59 - mmengine - INFO - Epoch(train) [34][ 680/1345] lr: 1.0000e-02 eta: 8:22:43 time: 0.1887 data_time: 0.0058 memory: 8327 grad_norm: 7.3398 loss: 3.4096 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.0620 loss_aux: 1.3475 2023/02/17 14:36:03 - mmengine - INFO - Epoch(train) [34][ 700/1345] lr: 1.0000e-02 eta: 8:22:39 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.1617 loss: 3.2645 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9475 loss_aux: 1.3170 2023/02/17 14:36:07 - mmengine - INFO - Epoch(train) [34][ 720/1345] lr: 1.0000e-02 eta: 8:22:35 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.7555 loss: 4.0125 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5201 loss_aux: 1.4924 2023/02/17 14:36:11 - mmengine - INFO - Epoch(train) [34][ 740/1345] lr: 1.0000e-02 eta: 8:22:31 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.4049 loss: 3.6424 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2243 loss_aux: 1.4181 2023/02/17 14:36:14 - mmengine - INFO - Epoch(train) [34][ 760/1345] lr: 1.0000e-02 eta: 8:22:27 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.3711 loss: 3.4597 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1105 loss_aux: 1.3492 2023/02/17 14:36:18 - mmengine - INFO - Epoch(train) [34][ 780/1345] lr: 1.0000e-02 eta: 8:22:23 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.4960 loss: 3.7765 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3787 loss_aux: 1.3978 2023/02/17 14:36:22 - mmengine - INFO - Epoch(train) [34][ 800/1345] lr: 1.0000e-02 eta: 8:22:19 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.5288 loss: 3.4425 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0827 loss_aux: 1.3598 2023/02/17 14:36:26 - mmengine - INFO - Epoch(train) [34][ 820/1345] lr: 1.0000e-02 eta: 8:22:15 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.3199 loss: 3.4244 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0504 loss_aux: 1.3740 2023/02/17 14:36:30 - mmengine - INFO - Epoch(train) [34][ 840/1345] lr: 1.0000e-02 eta: 8:22:10 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.2114 loss: 3.4450 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0563 loss_aux: 1.3887 2023/02/17 14:36:33 - mmengine - INFO - Epoch(train) [34][ 860/1345] lr: 1.0000e-02 eta: 8:22:06 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.5449 loss: 3.7444 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3056 loss_aux: 1.4388 2023/02/17 14:36:37 - mmengine - INFO - Epoch(train) [34][ 880/1345] lr: 1.0000e-02 eta: 8:22:02 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.5615 loss: 3.6025 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1599 loss_aux: 1.4426 2023/02/17 14:36:41 - mmengine - INFO - Epoch(train) [34][ 900/1345] lr: 1.0000e-02 eta: 8:21:58 time: 0.1908 data_time: 0.0076 memory: 8327 grad_norm: 7.5545 loss: 3.9216 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4087 loss_aux: 1.5129 2023/02/17 14:36:45 - mmengine - INFO - Epoch(train) [34][ 920/1345] lr: 1.0000e-02 eta: 8:21:54 time: 0.1889 data_time: 0.0059 memory: 8327 grad_norm: 7.3096 loss: 3.6400 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1962 loss_aux: 1.4437 2023/02/17 14:36:48 - mmengine - INFO - Epoch(train) [34][ 940/1345] lr: 1.0000e-02 eta: 8:21:50 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.2662 loss: 3.5350 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1358 loss_aux: 1.3991 2023/02/17 14:36:52 - mmengine - INFO - Epoch(train) [34][ 960/1345] lr: 1.0000e-02 eta: 8:21:46 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.4571 loss: 3.6199 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.2259 loss_aux: 1.3939 2023/02/17 14:36:56 - mmengine - INFO - Epoch(train) [34][ 980/1345] lr: 1.0000e-02 eta: 8:21:42 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.4871 loss: 3.3792 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1393 loss_aux: 1.2399 2023/02/17 14:37:00 - mmengine - INFO - Epoch(train) [34][1000/1345] lr: 1.0000e-02 eta: 8:21:38 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.4308 loss: 3.8671 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3797 loss_aux: 1.4874 2023/02/17 14:37:04 - mmengine - INFO - Epoch(train) [34][1020/1345] lr: 1.0000e-02 eta: 8:21:34 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.3936 loss: 3.3175 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0165 loss_aux: 1.3010 2023/02/17 14:37:07 - mmengine - INFO - Epoch(train) [34][1040/1345] lr: 1.0000e-02 eta: 8:21:30 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.5076 loss: 4.0283 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.5185 loss_aux: 1.5098 2023/02/17 14:37:11 - mmengine - INFO - Epoch(train) [34][1060/1345] lr: 1.0000e-02 eta: 8:21:26 time: 0.1902 data_time: 0.0066 memory: 8327 grad_norm: 7.5070 loss: 3.6240 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.1726 loss_aux: 1.4514 2023/02/17 14:37:15 - mmengine - INFO - Epoch(train) [34][1080/1345] lr: 1.0000e-02 eta: 8:21:22 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.5823 loss: 3.4315 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.1230 loss_aux: 1.3085 2023/02/17 14:37:19 - mmengine - INFO - Epoch(train) [34][1100/1345] lr: 1.0000e-02 eta: 8:21:18 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.6306 loss: 3.6372 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2411 loss_aux: 1.3962 2023/02/17 14:37:23 - mmengine - INFO - Epoch(train) [34][1120/1345] lr: 1.0000e-02 eta: 8:21:13 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.4841 loss: 3.8094 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3072 loss_aux: 1.5022 2023/02/17 14:37:26 - mmengine - INFO - Epoch(train) [34][1140/1345] lr: 1.0000e-02 eta: 8:21:09 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.2670 loss: 3.5737 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1994 loss_aux: 1.3743 2023/02/17 14:37:30 - mmengine - INFO - Epoch(train) [34][1160/1345] lr: 1.0000e-02 eta: 8:21:05 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.2641 loss: 3.6594 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2307 loss_aux: 1.4287 2023/02/17 14:37:34 - mmengine - INFO - Epoch(train) [34][1180/1345] lr: 1.0000e-02 eta: 8:21:01 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.4864 loss: 3.7610 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3482 loss_aux: 1.4128 2023/02/17 14:37:38 - mmengine - INFO - Epoch(train) [34][1200/1345] lr: 1.0000e-02 eta: 8:20:57 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.3458 loss: 3.5615 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1631 loss_aux: 1.3984 2023/02/17 14:37:42 - mmengine - INFO - Epoch(train) [34][1220/1345] lr: 1.0000e-02 eta: 8:20:53 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.3966 loss: 3.4447 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1343 loss_aux: 1.3104 2023/02/17 14:37:45 - mmengine - INFO - Epoch(train) [34][1240/1345] lr: 1.0000e-02 eta: 8:20:49 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.2883 loss: 3.6304 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2017 loss_aux: 1.4287 2023/02/17 14:37:49 - mmengine - INFO - Epoch(train) [34][1260/1345] lr: 1.0000e-02 eta: 8:20:45 time: 0.1900 data_time: 0.0064 memory: 8327 grad_norm: 7.6798 loss: 3.9375 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4208 loss_aux: 1.5167 2023/02/17 14:37:53 - mmengine - INFO - Epoch(train) [34][1280/1345] lr: 1.0000e-02 eta: 8:20:41 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.4161 loss: 3.5326 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1255 loss_aux: 1.4071 2023/02/17 14:37:57 - mmengine - INFO - Epoch(train) [34][1300/1345] lr: 1.0000e-02 eta: 8:20:37 time: 0.1890 data_time: 0.0059 memory: 8327 grad_norm: 7.3385 loss: 3.4847 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1112 loss_aux: 1.3734 2023/02/17 14:38:00 - mmengine - INFO - Epoch(train) [34][1320/1345] lr: 1.0000e-02 eta: 8:20:33 time: 0.1900 data_time: 0.0065 memory: 8327 grad_norm: 7.4290 loss: 3.4728 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.1190 loss_aux: 1.3538 2023/02/17 14:38:04 - mmengine - INFO - Epoch(train) [34][1340/1345] lr: 1.0000e-02 eta: 8:20:29 time: 0.1891 data_time: 0.0060 memory: 8327 grad_norm: 7.5031 loss: 4.0723 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5857 loss_aux: 1.4866 2023/02/17 14:38:05 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:38:05 - mmengine - INFO - Epoch(train) [34][1345/1345] lr: 1.0000e-02 eta: 8:20:27 time: 0.1837 data_time: 0.0060 memory: 8327 grad_norm: 7.3867 loss: 4.4588 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.8532 loss_aux: 1.6056 2023/02/17 14:38:05 - mmengine - INFO - Saving checkpoint at 34 epochs 2023/02/17 14:38:12 - mmengine - INFO - Epoch(train) [35][ 20/1345] lr: 1.0000e-02 eta: 8:20:25 time: 0.2082 data_time: 0.0153 memory: 8327 grad_norm: 7.1505 loss: 3.3420 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0127 loss_aux: 1.3293 2023/02/17 14:38:16 - mmengine - INFO - Epoch(train) [35][ 40/1345] lr: 1.0000e-02 eta: 8:20:21 time: 0.1926 data_time: 0.0040 memory: 8327 grad_norm: 7.3127 loss: 3.7538 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3106 loss_aux: 1.4432 2023/02/17 14:38:20 - mmengine - INFO - Epoch(train) [35][ 60/1345] lr: 1.0000e-02 eta: 8:20:17 time: 0.1902 data_time: 0.0073 memory: 8327 grad_norm: 7.3921 loss: 3.3735 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0089 loss_aux: 1.3646 2023/02/17 14:38:23 - mmengine - INFO - Epoch(train) [35][ 80/1345] lr: 1.0000e-02 eta: 8:20:13 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.1580 loss: 3.6059 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1931 loss_aux: 1.4128 2023/02/17 14:38:27 - mmengine - INFO - Epoch(train) [35][ 100/1345] lr: 1.0000e-02 eta: 8:20:09 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.2722 loss: 3.3962 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0364 loss_aux: 1.3598 2023/02/17 14:38:31 - mmengine - INFO - Epoch(train) [35][ 120/1345] lr: 1.0000e-02 eta: 8:20:05 time: 0.1904 data_time: 0.0072 memory: 8327 grad_norm: 7.6076 loss: 3.4901 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1221 loss_aux: 1.3680 2023/02/17 14:38:35 - mmengine - INFO - Epoch(train) [35][ 140/1345] lr: 1.0000e-02 eta: 8:20:01 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.4078 loss: 3.4830 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1083 loss_aux: 1.3747 2023/02/17 14:38:38 - mmengine - INFO - Epoch(train) [35][ 160/1345] lr: 1.0000e-02 eta: 8:19:56 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.6139 loss: 3.7115 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2792 loss_aux: 1.4322 2023/02/17 14:38:42 - mmengine - INFO - Epoch(train) [35][ 180/1345] lr: 1.0000e-02 eta: 8:19:52 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.7207 loss: 3.6507 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2061 loss_aux: 1.4446 2023/02/17 14:38:46 - mmengine - INFO - Epoch(train) [35][ 200/1345] lr: 1.0000e-02 eta: 8:19:48 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.3965 loss: 3.5294 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1466 loss_aux: 1.3828 2023/02/17 14:38:50 - mmengine - INFO - Epoch(train) [35][ 220/1345] lr: 1.0000e-02 eta: 8:19:44 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.3856 loss: 3.8723 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4227 loss_aux: 1.4496 2023/02/17 14:38:54 - mmengine - INFO - Epoch(train) [35][ 240/1345] lr: 1.0000e-02 eta: 8:19:40 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.1337 loss: 3.7517 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3164 loss_aux: 1.4354 2023/02/17 14:38:57 - mmengine - INFO - Epoch(train) [35][ 260/1345] lr: 1.0000e-02 eta: 8:19:36 time: 0.1888 data_time: 0.0058 memory: 8327 grad_norm: 7.3121 loss: 3.7064 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2545 loss_aux: 1.4519 2023/02/17 14:38:59 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:39:01 - mmengine - INFO - Epoch(train) [35][ 280/1345] lr: 1.0000e-02 eta: 8:19:32 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.2969 loss: 3.5700 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1900 loss_aux: 1.3799 2023/02/17 14:39:05 - mmengine - INFO - Epoch(train) [35][ 300/1345] lr: 1.0000e-02 eta: 8:19:28 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.2245 loss: 3.6666 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2919 loss_aux: 1.3748 2023/02/17 14:39:09 - mmengine - INFO - Epoch(train) [35][ 320/1345] lr: 1.0000e-02 eta: 8:19:24 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.3771 loss: 3.8382 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3590 loss_aux: 1.4791 2023/02/17 14:39:13 - mmengine - INFO - Epoch(train) [35][ 340/1345] lr: 1.0000e-02 eta: 8:19:20 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.4111 loss: 3.5424 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1651 loss_aux: 1.3773 2023/02/17 14:39:16 - mmengine - INFO - Epoch(train) [35][ 360/1345] lr: 1.0000e-02 eta: 8:19:16 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.4405 loss: 3.4712 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.0716 loss_aux: 1.3996 2023/02/17 14:39:21 - mmengine - INFO - Epoch(train) [35][ 380/1345] lr: 1.0000e-02 eta: 8:19:13 time: 0.2104 data_time: 0.0271 memory: 8327 grad_norm: 7.5459 loss: 3.5753 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1903 loss_aux: 1.3851 2023/02/17 14:39:24 - mmengine - INFO - Epoch(train) [35][ 400/1345] lr: 1.0000e-02 eta: 8:19:09 time: 0.1887 data_time: 0.0057 memory: 8327 grad_norm: 7.6191 loss: 3.6902 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2596 loss_aux: 1.4306 2023/02/17 14:39:28 - mmengine - INFO - Epoch(train) [35][ 420/1345] lr: 1.0000e-02 eta: 8:19:05 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.7135 loss: 3.4946 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0847 loss_aux: 1.4099 2023/02/17 14:39:32 - mmengine - INFO - Epoch(train) [35][ 440/1345] lr: 1.0000e-02 eta: 8:19:01 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.2064 loss: 3.4801 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0989 loss_aux: 1.3812 2023/02/17 14:39:36 - mmengine - INFO - Epoch(train) [35][ 460/1345] lr: 1.0000e-02 eta: 8:18:57 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.3976 loss: 3.6651 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2448 loss_aux: 1.4202 2023/02/17 14:39:39 - mmengine - INFO - Epoch(train) [35][ 480/1345] lr: 1.0000e-02 eta: 8:18:53 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.2708 loss: 3.0840 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8344 loss_aux: 1.2496 2023/02/17 14:39:43 - mmengine - INFO - Epoch(train) [35][ 500/1345] lr: 1.0000e-02 eta: 8:18:48 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.4827 loss: 3.5075 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0979 loss_aux: 1.4097 2023/02/17 14:39:47 - mmengine - INFO - Epoch(train) [35][ 520/1345] lr: 1.0000e-02 eta: 8:18:44 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.4369 loss: 3.5298 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1543 loss_aux: 1.3756 2023/02/17 14:39:51 - mmengine - INFO - Epoch(train) [35][ 540/1345] lr: 1.0000e-02 eta: 8:18:40 time: 0.1893 data_time: 0.0062 memory: 8327 grad_norm: 7.4840 loss: 3.8752 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4145 loss_aux: 1.4606 2023/02/17 14:39:55 - mmengine - INFO - Epoch(train) [35][ 560/1345] lr: 1.0000e-02 eta: 8:18:36 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.5377 loss: 3.7305 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2807 loss_aux: 1.4497 2023/02/17 14:39:58 - mmengine - INFO - Epoch(train) [35][ 580/1345] lr: 1.0000e-02 eta: 8:18:32 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.5952 loss: 3.7319 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2730 loss_aux: 1.4589 2023/02/17 14:40:02 - mmengine - INFO - Epoch(train) [35][ 600/1345] lr: 1.0000e-02 eta: 8:18:28 time: 0.1891 data_time: 0.0060 memory: 8327 grad_norm: 8.0098 loss: 3.8598 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3433 loss_aux: 1.5165 2023/02/17 14:40:06 - mmengine - INFO - Epoch(train) [35][ 620/1345] lr: 1.0000e-02 eta: 8:18:24 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.4039 loss: 3.5420 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1897 loss_aux: 1.3523 2023/02/17 14:40:10 - mmengine - INFO - Epoch(train) [35][ 640/1345] lr: 1.0000e-02 eta: 8:18:20 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.4084 loss: 3.3737 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0420 loss_aux: 1.3316 2023/02/17 14:40:14 - mmengine - INFO - Epoch(train) [35][ 660/1345] lr: 1.0000e-02 eta: 8:18:16 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.6246 loss: 3.3523 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9917 loss_aux: 1.3607 2023/02/17 14:40:17 - mmengine - INFO - Epoch(train) [35][ 680/1345] lr: 1.0000e-02 eta: 8:18:12 time: 0.1891 data_time: 0.0060 memory: 8327 grad_norm: 7.4673 loss: 3.7289 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2689 loss_aux: 1.4600 2023/02/17 14:40:21 - mmengine - INFO - Epoch(train) [35][ 700/1345] lr: 1.0000e-02 eta: 8:18:08 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.3835 loss: 3.8436 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3645 loss_aux: 1.4791 2023/02/17 14:40:25 - mmengine - INFO - Epoch(train) [35][ 720/1345] lr: 1.0000e-02 eta: 8:18:04 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.4653 loss: 3.8880 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4389 loss_aux: 1.4491 2023/02/17 14:40:29 - mmengine - INFO - Epoch(train) [35][ 740/1345] lr: 1.0000e-02 eta: 8:18:00 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.5011 loss: 3.5719 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1966 loss_aux: 1.3753 2023/02/17 14:40:32 - mmengine - INFO - Epoch(train) [35][ 760/1345] lr: 1.0000e-02 eta: 8:17:56 time: 0.1888 data_time: 0.0057 memory: 8327 grad_norm: 7.4681 loss: 3.9169 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3969 loss_aux: 1.5200 2023/02/17 14:40:36 - mmengine - INFO - Epoch(train) [35][ 780/1345] lr: 1.0000e-02 eta: 8:17:51 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.2336 loss: 3.7306 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3169 loss_aux: 1.4137 2023/02/17 14:40:40 - mmengine - INFO - Epoch(train) [35][ 800/1345] lr: 1.0000e-02 eta: 8:17:47 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.4380 loss: 3.6986 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2869 loss_aux: 1.4118 2023/02/17 14:40:44 - mmengine - INFO - Epoch(train) [35][ 820/1345] lr: 1.0000e-02 eta: 8:17:43 time: 0.1896 data_time: 0.0064 memory: 8327 grad_norm: 7.4119 loss: 3.4583 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1038 loss_aux: 1.3545 2023/02/17 14:40:48 - mmengine - INFO - Epoch(train) [35][ 840/1345] lr: 1.0000e-02 eta: 8:17:39 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.4972 loss: 3.4288 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0744 loss_aux: 1.3544 2023/02/17 14:40:51 - mmengine - INFO - Epoch(train) [35][ 860/1345] lr: 1.0000e-02 eta: 8:17:35 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.6604 loss: 3.9328 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3940 loss_aux: 1.5388 2023/02/17 14:40:55 - mmengine - INFO - Epoch(train) [35][ 880/1345] lr: 1.0000e-02 eta: 8:17:31 time: 0.1902 data_time: 0.0065 memory: 8327 grad_norm: 7.5076 loss: 3.5893 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2030 loss_aux: 1.3863 2023/02/17 14:40:59 - mmengine - INFO - Epoch(train) [35][ 900/1345] lr: 1.0000e-02 eta: 8:17:27 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.4331 loss: 3.3867 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.0653 loss_aux: 1.3214 2023/02/17 14:41:03 - mmengine - INFO - Epoch(train) [35][ 920/1345] lr: 1.0000e-02 eta: 8:17:23 time: 0.1890 data_time: 0.0060 memory: 8327 grad_norm: 7.4466 loss: 3.5949 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2714 loss_aux: 1.3236 2023/02/17 14:41:07 - mmengine - INFO - Epoch(train) [35][ 940/1345] lr: 1.0000e-02 eta: 8:17:19 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.4630 loss: 3.4706 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1138 loss_aux: 1.3568 2023/02/17 14:41:10 - mmengine - INFO - Epoch(train) [35][ 960/1345] lr: 1.0000e-02 eta: 8:17:15 time: 0.1899 data_time: 0.0060 memory: 8327 grad_norm: 7.3436 loss: 3.5343 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1504 loss_aux: 1.3839 2023/02/17 14:41:15 - mmengine - INFO - Epoch(train) [35][ 980/1345] lr: 1.0000e-02 eta: 8:17:12 time: 0.2096 data_time: 0.0268 memory: 8327 grad_norm: 7.4746 loss: 3.7053 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2950 loss_aux: 1.4103 2023/02/17 14:41:18 - mmengine - INFO - Epoch(train) [35][1000/1345] lr: 1.0000e-02 eta: 8:17:08 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.1662 loss: 3.2598 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9149 loss_aux: 1.3450 2023/02/17 14:41:22 - mmengine - INFO - Epoch(train) [35][1020/1345] lr: 1.0000e-02 eta: 8:17:04 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.5914 loss: 3.4765 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1193 loss_aux: 1.3571 2023/02/17 14:41:26 - mmengine - INFO - Epoch(train) [35][1040/1345] lr: 1.0000e-02 eta: 8:17:00 time: 0.1895 data_time: 0.0056 memory: 8327 grad_norm: 7.4791 loss: 3.3855 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0222 loss_aux: 1.3633 2023/02/17 14:41:30 - mmengine - INFO - Epoch(train) [35][1060/1345] lr: 1.0000e-02 eta: 8:16:56 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 7.3346 loss: 3.3145 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0323 loss_aux: 1.2822 2023/02/17 14:41:34 - mmengine - INFO - Epoch(train) [35][1080/1345] lr: 1.0000e-02 eta: 8:16:52 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.5139 loss: 4.0569 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5327 loss_aux: 1.5242 2023/02/17 14:41:37 - mmengine - INFO - Epoch(train) [35][1100/1345] lr: 1.0000e-02 eta: 8:16:48 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.3736 loss: 3.3095 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9936 loss_aux: 1.3159 2023/02/17 14:41:41 - mmengine - INFO - Epoch(train) [35][1120/1345] lr: 1.0000e-02 eta: 8:16:44 time: 0.1902 data_time: 0.0058 memory: 8327 grad_norm: 7.4297 loss: 3.7542 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2640 loss_aux: 1.4901 2023/02/17 14:41:45 - mmengine - INFO - Epoch(train) [35][1140/1345] lr: 1.0000e-02 eta: 8:16:40 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.7502 loss: 3.4410 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1039 loss_aux: 1.3370 2023/02/17 14:41:49 - mmengine - INFO - Epoch(train) [35][1160/1345] lr: 1.0000e-02 eta: 8:16:36 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.8244 loss: 3.6830 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2419 loss_aux: 1.4412 2023/02/17 14:41:52 - mmengine - INFO - Epoch(train) [35][1180/1345] lr: 1.0000e-02 eta: 8:16:32 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.5671 loss: 2.9240 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7454 loss_aux: 1.1786 2023/02/17 14:41:56 - mmengine - INFO - Epoch(train) [35][1200/1345] lr: 1.0000e-02 eta: 8:16:28 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.4801 loss: 3.5725 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1862 loss_aux: 1.3862 2023/02/17 14:42:00 - mmengine - INFO - Epoch(train) [35][1220/1345] lr: 1.0000e-02 eta: 8:16:24 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.5584 loss: 3.7889 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3060 loss_aux: 1.4830 2023/02/17 14:42:04 - mmengine - INFO - Epoch(train) [35][1240/1345] lr: 1.0000e-02 eta: 8:16:20 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.6624 loss: 3.6613 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2289 loss_aux: 1.4324 2023/02/17 14:42:08 - mmengine - INFO - Epoch(train) [35][1260/1345] lr: 1.0000e-02 eta: 8:16:16 time: 0.1898 data_time: 0.0060 memory: 8327 grad_norm: 7.6837 loss: 3.9315 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4444 loss_aux: 1.4872 2023/02/17 14:42:10 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:42:11 - mmengine - INFO - Epoch(train) [35][1280/1345] lr: 1.0000e-02 eta: 8:16:12 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.6075 loss: 3.7485 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3096 loss_aux: 1.4389 2023/02/17 14:42:15 - mmengine - INFO - Epoch(train) [35][1300/1345] lr: 1.0000e-02 eta: 8:16:08 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.3714 loss: 3.7117 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2706 loss_aux: 1.4411 2023/02/17 14:42:19 - mmengine - INFO - Epoch(train) [35][1320/1345] lr: 1.0000e-02 eta: 8:16:04 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.4702 loss: 3.6737 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2547 loss_aux: 1.4190 2023/02/17 14:42:23 - mmengine - INFO - Epoch(train) [35][1340/1345] lr: 1.0000e-02 eta: 8:16:00 time: 0.1901 data_time: 0.0066 memory: 8327 grad_norm: 7.4296 loss: 3.3766 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0363 loss_aux: 1.3403 2023/02/17 14:42:24 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:42:24 - mmengine - INFO - Epoch(train) [35][1345/1345] lr: 1.0000e-02 eta: 8:15:58 time: 0.1836 data_time: 0.0066 memory: 8327 grad_norm: 7.4507 loss: 3.6271 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 2.2482 loss_aux: 1.3789 2023/02/17 14:42:24 - mmengine - INFO - Saving checkpoint at 35 epochs 2023/02/17 14:42:27 - mmengine - INFO - Epoch(val) [35][ 20/181] eta: 0:00:09 time: 0.0562 data_time: 0.0076 memory: 1994 2023/02/17 14:42:28 - mmengine - INFO - Epoch(val) [35][ 40/181] eta: 0:00:07 time: 0.0523 data_time: 0.0045 memory: 1994 2023/02/17 14:42:29 - mmengine - INFO - Epoch(val) [35][ 60/181] eta: 0:00:06 time: 0.0526 data_time: 0.0047 memory: 1994 2023/02/17 14:42:30 - mmengine - INFO - Epoch(val) [35][ 80/181] eta: 0:00:05 time: 0.0524 data_time: 0.0047 memory: 1994 2023/02/17 14:42:31 - mmengine - INFO - Epoch(val) [35][100/181] eta: 0:00:04 time: 0.0524 data_time: 0.0046 memory: 1994 2023/02/17 14:42:32 - mmengine - INFO - Epoch(val) [35][120/181] eta: 0:00:03 time: 0.0526 data_time: 0.0047 memory: 1994 2023/02/17 14:42:33 - mmengine - INFO - Epoch(val) [35][140/181] eta: 0:00:02 time: 0.0519 data_time: 0.0044 memory: 1994 2023/02/17 14:42:34 - mmengine - INFO - Epoch(val) [35][160/181] eta: 0:00:01 time: 0.0517 data_time: 0.0042 memory: 1994 2023/02/17 14:42:36 - mmengine - INFO - Epoch(val) [35][180/181] eta: 0:00:00 time: 0.0515 data_time: 0.0042 memory: 1994 2023/02/17 14:42:36 - mmengine - INFO - Epoch(val) [35][181/181] acc/top1: 0.3680 acc/top5: 0.6598 acc/mean1: 0.3256 2023/02/17 14:42:41 - mmengine - INFO - Epoch(train) [36][ 20/1345] lr: 1.0000e-02 eta: 8:15:57 time: 0.2388 data_time: 0.0350 memory: 8327 grad_norm: 7.4105 loss: 3.6437 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2169 loss_aux: 1.4267 2023/02/17 14:42:44 - mmengine - INFO - Epoch(train) [36][ 40/1345] lr: 1.0000e-02 eta: 8:15:53 time: 0.1910 data_time: 0.0039 memory: 8327 grad_norm: 7.1258 loss: 3.7643 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2958 loss_aux: 1.4685 2023/02/17 14:42:48 - mmengine - INFO - Epoch(train) [36][ 60/1345] lr: 1.0000e-02 eta: 8:15:49 time: 0.1900 data_time: 0.0059 memory: 8327 grad_norm: 7.1049 loss: 3.7153 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2311 loss_aux: 1.4841 2023/02/17 14:42:52 - mmengine - INFO - Epoch(train) [36][ 80/1345] lr: 1.0000e-02 eta: 8:15:45 time: 0.1898 data_time: 0.0064 memory: 8327 grad_norm: 7.4877 loss: 3.5419 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1849 loss_aux: 1.3570 2023/02/17 14:42:56 - mmengine - INFO - Epoch(train) [36][ 100/1345] lr: 1.0000e-02 eta: 8:15:41 time: 0.1897 data_time: 0.0057 memory: 8327 grad_norm: 7.4894 loss: 3.4477 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0823 loss_aux: 1.3654 2023/02/17 14:43:00 - mmengine - INFO - Epoch(train) [36][ 120/1345] lr: 1.0000e-02 eta: 8:15:37 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.3457 loss: 3.6278 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2373 loss_aux: 1.3905 2023/02/17 14:43:03 - mmengine - INFO - Epoch(train) [36][ 140/1345] lr: 1.0000e-02 eta: 8:15:33 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.3627 loss: 3.6704 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2748 loss_aux: 1.3956 2023/02/17 14:43:07 - mmengine - INFO - Epoch(train) [36][ 160/1345] lr: 1.0000e-02 eta: 8:15:29 time: 0.1898 data_time: 0.0060 memory: 8327 grad_norm: 7.2268 loss: 3.9771 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4660 loss_aux: 1.5111 2023/02/17 14:43:11 - mmengine - INFO - Epoch(train) [36][ 180/1345] lr: 1.0000e-02 eta: 8:15:25 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.3842 loss: 3.3415 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0135 loss_aux: 1.3280 2023/02/17 14:43:15 - mmengine - INFO - Epoch(train) [36][ 200/1345] lr: 1.0000e-02 eta: 8:15:21 time: 0.1892 data_time: 0.0061 memory: 8327 grad_norm: 7.5132 loss: 3.4093 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0347 loss_aux: 1.3747 2023/02/17 14:43:19 - mmengine - INFO - Epoch(train) [36][ 220/1345] lr: 1.0000e-02 eta: 8:15:17 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.2314 loss: 3.5838 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2276 loss_aux: 1.3562 2023/02/17 14:43:22 - mmengine - INFO - Epoch(train) [36][ 240/1345] lr: 1.0000e-02 eta: 8:15:13 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5340 loss: 3.9354 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3923 loss_aux: 1.5431 2023/02/17 14:43:26 - mmengine - INFO - Epoch(train) [36][ 260/1345] lr: 1.0000e-02 eta: 8:15:09 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.3001 loss: 3.2188 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8907 loss_aux: 1.3281 2023/02/17 14:43:30 - mmengine - INFO - Epoch(train) [36][ 280/1345] lr: 1.0000e-02 eta: 8:15:05 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.2723 loss: 3.1955 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8795 loss_aux: 1.3160 2023/02/17 14:43:34 - mmengine - INFO - Epoch(train) [36][ 300/1345] lr: 1.0000e-02 eta: 8:15:01 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.3689 loss: 3.5368 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1487 loss_aux: 1.3881 2023/02/17 14:43:38 - mmengine - INFO - Epoch(train) [36][ 320/1345] lr: 1.0000e-02 eta: 8:14:57 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.2852 loss: 3.6707 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2316 loss_aux: 1.4392 2023/02/17 14:43:41 - mmengine - INFO - Epoch(train) [36][ 340/1345] lr: 1.0000e-02 eta: 8:14:53 time: 0.1892 data_time: 0.0062 memory: 8327 grad_norm: 7.5099 loss: 3.3707 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0264 loss_aux: 1.3443 2023/02/17 14:43:45 - mmengine - INFO - Epoch(train) [36][ 360/1345] lr: 1.0000e-02 eta: 8:14:49 time: 0.1897 data_time: 0.0064 memory: 8327 grad_norm: 7.6753 loss: 3.7443 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2570 loss_aux: 1.4873 2023/02/17 14:43:49 - mmengine - INFO - Epoch(train) [36][ 380/1345] lr: 1.0000e-02 eta: 8:14:45 time: 0.1906 data_time: 0.0069 memory: 8327 grad_norm: 7.3174 loss: 3.3659 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0845 loss_aux: 1.2815 2023/02/17 14:43:53 - mmengine - INFO - Epoch(train) [36][ 400/1345] lr: 1.0000e-02 eta: 8:14:41 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.3695 loss: 3.6204 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1772 loss_aux: 1.4433 2023/02/17 14:43:57 - mmengine - INFO - Epoch(train) [36][ 420/1345] lr: 1.0000e-02 eta: 8:14:37 time: 0.1891 data_time: 0.0060 memory: 8327 grad_norm: 7.6675 loss: 3.5813 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1781 loss_aux: 1.4032 2023/02/17 14:44:00 - mmengine - INFO - Epoch(train) [36][ 440/1345] lr: 1.0000e-02 eta: 8:14:33 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.4396 loss: 3.4545 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.1060 loss_aux: 1.3485 2023/02/17 14:44:04 - mmengine - INFO - Epoch(train) [36][ 460/1345] lr: 1.0000e-02 eta: 8:14:28 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.4759 loss: 3.6072 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2306 loss_aux: 1.3767 2023/02/17 14:44:08 - mmengine - INFO - Epoch(train) [36][ 480/1345] lr: 1.0000e-02 eta: 8:14:24 time: 0.1899 data_time: 0.0060 memory: 8327 grad_norm: 7.6823 loss: 3.5263 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1936 loss_aux: 1.3327 2023/02/17 14:44:12 - mmengine - INFO - Epoch(train) [36][ 500/1345] lr: 1.0000e-02 eta: 8:14:22 time: 0.2111 data_time: 0.0270 memory: 8327 grad_norm: 7.3470 loss: 3.5144 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1056 loss_aux: 1.4089 2023/02/17 14:44:16 - mmengine - INFO - Epoch(train) [36][ 520/1345] lr: 1.0000e-02 eta: 8:14:18 time: 0.1899 data_time: 0.0063 memory: 8327 grad_norm: 7.2302 loss: 3.7533 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2966 loss_aux: 1.4567 2023/02/17 14:44:20 - mmengine - INFO - Epoch(train) [36][ 540/1345] lr: 1.0000e-02 eta: 8:14:14 time: 0.1912 data_time: 0.0070 memory: 8327 grad_norm: 7.4972 loss: 3.9709 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4027 loss_aux: 1.5682 2023/02/17 14:44:24 - mmengine - INFO - Epoch(train) [36][ 560/1345] lr: 1.0000e-02 eta: 8:14:10 time: 0.1896 data_time: 0.0061 memory: 8327 grad_norm: 7.4363 loss: 3.8474 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3827 loss_aux: 1.4647 2023/02/17 14:44:27 - mmengine - INFO - Epoch(train) [36][ 580/1345] lr: 1.0000e-02 eta: 8:14:06 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.6601 loss: 3.6633 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2340 loss_aux: 1.4293 2023/02/17 14:44:31 - mmengine - INFO - Epoch(train) [36][ 600/1345] lr: 1.0000e-02 eta: 8:14:02 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.4676 loss: 3.7233 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2506 loss_aux: 1.4727 2023/02/17 14:44:35 - mmengine - INFO - Epoch(train) [36][ 620/1345] lr: 1.0000e-02 eta: 8:13:58 time: 0.1890 data_time: 0.0060 memory: 8327 grad_norm: 7.5830 loss: 3.5297 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1458 loss_aux: 1.3839 2023/02/17 14:44:39 - mmengine - INFO - Epoch(train) [36][ 640/1345] lr: 1.0000e-02 eta: 8:13:54 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.4960 loss: 3.5177 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1361 loss_aux: 1.3817 2023/02/17 14:44:42 - mmengine - INFO - Epoch(train) [36][ 660/1345] lr: 1.0000e-02 eta: 8:13:50 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.6440 loss: 3.8967 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4236 loss_aux: 1.4730 2023/02/17 14:44:46 - mmengine - INFO - Epoch(train) [36][ 680/1345] lr: 1.0000e-02 eta: 8:13:46 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.4696 loss: 3.9210 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3970 loss_aux: 1.5241 2023/02/17 14:44:50 - mmengine - INFO - Epoch(train) [36][ 700/1345] lr: 1.0000e-02 eta: 8:13:41 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.4466 loss: 3.4959 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0671 loss_aux: 1.4289 2023/02/17 14:44:54 - mmengine - INFO - Epoch(train) [36][ 720/1345] lr: 1.0000e-02 eta: 8:13:37 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.6133 loss: 3.5143 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1358 loss_aux: 1.3785 2023/02/17 14:44:58 - mmengine - INFO - Epoch(train) [36][ 740/1345] lr: 1.0000e-02 eta: 8:13:33 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.3914 loss: 3.8016 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3796 loss_aux: 1.4220 2023/02/17 14:45:01 - mmengine - INFO - Epoch(train) [36][ 760/1345] lr: 1.0000e-02 eta: 8:13:29 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.5958 loss: 3.7983 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3142 loss_aux: 1.4841 2023/02/17 14:45:05 - mmengine - INFO - Epoch(train) [36][ 780/1345] lr: 1.0000e-02 eta: 8:13:25 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.4556 loss: 3.2192 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.9658 loss_aux: 1.2534 2023/02/17 14:45:09 - mmengine - INFO - Epoch(train) [36][ 800/1345] lr: 1.0000e-02 eta: 8:13:21 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.4496 loss: 3.6652 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2455 loss_aux: 1.4197 2023/02/17 14:45:13 - mmengine - INFO - Epoch(train) [36][ 820/1345] lr: 1.0000e-02 eta: 8:13:17 time: 0.1900 data_time: 0.0065 memory: 8327 grad_norm: 7.4354 loss: 3.6264 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2610 loss_aux: 1.3655 2023/02/17 14:45:17 - mmengine - INFO - Epoch(train) [36][ 840/1345] lr: 1.0000e-02 eta: 8:13:14 time: 0.1991 data_time: 0.0157 memory: 8327 grad_norm: 7.3270 loss: 3.5564 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1934 loss_aux: 1.3630 2023/02/17 14:45:21 - mmengine - INFO - Epoch(train) [36][ 860/1345] lr: 1.0000e-02 eta: 8:13:10 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.4085 loss: 3.6375 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2091 loss_aux: 1.4284 2023/02/17 14:45:24 - mmengine - INFO - Epoch(train) [36][ 880/1345] lr: 1.0000e-02 eta: 8:13:06 time: 0.1900 data_time: 0.0057 memory: 8327 grad_norm: 7.4143 loss: 3.1411 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8485 loss_aux: 1.2926 2023/02/17 14:45:28 - mmengine - INFO - Epoch(train) [36][ 900/1345] lr: 1.0000e-02 eta: 8:13:02 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.5585 loss: 3.7660 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2722 loss_aux: 1.4937 2023/02/17 14:45:32 - mmengine - INFO - Epoch(train) [36][ 920/1345] lr: 1.0000e-02 eta: 8:12:58 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.6497 loss: 3.6316 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2343 loss_aux: 1.3973 2023/02/17 14:45:33 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:45:36 - mmengine - INFO - Epoch(train) [36][ 940/1345] lr: 1.0000e-02 eta: 8:12:54 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.4712 loss: 3.6919 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2426 loss_aux: 1.4493 2023/02/17 14:45:40 - mmengine - INFO - Epoch(train) [36][ 960/1345] lr: 1.0000e-02 eta: 8:12:50 time: 0.1908 data_time: 0.0073 memory: 8327 grad_norm: 7.4214 loss: 3.6319 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2049 loss_aux: 1.4271 2023/02/17 14:45:43 - mmengine - INFO - Epoch(train) [36][ 980/1345] lr: 1.0000e-02 eta: 8:12:46 time: 0.1900 data_time: 0.0057 memory: 8327 grad_norm: 7.4245 loss: 3.8006 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3404 loss_aux: 1.4602 2023/02/17 14:45:47 - mmengine - INFO - Epoch(train) [36][1000/1345] lr: 1.0000e-02 eta: 8:12:42 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.4846 loss: 3.6788 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2806 loss_aux: 1.3982 2023/02/17 14:45:51 - mmengine - INFO - Epoch(train) [36][1020/1345] lr: 1.0000e-02 eta: 8:12:38 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.5026 loss: 3.6037 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2057 loss_aux: 1.3980 2023/02/17 14:45:55 - mmengine - INFO - Epoch(train) [36][1040/1345] lr: 1.0000e-02 eta: 8:12:33 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.3493 loss: 3.5761 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1755 loss_aux: 1.4007 2023/02/17 14:45:59 - mmengine - INFO - Epoch(train) [36][1060/1345] lr: 1.0000e-02 eta: 8:12:29 time: 0.1893 data_time: 0.0056 memory: 8327 grad_norm: 7.6106 loss: 3.7736 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2818 loss_aux: 1.4918 2023/02/17 14:46:02 - mmengine - INFO - Epoch(train) [36][1080/1345] lr: 1.0000e-02 eta: 8:12:25 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 7.3062 loss: 3.8907 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4430 loss_aux: 1.4477 2023/02/17 14:46:06 - mmengine - INFO - Epoch(train) [36][1100/1345] lr: 1.0000e-02 eta: 8:12:21 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.8869 loss: 3.8248 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3924 loss_aux: 1.4324 2023/02/17 14:46:10 - mmengine - INFO - Epoch(train) [36][1120/1345] lr: 1.0000e-02 eta: 8:12:17 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.5235 loss: 3.7106 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2935 loss_aux: 1.4170 2023/02/17 14:46:14 - mmengine - INFO - Epoch(train) [36][1140/1345] lr: 1.0000e-02 eta: 8:12:13 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.5217 loss: 3.4887 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1243 loss_aux: 1.3644 2023/02/17 14:46:17 - mmengine - INFO - Epoch(train) [36][1160/1345] lr: 1.0000e-02 eta: 8:12:09 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.6163 loss: 3.2484 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9172 loss_aux: 1.3313 2023/02/17 14:46:21 - mmengine - INFO - Epoch(train) [36][1180/1345] lr: 1.0000e-02 eta: 8:12:05 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.4557 loss: 3.2898 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9483 loss_aux: 1.3415 2023/02/17 14:46:25 - mmengine - INFO - Epoch(train) [36][1200/1345] lr: 1.0000e-02 eta: 8:12:01 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.3895 loss: 3.8707 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4107 loss_aux: 1.4600 2023/02/17 14:46:29 - mmengine - INFO - Epoch(train) [36][1220/1345] lr: 1.0000e-02 eta: 8:11:57 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.4613 loss: 3.9444 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4443 loss_aux: 1.5001 2023/02/17 14:46:33 - mmengine - INFO - Epoch(train) [36][1240/1345] lr: 1.0000e-02 eta: 8:11:53 time: 0.1889 data_time: 0.0057 memory: 8327 grad_norm: 7.6476 loss: 3.5954 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2159 loss_aux: 1.3794 2023/02/17 14:46:36 - mmengine - INFO - Epoch(train) [36][1260/1345] lr: 1.0000e-02 eta: 8:11:49 time: 0.1898 data_time: 0.0065 memory: 8327 grad_norm: 7.7056 loss: 3.7145 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2681 loss_aux: 1.4464 2023/02/17 14:46:40 - mmengine - INFO - Epoch(train) [36][1280/1345] lr: 1.0000e-02 eta: 8:11:45 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.4133 loss: 3.4999 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1142 loss_aux: 1.3856 2023/02/17 14:46:44 - mmengine - INFO - Epoch(train) [36][1300/1345] lr: 1.0000e-02 eta: 8:11:41 time: 0.1909 data_time: 0.0059 memory: 8327 grad_norm: 7.3621 loss: 3.3878 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0389 loss_aux: 1.3489 2023/02/17 14:46:48 - mmengine - INFO - Epoch(train) [36][1320/1345] lr: 1.0000e-02 eta: 8:11:37 time: 0.1915 data_time: 0.0063 memory: 8327 grad_norm: 7.4969 loss: 3.8209 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3807 loss_aux: 1.4401 2023/02/17 14:46:52 - mmengine - INFO - Epoch(train) [36][1340/1345] lr: 1.0000e-02 eta: 8:11:33 time: 0.1890 data_time: 0.0059 memory: 8327 grad_norm: 7.5952 loss: 3.4972 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1468 loss_aux: 1.3503 2023/02/17 14:46:52 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:46:52 - mmengine - INFO - Epoch(train) [36][1345/1345] lr: 1.0000e-02 eta: 8:11:32 time: 0.1831 data_time: 0.0060 memory: 8327 grad_norm: 7.5928 loss: 3.6561 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.2236 loss_aux: 1.4324 2023/02/17 14:46:52 - mmengine - INFO - Saving checkpoint at 36 epochs 2023/02/17 14:46:59 - mmengine - INFO - Epoch(train) [37][ 20/1345] lr: 1.0000e-02 eta: 8:11:29 time: 0.2058 data_time: 0.0158 memory: 8327 grad_norm: 7.6864 loss: 3.7784 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3350 loss_aux: 1.4434 2023/02/17 14:47:03 - mmengine - INFO - Epoch(train) [37][ 40/1345] lr: 1.0000e-02 eta: 8:11:25 time: 0.1905 data_time: 0.0040 memory: 8327 grad_norm: 7.3469 loss: 3.4643 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1081 loss_aux: 1.3563 2023/02/17 14:47:07 - mmengine - INFO - Epoch(train) [37][ 60/1345] lr: 1.0000e-02 eta: 8:11:21 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.2590 loss: 3.4862 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0853 loss_aux: 1.4009 2023/02/17 14:47:11 - mmengine - INFO - Epoch(train) [37][ 80/1345] lr: 1.0000e-02 eta: 8:11:17 time: 0.1904 data_time: 0.0071 memory: 8327 grad_norm: 7.5659 loss: 3.4376 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0897 loss_aux: 1.3479 2023/02/17 14:47:14 - mmengine - INFO - Epoch(train) [37][ 100/1345] lr: 1.0000e-02 eta: 8:11:13 time: 0.1889 data_time: 0.0059 memory: 8327 grad_norm: 7.5027 loss: 3.5225 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2072 loss_aux: 1.3154 2023/02/17 14:47:18 - mmengine - INFO - Epoch(train) [37][ 120/1345] lr: 1.0000e-02 eta: 8:11:09 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.5095 loss: 3.4464 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0965 loss_aux: 1.3499 2023/02/17 14:47:22 - mmengine - INFO - Epoch(train) [37][ 140/1345] lr: 1.0000e-02 eta: 8:11:05 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.2295 loss: 3.4178 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0450 loss_aux: 1.3729 2023/02/17 14:47:26 - mmengine - INFO - Epoch(train) [37][ 160/1345] lr: 1.0000e-02 eta: 8:11:01 time: 0.1900 data_time: 0.0057 memory: 8327 grad_norm: 7.4606 loss: 3.5268 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1193 loss_aux: 1.4075 2023/02/17 14:47:30 - mmengine - INFO - Epoch(train) [37][ 180/1345] lr: 1.0000e-02 eta: 8:10:57 time: 0.1905 data_time: 0.0070 memory: 8327 grad_norm: 7.3480 loss: 2.8755 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6993 loss_aux: 1.1762 2023/02/17 14:47:33 - mmengine - INFO - Epoch(train) [37][ 200/1345] lr: 1.0000e-02 eta: 8:10:53 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.4475 loss: 3.4369 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1083 loss_aux: 1.3286 2023/02/17 14:47:38 - mmengine - INFO - Epoch(train) [37][ 220/1345] lr: 1.0000e-02 eta: 8:10:50 time: 0.2094 data_time: 0.0261 memory: 8327 grad_norm: 7.5737 loss: 3.4118 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0858 loss_aux: 1.3259 2023/02/17 14:47:41 - mmengine - INFO - Epoch(train) [37][ 240/1345] lr: 1.0000e-02 eta: 8:10:46 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.3908 loss: 3.7778 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3470 loss_aux: 1.4308 2023/02/17 14:47:45 - mmengine - INFO - Epoch(train) [37][ 260/1345] lr: 1.0000e-02 eta: 8:10:42 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.4313 loss: 3.4350 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0955 loss_aux: 1.3395 2023/02/17 14:47:49 - mmengine - INFO - Epoch(train) [37][ 280/1345] lr: 1.0000e-02 eta: 8:10:38 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.5518 loss: 3.3633 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9949 loss_aux: 1.3683 2023/02/17 14:47:53 - mmengine - INFO - Epoch(train) [37][ 300/1345] lr: 1.0000e-02 eta: 8:10:34 time: 0.1890 data_time: 0.0060 memory: 8327 grad_norm: 7.4623 loss: 3.4896 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1425 loss_aux: 1.3470 2023/02/17 14:47:56 - mmengine - INFO - Epoch(train) [37][ 320/1345] lr: 1.0000e-02 eta: 8:10:30 time: 0.1890 data_time: 0.0059 memory: 8327 grad_norm: 7.4928 loss: 3.2896 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0065 loss_aux: 1.2831 2023/02/17 14:48:00 - mmengine - INFO - Epoch(train) [37][ 340/1345] lr: 1.0000e-02 eta: 8:10:26 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.7264 loss: 3.3600 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0100 loss_aux: 1.3499 2023/02/17 14:48:04 - mmengine - INFO - Epoch(train) [37][ 360/1345] lr: 1.0000e-02 eta: 8:10:21 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.3771 loss: 3.8098 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3733 loss_aux: 1.4365 2023/02/17 14:48:08 - mmengine - INFO - Epoch(train) [37][ 380/1345] lr: 1.0000e-02 eta: 8:10:17 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.4659 loss: 3.5052 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1204 loss_aux: 1.3848 2023/02/17 14:48:12 - mmengine - INFO - Epoch(train) [37][ 400/1345] lr: 1.0000e-02 eta: 8:10:13 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.6216 loss: 3.8292 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3535 loss_aux: 1.4757 2023/02/17 14:48:15 - mmengine - INFO - Epoch(train) [37][ 420/1345] lr: 1.0000e-02 eta: 8:10:09 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.7594 loss: 3.9270 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4328 loss_aux: 1.4942 2023/02/17 14:48:19 - mmengine - INFO - Epoch(train) [37][ 440/1345] lr: 1.0000e-02 eta: 8:10:05 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.3411 loss: 3.4764 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1058 loss_aux: 1.3705 2023/02/17 14:48:23 - mmengine - INFO - Epoch(train) [37][ 460/1345] lr: 1.0000e-02 eta: 8:10:01 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.3669 loss: 3.2701 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9592 loss_aux: 1.3109 2023/02/17 14:48:27 - mmengine - INFO - Epoch(train) [37][ 480/1345] lr: 1.0000e-02 eta: 8:09:57 time: 0.1892 data_time: 0.0063 memory: 8327 grad_norm: 7.4767 loss: 4.0258 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5208 loss_aux: 1.5051 2023/02/17 14:48:31 - mmengine - INFO - Epoch(train) [37][ 500/1345] lr: 1.0000e-02 eta: 8:09:53 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.5281 loss: 3.4658 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1485 loss_aux: 1.3173 2023/02/17 14:48:34 - mmengine - INFO - Epoch(train) [37][ 520/1345] lr: 1.0000e-02 eta: 8:09:49 time: 0.1892 data_time: 0.0060 memory: 8327 grad_norm: 7.6006 loss: 3.7659 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3083 loss_aux: 1.4576 2023/02/17 14:48:38 - mmengine - INFO - Epoch(train) [37][ 540/1345] lr: 1.0000e-02 eta: 8:09:45 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.4679 loss: 3.8720 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3647 loss_aux: 1.5073 2023/02/17 14:48:42 - mmengine - INFO - Epoch(train) [37][ 560/1345] lr: 1.0000e-02 eta: 8:09:41 time: 0.1898 data_time: 0.0060 memory: 8327 grad_norm: 7.4468 loss: 3.4771 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1053 loss_aux: 1.3718 2023/02/17 14:48:46 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:48:46 - mmengine - INFO - Epoch(train) [37][ 580/1345] lr: 1.0000e-02 eta: 8:09:37 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.6735 loss: 3.7839 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3382 loss_aux: 1.4457 2023/02/17 14:48:50 - mmengine - INFO - Epoch(train) [37][ 600/1345] lr: 1.0000e-02 eta: 8:09:33 time: 0.1899 data_time: 0.0068 memory: 8327 grad_norm: 7.2467 loss: 3.6268 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1747 loss_aux: 1.4521 2023/02/17 14:48:53 - mmengine - INFO - Epoch(train) [37][ 620/1345] lr: 1.0000e-02 eta: 8:09:29 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.2986 loss: 3.7215 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2795 loss_aux: 1.4420 2023/02/17 14:48:57 - mmengine - INFO - Epoch(train) [37][ 640/1345] lr: 1.0000e-02 eta: 8:09:25 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.5432 loss: 4.0455 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4860 loss_aux: 1.5595 2023/02/17 14:49:01 - mmengine - INFO - Epoch(train) [37][ 660/1345] lr: 1.0000e-02 eta: 8:09:21 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.5404 loss: 3.2950 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9775 loss_aux: 1.3175 2023/02/17 14:49:05 - mmengine - INFO - Epoch(train) [37][ 680/1345] lr: 1.0000e-02 eta: 8:09:17 time: 0.1903 data_time: 0.0062 memory: 8327 grad_norm: 7.5628 loss: 3.6311 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2453 loss_aux: 1.3858 2023/02/17 14:49:09 - mmengine - INFO - Epoch(train) [37][ 700/1345] lr: 1.0000e-02 eta: 8:09:13 time: 0.1900 data_time: 0.0066 memory: 8327 grad_norm: 7.5018 loss: 3.4732 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1324 loss_aux: 1.3408 2023/02/17 14:49:12 - mmengine - INFO - Epoch(train) [37][ 720/1345] lr: 1.0000e-02 eta: 8:09:09 time: 0.1890 data_time: 0.0060 memory: 8327 grad_norm: 7.5520 loss: 3.5278 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.0894 loss_aux: 1.4384 2023/02/17 14:49:16 - mmengine - INFO - Epoch(train) [37][ 740/1345] lr: 1.0000e-02 eta: 8:09:05 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.6874 loss: 3.8800 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4196 loss_aux: 1.4604 2023/02/17 14:49:20 - mmengine - INFO - Epoch(train) [37][ 760/1345] lr: 1.0000e-02 eta: 8:09:01 time: 0.1897 data_time: 0.0056 memory: 8327 grad_norm: 7.7226 loss: 3.3965 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0430 loss_aux: 1.3535 2023/02/17 14:49:24 - mmengine - INFO - Epoch(train) [37][ 780/1345] lr: 1.0000e-02 eta: 8:08:57 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.3924 loss: 3.3827 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0674 loss_aux: 1.3152 2023/02/17 14:49:27 - mmengine - INFO - Epoch(train) [37][ 800/1345] lr: 1.0000e-02 eta: 8:08:53 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.6055 loss: 3.5723 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1280 loss_aux: 1.4443 2023/02/17 14:49:31 - mmengine - INFO - Epoch(train) [37][ 820/1345] lr: 1.0000e-02 eta: 8:08:49 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5295 loss: 3.3769 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0519 loss_aux: 1.3250 2023/02/17 14:49:35 - mmengine - INFO - Epoch(train) [37][ 840/1345] lr: 1.0000e-02 eta: 8:08:45 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.5646 loss: 3.4407 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.0559 loss_aux: 1.3848 2023/02/17 14:49:39 - mmengine - INFO - Epoch(train) [37][ 860/1345] lr: 1.0000e-02 eta: 8:08:41 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.4697 loss: 3.7452 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3300 loss_aux: 1.4152 2023/02/17 14:49:43 - mmengine - INFO - Epoch(train) [37][ 880/1345] lr: 1.0000e-02 eta: 8:08:37 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.4447 loss: 3.3832 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0546 loss_aux: 1.3286 2023/02/17 14:49:46 - mmengine - INFO - Epoch(train) [37][ 900/1345] lr: 1.0000e-02 eta: 8:08:33 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.1929 loss: 3.4663 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0877 loss_aux: 1.3786 2023/02/17 14:49:50 - mmengine - INFO - Epoch(train) [37][ 920/1345] lr: 1.0000e-02 eta: 8:08:29 time: 0.1991 data_time: 0.0159 memory: 8327 grad_norm: 7.3995 loss: 3.7540 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3323 loss_aux: 1.4218 2023/02/17 14:49:54 - mmengine - INFO - Epoch(train) [37][ 940/1345] lr: 1.0000e-02 eta: 8:08:25 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.2437 loss: 3.4719 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.0677 loss_aux: 1.4042 2023/02/17 14:49:58 - mmengine - INFO - Epoch(train) [37][ 960/1345] lr: 1.0000e-02 eta: 8:08:21 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.5543 loss: 3.5424 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1865 loss_aux: 1.3559 2023/02/17 14:50:02 - mmengine - INFO - Epoch(train) [37][ 980/1345] lr: 1.0000e-02 eta: 8:08:17 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.5665 loss: 3.8158 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3341 loss_aux: 1.4817 2023/02/17 14:50:06 - mmengine - INFO - Epoch(train) [37][1000/1345] lr: 1.0000e-02 eta: 8:08:13 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.5526 loss: 3.5625 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1909 loss_aux: 1.3716 2023/02/17 14:50:09 - mmengine - INFO - Epoch(train) [37][1020/1345] lr: 1.0000e-02 eta: 8:08:09 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.5880 loss: 4.0106 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5064 loss_aux: 1.5043 2023/02/17 14:50:13 - mmengine - INFO - Epoch(train) [37][1040/1345] lr: 1.0000e-02 eta: 8:08:05 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.3591 loss: 3.5441 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1749 loss_aux: 1.3693 2023/02/17 14:50:17 - mmengine - INFO - Epoch(train) [37][1060/1345] lr: 1.0000e-02 eta: 8:08:01 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.3972 loss: 2.9580 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7178 loss_aux: 1.2401 2023/02/17 14:50:21 - mmengine - INFO - Epoch(train) [37][1080/1345] lr: 1.0000e-02 eta: 8:07:57 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.3248 loss: 3.6566 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1801 loss_aux: 1.4766 2023/02/17 14:50:25 - mmengine - INFO - Epoch(train) [37][1100/1345] lr: 1.0000e-02 eta: 8:07:53 time: 0.1910 data_time: 0.0077 memory: 8327 grad_norm: 7.3686 loss: 3.8404 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3429 loss_aux: 1.4975 2023/02/17 14:50:28 - mmengine - INFO - Epoch(train) [37][1120/1345] lr: 1.0000e-02 eta: 8:07:49 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.6621 loss: 4.0187 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5464 loss_aux: 1.4724 2023/02/17 14:50:32 - mmengine - INFO - Epoch(train) [37][1140/1345] lr: 1.0000e-02 eta: 8:07:45 time: 0.1897 data_time: 0.0062 memory: 8327 grad_norm: 7.6497 loss: 3.6574 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2351 loss_aux: 1.4222 2023/02/17 14:50:36 - mmengine - INFO - Epoch(train) [37][1160/1345] lr: 1.0000e-02 eta: 8:07:41 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.5015 loss: 3.4361 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0782 loss_aux: 1.3579 2023/02/17 14:50:40 - mmengine - INFO - Epoch(train) [37][1180/1345] lr: 1.0000e-02 eta: 8:07:37 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.6342 loss: 3.8715 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3989 loss_aux: 1.4726 2023/02/17 14:50:44 - mmengine - INFO - Epoch(train) [37][1200/1345] lr: 1.0000e-02 eta: 8:07:33 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.4648 loss: 3.5659 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1084 loss_aux: 1.4574 2023/02/17 14:50:47 - mmengine - INFO - Epoch(train) [37][1220/1345] lr: 1.0000e-02 eta: 8:07:29 time: 0.1892 data_time: 0.0060 memory: 8327 grad_norm: 7.5483 loss: 3.6920 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2761 loss_aux: 1.4160 2023/02/17 14:50:51 - mmengine - INFO - Epoch(train) [37][1240/1345] lr: 1.0000e-02 eta: 8:07:25 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.6018 loss: 3.4079 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0903 loss_aux: 1.3176 2023/02/17 14:50:55 - mmengine - INFO - Epoch(train) [37][1260/1345] lr: 1.0000e-02 eta: 8:07:21 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.6830 loss: 3.8224 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3231 loss_aux: 1.4993 2023/02/17 14:50:59 - mmengine - INFO - Epoch(train) [37][1280/1345] lr: 1.0000e-02 eta: 8:07:17 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.4102 loss: 3.4159 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0831 loss_aux: 1.3327 2023/02/17 14:51:02 - mmengine - INFO - Epoch(train) [37][1300/1345] lr: 1.0000e-02 eta: 8:07:13 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.4927 loss: 3.7078 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3408 loss_aux: 1.3671 2023/02/17 14:51:06 - mmengine - INFO - Epoch(train) [37][1320/1345] lr: 1.0000e-02 eta: 8:07:09 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.5244 loss: 3.4480 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0355 loss_aux: 1.4125 2023/02/17 14:51:10 - mmengine - INFO - Epoch(train) [37][1340/1345] lr: 1.0000e-02 eta: 8:07:05 time: 0.1898 data_time: 0.0060 memory: 8327 grad_norm: 7.4859 loss: 3.6025 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2311 loss_aux: 1.3714 2023/02/17 14:51:11 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:51:11 - mmengine - INFO - Epoch(train) [37][1345/1345] lr: 1.0000e-02 eta: 8:07:03 time: 0.1838 data_time: 0.0060 memory: 8327 grad_norm: 7.5384 loss: 3.9627 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.4661 loss_aux: 1.4966 2023/02/17 14:51:11 - mmengine - INFO - Saving checkpoint at 37 epochs 2023/02/17 14:51:18 - mmengine - INFO - Epoch(train) [38][ 20/1345] lr: 1.0000e-02 eta: 8:07:00 time: 0.2038 data_time: 0.0154 memory: 8327 grad_norm: 7.5161 loss: 3.5346 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1437 loss_aux: 1.3909 2023/02/17 14:51:21 - mmengine - INFO - Epoch(train) [38][ 40/1345] lr: 1.0000e-02 eta: 8:06:56 time: 0.1920 data_time: 0.0039 memory: 8327 grad_norm: 7.3371 loss: 3.1527 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8815 loss_aux: 1.2712 2023/02/17 14:51:25 - mmengine - INFO - Epoch(train) [38][ 60/1345] lr: 1.0000e-02 eta: 8:06:52 time: 0.1904 data_time: 0.0068 memory: 8327 grad_norm: 7.6820 loss: 3.7833 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3363 loss_aux: 1.4469 2023/02/17 14:51:29 - mmengine - INFO - Epoch(train) [38][ 80/1345] lr: 1.0000e-02 eta: 8:06:48 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.5270 loss: 3.4468 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1069 loss_aux: 1.3400 2023/02/17 14:51:33 - mmengine - INFO - Epoch(train) [38][ 100/1345] lr: 1.0000e-02 eta: 8:06:44 time: 0.1892 data_time: 0.0060 memory: 8327 grad_norm: 7.5463 loss: 3.5882 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1996 loss_aux: 1.3887 2023/02/17 14:51:37 - mmengine - INFO - Epoch(train) [38][ 120/1345] lr: 1.0000e-02 eta: 8:06:40 time: 0.1889 data_time: 0.0060 memory: 8327 grad_norm: 7.6660 loss: 3.6433 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2098 loss_aux: 1.4334 2023/02/17 14:51:40 - mmengine - INFO - Epoch(train) [38][ 140/1345] lr: 1.0000e-02 eta: 8:06:36 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.2700 loss: 3.8163 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3495 loss_aux: 1.4668 2023/02/17 14:51:44 - mmengine - INFO - Epoch(train) [38][ 160/1345] lr: 1.0000e-02 eta: 8:06:32 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.5460 loss: 3.5815 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1977 loss_aux: 1.3839 2023/02/17 14:51:48 - mmengine - INFO - Epoch(train) [38][ 180/1345] lr: 1.0000e-02 eta: 8:06:28 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.5744 loss: 3.6314 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2678 loss_aux: 1.3636 2023/02/17 14:51:52 - mmengine - INFO - Epoch(train) [38][ 200/1345] lr: 1.0000e-02 eta: 8:06:24 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.5474 loss: 3.3292 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0049 loss_aux: 1.3244 2023/02/17 14:51:56 - mmengine - INFO - Epoch(train) [38][ 220/1345] lr: 1.0000e-02 eta: 8:06:20 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.4087 loss: 3.5622 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1337 loss_aux: 1.4285 2023/02/17 14:51:58 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:51:59 - mmengine - INFO - Epoch(train) [38][ 240/1345] lr: 1.0000e-02 eta: 8:06:16 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5893 loss: 3.5901 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1990 loss_aux: 1.3911 2023/02/17 14:52:03 - mmengine - INFO - Epoch(train) [38][ 260/1345] lr: 1.0000e-02 eta: 8:06:12 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.4003 loss: 3.8253 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3257 loss_aux: 1.4996 2023/02/17 14:52:07 - mmengine - INFO - Epoch(train) [38][ 280/1345] lr: 1.0000e-02 eta: 8:06:08 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.4827 loss: 3.5075 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1457 loss_aux: 1.3618 2023/02/17 14:52:11 - mmengine - INFO - Epoch(train) [38][ 300/1345] lr: 1.0000e-02 eta: 8:06:04 time: 0.1897 data_time: 0.0062 memory: 8327 grad_norm: 7.5741 loss: 3.5159 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1835 loss_aux: 1.3325 2023/02/17 14:52:14 - mmengine - INFO - Epoch(train) [38][ 320/1345] lr: 1.0000e-02 eta: 8:06:00 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.7233 loss: 3.5573 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1456 loss_aux: 1.4117 2023/02/17 14:52:18 - mmengine - INFO - Epoch(train) [38][ 340/1345] lr: 1.0000e-02 eta: 8:05:56 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.7849 loss: 3.2185 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9629 loss_aux: 1.2556 2023/02/17 14:52:22 - mmengine - INFO - Epoch(train) [38][ 360/1345] lr: 1.0000e-02 eta: 8:05:52 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.5119 loss: 3.9144 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4444 loss_aux: 1.4700 2023/02/17 14:52:26 - mmengine - INFO - Epoch(train) [38][ 380/1345] lr: 1.0000e-02 eta: 8:05:48 time: 0.1898 data_time: 0.0061 memory: 8327 grad_norm: 7.6963 loss: 3.6957 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2831 loss_aux: 1.4126 2023/02/17 14:52:30 - mmengine - INFO - Epoch(train) [38][ 400/1345] lr: 1.0000e-02 eta: 8:05:44 time: 0.1907 data_time: 0.0073 memory: 8327 grad_norm: 7.4155 loss: 3.8467 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3924 loss_aux: 1.4543 2023/02/17 14:52:33 - mmengine - INFO - Epoch(train) [38][ 420/1345] lr: 1.0000e-02 eta: 8:05:40 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.5619 loss: 3.5134 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1101 loss_aux: 1.4032 2023/02/17 14:52:37 - mmengine - INFO - Epoch(train) [38][ 440/1345] lr: 1.0000e-02 eta: 8:05:36 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.6977 loss: 3.4205 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.0810 loss_aux: 1.3396 2023/02/17 14:52:41 - mmengine - INFO - Epoch(train) [38][ 460/1345] lr: 1.0000e-02 eta: 8:05:32 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.6842 loss: 3.3893 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0289 loss_aux: 1.3603 2023/02/17 14:52:45 - mmengine - INFO - Epoch(train) [38][ 480/1345] lr: 1.0000e-02 eta: 8:05:28 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.7586 loss: 3.3032 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9508 loss_aux: 1.3525 2023/02/17 14:52:49 - mmengine - INFO - Epoch(train) [38][ 500/1345] lr: 1.0000e-02 eta: 8:05:24 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.6296 loss: 3.7188 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2614 loss_aux: 1.4575 2023/02/17 14:52:52 - mmengine - INFO - Epoch(train) [38][ 520/1345] lr: 1.0000e-02 eta: 8:05:20 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.5696 loss: 3.3583 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0157 loss_aux: 1.3426 2023/02/17 14:52:56 - mmengine - INFO - Epoch(train) [38][ 540/1345] lr: 1.0000e-02 eta: 8:05:16 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.4445 loss: 4.0246 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5173 loss_aux: 1.5073 2023/02/17 14:53:00 - mmengine - INFO - Epoch(train) [38][ 560/1345] lr: 1.0000e-02 eta: 8:05:12 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.5317 loss: 3.5917 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1949 loss_aux: 1.3967 2023/02/17 14:53:04 - mmengine - INFO - Epoch(train) [38][ 580/1345] lr: 1.0000e-02 eta: 8:05:08 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5420 loss: 3.4725 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1285 loss_aux: 1.3440 2023/02/17 14:53:08 - mmengine - INFO - Epoch(train) [38][ 600/1345] lr: 1.0000e-02 eta: 8:05:04 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.6424 loss: 3.7349 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3165 loss_aux: 1.4184 2023/02/17 14:53:11 - mmengine - INFO - Epoch(train) [38][ 620/1345] lr: 1.0000e-02 eta: 8:05:00 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.7122 loss: 3.8250 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3713 loss_aux: 1.4536 2023/02/17 14:53:15 - mmengine - INFO - Epoch(train) [38][ 640/1345] lr: 1.0000e-02 eta: 8:04:56 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.4096 loss: 3.7426 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3521 loss_aux: 1.3905 2023/02/17 14:53:19 - mmengine - INFO - Epoch(train) [38][ 660/1345] lr: 1.0000e-02 eta: 8:04:52 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.6420 loss: 3.9437 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4531 loss_aux: 1.4907 2023/02/17 14:53:23 - mmengine - INFO - Epoch(train) [38][ 680/1345] lr: 1.0000e-02 eta: 8:04:48 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.2354 loss: 3.4667 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1295 loss_aux: 1.3372 2023/02/17 14:53:26 - mmengine - INFO - Epoch(train) [38][ 700/1345] lr: 1.0000e-02 eta: 8:04:44 time: 0.1892 data_time: 0.0061 memory: 8327 grad_norm: 7.4061 loss: 3.6951 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2537 loss_aux: 1.4414 2023/02/17 14:53:30 - mmengine - INFO - Epoch(train) [38][ 720/1345] lr: 1.0000e-02 eta: 8:04:40 time: 0.1890 data_time: 0.0060 memory: 8327 grad_norm: 7.5428 loss: 3.7070 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2626 loss_aux: 1.4444 2023/02/17 14:53:34 - mmengine - INFO - Epoch(train) [38][ 740/1345] lr: 1.0000e-02 eta: 8:04:36 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.3493 loss: 3.7418 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3170 loss_aux: 1.4248 2023/02/17 14:53:38 - mmengine - INFO - Epoch(train) [38][ 760/1345] lr: 1.0000e-02 eta: 8:04:32 time: 0.1892 data_time: 0.0060 memory: 8327 grad_norm: 7.3836 loss: 3.8334 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3579 loss_aux: 1.4754 2023/02/17 14:53:42 - mmengine - INFO - Epoch(train) [38][ 780/1345] lr: 1.0000e-02 eta: 8:04:28 time: 0.1900 data_time: 0.0062 memory: 8327 grad_norm: 7.4427 loss: 3.9867 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4620 loss_aux: 1.5247 2023/02/17 14:53:45 - mmengine - INFO - Epoch(train) [38][ 800/1345] lr: 1.0000e-02 eta: 8:04:24 time: 0.1897 data_time: 0.0064 memory: 8327 grad_norm: 7.5082 loss: 3.4531 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1483 loss_aux: 1.3049 2023/02/17 14:53:49 - mmengine - INFO - Epoch(train) [38][ 820/1345] lr: 1.0000e-02 eta: 8:04:20 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.5060 loss: 3.2081 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9261 loss_aux: 1.2821 2023/02/17 14:53:53 - mmengine - INFO - Epoch(train) [38][ 840/1345] lr: 1.0000e-02 eta: 8:04:16 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.5657 loss: 3.6960 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2426 loss_aux: 1.4535 2023/02/17 14:53:57 - mmengine - INFO - Epoch(train) [38][ 860/1345] lr: 1.0000e-02 eta: 8:04:11 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.4200 loss: 3.4481 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.0481 loss_aux: 1.4000 2023/02/17 14:54:01 - mmengine - INFO - Epoch(train) [38][ 880/1345] lr: 1.0000e-02 eta: 8:04:07 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.3468 loss: 3.6194 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2074 loss_aux: 1.4120 2023/02/17 14:54:04 - mmengine - INFO - Epoch(train) [38][ 900/1345] lr: 1.0000e-02 eta: 8:04:03 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.3532 loss: 3.2498 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9673 loss_aux: 1.2825 2023/02/17 14:54:08 - mmengine - INFO - Epoch(train) [38][ 920/1345] lr: 1.0000e-02 eta: 8:03:59 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5690 loss: 3.7287 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3024 loss_aux: 1.4263 2023/02/17 14:54:12 - mmengine - INFO - Epoch(train) [38][ 940/1345] lr: 1.0000e-02 eta: 8:03:55 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.4675 loss: 3.7309 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3235 loss_aux: 1.4074 2023/02/17 14:54:16 - mmengine - INFO - Epoch(train) [38][ 960/1345] lr: 1.0000e-02 eta: 8:03:51 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.4734 loss: 3.3341 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0196 loss_aux: 1.3145 2023/02/17 14:54:20 - mmengine - INFO - Epoch(train) [38][ 980/1345] lr: 1.0000e-02 eta: 8:03:47 time: 0.1898 data_time: 0.0066 memory: 8327 grad_norm: 7.5072 loss: 3.4797 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1229 loss_aux: 1.3568 2023/02/17 14:54:23 - mmengine - INFO - Epoch(train) [38][1000/1345] lr: 1.0000e-02 eta: 8:03:43 time: 0.1892 data_time: 0.0060 memory: 8327 grad_norm: 7.5893 loss: 3.4994 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1149 loss_aux: 1.3845 2023/02/17 14:54:27 - mmengine - INFO - Epoch(train) [38][1020/1345] lr: 1.0000e-02 eta: 8:03:39 time: 0.1892 data_time: 0.0062 memory: 8327 grad_norm: 7.5522 loss: 3.5975 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.2217 loss_aux: 1.3758 2023/02/17 14:54:31 - mmengine - INFO - Epoch(train) [38][1040/1345] lr: 1.0000e-02 eta: 8:03:35 time: 0.1892 data_time: 0.0061 memory: 8327 grad_norm: 7.7242 loss: 3.5771 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1748 loss_aux: 1.4023 2023/02/17 14:54:35 - mmengine - INFO - Epoch(train) [38][1060/1345] lr: 1.0000e-02 eta: 8:03:31 time: 0.1896 data_time: 0.0061 memory: 8327 grad_norm: 7.5930 loss: 3.4525 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0816 loss_aux: 1.3709 2023/02/17 14:54:38 - mmengine - INFO - Epoch(train) [38][1080/1345] lr: 1.0000e-02 eta: 8:03:27 time: 0.1891 data_time: 0.0060 memory: 8327 grad_norm: 7.5678 loss: 3.7943 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3266 loss_aux: 1.4677 2023/02/17 14:54:42 - mmengine - INFO - Epoch(train) [38][1100/1345] lr: 1.0000e-02 eta: 8:03:23 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.5307 loss: 3.6703 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2585 loss_aux: 1.4118 2023/02/17 14:54:46 - mmengine - INFO - Epoch(train) [38][1120/1345] lr: 1.0000e-02 eta: 8:03:19 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.6112 loss: 3.5471 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2079 loss_aux: 1.3392 2023/02/17 14:54:50 - mmengine - INFO - Epoch(train) [38][1140/1345] lr: 1.0000e-02 eta: 8:03:15 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.6312 loss: 3.0619 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8487 loss_aux: 1.2132 2023/02/17 14:54:54 - mmengine - INFO - Epoch(train) [38][1160/1345] lr: 1.0000e-02 eta: 8:03:11 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.7317 loss: 3.4729 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.1199 loss_aux: 1.3530 2023/02/17 14:54:57 - mmengine - INFO - Epoch(train) [38][1180/1345] lr: 1.0000e-02 eta: 8:03:07 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.5261 loss: 3.8126 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3315 loss_aux: 1.4811 2023/02/17 14:55:01 - mmengine - INFO - Epoch(train) [38][1200/1345] lr: 1.0000e-02 eta: 8:03:03 time: 0.1897 data_time: 0.0065 memory: 8327 grad_norm: 7.4360 loss: 3.8373 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3417 loss_aux: 1.4956 2023/02/17 14:55:05 - mmengine - INFO - Epoch(train) [38][1220/1345] lr: 1.0000e-02 eta: 8:02:59 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.2381 loss: 3.6719 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2830 loss_aux: 1.3889 2023/02/17 14:55:08 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:55:09 - mmengine - INFO - Epoch(train) [38][1240/1345] lr: 1.0000e-02 eta: 8:02:55 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.5427 loss: 3.8663 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3566 loss_aux: 1.5096 2023/02/17 14:55:13 - mmengine - INFO - Epoch(train) [38][1260/1345] lr: 1.0000e-02 eta: 8:02:51 time: 0.1909 data_time: 0.0058 memory: 8327 grad_norm: 7.4746 loss: 3.6884 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2877 loss_aux: 1.4007 2023/02/17 14:55:16 - mmengine - INFO - Epoch(train) [38][1280/1345] lr: 1.0000e-02 eta: 8:02:47 time: 0.1922 data_time: 0.0058 memory: 8327 grad_norm: 7.6486 loss: 3.7348 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3342 loss_aux: 1.4007 2023/02/17 14:55:20 - mmengine - INFO - Epoch(train) [38][1300/1345] lr: 1.0000e-02 eta: 8:02:43 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.3622 loss: 3.8366 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.3302 loss_aux: 1.5064 2023/02/17 14:55:24 - mmengine - INFO - Epoch(train) [38][1320/1345] lr: 1.0000e-02 eta: 8:02:39 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.1818 loss: 3.6028 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2004 loss_aux: 1.4024 2023/02/17 14:55:28 - mmengine - INFO - Epoch(train) [38][1340/1345] lr: 1.0000e-02 eta: 8:02:35 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.6014 loss: 3.6667 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2728 loss_aux: 1.3939 2023/02/17 14:55:29 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:55:29 - mmengine - INFO - Epoch(train) [38][1345/1345] lr: 1.0000e-02 eta: 8:02:34 time: 0.1832 data_time: 0.0059 memory: 8327 grad_norm: 7.5200 loss: 4.1135 top1_acc: 0.0000 top5_acc: 1.0000 loss_cls: 2.5670 loss_aux: 1.5465 2023/02/17 14:55:29 - mmengine - INFO - Saving checkpoint at 38 epochs 2023/02/17 14:55:35 - mmengine - INFO - Epoch(train) [39][ 20/1345] lr: 1.0000e-02 eta: 8:02:31 time: 0.2060 data_time: 0.0148 memory: 8327 grad_norm: 7.5987 loss: 3.6820 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2175 loss_aux: 1.4644 2023/02/17 14:55:39 - mmengine - INFO - Epoch(train) [39][ 40/1345] lr: 1.0000e-02 eta: 8:02:27 time: 0.1918 data_time: 0.0047 memory: 8327 grad_norm: 7.3959 loss: 3.3225 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0289 loss_aux: 1.2936 2023/02/17 14:55:43 - mmengine - INFO - Epoch(train) [39][ 60/1345] lr: 1.0000e-02 eta: 8:02:23 time: 0.1902 data_time: 0.0058 memory: 8327 grad_norm: 7.3295 loss: 3.1459 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8665 loss_aux: 1.2793 2023/02/17 14:55:47 - mmengine - INFO - Epoch(train) [39][ 80/1345] lr: 1.0000e-02 eta: 8:02:19 time: 0.1901 data_time: 0.0064 memory: 8327 grad_norm: 7.5874 loss: 3.5585 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1574 loss_aux: 1.4012 2023/02/17 14:55:51 - mmengine - INFO - Epoch(train) [39][ 100/1345] lr: 1.0000e-02 eta: 8:02:15 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.4251 loss: 3.6612 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2224 loss_aux: 1.4388 2023/02/17 14:55:54 - mmengine - INFO - Epoch(train) [39][ 120/1345] lr: 1.0000e-02 eta: 8:02:11 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.3252 loss: 3.4149 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1256 loss_aux: 1.2893 2023/02/17 14:55:58 - mmengine - INFO - Epoch(train) [39][ 140/1345] lr: 1.0000e-02 eta: 8:02:07 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.3694 loss: 3.2515 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9762 loss_aux: 1.2753 2023/02/17 14:56:02 - mmengine - INFO - Epoch(train) [39][ 160/1345] lr: 1.0000e-02 eta: 8:02:03 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.6483 loss: 3.6663 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.2383 loss_aux: 1.4280 2023/02/17 14:56:06 - mmengine - INFO - Epoch(train) [39][ 180/1345] lr: 1.0000e-02 eta: 8:01:59 time: 0.1903 data_time: 0.0064 memory: 8327 grad_norm: 7.5438 loss: 3.1729 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9039 loss_aux: 1.2690 2023/02/17 14:56:10 - mmengine - INFO - Epoch(train) [39][ 200/1345] lr: 1.0000e-02 eta: 8:01:55 time: 0.1914 data_time: 0.0072 memory: 8327 grad_norm: 7.2611 loss: 3.5703 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1960 loss_aux: 1.3743 2023/02/17 14:56:13 - mmengine - INFO - Epoch(train) [39][ 220/1345] lr: 1.0000e-02 eta: 8:01:51 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.3315 loss: 3.4687 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0809 loss_aux: 1.3878 2023/02/17 14:56:17 - mmengine - INFO - Epoch(train) [39][ 240/1345] lr: 1.0000e-02 eta: 8:01:47 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.3526 loss: 3.3003 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9890 loss_aux: 1.3113 2023/02/17 14:56:21 - mmengine - INFO - Epoch(train) [39][ 260/1345] lr: 1.0000e-02 eta: 8:01:43 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.6006 loss: 3.7335 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2733 loss_aux: 1.4602 2023/02/17 14:56:25 - mmengine - INFO - Epoch(train) [39][ 280/1345] lr: 1.0000e-02 eta: 8:01:39 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.7665 loss: 3.5923 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.1964 loss_aux: 1.3959 2023/02/17 14:56:29 - mmengine - INFO - Epoch(train) [39][ 300/1345] lr: 1.0000e-02 eta: 8:01:35 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.6152 loss: 3.8773 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4187 loss_aux: 1.4586 2023/02/17 14:56:32 - mmengine - INFO - Epoch(train) [39][ 320/1345] lr: 1.0000e-02 eta: 8:01:31 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7126 loss: 3.5279 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1318 loss_aux: 1.3961 2023/02/17 14:56:36 - mmengine - INFO - Epoch(train) [39][ 340/1345] lr: 1.0000e-02 eta: 8:01:27 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.3934 loss: 3.7324 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.3053 loss_aux: 1.4271 2023/02/17 14:56:40 - mmengine - INFO - Epoch(train) [39][ 360/1345] lr: 1.0000e-02 eta: 8:01:23 time: 0.1896 data_time: 0.0056 memory: 8327 grad_norm: 7.4569 loss: 3.6897 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2910 loss_aux: 1.3987 2023/02/17 14:56:44 - mmengine - INFO - Epoch(train) [39][ 380/1345] lr: 1.0000e-02 eta: 8:01:19 time: 0.1903 data_time: 0.0058 memory: 8327 grad_norm: 7.2983 loss: 3.3890 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0465 loss_aux: 1.3426 2023/02/17 14:56:48 - mmengine - INFO - Epoch(train) [39][ 400/1345] lr: 1.0000e-02 eta: 8:01:15 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.1985 loss: 3.5811 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1756 loss_aux: 1.4055 2023/02/17 14:56:51 - mmengine - INFO - Epoch(train) [39][ 420/1345] lr: 1.0000e-02 eta: 8:01:11 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.5787 loss: 3.4902 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0935 loss_aux: 1.3967 2023/02/17 14:56:55 - mmengine - INFO - Epoch(train) [39][ 440/1345] lr: 1.0000e-02 eta: 8:01:07 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.4504 loss: 3.5254 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1564 loss_aux: 1.3690 2023/02/17 14:56:59 - mmengine - INFO - Epoch(train) [39][ 460/1345] lr: 1.0000e-02 eta: 8:01:03 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.5864 loss: 3.5905 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.2262 loss_aux: 1.3643 2023/02/17 14:57:03 - mmengine - INFO - Epoch(train) [39][ 480/1345] lr: 1.0000e-02 eta: 8:00:59 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.6241 loss: 3.5585 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1488 loss_aux: 1.4097 2023/02/17 14:57:07 - mmengine - INFO - Epoch(train) [39][ 500/1345] lr: 1.0000e-02 eta: 8:00:55 time: 0.1900 data_time: 0.0058 memory: 8327 grad_norm: 7.3837 loss: 3.4099 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0628 loss_aux: 1.3471 2023/02/17 14:57:10 - mmengine - INFO - Epoch(train) [39][ 520/1345] lr: 1.0000e-02 eta: 8:00:51 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5073 loss: 3.4966 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1396 loss_aux: 1.3570 2023/02/17 14:57:14 - mmengine - INFO - Epoch(train) [39][ 540/1345] lr: 1.0000e-02 eta: 8:00:47 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5905 loss: 3.4376 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0797 loss_aux: 1.3579 2023/02/17 14:57:18 - mmengine - INFO - Epoch(train) [39][ 560/1345] lr: 1.0000e-02 eta: 8:00:43 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.6768 loss: 3.4617 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1308 loss_aux: 1.3309 2023/02/17 14:57:22 - mmengine - INFO - Epoch(train) [39][ 580/1345] lr: 1.0000e-02 eta: 8:00:39 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.4805 loss: 3.3801 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0588 loss_aux: 1.3213 2023/02/17 14:57:26 - mmengine - INFO - Epoch(train) [39][ 600/1345] lr: 1.0000e-02 eta: 8:00:35 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.4843 loss: 3.3572 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0192 loss_aux: 1.3380 2023/02/17 14:57:29 - mmengine - INFO - Epoch(train) [39][ 620/1345] lr: 1.0000e-02 eta: 8:00:31 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.5166 loss: 3.4266 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0817 loss_aux: 1.3449 2023/02/17 14:57:33 - mmengine - INFO - Epoch(train) [39][ 640/1345] lr: 1.0000e-02 eta: 8:00:27 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.7831 loss: 3.5676 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1854 loss_aux: 1.3821 2023/02/17 14:57:37 - mmengine - INFO - Epoch(train) [39][ 660/1345] lr: 1.0000e-02 eta: 8:00:23 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.4297 loss: 3.2450 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9733 loss_aux: 1.2717 2023/02/17 14:57:41 - mmengine - INFO - Epoch(train) [39][ 680/1345] lr: 1.0000e-02 eta: 8:00:19 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.5391 loss: 3.5329 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1566 loss_aux: 1.3763 2023/02/17 14:57:44 - mmengine - INFO - Epoch(train) [39][ 700/1345] lr: 1.0000e-02 eta: 8:00:15 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.4117 loss: 3.3657 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.0499 loss_aux: 1.3158 2023/02/17 14:57:48 - mmengine - INFO - Epoch(train) [39][ 720/1345] lr: 1.0000e-02 eta: 8:00:11 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.5877 loss: 3.4766 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1314 loss_aux: 1.3451 2023/02/17 14:57:52 - mmengine - INFO - Epoch(train) [39][ 740/1345] lr: 1.0000e-02 eta: 8:00:07 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.6421 loss: 3.5456 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1630 loss_aux: 1.3826 2023/02/17 14:57:56 - mmengine - INFO - Epoch(train) [39][ 760/1345] lr: 1.0000e-02 eta: 8:00:03 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.4929 loss: 3.0729 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.8889 loss_aux: 1.1840 2023/02/17 14:58:00 - mmengine - INFO - Epoch(train) [39][ 780/1345] lr: 1.0000e-02 eta: 7:59:59 time: 0.1912 data_time: 0.0075 memory: 8327 grad_norm: 7.3402 loss: 3.7446 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2669 loss_aux: 1.4776 2023/02/17 14:58:03 - mmengine - INFO - Epoch(train) [39][ 800/1345] lr: 1.0000e-02 eta: 7:59:55 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.4617 loss: 3.4845 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0959 loss_aux: 1.3886 2023/02/17 14:58:07 - mmengine - INFO - Epoch(train) [39][ 820/1345] lr: 1.0000e-02 eta: 7:59:52 time: 0.1997 data_time: 0.0158 memory: 8327 grad_norm: 7.7331 loss: 3.4167 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0984 loss_aux: 1.3182 2023/02/17 14:58:11 - mmengine - INFO - Epoch(train) [39][ 840/1345] lr: 1.0000e-02 eta: 7:59:48 time: 0.1896 data_time: 0.0056 memory: 8327 grad_norm: 7.6558 loss: 3.6618 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2767 loss_aux: 1.3851 2023/02/17 14:58:15 - mmengine - INFO - Epoch(train) [39][ 860/1345] lr: 1.0000e-02 eta: 7:59:44 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.6065 loss: 3.6433 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2587 loss_aux: 1.3846 2023/02/17 14:58:19 - mmengine - INFO - Epoch(train) [39][ 880/1345] lr: 1.0000e-02 eta: 7:59:40 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.3657 loss: 3.0941 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8805 loss_aux: 1.2135 2023/02/17 14:58:21 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:58:23 - mmengine - INFO - Epoch(train) [39][ 900/1345] lr: 1.0000e-02 eta: 7:59:36 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5259 loss: 3.5176 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1144 loss_aux: 1.4031 2023/02/17 14:58:26 - mmengine - INFO - Epoch(train) [39][ 920/1345] lr: 1.0000e-02 eta: 7:59:32 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.5598 loss: 3.8832 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4466 loss_aux: 1.4366 2023/02/17 14:58:30 - mmengine - INFO - Epoch(train) [39][ 940/1345] lr: 1.0000e-02 eta: 7:59:28 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.4402 loss: 3.7621 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3122 loss_aux: 1.4499 2023/02/17 14:58:34 - mmengine - INFO - Epoch(train) [39][ 960/1345] lr: 1.0000e-02 eta: 7:59:24 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.4877 loss: 4.0250 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5030 loss_aux: 1.5220 2023/02/17 14:58:38 - mmengine - INFO - Epoch(train) [39][ 980/1345] lr: 1.0000e-02 eta: 7:59:20 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.6283 loss: 3.4876 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1627 loss_aux: 1.3248 2023/02/17 14:58:42 - mmengine - INFO - Epoch(train) [39][1000/1345] lr: 1.0000e-02 eta: 7:59:16 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.4922 loss: 3.5881 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2181 loss_aux: 1.3700 2023/02/17 14:58:45 - mmengine - INFO - Epoch(train) [39][1020/1345] lr: 1.0000e-02 eta: 7:59:12 time: 0.1902 data_time: 0.0058 memory: 8327 grad_norm: 7.6388 loss: 3.9200 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4534 loss_aux: 1.4666 2023/02/17 14:58:49 - mmengine - INFO - Epoch(train) [39][1040/1345] lr: 1.0000e-02 eta: 7:59:08 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 7.8295 loss: 3.7984 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3297 loss_aux: 1.4687 2023/02/17 14:58:53 - mmengine - INFO - Epoch(train) [39][1060/1345] lr: 1.0000e-02 eta: 7:59:04 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.4680 loss: 3.4888 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.1674 loss_aux: 1.3214 2023/02/17 14:58:57 - mmengine - INFO - Epoch(train) [39][1080/1345] lr: 1.0000e-02 eta: 7:59:00 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.5412 loss: 3.3024 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 1.9917 loss_aux: 1.3106 2023/02/17 14:59:01 - mmengine - INFO - Epoch(train) [39][1100/1345] lr: 1.0000e-02 eta: 7:58:56 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.7725 loss: 3.6511 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2378 loss_aux: 1.4132 2023/02/17 14:59:04 - mmengine - INFO - Epoch(train) [39][1120/1345] lr: 1.0000e-02 eta: 7:58:52 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.4198 loss: 3.5663 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.1857 loss_aux: 1.3806 2023/02/17 14:59:08 - mmengine - INFO - Epoch(train) [39][1140/1345] lr: 1.0000e-02 eta: 7:58:48 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.4116 loss: 3.6767 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2748 loss_aux: 1.4019 2023/02/17 14:59:12 - mmengine - INFO - Epoch(train) [39][1160/1345] lr: 1.0000e-02 eta: 7:58:44 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.8834 loss: 4.0103 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4556 loss_aux: 1.5548 2023/02/17 14:59:16 - mmengine - INFO - Epoch(train) [39][1180/1345] lr: 1.0000e-02 eta: 7:58:40 time: 0.1900 data_time: 0.0063 memory: 8327 grad_norm: 7.8148 loss: 4.0830 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5052 loss_aux: 1.5778 2023/02/17 14:59:19 - mmengine - INFO - Epoch(train) [39][1200/1345] lr: 1.0000e-02 eta: 7:58:36 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.5188 loss: 3.4801 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1178 loss_aux: 1.3622 2023/02/17 14:59:23 - mmengine - INFO - Epoch(train) [39][1220/1345] lr: 1.0000e-02 eta: 7:58:32 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.3359 loss: 3.6811 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2919 loss_aux: 1.3892 2023/02/17 14:59:27 - mmengine - INFO - Epoch(train) [39][1240/1345] lr: 1.0000e-02 eta: 7:58:28 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.4363 loss: 3.6044 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.1853 loss_aux: 1.4192 2023/02/17 14:59:31 - mmengine - INFO - Epoch(train) [39][1260/1345] lr: 1.0000e-02 eta: 7:58:24 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.6079 loss: 3.5249 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1722 loss_aux: 1.3527 2023/02/17 14:59:35 - mmengine - INFO - Epoch(train) [39][1280/1345] lr: 1.0000e-02 eta: 7:58:20 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.4072 loss: 3.4522 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1280 loss_aux: 1.3242 2023/02/17 14:59:38 - mmengine - INFO - Epoch(train) [39][1300/1345] lr: 1.0000e-02 eta: 7:58:16 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.5082 loss: 3.4655 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0711 loss_aux: 1.3944 2023/02/17 14:59:42 - mmengine - INFO - Epoch(train) [39][1320/1345] lr: 1.0000e-02 eta: 7:58:12 time: 0.1918 data_time: 0.0069 memory: 8327 grad_norm: 7.8656 loss: 3.6846 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2606 loss_aux: 1.4241 2023/02/17 14:59:46 - mmengine - INFO - Epoch(train) [39][1340/1345] lr: 1.0000e-02 eta: 7:58:08 time: 0.1900 data_time: 0.0069 memory: 8327 grad_norm: 7.6398 loss: 3.7149 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2955 loss_aux: 1.4193 2023/02/17 14:59:47 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 14:59:47 - mmengine - INFO - Epoch(train) [39][1345/1345] lr: 1.0000e-02 eta: 7:58:06 time: 0.1838 data_time: 0.0069 memory: 8327 grad_norm: 7.7294 loss: 4.1079 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.5634 loss_aux: 1.5445 2023/02/17 14:59:47 - mmengine - INFO - Saving checkpoint at 39 epochs 2023/02/17 14:59:54 - mmengine - INFO - Epoch(train) [40][ 20/1345] lr: 1.0000e-02 eta: 7:58:03 time: 0.2070 data_time: 0.0155 memory: 8327 grad_norm: 7.6085 loss: 3.2091 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9347 loss_aux: 1.2744 2023/02/17 14:59:57 - mmengine - INFO - Epoch(train) [40][ 40/1345] lr: 1.0000e-02 eta: 7:58:00 time: 0.1920 data_time: 0.0050 memory: 8327 grad_norm: 7.5195 loss: 3.6302 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2430 loss_aux: 1.3872 2023/02/17 15:00:01 - mmengine - INFO - Epoch(train) [40][ 60/1345] lr: 1.0000e-02 eta: 7:57:56 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5823 loss: 3.6175 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2289 loss_aux: 1.3886 2023/02/17 15:00:05 - mmengine - INFO - Epoch(train) [40][ 80/1345] lr: 1.0000e-02 eta: 7:57:52 time: 0.1901 data_time: 0.0060 memory: 8327 grad_norm: 7.7870 loss: 3.6622 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2338 loss_aux: 1.4284 2023/02/17 15:00:09 - mmengine - INFO - Epoch(train) [40][ 100/1345] lr: 1.0000e-02 eta: 7:57:48 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.5259 loss: 3.8645 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3596 loss_aux: 1.5049 2023/02/17 15:00:13 - mmengine - INFO - Epoch(train) [40][ 120/1345] lr: 1.0000e-02 eta: 7:57:44 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.4815 loss: 3.3144 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0007 loss_aux: 1.3137 2023/02/17 15:00:16 - mmengine - INFO - Epoch(train) [40][ 140/1345] lr: 1.0000e-02 eta: 7:57:40 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.6075 loss: 3.2370 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9519 loss_aux: 1.2851 2023/02/17 15:00:20 - mmengine - INFO - Epoch(train) [40][ 160/1345] lr: 1.0000e-02 eta: 7:57:36 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.4149 loss: 3.6113 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1990 loss_aux: 1.4123 2023/02/17 15:00:24 - mmengine - INFO - Epoch(train) [40][ 180/1345] lr: 1.0000e-02 eta: 7:57:32 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.5124 loss: 3.6222 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2292 loss_aux: 1.3929 2023/02/17 15:00:28 - mmengine - INFO - Epoch(train) [40][ 200/1345] lr: 1.0000e-02 eta: 7:57:28 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.6542 loss: 3.6620 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.2524 loss_aux: 1.4096 2023/02/17 15:00:32 - mmengine - INFO - Epoch(train) [40][ 220/1345] lr: 1.0000e-02 eta: 7:57:24 time: 0.1889 data_time: 0.0058 memory: 8327 grad_norm: 7.7959 loss: 3.6572 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2340 loss_aux: 1.4232 2023/02/17 15:00:35 - mmengine - INFO - Epoch(train) [40][ 240/1345] lr: 1.0000e-02 eta: 7:57:20 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.4081 loss: 3.4504 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.0960 loss_aux: 1.3544 2023/02/17 15:00:39 - mmengine - INFO - Epoch(train) [40][ 260/1345] lr: 1.0000e-02 eta: 7:57:16 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.5349 loss: 3.4856 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0613 loss_aux: 1.4243 2023/02/17 15:00:43 - mmengine - INFO - Epoch(train) [40][ 280/1345] lr: 1.0000e-02 eta: 7:57:12 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.5129 loss: 3.4793 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1243 loss_aux: 1.3549 2023/02/17 15:00:47 - mmengine - INFO - Epoch(train) [40][ 300/1345] lr: 1.0000e-02 eta: 7:57:09 time: 0.2093 data_time: 0.0258 memory: 8327 grad_norm: 7.6020 loss: 3.5448 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1186 loss_aux: 1.4262 2023/02/17 15:00:51 - mmengine - INFO - Epoch(train) [40][ 320/1345] lr: 1.0000e-02 eta: 7:57:05 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.7122 loss: 3.5285 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1577 loss_aux: 1.3708 2023/02/17 15:00:55 - mmengine - INFO - Epoch(train) [40][ 340/1345] lr: 1.0000e-02 eta: 7:57:01 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.4137 loss: 3.4326 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1145 loss_aux: 1.3181 2023/02/17 15:00:58 - mmengine - INFO - Epoch(train) [40][ 360/1345] lr: 1.0000e-02 eta: 7:56:57 time: 0.1892 data_time: 0.0060 memory: 8327 grad_norm: 7.4134 loss: 3.4384 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1205 loss_aux: 1.3179 2023/02/17 15:01:02 - mmengine - INFO - Epoch(train) [40][ 380/1345] lr: 1.0000e-02 eta: 7:56:53 time: 0.1904 data_time: 0.0068 memory: 8327 grad_norm: 7.4962 loss: 3.9244 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3998 loss_aux: 1.5246 2023/02/17 15:01:06 - mmengine - INFO - Epoch(train) [40][ 400/1345] lr: 1.0000e-02 eta: 7:56:49 time: 0.1892 data_time: 0.0060 memory: 8327 grad_norm: 7.2123 loss: 3.4874 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.1438 loss_aux: 1.3435 2023/02/17 15:01:10 - mmengine - INFO - Epoch(train) [40][ 420/1345] lr: 1.0000e-02 eta: 7:56:45 time: 0.1904 data_time: 0.0066 memory: 8327 grad_norm: 7.5303 loss: 3.5225 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1116 loss_aux: 1.4109 2023/02/17 15:01:14 - mmengine - INFO - Epoch(train) [40][ 440/1345] lr: 1.0000e-02 eta: 7:56:41 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.4685 loss: 3.5817 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1874 loss_aux: 1.3943 2023/02/17 15:01:17 - mmengine - INFO - Epoch(train) [40][ 460/1345] lr: 1.0000e-02 eta: 7:56:37 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.6030 loss: 3.8896 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4091 loss_aux: 1.4805 2023/02/17 15:01:21 - mmengine - INFO - Epoch(train) [40][ 480/1345] lr: 1.0000e-02 eta: 7:56:33 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.4377 loss: 3.7108 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2690 loss_aux: 1.4418 2023/02/17 15:01:25 - mmengine - INFO - Epoch(train) [40][ 500/1345] lr: 1.0000e-02 eta: 7:56:29 time: 0.1897 data_time: 0.0062 memory: 8327 grad_norm: 7.6449 loss: 3.7090 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2547 loss_aux: 1.4543 2023/02/17 15:01:29 - mmengine - INFO - Epoch(train) [40][ 520/1345] lr: 1.0000e-02 eta: 7:56:25 time: 0.1901 data_time: 0.0059 memory: 8327 grad_norm: 7.5684 loss: 3.7745 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3532 loss_aux: 1.4213 2023/02/17 15:01:33 - mmengine - INFO - Epoch(train) [40][ 540/1345] lr: 1.0000e-02 eta: 7:56:21 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.5306 loss: 3.3413 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9924 loss_aux: 1.3488 2023/02/17 15:01:34 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:01:36 - mmengine - INFO - Epoch(train) [40][ 560/1345] lr: 1.0000e-02 eta: 7:56:17 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.4189 loss: 3.7292 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2769 loss_aux: 1.4523 2023/02/17 15:01:40 - mmengine - INFO - Epoch(train) [40][ 580/1345] lr: 1.0000e-02 eta: 7:56:13 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.5428 loss: 3.6053 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.2184 loss_aux: 1.3869 2023/02/17 15:01:44 - mmengine - INFO - Epoch(train) [40][ 600/1345] lr: 1.0000e-02 eta: 7:56:09 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.5806 loss: 3.4321 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0873 loss_aux: 1.3449 2023/02/17 15:01:48 - mmengine - INFO - Epoch(train) [40][ 620/1345] lr: 1.0000e-02 eta: 7:56:05 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.4778 loss: 3.4097 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0850 loss_aux: 1.3247 2023/02/17 15:01:52 - mmengine - INFO - Epoch(train) [40][ 640/1345] lr: 1.0000e-02 eta: 7:56:01 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.4531 loss: 3.1396 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8904 loss_aux: 1.2493 2023/02/17 15:01:55 - mmengine - INFO - Epoch(train) [40][ 660/1345] lr: 1.0000e-02 eta: 7:55:57 time: 0.1890 data_time: 0.0059 memory: 8327 grad_norm: 7.7485 loss: 3.3832 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0547 loss_aux: 1.3284 2023/02/17 15:01:59 - mmengine - INFO - Epoch(train) [40][ 680/1345] lr: 1.0000e-02 eta: 7:55:53 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.7049 loss: 3.3832 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0054 loss_aux: 1.3778 2023/02/17 15:02:03 - mmengine - INFO - Epoch(train) [40][ 700/1345] lr: 1.0000e-02 eta: 7:55:49 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.5963 loss: 3.7343 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2909 loss_aux: 1.4434 2023/02/17 15:02:07 - mmengine - INFO - Epoch(train) [40][ 720/1345] lr: 1.0000e-02 eta: 7:55:45 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.5215 loss: 3.6669 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2621 loss_aux: 1.4048 2023/02/17 15:02:11 - mmengine - INFO - Epoch(train) [40][ 740/1345] lr: 1.0000e-02 eta: 7:55:41 time: 0.1892 data_time: 0.0060 memory: 8327 grad_norm: 7.4437 loss: 3.3460 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9681 loss_aux: 1.3780 2023/02/17 15:02:14 - mmengine - INFO - Epoch(train) [40][ 760/1345] lr: 1.0000e-02 eta: 7:55:37 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.2612 loss: 3.8070 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3976 loss_aux: 1.4094 2023/02/17 15:02:18 - mmengine - INFO - Epoch(train) [40][ 780/1345] lr: 1.0000e-02 eta: 7:55:33 time: 0.1926 data_time: 0.0058 memory: 8327 grad_norm: 7.5358 loss: 3.5377 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1935 loss_aux: 1.3442 2023/02/17 15:02:22 - mmengine - INFO - Epoch(train) [40][ 800/1345] lr: 1.0000e-02 eta: 7:55:29 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.4344 loss: 3.6364 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2017 loss_aux: 1.4347 2023/02/17 15:02:26 - mmengine - INFO - Epoch(train) [40][ 820/1345] lr: 1.0000e-02 eta: 7:55:25 time: 0.1894 data_time: 0.0061 memory: 8327 grad_norm: 7.5956 loss: 3.2904 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9799 loss_aux: 1.3104 2023/02/17 15:02:30 - mmengine - INFO - Epoch(train) [40][ 840/1345] lr: 1.0000e-02 eta: 7:55:21 time: 0.1897 data_time: 0.0057 memory: 8327 grad_norm: 7.9861 loss: 3.8312 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3831 loss_aux: 1.4481 2023/02/17 15:02:33 - mmengine - INFO - Epoch(train) [40][ 860/1345] lr: 1.0000e-02 eta: 7:55:17 time: 0.1890 data_time: 0.0056 memory: 8327 grad_norm: 7.7014 loss: 3.5174 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.1295 loss_aux: 1.3878 2023/02/17 15:02:37 - mmengine - INFO - Epoch(train) [40][ 880/1345] lr: 1.0000e-02 eta: 7:55:13 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.6901 loss: 3.5702 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2276 loss_aux: 1.3426 2023/02/17 15:02:41 - mmengine - INFO - Epoch(train) [40][ 900/1345] lr: 1.0000e-02 eta: 7:55:09 time: 0.1900 data_time: 0.0063 memory: 8327 grad_norm: 7.4757 loss: 3.4729 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.0759 loss_aux: 1.3970 2023/02/17 15:02:45 - mmengine - INFO - Epoch(train) [40][ 920/1345] lr: 1.0000e-02 eta: 7:55:05 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.7099 loss: 3.6678 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2537 loss_aux: 1.4141 2023/02/17 15:02:49 - mmengine - INFO - Epoch(train) [40][ 940/1345] lr: 1.0000e-02 eta: 7:55:01 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.7723 loss: 3.7220 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2843 loss_aux: 1.4377 2023/02/17 15:02:52 - mmengine - INFO - Epoch(train) [40][ 960/1345] lr: 1.0000e-02 eta: 7:54:57 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.4769 loss: 3.4083 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0355 loss_aux: 1.3729 2023/02/17 15:02:56 - mmengine - INFO - Epoch(train) [40][ 980/1345] lr: 1.0000e-02 eta: 7:54:53 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.6307 loss: 3.3228 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9325 loss_aux: 1.3903 2023/02/17 15:03:00 - mmengine - INFO - Epoch(train) [40][1000/1345] lr: 1.0000e-02 eta: 7:54:49 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.5933 loss: 3.3953 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0967 loss_aux: 1.2987 2023/02/17 15:03:04 - mmengine - INFO - Epoch(train) [40][1020/1345] lr: 1.0000e-02 eta: 7:54:45 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.3859 loss: 3.5457 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1545 loss_aux: 1.3912 2023/02/17 15:03:07 - mmengine - INFO - Epoch(train) [40][1040/1345] lr: 1.0000e-02 eta: 7:54:41 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.6655 loss: 3.5933 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1857 loss_aux: 1.4076 2023/02/17 15:03:11 - mmengine - INFO - Epoch(train) [40][1060/1345] lr: 1.0000e-02 eta: 7:54:37 time: 0.1897 data_time: 0.0057 memory: 8327 grad_norm: 7.6798 loss: 4.0371 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5043 loss_aux: 1.5328 2023/02/17 15:03:15 - mmengine - INFO - Epoch(train) [40][1080/1345] lr: 1.0000e-02 eta: 7:54:33 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.5008 loss: 3.3544 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0418 loss_aux: 1.3126 2023/02/17 15:03:19 - mmengine - INFO - Epoch(train) [40][1100/1345] lr: 1.0000e-02 eta: 7:54:29 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.3784 loss: 3.9034 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3758 loss_aux: 1.5276 2023/02/17 15:03:23 - mmengine - INFO - Epoch(train) [40][1120/1345] lr: 1.0000e-02 eta: 7:54:25 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.6396 loss: 3.2769 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9708 loss_aux: 1.3061 2023/02/17 15:03:27 - mmengine - INFO - Epoch(train) [40][1140/1345] lr: 1.0000e-02 eta: 7:54:22 time: 0.1997 data_time: 0.0159 memory: 8327 grad_norm: 7.6657 loss: 3.8639 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4036 loss_aux: 1.4604 2023/02/17 15:03:30 - mmengine - INFO - Epoch(train) [40][1160/1345] lr: 1.0000e-02 eta: 7:54:18 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.6906 loss: 3.8736 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4424 loss_aux: 1.4312 2023/02/17 15:03:34 - mmengine - INFO - Epoch(train) [40][1180/1345] lr: 1.0000e-02 eta: 7:54:14 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.5834 loss: 3.6793 top1_acc: 0.1250 top5_acc: 0.8750 loss_cls: 2.2889 loss_aux: 1.3904 2023/02/17 15:03:38 - mmengine - INFO - Epoch(train) [40][1200/1345] lr: 1.0000e-02 eta: 7:54:10 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.5118 loss: 3.7513 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3389 loss_aux: 1.4123 2023/02/17 15:03:42 - mmengine - INFO - Epoch(train) [40][1220/1345] lr: 1.0000e-02 eta: 7:54:06 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.6610 loss: 3.5495 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1806 loss_aux: 1.3688 2023/02/17 15:03:46 - mmengine - INFO - Epoch(train) [40][1240/1345] lr: 1.0000e-02 eta: 7:54:02 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.4440 loss: 3.5810 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1815 loss_aux: 1.3995 2023/02/17 15:03:49 - mmengine - INFO - Epoch(train) [40][1260/1345] lr: 1.0000e-02 eta: 7:53:58 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.4241 loss: 3.6943 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2815 loss_aux: 1.4128 2023/02/17 15:03:53 - mmengine - INFO - Epoch(train) [40][1280/1345] lr: 1.0000e-02 eta: 7:53:54 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.5309 loss: 3.2105 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8766 loss_aux: 1.3339 2023/02/17 15:03:57 - mmengine - INFO - Epoch(train) [40][1300/1345] lr: 1.0000e-02 eta: 7:53:50 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.4657 loss: 3.7701 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3067 loss_aux: 1.4634 2023/02/17 15:04:01 - mmengine - INFO - Epoch(train) [40][1320/1345] lr: 1.0000e-02 eta: 7:53:46 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5964 loss: 3.7879 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3397 loss_aux: 1.4482 2023/02/17 15:04:05 - mmengine - INFO - Epoch(train) [40][1340/1345] lr: 1.0000e-02 eta: 7:53:42 time: 0.1901 data_time: 0.0060 memory: 8327 grad_norm: 7.7585 loss: 3.8154 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3539 loss_aux: 1.4614 2023/02/17 15:04:05 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:04:05 - mmengine - INFO - Epoch(train) [40][1345/1345] lr: 1.0000e-02 eta: 7:53:40 time: 0.1836 data_time: 0.0061 memory: 8327 grad_norm: 7.5720 loss: 3.8257 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.3585 loss_aux: 1.4672 2023/02/17 15:04:05 - mmengine - INFO - Saving checkpoint at 40 epochs 2023/02/17 15:04:09 - mmengine - INFO - Epoch(val) [40][ 20/181] eta: 0:00:09 time: 0.0572 data_time: 0.0076 memory: 1994 2023/02/17 15:04:10 - mmengine - INFO - Epoch(val) [40][ 40/181] eta: 0:00:07 time: 0.0526 data_time: 0.0047 memory: 1994 2023/02/17 15:04:11 - mmengine - INFO - Epoch(val) [40][ 60/181] eta: 0:00:06 time: 0.0525 data_time: 0.0047 memory: 1994 2023/02/17 15:04:12 - mmengine - INFO - Epoch(val) [40][ 80/181] eta: 0:00:05 time: 0.0524 data_time: 0.0047 memory: 1994 2023/02/17 15:04:13 - mmengine - INFO - Epoch(val) [40][100/181] eta: 0:00:04 time: 0.0522 data_time: 0.0044 memory: 1994 2023/02/17 15:04:14 - mmengine - INFO - Epoch(val) [40][120/181] eta: 0:00:03 time: 0.0523 data_time: 0.0045 memory: 1994 2023/02/17 15:04:15 - mmengine - INFO - Epoch(val) [40][140/181] eta: 0:00:02 time: 0.0521 data_time: 0.0043 memory: 1994 2023/02/17 15:04:16 - mmengine - INFO - Epoch(val) [40][160/181] eta: 0:00:01 time: 0.0520 data_time: 0.0044 memory: 1994 2023/02/17 15:04:17 - mmengine - INFO - Epoch(val) [40][180/181] eta: 0:00:00 time: 0.0516 data_time: 0.0042 memory: 1994 2023/02/17 15:04:18 - mmengine - INFO - Epoch(val) [40][181/181] acc/top1: 0.3766 acc/top5: 0.6748 acc/mean1: 0.3332 2023/02/17 15:04:23 - mmengine - INFO - Epoch(train) [41][ 20/1345] lr: 1.0000e-02 eta: 7:53:39 time: 0.2389 data_time: 0.0404 memory: 8327 grad_norm: 7.5589 loss: 3.2733 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9725 loss_aux: 1.3008 2023/02/17 15:04:26 - mmengine - INFO - Epoch(train) [41][ 40/1345] lr: 1.0000e-02 eta: 7:53:35 time: 0.1916 data_time: 0.0049 memory: 8327 grad_norm: 7.4218 loss: 3.3863 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0601 loss_aux: 1.3262 2023/02/17 15:04:30 - mmengine - INFO - Epoch(train) [41][ 60/1345] lr: 1.0000e-02 eta: 7:53:31 time: 0.1893 data_time: 0.0054 memory: 8327 grad_norm: 7.3491 loss: 3.5362 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2026 loss_aux: 1.3335 2023/02/17 15:04:34 - mmengine - INFO - Epoch(train) [41][ 80/1345] lr: 1.0000e-02 eta: 7:53:27 time: 0.1894 data_time: 0.0061 memory: 8327 grad_norm: 7.1912 loss: 3.3315 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9657 loss_aux: 1.3658 2023/02/17 15:04:38 - mmengine - INFO - Epoch(train) [41][ 100/1345] lr: 1.0000e-02 eta: 7:53:23 time: 0.1895 data_time: 0.0055 memory: 8327 grad_norm: 7.5207 loss: 3.7171 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3144 loss_aux: 1.4028 2023/02/17 15:04:42 - mmengine - INFO - Epoch(train) [41][ 120/1345] lr: 1.0000e-02 eta: 7:53:19 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 7.6016 loss: 3.6883 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2545 loss_aux: 1.4339 2023/02/17 15:04:45 - mmengine - INFO - Epoch(train) [41][ 140/1345] lr: 1.0000e-02 eta: 7:53:15 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.4288 loss: 3.8012 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3356 loss_aux: 1.4657 2023/02/17 15:04:49 - mmengine - INFO - Epoch(train) [41][ 160/1345] lr: 1.0000e-02 eta: 7:53:11 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.5298 loss: 3.5247 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1433 loss_aux: 1.3813 2023/02/17 15:04:53 - mmengine - INFO - Epoch(train) [41][ 180/1345] lr: 1.0000e-02 eta: 7:53:07 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.6050 loss: 3.4741 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0892 loss_aux: 1.3849 2023/02/17 15:04:57 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:04:57 - mmengine - INFO - Epoch(train) [41][ 200/1345] lr: 1.0000e-02 eta: 7:53:03 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.8332 loss: 3.7404 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3121 loss_aux: 1.4283 2023/02/17 15:05:00 - mmengine - INFO - Epoch(train) [41][ 220/1345] lr: 1.0000e-02 eta: 7:52:59 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.4955 loss: 3.6203 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2200 loss_aux: 1.4003 2023/02/17 15:05:04 - mmengine - INFO - Epoch(train) [41][ 240/1345] lr: 1.0000e-02 eta: 7:52:55 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.5540 loss: 3.4657 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0924 loss_aux: 1.3733 2023/02/17 15:05:08 - mmengine - INFO - Epoch(train) [41][ 260/1345] lr: 1.0000e-02 eta: 7:52:51 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.6330 loss: 3.3302 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0233 loss_aux: 1.3069 2023/02/17 15:05:12 - mmengine - INFO - Epoch(train) [41][ 280/1345] lr: 1.0000e-02 eta: 7:52:47 time: 0.1901 data_time: 0.0066 memory: 8327 grad_norm: 7.4970 loss: 3.5204 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1006 loss_aux: 1.4198 2023/02/17 15:05:16 - mmengine - INFO - Epoch(train) [41][ 300/1345] lr: 1.0000e-02 eta: 7:52:43 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.5582 loss: 3.5630 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1889 loss_aux: 1.3741 2023/02/17 15:05:19 - mmengine - INFO - Epoch(train) [41][ 320/1345] lr: 1.0000e-02 eta: 7:52:39 time: 0.1900 data_time: 0.0058 memory: 8327 grad_norm: 7.4397 loss: 3.3798 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.0375 loss_aux: 1.3423 2023/02/17 15:05:23 - mmengine - INFO - Epoch(train) [41][ 340/1345] lr: 1.0000e-02 eta: 7:52:35 time: 0.1892 data_time: 0.0060 memory: 8327 grad_norm: 7.3911 loss: 3.5664 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.1504 loss_aux: 1.4160 2023/02/17 15:05:27 - mmengine - INFO - Epoch(train) [41][ 360/1345] lr: 1.0000e-02 eta: 7:52:31 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.6808 loss: 3.6310 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2379 loss_aux: 1.3931 2023/02/17 15:05:31 - mmengine - INFO - Epoch(train) [41][ 380/1345] lr: 1.0000e-02 eta: 7:52:27 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.5807 loss: 4.0532 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5498 loss_aux: 1.5034 2023/02/17 15:05:35 - mmengine - INFO - Epoch(train) [41][ 400/1345] lr: 1.0000e-02 eta: 7:52:24 time: 0.1993 data_time: 0.0159 memory: 8327 grad_norm: 7.3440 loss: 3.3755 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0348 loss_aux: 1.3407 2023/02/17 15:05:39 - mmengine - INFO - Epoch(train) [41][ 420/1345] lr: 1.0000e-02 eta: 7:52:20 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.4959 loss: 3.6752 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2279 loss_aux: 1.4473 2023/02/17 15:05:42 - mmengine - INFO - Epoch(train) [41][ 440/1345] lr: 1.0000e-02 eta: 7:52:16 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.3865 loss: 3.1198 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8173 loss_aux: 1.3026 2023/02/17 15:05:46 - mmengine - INFO - Epoch(train) [41][ 460/1345] lr: 1.0000e-02 eta: 7:52:12 time: 0.1904 data_time: 0.0068 memory: 8327 grad_norm: 7.2252 loss: 3.0955 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8286 loss_aux: 1.2669 2023/02/17 15:05:50 - mmengine - INFO - Epoch(train) [41][ 480/1345] lr: 1.0000e-02 eta: 7:52:08 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.5297 loss: 3.6767 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2353 loss_aux: 1.4414 2023/02/17 15:05:54 - mmengine - INFO - Epoch(train) [41][ 500/1345] lr: 1.0000e-02 eta: 7:52:04 time: 0.1892 data_time: 0.0056 memory: 8327 grad_norm: 7.5601 loss: 3.5481 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1440 loss_aux: 1.4041 2023/02/17 15:05:58 - mmengine - INFO - Epoch(train) [41][ 520/1345] lr: 1.0000e-02 eta: 7:52:00 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.5851 loss: 3.3802 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0523 loss_aux: 1.3279 2023/02/17 15:06:01 - mmengine - INFO - Epoch(train) [41][ 540/1345] lr: 1.0000e-02 eta: 7:51:56 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.4865 loss: 3.7082 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2274 loss_aux: 1.4809 2023/02/17 15:06:05 - mmengine - INFO - Epoch(train) [41][ 560/1345] lr: 1.0000e-02 eta: 7:51:52 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.6089 loss: 3.7343 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3377 loss_aux: 1.3966 2023/02/17 15:06:09 - mmengine - INFO - Epoch(train) [41][ 580/1345] lr: 1.0000e-02 eta: 7:51:48 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.5519 loss: 3.3862 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0636 loss_aux: 1.3226 2023/02/17 15:06:13 - mmengine - INFO - Epoch(train) [41][ 600/1345] lr: 1.0000e-02 eta: 7:51:44 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.6807 loss: 3.7901 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3512 loss_aux: 1.4389 2023/02/17 15:06:17 - mmengine - INFO - Epoch(train) [41][ 620/1345] lr: 1.0000e-02 eta: 7:51:40 time: 0.1896 data_time: 0.0056 memory: 8327 grad_norm: 7.6510 loss: 3.2672 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9520 loss_aux: 1.3152 2023/02/17 15:06:20 - mmengine - INFO - Epoch(train) [41][ 640/1345] lr: 1.0000e-02 eta: 7:51:36 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.8145 loss: 3.7092 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2650 loss_aux: 1.4441 2023/02/17 15:06:24 - mmengine - INFO - Epoch(train) [41][ 660/1345] lr: 1.0000e-02 eta: 7:51:32 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.4619 loss: 3.2285 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9201 loss_aux: 1.3083 2023/02/17 15:06:28 - mmengine - INFO - Epoch(train) [41][ 680/1345] lr: 1.0000e-02 eta: 7:51:28 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.5778 loss: 3.6602 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.2314 loss_aux: 1.4288 2023/02/17 15:06:32 - mmengine - INFO - Epoch(train) [41][ 700/1345] lr: 1.0000e-02 eta: 7:51:24 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.5163 loss: 3.8084 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3948 loss_aux: 1.4136 2023/02/17 15:06:35 - mmengine - INFO - Epoch(train) [41][ 720/1345] lr: 1.0000e-02 eta: 7:51:20 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.4751 loss: 3.6899 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2925 loss_aux: 1.3973 2023/02/17 15:06:39 - mmengine - INFO - Epoch(train) [41][ 740/1345] lr: 1.0000e-02 eta: 7:51:16 time: 0.1899 data_time: 0.0060 memory: 8327 grad_norm: 7.8281 loss: 3.2862 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9514 loss_aux: 1.3348 2023/02/17 15:06:43 - mmengine - INFO - Epoch(train) [41][ 760/1345] lr: 1.0000e-02 eta: 7:51:12 time: 0.1899 data_time: 0.0066 memory: 8327 grad_norm: 7.6532 loss: 3.5227 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1422 loss_aux: 1.3806 2023/02/17 15:06:47 - mmengine - INFO - Epoch(train) [41][ 780/1345] lr: 1.0000e-02 eta: 7:51:08 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.4453 loss: 3.2253 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9405 loss_aux: 1.2849 2023/02/17 15:06:51 - mmengine - INFO - Epoch(train) [41][ 800/1345] lr: 1.0000e-02 eta: 7:51:04 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5327 loss: 3.7748 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3044 loss_aux: 1.4704 2023/02/17 15:06:54 - mmengine - INFO - Epoch(train) [41][ 820/1345] lr: 1.0000e-02 eta: 7:51:00 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.6181 loss: 3.8206 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3169 loss_aux: 1.5037 2023/02/17 15:06:58 - mmengine - INFO - Epoch(train) [41][ 840/1345] lr: 1.0000e-02 eta: 7:50:56 time: 0.1913 data_time: 0.0059 memory: 8327 grad_norm: 7.5989 loss: 3.2606 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.9460 loss_aux: 1.3146 2023/02/17 15:07:02 - mmengine - INFO - Epoch(train) [41][ 860/1345] lr: 1.0000e-02 eta: 7:50:52 time: 0.1907 data_time: 0.0060 memory: 8327 grad_norm: 7.9026 loss: 3.6750 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2940 loss_aux: 1.3810 2023/02/17 15:07:06 - mmengine - INFO - Epoch(train) [41][ 880/1345] lr: 1.0000e-02 eta: 7:50:48 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5958 loss: 3.3781 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0701 loss_aux: 1.3081 2023/02/17 15:07:10 - mmengine - INFO - Epoch(train) [41][ 900/1345] lr: 1.0000e-02 eta: 7:50:44 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.7467 loss: 4.1301 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.5679 loss_aux: 1.5622 2023/02/17 15:07:13 - mmengine - INFO - Epoch(train) [41][ 920/1345] lr: 1.0000e-02 eta: 7:50:40 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.5869 loss: 3.7461 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3217 loss_aux: 1.4244 2023/02/17 15:07:17 - mmengine - INFO - Epoch(train) [41][ 940/1345] lr: 1.0000e-02 eta: 7:50:36 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.4726 loss: 3.2975 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9875 loss_aux: 1.3101 2023/02/17 15:07:21 - mmengine - INFO - Epoch(train) [41][ 960/1345] lr: 1.0000e-02 eta: 7:50:32 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.4841 loss: 3.3331 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.0321 loss_aux: 1.3010 2023/02/17 15:07:25 - mmengine - INFO - Epoch(train) [41][ 980/1345] lr: 1.0000e-02 eta: 7:50:28 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.4364 loss: 3.2948 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9963 loss_aux: 1.2985 2023/02/17 15:07:29 - mmengine - INFO - Epoch(train) [41][1000/1345] lr: 1.0000e-02 eta: 7:50:24 time: 0.1900 data_time: 0.0065 memory: 8327 grad_norm: 7.7574 loss: 3.3136 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9953 loss_aux: 1.3183 2023/02/17 15:07:32 - mmengine - INFO - Epoch(train) [41][1020/1345] lr: 1.0000e-02 eta: 7:50:20 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.5190 loss: 3.8261 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3778 loss_aux: 1.4483 2023/02/17 15:07:36 - mmengine - INFO - Epoch(train) [41][1040/1345] lr: 1.0000e-02 eta: 7:50:16 time: 0.1892 data_time: 0.0060 memory: 8327 grad_norm: 7.4737 loss: 3.3784 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0643 loss_aux: 1.3141 2023/02/17 15:07:40 - mmengine - INFO - Epoch(train) [41][1060/1345] lr: 1.0000e-02 eta: 7:50:12 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.6048 loss: 3.6544 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2413 loss_aux: 1.4131 2023/02/17 15:07:44 - mmengine - INFO - Epoch(train) [41][1080/1345] lr: 1.0000e-02 eta: 7:50:08 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.5180 loss: 3.5046 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1309 loss_aux: 1.3737 2023/02/17 15:07:48 - mmengine - INFO - Epoch(train) [41][1100/1345] lr: 1.0000e-02 eta: 7:50:04 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.5512 loss: 3.4879 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1461 loss_aux: 1.3417 2023/02/17 15:07:51 - mmengine - INFO - Epoch(train) [41][1120/1345] lr: 1.0000e-02 eta: 7:50:01 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.8367 loss: 3.6107 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2284 loss_aux: 1.3822 2023/02/17 15:07:55 - mmengine - INFO - Epoch(train) [41][1140/1345] lr: 1.0000e-02 eta: 7:49:57 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.7474 loss: 3.7199 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2760 loss_aux: 1.4439 2023/02/17 15:07:59 - mmengine - INFO - Epoch(train) [41][1160/1345] lr: 1.0000e-02 eta: 7:49:53 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.6211 loss: 3.6620 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2396 loss_aux: 1.4224 2023/02/17 15:08:03 - mmengine - INFO - Epoch(train) [41][1180/1345] lr: 1.0000e-02 eta: 7:49:49 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.8953 loss: 3.7342 top1_acc: 0.1250 top5_acc: 0.8750 loss_cls: 2.2919 loss_aux: 1.4423 2023/02/17 15:08:07 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:08:07 - mmengine - INFO - Epoch(train) [41][1200/1345] lr: 1.0000e-02 eta: 7:49:45 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.8209 loss: 3.8813 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3737 loss_aux: 1.5075 2023/02/17 15:08:10 - mmengine - INFO - Epoch(train) [41][1220/1345] lr: 1.0000e-02 eta: 7:49:41 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.7162 loss: 3.7358 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2981 loss_aux: 1.4377 2023/02/17 15:08:14 - mmengine - INFO - Epoch(train) [41][1240/1345] lr: 1.0000e-02 eta: 7:49:37 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.6173 loss: 3.3305 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9969 loss_aux: 1.3336 2023/02/17 15:08:18 - mmengine - INFO - Epoch(train) [41][1260/1345] lr: 1.0000e-02 eta: 7:49:33 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.4428 loss: 3.7295 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3003 loss_aux: 1.4292 2023/02/17 15:08:22 - mmengine - INFO - Epoch(train) [41][1280/1345] lr: 1.0000e-02 eta: 7:49:29 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.4449 loss: 3.6942 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2161 loss_aux: 1.4781 2023/02/17 15:08:26 - mmengine - INFO - Epoch(train) [41][1300/1345] lr: 1.0000e-02 eta: 7:49:25 time: 0.1903 data_time: 0.0069 memory: 8327 grad_norm: 7.6781 loss: 3.7556 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.3323 loss_aux: 1.4232 2023/02/17 15:08:29 - mmengine - INFO - Epoch(train) [41][1320/1345] lr: 1.0000e-02 eta: 7:49:21 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.4151 loss: 3.7111 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2792 loss_aux: 1.4318 2023/02/17 15:08:33 - mmengine - INFO - Epoch(train) [41][1340/1345] lr: 1.0000e-02 eta: 7:49:17 time: 0.1903 data_time: 0.0059 memory: 8327 grad_norm: 7.6890 loss: 3.6719 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2178 loss_aux: 1.4542 2023/02/17 15:08:34 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:08:34 - mmengine - INFO - Epoch(train) [41][1345/1345] lr: 1.0000e-02 eta: 7:49:15 time: 0.1846 data_time: 0.0059 memory: 8327 grad_norm: 7.6317 loss: 3.8651 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.3636 loss_aux: 1.5015 2023/02/17 15:08:34 - mmengine - INFO - Saving checkpoint at 41 epochs 2023/02/17 15:08:41 - mmengine - INFO - Epoch(train) [42][ 20/1345] lr: 1.0000e-02 eta: 7:49:12 time: 0.2055 data_time: 0.0144 memory: 8327 grad_norm: 7.5603 loss: 3.6779 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3004 loss_aux: 1.3775 2023/02/17 15:08:44 - mmengine - INFO - Epoch(train) [42][ 40/1345] lr: 1.0000e-02 eta: 7:49:08 time: 0.1921 data_time: 0.0052 memory: 8327 grad_norm: 7.6925 loss: 3.1941 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8824 loss_aux: 1.3117 2023/02/17 15:08:48 - mmengine - INFO - Epoch(train) [42][ 60/1345] lr: 1.0000e-02 eta: 7:49:04 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.5932 loss: 3.5988 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2043 loss_aux: 1.3946 2023/02/17 15:08:52 - mmengine - INFO - Epoch(train) [42][ 80/1345] lr: 1.0000e-02 eta: 7:49:00 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.4719 loss: 3.7614 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2674 loss_aux: 1.4940 2023/02/17 15:08:56 - mmengine - INFO - Epoch(train) [42][ 100/1345] lr: 1.0000e-02 eta: 7:48:56 time: 0.1890 data_time: 0.0057 memory: 8327 grad_norm: 7.5362 loss: 3.1431 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8685 loss_aux: 1.2746 2023/02/17 15:09:00 - mmengine - INFO - Epoch(train) [42][ 120/1345] lr: 1.0000e-02 eta: 7:48:53 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.5321 loss: 3.4556 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0693 loss_aux: 1.3862 2023/02/17 15:09:04 - mmengine - INFO - Epoch(train) [42][ 140/1345] lr: 1.0000e-02 eta: 7:48:50 time: 0.2094 data_time: 0.0259 memory: 8327 grad_norm: 7.5222 loss: 3.5202 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1166 loss_aux: 1.4036 2023/02/17 15:09:08 - mmengine - INFO - Epoch(train) [42][ 160/1345] lr: 1.0000e-02 eta: 7:48:46 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.2912 loss: 2.9290 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7278 loss_aux: 1.2013 2023/02/17 15:09:11 - mmengine - INFO - Epoch(train) [42][ 180/1345] lr: 1.0000e-02 eta: 7:48:42 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.3257 loss: 3.2563 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9520 loss_aux: 1.3043 2023/02/17 15:09:15 - mmengine - INFO - Epoch(train) [42][ 200/1345] lr: 1.0000e-02 eta: 7:48:38 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 7.7200 loss: 3.2262 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9144 loss_aux: 1.3118 2023/02/17 15:09:19 - mmengine - INFO - Epoch(train) [42][ 220/1345] lr: 1.0000e-02 eta: 7:48:34 time: 0.1894 data_time: 0.0062 memory: 8327 grad_norm: 7.7021 loss: 3.1065 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8536 loss_aux: 1.2530 2023/02/17 15:09:23 - mmengine - INFO - Epoch(train) [42][ 240/1345] lr: 1.0000e-02 eta: 7:48:30 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.8114 loss: 3.7018 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2823 loss_aux: 1.4195 2023/02/17 15:09:27 - mmengine - INFO - Epoch(train) [42][ 260/1345] lr: 1.0000e-02 eta: 7:48:26 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.5724 loss: 3.5434 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1658 loss_aux: 1.3776 2023/02/17 15:09:30 - mmengine - INFO - Epoch(train) [42][ 280/1345] lr: 1.0000e-02 eta: 7:48:22 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.7630 loss: 3.3957 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1002 loss_aux: 1.2956 2023/02/17 15:09:34 - mmengine - INFO - Epoch(train) [42][ 300/1345] lr: 1.0000e-02 eta: 7:48:18 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.3665 loss: 3.3647 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0223 loss_aux: 1.3423 2023/02/17 15:09:38 - mmengine - INFO - Epoch(train) [42][ 320/1345] lr: 1.0000e-02 eta: 7:48:14 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.7185 loss: 3.6531 top1_acc: 0.1250 top5_acc: 1.0000 loss_cls: 2.2807 loss_aux: 1.3724 2023/02/17 15:09:42 - mmengine - INFO - Epoch(train) [42][ 340/1345] lr: 1.0000e-02 eta: 7:48:10 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.5693 loss: 3.4636 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0953 loss_aux: 1.3682 2023/02/17 15:09:45 - mmengine - INFO - Epoch(train) [42][ 360/1345] lr: 1.0000e-02 eta: 7:48:06 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.6665 loss: 3.8362 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3390 loss_aux: 1.4972 2023/02/17 15:09:49 - mmengine - INFO - Epoch(train) [42][ 380/1345] lr: 1.0000e-02 eta: 7:48:02 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.7224 loss: 3.5206 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1261 loss_aux: 1.3945 2023/02/17 15:09:53 - mmengine - INFO - Epoch(train) [42][ 400/1345] lr: 1.0000e-02 eta: 7:47:58 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.9453 loss: 3.6350 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1944 loss_aux: 1.4406 2023/02/17 15:09:57 - mmengine - INFO - Epoch(train) [42][ 420/1345] lr: 1.0000e-02 eta: 7:47:54 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.6930 loss: 3.4820 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1103 loss_aux: 1.3717 2023/02/17 15:10:01 - mmengine - INFO - Epoch(train) [42][ 440/1345] lr: 1.0000e-02 eta: 7:47:50 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.7021 loss: 3.6860 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2700 loss_aux: 1.4160 2023/02/17 15:10:04 - mmengine - INFO - Epoch(train) [42][ 460/1345] lr: 1.0000e-02 eta: 7:47:46 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7223 loss: 3.6229 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2201 loss_aux: 1.4029 2023/02/17 15:10:08 - mmengine - INFO - Epoch(train) [42][ 480/1345] lr: 1.0000e-02 eta: 7:47:42 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.6849 loss: 3.7366 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2918 loss_aux: 1.4448 2023/02/17 15:10:12 - mmengine - INFO - Epoch(train) [42][ 500/1345] lr: 1.0000e-02 eta: 7:47:38 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.7816 loss: 3.6793 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2780 loss_aux: 1.4014 2023/02/17 15:10:16 - mmengine - INFO - Epoch(train) [42][ 520/1345] lr: 1.0000e-02 eta: 7:47:34 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.6591 loss: 3.4221 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1077 loss_aux: 1.3144 2023/02/17 15:10:20 - mmengine - INFO - Epoch(train) [42][ 540/1345] lr: 1.0000e-02 eta: 7:47:30 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.7018 loss: 3.5955 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2152 loss_aux: 1.3803 2023/02/17 15:10:23 - mmengine - INFO - Epoch(train) [42][ 560/1345] lr: 1.0000e-02 eta: 7:47:26 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.3835 loss: 3.2978 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9658 loss_aux: 1.3320 2023/02/17 15:10:27 - mmengine - INFO - Epoch(train) [42][ 580/1345] lr: 1.0000e-02 eta: 7:47:22 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.5464 loss: 3.6190 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2472 loss_aux: 1.3719 2023/02/17 15:10:31 - mmengine - INFO - Epoch(train) [42][ 600/1345] lr: 1.0000e-02 eta: 7:47:18 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.6755 loss: 3.6048 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2084 loss_aux: 1.3965 2023/02/17 15:10:35 - mmengine - INFO - Epoch(train) [42][ 620/1345] lr: 1.0000e-02 eta: 7:47:14 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.6600 loss: 3.5283 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1805 loss_aux: 1.3478 2023/02/17 15:10:39 - mmengine - INFO - Epoch(train) [42][ 640/1345] lr: 1.0000e-02 eta: 7:47:10 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.5899 loss: 3.4610 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1011 loss_aux: 1.3598 2023/02/17 15:10:42 - mmengine - INFO - Epoch(train) [42][ 660/1345] lr: 1.0000e-02 eta: 7:47:06 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.5492 loss: 3.6769 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2423 loss_aux: 1.4345 2023/02/17 15:10:46 - mmengine - INFO - Epoch(train) [42][ 680/1345] lr: 1.0000e-02 eta: 7:47:02 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.7566 loss: 3.5281 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1580 loss_aux: 1.3701 2023/02/17 15:10:50 - mmengine - INFO - Epoch(train) [42][ 700/1345] lr: 1.0000e-02 eta: 7:46:58 time: 0.1899 data_time: 0.0066 memory: 8327 grad_norm: 7.6929 loss: 3.4976 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1698 loss_aux: 1.3278 2023/02/17 15:10:54 - mmengine - INFO - Epoch(train) [42][ 720/1345] lr: 1.0000e-02 eta: 7:46:54 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5483 loss: 3.7820 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3618 loss_aux: 1.4203 2023/02/17 15:10:58 - mmengine - INFO - Epoch(train) [42][ 740/1345] lr: 1.0000e-02 eta: 7:46:50 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.5590 loss: 3.7260 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3170 loss_aux: 1.4090 2023/02/17 15:11:01 - mmengine - INFO - Epoch(train) [42][ 760/1345] lr: 1.0000e-02 eta: 7:46:46 time: 0.1898 data_time: 0.0064 memory: 8327 grad_norm: 7.7465 loss: 3.4700 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1031 loss_aux: 1.3669 2023/02/17 15:11:05 - mmengine - INFO - Epoch(train) [42][ 780/1345] lr: 1.0000e-02 eta: 7:46:42 time: 0.1894 data_time: 0.0061 memory: 8327 grad_norm: 7.8023 loss: 3.9130 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4583 loss_aux: 1.4547 2023/02/17 15:11:09 - mmengine - INFO - Epoch(train) [42][ 800/1345] lr: 1.0000e-02 eta: 7:46:38 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.7731 loss: 3.8177 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3578 loss_aux: 1.4599 2023/02/17 15:11:13 - mmengine - INFO - Epoch(train) [42][ 820/1345] lr: 1.0000e-02 eta: 7:46:34 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.5487 loss: 3.1129 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8445 loss_aux: 1.2684 2023/02/17 15:11:17 - mmengine - INFO - Epoch(train) [42][ 840/1345] lr: 1.0000e-02 eta: 7:46:30 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.5599 loss: 3.6038 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1514 loss_aux: 1.4525 2023/02/17 15:11:19 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:11:20 - mmengine - INFO - Epoch(train) [42][ 860/1345] lr: 1.0000e-02 eta: 7:46:26 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.6128 loss: 3.8483 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3360 loss_aux: 1.5123 2023/02/17 15:11:24 - mmengine - INFO - Epoch(train) [42][ 880/1345] lr: 1.0000e-02 eta: 7:46:23 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.6374 loss: 3.6740 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2905 loss_aux: 1.3835 2023/02/17 15:11:28 - mmengine - INFO - Epoch(train) [42][ 900/1345] lr: 1.0000e-02 eta: 7:46:19 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.4945 loss: 3.6826 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2575 loss_aux: 1.4251 2023/02/17 15:11:32 - mmengine - INFO - Epoch(train) [42][ 920/1345] lr: 1.0000e-02 eta: 7:46:15 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.7572 loss: 3.6475 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2754 loss_aux: 1.3721 2023/02/17 15:11:36 - mmengine - INFO - Epoch(train) [42][ 940/1345] lr: 1.0000e-02 eta: 7:46:11 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.4848 loss: 3.5749 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1898 loss_aux: 1.3851 2023/02/17 15:11:39 - mmengine - INFO - Epoch(train) [42][ 960/1345] lr: 1.0000e-02 eta: 7:46:07 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.5276 loss: 3.5040 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1741 loss_aux: 1.3299 2023/02/17 15:11:43 - mmengine - INFO - Epoch(train) [42][ 980/1345] lr: 1.0000e-02 eta: 7:46:03 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.5801 loss: 3.4993 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1192 loss_aux: 1.3801 2023/02/17 15:11:47 - mmengine - INFO - Epoch(train) [42][1000/1345] lr: 1.0000e-02 eta: 7:45:59 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7101 loss: 3.7655 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3784 loss_aux: 1.3871 2023/02/17 15:11:51 - mmengine - INFO - Epoch(train) [42][1020/1345] lr: 1.0000e-02 eta: 7:45:55 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.5420 loss: 3.8147 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3802 loss_aux: 1.4345 2023/02/17 15:11:54 - mmengine - INFO - Epoch(train) [42][1040/1345] lr: 1.0000e-02 eta: 7:45:51 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.1302 loss: 3.2713 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9687 loss_aux: 1.3026 2023/02/17 15:11:58 - mmengine - INFO - Epoch(train) [42][1060/1345] lr: 1.0000e-02 eta: 7:45:47 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.5485 loss: 3.7154 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2988 loss_aux: 1.4166 2023/02/17 15:12:02 - mmengine - INFO - Epoch(train) [42][1080/1345] lr: 1.0000e-02 eta: 7:45:43 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.4690 loss: 3.9132 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3843 loss_aux: 1.5289 2023/02/17 15:12:06 - mmengine - INFO - Epoch(train) [42][1100/1345] lr: 1.0000e-02 eta: 7:45:39 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.4723 loss: 3.9168 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4039 loss_aux: 1.5129 2023/02/17 15:12:10 - mmengine - INFO - Epoch(train) [42][1120/1345] lr: 1.0000e-02 eta: 7:45:35 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.6675 loss: 3.9173 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4721 loss_aux: 1.4452 2023/02/17 15:12:13 - mmengine - INFO - Epoch(train) [42][1140/1345] lr: 1.0000e-02 eta: 7:45:31 time: 0.1902 data_time: 0.0058 memory: 8327 grad_norm: 7.5745 loss: 3.6575 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.2433 loss_aux: 1.4141 2023/02/17 15:12:17 - mmengine - INFO - Epoch(train) [42][1160/1345] lr: 1.0000e-02 eta: 7:45:27 time: 0.1909 data_time: 0.0057 memory: 8327 grad_norm: 7.3856 loss: 3.5030 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1401 loss_aux: 1.3629 2023/02/17 15:12:21 - mmengine - INFO - Epoch(train) [42][1180/1345] lr: 1.0000e-02 eta: 7:45:23 time: 0.1903 data_time: 0.0063 memory: 8327 grad_norm: 7.6264 loss: 3.6008 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2233 loss_aux: 1.3774 2023/02/17 15:12:25 - mmengine - INFO - Epoch(train) [42][1200/1345] lr: 1.0000e-02 eta: 7:45:19 time: 0.1894 data_time: 0.0053 memory: 8327 grad_norm: 7.4710 loss: 3.0671 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8515 loss_aux: 1.2157 2023/02/17 15:12:29 - mmengine - INFO - Epoch(train) [42][1220/1345] lr: 1.0000e-02 eta: 7:45:15 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.6491 loss: 3.3830 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0432 loss_aux: 1.3397 2023/02/17 15:12:32 - mmengine - INFO - Epoch(train) [42][1240/1345] lr: 1.0000e-02 eta: 7:45:11 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.4923 loss: 3.3896 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0953 loss_aux: 1.2943 2023/02/17 15:12:36 - mmengine - INFO - Epoch(train) [42][1260/1345] lr: 1.0000e-02 eta: 7:45:07 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5335 loss: 3.2511 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9683 loss_aux: 1.2828 2023/02/17 15:12:40 - mmengine - INFO - Epoch(train) [42][1280/1345] lr: 1.0000e-02 eta: 7:45:03 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.5215 loss: 3.4614 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1369 loss_aux: 1.3245 2023/02/17 15:12:44 - mmengine - INFO - Epoch(train) [42][1300/1345] lr: 1.0000e-02 eta: 7:44:59 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5779 loss: 3.9249 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4509 loss_aux: 1.4739 2023/02/17 15:12:48 - mmengine - INFO - Epoch(train) [42][1320/1345] lr: 1.0000e-02 eta: 7:44:55 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.6195 loss: 3.6263 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2058 loss_aux: 1.4205 2023/02/17 15:12:51 - mmengine - INFO - Epoch(train) [42][1340/1345] lr: 1.0000e-02 eta: 7:44:51 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.5501 loss: 3.1764 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9170 loss_aux: 1.2594 2023/02/17 15:12:52 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:12:52 - mmengine - INFO - Epoch(train) [42][1345/1345] lr: 1.0000e-02 eta: 7:44:50 time: 0.1834 data_time: 0.0061 memory: 8327 grad_norm: 7.5766 loss: 3.4714 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.1510 loss_aux: 1.3204 2023/02/17 15:12:52 - mmengine - INFO - Saving checkpoint at 42 epochs 2023/02/17 15:12:59 - mmengine - INFO - Epoch(train) [43][ 20/1345] lr: 1.0000e-02 eta: 7:44:47 time: 0.2063 data_time: 0.0160 memory: 8327 grad_norm: 7.7077 loss: 4.0113 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4992 loss_aux: 1.5121 2023/02/17 15:13:03 - mmengine - INFO - Epoch(train) [43][ 40/1345] lr: 1.0000e-02 eta: 7:44:43 time: 0.1903 data_time: 0.0040 memory: 8327 grad_norm: 7.5984 loss: 3.5098 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1163 loss_aux: 1.3935 2023/02/17 15:13:07 - mmengine - INFO - Epoch(train) [43][ 60/1345] lr: 1.0000e-02 eta: 7:44:39 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.5264 loss: 3.5481 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1451 loss_aux: 1.4030 2023/02/17 15:13:10 - mmengine - INFO - Epoch(train) [43][ 80/1345] lr: 1.0000e-02 eta: 7:44:35 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.4426 loss: 3.5337 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1935 loss_aux: 1.3402 2023/02/17 15:13:14 - mmengine - INFO - Epoch(train) [43][ 100/1345] lr: 1.0000e-02 eta: 7:44:31 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.6542 loss: 3.6691 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2371 loss_aux: 1.4320 2023/02/17 15:13:18 - mmengine - INFO - Epoch(train) [43][ 120/1345] lr: 1.0000e-02 eta: 7:44:27 time: 0.1891 data_time: 0.0060 memory: 8327 grad_norm: 7.5193 loss: 3.5298 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1172 loss_aux: 1.4126 2023/02/17 15:13:22 - mmengine - INFO - Epoch(train) [43][ 140/1345] lr: 1.0000e-02 eta: 7:44:23 time: 0.1893 data_time: 0.0061 memory: 8327 grad_norm: 7.3702 loss: 3.2933 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9796 loss_aux: 1.3137 2023/02/17 15:13:26 - mmengine - INFO - Epoch(train) [43][ 160/1345] lr: 1.0000e-02 eta: 7:44:19 time: 0.1893 data_time: 0.0061 memory: 8327 grad_norm: 7.5782 loss: 3.5807 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.1783 loss_aux: 1.4024 2023/02/17 15:13:29 - mmengine - INFO - Epoch(train) [43][ 180/1345] lr: 1.0000e-02 eta: 7:44:15 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.4449 loss: 3.5318 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1702 loss_aux: 1.3616 2023/02/17 15:13:33 - mmengine - INFO - Epoch(train) [43][ 200/1345] lr: 1.0000e-02 eta: 7:44:11 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.6184 loss: 3.3093 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0251 loss_aux: 1.2842 2023/02/17 15:13:37 - mmengine - INFO - Epoch(train) [43][ 220/1345] lr: 1.0000e-02 eta: 7:44:07 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.4886 loss: 3.5090 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1000 loss_aux: 1.4091 2023/02/17 15:13:41 - mmengine - INFO - Epoch(train) [43][ 240/1345] lr: 1.0000e-02 eta: 7:44:03 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.3905 loss: 3.2756 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9437 loss_aux: 1.3319 2023/02/17 15:13:44 - mmengine - INFO - Epoch(train) [43][ 260/1345] lr: 1.0000e-02 eta: 7:43:59 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.6870 loss: 3.6480 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2272 loss_aux: 1.4208 2023/02/17 15:13:48 - mmengine - INFO - Epoch(train) [43][ 280/1345] lr: 1.0000e-02 eta: 7:43:55 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.5860 loss: 3.0824 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8757 loss_aux: 1.2066 2023/02/17 15:13:52 - mmengine - INFO - Epoch(train) [43][ 300/1345] lr: 1.0000e-02 eta: 7:43:51 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.7762 loss: 3.8782 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4298 loss_aux: 1.4483 2023/02/17 15:13:56 - mmengine - INFO - Epoch(train) [43][ 320/1345] lr: 1.0000e-02 eta: 7:43:47 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.4969 loss: 3.5559 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1206 loss_aux: 1.4352 2023/02/17 15:14:00 - mmengine - INFO - Epoch(train) [43][ 340/1345] lr: 1.0000e-02 eta: 7:43:43 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.3374 loss: 3.1637 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8921 loss_aux: 1.2716 2023/02/17 15:14:03 - mmengine - INFO - Epoch(train) [43][ 360/1345] lr: 1.0000e-02 eta: 7:43:39 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.7972 loss: 3.5003 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0541 loss_aux: 1.4462 2023/02/17 15:14:07 - mmengine - INFO - Epoch(train) [43][ 380/1345] lr: 1.0000e-02 eta: 7:43:35 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.4623 loss: 3.7675 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2748 loss_aux: 1.4927 2023/02/17 15:14:11 - mmengine - INFO - Epoch(train) [43][ 400/1345] lr: 1.0000e-02 eta: 7:43:31 time: 0.1899 data_time: 0.0058 memory: 8327 grad_norm: 7.4339 loss: 2.9036 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 1.6696 loss_aux: 1.2340 2023/02/17 15:14:15 - mmengine - INFO - Epoch(train) [43][ 420/1345] lr: 1.0000e-02 eta: 7:43:27 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.6544 loss: 3.4224 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0566 loss_aux: 1.3658 2023/02/17 15:14:19 - mmengine - INFO - Epoch(train) [43][ 440/1345] lr: 1.0000e-02 eta: 7:43:23 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.6864 loss: 3.6497 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1975 loss_aux: 1.4522 2023/02/17 15:14:22 - mmengine - INFO - Epoch(train) [43][ 460/1345] lr: 1.0000e-02 eta: 7:43:19 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.8156 loss: 3.9107 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4133 loss_aux: 1.4974 2023/02/17 15:14:26 - mmengine - INFO - Epoch(train) [43][ 480/1345] lr: 1.0000e-02 eta: 7:43:15 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.8195 loss: 3.5443 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1506 loss_aux: 1.3937 2023/02/17 15:14:30 - mmengine - INFO - Epoch(train) [43][ 500/1345] lr: 1.0000e-02 eta: 7:43:12 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.6999 loss: 3.3864 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0479 loss_aux: 1.3385 2023/02/17 15:14:32 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:14:34 - mmengine - INFO - Epoch(train) [43][ 520/1345] lr: 1.0000e-02 eta: 7:43:08 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.6088 loss: 3.8257 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4305 loss_aux: 1.3951 2023/02/17 15:14:38 - mmengine - INFO - Epoch(train) [43][ 540/1345] lr: 1.0000e-02 eta: 7:43:04 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.6397 loss: 3.6736 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2997 loss_aux: 1.3739 2023/02/17 15:14:41 - mmengine - INFO - Epoch(train) [43][ 560/1345] lr: 1.0000e-02 eta: 7:43:00 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.4916 loss: 3.6791 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2937 loss_aux: 1.3854 2023/02/17 15:14:45 - mmengine - INFO - Epoch(train) [43][ 580/1345] lr: 1.0000e-02 eta: 7:42:56 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.6820 loss: 3.4985 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.1124 loss_aux: 1.3861 2023/02/17 15:14:49 - mmengine - INFO - Epoch(train) [43][ 600/1345] lr: 1.0000e-02 eta: 7:42:52 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.6262 loss: 3.4616 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1217 loss_aux: 1.3398 2023/02/17 15:14:53 - mmengine - INFO - Epoch(train) [43][ 620/1345] lr: 1.0000e-02 eta: 7:42:48 time: 0.1897 data_time: 0.0057 memory: 8327 grad_norm: 7.4255 loss: 3.3926 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0761 loss_aux: 1.3165 2023/02/17 15:14:56 - mmengine - INFO - Epoch(train) [43][ 640/1345] lr: 1.0000e-02 eta: 7:42:44 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.3914 loss: 3.0710 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8397 loss_aux: 1.2313 2023/02/17 15:15:00 - mmengine - INFO - Epoch(train) [43][ 660/1345] lr: 1.0000e-02 eta: 7:42:40 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.6033 loss: 3.5192 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.1125 loss_aux: 1.4067 2023/02/17 15:15:04 - mmengine - INFO - Epoch(train) [43][ 680/1345] lr: 1.0000e-02 eta: 7:42:36 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.4327 loss: 3.3517 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0081 loss_aux: 1.3435 2023/02/17 15:15:08 - mmengine - INFO - Epoch(train) [43][ 700/1345] lr: 1.0000e-02 eta: 7:42:32 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.6116 loss: 3.6859 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1963 loss_aux: 1.4896 2023/02/17 15:15:12 - mmengine - INFO - Epoch(train) [43][ 720/1345] lr: 1.0000e-02 eta: 7:42:28 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.5124 loss: 3.3534 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0513 loss_aux: 1.3021 2023/02/17 15:15:15 - mmengine - INFO - Epoch(train) [43][ 740/1345] lr: 1.0000e-02 eta: 7:42:24 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.7668 loss: 3.4339 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1139 loss_aux: 1.3200 2023/02/17 15:15:19 - mmengine - INFO - Epoch(train) [43][ 760/1345] lr: 1.0000e-02 eta: 7:42:20 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.5961 loss: 4.0670 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5045 loss_aux: 1.5626 2023/02/17 15:15:23 - mmengine - INFO - Epoch(train) [43][ 780/1345] lr: 1.0000e-02 eta: 7:42:16 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.5171 loss: 3.4584 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0857 loss_aux: 1.3727 2023/02/17 15:15:27 - mmengine - INFO - Epoch(train) [43][ 800/1345] lr: 1.0000e-02 eta: 7:42:12 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.7329 loss: 3.5241 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1587 loss_aux: 1.3654 2023/02/17 15:15:31 - mmengine - INFO - Epoch(train) [43][ 820/1345] lr: 1.0000e-02 eta: 7:42:08 time: 0.1905 data_time: 0.0071 memory: 8327 grad_norm: 7.5969 loss: 3.3300 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0251 loss_aux: 1.3048 2023/02/17 15:15:34 - mmengine - INFO - Epoch(train) [43][ 840/1345] lr: 1.0000e-02 eta: 7:42:04 time: 0.1890 data_time: 0.0058 memory: 8327 grad_norm: 7.4236 loss: 3.2371 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9464 loss_aux: 1.2907 2023/02/17 15:15:38 - mmengine - INFO - Epoch(train) [43][ 860/1345] lr: 1.0000e-02 eta: 7:42:00 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.5924 loss: 3.8103 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3558 loss_aux: 1.4545 2023/02/17 15:15:42 - mmengine - INFO - Epoch(train) [43][ 880/1345] lr: 1.0000e-02 eta: 7:41:56 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.4479 loss: 3.5024 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1336 loss_aux: 1.3688 2023/02/17 15:15:46 - mmengine - INFO - Epoch(train) [43][ 900/1345] lr: 1.0000e-02 eta: 7:41:52 time: 0.1896 data_time: 0.0061 memory: 8327 grad_norm: 7.7274 loss: 3.3500 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0118 loss_aux: 1.3382 2023/02/17 15:15:50 - mmengine - INFO - Epoch(train) [43][ 920/1345] lr: 1.0000e-02 eta: 7:41:48 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.8018 loss: 4.0414 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4591 loss_aux: 1.5823 2023/02/17 15:15:53 - mmengine - INFO - Epoch(train) [43][ 940/1345] lr: 1.0000e-02 eta: 7:41:44 time: 0.1899 data_time: 0.0057 memory: 8327 grad_norm: 7.5918 loss: 3.6473 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2498 loss_aux: 1.3975 2023/02/17 15:15:57 - mmengine - INFO - Epoch(train) [43][ 960/1345] lr: 1.0000e-02 eta: 7:41:40 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.4372 loss: 3.4110 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0770 loss_aux: 1.3340 2023/02/17 15:16:01 - mmengine - INFO - Epoch(train) [43][ 980/1345] lr: 1.0000e-02 eta: 7:41:36 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.7606 loss: 3.3791 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0356 loss_aux: 1.3434 2023/02/17 15:16:05 - mmengine - INFO - Epoch(train) [43][1000/1345] lr: 1.0000e-02 eta: 7:41:32 time: 0.1908 data_time: 0.0073 memory: 8327 grad_norm: 7.7877 loss: 3.7557 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3380 loss_aux: 1.4177 2023/02/17 15:16:09 - mmengine - INFO - Epoch(train) [43][1020/1345] lr: 1.0000e-02 eta: 7:41:28 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.6191 loss: 3.6777 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2543 loss_aux: 1.4234 2023/02/17 15:16:12 - mmengine - INFO - Epoch(train) [43][1040/1345] lr: 1.0000e-02 eta: 7:41:24 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.5304 loss: 3.5773 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1889 loss_aux: 1.3884 2023/02/17 15:16:16 - mmengine - INFO - Epoch(train) [43][1060/1345] lr: 1.0000e-02 eta: 7:41:20 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.5848 loss: 3.4432 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.0692 loss_aux: 1.3740 2023/02/17 15:16:20 - mmengine - INFO - Epoch(train) [43][1080/1345] lr: 1.0000e-02 eta: 7:41:16 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.5338 loss: 3.4780 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0941 loss_aux: 1.3839 2023/02/17 15:16:24 - mmengine - INFO - Epoch(train) [43][1100/1345] lr: 1.0000e-02 eta: 7:41:12 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.7020 loss: 3.5276 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1510 loss_aux: 1.3766 2023/02/17 15:16:27 - mmengine - INFO - Epoch(train) [43][1120/1345] lr: 1.0000e-02 eta: 7:41:08 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.6107 loss: 3.8085 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3228 loss_aux: 1.4856 2023/02/17 15:16:31 - mmengine - INFO - Epoch(train) [43][1140/1345] lr: 1.0000e-02 eta: 7:41:04 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.7744 loss: 3.3439 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0108 loss_aux: 1.3331 2023/02/17 15:16:35 - mmengine - INFO - Epoch(train) [43][1160/1345] lr: 1.0000e-02 eta: 7:41:00 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.6076 loss: 3.7542 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3235 loss_aux: 1.4307 2023/02/17 15:16:39 - mmengine - INFO - Epoch(train) [43][1180/1345] lr: 1.0000e-02 eta: 7:40:56 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.5195 loss: 3.9304 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4222 loss_aux: 1.5081 2023/02/17 15:16:43 - mmengine - INFO - Epoch(train) [43][1200/1345] lr: 1.0000e-02 eta: 7:40:52 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.4705 loss: 3.4996 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1401 loss_aux: 1.3595 2023/02/17 15:16:46 - mmengine - INFO - Epoch(train) [43][1220/1345] lr: 1.0000e-02 eta: 7:40:49 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5713 loss: 3.5846 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1995 loss_aux: 1.3852 2023/02/17 15:16:50 - mmengine - INFO - Epoch(train) [43][1240/1345] lr: 1.0000e-02 eta: 7:40:45 time: 0.1901 data_time: 0.0057 memory: 8327 grad_norm: 7.6809 loss: 3.6659 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2640 loss_aux: 1.4019 2023/02/17 15:16:54 - mmengine - INFO - Epoch(train) [43][1260/1345] lr: 1.0000e-02 eta: 7:40:41 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.6418 loss: 3.5327 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1090 loss_aux: 1.4237 2023/02/17 15:16:58 - mmengine - INFO - Epoch(train) [43][1280/1345] lr: 1.0000e-02 eta: 7:40:37 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.8098 loss: 3.6189 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2289 loss_aux: 1.3900 2023/02/17 15:17:02 - mmengine - INFO - Epoch(train) [43][1300/1345] lr: 1.0000e-02 eta: 7:40:33 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.7139 loss: 3.6110 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1952 loss_aux: 1.4158 2023/02/17 15:17:05 - mmengine - INFO - Epoch(train) [43][1320/1345] lr: 1.0000e-02 eta: 7:40:29 time: 0.1899 data_time: 0.0057 memory: 8327 grad_norm: 7.6631 loss: 3.7143 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3212 loss_aux: 1.3931 2023/02/17 15:17:09 - mmengine - INFO - Epoch(train) [43][1340/1345] lr: 1.0000e-02 eta: 7:40:25 time: 0.1895 data_time: 0.0061 memory: 8327 grad_norm: 7.5828 loss: 3.7980 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3853 loss_aux: 1.4127 2023/02/17 15:17:10 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:17:10 - mmengine - INFO - Epoch(train) [43][1345/1345] lr: 1.0000e-02 eta: 7:40:23 time: 0.1833 data_time: 0.0061 memory: 8327 grad_norm: 7.4904 loss: 3.8249 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.4238 loss_aux: 1.4011 2023/02/17 15:17:10 - mmengine - INFO - Saving checkpoint at 43 epochs 2023/02/17 15:17:17 - mmengine - INFO - Epoch(train) [44][ 20/1345] lr: 1.0000e-02 eta: 7:40:20 time: 0.2061 data_time: 0.0158 memory: 8327 grad_norm: 7.3767 loss: 3.5018 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1460 loss_aux: 1.3558 2023/02/17 15:17:21 - mmengine - INFO - Epoch(train) [44][ 40/1345] lr: 1.0000e-02 eta: 7:40:16 time: 0.1913 data_time: 0.0043 memory: 8327 grad_norm: 7.3573 loss: 3.5245 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1773 loss_aux: 1.3471 2023/02/17 15:17:24 - mmengine - INFO - Epoch(train) [44][ 60/1345] lr: 1.0000e-02 eta: 7:40:13 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.6825 loss: 3.8612 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3506 loss_aux: 1.5107 2023/02/17 15:17:28 - mmengine - INFO - Epoch(train) [44][ 80/1345] lr: 1.0000e-02 eta: 7:40:09 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.5939 loss: 3.5544 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1729 loss_aux: 1.3815 2023/02/17 15:17:32 - mmengine - INFO - Epoch(train) [44][ 100/1345] lr: 1.0000e-02 eta: 7:40:05 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.6297 loss: 3.2894 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9957 loss_aux: 1.2937 2023/02/17 15:17:36 - mmengine - INFO - Epoch(train) [44][ 120/1345] lr: 1.0000e-02 eta: 7:40:01 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.3901 loss: 3.1596 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9293 loss_aux: 1.2302 2023/02/17 15:17:40 - mmengine - INFO - Epoch(train) [44][ 140/1345] lr: 1.0000e-02 eta: 7:39:57 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.3846 loss: 3.1683 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9254 loss_aux: 1.2429 2023/02/17 15:17:43 - mmengine - INFO - Epoch(train) [44][ 160/1345] lr: 1.0000e-02 eta: 7:39:53 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5367 loss: 3.4655 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0972 loss_aux: 1.3683 2023/02/17 15:17:44 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:17:47 - mmengine - INFO - Epoch(train) [44][ 180/1345] lr: 1.0000e-02 eta: 7:39:49 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5757 loss: 3.1196 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8659 loss_aux: 1.2537 2023/02/17 15:17:51 - mmengine - INFO - Epoch(train) [44][ 200/1345] lr: 1.0000e-02 eta: 7:39:45 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.4966 loss: 3.7606 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3090 loss_aux: 1.4516 2023/02/17 15:17:55 - mmengine - INFO - Epoch(train) [44][ 220/1345] lr: 1.0000e-02 eta: 7:39:41 time: 0.1895 data_time: 0.0061 memory: 8327 grad_norm: 7.5042 loss: 3.3940 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0694 loss_aux: 1.3245 2023/02/17 15:17:59 - mmengine - INFO - Epoch(train) [44][ 240/1345] lr: 1.0000e-02 eta: 7:39:37 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.4016 loss: 2.9555 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7404 loss_aux: 1.2151 2023/02/17 15:18:02 - mmengine - INFO - Epoch(train) [44][ 260/1345] lr: 1.0000e-02 eta: 7:39:33 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.9489 loss: 3.5363 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1325 loss_aux: 1.4038 2023/02/17 15:18:06 - mmengine - INFO - Epoch(train) [44][ 280/1345] lr: 1.0000e-02 eta: 7:39:29 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7028 loss: 3.6599 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2503 loss_aux: 1.4097 2023/02/17 15:18:10 - mmengine - INFO - Epoch(train) [44][ 300/1345] lr: 1.0000e-02 eta: 7:39:25 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.8037 loss: 3.6425 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2671 loss_aux: 1.3754 2023/02/17 15:18:14 - mmengine - INFO - Epoch(train) [44][ 320/1345] lr: 1.0000e-02 eta: 7:39:21 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.3649 loss: 3.2755 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9424 loss_aux: 1.3331 2023/02/17 15:18:18 - mmengine - INFO - Epoch(train) [44][ 340/1345] lr: 1.0000e-02 eta: 7:39:17 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.5810 loss: 3.6141 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2266 loss_aux: 1.3875 2023/02/17 15:18:21 - mmengine - INFO - Epoch(train) [44][ 360/1345] lr: 1.0000e-02 eta: 7:39:13 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.3614 loss: 3.3314 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9706 loss_aux: 1.3608 2023/02/17 15:18:25 - mmengine - INFO - Epoch(train) [44][ 380/1345] lr: 1.0000e-02 eta: 7:39:09 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.5713 loss: 3.0611 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8186 loss_aux: 1.2424 2023/02/17 15:18:29 - mmengine - INFO - Epoch(train) [44][ 400/1345] lr: 1.0000e-02 eta: 7:39:05 time: 0.1901 data_time: 0.0067 memory: 8327 grad_norm: 7.7099 loss: 3.3925 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0950 loss_aux: 1.2975 2023/02/17 15:18:33 - mmengine - INFO - Epoch(train) [44][ 420/1345] lr: 1.0000e-02 eta: 7:39:01 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.5247 loss: 3.3453 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9890 loss_aux: 1.3564 2023/02/17 15:18:37 - mmengine - INFO - Epoch(train) [44][ 440/1345] lr: 1.0000e-02 eta: 7:38:57 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.6910 loss: 3.8279 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3496 loss_aux: 1.4783 2023/02/17 15:18:40 - mmengine - INFO - Epoch(train) [44][ 460/1345] lr: 1.0000e-02 eta: 7:38:53 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.6327 loss: 3.4493 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0949 loss_aux: 1.3544 2023/02/17 15:18:44 - mmengine - INFO - Epoch(train) [44][ 480/1345] lr: 1.0000e-02 eta: 7:38:49 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.6490 loss: 3.5267 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1144 loss_aux: 1.4123 2023/02/17 15:18:48 - mmengine - INFO - Epoch(train) [44][ 500/1345] lr: 1.0000e-02 eta: 7:38:45 time: 0.1910 data_time: 0.0064 memory: 8327 grad_norm: 7.6613 loss: 3.2789 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9904 loss_aux: 1.2885 2023/02/17 15:18:52 - mmengine - INFO - Epoch(train) [44][ 520/1345] lr: 1.0000e-02 eta: 7:38:41 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.7185 loss: 3.5111 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1314 loss_aux: 1.3797 2023/02/17 15:18:56 - mmengine - INFO - Epoch(train) [44][ 540/1345] lr: 1.0000e-02 eta: 7:38:38 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.7537 loss: 3.3622 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0684 loss_aux: 1.2937 2023/02/17 15:18:59 - mmengine - INFO - Epoch(train) [44][ 560/1345] lr: 1.0000e-02 eta: 7:38:34 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.7308 loss: 3.8088 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3662 loss_aux: 1.4426 2023/02/17 15:19:03 - mmengine - INFO - Epoch(train) [44][ 580/1345] lr: 1.0000e-02 eta: 7:38:30 time: 0.1899 data_time: 0.0064 memory: 8327 grad_norm: 7.5017 loss: 3.7136 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.2858 loss_aux: 1.4278 2023/02/17 15:19:07 - mmengine - INFO - Epoch(train) [44][ 600/1345] lr: 1.0000e-02 eta: 7:38:26 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.5857 loss: 3.6484 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2366 loss_aux: 1.4118 2023/02/17 15:19:11 - mmengine - INFO - Epoch(train) [44][ 620/1345] lr: 1.0000e-02 eta: 7:38:22 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.7480 loss: 3.6549 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2453 loss_aux: 1.4095 2023/02/17 15:19:14 - mmengine - INFO - Epoch(train) [44][ 640/1345] lr: 1.0000e-02 eta: 7:38:18 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.6226 loss: 3.6755 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2585 loss_aux: 1.4170 2023/02/17 15:19:18 - mmengine - INFO - Epoch(train) [44][ 660/1345] lr: 1.0000e-02 eta: 7:38:14 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 7.6696 loss: 3.5518 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1763 loss_aux: 1.3755 2023/02/17 15:19:22 - mmengine - INFO - Epoch(train) [44][ 680/1345] lr: 1.0000e-02 eta: 7:38:10 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.6087 loss: 3.8514 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3852 loss_aux: 1.4661 2023/02/17 15:19:26 - mmengine - INFO - Epoch(train) [44][ 700/1345] lr: 1.0000e-02 eta: 7:38:06 time: 0.1893 data_time: 0.0056 memory: 8327 grad_norm: 7.5783 loss: 3.5330 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1619 loss_aux: 1.3711 2023/02/17 15:19:30 - mmengine - INFO - Epoch(train) [44][ 720/1345] lr: 1.0000e-02 eta: 7:38:02 time: 0.1905 data_time: 0.0064 memory: 8327 grad_norm: 7.6600 loss: 3.4886 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1128 loss_aux: 1.3758 2023/02/17 15:19:34 - mmengine - INFO - Epoch(train) [44][ 740/1345] lr: 1.0000e-02 eta: 7:38:00 time: 0.2298 data_time: 0.0460 memory: 8327 grad_norm: 7.5339 loss: 3.2765 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9928 loss_aux: 1.2837 2023/02/17 15:19:38 - mmengine - INFO - Epoch(train) [44][ 760/1345] lr: 1.0000e-02 eta: 7:37:56 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.8302 loss: 3.7700 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2809 loss_aux: 1.4891 2023/02/17 15:19:42 - mmengine - INFO - Epoch(train) [44][ 780/1345] lr: 1.0000e-02 eta: 7:37:52 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.6032 loss: 3.7079 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3254 loss_aux: 1.3825 2023/02/17 15:19:46 - mmengine - INFO - Epoch(train) [44][ 800/1345] lr: 1.0000e-02 eta: 7:37:48 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.5329 loss: 3.6734 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3078 loss_aux: 1.3656 2023/02/17 15:19:49 - mmengine - INFO - Epoch(train) [44][ 820/1345] lr: 1.0000e-02 eta: 7:37:44 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.7850 loss: 3.7752 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3757 loss_aux: 1.3995 2023/02/17 15:19:53 - mmengine - INFO - Epoch(train) [44][ 840/1345] lr: 1.0000e-02 eta: 7:37:40 time: 0.1902 data_time: 0.0063 memory: 8327 grad_norm: 7.6972 loss: 3.7833 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3305 loss_aux: 1.4528 2023/02/17 15:19:57 - mmengine - INFO - Epoch(train) [44][ 860/1345] lr: 1.0000e-02 eta: 7:37:36 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.9810 loss: 3.5847 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2209 loss_aux: 1.3638 2023/02/17 15:20:01 - mmengine - INFO - Epoch(train) [44][ 880/1345] lr: 1.0000e-02 eta: 7:37:32 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.5714 loss: 3.7385 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3005 loss_aux: 1.4380 2023/02/17 15:20:05 - mmengine - INFO - Epoch(train) [44][ 900/1345] lr: 1.0000e-02 eta: 7:37:28 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.7309 loss: 3.3873 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0598 loss_aux: 1.3275 2023/02/17 15:20:08 - mmengine - INFO - Epoch(train) [44][ 920/1345] lr: 1.0000e-02 eta: 7:37:24 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.6281 loss: 3.5379 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1356 loss_aux: 1.4022 2023/02/17 15:20:12 - mmengine - INFO - Epoch(train) [44][ 940/1345] lr: 1.0000e-02 eta: 7:37:20 time: 0.1900 data_time: 0.0057 memory: 8327 grad_norm: 7.5646 loss: 3.3735 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0968 loss_aux: 1.2767 2023/02/17 15:20:16 - mmengine - INFO - Epoch(train) [44][ 960/1345] lr: 1.0000e-02 eta: 7:37:17 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.5875 loss: 3.7910 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3658 loss_aux: 1.4253 2023/02/17 15:20:20 - mmengine - INFO - Epoch(train) [44][ 980/1345] lr: 1.0000e-02 eta: 7:37:13 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.4238 loss: 3.4215 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.1228 loss_aux: 1.2987 2023/02/17 15:20:24 - mmengine - INFO - Epoch(train) [44][1000/1345] lr: 1.0000e-02 eta: 7:37:09 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.6021 loss: 3.7089 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2807 loss_aux: 1.4282 2023/02/17 15:20:27 - mmengine - INFO - Epoch(train) [44][1020/1345] lr: 1.0000e-02 eta: 7:37:05 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.8515 loss: 3.4257 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.0927 loss_aux: 1.3330 2023/02/17 15:20:31 - mmengine - INFO - Epoch(train) [44][1040/1345] lr: 1.0000e-02 eta: 7:37:01 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.6195 loss: 3.5029 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1413 loss_aux: 1.3616 2023/02/17 15:20:35 - mmengine - INFO - Epoch(train) [44][1060/1345] lr: 1.0000e-02 eta: 7:36:57 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.4893 loss: 3.6598 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2205 loss_aux: 1.4393 2023/02/17 15:20:39 - mmengine - INFO - Epoch(train) [44][1080/1345] lr: 1.0000e-02 eta: 7:36:53 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.6500 loss: 3.5361 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1763 loss_aux: 1.3598 2023/02/17 15:20:43 - mmengine - INFO - Epoch(train) [44][1100/1345] lr: 1.0000e-02 eta: 7:36:49 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.4993 loss: 3.3804 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0398 loss_aux: 1.3406 2023/02/17 15:20:46 - mmengine - INFO - Epoch(train) [44][1120/1345] lr: 1.0000e-02 eta: 7:36:45 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.5870 loss: 3.8415 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3906 loss_aux: 1.4509 2023/02/17 15:20:50 - mmengine - INFO - Epoch(train) [44][1140/1345] lr: 1.0000e-02 eta: 7:36:41 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.6602 loss: 3.5352 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1693 loss_aux: 1.3659 2023/02/17 15:20:54 - mmengine - INFO - Epoch(train) [44][1160/1345] lr: 1.0000e-02 eta: 7:36:37 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.5927 loss: 3.4607 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0439 loss_aux: 1.4167 2023/02/17 15:20:55 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:20:58 - mmengine - INFO - Epoch(train) [44][1180/1345] lr: 1.0000e-02 eta: 7:36:33 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.6567 loss: 3.7243 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.2756 loss_aux: 1.4487 2023/02/17 15:21:02 - mmengine - INFO - Epoch(train) [44][1200/1345] lr: 1.0000e-02 eta: 7:36:29 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.4506 loss: 3.7106 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2892 loss_aux: 1.4214 2023/02/17 15:21:05 - mmengine - INFO - Epoch(train) [44][1220/1345] lr: 1.0000e-02 eta: 7:36:25 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 7.4842 loss: 3.2858 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 1.9684 loss_aux: 1.3174 2023/02/17 15:21:09 - mmengine - INFO - Epoch(train) [44][1240/1345] lr: 1.0000e-02 eta: 7:36:21 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.6436 loss: 3.5938 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2205 loss_aux: 1.3733 2023/02/17 15:21:13 - mmengine - INFO - Epoch(train) [44][1260/1345] lr: 1.0000e-02 eta: 7:36:17 time: 0.1900 data_time: 0.0060 memory: 8327 grad_norm: 7.4990 loss: 3.7652 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3631 loss_aux: 1.4022 2023/02/17 15:21:17 - mmengine - INFO - Epoch(train) [44][1280/1345] lr: 1.0000e-02 eta: 7:36:13 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.4199 loss: 3.5246 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1308 loss_aux: 1.3937 2023/02/17 15:21:21 - mmengine - INFO - Epoch(train) [44][1300/1345] lr: 1.0000e-02 eta: 7:36:09 time: 0.1900 data_time: 0.0061 memory: 8327 grad_norm: 7.7259 loss: 3.4706 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1177 loss_aux: 1.3529 2023/02/17 15:21:24 - mmengine - INFO - Epoch(train) [44][1320/1345] lr: 1.0000e-02 eta: 7:36:05 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.8764 loss: 3.9070 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4342 loss_aux: 1.4729 2023/02/17 15:21:28 - mmengine - INFO - Epoch(train) [44][1340/1345] lr: 1.0000e-02 eta: 7:36:01 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.7159 loss: 4.0564 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4949 loss_aux: 1.5615 2023/02/17 15:21:29 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:21:29 - mmengine - INFO - Epoch(train) [44][1345/1345] lr: 1.0000e-02 eta: 7:36:00 time: 0.1832 data_time: 0.0059 memory: 8327 grad_norm: 7.5719 loss: 3.9226 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.4347 loss_aux: 1.4879 2023/02/17 15:21:29 - mmengine - INFO - Saving checkpoint at 44 epochs 2023/02/17 15:21:36 - mmengine - INFO - Epoch(train) [45][ 20/1345] lr: 1.0000e-02 eta: 7:35:57 time: 0.2068 data_time: 0.0147 memory: 8327 grad_norm: 7.3121 loss: 2.9860 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.8110 loss_aux: 1.1750 2023/02/17 15:21:39 - mmengine - INFO - Epoch(train) [45][ 40/1345] lr: 1.0000e-02 eta: 7:35:53 time: 0.1923 data_time: 0.0056 memory: 8327 grad_norm: 7.6928 loss: 3.7974 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3398 loss_aux: 1.4576 2023/02/17 15:21:43 - mmengine - INFO - Epoch(train) [45][ 60/1345] lr: 1.0000e-02 eta: 7:35:49 time: 0.1891 data_time: 0.0057 memory: 8327 grad_norm: 7.5553 loss: 3.3438 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9971 loss_aux: 1.3467 2023/02/17 15:21:47 - mmengine - INFO - Epoch(train) [45][ 80/1345] lr: 1.0000e-02 eta: 7:35:45 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.6958 loss: 3.6474 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2511 loss_aux: 1.3963 2023/02/17 15:21:51 - mmengine - INFO - Epoch(train) [45][ 100/1345] lr: 1.0000e-02 eta: 7:35:41 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.5422 loss: 3.6075 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2361 loss_aux: 1.3714 2023/02/17 15:21:55 - mmengine - INFO - Epoch(train) [45][ 120/1345] lr: 1.0000e-02 eta: 7:35:37 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.4204 loss: 3.6119 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1919 loss_aux: 1.4201 2023/02/17 15:21:58 - mmengine - INFO - Epoch(train) [45][ 140/1345] lr: 1.0000e-02 eta: 7:35:33 time: 0.1900 data_time: 0.0060 memory: 8327 grad_norm: 7.4928 loss: 3.4950 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1616 loss_aux: 1.3334 2023/02/17 15:22:02 - mmengine - INFO - Epoch(train) [45][ 160/1345] lr: 1.0000e-02 eta: 7:35:29 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.4741 loss: 3.2457 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9389 loss_aux: 1.3068 2023/02/17 15:22:06 - mmengine - INFO - Epoch(train) [45][ 180/1345] lr: 1.0000e-02 eta: 7:35:26 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.3027 loss: 3.4335 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0980 loss_aux: 1.3354 2023/02/17 15:22:10 - mmengine - INFO - Epoch(train) [45][ 200/1345] lr: 1.0000e-02 eta: 7:35:22 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 7.4807 loss: 3.6063 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2372 loss_aux: 1.3691 2023/02/17 15:22:14 - mmengine - INFO - Epoch(train) [45][ 220/1345] lr: 1.0000e-02 eta: 7:35:18 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.6755 loss: 3.7786 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3195 loss_aux: 1.4590 2023/02/17 15:22:18 - mmengine - INFO - Epoch(train) [45][ 240/1345] lr: 1.0000e-02 eta: 7:35:14 time: 0.2016 data_time: 0.0163 memory: 8327 grad_norm: 7.4559 loss: 3.8273 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3270 loss_aux: 1.5003 2023/02/17 15:22:21 - mmengine - INFO - Epoch(train) [45][ 260/1345] lr: 1.0000e-02 eta: 7:35:10 time: 0.1900 data_time: 0.0057 memory: 8327 grad_norm: 7.6285 loss: 3.4574 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0896 loss_aux: 1.3678 2023/02/17 15:22:25 - mmengine - INFO - Epoch(train) [45][ 280/1345] lr: 1.0000e-02 eta: 7:35:06 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.5763 loss: 3.3610 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0223 loss_aux: 1.3388 2023/02/17 15:22:29 - mmengine - INFO - Epoch(train) [45][ 300/1345] lr: 1.0000e-02 eta: 7:35:02 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5286 loss: 3.0395 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7979 loss_aux: 1.2416 2023/02/17 15:22:33 - mmengine - INFO - Epoch(train) [45][ 320/1345] lr: 1.0000e-02 eta: 7:34:58 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.7960 loss: 3.3741 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0518 loss_aux: 1.3222 2023/02/17 15:22:37 - mmengine - INFO - Epoch(train) [45][ 340/1345] lr: 1.0000e-02 eta: 7:34:54 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.5936 loss: 3.5002 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1359 loss_aux: 1.3643 2023/02/17 15:22:40 - mmengine - INFO - Epoch(train) [45][ 360/1345] lr: 1.0000e-02 eta: 7:34:51 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.9105 loss: 3.3507 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0092 loss_aux: 1.3415 2023/02/17 15:22:44 - mmengine - INFO - Epoch(train) [45][ 380/1345] lr: 1.0000e-02 eta: 7:34:47 time: 0.1996 data_time: 0.0160 memory: 8327 grad_norm: 7.6306 loss: 3.4369 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0819 loss_aux: 1.3550 2023/02/17 15:22:48 - mmengine - INFO - Epoch(train) [45][ 400/1345] lr: 1.0000e-02 eta: 7:34:43 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.7107 loss: 3.6078 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.2426 loss_aux: 1.3653 2023/02/17 15:22:52 - mmengine - INFO - Epoch(train) [45][ 420/1345] lr: 1.0000e-02 eta: 7:34:39 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.6373 loss: 3.8803 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.4074 loss_aux: 1.4729 2023/02/17 15:22:56 - mmengine - INFO - Epoch(train) [45][ 440/1345] lr: 1.0000e-02 eta: 7:34:35 time: 0.1910 data_time: 0.0077 memory: 8327 grad_norm: 7.6378 loss: 3.6509 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1830 loss_aux: 1.4679 2023/02/17 15:23:00 - mmengine - INFO - Epoch(train) [45][ 460/1345] lr: 1.0000e-02 eta: 7:34:31 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.5107 loss: 3.4804 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0992 loss_aux: 1.3812 2023/02/17 15:23:03 - mmengine - INFO - Epoch(train) [45][ 480/1345] lr: 1.0000e-02 eta: 7:34:27 time: 0.1898 data_time: 0.0056 memory: 8327 grad_norm: 7.5205 loss: 3.3476 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0438 loss_aux: 1.3038 2023/02/17 15:23:07 - mmengine - INFO - Epoch(train) [45][ 500/1345] lr: 1.0000e-02 eta: 7:34:23 time: 0.1902 data_time: 0.0060 memory: 8327 grad_norm: 7.4978 loss: 3.2359 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9593 loss_aux: 1.2765 2023/02/17 15:23:11 - mmengine - INFO - Epoch(train) [45][ 520/1345] lr: 1.0000e-02 eta: 7:34:20 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5399 loss: 3.5960 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2345 loss_aux: 1.3615 2023/02/17 15:23:15 - mmengine - INFO - Epoch(train) [45][ 540/1345] lr: 1.0000e-02 eta: 7:34:16 time: 0.1894 data_time: 0.0063 memory: 8327 grad_norm: 7.7697 loss: 3.7338 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2909 loss_aux: 1.4429 2023/02/17 15:23:19 - mmengine - INFO - Epoch(train) [45][ 560/1345] lr: 1.0000e-02 eta: 7:34:12 time: 0.1892 data_time: 0.0060 memory: 8327 grad_norm: 7.7024 loss: 3.4028 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0575 loss_aux: 1.3452 2023/02/17 15:23:22 - mmengine - INFO - Epoch(train) [45][ 580/1345] lr: 1.0000e-02 eta: 7:34:08 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.6397 loss: 3.9925 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5437 loss_aux: 1.4489 2023/02/17 15:23:26 - mmengine - INFO - Epoch(train) [45][ 600/1345] lr: 1.0000e-02 eta: 7:34:04 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.8971 loss: 3.8815 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4177 loss_aux: 1.4638 2023/02/17 15:23:30 - mmengine - INFO - Epoch(train) [45][ 620/1345] lr: 1.0000e-02 eta: 7:34:00 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.7226 loss: 3.5410 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1876 loss_aux: 1.3535 2023/02/17 15:23:34 - mmengine - INFO - Epoch(train) [45][ 640/1345] lr: 1.0000e-02 eta: 7:33:56 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.7701 loss: 3.4569 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1169 loss_aux: 1.3400 2023/02/17 15:23:38 - mmengine - INFO - Epoch(train) [45][ 660/1345] lr: 1.0000e-02 eta: 7:33:52 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.7795 loss: 3.6752 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2702 loss_aux: 1.4050 2023/02/17 15:23:41 - mmengine - INFO - Epoch(train) [45][ 680/1345] lr: 1.0000e-02 eta: 7:33:48 time: 0.1920 data_time: 0.0059 memory: 8327 grad_norm: 7.5271 loss: 3.3979 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0937 loss_aux: 1.3042 2023/02/17 15:23:45 - mmengine - INFO - Epoch(train) [45][ 700/1345] lr: 1.0000e-02 eta: 7:33:44 time: 0.1912 data_time: 0.0057 memory: 8327 grad_norm: 7.4696 loss: 3.8250 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3804 loss_aux: 1.4446 2023/02/17 15:23:49 - mmengine - INFO - Epoch(train) [45][ 720/1345] lr: 1.0000e-02 eta: 7:33:40 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.7126 loss: 3.5881 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.1356 loss_aux: 1.4525 2023/02/17 15:23:53 - mmengine - INFO - Epoch(train) [45][ 740/1345] lr: 1.0000e-02 eta: 7:33:36 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5512 loss: 3.2553 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9283 loss_aux: 1.3270 2023/02/17 15:23:57 - mmengine - INFO - Epoch(train) [45][ 760/1345] lr: 1.0000e-02 eta: 7:33:32 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.5710 loss: 3.3268 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9671 loss_aux: 1.3597 2023/02/17 15:24:00 - mmengine - INFO - Epoch(train) [45][ 780/1345] lr: 1.0000e-02 eta: 7:33:28 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5177 loss: 3.4589 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1010 loss_aux: 1.3579 2023/02/17 15:24:04 - mmengine - INFO - Epoch(train) [45][ 800/1345] lr: 1.0000e-02 eta: 7:33:25 time: 0.1993 data_time: 0.0160 memory: 8327 grad_norm: 7.4135 loss: 3.2429 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9437 loss_aux: 1.2992 2023/02/17 15:24:08 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:24:08 - mmengine - INFO - Epoch(train) [45][ 820/1345] lr: 1.0000e-02 eta: 7:33:21 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.7316 loss: 3.9874 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4757 loss_aux: 1.5117 2023/02/17 15:24:12 - mmengine - INFO - Epoch(train) [45][ 840/1345] lr: 1.0000e-02 eta: 7:33:17 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.6142 loss: 3.5304 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1350 loss_aux: 1.3954 2023/02/17 15:24:48 - mmengine - INFO - Epoch(train) [45][ 860/1345] lr: 1.0000e-02 eta: 7:34:28 time: 1.7879 data_time: 0.0062 memory: 8327 grad_norm: 7.4218 loss: 3.1622 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8915 loss_aux: 1.2707 2023/02/17 15:24:52 - mmengine - INFO - Epoch(train) [45][ 880/1345] lr: 1.0000e-02 eta: 7:34:25 time: 0.1933 data_time: 0.0057 memory: 8327 grad_norm: 7.4157 loss: 3.3156 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0112 loss_aux: 1.3044 2023/02/17 15:24:55 - mmengine - INFO - Epoch(train) [45][ 900/1345] lr: 1.0000e-02 eta: 7:34:21 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.7276 loss: 3.4283 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.1179 loss_aux: 1.3104 2023/02/17 15:24:59 - mmengine - INFO - Epoch(train) [45][ 920/1345] lr: 1.0000e-02 eta: 7:34:17 time: 0.1900 data_time: 0.0057 memory: 8327 grad_norm: 7.6457 loss: 3.3453 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9571 loss_aux: 1.3883 2023/02/17 15:25:03 - mmengine - INFO - Epoch(train) [45][ 940/1345] lr: 1.0000e-02 eta: 7:34:13 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.5414 loss: 3.9123 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3753 loss_aux: 1.5370 2023/02/17 15:25:07 - mmengine - INFO - Epoch(train) [45][ 960/1345] lr: 1.0000e-02 eta: 7:34:09 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7467 loss: 3.2075 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9284 loss_aux: 1.2791 2023/02/17 15:25:11 - mmengine - INFO - Epoch(train) [45][ 980/1345] lr: 1.0000e-02 eta: 7:34:05 time: 0.1913 data_time: 0.0074 memory: 8327 grad_norm: 7.6261 loss: 3.3953 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0510 loss_aux: 1.3442 2023/02/17 15:25:14 - mmengine - INFO - Epoch(train) [45][1000/1345] lr: 1.0000e-02 eta: 7:34:01 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5628 loss: 3.7879 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3862 loss_aux: 1.4017 2023/02/17 15:25:18 - mmengine - INFO - Epoch(train) [45][1020/1345] lr: 1.0000e-02 eta: 7:33:57 time: 0.1894 data_time: 0.0061 memory: 8327 grad_norm: 7.7296 loss: 3.7355 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3041 loss_aux: 1.4314 2023/02/17 15:25:22 - mmengine - INFO - Epoch(train) [45][1040/1345] lr: 1.0000e-02 eta: 7:33:53 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.7044 loss: 3.8029 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3414 loss_aux: 1.4615 2023/02/17 15:25:26 - mmengine - INFO - Epoch(train) [45][1060/1345] lr: 1.0000e-02 eta: 7:33:49 time: 0.1911 data_time: 0.0075 memory: 8327 grad_norm: 7.2345 loss: 3.4176 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0498 loss_aux: 1.3677 2023/02/17 15:25:30 - mmengine - INFO - Epoch(train) [45][1080/1345] lr: 1.0000e-02 eta: 7:33:45 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.7352 loss: 3.6988 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3144 loss_aux: 1.3844 2023/02/17 15:25:33 - mmengine - INFO - Epoch(train) [45][1100/1345] lr: 1.0000e-02 eta: 7:33:41 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.7328 loss: 3.1818 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9221 loss_aux: 1.2596 2023/02/17 15:25:37 - mmengine - INFO - Epoch(train) [45][1120/1345] lr: 1.0000e-02 eta: 7:33:37 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.5907 loss: 3.4127 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0397 loss_aux: 1.3730 2023/02/17 15:25:41 - mmengine - INFO - Epoch(train) [45][1140/1345] lr: 1.0000e-02 eta: 7:33:33 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.7423 loss: 3.5265 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1456 loss_aux: 1.3808 2023/02/17 15:25:45 - mmengine - INFO - Epoch(train) [45][1160/1345] lr: 1.0000e-02 eta: 7:33:29 time: 0.1898 data_time: 0.0062 memory: 8327 grad_norm: 7.5401 loss: 3.0492 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8454 loss_aux: 1.2038 2023/02/17 15:25:49 - mmengine - INFO - Epoch(train) [45][1180/1345] lr: 1.0000e-02 eta: 7:33:25 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.7236 loss: 3.4284 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.0703 loss_aux: 1.3581 2023/02/17 15:25:52 - mmengine - INFO - Epoch(train) [45][1200/1345] lr: 1.0000e-02 eta: 7:33:21 time: 0.1897 data_time: 0.0063 memory: 8327 grad_norm: 7.7826 loss: 3.3694 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0848 loss_aux: 1.2846 2023/02/17 15:25:56 - mmengine - INFO - Epoch(train) [45][1220/1345] lr: 1.0000e-02 eta: 7:33:17 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.8445 loss: 3.3545 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0759 loss_aux: 1.2786 2023/02/17 15:26:00 - mmengine - INFO - Epoch(train) [45][1240/1345] lr: 1.0000e-02 eta: 7:33:13 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.6818 loss: 3.5173 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1600 loss_aux: 1.3573 2023/02/17 15:26:04 - mmengine - INFO - Epoch(train) [45][1260/1345] lr: 1.0000e-02 eta: 7:33:09 time: 0.1910 data_time: 0.0057 memory: 8327 grad_norm: 7.7203 loss: 3.5815 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2280 loss_aux: 1.3534 2023/02/17 15:26:08 - mmengine - INFO - Epoch(train) [45][1280/1345] lr: 1.0000e-02 eta: 7:33:05 time: 0.1912 data_time: 0.0057 memory: 8327 grad_norm: 7.5635 loss: 3.8350 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3621 loss_aux: 1.4730 2023/02/17 15:26:11 - mmengine - INFO - Epoch(train) [45][1300/1345] lr: 1.0000e-02 eta: 7:33:01 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.5319 loss: 3.7464 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3321 loss_aux: 1.4143 2023/02/17 15:26:15 - mmengine - INFO - Epoch(train) [45][1320/1345] lr: 1.0000e-02 eta: 7:32:57 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.5404 loss: 3.2372 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9712 loss_aux: 1.2660 2023/02/17 15:26:19 - mmengine - INFO - Epoch(train) [45][1340/1345] lr: 1.0000e-02 eta: 7:32:53 time: 0.1899 data_time: 0.0064 memory: 8327 grad_norm: 7.5745 loss: 3.3376 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0406 loss_aux: 1.2969 2023/02/17 15:26:20 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:26:20 - mmengine - INFO - Epoch(train) [45][1345/1345] lr: 1.0000e-02 eta: 7:32:52 time: 0.1836 data_time: 0.0062 memory: 8327 grad_norm: 7.4573 loss: 3.4874 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.1145 loss_aux: 1.3729 2023/02/17 15:26:20 - mmengine - INFO - Saving checkpoint at 45 epochs 2023/02/17 15:26:23 - mmengine - INFO - Epoch(val) [45][ 20/181] eta: 0:00:09 time: 0.0561 data_time: 0.0074 memory: 1994 2023/02/17 15:26:24 - mmengine - INFO - Epoch(val) [45][ 40/181] eta: 0:00:07 time: 0.0522 data_time: 0.0045 memory: 1994 2023/02/17 15:26:25 - mmengine - INFO - Epoch(val) [45][ 60/181] eta: 0:00:06 time: 0.0524 data_time: 0.0045 memory: 1994 2023/02/17 15:26:27 - mmengine - INFO - Epoch(val) [45][ 80/181] eta: 0:00:05 time: 0.0525 data_time: 0.0045 memory: 1994 2023/02/17 15:26:28 - mmengine - INFO - Epoch(val) [45][100/181] eta: 0:00:04 time: 0.0525 data_time: 0.0047 memory: 1994 2023/02/17 15:26:29 - mmengine - INFO - Epoch(val) [45][120/181] eta: 0:00:03 time: 0.0529 data_time: 0.0047 memory: 1994 2023/02/17 15:26:30 - mmengine - INFO - Epoch(val) [45][140/181] eta: 0:00:02 time: 0.0522 data_time: 0.0045 memory: 1994 2023/02/17 15:26:31 - mmengine - INFO - Epoch(val) [45][160/181] eta: 0:00:01 time: 0.0519 data_time: 0.0043 memory: 1994 2023/02/17 15:26:32 - mmengine - INFO - Epoch(val) [45][180/181] eta: 0:00:00 time: 0.0519 data_time: 0.0043 memory: 1994 2023/02/17 15:26:34 - mmengine - INFO - Epoch(val) [45][181/181] acc/top1: 0.3803 acc/top5: 0.6707 acc/mean1: 0.3417 2023/02/17 15:26:34 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/lilin/Repos/mmact_dev/mmaction2/work_dirs/fix_flip/tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb/best_acc/top1_epoch_30.pth is removed 2023/02/17 15:26:35 - mmengine - INFO - The best checkpoint with 0.3803 acc/top1 at 45 epoch is saved to best_acc/top1_epoch_45.pth. 2023/02/17 15:26:39 - mmengine - INFO - Epoch(train) [46][ 20/1345] lr: 1.0000e-02 eta: 7:32:49 time: 0.2054 data_time: 0.0149 memory: 8327 grad_norm: 7.5316 loss: 3.5885 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.1442 loss_aux: 1.4443 2023/02/17 15:26:43 - mmengine - INFO - Epoch(train) [46][ 40/1345] lr: 1.0000e-02 eta: 7:32:45 time: 0.1927 data_time: 0.0056 memory: 8327 grad_norm: 7.5817 loss: 3.7417 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2876 loss_aux: 1.4540 2023/02/17 15:26:47 - mmengine - INFO - Epoch(train) [46][ 60/1345] lr: 1.0000e-02 eta: 7:32:41 time: 0.1898 data_time: 0.0052 memory: 8327 grad_norm: 7.6540 loss: 3.1860 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8747 loss_aux: 1.3113 2023/02/17 15:26:51 - mmengine - INFO - Epoch(train) [46][ 80/1345] lr: 1.0000e-02 eta: 7:32:37 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.7508 loss: 3.1418 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8883 loss_aux: 1.2535 2023/02/17 15:26:55 - mmengine - INFO - Epoch(train) [46][ 100/1345] lr: 1.0000e-02 eta: 7:32:33 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.4064 loss: 3.2237 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9191 loss_aux: 1.3046 2023/02/17 15:26:58 - mmengine - INFO - Epoch(train) [46][ 120/1345] lr: 1.0000e-02 eta: 7:32:29 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.7480 loss: 3.8856 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4260 loss_aux: 1.4596 2023/02/17 15:27:02 - mmengine - INFO - Epoch(train) [46][ 140/1345] lr: 1.0000e-02 eta: 7:32:25 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.6330 loss: 3.2051 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9325 loss_aux: 1.2726 2023/02/17 15:27:06 - mmengine - INFO - Epoch(train) [46][ 160/1345] lr: 1.0000e-02 eta: 7:32:21 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.7176 loss: 3.3070 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0176 loss_aux: 1.2894 2023/02/17 15:27:10 - mmengine - INFO - Epoch(train) [46][ 180/1345] lr: 1.0000e-02 eta: 7:32:17 time: 0.1899 data_time: 0.0060 memory: 8327 grad_norm: 7.4904 loss: 3.5618 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2270 loss_aux: 1.3348 2023/02/17 15:27:14 - mmengine - INFO - Epoch(train) [46][ 200/1345] lr: 1.0000e-02 eta: 7:32:13 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.5304 loss: 3.5517 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1720 loss_aux: 1.3796 2023/02/17 15:27:17 - mmengine - INFO - Epoch(train) [46][ 220/1345] lr: 1.0000e-02 eta: 7:32:09 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5743 loss: 3.6261 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2186 loss_aux: 1.4075 2023/02/17 15:27:21 - mmengine - INFO - Epoch(train) [46][ 240/1345] lr: 1.0000e-02 eta: 7:32:05 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.7102 loss: 3.8923 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4310 loss_aux: 1.4614 2023/02/17 15:27:25 - mmengine - INFO - Epoch(train) [46][ 260/1345] lr: 1.0000e-02 eta: 7:32:01 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.6318 loss: 3.7630 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3078 loss_aux: 1.4552 2023/02/17 15:27:29 - mmengine - INFO - Epoch(train) [46][ 280/1345] lr: 1.0000e-02 eta: 7:31:57 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.5877 loss: 3.6028 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1828 loss_aux: 1.4200 2023/02/17 15:27:33 - mmengine - INFO - Epoch(train) [46][ 300/1345] lr: 1.0000e-02 eta: 7:31:53 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.8993 loss: 3.5033 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1199 loss_aux: 1.3834 2023/02/17 15:27:36 - mmengine - INFO - Epoch(train) [46][ 320/1345] lr: 1.0000e-02 eta: 7:31:49 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.6374 loss: 3.5958 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2379 loss_aux: 1.3579 2023/02/17 15:27:40 - mmengine - INFO - Epoch(train) [46][ 340/1345] lr: 1.0000e-02 eta: 7:31:45 time: 0.1908 data_time: 0.0067 memory: 8327 grad_norm: 7.7769 loss: 3.3631 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0263 loss_aux: 1.3368 2023/02/17 15:27:44 - mmengine - INFO - Epoch(train) [46][ 360/1345] lr: 1.0000e-02 eta: 7:31:41 time: 0.1897 data_time: 0.0057 memory: 8327 grad_norm: 7.7155 loss: 3.6041 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1599 loss_aux: 1.4442 2023/02/17 15:27:48 - mmengine - INFO - Epoch(train) [46][ 380/1345] lr: 1.0000e-02 eta: 7:31:37 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.4462 loss: 3.6196 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2432 loss_aux: 1.3764 2023/02/17 15:27:52 - mmengine - INFO - Epoch(train) [46][ 400/1345] lr: 1.0000e-02 eta: 7:31:33 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.5842 loss: 3.4837 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1290 loss_aux: 1.3547 2023/02/17 15:27:55 - mmengine - INFO - Epoch(train) [46][ 420/1345] lr: 1.0000e-02 eta: 7:31:29 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.7924 loss: 3.5519 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1595 loss_aux: 1.3924 2023/02/17 15:27:59 - mmengine - INFO - Epoch(train) [46][ 440/1345] lr: 1.0000e-02 eta: 7:31:25 time: 0.1892 data_time: 0.0058 memory: 8327 grad_norm: 7.3992 loss: 3.1651 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.8939 loss_aux: 1.2712 2023/02/17 15:28:03 - mmengine - INFO - Epoch(train) [46][ 460/1345] lr: 1.0000e-02 eta: 7:31:21 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.5936 loss: 3.3931 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0490 loss_aux: 1.3441 2023/02/17 15:28:06 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:28:07 - mmengine - INFO - Epoch(train) [46][ 480/1345] lr: 1.0000e-02 eta: 7:31:17 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.7371 loss: 3.5317 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2123 loss_aux: 1.3194 2023/02/17 15:28:11 - mmengine - INFO - Epoch(train) [46][ 500/1345] lr: 1.0000e-02 eta: 7:31:13 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.3721 loss: 3.4411 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.0359 loss_aux: 1.4052 2023/02/17 15:28:14 - mmengine - INFO - Epoch(train) [46][ 520/1345] lr: 1.0000e-02 eta: 7:31:09 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.6291 loss: 3.5006 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1751 loss_aux: 1.3254 2023/02/17 15:28:18 - mmengine - INFO - Epoch(train) [46][ 540/1345] lr: 1.0000e-02 eta: 7:31:05 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.6018 loss: 3.0840 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 1.8286 loss_aux: 1.2554 2023/02/17 15:28:22 - mmengine - INFO - Epoch(train) [46][ 560/1345] lr: 1.0000e-02 eta: 7:31:01 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.6197 loss: 3.4592 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1319 loss_aux: 1.3273 2023/02/17 15:28:26 - mmengine - INFO - Epoch(train) [46][ 580/1345] lr: 1.0000e-02 eta: 7:30:57 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.6984 loss: 3.7556 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3343 loss_aux: 1.4212 2023/02/17 15:28:29 - mmengine - INFO - Epoch(train) [46][ 600/1345] lr: 1.0000e-02 eta: 7:30:53 time: 0.1891 data_time: 0.0058 memory: 8327 grad_norm: 7.6731 loss: 3.6511 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2111 loss_aux: 1.4400 2023/02/17 15:28:33 - mmengine - INFO - Epoch(train) [46][ 620/1345] lr: 1.0000e-02 eta: 7:30:49 time: 0.1899 data_time: 0.0064 memory: 8327 grad_norm: 7.3395 loss: 3.3058 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0027 loss_aux: 1.3031 2023/02/17 15:28:37 - mmengine - INFO - Epoch(train) [46][ 640/1345] lr: 1.0000e-02 eta: 7:30:45 time: 0.1900 data_time: 0.0058 memory: 8327 grad_norm: 7.8339 loss: 3.7101 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2571 loss_aux: 1.4530 2023/02/17 15:28:41 - mmengine - INFO - Epoch(train) [46][ 660/1345] lr: 1.0000e-02 eta: 7:30:42 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.6798 loss: 3.7263 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2911 loss_aux: 1.4352 2023/02/17 15:28:45 - mmengine - INFO - Epoch(train) [46][ 680/1345] lr: 1.0000e-02 eta: 7:30:38 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.5383 loss: 3.4710 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1255 loss_aux: 1.3456 2023/02/17 15:28:48 - mmengine - INFO - Epoch(train) [46][ 700/1345] lr: 1.0000e-02 eta: 7:30:34 time: 0.1894 data_time: 0.0062 memory: 8327 grad_norm: 7.6605 loss: 3.7497 top1_acc: 0.1250 top5_acc: 0.8750 loss_cls: 2.3086 loss_aux: 1.4410 2023/02/17 15:28:52 - mmengine - INFO - Epoch(train) [46][ 720/1345] lr: 1.0000e-02 eta: 7:30:30 time: 0.1895 data_time: 0.0061 memory: 8327 grad_norm: 7.7717 loss: 3.4985 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1236 loss_aux: 1.3749 2023/02/17 15:28:56 - mmengine - INFO - Epoch(train) [46][ 740/1345] lr: 1.0000e-02 eta: 7:30:26 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.7879 loss: 3.6045 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1541 loss_aux: 1.4504 2023/02/17 15:29:00 - mmengine - INFO - Epoch(train) [46][ 760/1345] lr: 1.0000e-02 eta: 7:30:22 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.5920 loss: 3.6368 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2560 loss_aux: 1.3808 2023/02/17 15:29:04 - mmengine - INFO - Epoch(train) [46][ 780/1345] lr: 1.0000e-02 eta: 7:30:18 time: 0.1901 data_time: 0.0061 memory: 8327 grad_norm: 7.3710 loss: 3.3839 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0838 loss_aux: 1.3002 2023/02/17 15:29:07 - mmengine - INFO - Epoch(train) [46][ 800/1345] lr: 1.0000e-02 eta: 7:30:14 time: 0.1899 data_time: 0.0060 memory: 8327 grad_norm: 7.6521 loss: 3.5988 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2068 loss_aux: 1.3921 2023/02/17 15:29:11 - mmengine - INFO - Epoch(train) [46][ 820/1345] lr: 1.0000e-02 eta: 7:30:10 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.8191 loss: 3.2850 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9798 loss_aux: 1.3052 2023/02/17 15:29:15 - mmengine - INFO - Epoch(train) [46][ 840/1345] lr: 1.0000e-02 eta: 7:30:06 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.9073 loss: 3.5131 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1310 loss_aux: 1.3821 2023/02/17 15:29:19 - mmengine - INFO - Epoch(train) [46][ 860/1345] lr: 1.0000e-02 eta: 7:30:02 time: 0.1895 data_time: 0.0061 memory: 8327 grad_norm: 7.5389 loss: 3.5549 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1630 loss_aux: 1.3919 2023/02/17 15:29:23 - mmengine - INFO - Epoch(train) [46][ 880/1345] lr: 1.0000e-02 eta: 7:29:58 time: 0.1897 data_time: 0.0061 memory: 8327 grad_norm: 7.4730 loss: 3.1765 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9224 loss_aux: 1.2541 2023/02/17 15:29:26 - mmengine - INFO - Epoch(train) [46][ 900/1345] lr: 1.0000e-02 eta: 7:29:54 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.4960 loss: 3.4855 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1373 loss_aux: 1.3482 2023/02/17 15:29:30 - mmengine - INFO - Epoch(train) [46][ 920/1345] lr: 1.0000e-02 eta: 7:29:50 time: 0.1894 data_time: 0.0061 memory: 8327 grad_norm: 7.6834 loss: 3.6682 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2347 loss_aux: 1.4335 2023/02/17 15:29:34 - mmengine - INFO - Epoch(train) [46][ 940/1345] lr: 1.0000e-02 eta: 7:29:46 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.7169 loss: 3.4463 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0691 loss_aux: 1.3772 2023/02/17 15:29:38 - mmengine - INFO - Epoch(train) [46][ 960/1345] lr: 1.0000e-02 eta: 7:29:42 time: 0.1901 data_time: 0.0060 memory: 8327 grad_norm: 7.6442 loss: 3.1533 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8621 loss_aux: 1.2912 2023/02/17 15:29:42 - mmengine - INFO - Epoch(train) [46][ 980/1345] lr: 1.0000e-02 eta: 7:29:38 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.8204 loss: 3.7249 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3162 loss_aux: 1.4087 2023/02/17 15:29:45 - mmengine - INFO - Epoch(train) [46][1000/1345] lr: 1.0000e-02 eta: 7:29:34 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.4644 loss: 3.4650 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0879 loss_aux: 1.3771 2023/02/17 15:29:49 - mmengine - INFO - Epoch(train) [46][1020/1345] lr: 1.0000e-02 eta: 7:29:30 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.4565 loss: 3.5612 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1776 loss_aux: 1.3835 2023/02/17 15:29:53 - mmengine - INFO - Epoch(train) [46][1040/1345] lr: 1.0000e-02 eta: 7:29:26 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.8121 loss: 3.8952 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3734 loss_aux: 1.5218 2023/02/17 15:29:57 - mmengine - INFO - Epoch(train) [46][1060/1345] lr: 1.0000e-02 eta: 7:29:22 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.7269 loss: 3.6297 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1526 loss_aux: 1.4771 2023/02/17 15:30:01 - mmengine - INFO - Epoch(train) [46][1080/1345] lr: 1.0000e-02 eta: 7:29:18 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.6610 loss: 3.1147 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8524 loss_aux: 1.2623 2023/02/17 15:30:04 - mmengine - INFO - Epoch(train) [46][1100/1345] lr: 1.0000e-02 eta: 7:29:14 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.5178 loss: 3.2729 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0064 loss_aux: 1.2665 2023/02/17 15:30:08 - mmengine - INFO - Epoch(train) [46][1120/1345] lr: 1.0000e-02 eta: 7:29:10 time: 0.1897 data_time: 0.0061 memory: 8327 grad_norm: 7.7828 loss: 3.2645 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9299 loss_aux: 1.3347 2023/02/17 15:30:12 - mmengine - INFO - Epoch(train) [46][1140/1345] lr: 1.0000e-02 eta: 7:29:06 time: 0.1895 data_time: 0.0061 memory: 8327 grad_norm: 7.6065 loss: 3.8210 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3553 loss_aux: 1.4657 2023/02/17 15:30:16 - mmengine - INFO - Epoch(train) [46][1160/1345] lr: 1.0000e-02 eta: 7:29:02 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.5454 loss: 3.2199 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9678 loss_aux: 1.2521 2023/02/17 15:30:20 - mmengine - INFO - Epoch(train) [46][1180/1345] lr: 1.0000e-02 eta: 7:28:58 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.5675 loss: 3.4019 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0602 loss_aux: 1.3417 2023/02/17 15:30:23 - mmengine - INFO - Epoch(train) [46][1200/1345] lr: 1.0000e-02 eta: 7:28:54 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.9759 loss: 3.9314 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4994 loss_aux: 1.4320 2023/02/17 15:30:27 - mmengine - INFO - Epoch(train) [46][1220/1345] lr: 1.0000e-02 eta: 7:28:50 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.5405 loss: 3.8914 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3686 loss_aux: 1.5228 2023/02/17 15:30:31 - mmengine - INFO - Epoch(train) [46][1240/1345] lr: 1.0000e-02 eta: 7:28:46 time: 0.1905 data_time: 0.0068 memory: 8327 grad_norm: 7.3787 loss: 3.4312 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1053 loss_aux: 1.3260 2023/02/17 15:30:35 - mmengine - INFO - Epoch(train) [46][1260/1345] lr: 1.0000e-02 eta: 7:28:42 time: 0.1919 data_time: 0.0077 memory: 8327 grad_norm: 7.5985 loss: 3.2916 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0097 loss_aux: 1.2819 2023/02/17 15:30:39 - mmengine - INFO - Epoch(train) [46][1280/1345] lr: 1.0000e-02 eta: 7:28:38 time: 0.1900 data_time: 0.0058 memory: 8327 grad_norm: 7.6087 loss: 3.5156 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1059 loss_aux: 1.4096 2023/02/17 15:30:42 - mmengine - INFO - Epoch(train) [46][1300/1345] lr: 1.0000e-02 eta: 7:28:34 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.4430 loss: 3.4388 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0766 loss_aux: 1.3622 2023/02/17 15:30:46 - mmengine - INFO - Epoch(train) [46][1320/1345] lr: 1.0000e-02 eta: 7:28:30 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.4804 loss: 3.1334 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8481 loss_aux: 1.2853 2023/02/17 15:30:50 - mmengine - INFO - Epoch(train) [46][1340/1345] lr: 1.0000e-02 eta: 7:28:27 time: 0.1898 data_time: 0.0067 memory: 8327 grad_norm: 7.7006 loss: 3.0707 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8449 loss_aux: 1.2258 2023/02/17 15:30:51 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:30:51 - mmengine - INFO - Epoch(train) [46][1345/1345] lr: 1.0000e-02 eta: 7:28:25 time: 0.1839 data_time: 0.0067 memory: 8327 grad_norm: 7.6009 loss: 3.3143 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.0061 loss_aux: 1.3082 2023/02/17 15:30:51 - mmengine - INFO - Saving checkpoint at 46 epochs 2023/02/17 15:30:58 - mmengine - INFO - Epoch(train) [47][ 20/1345] lr: 1.0000e-02 eta: 7:28:22 time: 0.2062 data_time: 0.0149 memory: 8327 grad_norm: 7.4718 loss: 3.5846 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2109 loss_aux: 1.3738 2023/02/17 15:31:01 - mmengine - INFO - Epoch(train) [47][ 40/1345] lr: 1.0000e-02 eta: 7:28:18 time: 0.1926 data_time: 0.0042 memory: 8327 grad_norm: 7.6816 loss: 3.4382 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0866 loss_aux: 1.3517 2023/02/17 15:31:05 - mmengine - INFO - Epoch(train) [47][ 60/1345] lr: 1.0000e-02 eta: 7:28:14 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5342 loss: 3.5508 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.1240 loss_aux: 1.4268 2023/02/17 15:31:09 - mmengine - INFO - Epoch(train) [47][ 80/1345] lr: 1.0000e-02 eta: 7:28:10 time: 0.1897 data_time: 0.0064 memory: 8327 grad_norm: 7.4429 loss: 3.6176 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2316 loss_aux: 1.3860 2023/02/17 15:31:13 - mmengine - INFO - Epoch(train) [47][ 100/1345] lr: 1.0000e-02 eta: 7:28:06 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.5690 loss: 3.4631 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.0875 loss_aux: 1.3756 2023/02/17 15:31:17 - mmengine - INFO - Epoch(train) [47][ 120/1345] lr: 1.0000e-02 eta: 7:28:02 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.7457 loss: 3.2460 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9865 loss_aux: 1.2595 2023/02/17 15:31:18 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:31:20 - mmengine - INFO - Epoch(train) [47][ 140/1345] lr: 1.0000e-02 eta: 7:27:58 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.9263 loss: 3.5694 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1783 loss_aux: 1.3911 2023/02/17 15:31:24 - mmengine - INFO - Epoch(train) [47][ 160/1345] lr: 1.0000e-02 eta: 7:27:54 time: 0.1891 data_time: 0.0059 memory: 8327 grad_norm: 7.6646 loss: 3.5561 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1606 loss_aux: 1.3955 2023/02/17 15:31:28 - mmengine - INFO - Epoch(train) [47][ 180/1345] lr: 1.0000e-02 eta: 7:27:50 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.6220 loss: 3.4766 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0936 loss_aux: 1.3830 2023/02/17 15:31:32 - mmengine - INFO - Epoch(train) [47][ 200/1345] lr: 1.0000e-02 eta: 7:27:46 time: 0.1892 data_time: 0.0064 memory: 8327 grad_norm: 7.8613 loss: 3.3935 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0593 loss_aux: 1.3342 2023/02/17 15:31:36 - mmengine - INFO - Epoch(train) [47][ 220/1345] lr: 1.0000e-02 eta: 7:27:42 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.6895 loss: 3.2783 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9203 loss_aux: 1.3580 2023/02/17 15:31:39 - mmengine - INFO - Epoch(train) [47][ 240/1345] lr: 1.0000e-02 eta: 7:27:38 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.5299 loss: 3.2329 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9177 loss_aux: 1.3153 2023/02/17 15:31:43 - mmengine - INFO - Epoch(train) [47][ 260/1345] lr: 1.0000e-02 eta: 7:27:34 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.6781 loss: 3.7800 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3716 loss_aux: 1.4083 2023/02/17 15:31:47 - mmengine - INFO - Epoch(train) [47][ 280/1345] lr: 1.0000e-02 eta: 7:27:30 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.6461 loss: 3.2414 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9932 loss_aux: 1.2482 2023/02/17 15:31:51 - mmengine - INFO - Epoch(train) [47][ 300/1345] lr: 1.0000e-02 eta: 7:27:26 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.5747 loss: 3.3687 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0118 loss_aux: 1.3569 2023/02/17 15:31:55 - mmengine - INFO - Epoch(train) [47][ 320/1345] lr: 1.0000e-02 eta: 7:27:22 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.7957 loss: 3.1588 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8388 loss_aux: 1.3200 2023/02/17 15:31:58 - mmengine - INFO - Epoch(train) [47][ 340/1345] lr: 1.0000e-02 eta: 7:27:19 time: 0.1895 data_time: 0.0062 memory: 8327 grad_norm: 7.5205 loss: 2.8930 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7660 loss_aux: 1.1270 2023/02/17 15:32:02 - mmengine - INFO - Epoch(train) [47][ 360/1345] lr: 1.0000e-02 eta: 7:27:15 time: 0.1901 data_time: 0.0059 memory: 8327 grad_norm: 7.4031 loss: 3.4305 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1065 loss_aux: 1.3240 2023/02/17 15:32:06 - mmengine - INFO - Epoch(train) [47][ 380/1345] lr: 1.0000e-02 eta: 7:27:11 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.7162 loss: 3.4500 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0892 loss_aux: 1.3608 2023/02/17 15:32:10 - mmengine - INFO - Epoch(train) [47][ 400/1345] lr: 1.0000e-02 eta: 7:27:07 time: 0.1895 data_time: 0.0061 memory: 8327 grad_norm: 7.8299 loss: 3.6573 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1806 loss_aux: 1.4767 2023/02/17 15:32:13 - mmengine - INFO - Epoch(train) [47][ 420/1345] lr: 1.0000e-02 eta: 7:27:03 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.7632 loss: 3.5604 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1743 loss_aux: 1.3861 2023/02/17 15:32:17 - mmengine - INFO - Epoch(train) [47][ 440/1345] lr: 1.0000e-02 eta: 7:26:59 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.8884 loss: 3.7643 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2925 loss_aux: 1.4718 2023/02/17 15:32:21 - mmengine - INFO - Epoch(train) [47][ 460/1345] lr: 1.0000e-02 eta: 7:26:55 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.7858 loss: 3.5348 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1624 loss_aux: 1.3723 2023/02/17 15:32:25 - mmengine - INFO - Epoch(train) [47][ 480/1345] lr: 1.0000e-02 eta: 7:26:51 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.5622 loss: 3.6202 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2224 loss_aux: 1.3978 2023/02/17 15:32:29 - mmengine - INFO - Epoch(train) [47][ 500/1345] lr: 1.0000e-02 eta: 7:26:47 time: 0.1902 data_time: 0.0060 memory: 8327 grad_norm: 7.6522 loss: 3.4594 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1149 loss_aux: 1.3445 2023/02/17 15:32:33 - mmengine - INFO - Epoch(train) [47][ 520/1345] lr: 1.0000e-02 eta: 7:26:43 time: 0.1901 data_time: 0.0059 memory: 8327 grad_norm: 7.6668 loss: 3.5088 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0874 loss_aux: 1.4215 2023/02/17 15:32:36 - mmengine - INFO - Epoch(train) [47][ 540/1345] lr: 1.0000e-02 eta: 7:26:39 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.3525 loss: 3.4005 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0935 loss_aux: 1.3070 2023/02/17 15:32:40 - mmengine - INFO - Epoch(train) [47][ 560/1345] lr: 1.0000e-02 eta: 7:26:35 time: 0.1899 data_time: 0.0057 memory: 8327 grad_norm: 7.5785 loss: 3.5927 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2097 loss_aux: 1.3829 2023/02/17 15:32:44 - mmengine - INFO - Epoch(train) [47][ 580/1345] lr: 1.0000e-02 eta: 7:26:31 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.4746 loss: 3.5427 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.1609 loss_aux: 1.3818 2023/02/17 15:32:48 - mmengine - INFO - Epoch(train) [47][ 600/1345] lr: 1.0000e-02 eta: 7:26:27 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7770 loss: 3.4093 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1014 loss_aux: 1.3078 2023/02/17 15:32:51 - mmengine - INFO - Epoch(train) [47][ 620/1345] lr: 1.0000e-02 eta: 7:26:23 time: 0.1896 data_time: 0.0061 memory: 8327 grad_norm: 7.6723 loss: 3.3283 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9666 loss_aux: 1.3618 2023/02/17 15:32:55 - mmengine - INFO - Epoch(train) [47][ 640/1345] lr: 1.0000e-02 eta: 7:26:19 time: 0.1900 data_time: 0.0057 memory: 8327 grad_norm: 7.3788 loss: 3.3333 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0387 loss_aux: 1.2946 2023/02/17 15:32:59 - mmengine - INFO - Epoch(train) [47][ 660/1345] lr: 1.0000e-02 eta: 7:26:15 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.7027 loss: 3.4151 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0659 loss_aux: 1.3492 2023/02/17 15:33:03 - mmengine - INFO - Epoch(train) [47][ 680/1345] lr: 1.0000e-02 eta: 7:26:11 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.3980 loss: 3.3529 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.0280 loss_aux: 1.3249 2023/02/17 15:33:07 - mmengine - INFO - Epoch(train) [47][ 700/1345] lr: 1.0000e-02 eta: 7:26:07 time: 0.1901 data_time: 0.0063 memory: 8327 grad_norm: 7.4501 loss: 3.5094 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1472 loss_aux: 1.3623 2023/02/17 15:33:10 - mmengine - INFO - Epoch(train) [47][ 720/1345] lr: 1.0000e-02 eta: 7:26:03 time: 0.1897 data_time: 0.0063 memory: 8327 grad_norm: 7.6244 loss: 3.3357 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0624 loss_aux: 1.2733 2023/02/17 15:33:14 - mmengine - INFO - Epoch(train) [47][ 740/1345] lr: 1.0000e-02 eta: 7:25:59 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.6925 loss: 4.0201 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5247 loss_aux: 1.4954 2023/02/17 15:33:18 - mmengine - INFO - Epoch(train) [47][ 760/1345] lr: 1.0000e-02 eta: 7:25:55 time: 0.1901 data_time: 0.0059 memory: 8327 grad_norm: 7.6579 loss: 3.4924 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1556 loss_aux: 1.3368 2023/02/17 15:33:22 - mmengine - INFO - Epoch(train) [47][ 780/1345] lr: 1.0000e-02 eta: 7:25:51 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.7727 loss: 3.4488 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0967 loss_aux: 1.3521 2023/02/17 15:33:26 - mmengine - INFO - Epoch(train) [47][ 800/1345] lr: 1.0000e-02 eta: 7:25:47 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.6299 loss: 3.3270 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.0598 loss_aux: 1.2672 2023/02/17 15:33:29 - mmengine - INFO - Epoch(train) [47][ 820/1345] lr: 1.0000e-02 eta: 7:25:43 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.8327 loss: 3.4463 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1450 loss_aux: 1.3013 2023/02/17 15:33:33 - mmengine - INFO - Epoch(train) [47][ 840/1345] lr: 1.0000e-02 eta: 7:25:39 time: 0.1906 data_time: 0.0070 memory: 8327 grad_norm: 7.4168 loss: 3.4275 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1333 loss_aux: 1.2942 2023/02/17 15:33:37 - mmengine - INFO - Epoch(train) [47][ 860/1345] lr: 1.0000e-02 eta: 7:25:35 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.7646 loss: 3.5410 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1819 loss_aux: 1.3591 2023/02/17 15:33:41 - mmengine - INFO - Epoch(train) [47][ 880/1345] lr: 1.0000e-02 eta: 7:25:32 time: 0.1899 data_time: 0.0064 memory: 8327 grad_norm: 7.8125 loss: 3.6648 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2228 loss_aux: 1.4420 2023/02/17 15:33:45 - mmengine - INFO - Epoch(train) [47][ 900/1345] lr: 1.0000e-02 eta: 7:25:28 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.5958 loss: 3.6396 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2479 loss_aux: 1.3916 2023/02/17 15:33:48 - mmengine - INFO - Epoch(train) [47][ 920/1345] lr: 1.0000e-02 eta: 7:25:24 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.7474 loss: 3.3449 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0201 loss_aux: 1.3248 2023/02/17 15:33:52 - mmengine - INFO - Epoch(train) [47][ 940/1345] lr: 1.0000e-02 eta: 7:25:20 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.7022 loss: 3.7281 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.2875 loss_aux: 1.4406 2023/02/17 15:33:56 - mmengine - INFO - Epoch(train) [47][ 960/1345] lr: 1.0000e-02 eta: 7:25:16 time: 0.1901 data_time: 0.0058 memory: 8327 grad_norm: 7.6977 loss: 3.5765 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1694 loss_aux: 1.4071 2023/02/17 15:34:00 - mmengine - INFO - Epoch(train) [47][ 980/1345] lr: 1.0000e-02 eta: 7:25:12 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.7900 loss: 3.4024 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0810 loss_aux: 1.3214 2023/02/17 15:34:04 - mmengine - INFO - Epoch(train) [47][1000/1345] lr: 1.0000e-02 eta: 7:25:08 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 7.5473 loss: 3.4883 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1373 loss_aux: 1.3511 2023/02/17 15:34:07 - mmengine - INFO - Epoch(train) [47][1020/1345] lr: 1.0000e-02 eta: 7:25:04 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.4500 loss: 3.6716 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2685 loss_aux: 1.4031 2023/02/17 15:34:11 - mmengine - INFO - Epoch(train) [47][1040/1345] lr: 1.0000e-02 eta: 7:25:00 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.7623 loss: 3.8442 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3673 loss_aux: 1.4769 2023/02/17 15:34:15 - mmengine - INFO - Epoch(train) [47][1060/1345] lr: 1.0000e-02 eta: 7:24:56 time: 0.1900 data_time: 0.0063 memory: 8327 grad_norm: 7.6852 loss: 3.3396 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9633 loss_aux: 1.3763 2023/02/17 15:34:19 - mmengine - INFO - Epoch(train) [47][1080/1345] lr: 1.0000e-02 eta: 7:24:52 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.8189 loss: 3.1926 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9574 loss_aux: 1.2352 2023/02/17 15:34:23 - mmengine - INFO - Epoch(train) [47][1100/1345] lr: 1.0000e-02 eta: 7:24:48 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.3305 loss: 3.1311 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8352 loss_aux: 1.2959 2023/02/17 15:34:26 - mmengine - INFO - Epoch(train) [47][1120/1345] lr: 1.0000e-02 eta: 7:24:44 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.4233 loss: 3.3778 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0696 loss_aux: 1.3082 2023/02/17 15:34:28 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:34:30 - mmengine - INFO - Epoch(train) [47][1140/1345] lr: 1.0000e-02 eta: 7:24:40 time: 0.1899 data_time: 0.0061 memory: 8327 grad_norm: 7.7228 loss: 3.2319 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9393 loss_aux: 1.2926 2023/02/17 15:34:34 - mmengine - INFO - Epoch(train) [47][1160/1345] lr: 1.0000e-02 eta: 7:24:36 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.7072 loss: 3.8206 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3798 loss_aux: 1.4408 2023/02/17 15:34:38 - mmengine - INFO - Epoch(train) [47][1180/1345] lr: 1.0000e-02 eta: 7:24:32 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.7477 loss: 3.3085 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9842 loss_aux: 1.3243 2023/02/17 15:34:42 - mmengine - INFO - Epoch(train) [47][1200/1345] lr: 1.0000e-02 eta: 7:24:28 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.7027 loss: 3.6322 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2170 loss_aux: 1.4152 2023/02/17 15:34:45 - mmengine - INFO - Epoch(train) [47][1220/1345] lr: 1.0000e-02 eta: 7:24:24 time: 0.1902 data_time: 0.0059 memory: 8327 grad_norm: 7.4244 loss: 3.2811 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9912 loss_aux: 1.2900 2023/02/17 15:34:49 - mmengine - INFO - Epoch(train) [47][1240/1345] lr: 1.0000e-02 eta: 7:24:20 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.7144 loss: 3.4396 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1000 loss_aux: 1.3397 2023/02/17 15:34:53 - mmengine - INFO - Epoch(train) [47][1260/1345] lr: 1.0000e-02 eta: 7:24:16 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.8017 loss: 3.7226 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3398 loss_aux: 1.3828 2023/02/17 15:34:57 - mmengine - INFO - Epoch(train) [47][1280/1345] lr: 1.0000e-02 eta: 7:24:12 time: 0.1902 data_time: 0.0058 memory: 8327 grad_norm: 7.8523 loss: 3.9099 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3979 loss_aux: 1.5120 2023/02/17 15:35:01 - mmengine - INFO - Epoch(train) [47][1300/1345] lr: 1.0000e-02 eta: 7:24:08 time: 0.1902 data_time: 0.0064 memory: 8327 grad_norm: 7.6594 loss: 3.4271 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1046 loss_aux: 1.3226 2023/02/17 15:35:04 - mmengine - INFO - Epoch(train) [47][1320/1345] lr: 1.0000e-02 eta: 7:24:04 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.7264 loss: 3.5251 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1191 loss_aux: 1.4060 2023/02/17 15:35:08 - mmengine - INFO - Epoch(train) [47][1340/1345] lr: 1.0000e-02 eta: 7:24:00 time: 0.1899 data_time: 0.0061 memory: 8327 grad_norm: 7.7041 loss: 3.4847 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.1016 loss_aux: 1.3831 2023/02/17 15:35:09 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:35:09 - mmengine - INFO - Epoch(train) [47][1345/1345] lr: 1.0000e-02 eta: 7:23:59 time: 0.1838 data_time: 0.0061 memory: 8327 grad_norm: 7.6535 loss: 3.8978 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.3813 loss_aux: 1.5165 2023/02/17 15:35:09 - mmengine - INFO - Saving checkpoint at 47 epochs 2023/02/17 15:35:16 - mmengine - INFO - Epoch(train) [48][ 20/1345] lr: 1.0000e-02 eta: 7:23:56 time: 0.2048 data_time: 0.0160 memory: 8327 grad_norm: 7.5287 loss: 4.0007 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4897 loss_aux: 1.5109 2023/02/17 15:35:20 - mmengine - INFO - Epoch(train) [48][ 40/1345] lr: 1.0000e-02 eta: 7:23:52 time: 0.1909 data_time: 0.0040 memory: 8327 grad_norm: 7.6358 loss: 3.5428 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1630 loss_aux: 1.3798 2023/02/17 15:35:23 - mmengine - INFO - Epoch(train) [48][ 60/1345] lr: 1.0000e-02 eta: 7:23:48 time: 0.1896 data_time: 0.0061 memory: 8327 grad_norm: 7.3945 loss: 3.3129 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0494 loss_aux: 1.2635 2023/02/17 15:35:27 - mmengine - INFO - Epoch(train) [48][ 80/1345] lr: 1.0000e-02 eta: 7:23:44 time: 0.1895 data_time: 0.0061 memory: 8327 grad_norm: 7.6333 loss: 3.0949 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8438 loss_aux: 1.2511 2023/02/17 15:35:31 - mmengine - INFO - Epoch(train) [48][ 100/1345] lr: 1.0000e-02 eta: 7:23:40 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.5490 loss: 3.4048 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.0429 loss_aux: 1.3619 2023/02/17 15:35:35 - mmengine - INFO - Epoch(train) [48][ 120/1345] lr: 1.0000e-02 eta: 7:23:36 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5695 loss: 3.8489 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3903 loss_aux: 1.4586 2023/02/17 15:35:38 - mmengine - INFO - Epoch(train) [48][ 140/1345] lr: 1.0000e-02 eta: 7:23:32 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.8848 loss: 3.4190 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.0866 loss_aux: 1.3325 2023/02/17 15:35:42 - mmengine - INFO - Epoch(train) [48][ 160/1345] lr: 1.0000e-02 eta: 7:23:28 time: 0.1904 data_time: 0.0057 memory: 8327 grad_norm: 7.4446 loss: 3.7094 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2634 loss_aux: 1.4459 2023/02/17 15:35:46 - mmengine - INFO - Epoch(train) [48][ 180/1345] lr: 1.0000e-02 eta: 7:23:24 time: 0.1901 data_time: 0.0061 memory: 8327 grad_norm: 7.6448 loss: 3.5443 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1090 loss_aux: 1.4352 2023/02/17 15:35:50 - mmengine - INFO - Epoch(train) [48][ 200/1345] lr: 1.0000e-02 eta: 7:23:20 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.4516 loss: 3.5079 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1692 loss_aux: 1.3387 2023/02/17 15:35:54 - mmengine - INFO - Epoch(train) [48][ 220/1345] lr: 1.0000e-02 eta: 7:23:16 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.5748 loss: 3.4976 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0563 loss_aux: 1.4413 2023/02/17 15:35:58 - mmengine - INFO - Epoch(train) [48][ 240/1345] lr: 1.0000e-02 eta: 7:23:12 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.7398 loss: 3.5094 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1514 loss_aux: 1.3580 2023/02/17 15:36:01 - mmengine - INFO - Epoch(train) [48][ 260/1345] lr: 1.0000e-02 eta: 7:23:08 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.7513 loss: 3.5051 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1345 loss_aux: 1.3706 2023/02/17 15:36:05 - mmengine - INFO - Epoch(train) [48][ 280/1345] lr: 1.0000e-02 eta: 7:23:04 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.6809 loss: 3.3641 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0486 loss_aux: 1.3155 2023/02/17 15:36:09 - mmengine - INFO - Epoch(train) [48][ 300/1345] lr: 1.0000e-02 eta: 7:23:00 time: 0.1899 data_time: 0.0057 memory: 8327 grad_norm: 7.6475 loss: 3.4509 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0567 loss_aux: 1.3942 2023/02/17 15:36:13 - mmengine - INFO - Epoch(train) [48][ 320/1345] lr: 1.0000e-02 eta: 7:22:56 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 7.9006 loss: 3.4556 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1311 loss_aux: 1.3245 2023/02/17 15:36:17 - mmengine - INFO - Epoch(train) [48][ 340/1345] lr: 1.0000e-02 eta: 7:22:53 time: 0.1901 data_time: 0.0057 memory: 8327 grad_norm: 7.4706 loss: 3.6320 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2392 loss_aux: 1.3927 2023/02/17 15:36:20 - mmengine - INFO - Epoch(train) [48][ 360/1345] lr: 1.0000e-02 eta: 7:22:49 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.5709 loss: 3.4090 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0620 loss_aux: 1.3470 2023/02/17 15:36:24 - mmengine - INFO - Epoch(train) [48][ 380/1345] lr: 1.0000e-02 eta: 7:22:45 time: 0.1891 data_time: 0.0056 memory: 8327 grad_norm: 7.6642 loss: 3.5399 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1683 loss_aux: 1.3716 2023/02/17 15:36:28 - mmengine - INFO - Epoch(train) [48][ 400/1345] lr: 1.0000e-02 eta: 7:22:42 time: 0.2096 data_time: 0.0259 memory: 8327 grad_norm: 7.6032 loss: 3.4518 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1087 loss_aux: 1.3431 2023/02/17 15:36:32 - mmengine - INFO - Epoch(train) [48][ 420/1345] lr: 1.0000e-02 eta: 7:22:38 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 8.0119 loss: 3.6651 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2366 loss_aux: 1.4285 2023/02/17 15:36:36 - mmengine - INFO - Epoch(train) [48][ 440/1345] lr: 1.0000e-02 eta: 7:22:34 time: 0.1900 data_time: 0.0058 memory: 8327 grad_norm: 7.5086 loss: 3.1502 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9553 loss_aux: 1.1949 2023/02/17 15:36:40 - mmengine - INFO - Epoch(train) [48][ 460/1345] lr: 1.0000e-02 eta: 7:22:30 time: 0.1901 data_time: 0.0057 memory: 8327 grad_norm: 7.6596 loss: 3.5831 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1766 loss_aux: 1.4064 2023/02/17 15:36:43 - mmengine - INFO - Epoch(train) [48][ 480/1345] lr: 1.0000e-02 eta: 7:22:26 time: 0.1896 data_time: 0.0061 memory: 8327 grad_norm: 7.6374 loss: 3.2502 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 1.9447 loss_aux: 1.3055 2023/02/17 15:36:47 - mmengine - INFO - Epoch(train) [48][ 500/1345] lr: 1.0000e-02 eta: 7:22:22 time: 0.1894 data_time: 0.0061 memory: 8327 grad_norm: 7.6904 loss: 3.2608 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9529 loss_aux: 1.3079 2023/02/17 15:36:51 - mmengine - INFO - Epoch(train) [48][ 520/1345] lr: 1.0000e-02 eta: 7:22:18 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.6654 loss: 3.0379 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8216 loss_aux: 1.2164 2023/02/17 15:36:55 - mmengine - INFO - Epoch(train) [48][ 540/1345] lr: 1.0000e-02 eta: 7:22:14 time: 0.1902 data_time: 0.0059 memory: 8327 grad_norm: 7.5494 loss: 3.8607 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4168 loss_aux: 1.4439 2023/02/17 15:36:59 - mmengine - INFO - Epoch(train) [48][ 560/1345] lr: 1.0000e-02 eta: 7:22:10 time: 0.1894 data_time: 0.0061 memory: 8327 grad_norm: 7.5976 loss: 3.4876 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1199 loss_aux: 1.3676 2023/02/17 15:37:02 - mmengine - INFO - Epoch(train) [48][ 580/1345] lr: 1.0000e-02 eta: 7:22:06 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.7488 loss: 3.0433 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7861 loss_aux: 1.2572 2023/02/17 15:37:06 - mmengine - INFO - Epoch(train) [48][ 600/1345] lr: 1.0000e-02 eta: 7:22:02 time: 0.1915 data_time: 0.0081 memory: 8327 grad_norm: 7.3213 loss: 3.4562 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1330 loss_aux: 1.3232 2023/02/17 15:37:10 - mmengine - INFO - Epoch(train) [48][ 620/1345] lr: 1.0000e-02 eta: 7:21:58 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.6879 loss: 3.7295 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2910 loss_aux: 1.4385 2023/02/17 15:37:14 - mmengine - INFO - Epoch(train) [48][ 640/1345] lr: 1.0000e-02 eta: 7:21:54 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.9091 loss: 3.2955 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0178 loss_aux: 1.2777 2023/02/17 15:37:18 - mmengine - INFO - Epoch(train) [48][ 660/1345] lr: 1.0000e-02 eta: 7:21:50 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.9251 loss: 3.5075 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1602 loss_aux: 1.3473 2023/02/17 15:37:21 - mmengine - INFO - Epoch(train) [48][ 680/1345] lr: 1.0000e-02 eta: 7:21:46 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.6805 loss: 3.1623 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8948 loss_aux: 1.2675 2023/02/17 15:37:25 - mmengine - INFO - Epoch(train) [48][ 700/1345] lr: 1.0000e-02 eta: 7:21:42 time: 0.1898 data_time: 0.0060 memory: 8327 grad_norm: 7.8830 loss: 3.9131 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4011 loss_aux: 1.5120 2023/02/17 15:37:29 - mmengine - INFO - Epoch(train) [48][ 720/1345] lr: 1.0000e-02 eta: 7:21:38 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5287 loss: 3.2015 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9264 loss_aux: 1.2751 2023/02/17 15:37:33 - mmengine - INFO - Epoch(train) [48][ 740/1345] lr: 1.0000e-02 eta: 7:21:34 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.7937 loss: 3.6452 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2760 loss_aux: 1.3692 2023/02/17 15:37:37 - mmengine - INFO - Epoch(train) [48][ 760/1345] lr: 1.0000e-02 eta: 7:21:30 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.8587 loss: 3.7435 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2936 loss_aux: 1.4499 2023/02/17 15:37:40 - mmengine - INFO - Epoch(train) [48][ 780/1345] lr: 1.0000e-02 eta: 7:21:26 time: 0.1898 data_time: 0.0061 memory: 8327 grad_norm: 7.4666 loss: 3.5127 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1357 loss_aux: 1.3770 2023/02/17 15:37:41 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:37:44 - mmengine - INFO - Epoch(train) [48][ 800/1345] lr: 1.0000e-02 eta: 7:21:22 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.6218 loss: 3.7304 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2962 loss_aux: 1.4341 2023/02/17 15:37:48 - mmengine - INFO - Epoch(train) [48][ 820/1345] lr: 1.0000e-02 eta: 7:21:18 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.4025 loss: 3.4161 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0403 loss_aux: 1.3759 2023/02/17 15:37:52 - mmengine - INFO - Epoch(train) [48][ 840/1345] lr: 1.0000e-02 eta: 7:21:14 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.5712 loss: 3.6959 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2791 loss_aux: 1.4168 2023/02/17 15:37:56 - mmengine - INFO - Epoch(train) [48][ 860/1345] lr: 1.0000e-02 eta: 7:21:10 time: 0.1904 data_time: 0.0064 memory: 8327 grad_norm: 7.7287 loss: 3.3592 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0556 loss_aux: 1.3036 2023/02/17 15:37:59 - mmengine - INFO - Epoch(train) [48][ 880/1345] lr: 1.0000e-02 eta: 7:21:07 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.7048 loss: 3.4181 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0873 loss_aux: 1.3309 2023/02/17 15:38:03 - mmengine - INFO - Epoch(train) [48][ 900/1345] lr: 1.0000e-02 eta: 7:21:03 time: 0.1892 data_time: 0.0059 memory: 8327 grad_norm: 7.6578 loss: 3.3497 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0529 loss_aux: 1.2968 2023/02/17 15:38:07 - mmengine - INFO - Epoch(train) [48][ 920/1345] lr: 1.0000e-02 eta: 7:20:59 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.9033 loss: 3.5537 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1988 loss_aux: 1.3550 2023/02/17 15:38:11 - mmengine - INFO - Epoch(train) [48][ 940/1345] lr: 1.0000e-02 eta: 7:20:55 time: 0.1909 data_time: 0.0067 memory: 8327 grad_norm: 7.7563 loss: 3.6945 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2631 loss_aux: 1.4314 2023/02/17 15:38:15 - mmengine - INFO - Epoch(train) [48][ 960/1345] lr: 1.0000e-02 eta: 7:20:51 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.5985 loss: 3.2844 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9608 loss_aux: 1.3236 2023/02/17 15:38:18 - mmengine - INFO - Epoch(train) [48][ 980/1345] lr: 1.0000e-02 eta: 7:20:47 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.6266 loss: 3.7339 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3154 loss_aux: 1.4185 2023/02/17 15:38:22 - mmengine - INFO - Epoch(train) [48][1000/1345] lr: 1.0000e-02 eta: 7:20:43 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.4691 loss: 3.1644 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9532 loss_aux: 1.2112 2023/02/17 15:38:26 - mmengine - INFO - Epoch(train) [48][1020/1345] lr: 1.0000e-02 eta: 7:20:39 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.8642 loss: 3.7600 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3323 loss_aux: 1.4277 2023/02/17 15:38:30 - mmengine - INFO - Epoch(train) [48][1040/1345] lr: 1.0000e-02 eta: 7:20:35 time: 0.1904 data_time: 0.0062 memory: 8327 grad_norm: 7.6210 loss: 3.5536 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1434 loss_aux: 1.4102 2023/02/17 15:38:34 - mmengine - INFO - Epoch(train) [48][1060/1345] lr: 1.0000e-02 eta: 7:20:31 time: 0.1913 data_time: 0.0057 memory: 8327 grad_norm: 7.6093 loss: 3.5848 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2003 loss_aux: 1.3844 2023/02/17 15:38:37 - mmengine - INFO - Epoch(train) [48][1080/1345] lr: 1.0000e-02 eta: 7:20:27 time: 0.1909 data_time: 0.0057 memory: 8327 grad_norm: 7.6948 loss: 3.2831 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.0023 loss_aux: 1.2809 2023/02/17 15:38:41 - mmengine - INFO - Epoch(train) [48][1100/1345] lr: 1.0000e-02 eta: 7:20:23 time: 0.1897 data_time: 0.0061 memory: 8327 grad_norm: 7.6772 loss: 3.3064 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0040 loss_aux: 1.3024 2023/02/17 15:38:45 - mmengine - INFO - Epoch(train) [48][1120/1345] lr: 1.0000e-02 eta: 7:20:19 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.6584 loss: 3.2759 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9881 loss_aux: 1.2878 2023/02/17 15:38:49 - mmengine - INFO - Epoch(train) [48][1140/1345] lr: 1.0000e-02 eta: 7:20:15 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.7419 loss: 4.0202 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4653 loss_aux: 1.5549 2023/02/17 15:38:53 - mmengine - INFO - Epoch(train) [48][1160/1345] lr: 1.0000e-02 eta: 7:20:11 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.5780 loss: 3.2880 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9410 loss_aux: 1.3471 2023/02/17 15:38:56 - mmengine - INFO - Epoch(train) [48][1180/1345] lr: 1.0000e-02 eta: 7:20:07 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.5908 loss: 3.6792 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2762 loss_aux: 1.4030 2023/02/17 15:39:00 - mmengine - INFO - Epoch(train) [48][1200/1345] lr: 1.0000e-02 eta: 7:20:03 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.5760 loss: 3.4629 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1460 loss_aux: 1.3169 2023/02/17 15:39:04 - mmengine - INFO - Epoch(train) [48][1220/1345] lr: 1.0000e-02 eta: 7:19:59 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.7336 loss: 3.5263 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1596 loss_aux: 1.3667 2023/02/17 15:39:08 - mmengine - INFO - Epoch(train) [48][1240/1345] lr: 1.0000e-02 eta: 7:19:55 time: 0.1893 data_time: 0.0060 memory: 8327 grad_norm: 7.7165 loss: 3.2152 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9338 loss_aux: 1.2814 2023/02/17 15:39:12 - mmengine - INFO - Epoch(train) [48][1260/1345] lr: 1.0000e-02 eta: 7:19:52 time: 0.2095 data_time: 0.0260 memory: 8327 grad_norm: 7.7850 loss: 3.4757 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1805 loss_aux: 1.2952 2023/02/17 15:39:16 - mmengine - INFO - Epoch(train) [48][1280/1345] lr: 1.0000e-02 eta: 7:19:48 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.6850 loss: 3.3464 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9970 loss_aux: 1.3494 2023/02/17 15:39:20 - mmengine - INFO - Epoch(train) [48][1300/1345] lr: 1.0000e-02 eta: 7:19:44 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.5112 loss: 3.3959 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0465 loss_aux: 1.3494 2023/02/17 15:39:24 - mmengine - INFO - Epoch(train) [48][1320/1345] lr: 1.0000e-02 eta: 7:19:41 time: 0.2102 data_time: 0.0262 memory: 8327 grad_norm: 7.6209 loss: 3.8584 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3524 loss_aux: 1.5059 2023/02/17 15:39:28 - mmengine - INFO - Epoch(train) [48][1340/1345] lr: 1.0000e-02 eta: 7:19:37 time: 0.1901 data_time: 0.0060 memory: 8327 grad_norm: 7.6256 loss: 3.3657 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.0268 loss_aux: 1.3389 2023/02/17 15:39:28 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:39:28 - mmengine - INFO - Epoch(train) [48][1345/1345] lr: 1.0000e-02 eta: 7:19:36 time: 0.1840 data_time: 0.0060 memory: 8327 grad_norm: 7.4494 loss: 3.4808 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.1382 loss_aux: 1.3426 2023/02/17 15:39:28 - mmengine - INFO - Saving checkpoint at 48 epochs 2023/02/17 15:39:35 - mmengine - INFO - Epoch(train) [49][ 20/1345] lr: 1.0000e-02 eta: 7:19:33 time: 0.2077 data_time: 0.0167 memory: 8327 grad_norm: 7.5633 loss: 3.1803 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9018 loss_aux: 1.2785 2023/02/17 15:39:39 - mmengine - INFO - Epoch(train) [49][ 40/1345] lr: 1.0000e-02 eta: 7:19:29 time: 0.1909 data_time: 0.0040 memory: 8327 grad_norm: 7.5002 loss: 3.3675 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0376 loss_aux: 1.3298 2023/02/17 15:39:43 - mmengine - INFO - Epoch(train) [49][ 60/1345] lr: 1.0000e-02 eta: 7:19:25 time: 0.1899 data_time: 0.0061 memory: 8327 grad_norm: 7.6706 loss: 3.1060 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8757 loss_aux: 1.2303 2023/02/17 15:39:47 - mmengine - INFO - Epoch(train) [49][ 80/1345] lr: 1.0000e-02 eta: 7:19:21 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.8195 loss: 3.9025 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4487 loss_aux: 1.4537 2023/02/17 15:39:51 - mmengine - INFO - Epoch(train) [49][ 100/1345] lr: 1.0000e-02 eta: 7:19:17 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.7640 loss: 3.5604 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1685 loss_aux: 1.3920 2023/02/17 15:39:54 - mmengine - INFO - Epoch(train) [49][ 120/1345] lr: 1.0000e-02 eta: 7:19:13 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 8.0470 loss: 3.2336 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9817 loss_aux: 1.2518 2023/02/17 15:39:58 - mmengine - INFO - Epoch(train) [49][ 140/1345] lr: 1.0000e-02 eta: 7:19:09 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.8049 loss: 3.6131 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2397 loss_aux: 1.3734 2023/02/17 15:40:02 - mmengine - INFO - Epoch(train) [49][ 160/1345] lr: 1.0000e-02 eta: 7:19:05 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.7431 loss: 3.5686 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1493 loss_aux: 1.4193 2023/02/17 15:40:06 - mmengine - INFO - Epoch(train) [49][ 180/1345] lr: 1.0000e-02 eta: 7:19:01 time: 0.1899 data_time: 0.0058 memory: 8327 grad_norm: 7.5120 loss: 3.2830 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9846 loss_aux: 1.2984 2023/02/17 15:40:10 - mmengine - INFO - Epoch(train) [49][ 200/1345] lr: 1.0000e-02 eta: 7:18:57 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.6216 loss: 3.5456 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1500 loss_aux: 1.3957 2023/02/17 15:40:13 - mmengine - INFO - Epoch(train) [49][ 220/1345] lr: 1.0000e-02 eta: 7:18:53 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.6418 loss: 3.4362 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0604 loss_aux: 1.3758 2023/02/17 15:40:17 - mmengine - INFO - Epoch(train) [49][ 240/1345] lr: 1.0000e-02 eta: 7:18:49 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.6763 loss: 3.4063 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0697 loss_aux: 1.3366 2023/02/17 15:40:21 - mmengine - INFO - Epoch(train) [49][ 260/1345] lr: 1.0000e-02 eta: 7:18:45 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.5347 loss: 3.3649 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0325 loss_aux: 1.3324 2023/02/17 15:40:25 - mmengine - INFO - Epoch(train) [49][ 280/1345] lr: 1.0000e-02 eta: 7:18:41 time: 0.1900 data_time: 0.0059 memory: 8327 grad_norm: 7.8313 loss: 3.7344 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2560 loss_aux: 1.4784 2023/02/17 15:40:29 - mmengine - INFO - Epoch(train) [49][ 300/1345] lr: 1.0000e-02 eta: 7:18:38 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.8537 loss: 3.5097 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1345 loss_aux: 1.3752 2023/02/17 15:40:32 - mmengine - INFO - Epoch(train) [49][ 320/1345] lr: 1.0000e-02 eta: 7:18:34 time: 0.1907 data_time: 0.0074 memory: 8327 grad_norm: 7.6760 loss: 3.6607 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2071 loss_aux: 1.4536 2023/02/17 15:40:36 - mmengine - INFO - Epoch(train) [49][ 340/1345] lr: 1.0000e-02 eta: 7:18:30 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.5837 loss: 3.4512 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0544 loss_aux: 1.3968 2023/02/17 15:40:40 - mmengine - INFO - Epoch(train) [49][ 360/1345] lr: 1.0000e-02 eta: 7:18:26 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.9357 loss: 3.6911 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2613 loss_aux: 1.4298 2023/02/17 15:40:44 - mmengine - INFO - Epoch(train) [49][ 380/1345] lr: 1.0000e-02 eta: 7:18:22 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.6861 loss: 3.5370 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2040 loss_aux: 1.3330 2023/02/17 15:40:47 - mmengine - INFO - Epoch(train) [49][ 400/1345] lr: 1.0000e-02 eta: 7:18:18 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.7049 loss: 3.4383 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0831 loss_aux: 1.3552 2023/02/17 15:40:51 - mmengine - INFO - Epoch(train) [49][ 420/1345] lr: 1.0000e-02 eta: 7:18:14 time: 0.1902 data_time: 0.0065 memory: 8327 grad_norm: 7.6476 loss: 3.4887 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1010 loss_aux: 1.3877 2023/02/17 15:40:55 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:40:55 - mmengine - INFO - Epoch(train) [49][ 440/1345] lr: 1.0000e-02 eta: 7:18:10 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.6806 loss: 3.3842 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0545 loss_aux: 1.3297 2023/02/17 15:40:59 - mmengine - INFO - Epoch(train) [49][ 460/1345] lr: 1.0000e-02 eta: 7:18:06 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.8247 loss: 3.4430 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1083 loss_aux: 1.3347 2023/02/17 15:41:03 - mmengine - INFO - Epoch(train) [49][ 480/1345] lr: 1.0000e-02 eta: 7:18:02 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.4816 loss: 3.4445 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0934 loss_aux: 1.3510 2023/02/17 15:41:06 - mmengine - INFO - Epoch(train) [49][ 500/1345] lr: 1.0000e-02 eta: 7:17:58 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.5997 loss: 3.1562 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9111 loss_aux: 1.2451 2023/02/17 15:41:10 - mmengine - INFO - Epoch(train) [49][ 520/1345] lr: 1.0000e-02 eta: 7:17:54 time: 0.1899 data_time: 0.0058 memory: 8327 grad_norm: 7.8631 loss: 3.9568 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4329 loss_aux: 1.5239 2023/02/17 15:41:14 - mmengine - INFO - Epoch(train) [49][ 540/1345] lr: 1.0000e-02 eta: 7:17:50 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.5096 loss: 3.4460 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0524 loss_aux: 1.3935 2023/02/17 15:41:18 - mmengine - INFO - Epoch(train) [49][ 560/1345] lr: 1.0000e-02 eta: 7:17:46 time: 0.1899 data_time: 0.0060 memory: 8327 grad_norm: 7.5612 loss: 3.1948 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9421 loss_aux: 1.2528 2023/02/17 15:41:22 - mmengine - INFO - Epoch(train) [49][ 580/1345] lr: 1.0000e-02 eta: 7:17:42 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.8117 loss: 3.2996 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9662 loss_aux: 1.3335 2023/02/17 15:41:25 - mmengine - INFO - Epoch(train) [49][ 600/1345] lr: 1.0000e-02 eta: 7:17:38 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 8.0186 loss: 3.5226 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1713 loss_aux: 1.3513 2023/02/17 15:41:29 - mmengine - INFO - Epoch(train) [49][ 620/1345] lr: 1.0000e-02 eta: 7:17:34 time: 0.1905 data_time: 0.0065 memory: 8327 grad_norm: 7.7344 loss: 3.4119 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1093 loss_aux: 1.3026 2023/02/17 15:41:33 - mmengine - INFO - Epoch(train) [49][ 640/1345] lr: 1.0000e-02 eta: 7:17:30 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.7698 loss: 3.5212 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1355 loss_aux: 1.3857 2023/02/17 15:41:37 - mmengine - INFO - Epoch(train) [49][ 660/1345] lr: 1.0000e-02 eta: 7:17:26 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.8041 loss: 3.2968 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0372 loss_aux: 1.2596 2023/02/17 15:41:41 - mmengine - INFO - Epoch(train) [49][ 680/1345] lr: 1.0000e-02 eta: 7:17:22 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5815 loss: 3.3009 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0410 loss_aux: 1.2600 2023/02/17 15:41:44 - mmengine - INFO - Epoch(train) [49][ 700/1345] lr: 1.0000e-02 eta: 7:17:18 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.4472 loss: 3.7979 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3170 loss_aux: 1.4810 2023/02/17 15:41:48 - mmengine - INFO - Epoch(train) [49][ 720/1345] lr: 1.0000e-02 eta: 7:17:14 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.7949 loss: 3.3858 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0660 loss_aux: 1.3197 2023/02/17 15:41:52 - mmengine - INFO - Epoch(train) [49][ 740/1345] lr: 1.0000e-02 eta: 7:17:11 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.5320 loss: 3.4829 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.1137 loss_aux: 1.3692 2023/02/17 15:41:56 - mmengine - INFO - Epoch(train) [49][ 760/1345] lr: 1.0000e-02 eta: 7:17:07 time: 0.1902 data_time: 0.0064 memory: 8327 grad_norm: 7.6023 loss: 3.3347 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9972 loss_aux: 1.3375 2023/02/17 15:42:00 - mmengine - INFO - Epoch(train) [49][ 780/1345] lr: 1.0000e-02 eta: 7:17:03 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.3618 loss: 3.3011 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0153 loss_aux: 1.2858 2023/02/17 15:42:03 - mmengine - INFO - Epoch(train) [49][ 800/1345] lr: 1.0000e-02 eta: 7:16:59 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.4927 loss: 3.3016 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0168 loss_aux: 1.2848 2023/02/17 15:42:07 - mmengine - INFO - Epoch(train) [49][ 820/1345] lr: 1.0000e-02 eta: 7:16:55 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.5143 loss: 3.4695 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1097 loss_aux: 1.3598 2023/02/17 15:42:11 - mmengine - INFO - Epoch(train) [49][ 840/1345] lr: 1.0000e-02 eta: 7:16:51 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.8422 loss: 3.5772 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.1801 loss_aux: 1.3972 2023/02/17 15:42:15 - mmengine - INFO - Epoch(train) [49][ 860/1345] lr: 1.0000e-02 eta: 7:16:47 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.6148 loss: 3.3153 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9962 loss_aux: 1.3191 2023/02/17 15:42:19 - mmengine - INFO - Epoch(train) [49][ 880/1345] lr: 1.0000e-02 eta: 7:16:43 time: 0.1901 data_time: 0.0058 memory: 8327 grad_norm: 7.6909 loss: 3.4157 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0988 loss_aux: 1.3169 2023/02/17 15:42:22 - mmengine - INFO - Epoch(train) [49][ 900/1345] lr: 1.0000e-02 eta: 7:16:39 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.4362 loss: 3.1074 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8927 loss_aux: 1.2147 2023/02/17 15:42:26 - mmengine - INFO - Epoch(train) [49][ 920/1345] lr: 1.0000e-02 eta: 7:16:35 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.6437 loss: 3.3916 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0691 loss_aux: 1.3225 2023/02/17 15:42:30 - mmengine - INFO - Epoch(train) [49][ 940/1345] lr: 1.0000e-02 eta: 7:16:31 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.9798 loss: 3.7848 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3552 loss_aux: 1.4296 2023/02/17 15:42:34 - mmengine - INFO - Epoch(train) [49][ 960/1345] lr: 1.0000e-02 eta: 7:16:27 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.6322 loss: 3.4594 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1168 loss_aux: 1.3426 2023/02/17 15:42:38 - mmengine - INFO - Epoch(train) [49][ 980/1345] lr: 1.0000e-02 eta: 7:16:23 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.8284 loss: 3.6910 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3039 loss_aux: 1.3872 2023/02/17 15:42:41 - mmengine - INFO - Epoch(train) [49][1000/1345] lr: 1.0000e-02 eta: 7:16:19 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.6908 loss: 3.2463 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9936 loss_aux: 1.2526 2023/02/17 15:42:45 - mmengine - INFO - Epoch(train) [49][1020/1345] lr: 1.0000e-02 eta: 7:16:15 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.5429 loss: 3.5653 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1479 loss_aux: 1.4174 2023/02/17 15:42:49 - mmengine - INFO - Epoch(train) [49][1040/1345] lr: 1.0000e-02 eta: 7:16:11 time: 0.1912 data_time: 0.0059 memory: 8327 grad_norm: 7.5331 loss: 3.8065 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3288 loss_aux: 1.4777 2023/02/17 15:42:53 - mmengine - INFO - Epoch(train) [49][1060/1345] lr: 1.0000e-02 eta: 7:16:07 time: 0.1934 data_time: 0.0057 memory: 8327 grad_norm: 7.5181 loss: 3.4915 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0987 loss_aux: 1.3929 2023/02/17 15:42:57 - mmengine - INFO - Epoch(train) [49][1080/1345] lr: 1.0000e-02 eta: 7:16:03 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.6716 loss: 3.4940 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1822 loss_aux: 1.3118 2023/02/17 15:43:00 - mmengine - INFO - Epoch(train) [49][1100/1345] lr: 1.0000e-02 eta: 7:16:00 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.7391 loss: 3.4797 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.1345 loss_aux: 1.3453 2023/02/17 15:43:04 - mmengine - INFO - Epoch(train) [49][1120/1345] lr: 1.0000e-02 eta: 7:15:56 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.8310 loss: 3.6110 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2051 loss_aux: 1.4059 2023/02/17 15:43:08 - mmengine - INFO - Epoch(train) [49][1140/1345] lr: 1.0000e-02 eta: 7:15:52 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.7419 loss: 3.1838 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8949 loss_aux: 1.2889 2023/02/17 15:43:12 - mmengine - INFO - Epoch(train) [49][1160/1345] lr: 1.0000e-02 eta: 7:15:48 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.5792 loss: 3.9988 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4520 loss_aux: 1.5468 2023/02/17 15:43:16 - mmengine - INFO - Epoch(train) [49][1180/1345] lr: 1.0000e-02 eta: 7:15:44 time: 0.1902 data_time: 0.0067 memory: 8327 grad_norm: 7.5881 loss: 3.4270 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1153 loss_aux: 1.3117 2023/02/17 15:43:19 - mmengine - INFO - Epoch(train) [49][1200/1345] lr: 1.0000e-02 eta: 7:15:40 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5546 loss: 2.8290 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6480 loss_aux: 1.1811 2023/02/17 15:43:23 - mmengine - INFO - Epoch(train) [49][1220/1345] lr: 1.0000e-02 eta: 7:15:36 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.3490 loss: 3.3715 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0952 loss_aux: 1.2762 2023/02/17 15:43:27 - mmengine - INFO - Epoch(train) [49][1240/1345] lr: 1.0000e-02 eta: 7:15:32 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.6388 loss: 3.5131 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1411 loss_aux: 1.3720 2023/02/17 15:43:31 - mmengine - INFO - Epoch(train) [49][1260/1345] lr: 1.0000e-02 eta: 7:15:28 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.5440 loss: 3.0349 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7810 loss_aux: 1.2539 2023/02/17 15:43:35 - mmengine - INFO - Epoch(train) [49][1280/1345] lr: 1.0000e-02 eta: 7:15:24 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.6219 loss: 3.5120 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1649 loss_aux: 1.3471 2023/02/17 15:43:38 - mmengine - INFO - Epoch(train) [49][1300/1345] lr: 1.0000e-02 eta: 7:15:20 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5408 loss: 3.5387 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1341 loss_aux: 1.4046 2023/02/17 15:43:42 - mmengine - INFO - Epoch(train) [49][1320/1345] lr: 1.0000e-02 eta: 7:15:16 time: 0.1892 data_time: 0.0057 memory: 8327 grad_norm: 8.0572 loss: 3.5831 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2310 loss_aux: 1.3521 2023/02/17 15:43:46 - mmengine - INFO - Epoch(train) [49][1340/1345] lr: 1.0000e-02 eta: 7:15:12 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.6441 loss: 3.5601 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1583 loss_aux: 1.4017 2023/02/17 15:43:47 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:43:47 - mmengine - INFO - Epoch(train) [49][1345/1345] lr: 1.0000e-02 eta: 7:15:11 time: 0.1842 data_time: 0.0063 memory: 8327 grad_norm: 7.5006 loss: 3.8567 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.3774 loss_aux: 1.4792 2023/02/17 15:43:47 - mmengine - INFO - Saving checkpoint at 49 epochs 2023/02/17 15:43:54 - mmengine - INFO - Epoch(train) [50][ 20/1345] lr: 1.0000e-02 eta: 7:15:08 time: 0.2088 data_time: 0.0148 memory: 8327 grad_norm: 7.4843 loss: 3.5416 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1353 loss_aux: 1.4062 2023/02/17 15:43:58 - mmengine - INFO - Epoch(train) [50][ 40/1345] lr: 1.0000e-02 eta: 7:15:04 time: 0.1923 data_time: 0.0059 memory: 8327 grad_norm: 7.6171 loss: 3.1796 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9256 loss_aux: 1.2539 2023/02/17 15:44:01 - mmengine - INFO - Epoch(train) [50][ 60/1345] lr: 1.0000e-02 eta: 7:15:00 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.5638 loss: 3.8994 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3912 loss_aux: 1.5082 2023/02/17 15:44:05 - mmengine - INFO - Epoch(train) [50][ 80/1345] lr: 1.0000e-02 eta: 7:14:56 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.3263 loss: 3.6774 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2623 loss_aux: 1.4151 2023/02/17 15:44:08 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:44:09 - mmengine - INFO - Epoch(train) [50][ 100/1345] lr: 1.0000e-02 eta: 7:14:52 time: 0.1894 data_time: 0.0056 memory: 8327 grad_norm: 7.6283 loss: 3.4968 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1469 loss_aux: 1.3500 2023/02/17 15:44:13 - mmengine - INFO - Epoch(train) [50][ 120/1345] lr: 1.0000e-02 eta: 7:14:48 time: 0.1901 data_time: 0.0065 memory: 8327 grad_norm: 7.5988 loss: 3.0973 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8657 loss_aux: 1.2316 2023/02/17 15:44:17 - mmengine - INFO - Epoch(train) [50][ 140/1345] lr: 1.0000e-02 eta: 7:14:44 time: 0.1915 data_time: 0.0079 memory: 8327 grad_norm: 7.4242 loss: 3.4505 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0936 loss_aux: 1.3569 2023/02/17 15:44:20 - mmengine - INFO - Epoch(train) [50][ 160/1345] lr: 1.0000e-02 eta: 7:14:40 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.7673 loss: 3.6590 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2169 loss_aux: 1.4421 2023/02/17 15:44:24 - mmengine - INFO - Epoch(train) [50][ 180/1345] lr: 1.0000e-02 eta: 7:14:36 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.6932 loss: 3.2183 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.9415 loss_aux: 1.2769 2023/02/17 15:44:28 - mmengine - INFO - Epoch(train) [50][ 200/1345] lr: 1.0000e-02 eta: 7:14:32 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.8914 loss: 3.9126 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4408 loss_aux: 1.4718 2023/02/17 15:44:32 - mmengine - INFO - Epoch(train) [50][ 220/1345] lr: 1.0000e-02 eta: 7:14:28 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.4905 loss: 3.3948 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0552 loss_aux: 1.3395 2023/02/17 15:44:36 - mmengine - INFO - Epoch(train) [50][ 240/1345] lr: 1.0000e-02 eta: 7:14:24 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.4580 loss: 3.5709 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1643 loss_aux: 1.4065 2023/02/17 15:44:39 - mmengine - INFO - Epoch(train) [50][ 260/1345] lr: 1.0000e-02 eta: 7:14:20 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.4519 loss: 3.5074 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1210 loss_aux: 1.3864 2023/02/17 15:44:43 - mmengine - INFO - Epoch(train) [50][ 280/1345] lr: 1.0000e-02 eta: 7:14:17 time: 0.1909 data_time: 0.0058 memory: 8327 grad_norm: 7.8635 loss: 3.3137 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0136 loss_aux: 1.3001 2023/02/17 15:44:47 - mmengine - INFO - Epoch(train) [50][ 300/1345] lr: 1.0000e-02 eta: 7:14:13 time: 0.1897 data_time: 0.0063 memory: 8327 grad_norm: 7.7611 loss: 3.2549 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9717 loss_aux: 1.2832 2023/02/17 15:44:51 - mmengine - INFO - Epoch(train) [50][ 320/1345] lr: 1.0000e-02 eta: 7:14:09 time: 0.1918 data_time: 0.0082 memory: 8327 grad_norm: 7.6451 loss: 3.6541 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2280 loss_aux: 1.4262 2023/02/17 15:44:55 - mmengine - INFO - Epoch(train) [50][ 340/1345] lr: 1.0000e-02 eta: 7:14:05 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.6041 loss: 3.4985 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1400 loss_aux: 1.3585 2023/02/17 15:44:58 - mmengine - INFO - Epoch(train) [50][ 360/1345] lr: 1.0000e-02 eta: 7:14:01 time: 0.1902 data_time: 0.0061 memory: 8327 grad_norm: 7.3939 loss: 3.2910 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0202 loss_aux: 1.2708 2023/02/17 15:45:02 - mmengine - INFO - Epoch(train) [50][ 380/1345] lr: 1.0000e-02 eta: 7:13:57 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.3981 loss: 3.5302 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1558 loss_aux: 1.3745 2023/02/17 15:45:06 - mmengine - INFO - Epoch(train) [50][ 400/1345] lr: 1.0000e-02 eta: 7:13:53 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.7228 loss: 3.4693 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0923 loss_aux: 1.3770 2023/02/17 15:45:10 - mmengine - INFO - Epoch(train) [50][ 420/1345] lr: 1.0000e-02 eta: 7:13:49 time: 0.1903 data_time: 0.0064 memory: 8327 grad_norm: 7.6763 loss: 3.3643 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0240 loss_aux: 1.3402 2023/02/17 15:45:14 - mmengine - INFO - Epoch(train) [50][ 440/1345] lr: 1.0000e-02 eta: 7:13:45 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.7977 loss: 3.2643 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9225 loss_aux: 1.3417 2023/02/17 15:45:17 - mmengine - INFO - Epoch(train) [50][ 460/1345] lr: 1.0000e-02 eta: 7:13:41 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.6268 loss: 3.7964 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3494 loss_aux: 1.4470 2023/02/17 15:45:21 - mmengine - INFO - Epoch(train) [50][ 480/1345] lr: 1.0000e-02 eta: 7:13:37 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.6018 loss: 3.3240 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9583 loss_aux: 1.3657 2023/02/17 15:45:25 - mmengine - INFO - Epoch(train) [50][ 500/1345] lr: 1.0000e-02 eta: 7:13:33 time: 0.1901 data_time: 0.0061 memory: 8327 grad_norm: 7.9067 loss: 3.7023 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2848 loss_aux: 1.4175 2023/02/17 15:45:29 - mmengine - INFO - Epoch(train) [50][ 520/1345] lr: 1.0000e-02 eta: 7:13:29 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.8128 loss: 3.5151 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2107 loss_aux: 1.3044 2023/02/17 15:45:33 - mmengine - INFO - Epoch(train) [50][ 540/1345] lr: 1.0000e-02 eta: 7:13:25 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.6876 loss: 2.9946 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7691 loss_aux: 1.2255 2023/02/17 15:45:36 - mmengine - INFO - Epoch(train) [50][ 560/1345] lr: 1.0000e-02 eta: 7:13:21 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.7556 loss: 4.0384 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5528 loss_aux: 1.4855 2023/02/17 15:45:40 - mmengine - INFO - Epoch(train) [50][ 580/1345] lr: 1.0000e-02 eta: 7:13:17 time: 0.1899 data_time: 0.0061 memory: 8327 grad_norm: 7.6576 loss: 3.5786 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2435 loss_aux: 1.3351 2023/02/17 15:45:44 - mmengine - INFO - Epoch(train) [50][ 600/1345] lr: 1.0000e-02 eta: 7:13:13 time: 0.1902 data_time: 0.0066 memory: 8327 grad_norm: 7.5360 loss: 3.3670 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9972 loss_aux: 1.3698 2023/02/17 15:45:48 - mmengine - INFO - Epoch(train) [50][ 620/1345] lr: 1.0000e-02 eta: 7:13:10 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.6358 loss: 3.5661 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2094 loss_aux: 1.3566 2023/02/17 15:45:52 - mmengine - INFO - Epoch(train) [50][ 640/1345] lr: 1.0000e-02 eta: 7:13:06 time: 0.1898 data_time: 0.0061 memory: 8327 grad_norm: 7.7289 loss: 3.4393 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1268 loss_aux: 1.3125 2023/02/17 15:45:55 - mmengine - INFO - Epoch(train) [50][ 660/1345] lr: 1.0000e-02 eta: 7:13:02 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.5178 loss: 3.3999 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0478 loss_aux: 1.3521 2023/02/17 15:45:59 - mmengine - INFO - Epoch(train) [50][ 680/1345] lr: 1.0000e-02 eta: 7:12:58 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.6295 loss: 3.4187 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0556 loss_aux: 1.3631 2023/02/17 15:46:03 - mmengine - INFO - Epoch(train) [50][ 700/1345] lr: 1.0000e-02 eta: 7:12:54 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.7743 loss: 3.7510 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3285 loss_aux: 1.4225 2023/02/17 15:46:07 - mmengine - INFO - Epoch(train) [50][ 720/1345] lr: 1.0000e-02 eta: 7:12:50 time: 0.1896 data_time: 0.0061 memory: 8327 grad_norm: 7.8360 loss: 3.7184 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2994 loss_aux: 1.4190 2023/02/17 15:46:11 - mmengine - INFO - Epoch(train) [50][ 740/1345] lr: 1.0000e-02 eta: 7:12:46 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.6122 loss: 3.8672 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4021 loss_aux: 1.4651 2023/02/17 15:46:14 - mmengine - INFO - Epoch(train) [50][ 760/1345] lr: 1.0000e-02 eta: 7:12:42 time: 0.1900 data_time: 0.0060 memory: 8327 grad_norm: 7.6418 loss: 3.3448 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9599 loss_aux: 1.3849 2023/02/17 15:46:18 - mmengine - INFO - Epoch(train) [50][ 780/1345] lr: 1.0000e-02 eta: 7:12:38 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.3568 loss: 3.3289 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.0118 loss_aux: 1.3171 2023/02/17 15:46:22 - mmengine - INFO - Epoch(train) [50][ 800/1345] lr: 1.0000e-02 eta: 7:12:34 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.8344 loss: 3.2597 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9612 loss_aux: 1.2986 2023/02/17 15:46:26 - mmengine - INFO - Epoch(train) [50][ 820/1345] lr: 1.0000e-02 eta: 7:12:30 time: 0.1926 data_time: 0.0088 memory: 8327 grad_norm: 7.7795 loss: 3.4215 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0645 loss_aux: 1.3570 2023/02/17 15:46:30 - mmengine - INFO - Epoch(train) [50][ 840/1345] lr: 1.0000e-02 eta: 7:12:26 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.7786 loss: 3.3823 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0542 loss_aux: 1.3282 2023/02/17 15:46:33 - mmengine - INFO - Epoch(train) [50][ 860/1345] lr: 1.0000e-02 eta: 7:12:22 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.7077 loss: 3.5161 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1256 loss_aux: 1.3906 2023/02/17 15:46:37 - mmengine - INFO - Epoch(train) [50][ 880/1345] lr: 1.0000e-02 eta: 7:12:18 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.4370 loss: 3.6349 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2035 loss_aux: 1.4313 2023/02/17 15:46:41 - mmengine - INFO - Epoch(train) [50][ 900/1345] lr: 1.0000e-02 eta: 7:12:14 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.5548 loss: 3.2886 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9911 loss_aux: 1.2975 2023/02/17 15:46:45 - mmengine - INFO - Epoch(train) [50][ 920/1345] lr: 1.0000e-02 eta: 7:12:10 time: 0.1900 data_time: 0.0058 memory: 8327 grad_norm: 7.6749 loss: 3.5983 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2104 loss_aux: 1.3879 2023/02/17 15:46:49 - mmengine - INFO - Epoch(train) [50][ 940/1345] lr: 1.0000e-02 eta: 7:12:07 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.7667 loss: 3.4634 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1346 loss_aux: 1.3288 2023/02/17 15:46:52 - mmengine - INFO - Epoch(train) [50][ 960/1345] lr: 1.0000e-02 eta: 7:12:03 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.5835 loss: 3.5252 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.1698 loss_aux: 1.3554 2023/02/17 15:46:56 - mmengine - INFO - Epoch(train) [50][ 980/1345] lr: 1.0000e-02 eta: 7:11:59 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.8122 loss: 3.4433 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0945 loss_aux: 1.3488 2023/02/17 15:47:00 - mmengine - INFO - Epoch(train) [50][1000/1345] lr: 1.0000e-02 eta: 7:11:55 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.7964 loss: 3.4869 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0966 loss_aux: 1.3904 2023/02/17 15:47:04 - mmengine - INFO - Epoch(train) [50][1020/1345] lr: 1.0000e-02 eta: 7:11:51 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.6798 loss: 3.3121 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0253 loss_aux: 1.2868 2023/02/17 15:47:08 - mmengine - INFO - Epoch(train) [50][1040/1345] lr: 1.0000e-02 eta: 7:11:47 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.8416 loss: 3.8303 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4068 loss_aux: 1.4234 2023/02/17 15:47:11 - mmengine - INFO - Epoch(train) [50][1060/1345] lr: 1.0000e-02 eta: 7:11:43 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.7394 loss: 3.7118 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.2602 loss_aux: 1.4516 2023/02/17 15:47:15 - mmengine - INFO - Epoch(train) [50][1080/1345] lr: 1.0000e-02 eta: 7:11:39 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.5411 loss: 3.5246 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2009 loss_aux: 1.3237 2023/02/17 15:47:18 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:47:19 - mmengine - INFO - Epoch(train) [50][1100/1345] lr: 1.0000e-02 eta: 7:11:35 time: 0.1915 data_time: 0.0075 memory: 8327 grad_norm: 7.7988 loss: 3.3325 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0148 loss_aux: 1.3176 2023/02/17 15:47:23 - mmengine - INFO - Epoch(train) [50][1120/1345] lr: 1.0000e-02 eta: 7:11:31 time: 0.1900 data_time: 0.0060 memory: 8327 grad_norm: 7.7458 loss: 3.0176 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8131 loss_aux: 1.2045 2023/02/17 15:47:27 - mmengine - INFO - Epoch(train) [50][1140/1345] lr: 1.0000e-02 eta: 7:11:27 time: 0.1893 data_time: 0.0059 memory: 8327 grad_norm: 7.7019 loss: 3.1379 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8451 loss_aux: 1.2928 2023/02/17 15:47:30 - mmengine - INFO - Epoch(train) [50][1160/1345] lr: 1.0000e-02 eta: 7:11:23 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 8.0121 loss: 3.2371 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9234 loss_aux: 1.3138 2023/02/17 15:47:34 - mmengine - INFO - Epoch(train) [50][1180/1345] lr: 1.0000e-02 eta: 7:11:19 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.6867 loss: 3.6983 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2787 loss_aux: 1.4196 2023/02/17 15:47:38 - mmengine - INFO - Epoch(train) [50][1200/1345] lr: 1.0000e-02 eta: 7:11:15 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.9492 loss: 3.7467 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3356 loss_aux: 1.4111 2023/02/17 15:47:42 - mmengine - INFO - Epoch(train) [50][1220/1345] lr: 1.0000e-02 eta: 7:11:11 time: 0.1901 data_time: 0.0064 memory: 8327 grad_norm: 7.7033 loss: 3.6741 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1968 loss_aux: 1.4773 2023/02/17 15:47:46 - mmengine - INFO - Epoch(train) [50][1240/1345] lr: 1.0000e-02 eta: 7:11:07 time: 0.1898 data_time: 0.0061 memory: 8327 grad_norm: 7.9402 loss: 3.8575 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3508 loss_aux: 1.5067 2023/02/17 15:47:49 - mmengine - INFO - Epoch(train) [50][1260/1345] lr: 1.0000e-02 eta: 7:11:03 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7232 loss: 3.5575 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.1387 loss_aux: 1.4188 2023/02/17 15:47:53 - mmengine - INFO - Epoch(train) [50][1280/1345] lr: 1.0000e-02 eta: 7:11:00 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.5113 loss: 3.4876 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1409 loss_aux: 1.3467 2023/02/17 15:47:57 - mmengine - INFO - Epoch(train) [50][1300/1345] lr: 1.0000e-02 eta: 7:10:56 time: 0.1897 data_time: 0.0057 memory: 8327 grad_norm: 7.5359 loss: 3.6881 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2480 loss_aux: 1.4401 2023/02/17 15:48:01 - mmengine - INFO - Epoch(train) [50][1320/1345] lr: 1.0000e-02 eta: 7:10:52 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.8739 loss: 3.6577 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2149 loss_aux: 1.4428 2023/02/17 15:48:05 - mmengine - INFO - Epoch(train) [50][1340/1345] lr: 1.0000e-02 eta: 7:10:48 time: 0.1897 data_time: 0.0061 memory: 8327 grad_norm: 7.8095 loss: 3.7105 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3583 loss_aux: 1.3522 2023/02/17 15:48:05 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:48:05 - mmengine - INFO - Epoch(train) [50][1345/1345] lr: 1.0000e-02 eta: 7:10:46 time: 0.1837 data_time: 0.0061 memory: 8327 grad_norm: 7.6057 loss: 3.7534 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.3905 loss_aux: 1.3629 2023/02/17 15:48:05 - mmengine - INFO - Saving checkpoint at 50 epochs 2023/02/17 15:48:09 - mmengine - INFO - Epoch(val) [50][ 20/181] eta: 0:00:09 time: 0.0566 data_time: 0.0074 memory: 1994 2023/02/17 15:48:10 - mmengine - INFO - Epoch(val) [50][ 40/181] eta: 0:00:07 time: 0.0526 data_time: 0.0047 memory: 1994 2023/02/17 15:48:11 - mmengine - INFO - Epoch(val) [50][ 60/181] eta: 0:00:06 time: 0.0530 data_time: 0.0048 memory: 1994 2023/02/17 15:48:13 - mmengine - INFO - Epoch(val) [50][ 80/181] eta: 0:00:06 time: 0.0847 data_time: 0.0049 memory: 1994 2023/02/17 15:48:14 - mmengine - INFO - Epoch(val) [50][100/181] eta: 0:00:04 time: 0.0534 data_time: 0.0049 memory: 1994 2023/02/17 15:48:15 - mmengine - INFO - Epoch(val) [50][120/181] eta: 0:00:03 time: 0.0525 data_time: 0.0046 memory: 1994 2023/02/17 15:48:16 - mmengine - INFO - Epoch(val) [50][140/181] eta: 0:00:02 time: 0.0540 data_time: 0.0045 memory: 1994 2023/02/17 15:48:17 - mmengine - INFO - Epoch(val) [50][160/181] eta: 0:00:01 time: 0.0532 data_time: 0.0042 memory: 1994 2023/02/17 15:48:18 - mmengine - INFO - Epoch(val) [50][180/181] eta: 0:00:00 time: 0.0513 data_time: 0.0041 memory: 1994 2023/02/17 15:48:18 - mmengine - INFO - Epoch(val) [50][181/181] acc/top1: 0.3698 acc/top5: 0.6732 acc/mean1: 0.3375 2023/02/17 15:48:23 - mmengine - INFO - Epoch(train) [51][ 20/1345] lr: 1.0000e-02 eta: 7:10:44 time: 0.2391 data_time: 0.0451 memory: 8327 grad_norm: 7.6679 loss: 3.2195 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9361 loss_aux: 1.2834 2023/02/17 15:48:27 - mmengine - INFO - Epoch(train) [51][ 40/1345] lr: 1.0000e-02 eta: 7:10:41 time: 0.1914 data_time: 0.0044 memory: 8327 grad_norm: 7.6082 loss: 3.1519 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8337 loss_aux: 1.3182 2023/02/17 15:48:31 - mmengine - INFO - Epoch(train) [51][ 60/1345] lr: 1.0000e-02 eta: 7:10:37 time: 0.1909 data_time: 0.0072 memory: 8327 grad_norm: 7.3455 loss: 3.2692 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.9358 loss_aux: 1.3334 2023/02/17 15:48:35 - mmengine - INFO - Epoch(train) [51][ 80/1345] lr: 1.0000e-02 eta: 7:10:33 time: 0.1897 data_time: 0.0057 memory: 8327 grad_norm: 7.7472 loss: 3.5682 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1706 loss_aux: 1.3976 2023/02/17 15:48:38 - mmengine - INFO - Epoch(train) [51][ 100/1345] lr: 1.0000e-02 eta: 7:10:29 time: 0.1900 data_time: 0.0058 memory: 8327 grad_norm: 7.7041 loss: 3.5923 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2107 loss_aux: 1.3816 2023/02/17 15:48:42 - mmengine - INFO - Epoch(train) [51][ 120/1345] lr: 1.0000e-02 eta: 7:10:25 time: 0.1897 data_time: 0.0061 memory: 8327 grad_norm: 7.8475 loss: 3.3184 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9840 loss_aux: 1.3344 2023/02/17 15:48:46 - mmengine - INFO - Epoch(train) [51][ 140/1345] lr: 1.0000e-02 eta: 7:10:21 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.5632 loss: 3.5404 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1043 loss_aux: 1.4361 2023/02/17 15:48:50 - mmengine - INFO - Epoch(train) [51][ 160/1345] lr: 1.0000e-02 eta: 7:10:17 time: 0.1897 data_time: 0.0057 memory: 8327 grad_norm: 7.5072 loss: 3.4178 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0631 loss_aux: 1.3547 2023/02/17 15:48:54 - mmengine - INFO - Epoch(train) [51][ 180/1345] lr: 1.0000e-02 eta: 7:10:13 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.7160 loss: 3.2735 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9806 loss_aux: 1.2929 2023/02/17 15:48:57 - mmengine - INFO - Epoch(train) [51][ 200/1345] lr: 1.0000e-02 eta: 7:10:09 time: 0.1905 data_time: 0.0058 memory: 8327 grad_norm: 7.7897 loss: 3.8287 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3566 loss_aux: 1.4721 2023/02/17 15:49:01 - mmengine - INFO - Epoch(train) [51][ 220/1345] lr: 1.0000e-02 eta: 7:10:05 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5895 loss: 3.5764 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1962 loss_aux: 1.3803 2023/02/17 15:49:05 - mmengine - INFO - Epoch(train) [51][ 240/1345] lr: 1.0000e-02 eta: 7:10:01 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.6498 loss: 3.5096 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1577 loss_aux: 1.3519 2023/02/17 15:49:09 - mmengine - INFO - Epoch(train) [51][ 260/1345] lr: 1.0000e-02 eta: 7:09:57 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.7413 loss: 3.4540 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1132 loss_aux: 1.3408 2023/02/17 15:49:13 - mmengine - INFO - Epoch(train) [51][ 280/1345] lr: 1.0000e-02 eta: 7:09:53 time: 0.1898 data_time: 0.0062 memory: 8327 grad_norm: 7.8888 loss: 3.6015 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.1742 loss_aux: 1.4273 2023/02/17 15:49:16 - mmengine - INFO - Epoch(train) [51][ 300/1345] lr: 1.0000e-02 eta: 7:09:49 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.5601 loss: 3.2503 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9571 loss_aux: 1.2932 2023/02/17 15:49:20 - mmengine - INFO - Epoch(train) [51][ 320/1345] lr: 1.0000e-02 eta: 7:09:45 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.7066 loss: 3.4059 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0965 loss_aux: 1.3095 2023/02/17 15:49:24 - mmengine - INFO - Epoch(train) [51][ 340/1345] lr: 1.0000e-02 eta: 7:09:42 time: 0.1910 data_time: 0.0074 memory: 8327 grad_norm: 7.7161 loss: 3.0267 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8388 loss_aux: 1.1880 2023/02/17 15:49:28 - mmengine - INFO - Epoch(train) [51][ 360/1345] lr: 1.0000e-02 eta: 7:09:38 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.7201 loss: 3.1061 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8693 loss_aux: 1.2368 2023/02/17 15:49:32 - mmengine - INFO - Epoch(train) [51][ 380/1345] lr: 1.0000e-02 eta: 7:09:34 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.7349 loss: 3.5728 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1814 loss_aux: 1.3914 2023/02/17 15:49:35 - mmengine - INFO - Epoch(train) [51][ 400/1345] lr: 1.0000e-02 eta: 7:09:30 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.7382 loss: 3.4223 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0782 loss_aux: 1.3441 2023/02/17 15:49:39 - mmengine - INFO - Epoch(train) [51][ 420/1345] lr: 1.0000e-02 eta: 7:09:26 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.9043 loss: 3.5423 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1469 loss_aux: 1.3955 2023/02/17 15:49:43 - mmengine - INFO - Epoch(train) [51][ 440/1345] lr: 1.0000e-02 eta: 7:09:22 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.5711 loss: 3.3381 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0114 loss_aux: 1.3267 2023/02/17 15:49:47 - mmengine - INFO - Epoch(train) [51][ 460/1345] lr: 1.0000e-02 eta: 7:09:18 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7141 loss: 3.2814 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9888 loss_aux: 1.2926 2023/02/17 15:49:51 - mmengine - INFO - Epoch(train) [51][ 480/1345] lr: 1.0000e-02 eta: 7:09:14 time: 0.1908 data_time: 0.0068 memory: 8327 grad_norm: 7.6071 loss: 3.5004 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.1134 loss_aux: 1.3870 2023/02/17 15:49:54 - mmengine - INFO - Epoch(train) [51][ 500/1345] lr: 1.0000e-02 eta: 7:09:10 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.6668 loss: 3.2983 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9891 loss_aux: 1.3092 2023/02/17 15:49:58 - mmengine - INFO - Epoch(train) [51][ 520/1345] lr: 1.0000e-02 eta: 7:09:06 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7671 loss: 3.4729 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1432 loss_aux: 1.3297 2023/02/17 15:50:02 - mmengine - INFO - Epoch(train) [51][ 540/1345] lr: 1.0000e-02 eta: 7:09:02 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.6585 loss: 3.0593 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7992 loss_aux: 1.2601 2023/02/17 15:50:06 - mmengine - INFO - Epoch(train) [51][ 560/1345] lr: 1.0000e-02 eta: 7:08:59 time: 0.2097 data_time: 0.0261 memory: 8327 grad_norm: 7.5676 loss: 3.4264 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0563 loss_aux: 1.3702 2023/02/17 15:50:10 - mmengine - INFO - Epoch(train) [51][ 580/1345] lr: 1.0000e-02 eta: 7:08:55 time: 0.1901 data_time: 0.0059 memory: 8327 grad_norm: 7.6287 loss: 3.1699 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8698 loss_aux: 1.3002 2023/02/17 15:50:14 - mmengine - INFO - Epoch(train) [51][ 600/1345] lr: 1.0000e-02 eta: 7:08:51 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.9403 loss: 3.2156 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9077 loss_aux: 1.3079 2023/02/17 15:50:18 - mmengine - INFO - Epoch(train) [51][ 620/1345] lr: 1.0000e-02 eta: 7:08:47 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.5710 loss: 3.2611 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0063 loss_aux: 1.2548 2023/02/17 15:50:21 - mmengine - INFO - Epoch(train) [51][ 640/1345] lr: 1.0000e-02 eta: 7:08:43 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.9355 loss: 3.3506 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0025 loss_aux: 1.3481 2023/02/17 15:50:25 - mmengine - INFO - Epoch(train) [51][ 660/1345] lr: 1.0000e-02 eta: 7:08:39 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.7737 loss: 3.4694 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1059 loss_aux: 1.3635 2023/02/17 15:50:29 - mmengine - INFO - Epoch(train) [51][ 680/1345] lr: 1.0000e-02 eta: 7:08:35 time: 0.1917 data_time: 0.0075 memory: 8327 grad_norm: 7.8633 loss: 3.3928 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0680 loss_aux: 1.3248 2023/02/17 15:50:33 - mmengine - INFO - Epoch(train) [51][ 700/1345] lr: 1.0000e-02 eta: 7:08:32 time: 0.1997 data_time: 0.0161 memory: 8327 grad_norm: 7.5963 loss: 3.4266 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0398 loss_aux: 1.3868 2023/02/17 15:50:37 - mmengine - INFO - Epoch(train) [51][ 720/1345] lr: 1.0000e-02 eta: 7:08:28 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.5303 loss: 3.6173 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2192 loss_aux: 1.3981 2023/02/17 15:50:41 - mmengine - INFO - Epoch(train) [51][ 740/1345] lr: 1.0000e-02 eta: 7:08:24 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.7793 loss: 3.4784 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0606 loss_aux: 1.4179 2023/02/17 15:50:43 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:50:44 - mmengine - INFO - Epoch(train) [51][ 760/1345] lr: 1.0000e-02 eta: 7:08:20 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.8124 loss: 3.3385 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9936 loss_aux: 1.3449 2023/02/17 15:50:48 - mmengine - INFO - Epoch(train) [51][ 780/1345] lr: 1.0000e-02 eta: 7:08:16 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.6576 loss: 2.7172 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5822 loss_aux: 1.1349 2023/02/17 15:50:52 - mmengine - INFO - Epoch(train) [51][ 800/1345] lr: 1.0000e-02 eta: 7:08:12 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.7884 loss: 3.8548 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4114 loss_aux: 1.4433 2023/02/17 15:50:56 - mmengine - INFO - Epoch(train) [51][ 820/1345] lr: 1.0000e-02 eta: 7:08:08 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.5925 loss: 3.2075 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9538 loss_aux: 1.2538 2023/02/17 15:51:00 - mmengine - INFO - Epoch(train) [51][ 840/1345] lr: 1.0000e-02 eta: 7:08:04 time: 0.1899 data_time: 0.0060 memory: 8327 grad_norm: 7.7018 loss: 3.6000 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2316 loss_aux: 1.3684 2023/02/17 15:51:03 - mmengine - INFO - Epoch(train) [51][ 860/1345] lr: 1.0000e-02 eta: 7:08:00 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.8974 loss: 3.7749 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3484 loss_aux: 1.4264 2023/02/17 15:51:07 - mmengine - INFO - Epoch(train) [51][ 880/1345] lr: 1.0000e-02 eta: 7:07:56 time: 0.1903 data_time: 0.0059 memory: 8327 grad_norm: 7.7425 loss: 3.2465 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9342 loss_aux: 1.3123 2023/02/17 15:51:11 - mmengine - INFO - Epoch(train) [51][ 900/1345] lr: 1.0000e-02 eta: 7:07:52 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5664 loss: 3.2638 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9760 loss_aux: 1.2878 2023/02/17 15:51:15 - mmengine - INFO - Epoch(train) [51][ 920/1345] lr: 1.0000e-02 eta: 7:07:49 time: 0.1900 data_time: 0.0058 memory: 8327 grad_norm: 8.0068 loss: 3.7210 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2929 loss_aux: 1.4282 2023/02/17 15:51:19 - mmengine - INFO - Epoch(train) [51][ 940/1345] lr: 1.0000e-02 eta: 7:07:45 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.8058 loss: 3.6921 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.2516 loss_aux: 1.4405 2023/02/17 15:51:22 - mmengine - INFO - Epoch(train) [51][ 960/1345] lr: 1.0000e-02 eta: 7:07:41 time: 0.1893 data_time: 0.0057 memory: 8327 grad_norm: 7.5977 loss: 3.4861 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1084 loss_aux: 1.3778 2023/02/17 15:51:26 - mmengine - INFO - Epoch(train) [51][ 980/1345] lr: 1.0000e-02 eta: 7:07:37 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.9664 loss: 3.6274 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1896 loss_aux: 1.4378 2023/02/17 15:51:30 - mmengine - INFO - Epoch(train) [51][1000/1345] lr: 1.0000e-02 eta: 7:07:33 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.6440 loss: 3.3636 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0292 loss_aux: 1.3343 2023/02/17 15:51:34 - mmengine - INFO - Epoch(train) [51][1020/1345] lr: 1.0000e-02 eta: 7:07:29 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.5975 loss: 3.2628 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0251 loss_aux: 1.2376 2023/02/17 15:51:38 - mmengine - INFO - Epoch(train) [51][1040/1345] lr: 1.0000e-02 eta: 7:07:25 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.7000 loss: 3.2346 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9412 loss_aux: 1.2934 2023/02/17 15:51:41 - mmengine - INFO - Epoch(train) [51][1060/1345] lr: 1.0000e-02 eta: 7:07:21 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.7274 loss: 3.5446 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1433 loss_aux: 1.4013 2023/02/17 15:51:45 - mmengine - INFO - Epoch(train) [51][1080/1345] lr: 1.0000e-02 eta: 7:07:17 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.6017 loss: 3.6578 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2713 loss_aux: 1.3865 2023/02/17 15:51:49 - mmengine - INFO - Epoch(train) [51][1100/1345] lr: 1.0000e-02 eta: 7:07:13 time: 0.1912 data_time: 0.0077 memory: 8327 grad_norm: 7.7385 loss: 3.4244 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1172 loss_aux: 1.3072 2023/02/17 15:51:53 - mmengine - INFO - Epoch(train) [51][1120/1345] lr: 1.0000e-02 eta: 7:07:09 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.6293 loss: 3.4786 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1372 loss_aux: 1.3413 2023/02/17 15:51:57 - mmengine - INFO - Epoch(train) [51][1140/1345] lr: 1.0000e-02 eta: 7:07:05 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.6814 loss: 3.4539 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.1120 loss_aux: 1.3419 2023/02/17 15:52:00 - mmengine - INFO - Epoch(train) [51][1160/1345] lr: 1.0000e-02 eta: 7:07:01 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7349 loss: 3.6270 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2266 loss_aux: 1.4004 2023/02/17 15:52:04 - mmengine - INFO - Epoch(train) [51][1180/1345] lr: 1.0000e-02 eta: 7:06:57 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.6455 loss: 3.3146 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 1.9964 loss_aux: 1.3182 2023/02/17 15:52:08 - mmengine - INFO - Epoch(train) [51][1200/1345] lr: 1.0000e-02 eta: 7:06:53 time: 0.1899 data_time: 0.0058 memory: 8327 grad_norm: 7.9092 loss: 3.3773 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0206 loss_aux: 1.3567 2023/02/17 15:52:12 - mmengine - INFO - Epoch(train) [51][1220/1345] lr: 1.0000e-02 eta: 7:06:49 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.8370 loss: 3.4617 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1296 loss_aux: 1.3320 2023/02/17 15:52:16 - mmengine - INFO - Epoch(train) [51][1240/1345] lr: 1.0000e-02 eta: 7:06:46 time: 0.1902 data_time: 0.0065 memory: 8327 grad_norm: 7.7368 loss: 3.6714 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2485 loss_aux: 1.4229 2023/02/17 15:52:19 - mmengine - INFO - Epoch(train) [51][1260/1345] lr: 1.0000e-02 eta: 7:06:42 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.5803 loss: 3.5652 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2165 loss_aux: 1.3487 2023/02/17 15:52:23 - mmengine - INFO - Epoch(train) [51][1280/1345] lr: 1.0000e-02 eta: 7:06:38 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.8059 loss: 3.7632 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3215 loss_aux: 1.4417 2023/02/17 15:52:27 - mmengine - INFO - Epoch(train) [51][1300/1345] lr: 1.0000e-02 eta: 7:06:34 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.5324 loss: 3.3771 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0219 loss_aux: 1.3552 2023/02/17 15:52:31 - mmengine - INFO - Epoch(train) [51][1320/1345] lr: 1.0000e-02 eta: 7:06:30 time: 0.1900 data_time: 0.0061 memory: 8327 grad_norm: 7.7380 loss: 3.1294 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.8513 loss_aux: 1.2781 2023/02/17 15:52:35 - mmengine - INFO - Epoch(train) [51][1340/1345] lr: 1.0000e-02 eta: 7:06:26 time: 0.1898 data_time: 0.0061 memory: 8327 grad_norm: 7.6913 loss: 3.7473 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.3000 loss_aux: 1.4472 2023/02/17 15:52:36 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:52:36 - mmengine - INFO - Epoch(train) [51][1345/1345] lr: 1.0000e-02 eta: 7:06:25 time: 0.1845 data_time: 0.0069 memory: 8327 grad_norm: 7.5898 loss: 3.8366 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.3714 loss_aux: 1.4652 2023/02/17 15:52:36 - mmengine - INFO - Saving checkpoint at 51 epochs 2023/02/17 15:52:42 - mmengine - INFO - Epoch(train) [52][ 20/1345] lr: 1.0000e-02 eta: 7:06:22 time: 0.2136 data_time: 0.0212 memory: 8327 grad_norm: 7.5552 loss: 3.4967 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1133 loss_aux: 1.3834 2023/02/17 15:52:46 - mmengine - INFO - Epoch(train) [52][ 40/1345] lr: 1.0000e-02 eta: 7:06:18 time: 0.1913 data_time: 0.0048 memory: 8327 grad_norm: 7.5248 loss: 3.1753 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9079 loss_aux: 1.2673 2023/02/17 15:52:50 - mmengine - INFO - Epoch(train) [52][ 60/1345] lr: 1.0000e-02 eta: 7:06:14 time: 0.1898 data_time: 0.0056 memory: 8327 grad_norm: 7.4476 loss: 3.7659 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2871 loss_aux: 1.4788 2023/02/17 15:52:54 - mmengine - INFO - Epoch(train) [52][ 80/1345] lr: 1.0000e-02 eta: 7:06:10 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.4229 loss: 3.1694 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8983 loss_aux: 1.2711 2023/02/17 15:52:58 - mmengine - INFO - Epoch(train) [52][ 100/1345] lr: 1.0000e-02 eta: 7:06:06 time: 0.1894 data_time: 0.0060 memory: 8327 grad_norm: 7.6393 loss: 3.1264 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9092 loss_aux: 1.2172 2023/02/17 15:53:01 - mmengine - INFO - Epoch(train) [52][ 120/1345] lr: 1.0000e-02 eta: 7:06:02 time: 0.1901 data_time: 0.0059 memory: 8327 grad_norm: 7.4354 loss: 3.2389 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9466 loss_aux: 1.2923 2023/02/17 15:53:05 - mmengine - INFO - Epoch(train) [52][ 140/1345] lr: 1.0000e-02 eta: 7:05:58 time: 0.1899 data_time: 0.0058 memory: 8327 grad_norm: 7.5705 loss: 3.3211 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0075 loss_aux: 1.3136 2023/02/17 15:53:09 - mmengine - INFO - Epoch(train) [52][ 160/1345] lr: 1.0000e-02 eta: 7:05:54 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.8605 loss: 3.5211 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1256 loss_aux: 1.3955 2023/02/17 15:53:13 - mmengine - INFO - Epoch(train) [52][ 180/1345] lr: 1.0000e-02 eta: 7:05:50 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.6873 loss: 3.1695 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8416 loss_aux: 1.3278 2023/02/17 15:53:17 - mmengine - INFO - Epoch(train) [52][ 200/1345] lr: 1.0000e-02 eta: 7:05:46 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.5725 loss: 3.1273 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8164 loss_aux: 1.3110 2023/02/17 15:53:20 - mmengine - INFO - Epoch(train) [52][ 220/1345] lr: 1.0000e-02 eta: 7:05:42 time: 0.1920 data_time: 0.0060 memory: 8327 grad_norm: 7.6411 loss: 3.6015 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1609 loss_aux: 1.4406 2023/02/17 15:53:24 - mmengine - INFO - Epoch(train) [52][ 240/1345] lr: 1.0000e-02 eta: 7:05:39 time: 0.1895 data_time: 0.0061 memory: 8327 grad_norm: 7.6234 loss: 3.2250 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 1.9543 loss_aux: 1.2707 2023/02/17 15:53:28 - mmengine - INFO - Epoch(train) [52][ 260/1345] lr: 1.0000e-02 eta: 7:05:35 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.6254 loss: 3.4569 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0969 loss_aux: 1.3600 2023/02/17 15:53:32 - mmengine - INFO - Epoch(train) [52][ 280/1345] lr: 1.0000e-02 eta: 7:05:31 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.8074 loss: 3.6424 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2081 loss_aux: 1.4344 2023/02/17 15:53:36 - mmengine - INFO - Epoch(train) [52][ 300/1345] lr: 1.0000e-02 eta: 7:05:27 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7912 loss: 3.5498 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2233 loss_aux: 1.3265 2023/02/17 15:53:39 - mmengine - INFO - Epoch(train) [52][ 320/1345] lr: 1.0000e-02 eta: 7:05:23 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.8440 loss: 3.6941 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2529 loss_aux: 1.4412 2023/02/17 15:53:43 - mmengine - INFO - Epoch(train) [52][ 340/1345] lr: 1.0000e-02 eta: 7:05:19 time: 0.1899 data_time: 0.0063 memory: 8327 grad_norm: 7.9402 loss: 3.2920 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9646 loss_aux: 1.3274 2023/02/17 15:53:47 - mmengine - INFO - Epoch(train) [52][ 360/1345] lr: 1.0000e-02 eta: 7:05:15 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.8616 loss: 3.4168 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0756 loss_aux: 1.3412 2023/02/17 15:53:51 - mmengine - INFO - Epoch(train) [52][ 380/1345] lr: 1.0000e-02 eta: 7:05:11 time: 0.1918 data_time: 0.0079 memory: 8327 grad_norm: 7.5559 loss: 3.3884 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0602 loss_aux: 1.3282 2023/02/17 15:53:55 - mmengine - INFO - Epoch(train) [52][ 400/1345] lr: 1.0000e-02 eta: 7:05:07 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.5966 loss: 3.3377 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0379 loss_aux: 1.2998 2023/02/17 15:53:56 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:53:58 - mmengine - INFO - Epoch(train) [52][ 420/1345] lr: 1.0000e-02 eta: 7:05:03 time: 0.1901 data_time: 0.0058 memory: 8327 grad_norm: 7.6544 loss: 3.7159 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3072 loss_aux: 1.4088 2023/02/17 15:54:02 - mmengine - INFO - Epoch(train) [52][ 440/1345] lr: 1.0000e-02 eta: 7:04:59 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.7398 loss: 3.6181 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1951 loss_aux: 1.4230 2023/02/17 15:54:06 - mmengine - INFO - Epoch(train) [52][ 460/1345] lr: 1.0000e-02 eta: 7:04:55 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.7227 loss: 3.5586 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2129 loss_aux: 1.3457 2023/02/17 15:54:10 - mmengine - INFO - Epoch(train) [52][ 480/1345] lr: 1.0000e-02 eta: 7:04:51 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.7027 loss: 3.4466 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0908 loss_aux: 1.3558 2023/02/17 15:54:14 - mmengine - INFO - Epoch(train) [52][ 500/1345] lr: 1.0000e-02 eta: 7:04:47 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.4899 loss: 3.1689 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8930 loss_aux: 1.2758 2023/02/17 15:54:17 - mmengine - INFO - Epoch(train) [52][ 520/1345] lr: 1.0000e-02 eta: 7:04:43 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.7410 loss: 3.2502 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9785 loss_aux: 1.2716 2023/02/17 15:54:21 - mmengine - INFO - Epoch(train) [52][ 540/1345] lr: 1.0000e-02 eta: 7:04:39 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5094 loss: 3.5513 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1551 loss_aux: 1.3963 2023/02/17 15:54:25 - mmengine - INFO - Epoch(train) [52][ 560/1345] lr: 1.0000e-02 eta: 7:04:36 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.6818 loss: 3.2549 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9590 loss_aux: 1.2959 2023/02/17 15:54:29 - mmengine - INFO - Epoch(train) [52][ 580/1345] lr: 1.0000e-02 eta: 7:04:32 time: 0.1995 data_time: 0.0158 memory: 8327 grad_norm: 7.5947 loss: 3.1093 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8121 loss_aux: 1.2972 2023/02/17 15:54:33 - mmengine - INFO - Epoch(train) [52][ 600/1345] lr: 1.0000e-02 eta: 7:04:28 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.7461 loss: 3.3197 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0621 loss_aux: 1.2575 2023/02/17 15:54:37 - mmengine - INFO - Epoch(train) [52][ 620/1345] lr: 1.0000e-02 eta: 7:04:24 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7860 loss: 3.2543 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9955 loss_aux: 1.2588 2023/02/17 15:54:40 - mmengine - INFO - Epoch(train) [52][ 640/1345] lr: 1.0000e-02 eta: 7:04:20 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.6197 loss: 3.4662 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1193 loss_aux: 1.3469 2023/02/17 15:54:44 - mmengine - INFO - Epoch(train) [52][ 660/1345] lr: 1.0000e-02 eta: 7:04:16 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.5651 loss: 3.1958 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9106 loss_aux: 1.2852 2023/02/17 15:54:48 - mmengine - INFO - Epoch(train) [52][ 680/1345] lr: 1.0000e-02 eta: 7:04:12 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5947 loss: 3.3727 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0304 loss_aux: 1.3423 2023/02/17 15:54:52 - mmengine - INFO - Epoch(train) [52][ 700/1345] lr: 1.0000e-02 eta: 7:04:08 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.9166 loss: 3.1336 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8688 loss_aux: 1.2648 2023/02/17 15:54:56 - mmengine - INFO - Epoch(train) [52][ 720/1345] lr: 1.0000e-02 eta: 7:04:04 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.5848 loss: 3.4980 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0949 loss_aux: 1.4032 2023/02/17 15:54:59 - mmengine - INFO - Epoch(train) [52][ 740/1345] lr: 1.0000e-02 eta: 7:04:00 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.6257 loss: 3.4653 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1230 loss_aux: 1.3423 2023/02/17 15:55:03 - mmengine - INFO - Epoch(train) [52][ 760/1345] lr: 1.0000e-02 eta: 7:03:56 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.9568 loss: 3.6579 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2471 loss_aux: 1.4108 2023/02/17 15:55:07 - mmengine - INFO - Epoch(train) [52][ 780/1345] lr: 1.0000e-02 eta: 7:03:53 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.6244 loss: 3.4845 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1097 loss_aux: 1.3748 2023/02/17 15:55:11 - mmengine - INFO - Epoch(train) [52][ 800/1345] lr: 1.0000e-02 eta: 7:03:49 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 7.7571 loss: 3.6133 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2457 loss_aux: 1.3676 2023/02/17 15:55:15 - mmengine - INFO - Epoch(train) [52][ 820/1345] lr: 1.0000e-02 eta: 7:03:45 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5654 loss: 3.3814 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0440 loss_aux: 1.3374 2023/02/17 15:55:18 - mmengine - INFO - Epoch(train) [52][ 840/1345] lr: 1.0000e-02 eta: 7:03:41 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.6359 loss: 3.4294 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0784 loss_aux: 1.3510 2023/02/17 15:55:22 - mmengine - INFO - Epoch(train) [52][ 860/1345] lr: 1.0000e-02 eta: 7:03:37 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.7794 loss: 3.5944 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1875 loss_aux: 1.4069 2023/02/17 15:55:26 - mmengine - INFO - Epoch(train) [52][ 880/1345] lr: 1.0000e-02 eta: 7:03:33 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.8081 loss: 3.6383 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2440 loss_aux: 1.3942 2023/02/17 15:55:30 - mmengine - INFO - Epoch(train) [52][ 900/1345] lr: 1.0000e-02 eta: 7:03:29 time: 0.1900 data_time: 0.0061 memory: 8327 grad_norm: 7.7746 loss: 3.2841 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9996 loss_aux: 1.2845 2023/02/17 15:55:34 - mmengine - INFO - Epoch(train) [52][ 920/1345] lr: 1.0000e-02 eta: 7:03:25 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.9443 loss: 3.2856 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9958 loss_aux: 1.2898 2023/02/17 15:55:37 - mmengine - INFO - Epoch(train) [52][ 940/1345] lr: 1.0000e-02 eta: 7:03:21 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.4825 loss: 3.0921 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8199 loss_aux: 1.2722 2023/02/17 15:55:41 - mmengine - INFO - Epoch(train) [52][ 960/1345] lr: 1.0000e-02 eta: 7:03:17 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.4397 loss: 3.2739 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9866 loss_aux: 1.2873 2023/02/17 15:55:45 - mmengine - INFO - Epoch(train) [52][ 980/1345] lr: 1.0000e-02 eta: 7:03:13 time: 0.1908 data_time: 0.0071 memory: 8327 grad_norm: 7.6518 loss: 3.3850 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.0672 loss_aux: 1.3177 2023/02/17 15:55:49 - mmengine - INFO - Epoch(train) [52][1000/1345] lr: 1.0000e-02 eta: 7:03:09 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.7444 loss: 3.4906 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1389 loss_aux: 1.3517 2023/02/17 15:55:53 - mmengine - INFO - Epoch(train) [52][1020/1345] lr: 1.0000e-02 eta: 7:03:05 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.5090 loss: 3.2848 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9922 loss_aux: 1.2926 2023/02/17 15:55:56 - mmengine - INFO - Epoch(train) [52][1040/1345] lr: 1.0000e-02 eta: 7:03:01 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.7991 loss: 3.2402 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9057 loss_aux: 1.3345 2023/02/17 15:56:00 - mmengine - INFO - Epoch(train) [52][1060/1345] lr: 1.0000e-02 eta: 7:02:57 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.6175 loss: 3.3923 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0604 loss_aux: 1.3319 2023/02/17 15:56:04 - mmengine - INFO - Epoch(train) [52][1080/1345] lr: 1.0000e-02 eta: 7:02:54 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.6328 loss: 3.4575 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0984 loss_aux: 1.3591 2023/02/17 15:56:08 - mmengine - INFO - Epoch(train) [52][1100/1345] lr: 1.0000e-02 eta: 7:02:50 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.5986 loss: 3.6849 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2475 loss_aux: 1.4374 2023/02/17 15:56:12 - mmengine - INFO - Epoch(train) [52][1120/1345] lr: 1.0000e-02 eta: 7:02:46 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.4854 loss: 3.4609 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1245 loss_aux: 1.3364 2023/02/17 15:56:15 - mmengine - INFO - Epoch(train) [52][1140/1345] lr: 1.0000e-02 eta: 7:02:42 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.7597 loss: 3.3710 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0710 loss_aux: 1.3000 2023/02/17 15:56:19 - mmengine - INFO - Epoch(train) [52][1160/1345] lr: 1.0000e-02 eta: 7:02:38 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.8958 loss: 3.5175 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1431 loss_aux: 1.3745 2023/02/17 15:56:23 - mmengine - INFO - Epoch(train) [52][1180/1345] lr: 1.0000e-02 eta: 7:02:34 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.5544 loss: 3.3432 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9933 loss_aux: 1.3499 2023/02/17 15:56:27 - mmengine - INFO - Epoch(train) [52][1200/1345] lr: 1.0000e-02 eta: 7:02:30 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.5115 loss: 3.6057 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2201 loss_aux: 1.3856 2023/02/17 15:56:31 - mmengine - INFO - Epoch(train) [52][1220/1345] lr: 1.0000e-02 eta: 7:02:26 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.7115 loss: 3.3459 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0751 loss_aux: 1.2708 2023/02/17 15:56:34 - mmengine - INFO - Epoch(train) [52][1240/1345] lr: 1.0000e-02 eta: 7:02:22 time: 0.1907 data_time: 0.0057 memory: 8327 grad_norm: 7.7573 loss: 3.4071 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0951 loss_aux: 1.3120 2023/02/17 15:56:38 - mmengine - INFO - Epoch(train) [52][1260/1345] lr: 1.0000e-02 eta: 7:02:18 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.9762 loss: 3.6017 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1835 loss_aux: 1.4183 2023/02/17 15:56:42 - mmengine - INFO - Epoch(train) [52][1280/1345] lr: 1.0000e-02 eta: 7:02:14 time: 0.1900 data_time: 0.0057 memory: 8327 grad_norm: 7.7175 loss: 3.3792 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0494 loss_aux: 1.3297 2023/02/17 15:56:46 - mmengine - INFO - Epoch(train) [52][1300/1345] lr: 1.0000e-02 eta: 7:02:10 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.8186 loss: 3.4003 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0739 loss_aux: 1.3264 2023/02/17 15:56:50 - mmengine - INFO - Epoch(train) [52][1320/1345] lr: 1.0000e-02 eta: 7:02:06 time: 0.1899 data_time: 0.0057 memory: 8327 grad_norm: 7.9592 loss: 3.5897 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.2080 loss_aux: 1.3817 2023/02/17 15:56:53 - mmengine - INFO - Epoch(train) [52][1340/1345] lr: 1.0000e-02 eta: 7:02:02 time: 0.1903 data_time: 0.0060 memory: 8327 grad_norm: 7.5871 loss: 3.4493 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0790 loss_aux: 1.3703 2023/02/17 15:56:54 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:56:54 - mmengine - INFO - Epoch(train) [52][1345/1345] lr: 1.0000e-02 eta: 7:02:01 time: 0.1841 data_time: 0.0060 memory: 8327 grad_norm: 7.5226 loss: 4.0880 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.5258 loss_aux: 1.5622 2023/02/17 15:56:54 - mmengine - INFO - Saving checkpoint at 52 epochs 2023/02/17 15:57:01 - mmengine - INFO - Epoch(train) [53][ 20/1345] lr: 1.0000e-02 eta: 7:01:58 time: 0.2074 data_time: 0.0146 memory: 8327 grad_norm: 7.5853 loss: 3.0701 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8371 loss_aux: 1.2330 2023/02/17 15:57:05 - mmengine - INFO - Epoch(train) [53][ 40/1345] lr: 1.0000e-02 eta: 7:01:54 time: 0.1902 data_time: 0.0050 memory: 8327 grad_norm: 7.5618 loss: 3.2106 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9435 loss_aux: 1.2671 2023/02/17 15:57:08 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 15:57:08 - mmengine - INFO - Epoch(train) [53][ 60/1345] lr: 1.0000e-02 eta: 7:01:50 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.6218 loss: 3.4241 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0479 loss_aux: 1.3762 2023/02/17 15:57:12 - mmengine - INFO - Epoch(train) [53][ 80/1345] lr: 1.0000e-02 eta: 7:01:46 time: 0.1899 data_time: 0.0058 memory: 8327 grad_norm: 7.6370 loss: 3.5406 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1604 loss_aux: 1.3803 2023/02/17 15:57:16 - mmengine - INFO - Epoch(train) [53][ 100/1345] lr: 1.0000e-02 eta: 7:01:42 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.8547 loss: 3.3034 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9610 loss_aux: 1.3424 2023/02/17 15:57:20 - mmengine - INFO - Epoch(train) [53][ 120/1345] lr: 1.0000e-02 eta: 7:01:38 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.7536 loss: 3.5147 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1095 loss_aux: 1.4052 2023/02/17 15:57:24 - mmengine - INFO - Epoch(train) [53][ 140/1345] lr: 1.0000e-02 eta: 7:01:34 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.8382 loss: 3.4401 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1009 loss_aux: 1.3391 2023/02/17 15:57:27 - mmengine - INFO - Epoch(train) [53][ 160/1345] lr: 1.0000e-02 eta: 7:01:30 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.6986 loss: 3.6095 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2097 loss_aux: 1.3998 2023/02/17 15:57:31 - mmengine - INFO - Epoch(train) [53][ 180/1345] lr: 1.0000e-02 eta: 7:01:26 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.4583 loss: 3.4153 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1092 loss_aux: 1.3061 2023/02/17 15:57:35 - mmengine - INFO - Epoch(train) [53][ 200/1345] lr: 1.0000e-02 eta: 7:01:23 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.7921 loss: 3.2580 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9261 loss_aux: 1.3318 2023/02/17 15:57:39 - mmengine - INFO - Epoch(train) [53][ 220/1345] lr: 1.0000e-02 eta: 7:01:19 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.6624 loss: 3.6522 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2767 loss_aux: 1.3755 2023/02/17 15:57:43 - mmengine - INFO - Epoch(train) [53][ 240/1345] lr: 1.0000e-02 eta: 7:01:15 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.7244 loss: 3.0375 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7850 loss_aux: 1.2526 2023/02/17 15:57:46 - mmengine - INFO - Epoch(train) [53][ 260/1345] lr: 1.0000e-02 eta: 7:01:11 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.7862 loss: 3.7468 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2796 loss_aux: 1.4672 2023/02/17 15:57:50 - mmengine - INFO - Epoch(train) [53][ 280/1345] lr: 1.0000e-02 eta: 7:01:07 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7828 loss: 3.2817 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9801 loss_aux: 1.3016 2023/02/17 15:57:54 - mmengine - INFO - Epoch(train) [53][ 300/1345] lr: 1.0000e-02 eta: 7:01:03 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.6487 loss: 3.1751 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8736 loss_aux: 1.3016 2023/02/17 15:57:58 - mmengine - INFO - Epoch(train) [53][ 320/1345] lr: 1.0000e-02 eta: 7:00:59 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.4763 loss: 3.4158 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0897 loss_aux: 1.3261 2023/02/17 15:58:02 - mmengine - INFO - Epoch(train) [53][ 340/1345] lr: 1.0000e-02 eta: 7:00:55 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.7302 loss: 3.3652 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0261 loss_aux: 1.3391 2023/02/17 15:58:05 - mmengine - INFO - Epoch(train) [53][ 360/1345] lr: 1.0000e-02 eta: 7:00:51 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 8.0631 loss: 3.9632 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4822 loss_aux: 1.4810 2023/02/17 15:58:09 - mmengine - INFO - Epoch(train) [53][ 380/1345] lr: 1.0000e-02 eta: 7:00:47 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.6286 loss: 3.4795 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1269 loss_aux: 1.3526 2023/02/17 15:58:13 - mmengine - INFO - Epoch(train) [53][ 400/1345] lr: 1.0000e-02 eta: 7:00:43 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.4672 loss: 3.2477 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9614 loss_aux: 1.2863 2023/02/17 15:58:17 - mmengine - INFO - Epoch(train) [53][ 420/1345] lr: 1.0000e-02 eta: 7:00:39 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7002 loss: 3.6751 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1899 loss_aux: 1.4852 2023/02/17 15:58:21 - mmengine - INFO - Epoch(train) [53][ 440/1345] lr: 1.0000e-02 eta: 7:00:35 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.7649 loss: 2.9556 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7623 loss_aux: 1.1934 2023/02/17 15:58:24 - mmengine - INFO - Epoch(train) [53][ 460/1345] lr: 1.0000e-02 eta: 7:00:31 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.8401 loss: 3.5114 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1551 loss_aux: 1.3563 2023/02/17 15:58:28 - mmengine - INFO - Epoch(train) [53][ 480/1345] lr: 1.0000e-02 eta: 7:00:27 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.8923 loss: 3.7497 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3066 loss_aux: 1.4431 2023/02/17 15:58:32 - mmengine - INFO - Epoch(train) [53][ 500/1345] lr: 1.0000e-02 eta: 7:00:24 time: 0.1894 data_time: 0.0059 memory: 8327 grad_norm: 7.6950 loss: 3.5654 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1951 loss_aux: 1.3703 2023/02/17 15:58:36 - mmengine - INFO - Epoch(train) [53][ 520/1345] lr: 1.0000e-02 eta: 7:00:20 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 8.0324 loss: 3.8050 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3607 loss_aux: 1.4443 2023/02/17 15:58:40 - mmengine - INFO - Epoch(train) [53][ 540/1345] lr: 1.0000e-02 eta: 7:00:16 time: 0.1898 data_time: 0.0060 memory: 8327 grad_norm: 7.4683 loss: 3.2482 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9341 loss_aux: 1.3141 2023/02/17 15:58:43 - mmengine - INFO - Epoch(train) [53][ 560/1345] lr: 1.0000e-02 eta: 7:00:12 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.8080 loss: 3.4326 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1286 loss_aux: 1.3040 2023/02/17 15:58:47 - mmengine - INFO - Epoch(train) [53][ 580/1345] lr: 1.0000e-02 eta: 7:00:08 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.7605 loss: 3.4752 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1100 loss_aux: 1.3652 2023/02/17 15:58:51 - mmengine - INFO - Epoch(train) [53][ 600/1345] lr: 1.0000e-02 eta: 7:00:04 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.6245 loss: 3.3155 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9902 loss_aux: 1.3254 2023/02/17 15:58:55 - mmengine - INFO - Epoch(train) [53][ 620/1345] lr: 1.0000e-02 eta: 7:00:00 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.6937 loss: 3.4639 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1090 loss_aux: 1.3549 2023/02/17 15:58:59 - mmengine - INFO - Epoch(train) [53][ 640/1345] lr: 1.0000e-02 eta: 6:59:56 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.4082 loss: 3.0275 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8289 loss_aux: 1.1987 2023/02/17 15:59:02 - mmengine - INFO - Epoch(train) [53][ 660/1345] lr: 1.0000e-02 eta: 6:59:52 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.7090 loss: 3.7373 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2454 loss_aux: 1.4919 2023/02/17 15:59:06 - mmengine - INFO - Epoch(train) [53][ 680/1345] lr: 1.0000e-02 eta: 6:59:48 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.6549 loss: 3.3943 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0459 loss_aux: 1.3484 2023/02/17 15:59:10 - mmengine - INFO - Epoch(train) [53][ 700/1345] lr: 1.0000e-02 eta: 6:59:44 time: 0.1904 data_time: 0.0066 memory: 8327 grad_norm: 7.5695 loss: 3.5836 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1986 loss_aux: 1.3850 2023/02/17 15:59:14 - mmengine - INFO - Epoch(train) [53][ 720/1345] lr: 1.0000e-02 eta: 6:59:40 time: 0.1904 data_time: 0.0060 memory: 8327 grad_norm: 7.8235 loss: 3.6842 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2493 loss_aux: 1.4349 2023/02/17 15:59:18 - mmengine - INFO - Epoch(train) [53][ 740/1345] lr: 1.0000e-02 eta: 6:59:36 time: 0.1899 data_time: 0.0060 memory: 8327 grad_norm: 7.7705 loss: 3.5994 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2049 loss_aux: 1.3945 2023/02/17 15:59:21 - mmengine - INFO - Epoch(train) [53][ 760/1345] lr: 1.0000e-02 eta: 6:59:32 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.6104 loss: 3.5754 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1379 loss_aux: 1.4375 2023/02/17 15:59:25 - mmengine - INFO - Epoch(train) [53][ 780/1345] lr: 1.0000e-02 eta: 6:59:29 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.8541 loss: 3.4273 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1037 loss_aux: 1.3236 2023/02/17 15:59:29 - mmengine - INFO - Epoch(train) [53][ 800/1345] lr: 1.0000e-02 eta: 6:59:25 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.9684 loss: 3.5966 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1758 loss_aux: 1.4207 2023/02/17 15:59:33 - mmengine - INFO - Epoch(train) [53][ 820/1345] lr: 1.0000e-02 eta: 6:59:21 time: 0.1899 data_time: 0.0061 memory: 8327 grad_norm: 7.7780 loss: 3.6399 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2133 loss_aux: 1.4267 2023/02/17 15:59:37 - mmengine - INFO - Epoch(train) [53][ 840/1345] lr: 1.0000e-02 eta: 6:59:17 time: 0.1898 data_time: 0.0060 memory: 8327 grad_norm: 7.7065 loss: 3.3115 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0177 loss_aux: 1.2937 2023/02/17 15:59:40 - mmengine - INFO - Epoch(train) [53][ 860/1345] lr: 1.0000e-02 eta: 6:59:13 time: 0.1897 data_time: 0.0057 memory: 8327 grad_norm: 7.7040 loss: 3.6492 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2064 loss_aux: 1.4428 2023/02/17 15:59:44 - mmengine - INFO - Epoch(train) [53][ 880/1345] lr: 1.0000e-02 eta: 6:59:09 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.6137 loss: 3.7631 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3800 loss_aux: 1.3831 2023/02/17 15:59:48 - mmengine - INFO - Epoch(train) [53][ 900/1345] lr: 1.0000e-02 eta: 6:59:05 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.5549 loss: 3.4780 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1126 loss_aux: 1.3654 2023/02/17 15:59:52 - mmengine - INFO - Epoch(train) [53][ 920/1345] lr: 1.0000e-02 eta: 6:59:01 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.7373 loss: 3.2021 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9902 loss_aux: 1.2119 2023/02/17 15:59:56 - mmengine - INFO - Epoch(train) [53][ 940/1345] lr: 1.0000e-02 eta: 6:58:57 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.6584 loss: 3.2429 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9442 loss_aux: 1.2987 2023/02/17 15:59:59 - mmengine - INFO - Epoch(train) [53][ 960/1345] lr: 1.0000e-02 eta: 6:58:53 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.6680 loss: 3.1098 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8331 loss_aux: 1.2767 2023/02/17 16:00:03 - mmengine - INFO - Epoch(train) [53][ 980/1345] lr: 1.0000e-02 eta: 6:58:49 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.9363 loss: 3.5488 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1833 loss_aux: 1.3656 2023/02/17 16:00:07 - mmengine - INFO - Epoch(train) [53][1000/1345] lr: 1.0000e-02 eta: 6:58:45 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.4530 loss: 3.5310 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1435 loss_aux: 1.3875 2023/02/17 16:00:11 - mmengine - INFO - Epoch(train) [53][1020/1345] lr: 1.0000e-02 eta: 6:58:41 time: 0.1901 data_time: 0.0063 memory: 8327 grad_norm: 7.6060 loss: 3.7041 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2138 loss_aux: 1.4903 2023/02/17 16:00:15 - mmengine - INFO - Epoch(train) [53][1040/1345] lr: 1.0000e-02 eta: 6:58:37 time: 0.1903 data_time: 0.0060 memory: 8327 grad_norm: 7.4740 loss: 3.2892 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0376 loss_aux: 1.2516 2023/02/17 16:00:18 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 16:00:18 - mmengine - INFO - Epoch(train) [53][1060/1345] lr: 1.0000e-02 eta: 6:58:34 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.7080 loss: 3.3926 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0115 loss_aux: 1.3810 2023/02/17 16:00:22 - mmengine - INFO - Epoch(train) [53][1080/1345] lr: 1.0000e-02 eta: 6:58:30 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.5446 loss: 3.4553 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1104 loss_aux: 1.3449 2023/02/17 16:00:26 - mmengine - INFO - Epoch(train) [53][1100/1345] lr: 1.0000e-02 eta: 6:58:26 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.8129 loss: 3.5366 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1689 loss_aux: 1.3677 2023/02/17 16:00:30 - mmengine - INFO - Epoch(train) [53][1120/1345] lr: 1.0000e-02 eta: 6:58:22 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.7654 loss: 3.5405 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1812 loss_aux: 1.3593 2023/02/17 16:00:34 - mmengine - INFO - Epoch(train) [53][1140/1345] lr: 1.0000e-02 eta: 6:58:18 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.9915 loss: 3.4895 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1384 loss_aux: 1.3512 2023/02/17 16:00:37 - mmengine - INFO - Epoch(train) [53][1160/1345] lr: 1.0000e-02 eta: 6:58:14 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.5209 loss: 3.2581 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9548 loss_aux: 1.3032 2023/02/17 16:00:41 - mmengine - INFO - Epoch(train) [53][1180/1345] lr: 1.0000e-02 eta: 6:58:10 time: 0.1910 data_time: 0.0067 memory: 8327 grad_norm: 7.3908 loss: 3.6436 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1940 loss_aux: 1.4496 2023/02/17 16:00:45 - mmengine - INFO - Epoch(train) [53][1200/1345] lr: 1.0000e-02 eta: 6:58:06 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.5448 loss: 3.4082 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1065 loss_aux: 1.3018 2023/02/17 16:00:49 - mmengine - INFO - Epoch(train) [53][1220/1345] lr: 1.0000e-02 eta: 6:58:02 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.8812 loss: 3.7509 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.3811 loss_aux: 1.3698 2023/02/17 16:00:53 - mmengine - INFO - Epoch(train) [53][1240/1345] lr: 1.0000e-02 eta: 6:57:58 time: 0.1919 data_time: 0.0074 memory: 8327 grad_norm: 7.7315 loss: 3.4402 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0686 loss_aux: 1.3716 2023/02/17 16:00:56 - mmengine - INFO - Epoch(train) [53][1260/1345] lr: 1.0000e-02 eta: 6:57:54 time: 0.1901 data_time: 0.0061 memory: 8327 grad_norm: 7.6618 loss: 3.6320 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2196 loss_aux: 1.4124 2023/02/17 16:01:00 - mmengine - INFO - Epoch(train) [53][1280/1345] lr: 1.0000e-02 eta: 6:57:50 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.6520 loss: 3.5504 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2025 loss_aux: 1.3479 2023/02/17 16:01:04 - mmengine - INFO - Epoch(train) [53][1300/1345] lr: 1.0000e-02 eta: 6:57:47 time: 0.1915 data_time: 0.0071 memory: 8327 grad_norm: 7.8798 loss: 3.4020 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0883 loss_aux: 1.3136 2023/02/17 16:01:08 - mmengine - INFO - Epoch(train) [53][1320/1345] lr: 1.0000e-02 eta: 6:57:43 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.5802 loss: 3.3766 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0217 loss_aux: 1.3549 2023/02/17 16:01:12 - mmengine - INFO - Epoch(train) [53][1340/1345] lr: 1.0000e-02 eta: 6:57:39 time: 0.1918 data_time: 0.0068 memory: 8327 grad_norm: 7.4099 loss: 3.0597 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8360 loss_aux: 1.2237 2023/02/17 16:01:13 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 16:01:13 - mmengine - INFO - Epoch(train) [53][1345/1345] lr: 1.0000e-02 eta: 6:57:38 time: 0.1846 data_time: 0.0060 memory: 8327 grad_norm: 7.2999 loss: 3.3743 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.0531 loss_aux: 1.3212 2023/02/17 16:01:13 - mmengine - INFO - Saving checkpoint at 53 epochs 2023/02/17 16:01:19 - mmengine - INFO - Epoch(train) [54][ 20/1345] lr: 1.0000e-02 eta: 6:57:34 time: 0.2054 data_time: 0.0141 memory: 8327 grad_norm: 7.3665 loss: 3.2881 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9897 loss_aux: 1.2985 2023/02/17 16:01:23 - mmengine - INFO - Epoch(train) [54][ 40/1345] lr: 1.0000e-02 eta: 6:57:30 time: 0.1937 data_time: 0.0068 memory: 8327 grad_norm: 7.6709 loss: 3.1843 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9167 loss_aux: 1.2676 2023/02/17 16:01:27 - mmengine - INFO - Epoch(train) [54][ 60/1345] lr: 1.0000e-02 eta: 6:57:27 time: 0.1903 data_time: 0.0049 memory: 8327 grad_norm: 7.7211 loss: 3.4612 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0434 loss_aux: 1.4178 2023/02/17 16:01:31 - mmengine - INFO - Epoch(train) [54][ 80/1345] lr: 1.0000e-02 eta: 6:57:23 time: 0.1910 data_time: 0.0071 memory: 8327 grad_norm: 7.8229 loss: 3.0845 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8797 loss_aux: 1.2048 2023/02/17 16:01:35 - mmengine - INFO - Epoch(train) [54][ 100/1345] lr: 1.0000e-02 eta: 6:57:19 time: 0.1902 data_time: 0.0058 memory: 8327 grad_norm: 7.8365 loss: 3.3385 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0443 loss_aux: 1.2942 2023/02/17 16:01:38 - mmengine - INFO - Epoch(train) [54][ 120/1345] lr: 1.0000e-02 eta: 6:57:15 time: 0.1901 data_time: 0.0059 memory: 8327 grad_norm: 7.6687 loss: 3.5855 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1764 loss_aux: 1.4091 2023/02/17 16:01:42 - mmengine - INFO - Epoch(train) [54][ 140/1345] lr: 1.0000e-02 eta: 6:57:11 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.6967 loss: 3.2873 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9720 loss_aux: 1.3154 2023/02/17 16:01:46 - mmengine - INFO - Epoch(train) [54][ 160/1345] lr: 1.0000e-02 eta: 6:57:07 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.6747 loss: 3.2335 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9447 loss_aux: 1.2888 2023/02/17 16:01:50 - mmengine - INFO - Epoch(train) [54][ 180/1345] lr: 1.0000e-02 eta: 6:57:03 time: 0.1900 data_time: 0.0065 memory: 8327 grad_norm: 7.5285 loss: 3.3252 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0349 loss_aux: 1.2903 2023/02/17 16:01:54 - mmengine - INFO - Epoch(train) [54][ 200/1345] lr: 1.0000e-02 eta: 6:56:59 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.5916 loss: 3.2497 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9661 loss_aux: 1.2836 2023/02/17 16:01:57 - mmengine - INFO - Epoch(train) [54][ 220/1345] lr: 1.0000e-02 eta: 6:56:55 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.6785 loss: 3.4101 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.0582 loss_aux: 1.3519 2023/02/17 16:02:01 - mmengine - INFO - Epoch(train) [54][ 240/1345] lr: 1.0000e-02 eta: 6:56:51 time: 0.1896 data_time: 0.0061 memory: 8327 grad_norm: 7.9606 loss: 3.6005 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1927 loss_aux: 1.4077 2023/02/17 16:02:05 - mmengine - INFO - Epoch(train) [54][ 260/1345] lr: 1.0000e-02 eta: 6:56:47 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.8778 loss: 3.3319 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0261 loss_aux: 1.3058 2023/02/17 16:02:09 - mmengine - INFO - Epoch(train) [54][ 280/1345] lr: 1.0000e-02 eta: 6:56:43 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.7605 loss: 3.2405 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9661 loss_aux: 1.2744 2023/02/17 16:02:13 - mmengine - INFO - Epoch(train) [54][ 300/1345] lr: 1.0000e-02 eta: 6:56:39 time: 0.1895 data_time: 0.0057 memory: 8327 grad_norm: 7.7536 loss: 3.4172 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0308 loss_aux: 1.3864 2023/02/17 16:02:16 - mmengine - INFO - Epoch(train) [54][ 320/1345] lr: 1.0000e-02 eta: 6:56:36 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.7319 loss: 3.2516 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8980 loss_aux: 1.3536 2023/02/17 16:02:20 - mmengine - INFO - Epoch(train) [54][ 340/1345] lr: 1.0000e-02 eta: 6:56:32 time: 0.1909 data_time: 0.0074 memory: 8327 grad_norm: 7.7582 loss: 3.1100 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8457 loss_aux: 1.2643 2023/02/17 16:02:24 - mmengine - INFO - Epoch(train) [54][ 360/1345] lr: 1.0000e-02 eta: 6:56:28 time: 0.1905 data_time: 0.0070 memory: 8327 grad_norm: 7.7503 loss: 3.5043 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.0949 loss_aux: 1.4094 2023/02/17 16:02:28 - mmengine - INFO - Epoch(train) [54][ 380/1345] lr: 1.0000e-02 eta: 6:56:24 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.8608 loss: 3.7371 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3111 loss_aux: 1.4260 2023/02/17 16:02:32 - mmengine - INFO - Epoch(train) [54][ 400/1345] lr: 1.0000e-02 eta: 6:56:20 time: 0.1894 data_time: 0.0057 memory: 8327 grad_norm: 7.5346 loss: 3.2606 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8879 loss_aux: 1.3728 2023/02/17 16:02:35 - mmengine - INFO - Epoch(train) [54][ 420/1345] lr: 1.0000e-02 eta: 6:56:16 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.7477 loss: 3.4399 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1126 loss_aux: 1.3272 2023/02/17 16:02:39 - mmengine - INFO - Epoch(train) [54][ 440/1345] lr: 1.0000e-02 eta: 6:56:12 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.4727 loss: 3.2932 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9747 loss_aux: 1.3185 2023/02/17 16:02:43 - mmengine - INFO - Epoch(train) [54][ 460/1345] lr: 1.0000e-02 eta: 6:56:08 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.8545 loss: 3.6037 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2136 loss_aux: 1.3901 2023/02/17 16:02:47 - mmengine - INFO - Epoch(train) [54][ 480/1345] lr: 1.0000e-02 eta: 6:56:04 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.7938 loss: 3.9546 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4559 loss_aux: 1.4987 2023/02/17 16:02:51 - mmengine - INFO - Epoch(train) [54][ 500/1345] lr: 1.0000e-02 eta: 6:56:00 time: 0.1915 data_time: 0.0076 memory: 8327 grad_norm: 7.6337 loss: 3.7376 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2869 loss_aux: 1.4507 2023/02/17 16:02:55 - mmengine - INFO - Epoch(train) [54][ 520/1345] lr: 1.0000e-02 eta: 6:55:56 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.6667 loss: 3.1744 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9013 loss_aux: 1.2731 2023/02/17 16:02:58 - mmengine - INFO - Epoch(train) [54][ 540/1345] lr: 1.0000e-02 eta: 6:55:52 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.5881 loss: 3.6121 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2332 loss_aux: 1.3788 2023/02/17 16:03:02 - mmengine - INFO - Epoch(train) [54][ 560/1345] lr: 1.0000e-02 eta: 6:55:49 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.4558 loss: 3.1999 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9203 loss_aux: 1.2796 2023/02/17 16:03:06 - mmengine - INFO - Epoch(train) [54][ 580/1345] lr: 1.0000e-02 eta: 6:55:45 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.6383 loss: 3.3759 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0844 loss_aux: 1.2915 2023/02/17 16:03:10 - mmengine - INFO - Epoch(train) [54][ 600/1345] lr: 1.0000e-02 eta: 6:55:41 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.9556 loss: 3.3881 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0053 loss_aux: 1.3828 2023/02/17 16:03:14 - mmengine - INFO - Epoch(train) [54][ 620/1345] lr: 1.0000e-02 eta: 6:55:37 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.4900 loss: 3.2570 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9596 loss_aux: 1.2974 2023/02/17 16:03:17 - mmengine - INFO - Epoch(train) [54][ 640/1345] lr: 1.0000e-02 eta: 6:55:33 time: 0.1911 data_time: 0.0074 memory: 8327 grad_norm: 7.7316 loss: 3.0430 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8032 loss_aux: 1.2399 2023/02/17 16:03:21 - mmengine - INFO - Epoch(train) [54][ 660/1345] lr: 1.0000e-02 eta: 6:55:29 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.5124 loss: 3.5675 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1552 loss_aux: 1.4123 2023/02/17 16:03:25 - mmengine - INFO - Epoch(train) [54][ 680/1345] lr: 1.0000e-02 eta: 6:55:25 time: 0.1894 data_time: 0.0058 memory: 8327 grad_norm: 7.6391 loss: 3.1050 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8950 loss_aux: 1.2100 2023/02/17 16:03:29 - mmengine - INFO - Epoch(train) [54][ 700/1345] lr: 1.0000e-02 eta: 6:55:21 time: 0.1904 data_time: 0.0058 memory: 8327 grad_norm: 7.9144 loss: 3.3686 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0570 loss_aux: 1.3117 2023/02/17 16:03:32 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 16:03:33 - mmengine - INFO - Epoch(train) [54][ 720/1345] lr: 1.0000e-02 eta: 6:55:17 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.9776 loss: 3.1762 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9251 loss_aux: 1.2511 2023/02/17 16:03:36 - mmengine - INFO - Epoch(train) [54][ 740/1345] lr: 1.0000e-02 eta: 6:55:13 time: 0.1904 data_time: 0.0057 memory: 8327 grad_norm: 7.7634 loss: 3.1933 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9304 loss_aux: 1.2629 2023/02/17 16:03:40 - mmengine - INFO - Epoch(train) [54][ 760/1345] lr: 1.0000e-02 eta: 6:55:09 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.9209 loss: 3.5677 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1731 loss_aux: 1.3946 2023/02/17 16:03:44 - mmengine - INFO - Epoch(train) [54][ 780/1345] lr: 1.0000e-02 eta: 6:55:05 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.9089 loss: 3.0584 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8191 loss_aux: 1.2393 2023/02/17 16:03:48 - mmengine - INFO - Epoch(train) [54][ 800/1345] lr: 1.0000e-02 eta: 6:55:02 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.7944 loss: 3.5269 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.1072 loss_aux: 1.4197 2023/02/17 16:03:52 - mmengine - INFO - Epoch(train) [54][ 820/1345] lr: 1.0000e-02 eta: 6:54:58 time: 0.1905 data_time: 0.0058 memory: 8327 grad_norm: 7.5710 loss: 3.3772 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0334 loss_aux: 1.3438 2023/02/17 16:03:55 - mmengine - INFO - Epoch(train) [54][ 840/1345] lr: 1.0000e-02 eta: 6:54:54 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.8256 loss: 3.1953 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9282 loss_aux: 1.2671 2023/02/17 16:03:59 - mmengine - INFO - Epoch(train) [54][ 860/1345] lr: 1.0000e-02 eta: 6:54:50 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.9815 loss: 3.6943 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2481 loss_aux: 1.4463 2023/02/17 16:04:03 - mmengine - INFO - Epoch(train) [54][ 880/1345] lr: 1.0000e-02 eta: 6:54:46 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 8.0395 loss: 3.3710 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0073 loss_aux: 1.3637 2023/02/17 16:04:07 - mmengine - INFO - Epoch(train) [54][ 900/1345] lr: 1.0000e-02 eta: 6:54:42 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.9513 loss: 3.5822 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1541 loss_aux: 1.4281 2023/02/17 16:04:11 - mmengine - INFO - Epoch(train) [54][ 920/1345] lr: 1.0000e-02 eta: 6:54:38 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.7668 loss: 3.3150 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0633 loss_aux: 1.2517 2023/02/17 16:04:14 - mmengine - INFO - Epoch(train) [54][ 940/1345] lr: 1.0000e-02 eta: 6:54:34 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.7393 loss: 3.6581 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2587 loss_aux: 1.3994 2023/02/17 16:04:18 - mmengine - INFO - Epoch(train) [54][ 960/1345] lr: 1.0000e-02 eta: 6:54:30 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.7603 loss: 3.5510 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1963 loss_aux: 1.3547 2023/02/17 16:04:22 - mmengine - INFO - Epoch(train) [54][ 980/1345] lr: 1.0000e-02 eta: 6:54:26 time: 0.1898 data_time: 0.0060 memory: 8327 grad_norm: 7.6618 loss: 3.8446 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4185 loss_aux: 1.4261 2023/02/17 16:04:26 - mmengine - INFO - Epoch(train) [54][1000/1345] lr: 1.0000e-02 eta: 6:54:22 time: 0.1900 data_time: 0.0059 memory: 8327 grad_norm: 7.8466 loss: 3.7013 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2834 loss_aux: 1.4179 2023/02/17 16:04:30 - mmengine - INFO - Epoch(train) [54][1020/1345] lr: 1.0000e-02 eta: 6:54:18 time: 0.1898 data_time: 0.0060 memory: 8327 grad_norm: 7.9138 loss: 3.6418 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2285 loss_aux: 1.4133 2023/02/17 16:04:33 - mmengine - INFO - Epoch(train) [54][1040/1345] lr: 1.0000e-02 eta: 6:54:14 time: 0.1901 data_time: 0.0061 memory: 8327 grad_norm: 7.9873 loss: 3.6094 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.1838 loss_aux: 1.4256 2023/02/17 16:04:37 - mmengine - INFO - Epoch(train) [54][1060/1345] lr: 1.0000e-02 eta: 6:54:11 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.7516 loss: 3.4164 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.0581 loss_aux: 1.3583 2023/02/17 16:04:41 - mmengine - INFO - Epoch(train) [54][1080/1345] lr: 1.0000e-02 eta: 6:54:07 time: 0.1900 data_time: 0.0061 memory: 8327 grad_norm: 7.7969 loss: 3.6613 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.2425 loss_aux: 1.4187 2023/02/17 16:04:45 - mmengine - INFO - Epoch(train) [54][1100/1345] lr: 1.0000e-02 eta: 6:54:03 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.5507 loss: 3.4346 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0658 loss_aux: 1.3689 2023/02/17 16:04:49 - mmengine - INFO - Epoch(train) [54][1120/1345] lr: 1.0000e-02 eta: 6:53:59 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.6856 loss: 3.2049 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9811 loss_aux: 1.2238 2023/02/17 16:04:52 - mmengine - INFO - Epoch(train) [54][1140/1345] lr: 1.0000e-02 eta: 6:53:55 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.8324 loss: 3.2201 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9613 loss_aux: 1.2589 2023/02/17 16:04:56 - mmengine - INFO - Epoch(train) [54][1160/1345] lr: 1.0000e-02 eta: 6:53:51 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.8698 loss: 3.7730 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3475 loss_aux: 1.4254 2023/02/17 16:05:00 - mmengine - INFO - Epoch(train) [54][1180/1345] lr: 1.0000e-02 eta: 6:53:47 time: 0.1997 data_time: 0.0158 memory: 8327 grad_norm: 7.6074 loss: 3.2832 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0082 loss_aux: 1.2750 2023/02/17 16:05:04 - mmengine - INFO - Epoch(train) [54][1200/1345] lr: 1.0000e-02 eta: 6:53:43 time: 0.1899 data_time: 0.0060 memory: 8327 grad_norm: 7.7024 loss: 3.7418 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2848 loss_aux: 1.4570 2023/02/17 16:05:08 - mmengine - INFO - Epoch(train) [54][1220/1345] lr: 1.0000e-02 eta: 6:53:40 time: 0.1898 data_time: 0.0060 memory: 8327 grad_norm: 7.6940 loss: 3.1461 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8440 loss_aux: 1.3021 2023/02/17 16:05:12 - mmengine - INFO - Epoch(train) [54][1240/1345] lr: 1.0000e-02 eta: 6:53:36 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.5673 loss: 3.3580 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0529 loss_aux: 1.3051 2023/02/17 16:05:15 - mmengine - INFO - Epoch(train) [54][1260/1345] lr: 1.0000e-02 eta: 6:53:32 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.9162 loss: 3.4902 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1149 loss_aux: 1.3753 2023/02/17 16:05:19 - mmengine - INFO - Epoch(train) [54][1280/1345] lr: 1.0000e-02 eta: 6:53:28 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.7313 loss: 3.5750 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1859 loss_aux: 1.3892 2023/02/17 16:05:23 - mmengine - INFO - Epoch(train) [54][1300/1345] lr: 1.0000e-02 eta: 6:53:24 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7057 loss: 3.3730 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0326 loss_aux: 1.3404 2023/02/17 16:05:27 - mmengine - INFO - Epoch(train) [54][1320/1345] lr: 1.0000e-02 eta: 6:53:20 time: 0.1893 data_time: 0.0058 memory: 8327 grad_norm: 7.6628 loss: 3.4064 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0615 loss_aux: 1.3449 2023/02/17 16:05:31 - mmengine - INFO - Epoch(train) [54][1340/1345] lr: 1.0000e-02 eta: 6:53:16 time: 0.1909 data_time: 0.0069 memory: 8327 grad_norm: 7.5030 loss: 3.3570 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9860 loss_aux: 1.3710 2023/02/17 16:05:31 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 16:05:31 - mmengine - INFO - Epoch(train) [54][1345/1345] lr: 1.0000e-02 eta: 6:53:15 time: 0.1842 data_time: 0.0061 memory: 8327 grad_norm: 7.4391 loss: 3.4935 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.0940 loss_aux: 1.3995 2023/02/17 16:05:31 - mmengine - INFO - Saving checkpoint at 54 epochs 2023/02/17 16:05:38 - mmengine - INFO - Epoch(train) [55][ 20/1345] lr: 1.0000e-02 eta: 6:53:11 time: 0.2046 data_time: 0.0151 memory: 8327 grad_norm: 7.4490 loss: 3.2261 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9051 loss_aux: 1.3210 2023/02/17 16:05:42 - mmengine - INFO - Epoch(train) [55][ 40/1345] lr: 1.0000e-02 eta: 6:53:08 time: 0.1910 data_time: 0.0042 memory: 8327 grad_norm: 7.7426 loss: 3.9577 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4722 loss_aux: 1.4855 2023/02/17 16:05:46 - mmengine - INFO - Epoch(train) [55][ 60/1345] lr: 1.0000e-02 eta: 6:53:04 time: 0.1901 data_time: 0.0058 memory: 8327 grad_norm: 7.5353 loss: 3.1567 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9124 loss_aux: 1.2442 2023/02/17 16:05:49 - mmengine - INFO - Epoch(train) [55][ 80/1345] lr: 1.0000e-02 eta: 6:53:00 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.6239 loss: 2.8974 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6686 loss_aux: 1.2289 2023/02/17 16:05:53 - mmengine - INFO - Epoch(train) [55][ 100/1345] lr: 1.0000e-02 eta: 6:52:56 time: 0.1897 data_time: 0.0057 memory: 8327 grad_norm: 7.6876 loss: 3.2356 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9844 loss_aux: 1.2512 2023/02/17 16:05:57 - mmengine - INFO - Epoch(train) [55][ 120/1345] lr: 1.0000e-02 eta: 6:52:52 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.5341 loss: 3.2428 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9436 loss_aux: 1.2992 2023/02/17 16:06:01 - mmengine - INFO - Epoch(train) [55][ 140/1345] lr: 1.0000e-02 eta: 6:52:48 time: 0.1904 data_time: 0.0064 memory: 8327 grad_norm: 7.7128 loss: 3.4593 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0946 loss_aux: 1.3647 2023/02/17 16:06:05 - mmengine - INFO - Epoch(train) [55][ 160/1345] lr: 1.0000e-02 eta: 6:52:44 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.5051 loss: 3.4548 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0807 loss_aux: 1.3741 2023/02/17 16:06:08 - mmengine - INFO - Epoch(train) [55][ 180/1345] lr: 1.0000e-02 eta: 6:52:40 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.9102 loss: 3.5013 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1339 loss_aux: 1.3674 2023/02/17 16:06:12 - mmengine - INFO - Epoch(train) [55][ 200/1345] lr: 1.0000e-02 eta: 6:52:36 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.7850 loss: 3.7695 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3051 loss_aux: 1.4644 2023/02/17 16:06:16 - mmengine - INFO - Epoch(train) [55][ 220/1345] lr: 1.0000e-02 eta: 6:52:32 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.5276 loss: 3.6749 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2224 loss_aux: 1.4525 2023/02/17 16:06:20 - mmengine - INFO - Epoch(train) [55][ 240/1345] lr: 1.0000e-02 eta: 6:52:28 time: 0.1909 data_time: 0.0070 memory: 8327 grad_norm: 7.7106 loss: 3.4692 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0958 loss_aux: 1.3734 2023/02/17 16:06:24 - mmengine - INFO - Epoch(train) [55][ 260/1345] lr: 1.0000e-02 eta: 6:52:24 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.5820 loss: 3.2762 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9840 loss_aux: 1.2921 2023/02/17 16:06:27 - mmengine - INFO - Epoch(train) [55][ 280/1345] lr: 1.0000e-02 eta: 6:52:21 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.5387 loss: 3.3594 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9929 loss_aux: 1.3665 2023/02/17 16:06:31 - mmengine - INFO - Epoch(train) [55][ 300/1345] lr: 1.0000e-02 eta: 6:52:17 time: 0.1914 data_time: 0.0073 memory: 8327 grad_norm: 7.5178 loss: 3.2516 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 1.9524 loss_aux: 1.2992 2023/02/17 16:06:35 - mmengine - INFO - Epoch(train) [55][ 320/1345] lr: 1.0000e-02 eta: 6:52:13 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.7110 loss: 3.4411 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0918 loss_aux: 1.3493 2023/02/17 16:06:39 - mmengine - INFO - Epoch(train) [55][ 340/1345] lr: 1.0000e-02 eta: 6:52:09 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.5537 loss: 3.1529 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9018 loss_aux: 1.2511 2023/02/17 16:06:43 - mmengine - INFO - Epoch(train) [55][ 360/1345] lr: 1.0000e-02 eta: 6:52:05 time: 0.1899 data_time: 0.0058 memory: 8327 grad_norm: 7.8554 loss: 3.6597 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2017 loss_aux: 1.4580 2023/02/17 16:06:45 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 16:06:47 - mmengine - INFO - Epoch(train) [55][ 380/1345] lr: 1.0000e-02 eta: 6:52:01 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.8694 loss: 3.7913 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3474 loss_aux: 1.4440 2023/02/17 16:06:50 - mmengine - INFO - Epoch(train) [55][ 400/1345] lr: 1.0000e-02 eta: 6:51:57 time: 0.1906 data_time: 0.0066 memory: 8327 grad_norm: 7.6972 loss: 3.2381 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9512 loss_aux: 1.2869 2023/02/17 16:06:54 - mmengine - INFO - Epoch(train) [55][ 420/1345] lr: 1.0000e-02 eta: 6:51:53 time: 0.1901 data_time: 0.0061 memory: 8327 grad_norm: 8.0752 loss: 3.5766 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1903 loss_aux: 1.3863 2023/02/17 16:06:58 - mmengine - INFO - Epoch(train) [55][ 440/1345] lr: 1.0000e-02 eta: 6:51:49 time: 0.1899 data_time: 0.0060 memory: 8327 grad_norm: 7.8506 loss: 3.7601 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3369 loss_aux: 1.4231 2023/02/17 16:07:02 - mmengine - INFO - Epoch(train) [55][ 460/1345] lr: 1.0000e-02 eta: 6:51:45 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.8427 loss: 3.6721 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2940 loss_aux: 1.3781 2023/02/17 16:07:06 - mmengine - INFO - Epoch(train) [55][ 480/1345] lr: 1.0000e-02 eta: 6:51:41 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7503 loss: 3.1701 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9369 loss_aux: 1.2332 2023/02/17 16:07:09 - mmengine - INFO - Epoch(train) [55][ 500/1345] lr: 1.0000e-02 eta: 6:51:38 time: 0.1901 data_time: 0.0059 memory: 8327 grad_norm: 8.0892 loss: 3.4577 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1101 loss_aux: 1.3476 2023/02/17 16:07:13 - mmengine - INFO - Epoch(train) [55][ 520/1345] lr: 1.0000e-02 eta: 6:51:34 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.7559 loss: 3.3668 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0468 loss_aux: 1.3200 2023/02/17 16:07:17 - mmengine - INFO - Epoch(train) [55][ 540/1345] lr: 1.0000e-02 eta: 6:51:30 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.5785 loss: 3.6391 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.2191 loss_aux: 1.4200 2023/02/17 16:07:21 - mmengine - INFO - Epoch(train) [55][ 560/1345] lr: 1.0000e-02 eta: 6:51:26 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 8.0520 loss: 3.8556 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3641 loss_aux: 1.4915 2023/02/17 16:07:25 - mmengine - INFO - Epoch(train) [55][ 580/1345] lr: 1.0000e-02 eta: 6:51:22 time: 0.1905 data_time: 0.0059 memory: 8327 grad_norm: 7.8993 loss: 3.5748 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1606 loss_aux: 1.4142 2023/02/17 16:07:28 - mmengine - INFO - Epoch(train) [55][ 600/1345] lr: 1.0000e-02 eta: 6:51:18 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.6833 loss: 3.5060 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1785 loss_aux: 1.3275 2023/02/17 16:07:32 - mmengine - INFO - Epoch(train) [55][ 620/1345] lr: 1.0000e-02 eta: 6:51:14 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.6940 loss: 3.5406 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1233 loss_aux: 1.4173 2023/02/17 16:07:36 - mmengine - INFO - Epoch(train) [55][ 640/1345] lr: 1.0000e-02 eta: 6:51:10 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.8332 loss: 3.5781 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2314 loss_aux: 1.3467 2023/02/17 16:07:40 - mmengine - INFO - Epoch(train) [55][ 660/1345] lr: 1.0000e-02 eta: 6:51:06 time: 0.1896 data_time: 0.0061 memory: 8327 grad_norm: 7.9772 loss: 3.3458 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0036 loss_aux: 1.3422 2023/02/17 16:07:44 - mmengine - INFO - Epoch(train) [55][ 680/1345] lr: 1.0000e-02 eta: 6:51:02 time: 0.1903 data_time: 0.0058 memory: 8327 grad_norm: 7.7379 loss: 3.5115 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1066 loss_aux: 1.4049 2023/02/17 16:07:47 - mmengine - INFO - Epoch(train) [55][ 700/1345] lr: 1.0000e-02 eta: 6:50:58 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.4705 loss: 3.2548 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9242 loss_aux: 1.3305 2023/02/17 16:07:51 - mmengine - INFO - Epoch(train) [55][ 720/1345] lr: 1.0000e-02 eta: 6:50:54 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.8090 loss: 3.3582 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0379 loss_aux: 1.3204 2023/02/17 16:07:55 - mmengine - INFO - Epoch(train) [55][ 740/1345] lr: 1.0000e-02 eta: 6:50:51 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.9744 loss: 3.4322 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1124 loss_aux: 1.3198 2023/02/17 16:07:59 - mmengine - INFO - Epoch(train) [55][ 760/1345] lr: 1.0000e-02 eta: 6:50:47 time: 0.1923 data_time: 0.0058 memory: 8327 grad_norm: 7.8952 loss: 3.5979 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1599 loss_aux: 1.4380 2023/02/17 16:08:03 - mmengine - INFO - Epoch(train) [55][ 780/1345] lr: 1.0000e-02 eta: 6:50:43 time: 0.1911 data_time: 0.0072 memory: 8327 grad_norm: 7.9062 loss: 3.4380 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0481 loss_aux: 1.3899 2023/02/17 16:08:06 - mmengine - INFO - Epoch(train) [55][ 800/1345] lr: 1.0000e-02 eta: 6:50:39 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.6453 loss: 3.3470 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0325 loss_aux: 1.3146 2023/02/17 16:08:10 - mmengine - INFO - Epoch(train) [55][ 820/1345] lr: 1.0000e-02 eta: 6:50:35 time: 0.1901 data_time: 0.0061 memory: 8327 grad_norm: 7.8023 loss: 3.6042 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1883 loss_aux: 1.4159 2023/02/17 16:08:14 - mmengine - INFO - Epoch(train) [55][ 840/1345] lr: 1.0000e-02 eta: 6:50:32 time: 0.2097 data_time: 0.0260 memory: 8327 grad_norm: 7.6004 loss: 3.0491 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8221 loss_aux: 1.2270 2023/02/17 16:08:18 - mmengine - INFO - Epoch(train) [55][ 860/1345] lr: 1.0000e-02 eta: 6:50:28 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.9242 loss: 3.4083 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0959 loss_aux: 1.3125 2023/02/17 16:08:22 - mmengine - INFO - Epoch(train) [55][ 880/1345] lr: 1.0000e-02 eta: 6:50:24 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.8178 loss: 3.2018 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9290 loss_aux: 1.2728 2023/02/17 16:08:26 - mmengine - INFO - Epoch(train) [55][ 900/1345] lr: 1.0000e-02 eta: 6:50:20 time: 0.1932 data_time: 0.0094 memory: 8327 grad_norm: 7.7321 loss: 3.3203 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0092 loss_aux: 1.3111 2023/02/17 16:08:30 - mmengine - INFO - Epoch(train) [55][ 920/1345] lr: 1.0000e-02 eta: 6:50:16 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.7794 loss: 3.4687 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.0948 loss_aux: 1.3739 2023/02/17 16:08:33 - mmengine - INFO - Epoch(train) [55][ 940/1345] lr: 1.0000e-02 eta: 6:50:12 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.8340 loss: 3.8993 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4314 loss_aux: 1.4679 2023/02/17 16:08:37 - mmengine - INFO - Epoch(train) [55][ 960/1345] lr: 1.0000e-02 eta: 6:50:08 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.7694 loss: 3.6162 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1985 loss_aux: 1.4177 2023/02/17 16:08:41 - mmengine - INFO - Epoch(train) [55][ 980/1345] lr: 1.0000e-02 eta: 6:50:04 time: 0.1900 data_time: 0.0059 memory: 8327 grad_norm: 7.7052 loss: 3.2790 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0028 loss_aux: 1.2762 2023/02/17 16:08:45 - mmengine - INFO - Epoch(train) [55][1000/1345] lr: 1.0000e-02 eta: 6:50:01 time: 0.1899 data_time: 0.0058 memory: 8327 grad_norm: 7.7624 loss: 3.6503 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2511 loss_aux: 1.3992 2023/02/17 16:08:49 - mmengine - INFO - Epoch(train) [55][1020/1345] lr: 1.0000e-02 eta: 6:49:57 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.7960 loss: 3.6587 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2312 loss_aux: 1.4275 2023/02/17 16:08:53 - mmengine - INFO - Epoch(train) [55][1040/1345] lr: 1.0000e-02 eta: 6:49:53 time: 0.1903 data_time: 0.0060 memory: 8327 grad_norm: 7.8137 loss: 3.7626 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.2974 loss_aux: 1.4652 2023/02/17 16:08:56 - mmengine - INFO - Epoch(train) [55][1060/1345] lr: 1.0000e-02 eta: 6:49:49 time: 0.1918 data_time: 0.0080 memory: 8327 grad_norm: 7.7338 loss: 3.4896 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.1239 loss_aux: 1.3658 2023/02/17 16:09:00 - mmengine - INFO - Epoch(train) [55][1080/1345] lr: 1.0000e-02 eta: 6:49:45 time: 0.1900 data_time: 0.0059 memory: 8327 grad_norm: 7.7789 loss: 3.5293 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1874 loss_aux: 1.3418 2023/02/17 16:09:04 - mmengine - INFO - Epoch(train) [55][1100/1345] lr: 1.0000e-02 eta: 6:49:41 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.8117 loss: 3.6551 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2714 loss_aux: 1.3837 2023/02/17 16:09:08 - mmengine - INFO - Epoch(train) [55][1120/1345] lr: 1.0000e-02 eta: 6:49:37 time: 0.1903 data_time: 0.0061 memory: 8327 grad_norm: 7.5488 loss: 3.3695 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0438 loss_aux: 1.3258 2023/02/17 16:09:12 - mmengine - INFO - Epoch(train) [55][1140/1345] lr: 1.0000e-02 eta: 6:49:33 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.7554 loss: 3.3054 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9774 loss_aux: 1.3279 2023/02/17 16:09:15 - mmengine - INFO - Epoch(train) [55][1160/1345] lr: 1.0000e-02 eta: 6:49:29 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.8826 loss: 3.2934 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0006 loss_aux: 1.2929 2023/02/17 16:09:19 - mmengine - INFO - Epoch(train) [55][1180/1345] lr: 1.0000e-02 eta: 6:49:25 time: 0.1898 data_time: 0.0060 memory: 8327 grad_norm: 7.8127 loss: 3.4252 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0554 loss_aux: 1.3698 2023/02/17 16:09:23 - mmengine - INFO - Epoch(train) [55][1200/1345] lr: 1.0000e-02 eta: 6:49:21 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.9423 loss: 3.5932 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1565 loss_aux: 1.4367 2023/02/17 16:09:27 - mmengine - INFO - Epoch(train) [55][1220/1345] lr: 1.0000e-02 eta: 6:49:18 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.8886 loss: 3.5844 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.2214 loss_aux: 1.3629 2023/02/17 16:09:31 - mmengine - INFO - Epoch(train) [55][1240/1345] lr: 1.0000e-02 eta: 6:49:14 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.5602 loss: 3.5737 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2004 loss_aux: 1.3733 2023/02/17 16:09:34 - mmengine - INFO - Epoch(train) [55][1260/1345] lr: 1.0000e-02 eta: 6:49:10 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.7813 loss: 3.5989 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1855 loss_aux: 1.4134 2023/02/17 16:09:38 - mmengine - INFO - Epoch(train) [55][1280/1345] lr: 1.0000e-02 eta: 6:49:06 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.8353 loss: 3.3813 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0400 loss_aux: 1.3414 2023/02/17 16:09:42 - mmengine - INFO - Epoch(train) [55][1300/1345] lr: 1.0000e-02 eta: 6:49:02 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.7392 loss: 3.4507 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0848 loss_aux: 1.3659 2023/02/17 16:09:46 - mmengine - INFO - Epoch(train) [55][1320/1345] lr: 1.0000e-02 eta: 6:48:58 time: 0.1900 data_time: 0.0060 memory: 8327 grad_norm: 7.6308 loss: 3.4582 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0738 loss_aux: 1.3844 2023/02/17 16:09:50 - mmengine - INFO - Epoch(train) [55][1340/1345] lr: 1.0000e-02 eta: 6:48:54 time: 0.1908 data_time: 0.0060 memory: 8327 grad_norm: 7.7709 loss: 3.3214 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9610 loss_aux: 1.3603 2023/02/17 16:09:50 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 16:09:50 - mmengine - INFO - Epoch(train) [55][1345/1345] lr: 1.0000e-02 eta: 6:48:53 time: 0.1851 data_time: 0.0061 memory: 8327 grad_norm: 7.6718 loss: 3.7071 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.2999 loss_aux: 1.4072 2023/02/17 16:09:50 - mmengine - INFO - Saving checkpoint at 55 epochs 2023/02/17 16:09:54 - mmengine - INFO - Epoch(val) [55][ 20/181] eta: 0:00:09 time: 0.0567 data_time: 0.0076 memory: 1994 2023/02/17 16:09:55 - mmengine - INFO - Epoch(val) [55][ 40/181] eta: 0:00:07 time: 0.0528 data_time: 0.0047 memory: 1994 2023/02/17 16:09:56 - mmengine - INFO - Epoch(val) [55][ 60/181] eta: 0:00:06 time: 0.0526 data_time: 0.0046 memory: 1994 2023/02/17 16:09:57 - mmengine - INFO - Epoch(val) [55][ 80/181] eta: 0:00:05 time: 0.0532 data_time: 0.0048 memory: 1994 2023/02/17 16:09:58 - mmengine - INFO - Epoch(val) [55][100/181] eta: 0:00:04 time: 0.0526 data_time: 0.0046 memory: 1994 2023/02/17 16:09:59 - mmengine - INFO - Epoch(val) [55][120/181] eta: 0:00:03 time: 0.0526 data_time: 0.0048 memory: 1994 2023/02/17 16:10:00 - mmengine - INFO - Epoch(val) [55][140/181] eta: 0:00:02 time: 0.0521 data_time: 0.0044 memory: 1994 2023/02/17 16:10:01 - mmengine - INFO - Epoch(val) [55][160/181] eta: 0:00:01 time: 0.0520 data_time: 0.0045 memory: 1994 2023/02/17 16:10:02 - mmengine - INFO - Epoch(val) [55][180/181] eta: 0:00:00 time: 0.0520 data_time: 0.0045 memory: 1994 2023/02/17 16:10:03 - mmengine - INFO - Epoch(val) [55][181/181] acc/top1: 0.3810 acc/top5: 0.6840 acc/mean1: 0.3432 2023/02/17 16:10:03 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/lilin/Repos/mmact_dev/mmaction2/work_dirs/fix_flip/tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb/best_acc/top1_epoch_45.pth is removed 2023/02/17 16:10:05 - mmengine - INFO - The best checkpoint with 0.3810 acc/top1 at 55 epoch is saved to best_acc/top1_epoch_55.pth. 2023/02/17 16:10:09 - mmengine - INFO - Epoch(train) [56][ 20/1345] lr: 1.0000e-02 eta: 6:48:50 time: 0.2053 data_time: 0.0151 memory: 8327 grad_norm: 7.9120 loss: 3.4633 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0843 loss_aux: 1.3790 2023/02/17 16:10:10 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 16:10:13 - mmengine - INFO - Epoch(train) [56][ 40/1345] lr: 1.0000e-02 eta: 6:48:46 time: 0.1907 data_time: 0.0047 memory: 8327 grad_norm: 7.6741 loss: 3.1102 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.8583 loss_aux: 1.2519 2023/02/17 16:10:17 - mmengine - INFO - Epoch(train) [56][ 60/1345] lr: 1.0000e-02 eta: 6:48:42 time: 0.1912 data_time: 0.0060 memory: 8327 grad_norm: 7.9682 loss: 3.3014 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9930 loss_aux: 1.3084 2023/02/17 16:10:20 - mmengine - INFO - Epoch(train) [56][ 80/1345] lr: 1.0000e-02 eta: 6:48:38 time: 0.1903 data_time: 0.0060 memory: 8327 grad_norm: 7.8993 loss: 3.6678 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2817 loss_aux: 1.3861 2023/02/17 16:10:24 - mmengine - INFO - Epoch(train) [56][ 100/1345] lr: 1.0000e-02 eta: 6:48:34 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 8.1968 loss: 3.6327 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2732 loss_aux: 1.3595 2023/02/17 16:10:28 - mmengine - INFO - Epoch(train) [56][ 120/1345] lr: 1.0000e-02 eta: 6:48:30 time: 0.1920 data_time: 0.0079 memory: 8327 grad_norm: 7.4004 loss: 3.5987 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2128 loss_aux: 1.3859 2023/02/17 16:10:32 - mmengine - INFO - Epoch(train) [56][ 140/1345] lr: 1.0000e-02 eta: 6:48:26 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.7627 loss: 3.6097 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1915 loss_aux: 1.4182 2023/02/17 16:10:36 - mmengine - INFO - Epoch(train) [56][ 160/1345] lr: 1.0000e-02 eta: 6:48:22 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.6864 loss: 3.3211 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 1.9720 loss_aux: 1.3491 2023/02/17 16:10:39 - mmengine - INFO - Epoch(train) [56][ 180/1345] lr: 1.0000e-02 eta: 6:48:18 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.8078 loss: 3.0984 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8019 loss_aux: 1.2966 2023/02/17 16:10:43 - mmengine - INFO - Epoch(train) [56][ 200/1345] lr: 1.0000e-02 eta: 6:48:14 time: 0.1900 data_time: 0.0060 memory: 8327 grad_norm: 7.7034 loss: 3.3802 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0363 loss_aux: 1.3440 2023/02/17 16:10:47 - mmengine - INFO - Epoch(train) [56][ 220/1345] lr: 1.0000e-02 eta: 6:48:11 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.5378 loss: 3.1867 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9190 loss_aux: 1.2676 2023/02/17 16:10:51 - mmengine - INFO - Epoch(train) [56][ 240/1345] lr: 1.0000e-02 eta: 6:48:07 time: 0.1895 data_time: 0.0059 memory: 8327 grad_norm: 7.6274 loss: 3.0928 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8671 loss_aux: 1.2257 2023/02/17 16:10:55 - mmengine - INFO - Epoch(train) [56][ 260/1345] lr: 1.0000e-02 eta: 6:48:03 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.4270 loss: 3.4654 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0863 loss_aux: 1.3791 2023/02/17 16:10:58 - mmengine - INFO - Epoch(train) [56][ 280/1345] lr: 1.0000e-02 eta: 6:47:59 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.9360 loss: 3.5968 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2263 loss_aux: 1.3705 2023/02/17 16:11:02 - mmengine - INFO - Epoch(train) [56][ 300/1345] lr: 1.0000e-02 eta: 6:47:55 time: 0.1896 data_time: 0.0057 memory: 8327 grad_norm: 7.6416 loss: 3.1664 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9433 loss_aux: 1.2231 2023/02/17 16:11:06 - mmengine - INFO - Epoch(train) [56][ 320/1345] lr: 1.0000e-02 eta: 6:47:51 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.9046 loss: 3.3582 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0531 loss_aux: 1.3051 2023/02/17 16:11:10 - mmengine - INFO - Epoch(train) [56][ 340/1345] lr: 1.0000e-02 eta: 6:47:47 time: 0.1918 data_time: 0.0079 memory: 8327 grad_norm: 7.8624 loss: 3.6971 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2713 loss_aux: 1.4259 2023/02/17 16:11:14 - mmengine - INFO - Epoch(train) [56][ 360/1345] lr: 1.0000e-02 eta: 6:47:43 time: 0.1895 data_time: 0.0058 memory: 8327 grad_norm: 7.6280 loss: 3.4048 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0843 loss_aux: 1.3205 2023/02/17 16:11:17 - mmengine - INFO - Epoch(train) [56][ 380/1345] lr: 1.0000e-02 eta: 6:47:39 time: 0.1898 data_time: 0.0057 memory: 8327 grad_norm: 7.6026 loss: 3.1146 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8088 loss_aux: 1.3058 2023/02/17 16:11:21 - mmengine - INFO - Epoch(train) [56][ 400/1345] lr: 1.0000e-02 eta: 6:47:35 time: 0.1915 data_time: 0.0075 memory: 8327 grad_norm: 7.6721 loss: 3.1120 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8256 loss_aux: 1.2864 2023/02/17 16:11:25 - mmengine - INFO - Epoch(train) [56][ 420/1345] lr: 1.0000e-02 eta: 6:47:31 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.8803 loss: 3.6960 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2901 loss_aux: 1.4059 2023/02/17 16:11:29 - mmengine - INFO - Epoch(train) [56][ 440/1345] lr: 1.0000e-02 eta: 6:47:28 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.7083 loss: 3.1186 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8772 loss_aux: 1.2415 2023/02/17 16:11:33 - mmengine - INFO - Epoch(train) [56][ 460/1345] lr: 1.0000e-02 eta: 6:47:24 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.5071 loss: 3.5903 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1418 loss_aux: 1.4485 2023/02/17 16:11:36 - mmengine - INFO - Epoch(train) [56][ 480/1345] lr: 1.0000e-02 eta: 6:47:20 time: 0.1896 data_time: 0.0060 memory: 8327 grad_norm: 7.7988 loss: 3.3516 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0564 loss_aux: 1.2952 2023/02/17 16:11:40 - mmengine - INFO - Epoch(train) [56][ 500/1345] lr: 1.0000e-02 eta: 6:47:16 time: 0.1900 data_time: 0.0060 memory: 8327 grad_norm: 7.8568 loss: 3.4665 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1542 loss_aux: 1.3123 2023/02/17 16:11:44 - mmengine - INFO - Epoch(train) [56][ 520/1345] lr: 1.0000e-02 eta: 6:47:12 time: 0.1898 data_time: 0.0060 memory: 8327 grad_norm: 7.7607 loss: 3.2966 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0181 loss_aux: 1.2785 2023/02/17 16:11:48 - mmengine - INFO - Epoch(train) [56][ 540/1345] lr: 1.0000e-02 eta: 6:47:08 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.8475 loss: 3.8372 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3821 loss_aux: 1.4552 2023/02/17 16:11:52 - mmengine - INFO - Epoch(train) [56][ 560/1345] lr: 1.0000e-02 eta: 6:47:04 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.8179 loss: 3.3866 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0663 loss_aux: 1.3203 2023/02/17 16:11:55 - mmengine - INFO - Epoch(train) [56][ 580/1345] lr: 1.0000e-02 eta: 6:47:00 time: 0.1895 data_time: 0.0060 memory: 8327 grad_norm: 7.7489 loss: 3.4605 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1079 loss_aux: 1.3526 2023/02/17 16:11:59 - mmengine - INFO - Epoch(train) [56][ 600/1345] lr: 1.0000e-02 eta: 6:46:56 time: 0.1903 data_time: 0.0058 memory: 8327 grad_norm: 7.8761 loss: 3.2632 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 1.9500 loss_aux: 1.3132 2023/02/17 16:12:03 - mmengine - INFO - Epoch(train) [56][ 620/1345] lr: 1.0000e-02 eta: 6:46:52 time: 0.1899 data_time: 0.0062 memory: 8327 grad_norm: 7.7424 loss: 3.2470 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9691 loss_aux: 1.2780 2023/02/17 16:12:07 - mmengine - INFO - Epoch(train) [56][ 640/1345] lr: 1.0000e-02 eta: 6:46:48 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.9254 loss: 3.6657 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2760 loss_aux: 1.3897 2023/02/17 16:12:11 - mmengine - INFO - Epoch(train) [56][ 660/1345] lr: 1.0000e-02 eta: 6:46:45 time: 0.1910 data_time: 0.0066 memory: 8327 grad_norm: 7.8164 loss: 2.8690 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6816 loss_aux: 1.1875 2023/02/17 16:12:15 - mmengine - INFO - Epoch(train) [56][ 680/1345] lr: 1.0000e-02 eta: 6:46:41 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.7021 loss: 3.4890 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1595 loss_aux: 1.3295 2023/02/17 16:12:18 - mmengine - INFO - Epoch(train) [56][ 700/1345] lr: 1.0000e-02 eta: 6:46:37 time: 0.1897 data_time: 0.0061 memory: 8327 grad_norm: 7.5929 loss: 3.4408 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1122 loss_aux: 1.3286 2023/02/17 16:12:22 - mmengine - INFO - Epoch(train) [56][ 720/1345] lr: 1.0000e-02 eta: 6:46:33 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.7561 loss: 3.4857 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0953 loss_aux: 1.3904 2023/02/17 16:12:26 - mmengine - INFO - Epoch(train) [56][ 740/1345] lr: 1.0000e-02 eta: 6:46:29 time: 0.1900 data_time: 0.0059 memory: 8327 grad_norm: 7.7015 loss: 3.5239 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1681 loss_aux: 1.3557 2023/02/17 16:12:30 - mmengine - INFO - Epoch(train) [56][ 760/1345] lr: 1.0000e-02 eta: 6:46:25 time: 0.1899 data_time: 0.0058 memory: 8327 grad_norm: 7.5672 loss: 3.3867 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0032 loss_aux: 1.3834 2023/02/17 16:12:34 - mmengine - INFO - Epoch(train) [56][ 780/1345] lr: 1.0000e-02 eta: 6:46:21 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.8435 loss: 3.7975 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3818 loss_aux: 1.4157 2023/02/17 16:12:37 - mmengine - INFO - Epoch(train) [56][ 800/1345] lr: 1.0000e-02 eta: 6:46:17 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.8997 loss: 3.6530 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2226 loss_aux: 1.4303 2023/02/17 16:12:41 - mmengine - INFO - Epoch(train) [56][ 820/1345] lr: 1.0000e-02 eta: 6:46:13 time: 0.1905 data_time: 0.0060 memory: 8327 grad_norm: 7.7164 loss: 3.3946 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.0250 loss_aux: 1.3696 2023/02/17 16:12:45 - mmengine - INFO - Epoch(train) [56][ 840/1345] lr: 1.0000e-02 eta: 6:46:09 time: 0.1900 data_time: 0.0060 memory: 8327 grad_norm: 7.8721 loss: 3.3987 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0331 loss_aux: 1.3656 2023/02/17 16:12:49 - mmengine - INFO - Epoch(train) [56][ 860/1345] lr: 1.0000e-02 eta: 6:46:05 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.8545 loss: 3.6424 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2461 loss_aux: 1.3962 2023/02/17 16:12:53 - mmengine - INFO - Epoch(train) [56][ 880/1345] lr: 1.0000e-02 eta: 6:46:01 time: 0.1899 data_time: 0.0063 memory: 8327 grad_norm: 7.5971 loss: 3.8404 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3692 loss_aux: 1.4712 2023/02/17 16:12:56 - mmengine - INFO - Epoch(train) [56][ 900/1345] lr: 1.0000e-02 eta: 6:45:58 time: 0.1899 data_time: 0.0058 memory: 8327 grad_norm: 7.6701 loss: 3.6339 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1848 loss_aux: 1.4491 2023/02/17 16:13:00 - mmengine - INFO - Epoch(train) [56][ 920/1345] lr: 1.0000e-02 eta: 6:45:54 time: 0.1903 data_time: 0.0060 memory: 8327 grad_norm: 7.7350 loss: 3.0726 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8499 loss_aux: 1.2227 2023/02/17 16:13:04 - mmengine - INFO - Epoch(train) [56][ 940/1345] lr: 1.0000e-02 eta: 6:45:50 time: 0.1899 data_time: 0.0058 memory: 8327 grad_norm: 7.7235 loss: 3.6949 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2658 loss_aux: 1.4291 2023/02/17 16:13:08 - mmengine - INFO - Epoch(train) [56][ 960/1345] lr: 1.0000e-02 eta: 6:45:46 time: 0.1904 data_time: 0.0059 memory: 8327 grad_norm: 7.6839 loss: 3.3239 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0100 loss_aux: 1.3140 2023/02/17 16:13:12 - mmengine - INFO - Epoch(train) [56][ 980/1345] lr: 1.0000e-02 eta: 6:45:42 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.9116 loss: 3.4785 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.0876 loss_aux: 1.3909 2023/02/17 16:13:15 - mmengine - INFO - Epoch(train) [56][1000/1345] lr: 1.0000e-02 eta: 6:45:38 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.7220 loss: 3.3512 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0348 loss_aux: 1.3164 2023/02/17 16:13:19 - mmengine - INFO - Epoch(train) [56][1020/1345] lr: 1.0000e-02 eta: 6:45:34 time: 0.1900 data_time: 0.0060 memory: 8327 grad_norm: 7.5599 loss: 3.2496 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9257 loss_aux: 1.3240 2023/02/17 16:13:20 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 16:13:23 - mmengine - INFO - Epoch(train) [56][1040/1345] lr: 1.0000e-02 eta: 6:45:30 time: 0.1898 data_time: 0.0061 memory: 8327 grad_norm: 7.7405 loss: 3.5696 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1216 loss_aux: 1.4480 2023/02/17 16:13:27 - mmengine - INFO - Epoch(train) [56][1060/1345] lr: 1.0000e-02 eta: 6:45:26 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.8296 loss: 3.6635 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2921 loss_aux: 1.3714 2023/02/17 16:13:31 - mmengine - INFO - Epoch(train) [56][1080/1345] lr: 1.0000e-02 eta: 6:45:22 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.3670 loss: 3.5082 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1296 loss_aux: 1.3786 2023/02/17 16:13:35 - mmengine - INFO - Epoch(train) [56][1100/1345] lr: 1.0000e-02 eta: 6:45:19 time: 0.1999 data_time: 0.0159 memory: 8327 grad_norm: 7.7657 loss: 3.1450 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8494 loss_aux: 1.2957 2023/02/17 16:13:38 - mmengine - INFO - Epoch(train) [56][1120/1345] lr: 1.0000e-02 eta: 6:45:15 time: 0.1897 data_time: 0.0060 memory: 8327 grad_norm: 7.6525 loss: 3.3421 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.0350 loss_aux: 1.3071 2023/02/17 16:13:42 - mmengine - INFO - Epoch(train) [56][1140/1345] lr: 1.0000e-02 eta: 6:45:11 time: 0.1904 data_time: 0.0065 memory: 8327 grad_norm: 7.7960 loss: 3.7966 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3059 loss_aux: 1.4907 2023/02/17 16:13:46 - mmengine - INFO - Epoch(train) [56][1160/1345] lr: 1.0000e-02 eta: 6:45:07 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.7355 loss: 3.2940 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0520 loss_aux: 1.2419 2023/02/17 16:13:50 - mmengine - INFO - Epoch(train) [56][1180/1345] lr: 1.0000e-02 eta: 6:45:03 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.6432 loss: 3.2980 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9846 loss_aux: 1.3134 2023/02/17 16:13:54 - mmengine - INFO - Epoch(train) [56][1200/1345] lr: 1.0000e-02 eta: 6:44:59 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.6721 loss: 3.5370 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1559 loss_aux: 1.3811 2023/02/17 16:13:57 - mmengine - INFO - Epoch(train) [56][1220/1345] lr: 1.0000e-02 eta: 6:44:55 time: 0.1911 data_time: 0.0059 memory: 8327 grad_norm: 7.9437 loss: 3.6730 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2775 loss_aux: 1.3955 2023/02/17 16:14:01 - mmengine - INFO - Epoch(train) [56][1240/1345] lr: 1.0000e-02 eta: 6:44:51 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.5792 loss: 3.5150 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1496 loss_aux: 1.3654 2023/02/17 16:14:05 - mmengine - INFO - Epoch(train) [56][1260/1345] lr: 1.0000e-02 eta: 6:44:48 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.8265 loss: 3.4740 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0940 loss_aux: 1.3800 2023/02/17 16:14:09 - mmengine - INFO - Epoch(train) [56][1280/1345] lr: 1.0000e-02 eta: 6:44:44 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.6696 loss: 3.0203 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8009 loss_aux: 1.2193 2023/02/17 16:14:13 - mmengine - INFO - Epoch(train) [56][1300/1345] lr: 1.0000e-02 eta: 6:44:40 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.7894 loss: 3.6477 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2360 loss_aux: 1.4118 2023/02/17 16:14:17 - mmengine - INFO - Epoch(train) [56][1320/1345] lr: 1.0000e-02 eta: 6:44:36 time: 0.1921 data_time: 0.0060 memory: 8327 grad_norm: 7.9163 loss: 3.5097 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1561 loss_aux: 1.3536 2023/02/17 16:14:20 - mmengine - INFO - Epoch(train) [56][1340/1345] lr: 1.0000e-02 eta: 6:44:32 time: 0.1913 data_time: 0.0062 memory: 8327 grad_norm: 7.8930 loss: 3.5882 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1764 loss_aux: 1.4118 2023/02/17 16:14:21 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 16:14:21 - mmengine - INFO - Epoch(train) [56][1345/1345] lr: 1.0000e-02 eta: 6:44:31 time: 0.1848 data_time: 0.0064 memory: 8327 grad_norm: 7.7338 loss: 3.8093 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.3179 loss_aux: 1.4915 2023/02/17 16:14:21 - mmengine - INFO - Saving checkpoint at 56 epochs 2023/02/17 16:14:28 - mmengine - INFO - Epoch(train) [57][ 20/1345] lr: 1.0000e-02 eta: 6:44:28 time: 0.2069 data_time: 0.0166 memory: 8327 grad_norm: 7.6459 loss: 3.2957 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 1.9686 loss_aux: 1.3271 2023/02/17 16:14:32 - mmengine - INFO - Epoch(train) [57][ 40/1345] lr: 1.0000e-02 eta: 6:44:24 time: 0.1931 data_time: 0.0056 memory: 8327 grad_norm: 7.5831 loss: 3.3601 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9968 loss_aux: 1.3633 2023/02/17 16:14:36 - mmengine - INFO - Epoch(train) [57][ 60/1345] lr: 1.0000e-02 eta: 6:44:20 time: 0.1901 data_time: 0.0060 memory: 8327 grad_norm: 7.6493 loss: 3.3215 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0111 loss_aux: 1.3103 2023/02/17 16:14:39 - mmengine - INFO - Epoch(train) [57][ 80/1345] lr: 1.0000e-02 eta: 6:44:16 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.4519 loss: 3.2212 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9403 loss_aux: 1.2809 2023/02/17 16:14:43 - mmengine - INFO - Epoch(train) [57][ 100/1345] lr: 1.0000e-02 eta: 6:44:12 time: 0.1905 data_time: 0.0061 memory: 8327 grad_norm: 7.8158 loss: 3.5620 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1608 loss_aux: 1.4011 2023/02/17 16:14:47 - mmengine - INFO - Epoch(train) [57][ 120/1345] lr: 1.0000e-02 eta: 6:44:08 time: 0.1898 data_time: 0.0060 memory: 8327 grad_norm: 7.6308 loss: 3.6157 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2213 loss_aux: 1.3944 2023/02/17 16:14:51 - mmengine - INFO - Epoch(train) [57][ 140/1345] lr: 1.0000e-02 eta: 6:44:04 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.6629 loss: 3.6713 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2520 loss_aux: 1.4193 2023/02/17 16:14:55 - mmengine - INFO - Epoch(train) [57][ 160/1345] lr: 1.0000e-02 eta: 6:44:00 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.6005 loss: 2.9888 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7813 loss_aux: 1.2076 2023/02/17 16:14:58 - mmengine - INFO - Epoch(train) [57][ 180/1345] lr: 1.0000e-02 eta: 6:43:56 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.8078 loss: 3.1806 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8997 loss_aux: 1.2809 2023/02/17 16:15:02 - mmengine - INFO - Epoch(train) [57][ 200/1345] lr: 1.0000e-02 eta: 6:43:52 time: 0.1904 data_time: 0.0059 memory: 8327 grad_norm: 7.5511 loss: 3.4873 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1268 loss_aux: 1.3605 2023/02/17 16:15:06 - mmengine - INFO - Epoch(train) [57][ 220/1345] lr: 1.0000e-02 eta: 6:43:49 time: 0.1898 data_time: 0.0061 memory: 8327 grad_norm: 7.7215 loss: 3.4157 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0795 loss_aux: 1.3362 2023/02/17 16:15:10 - mmengine - INFO - Epoch(train) [57][ 240/1345] lr: 1.0000e-02 eta: 6:43:45 time: 0.1900 data_time: 0.0058 memory: 8327 grad_norm: 7.8071 loss: 3.4440 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0599 loss_aux: 1.3840 2023/02/17 16:15:14 - mmengine - INFO - Epoch(train) [57][ 260/1345] lr: 1.0000e-02 eta: 6:43:41 time: 0.1904 data_time: 0.0058 memory: 8327 grad_norm: 7.7981 loss: 3.5040 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1404 loss_aux: 1.3636 2023/02/17 16:15:18 - mmengine - INFO - Epoch(train) [57][ 280/1345] lr: 1.0000e-02 eta: 6:43:37 time: 0.1899 data_time: 0.0058 memory: 8327 grad_norm: 7.6303 loss: 3.1639 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8661 loss_aux: 1.2978 2023/02/17 16:15:21 - mmengine - INFO - Epoch(train) [57][ 300/1345] lr: 1.0000e-02 eta: 6:43:33 time: 0.1903 data_time: 0.0059 memory: 8327 grad_norm: 7.8687 loss: 3.8670 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4253 loss_aux: 1.4416 2023/02/17 16:15:25 - mmengine - INFO - Epoch(train) [57][ 320/1345] lr: 1.0000e-02 eta: 6:43:29 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.5627 loss: 3.6038 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1866 loss_aux: 1.4172 2023/02/17 16:15:29 - mmengine - INFO - Epoch(train) [57][ 340/1345] lr: 1.0000e-02 eta: 6:43:25 time: 0.1906 data_time: 0.0066 memory: 8327 grad_norm: 7.7242 loss: 3.2780 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9489 loss_aux: 1.3291 2023/02/17 16:15:33 - mmengine - INFO - Epoch(train) [57][ 360/1345] lr: 1.0000e-02 eta: 6:43:21 time: 0.1896 data_time: 0.0059 memory: 8327 grad_norm: 7.9771 loss: 3.2119 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9240 loss_aux: 1.2879 2023/02/17 16:15:37 - mmengine - INFO - Epoch(train) [57][ 380/1345] lr: 1.0000e-02 eta: 6:43:17 time: 0.1901 data_time: 0.0065 memory: 8327 grad_norm: 7.7648 loss: 3.2993 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0046 loss_aux: 1.2946 2023/02/17 16:15:40 - mmengine - INFO - Epoch(train) [57][ 400/1345] lr: 1.0000e-02 eta: 6:43:13 time: 0.1903 data_time: 0.0058 memory: 8327 grad_norm: 7.9378 loss: 3.7950 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3678 loss_aux: 1.4272 2023/02/17 16:15:44 - mmengine - INFO - Epoch(train) [57][ 420/1345] lr: 1.0000e-02 eta: 6:43:10 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.8784 loss: 3.3826 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0465 loss_aux: 1.3361 2023/02/17 16:15:48 - mmengine - INFO - Epoch(train) [57][ 440/1345] lr: 1.0000e-02 eta: 6:43:06 time: 0.1899 data_time: 0.0059 memory: 8327 grad_norm: 7.7598 loss: 3.4366 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1143 loss_aux: 1.3224 2023/02/17 16:15:52 - mmengine - INFO - Epoch(train) [57][ 460/1345] lr: 1.0000e-02 eta: 6:43:02 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.6415 loss: 3.2506 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9538 loss_aux: 1.2968 2023/02/17 16:15:56 - mmengine - INFO - Epoch(train) [57][ 480/1345] lr: 1.0000e-02 eta: 6:42:58 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.7006 loss: 3.4682 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1103 loss_aux: 1.3579 2023/02/17 16:15:59 - mmengine - INFO - Epoch(train) [57][ 500/1345] lr: 1.0000e-02 eta: 6:42:54 time: 0.1897 data_time: 0.0059 memory: 8327 grad_norm: 7.6379 loss: 3.0918 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8579 loss_aux: 1.2339 2023/02/17 16:16:03 - mmengine - INFO - Epoch(train) [57][ 520/1345] lr: 1.0000e-02 eta: 6:42:50 time: 0.1898 data_time: 0.0059 memory: 8327 grad_norm: 7.6307 loss: 3.4330 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0731 loss_aux: 1.3599 2023/02/17 16:16:07 - mmengine - INFO - Epoch(train) [57][ 540/1345] lr: 1.0000e-02 eta: 6:42:46 time: 0.1900 data_time: 0.0059 memory: 8327 grad_norm: 7.6836 loss: 3.4306 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0690 loss_aux: 1.3616 2023/02/17 16:16:11 - mmengine - INFO - Epoch(train) [57][ 560/1345] lr: 1.0000e-02 eta: 6:42:42 time: 0.1902 data_time: 0.0061 memory: 8327 grad_norm: 7.9503 loss: 3.1880 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8730 loss_aux: 1.3150 2023/02/17 16:16:15 - mmengine - INFO - Epoch(train) [57][ 580/1345] lr: 1.0000e-02 eta: 6:42:38 time: 0.1898 data_time: 0.0060 memory: 8327 grad_norm: 7.9781 loss: 3.7883 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3220 loss_aux: 1.4663 2023/02/17 16:16:18 - mmengine - INFO - Epoch(train) [57][ 600/1345] lr: 1.0000e-02 eta: 6:42:34 time: 0.1900 data_time: 0.0057 memory: 8327 grad_norm: 7.6334 loss: 3.3676 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0648 loss_aux: 1.3028 2023/02/17 16:16:22 - mmengine - INFO - Epoch(train) [57][ 620/1345] lr: 1.0000e-02 eta: 6:42:30 time: 0.1912 data_time: 0.0075 memory: 8327 grad_norm: 7.7920 loss: 3.4708 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1120 loss_aux: 1.3588 2023/02/17 16:16:26 - mmengine - INFO - Epoch(train) [57][ 640/1345] lr: 1.0000e-02 eta: 6:42:27 time: 0.1896 data_time: 0.0058 memory: 8327 grad_norm: 7.7115 loss: 3.0657 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8056 loss_aux: 1.2601 2023/02/17 16:16:30 - mmengine - INFO - Epoch(train) [57][ 660/1345] lr: 1.0000e-02 eta: 6:42:23 time: 0.1921 data_time: 0.0084 memory: 8327 grad_norm: 7.6932 loss: 3.2125 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9174 loss_aux: 1.2951 2023/02/17 16:16:34 - mmengine - INFO - Exp name: tpn-tsm_imagenet-pretrained-r50_8xb8-1x1x8-150e_sthv1-rgb_20230217_120710 2023/02/17 16:16:34 - mmengine - INFO - Epoch(train) [57][ 680/1345] lr: 1.0000e-02 eta: 6:42:19 time: 0.1898 data_time: 0.0058 memory: 8327 grad_norm: 7.7706 loss: 3.2624 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9333 loss_aux: 1.3292 2023/02/17 16:16:37 - mmengine - INFO - Epoch(train) [57][ 700/1345] lr: 1.0000e-02 eta: 6:42:15 time: 0.1897 data_time: 0.0058 memory: 8327 grad_norm: 7.7168 loss: 3.0509 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8254 loss_aux: 1.2255 2023/02/17 16:16:41 - mmengine - INFO - Epoch(train) [57][ 720/1345] lr: 1.0000e-02 eta: 6:42:11 time: 0.1899 data_time: 0.0060 memory: 8327 grad_norm: 7.8329 loss: 3.6128 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1964 loss_aux: 1.4164 2023/02/17 16:16:45 - mmengine - INFO - Epoch(train) [57][ 740/1