2022/09/15 15:25:06 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.7.13 (default, Mar 29 2022, 02:18:16) [GCC 7.5.0] CUDA available: True numpy_random_seed: 448179328 GPU 0,1: 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: 4.5.4 MMEngine: 0.1.0 Runtime environment: cudnn_benchmark: True mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: None Distributed launcher: slurm Distributed training: True GPU number: 2 ------------------------------------------------------------ 2022/09/15 15:25:07 - mmengine - INFO - Config: mj_rec_data_root = 'data/rec/Syn90k/' mj_rec_train = dict( type='OCRDataset', data_root='data/rec/Syn90k/', data_prefix=dict(img_path='mnt/ramdisk/max/90kDICT32px'), ann_file='train_labels.json', test_mode=False, pipeline=None) mj_sub_rec_train = dict( type='OCRDataset', data_root='data/rec/Syn90k/', data_prefix=dict(img_path='mnt/ramdisk/max/90kDICT32px'), ann_file='subset_train_labels.json', test_mode=False, pipeline=None) st_data_root = 'data/rec/SynthText/' st_rec_train = dict( type='OCRDataset', data_root='data/rec/SynthText/', data_prefix=dict(img_path='synthtext/SynthText_patch_horizontal'), ann_file='train_labels.json', test_mode=False, pipeline=None) st_an_rec_train = dict( type='OCRDataset', data_root='data/rec/SynthText/', data_prefix=dict(img_path='synthtext/SynthText_patch_horizontal'), ann_file='alphanumeric_train_labels.json', test_mode=False, pipeline=None) st_sub_rec_train = dict( type='OCRDataset', data_root='data/rec/SynthText/', data_prefix=dict(img_path='synthtext/SynthText_patch_horizontal'), ann_file='subset_train_labels.json', test_mode=False, pipeline=None) cute80_rec_data_root = 'data/rec/ct80/' cute80_rec_test = dict( type='OCRDataset', data_root='data/rec/ct80/', ann_file='test_labels.json', test_mode=True, pipeline=None) iiit5k_rec_data_root = 'data/rec/IIIT5K/' iiit5k_rec_train = dict( type='OCRDataset', data_root='data/rec/IIIT5K/', ann_file='train_labels.json', test_mode=False, pipeline=None) iiit5k_rec_test = dict( type='OCRDataset', data_root='data/rec/IIIT5K/', ann_file='test_labels.json', test_mode=True, pipeline=None) svt_rec_data_root = 'data/rec/svt/' svt_rec_test = dict( type='OCRDataset', data_root='data/rec/svt/', ann_file='test_labels.json', test_mode=True, pipeline=None) svtp_rec_data_root = 'data/rec/svtp/' svtp_rec_test = dict( type='OCRDataset', data_root='data/rec/svtp/', ann_file='test_labels.json', test_mode=True, pipeline=None) ic13_rec_data_root = 'data/rec/icdar_2013/' ic13_rec_train = dict( type='OCRDataset', data_root='data/rec/icdar_2013/', ann_file='train_labels.json', test_mode=False, pipeline=None) ic13_rec_test = dict( type='OCRDataset', data_root='data/rec/icdar_2013/', ann_file='test_labels.json', test_mode=True, pipeline=None) ic15_rec_data_root = 'data/rec/icdar_2015/' ic15_rec_train = dict( type='OCRDataset', data_root='data/rec/icdar_2015/', ann_file='train_labels.json', test_mode=False, pipeline=None) ic15_rec_test = dict( type='OCRDataset', data_root='data/rec/icdar_2015/', ann_file='test_labels.json', test_mode=True, pipeline=None) default_scope = 'mmocr' env_cfg = dict( cudnn_benchmark=True, mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), dist_cfg=dict(backend='nccl')) randomness = dict(seed=None) default_hooks = dict( timer=dict(type='IterTimerHook'), logger=dict(type='LoggerHook', interval=100), param_scheduler=dict(type='ParamSchedulerHook'), checkpoint=dict( type='CheckpointHook', interval=1, out_dir='sproject:s3://1.0.0rc0_recog_retest'), sampler_seed=dict(type='DistSamplerSeedHook'), sync_buffer=dict(type='SyncBuffersHook'), visualization=dict( type='VisualizationHook', interval=1, enable=False, show=False, draw_gt=False, draw_pred=False)) log_level = 'INFO' log_processor = dict(type='LogProcessor', window_size=10, by_epoch=True) load_from = None resume = False val_evaluator = dict( type='MultiDatasetsEvaluator', metrics=[dict(type='WordMetric', mode=['ignore_case_symbol'])], dataset_prefixes=['CUTE80', 'IIIT5K', 'SVT', 'SVTP', 'IC13', 'IC15']) test_evaluator = dict( type='MultiDatasetsEvaluator', metrics=[dict(type='WordMetric', mode=['ignore_case_symbol'])], dataset_prefixes=['CUTE80', 'IIIT5K', 'SVT', 'SVTP', 'IC13', 'IC15']) vis_backends = [dict(type='LocalVisBackend')] visualizer = dict( type='TextRecogLocalVisualizer', name='visualizer', vis_backends=[dict(type='LocalVisBackend')]) optim_wrapper = dict( type='OptimWrapper', optimizer=dict(type='Adam', lr=0.0001)) train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=20, val_interval=1) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') param_scheduler = [ dict( type='LinearLR', end=2, start_factor=0.001, convert_to_iter_based=True), dict(type='MultiStepLR', milestones=[16, 18], end=20) ] dictionary = dict( type='Dictionary', dict_file= 'configs/textrecog/abinet/../../../dicts/lower_english_digits.txt', with_start=True, with_end=True, same_start_end=True, with_padding=False, with_unknown=False) model = dict( type='ABINet', backbone=dict(type='ResNetABI'), encoder=dict( type='ABIEncoder', n_layers=3, n_head=8, d_model=512, d_inner=2048, dropout=0.1, max_len=256), decoder=dict( type='ABIFuser', vision_decoder=dict( type='ABIVisionDecoder', in_channels=512, num_channels=64, attn_height=8, attn_width=32, attn_mode='nearest', init_cfg=dict(type='Xavier', layer='Conv2d')), module_loss=dict(type='ABIModuleLoss', letter_case='lower'), postprocessor=dict(type='AttentionPostprocessor'), dictionary=dict( type='Dictionary', dict_file= 'configs/textrecog/abinet/../../../dicts/lower_english_digits.txt', with_start=True, with_end=True, same_start_end=True, with_padding=False, with_unknown=False), max_seq_len=26), data_preprocessor=dict( type='TextRecogDataPreprocessor', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375])) file_client_args = dict(backend='disk') train_pipeline = [ dict( type='LoadImageFromFile', file_client_args=dict(backend='disk'), ignore_empty=True, min_size=2), dict(type='LoadOCRAnnotations', with_text=True), dict(type='Resize', scale=(128, 32)), dict( type='RandomApply', prob=0.5, transforms=[ dict( type='RandomChoice', transforms=[ dict(type='RandomRotate', max_angle=15), dict( type='TorchVisionWrapper', op='RandomAffine', degrees=15, translate=(0.3, 0.3), scale=(0.5, 2.0), shear=(-45, 45)), dict( type='TorchVisionWrapper', op='RandomPerspective', distortion_scale=0.5, p=1) ]) ]), dict( type='RandomApply', prob=0.25, transforms=[ dict(type='PyramidRescale'), dict( type='mmdet.Albu', transforms=[ dict(type='GaussNoise', var_limit=(20, 20), p=0.5), dict(type='MotionBlur', blur_limit=6, p=0.5) ]) ]), dict( type='RandomApply', prob=0.25, transforms=[ dict( type='TorchVisionWrapper', op='ColorJitter', brightness=0.5, saturation=0.5, contrast=0.5, hue=0.1) ]), dict( type='PackTextRecogInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) ] test_pipeline = [ dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')), dict(type='Resize', scale=(128, 32)), dict(type='LoadOCRAnnotations', with_text=True), dict( type='PackTextRecogInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) ] train_list = [ dict( type='OCRDataset', data_root='data/rec/Syn90k/', data_prefix=dict(img_path='mnt/ramdisk/max/90kDICT32px'), ann_file='train_labels.json', test_mode=False, pipeline=None), dict( type='OCRDataset', data_root='data/rec/SynthText/', data_prefix=dict(img_path='synthtext/SynthText_patch_horizontal'), ann_file='alphanumeric_train_labels.json', test_mode=False, pipeline=None) ] test_list = [ dict( type='OCRDataset', data_root='data/rec/ct80/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/IIIT5K/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/svt/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/svtp/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/icdar_2013/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/icdar_2015/', ann_file='test_labels.json', test_mode=True, pipeline=None) ] train_dataset = dict( type='ConcatDataset', datasets=[ dict( type='OCRDataset', data_root='data/rec/Syn90k/', data_prefix=dict(img_path='mnt/ramdisk/max/90kDICT32px'), ann_file='train_labels.json', test_mode=False, pipeline=None), dict( type='OCRDataset', data_root='data/rec/SynthText/', data_prefix=dict(img_path='synthtext/SynthText_patch_horizontal'), ann_file='alphanumeric_train_labels.json', test_mode=False, pipeline=None) ], pipeline=[ dict( type='LoadImageFromFile', file_client_args=dict(backend='disk'), ignore_empty=True, min_size=2), dict(type='LoadOCRAnnotations', with_text=True), dict(type='Resize', scale=(128, 32)), dict( type='RandomApply', prob=0.5, transforms=[ dict( type='RandomChoice', transforms=[ dict(type='RandomRotate', max_angle=15), dict( type='TorchVisionWrapper', op='RandomAffine', degrees=15, translate=(0.3, 0.3), scale=(0.5, 2.0), shear=(-45, 45)), dict( type='TorchVisionWrapper', op='RandomPerspective', distortion_scale=0.5, p=1) ]) ]), dict( type='RandomApply', prob=0.25, transforms=[ dict(type='PyramidRescale'), dict( type='mmdet.Albu', transforms=[ dict(type='GaussNoise', var_limit=(20, 20), p=0.5), dict(type='MotionBlur', blur_limit=6, p=0.5) ]) ]), dict( type='RandomApply', prob=0.25, transforms=[ dict( type='TorchVisionWrapper', op='ColorJitter', brightness=0.5, saturation=0.5, contrast=0.5, hue=0.1) ]), dict( type='PackTextRecogInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) ]) test_dataset = dict( type='ConcatDataset', datasets=[ dict( type='OCRDataset', data_root='data/rec/ct80/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/IIIT5K/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/svt/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/svtp/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/icdar_2013/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/icdar_2015/', ann_file='test_labels.json', test_mode=True, pipeline=None) ], pipeline=[ dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')), dict(type='Resize', scale=(128, 32)), dict(type='LoadOCRAnnotations', with_text=True), dict( type='PackTextRecogInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) ]) train_dataloader = dict( batch_size=768, num_workers=32, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='ConcatDataset', datasets=[ dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/Syn90k', data_prefix=dict(img_path='mnt/ramdisk/max/90kDICT32px'), ann_file='train_labels.json', test_mode=False, pipeline=None), dict( type='OCRDataset', data_root= 'openmmlab:s3://openmmlab/datasets/ocr/recog/SynthText', data_prefix=dict( img_path='synthtext/SynthText_patch_horizontal'), ann_file='alphanumeric_train_labels.json', test_mode=False, pipeline=None) ], pipeline=[ dict( type='LoadImageFromFile', file_client_args=dict(backend='petrel'), ignore_empty=True, min_size=2), dict(type='LoadOCRAnnotations', with_text=True), dict(type='Resize', scale=(128, 32)), dict( type='RandomApply', prob=0.5, transforms=[ dict( type='RandomChoice', transforms=[ dict(type='RandomRotate', max_angle=15), dict( type='TorchVisionWrapper', op='RandomAffine', degrees=15, translate=(0.3, 0.3), scale=(0.5, 2.0), shear=(-45, 45)), dict( type='TorchVisionWrapper', op='RandomPerspective', distortion_scale=0.5, p=1) ]) ]), dict( type='RandomApply', prob=0.25, transforms=[ dict(type='PyramidRescale'), dict( type='mmdet.Albu', transforms=[ dict(type='GaussNoise', var_limit=(20, 20), p=0.5), dict(type='MotionBlur', blur_limit=6, p=0.5) ]) ]), dict( type='RandomApply', prob=0.25, transforms=[ dict( type='TorchVisionWrapper', op='ColorJitter', brightness=0.5, saturation=0.5, contrast=0.5, hue=0.1) ]), dict( type='PackTextRecogInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) ])) test_dataloader = dict( batch_size=1, num_workers=4, persistent_workers=True, drop_last=False, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='ConcatDataset', datasets=[ dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/ct80', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/IIIT5K', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/svt', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/svtp', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root= 'openmmlab:s3://openmmlab/datasets/ocr/recog/icdar_2013', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root= 'openmmlab:s3://openmmlab/datasets/ocr/recog/icdar_2015', ann_file='test_labels.json', test_mode=True, pipeline=None) ], pipeline=[ dict( type='LoadImageFromFile', file_client_args=dict(backend='petrel')), dict(type='Resize', scale=(128, 32)), dict(type='LoadOCRAnnotations', with_text=True), dict( type='PackTextRecogInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) ])) val_dataloader = dict( batch_size=1, num_workers=4, persistent_workers=True, drop_last=False, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='ConcatDataset', datasets=[ dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/ct80', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/IIIT5K', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/svt', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/svtp', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root= 'openmmlab:s3://openmmlab/datasets/ocr/recog/icdar_2013', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root= 'openmmlab:s3://openmmlab/datasets/ocr/recog/icdar_2015', ann_file='test_labels.json', test_mode=True, pipeline=None) ], pipeline=[ dict( type='LoadImageFromFile', file_client_args=dict(backend='petrel')), dict(type='Resize', scale=(128, 32)), dict(type='LoadOCRAnnotations', with_text=True), dict( type='PackTextRecogInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) ])) launcher = 'slurm' work_dir = './work_dirs/abinet-vision_20e_st-an_mj' Name of parameter - Initialization information backbone.conv1.weight - torch.Size([32, 3, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.conv1.bias - torch.Size([32]): XavierInit: gain=1, distribution=normal, bias=0 backbone.bn1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of ABINet backbone.bn1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of ABINet backbone.layer1.0.conv1.weight - torch.Size([32, 32, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer1.0.conv2.weight - torch.Size([32, 32, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer1.0.bn1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of ABINet backbone.layer1.0.bn1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of ABINet backbone.layer1.0.bn2.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of ABINet backbone.layer1.0.bn2.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of ABINet backbone.layer1.0.downsample.0.weight - torch.Size([32, 32, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer1.0.downsample.1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of ABINet backbone.layer1.0.downsample.1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of ABINet backbone.layer1.1.conv1.weight - torch.Size([32, 32, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer1.1.conv2.weight - torch.Size([32, 32, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer1.1.bn1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of ABINet backbone.layer1.1.bn1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of ABINet backbone.layer1.1.bn2.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of ABINet backbone.layer1.1.bn2.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of ABINet backbone.layer1.2.conv1.weight - torch.Size([32, 32, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer1.2.conv2.weight - torch.Size([32, 32, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer1.2.bn1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of ABINet backbone.layer1.2.bn1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of ABINet backbone.layer1.2.bn2.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of ABINet backbone.layer1.2.bn2.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.0.conv1.weight - torch.Size([64, 32, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer2.0.conv2.weight - torch.Size([64, 64, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer2.0.bn1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.0.bn1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.0.bn2.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.0.bn2.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.0.downsample.0.weight - torch.Size([64, 32, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer2.0.downsample.1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.0.downsample.1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.1.conv1.weight - torch.Size([64, 64, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer2.1.conv2.weight - torch.Size([64, 64, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer2.1.bn1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.1.bn1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.1.bn2.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.1.bn2.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.2.conv1.weight - torch.Size([64, 64, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer2.2.conv2.weight - torch.Size([64, 64, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer2.2.bn1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.2.bn1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.2.bn2.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.2.bn2.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.3.conv1.weight - torch.Size([64, 64, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer2.3.conv2.weight - torch.Size([64, 64, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer2.3.bn1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.3.bn1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.3.bn2.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer2.3.bn2.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.0.conv1.weight - torch.Size([128, 64, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer3.0.conv2.weight - torch.Size([128, 128, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer3.0.bn1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.0.bn1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.0.bn2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.0.bn2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.0.downsample.0.weight - torch.Size([128, 64, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer3.0.downsample.1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.0.downsample.1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.1.conv1.weight - torch.Size([128, 128, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer3.1.conv2.weight - torch.Size([128, 128, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer3.1.bn1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.1.bn1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.1.bn2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.1.bn2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.2.conv1.weight - torch.Size([128, 128, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer3.2.conv2.weight - torch.Size([128, 128, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer3.2.bn1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.2.bn1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.2.bn2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.2.bn2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.3.conv1.weight - torch.Size([128, 128, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer3.3.conv2.weight - torch.Size([128, 128, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer3.3.bn1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.3.bn1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.3.bn2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.3.bn2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.4.conv1.weight - torch.Size([128, 128, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer3.4.conv2.weight - torch.Size([128, 128, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer3.4.bn1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.4.bn1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.4.bn2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.4.bn2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.5.conv1.weight - torch.Size([128, 128, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer3.5.conv2.weight - torch.Size([128, 128, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer3.5.bn1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.5.bn1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.5.bn2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer3.5.bn2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.0.conv1.weight - torch.Size([256, 128, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer4.0.conv2.weight - torch.Size([256, 256, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer4.0.bn1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.0.bn1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.0.bn2.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.0.bn2.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.0.downsample.0.weight - torch.Size([256, 128, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer4.0.downsample.1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.0.downsample.1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.1.conv1.weight - torch.Size([256, 256, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer4.1.conv2.weight - torch.Size([256, 256, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer4.1.bn1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.1.bn1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.1.bn2.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.1.bn2.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.2.conv1.weight - torch.Size([256, 256, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer4.2.conv2.weight - torch.Size([256, 256, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer4.2.bn1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.2.bn1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.2.bn2.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.2.bn2.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.3.conv1.weight - torch.Size([256, 256, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer4.3.conv2.weight - torch.Size([256, 256, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer4.3.bn1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.3.bn1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.3.bn2.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.3.bn2.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.4.conv1.weight - torch.Size([256, 256, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer4.4.conv2.weight - torch.Size([256, 256, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer4.4.bn1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.4.bn1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.4.bn2.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.4.bn2.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.5.conv1.weight - torch.Size([256, 256, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer4.5.conv2.weight - torch.Size([256, 256, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer4.5.bn1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.5.bn1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.5.bn2.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer4.5.bn2.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of ABINet backbone.layer5.0.conv1.weight - torch.Size([512, 256, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer5.0.conv2.weight - torch.Size([512, 512, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer5.0.bn1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet backbone.layer5.0.bn1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet backbone.layer5.0.bn2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet backbone.layer5.0.bn2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet backbone.layer5.0.downsample.0.weight - torch.Size([512, 256, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer5.0.downsample.1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet backbone.layer5.0.downsample.1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet backbone.layer5.1.conv1.weight - torch.Size([512, 512, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer5.1.conv2.weight - torch.Size([512, 512, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer5.1.bn1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet backbone.layer5.1.bn1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet backbone.layer5.1.bn2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet backbone.layer5.1.bn2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet backbone.layer5.2.conv1.weight - torch.Size([512, 512, 1, 1]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer5.2.conv2.weight - torch.Size([512, 512, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 backbone.layer5.2.bn1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet backbone.layer5.2.bn1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet backbone.layer5.2.bn2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet backbone.layer5.2.bn2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.0.attentions.0.attn.in_proj_weight - torch.Size([1536, 512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.0.attentions.0.attn.in_proj_bias - torch.Size([1536]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.0.attentions.0.attn.out_proj.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.0.attentions.0.attn.out_proj.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.0.ffns.0.layers.0.0.weight - torch.Size([2048, 512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.0.ffns.0.layers.0.0.bias - torch.Size([2048]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.0.ffns.0.layers.1.weight - torch.Size([512, 2048]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.0.ffns.0.layers.1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.0.norms.0.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.0.norms.0.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.0.norms.1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.0.norms.1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.1.attentions.0.attn.in_proj_weight - torch.Size([1536, 512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.1.attentions.0.attn.in_proj_bias - torch.Size([1536]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.1.attentions.0.attn.out_proj.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.1.attentions.0.attn.out_proj.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.1.ffns.0.layers.0.0.weight - torch.Size([2048, 512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.1.ffns.0.layers.0.0.bias - torch.Size([2048]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.1.ffns.0.layers.1.weight - torch.Size([512, 2048]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.1.ffns.0.layers.1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.1.norms.0.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.1.norms.0.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.1.norms.1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.1.norms.1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.2.attentions.0.attn.in_proj_weight - torch.Size([1536, 512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.2.attentions.0.attn.in_proj_bias - torch.Size([1536]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.2.attentions.0.attn.out_proj.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.2.attentions.0.attn.out_proj.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.2.ffns.0.layers.0.0.weight - torch.Size([2048, 512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.2.ffns.0.layers.0.0.bias - torch.Size([2048]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.2.ffns.0.layers.1.weight - torch.Size([512, 2048]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.2.ffns.0.layers.1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.2.norms.0.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.2.norms.0.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.2.norms.1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet encoder.transformer.2.norms.1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.k_encoder.0.conv.weight - torch.Size([64, 512, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 decoder.vision_decoder.k_encoder.0.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.k_encoder.0.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.k_encoder.1.conv.weight - torch.Size([64, 64, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 decoder.vision_decoder.k_encoder.1.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.k_encoder.1.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.k_encoder.2.conv.weight - torch.Size([64, 64, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 decoder.vision_decoder.k_encoder.2.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.k_encoder.2.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.k_encoder.3.conv.weight - torch.Size([64, 64, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 decoder.vision_decoder.k_encoder.3.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.k_encoder.3.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.k_decoder.0.1.conv.weight - torch.Size([64, 64, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 decoder.vision_decoder.k_decoder.0.1.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.k_decoder.0.1.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.k_decoder.1.1.conv.weight - torch.Size([64, 64, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 decoder.vision_decoder.k_decoder.1.1.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.k_decoder.1.1.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.k_decoder.2.1.conv.weight - torch.Size([64, 64, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 decoder.vision_decoder.k_decoder.2.1.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.k_decoder.2.1.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.k_decoder.3.1.conv.weight - torch.Size([512, 64, 3, 3]): XavierInit: gain=1, distribution=normal, bias=0 decoder.vision_decoder.k_decoder.3.1.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.k_decoder.3.1.bn.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.project.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.project.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.cls.weight - torch.Size([37, 512]): The value is the same before and after calling `init_weights` of ABINet decoder.vision_decoder.cls.bias - torch.Size([37]): The value is the same before and after calling `init_weights` of ABINet 2022/09/15 15:27:44 - mmengine - INFO - Checkpoints will be saved to sproject:s3://1.0.0rc0_recog_retest/abinet-vision_20e_st-an_mj by PetrelBackend. 2022/09/15 15:38:16 - mmengine - INFO - Epoch(train) [1][100/10520] lr: 5.7008e-07 eta: 15 days, 9:14:37 time: 1.5516 data_time: 0.3807 memory: 68044 loss_visual: 3.0137 loss: 3.0137 2022/09/15 15:40:16 - mmengine - INFO - Epoch(train) [1][200/10520] lr: 1.0449e-06 eta: 9 days, 3:25:16 time: 1.7235 data_time: 0.5278 memory: 56770 loss_visual: 1.6321 loss: 1.6321 2022/09/15 15:42:14 - mmengine - INFO - Epoch(train) [1][300/10520] lr: 1.5197e-06 eta: 7 days, 1:19:37 time: 1.2871 data_time: 0.1612 memory: 56770 loss_visual: 1.3378 loss: 1.3378 2022/09/15 15:44:15 - mmengine - INFO - Epoch(train) [1][400/10520] lr: 1.9946e-06 eta: 6 days, 0:27:40 time: 1.0609 data_time: 0.1822 memory: 56770 loss_visual: 1.1348 loss: 1.1348 2022/09/15 15:46:15 - mmengine - INFO - Epoch(train) [1][500/10520] lr: 2.4694e-06 eta: 5 days, 9:31:16 time: 1.0896 data_time: 0.2683 memory: 56770 loss_visual: 1.0179 loss: 1.0179 2022/09/15 15:48:13 - mmengine - INFO - Epoch(train) [1][600/10520] lr: 2.9442e-06 eta: 4 days, 23:25:38 time: 0.9224 data_time: 0.0747 memory: 56770 loss_visual: 0.9720 loss: 0.9720 2022/09/15 15:50:15 - mmengine - INFO - Epoch(train) [1][700/10520] lr: 3.4191e-06 eta: 4 days, 16:25:27 time: 0.8631 data_time: 0.0060 memory: 56770 loss_visual: 0.9386 loss: 0.9386 2022/09/15 15:52:17 - mmengine - INFO - Epoch(train) [1][800/10520] lr: 3.8939e-06 eta: 4 days, 11:12:26 time: 0.9508 data_time: 0.0069 memory: 56770 loss_visual: 0.9251 loss: 0.9251 2022/09/15 15:54:24 - mmengine - INFO - Epoch(train) [1][900/10520] lr: 4.3687e-06 eta: 4 days, 7:28:07 time: 1.5755 data_time: 0.3307 memory: 56770 loss_visual: 0.9046 loss: 0.9046 2022/09/15 15:56:26 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 15:56:26 - mmengine - INFO - Epoch(train) [1][1000/10520] lr: 4.8436e-06 eta: 4 days, 4:10:57 time: 1.7128 data_time: 0.5043 memory: 56770 loss_visual: 0.8879 loss: 0.8879 2022/09/15 15:58:27 - mmengine - INFO - Epoch(train) [1][1100/10520] lr: 5.3184e-06 eta: 4 days, 1:25:00 time: 1.2940 data_time: 0.1932 memory: 56770 loss_visual: 0.8699 loss: 0.8699 2022/09/15 16:00:32 - mmengine - INFO - Epoch(train) [1][1200/10520] lr: 5.7932e-06 eta: 3 days, 23:18:33 time: 1.0567 data_time: 0.2431 memory: 56770 loss_visual: 0.8769 loss: 0.8769 2022/09/15 16:02:35 - mmengine - INFO - Epoch(train) [1][1300/10520] lr: 6.2681e-06 eta: 3 days, 21:26:46 time: 1.1020 data_time: 0.2842 memory: 56770 loss_visual: 0.8589 loss: 0.8589 2022/09/15 16:04:37 - mmengine - INFO - Epoch(train) [1][1400/10520] lr: 6.7429e-06 eta: 3 days, 19:45:18 time: 0.9243 data_time: 0.0758 memory: 56770 loss_visual: 0.8615 loss: 0.8615 2022/09/15 16:06:38 - mmengine - INFO - Epoch(train) [1][1500/10520] lr: 7.2177e-06 eta: 3 days, 18:18:17 time: 0.8728 data_time: 0.0060 memory: 56770 loss_visual: 0.8548 loss: 0.8548 2022/09/15 16:08:38 - mmengine - INFO - Epoch(train) [1][1600/10520] lr: 7.6926e-06 eta: 3 days, 16:57:45 time: 0.9370 data_time: 0.0063 memory: 56770 loss_visual: 0.8533 loss: 0.8533 2022/09/15 16:10:43 - mmengine - INFO - Epoch(train) [1][1700/10520] lr: 8.1674e-06 eta: 3 days, 15:57:45 time: 1.5883 data_time: 0.3706 memory: 56770 loss_visual: 0.8444 loss: 0.8444 2022/09/15 16:12:44 - mmengine - INFO - Epoch(train) [1][1800/10520] lr: 8.6422e-06 eta: 3 days, 14:55:46 time: 1.6853 data_time: 0.5421 memory: 56770 loss_visual: 0.8368 loss: 0.8368 2022/09/15 16:14:44 - mmengine - INFO - Epoch(train) [1][1900/10520] lr: 9.1171e-06 eta: 3 days, 13:58:24 time: 1.3304 data_time: 0.1600 memory: 56770 loss_visual: 0.8451 loss: 0.8451 2022/09/15 16:16:48 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 16:16:48 - mmengine - INFO - Epoch(train) [1][2000/10520] lr: 9.5919e-06 eta: 3 days, 13:12:59 time: 1.0450 data_time: 0.2305 memory: 56770 loss_visual: 0.8410 loss: 0.8410 2022/09/15 16:18:50 - mmengine - INFO - Epoch(train) [1][2100/10520] lr: 1.0067e-05 eta: 3 days, 12:27:56 time: 1.0984 data_time: 0.2491 memory: 56770 loss_visual: 0.8410 loss: 0.8410 2022/09/15 16:20:50 - mmengine - INFO - Epoch(train) [1][2200/10520] lr: 1.0542e-05 eta: 3 days, 11:45:37 time: 0.9806 data_time: 0.0721 memory: 56770 loss_visual: 0.8343 loss: 0.8343 2022/09/15 16:22:53 - mmengine - INFO - Epoch(train) [1][2300/10520] lr: 1.1016e-05 eta: 3 days, 11:09:29 time: 0.8919 data_time: 0.0067 memory: 56770 loss_visual: 0.8409 loss: 0.8409 2022/09/15 16:24:56 - mmengine - INFO - Epoch(train) [1][2400/10520] lr: 1.1491e-05 eta: 3 days, 10:36:45 time: 0.9474 data_time: 0.0065 memory: 56770 loss_visual: 0.8247 loss: 0.8247 2022/09/15 16:27:05 - mmengine - INFO - Epoch(train) [1][2500/10520] lr: 1.1966e-05 eta: 3 days, 10:15:51 time: 1.6985 data_time: 0.3528 memory: 56770 loss_visual: 0.8267 loss: 0.8267 2022/09/15 16:29:07 - mmengine - INFO - Epoch(train) [1][2600/10520] lr: 1.2441e-05 eta: 3 days, 9:45:48 time: 1.7132 data_time: 0.4941 memory: 56770 loss_visual: 0.8265 loss: 0.8265 2022/09/15 16:31:09 - mmengine - INFO - Epoch(train) [1][2700/10520] lr: 1.2916e-05 eta: 3 days, 9:18:46 time: 1.3010 data_time: 0.2103 memory: 56770 loss_visual: 0.8237 loss: 0.8237 2022/09/15 16:33:11 - mmengine - INFO - Epoch(train) [1][2800/10520] lr: 1.3391e-05 eta: 3 days, 8:53:06 time: 1.0896 data_time: 0.2288 memory: 56770 loss_visual: 0.8215 loss: 0.8215 2022/09/15 16:35:15 - mmengine - INFO - Epoch(train) [1][2900/10520] lr: 1.3865e-05 eta: 3 days, 8:30:25 time: 1.1021 data_time: 0.2303 memory: 56770 loss_visual: 0.8148 loss: 0.8148 2022/09/15 16:37:17 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 16:37:17 - mmengine - INFO - Epoch(train) [1][3000/10520] lr: 1.4340e-05 eta: 3 days, 8:07:59 time: 0.9079 data_time: 0.0722 memory: 56770 loss_visual: 0.8059 loss: 0.8059 2022/09/15 16:39:16 - mmengine - INFO - Epoch(train) [1][3100/10520] lr: 1.4815e-05 eta: 3 days, 7:43:34 time: 0.8622 data_time: 0.0065 memory: 56770 loss_visual: 0.8138 loss: 0.8138 2022/09/15 16:41:16 - mmengine - INFO - Epoch(train) [1][3200/10520] lr: 1.5290e-05 eta: 3 days, 7:21:17 time: 0.9308 data_time: 0.0060 memory: 56770 loss_visual: 0.8087 loss: 0.8087 2022/09/15 16:43:22 - mmengine - INFO - Epoch(train) [1][3300/10520] lr: 1.5765e-05 eta: 3 days, 7:06:33 time: 1.6373 data_time: 0.3735 memory: 56770 loss_visual: 0.8123 loss: 0.8123 2022/09/15 16:45:23 - mmengine - INFO - Epoch(train) [1][3400/10520] lr: 1.6240e-05 eta: 3 days, 6:47:59 time: 1.6865 data_time: 0.4653 memory: 56770 loss_visual: 0.7981 loss: 0.7981 2022/09/15 16:47:24 - mmengine - INFO - Epoch(train) [1][3500/10520] lr: 1.6714e-05 eta: 3 days, 6:29:18 time: 1.3728 data_time: 0.2218 memory: 56770 loss_visual: 0.7982 loss: 0.7982 2022/09/15 16:49:25 - mmengine - INFO - Epoch(train) [1][3600/10520] lr: 1.7189e-05 eta: 3 days, 6:12:14 time: 1.0812 data_time: 0.2401 memory: 56770 loss_visual: 0.8011 loss: 0.8011 2022/09/15 16:51:25 - mmengine - INFO - Epoch(train) [1][3700/10520] lr: 1.7664e-05 eta: 3 days, 5:55:14 time: 1.1234 data_time: 0.2144 memory: 56770 loss_visual: 0.7898 loss: 0.7898 2022/09/15 16:53:25 - mmengine - INFO - Epoch(train) [1][3800/10520] lr: 1.8139e-05 eta: 3 days, 5:38:12 time: 0.9225 data_time: 0.0973 memory: 56770 loss_visual: 0.7998 loss: 0.7998 2022/09/15 16:55:24 - mmengine - INFO - Epoch(train) [1][3900/10520] lr: 1.8614e-05 eta: 3 days, 5:21:50 time: 0.8386 data_time: 0.0062 memory: 56770 loss_visual: 0.7854 loss: 0.7854 2022/09/15 16:57:25 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 16:57:25 - mmengine - INFO - Epoch(train) [1][4000/10520] lr: 1.9089e-05 eta: 3 days, 5:08:02 time: 0.9209 data_time: 0.0061 memory: 56770 loss_visual: 0.7919 loss: 0.7919 2022/09/15 16:59:31 - mmengine - INFO - Epoch(train) [1][4100/10520] lr: 1.9563e-05 eta: 3 days, 4:57:54 time: 1.5842 data_time: 0.3216 memory: 56770 loss_visual: 0.7789 loss: 0.7789 2022/09/15 17:01:32 - mmengine - INFO - Epoch(train) [1][4200/10520] lr: 2.0038e-05 eta: 3 days, 4:45:33 time: 1.7184 data_time: 0.4895 memory: 56770 loss_visual: 0.7826 loss: 0.7826 2022/09/15 17:03:33 - mmengine - INFO - Epoch(train) [1][4300/10520] lr: 2.0513e-05 eta: 3 days, 4:32:41 time: 1.3700 data_time: 0.2130 memory: 56770 loss_visual: 0.7700 loss: 0.7700 2022/09/15 17:05:34 - mmengine - INFO - Epoch(train) [1][4400/10520] lr: 2.0988e-05 eta: 3 days, 4:20:27 time: 1.0548 data_time: 0.1791 memory: 56770 loss_visual: 0.7655 loss: 0.7655 2022/09/15 17:07:34 - mmengine - INFO - Epoch(train) [1][4500/10520] lr: 2.1463e-05 eta: 3 days, 4:08:04 time: 1.1594 data_time: 0.2330 memory: 56770 loss_visual: 0.7765 loss: 0.7765 2022/09/15 17:09:34 - mmengine - INFO - Epoch(train) [1][4600/10520] lr: 2.1938e-05 eta: 3 days, 3:55:39 time: 0.9540 data_time: 0.0788 memory: 56770 loss_visual: 0.7689 loss: 0.7689 2022/09/15 17:11:33 - mmengine - INFO - Epoch(train) [1][4700/10520] lr: 2.2412e-05 eta: 3 days, 3:43:29 time: 0.8278 data_time: 0.0062 memory: 56770 loss_visual: 0.7511 loss: 0.7511 2022/09/15 17:13:33 - mmengine - INFO - Epoch(train) [1][4800/10520] lr: 2.2887e-05 eta: 3 days, 3:32:17 time: 0.9246 data_time: 0.0062 memory: 56770 loss_visual: 0.7514 loss: 0.7514 2022/09/15 17:15:38 - mmengine - INFO - Epoch(train) [1][4900/10520] lr: 2.3362e-05 eta: 3 days, 3:25:29 time: 1.5823 data_time: 0.3283 memory: 56770 loss_visual: 0.7452 loss: 0.7452 2022/09/15 17:17:40 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 17:17:40 - mmengine - INFO - Epoch(train) [1][5000/10520] lr: 2.3837e-05 eta: 3 days, 3:15:46 time: 1.7717 data_time: 0.5178 memory: 56770 loss_visual: 0.7260 loss: 0.7260 2022/09/15 17:19:40 - mmengine - INFO - Epoch(train) [1][5100/10520] lr: 2.4312e-05 eta: 3 days, 3:05:39 time: 1.3373 data_time: 0.1861 memory: 56770 loss_visual: 0.7148 loss: 0.7148 2022/09/15 17:21:41 - mmengine - INFO - Epoch(train) [1][5200/10520] lr: 2.4787e-05 eta: 3 days, 2:56:52 time: 1.0530 data_time: 0.2109 memory: 56770 loss_visual: 0.6999 loss: 0.6999 2022/09/15 17:23:42 - mmengine - INFO - Epoch(train) [1][5300/10520] lr: 2.5261e-05 eta: 3 days, 2:47:42 time: 1.0800 data_time: 0.2463 memory: 56770 loss_visual: 0.6837 loss: 0.6837 2022/09/15 17:25:42 - mmengine - INFO - Epoch(train) [1][5400/10520] lr: 2.5736e-05 eta: 3 days, 2:38:22 time: 0.9609 data_time: 0.0764 memory: 56770 loss_visual: 0.6531 loss: 0.6531 2022/09/15 17:27:42 - mmengine - INFO - Epoch(train) [1][5500/10520] lr: 2.6211e-05 eta: 3 days, 2:29:22 time: 0.8869 data_time: 0.0060 memory: 56770 loss_visual: 0.6195 loss: 0.6195 2022/09/15 17:29:43 - mmengine - INFO - Epoch(train) [1][5600/10520] lr: 2.6686e-05 eta: 3 days, 2:21:09 time: 0.9535 data_time: 0.0061 memory: 56770 loss_visual: 0.5981 loss: 0.5981 2022/09/15 17:31:49 - mmengine - INFO - Epoch(train) [1][5700/10520] lr: 2.7161e-05 eta: 3 days, 2:16:00 time: 1.6127 data_time: 0.3116 memory: 56770 loss_visual: 0.5756 loss: 0.5756 2022/09/15 17:33:50 - mmengine - INFO - Epoch(train) [1][5800/10520] lr: 2.7636e-05 eta: 3 days, 2:08:30 time: 1.7237 data_time: 0.4782 memory: 56770 loss_visual: 0.5479 loss: 0.5479 2022/09/15 17:35:51 - mmengine - INFO - Epoch(train) [1][5900/10520] lr: 2.8110e-05 eta: 3 days, 2:00:28 time: 1.3467 data_time: 0.2226 memory: 56770 loss_visual: 0.5225 loss: 0.5225 2022/09/15 17:37:52 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 17:37:52 - mmengine - INFO - Epoch(train) [1][6000/10520] lr: 2.8585e-05 eta: 3 days, 1:53:14 time: 1.0674 data_time: 0.2487 memory: 56770 loss_visual: 0.4908 loss: 0.4908 2022/09/15 17:39:52 - mmengine - INFO - Epoch(train) [1][6100/10520] lr: 2.9060e-05 eta: 3 days, 1:45:35 time: 1.0927 data_time: 0.2154 memory: 56770 loss_visual: 0.4683 loss: 0.4683 2022/09/15 17:41:51 - mmengine - INFO - Epoch(train) [1][6200/10520] lr: 2.9535e-05 eta: 3 days, 1:37:22 time: 0.9827 data_time: 0.1117 memory: 56770 loss_visual: 0.4490 loss: 0.4490 2022/09/15 17:43:52 - mmengine - INFO - Epoch(train) [1][6300/10520] lr: 3.0010e-05 eta: 3 days, 1:30:09 time: 0.8704 data_time: 0.0062 memory: 56770 loss_visual: 0.4325 loss: 0.4325 2022/09/15 17:45:52 - mmengine - INFO - Epoch(train) [1][6400/10520] lr: 3.0485e-05 eta: 3 days, 1:23:11 time: 0.9393 data_time: 0.0061 memory: 56770 loss_visual: 0.4158 loss: 0.4158 2022/09/15 17:48:00 - mmengine - INFO - Epoch(train) [1][6500/10520] lr: 3.0959e-05 eta: 3 days, 1:19:57 time: 1.6017 data_time: 0.3244 memory: 56770 loss_visual: 0.4012 loss: 0.4012 2022/09/15 17:50:02 - mmengine - INFO - Epoch(train) [1][6600/10520] lr: 3.1434e-05 eta: 3 days, 1:13:57 time: 1.7463 data_time: 0.4569 memory: 56770 loss_visual: 0.3988 loss: 0.3988 2022/09/15 17:52:04 - mmengine - INFO - Epoch(train) [1][6700/10520] lr: 3.1909e-05 eta: 3 days, 1:08:08 time: 1.3689 data_time: 0.1755 memory: 56770 loss_visual: 0.3803 loss: 0.3803 2022/09/15 17:54:05 - mmengine - INFO - Epoch(train) [1][6800/10520] lr: 3.2384e-05 eta: 3 days, 1:01:51 time: 1.0621 data_time: 0.1943 memory: 56770 loss_visual: 0.3701 loss: 0.3701 2022/09/15 17:56:06 - mmengine - INFO - Epoch(train) [1][6900/10520] lr: 3.2859e-05 eta: 3 days, 0:55:40 time: 1.0545 data_time: 0.2289 memory: 56770 loss_visual: 0.3676 loss: 0.3676 2022/09/15 17:58:07 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 17:58:07 - mmengine - INFO - Epoch(train) [1][7000/10520] lr: 3.3334e-05 eta: 3 days, 0:49:36 time: 0.9698 data_time: 0.1077 memory: 56770 loss_visual: 0.3517 loss: 0.3517 2022/09/15 18:00:12 - mmengine - INFO - Epoch(train) [1][7100/10520] lr: 3.3808e-05 eta: 3 days, 0:45:41 time: 1.3783 data_time: 0.0246 memory: 56770 loss_visual: 0.3427 loss: 0.3427 2022/09/15 18:02:13 - mmengine - INFO - Epoch(train) [1][7200/10520] lr: 3.4283e-05 eta: 3 days, 0:40:03 time: 0.9649 data_time: 0.0060 memory: 56770 loss_visual: 0.3388 loss: 0.3388 2022/09/15 18:04:20 - mmengine - INFO - Epoch(train) [1][7300/10520] lr: 3.4758e-05 eta: 3 days, 0:37:05 time: 1.5719 data_time: 0.3270 memory: 56770 loss_visual: 0.3337 loss: 0.3337 2022/09/15 18:06:22 - mmengine - INFO - Epoch(train) [1][7400/10520] lr: 3.5233e-05 eta: 3 days, 0:31:38 time: 1.8028 data_time: 0.5261 memory: 56770 loss_visual: 0.3224 loss: 0.3224 2022/09/15 18:08:23 - mmengine - INFO - Epoch(train) [1][7500/10520] lr: 3.5708e-05 eta: 3 days, 0:25:53 time: 1.3344 data_time: 0.2091 memory: 56770 loss_visual: 0.3196 loss: 0.3196 2022/09/15 18:10:24 - mmengine - INFO - Epoch(train) [1][7600/10520] lr: 3.6183e-05 eta: 3 days, 0:20:39 time: 1.0489 data_time: 0.2044 memory: 56770 loss_visual: 0.3168 loss: 0.3168 2022/09/15 18:12:26 - mmengine - INFO - Epoch(train) [1][7700/10520] lr: 3.6657e-05 eta: 3 days, 0:15:40 time: 1.0515 data_time: 0.2278 memory: 56770 loss_visual: 0.3047 loss: 0.3047 2022/09/15 18:14:27 - mmengine - INFO - Epoch(train) [1][7800/10520] lr: 3.7132e-05 eta: 3 days, 0:10:07 time: 0.9510 data_time: 0.1003 memory: 56770 loss_visual: 0.3023 loss: 0.3023 2022/09/15 18:16:27 - mmengine - INFO - Epoch(train) [1][7900/10520] lr: 3.7607e-05 eta: 3 days, 0:04:49 time: 0.8971 data_time: 0.0063 memory: 56770 loss_visual: 0.2978 loss: 0.2978 2022/09/15 18:18:28 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 18:18:28 - mmengine - INFO - Epoch(train) [1][8000/10520] lr: 3.8082e-05 eta: 2 days, 23:59:40 time: 0.9854 data_time: 0.0073 memory: 56770 loss_visual: 0.2903 loss: 0.2903 2022/09/15 18:20:35 - mmengine - INFO - Epoch(train) [1][8100/10520] lr: 3.8557e-05 eta: 2 days, 23:56:59 time: 1.5960 data_time: 0.3182 memory: 56770 loss_visual: 0.2852 loss: 0.2852 2022/09/15 18:22:36 - mmengine - INFO - Epoch(train) [1][8200/10520] lr: 3.9032e-05 eta: 2 days, 23:51:50 time: 1.6913 data_time: 0.4786 memory: 56770 loss_visual: 0.2791 loss: 0.2791 2022/09/15 18:24:36 - mmengine - INFO - Epoch(train) [1][8300/10520] lr: 3.9506e-05 eta: 2 days, 23:46:21 time: 1.3078 data_time: 0.1787 memory: 56770 loss_visual: 0.2770 loss: 0.2770 2022/09/15 18:26:38 - mmengine - INFO - Epoch(train) [1][8400/10520] lr: 3.9981e-05 eta: 2 days, 23:42:07 time: 1.0495 data_time: 0.2059 memory: 56770 loss_visual: 0.2794 loss: 0.2794 2022/09/15 18:28:39 - mmengine - INFO - Epoch(train) [1][8500/10520] lr: 4.0456e-05 eta: 2 days, 23:37:18 time: 1.0854 data_time: 0.2630 memory: 56770 loss_visual: 0.2739 loss: 0.2739 2022/09/15 18:30:38 - mmengine - INFO - Epoch(train) [1][8600/10520] lr: 4.0931e-05 eta: 2 days, 23:31:48 time: 0.9683 data_time: 0.1052 memory: 56770 loss_visual: 0.2648 loss: 0.2648 2022/09/15 18:32:39 - mmengine - INFO - Epoch(train) [1][8700/10520] lr: 4.1406e-05 eta: 2 days, 23:26:55 time: 0.8881 data_time: 0.0066 memory: 56770 loss_visual: 0.2687 loss: 0.2687 2022/09/15 18:34:40 - mmengine - INFO - Epoch(train) [1][8800/10520] lr: 4.1881e-05 eta: 2 days, 23:22:18 time: 0.9773 data_time: 0.0062 memory: 56770 loss_visual: 0.2685 loss: 0.2685 2022/09/15 18:36:46 - mmengine - INFO - Epoch(train) [1][8900/10520] lr: 4.2355e-05 eta: 2 days, 23:19:35 time: 1.5640 data_time: 0.2794 memory: 56770 loss_visual: 0.2592 loss: 0.2592 2022/09/15 18:38:49 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 18:38:49 - mmengine - INFO - Epoch(train) [1][9000/10520] lr: 4.2830e-05 eta: 2 days, 23:15:47 time: 1.7989 data_time: 0.4880 memory: 56770 loss_visual: 0.2532 loss: 0.2532 2022/09/15 18:40:49 - mmengine - INFO - Epoch(train) [1][9100/10520] lr: 4.3305e-05 eta: 2 days, 23:11:10 time: 1.3795 data_time: 0.1793 memory: 56770 loss_visual: 0.2555 loss: 0.2555 2022/09/15 18:42:50 - mmengine - INFO - Epoch(train) [1][9200/10520] lr: 4.3780e-05 eta: 2 days, 23:06:43 time: 1.0336 data_time: 0.1829 memory: 56770 loss_visual: 0.2421 loss: 0.2421 2022/09/15 18:44:51 - mmengine - INFO - Epoch(train) [1][9300/10520] lr: 4.4255e-05 eta: 2 days, 23:02:08 time: 1.0884 data_time: 0.2150 memory: 56770 loss_visual: 0.2445 loss: 0.2445 2022/09/15 18:46:52 - mmengine - INFO - Epoch(train) [1][9400/10520] lr: 4.4730e-05 eta: 2 days, 22:57:50 time: 0.9661 data_time: 0.1090 memory: 56770 loss_visual: 0.2402 loss: 0.2402 2022/09/15 18:48:53 - mmengine - INFO - Epoch(train) [1][9500/10520] lr: 4.5204e-05 eta: 2 days, 22:53:44 time: 0.8350 data_time: 0.0065 memory: 56770 loss_visual: 0.2357 loss: 0.2357 2022/09/15 18:50:55 - mmengine - INFO - Epoch(train) [1][9600/10520] lr: 4.5679e-05 eta: 2 days, 22:49:45 time: 0.9664 data_time: 0.0069 memory: 56770 loss_visual: 0.2345 loss: 0.2345 2022/09/15 18:53:02 - mmengine - INFO - Epoch(train) [1][9700/10520] lr: 4.6154e-05 eta: 2 days, 22:47:51 time: 1.6090 data_time: 0.3374 memory: 56770 loss_visual: 0.2394 loss: 0.2394 2022/09/15 18:55:05 - mmengine - INFO - Epoch(train) [1][9800/10520] lr: 4.6629e-05 eta: 2 days, 22:44:14 time: 1.6962 data_time: 0.4845 memory: 56770 loss_visual: 0.2431 loss: 0.2431 2022/09/15 18:57:05 - mmengine - INFO - Epoch(train) [1][9900/10520] lr: 4.7104e-05 eta: 2 days, 22:39:50 time: 1.3139 data_time: 0.1798 memory: 56770 loss_visual: 0.2275 loss: 0.2275 2022/09/15 18:59:07 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 18:59:07 - mmengine - INFO - Epoch(train) [1][10000/10520] lr: 4.7578e-05 eta: 2 days, 22:36:09 time: 1.1047 data_time: 0.2189 memory: 56770 loss_visual: 0.2353 loss: 0.2353 2022/09/15 19:01:09 - mmengine - INFO - Epoch(train) [1][10100/10520] lr: 4.8053e-05 eta: 2 days, 22:32:12 time: 1.0823 data_time: 0.2395 memory: 56770 loss_visual: 0.2232 loss: 0.2232 2022/09/15 19:03:07 - mmengine - INFO - Epoch(train) [1][10200/10520] lr: 4.8528e-05 eta: 2 days, 22:27:29 time: 0.9187 data_time: 0.0989 memory: 56770 loss_visual: 0.2221 loss: 0.2221 2022/09/15 19:05:08 - mmengine - INFO - Epoch(train) [1][10300/10520] lr: 4.9003e-05 eta: 2 days, 22:23:23 time: 0.8834 data_time: 0.0063 memory: 56770 loss_visual: 0.2230 loss: 0.2230 2022/09/15 19:07:08 - mmengine - INFO - Epoch(train) [1][10400/10520] lr: 4.9478e-05 eta: 2 days, 22:19:04 time: 0.9506 data_time: 0.0064 memory: 56770 loss_visual: 0.2238 loss: 0.2238 2022/09/15 19:09:08 - mmengine - INFO - Epoch(train) [1][10500/10520] lr: 4.9953e-05 eta: 2 days, 22:15:01 time: 1.2688 data_time: 0.2022 memory: 56770 loss_visual: 0.2177 loss: 0.2177 2022/09/15 19:09:38 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 19:09:38 - mmengine - INFO - Saving checkpoint at 1 epochs 2022/09/15 19:11:41 - mmengine - INFO - Epoch(val) [1][100/3836] eta: 0:14:06 time: 0.2266 data_time: 0.0007 memory: 62396 2022/09/15 19:11:47 - mmengine - INFO - Epoch(val) [1][200/3836] eta: 0:00:42 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/15 19:11:49 - mmengine - INFO - Epoch(val) [1][300/3836] eta: 0:00:41 time: 0.0117 data_time: 0.0004 memory: 480 2022/09/15 19:11:50 - mmengine - INFO - Epoch(val) [1][400/3836] eta: 0:00:40 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/15 19:11:51 - mmengine - INFO - Epoch(val) [1][500/3836] eta: 0:00:37 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/15 19:11:52 - mmengine - INFO - Epoch(val) [1][600/3836] eta: 0:00:38 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/15 19:11:54 - mmengine - INFO - Epoch(val) [1][700/3836] eta: 0:00:35 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/15 19:11:55 - mmengine - INFO - Epoch(val) [1][800/3836] eta: 0:00:38 time: 0.0127 data_time: 0.0005 memory: 480 2022/09/15 19:11:56 - mmengine - INFO - Epoch(val) [1][900/3836] eta: 0:00:34 time: 0.0118 data_time: 0.0006 memory: 480 2022/09/15 19:11:57 - mmengine - INFO - Epoch(val) [1][1000/3836] eta: 0:00:34 time: 0.0121 data_time: 0.0005 memory: 480 2022/09/15 19:11:58 - mmengine - INFO - Epoch(val) [1][1100/3836] eta: 0:00:32 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/15 19:12:00 - mmengine - INFO - Epoch(val) [1][1200/3836] eta: 0:00:33 time: 0.0128 data_time: 0.0006 memory: 480 2022/09/15 19:12:01 - mmengine - INFO - Epoch(val) [1][1300/3836] eta: 0:00:30 time: 0.0122 data_time: 0.0005 memory: 480 2022/09/15 19:12:02 - mmengine - INFO - Epoch(val) [1][1400/3836] eta: 0:00:34 time: 0.0141 data_time: 0.0007 memory: 480 2022/09/15 19:12:03 - mmengine - INFO - Epoch(val) [1][1500/3836] eta: 0:00:25 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/15 19:12:04 - mmengine - INFO - Epoch(val) [1][1600/3836] eta: 0:00:28 time: 0.0127 data_time: 0.0005 memory: 480 2022/09/15 19:12:06 - mmengine - INFO - Epoch(val) [1][1700/3836] eta: 0:00:24 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/15 19:12:07 - mmengine - INFO - Epoch(val) [1][1800/3836] eta: 0:00:23 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/15 19:12:08 - mmengine - INFO - Epoch(val) [1][1900/3836] eta: 0:00:22 time: 0.0116 data_time: 0.0004 memory: 480 2022/09/15 19:12:09 - mmengine - INFO - Epoch(val) [1][2000/3836] eta: 0:00:21 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/15 19:12:11 - mmengine - INFO - Epoch(val) [1][2100/3836] eta: 0:00:19 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/15 19:12:12 - mmengine - INFO - Epoch(val) [1][2200/3836] eta: 0:00:20 time: 0.0124 data_time: 0.0011 memory: 480 2022/09/15 19:12:13 - mmengine - INFO - Epoch(val) [1][2300/3836] eta: 0:00:23 time: 0.0153 data_time: 0.0007 memory: 480 2022/09/15 19:12:14 - mmengine - INFO - Epoch(val) [1][2400/3836] eta: 0:00:16 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/15 19:12:16 - mmengine - INFO - Epoch(val) [1][2500/3836] eta: 0:00:16 time: 0.0124 data_time: 0.0006 memory: 480 2022/09/15 19:12:17 - mmengine - INFO - Epoch(val) [1][2600/3836] eta: 0:00:15 time: 0.0123 data_time: 0.0006 memory: 480 2022/09/15 19:12:18 - mmengine - INFO - Epoch(val) [1][2700/3836] eta: 0:00:12 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/15 19:12:19 - mmengine - INFO - Epoch(val) [1][2800/3836] eta: 0:00:12 time: 0.0123 data_time: 0.0004 memory: 480 2022/09/15 19:12:20 - mmengine - INFO - Epoch(val) [1][2900/3836] eta: 0:00:10 time: 0.0113 data_time: 0.0004 memory: 480 2022/09/15 19:12:22 - mmengine - INFO - Epoch(val) [1][3000/3836] eta: 0:00:09 time: 0.0116 data_time: 0.0004 memory: 480 2022/09/15 19:12:23 - mmengine - INFO - Epoch(val) [1][3100/3836] eta: 0:00:08 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/15 19:12:24 - mmengine - INFO - Epoch(val) [1][3200/3836] eta: 0:00:07 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/15 19:12:26 - mmengine - INFO - Epoch(val) [1][3300/3836] eta: 0:00:06 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/15 19:12:27 - mmengine - INFO - Epoch(val) [1][3400/3836] eta: 0:00:05 time: 0.0124 data_time: 0.0005 memory: 480 2022/09/15 19:12:28 - mmengine - INFO - Epoch(val) [1][3500/3836] eta: 0:00:03 time: 0.0115 data_time: 0.0004 memory: 480 2022/09/15 19:12:29 - mmengine - INFO - Epoch(val) [1][3600/3836] eta: 0:00:02 time: 0.0107 data_time: 0.0004 memory: 480 2022/09/15 19:12:30 - mmengine - INFO - Epoch(val) [1][3700/3836] eta: 0:00:01 time: 0.0136 data_time: 0.0006 memory: 480 2022/09/15 19:12:31 - mmengine - INFO - Epoch(val) [1][3800/3836] eta: 0:00:00 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/15 19:12:32 - mmengine - INFO - Epoch(val) [1][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.4722 IIIT5K/recog/word_acc_ignore_case_symbol: 0.7107 SVT/recog/word_acc_ignore_case_symbol: 0.6569 SVTP/recog/word_acc_ignore_case_symbol: 0.5147 IC13/recog/word_acc_ignore_case_symbol: 0.7478 IC15/recog/word_acc_ignore_case_symbol: 0.4608 2022/09/15 19:14:52 - mmengine - INFO - Epoch(train) [2][100/10520] lr: 5.0522e-05 eta: 2 days, 22:18:00 time: 1.4707 data_time: 0.5553 memory: 56769 loss_visual: 0.2153 loss: 0.2153 2022/09/15 19:16:58 - mmengine - INFO - Epoch(train) [2][200/10520] lr: 5.0997e-05 eta: 2 days, 22:15:49 time: 1.7726 data_time: 0.5289 memory: 56769 loss_visual: 0.2127 loss: 0.2127 2022/09/15 19:19:01 - mmengine - INFO - Epoch(train) [2][300/10520] lr: 5.1472e-05 eta: 2 days, 22:12:19 time: 1.2238 data_time: 0.0067 memory: 56769 loss_visual: 0.2127 loss: 0.2127 2022/09/15 19:21:03 - mmengine - INFO - Epoch(train) [2][400/10520] lr: 5.1947e-05 eta: 2 days, 22:08:56 time: 1.1578 data_time: 0.0072 memory: 56769 loss_visual: 0.2139 loss: 0.2139 2022/09/15 19:22:40 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 19:23:09 - mmengine - INFO - Epoch(train) [2][500/10520] lr: 5.2422e-05 eta: 2 days, 22:06:40 time: 1.1221 data_time: 0.2396 memory: 56769 loss_visual: 0.2053 loss: 0.2053 2022/09/15 19:25:11 - mmengine - INFO - Epoch(train) [2][600/10520] lr: 5.2897e-05 eta: 2 days, 22:03:13 time: 1.0662 data_time: 0.2343 memory: 56769 loss_visual: 0.2045 loss: 0.2045 2022/09/15 19:27:14 - mmengine - INFO - Epoch(train) [2][700/10520] lr: 5.3371e-05 eta: 2 days, 21:59:58 time: 0.8595 data_time: 0.0064 memory: 56769 loss_visual: 0.2072 loss: 0.2072 2022/09/15 19:29:15 - mmengine - INFO - Epoch(train) [2][800/10520] lr: 5.3846e-05 eta: 2 days, 21:56:15 time: 0.8859 data_time: 0.0070 memory: 56769 loss_visual: 0.2024 loss: 0.2024 2022/09/15 19:31:23 - mmengine - INFO - Epoch(train) [2][900/10520] lr: 5.4321e-05 eta: 2 days, 21:54:36 time: 1.4713 data_time: 0.5338 memory: 56769 loss_visual: 0.2047 loss: 0.2047 2022/09/15 19:33:26 - mmengine - INFO - Epoch(train) [2][1000/10520] lr: 5.4796e-05 eta: 2 days, 21:51:25 time: 1.6855 data_time: 0.4696 memory: 56769 loss_visual: 0.2032 loss: 0.2032 2022/09/15 19:35:26 - mmengine - INFO - Epoch(train) [2][1100/10520] lr: 5.5271e-05 eta: 2 days, 21:47:28 time: 1.2186 data_time: 0.0063 memory: 56769 loss_visual: 0.2032 loss: 0.2032 2022/09/15 19:37:27 - mmengine - INFO - Epoch(train) [2][1200/10520] lr: 5.5746e-05 eta: 2 days, 21:43:55 time: 1.2029 data_time: 0.0064 memory: 56769 loss_visual: 0.2010 loss: 0.2010 2022/09/15 19:39:30 - mmengine - INFO - Epoch(train) [2][1300/10520] lr: 5.6220e-05 eta: 2 days, 21:40:59 time: 1.0997 data_time: 0.2407 memory: 56769 loss_visual: 0.1905 loss: 0.1905 2022/09/15 19:41:31 - mmengine - INFO - Epoch(train) [2][1400/10520] lr: 5.6695e-05 eta: 2 days, 21:37:18 time: 1.1370 data_time: 0.2730 memory: 56769 loss_visual: 0.1973 loss: 0.1973 2022/09/15 19:43:11 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 19:43:31 - mmengine - INFO - Epoch(train) [2][1500/10520] lr: 5.7170e-05 eta: 2 days, 21:33:21 time: 0.8675 data_time: 0.0064 memory: 56769 loss_visual: 0.2009 loss: 0.2009 2022/09/15 19:45:32 - mmengine - INFO - Epoch(train) [2][1600/10520] lr: 5.7645e-05 eta: 2 days, 21:29:55 time: 0.8900 data_time: 0.0081 memory: 56769 loss_visual: 0.1896 loss: 0.1896 2022/09/15 19:47:38 - mmengine - INFO - Epoch(train) [2][1700/10520] lr: 5.8120e-05 eta: 2 days, 21:27:43 time: 1.4154 data_time: 0.5234 memory: 56769 loss_visual: 0.1924 loss: 0.1924 2022/09/15 19:49:42 - mmengine - INFO - Epoch(train) [2][1800/10520] lr: 5.8595e-05 eta: 2 days, 21:25:08 time: 1.7455 data_time: 0.4899 memory: 56769 loss_visual: 0.1908 loss: 0.1908 2022/09/15 19:51:43 - mmengine - INFO - Epoch(train) [2][1900/10520] lr: 5.9069e-05 eta: 2 days, 21:21:40 time: 1.2613 data_time: 0.0064 memory: 56769 loss_visual: 0.1866 loss: 0.1866 2022/09/15 19:53:45 - mmengine - INFO - Epoch(train) [2][2000/10520] lr: 5.9544e-05 eta: 2 days, 21:18:16 time: 1.1808 data_time: 0.0067 memory: 56769 loss_visual: 0.1836 loss: 0.1836 2022/09/15 19:55:50 - mmengine - INFO - Epoch(train) [2][2100/10520] lr: 6.0019e-05 eta: 2 days, 21:16:04 time: 1.1527 data_time: 0.2433 memory: 56769 loss_visual: 0.1835 loss: 0.1835 2022/09/15 19:57:52 - mmengine - INFO - Epoch(train) [2][2200/10520] lr: 6.0494e-05 eta: 2 days, 21:12:48 time: 1.1395 data_time: 0.2570 memory: 56769 loss_visual: 0.1833 loss: 0.1833 2022/09/15 19:59:53 - mmengine - INFO - Epoch(train) [2][2300/10520] lr: 6.0969e-05 eta: 2 days, 21:09:21 time: 0.8691 data_time: 0.0072 memory: 56769 loss_visual: 0.1867 loss: 0.1867 2022/09/15 20:01:57 - mmengine - INFO - Epoch(train) [2][2400/10520] lr: 6.1444e-05 eta: 2 days, 21:06:48 time: 0.9102 data_time: 0.0067 memory: 56769 loss_visual: 0.1919 loss: 0.1919 2022/09/15 20:03:40 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 20:04:05 - mmengine - INFO - Epoch(train) [2][2500/10520] lr: 6.1918e-05 eta: 2 days, 21:05:20 time: 1.4034 data_time: 0.4841 memory: 56769 loss_visual: 0.1896 loss: 0.1896 2022/09/15 20:06:10 - mmengine - INFO - Epoch(train) [2][2600/10520] lr: 6.2393e-05 eta: 2 days, 21:02:55 time: 1.7435 data_time: 0.4667 memory: 56769 loss_visual: 0.1730 loss: 0.1730 2022/09/15 20:08:13 - mmengine - INFO - Epoch(train) [2][2700/10520] lr: 6.2868e-05 eta: 2 days, 21:00:00 time: 1.2210 data_time: 0.0069 memory: 56769 loss_visual: 0.1823 loss: 0.1823 2022/09/15 20:10:16 - mmengine - INFO - Epoch(train) [2][2800/10520] lr: 6.3343e-05 eta: 2 days, 20:57:12 time: 1.2031 data_time: 0.0069 memory: 56769 loss_visual: 0.1768 loss: 0.1768 2022/09/15 20:12:20 - mmengine - INFO - Epoch(train) [2][2900/10520] lr: 6.3818e-05 eta: 2 days, 20:54:44 time: 1.1438 data_time: 0.3022 memory: 56769 loss_visual: 0.1864 loss: 0.1864 2022/09/15 20:14:22 - mmengine - INFO - Epoch(train) [2][3000/10520] lr: 6.4293e-05 eta: 2 days, 20:51:40 time: 1.1361 data_time: 0.2937 memory: 56769 loss_visual: 0.1724 loss: 0.1724 2022/09/15 20:16:24 - mmengine - INFO - Epoch(train) [2][3100/10520] lr: 6.4767e-05 eta: 2 days, 20:48:32 time: 0.8608 data_time: 0.0066 memory: 56769 loss_visual: 0.1734 loss: 0.1734 2022/09/15 20:18:25 - mmengine - INFO - Epoch(train) [2][3200/10520] lr: 6.5242e-05 eta: 2 days, 20:45:16 time: 0.8640 data_time: 0.0064 memory: 56769 loss_visual: 0.1759 loss: 0.1759 2022/09/15 20:20:30 - mmengine - INFO - Epoch(train) [2][3300/10520] lr: 6.5717e-05 eta: 2 days, 20:43:03 time: 1.3845 data_time: 0.4642 memory: 56769 loss_visual: 0.1727 loss: 0.1727 2022/09/15 20:22:36 - mmengine - INFO - Epoch(train) [2][3400/10520] lr: 6.6192e-05 eta: 2 days, 20:40:51 time: 1.7954 data_time: 0.4727 memory: 56769 loss_visual: 0.1694 loss: 0.1694 2022/09/15 20:24:11 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 20:24:37 - mmengine - INFO - Epoch(train) [2][3500/10520] lr: 6.6667e-05 eta: 2 days, 20:37:44 time: 1.2737 data_time: 0.0065 memory: 56769 loss_visual: 0.1693 loss: 0.1693 2022/09/15 20:26:38 - mmengine - INFO - Epoch(train) [2][3600/10520] lr: 6.7142e-05 eta: 2 days, 20:34:24 time: 1.1900 data_time: 0.0067 memory: 56769 loss_visual: 0.1684 loss: 0.1684 2022/09/15 20:28:42 - mmengine - INFO - Epoch(train) [2][3700/10520] lr: 6.7616e-05 eta: 2 days, 20:32:01 time: 1.1579 data_time: 0.2763 memory: 56769 loss_visual: 0.1668 loss: 0.1668 2022/09/15 20:30:46 - mmengine - INFO - Epoch(train) [2][3800/10520] lr: 6.8091e-05 eta: 2 days, 20:29:27 time: 1.1501 data_time: 0.2837 memory: 56769 loss_visual: 0.1669 loss: 0.1669 2022/09/15 20:32:48 - mmengine - INFO - Epoch(train) [2][3900/10520] lr: 6.8566e-05 eta: 2 days, 20:26:32 time: 0.8608 data_time: 0.0064 memory: 56769 loss_visual: 0.1669 loss: 0.1669 2022/09/15 20:34:51 - mmengine - INFO - Epoch(train) [2][4000/10520] lr: 6.9041e-05 eta: 2 days, 20:23:48 time: 0.8810 data_time: 0.0068 memory: 56769 loss_visual: 0.1664 loss: 0.1664 2022/09/15 20:36:59 - mmengine - INFO - Epoch(train) [2][4100/10520] lr: 6.9516e-05 eta: 2 days, 20:22:17 time: 1.4471 data_time: 0.4644 memory: 56769 loss_visual: 0.1659 loss: 0.1659 2022/09/15 20:39:04 - mmengine - INFO - Epoch(train) [2][4200/10520] lr: 6.9991e-05 eta: 2 days, 20:20:01 time: 1.7197 data_time: 0.4631 memory: 56769 loss_visual: 0.1611 loss: 0.1611 2022/09/15 20:41:08 - mmengine - INFO - Epoch(train) [2][4300/10520] lr: 7.0465e-05 eta: 2 days, 20:17:27 time: 1.2954 data_time: 0.0070 memory: 56769 loss_visual: 0.1718 loss: 0.1718 2022/09/15 20:43:11 - mmengine - INFO - Epoch(train) [2][4400/10520] lr: 7.0940e-05 eta: 2 days, 20:14:49 time: 1.1952 data_time: 0.0066 memory: 56769 loss_visual: 0.1625 loss: 0.1625 2022/09/15 20:44:46 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 20:45:15 - mmengine - INFO - Epoch(train) [2][4500/10520] lr: 7.1415e-05 eta: 2 days, 20:12:16 time: 1.1872 data_time: 0.2998 memory: 56769 loss_visual: 0.1581 loss: 0.1581 2022/09/15 20:47:17 - mmengine - INFO - Epoch(train) [2][4600/10520] lr: 7.1890e-05 eta: 2 days, 20:09:21 time: 1.1487 data_time: 0.2845 memory: 56769 loss_visual: 0.1622 loss: 0.1622 2022/09/15 20:49:20 - mmengine - INFO - Epoch(train) [2][4700/10520] lr: 7.2365e-05 eta: 2 days, 20:06:43 time: 0.8409 data_time: 0.0075 memory: 56769 loss_visual: 0.1549 loss: 0.1549 2022/09/15 20:51:22 - mmengine - INFO - Epoch(train) [2][4800/10520] lr: 7.2840e-05 eta: 2 days, 20:03:54 time: 0.8451 data_time: 0.0063 memory: 56769 loss_visual: 0.1585 loss: 0.1585 2022/09/15 20:53:29 - mmengine - INFO - Epoch(train) [2][4900/10520] lr: 7.3314e-05 eta: 2 days, 20:02:12 time: 1.4520 data_time: 0.4596 memory: 56769 loss_visual: 0.1600 loss: 0.1600 2022/09/15 20:55:35 - mmengine - INFO - Epoch(train) [2][5000/10520] lr: 7.3789e-05 eta: 2 days, 20:00:01 time: 1.7760 data_time: 0.4879 memory: 56769 loss_visual: 0.1578 loss: 0.1578 2022/09/15 20:57:38 - mmengine - INFO - Epoch(train) [2][5100/10520] lr: 7.4264e-05 eta: 2 days, 19:57:24 time: 1.2493 data_time: 0.0072 memory: 56769 loss_visual: 0.1551 loss: 0.1551 2022/09/15 20:59:40 - mmengine - INFO - Epoch(train) [2][5200/10520] lr: 7.4739e-05 eta: 2 days, 19:54:39 time: 1.2474 data_time: 0.0066 memory: 56769 loss_visual: 0.1602 loss: 0.1602 2022/09/15 21:01:46 - mmengine - INFO - Epoch(train) [2][5300/10520] lr: 7.5214e-05 eta: 2 days, 19:52:34 time: 1.1532 data_time: 0.2829 memory: 56769 loss_visual: 0.1528 loss: 0.1528 2022/09/15 21:03:49 - mmengine - INFO - Epoch(train) [2][5400/10520] lr: 7.5689e-05 eta: 2 days, 19:50:04 time: 1.1285 data_time: 0.2700 memory: 56769 loss_visual: 0.1490 loss: 0.1490 2022/09/15 21:05:31 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 21:05:51 - mmengine - INFO - Epoch(train) [2][5500/10520] lr: 7.6163e-05 eta: 2 days, 19:47:15 time: 0.8698 data_time: 0.0070 memory: 56769 loss_visual: 0.1561 loss: 0.1561 2022/09/15 21:07:55 - mmengine - INFO - Epoch(train) [2][5600/10520] lr: 7.6638e-05 eta: 2 days, 19:44:46 time: 0.9321 data_time: 0.0067 memory: 56769 loss_visual: 0.1570 loss: 0.1570 2022/09/15 21:10:04 - mmengine - INFO - Epoch(train) [2][5700/10520] lr: 7.7113e-05 eta: 2 days, 19:43:19 time: 1.4380 data_time: 0.4561 memory: 56769 loss_visual: 0.1585 loss: 0.1585 2022/09/15 21:12:09 - mmengine - INFO - Epoch(train) [2][5800/10520] lr: 7.7588e-05 eta: 2 days, 19:41:13 time: 1.7431 data_time: 0.4760 memory: 56769 loss_visual: 0.1522 loss: 0.1522 2022/09/15 21:14:14 - mmengine - INFO - Epoch(train) [2][5900/10520] lr: 7.8063e-05 eta: 2 days, 19:38:53 time: 1.2590 data_time: 0.0066 memory: 56769 loss_visual: 0.1518 loss: 0.1518 2022/09/15 21:16:18 - mmengine - INFO - Epoch(train) [2][6000/10520] lr: 7.8538e-05 eta: 2 days, 19:36:38 time: 1.2587 data_time: 0.0065 memory: 56769 loss_visual: 0.1465 loss: 0.1465 2022/09/15 21:18:22 - mmengine - INFO - Epoch(train) [2][6100/10520] lr: 7.9012e-05 eta: 2 days, 19:34:15 time: 1.1610 data_time: 0.2923 memory: 56769 loss_visual: 0.1578 loss: 0.1578 2022/09/15 21:20:25 - mmengine - INFO - Epoch(train) [2][6200/10520] lr: 7.9487e-05 eta: 2 days, 19:31:38 time: 1.1410 data_time: 0.2713 memory: 56769 loss_visual: 0.1537 loss: 0.1537 2022/09/15 21:22:28 - mmengine - INFO - Epoch(train) [2][6300/10520] lr: 7.9962e-05 eta: 2 days, 19:29:07 time: 0.8292 data_time: 0.0068 memory: 56769 loss_visual: 0.1580 loss: 0.1580 2022/09/15 21:24:32 - mmengine - INFO - Epoch(train) [2][6400/10520] lr: 8.0437e-05 eta: 2 days, 19:26:34 time: 0.8499 data_time: 0.0067 memory: 56769 loss_visual: 0.1480 loss: 0.1480 2022/09/15 21:26:13 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 21:26:38 - mmengine - INFO - Epoch(train) [2][6500/10520] lr: 8.0912e-05 eta: 2 days, 19:24:44 time: 1.4479 data_time: 0.4744 memory: 56769 loss_visual: 0.1468 loss: 0.1468 2022/09/15 21:28:44 - mmengine - INFO - Epoch(train) [2][6600/10520] lr: 8.1387e-05 eta: 2 days, 19:22:34 time: 1.7567 data_time: 0.4810 memory: 56769 loss_visual: 0.1513 loss: 0.1513 2022/09/15 21:30:46 - mmengine - INFO - Epoch(train) [2][6700/10520] lr: 8.1861e-05 eta: 2 days, 19:19:54 time: 1.2516 data_time: 0.0063 memory: 56769 loss_visual: 0.1570 loss: 0.1570 2022/09/15 21:32:48 - mmengine - INFO - Epoch(train) [2][6800/10520] lr: 8.2336e-05 eta: 2 days, 19:17:12 time: 1.2363 data_time: 0.0066 memory: 56769 loss_visual: 0.1505 loss: 0.1505 2022/09/15 21:34:54 - mmengine - INFO - Epoch(train) [2][6900/10520] lr: 8.2811e-05 eta: 2 days, 19:15:06 time: 1.1487 data_time: 0.2773 memory: 56769 loss_visual: 0.1496 loss: 0.1496 2022/09/15 21:36:56 - mmengine - INFO - Epoch(train) [2][7000/10520] lr: 8.3286e-05 eta: 2 days, 19:12:31 time: 1.1663 data_time: 0.2885 memory: 56769 loss_visual: 0.1465 loss: 0.1465 2022/09/15 21:38:58 - mmengine - INFO - Epoch(train) [2][7100/10520] lr: 8.3761e-05 eta: 2 days, 19:09:41 time: 0.8803 data_time: 0.0065 memory: 56769 loss_visual: 0.1504 loss: 0.1504 2022/09/15 21:41:01 - mmengine - INFO - Epoch(train) [2][7200/10520] lr: 8.4236e-05 eta: 2 days, 19:07:07 time: 0.8750 data_time: 0.0066 memory: 56769 loss_visual: 0.1447 loss: 0.1447 2022/09/15 21:43:09 - mmengine - INFO - Epoch(train) [2][7300/10520] lr: 8.4710e-05 eta: 2 days, 19:05:33 time: 1.4637 data_time: 0.4710 memory: 56769 loss_visual: 0.1467 loss: 0.1467 2022/09/15 21:45:14 - mmengine - INFO - Epoch(train) [2][7400/10520] lr: 8.5185e-05 eta: 2 days, 19:03:21 time: 1.7755 data_time: 0.4869 memory: 56769 loss_visual: 0.1412 loss: 0.1412 2022/09/15 21:46:51 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 21:47:18 - mmengine - INFO - Epoch(train) [2][7500/10520] lr: 8.5660e-05 eta: 2 days, 19:01:01 time: 1.2538 data_time: 0.0067 memory: 56769 loss_visual: 0.1470 loss: 0.1470 2022/09/15 21:49:22 - mmengine - INFO - Epoch(train) [2][7600/10520] lr: 8.6135e-05 eta: 2 days, 18:58:42 time: 1.2112 data_time: 0.0070 memory: 56769 loss_visual: 0.1430 loss: 0.1430 2022/09/15 21:51:27 - mmengine - INFO - Epoch(train) [2][7700/10520] lr: 8.6610e-05 eta: 2 days, 18:56:33 time: 1.1757 data_time: 0.3389 memory: 56769 loss_visual: 0.1445 loss: 0.1445 2022/09/15 21:53:30 - mmengine - INFO - Epoch(train) [2][7800/10520] lr: 8.7085e-05 eta: 2 days, 18:54:08 time: 1.1540 data_time: 0.2696 memory: 56769 loss_visual: 0.1449 loss: 0.1449 2022/09/15 21:55:33 - mmengine - INFO - Epoch(train) [2][7900/10520] lr: 8.7559e-05 eta: 2 days, 18:51:38 time: 0.8525 data_time: 0.0066 memory: 56769 loss_visual: 0.1437 loss: 0.1437 2022/09/15 21:57:35 - mmengine - INFO - Epoch(train) [2][8000/10520] lr: 8.8034e-05 eta: 2 days, 18:48:55 time: 0.8724 data_time: 0.0089 memory: 56769 loss_visual: 0.1419 loss: 0.1419 2022/09/15 21:59:41 - mmengine - INFO - Epoch(train) [2][8100/10520] lr: 8.8509e-05 eta: 2 days, 18:46:49 time: 1.3594 data_time: 0.4794 memory: 56769 loss_visual: 0.1361 loss: 0.1361 2022/09/15 22:01:45 - mmengine - INFO - Epoch(train) [2][8200/10520] lr: 8.8984e-05 eta: 2 days, 18:44:30 time: 1.6793 data_time: 0.4285 memory: 56769 loss_visual: 0.1418 loss: 0.1418 2022/09/15 22:03:46 - mmengine - INFO - Epoch(train) [2][8300/10520] lr: 8.9459e-05 eta: 2 days, 18:41:49 time: 1.2175 data_time: 0.0067 memory: 56769 loss_visual: 0.1384 loss: 0.1384 2022/09/15 22:05:49 - mmengine - INFO - Epoch(train) [2][8400/10520] lr: 8.9934e-05 eta: 2 days, 18:39:10 time: 1.1950 data_time: 0.0066 memory: 56769 loss_visual: 0.1380 loss: 0.1380 2022/09/15 22:07:24 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 22:07:53 - mmengine - INFO - Epoch(train) [2][8500/10520] lr: 9.0408e-05 eta: 2 days, 18:36:55 time: 1.2389 data_time: 0.3137 memory: 56769 loss_visual: 0.1396 loss: 0.1396 2022/09/15 22:09:53 - mmengine - INFO - Epoch(train) [2][8600/10520] lr: 9.0883e-05 eta: 2 days, 18:34:02 time: 1.1648 data_time: 0.3011 memory: 56769 loss_visual: 0.1465 loss: 0.1465 2022/09/15 22:11:54 - mmengine - INFO - Epoch(train) [2][8700/10520] lr: 9.1358e-05 eta: 2 days, 18:31:13 time: 0.8657 data_time: 0.0070 memory: 56769 loss_visual: 0.1385 loss: 0.1385 2022/09/15 22:13:56 - mmengine - INFO - Epoch(train) [2][8800/10520] lr: 9.1833e-05 eta: 2 days, 18:28:32 time: 0.8426 data_time: 0.0063 memory: 56769 loss_visual: 0.1421 loss: 0.1421 2022/09/15 22:16:01 - mmengine - INFO - Epoch(train) [2][8900/10520] lr: 9.2308e-05 eta: 2 days, 18:26:24 time: 1.3566 data_time: 0.4525 memory: 56769 loss_visual: 0.1365 loss: 0.1365 2022/09/15 22:18:08 - mmengine - INFO - Epoch(train) [2][9000/10520] lr: 9.2783e-05 eta: 2 days, 18:24:34 time: 1.7776 data_time: 0.4909 memory: 56769 loss_visual: 0.1355 loss: 0.1355 2022/09/15 22:20:08 - mmengine - INFO - Epoch(train) [2][9100/10520] lr: 9.3257e-05 eta: 2 days, 18:21:41 time: 1.2488 data_time: 0.0062 memory: 56769 loss_visual: 0.1389 loss: 0.1389 2022/09/15 22:22:09 - mmengine - INFO - Epoch(train) [2][9200/10520] lr: 9.3732e-05 eta: 2 days, 18:18:57 time: 1.2374 data_time: 0.0064 memory: 56769 loss_visual: 0.1400 loss: 0.1400 2022/09/15 22:24:14 - mmengine - INFO - Epoch(train) [2][9300/10520] lr: 9.4207e-05 eta: 2 days, 18:16:49 time: 1.2140 data_time: 0.3218 memory: 56769 loss_visual: 0.1361 loss: 0.1361 2022/09/15 22:26:16 - mmengine - INFO - Epoch(train) [2][9400/10520] lr: 9.4682e-05 eta: 2 days, 18:14:15 time: 1.1386 data_time: 0.2952 memory: 56769 loss_visual: 0.1318 loss: 0.1318 2022/09/15 22:27:57 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 22:28:18 - mmengine - INFO - Epoch(train) [2][9500/10520] lr: 9.5157e-05 eta: 2 days, 18:11:32 time: 0.8860 data_time: 0.0066 memory: 56769 loss_visual: 0.1348 loss: 0.1348 2022/09/15 22:30:19 - mmengine - INFO - Epoch(train) [2][9600/10520] lr: 9.5632e-05 eta: 2 days, 18:08:49 time: 0.8889 data_time: 0.0063 memory: 56769 loss_visual: 0.1336 loss: 0.1336 2022/09/15 22:32:25 - mmengine - INFO - Epoch(train) [2][9700/10520] lr: 9.6106e-05 eta: 2 days, 18:06:52 time: 1.3993 data_time: 0.4844 memory: 56769 loss_visual: 0.1316 loss: 0.1316 2022/09/15 22:34:30 - mmengine - INFO - Epoch(train) [2][9800/10520] lr: 9.6581e-05 eta: 2 days, 18:04:45 time: 1.6940 data_time: 0.4396 memory: 56769 loss_visual: 0.1359 loss: 0.1359 2022/09/15 22:36:32 - mmengine - INFO - Epoch(train) [2][9900/10520] lr: 9.7056e-05 eta: 2 days, 18:02:15 time: 1.2814 data_time: 0.0070 memory: 56769 loss_visual: 0.1342 loss: 0.1342 2022/09/15 22:38:33 - mmengine - INFO - Epoch(train) [2][10000/10520] lr: 9.7531e-05 eta: 2 days, 17:59:31 time: 1.2162 data_time: 0.0103 memory: 56769 loss_visual: 0.1340 loss: 0.1340 2022/09/15 22:40:36 - mmengine - INFO - Epoch(train) [2][10100/10520] lr: 9.8006e-05 eta: 2 days, 17:57:05 time: 1.1769 data_time: 0.2519 memory: 56769 loss_visual: 0.1306 loss: 0.1306 2022/09/15 22:42:37 - mmengine - INFO - Epoch(train) [2][10200/10520] lr: 9.8481e-05 eta: 2 days, 17:54:25 time: 1.1393 data_time: 0.2592 memory: 56769 loss_visual: 0.1327 loss: 0.1327 2022/09/15 22:44:39 - mmengine - INFO - Epoch(train) [2][10300/10520] lr: 9.8955e-05 eta: 2 days, 17:51:48 time: 0.8879 data_time: 0.0064 memory: 56769 loss_visual: 0.1291 loss: 0.1291 2022/09/15 22:46:40 - mmengine - INFO - Epoch(train) [2][10400/10520] lr: 9.9430e-05 eta: 2 days, 17:49:08 time: 0.8797 data_time: 0.0066 memory: 56769 loss_visual: 0.1340 loss: 0.1340 2022/09/15 22:48:20 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 22:48:42 - mmengine - INFO - Epoch(train) [2][10500/10520] lr: 9.9905e-05 eta: 2 days, 17:46:33 time: 1.1484 data_time: 0.2998 memory: 56769 loss_visual: 0.1259 loss: 0.1259 2022/09/15 22:49:01 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 22:49:01 - mmengine - INFO - Saving checkpoint at 2 epochs 2022/09/15 22:49:24 - mmengine - INFO - Epoch(val) [2][100/3836] eta: 0:08:20 time: 0.1340 data_time: 0.0006 memory: 56769 2022/09/15 22:49:30 - mmengine - INFO - Epoch(val) [2][200/3836] eta: 0:00:45 time: 0.0125 data_time: 0.0005 memory: 480 2022/09/15 22:49:31 - mmengine - INFO - Epoch(val) [2][300/3836] eta: 0:00:41 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/15 22:49:33 - mmengine - INFO - Epoch(val) [2][400/3836] eta: 0:00:41 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/15 22:49:34 - mmengine - INFO - Epoch(val) [2][500/3836] eta: 0:00:39 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/15 22:49:35 - mmengine - INFO - Epoch(val) [2][600/3836] eta: 0:00:42 time: 0.0132 data_time: 0.0022 memory: 480 2022/09/15 22:49:36 - mmengine - INFO - Epoch(val) [2][700/3836] eta: 0:00:36 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/15 22:49:37 - mmengine - INFO - Epoch(val) [2][800/3836] eta: 0:00:35 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/15 22:49:39 - mmengine - INFO - Epoch(val) [2][900/3836] eta: 0:00:33 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/15 22:49:40 - mmengine - INFO - Epoch(val) [2][1000/3836] eta: 0:00:32 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/15 22:49:41 - mmengine - INFO - Epoch(val) [2][1100/3836] eta: 0:00:32 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/15 22:49:42 - mmengine - INFO - Epoch(val) [2][1200/3836] eta: 0:00:31 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/15 22:49:43 - mmengine - INFO - Epoch(val) [2][1300/3836] eta: 0:00:29 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/15 22:49:45 - mmengine - INFO - Epoch(val) [2][1400/3836] eta: 0:00:28 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/15 22:49:46 - mmengine - INFO - Epoch(val) [2][1500/3836] eta: 0:00:31 time: 0.0136 data_time: 0.0007 memory: 480 2022/09/15 22:49:47 - mmengine - INFO - Epoch(val) [2][1600/3836] eta: 0:00:25 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/15 22:49:48 - mmengine - INFO - Epoch(val) [2][1700/3836] eta: 0:00:24 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/15 22:49:49 - mmengine - INFO - Epoch(val) [2][1800/3836] eta: 0:00:23 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/15 22:49:51 - mmengine - INFO - Epoch(val) [2][1900/3836] eta: 0:00:23 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/15 22:49:52 - mmengine - INFO - Epoch(val) [2][2000/3836] eta: 0:00:22 time: 0.0121 data_time: 0.0005 memory: 480 2022/09/15 22:49:53 - mmengine - INFO - Epoch(val) [2][2100/3836] eta: 0:00:20 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/15 22:49:54 - mmengine - INFO - Epoch(val) [2][2200/3836] eta: 0:00:19 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/15 22:49:55 - mmengine - INFO - Epoch(val) [2][2300/3836] eta: 0:00:17 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/15 22:49:57 - mmengine - INFO - Epoch(val) [2][2400/3836] eta: 0:00:17 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/15 22:49:58 - mmengine - INFO - Epoch(val) [2][2500/3836] eta: 0:00:17 time: 0.0133 data_time: 0.0005 memory: 480 2022/09/15 22:49:59 - mmengine - INFO - Epoch(val) [2][2600/3836] eta: 0:00:13 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/15 22:50:00 - mmengine - INFO - Epoch(val) [2][2700/3836] eta: 0:00:14 time: 0.0125 data_time: 0.0005 memory: 480 2022/09/15 22:50:02 - mmengine - INFO - Epoch(val) [2][2800/3836] eta: 0:00:12 time: 0.0118 data_time: 0.0004 memory: 480 2022/09/15 22:50:03 - mmengine - INFO - Epoch(val) [2][2900/3836] eta: 0:00:10 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/15 22:50:04 - mmengine - INFO - Epoch(val) [2][3000/3836] eta: 0:00:09 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/15 22:50:05 - mmengine - INFO - Epoch(val) [2][3100/3836] eta: 0:00:07 time: 0.0105 data_time: 0.0004 memory: 480 2022/09/15 22:50:06 - mmengine - INFO - Epoch(val) [2][3200/3836] eta: 0:00:06 time: 0.0105 data_time: 0.0005 memory: 480 2022/09/15 22:50:07 - mmengine - INFO - Epoch(val) [2][3300/3836] eta: 0:00:05 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/15 22:50:08 - mmengine - INFO - Epoch(val) [2][3400/3836] eta: 0:00:04 time: 0.0111 data_time: 0.0004 memory: 480 2022/09/15 22:50:09 - mmengine - INFO - Epoch(val) [2][3500/3836] eta: 0:00:03 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/15 22:50:11 - mmengine - INFO - Epoch(val) [2][3600/3836] eta: 0:00:02 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/15 22:50:12 - mmengine - INFO - Epoch(val) [2][3700/3836] eta: 0:00:01 time: 0.0106 data_time: 0.0004 memory: 480 2022/09/15 22:50:13 - mmengine - INFO - Epoch(val) [2][3800/3836] eta: 0:00:00 time: 0.0105 data_time: 0.0005 memory: 480 2022/09/15 22:50:13 - mmengine - INFO - Epoch(val) [2][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.7187 IIIT5K/recog/word_acc_ignore_case_symbol: 0.8620 SVT/recog/word_acc_ignore_case_symbol: 0.7960 SVTP/recog/word_acc_ignore_case_symbol: 0.6760 IC13/recog/word_acc_ignore_case_symbol: 0.8522 IC15/recog/word_acc_ignore_case_symbol: 0.6216 2022/09/15 22:52:34 - mmengine - INFO - Epoch(train) [3][100/10520] lr: 1.0000e-04 eta: 2 days, 17:45:24 time: 1.4881 data_time: 0.3796 memory: 56769 loss_visual: 0.1291 loss: 0.1291 2022/09/15 22:54:39 - mmengine - INFO - Epoch(train) [3][200/10520] lr: 1.0000e-04 eta: 2 days, 17:43:23 time: 1.7014 data_time: 0.5404 memory: 56769 loss_visual: 0.1342 loss: 0.1342 2022/09/15 22:56:41 - mmengine - INFO - Epoch(train) [3][300/10520] lr: 1.0000e-04 eta: 2 days, 17:40:46 time: 1.0348 data_time: 0.2190 memory: 56769 loss_visual: 0.1333 loss: 0.1333 2022/09/15 22:58:44 - mmengine - INFO - Epoch(train) [3][400/10520] lr: 1.0000e-04 eta: 2 days, 17:38:26 time: 1.0486 data_time: 0.1229 memory: 56769 loss_visual: 0.1305 loss: 0.1305 2022/09/15 23:00:46 - mmengine - INFO - Epoch(train) [3][500/10520] lr: 1.0000e-04 eta: 2 days, 17:35:57 time: 1.0554 data_time: 0.2180 memory: 56769 loss_visual: 0.1308 loss: 0.1308 2022/09/15 23:02:51 - mmengine - INFO - Epoch(train) [3][600/10520] lr: 1.0000e-04 eta: 2 days, 17:33:49 time: 1.1337 data_time: 0.1042 memory: 56769 loss_visual: 0.1308 loss: 0.1308 2022/09/15 23:04:54 - mmengine - INFO - Epoch(train) [3][700/10520] lr: 1.0000e-04 eta: 2 days, 17:31:23 time: 1.0857 data_time: 0.0389 memory: 56769 loss_visual: 0.1264 loss: 0.1264 2022/09/15 23:06:56 - mmengine - INFO - Epoch(train) [3][800/10520] lr: 1.0000e-04 eta: 2 days, 17:28:56 time: 0.8960 data_time: 0.0394 memory: 56769 loss_visual: 0.1274 loss: 0.1274 2022/09/15 23:09:05 - mmengine - INFO - Epoch(train) [3][900/10520] lr: 1.0000e-04 eta: 2 days, 17:27:23 time: 1.5160 data_time: 0.3874 memory: 56769 loss_visual: 0.1268 loss: 0.1268 2022/09/15 23:10:14 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 23:11:09 - mmengine - INFO - Epoch(train) [3][1000/10520] lr: 1.0000e-04 eta: 2 days, 17:25:09 time: 1.6559 data_time: 0.4954 memory: 56769 loss_visual: 0.1281 loss: 0.1281 2022/09/15 23:13:12 - mmengine - INFO - Epoch(train) [3][1100/10520] lr: 1.0000e-04 eta: 2 days, 17:22:44 time: 1.0808 data_time: 0.2280 memory: 56769 loss_visual: 0.1254 loss: 0.1254 2022/09/15 23:15:15 - mmengine - INFO - Epoch(train) [3][1200/10520] lr: 1.0000e-04 eta: 2 days, 17:20:28 time: 1.0424 data_time: 0.2025 memory: 56769 loss_visual: 0.1239 loss: 0.1239 2022/09/15 23:17:18 - mmengine - INFO - Epoch(train) [3][1300/10520] lr: 1.0000e-04 eta: 2 days, 17:18:02 time: 1.0490 data_time: 0.1645 memory: 56769 loss_visual: 0.1304 loss: 0.1304 2022/09/15 23:19:22 - mmengine - INFO - Epoch(train) [3][1400/10520] lr: 1.0000e-04 eta: 2 days, 17:15:53 time: 1.1460 data_time: 0.1164 memory: 56769 loss_visual: 0.1273 loss: 0.1273 2022/09/15 23:21:27 - mmengine - INFO - Epoch(train) [3][1500/10520] lr: 1.0000e-04 eta: 2 days, 17:13:42 time: 1.1208 data_time: 0.0394 memory: 56769 loss_visual: 0.1254 loss: 0.1254 2022/09/15 23:23:29 - mmengine - INFO - Epoch(train) [3][1600/10520] lr: 1.0000e-04 eta: 2 days, 17:11:18 time: 0.9045 data_time: 0.0862 memory: 56769 loss_visual: 0.1229 loss: 0.1229 2022/09/15 23:25:39 - mmengine - INFO - Epoch(train) [3][1700/10520] lr: 1.0000e-04 eta: 2 days, 17:09:49 time: 1.5410 data_time: 0.3832 memory: 56769 loss_visual: 0.1177 loss: 0.1177 2022/09/15 23:27:47 - mmengine - INFO - Epoch(train) [3][1800/10520] lr: 1.0000e-04 eta: 2 days, 17:08:11 time: 1.7269 data_time: 0.5661 memory: 56769 loss_visual: 0.1242 loss: 0.1242 2022/09/15 23:29:52 - mmengine - INFO - Epoch(train) [3][1900/10520] lr: 1.0000e-04 eta: 2 days, 17:06:04 time: 1.0812 data_time: 0.2570 memory: 56769 loss_visual: 0.1257 loss: 0.1257 2022/09/15 23:31:09 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 23:31:57 - mmengine - INFO - Epoch(train) [3][2000/10520] lr: 1.0000e-04 eta: 2 days, 17:04:00 time: 1.0282 data_time: 0.2080 memory: 56769 loss_visual: 0.1290 loss: 0.1290 2022/09/15 23:34:01 - mmengine - INFO - Epoch(train) [3][2100/10520] lr: 1.0000e-04 eta: 2 days, 17:01:50 time: 1.0690 data_time: 0.2105 memory: 56769 loss_visual: 0.1272 loss: 0.1272 2022/09/15 23:36:06 - mmengine - INFO - Epoch(train) [3][2200/10520] lr: 1.0000e-04 eta: 2 days, 16:59:39 time: 1.1336 data_time: 0.0741 memory: 56769 loss_visual: 0.1218 loss: 0.1218 2022/09/15 23:38:10 - mmengine - INFO - Epoch(train) [3][2300/10520] lr: 1.0000e-04 eta: 2 days, 16:57:29 time: 1.1022 data_time: 0.0626 memory: 56769 loss_visual: 0.1224 loss: 0.1224 2022/09/15 23:40:12 - mmengine - INFO - Epoch(train) [3][2400/10520] lr: 1.0000e-04 eta: 2 days, 16:55:00 time: 0.8922 data_time: 0.0409 memory: 56769 loss_visual: 0.1200 loss: 0.1200 2022/09/15 23:42:21 - mmengine - INFO - Epoch(train) [3][2500/10520] lr: 1.0000e-04 eta: 2 days, 16:53:27 time: 1.4953 data_time: 0.3994 memory: 56769 loss_visual: 0.1193 loss: 0.1193 2022/09/15 23:44:26 - mmengine - INFO - Epoch(train) [3][2600/10520] lr: 1.0000e-04 eta: 2 days, 16:51:23 time: 1.6332 data_time: 0.5021 memory: 56769 loss_visual: 0.1256 loss: 0.1256 2022/09/15 23:46:30 - mmengine - INFO - Epoch(train) [3][2700/10520] lr: 1.0000e-04 eta: 2 days, 16:49:06 time: 1.0707 data_time: 0.2303 memory: 56769 loss_visual: 0.1140 loss: 0.1140 2022/09/15 23:48:32 - mmengine - INFO - Epoch(train) [3][2800/10520] lr: 1.0000e-04 eta: 2 days, 16:46:42 time: 1.0006 data_time: 0.1760 memory: 56769 loss_visual: 0.1206 loss: 0.1206 2022/09/15 23:50:35 - mmengine - INFO - Epoch(train) [3][2900/10520] lr: 1.0000e-04 eta: 2 days, 16:44:21 time: 1.0819 data_time: 0.1815 memory: 56769 loss_visual: 0.1203 loss: 0.1203 2022/09/15 23:51:50 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/15 23:52:39 - mmengine - INFO - Epoch(train) [3][3000/10520] lr: 1.0000e-04 eta: 2 days, 16:42:06 time: 1.1592 data_time: 0.1209 memory: 56769 loss_visual: 0.1190 loss: 0.1190 2022/09/15 23:54:41 - mmengine - INFO - Epoch(train) [3][3100/10520] lr: 1.0000e-04 eta: 2 days, 16:39:35 time: 1.0886 data_time: 0.0383 memory: 56769 loss_visual: 0.1230 loss: 0.1230 2022/09/15 23:56:43 - mmengine - INFO - Epoch(train) [3][3200/10520] lr: 1.0000e-04 eta: 2 days, 16:37:09 time: 0.9304 data_time: 0.0712 memory: 56769 loss_visual: 0.1195 loss: 0.1195 2022/09/15 23:58:51 - mmengine - INFO - Epoch(train) [3][3300/10520] lr: 1.0000e-04 eta: 2 days, 16:35:28 time: 1.5194 data_time: 0.3835 memory: 56769 loss_visual: 0.1186 loss: 0.1186 2022/09/16 00:01:00 - mmengine - INFO - Epoch(train) [3][3400/10520] lr: 1.0000e-04 eta: 2 days, 16:33:54 time: 1.6267 data_time: 0.5111 memory: 56769 loss_visual: 0.1121 loss: 0.1121 2022/09/16 00:03:02 - mmengine - INFO - Epoch(train) [3][3500/10520] lr: 1.0000e-04 eta: 2 days, 16:31:26 time: 1.0613 data_time: 0.2227 memory: 56769 loss_visual: 0.1166 loss: 0.1166 2022/09/16 00:05:06 - mmengine - INFO - Epoch(train) [3][3600/10520] lr: 1.0000e-04 eta: 2 days, 16:29:11 time: 0.9987 data_time: 0.1170 memory: 56769 loss_visual: 0.1213 loss: 0.1213 2022/09/16 00:07:09 - mmengine - INFO - Epoch(train) [3][3700/10520] lr: 1.0000e-04 eta: 2 days, 16:26:53 time: 1.0666 data_time: 0.2102 memory: 56769 loss_visual: 0.1195 loss: 0.1195 2022/09/16 00:09:13 - mmengine - INFO - Epoch(train) [3][3800/10520] lr: 1.0000e-04 eta: 2 days, 16:24:41 time: 1.1726 data_time: 0.0816 memory: 56769 loss_visual: 0.1190 loss: 0.1190 2022/09/16 00:11:15 - mmengine - INFO - Epoch(train) [3][3900/10520] lr: 1.0000e-04 eta: 2 days, 16:22:15 time: 1.0760 data_time: 0.0741 memory: 56769 loss_visual: 0.1191 loss: 0.1191 2022/09/16 00:12:31 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 00:13:18 - mmengine - INFO - Epoch(train) [3][4000/10520] lr: 1.0000e-04 eta: 2 days, 16:19:53 time: 0.8902 data_time: 0.0713 memory: 56769 loss_visual: 0.1183 loss: 0.1183 2022/09/16 00:15:26 - mmengine - INFO - Epoch(train) [3][4100/10520] lr: 1.0000e-04 eta: 2 days, 16:18:10 time: 1.4765 data_time: 0.3995 memory: 56769 loss_visual: 0.1188 loss: 0.1188 2022/09/16 00:17:29 - mmengine - INFO - Epoch(train) [3][4200/10520] lr: 1.0000e-04 eta: 2 days, 16:15:53 time: 1.6089 data_time: 0.4715 memory: 56769 loss_visual: 0.1143 loss: 0.1143 2022/09/16 00:19:32 - mmengine - INFO - Epoch(train) [3][4300/10520] lr: 1.0000e-04 eta: 2 days, 16:13:35 time: 1.1170 data_time: 0.1985 memory: 56769 loss_visual: 0.1187 loss: 0.1187 2022/09/16 00:21:38 - mmengine - INFO - Epoch(train) [3][4400/10520] lr: 1.0000e-04 eta: 2 days, 16:11:35 time: 1.0393 data_time: 0.1812 memory: 56769 loss_visual: 0.1164 loss: 0.1164 2022/09/16 00:23:40 - mmengine - INFO - Epoch(train) [3][4500/10520] lr: 1.0000e-04 eta: 2 days, 16:09:08 time: 1.0242 data_time: 0.1899 memory: 56769 loss_visual: 0.1178 loss: 0.1178 2022/09/16 00:25:43 - mmengine - INFO - Epoch(train) [3][4600/10520] lr: 1.0000e-04 eta: 2 days, 16:06:54 time: 1.1506 data_time: 0.1129 memory: 56769 loss_visual: 0.1177 loss: 0.1177 2022/09/16 00:27:46 - mmengine - INFO - Epoch(train) [3][4700/10520] lr: 1.0000e-04 eta: 2 days, 16:04:29 time: 1.0587 data_time: 0.0410 memory: 56769 loss_visual: 0.1157 loss: 0.1157 2022/09/16 00:29:49 - mmengine - INFO - Epoch(train) [3][4800/10520] lr: 1.0000e-04 eta: 2 days, 16:02:11 time: 0.9001 data_time: 0.0732 memory: 56769 loss_visual: 0.1114 loss: 0.1114 2022/09/16 00:31:59 - mmengine - INFO - Epoch(train) [3][4900/10520] lr: 1.0000e-04 eta: 2 days, 16:00:42 time: 1.5864 data_time: 0.4175 memory: 56769 loss_visual: 0.1136 loss: 0.1136 2022/09/16 00:33:09 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 00:34:04 - mmengine - INFO - Epoch(train) [3][5000/10520] lr: 1.0000e-04 eta: 2 days, 15:58:38 time: 1.6274 data_time: 0.5141 memory: 56769 loss_visual: 0.1164 loss: 0.1164 2022/09/16 00:36:06 - mmengine - INFO - Epoch(train) [3][5100/10520] lr: 1.0000e-04 eta: 2 days, 15:56:11 time: 1.0981 data_time: 0.2387 memory: 56769 loss_visual: 0.1140 loss: 0.1140 2022/09/16 00:38:10 - mmengine - INFO - Epoch(train) [3][5200/10520] lr: 1.0000e-04 eta: 2 days, 15:53:59 time: 1.0202 data_time: 0.1559 memory: 56769 loss_visual: 0.1114 loss: 0.1114 2022/09/16 00:40:13 - mmengine - INFO - Epoch(train) [3][5300/10520] lr: 1.0000e-04 eta: 2 days, 15:51:44 time: 1.0666 data_time: 0.2091 memory: 56769 loss_visual: 0.1151 loss: 0.1151 2022/09/16 00:42:17 - mmengine - INFO - Epoch(train) [3][5400/10520] lr: 1.0000e-04 eta: 2 days, 15:49:33 time: 1.1284 data_time: 0.1073 memory: 56769 loss_visual: 0.1146 loss: 0.1146 2022/09/16 00:44:21 - mmengine - INFO - Epoch(train) [3][5500/10520] lr: 1.0000e-04 eta: 2 days, 15:47:18 time: 1.0869 data_time: 0.0482 memory: 56769 loss_visual: 0.1193 loss: 0.1193 2022/09/16 00:46:25 - mmengine - INFO - Epoch(train) [3][5600/10520] lr: 1.0000e-04 eta: 2 days, 15:45:07 time: 0.8939 data_time: 0.0398 memory: 56769 loss_visual: 0.1150 loss: 0.1150 2022/09/16 00:48:32 - mmengine - INFO - Epoch(train) [3][5700/10520] lr: 1.0000e-04 eta: 2 days, 15:43:23 time: 1.4920 data_time: 0.3820 memory: 56769 loss_visual: 0.1112 loss: 0.1112 2022/09/16 00:50:36 - mmengine - INFO - Epoch(train) [3][5800/10520] lr: 1.0000e-04 eta: 2 days, 15:41:10 time: 1.6104 data_time: 0.5006 memory: 56769 loss_visual: 0.1131 loss: 0.1131 2022/09/16 00:52:39 - mmengine - INFO - Epoch(train) [3][5900/10520] lr: 1.0000e-04 eta: 2 days, 15:38:48 time: 1.0520 data_time: 0.2239 memory: 56769 loss_visual: 0.1132 loss: 0.1132 2022/09/16 00:53:55 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 00:54:43 - mmengine - INFO - Epoch(train) [3][6000/10520] lr: 1.0000e-04 eta: 2 days, 15:36:37 time: 1.0592 data_time: 0.1949 memory: 56769 loss_visual: 0.1078 loss: 0.1078 2022/09/16 00:56:46 - mmengine - INFO - Epoch(train) [3][6100/10520] lr: 1.0000e-04 eta: 2 days, 15:34:19 time: 1.0559 data_time: 0.1876 memory: 56769 loss_visual: 0.1089 loss: 0.1089 2022/09/16 00:58:49 - mmengine - INFO - Epoch(train) [3][6200/10520] lr: 1.0000e-04 eta: 2 days, 15:32:07 time: 1.1288 data_time: 0.1052 memory: 56769 loss_visual: 0.1112 loss: 0.1112 2022/09/16 01:00:52 - mmengine - INFO - Epoch(train) [3][6300/10520] lr: 1.0000e-04 eta: 2 days, 15:29:48 time: 1.0898 data_time: 0.0717 memory: 56769 loss_visual: 0.1073 loss: 0.1073 2022/09/16 01:02:55 - mmengine - INFO - Epoch(train) [3][6400/10520] lr: 1.0000e-04 eta: 2 days, 15:27:29 time: 0.8827 data_time: 0.0396 memory: 56769 loss_visual: 0.1133 loss: 0.1133 2022/09/16 01:05:05 - mmengine - INFO - Epoch(train) [3][6500/10520] lr: 1.0000e-04 eta: 2 days, 15:25:56 time: 1.5119 data_time: 0.3181 memory: 56769 loss_visual: 0.1111 loss: 0.1111 2022/09/16 01:07:08 - mmengine - INFO - Epoch(train) [3][6600/10520] lr: 1.0000e-04 eta: 2 days, 15:23:40 time: 1.5867 data_time: 0.4485 memory: 56769 loss_visual: 0.1116 loss: 0.1116 2022/09/16 01:09:12 - mmengine - INFO - Epoch(train) [3][6700/10520] lr: 1.0000e-04 eta: 2 days, 15:21:29 time: 1.0901 data_time: 0.2439 memory: 56769 loss_visual: 0.1093 loss: 0.1093 2022/09/16 01:11:16 - mmengine - INFO - Epoch(train) [3][6800/10520] lr: 1.0000e-04 eta: 2 days, 15:19:22 time: 1.0490 data_time: 0.1730 memory: 56769 loss_visual: 0.1109 loss: 0.1109 2022/09/16 01:13:21 - mmengine - INFO - Epoch(train) [3][6900/10520] lr: 1.0000e-04 eta: 2 days, 15:17:16 time: 1.0688 data_time: 0.2034 memory: 56769 loss_visual: 0.1104 loss: 0.1104 2022/09/16 01:14:35 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 01:15:25 - mmengine - INFO - Epoch(train) [3][7000/10520] lr: 1.0000e-04 eta: 2 days, 15:15:02 time: 1.1286 data_time: 0.0780 memory: 56769 loss_visual: 0.1144 loss: 0.1144 2022/09/16 01:17:29 - mmengine - INFO - Epoch(train) [3][7100/10520] lr: 1.0000e-04 eta: 2 days, 15:12:53 time: 1.0933 data_time: 0.0696 memory: 56769 loss_visual: 0.1032 loss: 0.1032 2022/09/16 01:19:32 - mmengine - INFO - Epoch(train) [3][7200/10520] lr: 1.0000e-04 eta: 2 days, 15:10:38 time: 0.9126 data_time: 0.0739 memory: 56769 loss_visual: 0.1134 loss: 0.1134 2022/09/16 01:21:41 - mmengine - INFO - Epoch(train) [3][7300/10520] lr: 1.0000e-04 eta: 2 days, 15:08:56 time: 1.4952 data_time: 0.4080 memory: 56769 loss_visual: 0.1116 loss: 0.1116 2022/09/16 01:23:45 - mmengine - INFO - Epoch(train) [3][7400/10520] lr: 1.0000e-04 eta: 2 days, 15:06:48 time: 1.7050 data_time: 0.5090 memory: 56769 loss_visual: 0.1071 loss: 0.1071 2022/09/16 01:25:47 - mmengine - INFO - Epoch(train) [3][7500/10520] lr: 1.0000e-04 eta: 2 days, 15:04:27 time: 1.0834 data_time: 0.1701 memory: 56769 loss_visual: 0.1074 loss: 0.1074 2022/09/16 01:27:52 - mmengine - INFO - Epoch(train) [3][7600/10520] lr: 1.0000e-04 eta: 2 days, 15:02:20 time: 1.0588 data_time: 0.2026 memory: 56769 loss_visual: 0.1065 loss: 0.1065 2022/09/16 01:29:56 - mmengine - INFO - Epoch(train) [3][7700/10520] lr: 1.0000e-04 eta: 2 days, 15:00:09 time: 1.0680 data_time: 0.2153 memory: 56769 loss_visual: 0.1064 loss: 0.1064 2022/09/16 01:32:00 - mmengine - INFO - Epoch(train) [3][7800/10520] lr: 1.0000e-04 eta: 2 days, 14:57:59 time: 1.1368 data_time: 0.1172 memory: 56769 loss_visual: 0.1041 loss: 0.1041 2022/09/16 01:34:03 - mmengine - INFO - Epoch(train) [3][7900/10520] lr: 1.0000e-04 eta: 2 days, 14:55:44 time: 1.0551 data_time: 0.0568 memory: 56769 loss_visual: 0.1075 loss: 0.1075 2022/09/16 01:35:19 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 01:36:06 - mmengine - INFO - Epoch(train) [3][8000/10520] lr: 1.0000e-04 eta: 2 days, 14:53:28 time: 0.9386 data_time: 0.0808 memory: 56769 loss_visual: 0.1047 loss: 0.1047 2022/09/16 01:38:14 - mmengine - INFO - Epoch(train) [3][8100/10520] lr: 1.0000e-04 eta: 2 days, 14:51:45 time: 1.4945 data_time: 0.4007 memory: 56769 loss_visual: 0.1079 loss: 0.1079 2022/09/16 01:40:19 - mmengine - INFO - Epoch(train) [3][8200/10520] lr: 1.0000e-04 eta: 2 days, 14:49:38 time: 1.6750 data_time: 0.5647 memory: 56769 loss_visual: 0.1047 loss: 0.1047 2022/09/16 01:42:22 - mmengine - INFO - Epoch(train) [3][8300/10520] lr: 1.0000e-04 eta: 2 days, 14:47:21 time: 1.1138 data_time: 0.2308 memory: 56769 loss_visual: 0.1101 loss: 0.1101 2022/09/16 01:44:24 - mmengine - INFO - Epoch(train) [3][8400/10520] lr: 1.0000e-04 eta: 2 days, 14:45:00 time: 1.0191 data_time: 0.1608 memory: 56769 loss_visual: 0.1061 loss: 0.1061 2022/09/16 01:46:28 - mmengine - INFO - Epoch(train) [3][8500/10520] lr: 1.0000e-04 eta: 2 days, 14:42:51 time: 1.0878 data_time: 0.2143 memory: 56769 loss_visual: 0.1061 loss: 0.1061 2022/09/16 01:48:32 - mmengine - INFO - Epoch(train) [3][8600/10520] lr: 1.0000e-04 eta: 2 days, 14:40:42 time: 1.1470 data_time: 0.1074 memory: 56769 loss_visual: 0.1013 loss: 0.1013 2022/09/16 01:50:37 - mmengine - INFO - Epoch(train) [3][8700/10520] lr: 1.0000e-04 eta: 2 days, 14:38:33 time: 1.0746 data_time: 0.0396 memory: 56769 loss_visual: 0.1043 loss: 0.1043 2022/09/16 01:52:39 - mmengine - INFO - Epoch(train) [3][8800/10520] lr: 1.0000e-04 eta: 2 days, 14:36:13 time: 0.9042 data_time: 0.0416 memory: 56769 loss_visual: 0.1094 loss: 0.1094 2022/09/16 01:54:48 - mmengine - INFO - Epoch(train) [3][8900/10520] lr: 1.0000e-04 eta: 2 days, 14:34:35 time: 1.5268 data_time: 0.4068 memory: 56769 loss_visual: 0.1091 loss: 0.1091 2022/09/16 01:55:58 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 01:56:53 - mmengine - INFO - Epoch(train) [3][9000/10520] lr: 1.0000e-04 eta: 2 days, 14:32:31 time: 1.6434 data_time: 0.5075 memory: 56769 loss_visual: 0.1035 loss: 0.1035 2022/09/16 01:58:56 - mmengine - INFO - Epoch(train) [3][9100/10520] lr: 1.0000e-04 eta: 2 days, 14:30:15 time: 1.0426 data_time: 0.2198 memory: 56769 loss_visual: 0.1072 loss: 0.1072 2022/09/16 02:01:02 - mmengine - INFO - Epoch(train) [3][9200/10520] lr: 1.0000e-04 eta: 2 days, 14:28:14 time: 1.0534 data_time: 0.2025 memory: 56769 loss_visual: 0.1036 loss: 0.1036 2022/09/16 02:03:05 - mmengine - INFO - Epoch(train) [3][9300/10520] lr: 1.0000e-04 eta: 2 days, 14:25:59 time: 1.0643 data_time: 0.1869 memory: 56769 loss_visual: 0.1066 loss: 0.1066 2022/09/16 02:05:11 - mmengine - INFO - Epoch(train) [3][9400/10520] lr: 1.0000e-04 eta: 2 days, 14:24:01 time: 1.1683 data_time: 0.1201 memory: 56769 loss_visual: 0.1074 loss: 0.1074 2022/09/16 02:07:15 - mmengine - INFO - Epoch(train) [3][9500/10520] lr: 1.0000e-04 eta: 2 days, 14:21:52 time: 1.0874 data_time: 0.0749 memory: 56769 loss_visual: 0.1057 loss: 0.1057 2022/09/16 02:09:16 - mmengine - INFO - Epoch(train) [3][9600/10520] lr: 1.0000e-04 eta: 2 days, 14:19:28 time: 0.9131 data_time: 0.0402 memory: 56769 loss_visual: 0.1053 loss: 0.1053 2022/09/16 02:11:26 - mmengine - INFO - Epoch(train) [3][9700/10520] lr: 1.0000e-04 eta: 2 days, 14:17:50 time: 1.5689 data_time: 0.3430 memory: 56769 loss_visual: 0.1046 loss: 0.1046 2022/09/16 02:13:32 - mmengine - INFO - Epoch(train) [3][9800/10520] lr: 1.0000e-04 eta: 2 days, 14:15:55 time: 1.6217 data_time: 0.4557 memory: 56769 loss_visual: 0.1045 loss: 0.1045 2022/09/16 02:15:35 - mmengine - INFO - Epoch(train) [3][9900/10520] lr: 1.0000e-04 eta: 2 days, 14:13:36 time: 1.0531 data_time: 0.2361 memory: 56769 loss_visual: 0.1063 loss: 0.1063 2022/09/16 02:16:52 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 02:17:40 - mmengine - INFO - Epoch(train) [3][10000/10520] lr: 1.0000e-04 eta: 2 days, 14:11:30 time: 1.0229 data_time: 0.1624 memory: 56769 loss_visual: 0.1035 loss: 0.1035 2022/09/16 02:19:43 - mmengine - INFO - Epoch(train) [3][10100/10520] lr: 1.0000e-04 eta: 2 days, 14:09:16 time: 1.0497 data_time: 0.1951 memory: 56769 loss_visual: 0.1052 loss: 0.1052 2022/09/16 02:21:46 - mmengine - INFO - Epoch(train) [3][10200/10520] lr: 1.0000e-04 eta: 2 days, 14:07:04 time: 1.0910 data_time: 0.0701 memory: 56769 loss_visual: 0.1102 loss: 0.1102 2022/09/16 02:23:49 - mmengine - INFO - Epoch(train) [3][10300/10520] lr: 1.0000e-04 eta: 2 days, 14:04:50 time: 1.1129 data_time: 0.0758 memory: 56769 loss_visual: 0.1056 loss: 0.1056 2022/09/16 02:25:52 - mmengine - INFO - Epoch(train) [3][10400/10520] lr: 1.0000e-04 eta: 2 days, 14:02:32 time: 0.9214 data_time: 0.0915 memory: 56769 loss_visual: 0.1041 loss: 0.1041 2022/09/16 02:27:56 - mmengine - INFO - Epoch(train) [3][10500/10520] lr: 1.0000e-04 eta: 2 days, 14:00:21 time: 1.2247 data_time: 0.2422 memory: 56769 loss_visual: 0.1000 loss: 0.1000 2022/09/16 02:28:14 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 02:28:14 - mmengine - INFO - Saving checkpoint at 3 epochs 2022/09/16 02:28:38 - mmengine - INFO - Epoch(val) [3][100/3836] eta: 0:07:08 time: 0.1148 data_time: 0.0005 memory: 56769 2022/09/16 02:28:44 - mmengine - INFO - Epoch(val) [3][200/3836] eta: 0:00:40 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/16 02:28:45 - mmengine - INFO - Epoch(val) [3][300/3836] eta: 0:00:41 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/16 02:28:47 - mmengine - INFO - Epoch(val) [3][400/3836] eta: 0:00:42 time: 0.0123 data_time: 0.0005 memory: 480 2022/09/16 02:28:48 - mmengine - INFO - Epoch(val) [3][500/3836] eta: 0:00:39 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 02:28:49 - mmengine - INFO - Epoch(val) [3][600/3836] eta: 0:00:37 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 02:28:50 - mmengine - INFO - Epoch(val) [3][700/3836] eta: 0:00:35 time: 0.0114 data_time: 0.0004 memory: 480 2022/09/16 02:28:51 - mmengine - INFO - Epoch(val) [3][800/3836] eta: 0:00:35 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 02:28:52 - mmengine - INFO - Epoch(val) [3][900/3836] eta: 0:00:32 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/16 02:28:54 - mmengine - INFO - Epoch(val) [3][1000/3836] eta: 0:00:33 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 02:28:55 - mmengine - INFO - Epoch(val) [3][1100/3836] eta: 0:00:31 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/16 02:28:56 - mmengine - INFO - Epoch(val) [3][1200/3836] eta: 0:00:29 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/16 02:28:57 - mmengine - INFO - Epoch(val) [3][1300/3836] eta: 0:00:32 time: 0.0128 data_time: 0.0011 memory: 480 2022/09/16 02:28:58 - mmengine - INFO - Epoch(val) [3][1400/3836] eta: 0:00:28 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 02:28:59 - mmengine - INFO - Epoch(val) [3][1500/3836] eta: 0:00:27 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 02:29:01 - mmengine - INFO - Epoch(val) [3][1600/3836] eta: 0:00:26 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/16 02:29:02 - mmengine - INFO - Epoch(val) [3][1700/3836] eta: 0:00:23 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/16 02:29:03 - mmengine - INFO - Epoch(val) [3][1800/3836] eta: 0:00:23 time: 0.0115 data_time: 0.0004 memory: 480 2022/09/16 02:29:04 - mmengine - INFO - Epoch(val) [3][1900/3836] eta: 0:00:22 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 02:29:05 - mmengine - INFO - Epoch(val) [3][2000/3836] eta: 0:00:21 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 02:29:07 - mmengine - INFO - Epoch(val) [3][2100/3836] eta: 0:00:20 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 02:29:08 - mmengine - INFO - Epoch(val) [3][2200/3836] eta: 0:00:19 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 02:29:09 - mmengine - INFO - Epoch(val) [3][2300/3836] eta: 0:00:17 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/16 02:29:10 - mmengine - INFO - Epoch(val) [3][2400/3836] eta: 0:00:16 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/16 02:29:11 - mmengine - INFO - Epoch(val) [3][2500/3836] eta: 0:00:15 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 02:29:12 - mmengine - INFO - Epoch(val) [3][2600/3836] eta: 0:00:14 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 02:29:14 - mmengine - INFO - Epoch(val) [3][2700/3836] eta: 0:00:13 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 02:29:15 - mmengine - INFO - Epoch(val) [3][2800/3836] eta: 0:00:12 time: 0.0120 data_time: 0.0012 memory: 480 2022/09/16 02:29:16 - mmengine - INFO - Epoch(val) [3][2900/3836] eta: 0:00:10 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 02:29:17 - mmengine - INFO - Epoch(val) [3][3000/3836] eta: 0:00:09 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/16 02:29:18 - mmengine - INFO - Epoch(val) [3][3100/3836] eta: 0:00:08 time: 0.0109 data_time: 0.0004 memory: 480 2022/09/16 02:29:19 - mmengine - INFO - Epoch(val) [3][3200/3836] eta: 0:00:06 time: 0.0110 data_time: 0.0004 memory: 480 2022/09/16 02:29:20 - mmengine - INFO - Epoch(val) [3][3300/3836] eta: 0:00:05 time: 0.0109 data_time: 0.0004 memory: 480 2022/09/16 02:29:21 - mmengine - INFO - Epoch(val) [3][3400/3836] eta: 0:00:04 time: 0.0110 data_time: 0.0005 memory: 480 2022/09/16 02:29:23 - mmengine - INFO - Epoch(val) [3][3500/3836] eta: 0:00:03 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/16 02:29:24 - mmengine - INFO - Epoch(val) [3][3600/3836] eta: 0:00:02 time: 0.0109 data_time: 0.0004 memory: 480 2022/09/16 02:29:25 - mmengine - INFO - Epoch(val) [3][3700/3836] eta: 0:00:01 time: 0.0108 data_time: 0.0004 memory: 480 2022/09/16 02:29:26 - mmengine - INFO - Epoch(val) [3][3800/3836] eta: 0:00:00 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/16 02:29:26 - mmengine - INFO - Epoch(val) [3][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.7535 IIIT5K/recog/word_acc_ignore_case_symbol: 0.8990 SVT/recog/word_acc_ignore_case_symbol: 0.8315 SVTP/recog/word_acc_ignore_case_symbol: 0.7225 IC13/recog/word_acc_ignore_case_symbol: 0.8749 IC15/recog/word_acc_ignore_case_symbol: 0.6895 2022/09/16 02:31:54 - mmengine - INFO - Epoch(train) [4][100/10520] lr: 1.0000e-04 eta: 2 days, 13:59:22 time: 1.7877 data_time: 0.3414 memory: 56769 loss_visual: 0.1082 loss: 0.1082 2022/09/16 02:34:01 - mmengine - INFO - Epoch(train) [4][200/10520] lr: 1.0000e-04 eta: 2 days, 13:57:33 time: 1.8885 data_time: 0.5673 memory: 56769 loss_visual: 0.1021 loss: 0.1021 2022/09/16 02:36:08 - mmengine - INFO - Epoch(train) [4][300/10520] lr: 1.0000e-04 eta: 2 days, 13:55:36 time: 1.0704 data_time: 0.1846 memory: 56769 loss_visual: 0.0977 loss: 0.0977 2022/09/16 02:38:16 - mmengine - INFO - Epoch(train) [4][400/10520] lr: 1.0000e-04 eta: 2 days, 13:53:52 time: 1.0183 data_time: 0.1276 memory: 56769 loss_visual: 0.0954 loss: 0.0954 2022/09/16 02:39:05 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 02:40:25 - mmengine - INFO - Epoch(train) [4][500/10520] lr: 1.0000e-04 eta: 2 days, 13:52:06 time: 1.0767 data_time: 0.2540 memory: 56769 loss_visual: 0.1016 loss: 0.1016 2022/09/16 02:42:31 - mmengine - INFO - Epoch(train) [4][600/10520] lr: 1.0000e-04 eta: 2 days, 13:50:07 time: 1.0049 data_time: 0.1593 memory: 56769 loss_visual: 0.1033 loss: 0.1033 2022/09/16 02:44:40 - mmengine - INFO - Epoch(train) [4][700/10520] lr: 1.0000e-04 eta: 2 days, 13:48:30 time: 0.9386 data_time: 0.0066 memory: 56769 loss_visual: 0.1053 loss: 0.1053 2022/09/16 02:46:47 - mmengine - INFO - Epoch(train) [4][800/10520] lr: 1.0000e-04 eta: 2 days, 13:46:36 time: 0.9996 data_time: 0.0065 memory: 56769 loss_visual: 0.1001 loss: 0.1001 2022/09/16 02:49:02 - mmengine - INFO - Epoch(train) [4][900/10520] lr: 1.0000e-04 eta: 2 days, 13:45:24 time: 1.7882 data_time: 0.3554 memory: 56769 loss_visual: 0.1036 loss: 0.1036 2022/09/16 02:51:11 - mmengine - INFO - Epoch(train) [4][1000/10520] lr: 1.0000e-04 eta: 2 days, 13:43:39 time: 1.9097 data_time: 0.5126 memory: 56769 loss_visual: 0.1010 loss: 0.1010 2022/09/16 02:53:18 - mmengine - INFO - Epoch(train) [4][1100/10520] lr: 1.0000e-04 eta: 2 days, 13:41:47 time: 1.0605 data_time: 0.2025 memory: 56769 loss_visual: 0.1013 loss: 0.1013 2022/09/16 02:55:26 - mmengine - INFO - Epoch(train) [4][1200/10520] lr: 1.0000e-04 eta: 2 days, 13:39:59 time: 1.0010 data_time: 0.1100 memory: 56769 loss_visual: 0.1028 loss: 0.1028 2022/09/16 02:57:34 - mmengine - INFO - Epoch(train) [4][1300/10520] lr: 1.0000e-04 eta: 2 days, 13:38:10 time: 1.0412 data_time: 0.2209 memory: 56769 loss_visual: 0.1057 loss: 0.1057 2022/09/16 02:59:41 - mmengine - INFO - Epoch(train) [4][1400/10520] lr: 1.0000e-04 eta: 2 days, 13:36:16 time: 1.0094 data_time: 0.1907 memory: 56769 loss_visual: 0.1046 loss: 0.1046 2022/09/16 03:00:31 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 03:01:49 - mmengine - INFO - Epoch(train) [4][1500/10520] lr: 1.0000e-04 eta: 2 days, 13:34:26 time: 0.9108 data_time: 0.0066 memory: 56769 loss_visual: 0.1032 loss: 0.1032 2022/09/16 03:03:57 - mmengine - INFO - Epoch(train) [4][1600/10520] lr: 1.0000e-04 eta: 2 days, 13:32:36 time: 1.0674 data_time: 0.0064 memory: 56769 loss_visual: 0.1037 loss: 0.1037 2022/09/16 03:06:12 - mmengine - INFO - Epoch(train) [4][1700/10520] lr: 1.0000e-04 eta: 2 days, 13:31:29 time: 1.7980 data_time: 0.4217 memory: 56769 loss_visual: 0.0981 loss: 0.0981 2022/09/16 03:08:19 - mmengine - INFO - Epoch(train) [4][1800/10520] lr: 1.0000e-04 eta: 2 days, 13:29:34 time: 1.8295 data_time: 0.5441 memory: 56769 loss_visual: 0.0988 loss: 0.0988 2022/09/16 03:10:27 - mmengine - INFO - Epoch(train) [4][1900/10520] lr: 1.0000e-04 eta: 2 days, 13:27:44 time: 1.1145 data_time: 0.2174 memory: 56769 loss_visual: 0.1025 loss: 0.1025 2022/09/16 03:12:35 - mmengine - INFO - Epoch(train) [4][2000/10520] lr: 1.0000e-04 eta: 2 days, 13:25:54 time: 0.9830 data_time: 0.1239 memory: 56769 loss_visual: 0.0980 loss: 0.0980 2022/09/16 03:14:43 - mmengine - INFO - Epoch(train) [4][2100/10520] lr: 1.0000e-04 eta: 2 days, 13:24:01 time: 1.0565 data_time: 0.2185 memory: 56769 loss_visual: 0.0990 loss: 0.0990 2022/09/16 03:16:49 - mmengine - INFO - Epoch(train) [4][2200/10520] lr: 1.0000e-04 eta: 2 days, 13:22:03 time: 1.0145 data_time: 0.1635 memory: 56769 loss_visual: 0.0989 loss: 0.0989 2022/09/16 03:18:57 - mmengine - INFO - Epoch(train) [4][2300/10520] lr: 1.0000e-04 eta: 2 days, 13:20:11 time: 0.9478 data_time: 0.0064 memory: 56769 loss_visual: 0.0994 loss: 0.0994 2022/09/16 03:21:04 - mmengine - INFO - Epoch(train) [4][2400/10520] lr: 1.0000e-04 eta: 2 days, 13:18:18 time: 0.9996 data_time: 0.0068 memory: 56769 loss_visual: 0.1012 loss: 0.1012 2022/09/16 03:22:02 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 03:23:20 - mmengine - INFO - Epoch(train) [4][2500/10520] lr: 1.0000e-04 eta: 2 days, 13:17:10 time: 1.8659 data_time: 0.4244 memory: 56769 loss_visual: 0.0956 loss: 0.0956 2022/09/16 03:25:29 - mmengine - INFO - Epoch(train) [4][2600/10520] lr: 1.0000e-04 eta: 2 days, 13:15:25 time: 1.8632 data_time: 0.5260 memory: 56769 loss_visual: 0.0999 loss: 0.0999 2022/09/16 03:27:37 - mmengine - INFO - Epoch(train) [4][2700/10520] lr: 1.0000e-04 eta: 2 days, 13:13:32 time: 1.0567 data_time: 0.1988 memory: 56769 loss_visual: 0.0993 loss: 0.0993 2022/09/16 03:29:46 - mmengine - INFO - Epoch(train) [4][2800/10520] lr: 1.0000e-04 eta: 2 days, 13:11:47 time: 0.9816 data_time: 0.1245 memory: 56769 loss_visual: 0.0943 loss: 0.0943 2022/09/16 03:31:53 - mmengine - INFO - Epoch(train) [4][2900/10520] lr: 1.0000e-04 eta: 2 days, 13:09:52 time: 1.0454 data_time: 0.1816 memory: 56769 loss_visual: 0.0993 loss: 0.0993 2022/09/16 03:34:00 - mmengine - INFO - Epoch(train) [4][3000/10520] lr: 1.0000e-04 eta: 2 days, 13:07:54 time: 1.0019 data_time: 0.1501 memory: 56769 loss_visual: 0.1036 loss: 0.1036 2022/09/16 03:36:07 - mmengine - INFO - Epoch(train) [4][3100/10520] lr: 1.0000e-04 eta: 2 days, 13:06:02 time: 0.9420 data_time: 0.0064 memory: 56769 loss_visual: 0.0993 loss: 0.0993 2022/09/16 03:38:15 - mmengine - INFO - Epoch(train) [4][3200/10520] lr: 1.0000e-04 eta: 2 days, 13:04:10 time: 0.9964 data_time: 0.0066 memory: 56769 loss_visual: 0.1000 loss: 0.1000 2022/09/16 03:40:33 - mmengine - INFO - Epoch(train) [4][3300/10520] lr: 1.0000e-04 eta: 2 days, 13:03:11 time: 1.8439 data_time: 0.4138 memory: 56769 loss_visual: 0.1004 loss: 0.1004 2022/09/16 03:42:42 - mmengine - INFO - Epoch(train) [4][3400/10520] lr: 1.0000e-04 eta: 2 days, 13:01:24 time: 1.8509 data_time: 0.5099 memory: 56769 loss_visual: 0.0970 loss: 0.0970 2022/09/16 03:43:32 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 03:44:50 - mmengine - INFO - Epoch(train) [4][3500/10520] lr: 1.0000e-04 eta: 2 days, 12:59:32 time: 1.0952 data_time: 0.2079 memory: 56769 loss_visual: 0.0966 loss: 0.0966 2022/09/16 03:46:58 - mmengine - INFO - Epoch(train) [4][3600/10520] lr: 1.0000e-04 eta: 2 days, 12:57:38 time: 0.9995 data_time: 0.1398 memory: 56769 loss_visual: 0.0925 loss: 0.0925 2022/09/16 03:49:04 - mmengine - INFO - Epoch(train) [4][3700/10520] lr: 1.0000e-04 eta: 2 days, 12:55:39 time: 1.0414 data_time: 0.2220 memory: 56769 loss_visual: 0.0988 loss: 0.0988 2022/09/16 03:51:11 - mmengine - INFO - Epoch(train) [4][3800/10520] lr: 1.0000e-04 eta: 2 days, 12:53:41 time: 0.9764 data_time: 0.1510 memory: 56769 loss_visual: 0.0998 loss: 0.0998 2022/09/16 03:53:19 - mmengine - INFO - Epoch(train) [4][3900/10520] lr: 1.0000e-04 eta: 2 days, 12:51:49 time: 0.9111 data_time: 0.0073 memory: 56769 loss_visual: 0.0988 loss: 0.0988 2022/09/16 03:55:25 - mmengine - INFO - Epoch(train) [4][4000/10520] lr: 1.0000e-04 eta: 2 days, 12:49:50 time: 1.0205 data_time: 0.0068 memory: 56769 loss_visual: 0.0952 loss: 0.0952 2022/09/16 03:57:39 - mmengine - INFO - Epoch(train) [4][4100/10520] lr: 1.0000e-04 eta: 2 days, 12:48:27 time: 1.7867 data_time: 0.4057 memory: 56769 loss_visual: 0.0968 loss: 0.0968 2022/09/16 03:59:48 - mmengine - INFO - Epoch(train) [4][4200/10520] lr: 1.0000e-04 eta: 2 days, 12:46:38 time: 1.8801 data_time: 0.5229 memory: 56769 loss_visual: 0.0973 loss: 0.0973 2022/09/16 04:01:55 - mmengine - INFO - Epoch(train) [4][4300/10520] lr: 1.0000e-04 eta: 2 days, 12:44:41 time: 1.0928 data_time: 0.2359 memory: 56769 loss_visual: 0.1023 loss: 0.1023 2022/09/16 04:04:03 - mmengine - INFO - Epoch(train) [4][4400/10520] lr: 1.0000e-04 eta: 2 days, 12:42:50 time: 1.0122 data_time: 0.1288 memory: 56769 loss_visual: 0.0989 loss: 0.0989 2022/09/16 04:04:52 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 04:06:10 - mmengine - INFO - Epoch(train) [4][4500/10520] lr: 1.0000e-04 eta: 2 days, 12:40:54 time: 1.0472 data_time: 0.2281 memory: 56769 loss_visual: 0.0987 loss: 0.0987 2022/09/16 04:08:17 - mmengine - INFO - Epoch(train) [4][4600/10520] lr: 1.0000e-04 eta: 2 days, 12:38:55 time: 1.0186 data_time: 0.1711 memory: 56769 loss_visual: 0.0961 loss: 0.0961 2022/09/16 04:10:25 - mmengine - INFO - Epoch(train) [4][4700/10520] lr: 1.0000e-04 eta: 2 days, 12:37:02 time: 0.9225 data_time: 0.0071 memory: 56769 loss_visual: 0.0980 loss: 0.0980 2022/09/16 04:12:31 - mmengine - INFO - Epoch(train) [4][4800/10520] lr: 1.0000e-04 eta: 2 days, 12:35:03 time: 1.0025 data_time: 0.0068 memory: 56769 loss_visual: 0.0955 loss: 0.0955 2022/09/16 04:14:47 - mmengine - INFO - Epoch(train) [4][4900/10520] lr: 1.0000e-04 eta: 2 days, 12:33:46 time: 1.7812 data_time: 0.3586 memory: 56769 loss_visual: 0.0899 loss: 0.0899 2022/09/16 04:16:56 - mmengine - INFO - Epoch(train) [4][5000/10520] lr: 1.0000e-04 eta: 2 days, 12:31:57 time: 1.8831 data_time: 0.5293 memory: 56769 loss_visual: 0.1035 loss: 0.1035 2022/09/16 04:19:02 - mmengine - INFO - Epoch(train) [4][5100/10520] lr: 1.0000e-04 eta: 2 days, 12:29:58 time: 1.0627 data_time: 0.1914 memory: 56769 loss_visual: 0.0931 loss: 0.0931 2022/09/16 04:21:10 - mmengine - INFO - Epoch(train) [4][5200/10520] lr: 1.0000e-04 eta: 2 days, 12:28:04 time: 1.0117 data_time: 0.1235 memory: 56769 loss_visual: 0.0983 loss: 0.0983 2022/09/16 04:23:18 - mmengine - INFO - Epoch(train) [4][5300/10520] lr: 1.0000e-04 eta: 2 days, 12:26:12 time: 1.0512 data_time: 0.2303 memory: 56769 loss_visual: 0.0983 loss: 0.0983 2022/09/16 04:25:25 - mmengine - INFO - Epoch(train) [4][5400/10520] lr: 1.0000e-04 eta: 2 days, 12:24:10 time: 1.0212 data_time: 0.1870 memory: 56769 loss_visual: 0.1018 loss: 0.1018 2022/09/16 04:26:14 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 04:27:31 - mmengine - INFO - Epoch(train) [4][5500/10520] lr: 1.0000e-04 eta: 2 days, 12:22:11 time: 0.9157 data_time: 0.0067 memory: 56769 loss_visual: 0.0949 loss: 0.0949 2022/09/16 04:29:38 - mmengine - INFO - Epoch(train) [4][5600/10520] lr: 1.0000e-04 eta: 2 days, 12:20:13 time: 1.0295 data_time: 0.0070 memory: 56769 loss_visual: 0.0959 loss: 0.0959 2022/09/16 04:31:53 - mmengine - INFO - Epoch(train) [4][5700/10520] lr: 1.0000e-04 eta: 2 days, 12:18:52 time: 1.8441 data_time: 0.3963 memory: 56769 loss_visual: 0.0949 loss: 0.0949 2022/09/16 04:34:02 - mmengine - INFO - Epoch(train) [4][5800/10520] lr: 1.0000e-04 eta: 2 days, 12:17:01 time: 1.8975 data_time: 0.5252 memory: 56769 loss_visual: 0.0933 loss: 0.0933 2022/09/16 04:36:08 - mmengine - INFO - Epoch(train) [4][5900/10520] lr: 1.0000e-04 eta: 2 days, 12:15:01 time: 1.0794 data_time: 0.1971 memory: 56769 loss_visual: 0.0931 loss: 0.0931 2022/09/16 04:38:15 - mmengine - INFO - Epoch(train) [4][6000/10520] lr: 1.0000e-04 eta: 2 days, 12:13:03 time: 0.9872 data_time: 0.1210 memory: 56769 loss_visual: 0.0976 loss: 0.0976 2022/09/16 04:40:23 - mmengine - INFO - Epoch(train) [4][6100/10520] lr: 1.0000e-04 eta: 2 days, 12:11:05 time: 1.0438 data_time: 0.2179 memory: 56769 loss_visual: 0.0971 loss: 0.0971 2022/09/16 04:42:29 - mmengine - INFO - Epoch(train) [4][6200/10520] lr: 1.0000e-04 eta: 2 days, 12:09:06 time: 1.0175 data_time: 0.1977 memory: 56769 loss_visual: 0.0946 loss: 0.0946 2022/09/16 04:44:37 - mmengine - INFO - Epoch(train) [4][6300/10520] lr: 1.0000e-04 eta: 2 days, 12:07:09 time: 0.9198 data_time: 0.0062 memory: 56769 loss_visual: 0.0911 loss: 0.0911 2022/09/16 04:46:45 - mmengine - INFO - Epoch(train) [4][6400/10520] lr: 1.0000e-04 eta: 2 days, 12:05:16 time: 1.0130 data_time: 0.0068 memory: 56769 loss_visual: 0.0967 loss: 0.0967 2022/09/16 04:47:43 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 04:49:00 - mmengine - INFO - Epoch(train) [4][6500/10520] lr: 1.0000e-04 eta: 2 days, 12:03:55 time: 1.8107 data_time: 0.4041 memory: 56769 loss_visual: 0.0973 loss: 0.0973 2022/09/16 04:51:09 - mmengine - INFO - Epoch(train) [4][6600/10520] lr: 1.0000e-04 eta: 2 days, 12:02:05 time: 1.8464 data_time: 0.4867 memory: 56769 loss_visual: 0.0974 loss: 0.0974 2022/09/16 04:53:15 - mmengine - INFO - Epoch(train) [4][6700/10520] lr: 1.0000e-04 eta: 2 days, 12:00:02 time: 1.0532 data_time: 0.1785 memory: 56769 loss_visual: 0.0988 loss: 0.0988 2022/09/16 04:55:24 - mmengine - INFO - Epoch(train) [4][6800/10520] lr: 1.0000e-04 eta: 2 days, 11:58:13 time: 0.9904 data_time: 0.1133 memory: 56769 loss_visual: 0.0989 loss: 0.0989 2022/09/16 04:57:32 - mmengine - INFO - Epoch(train) [4][6900/10520] lr: 1.0000e-04 eta: 2 days, 11:56:19 time: 1.0580 data_time: 0.2223 memory: 56769 loss_visual: 0.0948 loss: 0.0948 2022/09/16 04:59:40 - mmengine - INFO - Epoch(train) [4][7000/10520] lr: 1.0000e-04 eta: 2 days, 11:54:22 time: 1.0168 data_time: 0.1943 memory: 56769 loss_visual: 0.0977 loss: 0.0977 2022/09/16 05:01:48 - mmengine - INFO - Epoch(train) [4][7100/10520] lr: 1.0000e-04 eta: 2 days, 11:52:30 time: 0.9214 data_time: 0.0118 memory: 56769 loss_visual: 0.0954 loss: 0.0954 2022/09/16 05:03:56 - mmengine - INFO - Epoch(train) [4][7200/10520] lr: 1.0000e-04 eta: 2 days, 11:50:36 time: 1.0109 data_time: 0.0065 memory: 56769 loss_visual: 0.0975 loss: 0.0975 2022/09/16 05:06:13 - mmengine - INFO - Epoch(train) [4][7300/10520] lr: 1.0000e-04 eta: 2 days, 11:49:17 time: 1.8377 data_time: 0.3881 memory: 56769 loss_visual: 0.0951 loss: 0.0951 2022/09/16 05:08:21 - mmengine - INFO - Epoch(train) [4][7400/10520] lr: 1.0000e-04 eta: 2 days, 11:47:22 time: 1.9341 data_time: 0.4962 memory: 56769 loss_visual: 0.0974 loss: 0.0974 2022/09/16 05:09:09 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 05:10:27 - mmengine - INFO - Epoch(train) [4][7500/10520] lr: 1.0000e-04 eta: 2 days, 11:45:20 time: 1.1032 data_time: 0.1769 memory: 56769 loss_visual: 0.0924 loss: 0.0924 2022/09/16 05:12:36 - mmengine - INFO - Epoch(train) [4][7600/10520] lr: 1.0000e-04 eta: 2 days, 11:43:32 time: 1.0010 data_time: 0.1139 memory: 56769 loss_visual: 0.0962 loss: 0.0962 2022/09/16 05:14:45 - mmengine - INFO - Epoch(train) [4][7700/10520] lr: 1.0000e-04 eta: 2 days, 11:41:40 time: 1.0523 data_time: 0.2326 memory: 56769 loss_visual: 0.0906 loss: 0.0906 2022/09/16 05:16:51 - mmengine - INFO - Epoch(train) [4][7800/10520] lr: 1.0000e-04 eta: 2 days, 11:39:35 time: 0.9955 data_time: 0.1491 memory: 56769 loss_visual: 0.0945 loss: 0.0945 2022/09/16 05:18:58 - mmengine - INFO - Epoch(train) [4][7900/10520] lr: 1.0000e-04 eta: 2 days, 11:37:36 time: 0.9195 data_time: 0.0068 memory: 56769 loss_visual: 0.0928 loss: 0.0928 2022/09/16 05:21:06 - mmengine - INFO - Epoch(train) [4][8000/10520] lr: 1.0000e-04 eta: 2 days, 11:35:43 time: 1.0055 data_time: 0.0069 memory: 56769 loss_visual: 0.0967 loss: 0.0967 2022/09/16 05:23:21 - mmengine - INFO - Epoch(train) [4][8100/10520] lr: 1.0000e-04 eta: 2 days, 11:34:16 time: 1.8003 data_time: 0.3735 memory: 56769 loss_visual: 0.0931 loss: 0.0931 2022/09/16 05:25:28 - mmengine - INFO - Epoch(train) [4][8200/10520] lr: 1.0000e-04 eta: 2 days, 11:32:18 time: 1.8484 data_time: 0.5152 memory: 56769 loss_visual: 0.0939 loss: 0.0939 2022/09/16 05:27:35 - mmengine - INFO - Epoch(train) [4][8300/10520] lr: 1.0000e-04 eta: 2 days, 11:30:18 time: 1.0589 data_time: 0.1789 memory: 56769 loss_visual: 0.0964 loss: 0.0964 2022/09/16 05:29:44 - mmengine - INFO - Epoch(train) [4][8400/10520] lr: 1.0000e-04 eta: 2 days, 11:28:24 time: 1.0147 data_time: 0.1390 memory: 56769 loss_visual: 0.0997 loss: 0.0997 2022/09/16 05:30:32 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 05:31:51 - mmengine - INFO - Epoch(train) [4][8500/10520] lr: 1.0000e-04 eta: 2 days, 11:26:26 time: 1.0561 data_time: 0.2362 memory: 56769 loss_visual: 0.0925 loss: 0.0925 2022/09/16 05:33:57 - mmengine - INFO - Epoch(train) [4][8600/10520] lr: 1.0000e-04 eta: 2 days, 11:24:23 time: 0.9971 data_time: 0.1764 memory: 56769 loss_visual: 0.0911 loss: 0.0911 2022/09/16 05:36:05 - mmengine - INFO - Epoch(train) [4][8700/10520] lr: 1.0000e-04 eta: 2 days, 11:22:24 time: 0.9316 data_time: 0.0075 memory: 56769 loss_visual: 0.0916 loss: 0.0916 2022/09/16 05:38:12 - mmengine - INFO - Epoch(train) [4][8800/10520] lr: 1.0000e-04 eta: 2 days, 11:20:27 time: 1.0120 data_time: 0.0064 memory: 56769 loss_visual: 0.0952 loss: 0.0952 2022/09/16 05:40:28 - mmengine - INFO - Epoch(train) [4][8900/10520] lr: 1.0000e-04 eta: 2 days, 11:19:02 time: 1.8560 data_time: 0.3789 memory: 56769 loss_visual: 0.0912 loss: 0.0912 2022/09/16 05:42:35 - mmengine - INFO - Epoch(train) [4][9000/10520] lr: 1.0000e-04 eta: 2 days, 11:17:04 time: 1.8710 data_time: 0.5284 memory: 56769 loss_visual: 0.0911 loss: 0.0911 2022/09/16 05:44:42 - mmengine - INFO - Epoch(train) [4][9100/10520] lr: 1.0000e-04 eta: 2 days, 11:15:03 time: 1.0688 data_time: 0.1715 memory: 56769 loss_visual: 0.0943 loss: 0.0943 2022/09/16 05:46:48 - mmengine - INFO - Epoch(train) [4][9200/10520] lr: 1.0000e-04 eta: 2 days, 11:12:58 time: 0.9962 data_time: 0.1332 memory: 56769 loss_visual: 0.0880 loss: 0.0880 2022/09/16 05:48:55 - mmengine - INFO - Epoch(train) [4][9300/10520] lr: 1.0000e-04 eta: 2 days, 11:10:57 time: 1.0715 data_time: 0.2470 memory: 56769 loss_visual: 0.0946 loss: 0.0946 2022/09/16 05:51:00 - mmengine - INFO - Epoch(train) [4][9400/10520] lr: 1.0000e-04 eta: 2 days, 11:08:51 time: 1.0149 data_time: 0.1540 memory: 56769 loss_visual: 0.0927 loss: 0.0927 2022/09/16 05:51:49 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 05:53:07 - mmengine - INFO - Epoch(train) [4][9500/10520] lr: 1.0000e-04 eta: 2 days, 11:06:52 time: 0.9123 data_time: 0.0070 memory: 56769 loss_visual: 0.0933 loss: 0.0933 2022/09/16 05:55:15 - mmengine - INFO - Epoch(train) [4][9600/10520] lr: 1.0000e-04 eta: 2 days, 11:04:53 time: 1.0132 data_time: 0.0066 memory: 56769 loss_visual: 0.0919 loss: 0.0919 2022/09/16 05:57:29 - mmengine - INFO - Epoch(train) [4][9700/10520] lr: 1.0000e-04 eta: 2 days, 11:03:23 time: 1.8112 data_time: 0.3965 memory: 56769 loss_visual: 0.0865 loss: 0.0865 2022/09/16 05:59:37 - mmengine - INFO - Epoch(train) [4][9800/10520] lr: 1.0000e-04 eta: 2 days, 11:01:25 time: 1.8605 data_time: 0.5228 memory: 56769 loss_visual: 0.0928 loss: 0.0928 2022/09/16 06:01:47 - mmengine - INFO - Epoch(train) [4][9900/10520] lr: 1.0000e-04 eta: 2 days, 10:59:37 time: 1.0361 data_time: 0.1815 memory: 56769 loss_visual: 0.0922 loss: 0.0922 2022/09/16 06:03:55 - mmengine - INFO - Epoch(train) [4][10000/10520] lr: 1.0000e-04 eta: 2 days, 10:57:42 time: 0.9977 data_time: 0.1129 memory: 56769 loss_visual: 0.0885 loss: 0.0885 2022/09/16 06:06:04 - mmengine - INFO - Epoch(train) [4][10100/10520] lr: 1.0000e-04 eta: 2 days, 10:55:48 time: 1.0458 data_time: 0.2216 memory: 56769 loss_visual: 0.0911 loss: 0.0911 2022/09/16 06:08:11 - mmengine - INFO - Epoch(train) [4][10200/10520] lr: 1.0000e-04 eta: 2 days, 10:53:48 time: 0.9986 data_time: 0.1816 memory: 56769 loss_visual: 0.0881 loss: 0.0881 2022/09/16 06:10:18 - mmengine - INFO - Epoch(train) [4][10300/10520] lr: 1.0000e-04 eta: 2 days, 10:51:49 time: 0.9063 data_time: 0.0066 memory: 56769 loss_visual: 0.0904 loss: 0.0904 2022/09/16 06:12:28 - mmengine - INFO - Epoch(train) [4][10400/10520] lr: 1.0000e-04 eta: 2 days, 10:49:57 time: 1.0240 data_time: 0.0071 memory: 56769 loss_visual: 0.0917 loss: 0.0917 2022/09/16 06:13:25 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 06:14:35 - mmengine - INFO - Epoch(train) [4][10500/10520] lr: 1.0000e-04 eta: 2 days, 10:47:57 time: 1.3776 data_time: 0.1926 memory: 56769 loss_visual: 0.0879 loss: 0.0879 2022/09/16 06:14:53 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 06:14:53 - mmengine - INFO - Saving checkpoint at 4 epochs 2022/09/16 06:15:18 - mmengine - INFO - Epoch(val) [4][100/3836] eta: 0:08:57 time: 0.1440 data_time: 0.0006 memory: 56769 2022/09/16 06:15:23 - mmengine - INFO - Epoch(val) [4][200/3836] eta: 0:00:41 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 06:15:24 - mmengine - INFO - Epoch(val) [4][300/3836] eta: 0:00:39 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/16 06:15:26 - mmengine - INFO - Epoch(val) [4][400/3836] eta: 0:00:39 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/16 06:15:27 - mmengine - INFO - Epoch(val) [4][500/3836] eta: 0:00:36 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/16 06:15:28 - mmengine - INFO - Epoch(val) [4][600/3836] eta: 0:00:38 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/16 06:15:29 - mmengine - INFO - Epoch(val) [4][700/3836] eta: 0:00:35 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/16 06:15:30 - mmengine - INFO - Epoch(val) [4][800/3836] eta: 0:00:35 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 06:15:32 - mmengine - INFO - Epoch(val) [4][900/3836] eta: 0:00:33 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/16 06:15:33 - mmengine - INFO - Epoch(val) [4][1000/3836] eta: 0:00:33 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 06:15:34 - mmengine - INFO - Epoch(val) [4][1100/3836] eta: 0:00:31 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/16 06:15:35 - mmengine - INFO - Epoch(val) [4][1200/3836] eta: 0:00:29 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/16 06:15:36 - mmengine - INFO - Epoch(val) [4][1300/3836] eta: 0:00:29 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 06:15:37 - mmengine - INFO - Epoch(val) [4][1400/3836] eta: 0:00:28 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 06:15:38 - mmengine - INFO - Epoch(val) [4][1500/3836] eta: 0:00:28 time: 0.0123 data_time: 0.0005 memory: 480 2022/09/16 06:15:40 - mmengine - INFO - Epoch(val) [4][1600/3836] eta: 0:00:24 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/16 06:15:41 - mmengine - INFO - Epoch(val) [4][1700/3836] eta: 0:00:24 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/16 06:15:42 - mmengine - INFO - Epoch(val) [4][1800/3836] eta: 0:00:23 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/16 06:15:43 - mmengine - INFO - Epoch(val) [4][1900/3836] eta: 0:00:22 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 06:15:44 - mmengine - INFO - Epoch(val) [4][2000/3836] eta: 0:00:21 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/16 06:15:45 - mmengine - INFO - Epoch(val) [4][2100/3836] eta: 0:00:20 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/16 06:15:47 - mmengine - INFO - Epoch(val) [4][2200/3836] eta: 0:00:18 time: 0.0110 data_time: 0.0005 memory: 480 2022/09/16 06:15:48 - mmengine - INFO - Epoch(val) [4][2300/3836] eta: 0:00:17 time: 0.0117 data_time: 0.0006 memory: 480 2022/09/16 06:15:49 - mmengine - INFO - Epoch(val) [4][2400/3836] eta: 0:00:16 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 06:15:50 - mmengine - INFO - Epoch(val) [4][2500/3836] eta: 0:00:15 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 06:15:51 - mmengine - INFO - Epoch(val) [4][2600/3836] eta: 0:00:14 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/16 06:15:53 - mmengine - INFO - Epoch(val) [4][2700/3836] eta: 0:00:13 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 06:15:54 - mmengine - INFO - Epoch(val) [4][2800/3836] eta: 0:00:12 time: 0.0117 data_time: 0.0004 memory: 480 2022/09/16 06:15:55 - mmengine - INFO - Epoch(val) [4][2900/3836] eta: 0:00:10 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/16 06:15:56 - mmengine - INFO - Epoch(val) [4][3000/3836] eta: 0:00:09 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/16 06:15:57 - mmengine - INFO - Epoch(val) [4][3100/3836] eta: 0:00:07 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/16 06:15:58 - mmengine - INFO - Epoch(val) [4][3200/3836] eta: 0:00:06 time: 0.0107 data_time: 0.0005 memory: 480 2022/09/16 06:15:59 - mmengine - INFO - Epoch(val) [4][3300/3836] eta: 0:00:05 time: 0.0110 data_time: 0.0005 memory: 480 2022/09/16 06:16:00 - mmengine - INFO - Epoch(val) [4][3400/3836] eta: 0:00:04 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/16 06:16:01 - mmengine - INFO - Epoch(val) [4][3500/3836] eta: 0:00:03 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/16 06:16:03 - mmengine - INFO - Epoch(val) [4][3600/3836] eta: 0:00:02 time: 0.0108 data_time: 0.0004 memory: 480 2022/09/16 06:16:04 - mmengine - INFO - Epoch(val) [4][3700/3836] eta: 0:00:01 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/16 06:16:05 - mmengine - INFO - Epoch(val) [4][3800/3836] eta: 0:00:00 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/16 06:16:05 - mmengine - INFO - Epoch(val) [4][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.7535 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9013 SVT/recog/word_acc_ignore_case_symbol: 0.8454 SVTP/recog/word_acc_ignore_case_symbol: 0.7426 IC13/recog/word_acc_ignore_case_symbol: 0.8670 IC15/recog/word_acc_ignore_case_symbol: 0.6991 2022/09/16 06:18:32 - mmengine - INFO - Epoch(train) [5][100/10520] lr: 1.0000e-04 eta: 2 days, 10:46:24 time: 1.5524 data_time: 0.5586 memory: 56769 loss_visual: 0.0949 loss: 0.0949 2022/09/16 06:20:44 - mmengine - INFO - Epoch(train) [5][200/10520] lr: 1.0000e-04 eta: 2 days, 10:44:44 time: 2.0746 data_time: 0.7034 memory: 56769 loss_visual: 0.0928 loss: 0.0928 2022/09/16 06:22:52 - mmengine - INFO - Epoch(train) [5][300/10520] lr: 1.0000e-04 eta: 2 days, 10:42:46 time: 1.9407 data_time: 0.6160 memory: 56769 loss_visual: 0.0843 loss: 0.0843 2022/09/16 06:24:59 - mmengine - INFO - Epoch(train) [5][400/10520] lr: 1.0000e-04 eta: 2 days, 10:40:44 time: 1.0264 data_time: 0.1698 memory: 56769 loss_visual: 0.0915 loss: 0.0915 2022/09/16 06:27:06 - mmengine - INFO - Epoch(train) [5][500/10520] lr: 1.0000e-04 eta: 2 days, 10:38:42 time: 0.8960 data_time: 0.0242 memory: 56769 loss_visual: 0.0913 loss: 0.0913 2022/09/16 06:29:13 - mmengine - INFO - Epoch(train) [5][600/10520] lr: 1.0000e-04 eta: 2 days, 10:36:41 time: 0.8896 data_time: 0.0243 memory: 56769 loss_visual: 0.0953 loss: 0.0953 2022/09/16 06:31:19 - mmengine - INFO - Epoch(train) [5][700/10520] lr: 1.0000e-04 eta: 2 days, 10:34:38 time: 0.8994 data_time: 0.0070 memory: 56769 loss_visual: 0.0915 loss: 0.0915 2022/09/16 06:33:27 - mmengine - INFO - Epoch(train) [5][800/10520] lr: 1.0000e-04 eta: 2 days, 10:32:39 time: 0.8449 data_time: 0.0068 memory: 56769 loss_visual: 0.0912 loss: 0.0912 2022/09/16 06:35:41 - mmengine - INFO - Epoch(train) [5][900/10520] lr: 1.0000e-04 eta: 2 days, 10:31:03 time: 1.5547 data_time: 0.5496 memory: 56769 loss_visual: 0.0848 loss: 0.0848 2022/09/16 06:36:04 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 06:37:52 - mmengine - INFO - Epoch(train) [5][1000/10520] lr: 1.0000e-04 eta: 2 days, 10:29:19 time: 2.1276 data_time: 0.6681 memory: 56769 loss_visual: 0.0873 loss: 0.0873 2022/09/16 06:39:59 - mmengine - INFO - Epoch(train) [5][1100/10520] lr: 1.0000e-04 eta: 2 days, 10:27:20 time: 1.9421 data_time: 0.6149 memory: 56769 loss_visual: 0.0910 loss: 0.0910 2022/09/16 06:42:06 - mmengine - INFO - Epoch(train) [5][1200/10520] lr: 1.0000e-04 eta: 2 days, 10:25:18 time: 0.9981 data_time: 0.1499 memory: 56769 loss_visual: 0.0900 loss: 0.0900 2022/09/16 06:44:14 - mmengine - INFO - Epoch(train) [5][1300/10520] lr: 1.0000e-04 eta: 2 days, 10:23:18 time: 0.8825 data_time: 0.0254 memory: 56769 loss_visual: 0.0914 loss: 0.0914 2022/09/16 06:46:20 - mmengine - INFO - Epoch(train) [5][1400/10520] lr: 1.0000e-04 eta: 2 days, 10:21:14 time: 0.8565 data_time: 0.0338 memory: 56769 loss_visual: 0.0875 loss: 0.0875 2022/09/16 06:48:27 - mmengine - INFO - Epoch(train) [5][1500/10520] lr: 1.0000e-04 eta: 2 days, 10:19:14 time: 0.8695 data_time: 0.0069 memory: 56769 loss_visual: 0.0894 loss: 0.0894 2022/09/16 06:50:34 - mmengine - INFO - Epoch(train) [5][1600/10520] lr: 1.0000e-04 eta: 2 days, 10:17:12 time: 0.8639 data_time: 0.0071 memory: 56769 loss_visual: 0.0839 loss: 0.0839 2022/09/16 06:52:47 - mmengine - INFO - Epoch(train) [5][1700/10520] lr: 1.0000e-04 eta: 2 days, 10:15:33 time: 1.5365 data_time: 0.5606 memory: 56769 loss_visual: 0.0906 loss: 0.0906 2022/09/16 06:54:58 - mmengine - INFO - Epoch(train) [5][1800/10520] lr: 1.0000e-04 eta: 2 days, 10:13:46 time: 2.1047 data_time: 0.6974 memory: 56769 loss_visual: 0.0867 loss: 0.0867 2022/09/16 06:57:05 - mmengine - INFO - Epoch(train) [5][1900/10520] lr: 1.0000e-04 eta: 2 days, 10:11:43 time: 1.9882 data_time: 0.6052 memory: 56769 loss_visual: 0.0911 loss: 0.0911 2022/09/16 06:57:22 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 06:59:13 - mmengine - INFO - Epoch(train) [5][2000/10520] lr: 1.0000e-04 eta: 2 days, 10:09:44 time: 1.0290 data_time: 0.1721 memory: 56769 loss_visual: 0.0917 loss: 0.0917 2022/09/16 07:01:20 - mmengine - INFO - Epoch(train) [5][2100/10520] lr: 1.0000e-04 eta: 2 days, 10:07:42 time: 0.9220 data_time: 0.0234 memory: 56769 loss_visual: 0.0851 loss: 0.0851 2022/09/16 07:03:26 - mmengine - INFO - Epoch(train) [5][2200/10520] lr: 1.0000e-04 eta: 2 days, 10:05:38 time: 0.8515 data_time: 0.0236 memory: 56769 loss_visual: 0.0865 loss: 0.0865 2022/09/16 07:05:32 - mmengine - INFO - Epoch(train) [5][2300/10520] lr: 1.0000e-04 eta: 2 days, 10:03:33 time: 0.8716 data_time: 0.0067 memory: 56769 loss_visual: 0.0914 loss: 0.0914 2022/09/16 07:07:39 - mmengine - INFO - Epoch(train) [5][2400/10520] lr: 1.0000e-04 eta: 2 days, 10:01:32 time: 0.8617 data_time: 0.0069 memory: 56769 loss_visual: 0.0876 loss: 0.0876 2022/09/16 07:09:52 - mmengine - INFO - Epoch(train) [5][2500/10520] lr: 1.0000e-04 eta: 2 days, 9:59:51 time: 1.5581 data_time: 0.5159 memory: 56769 loss_visual: 0.0893 loss: 0.0893 2022/09/16 07:12:03 - mmengine - INFO - Epoch(train) [5][2600/10520] lr: 1.0000e-04 eta: 2 days, 9:58:06 time: 2.1153 data_time: 0.6978 memory: 56769 loss_visual: 0.0834 loss: 0.0834 2022/09/16 07:14:10 - mmengine - INFO - Epoch(train) [5][2700/10520] lr: 1.0000e-04 eta: 2 days, 9:56:01 time: 1.9325 data_time: 0.5612 memory: 56769 loss_visual: 0.0867 loss: 0.0867 2022/09/16 07:16:17 - mmengine - INFO - Epoch(train) [5][2800/10520] lr: 1.0000e-04 eta: 2 days, 9:53:59 time: 1.0520 data_time: 0.1673 memory: 56769 loss_visual: 0.0873 loss: 0.0873 2022/09/16 07:18:23 - mmengine - INFO - Epoch(train) [5][2900/10520] lr: 1.0000e-04 eta: 2 days, 9:51:55 time: 0.9085 data_time: 0.0577 memory: 56769 loss_visual: 0.0905 loss: 0.0905 2022/09/16 07:18:54 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 07:20:31 - mmengine - INFO - Epoch(train) [5][3000/10520] lr: 1.0000e-04 eta: 2 days, 9:49:55 time: 0.9268 data_time: 0.0702 memory: 56769 loss_visual: 0.0899 loss: 0.0899 2022/09/16 07:22:38 - mmengine - INFO - Epoch(train) [5][3100/10520] lr: 1.0000e-04 eta: 2 days, 9:47:52 time: 0.8335 data_time: 0.0064 memory: 56769 loss_visual: 0.0939 loss: 0.0939 2022/09/16 07:24:45 - mmengine - INFO - Epoch(train) [5][3200/10520] lr: 1.0000e-04 eta: 2 days, 9:45:51 time: 0.8638 data_time: 0.0071 memory: 56769 loss_visual: 0.0878 loss: 0.0878 2022/09/16 07:26:58 - mmengine - INFO - Epoch(train) [5][3300/10520] lr: 1.0000e-04 eta: 2 days, 9:44:10 time: 1.5076 data_time: 0.5038 memory: 56769 loss_visual: 0.0878 loss: 0.0878 2022/09/16 07:29:10 - mmengine - INFO - Epoch(train) [5][3400/10520] lr: 1.0000e-04 eta: 2 days, 9:42:28 time: 2.1092 data_time: 0.6309 memory: 56769 loss_visual: 0.0855 loss: 0.0855 2022/09/16 07:31:18 - mmengine - INFO - Epoch(train) [5][3500/10520] lr: 1.0000e-04 eta: 2 days, 9:40:28 time: 1.9300 data_time: 0.5888 memory: 56769 loss_visual: 0.0859 loss: 0.0859 2022/09/16 07:33:25 - mmengine - INFO - Epoch(train) [5][3600/10520] lr: 1.0000e-04 eta: 2 days, 9:38:27 time: 1.0328 data_time: 0.1757 memory: 56769 loss_visual: 0.0889 loss: 0.0889 2022/09/16 07:35:33 - mmengine - INFO - Epoch(train) [5][3700/10520] lr: 1.0000e-04 eta: 2 days, 9:36:27 time: 0.9222 data_time: 0.0259 memory: 56769 loss_visual: 0.0879 loss: 0.0879 2022/09/16 07:37:39 - mmengine - INFO - Epoch(train) [5][3800/10520] lr: 1.0000e-04 eta: 2 days, 9:34:23 time: 0.9258 data_time: 0.0258 memory: 56769 loss_visual: 0.0827 loss: 0.0827 2022/09/16 07:39:46 - mmengine - INFO - Epoch(train) [5][3900/10520] lr: 1.0000e-04 eta: 2 days, 9:32:18 time: 0.8619 data_time: 0.0070 memory: 56769 loss_visual: 0.0855 loss: 0.0855 2022/09/16 07:40:16 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 07:41:52 - mmengine - INFO - Epoch(train) [5][4000/10520] lr: 1.0000e-04 eta: 2 days, 9:30:12 time: 0.8619 data_time: 0.0069 memory: 56769 loss_visual: 0.0894 loss: 0.0894 2022/09/16 07:44:04 - mmengine - INFO - Epoch(train) [5][4100/10520] lr: 1.0000e-04 eta: 2 days, 9:28:29 time: 1.4987 data_time: 0.5268 memory: 56769 loss_visual: 0.0911 loss: 0.0911 2022/09/16 07:46:18 - mmengine - INFO - Epoch(train) [5][4200/10520] lr: 1.0000e-04 eta: 2 days, 9:26:50 time: 2.1481 data_time: 0.6779 memory: 56769 loss_visual: 0.0880 loss: 0.0880 2022/09/16 07:48:25 - mmengine - INFO - Epoch(train) [5][4300/10520] lr: 1.0000e-04 eta: 2 days, 9:24:48 time: 1.9356 data_time: 0.6096 memory: 56769 loss_visual: 0.0860 loss: 0.0860 2022/09/16 07:50:31 - mmengine - INFO - Epoch(train) [5][4400/10520] lr: 1.0000e-04 eta: 2 days, 9:22:41 time: 1.0510 data_time: 0.1985 memory: 56769 loss_visual: 0.0885 loss: 0.0885 2022/09/16 07:52:36 - mmengine - INFO - Epoch(train) [5][4500/10520] lr: 1.0000e-04 eta: 2 days, 9:20:31 time: 0.8475 data_time: 0.0242 memory: 56769 loss_visual: 0.0828 loss: 0.0828 2022/09/16 07:54:42 - mmengine - INFO - Epoch(train) [5][4600/10520] lr: 1.0000e-04 eta: 2 days, 9:18:26 time: 0.8601 data_time: 0.0235 memory: 56769 loss_visual: 0.0859 loss: 0.0859 2022/09/16 07:56:48 - mmengine - INFO - Epoch(train) [5][4700/10520] lr: 1.0000e-04 eta: 2 days, 9:16:22 time: 0.8681 data_time: 0.0072 memory: 56769 loss_visual: 0.0901 loss: 0.0901 2022/09/16 07:58:55 - mmengine - INFO - Epoch(train) [5][4800/10520] lr: 1.0000e-04 eta: 2 days, 9:14:18 time: 0.9093 data_time: 0.0073 memory: 56769 loss_visual: 0.0872 loss: 0.0872 2022/09/16 08:01:08 - mmengine - INFO - Epoch(train) [5][4900/10520] lr: 1.0000e-04 eta: 2 days, 9:12:37 time: 1.4828 data_time: 0.5239 memory: 56769 loss_visual: 0.0887 loss: 0.0887 2022/09/16 08:01:32 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 08:03:21 - mmengine - INFO - Epoch(train) [5][5000/10520] lr: 1.0000e-04 eta: 2 days, 9:10:52 time: 2.1826 data_time: 0.6737 memory: 56769 loss_visual: 0.0845 loss: 0.0845 2022/09/16 08:05:26 - mmengine - INFO - Epoch(train) [5][5100/10520] lr: 1.0000e-04 eta: 2 days, 9:08:44 time: 1.9380 data_time: 0.6278 memory: 56769 loss_visual: 0.0873 loss: 0.0873 2022/09/16 08:07:32 - mmengine - INFO - Epoch(train) [5][5200/10520] lr: 1.0000e-04 eta: 2 days, 9:06:36 time: 1.0121 data_time: 0.1758 memory: 56769 loss_visual: 0.0864 loss: 0.0864 2022/09/16 08:09:38 - mmengine - INFO - Epoch(train) [5][5300/10520] lr: 1.0000e-04 eta: 2 days, 9:04:33 time: 0.8811 data_time: 0.0258 memory: 56769 loss_visual: 0.0832 loss: 0.0832 2022/09/16 08:11:45 - mmengine - INFO - Epoch(train) [5][5400/10520] lr: 1.0000e-04 eta: 2 days, 9:02:29 time: 0.8931 data_time: 0.0220 memory: 56769 loss_visual: 0.0869 loss: 0.0869 2022/09/16 08:13:52 - mmengine - INFO - Epoch(train) [5][5500/10520] lr: 1.0000e-04 eta: 2 days, 9:00:25 time: 0.8706 data_time: 0.0065 memory: 56769 loss_visual: 0.0889 loss: 0.0889 2022/09/16 08:15:59 - mmengine - INFO - Epoch(train) [5][5600/10520] lr: 1.0000e-04 eta: 2 days, 8:58:22 time: 0.8639 data_time: 0.0066 memory: 56769 loss_visual: 0.0887 loss: 0.0887 2022/09/16 08:18:11 - mmengine - INFO - Epoch(train) [5][5700/10520] lr: 1.0000e-04 eta: 2 days, 8:56:37 time: 1.4758 data_time: 0.5053 memory: 56769 loss_visual: 0.0877 loss: 0.0877 2022/09/16 08:20:25 - mmengine - INFO - Epoch(train) [5][5800/10520] lr: 1.0000e-04 eta: 2 days, 8:54:57 time: 2.1560 data_time: 0.6490 memory: 56769 loss_visual: 0.0857 loss: 0.0857 2022/09/16 08:22:31 - mmengine - INFO - Epoch(train) [5][5900/10520] lr: 1.0000e-04 eta: 2 days, 8:52:53 time: 1.9483 data_time: 0.6555 memory: 56769 loss_visual: 0.0828 loss: 0.0828 2022/09/16 08:22:49 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 08:24:38 - mmengine - INFO - Epoch(train) [5][6000/10520] lr: 1.0000e-04 eta: 2 days, 8:50:48 time: 1.0584 data_time: 0.2192 memory: 56769 loss_visual: 0.0859 loss: 0.0859 2022/09/16 08:26:45 - mmengine - INFO - Epoch(train) [5][6100/10520] lr: 1.0000e-04 eta: 2 days, 8:48:47 time: 0.8669 data_time: 0.0227 memory: 56769 loss_visual: 0.0854 loss: 0.0854 2022/09/16 08:28:54 - mmengine - INFO - Epoch(train) [5][6200/10520] lr: 1.0000e-04 eta: 2 days, 8:46:48 time: 0.9286 data_time: 0.0317 memory: 56769 loss_visual: 0.0853 loss: 0.0853 2022/09/16 08:31:00 - mmengine - INFO - Epoch(train) [5][6300/10520] lr: 1.0000e-04 eta: 2 days, 8:44:44 time: 0.8680 data_time: 0.0076 memory: 56769 loss_visual: 0.0887 loss: 0.0887 2022/09/16 08:33:07 - mmengine - INFO - Epoch(train) [5][6400/10520] lr: 1.0000e-04 eta: 2 days, 8:42:39 time: 0.9034 data_time: 0.0082 memory: 56769 loss_visual: 0.0839 loss: 0.0839 2022/09/16 08:35:18 - mmengine - INFO - Epoch(train) [5][6500/10520] lr: 1.0000e-04 eta: 2 days, 8:40:49 time: 1.4647 data_time: 0.4870 memory: 56769 loss_visual: 0.0842 loss: 0.0842 2022/09/16 08:37:30 - mmengine - INFO - Epoch(train) [5][6600/10520] lr: 1.0000e-04 eta: 2 days, 8:39:01 time: 2.1493 data_time: 0.6364 memory: 56769 loss_visual: 0.0883 loss: 0.0883 2022/09/16 08:39:35 - mmengine - INFO - Epoch(train) [5][6700/10520] lr: 1.0000e-04 eta: 2 days, 8:36:53 time: 1.9325 data_time: 0.5850 memory: 56769 loss_visual: 0.0861 loss: 0.0861 2022/09/16 08:41:41 - mmengine - INFO - Epoch(train) [5][6800/10520] lr: 1.0000e-04 eta: 2 days, 8:34:47 time: 1.0585 data_time: 0.1888 memory: 56769 loss_visual: 0.0833 loss: 0.0833 2022/09/16 08:43:48 - mmengine - INFO - Epoch(train) [5][6900/10520] lr: 1.0000e-04 eta: 2 days, 8:32:44 time: 0.8970 data_time: 0.0258 memory: 56769 loss_visual: 0.0876 loss: 0.0876 2022/09/16 08:44:18 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 08:45:56 - mmengine - INFO - Epoch(train) [5][7000/10520] lr: 1.0000e-04 eta: 2 days, 8:30:43 time: 0.9177 data_time: 0.0610 memory: 56769 loss_visual: 0.0879 loss: 0.0879 2022/09/16 08:48:02 - mmengine - INFO - Epoch(train) [5][7100/10520] lr: 1.0000e-04 eta: 2 days, 8:28:36 time: 0.8640 data_time: 0.0067 memory: 56769 loss_visual: 0.0837 loss: 0.0837 2022/09/16 08:50:08 - mmengine - INFO - Epoch(train) [5][7200/10520] lr: 1.0000e-04 eta: 2 days, 8:26:29 time: 0.8720 data_time: 0.0072 memory: 56769 loss_visual: 0.0857 loss: 0.0857 2022/09/16 08:52:20 - mmengine - INFO - Epoch(train) [5][7300/10520] lr: 1.0000e-04 eta: 2 days, 8:24:42 time: 1.5019 data_time: 0.4628 memory: 56769 loss_visual: 0.0828 loss: 0.0828 2022/09/16 08:54:32 - mmengine - INFO - Epoch(train) [5][7400/10520] lr: 1.0000e-04 eta: 2 days, 8:22:56 time: 2.0720 data_time: 0.6810 memory: 56769 loss_visual: 0.0842 loss: 0.0842 2022/09/16 08:56:40 - mmengine - INFO - Epoch(train) [5][7500/10520] lr: 1.0000e-04 eta: 2 days, 8:20:55 time: 1.9200 data_time: 0.5862 memory: 56769 loss_visual: 0.0846 loss: 0.0846 2022/09/16 08:58:48 - mmengine - INFO - Epoch(train) [5][7600/10520] lr: 1.0000e-04 eta: 2 days, 8:18:55 time: 1.0423 data_time: 0.2140 memory: 56769 loss_visual: 0.0836 loss: 0.0836 2022/09/16 09:00:55 - mmengine - INFO - Epoch(train) [5][7700/10520] lr: 1.0000e-04 eta: 2 days, 8:16:52 time: 0.8846 data_time: 0.0612 memory: 56769 loss_visual: 0.0846 loss: 0.0846 2022/09/16 09:03:01 - mmengine - INFO - Epoch(train) [5][7800/10520] lr: 1.0000e-04 eta: 2 days, 8:14:45 time: 0.8970 data_time: 0.0341 memory: 56769 loss_visual: 0.0859 loss: 0.0859 2022/09/16 09:05:08 - mmengine - INFO - Epoch(train) [5][7900/10520] lr: 1.0000e-04 eta: 2 days, 8:12:41 time: 0.8832 data_time: 0.0071 memory: 56769 loss_visual: 0.0894 loss: 0.0894 2022/09/16 09:05:38 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 09:07:15 - mmengine - INFO - Epoch(train) [5][8000/10520] lr: 1.0000e-04 eta: 2 days, 8:10:38 time: 0.8744 data_time: 0.0066 memory: 56769 loss_visual: 0.0818 loss: 0.0818 2022/09/16 09:09:27 - mmengine - INFO - Epoch(train) [5][8100/10520] lr: 1.0000e-04 eta: 2 days, 8:08:53 time: 1.5085 data_time: 0.4793 memory: 56769 loss_visual: 0.0878 loss: 0.0878 2022/09/16 09:11:39 - mmengine - INFO - Epoch(train) [5][8200/10520] lr: 1.0000e-04 eta: 2 days, 8:07:03 time: 2.1099 data_time: 0.6643 memory: 56769 loss_visual: 0.0849 loss: 0.0849 2022/09/16 09:13:46 - mmengine - INFO - Epoch(train) [5][8300/10520] lr: 1.0000e-04 eta: 2 days, 8:04:59 time: 1.9737 data_time: 0.6265 memory: 56769 loss_visual: 0.0893 loss: 0.0893 2022/09/16 09:15:52 - mmengine - INFO - Epoch(train) [5][8400/10520] lr: 1.0000e-04 eta: 2 days, 8:02:53 time: 1.0903 data_time: 0.2095 memory: 56769 loss_visual: 0.0837 loss: 0.0837 2022/09/16 09:17:57 - mmengine - INFO - Epoch(train) [5][8500/10520] lr: 1.0000e-04 eta: 2 days, 8:00:45 time: 0.8637 data_time: 0.0223 memory: 56769 loss_visual: 0.0894 loss: 0.0894 2022/09/16 09:20:04 - mmengine - INFO - Epoch(train) [5][8600/10520] lr: 1.0000e-04 eta: 2 days, 7:58:40 time: 0.9063 data_time: 0.0239 memory: 56769 loss_visual: 0.0835 loss: 0.0835 2022/09/16 09:22:10 - mmengine - INFO - Epoch(train) [5][8700/10520] lr: 1.0000e-04 eta: 2 days, 7:56:32 time: 0.8695 data_time: 0.0069 memory: 56769 loss_visual: 0.0826 loss: 0.0826 2022/09/16 09:24:15 - mmengine - INFO - Epoch(train) [5][8800/10520] lr: 1.0000e-04 eta: 2 days, 7:54:23 time: 0.8593 data_time: 0.0078 memory: 56769 loss_visual: 0.0879 loss: 0.0879 2022/09/16 09:26:27 - mmengine - INFO - Epoch(train) [5][8900/10520] lr: 1.0000e-04 eta: 2 days, 7:52:34 time: 1.4969 data_time: 0.5454 memory: 56769 loss_visual: 0.0838 loss: 0.0838 2022/09/16 09:26:51 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 09:28:40 - mmengine - INFO - Epoch(train) [5][9000/10520] lr: 1.0000e-04 eta: 2 days, 7:50:51 time: 2.1364 data_time: 0.7003 memory: 56769 loss_visual: 0.0858 loss: 0.0858 2022/09/16 09:30:47 - mmengine - INFO - Epoch(train) [5][9100/10520] lr: 1.0000e-04 eta: 2 days, 7:48:46 time: 1.9261 data_time: 0.6119 memory: 56769 loss_visual: 0.0898 loss: 0.0898 2022/09/16 09:32:54 - mmengine - INFO - Epoch(train) [5][9200/10520] lr: 1.0000e-04 eta: 2 days, 7:46:41 time: 1.0602 data_time: 0.2271 memory: 56769 loss_visual: 0.0824 loss: 0.0824 2022/09/16 09:35:00 - mmengine - INFO - Epoch(train) [5][9300/10520] lr: 1.0000e-04 eta: 2 days, 7:44:35 time: 0.8708 data_time: 0.0226 memory: 56769 loss_visual: 0.0864 loss: 0.0864 2022/09/16 09:37:05 - mmengine - INFO - Epoch(train) [5][9400/10520] lr: 1.0000e-04 eta: 2 days, 7:42:27 time: 0.8982 data_time: 0.0675 memory: 56769 loss_visual: 0.0865 loss: 0.0865 2022/09/16 09:39:12 - mmengine - INFO - Epoch(train) [5][9500/10520] lr: 1.0000e-04 eta: 2 days, 7:40:21 time: 0.8611 data_time: 0.0065 memory: 56769 loss_visual: 0.0887 loss: 0.0887 2022/09/16 09:41:17 - mmengine - INFO - Epoch(train) [5][9600/10520] lr: 1.0000e-04 eta: 2 days, 7:38:13 time: 0.8611 data_time: 0.0067 memory: 56769 loss_visual: 0.0832 loss: 0.0832 2022/09/16 09:43:31 - mmengine - INFO - Epoch(train) [5][9700/10520] lr: 1.0000e-04 eta: 2 days, 7:36:29 time: 1.5402 data_time: 0.4607 memory: 56769 loss_visual: 0.0869 loss: 0.0869 2022/09/16 09:45:44 - mmengine - INFO - Epoch(train) [5][9800/10520] lr: 1.0000e-04 eta: 2 days, 7:34:43 time: 2.1320 data_time: 0.6421 memory: 56769 loss_visual: 0.0875 loss: 0.0875 2022/09/16 09:47:50 - mmengine - INFO - Epoch(train) [5][9900/10520] lr: 1.0000e-04 eta: 2 days, 7:32:39 time: 1.9214 data_time: 0.5819 memory: 56769 loss_visual: 0.0818 loss: 0.0818 2022/09/16 09:48:08 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 09:49:56 - mmengine - INFO - Epoch(train) [5][10000/10520] lr: 1.0000e-04 eta: 2 days, 7:30:31 time: 1.1020 data_time: 0.2403 memory: 56769 loss_visual: 0.0836 loss: 0.0836 2022/09/16 09:52:03 - mmengine - INFO - Epoch(train) [5][10100/10520] lr: 1.0000e-04 eta: 2 days, 7:28:28 time: 0.8850 data_time: 0.0256 memory: 56769 loss_visual: 0.0796 loss: 0.0796 2022/09/16 09:54:12 - mmengine - INFO - Epoch(train) [5][10200/10520] lr: 1.0000e-04 eta: 2 days, 7:26:29 time: 0.8860 data_time: 0.0628 memory: 56769 loss_visual: 0.0835 loss: 0.0835 2022/09/16 09:56:18 - mmengine - INFO - Epoch(train) [5][10300/10520] lr: 1.0000e-04 eta: 2 days, 7:24:23 time: 0.8883 data_time: 0.0066 memory: 56769 loss_visual: 0.0808 loss: 0.0808 2022/09/16 09:58:26 - mmengine - INFO - Epoch(train) [5][10400/10520] lr: 1.0000e-04 eta: 2 days, 7:22:19 time: 0.8710 data_time: 0.0066 memory: 56769 loss_visual: 0.0815 loss: 0.0815 2022/09/16 10:00:32 - mmengine - INFO - Epoch(train) [5][10500/10520] lr: 1.0000e-04 eta: 2 days, 7:20:13 time: 1.2828 data_time: 0.3295 memory: 56769 loss_visual: 0.0808 loss: 0.0808 2022/09/16 10:00:51 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 10:00:51 - mmengine - INFO - Saving checkpoint at 5 epochs 2022/09/16 10:01:14 - mmengine - INFO - Epoch(val) [5][100/3836] eta: 0:06:09 time: 0.0989 data_time: 0.0007 memory: 56769 2022/09/16 10:01:20 - mmengine - INFO - Epoch(val) [5][200/3836] eta: 0:00:42 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 10:01:21 - mmengine - INFO - Epoch(val) [5][300/3836] eta: 0:00:40 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 10:01:22 - mmengine - INFO - Epoch(val) [5][400/3836] eta: 0:00:39 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 10:01:24 - mmengine - INFO - Epoch(val) [5][500/3836] eta: 0:00:38 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 10:01:25 - mmengine - INFO - Epoch(val) [5][600/3836] eta: 0:00:41 time: 0.0127 data_time: 0.0005 memory: 480 2022/09/16 10:01:26 - mmengine - INFO - Epoch(val) [5][700/3836] eta: 0:00:36 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/16 10:01:27 - mmengine - INFO - Epoch(val) [5][800/3836] eta: 0:00:36 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/16 10:01:28 - mmengine - INFO - Epoch(val) [5][900/3836] eta: 0:00:33 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/16 10:01:29 - mmengine - INFO - Epoch(val) [5][1000/3836] eta: 0:00:31 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/16 10:01:31 - mmengine - INFO - Epoch(val) [5][1100/3836] eta: 0:00:35 time: 0.0128 data_time: 0.0006 memory: 480 2022/09/16 10:01:32 - mmengine - INFO - Epoch(val) [5][1200/3836] eta: 0:00:31 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/16 10:01:33 - mmengine - INFO - Epoch(val) [5][1300/3836] eta: 0:00:29 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 10:01:34 - mmengine - INFO - Epoch(val) [5][1400/3836] eta: 0:00:27 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/16 10:01:35 - mmengine - INFO - Epoch(val) [5][1500/3836] eta: 0:00:26 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/16 10:01:37 - mmengine - INFO - Epoch(val) [5][1600/3836] eta: 0:00:25 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/16 10:01:38 - mmengine - INFO - Epoch(val) [5][1700/3836] eta: 0:00:24 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 10:01:39 - mmengine - INFO - Epoch(val) [5][1800/3836] eta: 0:00:23 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 10:01:40 - mmengine - INFO - Epoch(val) [5][1900/3836] eta: 0:00:22 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 10:01:41 - mmengine - INFO - Epoch(val) [5][2000/3836] eta: 0:00:21 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 10:01:43 - mmengine - INFO - Epoch(val) [5][2100/3836] eta: 0:00:20 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 10:01:44 - mmengine - INFO - Epoch(val) [5][2200/3836] eta: 0:00:19 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 10:01:45 - mmengine - INFO - Epoch(val) [5][2300/3836] eta: 0:00:18 time: 0.0121 data_time: 0.0005 memory: 480 2022/09/16 10:01:46 - mmengine - INFO - Epoch(val) [5][2400/3836] eta: 0:00:18 time: 0.0131 data_time: 0.0005 memory: 480 2022/09/16 10:01:47 - mmengine - INFO - Epoch(val) [5][2500/3836] eta: 0:00:15 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 10:01:49 - mmengine - INFO - Epoch(val) [5][2600/3836] eta: 0:00:14 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 10:01:50 - mmengine - INFO - Epoch(val) [5][2700/3836] eta: 0:00:13 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/16 10:01:51 - mmengine - INFO - Epoch(val) [5][2800/3836] eta: 0:00:11 time: 0.0112 data_time: 0.0004 memory: 480 2022/09/16 10:01:52 - mmengine - INFO - Epoch(val) [5][2900/3836] eta: 0:00:10 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/16 10:01:53 - mmengine - INFO - Epoch(val) [5][3000/3836] eta: 0:00:09 time: 0.0116 data_time: 0.0006 memory: 480 2022/09/16 10:01:54 - mmengine - INFO - Epoch(val) [5][3100/3836] eta: 0:00:08 time: 0.0116 data_time: 0.0006 memory: 480 2022/09/16 10:01:55 - mmengine - INFO - Epoch(val) [5][3200/3836] eta: 0:00:07 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/16 10:01:57 - mmengine - INFO - Epoch(val) [5][3300/3836] eta: 0:00:06 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/16 10:01:58 - mmengine - INFO - Epoch(val) [5][3400/3836] eta: 0:00:04 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/16 10:01:59 - mmengine - INFO - Epoch(val) [5][3500/3836] eta: 0:00:03 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/16 10:02:00 - mmengine - INFO - Epoch(val) [5][3600/3836] eta: 0:00:02 time: 0.0118 data_time: 0.0006 memory: 480 2022/09/16 10:02:01 - mmengine - INFO - Epoch(val) [5][3700/3836] eta: 0:00:01 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/16 10:02:03 - mmengine - INFO - Epoch(val) [5][3800/3836] eta: 0:00:00 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 10:02:03 - mmengine - INFO - Epoch(val) [5][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.7778 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9243 SVT/recog/word_acc_ignore_case_symbol: 0.8671 SVTP/recog/word_acc_ignore_case_symbol: 0.7736 IC13/recog/word_acc_ignore_case_symbol: 0.8887 IC15/recog/word_acc_ignore_case_symbol: 0.7289 2022/09/16 10:04:20 - mmengine - INFO - Epoch(train) [6][100/10520] lr: 1.0000e-04 eta: 2 days, 7:17:55 time: 1.3397 data_time: 0.3090 memory: 56769 loss_visual: 0.0763 loss: 0.0763 2022/09/16 10:06:28 - mmengine - INFO - Epoch(train) [6][200/10520] lr: 1.0000e-04 eta: 2 days, 7:15:56 time: 1.8751 data_time: 0.5153 memory: 56769 loss_visual: 0.0835 loss: 0.0835 2022/09/16 10:08:32 - mmengine - INFO - Epoch(train) [6][300/10520] lr: 1.0000e-04 eta: 2 days, 7:13:42 time: 1.5794 data_time: 0.4308 memory: 56769 loss_visual: 0.0810 loss: 0.0810 2022/09/16 10:10:36 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 10:10:36 - mmengine - INFO - Epoch(train) [6][400/10520] lr: 1.0000e-04 eta: 2 days, 7:11:28 time: 1.0384 data_time: 0.2203 memory: 56769 loss_visual: 0.0810 loss: 0.0810 2022/09/16 10:12:41 - mmengine - INFO - Epoch(train) [6][500/10520] lr: 1.0000e-04 eta: 2 days, 7:09:17 time: 0.9833 data_time: 0.1232 memory: 56769 loss_visual: 0.0778 loss: 0.0778 2022/09/16 10:14:44 - mmengine - INFO - Epoch(train) [6][600/10520] lr: 1.0000e-04 eta: 2 days, 7:07:03 time: 0.8277 data_time: 0.0077 memory: 56769 loss_visual: 0.0771 loss: 0.0771 2022/09/16 10:16:49 - mmengine - INFO - Epoch(train) [6][700/10520] lr: 1.0000e-04 eta: 2 days, 7:04:52 time: 0.8302 data_time: 0.0073 memory: 56769 loss_visual: 0.0869 loss: 0.0869 2022/09/16 10:18:53 - mmengine - INFO - Epoch(train) [6][800/10520] lr: 1.0000e-04 eta: 2 days, 7:02:39 time: 0.9015 data_time: 0.0069 memory: 56769 loss_visual: 0.0822 loss: 0.0822 2022/09/16 10:21:01 - mmengine - INFO - Epoch(train) [6][900/10520] lr: 1.0000e-04 eta: 2 days, 7:00:39 time: 1.3464 data_time: 0.3241 memory: 56769 loss_visual: 0.0769 loss: 0.0769 2022/09/16 10:23:10 - mmengine - INFO - Epoch(train) [6][1000/10520] lr: 1.0000e-04 eta: 2 days, 6:58:42 time: 1.8925 data_time: 0.5371 memory: 56769 loss_visual: 0.0835 loss: 0.0835 2022/09/16 10:25:15 - mmengine - INFO - Epoch(train) [6][1100/10520] lr: 1.0000e-04 eta: 2 days, 6:56:32 time: 1.5729 data_time: 0.4323 memory: 56769 loss_visual: 0.0814 loss: 0.0814 2022/09/16 10:27:19 - mmengine - INFO - Epoch(train) [6][1200/10520] lr: 1.0000e-04 eta: 2 days, 6:54:19 time: 1.0692 data_time: 0.2207 memory: 56769 loss_visual: 0.0806 loss: 0.0806 2022/09/16 10:29:22 - mmengine - INFO - Epoch(train) [6][1300/10520] lr: 1.0000e-04 eta: 2 days, 6:52:02 time: 0.9573 data_time: 0.0911 memory: 56769 loss_visual: 0.0805 loss: 0.0805 2022/09/16 10:31:25 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 10:31:25 - mmengine - INFO - Epoch(train) [6][1400/10520] lr: 1.0000e-04 eta: 2 days, 6:49:48 time: 0.9079 data_time: 0.0104 memory: 56769 loss_visual: 0.0819 loss: 0.0819 2022/09/16 10:33:30 - mmengine - INFO - Epoch(train) [6][1500/10520] lr: 1.0000e-04 eta: 2 days, 6:47:36 time: 0.8405 data_time: 0.0072 memory: 56769 loss_visual: 0.0841 loss: 0.0841 2022/09/16 10:35:36 - mmengine - INFO - Epoch(train) [6][1600/10520] lr: 1.0000e-04 eta: 2 days, 6:45:30 time: 0.9027 data_time: 0.0066 memory: 56769 loss_visual: 0.0817 loss: 0.0817 2022/09/16 10:37:46 - mmengine - INFO - Epoch(train) [6][1700/10520] lr: 1.0000e-04 eta: 2 days, 6:43:34 time: 1.3941 data_time: 0.2748 memory: 56769 loss_visual: 0.0858 loss: 0.0858 2022/09/16 10:39:55 - mmengine - INFO - Epoch(train) [6][1800/10520] lr: 1.0000e-04 eta: 2 days, 6:41:37 time: 1.8892 data_time: 0.5300 memory: 56769 loss_visual: 0.0794 loss: 0.0794 2022/09/16 10:42:01 - mmengine - INFO - Epoch(train) [6][1900/10520] lr: 1.0000e-04 eta: 2 days, 6:39:30 time: 1.6407 data_time: 0.4563 memory: 56769 loss_visual: 0.0809 loss: 0.0809 2022/09/16 10:44:08 - mmengine - INFO - Epoch(train) [6][2000/10520] lr: 1.0000e-04 eta: 2 days, 6:37:27 time: 1.0836 data_time: 0.2362 memory: 56769 loss_visual: 0.0821 loss: 0.0821 2022/09/16 10:46:13 - mmengine - INFO - Epoch(train) [6][2100/10520] lr: 1.0000e-04 eta: 2 days, 6:35:16 time: 0.9906 data_time: 0.1230 memory: 56769 loss_visual: 0.0798 loss: 0.0798 2022/09/16 10:48:18 - mmengine - INFO - Epoch(train) [6][2200/10520] lr: 1.0000e-04 eta: 2 days, 6:33:06 time: 0.8454 data_time: 0.0069 memory: 56769 loss_visual: 0.0822 loss: 0.0822 2022/09/16 10:50:23 - mmengine - INFO - Epoch(train) [6][2300/10520] lr: 1.0000e-04 eta: 2 days, 6:30:56 time: 0.9018 data_time: 0.0067 memory: 56769 loss_visual: 0.0792 loss: 0.0792 2022/09/16 10:52:27 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 10:52:27 - mmengine - INFO - Epoch(train) [6][2400/10520] lr: 1.0000e-04 eta: 2 days, 6:28:44 time: 0.8435 data_time: 0.0083 memory: 56769 loss_visual: 0.0875 loss: 0.0875 2022/09/16 10:54:38 - mmengine - INFO - Epoch(train) [6][2500/10520] lr: 1.0000e-04 eta: 2 days, 6:26:52 time: 1.3978 data_time: 0.3341 memory: 56769 loss_visual: 0.0799 loss: 0.0799 2022/09/16 10:56:48 - mmengine - INFO - Epoch(train) [6][2600/10520] lr: 1.0000e-04 eta: 2 days, 6:24:55 time: 1.9399 data_time: 0.5081 memory: 56769 loss_visual: 0.0822 loss: 0.0822 2022/09/16 10:58:53 - mmengine - INFO - Epoch(train) [6][2700/10520] lr: 1.0000e-04 eta: 2 days, 6:22:46 time: 1.6689 data_time: 0.5065 memory: 56769 loss_visual: 0.0798 loss: 0.0798 2022/09/16 11:01:00 - mmengine - INFO - Epoch(train) [6][2800/10520] lr: 1.0000e-04 eta: 2 days, 6:20:43 time: 1.0799 data_time: 0.2517 memory: 56769 loss_visual: 0.0787 loss: 0.0787 2022/09/16 11:03:06 - mmengine - INFO - Epoch(train) [6][2900/10520] lr: 1.0000e-04 eta: 2 days, 6:18:34 time: 0.9408 data_time: 0.1231 memory: 56769 loss_visual: 0.0817 loss: 0.0817 2022/09/16 11:05:10 - mmengine - INFO - Epoch(train) [6][3000/10520] lr: 1.0000e-04 eta: 2 days, 6:16:22 time: 0.8265 data_time: 0.0068 memory: 56769 loss_visual: 0.0813 loss: 0.0813 2022/09/16 11:07:14 - mmengine - INFO - Epoch(train) [6][3100/10520] lr: 1.0000e-04 eta: 2 days, 6:14:10 time: 0.8318 data_time: 0.0069 memory: 56769 loss_visual: 0.0758 loss: 0.0758 2022/09/16 11:09:18 - mmengine - INFO - Epoch(train) [6][3200/10520] lr: 1.0000e-04 eta: 2 days, 6:11:57 time: 0.8687 data_time: 0.0067 memory: 56769 loss_visual: 0.0798 loss: 0.0798 2022/09/16 11:11:28 - mmengine - INFO - Epoch(train) [6][3300/10520] lr: 1.0000e-04 eta: 2 days, 6:10:02 time: 1.4151 data_time: 0.2922 memory: 56769 loss_visual: 0.0788 loss: 0.0788 2022/09/16 11:13:39 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 11:13:39 - mmengine - INFO - Epoch(train) [6][3400/10520] lr: 1.0000e-04 eta: 2 days, 6:08:09 time: 1.9681 data_time: 0.5540 memory: 56769 loss_visual: 0.0806 loss: 0.0806 2022/09/16 11:15:45 - mmengine - INFO - Epoch(train) [6][3500/10520] lr: 1.0000e-04 eta: 2 days, 6:06:03 time: 1.7108 data_time: 0.4313 memory: 56769 loss_visual: 0.0765 loss: 0.0765 2022/09/16 11:17:53 - mmengine - INFO - Epoch(train) [6][3600/10520] lr: 1.0000e-04 eta: 2 days, 6:04:00 time: 1.0616 data_time: 0.2437 memory: 56769 loss_visual: 0.0815 loss: 0.0815 2022/09/16 11:19:58 - mmengine - INFO - Epoch(train) [6][3700/10520] lr: 1.0000e-04 eta: 2 days, 6:01:52 time: 0.9692 data_time: 0.1112 memory: 56769 loss_visual: 0.0831 loss: 0.0831 2022/09/16 11:22:04 - mmengine - INFO - Epoch(train) [6][3800/10520] lr: 1.0000e-04 eta: 2 days, 5:59:43 time: 0.8793 data_time: 0.0072 memory: 56769 loss_visual: 0.0785 loss: 0.0785 2022/09/16 11:24:10 - mmengine - INFO - Epoch(train) [6][3900/10520] lr: 1.0000e-04 eta: 2 days, 5:57:37 time: 0.8624 data_time: 0.0073 memory: 56769 loss_visual: 0.0777 loss: 0.0777 2022/09/16 11:26:15 - mmengine - INFO - Epoch(train) [6][4000/10520] lr: 1.0000e-04 eta: 2 days, 5:55:27 time: 0.8447 data_time: 0.0068 memory: 56769 loss_visual: 0.0798 loss: 0.0798 2022/09/16 11:28:26 - mmengine - INFO - Epoch(train) [6][4100/10520] lr: 1.0000e-04 eta: 2 days, 5:53:34 time: 1.4005 data_time: 0.3247 memory: 56769 loss_visual: 0.0781 loss: 0.0781 2022/09/16 11:30:37 - mmengine - INFO - Epoch(train) [6][4200/10520] lr: 1.0000e-04 eta: 2 days, 5:51:40 time: 1.9705 data_time: 0.5193 memory: 56769 loss_visual: 0.0773 loss: 0.0773 2022/09/16 11:32:41 - mmengine - INFO - Epoch(train) [6][4300/10520] lr: 1.0000e-04 eta: 2 days, 5:49:29 time: 1.6672 data_time: 0.4824 memory: 56769 loss_visual: 0.0787 loss: 0.0787 2022/09/16 11:34:47 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 11:34:47 - mmengine - INFO - Epoch(train) [6][4400/10520] lr: 1.0000e-04 eta: 2 days, 5:47:20 time: 1.0793 data_time: 0.2226 memory: 56769 loss_visual: 0.0821 loss: 0.0821 2022/09/16 11:36:51 - mmengine - INFO - Epoch(train) [6][4500/10520] lr: 1.0000e-04 eta: 2 days, 5:45:09 time: 0.9427 data_time: 0.1232 memory: 56769 loss_visual: 0.0842 loss: 0.0842 2022/09/16 11:38:55 - mmengine - INFO - Epoch(train) [6][4600/10520] lr: 1.0000e-04 eta: 2 days, 5:42:57 time: 0.8278 data_time: 0.0068 memory: 56769 loss_visual: 0.0816 loss: 0.0816 2022/09/16 11:41:01 - mmengine - INFO - Epoch(train) [6][4700/10520] lr: 1.0000e-04 eta: 2 days, 5:40:50 time: 0.8840 data_time: 0.0068 memory: 56769 loss_visual: 0.0785 loss: 0.0785 2022/09/16 11:43:07 - mmengine - INFO - Epoch(train) [6][4800/10520] lr: 1.0000e-04 eta: 2 days, 5:38:44 time: 0.9310 data_time: 0.0078 memory: 56769 loss_visual: 0.0836 loss: 0.0836 2022/09/16 11:45:20 - mmengine - INFO - Epoch(train) [6][4900/10520] lr: 1.0000e-04 eta: 2 days, 5:36:55 time: 1.3247 data_time: 0.2524 memory: 56769 loss_visual: 0.0751 loss: 0.0751 2022/09/16 11:47:32 - mmengine - INFO - Epoch(train) [6][5000/10520] lr: 1.0000e-04 eta: 2 days, 5:35:03 time: 1.9807 data_time: 0.5581 memory: 56769 loss_visual: 0.0826 loss: 0.0826 2022/09/16 11:49:38 - mmengine - INFO - Epoch(train) [6][5100/10520] lr: 1.0000e-04 eta: 2 days, 5:32:57 time: 1.6982 data_time: 0.4564 memory: 56769 loss_visual: 0.0807 loss: 0.0807 2022/09/16 11:51:44 - mmengine - INFO - Epoch(train) [6][5200/10520] lr: 1.0000e-04 eta: 2 days, 5:30:51 time: 1.0976 data_time: 0.2039 memory: 56769 loss_visual: 0.0730 loss: 0.0730 2022/09/16 11:53:52 - mmengine - INFO - Epoch(train) [6][5300/10520] lr: 1.0000e-04 eta: 2 days, 5:28:49 time: 1.1928 data_time: 0.2141 memory: 56769 loss_visual: 0.0775 loss: 0.0775 2022/09/16 11:55:58 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 11:55:58 - mmengine - INFO - Epoch(train) [6][5400/10520] lr: 1.0000e-04 eta: 2 days, 5:26:41 time: 0.8612 data_time: 0.0065 memory: 56769 loss_visual: 0.0833 loss: 0.0833 2022/09/16 11:58:03 - mmengine - INFO - Epoch(train) [6][5500/10520] lr: 1.0000e-04 eta: 2 days, 5:24:32 time: 0.8768 data_time: 0.0067 memory: 56769 loss_visual: 0.0799 loss: 0.0799 2022/09/16 12:00:18 - mmengine - INFO - Epoch(train) [6][5600/10520] lr: 1.0000e-04 eta: 2 days, 5:22:48 time: 0.8583 data_time: 0.0067 memory: 56769 loss_visual: 0.0817 loss: 0.0817 2022/09/16 12:02:28 - mmengine - INFO - Epoch(train) [6][5700/10520] lr: 1.0000e-04 eta: 2 days, 5:20:52 time: 1.3370 data_time: 0.2558 memory: 56769 loss_visual: 0.0816 loss: 0.0816 2022/09/16 12:04:40 - mmengine - INFO - Epoch(train) [6][5800/10520] lr: 1.0000e-04 eta: 2 days, 5:19:01 time: 1.9401 data_time: 0.5704 memory: 56769 loss_visual: 0.0833 loss: 0.0833 2022/09/16 12:06:48 - mmengine - INFO - Epoch(train) [6][5900/10520] lr: 1.0000e-04 eta: 2 days, 5:16:59 time: 1.8182 data_time: 0.5105 memory: 56769 loss_visual: 0.0782 loss: 0.0782 2022/09/16 12:08:57 - mmengine - INFO - Epoch(train) [6][6000/10520] lr: 1.0000e-04 eta: 2 days, 5:15:00 time: 1.1324 data_time: 0.2831 memory: 56769 loss_visual: 0.0792 loss: 0.0792 2022/09/16 12:11:01 - mmengine - INFO - Epoch(train) [6][6100/10520] lr: 1.0000e-04 eta: 2 days, 5:12:47 time: 0.9402 data_time: 0.1180 memory: 56769 loss_visual: 0.0810 loss: 0.0810 2022/09/16 12:13:05 - mmengine - INFO - Epoch(train) [6][6200/10520] lr: 1.0000e-04 eta: 2 days, 5:10:35 time: 0.8567 data_time: 0.0070 memory: 56769 loss_visual: 0.0748 loss: 0.0748 2022/09/16 12:15:09 - mmengine - INFO - Epoch(train) [6][6300/10520] lr: 1.0000e-04 eta: 2 days, 5:08:23 time: 0.8641 data_time: 0.0076 memory: 56769 loss_visual: 0.0840 loss: 0.0840 2022/09/16 12:17:12 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 12:17:12 - mmengine - INFO - Epoch(train) [6][6400/10520] lr: 1.0000e-04 eta: 2 days, 5:06:09 time: 0.8606 data_time: 0.0067 memory: 56769 loss_visual: 0.0830 loss: 0.0830 2022/09/16 12:19:21 - mmengine - INFO - Epoch(train) [6][6500/10520] lr: 1.0000e-04 eta: 2 days, 5:04:08 time: 1.2886 data_time: 0.2815 memory: 56769 loss_visual: 0.0796 loss: 0.0796 2022/09/16 12:21:30 - mmengine - INFO - Epoch(train) [6][6600/10520] lr: 1.0000e-04 eta: 2 days, 5:02:09 time: 1.8083 data_time: 0.4702 memory: 56769 loss_visual: 0.0788 loss: 0.0788 2022/09/16 12:23:37 - mmengine - INFO - Epoch(train) [6][6700/10520] lr: 1.0000e-04 eta: 2 days, 5:00:05 time: 1.7628 data_time: 0.4571 memory: 56769 loss_visual: 0.0771 loss: 0.0771 2022/09/16 12:25:43 - mmengine - INFO - Epoch(train) [6][6800/10520] lr: 1.0000e-04 eta: 2 days, 4:57:58 time: 1.1320 data_time: 0.2965 memory: 56769 loss_visual: 0.0776 loss: 0.0776 2022/09/16 12:27:48 - mmengine - INFO - Epoch(train) [6][6900/10520] lr: 1.0000e-04 eta: 2 days, 4:55:47 time: 0.9572 data_time: 0.1133 memory: 56769 loss_visual: 0.0772 loss: 0.0772 2022/09/16 12:29:53 - mmengine - INFO - Epoch(train) [6][7000/10520] lr: 1.0000e-04 eta: 2 days, 4:53:39 time: 0.8957 data_time: 0.0075 memory: 56769 loss_visual: 0.0787 loss: 0.0787 2022/09/16 12:31:59 - mmengine - INFO - Epoch(train) [6][7100/10520] lr: 1.0000e-04 eta: 2 days, 4:51:31 time: 0.8947 data_time: 0.0070 memory: 56769 loss_visual: 0.0786 loss: 0.0786 2022/09/16 12:34:03 - mmengine - INFO - Epoch(train) [6][7200/10520] lr: 1.0000e-04 eta: 2 days, 4:49:20 time: 0.8655 data_time: 0.0099 memory: 56769 loss_visual: 0.0796 loss: 0.0796 2022/09/16 12:36:14 - mmengine - INFO - Epoch(train) [6][7300/10520] lr: 1.0000e-04 eta: 2 days, 4:47:26 time: 1.4198 data_time: 0.2923 memory: 56769 loss_visual: 0.0844 loss: 0.0844 2022/09/16 12:38:25 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 12:38:25 - mmengine - INFO - Epoch(train) [6][7400/10520] lr: 1.0000e-04 eta: 2 days, 4:45:30 time: 1.7971 data_time: 0.4249 memory: 56769 loss_visual: 0.0761 loss: 0.0761 2022/09/16 12:40:30 - mmengine - INFO - Epoch(train) [6][7500/10520] lr: 1.0000e-04 eta: 2 days, 4:43:21 time: 1.6905 data_time: 0.4658 memory: 56769 loss_visual: 0.0783 loss: 0.0783 2022/09/16 12:42:36 - mmengine - INFO - Epoch(train) [6][7600/10520] lr: 1.0000e-04 eta: 2 days, 4:41:14 time: 1.1395 data_time: 0.2762 memory: 56769 loss_visual: 0.0800 loss: 0.0800 2022/09/16 12:44:40 - mmengine - INFO - Epoch(train) [6][7700/10520] lr: 1.0000e-04 eta: 2 days, 4:39:01 time: 0.9542 data_time: 0.1250 memory: 56769 loss_visual: 0.0766 loss: 0.0766 2022/09/16 12:46:45 - mmengine - INFO - Epoch(train) [6][7800/10520] lr: 1.0000e-04 eta: 2 days, 4:36:51 time: 0.8863 data_time: 0.0065 memory: 56769 loss_visual: 0.0813 loss: 0.0813 2022/09/16 12:48:51 - mmengine - INFO - Epoch(train) [6][7900/10520] lr: 1.0000e-04 eta: 2 days, 4:34:44 time: 0.8840 data_time: 0.0071 memory: 56769 loss_visual: 0.0815 loss: 0.0815 2022/09/16 12:50:56 - mmengine - INFO - Epoch(train) [6][8000/10520] lr: 1.0000e-04 eta: 2 days, 4:32:35 time: 0.8273 data_time: 0.0068 memory: 56769 loss_visual: 0.0779 loss: 0.0779 2022/09/16 12:53:04 - mmengine - INFO - Epoch(train) [6][8100/10520] lr: 1.0000e-04 eta: 2 days, 4:30:33 time: 1.2384 data_time: 0.2888 memory: 56769 loss_visual: 0.0808 loss: 0.0808 2022/09/16 12:55:13 - mmengine - INFO - Epoch(train) [6][8200/10520] lr: 1.0000e-04 eta: 2 days, 4:28:35 time: 1.8066 data_time: 0.4461 memory: 56769 loss_visual: 0.0761 loss: 0.0761 2022/09/16 12:57:19 - mmengine - INFO - Epoch(train) [6][8300/10520] lr: 1.0000e-04 eta: 2 days, 4:26:27 time: 1.6636 data_time: 0.4575 memory: 56769 loss_visual: 0.0776 loss: 0.0776 2022/09/16 12:59:24 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 12:59:24 - mmengine - INFO - Epoch(train) [6][8400/10520] lr: 1.0000e-04 eta: 2 days, 4:24:18 time: 1.1001 data_time: 0.2773 memory: 56769 loss_visual: 0.0789 loss: 0.0789 2022/09/16 13:01:30 - mmengine - INFO - Epoch(train) [6][8500/10520] lr: 1.0000e-04 eta: 2 days, 4:22:10 time: 0.9674 data_time: 0.1242 memory: 56769 loss_visual: 0.0832 loss: 0.0832 2022/09/16 13:03:35 - mmengine - INFO - Epoch(train) [6][8600/10520] lr: 1.0000e-04 eta: 2 days, 4:20:00 time: 0.8861 data_time: 0.0086 memory: 56769 loss_visual: 0.0785 loss: 0.0785 2022/09/16 13:05:42 - mmengine - INFO - Epoch(train) [6][8700/10520] lr: 1.0000e-04 eta: 2 days, 4:17:58 time: 1.0132 data_time: 0.0075 memory: 56769 loss_visual: 0.0821 loss: 0.0821 2022/09/16 13:07:49 - mmengine - INFO - Epoch(train) [6][8800/10520] lr: 1.0000e-04 eta: 2 days, 4:15:51 time: 0.8470 data_time: 0.0267 memory: 56769 loss_visual: 0.0785 loss: 0.0785 2022/09/16 13:09:55 - mmengine - INFO - Epoch(train) [6][8900/10520] lr: 1.0000e-04 eta: 2 days, 4:13:46 time: 1.1255 data_time: 0.2330 memory: 56769 loss_visual: 0.0788 loss: 0.0788 2022/09/16 13:12:05 - mmengine - INFO - Epoch(train) [6][9000/10520] lr: 1.0000e-04 eta: 2 days, 4:11:46 time: 1.6732 data_time: 0.4327 memory: 56769 loss_visual: 0.0808 loss: 0.0808 2022/09/16 13:14:13 - mmengine - INFO - Epoch(train) [6][9100/10520] lr: 1.0000e-04 eta: 2 days, 4:09:46 time: 1.5351 data_time: 0.4076 memory: 56769 loss_visual: 0.0803 loss: 0.0803 2022/09/16 13:16:24 - mmengine - INFO - Epoch(train) [6][9200/10520] lr: 1.0000e-04 eta: 2 days, 4:07:50 time: 1.1945 data_time: 0.3438 memory: 56769 loss_visual: 0.0756 loss: 0.0756 2022/09/16 13:18:34 - mmengine - INFO - Epoch(train) [6][9300/10520] lr: 1.0000e-04 eta: 2 days, 4:05:53 time: 1.1411 data_time: 0.1545 memory: 56769 loss_visual: 0.0802 loss: 0.0802 2022/09/16 13:20:44 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 13:20:44 - mmengine - INFO - Epoch(train) [6][9400/10520] lr: 1.0000e-04 eta: 2 days, 4:03:55 time: 1.1724 data_time: 0.0081 memory: 56769 loss_visual: 0.0785 loss: 0.0785 2022/09/16 13:22:50 - mmengine - INFO - Epoch(train) [6][9500/10520] lr: 1.0000e-04 eta: 2 days, 4:01:49 time: 1.0394 data_time: 0.0568 memory: 56769 loss_visual: 0.0787 loss: 0.0787 2022/09/16 13:24:58 - mmengine - INFO - Epoch(train) [6][9600/10520] lr: 1.0000e-04 eta: 2 days, 3:59:47 time: 0.9469 data_time: 0.0567 memory: 56769 loss_visual: 0.0803 loss: 0.0803 2022/09/16 13:27:06 - mmengine - INFO - Epoch(train) [6][9700/10520] lr: 1.0000e-04 eta: 2 days, 3:57:45 time: 1.1383 data_time: 0.1926 memory: 56769 loss_visual: 0.0816 loss: 0.0816 2022/09/16 13:29:17 - mmengine - INFO - Epoch(train) [6][9800/10520] lr: 1.0000e-04 eta: 2 days, 3:55:48 time: 1.4901 data_time: 0.3250 memory: 56769 loss_visual: 0.0802 loss: 0.0802 2022/09/16 13:31:26 - mmengine - INFO - Epoch(train) [6][9900/10520] lr: 1.0000e-04 eta: 2 days, 3:53:48 time: 1.6294 data_time: 0.4558 memory: 56769 loss_visual: 0.0832 loss: 0.0832 2022/09/16 13:33:35 - mmengine - INFO - Epoch(train) [6][10000/10520] lr: 1.0000e-04 eta: 2 days, 3:51:49 time: 1.2559 data_time: 0.4139 memory: 56769 loss_visual: 0.0735 loss: 0.0735 2022/09/16 13:35:44 - mmengine - INFO - Epoch(train) [6][10100/10520] lr: 1.0000e-04 eta: 2 days, 3:49:48 time: 1.1379 data_time: 0.1397 memory: 56769 loss_visual: 0.0755 loss: 0.0755 2022/09/16 13:37:52 - mmengine - INFO - Epoch(train) [6][10200/10520] lr: 1.0000e-04 eta: 2 days, 3:47:47 time: 1.1498 data_time: 0.0070 memory: 56769 loss_visual: 0.0764 loss: 0.0764 2022/09/16 13:39:59 - mmengine - INFO - Epoch(train) [6][10300/10520] lr: 1.0000e-04 eta: 2 days, 3:45:42 time: 1.0460 data_time: 0.0225 memory: 56769 loss_visual: 0.0796 loss: 0.0796 2022/09/16 13:42:06 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 13:42:06 - mmengine - INFO - Epoch(train) [6][10400/10520] lr: 1.0000e-04 eta: 2 days, 3:43:36 time: 0.8834 data_time: 0.0565 memory: 56769 loss_visual: 0.0790 loss: 0.0790 2022/09/16 13:44:10 - mmengine - INFO - Epoch(train) [6][10500/10520] lr: 1.0000e-04 eta: 2 days, 3:41:25 time: 0.9922 data_time: 0.1564 memory: 56769 loss_visual: 0.0731 loss: 0.0731 2022/09/16 13:44:32 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 13:44:32 - mmengine - INFO - Saving checkpoint at 6 epochs 2022/09/16 13:44:52 - mmengine - INFO - Epoch(val) [6][100/3836] eta: 0:04:55 time: 0.0791 data_time: 0.0006 memory: 56769 2022/09/16 13:44:57 - mmengine - INFO - Epoch(val) [6][200/3836] eta: 0:00:39 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/16 13:44:58 - mmengine - INFO - Epoch(val) [6][300/3836] eta: 0:00:40 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 13:45:00 - mmengine - INFO - Epoch(val) [6][400/3836] eta: 0:00:39 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 13:45:01 - mmengine - INFO - Epoch(val) [6][500/3836] eta: 0:00:41 time: 0.0123 data_time: 0.0006 memory: 480 2022/09/16 13:45:02 - mmengine - INFO - Epoch(val) [6][600/3836] eta: 0:00:37 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 13:45:03 - mmengine - INFO - Epoch(val) [6][700/3836] eta: 0:00:36 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 13:45:04 - mmengine - INFO - Epoch(val) [6][800/3836] eta: 0:00:36 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/16 13:45:06 - mmengine - INFO - Epoch(val) [6][900/3836] eta: 0:00:32 time: 0.0110 data_time: 0.0005 memory: 480 2022/09/16 13:45:07 - mmengine - INFO - Epoch(val) [6][1000/3836] eta: 0:00:32 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 13:45:08 - mmengine - INFO - Epoch(val) [6][1100/3836] eta: 0:00:31 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 13:45:09 - mmengine - INFO - Epoch(val) [6][1200/3836] eta: 0:00:30 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/16 13:45:10 - mmengine - INFO - Epoch(val) [6][1300/3836] eta: 0:00:29 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 13:45:11 - mmengine - INFO - Epoch(val) [6][1400/3836] eta: 0:00:27 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/16 13:45:13 - mmengine - INFO - Epoch(val) [6][1500/3836] eta: 0:00:26 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 13:45:14 - mmengine - INFO - Epoch(val) [6][1600/3836] eta: 0:00:29 time: 0.0132 data_time: 0.0013 memory: 480 2022/09/16 13:45:15 - mmengine - INFO - Epoch(val) [6][1700/3836] eta: 0:00:24 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/16 13:45:16 - mmengine - INFO - Epoch(val) [6][1800/3836] eta: 0:00:23 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 13:45:17 - mmengine - INFO - Epoch(val) [6][1900/3836] eta: 0:00:22 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 13:45:19 - mmengine - INFO - Epoch(val) [6][2000/3836] eta: 0:00:21 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 13:45:20 - mmengine - INFO - Epoch(val) [6][2100/3836] eta: 0:00:19 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/16 13:45:21 - mmengine - INFO - Epoch(val) [6][2200/3836] eta: 0:00:19 time: 0.0120 data_time: 0.0008 memory: 480 2022/09/16 13:45:22 - mmengine - INFO - Epoch(val) [6][2300/3836] eta: 0:00:17 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/16 13:45:23 - mmengine - INFO - Epoch(val) [6][2400/3836] eta: 0:00:16 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 13:45:25 - mmengine - INFO - Epoch(val) [6][2500/3836] eta: 0:00:15 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 13:45:26 - mmengine - INFO - Epoch(val) [6][2600/3836] eta: 0:00:13 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/16 13:45:27 - mmengine - INFO - Epoch(val) [6][2700/3836] eta: 0:00:13 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/16 13:45:28 - mmengine - INFO - Epoch(val) [6][2800/3836] eta: 0:00:11 time: 0.0113 data_time: 0.0004 memory: 480 2022/09/16 13:45:29 - mmengine - INFO - Epoch(val) [6][2900/3836] eta: 0:00:10 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/16 13:45:30 - mmengine - INFO - Epoch(val) [6][3000/3836] eta: 0:00:10 time: 0.0126 data_time: 0.0005 memory: 480 2022/09/16 13:45:32 - mmengine - INFO - Epoch(val) [6][3100/3836] eta: 0:00:11 time: 0.0159 data_time: 0.0006 memory: 480 2022/09/16 13:45:33 - mmengine - INFO - Epoch(val) [6][3200/3836] eta: 0:00:06 time: 0.0107 data_time: 0.0005 memory: 480 2022/09/16 13:45:34 - mmengine - INFO - Epoch(val) [6][3300/3836] eta: 0:00:06 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 13:45:35 - mmengine - INFO - Epoch(val) [6][3400/3836] eta: 0:00:04 time: 0.0107 data_time: 0.0004 memory: 480 2022/09/16 13:45:36 - mmengine - INFO - Epoch(val) [6][3500/3836] eta: 0:00:03 time: 0.0110 data_time: 0.0005 memory: 480 2022/09/16 13:45:37 - mmengine - INFO - Epoch(val) [6][3600/3836] eta: 0:00:02 time: 0.0107 data_time: 0.0004 memory: 480 2022/09/16 13:45:38 - mmengine - INFO - Epoch(val) [6][3700/3836] eta: 0:00:01 time: 0.0107 data_time: 0.0004 memory: 480 2022/09/16 13:45:39 - mmengine - INFO - Epoch(val) [6][3800/3836] eta: 0:00:00 time: 0.0107 data_time: 0.0004 memory: 480 2022/09/16 13:45:40 - mmengine - INFO - Epoch(val) [6][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.8125 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9270 SVT/recog/word_acc_ignore_case_symbol: 0.8733 SVTP/recog/word_acc_ignore_case_symbol: 0.7829 IC13/recog/word_acc_ignore_case_symbol: 0.9143 IC15/recog/word_acc_ignore_case_symbol: 0.7434 2022/09/16 13:48:03 - mmengine - INFO - Epoch(train) [7][100/10520] lr: 1.0000e-04 eta: 2 days, 3:39:24 time: 1.3443 data_time: 0.4280 memory: 56769 loss_visual: 0.0747 loss: 0.0747 2022/09/16 13:50:18 - mmengine - INFO - Epoch(train) [7][200/10520] lr: 1.0000e-04 eta: 2 days, 3:37:38 time: 2.1705 data_time: 0.7011 memory: 56769 loss_visual: 0.0753 loss: 0.0753 2022/09/16 13:52:28 - mmengine - INFO - Epoch(train) [7][300/10520] lr: 1.0000e-04 eta: 2 days, 3:35:39 time: 1.7392 data_time: 0.3428 memory: 56769 loss_visual: 0.0730 loss: 0.0730 2022/09/16 13:54:37 - mmengine - INFO - Epoch(train) [7][400/10520] lr: 1.0000e-04 eta: 2 days, 3:33:38 time: 1.2815 data_time: 0.4091 memory: 56769 loss_visual: 0.0775 loss: 0.0775 2022/09/16 13:56:44 - mmengine - INFO - Epoch(train) [7][500/10520] lr: 1.0000e-04 eta: 2 days, 3:31:35 time: 0.8593 data_time: 0.0066 memory: 56769 loss_visual: 0.0784 loss: 0.0784 2022/09/16 13:58:52 - mmengine - INFO - Epoch(train) [7][600/10520] lr: 1.0000e-04 eta: 2 days, 3:29:32 time: 0.9092 data_time: 0.0080 memory: 56769 loss_visual: 0.0782 loss: 0.0782 2022/09/16 14:01:01 - mmengine - INFO - Epoch(train) [7][700/10520] lr: 1.0000e-04 eta: 2 days, 3:27:30 time: 1.0398 data_time: 0.0069 memory: 56769 loss_visual: 0.0781 loss: 0.0781 2022/09/16 14:03:09 - mmengine - INFO - Epoch(train) [7][800/10520] lr: 1.0000e-04 eta: 2 days, 3:25:29 time: 0.8925 data_time: 0.0068 memory: 56769 loss_visual: 0.0768 loss: 0.0768 2022/09/16 14:04:58 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 14:05:22 - mmengine - INFO - Epoch(train) [7][900/10520] lr: 1.0000e-04 eta: 2 days, 3:23:37 time: 1.3363 data_time: 0.3941 memory: 56769 loss_visual: 0.0780 loss: 0.0780 2022/09/16 14:07:38 - mmengine - INFO - Epoch(train) [7][1000/10520] lr: 1.0000e-04 eta: 2 days, 3:21:53 time: 2.0803 data_time: 0.7098 memory: 56769 loss_visual: 0.0735 loss: 0.0735 2022/09/16 14:09:46 - mmengine - INFO - Epoch(train) [7][1100/10520] lr: 1.0000e-04 eta: 2 days, 3:19:51 time: 1.5783 data_time: 0.3466 memory: 56769 loss_visual: 0.0778 loss: 0.0778 2022/09/16 14:11:55 - mmengine - INFO - Epoch(train) [7][1200/10520] lr: 1.0000e-04 eta: 2 days, 3:17:49 time: 1.2017 data_time: 0.3508 memory: 56769 loss_visual: 0.0798 loss: 0.0798 2022/09/16 14:14:05 - mmengine - INFO - Epoch(train) [7][1300/10520] lr: 1.0000e-04 eta: 2 days, 3:15:51 time: 0.9782 data_time: 0.0065 memory: 56769 loss_visual: 0.0801 loss: 0.0801 2022/09/16 14:16:14 - mmengine - INFO - Epoch(train) [7][1400/10520] lr: 1.0000e-04 eta: 2 days, 3:13:51 time: 1.0088 data_time: 0.0072 memory: 56769 loss_visual: 0.0784 loss: 0.0784 2022/09/16 14:18:22 - mmengine - INFO - Epoch(train) [7][1500/10520] lr: 1.0000e-04 eta: 2 days, 3:11:48 time: 1.0255 data_time: 0.0071 memory: 56769 loss_visual: 0.0791 loss: 0.0791 2022/09/16 14:20:29 - mmengine - INFO - Epoch(train) [7][1600/10520] lr: 1.0000e-04 eta: 2 days, 3:09:43 time: 0.8297 data_time: 0.0082 memory: 56769 loss_visual: 0.0783 loss: 0.0783 2022/09/16 14:22:43 - mmengine - INFO - Epoch(train) [7][1700/10520] lr: 1.0000e-04 eta: 2 days, 3:07:52 time: 1.3682 data_time: 0.4219 memory: 56769 loss_visual: 0.0768 loss: 0.0768 2022/09/16 14:24:57 - mmengine - INFO - Epoch(train) [7][1800/10520] lr: 1.0000e-04 eta: 2 days, 3:06:02 time: 2.0590 data_time: 0.7411 memory: 56769 loss_visual: 0.0782 loss: 0.0782 2022/09/16 14:26:36 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 14:27:04 - mmengine - INFO - Epoch(train) [7][1900/10520] lr: 1.0000e-04 eta: 2 days, 3:03:59 time: 1.5084 data_time: 0.3714 memory: 56769 loss_visual: 0.0795 loss: 0.0795 2022/09/16 14:29:12 - mmengine - INFO - Epoch(train) [7][2000/10520] lr: 1.0000e-04 eta: 2 days, 3:01:55 time: 1.2596 data_time: 0.3886 memory: 56769 loss_visual: 0.0784 loss: 0.0784 2022/09/16 14:31:23 - mmengine - INFO - Epoch(train) [7][2100/10520] lr: 1.0000e-04 eta: 2 days, 2:59:58 time: 1.0456 data_time: 0.0088 memory: 56769 loss_visual: 0.0752 loss: 0.0752 2022/09/16 14:33:32 - mmengine - INFO - Epoch(train) [7][2200/10520] lr: 1.0000e-04 eta: 2 days, 2:57:56 time: 1.1331 data_time: 0.0069 memory: 56769 loss_visual: 0.0739 loss: 0.0739 2022/09/16 14:35:39 - mmengine - INFO - Epoch(train) [7][2300/10520] lr: 1.0000e-04 eta: 2 days, 2:55:53 time: 1.0648 data_time: 0.0069 memory: 56769 loss_visual: 0.0752 loss: 0.0752 2022/09/16 14:37:47 - mmengine - INFO - Epoch(train) [7][2400/10520] lr: 1.0000e-04 eta: 2 days, 2:53:49 time: 0.8315 data_time: 0.0076 memory: 56769 loss_visual: 0.0751 loss: 0.0751 2022/09/16 14:40:00 - mmengine - INFO - Epoch(train) [7][2500/10520] lr: 1.0000e-04 eta: 2 days, 2:51:56 time: 1.3833 data_time: 0.3415 memory: 56769 loss_visual: 0.0755 loss: 0.0755 2022/09/16 14:42:15 - mmengine - INFO - Epoch(train) [7][2600/10520] lr: 1.0000e-04 eta: 2 days, 2:50:08 time: 2.0241 data_time: 0.6915 memory: 56769 loss_visual: 0.0752 loss: 0.0752 2022/09/16 14:44:23 - mmengine - INFO - Epoch(train) [7][2700/10520] lr: 1.0000e-04 eta: 2 days, 2:48:05 time: 1.5937 data_time: 0.4070 memory: 56769 loss_visual: 0.0786 loss: 0.0786 2022/09/16 14:46:32 - mmengine - INFO - Epoch(train) [7][2800/10520] lr: 1.0000e-04 eta: 2 days, 2:46:04 time: 1.2021 data_time: 0.3731 memory: 56769 loss_visual: 0.0794 loss: 0.0794 2022/09/16 14:48:12 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 14:48:43 - mmengine - INFO - Epoch(train) [7][2900/10520] lr: 1.0000e-04 eta: 2 days, 2:44:09 time: 1.0318 data_time: 0.0071 memory: 56769 loss_visual: 0.0782 loss: 0.0782 2022/09/16 14:50:53 - mmengine - INFO - Epoch(train) [7][3000/10520] lr: 1.0000e-04 eta: 2 days, 2:42:09 time: 1.1425 data_time: 0.0069 memory: 56769 loss_visual: 0.0739 loss: 0.0739 2022/09/16 14:53:01 - mmengine - INFO - Epoch(train) [7][3100/10520] lr: 1.0000e-04 eta: 2 days, 2:40:06 time: 1.0637 data_time: 0.0070 memory: 56769 loss_visual: 0.0809 loss: 0.0809 2022/09/16 14:55:09 - mmengine - INFO - Epoch(train) [7][3200/10520] lr: 1.0000e-04 eta: 2 days, 2:38:03 time: 0.9208 data_time: 0.0068 memory: 56769 loss_visual: 0.0737 loss: 0.0737 2022/09/16 14:57:22 - mmengine - INFO - Epoch(train) [7][3300/10520] lr: 1.0000e-04 eta: 2 days, 2:36:09 time: 1.3118 data_time: 0.3576 memory: 56769 loss_visual: 0.0730 loss: 0.0730 2022/09/16 14:59:36 - mmengine - INFO - Epoch(train) [7][3400/10520] lr: 1.0000e-04 eta: 2 days, 2:34:19 time: 1.9548 data_time: 0.7019 memory: 56769 loss_visual: 0.0775 loss: 0.0775 2022/09/16 15:01:45 - mmengine - INFO - Epoch(train) [7][3500/10520] lr: 1.0000e-04 eta: 2 days, 2:32:17 time: 1.6067 data_time: 0.3937 memory: 56769 loss_visual: 0.0761 loss: 0.0761 2022/09/16 15:03:54 - mmengine - INFO - Epoch(train) [7][3600/10520] lr: 1.0000e-04 eta: 2 days, 2:30:17 time: 1.2711 data_time: 0.3872 memory: 56769 loss_visual: 0.0784 loss: 0.0784 2022/09/16 15:06:03 - mmengine - INFO - Epoch(train) [7][3700/10520] lr: 1.0000e-04 eta: 2 days, 2:28:16 time: 1.0364 data_time: 0.0069 memory: 56769 loss_visual: 0.0782 loss: 0.0782 2022/09/16 15:08:13 - mmengine - INFO - Epoch(train) [7][3800/10520] lr: 1.0000e-04 eta: 2 days, 2:26:17 time: 1.0883 data_time: 0.0076 memory: 56769 loss_visual: 0.0771 loss: 0.0771 2022/09/16 15:10:01 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 15:10:20 - mmengine - INFO - Epoch(train) [7][3900/10520] lr: 1.0000e-04 eta: 2 days, 2:24:11 time: 1.0378 data_time: 0.0068 memory: 56769 loss_visual: 0.0775 loss: 0.0775 2022/09/16 15:12:28 - mmengine - INFO - Epoch(train) [7][4000/10520] lr: 1.0000e-04 eta: 2 days, 2:22:07 time: 0.8411 data_time: 0.0070 memory: 56769 loss_visual: 0.0747 loss: 0.0747 2022/09/16 15:14:41 - mmengine - INFO - Epoch(train) [7][4100/10520] lr: 1.0000e-04 eta: 2 days, 2:20:14 time: 1.3062 data_time: 0.3452 memory: 56769 loss_visual: 0.0747 loss: 0.0747 2022/09/16 15:16:55 - mmengine - INFO - Epoch(train) [7][4200/10520] lr: 1.0000e-04 eta: 2 days, 2:18:24 time: 2.0061 data_time: 0.7073 memory: 56769 loss_visual: 0.0737 loss: 0.0737 2022/09/16 15:19:04 - mmengine - INFO - Epoch(train) [7][4300/10520] lr: 1.0000e-04 eta: 2 days, 2:16:22 time: 1.5498 data_time: 0.3747 memory: 56769 loss_visual: 0.0747 loss: 0.0747 2022/09/16 15:21:13 - mmengine - INFO - Epoch(train) [7][4400/10520] lr: 1.0000e-04 eta: 2 days, 2:14:21 time: 1.2463 data_time: 0.3882 memory: 56769 loss_visual: 0.0838 loss: 0.0838 2022/09/16 15:23:24 - mmengine - INFO - Epoch(train) [7][4500/10520] lr: 1.0000e-04 eta: 2 days, 2:12:23 time: 1.1152 data_time: 0.0080 memory: 56769 loss_visual: 0.0729 loss: 0.0729 2022/09/16 15:25:32 - mmengine - INFO - Epoch(train) [7][4600/10520] lr: 1.0000e-04 eta: 2 days, 2:10:20 time: 1.0925 data_time: 0.0072 memory: 56769 loss_visual: 0.0779 loss: 0.0779 2022/09/16 15:27:39 - mmengine - INFO - Epoch(train) [7][4700/10520] lr: 1.0000e-04 eta: 2 days, 2:08:13 time: 1.0670 data_time: 0.0070 memory: 56769 loss_visual: 0.0765 loss: 0.0765 2022/09/16 15:29:46 - mmengine - INFO - Epoch(train) [7][4800/10520] lr: 1.0000e-04 eta: 2 days, 2:06:08 time: 0.8484 data_time: 0.0079 memory: 56769 loss_visual: 0.0799 loss: 0.0799 2022/09/16 15:31:36 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 15:31:59 - mmengine - INFO - Epoch(train) [7][4900/10520] lr: 1.0000e-04 eta: 2 days, 2:04:14 time: 1.2783 data_time: 0.3432 memory: 56769 loss_visual: 0.0737 loss: 0.0737 2022/09/16 15:34:14 - mmengine - INFO - Epoch(train) [7][5000/10520] lr: 1.0000e-04 eta: 2 days, 2:02:26 time: 2.0611 data_time: 0.7441 memory: 56769 loss_visual: 0.0804 loss: 0.0804 2022/09/16 15:36:23 - mmengine - INFO - Epoch(train) [7][5100/10520] lr: 1.0000e-04 eta: 2 days, 2:00:23 time: 1.5855 data_time: 0.3999 memory: 56769 loss_visual: 0.0774 loss: 0.0774 2022/09/16 15:38:30 - mmengine - INFO - Epoch(train) [7][5200/10520] lr: 1.0000e-04 eta: 2 days, 1:58:18 time: 1.2540 data_time: 0.3722 memory: 56769 loss_visual: 0.0748 loss: 0.0748 2022/09/16 15:40:40 - mmengine - INFO - Epoch(train) [7][5300/10520] lr: 1.0000e-04 eta: 2 days, 1:56:19 time: 1.0294 data_time: 0.0065 memory: 56769 loss_visual: 0.0740 loss: 0.0740 2022/09/16 15:42:57 - mmengine - INFO - Epoch(train) [7][5400/10520] lr: 1.0000e-04 eta: 2 days, 1:54:33 time: 1.8817 data_time: 0.3654 memory: 56769 loss_visual: 0.0712 loss: 0.0712 2022/09/16 15:45:05 - mmengine - INFO - Epoch(train) [7][5500/10520] lr: 1.0000e-04 eta: 2 days, 1:52:29 time: 1.8712 data_time: 0.4086 memory: 56769 loss_visual: 0.0730 loss: 0.0730 2022/09/16 15:47:14 - mmengine - INFO - Epoch(train) [7][5600/10520] lr: 1.0000e-04 eta: 2 days, 1:50:28 time: 1.2581 data_time: 0.3993 memory: 56769 loss_visual: 0.0765 loss: 0.0765 2022/09/16 15:49:24 - mmengine - INFO - Epoch(train) [7][5700/10520] lr: 1.0000e-04 eta: 2 days, 1:48:28 time: 0.9449 data_time: 0.0064 memory: 56769 loss_visual: 0.0743 loss: 0.0743 2022/09/16 15:51:38 - mmengine - INFO - Epoch(train) [7][5800/10520] lr: 1.0000e-04 eta: 2 days, 1:46:35 time: 1.2959 data_time: 0.3289 memory: 56769 loss_visual: 0.0720 loss: 0.0720 2022/09/16 15:53:24 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 15:53:46 - mmengine - INFO - Epoch(train) [7][5900/10520] lr: 1.0000e-04 eta: 2 days, 1:44:32 time: 1.3697 data_time: 0.3199 memory: 56769 loss_visual: 0.0795 loss: 0.0795 2022/09/16 15:56:01 - mmengine - INFO - Epoch(train) [7][6000/10520] lr: 1.0000e-04 eta: 2 days, 1:42:42 time: 1.5443 data_time: 0.1749 memory: 56769 loss_visual: 0.0752 loss: 0.0752 2022/09/16 15:58:11 - mmengine - INFO - Epoch(train) [7][6100/10520] lr: 1.0000e-04 eta: 2 days, 1:40:43 time: 1.3280 data_time: 0.0070 memory: 56769 loss_visual: 0.0751 loss: 0.0751 2022/09/16 16:00:25 - mmengine - INFO - Epoch(train) [7][6200/10520] lr: 1.0000e-04 eta: 2 days, 1:38:50 time: 1.6387 data_time: 0.3606 memory: 56769 loss_visual: 0.0784 loss: 0.0784 2022/09/16 16:02:35 - mmengine - INFO - Epoch(train) [7][6300/10520] lr: 1.0000e-04 eta: 2 days, 1:36:51 time: 1.4057 data_time: 0.3943 memory: 56769 loss_visual: 0.0741 loss: 0.0741 2022/09/16 16:04:45 - mmengine - INFO - Epoch(train) [7][6400/10520] lr: 1.0000e-04 eta: 2 days, 1:34:50 time: 1.2365 data_time: 0.3240 memory: 56769 loss_visual: 0.0717 loss: 0.0717 2022/09/16 16:06:57 - mmengine - INFO - Epoch(train) [7][6500/10520] lr: 1.0000e-04 eta: 2 days, 1:32:54 time: 1.1124 data_time: 0.0070 memory: 56769 loss_visual: 0.0769 loss: 0.0769 2022/09/16 16:09:10 - mmengine - INFO - Epoch(train) [7][6600/10520] lr: 1.0000e-04 eta: 2 days, 1:31:01 time: 1.3706 data_time: 0.3290 memory: 56769 loss_visual: 0.0747 loss: 0.0747 2022/09/16 16:11:21 - mmengine - INFO - Epoch(train) [7][6700/10520] lr: 1.0000e-04 eta: 2 days, 1:29:02 time: 1.3563 data_time: 0.3065 memory: 56769 loss_visual: 0.0745 loss: 0.0745 2022/09/16 16:13:35 - mmengine - INFO - Epoch(train) [7][6800/10520] lr: 1.0000e-04 eta: 2 days, 1:27:09 time: 1.3884 data_time: 0.1673 memory: 56769 loss_visual: 0.0756 loss: 0.0756 2022/09/16 16:15:18 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 16:15:46 - mmengine - INFO - Epoch(train) [7][6900/10520] lr: 1.0000e-04 eta: 2 days, 1:25:11 time: 1.3540 data_time: 0.0257 memory: 56769 loss_visual: 0.0752 loss: 0.0752 2022/09/16 16:17:59 - mmengine - INFO - Epoch(train) [7][7000/10520] lr: 1.0000e-04 eta: 2 days, 1:23:18 time: 1.7178 data_time: 0.4295 memory: 56769 loss_visual: 0.0741 loss: 0.0741 2022/09/16 16:20:09 - mmengine - INFO - Epoch(train) [7][7100/10520] lr: 1.0000e-04 eta: 2 days, 1:21:18 time: 1.3900 data_time: 0.4022 memory: 56769 loss_visual: 0.0753 loss: 0.0753 2022/09/16 16:22:19 - mmengine - INFO - Epoch(train) [7][7200/10520] lr: 1.0000e-04 eta: 2 days, 1:19:17 time: 1.2649 data_time: 0.3294 memory: 56769 loss_visual: 0.0808 loss: 0.0808 2022/09/16 16:24:31 - mmengine - INFO - Epoch(train) [7][7300/10520] lr: 1.0000e-04 eta: 2 days, 1:17:21 time: 1.0824 data_time: 0.0068 memory: 56769 loss_visual: 0.0756 loss: 0.0756 2022/09/16 16:26:45 - mmengine - INFO - Epoch(train) [7][7400/10520] lr: 1.0000e-04 eta: 2 days, 1:15:27 time: 1.3702 data_time: 0.3488 memory: 56769 loss_visual: 0.0717 loss: 0.0717 2022/09/16 16:28:54 - mmengine - INFO - Epoch(train) [7][7500/10520] lr: 1.0000e-04 eta: 2 days, 1:13:26 time: 1.3355 data_time: 0.3194 memory: 56769 loss_visual: 0.0736 loss: 0.0736 2022/09/16 16:31:09 - mmengine - INFO - Epoch(train) [7][7600/10520] lr: 1.0000e-04 eta: 2 days, 1:11:36 time: 1.4492 data_time: 0.2023 memory: 56769 loss_visual: 0.0750 loss: 0.0750 2022/09/16 16:33:19 - mmengine - INFO - Epoch(train) [7][7700/10520] lr: 1.0000e-04 eta: 2 days, 1:09:34 time: 1.3665 data_time: 0.0237 memory: 56769 loss_visual: 0.0776 loss: 0.0776 2022/09/16 16:35:32 - mmengine - INFO - Epoch(train) [7][7800/10520] lr: 1.0000e-04 eta: 2 days, 1:07:40 time: 1.7067 data_time: 0.4487 memory: 56769 loss_visual: 0.0777 loss: 0.0777 2022/09/16 16:37:15 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 16:37:43 - mmengine - INFO - Epoch(train) [7][7900/10520] lr: 1.0000e-04 eta: 2 days, 1:05:41 time: 1.4313 data_time: 0.4145 memory: 56769 loss_visual: 0.0723 loss: 0.0723 2022/09/16 16:39:52 - mmengine - INFO - Epoch(train) [7][8000/10520] lr: 1.0000e-04 eta: 2 days, 1:03:39 time: 1.2626 data_time: 0.3563 memory: 56769 loss_visual: 0.0771 loss: 0.0771 2022/09/16 16:42:03 - mmengine - INFO - Epoch(train) [7][8100/10520] lr: 1.0000e-04 eta: 2 days, 1:01:40 time: 1.0663 data_time: 0.0066 memory: 56769 loss_visual: 0.0726 loss: 0.0726 2022/09/16 16:44:15 - mmengine - INFO - Epoch(train) [7][8200/10520] lr: 1.0000e-04 eta: 2 days, 0:59:43 time: 1.3246 data_time: 0.3041 memory: 56769 loss_visual: 0.0726 loss: 0.0726 2022/09/16 16:46:25 - mmengine - INFO - Epoch(train) [7][8300/10520] lr: 1.0000e-04 eta: 2 days, 0:57:43 time: 1.3380 data_time: 0.2952 memory: 56769 loss_visual: 0.0713 loss: 0.0713 2022/09/16 16:48:38 - mmengine - INFO - Epoch(train) [7][8400/10520] lr: 1.0000e-04 eta: 2 days, 0:55:48 time: 1.4191 data_time: 0.1923 memory: 56769 loss_visual: 0.0756 loss: 0.0756 2022/09/16 16:50:49 - mmengine - INFO - Epoch(train) [7][8500/10520] lr: 1.0000e-04 eta: 2 days, 0:53:48 time: 1.2732 data_time: 0.0575 memory: 56769 loss_visual: 0.0789 loss: 0.0789 2022/09/16 16:53:03 - mmengine - INFO - Epoch(train) [7][8600/10520] lr: 1.0000e-04 eta: 2 days, 0:51:55 time: 1.6397 data_time: 0.4224 memory: 56769 loss_visual: 0.0794 loss: 0.0794 2022/09/16 16:55:13 - mmengine - INFO - Epoch(train) [7][8700/10520] lr: 1.0000e-04 eta: 2 days, 0:49:55 time: 1.4452 data_time: 0.3838 memory: 56769 loss_visual: 0.0765 loss: 0.0765 2022/09/16 16:57:22 - mmengine - INFO - Epoch(train) [7][8800/10520] lr: 1.0000e-04 eta: 2 days, 0:47:53 time: 1.3323 data_time: 0.3808 memory: 56769 loss_visual: 0.0728 loss: 0.0728 2022/09/16 16:59:09 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 16:59:34 - mmengine - INFO - Epoch(train) [7][8900/10520] lr: 1.0000e-04 eta: 2 days, 0:45:55 time: 1.0187 data_time: 0.0066 memory: 56769 loss_visual: 0.0783 loss: 0.0783 2022/09/16 17:01:47 - mmengine - INFO - Epoch(train) [7][9000/10520] lr: 1.0000e-04 eta: 2 days, 0:44:00 time: 1.3391 data_time: 0.3325 memory: 56769 loss_visual: 0.0759 loss: 0.0759 2022/09/16 17:03:57 - mmengine - INFO - Epoch(train) [7][9100/10520] lr: 1.0000e-04 eta: 2 days, 0:41:58 time: 1.3652 data_time: 0.3337 memory: 56769 loss_visual: 0.0709 loss: 0.0709 2022/09/16 17:06:08 - mmengine - INFO - Epoch(train) [7][9200/10520] lr: 1.0000e-04 eta: 2 days, 0:40:01 time: 1.3385 data_time: 0.1691 memory: 56769 loss_visual: 0.0752 loss: 0.0752 2022/09/16 17:08:19 - mmengine - INFO - Epoch(train) [7][9300/10520] lr: 1.0000e-04 eta: 2 days, 0:38:01 time: 1.3533 data_time: 0.0220 memory: 56769 loss_visual: 0.0716 loss: 0.0716 2022/09/16 17:10:34 - mmengine - INFO - Epoch(train) [7][9400/10520] lr: 1.0000e-04 eta: 2 days, 0:36:09 time: 1.6887 data_time: 0.4403 memory: 56769 loss_visual: 0.0742 loss: 0.0742 2022/09/16 17:12:44 - mmengine - INFO - Epoch(train) [7][9500/10520] lr: 1.0000e-04 eta: 2 days, 0:34:09 time: 1.4626 data_time: 0.3768 memory: 56769 loss_visual: 0.0800 loss: 0.0800 2022/09/16 17:14:54 - mmengine - INFO - Epoch(train) [7][9600/10520] lr: 1.0000e-04 eta: 2 days, 0:32:08 time: 1.2738 data_time: 0.3439 memory: 56769 loss_visual: 0.0741 loss: 0.0741 2022/09/16 17:17:06 - mmengine - INFO - Epoch(train) [7][9700/10520] lr: 1.0000e-04 eta: 2 days, 0:30:10 time: 1.0380 data_time: 0.0068 memory: 56769 loss_visual: 0.0723 loss: 0.0723 2022/09/16 17:19:18 - mmengine - INFO - Epoch(train) [7][9800/10520] lr: 1.0000e-04 eta: 2 days, 0:28:13 time: 1.3650 data_time: 0.3243 memory: 56769 loss_visual: 0.0682 loss: 0.0682 2022/09/16 17:21:05 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 17:21:28 - mmengine - INFO - Epoch(train) [7][9900/10520] lr: 1.0000e-04 eta: 2 days, 0:26:11 time: 1.3697 data_time: 0.3215 memory: 56769 loss_visual: 0.0774 loss: 0.0774 2022/09/16 17:23:40 - mmengine - INFO - Epoch(train) [7][10000/10520] lr: 1.0000e-04 eta: 2 days, 0:24:15 time: 1.3290 data_time: 0.1538 memory: 56769 loss_visual: 0.0699 loss: 0.0699 2022/09/16 17:25:51 - mmengine - INFO - Epoch(train) [7][10100/10520] lr: 1.0000e-04 eta: 2 days, 0:22:15 time: 1.3148 data_time: 0.0234 memory: 56769 loss_visual: 0.0742 loss: 0.0742 2022/09/16 17:28:04 - mmengine - INFO - Epoch(train) [7][10200/10520] lr: 1.0000e-04 eta: 2 days, 0:20:19 time: 1.6143 data_time: 0.3976 memory: 56769 loss_visual: 0.0705 loss: 0.0705 2022/09/16 17:30:14 - mmengine - INFO - Epoch(train) [7][10300/10520] lr: 1.0000e-04 eta: 2 days, 0:18:18 time: 1.4110 data_time: 0.3989 memory: 56769 loss_visual: 0.0694 loss: 0.0694 2022/09/16 17:32:23 - mmengine - INFO - Epoch(train) [7][10400/10520] lr: 1.0000e-04 eta: 2 days, 0:16:15 time: 1.3065 data_time: 0.3615 memory: 56769 loss_visual: 0.0733 loss: 0.0733 2022/09/16 17:34:29 - mmengine - INFO - Epoch(train) [7][10500/10520] lr: 1.0000e-04 eta: 2 days, 0:14:06 time: 0.9611 data_time: 0.0060 memory: 56769 loss_visual: 0.0740 loss: 0.0740 2022/09/16 17:34:50 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 17:34:50 - mmengine - INFO - Saving checkpoint at 7 epochs 2022/09/16 17:35:11 - mmengine - INFO - Epoch(val) [7][100/3836] eta: 0:05:09 time: 0.0829 data_time: 0.0005 memory: 56769 2022/09/16 17:35:16 - mmengine - INFO - Epoch(val) [7][200/3836] eta: 0:00:42 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 17:35:17 - mmengine - INFO - Epoch(val) [7][300/3836] eta: 0:00:39 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/16 17:35:18 - mmengine - INFO - Epoch(val) [7][400/3836] eta: 0:00:39 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 17:35:20 - mmengine - INFO - Epoch(val) [7][500/3836] eta: 0:00:39 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/16 17:35:21 - mmengine - INFO - Epoch(val) [7][600/3836] eta: 0:00:38 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/16 17:35:22 - mmengine - INFO - Epoch(val) [7][700/3836] eta: 0:00:36 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 17:35:23 - mmengine - INFO - Epoch(val) [7][800/3836] eta: 0:00:35 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 17:35:24 - mmengine - INFO - Epoch(val) [7][900/3836] eta: 0:00:31 time: 0.0109 data_time: 0.0004 memory: 480 2022/09/16 17:35:26 - mmengine - INFO - Epoch(val) [7][1000/3836] eta: 0:00:30 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/16 17:35:27 - mmengine - INFO - Epoch(val) [7][1100/3836] eta: 0:00:32 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/16 17:35:28 - mmengine - INFO - Epoch(val) [7][1200/3836] eta: 0:00:30 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 17:35:29 - mmengine - INFO - Epoch(val) [7][1300/3836] eta: 0:00:29 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 17:35:30 - mmengine - INFO - Epoch(val) [7][1400/3836] eta: 0:00:29 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/16 17:35:31 - mmengine - INFO - Epoch(val) [7][1500/3836] eta: 0:00:26 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 17:35:33 - mmengine - INFO - Epoch(val) [7][1600/3836] eta: 0:00:25 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/16 17:35:34 - mmengine - INFO - Epoch(val) [7][1700/3836] eta: 0:00:26 time: 0.0123 data_time: 0.0006 memory: 480 2022/09/16 17:35:35 - mmengine - INFO - Epoch(val) [7][1800/3836] eta: 0:00:23 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 17:35:36 - mmengine - INFO - Epoch(val) [7][1900/3836] eta: 0:00:22 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 17:35:37 - mmengine - INFO - Epoch(val) [7][2000/3836] eta: 0:00:21 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 17:35:38 - mmengine - INFO - Epoch(val) [7][2100/3836] eta: 0:00:20 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 17:35:40 - mmengine - INFO - Epoch(val) [7][2200/3836] eta: 0:00:19 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/16 17:35:41 - mmengine - INFO - Epoch(val) [7][2300/3836] eta: 0:00:18 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/16 17:35:42 - mmengine - INFO - Epoch(val) [7][2400/3836] eta: 0:00:16 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 17:35:43 - mmengine - INFO - Epoch(val) [7][2500/3836] eta: 0:00:17 time: 0.0132 data_time: 0.0009 memory: 480 2022/09/16 17:35:44 - mmengine - INFO - Epoch(val) [7][2600/3836] eta: 0:00:14 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 17:35:46 - mmengine - INFO - Epoch(val) [7][2700/3836] eta: 0:00:13 time: 0.0121 data_time: 0.0005 memory: 480 2022/09/16 17:35:47 - mmengine - INFO - Epoch(val) [7][2800/3836] eta: 0:00:12 time: 0.0117 data_time: 0.0004 memory: 480 2022/09/16 17:35:48 - mmengine - INFO - Epoch(val) [7][2900/3836] eta: 0:00:10 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 17:35:49 - mmengine - INFO - Epoch(val) [7][3000/3836] eta: 0:00:09 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 17:35:50 - mmengine - INFO - Epoch(val) [7][3100/3836] eta: 0:00:08 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 17:35:51 - mmengine - INFO - Epoch(val) [7][3200/3836] eta: 0:00:07 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/16 17:35:53 - mmengine - INFO - Epoch(val) [7][3300/3836] eta: 0:00:06 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/16 17:35:54 - mmengine - INFO - Epoch(val) [7][3400/3836] eta: 0:00:05 time: 0.0121 data_time: 0.0008 memory: 480 2022/09/16 17:35:55 - mmengine - INFO - Epoch(val) [7][3500/3836] eta: 0:00:03 time: 0.0108 data_time: 0.0004 memory: 480 2022/09/16 17:35:56 - mmengine - INFO - Epoch(val) [7][3600/3836] eta: 0:00:02 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/16 17:35:57 - mmengine - INFO - Epoch(val) [7][3700/3836] eta: 0:00:01 time: 0.0107 data_time: 0.0004 memory: 480 2022/09/16 17:35:58 - mmengine - INFO - Epoch(val) [7][3800/3836] eta: 0:00:00 time: 0.0107 data_time: 0.0005 memory: 480 2022/09/16 17:35:59 - mmengine - INFO - Epoch(val) [7][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.8160 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9257 SVT/recog/word_acc_ignore_case_symbol: 0.8825 SVTP/recog/word_acc_ignore_case_symbol: 0.7891 IC13/recog/word_acc_ignore_case_symbol: 0.9015 IC15/recog/word_acc_ignore_case_symbol: 0.7540 2022/09/16 17:38:20 - mmengine - INFO - Epoch(train) [8][100/10520] lr: 1.0000e-04 eta: 2 days, 0:11:52 time: 1.7629 data_time: 0.6493 memory: 56769 loss_visual: 0.0735 loss: 0.0735 2022/09/16 17:40:26 - mmengine - INFO - Epoch(train) [8][200/10520] lr: 1.0000e-04 eta: 2 days, 0:09:42 time: 2.0046 data_time: 0.7997 memory: 56769 loss_visual: 0.0732 loss: 0.0732 2022/09/16 17:42:29 - mmengine - INFO - Epoch(train) [8][300/10520] lr: 1.0000e-04 eta: 2 days, 0:07:29 time: 1.5411 data_time: 0.4959 memory: 56769 loss_visual: 0.0750 loss: 0.0750 2022/09/16 17:43:45 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 17:44:33 - mmengine - INFO - Epoch(train) [8][400/10520] lr: 1.0000e-04 eta: 2 days, 0:05:15 time: 0.9082 data_time: 0.0068 memory: 56769 loss_visual: 0.0717 loss: 0.0717 2022/09/16 17:46:37 - mmengine - INFO - Epoch(train) [8][500/10520] lr: 1.0000e-04 eta: 2 days, 0:03:03 time: 0.9752 data_time: 0.0413 memory: 56769 loss_visual: 0.0729 loss: 0.0729 2022/09/16 17:48:42 - mmengine - INFO - Epoch(train) [8][600/10520] lr: 1.0000e-04 eta: 2 days, 0:00:52 time: 1.0746 data_time: 0.0433 memory: 56769 loss_visual: 0.0774 loss: 0.0774 2022/09/16 17:50:47 - mmengine - INFO - Epoch(train) [8][700/10520] lr: 1.0000e-04 eta: 1 day, 23:58:42 time: 1.0096 data_time: 0.0069 memory: 56769 loss_visual: 0.0722 loss: 0.0722 2022/09/16 17:52:56 - mmengine - INFO - Epoch(train) [8][800/10520] lr: 1.0000e-04 eta: 1 day, 23:56:39 time: 1.1436 data_time: 0.0664 memory: 56769 loss_visual: 0.0690 loss: 0.0690 2022/09/16 17:55:06 - mmengine - INFO - Epoch(train) [8][900/10520] lr: 1.0000e-04 eta: 1 day, 23:54:39 time: 1.4874 data_time: 0.4073 memory: 56769 loss_visual: 0.0744 loss: 0.0744 2022/09/16 17:57:15 - mmengine - INFO - Epoch(train) [8][1000/10520] lr: 1.0000e-04 eta: 1 day, 23:52:34 time: 1.4818 data_time: 0.4463 memory: 56769 loss_visual: 0.0709 loss: 0.0709 2022/09/16 17:59:24 - mmengine - INFO - Epoch(train) [8][1100/10520] lr: 1.0000e-04 eta: 1 day, 23:50:31 time: 1.5565 data_time: 0.4812 memory: 56769 loss_visual: 0.0719 loss: 0.0719 2022/09/16 18:01:38 - mmengine - INFO - Epoch(train) [8][1200/10520] lr: 1.0000e-04 eta: 1 day, 23:48:36 time: 1.3060 data_time: 0.1783 memory: 56769 loss_visual: 0.0717 loss: 0.0717 2022/09/16 18:03:49 - mmengine - INFO - Epoch(train) [8][1300/10520] lr: 1.0000e-04 eta: 1 day, 23:46:38 time: 1.6443 data_time: 0.6091 memory: 56769 loss_visual: 0.0719 loss: 0.0719 2022/09/16 18:05:04 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 18:05:55 - mmengine - INFO - Epoch(train) [8][1400/10520] lr: 1.0000e-04 eta: 1 day, 23:44:29 time: 1.3941 data_time: 0.3239 memory: 56769 loss_visual: 0.0739 loss: 0.0739 2022/09/16 18:08:05 - mmengine - INFO - Epoch(train) [8][1500/10520] lr: 1.0000e-04 eta: 1 day, 23:42:26 time: 1.2065 data_time: 0.3164 memory: 56769 loss_visual: 0.0687 loss: 0.0687 2022/09/16 18:10:18 - mmengine - INFO - Epoch(train) [8][1600/10520] lr: 1.0000e-04 eta: 1 day, 23:40:30 time: 1.3610 data_time: 0.4064 memory: 56769 loss_visual: 0.0710 loss: 0.0710 2022/09/16 18:12:22 - mmengine - INFO - Epoch(train) [8][1700/10520] lr: 1.0000e-04 eta: 1 day, 23:38:19 time: 1.2891 data_time: 0.2820 memory: 56769 loss_visual: 0.0672 loss: 0.0672 2022/09/16 18:14:29 - mmengine - INFO - Epoch(train) [8][1800/10520] lr: 1.0000e-04 eta: 1 day, 23:36:12 time: 1.0882 data_time: 0.0072 memory: 56769 loss_visual: 0.0706 loss: 0.0706 2022/09/16 18:16:36 - mmengine - INFO - Epoch(train) [8][1900/10520] lr: 1.0000e-04 eta: 1 day, 23:34:05 time: 1.0412 data_time: 0.0069 memory: 56769 loss_visual: 0.0754 loss: 0.0754 2022/09/16 18:18:49 - mmengine - INFO - Epoch(train) [8][2000/10520] lr: 1.0000e-04 eta: 1 day, 23:32:09 time: 1.2397 data_time: 0.1025 memory: 56769 loss_visual: 0.0716 loss: 0.0716 2022/09/16 18:21:03 - mmengine - INFO - Epoch(train) [8][2100/10520] lr: 1.0000e-04 eta: 1 day, 23:30:13 time: 1.4818 data_time: 0.4421 memory: 56769 loss_visual: 0.0731 loss: 0.0731 2022/09/16 18:23:11 - mmengine - INFO - Epoch(train) [8][2200/10520] lr: 1.0000e-04 eta: 1 day, 23:28:09 time: 1.3872 data_time: 0.3225 memory: 56769 loss_visual: 0.0739 loss: 0.0739 2022/09/16 18:25:24 - mmengine - INFO - Epoch(train) [8][2300/10520] lr: 1.0000e-04 eta: 1 day, 23:26:12 time: 1.3645 data_time: 0.2976 memory: 56769 loss_visual: 0.0708 loss: 0.0708 2022/09/16 18:26:43 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 18:27:37 - mmengine - INFO - Epoch(train) [8][2400/10520] lr: 1.0000e-04 eta: 1 day, 23:24:16 time: 1.4004 data_time: 0.2889 memory: 56769 loss_visual: 0.0752 loss: 0.0752 2022/09/16 18:29:49 - mmengine - INFO - Epoch(train) [8][2500/10520] lr: 1.0000e-04 eta: 1 day, 23:22:18 time: 1.5136 data_time: 0.2897 memory: 56769 loss_visual: 0.0725 loss: 0.0725 2022/09/16 18:32:00 - mmengine - INFO - Epoch(train) [8][2600/10520] lr: 1.0000e-04 eta: 1 day, 23:20:17 time: 1.1250 data_time: 0.0070 memory: 56769 loss_visual: 0.0720 loss: 0.0720 2022/09/16 18:34:08 - mmengine - INFO - Epoch(train) [8][2700/10520] lr: 1.0000e-04 eta: 1 day, 23:18:12 time: 1.0191 data_time: 0.0074 memory: 56769 loss_visual: 0.0722 loss: 0.0722 2022/09/16 18:36:20 - mmengine - INFO - Epoch(train) [8][2800/10520] lr: 1.0000e-04 eta: 1 day, 23:16:14 time: 1.2685 data_time: 0.1604 memory: 56769 loss_visual: 0.0703 loss: 0.0703 2022/09/16 18:38:27 - mmengine - INFO - Epoch(train) [8][2900/10520] lr: 1.0000e-04 eta: 1 day, 23:14:06 time: 1.2705 data_time: 0.4486 memory: 56769 loss_visual: 0.0717 loss: 0.0717 2022/09/16 18:40:27 - mmengine - INFO - Epoch(train) [8][3000/10520] lr: 1.0000e-04 eta: 1 day, 23:11:46 time: 1.1748 data_time: 0.2386 memory: 56769 loss_visual: 0.0720 loss: 0.0720 2022/09/16 18:42:30 - mmengine - INFO - Epoch(train) [8][3100/10520] lr: 1.0000e-04 eta: 1 day, 23:09:33 time: 1.2903 data_time: 0.2431 memory: 56769 loss_visual: 0.0775 loss: 0.0775 2022/09/16 18:44:45 - mmengine - INFO - Epoch(train) [8][3200/10520] lr: 1.0000e-04 eta: 1 day, 23:07:40 time: 1.7478 data_time: 0.2410 memory: 56769 loss_visual: 0.0774 loss: 0.0774 2022/09/16 18:46:54 - mmengine - INFO - Epoch(train) [8][3300/10520] lr: 1.0000e-04 eta: 1 day, 23:05:35 time: 1.6209 data_time: 0.2374 memory: 56769 loss_visual: 0.0694 loss: 0.0694 2022/09/16 18:48:15 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 18:49:04 - mmengine - INFO - Epoch(train) [8][3400/10520] lr: 1.0000e-04 eta: 1 day, 23:03:33 time: 0.9134 data_time: 0.0960 memory: 56769 loss_visual: 0.0713 loss: 0.0713 2022/09/16 18:51:13 - mmengine - INFO - Epoch(train) [8][3500/10520] lr: 1.0000e-04 eta: 1 day, 23:01:31 time: 0.9535 data_time: 0.0576 memory: 56769 loss_visual: 0.0735 loss: 0.0735 2022/09/16 18:53:26 - mmengine - INFO - Epoch(train) [8][3600/10520] lr: 1.0000e-04 eta: 1 day, 22:59:33 time: 1.1165 data_time: 0.1971 memory: 56769 loss_visual: 0.0753 loss: 0.0753 2022/09/16 18:55:39 - mmengine - INFO - Epoch(train) [8][3700/10520] lr: 1.0000e-04 eta: 1 day, 22:57:36 time: 1.3854 data_time: 0.3453 memory: 56769 loss_visual: 0.0719 loss: 0.0719 2022/09/16 18:57:49 - mmengine - INFO - Epoch(train) [8][3800/10520] lr: 1.0000e-04 eta: 1 day, 22:55:34 time: 1.2443 data_time: 0.2018 memory: 56769 loss_visual: 0.0716 loss: 0.0716 2022/09/16 19:00:03 - mmengine - INFO - Epoch(train) [8][3900/10520] lr: 1.0000e-04 eta: 1 day, 22:53:39 time: 1.6666 data_time: 0.1797 memory: 56769 loss_visual: 0.0721 loss: 0.0721 2022/09/16 19:02:15 - mmengine - INFO - Epoch(train) [8][4000/10520] lr: 1.0000e-04 eta: 1 day, 22:51:41 time: 1.6482 data_time: 0.3109 memory: 56769 loss_visual: 0.0725 loss: 0.0725 2022/09/16 19:04:25 - mmengine - INFO - Epoch(train) [8][4100/10520] lr: 1.0000e-04 eta: 1 day, 22:49:38 time: 1.5905 data_time: 0.3035 memory: 56769 loss_visual: 0.0681 loss: 0.0681 2022/09/16 19:06:35 - mmengine - INFO - Epoch(train) [8][4200/10520] lr: 1.0000e-04 eta: 1 day, 22:47:37 time: 0.9625 data_time: 0.0964 memory: 56769 loss_visual: 0.0748 loss: 0.0748 2022/09/16 19:08:44 - mmengine - INFO - Epoch(train) [8][4300/10520] lr: 1.0000e-04 eta: 1 day, 22:45:33 time: 0.9159 data_time: 0.0923 memory: 56769 loss_visual: 0.0705 loss: 0.0705 2022/09/16 19:10:04 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 19:10:56 - mmengine - INFO - Epoch(train) [8][4400/10520] lr: 1.0000e-04 eta: 1 day, 22:43:33 time: 1.0976 data_time: 0.1875 memory: 56769 loss_visual: 0.0708 loss: 0.0708 2022/09/16 19:13:06 - mmengine - INFO - Epoch(train) [8][4500/10520] lr: 1.0000e-04 eta: 1 day, 22:41:32 time: 1.3639 data_time: 0.3667 memory: 56769 loss_visual: 0.0739 loss: 0.0739 2022/09/16 19:15:16 - mmengine - INFO - Epoch(train) [8][4600/10520] lr: 1.0000e-04 eta: 1 day, 22:39:29 time: 1.2550 data_time: 0.1617 memory: 56769 loss_visual: 0.0702 loss: 0.0702 2022/09/16 19:17:30 - mmengine - INFO - Epoch(train) [8][4700/10520] lr: 1.0000e-04 eta: 1 day, 22:37:33 time: 1.5994 data_time: 0.1770 memory: 56769 loss_visual: 0.0732 loss: 0.0732 2022/09/16 19:19:43 - mmengine - INFO - Epoch(train) [8][4800/10520] lr: 1.0000e-04 eta: 1 day, 22:35:36 time: 1.6624 data_time: 0.3161 memory: 56769 loss_visual: 0.0704 loss: 0.0704 2022/09/16 19:21:52 - mmengine - INFO - Epoch(train) [8][4900/10520] lr: 1.0000e-04 eta: 1 day, 22:33:33 time: 1.5868 data_time: 0.3092 memory: 56769 loss_visual: 0.0743 loss: 0.0743 2022/09/16 19:24:02 - mmengine - INFO - Epoch(train) [8][5000/10520] lr: 1.0000e-04 eta: 1 day, 22:31:29 time: 0.9432 data_time: 0.0796 memory: 56769 loss_visual: 0.0719 loss: 0.0719 2022/09/16 19:26:11 - mmengine - INFO - Epoch(train) [8][5100/10520] lr: 1.0000e-04 eta: 1 day, 22:29:26 time: 0.9279 data_time: 0.0588 memory: 56769 loss_visual: 0.0764 loss: 0.0764 2022/09/16 19:28:23 - mmengine - INFO - Epoch(train) [8][5200/10520] lr: 1.0000e-04 eta: 1 day, 22:27:28 time: 1.0845 data_time: 0.1864 memory: 56769 loss_visual: 0.0674 loss: 0.0674 2022/09/16 19:30:36 - mmengine - INFO - Epoch(train) [8][5300/10520] lr: 1.0000e-04 eta: 1 day, 22:25:30 time: 1.3746 data_time: 0.3517 memory: 56769 loss_visual: 0.0747 loss: 0.0747 2022/09/16 19:31:56 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 19:32:46 - mmengine - INFO - Epoch(train) [8][5400/10520] lr: 1.0000e-04 eta: 1 day, 22:23:28 time: 1.0957 data_time: 0.0079 memory: 56769 loss_visual: 0.0746 loss: 0.0746 2022/09/16 19:35:02 - mmengine - INFO - Epoch(train) [8][5500/10520] lr: 1.0000e-04 eta: 1 day, 22:21:34 time: 1.6707 data_time: 0.0254 memory: 56769 loss_visual: 0.0719 loss: 0.0719 2022/09/16 19:37:12 - mmengine - INFO - Epoch(train) [8][5600/10520] lr: 1.0000e-04 eta: 1 day, 22:19:32 time: 1.7734 data_time: 0.3284 memory: 56769 loss_visual: 0.0754 loss: 0.0754 2022/09/16 19:39:23 - mmengine - INFO - Epoch(train) [8][5700/10520] lr: 1.0000e-04 eta: 1 day, 22:17:32 time: 1.6724 data_time: 0.2955 memory: 56769 loss_visual: 0.0724 loss: 0.0724 2022/09/16 19:41:38 - mmengine - INFO - Epoch(train) [8][5800/10520] lr: 1.0000e-04 eta: 1 day, 22:15:36 time: 1.3196 data_time: 0.3812 memory: 56769 loss_visual: 0.0696 loss: 0.0696 2022/09/16 19:43:47 - mmengine - INFO - Epoch(train) [8][5900/10520] lr: 1.0000e-04 eta: 1 day, 22:13:32 time: 1.1716 data_time: 0.2925 memory: 56769 loss_visual: 0.0739 loss: 0.0739 2022/09/16 19:45:59 - mmengine - INFO - Epoch(train) [8][6000/10520] lr: 1.0000e-04 eta: 1 day, 22:11:33 time: 1.1261 data_time: 0.0069 memory: 56769 loss_visual: 0.0714 loss: 0.0714 2022/09/16 19:48:08 - mmengine - INFO - Epoch(train) [8][6100/10520] lr: 1.0000e-04 eta: 1 day, 22:09:30 time: 1.1398 data_time: 0.0070 memory: 56769 loss_visual: 0.0741 loss: 0.0741 2022/09/16 19:50:20 - mmengine - INFO - Epoch(train) [8][6200/10520] lr: 1.0000e-04 eta: 1 day, 22:07:31 time: 0.8917 data_time: 0.0411 memory: 56769 loss_visual: 0.0735 loss: 0.0735 2022/09/16 19:52:34 - mmengine - INFO - Epoch(train) [8][6300/10520] lr: 1.0000e-04 eta: 1 day, 22:05:34 time: 1.5772 data_time: 0.0852 memory: 56769 loss_visual: 0.0754 loss: 0.0754 2022/09/16 19:53:50 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 19:54:49 - mmengine - INFO - Epoch(train) [8][6400/10520] lr: 1.0000e-04 eta: 1 day, 22:03:39 time: 1.8648 data_time: 0.4512 memory: 56769 loss_visual: 0.0703 loss: 0.0703 2022/09/16 19:57:00 - mmengine - INFO - Epoch(train) [8][6500/10520] lr: 1.0000e-04 eta: 1 day, 22:01:39 time: 1.7586 data_time: 0.3653 memory: 56769 loss_visual: 0.0713 loss: 0.0713 2022/09/16 19:59:13 - mmengine - INFO - Epoch(train) [8][6600/10520] lr: 1.0000e-04 eta: 1 day, 21:59:40 time: 1.2050 data_time: 0.3869 memory: 56769 loss_visual: 0.0717 loss: 0.0717 2022/09/16 20:01:23 - mmengine - INFO - Epoch(train) [8][6700/10520] lr: 1.0000e-04 eta: 1 day, 21:57:37 time: 1.1186 data_time: 0.2720 memory: 56769 loss_visual: 0.0754 loss: 0.0754 2022/09/16 20:03:35 - mmengine - INFO - Epoch(train) [8][6800/10520] lr: 1.0000e-04 eta: 1 day, 21:55:39 time: 1.1314 data_time: 0.0071 memory: 56769 loss_visual: 0.0684 loss: 0.0684 2022/09/16 20:05:48 - mmengine - INFO - Epoch(train) [8][6900/10520] lr: 1.0000e-04 eta: 1 day, 21:53:40 time: 1.1309 data_time: 0.0066 memory: 56769 loss_visual: 0.0748 loss: 0.0748 2022/09/16 20:08:00 - mmengine - INFO - Epoch(train) [8][7000/10520] lr: 1.0000e-04 eta: 1 day, 21:51:40 time: 1.2152 data_time: 0.0804 memory: 56769 loss_visual: 0.0717 loss: 0.0717 2022/09/16 20:10:18 - mmengine - INFO - Epoch(train) [8][7100/10520] lr: 1.0000e-04 eta: 1 day, 21:49:51 time: 1.4427 data_time: 0.1683 memory: 56769 loss_visual: 0.0683 loss: 0.0683 2022/09/16 20:12:35 - mmengine - INFO - Epoch(train) [8][7200/10520] lr: 1.0000e-04 eta: 1 day, 21:47:59 time: 1.9164 data_time: 0.6381 memory: 56769 loss_visual: 0.0747 loss: 0.0747 2022/09/16 20:14:47 - mmengine - INFO - Epoch(train) [8][7300/10520] lr: 1.0000e-04 eta: 1 day, 21:45:58 time: 2.0684 data_time: 0.5390 memory: 56769 loss_visual: 0.0740 loss: 0.0740 2022/09/16 20:16:05 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 20:16:57 - mmengine - INFO - Epoch(train) [8][7400/10520] lr: 1.0000e-04 eta: 1 day, 21:43:56 time: 1.3616 data_time: 0.3254 memory: 56769 loss_visual: 0.0716 loss: 0.0716 2022/09/16 20:19:06 - mmengine - INFO - Epoch(train) [8][7500/10520] lr: 1.0000e-04 eta: 1 day, 21:41:52 time: 0.8632 data_time: 0.0070 memory: 56769 loss_visual: 0.0737 loss: 0.0737 2022/09/16 20:21:17 - mmengine - INFO - Epoch(train) [8][7600/10520] lr: 1.0000e-04 eta: 1 day, 21:39:49 time: 0.9499 data_time: 0.0063 memory: 56769 loss_visual: 0.0693 loss: 0.0693 2022/09/16 20:23:27 - mmengine - INFO - Epoch(train) [8][7700/10520] lr: 1.0000e-04 eta: 1 day, 21:37:47 time: 0.9993 data_time: 0.0071 memory: 56769 loss_visual: 0.0673 loss: 0.0673 2022/09/16 20:25:37 - mmengine - INFO - Epoch(train) [8][7800/10520] lr: 1.0000e-04 eta: 1 day, 21:35:44 time: 1.0812 data_time: 0.1140 memory: 56769 loss_visual: 0.0742 loss: 0.0742 2022/09/16 20:27:50 - mmengine - INFO - Epoch(train) [8][7900/10520] lr: 1.0000e-04 eta: 1 day, 21:33:46 time: 1.3988 data_time: 0.1522 memory: 56769 loss_visual: 0.0671 loss: 0.0671 2022/09/16 20:30:06 - mmengine - INFO - Epoch(train) [8][8000/10520] lr: 1.0000e-04 eta: 1 day, 21:31:52 time: 1.8693 data_time: 0.5812 memory: 56769 loss_visual: 0.0641 loss: 0.0641 2022/09/16 20:32:18 - mmengine - INFO - Epoch(train) [8][8100/10520] lr: 1.0000e-04 eta: 1 day, 21:29:52 time: 2.0199 data_time: 0.5560 memory: 56769 loss_visual: 0.0727 loss: 0.0727 2022/09/16 20:34:28 - mmengine - INFO - Epoch(train) [8][8200/10520] lr: 1.0000e-04 eta: 1 day, 21:27:49 time: 1.3841 data_time: 0.2865 memory: 56769 loss_visual: 0.0703 loss: 0.0703 2022/09/16 20:36:37 - mmengine - INFO - Epoch(train) [8][8300/10520] lr: 1.0000e-04 eta: 1 day, 21:25:45 time: 0.8953 data_time: 0.0079 memory: 56769 loss_visual: 0.0702 loss: 0.0702 2022/09/16 20:37:57 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 20:38:48 - mmengine - INFO - Epoch(train) [8][8400/10520] lr: 1.0000e-04 eta: 1 day, 21:23:43 time: 1.0450 data_time: 0.0070 memory: 56769 loss_visual: 0.0746 loss: 0.0746 2022/09/16 20:40:59 - mmengine - INFO - Epoch(train) [8][8500/10520] lr: 1.0000e-04 eta: 1 day, 21:21:41 time: 1.0222 data_time: 0.0068 memory: 56769 loss_visual: 0.0723 loss: 0.0723 2022/09/16 20:43:08 - mmengine - INFO - Epoch(train) [8][8600/10520] lr: 1.0000e-04 eta: 1 day, 21:19:37 time: 1.1578 data_time: 0.1059 memory: 56769 loss_visual: 0.0694 loss: 0.0694 2022/09/16 20:45:22 - mmengine - INFO - Epoch(train) [8][8700/10520] lr: 1.0000e-04 eta: 1 day, 21:17:40 time: 1.3697 data_time: 0.1735 memory: 56769 loss_visual: 0.0693 loss: 0.0693 2022/09/16 20:47:36 - mmengine - INFO - Epoch(train) [8][8800/10520] lr: 1.0000e-04 eta: 1 day, 21:15:43 time: 1.5303 data_time: 0.5121 memory: 56769 loss_visual: 0.0671 loss: 0.0671 2022/09/16 20:49:50 - mmengine - INFO - Epoch(train) [8][8900/10520] lr: 1.0000e-04 eta: 1 day, 21:13:46 time: 1.7310 data_time: 0.4772 memory: 56769 loss_visual: 0.0719 loss: 0.0719 2022/09/16 20:52:03 - mmengine - INFO - Epoch(train) [8][9000/10520] lr: 1.0000e-04 eta: 1 day, 21:11:47 time: 1.3364 data_time: 0.2367 memory: 56769 loss_visual: 0.0696 loss: 0.0696 2022/09/16 20:54:13 - mmengine - INFO - Epoch(train) [8][9100/10520] lr: 1.0000e-04 eta: 1 day, 21:09:44 time: 0.8669 data_time: 0.0066 memory: 56769 loss_visual: 0.0690 loss: 0.0690 2022/09/16 20:56:26 - mmengine - INFO - Epoch(train) [8][9200/10520] lr: 1.0000e-04 eta: 1 day, 21:07:44 time: 1.0546 data_time: 0.0067 memory: 56769 loss_visual: 0.0755 loss: 0.0755 2022/09/16 20:58:37 - mmengine - INFO - Epoch(train) [8][9300/10520] lr: 1.0000e-04 eta: 1 day, 21:05:43 time: 1.2948 data_time: 0.1089 memory: 56769 loss_visual: 0.0718 loss: 0.0718 2022/09/16 20:59:54 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 21:00:48 - mmengine - INFO - Epoch(train) [8][9400/10520] lr: 1.0000e-04 eta: 1 day, 21:03:41 time: 1.4704 data_time: 0.2129 memory: 56769 loss_visual: 0.0701 loss: 0.0701 2022/09/16 21:03:00 - mmengine - INFO - Epoch(train) [8][9500/10520] lr: 1.0000e-04 eta: 1 day, 21:01:40 time: 1.3896 data_time: 0.1464 memory: 56769 loss_visual: 0.0662 loss: 0.0662 2022/09/16 21:05:14 - mmengine - INFO - Epoch(train) [8][9600/10520] lr: 1.0000e-04 eta: 1 day, 20:59:44 time: 1.6726 data_time: 0.5187 memory: 56769 loss_visual: 0.0704 loss: 0.0704 2022/09/16 21:07:26 - mmengine - INFO - Epoch(train) [8][9700/10520] lr: 1.0000e-04 eta: 1 day, 20:57:43 time: 1.7181 data_time: 0.4811 memory: 56769 loss_visual: 0.0789 loss: 0.0789 2022/09/16 21:09:39 - mmengine - INFO - Epoch(train) [8][9800/10520] lr: 1.0000e-04 eta: 1 day, 20:55:43 time: 1.1197 data_time: 0.2249 memory: 56769 loss_visual: 0.0741 loss: 0.0741 2022/09/16 21:11:47 - mmengine - INFO - Epoch(train) [8][9900/10520] lr: 1.0000e-04 eta: 1 day, 20:53:37 time: 0.8984 data_time: 0.0068 memory: 56769 loss_visual: 0.0714 loss: 0.0714 2022/09/16 21:13:55 - mmengine - INFO - Epoch(train) [8][10000/10520] lr: 1.0000e-04 eta: 1 day, 20:51:32 time: 0.8441 data_time: 0.0068 memory: 56769 loss_visual: 0.0660 loss: 0.0660 2022/09/16 21:16:46 - mmengine - INFO - Epoch(train) [8][10100/10520] lr: 1.0000e-04 eta: 1 day, 20:50:29 time: 0.8691 data_time: 0.0067 memory: 56769 loss_visual: 0.0708 loss: 0.0708 2022/09/16 21:19:17 - mmengine - INFO - Epoch(train) [8][10200/10520] lr: 1.0000e-04 eta: 1 day, 20:48:57 time: 0.8720 data_time: 0.0092 memory: 56769 loss_visual: 0.0696 loss: 0.0696 2022/09/16 21:22:01 - mmengine - INFO - Epoch(train) [8][10300/10520] lr: 1.0000e-04 eta: 1 day, 20:47:46 time: 0.8954 data_time: 0.0069 memory: 56769 loss_visual: 0.0682 loss: 0.0682 2022/09/16 21:24:00 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 21:24:52 - mmengine - INFO - Epoch(train) [8][10400/10520] lr: 1.0000e-04 eta: 1 day, 20:46:42 time: 1.8334 data_time: 0.6659 memory: 56769 loss_visual: 0.0709 loss: 0.0709 2022/09/16 21:27:03 - mmengine - INFO - Epoch(train) [8][10500/10520] lr: 1.0000e-04 eta: 1 day, 20:44:41 time: 2.4881 data_time: 0.4164 memory: 56769 loss_visual: 0.0668 loss: 0.0668 2022/09/16 21:27:21 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 21:27:21 - mmengine - INFO - Saving checkpoint at 8 epochs 2022/09/16 21:27:41 - mmengine - INFO - Epoch(val) [8][100/3836] eta: 0:05:33 time: 0.0894 data_time: 0.0006 memory: 56769 2022/09/16 21:27:46 - mmengine - INFO - Epoch(val) [8][200/3836] eta: 0:00:42 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 21:27:47 - mmengine - INFO - Epoch(val) [8][300/3836] eta: 0:00:40 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/16 21:27:48 - mmengine - INFO - Epoch(val) [8][400/3836] eta: 0:00:39 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/16 21:27:49 - mmengine - INFO - Epoch(val) [8][500/3836] eta: 0:00:39 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/16 21:27:50 - mmengine - INFO - Epoch(val) [8][600/3836] eta: 0:00:38 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 21:27:52 - mmengine - INFO - Epoch(val) [8][700/3836] eta: 0:00:36 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 21:27:53 - mmengine - INFO - Epoch(val) [8][800/3836] eta: 0:00:35 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/16 21:27:54 - mmengine - INFO - Epoch(val) [8][900/3836] eta: 0:00:34 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/16 21:27:55 - mmengine - INFO - Epoch(val) [8][1000/3836] eta: 0:00:32 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/16 21:27:56 - mmengine - INFO - Epoch(val) [8][1100/3836] eta: 0:00:31 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 21:27:58 - mmengine - INFO - Epoch(val) [8][1200/3836] eta: 0:00:30 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 21:27:59 - mmengine - INFO - Epoch(val) [8][1300/3836] eta: 0:00:28 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/16 21:28:00 - mmengine - INFO - Epoch(val) [8][1400/3836] eta: 0:00:28 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 21:28:01 - mmengine - INFO - Epoch(val) [8][1500/3836] eta: 0:00:29 time: 0.0127 data_time: 0.0005 memory: 480 2022/09/16 21:28:02 - mmengine - INFO - Epoch(val) [8][1600/3836] eta: 0:00:25 time: 0.0116 data_time: 0.0004 memory: 480 2022/09/16 21:28:04 - mmengine - INFO - Epoch(val) [8][1700/3836] eta: 0:00:25 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/16 21:28:05 - mmengine - INFO - Epoch(val) [8][1800/3836] eta: 0:00:23 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/16 21:28:06 - mmengine - INFO - Epoch(val) [8][1900/3836] eta: 0:00:24 time: 0.0127 data_time: 0.0006 memory: 480 2022/09/16 21:28:07 - mmengine - INFO - Epoch(val) [8][2000/3836] eta: 0:00:21 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 21:28:08 - mmengine - INFO - Epoch(val) [8][2100/3836] eta: 0:00:19 time: 0.0110 data_time: 0.0005 memory: 480 2022/09/16 21:28:10 - mmengine - INFO - Epoch(val) [8][2200/3836] eta: 0:00:19 time: 0.0118 data_time: 0.0006 memory: 480 2022/09/16 21:28:11 - mmengine - INFO - Epoch(val) [8][2300/3836] eta: 0:00:18 time: 0.0121 data_time: 0.0005 memory: 480 2022/09/16 21:28:12 - mmengine - INFO - Epoch(val) [8][2400/3836] eta: 0:00:16 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/16 21:28:13 - mmengine - INFO - Epoch(val) [8][2500/3836] eta: 0:00:15 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 21:28:14 - mmengine - INFO - Epoch(val) [8][2600/3836] eta: 0:00:14 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/16 21:28:15 - mmengine - INFO - Epoch(val) [8][2700/3836] eta: 0:00:13 time: 0.0120 data_time: 0.0006 memory: 480 2022/09/16 21:28:17 - mmengine - INFO - Epoch(val) [8][2800/3836] eta: 0:00:11 time: 0.0116 data_time: 0.0004 memory: 480 2022/09/16 21:28:18 - mmengine - INFO - Epoch(val) [8][2900/3836] eta: 0:00:10 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 21:28:19 - mmengine - INFO - Epoch(val) [8][3000/3836] eta: 0:00:09 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/16 21:28:20 - mmengine - INFO - Epoch(val) [8][3100/3836] eta: 0:00:08 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/16 21:28:21 - mmengine - INFO - Epoch(val) [8][3200/3836] eta: 0:00:07 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/16 21:28:23 - mmengine - INFO - Epoch(val) [8][3300/3836] eta: 0:00:06 time: 0.0114 data_time: 0.0004 memory: 480 2022/09/16 21:28:24 - mmengine - INFO - Epoch(val) [8][3400/3836] eta: 0:00:04 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/16 21:28:25 - mmengine - INFO - Epoch(val) [8][3500/3836] eta: 0:00:03 time: 0.0110 data_time: 0.0004 memory: 480 2022/09/16 21:28:26 - mmengine - INFO - Epoch(val) [8][3600/3836] eta: 0:00:03 time: 0.0139 data_time: 0.0021 memory: 480 2022/09/16 21:28:27 - mmengine - INFO - Epoch(val) [8][3700/3836] eta: 0:00:01 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/16 21:28:29 - mmengine - INFO - Epoch(val) [8][3800/3836] eta: 0:00:01 time: 0.0317 data_time: 0.0212 memory: 480 2022/09/16 21:28:30 - mmengine - INFO - Epoch(val) [8][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.7882 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9313 SVT/recog/word_acc_ignore_case_symbol: 0.8841 SVTP/recog/word_acc_ignore_case_symbol: 0.8016 IC13/recog/word_acc_ignore_case_symbol: 0.9025 IC15/recog/word_acc_ignore_case_symbol: 0.7535 2022/09/16 21:31:18 - mmengine - INFO - Epoch(train) [9][100/10520] lr: 1.0000e-04 eta: 1 day, 20:42:56 time: 0.9231 data_time: 0.0074 memory: 56769 loss_visual: 0.0678 loss: 0.0678 2022/09/16 21:33:31 - mmengine - INFO - Epoch(train) [9][200/10520] lr: 1.0000e-04 eta: 1 day, 20:40:57 time: 1.4801 data_time: 0.5240 memory: 56769 loss_visual: 0.0735 loss: 0.0735 2022/09/16 21:35:44 - mmengine - INFO - Epoch(train) [9][300/10520] lr: 1.0000e-04 eta: 1 day, 20:38:58 time: 1.9732 data_time: 0.5529 memory: 56769 loss_visual: 0.0715 loss: 0.0715 2022/09/16 21:37:52 - mmengine - INFO - Epoch(train) [9][400/10520] lr: 1.0000e-04 eta: 1 day, 20:36:50 time: 1.8408 data_time: 0.4650 memory: 56769 loss_visual: 0.0673 loss: 0.0673 2022/09/16 21:40:01 - mmengine - INFO - Epoch(train) [9][500/10520] lr: 1.0000e-04 eta: 1 day, 20:34:45 time: 0.8260 data_time: 0.0066 memory: 56769 loss_visual: 0.0689 loss: 0.0689 2022/09/16 21:42:11 - mmengine - INFO - Epoch(train) [9][600/10520] lr: 1.0000e-04 eta: 1 day, 20:32:40 time: 1.0620 data_time: 0.2098 memory: 56769 loss_visual: 0.0717 loss: 0.0717 2022/09/16 21:44:20 - mmengine - INFO - Epoch(train) [9][700/10520] lr: 1.0000e-04 eta: 1 day, 20:30:35 time: 1.0477 data_time: 0.1301 memory: 56769 loss_visual: 0.0669 loss: 0.0669 2022/09/16 21:46:28 - mmengine - INFO - Epoch(train) [9][800/10520] lr: 1.0000e-04 eta: 1 day, 20:28:28 time: 0.9871 data_time: 0.1220 memory: 56769 loss_visual: 0.0745 loss: 0.0745 2022/09/16 21:47:30 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 21:48:42 - mmengine - INFO - Epoch(train) [9][900/10520] lr: 1.0000e-04 eta: 1 day, 20:26:29 time: 1.3046 data_time: 0.0072 memory: 56769 loss_visual: 0.0697 loss: 0.0697 2022/09/16 21:50:53 - mmengine - INFO - Epoch(train) [9][1000/10520] lr: 1.0000e-04 eta: 1 day, 20:24:25 time: 1.7947 data_time: 0.6872 memory: 56769 loss_visual: 0.0692 loss: 0.0692 2022/09/16 21:53:03 - mmengine - INFO - Epoch(train) [9][1100/10520] lr: 1.0000e-04 eta: 1 day, 20:22:21 time: 2.0393 data_time: 0.6468 memory: 56769 loss_visual: 0.0749 loss: 0.0749 2022/09/16 21:55:09 - mmengine - INFO - Epoch(train) [9][1200/10520] lr: 1.0000e-04 eta: 1 day, 20:20:12 time: 1.7413 data_time: 0.4816 memory: 56769 loss_visual: 0.0697 loss: 0.0697 2022/09/16 21:57:16 - mmengine - INFO - Epoch(train) [9][1300/10520] lr: 1.0000e-04 eta: 1 day, 20:18:03 time: 0.8927 data_time: 0.0072 memory: 56769 loss_visual: 0.0651 loss: 0.0651 2022/09/16 21:59:22 - mmengine - INFO - Epoch(train) [9][1400/10520] lr: 1.0000e-04 eta: 1 day, 20:15:53 time: 0.8400 data_time: 0.0068 memory: 56769 loss_visual: 0.0693 loss: 0.0693 2022/09/16 22:01:30 - mmengine - INFO - Epoch(train) [9][1500/10520] lr: 1.0000e-04 eta: 1 day, 20:13:45 time: 1.0089 data_time: 0.1909 memory: 56769 loss_visual: 0.0710 loss: 0.0710 2022/09/16 22:03:36 - mmengine - INFO - Epoch(train) [9][1600/10520] lr: 1.0000e-04 eta: 1 day, 20:11:35 time: 1.0159 data_time: 0.1489 memory: 56769 loss_visual: 0.0698 loss: 0.0698 2022/09/16 22:05:44 - mmengine - INFO - Epoch(train) [9][1700/10520] lr: 1.0000e-04 eta: 1 day, 20:09:29 time: 1.3191 data_time: 0.2948 memory: 56769 loss_visual: 0.0729 loss: 0.0729 2022/09/16 22:07:56 - mmengine - INFO - Epoch(train) [9][1800/10520] lr: 1.0000e-04 eta: 1 day, 20:07:27 time: 1.5077 data_time: 0.4891 memory: 56769 loss_visual: 0.0695 loss: 0.0695 2022/09/16 22:08:48 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 22:10:04 - mmengine - INFO - Epoch(train) [9][1900/10520] lr: 1.0000e-04 eta: 1 day, 20:05:20 time: 1.7539 data_time: 0.4515 memory: 56769 loss_visual: 0.0695 loss: 0.0695 2022/09/16 22:12:26 - mmengine - INFO - Epoch(train) [9][2000/10520] lr: 1.0000e-04 eta: 1 day, 20:03:33 time: 2.7851 data_time: 1.7687 memory: 56769 loss_visual: 0.0703 loss: 0.0703 2022/09/16 22:16:01 - mmengine - INFO - Epoch(train) [9][2100/10520] lr: 1.0000e-04 eta: 1 day, 20:03:31 time: 0.8247 data_time: 0.0068 memory: 56769 loss_visual: 0.0685 loss: 0.0685 2022/09/16 22:19:25 - mmengine - INFO - Epoch(train) [9][2200/10520] lr: 1.0000e-04 eta: 1 day, 20:03:13 time: 0.8847 data_time: 0.0074 memory: 56769 loss_visual: 0.0676 loss: 0.0676 2022/09/16 22:21:55 - mmengine - INFO - Epoch(train) [9][2300/10520] lr: 1.0000e-04 eta: 1 day, 20:01:36 time: 0.9325 data_time: 0.0073 memory: 56769 loss_visual: 0.0685 loss: 0.0685 2022/09/16 22:23:56 - mmengine - INFO - Epoch(train) [9][2400/10520] lr: 1.0000e-04 eta: 1 day, 19:59:19 time: 1.2335 data_time: 0.3266 memory: 56769 loss_visual: 0.0685 loss: 0.0685 2022/09/16 22:26:07 - mmengine - INFO - Epoch(train) [9][2500/10520] lr: 1.0000e-04 eta: 1 day, 19:57:15 time: 1.2542 data_time: 0.1402 memory: 56769 loss_visual: 0.0686 loss: 0.0686 2022/09/16 22:28:19 - mmengine - INFO - Epoch(train) [9][2600/10520] lr: 1.0000e-04 eta: 1 day, 19:55:13 time: 1.3396 data_time: 0.2498 memory: 56769 loss_visual: 0.0694 loss: 0.0694 2022/09/16 22:30:32 - mmengine - INFO - Epoch(train) [9][2700/10520] lr: 1.0000e-04 eta: 1 day, 19:53:13 time: 1.6837 data_time: 0.2481 memory: 56769 loss_visual: 0.0729 loss: 0.0729 2022/09/16 22:32:41 - mmengine - INFO - Epoch(train) [9][2800/10520] lr: 1.0000e-04 eta: 1 day, 19:51:06 time: 1.5861 data_time: 0.2499 memory: 56769 loss_visual: 0.0711 loss: 0.0711 2022/09/16 22:33:32 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 22:34:52 - mmengine - INFO - Epoch(train) [9][2900/10520] lr: 1.0000e-04 eta: 1 day, 19:49:03 time: 0.9765 data_time: 0.1233 memory: 56769 loss_visual: 0.0686 loss: 0.0686 2022/09/16 22:37:04 - mmengine - INFO - Epoch(train) [9][3000/10520] lr: 1.0000e-04 eta: 1 day, 19:47:00 time: 1.0472 data_time: 0.1963 memory: 56769 loss_visual: 0.0680 loss: 0.0680 2022/09/16 22:39:16 - mmengine - INFO - Epoch(train) [9][3100/10520] lr: 1.0000e-04 eta: 1 day, 19:44:59 time: 1.2491 data_time: 0.3703 memory: 56769 loss_visual: 0.0656 loss: 0.0656 2022/09/16 22:41:27 - mmengine - INFO - Epoch(train) [9][3200/10520] lr: 1.0000e-04 eta: 1 day, 19:42:55 time: 1.2944 data_time: 0.3148 memory: 56769 loss_visual: 0.0682 loss: 0.0682 2022/09/16 22:43:37 - mmengine - INFO - Epoch(train) [9][3300/10520] lr: 1.0000e-04 eta: 1 day, 19:40:50 time: 1.2267 data_time: 0.1529 memory: 56769 loss_visual: 0.0699 loss: 0.0699 2022/09/16 22:45:48 - mmengine - INFO - Epoch(train) [9][3400/10520] lr: 1.0000e-04 eta: 1 day, 19:38:46 time: 1.3141 data_time: 0.2485 memory: 56769 loss_visual: 0.0688 loss: 0.0688 2022/09/16 22:48:01 - mmengine - INFO - Epoch(train) [9][3500/10520] lr: 1.0000e-04 eta: 1 day, 19:36:46 time: 1.6956 data_time: 0.2753 memory: 56769 loss_visual: 0.0684 loss: 0.0684 2022/09/16 22:50:10 - mmengine - INFO - Epoch(train) [9][3600/10520] lr: 1.0000e-04 eta: 1 day, 19:34:39 time: 1.5343 data_time: 0.2395 memory: 56769 loss_visual: 0.0680 loss: 0.0680 2022/09/16 22:52:22 - mmengine - INFO - Epoch(train) [9][3700/10520] lr: 1.0000e-04 eta: 1 day, 19:32:36 time: 0.9788 data_time: 0.1161 memory: 56769 loss_visual: 0.0707 loss: 0.0707 2022/09/16 22:54:32 - mmengine - INFO - Epoch(train) [9][3800/10520] lr: 1.0000e-04 eta: 1 day, 19:30:32 time: 1.0276 data_time: 0.1803 memory: 56769 loss_visual: 0.0697 loss: 0.0697 2022/09/16 22:55:26 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 22:56:46 - mmengine - INFO - Epoch(train) [9][3900/10520] lr: 1.0000e-04 eta: 1 day, 19:28:32 time: 1.2232 data_time: 0.3993 memory: 56769 loss_visual: 0.0652 loss: 0.0652 2022/09/16 22:58:56 - mmengine - INFO - Epoch(train) [9][4000/10520] lr: 1.0000e-04 eta: 1 day, 19:26:27 time: 1.2986 data_time: 0.3456 memory: 56769 loss_visual: 0.0714 loss: 0.0714 2022/09/16 23:01:06 - mmengine - INFO - Epoch(train) [9][4100/10520] lr: 1.0000e-04 eta: 1 day, 19:24:22 time: 1.2464 data_time: 0.1574 memory: 56769 loss_visual: 0.0649 loss: 0.0649 2022/09/16 23:03:18 - mmengine - INFO - Epoch(train) [9][4200/10520] lr: 1.0000e-04 eta: 1 day, 19:22:20 time: 1.3670 data_time: 0.2827 memory: 56769 loss_visual: 0.0716 loss: 0.0716 2022/09/16 23:05:32 - mmengine - INFO - Epoch(train) [9][4300/10520] lr: 1.0000e-04 eta: 1 day, 19:20:20 time: 1.7021 data_time: 0.2443 memory: 56769 loss_visual: 0.0726 loss: 0.0726 2022/09/16 23:07:42 - mmengine - INFO - Epoch(train) [9][4400/10520] lr: 1.0000e-04 eta: 1 day, 19:18:14 time: 1.6108 data_time: 0.2650 memory: 56769 loss_visual: 0.0696 loss: 0.0696 2022/09/16 23:09:52 - mmengine - INFO - Epoch(train) [9][4500/10520] lr: 1.0000e-04 eta: 1 day, 19:16:10 time: 0.9970 data_time: 0.1215 memory: 56769 loss_visual: 0.0691 loss: 0.0691 2022/09/16 23:12:01 - mmengine - INFO - Epoch(train) [9][4600/10520] lr: 1.0000e-04 eta: 1 day, 19:14:03 time: 1.0329 data_time: 0.1809 memory: 56769 loss_visual: 0.0714 loss: 0.0714 2022/09/16 23:14:14 - mmengine - INFO - Epoch(train) [9][4700/10520] lr: 1.0000e-04 eta: 1 day, 19:12:02 time: 1.3028 data_time: 0.4833 memory: 56769 loss_visual: 0.0677 loss: 0.0677 2022/09/16 23:16:24 - mmengine - INFO - Epoch(train) [9][4800/10520] lr: 1.0000e-04 eta: 1 day, 19:09:57 time: 1.2440 data_time: 0.3005 memory: 56769 loss_visual: 0.0644 loss: 0.0644 2022/09/16 23:17:17 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 23:18:35 - mmengine - INFO - Epoch(train) [9][4900/10520] lr: 1.0000e-04 eta: 1 day, 19:07:53 time: 1.2677 data_time: 0.1840 memory: 56769 loss_visual: 0.0764 loss: 0.0764 2022/09/16 23:20:48 - mmengine - INFO - Epoch(train) [9][5000/10520] lr: 1.0000e-04 eta: 1 day, 19:05:51 time: 1.3565 data_time: 0.2411 memory: 56769 loss_visual: 0.0696 loss: 0.0696 2022/09/16 23:23:02 - mmengine - INFO - Epoch(train) [9][5100/10520] lr: 1.0000e-04 eta: 1 day, 19:03:52 time: 1.7146 data_time: 0.2380 memory: 56769 loss_visual: 0.0715 loss: 0.0715 2022/09/16 23:25:11 - mmengine - INFO - Epoch(train) [9][5200/10520] lr: 1.0000e-04 eta: 1 day, 19:01:46 time: 1.5772 data_time: 0.2430 memory: 56769 loss_visual: 0.0648 loss: 0.0648 2022/09/16 23:27:23 - mmengine - INFO - Epoch(train) [9][5300/10520] lr: 1.0000e-04 eta: 1 day, 18:59:42 time: 1.0036 data_time: 0.0900 memory: 56769 loss_visual: 0.0695 loss: 0.0695 2022/09/16 23:29:32 - mmengine - INFO - Epoch(train) [9][5400/10520] lr: 1.0000e-04 eta: 1 day, 18:57:36 time: 1.0346 data_time: 0.1704 memory: 56769 loss_visual: 0.0665 loss: 0.0665 2022/09/16 23:31:44 - mmengine - INFO - Epoch(train) [9][5500/10520] lr: 1.0000e-04 eta: 1 day, 18:55:33 time: 1.2165 data_time: 0.3887 memory: 56769 loss_visual: 0.0681 loss: 0.0681 2022/09/16 23:33:54 - mmengine - INFO - Epoch(train) [9][5600/10520] lr: 1.0000e-04 eta: 1 day, 18:53:27 time: 1.2291 data_time: 0.3168 memory: 56769 loss_visual: 0.0681 loss: 0.0681 2022/09/16 23:36:04 - mmengine - INFO - Epoch(train) [9][5700/10520] lr: 1.0000e-04 eta: 1 day, 18:51:23 time: 1.2455 data_time: 0.1525 memory: 56769 loss_visual: 0.0692 loss: 0.0692 2022/09/16 23:38:17 - mmengine - INFO - Epoch(train) [9][5800/10520] lr: 1.0000e-04 eta: 1 day, 18:49:22 time: 1.3477 data_time: 0.2788 memory: 56769 loss_visual: 0.0721 loss: 0.0721 2022/09/16 23:39:11 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/16 23:40:32 - mmengine - INFO - Epoch(train) [9][5900/10520] lr: 1.0000e-04 eta: 1 day, 18:47:22 time: 1.7579 data_time: 0.2596 memory: 56769 loss_visual: 0.0693 loss: 0.0693 2022/09/16 23:42:42 - mmengine - INFO - Epoch(train) [9][6000/10520] lr: 1.0000e-04 eta: 1 day, 18:45:17 time: 1.5701 data_time: 0.2566 memory: 56769 loss_visual: 0.0709 loss: 0.0709 2022/09/16 23:44:53 - mmengine - INFO - Epoch(train) [9][6100/10520] lr: 1.0000e-04 eta: 1 day, 18:43:13 time: 0.9834 data_time: 0.1236 memory: 56769 loss_visual: 0.0702 loss: 0.0702 2022/09/16 23:47:03 - mmengine - INFO - Epoch(train) [9][6200/10520] lr: 1.0000e-04 eta: 1 day, 18:41:07 time: 1.0261 data_time: 0.2086 memory: 56769 loss_visual: 0.0687 loss: 0.0687 2022/09/16 23:49:14 - mmengine - INFO - Epoch(train) [9][6300/10520] lr: 1.0000e-04 eta: 1 day, 18:39:03 time: 1.2092 data_time: 0.3923 memory: 56769 loss_visual: 0.0692 loss: 0.0692 2022/09/16 23:51:23 - mmengine - INFO - Epoch(train) [9][6400/10520] lr: 1.0000e-04 eta: 1 day, 18:36:57 time: 1.3007 data_time: 0.3388 memory: 56769 loss_visual: 0.0687 loss: 0.0687 2022/09/16 23:53:35 - mmengine - INFO - Epoch(train) [9][6500/10520] lr: 1.0000e-04 eta: 1 day, 18:34:53 time: 1.2932 data_time: 0.1656 memory: 56769 loss_visual: 0.0690 loss: 0.0690 2022/09/16 23:55:49 - mmengine - INFO - Epoch(train) [9][6600/10520] lr: 1.0000e-04 eta: 1 day, 18:32:54 time: 1.3541 data_time: 0.2762 memory: 56769 loss_visual: 0.0685 loss: 0.0685 2022/09/16 23:58:02 - mmengine - INFO - Epoch(train) [9][6700/10520] lr: 1.0000e-04 eta: 1 day, 18:30:53 time: 1.6710 data_time: 0.2646 memory: 56769 loss_visual: 0.0722 loss: 0.0722 2022/09/17 00:00:14 - mmengine - INFO - Epoch(train) [9][6800/10520] lr: 1.0000e-04 eta: 1 day, 18:28:49 time: 1.8735 data_time: 0.2650 memory: 56769 loss_visual: 0.0731 loss: 0.0731 2022/09/17 00:01:05 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 00:02:26 - mmengine - INFO - Epoch(train) [9][6900/10520] lr: 1.0000e-04 eta: 1 day, 18:26:47 time: 1.0151 data_time: 0.0985 memory: 56769 loss_visual: 0.0644 loss: 0.0644 2022/09/17 00:04:36 - mmengine - INFO - Epoch(train) [9][7000/10520] lr: 1.0000e-04 eta: 1 day, 18:24:41 time: 1.0150 data_time: 0.1715 memory: 56769 loss_visual: 0.0709 loss: 0.0709 2022/09/17 00:06:49 - mmengine - INFO - Epoch(train) [9][7100/10520] lr: 1.0000e-04 eta: 1 day, 18:22:40 time: 1.2628 data_time: 0.3981 memory: 56769 loss_visual: 0.0716 loss: 0.0716 2022/09/17 00:08:59 - mmengine - INFO - Epoch(train) [9][7200/10520] lr: 1.0000e-04 eta: 1 day, 18:20:33 time: 1.2656 data_time: 0.3385 memory: 56769 loss_visual: 0.0691 loss: 0.0691 2022/09/17 00:11:10 - mmengine - INFO - Epoch(train) [9][7300/10520] lr: 1.0000e-04 eta: 1 day, 18:18:29 time: 1.2849 data_time: 0.1553 memory: 56769 loss_visual: 0.0644 loss: 0.0644 2022/09/17 00:13:22 - mmengine - INFO - Epoch(train) [9][7400/10520] lr: 1.0000e-04 eta: 1 day, 18:16:26 time: 1.3392 data_time: 0.2750 memory: 56769 loss_visual: 0.0700 loss: 0.0700 2022/09/17 00:15:36 - mmengine - INFO - Epoch(train) [9][7500/10520] lr: 1.0000e-04 eta: 1 day, 18:14:26 time: 1.6903 data_time: 0.2344 memory: 56769 loss_visual: 0.0689 loss: 0.0689 2022/09/17 00:17:45 - mmengine - INFO - Epoch(train) [9][7600/10520] lr: 1.0000e-04 eta: 1 day, 18:12:20 time: 1.6209 data_time: 0.2880 memory: 56769 loss_visual: 0.0645 loss: 0.0645 2022/09/17 00:19:56 - mmengine - INFO - Epoch(train) [9][7700/10520] lr: 1.0000e-04 eta: 1 day, 18:10:15 time: 1.0095 data_time: 0.1292 memory: 56769 loss_visual: 0.0670 loss: 0.0670 2022/09/17 00:22:07 - mmengine - INFO - Epoch(train) [9][7800/10520] lr: 1.0000e-04 eta: 1 day, 18:08:10 time: 1.0337 data_time: 0.1976 memory: 56769 loss_visual: 0.0658 loss: 0.0658 2022/09/17 00:22:59 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 00:24:20 - mmengine - INFO - Epoch(train) [9][7900/10520] lr: 1.0000e-04 eta: 1 day, 18:06:08 time: 1.2269 data_time: 0.3593 memory: 56769 loss_visual: 0.0666 loss: 0.0666 2022/09/17 00:26:31 - mmengine - INFO - Epoch(train) [9][8000/10520] lr: 1.0000e-04 eta: 1 day, 18:04:04 time: 1.3107 data_time: 0.3524 memory: 56769 loss_visual: 0.0671 loss: 0.0671 2022/09/17 00:28:42 - mmengine - INFO - Epoch(train) [9][8100/10520] lr: 1.0000e-04 eta: 1 day, 18:01:59 time: 1.2488 data_time: 0.1522 memory: 56769 loss_visual: 0.0705 loss: 0.0705 2022/09/17 00:30:53 - mmengine - INFO - Epoch(train) [9][8200/10520] lr: 1.0000e-04 eta: 1 day, 17:59:56 time: 1.3303 data_time: 0.2316 memory: 56769 loss_visual: 0.0729 loss: 0.0729 2022/09/17 00:33:07 - mmengine - INFO - Epoch(train) [9][8300/10520] lr: 1.0000e-04 eta: 1 day, 17:57:55 time: 1.7439 data_time: 0.2461 memory: 56769 loss_visual: 0.0626 loss: 0.0626 2022/09/17 00:35:16 - mmengine - INFO - Epoch(train) [9][8400/10520] lr: 1.0000e-04 eta: 1 day, 17:55:47 time: 1.5525 data_time: 0.2463 memory: 56769 loss_visual: 0.0730 loss: 0.0730 2022/09/17 00:37:27 - mmengine - INFO - Epoch(train) [9][8500/10520] lr: 1.0000e-04 eta: 1 day, 17:53:44 time: 1.1402 data_time: 0.3197 memory: 56769 loss_visual: 0.0641 loss: 0.0641 2022/09/17 00:39:37 - mmengine - INFO - Epoch(train) [9][8600/10520] lr: 1.0000e-04 eta: 1 day, 17:51:38 time: 1.1605 data_time: 0.3420 memory: 56769 loss_visual: 0.0646 loss: 0.0646 2022/09/17 00:41:58 - mmengine - INFO - Epoch(train) [9][8700/10520] lr: 1.0000e-04 eta: 1 day, 17:49:46 time: 1.2525 data_time: 0.4307 memory: 56769 loss_visual: 0.0695 loss: 0.0695 2022/09/17 00:44:01 - mmengine - INFO - Epoch(train) [9][8800/10520] lr: 1.0000e-04 eta: 1 day, 17:47:32 time: 1.1770 data_time: 0.0569 memory: 56769 loss_visual: 0.0671 loss: 0.0671 2022/09/17 00:44:57 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 00:46:14 - mmengine - INFO - Epoch(train) [9][8900/10520] lr: 1.0000e-04 eta: 1 day, 17:45:29 time: 1.4811 data_time: 0.0578 memory: 56769 loss_visual: 0.0667 loss: 0.0667 2022/09/17 00:48:26 - mmengine - INFO - Epoch(train) [9][9000/10520] lr: 1.0000e-04 eta: 1 day, 17:43:26 time: 1.6343 data_time: 0.2572 memory: 56769 loss_visual: 0.0690 loss: 0.0690 2022/09/17 00:50:34 - mmengine - INFO - Epoch(train) [9][9100/10520] lr: 1.0000e-04 eta: 1 day, 17:41:18 time: 1.0978 data_time: 0.2758 memory: 56769 loss_visual: 0.0647 loss: 0.0647 2022/09/17 00:52:45 - mmengine - INFO - Epoch(train) [9][9200/10520] lr: 1.0000e-04 eta: 1 day, 17:39:13 time: 1.1245 data_time: 0.2643 memory: 56769 loss_visual: 0.0666 loss: 0.0666 2022/09/17 00:54:57 - mmengine - INFO - Epoch(train) [9][9300/10520] lr: 1.0000e-04 eta: 1 day, 17:37:10 time: 0.8911 data_time: 0.0340 memory: 56769 loss_visual: 0.0709 loss: 0.0709 2022/09/17 00:57:08 - mmengine - INFO - Epoch(train) [9][9400/10520] lr: 1.0000e-04 eta: 1 day, 17:35:05 time: 1.0505 data_time: 0.1542 memory: 56769 loss_visual: 0.0655 loss: 0.0655 2022/09/17 00:59:22 - mmengine - INFO - Epoch(train) [9][9500/10520] lr: 1.0000e-04 eta: 1 day, 17:33:04 time: 1.2526 data_time: 0.2419 memory: 56769 loss_visual: 0.0686 loss: 0.0686 2022/09/17 01:01:34 - mmengine - INFO - Epoch(train) [9][9600/10520] lr: 1.0000e-04 eta: 1 day, 17:31:01 time: 1.4398 data_time: 0.1387 memory: 56769 loss_visual: 0.0697 loss: 0.0697 2022/09/17 01:03:45 - mmengine - INFO - Epoch(train) [9][9700/10520] lr: 1.0000e-04 eta: 1 day, 17:28:56 time: 1.2991 data_time: 0.0081 memory: 56769 loss_visual: 0.0675 loss: 0.0675 2022/09/17 01:05:59 - mmengine - INFO - Epoch(train) [9][9800/10520] lr: 1.0000e-04 eta: 1 day, 17:26:55 time: 1.5850 data_time: 0.4358 memory: 56769 loss_visual: 0.0662 loss: 0.0662 2022/09/17 01:06:49 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 01:08:13 - mmengine - INFO - Epoch(train) [9][9900/10520] lr: 1.0000e-04 eta: 1 day, 17:24:54 time: 1.5829 data_time: 0.3829 memory: 56769 loss_visual: 0.0669 loss: 0.0669 2022/09/17 01:10:19 - mmengine - INFO - Epoch(train) [9][10000/10520] lr: 1.0000e-04 eta: 1 day, 17:22:44 time: 1.7248 data_time: 0.3950 memory: 56769 loss_visual: 0.0698 loss: 0.0698 2022/09/17 01:12:35 - mmengine - INFO - Epoch(train) [9][10100/10520] lr: 1.0000e-04 eta: 1 day, 17:20:45 time: 1.2587 data_time: 0.3592 memory: 56769 loss_visual: 0.0714 loss: 0.0714 2022/09/17 01:14:45 - mmengine - INFO - Epoch(train) [9][10200/10520] lr: 1.0000e-04 eta: 1 day, 17:18:39 time: 1.2249 data_time: 0.3635 memory: 56769 loss_visual: 0.0662 loss: 0.0662 2022/09/17 01:16:56 - mmengine - INFO - Epoch(train) [9][10300/10520] lr: 1.0000e-04 eta: 1 day, 17:16:35 time: 1.4701 data_time: 0.4480 memory: 56769 loss_visual: 0.0700 loss: 0.0700 2022/09/17 01:19:06 - mmengine - INFO - Epoch(train) [9][10400/10520] lr: 1.0000e-04 eta: 1 day, 17:14:28 time: 1.1605 data_time: 0.1347 memory: 56769 loss_visual: 0.0680 loss: 0.0680 2022/09/17 01:21:12 - mmengine - INFO - Epoch(train) [9][10500/10520] lr: 1.0000e-04 eta: 1 day, 17:12:18 time: 0.9891 data_time: 0.0902 memory: 56769 loss_visual: 0.0716 loss: 0.0716 2022/09/17 01:21:34 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 01:21:34 - mmengine - INFO - Saving checkpoint at 9 epochs 2022/09/17 01:21:54 - mmengine - INFO - Epoch(val) [9][100/3836] eta: 0:05:17 time: 0.0850 data_time: 0.0006 memory: 56769 2022/09/17 01:21:59 - mmengine - INFO - Epoch(val) [9][200/3836] eta: 0:00:42 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 01:22:00 - mmengine - INFO - Epoch(val) [9][300/3836] eta: 0:00:41 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 01:22:01 - mmengine - INFO - Epoch(val) [9][400/3836] eta: 0:00:38 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/17 01:22:03 - mmengine - INFO - Epoch(val) [9][500/3836] eta: 0:00:38 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 01:22:04 - mmengine - INFO - Epoch(val) [9][600/3836] eta: 0:01:14 time: 0.0229 data_time: 0.0117 memory: 480 2022/09/17 01:22:05 - mmengine - INFO - Epoch(val) [9][700/3836] eta: 0:00:35 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/17 01:22:06 - mmengine - INFO - Epoch(val) [9][800/3836] eta: 0:00:33 time: 0.0110 data_time: 0.0005 memory: 480 2022/09/17 01:22:07 - mmengine - INFO - Epoch(val) [9][900/3836] eta: 0:00:32 time: 0.0110 data_time: 0.0005 memory: 480 2022/09/17 01:22:08 - mmengine - INFO - Epoch(val) [9][1000/3836] eta: 0:00:33 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 01:22:10 - mmengine - INFO - Epoch(val) [9][1100/3836] eta: 0:00:30 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/17 01:22:11 - mmengine - INFO - Epoch(val) [9][1200/3836] eta: 0:00:30 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 01:22:12 - mmengine - INFO - Epoch(val) [9][1300/3836] eta: 0:00:29 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 01:22:13 - mmengine - INFO - Epoch(val) [9][1400/3836] eta: 0:00:28 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 01:22:14 - mmengine - INFO - Epoch(val) [9][1500/3836] eta: 0:00:27 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 01:22:15 - mmengine - INFO - Epoch(val) [9][1600/3836] eta: 0:00:26 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 01:22:17 - mmengine - INFO - Epoch(val) [9][1700/3836] eta: 0:00:26 time: 0.0126 data_time: 0.0005 memory: 480 2022/09/17 01:22:18 - mmengine - INFO - Epoch(val) [9][1800/3836] eta: 0:00:23 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 01:22:19 - mmengine - INFO - Epoch(val) [9][1900/3836] eta: 0:00:22 time: 0.0115 data_time: 0.0007 memory: 480 2022/09/17 01:22:20 - mmengine - INFO - Epoch(val) [9][2000/3836] eta: 0:00:20 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 01:22:21 - mmengine - INFO - Epoch(val) [9][2100/3836] eta: 0:00:19 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 01:22:23 - mmengine - INFO - Epoch(val) [9][2200/3836] eta: 0:00:18 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/17 01:22:24 - mmengine - INFO - Epoch(val) [9][2300/3836] eta: 0:00:16 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/17 01:22:25 - mmengine - INFO - Epoch(val) [9][2400/3836] eta: 0:00:16 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 01:22:26 - mmengine - INFO - Epoch(val) [9][2500/3836] eta: 0:00:15 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 01:22:27 - mmengine - INFO - Epoch(val) [9][2600/3836] eta: 0:00:14 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 01:22:28 - mmengine - INFO - Epoch(val) [9][2700/3836] eta: 0:00:21 time: 0.0187 data_time: 0.0025 memory: 480 2022/09/17 01:22:30 - mmengine - INFO - Epoch(val) [9][2800/3836] eta: 0:00:11 time: 0.0112 data_time: 0.0004 memory: 480 2022/09/17 01:22:31 - mmengine - INFO - Epoch(val) [9][2900/3836] eta: 0:00:10 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 01:22:32 - mmengine - INFO - Epoch(val) [9][3000/3836] eta: 0:00:09 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 01:22:33 - mmengine - INFO - Epoch(val) [9][3100/3836] eta: 0:00:08 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 01:22:34 - mmengine - INFO - Epoch(val) [9][3200/3836] eta: 0:00:07 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 01:22:35 - mmengine - INFO - Epoch(val) [9][3300/3836] eta: 0:00:05 time: 0.0110 data_time: 0.0005 memory: 480 2022/09/17 01:22:37 - mmengine - INFO - Epoch(val) [9][3400/3836] eta: 0:00:04 time: 0.0107 data_time: 0.0004 memory: 480 2022/09/17 01:22:38 - mmengine - INFO - Epoch(val) [9][3500/3836] eta: 0:00:03 time: 0.0107 data_time: 0.0004 memory: 480 2022/09/17 01:22:39 - mmengine - INFO - Epoch(val) [9][3600/3836] eta: 0:00:02 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 01:22:40 - mmengine - INFO - Epoch(val) [9][3700/3836] eta: 0:00:01 time: 0.0110 data_time: 0.0005 memory: 480 2022/09/17 01:22:41 - mmengine - INFO - Epoch(val) [9][3800/3836] eta: 0:00:00 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/17 01:22:42 - mmengine - INFO - Epoch(val) [9][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.8160 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9343 SVT/recog/word_acc_ignore_case_symbol: 0.8995 SVTP/recog/word_acc_ignore_case_symbol: 0.8016 IC13/recog/word_acc_ignore_case_symbol: 0.9182 IC15/recog/word_acc_ignore_case_symbol: 0.7703 2022/09/17 01:25:07 - mmengine - INFO - Epoch(train) [10][100/10520] lr: 1.0000e-04 eta: 1 day, 17:10:00 time: 1.7193 data_time: 0.7351 memory: 56769 loss_visual: 0.0672 loss: 0.0672 2022/09/17 01:27:18 - mmengine - INFO - Epoch(train) [10][200/10520] lr: 1.0000e-04 eta: 1 day, 17:07:55 time: 2.0866 data_time: 0.6786 memory: 56769 loss_visual: 0.0631 loss: 0.0631 2022/09/17 01:29:26 - mmengine - INFO - Epoch(train) [10][300/10520] lr: 1.0000e-04 eta: 1 day, 17:05:46 time: 1.5062 data_time: 0.2541 memory: 56769 loss_visual: 0.0678 loss: 0.0678 2022/09/17 01:29:45 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 01:31:30 - mmengine - INFO - Epoch(train) [10][400/10520] lr: 1.0000e-04 eta: 1 day, 17:03:34 time: 1.2199 data_time: 0.0072 memory: 56769 loss_visual: 0.0687 loss: 0.0687 2022/09/17 01:33:37 - mmengine - INFO - Epoch(train) [10][500/10520] lr: 1.0000e-04 eta: 1 day, 17:01:24 time: 0.9440 data_time: 0.0074 memory: 56769 loss_visual: 0.0702 loss: 0.0702 2022/09/17 01:35:43 - mmengine - INFO - Epoch(train) [10][600/10520] lr: 1.0000e-04 eta: 1 day, 16:59:12 time: 0.9706 data_time: 0.0068 memory: 56769 loss_visual: 0.0675 loss: 0.0675 2022/09/17 01:37:48 - mmengine - INFO - Epoch(train) [10][700/10520] lr: 1.0000e-04 eta: 1 day, 16:57:01 time: 1.0046 data_time: 0.0395 memory: 56769 loss_visual: 0.0663 loss: 0.0663 2022/09/17 01:39:55 - mmengine - INFO - Epoch(train) [10][800/10520] lr: 1.0000e-04 eta: 1 day, 16:54:51 time: 0.9500 data_time: 0.1263 memory: 56769 loss_visual: 0.0695 loss: 0.0695 2022/09/17 01:42:08 - mmengine - INFO - Epoch(train) [10][900/10520] lr: 1.0000e-04 eta: 1 day, 16:52:49 time: 1.6774 data_time: 0.7171 memory: 56769 loss_visual: 0.0700 loss: 0.0700 2022/09/17 01:44:19 - mmengine - INFO - Epoch(train) [10][1000/10520] lr: 1.0000e-04 eta: 1 day, 16:50:43 time: 2.0390 data_time: 0.6630 memory: 56769 loss_visual: 0.0680 loss: 0.0680 2022/09/17 01:46:23 - mmengine - INFO - Epoch(train) [10][1100/10520] lr: 1.0000e-04 eta: 1 day, 16:48:31 time: 1.5153 data_time: 0.2853 memory: 56769 loss_visual: 0.0675 loss: 0.0675 2022/09/17 01:48:30 - mmengine - INFO - Epoch(train) [10][1200/10520] lr: 1.0000e-04 eta: 1 day, 16:46:21 time: 1.1971 data_time: 0.0074 memory: 56769 loss_visual: 0.0692 loss: 0.0692 2022/09/17 01:50:37 - mmengine - INFO - Epoch(train) [10][1300/10520] lr: 1.0000e-04 eta: 1 day, 16:44:11 time: 0.9576 data_time: 0.0072 memory: 56769 loss_visual: 0.0638 loss: 0.0638 2022/09/17 01:51:07 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 01:52:45 - mmengine - INFO - Epoch(train) [10][1400/10520] lr: 1.0000e-04 eta: 1 day, 16:42:03 time: 0.9667 data_time: 0.0074 memory: 56769 loss_visual: 0.0678 loss: 0.0678 2022/09/17 01:54:51 - mmengine - INFO - Epoch(train) [10][1500/10520] lr: 1.0000e-04 eta: 1 day, 16:39:52 time: 1.0102 data_time: 0.0500 memory: 56769 loss_visual: 0.0664 loss: 0.0664 2022/09/17 01:56:58 - mmengine - INFO - Epoch(train) [10][1600/10520] lr: 1.0000e-04 eta: 1 day, 16:37:43 time: 0.9663 data_time: 0.1265 memory: 56769 loss_visual: 0.0686 loss: 0.0686 2022/09/17 01:59:11 - mmengine - INFO - Epoch(train) [10][1700/10520] lr: 1.0000e-04 eta: 1 day, 16:35:40 time: 1.6459 data_time: 0.7442 memory: 56769 loss_visual: 0.0667 loss: 0.0667 2022/09/17 02:01:20 - mmengine - INFO - Epoch(train) [10][1800/10520] lr: 1.0000e-04 eta: 1 day, 16:33:33 time: 1.9981 data_time: 0.6450 memory: 56769 loss_visual: 0.0650 loss: 0.0650 2022/09/17 02:03:26 - mmengine - INFO - Epoch(train) [10][1900/10520] lr: 1.0000e-04 eta: 1 day, 16:31:22 time: 1.5607 data_time: 0.2899 memory: 56769 loss_visual: 0.0652 loss: 0.0652 2022/09/17 02:05:32 - mmengine - INFO - Epoch(train) [10][2000/10520] lr: 1.0000e-04 eta: 1 day, 16:29:12 time: 1.1955 data_time: 0.0077 memory: 56769 loss_visual: 0.0678 loss: 0.0678 2022/09/17 02:07:40 - mmengine - INFO - Epoch(train) [10][2100/10520] lr: 1.0000e-04 eta: 1 day, 16:27:03 time: 0.9399 data_time: 0.0075 memory: 56769 loss_visual: 0.0701 loss: 0.0701 2022/09/17 02:09:46 - mmengine - INFO - Epoch(train) [10][2200/10520] lr: 1.0000e-04 eta: 1 day, 16:24:53 time: 0.9960 data_time: 0.0066 memory: 56769 loss_visual: 0.0663 loss: 0.0663 2022/09/17 02:11:53 - mmengine - INFO - Epoch(train) [10][2300/10520] lr: 1.0000e-04 eta: 1 day, 16:22:42 time: 0.9973 data_time: 0.0473 memory: 56769 loss_visual: 0.0699 loss: 0.0699 2022/09/17 02:12:21 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 02:13:59 - mmengine - INFO - Epoch(train) [10][2400/10520] lr: 1.0000e-04 eta: 1 day, 16:20:32 time: 0.9582 data_time: 0.1356 memory: 56769 loss_visual: 0.0654 loss: 0.0654 2022/09/17 02:16:13 - mmengine - INFO - Epoch(train) [10][2500/10520] lr: 1.0000e-04 eta: 1 day, 16:18:30 time: 1.6998 data_time: 0.7205 memory: 56769 loss_visual: 0.0678 loss: 0.0678 2022/09/17 02:18:23 - mmengine - INFO - Epoch(train) [10][2600/10520] lr: 1.0000e-04 eta: 1 day, 16:16:24 time: 2.0268 data_time: 0.6493 memory: 56769 loss_visual: 0.0697 loss: 0.0697 2022/09/17 02:20:29 - mmengine - INFO - Epoch(train) [10][2700/10520] lr: 1.0000e-04 eta: 1 day, 16:14:14 time: 1.5488 data_time: 0.2896 memory: 56769 loss_visual: 0.0656 loss: 0.0656 2022/09/17 02:22:35 - mmengine - INFO - Epoch(train) [10][2800/10520] lr: 1.0000e-04 eta: 1 day, 16:12:03 time: 1.2033 data_time: 0.0115 memory: 56769 loss_visual: 0.0672 loss: 0.0672 2022/09/17 02:24:41 - mmengine - INFO - Epoch(train) [10][2900/10520] lr: 1.0000e-04 eta: 1 day, 16:09:52 time: 0.9303 data_time: 0.0085 memory: 56769 loss_visual: 0.0657 loss: 0.0657 2022/09/17 02:26:47 - mmengine - INFO - Epoch(train) [10][3000/10520] lr: 1.0000e-04 eta: 1 day, 16:07:42 time: 0.9910 data_time: 0.0073 memory: 56769 loss_visual: 0.0672 loss: 0.0672 2022/09/17 02:28:53 - mmengine - INFO - Epoch(train) [10][3100/10520] lr: 1.0000e-04 eta: 1 day, 16:05:30 time: 1.0052 data_time: 0.0421 memory: 56769 loss_visual: 0.0660 loss: 0.0660 2022/09/17 02:31:00 - mmengine - INFO - Epoch(train) [10][3200/10520] lr: 1.0000e-04 eta: 1 day, 16:03:21 time: 0.9669 data_time: 0.1478 memory: 56769 loss_visual: 0.0670 loss: 0.0670 2022/09/17 02:33:13 - mmengine - INFO - Epoch(train) [10][3300/10520] lr: 1.0000e-04 eta: 1 day, 16:01:19 time: 1.6175 data_time: 0.7289 memory: 56769 loss_visual: 0.0665 loss: 0.0665 2022/09/17 02:33:36 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 02:35:23 - mmengine - INFO - Epoch(train) [10][3400/10520] lr: 1.0000e-04 eta: 1 day, 15:59:13 time: 2.0009 data_time: 0.6209 memory: 56769 loss_visual: 0.0663 loss: 0.0663 2022/09/17 02:37:29 - mmengine - INFO - Epoch(train) [10][3500/10520] lr: 1.0000e-04 eta: 1 day, 15:57:02 time: 1.5304 data_time: 0.2675 memory: 56769 loss_visual: 0.0624 loss: 0.0624 2022/09/17 02:39:35 - mmengine - INFO - Epoch(train) [10][3600/10520] lr: 1.0000e-04 eta: 1 day, 15:54:51 time: 1.1957 data_time: 0.0069 memory: 56769 loss_visual: 0.0686 loss: 0.0686 2022/09/17 02:41:42 - mmengine - INFO - Epoch(train) [10][3700/10520] lr: 1.0000e-04 eta: 1 day, 15:52:42 time: 0.9519 data_time: 0.0068 memory: 56769 loss_visual: 0.0657 loss: 0.0657 2022/09/17 02:43:49 - mmengine - INFO - Epoch(train) [10][3800/10520] lr: 1.0000e-04 eta: 1 day, 15:50:32 time: 0.9797 data_time: 0.0069 memory: 56769 loss_visual: 0.0650 loss: 0.0650 2022/09/17 02:45:55 - mmengine - INFO - Epoch(train) [10][3900/10520] lr: 1.0000e-04 eta: 1 day, 15:48:22 time: 1.0129 data_time: 0.0382 memory: 56769 loss_visual: 0.0684 loss: 0.0684 2022/09/17 02:48:02 - mmengine - INFO - Epoch(train) [10][4000/10520] lr: 1.0000e-04 eta: 1 day, 15:46:12 time: 0.9421 data_time: 0.1241 memory: 56769 loss_visual: 0.0651 loss: 0.0651 2022/09/17 02:50:16 - mmengine - INFO - Epoch(train) [10][4100/10520] lr: 1.0000e-04 eta: 1 day, 15:44:10 time: 1.7089 data_time: 0.7429 memory: 56769 loss_visual: 0.0658 loss: 0.0658 2022/09/17 02:52:26 - mmengine - INFO - Epoch(train) [10][4200/10520] lr: 1.0000e-04 eta: 1 day, 15:42:04 time: 1.9912 data_time: 0.6142 memory: 56769 loss_visual: 0.0664 loss: 0.0664 2022/09/17 02:54:32 - mmengine - INFO - Epoch(train) [10][4300/10520] lr: 1.0000e-04 eta: 1 day, 15:39:53 time: 1.5169 data_time: 0.2838 memory: 56769 loss_visual: 0.0673 loss: 0.0673 2022/09/17 02:54:51 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 02:56:38 - mmengine - INFO - Epoch(train) [10][4400/10520] lr: 1.0000e-04 eta: 1 day, 15:37:43 time: 1.2491 data_time: 0.0071 memory: 56769 loss_visual: 0.0686 loss: 0.0686 2022/09/17 02:58:47 - mmengine - INFO - Epoch(train) [10][4500/10520] lr: 1.0000e-04 eta: 1 day, 15:35:36 time: 0.9669 data_time: 0.0071 memory: 56769 loss_visual: 0.0684 loss: 0.0684 2022/09/17 03:00:54 - mmengine - INFO - Epoch(train) [10][4600/10520] lr: 1.0000e-04 eta: 1 day, 15:33:27 time: 1.0124 data_time: 0.0071 memory: 56769 loss_visual: 0.0694 loss: 0.0694 2022/09/17 03:03:01 - mmengine - INFO - Epoch(train) [10][4700/10520] lr: 1.0000e-04 eta: 1 day, 15:31:17 time: 0.9991 data_time: 0.0417 memory: 56769 loss_visual: 0.0666 loss: 0.0666 2022/09/17 03:05:07 - mmengine - INFO - Epoch(train) [10][4800/10520] lr: 1.0000e-04 eta: 1 day, 15:29:07 time: 0.9569 data_time: 0.1214 memory: 56769 loss_visual: 0.0619 loss: 0.0619 2022/09/17 03:07:22 - mmengine - INFO - Epoch(train) [10][4900/10520] lr: 1.0000e-04 eta: 1 day, 15:27:06 time: 1.7545 data_time: 0.7707 memory: 56769 loss_visual: 0.0692 loss: 0.0692 2022/09/17 03:09:33 - mmengine - INFO - Epoch(train) [10][5000/10520] lr: 1.0000e-04 eta: 1 day, 15:25:00 time: 2.0343 data_time: 0.6748 memory: 56769 loss_visual: 0.0609 loss: 0.0609 2022/09/17 03:11:39 - mmengine - INFO - Epoch(train) [10][5100/10520] lr: 1.0000e-04 eta: 1 day, 15:22:50 time: 1.5159 data_time: 0.2881 memory: 56769 loss_visual: 0.0714 loss: 0.0714 2022/09/17 03:13:45 - mmengine - INFO - Epoch(train) [10][5200/10520] lr: 1.0000e-04 eta: 1 day, 15:20:40 time: 1.2045 data_time: 0.0075 memory: 56769 loss_visual: 0.0678 loss: 0.0678 2022/09/17 03:15:52 - mmengine - INFO - Epoch(train) [10][5300/10520] lr: 1.0000e-04 eta: 1 day, 15:18:30 time: 0.9452 data_time: 0.0070 memory: 56769 loss_visual: 0.0665 loss: 0.0665 2022/09/17 03:16:23 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 03:17:58 - mmengine - INFO - Epoch(train) [10][5400/10520] lr: 1.0000e-04 eta: 1 day, 15:16:19 time: 0.9496 data_time: 0.0072 memory: 56769 loss_visual: 0.0713 loss: 0.0713 2022/09/17 03:20:04 - mmengine - INFO - Epoch(train) [10][5500/10520] lr: 1.0000e-04 eta: 1 day, 15:14:09 time: 1.0391 data_time: 0.0415 memory: 56769 loss_visual: 0.0639 loss: 0.0639 2022/09/17 03:22:12 - mmengine - INFO - Epoch(train) [10][5600/10520] lr: 1.0000e-04 eta: 1 day, 15:12:01 time: 0.9544 data_time: 0.1282 memory: 56769 loss_visual: 0.0681 loss: 0.0681 2022/09/17 03:24:26 - mmengine - INFO - Epoch(train) [10][5700/10520] lr: 1.0000e-04 eta: 1 day, 15:09:58 time: 1.6842 data_time: 0.7524 memory: 56769 loss_visual: 0.0660 loss: 0.0660 2022/09/17 03:26:35 - mmengine - INFO - Epoch(train) [10][5800/10520] lr: 1.0000e-04 eta: 1 day, 15:07:51 time: 1.9457 data_time: 0.6317 memory: 56769 loss_visual: 0.0682 loss: 0.0682 2022/09/17 03:28:40 - mmengine - INFO - Epoch(train) [10][5900/10520] lr: 1.0000e-04 eta: 1 day, 15:05:39 time: 1.4894 data_time: 0.2693 memory: 56769 loss_visual: 0.0687 loss: 0.0687 2022/09/17 03:30:46 - mmengine - INFO - Epoch(train) [10][6000/10520] lr: 1.0000e-04 eta: 1 day, 15:03:29 time: 1.2060 data_time: 0.0072 memory: 56769 loss_visual: 0.0656 loss: 0.0656 2022/09/17 03:32:54 - mmengine - INFO - Epoch(train) [10][6100/10520] lr: 1.0000e-04 eta: 1 day, 15:01:21 time: 0.9370 data_time: 0.0072 memory: 56769 loss_visual: 0.0679 loss: 0.0679 2022/09/17 03:35:01 - mmengine - INFO - Epoch(train) [10][6200/10520] lr: 1.0000e-04 eta: 1 day, 14:59:12 time: 0.9891 data_time: 0.0071 memory: 56769 loss_visual: 0.0640 loss: 0.0640 2022/09/17 03:37:07 - mmengine - INFO - Epoch(train) [10][6300/10520] lr: 1.0000e-04 eta: 1 day, 14:57:01 time: 1.0115 data_time: 0.0413 memory: 56769 loss_visual: 0.0653 loss: 0.0653 2022/09/17 03:37:36 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 03:39:14 - mmengine - INFO - Epoch(train) [10][6400/10520] lr: 1.0000e-04 eta: 1 day, 14:54:51 time: 0.9728 data_time: 0.1164 memory: 56769 loss_visual: 0.0672 loss: 0.0672 2022/09/17 03:41:27 - mmengine - INFO - Epoch(train) [10][6500/10520] lr: 1.0000e-04 eta: 1 day, 14:52:49 time: 1.6375 data_time: 0.6997 memory: 56769 loss_visual: 0.0655 loss: 0.0655 2022/09/17 03:43:37 - mmengine - INFO - Epoch(train) [10][6600/10520] lr: 1.0000e-04 eta: 1 day, 14:50:42 time: 1.9701 data_time: 0.6348 memory: 56769 loss_visual: 0.0671 loss: 0.0671 2022/09/17 03:45:42 - mmengine - INFO - Epoch(train) [10][6700/10520] lr: 1.0000e-04 eta: 1 day, 14:48:31 time: 1.5258 data_time: 0.2795 memory: 56769 loss_visual: 0.0722 loss: 0.0722 2022/09/17 03:47:49 - mmengine - INFO - Epoch(train) [10][6800/10520] lr: 1.0000e-04 eta: 1 day, 14:46:21 time: 1.2200 data_time: 0.0072 memory: 56769 loss_visual: 0.0651 loss: 0.0651 2022/09/17 03:49:55 - mmengine - INFO - Epoch(train) [10][6900/10520] lr: 1.0000e-04 eta: 1 day, 14:44:10 time: 0.9283 data_time: 0.0069 memory: 56769 loss_visual: 0.0648 loss: 0.0648 2022/09/17 03:52:00 - mmengine - INFO - Epoch(train) [10][7000/10520] lr: 1.0000e-04 eta: 1 day, 14:41:59 time: 0.9858 data_time: 0.0069 memory: 56769 loss_visual: 0.0655 loss: 0.0655 2022/09/17 03:54:08 - mmengine - INFO - Epoch(train) [10][7100/10520] lr: 1.0000e-04 eta: 1 day, 14:39:50 time: 1.0171 data_time: 0.0485 memory: 56769 loss_visual: 0.0659 loss: 0.0659 2022/09/17 03:56:14 - mmengine - INFO - Epoch(train) [10][7200/10520] lr: 1.0000e-04 eta: 1 day, 14:37:40 time: 0.9724 data_time: 0.1252 memory: 56769 loss_visual: 0.0661 loss: 0.0661 2022/09/17 03:58:27 - mmengine - INFO - Epoch(train) [10][7300/10520] lr: 1.0000e-04 eta: 1 day, 14:35:37 time: 1.7353 data_time: 0.7719 memory: 56769 loss_visual: 0.0686 loss: 0.0686 2022/09/17 03:58:50 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 04:00:39 - mmengine - INFO - Epoch(train) [10][7400/10520] lr: 1.0000e-04 eta: 1 day, 14:33:33 time: 2.0407 data_time: 0.6593 memory: 56769 loss_visual: 0.0658 loss: 0.0658 2022/09/17 04:02:44 - mmengine - INFO - Epoch(train) [10][7500/10520] lr: 1.0000e-04 eta: 1 day, 14:31:22 time: 1.5538 data_time: 0.3008 memory: 56769 loss_visual: 0.0678 loss: 0.0678 2022/09/17 04:04:50 - mmengine - INFO - Epoch(train) [10][7600/10520] lr: 1.0000e-04 eta: 1 day, 14:29:11 time: 1.1852 data_time: 0.0072 memory: 56769 loss_visual: 0.0675 loss: 0.0675 2022/09/17 04:06:58 - mmengine - INFO - Epoch(train) [10][7700/10520] lr: 1.0000e-04 eta: 1 day, 14:27:03 time: 0.9269 data_time: 0.0090 memory: 56769 loss_visual: 0.0677 loss: 0.0677 2022/09/17 04:09:04 - mmengine - INFO - Epoch(train) [10][7800/10520] lr: 1.0000e-04 eta: 1 day, 14:24:52 time: 0.9880 data_time: 0.0072 memory: 56769 loss_visual: 0.0669 loss: 0.0669 2022/09/17 04:11:10 - mmengine - INFO - Epoch(train) [10][7900/10520] lr: 1.0000e-04 eta: 1 day, 14:22:42 time: 0.9947 data_time: 0.0526 memory: 56769 loss_visual: 0.0693 loss: 0.0693 2022/09/17 04:13:17 - mmengine - INFO - Epoch(train) [10][8000/10520] lr: 1.0000e-04 eta: 1 day, 14:20:32 time: 0.9708 data_time: 0.1435 memory: 56769 loss_visual: 0.0640 loss: 0.0640 2022/09/17 04:15:32 - mmengine - INFO - Epoch(train) [10][8100/10520] lr: 1.0000e-04 eta: 1 day, 14:18:32 time: 1.6633 data_time: 0.7635 memory: 56769 loss_visual: 0.0686 loss: 0.0686 2022/09/17 04:17:43 - mmengine - INFO - Epoch(train) [10][8200/10520] lr: 1.0000e-04 eta: 1 day, 14:16:26 time: 2.0946 data_time: 0.7178 memory: 56769 loss_visual: 0.0649 loss: 0.0649 2022/09/17 04:19:49 - mmengine - INFO - Epoch(train) [10][8300/10520] lr: 1.0000e-04 eta: 1 day, 14:14:16 time: 1.5122 data_time: 0.2812 memory: 56769 loss_visual: 0.0662 loss: 0.0662 2022/09/17 04:20:08 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 04:21:54 - mmengine - INFO - Epoch(train) [10][8400/10520] lr: 1.0000e-04 eta: 1 day, 14:12:04 time: 1.2108 data_time: 0.0074 memory: 56769 loss_visual: 0.0668 loss: 0.0668 2022/09/17 04:24:01 - mmengine - INFO - Epoch(train) [10][8500/10520] lr: 1.0000e-04 eta: 1 day, 14:09:55 time: 0.9369 data_time: 0.0068 memory: 56769 loss_visual: 0.0654 loss: 0.0654 2022/09/17 04:26:08 - mmengine - INFO - Epoch(train) [10][8600/10520] lr: 1.0000e-04 eta: 1 day, 14:07:46 time: 0.9573 data_time: 0.0072 memory: 56769 loss_visual: 0.0640 loss: 0.0640 2022/09/17 04:28:13 - mmengine - INFO - Epoch(train) [10][8700/10520] lr: 1.0000e-04 eta: 1 day, 14:05:34 time: 1.0012 data_time: 0.0448 memory: 56769 loss_visual: 0.0656 loss: 0.0656 2022/09/17 04:30:20 - mmengine - INFO - Epoch(train) [10][8800/10520] lr: 1.0000e-04 eta: 1 day, 14:03:25 time: 0.9445 data_time: 0.1291 memory: 56769 loss_visual: 0.0648 loss: 0.0648 2022/09/17 04:32:34 - mmengine - INFO - Epoch(train) [10][8900/10520] lr: 1.0000e-04 eta: 1 day, 14:01:23 time: 1.6391 data_time: 0.7444 memory: 56769 loss_visual: 0.0630 loss: 0.0630 2022/09/17 04:34:45 - mmengine - INFO - Epoch(train) [10][9000/10520] lr: 1.0000e-04 eta: 1 day, 13:59:17 time: 1.9972 data_time: 0.6392 memory: 56769 loss_visual: 0.0694 loss: 0.0694 2022/09/17 04:36:49 - mmengine - INFO - Epoch(train) [10][9100/10520] lr: 1.0000e-04 eta: 1 day, 13:57:05 time: 1.5202 data_time: 0.2828 memory: 56769 loss_visual: 0.0592 loss: 0.0592 2022/09/17 04:38:55 - mmengine - INFO - Epoch(train) [10][9200/10520] lr: 1.0000e-04 eta: 1 day, 13:54:54 time: 1.1846 data_time: 0.0073 memory: 56769 loss_visual: 0.0661 loss: 0.0661 2022/09/17 04:41:02 - mmengine - INFO - Epoch(train) [10][9300/10520] lr: 1.0000e-04 eta: 1 day, 13:52:46 time: 0.9270 data_time: 0.0067 memory: 56769 loss_visual: 0.0671 loss: 0.0671 2022/09/17 04:41:32 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 04:43:07 - mmengine - INFO - Epoch(train) [10][9400/10520] lr: 1.0000e-04 eta: 1 day, 13:50:34 time: 0.9638 data_time: 0.0070 memory: 56769 loss_visual: 0.0668 loss: 0.0668 2022/09/17 04:45:12 - mmengine - INFO - Epoch(train) [10][9500/10520] lr: 1.0000e-04 eta: 1 day, 13:48:23 time: 1.0325 data_time: 0.0448 memory: 56769 loss_visual: 0.0655 loss: 0.0655 2022/09/17 04:47:19 - mmengine - INFO - Epoch(train) [10][9600/10520] lr: 1.0000e-04 eta: 1 day, 13:46:13 time: 0.9311 data_time: 0.1095 memory: 56769 loss_visual: 0.0689 loss: 0.0689 2022/09/17 04:49:32 - mmengine - INFO - Epoch(train) [10][9700/10520] lr: 1.0000e-04 eta: 1 day, 13:44:11 time: 1.6915 data_time: 0.7489 memory: 56769 loss_visual: 0.0682 loss: 0.0682 2022/09/17 04:51:41 - mmengine - INFO - Epoch(train) [10][9800/10520] lr: 1.0000e-04 eta: 1 day, 13:42:03 time: 2.0062 data_time: 0.6602 memory: 56769 loss_visual: 0.0693 loss: 0.0693 2022/09/17 04:53:46 - mmengine - INFO - Epoch(train) [10][9900/10520] lr: 1.0000e-04 eta: 1 day, 13:39:51 time: 1.5175 data_time: 0.2894 memory: 56769 loss_visual: 0.0669 loss: 0.0669 2022/09/17 04:55:51 - mmengine - INFO - Epoch(train) [10][10000/10520] lr: 1.0000e-04 eta: 1 day, 13:37:40 time: 1.1640 data_time: 0.0071 memory: 56769 loss_visual: 0.0698 loss: 0.0698 2022/09/17 04:57:57 - mmengine - INFO - Epoch(train) [10][10100/10520] lr: 1.0000e-04 eta: 1 day, 13:35:30 time: 0.9597 data_time: 0.0065 memory: 56769 loss_visual: 0.0670 loss: 0.0670 2022/09/17 05:00:02 - mmengine - INFO - Epoch(train) [10][10200/10520] lr: 1.0000e-04 eta: 1 day, 13:33:19 time: 0.9690 data_time: 0.0070 memory: 56769 loss_visual: 0.0610 loss: 0.0610 2022/09/17 05:02:08 - mmengine - INFO - Epoch(train) [10][10300/10520] lr: 1.0000e-04 eta: 1 day, 13:31:08 time: 1.0031 data_time: 0.0414 memory: 56769 loss_visual: 0.0667 loss: 0.0667 2022/09/17 05:02:37 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 05:04:14 - mmengine - INFO - Epoch(train) [10][10400/10520] lr: 1.0000e-04 eta: 1 day, 13:28:58 time: 0.9793 data_time: 0.1358 memory: 56769 loss_visual: 0.0631 loss: 0.0631 2022/09/17 05:06:19 - mmengine - INFO - Epoch(train) [10][10500/10520] lr: 1.0000e-04 eta: 1 day, 13:26:47 time: 1.3083 data_time: 0.4417 memory: 56769 loss_visual: 0.0661 loss: 0.0661 2022/09/17 05:06:38 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 05:06:38 - mmengine - INFO - Saving checkpoint at 10 epochs 2022/09/17 05:06:58 - mmengine - INFO - Epoch(val) [10][100/3836] eta: 0:05:36 time: 0.0902 data_time: 0.0005 memory: 56769 2022/09/17 05:07:03 - mmengine - INFO - Epoch(val) [10][200/3836] eta: 0:00:41 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 05:07:04 - mmengine - INFO - Epoch(val) [10][300/3836] eta: 0:00:40 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 05:07:05 - mmengine - INFO - Epoch(val) [10][400/3836] eta: 0:00:39 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 05:07:07 - mmengine - INFO - Epoch(val) [10][500/3836] eta: 0:00:39 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 05:07:08 - mmengine - INFO - Epoch(val) [10][600/3836] eta: 0:00:36 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 05:07:09 - mmengine - INFO - Epoch(val) [10][700/3836] eta: 0:00:35 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/17 05:07:10 - mmengine - INFO - Epoch(val) [10][800/3836] eta: 0:00:34 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 05:07:11 - mmengine - INFO - Epoch(val) [10][900/3836] eta: 0:00:33 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 05:07:12 - mmengine - INFO - Epoch(val) [10][1000/3836] eta: 0:00:34 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/17 05:07:14 - mmengine - INFO - Epoch(val) [10][1100/3836] eta: 0:00:31 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 05:07:15 - mmengine - INFO - Epoch(val) [10][1200/3836] eta: 0:00:33 time: 0.0126 data_time: 0.0006 memory: 480 2022/09/17 05:07:16 - mmengine - INFO - Epoch(val) [10][1300/3836] eta: 0:00:29 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 05:07:18 - mmengine - INFO - Epoch(val) [10][1400/3836] eta: 0:00:28 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 05:07:19 - mmengine - INFO - Epoch(val) [10][1500/3836] eta: 0:00:27 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 05:07:20 - mmengine - INFO - Epoch(val) [10][1600/3836] eta: 0:00:45 time: 0.0205 data_time: 0.0014 memory: 480 2022/09/17 05:07:21 - mmengine - INFO - Epoch(val) [10][1700/3836] eta: 0:00:24 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 05:07:22 - mmengine - INFO - Epoch(val) [10][1800/3836] eta: 0:00:23 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 05:07:24 - mmengine - INFO - Epoch(val) [10][1900/3836] eta: 0:00:22 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 05:07:25 - mmengine - INFO - Epoch(val) [10][2000/3836] eta: 0:00:20 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/17 05:07:26 - mmengine - INFO - Epoch(val) [10][2100/3836] eta: 0:00:19 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 05:07:27 - mmengine - INFO - Epoch(val) [10][2200/3836] eta: 0:00:19 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 05:07:28 - mmengine - INFO - Epoch(val) [10][2300/3836] eta: 0:00:17 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 05:07:29 - mmengine - INFO - Epoch(val) [10][2400/3836] eta: 0:00:16 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 05:07:31 - mmengine - INFO - Epoch(val) [10][2500/3836] eta: 0:00:16 time: 0.0124 data_time: 0.0005 memory: 480 2022/09/17 05:07:32 - mmengine - INFO - Epoch(val) [10][2600/3836] eta: 0:00:14 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 05:07:33 - mmengine - INFO - Epoch(val) [10][2700/3836] eta: 0:00:13 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 05:07:34 - mmengine - INFO - Epoch(val) [10][2800/3836] eta: 0:00:11 time: 0.0113 data_time: 0.0004 memory: 480 2022/09/17 05:07:36 - mmengine - INFO - Epoch(val) [10][2900/3836] eta: 0:00:10 time: 0.0110 data_time: 0.0005 memory: 480 2022/09/17 05:07:37 - mmengine - INFO - Epoch(val) [10][3000/3836] eta: 0:00:09 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 05:07:38 - mmengine - INFO - Epoch(val) [10][3100/3836] eta: 0:00:08 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 05:07:39 - mmengine - INFO - Epoch(val) [10][3200/3836] eta: 0:00:06 time: 0.0105 data_time: 0.0005 memory: 480 2022/09/17 05:07:40 - mmengine - INFO - Epoch(val) [10][3300/3836] eta: 0:00:05 time: 0.0106 data_time: 0.0005 memory: 480 2022/09/17 05:07:41 - mmengine - INFO - Epoch(val) [10][3400/3836] eta: 0:00:04 time: 0.0106 data_time: 0.0005 memory: 480 2022/09/17 05:07:42 - mmengine - INFO - Epoch(val) [10][3500/3836] eta: 0:00:03 time: 0.0106 data_time: 0.0005 memory: 480 2022/09/17 05:07:43 - mmengine - INFO - Epoch(val) [10][3600/3836] eta: 0:00:02 time: 0.0106 data_time: 0.0005 memory: 480 2022/09/17 05:07:45 - mmengine - INFO - Epoch(val) [10][3700/3836] eta: 0:00:01 time: 0.0106 data_time: 0.0005 memory: 480 2022/09/17 05:07:46 - mmengine - INFO - Epoch(val) [10][3800/3836] eta: 0:00:00 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 05:07:46 - mmengine - INFO - Epoch(val) [10][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.7917 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9350 SVT/recog/word_acc_ignore_case_symbol: 0.8825 SVTP/recog/word_acc_ignore_case_symbol: 0.8047 IC13/recog/word_acc_ignore_case_symbol: 0.9143 IC15/recog/word_acc_ignore_case_symbol: 0.7670 2022/09/17 05:10:03 - mmengine - INFO - Epoch(train) [11][100/10520] lr: 1.0000e-04 eta: 1 day, 13:24:15 time: 1.6199 data_time: 0.4658 memory: 56769 loss_visual: 0.0648 loss: 0.0648 2022/09/17 05:12:03 - mmengine - INFO - Epoch(train) [11][200/10520] lr: 1.0000e-04 eta: 1 day, 13:21:59 time: 1.7879 data_time: 0.7126 memory: 56769 loss_visual: 0.0661 loss: 0.0661 2022/09/17 05:13:59 - mmengine - INFO - Epoch(train) [11][300/10520] lr: 1.0000e-04 eta: 1 day, 13:19:39 time: 1.1232 data_time: 0.3066 memory: 56769 loss_visual: 0.0690 loss: 0.0690 2022/09/17 05:15:55 - mmengine - INFO - Epoch(train) [11][400/10520] lr: 1.0000e-04 eta: 1 day, 13:17:19 time: 0.8715 data_time: 0.0529 memory: 56769 loss_visual: 0.0641 loss: 0.0641 2022/09/17 05:17:53 - mmengine - INFO - Epoch(train) [11][500/10520] lr: 1.0000e-04 eta: 1 day, 13:15:00 time: 0.8790 data_time: 0.0242 memory: 56769 loss_visual: 0.0617 loss: 0.0617 2022/09/17 05:19:49 - mmengine - INFO - Epoch(train) [11][600/10520] lr: 1.0000e-04 eta: 1 day, 13:12:40 time: 0.8609 data_time: 0.0069 memory: 56769 loss_visual: 0.0675 loss: 0.0675 2022/09/17 05:21:46 - mmengine - INFO - Epoch(train) [11][700/10520] lr: 1.0000e-04 eta: 1 day, 13:10:21 time: 0.9076 data_time: 0.0071 memory: 56769 loss_visual: 0.0668 loss: 0.0668 2022/09/17 05:23:44 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 05:23:44 - mmengine - INFO - Epoch(train) [11][800/10520] lr: 1.0000e-04 eta: 1 day, 13:08:03 time: 0.9757 data_time: 0.0071 memory: 56769 loss_visual: 0.0639 loss: 0.0639 2022/09/17 05:25:45 - mmengine - INFO - Epoch(train) [11][900/10520] lr: 1.0000e-04 eta: 1 day, 13:05:48 time: 1.4715 data_time: 0.4526 memory: 56769 loss_visual: 0.0638 loss: 0.0638 2022/09/17 05:27:44 - mmengine - INFO - Epoch(train) [11][1000/10520] lr: 1.0000e-04 eta: 1 day, 13:03:31 time: 1.7517 data_time: 0.7350 memory: 56769 loss_visual: 0.0611 loss: 0.0611 2022/09/17 05:29:42 - mmengine - INFO - Epoch(train) [11][1100/10520] lr: 1.0000e-04 eta: 1 day, 13:01:13 time: 1.1845 data_time: 0.3316 memory: 56769 loss_visual: 0.0642 loss: 0.0642 2022/09/17 05:31:39 - mmengine - INFO - Epoch(train) [11][1200/10520] lr: 1.0000e-04 eta: 1 day, 12:58:54 time: 0.9238 data_time: 0.0259 memory: 56769 loss_visual: 0.0665 loss: 0.0665 2022/09/17 05:33:36 - mmengine - INFO - Epoch(train) [11][1300/10520] lr: 1.0000e-04 eta: 1 day, 12:56:36 time: 0.9391 data_time: 0.0288 memory: 56769 loss_visual: 0.0646 loss: 0.0646 2022/09/17 05:35:32 - mmengine - INFO - Epoch(train) [11][1400/10520] lr: 1.0000e-04 eta: 1 day, 12:54:16 time: 0.8877 data_time: 0.0081 memory: 56769 loss_visual: 0.0638 loss: 0.0638 2022/09/17 05:37:29 - mmengine - INFO - Epoch(train) [11][1500/10520] lr: 1.0000e-04 eta: 1 day, 12:51:58 time: 0.9120 data_time: 0.0101 memory: 56769 loss_visual: 0.0717 loss: 0.0717 2022/09/17 05:39:27 - mmengine - INFO - Epoch(train) [11][1600/10520] lr: 1.0000e-04 eta: 1 day, 12:49:39 time: 1.0118 data_time: 0.0072 memory: 56769 loss_visual: 0.0638 loss: 0.0638 2022/09/17 05:41:29 - mmengine - INFO - Epoch(train) [11][1700/10520] lr: 1.0000e-04 eta: 1 day, 12:47:26 time: 1.5676 data_time: 0.4145 memory: 56769 loss_visual: 0.0651 loss: 0.0651 2022/09/17 05:43:28 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 05:43:28 - mmengine - INFO - Epoch(train) [11][1800/10520] lr: 1.0000e-04 eta: 1 day, 12:45:09 time: 1.6921 data_time: 0.7426 memory: 56769 loss_visual: 0.0672 loss: 0.0672 2022/09/17 05:45:24 - mmengine - INFO - Epoch(train) [11][1900/10520] lr: 1.0000e-04 eta: 1 day, 12:42:49 time: 1.1544 data_time: 0.3058 memory: 56769 loss_visual: 0.0670 loss: 0.0670 2022/09/17 05:47:20 - mmengine - INFO - Epoch(train) [11][2000/10520] lr: 1.0000e-04 eta: 1 day, 12:40:30 time: 0.8467 data_time: 0.0253 memory: 56769 loss_visual: 0.0643 loss: 0.0643 2022/09/17 05:49:16 - mmengine - INFO - Epoch(train) [11][2100/10520] lr: 1.0000e-04 eta: 1 day, 12:38:11 time: 0.8535 data_time: 0.0239 memory: 56769 loss_visual: 0.0644 loss: 0.0644 2022/09/17 05:51:12 - mmengine - INFO - Epoch(train) [11][2200/10520] lr: 1.0000e-04 eta: 1 day, 12:35:52 time: 0.8586 data_time: 0.0064 memory: 56769 loss_visual: 0.0634 loss: 0.0634 2022/09/17 05:53:09 - mmengine - INFO - Epoch(train) [11][2300/10520] lr: 1.0000e-04 eta: 1 day, 12:33:33 time: 0.9600 data_time: 0.0075 memory: 56769 loss_visual: 0.0658 loss: 0.0658 2022/09/17 05:55:06 - mmengine - INFO - Epoch(train) [11][2400/10520] lr: 1.0000e-04 eta: 1 day, 12:31:14 time: 1.0630 data_time: 0.0076 memory: 56769 loss_visual: 0.0643 loss: 0.0643 2022/09/17 05:57:08 - mmengine - INFO - Epoch(train) [11][2500/10520] lr: 1.0000e-04 eta: 1 day, 12:29:01 time: 1.5048 data_time: 0.4542 memory: 56769 loss_visual: 0.0644 loss: 0.0644 2022/09/17 05:59:07 - mmengine - INFO - Epoch(train) [11][2600/10520] lr: 1.0000e-04 eta: 1 day, 12:26:44 time: 1.7093 data_time: 0.7665 memory: 56769 loss_visual: 0.0675 loss: 0.0675 2022/09/17 06:01:08 - mmengine - INFO - Epoch(train) [11][2700/10520] lr: 1.0000e-04 eta: 1 day, 12:24:30 time: 1.1204 data_time: 0.2986 memory: 56769 loss_visual: 0.0608 loss: 0.0608 2022/09/17 06:03:04 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 06:03:04 - mmengine - INFO - Epoch(train) [11][2800/10520] lr: 1.0000e-04 eta: 1 day, 12:22:11 time: 0.8970 data_time: 0.0411 memory: 56769 loss_visual: 0.0620 loss: 0.0620 2022/09/17 06:05:00 - mmengine - INFO - Epoch(train) [11][2900/10520] lr: 1.0000e-04 eta: 1 day, 12:19:52 time: 0.9181 data_time: 0.0603 memory: 56769 loss_visual: 0.0639 loss: 0.0639 2022/09/17 06:06:56 - mmengine - INFO - Epoch(train) [11][3000/10520] lr: 1.0000e-04 eta: 1 day, 12:17:33 time: 0.8563 data_time: 0.0072 memory: 56769 loss_visual: 0.0655 loss: 0.0655 2022/09/17 06:08:52 - mmengine - INFO - Epoch(train) [11][3100/10520] lr: 1.0000e-04 eta: 1 day, 12:15:14 time: 0.9136 data_time: 0.0075 memory: 56769 loss_visual: 0.0665 loss: 0.0665 2022/09/17 06:10:49 - mmengine - INFO - Epoch(train) [11][3200/10520] lr: 1.0000e-04 eta: 1 day, 12:12:56 time: 0.9783 data_time: 0.0069 memory: 56769 loss_visual: 0.0666 loss: 0.0666 2022/09/17 06:12:51 - mmengine - INFO - Epoch(train) [11][3300/10520] lr: 1.0000e-04 eta: 1 day, 12:10:43 time: 1.5602 data_time: 0.4298 memory: 56769 loss_visual: 0.0669 loss: 0.0669 2022/09/17 06:14:51 - mmengine - INFO - Epoch(train) [11][3400/10520] lr: 1.0000e-04 eta: 1 day, 12:08:28 time: 1.7663 data_time: 0.7851 memory: 56769 loss_visual: 0.0691 loss: 0.0691 2022/09/17 06:16:47 - mmengine - INFO - Epoch(train) [11][3500/10520] lr: 1.0000e-04 eta: 1 day, 12:06:09 time: 1.1588 data_time: 0.3093 memory: 56769 loss_visual: 0.0652 loss: 0.0652 2022/09/17 06:18:45 - mmengine - INFO - Epoch(train) [11][3600/10520] lr: 1.0000e-04 eta: 1 day, 12:03:52 time: 0.9114 data_time: 0.0248 memory: 56769 loss_visual: 0.0649 loss: 0.0649 2022/09/17 06:20:42 - mmengine - INFO - Epoch(train) [11][3700/10520] lr: 1.0000e-04 eta: 1 day, 12:01:34 time: 0.9034 data_time: 0.0246 memory: 56769 loss_visual: 0.0655 loss: 0.0655 2022/09/17 06:22:38 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 06:22:38 - mmengine - INFO - Epoch(train) [11][3800/10520] lr: 1.0000e-04 eta: 1 day, 11:59:15 time: 0.8242 data_time: 0.0071 memory: 56769 loss_visual: 0.0647 loss: 0.0647 2022/09/17 06:24:34 - mmengine - INFO - Epoch(train) [11][3900/10520] lr: 1.0000e-04 eta: 1 day, 11:56:56 time: 0.9499 data_time: 0.0068 memory: 56769 loss_visual: 0.0630 loss: 0.0630 2022/09/17 06:26:31 - mmengine - INFO - Epoch(train) [11][4000/10520] lr: 1.0000e-04 eta: 1 day, 11:54:38 time: 1.0183 data_time: 0.0082 memory: 56769 loss_visual: 0.0663 loss: 0.0663 2022/09/17 06:28:33 - mmengine - INFO - Epoch(train) [11][4100/10520] lr: 1.0000e-04 eta: 1 day, 11:52:26 time: 1.5471 data_time: 0.4266 memory: 56769 loss_visual: 0.0650 loss: 0.0650 2022/09/17 06:30:32 - mmengine - INFO - Epoch(train) [11][4200/10520] lr: 1.0000e-04 eta: 1 day, 11:50:10 time: 1.7455 data_time: 0.6939 memory: 56769 loss_visual: 0.0703 loss: 0.0703 2022/09/17 06:32:28 - mmengine - INFO - Epoch(train) [11][4300/10520] lr: 1.0000e-04 eta: 1 day, 11:47:51 time: 1.1176 data_time: 0.2471 memory: 56769 loss_visual: 0.0665 loss: 0.0665 2022/09/17 06:34:25 - mmengine - INFO - Epoch(train) [11][4400/10520] lr: 1.0000e-04 eta: 1 day, 11:45:33 time: 0.9005 data_time: 0.0755 memory: 56769 loss_visual: 0.0678 loss: 0.0678 2022/09/17 06:36:21 - mmengine - INFO - Epoch(train) [11][4500/10520] lr: 1.0000e-04 eta: 1 day, 11:43:14 time: 0.8629 data_time: 0.0409 memory: 56769 loss_visual: 0.0658 loss: 0.0658 2022/09/17 06:38:16 - mmengine - INFO - Epoch(train) [11][4600/10520] lr: 1.0000e-04 eta: 1 day, 11:40:56 time: 0.8775 data_time: 0.0068 memory: 56769 loss_visual: 0.0623 loss: 0.0623 2022/09/17 06:40:14 - mmengine - INFO - Epoch(train) [11][4700/10520] lr: 1.0000e-04 eta: 1 day, 11:38:39 time: 0.9326 data_time: 0.0068 memory: 56769 loss_visual: 0.0660 loss: 0.0660 2022/09/17 06:42:11 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 06:42:11 - mmengine - INFO - Epoch(train) [11][4800/10520] lr: 1.0000e-04 eta: 1 day, 11:36:21 time: 1.0292 data_time: 0.0068 memory: 56769 loss_visual: 0.0642 loss: 0.0642 2022/09/17 06:44:13 - mmengine - INFO - Epoch(train) [11][4900/10520] lr: 1.0000e-04 eta: 1 day, 11:34:08 time: 1.5499 data_time: 0.4050 memory: 56769 loss_visual: 0.0692 loss: 0.0692 2022/09/17 06:46:12 - mmengine - INFO - Epoch(train) [11][5000/10520] lr: 1.0000e-04 eta: 1 day, 11:31:52 time: 1.7207 data_time: 0.7261 memory: 56769 loss_visual: 0.0636 loss: 0.0636 2022/09/17 06:48:07 - mmengine - INFO - Epoch(train) [11][5100/10520] lr: 1.0000e-04 eta: 1 day, 11:29:34 time: 1.0936 data_time: 0.2586 memory: 56769 loss_visual: 0.0602 loss: 0.0602 2022/09/17 06:50:04 - mmengine - INFO - Epoch(train) [11][5200/10520] lr: 1.0000e-04 eta: 1 day, 11:27:16 time: 0.9145 data_time: 0.0402 memory: 56769 loss_visual: 0.0632 loss: 0.0632 2022/09/17 06:51:59 - mmengine - INFO - Epoch(train) [11][5300/10520] lr: 1.0000e-04 eta: 1 day, 11:24:57 time: 0.8931 data_time: 0.0392 memory: 56769 loss_visual: 0.0683 loss: 0.0683 2022/09/17 06:53:55 - mmengine - INFO - Epoch(train) [11][5400/10520] lr: 1.0000e-04 eta: 1 day, 11:22:39 time: 0.8619 data_time: 0.0071 memory: 56769 loss_visual: 0.0660 loss: 0.0660 2022/09/17 06:55:52 - mmengine - INFO - Epoch(train) [11][5500/10520] lr: 1.0000e-04 eta: 1 day, 11:20:21 time: 0.9115 data_time: 0.0069 memory: 56769 loss_visual: 0.0616 loss: 0.0616 2022/09/17 06:57:48 - mmengine - INFO - Epoch(train) [11][5600/10520] lr: 1.0000e-04 eta: 1 day, 11:18:04 time: 0.9922 data_time: 0.0071 memory: 56769 loss_visual: 0.0640 loss: 0.0640 2022/09/17 06:59:51 - mmengine - INFO - Epoch(train) [11][5700/10520] lr: 1.0000e-04 eta: 1 day, 11:15:52 time: 1.5292 data_time: 0.3845 memory: 56769 loss_visual: 0.0663 loss: 0.0663 2022/09/17 07:01:49 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 07:01:49 - mmengine - INFO - Epoch(train) [11][5800/10520] lr: 1.0000e-04 eta: 1 day, 11:13:36 time: 1.6921 data_time: 0.6350 memory: 56769 loss_visual: 0.0661 loss: 0.0661 2022/09/17 07:03:47 - mmengine - INFO - Epoch(train) [11][5900/10520] lr: 1.0000e-04 eta: 1 day, 11:11:19 time: 1.1911 data_time: 0.2750 memory: 56769 loss_visual: 0.0624 loss: 0.0624 2022/09/17 07:05:45 - mmengine - INFO - Epoch(train) [11][6000/10520] lr: 1.0000e-04 eta: 1 day, 11:09:03 time: 0.9430 data_time: 0.0774 memory: 56769 loss_visual: 0.0632 loss: 0.0632 2022/09/17 07:07:41 - mmengine - INFO - Epoch(train) [11][6100/10520] lr: 1.0000e-04 eta: 1 day, 11:06:46 time: 0.9038 data_time: 0.0402 memory: 56769 loss_visual: 0.0646 loss: 0.0646 2022/09/17 07:09:38 - mmengine - INFO - Epoch(train) [11][6200/10520] lr: 1.0000e-04 eta: 1 day, 11:04:29 time: 0.8608 data_time: 0.0068 memory: 56769 loss_visual: 0.0641 loss: 0.0641 2022/09/17 07:11:36 - mmengine - INFO - Epoch(train) [11][6300/10520] lr: 1.0000e-04 eta: 1 day, 11:02:12 time: 0.9125 data_time: 0.0068 memory: 56769 loss_visual: 0.0630 loss: 0.0630 2022/09/17 07:13:34 - mmengine - INFO - Epoch(train) [11][6400/10520] lr: 1.0000e-04 eta: 1 day, 10:59:56 time: 1.0011 data_time: 0.0085 memory: 56769 loss_visual: 0.0659 loss: 0.0659 2022/09/17 07:15:36 - mmengine - INFO - Epoch(train) [11][6500/10520] lr: 1.0000e-04 eta: 1 day, 10:57:44 time: 1.5012 data_time: 0.4585 memory: 56769 loss_visual: 0.0617 loss: 0.0617 2022/09/17 07:17:36 - mmengine - INFO - Epoch(train) [11][6600/10520] lr: 1.0000e-04 eta: 1 day, 10:55:30 time: 1.7703 data_time: 0.6904 memory: 56769 loss_visual: 0.0663 loss: 0.0663 2022/09/17 07:19:32 - mmengine - INFO - Epoch(train) [11][6700/10520] lr: 1.0000e-04 eta: 1 day, 10:53:12 time: 1.1379 data_time: 0.2878 memory: 56769 loss_visual: 0.0697 loss: 0.0697 2022/09/17 07:21:29 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 07:21:29 - mmengine - INFO - Epoch(train) [11][6800/10520] lr: 1.0000e-04 eta: 1 day, 10:50:55 time: 0.8711 data_time: 0.0558 memory: 56769 loss_visual: 0.0647 loss: 0.0647 2022/09/17 07:23:25 - mmengine - INFO - Epoch(train) [11][6900/10520] lr: 1.0000e-04 eta: 1 day, 10:48:38 time: 0.8923 data_time: 0.0397 memory: 56769 loss_visual: 0.0648 loss: 0.0648 2022/09/17 07:25:21 - mmengine - INFO - Epoch(train) [11][7000/10520] lr: 1.0000e-04 eta: 1 day, 10:46:20 time: 0.8856 data_time: 0.0069 memory: 56769 loss_visual: 0.0657 loss: 0.0657 2022/09/17 07:27:18 - mmengine - INFO - Epoch(train) [11][7100/10520] lr: 1.0000e-04 eta: 1 day, 10:44:04 time: 0.9108 data_time: 0.0070 memory: 56769 loss_visual: 0.0642 loss: 0.0642 2022/09/17 07:29:16 - mmengine - INFO - Epoch(train) [11][7200/10520] lr: 1.0000e-04 eta: 1 day, 10:41:47 time: 0.9930 data_time: 0.0066 memory: 56769 loss_visual: 0.0643 loss: 0.0643 2022/09/17 07:31:17 - mmengine - INFO - Epoch(train) [11][7300/10520] lr: 1.0000e-04 eta: 1 day, 10:39:35 time: 1.4812 data_time: 0.4561 memory: 56769 loss_visual: 0.0658 loss: 0.0658 2022/09/17 07:33:17 - mmengine - INFO - Epoch(train) [11][7400/10520] lr: 1.0000e-04 eta: 1 day, 10:37:20 time: 1.7065 data_time: 0.6445 memory: 56769 loss_visual: 0.0630 loss: 0.0630 2022/09/17 07:35:13 - mmengine - INFO - Epoch(train) [11][7500/10520] lr: 1.0000e-04 eta: 1 day, 10:35:04 time: 1.1144 data_time: 0.2877 memory: 56769 loss_visual: 0.0654 loss: 0.0654 2022/09/17 07:37:11 - mmengine - INFO - Epoch(train) [11][7600/10520] lr: 1.0000e-04 eta: 1 day, 10:32:47 time: 0.8892 data_time: 0.0575 memory: 56769 loss_visual: 0.0638 loss: 0.0638 2022/09/17 07:39:07 - mmengine - INFO - Epoch(train) [11][7700/10520] lr: 1.0000e-04 eta: 1 day, 10:30:30 time: 0.8607 data_time: 0.0434 memory: 56769 loss_visual: 0.0645 loss: 0.0645 2022/09/17 07:41:03 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 07:41:03 - mmengine - INFO - Epoch(train) [11][7800/10520] lr: 1.0000e-04 eta: 1 day, 10:28:13 time: 0.8645 data_time: 0.0077 memory: 56769 loss_visual: 0.0650 loss: 0.0650 2022/09/17 07:43:00 - mmengine - INFO - Epoch(train) [11][7900/10520] lr: 1.0000e-04 eta: 1 day, 10:25:57 time: 0.9545 data_time: 0.0067 memory: 56769 loss_visual: 0.0632 loss: 0.0632 2022/09/17 07:44:58 - mmengine - INFO - Epoch(train) [11][8000/10520] lr: 1.0000e-04 eta: 1 day, 10:23:41 time: 1.0301 data_time: 0.0066 memory: 56769 loss_visual: 0.0597 loss: 0.0597 2022/09/17 07:46:59 - mmengine - INFO - Epoch(train) [11][8100/10520] lr: 1.0000e-04 eta: 1 day, 10:21:28 time: 1.5127 data_time: 0.4149 memory: 56769 loss_visual: 0.0668 loss: 0.0668 2022/09/17 07:48:59 - mmengine - INFO - Epoch(train) [11][8200/10520] lr: 1.0000e-04 eta: 1 day, 10:19:15 time: 1.7259 data_time: 0.7731 memory: 56769 loss_visual: 0.0623 loss: 0.0623 2022/09/17 07:50:56 - mmengine - INFO - Epoch(train) [11][8300/10520] lr: 1.0000e-04 eta: 1 day, 10:16:59 time: 1.1306 data_time: 0.3001 memory: 56769 loss_visual: 0.0601 loss: 0.0601 2022/09/17 07:52:54 - mmengine - INFO - Epoch(train) [11][8400/10520] lr: 1.0000e-04 eta: 1 day, 10:14:43 time: 0.9439 data_time: 0.0939 memory: 56769 loss_visual: 0.0635 loss: 0.0635 2022/09/17 07:54:52 - mmengine - INFO - Epoch(train) [11][8500/10520] lr: 1.0000e-04 eta: 1 day, 10:12:27 time: 0.9409 data_time: 0.0907 memory: 56769 loss_visual: 0.0644 loss: 0.0644 2022/09/17 07:56:48 - mmengine - INFO - Epoch(train) [11][8600/10520] lr: 1.0000e-04 eta: 1 day, 10:10:11 time: 0.8619 data_time: 0.0068 memory: 56769 loss_visual: 0.0607 loss: 0.0607 2022/09/17 07:58:45 - mmengine - INFO - Epoch(train) [11][8700/10520] lr: 1.0000e-04 eta: 1 day, 10:07:55 time: 0.9169 data_time: 0.0069 memory: 56769 loss_visual: 0.0640 loss: 0.0640 2022/09/17 08:00:43 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 08:00:43 - mmengine - INFO - Epoch(train) [11][8800/10520] lr: 1.0000e-04 eta: 1 day, 10:05:39 time: 0.9885 data_time: 0.0071 memory: 56769 loss_visual: 0.0598 loss: 0.0598 2022/09/17 08:02:45 - mmengine - INFO - Epoch(train) [11][8900/10520] lr: 1.0000e-04 eta: 1 day, 10:03:27 time: 1.5538 data_time: 0.3951 memory: 56769 loss_visual: 0.0627 loss: 0.0627 2022/09/17 08:04:45 - mmengine - INFO - Epoch(train) [11][9000/10520] lr: 1.0000e-04 eta: 1 day, 10:01:13 time: 1.7028 data_time: 0.7301 memory: 56769 loss_visual: 0.0618 loss: 0.0618 2022/09/17 08:06:42 - mmengine - INFO - Epoch(train) [11][9100/10520] lr: 1.0000e-04 eta: 1 day, 9:58:58 time: 1.1180 data_time: 0.2648 memory: 56769 loss_visual: 0.0608 loss: 0.0608 2022/09/17 08:08:40 - mmengine - INFO - Epoch(train) [11][9200/10520] lr: 1.0000e-04 eta: 1 day, 9:56:42 time: 0.9338 data_time: 0.0941 memory: 56769 loss_visual: 0.0636 loss: 0.0636 2022/09/17 08:10:37 - mmengine - INFO - Epoch(train) [11][9300/10520] lr: 1.0000e-04 eta: 1 day, 9:54:26 time: 0.8649 data_time: 0.0421 memory: 56769 loss_visual: 0.0656 loss: 0.0656 2022/09/17 08:12:34 - mmengine - INFO - Epoch(train) [11][9400/10520] lr: 1.0000e-04 eta: 1 day, 9:52:11 time: 0.8544 data_time: 0.0075 memory: 56769 loss_visual: 0.0639 loss: 0.0639 2022/09/17 08:14:32 - mmengine - INFO - Epoch(train) [11][9500/10520] lr: 1.0000e-04 eta: 1 day, 9:49:56 time: 0.9193 data_time: 0.0076 memory: 56769 loss_visual: 0.0630 loss: 0.0630 2022/09/17 08:16:31 - mmengine - INFO - Epoch(train) [11][9600/10520] lr: 1.0000e-04 eta: 1 day, 9:47:42 time: 1.0329 data_time: 0.0074 memory: 56769 loss_visual: 0.0669 loss: 0.0669 2022/09/17 08:18:33 - mmengine - INFO - Epoch(train) [11][9700/10520] lr: 1.0000e-04 eta: 1 day, 9:45:30 time: 1.6208 data_time: 0.4012 memory: 56769 loss_visual: 0.0626 loss: 0.0626 2022/09/17 08:20:33 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 08:20:33 - mmengine - INFO - Epoch(train) [11][9800/10520] lr: 1.0000e-04 eta: 1 day, 9:43:17 time: 1.7542 data_time: 0.7189 memory: 56769 loss_visual: 0.0656 loss: 0.0656 2022/09/17 08:22:30 - mmengine - INFO - Epoch(train) [11][9900/10520] lr: 1.0000e-04 eta: 1 day, 9:41:01 time: 1.1312 data_time: 0.2713 memory: 56769 loss_visual: 0.0643 loss: 0.0643 2022/09/17 08:24:28 - mmengine - INFO - Epoch(train) [11][10000/10520] lr: 1.0000e-04 eta: 1 day, 9:38:45 time: 0.9020 data_time: 0.0427 memory: 56769 loss_visual: 0.0662 loss: 0.0662 2022/09/17 08:26:24 - mmengine - INFO - Epoch(train) [11][10100/10520] lr: 1.0000e-04 eta: 1 day, 9:36:30 time: 0.9422 data_time: 0.0429 memory: 56769 loss_visual: 0.0652 loss: 0.0652 2022/09/17 08:28:20 - mmengine - INFO - Epoch(train) [11][10200/10520] lr: 1.0000e-04 eta: 1 day, 9:34:13 time: 0.8723 data_time: 0.0069 memory: 56769 loss_visual: 0.0682 loss: 0.0682 2022/09/17 08:30:19 - mmengine - INFO - Epoch(train) [11][10300/10520] lr: 1.0000e-04 eta: 1 day, 9:31:59 time: 0.9406 data_time: 0.0068 memory: 56769 loss_visual: 0.0640 loss: 0.0640 2022/09/17 08:32:16 - mmengine - INFO - Epoch(train) [11][10400/10520] lr: 1.0000e-04 eta: 1 day, 9:29:43 time: 1.0335 data_time: 0.0084 memory: 56769 loss_visual: 0.0633 loss: 0.0633 2022/09/17 08:34:13 - mmengine - INFO - Epoch(train) [11][10500/10520] lr: 1.0000e-04 eta: 1 day, 9:27:27 time: 1.2626 data_time: 0.2589 memory: 56769 loss_visual: 0.0629 loss: 0.0629 2022/09/17 08:34:31 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 08:34:31 - mmengine - INFO - Saving checkpoint at 11 epochs 2022/09/17 08:34:52 - mmengine - INFO - Epoch(val) [11][100/3836] eta: 0:05:53 time: 0.0946 data_time: 0.0005 memory: 56769 2022/09/17 08:34:56 - mmengine - INFO - Epoch(val) [11][200/3836] eta: 0:00:43 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 08:34:58 - mmengine - INFO - Epoch(val) [11][300/3836] eta: 0:00:41 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/17 08:34:59 - mmengine - INFO - Epoch(val) [11][400/3836] eta: 0:00:40 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 08:35:00 - mmengine - INFO - Epoch(val) [11][500/3836] eta: 0:00:40 time: 0.0121 data_time: 0.0005 memory: 480 2022/09/17 08:35:01 - mmengine - INFO - Epoch(val) [11][600/3836] eta: 0:00:37 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 08:35:03 - mmengine - INFO - Epoch(val) [11][700/3836] eta: 0:00:36 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 08:35:04 - mmengine - INFO - Epoch(val) [11][800/3836] eta: 0:00:34 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/17 08:35:05 - mmengine - INFO - Epoch(val) [11][900/3836] eta: 0:00:38 time: 0.0130 data_time: 0.0007 memory: 480 2022/09/17 08:35:06 - mmengine - INFO - Epoch(val) [11][1000/3836] eta: 0:00:32 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 08:35:07 - mmengine - INFO - Epoch(val) [11][1100/3836] eta: 0:00:30 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/17 08:35:08 - mmengine - INFO - Epoch(val) [11][1200/3836] eta: 0:00:28 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/17 08:35:09 - mmengine - INFO - Epoch(val) [11][1300/3836] eta: 0:00:27 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/17 08:35:11 - mmengine - INFO - Epoch(val) [11][1400/3836] eta: 0:00:28 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 08:35:12 - mmengine - INFO - Epoch(val) [11][1500/3836] eta: 0:00:31 time: 0.0135 data_time: 0.0005 memory: 480 2022/09/17 08:35:13 - mmengine - INFO - Epoch(val) [11][1600/3836] eta: 0:00:26 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/17 08:35:14 - mmengine - INFO - Epoch(val) [11][1700/3836] eta: 0:00:24 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 08:35:15 - mmengine - INFO - Epoch(val) [11][1800/3836] eta: 0:00:23 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 08:35:17 - mmengine - INFO - Epoch(val) [11][1900/3836] eta: 0:00:22 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 08:35:18 - mmengine - INFO - Epoch(val) [11][2000/3836] eta: 0:00:21 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 08:35:19 - mmengine - INFO - Epoch(val) [11][2100/3836] eta: 0:00:20 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 08:35:20 - mmengine - INFO - Epoch(val) [11][2200/3836] eta: 0:00:17 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/17 08:35:21 - mmengine - INFO - Epoch(val) [11][2300/3836] eta: 0:00:17 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 08:35:23 - mmengine - INFO - Epoch(val) [11][2400/3836] eta: 0:00:17 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/17 08:35:24 - mmengine - INFO - Epoch(val) [11][2500/3836] eta: 0:00:14 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/17 08:35:25 - mmengine - INFO - Epoch(val) [11][2600/3836] eta: 0:00:14 time: 0.0114 data_time: 0.0004 memory: 480 2022/09/17 08:35:26 - mmengine - INFO - Epoch(val) [11][2700/3836] eta: 0:00:13 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 08:35:27 - mmengine - INFO - Epoch(val) [11][2800/3836] eta: 0:00:12 time: 0.0116 data_time: 0.0004 memory: 480 2022/09/17 08:35:28 - mmengine - INFO - Epoch(val) [11][2900/3836] eta: 0:00:10 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 08:35:30 - mmengine - INFO - Epoch(val) [11][3000/3836] eta: 0:00:09 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 08:35:31 - mmengine - INFO - Epoch(val) [11][3100/3836] eta: 0:00:08 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 08:35:32 - mmengine - INFO - Epoch(val) [11][3200/3836] eta: 0:00:06 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/17 08:35:33 - mmengine - INFO - Epoch(val) [11][3300/3836] eta: 0:00:05 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/17 08:35:34 - mmengine - INFO - Epoch(val) [11][3400/3836] eta: 0:00:04 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/17 08:35:35 - mmengine - INFO - Epoch(val) [11][3500/3836] eta: 0:00:03 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/17 08:35:36 - mmengine - INFO - Epoch(val) [11][3600/3836] eta: 0:00:02 time: 0.0108 data_time: 0.0004 memory: 480 2022/09/17 08:35:37 - mmengine - INFO - Epoch(val) [11][3700/3836] eta: 0:00:01 time: 0.0108 data_time: 0.0004 memory: 480 2022/09/17 08:35:39 - mmengine - INFO - Epoch(val) [11][3800/3836] eta: 0:00:00 time: 0.0108 data_time: 0.0004 memory: 480 2022/09/17 08:35:39 - mmengine - INFO - Epoch(val) [11][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.8437 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9410 SVT/recog/word_acc_ignore_case_symbol: 0.8918 SVTP/recog/word_acc_ignore_case_symbol: 0.7984 IC13/recog/word_acc_ignore_case_symbol: 0.9172 IC15/recog/word_acc_ignore_case_symbol: 0.7684 2022/09/17 08:38:01 - mmengine - INFO - Epoch(train) [12][100/10520] lr: 1.0000e-04 eta: 1 day, 9:25:01 time: 1.5518 data_time: 0.5018 memory: 56769 loss_visual: 0.0590 loss: 0.0590 2022/09/17 08:40:04 - mmengine - INFO - Epoch(train) [12][200/10520] lr: 1.0000e-04 eta: 1 day, 9:22:50 time: 1.5455 data_time: 0.4274 memory: 56769 loss_visual: 0.0641 loss: 0.0641 2022/09/17 08:41:41 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 08:42:08 - mmengine - INFO - Epoch(train) [12][300/10520] lr: 1.0000e-04 eta: 1 day, 9:20:40 time: 1.4183 data_time: 0.3860 memory: 56769 loss_visual: 0.0646 loss: 0.0646 2022/09/17 08:44:12 - mmengine - INFO - Epoch(train) [12][400/10520] lr: 1.0000e-04 eta: 1 day, 9:18:30 time: 1.3870 data_time: 0.2630 memory: 56769 loss_visual: 0.0592 loss: 0.0592 2022/09/17 08:46:14 - mmengine - INFO - Epoch(train) [12][500/10520] lr: 1.0000e-04 eta: 1 day, 9:16:19 time: 1.1006 data_time: 0.0070 memory: 56769 loss_visual: 0.0619 loss: 0.0619 2022/09/17 08:48:15 - mmengine - INFO - Epoch(train) [12][600/10520] lr: 1.0000e-04 eta: 1 day, 9:14:07 time: 0.9499 data_time: 0.0071 memory: 56769 loss_visual: 0.0662 loss: 0.0662 2022/09/17 08:50:19 - mmengine - INFO - Epoch(train) [12][700/10520] lr: 1.0000e-04 eta: 1 day, 9:11:57 time: 0.9001 data_time: 0.0077 memory: 56769 loss_visual: 0.0636 loss: 0.0636 2022/09/17 08:52:21 - mmengine - INFO - Epoch(train) [12][800/10520] lr: 1.0000e-04 eta: 1 day, 9:09:45 time: 0.8971 data_time: 0.0370 memory: 56769 loss_visual: 0.0657 loss: 0.0657 2022/09/17 08:54:30 - mmengine - INFO - Epoch(train) [12][900/10520] lr: 1.0000e-04 eta: 1 day, 9:07:40 time: 1.5520 data_time: 0.5306 memory: 56769 loss_visual: 0.0659 loss: 0.0659 2022/09/17 08:56:32 - mmengine - INFO - Epoch(train) [12][1000/10520] lr: 1.0000e-04 eta: 1 day, 9:05:28 time: 1.4760 data_time: 0.4431 memory: 56769 loss_visual: 0.0586 loss: 0.0586 2022/09/17 08:58:38 - mmengine - INFO - Epoch(train) [12][1100/10520] lr: 1.0000e-04 eta: 1 day, 9:03:20 time: 1.4137 data_time: 0.3957 memory: 56769 loss_visual: 0.0653 loss: 0.0653 2022/09/17 09:00:42 - mmengine - INFO - Epoch(train) [12][1200/10520] lr: 1.0000e-04 eta: 1 day, 9:01:10 time: 1.3764 data_time: 0.2509 memory: 56769 loss_visual: 0.0612 loss: 0.0612 2022/09/17 09:02:17 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 09:02:45 - mmengine - INFO - Epoch(train) [12][1300/10520] lr: 1.0000e-04 eta: 1 day, 8:59:00 time: 1.1090 data_time: 0.0113 memory: 56769 loss_visual: 0.0632 loss: 0.0632 2022/09/17 09:04:48 - mmengine - INFO - Epoch(train) [12][1400/10520] lr: 1.0000e-04 eta: 1 day, 8:56:50 time: 0.9726 data_time: 0.0072 memory: 56769 loss_visual: 0.0673 loss: 0.0673 2022/09/17 09:06:51 - mmengine - INFO - Epoch(train) [12][1500/10520] lr: 1.0000e-04 eta: 1 day, 8:54:39 time: 0.9130 data_time: 0.0071 memory: 56769 loss_visual: 0.0617 loss: 0.0617 2022/09/17 09:08:53 - mmengine - INFO - Epoch(train) [12][1600/10520] lr: 1.0000e-04 eta: 1 day, 8:52:28 time: 0.8419 data_time: 0.0256 memory: 56769 loss_visual: 0.0619 loss: 0.0619 2022/09/17 09:11:02 - mmengine - INFO - Epoch(train) [12][1700/10520] lr: 1.0000e-04 eta: 1 day, 8:50:22 time: 1.5074 data_time: 0.5474 memory: 56769 loss_visual: 0.0626 loss: 0.0626 2022/09/17 09:13:04 - mmengine - INFO - Epoch(train) [12][1800/10520] lr: 1.0000e-04 eta: 1 day, 8:48:11 time: 1.4853 data_time: 0.4650 memory: 56769 loss_visual: 0.0619 loss: 0.0619 2022/09/17 09:15:10 - mmengine - INFO - Epoch(train) [12][1900/10520] lr: 1.0000e-04 eta: 1 day, 8:46:03 time: 1.4475 data_time: 0.4279 memory: 56769 loss_visual: 0.0653 loss: 0.0653 2022/09/17 09:17:13 - mmengine - INFO - Epoch(train) [12][2000/10520] lr: 1.0000e-04 eta: 1 day, 8:43:52 time: 1.3616 data_time: 0.2659 memory: 56769 loss_visual: 0.0591 loss: 0.0591 2022/09/17 09:19:17 - mmengine - INFO - Epoch(train) [12][2100/10520] lr: 1.0000e-04 eta: 1 day, 8:41:42 time: 1.0609 data_time: 0.0076 memory: 56769 loss_visual: 0.0597 loss: 0.0597 2022/09/17 09:21:21 - mmengine - INFO - Epoch(train) [12][2200/10520] lr: 1.0000e-04 eta: 1 day, 8:39:33 time: 0.9400 data_time: 0.0115 memory: 56769 loss_visual: 0.0607 loss: 0.0607 2022/09/17 09:23:01 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 09:23:23 - mmengine - INFO - Epoch(train) [12][2300/10520] lr: 1.0000e-04 eta: 1 day, 8:37:22 time: 0.8922 data_time: 0.0086 memory: 56769 loss_visual: 0.0608 loss: 0.0608 2022/09/17 09:25:26 - mmengine - INFO - Epoch(train) [12][2400/10520] lr: 1.0000e-04 eta: 1 day, 8:35:11 time: 0.8984 data_time: 0.0229 memory: 56769 loss_visual: 0.0619 loss: 0.0619 2022/09/17 09:27:35 - mmengine - INFO - Epoch(train) [12][2500/10520] lr: 1.0000e-04 eta: 1 day, 8:33:06 time: 1.5276 data_time: 0.4451 memory: 56769 loss_visual: 0.0679 loss: 0.0679 2022/09/17 09:29:36 - mmengine - INFO - Epoch(train) [12][2600/10520] lr: 1.0000e-04 eta: 1 day, 8:30:54 time: 1.4917 data_time: 0.4753 memory: 56769 loss_visual: 0.0609 loss: 0.0609 2022/09/17 09:31:40 - mmengine - INFO - Epoch(train) [12][2700/10520] lr: 1.0000e-04 eta: 1 day, 8:28:44 time: 1.4226 data_time: 0.4195 memory: 56769 loss_visual: 0.0606 loss: 0.0606 2022/09/17 09:33:43 - mmengine - INFO - Epoch(train) [12][2800/10520] lr: 1.0000e-04 eta: 1 day, 8:26:34 time: 1.4295 data_time: 0.2916 memory: 56769 loss_visual: 0.0638 loss: 0.0638 2022/09/17 09:35:47 - mmengine - INFO - Epoch(train) [12][2900/10520] lr: 1.0000e-04 eta: 1 day, 8:24:24 time: 1.1212 data_time: 0.0085 memory: 56769 loss_visual: 0.0676 loss: 0.0676 2022/09/17 09:37:49 - mmengine - INFO - Epoch(train) [12][3000/10520] lr: 1.0000e-04 eta: 1 day, 8:22:13 time: 0.9524 data_time: 0.0076 memory: 56769 loss_visual: 0.0658 loss: 0.0658 2022/09/17 09:39:51 - mmengine - INFO - Epoch(train) [12][3100/10520] lr: 1.0000e-04 eta: 1 day, 8:20:02 time: 0.9105 data_time: 0.0073 memory: 56769 loss_visual: 0.0684 loss: 0.0684 2022/09/17 09:41:53 - mmengine - INFO - Epoch(train) [12][3200/10520] lr: 1.0000e-04 eta: 1 day, 8:17:51 time: 0.8457 data_time: 0.0260 memory: 56769 loss_visual: 0.0643 loss: 0.0643 2022/09/17 09:43:37 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 09:44:01 - mmengine - INFO - Epoch(train) [12][3300/10520] lr: 1.0000e-04 eta: 1 day, 8:15:44 time: 1.5265 data_time: 0.5163 memory: 56769 loss_visual: 0.0617 loss: 0.0617 2022/09/17 09:46:03 - mmengine - INFO - Epoch(train) [12][3400/10520] lr: 1.0000e-04 eta: 1 day, 8:13:33 time: 1.4514 data_time: 0.4533 memory: 56769 loss_visual: 0.0671 loss: 0.0671 2022/09/17 09:48:10 - mmengine - INFO - Epoch(train) [12][3500/10520] lr: 1.0000e-04 eta: 1 day, 8:11:26 time: 1.4936 data_time: 0.4172 memory: 56769 loss_visual: 0.0658 loss: 0.0658 2022/09/17 09:50:12 - mmengine - INFO - Epoch(train) [12][3600/10520] lr: 1.0000e-04 eta: 1 day, 8:09:16 time: 1.3446 data_time: 0.2614 memory: 56769 loss_visual: 0.0608 loss: 0.0608 2022/09/17 09:52:14 - mmengine - INFO - Epoch(train) [12][3700/10520] lr: 1.0000e-04 eta: 1 day, 8:07:04 time: 1.0992 data_time: 0.0071 memory: 56769 loss_visual: 0.0617 loss: 0.0617 2022/09/17 09:54:17 - mmengine - INFO - Epoch(train) [12][3800/10520] lr: 1.0000e-04 eta: 1 day, 8:04:54 time: 1.0076 data_time: 0.0076 memory: 56769 loss_visual: 0.0611 loss: 0.0611 2022/09/17 09:56:19 - mmengine - INFO - Epoch(train) [12][3900/10520] lr: 1.0000e-04 eta: 1 day, 8:02:43 time: 0.9210 data_time: 0.0080 memory: 56769 loss_visual: 0.0650 loss: 0.0650 2022/09/17 09:58:20 - mmengine - INFO - Epoch(train) [12][4000/10520] lr: 1.0000e-04 eta: 1 day, 8:00:32 time: 0.8849 data_time: 0.0268 memory: 56769 loss_visual: 0.0585 loss: 0.0585 2022/09/17 10:00:29 - mmengine - INFO - Epoch(train) [12][4100/10520] lr: 1.0000e-04 eta: 1 day, 7:58:25 time: 1.4894 data_time: 0.4618 memory: 56769 loss_visual: 0.0625 loss: 0.0625 2022/09/17 10:02:30 - mmengine - INFO - Epoch(train) [12][4200/10520] lr: 1.0000e-04 eta: 1 day, 7:56:14 time: 1.4528 data_time: 0.4056 memory: 56769 loss_visual: 0.0617 loss: 0.0617 2022/09/17 10:04:09 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 10:04:37 - mmengine - INFO - Epoch(train) [12][4300/10520] lr: 1.0000e-04 eta: 1 day, 7:54:07 time: 1.4506 data_time: 0.4150 memory: 56769 loss_visual: 0.0651 loss: 0.0651 2022/09/17 10:06:39 - mmengine - INFO - Epoch(train) [12][4400/10520] lr: 1.0000e-04 eta: 1 day, 7:51:56 time: 1.4299 data_time: 0.2891 memory: 56769 loss_visual: 0.0617 loss: 0.0617 2022/09/17 10:08:40 - mmengine - INFO - Epoch(train) [12][4500/10520] lr: 1.0000e-04 eta: 1 day, 7:49:44 time: 1.1111 data_time: 0.0074 memory: 56769 loss_visual: 0.0621 loss: 0.0621 2022/09/17 10:10:41 - mmengine - INFO - Epoch(train) [12][4600/10520] lr: 1.0000e-04 eta: 1 day, 7:47:32 time: 1.0295 data_time: 0.0084 memory: 56769 loss_visual: 0.0634 loss: 0.0634 2022/09/17 10:12:42 - mmengine - INFO - Epoch(train) [12][4700/10520] lr: 1.0000e-04 eta: 1 day, 7:45:21 time: 0.8763 data_time: 0.0073 memory: 56769 loss_visual: 0.0599 loss: 0.0599 2022/09/17 10:14:43 - mmengine - INFO - Epoch(train) [12][4800/10520] lr: 1.0000e-04 eta: 1 day, 7:43:10 time: 0.8806 data_time: 0.0255 memory: 56769 loss_visual: 0.0625 loss: 0.0625 2022/09/17 10:16:51 - mmengine - INFO - Epoch(train) [12][4900/10520] lr: 1.0000e-04 eta: 1 day, 7:41:03 time: 1.5004 data_time: 0.4860 memory: 56769 loss_visual: 0.0634 loss: 0.0634 2022/09/17 10:18:53 - mmengine - INFO - Epoch(train) [12][5000/10520] lr: 1.0000e-04 eta: 1 day, 7:38:52 time: 1.4607 data_time: 0.4290 memory: 56769 loss_visual: 0.0652 loss: 0.0652 2022/09/17 10:20:57 - mmengine - INFO - Epoch(train) [12][5100/10520] lr: 1.0000e-04 eta: 1 day, 7:36:43 time: 1.4318 data_time: 0.3889 memory: 56769 loss_visual: 0.0620 loss: 0.0620 2022/09/17 10:22:58 - mmengine - INFO - Epoch(train) [12][5200/10520] lr: 1.0000e-04 eta: 1 day, 7:34:31 time: 1.3857 data_time: 0.2631 memory: 56769 loss_visual: 0.0616 loss: 0.0616 2022/09/17 10:24:31 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 10:24:59 - mmengine - INFO - Epoch(train) [12][5300/10520] lr: 1.0000e-04 eta: 1 day, 7:32:20 time: 1.1047 data_time: 0.0072 memory: 56769 loss_visual: 0.0672 loss: 0.0672 2022/09/17 10:27:00 - mmengine - INFO - Epoch(train) [12][5400/10520] lr: 1.0000e-04 eta: 1 day, 7:30:08 time: 0.9590 data_time: 0.0070 memory: 56769 loss_visual: 0.0636 loss: 0.0636 2022/09/17 10:29:02 - mmengine - INFO - Epoch(train) [12][5500/10520] lr: 1.0000e-04 eta: 1 day, 7:27:57 time: 0.8963 data_time: 0.0069 memory: 56769 loss_visual: 0.0606 loss: 0.0606 2022/09/17 10:31:03 - mmengine - INFO - Epoch(train) [12][5600/10520] lr: 1.0000e-04 eta: 1 day, 7:25:46 time: 0.9027 data_time: 0.0285 memory: 56769 loss_visual: 0.0666 loss: 0.0666 2022/09/17 10:33:09 - mmengine - INFO - Epoch(train) [12][5700/10520] lr: 1.0000e-04 eta: 1 day, 7:23:39 time: 1.4381 data_time: 0.4721 memory: 56769 loss_visual: 0.0562 loss: 0.0562 2022/09/17 10:35:10 - mmengine - INFO - Epoch(train) [12][5800/10520] lr: 1.0000e-04 eta: 1 day, 7:21:27 time: 1.4514 data_time: 0.4359 memory: 56769 loss_visual: 0.0674 loss: 0.0674 2022/09/17 10:37:15 - mmengine - INFO - Epoch(train) [12][5900/10520] lr: 1.0000e-04 eta: 1 day, 7:19:18 time: 1.4187 data_time: 0.4292 memory: 56769 loss_visual: 0.0610 loss: 0.0610 2022/09/17 10:39:18 - mmengine - INFO - Epoch(train) [12][6000/10520] lr: 1.0000e-04 eta: 1 day, 7:17:08 time: 1.4113 data_time: 0.3231 memory: 56769 loss_visual: 0.0623 loss: 0.0623 2022/09/17 10:41:19 - mmengine - INFO - Epoch(train) [12][6100/10520] lr: 1.0000e-04 eta: 1 day, 7:14:57 time: 1.1211 data_time: 0.0071 memory: 56769 loss_visual: 0.0607 loss: 0.0607 2022/09/17 10:43:20 - mmengine - INFO - Epoch(train) [12][6200/10520] lr: 1.0000e-04 eta: 1 day, 7:12:46 time: 0.9594 data_time: 0.0069 memory: 56769 loss_visual: 0.0641 loss: 0.0641 2022/09/17 10:44:59 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 10:45:22 - mmengine - INFO - Epoch(train) [12][6300/10520] lr: 1.0000e-04 eta: 1 day, 7:10:35 time: 0.9013 data_time: 0.0078 memory: 56769 loss_visual: 0.0630 loss: 0.0630 2022/09/17 10:47:24 - mmengine - INFO - Epoch(train) [12][6400/10520] lr: 1.0000e-04 eta: 1 day, 7:08:24 time: 0.8895 data_time: 0.0237 memory: 56769 loss_visual: 0.0638 loss: 0.0638 2022/09/17 10:49:31 - mmengine - INFO - Epoch(train) [12][6500/10520] lr: 1.0000e-04 eta: 1 day, 7:06:17 time: 1.5048 data_time: 0.4982 memory: 56769 loss_visual: 0.0611 loss: 0.0611 2022/09/17 10:51:32 - mmengine - INFO - Epoch(train) [12][6600/10520] lr: 1.0000e-04 eta: 1 day, 7:04:06 time: 1.4333 data_time: 0.4567 memory: 56769 loss_visual: 0.0630 loss: 0.0630 2022/09/17 10:53:38 - mmengine - INFO - Epoch(train) [12][6700/10520] lr: 1.0000e-04 eta: 1 day, 7:01:58 time: 1.4353 data_time: 0.4310 memory: 56769 loss_visual: 0.0581 loss: 0.0581 2022/09/17 10:55:40 - mmengine - INFO - Epoch(train) [12][6800/10520] lr: 1.0000e-04 eta: 1 day, 6:59:48 time: 1.4037 data_time: 0.3077 memory: 56769 loss_visual: 0.0587 loss: 0.0587 2022/09/17 10:57:41 - mmengine - INFO - Epoch(train) [12][6900/10520] lr: 1.0000e-04 eta: 1 day, 6:57:36 time: 1.0787 data_time: 0.0071 memory: 56769 loss_visual: 0.0603 loss: 0.0603 2022/09/17 10:59:43 - mmengine - INFO - Epoch(train) [12][7000/10520] lr: 1.0000e-04 eta: 1 day, 6:55:26 time: 0.9682 data_time: 0.0072 memory: 56769 loss_visual: 0.0627 loss: 0.0627 2022/09/17 11:01:46 - mmengine - INFO - Epoch(train) [12][7100/10520] lr: 1.0000e-04 eta: 1 day, 6:53:16 time: 0.9024 data_time: 0.0069 memory: 56769 loss_visual: 0.0651 loss: 0.0651 2022/09/17 11:03:49 - mmengine - INFO - Epoch(train) [12][7200/10520] lr: 1.0000e-04 eta: 1 day, 6:51:06 time: 0.8893 data_time: 0.0251 memory: 56769 loss_visual: 0.0611 loss: 0.0611 2022/09/17 11:05:33 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 11:05:57 - mmengine - INFO - Epoch(train) [12][7300/10520] lr: 1.0000e-04 eta: 1 day, 6:49:00 time: 1.4830 data_time: 0.4669 memory: 56769 loss_visual: 0.0604 loss: 0.0604 2022/09/17 11:07:58 - mmengine - INFO - Epoch(train) [12][7400/10520] lr: 1.0000e-04 eta: 1 day, 6:46:48 time: 1.4580 data_time: 0.4558 memory: 56769 loss_visual: 0.0599 loss: 0.0599 2022/09/17 11:10:03 - mmengine - INFO - Epoch(train) [12][7500/10520] lr: 1.0000e-04 eta: 1 day, 6:44:41 time: 1.4538 data_time: 0.4607 memory: 56769 loss_visual: 0.0626 loss: 0.0626 2022/09/17 11:12:05 - mmengine - INFO - Epoch(train) [12][7600/10520] lr: 1.0000e-04 eta: 1 day, 6:42:30 time: 1.3770 data_time: 0.2937 memory: 56769 loss_visual: 0.0638 loss: 0.0638 2022/09/17 11:14:06 - mmengine - INFO - Epoch(train) [12][7700/10520] lr: 1.0000e-04 eta: 1 day, 6:40:19 time: 1.1436 data_time: 0.0069 memory: 56769 loss_visual: 0.0609 loss: 0.0609 2022/09/17 11:16:07 - mmengine - INFO - Epoch(train) [12][7800/10520] lr: 1.0000e-04 eta: 1 day, 6:38:07 time: 0.9593 data_time: 0.0071 memory: 56769 loss_visual: 0.0612 loss: 0.0612 2022/09/17 11:18:07 - mmengine - INFO - Epoch(train) [12][7900/10520] lr: 1.0000e-04 eta: 1 day, 6:35:56 time: 0.9081 data_time: 0.0077 memory: 56769 loss_visual: 0.0629 loss: 0.0629 2022/09/17 11:20:09 - mmengine - INFO - Epoch(train) [12][8000/10520] lr: 1.0000e-04 eta: 1 day, 6:33:45 time: 0.8876 data_time: 0.0278 memory: 56769 loss_visual: 0.0598 loss: 0.0598 2022/09/17 11:22:17 - mmengine - INFO - Epoch(train) [12][8100/10520] lr: 1.0000e-04 eta: 1 day, 6:31:39 time: 1.4522 data_time: 0.4632 memory: 56769 loss_visual: 0.0622 loss: 0.0622 2022/09/17 11:24:18 - mmengine - INFO - Epoch(train) [12][8200/10520] lr: 1.0000e-04 eta: 1 day, 6:29:28 time: 1.4188 data_time: 0.4401 memory: 56769 loss_visual: 0.0582 loss: 0.0582 2022/09/17 11:25:56 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 11:26:24 - mmengine - INFO - Epoch(train) [12][8300/10520] lr: 1.0000e-04 eta: 1 day, 6:27:20 time: 1.4389 data_time: 0.4152 memory: 56769 loss_visual: 0.0640 loss: 0.0640 2022/09/17 11:28:27 - mmengine - INFO - Epoch(train) [12][8400/10520] lr: 1.0000e-04 eta: 1 day, 6:25:10 time: 1.4232 data_time: 0.3027 memory: 56769 loss_visual: 0.0632 loss: 0.0632 2022/09/17 11:30:29 - mmengine - INFO - Epoch(train) [12][8500/10520] lr: 1.0000e-04 eta: 1 day, 6:23:01 time: 1.0774 data_time: 0.0069 memory: 56769 loss_visual: 0.0637 loss: 0.0637 2022/09/17 11:32:30 - mmengine - INFO - Epoch(train) [12][8600/10520] lr: 1.0000e-04 eta: 1 day, 6:20:49 time: 0.9562 data_time: 0.0072 memory: 56769 loss_visual: 0.0576 loss: 0.0576 2022/09/17 11:34:32 - mmengine - INFO - Epoch(train) [12][8700/10520] lr: 1.0000e-04 eta: 1 day, 6:18:39 time: 0.9013 data_time: 0.0072 memory: 56769 loss_visual: 0.0623 loss: 0.0623 2022/09/17 11:36:33 - mmengine - INFO - Epoch(train) [12][8800/10520] lr: 1.0000e-04 eta: 1 day, 6:16:28 time: 0.8845 data_time: 0.0248 memory: 56769 loss_visual: 0.0620 loss: 0.0620 2022/09/17 11:38:41 - mmengine - INFO - Epoch(train) [12][8900/10520] lr: 1.0000e-04 eta: 1 day, 6:14:22 time: 1.4275 data_time: 0.4757 memory: 56769 loss_visual: 0.0617 loss: 0.0617 2022/09/17 11:40:43 - mmengine - INFO - Epoch(train) [12][9000/10520] lr: 1.0000e-04 eta: 1 day, 6:12:11 time: 1.4596 data_time: 0.4775 memory: 56769 loss_visual: 0.0618 loss: 0.0618 2022/09/17 11:42:50 - mmengine - INFO - Epoch(train) [12][9100/10520] lr: 1.0000e-04 eta: 1 day, 6:10:04 time: 1.4414 data_time: 0.4204 memory: 56769 loss_visual: 0.0618 loss: 0.0618 2022/09/17 11:44:52 - mmengine - INFO - Epoch(train) [12][9200/10520] lr: 1.0000e-04 eta: 1 day, 6:07:54 time: 1.4032 data_time: 0.3022 memory: 56769 loss_visual: 0.0640 loss: 0.0640 2022/09/17 11:46:24 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 11:46:53 - mmengine - INFO - Epoch(train) [12][9300/10520] lr: 1.0000e-04 eta: 1 day, 6:05:43 time: 1.1534 data_time: 0.0067 memory: 56769 loss_visual: 0.0661 loss: 0.0661 2022/09/17 11:48:54 - mmengine - INFO - Epoch(train) [12][9400/10520] lr: 1.0000e-04 eta: 1 day, 6:03:32 time: 0.9925 data_time: 0.0073 memory: 56769 loss_visual: 0.0605 loss: 0.0605 2022/09/17 11:50:54 - mmengine - INFO - Epoch(train) [12][9500/10520] lr: 1.0000e-04 eta: 1 day, 6:01:21 time: 0.9110 data_time: 0.0074 memory: 56769 loss_visual: 0.0620 loss: 0.0620 2022/09/17 11:52:55 - mmengine - INFO - Epoch(train) [12][9600/10520] lr: 1.0000e-04 eta: 1 day, 5:59:10 time: 0.8841 data_time: 0.0277 memory: 56769 loss_visual: 0.0571 loss: 0.0571 2022/09/17 11:55:01 - mmengine - INFO - Epoch(train) [12][9700/10520] lr: 1.0000e-04 eta: 1 day, 5:57:02 time: 1.4426 data_time: 0.4586 memory: 56769 loss_visual: 0.0652 loss: 0.0652 2022/09/17 11:57:02 - mmengine - INFO - Epoch(train) [12][9800/10520] lr: 1.0000e-04 eta: 1 day, 5:54:51 time: 1.4080 data_time: 0.4447 memory: 56769 loss_visual: 0.0575 loss: 0.0575 2022/09/17 11:59:09 - mmengine - INFO - Epoch(train) [12][9900/10520] lr: 1.0000e-04 eta: 1 day, 5:52:44 time: 1.5455 data_time: 0.5150 memory: 56769 loss_visual: 0.0625 loss: 0.0625 2022/09/17 12:01:15 - mmengine - INFO - Epoch(train) [12][10000/10520] lr: 1.0000e-04 eta: 1 day, 5:50:37 time: 1.4058 data_time: 0.3233 memory: 56769 loss_visual: 0.0632 loss: 0.0632 2022/09/17 12:03:16 - mmengine - INFO - Epoch(train) [12][10100/10520] lr: 1.0000e-04 eta: 1 day, 5:48:26 time: 1.0843 data_time: 0.0076 memory: 56769 loss_visual: 0.0611 loss: 0.0611 2022/09/17 12:05:20 - mmengine - INFO - Epoch(train) [12][10200/10520] lr: 1.0000e-04 eta: 1 day, 5:46:18 time: 0.9618 data_time: 0.0072 memory: 56769 loss_visual: 0.0634 loss: 0.0634 2022/09/17 12:07:01 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 12:07:24 - mmengine - INFO - Epoch(train) [12][10300/10520] lr: 1.0000e-04 eta: 1 day, 5:44:09 time: 0.9171 data_time: 0.0077 memory: 56769 loss_visual: 0.0619 loss: 0.0619 2022/09/17 12:09:26 - mmengine - INFO - Epoch(train) [12][10400/10520] lr: 1.0000e-04 eta: 1 day, 5:41:58 time: 0.8840 data_time: 0.0261 memory: 56769 loss_visual: 0.0617 loss: 0.0617 2022/09/17 12:11:28 - mmengine - INFO - Epoch(train) [12][10500/10520] lr: 1.0000e-04 eta: 1 day, 5:39:48 time: 1.1843 data_time: 0.2918 memory: 56769 loss_visual: 0.0638 loss: 0.0638 2022/09/17 12:11:47 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 12:11:47 - mmengine - INFO - Saving checkpoint at 12 epochs 2022/09/17 12:12:07 - mmengine - INFO - Epoch(val) [12][100/3836] eta: 0:06:28 time: 0.1041 data_time: 0.0006 memory: 56769 2022/09/17 12:12:11 - mmengine - INFO - Epoch(val) [12][200/3836] eta: 0:00:42 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 12:12:13 - mmengine - INFO - Epoch(val) [12][300/3836] eta: 0:00:41 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 12:12:14 - mmengine - INFO - Epoch(val) [12][400/3836] eta: 0:00:41 time: 0.0121 data_time: 0.0013 memory: 480 2022/09/17 12:12:15 - mmengine - INFO - Epoch(val) [12][500/3836] eta: 0:00:38 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 12:12:16 - mmengine - INFO - Epoch(val) [12][600/3836] eta: 0:00:42 time: 0.0131 data_time: 0.0006 memory: 480 2022/09/17 12:12:17 - mmengine - INFO - Epoch(val) [12][700/3836] eta: 0:00:35 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 12:12:19 - mmengine - INFO - Epoch(val) [12][800/3836] eta: 0:00:36 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/17 12:12:20 - mmengine - INFO - Epoch(val) [12][900/3836] eta: 0:00:34 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/17 12:12:21 - mmengine - INFO - Epoch(val) [12][1000/3836] eta: 0:00:38 time: 0.0135 data_time: 0.0006 memory: 480 2022/09/17 12:12:22 - mmengine - INFO - Epoch(val) [12][1100/3836] eta: 0:00:32 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/17 12:12:24 - mmengine - INFO - Epoch(val) [12][1200/3836] eta: 0:00:30 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 12:12:25 - mmengine - INFO - Epoch(val) [12][1300/3836] eta: 0:00:27 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/17 12:12:26 - mmengine - INFO - Epoch(val) [12][1400/3836] eta: 0:00:28 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 12:12:27 - mmengine - INFO - Epoch(val) [12][1500/3836] eta: 0:00:26 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 12:12:28 - mmengine - INFO - Epoch(val) [12][1600/3836] eta: 0:00:25 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 12:12:30 - mmengine - INFO - Epoch(val) [12][1700/3836] eta: 0:00:23 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/17 12:12:31 - mmengine - INFO - Epoch(val) [12][1800/3836] eta: 0:00:24 time: 0.0122 data_time: 0.0006 memory: 480 2022/09/17 12:12:32 - mmengine - INFO - Epoch(val) [12][1900/3836] eta: 0:00:22 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/17 12:12:33 - mmengine - INFO - Epoch(val) [12][2000/3836] eta: 0:00:20 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 12:12:34 - mmengine - INFO - Epoch(val) [12][2100/3836] eta: 0:00:20 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 12:12:36 - mmengine - INFO - Epoch(val) [12][2200/3836] eta: 0:00:19 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 12:12:37 - mmengine - INFO - Epoch(val) [12][2300/3836] eta: 0:00:17 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 12:12:38 - mmengine - INFO - Epoch(val) [12][2400/3836] eta: 0:00:16 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 12:12:39 - mmengine - INFO - Epoch(val) [12][2500/3836] eta: 0:00:16 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/17 12:12:40 - mmengine - INFO - Epoch(val) [12][2600/3836] eta: 0:00:14 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 12:12:42 - mmengine - INFO - Epoch(val) [12][2700/3836] eta: 0:00:13 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 12:12:43 - mmengine - INFO - Epoch(val) [12][2800/3836] eta: 0:00:11 time: 0.0115 data_time: 0.0004 memory: 480 2022/09/17 12:12:44 - mmengine - INFO - Epoch(val) [12][2900/3836] eta: 0:00:10 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 12:12:46 - mmengine - INFO - Epoch(val) [12][3000/3836] eta: 0:00:09 time: 0.0120 data_time: 0.0006 memory: 480 2022/09/17 12:12:47 - mmengine - INFO - Epoch(val) [12][3100/3836] eta: 0:00:09 time: 0.0126 data_time: 0.0014 memory: 480 2022/09/17 12:12:48 - mmengine - INFO - Epoch(val) [12][3200/3836] eta: 0:00:06 time: 0.0106 data_time: 0.0005 memory: 480 2022/09/17 12:12:49 - mmengine - INFO - Epoch(val) [12][3300/3836] eta: 0:00:05 time: 0.0105 data_time: 0.0005 memory: 480 2022/09/17 12:12:50 - mmengine - INFO - Epoch(val) [12][3400/3836] eta: 0:00:04 time: 0.0106 data_time: 0.0005 memory: 480 2022/09/17 12:12:51 - mmengine - INFO - Epoch(val) [12][3500/3836] eta: 0:00:03 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/17 12:12:52 - mmengine - INFO - Epoch(val) [12][3600/3836] eta: 0:00:02 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/17 12:12:53 - mmengine - INFO - Epoch(val) [12][3700/3836] eta: 0:00:01 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/17 12:12:55 - mmengine - INFO - Epoch(val) [12][3800/3836] eta: 0:00:00 time: 0.0105 data_time: 0.0005 memory: 480 2022/09/17 12:12:55 - mmengine - INFO - Epoch(val) [12][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.8229 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9440 SVT/recog/word_acc_ignore_case_symbol: 0.8918 SVTP/recog/word_acc_ignore_case_symbol: 0.8062 IC13/recog/word_acc_ignore_case_symbol: 0.9143 IC15/recog/word_acc_ignore_case_symbol: 0.7718 2022/09/17 12:15:09 - mmengine - INFO - Epoch(train) [13][100/10520] lr: 1.0000e-04 eta: 1 day, 5:37:16 time: 1.4074 data_time: 0.5543 memory: 56769 loss_visual: 0.0601 loss: 0.0601 2022/09/17 12:17:10 - mmengine - INFO - Epoch(train) [13][200/10520] lr: 1.0000e-04 eta: 1 day, 5:35:05 time: 1.5770 data_time: 0.4528 memory: 56769 loss_visual: 0.0615 loss: 0.0615 2022/09/17 12:19:10 - mmengine - INFO - Epoch(train) [13][300/10520] lr: 1.0000e-04 eta: 1 day, 5:32:54 time: 1.3930 data_time: 0.2709 memory: 56769 loss_visual: 0.0613 loss: 0.0613 2022/09/17 12:21:08 - mmengine - INFO - Epoch(train) [13][400/10520] lr: 1.0000e-04 eta: 1 day, 5:30:41 time: 1.4301 data_time: 0.2893 memory: 56769 loss_visual: 0.0610 loss: 0.0610 2022/09/17 12:23:06 - mmengine - INFO - Epoch(train) [13][500/10520] lr: 1.0000e-04 eta: 1 day, 5:28:28 time: 0.8706 data_time: 0.0075 memory: 56769 loss_visual: 0.0609 loss: 0.0609 2022/09/17 12:25:04 - mmengine - INFO - Epoch(train) [13][600/10520] lr: 1.0000e-04 eta: 1 day, 5:26:16 time: 0.8856 data_time: 0.0071 memory: 56769 loss_visual: 0.0649 loss: 0.0649 2022/09/17 12:27:03 - mmengine - INFO - Epoch(train) [13][700/10520] lr: 1.0000e-04 eta: 1 day, 5:24:04 time: 0.8629 data_time: 0.0073 memory: 56769 loss_visual: 0.0627 loss: 0.0627 2022/09/17 12:28:15 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 12:29:01 - mmengine - INFO - Epoch(train) [13][800/10520] lr: 1.0000e-04 eta: 1 day, 5:21:51 time: 0.8594 data_time: 0.0264 memory: 56769 loss_visual: 0.0606 loss: 0.0606 2022/09/17 12:31:02 - mmengine - INFO - Epoch(train) [13][900/10520] lr: 1.0000e-04 eta: 1 day, 5:19:40 time: 1.3196 data_time: 0.4248 memory: 56769 loss_visual: 0.0611 loss: 0.0611 2022/09/17 12:33:03 - mmengine - INFO - Epoch(train) [13][1000/10520] lr: 1.0000e-04 eta: 1 day, 5:17:30 time: 1.5630 data_time: 0.4463 memory: 56769 loss_visual: 0.0638 loss: 0.0638 2022/09/17 12:35:03 - mmengine - INFO - Epoch(train) [13][1100/10520] lr: 1.0000e-04 eta: 1 day, 5:15:19 time: 1.4288 data_time: 0.2722 memory: 56769 loss_visual: 0.0637 loss: 0.0637 2022/09/17 12:37:02 - mmengine - INFO - Epoch(train) [13][1200/10520] lr: 1.0000e-04 eta: 1 day, 5:13:06 time: 1.4437 data_time: 0.2804 memory: 56769 loss_visual: 0.0590 loss: 0.0590 2022/09/17 12:39:00 - mmengine - INFO - Epoch(train) [13][1300/10520] lr: 1.0000e-04 eta: 1 day, 5:10:54 time: 0.8860 data_time: 0.0072 memory: 56769 loss_visual: 0.0606 loss: 0.0606 2022/09/17 12:40:58 - mmengine - INFO - Epoch(train) [13][1400/10520] lr: 1.0000e-04 eta: 1 day, 5:08:42 time: 0.8658 data_time: 0.0090 memory: 56769 loss_visual: 0.0650 loss: 0.0650 2022/09/17 12:42:56 - mmengine - INFO - Epoch(train) [13][1500/10520] lr: 1.0000e-04 eta: 1 day, 5:06:29 time: 0.8650 data_time: 0.0068 memory: 56769 loss_visual: 0.0590 loss: 0.0590 2022/09/17 12:44:53 - mmengine - INFO - Epoch(train) [13][1600/10520] lr: 1.0000e-04 eta: 1 day, 5:04:16 time: 0.8856 data_time: 0.0273 memory: 56769 loss_visual: 0.0603 loss: 0.0603 2022/09/17 12:46:55 - mmengine - INFO - Epoch(train) [13][1700/10520] lr: 1.0000e-04 eta: 1 day, 5:02:06 time: 1.2881 data_time: 0.4550 memory: 56769 loss_visual: 0.0612 loss: 0.0612 2022/09/17 12:48:04 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 12:48:56 - mmengine - INFO - Epoch(train) [13][1800/10520] lr: 1.0000e-04 eta: 1 day, 4:59:56 time: 1.5859 data_time: 0.4479 memory: 56769 loss_visual: 0.0596 loss: 0.0596 2022/09/17 12:50:56 - mmengine - INFO - Epoch(train) [13][1900/10520] lr: 1.0000e-04 eta: 1 day, 4:57:45 time: 1.4425 data_time: 0.2958 memory: 56769 loss_visual: 0.0649 loss: 0.0649 2022/09/17 12:52:54 - mmengine - INFO - Epoch(train) [13][2000/10520] lr: 1.0000e-04 eta: 1 day, 4:55:32 time: 1.4756 data_time: 0.3105 memory: 56769 loss_visual: 0.0612 loss: 0.0612 2022/09/17 12:54:52 - mmengine - INFO - Epoch(train) [13][2100/10520] lr: 1.0000e-04 eta: 1 day, 4:53:20 time: 0.9174 data_time: 0.0067 memory: 56769 loss_visual: 0.0576 loss: 0.0576 2022/09/17 12:56:51 - mmengine - INFO - Epoch(train) [13][2200/10520] lr: 1.0000e-04 eta: 1 day, 4:51:08 time: 0.9004 data_time: 0.0067 memory: 56769 loss_visual: 0.0614 loss: 0.0614 2022/09/17 12:58:48 - mmengine - INFO - Epoch(train) [13][2300/10520] lr: 1.0000e-04 eta: 1 day, 4:48:55 time: 0.8954 data_time: 0.0073 memory: 56769 loss_visual: 0.0639 loss: 0.0639 2022/09/17 13:00:46 - mmengine - INFO - Epoch(train) [13][2400/10520] lr: 1.0000e-04 eta: 1 day, 4:46:43 time: 0.8572 data_time: 0.0238 memory: 56769 loss_visual: 0.0580 loss: 0.0580 2022/09/17 13:02:47 - mmengine - INFO - Epoch(train) [13][2500/10520] lr: 1.0000e-04 eta: 1 day, 4:44:32 time: 1.2949 data_time: 0.4474 memory: 56769 loss_visual: 0.0616 loss: 0.0616 2022/09/17 13:04:49 - mmengine - INFO - Epoch(train) [13][2600/10520] lr: 1.0000e-04 eta: 1 day, 4:42:23 time: 1.6166 data_time: 0.4510 memory: 56769 loss_visual: 0.0589 loss: 0.0589 2022/09/17 13:06:50 - mmengine - INFO - Epoch(train) [13][2700/10520] lr: 1.0000e-04 eta: 1 day, 4:40:12 time: 1.4607 data_time: 0.2699 memory: 56769 loss_visual: 0.0595 loss: 0.0595 2022/09/17 13:08:00 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 13:08:48 - mmengine - INFO - Epoch(train) [13][2800/10520] lr: 1.0000e-04 eta: 1 day, 4:38:00 time: 1.4476 data_time: 0.3040 memory: 56769 loss_visual: 0.0590 loss: 0.0590 2022/09/17 13:10:44 - mmengine - INFO - Epoch(train) [13][2900/10520] lr: 1.0000e-04 eta: 1 day, 4:35:47 time: 0.8858 data_time: 0.0066 memory: 56769 loss_visual: 0.0614 loss: 0.0614 2022/09/17 13:12:43 - mmengine - INFO - Epoch(train) [13][3000/10520] lr: 1.0000e-04 eta: 1 day, 4:33:35 time: 0.8815 data_time: 0.0071 memory: 56769 loss_visual: 0.0638 loss: 0.0638 2022/09/17 13:14:40 - mmengine - INFO - Epoch(train) [13][3100/10520] lr: 1.0000e-04 eta: 1 day, 4:31:22 time: 0.8787 data_time: 0.0066 memory: 56769 loss_visual: 0.0617 loss: 0.0617 2022/09/17 13:16:38 - mmengine - INFO - Epoch(train) [13][3200/10520] lr: 1.0000e-04 eta: 1 day, 4:29:10 time: 0.8552 data_time: 0.0330 memory: 56769 loss_visual: 0.0599 loss: 0.0599 2022/09/17 13:18:40 - mmengine - INFO - Epoch(train) [13][3300/10520] lr: 1.0000e-04 eta: 1 day, 4:27:01 time: 1.3185 data_time: 0.4585 memory: 56769 loss_visual: 0.0642 loss: 0.0642 2022/09/17 13:20:40 - mmengine - INFO - Epoch(train) [13][3400/10520] lr: 1.0000e-04 eta: 1 day, 4:24:50 time: 1.5943 data_time: 0.4497 memory: 56769 loss_visual: 0.0589 loss: 0.0589 2022/09/17 13:22:43 - mmengine - INFO - Epoch(train) [13][3500/10520] lr: 1.0000e-04 eta: 1 day, 4:22:41 time: 1.4671 data_time: 0.2714 memory: 56769 loss_visual: 0.0613 loss: 0.0613 2022/09/17 13:24:41 - mmengine - INFO - Epoch(train) [13][3600/10520] lr: 1.0000e-04 eta: 1 day, 4:20:29 time: 1.4558 data_time: 0.2898 memory: 56769 loss_visual: 0.0631 loss: 0.0631 2022/09/17 13:26:40 - mmengine - INFO - Epoch(train) [13][3700/10520] lr: 1.0000e-04 eta: 1 day, 4:18:17 time: 0.9270 data_time: 0.0072 memory: 56769 loss_visual: 0.0613 loss: 0.0613 2022/09/17 13:27:52 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 13:28:37 - mmengine - INFO - Epoch(train) [13][3800/10520] lr: 1.0000e-04 eta: 1 day, 4:16:05 time: 0.9182 data_time: 0.0089 memory: 56769 loss_visual: 0.0624 loss: 0.0624 2022/09/17 13:30:35 - mmengine - INFO - Epoch(train) [13][3900/10520] lr: 1.0000e-04 eta: 1 day, 4:13:53 time: 0.8989 data_time: 0.0071 memory: 56769 loss_visual: 0.0617 loss: 0.0617 2022/09/17 13:32:33 - mmengine - INFO - Epoch(train) [13][4000/10520] lr: 1.0000e-04 eta: 1 day, 4:11:41 time: 0.8964 data_time: 0.0383 memory: 56769 loss_visual: 0.0609 loss: 0.0609 2022/09/17 13:34:36 - mmengine - INFO - Epoch(train) [13][4100/10520] lr: 1.0000e-04 eta: 1 day, 4:09:32 time: 1.3013 data_time: 0.4539 memory: 56769 loss_visual: 0.0596 loss: 0.0596 2022/09/17 13:36:38 - mmengine - INFO - Epoch(train) [13][4200/10520] lr: 1.0000e-04 eta: 1 day, 4:07:22 time: 1.6444 data_time: 0.4713 memory: 56769 loss_visual: 0.0678 loss: 0.0678 2022/09/17 13:38:39 - mmengine - INFO - Epoch(train) [13][4300/10520] lr: 1.0000e-04 eta: 1 day, 4:05:12 time: 1.4750 data_time: 0.3168 memory: 56769 loss_visual: 0.0650 loss: 0.0650 2022/09/17 13:40:38 - mmengine - INFO - Epoch(train) [13][4400/10520] lr: 1.0000e-04 eta: 1 day, 4:03:01 time: 1.4246 data_time: 0.2814 memory: 56769 loss_visual: 0.0575 loss: 0.0575 2022/09/17 13:42:36 - mmengine - INFO - Epoch(train) [13][4500/10520] lr: 1.0000e-04 eta: 1 day, 4:00:49 time: 0.8839 data_time: 0.0073 memory: 56769 loss_visual: 0.0568 loss: 0.0568 2022/09/17 13:44:34 - mmengine - INFO - Epoch(train) [13][4600/10520] lr: 1.0000e-04 eta: 1 day, 3:58:37 time: 0.9106 data_time: 0.0071 memory: 56769 loss_visual: 0.0621 loss: 0.0621 2022/09/17 13:46:33 - mmengine - INFO - Epoch(train) [13][4700/10520] lr: 1.0000e-04 eta: 1 day, 3:56:26 time: 0.8844 data_time: 0.0074 memory: 56769 loss_visual: 0.0623 loss: 0.0623 2022/09/17 13:47:47 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 13:48:32 - mmengine - INFO - Epoch(train) [13][4800/10520] lr: 1.0000e-04 eta: 1 day, 3:54:15 time: 0.8821 data_time: 0.0287 memory: 56769 loss_visual: 0.0639 loss: 0.0639 2022/09/17 13:50:35 - mmengine - INFO - Epoch(train) [13][4900/10520] lr: 1.0000e-04 eta: 1 day, 3:52:06 time: 1.3071 data_time: 0.4608 memory: 56769 loss_visual: 0.0600 loss: 0.0600 2022/09/17 13:52:37 - mmengine - INFO - Epoch(train) [13][5000/10520] lr: 1.0000e-04 eta: 1 day, 3:49:57 time: 1.6284 data_time: 0.4210 memory: 56769 loss_visual: 0.0603 loss: 0.0603 2022/09/17 13:54:38 - mmengine - INFO - Epoch(train) [13][5100/10520] lr: 1.0000e-04 eta: 1 day, 3:47:47 time: 1.4597 data_time: 0.2668 memory: 56769 loss_visual: 0.0646 loss: 0.0646 2022/09/17 13:56:36 - mmengine - INFO - Epoch(train) [13][5200/10520] lr: 1.0000e-04 eta: 1 day, 3:45:35 time: 1.4916 data_time: 0.2761 memory: 56769 loss_visual: 0.0628 loss: 0.0628 2022/09/17 13:58:34 - mmengine - INFO - Epoch(train) [13][5300/10520] lr: 1.0000e-04 eta: 1 day, 3:43:24 time: 0.9242 data_time: 0.0072 memory: 56769 loss_visual: 0.0595 loss: 0.0595 2022/09/17 14:00:34 - mmengine - INFO - Epoch(train) [13][5400/10520] lr: 1.0000e-04 eta: 1 day, 3:41:13 time: 0.8958 data_time: 0.0070 memory: 56769 loss_visual: 0.0612 loss: 0.0612 2022/09/17 14:02:33 - mmengine - INFO - Epoch(train) [13][5500/10520] lr: 1.0000e-04 eta: 1 day, 3:39:02 time: 0.8862 data_time: 0.0067 memory: 56769 loss_visual: 0.0602 loss: 0.0602 2022/09/17 14:04:32 - mmengine - INFO - Epoch(train) [13][5600/10520] lr: 1.0000e-04 eta: 1 day, 3:36:51 time: 0.8502 data_time: 0.0252 memory: 56769 loss_visual: 0.0554 loss: 0.0554 2022/09/17 14:06:35 - mmengine - INFO - Epoch(train) [13][5700/10520] lr: 1.0000e-04 eta: 1 day, 3:34:42 time: 1.3724 data_time: 0.4929 memory: 56769 loss_visual: 0.0567 loss: 0.0567 2022/09/17 14:07:43 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 14:08:35 - mmengine - INFO - Epoch(train) [13][5800/10520] lr: 1.0000e-04 eta: 1 day, 3:32:32 time: 1.5886 data_time: 0.4479 memory: 56769 loss_visual: 0.0582 loss: 0.0582 2022/09/17 14:10:38 - mmengine - INFO - Epoch(train) [13][5900/10520] lr: 1.0000e-04 eta: 1 day, 3:30:23 time: 1.4130 data_time: 0.2763 memory: 56769 loss_visual: 0.0641 loss: 0.0641 2022/09/17 14:12:35 - mmengine - INFO - Epoch(train) [13][6000/10520] lr: 1.0000e-04 eta: 1 day, 3:28:11 time: 1.4385 data_time: 0.2728 memory: 56769 loss_visual: 0.0611 loss: 0.0611 2022/09/17 14:14:34 - mmengine - INFO - Epoch(train) [13][6100/10520] lr: 1.0000e-04 eta: 1 day, 3:26:00 time: 0.9395 data_time: 0.0069 memory: 56769 loss_visual: 0.0618 loss: 0.0618 2022/09/17 14:16:32 - mmengine - INFO - Epoch(train) [13][6200/10520] lr: 1.0000e-04 eta: 1 day, 3:23:48 time: 0.8791 data_time: 0.0069 memory: 56769 loss_visual: 0.0576 loss: 0.0576 2022/09/17 14:18:29 - mmengine - INFO - Epoch(train) [13][6300/10520] lr: 1.0000e-04 eta: 1 day, 3:21:36 time: 0.8939 data_time: 0.0068 memory: 56769 loss_visual: 0.0576 loss: 0.0576 2022/09/17 14:20:28 - mmengine - INFO - Epoch(train) [13][6400/10520] lr: 1.0000e-04 eta: 1 day, 3:19:25 time: 0.8480 data_time: 0.0272 memory: 56769 loss_visual: 0.0623 loss: 0.0623 2022/09/17 14:22:31 - mmengine - INFO - Epoch(train) [13][6500/10520] lr: 1.0000e-04 eta: 1 day, 3:17:16 time: 1.3077 data_time: 0.4525 memory: 56769 loss_visual: 0.0629 loss: 0.0629 2022/09/17 14:24:32 - mmengine - INFO - Epoch(train) [13][6600/10520] lr: 1.0000e-04 eta: 1 day, 3:15:07 time: 1.6362 data_time: 0.4349 memory: 56769 loss_visual: 0.0586 loss: 0.0586 2022/09/17 14:26:33 - mmengine - INFO - Epoch(train) [13][6700/10520] lr: 1.0000e-04 eta: 1 day, 3:12:57 time: 1.4373 data_time: 0.2667 memory: 56769 loss_visual: 0.0628 loss: 0.0628 2022/09/17 14:27:45 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 14:28:33 - mmengine - INFO - Epoch(train) [13][6800/10520] lr: 1.0000e-04 eta: 1 day, 3:10:47 time: 1.4569 data_time: 0.2919 memory: 56769 loss_visual: 0.0614 loss: 0.0614 2022/09/17 14:30:32 - mmengine - INFO - Epoch(train) [13][6900/10520] lr: 1.0000e-04 eta: 1 day, 3:08:36 time: 0.9050 data_time: 0.0076 memory: 56769 loss_visual: 0.0574 loss: 0.0574 2022/09/17 14:32:32 - mmengine - INFO - Epoch(train) [13][7000/10520] lr: 1.0000e-04 eta: 1 day, 3:06:26 time: 0.9308 data_time: 0.0067 memory: 56769 loss_visual: 0.0577 loss: 0.0577 2022/09/17 14:34:31 - mmengine - INFO - Epoch(train) [13][7100/10520] lr: 1.0000e-04 eta: 1 day, 3:04:15 time: 0.8890 data_time: 0.0069 memory: 56769 loss_visual: 0.0607 loss: 0.0607 2022/09/17 14:36:30 - mmengine - INFO - Epoch(train) [13][7200/10520] lr: 1.0000e-04 eta: 1 day, 3:02:04 time: 0.9109 data_time: 0.0262 memory: 56769 loss_visual: 0.0610 loss: 0.0610 2022/09/17 14:38:35 - mmengine - INFO - Epoch(train) [13][7300/10520] lr: 1.0000e-04 eta: 1 day, 2:59:57 time: 1.3185 data_time: 0.4647 memory: 56769 loss_visual: 0.0640 loss: 0.0640 2022/09/17 14:40:37 - mmengine - INFO - Epoch(train) [13][7400/10520] lr: 1.0000e-04 eta: 1 day, 2:57:48 time: 1.6005 data_time: 0.4609 memory: 56769 loss_visual: 0.0632 loss: 0.0632 2022/09/17 14:42:40 - mmengine - INFO - Epoch(train) [13][7500/10520] lr: 1.0000e-04 eta: 1 day, 2:55:39 time: 1.4675 data_time: 0.2946 memory: 56769 loss_visual: 0.0600 loss: 0.0600 2022/09/17 14:44:39 - mmengine - INFO - Epoch(train) [13][7600/10520] lr: 1.0000e-04 eta: 1 day, 2:53:28 time: 1.4241 data_time: 0.2855 memory: 56769 loss_visual: 0.0599 loss: 0.0599 2022/09/17 14:46:39 - mmengine - INFO - Epoch(train) [13][7700/10520] lr: 1.0000e-04 eta: 1 day, 2:51:18 time: 0.9079 data_time: 0.0070 memory: 56769 loss_visual: 0.0615 loss: 0.0615 2022/09/17 14:47:53 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 14:48:38 - mmengine - INFO - Epoch(train) [13][7800/10520] lr: 1.0000e-04 eta: 1 day, 2:49:07 time: 0.8796 data_time: 0.0064 memory: 56769 loss_visual: 0.0600 loss: 0.0600 2022/09/17 14:50:36 - mmengine - INFO - Epoch(train) [13][7900/10520] lr: 1.0000e-04 eta: 1 day, 2:46:56 time: 0.8627 data_time: 0.0064 memory: 56769 loss_visual: 0.0604 loss: 0.0604 2022/09/17 14:52:34 - mmengine - INFO - Epoch(train) [13][8000/10520] lr: 1.0000e-04 eta: 1 day, 2:44:45 time: 0.8372 data_time: 0.0228 memory: 56769 loss_visual: 0.0542 loss: 0.0542 2022/09/17 14:54:37 - mmengine - INFO - Epoch(train) [13][8100/10520] lr: 1.0000e-04 eta: 1 day, 2:42:37 time: 1.3322 data_time: 0.4814 memory: 56769 loss_visual: 0.0608 loss: 0.0608 2022/09/17 14:56:39 - mmengine - INFO - Epoch(train) [13][8200/10520] lr: 1.0000e-04 eta: 1 day, 2:40:28 time: 1.7041 data_time: 0.5297 memory: 56769 loss_visual: 0.0613 loss: 0.0613 2022/09/17 14:58:42 - mmengine - INFO - Epoch(train) [13][8300/10520] lr: 1.0000e-04 eta: 1 day, 2:38:19 time: 1.4266 data_time: 0.2699 memory: 56769 loss_visual: 0.0628 loss: 0.0628 2022/09/17 15:00:41 - mmengine - INFO - Epoch(train) [13][8400/10520] lr: 1.0000e-04 eta: 1 day, 2:36:09 time: 1.4410 data_time: 0.2625 memory: 56769 loss_visual: 0.0626 loss: 0.0626 2022/09/17 15:02:39 - mmengine - INFO - Epoch(train) [13][8500/10520] lr: 1.0000e-04 eta: 1 day, 2:33:58 time: 0.8736 data_time: 0.0069 memory: 56769 loss_visual: 0.0591 loss: 0.0591 2022/09/17 15:04:37 - mmengine - INFO - Epoch(train) [13][8600/10520] lr: 1.0000e-04 eta: 1 day, 2:31:46 time: 0.9134 data_time: 0.0068 memory: 56769 loss_visual: 0.0583 loss: 0.0583 2022/09/17 15:06:35 - mmengine - INFO - Epoch(train) [13][8700/10520] lr: 1.0000e-04 eta: 1 day, 2:29:35 time: 0.8739 data_time: 0.0079 memory: 56769 loss_visual: 0.0621 loss: 0.0621 2022/09/17 15:07:48 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 15:08:33 - mmengine - INFO - Epoch(train) [13][8800/10520] lr: 1.0000e-04 eta: 1 day, 2:27:24 time: 0.8573 data_time: 0.0367 memory: 56769 loss_visual: 0.0619 loss: 0.0619 2022/09/17 15:10:36 - mmengine - INFO - Epoch(train) [13][8900/10520] lr: 1.0000e-04 eta: 1 day, 2:25:16 time: 1.3717 data_time: 0.4861 memory: 56769 loss_visual: 0.0602 loss: 0.0602 2022/09/17 15:12:38 - mmengine - INFO - Epoch(train) [13][9000/10520] lr: 1.0000e-04 eta: 1 day, 2:23:07 time: 1.5745 data_time: 0.4566 memory: 56769 loss_visual: 0.0597 loss: 0.0597 2022/09/17 15:14:39 - mmengine - INFO - Epoch(train) [13][9100/10520] lr: 1.0000e-04 eta: 1 day, 2:20:58 time: 1.4445 data_time: 0.2718 memory: 56769 loss_visual: 0.0603 loss: 0.0603 2022/09/17 15:16:37 - mmengine - INFO - Epoch(train) [13][9200/10520] lr: 1.0000e-04 eta: 1 day, 2:18:46 time: 1.4371 data_time: 0.2704 memory: 56769 loss_visual: 0.0581 loss: 0.0581 2022/09/17 15:18:35 - mmengine - INFO - Epoch(train) [13][9300/10520] lr: 1.0000e-04 eta: 1 day, 2:16:36 time: 0.8876 data_time: 0.0071 memory: 56769 loss_visual: 0.0630 loss: 0.0630 2022/09/17 15:20:32 - mmengine - INFO - Epoch(train) [13][9400/10520] lr: 1.0000e-04 eta: 1 day, 2:14:24 time: 0.8807 data_time: 0.0066 memory: 56769 loss_visual: 0.0595 loss: 0.0595 2022/09/17 15:22:31 - mmengine - INFO - Epoch(train) [13][9500/10520] lr: 1.0000e-04 eta: 1 day, 2:12:14 time: 0.9110 data_time: 0.0070 memory: 56769 loss_visual: 0.0598 loss: 0.0598 2022/09/17 15:24:29 - mmengine - INFO - Epoch(train) [13][9600/10520] lr: 1.0000e-04 eta: 1 day, 2:10:02 time: 0.8476 data_time: 0.0263 memory: 56769 loss_visual: 0.0641 loss: 0.0641 2022/09/17 15:26:31 - mmengine - INFO - Epoch(train) [13][9700/10520] lr: 1.0000e-04 eta: 1 day, 2:07:54 time: 1.3066 data_time: 0.4398 memory: 56769 loss_visual: 0.0598 loss: 0.0598 2022/09/17 15:27:41 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 15:28:33 - mmengine - INFO - Epoch(train) [13][9800/10520] lr: 1.0000e-04 eta: 1 day, 2:05:45 time: 1.5708 data_time: 0.4306 memory: 56769 loss_visual: 0.0603 loss: 0.0603 2022/09/17 15:30:34 - mmengine - INFO - Epoch(train) [13][9900/10520] lr: 1.0000e-04 eta: 1 day, 2:03:36 time: 1.4358 data_time: 0.2774 memory: 56769 loss_visual: 0.0586 loss: 0.0586 2022/09/17 15:32:32 - mmengine - INFO - Epoch(train) [13][10000/10520] lr: 1.0000e-04 eta: 1 day, 2:01:25 time: 1.4074 data_time: 0.2505 memory: 56769 loss_visual: 0.0640 loss: 0.0640 2022/09/17 15:34:31 - mmengine - INFO - Epoch(train) [13][10100/10520] lr: 1.0000e-04 eta: 1 day, 1:59:15 time: 0.9210 data_time: 0.0065 memory: 56769 loss_visual: 0.0654 loss: 0.0654 2022/09/17 15:36:30 - mmengine - INFO - Epoch(train) [13][10200/10520] lr: 1.0000e-04 eta: 1 day, 1:57:04 time: 0.9354 data_time: 0.0080 memory: 56769 loss_visual: 0.0584 loss: 0.0584 2022/09/17 15:38:28 - mmengine - INFO - Epoch(train) [13][10300/10520] lr: 1.0000e-04 eta: 1 day, 1:54:54 time: 0.9336 data_time: 0.0073 memory: 56769 loss_visual: 0.0611 loss: 0.0611 2022/09/17 15:40:29 - mmengine - INFO - Epoch(train) [13][10400/10520] lr: 1.0000e-04 eta: 1 day, 1:52:44 time: 0.8878 data_time: 0.0238 memory: 56769 loss_visual: 0.0615 loss: 0.0615 2022/09/17 15:42:29 - mmengine - INFO - Epoch(train) [13][10500/10520] lr: 1.0000e-04 eta: 1 day, 1:50:35 time: 1.1372 data_time: 0.3085 memory: 56769 loss_visual: 0.0604 loss: 0.0604 2022/09/17 15:42:48 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 15:42:48 - mmengine - INFO - Saving checkpoint at 13 epochs 2022/09/17 15:43:04 - mmengine - INFO - Epoch(val) [13][100/3836] eta: 0:05:18 time: 0.0853 data_time: 0.0005 memory: 56769 2022/09/17 15:43:08 - mmengine - INFO - Epoch(val) [13][200/3836] eta: 0:00:41 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 15:43:09 - mmengine - INFO - Epoch(val) [13][300/3836] eta: 0:00:40 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 15:43:10 - mmengine - INFO - Epoch(val) [13][400/3836] eta: 0:00:39 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 15:43:11 - mmengine - INFO - Epoch(val) [13][500/3836] eta: 0:00:39 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/17 15:43:13 - mmengine - INFO - Epoch(val) [13][600/3836] eta: 0:00:36 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/17 15:43:14 - mmengine - INFO - Epoch(val) [13][700/3836] eta: 0:00:37 time: 0.0119 data_time: 0.0007 memory: 480 2022/09/17 15:43:15 - mmengine - INFO - Epoch(val) [13][800/3836] eta: 0:00:35 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 15:43:16 - mmengine - INFO - Epoch(val) [13][900/3836] eta: 0:00:38 time: 0.0130 data_time: 0.0005 memory: 480 2022/09/17 15:43:17 - mmengine - INFO - Epoch(val) [13][1000/3836] eta: 0:00:30 time: 0.0106 data_time: 0.0005 memory: 480 2022/09/17 15:43:18 - mmengine - INFO - Epoch(val) [13][1100/3836] eta: 0:00:32 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 15:43:20 - mmengine - INFO - Epoch(val) [13][1200/3836] eta: 0:00:30 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 15:43:21 - mmengine - INFO - Epoch(val) [13][1300/3836] eta: 0:00:30 time: 0.0121 data_time: 0.0005 memory: 480 2022/09/17 15:43:22 - mmengine - INFO - Epoch(val) [13][1400/3836] eta: 0:00:28 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/17 15:43:23 - mmengine - INFO - Epoch(val) [13][1500/3836] eta: 0:00:26 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 15:43:24 - mmengine - INFO - Epoch(val) [13][1600/3836] eta: 0:00:25 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 15:43:26 - mmengine - INFO - Epoch(val) [13][1700/3836] eta: 0:00:24 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 15:43:27 - mmengine - INFO - Epoch(val) [13][1800/3836] eta: 0:00:24 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 15:43:28 - mmengine - INFO - Epoch(val) [13][1900/3836] eta: 0:00:22 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 15:43:29 - mmengine - INFO - Epoch(val) [13][2000/3836] eta: 0:00:21 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 15:43:30 - mmengine - INFO - Epoch(val) [13][2100/3836] eta: 0:00:20 time: 0.0119 data_time: 0.0004 memory: 480 2022/09/17 15:43:31 - mmengine - INFO - Epoch(val) [13][2200/3836] eta: 0:00:19 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/17 15:43:33 - mmengine - INFO - Epoch(val) [13][2300/3836] eta: 0:00:17 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 15:43:34 - mmengine - INFO - Epoch(val) [13][2400/3836] eta: 0:00:16 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 15:43:35 - mmengine - INFO - Epoch(val) [13][2500/3836] eta: 0:00:15 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 15:43:36 - mmengine - INFO - Epoch(val) [13][2600/3836] eta: 0:00:15 time: 0.0122 data_time: 0.0005 memory: 480 2022/09/17 15:43:37 - mmengine - INFO - Epoch(val) [13][2700/3836] eta: 0:00:12 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 15:43:39 - mmengine - INFO - Epoch(val) [13][2800/3836] eta: 0:00:17 time: 0.0166 data_time: 0.0005 memory: 480 2022/09/17 15:43:40 - mmengine - INFO - Epoch(val) [13][2900/3836] eta: 0:00:11 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 15:43:41 - mmengine - INFO - Epoch(val) [13][3000/3836] eta: 0:00:10 time: 0.0126 data_time: 0.0005 memory: 480 2022/09/17 15:43:42 - mmengine - INFO - Epoch(val) [13][3100/3836] eta: 0:00:08 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 15:43:43 - mmengine - INFO - Epoch(val) [13][3200/3836] eta: 0:00:07 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 15:43:45 - mmengine - INFO - Epoch(val) [13][3300/3836] eta: 0:00:05 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/17 15:43:46 - mmengine - INFO - Epoch(val) [13][3400/3836] eta: 0:00:04 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 15:43:47 - mmengine - INFO - Epoch(val) [13][3500/3836] eta: 0:00:03 time: 0.0106 data_time: 0.0005 memory: 480 2022/09/17 15:43:48 - mmengine - INFO - Epoch(val) [13][3600/3836] eta: 0:00:02 time: 0.0106 data_time: 0.0005 memory: 480 2022/09/17 15:43:49 - mmengine - INFO - Epoch(val) [13][3700/3836] eta: 0:00:01 time: 0.0106 data_time: 0.0005 memory: 480 2022/09/17 15:43:50 - mmengine - INFO - Epoch(val) [13][3800/3836] eta: 0:00:00 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/17 15:43:51 - mmengine - INFO - Epoch(val) [13][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.8333 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9393 SVT/recog/word_acc_ignore_case_symbol: 0.8980 SVTP/recog/word_acc_ignore_case_symbol: 0.8109 IC13/recog/word_acc_ignore_case_symbol: 0.9271 IC15/recog/word_acc_ignore_case_symbol: 0.7684 2022/09/17 15:46:16 - mmengine - INFO - Epoch(train) [14][100/10520] lr: 1.0000e-04 eta: 1 day, 1:48:09 time: 1.7143 data_time: 0.7869 memory: 56769 loss_visual: 0.0555 loss: 0.0555 2022/09/17 15:48:24 - mmengine - INFO - Epoch(train) [14][200/10520] lr: 1.0000e-04 eta: 1 day, 1:46:04 time: 2.0050 data_time: 0.7551 memory: 56769 loss_visual: 0.0603 loss: 0.0603 2022/09/17 15:49:12 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 15:50:30 - mmengine - INFO - Epoch(train) [14][300/10520] lr: 1.0000e-04 eta: 1 day, 1:43:58 time: 1.3266 data_time: 0.0084 memory: 56769 loss_visual: 0.0604 loss: 0.0604 2022/09/17 15:52:36 - mmengine - INFO - Epoch(train) [14][400/10520] lr: 1.0000e-04 eta: 1 day, 1:41:51 time: 0.9596 data_time: 0.0078 memory: 56769 loss_visual: 0.0551 loss: 0.0551 2022/09/17 15:54:42 - mmengine - INFO - Epoch(train) [14][500/10520] lr: 1.0000e-04 eta: 1 day, 1:39:45 time: 0.9219 data_time: 0.0069 memory: 56769 loss_visual: 0.0604 loss: 0.0604 2022/09/17 15:56:48 - mmengine - INFO - Epoch(train) [14][600/10520] lr: 1.0000e-04 eta: 1 day, 1:37:38 time: 0.8807 data_time: 0.0075 memory: 56769 loss_visual: 0.0620 loss: 0.0620 2022/09/17 15:58:52 - mmengine - INFO - Epoch(train) [14][700/10520] lr: 1.0000e-04 eta: 1 day, 1:35:31 time: 0.9013 data_time: 0.0357 memory: 56769 loss_visual: 0.0636 loss: 0.0636 2022/09/17 16:00:58 - mmengine - INFO - Epoch(train) [14][800/10520] lr: 1.0000e-04 eta: 1 day, 1:33:24 time: 0.9865 data_time: 0.1350 memory: 56769 loss_visual: 0.0622 loss: 0.0622 2022/09/17 16:03:11 - mmengine - INFO - Epoch(train) [14][900/10520] lr: 1.0000e-04 eta: 1 day, 1:31:21 time: 1.7138 data_time: 0.7597 memory: 56769 loss_visual: 0.0587 loss: 0.0587 2022/09/17 16:05:19 - mmengine - INFO - Epoch(train) [14][1000/10520] lr: 1.0000e-04 eta: 1 day, 1:29:16 time: 1.9399 data_time: 0.6657 memory: 56769 loss_visual: 0.0629 loss: 0.0629 2022/09/17 16:07:24 - mmengine - INFO - Epoch(train) [14][1100/10520] lr: 1.0000e-04 eta: 1 day, 1:27:09 time: 1.3292 data_time: 0.0070 memory: 56769 loss_visual: 0.0575 loss: 0.0575 2022/09/17 16:09:29 - mmengine - INFO - Epoch(train) [14][1200/10520] lr: 1.0000e-04 eta: 1 day, 1:25:02 time: 0.9420 data_time: 0.0068 memory: 56769 loss_visual: 0.0626 loss: 0.0626 2022/09/17 16:10:16 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 16:11:33 - mmengine - INFO - Epoch(train) [14][1300/10520] lr: 1.0000e-04 eta: 1 day, 1:22:54 time: 0.9504 data_time: 0.0075 memory: 56769 loss_visual: 0.0591 loss: 0.0591 2022/09/17 16:13:38 - mmengine - INFO - Epoch(train) [14][1400/10520] lr: 1.0000e-04 eta: 1 day, 1:20:47 time: 0.8962 data_time: 0.0070 memory: 56769 loss_visual: 0.0614 loss: 0.0614 2022/09/17 16:15:43 - mmengine - INFO - Epoch(train) [14][1500/10520] lr: 1.0000e-04 eta: 1 day, 1:18:40 time: 0.9241 data_time: 0.0542 memory: 56769 loss_visual: 0.0577 loss: 0.0577 2022/09/17 16:17:49 - mmengine - INFO - Epoch(train) [14][1600/10520] lr: 1.0000e-04 eta: 1 day, 1:16:34 time: 0.9998 data_time: 0.1728 memory: 56769 loss_visual: 0.0567 loss: 0.0567 2022/09/17 16:20:01 - mmengine - INFO - Epoch(train) [14][1700/10520] lr: 1.0000e-04 eta: 1 day, 1:14:30 time: 1.7354 data_time: 0.8083 memory: 56769 loss_visual: 0.0630 loss: 0.0630 2022/09/17 16:22:08 - mmengine - INFO - Epoch(train) [14][1800/10520] lr: 1.0000e-04 eta: 1 day, 1:12:24 time: 1.9052 data_time: 0.5829 memory: 56769 loss_visual: 0.0608 loss: 0.0608 2022/09/17 16:24:15 - mmengine - INFO - Epoch(train) [14][1900/10520] lr: 1.0000e-04 eta: 1 day, 1:10:18 time: 1.3022 data_time: 0.0078 memory: 56769 loss_visual: 0.0586 loss: 0.0586 2022/09/17 16:26:20 - mmengine - INFO - Epoch(train) [14][2000/10520] lr: 1.0000e-04 eta: 1 day, 1:08:11 time: 0.9153 data_time: 0.0068 memory: 56769 loss_visual: 0.0626 loss: 0.0626 2022/09/17 16:28:26 - mmengine - INFO - Epoch(train) [14][2100/10520] lr: 1.0000e-04 eta: 1 day, 1:06:05 time: 0.9681 data_time: 0.0068 memory: 56769 loss_visual: 0.0617 loss: 0.0617 2022/09/17 16:30:30 - mmengine - INFO - Epoch(train) [14][2200/10520] lr: 1.0000e-04 eta: 1 day, 1:03:57 time: 0.8795 data_time: 0.0076 memory: 56769 loss_visual: 0.0572 loss: 0.0572 2022/09/17 16:31:19 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 16:32:35 - mmengine - INFO - Epoch(train) [14][2300/10520] lr: 1.0000e-04 eta: 1 day, 1:01:50 time: 0.9694 data_time: 0.0496 memory: 56769 loss_visual: 0.0622 loss: 0.0622 2022/09/17 16:34:40 - mmengine - INFO - Epoch(train) [14][2400/10520] lr: 1.0000e-04 eta: 1 day, 0:59:43 time: 0.9766 data_time: 0.1577 memory: 56769 loss_visual: 0.0570 loss: 0.0570 2022/09/17 16:36:52 - mmengine - INFO - Epoch(train) [14][2500/10520] lr: 1.0000e-04 eta: 1 day, 0:57:40 time: 1.6869 data_time: 0.7043 memory: 56769 loss_visual: 0.0564 loss: 0.0564 2022/09/17 16:39:00 - mmengine - INFO - Epoch(train) [14][2600/10520] lr: 1.0000e-04 eta: 1 day, 0:55:34 time: 1.9445 data_time: 0.6406 memory: 56769 loss_visual: 0.0575 loss: 0.0575 2022/09/17 16:41:06 - mmengine - INFO - Epoch(train) [14][2700/10520] lr: 1.0000e-04 eta: 1 day, 0:53:28 time: 1.3999 data_time: 0.0079 memory: 56769 loss_visual: 0.0610 loss: 0.0610 2022/09/17 16:43:11 - mmengine - INFO - Epoch(train) [14][2800/10520] lr: 1.0000e-04 eta: 1 day, 0:51:21 time: 0.9187 data_time: 0.0073 memory: 56769 loss_visual: 0.0579 loss: 0.0579 2022/09/17 16:45:16 - mmengine - INFO - Epoch(train) [14][2900/10520] lr: 1.0000e-04 eta: 1 day, 0:49:14 time: 0.9250 data_time: 0.0078 memory: 56769 loss_visual: 0.0587 loss: 0.0587 2022/09/17 16:47:21 - mmengine - INFO - Epoch(train) [14][3000/10520] lr: 1.0000e-04 eta: 1 day, 0:47:07 time: 0.9205 data_time: 0.0072 memory: 56769 loss_visual: 0.0594 loss: 0.0594 2022/09/17 16:49:26 - mmengine - INFO - Epoch(train) [14][3100/10520] lr: 1.0000e-04 eta: 1 day, 0:45:00 time: 0.9342 data_time: 0.0986 memory: 56769 loss_visual: 0.0637 loss: 0.0637 2022/09/17 16:51:31 - mmengine - INFO - Epoch(train) [14][3200/10520] lr: 1.0000e-04 eta: 1 day, 0:42:53 time: 0.9967 data_time: 0.1771 memory: 56769 loss_visual: 0.0640 loss: 0.0640 2022/09/17 16:52:29 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 16:53:43 - mmengine - INFO - Epoch(train) [14][3300/10520] lr: 1.0000e-04 eta: 1 day, 0:40:49 time: 1.7826 data_time: 0.7865 memory: 56769 loss_visual: 0.0638 loss: 0.0638 2022/09/17 16:55:50 - mmengine - INFO - Epoch(train) [14][3400/10520] lr: 1.0000e-04 eta: 1 day, 0:38:43 time: 1.9454 data_time: 0.6512 memory: 56769 loss_visual: 0.0585 loss: 0.0585 2022/09/17 16:57:56 - mmengine - INFO - Epoch(train) [14][3500/10520] lr: 1.0000e-04 eta: 1 day, 0:36:37 time: 1.3255 data_time: 0.0078 memory: 56769 loss_visual: 0.0583 loss: 0.0583 2022/09/17 17:00:00 - mmengine - INFO - Epoch(train) [14][3600/10520] lr: 1.0000e-04 eta: 1 day, 0:34:29 time: 0.9098 data_time: 0.0072 memory: 56769 loss_visual: 0.0586 loss: 0.0586 2022/09/17 17:02:05 - mmengine - INFO - Epoch(train) [14][3700/10520] lr: 1.0000e-04 eta: 1 day, 0:32:22 time: 0.9175 data_time: 0.0070 memory: 56769 loss_visual: 0.0602 loss: 0.0602 2022/09/17 17:04:09 - mmengine - INFO - Epoch(train) [14][3800/10520] lr: 1.0000e-04 eta: 1 day, 0:30:15 time: 0.9095 data_time: 0.0070 memory: 56769 loss_visual: 0.0551 loss: 0.0551 2022/09/17 17:06:13 - mmengine - INFO - Epoch(train) [14][3900/10520] lr: 1.0000e-04 eta: 1 day, 0:28:07 time: 0.9409 data_time: 0.0412 memory: 56769 loss_visual: 0.0584 loss: 0.0584 2022/09/17 17:08:19 - mmengine - INFO - Epoch(train) [14][4000/10520] lr: 1.0000e-04 eta: 1 day, 0:26:01 time: 1.0072 data_time: 0.1354 memory: 56769 loss_visual: 0.0603 loss: 0.0603 2022/09/17 17:10:30 - mmengine - INFO - Epoch(train) [14][4100/10520] lr: 1.0000e-04 eta: 1 day, 0:23:57 time: 1.7526 data_time: 0.7876 memory: 56769 loss_visual: 0.0634 loss: 0.0634 2022/09/17 17:12:40 - mmengine - INFO - Epoch(train) [14][4200/10520] lr: 1.0000e-04 eta: 1 day, 0:21:52 time: 1.9290 data_time: 0.6167 memory: 56769 loss_visual: 0.0606 loss: 0.0606 2022/09/17 17:13:28 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 17:14:44 - mmengine - INFO - Epoch(train) [14][4300/10520] lr: 1.0000e-04 eta: 1 day, 0:19:45 time: 1.2835 data_time: 0.0088 memory: 56769 loss_visual: 0.0544 loss: 0.0544 2022/09/17 17:16:49 - mmengine - INFO - Epoch(train) [14][4400/10520] lr: 1.0000e-04 eta: 1 day, 0:17:38 time: 0.9745 data_time: 0.0071 memory: 56769 loss_visual: 0.0617 loss: 0.0617 2022/09/17 17:18:54 - mmengine - INFO - Epoch(train) [14][4500/10520] lr: 1.0000e-04 eta: 1 day, 0:15:31 time: 0.9751 data_time: 0.0116 memory: 56769 loss_visual: 0.0616 loss: 0.0616 2022/09/17 17:20:57 - mmengine - INFO - Epoch(train) [14][4600/10520] lr: 1.0000e-04 eta: 1 day, 0:13:23 time: 0.8719 data_time: 0.0070 memory: 56769 loss_visual: 0.0564 loss: 0.0564 2022/09/17 17:23:02 - mmengine - INFO - Epoch(train) [14][4700/10520] lr: 1.0000e-04 eta: 1 day, 0:11:16 time: 0.9374 data_time: 0.0388 memory: 56769 loss_visual: 0.0617 loss: 0.0617 2022/09/17 17:25:08 - mmengine - INFO - Epoch(train) [14][4800/10520] lr: 1.0000e-04 eta: 1 day, 0:09:10 time: 1.0380 data_time: 0.1554 memory: 56769 loss_visual: 0.0569 loss: 0.0569 2022/09/17 17:27:19 - mmengine - INFO - Epoch(train) [14][4900/10520] lr: 1.0000e-04 eta: 1 day, 0:07:05 time: 1.7125 data_time: 0.7454 memory: 56769 loss_visual: 0.0575 loss: 0.0575 2022/09/17 17:29:25 - mmengine - INFO - Epoch(train) [14][5000/10520] lr: 1.0000e-04 eta: 1 day, 0:04:59 time: 1.8546 data_time: 0.6285 memory: 56769 loss_visual: 0.0624 loss: 0.0624 2022/09/17 17:31:30 - mmengine - INFO - Epoch(train) [14][5100/10520] lr: 1.0000e-04 eta: 1 day, 0:02:52 time: 1.2943 data_time: 0.0072 memory: 56769 loss_visual: 0.0576 loss: 0.0576 2022/09/17 17:33:34 - mmengine - INFO - Epoch(train) [14][5200/10520] lr: 1.0000e-04 eta: 1 day, 0:00:45 time: 0.9366 data_time: 0.0080 memory: 56769 loss_visual: 0.0622 loss: 0.0622 2022/09/17 17:34:22 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 17:35:38 - mmengine - INFO - Epoch(train) [14][5300/10520] lr: 1.0000e-04 eta: 23:58:37 time: 0.9748 data_time: 0.0085 memory: 56769 loss_visual: 0.0598 loss: 0.0598 2022/09/17 17:37:40 - mmengine - INFO - Epoch(train) [14][5400/10520] lr: 1.0000e-04 eta: 23:56:29 time: 0.9222 data_time: 0.0080 memory: 56769 loss_visual: 0.0625 loss: 0.0625 2022/09/17 17:39:44 - mmengine - INFO - Epoch(train) [14][5500/10520] lr: 1.0000e-04 eta: 23:54:21 time: 0.9424 data_time: 0.1060 memory: 56769 loss_visual: 0.0622 loss: 0.0622 2022/09/17 17:41:50 - mmengine - INFO - Epoch(train) [14][5600/10520] lr: 1.0000e-04 eta: 23:52:15 time: 1.0229 data_time: 0.1757 memory: 56769 loss_visual: 0.0552 loss: 0.0552 2022/09/17 17:44:00 - mmengine - INFO - Epoch(train) [14][5700/10520] lr: 1.0000e-04 eta: 23:50:10 time: 1.6924 data_time: 0.6962 memory: 56769 loss_visual: 0.0611 loss: 0.0611 2022/09/17 17:46:08 - mmengine - INFO - Epoch(train) [14][5800/10520] lr: 1.0000e-04 eta: 23:48:05 time: 1.9009 data_time: 0.6404 memory: 56769 loss_visual: 0.0611 loss: 0.0611 2022/09/17 17:48:13 - mmengine - INFO - Epoch(train) [14][5900/10520] lr: 1.0000e-04 eta: 23:45:58 time: 1.3381 data_time: 0.0070 memory: 56769 loss_visual: 0.0591 loss: 0.0591 2022/09/17 17:50:20 - mmengine - INFO - Epoch(train) [14][6000/10520] lr: 1.0000e-04 eta: 23:43:52 time: 0.9032 data_time: 0.0071 memory: 56769 loss_visual: 0.0609 loss: 0.0609 2022/09/17 17:52:24 - mmengine - INFO - Epoch(train) [14][6100/10520] lr: 1.0000e-04 eta: 23:41:44 time: 0.9531 data_time: 0.0065 memory: 56769 loss_visual: 0.0662 loss: 0.0662 2022/09/17 17:54:28 - mmengine - INFO - Epoch(train) [14][6200/10520] lr: 1.0000e-04 eta: 23:39:37 time: 0.9333 data_time: 0.0067 memory: 56769 loss_visual: 0.0568 loss: 0.0568 2022/09/17 17:55:16 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 17:56:32 - mmengine - INFO - Epoch(train) [14][6300/10520] lr: 1.0000e-04 eta: 23:37:30 time: 1.0024 data_time: 0.0740 memory: 56769 loss_visual: 0.0591 loss: 0.0591 2022/09/17 17:58:38 - mmengine - INFO - Epoch(train) [14][6400/10520] lr: 1.0000e-04 eta: 23:35:23 time: 1.0027 data_time: 0.1487 memory: 56769 loss_visual: 0.0602 loss: 0.0602 2022/09/17 18:00:52 - mmengine - INFO - Epoch(train) [14][6500/10520] lr: 1.0000e-04 eta: 23:33:20 time: 1.7203 data_time: 0.7012 memory: 56769 loss_visual: 0.0572 loss: 0.0572 2022/09/17 18:03:00 - mmengine - INFO - Epoch(train) [14][6600/10520] lr: 1.0000e-04 eta: 23:31:15 time: 1.8939 data_time: 0.6515 memory: 56769 loss_visual: 0.0566 loss: 0.0566 2022/09/17 18:05:04 - mmengine - INFO - Epoch(train) [14][6700/10520] lr: 1.0000e-04 eta: 23:29:07 time: 1.2892 data_time: 0.0073 memory: 56769 loss_visual: 0.0596 loss: 0.0596 2022/09/17 18:07:08 - mmengine - INFO - Epoch(train) [14][6800/10520] lr: 1.0000e-04 eta: 23:27:00 time: 0.9377 data_time: 0.0076 memory: 56769 loss_visual: 0.0627 loss: 0.0627 2022/09/17 18:09:11 - mmengine - INFO - Epoch(train) [14][6900/10520] lr: 1.0000e-04 eta: 23:24:52 time: 0.9327 data_time: 0.0070 memory: 56769 loss_visual: 0.0607 loss: 0.0607 2022/09/17 18:11:16 - mmengine - INFO - Epoch(train) [14][7000/10520] lr: 1.0000e-04 eta: 23:22:45 time: 0.9029 data_time: 0.0068 memory: 56769 loss_visual: 0.0589 loss: 0.0589 2022/09/17 18:13:21 - mmengine - INFO - Epoch(train) [14][7100/10520] lr: 1.0000e-04 eta: 23:20:38 time: 0.9404 data_time: 0.0562 memory: 56769 loss_visual: 0.0610 loss: 0.0610 2022/09/17 18:15:25 - mmengine - INFO - Epoch(train) [14][7200/10520] lr: 1.0000e-04 eta: 23:18:31 time: 0.9903 data_time: 0.1505 memory: 56769 loss_visual: 0.0595 loss: 0.0595 2022/09/17 18:16:22 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 18:17:35 - mmengine - INFO - Epoch(train) [14][7300/10520] lr: 1.0000e-04 eta: 23:16:26 time: 1.7131 data_time: 0.7453 memory: 56769 loss_visual: 0.0605 loss: 0.0605 2022/09/17 18:19:43 - mmengine - INFO - Epoch(train) [14][7400/10520] lr: 1.0000e-04 eta: 23:14:21 time: 1.9474 data_time: 0.6937 memory: 56769 loss_visual: 0.0605 loss: 0.0605 2022/09/17 18:21:47 - mmengine - INFO - Epoch(train) [14][7500/10520] lr: 1.0000e-04 eta: 23:12:13 time: 1.2568 data_time: 0.0075 memory: 56769 loss_visual: 0.0555 loss: 0.0555 2022/09/17 18:23:51 - mmengine - INFO - Epoch(train) [14][7600/10520] lr: 1.0000e-04 eta: 23:10:06 time: 0.9116 data_time: 0.0065 memory: 56769 loss_visual: 0.0580 loss: 0.0580 2022/09/17 18:25:55 - mmengine - INFO - Epoch(train) [14][7700/10520] lr: 1.0000e-04 eta: 23:07:58 time: 0.9307 data_time: 0.0070 memory: 56769 loss_visual: 0.0571 loss: 0.0571 2022/09/17 18:28:00 - mmengine - INFO - Epoch(train) [14][7800/10520] lr: 1.0000e-04 eta: 23:05:52 time: 0.9159 data_time: 0.0075 memory: 56769 loss_visual: 0.0617 loss: 0.0617 2022/09/17 18:30:05 - mmengine - INFO - Epoch(train) [14][7900/10520] lr: 1.0000e-04 eta: 23:03:45 time: 0.9978 data_time: 0.0564 memory: 56769 loss_visual: 0.0564 loss: 0.0564 2022/09/17 18:32:10 - mmengine - INFO - Epoch(train) [14][8000/10520] lr: 1.0000e-04 eta: 23:01:38 time: 1.0193 data_time: 0.1461 memory: 56769 loss_visual: 0.0598 loss: 0.0598 2022/09/17 18:34:22 - mmengine - INFO - Epoch(train) [14][8100/10520] lr: 1.0000e-04 eta: 22:59:34 time: 1.7292 data_time: 0.7381 memory: 56769 loss_visual: 0.0599 loss: 0.0599 2022/09/17 18:36:30 - mmengine - INFO - Epoch(train) [14][8200/10520] lr: 1.0000e-04 eta: 22:57:29 time: 1.9532 data_time: 0.6859 memory: 56769 loss_visual: 0.0574 loss: 0.0574 2022/09/17 18:37:18 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 18:38:34 - mmengine - INFO - Epoch(train) [14][8300/10520] lr: 1.0000e-04 eta: 22:55:21 time: 1.2554 data_time: 0.0076 memory: 56769 loss_visual: 0.0598 loss: 0.0598 2022/09/17 18:40:39 - mmengine - INFO - Epoch(train) [14][8400/10520] lr: 1.0000e-04 eta: 22:53:14 time: 0.9097 data_time: 0.0074 memory: 56769 loss_visual: 0.0612 loss: 0.0612 2022/09/17 18:42:43 - mmengine - INFO - Epoch(train) [14][8500/10520] lr: 1.0000e-04 eta: 22:51:07 time: 0.9316 data_time: 0.0074 memory: 56769 loss_visual: 0.0635 loss: 0.0635 2022/09/17 18:44:47 - mmengine - INFO - Epoch(train) [14][8600/10520] lr: 1.0000e-04 eta: 22:49:00 time: 0.8978 data_time: 0.0067 memory: 56769 loss_visual: 0.0544 loss: 0.0544 2022/09/17 18:46:53 - mmengine - INFO - Epoch(train) [14][8700/10520] lr: 1.0000e-04 eta: 22:46:53 time: 0.9874 data_time: 0.0548 memory: 56769 loss_visual: 0.0571 loss: 0.0571 2022/09/17 18:48:59 - mmengine - INFO - Epoch(train) [14][8800/10520] lr: 1.0000e-04 eta: 22:44:47 time: 1.0213 data_time: 0.1430 memory: 56769 loss_visual: 0.0587 loss: 0.0587 2022/09/17 18:51:11 - mmengine - INFO - Epoch(train) [14][8900/10520] lr: 1.0000e-04 eta: 22:42:43 time: 1.7903 data_time: 0.7574 memory: 56769 loss_visual: 0.0593 loss: 0.0593 2022/09/17 18:53:18 - mmengine - INFO - Epoch(train) [14][9000/10520] lr: 1.0000e-04 eta: 22:40:37 time: 1.8907 data_time: 0.6452 memory: 56769 loss_visual: 0.0632 loss: 0.0632 2022/09/17 18:55:25 - mmengine - INFO - Epoch(train) [14][9100/10520] lr: 1.0000e-04 eta: 22:38:31 time: 1.3282 data_time: 0.0078 memory: 56769 loss_visual: 0.0575 loss: 0.0575 2022/09/17 18:57:30 - mmengine - INFO - Epoch(train) [14][9200/10520] lr: 1.0000e-04 eta: 22:36:24 time: 0.9091 data_time: 0.0073 memory: 56769 loss_visual: 0.0603 loss: 0.0603 2022/09/17 18:58:17 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 18:59:35 - mmengine - INFO - Epoch(train) [14][9300/10520] lr: 1.0000e-04 eta: 22:34:17 time: 0.9665 data_time: 0.0070 memory: 56769 loss_visual: 0.0577 loss: 0.0577 2022/09/17 19:01:39 - mmengine - INFO - Epoch(train) [14][9400/10520] lr: 1.0000e-04 eta: 22:32:10 time: 0.9096 data_time: 0.0069 memory: 56769 loss_visual: 0.0601 loss: 0.0601 2022/09/17 19:03:44 - mmengine - INFO - Epoch(train) [14][9500/10520] lr: 1.0000e-04 eta: 22:30:03 time: 0.9740 data_time: 0.0568 memory: 56769 loss_visual: 0.0637 loss: 0.0637 2022/09/17 19:05:49 - mmengine - INFO - Epoch(train) [14][9600/10520] lr: 1.0000e-04 eta: 22:27:56 time: 0.9850 data_time: 0.1495 memory: 56769 loss_visual: 0.0582 loss: 0.0582 2022/09/17 19:08:01 - mmengine - INFO - Epoch(train) [14][9700/10520] lr: 1.0000e-04 eta: 22:25:52 time: 1.7165 data_time: 0.7163 memory: 56769 loss_visual: 0.0598 loss: 0.0598 2022/09/17 19:10:08 - mmengine - INFO - Epoch(train) [14][9800/10520] lr: 1.0000e-04 eta: 22:23:46 time: 1.9192 data_time: 0.6655 memory: 56769 loss_visual: 0.0580 loss: 0.0580 2022/09/17 19:12:13 - mmengine - INFO - Epoch(train) [14][9900/10520] lr: 1.0000e-04 eta: 22:21:40 time: 1.2871 data_time: 0.0076 memory: 56769 loss_visual: 0.0582 loss: 0.0582 2022/09/17 19:14:19 - mmengine - INFO - Epoch(train) [14][10000/10520] lr: 1.0000e-04 eta: 22:19:33 time: 0.8854 data_time: 0.0075 memory: 56769 loss_visual: 0.0597 loss: 0.0597 2022/09/17 19:16:23 - mmengine - INFO - Epoch(train) [14][10100/10520] lr: 1.0000e-04 eta: 22:17:26 time: 0.9333 data_time: 0.0075 memory: 56769 loss_visual: 0.0621 loss: 0.0621 2022/09/17 19:18:28 - mmengine - INFO - Epoch(train) [14][10200/10520] lr: 1.0000e-04 eta: 22:15:19 time: 0.9067 data_time: 0.0070 memory: 56769 loss_visual: 0.0585 loss: 0.0585 2022/09/17 19:19:18 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 19:20:35 - mmengine - INFO - Epoch(train) [14][10300/10520] lr: 1.0000e-04 eta: 22:13:13 time: 0.9970 data_time: 0.0597 memory: 56769 loss_visual: 0.0566 loss: 0.0566 2022/09/17 19:22:39 - mmengine - INFO - Epoch(train) [14][10400/10520] lr: 1.0000e-04 eta: 22:11:06 time: 1.0128 data_time: 0.1407 memory: 56769 loss_visual: 0.0601 loss: 0.0601 2022/09/17 19:24:45 - mmengine - INFO - Epoch(train) [14][10500/10520] lr: 1.0000e-04 eta: 22:08:59 time: 1.3670 data_time: 0.4657 memory: 56769 loss_visual: 0.0585 loss: 0.0585 2022/09/17 19:25:04 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 19:25:04 - mmengine - INFO - Saving checkpoint at 14 epochs 2022/09/17 19:25:23 - mmengine - INFO - Epoch(val) [14][100/3836] eta: 0:06:58 time: 0.1120 data_time: 0.0007 memory: 56769 2022/09/17 19:25:28 - mmengine - INFO - Epoch(val) [14][200/3836] eta: 0:00:40 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/17 19:25:29 - mmengine - INFO - Epoch(val) [14][300/3836] eta: 0:00:40 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/17 19:25:31 - mmengine - INFO - Epoch(val) [14][400/3836] eta: 0:00:42 time: 0.0125 data_time: 0.0007 memory: 480 2022/09/17 19:25:32 - mmengine - INFO - Epoch(val) [14][500/3836] eta: 0:00:39 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 19:25:33 - mmengine - INFO - Epoch(val) [14][600/3836] eta: 0:00:39 time: 0.0123 data_time: 0.0006 memory: 480 2022/09/17 19:25:34 - mmengine - INFO - Epoch(val) [14][700/3836] eta: 0:00:35 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 19:25:35 - mmengine - INFO - Epoch(val) [14][800/3836] eta: 0:00:34 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/17 19:25:37 - mmengine - INFO - Epoch(val) [14][900/3836] eta: 0:00:33 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 19:25:38 - mmengine - INFO - Epoch(val) [14][1000/3836] eta: 0:00:33 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/17 19:25:39 - mmengine - INFO - Epoch(val) [14][1100/3836] eta: 0:00:31 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 19:25:40 - mmengine - INFO - Epoch(val) [14][1200/3836] eta: 0:00:30 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 19:25:41 - mmengine - INFO - Epoch(val) [14][1300/3836] eta: 0:00:29 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 19:25:43 - mmengine - INFO - Epoch(val) [14][1400/3836] eta: 0:00:28 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 19:25:44 - mmengine - INFO - Epoch(val) [14][1500/3836] eta: 0:00:27 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 19:25:45 - mmengine - INFO - Epoch(val) [14][1600/3836] eta: 0:00:25 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/17 19:25:46 - mmengine - INFO - Epoch(val) [14][1700/3836] eta: 0:00:26 time: 0.0125 data_time: 0.0005 memory: 480 2022/09/17 19:25:47 - mmengine - INFO - Epoch(val) [14][1800/3836] eta: 0:00:23 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 19:25:49 - mmengine - INFO - Epoch(val) [14][1900/3836] eta: 0:00:22 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 19:25:50 - mmengine - INFO - Epoch(val) [14][2000/3836] eta: 0:00:21 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/17 19:25:51 - mmengine - INFO - Epoch(val) [14][2100/3836] eta: 0:00:19 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 19:25:52 - mmengine - INFO - Epoch(val) [14][2200/3836] eta: 0:00:18 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 19:25:53 - mmengine - INFO - Epoch(val) [14][2300/3836] eta: 0:00:18 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 19:25:54 - mmengine - INFO - Epoch(val) [14][2400/3836] eta: 0:00:16 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 19:25:56 - mmengine - INFO - Epoch(val) [14][2500/3836] eta: 0:00:15 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 19:25:57 - mmengine - INFO - Epoch(val) [14][2600/3836] eta: 0:00:14 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 19:25:58 - mmengine - INFO - Epoch(val) [14][2700/3836] eta: 0:00:13 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 19:25:59 - mmengine - INFO - Epoch(val) [14][2800/3836] eta: 0:00:11 time: 0.0113 data_time: 0.0004 memory: 480 2022/09/17 19:26:00 - mmengine - INFO - Epoch(val) [14][2900/3836] eta: 0:00:10 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 19:26:01 - mmengine - INFO - Epoch(val) [14][3000/3836] eta: 0:00:10 time: 0.0123 data_time: 0.0012 memory: 480 2022/09/17 19:26:03 - mmengine - INFO - Epoch(val) [14][3100/3836] eta: 0:00:08 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 19:26:04 - mmengine - INFO - Epoch(val) [14][3200/3836] eta: 0:00:06 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/17 19:26:05 - mmengine - INFO - Epoch(val) [14][3300/3836] eta: 0:00:05 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/17 19:26:06 - mmengine - INFO - Epoch(val) [14][3400/3836] eta: 0:00:04 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/17 19:26:07 - mmengine - INFO - Epoch(val) [14][3500/3836] eta: 0:00:03 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/17 19:26:08 - mmengine - INFO - Epoch(val) [14][3600/3836] eta: 0:00:02 time: 0.0108 data_time: 0.0004 memory: 480 2022/09/17 19:26:09 - mmengine - INFO - Epoch(val) [14][3700/3836] eta: 0:00:01 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/17 19:26:10 - mmengine - INFO - Epoch(val) [14][3800/3836] eta: 0:00:00 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/17 19:26:11 - mmengine - INFO - Epoch(val) [14][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.8507 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9400 SVT/recog/word_acc_ignore_case_symbol: 0.8918 SVTP/recog/word_acc_ignore_case_symbol: 0.8078 IC13/recog/word_acc_ignore_case_symbol: 0.9251 IC15/recog/word_acc_ignore_case_symbol: 0.7756 2022/09/17 19:28:30 - mmengine - INFO - Epoch(train) [15][100/10520] lr: 1.0000e-04 eta: 22:06:30 time: 1.4547 data_time: 0.6080 memory: 56769 loss_visual: 0.0605 loss: 0.0605 2022/09/17 19:30:34 - mmengine - INFO - Epoch(train) [15][200/10520] lr: 1.0000e-04 eta: 22:04:23 time: 1.8673 data_time: 0.7888 memory: 56769 loss_visual: 0.0548 loss: 0.0548 2022/09/17 19:32:34 - mmengine - INFO - Epoch(train) [15][300/10520] lr: 1.0000e-04 eta: 22:02:14 time: 1.5056 data_time: 0.3806 memory: 56769 loss_visual: 0.0584 loss: 0.0584 2022/09/17 19:34:35 - mmengine - INFO - Epoch(train) [15][400/10520] lr: 1.0000e-04 eta: 22:00:06 time: 1.0396 data_time: 0.0960 memory: 56769 loss_visual: 0.0553 loss: 0.0553 2022/09/17 19:36:36 - mmengine - INFO - Epoch(train) [15][500/10520] lr: 1.0000e-04 eta: 21:57:57 time: 1.0073 data_time: 0.0235 memory: 56769 loss_visual: 0.0586 loss: 0.0586 2022/09/17 19:38:36 - mmengine - INFO - Epoch(train) [15][600/10520] lr: 1.0000e-04 eta: 21:55:48 time: 0.8924 data_time: 0.0243 memory: 56769 loss_visual: 0.0578 loss: 0.0578 2022/09/17 19:40:38 - mmengine - INFO - Epoch(train) [15][700/10520] lr: 1.0000e-04 eta: 21:53:40 time: 0.9000 data_time: 0.0079 memory: 56769 loss_visual: 0.0569 loss: 0.0569 2022/09/17 19:41:07 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 19:42:40 - mmengine - INFO - Epoch(train) [15][800/10520] lr: 1.0000e-04 eta: 21:51:32 time: 0.9256 data_time: 0.0075 memory: 56769 loss_visual: 0.0596 loss: 0.0596 2022/09/17 19:44:45 - mmengine - INFO - Epoch(train) [15][900/10520] lr: 1.0000e-04 eta: 21:49:25 time: 1.3890 data_time: 0.5355 memory: 56769 loss_visual: 0.0594 loss: 0.0594 2022/09/17 19:46:48 - mmengine - INFO - Epoch(train) [15][1000/10520] lr: 1.0000e-04 eta: 21:47:17 time: 1.7963 data_time: 0.6256 memory: 56769 loss_visual: 0.0578 loss: 0.0578 2022/09/17 19:48:48 - mmengine - INFO - Epoch(train) [15][1100/10520] lr: 1.0000e-04 eta: 21:45:08 time: 1.4661 data_time: 0.4074 memory: 56769 loss_visual: 0.0607 loss: 0.0607 2022/09/17 19:50:48 - mmengine - INFO - Epoch(train) [15][1200/10520] lr: 1.0000e-04 eta: 21:43:00 time: 1.1199 data_time: 0.1641 memory: 56769 loss_visual: 0.0592 loss: 0.0592 2022/09/17 19:52:48 - mmengine - INFO - Epoch(train) [15][1300/10520] lr: 1.0000e-04 eta: 21:40:50 time: 0.9973 data_time: 0.0230 memory: 56769 loss_visual: 0.0609 loss: 0.0609 2022/09/17 19:54:46 - mmengine - INFO - Epoch(train) [15][1400/10520] lr: 1.0000e-04 eta: 21:38:41 time: 0.8479 data_time: 0.0253 memory: 56769 loss_visual: 0.0628 loss: 0.0628 2022/09/17 19:56:47 - mmengine - INFO - Epoch(train) [15][1500/10520] lr: 1.0000e-04 eta: 21:36:32 time: 0.8702 data_time: 0.0071 memory: 56769 loss_visual: 0.0556 loss: 0.0556 2022/09/17 19:58:47 - mmengine - INFO - Epoch(train) [15][1600/10520] lr: 1.0000e-04 eta: 21:34:24 time: 0.8826 data_time: 0.0081 memory: 56769 loss_visual: 0.0538 loss: 0.0538 2022/09/17 20:00:53 - mmengine - INFO - Epoch(train) [15][1700/10520] lr: 1.0000e-04 eta: 21:32:17 time: 1.4228 data_time: 0.5208 memory: 56769 loss_visual: 0.0618 loss: 0.0618 2022/09/17 20:01:15 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 20:02:55 - mmengine - INFO - Epoch(train) [15][1800/10520] lr: 1.0000e-04 eta: 21:30:09 time: 1.6988 data_time: 0.5765 memory: 56769 loss_visual: 0.0563 loss: 0.0563 2022/09/17 20:04:55 - mmengine - INFO - Epoch(train) [15][1900/10520] lr: 1.0000e-04 eta: 21:28:00 time: 1.5466 data_time: 0.5285 memory: 56769 loss_visual: 0.0589 loss: 0.0589 2022/09/17 20:06:56 - mmengine - INFO - Epoch(train) [15][2000/10520] lr: 1.0000e-04 eta: 21:25:52 time: 1.1255 data_time: 0.1815 memory: 56769 loss_visual: 0.0594 loss: 0.0594 2022/09/17 20:08:57 - mmengine - INFO - Epoch(train) [15][2100/10520] lr: 1.0000e-04 eta: 21:23:44 time: 1.0169 data_time: 0.0377 memory: 56769 loss_visual: 0.0555 loss: 0.0555 2022/09/17 20:10:57 - mmengine - INFO - Epoch(train) [15][2200/10520] lr: 1.0000e-04 eta: 21:21:35 time: 0.8917 data_time: 0.0600 memory: 56769 loss_visual: 0.0609 loss: 0.0609 2022/09/17 20:12:57 - mmengine - INFO - Epoch(train) [15][2300/10520] lr: 1.0000e-04 eta: 21:19:26 time: 0.8419 data_time: 0.0069 memory: 56769 loss_visual: 0.0612 loss: 0.0612 2022/09/17 20:14:57 - mmengine - INFO - Epoch(train) [15][2400/10520] lr: 1.0000e-04 eta: 21:17:17 time: 0.8899 data_time: 0.0069 memory: 56769 loss_visual: 0.0568 loss: 0.0568 2022/09/17 20:17:01 - mmengine - INFO - Epoch(train) [15][2500/10520] lr: 1.0000e-04 eta: 21:15:10 time: 1.4247 data_time: 0.5094 memory: 56769 loss_visual: 0.0613 loss: 0.0613 2022/09/17 20:19:03 - mmengine - INFO - Epoch(train) [15][2600/10520] lr: 1.0000e-04 eta: 21:13:02 time: 1.6574 data_time: 0.6240 memory: 56769 loss_visual: 0.0576 loss: 0.0576 2022/09/17 20:21:05 - mmengine - INFO - Epoch(train) [15][2700/10520] lr: 1.0000e-04 eta: 21:10:54 time: 1.5625 data_time: 0.5114 memory: 56769 loss_visual: 0.0617 loss: 0.0617 2022/09/17 20:21:24 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 20:23:06 - mmengine - INFO - Epoch(train) [15][2800/10520] lr: 1.0000e-04 eta: 21:08:46 time: 1.0838 data_time: 0.1158 memory: 56769 loss_visual: 0.0588 loss: 0.0588 2022/09/17 20:25:06 - mmengine - INFO - Epoch(train) [15][2900/10520] lr: 1.0000e-04 eta: 21:06:37 time: 1.0172 data_time: 0.0370 memory: 56769 loss_visual: 0.0567 loss: 0.0567 2022/09/17 20:27:07 - mmengine - INFO - Epoch(train) [15][3000/10520] lr: 1.0000e-04 eta: 21:04:29 time: 0.9155 data_time: 0.0271 memory: 56769 loss_visual: 0.0591 loss: 0.0591 2022/09/17 20:29:07 - mmengine - INFO - Epoch(train) [15][3100/10520] lr: 1.0000e-04 eta: 21:02:20 time: 0.8462 data_time: 0.0071 memory: 56769 loss_visual: 0.0572 loss: 0.0572 2022/09/17 20:31:07 - mmengine - INFO - Epoch(train) [15][3200/10520] lr: 1.0000e-04 eta: 21:00:12 time: 0.8893 data_time: 0.0078 memory: 56769 loss_visual: 0.0588 loss: 0.0588 2022/09/17 20:33:14 - mmengine - INFO - Epoch(train) [15][3300/10520] lr: 1.0000e-04 eta: 20:58:06 time: 1.4697 data_time: 0.5943 memory: 56769 loss_visual: 0.0586 loss: 0.0586 2022/09/17 20:35:19 - mmengine - INFO - Epoch(train) [15][3400/10520] lr: 1.0000e-04 eta: 20:55:59 time: 1.6890 data_time: 0.6124 memory: 56769 loss_visual: 0.0599 loss: 0.0599 2022/09/17 20:37:21 - mmengine - INFO - Epoch(train) [15][3500/10520] lr: 1.0000e-04 eta: 20:53:51 time: 1.5705 data_time: 0.4842 memory: 56769 loss_visual: 0.0605 loss: 0.0605 2022/09/17 20:39:23 - mmengine - INFO - Epoch(train) [15][3600/10520] lr: 1.0000e-04 eta: 20:51:43 time: 1.1272 data_time: 0.1360 memory: 56769 loss_visual: 0.0597 loss: 0.0597 2022/09/17 20:41:24 - mmengine - INFO - Epoch(train) [15][3700/10520] lr: 1.0000e-04 eta: 20:49:35 time: 1.0275 data_time: 0.0228 memory: 56769 loss_visual: 0.0593 loss: 0.0593 2022/09/17 20:41:50 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 20:43:25 - mmengine - INFO - Epoch(train) [15][3800/10520] lr: 1.0000e-04 eta: 20:47:27 time: 0.8479 data_time: 0.0253 memory: 56769 loss_visual: 0.0561 loss: 0.0561 2022/09/17 20:45:25 - mmengine - INFO - Epoch(train) [15][3900/10520] lr: 1.0000e-04 eta: 20:45:18 time: 0.8528 data_time: 0.0079 memory: 56769 loss_visual: 0.0627 loss: 0.0627 2022/09/17 20:47:26 - mmengine - INFO - Epoch(train) [15][4000/10520] lr: 1.0000e-04 eta: 20:43:10 time: 0.9109 data_time: 0.0078 memory: 56769 loss_visual: 0.0573 loss: 0.0573 2022/09/17 20:49:32 - mmengine - INFO - Epoch(train) [15][4100/10520] lr: 1.0000e-04 eta: 20:41:04 time: 1.4662 data_time: 0.5763 memory: 56769 loss_visual: 0.0598 loss: 0.0598 2022/09/17 20:51:37 - mmengine - INFO - Epoch(train) [15][4200/10520] lr: 1.0000e-04 eta: 20:38:57 time: 1.7551 data_time: 0.6063 memory: 56769 loss_visual: 0.0546 loss: 0.0546 2022/09/17 20:53:39 - mmengine - INFO - Epoch(train) [15][4300/10520] lr: 1.0000e-04 eta: 20:36:49 time: 1.5699 data_time: 0.4416 memory: 56769 loss_visual: 0.0601 loss: 0.0601 2022/09/17 20:55:41 - mmengine - INFO - Epoch(train) [15][4400/10520] lr: 1.0000e-04 eta: 20:34:41 time: 1.1440 data_time: 0.1615 memory: 56769 loss_visual: 0.0557 loss: 0.0557 2022/09/17 20:57:43 - mmengine - INFO - Epoch(train) [15][4500/10520] lr: 1.0000e-04 eta: 20:32:34 time: 0.9927 data_time: 0.0265 memory: 56769 loss_visual: 0.0560 loss: 0.0560 2022/09/17 20:59:46 - mmengine - INFO - Epoch(train) [15][4600/10520] lr: 1.0000e-04 eta: 20:30:26 time: 0.9043 data_time: 0.0408 memory: 56769 loss_visual: 0.0612 loss: 0.0612 2022/09/17 21:01:48 - mmengine - INFO - Epoch(train) [15][4700/10520] lr: 1.0000e-04 eta: 20:28:19 time: 0.8758 data_time: 0.0074 memory: 56769 loss_visual: 0.0581 loss: 0.0581 2022/09/17 21:02:17 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 21:03:50 - mmengine - INFO - Epoch(train) [15][4800/10520] lr: 1.0000e-04 eta: 20:26:11 time: 0.8808 data_time: 0.0076 memory: 56769 loss_visual: 0.0569 loss: 0.0569 2022/09/17 21:05:57 - mmengine - INFO - Epoch(train) [15][4900/10520] lr: 1.0000e-04 eta: 20:24:05 time: 1.4443 data_time: 0.5632 memory: 56769 loss_visual: 0.0557 loss: 0.0557 2022/09/17 21:08:02 - mmengine - INFO - Epoch(train) [15][5000/10520] lr: 1.0000e-04 eta: 20:21:58 time: 1.7470 data_time: 0.6614 memory: 56769 loss_visual: 0.0603 loss: 0.0603 2022/09/17 21:10:06 - mmengine - INFO - Epoch(train) [15][5100/10520] lr: 1.0000e-04 eta: 20:19:51 time: 1.5973 data_time: 0.4588 memory: 56769 loss_visual: 0.0597 loss: 0.0597 2022/09/17 21:12:08 - mmengine - INFO - Epoch(train) [15][5200/10520] lr: 1.0000e-04 eta: 20:17:43 time: 1.1295 data_time: 0.1496 memory: 56769 loss_visual: 0.0587 loss: 0.0587 2022/09/17 21:14:09 - mmengine - INFO - Epoch(train) [15][5300/10520] lr: 1.0000e-04 eta: 20:15:36 time: 1.0120 data_time: 0.0242 memory: 56769 loss_visual: 0.0597 loss: 0.0597 2022/09/17 21:16:10 - mmengine - INFO - Epoch(train) [15][5400/10520] lr: 1.0000e-04 eta: 20:13:27 time: 0.8589 data_time: 0.0321 memory: 56769 loss_visual: 0.0573 loss: 0.0573 2022/09/17 21:18:11 - mmengine - INFO - Epoch(train) [15][5500/10520] lr: 1.0000e-04 eta: 20:11:19 time: 0.9198 data_time: 0.0075 memory: 56769 loss_visual: 0.0559 loss: 0.0559 2022/09/17 21:20:13 - mmengine - INFO - Epoch(train) [15][5600/10520] lr: 1.0000e-04 eta: 20:09:12 time: 0.8773 data_time: 0.0077 memory: 56769 loss_visual: 0.0592 loss: 0.0592 2022/09/17 21:22:21 - mmengine - INFO - Epoch(train) [15][5700/10520] lr: 1.0000e-04 eta: 20:07:06 time: 1.4536 data_time: 0.5839 memory: 56769 loss_visual: 0.0554 loss: 0.0554 2022/09/17 21:22:43 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 21:24:25 - mmengine - INFO - Epoch(train) [15][5800/10520] lr: 1.0000e-04 eta: 20:04:59 time: 1.6990 data_time: 0.6210 memory: 56769 loss_visual: 0.0561 loss: 0.0561 2022/09/17 21:26:27 - mmengine - INFO - Epoch(train) [15][5900/10520] lr: 1.0000e-04 eta: 20:02:52 time: 1.5869 data_time: 0.4232 memory: 56769 loss_visual: 0.0558 loss: 0.0558 2022/09/17 21:28:31 - mmengine - INFO - Epoch(train) [15][6000/10520] lr: 1.0000e-04 eta: 20:00:44 time: 1.0923 data_time: 0.1036 memory: 56769 loss_visual: 0.0599 loss: 0.0599 2022/09/17 21:30:32 - mmengine - INFO - Epoch(train) [15][6100/10520] lr: 1.0000e-04 eta: 19:58:37 time: 0.9761 data_time: 0.0243 memory: 56769 loss_visual: 0.0528 loss: 0.0528 2022/09/17 21:32:32 - mmengine - INFO - Epoch(train) [15][6200/10520] lr: 1.0000e-04 eta: 19:56:28 time: 0.8871 data_time: 0.0244 memory: 56769 loss_visual: 0.0564 loss: 0.0564 2022/09/17 21:34:35 - mmengine - INFO - Epoch(train) [15][6300/10520] lr: 1.0000e-04 eta: 19:54:21 time: 0.8796 data_time: 0.0079 memory: 56769 loss_visual: 0.0568 loss: 0.0568 2022/09/17 21:36:36 - mmengine - INFO - Epoch(train) [15][6400/10520] lr: 1.0000e-04 eta: 19:52:13 time: 0.8903 data_time: 0.0080 memory: 56769 loss_visual: 0.0608 loss: 0.0608 2022/09/17 21:38:44 - mmengine - INFO - Epoch(train) [15][6500/10520] lr: 1.0000e-04 eta: 19:50:07 time: 1.4129 data_time: 0.5644 memory: 56769 loss_visual: 0.0565 loss: 0.0565 2022/09/17 21:40:50 - mmengine - INFO - Epoch(train) [15][6600/10520] lr: 1.0000e-04 eta: 19:48:01 time: 1.6953 data_time: 0.5772 memory: 56769 loss_visual: 0.0533 loss: 0.0533 2022/09/17 21:42:55 - mmengine - INFO - Epoch(train) [15][6700/10520] lr: 1.0000e-04 eta: 19:45:55 time: 1.6787 data_time: 0.4754 memory: 56769 loss_visual: 0.0599 loss: 0.0599 2022/09/17 21:43:15 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 21:44:59 - mmengine - INFO - Epoch(train) [15][6800/10520] lr: 1.0000e-04 eta: 19:43:48 time: 1.1216 data_time: 0.1609 memory: 56769 loss_visual: 0.0574 loss: 0.0574 2022/09/17 21:47:00 - mmengine - INFO - Epoch(train) [15][6900/10520] lr: 1.0000e-04 eta: 19:41:40 time: 0.9900 data_time: 0.0239 memory: 56769 loss_visual: 0.0562 loss: 0.0562 2022/09/17 21:49:04 - mmengine - INFO - Epoch(train) [15][7000/10520] lr: 1.0000e-04 eta: 19:39:33 time: 0.9174 data_time: 0.0647 memory: 56769 loss_visual: 0.0612 loss: 0.0612 2022/09/17 21:51:08 - mmengine - INFO - Epoch(train) [15][7100/10520] lr: 1.0000e-04 eta: 19:37:26 time: 0.9121 data_time: 0.0071 memory: 56769 loss_visual: 0.0537 loss: 0.0537 2022/09/17 21:53:12 - mmengine - INFO - Epoch(train) [15][7200/10520] lr: 1.0000e-04 eta: 19:35:19 time: 0.8757 data_time: 0.0074 memory: 56769 loss_visual: 0.0584 loss: 0.0584 2022/09/17 21:55:20 - mmengine - INFO - Epoch(train) [15][7300/10520] lr: 1.0000e-04 eta: 19:33:13 time: 1.4443 data_time: 0.5049 memory: 56769 loss_visual: 0.0659 loss: 0.0659 2022/09/17 21:57:26 - mmengine - INFO - Epoch(train) [15][7400/10520] lr: 1.0000e-04 eta: 19:31:07 time: 1.6600 data_time: 0.5404 memory: 56769 loss_visual: 0.0589 loss: 0.0589 2022/09/17 21:59:30 - mmengine - INFO - Epoch(train) [15][7500/10520] lr: 1.0000e-04 eta: 19:29:00 time: 1.6197 data_time: 0.5093 memory: 56769 loss_visual: 0.0563 loss: 0.0563 2022/09/17 22:01:33 - mmengine - INFO - Epoch(train) [15][7600/10520] lr: 1.0000e-04 eta: 19:26:53 time: 1.2075 data_time: 0.1981 memory: 56769 loss_visual: 0.0580 loss: 0.0580 2022/09/17 22:03:35 - mmengine - INFO - Epoch(train) [15][7700/10520] lr: 1.0000e-04 eta: 19:24:46 time: 1.0446 data_time: 0.0259 memory: 56769 loss_visual: 0.0560 loss: 0.0560 2022/09/17 22:04:01 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 22:05:38 - mmengine - INFO - Epoch(train) [15][7800/10520] lr: 1.0000e-04 eta: 19:22:38 time: 0.9021 data_time: 0.0260 memory: 56769 loss_visual: 0.0531 loss: 0.0531 2022/09/17 22:07:41 - mmengine - INFO - Epoch(train) [15][7900/10520] lr: 1.0000e-04 eta: 19:20:31 time: 0.8718 data_time: 0.0091 memory: 56769 loss_visual: 0.0613 loss: 0.0613 2022/09/17 22:09:45 - mmengine - INFO - Epoch(train) [15][8000/10520] lr: 1.0000e-04 eta: 19:18:24 time: 0.9212 data_time: 0.0077 memory: 56769 loss_visual: 0.0580 loss: 0.0580 2022/09/17 22:11:51 - mmengine - INFO - Epoch(train) [15][8100/10520] lr: 1.0000e-04 eta: 19:16:18 time: 1.3977 data_time: 0.4948 memory: 56769 loss_visual: 0.0573 loss: 0.0573 2022/09/17 22:13:55 - mmengine - INFO - Epoch(train) [15][8200/10520] lr: 1.0000e-04 eta: 19:14:11 time: 1.6361 data_time: 0.5694 memory: 56769 loss_visual: 0.0596 loss: 0.0596 2022/09/17 22:15:58 - mmengine - INFO - Epoch(train) [15][8300/10520] lr: 1.0000e-04 eta: 19:12:04 time: 1.6188 data_time: 0.4928 memory: 56769 loss_visual: 0.0564 loss: 0.0564 2022/09/17 22:18:02 - mmengine - INFO - Epoch(train) [15][8400/10520] lr: 1.0000e-04 eta: 19:09:57 time: 1.1758 data_time: 0.1782 memory: 56769 loss_visual: 0.0565 loss: 0.0565 2022/09/17 22:20:04 - mmengine - INFO - Epoch(train) [15][8500/10520] lr: 1.0000e-04 eta: 19:07:50 time: 1.0290 data_time: 0.0243 memory: 56769 loss_visual: 0.0537 loss: 0.0537 2022/09/17 22:22:06 - mmengine - INFO - Epoch(train) [15][8600/10520] lr: 1.0000e-04 eta: 19:05:42 time: 0.8807 data_time: 0.0246 memory: 56769 loss_visual: 0.0570 loss: 0.0570 2022/09/17 22:24:08 - mmengine - INFO - Epoch(train) [15][8700/10520] lr: 1.0000e-04 eta: 19:03:35 time: 0.8860 data_time: 0.0073 memory: 56769 loss_visual: 0.0579 loss: 0.0579 2022/09/17 22:24:37 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 22:26:10 - mmengine - INFO - Epoch(train) [15][8800/10520] lr: 1.0000e-04 eta: 19:01:27 time: 0.8868 data_time: 0.0080 memory: 56769 loss_visual: 0.0578 loss: 0.0578 2022/09/17 22:28:17 - mmengine - INFO - Epoch(train) [15][8900/10520] lr: 1.0000e-04 eta: 18:59:21 time: 1.4074 data_time: 0.4869 memory: 56769 loss_visual: 0.0560 loss: 0.0560 2022/09/17 22:30:22 - mmengine - INFO - Epoch(train) [15][9000/10520] lr: 1.0000e-04 eta: 18:57:15 time: 1.7091 data_time: 0.5583 memory: 56769 loss_visual: 0.0598 loss: 0.0598 2022/09/17 22:32:26 - mmengine - INFO - Epoch(train) [15][9100/10520] lr: 1.0000e-04 eta: 18:55:08 time: 1.6664 data_time: 0.4922 memory: 56769 loss_visual: 0.0566 loss: 0.0566 2022/09/17 22:34:30 - mmengine - INFO - Epoch(train) [15][9200/10520] lr: 1.0000e-04 eta: 18:53:01 time: 1.1804 data_time: 0.1733 memory: 56769 loss_visual: 0.0591 loss: 0.0591 2022/09/17 22:36:34 - mmengine - INFO - Epoch(train) [15][9300/10520] lr: 1.0000e-04 eta: 18:50:54 time: 1.0234 data_time: 0.0248 memory: 56769 loss_visual: 0.0572 loss: 0.0572 2022/09/17 22:38:37 - mmengine - INFO - Epoch(train) [15][9400/10520] lr: 1.0000e-04 eta: 18:48:47 time: 0.9086 data_time: 0.0239 memory: 56769 loss_visual: 0.0609 loss: 0.0609 2022/09/17 22:40:39 - mmengine - INFO - Epoch(train) [15][9500/10520] lr: 1.0000e-04 eta: 18:46:40 time: 0.8666 data_time: 0.0076 memory: 56769 loss_visual: 0.0648 loss: 0.0648 2022/09/17 22:42:40 - mmengine - INFO - Epoch(train) [15][9600/10520] lr: 1.0000e-04 eta: 18:44:32 time: 0.9006 data_time: 0.0070 memory: 56769 loss_visual: 0.0538 loss: 0.0538 2022/09/17 22:44:49 - mmengine - INFO - Epoch(train) [15][9700/10520] lr: 1.0000e-04 eta: 18:42:27 time: 1.4108 data_time: 0.4866 memory: 56769 loss_visual: 0.0546 loss: 0.0546 2022/09/17 22:45:12 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 22:46:53 - mmengine - INFO - Epoch(train) [15][9800/10520] lr: 1.0000e-04 eta: 18:40:20 time: 1.6423 data_time: 0.5501 memory: 56769 loss_visual: 0.0604 loss: 0.0604 2022/09/17 22:48:57 - mmengine - INFO - Epoch(train) [15][9900/10520] lr: 1.0000e-04 eta: 18:38:13 time: 1.6138 data_time: 0.4789 memory: 56769 loss_visual: 0.0568 loss: 0.0568 2022/09/17 22:51:01 - mmengine - INFO - Epoch(train) [15][10000/10520] lr: 1.0000e-04 eta: 18:36:06 time: 1.2086 data_time: 0.1911 memory: 56769 loss_visual: 0.0588 loss: 0.0588 2022/09/17 22:53:03 - mmengine - INFO - Epoch(train) [15][10100/10520] lr: 1.0000e-04 eta: 18:33:59 time: 1.0334 data_time: 0.0238 memory: 56769 loss_visual: 0.0547 loss: 0.0547 2022/09/17 22:55:05 - mmengine - INFO - Epoch(train) [15][10200/10520] lr: 1.0000e-04 eta: 18:31:51 time: 0.9092 data_time: 0.0236 memory: 56769 loss_visual: 0.0566 loss: 0.0566 2022/09/17 22:57:07 - mmengine - INFO - Epoch(train) [15][10300/10520] lr: 1.0000e-04 eta: 18:29:44 time: 0.9236 data_time: 0.0072 memory: 56769 loss_visual: 0.0564 loss: 0.0564 2022/09/17 22:59:10 - mmengine - INFO - Epoch(train) [15][10400/10520] lr: 1.0000e-04 eta: 18:27:37 time: 0.8983 data_time: 0.0073 memory: 56769 loss_visual: 0.0537 loss: 0.0537 2022/09/17 23:01:13 - mmengine - INFO - Epoch(train) [15][10500/10520] lr: 1.0000e-04 eta: 18:25:30 time: 1.1782 data_time: 0.3056 memory: 56769 loss_visual: 0.0589 loss: 0.0589 2022/09/17 23:01:32 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 23:01:32 - mmengine - INFO - Saving checkpoint at 15 epochs 2022/09/17 23:01:48 - mmengine - INFO - Epoch(val) [15][100/3836] eta: 0:04:34 time: 0.0735 data_time: 0.0006 memory: 56769 2022/09/17 23:01:51 - mmengine - INFO - Epoch(val) [15][200/3836] eta: 0:00:42 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 23:01:52 - mmengine - INFO - Epoch(val) [15][300/3836] eta: 0:00:41 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 23:01:54 - mmengine - INFO - Epoch(val) [15][400/3836] eta: 0:00:39 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 23:01:55 - mmengine - INFO - Epoch(val) [15][500/3836] eta: 0:00:45 time: 0.0135 data_time: 0.0005 memory: 480 2022/09/17 23:01:56 - mmengine - INFO - Epoch(val) [15][600/3836] eta: 0:00:37 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 23:01:57 - mmengine - INFO - Epoch(val) [15][700/3836] eta: 0:00:35 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/17 23:01:58 - mmengine - INFO - Epoch(val) [15][800/3836] eta: 0:00:34 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 23:02:00 - mmengine - INFO - Epoch(val) [15][900/3836] eta: 0:00:33 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 23:02:01 - mmengine - INFO - Epoch(val) [15][1000/3836] eta: 0:00:34 time: 0.0121 data_time: 0.0005 memory: 480 2022/09/17 23:02:02 - mmengine - INFO - Epoch(val) [15][1100/3836] eta: 0:00:32 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 23:02:03 - mmengine - INFO - Epoch(val) [15][1200/3836] eta: 0:00:31 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 23:02:05 - mmengine - INFO - Epoch(val) [15][1300/3836] eta: 0:00:29 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 23:02:06 - mmengine - INFO - Epoch(val) [15][1400/3836] eta: 0:00:27 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 23:02:07 - mmengine - INFO - Epoch(val) [15][1500/3836] eta: 0:00:27 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/17 23:02:08 - mmengine - INFO - Epoch(val) [15][1600/3836] eta: 0:00:26 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 23:02:09 - mmengine - INFO - Epoch(val) [15][1700/3836] eta: 0:00:25 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 23:02:11 - mmengine - INFO - Epoch(val) [15][1800/3836] eta: 0:00:23 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 23:02:12 - mmengine - INFO - Epoch(val) [15][1900/3836] eta: 0:00:22 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 23:02:13 - mmengine - INFO - Epoch(val) [15][2000/3836] eta: 0:00:21 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/17 23:02:14 - mmengine - INFO - Epoch(val) [15][2100/3836] eta: 0:00:21 time: 0.0122 data_time: 0.0013 memory: 480 2022/09/17 23:02:15 - mmengine - INFO - Epoch(val) [15][2200/3836] eta: 0:00:19 time: 0.0119 data_time: 0.0006 memory: 480 2022/09/17 23:02:17 - mmengine - INFO - Epoch(val) [15][2300/3836] eta: 0:00:18 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 23:02:18 - mmengine - INFO - Epoch(val) [15][2400/3836] eta: 0:00:17 time: 0.0122 data_time: 0.0005 memory: 480 2022/09/17 23:02:19 - mmengine - INFO - Epoch(val) [15][2500/3836] eta: 0:00:15 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 23:02:20 - mmengine - INFO - Epoch(val) [15][2600/3836] eta: 0:00:14 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 23:02:22 - mmengine - INFO - Epoch(val) [15][2700/3836] eta: 0:00:12 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/17 23:02:23 - mmengine - INFO - Epoch(val) [15][2800/3836] eta: 0:00:12 time: 0.0117 data_time: 0.0004 memory: 480 2022/09/17 23:02:24 - mmengine - INFO - Epoch(val) [15][2900/3836] eta: 0:00:10 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/17 23:02:25 - mmengine - INFO - Epoch(val) [15][3000/3836] eta: 0:00:09 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 23:02:26 - mmengine - INFO - Epoch(val) [15][3100/3836] eta: 0:00:08 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/17 23:02:27 - mmengine - INFO - Epoch(val) [15][3200/3836] eta: 0:00:07 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 23:02:29 - mmengine - INFO - Epoch(val) [15][3300/3836] eta: 0:00:05 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/17 23:02:30 - mmengine - INFO - Epoch(val) [15][3400/3836] eta: 0:00:04 time: 0.0108 data_time: 0.0004 memory: 480 2022/09/17 23:02:31 - mmengine - INFO - Epoch(val) [15][3500/3836] eta: 0:00:03 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/17 23:02:32 - mmengine - INFO - Epoch(val) [15][3600/3836] eta: 0:00:02 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/17 23:02:33 - mmengine - INFO - Epoch(val) [15][3700/3836] eta: 0:00:01 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/17 23:02:34 - mmengine - INFO - Epoch(val) [15][3800/3836] eta: 0:00:00 time: 0.0110 data_time: 0.0005 memory: 480 2022/09/17 23:02:35 - mmengine - INFO - Epoch(val) [15][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.8333 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9443 SVT/recog/word_acc_ignore_case_symbol: 0.8995 SVTP/recog/word_acc_ignore_case_symbol: 0.8264 IC13/recog/word_acc_ignore_case_symbol: 0.9202 IC15/recog/word_acc_ignore_case_symbol: 0.7737 2022/09/17 23:04:56 - mmengine - INFO - Epoch(train) [16][100/10520] lr: 1.0000e-04 eta: 18:23:01 time: 1.3268 data_time: 0.3034 memory: 56769 loss_visual: 0.0563 loss: 0.0563 2022/09/17 23:07:09 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 23:07:09 - mmengine - INFO - Epoch(train) [16][200/10520] lr: 1.0000e-04 eta: 18:20:57 time: 1.9143 data_time: 0.7028 memory: 56769 loss_visual: 0.0576 loss: 0.0576 2022/09/17 23:09:17 - mmengine - INFO - Epoch(train) [16][300/10520] lr: 1.0000e-04 eta: 18:18:52 time: 1.7860 data_time: 0.6080 memory: 56769 loss_visual: 0.0568 loss: 0.0568 2022/09/17 23:11:22 - mmengine - INFO - Epoch(train) [16][400/10520] lr: 1.0000e-04 eta: 18:16:46 time: 1.5181 data_time: 0.3251 memory: 56769 loss_visual: 0.0539 loss: 0.0539 2022/09/17 23:13:27 - mmengine - INFO - Epoch(train) [16][500/10520] lr: 1.0000e-04 eta: 18:14:39 time: 0.9176 data_time: 0.0387 memory: 56769 loss_visual: 0.0592 loss: 0.0592 2022/09/17 23:15:34 - mmengine - INFO - Epoch(train) [16][600/10520] lr: 1.0000e-04 eta: 18:12:34 time: 0.9122 data_time: 0.0074 memory: 56769 loss_visual: 0.0596 loss: 0.0596 2022/09/17 23:17:42 - mmengine - INFO - Epoch(train) [16][700/10520] lr: 1.0000e-04 eta: 18:10:28 time: 0.9145 data_time: 0.0086 memory: 56769 loss_visual: 0.0578 loss: 0.0578 2022/09/17 23:19:48 - mmengine - INFO - Epoch(train) [16][800/10520] lr: 1.0000e-04 eta: 18:08:22 time: 0.8664 data_time: 0.0076 memory: 56769 loss_visual: 0.0565 loss: 0.0565 2022/09/17 23:21:59 - mmengine - INFO - Epoch(train) [16][900/10520] lr: 1.0000e-04 eta: 18:06:17 time: 1.3207 data_time: 0.2985 memory: 56769 loss_visual: 0.0579 loss: 0.0579 2022/09/17 23:24:10 - mmengine - INFO - Epoch(train) [16][1000/10520] lr: 1.0000e-04 eta: 18:04:13 time: 1.9323 data_time: 0.6891 memory: 56769 loss_visual: 0.0581 loss: 0.0581 2022/09/17 23:26:19 - mmengine - INFO - Epoch(train) [16][1100/10520] lr: 1.0000e-04 eta: 18:02:08 time: 1.7973 data_time: 0.5889 memory: 56769 loss_visual: 0.0614 loss: 0.0614 2022/09/17 23:28:27 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 23:28:27 - mmengine - INFO - Epoch(train) [16][1200/10520] lr: 1.0000e-04 eta: 18:00:02 time: 1.5076 data_time: 0.3093 memory: 56769 loss_visual: 0.0589 loss: 0.0589 2022/09/17 23:30:34 - mmengine - INFO - Epoch(train) [16][1300/10520] lr: 1.0000e-04 eta: 17:57:57 time: 0.9681 data_time: 0.0408 memory: 56769 loss_visual: 0.0574 loss: 0.0574 2022/09/17 23:32:41 - mmengine - INFO - Epoch(train) [16][1400/10520] lr: 1.0000e-04 eta: 17:55:51 time: 0.9373 data_time: 0.0070 memory: 56769 loss_visual: 0.0569 loss: 0.0569 2022/09/17 23:34:47 - mmengine - INFO - Epoch(train) [16][1500/10520] lr: 1.0000e-04 eta: 17:53:45 time: 0.9713 data_time: 0.0093 memory: 56769 loss_visual: 0.0563 loss: 0.0563 2022/09/17 23:36:52 - mmengine - INFO - Epoch(train) [16][1600/10520] lr: 1.0000e-04 eta: 17:51:38 time: 0.9061 data_time: 0.0073 memory: 56769 loss_visual: 0.0565 loss: 0.0565 2022/09/17 23:39:03 - mmengine - INFO - Epoch(train) [16][1700/10520] lr: 1.0000e-04 eta: 17:49:34 time: 1.3056 data_time: 0.2881 memory: 56769 loss_visual: 0.0565 loss: 0.0565 2022/09/17 23:41:14 - mmengine - INFO - Epoch(train) [16][1800/10520] lr: 1.0000e-04 eta: 17:47:29 time: 1.8975 data_time: 0.7051 memory: 56769 loss_visual: 0.0573 loss: 0.0573 2022/09/17 23:43:23 - mmengine - INFO - Epoch(train) [16][1900/10520] lr: 1.0000e-04 eta: 17:45:24 time: 1.8074 data_time: 0.6312 memory: 56769 loss_visual: 0.0561 loss: 0.0561 2022/09/17 23:45:30 - mmengine - INFO - Epoch(train) [16][2000/10520] lr: 1.0000e-04 eta: 17:43:18 time: 1.4872 data_time: 0.3125 memory: 56769 loss_visual: 0.0594 loss: 0.0594 2022/09/17 23:47:37 - mmengine - INFO - Epoch(train) [16][2100/10520] lr: 1.0000e-04 eta: 17:41:12 time: 0.9238 data_time: 0.0404 memory: 56769 loss_visual: 0.0564 loss: 0.0564 2022/09/17 23:49:43 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/17 23:49:43 - mmengine - INFO - Epoch(train) [16][2200/10520] lr: 1.0000e-04 eta: 17:39:06 time: 0.9454 data_time: 0.0071 memory: 56769 loss_visual: 0.0598 loss: 0.0598 2022/09/17 23:51:50 - mmengine - INFO - Epoch(train) [16][2300/10520] lr: 1.0000e-04 eta: 17:37:00 time: 0.9251 data_time: 0.0079 memory: 56769 loss_visual: 0.0562 loss: 0.0562 2022/09/17 23:53:55 - mmengine - INFO - Epoch(train) [16][2400/10520] lr: 1.0000e-04 eta: 17:34:54 time: 0.8742 data_time: 0.0073 memory: 56769 loss_visual: 0.0554 loss: 0.0554 2022/09/17 23:56:07 - mmengine - INFO - Epoch(train) [16][2500/10520] lr: 1.0000e-04 eta: 17:32:50 time: 1.3429 data_time: 0.3138 memory: 56769 loss_visual: 0.0570 loss: 0.0570 2022/09/17 23:58:19 - mmengine - INFO - Epoch(train) [16][2600/10520] lr: 1.0000e-04 eta: 17:30:46 time: 1.8931 data_time: 0.6559 memory: 56769 loss_visual: 0.0561 loss: 0.0561 2022/09/18 00:00:31 - mmengine - INFO - Epoch(train) [16][2700/10520] lr: 1.0000e-04 eta: 17:28:41 time: 1.7724 data_time: 0.5745 memory: 56769 loss_visual: 0.0531 loss: 0.0531 2022/09/18 00:02:36 - mmengine - INFO - Epoch(train) [16][2800/10520] lr: 1.0000e-04 eta: 17:26:35 time: 1.5033 data_time: 0.3254 memory: 56769 loss_visual: 0.0554 loss: 0.0554 2022/09/18 00:04:42 - mmengine - INFO - Epoch(train) [16][2900/10520] lr: 1.0000e-04 eta: 17:24:29 time: 0.9370 data_time: 0.0374 memory: 56769 loss_visual: 0.0564 loss: 0.0564 2022/09/18 00:06:48 - mmengine - INFO - Epoch(train) [16][3000/10520] lr: 1.0000e-04 eta: 17:22:23 time: 0.9803 data_time: 0.0068 memory: 56769 loss_visual: 0.0550 loss: 0.0550 2022/09/18 00:08:55 - mmengine - INFO - Epoch(train) [16][3100/10520] lr: 1.0000e-04 eta: 17:20:17 time: 0.9563 data_time: 0.0077 memory: 56769 loss_visual: 0.0566 loss: 0.0566 2022/09/18 00:11:00 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 00:11:00 - mmengine - INFO - Epoch(train) [16][3200/10520] lr: 1.0000e-04 eta: 17:18:10 time: 0.8922 data_time: 0.0072 memory: 56769 loss_visual: 0.0549 loss: 0.0549 2022/09/18 00:13:11 - mmengine - INFO - Epoch(train) [16][3300/10520] lr: 1.0000e-04 eta: 17:16:06 time: 1.3322 data_time: 0.2937 memory: 56769 loss_visual: 0.0532 loss: 0.0532 2022/09/18 00:15:22 - mmengine - INFO - Epoch(train) [16][3400/10520] lr: 1.0000e-04 eta: 17:14:01 time: 1.8963 data_time: 0.6889 memory: 56769 loss_visual: 0.0582 loss: 0.0582 2022/09/18 00:17:30 - mmengine - INFO - Epoch(train) [16][3500/10520] lr: 1.0000e-04 eta: 17:11:55 time: 1.7543 data_time: 0.6010 memory: 56769 loss_visual: 0.0556 loss: 0.0556 2022/09/18 00:19:37 - mmengine - INFO - Epoch(train) [16][3600/10520] lr: 1.0000e-04 eta: 17:09:50 time: 1.5255 data_time: 0.3320 memory: 56769 loss_visual: 0.0593 loss: 0.0593 2022/09/18 00:21:44 - mmengine - INFO - Epoch(train) [16][3700/10520] lr: 1.0000e-04 eta: 17:07:44 time: 0.9191 data_time: 0.0443 memory: 56769 loss_visual: 0.0554 loss: 0.0554 2022/09/18 00:23:53 - mmengine - INFO - Epoch(train) [16][3800/10520] lr: 1.0000e-04 eta: 17:05:38 time: 0.9512 data_time: 0.0074 memory: 56769 loss_visual: 0.0577 loss: 0.0577 2022/09/18 00:25:58 - mmengine - INFO - Epoch(train) [16][3900/10520] lr: 1.0000e-04 eta: 17:03:32 time: 0.9994 data_time: 0.0132 memory: 56769 loss_visual: 0.0581 loss: 0.0581 2022/09/18 00:28:03 - mmengine - INFO - Epoch(train) [16][4000/10520] lr: 1.0000e-04 eta: 17:01:26 time: 0.8905 data_time: 0.0068 memory: 56769 loss_visual: 0.0605 loss: 0.0605 2022/09/18 00:30:13 - mmengine - INFO - Epoch(train) [16][4100/10520] lr: 1.0000e-04 eta: 16:59:21 time: 1.3182 data_time: 0.3038 memory: 56769 loss_visual: 0.0612 loss: 0.0612 2022/09/18 00:32:26 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 00:32:26 - mmengine - INFO - Epoch(train) [16][4200/10520] lr: 1.0000e-04 eta: 16:57:16 time: 1.9586 data_time: 0.7396 memory: 56769 loss_visual: 0.0552 loss: 0.0552 2022/09/18 00:34:34 - mmengine - INFO - Epoch(train) [16][4300/10520] lr: 1.0000e-04 eta: 16:55:11 time: 1.8168 data_time: 0.6845 memory: 56769 loss_visual: 0.0571 loss: 0.0571 2022/09/18 00:36:39 - mmengine - INFO - Epoch(train) [16][4400/10520] lr: 1.0000e-04 eta: 16:53:04 time: 1.5355 data_time: 0.3446 memory: 56769 loss_visual: 0.0582 loss: 0.0582 2022/09/18 00:38:44 - mmengine - INFO - Epoch(train) [16][4500/10520] lr: 1.0000e-04 eta: 16:50:58 time: 0.9405 data_time: 0.0545 memory: 56769 loss_visual: 0.0586 loss: 0.0586 2022/09/18 00:40:50 - mmengine - INFO - Epoch(train) [16][4600/10520] lr: 1.0000e-04 eta: 16:48:52 time: 0.9411 data_time: 0.0068 memory: 56769 loss_visual: 0.0582 loss: 0.0582 2022/09/18 00:42:58 - mmengine - INFO - Epoch(train) [16][4700/10520] lr: 1.0000e-04 eta: 16:46:46 time: 0.9183 data_time: 0.0075 memory: 56769 loss_visual: 0.0581 loss: 0.0581 2022/09/18 00:45:05 - mmengine - INFO - Epoch(train) [16][4800/10520] lr: 1.0000e-04 eta: 16:44:41 time: 0.8633 data_time: 0.0073 memory: 56769 loss_visual: 0.0580 loss: 0.0580 2022/09/18 00:47:18 - mmengine - INFO - Epoch(train) [16][4900/10520] lr: 1.0000e-04 eta: 16:42:36 time: 1.3425 data_time: 0.2970 memory: 56769 loss_visual: 0.0549 loss: 0.0549 2022/09/18 00:49:31 - mmengine - INFO - Epoch(train) [16][5000/10520] lr: 1.0000e-04 eta: 16:40:32 time: 1.9380 data_time: 0.6786 memory: 56769 loss_visual: 0.0587 loss: 0.0587 2022/09/18 00:51:39 - mmengine - INFO - Epoch(train) [16][5100/10520] lr: 1.0000e-04 eta: 16:38:27 time: 1.7815 data_time: 0.6117 memory: 56769 loss_visual: 0.0585 loss: 0.0585 2022/09/18 00:53:45 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 00:53:45 - mmengine - INFO - Epoch(train) [16][5200/10520] lr: 1.0000e-04 eta: 16:36:21 time: 1.5415 data_time: 0.3317 memory: 56769 loss_visual: 0.0526 loss: 0.0526 2022/09/18 00:55:52 - mmengine - INFO - Epoch(train) [16][5300/10520] lr: 1.0000e-04 eta: 16:34:15 time: 0.9621 data_time: 0.0748 memory: 56769 loss_visual: 0.0544 loss: 0.0544 2022/09/18 00:57:59 - mmengine - INFO - Epoch(train) [16][5400/10520] lr: 1.0000e-04 eta: 16:32:09 time: 0.9532 data_time: 0.0071 memory: 56769 loss_visual: 0.0571 loss: 0.0571 2022/09/18 01:00:06 - mmengine - INFO - Epoch(train) [16][5500/10520] lr: 1.0000e-04 eta: 16:30:03 time: 0.9665 data_time: 0.0068 memory: 56769 loss_visual: 0.0579 loss: 0.0579 2022/09/18 01:02:11 - mmengine - INFO - Epoch(train) [16][5600/10520] lr: 1.0000e-04 eta: 16:27:56 time: 0.8504 data_time: 0.0074 memory: 56769 loss_visual: 0.0560 loss: 0.0560 2022/09/18 01:04:23 - mmengine - INFO - Epoch(train) [16][5700/10520] lr: 1.0000e-04 eta: 16:25:52 time: 1.3289 data_time: 0.3196 memory: 56769 loss_visual: 0.0558 loss: 0.0558 2022/09/18 01:06:35 - mmengine - INFO - Epoch(train) [16][5800/10520] lr: 1.0000e-04 eta: 16:23:47 time: 1.9501 data_time: 0.6975 memory: 56769 loss_visual: 0.0538 loss: 0.0538 2022/09/18 01:08:45 - mmengine - INFO - Epoch(train) [16][5900/10520] lr: 1.0000e-04 eta: 16:21:42 time: 1.7907 data_time: 0.6313 memory: 56769 loss_visual: 0.0579 loss: 0.0579 2022/09/18 01:10:52 - mmengine - INFO - Epoch(train) [16][6000/10520] lr: 1.0000e-04 eta: 16:19:36 time: 1.5265 data_time: 0.3551 memory: 56769 loss_visual: 0.0546 loss: 0.0546 2022/09/18 01:13:00 - mmengine - INFO - Epoch(train) [16][6100/10520] lr: 1.0000e-04 eta: 16:17:31 time: 1.0012 data_time: 0.0780 memory: 56769 loss_visual: 0.0603 loss: 0.0603 2022/09/18 01:15:06 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 01:15:06 - mmengine - INFO - Epoch(train) [16][6200/10520] lr: 1.0000e-04 eta: 16:15:25 time: 0.9157 data_time: 0.0069 memory: 56769 loss_visual: 0.0548 loss: 0.0548 2022/09/18 01:17:14 - mmengine - INFO - Epoch(train) [16][6300/10520] lr: 1.0000e-04 eta: 16:13:19 time: 0.9388 data_time: 0.0131 memory: 56769 loss_visual: 0.0587 loss: 0.0587 2022/09/18 01:19:20 - mmengine - INFO - Epoch(train) [16][6400/10520] lr: 1.0000e-04 eta: 16:11:13 time: 0.8797 data_time: 0.0078 memory: 56769 loss_visual: 0.0528 loss: 0.0528 2022/09/18 01:21:31 - mmengine - INFO - Epoch(train) [16][6500/10520] lr: 1.0000e-04 eta: 16:09:08 time: 1.3000 data_time: 0.2992 memory: 56769 loss_visual: 0.0564 loss: 0.0564 2022/09/18 01:23:44 - mmengine - INFO - Epoch(train) [16][6600/10520] lr: 1.0000e-04 eta: 16:07:04 time: 1.9228 data_time: 0.7015 memory: 56769 loss_visual: 0.0522 loss: 0.0522 2022/09/18 01:25:53 - mmengine - INFO - Epoch(train) [16][6700/10520] lr: 1.0000e-04 eta: 16:04:59 time: 1.7670 data_time: 0.6091 memory: 56769 loss_visual: 0.0566 loss: 0.0566 2022/09/18 01:28:01 - mmengine - INFO - Epoch(train) [16][6800/10520] lr: 1.0000e-04 eta: 16:02:53 time: 1.5300 data_time: 0.3245 memory: 56769 loss_visual: 0.0574 loss: 0.0574 2022/09/18 01:30:08 - mmengine - INFO - Epoch(train) [16][6900/10520] lr: 1.0000e-04 eta: 16:00:47 time: 0.9563 data_time: 0.0779 memory: 56769 loss_visual: 0.0616 loss: 0.0616 2022/09/18 01:32:13 - mmengine - INFO - Epoch(train) [16][7000/10520] lr: 1.0000e-04 eta: 15:58:40 time: 0.9454 data_time: 0.0067 memory: 56769 loss_visual: 0.0561 loss: 0.0561 2022/09/18 01:34:21 - mmengine - INFO - Epoch(train) [16][7100/10520] lr: 1.0000e-04 eta: 15:56:35 time: 0.9439 data_time: 0.0072 memory: 56769 loss_visual: 0.0563 loss: 0.0563 2022/09/18 01:36:27 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 01:36:27 - mmengine - INFO - Epoch(train) [16][7200/10520] lr: 1.0000e-04 eta: 15:54:29 time: 0.8594 data_time: 0.0074 memory: 56769 loss_visual: 0.0541 loss: 0.0541 2022/09/18 01:38:38 - mmengine - INFO - Epoch(train) [16][7300/10520] lr: 1.0000e-04 eta: 15:52:24 time: 1.3240 data_time: 0.2689 memory: 56769 loss_visual: 0.0586 loss: 0.0586 2022/09/18 01:40:50 - mmengine - INFO - Epoch(train) [16][7400/10520] lr: 1.0000e-04 eta: 15:50:19 time: 1.9517 data_time: 0.6256 memory: 56769 loss_visual: 0.0552 loss: 0.0552 2022/09/18 01:42:58 - mmengine - INFO - Epoch(train) [16][7500/10520] lr: 1.0000e-04 eta: 15:48:14 time: 1.7513 data_time: 0.5776 memory: 56769 loss_visual: 0.0552 loss: 0.0552 2022/09/18 01:45:06 - mmengine - INFO - Epoch(train) [16][7600/10520] lr: 1.0000e-04 eta: 15:46:08 time: 1.5323 data_time: 0.3485 memory: 56769 loss_visual: 0.0592 loss: 0.0592 2022/09/18 01:47:12 - mmengine - INFO - Epoch(train) [16][7700/10520] lr: 1.0000e-04 eta: 15:44:02 time: 0.9746 data_time: 0.0765 memory: 56769 loss_visual: 0.0547 loss: 0.0547 2022/09/18 01:49:20 - mmengine - INFO - Epoch(train) [16][7800/10520] lr: 1.0000e-04 eta: 15:41:56 time: 1.0000 data_time: 0.0070 memory: 56769 loss_visual: 0.0582 loss: 0.0582 2022/09/18 01:51:28 - mmengine - INFO - Epoch(train) [16][7900/10520] lr: 1.0000e-04 eta: 15:39:50 time: 0.9577 data_time: 0.0077 memory: 56769 loss_visual: 0.0546 loss: 0.0546 2022/09/18 01:53:37 - mmengine - INFO - Epoch(train) [16][8000/10520] lr: 1.0000e-04 eta: 15:37:45 time: 0.8631 data_time: 0.0077 memory: 56769 loss_visual: 0.0571 loss: 0.0571 2022/09/18 01:55:52 - mmengine - INFO - Epoch(train) [16][8100/10520] lr: 1.0000e-04 eta: 15:35:41 time: 1.4441 data_time: 0.2774 memory: 56769 loss_visual: 0.0557 loss: 0.0557 2022/09/18 01:58:04 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 01:58:04 - mmengine - INFO - Epoch(train) [16][8200/10520] lr: 1.0000e-04 eta: 15:33:37 time: 1.9714 data_time: 0.6727 memory: 56769 loss_visual: 0.0551 loss: 0.0551 2022/09/18 02:00:14 - mmengine - INFO - Epoch(train) [16][8300/10520] lr: 1.0000e-04 eta: 15:31:31 time: 1.8752 data_time: 0.6119 memory: 56769 loss_visual: 0.0540 loss: 0.0540 2022/09/18 02:02:23 - mmengine - INFO - Epoch(train) [16][8400/10520] lr: 1.0000e-04 eta: 15:29:26 time: 1.5896 data_time: 0.3655 memory: 56769 loss_visual: 0.0560 loss: 0.0560 2022/09/18 02:04:31 - mmengine - INFO - Epoch(train) [16][8500/10520] lr: 1.0000e-04 eta: 15:27:20 time: 0.9576 data_time: 0.0533 memory: 56769 loss_visual: 0.0552 loss: 0.0552 2022/09/18 02:06:38 - mmengine - INFO - Epoch(train) [16][8600/10520] lr: 1.0000e-04 eta: 15:25:14 time: 0.9265 data_time: 0.0070 memory: 56769 loss_visual: 0.0578 loss: 0.0578 2022/09/18 02:08:44 - mmengine - INFO - Epoch(train) [16][8700/10520] lr: 1.0000e-04 eta: 15:23:08 time: 0.9460 data_time: 0.0070 memory: 56769 loss_visual: 0.0551 loss: 0.0551 2022/09/18 02:10:50 - mmengine - INFO - Epoch(train) [16][8800/10520] lr: 1.0000e-04 eta: 15:21:02 time: 0.8640 data_time: 0.0071 memory: 56769 loss_visual: 0.0549 loss: 0.0549 2022/09/18 02:13:01 - mmengine - INFO - Epoch(train) [16][8900/10520] lr: 1.0000e-04 eta: 15:18:57 time: 1.3262 data_time: 0.2391 memory: 56769 loss_visual: 0.0565 loss: 0.0565 2022/09/18 02:15:14 - mmengine - INFO - Epoch(train) [16][9000/10520] lr: 1.0000e-04 eta: 15:16:53 time: 1.9216 data_time: 0.6928 memory: 56769 loss_visual: 0.0533 loss: 0.0533 2022/09/18 02:17:23 - mmengine - INFO - Epoch(train) [16][9100/10520] lr: 1.0000e-04 eta: 15:14:47 time: 1.7670 data_time: 0.5762 memory: 56769 loss_visual: 0.0559 loss: 0.0559 2022/09/18 02:19:31 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 02:19:31 - mmengine - INFO - Epoch(train) [16][9200/10520] lr: 1.0000e-04 eta: 15:12:41 time: 1.5452 data_time: 0.3408 memory: 56769 loss_visual: 0.0558 loss: 0.0558 2022/09/18 02:21:39 - mmengine - INFO - Epoch(train) [16][9300/10520] lr: 1.0000e-04 eta: 15:10:36 time: 0.9673 data_time: 0.0763 memory: 56769 loss_visual: 0.0579 loss: 0.0579 2022/09/18 02:23:46 - mmengine - INFO - Epoch(train) [16][9400/10520] lr: 1.0000e-04 eta: 15:08:30 time: 0.9540 data_time: 0.0069 memory: 56769 loss_visual: 0.0558 loss: 0.0558 2022/09/18 02:25:52 - mmengine - INFO - Epoch(train) [16][9500/10520] lr: 1.0000e-04 eta: 15:06:23 time: 0.9555 data_time: 0.0079 memory: 56769 loss_visual: 0.0546 loss: 0.0546 2022/09/18 02:28:00 - mmengine - INFO - Epoch(train) [16][9600/10520] lr: 1.0000e-04 eta: 15:04:18 time: 0.9086 data_time: 0.0074 memory: 56769 loss_visual: 0.0553 loss: 0.0553 2022/09/18 02:30:11 - mmengine - INFO - Epoch(train) [16][9700/10520] lr: 1.0000e-04 eta: 15:02:13 time: 1.3286 data_time: 0.2878 memory: 56769 loss_visual: 0.0568 loss: 0.0568 2022/09/18 02:32:25 - mmengine - INFO - Epoch(train) [16][9800/10520] lr: 1.0000e-04 eta: 15:00:09 time: 2.0818 data_time: 0.8287 memory: 56769 loss_visual: 0.0568 loss: 0.0568 2022/09/18 02:34:35 - mmengine - INFO - Epoch(train) [16][9900/10520] lr: 1.0000e-04 eta: 14:58:03 time: 1.8220 data_time: 0.5915 memory: 56769 loss_visual: 0.0610 loss: 0.0610 2022/09/18 02:36:42 - mmengine - INFO - Epoch(train) [16][10000/10520] lr: 1.0000e-04 eta: 14:55:57 time: 1.5552 data_time: 0.3760 memory: 56769 loss_visual: 0.0560 loss: 0.0560 2022/09/18 02:38:50 - mmengine - INFO - Epoch(train) [16][10100/10520] lr: 1.0000e-04 eta: 14:53:51 time: 0.9435 data_time: 0.0411 memory: 56769 loss_visual: 0.0579 loss: 0.0579 2022/09/18 02:40:59 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 02:40:59 - mmengine - INFO - Epoch(train) [16][10200/10520] lr: 1.0000e-04 eta: 14:51:46 time: 0.9074 data_time: 0.0077 memory: 56769 loss_visual: 0.0564 loss: 0.0564 2022/09/18 02:43:05 - mmengine - INFO - Epoch(train) [16][10300/10520] lr: 1.0000e-04 eta: 14:49:40 time: 0.9127 data_time: 0.0081 memory: 56769 loss_visual: 0.0606 loss: 0.0606 2022/09/18 02:45:14 - mmengine - INFO - Epoch(train) [16][10400/10520] lr: 1.0000e-04 eta: 14:47:34 time: 0.8704 data_time: 0.0070 memory: 56769 loss_visual: 0.0563 loss: 0.0563 2022/09/18 02:47:20 - mmengine - INFO - Epoch(train) [16][10500/10520] lr: 1.0000e-04 eta: 14:45:28 time: 1.1233 data_time: 0.1537 memory: 56769 loss_visual: 0.0547 loss: 0.0547 2022/09/18 02:47:40 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 02:47:40 - mmengine - INFO - Saving checkpoint at 16 epochs 2022/09/18 02:47:58 - mmengine - INFO - Epoch(val) [16][100/3836] eta: 0:05:18 time: 0.0853 data_time: 0.0006 memory: 56769 2022/09/18 02:48:03 - mmengine - INFO - Epoch(val) [16][200/3836] eta: 0:00:40 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/18 02:48:04 - mmengine - INFO - Epoch(val) [16][300/3836] eta: 0:00:41 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 02:48:05 - mmengine - INFO - Epoch(val) [16][400/3836] eta: 0:00:39 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 02:48:06 - mmengine - INFO - Epoch(val) [16][500/3836] eta: 0:00:38 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 02:48:08 - mmengine - INFO - Epoch(val) [16][600/3836] eta: 0:00:38 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 02:48:09 - mmengine - INFO - Epoch(val) [16][700/3836] eta: 0:00:36 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 02:48:10 - mmengine - INFO - Epoch(val) [16][800/3836] eta: 0:00:34 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/18 02:48:11 - mmengine - INFO - Epoch(val) [16][900/3836] eta: 0:00:32 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/18 02:48:12 - mmengine - INFO - Epoch(val) [16][1000/3836] eta: 0:00:33 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 02:48:13 - mmengine - INFO - Epoch(val) [16][1100/3836] eta: 0:00:32 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 02:48:15 - mmengine - INFO - Epoch(val) [16][1200/3836] eta: 0:01:03 time: 0.0241 data_time: 0.0019 memory: 480 2022/09/18 02:48:16 - mmengine - INFO - Epoch(val) [16][1300/3836] eta: 0:00:30 time: 0.0121 data_time: 0.0007 memory: 480 2022/09/18 02:48:17 - mmengine - INFO - Epoch(val) [16][1400/3836] eta: 0:00:27 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 02:48:18 - mmengine - INFO - Epoch(val) [16][1500/3836] eta: 0:00:26 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 02:48:20 - mmengine - INFO - Epoch(val) [16][1600/3836] eta: 0:00:25 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/18 02:48:21 - mmengine - INFO - Epoch(val) [16][1700/3836] eta: 0:00:24 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 02:48:22 - mmengine - INFO - Epoch(val) [16][1800/3836] eta: 0:00:23 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 02:48:23 - mmengine - INFO - Epoch(val) [16][1900/3836] eta: 0:00:22 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 02:48:24 - mmengine - INFO - Epoch(val) [16][2000/3836] eta: 0:00:20 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/18 02:48:25 - mmengine - INFO - Epoch(val) [16][2100/3836] eta: 0:00:20 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 02:48:26 - mmengine - INFO - Epoch(val) [16][2200/3836] eta: 0:00:18 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/18 02:48:28 - mmengine - INFO - Epoch(val) [16][2300/3836] eta: 0:00:17 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 02:48:29 - mmengine - INFO - Epoch(val) [16][2400/3836] eta: 0:00:16 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 02:48:30 - mmengine - INFO - Epoch(val) [16][2500/3836] eta: 0:00:14 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/18 02:48:31 - mmengine - INFO - Epoch(val) [16][2600/3836] eta: 0:00:20 time: 0.0162 data_time: 0.0006 memory: 480 2022/09/18 02:48:32 - mmengine - INFO - Epoch(val) [16][2700/3836] eta: 0:00:13 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 02:48:34 - mmengine - INFO - Epoch(val) [16][2800/3836] eta: 0:00:12 time: 0.0119 data_time: 0.0004 memory: 480 2022/09/18 02:48:35 - mmengine - INFO - Epoch(val) [16][2900/3836] eta: 0:00:12 time: 0.0130 data_time: 0.0017 memory: 480 2022/09/18 02:48:36 - mmengine - INFO - Epoch(val) [16][3000/3836] eta: 0:00:09 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 02:48:37 - mmengine - INFO - Epoch(val) [16][3100/3836] eta: 0:00:08 time: 0.0114 data_time: 0.0007 memory: 480 2022/09/18 02:48:39 - mmengine - INFO - Epoch(val) [16][3200/3836] eta: 0:00:07 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 02:48:40 - mmengine - INFO - Epoch(val) [16][3300/3836] eta: 0:00:05 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/18 02:48:41 - mmengine - INFO - Epoch(val) [16][3400/3836] eta: 0:00:04 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/18 02:48:42 - mmengine - INFO - Epoch(val) [16][3500/3836] eta: 0:00:03 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/18 02:48:43 - mmengine - INFO - Epoch(val) [16][3600/3836] eta: 0:00:02 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 02:48:44 - mmengine - INFO - Epoch(val) [16][3700/3836] eta: 0:00:01 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/18 02:48:45 - mmengine - INFO - Epoch(val) [16][3800/3836] eta: 0:00:00 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 02:48:46 - mmengine - INFO - Epoch(val) [16][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.8576 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9430 SVT/recog/word_acc_ignore_case_symbol: 0.8995 SVTP/recog/word_acc_ignore_case_symbol: 0.8171 IC13/recog/word_acc_ignore_case_symbol: 0.9291 IC15/recog/word_acc_ignore_case_symbol: 0.7790 2022/09/18 02:51:05 - mmengine - INFO - Epoch(train) [17][100/10520] lr: 1.0000e-05 eta: 14:42:59 time: 1.5474 data_time: 0.5427 memory: 56769 loss_visual: 0.0509 loss: 0.0509 2022/09/18 02:53:05 - mmengine - INFO - Epoch(train) [17][200/10520] lr: 1.0000e-05 eta: 14:40:51 time: 1.7022 data_time: 0.7417 memory: 56769 loss_visual: 0.0522 loss: 0.0522 2022/09/18 02:55:03 - mmengine - INFO - Epoch(train) [17][300/10520] lr: 1.0000e-05 eta: 14:38:43 time: 1.2900 data_time: 0.4347 memory: 56769 loss_visual: 0.0516 loss: 0.0516 2022/09/18 02:57:04 - mmengine - INFO - Epoch(train) [17][400/10520] lr: 1.0000e-05 eta: 14:36:35 time: 1.0336 data_time: 0.0413 memory: 56769 loss_visual: 0.0474 loss: 0.0474 2022/09/18 02:59:03 - mmengine - INFO - Epoch(train) [17][500/10520] lr: 1.0000e-05 eta: 14:34:27 time: 1.0919 data_time: 0.0422 memory: 56769 loss_visual: 0.0538 loss: 0.0538 2022/09/18 03:01:03 - mmengine - INFO - Epoch(train) [17][600/10520] lr: 1.0000e-05 eta: 14:32:19 time: 1.0820 data_time: 0.0232 memory: 56769 loss_visual: 0.0534 loss: 0.0534 2022/09/18 03:02:42 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 03:03:01 - mmengine - INFO - Epoch(train) [17][700/10520] lr: 1.0000e-05 eta: 14:30:11 time: 0.9332 data_time: 0.0067 memory: 56769 loss_visual: 0.0486 loss: 0.0486 2022/09/18 03:05:01 - mmengine - INFO - Epoch(train) [17][800/10520] lr: 1.0000e-05 eta: 14:28:04 time: 0.8581 data_time: 0.0071 memory: 56769 loss_visual: 0.0525 loss: 0.0525 2022/09/18 03:07:06 - mmengine - INFO - Epoch(train) [17][900/10520] lr: 1.0000e-05 eta: 14:25:57 time: 1.4986 data_time: 0.4895 memory: 56769 loss_visual: 0.0497 loss: 0.0497 2022/09/18 03:09:08 - mmengine - INFO - Epoch(train) [17][1000/10520] lr: 1.0000e-05 eta: 14:23:50 time: 1.7073 data_time: 0.7077 memory: 56769 loss_visual: 0.0503 loss: 0.0503 2022/09/18 03:11:06 - mmengine - INFO - Epoch(train) [17][1100/10520] lr: 1.0000e-05 eta: 14:21:42 time: 1.2744 data_time: 0.4376 memory: 56769 loss_visual: 0.0512 loss: 0.0512 2022/09/18 03:13:07 - mmengine - INFO - Epoch(train) [17][1200/10520] lr: 1.0000e-05 eta: 14:19:34 time: 1.0032 data_time: 0.0605 memory: 56769 loss_visual: 0.0524 loss: 0.0524 2022/09/18 03:15:07 - mmengine - INFO - Epoch(train) [17][1300/10520] lr: 1.0000e-05 eta: 14:17:27 time: 1.1028 data_time: 0.1098 memory: 56769 loss_visual: 0.0491 loss: 0.0491 2022/09/18 03:17:10 - mmengine - INFO - Epoch(train) [17][1400/10520] lr: 1.0000e-05 eta: 14:15:20 time: 1.0488 data_time: 0.0239 memory: 56769 loss_visual: 0.0505 loss: 0.0505 2022/09/18 03:19:14 - mmengine - INFO - Epoch(train) [17][1500/10520] lr: 1.0000e-05 eta: 14:13:13 time: 0.9125 data_time: 0.0107 memory: 56769 loss_visual: 0.0516 loss: 0.0516 2022/09/18 03:21:18 - mmengine - INFO - Epoch(train) [17][1600/10520] lr: 1.0000e-05 eta: 14:11:06 time: 0.8682 data_time: 0.0072 memory: 56769 loss_visual: 0.0503 loss: 0.0503 2022/09/18 03:23:05 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 03:23:26 - mmengine - INFO - Epoch(train) [17][1700/10520] lr: 1.0000e-05 eta: 14:09:01 time: 1.1784 data_time: 0.2367 memory: 56769 loss_visual: 0.0528 loss: 0.0528 2022/09/18 03:25:33 - mmengine - INFO - Epoch(train) [17][1800/10520] lr: 1.0000e-05 eta: 14:06:55 time: 1.4159 data_time: 0.4766 memory: 56769 loss_visual: 0.0524 loss: 0.0524 2022/09/18 03:27:40 - mmengine - INFO - Epoch(train) [17][1900/10520] lr: 1.0000e-05 eta: 14:04:49 time: 1.3980 data_time: 0.5654 memory: 56769 loss_visual: 0.0538 loss: 0.0538 2022/09/18 03:29:48 - mmengine - INFO - Epoch(train) [17][2000/10520] lr: 1.0000e-05 eta: 14:02:43 time: 1.4532 data_time: 0.2726 memory: 56769 loss_visual: 0.0493 loss: 0.0493 2022/09/18 03:31:53 - mmengine - INFO - Epoch(train) [17][2100/10520] lr: 1.0000e-05 eta: 14:00:37 time: 1.5113 data_time: 0.2656 memory: 56769 loss_visual: 0.0461 loss: 0.0461 2022/09/18 03:33:58 - mmengine - INFO - Epoch(train) [17][2200/10520] lr: 1.0000e-05 eta: 13:58:30 time: 1.0670 data_time: 0.0228 memory: 56769 loss_visual: 0.0525 loss: 0.0525 2022/09/18 03:36:03 - mmengine - INFO - Epoch(train) [17][2300/10520] lr: 1.0000e-05 eta: 13:56:24 time: 0.9420 data_time: 0.0080 memory: 56769 loss_visual: 0.0506 loss: 0.0506 2022/09/18 03:38:09 - mmengine - INFO - Epoch(train) [17][2400/10520] lr: 1.0000e-05 eta: 13:54:17 time: 0.8581 data_time: 0.0075 memory: 56769 loss_visual: 0.0523 loss: 0.0523 2022/09/18 03:40:16 - mmengine - INFO - Epoch(train) [17][2500/10520] lr: 1.0000e-05 eta: 13:52:11 time: 1.1885 data_time: 0.2340 memory: 56769 loss_visual: 0.0516 loss: 0.0516 2022/09/18 03:42:23 - mmengine - INFO - Epoch(train) [17][2600/10520] lr: 1.0000e-05 eta: 13:50:05 time: 1.4831 data_time: 0.4635 memory: 56769 loss_visual: 0.0496 loss: 0.0496 2022/09/18 03:44:05 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 03:44:30 - mmengine - INFO - Epoch(train) [17][2700/10520] lr: 1.0000e-05 eta: 13:47:59 time: 1.3900 data_time: 0.5685 memory: 56769 loss_visual: 0.0481 loss: 0.0481 2022/09/18 03:46:38 - mmengine - INFO - Epoch(train) [17][2800/10520] lr: 1.0000e-05 eta: 13:45:54 time: 1.4984 data_time: 0.3205 memory: 56769 loss_visual: 0.0523 loss: 0.0523 2022/09/18 03:48:41 - mmengine - INFO - Epoch(train) [17][2900/10520] lr: 1.0000e-05 eta: 13:43:47 time: 1.5509 data_time: 0.2769 memory: 56769 loss_visual: 0.0518 loss: 0.0518 2022/09/18 03:50:45 - mmengine - INFO - Epoch(train) [17][3000/10520] lr: 1.0000e-05 eta: 13:41:40 time: 1.0254 data_time: 0.0279 memory: 56769 loss_visual: 0.0515 loss: 0.0515 2022/09/18 03:52:50 - mmengine - INFO - Epoch(train) [17][3100/10520] lr: 1.0000e-05 eta: 13:39:34 time: 0.8905 data_time: 0.0083 memory: 56769 loss_visual: 0.0509 loss: 0.0509 2022/09/18 03:54:53 - mmengine - INFO - Epoch(train) [17][3200/10520] lr: 1.0000e-05 eta: 13:37:27 time: 0.8690 data_time: 0.0073 memory: 56769 loss_visual: 0.0543 loss: 0.0543 2022/09/18 03:56:59 - mmengine - INFO - Epoch(train) [17][3300/10520] lr: 1.0000e-05 eta: 13:35:21 time: 1.1787 data_time: 0.2083 memory: 56769 loss_visual: 0.0508 loss: 0.0508 2022/09/18 03:59:06 - mmengine - INFO - Epoch(train) [17][3400/10520] lr: 1.0000e-05 eta: 13:33:15 time: 1.4317 data_time: 0.5007 memory: 56769 loss_visual: 0.0474 loss: 0.0474 2022/09/18 04:01:13 - mmengine - INFO - Epoch(train) [17][3500/10520] lr: 1.0000e-05 eta: 13:31:09 time: 1.4339 data_time: 0.5618 memory: 56769 loss_visual: 0.0493 loss: 0.0493 2022/09/18 04:03:22 - mmengine - INFO - Epoch(train) [17][3600/10520] lr: 1.0000e-05 eta: 13:29:03 time: 1.4925 data_time: 0.2843 memory: 56769 loss_visual: 0.0516 loss: 0.0516 2022/09/18 04:04:56 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 04:05:26 - mmengine - INFO - Epoch(train) [17][3700/10520] lr: 1.0000e-05 eta: 13:26:57 time: 1.5314 data_time: 0.2650 memory: 56769 loss_visual: 0.0507 loss: 0.0507 2022/09/18 04:07:30 - mmengine - INFO - Epoch(train) [17][3800/10520] lr: 1.0000e-05 eta: 13:24:50 time: 1.0041 data_time: 0.0236 memory: 56769 loss_visual: 0.0483 loss: 0.0483 2022/09/18 04:09:34 - mmengine - INFO - Epoch(train) [17][3900/10520] lr: 1.0000e-05 eta: 13:22:43 time: 0.9056 data_time: 0.0071 memory: 56769 loss_visual: 0.0538 loss: 0.0538 2022/09/18 04:11:39 - mmengine - INFO - Epoch(train) [17][4000/10520] lr: 1.0000e-05 eta: 13:20:37 time: 0.8732 data_time: 0.0071 memory: 56769 loss_visual: 0.0520 loss: 0.0520 2022/09/18 04:13:45 - mmengine - INFO - Epoch(train) [17][4100/10520] lr: 1.0000e-05 eta: 13:18:31 time: 1.1949 data_time: 0.2086 memory: 56769 loss_visual: 0.0498 loss: 0.0498 2022/09/18 04:15:51 - mmengine - INFO - Epoch(train) [17][4200/10520] lr: 1.0000e-05 eta: 13:16:25 time: 1.4109 data_time: 0.4375 memory: 56769 loss_visual: 0.0507 loss: 0.0507 2022/09/18 04:17:59 - mmengine - INFO - Epoch(train) [17][4300/10520] lr: 1.0000e-05 eta: 13:14:19 time: 1.3960 data_time: 0.5637 memory: 56769 loss_visual: 0.0548 loss: 0.0548 2022/09/18 04:20:09 - mmengine - INFO - Epoch(train) [17][4400/10520] lr: 1.0000e-05 eta: 13:12:13 time: 1.5127 data_time: 0.2879 memory: 56769 loss_visual: 0.0502 loss: 0.0502 2022/09/18 04:22:14 - mmengine - INFO - Epoch(train) [17][4500/10520] lr: 1.0000e-05 eta: 13:10:07 time: 1.5495 data_time: 0.2951 memory: 56769 loss_visual: 0.0489 loss: 0.0489 2022/09/18 04:24:18 - mmengine - INFO - Epoch(train) [17][4600/10520] lr: 1.0000e-05 eta: 13:08:00 time: 1.0577 data_time: 0.0233 memory: 56769 loss_visual: 0.0495 loss: 0.0495 2022/09/18 04:25:58 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 04:26:22 - mmengine - INFO - Epoch(train) [17][4700/10520] lr: 1.0000e-05 eta: 13:05:54 time: 0.9503 data_time: 0.0098 memory: 56769 loss_visual: 0.0528 loss: 0.0528 2022/09/18 04:28:26 - mmengine - INFO - Epoch(train) [17][4800/10520] lr: 1.0000e-05 eta: 13:03:47 time: 0.8886 data_time: 0.0071 memory: 56769 loss_visual: 0.0485 loss: 0.0485 2022/09/18 04:30:34 - mmengine - INFO - Epoch(train) [17][4900/10520] lr: 1.0000e-05 eta: 13:01:41 time: 1.2211 data_time: 0.2028 memory: 56769 loss_visual: 0.0464 loss: 0.0464 2022/09/18 04:32:41 - mmengine - INFO - Epoch(train) [17][5000/10520] lr: 1.0000e-05 eta: 12:59:35 time: 1.4241 data_time: 0.4898 memory: 56769 loss_visual: 0.0528 loss: 0.0528 2022/09/18 04:34:48 - mmengine - INFO - Epoch(train) [17][5100/10520] lr: 1.0000e-05 eta: 12:57:29 time: 1.4480 data_time: 0.5691 memory: 56769 loss_visual: 0.0481 loss: 0.0481 2022/09/18 04:36:56 - mmengine - INFO - Epoch(train) [17][5200/10520] lr: 1.0000e-05 eta: 12:55:24 time: 1.5024 data_time: 0.2764 memory: 56769 loss_visual: 0.0493 loss: 0.0493 2022/09/18 04:39:01 - mmengine - INFO - Epoch(train) [17][5300/10520] lr: 1.0000e-05 eta: 12:53:17 time: 1.5142 data_time: 0.2641 memory: 56769 loss_visual: 0.0487 loss: 0.0487 2022/09/18 04:41:04 - mmengine - INFO - Epoch(train) [17][5400/10520] lr: 1.0000e-05 eta: 12:51:10 time: 1.0225 data_time: 0.0258 memory: 56769 loss_visual: 0.0556 loss: 0.0556 2022/09/18 04:43:07 - mmengine - INFO - Epoch(train) [17][5500/10520] lr: 1.0000e-05 eta: 12:49:04 time: 0.9019 data_time: 0.0071 memory: 56769 loss_visual: 0.0496 loss: 0.0496 2022/09/18 04:45:13 - mmengine - INFO - Epoch(train) [17][5600/10520] lr: 1.0000e-05 eta: 12:46:57 time: 0.8619 data_time: 0.0081 memory: 56769 loss_visual: 0.0488 loss: 0.0488 2022/09/18 04:46:59 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 04:47:20 - mmengine - INFO - Epoch(train) [17][5700/10520] lr: 1.0000e-05 eta: 12:44:51 time: 1.1885 data_time: 0.2577 memory: 56769 loss_visual: 0.0482 loss: 0.0482 2022/09/18 04:49:28 - mmengine - INFO - Epoch(train) [17][5800/10520] lr: 1.0000e-05 eta: 12:42:46 time: 1.4984 data_time: 0.5370 memory: 56769 loss_visual: 0.0512 loss: 0.0512 2022/09/18 04:51:34 - mmengine - INFO - Epoch(train) [17][5900/10520] lr: 1.0000e-05 eta: 12:40:39 time: 1.4644 data_time: 0.6342 memory: 56769 loss_visual: 0.0493 loss: 0.0493 2022/09/18 04:53:44 - mmengine - INFO - Epoch(train) [17][6000/10520] lr: 1.0000e-05 eta: 12:38:34 time: 1.5191 data_time: 0.3518 memory: 56769 loss_visual: 0.0492 loss: 0.0492 2022/09/18 04:55:48 - mmengine - INFO - Epoch(train) [17][6100/10520] lr: 1.0000e-05 eta: 12:36:27 time: 1.5903 data_time: 0.2928 memory: 56769 loss_visual: 0.0487 loss: 0.0487 2022/09/18 04:57:52 - mmengine - INFO - Epoch(train) [17][6200/10520] lr: 1.0000e-05 eta: 12:34:21 time: 1.0459 data_time: 0.0242 memory: 56769 loss_visual: 0.0462 loss: 0.0462 2022/09/18 04:59:56 - mmengine - INFO - Epoch(train) [17][6300/10520] lr: 1.0000e-05 eta: 12:32:14 time: 0.9087 data_time: 0.0071 memory: 56769 loss_visual: 0.0524 loss: 0.0524 2022/09/18 05:02:01 - mmengine - INFO - Epoch(train) [17][6400/10520] lr: 1.0000e-05 eta: 12:30:08 time: 0.8748 data_time: 0.0078 memory: 56769 loss_visual: 0.0491 loss: 0.0491 2022/09/18 05:04:08 - mmengine - INFO - Epoch(train) [17][6500/10520] lr: 1.0000e-05 eta: 12:28:02 time: 1.1514 data_time: 0.2533 memory: 56769 loss_visual: 0.0507 loss: 0.0507 2022/09/18 05:06:13 - mmengine - INFO - Epoch(train) [17][6600/10520] lr: 1.0000e-05 eta: 12:25:55 time: 1.4466 data_time: 0.5029 memory: 56769 loss_visual: 0.0508 loss: 0.0508 2022/09/18 05:07:53 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 05:08:19 - mmengine - INFO - Epoch(train) [17][6700/10520] lr: 1.0000e-05 eta: 12:23:49 time: 1.4484 data_time: 0.5827 memory: 56769 loss_visual: 0.0488 loss: 0.0488 2022/09/18 05:10:26 - mmengine - INFO - Epoch(train) [17][6800/10520] lr: 1.0000e-05 eta: 12:21:43 time: 1.4954 data_time: 0.2704 memory: 56769 loss_visual: 0.0527 loss: 0.0527 2022/09/18 05:12:31 - mmengine - INFO - Epoch(train) [17][6900/10520] lr: 1.0000e-05 eta: 12:19:37 time: 1.5251 data_time: 0.3103 memory: 56769 loss_visual: 0.0503 loss: 0.0503 2022/09/18 05:14:34 - mmengine - INFO - Epoch(train) [17][7000/10520] lr: 1.0000e-05 eta: 12:17:30 time: 1.0645 data_time: 0.0242 memory: 56769 loss_visual: 0.0513 loss: 0.0513 2022/09/18 05:16:38 - mmengine - INFO - Epoch(train) [17][7100/10520] lr: 1.0000e-05 eta: 12:15:24 time: 0.9397 data_time: 0.0073 memory: 56769 loss_visual: 0.0462 loss: 0.0462 2022/09/18 05:18:42 - mmengine - INFO - Epoch(train) [17][7200/10520] lr: 1.0000e-05 eta: 12:13:17 time: 0.8879 data_time: 0.0071 memory: 56769 loss_visual: 0.0497 loss: 0.0497 2022/09/18 05:20:48 - mmengine - INFO - Epoch(train) [17][7300/10520] lr: 1.0000e-05 eta: 12:11:11 time: 1.1646 data_time: 0.2486 memory: 56769 loss_visual: 0.0501 loss: 0.0501 2022/09/18 05:22:55 - mmengine - INFO - Epoch(train) [17][7400/10520] lr: 1.0000e-05 eta: 12:09:05 time: 1.4232 data_time: 0.4657 memory: 56769 loss_visual: 0.0516 loss: 0.0516 2022/09/18 05:25:00 - mmengine - INFO - Epoch(train) [17][7500/10520] lr: 1.0000e-05 eta: 12:06:59 time: 1.4158 data_time: 0.5630 memory: 56769 loss_visual: 0.0515 loss: 0.0515 2022/09/18 05:27:08 - mmengine - INFO - Epoch(train) [17][7600/10520] lr: 1.0000e-05 eta: 12:04:53 time: 1.4765 data_time: 0.2958 memory: 56769 loss_visual: 0.0517 loss: 0.0517 2022/09/18 05:28:43 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 05:29:13 - mmengine - INFO - Epoch(train) [17][7700/10520] lr: 1.0000e-05 eta: 12:02:46 time: 1.5694 data_time: 0.2790 memory: 56769 loss_visual: 0.0486 loss: 0.0486 2022/09/18 05:31:17 - mmengine - INFO - Epoch(train) [17][7800/10520] lr: 1.0000e-05 eta: 12:00:40 time: 1.0649 data_time: 0.0247 memory: 56769 loss_visual: 0.0509 loss: 0.0509 2022/09/18 05:33:22 - mmengine - INFO - Epoch(train) [17][7900/10520] lr: 1.0000e-05 eta: 11:58:33 time: 0.9159 data_time: 0.0072 memory: 56769 loss_visual: 0.0506 loss: 0.0506 2022/09/18 05:35:26 - mmengine - INFO - Epoch(train) [17][8000/10520] lr: 1.0000e-05 eta: 11:56:27 time: 0.8286 data_time: 0.0071 memory: 56769 loss_visual: 0.0497 loss: 0.0497 2022/09/18 05:37:32 - mmengine - INFO - Epoch(train) [17][8100/10520] lr: 1.0000e-05 eta: 11:54:21 time: 1.1799 data_time: 0.2211 memory: 56769 loss_visual: 0.0463 loss: 0.0463 2022/09/18 05:39:38 - mmengine - INFO - Epoch(train) [17][8200/10520] lr: 1.0000e-05 eta: 11:52:15 time: 1.4441 data_time: 0.4772 memory: 56769 loss_visual: 0.0502 loss: 0.0502 2022/09/18 05:41:46 - mmengine - INFO - Epoch(train) [17][8300/10520] lr: 1.0000e-05 eta: 11:50:09 time: 1.4290 data_time: 0.5699 memory: 56769 loss_visual: 0.0493 loss: 0.0493 2022/09/18 05:43:54 - mmengine - INFO - Epoch(train) [17][8400/10520] lr: 1.0000e-05 eta: 11:48:03 time: 1.5337 data_time: 0.3294 memory: 56769 loss_visual: 0.0546 loss: 0.0546 2022/09/18 05:45:57 - mmengine - INFO - Epoch(train) [17][8500/10520] lr: 1.0000e-05 eta: 11:45:56 time: 1.5480 data_time: 0.2522 memory: 56769 loss_visual: 0.0477 loss: 0.0477 2022/09/18 05:48:02 - mmengine - INFO - Epoch(train) [17][8600/10520] lr: 1.0000e-05 eta: 11:43:50 time: 1.0551 data_time: 0.0228 memory: 56769 loss_visual: 0.0517 loss: 0.0517 2022/09/18 05:49:42 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 05:50:06 - mmengine - INFO - Epoch(train) [17][8700/10520] lr: 1.0000e-05 eta: 11:41:43 time: 0.9174 data_time: 0.0074 memory: 56769 loss_visual: 0.0508 loss: 0.0508 2022/09/18 05:52:10 - mmengine - INFO - Epoch(train) [17][8800/10520] lr: 1.0000e-05 eta: 11:39:37 time: 0.8516 data_time: 0.0073 memory: 56769 loss_visual: 0.0515 loss: 0.0515 2022/09/18 05:54:18 - mmengine - INFO - Epoch(train) [17][8900/10520] lr: 1.0000e-05 eta: 11:37:31 time: 1.1938 data_time: 0.2674 memory: 56769 loss_visual: 0.0476 loss: 0.0476 2022/09/18 05:56:25 - mmengine - INFO - Epoch(train) [17][9000/10520] lr: 1.0000e-05 eta: 11:35:25 time: 1.4033 data_time: 0.4662 memory: 56769 loss_visual: 0.0494 loss: 0.0494 2022/09/18 05:58:30 - mmengine - INFO - Epoch(train) [17][9100/10520] lr: 1.0000e-05 eta: 11:33:19 time: 1.3976 data_time: 0.5434 memory: 56769 loss_visual: 0.0498 loss: 0.0498 2022/09/18 06:00:41 - mmengine - INFO - Epoch(train) [17][9200/10520] lr: 1.0000e-05 eta: 11:31:13 time: 1.5059 data_time: 0.2625 memory: 56769 loss_visual: 0.0480 loss: 0.0480 2022/09/18 06:02:46 - mmengine - INFO - Epoch(train) [17][9300/10520] lr: 1.0000e-05 eta: 11:29:07 time: 1.5409 data_time: 0.2957 memory: 56769 loss_visual: 0.0531 loss: 0.0531 2022/09/18 06:04:50 - mmengine - INFO - Epoch(train) [17][9400/10520] lr: 1.0000e-05 eta: 11:27:00 time: 1.0541 data_time: 0.0245 memory: 56769 loss_visual: 0.0478 loss: 0.0478 2022/09/18 06:06:55 - mmengine - INFO - Epoch(train) [17][9500/10520] lr: 1.0000e-05 eta: 11:24:54 time: 0.9744 data_time: 0.0072 memory: 56769 loss_visual: 0.0473 loss: 0.0473 2022/09/18 06:08:59 - mmengine - INFO - Epoch(train) [17][9600/10520] lr: 1.0000e-05 eta: 11:22:48 time: 0.9180 data_time: 0.0088 memory: 56769 loss_visual: 0.0473 loss: 0.0473 2022/09/18 06:10:46 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 06:11:07 - mmengine - INFO - Epoch(train) [17][9700/10520] lr: 1.0000e-05 eta: 11:20:42 time: 1.1799 data_time: 0.2601 memory: 56769 loss_visual: 0.0525 loss: 0.0525 2022/09/18 06:13:14 - mmengine - INFO - Epoch(train) [17][9800/10520] lr: 1.0000e-05 eta: 11:18:36 time: 1.4224 data_time: 0.4964 memory: 56769 loss_visual: 0.0499 loss: 0.0499 2022/09/18 06:15:19 - mmengine - INFO - Epoch(train) [17][9900/10520] lr: 1.0000e-05 eta: 11:16:29 time: 1.3992 data_time: 0.5411 memory: 56769 loss_visual: 0.0531 loss: 0.0531 2022/09/18 06:17:25 - mmengine - INFO - Epoch(train) [17][10000/10520] lr: 1.0000e-05 eta: 11:14:23 time: 1.4817 data_time: 0.2917 memory: 56769 loss_visual: 0.0492 loss: 0.0492 2022/09/18 06:19:30 - mmengine - INFO - Epoch(train) [17][10100/10520] lr: 1.0000e-05 eta: 11:12:17 time: 1.5596 data_time: 0.2730 memory: 56769 loss_visual: 0.0517 loss: 0.0517 2022/09/18 06:21:34 - mmengine - INFO - Epoch(train) [17][10200/10520] lr: 1.0000e-05 eta: 11:10:10 time: 1.0865 data_time: 0.0577 memory: 56769 loss_visual: 0.0466 loss: 0.0466 2022/09/18 06:23:38 - mmengine - INFO - Epoch(train) [17][10300/10520] lr: 1.0000e-05 eta: 11:08:04 time: 0.9053 data_time: 0.0070 memory: 56769 loss_visual: 0.0535 loss: 0.0535 2022/09/18 06:25:42 - mmengine - INFO - Epoch(train) [17][10400/10520] lr: 1.0000e-05 eta: 11:05:57 time: 0.8898 data_time: 0.0073 memory: 56769 loss_visual: 0.0555 loss: 0.0555 2022/09/18 06:27:44 - mmengine - INFO - Epoch(train) [17][10500/10520] lr: 1.0000e-05 eta: 11:03:50 time: 1.0695 data_time: 0.1407 memory: 56769 loss_visual: 0.0468 loss: 0.0468 2022/09/18 06:28:05 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 06:28:05 - mmengine - INFO - Saving checkpoint at 17 epochs 2022/09/18 06:28:22 - mmengine - INFO - Epoch(val) [17][100/3836] eta: 0:05:48 time: 0.0932 data_time: 0.0006 memory: 56769 2022/09/18 06:28:27 - mmengine - INFO - Epoch(val) [17][200/3836] eta: 0:00:42 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 06:28:28 - mmengine - INFO - Epoch(val) [17][300/3836] eta: 0:00:41 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 06:28:29 - mmengine - INFO - Epoch(val) [17][400/3836] eta: 0:00:41 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/18 06:28:30 - mmengine - INFO - Epoch(val) [17][500/3836] eta: 0:00:39 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 06:28:31 - mmengine - INFO - Epoch(val) [17][600/3836] eta: 0:00:37 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 06:28:32 - mmengine - INFO - Epoch(val) [17][700/3836] eta: 0:00:34 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/18 06:28:34 - mmengine - INFO - Epoch(val) [17][800/3836] eta: 0:00:35 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 06:28:35 - mmengine - INFO - Epoch(val) [17][900/3836] eta: 0:00:34 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 06:28:36 - mmengine - INFO - Epoch(val) [17][1000/3836] eta: 0:00:32 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 06:28:37 - mmengine - INFO - Epoch(val) [17][1100/3836] eta: 0:00:30 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/18 06:28:38 - mmengine - INFO - Epoch(val) [17][1200/3836] eta: 0:00:29 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/18 06:28:39 - mmengine - INFO - Epoch(val) [17][1300/3836] eta: 0:00:29 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 06:28:41 - mmengine - INFO - Epoch(val) [17][1400/3836] eta: 0:00:28 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 06:28:42 - mmengine - INFO - Epoch(val) [17][1500/3836] eta: 0:00:32 time: 0.0140 data_time: 0.0013 memory: 480 2022/09/18 06:28:43 - mmengine - INFO - Epoch(val) [17][1600/3836] eta: 0:00:26 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 06:28:44 - mmengine - INFO - Epoch(val) [17][1700/3836] eta: 0:00:25 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/18 06:28:45 - mmengine - INFO - Epoch(val) [17][1800/3836] eta: 0:00:24 time: 0.0121 data_time: 0.0006 memory: 480 2022/09/18 06:28:47 - mmengine - INFO - Epoch(val) [17][1900/3836] eta: 0:00:22 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/18 06:28:48 - mmengine - INFO - Epoch(val) [17][2000/3836] eta: 0:00:22 time: 0.0122 data_time: 0.0005 memory: 480 2022/09/18 06:28:49 - mmengine - INFO - Epoch(val) [17][2100/3836] eta: 0:00:20 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 06:28:50 - mmengine - INFO - Epoch(val) [17][2200/3836] eta: 0:00:19 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/18 06:28:51 - mmengine - INFO - Epoch(val) [17][2300/3836] eta: 0:00:18 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 06:28:53 - mmengine - INFO - Epoch(val) [17][2400/3836] eta: 0:00:16 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 06:28:54 - mmengine - INFO - Epoch(val) [17][2500/3836] eta: 0:00:15 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 06:28:55 - mmengine - INFO - Epoch(val) [17][2600/3836] eta: 0:00:14 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 06:28:56 - mmengine - INFO - Epoch(val) [17][2700/3836] eta: 0:00:13 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 06:28:58 - mmengine - INFO - Epoch(val) [17][2800/3836] eta: 0:00:12 time: 0.0119 data_time: 0.0004 memory: 480 2022/09/18 06:28:59 - mmengine - INFO - Epoch(val) [17][2900/3836] eta: 0:00:10 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 06:29:00 - mmengine - INFO - Epoch(val) [17][3000/3836] eta: 0:00:09 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 06:29:01 - mmengine - INFO - Epoch(val) [17][3100/3836] eta: 0:00:09 time: 0.0122 data_time: 0.0005 memory: 480 2022/09/18 06:29:02 - mmengine - INFO - Epoch(val) [17][3200/3836] eta: 0:00:07 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 06:29:03 - mmengine - INFO - Epoch(val) [17][3300/3836] eta: 0:00:06 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/18 06:29:05 - mmengine - INFO - Epoch(val) [17][3400/3836] eta: 0:00:04 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 06:29:06 - mmengine - INFO - Epoch(val) [17][3500/3836] eta: 0:00:03 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/18 06:29:07 - mmengine - INFO - Epoch(val) [17][3600/3836] eta: 0:00:02 time: 0.0119 data_time: 0.0007 memory: 480 2022/09/18 06:29:08 - mmengine - INFO - Epoch(val) [17][3700/3836] eta: 0:00:01 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 06:29:09 - mmengine - INFO - Epoch(val) [17][3800/3836] eta: 0:00:00 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 06:29:10 - mmengine - INFO - Epoch(val) [17][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.8333 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9507 SVT/recog/word_acc_ignore_case_symbol: 0.9104 SVTP/recog/word_acc_ignore_case_symbol: 0.8357 IC13/recog/word_acc_ignore_case_symbol: 0.9369 IC15/recog/word_acc_ignore_case_symbol: 0.7896 2022/09/18 06:31:30 - mmengine - INFO - Epoch(train) [18][100/10520] lr: 1.0000e-05 eta: 11:01:21 time: 1.3127 data_time: 0.4485 memory: 56769 loss_visual: 0.0480 loss: 0.0480 2022/09/18 06:32:43 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 06:33:42 - mmengine - INFO - Epoch(train) [18][200/10520] lr: 1.0000e-05 eta: 10:59:16 time: 2.0099 data_time: 0.7225 memory: 56769 loss_visual: 0.0499 loss: 0.0499 2022/09/18 06:35:48 - mmengine - INFO - Epoch(train) [18][300/10520] lr: 1.0000e-05 eta: 10:57:09 time: 1.7654 data_time: 0.3786 memory: 56769 loss_visual: 0.0494 loss: 0.0494 2022/09/18 06:37:54 - mmengine - INFO - Epoch(train) [18][400/10520] lr: 1.0000e-05 eta: 10:55:03 time: 1.0442 data_time: 0.0256 memory: 56769 loss_visual: 0.0501 loss: 0.0501 2022/09/18 06:40:00 - mmengine - INFO - Epoch(train) [18][500/10520] lr: 1.0000e-05 eta: 10:52:57 time: 0.8910 data_time: 0.0075 memory: 56769 loss_visual: 0.0468 loss: 0.0468 2022/09/18 06:42:06 - mmengine - INFO - Epoch(train) [18][600/10520] lr: 1.0000e-05 eta: 10:50:51 time: 0.9154 data_time: 0.0071 memory: 56769 loss_visual: 0.0503 loss: 0.0503 2022/09/18 06:44:11 - mmengine - INFO - Epoch(train) [18][700/10520] lr: 1.0000e-05 eta: 10:48:44 time: 0.9509 data_time: 0.0083 memory: 56769 loss_visual: 0.0519 loss: 0.0519 2022/09/18 06:46:17 - mmengine - INFO - Epoch(train) [18][800/10520] lr: 1.0000e-05 eta: 10:46:38 time: 0.9304 data_time: 0.0069 memory: 56769 loss_visual: 0.0486 loss: 0.0486 2022/09/18 06:48:28 - mmengine - INFO - Epoch(train) [18][900/10520] lr: 1.0000e-05 eta: 10:44:33 time: 1.3387 data_time: 0.5066 memory: 56769 loss_visual: 0.0470 loss: 0.0470 2022/09/18 06:50:40 - mmengine - INFO - Epoch(train) [18][1000/10520] lr: 1.0000e-05 eta: 10:42:28 time: 2.0096 data_time: 0.7102 memory: 56769 loss_visual: 0.0500 loss: 0.0500 2022/09/18 06:52:47 - mmengine - INFO - Epoch(train) [18][1100/10520] lr: 1.0000e-05 eta: 10:40:22 time: 1.7667 data_time: 0.4121 memory: 56769 loss_visual: 0.0469 loss: 0.0469 2022/09/18 06:54:04 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 06:54:51 - mmengine - INFO - Epoch(train) [18][1200/10520] lr: 1.0000e-05 eta: 10:38:15 time: 1.0726 data_time: 0.0243 memory: 56769 loss_visual: 0.0493 loss: 0.0493 2022/09/18 06:56:59 - mmengine - INFO - Epoch(train) [18][1300/10520] lr: 1.0000e-05 eta: 10:36:10 time: 0.8830 data_time: 0.0070 memory: 56769 loss_visual: 0.0493 loss: 0.0493 2022/09/18 06:59:04 - mmengine - INFO - Epoch(train) [18][1400/10520] lr: 1.0000e-05 eta: 10:34:03 time: 0.9191 data_time: 0.0076 memory: 56769 loss_visual: 0.0489 loss: 0.0489 2022/09/18 07:01:09 - mmengine - INFO - Epoch(train) [18][1500/10520] lr: 1.0000e-05 eta: 10:31:57 time: 0.9079 data_time: 0.0070 memory: 56769 loss_visual: 0.0505 loss: 0.0505 2022/09/18 07:03:15 - mmengine - INFO - Epoch(train) [18][1600/10520] lr: 1.0000e-05 eta: 10:29:51 time: 0.9328 data_time: 0.0071 memory: 56769 loss_visual: 0.0495 loss: 0.0495 2022/09/18 07:05:25 - mmengine - INFO - Epoch(train) [18][1700/10520] lr: 1.0000e-05 eta: 10:27:45 time: 1.3261 data_time: 0.4869 memory: 56769 loss_visual: 0.0505 loss: 0.0505 2022/09/18 07:07:38 - mmengine - INFO - Epoch(train) [18][1800/10520] lr: 1.0000e-05 eta: 10:25:40 time: 2.0108 data_time: 0.6883 memory: 56769 loss_visual: 0.0529 loss: 0.0529 2022/09/18 07:09:45 - mmengine - INFO - Epoch(train) [18][1900/10520] lr: 1.0000e-05 eta: 10:23:34 time: 1.7991 data_time: 0.3978 memory: 56769 loss_visual: 0.0489 loss: 0.0489 2022/09/18 07:11:53 - mmengine - INFO - Epoch(train) [18][2000/10520] lr: 1.0000e-05 eta: 10:21:28 time: 1.1204 data_time: 0.0230 memory: 56769 loss_visual: 0.0475 loss: 0.0475 2022/09/18 07:13:58 - mmengine - INFO - Epoch(train) [18][2100/10520] lr: 1.0000e-05 eta: 10:19:22 time: 0.8775 data_time: 0.0071 memory: 56769 loss_visual: 0.0488 loss: 0.0488 2022/09/18 07:15:17 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 07:16:05 - mmengine - INFO - Epoch(train) [18][2200/10520] lr: 1.0000e-05 eta: 10:17:16 time: 0.9290 data_time: 0.0074 memory: 56769 loss_visual: 0.0488 loss: 0.0488 2022/09/18 07:18:12 - mmengine - INFO - Epoch(train) [18][2300/10520] lr: 1.0000e-05 eta: 10:15:10 time: 0.9088 data_time: 0.0082 memory: 56769 loss_visual: 0.0513 loss: 0.0513 2022/09/18 07:20:18 - mmengine - INFO - Epoch(train) [18][2400/10520] lr: 1.0000e-05 eta: 10:13:04 time: 0.8986 data_time: 0.0073 memory: 56769 loss_visual: 0.0487 loss: 0.0487 2022/09/18 07:22:28 - mmengine - INFO - Epoch(train) [18][2500/10520] lr: 1.0000e-05 eta: 10:10:58 time: 1.3347 data_time: 0.4818 memory: 56769 loss_visual: 0.0497 loss: 0.0497 2022/09/18 07:24:40 - mmengine - INFO - Epoch(train) [18][2600/10520] lr: 1.0000e-05 eta: 10:08:53 time: 2.0555 data_time: 0.7259 memory: 56769 loss_visual: 0.0497 loss: 0.0497 2022/09/18 07:26:46 - mmengine - INFO - Epoch(train) [18][2700/10520] lr: 1.0000e-05 eta: 10:06:47 time: 1.7171 data_time: 0.3905 memory: 56769 loss_visual: 0.0449 loss: 0.0449 2022/09/18 07:28:51 - mmengine - INFO - Epoch(train) [18][2800/10520] lr: 1.0000e-05 eta: 10:04:41 time: 1.1274 data_time: 0.0234 memory: 56769 loss_visual: 0.0478 loss: 0.0478 2022/09/18 07:30:57 - mmengine - INFO - Epoch(train) [18][2900/10520] lr: 1.0000e-05 eta: 10:02:34 time: 0.8716 data_time: 0.0069 memory: 56769 loss_visual: 0.0480 loss: 0.0480 2022/09/18 07:33:06 - mmengine - INFO - Epoch(train) [18][3000/10520] lr: 1.0000e-05 eta: 10:00:29 time: 0.9537 data_time: 0.0094 memory: 56769 loss_visual: 0.0522 loss: 0.0522 2022/09/18 07:35:14 - mmengine - INFO - Epoch(train) [18][3100/10520] lr: 1.0000e-05 eta: 9:58:23 time: 0.9345 data_time: 0.0072 memory: 56769 loss_visual: 0.0474 loss: 0.0474 2022/09/18 07:36:32 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 07:37:20 - mmengine - INFO - Epoch(train) [18][3200/10520] lr: 1.0000e-05 eta: 9:56:17 time: 0.9272 data_time: 0.0071 memory: 56769 loss_visual: 0.0484 loss: 0.0484 2022/09/18 07:39:31 - mmengine - INFO - Epoch(train) [18][3300/10520] lr: 1.0000e-05 eta: 9:54:11 time: 1.4089 data_time: 0.4864 memory: 56769 loss_visual: 0.0466 loss: 0.0466 2022/09/18 07:41:43 - mmengine - INFO - Epoch(train) [18][3400/10520] lr: 1.0000e-05 eta: 9:52:06 time: 2.0672 data_time: 0.7122 memory: 56769 loss_visual: 0.0465 loss: 0.0465 2022/09/18 07:43:49 - mmengine - INFO - Epoch(train) [18][3500/10520] lr: 1.0000e-05 eta: 9:50:00 time: 1.7669 data_time: 0.4205 memory: 56769 loss_visual: 0.0522 loss: 0.0522 2022/09/18 07:45:56 - mmengine - INFO - Epoch(train) [18][3600/10520] lr: 1.0000e-05 eta: 9:47:54 time: 1.1456 data_time: 0.0245 memory: 56769 loss_visual: 0.0441 loss: 0.0441 2022/09/18 07:48:03 - mmengine - INFO - Epoch(train) [18][3700/10520] lr: 1.0000e-05 eta: 9:45:48 time: 0.8783 data_time: 0.0071 memory: 56769 loss_visual: 0.0481 loss: 0.0481 2022/09/18 07:50:11 - mmengine - INFO - Epoch(train) [18][3800/10520] lr: 1.0000e-05 eta: 9:43:42 time: 0.9514 data_time: 0.0069 memory: 56769 loss_visual: 0.0541 loss: 0.0541 2022/09/18 07:52:17 - mmengine - INFO - Epoch(train) [18][3900/10520] lr: 1.0000e-05 eta: 9:41:36 time: 0.9333 data_time: 0.0070 memory: 56769 loss_visual: 0.0494 loss: 0.0494 2022/09/18 07:54:22 - mmengine - INFO - Epoch(train) [18][4000/10520] lr: 1.0000e-05 eta: 9:39:29 time: 0.8958 data_time: 0.0068 memory: 56769 loss_visual: 0.0483 loss: 0.0483 2022/09/18 07:56:33 - mmengine - INFO - Epoch(train) [18][4100/10520] lr: 1.0000e-05 eta: 9:37:24 time: 1.3210 data_time: 0.4728 memory: 56769 loss_visual: 0.0493 loss: 0.0493 2022/09/18 07:57:46 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 07:58:45 - mmengine - INFO - Epoch(train) [18][4200/10520] lr: 1.0000e-05 eta: 9:35:18 time: 2.0333 data_time: 0.7697 memory: 56769 loss_visual: 0.0492 loss: 0.0492 2022/09/18 08:00:50 - mmengine - INFO - Epoch(train) [18][4300/10520] lr: 1.0000e-05 eta: 9:33:12 time: 1.7316 data_time: 0.3950 memory: 56769 loss_visual: 0.0476 loss: 0.0476 2022/09/18 08:02:55 - mmengine - INFO - Epoch(train) [18][4400/10520] lr: 1.0000e-05 eta: 9:31:06 time: 1.0825 data_time: 0.0265 memory: 56769 loss_visual: 0.0498 loss: 0.0498 2022/09/18 08:05:00 - mmengine - INFO - Epoch(train) [18][4500/10520] lr: 1.0000e-05 eta: 9:28:59 time: 0.9120 data_time: 0.0069 memory: 56769 loss_visual: 0.0505 loss: 0.0505 2022/09/18 08:07:04 - mmengine - INFO - Epoch(train) [18][4600/10520] lr: 1.0000e-05 eta: 9:26:53 time: 0.9400 data_time: 0.0084 memory: 56769 loss_visual: 0.0488 loss: 0.0488 2022/09/18 08:09:10 - mmengine - INFO - Epoch(train) [18][4700/10520] lr: 1.0000e-05 eta: 9:24:47 time: 0.9383 data_time: 0.0076 memory: 56769 loss_visual: 0.0495 loss: 0.0495 2022/09/18 08:11:14 - mmengine - INFO - Epoch(train) [18][4800/10520] lr: 1.0000e-05 eta: 9:22:40 time: 0.8963 data_time: 0.0070 memory: 56769 loss_visual: 0.0475 loss: 0.0475 2022/09/18 08:13:27 - mmengine - INFO - Epoch(train) [18][4900/10520] lr: 1.0000e-05 eta: 9:20:35 time: 1.3018 data_time: 0.4437 memory: 56769 loss_visual: 0.0492 loss: 0.0492 2022/09/18 08:15:40 - mmengine - INFO - Epoch(train) [18][5000/10520] lr: 1.0000e-05 eta: 9:18:30 time: 2.1026 data_time: 0.7224 memory: 56769 loss_visual: 0.0497 loss: 0.0497 2022/09/18 08:17:49 - mmengine - INFO - Epoch(train) [18][5100/10520] lr: 1.0000e-05 eta: 9:16:24 time: 1.8553 data_time: 0.4180 memory: 56769 loss_visual: 0.0501 loss: 0.0501 2022/09/18 08:19:06 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 08:19:56 - mmengine - INFO - Epoch(train) [18][5200/10520] lr: 1.0000e-05 eta: 9:14:18 time: 1.1622 data_time: 0.0334 memory: 56769 loss_visual: 0.0480 loss: 0.0480 2022/09/18 08:22:01 - mmengine - INFO - Epoch(train) [18][5300/10520] lr: 1.0000e-05 eta: 9:12:12 time: 0.8679 data_time: 0.0071 memory: 56769 loss_visual: 0.0484 loss: 0.0484 2022/09/18 08:24:08 - mmengine - INFO - Epoch(train) [18][5400/10520] lr: 1.0000e-05 eta: 9:10:06 time: 0.9348 data_time: 0.0077 memory: 56769 loss_visual: 0.0475 loss: 0.0475 2022/09/18 08:26:14 - mmengine - INFO - Epoch(train) [18][5500/10520] lr: 1.0000e-05 eta: 9:07:59 time: 0.9656 data_time: 0.0071 memory: 56769 loss_visual: 0.0495 loss: 0.0495 2022/09/18 08:28:19 - mmengine - INFO - Epoch(train) [18][5600/10520] lr: 1.0000e-05 eta: 9:05:53 time: 0.8983 data_time: 0.0070 memory: 56769 loss_visual: 0.0504 loss: 0.0504 2022/09/18 08:30:30 - mmengine - INFO - Epoch(train) [18][5700/10520] lr: 1.0000e-05 eta: 9:03:48 time: 1.3376 data_time: 0.4874 memory: 56769 loss_visual: 0.0503 loss: 0.0503 2022/09/18 08:32:41 - mmengine - INFO - Epoch(train) [18][5800/10520] lr: 1.0000e-05 eta: 9:01:42 time: 2.0040 data_time: 0.7816 memory: 56769 loss_visual: 0.0485 loss: 0.0485 2022/09/18 08:34:49 - mmengine - INFO - Epoch(train) [18][5900/10520] lr: 1.0000e-05 eta: 8:59:36 time: 1.7065 data_time: 0.3751 memory: 56769 loss_visual: 0.0518 loss: 0.0518 2022/09/18 08:36:53 - mmengine - INFO - Epoch(train) [18][6000/10520] lr: 1.0000e-05 eta: 8:57:30 time: 1.0769 data_time: 0.0228 memory: 56769 loss_visual: 0.0505 loss: 0.0505 2022/09/18 08:38:58 - mmengine - INFO - Epoch(train) [18][6100/10520] lr: 1.0000e-05 eta: 8:55:23 time: 0.9239 data_time: 0.0081 memory: 56769 loss_visual: 0.0505 loss: 0.0505 2022/09/18 08:40:15 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 08:41:04 - mmengine - INFO - Epoch(train) [18][6200/10520] lr: 1.0000e-05 eta: 8:53:17 time: 0.9130 data_time: 0.0074 memory: 56769 loss_visual: 0.0514 loss: 0.0514 2022/09/18 08:43:10 - mmengine - INFO - Epoch(train) [18][6300/10520] lr: 1.0000e-05 eta: 8:51:11 time: 0.9453 data_time: 0.0071 memory: 56769 loss_visual: 0.0477 loss: 0.0477 2022/09/18 08:45:17 - mmengine - INFO - Epoch(train) [18][6400/10520] lr: 1.0000e-05 eta: 8:49:05 time: 0.9224 data_time: 0.0074 memory: 56769 loss_visual: 0.0498 loss: 0.0498 2022/09/18 08:47:29 - mmengine - INFO - Epoch(train) [18][6500/10520] lr: 1.0000e-05 eta: 8:46:59 time: 1.3419 data_time: 0.4860 memory: 56769 loss_visual: 0.0484 loss: 0.0484 2022/09/18 08:49:42 - mmengine - INFO - Epoch(train) [18][6600/10520] lr: 1.0000e-05 eta: 8:44:54 time: 2.1432 data_time: 0.8198 memory: 56769 loss_visual: 0.0469 loss: 0.0469 2022/09/18 08:51:49 - mmengine - INFO - Epoch(train) [18][6700/10520] lr: 1.0000e-05 eta: 8:42:48 time: 1.7321 data_time: 0.4020 memory: 56769 loss_visual: 0.0469 loss: 0.0469 2022/09/18 08:53:55 - mmengine - INFO - Epoch(train) [18][6800/10520] lr: 1.0000e-05 eta: 8:40:42 time: 1.0408 data_time: 0.0580 memory: 56769 loss_visual: 0.0489 loss: 0.0489 2022/09/18 08:56:01 - mmengine - INFO - Epoch(train) [18][6900/10520] lr: 1.0000e-05 eta: 8:38:36 time: 0.9059 data_time: 0.0071 memory: 56769 loss_visual: 0.0514 loss: 0.0514 2022/09/18 08:58:08 - mmengine - INFO - Epoch(train) [18][7000/10520] lr: 1.0000e-05 eta: 8:36:30 time: 0.9599 data_time: 0.0074 memory: 56769 loss_visual: 0.0483 loss: 0.0483 2022/09/18 09:00:13 - mmengine - INFO - Epoch(train) [18][7100/10520] lr: 1.0000e-05 eta: 8:34:23 time: 0.9385 data_time: 0.0083 memory: 56769 loss_visual: 0.0487 loss: 0.0487 2022/09/18 09:01:31 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 09:02:19 - mmengine - INFO - Epoch(train) [18][7200/10520] lr: 1.0000e-05 eta: 8:32:17 time: 0.8953 data_time: 0.0072 memory: 56769 loss_visual: 0.0471 loss: 0.0471 2022/09/18 09:04:32 - mmengine - INFO - Epoch(train) [18][7300/10520] lr: 1.0000e-05 eta: 8:30:12 time: 1.3210 data_time: 0.4642 memory: 56769 loss_visual: 0.0525 loss: 0.0525 2022/09/18 09:06:46 - mmengine - INFO - Epoch(train) [18][7400/10520] lr: 1.0000e-05 eta: 8:28:07 time: 2.0467 data_time: 0.7460 memory: 56769 loss_visual: 0.0524 loss: 0.0524 2022/09/18 09:08:54 - mmengine - INFO - Epoch(train) [18][7500/10520] lr: 1.0000e-05 eta: 8:26:01 time: 1.7572 data_time: 0.3772 memory: 56769 loss_visual: 0.0472 loss: 0.0472 2022/09/18 09:10:59 - mmengine - INFO - Epoch(train) [18][7600/10520] lr: 1.0000e-05 eta: 8:23:54 time: 1.1203 data_time: 0.0223 memory: 56769 loss_visual: 0.0468 loss: 0.0468 2022/09/18 09:13:06 - mmengine - INFO - Epoch(train) [18][7700/10520] lr: 1.0000e-05 eta: 8:21:48 time: 0.8753 data_time: 0.0071 memory: 56769 loss_visual: 0.0522 loss: 0.0522 2022/09/18 09:15:14 - mmengine - INFO - Epoch(train) [18][7800/10520] lr: 1.0000e-05 eta: 8:19:42 time: 0.9518 data_time: 0.0071 memory: 56769 loss_visual: 0.0513 loss: 0.0513 2022/09/18 09:17:18 - mmengine - INFO - Epoch(train) [18][7900/10520] lr: 1.0000e-05 eta: 8:17:36 time: 0.9505 data_time: 0.0070 memory: 56769 loss_visual: 0.0508 loss: 0.0508 2022/09/18 09:19:24 - mmengine - INFO - Epoch(train) [18][8000/10520] lr: 1.0000e-05 eta: 8:15:30 time: 0.8951 data_time: 0.0076 memory: 56769 loss_visual: 0.0516 loss: 0.0516 2022/09/18 09:21:35 - mmengine - INFO - Epoch(train) [18][8100/10520] lr: 1.0000e-05 eta: 8:13:24 time: 1.3249 data_time: 0.4720 memory: 56769 loss_visual: 0.0472 loss: 0.0472 2022/09/18 09:22:48 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 09:23:47 - mmengine - INFO - Epoch(train) [18][8200/10520] lr: 1.0000e-05 eta: 8:11:18 time: 2.0710 data_time: 0.6972 memory: 56769 loss_visual: 0.0480 loss: 0.0480 2022/09/18 09:25:54 - mmengine - INFO - Epoch(train) [18][8300/10520] lr: 1.0000e-05 eta: 8:09:12 time: 1.7865 data_time: 0.4365 memory: 56769 loss_visual: 0.0476 loss: 0.0476 2022/09/18 09:28:00 - mmengine - INFO - Epoch(train) [18][8400/10520] lr: 1.0000e-05 eta: 8:07:06 time: 1.0860 data_time: 0.0227 memory: 56769 loss_visual: 0.0492 loss: 0.0492 2022/09/18 09:30:06 - mmengine - INFO - Epoch(train) [18][8500/10520] lr: 1.0000e-05 eta: 8:05:00 time: 0.9214 data_time: 0.0080 memory: 56769 loss_visual: 0.0486 loss: 0.0486 2022/09/18 09:32:12 - mmengine - INFO - Epoch(train) [18][8600/10520] lr: 1.0000e-05 eta: 8:02:54 time: 0.9627 data_time: 0.0117 memory: 56769 loss_visual: 0.0466 loss: 0.0466 2022/09/18 09:34:19 - mmengine - INFO - Epoch(train) [18][8700/10520] lr: 1.0000e-05 eta: 8:00:48 time: 0.9304 data_time: 0.0079 memory: 56769 loss_visual: 0.0504 loss: 0.0504 2022/09/18 09:36:25 - mmengine - INFO - Epoch(train) [18][8800/10520] lr: 1.0000e-05 eta: 7:58:41 time: 0.9188 data_time: 0.0072 memory: 56769 loss_visual: 0.0519 loss: 0.0519 2022/09/18 09:38:35 - mmengine - INFO - Epoch(train) [18][8900/10520] lr: 1.0000e-05 eta: 7:56:35 time: 1.3269 data_time: 0.4873 memory: 56769 loss_visual: 0.0507 loss: 0.0507 2022/09/18 09:40:48 - mmengine - INFO - Epoch(train) [18][9000/10520] lr: 1.0000e-05 eta: 7:54:30 time: 2.0727 data_time: 0.7612 memory: 56769 loss_visual: 0.0496 loss: 0.0496 2022/09/18 09:42:52 - mmengine - INFO - Epoch(train) [18][9100/10520] lr: 1.0000e-05 eta: 7:52:24 time: 1.6968 data_time: 0.3919 memory: 56769 loss_visual: 0.0527 loss: 0.0527 2022/09/18 09:44:10 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 09:44:59 - mmengine - INFO - Epoch(train) [18][9200/10520] lr: 1.0000e-05 eta: 7:50:18 time: 1.1130 data_time: 0.0242 memory: 56769 loss_visual: 0.0481 loss: 0.0481 2022/09/18 09:47:06 - mmengine - INFO - Epoch(train) [18][9300/10520] lr: 1.0000e-05 eta: 7:48:11 time: 0.8812 data_time: 0.0072 memory: 56769 loss_visual: 0.0475 loss: 0.0475 2022/09/18 09:49:13 - mmengine - INFO - Epoch(train) [18][9400/10520] lr: 1.0000e-05 eta: 7:46:05 time: 1.0076 data_time: 0.0075 memory: 56769 loss_visual: 0.0511 loss: 0.0511 2022/09/18 09:51:19 - mmengine - INFO - Epoch(train) [18][9500/10520] lr: 1.0000e-05 eta: 7:43:59 time: 0.9145 data_time: 0.0070 memory: 56769 loss_visual: 0.0473 loss: 0.0473 2022/09/18 09:53:23 - mmengine - INFO - Epoch(train) [18][9600/10520] lr: 1.0000e-05 eta: 7:41:53 time: 0.9057 data_time: 0.0072 memory: 56769 loss_visual: 0.0481 loss: 0.0481 2022/09/18 09:55:32 - mmengine - INFO - Epoch(train) [18][9700/10520] lr: 1.0000e-05 eta: 7:39:47 time: 1.3148 data_time: 0.4675 memory: 56769 loss_visual: 0.0493 loss: 0.0493 2022/09/18 09:57:44 - mmengine - INFO - Epoch(train) [18][9800/10520] lr: 1.0000e-05 eta: 7:37:41 time: 1.9697 data_time: 0.6847 memory: 56769 loss_visual: 0.0516 loss: 0.0516 2022/09/18 09:59:50 - mmengine - INFO - Epoch(train) [18][9900/10520] lr: 1.0000e-05 eta: 7:35:35 time: 1.7177 data_time: 0.4007 memory: 56769 loss_visual: 0.0473 loss: 0.0473 2022/09/18 10:01:58 - mmengine - INFO - Epoch(train) [18][10000/10520] lr: 1.0000e-05 eta: 7:33:29 time: 1.1179 data_time: 0.0250 memory: 56769 loss_visual: 0.0483 loss: 0.0483 2022/09/18 10:04:05 - mmengine - INFO - Epoch(train) [18][10100/10520] lr: 1.0000e-05 eta: 7:31:23 time: 0.8932 data_time: 0.0077 memory: 56769 loss_visual: 0.0481 loss: 0.0481 2022/09/18 10:05:24 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 10:06:12 - mmengine - INFO - Epoch(train) [18][10200/10520] lr: 1.0000e-05 eta: 7:29:17 time: 0.9288 data_time: 0.0085 memory: 56769 loss_visual: 0.0475 loss: 0.0475 2022/09/18 10:08:17 - mmengine - INFO - Epoch(train) [18][10300/10520] lr: 1.0000e-05 eta: 7:27:10 time: 0.9033 data_time: 0.0079 memory: 56769 loss_visual: 0.0468 loss: 0.0468 2022/09/18 10:10:23 - mmengine - INFO - Epoch(train) [18][10400/10520] lr: 1.0000e-05 eta: 7:25:04 time: 0.9274 data_time: 0.0073 memory: 56769 loss_visual: 0.0484 loss: 0.0484 2022/09/18 10:12:28 - mmengine - INFO - Epoch(train) [18][10500/10520] lr: 1.0000e-05 eta: 7:22:58 time: 1.1498 data_time: 0.2979 memory: 56769 loss_visual: 0.0482 loss: 0.0482 2022/09/18 10:12:48 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 10:12:48 - mmengine - INFO - Saving checkpoint at 18 epochs 2022/09/18 10:13:06 - mmengine - INFO - Epoch(val) [18][100/3836] eta: 0:05:17 time: 0.0850 data_time: 0.0006 memory: 56769 2022/09/18 10:13:10 - mmengine - INFO - Epoch(val) [18][200/3836] eta: 0:00:40 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/18 10:13:11 - mmengine - INFO - Epoch(val) [18][300/3836] eta: 0:00:42 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/18 10:13:13 - mmengine - INFO - Epoch(val) [18][400/3836] eta: 0:00:38 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/18 10:13:14 - mmengine - INFO - Epoch(val) [18][500/3836] eta: 0:00:41 time: 0.0125 data_time: 0.0011 memory: 480 2022/09/18 10:13:15 - mmengine - INFO - Epoch(val) [18][600/3836] eta: 0:00:38 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/18 10:13:16 - mmengine - INFO - Epoch(val) [18][700/3836] eta: 0:00:36 time: 0.0117 data_time: 0.0006 memory: 480 2022/09/18 10:13:18 - mmengine - INFO - Epoch(val) [18][800/3836] eta: 0:00:35 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 10:13:19 - mmengine - INFO - Epoch(val) [18][900/3836] eta: 0:00:34 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 10:13:20 - mmengine - INFO - Epoch(val) [18][1000/3836] eta: 0:00:33 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/18 10:13:21 - mmengine - INFO - Epoch(val) [18][1100/3836] eta: 0:00:32 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/18 10:13:22 - mmengine - INFO - Epoch(val) [18][1200/3836] eta: 0:00:31 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 10:13:24 - mmengine - INFO - Epoch(val) [18][1300/3836] eta: 0:00:29 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 10:13:25 - mmengine - INFO - Epoch(val) [18][1400/3836] eta: 0:00:27 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/18 10:13:26 - mmengine - INFO - Epoch(val) [18][1500/3836] eta: 0:00:27 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 10:13:27 - mmengine - INFO - Epoch(val) [18][1600/3836] eta: 0:00:26 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/18 10:13:28 - mmengine - INFO - Epoch(val) [18][1700/3836] eta: 0:00:24 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 10:13:29 - mmengine - INFO - Epoch(val) [18][1800/3836] eta: 0:00:23 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 10:13:31 - mmengine - INFO - Epoch(val) [18][1900/3836] eta: 0:00:22 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 10:13:32 - mmengine - INFO - Epoch(val) [18][2000/3836] eta: 0:00:21 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 10:13:33 - mmengine - INFO - Epoch(val) [18][2100/3836] eta: 0:00:20 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/18 10:13:34 - mmengine - INFO - Epoch(val) [18][2200/3836] eta: 0:00:19 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 10:13:35 - mmengine - INFO - Epoch(val) [18][2300/3836] eta: 0:00:17 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 10:13:37 - mmengine - INFO - Epoch(val) [18][2400/3836] eta: 0:00:15 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/18 10:13:38 - mmengine - INFO - Epoch(val) [18][2500/3836] eta: 0:00:15 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 10:13:39 - mmengine - INFO - Epoch(val) [18][2600/3836] eta: 0:00:14 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 10:13:40 - mmengine - INFO - Epoch(val) [18][2700/3836] eta: 0:00:13 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 10:13:42 - mmengine - INFO - Epoch(val) [18][2800/3836] eta: 0:00:11 time: 0.0113 data_time: 0.0004 memory: 480 2022/09/18 10:13:43 - mmengine - INFO - Epoch(val) [18][2900/3836] eta: 0:00:10 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 10:13:44 - mmengine - INFO - Epoch(val) [18][3000/3836] eta: 0:00:09 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 10:13:45 - mmengine - INFO - Epoch(val) [18][3100/3836] eta: 0:00:08 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/18 10:13:46 - mmengine - INFO - Epoch(val) [18][3200/3836] eta: 0:00:07 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 10:13:48 - mmengine - INFO - Epoch(val) [18][3300/3836] eta: 0:00:05 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/18 10:13:49 - mmengine - INFO - Epoch(val) [18][3400/3836] eta: 0:00:04 time: 0.0110 data_time: 0.0005 memory: 480 2022/09/18 10:13:50 - mmengine - INFO - Epoch(val) [18][3500/3836] eta: 0:00:03 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/18 10:13:51 - mmengine - INFO - Epoch(val) [18][3600/3836] eta: 0:00:02 time: 0.0106 data_time: 0.0005 memory: 480 2022/09/18 10:13:52 - mmengine - INFO - Epoch(val) [18][3700/3836] eta: 0:00:01 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/18 10:13:53 - mmengine - INFO - Epoch(val) [18][3800/3836] eta: 0:00:00 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 10:13:54 - mmengine - INFO - Epoch(val) [18][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.8437 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9523 SVT/recog/word_acc_ignore_case_symbol: 0.9057 SVTP/recog/word_acc_ignore_case_symbol: 0.8403 IC13/recog/word_acc_ignore_case_symbol: 0.9369 IC15/recog/word_acc_ignore_case_symbol: 0.7886 2022/09/18 10:16:18 - mmengine - INFO - Epoch(train) [19][100/10520] lr: 1.0000e-06 eta: 7:20:28 time: 1.8137 data_time: 0.7180 memory: 56769 loss_visual: 0.0505 loss: 0.0505 2022/09/18 10:18:23 - mmengine - INFO - Epoch(train) [19][200/10520] lr: 1.0000e-06 eta: 7:18:22 time: 1.9688 data_time: 0.6354 memory: 56769 loss_visual: 0.0543 loss: 0.0543 2022/09/18 10:20:28 - mmengine - INFO - Epoch(train) [19][300/10520] lr: 1.0000e-06 eta: 7:16:15 time: 1.5771 data_time: 0.3583 memory: 56769 loss_visual: 0.0472 loss: 0.0472 2022/09/18 10:22:32 - mmengine - INFO - Epoch(train) [19][400/10520] lr: 1.0000e-06 eta: 7:14:09 time: 1.0936 data_time: 0.0076 memory: 56769 loss_visual: 0.0470 loss: 0.0470 2022/09/18 10:24:36 - mmengine - INFO - Epoch(train) [19][500/10520] lr: 1.0000e-06 eta: 7:12:02 time: 0.8995 data_time: 0.0070 memory: 56769 loss_visual: 0.0473 loss: 0.0473 2022/09/18 10:26:39 - mmengine - INFO - Epoch(train) [19][600/10520] lr: 1.0000e-06 eta: 7:09:56 time: 0.8661 data_time: 0.0072 memory: 56769 loss_visual: 0.0487 loss: 0.0487 2022/09/18 10:27:26 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 10:28:40 - mmengine - INFO - Epoch(train) [19][700/10520] lr: 1.0000e-06 eta: 7:07:49 time: 0.8276 data_time: 0.0071 memory: 56769 loss_visual: 0.0461 loss: 0.0461 2022/09/18 10:30:44 - mmengine - INFO - Epoch(train) [19][800/10520] lr: 1.0000e-06 eta: 7:05:42 time: 0.9649 data_time: 0.0911 memory: 56769 loss_visual: 0.0492 loss: 0.0492 2022/09/18 10:32:55 - mmengine - INFO - Epoch(train) [19][900/10520] lr: 1.0000e-06 eta: 7:03:37 time: 1.7789 data_time: 0.7078 memory: 56769 loss_visual: 0.0500 loss: 0.0500 2022/09/18 10:35:02 - mmengine - INFO - Epoch(train) [19][1000/10520] lr: 1.0000e-06 eta: 7:01:31 time: 2.0006 data_time: 0.6355 memory: 56769 loss_visual: 0.0472 loss: 0.0472 2022/09/18 10:37:07 - mmengine - INFO - Epoch(train) [19][1100/10520] lr: 1.0000e-06 eta: 6:59:24 time: 1.6072 data_time: 0.4207 memory: 56769 loss_visual: 0.0506 loss: 0.0506 2022/09/18 10:39:11 - mmengine - INFO - Epoch(train) [19][1200/10520] lr: 1.0000e-06 eta: 6:57:18 time: 1.0523 data_time: 0.0079 memory: 56769 loss_visual: 0.0502 loss: 0.0502 2022/09/18 10:41:14 - mmengine - INFO - Epoch(train) [19][1300/10520] lr: 1.0000e-06 eta: 6:55:11 time: 0.8739 data_time: 0.0072 memory: 56769 loss_visual: 0.0525 loss: 0.0525 2022/09/18 10:43:20 - mmengine - INFO - Epoch(train) [19][1400/10520] lr: 1.0000e-06 eta: 6:53:05 time: 0.8485 data_time: 0.0077 memory: 56769 loss_visual: 0.0509 loss: 0.0509 2022/09/18 10:45:24 - mmengine - INFO - Epoch(train) [19][1500/10520] lr: 1.0000e-06 eta: 6:50:59 time: 0.8591 data_time: 0.0076 memory: 56769 loss_visual: 0.0470 loss: 0.0470 2022/09/18 10:47:29 - mmengine - INFO - Epoch(train) [19][1600/10520] lr: 1.0000e-06 eta: 6:48:52 time: 0.9743 data_time: 0.1115 memory: 56769 loss_visual: 0.0498 loss: 0.0498 2022/09/18 10:48:28 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 10:49:41 - mmengine - INFO - Epoch(train) [19][1700/10520] lr: 1.0000e-06 eta: 6:46:47 time: 1.7645 data_time: 0.7371 memory: 56769 loss_visual: 0.0461 loss: 0.0461 2022/09/18 10:51:49 - mmengine - INFO - Epoch(train) [19][1800/10520] lr: 1.0000e-06 eta: 6:44:41 time: 2.0785 data_time: 0.7014 memory: 56769 loss_visual: 0.0466 loss: 0.0466 2022/09/18 10:53:53 - mmengine - INFO - Epoch(train) [19][1900/10520] lr: 1.0000e-06 eta: 6:42:34 time: 1.5932 data_time: 0.4318 memory: 56769 loss_visual: 0.0478 loss: 0.0478 2022/09/18 10:56:00 - mmengine - INFO - Epoch(train) [19][2000/10520] lr: 1.0000e-06 eta: 6:40:28 time: 1.0484 data_time: 0.0074 memory: 56769 loss_visual: 0.0495 loss: 0.0495 2022/09/18 10:58:04 - mmengine - INFO - Epoch(train) [19][2100/10520] lr: 1.0000e-06 eta: 6:38:22 time: 0.8719 data_time: 0.0075 memory: 56769 loss_visual: 0.0459 loss: 0.0459 2022/09/18 11:00:10 - mmengine - INFO - Epoch(train) [19][2200/10520] lr: 1.0000e-06 eta: 6:36:15 time: 0.8480 data_time: 0.0080 memory: 56769 loss_visual: 0.0489 loss: 0.0489 2022/09/18 11:02:16 - mmengine - INFO - Epoch(train) [19][2300/10520] lr: 1.0000e-06 eta: 6:34:09 time: 0.8772 data_time: 0.0070 memory: 56769 loss_visual: 0.0454 loss: 0.0454 2022/09/18 11:04:21 - mmengine - INFO - Epoch(train) [19][2400/10520] lr: 1.0000e-06 eta: 6:32:03 time: 0.9712 data_time: 0.0939 memory: 56769 loss_visual: 0.0449 loss: 0.0449 2022/09/18 11:06:32 - mmengine - INFO - Epoch(train) [19][2500/10520] lr: 1.0000e-06 eta: 6:29:57 time: 1.7735 data_time: 0.7462 memory: 56769 loss_visual: 0.0493 loss: 0.0493 2022/09/18 11:08:39 - mmengine - INFO - Epoch(train) [19][2600/10520] lr: 1.0000e-06 eta: 6:27:51 time: 2.0763 data_time: 0.7384 memory: 56769 loss_visual: 0.0471 loss: 0.0471 2022/09/18 11:09:26 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 11:10:42 - mmengine - INFO - Epoch(train) [19][2700/10520] lr: 1.0000e-06 eta: 6:25:45 time: 1.5933 data_time: 0.4168 memory: 56769 loss_visual: 0.0437 loss: 0.0437 2022/09/18 11:12:45 - mmengine - INFO - Epoch(train) [19][2800/10520] lr: 1.0000e-06 eta: 6:23:38 time: 1.0523 data_time: 0.0076 memory: 56769 loss_visual: 0.0499 loss: 0.0499 2022/09/18 11:14:50 - mmengine - INFO - Epoch(train) [19][2900/10520] lr: 1.0000e-06 eta: 6:21:32 time: 0.8819 data_time: 0.0098 memory: 56769 loss_visual: 0.0450 loss: 0.0450 2022/09/18 11:16:55 - mmengine - INFO - Epoch(train) [19][3000/10520] lr: 1.0000e-06 eta: 6:19:25 time: 0.8677 data_time: 0.0078 memory: 56769 loss_visual: 0.0464 loss: 0.0464 2022/09/18 11:19:00 - mmengine - INFO - Epoch(train) [19][3100/10520] lr: 1.0000e-06 eta: 6:17:19 time: 0.8988 data_time: 0.0073 memory: 56769 loss_visual: 0.0460 loss: 0.0460 2022/09/18 11:21:06 - mmengine - INFO - Epoch(train) [19][3200/10520] lr: 1.0000e-06 eta: 6:15:13 time: 0.9634 data_time: 0.0944 memory: 56769 loss_visual: 0.0435 loss: 0.0435 2022/09/18 11:23:20 - mmengine - INFO - Epoch(train) [19][3300/10520] lr: 1.0000e-06 eta: 6:13:07 time: 1.7977 data_time: 0.7288 memory: 56769 loss_visual: 0.0474 loss: 0.0474 2022/09/18 11:25:27 - mmengine - INFO - Epoch(train) [19][3400/10520] lr: 1.0000e-06 eta: 6:11:01 time: 2.0765 data_time: 0.7022 memory: 56769 loss_visual: 0.0441 loss: 0.0441 2022/09/18 11:27:31 - mmengine - INFO - Epoch(train) [19][3500/10520] lr: 1.0000e-06 eta: 6:08:55 time: 1.6243 data_time: 0.4066 memory: 56769 loss_visual: 0.0496 loss: 0.0496 2022/09/18 11:29:35 - mmengine - INFO - Epoch(train) [19][3600/10520] lr: 1.0000e-06 eta: 6:06:48 time: 1.0855 data_time: 0.0070 memory: 56769 loss_visual: 0.0498 loss: 0.0498 2022/09/18 11:30:22 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 11:31:39 - mmengine - INFO - Epoch(train) [19][3700/10520] lr: 1.0000e-06 eta: 6:04:42 time: 0.8516 data_time: 0.0074 memory: 56769 loss_visual: 0.0500 loss: 0.0500 2022/09/18 11:33:42 - mmengine - INFO - Epoch(train) [19][3800/10520] lr: 1.0000e-06 eta: 6:02:36 time: 0.8668 data_time: 0.0076 memory: 56769 loss_visual: 0.0475 loss: 0.0475 2022/09/18 11:35:45 - mmengine - INFO - Epoch(train) [19][3900/10520] lr: 1.0000e-06 eta: 6:00:29 time: 0.8341 data_time: 0.0087 memory: 56769 loss_visual: 0.0513 loss: 0.0513 2022/09/18 11:37:50 - mmengine - INFO - Epoch(train) [19][4000/10520] lr: 1.0000e-06 eta: 5:58:23 time: 0.9911 data_time: 0.0587 memory: 56769 loss_visual: 0.0471 loss: 0.0471 2022/09/18 11:40:01 - mmengine - INFO - Epoch(train) [19][4100/10520] lr: 1.0000e-06 eta: 5:56:17 time: 1.7164 data_time: 0.6836 memory: 56769 loss_visual: 0.0532 loss: 0.0532 2022/09/18 11:42:08 - mmengine - INFO - Epoch(train) [19][4200/10520] lr: 1.0000e-06 eta: 5:54:11 time: 2.0375 data_time: 0.6545 memory: 56769 loss_visual: 0.0508 loss: 0.0508 2022/09/18 11:44:11 - mmengine - INFO - Epoch(train) [19][4300/10520] lr: 1.0000e-06 eta: 5:52:04 time: 1.6203 data_time: 0.4016 memory: 56769 loss_visual: 0.0497 loss: 0.0497 2022/09/18 11:46:16 - mmengine - INFO - Epoch(train) [19][4400/10520] lr: 1.0000e-06 eta: 5:49:58 time: 1.0706 data_time: 0.0075 memory: 56769 loss_visual: 0.0468 loss: 0.0468 2022/09/18 11:48:21 - mmengine - INFO - Epoch(train) [19][4500/10520] lr: 1.0000e-06 eta: 5:47:52 time: 0.8691 data_time: 0.0075 memory: 56769 loss_visual: 0.0450 loss: 0.0450 2022/09/18 11:50:24 - mmengine - INFO - Epoch(train) [19][4600/10520] lr: 1.0000e-06 eta: 5:45:45 time: 0.8245 data_time: 0.0072 memory: 56769 loss_visual: 0.0523 loss: 0.0523 2022/09/18 11:51:13 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 11:52:30 - mmengine - INFO - Epoch(train) [19][4700/10520] lr: 1.0000e-06 eta: 5:43:39 time: 0.8762 data_time: 0.0075 memory: 56769 loss_visual: 0.0501 loss: 0.0501 2022/09/18 11:54:35 - mmengine - INFO - Epoch(train) [19][4800/10520] lr: 1.0000e-06 eta: 5:41:33 time: 0.9568 data_time: 0.0678 memory: 56769 loss_visual: 0.0501 loss: 0.0501 2022/09/18 11:56:46 - mmengine - INFO - Epoch(train) [19][4900/10520] lr: 1.0000e-06 eta: 5:39:27 time: 1.7157 data_time: 0.7167 memory: 56769 loss_visual: 0.0456 loss: 0.0456 2022/09/18 11:58:53 - mmengine - INFO - Epoch(train) [19][5000/10520] lr: 1.0000e-06 eta: 5:37:21 time: 2.0523 data_time: 0.6316 memory: 56769 loss_visual: 0.0459 loss: 0.0459 2022/09/18 12:00:59 - mmengine - INFO - Epoch(train) [19][5100/10520] lr: 1.0000e-06 eta: 5:35:15 time: 1.6187 data_time: 0.4190 memory: 56769 loss_visual: 0.0486 loss: 0.0486 2022/09/18 12:03:03 - mmengine - INFO - Epoch(train) [19][5200/10520] lr: 1.0000e-06 eta: 5:33:08 time: 1.1390 data_time: 0.0077 memory: 56769 loss_visual: 0.0523 loss: 0.0523 2022/09/18 12:05:07 - mmengine - INFO - Epoch(train) [19][5300/10520] lr: 1.0000e-06 eta: 5:31:02 time: 0.8605 data_time: 0.0074 memory: 56769 loss_visual: 0.0492 loss: 0.0492 2022/09/18 12:07:10 - mmengine - INFO - Epoch(train) [19][5400/10520] lr: 1.0000e-06 eta: 5:28:55 time: 0.8274 data_time: 0.0071 memory: 56769 loss_visual: 0.0504 loss: 0.0504 2022/09/18 12:09:15 - mmengine - INFO - Epoch(train) [19][5500/10520] lr: 1.0000e-06 eta: 5:26:49 time: 0.8482 data_time: 0.0074 memory: 56769 loss_visual: 0.0498 loss: 0.0498 2022/09/18 12:11:20 - mmengine - INFO - Epoch(train) [19][5600/10520] lr: 1.0000e-06 eta: 5:24:43 time: 0.9656 data_time: 0.1008 memory: 56769 loss_visual: 0.0495 loss: 0.0495 2022/09/18 12:12:18 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 12:13:32 - mmengine - INFO - Epoch(train) [19][5700/10520] lr: 1.0000e-06 eta: 5:22:37 time: 1.7639 data_time: 0.7541 memory: 56769 loss_visual: 0.0462 loss: 0.0462 2022/09/18 12:15:42 - mmengine - INFO - Epoch(train) [19][5800/10520] lr: 1.0000e-06 eta: 5:20:31 time: 1.9894 data_time: 0.6863 memory: 56769 loss_visual: 0.0471 loss: 0.0471 2022/09/18 12:17:47 - mmengine - INFO - Epoch(train) [19][5900/10520] lr: 1.0000e-06 eta: 5:18:25 time: 1.6797 data_time: 0.4766 memory: 56769 loss_visual: 0.0466 loss: 0.0466 2022/09/18 12:19:52 - mmengine - INFO - Epoch(train) [19][6000/10520] lr: 1.0000e-06 eta: 5:16:19 time: 1.0914 data_time: 0.0080 memory: 56769 loss_visual: 0.0518 loss: 0.0518 2022/09/18 12:21:58 - mmengine - INFO - Epoch(train) [19][6100/10520] lr: 1.0000e-06 eta: 5:14:12 time: 0.8929 data_time: 0.0088 memory: 56769 loss_visual: 0.0487 loss: 0.0487 2022/09/18 12:24:02 - mmengine - INFO - Epoch(train) [19][6200/10520] lr: 1.0000e-06 eta: 5:12:06 time: 0.8718 data_time: 0.0082 memory: 56769 loss_visual: 0.0468 loss: 0.0468 2022/09/18 12:26:07 - mmengine - INFO - Epoch(train) [19][6300/10520] lr: 1.0000e-06 eta: 5:10:00 time: 0.8993 data_time: 0.0099 memory: 56769 loss_visual: 0.0517 loss: 0.0517 2022/09/18 12:28:12 - mmengine - INFO - Epoch(train) [19][6400/10520] lr: 1.0000e-06 eta: 5:07:54 time: 0.9588 data_time: 0.0549 memory: 56769 loss_visual: 0.0517 loss: 0.0517 2022/09/18 12:30:24 - mmengine - INFO - Epoch(train) [19][6500/10520] lr: 1.0000e-06 eta: 5:05:48 time: 1.8396 data_time: 0.8015 memory: 56769 loss_visual: 0.0515 loss: 0.0515 2022/09/18 12:32:34 - mmengine - INFO - Epoch(train) [19][6600/10520] lr: 1.0000e-06 eta: 5:03:42 time: 2.0673 data_time: 0.7347 memory: 56769 loss_visual: 0.0494 loss: 0.0494 2022/09/18 12:33:20 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 12:34:38 - mmengine - INFO - Epoch(train) [19][6700/10520] lr: 1.0000e-06 eta: 5:01:35 time: 1.6325 data_time: 0.4225 memory: 56769 loss_visual: 0.0488 loss: 0.0488 2022/09/18 12:36:42 - mmengine - INFO - Epoch(train) [19][6800/10520] lr: 1.0000e-06 eta: 4:59:29 time: 1.0544 data_time: 0.0074 memory: 56769 loss_visual: 0.0472 loss: 0.0472 2022/09/18 12:38:46 - mmengine - INFO - Epoch(train) [19][6900/10520] lr: 1.0000e-06 eta: 4:57:23 time: 0.8440 data_time: 0.0071 memory: 56769 loss_visual: 0.0490 loss: 0.0490 2022/09/18 12:40:49 - mmengine - INFO - Epoch(train) [19][7000/10520] lr: 1.0000e-06 eta: 4:55:16 time: 0.8361 data_time: 0.0070 memory: 56769 loss_visual: 0.0504 loss: 0.0504 2022/09/18 12:42:53 - mmengine - INFO - Epoch(train) [19][7100/10520] lr: 1.0000e-06 eta: 4:53:10 time: 0.8719 data_time: 0.0076 memory: 56769 loss_visual: 0.0457 loss: 0.0457 2022/09/18 12:44:57 - mmengine - INFO - Epoch(train) [19][7200/10520] lr: 1.0000e-06 eta: 4:51:04 time: 0.9531 data_time: 0.0933 memory: 56769 loss_visual: 0.0475 loss: 0.0475 2022/09/18 12:47:09 - mmengine - INFO - Epoch(train) [19][7300/10520] lr: 1.0000e-06 eta: 4:48:58 time: 1.8171 data_time: 0.7613 memory: 56769 loss_visual: 0.0495 loss: 0.0495 2022/09/18 12:49:18 - mmengine - INFO - Epoch(train) [19][7400/10520] lr: 1.0000e-06 eta: 4:46:52 time: 2.0948 data_time: 0.7333 memory: 56769 loss_visual: 0.0496 loss: 0.0496 2022/09/18 12:51:26 - mmengine - INFO - Epoch(train) [19][7500/10520] lr: 1.0000e-06 eta: 4:44:46 time: 1.6917 data_time: 0.4807 memory: 56769 loss_visual: 0.0480 loss: 0.0480 2022/09/18 12:53:31 - mmengine - INFO - Epoch(train) [19][7600/10520] lr: 1.0000e-06 eta: 4:42:40 time: 1.1209 data_time: 0.0079 memory: 56769 loss_visual: 0.0438 loss: 0.0438 2022/09/18 12:54:18 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 12:55:35 - mmengine - INFO - Epoch(train) [19][7700/10520] lr: 1.0000e-06 eta: 4:40:33 time: 0.8330 data_time: 0.0072 memory: 56769 loss_visual: 0.0457 loss: 0.0457 2022/09/18 12:57:39 - mmengine - INFO - Epoch(train) [19][7800/10520] lr: 1.0000e-06 eta: 4:38:27 time: 0.8341 data_time: 0.0074 memory: 56769 loss_visual: 0.0499 loss: 0.0499 2022/09/18 12:59:42 - mmengine - INFO - Epoch(train) [19][7900/10520] lr: 1.0000e-06 eta: 4:36:20 time: 0.8705 data_time: 0.0072 memory: 56769 loss_visual: 0.0472 loss: 0.0472 2022/09/18 13:01:48 - mmengine - INFO - Epoch(train) [19][8000/10520] lr: 1.0000e-06 eta: 4:34:14 time: 0.9340 data_time: 0.0963 memory: 56769 loss_visual: 0.0455 loss: 0.0455 2022/09/18 13:04:01 - mmengine - INFO - Epoch(train) [19][8100/10520] lr: 1.0000e-06 eta: 4:32:08 time: 1.7900 data_time: 0.7416 memory: 56769 loss_visual: 0.0488 loss: 0.0488 2022/09/18 13:06:08 - mmengine - INFO - Epoch(train) [19][8200/10520] lr: 1.0000e-06 eta: 4:30:02 time: 2.0314 data_time: 0.6800 memory: 56769 loss_visual: 0.0458 loss: 0.0458 2022/09/18 13:08:11 - mmengine - INFO - Epoch(train) [19][8300/10520] lr: 1.0000e-06 eta: 4:27:56 time: 1.6382 data_time: 0.4066 memory: 56769 loss_visual: 0.0481 loss: 0.0481 2022/09/18 13:10:15 - mmengine - INFO - Epoch(train) [19][8400/10520] lr: 1.0000e-06 eta: 4:25:50 time: 1.0936 data_time: 0.0073 memory: 56769 loss_visual: 0.0455 loss: 0.0455 2022/09/18 13:12:19 - mmengine - INFO - Epoch(train) [19][8500/10520] lr: 1.0000e-06 eta: 4:23:43 time: 0.8692 data_time: 0.0073 memory: 56769 loss_visual: 0.0510 loss: 0.0510 2022/09/18 13:14:22 - mmengine - INFO - Epoch(train) [19][8600/10520] lr: 1.0000e-06 eta: 4:21:37 time: 0.8321 data_time: 0.0069 memory: 56769 loss_visual: 0.0452 loss: 0.0452 2022/09/18 13:15:10 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 13:16:27 - mmengine - INFO - Epoch(train) [19][8700/10520] lr: 1.0000e-06 eta: 4:19:31 time: 0.8641 data_time: 0.0069 memory: 56769 loss_visual: 0.0489 loss: 0.0489 2022/09/18 13:18:33 - mmengine - INFO - Epoch(train) [19][8800/10520] lr: 1.0000e-06 eta: 4:17:24 time: 0.9490 data_time: 0.1114 memory: 56769 loss_visual: 0.0471 loss: 0.0471 2022/09/18 13:20:44 - mmengine - INFO - Epoch(train) [19][8900/10520] lr: 1.0000e-06 eta: 4:15:19 time: 1.7072 data_time: 0.6900 memory: 56769 loss_visual: 0.0495 loss: 0.0495 2022/09/18 13:22:50 - mmengine - INFO - Epoch(train) [19][9000/10520] lr: 1.0000e-06 eta: 4:13:12 time: 2.0618 data_time: 0.6775 memory: 56769 loss_visual: 0.0488 loss: 0.0488 2022/09/18 13:24:53 - mmengine - INFO - Epoch(train) [19][9100/10520] lr: 1.0000e-06 eta: 4:11:06 time: 1.6166 data_time: 0.4008 memory: 56769 loss_visual: 0.0487 loss: 0.0487 2022/09/18 13:26:57 - mmengine - INFO - Epoch(train) [19][9200/10520] lr: 1.0000e-06 eta: 4:09:00 time: 1.0645 data_time: 0.0074 memory: 56769 loss_visual: 0.0491 loss: 0.0491 2022/09/18 13:29:01 - mmengine - INFO - Epoch(train) [19][9300/10520] lr: 1.0000e-06 eta: 4:06:53 time: 0.8963 data_time: 0.0078 memory: 56769 loss_visual: 0.0512 loss: 0.0512 2022/09/18 13:31:04 - mmengine - INFO - Epoch(train) [19][9400/10520] lr: 1.0000e-06 eta: 4:04:47 time: 0.8312 data_time: 0.0073 memory: 56769 loss_visual: 0.0501 loss: 0.0501 2022/09/18 13:33:07 - mmengine - INFO - Epoch(train) [19][9500/10520] lr: 1.0000e-06 eta: 4:02:41 time: 0.8870 data_time: 0.0072 memory: 56769 loss_visual: 0.0474 loss: 0.0474 2022/09/18 13:35:11 - mmengine - INFO - Epoch(train) [19][9600/10520] lr: 1.0000e-06 eta: 4:00:34 time: 0.9487 data_time: 0.0891 memory: 56769 loss_visual: 0.0537 loss: 0.0537 2022/09/18 13:36:10 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 13:37:25 - mmengine - INFO - Epoch(train) [19][9700/10520] lr: 1.0000e-06 eta: 3:58:29 time: 1.7923 data_time: 0.7665 memory: 56769 loss_visual: 0.0462 loss: 0.0462 2022/09/18 13:39:35 - mmengine - INFO - Epoch(train) [19][9800/10520] lr: 1.0000e-06 eta: 3:56:23 time: 2.0575 data_time: 0.7305 memory: 56769 loss_visual: 0.0477 loss: 0.0477 2022/09/18 13:41:39 - mmengine - INFO - Epoch(train) [19][9900/10520] lr: 1.0000e-06 eta: 3:54:16 time: 1.6818 data_time: 0.4496 memory: 56769 loss_visual: 0.0451 loss: 0.0451 2022/09/18 13:43:44 - mmengine - INFO - Epoch(train) [19][10000/10520] lr: 1.0000e-06 eta: 3:52:10 time: 1.0669 data_time: 0.0079 memory: 56769 loss_visual: 0.0465 loss: 0.0465 2022/09/18 13:45:48 - mmengine - INFO - Epoch(train) [19][10100/10520] lr: 1.0000e-06 eta: 3:50:04 time: 0.8652 data_time: 0.0076 memory: 56769 loss_visual: 0.0491 loss: 0.0491 2022/09/18 13:47:53 - mmengine - INFO - Epoch(train) [19][10200/10520] lr: 1.0000e-06 eta: 3:47:57 time: 0.8684 data_time: 0.0081 memory: 56769 loss_visual: 0.0496 loss: 0.0496 2022/09/18 13:49:58 - mmengine - INFO - Epoch(train) [19][10300/10520] lr: 1.0000e-06 eta: 3:45:51 time: 0.8639 data_time: 0.0076 memory: 56769 loss_visual: 0.0442 loss: 0.0442 2022/09/18 13:52:02 - mmengine - INFO - Epoch(train) [19][10400/10520] lr: 1.0000e-06 eta: 3:43:45 time: 1.0045 data_time: 0.1180 memory: 56769 loss_visual: 0.0484 loss: 0.0484 2022/09/18 13:54:07 - mmengine - INFO - Epoch(train) [19][10500/10520] lr: 1.0000e-06 eta: 3:41:39 time: 1.3101 data_time: 0.4055 memory: 56769 loss_visual: 0.0510 loss: 0.0510 2022/09/18 13:54:25 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 13:54:25 - mmengine - INFO - Saving checkpoint at 19 epochs 2022/09/18 13:54:43 - mmengine - INFO - Epoch(val) [19][100/3836] eta: 0:05:04 time: 0.0815 data_time: 0.0006 memory: 56769 2022/09/18 13:54:48 - mmengine - INFO - Epoch(val) [19][200/3836] eta: 0:00:43 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/18 13:54:49 - mmengine - INFO - Epoch(val) [19][300/3836] eta: 0:00:41 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 13:54:50 - mmengine - INFO - Epoch(val) [19][400/3836] eta: 0:00:40 time: 0.0118 data_time: 0.0006 memory: 480 2022/09/18 13:54:52 - mmengine - INFO - Epoch(val) [19][500/3836] eta: 0:00:39 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 13:54:53 - mmengine - INFO - Epoch(val) [19][600/3836] eta: 0:00:39 time: 0.0121 data_time: 0.0005 memory: 480 2022/09/18 13:54:54 - mmengine - INFO - Epoch(val) [19][700/3836] eta: 0:00:37 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/18 13:54:55 - mmengine - INFO - Epoch(val) [19][800/3836] eta: 0:00:34 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 13:54:56 - mmengine - INFO - Epoch(val) [19][900/3836] eta: 0:00:35 time: 0.0120 data_time: 0.0006 memory: 480 2022/09/18 13:54:58 - mmengine - INFO - Epoch(val) [19][1000/3836] eta: 0:00:33 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/18 13:54:59 - mmengine - INFO - Epoch(val) [19][1100/3836] eta: 0:00:32 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/18 13:55:00 - mmengine - INFO - Epoch(val) [19][1200/3836] eta: 0:00:31 time: 0.0121 data_time: 0.0005 memory: 480 2022/09/18 13:55:01 - mmengine - INFO - Epoch(val) [19][1300/3836] eta: 0:00:29 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 13:55:02 - mmengine - INFO - Epoch(val) [19][1400/3836] eta: 0:00:26 time: 0.0110 data_time: 0.0005 memory: 480 2022/09/18 13:55:04 - mmengine - INFO - Epoch(val) [19][1500/3836] eta: 0:00:26 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 13:55:05 - mmengine - INFO - Epoch(val) [19][1600/3836] eta: 0:00:26 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 13:55:06 - mmengine - INFO - Epoch(val) [19][1700/3836] eta: 0:00:24 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 13:55:07 - mmengine - INFO - Epoch(val) [19][1800/3836] eta: 0:00:23 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 13:55:08 - mmengine - INFO - Epoch(val) [19][1900/3836] eta: 0:00:22 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 13:55:10 - mmengine - INFO - Epoch(val) [19][2000/3836] eta: 0:00:21 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 13:55:11 - mmengine - INFO - Epoch(val) [19][2100/3836] eta: 0:00:22 time: 0.0128 data_time: 0.0005 memory: 480 2022/09/18 13:55:12 - mmengine - INFO - Epoch(val) [19][2200/3836] eta: 0:00:19 time: 0.0118 data_time: 0.0005 memory: 480 2022/09/18 13:55:13 - mmengine - INFO - Epoch(val) [19][2300/3836] eta: 0:00:17 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/18 13:55:14 - mmengine - INFO - Epoch(val) [19][2400/3836] eta: 0:00:16 time: 0.0117 data_time: 0.0006 memory: 480 2022/09/18 13:55:16 - mmengine - INFO - Epoch(val) [19][2500/3836] eta: 0:00:15 time: 0.0118 data_time: 0.0006 memory: 480 2022/09/18 13:55:17 - mmengine - INFO - Epoch(val) [19][2600/3836] eta: 0:00:14 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/18 13:55:18 - mmengine - INFO - Epoch(val) [19][2700/3836] eta: 0:00:12 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/18 13:55:19 - mmengine - INFO - Epoch(val) [19][2800/3836] eta: 0:00:12 time: 0.0118 data_time: 0.0004 memory: 480 2022/09/18 13:55:21 - mmengine - INFO - Epoch(val) [19][2900/3836] eta: 0:00:11 time: 0.0121 data_time: 0.0005 memory: 480 2022/09/18 13:55:22 - mmengine - INFO - Epoch(val) [19][3000/3836] eta: 0:00:09 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 13:55:23 - mmengine - INFO - Epoch(val) [19][3100/3836] eta: 0:00:08 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/18 13:55:24 - mmengine - INFO - Epoch(val) [19][3200/3836] eta: 0:00:07 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/18 13:55:25 - mmengine - INFO - Epoch(val) [19][3300/3836] eta: 0:00:06 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 13:55:26 - mmengine - INFO - Epoch(val) [19][3400/3836] eta: 0:00:04 time: 0.0112 data_time: 0.0005 memory: 480 2022/09/18 13:55:28 - mmengine - INFO - Epoch(val) [19][3500/3836] eta: 0:00:03 time: 0.0109 data_time: 0.0005 memory: 480 2022/09/18 13:55:29 - mmengine - INFO - Epoch(val) [19][3600/3836] eta: 0:00:02 time: 0.0110 data_time: 0.0005 memory: 480 2022/09/18 13:55:30 - mmengine - INFO - Epoch(val) [19][3700/3836] eta: 0:00:01 time: 0.0131 data_time: 0.0005 memory: 480 2022/09/18 13:55:31 - mmengine - INFO - Epoch(val) [19][3800/3836] eta: 0:00:00 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 13:55:32 - mmengine - INFO - Epoch(val) [19][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.8472 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9537 SVT/recog/word_acc_ignore_case_symbol: 0.9026 SVTP/recog/word_acc_ignore_case_symbol: 0.8388 IC13/recog/word_acc_ignore_case_symbol: 0.9350 IC15/recog/word_acc_ignore_case_symbol: 0.7891 2022/09/18 13:57:57 - mmengine - INFO - Epoch(train) [20][100/10520] lr: 1.0000e-06 eta: 3:39:08 time: 1.6053 data_time: 0.4247 memory: 56769 loss_visual: 0.0480 loss: 0.0480 2022/09/18 13:58:20 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 14:00:03 - mmengine - INFO - Epoch(train) [20][200/10520] lr: 1.0000e-06 eta: 3:37:02 time: 1.7026 data_time: 0.5849 memory: 56769 loss_visual: 0.0466 loss: 0.0466 2022/09/18 14:02:11 - mmengine - INFO - Epoch(train) [20][300/10520] lr: 1.0000e-06 eta: 3:34:56 time: 1.1769 data_time: 0.2653 memory: 56769 loss_visual: 0.0460 loss: 0.0460 2022/09/18 14:04:18 - mmengine - INFO - Epoch(train) [20][400/10520] lr: 1.0000e-06 eta: 3:32:49 time: 1.2677 data_time: 0.1938 memory: 56769 loss_visual: 0.0473 loss: 0.0473 2022/09/18 14:06:24 - mmengine - INFO - Epoch(train) [20][500/10520] lr: 1.0000e-06 eta: 3:30:43 time: 1.1469 data_time: 0.0572 memory: 56769 loss_visual: 0.0500 loss: 0.0500 2022/09/18 14:08:29 - mmengine - INFO - Epoch(train) [20][600/10520] lr: 1.0000e-06 eta: 3:28:37 time: 0.8897 data_time: 0.0260 memory: 56769 loss_visual: 0.0501 loss: 0.0501 2022/09/18 14:10:35 - mmengine - INFO - Epoch(train) [20][700/10520] lr: 1.0000e-06 eta: 3:26:31 time: 0.9155 data_time: 0.0295 memory: 56769 loss_visual: 0.0496 loss: 0.0496 2022/09/18 14:12:40 - mmengine - INFO - Epoch(train) [20][800/10520] lr: 1.0000e-06 eta: 3:24:25 time: 0.8979 data_time: 0.0248 memory: 56769 loss_visual: 0.0487 loss: 0.0487 2022/09/18 14:14:53 - mmengine - INFO - Epoch(train) [20][900/10520] lr: 1.0000e-06 eta: 3:22:19 time: 1.5835 data_time: 0.4257 memory: 56769 loss_visual: 0.0460 loss: 0.0460 2022/09/18 14:17:00 - mmengine - INFO - Epoch(train) [20][1000/10520] lr: 1.0000e-06 eta: 3:20:13 time: 1.7048 data_time: 0.6029 memory: 56769 loss_visual: 0.0479 loss: 0.0479 2022/09/18 14:19:07 - mmengine - INFO - Epoch(train) [20][1100/10520] lr: 1.0000e-06 eta: 3:18:06 time: 1.1505 data_time: 0.3168 memory: 56769 loss_visual: 0.0458 loss: 0.0458 2022/09/18 14:19:27 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 14:21:15 - mmengine - INFO - Epoch(train) [20][1200/10520] lr: 1.0000e-06 eta: 3:16:00 time: 1.2670 data_time: 0.1627 memory: 56769 loss_visual: 0.0490 loss: 0.0490 2022/09/18 14:23:20 - mmengine - INFO - Epoch(train) [20][1300/10520] lr: 1.0000e-06 eta: 3:13:54 time: 1.1592 data_time: 0.0582 memory: 56769 loss_visual: 0.0457 loss: 0.0457 2022/09/18 14:25:25 - mmengine - INFO - Epoch(train) [20][1400/10520] lr: 1.0000e-06 eta: 3:11:48 time: 0.8926 data_time: 0.0252 memory: 56769 loss_visual: 0.0466 loss: 0.0466 2022/09/18 14:27:29 - mmengine - INFO - Epoch(train) [20][1500/10520] lr: 1.0000e-06 eta: 3:09:41 time: 0.8874 data_time: 0.0234 memory: 56769 loss_visual: 0.0463 loss: 0.0463 2022/09/18 14:29:35 - mmengine - INFO - Epoch(train) [20][1600/10520] lr: 1.0000e-06 eta: 3:07:35 time: 0.8943 data_time: 0.0238 memory: 56769 loss_visual: 0.0480 loss: 0.0480 2022/09/18 14:31:46 - mmengine - INFO - Epoch(train) [20][1700/10520] lr: 1.0000e-06 eta: 3:05:29 time: 1.5668 data_time: 0.4181 memory: 56769 loss_visual: 0.0494 loss: 0.0494 2022/09/18 14:33:52 - mmengine - INFO - Epoch(train) [20][1800/10520] lr: 1.0000e-06 eta: 3:03:23 time: 1.7063 data_time: 0.5888 memory: 56769 loss_visual: 0.0482 loss: 0.0482 2022/09/18 14:35:58 - mmengine - INFO - Epoch(train) [20][1900/10520] lr: 1.0000e-06 eta: 3:01:17 time: 1.1765 data_time: 0.3097 memory: 56769 loss_visual: 0.0478 loss: 0.0478 2022/09/18 14:38:06 - mmengine - INFO - Epoch(train) [20][2000/10520] lr: 1.0000e-06 eta: 2:59:11 time: 1.3284 data_time: 0.2364 memory: 56769 loss_visual: 0.0508 loss: 0.0508 2022/09/18 14:40:12 - mmengine - INFO - Epoch(train) [20][2100/10520] lr: 1.0000e-06 eta: 2:57:05 time: 1.1696 data_time: 0.0940 memory: 56769 loss_visual: 0.0498 loss: 0.0498 2022/09/18 14:40:38 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 14:42:17 - mmengine - INFO - Epoch(train) [20][2200/10520] lr: 1.0000e-06 eta: 2:54:58 time: 0.8839 data_time: 0.0257 memory: 56769 loss_visual: 0.0478 loss: 0.0478 2022/09/18 14:44:22 - mmengine - INFO - Epoch(train) [20][2300/10520] lr: 1.0000e-06 eta: 2:52:52 time: 0.8992 data_time: 0.0255 memory: 56769 loss_visual: 0.0516 loss: 0.0516 2022/09/18 14:46:30 - mmengine - INFO - Epoch(train) [20][2400/10520] lr: 1.0000e-06 eta: 2:50:46 time: 0.9354 data_time: 0.0251 memory: 56769 loss_visual: 0.0492 loss: 0.0492 2022/09/18 14:48:43 - mmengine - INFO - Epoch(train) [20][2500/10520] lr: 1.0000e-06 eta: 2:48:40 time: 1.6036 data_time: 0.3729 memory: 56769 loss_visual: 0.0486 loss: 0.0486 2022/09/18 14:50:50 - mmengine - INFO - Epoch(train) [20][2600/10520] lr: 1.0000e-06 eta: 2:46:34 time: 1.7500 data_time: 0.5769 memory: 56769 loss_visual: 0.0462 loss: 0.0462 2022/09/18 14:52:57 - mmengine - INFO - Epoch(train) [20][2700/10520] lr: 1.0000e-06 eta: 2:44:28 time: 1.1811 data_time: 0.3444 memory: 56769 loss_visual: 0.0481 loss: 0.0481 2022/09/18 14:55:07 - mmengine - INFO - Epoch(train) [20][2800/10520] lr: 1.0000e-06 eta: 2:42:22 time: 1.2912 data_time: 0.2131 memory: 56769 loss_visual: 0.0464 loss: 0.0464 2022/09/18 14:57:12 - mmengine - INFO - Epoch(train) [20][2900/10520] lr: 1.0000e-06 eta: 2:40:15 time: 1.1260 data_time: 0.0538 memory: 56769 loss_visual: 0.0466 loss: 0.0466 2022/09/18 14:59:18 - mmengine - INFO - Epoch(train) [20][3000/10520] lr: 1.0000e-06 eta: 2:38:09 time: 0.8783 data_time: 0.0281 memory: 56769 loss_visual: 0.0476 loss: 0.0476 2022/09/18 15:01:27 - mmengine - INFO - Epoch(train) [20][3100/10520] lr: 1.0000e-06 eta: 2:36:03 time: 0.8988 data_time: 0.0256 memory: 56769 loss_visual: 0.0526 loss: 0.0526 2022/09/18 15:01:59 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 15:03:35 - mmengine - INFO - Epoch(train) [20][3200/10520] lr: 1.0000e-06 eta: 2:33:57 time: 0.8913 data_time: 0.0237 memory: 56769 loss_visual: 0.0491 loss: 0.0491 2022/09/18 15:05:49 - mmengine - INFO - Epoch(train) [20][3300/10520] lr: 1.0000e-06 eta: 2:31:51 time: 1.6363 data_time: 0.4034 memory: 56769 loss_visual: 0.0465 loss: 0.0465 2022/09/18 15:07:56 - mmengine - INFO - Epoch(train) [20][3400/10520] lr: 1.0000e-06 eta: 2:29:45 time: 1.7102 data_time: 0.5400 memory: 56769 loss_visual: 0.0502 loss: 0.0502 2022/09/18 15:10:04 - mmengine - INFO - Epoch(train) [20][3500/10520] lr: 1.0000e-06 eta: 2:27:39 time: 1.1807 data_time: 0.3138 memory: 56769 loss_visual: 0.0465 loss: 0.0465 2022/09/18 15:12:13 - mmengine - INFO - Epoch(train) [20][3600/10520] lr: 1.0000e-06 eta: 2:25:33 time: 1.2732 data_time: 0.1910 memory: 56769 loss_visual: 0.0483 loss: 0.0483 2022/09/18 15:14:19 - mmengine - INFO - Epoch(train) [20][3700/10520] lr: 1.0000e-06 eta: 2:23:26 time: 1.1770 data_time: 0.0601 memory: 56769 loss_visual: 0.0513 loss: 0.0513 2022/09/18 15:16:24 - mmengine - INFO - Epoch(train) [20][3800/10520] lr: 1.0000e-06 eta: 2:21:20 time: 0.8468 data_time: 0.0227 memory: 56769 loss_visual: 0.0484 loss: 0.0484 2022/09/18 15:18:30 - mmengine - INFO - Epoch(train) [20][3900/10520] lr: 1.0000e-06 eta: 2:19:14 time: 0.8970 data_time: 0.0253 memory: 56769 loss_visual: 0.0501 loss: 0.0501 2022/09/18 15:20:38 - mmengine - INFO - Epoch(train) [20][4000/10520] lr: 1.0000e-06 eta: 2:17:08 time: 0.9352 data_time: 0.0258 memory: 56769 loss_visual: 0.0525 loss: 0.0525 2022/09/18 15:22:52 - mmengine - INFO - Epoch(train) [20][4100/10520] lr: 1.0000e-06 eta: 2:15:02 time: 1.6336 data_time: 0.4161 memory: 56769 loss_visual: 0.0458 loss: 0.0458 2022/09/18 15:23:15 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 15:24:59 - mmengine - INFO - Epoch(train) [20][4200/10520] lr: 1.0000e-06 eta: 2:12:56 time: 1.7132 data_time: 0.5500 memory: 56769 loss_visual: 0.0522 loss: 0.0522 2022/09/18 15:27:07 - mmengine - INFO - Epoch(train) [20][4300/10520] lr: 1.0000e-06 eta: 2:10:50 time: 1.1586 data_time: 0.3396 memory: 56769 loss_visual: 0.0461 loss: 0.0461 2022/09/18 15:29:17 - mmengine - INFO - Epoch(train) [20][4400/10520] lr: 1.0000e-06 eta: 2:08:43 time: 1.2980 data_time: 0.1882 memory: 56769 loss_visual: 0.0462 loss: 0.0462 2022/09/18 15:31:24 - mmengine - INFO - Epoch(train) [20][4500/10520] lr: 1.0000e-06 eta: 2:06:37 time: 1.2120 data_time: 0.0532 memory: 56769 loss_visual: 0.0494 loss: 0.0494 2022/09/18 15:33:30 - mmengine - INFO - Epoch(train) [20][4600/10520] lr: 1.0000e-06 eta: 2:04:31 time: 0.8586 data_time: 0.0241 memory: 56769 loss_visual: 0.0483 loss: 0.0483 2022/09/18 15:35:36 - mmengine - INFO - Epoch(train) [20][4700/10520] lr: 1.0000e-06 eta: 2:02:25 time: 0.8971 data_time: 0.0249 memory: 56769 loss_visual: 0.0491 loss: 0.0491 2022/09/18 15:37:43 - mmengine - INFO - Epoch(train) [20][4800/10520] lr: 1.0000e-06 eta: 2:00:19 time: 0.9268 data_time: 0.0245 memory: 56769 loss_visual: 0.0461 loss: 0.0461 2022/09/18 15:39:57 - mmengine - INFO - Epoch(train) [20][4900/10520] lr: 1.0000e-06 eta: 1:58:13 time: 1.6196 data_time: 0.3799 memory: 56769 loss_visual: 0.0480 loss: 0.0480 2022/09/18 15:42:05 - mmengine - INFO - Epoch(train) [20][5000/10520] lr: 1.0000e-06 eta: 1:56:07 time: 1.7550 data_time: 0.5827 memory: 56769 loss_visual: 0.0509 loss: 0.0509 2022/09/18 15:44:13 - mmengine - INFO - Epoch(train) [20][5100/10520] lr: 1.0000e-06 eta: 1:54:00 time: 1.1313 data_time: 0.3117 memory: 56769 loss_visual: 0.0488 loss: 0.0488 2022/09/18 15:44:34 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 15:46:23 - mmengine - INFO - Epoch(train) [20][5200/10520] lr: 1.0000e-06 eta: 1:51:54 time: 1.2706 data_time: 0.1863 memory: 56769 loss_visual: 0.0474 loss: 0.0474 2022/09/18 15:48:30 - mmengine - INFO - Epoch(train) [20][5300/10520] lr: 1.0000e-06 eta: 1:49:48 time: 1.1629 data_time: 0.0569 memory: 56769 loss_visual: 0.0512 loss: 0.0512 2022/09/18 15:50:37 - mmengine - INFO - Epoch(train) [20][5400/10520] lr: 1.0000e-06 eta: 1:47:42 time: 0.8879 data_time: 0.0248 memory: 56769 loss_visual: 0.0489 loss: 0.0489 2022/09/18 15:52:46 - mmengine - INFO - Epoch(train) [20][5500/10520] lr: 1.0000e-06 eta: 1:45:36 time: 0.8582 data_time: 0.0239 memory: 56769 loss_visual: 0.0484 loss: 0.0484 2022/09/18 15:54:52 - mmengine - INFO - Epoch(train) [20][5600/10520] lr: 1.0000e-06 eta: 1:43:29 time: 0.9491 data_time: 0.0250 memory: 56769 loss_visual: 0.0462 loss: 0.0462 2022/09/18 15:57:06 - mmengine - INFO - Epoch(train) [20][5700/10520] lr: 1.0000e-06 eta: 1:41:23 time: 1.6999 data_time: 0.4015 memory: 56769 loss_visual: 0.0482 loss: 0.0482 2022/09/18 15:59:14 - mmengine - INFO - Epoch(train) [20][5800/10520] lr: 1.0000e-06 eta: 1:39:17 time: 1.7354 data_time: 0.5308 memory: 56769 loss_visual: 0.0494 loss: 0.0494 2022/09/18 16:01:24 - mmengine - INFO - Epoch(train) [20][5900/10520] lr: 1.0000e-06 eta: 1:37:11 time: 1.1489 data_time: 0.2928 memory: 56769 loss_visual: 0.0459 loss: 0.0459 2022/09/18 16:03:34 - mmengine - INFO - Epoch(train) [20][6000/10520] lr: 1.0000e-06 eta: 1:35:05 time: 1.3589 data_time: 0.1842 memory: 56769 loss_visual: 0.0488 loss: 0.0488 2022/09/18 16:05:40 - mmengine - INFO - Epoch(train) [20][6100/10520] lr: 1.0000e-06 eta: 1:32:59 time: 1.1644 data_time: 0.0635 memory: 56769 loss_visual: 0.0495 loss: 0.0495 2022/09/18 16:06:06 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 16:07:45 - mmengine - INFO - Epoch(train) [20][6200/10520] lr: 1.0000e-06 eta: 1:30:52 time: 0.8539 data_time: 0.0370 memory: 56769 loss_visual: 0.0473 loss: 0.0473 2022/09/18 16:09:51 - mmengine - INFO - Epoch(train) [20][6300/10520] lr: 1.0000e-06 eta: 1:28:46 time: 0.8804 data_time: 0.0243 memory: 56769 loss_visual: 0.0504 loss: 0.0504 2022/09/18 16:11:58 - mmengine - INFO - Epoch(train) [20][6400/10520] lr: 1.0000e-06 eta: 1:26:40 time: 0.9475 data_time: 0.0240 memory: 56769 loss_visual: 0.0502 loss: 0.0502 2022/09/18 16:14:13 - mmengine - INFO - Epoch(train) [20][6500/10520] lr: 1.0000e-06 eta: 1:24:34 time: 1.6651 data_time: 0.4467 memory: 56769 loss_visual: 0.0487 loss: 0.0487 2022/09/18 16:16:21 - mmengine - INFO - Epoch(train) [20][6600/10520] lr: 1.0000e-06 eta: 1:22:28 time: 1.7170 data_time: 0.5392 memory: 56769 loss_visual: 0.0497 loss: 0.0497 2022/09/18 16:18:28 - mmengine - INFO - Epoch(train) [20][6700/10520] lr: 1.0000e-06 eta: 1:20:22 time: 1.1155 data_time: 0.2954 memory: 56769 loss_visual: 0.0467 loss: 0.0467 2022/09/18 16:20:36 - mmengine - INFO - Epoch(train) [20][6800/10520] lr: 1.0000e-06 eta: 1:18:15 time: 1.3086 data_time: 0.1879 memory: 56769 loss_visual: 0.0493 loss: 0.0493 2022/09/18 16:22:41 - mmengine - INFO - Epoch(train) [20][6900/10520] lr: 1.0000e-06 eta: 1:16:09 time: 1.1688 data_time: 0.0578 memory: 56769 loss_visual: 0.0493 loss: 0.0493 2022/09/18 16:24:47 - mmengine - INFO - Epoch(train) [20][7000/10520] lr: 1.0000e-06 eta: 1:14:03 time: 0.8780 data_time: 0.0253 memory: 56769 loss_visual: 0.0461 loss: 0.0461 2022/09/18 16:26:53 - mmengine - INFO - Epoch(train) [20][7100/10520] lr: 1.0000e-06 eta: 1:11:57 time: 0.9037 data_time: 0.0249 memory: 56769 loss_visual: 0.0474 loss: 0.0474 2022/09/18 16:27:24 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 16:29:00 - mmengine - INFO - Epoch(train) [20][7200/10520] lr: 1.0000e-06 eta: 1:09:50 time: 0.8920 data_time: 0.0231 memory: 56769 loss_visual: 0.0461 loss: 0.0461 2022/09/18 16:31:14 - mmengine - INFO - Epoch(train) [20][7300/10520] lr: 1.0000e-06 eta: 1:07:44 time: 1.5954 data_time: 0.4006 memory: 56769 loss_visual: 0.0481 loss: 0.0481 2022/09/18 16:33:21 - mmengine - INFO - Epoch(train) [20][7400/10520] lr: 1.0000e-06 eta: 1:05:38 time: 1.7098 data_time: 0.5263 memory: 56769 loss_visual: 0.0459 loss: 0.0459 2022/09/18 16:35:28 - mmengine - INFO - Epoch(train) [20][7500/10520] lr: 1.0000e-06 eta: 1:03:32 time: 1.1220 data_time: 0.2971 memory: 56769 loss_visual: 0.0446 loss: 0.0446 2022/09/18 16:37:38 - mmengine - INFO - Epoch(train) [20][7600/10520] lr: 1.0000e-06 eta: 1:01:26 time: 1.3514 data_time: 0.2030 memory: 56769 loss_visual: 0.0487 loss: 0.0487 2022/09/18 16:39:43 - mmengine - INFO - Epoch(train) [20][7700/10520] lr: 1.0000e-06 eta: 0:59:19 time: 1.1581 data_time: 0.0550 memory: 56769 loss_visual: 0.0479 loss: 0.0479 2022/09/18 16:41:48 - mmengine - INFO - Epoch(train) [20][7800/10520] lr: 1.0000e-06 eta: 0:57:13 time: 0.8992 data_time: 0.0262 memory: 56769 loss_visual: 0.0470 loss: 0.0470 2022/09/18 16:43:55 - mmengine - INFO - Epoch(train) [20][7900/10520] lr: 1.0000e-06 eta: 0:55:07 time: 0.8693 data_time: 0.0322 memory: 56769 loss_visual: 0.0498 loss: 0.0498 2022/09/18 16:46:01 - mmengine - INFO - Epoch(train) [20][8000/10520] lr: 1.0000e-06 eta: 0:53:01 time: 0.9086 data_time: 0.0262 memory: 56769 loss_visual: 0.0498 loss: 0.0498 2022/09/18 16:48:15 - mmengine - INFO - Epoch(train) [20][8100/10520] lr: 1.0000e-06 eta: 0:50:55 time: 1.6054 data_time: 0.4299 memory: 56769 loss_visual: 0.0492 loss: 0.0492 2022/09/18 16:48:38 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 16:50:24 - mmengine - INFO - Epoch(train) [20][8200/10520] lr: 1.0000e-06 eta: 0:48:48 time: 1.7271 data_time: 0.5676 memory: 56769 loss_visual: 0.0474 loss: 0.0474 2022/09/18 16:52:30 - mmengine - INFO - Epoch(train) [20][8300/10520] lr: 1.0000e-06 eta: 0:46:42 time: 1.1371 data_time: 0.3051 memory: 56769 loss_visual: 0.0502 loss: 0.0502 2022/09/18 16:54:39 - mmengine - INFO - Epoch(train) [20][8400/10520] lr: 1.0000e-06 eta: 0:44:36 time: 1.3117 data_time: 0.1821 memory: 56769 loss_visual: 0.0475 loss: 0.0475 2022/09/18 16:56:44 - mmengine - INFO - Epoch(train) [20][8500/10520] lr: 1.0000e-06 eta: 0:42:30 time: 1.1355 data_time: 0.0558 memory: 56769 loss_visual: 0.0460 loss: 0.0460 2022/09/18 16:58:49 - mmengine - INFO - Epoch(train) [20][8600/10520] lr: 1.0000e-06 eta: 0:40:23 time: 0.8731 data_time: 0.0248 memory: 56769 loss_visual: 0.0468 loss: 0.0468 2022/09/18 17:00:56 - mmengine - INFO - Epoch(train) [20][8700/10520] lr: 1.0000e-06 eta: 0:38:17 time: 0.8591 data_time: 0.0237 memory: 56769 loss_visual: 0.0460 loss: 0.0460 2022/09/18 17:03:06 - mmengine - INFO - Epoch(train) [20][8800/10520] lr: 1.0000e-06 eta: 0:36:11 time: 0.9033 data_time: 0.0251 memory: 56769 loss_visual: 0.0497 loss: 0.0497 2022/09/18 17:05:20 - mmengine - INFO - Epoch(train) [20][8900/10520] lr: 1.0000e-06 eta: 0:34:05 time: 1.6414 data_time: 0.4471 memory: 56769 loss_visual: 0.0478 loss: 0.0478 2022/09/18 17:07:28 - mmengine - INFO - Epoch(train) [20][9000/10520] lr: 1.0000e-06 eta: 0:31:58 time: 1.7104 data_time: 0.6020 memory: 56769 loss_visual: 0.0499 loss: 0.0499 2022/09/18 17:09:37 - mmengine - INFO - Epoch(train) [20][9100/10520] lr: 1.0000e-06 eta: 0:29:52 time: 1.1260 data_time: 0.3132 memory: 56769 loss_visual: 0.0514 loss: 0.0514 2022/09/18 17:09:57 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 17:11:45 - mmengine - INFO - Epoch(train) [20][9200/10520] lr: 1.0000e-06 eta: 0:27:46 time: 1.2908 data_time: 0.1925 memory: 56769 loss_visual: 0.0494 loss: 0.0494 2022/09/18 17:13:50 - mmengine - INFO - Epoch(train) [20][9300/10520] lr: 1.0000e-06 eta: 0:25:40 time: 1.2010 data_time: 0.0703 memory: 56769 loss_visual: 0.0499 loss: 0.0499 2022/09/18 17:15:59 - mmengine - INFO - Epoch(train) [20][9400/10520] lr: 1.0000e-06 eta: 0:23:34 time: 0.8427 data_time: 0.0243 memory: 56769 loss_visual: 0.0461 loss: 0.0461 2022/09/18 17:18:04 - mmengine - INFO - Epoch(train) [20][9500/10520] lr: 1.0000e-06 eta: 0:21:27 time: 0.8858 data_time: 0.0265 memory: 56769 loss_visual: 0.0494 loss: 0.0494 2022/09/18 17:20:10 - mmengine - INFO - Epoch(train) [20][9600/10520] lr: 1.0000e-06 eta: 0:19:21 time: 0.9050 data_time: 0.0331 memory: 56769 loss_visual: 0.0500 loss: 0.0500 2022/09/18 17:22:22 - mmengine - INFO - Epoch(train) [20][9700/10520] lr: 1.0000e-06 eta: 0:17:15 time: 1.6119 data_time: 0.4582 memory: 56769 loss_visual: 0.0516 loss: 0.0516 2022/09/18 17:24:30 - mmengine - INFO - Epoch(train) [20][9800/10520] lr: 1.0000e-06 eta: 0:15:09 time: 1.7503 data_time: 0.5881 memory: 56769 loss_visual: 0.0461 loss: 0.0461 2022/09/18 17:26:38 - mmengine - INFO - Epoch(train) [20][9900/10520] lr: 1.0000e-06 eta: 0:13:02 time: 1.1921 data_time: 0.3702 memory: 56769 loss_visual: 0.0477 loss: 0.0477 2022/09/18 17:28:46 - mmengine - INFO - Epoch(train) [20][10000/10520] lr: 1.0000e-06 eta: 0:10:56 time: 1.2721 data_time: 0.2026 memory: 56769 loss_visual: 0.0489 loss: 0.0489 2022/09/18 17:30:51 - mmengine - INFO - Epoch(train) [20][10100/10520] lr: 1.0000e-06 eta: 0:08:50 time: 1.1596 data_time: 0.0552 memory: 56769 loss_visual: 0.0438 loss: 0.0438 2022/09/18 17:31:17 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 17:32:56 - mmengine - INFO - Epoch(train) [20][10200/10520] lr: 1.0000e-06 eta: 0:06:44 time: 0.8803 data_time: 0.0236 memory: 56769 loss_visual: 0.0499 loss: 0.0499 2022/09/18 17:35:02 - mmengine - INFO - Epoch(train) [20][10300/10520] lr: 1.0000e-06 eta: 0:04:37 time: 0.8962 data_time: 0.0256 memory: 56769 loss_visual: 0.0509 loss: 0.0509 2022/09/18 17:37:08 - mmengine - INFO - Epoch(train) [20][10400/10520] lr: 1.0000e-06 eta: 0:02:31 time: 0.8973 data_time: 0.0247 memory: 56769 loss_visual: 0.0476 loss: 0.0476 2022/09/18 17:39:16 - mmengine - INFO - Epoch(train) [20][10500/10520] lr: 1.0000e-06 eta: 0:00:25 time: 1.2938 data_time: 0.2311 memory: 56769 loss_visual: 0.0477 loss: 0.0477 2022/09/18 17:39:34 - mmengine - INFO - Exp name: abinet-vision_20e_st-an_mj_20220915_152445 2022/09/18 17:39:34 - mmengine - INFO - Saving checkpoint at 20 epochs 2022/09/18 17:39:49 - mmengine - INFO - Epoch(val) [20][100/3836] eta: 0:04:12 time: 0.0676 data_time: 0.0006 memory: 56769 2022/09/18 17:39:53 - mmengine - INFO - Epoch(val) [20][200/3836] eta: 0:00:43 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/18 17:39:54 - mmengine - INFO - Epoch(val) [20][300/3836] eta: 0:00:41 time: 0.0117 data_time: 0.0006 memory: 480 2022/09/18 17:39:56 - mmengine - INFO - Epoch(val) [20][400/3836] eta: 0:00:39 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/18 17:39:57 - mmengine - INFO - Epoch(val) [20][500/3836] eta: 0:00:41 time: 0.0123 data_time: 0.0005 memory: 480 2022/09/18 17:39:58 - mmengine - INFO - Epoch(val) [20][600/3836] eta: 0:00:37 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 17:39:59 - mmengine - INFO - Epoch(val) [20][700/3836] eta: 0:00:37 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/18 17:40:01 - mmengine - INFO - Epoch(val) [20][800/3836] eta: 0:00:38 time: 0.0128 data_time: 0.0005 memory: 480 2022/09/18 17:40:02 - mmengine - INFO - Epoch(val) [20][900/3836] eta: 0:00:35 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/18 17:40:03 - mmengine - INFO - Epoch(val) [20][1000/3836] eta: 0:00:35 time: 0.0125 data_time: 0.0006 memory: 480 2022/09/18 17:40:04 - mmengine - INFO - Epoch(val) [20][1100/3836] eta: 0:00:31 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 17:40:05 - mmengine - INFO - Epoch(val) [20][1200/3836] eta: 0:00:30 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 17:40:07 - mmengine - INFO - Epoch(val) [20][1300/3836] eta: 0:00:28 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/18 17:40:08 - mmengine - INFO - Epoch(val) [20][1400/3836] eta: 0:00:29 time: 0.0120 data_time: 0.0005 memory: 480 2022/09/18 17:40:09 - mmengine - INFO - Epoch(val) [20][1500/3836] eta: 0:00:27 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 17:40:10 - mmengine - INFO - Epoch(val) [20][1600/3836] eta: 0:00:31 time: 0.0140 data_time: 0.0006 memory: 480 2022/09/18 17:40:11 - mmengine - INFO - Epoch(val) [20][1700/3836] eta: 0:00:24 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 17:40:13 - mmengine - INFO - Epoch(val) [20][1800/3836] eta: 0:00:23 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 17:40:14 - mmengine - INFO - Epoch(val) [20][1900/3836] eta: 0:00:23 time: 0.0121 data_time: 0.0005 memory: 480 2022/09/18 17:40:15 - mmengine - INFO - Epoch(val) [20][2000/3836] eta: 0:00:21 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 17:40:17 - mmengine - INFO - Epoch(val) [20][2100/3836] eta: 0:00:20 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/18 17:40:18 - mmengine - INFO - Epoch(val) [20][2200/3836] eta: 0:00:19 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 17:40:19 - mmengine - INFO - Epoch(val) [20][2300/3836] eta: 0:00:17 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/18 17:40:20 - mmengine - INFO - Epoch(val) [20][2400/3836] eta: 0:00:16 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 17:40:21 - mmengine - INFO - Epoch(val) [20][2500/3836] eta: 0:00:15 time: 0.0113 data_time: 0.0005 memory: 480 2022/09/18 17:40:22 - mmengine - INFO - Epoch(val) [20][2600/3836] eta: 0:00:14 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 17:40:24 - mmengine - INFO - Epoch(val) [20][2700/3836] eta: 0:00:13 time: 0.0116 data_time: 0.0005 memory: 480 2022/09/18 17:40:25 - mmengine - INFO - Epoch(val) [20][2800/3836] eta: 0:00:11 time: 0.0113 data_time: 0.0004 memory: 480 2022/09/18 17:40:26 - mmengine - INFO - Epoch(val) [20][2900/3836] eta: 0:00:10 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 17:40:27 - mmengine - INFO - Epoch(val) [20][3000/3836] eta: 0:00:09 time: 0.0117 data_time: 0.0005 memory: 480 2022/09/18 17:40:28 - mmengine - INFO - Epoch(val) [20][3100/3836] eta: 0:00:08 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 17:40:29 - mmengine - INFO - Epoch(val) [20][3200/3836] eta: 0:00:07 time: 0.0111 data_time: 0.0005 memory: 480 2022/09/18 17:40:31 - mmengine - INFO - Epoch(val) [20][3300/3836] eta: 0:00:06 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 17:40:32 - mmengine - INFO - Epoch(val) [20][3400/3836] eta: 0:00:04 time: 0.0114 data_time: 0.0005 memory: 480 2022/09/18 17:40:33 - mmengine - INFO - Epoch(val) [20][3500/3836] eta: 0:00:03 time: 0.0119 data_time: 0.0005 memory: 480 2022/09/18 17:40:34 - mmengine - INFO - Epoch(val) [20][3600/3836] eta: 0:00:02 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 17:40:35 - mmengine - INFO - Epoch(val) [20][3700/3836] eta: 0:00:01 time: 0.0115 data_time: 0.0005 memory: 480 2022/09/18 17:40:37 - mmengine - INFO - Epoch(val) [20][3800/3836] eta: 0:00:00 time: 0.0108 data_time: 0.0005 memory: 480 2022/09/18 17:40:37 - mmengine - INFO - Epoch(val) [20][3836/3836] CUTE80/recog/word_acc_ignore_case_symbol: 0.8472 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9540 SVT/recog/word_acc_ignore_case_symbol: 0.9026 SVTP/recog/word_acc_ignore_case_symbol: 0.8372 IC13/recog/word_acc_ignore_case_symbol: 0.9360 IC15/recog/word_acc_ignore_case_symbol: 0.7896